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Simplest possible persistent-3D sim. A hot source voxel continuously injects energy, it spreads outward. Useful as a reference test for the persistent plumbing and as a building block (feed the output into a warp filter etc).\",\n  \"CREDIT\": \"ossia 3D catalog\",\n  \"ISFVSN\": \"2.0\",\n  \"MODE\": \"COMPUTE_SHADER\",\n  \"CATEGORIES\": [\n    \"3D-GENERATOR\",\n    \"SIMULATION\"\n  ],\n  \"INPUTS\": [\n    {\n      \"NAME\": \"alpha\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.15,\n      \"MIN\": 0.01,\n      \"MAX\": 0.15,\n      \"LABEL\": \"Diffusion\"\n    },\n    {\n      \"NAME\": \"sourcePos\",\n      \"TYPE\": \"point3D\",\n      \"DEFAULT\": [\n        0.0,\n        0.0,\n        0.0\n      ],\n      \"MIN\": [\n        -1,\n        -1,\n        -1\n      ],\n      \"MAX\": [\n        1,\n        1,\n        1\n      ],\n      \"LABEL\": \"Source\"\n    },\n    {\n      \"NAME\": \"sourceSize\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.1,\n      \"MIN\": 0.01,\n      \"MAX\": 0.4,\n      \"LABEL\": \"Source size\"\n    },\n    {\n      \"NAME\": \"sourceTemp\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 1.0,\n      \"MIN\": 0.0,\n      \"MAX\": 4.0,\n      \"LABEL\": \"Source temp\"\n    },\n    {\n      \"NAME\": \"ambient\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.0,\n      \"MIN\": 0.0,\n      \"MAX\": 1.0,\n      \"LABEL\": \"Ambient temp\"\n    },\n    {\n      \"NAME\": \"coolRate\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.995,\n      \"MIN\": 0.9,\n      \"MAX\": 1.0,\n      \"LABEL\": \"Cooling\"\n    },\n    {\n      \"NAME\": \"clear\",\n      \"TYPE\": \"event\",\n      \"LABEL\": \"Clear\"\n    }\n  ],\n  \"RESOURCES\": [\n    {\n      \"NAME\": \"state\",\n      \"TYPE\": \"image\",\n      \"ACCESS\": \"read_write\",\n      \"FORMAT\": \"rgba16f\",\n      \"WIDTH\": \"64\",\n      \"HEIGHT\": \"64\",\n      \"DEPTH\": \"64\",\n      \"PERSISTENT\": true\n    }\n  ],\n  \"PASSES\": [\n    {\n      \"LOCAL_SIZE\": [\n        4,\n        4,\n        4\n      ],\n      \"EXECUTION_MODEL\": {\n        \"TYPE\": \"3D_IMAGE\",\n        \"TARGET\": \"state\"\n      }\n    }\n  ]\n}*/\n\n// Clamp-to-edge 3D voxel load\nvec4 loadC(in ivec3 c, in ivec3 sz) {\n    return imageLoad(state_prev, clamp(c, ivec3(0), sz - 1));\n}\n// 6-neighbour Laplacian of the given channel index (0=r,1=g,2=b,3=a)\nfloat lap6(in ivec3 p, in ivec3 sz, int ch) {\n    float c = imageLoad(state_prev, p)[ch];\n    float s = loadC(p + ivec3( 1,0,0), sz)[ch]\n            + loadC(p + ivec3(-1,0,0), sz)[ch]\n            + loadC(p + ivec3(0, 1,0), sz)[ch]\n            + loadC(p + ivec3(0,-1,0), sz)[ch]\n            + loadC(p + ivec3(0,0, 1), sz)[ch]\n            + loadC(p + ivec3(0,0,-1), sz)[ch];\n    return s - 6.0 * c;\n}\n// 3D gradient via central differences on channel `ch`\nvec3 grad3(in ivec3 p, in ivec3 sz, int ch) {\n    return 0.5 * vec3(\n        loadC(p + ivec3( 1,0,0), sz)[ch] - loadC(p + ivec3(-1,0,0), sz)[ch],\n        loadC(p + ivec3(0, 1,0), sz)[ch] - loadC(p + ivec3(0,-1,0), sz)[ch],\n        loadC(p + ivec3(0,0, 1), sz)[ch] - loadC(p + ivec3(0,0,-1), sz)[ch]);\n}\n\nvoid main()\n{\n    ivec3 pos  = ivec3(gl_GlobalInvocationID.xyz);\n    ivec3 size = imageSize(state);\n    if(any(greaterThanEqual(pos, size))) return;\n    vec3  p    = (vec3(pos) + 0.5) / vec3(size);\n    vec3  pc   = p * 2.0 - 1.0;\n    vec4  prev = imageLoad(state_prev, pos);\n\n    // Seed on the first dispatch. score currently starts FRAMEINDEX at 1, not\n    // at 0 as the ISF spec says (see showcase/volume/_engine); <= 1 works either way.\n    if(FRAMEINDEX <= 1 || clear){\n        imageStore(state, pos, vec4(ambient, ambient, ambient, 1.0));\n        return;\n    }\n    float u = prev.r;\n    float lu = lap6(pos, size, 0);\n    // Explicit (FTCS) diffusion on the 6-neighbour stencil is only stable for\n    // D * dt <= 1/6 per step (von Neumann analysis); above it the highest\n    // spatial frequency grows every step and the volume turns into a\n    // checkerboard. The step is capped just below that bound.\n    const float kMaxDiffStep = 0.15;\n    float uNew = u + min(alpha, kMaxDiffStep) * lu;\n    // Cool toward ambient\n    uNew = mix(ambient, uNew, coolRate);\n    // Source\n    float r = length(pc - sourcePos);\n    float w = smoothstep(sourceSize, 0.0, r);\n    uNew = mix(uNew, sourceTemp, w);\n    vec4 next = vec4(uNew, uNew, uNew, 1.0);\n\n    imageStore(state, pos, next);\n}\n","Root":"<LIBRARY>:packages/score-csf-testers/shaderlib/volume/04-simulations/04-10_heat_diffusion.cs","Inlets":[{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":0,"Hidden":true,"Custom":"alpha","Exposed":"alpha","Value":{"Float":0.15000000596046448},"Init":{"Float":0.15000000596046448},"Domain":{"Float":{"Min":0.009999999776482582,"Max":0.15000000596046448}}},{"uuid":"377e8205-b442-4d54-8832-3761def522b2","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"sourcePos","Exposed":"sourcepos","Value":{"Vec3f":[0.0,-0.07797885686159134,0.0]},"Init":{"Vec3f":[0.0,0.0,0.0]},"Domain":{"Vec3f":{"Min":[-1.0,-1.0,-1.0],"Max":[1.0,1.0,1.0],"Values":[[],[],[]]}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":2,"Hidden":true,"Custom":"sourceSize","Exposed":"sourcesize","Value":{"Float":0.2180507928133011},"Init":{"Float":0.10000000149011612},"Domain":{"Float":{"Min":0.009999999776482582,"Max":0.4000000059604645}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":3,"Hidden":true,"Custom":"sourceTemp","Exposed":"sourcetemp","Value":{"Float":2.1338541507720947},"Init":{"Float":1.0},"Domain":{"Float":{"Min":0.0,"Max":4.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":4,"Hidden":true,"Custom":"ambient","Exposed":"ambient","Value":{"Float":0.0},"Init":{"Float":0.0},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":5,"Hidden":true,"Custom":"coolRate","Exposed":"coolrate","Value":{"Float":0.9883463382720947},"Init":{"Float":0.9950000047683716},"Domain":{"Float":{"Min":0.8999999761581421,"Max":1.0}}},{"uuid":"feb87e84-e0d2-428f-96ff-a123ac964f59","ObjectName":"Inlet","id":6,"Hidden":true,"Custom":"clear","Exposed":"clear","Value":{"Bool":false},"Init":{"Bool":false},"Domain":{"Bool":null}}],"Outlets":[{"uuid":"f1c71046-b754-49a5-8e66-d01374773dfc","ObjectName":"Outlet","id":0,"Hidden":false,"Custom":"state","Exposed":"state"}]},{"uuid":"d757bd0d-c0a1-4aec-bf72-945b722ab85b","ObjectName":"MathGenerator","id":26,"Metadata":{"ScriptingName":"Random XYZ","Comment":"","Color":"Transparent1","Label":"","Touched":true},"Duration":10584000000,"Height":300.0,"StartOffset":0,"LoopDuration":10584000000,"Pos":[-656.3541883299049,-86.67475829904835],"Size":[216.0,175.0],"Loops":false,"FoldMode":2,"Inlets":[{"uuid":"9ae797ea-d94c-4792-acec-9ec1932bae5d","ObjectName":"Inlet","id":0,"Hidden":true,"Custom":"Expression (ExprTK)","Exposed":"expression (exprtk)","Value":{"String":"return [\n( noise(10 pos * a, 0.5, 0.1) - 0.5),\n( noise(100000 + 10 pos * b, 0.8, 0.1) - 0.5), \n( noise(10 pos * c, 4.1, 10.1) - 0.5)\n]"},"Init":{"String":"cos(t) + log(pos * (1+a) / (1+abs(dt)))"},"Domain":{}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"Param (a)","Exposed":"param (a)","Value":{"Float":1.0},"Init":{"Float":0.5},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":2,"Hidden":true,"Custom":"Param (b)","Exposed":"param (b)","Value":{"Float":0.8768140077590942},"Init":{"Float":0.5},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":3,"Hidden":true,"Custom":"Param (c)","Exposed":"param (c)","Value":{"Float":0.643480658531189},"Init":{"Float":0.5},"Domain":{"Float":{"Min":0.0,"Max":1.0}}}],"Outlets":[{"uuid":"cff96158-cc72-46d7-99dc-b6038171375b","ObjectName":"Outlet","id":0,"Hidden":false,"Custom":"out","Exposed":"out"}]},{"uuid":"a5bbffe0-93d2-4e70-995c-cf46c2c43520","ObjectName":"CSF","id":31,"Metadata":{"ScriptingName":"08-01_domain_warp_noise","Comment":"","Color":"Transparent1","Label":"","Touched":true},"Duration":10584000000,"Height":300.0,"StartOffset":0,"LoopDuration":10584000000,"Pos":[-42.73500000000013,-120.42349999999999],"Size":[228.0,125.0],"Loops":false,"FoldMode":2,"Compute":"/*{\n  \"DESCRIPTION\": \"Domain warp by a noise offset: sample input at p + noise(p). Melts / swirls the volume. The output is rgba16f, so signed and HDR inputs (01-15 curl noise, the simulations, 07-06 Laplacian...) pass through without clipping.\",\n  \"CREDIT\": \"ossia 3D catalog\",\n  \"ISFVSN\": \"2.0\",\n  \"MODE\": \"COMPUTE_SHADER\",\n  \"CATEGORIES\": [\n    \"3D-FILTER\",\n    \"WARP\"\n  ],\n  \"INPUTS\": [\n    {\n      \"NAME\": \"volIn\",\n      \"TYPE\": \"texture\",\n      \"DIMENSIONS\": 3,\n      \"LABEL\": \"Input volume\"\n    },\n    {\n      \"NAME\": \"amount\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.15,\n      \"MIN\": 0.0,\n      \"MAX\": 1.0,\n      \"LABEL\": \"Warp amount\"\n    },\n    {\n      \"NAME\": \"scale\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 3.0,\n      \"MIN\": 0.5,\n      \"MAX\": 16.0,\n      \"LABEL\": \"Noise scale\"\n    },\n    {\n      \"NAME\": \"drift\",\n      \"TYPE\": \"float\",\n      \"DEFAULT\": 0.2,\n      \"MIN\": 0.0,\n      \"MAX\": 2.0,\n      \"LABEL\": \"Drift\"\n    }\n  ],\n  \"RESOURCES\": [\n    {\n      \"NAME\": \"volOut\",\n      \"TYPE\": \"image\",\n      \"ACCESS\": \"write_only\",\n      \"FORMAT\": \"rgba16f\",\n      \"WIDTH\": \"$WIDTH_volIn\",\n      \"HEIGHT\": \"$HEIGHT_volIn\",\n      \"DEPTH\": \"$DEPTH_volIn\"\n    }\n  ],\n  \"PASSES\": [\n    {\n      \"LOCAL_SIZE\": [\n        4,\n        4,\n        4\n      ],\n      \"EXECUTION_MODEL\": {\n        \"TYPE\": \"3D_IMAGE\",\n        \"TARGET\": \"volOut\"\n      }\n    }\n  ]\n}*/\n\n// Simplex 3D noise (Ashima Arts, ISC-licensed, widely used)\nvec4 mod289(vec4 x){return x-floor(x*(1.0/289.0))*289.0;}\nvec3 mod289(vec3 x){return x-floor(x*(1.0/289.0))*289.0;}\nvec4 permute(vec4 x){return mod289(((x*34.0)+1.0)*x);}\nvec4 taylorInvSqrt(vec4 r){return 1.79284291400159-0.85373472095314*r;}\nfloat snoise(vec3 v){\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    vec3 i  = floor(v + dot(v, C.yyy));\n    vec3 x0 = v - i + dot(i, C.xxx);\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    vec3 x1 = x0 - i1 + C.xxx;\n    vec3 x2 = x0 - i2 + C.yyy;\n    vec3 x3 = x0 - D.yyy;\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    float n_ = 0.142857142857;\n    vec3 ns = n_ * D.wyz - D.xzx;\n    vec4 j = p - 49.0 * floor(p * ns.z * ns.z);\n    vec4 x_ = floor(j * ns.z);\n    vec4 y_ = floor(j - 7.0 * x_);\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    vec4 b0 = vec4(x.xy, y.xy);\n    vec4 b1 = vec4(x.zw, y.zw);\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    vec4 a0 = b0.xzyw + s0.xzyw*sh.xxyy;\n    vec4 a1 = b1.xzyw + s1.xzyw*sh.zzww;\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    vec4 norm = taylorInvSqrt(vec4(dot(p0,p0),dot(p1,p1),dot(p2,p2),dot(p3,p3)));\n    p0 *= norm.x; p1 *= norm.y; p2 *= norm.z; p3 *= norm.w;\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),dot(p2,x2),dot(p3,x3)));\n}\n\nvoid main()\n{\n    ivec3 pos = ivec3(gl_GlobalInvocationID.xyz);\n    ivec3 size = imageSize(volOut);\n    if(any(greaterThanEqual(pos, size))) return;\n    vec3 p  = (vec3(pos) + 0.5) / vec3(size);\n    vec3 pc = p * 2.0 - 1.0;\n\n    vec3 q = pc * scale + vec3(TIME*drift);\n    vec3 off = vec3(snoise(q), snoise(q+5.2), snoise(q+9.1)) * amount;\n    vec3 uvw = p + off;\n    vec4 s = texture(volIn, uvw);\n    imageStore(volOut, pos, s);\n\n}\n","Root":"<LIBRARY>:packages/score-csf-testers/shaderlib/volume/08-warp/08-01_domain_warp_noise.cs","Inlets":[{"uuid":"5ac86198-2d03-4830-9e41-a6d529922d29","ObjectName":"Inlet","id":0,"Hidden":false,"Custom":"volIn","Exposed":"volin","Format":0,"FormatSet":false,"Filter":2,"AddressMode":1,"MipmapMode":0},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"amount","Exposed":"amount","Value":{"Float":0.266997754573822},"Init":{"Float":0.15000000596046448},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":2,"Hidden":true,"Custom":"scale","Exposed":"scale","Value":{"Float":3.0},"Init":{"Float":3.0},"Domain":{"Float":{"Min":0.5,"Max":16.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":3,"Hidden":true,"Custom":"drift","Exposed":"drift","Value":{"Float":0.20000000298023224},"Init":{"Float":0.20000000298023224},"Domain":{"Float":{"Min":0.0,"Max":2.0}}}],"Outlets":[{"uuid":"f1c71046-b754-49a5-8e66-d01374773dfc","ObjectName":"Outlet","id":0,"Hidden":false,"Custom":"volOut","Exposed":"volout"}]},{"uuid":"d757bd0d-c0a1-4aec-bf72-945b722ab85b","ObjectName":"MathGenerator","id":32,"Metadata":{"ScriptingName":"Orbit","Comment":"","Color":"Transparent1","Label":"","Touched":true},"Duration":10584000000,"Height":300.0,"StartOffset":0,"LoopDuration":10584000000,"Pos":[564.7032058572279,-58.713722613140135],"Size":[216.0,190.0],"Loops":false,"FoldMode":0,"Inlets":[{"uuid":"9ae797ea-d94c-4792-acec-9ec1932bae5d","ObjectName":"Inlet","id":0,"Hidden":true,"Custom":"Expression (ExprTK)","Exposed":"expression (exprtk)","Value":{"String":"  var speed := 0.5 a;\n  m1 := m1 + 2 pi speed dt / 705600000;\n  m1 := m1 - 2 pi floor(m1 / (2 pi));\n  var r := 0.5 + 19.5 b;\n  var el := 0.45 pi (2 c - 1);\n  return [r cos(el) cos(m1), r sin(el), r cos(el) sin(m1)]"},"Init":{"String":"cos(t) + log(pos * (1+a) / (1+abs(dt)))"},"Domain":{}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"Param (a)","Exposed":"param (a)","Value":{"Float":0.23333333432674408},"Init":{"Float":0.5},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":2,"Hidden":true,"Custom":"Param (b)","Exposed":"param (b)","Value":{"Float":0.03333333507180214},"Init":{"Float":0.5},"Domain":{"Float":{"Min":0.0,"Max":1.0}}},{"uuid":"af2b4fc3-aecb-4c15-a5aa-1c573a239925","ObjectName":"Inlet","id":3,"Hidden":true,"Custom":"Param (c)","Exposed":"param 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}\nli.unchecked::marker { content: \"\\2610\"; }\nli.checked::marker { content: \"\\2612\"; }\n</style></head><body style=\" font-family:'Ubuntu'; font-size:13px; font-weight:400; font-style:normal;\">\n<p style=\" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\">This example shows: <br />1) How to process a 3D volumetric texture. <br />heat diffusion generates a diffusion volumetric texture,<br />with a single circular source navigating in it.</p></body></html>"},"Init":{"String":"(Double-click to edit)"},"Domain":{}},{"uuid":"fb27e4cb-ea7f-41e2-ad92-2354498c1b6b","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"Auto-reflow","Exposed":"auto-reflow","Value":{"Bool":false},"Init":{"Bool":false},"Domain":{"Bool":null}}],"Outlets":[]},{"uuid":"7be51631-fb4b-4152-9ca7-86fdafa8a989","ObjectName":"Display","id":34,"Metadata":{"ScriptingName":"Text Box.1","Comment":"","Color":"Transparent1","Label":"","Touched":true},"Duration":10584000000,"Height":300.0,"StartOffset":0,"LoopDuration":10584000000,"Pos":[-41.97988033278018,-202.13292526551126],"Size":[348.0,53.0],"Loops":false,"FoldMode":0,"Inlets":[{"uuid":"9ae797ea-d94c-4792-acec-9ec1932bae5d","ObjectName":"Inlet","id":0,"Hidden":true,"Custom":"in","Exposed":"in","Value":{"String":"<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n<html><head><meta name=\"qrichtext\" content=\"1\" /><meta charset=\"utf-8\" /><style type=\"text/css\">\np, li { white-space: pre-wrap; }\nhr { height: 1px; border-width: 0; }\nli.unchecked::marker { content: \"\\2610\"; }\nli.checked::marker { content: \"\\2612\"; }\n</style></head><body style=\" font-family:'Ubuntu'; font-size:13px; font-weight:400; font-style:normal;\">\n<p style=\" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\">Then, this shader behaves exactly like a standard ISF filter<br />except it operates on 3D textures instead of 2D.<br />Change the amount to see the effect.</p></body></html>"},"Init":{"String":"(Double-click to edit)"},"Domain":{}},{"uuid":"fb27e4cb-ea7f-41e2-ad92-2354498c1b6b","ObjectName":"Inlet","id":1,"Hidden":true,"Custom":"Auto-reflow","Exposed":"auto-reflow","Value":{"Bool":false},"Init":{"Bool":false},"Domain":{"Bool":null}}],"Outlets":[]},{"uuid":"7be51631-fb4b-4152-9ca7-86fdafa8a989","ObjectName":"Display","id":35,"Metadata":{"ScriptingName":"Text Box.36","Comment":"","Color":"Transparent1","Label":"","Touched":true},"Duration":10584000000,"Height":300.0,"StartOffset":0,"LoopDuration":10584000000,"Pos":[360.7552418239098,-225.03129025141982],"Size":[330.0,68.0],"Loops":false,"FoldMode":0,"Inlets":[{"uuid":"9ae797ea-d94c-4792-acec-9ec1932bae5d","ObjectName":"Inlet","id":0,"Hidden":true,"Custom":"in","Exposed":"in","Value":{"String":"<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n<html><head><meta name=\"qrichtext\" content=\"1\" /><meta charset=\"utf-8\" /><style type=\"text/css\">\np, li { white-space: pre-wrap; }\nhr { height: 1px; border-width: 0; }\nli.unchecked::marker { content: \"\\2610\"; }\nli.checked::marker { content: \"\\2612\"; }\n</style></head><body style=\" font-family:'Ubuntu'; font-size:13px; font-weight:400; font-style:normal;\">\n<p style=\" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\">VolumeToVoxels is an example compute shader, that <br />takes as input a volumetric texture and voxelizes it <br />(e.g. turns it into an actual point cloud, at configurable <br />resolution).</p></body></html>"},"Init":{"String":"(Double-click to 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qjPiOWzu6HH37Ah3w+j0QfF/4XrlFRFLhmy1B9sVgId+zdu3c8efjixQs6YV3Xn8oI59qDmYtBu3aN5XI5SqY52GKxEMQzuT0Alor9y0eB11MURdf1G+kNEX2FO2i6RlVVNzc3UTcItL1QKIzHYxDv7PYJHh7922g0SN/ZNE1N09AZdrFYRCKRjw7iO5g7ltyHuRi0azczj8dzeXlpx+ddPmT+iARectzyVfh8PkDPXq+XAlsH18O/ms/nh4eHhmEAbdd1vdFocIdeqVSov4GmabzXgXAI8v44Q9wrhzL6x2A3Tb26djtzIQ7XrB6L/4sBnQNnZ3noe72z3BdY+gX5BORBgkQ5CKngrieXy9FOSB6PthXCZODatK2qqvv7+yQfmkwmufJfLpfjknjPplzQbpLkOu5b2zN5Mly7Q1NV1SHg5TpwDlHefYfM3BfIfsHj8dyI92YYBjlT8iaXl5e0E2jU8X0KqnXcB8klfxcXF9RJC/9y6eeNjQ2+Oflrz3tbeQQmn8aNBhU3sXlrcx20azfwrdls1gHG5a/xR9H0EQJ/u8BN0zSZVEfBsqU3OTw8xAdFUbAmLQHUw7eSFUcX740v4bfx8PCQf0v3fzabPTw0ZHnT5F/T9bkPY66Ddu0GVqvVHDzv8i1l78nm8zn3vHZOZDKZwD9yGISiY7lxVywWo3nDYrGQY3NesFOpVIR/+Zr073w+X2bi//B+UD4rS5bh8ifm4hsfYq6Ddu0a83q9S75jXGZTfM4eCma9kVqTJQxCjbvowrvdLiUYqTksrkjTNI4mX9vGm4NCi8UimUzSv0s2Rbxvk2P2yWQij8pbW1tL7tCNtT/EXAft2jXGSWaCxePxJW/fvU7V4SuFMYCCPiy/hZugTfi2RH1bLBY+n282m9GQ4Pf7hWFAZrkIaVVOTOz1enaZz4cMQv1+v91oyk+DIzyu3Z+5Dtq12/tW3mdPfLAekJmAMxTOE/JDfLnM6/B4PPJ5ciBbdutcIDQWi5mmiXaCqqomEgkBCjg8PIRTi8ViGMxAF6FzWzLz+ZBBqNzwxev1oh7ydqfBGTKu3dTcG+eahTmEbEu+bB+F+MzPTWaYyIAGZeE4D5rOnHdUkVGIxWLBBer8fv/l5SUHWCqVCk0+DMNAWflisZjP54I0K3frD0nbWDIwN01TriAVgB1uwiXgkm97jp+6uQ7aNQu7Xaz0OAOlYDBInsjOJZmmKZftUUcVEJkFpy/AF7IP4ujzZDIReHjci/G7/ZDsF8tfecniI0E7G5bJZLxer9uU6w7tMb5Rrj1aUxTFIRr66IESlVnzoWI4HFI5NVwSGqkI28oACF8HYDHfLflf9L7i/r1SqfBtPR7P7L3REsMw0HiFTnvlERiuTpaQffHihSD5ZGf1el1O0nLtEdduaq6Ddu3OIuuPRagSKrAtgQJLorElACLrqUajUXgZ3iuL700QIdnf3+fiSvDFOMlEIvGohJ51XZdvnQCRv379WoY4vvrqK8sUsfwMPGZFkcdvj6JOyTXXPsRkpzCfz2Ox2LUtAS0N3Axnnhn51nA4nEwmebLU5/PxUkzBd1MBIck98+rwlQc3IeBNJpP5fN40TQElT6fTHo+Hu1qhGBK2trY2nU5vpEjlGjdXLMm1u7RHUoNgGYoS3UJwfNees12NODYsFot8Yb/fv7i4wOdUKoUSc/JQMp4rZB15LO9AZ7Q7mZuavJWqqpgNoNFtq9U6PDwUBpVwOJxIJISkay6Xk/d/dHQ0Go1CodDtePSuyeZCHK7d3h7DJP1ak0kF9Fl9b8L6dt5ksVjkcrmzszO7NeWIkuPUOA347iW7tziYcBW32CoYDIZCIUoqoNEtQI9wOMx3Lqta27FNyuWyjGmYpmmnAevateY6aNeeuYXDYUsXBt8k49GEZui6LmzIy0x8Pp+gvzEYDDgSwlWl/H4///cWXWmWaaK4zMqUDh0OhzhhfhWVSgV93Gk/8/l8MBjwFrcwPlCRNRqNJWWqFouFmzxcxlwH7dq9G6XIHsx4muvq6oqEL7jDvTb8h/q+3beCItLJyYmwwnQ6RY2Gpmnj8Rj1LDDhbvB/7c6KL5cJJ8JAIuzE5/MpikJhu+BAsa2iKNvb2wcHB1x1D/v58ssvj4+PhU0ikYiMcozHY5ljZyc8u2TyUPm0Y23XQbt2b8+WqhK57V7BEPkdHg6HgnLTYrHQNI0crrzJjWCHWCwmzPp5UEx1d6jR4LlKzvaTFaidL5DWl0NUZyFmCFXzM/T5fJqmra6u8gD84OAAnVyAVMBUVd3b21ssFhhpsHA+nxcKBVkNHAlSYeGNdF+fKIx2f+Y6aNfuyyyzXvcREOEoMiLs9Xq5v0C1CHeR17ZnhdcOhUJCGMgLvjkg631v+/v7lvrOfE2Px7M8/Rlny9dPpVLyCjAOHQiXiSHT4/EUi8XJZMLjYqxZLpeTySTNBtDffTQaff7556FQiLvavb09+adMpVJ+v1+g33044P4pm0uzc+3e7cFmqT6fj3sxh+BryVPC3tCS0XKTcDicTqeprE4GtUOhELAObH7rmpRwOIz94F9Og6P+APhWABkURfH7/Zubm61Wi7p/YYAJh8Pw17PZDHzBVqvVbDbpNmL9TCZzdnaGeh/sU1XVarXabDaFk+z3+6ZpKorCRzvLX+FxFp1+dHNpdq59BHswuRzDMASUebFYxGIx2bdSbaFsdkUuchWix+MZDAZEsyOjFSqVCiRYKRgX9ikD9EJFOH1G4o67SAT13BvStwTBQ2DP4/HI9YGVSsXv96PG3ePxDIdDUJsrlYqgDdLpdARG+Xw+Pzg4kG8dtFjtrlS4Ra6PXsbcccy1exd6tyRL3FVYLewHB+IAtABHWLpIvlxOc9EKhUKB0x7wmS4tEomQtCncLvdiwAdUVeXAC0hsgnAdHU6uIsEmoVBoPp9jh9iWfCIqFSkhCWk6hNvktbe3txVF2d/fb7VauFgSjUK3Ac4XROS+vb0tizrJ/RkajYaqqgJj2tIRo/ad6iotTXWjbBficO3OjfyLLNeJuOkD0z43Qie4BYPBGyWshAOpqjoYDHDyApaCxOD5+Tmh4dz7wyMD/xXQZB4R860Eg2eEn0VLF1wLV/MAXixzsVHgNxqN8JXX6wU0gaRfMBik6Hh7exv6qH6/n0apyWRSLpffvXsnDGkQRRJuAkoo7XqWy2Z5tsts+FzNhThcu3ezLFej0PLDhYHspsx8Zm2apqqquq7z5N5wOLxR2C5EcNwpG4YBljTtEKQOeFKetFQUZX193XxvQsTN75XlJIPDysJVx2IxQUnDUkMunU7H4/GjoyNw2jge4vF4wuEwoedbW1tgcVSrVU7ZXllZaTabfr9f6Gju8XjktGogELCU2P5AUz/hUPrTvXLX7sm4KyEn9YGAhuXmAn0Y6Slagqm9EDIL/DbLvQmdZ8kQaSLwLJVKo9FIpqn4/f5QKPTixQt+HzjQQaTjdDptOdhgRKFz8Hq9QBK2trY4MFKr1bxeL/UK4BgI6ssBPTcaDeiECIerVCqGYTQaDcKC0SElnU7v7+9zjCKdTo9Go1KpxN3xbDYbjUbyjzIajRaLhQBcWPKg7cjRljZ/HGp/H8VcB+3a3Ri9rnIrEEFsU1j/Q6JmYYmsxLb8C0+HkL8VosLJZHJ6ekqALD+NWCyWSCSOjo6EYyEC9Xg8mqYByuBi/7QfRVEwohBQEAwGESwfHh7iiMCIvF4v4lwuzAReM/KBVLqNNuRUChgKhfL5PNZZW1sTsJrNzU3eeNfj8TSbTUVR3r59K5xttVqVfxTMD4SyQ0tYyRVUWtJcmp1r92WYgAsz+ltj0BSMO9CfKXXGDZ7xQ7KUIKLxg0ajUQTU4XA4lUoNBgPsrd/vd7tdfg7w7EiIDQYDwTGhdoZjvvyr2Ww2mUyoB9XW1haocj6fbzqd4iiBQID2SZUjfIc+ny+VSr158waXPJ1OQQhZW1s7OjrCaqqqgmb35s2bbDZLETQulh8ClxkKhRqNhnxL8/l8v9+3rAKXrVqtCqpMrnm93q+//vqPkrHuTXHtbg3ZKs4N4LZk1Rzs1t4c9DLqVYiAVGCw2U2cLcVLCUnH+ZimOZ/P4aYtWSK6riuK8uWXX15dXcG7EXM5Ho9z0VEKdeWDhsNhNKXFLW21WkSm1jQNlSPCgISd06VVKpVGowGPLIxSo9GIyN0ej2cymfT7/UqlIlR1I8NZLBb5ZYLOKDdP6ff7uM/L/IhLemeflI99xuYmCV27RxNqMZbEJW6qrE8wrrBbDmvKqsQC8dlhis1PQGCSUVIOjmkwGHBBCVVVgQLjs2EY//Vf/8WJCpFIJBAI8H5XdIFc9pNOgzjXs9mMkGiaSXS7XX5/cFsEDjJBGTymBs1uOp1SkhOCc9DiAIuD9lAoFObzOUAbrp5qSWTG0QXioPPc5doejMaHVYo/dXMj6E/LHlJ6Rk67LXMClgEXD3jtYmqZ4CVo59sRnx1MqIiDUyNnR6UrmqYJYTK5lWAw+OMf//j8/FxV1fF4jC7gi8WiUCiQaJydXMlkMgmHw7FYbDAYrK2tXb03RNMIfiuVCsWh5XK52+1ySSZAMV6vt9FokHcOBAL1eh0QSi6X460Fr66ucMJ8UOl2uxB0VhSFSgc1TQPbT/4J4MeXxy4+QS6dg7kQh2sP4Y6Ftw7BoHPhtZxjlBtZCeb1euV9orCCtlrm/bcL4uhChNNDPItT8vl8oNDxDbe3t6+urhDUG4ZRr9chV8TXmc/nIM/JZYSpVMowDDj9yWQCagS8J1c6BehBW5GrBRBMZws0hnBk/K1UKvV6XeiBi70JRMBwODwajYBm0DCJk7e7n4J3tvzp0+m03+935kEL9kiahN2ruRCHa3dsJLTmwIKwU8whz2gZP1rGuQLZWd6Kh6XOR7cM8Lnx0FuoKEFyT4giVVWNx+PpdBrJOnw7n88xYFQqFeotoijKcDgkvQviHeMozWaTN52SGw7A5+Jfv9/PyXNoRgUnDhkQeGTBFQL64LcFPI1KpSKwFcPhMJpdcT08FNDLd6xUKnk8HpQdklm6cuL/OZjnjy/800GiubkQh2t3YJahzdbWFsV95OM4GCozprmvt5TLsHxLdV2XMWWeXJLRD8t92q2DU/L7/RSSEyeaTgCpyMlkMhwO4ZEjkQiA2vl8nkgkJpPJYDBAEEoHQprRkoPo8XjQLBwZORw3mUzCcSuKgqaLfFsKXVVVnc1mGDz8fn+xWKT4OhQKpVKpfr+fyWT4YAYG9/n5uZA+7ff7uPbZbBYMBuk+W/Z77Pf78/lc8LwO+VhnWzz3eFk2N4J27d6LBqlhEmofYJbxtSUqsqQcHQ+vhA6nDskl5/6EdllNnBKiSOzE7/erqhoMBv1+v8/nQ9EKJfqImmaaJsCNq6urZrNZKpV8Pl86naYDdbtd4ZRQ5QEg5eTkxO/3ZzKZ+XyORn/k+ywhYAqiOYtjOp1yYgapO1FtIaV2DcOIx+PCUAfHjR2SoJ2mafF4XBbsx+VHIhG+0CEfK/dsdE0wN4J27W6MdH8IAk4kEjSzptCP98y2rG1ZEmq0E7G01IZ23oqbzBKjPVMkCO+JK+VUQp/Pp+s6Qst8Pt9qtYLBYDwez2Qy4Kj1er1AINButzksK7DfxuNxKpUajUaYASDuxleI3+k0LB20gP/i32AwyIvFt7e32+02Bz0URcGFUHhOXxHPj0uFzGaz8XhMJyYkAITg2vK3AB1wyVxigBGxn7e5EfSnQqJ4+EZBRBamCHo4HMr5N+5WLCU3rwUcBBNyiXZ6/M775EMFoTFyCQwvsUPkm0wmFUUJhUJ+v386nYLzkEgkoHk/GAxarRYv3BgOh8lkEh1JsATuj8fRCJPJJeGghmFEo1EhIM3n80IbF+Jr4+R1Xdc0jfBuXBQ0NzidDtcLDp+Q0wuFQmgzSCUtGIqELouwXq8nl3pb2rUANL/545vkEp+ZuaXeD2oPBqstf6APceW0LW+GRIADR0i5B6TP5O+W74llqezs8K/gROhbQQtieco2JI8pcEZpH48lOUE4Go0uFotsNsvBB2xyfn7ON+EnMJvN4CWLxSIPHnmojnPjUtS8BRdh5TTyCUBKpVLhcx3gEvv7+7xmEobqR0uNbBmGdpA6cRa3ku0TBKAtzXXQz8Ru7Wc/xJXTEnpXMVkWYjowE/BB13U6Ig8G5bfa8sSu9aTCfixzWXbAqCwtHQgE+A5N06zX64A7aBNN06rVKvUKMAyj2WwGAoFSqYRaErRh5ZL5VL+H8QN0FBLfIB99dnbGg8d+vw9HyUl7XF2aA9DY+XA4xB4EMjhOhq43EAiAQF0ul4WbgKoW+k0JXbEEWILBoKIoQnRsyc9ZLBa886FrduZi0J+WOfCR7ySU9vv9cExU+ACLRCKI1zg3mSBjXk7yISZLKtOJWTI9rjVLipjX693a2qIhB0ExYk+4S+QVeTUjfHqhUCDRUSw3TVMAWIX7g+6uROSQqd98fQHSxVcCi0PTtHA4PJlM1tbWqHobMbLf7282m8L+8SMC+OYVKD6fTy71hkS18FNa3nnZj9uZ9l6TZOXTMBeD/tTN4VkX3sxlJqrclaAMejqdHh0dYTkPkUBCsKsK4S31PmScsOTtOTA97IwTtPEhGo0SamwYxps3b8DZIMjb4/FUKpX5fA4XjNwaF/9EKD2ZTKj9FXZOoSjJKgHEx7/T6ZSHwHLBi2CESqPeRGZxkHgIl9yjiJvaaNFyZD5xLfv7+/RUCLX1HDkRuBmWd375edvEZg70iZgbQbtmbcu8QtQHhKoYPB4PiQEFg0Figwllzcsf4nZ2o6qzWCwm6OVbVl1ToozW+eyzz6gT62w2a7VaoVAIqnWapqHHKwXXVBeO2jxO945Go/wEsCE1SaENcat5QpXmJXZ1Ogh4weCmhWBxCHcJynny+I0hByqpFK0jSQiJJflwfOZkN2kLh8Ner5dTvF1bcUu9n5ndE1XDebeW31KQhViSnDKFh5ZJwms5FR/ez9u5xBw2mUwsARbSFKV95vN5v99PIWGtVgsGg9yNogErmNF0Idvb261WizzReDxGmxWa4yOstlSAormFkEclFJvQA8IfeGEI1EgEvFhwoLBIJLK6utputwWWIRAYYQAjuqGAXVjy4SxbeeHS5E4xwjorn5i5WhyuWRvX0nQwgbRLvgAtpuB8Kabb2dkhoJbMuVrvRj/PtWIdQDC5y6CBxPI0hHOAd6ZOhovFAmV13FdOp9NsNhuLxUjXAu5+bW2N+M6tVguOEgV+WK3dbjv3IcQRAaSAPoipCWeJ8EsjdJhXKqKPLe9eiA8bGxsCBDydTi0dNyq/cfKRSAQYC9RcZbzFEuW3u8BrUwKePx5cPwV/7WLQj8s+4jMnvLGy/I1lyQYpCNO/gov0er2rq6vwIJz4RXilZSR4O6UFy7hM0IggFgRIxBT8UiDPoXboLEejUQfXPx6PZ7MZOkjBzs7O2u02B15N0zw7OysWi9TTxDAMkI5xOJA3ABPLvbFxrwinJuW8drsN1IjfQ+6v5cK8TqczHo/5PcGGoGlzwynl83nhFw+FQjjP+XxOAqfT9yb/ZNjJN998wxfG4/Eb5ULs1ll8kkiIS7P7mHajZ+6evLndOcALXHtQrOD1esEPMwzj+PiYnLXly8bHBpl0cYvLJA+1WCws5fPtBgDCEGj8QLGJXCURDAYFV+7xeLa2tvBvr9fb29t79eoVrTCdTsE5y2QyuMbhcEjsaUKfsX9N0/jOEfCSXyY0Q7hdyCXyJcTkQ+htSTNHk0PTNAVvPplM/H7/xcWFw/PA/w0EApT4JUPPrd/+9rd8oSVbA3Ryt9T7WnOThM8wZF7ezcmgp7DCMhrKcHPAARRFIUyAOnlzXyx4GUFsc0lNO+Ey4Y+IsUeJLO6USXrCclcc6uX7J20jRVGg64ZLgwRoJpO5urqiTer1erVaDQaDgDvQAIVqWKjGXVVV+EfqkAIoVgZ5SFYUdxgICdakKxJcp6waiqwAob1I+nFIhPjXUL8TzgGMbAwhs9mM7ipkRoTbaFm6nU6nBZVqDFfOTVWWbH/zzMzFoJ+SPYw3J79AkJ+dfyfQQ/6We0MuSilTnmV0xeGULM/BconADCFhELud0Dv/R/3f/hj01HUdwSxwhvF4HAqFCNJVVbXRaKBEhXKJrVZrPp+Xy2WO54LJixZZ5FV52pDOXKi0prFByKxyVQ0BOBZcHgQFhRQfkp/8JiBsx6gj3H/cRmKw0PrRaDQejwtyHNVqtdPpkO4KTPbON7XF4wY37pCI4mLQT8luVON3besgeRO56xJNvS0DZ1nbiA7K01AI2YTzt4Q4BB8qN4Ja5p5QvCzsATuxbPLN6QdUAIKtMEmHjcdj8MloSbvdHo1G5XKZ4tM3b96Agkbr9Pv9w8NDUnpTFIWORdUiOE8ZCMJIwOEOxMtwyrL2xcHBAX0mvIUjDxAURBRMC5HikzkYq6urdB+E2xWNRgWs3DAMWSJjb29POH9L5rvMtn7SDnq+RHR/62DLxaCfg8mNR3RTpFsAACAASURBVO0eCEEbXnCy+ACPwJ0sJRLl+a+l15ZTQAKAa7lcEO4QBPXlK6ImfoQ8zGYzgJtkAk2Yqx0hJ4YN19fXsRw1HQTOIBsmlK70+32fz0eSQI1GY7FY8Lp2+GJ4NPpp6H4KPxYIMHJakgPriKDH4zE+82oRUscncdfBYEBnm06nkSHkR2w0Ghg/eJmlx+M5Pj6WKS7w5t1ul98HcHVkuB9jA1pqyT8rGWSnaERxNs8NI4/HOXm99RjjOujnaUIITE+5XJfF3x+8+XDE/BkVZuJ8c/KedAja4TJO+Voog/J45JiEAwnic0LdGqcJ07+6rlPXVxSqvHv3DtxkflYcQ4fgHJa0223AGtlslgCHvb09KqfEaZA6B4zaqcB4OCyPfLhqGhfhwRVFwTDAhTUODg7ohtAgQSs0Gg1onArDHupZ6KAEbsDD8pMBKo0S80qlQvfc7/fL9IzBYCA3k6UKTG4ej4eH/w42/xjo8zJ80wdCIB/gGK7dt9lBxryAWP6Wo8mYyBPo6UxT5bEtpqvUxtRSOFQ4Qzt3T7o/guYnuSfskLhr5HHg+7A+ldIJjZe4VhGcuMfjGQwGuq5D1nmxWMBNE+bLY7fpdOr1esmromdVo9Hg68zn80gkQkG6UIUxmUx4bTRQYLmenu4AToDPXRRFoatAMlYQtyNeIwYz6vMNBX1OHen3+wKDAqc9GAyEcB4uW9f1QCAg3EOZnoFSb0EFiQat2xVwLx4lvuFcYnOH5jroR2Q3HZNleIEblSBbbig4wel0SlNyHn0LOIMA6UJRnmfq7FJzlk6ZSxJzDU+uaAw02VKjmZgPxD0gd6koCprsCZZMJnEhJMA/em9QBFUUZXd3l4YcSAiRlyRZDFCDcW5ra2s0h/B6vbVabTabEfohnLPAJAGQbYlvUGaSu2wY9KY5xRvVK3IQTZxlXdfpPpOEHve2IO2heltoD4ZJRr/fp9pIfBuNRuWOKnDZgsrHu3fvhNUURYlGo6Qb/nheLuXx1cK4NLtnbnbPHGXw0XWUp4wwnbf0swKzyq4QDi3s7MqseUGwALAIfBJ+CfgWX9FxBSSH/2tJ5iM2AtxftVoF183n800mk62trYODA84IJHSF01Qw38dqIFGQsihWmEwm/Brln0CgSTi7Bt7FkVoH4APVatLeWq0WXx+Eik6nw/tAEn7CheIQ0aNukN89hPmxWAyNvqh6cDqdUgcsfqpC5pDDRNwmk4mQHpDN++DsuiVZ//dnLs3ukzBLJpzds8Una3gluPinLPbo/IzC9ZATvJEWM+8pRYgzr3WmdJns1ATWM1WuEykbRmMSrhFcN2Iug9SMO0DhOfydwEiZz+d8z71eD2gP3SvydMKdwWfLCiCBMEP/olsrbYi/OHqz2STVUBJOKpVKlL4jRJ7riiQSCSwX1EtAK5R5Y4vFYjwe02wJFggE4K/5JcB9o/EVP+HbUdPmd+SdH2FcbGeug37CdifPGefSyTuXv+JCoJZ7U1WV6104FKFY7oHydXxbKFcQrGHZk5uOCwdKLzOCYtqWPAhp7NGYRJdMHEHoHHF3DC1m+e4Rs5DfTzDM7O6ApT9aZrSjYwUCAa/XS64fcswoPSfVf5R353I5QBPpdBpRLQJk7HY0GhUKBUH3jnqBy4LOPAFAhpa4wh7ot+Arh0IhuaSF/xxP3aveIS3a5UE/YXP41Zefmgkd/6jzEEJF4StLl81beEDBw+5Nszsrzqgl/gA6+/GXX65AwYbIic3ncxxXmClToozn3zRNExosYbeUvyLcme+No9t8K7t/LRnElnfAYQXBp1MiETMJTlTHmkBmiGWBDS8vL/Gh0WhAlYn2ic/UcIsfDtXenMZHYJGQTMYtlTnmkCgRMp9yb1mMItTC/JnZ/E5p0W6S8PHajZj8zivb1Xcg6URJME6ckDeBoDvEJ+1OmLP6BN07+kwOnefHwC/G+89HBbQ9xZ4RBhqG4fF4OGuNZzKJqLuxsUFHnE6njUYDJ0aiRdghP3+cpMy/FpKxljm9m/Y6sDOZ4IhxyzRNkLJVVV1fX8ePhXHl7du3+LC/v18sFjl/GR+I6MYDYRDG6XAYqxAUy5xIv9+PQ9AAJqtrraysnJ6eCnqHliwOTdOwjqV+Hl34yh+fw0exe2JhLx9iu0nCT8t44gURGcWqPH0nvB5ECJFds+XAQNKj14aKhHvC8M6TmjtBEAjwQecAfIwokhJiuJZoNArv7/V6kT0jOQt+aFpCDhfohFCmYQdWyFcnrLOMyJSz8UydYRi5XA7EPo4IQ0efmmbhpyGpDULtwSoZjUa4USALmqY5HA4FwX6C++XsLqB5ueJceB6ACAWDQfLjvJBSvv8Ol3+7m7byMTzpHTblciGO52zLJAb52yKXqMC74T0Mh8NEdHM4qBBUIuIgqrLlJgip8JaSUAPRdUHqAnWMp93gpnVdRxIPQTSNLthnp9PB+dBlyrQTudE4YSZ2903ghHBFOvlWyJ9vYVThjc+Xl5emaZZKJex2Mpng98JVj8djarw9GAzQ5hXeEyKrR0dHxPAzTZMIczTb4AWZwq3Aw0BjM09dyl4JAT4vYLH0xdgVBfuWl+/wr50tuZocj3+gZ1+G0+2Wen+65hDxkcqEw1a8roGqG0ic3nITvm06neb+S1aIlgvneLEf4dHz+bzX6xGegEQTuVePx4M1sS38RSQSoUNQyosj6RC554wxWp9vS9gO7hW9wLzYesniMaFuk4wTtFeWM6HwB3xturpwOJzNZq+urkB8jkQiRCve399PpVKC+geI3rgQeG0ud4dfh0jodv4xnU7zHIalQ5zP57LYtGACDv7AIMNcCjjk4tg752jfesB2MegnbwIXWMit2RUEWs76hfy77Mfx5vNtge1aGi+c44lEniTkBc3IdIGnFQgE+JuJc8vn8zw/CQQzmUxih3Cva2trtAlvHQ1HBt8EYhxtwnU2iEAi3E+74jGBS2dXHCQzVZYx3ByKcxGpJZNJeN5arZbP5w8PD8PhMOYcdD4U0wWDQdycWq1GP0e32wWuzUnQVG5uV3RKzRItx2luHP23XM1uCmJpsyXQg7sFqefzuUxxEQxMzZX7N9dBPx+z5M/ZmdfrFar4KB+FQhVhfbzegogwHZf+hcsj8X5+OPrMmRI8M8khDjQ3obcdJNyLi4v5fL6+vu7z+SgkbzabIA94PJ5IJIICOa/X+/nnn/NY+ODgYLFYTCaTUChEHhnnyUEPwzBoiJLZ3JbB9S3YNTdi3Wialk6ng8HgYDBAX5UXL17goOfn57PZbGdnB/1bY7HYYrGIx+O9Xg/ox3A4NE0TPytXHCRmBS0JBoMYI2V/RxfY7XY5fG9HHBQqCe2Klfjj9wDECU3SAvwQs2wocx/mJgk/UeNZeCod5EEiMkVUjuHwOGYyGYKSsRo24QlJXvxCs2NwAyg1NxqNgsEgxOzr9Tp2MhwOU6kUAA0EiZ1OJxaLIcQOBAKTyQQT+dlsRlzgSCRycnJCc3ag1cKrparqeDzGZeJUhciOi8bhg2Xu1PLfDzdOgsaQFgqFwEpsNBqVSqXT6eDEzs/P/X6/aZqoYByNRsCasQehNyvtVijhAdDs3CMxEokA9He+0mXug2ma14bG3iUqCW8EGTmv4PP5IpHI8iIh92FuocpzNueH1fJbrqFBims8PcXDLmFGTwgAJ7oKBADL2mv6zDXgUc4Al9FqtVCjnE6ne70eFHyImwUaw3A4nE6niUQiHo+Dfsc14TKZDMGvKPHAniH6A38n18LgioC0CFQKwfh4I1zpMrZMr3GqaydBO1wFBbDUPQDQTTAYHI1GPp8PQATvSBsOh+GpOWgDEggJxvIbaFcAienOtWdONY0f6Fjnd0QoXpJlIZRKfhRzHfQzNMu3fcnIghdYU0clLk4k75PeaksWGpaj8NruTSaqLO9ybRgGSoRxOUgG4oVJJBKDwQCBYbFYBDUQO+/3+91udzab/dmf/dkPP/xADoW8c7FY9Hg89C9Fo5xTiH5OVLjMaYg4PXD1+CXYee275RtQaI+zymaz8/lc1/XxexuNRolEAn1eOp0OImViScJQ4T2dThFi42JpiBK6KCB+FH5ZgTIo3wrZrvXOcvx+0zFMuQnv4q44cA9groN+PmZXtL28m8DLj4phLglE/Ul5RAmgADE1NheodcLJWDbZkwXbKLqBoh42iUQicJdE5kURtqZp9XrdNM14PB6NRrPZLOUA4Z1XVla++uorTg+YTqdI+ESjUYSfuOpyuQxOHtAA0IcRxVP1OXlqofxS/nytkTaI5bcOuyIsHgnP2Ww2mUy2t7eRDIDnLRaL+AohP4pxiA1N/p1mLbquY+TjTpD45tdWPDk/XaA/Xhv8OnvnJU152HLwBzicy4N+Pia8A5Sjd343eLIO7zCUjrGcyr4RasFlI1zljALSwMNn3uUIiT65B4rQcomOQpReolgoitLr9fr9Pm0OmIVqiyFydHl5eXFxEQwGv/rqK97N5He/+x0+oO6ZJq26ruNAuOqTk5PZbFYqlSh9RJUgBCMEAgGByGFXeoPldCFoYiL8WHD6lAjlZpdtw4fJZALoiYo+Dg4OcMnT6XQ0Gh0cHEA7kKY+vFaTKHS0w06nQ9lRAc0geIfbMg0WyCiKdzDLmyDYMuHz4k5B/2ttycPdrR93k4RP1QSClwM9jpvlahRnmaaJgBolIcAcyfsg74Sgm8fRIA/AAWF6C3cQi8XIU/CKQS6VR5UjPp8PECr8Zr/fX11d7XQ6lUql2Wwip9Tr9XK5XDqdDry3brdrGMbFxQXCSSwnknWr1SqXyyCQgbeAwo1YLAYghdhUiFJN0yRJPHwLRyNLg/LAk/SVOMmaRgUZjXWY/sshNq/hDAQCu7u7zWaTih5RNomDAqCn0ZQ3ncFygeMspAfpd6HplPCQ0IldGx1TOaLDOnQTBA1CMku92bu1JSeaDyx56kIcz9ksnznLhfITz/nFwlskd64CDALGRbFYBOyAfUJMjjYkR8B5FMCaEQ9SVioejwNlxhiAlneRSKTRaOTz+dlstr6+3mq1+v1+p9MBJK3r+pdffjmfz9FpKRwOo9EUvVeAp+PxeDqd9nq94/HYMAxw+JBkm06n8BHIwgETp+QhPoAZjc+ArQWIFh4tFotxxTi6z7LEnSzxTLuSf69wOIwrouJs7HPy3jY2NkB9Q8ZvPB5b7lmg0OCDrutyqEtUdPnEhMfDwQhgsTSv10s5W7u92VVIOduN/Pjy0fe1a96hE3cd9BM2u+eP3kk5Be/8eCFOwV9eVM0rgIXdFotFlHgQGI1/t7a2UDZC3nllZaVcLhNGnEgkiIpHXptwYUSdAFJ0Xe/3+3D0IGP0ej1oH4MWHY/HB4OBz+dLpVJv3rwBhwQABQ0q33zzzdnZGc55PB53u114/2QymcvlcFak+wG/TBqkiEYXiwUkLOCCuQcnzglnSsgEANK/l19grh8ibCUswUhGGD2qqDHagXXge28AFjCzQQBLLWOEA1HQOpvNKAHg8XgwXMnDiRzMOvtBTdM4hUY2KhC1I3vcN9Sr3UQ6Yxk/fochtuugn4PhFYIqhdzPexkKFx4Fcus0PUdsSyqXguA90GH6TK1YFEUhWTKfz5fP5yk7R2dCiAFXjieBCGSWQKVAYN5ut0mdZ21tDVpuOzs7P/zwQ6vVwlder5e6C/7qV7+C0Che73q9jjhufX2dU/rAz5vP5wA6ULqCay+XyxC14J1QMH7E43FgLNSDiiMJPB3q9XqFCT4F0XYl1MvMtVFFAnILfg78UoZhmKZJgxwBzVQXCn86m83ILweDQZAX+TngKaJB2g5qT6VSw+EQft8BQ6OdWxpF7kvmCT02zzNf7iDDLdu13tnj8aTTaYonLO2eRhE3Sfh8bDQa8feExJR55seBdQB5HWFhv98XtDu4GgZf7vf7qeJjfX2dxC1ns9nZ2RleUZ5IJJyk2+1ShE7oNryJYRihUKjb7UKZHsPGZDJ59+7dcDjEC4m3K5FIoHoFF+73+//5n/8Z+//5z3+O08YwcHZ2pqrqdDqtVqugiBGZN5/PI7MKz3t8fIzjopYaQTEg5na7TegzqTNTAToNb5jK4I5RmRy5Tju/wOnhQsqObtpwOASmT8PGeDwmkWsMFfTD8eEBEhy4IdgbEB76sfijIpDi6TTop+fttew8VKFQQOrVzjCm+ny+ZUQ2VEbEtBO9WjLORdywjM1ms3q97rzOg+Un3STh0zP+htB8jfdYunYeyvfDjer6uIwZj7h9Pl80Gp1OpwLISLl7FJsBq+UhEg9LOR5KJwxHgDZ3k8kEl2MYxqtXr1qtlq7r0Wj09PQUZ4IgrtPpqKqazWaj0ShhKWjbyineKFCs1WqYyKMebzKZ9Hq9YrE4m82Aik6nU0TThmGgx2AwGJxMJmAHl8vlXq8HOU0In/KGTxiKZKVAilspsrZMi8HvC3k8OMpsNgsMBxlOCCQBPDFNk5jL8/kcwC5uKc8u8p6zuNv9fl/ucoK7ioVCBE0YWigUQgsbB4i51+s54Bs81XEtMuC1yljSDbdz3HZ7u1ZeA4Wp11JQ7tXcCPo5GG/EKRTF8Xd7GR8tRDF4Pym6oYJsSvcR+KCqKgkP4dEnV4sUFhKGlowosKyoxyDl6AzD8Pl8fr8/Ho9Xq1Xw5L7//vvZbDYcDqFLt1gsyuWyYRhwW6BtUN/oFy9eIHTVdZ0ozxsbG3Ar6HM6GAzgjPL5/OnpKfKNULVHbZ5pmkBICoWCoiidTicQCKCN1qtXr7xeL7p6z+fzL774Ak2yQdmWBXSoip2Gq/X1dUFGikJ4LEQClvSkarXa7u4u7li9Xj8/P9/d3eVhbzAYhEcG+MAfA0A6QKWFH3o8HgvngJ7lUHGzy9GNx2NqOmMXQuq6LrMMyejclgmfFZsHGFMiOpywf3l9ufOLpc1mM66z+EjMjaCfjAnql2Q8v3ejgm/q7sw7oQiBs8fj4bwF3nUJ/FyEXZubm5j/RqNRavaMHqzCcbnWGsJS+BcEpIFAIJFIIDqu1WpffPEFaBiLxaJWqy0Wi3Q67fP5kDb0+/27u7uNRgNU7mq1enx8jCgYETECona7jWDc7/eHQqFoNNrtdlHzjSZPpVLp4uKi3+9ns1kEjJC3x/m/ePGi1Wqtrq4C+x6NRoi7h8Nhu91GFSKRC3ntH7jY6EtL9wFJ1K2tLXQTt/wdQRcJhUIgKTabzXg8DkDJNM1ms4nSbVLu5wXrghQfPTl8JoRNhMcGqwWDQVLF419RkT0cokPw69AC7UbMB6qmkY0//8sEvHdSFPMw5iYJn57JQSge7kAggDdNQAxuqtrDmVU830VROYXGiOOoTyv+4g0h8oZpmuVyGfg4UTuAACLQ3t7epoU0F9Z1HWGm1+u9uroaDoeZTAaT5clkMhwONU2DM83lcicnJ+A27O7ufvfdd3iNI5HIxcUFFToXi8XBYACg1jTNP/mTPxkMBhg50KNvc3Pzhx9+mM/na2trtVoNfufq6gptpXBppVJpNBphYECAHIvFWq3W1dXVeDwGhQONBebzOXyxgCm3Wi2fz4cGqdzlca4LlzPFBAIZ0WAwSJg7eIQ0AQePW5AfsUw8YDUAHZiyIEYW5PZVVc3lchj2ZBEl7knBHnEIAjBmOyfigB05rLCM51Xe55YfuFblvs110E/YBGQQgS25aXqveABlyXcWnmmhUwZ9S3QLCrEJesbrRxppyF9hZZST4JTS6TSXJ0WYiSQVFhLAOpvNUOcNlAPUZkSywWCwXC6fnp6m0+nNzc03b95g2PD5fOFwGPtXFAUCeATawsctFgsU0ZycnCiKks/nr66uXr582Wg0EI3qul6r1bBytVoFgcQwDPIvcJRer3cwGCBOBwTx9ddfI6TFPQ8EAo1GA8y8UCgEAoBwS2V9pUwmA9AAa0JyhGLw0WikvTf6WTFIUBk64mXhCaHfHQXfwNM508Pn821tbclJMIzTgLb5EyL4azoBhxDYQYZFeOo+kAm3+ODWYo/NXAf9HIzXs9HrRGl6oWJ7SVq0/EoIHFU7eSDM1nntHKXLeEtQmrHyF15wZJy6sLW1VavV1tfXS6XSd999hwjXMIxut6uqaiwWC4VC6NwB7/z69WsEbsFgcDgcorCl1+tRJi2RSJyfn4MpmE6nm83m7u4uKHRYv91uX11dGYaxtraWz+dxUYvFIpPJFAoFYK8AcMrl8nfffWcYxsuXLxHgw10CSMFEgWYPiILBDxFuKSJ61FsiGKcRtFAoIJM5nU7L5bKmaViZimUcCGcejyeVSvX7/dlsVigUzs7OMB2hURY4BlEGaVvo4ckyWDRIcI6aXZgMPomDewVIbdnqmy6BLlC1F8UH0dDuWwfHfWuffh/1MoK5DvppG29Xyv0v/BrFwkJ/T7td8X8FWQY7Q7UxcSQA1MbjcZKJQFwJruv29jaRK+hdwkBCJy/I4OHljMViCHIVRen3+6PRKBQKra2tHRwcYH2AsIA+yuXyDz/8gIl8pVI5Pz9HaNlut7PZbKfTyeVy3W43Ho+rqhqJRHRdbzabiqKk0+l6vX51dRUMBjOZDFJ8fr+/3W7XajW/3//5559fXl72er1GoxEOh7vd7s7ODmRAEJyCGTKdTlGPTo7J7/cjqZhOpxEjk4rexsYG7gn9cPDLsVgMp40RdzAYYFtkKRG8Y8oiq1Bh/kShKwlA47iqqkJ8g5wsyJScVwNIIRqNIoQXHoxYLEakYJIOtxuzw+/Nwf+GQiFeayqHEXy3fnvGiIN3Bq4lL7eTUXWwO5f5djaXxfGEjdBAwfmCv3WLpkoOFb10xFgsxo+FYhCBLYu2hPhcqVQIFj85ORFULISjpNNpYh0g6tc0zePxtNttlKUEg8Fms4kA8OjoCLDs1tZWt9ttNBogX5Mr93q99Xod2kA7OzskkfH27dvNzc2zszP0IUQa0OfznZ6eTiYTTdNevHhxdnaWTqeB6hiG8eLFi+l0ivHgs88+83g8GJZ++9vfmqa5ubkJZoXH4+n1elxTiap+yNv6/f5yuez1esGaAOFkZ2cHLXGxmt/v7/f7VNiJu4TcJpFA1tfXMY0AfByLxYjjDONTKNLoAGHR5/ORh43H41QYSYqm+KpWq6E3jTB4C513MBjYPWbj8bhWqzk8dXLXSjsoWf0/5yhTPoj1L6yPO7ZMdnHJ8r9l3qZ7hVlcFsfTM3hkepPtFHaE50YOu+Q9y9Nn4VlHfQem27TDVqtF0dnV1RUEi1dWVkqlUqfTwfLNzU1EjtVqldoYkteAvihK40DRLRQK9Xq92Wyurq7OZrNsNhsKhS4vLxHrYf8bGxupVKrdbiMVxiHvdrvNa5oRbudyucvLS4Dgm5ub9XodMf7Z2Vk0Gh2NRhcXF2tra5PJpNPp+Hy+nZ2dWq0G0aVIJAI/2263IQYSCAT+9m//9s2bN0hgjkYjMJGr1SoQZLAsTNPsdrvhcNjv908mE5SwN5tNv9+fTCZRbIkz/Prrr4+PjymbVyqVeOVLq9UqFot0PwGtUFwM74yngv+yqPfhDwlkT3q9XiQSwRAyn89zuRxi3mQy2e12hSeHzmEZuWcIXdnJvwCXgI/Gw0ai2/IT63//SPAVZJqd8HCuLGF2Ck0fUSOJH/frr7/mA5LroJ+M8c4XWMJJXSQUyTkYzvKYMuHfcmIYCAT4Gz6ZTOQ3ipKEMAg70Pwdvpj0NsnLkLISSuO4tB7E6hA8Aj5Gv5Uvvvji6OiIdFChGgo6MHKDoVCI6k1msxkk3yCbV6/XvV4v3O54PM5kMsfHx7lcrlwuHx8fg0EBTnQmk4EC1GKxWF9ff/v2bbfbbbfbX3zxBXRQx+Nxv9//wx/+MJvNtra2oEZNnnQ0GkUikWQyCSwbN3Y6nRaLReQkq9VqrVbr9/vRaBROaj6f12o11KCPx2OwWeDL6CfGfeM/mVxNh0ocuu2gl8DD4nnQdT2bzVLaAHtOpVK4vd1uN5vNAgPBV9FotN/v43GC99/c3IRCk+VTmsvlxuOx7ECxB1VV6Tlx5mkQaLaQaCqWBVbL+9xlPO9H8c6ug36qxnsvCQHyfD5HGMWbNsmb01/hUbYMXoSEIc2IiWxLpF3as8/n40VoeAn5W0oCZuSdEecKwT4VUiMCxVuKbNtgMPjmm2/++7//mzaBchNajbRaLRxO1/XRaFQul0F2HgwGwWAQTVTH43GpVNI0DcpNqOROJBJ/+MMfECCD+DwYDEKhUK/XW11dhSufTqeQygPPWtO01dVVGnU4I4JiH0iReL3ecDicTCZxpeCxra2tvX37FjRw4DP8N0VIS7ea96mi4kD6EblyNxUuIU7vdrv4jVqtVjgcLhQKuLpAIHB2dgbJfyJldjod4uTgzpMTBAEcn3HcVCqFakbZUaqqmkgkLi4u5IeQTpXkBgVai8wQ9f5xT0uHAHkZf3qtCOoD6DRda24EvZR99N/J4TToTaZMiNA2kJ5sS6ad5TMqxNEC0ZVodhSwU4yG+TjKKKjpH1Va53I5qq8VUlL8WoSrIxgXbzt2aBhGsVgExw41fqj8hlvp9/uZTGY6nWazWbjLfr+fTCYx8Qf1Akk2eMDhcNhqtX7yk58cHx83m82f/OQnJycnoE7Dy3c6HaTRRqORx+PZ2to6Pz8nsja83mQySSaTYGvQXf3qq6+A+SaTycH/GYSl6KZhiNJ1HY4Psw3C4hGo8lwcZJpxM0m3hMu6zmazL7/8EvgP3WQALIAUUFNDck6JROL4+FiYbIVCIYgo4Q7TMzAajcLhMM4cv2y3211dXY1Go3yspeNi/LCDQWgg55Lidg50btVxWDDqVGlpgtjLyqM310E/dqfsbDymoDJiGT6+Fozj0QpnNTlj1nDHQA/4CIECWZzYxsYG8mmgbVE2X8hqkrMQQiSUOJPev8/n63Q6pmmGw+Gtra3T01NFUba3ki29JgAAIABJREFUt1H4hyZYP/vZzxqNRq/XA9lga2ur3+/v7u4eHx/7/f7xeDyZTEA7+8UvfrG/vw8P+9lnn719+zaVSqE7OHCber0+mUzW19c1TYNmE4pW6vU63OuLFy+AnGDW4vP5zs7OTNP8m7/5m729PVVVz87OANDjKGhTALYcZhXAgghdJXo4SCZcJXl7exsYPeLo2WyGe0v91yHWipUBxNMoS6J3uNUUEcNxRyIRLkxRKpVms9lgMEgkEigdwnSHKpXAm8YviMcMWtuWjw28syXNzuv1Er4h5E5kZh6mcSpTNbB7jO2OxZPqwlYrj9VcFoetLcm5+bg/M3fKQoDM62sd9MaIoic33BNy94LKgRDjkB60cKyDgwNN05D35zvc2trCh2q1Sm8UyUGgQwr1RUSoHovFwIFDvd93332HYJ90lqEC+h//8R9oxYIEJkrJsfL29nY2mwUUbhjGv//7v49Go0ql8vLly9/97ne1Wm06naLAZDwe//DDD4FAoFqtHh0dwR+Vy2VEfIVCAcSJP/zhD8PhsFAoJJNJ+F9cy7/8y78gEYrTm06ng8EAfjwYDELdDSNcr9dDCQmcLDV/arfbYFBA8Xk+n79580bX9WAwCMbCcDjc29urVCqER0MwBJtjDJBZw6ByE08DpTTA1kkx4+zs7Ec/+tHKysrR0dHa2hrQpO3tbVK8g1elH2g+n4M7KD9dEES9lkQRjUaFeFY4c5/PR10TFZsXLZPJkDCIYBhFLFvDPHIHLZubJLyBLc9gW74I9a6IlpaVvsubHMLICgYCvRoeBzXcHJGkQhUqtONJQkVRSJJmY2MD83TiCSBURNXf8fExVl5bW6vX6zjK9vb269evMVZ1u92tra1Go1EsFuFWms0mIrtEIhGPx4+Pj8HH2NzcRKn3q1evfv/735+cnCSTyZ///Oco8j47O5tOp9vb2+iF6PF4vvjii7OzM7TUKhQKSFFms1ki9l1dXQUCgVQq1Wq18vk85FUBMVcqFSDjuGroOgEjIt0MCP5hOAEmYJomEANkBbEanB2BM8hA0qgg/0ZowitIEm5vb4PGhyWDwaBQKGBqQugKbrthGJlMBh45lUo1Gg3ydJQZpgfADsQIBoOEY1hGBmgrzmWJSACEP2lw09H38JTlgSyXE6fbchO6JyuP1VyI44HM+SGQ29xZ2vKulvyjQ9QsmJAttMz5yKtVq1VCMGDUYIUfJZFIgGHG18T++avISw35Owygk3hj6XQajbrD4TAcPZZvbGwcHh7iHPx+/3A41HUdU2xsO5lM4vG4z+c7OjpaXV29urrCFJ5yaM1m0zCMcrkMKgWQAVLsy2az3W4XReeRSOT8/BwON5lMjkYjVVUbjYbX60XtYqVSAX0QFxUKhZLJJGn1weGWSqXNzc1Op4OjdLtdFJHHYjEkNnu9Hq6OY1DUToxCWt63G2819FEpo7uzs0NKVVBr2tzcbDQa2Ger1QJfhbf6BlrSarU0TZtOp/iVwRyHGDc9BhDws6vnDoVCgUBALlQhbSbomfDldhG3oiiWBS8PUNH3scx10I/CPsQpy9M07p1lThL9y12toHdOp0RdiGhzuFpardvtEquP9vbjH/+41WrBX+AosmyjPFGwGxL4hBdI9MXFBaCPVCrVbDbhILxeL+DpQCCQTCZbrRYJPeOcF4tFKpWCGtw333xzeHhommahUCgWi41GA3N/kJEnk0m9XgfrA2WQiNxBCg6FQoPBALA7mB4oA0GgitMAeg4cnDQ5+/3+5ubmfD5fXV2Fv+v1epeXl4VCIZ/PY334pslkEggEOp0Ojg4yuNDhkA+NSBLSfcYYQEErSSyRB59MJiTkhF4h+E2pXCUWi5VKJeyfJEcwmm5ubrZaLT4jhNKeJYbg9/s3NzfBUZF/U7AnMTAID55sgkjTytN0uDc110E/VZOfTlpCL49QNg1uBi20zGJDaI3+FYRykG5CFTJtvr6+Dp0HYuNdXFyQx4c0B8gDmUyG5qHo7yecuTDM0GdKT0UiEVBuFUUplUq1Wg2UZ+pWpet6OByu1+uBQGA8HkcikXQ6XavVisVit9sdDoemaa6uroL+sbu7e3h4+OLFi729vbW1NWgiHx8fY9798uXLo6MjXdcp/QUJJ9CWER0DZpnNZru7u8gcAhzweDxgbWuahvwhCa6ORqNer4dyQVxjp9NpNpuTyQQVmMi5zWYzjCsY4SaTSaVSgdazx+MxDKPValUqFaiIIC5GQ0LeTJ0MQwinsnH3GovFCPGAvFS9XkfDWXj5zz77rNlsYpNCoTAcDsPhcDqdBgiTz+fPz89BX5GLpKLRqDDH4t6WipgsbXmlXGd7uq7cTRI+VXNAMEhdTFhOwup8q0wmw9dBdZ/Q0rtQKMiHps/v3r3b2NigJCFVQ/AkId5/LtxOh9je3pbDfNJIQnQM8hz4FTh/uAxorWErwzDW19dBZIYnAvd5d3cXVeYQA4nFYrVazev1Iuf56tWr3/72t5lMplarlUqly8tLBNq9Xu/k5ATkBPQZ4M0e37x5g7Pd2tqC4zs4OKBmV+DhYc1OpwN4BKqewAEgJodEpaZpSP1Np9PLy0uMoJgQkE8Mh8OKohweHp6cnIzHY8wDVlZW9vf3kTkksJ77ZSHPhpiaSszJTNPMZDJ85Waz+ctf/tIwjI2NDax8fHz86tUrfLu3t7ezs9NsNgH0w8ULbYX5zu2Sh5Ynyc2hDZDP53OYbwkk+rtFmT+6r3eThE/bhPoRSxiEF54gpEWrPVpIsp+WzYEQqcGn4IjUm46OzrnApNlEuTKe0uELuUS9zPlLJpM4UDabPT8/R+QVDocTiQRCeEh2tFqtQqHQbrfH4/H29vbvfvc7UIlfvXr19u1bYNAbGxso1QsGg5eXl0iRbWxsRKNRaAmBBgd2Qb1ez2Qyg8FgfX396uoqmUziiHDfKDDB5QADmc/nYBnncjlqQYt7BUIxp6WTnie6bgNpwYAEYBe0PKrexEG5X5MzYITdA7nmvsw0zWQyScEvfk1d1/P5PIgf2BCqI5eXlz//+c+Pjo7G4zGEk6D7AVnXs7Mz7LbT6aAQ3xI7Btxk+az6/X5N0yiCFtIbdoUk/vdou53Pxb2lKRffm51vfcxcDhfieG62TLAgC0sKRFR4Z/7CYErOS4opWOOxPPkCWenf7tws6xhhXDUikUiQbJ7P56PyNhReU3k3eCCDwWBtbe3q6qrRaCAg3djYeP36NcBfokhDaS8ej+dyuaurq0gk8vr1a7hO4Ko+n09VVRQNApHv9XqQ8F9dXU0mk1AWBbcaMSwAELikwWBAbQq8Xi80OnBRuq5DoQkRN5ULplIpaP+T3BXOAcqlvOsYF7mndot06+jHgpvOZrO4YyRqyvnpnU4HQDmXqcPK9Xodyv3AnWmfGEjo6JqmCQleMgiZWv70Ho+H4gDeJkJohkmmqioY2ZZ7g7KV5ZMm+2tLSPARmuugl7LHObp+oMnadcKkUohfLGv/aIksySSrf9zaoNhA+0fByHw+z2QypJDn8XiCwSDyh+FwGPgAyNH9fh9tU9rtNjocvn37Fr0EAQe/ffs2k8m8ffsWEa6macjX9ft9lICjRhypQrhp+CxUCVKlHIlvgP+H2haUMgYCAb/fD2ozJOWoJylAfJ/PFwgEEHoXi0WsjHgcp8SZauj7VSgUKDglVrL826Fanf/ck8kECqu0BJWfcndBEqJCXA+/Px6PuVPDfbaj2WGolmNhLOQemS4Q4rSy09Tf52wtOXMg7chhB5UOOtQNPlrv7DroD+Uj87DlMY/Dd2s8p8cTkgAoVFUFcIloC01JsMnyWgrC4egFCwaDKOqDsj5lpQDaImXn9XpJuMPn88G/oFSaCrshb4S6bSTQwC+G6AdiNLhdtN8mLTqEhFRPjDaGvHk2NY3FueGGALvAmoPBAMlSHGJ1dbXT6XS73c3NzfPz8/X1dWACg8EgHA73+/21tTVN00hHOxqNgjoyGAyQJ4RPpxrCG5nwK1BzQgxUhJVtbGyg5tvj8ei6Pp1OY7EY73dDo7scpeIBkM+NxFiEVCFodpb6RxMmyyUcxVlc955eTGfM5E7MjaBtzYHyJSADduvz32n5/u33rQi+5NMj64Fx9yqr31EBMXwWockcpuDFL4Qw2jE36DPNduH3Ie1G7AWI7iMmBUsXcAcC5OFwCLoIpufwtojpIGuHtB4wZXhw1AQDUgA2AuIw1UCjBQlBEEA8AU/jYuF3wuEw+tJS5xTsFic2GAxQ0NhoNDDNh8ZFvV4HOqyqKnXqor1hIAGuQhTm5cc5SrHSQjSISaVS1A0SPxMyqxi6EB2/fPny4uJiNpsRs/Crr746PT2lnrZ4YIRnBnG9LB4Al8rJoLwk1fL8H5V0hvJQU2qXxXFj4w+K5UNDCRyiIgjlGMJqggL6tVIvH2gO2RX+r1z6hXcMuXt6z0OhEKd8AARYXV2lzamjisD9kkMey5EP+CyuHaoXeLdRZEExMoK4breL7rHw6aiiRkoN8tCk8Fcqla6urvx+/8uXLxVFiUaj8Cbj8TidTsMVwqfv7+/rur67uzufz8/Pz6H7HI/HS6XSYrFAJfRisXj79i3k9KBeDyUjYLX46VHMDRgBNEScM9290WgE4jMVapNAK3h4RJFEgEnDm91TwR8w0utAq618Po8+BgBk4vE40U7wM0FWBQuhnQ3RD6DSP/vZz1ZWVn7zm99g/UAgMBwOd3d35RAEmqVy2Cu0NuYbPolp6OLjnaTL4vhQ4zG1gywL/0pOjt00oF6mYlDOkgvTW7klKAm3kw2Hw0gkQuVto9FoY2OD6raxTyTHOBIiS9jIiJDlFIQIsz6fD3pyyGWBTgDoA9E6Ng8GgwCsEZehIQsc7nA4xKxcVVVd1xGi9nq9tbW1o6Mjn8+HbNhoNII0vqZpONBwOEQHv6+++urs7AyF0SDhAffAHcBUvdPpoJBaURSUb3AQAD4OzhoVKFTrTBQ9cB/ptAHOoGAaww9MqDOSC5EsEwC4gfCblE+r1WpQCkQVKOQ4oHj305/+FA12UX0D951KpUgqD/x6wzDa7bbsoFEIw8NzwZzRYde8kmC/LS3RtQcbeGW/ufwmDlE2eV5EefCYSFsJRlRZvIfValVmgCDtjgzb+vo6UbsAepRKJT6TEMoReVWY87SAB9qkMY/P2DCfz6MUTVGUZDIJcBnQJ8JPckOLxSIajaJk5uTkBJ50NBpBOVpRlHfv3hWLRcMwTk9Pr94bmrngQqbT6f/+7/9qmnZ6enp+fg5RC8AgiG1DoRDObXd31+v1bm9vE7UOPIdIJIJKE3KOu7u7xWIxlUqBn1AoFKrVKmBxICrQJyE57HK5nH1vuANEQJZDAU5mELjGJP3BFzbfGxjf/Oa/fv0avXT58u+//17+1eRi0WUe4JtOCpWlpQuWX/i0zI2gn6EJ2C5XnkToh4I3EnFG5grJdMyCoQSEaBquAYXUcEmtVgsICSnKc+Uazuuwi+wcaiOhnoxJMfwg4lntvYHGAMVkgLbI1IF6QS0z0KmEVPlxyel0GpJJUHSbz+dIheGr6XTabrcLhQKibCDRhUIB4EM4HEaLE1I1ikajtVotEAicnp4uFourqyvTNNFCBWxfbIUylkaj4fP5Li4uer1eMpnEPT88PBwOh9lsFgA3EonNZhPaIMA6IFGN63KgA3OT16HuscI0DvwTvuZ4PCZFU/pKaCgMd2+XYrEsARfCZ3maCNqywMfwSXkRPnXg7HLLY9nVtjxmry1H0I/3XJ+0ORQ+PR7j4kTy9JN/i8uBi+e5Ph7Iy3ogtzOQIuAg0B8LqDGcKWJ5lHoT1gEwBLgK8Gj8xUlGo9Fut4uCbCDaVNOMLrSDwYAE8tE0C0E68p90YhSfkpeBg+A3Af+Gw2EMKjhJHIuaxXCaMI+Iabqw/D28xd1G8M4HVMhRcb1/yMiRfAcWQsOadiJcO78DlkE0r6YRRhEwFwV1OqosNf5vIsg7kVOPc8tr5Gs+rbdS07Rf//rXvPjThTjuxR75cwATZsrCe0Uug94rckzkVuhJ4orDH3hWqAHBERGr4gMl2eA0kWuicjviV/AuM/C5QFqBpGOmn8vlQPDo9/tAJCKRSC6XoyZbUBalJZCs03U9EokoilKtVhOJxLffflsqlUKh0M7ODl6t1dVVcDZwW8B2CAQC6XQactXUtBsgEtVT4NKKxSLYhPI9scsNLnm3qd01OUqOeBCKRUsMwyCRQt7ES9ihZahuF59SEoI/deBoYq5jeWnGe++MDCf3uZaTCboEu+j+1g+nc/HhvYbkLsTh2v9//uQPVCLIea+gcCGGQu6L9CcDgQAPsT/k2RUqI7AryzmvHWeLO27Q9fx+fyKROD09TSQS2WwWKhk//vGPF4vF+fn5X/zFX6RSqbOzs1evXl1cXORyOZD2fvrTnwK8RtQ2Ho+DweDe3l65XB4MBqenp6jTA5cO+UmK7lF2SL13cTKdTsfj8RQKBWQXkdvEFIESg3Yo0PJuAuWggi4oMcf5miCrEKjFkwHRaHR9fV3QP0JzW7nU2w52kMNqcs3XJl189g20+P6fSlTkbC4P2tbs+LlPy6iSimKZD+dZy9RvCoJIRwJ4AvBu7sepl7NwhtyDC/QPglPoK+APpJKMlWnPQkEjr1Cn+0DdFFEuiBwXpDyQJARafXJycnp6qmlas9mEutu7d+8Am7x7945U9CBYCpGK8/Nz4DDz+RzICXXbA+0SWhxgofDRDgg4rpFzVDAXIY8GtN1SeFMmcvBImchtqK4k7ScshL7oaDSiYBPY8S9/+ct3797xw00mk2w2CzE/4amQsWY7iPkWbpeeovmnxPpwWRyi0QNtWY3C+zRztoOlLpff76eVhaS5g93tYMCfafn5djiWfDmWcRAIIZZrUtkCj2epuEO+z+Q6OYYLJ0WuDZRqAi40TSO/jJIQ7sWgeYahAjgMEoDYOZiCoFXQjJuATg6go0YReT8IqO7t7SGWRLQLvjPaBVQqlWq1Op1OK5UKwBn07cZ+wuFwKpVCC3DUrEMeGgXfhKhEIhGobWBST6U38N1EDCejG4gLpx8Cd4wwKHLH0Aahnxg6U0dHR+l0mv/u4/H4n/7pn+RH9/vvv+fPCU7Azr3yagA783g88uYy+SQcDsutsGR9PqrqXHmO5kIcN3DcnCvGJ/tUHEWeiABTvhrPtzhkuu+vUJXvGQciHwdnAZ4ZrY/sHOnawOGirA7rINwjGh98kGmavLe33XUJS8gjo7YCpdiZTAbqd5lMBow6SHAAmoAvAJhAsDXuLTwXBfjpdBpUNmCXlL5DytHr9aIv6traWiqVghLpcDj87LPPdF1vNpvQ90BHWjQ5VFV1dXUVwn6apuHCQd5QVTWZTMJT9/v9yWQCJD2RSICnAcEN/M3lcmhgOJ/PUbKIAUYu0rM0mW9nt5BLDtEjihp64bfgGIvw/AiqWA5nJWzFjatUwwKBwLfffnt2dsZlDjOZDIT9aDW4YPzWzgd9uuayOJ6z2VEpeFIbEms8WjRNE51KaCFNabETXdfxWoLbEAwGvV4vcSqo4BtsMJnvcburAMuKF9GQvgeCL+AeVEGDehY0kULJtWEY6B4CLY5gMJjL5ZrN5mefffbdd99NJpNisejxeJrNZjqdRvOqUqnUaDROT0//6q/+6l//9V+LxSIU/YPBIFSeqYKc4nSO8Nrdf8JnCJqgYhz8LlSSQ/u573m9zGmzdKx2NDUHb3gtU0KuVdF13Y5V/amZzOJwI+hnZRx3pr9cblQoPMG7hNcD6T6kjEDGQviJBnpAVxFh8a5IQEgRtGKHRIFCpGmHQV9rclMunD9dI839UTwCx43gPZvNorETdOam0ymiV13XDw4OdF0vlUp7e3tIHl5eXgJxPjw8RNbu5OQEIhjoEoDwkwYenAwukyBjIjwQEMEHMP6jcBFXXgbtIPPynEy+OofZ5IqNOQMaTzeH5GLQz9w47iwgwhwIxgRcmAvzKAZ1ExT34X1ALTJXCOK6CsQ7pg80T7fD929qnElCddJIZGHIIZ3SWq2GVNh0Ot3b2wPy0Gq1Go2GaZqNRqNWq0FoAidJ/f1ms1kkEgEeAv3+xWKxtbWFoD6fz+PD6urqfD6HMonP54tEIiBpaJoG3h7dN03TUqkUqL50w0Gzq1ar3OknEomVlZXNzU3agwzs4gMHjnj/RvleCWlDok/I9xZqqPJyXJ28nOvJCAe1++0sl9sBJqResmJlDl/dxwj3EWl2zxNZd+1GD65AqAB6AJdH6wCrxTp+vx9+gajQNCMWokjLmbLDgy5UIVJFGY9JBTogJQCQXgNzi0oi6SviRyMGv7q6gquaTqe6rudyudFo5Pf7q9WqaZpfffWVpmk/+9nP4vE4afLt7OxAqfnP//zP6/W6pmko1I7FYkBjqMQG8wncoslkgiJDTDtw/gcHB6qqHh4e4tKwMqjHZ2dnhmFEo1HkNpATgwIJceZw1ZzoAvN4PGgUwGnsqqpmMhkq8cdoFI/HX758ubm5Sdsiu/jXf/3XQnA6m81CoZD8Y1mGvZbwt/OzZwfmOKMoKw9rvJLe7tt7MhfiuAMTIAUKi+5bSnRJW/6B5v6Upt4AMWAEaPBIlsOOwqPsfPncv4DhABIbej/HYrGNjQ208isUCjg0ykDgAckjEClb4Epa6jHRiYHtAFIwjvjtt99+//330L64vLzM5/OvX7/+x3/8x3/7t38LBAKrq6vv3r3b3t7+z//8z83NzWAweHh4WCqVTk9PKSsIpWP05MYZIjJF2TeobLFYzDRNqOiBGYJK+nQ6HYlEMHKgFSHWx68AKh6ulFd88NoQ/GQAXmjugvp+SEfRhhA+JdVpmGEY+/v7ssqH0AJtmV/Wwahok5aEQqFUKgUMioft3j8uCCRczu43fQbm8qDvxbhXkv9+LPuQGZmlwB717kSFNJi/EHSHhDE+RCIRpLwQcS/ZZoWyZL1ej97Vy8tLkAqI9gB3w50UnwFQ7I/Yk1rQQl8U7WXz+fx4PN7a2kLkOx6PEQiXy+VGo5HNZg8ODv70T//0/Px8e3v75OTk+Ph4OBx++eWXv//973d2dv7whz+sr68fHBxAegmi8qQyCodCaBLcKxYC+UF8PZvNSBUaXIXJZNLtdkejESUeIRkou8tlfvpreQ7LlMBc+6vd2jPKNavEJyHDwLzyx6s9e060y+L4JEwQiLiTccJBeoZX+pE7RrgNkJpyZXdyMhwGISV7eGfTNCnsgo+mChq4SKzD5zowzOs5zYtX3MjEAyESJ48sFMc/hvnTozU+G3Aw9f1wS4U8y+z56d55V4vjbioMhfo3eU1BDv+BKxVvnZQT8Ed4Pb4fy+w5kerwvtFbR0UWQsBLO7fclXACqEmRI3qS/cT+CX3mJwCcQTgHGjyIPY1IH1V8mCUQiduyvpzDC7wsSNCaeKI+wtmWeXSXqRkRmsY6HGvOetkseZLP6c67ScLbODv+bMkfiNsg1N3aHeK+fTfPQePlofw+HCKGE2KMoYKDCnDQ3pSydlAl5iEkl9RZ/hW1K4UQ/oU8BUHGlCQ0TRMSFpqmQdUT8tCVSoUSeqlUSlGU3d1dj8fj9/s3NjYqlcrm5iZENlRV/eKLL9Lp9Gw20zStVCqBUYdcHOJo/GqQfqaSHJLvwY3CPZETrfxuUMkf/oIvgb9022lXtITfyTt8MBwIFZYrc9aHUO1iact40mVUOBbPyM/e2twk4V36PprY3mGL6w80Xj3BF/L5OxVGI4TUdd3j8SB/5fP5IB5N3C+Px5NKpVDW7PV6I5EICRbDs9Do5QyC43BYE+4V+9za2tI0bTQaFYvFfD6PoW5tbQ2uuVgs4ljwy9QOStM08LibzSaqabrdbj6fb7fb/X4fZX61Wq3b7YbD4UajkUqlksnk2dlZLpdLJpMgOfzpn/7p6elpKpWCcvQ//MM//M///M9Pf/rTtbU1r9e7sbHx7bffnpyc/P3f//14PO73+3/3d38HRwN0OxAIhMNhlDJClA4ePJlMUsgPubv19fXxeLy5uTmZTNbW1iaTye7ubqVSSSQS0LTL5/OVSgW62H6/3zTNRCKBTuEAajAoglpDiAqVVpJ8B24aWIAk4opWsCiJpFI9KPbt7u6iKznuME44m82CYcKTe3b5umuBbHmWRnx5YT/KI3h9HthcDNq1GxhVG2KOCSgArZ3BNPD7/fF4HJzi9fX14+NjlC9D2x4v3pLNc4E5UNwKNBlK/GDdYqpL31IlIRXIEBZMwAUuASqjgDuwvmEY8Xh8OBwGAoFut4v+UqjqDgaDrVbrs88+29/fX1tbe/v2ra7rg8Hg1atX33//fSaTqdfrwWBwOByi/htniPaGvLCQZEZkMJpGRypvMU0TvphEKri+612ZpXyzQ/WgZeuyDzmca7fAoD+5Mco111xz7XGamyR0zTXXXHsy5iYJXXu8dm2JrSWdxjXXno25ScJ7safoLGTRBiwE2QDZKgC7ENgEcIzUHJcqJfKDnWolLac2taFQaHV1FfrLr169UhRlMBhEIpHNzc1Go6GqaiqVgkwdKgkXi0UqlSJ9DJTJqaqKbrAkhge9CEhF48zxAYb+VcgfRqNRlPOhoG51dXUymVQqlVarVS6Xe73et99+e3Fx8fnnn7darZ2dHSDXpVIJlw+iC0p4kFiD+AaIgEgb0lXjiKAPqqqaTqdHo1G1Wk0mk0RHyeVyqVQKuT6IPQmU4WWKVIXRi/onyJoeyBziEmgF3B9KIeCEOSTtoJrrcJ5P8dV4MHMrCZ+SORDRhA/07hF/jjJRaEaF5D7079GVORwOg1KmaVomkwFzA8uj7y0cDsPXeL3eWCyGijhyfMTcIAEK+Cmu0nBtmoiIzIZhoMR5ZWWl0WhAIHQ6nXY6nVAoBCUjyKKiuA6ODDWB0BStVqvgAv7oRz969+7pcUr1AAAgAElEQVTdX/7lX759+/YXv/hFrVZ78eIFGn6DI9Hv96vVqt/vB00F0ndQUs1kMhcXF4VC4ezszDTNXC5Xr9eHw+E333zzm9/8JhaLRSKRWq0WiUTC4XCr1Xr16tXR0ZHH4ymVSoPBIJvNejyeRCJxdXW1vb1dr9eTyaRpmtFoVNf1YDA4Go3i8fhgMCgWi1dXV1tbW81mM5fL9Xq9yWRimubZ2dnOzo5hGKPRCPv0+XytVgsber3eaDSKJuuUgyUCHw2KYHfwqhkMS6RXjg0xypL/JX4OShzRlACPCs5TaKESiURkjVC5OfcytDzXyFwWx0ewG6WzHzj3LbSRlrtKcwEHom0J0RxJ5vMlQp2ufF28SzQdy+fzEfGLh3icrYGdU4BPDaWCwWC/30+lUq1WC94Q3A/obKysrBSLRchYj0aj2WxmGMbLly/39vbQYQAkaH7y9/FbuNwG1xzMZXG4dgPjShqcx2YpS39/Jiv3w02TVAWnXZP4Pe9IwGl8MF43vHwNsWvL2DIPhkNDgE/ZNIlmJ1Yku+YamVCybOmdb+evZZkLO/E50p4WzC5C5wJDVLTN5TLo0oAC0WwA68CPY0ggkTwCkUzTRBsU4OAQiKBOCDgcnYk8NRFO1fL878/s2qbgA6EfvIpd0JNb0pa5ENc1L2kui+OZ2E01RZf/ijfSplyTvP6SrxwJSeP9h3eOxWIovVMUBa1CkVsDukqAKT5gw2q1SnV0AH91Xd/d3QUsm0wmgZWTPj0JwAIVAcaCSBzgO3q84oj4kEgk0IQF8LRhGNls1jCMZDI5nU4hkocGLvDpgFMIq0GrMCqVpnJ5SADS6QFErlar6XQaKYFAIBAMBqvVqq7r0Hf2+/2RSIRX2DvzWyzr5rk+ATWWJXdMeVSMWH6/PxaL8T3gtPmS3d1d4aByT2EXev5Ac1kcT8ksu2YQUYFeP03TgACsrKykUqnxeAzmAEqQR6ORoijZbHYwGIB6Af84Ho+xByqbhkPhrUCohpiXti+jJcK1O+gz1SiiJQqC4nw+P51OoawfDofhMlBrh/AWm7fbbfhr472hOrzVamFJKBSCXmU0Gh2NRuiaaJpmPp8fDAamacZiMVQSTqdT3BkcfTqdBgIBKJqijhwhZL/f9/l83W4XGqG4IePxGM1tUfCNWkfor5LEj6ypRO1skIPF0ZvN5ng89vl8wfdWKpUuLy9R9JhMJnVdR+dZ3HPSAOGUDH638cMJrA++AtVe8ukRdQPARASV97QJSV+RXV1dCaOy5VzHteXNbXn1lMyB4Utpemp1DB9BfbWn0ylCpG63qygKBIvn8zk1c2q3216vdzweRyKRwWBQq9V0XQ+8N/QfQbgEP4UAE94KoR+J8/KBQZBM4sZhYvICPNeHE1MU5ejoaDgcYit0xYZ/wTUiVkXYi3LzRCKBeBajEZxOv9+Hd0Z/RVDxPB5Po9FAi5DBYABFEe56cFfJDUEjCWIaWI6w/f+x96YxcmTXuWBsmRkZue9LZVZlbawq7uzm0jtbbbVaasmSNbLGHliQbMAajzGGfwzwgAHmx8xf/ZiH8eh5/OARrBFsy34Q8LSNrbHVLbEXNclu7msVa82qrNz3JXKLZRD5VV8GM6uKRbK4qJsHQqsYGRkZy41zz/3Od74zPDyMEPvo0aOQ4Z+YmFAUBdtxadji9/sNBoPT6TT2TFEUr9eL+FRVVZfLhV4EkiS53W4kNsvlsiiKt27dcjqd5XLZYrGUy+V0Ok00+3Hf0H4M54nJQO8rB5uC9zW3JeorZAd91N830vx+/+ADxQUODsunIfPu2tMI+okw/dui1zseJBT3CWD2aenBhyI+Ij0J9VAyvA9k5vER6cbd6XSknuEgiPLwi8QdAGbVE+n0mbedoBx6Yam+CydXrYdu9Ugx+MWtVgueGnMG4mto/dRqNYfDAacMTiF8faPRwKna7fZ2uw32CPhk5BZxHIdwGMiyHkHGPbFarZlMxmQyFQoF8A7X19cxx5TL5ZGRkUQiQTpd5XI5qBSJogg6Njl+u90eGxsrFov4tFgsMgzTaDRA9B4fH+92u6IoghUOrhuBIx68Rw8ZSGQIQfMEXp7cVbKzyWRC8K43juPq9fogPI01zaaw9RPSXegJt6c86Mcc//bpgQ3mxwg00bfzo6+XGxS/1jcG3HS3Tb++qel1/fVfIcfXtwMnks0IdU0mE5r7kSaEVqsVDbw7nQ7wB7vdDvyBoqixsbFyucyyLGJSwDtAD/bs2QN3D943FhkOhwNfhMdEbhCrEJPJBNGler0Oj4b1CsuyhUIBJ4mqGZx2o9EAEoJW6IBQaJouFovYk8xPJOtYKpVarRYwqz7ppbt2d9wKAdNPdeSAmAixNCGLITRpxFeg0YqVDdEdJbM+JsXBOH2rpOJT77wTewpxPDrbVCdaP6DJUNZnb/Qo3qbB6SMY6IOqZuSn0b20Tw57cL2MJfymTaDJ0fD+k08RxyG/B5eBLtcABOCdAc4i0o/FYghXkV6Dd0MFCuoveJ5H4mt1dRUBNRpKWa3WQqFQqVRomk4mk0Deu91usVhEFq7VamGlT8SgScttPD7k63CGnU4HTg0lJMShG41Gq9VKGoMh8Ui67pIkISRbURgJ3IawAzEP4Z6QHr76OsxBTc6+e96niD/4TwKUI3UpSRJxx2azGTMW2T8UCvW1/R4aGuobOX1ZxKdJwge3p+U9nwTblMXV11JIvw8hBTscDrKARXyE7XhdUYKof7f72MTki2ReIRKafbtBkJPgFUA8sQ/cmclkqtVqpp6JoojZy+FwIBBGbTTqTXiehwcnLa8QTQMHwJmA4IEsH+mZhGI53BN9l6zBG9g3lfYRwPVi333NrgbrfQY/JYU2YPXhPEk+FlMLx3FIEqCZAE6YxLaESKPHmvrO+V5Zj31T8uB3B5/p4JZBWt7TwpwH5EE/xaB/C2wQlSaS7XpaBQnBUIsMjBXlc3a7HRFTJBJBg06Px9NsNvHOGwwGq9UK94dwmIi748h6RzN4bvq3dKvd9MsF/Iq+pwYhUciyjP4p2A4iAWoO4cfhghHIk/wYYS4jiEPROWAKYB0Mw2C7IAjYzWazkUwaquH1ChWEBYhbjbU8visIAs4EcwBiT9JThtBFEPCSEmo9gKMnUUAAmhTdIAcLmg2eQl8GuK+Rjf4Ob++OB8k2ZEsflgJWCdmTrI30ad6tfvFpvc8D2lOI45HaA+LF22hxDBZlIIqEY61UKoVCAS4smUwyDIMSZ4qiUqkU+KqFQgEHxHK+Wq2ilxUhlsEbEpIsOQHiegaZGzsPl/TtBEmQjjAZmIZ+ydzpdOAKwdbAr+Niif4DZhrkMxmGAdSLXBbOGbQW5AyxnUS1JAWqp/GRJQgSkgCUKYoSRTEUCpGGh2C5jI2NSZLk9/sJtjMxMdHtdgOBgB7zpSgKWwRB0IulgMsRi8XII4b2CMuy2HOrPjWD3Um2GTCbOnQyGeNomMb0aRJMfoPPF4T0rX7uqe2WPY2gnzgbJDboI1N9h+xNY9vB/FsfD5fgAFhlk+hMH9IiP4a/+9pqEH7IIKp+r9ZXbSHLss1ma7fb0MaDO4bIHKJgsOhA3AYjgqbpoaGhSqWC1QPpD4s4lxTI6SN9fUMTfT4Wl6m/Ij1GAfoH9NugYSTLciQSAW5bqVQ8Hk8ulwuHwzhOoVBwu93ZbNZoNPp8PtAfZVlGExa32w3Npnw+D1GkdruNKdNgMLhcLvRahGYIZORIRk6fRNVPz30YxaA2YV8NYR8ChjoawoUHaN7pdAgSTb6Ck9QPLWJ6zuVTuw97GkE/QaZ/i/RxKPEa5DXQVyIMvgA72bKp6X1r31f0SOI2LniHP0TiR3IhyIwh/QU+HO5AvV4fHx9HKcdLL72E9b7L5QqFQrIsl8vlWCymKEqtVhsfH0cH7kKhMDk5CcnTSCSC4zSbTZ7nzWYzya3hrnq9XiAbpHkrUnkEksbpITGI++/z+RA4Y25gGAahLsuy6XS60WhMTU2h1JBl2fX1dUwwHo+nUqlEIhFZluHBgZDgnKFIl0gkVFWNx+OAROx2O+bFXC4HHiTJjoJsh9UGocQRPIrQEMmIGoyXBx9inzJJp9MhMlVAw3EhhIxotVpJ1Izqyr5SQ/zu4EZyzJ0MlafWZ08j6EdqhKgE70D8IIlNCEiq36h/3+5a3TsYK23/RX1d36Zf3HTLXd+3TXfY6iqAKYNuDOXPbre7urpqs9larRbqNZAkzGazXq+31WoVCgUgIbIsVyoVuCe4UUVRUH0Dx+fz+XBMZD6xBbQ5IBLYSAjRk5OT2WyWnCqqCjHHKIpisVhyuRxmFyw7wGhOJBLAB+BGEdSXy2WDwQBeNuJQIAa1Wo0UQAqCgGpGNLdFkhDXAmjFaDQS5gyJeYGA6yVAidrfzp8R2U3/RYw6UlhIxFJQ3ol9APvoOR7kUIMbn9rO7SkP+tHZpvUm+rBFL4VOvLaeZteXlB/8Wx+AEwwXeX9Ef+TFAx2CrFvJPIF/Ev4AOR/9KfVRaPsKvvuuUf8VfZoRZ6g/c7hLANyAI4B4IgWHqBDcDHhthJ8ohgRaqq9YAWJLYA1cIwJMuG+bzYb2r6jYRsTt9XpBSbbb7QBSKIqC9jGodaRG0e12I5ZEDpMkGAFBNJtNjuNIug+OlcAmuEAophJHTx4BOCrdbheFnQhmwTLGvdKj5GQhoq8eJLNL3/DbYd3QoE/fns6xzcrpKb7xgPYU4ngU1jfK9dUomwY1ffLKmx5Q/yqS4+jzdUajsd1uw++gDhDuz2azURRVqVTg9bCMlSQJujZwOkQTg/jWvvWvHi/etPEKOQ2iDUKumpxe3zRDhHVIuQQRP+I4zmKxgHLncDj0kkPw45IkofQO+yMBqBdxxgHh7vH1arVaKpXgteHaUBWCs63X6/l8Ht9FfA1PjUmLYZhSqQT3ijMh1dL4L7yt0WgEzQOIM6YKnAbkTfCsQTdEqhAUOnwXuAq4xuaeEfiCPGsMFcLoIMmGQVGUu/rKvkl3kKsHzOepz3289lTNbnfsru/GppVg92p9URKpuiY0NX01NlxnrVbDuSH0I+lBoncBghoqJvQtUeD74M70YMtgza7JZCIkCsIN6LsV8D7624XqPhAwSB0d9m80Gmaz2efzdTodURRHR0eRi4tEIjabrdPpQBwDV+T3++GziLMmUBI8GkiE8Ob4CrBURL5ERRrViajShgqHIAjEBWOecLlcAIuxHYdVFCUcDo+Pj7MsGwqFMHO0Wq2RkRGbzQbH2m63m80m5hs4X8wxBGZhWbbZbKLmBScPGAQVK3DWZLboWx7hZLbHwTatOezT4uhbGGGJo4fO9IUqhD74pBn9yQK7P1EX02fQqdmVEKCv9GBTlkVfVe7gR4M8ucECk015xH3FDoMVEEivkRZE2yxvtxIm7ru0TQtStlpND9qm3VJI3AdXAiYDJgyLxQLGgsVicTqd6+vrUD6qVCqSJIXDYZZl19bWaJqemJhYWVmBPhHSa4qiOJ1O8AgBU2By4nm+0WggkgXxo1arcRzn9XrL5TJx4nB8hE1IgAuEsc1mc2RkZG1tDbfFZrNJkuT1ejOZTLfb9fl81WrVbrfn83kyAePWDQ0Nra+v45+QB5mYmLhx4wbuA7Bmq9VaKpVQwoMTJrMmpD+wAiCLAMiTYnlEnCZZOvSRfFBfvv1j2nSM9f2TjIS+tgZ9Pz04oh6v0U/MmdyTfbo6qthstm63+1uRtejrMrWNhv1g+w/EMjabrVwubzNz7OSn7+mL9yHMT6hd+to8ojGNIBolMxA2Qkc+tGSFrgW8MFQsyNdJ19p6vQ4ABMsCBKdAGDqdjtFoRPsr4ln0HbzIWQE7Bpytz5IR+BhABI6Dq0BcH41G5+fnETJ3Op3JycmVlRW443q9DqocpKnIE0RfRNSdE68HMKpWq2Efg8GA6kq90CteZlJbpCgKCkzIaTscDgg27RCJ3jRoICWgffuTypq+g5OizQccNp9aM32qKglRIXby5EnI5RBpYILW6RV5kDGLRqMIr2ia3rNnD+oFdleRa1NahV53Rp+LI95tU7mcPl0LvK591D0SfOndul6jR48+64+8ExBzq41k8YuYlJz/INhNHB/RbEPSDDEgiWdJu1sA6AS2xkc4LMABUl1CHCKheKuqOjQ0VKvVgPm2Wi0MCUSaxN8Fg0HoyZGbRuSeu92u1+utVqvQbCLxIyEy4yB+v79UKmWzWei+ut1uzCulUgmKIs1mEz/darUajQb41yAFij1rNptQ60cVuL6eEFOC3W6v1Wq4IfiIiGjDsJjYdCm2cwOqPjgSXC7X4MH1hZT39CtPbZsk4Se85RUKwOx2+ze+8Y1sNisIwve///1vf/vbjUbD4XCsrq4Gg0FAjTdu3BgfHz9//vyXvvSl8+fPOxyOcDhsNBozmQypDDaZTO+88876+nq9Xt/hCZAoDOHGVmIFZKM+YOlLM+r376NG6eu/EaiShs0Ir8hrBj02gADYjiPoMY2+EH6wPVXf6Q0iP0SxE8cnsyBBOXAaiF4JvQ9q981ms91uC4IAr+d0OgF0dDodNMxGmg5trfsqNQCm4+dAnBAEgeO4Wq0WiUQAkrAs++abb3o8ntXVVUmS8vm8JEmhUAgRKJz4+fPnPR6P3W4vlUoej+fatWsej6fT6ZjNZq/XW6vVTp8+ffjwYVEU4/H4sWPHZFlOpVIMw/j9/lQqRdP00aNHa7VaOBwG269QKCSTyT/8wz88e/as1+sF0y4UCrnd7kql0ul01tfX9+zZU6/XBUE4ffr0kSNHyuXy6OhoPB5XVfXIkSMfffRRLBYrlUpnzpx5+eWXQd9Op9Nerzcej1++fHlw5r4rr2MwSdi3Q18vYGKVSmUrmOupd95d+4RH0HjlqtVqNptFIn5+ft5sNmez2VQqZTab8/n8lStXstmszWYrlUqZTEYUxbm5OaR0bt682e12l5aWEB9lMhlFUUql0vbonr4pFKxP10J/en3UCP343jnIAB1eURTxQ/pFtB5W1tNmN9VO0q/i+5YLfd6ZhPykOLtvYdvHWiEcZFLCRwJq+GgEpEQSxOv1IhrtdDp+vx/gLNwr4auRBgUIk/ViPaRYnOQ/S6WSIAgo+piYmLBYLF6vN5FIGAyGF198EcTEw4cPF4vFer1usVjC4fDp06dPnjzZaDSsVusLL7wAnoyiKNPT08vLy7FY7JVXXimXy0ePHi2VSi6Xy+FwjI6OKooSjUYnJyeHhobm5uampqYcDgcKC2OxGPonRKNRiEEHg8HR0dFqterxeGKxmCRJIyMj169fP3jwIC7zyJEjXq8XFzI0NNRut1OplNfrxROfmppCDJFMJvtuviAIBNHeapRuP7oGwTQyJPooOo9ejoPeYinw2646PRhBf8IxaPBY4Xz1PDNielRxh2i12+0WRdFisRA5C1CmSL+SvlwZiibgJvSVKbsI1XEch2scHMTIkvWNWr3oRB8BQN8Pm9AqSEje1yp78DUmLbfJZKP/abh1rEUQOMMdoyAF4bbX683n8+QkwRSERDLR9oQOJx4lIZyh0g+FIQBMAHGQCxQEAU8Nqv9QBMXAwGICeUvMvgzDTE9Pr6ysBIPBpaUlXNfExAQIi1hXIVs4MzOzvr5eqVRQqDI6Ojo/Pz8+Pr60tMTzvM1m83q9N2/etNvtEAYhyny4P2NjY8vLy6DQgFUC5gnRFdFzHNH3C16eZDX1NE3yOMht/KQm4ugtfn3THu2/LTnDTx0GLcvy5z73OXThfOGFF2ZmZtrt9r59+3ieHx4e9ng8r7zyit1uRzjzmc98hqKol19+ORgMms1mj8dz/Pjx0dHRoaEhnufL5fLv/M7vJJPJffv2vfDCCy6Xy+/3C4IQDAYPHjzo8Xii0ajT6Tx06NCBAwc6nc7LL7/8zDPP2O12n88XDodlWX7zzTdtNtvk5GQgEHj++ecNBoPb7Q4Ggy+++CJN0w/yOiGeGpxgkGfT02b1+Puggjv5g6S/CAGZ/JPspgeRwZMjG+HBCROLYRgkbImum6qqw8PDgIP7PBGZFRwOBygW+CJBSwhuTo5GqhDhi71eL4BdzJEk7wcIhaIoDIOxsTG0ZATvDbCv0WjEczQajZVKxWKx1Go1o9H47LPPiqLY7XYR1Hu9XrPZvHfv3krPnE6n2+0eHx9vNBpjY2ONRsPlch08eHB5efn111+/fPky+s8eO3YMsA+KAw0GA+jegMtfe+212dlZq9UqCILH4wHMbTabJ3sGzNdisWDempmZCYfDqVSKOCNMSGTWv2sE/Uk1dUBS6reIhPepw6ApigLyiHfPaDTGYrFwOGyz2Y4ePfqjH/2IpumxsbFKpVKv12OxmNFotNvtbrfbbren0+np6el0Oh0IBBKJRL1eP3bs2OzsrNlshnw7pCEEQbDZbMViEZDimTNnotHooUOHhoeHi8UigqypqSmAiYcPHy4UCsFgMJvNRqNRrGdjsVg6nQ6FQpCa20VDxfAgILMVKXDT6KPvi33aSZsaUX8mL0w4HM5kMjzPQ+RIUZQrV65ghUFQi0AgUC6Xi8UiUAtUSKP8D4JB8MKEGEfq9JD7xRoFgTagD1Du8PRJOyuWZcfGxiDzLwhCu90ul8s8z//gBz/4yle+Ary4Wq2Ojo46HI58Pg9YIxKJXLp06etf/3oqlRoZGbly5UogENi7dy86FjqdTpqmx8fHL1++LIril7/8Zag5Y9b5kz/5k2KxuHfv3vfffx+IhyzLe/bsuXjxYrVaPX78+Orq6szMTLlc9vl8r7zyisvlqlariUTi+eefx2mn0+lgMFipVA4cOFAsFs+cOXPgwIFSqXT58mXccKfTuemD7rNtnu+ukHmenEBV3bbW8ck5z7vaEz2f7ArE0W63h4aG0un0pvArcSIOh8NkMmWzWX1mjxwKa2TiSvDa960r+wqxCBxGMmx9eUJ93mzno2fTT7eCOOx2O/yFIAiLi4urq6ugo83PzweDwfHxcYvFkkgkGo1GMpkMh8Mej4eiqHQ63Ww233jjjX/7t39zuVyyLBeLxZMnT546dcrn8+3du/fq1asMw1SrVSjmoOFTpVIZHx+v1+utVsvj8aA9YDAYNJlMZ8+eHR8fbzabsVhscXGx2+2Wy+WxsbF0Ol2pVCYmJlDpB25Dp9OZmZlJJBK5XM5sNn/xi1/827/92xMnTgQCgXa7XavVrl279vWvf31ubk4QhOvXr+PGrq6uklIXj8eDWwGqBpGzaDQa4GDs3bt3ZGQEv47aQqvVev78+VdffTWfz5tMpvn5eZvNNjEx4XA4ZmdnwcpYWFj48pe//Ktf/crj8czNzZ04cQIsC0EQZmdnbTabyWQaGRlZXFykaTqbzU5MTKyurgYCgWazaTQac7kcql2ef/75X/ziF5gbAFjn83mj0TgyMvKLX/wiHA6Lorh///5UKgWCHTKHdrt9dXUVKHYmk+E4LhgMfvTRR4CbITaiHw/Q0tOPh7vOvpvaplhcnxLeb6PRT6SP/jTyoJ9//vmzZ88iiyVJEiDC11577cqVKydOnGBZ9sqVK4lEAiRZxMWCIFSrVUh2IdzTA7Icxw0NDQE3BInVYrGAAvXZz352dXX1wIEDiqL85Cc/gcIkvBWRMIa/UBTl0KFDFy5c4DiO53kww/x+f6VSwS/CzcHRQOphdHR0YWGBFJLV63Xy5gw6aEKGbbfbMzMzLpcrEomEQqFyuVyr1d5++2232z0yMsJx3NTUVD6f//Wvf/36668vLS2NjY0RpYtUKhWLxRYWFj744IOTJ0+6XC6Px4NO22jFIssy6j6Wl5dTqdQXv/jFer2ezWbHx8er1erp06dHRkZQE3jp0iWapgH+uN3u06dP8zwfi8Xefffd3/3d311fXw8EAsCF4/E4cKF6vb6+vj42NvaDH/zgtddeg+P+8MMPs9ns1NSU2+02GAyVSmVkZGRhYeHdd9+tVqt46EajEZRwMimSCdXv9xcKBZDtcLuA0ZtMplAotLCwAA7MyMjI0tLS8PBws2eCIDidzrW1NfCsR0ZG1tfXEZhjkVQsFmdmZlZWVjiOQ/X85ORkuVzO5XIYNmiI5XQ6i8UiQBVBEPL5vM1mgxJ3MBiMx+NEogSQEdH5xOJscXFRX4tEUVQ0Gk2n0z6fD6U9MIBXLpdLD5rdh3cmGeNBR7ZNwmZ3kyufNjf9aXTQX/3qV8fHx1utVi6XSyQSTqcznU4/++yz586dm5iYaLVaaDiCCAWUVZZlL126tG/fPkVRhoeHkYwCyHvjxo1nnnmGEFplWf7e9773e7/3e6IotlqtI0eO5HI5YH+lUumZZ565ceOGz+cTRXFqamphYeHatWvPPPOMJEmiKGLlHovFoE4J972wsID2phcvXnS5XG63e2Ji4pe//OXx48erPYtGo/CAP/vZz+bn57eJoAHjgo6CWAxSea1Wy+/3r66uRqPRZDLpcrlMJtPa2trIyAj0i9FcNRwOLyws+Hy+fD5frVb379+PeBB9V71ebzqdxqQCJCGTyUxMTJRKJY7jXC4XuHHofj00NHThwgVATAAfkGrzer1LS0uhUMhms3Ect7a2hmaDqVQKhX+lUml8fPzmzZu4FeVyOZPJgPQNrBbab5VKJZVKuVwuKB/hulCfQqrgMD17PJ5Wq/W5z33O7XafPXt2dHS02Wy+88473/jGNxYWFoaHh6vVqiAIyWQSoEEkEslkMugfCGRjZmbmr//6r1944QWHw3HkyJHvfve7f/qnf3rx4sVarTYzM3Pz5k2fz4dK9LfeeuvVV1+dm5s7fPjw3NzcyMiIz+f7yU9+Eg6HofhhtVpnZ2cdDocgCDzP//jHP3799dfD4fC1a9fAJPH5fI1Gw+fzDQ8PLy0tARZPJpMnTpy4cOHCzMyM1WpdWlpqNpuRSGR9ff2DDz4g/lGfJLxvN1XXpDcAACAASURBVHRPibhH7KDpzViDmwqU3wdfZYdffAQO+pOPQb/33ntXr16FbEIikfD5fPF43GazLS0tpVIpuMWDBw8mk8l4PA7mabfbbbfbsVhMVdX33nsPa3m73d5oNFD0heCRpmmHw0HT9Pr6erFYrNVqPM8vLy9DPm14ePijjz6qVqtzc3NgXNVqNUgAE2VhyDPG43Gr1YpSQIfDEY/HBUFAxFQul7PZbD6fP3XqlN1uh0TDjRs3MpmMz+dbWlra5mUg6A3ke7CgbrVaYBZzHIcoOBqNwnvmcjmoADcaDfAEbDYbqMehUKhQKJTLZZvNVq/XA4HA0tLS0aNHDQaD2Ww+f/58JBJptVpQiRsaGkqlUkCHy+Vyu91GGbrP58ObALIEwzDFYlEQhHq9PjIycuPGDUmSPvOZz3z44YeRSASI0/Xr18+fPw9CbiaTQeJRlmUEtoSTAxUOHA0zJYgQJNIn6nSqqrbbbcARWGGYzeZwOJzP571er8ViuXbtWjAY5Hne7/fPzc3l8/lCoQDBUtSMFAoFh8Nx+PDhcrl8+vRph8MBDesLFy7IsgzaXLPZXFtbGx4edjgc+/fvB7dkeXkZ3cTNZnO5XEZikGEY4Dmgf8RiMUiUoGjFYDDYbLZsNuv3+9fX1w8dOgSxf+QAyZQMlAyAxqZtA3fXO2/PpXtkXa/Uzcpk9JWf+u3bLyAIYXTwi5s2WnyU9gmPoIkMOWqf3G63fjHIsqzVaiVdU6GfoO9qXCwWMeL1H21qm6bdWJYFDQBbwBYoFov4FBElioCdTmcfYnhX0//QNhG0KIp/8Rd/sba2Fg6HE4lEJpM5duxYsVgslUomk2lhYeHw4cM//elPX3zxRZThxWIxWZYvXLigquqzzz5bqVRarRaA5p/85CdHjx6FrtCZM2ccDsdzzz136tSp4eFht9sNktnIyMjVq1dBXq7X68FgcGFhIRgMnjp16pVXXlEUxev1Go1GYBf//u//fvLkSaDSgINYlv35z3/+0ksvCYKwsrIyNjb21ltvYUVCynAAueICUXJNtFKBDDidzkKhQDh25CscxzmdToBXwD0Q/huNRnDkwYZ0Op0ul2t+ft5qtdZqtQMHDly/fh0TldfrRTH66uqqyWRCbqPZbE5PT9+8eZMMgL17987Pz8/MzCwuLjYaDYR1k5OT8/PzeNtRDg7QA/MHGpADAcO5kV7pmJYoipqamspkMuVyGaQd3ARSEdonixEMBkulEtEpHRwzOzSGYSAdRT2ppijKYOHY9oI597doGCxt33X7NEIcL774oiRJFosFsmcLCwuzs7NIeb300kvVatXr9SLsslgsVqv1ww8/DIVC9Xrd5/PBN8Xj8SNHjvzqV786evSoKIofffTRSy+91Gw2RVHM5/PHjx9fWVmBqk4qlfJ4PCsrK5OTk3DuNE0Hg8FisVipVPbu3QvAsVQqiaJ47do1lCG8/fbb3/zmN7///e+jyvw+bHsHPTo6CswaiGcwGBwZGbl48SKBQUk77X379sEZLS8vg6KL1QP0Py9evIilBs/zxWIRfDKfz3fu3Lnh4WEQLdA6BBjI/Pw8Co5xJ8H8BeNQFEWTyVQsFsEna/cMhPHV1dXDhw93Oh2n0xmPx+G/Go0GkgQAmoGBEvlNXCzYHQ6Hw2g0FotF5GAhrIwJALC+KIpjY2PNZtNms5EqcBTKHz16NJFISJK0sLAwMjLywgsv/O3f/q0oisB8eJ4fHR2dnZ0FUIPw1u/3X7p0idzwEydOrKysQO+fvNKTk5MLCwt488GMzmazw8PDiUSCCJJYrVbkXXEcrK5InSHxGkNDQ5lMpi8BGA6HFUVJp9NkC03Tfr8fZG293QcSDc4JKQUazK7rd975BHDXssadm7kXGeyQU/jgqMVDxT0+dRAH8jM+n+/GjRsGgwEz7djYGKQsh4eHV1dXkXDvdDrVahUhrdVqhQ5kNpt1OBzPPvsswzCTk5N+v//s2bPtdhsoJ0VR+/btg1sBKooE2ujoaCgUgiwOx3GhUCgajV69erVYLDqdzkwmEwgEOp3OrVu3BEGo1WpoZhoOh+EN7+MyLbdlIDexWq1ms9kMBsPc3BzDMKlU6vLly6QYDMiM0WhcXFxcWVnR01QKhQLB9ZC/unXrFsuy8A6XL1+maRqgeSqVgiPzeDxAxrFnqVQ6fvy4JEnZbDadTiPuw5IF02cymcQzAqiCX7l69SomNqxa4K1Qc4TXo9VqYRDjIyKJV6lU2u02Ij5JktxuN5kmiQwpTdPDw8MgnKC1ea1WW1paCgQCBw4cqNfrDodjampqdXV1aGjIarWCcLlnz55bt26BoRGNRhOJBAjRyWQSJ3/w4MErV66cPXsWd9VqtUI/pNPpLC4ukpaJAJpoml5dXSVDNBAIoOgJhpuArAnhniN7icJ0vXceGRnJZDJ9KTskA/RbwEm/j6U6cCTcN8IVwRIE0h/6nfUaA5s6MuTqSdkq9u+L/UmFF/3xHAAIi5w80hhkFYVc/Q4v58Fpdo8Ylf6ER9D6Tmt665OPiEajDMMgjb6V1GefSIW+6E5f69UnRGcwGPbt23fz5k0kqXDM0dFRyC8MntJ9XObhCWp6hPu3C5tH0K1W680333zvvfe+9KUvpdNpv99fq9XMZjPP81evXj1y5Mjbb7999OhRnuex+v6nf/qnb37zm8Vi0WKxpNNpnuftdjskkkVRRHlFpVLx+Xw/+tGPvva1r5Hm4oiUGYZZW1sbGhpKJpNwZOh1DWljURTNZvPf//3fK4ri9/tpmtZHeUNDQ+VyGfEa4XJByJ80f8L7T95w3DHQq/HE6/U6AcEZhoGXJ08HOhiNRiMUClWr1X379oG50Wq14HRisZjf7z916hRyiadPn1YUJZVKAQ3zeDyFQgH1NaT1zPj4+K1btwg9HK7c5XKhoFFfBw8XqXdqgLD1/XzhjqHeR4q2oTGN4kk9JAqVPv2w0VA1wXxgpH4r48vlcoMj817N6XQ2Go2vfe1ry8vL8K2IRRqNRqvVyufzeDpIdS4sLEQiEcx8GPBYvkBz9erVq1/96lcXFhbW1tZA3xweHuZ5/vr162izu3fv3hs3bkxMTCCUsfUWfNVq1e12o3w0Ho+bTKZoNGoymd566y2cIVZspHfik0zSuKt9uiJoFHmbzea7PifQ4JxO584Pvs0x9QRnVVVXVlZQwEZcPDwpclZ3PdpWy0liK3lqtcgoyubZQkVRqtVqLBa7ePHiCy+8UK/Xl5eX9+3bFwqFLl26NDc3VyqV6vX69evXn3vuuYWFhWg0imKN1dVVq9UK5xIKhc6dOxcIBKAuhLp2mqaLxSIUpvx+/9LSkqIoRIktHo8DowAkAkDWbrcLghAKhZLJZDabRT9WOFaKojBjoQsXqbgDiE+k/fXFYFBcAnoL3eRWq+WyKlCDstvtlUoFC3/8DdocGHjoovLuu++SqsXR0dGzZ8+iVghZwUuXLqEQ/PDhw91ut9Fo4AyRGqVpemZm5uLFiysrKyBK7tu3b25uLpvNQlEE7L2xsTFE0ETnD3lORIWtVguai0S3BKKpiL5ROghVa1IvSkooMZaI6ggRPHlmsqsopj45uvvOE+K/JpOJ5/lQKMQwTCAQaDQa165d27t37/r6utvtPnLkyNzcnMViQZ0tMEMwL/1+P+CvlZWV1157rdvtvvrqq++//z5S65IklUqlb3zjG++//77ZbJ6enjaZTIFAYH19nef5sbGx3/zmN1A+OX78ONQHp6enl5aWtgI0+jgkm4p8PTKt3V2xT3IErW/F9HjtETzvwdUrKVTRa2LgTCwWy9DQ0K1bt7ZBEkm1N5lp+nbQN11EOTURsUN6jaT1yKIVn7rd7lKpFIvFQODTY6akFAigMPwRomOGYcAjZnuGkAqwBlxwo9GwCdQXjsu/vLzRaRBsGTIMwMmDb0VED+8G3jRpQiiKIuK+/fv3z87OolKRXOm+fftAnsFsgVQkOG2CIKAuBrA+EpIAWNBqYGFhoU/zxGw2Ex0oIqZM7qe++qlvuQZIXf9Q+vKEaAS+qRTizgcVGUKYAnG7LBYLcgbHjx8HdwU3wWKxBAIBXLIkSch+64VT0JIGoivYB60MSLkAwzDr6+u4e1idGD4WnkYhOzRwVFVFHEBR1HN7qUJdSBZuR9CbXuP25L+tPPij53R/upKET5rtZLre6u/7M1RtYJDdNSdDklqD7livrK+voty0twupwMb7CTV9eBnShgMvPJqGgF+B9xBkCShjkLOCFyO/gto/vPDo9kQmp2E/5XOq1+I8UFqv15vL5fT+jnTegnMEIY90F0R5ejgcBiricDhI2hbRaygUqtVqgA7gE2OxGMoO6/U6zq3b7UIlA6tvwBqDlGQg13odQfTiIgpQmDDgqvQ4htFo9Hg8faoAwWBQnySkKCoSieRyuT587548Dk7Jbrfr73CfbYMHDm7ZSmBgJ0OdHpC0xcajU+p8ki+WN/z1Tq5oq0+3ujnkoTwC+zQ6aIZhwuGw/pofr23fMEVv0JZ8EB8Ndsd9cKTuOk/o9fD63hmEn33MJCLljOU/wFm8VECiAFY0Gg2yigdcC+k7knFFgAkklIhcg0VHQkjAAojd7HY7uCKKolQqlampqfseCds8r7s+yvn5eRLwWq1WlJWCWA2QGpMNKUzvdru4Y0StH/dzfHxcH4bDxsbG4vG43rmguLFPcvb++LzAN3Y4hHZObtvFNaWiaKDWDne+79/tS1Q+eA39pvbpwqBhqMjYIdYBv6NvyES2bNXLB8EXkXkj+fRBauq9WqfTQVeO+z6C1+sNBALUk2FwTATrV1U1mUyiJhOBKum2BwUlOGIS/HIc12w29Q9CEATgG2iMK0kSsGaQYZDQw6q8VCqpqjo1NYWvk1OSjSaV014GVqyrLEerCqWqdI9JHY1GBUG4deuW0+l0OBxzc3MEWDAYDENDQydOnPjlL39Zr9fHxsY4jltYWABDQ1GUYDDo8/kWFhZwXST0Q+xPSLuk6wLpnADwB90OSfNv8vJPT0/fuHFDf0vhsklBKY4JVnifd74rhWPQc9lstk21anfFnhyQ9wkvVf/kO2hY1+Fm61XJ7jSW8rnXv8rVKlylZLt5sfjC67TU4eo1240LgiD8wR/8wfLy8ujo6A9/+MM/+qM/eu+99954443vfe97sVjs2LFjP//5z6empkRRRAHhe++9ZzQa//iP/3h5efnIkSOQ8nnrrbcgnsDz/NramiAILpfrzJkz99TBc7esr29Ax+VrRWLaRJ1ZN2WT1QPHLLeusW0tjJ2enkbD1o8++shisYyNjYmieOPGjXa7zbLs8ePHz549q+9+QvT8+ho/k98iDGUS9kL4GGUamP+gZI9lO6rPgS8TlBnpu0qlQpT+URZfLpc7nU6lUiFeGD1Kms2m0+kslUr4J03TWPijbntubm7v3r0qRVWOviKbBfvls83IqOTydF1ez6l/qe0/arvyIdPt0N1OrVZ79dVXaZo+efJkKpUaGxvL5/O1Wi0Wi0EW8Tvf+U6r1frKV75SrVbRm/j5558PhUKzs7M8z7vd7kuXLr3xxht/9Vd/BXeM+abb7UJ3Sd+mFtMSqNZQ8mu1WtlsVu/CjEZjMBjs886Q5Zufnyd7Ikbuk+YgHRK294yDmEM4HNa38X5qj8AGFU4+LQ6abdRKL32u63AFf/aPksVmuXWVT6xod2RomFZU2cQbSjlPR0vXfP7zn2cY5vnnn2+1Wl6vFxxhmqYjkchnP/vZY8eO5XI5q9X6zjvvQBMnGAxCX+nSpUvr6+uf//znUbQSj8cnJiaGhoZQzB2Pxx/XtVeOvMC0REMxJwtWWuqa4wvVQydM2aQY29OMjtluXhKW544dO+bxeIaGhnw+HwTh6vU62mZ/+9vfZhjm4MGDrVZrfHyc5/l4PG42m69evfrcc8/98z//89zc3Le+9S0ISE1PT2ezWYPBkMlkfvjDHz777LO///u/v7a2Bm7fl770JdTK/93f/Z2qqsViEX4B4iRwE4hDjUYjqmyg2oG0EhRZc7kcCJSQrsewliQJdd5ASOABgTLb7XbC3MANYVoiVy0ZqqVOO6jWq83IWG9jc/W//58pigr91++bVxfffvvtUql06NCha9eura+vm83mxcXF8+fPC4IAxvqFCxfcbjfw6Ha7PTU1de7cOaTIfD4fQnt9fwbI1xUKBTJ1IYmKv5FTVRSFVD+SfcBpI7xpGHrQzM/Pk4gPuTWe57cpeb2PuFWlaar3FcWswfdsU8vFmc3mL3zhC6qqnjp1CrW4X/7yl3/zm9+oqhoMBu12u9PpvHnzZqVSwcykKApUt5CyJrW7T+2u9snHoI1G4+TkpFZ1ZjRRqsp0O7nP/TdctYwIOv/qF9uBCCN1/f/6X7iWVnSXSCRQ5A3JiGg0OjExgRZZjUYjEom0222sc6enpxOJBEVRqVSK5/lardZut8PhMOK4QqHAsiwyDJCkuNcz73Q68/PzDwJxhMNhn88nG/n6vmccFz9ojM90XV4+sSyOTrlPv339P/4TRTOOc+9G/vGvT5w4ARVs6Mzt2bNneXkZuHAsFms2m1arNZvN8jxvsVhwZxYXF6FcDOcYiURWV1f37dt37dq1l19+ealn7XZ7fHwcaqImk8nn86XTaZZlf/3rX1MUlc/nUVSJs0UtYqvVQskPyQshlU+UBeG8iEi/vs0VcGdg1iQspSjK4/GYTKZcLrdnz54NsItWaYbqeIOyRWP48WtL9BY8xQcxtZf/Q/0qum2R1QNOG3MGzh8FF8A6iCe1WCy4FhwQX4SeuH5EoY5cvzwHY30rOtpOknJ79uzR+lQ88yJNqfaLZ0rPv2a7cYGtV2lJCgWDf/mXf2k0Gq9fvw4Rq6GhIejK1mo1lHEFAoF4PP7GG2/k83kwLyORSCqVOnPmzAcffLCrt/mTY61W67Of/eynK0lIHLSG8e1pcvxtOB8wsYHjug9ZDAUE1R1mEjp1trzE76KD1h4zo9qH73mGcLvdgiBgEtrKrFar2+1OJpP687Tb7aqiuNzu5Pq61IfoqVQlvrFwXlxcBAIAhGRsbAzRX6vVgloFHDQcMcnGIAkJWgVcHs/zOA4Sa3pt2PHx8cXFRQSh4XDY6XRiJAjerhDoskjB3W+GhwZlZeuv56+b4aCTyWS1WkV13CAcrG+bSzayLIvGBcQ7o+4G/A19Kfno6CjksPUDDKy++05nEQctm8wKzxsqpcQ3/qLr9LBNMfzP/9muapUpmC3C4fDq6urExIQsy4uLi4IgoFXQwsKCyWTav39/NBr96U9/Ojo6yvN8NBr98Y9/vGlRyVOjnjpovUGqGC8GCg77Om8+iAHCg6CawWAYHh5uNBqFQsHlcrXb7YWFBfKKkjYfxKcQbRBJkvr06vASbtVreRsHTdGq0dpjArCs+gil1hmWpe50HNrdrm0Aa+gVACdL3BPLsqSpFampAyUW6Mfw8HA2m4WqEdhyELLAjEu605LWKrhdPM+LoghJa0mSoPJMtDjQ+0qSpLsiUdFoVFEUm82G0hiz2ZzL5aBE6nK5oPSNOp2wIcYxxqXGTUpV5SLLSUYDa2RplmMNlErRDK0qGmG8UisrlCrJXVmRO3KrJYlityF265LabXVbSi8Ih6G1PMRdSRSM2Hkb6iS5+ffE4iAOWlteuCR79D55Zn0teLDKub9DfRqskpGOTX7x08Xi2MpcLpcoina7PZFIuFyuvnzagxscDSKdfD6PPnWdTgecKuzj9/shHj88PJzL5crlciKRePPNN1GpBWX3vj7fIPCDG9voGby5PtQieg6QiELJNXrccRxntVqTyeR9CzPtxAwGg8PhQFUIEAlIlSYSiUgkYh22rqys4ITBVYA/BdaMjq7kFgmCYLVa0bgPVY48z4fD4U7PfD7frVu3IOKKAkII1eNpQlMUshi486BkwEeQshpoW8P93fXSUKOMdCWAYzwjj8fD8zzR0mNoRuBsDM0yFC1TaqmZazREWZUkuatQiqzBKdrigKFZ7eo1d80ZWIOBMZoNwkhgjFUMlERxjFFRlXKrkBNTxaZWbY9aHr0j1lM4YEic9gkPEImM+0CipRqfv6ZNPLtExrg7zXFyclKWZYjiGgyGQqGwE5rzTow00oQgLV4ZTBvkv+Dpk7fpUU4qKKm944Qf5HCgKzw5FGO9Qd8L5cJ7pibHDnUVhfqfXumO+O8ONebKzJ/9leNef5Fh1dEjYr3I/cf/tmk23WXU/m//4L65qlWyQZsYo79YLDYajf3796fT6Xw+3+12b926tWnUQ/wvDP6L1BPj8tFQ3Ov1ejyeRCLhdrtRr+xyuQCpUw/NOI6bmJggijaKolit1kKhkEwmR0ZGkFtDvyik74Apo+4ZiWyg20RHFE0jG40Gum4D5QQnDwsLvWQrIYEQ0XpBEMCknpmZecDi0q1QAoKJD36Ecn+s6zFdOZ1OlCwO1m7oyy8pijayBifv9VlCE0NT9XqtUMul64liM6fQWiUewmfS27fdbiMvuhM9me3Z7oigp6enwVppNpt4OlD7kmXZ7XavrKyMjIxIkjQ7O0vtqoGnSPVUVqBt+4BrPpNFjh1s5teM5ZQZA4Dn+cnJyXQ6bbVavV7v+vo6x3GoBW2326S7RT6fdzqdu36BW5nNZjt06NCuRdBQn9mmga5+ItpqC1kEAZ7b+fp9e1NVtVKpbKRcKMrQg57FFl1v3n1OarTuZ95iGNVgVE2CUm/S8t2uQJK1M0QI3PfRtWvXyCVs9XUEjO12m6hLb2rhcLhUKi0uLiqKQqDkPj7Aw7BtXtrFxcWlpSVc2traGhw0UUNGUIMkIeqDkShDtTHRNoOsFQ6Iviq4FQSkxpq6VCpByFuvqry9oYiRsOIGd9hqcG7PeUcXK1BKIACkr5UnZDi/35/L5XQ/oXbkTptrXM+ev549b2RNNpMzYAlPuPfSDG0PCu9fOsUyHMNqxwFSRIAyLLOA9hCuSJ9k0l1rVjGFZLNZpGeR1xUEIZPJIBNLeJYPYt7hDk2r+VWerGJzPaM+tr7uoPfjH9TerdZdYrvdzuVyQLpAfERCFeWdqIHaRc5JLCCv5u4eyOq7lO2Og+6x/XmKZWhJks1C+fhnDKUcn1rlk6uHDh169dVXT506hUalc3NzmByq1eri4uL+/fur1ers7Oy3vvWteDzudrs/+uijY8eOzc3NnT59+kHOSn9uMEWhFj4SKIr6Xz664xVlWUbuuVIDx3alB03iS11m9gMLRdF/ds3c9yu9BbXCsYx023OrFPWI2jQ8siYXOzTiC8A0AGEOWATqvOG/AM2jvg7NRxAFY1JHDg0zHKR8kFrEu4cdVFWFcn+z2RweHt7UQQcCAZZlI5FIoVAQBIFhGFEU4dqQ71pYWCAyzQ9imGz0TQX1zwVyS30KzkDDKpUKend15U5BzJTb+UAgUClU3SXfHs9BnuVbcrPF1W8lbrAm7eRJeQuOv40WB/nnVqHANk0kIPi1fQJ5Z6YGRtuKTJdTAkPf3R0pH1/XPVlbZOZOa3VSNL1RE6QoCvINeqHXQQXt3TCVoug9UTVVvruDHsRSHshBbzxdjst85RuWuavCyq1mbLLj9TdHJkL/9f+xWq1jY2PJZPLYsWNXr17du3cviY8mJiaGh4dLpdL8/PzQ0NA777wTi8Xi8fgXvvCFf/3Xf6UeivW/nEG/Y99UJJkulavi5Fjw3dOzD+NXxmMBr8fGGw2KqvAmwy/f2YiOH5eFQiGXywUhOpfLhfYckUjkwoULjz570+12kcfDOwNPjdIYuO9mswlMGYEhMBw4bjg7lN6h5S7eOlDr4N8BNDudzm63u7a2Zu1Z3zmIogg9TM0D9s7HYrHArUMeb1duCyoYEcgP1qohZBvcCNYgce5Q2Ej2TFNn7oprlWWTwRQbGqMbxhdHP9vutMutQrae7DLtSr2saq/mBjFxU8XRbSLoR9hChb51xkIzlNRVGOZ2yMIwtKKoDAO8+Pa5PSDWsUNhP47jzGYzKTKCbjskBO7pHCxOaeRAK7tipKj7THHtQpKQE+uBn/0jKzYU3sxVtBW3Ka3NqxcvXrxx44YgCOfOncN863a7C4WCx+PJ5XJmsxnM0O985zuqqv7DP/xDu93+2c9+9sgIBrV6q1RplKtiQ2yXyg+L91Ms1+1WvlSqF0p1r7s/A/CQrP99o1VKpUy9+dtpN8lyp1rd6MMErWe4aeqRGwTSiAdEVbfJZJIkCUA5TdP5fN5kMsF/oSM7LhBuGleKTAMkhPT+FIhBPp/3eDx9Pz0RlmotQ6HKIqTVI/KbLDM1hrIGQtz3ch59wkjsRrYbDAZc9SBColc7gblcrkQigYQqgTKGY8Nz8zcpiprNXeY5s5P3BKwRnyOgdqlap1LvVkpiodIqKjTmsB1rcvU22Dm3jXO0LFrpPERQie4rEQWUZRl9c4g0yr1at42xtzGnassan2N02JfMlKYnwmKz8/7ZOerRGrRPk8kkMsAsyw4NDUmSBNGYGzdu7PBKpQ4tdenOfUGmu8ni4Bo1e7TNu2qRhf+0UQR1UMNytbCIohSOM1glA8fVpITRQtWodd6iDQCGohy96qmN6mGKKlMX6RAVimgIIKWqg/RkmqYYZpNieW30N9jc3Mbl0IyqKn03BRicNhTwc81W99I1jT0aCATmlzdaV+w6GlAqN4j3L5T6O6dtb/cdxehHj80jDU23Ksum//xn+PWL/8dPHCsrZv3iDpECavD6BOAfqrlcLiwzAV+AbgGPicU10GSn0wlEEp2tZVmORqOocszn8y6Xq16vS5IEJ9tsNtGPVRRFVIF3OlrptslkwmUaTArLqc9MdJeznNhmZIUyG9VGmzawlNmk1ESNGWjk1FZHu/sCr1RFLVp/5UDzo1um8v1CHajn1pcIwgYl/AnNALvpHTe0k8gQZVnW5/MRFoemJlnSNwAAIABJREFU8Ce30vVEup6gshTLcgJrdZrdPktw3D1jYAyyqvl0lVJkVZbkrqRIktKVVbk3yGiW4TiGY2nOyBqZ3msiGkpR8xjLGCSvhTMxXq83lUoNDw8XCgUo9s3PzzudTkmSyuVyKBS6efPmblGDNLKLJPNGQ6vd7XQfQ8PWdruNRL3dbq/Val6vt16vi6JY79nOX5C2yN460xNQHLnfqZ3aJauumaprJkg6NBqNdDodCAQ4jkNzUr7n+9ZXtOpqvc3MzGDdh65x2J/juEAgkEqlSplMX2QRCoW0/kClAs/z3W7XZDKxLIsegJV2pcRpZLLovrZnlF+5ag1wAXPFTCu01S/EDkpKu2FtvygIQi6Xg8C82WweGRkRRbFarSI9PcjtvyfjjIos0TSladeSgmN0xLifKtvdcJQsp7KcqtJUqrARIzfbj7ptz1aGsm8AEShII6r2G6hrLygDMshxHB66JEnLy8ug5SF8JnQOZBcRRKOMhTRnikQiOM7oYW0CYDl6JtppdWiPXZZkeiFpCLuljkTvGeqyDJUpsyZOjfqlYo1ZyVCFKvub67zcP+Xfg6F4HeA4tkBpD0rK2NKXM0TlNylIIaKX8OlErRuiKH1ar/DyNE3XlVKtU0xJjKpSLM0wNMsyLEOzGiO7J7HMMhwSbxLVbfa8dlfqtNqtRqM+KsRu1a+YWL61qGVoZ2dnVVVdWlpCunV2dlZ7o3tF8JVKJZFI7KLGUKFUL5brGvqxdIeG6oPb5JCynLnd4mArQxsdArUTKVdEDzshAhk5qiPdrvWfT2zS2Qumn483CT2pXbVKpQLcEOT/QqEAUI8Iqw/uj671hUKB7K8vlOrbv9VqLS4uovEoysOITAxZpIsVxlLpiIVWNVNtNBuCVVAVqiMqcotJrywYjUZRFEulEn4xn89DFBjyDg9y7QaTEjvYbIlM+pYdNx1KSU6n02w2p1KpcDh86dKle5JGpB7YyhlDOcNRFP0//J+3iYMcK0myYjCwNEVLGm3m8fhrOFxRFFmWBR0FlSmAhomkPWpJZFlGCMzzPHopIStYr9fBokMiHnkOWZaxIECTLaPRiL7m2sufMLBGVR5WHII6HurWW0ypzlREJuKlRgJSqcZEvZLVrMyuGboSJZhUA9t7cx7AO8Mwi8DVyrIcDAbdbveT0S0b58DyHzOUW63W/LzmmLpqpytpL8UgtoMt3W53txjKfTY8PIJmOiDLPvgBXeFuJcuNBpXV/IYky91MdduUUo1R74uLfPKQ+N5Vvv7xbVtOsxS1+ep8bGwMyHgqlRp0/bvgoEcONKUuvVegp6MSRW1EoC+PaMgeFe39g473MpkUdZBaSrEfZmhXUGqtmL7yXJuisEBLUcO9/8f+2lfmqQh10W46M8ubrO3o3qaaNn7uQBewCUXdMa+eneUvXL68cT0cV1ynCwmForrNarNerXdqnaY9ED9voCiBojZobfCS8O9A1rA6I3o6MPLpphfex/jR8CaJbtU2QhtAdeg9iNK4tbW1e1Lk2L04t3+EvfLCzPxiKhRwcRy7sJzO5neBpXAf1m63CTvYZDKhWTVeeMgQo5iFvJ82mw0kX9LgEZL8zWYTM7qiKKCvYgefT+vL12g0BEHj8KTTaZfLVVjvBVDR5oUF05Vl48e3mF7NcbNrxq5MXVg04cYn8pzHphTr2sQ/GuymS+yD6LaT9BRykqQpKqxr06ZPQ20jiInFYuFw+OzZs7FYDJ3g0dWXeiRGYBZHQLY4JEN7D16WTqcTCoUKhUKr1QJleFf4LZtaq9VyOBxer3dtbe3Bj2bzSP7hjs0l7aRMBhYLSCyj7h3uNDu0qlKyTF9e3mgkthP71SXzDl9fDIxQKFSpVDBQd9lBm+2y3KWnx/e88szdizv4a7XrrVu8TRZc9lde0qQvt7GyVPrwVsFkUTiT6o3YXnlpfNPdUmLh0vLtfqm9heEdLsnA0ftiSjzDjQQkVaUWUwYSECHZ4rEzdovSaNG8UbWZlaW0oSttlBspirInoqZL7JBXqjQYA0utF1i4PFVV9UG3qtLLF3F/e2Bfzx4OcWdHtk10tp4qyora7nSTmdLj8s5wVVi5o84tlUqBvWu1WrWJthdTw50RCgSc9fj4+NLSEii6pDWfzWYrFApgTKO9KXRKEX2jqpP89L9+aOoqGhSF5lU0TedKqsXCd3pqbXhPRFFMaSi9tuqc07jjDwSG4tfNZnO73Sb5tOqBYyrHyT2hOMvCjS7NMO0m29YUc1Kp1J//+Z9LkuT3+8+fP//ss8/+zd/8jZ4d/FCNpmlb2DZ02MRRZTlpKhcbk5OTWA0jLhkaGorH47vhoNXQRJumKWeH3Tusv8MrNB1XVXX85Tv2rjSYX164B0cJqxfZUporpQ3T+3aaZGp16LBH7sp0TWT2jXTmk/dWjjcZ7q5kOOIeRoNKPLu5s0VdQjqd7nQ6mUxmdHR0lx307AcWmqa+++H6d//pts7hx90mkXDvuyk8RfOUKn79P9zWtwVHmONYilIl6Y79i+uGcppT5Papd2/vzzKMoqIX8t3rTQ2cGvbIYpse8siqSsWzXN+KdSTQVVXKadGONuyXEnkODhoWdGn05YhH5g2qotI9B/0kUo/7ytK2uSfzS9q0kclVIXnzuCBpj8eDJCGW/8CL0eUWO8DVEsITgmuGYZaWlojLQwvabrcL+UD4cZvNJooiyAbNZrPdbgMQIz9db2lx8QtHD6NgIRAI5HI5kNhAxRME4cyZM7t1pagNw+Xox4b15qX61EH3xdPlZ1/KfOm/09YEv/65sHxrfn4+HA5fuXKlXq8/88wzmUzm2rVrW63kHoa5o26O4+ZP1Q0mplnTlrl6pRro820VBOj5Idt8SswVklSFOmRS//BkvxryoMUz9+OgVZXOruBbO30x0yUuU2KBb9xaN9L6Kpcd2HxyQ9GB5VRZoicjSrK0pYs3cmpHUngTZ+jRCvX2QBAYy7L79u0bfAxWCz864pMlRRBMQb/znQ9u1Orb3XqTyfC5Vw+cOTf/2ZMHZEn+l7cuNcS7LCYP7x8x80aHXVhYTjsdlnOXtDe2z5aXl6vVqtFonJmetggmRaU0mFqlev7/dgSt4ZVGAxBstbdPr2ZlI4LudruC2ahtpykNqqUp5WPn3hdB77rtopqd3hwOB/T4fT6fw+FYX1+/dOkS9ThscXER6VMwOog8NIBmYEQkbcIwDAJbwjlBHIqkGQpVUHMI8BppNGh4AllyuVzhcFgLAuiN0rJoNNrqGZoKos0rdKhtNhumgQc3lHo3m03E8tgYCoX8fr/2F61a/F2KpmiKVYk0EoaYNuq0EEpRJbKF7HDH/h8bx5gktc1QnPaVO42mGZVS+vwMeE3tsqHb0nGNGbVlanE1ziJosRdeChR8kSsCtbGn59d7L3rvDrFOp9NrH6OBA3jpVN0OfYQ8mtFEp2mV0sKzjbPacO7KABVaVamOLni6V2MYlby/25jBYLBardVqFXOqxWKpVqtIQZM7sJOfs3mk2MFmbtV40MW+c3WjH+aAqSem2pUGYzUr6XwrNPH6QxdLEpvtdKbsdFiKpXpvCXkXFyNJ8nqyyHHsympOUTRFmbv+RKmiwcedrpTJVdrtu+QQVIrq9g6pC+XvuL+KRj7a+PvjfW7vgNPRnRMZK4+fC7GT+JdhVUWmzCZKVahWl67X6/Pz86qqptNpvGnUYzLw6pAkJJw/lAWifgRbIFCH0ltCV4CUB0r+gFYDJ4WnJsQG+ESI2ZfL5XA4PHakSbPUBM184WiHoq7jJ/7lQ+HUlY1OtQi0y+UyUJEHL2UmcQBiZ2Sz9U9NVSkzb96/90CpXOx0O/V63eV0sRxbqVQMrCYKkUwl6o07OJoCL+zduy+xrrXsabfaPM+zHLu+vr5/5tBqYpllDYn1/oL+PZN7FEUjxnQlDVkyGAwaY4o1GA3GhkDFl9YpSh090m42zc2O4/yvzkdDUZNBA98rDWY0KHUk6vy8iYB7NE2PBqVsmfXYZK9DWUgaas2NLP1G3p6lpqPdRJ6bjnTyVVZRqZWM5ncGh6uq0Kru1bMIpuiQx+e2mUyGWr3psGuz8lvvXtuVVPZOvDNa8Dgcjn379pXL5Wazmc/nDx8+jGdXr9dXVlZ2mExq1ZlWnakXWY1EvIWZTaqBU2MBqbaZRMQuVBIOihkqipor1HKFWp84C0isJIhAmVMvvcNeuKox8FKZnfIo42t5ogu5fXiO12P7UBfMpK1excclkLiTFP9d23E6g93QeLu6avq//rQez3L/4Xtewq4l1wvCA+xR8qDFnhFhOY/Hg458QKUxosxms57Yg6I7uFHSYJCcM4Ju0n0cAkYmkwnV2xtMpi7NUKrTqY4Gb8+5Tqt28IcHVZG3gLDlbhOqVFrMGmUTt6QUgsFgNZ8zsRaubc+sZoxGh8lmM8lCM58Ta3cMQoXnlpUiw9jMJn+7UWYpiybi0bKLBVau2iRVFbP9ZLKiWa7Vanv27MkWsla/P5PINEVtLqQMBrVH1dAiPh/Diob194vNWpMOU7xRrTYYA6e2O3QvxLljQJbrDMdSLpuyXuAGPYvJoNZExmRQ25L23R16Rs2ptbvVWtNm4WVFbYhto5FT1TvC80dg6AUDZiFWZoDRjEYjBHJ3eJxum5n/CIHzltN8s828r+mGUzStNupKRMvIUrsZQY8/21BkNmj+zMLCgtPpZFm2VCq53W6o90J3jWXZeDw+PT2NJqFoe2E2m4vFotlsFkVxZYAi/ZAsHA5brVaQAdrtNvpe22w2dEFmGKbUM+oJsPtzlH3f6vaot502ncgz2dKutR/eFdO3/8BbAf4ckeqnaRrhMKH9ImdIWBCkty/pxoLhhCMQ1gQkluDZ49d4mqaSHPX/nd2YlliOMZosstxy2MwsyzyMrCm5Upz/BlOCUQNjncq64esvtihKpKjSP/66X5EcO6NsUlEU73CrUeaGrNRSugtQuE8N4+LFixjGgOMtro7BpBzyqVGfTFFawSFFr++xanmbWzeEijbHadMSECGKoq7/mlLkttTWvImqUlWRqYoaQrG2WW6yVGdomrqybNwUKRXbzFpew5JyFeM93islmS4l0/3voMPhaDabmK0FQYDrhADAzleBJw9Jp2/2MyU2Nb0MWV8BDjoRb28GTu10b9cZ3Vrbkgett/7uFrvioLUVirJRIGu328Gd8nq9eJEwIgHAtVqtRqNhNpudTmetVkMxWLutLdAe/DTuepq9/2rvBajQHo9nYWHB5XJhfU2KbndlSftYTM94J9YocTfe17Je/+N3wbHRRkk07C6UGtGwm6KpZLpcqz8UKutdzWq1Qv5C3zQEsTNkAOCjgSzDg2DVRbyzqqrookIaY5MmT0TBDolHomvRa3FCtbtUu7vhVkai3uEhb+H8/MG9w81W5yHRWki/bThrg8HgCnYdvq7ZqH7t5Y3L/y/vbf4+ftymSwqOd9oNaUQyrea3fHPJjZJlObynxRqo54foE9P9o/r969ZG+/ZBPhb9uKM7xFbvAia/rQQCSZ/JrT69v8gjHA5DFiORSDgcDrRIhxj6DgQa1dBEJ58wmLidlheYTcpkuJsqcsUaoygaLK7cyQ3b3l7Z33zvGk988kpmSx70HWc5cGd2wUEvbXDLtFQvoQFdv76B7umNbNTHyw9VOR5GM9TIwZYiUyeDlNd+i2z/jNYsNHvqivnWmvFJbr2+Q9v5uHc4LAYDNzkepCm625Ufl4MGtRZ+2W63Q7+fVAaSSLlW07CyQawAYv8ogAKmQSpWiFIHQmyWZd1u96DIBiyVKTM07XJYFlcy1dpDuRWkxwJpotrpdIpaop+u543/9/vPY7du9zIUFjmOlWWFYe5gQGkCbFfMzRrT9Pq63Y0AE3NYbw2Bmsw71ERXrpg5o/rv1T1X8rcpsCyroT3FxpyitAcYVncYb+uY7bJRigHuJ1cBpvn2nat2fa22trYGWVr8DeTBarWSzp/bfNfulR3+rtGs7JwHHfFK8Sx3dLKtKJTPKaeL3Lt3qlRub7+6rMX41APbbiUJNX4Db1Rb2uumrWuwNRaQkwX2QbKuu2I0RRl7etCTQ0rE2+95r8ZvC9HCiBba47WdTPU77zKnt+V4VpIVhIqt3jN7LAZvhQiXzNMGg8FisYBshztAkoQwXDKCO7hp8n42m03SL4MkRfBwczlNbmXT0+h0pOVVLbBAjd9Dulj8OgBxzD0aSpAyUJT6//7yItntxDPjiWTB5bTmi7XhIc+Z83doD1R7gfPa+m2FzInRgM1qbrY6Lod2085euKOYpd1g2w3qXOk2HUUwG0++MLO4kgn47KPD/l+9f33THD6WMkNTLdagKkUTV+fGxsaq1WqlUkHd766rio8G5dXcdtBBs2f6LVDGwPy0FQfRwGoEgWqeohlTvchNHdrp813Pc+Oh7lzC0O7SgYpcbtwbx3Ey3NHzoB+ng454ZZdNGfbJskKv5hiOoTiOMrBqpsTYBLWTefzFrIpCzX+ohfn/64d3nAzHMRSlRV4cq4mzUE+YbTUD69OAg90xdsLrkBXaZNKSb36/v1gsEvLQIzY0NOojXXW7XThrAAKoDCSuGfrRiJdJRSjiO+xDpOUJbks02LY6DZQGNJvNPXv2SJJ08+bNXU9CYMonbba36UpRqze1eneTodXq1Bt35wU3xDbLMhzLiM12XwHBpibJSqnS6HRk3mQoVxpbUSMAH8Wv8bxVqWSWaZomHnnXCxpZg0LT1HhITpa47Quvy3VGUWm7IEPBaif26iHxgxt8tS5Xsj0OyY4Xmo0W3YPXNcuW8XP3EBHfWr+jMOq+bTcwaJWq1JmSWe1IFG+gXFZlfp1jWdXIIXeAKu/HboN60M7905H55TRvMvg89kcvaXjftj1zY/syAdihQ4fQ2NTpdAqC8Mg6+vQZ2gsRBABoMlm+AFNG0ET8MoDpvoslMRQpNUQHrFwuh2Qj8tIbPpFWNeouRNx6ht53aNSCNje7fqV6aTqE9vpEk34ZdG1WS/rFE1pbxeLHOoiIZ/t6fmMGSmcrO+c+Yblw5tzdFcEwpdGyuVmieH6DREHGHdiZvEkrlMco6yNa9Jr7GbQcYo9GrQG4urnjzilZnXpeVBWKbm0HPkyEu50ubTMrFl7hWKoryc0ObeWVa/HNU5TELiyYWp3bO7x1gVXVzcNaq9WqyUv1xOqcTicom/dKfN5124WOKusFDf5azWnRqDaYtG7FGw4x5JZ7qk5qr8qD3ipxR/7JfMyK71X6bXyL1tpr3htCvxOr1ZuFYs1pt6SzZQOhyP92GvFT+pH08R8qZ1TlLm0xqY22pmqGZACqbJLJ5GNRgoZBcANsH0VRkMDgeR5drADU6guCkPgifAz4NRI7EwkUfBFy0nA0kObAlY4/06QZNX7ZRqkbD12PccNIpcBu8aDJFEIcsdaXgFNHDjap2hijWkVRhNydsWfVahWdCgD4NBqN4eHh5eVliHJ0u1273a6qaq1n27c9u29jGeq5qfZswjAT7aZKLENrGgn4CNPeeLjbkWiHoNgEJVngQHMmAy/ila1m1S4o9ZY26mbXDIRD3Xdv8qvaF4fc273gXYl2WBSOVc0ajkoLFtXCU8XahujCNtZsA5zfsD4RCL1BS8vhcCwvL7tcrrExLUNVKpUikci5c+cekibUo4igvXaVY1XeqDZatF1Qmx2aN6j5KmMXtMcTcGkaFyG3fPqmcdgn11s0x2qlHzWRmY5KqzlGbDEOi5IqshGvEgvIazmNXLmY4mIBOeRWzs4ant/brTboqyu705qW6KA3W93LNzQdFofDkcpp2KW+4yr1W2Kbxs568410vdFOfd34n/648cf/u1/siaMTB0eEih4LDxpMR9KUEhtR2qd332BxkIJAEocSPXvStwlBNPHdpBet/uG2RZrlaC0vf4/Fuw94pRh4gHRwPnZ/12xVGKOYj2tMFYfDUavVQLZ1Op12u71er6OiEh3ENdEYj4dhmHg83mq14Mofkh5eT6OGEju00aC90R1NJaR/H00OQdViKbHFEEoMsY6k1aq0u3SzrfU238aTbhRhu7bDa+NZQy/yQ36LZLnufu0Bl5QusdQOiMukvxeSH2hSzDDMIPb9KG0XClUsvFoR6bBHObqnW6wxlQYT9sjFGiOY1HiGbXUol01bVFp4NeBSjnjkVJFtdehCVV1MaX8M++U9EemX5xmLWeW0mnR6NCQl8qzAUwZO+5/YollWE360mpWPwaD7tFAoNDk5iXbRWNgiH6WpSEejaIzNsuzFixcHo6on0+7qTGsF1h2mGxVmNcvI8n013HxoRtwrvLPFYmm32/BlmCfgqYkIL1gQ2Jko38ML8zxfq9WIlyf0WHhn/V1K3ASnUyG0J00YyMq3Wl27TRMDude+Cjs0feyP8yklDc0q22pUKLW6PXeIpmmwnkFEuWuz110xRaUuL2k4TKa0+Uu3kuG2mR2yZS53L91W37likJTbPhpzj9pbPFn///a+rDtuI0sTEVhyX5hcRdKUTEmW7XKpyq7pqu7Tpx56Tr31T5kzL/MP5kf0U/+GeZinnjl9anq6y+WtxiXbVZashRJXkUkmc9+xxJzIS4VCEQASmYlMJkl8DzxJJBAIIIEvbty497tpOsMY79HdofpAb+dA//BL64+P3eOgYXkAAsx4bWSY3Mj7Y6TcWTUPS2qzbc21BV2qo7ihPDnQdo7VhEHqbXRUwvU2iulKJukUK+rRuZJLOaalVJvo8X5MxYpt0wEWrLnX57jZ0QsZ59WxWq7TpM8fXurLOWfntXpapeP200NtOUeljtq9SdiZPsfVSunpE+r4BO+SMahx1+tTLSQwJzHGhUJhGl7IEBHwtQT66zbVp1/SXKb/+k859qTevbNaPKuuruR1TX19UplSbNlQGIbBB0ix2w4CGrAuD74Ols8JhjNzy4D1zUuSslVHFgTNrNc3xqakR4NoLMRpqf73f/NBt2f+z//1behXCkG7LDQYxg9FQd0mVQcb7AKjFDMM31m5ScZs00J9C353kkuRZgfFdKKpSr3tflGTY3APXQYMdlf9I158vnV9ek26KvB2+3vvvVcoUMGm8/PzlZUVQsijR4/GfjERIls/75y+iumq39rM7RWzVKNZ6cs5u9nFKlbOap6cgxBZyjmvy1NRy2AIp/WFtHNepz4K01JOKhiYt92juUawA1i+j/dd3J2tLmaL1ex2lAf2a+/Nv15KfQGBsbL9acdxlP/29/Xbq2Kh4n/+l+y/PkqyGqPFYpGvczGHCGg0+ey2tbGIEK38lkzE+n3rsgi6NwDLEkwmk7AmA5QNzgoQ7Ge+YPgKKBuS5YB5wStKc+dSKVaZhbEJcLrXDXEcsrNbVFX1/37xZEoGKQwzrFcQTQyf31+jzoRbBefliZpLklScHFfw+6v20bl6f91qdpFDlMUM+fa5rmKHflvGDzbtnkmX3eptZNnqw23zxWutVAt/LUEm2UQice/ePfiZWq2WaZpeES8TBiweHx/v7+8vLi72ej3QI4Tp1HhIL9qJtLO01feJg8aI3F6xHmyarS71yagqeUElRj0J2iHoT8/i0/YHhkDQ7y07yznn5bG6mqdBOwdnqm/w+yWAWh2DLp03cFyarLSlElDzoII0VXz15xe27RwXqzSnrn85YklvrMiLN5kQ0mw2wdJkcXXMv8GCiPl8BN6hwfbhFYqBtdfX15lUJizN890ABj89e8dJGa7rgK12stLafOPJGInpSiHrnNfxeQMn4/bWsp1NklaXvk3pBGm0qcfcdqhLNz4oMIAxtZ1LLXV1wcZYWcw4uzjkJ5b32vOAtFsoP7S1tfXtt6HNNrZv2ftnb9dC4Ic+G6wbw28KKaYwWRh4ty+qlQdBo6Tu9xOdJv7oU89hQ8XK89d6TCfJGKm18GLWrrf8xjxNJduDMg5n07TlwnBx1HAm4azknWoL5VPkzqq9czxds39UEEd59T11PP33i7orF9B11TRthBRNs03Qu7tegMR6efv04p6DUxsEtAmcy3IIIeqZFkIdfAttspg8PmCDHct0ORgPwoHAztvb2zs7OwcHB6xkH4utZoMBKzHOm+R8DNzS0pJpmvV6fWiIOnOqsD3ZkizbEz78uEdHKfRCA+nh8sBhiDFpdSGmabDzxeQfH5epQffVk8EhSNmjCcRk90RNJ/3vedAlNf7XoSNozDGSTkZBH76R0v/jj/ik3S4WizRKem9P4PHx3MSxFH0Ht9fso7KKFLLwJt7Z0Gg8mGWD0u/bsxQy9r1188vHVJsh8ElQu05v3XHZM7Gr5yhHpbeMfEDD0vz0o/uO8tPB1IkuhBOUG6je1vsWOqnQgiMq9fLQx5uGTBlUMYQ++jpdc7BtuugH5oChKZ238Yl0FTGmkU7fZchSMf2W0J8qTEebYWh/88vtcrVVOq8//Hjr939wyU2/XEy+QF8bYFQaDcV+5IlPWAETVsOAASGLD7y04M1gTArpgow9GfMSQqDULDsRn78D3mpG1nw54Av2GXirC4UCUzplbmvhQtgrXa1WoQQPf6/Y0p8c48iv5gkpRcyNXsg41GRro5/dNr96YmRTNKi00abFJRREl23ub9jf7ejphNPsoA82rb6plBs4TdMOUK8/WKVPkG4PrQzmr60uyqecpZxzcKY+2LSaHfTTgXZ/w351og4T5RV/PkUhd37Z0WPOZlf/L/944QR79DLddXtJx5ZHR4jc/axD46B7dNRJxsln93r1NjYtpdJQUzTwmQaJdXror3sxKKNRbuBvnsaCS+/z+MsrDHI0/shkMouLi7Vard/vZzKZdDoNtXuWlpZOT09brdbMMo1DIOjlvEOoW91p92iYXaVJ/55V8WKOPp+puNPto+Wc0+nT7VThyUbJGOmZyrfP9YU09altLjmrC7auKs+OtJW8fV7H+TRdbMwkyP7q6HizAAAgAElEQVSZ+ncf9Xdeq5vLzjc/6YOVhHCgqWq90SlXmr2+VTy7tLJPPpiep8W/ZYGAxuuGYKe4mi1gKUMsMzijgbvj8TgkB8JrAM5HePkZTQNYCDCsFvJVIln8MnAxOLLZt6xxQsjW1tbJyQkEkPAXDgMDHwcta2nJgtos15yZ4ZL684VQNfy7fcuK6UqnhyBSbSHtbK3Y37/UN5bsjSXn94+oKL6ukb/7yPzjj7qhkXJDfX/NXivYr06oDmcmQdWEH7xnleuUVPdP1UEeh/LhJi0vD3RPNT/H8WOh4+exRMbpmfh/fH7hfOj1Hdu+WNUcyE5N+ogSQs+iILKxBv8qJ2X1rKZ+sGHajhPXqaFnWpQKMglnEPhMfREqVjrTZEgI68pms8VicWVlJZ1OJ5NJx3ESicTGxsYPP/wwM8HLEAg6pinNgVv9s3tms4NVjO+sUida3CBHJfW8jnMpYui0jkmcVoGhz23MoCGNKlY2l+1qC53V8OayralExXRhNJ92LBstpKnU7IvX6ldP9EKGZBJkMeuUatiauL7yRUVX0z4qtqrVhmEYj58dqaoaj8fnKn5jHko+hzVIyM4Hlo3NOIsPhWYakiDEwb6FjXBn+MpeLKgADF5VVSGzg/ecyKLSMMk4Pz+HVD3mV+EHBgCUXBEsRMElAhuTySQ8RTI7u452zw7feQcrTbxb1FRMHu9ru0XS7qGdY9W00H/8xeiZqNYipkVLijw71E6rWNeUVpdsLNr/+08xOnOlh6PFLDVuaIjqoB553KAe1VHDPOA3apa1Zlk5U5Sd1xedzKSNv/3VnaPjSjyuFxbS//7FQMJ0MlROBgt3a/ROtnv4r3t0MDitXpSbArBJOV2oNEgi5nR6U3w7Op3O559/Dr8glBXli/XMco0qhEzCsxrOJJ2/7movT+iTZDvKi9dqs4sMTVnN2/tnKjj1Yzp92lJxOqQ3OzRdpWcqXz/R4Vq/fKzrGh35Y7p6WKKvrW3To2yH/madPinVjFTQOrlDsL6+/vDhw2KxuLCwUCwWMcZra2vtdrtcLu/u7jK9ykvHtVyrZG5fZsayJx64GEJoGIH2+33mZOAdu7LTgJmuQP2Hh4eg3cF7sfkAauBi2J+J3gE1M6GlVCqlaVqtVoMC8NAC5PLxM3pelZiN8fybLFSJZB9uFWyM6HJTz0TtHlrKORhRQySdcIplNZFxFrOOaaE7q9b+KR3JDs7o33oLSpDQ6602yevzd/i3LWo305i8sH6+brdvO46q4YV8ytDD9MD+2/e67fR8IzINkEYqDxw7403v/vOn1uc/BtKDFmCaJl+Jaijurpu7J1qna15+ospK3nl/zfrmqf7rB+aPe1oqTtYXnS9+1H/zoVlpIHKKMCaZJPloy/rLK+2jLavSQKdIhQg8dnedgUQvi6iDOBAWDUII6pq0XNPYXaX12KhcAG3h/Pz8yy+/bLfb8XgcZGt2d3chEGoeROyuJYK8SMDFkI0C7ghYQnRVEGaeX/aWMo1/+ABWM78CCeJ5TAiCxUoz9pRTSfP5PKSMD12PgtO5+txZ32T7S1OV+xtWu4c0rDS7NNiu0cbgQd5YpIWMY7qylHP2Tml67Ys3ZixvWgYwjcO0NE3L/sNXVLXmp+dibYEJIdRxFrCxsWFZ1meffdZoNEBzyjTNXC739ddfB2kca+T9X3SKrwwNB52YJmPOvXWzWFErTRqWhtBoa2CD/PIQ7nwIY6ChE12j6YKD3G6iYmosJ+Ok1rpID71VoMsXGFE9qk4PrdF/EQuRngGwqtz7VVtByt53eVrHghDQpWRvL/uAMY7FYtOuBhsBwFJIWIIJs3+B4+B3YaTGvMYCIbK4Dt6rIAuxsjXDu3fv7u/vQwbpRQG9gckMYngsNQZKWfN8CiHbwrMBHnNhFOHZWTCf+X8xomlZH2xaJxUqjdBo455J/cgxna6+bC3b9Q6qtWn+1+UppswFisXi0tLSzs4OrdM4qBVp27SCV8DDExlb1Ul20QrOeBtv9KAtW1lbsF+XtT+Mogf94k1V78sn6J1j9aiELRv965+NXIqqjO6fYtNCf93VVnL0QT8s0WCgWku3LHSqkWxy1vo8tFhqCzvORSLWzfQtzB5eM1DekIQVQqiHwhwLggYp3whPu8wQBpGK8/NzhBBUBxcC2mAYYFktL168YGaUrutM/JPLNrz4SlgAFEKYeeOdbfE3t4Wou72B46L0mM6d3wSTsfbR4SDSC8rJGxoNZ0KKAmswA819Gr/R6SJ+VQYhoqKLfUC2bLDGSFvQVIXXdRv62ymzxW8/6X/11KvutWKa5vHxMXxmawOdTsfL7aAO4r5YjH+ror16hM0++uSzoFPkwzOqB/3kwOib6LRqs5K4V08PeuCzV87rdO2i3UWpBHWo0fBiRI3re+tWtYU3Fu3vX9LM/Z6F292LKdrWil1uoGYHg+mTTToQll/IkL1TNRWnQktxnRyXVU0lhQwpVnF1LLubEOXgMYx+b5fgY4a2tbnUalMptVwm+XTn4uePEBYEYmWLeIKxCWt64HBgZM38wnAg427eV8CfAkLlCCGwvC6MDSz0ArYzxSK26sjqBArK1G+flkHhcDkCz7Ztfi3R1RvjOkoxEt9asfNp56SMP9qy//0HY32RiiOfVvGDTRMinT98z/rmqdG3lMUs9SU+2ac6Yud1ukL46T3z+5e6rlKBt1ScQCJCJkkXEk8q+P6G/cVjfTHjGDpNZkGIRgEHVLOZpY2SKVgKnXZfDFqAbNLumahnur/vSCGqSldBXQNzFUX59Yfdk7L6/PDtD2oO0puPzod7qwCtrvLDqwv2P60CT44Q2Pf0kFbFVOYizC5HA8v/4Rf9XIpG8xQreH3ROavhlbzzZJ9GAt29ZWFECyf/6p6ZSzvlOjZt9OpY1TWiYvTRltXqov1T9Zd3rVoLnZS1e+v23qlKnSELTqWJ31+zH+9rK3nrzqpdTpKDM+yjGRgci4XM7feW6o1OOhXXNTUi6KmCTfn514PlajOfhm3bQmgEfMXHzAkfXFNXmOvDNUeUKRax5BFmCH/88cdPntDIBOFAwZcNhwjR3CNV22Mm6kKaUuf6olNrDUxjpKws2M02LZx4e8XeK9KCRHGD5FJOPk2aHVzIOOuLVBO520dP9rVMgsQN5+4tu1jFMR23uigVd2otfKtAG0R0qu58t6OtLjiLGSd4YsXsLOiBSoZjI/yuHvRn9+gNb3SoVKlp0YgvjMlpVb2zatXbuNtH+bTTN1GpjmkIbw/9dPhOivDXP8XgpxbO9uOuGiQOen4QAkE3OjhmkMd7Wo6KtNK4ZoyV1+fqaRUbGuVr0LdzHFp75qd9zVFQp0uVvCF2R9eU7TXrtIp/eKUtZR1dU6ottL5Ia2XtFdVcyqk06cPaNVG9jWAVOxScnFZbra5D41jtcNejI8hgJjBvqIIMNNsH+A6E+Vl5FDCr2SKe62obn7rCWmNkvb29/fLly/X19ZOTEyHwQ2iBrn399JNAskLktZeZLNhlQwMM2LdP9qEg7MX20xo+KKkIkedH2qsTKvf4eF/rm6jbVxttSuUJQ3m8j86qNLmbEDqXj+n48Z6mazSYWlOp6m8ZJpqEJoVVm0hR0EkZ757MnQYDBUF7PyQUpGzcfqdztRZ+dmT87YfdRgeflNX/9EG30aZkHdOpqmW9TW9au4c+fM/s9FCzI9LC/Q2qrHnsXoTyKmGicRJj/Mknn6iqko6Tehvn0/QW814IFRO2OIsQFeB3Xavlgxy9MlP5OgAB8erVq3qdhu9vbW2NFCIzJ+j1egcHB9fPIc7HRDOihIANMGkFx65PI8vLy1BskK0KMvr29wWDY1pIHZSdzgKgLIvQ7NCjZL5GCK2srKytrSGFxGM02K7bR6UavvTqnYBer/fs2bP79+8LuiVTxe8+7f/Hj7T8PA/0plxL3CAxnQZ0ozclWvgKL7BRhlBNbf7R7XZ/97vf8WQVguV4d83eWrX/7Tvjl3fNZhv9+YXOEud5OiYEXaQgSZBcFi6P6dgVVSCKTgkDQzOkx0vDkw+8HuBDzfhbwcsis42g3A/cB1TLG92CPga7XSCmw+xxfmfBlwJOCf5w1jiLaxZ4Vo4DAZ+4cK6hR8k/Lstp/O3P+9kUKVXxcRn/7I716MUcmREzTgj4l68V2/FM6K2/+y9UmVGuHeSRPgSCthw6z1rOU5dQPjNYAJxvqhk7F2joUeOp4l0/agYIgcDwgUltMB+0vOIHH+Skatd7JRunQH9g2MIgIeje8dS/ubkJMgtyCLxM8cL7Iwwh8lFDoWLl4JRWk1JViJydFxBCDg4OfDzRri/R0DdL1/Ug2QayW0lAMpl0HT98OiAMnDNOCAwIvrZRaJmEr0603ROal3lWpRoa81Sywx1DpcjCbfZGIbjvVdYLBeMUPA/sdRJiNgS5OKFxvujfxsbG3t4eC+Pjd+O94a9fv5bbkZlXjmsWhpCA0yDevTMQhzP6dAWMbnl14rJ/TCfgOE4YhEV6wf6DInN4UPSPits0R4wDCwKfy/EKoHQdtBgCphcsLS0dHdFSKF7wMp99Oiz8yvP5tsq9wpM3d3vFXi0M8mUJKjdGzvqfH4T7m82DksZ83kMWTaUPKtrwAkPM8yCwM9Of8w9i46XmoES3YFzLEfgyO/M2PpC1fEb5x2Xn8v/dhf73LbSxZK8VnIfvWwtpGpP6wYaVjJHVBXtrxU7GnIfb5id3rFsF571lW8Xk/oalYvKbD+nG3/68jxH59J6pYeU3D8yPb5uxC92E6cL/AoPU2JVvKQOIovizc0AghK7iypOAEEbdZgfN1exsTnAzCdoLrqrBfNY1e5dkDn0bysp5GASTVj4da4fnevYZhDgEumTKTWwLG0JY32RLWejwqH6tlZyzuWRv37JuFex6G8djVLIG0UBgGkun0RV42ufNZRrCkUvRVZ2zGi7VsWMPJEYdVMg6NlGWslRUcv7tmIWFBR8S9yoUICORSBQKBcUb8qLCVUQIPui4QdxKl910zFV51rmqOM6HPTC+Y4XGeUVQnlvlNl23JBIJyOPnZZgELwcE3gnGtfyTgXDH0N901AA7AY926Mj0p4uS1TRFhcaAVlRai3ogIgaiDoclgxD0/57RaN/nR/S1PaIJunR/h6BiBeeSF86QS4f/HfAX6mTjrr+rRBmkEV5ise2rRNDFKp6TJyNcf8V8LiNcUfA3k2dnRqAgtcyr1gkp3fJnPpaZuaT5ElnMPcKagtdeYOehyX5esRmuAXajPjOGRvc3dNLpKfGBKu9S1umZVHcU9B23VmxdU14c0dqDlk0zDNo9Wuc+FSOlOnq4TZ0ef36hWw6NeqYO3KyTjJOEQXaO1bFrXEzy8Ify1njZN5qm8RUdJ8fQiMzLxaRqdqVSycejdIkARaQJWwivOzcRrqneAhiByhkrPFyXBPn2DcPodDrM7GK6SEJKi2yUuTIRH1INW4R/AWPPoPmJ/MNtS1PJcs55fqTZDq0hq6nKt8+1mK78+kH/5YmaT1PTen3RebBpfbejL+VoBZZcyml0cM9Uu30lbqBcktxetV8eq3GDVsxYX6ScHtPJ2AR9iQ//xsbG0dGRF2NaAXzcAmBS5fXtSPmfV4+gWTnOmSEybOcZXr+OFzt7OTEEi1WOpxZ2ALeGUP2ET/uGRBimWufVf17Nji36CRF+XjL8I9VjZHu+PFYxVpodu1ihGcydHtV6Ni2EEfnmqdHp0yImqQTVhvw/38WyKZrGnTDsYkUt1XGzQ0uNNLuo0UGdPur26QekkMOSurlk59OkNX4h7GmBpQh57cBEkYJgqCeETaquKObR+PXHPA93c4uZjWpBQhhlxX05/sErZFVIzmb1U4RSgYJunOM4kAgjv8yyJ9oHQoK40L3x7nC5MdAor2saptXgQPoRkrXurNm7RbVYxUqV7tnoKKW6mkmSp4ea41CbutJA3z7XBxm2yrND6pIuZJxyA5UbqN3TsknnTSovdGxeVq39b9RI3gYSLOr56uLqEXSEqziqefmOhY0+x7oK3kPBFN6hIZ8xm83W63VBKdT1jLy32qufMkYiAvmkP7ttaaqyuuC0e1SYd22BSv+kEuTHXS0RIw/ft47LeDHrgOhoLkkFD8oNqiB2XMYfbBKMaHz0xpJdaeBUnHT7ygebJJ0gJ2Vs2VTs/+mB9ott67sdDXj80iGITI2HXC4H1ZC9mhqPnedwdn6zZcBvDJjTcx6C/wQSDHiUq5XK5DuEbBe+/Vqt5vq68ia2a9/8Y67Hu5mCn4Q6VW1k2TSBYFBbmeSpEwNVGjimU+2abh85DtVyi+kkplPRiXSCJGKk0sQqpiWHYgZV3dQ1Yg7oWFWpPFnfpAUxLBvpKlWRrLXQ2EoJoyKUB2xlZcV/h5pbrfrJOzZv7BxZ0DcFgg/BfwI4Mzsi+InkPflygvJGQYLDv3HZDx4QoeSdPqWuCeo4Vi5kgKhC78AdQQxNOTqn4rqlOlWkA8mwuEFMG1kWVetvdanQI81CLKqEUHd2Nkkrxu6eUL/2IP6V7nBe1+YtU8nr8YNH9PT0NPSOofmzjoMgcnHcIAgO3KG7hYggEkI+L1KQLcJ1ZTIZuSSS7CdhoXJygz6vdFhv+1rBThjEpJp6FyJttwp2rYWfHmpLOVKq48UM0TXHsulXrS6+v2GVG3hzidaQPavhrRXHHnyVTzutLrW1S3X02X2r11dyKfLF43ckkucEASvOhHIizMUOXVGXdETQ1xlDeWRmaylDzyIvA8qhdXK9K3k7QNM0n4J1Qna4MiJCYWcwFR9s2LpGyk28uWTvnqh31uxyA6cTBGOytUyLEN1dtyAaGiOl3qY5hxuL9sGZujRQqX/4vllvUwfIoCYW3ly2fv/IIA7VWG+EV8k7XIRFwfoAPpJ7oTi7Lx0RQV9nCJEMrrbM9Djan8gE/pV3dpWXc22T7z8IoXmFXsnh2D499LKpQ6EYaOTpoWraqNtXjkpULuG8gS1LWSs4CYM8O1RtB714rRnUv0wt7HYP2Q6qNFFcp/Lr7R569EJvdmhY3lLWOa1SSf5OD714rS5mnULm6k3nA8bPocGvYA4wpbPPjz8kIugbAUHPnm0U4tVCP6nrdr6WldfOruKQQV4b1xwztkAKJ+XVLEfybIT40gLRH5cv1iebnMF7UmGLlqRUu/A+w98n+++UDjkYVJUdVMl4u73eRvW2ulscv7eXy03w0/tEN5Owu+caz6PMByKCvhFgsstyGRF/4zQsCAPD0Pxa4auhgcbgcHRdEpTjlEdKFJ7SbalUKqxw7bTPNSrk8rizROinNoapS8/DPfdCRNDXFq52AbCzK5fJqXEhQj6Xa4K1jwNBngEI33o5HHVd7/f7gknuM2OQuxri9IL137btMWLF/Nu8KvDvcCjXgrhThCjcMXtEcdDXFsxQlbfbtg3Smq7Boa56xxPCtUF+49CQOD79WmjEVakDqJm9nyyWjm9taA+9dh4b47HPSBrT84/JO6wOnl7+Q+inmBNEBH2dwYu9CV8xU9r1/Z+2BS1v9GJwrx4C4Lq8bGfZh8CSWSa8ZFm0ekJ4Ec01o5uwYL/5xcON05iHNC4BEUHfCMA8XWYrZkqHzjgjEZCXlQq51z5uDS+j2zAuQoAJIfypYbuXq1puf6TeToIpBYQFYZx5ZKUpP41XaCCMCPpGAPQ8oWSc8BXIDAGDT7UD/rwg75BIJHxeG03TXHkWroJ3O/LcJ8cGCJniY7tBLovmvH614KXivdKFlMtDiB5/5bJJf0JcyU5HGAqvFww8G64TfPZWTOPllFmAGbmu0DTNSyUS3jSfIFkfm11+8wPmNwqNy3dpSsbXeDOPUfszAx/XpYBwV3FFMwkjgr5ZK4TMMS0XeBeOnXIHh6ytj6HLLpStcq3VLR8SxLPBvEP+UkpjQOiA3JnZ5MINvRZYDJg3Zwias/5MAxFBX1v4Oy5AH1koisofq8wfdF0Hz8ZIxmYmk5FJX64P6+PZEHwpAqUGr3M6t+U8ho5SMMGah67ymLf+TAMRQV9zsERB+SvIl+ULYF/u2xWLxXxm9KBq5GpZQzgdGJt8s7DdVZRDlpAO4tngSx2yo0YiWf9bPZ5fYozhQXAEyXOmkfzvEaaHiKBvBCAWwpUgYP1QVdWpvoFDx4BUKsWk92WoquoqvABB0F5ydF5aDexi/eP85PVDIRlyDNoK7gnl75h/XOAYhiQ7hN1wOdV+Nk72GQBd5aElIuibAv4Fkw1VVjJqSk8zO6NX+z6yZEMLzrp+5bpFdiX7jBxDw7QnoS2hQXlJgO/ktN0LMh3PoUNjbFzpC4kI+maBidx7EdOUVgiZMTuSDpGqqj5OZ6AV13FFDhGB3WA775Rw1S+Vt/i/5EGKGfobpL1eT5kChiZwBqfjkZ6KK220zhUigr7m8Enm9gnzmME7NrT9QqFg27bsdIYDdV3nzWrGL/F43IfvRuJBuYd8Uk9w+p7qYiD42X3OG2Sj/CTIc6yRFiqutNE6V4gI+kbANX7Ln4in/Y4lk0mfbzVNK5fLPjsAccteiG63G5zLXIcoxk3yHYAhwb9cU7hgISheGE8TeWjgs+BTAl//GCeKMCEigr7m8BfqZKF44ZJLkCm/Vx4KQDCc5ZQw+YqAQWQeSaVSMpex6AU5gTBg6DF0g791Ywxp6gDsX3nh0acuzCSAKRS7BK+ETH7/K60Jd3UREfRNgVcUxzRWhIaGrHkt7vk3mEgkDMOQCRRW2KBB/lvITGm1WnKDciM+fXYdwJg3P8haIoMwfkAIjdCHUH4Lf9cHPzhBDI/w7RXNu7t+iAj6poC9jf67Tcn17GpmCudKJpNetIIxjsfjnU5HtuMQQuBZFi4NITQ0HdFVq0FOFh/KwsGNaLmOzNh0nE6nfb71uXa5t9egdt91RUTQNxE+yW9Tcj0PbTaVSnU6HS+PquM4snPZXw+ID0dhHwS/BJ9pKYdzeNGWf7xHWIMc04ryatB1ZuDVJf+v5MIuE15C5LAOCxFBX3P4yHHMshsQXCF3g31ut9vjdUkwuuF6hbBioWXeIh5pLi9b3K5MNMaFyHGBQ3U/JvkFh8pPu3qlh7pNGCKTPCxEBH3NMScBT8z+Hcly1wdwPUQbACHEVPnhL1APOD3kNoPQsZxT4+rBkF3ePpBtUoHsZNfNJJHRsiyUgKGlzYXeJhIJr2TOCFNFRNARZoqAc2eE0OrqqjWAnIUMPlbTNPlVNfg7VIaUp0ueN5mvQ85+Dp7E4SVNJ9ukYZGdqy0c3ICFmc3QqDsf71OEqSIi6AgzBbNhc7mcHFLCM0WxWHSda48aYADmJHM3CwJJY/g6AspihDJ34T3RDLFYTB5OXPszlNZhZjMn06wIMiKCjnA5qNfr8sbxBIB4dzBvUQrS/nzZ2SDt88Y1byOHmxXt76BwjRbv9Xo+w0mQs0c+4quCiKAjTOGpCpAWLNRwkQMJ5DbT6XQ8HpcdrHwEIU894y0Augr+eY0cXjquQ8/Ce9LDZU84u88y4AyEMoIvJ0bwx5DFhAgRxsCoXgiEEBzC7FM5cA1j3Gw2fTwMAY1iCL/j09yFw33kkya/UqFNV4/5JA4HdkU+LD8Dh4amaZHPOhREFnSEmcLVfHMcxzCMbDbrU+GFcdlI3gnhX4GLA4YbDl0DnEQ7P1wxkzECKAP2+e7du8Hb9M/jjxAcEUFHmAXYRJ6nD4iTg8/9fr9er7PAjDGS113/lU/q35prC0PXAFlSTFjy0Iqi5PN5eTfeo+KjoD0SgvQZY7yzsxPK6SKMhIigI8wCrjNuWQMkOMHhAWSVNbYS6NWUVyWU4C4OV3t5VGoWXM+ysmC1WpWPmiTURL57rtlDroh8ypeFiKAjzAKu/MXoxjXeLp/PG4YRi8W8vCKgmDq0FIBrT0biU4GRA9rLwkUJVxG695lHLBbzbwpEmnykWQVMqZ5AhKGIFgkjzBQYY2E90BWEEFcTcgZgHWNd5XslfBCuiLeFvY4drzNDNwbk0yBhgpNDvnURxkNkQUeYKdh7y4ux8S/zGOtsvNfC1Qc90v5evg7ZsyFUOOT9KmGRoGs7iURi7ELs01Pw4FEoFMZoPyqUJSMi6AiXg0ajMZLSEMZYVVWf+taCnupQObfg+ws7+LPwqLX75P2Huobb7fal2KfBA7RLpdIY7UcJjTIigo4wC7jS1kgZGVDoltUBmaW1NTTMznXnIJ10XcwM7hoeD3yvAq7+raysZLPZaXYqgjsigo4wCwxdT1NVNZ/PC8ajQHCmadoDBAmxGBU+vhHBZGa+ZjYD4KcCQ2VCw4LrlcKd9D+Q71XAdJLT01PX1Hwv6Lo+thMmAo/oJkaYBfxdwxCSUa1WhdWtMQhubKEMH1+HECLNdJfYDMB1KjCS3R1iYEwQ78e05x+WZUWLhKEgIugIswBfKtuHHcaIfmMBxQF50P8UrgKk8rIhzz7s0vjQZlVVJ5S4c43Sk3X9x048CdiNUXcer6JKtDzohYigI8wC/FSaMYjra8woUtd1VVV9tOcFAehQpD5dBUiF3BaBTZj5zIc2D3Wvu7Ie37JrlF5YpbVH9f6P2v7QapACouVBL0QEHWG+FgkZRQKn+1vcMxPecyUR15CSodVMXKOkZ4NJ7uTq6mqofYkQCBFBR5gFZHYbWhQVGFxOBw8XQYSVGYkzHzTbQe5bEOPR64oCXul4PDthikqxWAy+8/b29tgnisAjIugIs4DsH+CDyXzM5JlNfoOocwgJNWwGEMQ1HCLGi2BxnQEo08HLly/HOzCK/RAQEXSE8BGkKNSoMkmgizS5u2PoSOBzCt5pzneYuYaFxBMhWXFKK2yuXbpCS3M+nvcIEUFHCB/jTdUNw/BJQgERekJIECevf99c8/f4Hby+YiazXFiLJX3Ia5WuIR8+CB60N7Olwkwmo0wN0QqhDyKCjjALBCyUJzh5J4wQ8IowuDIAAAEgSURBVDGWg9jLXpYvxti1sBYvZu3l9Bi7nFVwlY9p2MWNRmOk/fmythEmQXQTI8wCrmavwDW2bY8anjVV00wIs5O3u7pcgJj4eDh5nymlrgQM9Famj2QyGTkrQkFE0BFmgTGY10tZ33W3sRHElPZJPpRjunliAjva36ky0igyuVkqF3tUpoBKpTLqIXLthQgRQUeYEcZL2nYtej15y6O2w5vMrofouu7qu2B2dFidDN0sDegwyWazfFjkNOBf6PbGIhLsj3A5CBKWC3b3bDTmWa98aIvnR16TnuVJgoUr0Cjs6Z/oOMtrHAnQq5GUkiKEiMjFEeFyEI/Hgyh2zniV378qNu/QkI1Z2CgXH+C3eMl7zic7j410Oh2VMVTCwP8Hq/oyuErGeiYAAAAASUVORK5CYII=","AutomaticThumbnail":true}],"Version":5,"Commit":"5bbabca73a6a56659aeedfb7129e6de35e65ba7c","Tag":"3.8.2"}