diff --git a/AI/day03/1 - Convolutional Neural Network/1. Convolutional_Neural_Network.ipynb b/AI/day03/1 - Convolutional Neural Network/1. Convolutional_Neural_Network.ipynb
new file mode 100644
index 0000000..e22c6d3
--- /dev/null
+++ b/AI/day03/1 - Convolutional Neural Network/1. Convolutional_Neural_Network.ipynb	
@@ -0,0 +1,796 @@
+{
+ "cells": [
+  {
+   "attachments": {
+    "yolo-background-2.jpeg": {
+     "image/jpeg": 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3V0aTCyJiA6TmrfaY9i12VDhGiLAE8ipAVUjhanKeFnUEAakYCKrDwrQXoJkREdY1kz4H0mMFWhbEzlYgYAFgmhb4jw4poVE9FkEvTNlDP5UzXZ0giBMhoAwwELkS6FcspqgSABI+wzNiAU6G8hdStohWFMibTEsQfIuHbpFF5+C4OvnMemAglHYQG502FAJQUZzMmrFhYVs0NC2RNUlMZdVhe0s1EKTamQhca53AB8M+6/O7LosEpiihsUGPBo4VgLiBFx2yuYFHrcujaejOgsnwPgICG6pA0QHCQsjkM4rWbchC5M9oACDtZxSO4uCODqwXcO2TpeUXq6WMinPbFm67ZQcd5dTyGrPiVCxSl1IJAFTlFmkeRZQsgcSMLcGMt0DN2NipsaouEg6L2yvkw2VjHAQDGg8BuB4GiKQFmCMFgCrgegGAVmY4RlmFBWQuwT9jje9I4xqyp4FkpgjkuqrpLMt4V4HxeQzTr6VUjeZfRLZLGBlSPNu2GV2FwNCjwpQ1jCcSkCr1VMCEzXlnUiZIDXUrcukWqIBKQEcDK2EVu/Q2trNsYnSYW0RRKa0eJ22mwiBOIrLmXSgKSyQ+j1zYiayJjlieDSq7r4GeW15eFxRtqUcmRjLiTrq6gdjP5NiUykLwAMLeBFyRZXNCnVOTV9LRnQ8CgeAOEZ1SBoBIOpGUKUKuu2Wqq0p1QzjjkjyQ8xGSEMNOzsFlaNjzC4vIjIqo9xI1exh0u+rympOC0ywl3U01EJU5VsggEWx5pIW+FxZoDst9DOHNUosXj3C5G7kQ1dHFjCyICIHmkGEOC8AwRWQKg2BkK0BqAeBSZjAwsj4KyFyJn7bCkev+cxaMiXmYXiPTCaciq83060UltMAtuNH0Xi3VjmemsPRc+/fiA9Bvze80TVd62TmDlVjx30ZNVhMJ8K2EKZcCbA+AWxI4HyR4aXEkghssVgAFVCfMPBU5aMD1U6+jHWIoYk8MCCphkbZq3PgeVam5mErUbC1K2n0uWmKQLl1iKDTK77iGc2VZuF6V9ZQakguuRMunqC5KE5tiGKhfgrgWoDjj9qTAplDkVfU1l0FQeB2QKEd0SBckMC61ysKyVknHHmIhXqI4o8qxgkkNSImYzFzk0W45JY8pKpkCNbsZ1cjRzC12USpPDl1IBIJ1ZAcjRgoUs0F5FywAcl8ChkXpH6kwLCC8UArkikQnwEwCE1QLaFqBkK2BIhoDEFeAsEAC0zFBhZHwVsLaBHb4bvq/nlB4jsj251UvMoG4OV0cPqM9EW2reaUeknt9qpWTg0fiO4NbXURarBuszyOyw26XI7DAN5+vF+P+jO1WTQKKiQZaeA6o6GQ2qgHySQbJDGAjsjslbWKqBpW4ABmlBAiNGVzExKD5+ZQBDbKqJMLbsEFihKyxkToBsLhW+pVOTmK8Ljr1+J12u6YFHsrzsNEV9LQTJEdcbldKggSUtzWUMik0eCmBagOuSbEmBllLmlbaYlwHFFhxgMCGVsCMNTSIaLVgZsV1xloJqZtWsOo6sdkblptY/EDrAsQQYOoXfOSHkwxh7Cw0NVossS1TJTP3LXdSEWHKb7C0DgCQxILuoDCvj28GISXLDZUC8UcWKK4DQDoDIFia0B0DoMgAAiRHApAAAuEAC8zFBlWhANIsBLu1w5Hr/nFV5Pqm4WXnY07HkBgZ8zPxUY9ozB2Bnaaux9PzKnXN/OvQHhTu61Ne0+3tnSc4H12zse+0c58eD496NIrtNgQVVAmZaBcCwyO+oCCoYuF9Vm5HnVYE5mhgPqglB0k4CCb2OcIghlEo8DrRTQQtm4hYRc/DJWRDxYa7NRRrMxUhcXap4faEs6FHsTOA0dH0WskSBnXEGXYACBUnNWrMrY0eCjhbQNOPvXLDOKnKK2qRLoOwLByQcHWiGE5GrYmWIRwVKSLSdYlLrF1kNBpTznhloTFGHHGWwhKmbFmVEsmF4WdYaXpKX2daLM9dMaZd1IJQvTdZ5ikAwNcgNozAMsOgkIoZmKHdZZFfAWRbAhwEgmADB0myAwAICERHAtIAAoxBBSyKB4ZsJsQRJVtMJ72LzeLjZfBH7KhOs203KxHLk8kJS6FjWks7BfzMSBrNuL1OxA6Xb2fpeeJ7XVt12v2YysbIR456NJruIgRVXAWMwCQUFAvx6iFkWR7NoyzDJmtEaYgvj0YB1Vnh0zY4sW6J0kezRDgY/KywmstfDsToAF4mkBnEpHYEK2mRZopFOFzRq3BtkSycFBdMyDSUe/qOgKZcQZdhAeFEY1esyaTUZKKFzkKMSLK5YRq3dRrVEyQcg6DUg0EtDAMUzRhAakWImiN5IcsXLcciVs8o4wwwsl5G6sedZDRbwn2BPMrj5ETNdn3CtqAl1mKDti5kRbraw6xaKbs/YOhbonoIhspmKey6cGYjaeA4goyhFirAHIvYMKTGPQU0DwWwIkTXwJwscCzFUCC0iggrKQlQE5LGskZhWzxHvYfOPPHQSHSPE+E60eJ8olpWq8k5TfHoyZGXhdePRPJj2szlePeiP03SwLQr4dGbBojoUK+mmgfIjPOrLMqHjChrMGqvr5InK1YLqlO1Ql9tizRlYoo6GFso8J8rIAwGjBZVakhWmWQFUUt490IpwZQ0RwuNb6kFKZMwDWFe5hIFkhmExZgCRFBc1NTLA0OSqhemJITLq5YFkeajSUHQUDwFJIYAGBIQamyoQUiC0Tklwyi2WmTUDdLcBTDIPETUsZWHHRLRKC12FmykrmWhvW7C3o9BS20xjknMbdNYdagqgabpMzpgRwqgXFZzx0psxpAZmTpQOBnQX2Ir4AZLWA54lQxOpa4E1SzSRHK+BJRsIbFGCPM9CUhIAqEp5kJMIle1wZ3UaNPPblSWr63ma5y+6beLKCJSrxYy02ILWieCNMhgANMZ5ZSfBPqnQdLspNbvwGBZIJG6DArYZ9fXUgsdlDz6s2sDoa4LnWh7sviuBNSnVkrDRmuV3HUu0NGPQcIw2ysURBiGSbGNrJJuuaqxnbKRCKkXSHtTFTGCsV4ClZpgZtKUiSww2wxMcirkJmCgTyB0zYoMVC6yVkLxI6BK+qaFcVwaTakm/g9EuBLkkB0AoAJM3Iz+pGkrjE3TJLXdGN0EmpkgkhwGSJlY3LsMrsxYwtTlhy0o90WTCz7gk54lttiqS0ZZYmmNXVCBtN1hWSIBmlIXKJpLLnxGnhm0miBOiK7IZIr4VMLgDckzBv03z/ooasuCcCIiHI6srBTSJYZkSDinJHVlMnrIzDu+f90unH7XXDOL6n6e5a/EPYeLznkejgkXoCEpTRxRFjg0VZQEKQXJVxQzA8lQEw16qZES4BkJAckdCPENhm91dbA41PrMS9rY8BRciwF+ai15650qsKqWrrY2r35GKk8EySyueIyRVRy8Pqw9jqii2GTNWwCIbWK3tDAImlMvgM1tcAq4lcsHInW0cjMShYgo4AIVseYQZCSA4HQQBXJpmhn6tT1L0j65A8suh1gGE4DQOEUMMuWKCVrQtVxcblx6k7UzQJFdCXLLQaYbB8XwaXYXrLSplrmLlWeDPUttcIRkyuyvSWpHtAqm5SS+HGbwX0aAERYlgNZSYRYXM3i0EAwDgcBBM7U5e3+M9x6pk3qhx/EbjHoOB5Z8xy5QO6wj+gzvRPiFB66rDfZuPH9TohW01td5Hpb3VkN91x9R5Doa7BcgMSVsK5IYQ0dRIQ5ILgMiuAMYkBLk1mklwzgHBnAWyqBEDYZnalYA/BDaNQRyAesWbMZ5EinSfCqAHFt7RwKTdFmzTKpXC7KZonZKoOVWzUIcwsVF4qb0jCQ0Waur3OJo5XmrLCib3W97CvMtVcKK2ko7srAFdFfCDMmIkBMpAaDQGiOArIpmBGRoyscibMo4sqCU0AxoAMAaiCoAIjHoWkKlnui72RjNAyrcDorpKnZCzMFHg8KVC1XRecta/XkOYmTapXPEttsJCkpliaK1AUh+u42kAhp0vZ4CAyVs5XZxl9EMkDLMfM7EsUwGAVATDgTtTl7f452eeddhdvxhl0zsG+y6+8Hn4r1Fl35TaCtrjVrdYpCysJDE62G2rPxpu3N7LDfZudidRyTW/wBLWOa36ni1dFowHE9LVpixyHZkOFdmJMGhpPAihEYGytckEyeCXJqlJPGcA3DLBcrXJK48PgMmKyBqRoNYWT0ENlW6ZzDDWQiQsAkWWBLgtZoAG4HHMbeqSV+mKuOXi3VlawVxT3SmWVDBwxZpw1iWQZXWbK6kjXCp9KDOnWlMF1bXkctMGBUC1eSuWFNC8QzYXJZUBGFosge2uWFtSw0S8jOQiyXQkTBYsGEAAiisARIioYXCz7a7pfGJ0jVTOA0L0I0zNHQKsGxTIbvfCLpp6X+x77KLRUtvKoScyR4vTUV1UtCXVVWu4zcNLqzVrImMtunPfdPTDYk7K0mf3YNhgDhDgeDpBDV5W2eRdvkXpOgPau+uZmPYNfdWNzjLJ9S2z+bdHWd9rqT1uAK2ONYtDeC2lErWZSnNh8632Pey8yC3mg9v9INZiUitXnDtJsBasi6D0qOCvzHA0NZ8EIGAHChHK6wgJgatSEpZYGlZQelaK5m7LNAsA4CDQqI1NLDoQ2R9kz2GHssyFjBELLUttOWdICzRLguKWLIK22WtjEkt05JPLNSeurW1jhgaPqZZboUE1dOdaerWql9AWahatHmJUG0Q82B4WvNE2QlatMtJVUjMcTS7yEgDEAGFkgMa6Hm5Gl0Um3qdmHSagTXyzXGh7GiPYowBynoKXKMus/KTBq1jIzMCpSaHUbxKpj0B4LMpo1zMsDKrQ0W28KMr6WqPsYszX2umBj1GFtrsPYTNrq2MwpExqplxSLomOt7eKCLqqIDauzQ9dAdJwFEFNXlbt452+ddPr7Rr75OM9O3ONZcG3Ku21F85XZXrkdmF2uPXd1hmKLsv6/UKF1Lgt5yyux6TLy/2XjqjssJggNa91mUYd8jHzBpeAztOQegeAiCCGiE9CCHCBooZituKJcI1WmSA3QPw3Q5K15ilNDoAFsZH61Tzvq1dlqCA9brUUWJohMhlUBWJtw1BWdQAnuOkTtd1SSXhGRhwSFa2KFJAuSwV4jhCJtah7kuGAUYNVla4PZK30Ktqs60+21uK9sHKwlUAfMQAsl8Vrc9JY8vY6J5FpL35JqeIemeh1I8CNi/zB9MdTPzb7YxLowz/AD/NRlqqU2D8Q3rxARiDgeBsiBMuMUT0Or5u9DrFUtAYbetYOo7q1pmd84qdM4u2TVM6uVhweFLEAHgWhfAGZjGJBXV1qJTLeLPDKsqTfHyt7UmZb2tDxYHSyBdkcVW6FM2CVJ4CyhzAztk847zit1I8HQ4wM22MT1GV6I8T2I9YVfpMM9zaG+XyEgq6rDfZeNh7DDYJpNqaaryn2TJvj1HQ5zs+JJPTEAYqDgvMWKCAQsILwJkqWHrFMj9a6fS0+J6BoZ8OMr4NSRAx6reEUyCXQ7a1dt1ZKWjysUmS6Q5aKCIZDQ8ROJGkmliVj4+mfPnK2PhdFwOxHpEkqJrfd7zIfqH1FT2emPE+rpsPlPi9G12kzCKnRr2PoiNWNpsleh+s8yL5ky7MsA4qskIhVZmf18jR/n3znTfnjg+OvWn0nlOS3NjZ83fcPuXtpmeaZer0+meT+LNJiQYar4zbv87t7Enkng6HA7AJ3sVHpFGpMa05CeDoZf2tWX9HH1J5dbrfm1/Q4x5p5XHR/Cek9BxhULxrPInLE8r+mexHmbzJ81fQS0/cQhwuIXkqEC0erMtjCXWcWXRZG039i9R9m9Y3hvDeRfNHifSemekck9BytZvJ6ohxms4Dli1XpdenIpQFT0vO3PScyQ6/0pjt++5L9enxZ6I9B0OSnoPS/ieicrXIfKPEImJqZKTpFTEYngE4aQHJVwHSWQw2NlMS+/8AR9yS9T7bxPlXzHojw/iPNPoj0t4POeQ7g4e2fJHk9m8453knYnzHJTsWVf0DdfPX1d6EVzNrBxdat7yGx2dw8n8bouBpMlitJFyV9NHE7XcI9V9p9bb5I9M+ePKvpf0LyZZwMLSPA/PTHmPF0zqKy2A1d3BFyq9I4+y88tl/Nf257RHvrezMqfi42m+S+J9WgdBWcY3L56sxz0Suz66KPuAjXIfKnbfOHnaV/SeDweg6CZjA/VqMB9Dq+pPLb7Vorqd0lJfBmtbguOum7cJZj3otVx0xTt2susXE6x5u9b6FMv7iDusAu2AuxXQOWfS+Au+M/oMrmzutDF25bF2DzgbZJi2DbV4CGJlbYJ6stf6fpL36r676T0P4T0z6I9Devt9D+mPB4PEeJ8R4PB6DxHiRHEeby+M87Z6/0kl23fcrXtz+rp9ZdxavQ/bDlKdtt8qehfS2R+T+HxcLUuIaOrEklIGVZwPCrB0ZAYa4MZb31Hd2bte4BaHmyefsR2Bqiew247F10qLSG33EzZbv0HmPSeg9VVtvyB5HW8Tl2M2B2QCssIpF/wCLsDbG/FPqn0kVrtPHvzFRTcuz9BsXk/jNV12lo01CYLQr6mNXtru0+o+xU7kuIm5eQxjUysnIjVUP2XTsnKI73pqXxnAbr5JrU8VyMLOqH7Bx7ALaz9ReJv66z40+tezI7LYsWWXje9Hovk3inUx45NaxF3D5/t+cvVK9T5szzekDbBznp2/yx+jUDs1m1lazg3StfyjUOOfDvQqPn30av6y8nvqm5bW+VjHe1VxIXmTpnn1lN6JIuQXDXnz33MfR3mVtu49qL1qUjqEbsh1zNulj6u8Qsl4bfGv0HFH2sTJja+Gb6L8Xnwcl+qvpONHXn5Z+gaYfV7s/6X7BReR4CTNo/GwCWVmtjmNhtjXR9SM1umevyWlrestYxsdb2psOpKpV2XhU4ZfbdCG4vz8lxvm0fsvRx2z2sfX6oZiYbdOIQ2m5kRdCxcAvn7Ufi4km20Zj4Ei2+4dh3+R+VeIhcHULrNSrYqs+A/DPBwVYLG8GDtEd0tnV9sa6XsG9fqKXz3L2DKzZGdnS9hu+1YXbcgns92D1HOEcvaD8DWE9hsvWZG//ACr53lW45vTOYMq7RBblpxzcfHLqp3e1+bvqDuDGx2bdl/VqKbXe2byvxar6vSZw9cdC0rZoIVTaboj6b6/Q+N4VTYUTFqN7La9vvKZ26CaTlbL03eVLmOJ3DyPVa34rzsfPrex5ayB6gVhnM275R+yvTiG63EHGwzWXmW7yzxM1j0tj13FTcfnm4Tnz1IiZKzqpcw4nYL+yFwD1tNd5KaB0UV3axO1JuflluB+o0476In0z43feOdam9BB7AAWwrsOCx/QWUDrIs+sKntlMYxYefaXhHiIu1iTitHyyRUe1520+PPoBRO5qDsn0Nw7635PdknfJdNKU/exKkLa63R+DPln36mldZuNI9M9iz3i/OptuUhMc3n7dm24ttN3My86lcjwbGJhMxSVy9i3baVz9szrNaKanqs8tD+bsrBu+kgc5yM3jfOW+09FD5ec1h4Q7Ewp2RdMy88tuOgE6TnB2NjyHuk32evzfTVZOi7DIvK/Eguv07imoUsVifAeGkB4VYLGfD5utQlMW3qezKdJ2cPG1p3cdAKw8Arl5/cjJi4uG9baOwNe1rdXTdFylgy9hIvyZu13v0V8u8Qc4znRWcSFdqwIYyzdW1X9G32KfXvsnrZ8HIPLVdvLPF4Ws0IEr4rEVtnkUTZ7Yj6b7LUOX46z9N1yEV17FWW+hG4pkX5w3V6PWvFub0rw3i/OvFbjTxl7B3KfMvbuy9n5HVEUYdh5Dz+PQrI8ek0Xy+9VCck6HA6sel/Kufdqk/HKxsQ3RJXUzaedspHpdeG+oV7F47bo/FT5DoemOMeVvSvIOkdmeJPieZS9stSsdg6k+tXzR81e611Tc00+1do5NbzwWSRzCgbiL7rlwLuo+r/FL52rPlf3+qk9RttL9P9lB6jQHN/1HoOMdJ6PynGzzh/N7Juuij11zcvLkZGUp7YOu0/LG8sTMjPcycqXlZQ3kOIVxvnEDsvRZO36AvtduvJzeIvXb0zxV6N6F89ng8J5VyTynxAHgadxJ06pjMT4DcMsOiyg4SyGDZlRtS59L2xLuvS1O6nt4z8K+xZ4OMoXR85D1+sO7zoR2JhFMnP8AXZO4/J3lFo870Hg9DdD0nAEdTm0D2zsXy3ykeUHVrf8AleFl14c4PE+g85nV+bH7f0XlUeuu5eUz07p/XXcDxHWj1caP4nw2cei9Lza2wdRqYWDpiaMoCghi2EzHAXRh37l/Pk1V5iWRMKzRODvy3uCwsaB51ZUN/MfeqWw11nxS32GvpfynpOQekq/px8lem0/RPmbS+hcFjbK4zrrLzaU3YEpim9BFWuLnyhlPVPY8a7VOVWi9aoLJyq3scYkyFce7MrI3rhil9sld2mNVHTSeRPpzxTKzvr1uGmKluoMYhaeWZcnxb9EVt9Hs9H9K9gjordl/gdrrfBM2Jzs6Br9ZP2Ww9N3hui8Dw3g9K+DyniA/E+dJ4zzgb2foFg6TslNZIl+3ZCKKG5VASIOhyY4SkERVlfmnkQXB1bixp6scSegUVpIKFcBBDYYZkB8S7dR2gqGOYGIRqyI3VdSS5zi6gLVAKdB1Fr6XtVWnmv6x6Y8k6T89+dUf1zr+NPQ8TwPQsjyzzudotP6u6TSSabbLTMlpGbShL47sw1k41tycUFuNnhmbubPzHOSd/wBRcPOtPhvooRzY1gisWOM6/s8l5fh9w82jL/T+lq+Fy5/HwBVVF6V3At7pfbsbk0Rw87OoLhcvLaxgZP09wd4/0Sn5+c0ryq6udDdoWVmR1pI+fVZV09JjGWwa1qBu7JayIvBW1KNvK9/4mcb7V7Dh7vTcHB0fQ66rbhCbsB6Wz50ofVOGjKu2nRcDbX/j6cn7HFvuJtVZ+DFzsOOsVvEytE4QyfvCzbLV5aybPxl28eK5HhOxPoPRPCPZEYJ68ozeZ9v2m1qeq0DGfuGCLbqNTZFIGfnV3qe2broVm5UiiqM1E3Gb0wxNcZx+x3EhmLlzGZJyszA5xXX9znHP8Mb18X2vZc7TuK9yfDgkpgQaSsSwhKRQEywy2ABVGhHFnSFmyKywmrM4JJHAUQ4Hzzax+ym2dR2nNBrgWBq+S107juJXG+eCBBrKA6Hs7i+RoV2pxjGay7brG+c5aP0XTaz4ly2N+p33K+6t7Tduc9y1WaIEA3T6NjGxTUPX7pVNf1KEbntvhe7wabbW/S9rx7tayKb/ALzYfNe03Ubl+RtXQ9fq3kuoxHrtOSyTZiKazUDtPQRXHeefQPA5ON+n7+j6/ktku07DSJxNwsLG62y2gK1YECTBkLAtQEswvAzfozg76R6HRm4av5haV375/wBBcIor2bjasG9DxHtW120Vue9Q1ReW3aQBGI3jhpqfczQ8fMv+i2+wcxrWNsNU31Lf7Ch5GJZOc0+Z9mhLG2unclXWtpcdx9+1TQ9vNNCdWdRstN4zG+e/Sah270kV6tC5i0oshMoseME67XCyHKM20k6ZJ27udmbMtodLV93sQ0Q3qdKhxGXn9zNo3zmhd6TfOa/ABGmsy4y2Wvva40ja8k4uyeibVzeBlna66Ju643Xd5mPN8CrEp0FM0j2PoEfkOHZqp6QXBQR0YaEN4aDzLGBEFiA3DpAqoSBQdBYvA+eL2I203Ho+0g6fU5xi6TU8sKdX6CrhuB6qedKx0nZ3fS4RjP5KnLbM2nfReT4aZ2Pdaf4XygX1PQZ3G6L77rofI+eZdMQ4eOryJlY0aS+Wx9GzXSed3XzFvdY5KJquv+HlDJPo3b52G7vbBuf40/0PXa35LqsU6zTmb30UUQy0ftPSAPG+db7wWVjXqO+AarkTN+PMlC+NmOAbsW02Q46whfTM8JEK6ATBvvPlNucb1YyGh8w9e9EUN0Jm+AbvxS0P0rHp+na3882UdRAp5RZc+E6G+iPOJA9bFQTKtPPbzR9Nh1zaW2PQ4td2OZDZJjaPKPTK87sfaOWmsPsJU7OxJWVuriTMKp75xeJj/fU+3evasS6ck0DZLnO5aDMh6naMq92UhDFEouuY/TWTsevmbPVoewHoOPren0qEGNhvBm76gBo+WsG+6kXoubH6vUaOjk3KlNdsiMuTJkVMeXC0bjkF7rHEb14PZ+i5VzfDWzGoQX2brfQKzyfDKx6ZYOydJVB1xUCoXwOg7A5A5LSwPRLgJBoHCGwpeQU26gz03YuavT1XWae3ZU2Hq/Q18Nwi6YDvWH6Xr9i1mAKjn6aZHt914Ll+ENdd3uqeF8nQvSMGZZsZnQ9HauU85+bqtipLi6ygBDVkCPqSyrxbSOf3WXdDp11sVwcqz4WXYBie7zcU7XZ1/Rcpbt90upeQaDFOm1FxyLLSLCZM87T0Opc9yP0R5wU/0nb0zTcm3cjAWxZfgl2Qdcn2SgRYOA+sNAOLGsazGGiSG88C1O66AmUobBb6D5BfnDvVM6d7rqEp/UxGd6NZJQJq2apzQW161+y1vFvC7G0VnXz8NOQzjpV97rL3saZLNcuHbENwUTaN4V2TzDcH0HxEZn3EWq6I4aBxltS3KUHbjI4yFi1uTZYpR5Z2vn+k1TEzud9xsuzE9CjqpzGooDZzO96+YT6YAaHl5GLjiqmtk21xl0FloSs2hdcW2/cnr61uMcZvrPdr6NjvNcXIoxyZN46z0Ckctw9cx6biFsQ8O3BnVwpS6IgCRAFpmxViSWgLjSg4CwfDwYjkK1dVbOm61nV6ip6rU329jPX+gtcPwYZVqTrY+h6w9ga2xYGpzhsmxdN1le5jg7FvOs2jygq3pXVTC1fP6p/jdE7VdMWzwk14ltWsDN1bFeRTarqZuME3XLuIzSXNZD+2mLSvR8seQ9EaP4/zeU9bR7MiSQ4qs7/o5F+Xr3luuyLrcOuxrxz1zQuhMgHXmAwPaZgoNoGERq3VDGKZPM3ZQhMab5y2V9tFbvg7iTvPAGL9oL1dlnoXLevhDtVHSwSWrFuYyK591eXhXYdyZ5B6UkINtP0K6z5rlxZ3RTF1KxYHqJ4HVZN8Qb0z7qXvtqxgunFWVXdLnm5BC2QMPNueJfFztaDagtTbvXO9NcaWG77WJFXBIWa4q58r9R0xDLxysk2kKuI0WF5bJtvrYmTjTkXRNTl3TQauqbfGgdBa92XoeMc3xaK6Zk16H1nf0fkuMG049jgtdLqJ9M5ZaR4XQUWnvMADkTpSC1ngFyXwTI4EiBsPnzIrXfFv6LrRet09c1mpW76J13fvcbwA8gbIQ3/X2/V61/G02ZNkWrpevjcpw2u8jvNP87cP0G7detdiIR+sgp6/Z+uy/L13RJgJW2bj50N2A5iQr3LYOY5izYZUDudeI3upnvW0Gk+ePiPagvLScHVPBxZ2bgWxDuE7eEbEnkTJmQQ2r1oLFjzaVKFmxWg5LHqL9yxWcV8ZuiZmYeo+dTkfZlbyoukGs8lNcgDQwbclE2xZHBdiP4t1ww8gBu8B4RILJSDgeBYSgmETAYmfIMAHCNDRgYBsOSpECbQQC/cPZXd2BdyrNGSV5/fOY9loycawSsaq6FhZcm+obTmMV5CAdR5S0sKg+iz0wt0bRlqeZuzKbhnMxcW6PQBdhgaJpb9C57WVneUub0V2XomAc3xzFGNPdNH63v4fJ8VEx6PA/W3gfkothHC31lcYgASQ0VByJQBoOglpcBxToYVkq+0XzousrGt09WwNSofTuw7/AE7j+Ay1karCm/7ITptcxVpQ2RZY+j7Kw8dxVu19lt4Gfm70py6rPmoXST662orjrSma+LEdiNNkxnk1OSpykJm2DD2a6LKfvtPXtjhaSydc8Go+dGFduV7KUmCqzwIido4FsG7hO5ItoNzBllcIFS+Vh2GkQOtCwUs3PFyvqai3LlfHsrGvF+NqvnFmU9oZ/lpfLIs2RFNQpaSeUjQxlg9M3DT51Y2WExnY6IFB2Z8HYOAuSQHSEh0PA4sNh6WbBuRkGQ8Hg6F74d63uxrdo5qt1B1OezI8jdS03h2eS+lbev2/1M1K9DWDuPkDddnRNdaKobmdiVrb6+w85u1YtjWQtG32FLz9exbIZ8ep5OHe9a2i8zh0vfrI26T+y9AxbmOQEU4cll0zru9f5Piu0Y6Q6TwPQcYZGUoOCGDKQcU7EoAwS6HQUHYGwEXkGCH0vVe1mopeBqmg03sfQLryHn9YZK9M93/X17TatWPpV5F1r3vbaX5/yh2iwvx2LkfXYU3GhmF7A7BAsHImODTq7ILdiNZLU6sTlySWFmP4+TUNxgR8qi/YRIsaWFy4+Pnf00qmTEwFpHQ8NtPn7YB26N5QuYJWFqlHgZJpIR2aMDMng4kFarhK2QHR56tIx2+jfObcJ7uBeTWfsR9xAC1CIPwwomwUPcddmVfd6xu2GYhYOMKBtRsHGnoeI4HCFBc1mvANJ4HWEgyDINgkLxw71rdg/eJUNdsimBmyIlVVkrFtO498VLmsgp+3xaVkLo+AxWmVUXBqWHZmMGzsDzI/RkHMLNslFoy5G7Vp2xQgY6c3VyIp0bk6wO9pVukd6/vaipGheEnNjsu8X5xIx6vB0Oh4ngcG4EgOh2F4HgUDo3Q6hGBkPBYCWHjMOj6zQNXp8RwNUSmbd1/fs8l5/Z2rYtWubnrJ2dtkJSt7+Ya3rzbRH9bYINKIfAgXCGaQpFdmmFzMVoJQjqEV460iiZMEtCVSxElwGL3tWOM2nJHGmmdIAAlg0KgFjaxwLfPfZKKygVYptjSxXghQ2Yh5pUNyITKszDSsyszohuYnqfXvnF1J7qPZURnhIvgTALAkS7A7KvF13soqEAto4DslyBqCqh1pcB0iGEYlQPrEwIhLIJYUHA8CAQF54dx+8AW7TGcPJtWHn8I4jD5m4avYRMfILYt9pxbi2wqrl9dPgTWWPX5DlqhsvEj2KWxrCVF8SxK/modwb3Gew0pmHV8wE2eBqXHRXt4kXcry7IYvvhrAoK0xfsbFnpC5FirDocBUsgPRHgTMeBbHQ4TwFRLgdISEylgTrSen63VtPrfnvA0xJ3vvYd/aeO8+AFdTdKbGROsvetm9kowMSPpbIxW3kY7AjsjNjeAAzJkhs0iQzVW0EmI6OBsLBWA5aQgYlZgTrGvdgYeR9guJbAGB8HwQEVnsHCTh3XLWMoeFvQWqVmAZHw8avI82LYEoJtqbkUo5DECtthY301wD5X2kScmFARZZYOB4DwrwIklB5YgBxjweAoEgAoeaUhII6DANB1RQLBAIafB4OgkOBbeHav7wkbmMYpyC2vz+A8j0HNxb1rc+br82ZRafwMuxEm765FiNIRMe5FscdFsIolumxquXZh2u4dAJyKpvX8xH2mrtfFlb3y1jclekgwIAIENpPKSgnuSoWUQ5B6TzN4PKqQ7JwESKDg3AWCgQL4LPU1MmKj0fYaZnbHOMHXzGa77jd2HhPMh6SKZcxix9jyhyFH0LGxMeFa0J5li+QFvLgTiWwQ0y0OIkGSM0Sh0RM6peuziksiDJGefSW0ayWFgeZjACYsEwKlh6jMteeEmp7BQmQPrFpUbVeMEkcdLU7Lu4zxGqGuiJFQekWKsiVXP0jwtmYemqjKTwKk8CQcBQvg6T4EwcDsx0EgkOEpDsnQ6HQ8Hg9B4PBwPSdDweD0CQt3ENXd5Izdrm1Vs7WbArVc1DZ/ssE1i32jVbJyuS2FlScbIcCTYpCBiGkZNMrZ4CmORKa3GafYsY9sWyuLakbJx5XS6CZn6+5cUAd7EPdKsG4lMy2A+RqDxPWhqIih5BQR7JiAwsOh2BoEuSQUSoJUE0OzHAh1zXgcvyTmXlwxWwlY6WSjXvxKw9DKBkB6lSx663TUMtI7DDTMQ9I0EtRsHmIYMzCSWgWWTlJNdfgdAW8vyFZYYgdQsAGmmM8omZ1iLlqzWRYidhFr1KtNDMRAknQIcsKTJmzMtjDLOpY8DkS28MzHJJBOjUSYpYJv09aqgUwoPEOB4lQdDwIDwdI8HAQCCUgoOB4OB0FB0Oh4EgoPAoOB5TgW/inre6Bm8jOEKdjZVtxr7LVkUbMw21fRNDt36byuLkuV2NyqZV5xpZZsWDfXMIUg0DlbNxKboaIcI90fPe2WvvfEla3cDN2noOw/mnweF8HA4HA4DUHgIQxkCcksFgTB6AUHgUHYGARI0FGBIKmVAmU4CoFS/ZXwJgTA0hWqYg1pW4Bts+kTMNwNyTgaWOky2iODLSyExZiDpB0RUKyS27qDkRIrgxSEkFEzGVBNlbOFGRDjWcavtYtkTAkQY0oJU02O2DxZkbWD3ZyYWDstIklKswD0zbWCBCgWJ0PTPgWQoOzPgSHASHAWR0EAkEEpBAdDwdDkCw7J0PBwOQeDwdBMHAunEvVt2VveRR1KTMIW0jXZOet+i69avaOUWTKLmZrr90Pq78ioZcHg6HqpSCXiM6MXUelj6vL2Ore2OBeuJKru4GbtPE9J8TwOkdDgvA9J0OB4Ew3gTM8DgOAWgMAXUkg/EvhGkCBTmEgoXweaOAslQcBsGYhisrePAOlGJgc7peeBBB8FMSAhCyQeBgHZIwOq00IARGJUDYMDSQlSJRPLJasI1sosfXZOGx7OpQ+shSslSWyRiJkrwsprS/Y9mAwP6WkXEyYcB5mUDqQsHJh4OyNh2U6HSehwjoeafB0PAgPAojoIBoGiWw4HgSHQ6ooPMLBQIBKng4R0OE+C7cS9X3YI3ZEAQRVQrIcD1URotaYSHVnjnVRUT1W8CpPAuYcknJIsOPDTmhot4Zl2LeuIKpu0GbtPPPIOKeDweDgdDzHg6HA6TwOB0OB4PEJDyTyDstKAnAbCoscDgvg40cDhPgWHgaWI+OUmmuDKQFZhnTZKIHA8DTEcPCywhg2EmRYO1sVgPSUthmWcDyE0IlglEJS8esO0PaSx5b62N2da69QiXkwE3RJAKZWWCneVZZqFS6IOHdafcWKY7IpxQeqlYdmOAmDoec8D4qw8N4I7L4PBwGg8DhHgbBsEEtAkOBwPBxToKY6Cw4HFPB4jwKJSF14l6zuwZuxoIxEEAgtXCvRESLUieI8rdcSs9DwvgUHQfCSB+SrA3Eqc1hg9EqJvvEFV3aDN2nHn0HVPBwOB4PB5jweDwdJ4HQ4HQ4HCOh1J9Bx24ClPQf/8QAORAAAQQBAwICCAYCAgICAwAAAwECBAUABhESExQVIQcQIiMxMjM0FiAkJTVBFzYmMEBCRUYnQ0T/2gAIAQEAAQUCwnxbgGchww7HCw70d9UzE7li7Fk7uY0eP8s1Mm9VDT9VlWv6X+lRNpiIku2Z+jfgV2KmVr3q4sXfHylZFM1VUfsuCvB+nJCNx7yjcAjJCT7BsUVVaq+z/wDXChaVZy7IEDWyUjoNZsle3BIYeKx6tDFkDGLWTGqKs+9rY7HsnN3lUkJUzU82TGvtO3z545yp1U88T4h+Sh8pW/lydv8AH1GX9bUfzMBP+PSF/wCNkX96F/EGXZ39M+Nl8qVorANhDFDjLqB+6yXMcOQMrlE6VYWWopMuDXv7SRSzzWUVgmsTfPL1b4ZfdVn+0yfLJ7d8UquspoCswXnb2YmR6LiiKVu7Y0FsZ1K0Q4EFXrHnTUm5A+yuicbPTxP3nWruFlzzU7tqqUjVkFZgF99JVEbIUsscZFRz0yK3mZ6jwm3GubvJspwo7JExTuRFc4ENxsBEYNsyX2qOaQyT0XiYj3Oj+dSnymbuqj2PKTyj/Qdj24/ybAE5qKPyem2WnwrPsn/MTLVPc6b+TFXyJ8H/AAOvkPptsy7vSUnF1KJvIa+W+RfmZ+ZQubhfJW5G+lE+4r/p2DtnNjCM3ZVc5xWoOQrseuX7edXB+6/uDy7McySjWWQFy3erLN9hJcF+26N2UTN2VZEY1z0XLtEbGsRdM6p5RfbHQl4udm/B11crPsosjzqpPd1/b8FER73zE3wYkfmxhYQyEEWIM4uO+Q2o+LqqMwQahd7KFGVjp33NOhFXV3vLrSgu3mSZSHkNxMa9H5RfdJtt6z/eVH85A/1+Qv8Axh/86Jd6Q67O/pvxs3pjHt7OTdmZGfNa9X25CiZHaBk2xJLVqwk0yaN246jUMyI1NUTiYGwuZLGT7p4+6t+k23mbLaTHNGV/jRHckm/JB97aXdcSwYWpkxDyKe07GP7M2Zs/Gp7yui++t57o8dPowF/R3rOVtRs2uNaMV1ios1QvKhf5TJiezJn9nJaru0RnJoPqv8schj5JCyJGiR1LFLJBWNuSKWRHiuIseuaLDzRx0rSvM6y+EiSQrpHtNng4rE/il+D/AIvb7yX8I32y47H4rf1mETLRNxVH2BU9smWv0NNr54uEd5FXbCu5YCN27iKR+eG9TI8NkbGeqL8zfy742YRMdNYuI8Tsi2+zon3EBfZs3+cZ3uQ+ZSogWNXzRcuW8q+H93/cH7WL8ZzlYtqvGyd7UVuf3Db7iCxHjWGDjqZTCrpSKuKns1vmOs3YhCGflvL6dE5PaCvJmmJO5iSuiQZEel3aILK+SyWBHo9J7ELGEKQAKM95Sg6sXUrCoCnT9yiodjpy7yKjqImrXoW104qgQ7uVmnxTDyeyNpw3VlJ8MR3qk/d1H+wQP4M3+sO/ngrxo5OOXZEfxQ8p0iVaWCV75z4s0CQjPziGrQx3lL8cjTngE5/McE/QWqRZSx1KFqEPv7zJERkYDbKLu3+XDJEyVbkQMSqROdkY7UcQxZk+ZwidVqYf5R/UJJZArbDdx2or2RR9GOWhAYg6EAnyqoUwn4fjZIrRlCdf3CVZsIeePqSdvcKmLIbExziqkFPbOwSvJZPl4UsWvXuFsM3ZEEGSSSeW5kN9DJfIJMTzng4vL8stm6RP4xcemETZ0pN2xF3i47HfD/8AqXCpln9Ko+xP85MtPoab+ZPguEkY7kTBxPb2xW+QRqVXjUatX1RV9rlnPykHIJgLqNMBLkxCZyw9MiIeI4GEA9uMeTlp6M8OBAZVkOkOKw6CP4NKR/gMlc8BkKraMyZJoeUWD5S+kmRhu7NByR4YrSOs43KxcnCP/f8AcCO58WMnQEMrDJqt20E6I5HJ5Uyb5XN2cntC1azjXGTZ0TzSmJ0nv8iXE1KytYd5SaYm+2YLHPkdVkYE3otXisis6rYmpDKUMYro0uGQrUsPak1JHsDqszDWdAdAhJstinxy5YjrPSPkZq+rfbEdhl/UVTv+SVybVshd9MO/mx+VJIX2rFjngPcqTKIqlkasXbIIyS1NPaFnwcXFc1GJ7eNcqYMmz6qz3IIreI7AZCdXJ5P25ok5nc5s2I55J9gV8qHEThk/zcVjmTpyK9qIu8ldmN8zWUtZDJL+nKpYCRx5vm++OVG51WJjyMG3ULeeCYjTSk/VMYr423lFYjivD1nHmAgobkdJNopEDCV2BhoNs4adKNYGPPsQoRunG8DzEyWzm0n0jJ5RP47HYRMk/CD9pj8X4lVUmLhfhafRp1/Qn+JFyzT9JRCaIKY9PJzPNE2xEzbAsY4k+1FV1kGzdYIi51ciO9rfHF4oaxYzIR5I5HPEXCDY11yLYcaLvGsBJFnQF84+S/rQ/vVTfHt3YiT4M3449vkMShtd8h/bY72ks042J/k9Vcv6AC7s6Iyt1MNzYLk9hfhS/Vhp7wcUThaj6iQ5Ce1C+5iN9pHEMzW0jnVgyoK4Ric3OO5WgA5pQOKozVLu2j6jkMPCENUNXzhAJPd+rp5rOjqtzX2VCbogLt4onxyQLlKok4SmfkP9eu8tTQPszL/xV3801P2CZ5Ot7MEVsqEIzq2OsElooJIZsvqNUvFUIuLyc5qbqRdk5PxE3wBlGkea4K0hBkVitek4bexb5OlIrA+06K0aPAH5rGSeMyTLOabLfuzZnKZkMCypVizpFiw+8kS5bYQa4yyIeonu8Zq3u8S1qn614m8LlOrpixZ7nj7yeNzDqEsvPZ7QcuKJrzyJeGmBjIgDTHhr0GjRpj2+7l/SaLp2UpPOoZwmzMkN8nfSMnlE+wxyYTJPwgfZLnTTOg1cVjXPziioSGI2BEwDXJuvRauKFi41OCdR2c3bfk3xWo7Axxx05cUSSirElbOScLY8wT2J7k4Z6Z4kHPFQJiA5E1AzZwhezLF1bmN9wKY8RTS2OPHmNHJLeQAM/F9M7HauqW5I1/UBR/pKq1yxntlT4Fs4ZYJtojJoSLvl3Lcy4VyrHRfN2QPsxbtEySxuXwutDkR+A/6ok5y4o1aSPKG5urVVI8nzfCT9ZGZxPHlC7fWie/H5PgM4yIxEdGlp7nsxParNwRV4i1TxSPEO15YrxlWWzjJoDsA3UqNSdp6WNAk4pap8ckfXpvu2/DfOWb5L+vA/2ms847vPR6+dy1dqCevlfWbpCoqtdWEK1LDrHlq/yRR79DzaNz1X2E6amUrGDRi75w2ymTrmpqFIatbs2dIYwLERX2c0jEA5OgCaPArs+2dxEvty7F3LFMjJ5/bMh20sR0XvJxSjgRTS3y21H2OomL43C3bO1o39c4btrFf+LTGK6N1OD5MdzCksxwQyJHNe6euFlyLDItbjQtE2ZctFlSUpLIie7mJ7pGfqJHz1v3cv4HTP/wBBEyIn6HbHYTJHwgfY/wB4h2KX1u8sgy5k4siXJJNDMd3Gf3jLJ6ECTrCybKeCbhStCNjkIx7uLHySmxscrkjQhbrXgzsA4+GLGQRYkEOdmLZl/kqYKXjJ43IjmmvQJ+oiZYJzc2vGd1tGSJGqW9KOOONz58ZUlT4bRxxV/cjpYzfEojeAjBaZ/YMY+6kI22bJa5vavxzFytXlDj+SO9rLsA2RZ30s02n60PzRmIRNRRtxSm8SQ0/WAT3sRE7fVTOMnbZQM84gmLDOPYO8oDRL7hg2PDqCMwYKwSOmwYopCTnsDPoibAvh7TdNFYAZWo22T1SyIM9M9HTW/DPLNsl/Xgf7XWfJ/wDTv/ll/gZ42kXUwHRJTYchuREsI7zraSMsaokQbSsJGaXdHOVUaqsxCu3ePdSbMRF3ykO+vcuoHcZOo3mbEjvHU+e9mu0tRoyuixffD+edLWGyXY9c0xnPC1jXyBAGFIzy2ktjWRQ3slTub9Op84V9sluJU7jVSJ3pfJJnB2mDNK+OEakNqGURkjqK/BQVXGNYzIQGDSNIFIJqASrix+UOCNGzyfSk+YtvfSPqV33Er4FxPoEyH5xP6dhEyS1USu84H9vXZseaTxc1r0pbZjmRh25XKy1dJi00sgwx5hUtGWSOlrbkM6IdTjyPI7Q8i1aGN4wQAps1HmPbGFlxLV8GoM4sR3m1GpjeKYAvvN1z2sXmuI1+cXJiI/O52zqjKvsbVqPfOA738XySYqdUbk5X+5Q10d4o69LqnGi5Zi41sEKNBSi3tmv6Y2ywEe75tRRv350QrcVxR4kp+RrpYyxJSFjMmBfmpd1rCuXo5pr7wbE5RxFGK3RyMnfVr05WCQ2hWK8zR6lIpTKnlGb+niMc4UlHiCKaJrCSGq9BvfHunkUNP9/Gjp1bUDvEIMdiwr7pxZmmiMaN4mjtExMtS9KfpwqElovlv65bt8heWra1PJPPR3/yU4pwVhL9JKXd0kw59Qjkkjal7TDXqHkyrdteh+osZr0Y1T453NVc5rhG9nipW/8AtGMjcUnWyNJNDYC4lSwb5Ybuny92wQFUlgP5tRGIKvBKLINNflevcz7Kd4xJrQcMu5TnrYeeBCrhxA9uC1hJkON3EiTXslO8HDs6ENwJrGKN07LAsciMCMOGe0aCkPNlq0iZRi6RrNvPGAXs4bE65PpH+lt76R80HykyvgX4N8wEyB9pt5PxWcsKHqZHZ0xvdwZgE/5Cz/Yr5HLDFMjpDoF9zQfZxf5yWNxLOmkBSGwiETCpjthnuZAlg7I9bnzryf69A+zzhurANTAJs7bEbijxW7Ztnwwla9qIz23h2Wmb+4X7uNWTSkcTauCGLIuoApMsNRDdDPVLR3PfSFY27VGybEcqNHmj6VAv6kC+7IIZcdXCy7F+/dFryz42xJENrZr4KBmRWIwZGNI7U4mRapJTXZxC7KZzIkqMdh0jr7rUyu6M76lX/JE+EIrETUCLyX5Yv28Q7RslER0d798J8zHPQGoTp29R52AOshbNyrYQBMLF1AzhKoeIohBtbaY34W1UU8+hhOhSWnbiSR4ksedw1ceRr8if7bW/OLz0ci/uM+H3dPMrDR3xK2QR8kb46wF7qXeQmxwkJxxOBQqz2em1URq78fb+XGk3T2Ucj1esSulPH0CjLXsmuxPPD/y0ln7dGX9eL55hxxhT5oZb5TfdNCZMiwUYo2o3LZvKaQTpDocPt/UXbbdiY53HOoxMlSVFGnTGIQnc2ONrmRgrLXE+SG1OlPYjh1jNnT09o0gEMUaYR88n0y/QX6x/jD+5k/Avkg13jn+WJZAiQ1uGbrNV+d69EF7SMb5GaqhxI40MkViGc1Ho2pjMcGKKOgI446NjjYVIw2mLUxiuEJoGZ2IVyyUcccvsmxo0BqCINDNWKNQMYjG4xMamB+OJm2OT1bYUw1YLbuJSJ0aZP3CfB8RjD09YGZGrSV0izi9aZOmlroDOAl5ETOuRuEO1ycxNzTXFTxV3H6rT2r7qDawo2uU4ed123WuWK9GukER2qzjLSjrmkw1S4T2NemaXa/txMM0WpZJGx5LFOte1R2L3IuRWtfH1QJgnr8sRv6aB9awCNwUpFVSfVDIYIWqCc6+nd+4AeVj7UnKxr2c4l+jmyqZGNikYg7LG/B8Tr5Eg9J/RXGh8uhnRw8VenGVBX9a734f9Ply3R5B9QPbXrYPfgLV8ckmeK3yiG0drqlNq57lxVV2I142Jm/t8OLmjdv8ABybYi9PIE48PD6skkSDLlyoySNlL52VkvGIBd5w/mtS9GO+T3MqUTbByS9xYzm14401SzpDX8o0RBZMmtjCqZD5EXVKfu6JtmsWpxzqK3R1XDC/JMuNCzUSlCyaNBYqqqQ/tpG2V5hqe2F1WIHlVwk94/wCQn0H/ADn+aH9xJ8mzJIUa+4c0JZRCp1M5LgWkJgob3tD8rVzku35N/Vunr2/I5EcjYwWL690z+meoPzYiepcVM3wrEVAs/UyRNQdP9+FffAmtYqnbJk3z1jkU8dqxhCWPtBVZIAIyVHUBSR3cdLjRChHzjvSUHEPKYt29H3SP8hzTsYyzVJFfYDNaA9WrU5VYBYUauNDAjoenm9GujzQK3WI+pB7MqYpzDWinHMeKYjA6kI2SVWOa2En6WOBj0LHRWiYiLYaNkq+OBw81VEGOBT+diOU1hLZ29lAI7w/UHLuqZo3wSDaO7xvwA3cQ0RMRcR2cs3xnyLEYswUV45ACt/DVyJ706q7SyFa/uV2QiZppU8Q1P/GKdWrzVF6vm1vURWPGrTMUqiajVD7X0UQnNNizTA03Pa6NTvhBT4r7NhcfZR28rFnm6+lsh1FS5XPkK1rDSUGeXYElnrozd4gm8bOy7ZgHqRtGv6LVDf3VybJq72gbYi76NPuumIsf3l+zk2cxCNUQIw4qoobAPWDUt9ucm+NZ+nit96/5H/QenvDr5xU4ltK90hxxOARGKuKxW4wW6dL2a0e2SXNCrZCOybO2yPKI8k4h2GhnMp5ay0LPlrER90XFuTpkaU80eVIKwa20tM8al5UWJpSpjvJN8lSTjV1pKbjrmXnjszPHZmQ7mUWSP1C+OJ63eojPIK+/O9/AgWRow3rwizHuHSIpmya4Ug+rIY6/ILFcF0RHNdDczLRXdeQ/9PpzI30X+efKtxHU12+sI3HxiMwfUyiI51oj1Y3vxJmppY3VnfF2bd74KWNK+r27VjGkFqGKJrGx+MckdH2Gnxccika8WrBOdP6xQ5WWRXSI5HibYcZgZFPKErJ1hCwWplws2tsxj0xGbIhiThdR3Dsq0RSQNR9RsmjY0sNw+hqDfG/CfeyIct+q5jDUN0ewK1cTN8dK7cPWG6Xx8zwU8OVpYRLmYNrSyuo9EaxUVvLS5kdP1X50rviNOnnJuIvBSEQuM3bnsvxxeOdZXYj3bVkpYJZV+zuBypRoi9QhXscCdbL+hH5T2r56mbypICdBSk9zNjkekWBxdDc3uLCe8bnpuCJ8lJ5QtUE4WLib5qf2oPHzD56OG3/jkeA/a6eghyU8u1RVgt2AdPKoHzll09HNn4SiIjNKxBqtBHci6djKn4UibrpmKqppuKmLp6OuStFwJbk0NATH6FgOz8DwUxdDwVwejIYkJomEVE0NXJljDYCQAXF1yYgzVpCPsaQ1fLhTmI8BRbK5PKq84R27ski44rdsoF95t5Oz+5LN8kj8yJsnqg+UtnqH8fW7FTfNsIVyoLyPIK1zIZnTCjiq54NPQzt7UNY0e6l1v8YHU6XI3B5lRtkvUOd7O2095YMXVjviyUxqSm5Mc5bxXO5KZu0REUtF5WoHeyirz1UNHVSxytxxytxSKjatdooZokFqOUxANsXMXvBOlUSp28WMJw7iFvKsI+7aqP0rOEYbcXZXqxH52+GrBGyVQMaztTMWNYS69EuwykbJhNzUWn5Vo+rgvAMmwr/GfC38rmT95pJfepiL6pX2wWN/GlfZGPMhyhT4bmoq3Om2WAbLSvYCV7kKbfNJ8fE9Qs/485mN3RqpisXYabYqI5RiRWvA5McNd3IjMiCfKJWVMEbnKNYlOxjj2H8par+3i++b7S3z9q9q7FCJFaok2nk6Mmsa7nZt4zA8Xx4UZ78hxO0jyqtkoq0kdcPXjOLwOPnYCQE8SArHSJMnLxN4xsVvnE+mX4U33/qe9o2BOOQz87LoD7f17+qyCniDU2dbj5ZD2ZYahJGrGyPNswSYRNsqvsyJ7EhmEZtlH5SGr5Oz+y+eGZyQ7c4LjWbZETaWxfUP58T1Ku+eWKmPVOAvryG+7qPvgfWiFkCQ5FkuSYMbtYyByFryK0KH9l8gbmlc1bILILItc8ZZ4PIL180yeqpqB5vNTNc2J9al/lER3BHyWrqMqrBR+2S1Y4T2p0K9do8d3s6oAj4rgSGYpX89Pr+miyUGO6cQsk0hUFVmYaZFY14nRRox8VrFGR7cfKksRZqzypFGxl5H4VkuEEbPBFRIaS2AHbyR5JkR52b7YxybGqxzCrpsJH19OKC/1bY4HXB2xB6qrf5KCrk0eKa8bRGZJba1b5+WlCasGiNdmmRNZZakYjKHkqOVFIqj4NGXjmyPRjF4jevUeR2/Jd+HJRoxjIUl7mdxyjVbve2PlaXP8ezbvE+OrJBkEBvthLvED02mkx2vnRWBCGxZtKjV3OOAKCxy/kVPVZfYJ5Jdfambit84nyF+FKn67Da0AhdQX4GUOhbUZ6yTrmII1RfRroRtaQQlqtWxrSVlnZgqYsHVbJckVnCJeydcQxyoGq4VjYpriCWPTarjW8jJDGpYr80wfNFA8EiUE04h08js5ZJHtlT9m75CN3yS3Kb7lnwd8E+JMKmTGZujc5pkd3v2epie16t8t7VazPxXkfU3WkPYiNF9YzERlV97FbuSH5MkfcjROprBE5Vp2tj9ZnAr2OwjWtsrELg6f08vstf04yTmb+IR8l+d48vmpmubD+pSeVoNdxf3qj+PY96JNf7l/wBpA+1iiMgrxp+Pt8X+ZaJNokLfttUI50wkyUHKieZ8yOhUSORXPV3l0mkyaJncahgdpG8Ws6xkC0NLgRb2ME0SwiS21kTtoKxWvQsbo1Hm7GNyqX3KuaxP63zf1PmhhharSESKNhRwHRKBWq16eUNs54S3YUsoE+BHDmmRm7zU38CrvPnsvV5ryGuN9nGv4uaQiO2c8iifyEx73Rojyvr4YoAJSMaynauWT18TvTOZXj+9ELy1ejnVbQ9QgmoqOeozzG8yx0d3Eca84Vmw7TSHObAK58eY96yBORVRQZyAuco+8jgtV/Vx5w3+1jguaxjHoN2+1KVGzc8MnUeeLMvNKVyE/wAe6G6PgMTh+P8ATHR/FesODb3NQVoLWvS0stOFmq5NW6AaHwaEof8AIPo5E3syMQfpEywrnwpD8UqtQs4jMC95B+29roZ3LPppghVX2q/I/JLcqPumfI74f2TCJ5S09hzc44HyePExFxPNP6TNV/S3yC7aZ3yLg+n1CG5pBVseRWyRnICXHbhCMJIb9XV6bvr+KA4tcwgWYMSJbXxONPQu2wS+5X6i+bpvu9QvKmK8eRvq038lHI5ou6emaklIWCj3ZLJyC/7Wv84cf6Wo2+54P4u+tTfbQYrXgv29OWVnnV+U4EhjRx3iOpxhgtiX5rALJManJL3It1GZ4XSDaNxaJDH0jAHyu0m97puznyyWs9rpCeWNXJ8gzHy5xjZXz3TQtXExM1Wv6Kv1CeC2PJYZpHIwCsaVSQv0soTmkK7hDm3sELIUyPKk3zeVCT2H8t/U1URUkefWRMQirnxwT1e8ZEDn4iO4UFCxhyXcmxhoCFc+U6w2fXcA97GGqrqpnOsFu58VU6ZIrVWR8VbtbONxGJ3Sa+a94dLFcSBqtVHP7l+Vw3y5ngjMmRljyKdrm6aXLBvViSEYJx7QfQbaOcxsrnld01slTkjtGiaoaaPHq62sDVw5Oh4hDVFFFpWVlMG2vKvSUaul/wBWlSC3jA0kJshtKAVvFr6SzPp2ID8XU1GCjC+ijvucubBkp5fJF82GmRMgk6wCmlAKs444cx1o6IyQYL//AFfkhMq/KaL5H/D+3/B7clJ7tc2xPJw8T1N+H9Jl3XEsBfhuUmAoZAzqxrceJMRjcAB6yKQXbqKOwiShtAVkVJK6qCkfGSCbd6TEnOysktkWep1/aKw6RUE7aKSwajltPbkwO4nrDVyur+SMouDodV2pxE4NW09qyd4jFSCqYWr6rPAk4xv04ggcgr3m2P7D2uARCVHsggShdvqJWkmK3yrPv4Tvd8Vdl3NewOn16Ei42mW1hciipJJ4qCHKZHFpkzT+r4/mVZXIB5TCttxNwVsF78sfsA1EUNjFgdxqJ4BvRkQLM6LMUA1RYoVRaWudgqiAHNcBa2lkRF6DlRrH/HE+OJjlzQOmq60p/wAFUuC0lUBcyhgsc6jhOTwKDs/S9YRz6aGQbdLVjH+FxkyVVxpgvwnV5EqosF+3qXz/AC69Yi23DHLxwNkbIc9ADEV8qsSsXLwK+Hsa971hv2jRt3dJo8rtmy+/j538fO/jZ30fO/j538bIwq2Gfv4+d/Gzv4+d9Hzv4+S6mkmkq40KIL1bZJ/kDfD/ANJH3NL9lYj98FNkmEG8EgJETpuTHheuGildkGEdk0LVRrmrnB3Jw3Y4T8lRjKNzVa9MRPMXyp6mr5b4mJj8VuTl3I8TXZArgPZB/bc8Qk4+UZ6NbxUZ3iyWNs9WwQNb4dHzwuLgYAI5ZCd0JtbGbgzOEyUV5g6fgRy1XhcLPC4eeFw88Lh54XDzwuHmoIMcNV+UUkTQ6wI0sBGPZiEM3KVOYobE6drH/VdAWNjiYqPc3O4LhF6qjI4WKiOc5jX4jUamaO+Pq3/I74euJ92nwnfYPZ/yilbtqf8APY1grIQNCVsfC+jarJn+MKpc/wAX1Of4uqc/xhVZrfS0TTmNbuvoz8qD/t39W/5NTTKmTZK+g25US5Bq4Fg0lIIQY1sbnZilBjyZBuiNOOPmCRoER+PXzjFGVP8AtjzTQ18dnZ45Ozx6Zs4TnmdH5J2vs2Vf0i0vlFMVSv8A+2x++biJgfpM+DsGvs75yxqquKuPwktkjGzRcq57Hw/+1VVW6b/hvyb+rUn8M+2jsUZGmb4jH4x5wpLsitRY+tW8IDib4hW70SuIeFHJ0bESsk/9KlY12iTMM7V2ovw3WjqtXGHq7UcyukWj9TabqbXVlpFq6auuY81fg57WI+UEeMI0iRPukyUiOgl/2So/2HJ+q7GytaSbbMSLqe/1Eem1fPn6lqNWX+owQ+t2v5/Sr5o9Nk9Gw1Hp7UOo42nYsPVlsWRqbWDKE8r0gHqo34nTxx5GiGuupk8o9TMFQQtdTpCRNfNlUUDV0+3JmoLhlDVQo2q7qNqbUkzTtI8Wq6iuLq+1Zoqnh3ciXmpNhX6mHkOJHeDRMcFrMXSFS5Q6Np45D6YrZA/wPSbLoWjXE0FQpjNH1DEtxNDYVgnsJ/4lgvs1XLoRE2f/ANtj9+xyYj0yOu4WfB2Db7PHOOMxfi/4SIrRsii62URfOXJSJHS4IZkeyGaOlsYmR7BkiMy3fIaawckiMV5W/m03/Dan1WSqlVUjUzbG21XYSbuw1jd0xrHVtmzU9ElkkXXjuOk4cMPZ1Xup1BHY9nDpX+Rpw2B1ZIGeDkoe8jTzfdQyM7e5JvOyPaSp2RLIncpYHnuhzyOkLPknlTJ5oQI3dc2uR6WQUkW+how42ekOlPa1QvSbAWJrQZq++1VrMF1RTmO8O9TTOPp+BXhJDod0yL90hUyZ518j/Yqv/YM01YB0hektIepIGhNRV9XUUtmK39JHoqb+z+q61pBppOn9Tiv8l+kSCGbW60r7az/yPBMCHJ7uL6VXbJvyX0fj40mvv0l941AVhiirfSf6TrSGWq/++aqAWVp3QFxBTT3pEe2y0rAvqsdDVqn4F0miJpvNaVBLqgpvSBEg1uuBHsq2y1/Gsac43O9G8X7bLuH3V0rMSWZjfRmjEmfnvP5ivtRRPVWpJn4OQ+tnDmeIPr5Ssmg60ycRr4/qWzj8I00UtJFgGK6PMHKQlkAb1nhQUeeKS6RPDFWPPDJUkoQieKx0dll8tP8Abx/q3ZnhhrBklD445sDdFjunEJS18UpxFf1J5T+HwQwJEkVVLI91U6TYNivJFtcs/v8AfG/GN9FvwdgfpZtiJm3m5PIr0e2A3KZNpt1/GVUoKQHteZkIQHRYggNg0KbV8mIKRJrpZCklyEiR/FiFHGshmj+KmJkeeyTGgTknM01/DaietBrmNqqrmyqqcHS+tNcagiXNlBT/APKeaoE09F4WZiw4TYbIELsmLD3nZH+jq5f2pJAdzEaQunWbgjiG4VqiCn5RTRAQ6+JWlYKKLIKRXS63+SnqDYRFiz4jFHHsgqe40F3HLbO3F1HN5IMDAJ6l8sfXbV0QSgBXwXRHq/hlXaCsEnsVauSv/I6z+fybVxbJINXErGSdP1sw466KI8aDHhN9Xo/4eO3O3hvoxYBNP16gX0oeikTErts9KzVc2ur3EFoJNtPTIILAELQlPBl3Gn4V8wWhKUcdaOH32WGhaexNHqIkWvDoGlBIFpWrDCjRRw4/qfGER+DjCD+S/iPk6hfTk5TIaxM0KOpZMnTg10RuubOdllqkFVSD1zOEAmvms05V6in2s/LzzuP/AJfKaUSOjAEtJ8Pq1CwyHMauC8c47yMflAARWzE7K3pwnMyLEIOwrwNfaWMB0kcab+op2NlybhjYhp4ULcXcYbYMbzjWXy1Lto4CNJI1D9iljIGFaR6wG2ZFHIEclTCarYkmSnOLXkJADPkRhVcYrH0gCRxKB/jWWf3+N+MJd4rfhkdfcb5vm+J8VVMRfZrEysTafcJvWxqwBYoo4xDWmjKrQDYMQWgYeCI7o8YUVLn+NqpQfD3sdIZCCHtIggsiUibV2mv4aRFFKFD09W15ptRDsmso69gkhAbJzUn8N+WLTzjRrjSVnPjf4/sXYf0d2DnVukJtfGbXzYzbXmtllNGGsYUcYMLEEdwhMCiDY1zxsI0UcQPU+Ej5mjvjzTOSZzbnUbnUbnNuc25+Es/COfhDHaR54PTsZqStNMLjtLkdIHpBzC+X5N/yXmioV1I0/pkVBkj0dQny6rRcCmsaDTsbTkfNTxxyxQ2jSt0H5UHr+Pq+H599vVv6vh67oaNktDCRs7bj6N3J4j6RI5ZGl9NXdcSg9IzmGHqG9rk07J8/RtFajYmXLuVszl4plTEfDF+aohvMOHWdEzqh4iQ67tiR4aRzy4zpGCryLJkVfMoKrYxYSFmTIySwiZ0x2Py1y7AqY7wFtYr5cZqbN/67P7/GfGD9m1PZXAN4gXfGJnHPJuct8YNEbRhQxQRkDKc1HoiIifmuU3rY9YA8UcYYRrTxlcgBtGITQs03/D/k39VrEWfBFo+Sufg4mfg4uG0hKTPwnZ5VNuYjpHibj9oi52zc7Vudq3LzSZ7Cx/CczPwlLTPwnMxdKTETNvy6P8l9UqW2Ike2BJf1m4hEXIcN05/gEjPADZ4AbBU5mGR3k/zS4GONNQEZzdWunKr5loKDIcaPT6cdIct1ZkBdUs2TPfaMsowPz6jmdjVPaySPRjunpQ12YbLTUdqjINk4jJIiFSpspaT7JbXu3XVyJttq+4BH9H+oJ96wuvLtj6HWVvYSqK5PY2NxaEBLiWRgV4m2MgUUdoA0uRcSkLqC05ejees4NmNrK5gSDBJar09Fw3tvFbyQ/o/pDyC1MSRXxdBU8V66Vq3VzW8G5qGQ8F6RnC1aN5MI9oVacb1dIExWOQqINzsVFT1RIbIbf+ux+Wv2cClTY/eAxsoDlVyNxFRU6jcWQNM7sG6Pauckzm1M6jc6rM7kSZYuR0zB/Gv+xYnsqmRk3DiIueeKm6DjcnMT2dNrtK58pEY5fEeqxCQplcmeyU3GKxbySoinn2QA0lgaYrmo5qIjU/IIjhaR8Rl54jLzxGXniMvPEZeeIy8aryp1IrUSXFGvew9gzorHDsmlZwJJj+6Evi8OOob6BJyBrGrll6q7XKkdBlXMuPYQrw0xvczgg0p1yL3D+3r2kkzZVMkYup69sSocQQTd5JUno0Op8vJhI+NsDnKfn2NQ/jNbieWaeXjL339W/nvjXeSrumr471FW2YQNPXJY52AgP1Czoah0EqrG1ZMSuvmSIgB2tlGPUX9ySpwvpBs+rW61lzJWptTGpZp/SHZhHB9I5yhH6T7F7LTV5rtCK0uaYK5dEHncHVRgum0w1kPme3gqpq3ljEFJI+oFvqKC+pn+ihvsGrpfCpRyA0qiJMsYhi3MWq/ROo1YjqiSmdnbhdZ6SlWLvR/RmpkPMJ0+/jJlg9pJ3o/6ffKuyb/mmaAk2dmz0dSo5olLYBy60lazJdZpGzhkm6Mt5Emn01Oj18eolAQ9DKc4tDa830Nw3A0dsqpp6ycxKG3z8OWWfhyzwunrZqeB3OR6G2I52nrPpvoLZuO0/a9O1lnaamK8kerTaSvxqDNFNfCUmRH84qzmYSci4pkeYae0rccm+GMMKlnhRHTmPRzt82wfnlW/eA34KmR/ptbiJm2bep3sppzfqxeSkto/Vce03QEp8hAjcLJjvZT46ld+06ZYu8GOeXLfVxSguCWVLMkIZUb1uNe+SqgUkrRE8s+BkMTbWhmrIV5XuQZrQ48W7lYeYWZgnJk8isZ1M33ylgsh1BDuFQXWopneEM86w5j4Em8/VP0ZqF06LYu/RX2/cQbIkMUOwLLXREhxXtfuyFI7WWUqkzVI3GplKpKKIgWs0QUJg6ihqaA0fSYCpgnr50OpiRm+qmOwMglxGEkzU4Ybyaz45H1S0mMvAOdHsKsw7dAnhVRhkPq+0LWEstWOs42oLBl1ZejNzEBe1QZNj4JbT8mx3w5esm8sJTTuFOIkfUHpFe1Lx6MVHN5KibK2M5TDc1htGsR+ji6cBKh1qDiFjakC1b+UgT16tSdZzWMn/iYWX9hGuIvomd7BIRUjwrPpt0OZCWtoqusBl4xCS3tbF1NaK09nbSMiS5KZpUqlzUTlK9hNxliqQ/o1A6PqO0vdQgsV1JqhiwtS2PRk6r4KXWHJ0rUc8ag1TLAJ/pHhRmQtYMt4tXaS5EV8yWmTL+eJB62eNz9YTN/xZYcfxfNcrtbyIGL6SH43XJZ6P1y1rX6utyZ49aLnjdnllqu2hth6gupYK/V1rJG7Uk/l+J7Fc0zcTLCZcTYrLUJgnyAn6pV82eToVoOBGgyXTgLWMVVqmrng490G5uKhMci5Ii9yq1KOxtILH0ocJSs28ETaFH7ePv5c0yMicc3zy38s5pj0auVs5sLK2UOSSSUhGceiTRpQOsrwm0ZhHmiJ8bKK6Qyne104A0joGQ0bNeP5EMomIG1HFaOcyc6oE6Lo24kvtmCZtK4I5vhky0WUNwZa4q7qJvUecaMXNI1PilkVeZLInR04m5HcVRN0XNLyWvcJxqO2JKbKrrhyMMexJay6tuxtB/XamzoCN7s89HZIl9eMZzFoGPAq+j4QUj3QTyHOF1wxprwRgzjmRPhlSMBpfhNI5X1lU/HVlS5W1NOJBRKzFSNGEWOc7VpTRZF7Tw7NjdNacajNHaWzTdZW17bU7SWKm2yxK41vq7LU7iCiDVdS+kIbSWx46taN6vR7epk1y8I0J/DSgnF00avkvdLqLEk4OnAvXULwtbSBG2yn0neSn6IAZ59DN6eiNLSdNKKKxIS10jrejgMcVvcG6GoA6giFQLRSHNrpCYYZ46r7eaPcNXPs1KVs8WbRzm0TCcPUdrMY2ysLFz5iynteWU5yR3vkEPHHBiS4qNxzueaTitbVgi2IRNbbJhRWskdvpkx4PRkKxsd+0uM6uPcBIQyRT5TxyMOZgnnYV4Xw798vPHZKZqCeWaLT3AlXFa3pitjsVrzsDoJRvnWZ2DtHGcd0Pj3G6c4FP4mGbTWcZa0JB1zuG/NcY064neNzrTkzvJ6Z389M8UlpniknZLl6Yl2PPGo64lpFxtrFxthBxkuGje+iZ38TPEou/iULPEYWM0/xSe1IxtPO5SXw0KawGxknRacrq8+xg2DYNSupmZeXiWMXTT95NVGFdiiQPDqzVEpJQ7p6oM6q5tLgJah9HULVEqMtVXua8QIhSytURYlcRN3CCQ+BqPJ0EyC6fUeCBzdSUcKkrZLmdLWjOhRxJ8SDHl2zZgouh5Dkh6QDFPMr6Y8ibYwxRL2C6QgIpQtgO3XQUhCni2Io5nT66wuOiPC9pxGJxdPBhSAk9HbnK2CPnfWDEgzQT2NwHIMv+kyOiOcFACzvgpniAWuW0ZjblW54+bFviNwF0Z1zqLVjosPsUkMrqyVHNoGF0DOnLk2dzbEXmbVYXFxWJHJReV36Qt/GYo+4QRU6ZXq9z4j3tiuc1YOoJNLETWs1cl+kifHl/wCVCtyy14y2xuqgDcmuFxdbquN1UeWj7HULyx3+447ppL+S1URzrb282fmz0xeS5sqZ6J92pp/zZ02rixh5oYDBWtwMvi0wj0wwt0mRlWVGiKuPeRTKvq05Ge6HF+QLvXYUjbIlhHdXGuZO8nxyRtEtyyDPtyKpFUpO26oV3bjJjrNJRyq+iMjIcVfZaxqNSOqs0MzhZ3CL4sz4xfu3/UCVR42yliWvmGk1snjJDlB8vqcm7VnyWP8AGJe9VIfKiluDBIl3kGxZOP0m4scedmJysro+3YBzsQ52QlxIQcWIHO/MuKVz80591NsliH3zShWR59o/q1UaEs+nnVjYkcc0o3aZ+5ghsJNzrH9ukSpDSxb0nSSERZEeCUcTBjSTooem3Z4Edzk02M+fhGt4ppesTB0MIWeDQWqOojvTwWM3EgwhPQybFktTLmKG1ZCgV0TO/hgigsWywSjL0qxh3ht2JFyzsWgdHvF2W+Dnoze8riIEoonCE10jniFBkaS6MDxAuaBOsjGy+MmcpH4Zk4y1Tj9XExDjjoa6gpi30dVHqKE1km8ivct1HXHWQDYPpSUrKrvIPZxUgQVQQN80T545rVyTEK8lLDUbtQsI9bahny51Rp2cG11tEFKuTWCdKL7QGDVXiNutcUe75XWKOwjhbfPWTYrvjX8cc/fEImPOBRh3UsgsQuRovsK6v5xbINRNnek3sTD9LQFVfS1Fxvpaib/5Yh470sxkZ/lxu+l1Zw7ZpMeB410b5Wlr/KXMWXIzrHBBgR3SZlgLoYeIrorIR3qyhsHZVxlFGiQycijcEnN+Irs65MtKiPcKmiStxdGl2XRpdvwZIz8GHwelpQgv0XIXF0NJXJmmDzIpxSobmv2VT/p2O5w9EovilwrktR75HZxOT52L5/3V+zUmLyFtlMvHOaYr0xHYb6u3nQfaTvvMpP5FPWz5Oeb4i5zTFdm3q0391Zor5e+I7Pjpr3sWlQxZI30RSE08AgJY7VYUzXD++sDI3NQ7oCngLYgr9Kx4eNYjarg7GgcudHjnFM2bh7GPGNKnwnx42q5kXJtu88mv1A8c11658p9shJ3jTXNmrLcyDIabOLxhYx6lPOZBhjsBXMcTYDAtsxga6wI7NB89zJweZ6o5M39fo5yO7kMrNowTteMMiO4mJ8Csa9hAOaWosa2Ep9VUbEu7rxI3dkTPEHqtVAdb5A0LJixfwVKKGwhEqs3zQu+efJxX86JVUCajk5aa3nQS/wCQ7Fck3Z7w5E2dHiowJYyc48JSls4zIzegmdDyWK3O2bnZjzsh52I8SAJcbCG3EZsgZBI6r5+o0cRsdRxFzwCLi6fjZ4BHzwGPngMdMBXsjY1m2BlFDmlCtJPsofWsHxyCzpdXACDGTw+I4kQkGAjdVMbh9TlK0VuRHE1U4akve4zxR7XeKkXG2Mh+d1Kw1gdmeJyM8TPniZ88UkZ4mbPEyZ4oTPFXo482PKZZgDGlvKvKAX9r0W9i2lq9rLQCRVYVokcX6iYnzVH8YsEK4+qYuBr+hihJiDXEaqYSM9XqBWrSrwDM8pOyZV+U1j85pnPGOTpq7OWdTEfnLNsCBTPqoPYzZb298rdlyOxX0HAZIhmNgy++kx8rNRzbjJ8v3smyWS+Ynv8AUqIuaRYJkavJ3kmcUodFfieXu+7mMViTXtmzLWEdJc9Bknvkv7pW4jk59fdhZXFj5m2NkJsIrQt7prUqwvFnNMa7ddTyVKagkLFsOOI3NvPRflkxisLMXZU/J6OMjP8AKQdrRslNwBUeTEy4bzr1G7OiTGw5D88KmOzwySmJXkRaa0Soemr2uhz9b2UYs+4JYTIvCUHRrUblhBWK/wCD6b7NpfLUnnm+V67owKyDEd0hw4nQHWR2AEbcpOkmcc6ecM4ZtnHETNs2zbNs45x2xW5xxW4o8UeK3bNs2zjmkP5G0T9zFLMPFOhSElcV7om/c74x73vzkuaiVWELYOjvDcMa8uooKKw1ZMa2aMMiTOY7OqzHWCQRtuJs0/UbnNuPO1jZr+tlckV8WzO6EaTI68Rw15VfnX6FjdK1va4xrWM9wmq/mlm1Bzv6GuUy/tu35FRc4rijRc7Ya4yOxmEqmPV1SuDryCMqqxee2c8CX3SPzlnPbOa5zXGV0VuWEVo4mmnq+SSnfOmETZ3wwS7adppHWgXjP1xxlKmn02m2xF8Qh/AxFLJ1Hx2pqro1pJcoaOHNn6PDpHUSPNpO9Kv4OuOX4PuVcTSNwrXaJuVemirhyLoa73XRF2qv0Pddu3QN5iaFumMFom1YjdH3iOj6VvFe3S9tyTTNo3DaFuZZ4+hLoMv8NWWM0xYOT8MnZlDBfBy2epDy08mr7PLfN/V6OMZ7L5R+2VuoJjUg3MiXJxuS0d2nvVRymxeS504y504KYjoA1FZxAI+YRVV6qofqadslh2NBIGZXRJ0gn4fko4MQwWKKQzC155jGaWXAUHbI+vWDGjge7IInzZFmNRC6D0RRqidPOGINy50HYoXZ0X4gXZwXOm7OObYiZHOCxFNgPhl4ZxzjnTxws6apnBc45pJP3G0T9y281nu8dP8AIxN2NcjsEuxCrunV85MFLQNrTyla9jxOrXinCUUcWLFikx9W7lJrpKI+FPGrYM7kKFY9QdWZ7vCxiXw2JutbGRbLYOUlW8zz18ds1ApBH6PCuLZXdgwdqD5VVMl0LZcn8NN2TTCYyKkGvFs5iMTOkmdHOjiizpZ084Yg0zppnTTOk3Og1cQLM6Q+Paj27ZUxwXNTp7Z7OcWpkhrXxtMJtK6fRgGT3tjGSOFv+tacU7pdvE7t4Sxa5lG9q2UjT7JBmafYNjdOtY+/CpshziVbA6sF3Fjq+aLGazt1QuurnGa8uFaut7nb8d3KNb6QrVyrr+2z/INwmN1pduR2trdrz62v2KusdQo0npDuxqzX9y9rdcXS4LW1wuN1jZPUGrrZCJrC3JZO1RMXE1NPz8S2K4mobTJsQsvJFYrGJp8/DwQ2eEyc8GlZoED4h3N2ya5CNXKhFWbjG5ZD5QVgNzsxJiRY+dGGmKyImbxExSjXN/NsR5GA8n880wVpRddM67cU7M7geJOiJi20FqF1NEZnfMtKxrOCN3Zg1K8siY2OI8h65tm2NcrHRbZ4ksbB8gXXLncExhnYrnYRM2z4Y0jm4kh64rc2/L55vmmJD3y5T2klEr3cgh5FkLuMDvdcfOyt3QCpIR4utlcbi9qIueHhIkigiMfaxiOZWxDJjBquKNB5KjikK0TeonSXAN6RJS8yJ1lNHgdVgKiODI4/auYIiShwA5oMKgsbWE0tv01Zip5kRj8cAeTek1ic3xYzfcomIn5PLNs4JnDNvXv60XExCPTOomLwX1W8hwIGmvuZFg2RAkJ7yxf1DQYvdU8WIOvjWYzEaSvmvxVcIkVh5hAdVkoMgg0fP2xk1wUQvPHnxh+Lnx2cio3qSJDWhIZ4scjmN7hVcwjnrHERFKR4SAIQTpHSIrAo4sZBohpHTNGKu8V5DkjOermze3k12pYgmPtzlzrEzk5McRd7R6uwccnFAcFcYAcJYKmaDe4lio+QzNRXwWBe2kpiOI4YRurwjnPk0nMFxQeHxY8Tqt7JmSY6MZvm+J6mS3sG1ds556OKyVAF+DbZXfgyyxmiZTlZoZuN0XBbiaSrkxum4A1FGEBvqErW4QrXYrt/Xv5gMJiEPGcz2c2bnljHomOci4vr3zniuT8+mPKxnNTxCNNUOPerYXLfB+7RPjd7rYVBerWrgF2cI7kwdu9uCtwuQogTWpXMbi1Lc8G8vCNs8LTPCmqq1rM8PFja+MmFePHSRtx85cgzZjI6jinzTkOHGl2WmSypkjTlrHwsSxHnXlDzvy4QYN0GBFDYsENts1cZZsdjZjVzrpiOVc8855vnUTFLnUzqZzzlnLOWI7Oec85ZxTNVv6dZpr7jdMkadMU0ukLILXs6bnu5Y/guHcrcbpqfKLBqDQZUusICUeK4hSRSCxsxwcNI8+p1ca5rGlJs1TOTE5y86acSD7hEhpHbzaqEJu0m/S3ZxYXlnFXObD9lGDY9IaLI6jYb+8VcNJc17ZPLI1i17I7V6qPFjCQ2ZalGSSWa52Peiqc3BO6GzNBvR0xmkrZhS6As+smi7lqpRXXE2m7crwafuR4yjuNrXSNjPht0bdsYujr1MPoe/kC/x3fYvo6vc/x3f5/ju/z/AB3fI1PR7f4D0fXfXoo0mK5Sb5yTN85Zyzmub+rfN83xV3/Pv6t/Xv8A9mmP5Cw/kMcB3aQtiDWPtijVuXSbTqAuyPwbvNj854j8FKcJVs3KiTlTBWLuTrbZEs88T81nbYstd1lux0hVxTKudTAyCMzvCpmljvJYT5p2WHiMpM8Vl54jJXPED4swq4REMvbAVXR4rs7CqcngdI9F0zVvz8Ftdn4EnuQmi7hmLpm7bngt2meGXLc7G5zsrvdI14i9ve7drdrjQW7cRlguMjSn52586Bsc6c7LBp8p5AYJ5EhXHeGYebNrpppcWLYR8b8EHHx7K5zkSuDiyh7qbdSuaxJU1XqVSOQh05G8kQSY3bi0jHY8qvxHqjE5kwcwjceu2dxwcWQ569RXIPzwUpwXd0r85PRSTzMd1uT2v4uJORwwPaF0flIUU1WyWzxc1mOG55lkKMhdlNyC6a4oHEytuplQotYW3F+trIbi64thjTXd2ji65tVxmtbgmC1RYqn4nsHDL6QL9jv8iX+f5Fvs/wAi32M9Il5jvSHe7/5Fvs/yNfYz0iX71q9R3Lo34jn5v6t83zl69/z75vm+b+rfN83zfN83zlm+cs3zfN/y6X/kLFf3BVTLc6CcKzeLIlxug57H5epvJqFVJjRquDB5pHzoYo+OdNc7Yq50XJhAKRrYHTXornRXOg7OC5xXOm7EE7OhnHb1aQXeytHbWXPOWcs5Zyzlm+b5vm+bZxTE3ZgrKUHBaosBYzWBc/FYSY2zDJQIlNj4bm4/qDchHJiEaubtxVxxds5Mzy9fL1cvy8s5Yr+OS5m7ySeDHE6iqnB/sExz1XHLyQaLzdxXH+7zuU22K0bHsUhg7OYvBTBerfhnJUVq8mpLK3HEdi751U4tRytRpMioRmIR0gz2q1BxCCzrOTIROYO4UGH26nT3IqqEfWKbJoXjQAFe6R5lKxA41icQF7lw98NDRhFG9M7ci52ZVxK4y42oO/G0RlxNPquRKJBOBGVmI317erbOObfm8/Wub+rfOWb5yzlnLN83/Jvm+cs3zlnLNKLvYWTv3AnLLiCUxHRiYiq3B2JR4WZ32QXpGsO9bjbJB43UTUw2pkE1b0BHeKQ8bZxM8RhZ4hCxbCE7O+iZ30bO+i53kfFnATH2QW4HUA47x6jCTBzEl+rR/wDJWq/uWb5yzlm+b5vnLN83zf8ANxzbGvczBXMwGC1ZLZgtWI9PFq0+CBBLj4A8dCejDRpqJ6t/Vvm+b5yzlm+cseTbJjutiN2cd3NBjc7HMcmKNqJsqYwvTVZDmvT2WFOr39drk63PEOPdx29NwkYndvcyNCabJIEYVF4u4pIUwekiL5IicBqFWBVxnq1yHTmBzJJyuC5eAa98l0kLoGFchHpIcIjEIIcbzb1vds4q5xVEpRFeAr3DVqbOgi9ruungkhFXtYvLtWbJHamIBM6CJiBbnTTOGI3bNs2zb1bZtnn+dPWv59/Vvm+b5v8A9Gkv5Cy/kFZjxJhojVw9YmGiqzI3svNujus5M6irnJc5rnLOa51Fzq51VzrLnUXN1wYylx8GSxvUXN8XKCEE0VgmDbmj/wCTtP5L/r39W/519W65zVMHPOLG6knhwWqZqi/Nvm/5CfSOxGqJeTpK+8VyjYxVc1+6qvy8d1IJET/1a3fGjTjuu+DXchG+cYTSYz2m+EhTFEivRVGpVxExj3dMqJwC9W5NcoEYR27FWO8CJHRzEaORMM8daqkacqtM0ryOK9R5FhCcOS9WY5fOS3hFF7aB9pa2sBsILctZpIg4XtykTz2zbNvWmf36tvVtm2bZt+VcZ/4+k/5Cx/kMcmOTCDTDBa7JQGMeZ2+L/wBgyuRQyX4f2TJnxyqb04CL5Zo7+TtP5LNvVt/4e2bZtmyYrEz/xAA2EQACAQIDBQYFBAMBAQEBAAAAAQIDEQQFEhATICExFBUiMEFRBjIzQFIWIzRQJEVhQiWhcf/aAAgBAwEBPwHYhFy4zEdCnL9wqw1wMNh7GIVkUvmKfT+9vssWLl+FD4ZLRjbjqxaHJxr+EWMxMeiK9TEYiom0YdXp2l9m2X/pF5aE9lhmI6FnKd4lWrVjEweLbdmVneJS5SKTuvNuX22Lf09y5fiuXNRqLlyMhvbcuYjCValfeROzYn3KGBnGprkJL0QoL1XDYsWLcVtly5qL/wBPcv5rfMxHQw2nVzMVo08ik3CZGpqhzILmUOn2q/o350mRLC4GkNIiiPntjf8Ab3LnqVVqRKjK/hHTnJHZZXN3O1kQpspcvsr/ANM/OkQIosWLbGMiR8u2249l/tVJM5e5y9y6Lo1q9jl7l0NpF0XRqQmvcuvcuvck1H1G0vUuvcuvc1LoPlw3L+XZFololoigL7FjGL+ykQIFi21oaIi4bl+Bbbly5f7WvLRAnj5Rmdvmd4TO8ZneMzvKR3hV6neFSR2+p6neMzvGYswmdvqo7fUO8Kh26oxZhUXU7wqHeFQoY6U5lN6ocdy/k6TSaTSW2X+yYixb7+5cvssW4bl+JkEQ2vYxiEXL+Tcvtv8AbYxftk+dRnZZ7veFi3rspwjKSRXoUaFK0ijh6MKW8kYmjBw3kWaSxBeK5UwkNMV7laCpy0jXMwdCNSi5exKzkUqEqztEqUnTlpkYNLWUvk/pULbIj/ZwIbWIYxC47FuG439vi/psX1SrRSw3IjgfBqZLAwnK0WPL6Sja52CFOSMZSg0rsq0abw1rksA5U/CyOW0ofOzF04UvkIvoSpuSgd3bypdkstpzlZMw+FjTjKBHAUpckzBUI061mZpBKryMH9QpfJ/QW8lkS5f+xiRYnsZcYxCe2+23Ff7Wxbbi/pjdqpObeBuTm+wakZbNPlIrUa29uuhi/C4mZStaxJ3wquyhJRoJGPo1anOBUhOPKRBXaRDmosnzg9Jgadbfap9BxUVJmBlLtFmyL/yjMZN1uRg/nKXyfbryL+Uxf2LGRIkdjGMYhf0uM+mT+odqlu90PEydPdFKpKi7oWZTMRipVGiviHVtceJlutAsXJQsd5VIoq4iVbqXs7nbpKyMLKc+bkQ3i+YxWNalZEazpy1ojipb3UVqm8lqMH85S+Ty77bbG7G8N4jWi6Fz4rFvNsL+iv5WniZEiR4XsXFcuXLl/LuX865i/pXJpud0c16GmXWxZtGjkRVuqNLLM0yNMvYtL2LO3Qs79CEpwd0SxdeasxqT6ml+xpfsKLXoYSLUyhzh5fQ1o1o1obKkmOUjXIVSQq0inPkRf9qx+UnxxIEeNcLH5ljwnhLRLI8J4S0S0S0SyLRLRLRLRLRLI0s6GN+iYDCRrdTu6DZVy2EY3sYLDKo+Y8ugjsEDsEDsEDsEDsNP2Ow0zsEDsEDsEDsEDsMDsNP2Ow0/Y7DT9hYKMGJaF5cydRo3jN6yMrmi46SHRNyjcEIaRcuG5cvtt5FvOsWLFixYt57+yjEjyFssWGtq22LbLFi3lUo7xiy6DO7YHdsDu2B3dA7ugd2wO7YHdsDu2B3dA7tgd2wO7YHdsDu2BPBpIrxUXYxn0mjK2yHzGJf7bMv5ydi+23mNjflyVx0bm4NwRhYQ0W42PaheTYvxoX9bDatrGIX2PoYX5iHQuOSj1FJS6bbl9rfI187Fy+2fOJio+Ixf02ZV0ZTfiK7/AG2Zb88j0+8ttYnbitxoXlMv9hYtxW4b+Tfjv5EFtW1jFsvwWFTbNzI3UjdSHSY424vQwvzClaI8XFMxVfldGErXV2PHQXoQxMZk8bGLtYpYpTdhFWuqXUpYlT5Ea8ddjtkL2Fi4ydjtiKWLVWWlC6GKjzMZ8jMurwp3jJkcZRTvcq46lKNkzLZeKTPT7e5fzULhaLCF5LHx3L+fYsy3BYtx2LefHatrHsRY0kYtkKZVikYZR9S0C0C0CSgVLcXoYX5htaCfzEmp4W5CDWHujDbqcPEJLXyMPUjGfjK1VOotBHoYpXKdVRlYnU/cMLGEuciGnfMwcdbdz6dfkXtExM+ZUpb5WZ3TFSvc7rh7ndUPcw2C3Zu2aGW+6v5Se1c1cXMY2uC56XHw3L8Nhc9t+F3XpsXPgsaTSQVyOljZbY+XDYtwWLcFy+y+2xYsWI7b7WNFtkSKOSHURKdyNVxO0yO0SO0yHiJMlPVxdUYX5jT4SWEbZ2e0NBCjaOlnYor5SGFjHqRoa53KeEtLVsq03MWE8Vx4WF7kowT8LKFKMp3KVHdiofua2T+UxMvEcxxuW2atJQhrJ4eSVyfJly/krn5Vixu2bpigzRL2N0bocBwNBoNBoNJpN2zdMy7K3iHpufp5KdnIeQR9z9Px9z9Pw9z9Pw9zuCPudwR9z9PxlyUj9N29T9NI/TSP02iXw6ooxNLdOxbhXPkiVKcfQ3bN2zds3bNDNDNxKbsjD5JVrR6i+G6yMbl1TC9eOktctKKWQVZx1I/Tdc/Tdcr5JOirlSGl2Ll+OxYaLFixYtwWNJYsWLFuG5YtsQpjmN7bFixbj6IwEdUhUKtuh2er7G4rexuK3sbip7HZ6nsQwVVPodnq+x2er7HZ6vsdnqex2ep7Hdv/AA7JuPTbP5TFS8RzOY7ojMpYeriOiMLga0X0K+DnKHJFfK8RKXJHduL/AAO7cX+B3di/wO7sX+B3di/wO7sX+B3bi/wO7cX+B3bi/wAB5dil/wCCrDdux6eXpSI01IwOX75kcmpJc0dzUPY7ooex3Jh2dx4f2O48P7HceH9juPDex3JhvY7iw/sdx4f2O5KHsPJaBgsJGhUZm2Kq0sS1Fnb6/wCTO31/yZ2+v+TO31/yZ3hX/Jnb6/5MynF1aldRlI0p8jkcr2GVOcWzNV+5Yftw5dTVSsoshlmHcFdHduG/FHd2G/E7uw34o7uw34o7tw34o7uw34oWXUL8okaUaa8KPS7PiRWfLisYflVRh21SikddmZ/RbK7vUey5fyLGksWNJpNI1bYixYsW4bFuK3DpNJYtxtehlEP3LEErHK9rDSXoaV7DSXoWVr2FFewtLNKLIt/wt/wt/wAMXhHW+U7tqHdtQWW1H1KmQymz9No/TZmWAeC+YtzPhxbxcxQj6I5dLGmF+hoRoRoiaImlDii0bXNCHBFSCcGzMl+84ofTy3VKdexlFRS6bHyNR1NVhO5c6luFUkpMzz+U+G2zKKkaWI1snnMNfIpY2lWi5XO9qTvYwmZRr1NDKnK5mn1h9eHK/wCSin8qOURTXoXUj5SUki6seH0L2KuNo0XoqMzvEQrT8I3svsuJlDnUTKGIhDDKTJZjQpepRxMMT8pmf8ZlX5ntWzUXZqNRdl/IlsiNmo1GouXL3L2NRqZdlxnMuzmXE9vI5bbFixYsWPUyf6wl6k60Y+pCSlHrclUVutiEk1yY6sejYqq9xJcNixZFkcjkciyPiZcoj6nwwuchzjTXM31OL5yLx+YdezsOVkOrC9mydSMFdmrw6iNZM1KfQdSOnqRqxqS5FdXptIzL+Qz08tsuz4eneVmZhiuy0t4yOcVZLUo8ijnMXTc2iWcV5eOK5FLN41KWr2KebVasvAivm0ovR6mCrzrLUxSVi5qE7lz3ZnTviWy7OZzOZdibKfJ3Rg8Nhp0NUnzML4ZTS6GUYWnV1OQoulmFoFXnAzR/v2P+8OVr/IRr0UdZTzPF4uTjTMNm9SnN06q5lTOatf6BgM3q1JONQeZYmvVcYGJx+KoRSkYGpXb8bKdSNRcjHw32OSkzOMNGjZ0xje2xYg9PNEK86uBMPgd7Q1SMlvGs4GafxmVfme1PiSLbNQpXNRrNZck9kR7LcEeRLmXW3kNF0tly225rN4ddluKXIyqWmukVpf4/h6mDjicZUfiI4utl9Z0m7jxlfFTbZg8VXUtBQlXxlZxi+g416M0mKco09TO+KJh8zo4jlFlbNKNF2ZQzGjiOUGTzajCpu2SzSlGNzD5lCvLTExOZUsPLS2YfM6FeWlMxGY0aMtDYs3op8ynUU1dHxP0iPqfDDd5Gd1p00rEsLiXT3yZ33XjDdjq13T1auZLF1Owaru5gcLVxNPeTk7lSVV1N3Vk0ipiOzUPDK5Sw+KxNPeajBY2qtdOfVGC7RjNdmYWtWoYvczZPlTuZl/IZ1834e+qjPf4jMFi6MMLpkuZLeTjOUehRhSlRs5kKNGOElpMjpx7NexmNGhvLrqZPiZVbwMbio4SjqZLOK1tUIlDN4Tp3qE85ryeqC5FLNY1KGr1Mtx3aYszv+Sy5cTGxISMvodoxGgnlVWMtMWYbLt0mmYHAPC3ZLAf5W8KkfAZov8hnpw5Y/wB9FT+MzK8XDDSlqRVvi67lTRhIwoSaqGFhSc24GUwfa56kZrupQ5lKpVjV00uhgoOFHVbmZlB1McrdTNFWp23g7cVKKc0juvVhFGBhsPOlQ3bMBgamGrSmzMovs7K9lJ7UhIsWLcD2NkWMiWJISEtlixYsWLFixbgt5MZFzUajUatszLP5CJU1uWZfiatKpLQinha2PqupJWIUKuDk1JXMFTqt6nEyvDVIYicmjFTqbxKKKrtR5GUUqdatLWY2PZ8S9yYOFWpdv/8ATC0Jwqtx/wDwwFHeYqW9RmeCUordGCxaoTkpLmZbGGKxMp1jMqVLDVIuh1KsN7iYajNcHTo4dTRl1+ypo+KOkT1Phfqz4h6IWOxG63OkeUzUd6yGIco6d0To154TToMtpVYUvEY/Uqj1xKWX1qlG7KeJxNCG6UTB4Kr4qk/UyejUpOSmjs03mGuxNJwMx/kMXl32fDr/AHTO+eGcTA5bGrT5lPLqcaTpjyajchl9OFJ0yhhVQWmHQr5XTrVNZhcBSw0m4Ge/xWYHE0OxWl1RLVXU3HoUKVKnRfjKNGnDDvR1Mjgo0XIzlXxLLFiyGkW2ZLL/ACExc+b2Xeyd9LM1f7zkPoX4Mr/kImv8fSZZgoyb3iKWBo0flRUy+jOWpxKODpUn4YlLDQpTckVsHTrfMUsJSoPkiMVCPUqZfrxG/PiSLelMWHm1ewsPNu1h4ea9Ds1T2OzVfY7NV9iFCcZJ2KWa1qaSsd81vVHfNZ35GJzOrUo6ZIk4zk7ly4uC3C0JGkaErbGriFsfLZbZcuX4LFtmk0Ghliw+W2JbbcvtlzMsf+QiVPVSMqwLoTetG7RuYMUIx6GlRvp2YjlBtGX4WdaTlTdjDZO9blVd2TyapCV6TMJlboy1t8zB5fuKsqjfUxuFnX+SRSyeSq72oytk7166LsUsme811ZXJ5XGVVVEzHYLtVNQMNQVGmoI+KOkT1Phj5pGa4aWJS0lHDQUVqQ6cbWFSppckf+dKNPuSpRl8yIwUOSHRh1saeRpVjdx1aipHwMzPw1mxPl5Ny+34e51LlSnTrwtIpQp0lZMTj7nJ8zwuXU1Go1R6Iz2L7LyMDlUMRR5lLLsPShu7DyWk3yI4Sio6Einh1Qp6YmdRbxNom7ZoZoZoZu2btmFxHZqtxZ+fqJn6iZ+oZEviCTRi5urK5Z2NJYtswtTdV0xZ/QpR0ziU89wtLmkfqKlLoiPxBTlLSQrRqR1Jm8RvEKcLXE11HOKXUzyaqVIWZRoUIwWqI8Nhr9DGV8FheqO+cFL/AMnfOC/E75wX4nfWC/E78wX4nfWX+x31l/sYvOcHUhaKK1WEp3iKZrIyNRqNRfZZnPy482bm6GrFy5fhhC5NaSIoEqlhVjeo3iI8ya2wLFixpNO1mW/XQsVRoK05HeWFXNSKeOo1JWTKmOoU5aWzvHC/kd44X8iOPoTemLJ+ONjB5fTwvQ1K5z2Oxy28jkcjkfE0eUSXhZ8LuEdcmd6YX5ZMWY4P8zvDC/mRxNKSumSzDDx5XO8sJ+Z3lhPzO8sJ+Z3lhPzO8cJ+Z3jhPzHmWE/MqZlhNL8Zj5KpJsty8vTsyJ6LmKzSrTk4oWa173ud61b9SWMmsHviWcVvRnfmI9zvzEe5kONqYmp42SjCt4ZkEqXKJqQ5WNUOi6mtWZOEauYeIWAwjV9KOw4X8Udgwq/8o7BhPxR3fhvxQ8BhrfKZjQowqcjRG9y0S0T9s/bYoU2SVNF4FokuQzLkp17SM1pxpNKx1djK6NOryZmEVTq+AWY14x0xZ3liPyO8sR+R3nibadR2mr3fvLlTM69vmI4iVecbszPGVKMUoseaYrrqK+Mq1/nItbWMsWHb0LlxEUW2oRpQ4oY5CmX2XLl9tPkyE00VIEoSZaQoSYotmhmmwihTuYmFinBsjRdieFY6FhUriwzZodN2ZVhZXHsii5fbbbpMC93V1MzTE7z5DeTaMurSp1dU2ZjXdSreDPF7ni9zA150qviZPPlTVrH6hfoihn6n1iVPiDSfqE/UY/iQ/UTP1Ez9SM/Uj9iPxE/Yl8R/8M1zB4y2kfMyGK3NQxVWarNJlOpIjUZgJXwzkytVqb58zWzWzWzWzXI1yNTNTG2/MYzI1dsx6tVZcUib/wDlj25BLTJtGMzSpRm7E88xK9ShneJnK1zNMdKhCMjvmopdTKcfLEqbZWxbjidaHnklyuUc3nN2uZtj5YeEWjvyon1O/cT7nfmJ9zE4qdV3FUkbyRvJDqyFWkQm7E6juaxTHzHEy1f5CM8+oi/iMkfjMzf7pfntXU/1ZUMN8yM49B9DETcehhqsn12saNJpLFiwkQGWLbLm8HMlIlIiy5qNXDexSmSScbkbORKyKelkaMCtBRJMTKVWxWqaigkQSsVIoqRIQIRK6Wor20EiwhvbfUbhski4pGBpa2YzBRieCBgKca9XSZhTp4erpZdF0YSmqtaxj6CoEWomAoxqmNhGDJNFpFpFy5SpahYdIdJRKjSJSEZB9CoYpfvMiRZgP4jK31X9q9mQy8TRmUv3mhyFK4+eVjW3IF42jM4p1Wiu7IwN9aM++lBE2rnw/bdVCt88mybd7mA+dHxFbdwKjWrkJs5i/wC8EuQubFyiTd2ISEMy7lXTM9trTuS9zIucrmZfVFzltUrM6ZUTKHzIzlckMlSUhUVHpw6SxpNJbZEfGxxFFj4bbGrlLw9TXDRYpQ8VyrSRFqBTxKXUq1YzJHQUxyuUqlhYhJDxCZvYm9ib+JVq6ndFWpqVhva9q5Cr2JSuN7MtmodSvVw9Rcx9g/8ARRr4LD1dcTNq9PEV95F8jeM3jMrlJ1k0Zthq9eKcUd34r1RluGr0VzRmNSWoU7Lma+CnVcSeIm+g61b1FUcuo5EWZB9GoYiN6zEhGA/htlb52+G+y32GRv8AcZmL/wAhkiJ/qxj2ZC/3GZhL/IZWhqRhYaZoz35IEupkC8EzFU5docUVMPyMHS0zR8Sp7uFhU5uRGkzds3bN2zQzQyVORTosdPwjpPURpMjSI0h0TBUrVEZxhJ1mtMSWXYj8TKMLWo9YmO8VUtaW22p8ilTrVcv0RHl+J9YioSpzV0Z1Dwo6deOxbbY0kfJsWJIsW2oexSFNlOQ61y8TXElOIxvbr0m+ZvWb1m9ZvWbxmp7UPak2aWMZHmzCRMRGy6mInNPkyUqnuLxdS7Lsw1WphpakRz+pps0d/Sl6Dz+ouSRiKzqu5fkKQpGllhbJ0+QlZjImQfRqFf6z2XMC/wDBZU6v7W+zI/qMzH+Qx8yJ/qxyGdTIuVRmY/yGN8ihzmjPvkgPmzJ8bDD3Ukb2nPF62uQp4O3yCq4NO6gZnKGMso+h2NCwiR2ZHZ4m5gbiBuIG4iyGHSHBJDpJM0xNArFjeOhLVEln9VS6H6gn+J+oay6Iq1d5PUPm7l9i8LujC5zVw9PQd/VGrNFfMHVd7GKxUsQS5+RYsWNJpFGxYatxWLbGi2yxYUbEi5cUrCmzWOUhSZqL8DQkWLFkWRY5bUPYinTuSp2GhxKUeZh7JFWcJEsGqvQ7v9zu5Hdx2AjgfcWBOw+x2JiwR2I7CzsTJYVk6MkWsdSXOJ6jIGQ8qNQxHKsx7MB/BZU6vhuX8m5fjyL6jMy/kPYj/VD6kmRZki/dZmS/fY/lMN9RGffJAUfEUIRixWVUuhzRvom9ib+I8REqYoljGdsZ2xkcYRxp2m5vbkZEdjqJFWaZL7dCRc5E4j8tkI3J8hv7eJLZCDZTp2JRRuEdmRHDJChY7P7lNRj1LRLRN0iSSNKFFErRFKLORyLI8J4GTpwZUghqx/5F8xKJEyH6UzEr917cB/BZV+Z/bWMj+ozMf5DOgj/Vj6jImRv91mZfXZJ+Ewz/AHEZ9yhAj1I1Wnc3stWo7XI7VI7QztDHiWOvIc2+HUKbI1CEyE0Mr1LDm3ssW4bl/PRFighuMSUr7NJp8mxTWlE538y5fy4kiPUoWNVjVcUhSExNE5lScr8jXVN5VIV6vqKTkJmuxiKt+hCo7inEuhyJzsb6Q6shyuTR6WFCzJK5YyBftTMS/wB2WyxgP4DKvVly/l3L7bly5fbkf1GZj/IZIif6sfUuJmScqrMyqfvsk1pMNbeIz7nCBCndm5JrTt0mk3ZuzSaSxYsWNJzI1CNY35Vlq+5QmKZKVy+y5fyV1G7L7mJIRSkOQpCkKQmJjVx0rmgVNG6IosSuVLsjFkZSIt7HG5ukbtG5Ky0lx7cg0xi7yKuV06km9R3LR/I7lo/kOMKGFcEVH4n9vkX1GZj/ACGMimf6sl1GdDJZqNS8jEZfCrU13O6KLXzIo5TRhK+pGdTjPSk+hTaXMlKKRWlfoXLmo1F2XfBfbdnPbqZfZcuXLl/sLFuG/FbhuXI8mSnf7lD2Q2XOhvLEZXExCiOBpsMQrDgh00zdCpoUUOJY0G7JQsjFrnwWKM5UV4WLFVb9TtNT8jtNT8h4utLk2dXd/b5D9RmY/wAhjbINjX/yyRYsRqSpfKLFVpepv6nudpqe5OvUqvxDr6VYddscm/tL/ZpCRJFuND/o0PZDZYZLkUZXGyMiMhjGIQ2XRdGpCaLGnbJ8jF9f6HIeU7sxeTVKtTeJofw/VfqhZBVXqjEwVHA7lvmN+K3BzRY0j5H/APTkcixYsW8+xbhtxXL8aaNSHJMuXLmrg6DfDcv96h7IysJiLFUw8rD8QiL2sRckeI8RdikxMuahzHLkYnqXL7Ll+C5f7ejUeH5xkSzWv+R3hiPzO8MR+Y8bVqK0mdHfjY/NsWLFttvKs+K5fbcuXL+Tf+kiS2qYpimVWUSJGwktty5fZpRpRoRoQmOZrLj6GK6jF9/cv/zg5bbl9ly/n3L+RcuXNRC8iNBsnSsifLbcuX2X4LcFi3Hcv/QxJcGoVQk9RSdiNRCqixCO0naDfxN/E3yN8jfI3yN/E38TfRHVRvTfo7QmV/EMXDcv59y/2dy/3dhQMNTj6k9MehOrcm78NixYsWLf18SXHqN4zeM3jN4zeM1SNUjeSN5I3kjeSNcjXI3kjeSN4zeM3jNVxi/qX96iMmiU5MbH/cxJcaLcV+G5fgsSREYvvf/EAD0RAAEDAgIHBgYCAQQCAQUAAAABAgMEEQUSBhATFSExURQgMjNBUhYiIzA0QCRCUwdQYXE1QxdEkaGx8P/aAAgBAgEBPwHW7WhESr9MguyS5USrYpn8R3If9lRf0k+2gv31EFFLiqIIXL99BeQ7X6nB1BwGU7s9xkMb6K0jh2HUPPOQMpaVjsikrvndbWgmtRfsWLFv0k/SQUX7ipctqQiH5UbxGtjuVVP8tyFMrh3If3bard63esW76CfYtrRBddy5cv8AZUaKKuqxk1XMxzEYZDIZEMgkdhRxcvqosSgjp9lIh26j9hV4hC+n2TEFVV9TaPta569y5cuKopfu2EE/eX9lCIq3LbgU91XiStzNGxWcP5D/ANtBPtoLrsWLfaUaKo5RBC5cuXGvGO7qij+41RHD3L9i5cuKvfRBE79y/wCrcv8AsoMWxdHcxrUQzJYslx6jy5f9WxbuJ9tFF++qjRRULFy/cQa4zakEQcg5Ry37qCl7ardyxYsKgpYtqsW1W+xYt9yzuhkUyKWUspxMqllERVMqmRxZSymUsI1VLKWLGVS/30EEUzGczDlHJ/s6C/fUYKKX7ly+tHCKIoij1HqKoutBBRe7YtrVBU12Lfr0caSPspBhUSsupuaE3LCbmpzc1OJhUC+humnX0Fwqnb6G54PRDcsJuWE3RT9BuFwLwsbnpuhuem6C4XTt4WN0QdDc1N0NzU3Qq8LZHHdCZLPt9y2tBHFy+q5cUt9637K/oN4CqLruXL9xqDRBqj+Q9dWXWggoveuXLiqKuqxlLFi36uHeagzykO1M2mz9ReGpeBLIrI1chTVU07lVpPVTPm2bSGqlRcjkE4pcTjxJHZWjMQfmXhyIZNq3NYR1yqq3RSoxU5jVcrSWVsKXcMka/kYiv0FUf5ir+jmMxcv+iov6yfo2LFhUMpYsWMvcQRTMMUeo/upqUUsW799Vi37OHeag1V2Qyom7Yb0ftcguIPZHmUbiUrkzWN4PlhcYZNIl+BFPJ21bnb0jlW6D8SkVPpIU0j5YrvJOCDJmtV4/EtmxGtQXEXxsVyoVNU6VzHnb5WczEalzqdHIYTI6Rl1MR/HUk8S/ZsW7ttVi2vMZvt27iili36Fu4n6KKXL6lF7qdxCNRw5Nd9SalF7ty/ev+rYtrw7zkQY36diNv81eBHHevsqGJx2Z8pDNB2fIvMoEV7HIYa1PmSxGz+WqlY1duqIYbNBE3K/mRyoqcCXi1R7bOcNV2dqPMQni2GVnMbd2QxGL+Ndpkz0dlMOajIDEPx1JODl/29Rf3UUTVcuKv2UQYg4cKKWLCCCi9+xYsWLFv2cO/IQj8KDaZubaDadqP2pNC2dLKbpiI6RsPBCOmbCnA7KiOzC0TXvzKSYZC5eBBA2BC1zsDF4qVsLGrwQltazEKWiRY2uUfEkrFYp2VuTIQx7NuUxD8dSXxL9y2u/etqt9+3fuX7ty5cvqv3L/AKFxBoopfVb7CDB6D17ttSili37fE495eBh35CKMVEREUzNy8xHt5XHPRruJ8t+Ze/qX48y6GYuhnLmYc1r+DhtPEzi0SyNshdBHJ1MzepXqiwKlybg9U+3YtrsImuxYsW/3ZdTBRfuMH8h+tBNai6r9xPtogvAzGYupdS5czGYuX15lMyly4udDnzMPT6qGJV74FSxJjEiN5lPjzleiKpiVW6NjXob2lzLxN8zm+ZzfM5vmc3xOb4nN8zm+ZzfM5vmc3zMb4nN6ydTesnUfij3tsoq5luv3LFi2q5f9C/3L6rfcuX+/Yylhgoqd+3dYPcKt+5fWovfuX137zVKuXZNzD9IpmryPiOfofEk/Q+JJ+h8Sz9D4kn6HxHUdD4jqOh8Sz9BNJJuh8Sz9D4ln6HxLN7T4lm9p8ST+0TSWf2jNIZZH2Uo5FmZmUoPMQxe10JrZBEk26ZTE1tTsRSyZi6l1LqXUupmUzKZlMyl1LqZl1qiDv+Pt3Lly+tBNdy/27Fv9rUaKoq92xbuogwk+wov2bl++nIxLySbxCEUDppMjCopnU78jziXVC6l11IXVrDdzmUnaFOJdRVUupD5qGG+UhQeYhjHNB9laU8DXSoYxwjYJ4vvqL37Fvv3+3fXYy67fctqsW799VvuKN1L9tBpJ9i4vcuXMxnQzGYzCL3Lly9kMS8kyK+TKR4DJkzPciGFYesVUvFOBjtErpEkQiwB+XM9yJ/2VuESQKgzR6RERVchVYJJAzaIt/wDoVFRbKUdDJVuysKjBHRszZ04DqGqdRoubgR6PyZcznIhPgUkce0ufD0jF+ZyFZgr6aPaXuhDwlQw7ykKDzEMSpZJrOag7Dp8vhKbD6hHp8pjiZWNQReNy/dt9lRf9qX7djL37l9d/uKNLDkLFixbvoIo5e4onfVRVL6uJxLKWURBE7qpwMST6IrnbVLkczamNqTcFIoHUmIZb8yZ6byRr+RjK1KTfT5Dsy0CbTmYmkvZU2Zhu0WldtifjIpg1S+GT5UJYWVjFlatlKViJStSQxl1QkiJEnAdmbQt2ppBM+Jrcqiv2mFKpH5xh3lIQvWndmQ365G2sJjsnQbjkjfQra/tPMV6CKJ91RfuLw71y5fu5VvY9bd5VE4iXvy+wqar9y3dTiWLEkrYrZhaqFP7HbIfcdqi9x2qH3HbYfcdth9wlZEvqc0v3F4a0S4k0a+pnb1M7eptG9TO3qXRfUR7U9RrkdyF467Ftdtd0MyGdBXoZkMyF9SKgjkUfUMj5nboPcdth9x2yH3HbIfcdqiX1NvH1HTxs5qR2kbmQ2YkZszZmXvL0MS8qw52R43SB1vnYhvh6z7ZxU4k+okWT1ItIXoyz0uTYvJVSJfkVtd2SBi25lVjjpWLCxLCrd11KHEFo35kH4+r2KxrUQZi8r4kgHS1cbUarUUxCbJSXfzMQxR1cqZk5CYu5tKtO1CLjKhh3lIIvUuNuPuLwFW3MbI1RvH7VznqUX7Ny5x9DinprymUymU+bofN0Pm6HzdDIZCholqeSi4Tl4KputvU3W3qbsb1N2N6m629TdTeomE5uDVNyKzmpuFDcKG5h2D2QqWbJ1heWtULDWqpkf0LFjKZSxYyPdyQp8MklQ3HNY0xhqMPVtlFrp/cdsn9x2+b3Hb5vcdtm9x22b3FJWVEk7W3KTB5JIGqbhmNwzE2EPiS49tltrqlVkaqhVYnO2RURTetV7zetX7zelV7zelV7xMWq0/upvarXm9TRypnn8x5IiN9dVl18E5io1fUYiGN4k+j8J8S1AuklQfEFV1PiCq6m/wCq6m/6rqb/AKrqb/qupv8Aqupv+q6nxFOTYzUSHbZvcdsm9x2yb3HbJvcdvn6nb5+pHiM7nIiqYSqup0VRBNaoW7reZXRulbZo7Aq9y32ZuCv/AMR8P1/+M+H6/wDxnw/Xf41G4BXtW+zUqqHEqqNrNmvAXR/EM19mp8P1/wDjPh+v/wAYmAV/+NRmA17V8tSGDF4flVhiq1iL/I103GVCgZ9JCyFkLi3IKeWfkhLh0/QZhVT7RmG1Kf1N3z9Dd8/Q3fUdDd9R0N21HQ3bUdDdtR0N21HQ7BP0OwzJ6Ejdmti3AUX7WYwuJKh+U3VHYTBqdTc1Obqh6G6YehuiA3RAbsi6G64jdcXQ3XF0N0QC4VAhSRpC51kNLsarabEHNieqIh8S4l/kU+JcSvbaKfEuJf5FPiXEv8inxLif+RT4lxK9topoljlZVVyRyPuNVXJxFW2pVHLdtzFPNsgvK3doWo91lIcPiy3VDsMHtOwQe07BB7UOwQe07DB7TsMHtEw+FOSDIkj5Dj/Urg1qllMjhseY2LuhslX0FiVEuqGHOtUR/wDZhy/x4/8ArXX+UpIv1V11fCFxVec4sqrYyluIiXWwrREMOxR1HyF0qmE0snT0E0um9p8Xz+1D4un9qHxbM5eLUMHxPeCKtuRwTihpUvoWMtzKZP8AktqsZVtcsK1ULF1sWubJb2NnxsbFxs3GR6c0IkVZEMLblpmoJqV1kuIqKl7iuQRyKcDgLwMyC8roULWveiOI4m5fCJE32mxj6Gxj6CxM9psWe02TPRokLF5obBnQ2DOhsY/aLDH0OzMvexjOjUGJnwBB1PgCDqN0DhY7MikejTI22RTcRuIrKLsvBwqWMATOnE2Ud+Rs2IbNqGzZ0MjOgrGJ6GRvQyJ0FaiehkToZE6Gyb0HRsVqrYr0+pZBV4W1Kn2bGUwC+3OFjghlFcKrixY4C9xTZ2uab/8AkpD5kUyrbMZXFiyt4lldxU0MlSPEWqomINRhFVtlN5N42Iq9sj8pL5fAxLzhe7h3mIReA4qWcgiW5nBS6l1F4iWTmSVcUS2U/wBRZo5UYYFhrK6TM/khLV4REqwubyMLwunlR1TJ4UKdMNrpcrG8UIMOpUfLdvIxesons2MTeJhy/wAhn/Zh87UomOFr4kGSxzeFSu8pSTzV11fGBxM3NOqFLgtLDCktWvMrcOo5MvZF4i4RhtCxGzrxKjAaJIkmjUqMIwyjbmkK/YbT+OcUE4iC6uOrRLwPF5GlPiQwnBn13zLyJ8DoEYuSTiYdo+2pvLKtmjdHKSZbRuKjA42Ubpk9CmgfUSpG0j0cpYW/XkspJge2qtlA66DtHqJqJEsnzD9G42zsizcyowKjp2OzO4jrI5WmDYcyumy3J5cKon7B7OJh+G01dVOlb4EEfhdRP2ZrRuF0vaXJl4GKVdDHE6FrOJAv1GmHr9BuvGqySmiugmkc6ILpLPYZpJOfFFSfFFULpTOo3SCV6lFIssKKph/nIR3txHPb1GyNUfI1o12YWSym1bcv9mxZCyFjHUsqC8lMAHuRnM2jFXmX4CzsQVzUbmGvRwr7COWxteNjxLwUV6W4KMma5bEiWYpXecLz+7gjLS5irm7PHnUTEnu+ZEGYmitExJ7luMxHOy6Edc+VMzUHV6tdlKeRXpcR10uZy/C4jkFVB/qabf8Ak3mD4KyePtFQvylXS4W6FWwrxKLBaaGDbVXIjwTD6lrpIiLBKJlKk0hivZM+WmNFU/ntKaJjofmKZ6or0QwuJJkdmGsyVeQdwZYxLzi91LdzDvNsI7JFcSvqJn5YiLEJWP2co7EHSL8qlLXqq5VUSumklWNpU1U8NkUpJZv7mdj0K1qOqcpp/CxqMQ0ZqY4XujXkpPo66SV0iKllMIlZLTOpHLYw3COw1G1e5CORt6hSdyOkVyFDwmapTyOTD0QgpM0OZxhXmq1SvVNkpJ5q66ryHDly1N16lfS70pGLC4goZMHnbLKvAxvDpa9zZIeRJGtPQNYppU75ERDMJmetii0emnj2juCf8lfgjqZEVFRb9CDRiVY88jkT/sl0YlYzaKqHws+PxvRCrplppFYq3NEvLeovI0nlR0iNNHVR1K+Nq8SfDqxsrnNRSFJJcJyR+JDAKWohu6UrP/GSW/8A7iYE9G1bHOMdoaqaozx3sYCx1NNspvET0Na6tzEl+1xJ/wAL/wDo0hkclavE4KtlNHKiOmqrryMSwR1bPt43JYwZI6N8lO53MpcF7NVbd7ksNmb2p7blfZ071KfzGmH22LU16SK7Yl15FvQRFFaZFGpwIU+dDC/x0MO89CVzkiKZJah62U28tO9WPU7XJUeAp5pEXZqpHtp5crVHJLC9EcNW0d1N5RENdHMtkJsQijWxDWxS8h2Ixo5WiV8drqRVjZVshLiEcS5VIa5kzsqEldHG7KpvKNBj8zcyGP8Aop1QwExeR7bZRIajJtLm8ZE+UdLNs8w+qf2K5RQzyszXHuekmVVUkmWCO+a5HBUTN2rV4FLUvajmuXiUSVE6uW5Tvkjqtm5R98pXecLz1Kv28G8Zi34xRVMMdNlcnEckj3Oc3kQticnFwlPG2FVY4wq+zsqFdHG2S7eZhlS512qVk6xQ5kI8UkkjzWIsUYrfmHYovNEGYjdl7FJW9oQ0444q6xhSpV4asDV+YdgtVTrtn8kKuJ2JUTWwGE0EtHTuSReJW3ZhPMV+ZbqaIM21e1DsEuSyFNRbJFRSio+zXVRab+RnJORiSfVE593DvOH+QYfVNp3qria9ZNmYQMZG60hAyJZLsKK3aHKqGIq11hsr0cjWlLG5jbqVzXLWcDT5j7suJK+JczTedVl4uIqySP5kUXE6iT1N4TpfjzHrcom5qhjUKake/D2IhDTqkVijpVjlVSuamzUmskilixWI/YqVSOSZSnxCopkyxvsVWIz1XCR1yHG6uKLI1wuLVSts55UVtRWea4VEaQcJGKYtt+yM7OYd2hapnaORj61W0R0fI+pu5qy8zSiZ8bGZVHyOeuZxomqLG9EF5Gkv5BR4hLRvzMH6T1MrFYqFJjU9E/5eQuk9Uj8w7HJX07oV9Rr1aqOapDpNVU7cj+JLis8tR2lFF0mqVZZR2kM6ytkXmhWVa1U20cP4OM+V2Zo3FKpqWRRKqRH7S4/FKhfU3jOj89x7lc66lP5rTD/Kbr0nRyQXKGkfXTZEE0eooURs0nzEOCJVVLo43cEPh6hc/KknEZo5Ft3MzGI4RSU8KuzfMRLZyGF/joYf56EnGJblFI6N65RYJqqZVchHE+ju1EKWGRXK5UKBkjZlcqE+d704EmbZKYdEyR6o9So+hUWiKNkkq3eRxSJKtjDoUdK7OYhSJkRWDKl7fQpbSzXkK1EglasQ9u0qW5jEoEiYitKB7ljS5pB/U9TAvUxleRtp3R5UQdh8itzFpFjy5R0MrqXLlKKOSOP5yoVVeuZpFRSui4kdRUQN2dilpHOa57+ZhcD2uVrxYF7XnF4sUrvOF5ii/Zy6sG8djFPmgyoU1C17UuNo42tVo7C4riUUbYshBFsWZEH0THvzkNK2Fy2MVulOpSTs7NZUHxvddyIRsjyWVRrGo21zDI02eY02umKuIK2amW8ak+M1VQzI9ylPis1MlmOUfjVW7+6jsTmfDsXLwGu48TQqyYo1BqqjdfDoP8KmIcZLiJ66rKWUsphvmjvIsUFK1/mIRUscPhQko4pXXchBSxxLdoymjY5VJKdjxlLG30Eb6XJKNVn2qn+o7fmYjRcMq3pfIpumstZWKLhVZyyKbqrbeWpums/xqbprOPyKUmHVcEqSZSm0oq4Y0ZkUbphVoltkp8X1af8AqUm0qqHssrFH43M511ab7n9hvuf2k+MzOYqKhJtJXuWxsndDZOvyHIreAkT+aGzf0Ehd6l8nIotJJYI8jkuV+PyVCtystYi0ofktKxFKjSWSaPIqIYljT8QsjkSxzSxolfMq+gvQ0lavabGVVEaruZs3dBqPURq2W6CRrzHIt+IiOsWc1eIsTk9BY3dBWO9RtLI5l7HY5mpyFpJnJ4Tskvq0bTyqvhEo5vaMp5I5Gq5DDvKQQQ0q/GNGXtZV8TF6Crlq8yJwMAidA2SJ3jKGhq0r0c/kN4VLjE5XyTrdSH5pURTDW5YEKBbTIL88diio9k67hGJe4sTVdmURluQjcqcBeKlQq5FKKCSS+Ugw1UdmkH4U/NmjUp8OWN2Z6kFDs3q65U0z5G2YpFh8iPzPUnw5XLmjWxDhrkfnk4jsPzS7QqqVZ2oiEMaxNsaQr4TmYBxuYjA6e2UiiRGWUa3hZTYsQVvy2Eb1FYjvEhltyNmzoZGiNRDZtvcfwYqGIcJblvUUVPt4Kxc9xzGSMspHG1iF29REQR7eR8vU+XqXRVMVW8FkKagVY7jadjmZLCYZGglFChHCkDbIaatWXFnNadnf0Ozv6HZ5Oh2eTodnf0OzydDR6p3ZW7WROQz/AFAhjWytF/1ChT0P/kOHoO/1BjT0F/1CjcnIn0rheomksNj4oh6HxRD0PiaLofEsXQp9KoYn+ETTumYyzmjNPKKP+o3/AFBpX8mqRaeUkkiMtzI5m1EaPZ6mZpmYLKzlcW3MXKicVNOsstREn/JQ4fT7FuZiDqCk9iFS2hpv6HaKKTkw29F7Db0XsEfQewR1D7T+F7T+F7SbsTm8GklJA93Bp2GHodhh6FZQwsiVyIYFTRVMz0chuql9iG6qX2IaSUsEDkyNMCw+nfTo57R2H0aO8CE9DSNjVUYhU5sy8BP+S6nFeWttzRJVbe4q34mIxbeuso3AqXLyNyUqLyJcHhSJVsYNQMqJXoqGMYUymiVyIYNhTKmFHOQXAqToMwOj6GPUNPTPjytIsHpXMvlJsHgVeCGJYdHTmGYfC+mRXIPo4M1rDcPh9o7DYV/qJhkKf1Owwp/Ux+NsDo8qFGl4kUTVpGv8NbkNQ+CTOwj0oqm/K7iJjE7KjbIfFNSJpFUJIsirzJpVkdmKfzEUoV+g0obbZDtLGJxErIkGVMb3ZUUfVRsdlVTeEHU3hB1G1cD1+VRfnaUtGkBy7vA4d3SBqLlHJlUwL5MyiV0XJx26Dqdvg6iVETuNxa6Dlc7dB1O3QdTt0HU7dB1O3wdTt8HU7fB1H1sCpzKx2d1y/D7ebVhDlS5U4k+JytFxaWw3FpUXiJVv2G1N5SZjeU3U3lN1MKq3TKrXCsY9uVwxGxpZBFT0M/UVzRy3bcnpYqrSBUeN0ew63gQ+HsN/xofD2Hf40F0ew1P/AFofD2Hf40F0ew63loYth8MMrljYgtOxU8tB1HG7+if/AGEoGJ/RCWhY/wDoJhzfaLQwo7i0TDYXN8Juqn9huqn9o3DKX2iYVS+0psGpHPS7EMQwSkjS2RB2E03tMNwWjk/oaSU0VHUsbE2xS1s7YWo1x2+o6nb6jqMr5s17iVT+z7QlxGVU5mkU7pZ4lXqOqZIoGoijayfmriSZ8/iLZC5cSwily5cRVQupdSsS8SmjzEbLJYTVpb4m2MDfehQkc5X8CXNsluUGFsrXu4nwzS2+YqcApo48xQ4LBOmZBNGKT/k+F6Y+GaVF4FHhUdIi5ROBWNTtzRnhHJZSeT5FNHXNa+Qx57XUqmAOa2lQc5g2RruRpI/5orkEvytsVLlRboYu9VRFUo3N7MiNHOyuzKR16CVeYWoH1RjlSkzo2lJxYltVzSdf4yqhs3ryQyPT0Mjk9BWqZV9RrVUiarHIqlLjNPHEiKpRY/SpJe5XaT06+FRNIY1TxFFpDC2W7nFbpDC+W7XG/Yfcb+h9xR6R08cllcS6Z08KWuJpvC/1ItM6dw7Tema7Lc+NafqfHNOfHFOJpvTqfGtOO01p2+omm9Op8awHxrT9SrxDt7GvYLxMIukbyokfn4KLK/qbV/Uo+NPmUkkftV4m0f1No/qbR/U2j+ptX9Tav6m0f1Ns7qZrl/uIYVzUxDzVEYNi4iN/gC89eEfK9VJ8RcyRUG1r3IJXSZrFfVuiS6CYrIpQVbpmLcnqVZj2ZCPEZFaMxF6vRDEKt0ScBMVkU3rMb1mJ37dbqLE0SFokDDZRmxjJIkzkcSZTIg6xyGqULryIYtzQVOBhKGl6fzGFMn001s5ifgjzHPyIyo8lmpiD01oJ365M0K2U0djVJpBLi3NKo1crTR9qJRNubFMxUxokSmj/AJjzJ8pXN/jqYOn017tivdlrWEXFpKTxOVi2MEa5JHmNXWmUwfM2mQyvenMpolavFTSRPmiIW/I0mjzGMxWjQo3qkJI5VQictyJw95K9TFF+oww9300143lSCzikoKWSFFyi4TS+0XBaZf6m4aXobhpeg3AKXoLgNJ0FwGny8ijwKDNyMV0egTwoR4Ay3IwvRprqlEchiuj8UdSqIhuKPobhi6FHo/A+bkYro9C3khuGNphmjkMnMqcBhbNyN0QX5G5Kfobkp+huSn6G5qfoPwmBfQbhNOnoJg0RidCynXgUCr2dBFMK8t5P4yxlKP8AFUk8aly/6aCIYVzUrW3lUTgMS4vChHcy5cwlUupVp9VSDw8TgjzFbI1LjWpcwxE2blKjjjKkTUSMZbaIYqiZUMqIpdS6lhNVxERRzbIO+Z5Gny6nNH8Bi3MOf9VEMWddULcDCeBpd+YwpVvGmtvUT8DMScjHF/kRFR5LBOI11hz760EXXcvrqW3hVCnfW0Ez8rb3N6Yn/h//AAouJ4n/AIjGZ6p6sSRpgkWSka1wvBxWL9NTR7zHiL8piDkSBTBlvGvd5cTFJEbVNkX0IcVpUbxeS4jTP5PQnxNjWrZxg8js7l6mLSOdArEKTEezxbNUN/IicEIse48TEq9mIvjbEi8CFU2aOMtzHkTZWKWP6I6mdYSlcgkL0Ejeo6mcpi1O9JGcCjjcxiXETVj7/pWUwuywIXM2q5dBVF5Ec2xddRK2mqLXQtS5eCDJYIVzIVzmTvVyKbNOpk/5KC6S3MRgklS6ILQyL/UoKWSHm0rU+pcdzuXLlziKWLepj3BLmHOXs6CLexhXlvJ/ML6qNf4ykjfnUsW7mUt3b/ZQQwtOKlYn1FFIlH/gj+evCvEpWeYoyWzRr8z0MX8DBviMO8pUJmOXHVafMjSNq50MW4MaZ25hZGm0abVptmm3abdo2VCWZLEb7vEeiNFnQfVIOqkcNqLGEvvOYhTyyJ8qC0c3Qw+CSLmhpan8phTJZutGN5IQse+hyoOpZ1bxaaRRLHURXQnVFgaXLl/to5ETifTv4TKhlQ0gkTaRtsUXlIKvzFV5amj/AI3jnWQr1vAYL5Xdc9VSylVhDatbqJoxD7j4Yg6i6Mx9SkwZKXkpJQJLzFwZnQ3PH7RmERovhIqGmangI8jeGUXghj6rkQonM2ScTNFl5mePqZ4+pniT1M8a+ppHZViyL6kXBE16QeWhhP46a14F01qvAqpbFHNKryJ7svM2lyzVFYKwZUOhddBMakVtrC4q4TGnpwJ5M6juRlLGZNamfgY7xjMN/HQZzMK8t5N5hYsUqfxiXxL3U71i32UEML5qVfmKKRjlvQjuKljKYUlnKVfGRSy5SHzEMY8DBOClHWxwNVXj6uFMc268j4goLeEXSKg9GmK45HUtRIxa92a6Kdvf1O3PO2PO0yHaHnaHiVTkH1blIZ3I64tQ56cBVeSZxnDmZ2mHzqybOhvZ6tExheg/GZFT5UNJ356iNxSr9NNdkRboU+JrBHkN9vVLKhpPXLLPGtjb54mpquX7lzOiGdDMZi5cVTMX1aRX7RGpSuXZIKnG5UpeJTCKuKle7Oo7E6VU8RVYjTOiyo4wZ12ZUE1XLkj1XkQp1FagjUMiGRpl6FjKoiW7mJ0TqtmVpDgjo2WzqPwWRUskim5qj/IbmqP8huao/wAgzCJU5yG42ucjnO5DflSyarGkK2YhhX4yFtUz8o2W5nQzISLwKhMylOjmLc7fkQ3qhvU3mbxN4WN5uQ3ih25qnbkuLXtVDeCHb0GVrVUjma71E4jkPAuVTG/LQw1f46DOZhXlvJvML6qVP4ykqfMvdRP0EEMLX5lKvzFFGqf/AEB6li5hS/MpWOtIpf5SFPqIYx4WD3WuVVTK3g0e+R1aJFKbCQ7NK47HIdjeJRuG0glKh2U7KLTC0o2msNjsOZYc0c2wyFzynp1jUbe2vSHzoykT6Kd7SDzYyPwoevduXHKoiqXL6nOM5tRjhDSNfrxlKv0UOY5udMo7RuNVufDMLubj4cp0KKgZSeHWziTPylPd68REy/fymUymXu6ReBDCvxk1PfYllVw16obZTtCjqhVHSXGPzciWnkdyOzPOzPOzvQ2bkFuLca1zhzHoWUupxUyPUbTvGJK0hcpa5Mn1DHPAhhrf46DeZhXlvJ/M1IUv4ykviXXYt+jyEehha/MpVr9RRVuIon4B668J8Slf5qieEg8aGMeBhImZR9MisupHC3eeRTsbLHZWCwMQWNplYbNDKhYvqREUyNFaKg9bitUVq3KSNLcSyCa9IktKxSkX6TU72kC/UjI/Ch6l+8rbiM1qORTLc2LlGssZrGkTrzxlL5KCcxF43Gu6iogorUUtqRbJcmkzushCzKc9V9dy/wCjpF4EMK/GTVPcyGQsK0VCxTNaJGlhWtQ+QejR7BzBY1UpYuo+FthzFFY4iiUihQSNqGzYRtRBSVLuuY75aKYb81MgicTCktG4m4yLrpONMpJxevdtrsWLFjKWLFi2uxYVREMK8SlZ5i60/AE8WqxhbbOUrV+oojvlIHfOhjT/AJGktTlcolfwsolSxMSzryH4vAn9je0K/wBjekPuN5Q+4TE4epvOH3G8oOpvKDqbyg6iYnB7hcSpvcbzp+pvSHqbyg6jsQpuo7EafqbwgvzIsUp2J4jetPbmb5hub8gN+QGM1yVUzEYUz3bBlu6qGkPmRkPhQXn9tRUMpYsONIPPjKVPooWLd+ZVRvAp41e7iIli/wCvpD4EMJ/GTVMgjRWitHIoqFiKTIMq0NojiV6obW4+SwkyDHsUarG8hZUHbMcrS9hJnINmdca/gdoRCOTOOaY/wiQwn8ZD1MKWOytVR+HxOVXXN2s9xu1nuGMbDTqhN8rr/dsWLFixYsW1IYV4lKzzFLiCL/APUTVhciNcuYlomPdmubvZa1xlCxrr3MZcx7ERPQmRHO4GyVVG4dGq5l5i4XCvoMwqnTmhuqDobqg6G64OhuyDobth9puuH2m64OhuqDoJhlP6tN2U3tN1U/Q3ZTp/UXDKfoLhVN0NzU/QXB4PRBMIgtYTAob3NxU5uGnG4JAjsyjfkblb3eZpC3541IPAh69+5cv3ri8TSBv14yl4QIW7lixYsZOHEjYjFF7ly/6ekXgQwr8ZC5IlxEFQsJDckjVpYkRfQzuaQ1CpzHy5xq2JFvqa5RsiiyCyKK8Y4RzUQWSwtWo2ZXKUa8BeVzSHy0Qwr8ZD1I5FjW6HapLWudok6naJOotVKrctxzsyce/Yt9/Ck+ZStX6i6mmX+CepcuJIrOR2iVfU7RL1O0y9SaZ0vMfGJEJGZe5YsW768TKZddxFE+w3kaRc4/8Asp/Ah/YuXLl9d9SCd2xY0ittYynTNFf/AGPSLwIYV+Mgg/WijE4FQ0sPaOaJwEUuOUsI0RqisUVjhWOLqhtVLqpZSNnEo04H9TSDwoYV+Mh699PtXL/bwl3zcSow1XuzXQ3RL1EwmXqVDUgpdkq8R3PVfVdTMpnUecddi2u5fu2LClzMX12LmYRxmLl+400ivdi9CHFYGMRFUTF6dVvc3tT+43xT+4TGKdfUXF4E/sLjVOnqJjNOvqbyp/cbxp/cbyp/cbzp/cbzp/cbyp/cbzpvcbzp/cbyg9w7Fadv9jF6xtXUMRhR/jov2bFixYsWLFixbv2LFi3duXNIfAhhP4yanJcchmsIRFQ05DhyCoJwLipfUwRrSzTK0VjR7UMgkYjRreJSpwLfKaQ+BDCvxkPX7ty5cuXLly5cuXLly+tk6xeEStld6nbJvcdtm9w6pkk8Rfvu1WLard+xYsWFQymUylixYVBRFMxmMxmMwrhHcSqpm1PMXCoPaJhcHtN1U/Q3TTe0bhFMnobopug7BYOg3BYE9DdlN7TdlN7TdlP7TdlP7TddP7TddP7TdlN7TdlN7TdVN0H4RTr6DcBgzZyJNkmRP9j0g8tDCPx0FFFYLEZCMnTgP5jnDnmbVlMplGoZ1M6m0U2i6spYsN5lKvATkaQ+Awr8ZD1/bsWLIf8ARlQyoWUtrtqUVwvEtrv3LFtfA4dy3eUVC2q5czmbVcuori69xO7Yt3UuXEaiCp013Lly/wCjcv3bly5fXpD5aGEfjp3LCsGtsSpmHQqLBcWkVRKNRKQ7M47OotOp2dTs6nZ1OzuOzuOzqbBTYHZlOzKQsyicjSHwGFfjIepYt37Ftdi3dsW/RUVRVF/WvqUsW+7YtrQT/bdIvLQwf8dO/YyGRplaWQshlQyoZUMiGVDKhlaZWmRDIhlQshkMthORpF4DCfxkPX/ZVF/aXUv6KCf7bpF5aGD/AI6fesWLFixYsWLa0FE5GkXgMJ/GQ9f2/wD/xABTEAABAwEEBQYJBwoEBQQCAwABAAIDEQQSITETIkFRcRAyYXKBkQUUICMzQlKx0TRic4KSocEkMENTg5OissLhY6PS8BU1QHTxBkRQhCXiVJSz/9oACAEBAAY/AkORvBBOrGyWOu+hTQYnNPz0+lMECtXWQryP6wUfHkj63Idu9StbsKi6yagdx5ISPWjzQfpZBJvrh3KQnCSNuxVOdanka8ZjFTwjmnzre1F2jvtO1vOTrpUbzrH2Qnwvj0bZebXYndCzQNKGnOGah6yqBjcoV5t2iO4c1PL23bu1uK1XB2rSn9kWbHHFWe88NN0ZqFwaK3s1FwKrzHDEPbsKtGNTfOKgdHJozSuGSwNHUblknQvbpLQwVoPXaqjb7+Wz9Yrv8nwd9f3Lwnx/FeEuuVZugs96/wDrKzdEw96tPROxdp9/JDxPuR00hZQDEK/DEC5oV3BzXd6kEzdMDiC3CiIbzzg2uVEat800i/I44d6Y2yt0VhZRmnuUHYo7U43/AGdqDnUHzmZcFh5LuCjwJ1/wVkwprFMO0FNibhq5qIT2owjHWBoh5zTC9zq54KRjheNocJHN2UVAwEbGqQOwBAr0J+iDhlVXN8mA2pmkxlTCzANldH3EKzD5g9ytYp+kKsnXTPoxyWI/OHuTCRfBFLoQkfi6uA2NUqx9oq0tkxo4Xfmp3BdqkRDH1ujFRnoCtC0ZGkkd6ix1iMmjmha2t0LHALAKl3E5IvndcZuV5vOuo33XlD1eQoIqM/NHLSgJKkZJUAY3QeVqiPKOKmG4jyi51cuaNqwikXo3IzHMHAcrvzA5G8E1O4qLipHObrDJywWKHJaOiij48kd15j1tiFY2zjfFqnuVHO0Tt0uCtJjdTX2INkFWg7eQph3tVmqaYkIC8M96c/J/N4jcpORpVmJ3GIoJj8r+qfin3aiztJawIRvebh27Qd6bf9I03X9KrE4xdGxBr2AYc4ZKHro8cKbKKvp29zgnXK1r2oO5swHPbgQnDM1UNRXVGah0dWsL+YSou1PfE4sf04gq0VGN4qHRvDdUYH1lITHcOjbWqs1oul+YNM1KB6rqcsDxgL7sF3+T4N+v7l4S4rwn1ioPq+9D/tFB9OPerb9Mxdp5GNOdfwUjDdLn0o0+spYWS0u4XHrSOjDH/MWivfctNaiWA82P13q76OL2GZBQsu6ZoujRvlqL5HOup41XOxJu7AoQyeJkQbUQsGCwEQRfE5jgDTJOdVgpsLUJNO2nVX/MGDo0a+XMeN1xajnB97CnBWbWrrHsVUJd5qo2xXcKnWTGFzWvfzS0qWeW1X4matDI41CayhIrmrYOhpU2NN6jcKiNmNN5RjjN2eoJ6t7JSf8Adye9WbqD3K1fSFWPrhR/R8lj6w9yiHzUB0hYsLrzgwLXN515TbMk4DcssUYWakVauIzK1cMOdvUFcrqdU67sm7Vfpca9qoBhvWKoM08uy2IuaKuC1yeCHVRIUPVQ5KoqLq8vBS8G8oUXKOKn7PJonP1bx2gYrMrWkKIb9/KfzGs1YYJjC3oqmp/FRcVMt9UaHNDktAG5RdbkjHzlnihj+KtAFKX+UqPqhMvAHXVNGOIzVy/eBcNbb2okmvIWo/NcHqrGAt3OwqrRIMKNpd3HkCbU+lbQ9YI3mO0Z9cIPYaiq0bG3nNfewTJGc1wqjQg0OPzU7MY4kLzbxMyno359hUmG1VkkdW9q0OShY54e29g7LYouJUhjpK2nNyPYrQctY5qz6NodVgwKvUIOiFa7FYnaMltytW7FbKUNXNP8PLotL6JxIwWdc/J8GcXfyrwiP95rwm35zlZ+LVCd9lKh+n/qVv8ApWLtKrlgrpunCuqoXlocbuRWlD3MtBxujFoQGdeaBtVaNmtQ9rFrEXvJed55HRh1GHYudj71q4F3OVcaN9bYiGSSMBNcFXTy/ciNNLTLnBGUl91qpdmqqaSgvZJsJbRxeSwb1K88E13BRiGQREnnEJjZpdK5j8CMFI1znFrqCiN2MiuRU5+YPerT0Ae5NmdkGjvUpdiTF7pVK1v/APKeomH1WgJz3ULnYnBNe2gc015qvvFTSiy/hUcZxDVFwWhjxpIA4o9DgV9bFPVQ3S2ggXW7Aqy5lSqslLoxxWjsraM2zH8FreftG3FecaM9ibVMoykYOJRcWX3OKmvbKYchTOqORvQPIcoer5EvBvKOKi5QdxU3Zy5clSeW41t525YinlXoxVwNU2WSxNpSuCHi8Tmb7x5A5r61Ta7dvJRpxTDI8vJbtTnRWh0ZrkQmMnuG6c2p0Ir5w4YYL1R2qpe1UMjAQsZwpKz43Co+PIy6+64SYFV0TJfozQrW80afpBRTkYi9miOjkKidsuhNvH115t4eOgoV9sV5X8E8H2UP91Ty04OcLw4cjggR6rryCtEoGN3VHStKXnSZ1WjPNlFabnoVbR1MHMwKkxE26uBQFpjMNcnHFpUgyqVGI7p1tqhZJGYnaXGvBX7t4McjI+PzZ2szCtTh+scfvVnpG54ug1ag4Y+aFFY7zXHzfq7Fa6b2/wAvLaONE/yfBn0hH3LwgvDA+c5Wbou+9WPps5Q6J/6lbuvGrzJNGWuJCuukLX81zhvUoLiRRWarTg05I0AAGLnbAE6GzfWl2u5M0DXFY9/IKqBjQI4mYGnrLMd6MYIqOkLJvepW3B3oKRwdS7rplpkwoDXuTagNbW8Mapg3UUXmTL80K9oTCHuBAKnOLbgAC5zip+oPepBWmR+4q7i1kUZaG78GYpzqVpETT9qpC/MyFw5NnetnesSG8Sue37SDnvaG76ohrqVGYV67jq1TuKedgdmnJ5IxAGKoi1o0kp9ULT22S7HsiWjs7TGzftXFVUerWgULHYNvc0Jw21VoHQEEd6j6g8pyh4coUn0beXtUfHlKa4DWfn5dJXUbtIU3iDBWlLzsXOTr2JrWvlGuaZEyvi9czs5dGAZmqzDigm3B6oKiwzYnblh7SbXoryOAzVC5ksD2c7ElnRyURbTKQ8jfpOS6cRuOKnA9rJO5HKAfMCd1lrDH2m4Fele8Xhg9HkeOhHgU2t7L2kGSOv41D+xDgqbwjTaFC5l3IYFWdgwJfUhURIzab4V+N4p7J2hSiQaMDbsTbrmvZ0ZKQuF4XyE1xa+khrSigpID5wY9mS3tqMVdfej2XnDAqfAObpXU4VTMHaopgMlebQ3ogcNqsdb1C3PcrXdpTV/l5XGjal1DVZDHcKeT4M+lPuVuXhgfOcoT1ferF/25Tvp/6lbuMakhtLXXauAPtKtiY0xEVLSdqL5rlX15pqmyul0bGVa4ZFyDIxobP7A28eX5u9VWCqF0q6MOKDtISarxg6myl4K8CadZSGp5LUbtb4V0uxLse1qi3UCbxUegja9zzTWPQoxM1jXNfTU2hPbXNyoH3la9+jHvVAMS0H7laG53b/8AKxRyuBDRHR3G9VXiK+yFG9+LjX3q0gPfQO9pWbWd6RublBieZsKOasv1PcoST6iH1VWmao7ViZk1qzGCkd4w0mmKOidoITm85lXYBfk2vV57ieKxW5FNULh7acpOryx9XynKLhy5IuprUDeTmqjmV7Vcj1RuryZLm1VAKclK+VjVO0bA2qxTrt4gdCvEtaDsJWLm9j/7IgSMH11eMwkHSvSMWtK0Kmlai9tLqs1N5RwuiigZnkmhPBs73N3tTTRwxycKLSE01rqrJamNHArC1l/BivB0rjvur0Np4XVhY5jTeVNaI2FjHuLgwlAG8R7KGq52vsQpI2u44clqaPaRryOUPUCcQL2vSio69H1wjSh1hkUeRwG5dhTQXXXbnYKDpcUD0KNM4qEGRtab0zpYTRBN6dVQE4VbROBy2gq8ysUg9ePBWvbdlUGsG6oUcgY0vDxjToKoCYnHIK7eD3AYtKm3NlKZedS9XNSXQLpaDqqz7KCjuhW25SmpT7PKeuUO3yfBn0p9ytv+9y8NcXJnZ71Yf+3KP0/9S8Ifs05krHMcHHPAFVBrXcU3DxiQkuONKKMSw6Ju6tVxWIwQIK3dBWyqxwomhrqFb0bzskI2SshdnfLarSvfffTaVhTvUsVdalcEA6vYvFmUDHM10Q39YPctBdN+7WoTeKjddc/XybwV/RuaLw56lwwbv3qFpYG0OGKmOwx/imOkxlkAwG5SkcwuNT9UJ8pwjbirZfOqyejRuFxM7ferX1lZj/iBWensFc1Wc9VQEj9GFWPWkwpXemX5C+SQ6zk+L0k7jqxjNVlNXfqmL0TLnDFU5jBk0LELd0qkOud5TtI68dHnyNUJ3OTk7q8sfV5DylFRcOUxV843EjyXPaQ2AO5qNns5AujGq0DmG8Bi/wAi2X9ZsTsB2pr6Xa7DyWaNuUhpyF7zdaNqD2moOSJXNotZ5WvV/BZHuXMPcuYVzHL0Lu5ehPcqPYfrKzhhDAzZVZlRFpqME1SHpUQrTHNTaYaTKiLW1u6N2ZTT7R2rnitaEIupqd9E9wGI2oOPejGcU1o9pC+0P4heac+DqOVpY9xc6/S8rtVhjwRwUPVC+ut6LmNDTXZt5Cn9Rdio4Xh0pga2lHlDgouKZxQ21qmipcBHq12ckbhvCFRWjk6j3NqadVV1bVH06rlb64a9VBfaHUaM0yj3XC7Fp4FWbr/gpRIwP371aYsWkSHziF4sxOFdqkpQVYDd3Jhebt52Ktl2l0hhw4crusUKdPk+C3f4h9yty8N8XIdn8y8Gn/BKmH+P/UvCAOwRuUVY5ZXPeWgOenN/4a690yI3PBuNKc9ES2Fu31sU2WOzR2ht3EAmrVpNG2I37uHBYLBy2GvJX7lhnvRxRnv6NuVQm1nAbWho3EoRWNlXesSFKXgtc5uNUEOqFE4YecyTrQXgVwazem8UxwjdKXGlAUzSQOhc11KE1zRbvzTZa6zU+e0N8yyPCvrFGaTGuDGbE5z8A0XnORFSGaCQUVt+lb/ImU3u96tVd6gp+sarP1DyWW+TSra0TZHakLRRsfQmhmJvNcaoxNaIg3G+fwXmxiec92JKxyRaBVOJwG9OZEa3c0wgmlMRsTH7Uw/M5GqPrJyPV5Y+HI7yYuCCJzwUj9C6pFLu5Os7YrztlE+WdmjocleNmdod4UjmwF1DSgTmiBzxeJvBSyeLuJI5m5Ohcy6WtvF1ehHQWcyNG1NcWaMn1UV4Skpfuvyy9ZMfSr35NCvS2ZzNysE5F1pxp2q+bK5se8rUYXNeK3tyaCwsoAKnaiqYngFkPrFYOP1WrOT7K/SdwXrrJ3ev0nesn961mkL4hYO+yVE2+aEoJ3SVHiCnYjvRDdZ1w4BMa+qs+oOdWqlOOkJpToT9XcmNr0q0P3JpOx6bdlb24JvSFaB7WssGnBYk8jdYhu1NlDXAF+S59DudgiR7YyWO5FPHzORpbcmG46pTb0ZYSUOqoBvKDq7VRobKMehNdQ8ylDyRnoBR85QVyonlwD+orsl6J26QK3aoY2R2q1qguy3dQbExkoadfB7eqVZuv+Ckcxzo3+0FNWhcSa0VmbQcxXaOxjHTdxTbzxo3GjahWkNyuR/jyyC9RVHk+Df+4/BWzqrw3xch/v1l4K6YSpgyjohO4npxVsNNHI9jG3XKw2nROOgnJNzHBPJstoocelH8jmkvUxOCM3iNoDrtM0zxaF9onMYFS3BnFF0zbsj5ScruxdPJgs0d6xIbxxVKrWFRlRXhhTBCQCOM5AkVKfUFw2kCgQTG/NCa2mq2QVTSfZICag+LB4cOlXptYlwxpRPpXAVNFBGXPuVvGo2K4zVskf3rHsG5PgFQ1t4Hp83VM6YZPcFaKDFz2/yprCnThrXvJyc1Na6GMNzq1iBdsFEEIiNQKNjj5uuJRbYWgNbgZnZIxNrapnGmlOxUzO5AzOoDzY2otDA1oWBNzcpOlgKpvag2iYa11UU1M6ycvq8sfV5HcTynFwHzVgHniU0ZAImlcWjvPJaOp8FJ1PwWrsdVNN4XQ3m7laCn/SK04er8FawM9H8E1l4NeDiFVpryeFesP5lYHv8AR3AnsvBznc1eDBTD+6l6PiqdH9Sgr7A5NqyCHlux5qwWLSFBxUpa4g1bzcFH+UWh15l866OjMpqPXKaZRKTzRcNKKSw6B726SjHO5+O1GIWltobo3EY45bVdPN6DkvONJO9PaH5701t9tQrUd7kOujfYH8QvNmSHqOTanSXWbUTeuZVG9SUpcpuyUcYGbVA32jkqDIOC1wD1gjKxt03xgDgUQ8UWq6iMjnapFEHMxam76KDHC+m9VWbrLtRxb2rH2OSLqo3qjpRLXB2SdG4VHerS3YH4d6s4ZHpKsG1A6zXXxUEfNUHX/BSXJA8U5jwnlwoTUGvarHe9gKPWLtxOas9S3GuBVpu827H+PK+RuANFrkYrnLNbe7ksQ2tnCtR+avDY6Xfijw/qXgj6Eq0uEhY6OY+9WoPnY6WKlWNq6pTr82hjHOpiVqTyFp5t7BaIucaDeozHUVdiqgnhVZ+czvHduWawTRkSqVqVjmtw6Feoe1YNx6FpACyOtL1PWRPi0ssnVzKfejc1g9UghBQnZgul0oKAu5VQV6QFwqMAKqIRtc0tNTebRP3uREbrl/ByIu6oxHxWwcVPdxG/9mVEwNx0Pvbiq3quJB+7koaZ7UNZg7QsSBxWL2faRkjbpXZDHBA2t/jUuyGPmhU9FD7DE5z64DGiYImhgdm85oY1kBvVKLqc4AroWXqBDpQvHSDY1mSjaAGQFl66impnWTl2csfV5C2V+vXmhUbEe0r0JRAi5cvWZ/NyGW75w7VpbvnDtVCKgq9o69BREbbtVdjbdC0ob5w5lGUN1ztV4so7oV1go3kk1PSc7pTI3wX4ujYi2DzsrlBpG67Bgi14q07Forvm9yDRkMPIHlyiuabxU2R3KHinWfSXC7bSq/5xNhhtVZrW+03sNdVb4SNiFPV2plmit5td6tZo2gu4J7wZHvLXNq4b1zqrFgVCyi51FJrkm7gh9JyynDVZQV2pt4NNHCpKvDaa13ptMaR1VkG5tUblC68M1r2d31NZXQdcSDVI6UzEguGaLdoNEaVwKLjISw1AG5R3Jy7DmyioUJla0C/g4HoTS3EUVnLhheXahUB3FNDW0BZVFRdVEfcn6gqc0JIHOg20BqrTtIk/FWcveGagzUbg6/5zAg9Cg6/4J/m7zPmnFTuHtnNWV19zdTMJl41wrUbVY71DUHnKZrfYZ+PLVUrgcVmO5c4dy533LNQ3fbxc3NSyOJdVudF4X3Gv4qUfNPvXghzMXCE5q1QmFvnZCc8VbpYhcidQAHZwQkul7hvKJkYWyA6o2KVocHYYEKEj9YskLqq4LDMro2Ie0a4I1CIOqFQCq1Q7gE580L3tbgBI7AdiuxsDWnIszUslondSnNFKd6GCi6aLDCjwmnigmP3OGaJvZOHvRDc+lRirCC6h4KvPc4UY3ejpDpnP5zq4N6ENHQF9AWphOLwKFOLdaVtMNyvPzvuUuLuaMihn3qy7edtW3vUZYS3DZxXtSUvGmSDC8XiQLoUTYn3QSb1NqaAN/vRQ6oWJa3pKLASTcDq7FdO5AbQSrL1U5BDinLsVTki0vx70yKJtLvrLXfXl1XOw6U4utIY4fo3HW5Rj+eocVqxxj6v5+aoTOKlpUKJV2JwcH5+yU0M1iqFoNW0FUfM3QRTBRiSN5dWpIVKltE0RTXiTTJXCi4hTP3NVKlvnPVQuWm8P8RnwXoY5eq6itRc10eO/Jash6VQOaRSmK0ro9e7dUZoa3S2i+tyY4+cb70C0gUNMRnitamJJqFaHU9pQfOBKjGkaOKsoaK1lOXBVH/hFtSrhFWbym3oHEHawpt2tbmRw2rEUUXBONMa5jBUdM4M+cUAyYGnSp3RObJpHVoomObSgpko3sYGPv7FD1kQbzOkjBTlpqL5UF192jVDW7jGDVWO+Bkc1aGMrzGHHHf5APkspvRkyfvVsNbofVTxYgitOleC7t8uMRpczToywX71auGsqHEch/BPujDR4Jh/xByAsbx6eTMX9yxomG5eoDTFMrI6+c1SN17pKr6yzpRNYy+8upQPNcVdko29gC0qUyxh9Gk379ceCCg4BO6wTe1BSvezS5Btd6Nd4UjrtSW0Kjc1mVD/ZPLsZnZno3K+8G4M/ndCc+7QvO1XIvSFr6O9nVqra5xq4thdXpoj9I5PPzRyWQ8fdyDq/1KPRnRlwFSFE449J4qLgV3+9XpH9gQLcBdCe1RmmOhAQ4JzelQIoIceSqvxv4tJwTmEFpHLlyPKD3ZhVLWx12MwWiZzTm5uaYA3CuZKFyS6KVyTA8l4rkKBHRHRNGyiYRkc1hgvSfwhMdWvSqsdTsXPHcvSfwqXSurTyNR69L/CF6QfZC9J/CF6T+EKNpeKE7h+alxKbTenhwBFVZpo8JJK1xUV58ovNLna+XSn37RIDX21Z7zquNako6eMPowZqzaEXb1a0URvuqRmCrxca3k/FpoULwoU4cFPwCj66C4q10zqvRCvQV6zUcVFhvV4NMlHZNVHtkj6zF5qRjn6QYVWLenBa9QduCdE1wvYqz0yuJlQDxCszmi4RJs4KQXK1pl3qJpGFyvFSk/rKBMoQ6ldqgLc9F+K1k2KhkG7cjWEuFc2rRMJab20I3KHgvXHWxCpNG13SMCtHNeaNxTZrLaA83uaU4vN9t+mCtBu6jpCRhRM0d2tMaqMSMukRjarHfF7VKtIBOMTNvHl0ELWkUvayeyjNXoR0lLvkWclt6/KGDoT4g4Okbm2uKk+8J0UeqrBeaZjGpA6LRzmUuB2cEcRivOMJb81GoIb0q6B6hWH6wcla3h0J2OaFHLHEgYUWI4rDJENWKpTBB2qx5POdjRN0DnWppxfUZlOHiQs9QTrqIRHM0PQrOx7rzhSpUnWCjxryS13tXEhEHWLvVCrG27UXeAVZRRoNA3aU0V12kXYwtA2jb1LxG4h3wVlxxuO//wAlavo4PcnfSFEU9QclkPT+HI7ob/Uomn2Qm4bCFC51aNzoh01UtcUB83kiYcnYfehV8gpuKI0k3eE0h82HSPgufJ3ql+TvVdJN93wXPm7x8Fz5u8fBc+TvCDnOmBG0EfBektH2m/BDzlo+034L0to+034L0to+034LCW0fab8FrS2j7TfgsTM7iR8FNDGNVjy1M6CmXThdVnxrrCqlbadG0sNHNediIKPJEjyzjoB/MxdblHlyVZ2ocU8DeorO8+axwV0zPIIu9icTfND7ShDAaBOPzRmrLwKguuGRXNB1lNejdiRktXcjiK4KccFGL5Zr5hYWkO67UCWxSdWrVa9Sjq81Gse0LI1q5GuSHAr6wzXOKwFDpRivWXOvcQsWNxVnw9VRtdeYfnNKg0ZZKb+VehG800K0l4YMuhN2+dKBMYqaoNFXAx5OPSpXXaUXVhRbfaDXIlVqsCCvivRBO0eq7pxR0RrTNzNiIHN3OCa212UO6QgbNnWlxRzRXH0ZQtaoo5mlpYFPr180zM8rPo1aOsUfIsv/AHDVM6mOjz7F4ShloY4Hah2pssRvxnam1TyHlpJvUATnMe6RzG3sqYognDJGmS4xlPoa+cHJQ5VWHJjgqAXka1B96vOowHeqAXV6QYK6wVTtPOy/Slx+CkZHe0YYcSpHPbeutqK7MVHxHvU3WCh5KGhBIVNpyUjqY3aV3IAY9qlbjpTjfByCJde1g3i9NwDeZlj7as97C4yvexSXRzooQrhO0laR2eCxbVMjdUtaslocbiexmF2ii0khxaahuAzUXI5DhyWfiPfyl7nBrRiSdivxPbKz2mGo/MP8HC94wwVyw8q1ZE6Q809JTU09Cgr7SY5tZbRLWo9UIKvJH5EvVQ5D5OKi63KPLkxqmdKeo+R9IL7b2Ycm34nREb0dK849FVZtG6+ACofN1zoua6t9TbKkZhMdWrUJ5Gs0QxLlanRejdlQUUfW5bbQXsdiNWOGLVjXN2xOQ7VqEVvDnLGFjuDlG10TmnSjE5IVY7Z71ls2jpTT0qz9VR5qzhrBf0mYVRep3okgO7FGaUrImhzXtz2Jj4GXwI8d6pLE5vYrRdNTowjeaHCu0I3I/qhazJIem7/pXm7UD0OP4FVfCHjtHxXisQ0bz6V59UfFBjBda3JWhzOcKY9qYAysz8GtG1Xq40qUyaF7rjslR7BIOkJh0OilGbuXSkawbSqLnNBJV5mqN3kQD2ZA9Gct80+PBy8MjpU10lrqPII4rwXERf8AGG0c49AUtx17RuuHoKrHNoZRkaVT5LTcmvHNgoE66i7/AAypae2Flkjiqk0K1sVquVfxTaVea1IUlWtq7DH1eCzxQWDzf9Wm3imUkstl3PaLziiHWjTvLedVTdQe9M4qTiFEdteSCJsZ0R1tJ0ppOfSpbxuVyKiGlxvjJSc1+p6M7+KMjpQXPaAQTlRarc420ps5yhDjS60e5ANGAw8uVN7VFyjhyWfrD38kgs9ltFsZFzpY2aoReI5iLXG5jKNyw2ptkuva+EFxe4atLyMcEMtru5uhGCc6zk3286N+BCtEJjmMsL7lwN55rsRsxZJZ59jZtvIbRaDqdGZUULrHaYTL6N7mYFTWNsFLYxtXS3BlQbUYoYprSG858YwCFkh0jnlt69dwyV+OKd8lbojDdZOs4jkgnGN1+3k8IFrr1ZdbCm0oLKuCZI2JzrprkteKTPyG8fIk6qHk15WceUeQw3NJeXyc96jZ4vSppUuUlBkmJ+3FR8jh85diA6FBgBnkoa4ZrMc+qmxGJFEygFNycA6jGgCiemGhOtsVHskZxYvShvWwVtc03gTsRqHDFq53rOwTl3r6w5G/ShNqzdkfnLmkYfim8VB1EykjfrNVna4MA0mbT0I1A/2FaO1RdZNxNMVAQ4sOi9UotbOXDc4VTKsZrapNEaXHNrtRvx6PDetU9y1mtf1gm2ayNItBzc12EXSoobNJIZHPqa+9VLzdG8VWltbKuJpG2L1lL40XNtGTnbOAREMzJTd5rc1HCedHmjgrLI7CR3OWDqLnOTq71U4bEPIYZn3KuorwNQVO9rbrnjEq02cG+brqLwFe2VB+yvDRBunTONQi12MbLMJK7aoBpujA/crsEjtNkb+SL3NpHdpVT9Dh7+TcqOxWSNMVv6FSlOlAZFEULukLAXqLmOLRtaKhNY2znfiBgn3YbmqadClk2UDfvTK706g9YVUXFFz8tjfaKst5jRr11eCaZHXW5qRwyYKBqgwaQXA0u9KeL2qY6VI1QnWVsDcBeq9HSADAUpsT71G3TRO0eq0bU68akOR16DiteRzR0I3rRIOxUNpeF6d9OCfccS3pTe1Rdnu5L/qoUAoN6xUbC7MinfyWi0eCJ4bTZDrPhONFbLTcuVhkaW7jdUhgrpaOrd3XsVHoqCWrr/FP8T9FdOluc3m/FeFw6mmvu0detivBWgH5VfxDc8xT8eQwzSiAXqtefaVmh8JNjtNmdqMmbzgvDVzneJmhH0bUSy7pjIb+9TeL0uXTW7lW7irXLTXMgbXs/uobuF9lT9g8lqnc6rZ5qjo5MEaBqvEAYc2i5p7lhBIeDCjK+zSNZvLVTpR5XdVD8w3j5cPHkh6yd0oOvIhMc84IFhqnAzsab2RKwIPBdig4FRYBZDnqbDaKKFvSpgG3ck9R9dNWOPFW2goFt5wWYzKK71qgON7atazu7Cm0jePODMLLKnvTuH4pvFWfqJis9cPOfgud93Qpzvqoesmuq8O33lGHOdJq7eSHiiDezzoi0ESNOxPtDIwwNF4hm1Uhi0doLtUdCbBJITPKbz3q69gpm0qapAqKDiop5XgS3RcZsCe5z7znEkkdKmccCHkVUcljmlYLnNeckWWh16FvOvYJtidG5hGterhy+ZqKi6bqgYbwji9XerzmuZx8iyn55RDHtkbuK9IwvIyqtfAVomGgfcNW0Vta3ObFT1GHidK9KqdgZ/KmjRtdji1yEsTyJDnH6qtI4e9Ec7gsOXmLVbRVJqi69QhZ4dGCIuMNcNbFR2eFrYjXDRiibp5tNLSuLsk41rqlBgzNHJikByIChuyue2vs0WkeKOyDfZCs/XUl7KimbtJTcQbu9B9TzOfs7kHHWDoexG4xzHcFPq1L37VJdbq6DSDjVTXyb2l2qPMVj3rnO702N0xYKVzVC2XE0BqnxCS9Q7DVNEl4OxwchwUPEL0gPamxNDiRisWMHajUtHBWU0q6+PeqHLJPEFttVnhfzoWPwKfYI7zIXNLCa44plljJextfSY5p74JpbJf5zYjqoiBtXuzkfmV4b0hfG5kxLJGGhbrFeNOkktMwyMnIIZ60GLXMwLVHLabXaLbouYyZ2qFN4TBkM720IwpSg+Cmms9ul8HNrrROe1inNi1rLEyl/wBo0/8AKfFA6Qte68dIa+6iZ4SvSadgoB6uVOQwtBvRvNTy3az3hnRop70Hs1A4bqH7ld8cmcLuGsiWF801QG6R5oEDLDZjCXXaOqUyPQ2VsbpKO0cdCjy03goeSeUJvDymNjpqler3pjqtwWswtWRHFZlC615HVTdU9qeXw11s3NUQjjuudnRa+NBsKguVpTaarDALJbVBe56m4hZVqo3UJ19iaQx31hRej/iUtpvXS/ZRVvblntOxE6bPoWlv17FT51V6P+JCLma1d69JuV3S/cqaX+FRszuilUy7aJG1UZlkDmCTgjT/AHgpTdOKiHz0AX3aVUV117V2IqHiiMsUaEB2+imsktHPc3nNFE5xqbzNVjAnHG61rRuVlDqyPc2mrsUhO4tiFcG9KYxzL2Aqd3BWm7X1c/zFdIzuTS+erK4tA2LmvTWhr6k0y5G0a13nA3HpTLHo75ppKn3ImOUMEb63RuGxUdGxw3ELVijbwYFzG9yoY204KhhYRwWtYLM79i1ebsVnZ1YgE9sUbW3h6oom4EO9U0wIWiui8PXCw8jp5JLRbLPpptMWVvOGF0dK+Rf5jviqssYB67virwhoeu74r0P8ZVNDh13fFXjZqnruRY6Go6zvig4WbEGvPd8V6P70I5YrzB0kL5L/ABu+KvwR6N1LvOPkY08j7Xv5K3sVR0s0jKUwNKrzVliY7vUj3NDXbgm1eB2plwmrD3rJqqtcLVCs/Xb716Zn2l6Zn2l6Zn2l6Zn2l6Zn2l6Zn2lNPCY2SzGr3X61XpmfaXpmfaXp2faXpmfaXpmfaWkljgL97X3fcVo7E2NrdoZ+PkWr6Z/v5ZR0qFCg9VDZR7T96mrR+NQEwiN5N4Hmp+qVzSvRv+yUCYngdVZLJc0rmlcx3cjSJ5+qVQinKzh+ZiVHYrzjb9UfFiYK53XL08n2yqGaX7ZQO0bVquogZ/OEb1S5969F969EhJHGGvGRWjl127ihSOnarrcAoXuOJvZKJ74I3uNcXNxzXySH92F8lh/dhfJYf3YXyWH92F8kg/dhfJYf3YUr44Y43CmLW02+VCC/FueCiDHV856qwce9c9xTanEv2oYb9is5AA1dnFejb3KoiYD0NWBK9I/vVX6x3laji07wVeIq7eVi0FUAujo5LX9X8fzcPXHI36VvvUZ/wCpT0v8Af+Y0c14MxwYaVRAdaHt2NdJg3hgvS2kcHN/0r01r+234L01r+23/AEr01r+23/SvS2r7bf8ASrF4s6V+lv10pBypuHSsVL/3B/lb/wBJafGJJtNFI9tGj5yxNqX/ALopxskNpe1ubpHUCP5RHZ8K868V4pZ3+aNaOcKuQe60l9MqNpRWas0jgReIcU2qwcAqnHkbceHHoP55xhuY+20n8V/7f92f9S/9v+7P+pDCH7J+KkkJFXuLjQb1ms1fBJv12KMblUsubOcD7vz03XPKzq8o8pt8kEeyudtQ0ZqMfzwGwKHt9/lz9n8wVL17pCvNN4Iu0gIVGHHceSOoGW1QljQzztNXkzKBrqVQcJjtwUQe6uH4/mrpe0O3VVtuuDqXK07VpWtvzyOuxjp3lC1HwpGyY62gPuyVj8G2ADx60+tTmqa0SW2O1twqaVMRrniOxf8Ap6aGQOltV4yi4Nc1FBl0ozeEPCAnjc30TBgDyVJoN61pWjtVWuDh0KHrjkAOHnG+9QfQlScX+/kl8H+A7KyR0OEk0mQVr/41FFCyJt9sseRGNVJL4JskIscbqee9ZO8GWiyR2cMbrD1w4BSCxWazMkYdaQ1pTdic8+5Q+M3dOW69zKv5jwXxk/p5H1w8+f5WoSTVdI/BkTc3qHxjwHJBZZXhl/HVrvUdlhgdbLc/KJuxVt/giWCcnBhdQOG3GnDvXg/wboPlcGnv3+bgcKU+anSPN1jRUk7E/wD4T4IktcDK1lNcV/xO2wuslMDCcTWtKLxmTwLM3wd+uZUkDf0q3eEhYiBZXNbo9Li6p30VmfZPBLjY5CGvlecAdvJNbHi/dwDPaKZbv+IxWPSa8cNFYgWh/hOcXcsA4DE/eFNbZbbFaSIy58BGLPu2KDwj4wBa3WvR37jebQ4UooLda7c1sEgvGytGQpgMuTwiHYVneeOKzCvvY1531opYJYvMMjLhGHHOo3cVXxX/ADHfFaSOyXHitCJHfFXHwOI+ld8UPyLL/Ff8V8gH71/xXyAfvH/FYWSn13fFWmFgpHHK5rR2pt1ppU63/St7ULoxxzUuAr+em655Y+HKPKqD2J1VotrASnSkVDUHRWdxbwTpebd5wV+KyuMe+ifK31M2oGGB13fmhBEy9LuWtHcPlwdvvUNgsVn8a8ITCrW7BxULfCNng8Vk5zo/Vw/sn+CvAkDJZovSSSbFY7NbLFA2eU+kzDh0Y8VafA9jssMzw0aIuBwN0HHHpR/4potPew0e5W4g0Op/O1Rm4HVFb2atUbD5sZKV7mh2O1C7qtIyHDkYCH4bbhVna2vphmFzQsfYTesmi+0HioRnUcjhDE2oOa8WtLQx++id4owXBtcjZ7Q0Nl6FLZ4mN1DSqjLmgzPPYqS3CPaaqjJQtJIBVs0bQ0m5UgdZRS2dt+WzOvXBtCBkgn8ZpQwhu1eC/DjYTLDELrwNmP8Acqey2CGaQyAaRxZTRitV/wCjRjUPf/O3lkJOINPvTDIy+47aqdlcBRRdYclfnj3qz/QlSdZ/v5PCli8JHQtldVkxFQaVp31XhKx2CcTOEJaXDLWBT7DbZRZJ4nkkSbVLaoQRE6MhhIpUBoFfuVsw/Tfhy+K0ktVq2xQit3ip2ts8tnkipebKKZ/+EYLPBPbAznPhbUDghYrPpXSFl+8W6uVd6rZbNap5K0uBgrTfgVDNcdHpG3rr814M4yf08j3YHSTlwpwC8CW2dpdY43i9hWmOKYRbIHB5DWgPBvbk+e2OEUcjBopHYCtwBQ2Vk0c1oMoeA01ujH4r/wBO/wDYf0vVvjh9IYzgNqggM8UM0V6+xzg05oT2V4nhZOC5zMRtFe9QzeMxNgbEBcr0c2m9f+oKZGSPD64Xg4AYaEYck0EPpmkSNG+ihstuhtENqs7RGWhmdF4K8LwQk6A6R0RzFaH8PvU8Nis1oktUkTgWXPRimNVZRQ4W78CouoOTww8zRx6GVxuvOL9fIcl0P1d1E83vOaE1H1m/mLd9M/3rxQsffkrRzcseSS9O5rAVoJXF8ZFQSnulnMIrg1oK0Gk00RycQrRFpnMYwqBocXMLtc8l7SdgXm3diuudrbgvNvB6E5pfrN2LSF11pyqiGk16VR7tbcFRj9bcrj3hrjjiqF/byN7V2qXigWG6b2xaTxl2lpW7sVf0166r/j79LSuRzUkpJEg29qjmlnfX2aqRlomfC31aIu0mm2AlCV9pc1zsQApYJufHtUgfM5sYPavFr5e0jbw5J+ueWPhyt8t6k6in4D3qMX2toMalW2SKoirl2pn5dKzDEaRWoxF5Baa3k3ii5k1y0KSKUhxb6wTpSKgbEHw2dzm706V2rd5wV6KzOdHv3p0rRzc2ouDbtFB2+8qyeFpmOdYntoXD1cLqhs1mtLZppsgwdFV4Wb4QOhZanFzZXbr1fxXgyKyO0zYX4ygYYkYBeEPof6G8lpY8VabvvCuxTlrOKIGJOZThereKForlyR4qEnLTBet3KrdjU0/OQOjbXbVWUNbSo4beSVkhudKbosgKXgnstIuy1zcvMRuqPXqrcfnIMnGByco44ZjNE7PFNa7MVUDQ65hmreJ7v6Ol3t5L+jZf9q7iqEAjaCrscbGDc0U8g2aM06SmMdQ0UpJBv7le3IsbVrosHByJFee33qz/AERUnWf7+QC1WeK0UyvtrRXbLZ44Ac7jc1pp7FDJL7TmrTR2aFk2WkawXqcURZ4IoGnGkbA3l8M+M08fv+tnSpvfgvCGip4z4s/Lnc00Tiy7pzKdLhj0K0+LXdHdNbuV67j+Ktsl3XM10nop/wCeTwZQVxk/pUkr2EC6btQmDc8/gnQWmJs0TvVcm2iOB19jrzQZDQFNZbIRJd5rsiEYTY9IK1vOeb3f2qz2zQjxiBmjjfeOq3d955DLJZrjzmYnXaoWFkLfFaU0TsQtMLNWmTHOJaOxT2RllDbPOQZGX3a1DxUcELbkUYo1u7lD3xMc/wBotxXRuRuRsZXO63yPCBaGfKHirz0qjntbwTsbwacwnmwTGSfRa47WqS0TuuxMFSUZrB4ElmsgwvnMqG32mNzTK0XYa4k7k+02zwNNFZaVZI2vYCovC3iJ159DotL99adCju+DHx+DpK3bQ854Z8lu+mf71Z+STzRkirsWkljMUYFKJ8T4TLGTWoCLnR6OPcQrY5zSGuOCZdbVhOPJM5zQ99aYqMwDNtS0J77sMmOctSVfOiZhi2LBWsvAdR2CjEQALMggyeARS7HBTyTNvvFKBygkhF2Q7lZg7HDJXmsa0g7AoeoE3tXap7uNEOuEGGzuMlM1ep569WnQqeKu03VT2vaNIdg4qIHA0TmWizOe31brVLG+oJNWg7EIn2dznNwUtonwe/YpA9pabyEt03aZ9nJP1zyx8OVnlFOT+oph0D3qIltDTGiLGto0qt3sWjDaMIyVxgutV5w1t4REbaKb/e1R67W0zqVbHx4RV/FD8tlbTMaT3K0mJz3AtI103DaVB2+8oxzRtljObXioWls1ihhk9prUBarPHPTK81Mj8Rs91hq0aIYHejaBBGLQRQy3dY9vJP8AV9/lNkjdqubUIQtex2veocCm6kQ34rnwDD2kGvdAXA1wkV0sjI6HgqzB4GA2ceSRskYcS7aF5tgbwV58YcVRjQ3giQ0AlUc0OHStRgad45GWi9i3YrV9T8Vms1ms1zgucFzgvlY+z/dfLB9n+6+Vt+x/dEeNt7G/3TK3SWjMCiAitb4WVqWHWCbL48dI0Uxj/ujKLYbx/wAL+6H5jxm9JZbVtkhPO4qdzbRNaZJqX3Sn/e9Pms9ptFia/nRwmg4IWyzumDw25dLqtypXepIbM+VzZHXjpTt7OSOGR7YwQ43nKNpkiaTERQvyTRueRX/pLdIHU86/+dGtpLq+sRVThhqy8pABj4sf5mqYRCt1zXOA3BWS5aIYRFE1j2ucG3TTGq8C2wecsIeXOI2g3fgVanm0xSMlhcxjGureqMP99Csv/ff0lQAZXB7uS3UP6d4PerK5wu1pySNftNfLkkilMb69i00r9LIi6zTaOuxGV7zJKdqmkvV0hyQuyFhCbPPLfLcgFpYZDFIdyEs8hleO5Mnri3YjGTSu1Mb7Iom9qPFWov8AXIOfFBjMTeqgNo/OWjrHlh4crK+UU5u9E7bqIIqNxVAAOHlzdnvURLaauN3atG1tGqt0gbqq4G0buV1goFB2+8+XJAwhrnUoTxWvLG3q1K+Us7l8pZ9leanhedzsFnZP3jv9Khhm8T8VYKHR3r4VI9D4tXN0pa6nY1YuJw9ZxK5gXMZ3Lms7lHaLO+NgAxa+o2rnw95+C50GPzj8Fz4ftH4Kt+I8Cfh5ds+r+Ky5KvBPBXGhwNK4hZLJFsZbXpXOj7/7LnR9/wDZc6LvTHX46NcDtWfIwXqV37k5zXHGTvarLFY5TAXBxc4SFmVFE3xm1mbSOvOEhOAwCZO3wham2l9L8Ekxw3bVaNLPp2gNoa1xxqrY3Tzs0NzRxxvIa6rRUoMmfaAcaN0zmntUsjbS/wAXH+Kaj8xPJq1DDg7aohRjdGzMDNSOjqHa7g7sTn3+aK3WhWKayNuRzk0bJSqDZZnac5AMbiho7RoiK4GmtxwTLHa5C6aprRraZKV1mtMcFmaQNcjcnPfLQV9liZNZrU25WjqRtKtvjsok0dy5RoFK13DoVfGm0+iZ8Fo5bRVuZOjYPwUscjqsawkCmWIVtkvVdG9wa0sFDsCtdtcGscG3aMFMVpH2+eOTcSmyDwq9zm5XxVN//JXLu2OO57k4G2ykg0VsdKazNLGudTPOn++hBjMg6g7Spas1hS4AM1aWFlJKgq0F4cB4sc+s1FpAIOwrS+K3Ma3WOIahYZIGusoaGiM7EXCzX61FHuJpVNsPio8Va/SNZfdg7fmgBkOTwgI3DG0PJp1lZC115poeC1WOdwCo8hnWVBI0noKo6RgO68iWG8BmQsGk9ixHIWsJod/5xvajUVxVs6HD8V6eP7SoJoyessSq7FzgsZG96ppmV6y5wWa5wXOC5wXpGfaU5BqC48sHLj5OadVPPRVcQU6KQ6grSqfe1aJ2naHdqNwAMJwC884N4qPxI3xdxuCqvuF1u8tTtK6tBVUIBHSqUoOjybzHFrgc29dfKpv3hXyqb94V8qm/eFfKZv3hXymb7ZXymb7ZQkm8OzWf5mnIX/P5j/8AZch/+fnH/wBkrHw9N+/Kr/xh8h+faaqrLWx46HKptDxEdrXUVPGrRId2kci2SeZpHtz3feUQydznj1WWmp960LHyscP1iqMlIWTviLNerDTJQv8AHbTcbRxZpTQ4ov8A+ITOOOrU/FOLrVKauwo8q2OmtEk1bl2+a3U01NTeUEQcdd4CuyRi7vUVqgLItehF7FXzrRgY0x2L0sjWgnavCN55dTR0x6yYxj7t7OicdM8DZrJl+rtUnFcW8rup5cNqb+iN08ENJBpG9alEwlgkub+lXNGwOpgMqp10h18A3XFWmsrX83Bvq85aYRgufSPLeFG9lm05pdvNIqVKBDI2R4wvEav3qDRsa/S3q3+inxTwyz2YMGRcHGv3qzQvFmGlla03Gu5teKjhibG5ror/AJwbalRv0Fmuu3Nd8VaHTNs8RaNTVdie9D8nsteDv9SjbPdjY2uETaZ8UQ3ALwgSaFmlA7GKGRttc/nDgU2TTX5Djdc7Vb85eMyc+Q1w+5NUFuDyHMaRd34IiWJsrc9YIuiIa52YOVFNZo2OELtZuOxeE9uMY/mV0QMY72w4fFMbPNDHIxl2pFa/NwUnmmtJYcQeleE4nWW+ZrQWwyPJ1NbMLxYuAOBxWoWO7VgG/aV3Q2W7XaU2YMhgk9akitwlLTpLmXamNnbcq4F3QvShSvIwrWu9V8abNIbOS6MeprN/MWqaSURxvlc4YVwqmyCRzizENoKe9GkNL3zh8VfjswcKfrG/FOdJYKk5PErdVOe2y3muy8434p8UkNyRz6kXmrGH+IfFOpDe3awQEdjvAjMytWrYGv6s4R0li0YpnpWH8U/8luuaea6RuKx8H0/bt+K+Tf5gXyX+MLUsV79o1f8AL/8ANahprDoWb9I0/iqiyX31pd0rct61bBe/bN+KqLFV/s6ZqdC6DRyxEtcCa4p2kF1wcrb1m/jyC+y+Dq0UmicZDdvBv4J9aimY3Jwoc6Lm0TD0hHlaHYXslmT2IjHyGcfzVoNPVUmFKpk8b2sMbccNlE1kkgkK81lkWpodzkBSi3JormpXH2afeiHS6OCuY3dyc2ImN/qyVvU6UIZ3tcDrNc1uDggYnNHFwCqVJ4xmMkDGysjqgNz/AEiaLTEbOTlfFEZ7MS63Rvuuiadm+hUcdmpfN7PYgQ+jQPS7ZOCwk7wFzx9lecl7LqoadyDPGIZx/hsosgtisseia1+jq7DMlWqjy3z5a2uxTQWe0yR2duqBG66r0hMjt7sVHPFqPYaheO2cXWPF51N68XncL7BgrR9G73JlPZRYx3OOuFceRQCuC8INNPNloH3qMcVDLWl14KBvXgnlv6E6Sh3IuqQTt+snmRmmaDW57XHoVp0EEdnAu1DG03qzvjjLpRI4EgbNX+6aKYqzyWm86+64A11Bgr1lZF4xeoXMcagcrjI9rBd9Y0Qo8yV9gVVw2eeQ0rVjahYeD5frOQLrDaGrFkkQ9p7cEPy0CTap4xK1zKXqqVhjEoFbo20VjMM00T3aSgjPOyVhZNWKWGS++c7uxOdJI1zWakeFMFb2RgUaWZbecppJGaRwIcKuyNAm6SBjWtJ1tPdUbJDrbKSFysvVf/SqmK6wHevBok2zM29Ks4eKjQj+Yp944bAjq0HIL4LWbSmXcQSvCLX4hxlB+wFDH4zoooybtBmrTK+t2OrBhmKrRtkEVBW+CcehWOPxjxcyXtbYo6eFIZ3bY72OSlb/AMTjs5w82T0cEWm1OwNMdivUuWiPmuriV4U/Z/1I2gWyzXAwyXPW4UTfOXKi65T0nE3mTlsxC8ItjkIldK4jvUX5NKJhg+U+sjddRENZZJw3DWYjJorOwey1qcJ3C90BWmpyu/ipXY3b9WgjIIUTo8C5rBiDgrWwnEWfP6zVbGw2oNhEzmxgRtw1uCDTaW/u2fBPNqt4v5NDIm/BNueGHH2vMNoOChZY7SZA80e+ZjRREN8IwdBbAhNbPCFyI5DRtqeGCADJ5TvcBX7laXwN0ejZkW4g0VXyXiJKVLdlFqsMnC6i02SaGv6QhpARheHPlG3DFVuvHaz4KovU67P9Ku3iK/PYafwq5JemJxrqj8F6J/8AD8EWRX43jGpaMlcdPIyQc4tjaUDZrXpWbRom3m/cvSH9034L038Dfgh58Cu+NnwWl8baBj+ib8FedbmB9aXbjB+CNfCjelrYWn3halpe76jP9KkitD7zBHeGoBt6ArYHuIOnd6vSvNODt9Favq/jyDimzXnG1k6rdgUkj6FxeckThntXMBXowsuVl6urWlFm9essLw6CsCVg9Nj3Hlzz5czy5qXnG9hgnc4PA2lWqDSRsjdvOxU2owzRh7JY3DuGClIJ1aYqzyOxJHJFG9wZCRWSR3qtzJCtBhbci9VnRVOkLufjjsVW5HcrBvuu94VZG33eruG9AsGCN1t26oWhxJBre/aKlMAMHAZOV2LwhJpCMNXEncjfNIRi9vtdCcI23y4c4c1gUjC4OLDTDLyg54rZ4TeefcENygccnyF5Rdia5qpBA4LeprBMKxzC62uxUydG7HgnyNOD4jTuQJeyM3cL6Ms10O3NGCPU/FeFOs3+pQdIPvUV9t5lcarUHYpYZIyWvaWnHYnFg1aYDtRo4ULwadFFaXwuBBu5CmVfihFEdlbu9MNKF2wZrRNtM203cKBFr3yXfnP/AA5bk+EdOCr4sxx6cVkWcHkKlZDxeUNUn65WpGKcSjobOOxiu+L6h2Xc0WFsZ1L0boRizoKZJa5dA2IGklWileI6Fh4edv8AlcXwQP8AxetNvjUfwU48G2rxgPpepI19M/Z4qYxkObhiD0BUOSYcxWisnRfp9y0Yc1wpscvBZpzXx/zKCuehH8zlUuTrrSbu0K+7VCjGNCMlHI4UbWoVrbTWc6QAN6oWFkmDBgPNlH8jnLMP0Johf8HyA79G4KMStGteoTsUNKFw9b1sipJfNUdTnImTR3Tsac1+TshjfQi8ST+CtvjEkT9MW3dEScq9HSmUiYSWZkJmnikdGOdcCn0UVoY7QEEzYDNqtji66BI4/wARWjdaKDpXmLZZXcZ2rU8V6bsrPirrnQjhI34r0kHZK1WwMkbIRc5prvRdG5kobgarzsOj+9OkZaWtLm3S1zaK0z3mlr4Tl1grXWvpX7OlUZW7TCu9POF04uVWDDpQYyKMu6TSqiv1mtr+bGx2ARfa5jPaHfo2ZBYq0llb0mGKcIxRt7oWGQ6GotkBc07MFFNDH+Vswcz2loZ4Gtnbm1C6Gj2gXKC/cvSOwumtE0tjLhTcvQyfZKcXsc2rdoVrvyOZKHamGHag9huvGThsQoWstIGMb8njo6V6JoKaZAAW4aq1sdZykNNZrs0RRh6dyc+0A03RFTOa1zCYjzjXaFa6Qxl2mdrPF7atbH7lPRt04Vx4rNNNmlYJRnfNFrWYvbsdHrBXXxGF9CKOFO1V8YeziVq21YWolatpr2L0jD2LHR9y9G1YwDvXoFrWdy1oXdyGBHYucvSBYyhDzzV6Zq9M1emC9MF6Za1piCcxr79NoUnUVslAdpGO1aZZoGKXSi7moODv5VaP97VZjJGH4KjIWKSN0Yr6rm7Nyl6qtBhaXywYSQn8FdtlobC8VpHmQrNtuZFRtGb6hBTdibK7Mbf2y0cIbdcamo6FI/K0y4muGiCa+2TBkbPUJpfUgs1261uDRkidpVI2F56F52RkLx6jnYrCNmH6QPGKx2IecpVCOOZznO13G7mVK4GrrpoFZrIBrANCbG3EtGsabVoImyPL8MAml8YZ9IUyR9oYLrq6oTHy2Sad7W0Lw+lUyzQWfRBzXMbj0ISMaXXfZTSYZS7qKni74dXN4XhQBl24WDjzlGbTZHujGqKtVjb4NhdFDQ6S82mNFUo+dblTNXG4up/UgXWZ72g5XSvCANmNnHm88K51Vm4VxVphZXVeeKN5uzHBMaahrxUVGfLdc90Y9pi9JPLxVNC4jpWECws6wgCwaFzm96Y/WbEWnXa/ArRiB8rJKiruYSg6KwyOBydfR0lniLdokyK8JyEt86WG60YDnLMdgTm3qUTHVvmtVZbo9r8FcN8Oa6haVY6V+UMp3qAj9SP5nJ1/mbypg1ujDRsXRuTLwuNa3ElDM3cimwxxRue518iTZ/uiporPXZqn4oxiGzXelp+Ko6CMn5oPxUOls5Zo6+jwz/8ACDmtnaRtDsV6a2fvf7r5TbP3icI7baBxkITqWy2Z7JzT3qNjhQgDkfU/oj7wrWADTTSYgZi8uaVzK9i5qxauYV4TqKHzdNntKfrLEV4rmBTUGcJ97VbLslPPP96aHGtJDjREBrqlP0LTc2Ap5cC2NlQd5O5SOdVspwPQFSufJBsZzlI3oVOWOTBj2tLakZhGOV8LH9OagkZI2RzB6pwXomfZPxQY9sbW71g1lOkIuOZNcFVDYRt3JsbnaO2AUa79b0cU+OXBwwIpkrt4DWO1SDe5SOO+gVcFMD+pPvCtmv8ApXe9b+KtHBv4oqrXEKrLTI3g5SSyyF8grRxRcONFkpeUhEaU4L0n3IvedetE5rmMdjTBegHetHo7mFVkO5ejZ3Kpjah5pvcvRNXo29y9E1ejb3L0Te5ZhYqTqqVrDiXH38jpnPDLjCRxUjga1+KgANy7jVOke+pGACdiDgRi2ual6ikjscksEZfrPYVAwR4yx3iSdqiFLrg4qJwFc1500T8zeogGQaRp/R0/xVe0UUfQWj4IuLoy45mpx+5flTWSU5tFTQV7V8lB7VqWZjeCvmyw8XBYWWL7Kq+GFvYvRMcc6ALEADpVGt7Vdmc7iEWSWON1MpXY1Wms7ImtbldAQlacHb80bnPKJnIO5MvOByJI3FfkxE2Jxc1HTQk7tE1YWecrwo57Cy85jsfrK6bNEK7RWo+9HRtxca1Lsf8AeKxDj9dYwE/XTYhiG7SKrNv7v+6tl45XMhT2k20NeBK3AauCfJKdJM515x/BXsSNjQgH1o3AGlaIcl+aUQtHrEE+5eb8J91lJ96/5lP9WyD/AFKjrZbXnf4uz/Uqtn8IH7DVzrceMzR/SqaK1P42gf6U7zMzC1pcJNLex7lpjPI3W5gP3qSKd0zy11WXjXihEMGtOHJbfqf1LEjtwRuuaGnpUmkIoR6qsxjjledb0YTpGwTAOAx0JKsMjoZWtjmaT5l1M1AZjgIB6tfWKLI23AHFoaNyn6RyC8SWj1d6M72+bj3706R2Liar5K1/WT5mMuB+xq5rlzFgyixZVUbA4O9ovr+CbQHMIGztkYPZeV4w6N00O3RnELATgdOxPkgY+VjmlutgQi13gy90ib/9V5zwe9vCWv4L5FIfrf2WtYJG8H1/BfIZPtf2WpYXk7jJT8F/ysj9v/8AqrRpLw1ti81Kx/RWhWu27xT/AKI+8K2fTO96aGMBiaagJkIa9mJD+lMBxpiaqOINpjpHV2leNBzH3ucG7FhDIfqlfJZB2KJlMhRVpQI61Fmsws0XTgGalNLtXypn2F8oZ9lfKGfZXyiP7K+Ux9yEXjcF0b2r5TH9lfKIvvV6V8ZtMQoHs9cdKMczHRFYHFOiprE1rsUZG0KXdoT72q14fpXe/kmNCKgI8s31vcqckvkO4nkPXU1Pa5GcD5DfzEnVU43OPLxH9Ss/qOLtqMNqjFoacnVulqb4sHTP/V01gN6mEkboyGZOFFfY0MAqDcwvcVBXV0UIPeoCX5mhCZjhjUb1FHEMdqEk3n5gMnZBXWjs+suaQvisS0dq57e9c5veo2SzNZe27FhaYquG1Fmk0gPtDJaV73FpyaPVKDpJax0u1oiNMWRnbmo4oJNKy7rOrTtTxd1gaUT3lwaBsAUkccbY2ujDsccU1rTQhAuei5zroCkDZAS3o2K7KJZ31JvK5FYage0vkkDeyqtxefY/qRCG7yfCH7P+pYpzulV1S04HHmpzbO7zeFL2deU3oG2j5jjQFG54Nslz58lf6k8eE/B1kkceYIxl96BZ4Nsbm7tCE19kb4P8HwtyayMVPHBY+FYGdVjv9K1vDMjuq1yMbLXLMdz8B70Gtu3qb0a6FkzRRrt/FOif6RkobyW76n9Sx3I6ykLsdZcyLuKja2Gz0cPWafivQWU8Wu+K0s7Y23GhouV/3tTukoUdTSNqVchaXAbUyEMcHuNEyysHNxPTy5Bc0LmDuXMHcuY3uXo29yFI28h0b7tcMNvLrxhy9GFzAuYvRrmLJEM2rNUa/D2XYhP82GP0ZqW7cQrWWStJ0rqtJoc1rtI7FTYg0QN+KqWF9c6q7oIpG1qMFSKxY9ARaGAAqtxuCDC5jXblXVf9UoC62jshRc2PuWAZ3LWjC5jQsmdy5jO5cxncsmdyyZ3LmsXMYuaxXbRGx46Sq2R3mTuNackWGxT3f1J/marWHH9K73oV0le9Ax3txqnceSqk6a+5c1YGiNHVryY1qtqOG3kcPnKXrcjD0HyG+WAC2m8lFplZLWPNitAOGsUeRlP96yhY8Nfdbhqp0b3V3UWms85ZK3ItWhtTmyXBW9d1intI2lMv62qGG7uGSbwVn3VKdJM5zI24Ub6ykgmfMyOl5j6lSvgvGVuW/wBIsy7tKuxxxy7K4kqr4mtm9iqdDJA1jhsTfOtp6yGko+mw5K7uRqdiNck0NBw2qiDb1K5YLUkF47giw3ngilEZH6tRdHK2zB1GsF48Vc2PaW+RbPqfiuITfJ8Ifs/6k4blcLqLVIIHQmXWXa56vLJv3Bcw/ZXMcexasErh0MK+STfuysYrnWeG/iteWBnWmH4JjmSNmdXWuqOVkQJc2vOT9ZgYcqEEovmdfdXFaRvA9CtdPm/ioqgNvN5qcF9bkszuPI9OAyQiZnkga4lS2p4FRg1F7sSfz2OH5qX6I+8K1fSv96oH4bnYrmNi6qpn85YOoOQFsj2dA5WPPrMzVlpM1gMAqFG+aeMta8Grc+laNj7FaWg4SPN3DgqjQNrtZaBVSWV8zHvbrtdXNqpgVzU+VlnbO8DBpO1McYtQt1rxGHcslzU5xwAQlfPcDjqsa7IKZ77Q5k4pcrKBgtFZrZ4wytC/SZjvTmktIadXKvJdJ2kKelPQn3hW2jcDO8g3ulUuk8FkRxU4+dyv4ny8li1YCgVamvSsCCg4My2qjqrb3KtQh5GHJ6MlPcyOlApLxrqq0uDwwB5zRHSgmn/fOTayCQsP3JsujFMy9aWNl6POrVPTcpxXC+q5UVehQVdTNROjDXO51F6B9+n6JmATmQD8ufk2tP0iH5PGwj57fijpIQT817B+KBdZ6/tG/FY2evGZvxWFiw+lb8VUWOn7RvxWNix2edZ8VhZf8xvxXyT/ADW/FXW2PH6VvxVfFKftW/FUFmDq5h72/FE+IAv6ZW/FV8TBG7SN+KrJZbrdjRI34rWs1G9dvxXyf+MJ75LPQk5iRvxTH+KVa0/rG/FfJv42/Fa0IZxcFjE6TqlvxU1+Aw3qUq4GqDvm+qgh5HhD9n/UnJrtGyTrhYFn2AmxS3KHcOWQNk0R9vcv+d98jl/zS9+1ctbwgDxkcte2/wADkfyiR3VjWAnd3BeasWP+JJVHWNNgrgFihtTWEtEUuo4vbWnSrQIxg27rAUrmnOe2pO0qpAIrsK0bIzGzrBYFzu1Ulia6laXnc1a01Ebshci67hvRlMda5IRNjpvO5R2eNjrg3Bejf3Lmnu5cBVcw9y5p7lzHdy5p7lkVkfIbBam3JRlOArp1h7TfLy5JPoj7wrV9K738hZky7douOfQm8udOQR3rjmGocVZ7tnJ0cdwlpvdqF5pY7fRAmJpcMCD71r2WO7luVGwiKns5har3U4qkTnudxWu4t+sqaTHdeWveub7yGs6vFPv3nN2NJVNGyp2VVfF2Gp3LxdrWZ11Pcpb0TqEChyAxRhdLoXDa7JF8dsgtGyjTjirQ522L8QrYzN2ld71XkfJpKXjlRemPcvTHuUjL1cCgfz3Nb2hUuU4LVp2rmtKPmvevRA/WK9D/ABLIKUOaKFqk6qvZF7zSvFO6HfirO2uvcqUOH9SDY6CMHWw96a6+WXcxvQG8aw3qe7gymFU6R0tC45XUaT5/NV4yn7Ks90OdStaBAMi0jK78lo9HTpQbYX6KIZtuD8VrWnujb8ESy0gN+jb8EPyupP8Aht+CLvGMOmJvwRPjQw/wmfBY2qn7NnwRpbP8pnwVDbKfsmfBNpax2xM+C+VV/Zs+Cp4wBXIaNnwRe603G/OiZj2UVPGQT9Ez4KvjnZomfBYWtv7pvwWvahXoY34INZbA6Q7NG34J7LRabjwy9zG/BMibaaxc7CNnwWq5rfqhel7o2/BelP2AvSH9234JtWXSNwTbxzNEDUdy5zVk3vWDKrwlDIKPZo6/xK8mAHHkYVhyTMq1t4ZlY2qzjgSsbbB/F8F8uj+w5Y213ZCsJ5Xfsh8VlMe4LBh7XV5L4CrySllOazLtVL33rMd4XPb9oLns+2FjaYBxkRrbIeyvwXm2vk+5MFKF3ODUAEaEt4JrQ92PSmsa4kDeue7v5cDTgs68UKOLS32V6V/evSP+0sXnvXO8jAkcFznd/l58jo3UoIycukK0DV55zHSsMehPtbq10xCdTkYmBoDicTVBw2ivIQeTzsbX9YLSWeEwyfNyTQG0LHc3apXuaaO5CShrgfVV+829jsWBQduXQvkgaPbvbEXvNNjR+KqyFoO84oA5J7nxvOPOovNgPPzhVTV/VEjDpCtLy8tdpXHLpWE+HVXO/hWtGXrCEDinRhrGSHLYg3Fzw81AUfSP+i5y5o5ZT0UUvV/FNs3ibmyMPpS/A9ikQ6gUcNbl4Z9quMr0mmarHWtfuROiPenCuIqFo2Ek8Vcc8xvHtLztoZIehq820J3nMTsKvSGrm7lgT2q6T9UK96vsqsWq3aE1gaM9q5mCEj2UaVzRTctWOnUwV54IGyqLAKuKN6mO05rVld9Y4pxdkFcZEHE9Ke1rborkrxF6nSnaJl2gqcU5z3PcdgB2qr470tKYJrPFWX/bftQuXIgcrjF6R/eVzit6i21chqUWu4NCNBeK1QGLwy5xrUxf1I0xoCj5wV2J2kwcnSS2dwYwVZsrvVHQu+0naKC8G7S+iljeyJzSLueKZaIrTp2XrrgWXS1XjgFmr1a40p5N3ltptELotJcuh3b/AGVfF7vWfRa2gHGYLWtVkb+2XnLfZhwcsfCTfqtXy53YF6R8vWVI6Abhy1vkFc4nj5OuT3IgOd9j+6533LnrP8+/6I+8K1Y46V3vWMl9u5wVMrsrnclByOruUe9uHLmtYBwWRYtah3EZq62eQDdVYTuXpysbT9y9P9y9P9y+UnuXp3fZWs90nQtlFmsFRkWmjJrUtqvyjwV2xVanvg8YbIWEFs2VKq0SwW2N195dcdxXohIN7Vrw3etGVi2I9ixjb3ol0Dq77650jODUGB2q1c5veuczvWbPtrMfaHJzT3Lb3Lb3L+yz5M1n+Zu+1Iper+Kxqnva+MNcelMey4AGhRRnYKU5MVdjjfL0tGCeRFdqSReOaHjLxZi/mV2rS00sZOcWNU3xexSMbdxv4e9azSAsBgNwCwF3atchCkrQCudeX4Kh1aItDtIOlNZXLaUXaQOfnQDYgeajj2q9pKcMyvXr0qmCNMR0IaN9DtogC0O6SvNuo35yIZzygA2hzNFSpB3uQbs4qOJjaFuqADh2pgvsYP1bcysb/cuZK7tCsmjiuNa7aty9YqrW9i1mgheFiGgA6LLL1kXCyC47Vo+RuXeg4WUuad8jPimHxKOrdl9nxTAbP6tHHStx+9OcYewPbU/eh+S3cKU0jfiqGIj9q34p0bITpMzWQUcmt8QrTLzzPisPB3fM34oNNhAx/Ws+K+RD96z4r5F/ms+K+R/5rPivkY/fM+KFLIK/Ss+K+RD96z4pl+xi5ex8634qfxkXS6lKvqsz3rLlw/69/wBGfeFavpXe/kt7XOpo8QPrJtTnynqqWPZzh5OaqDyZrFbOxVoslks1ms+XVe5o3Ar00n208Oe53mjm7pCtIEz8JXesd6wnk+2vlEn2l6UniAucO1gX6L901a8bOxoQ/J4u5Y2KA/aH4rzng97D/hTFYeORdzlqeECz6SNeZttnf+0Xm3sf1ZKrBj+wrmS/aWU32lXz/wB6w03dVejkP1F8ml/dr5K/7C+Rv+ysbC8/VWt4Nl7FjZJmcWr0Mn2SvRSfZK/umaWDxkV5tapxl8Fz3ScNHXBNNhZOI61u2htKJrnebZerda/CilfFawyMnBt44IB1shLOBJWNp+5a1old9QfFC8LTJTYXUCrHY/tY/isIwCNujaq3pO+i9Fpa+3IjD4kxgzvVKrpBT2aKlMclirxkAG5E1V57r1Niwy3IGoaVqvRY2R3SULzqIGlUMaDoWLjyfMRDdqxiN7vXNDae0i59SVUGiI0bG4Z0xK5od1kHXmx0wIbhgrt2pd625XNJeojRzXt4oPaMRsVZYwzoBRoc8k53rBYqbxKXRaSl/VBrTs6U2tpx+iZ8EA61E9WNnwQPjIxNA3RtrxyRHjLa/RN+CY4WkNF2tNG3PuWFrAH0TPgifGwQPXLGU9yP5RdJGFY2/BU8da7hEz4L5aP3TPgvln+Uz4L5YP3TPgsbWP3TPgvlo/cs+C+W/wCUz4L5b/ks+CoLZU/Qs+Cv2u01c7JujbgO5fKD9kf/AAj/AKM+8K1fSu9/JbW15+A4JrfUGQXOr1liKJrvaCYN48nHk5pWRRBDsRRNNJMFtWZXOd+Yk+iPvarX9K73/nMgsCRwWpaZB2r0gf1wvO2aN3A0WtZT2PWFoMP1v7KrbaXcKKukkd9ULKT7DVrxP/dBYRzn9gFhHL//AFwuY4f/AFwtanbZys4+2Fyy/OYlUaXBUKOwK83E9K1gGuQpQ8nNvKgFwhUOtRUH3qrKU3o6YXnKowaiA0OQ80QVTkw5ywkNVV2tXp5OlFw5oQqg49hKZpJrt3ItCvB1KbKZq+QCNpqudRXnUunm44ppcMD6p2J93JPGd1Ndq45gIgMxOVFE7VGrrEHFGW5epvQDIm3nYUohjeO1Vv1psVwPq0epsKphxTmh2tXauauYVzCuYVzeTEq8CQ7eueXcf/hZPoz7wrV9K738l9uKxasMFjimVFLooo72GxYPXPavUWLR3qsl6q5z+9emm+0vTyr0svevTyd69PJ3r5S/vXppO9fKZF8oevTv71W+ZG7nIEMwV5rcOST6I+9qtf0rvf8A9Hqm7wWrM5awD+K87F96xY9nVJCq22T8NKtS0T/vCsNNIPpitVlqaN+kr+cyVb+PFa8lOKPvRxVK5qgxNNvJvVRmr1BVA0CxYKjJa8d1vzSvm7ldcwBp2hB7TUINJPWV/Z0rAgjoWOCq1tEOSl3BOZzXbCroVxwLqYYYr2XEYIiQXh1VcaCcclUuA+aSgYNZqLqVYck6W6Hk6t1E96LgKurzj6quarWg7SqxgyE+sckalldxNKK9EGmVwzZjdCu7fnIU1nIVlAJUjZJpzQ4OZHVq1jLGdt6zlXGOvv3UouYFzQslksv/AIiT6M+8K1fSu9/LzVgsliqrnLPy81ms+TVV67eHQVnymSVtTXeqMaGjo5JPoj72q2fSu9//AFOrI4dqy0nFG/ZonDcJPzjqivFOIwWOKu1wVQcVfPOXOKHk1WfIK4jcisVc2Ii8/HpRCoDyltcE7ClN3JGxmAOsU3HnZlNa04OGNVda0dqEw56rfOtmnMOSfG3VaHUwTg5xwKuN1QSrzgXGt3HcgxuqOhOOZG9VqSaqpWaje8GU/PV2mrTJOEdB0p7nG86m3/42T6M+8K1fSO9/k4hYD89gVSuCfTlhpu5Zfoj72q2fSv8Af/1n/8QAKBABAAICAQMDBQEBAQEAAAAAAQARITFBUWFxEIGRobHB0fDx4SAw/9oACAEBAAE/IR1HLh7R29sx1y3B8Bxf25jwMANV2irQdi+8LjoMM5ES10DNldJ4BK6joj0nyKLhcQCUcDqdI6OKaG67SnDdBuZ9G/v6FpG8TmLB8IoK7pOTtAZjynLo+ImyteZiqY24FJ0cHbNoyAm7sPJqCeAM4pJkQWjc4g3strc/cEucWzfHWGAQV1HEWNHYr5TBc/lMhi6zLmIlB7q9pdr0qj4ietstHWnhAkfcrjawMOUs6SEc/uCQ3POvPU7xD8t6m4zifgy8x9hmp/OH4UuUrtO80FRFoz5esDV8/eeZa/qQRh6MOU5mbh9VjAdI5aAOHn9IM/8AFT+uNRcJPsP2inK5GolTLQvObL3M4NgGkzM2rQ9ZbFaJm7TNSph6N3T7S7sGWVXJ+02WOeS3V9oV16Ljr0PWUb68ynWX/H0qckD3UsoKvnjMZDmpvrCcVnqU7hYg9qfBRiilQZfdlvtRoQr40QrQVOjKqIDJOcGbTY9ICIBVk4dY3gRfaV4bQ6uR6Yjy6YY8YzUdp9Ym7lqkVJwdKKjQCBoeCUcwsteBN0wYnhnUoPKm/iHdc0+8xBxkuFLzA0DMV6DrE/CRaz3g+xkYH7Zecg44Skr4JjTcrhabXlbvggUgVV2l/S7zhKxmjx6EJZ3n8neZfyqmT7TIwCd8NQUxaONwNL+fSHNfMVbWJi/RdMzC2PpLxMj0n6BZXJUNuMQWl3xFbH4YywayaJieIQvgi9Fl+lzir8Q2nHmZ1UVeLH9WCuzN88JlI+BydoJ8icdHaPhxipv8ShchfDDVv8uMZdzmbncQ0/KjFzEAb/aU32TbFzQDZ7GXEM/7E8i4XSBlHPK95VVtMBmUJcebfvlUNLZKLTtqZFfkMR+7pMsoUeLbDTa95eQPj2sMciuv9X/Z752/x49ogBs2xY5yGG72OmARrTuv9000T290el1xh/8Adcdpy9EcHgaDcQMLNoGtn6lSdNJcbPYfEOcOn8xKO1WMJbEnFXT2jZDAXhMX9NT5pmGPRv8AGJ5mk/uoxAHpWJQg/wAXeKXVT1kLLqpdT+HMgzX3SOn85n2GKbQHBwRLSnKPtXkC9XPiYIIjY1WRddIfpAi0nfoQfpYMRda5Zf8ANDsUECkCEXNY9rolpFbkPRgFl9Zwgae4obvJhrrGw3+AxByuq8zBQqlLgSNc+nVBRrFzt0iEbZgeFHv8SzyNHvmxyoFPOamtFLOjp5hs7CJMQ4ChZXZidxPolg+BroSla9kxxiFFVHbCZ6Ja9ZkjuJWD0/eO3h+JgGU0zRo6/pME68CpCoaPMUsW89YtnJi7raZgbXuiLzuGI4AXrbai9iDa4uZFFsMthPECnN94RjMlm95YQ7CGbWNWGgoMXM0yewg9i+06vrmfjQSGUGvRMP75mSdT9oM+zDiHTFueCel7rmVvrH0qY/r+8vEW/EKpfSAKlwBm4xItn3uazzkvNIE5b5SgVCL3yOpxuLmvaLUvfT0ZHCQEz92UaY0FqVMXxr9I+tqa8fOC9S/xCMcHMMb3a2UZCWbqMey3/MyTin3iQHzs2KvNlUNaNgK6UynWxjBqJL3YKa9Ki/f4o1UeFkvFW9ke8yiFGtekW9LvMogazAzrL/vRmrdLbwh2JZ7atV+Y+7m7GUB8SgZfsyyyXjGQ951IISKqxrvBnU2Nj94c4e/ZANoRZp31lg5yaJX8XL8gemUGpFVUmcstdvKXeMjkIspgswzWh3mEWqynUO0YRyZ+ZlghbILDHQMouL0BZ/Wo5lq6iXYgwHicTKM9yYIiSyXOwv3Y+1+4lA6CODu/afGJ3zAyAWhm0xN01zLJRdDeWFk5TEL6xtTFef7p9eIHr3Y7w93HSCPEf8m0ULWm6vllqLKZrF+8WimKus2YIElfBmHEDTdRlmS7zkZx9WUzJDDtxfzgKlOLHVIs7gunnHWHdaD64ptC6wHWtIsu21iCKKA0zKQuAuNx1ZLQ1DSN5Yoml2YFS9TtSfuK5qm4H9ejvgjddB4IbSCjeVcADGLKos7TtvhMqBsslAdGL0xMY15qziV+8C/Mtz1Co9lxcpE7Jt6wOp2uIzWDSX2gLDbOkusKwNHZLxd87G/PEGURAnCLogJitsbd0HMt0Ql6GKaMEDU2OEhsJn3/ALUtpr/zc0CZ2ZTz6A9tI+k2oXV1+2wTB6A/n9F7hvpCfT+gxGIoemlW6kJ0DfSW0bwERlkaZRLj38Q9FQEHV5iI72ahYY5ehqYeDiPbzWFapDqSrWWx5lqVHsmp6FwmnTTFDjuSzY8Qxp3pToUsNgifhlHGjn47Q0nj7ZnwVEHihC+Y3cWf+1CQUDjqJiG4oc4nZFQ5d5WXvOQDd4h5AdssXQ2b4mPKuBDLFLge6DpivoxWXkKuFqzuhsPmfB3H2DUfj2fszPDWtPWD0MnBnN/DtwMrYU2nRbrzObDo9z/Yaeuj94Yqp9WtdTUq217GGPCi7gXVsMh7IPpsQ6rC5pWdQ5IuIIIVCSFyURTKdojfPeLoOInW+ZaENv7ouCCMzWPilRqXmXEv/wAFM0n/AG4cRsPU4+I/rHlZiL+ziZosjqC0YKfDUy/cy7e8NphZcuYZZmWO+ihUa+y9JWVPeAKr2ExY9ZBS1mMU094IlKRZyKOpYq49bxxOO2db9If5P6gN9s35S09GDeJEVzWpgG5LjaJLrnDbi4yKBW1xbp6d2cnGC1iGDIIeXmGPGqlxO+dEXvCtu8B7yFNhPujAbYcsWRV0t1idOYgaUPcwCAUuiuZT5bpkSWh7IjRaeDGKl+oi6L5utG55ikKWM96jS/khJMCvERi0naW7hdt2946AFxYx36zFGc/gmXt6qlChEtR3BKDK51ZQjZTGU631n0UG0R/U6S1QUDoV9YzBmdgrxTa7YlQTCFbdbUME6Gos7P5RV1ehchnIysqBZ4jli7yyezlbCAaL63KiGMYr/hh1XRuZQZ9GfXSIGrPmVi5lZtZqPZkJlo8fM2tx5iwHwiu4BoYYG0l1kYd0AkjfVE0XVuC+pT7RWe1rucZneRwZYovUYCxrRr7tsTbF9JZZzY/EtpK2elwsXs6wHyvrLOl3BrOk0gl6rRog+NgW13iU+UDE/wAZ+UINVf0bIdCvsbWNzNXNn9zD7TMQ8xNq7GljxKDLMZTjkdZTMLPGFYYL6+YlNHEyuWKXFcS/KOBgeQ/1hzv0V4hi5XLMWUCsK/jCK/CBj4BCLIcRYqi6jLSOf9JAWfCIGu1QT5IDE7cvKCb608MjLr+pvCu8d4cHEupFoLmtHO5FgfUcx1/PlK9yfqPH/m4naQ/o9Z8oqB73+0JmRDJnOQmD+6eeZp8Rf66Km9ItTmm269fp/wDqmQQDAY5hhWiu0wYXtKxevMA09+UG/GzNhnMbLQsslPFQd/O9pVAOOYgbriagGj2hcU0WccEDgocHSP4kykBGIIPeh5ZC5ZFarvGmcoPEVNSwlQ3yhvFf6gH6Afx2ioCO7oQFkbNFtX+Jz9hBBDABFEJnjmOswRlfsQB5NYzCHt6fZ94F8vn7TPvv/EsRAyszJZh856sS0ptlXRLcAKe3EOaE/BOkEnfZLl3+ahNMOlBylNU+kJ2yJ8sy08J+80JY5l4P2lig18+mZh3DfgfSlmPmjTuniK3Nc7ES9xqGDaQ8oLoFuA5GNLq1ncwj7kChjoSjn6S/8CX6ahfWKecRnJUJV4pgIBtXMeL+ZmJlRdhrrJz38MGeHTa/tEIsN53D5w9Cz8S76HDAN7MeuuBfzDHkuIgDXUzCGk4F0GPEKUneMJFgeGhrXPfuYxRd/wDKB789RXhKukrSng/cpDjBRf1mqw9QeIFySuUVbQsVzuWRuut9Zr8QvSjpzHbZJi+fzBn3RH9mpeDwm4Xf3aT5iHeWMkaJMv7mUk65Y0/whrKtMUtXJ71DTRV3sQvIn0mKAI9Er4Vbh59GYnSw5ByT0loVqtiDPWF+s1Dv0mprvAdpxbXiZNQOQhg6HnHmIMO+qnB6srdXMTDeMPmf2buINWp8HxYRUuJ6AdejnUmqEeMO2YDzM8fb8RgOn55mOk15MTvcQsadIcFs7p1CTSKqiVqzA7XeY42+q8zVZxF/lCihOjETp7Eza8MMdrtAUA5hWzyq5uYuiZ3o7ZiA7Sxcb4KxK8pDvmUl0GWJ0cEEVzgmWWe1dfUixdRU2p7IxHCCx2wwbswW6VOLIXluNqA1piW3jxBwNXxpSohnbus/plsJbdXn5iJgnXSYsff70VQcPtBUP94lmd6/MsMtReMhNjgLJj0EBjFjD5IyZk3WXQtT710jmdGzAHZ6ykaSWGQJsWjgnpmX0TacRCoTxRQZU+7tMifBwHkDDfkZ/H3hwmBgfGJgn1OaE5+kfhjj4Sqg/voOoEzLYkOa95S1uoLTtF5dyP8AdYjD68K1mXmZ09DwNQBTwi3gC6PRQquCaxOTSaSpF7XUnLdF1DsHsJlC96j62YAX9ZP9hL+PgmBZeCB5IosWxtQHor7S/H1uusoKBVYzHXGK6ma7Mtsy8cRX2/I6i4KdlnG5pXXdUop69O0zsxmf+wBW1TRVBkNdEjbJUMPsXTLSVIeFmGAx+3r4bh4m1WuJW2FVEHu9kLmuYNLi74g0cliyLpKUIDpSDPMXH85liQvrRiCjO1+02hBRdGJ7APozNSa0CuB+pSpT77Uaj3nVyQZcYLzGwY9r24l2aDrA+MS9hkvqn4+lo7kLsHmj+hcuqQn4JAGl/LF8zO4PXjgKIUxwLrEyjtrhDrKh6C9VFmHEsNum+YBL+EFCBKgj7p93/iP4PwTS4/ZH6MB8ietcEUTRwHmZVtW/GJRNLzER9QhsktEgUQ4PvKvJN3kvJ7kHINVS3X3Rx2LqOiOPFOqXGpw1YBq1z6IKCqYBGhmFvsk4uUVRSVRQ1nfcTEfqPaUGrGIXUre8MLTQ4xMiAWNip9IlB8is6j1B20EUCgoFfdcaiCRPcHUHfIKMezGmuHcUb+kG+5jDSZe9R8O0PnFQ/kpb0XX7TWn/AGhF6fUY7cOb47RVIu0W1BVcsMvUwvshcCHQcK5f2mYbw+ocMww4d/MFbfLwSkEOWpeZm06nMULaUqLa4bSrrDl7Q+2jTwIfkg/t1mqG79HENTzCDLLovxHmIe7n6qRzC0ck2Xb1/RDYT5MrVzX2WWWOyTvpRB0FxcPtEEOwVmv8mHzlLvX9TIRsdh/M6idJydFG4N+oLtlAuqzpou3jxGWNBbao86iRKgdHugGwxbrAG6ifScp2Kp0H3sl1THSdv6MuEf8ADFamOF6c4dR+Yj6EgUo99KZjt3TnxM7eOs3NmUvmVqxl3KxlxZFBlBpuUQEt8QIxHRq788ynLYZgemWkQdXmVsOoxhuwbtXAS0pvC/KYfSZmOL1xzUvurtHHWAlC9XzNNpgVRoiG0A0MxCq9Jv8AWXDeplj2iVe9oQb/AKMztuH7RZ13dkAhp5XGuIQ91PDLDJYIoNDYu25UQK0u/oe4mQNGNqdUI0lJSluOc4xQH31GnJOQDc+TibxKPKNCuoQYGW1tZLPiZjsvhbbCg4DD+JUglxbakKKkLcOIDGdDW8eg8QVALGq6y+zi9+JiQgfS50B+6Kl1t9pi+PwMfsCBL7/44ROan5Zrz8t10YfqAZL4ZojXDm+xGxg6zwVLJtlIzZAZs+T+plkn5LHEIU4M91lJpETFNxfdKzJcwyUW84Y0HEB06TKSrAbxctkim/DDXQ8Md3iZOTLI3VALOWXzBpv269x/MS0SnUdESqixaiNsBcY+I7FtUgoc5jDY8yajKoBj8jzKxj7GqkOL+LQ2dTD4x8wbX63C7SVjiZKEU2KmT9oWTaZ9ppaVAdI6Yw6QOkChQ4eduspgkms8ZlWPjuCgZW1fTvGOxDqIFLkHEuuz36GPaXxGAsi0e8qZIo/HoPoI/BTcmlGqbYLZGM2OxNENSkO5KBjIqtxKmG+B7YVjxKBLyc+36Q8Ogj0wgt4K8VCDWLt8IOLi8naB0csexB3EgNbGq8Q73K7CwsIt0zrGrbLamjNUFdWS+1xA3eY2Os5uR39K+MG7OEHCnEmZWfGV/wBaWYU9HdYHoiQNI3hTe4qClvaG3lAmGziUMkAq+yJ6EbAZeDE58Kz046Q0GODPrHZ9qkGtYYwgOZhNBdRv2+Ag9xBRUvO5ki1w+8LWa89cTS+c8XLU/wC5yKuGPqxNK694zZKzjcajWADVOk0pGra8wIchE0XVc0rrATFPrqzHxNRs6TiU1LjERN0EZ+waesDHn3Jje4V7R/F+8EvF4TENd7VCJDeX19KqfbB+hY44hZi6N95ji7pwYrpFmnSGRvTpWIEQE8lt+/T45XByjerlnjkypiulmwYIdGuGvU1qFU4lGRXNroIQQiphL7EK3DmaMQYFWIP1nVQdRfiUM24/FQP9mov5mo9mtH8ZxHxAPhHulsY94u1YVLA6XE9cHMoOWFaGrTntscoLAMyhziAYN70bcAHeF6lAh/UXegxsEDmMITi19E1CdspmO9q5oXLV7MwcctSKorMzvDOxxceLTCKEoW+Yqr18jn8CRZ+LIeXALRZXxAZOcS+noPeYnAxbSJWuI6uI3jZVKriWBWl01kPviZUlAc4PwJjK7j4imW2L8FmLUI7SCmR1argT7JD/AKMBQNuVSdGY6DjCggyUvWxLs6mzsVwzqwZsk5QU0l0v6E6Oo5dR+Y1Ojyh+ZT7vo8/FMfA9U8xKrbQdYVdjBYiuLNptjJQ/EE0a94m1jco7BX9oTiF00gylIoDON60pGE7O+wMPyN8v7iMCt13j0R7iQMIVMZEC7vUM1C6PRFYZXn1XMGqwwOt2FC0RKRzl97mHtLUOU6bd7gc0VC4mP/CqoIzZ6sINsWQYfMi65kQrO6IUmCamZaqnBbgfMwJDw983CrOBig/klpGsUmOa9ZjZmbhTeZ0TzIpzR6Yh+961c6B4S1iVwsxbPZNWuJU20HELSqroDaAyjpd1uBCOQGJpd3r5nRHrWXod8oP3jJ+zQxRXA463UuiZg2y77C4+ME1eA5n+nTGJJ2VYjhokRoEK9JqG+3zKxi3S5nKAL76iIX+ITPjUGXaLSSGGLlwMTAL94UO7AWKOXodpWyKUkUdWCjXi4d7zK6oFZtAwxEKha4SqXzEClS90q8ynttA9BOKu8YxkK5mnF4hSICWXT7QXKogqMbdEdkzPI4XjQkULAHNRQEX6l3GaKXNR+XeBMnVuXe1OYoMpBMe8ARWtYY5PID6TkfMjwG9VLUCUc4bGKv3ZRq8oKFXT2le2LmNt0R6VV0tXAxHKYv3RzjSBB0IMfwWT6IMHLcCc3weFaZ3+IvmgUwXjcupTQc3wYR1kkvoJhZsb5w+/KN/qEL4jV7GUwhCtuM/eoWPLHJeGNuZjvGJY/S9rhlR1QKZh2cE5y4t+QSiuXlQUSAZeO4qAX8sPfrKIxXK2tRLJboIpiAFxU2EIbSVJifPPA40u0JUc40xtZDq6yj6Qy+jj+P6D7qIvK6maebQQLgirbmWHuqYN7esXbMM+hFFL8G/c6hUxO68QQDOYoFgollQLcZqWY6wl+PSzNkrEw+jF7JUrEp6HokQKvUGJWcMW5cbpZyghiLD/AMIlUBK+cfqXDLrVHGZzcAuYNZdwZ4vtGS5KRIPDajp2x4zKwzdYcTniIQjLjQmmKwuN2oh9LvWIYJivrNCsEDY4bxZSrTg38JUVfVPxjJBLTJtJfLMDe0Ql4FDg4qUjqWneI8NY/wBwyl1JW5Ugqp8ZZRlEBUmxiyF2hg/7kmtk7J3HSW3aP3mL2ZioQHN7I7VjttTLx1GXfepkD0jaHIvbUrZMIqY+acltSwkVBftwYA7K9UzcRwKQ247xoAIioSqlbOK5+J7199tSi1UOYPrPxcORtQHvLXY1PDMValwWB+HqEDXWKBUtjPMJLQ9hvMmKA+cD4ymMZisUAkxleJidYKcOsov7xAkaq4bBrWps8MdS2n2TBkxWiWppPpKa6j1mcIW2OcUkZQaaa4ouXKjvC4BAq21BvUSMlR6IxHZTtDIaMN3EqX1ekpEyNJpxDU9MAO1/ZFYmp4joy9yUF1ZrQdiFNzrou75mD0qOKl3GtobSHS0C0dDoSuQaqcugjw7xy19IteKfZ/NEgeYDeX/0Zi4W3+kX4J2P+qWuNWxVviAqjvBv4iNqkuzptLf3PqRTRm3GaM5zszoWCGrT0uZjgT7emgvatHKBwJrtD75BJHA6cQr53G6KoLYLto4awxfF/E3F/EHa+JTh9IQAcwSizAmPHiUo3TE+sViWF7rEQ2s9lOmmGca+qJWEOeZ5ceYUS/EiDRwaS5NMIW+xH6+lnYfCXM46orcyM+gve4wKDuengeZXafx2naw3Hh/y9FRUZwRYl5qJ6dRzNh33FG4CGcTJljBkjI4jEZ6N+NeZRXUA0EjMmVX0mJIILUWCEOyHwUVQ4lppVz0lww4zCENJVM0T0o7rli5wTlsS45i34JetuAvMylS7xZFdV95cBKIxKDeB+sX2Lvfi4f0j2b6RuFOstZgvyTC4siy6c3HSzEVFtZoxLy1hd90VC7NbyILgVkCco+kZgOgaOMy/mhKXm0Rt1rhgYZL7ExWdSF6iHQt7UUqZ1JMQ+KINBY2LLRBxfmEJFhMMYA3Lsu9QKMSeB4hH01Kpb7kbmNdVuudwUpsOVcLnumcCmGjJ/MqAljEC4IOCU+gpCol5E5h2qzzF6mLdS4Nq7XRwd49pyF6CoG5X9rYQtzuS89E7Qr8DpcVGrd7xuTgCyAxcvmbd28uYdes1XENVFhnmBqmsY1mNOhv1mRpXMucA/SU85hQg+Uio1fyJH4MxIWUwqu3M74oRjDd1cylziLdUXPeYPS50KgIf8WYdE6m57xa3IZ+CNYaFlxYjTnVDxfWFy2m3ij4zsa7e8n5iD4X4JvJeWOHCZNneYlnORU3KFHKCRXtAJcTTAMDcONk08iXU4/dHk9qZC4TM73CxoBVHs2h+oWr23/RL6LWJgI+B+obwfD9Rp5F3udkYTSyg38nxBll1H0fFW2OEMBRCPrheExyx5GHMd0tzgLTdNDU1HARmo2PuxjsLssVAlfnhp3gVWJKt0mdKCb59PKpmeggYppKylSU6YmC9AauH2IhnHoi6qGpTcFegYxC26MQggvGAEAaE1jUzcVZM9EzoiFQ5uBhZc95izh3YQgY1MHW65T6yrEMaOm9yhdiuIXJUJ8gDEjA1zwdF7k+06dlZvghrkbcPMqLHlEqVfdPAk/ayGRSVpbgc4VAPjU1PR9ZpPi5bFZaxFr1f1mNzUUq+ksYreSAwglhq4MJmkTJmdaLn5luCXfeAcEbvyhcUP1EtCgB95ZIYMJ1DYDjaTJ+OYlcntGNV7hcs4jwqTIhvIoXQlS+Vt4zAwQ5z1Cd3QsEQmiZ7xE8B6QkYFhuvLj0UVRZk1PEKPrLj8xehc6fVcua3A8IQlwAwOkZMlMKyNQjJgpuVMsgYezMwgA4O6NUO5dEHgzEV1Y/LIJgZmi33nDnB6THVGpnabQO5ZI2z7ZnU7Blb08yuCqvMdqyl45lol844OsvBZ1/vFl8gX2+5Bk1h5ERWy8Ebw3REUd4tHWAdYSS6e0R0zLWDDvFObtYhEXBwOD6Qg+E1yaOnmZdgWOwIHtWO5SygW1vsZjEZbj5iyhxZ7TS0d1MtzgtBOlmz3uBTTB8wS2onzGL8TPs4b7w2B0up8B6KbjGvn1AmnU6AQm8aCnuRa9OL4m/S5eb4geZheXF0N95fv67fiXiJQTOtlXgfie5CWaOH3lfFlDED20WYZiPMYoKlRnxr+8scvFjXI6PUyzwR4hmBpMRzKrx6FKPYqZpxNzvK9FegGOkSm0tdQUPVA4bHiL52U+qVwXNJgSNXTGOwLFUsSOmQHEzzpqYhngOMbmQlQzaNALKxktU44Y6woOoIoNEY155l0fL7CWyGq6DqYpUuK/Md0dDMubhrI8fY6W+/tD90+njmMbS8OCesl5ce37Q622OX9w4KzBTrrDbPIdFwaqPCUgATULHci5uYSHC62jq51a4OZrvAvtDXgGzibVsZfw4jJW3RGfLILQfQ/giIe5/xS4rMX8P4TUsA693vKCcWnZKR5+rl6BFZGiozcoOBwejWoNTG9zKyaa7XErzJyUHDwKzRUzRcVuEtI4QCUeipmvozFS8HicVO+ZfmUNzAaPKXol7ZGwYdXFp4IW8+pD5OZk18MGjForx0li84TpmAWlte8zO0KqjtCsUaBBcuvpLco1zArZaAgbzjPB2Sr7yBvPEtBMKOgckEjFWh8KWPUO5XTEqs1b9EeZ0/eKqMyY7Sr2nRxbiULCYN9MdfMBuKeGqFJt1MM9Jf9+YlabYN3GcrwIltKBu7cvrEq1Y6uqSgYIB41L8wcZmOp8xo5PmB2+ZY8nzDfJqfEff6InJMj1YW2sFsY6xJlbbu3+4FBtDPDFcb4uN8w8uuD/yf6mtuFgaNtVcwnPQto1e3NRIO0jLoeiOQ4AZOh9fhnQX7Xu76d4lHShblZXpOIiXau/B19+kVHIQHMm7s1riZrlCqrnDVZ6wmAYdezPpu82mB/wCsFec+8oC3YO8orjS8uorVWaJh+8K5AtPhr7x25WlKx1/PcXxTZMV6TqW0JyvRK3oY83AmQ7y8DBx6AcF1NREfUIlidXhGN7zmbl4IfmYfzwvBRk/CABZaYI7AZCrmWSJw7P8AdNkOQlpx+yPZBMcF4NT483Eq6a7bnz478TXcY6Q+xCdMW1M07wQDxRAMglSro+sTjmif9YhrqhyhHcvLW/zESqQagOwo3t9iRchFdYJdKvhxme88rbQUULOkp9HLIAB1dFJR7gLjqDBnK245mpYd1yvTnZfxKjEzQHWG/EyYAt76nrFvxdIxYJi71ySxEt80NdCWSmyVpMpm4sdW4MJGk1EAWKs58xHpPLM037TEbS/jLgAUsvMEyfWEBlw9gqYgwudY2S7O1XLPu3IzUR9wjMvgD0hijRyjcXothWc2lLbnLC/nrKWAaDy6m1G+VEWEJoTCY1/VNHwMClEdEN2t90SFu5YYKG+TU1ZKl6Rk36mgRnE/XJVs06BhMmz81FyxKfeMRJ7CBtM7r7QHZ0C2/BCc4oOqMQW2Nzn8gOesuO/8Avul9g+vEHbGuJWe7Osxsinw/wBUVbGE4qWVrW8nxENqC5nFRrCMz30hWhHSS4suqrKR2TrUK2lp3n2IMRi6S4Et3jZWGBwIdoTm8sIVbgNyu9DsU2WOfk8QALlKkDg1rUy4ZS18LHZYCg3LV0X8f5OAr5VO+vD3mvZvbGeHfXxDQmLpW6db+n0FUi8AZdfL8xZh2dgff331vMsq97LwVLuLQSh37fti7zpLZX935h851Bo/6fMZqWa9L/wPQd9Ynev5nB6S+j6T7OTOZwWV/edV1uE3vY/E5E/YQNBu2IZHcvufxd59LMIGBiWegAwMyHZ95x9FSeoKYr3zwlw2AiUY64sCw3BATLcFI9srBMw3jsYxim0ZXaXL8XjUs/ths8l3cxD/AKJrD0naC4w9UKlVn6zGeInYp95coXNxlf0zKmAEo41H3dHozvnHMqekfLpNFpHaAaH4WFKfRSEDFpz7pqH9UV4ucPlfjBt6TIrww+x8wehnR7xoXfNsSKRVc6vRcvT9oQnH6w1RXJeO0YAHBtJpbLQHglamwLO5l+QjLVWt9CHFhv213lTAsHHhC2AgwVfebsEoCBY/LRqYyRsHLXxMl4gzj5hk5pQ+Nyi4gdIOsecVjpFAJDX7pWKGryyCOc05qLrEcgTGkhsLkSdxcozy6zHLkNwYPLbXvUsw6Nh6IXcBGUSxv11uYMC3GHTXE5YAWPCLOUKbiqrbpLd3BClkHEBOCrOZkdTiYxOqM2AdTgGrG3S6Ro0gWFWoXXd1RWPujoc+80HTeYhQjzuCpCxlV5DrLiVCp2HYgDXX4xYRSpni4JbWFfiIuWH53MPif8ZyuFyFB6y6UEMqX+hhY6z32JvlGJGYULio7Gu4XTUsv7yPOiSuse8WBLCXhjFW4XW+GFlvcLvG4U96dKlD2xKtahuYGrEpVLxGUK7ojNIx6RZkLGlxvXcHc/zcPEPGWlLfX9EJFQuqyV4OrCSS0iOxHcb0uRsp4lMxY4b409fJ+YOkNEoIWuzLSsu99mAJ3f0iqq+HMUnOGHa3UPoV2soi31V+EtNoAV1XCEDdLpjbSr5eZxA9C11Y16CgMoCXVy0Kz0LQoGbgylfWLem8Q1xMkQo+fMpeizJbXWb7MG5tmZ/ExeuDcZmZiAuE5nufefW9BZqiRtKRijbOcQR1DF7ypyveWxrHnEOCnhUCZSqd6VDmPKpCzcA1MY+JRSrK95GlCMpNpy9t4lXnKVoWfuj0NDzOFzwJby5wlYCVAY3Oba9RWoxsyrJ0hCYonvgBQravpKkTRmliNdxx2S9QYL3Tc9rcHhvrNyGKvzuXZ9Xf8uYZn0yKYAwYSdl8FtQzAyYz4SwFlLqGTIhA12w9ZQLEdxMvc/SAWvB4gG9zD74lB5L+ukAeJ7Ar9y5KFUy6/eA0WXDylEqVny6t1ZXf0NTYI00dqmN6nXO5bsr5WJew7y3r0ly461iIqCaVlShjZL7H7gvJhYr7w1BlyCDwqY/7jfYY1B/NKlYR+k0p0gdeMH4nD4MYmQQiVi9k2J9pnEOr+iUqj1+3kUYKIVskTZqD+blpCtoZe0B2PEvuQpNPR+IwHZ3EqQqAkMb6S4HVjBsqoG9dRp7KkoCun8sCzdCuhG/Nu390vxIFSUTzC2gVinu/csrSw6TtK7oWlMzOyakx0ysp0JnGdFZ6SyGUN0T4jbXm5bkuiqmT+r7RhWL0PPEOdMZ5q6RljD5ZnumBpduXmKi99Apg9oEThEVoJ2FTLPiiVdvpDytQrAF9Y0KMZ+k0frT/AD0/y0/z0/w0/wANEMj3rd8rW+Ji/Cn+Wn+an+WmD8aKEhtRb4o55rhb0tt5339OfQL8973gyiYwN8pvqC/En1jfycx13+AYIAjz8JGmUuG5iORrE/T0xg3iCJbZapRlHmPNp/z8afgj5BtTtB8pmEeIbmA+PvMk7ftHiLiY8Mam3oK8yqW7IVAbKKalzUdT0194W9rmsxvtgN1h3j/MA1esViatYpmM00Rwz8o06fKdh8sQAMbLKtsMA6d0GLQ3DE7lKmbXErsNyr+X6T+t/E/r/wAT+/8AxPEfzxP638R0wYqmHT/xzOYEE0bQkTzroqBFOMP8yInnEZkbfvS4s7GENVfTw+Z6QmoXhgevmzsRG1i91arQxkJt5GfW4NQoMeNPQ34pX9dd4IF+i74vmXL+1+0yZ29L9P4nX0KLH9iVBw/nlF5vb5enic6l5ea6elj6WeqB2SDMTRqdYM2/+UmicieLFjLEtNU1vOhIKJk9Eue/pc1Ll+mvW5SXvtCxdSz23fqEDQ98zN0vDKVV70wI5Au6ZSDJ05FyYcgsymqLCQEAy5T0g6AsrHucEEkSvJNACvB/Z/8AOP8AzZKntKjQXrfA32dWHUhLciLrCT98e+FbMZPB9sSyLSFKnUmUI2gFMj5PpUo9blxlvrb1lTXgPS+aPt6GBF9qDipzkZmtwDmvSsxGarL6R5o0C816161/8Fe7an1v35ZPf0uUlxhrM3v+OZUyPRxDg9GPEaYQ1RuMsX5pcuodi6hs1VIpRJwB+IytHkjvpYV3jAe8Kd5dB6w+pz29OZxcr07+QG4UPnIupwGvLr7g7QDWUIxzbS4gbU2tRax9YqfU0sFNh+ULq+obtjwjiNLQt6Magv2Sg/qtQAbLJDIQ5U/mdZpFMM7MOu992Cv58vRbiO9DGOkq9HY9QZzVEzlfNuxb346xkSbhQN5uqXWNMSJfFmuBb/xTPAExV1a9OZrcvnifMv0EhUCzLK45PsYXZo705+MX5ItAIvYKrw79oNeb1DwNcw4M/eNGh6Y8I7Vl9R3XzDwsOYAWv0ZZ74GMOhw9t5lVddTCwLrNzqmjqBpUbTCopx6O4+MYNjg1ozns+mm22qsa39YDSGlUR1eHD7wRTrtgFVd/klpRXWDKYZ2rWIZrg9cuBwRb5dvdrlkv0DxgiGjaAPwQQtF2de2JjgkkAK8jql4Z9phGGAfDCxLbqa4UpgcGY/PMehv7wgg/CTsmEEJ0o0gxW6wemr7Tifae04vjrNF8cf8A2/odpRVZbMbmQAnNE/dTp6c1z0lTmWdfS/RQ5Pmb9DX8mYHZ6On9sUOLO8YOYMYfQxgGDEyneSGspFGZFHmpWLFLlmLRpucQt2PZQNGw3cVG0hhWEdqxb7LiO4usM/8Am4/k+/Mm7DnwuesyavtuZ4eolwRqVjN10CVl8uT6Bjg/pMjJUCJXwy+CaImDX+W/SK3FhW51lkpfzqwig5ezP/WJQca4wIjZOjwlQqhFaDM8G9tOIvGbxKYpWWpROZgC2OmYJXcGeYwLP8u/3LwQMDCZI7VEGKCx1cXLTBbbwERhHFYV7942xfw6hFbUIOW7qKEx5hX/AFGHO8xd0dcE0MsHPa3qBO0fbRP9dI4QCrCaebolBHwDk+kPR47XL4SgAdtc8R7Yv5THy0ojw8x+J9tMG/m5h/Ll6IgCcCVn8VCcVnigAedTElXTPXv27EYHUBYkd/0nmBtrf9J4x6Au6U9G01QaPkqsx81h8W2f+QL8aQGw5WZNcM3ENNAA3sxmZNZgAN9YdeG8s1hR9Y/5zsEIlC/RXmpacssa6F9YQKRFORzrSX1YDwi7qsqLV0x+oDkMV478HNaLYNp7mPeUdDbgW6vOEL7TPpGEC+3OVe80rPWxP8qMTeyGvsH9xn638+h631Rlk+FlzcpdxRXRoN1ENFCKdJfDBjKzwTMuhmZCS2Vmds+KtHxXoGXI2ZB8E96DOJw5dY1r3aKq6PS+uJZ2+Zc1njrLxfEJh/FnLK0w0pTT6XLhsqrMm6C4lUPpDOCtxD78xXi3SviYPAcrn0DgvFDd9IsRU2tzLH5KRIom+UyZikbgH3AGDWdAlYvyoGMrnuD8Vh0TS07cQRBMjP5vEeHlD/DvGW0y1XWXDoFmnaOnVyxxC7B7JSwMrh0ibrpyViMUXZ0MU1K9hKiPWGJkjl4jIcwmdiHyei/k5lomH8SP0KPdJn0VtwtBMJcy/CfzvMH8HCLRuAJ77lkDKU2fpEQpaEqWo+ju8P7YJw2n6yhBdGr8xwJ1wv8AUTnU21Xmo84bQsw4dziVAoyo+mZQAbHoXKTJV5ghqjwrc7v433JYJK8spWbqtQxhFsWX/TxLL8Xg3IMXVHzi5ctW1y8x4/WIaYoT++kfezQ1Hxds5nXsMSotSV7emZHC4xlqdvGIJWwzaymSdF7R+KlwQalSkrg9BJ3bFzNeZ/U4f3Ga6sKgnTcs4uM6uFsc/PLEobcHE57jbVOtkPmWUTieNyixBl+X8QprH57z7DL6qgq5jQse1e7Gqn0D3rcrDzvcJghhwae5HSXp8zErVW6SmDaGHHRfezqTpQOucZWVMr6fR9HuGvBdRRwkQ9Fu3fMyO+0tvnr7wUFmB4KrC9Y/5iNnSxheuD1FS7MUvgX3e2ZUIKY1+o+Ifq0JTgeP2x4/S0zzTzcM2GTyLH3+UP0SWpU0HX/icUjRvvDLzRHtUW8WseevnMQDAqG012jUAIK+DXzAZPf1VwSttdtxOJXiAlC61suf994vR1oW9zUqZq3Idje/eXtpXnS+XvZ2ln8XgrDOXTmVIAvLT39K594PD6Mj3nQ4Y6K6VGE/mgL/ANmbOoVfM/z29AQBoKsMgbc6FX6hMgNbK+zdi4NmTrL1v/i+XEJT6iNPaj7XFCMnlC864znsxu7dgLriYF57x2r0KmF+CxN17FwOGueD00H9KBXWs9E2034sw6XPdVFQ9LL8/QlHq1mfMtKBVd4BgRfp6aTADdHaDtD0GmBx7SkETvmFrh0jLxMjux31KpQ3UVfEoFXDPLoNbhvlNnPUwSnP5SrBuaI1Dm1fiD+/aBR3w5eQHtllz+7DFLChTHmf8wOlFlSrcPMYfYQfKY+3IlAQcronIiONzqGn2nCZ8P7tMzsCyaSFcMegfyc+mcCmvRsyPb0F30KaMsqb9Hmf9sjEbfsp1mGdwEgkSDbQ5DhjEdQjmBaYrRMOvuoIC+2edg+yH0MhorvuE2qaDp+ksqQaRUXgoS3hzBSUPc3/AJ6HaV+t5qcTIIbMg8dMdID83BZ7wBLe/DWMYWj45hSJBNXR21Xx6Ut7/ZlMuf2vUHBkwaYHiRT0SlWisTiGVuk03AtigEvMlWg8TsnEtfAHMS7y/RO9VEhUb9cdMlqcwgScG4z4gTNVFFbDcxMpr0U7OUbE7OY4f7kXIVJz0xrSKeGfKxgjAzDjtKbKCbEbxkqOE0FvkoZnNveeC89Jeazccbx5i1vEpO016W/0hleXt3xuP4Kzt1fB5RScqPS7GMDKxxxvYGXvz0xLBTIVwrgenc5FwD4m5+RO2Z132Ro9LPfpKrM6jM1FNsefS6y48+nECde24nZrziGdZlDz0n18FxRZQe7XouJiHak5tFwDcW2n6ROkhp+0WBolu4JI5uls/e/aYXRjiDgq3mdN7i2BjwXt3geAgJICju74gZHDyRLoCYVo4fT0FCNXpVMtALEZ4v0AKnSnnJPaV/LFua9Bq2tXlLpHAuiMcDy9Q+SAMMbd1jWZa9DpPY54ROWpwWFdjUOkwnjRSUtKHC4BOQIH9+03TnBMCl25gBcHLxLGxRNSs3c16OZ/ZnN8zcvvDF59B/FzHH/i6iIIHLuDhEu/RWRVnfinXEcLASvIfCQa7dyGgBioC/Tn04nMQYZ/RL7GmSrd8RqNbs6yurjXCPDvikHVPiY+bWV95fc+ZZ1JU9nzL8fMxMTJrAePEtMdVV+4EpgsiF9xP2j6fmQdmvAMbw8TA92ab4YfmNriXIe8paBK5WXbD+dpSYueawctR3sKHoS8vB1kBFFAwXME8loyoPmW6Tesyvf1zHae7q1dpo1CoZ6CdEmlX3nd/BP+eIFQf7xP9lH+5j/UfqNoNk4OfpEf2QYHJGLeBDK+qWkuClbud92Ug5Tng8ywnrR6Ab7fWUZIWa64ez6zGG2/T/F8E3VBa4kr+zKPpVEBzZlGa2BCvsyx5Jfr/eJca3QIF5FceftLqFjYz59oC8KBw67ieLlGt8Ymw9bamrxiUyvfjDjnvFAdQ1wxkuekUkr56Z3gP5hGYmjnPFkKgKzdjrrUPMFj8BLk19xz8GOQUh0GiyQIq9d9XkfWIy54qFslIksY8e8vBvWESdF2jfhWFT0f6ZLd9LMLwcBKbMHd+EIJa8ttaL8x83CxgQlkvCdiNYADaBgRI5BKlqco9exo7FTMKeygAU9cbnF/xAFNey52cVGvcsEorLL6wsXED49MNI4aylwwz7nZDHEbslob7JfduBZ3iUFw6O8bCV+e1UbUPS40Li/b1r04/wDIR/qe0qI5NwfCN5ohFptO2CVPQGVFBfeKAiOZ/ryzoeyVDJVivM0CTtos/JP9yf7cRWl7IBShJzmPoM9ipi+gYW1gg9IQ9GKJkVBELHGIaxqBkGRXjJFmTC0yQcsqvOIDdrwrCWn4EkAqN7ofXXCR+sCUDYIXBoqrmPnLZlKwBGAVDMs6+l3BysUlR/Q/mJYydP8ArLP4frPcv43P4v8AM/i/zCyfN4fWbRveRRSecDBFZfFCwO6n3ShYbTaekut4HqaHjsvfmc5QL/YR200t49tEZ5WyDL8xqpayPWDi5s0mSY6x7BSGEyEuC2gsQ8dk8YgGfMWjSF5rq+sNnKH7Niy/nwFEZyUDkFnYWa/zcsRuQqxUGoFH1MN1O6WaZCC3WWEwb+VdJYWYUtgv0LT3EwXxHxHo48Sp29M0mU2eZNSxn6zvHswPbT9Rtb1uibSPkkOGBvfRqWLI6dZPfXL8E5LuMsMwJHpUd0hDiIyVx9I8H+iW67UocBdUqX1JtpwHGqxOhCg67RRNpWZySriLWya76Qqthd2ehEwclkrnGj0BJQW0hXzRyrEZzX0R5dn78GB4mAlrm8XFKob4y/v6Q0VQDINGZdYnOa2QZgUXSdXpYmmHM3S/xYoMIOgOBy8xVwqeqUgYDBu5wX9YOL/gI7lFY64TaLwIshMnJHhgoWD04mgyPTX/AHMEBl2MdTIZq4VB5z2wYJyDKjZLxt6SlbPmb9bovjrLuXztMXSbYjlAH3UWat2Ov+maqTt2Q+I5UdvPSMupWrIxlWF33hs8GeHXMLp++DzGEKvrKnK+D81Lc88ykIphQJ7W5ySV/P8AbO3/AL7z7ON+Z239d5eq+8dBT0xL6kQCXBX8ybZmuCUA1WJWi4alGgyTKPTOSq7y0gupQVQqTQrow5kjkj7hFB5iVkCnUsR13Pp0l7JI24QKe5mMG2YC+BVMT6HB3lW4FRygZValWzbBwwm5PYPAa/E6l/XSmY9sDVDRLsBGQGJpfg57y89g1M9cukrTRxO8pjWju8IT86FQ7d3Sd6K4fVBKSDMisSksNOSe1spNjeTF3AV6MI6LvgYcShs6GYdZRmhprzGJT4tNMArK8GYG3iWTlHBH6JYP+MSqzB0KJZH8kS62HDT6T+hB8fYRtrByiLmIgDvFLgEemeK2qQTTmV/KYpHQxZ0fMpSzuke4KaqJcstz+9HlXDyx9TueTjMtl6JXJD7p/G+JnrFKoCDynuMshbRXcbschuHGpVGOjT744OznBli0LOAIvPOvH3ilMw3QofWbdAKt8sIIm7BUK7wA5F5qYel3RC+s7y6g6v7Zj9zmji7joDrsqgXu9crEyDNVcNE2KoNFdYEQa924B1YO0KHpzvpf1YUlmG17e7pNaFKpLh8vMKCRUYT/ANQwhFr/AMAhe3MCvLjmAjsYhfWpZt0TzDerx3MeoFp1FMyzREeYoQtRPBLxfcG5WBh6wgsFppgIcJmAK5UVRLG8IDeGbeYxu5sMIv4J0GIMw7JeFoRwrfzDTN+dy0Rxkb4TDwnKO44nliLbgO0HJXSW0aPqlG2gnclf12MZ0+kLMJUjusQmkLbhvgleTpo4yUqxzM1MRk8QtISvALRomx0VTrsVNHRgOWa3Ux0rzIFisGm3/lHfO81KF3kVLmB5wE1qg37ffshAZxQ+gsxxlH0A2HnKXkHJjPmW45kq+yA88pP7NiDZVyDIeehGS1Kg09u7Cfk8PwVjzAq5Roa70vriaYr3GNlOonencs+El4HArYIUffVB50SmgOK94JWfEVyzT+cQ1gK2rrHXynch/Wodjqnhi/63LAmzADhqL9SJQtvLOVToSlxPOA7IywSSBC4q1AWJ3Krbl0aTSPWZnVHAWpvLbej8VFCm4dtc6D6SnkDxL5V9YhaK+J/yWDRpeSNaGFG2Y1u5lQYiG7fEyd/KCMIr9FMdK+hqfpZVLSlBcxZZVsPb6RxsFut7JcdOQRmYkvTYpToRj3hCMjl2DDEpHI0QcB1qb+k9BYEL7VsmIFuX3etQqwA9zQfWFG3lFrqHxRUzMWetdoplhuubjKBZM1+cv0tbJbLx9olg0qW9ghRoHCfL0bb8EWb11jcX2jju3zVQRFDjXeVw8briAKlTxmtLhQP8V/yBQD58mGLSoLnkgFz/AIWZqw/NpQDulbtMuye6DY0otlt6DGCR0XxZ85Y6Uljyv1nilq+v9TBbNMGDgAOgKggKD1JUBeJxAAtdp1/rKVm+J7rcHZoFDlZmZlKtKussgFoDyNR8plUqHsoixnEujZfDt7QRhQ3HbSREVCWfxE/wysTLpxYvvMAsl/TQbvYGBWe50YrmigcV3d0RsXVtuvtBUc2xJB4On8YcK2+I60Y3xlRNvh1OMOocHaOlbpk/vSA8uOvD/wDJ8WviH+lL7w3MKW8VcwYi6rJiYo0czL20vLRR2MvbzGDQYrC6tQQEoB8uuYICDYL3wTLDLcD4xGeKnFTRr6RKZ6Uq3e92Wtfqi4KvUVHkOLGrxBV6rHo0hYUG27HRCXRc3b3hyQOqTtA1MAFHF/dZlc77UUFLTClqKUM6X7s35LnbPWEPkRhiyvcT95kgwxD+kFFRRenapaS4HQihEtAVe/MqNCLWxLLsVnfg69j4jlAk0cGPYmyLHT1H7wxXLi5rvvxEDgu6velqxAaDuXGCbcPac5ih3CFT+OHU2aNWzeHHNSwxLawrruFV3ha9sSvtGBKesN1q3nzFEo/rTllsQMbLOodDujI6d/eVZKbUhlFI0iFj0l6DAYb3A6mgfEoDKAukDbLwjMCivQRl8Yi9Pc3Mp4Wx24Zrl8UFfgImLjmbRah5Q+gFBXMqV0r8Ej5lthQ9w8l2YFj6s+n5mDH7yfz5OxYR/wA/HkONoPtNEnxcRhsn364DNj2iTMMRI9IVHyT/AHJ/tQX8mXbL3j0vzArFg5gr1T+25IjXhkWFWQ4DixjMrV5FO7aGteK+2FgWlvlhboXBfSJcFseh2TmOv3/6ysxOY2Yeq4AuOzQuB7yggtrn2bjDVYI8cxVuwKuoXlf+43TpfglhM7ZhwlIUbyg6OjKhppkEzkzXBTmdbV6wHs8ZkuviklTc7aFBmd0G1QqxBAbpe0+IWhoBtUirahOjLVMgbwnZ+WtlPmLWp+LjjmpczH7AB5EdOgcpbGAAGeW/EswuktHxkZ0LzqN2V45Ff894IXS6Byv3YWtV7mzqxAayttynqr4YVFR0V/dS06h2C8kJBMK/zVMs0a29wTAOb2XM0jVWZ8cgU6kHCHEtuusTNl2Lr8TDqnXuGiXrFafNTS/2hkwe/wBZVum8TV13qXdGBNRsKGRhq4JxYsIa36PE+qQqIPrK3BCoO4JkkvFohRRQk/dAC4GEsOI3owjGVbAEESmCya2kTG5mRhocRuzQiNIAvd8RkCjFogcJ0QvCXQxW/wCqUuZ952YlrgVfLDqsXokoxG1g8oyFD5fuaK/tM+8qrZcdF1N03jUVgxAjqPkv+WFLDaC6kRO72nMrwk5n4qW8r3nTHtN55qrL+JAWqcI6jBZkjpuMFWQdZCtz0L5xi7WhTKUwgkNV/e/xO7J+ovRgT/QjL6v+A6ReRMs5YFwGxTceVdRrsDY8/EwNJXYg8RVLRv3aHxF97gpl2uJbIKBDDiEHaksn5i98wfuNdTX7pgEStNbmQtVYN+E3SYYHe/KAVatZrpO2VnsmW7ZqYl8IaWFDcTSP6fmKbDtd0Wy/UhBDFwKvJEhC7qYwPQtTKUsbcGoaNvaK8PEvu0lS/ThixmFEkhwb5EPByDEVMEFu5Lhvte7hXv8AQDmT9pd5P8T08YwXtAG+BzdGRm6rP7+8vk4Ooze0vnHF5FTEYIzt96tzc97j09JQvAsOrD0gOf8A2QCK1o1txuMsLZbTT7wFP30NRuljftLDYNd4gHtHaYbjon6WMC34tPpDtKE1NXFwd4LXX7E2FV3V599jhPyRi0u9395kyOjUJhje5hbFlBkNeJYxHhmGN+N2TEtWxdleyXzTyM3+4uFxV+aYfKKLcXEwtuBqE/GYlISl31iACjm9wnlOJBY9nD7yrSh5f34mtWYvMHlAWyBOcBPraDoDstAjkev/ADKlbFWmb8dWPJNweePynLK+ZeifMAB1DpxFI52aAE0dGsF2EIWIt4P9+hYbb/G/IiSl60/vDfrexxVWcgVfA+mIhNv4PUbSY2AeyOzxXXxX4mwFsX2oGWP9jTbiL24D751NviebJP6l2QFKuodYbu1rcsjTJTXXESySoADeajVyoNnukqJ4NA5j6x/BMh0O+s6etX3Rw8K6G4/iBMTeBytbgRaHTIK83iAW2+bgrL9ULv8ABqf0N8qO+bdwgQ5xUQx1Jj6dq+RIkPhD45jxtg8hHHxLJx7yLgZ2vwQRj20hte8DDp+4YYprifmlGCJOxlGaXKd9w/dSuqOyDy/7faG/6c4qs0uxnTQQSy406D7sv+svN0Eo81Cu3rLyF0i1Q97bK9QlVbrD/ShFdoHy2GFsq1HpPiX/AMUOl+I0Ni40mWPnQNPr5b1Yw/8AceibaF1WrP3ugZvu7AN8N1iG8hgeLDfeIN7mxq+MxfKJvlL7yX7wOY2/IlZVv7UT2J5IrmJbz1mHnZhEC2Q0wvEMG29CPZK5vpD0hdzM/wCbM0RYO6O3wNISmTUnfPq4Ho1MKIb6Qn9fcl5sfdRJEPfc0hd0yZLOV2cRSa2Nl1JYlMvtJ1JRmorQ3BwlXZ579kPdsZkzxE7ahGjrEBQf0iMmM7eIeXoB7cAUA4ZqM2OwqpoivhLLKd4wxVb8QZm9Om4V1ZV34drpmz2AzPiyhe8nH6o9dsiL/hoRgRlJ5lB3doiy5zuGlpu9fvASSgKd0paTmtRhydJUnVZmIKWYN2BNHbApNDCYb3Mgl1GIT0PJQ7UL1LccCi5MZCoxiQWUY73kcqZhxBFIT/QJK+fQSmp+lGnnWUDgsmSfuVYdRXvZYbYfwwI/2F/Exw6k2h8qA7uW80jkGGUmWx1g13IOuYt3DshtuN2O0dQimLFZoRBYfgvHMdpetnJNRsXdEjEoIgq11fdDTWxikoDsS832ilkXnUN8BH6oSqwnKzLN/BOsv/hLlpZBTtBqAJhwiwap3lm53KveSCnu04mjK6ZE+HywH/qGct94a1BXFR0cuWDif6dOJWuUjRBUN8bGUxPfWhLPO1uyJJFtjvuYaxRtivQMasJAPZzBxhKrEBg6URsHLxzA1cmJIquwVs4UjVMekhcnokB+0ZVzerQMMNHPCP6pZze03gc75jDZzwR2RThsjHxCLNIJGJVuGapzvfKM9oKfecaHwb/6w0KZFZ0nXHR6oLF5GC9iWUiJHig/9iNT2amtIW+rCFxHSb2zlPDKXQfogm53vR7YgdYQQEp1gniEULoJtg+xTfcIR/LZ5jdFcHUPNlKkHjMXLG+9S6/q9LL5puskscMlYl8vMQ1UrZdFZolwUdHWVuryc+JeltYrPEs9TzB7TMlNhb1V/u0sBSXV0E5j1J8wRsAOf3m806Fo64Y24miVfiXcTrPpgnLG3aDW0pR3jsWg0wfOQmEM3zyQt089WYq4jynzAcIkm5WAogcFwau/ppRxu50QSqVAm7hlklnFQ7UqHZ5f3rHY7BzLEdYrr0v17zJKAg8LCdLtdRnBt4AxCXeYp6XGgv4qbanvgzZ4jCLe6F+IUK9wPxDTEf1Me0yX9zKGcrLQe5BViFkKhZmVAn1lxKuV5vcpOrQ4tNRdeen/AHLqi2rkjkM5Ywb3ZgA5lwh03DG79p8AhgrZV6Tt2CbgjasoQm6vrBlQXHpRBojbj1q9IKV+qV9ZX5H/AIB3J3ZQ16SaQhMAy51LsygI58F9Y7o1bzmLa8txIKkaOYrbHiCVerBxzKmhhfNVA4ZY7f8Al1CUekHLSW3V5Q0OGYNPGsQfWakSu/8AaJ0fejGhEfFQoFFY9O4DMB4/M7eHyZaxctam7ET2+JTqztmDkALnUI4xaLeSkZCKpYDMAGRsDj/OU7NAGLcGo+NszSSDLjP0Y8zILRtfELxIfErvPI9Cx/GOqR5s2YY7NxV2n3xE5XKKCW7SotodYTBZyxWefoNXqwm9mhrUW8C58kBMgOUyrqn1i0tM/Jpam1MYw5PCLSqn6EQcrYWzrAQMfuSvVmx7xlUttsxBjQOJ0uNaN6l3rpbCxjYM1Xd0uZAyoBXklvh+sZHVrrhEW7cr1xBpexPlTPftdLkJRCwRpsLjpUEn2O81EBXeIFAynuHqib8uJ+GQBU4xodLhqJCc0HlaNzI5Rfv/ANZkOWZOOfoXh6xm3g/kCujNRLoYg4CdFq+nmN2tTDGPEznSUN2hyRi7mszrdWbkGskqd3+uIUCNbpYemoMDlFOURcM91cepu4/EOY30SUgo8H5l09ymIrRzizC6nCwegS9N64eZm3JteZjVwIw0IQwZ9tMshuVibIIsy6P1S2v+mn2hDczzukD9gR80YUg3V5XEHVkL1EgC+2IpuFLZHOUdbzJQ908ISrXsp/u/R7/YT/oU/wA6Ifoijj0Wyhoq+9SwY2lwy8fRYtjqE7j4luj8RTugYgmvH53oqv0+5nFoxUA6x1cogSVQ4gYFHJAbZs4eIGKhWSmhKgg7V/ErL+IMJChPId+xGXSLek8lTLQpbog1lYcctyoCmdUWQIKVumHg64htlRWPIq888kqhVFNsxs3W8GIGa3U2gqvteomXrCBgwVurq3KuctpxAgj0fviteE0LL8y4V3bKmt9LA6jonNgu7qdyoqN8DAHoUlYH1V56mTUQU5IUq48k4/3OoYi8YRfdstC194KcwhXf15/wUScyMTsv9oB621YXHuJC6s6Zwswm2PkXs9lKRqMOoFytxfjumSVk1YuEguEf9Qo+E/csBP8AOsUIiXC1E142MY54/FZVuBbK1beX8s5OnEB4W8W5I6Ro1gIORySa0QNVUtsUzL6i7hKFlQaKjtJaadlmmTB7jI8Iu2B1kokEEu73eMByGmOQRsffRVMoajrrKHSpFkJ0j7/3+IpxjM/cP0wP5c0kKpIUhntU6SsEjUFfdP8AVl2kkXX4sKVhY3PjIllC2SxObWa74gWUPgl0ujFFsbjs9asV9IaoPCkO/ab8Q2X/AF1i30Ul/k/6zXv+nEzh6Iri5k9EKWpbs8zFCuyvNR0r4S/NfmR5Ae/e/fPo6n4jpicXsH0qdCkx6bkXXSVooCqnKZu+4WSqsOGWnldyz0dPUFV4BzD7pt8zjcf+vlEXOEI5R5lKhmhO6oIi1/CFESpcx6XBcTysKgyrIaclofldWGPjIWua3KjtdsuFNwNo1V3P+KtFMixUlLhqbEqZE+Y/UTZyfy22fESdaMPJDvvN5RBafgJXBUrbrLGkKeDLtWPiGsBaW+edSma1yoWffNwv1PzoQZjgHQTTTFFXzAXc+Ar8waQDSabIU+3DjecbYAZW8xv76pPxEP4iAhXiQbAUWlogNRyehYwlEalRXp6Aov0qAjTH00d/n0QJsoOCNyte6HzM+1LhmB0ISvkV+svY4cftEeu2PfApW4MoWCDo8wUmrYYTFciNS7rl3wmXr0Ot+ibCcrnZKgyL3jMnpdjGdjnLmIjG41B5X0QorwWxIC7LCmKc+kD7olxvvAEySfZFu6MlcoFWx6S0HUC4DUlFZVe8bFW28yylrvjC0FsrnCG1HjvYqXml06nPbtHJjWcKlY7uk+iB08Yi/eDqLJvg+sN5PeZW6QYJbBcy+quYUJVSymszqTewxqTqWwazR/fea9PLF+IsNuoEckKEi3UnKFLOrKJf0gRzJVI1wBA/cQXzYNYoOSOi+P8As0udhHy94+lcplCXmaZhHK22WVc7b+UMMHtRjy8+/M+dDH5lX4mYb5X8Tqr3z8SsfSJ4YV9TOw6JsfEelPSsYIfB/cFaUw0jzQ/4pjymyZ/0pR0VGcwrMNxGsS//ABUQhswGoo4PlFivu/6xhhaw7u45M3cFPcihB6aRMy0XMGBcMWK0lcRFcYAhh9tIA9oxn/GpS32iHEzXrftmYQPhLNWe2PWvb+4svelBMGk0qukt7tK3GNGurbu5gaXvkrN0tRRp9iC6FsFWsQazPckJ1+kD99kjpd4rFFaze1S8Xs00JfeKJQoHc42jjKNL7Y/MH1/N3gNhcuUW4+SL/wCFO8/KB/hlJQdIi9PmZl36cOfUaXD0QcRA9pj9v4S9Q1rUQSBy/pK1TG1ynTEoiblOhj6wVVHzAmnmK2JLPvUB8aBiFiZaQHTKBc3/AIKuc0fL0fYRe+wovVmmp+GUJCzpKZqraFTueFlj852nMudQqqQc8YlYQPdKaIy0rNzH4QFsybJXu14hyR2bMAtXlQRZD1SJs8tywqCXZpmNvZ3XK/g9DLBNd7d9LjeNGzqlr+PGOKK5PKU2hebd1zMTaN3KeWD3HgfufcL+qDTZG+4jkocDM4+WYcKbU+s1FsBQz0lv6x2H9fYgtgkwoohZ+f0jNFuGy2QKM0586Qwh8BXGAF2iKktxU99xI7+AVcYIcdTDAIDZKzL0KQ6T0tFY2Gx9Gi4YqL20e0JGUaF8Z58fETpe6ZdsfED0+AlOh7YlyDqQ/jLZb0Yegv0fTiX6b9Fkv/yZXrcuX6ZRjH+PKP1jF1CHVuyy+1Ix3lK9k46KtzYqPcZHuTIxKBKO0O/0VjR2lZaHqM6M94Szx3nHe5cNqLYKINsSa9esc3kZwN6u0H3mkW4yp1A1VlXfzcIZNAOfeCcf3RpMnmHIfMU7/wCT+JtSK/J8KLBxSiU3QgPJIB941i8p+SMJ5NPtcofC1+8LXwx+UHtPlfzNX9FDi3um+R/O0OEPP6o6Mfa+edLzPan7+UnOTrNdIMEIKRwSeyHt7WHxEMNyuK1/dI1LWHHYZmmPJ8tOB50+IYI9/cEhUCeZ+2iDClKQ/GRquNVbUkIXAFtPFjFek8UfsJYM+1x9pcRXAge8pc4fqMQGXS8EYAN3DGOu1SQcsNAToFb2hcBNsuCHlKlv96n0lyn2VAB4di4Y/UfQdRz08wWhevICCl0LI8ytFbd0v1kUUtgmPClM5eIgltEj6FQDkyh7cAD2ZnisTke7H3XbPWJRbhNy+7yNXF0Ebswt2GXWZhnxxFt29HUUCeJzitrqjGUpxshopV0id2aZQeruigQl0zqJc5fbMuB1Iw8gzgeEiLJL1Tpce6sZJZClJj6HvyrCFJFsXeijKmfQSgC6Ufmm1vwf4wi4ehTpBIPouDF/9li//Bv69/8A3SzrLlxTwv6dp1RDUBZ7q4IpczV+CPqzgg9U8TzHPEHqp0U6WYds5QL7y7j6wL+GPKPaUxVhhCI/XCmhp6O8yzyxVqKcMVw+8EwfbFfQOfwvaeEvU09SnT1mOyNt58s5A3xNztrqP35u82Hb2w/1Gh1g/wAcS2N9MvRg4Wnjze5n8cQn6uP8wPvFPu/2Tp+V+ydIfw5j+oU8E9qg1O5xFueEHtCEaiJnzB4E0FOw/mWo5eWlhgJ0QVNu0vyqbjBdPaYzJ4jrvigw7ep1EJWsFoG3Wkqjs3OUGwHFQcH2WdtBlshbomW2CZrFdplHCNh7eIm0eswoopmMrW1WIsGVgdWwxC2qN7UNdDQUHNoEhj4JeorKFj1gqn4mympSGDtIG9/JBK26hU3dryYJs5AEygGRy6BiWRiV57zPG5VNXWcSmssy8EoeQqSpRl8mWJiVVedfSKFp8EJA9AOdCTes3ueCGAPhB2/REPQmoSd8PRcpmY3CC5T1i9Fx9K/ov6CSKly/XJr3lusV6QxH+nKBQTwwqB2ExSt1lLpnPqvGZVL8Ijpgt/IwOq+UbZPaMonlBIf0Bfuf7H/YJv8Ap5nDP87w9CKsmf8AuR/8800RGMQLHsampHZL9Hn8fyl+inSV6f8AwQ3LlelSkKTdPlqVeB3zPpHIaBfEm7fX8hMuXeibns5PF9EExYgtqiXLrv6L9Wkp6WWGvg13qYINOCMkD65Q9rPTVzKFUVqg6pUlbJkibOB8RDWdH5m2Tn3jnKthzAmIU2w7UNmINVjBwU502pwwsxnVnxC1G3OM/ttM/wDBKkQPrNhu4LSXV19tSp1GULuEyzdXeIoePB4SuxmSOf8AZhQ1NgqKRod8I5XdgxEjy4378Qwot3ZQ2axkO5EWJZdzJ/2HAtd0CVssm7neZ4FaVCWQ+ZB7IruOuPAmAHO1Gfie4QpuPRpRxUrRCq2PGIpbw8h3l5p2V3ECofB6cGg0h6AdAYF1BVRHT0kHoH6KZmZ9KjMv/Bj63F9FwggmkX0uBGV6YSwfwcvSTsl9hAXO/kYodo5u7jykTUtnenveZaBcwLl+Zbq/M7z0xJ3onivcxD90Ax2mDe8SRe7Y+qQRxz+31S5cZfpcuVLly/Rfov0uX6XEwJRpfmL+rKX2ucTi6U+8Nm3Rvo+ly/S0tLjGUUBxkFhxErdL5jOZ2S5I6paBeqMFpZyzKKCGWQu5XWw97nMrIlsqaY58DlqHy0cR3f2mw7ZYwuTc5pUMRorvEsFu+sDoajrcx1LABLsmBJpUCcrM8asE3LE4ysbvcsiDt2gSUr8EsYKIDTFJvFlWClBuO4FBCVdoHMvee/GEETeCEXLiwEy1R0xMvOneFS0Y2TGaXCsnRgtXUwOhtllmxMnlAwqU6QihCY6HoYXPoBgQEBKysZUr1D1Yxj/5IehKj/8ABZ/T6vQIbEmpzxL1VGWZlLl/+r9CDUr9B2ic7LiGhgDFDqzABqtYsLr0uf2Or/wp/wDOvQ9H0CBKREocQ6URvM//2gAMAwEAAgADAAAAEMrOvFHMGwEvIvXQpJMtoHQFJEgILaYFm29jc+G0eYM8JSmTVjfmxATS7OBH334BLef332+70loO/wB/vvtZkPWgxZLarOQ/wYSRskS0ClJTrI2CTY2lvwHSYOZJcAA8OJYlp+XNsl3I4SACDK2snYCQT/vLuARrLt/bu3Q3DeJCzSD9AY1ssGBoBkQBCAx9Ja03/hul38XJ+U0Qr22l/s7fvi1vtLJYRa02tamm1ndZsSDJ/tsAm1IrqyYYAkASQJ7oJ6kwAICCKIMkDK0B9Yz8m0zmDTxuJaX+tbVqqxXZvCSCTvtv6f8Apbi/q5t22b/byrgUyajnSNWgUgC5yEJt8WykAyWW22SNJPMfPdfb/LcCff7hZL7Ntdbp7b2yyAZv7iyiumyAINI+2fS7Ej71C52ritNW9yfqtypCKAkgASbcbE2gAbOZSZfrLSnRaAqXJ3ypmLkWpb7SAE9vaugSTxIVZFVjU2NySffgAJfnSt0wdQbsEpNCekUAkGJtWEytJAv5yNNtPgJlSJ32tgAXdW227/8A8hJPT2w91w0frzp/oJGye9iYEkoFgNuqxnfQbCe/xKFlEJElhSX7SWpC9r3xpO6KU7AI/wA3L98p5LJJtuTIT1uzixHbikLyu3cRJZJ833YSZttLuRtuPP6DKmJgBSYTbaB99s2hJYl3mCb+CvQOTakD/vvrtbJL/uDLT/swiuCSYhnD9cOB9bJtS8J36ZDbs2R8zzIgSkTS0JJJRYaDZL9xCLJZQGPtlBPjTIAR7JJf1tACnb8kSACAbHAIB35h0Xlb9LvsK6B9uAFJ8mRsBNu2B8QnvRLKDbL/ALf57Ztdy2kHfiNC6W2SAf8A/wDt/uA30tv/AL74pAyw7Cp975N1G727kDm5stuX/Lzp5kN2Ag/9bSvWgkWENEWWMHAvWbHHfgeP3PkAApbWbJ7fZ9b7kz5mKBYaWeySEwg6f2JtJxTSS/sxaD7pZfPSJEd/a2b/AH/1uayW32YRqUu2Um5cblLZNrYNrcX/AOJuJEST+7LB/j5v/wDb9yg272J/EIysdtEVyvJSi2WsSNSz+gTCNgbeMfeSES6PEuAkPdlqgB069KRM777OjPRbrX87InyiME5gUAS2tSbJASP5jtfyQ3fl9eXoRpE3eU7/AH+P9+/2/wDs/O3buiS26kqQDbenopuHv72T1Q620loYpA9hvk21Zba3JmBZfKdH/oBd4nOLqhzWupTPnzumZaJONoN5CucL8y79DmJ2idWtMZPpOxdbwCO5pqe1HUTY3L9egp/9ZlKjxstqS1v2m3l8LIs2Wx59IKV3Y2ebx1ntPSGb/GEoQIRvBszM+Mmz+jHbt1L4qd1Fp52J8k21ohJ/Y21swQ+HZNbrl2Ybui0yZ/JVZflMnpt8K/tDmHkDIWMpjDZZZXrhe0ICCg+07EssKkAYsOWKEv6UmVa3JuTpGsAH7+SbTRxbkhEH4EIIly41KR/XuvOE4KJbvXPba4/tW/TV2viqoyC3jFXeDz+DoUWMVyeDciC1bvLvTodoYoZjeHg0TRRroFEWFTPNVl/e5CLTD+NCIMG1iDAdfIQz2/t5u9K8Ke1hwnQzzX5yxlIB+DbvbvJ9YC1ioiM1vQrlJgzvP2Et3oXRbm/h76+Vqu7Hmk0H3zAlk0LZg2rLIOWalOcSXIzi7SWMChmJSfb9ZtJwICcP6DvsoA6IzninTzZYJRyOa3gg4Q49p4544IWtIu8DBJVVH4YHOvfBh8OvmihrHdeK9RTa55KlbtZ1stZMKafXmQ3nDsKjtnS3bz0U1IGWj+uTDco92AfFG1ZzVB30k8PH4knOz9Z/pZIAVnQE7uAiwwCnL/8AFB94KMXTQe2lyDTto3nBuTFJtSEzAscPSZtLmoWX/Y/q2ulx7OsgOJicXD0Qi1w9P0qVWlq7735igWSWfozoG3n+NzUCJMvz33DPf+THxPV/2g/ameiWmMbDhUgJ8JtDwFk2DIEUJ+GQTaKORkL4p+zN2t/JEy2b0dck5V0GMoWbwy3eyB1U5bibHH3IBAINTlEM0XAkL6AwoOw3D8P6k99XIxVzQ1g1XVDxIragwVgpfW2WLRv01C5+uXWBAtxPTR+1Y6E6YrrNG/erAUSuMzWiaT0y7mtZEJpEaYMlR9JtZfgf1nXmbBbJ2+2Pfyy2iuKqWpEk/GKQg+fJ1zHLGspuh/2WZFXIKvS9/GZVSpg7viTGDogNqZq1ow5kxwf6lJYZlELx/wAplttrf1IItNhngRwggUFptSN2iVCfRYl+9nwDlEuXa3cpkG3/AN9ttu001/v+ed58RBzK06z/AMRQlffJdCUCf7pbk1cOXtoj+q2QUbQfVJCkdJ5yRHAJAgXEXOSk2fGH7WS7bWdJNpWfcR5Uf4LsHGbOMf6i34ZA/WU//wC+3yRBwbruU/s/coLZHJekfzaUoydLbVgMjM2fwFuhobWyf++6Se//AOuC773OazMZsRagOE/4k02mQQ00lZKMOXmFXdZ7ntZN4l6NdERBL9nY8Tfiv0l1NzbKt7Qn819vYmTvv8SbI6uMPdPHktw93aV4zqR+AntvaQ1ZoQQ9+Syxub1ISwlA3l01v2YTvJKLbtODf8CAk3+021tt8kl/v/Rthax03n18wfXV8IZJ3oFnYnv/AGS/PXv/AAMCOXtJG7VDU/cBEXST3ou4NZeb7KSTX9tqQLTYH8koAG22+P2kt9fgPG7MGPD8awOYSErYNpBMpEqDVIO+WSa36XzNsb2Wz+tDjpaTmKkl8GoSf2/22/23323+3/3yT0Zxw8Qwis1GyWQOT4LbaaX5JEklkttX+PwLgYsIKiT3g2jT/bRXT38az6ti6cECX1n3/wB/vvvvt/8A7WtfJKQMG5Hm53kjg5Z1kgNt7pbbkbWWkN77ftqb22gpJ9gCN/X7t+aPlfNXfyffy2pJp7f777b7/J7/ADbbXaZCbuxrlslBL/suT7Tbf/33/wBsuBISnv8AbIYvC2EtN9mmJbz/AGVv6ZW6EX8Mv1shCQO322+3/wBs398kmn00S0aEmA0t+k+zL2+0kltt99/++QL/xAAqEQEBAQACAQQCAQQCAwEAAAABABEQITEgQVFhMJFxQIGh8MHxULHR4f/aAAgBAwEBPxDl4TGeV5ID++Ie4Hux8d4/Sz/Xs8kf0Kyzue4hy9ttLTnIsZHLVUzF9rffOSODpuMZZM8kRHpZtt4H/wAC2yPP5HSAnuUxxnjutIWQ9I9mUGWWWcsnAfhNehtltvOTzlnp2Tki238O22S8iWXbvjLTnzZjc5hgYg4MaOBIK5yIoJZzC0aEYdWnCS7duHBEcuJckybFmXZG2222238e22WWWWWc76Ntghghzkyz1kc7Q65i946VHwD1Hr94/HtvA8eln8pH5Vlbb+HLIM4HrGuB49IA7Dr8ZHpBn+vI/HtvrI4Yke0uRC3Mo3kSMBsc9+lJsh5yz0rkmeo7gyHLbbbZnnbfwjD+HbeXhjY+vLLLLOos8bQhQslcKV5Xh69th2CIEyJS2Jbbfx5Z6Ts2Szbfgv4L7774XshTmJJzbttvsvssfeXPrQ/slsRBbi+lfSk3tDG87bwx6SOWZ+O+q+jgAhltvLP9KbP5SLLPxrL+HLOfbiO4dRCM+gHj6zbYZW2zGMZtv9G7JPgb74+W+y+yPJsi+cePJHa+y+yb73ms/JPzQfdnMV9190WFlBfxhDbbLJZs2LEIhz0mbbOdt5GDZZn6plkz+PLIIONPTttlnDEll21wyz0MWlpzsduyHUJCXS88nnPrhjnu7ttiORZZj368s/LomIQv4218SQ02AbAz3igavxYL6bHLPj3s+djtAheJRPM1RF+ozGybmi+17hr3NWDYznO22222/jyyyyI5ZiPwjPDy9bP5SPy5Z68s9LN5XhHmPTXneP4cILbZ/qAmgL35houo0N1CNRBH2tTvFoa8ET8DAw3222/uiU+H/wBQFfqAyNbF+R3IuMvwXj/LlnO2222lpEHKzZDZ6G2xDMz2HDHpZ/HtsMNtttttvOS+nbbbfTlnKSz7jyBeHt0lK8rott4bZw6uoIZeC7I+nbf6EyMtp+4rv/djhe5xfVsf3l75ICppCYe5Tbq6hZxPm8m8FhHnCckU+ZT6Xd7J/wByYql1n15yyyyyy222223nq69Q8fgb6SJm8vwWfykfhWXnbbbfynnePpnheX4TbeWf6XbefJeaV+C+GeNTzW7U8R6W5MOvEY34uoO5PRDIQYHxe/j+ZprwJY/VqzuI9yvPHeP8ON3BYNu7XAeVjgHhveGNL3yIfSZZbbzlkRLMpunrWbLPxkW222228pIy5JOcbGyyyyO4TZ6FhPuPUJepdk2WEcMs5XJJyYsSzzlnPXzdfNixafNp82nzafNp82nzdfN182nzafNp82nzLkbnrqoIG7gDHX5GsY7InSBHqNfDfRAe6+5eJqO9q7QbdwsuxDtv5U+YUcjByl0g9e289eVlFljnV7KBIQ2JOzRiOdttt9Yw85Z/SkfhZ/GDws8s3neHB8T54Zjz/RgmTOQ5M/GAQAfojPK6O2kxm5J/gl4Pe8YX131x8MfDwH4L676767676/RAN6F1J+HLJoSESaz1HABKeJe9SDGKoiTJcmZgsO8a9IMFsJ9Y7BtnG28a/EBvOWWWWWSzCbLPTtvHds8szbdF1t0lW5CY8+hrgmy21wyz1hhtiBFDFowvPiyP4V1V0conamRSWwnD4mj9jLQW22FDZZbbbbd3dtsi2hlttlltvpWbNsWIKDOBmWQWRHIzyEc7bEcOltvrGeSP6VJPw5Z6WYdwdR6Xy/CZZZZ62eKBmByhnV1YLDyHa25QMsXV1DTJhPLbUUPq/wA+fH+pyyQ45ZdvF7iUlOSN2RLsmyy8gQcLbAwQTLgNtttsEEzyQ2WWuG22WehvJqO+cslknqcesHqWzeE6I8+gby4HA7kyBfEs83i7KShoM3nb6Vi6SbNgkZHO5bfhmM0wejZmn+Lo9P5lsF1hXDDTGSx1sptfA2AkfuOvYdyAm8mF09modjPmWaDecs5yyyz+lGZn8QPIImYiI5CPSQjPO22222+k1FOZOSExsecsmPrEenLOPtHn0B1GPPAovaQ7gPN4qRGWScrHtkpvpZ4L9JMFl153e46aHytAfUlxZN97wWa6AkEhHKdyzDFgyGBvJu7EsLnXfevsWHqHepCcf1K38LD5sPmWcnJOTIbT5tPmDklEfN8iD7jD3jPmx82LC63IPuM+bT5jM3ZOSWI4yV5tLIGNmLZZb3l5uoVNySsyxsbOGrXCYPcDOrTchCPHOrXL3LlFvpMyyW2+kBlvUEAtth1xC2Dq7sKRYvE98LPySvvBe97pLAfQwz3BGgWkg4r4enzeQ6+Vog6h2Xj2hcLPfxM1mz1T8sW8vpF1eTCnXiHy2MQT4Uk75bgXjN/C/hz38XfxbbavtDvtKPVtn4QSPglvRYzfxfxvrk3xa+LXxb+LfxD+IfxfVCdZaFHGl8NPxr6F9C+tfWvA0sY8gdpi74t+ODYiIguAtIfCx8LfW31t9bfWwCKR5vmGV7WWWWWWS/OQv3L7C+wlLkdxD0sss2ThfT9JINjfpch6XadXW3LpKSMrM+PSAQenCV67O7fqV936b7n6b7n6b7/6lTN/q0X/AKMH7v032v1fa/V9uVM3+rD7/wBQV7OdinF1fys+V7riE2hgzAQxWvufq+x+r736vvfq+x+r7n6vsfq+x+rBzX6j9V+pNk52iPw7u4zqHxF0S4CU8zJkjyUfRBkMepyF6lph/N/2Tf8AdX/fN/3zH/6TC/8A2ZAj/eMCXZB1CoQPiIJ8QbHzDq5EQ8EPmajD/gj4P6j/APGn/wDGtv8A5X/VXZCf2s5hGEBIXmzJQuuOm7Xg4iPaE8ODmW1EEYgsOyZBvHVjYzqVbt2rUt95YIR262OTcvBPUd8gQSlm2WLRgJsW3b5yLbeMkeloF8zwZ7SQjaxGEbh4AiD2C+kvrLPws/CTvYu+yQnuSPuQiItg5fdYPeIOrvxOekbBOrboQLtMsohzYX2vlhLtxIPg29qvptO5HT4jPIbbckR68s4hi5AMNkDxG/aR7lvplm7Lq9kh4No9Cb1M10zssurqIEEXogg8YqeFgD1JJ5ppD4y8/wDPoSI8CANZD0vgzngbKhkjrLF5R7l0wN3XpYSsqVh7LZ+ImX8F8qu2fqmHiUwXm02thiF6cLD0+RKtW57T0imtcBApMPA2DlsLCyJE7sjtHoYhUYm6LhHdHbo+l1zpeZEZyWnII2wsLq6kLIeaSZ7rXbFn/cljkw/iJbnpDf5jzDqLGk2vWR8DbQpkN0xiO8JAj8TtB0sspPgHCfKI/CrZWL5rQ8B8W3j/AAvACldZ95e3vyu2afMfjKiH3K0sb3CxoPW2jJxK77MEzp1bRT1KI2vdSw6b2Xk1e/6byngPQbHs+oFRdZtsQ2CSPqEAPizLCSehnzHEaRFmkZJraoEtWuy6sCPhqwu7ti4ma9gRx+/5h8s5Id4PQNl2Q9Rh5nHq6uuAm5IIPZZ+JBGvaOl3R3dJbYe90ZS8pPZ1fJfDfRafEAQ8D3lvvdurqQF3w0cBIkUM9Gy1s6HuziF0IROn82jxIggfEh02Dn7TzrGOzCFU3skHC/drfX6nPInSOkcb5svO3dE/BdQD93lYghruL94zD+5bXkbaHnkLbhKXuOruz/dJ8M/+zzIfcpAPufJV/M+3D6YlPRbtYD73cgzUT7XZ/u8EIj8LM4H+G9vhAI7MIX+552s/SB14JJPaZDPLkZN1pI+jmQekG2O4/NgsXZxdnAZPxGnhGX7ZxvDbCPrPiwpcXp3v/Gnj5rx3S1O23UdOiQAYx1lm+aiy8h58bSQurrnSvm15yxYO28F7MZZaz7xF2cCWzIsI6jg+YA6ifNnbEcLs4s4MYDzEzZs2eXud3V1ZZMzN2TNWs21at48SGyV19v8AiNdu23vPuyupVg36s4xpO2JI75Y38pZhdP4m0CxOjYS9JgGZZVc9fq84++GRrs+1svd/8mlxmlu+E+U93t9MAlYnxYU78zcrf4no/wAPuZHRnsKfITLSZInhcZlvG7J0mAvtf5t74j8KZbonxLMO3P8A3G248NbOAy+SEDLISXi8aVhRCD0OyPTSYkW792klXzYR8yPHqZmPileCwW5Nk+bOPJap2dwz2dS97k8yRFA7Y1HdnAc2BQe0jxntjPBZ8Z/EsQ/UBfmZJvysJBFeCQF1/wBWFcHC2abo3d9m+zDl9QxeEdSnU5mu5Qi173A8QJixgca8MggktHYTzGHSB8RTZ/CGSLe8vklG7R1YsWLVsbNtQtglkJkJZLYe6WW3trLqckWI4PQg/uzKD5P+JTJ1nPoD+JNqD/NndYFoa2abhPMezb72sHTE4wjPVKg3KZ3Vn3d3E3a1GHSfd4SkQL4ka8WCvfIwH4lz2sEBsjU6usdgwC9rP4ujB/m6RMluBshz1PQMI2Y7iy3vLvvjbBPzEfjMpNzcLm7J3doaM/Nn5tFfuezv/wBxx68C9Z4cMmOJ983/ABfS31t9TfW30N9DZ6LJC+m+md/E9M8zbPm8bIZ7Wj2tQG3vbAFXYH/EN742jP1Fw32E/ISdsmGwybqf3EgPn/iCw8QShu1FnqA/xf7i/wBxYez9WPs/V9f/ABfX/wATS7IuAU1rOQvmQtEzdXVhYckcfGsqklmzyRJXg1urYIA20pCYyEhDuOlmx4sWefK/zoWHx8wvB++LTBm+l+76X7jWq7I8MWrg7q8w5Ie0K9uMs+F/C1e1oPEKm/MxCZTGOGd4H7lfZ+7wwTHTt9D931v3fW/d9b931P3fU/cP2fuYAPHzGz5sdIj8Kifi/mJK7v3SGCKwRjrGMbKY2FEumcJZ3J2And2Kk0Bdy+Il/wCL/wBZBde/4JxL3fRCaeD6L/poK6/qdMD7euf6zhE6kpmS/glfESaXqKFuxdFpolku721yEZb7P7vu/uMun7vfexUK7n5upgZ1AcL9y/eIdXV1EPaZ8WPix8W3hLDoirZ5yWtrBvKcuF0hLS3a+gbDLtbHkprIdSXteAL2KzleUNsE/hM9T53p/O2ZHdRWpqglq2VgLFpY38p6t2U9wh4rSPScEtQMtJMt+a35oyowIqTNvpf8USzGMduwvck9i/kv5JL2hYiMQXsM+bvVjofEoDzDe2cbsij2hv4z81919l9l9l9kt7yhedgTzZxlnOWWWcfLiJxDDpaifc3vLYIlE7D3yEfnyQ6xKfEzTwsHB+k08lsk+CKdM2RlGbffffB97T5uxtyHJDHBnfWXM1V2Yl4UDX/vvHSGV4/wOB7gs47WvpMcnpAiKyRky7OB5G28Ey3GwQQbxPqyQaF4Iu9u+IxK3F56yuSr1KMQQjDCMTrw7aQOhHbLK6XRkRXYsnSnH2tJ48oLOWA7tVJZhIOp4DVqR9sV2w+7KZGyGG/wX7e0M/V/jfgm2/lWkusBLr9jMjJYSbM2yoP+Zq8h8kt93knpDo/EUQ92J8Ux2+S/QydRHhv5XUh022yIwMh2XibDaTjDWiMa7NWkOtj0SMkHZY6/V1InmsE32IYZebmIcbJsxxatWS6LrIuvnjPedtsjszGlkKwPOoL2MCANIdrxZtJLsvBGG6GKrDEJFdThHkJfzAwUFgZo22BixZMe2TIp2SvgkRoCMvR/xLvHOeUDxlSM5HpZ4t4gIl0F29rVnbW83Fd5XlwR942f2r+87Fjl0Z8S2m228ttT1bbztvpyy9r39E28yfD/AH3vKBIWXHIhH/JL/F4Or+S+eTMjBm2j5J/0JxpfEvqvqvon4L6JT4np1JdrLXJwpkS7Rx/tZcH+opXOviehCtmOjcOb/wB2bu/TBuXZeJfYsyTLOcsmPLtdoScsxE9zC9sU59rpDljPPMo7eC23bE4p97wEQ5p6QXa2PSkcQhJkwYTC8TMjAPdF8t9Vp1kVSxtke0xbwN++MvotPaaccHzAbtCPcb/Gv8m8Rlt/4rvW2xFlksv5c5lndvl4MZev++8GyyB8JZ2aLbbnnPkhn8d7C1ed+JFZHgf8IF4H0Qpc+1i7l5wvpkfPE8A+DxmIbSMe0QPaIkpBnsRhyhHuj9SRDNkX53ipE92peg7onAzMQ+LJMtLSyyyySbu3ChSRUvLLONcQtYhhKITL5z5HGQm1K8MDyymdSLFtp4iPNmzyBiMFtstjEN4hif4k+JUdXmoDJTZ36nxSj4n+MJ5WHixGmPNrYoKKTPiX5x2t6EeZHuE8T8S0PzwR2L/alnMQ2LEsm87bbbwxbbbbN78ll5T4f778h2cwZyPP5y7/AMdtwiNFmeYXvHvMP7yXvC94zwwnpvvvus3zFkn3TWrdiLzMZ1d38JHOWW2+vtwggUAbdH07bbbymbtZFs/l2222231mzMQJ0pbXg7Jha3YDk+2++6d26OOAHj7LlwtEoRi3at0veGqQbQ3b+O3/AJpve/xr/J522238+WuL3tJ3Y7P++90hWCMD/Bxygf3Cfb+JAr4amB+WU977bP3ke8j34zd828GEZvnQ+8W2aXXUz4Dd82rVtvpCPS2NtttvLxgyZ3eQL20itu1Z6NtttnTkOjbcIH35222304scd+vLOTtATuJ+LgCb34CBeaSXvDe8RxxvctnyiE96lBCxJ1JAWTJE2aTdg8IBIj9QCZ4ZNv5x7Pq8r74Ytt9e28MfkCt5x4/778TOy7T6lzyTP3JD+xtyc+0c223btWubPHFiWWCys7uebdztvrI/KsbGUlg4Tgxn1sRDL5/Jln5Tq2PIBB6AmyayQWMrnRLZNLWCvwz8E4Ny3TslMyDLuEw7urx/dh3n9z52YWWfl231bDZ2Xv4tnizD/vvdIGGOH6ZFnjdBAJ9EVM7pxgnyNWua223ht3yASFICd2+h4sW222ww2222228ZBsNlHGQzpY97+LGHZ6mV6xOjYsLbfx6WnO2+tzkyaTuRm1hpH4WFlgfTiFMvbIBG9oHtbeIQxqBEllNmSW2IWFrd97933oLwrIMsss9O2+nLOdtm94Wzj2glDv8AvcNZjCtV12rP3/uz99pVLmjpz8ZHr31Nt5PwEehQmWSSRHNtvp23+t3h5LvDSeuBmcPRLYQhdLPnzgSG7wBaEarCv6/bIDp5mOE3hP3Tu/5rJxHxbI+0pZB13CnUhmBHV78GzVq16G28hBZaFttttq16dejbfWEEKOLM2LEhl2yGCFbbbbyY2POWenLOcsssssss9ZjPcHlE2GOsEbV3bHU0ZORsMnE18S6tgcNtyyTwHVNY4jUtix6WLbbLLLLLLLLLLLPTlnHme0fuYYK+5+77n7ncDvXO222y2Gtln4csiEY+gz1qMjZT1bbbbybbFKOFzlllllkx7/8ADBz4JCs+5dQmS6lLNmTOPpoM7Cw2WJ6BsxHp222222238+fcs/C0urXepUd228mybt6Msss9OlpGEGSz36ct4YnEk9oL1d1dtd2W2+g6xqxYGBiZ6TLLbbvljnbf6nbfSZZGkYsJ11ae7FAe8EsWb7L7L7+P77777L7IhvhgkBYskPSMJmIeTbeMbGxsbvnbbbeGLbf6FjCP6HLOWbLI1C2qEIYS1ekhClIentvryznLP/Bm2wyC9P19l9l9l9l9l9l9l9l9l9nNBW+Yz/4gsR/Ss8krx7Cds+y9JBBBB3B/5cHcDOcLLW1a2tra2rVrbYWICPIz/V//xAAqEQEBAQABAwMDBQADAQEAAAABABEhEDFBIFFhMHGRgaGxwdFA4fDxUP/aAAgBAgEBPxDr3xHR3RLC1ASOUDz6Xd6SPSEdWfpnfoZ6+YmYjrs/8FFyyZsQmWPo5jz6Ax2QY29oA094Jg/WXi/cWBPJH8l9Z2dDPpPQCPrnf6RJPWd/rBekFHR3SwTtJAYQ4xnd6MhQWpl2TYILUzPrMs6rnoZ6ZZbMqIk6WfWGWWWdVLYYREmzuEQBGIEJEbFj26GJFtjMuNjo3mFbWDcOT8FuEN36AciFNdTiCdGLg6Ey2WdNekCLbbLLLOuWddtjvD1222222fU22CHJdk36bPod0C3RxdyvQ7upHVnqRLxLM/T7uhmI9IQdVn0DPpvF0ErAmt3bm2BLbSGCGTuye/XHx0UEC+nbeo9A+gjqGWf8E8x9Fj/w22yy+h5kjyc2QWGQ1DkueoEHXZ6jDLsmzNtvp1a6hzLJmLfSQnUpJcWlpaetthnsXJ1nM5ndi2WTxsYLDvRtKFkwR722w/FqOx5LOjLLdhNu3J0a6hMOCMwh69WrbfTttttj4huyvhvhvivikDmRhuXxXjZ9ufakHMkPFq3BblzZlq1ce5OHPo7bM+nUhlttNoWllkR6yOrP0yJn1kdRn6bPV7bvmpEdQIcnWZOtcFydBesNt6kJlnpApcs/4pmBIdd+Cw8R+tE4R7GcO9SODYn0cWYjU3pXsxsUKn6ONjMqyy4QFizDBJLDZ6CHrttlkRbBsqeLLLLLLOqdAgmemekjmOLlLL1231rM8z8oUlttvRm5RtljIMgJZaXCZsiynqpS6NtttiAdQMiu8JjEdRlltvr236O6fYkO70HnMgQmO1gyB73leXMInQ+DWkjYcwHOEEzjfeIOHbpOAzghNGjVIbW9rLOuWfRItWuvtsz9EiCC7PpWYiZiPomfqlK9Kxx1+FmQ7BcLCLtaEOfUO30Q22dybFP+VACntOYnaezzAeZF2JBBcNjGEEow2hFgxhrvtad7xdKmhiDmS6OOhGB+roGWWWWrOpttixLsnXbbbbLLUREoba9DLLLJlhhtsiPU4W2zNlllllnXbeoQJE42IWlk5Jd0WWyd6C0tGTJcsw70HaFwtLTrixbbbbCQPq7bZZ6zLJ1BPwsCYCcC4HhEXgyzJx4E7ks8d+idhmZ8SfsJeD3YRHBcWava3HO8Zi5MnCPMcQjvqq236eWWWWWfVGHiZ+mEdSLYepHVn6O2222lymcz0BEzHeOvJ0hhPHqEOo7PVyz0gQ/4LCw+hv2UBZ5uMubKdy95VHhkHvjHnNlq3HGz3ewUfNoQ73iDBBSwW8l2wGyyLhHbpv3309tWWQI5ssssnE8WrPXlnUMhnmV6dt6MS7JsQ9QFjoTbYgdUktt9OSS2zOJY3KPEWY8womY7x1wMywLBmSIhRdnqGkG+kIS23rsG3Ptc+1z7XPtc+1z7XPtc+1z7XPtfZfZc+1z7Wvtc+0K+L3J5JePEljFgzCgu9rexwNEhG8I25ZG8M76JYzxJ3RkeGJ4MlcDZ6qA5GB3E4dkURsZNt+iQmWR0GFh12MZ65Z9HbfrkfRZ9e22WT0Hf0PLOrMd46ne8ZQczPUIuzo30Dv8AUCzLr3te98l8lu3atdfX3bX36gOHJuSXEyWAXbaeQtJb3Lip8nWPk9dABJ1tt9WvT9DbYI6sQgxuFbi4mZJ9OWdcw9UbfXi7yumWdS3rtvUOiSWWW2+nLJUpuD0DfVMsODqPMoAiXEzHEQYYcQsbnqEOdGOuOmWdcDW13LjEN4XJmLJzF8O+HfFsvG+Bez2vY/vGS5/f/b4X73wv3n2373sH7xQ4BObL2J68SPnH8yd/5cl+rVIAJhYXfHqMstt6lPXzbZjFl+iQmWSSc+sIJn6h3jt0Z+jtvpeD1DH0uSEuIeZnqRdl3evbeoR6nvfa7n3tdomWthDGFdrzOh7kkGOQOWycOZU8WHeR2gO/piaWFljPJDF8XJelnqR6ez6kBtbm5h6EPVkkS7bHXLLJYSBaWk6lWWW2TOoRM9dttegyyyCOiJ5mLZZ6cbGzoOlFiltttspJtlllkdjhDS7MzLkGxEj0FySWZPQxZswsO+oL5/a5R5bI0Hh0f4tiZ+X8S8ivGHftlh6HwsbyIPk7QVg/t97MozFmQqVjT2Dz+8CBvxzvf8QDuPe2gZuQYEHz4lmQe0MXzPWfaY5QfBS8C/E7Kzfa1nuFzsWHptsyrLIht6ZZdnTlnoyyz1kRHVmyyI9LMR123qeiRM9csuXRlllnrOd3+iz/AMBAcLeeWZ6pEz6Q1OwQPWqMs6Hk/aCg7PEEb7kfSRTHsP47QXC8O14q45v3kLpc8T7a48xUPu3eiTqg8PaT3t/rPUeHaWw50/mOUCY9Vz+7tfee/ahEZT3JMzLdto2CMLWW9dt9JHXs9Ujrlkcy9ltsJCe9p7wb7L7JZ24uI7BanB0yzouQXPxBYJh72HvO7OlvizItJ4sdBmV6rAd7ebPBd7uA/N8L8yPcfm82L435vjfmSwpmBudiznIdXI5tTj1Abbz2y7zCdnLmWPtY+3UdsvusDuyB5kvMe5ZeZUQ+5I95R8wvN5a70n2E+yvJi+N+Z8bKOZj9j2JjpcWLZCFlnXlRr+EZO7jYuxPOQaA5PkDhmfEIGjyx7w0cTmhB5+x/sGBPt2tJ5EIkHBfJw3A/h7+e98oN5ZC+XkEAECJjPdvmQEviU7ru8dDQ4vElr0TnDMGjbbc3NlllkPxHwh6Ozp23qQ229cVN7009rj2g+0H2s+1n2s6gZH29JPkt+Mb4d8O+HfDlfGfZwPDtijTnb5JQ9ptM6YXFtt6DOzWU+1vtb7G+xvtb7WGBG6Y0GzRn3keX5n3H5vlXyr535vnfmcS5SafkI96PetDk39fZnl3d7535vmfm+d+b5/5uzfmZfqv1bENP1uQNRr5hvNhYdJ2qcjm52vuSPPo2B6RIAdrbsyyvOr5l8y+ZHuYLzlKet7BmNj1fcy4Nnof4tTNfi+b+L5v4gT+qM9l8T/y+EDf8V838XzfxDP6m0h+K5yP6MnChZZcJkKj7dV2SXaAhLhSu/wAYj/HUD5l8y+RfIvkXyIg8pi6I7l2fQ7bPEgt7luyB3oFiXwXwdEN467fBCLli0HxeyNBhXP3m3/kmf+2YX/ZuTP3GR0/MyTNfMJxt5sqSHOTLEMOZ61JIjWXIbx/F8H8X/wAS+H+Ibx/Ft4/iQ2OIzb3RjyXfYJxubEblY2HdRoxcWuwSfYv5k2zw/ieHvcHdiqEyD1PI9pKHzFPWh7y+Bz0Ao5sm5djXkhK8l/P+3sn7/wCyP/d/sP8A93+3Gfuv9t9zw39f/kwdmZ4jZCxnLIM90Nc2RNt5uw8OM57zvNy5EsdcQZ4C2e7IeI9me8Msn95He6dA5DosdgzvdjbZs9yR7tlNnFrY3CK8j8Xxb4sdzH4uHs/Fg8H4gOO+PfHt/C9lt9hC88N86+dCewiL+LPuWfcnRg77WRTxayCWGi3ZYO0IbBOJ4BD+En0M4dg/EBNYRPCDfudBe0jZZ123q6ncddhHKCsbpMOEQ0L7774V2tHbqR3iC3dl9p4SwnJacjsaOWX4dtHQpNQfEUvtZ45Z0Yet6Hu9U7M+Geyj7lnYZJyS5l4XkJg1kz7yv3K0KvDc/wC4i85j5gAP5I6DM/p3ZjhPmD7Y/mTT2CZzYDfSaPR8N9zv7sPiPifDKeTj49pQO/knaOp9s/8AfMSFzPjY7YcnyQ84B3gPa35sXZgRn+Q/u7dzCd0w92HBye53IrCPNhW5/kq/P+sji7sHC9jYcn7o+Iun6vMheAsownB72hvAwVayI6B54v8A6SPaMnE8yMPB/UX7PZiW+Yv0IidS0NnY2E6X2b7UPHxfPTQGgTBey7IN5m8pZ90hw0lsbYTSIlyHbtZtp7WntJbDpZinzrgISAqeEiXg3kblHiB0SJZpM1pIeQh9gn+QSItgCHL7wrP0RgInhp24kWk0UzJgexC/itKMhi73HvEWgnHcZBCfMJzYYL3uZ+8tyCWAeO5zzbsxdpOFD7WuGc7290/qJIofOf1d4+f4nqucu1RLPO45Dl+0edjCV6O1D1+0ihp3J8ZZK+ZdzAh+5Z6L4jjHmDF7xXeeZa8HLvNRsBjwLbxHsb3lOTsfsMZ3lkfIn8wS3tE3fkmxhADY8m3Hvce9oBPDA/8A4bL2sOcuadblg7uLnxRN/Miv4ntRgIGrbxP0l4xa7v8A3eKbHxwbhxbmef8AIN+vKn9QtMeTtFflH9w0x1OS58w/XzY4Q72chfOTufd/9+kxvO/e4f8Av2ScAC3Mg+2fafuiON+2+fc/MoA8PfxZq7mkDB43LjUOLi5sj5hm7xEeONvKg773ihG4fxJE67Yy+ZYXsfxZblubIKiEuowuQHdkNtUKXFPvZPszyGmOOSd+7PIISdd8SlG24ni5Ktk9qhBTbZOfe0t1kMfMeHUsds6KdG820Mfm0NzZhR5hLsM0a7CWRYPXLjfEszrmdzWBvn/uVbn62cr9bcl9jJW/quMcu0nc2zAPfa7n3lWAtt9ZE4+cI8pCZHBh+s0D8y8JtLTEEuK2jiTIHNp7KDfygXfm/UEXQjDvXP5loNDH/wB+lzngyxnLn+WfuLYvAteOIx/LO+0bfjtbfi5MKz17V3ftBH5ZKHJGOTIZSnHSYNSJluwC7D5RhcZXm595riM93wjKmQD9ZvdJd4HCSNky9ALgLHtfZAH4mF97f/8AVYS8fNo/+W3KT22dNH7sZxzPI97bx85z7f8Av3iBsL5uVOczJRqGz+bZAM8W6tu4U5/cKZpPIOhvnLknVYEcfa7f/wDrbBcxMOEUxPeehz7zKQnTvPkIRLjbs5crhhxHLGms+81+4ngfEOwbcccQo4QZ91uWbvvEj7vbsjsQH8Q3OfEgH3/u/a9IPtNgLebNJsvo70BnGYmnFgfa4yXNtW4lDC/M6ILB+2ae1xXFt4efmSHlgSuXoOAAu2PdYiHGweJZec3+F39IPmc+UdfsSPvlZ43Ggo1MIeBJU+13vv8AUXRYlwrcg132YDmSkJQDmHMLcmahIIhs2wGEXlvKRTsHvCPd8t1R92Smfra3k78ttiwDgmK82I48Q6a97Vee0KdizYjuZN4SL4n2r4r4oaWKoe1rC95jekqKR4+YA+Ys3xZyGUwYhCGT4/fYQcPtKD8FZMfis8/sRofwRlrb7WovD7XEfD2v4EIRp+CafgpCn8T778Xz/wASh+SfvFcuw5UX4Z95Blo2jjMmhhsxyQEWffbAI+wn76dlF/u7aZ2bBD72IIsREeVGFm0ksiOcrdA0LWZXHy5JaJqMkzPeQVUEDexeR0homd0FFb9pDhs+0mFZ9pJyrNRrB5fB1SmvFtUG7/DbGK7ZYO67fvEEgWL8gP4uwLrfcSQ77WytovJb47AxCywQN4Yxtw2SXJxCD4tssdZjyMfi5MhbalzHmmXLgXK0hK8IhPiUrtCD4sCbptLNxV2hZG3h12BY5tkcpfggce2WdRGXaU4gH5xAIbL3nV5SNlnrQkJTjlbgjCMSbsvutjRB5G0wgZsSi+pE5l4FcwM7/wDJ3775d8m+TfLj3swJiZb+l5r+IbzvJpoanbjrC2jv2/7vmXzI95DHdHUX4hKPxD6L8SH8C3+Nebt78r3W+S04gxhlujMnf+09+wPHxZQPwSmo/BYuH8Fl4/i+L+Jb2fgk9j+C+z+L7P4moP8AEoS/F8G+DDU0IbCDbv8AUW/+RA2H6QfnT2+WeH7F2RB8WhAzW2dlr3Y25Tz4kDxaODCtwwIH5nbgzAQNC41A9S0QPIp+9K8tU/j/AGBrk2GAsjCCBY5E07LwyY7J8ZCWArP7sdB2tvJiSYkbj909XlZ07XLC4SteZ78wgdPYlAFHJ6J6fi4bzOllAO9oQiuLiMJx89TS0tfa19oHlaFxLcFDogoBmGfWT6A8lQ5Cce9rhM/R5WrNjzbAuEFucmXk8TrR6wPVzO35tAcQzmbZ7YgmqR6XwwF6LJL+2XNn7JJuP4i5L9kv/mEBP7BYtj24Ia8v2LtX4l/hRdgH4D+I/c/iHA/iGIfxCeH4svH8SPH8TPH8RZyviKHR+CWbn8RyI/ERpb4Jdph79fWFTmDxLAie8/8ASUD2P4huj8zfKEOOjEvZD4tWrOYEt26wO98WhfNyu00aukk0P2BtGXDDBT+T/JwRwJtpkju/kf5LPCzoF/J/kSeUziwkPLLiZ4l0nNXjLZHlbQbnGz7pMYrs7nX+rDJxl4f3uMED2qPQuxgHBYnayjEdl/qYZ8EOQSR5gswrYkFGBVsnYd9sJmQIeS5ogEMfZPAhaz+cf0j8zTCHzOn+59x+YVufvA55AgebbJyk+I6975ry0N5guZ2Nt/N4mAg4Pe25aHtBZ0C5zlJRPEBOy+V6Ft86+dGuwxzUrugHeWfohCBaZRJXVjOHSSQYYtuRgkPmNp4uE2Gn2J8nZiLskGFq8XC701zGKTFxewvYXxTg8dNzYGIjl1zrOkOdvydh9r0Heuy/cn8wz7B/EOEcM/SB4hZY+f8AYjzL3TCPvAUebfYVjv3blM4I+9EdXlcLuExxyFoz75u/583PFdFA37r/AFYhniQTuzzCR9pxdyhzmDOLfxPv8ygfEOwbcN8beztJ8btHUsfokiyv5zI2mclcUm4BUJCBnblzm4W2FNzKo4aRKgddqRmZr2jCfMwV8RCbL8Euclk76xjLOu222/RHQ0bzsLxNu0s4zzcCBYFiH+Y5uYH7xT8i3iCX2ia/eDbYfetW+SFjotYC49+gumEyz7EhmwY3p5oGiMCdXCY6vzAL46sO+/RWjSXAL5/smP2j+Lhcg74Jtssgtt6myyBcuNswF435/wBgf/T+Z7jn9GZKavh+LzjOg0z9m3+rAcoGfZtEe8EFlkqFE+HCiwHb3iF/KIeFfhs27QAuWclaXANIbDFcLd0zvny+09z4gnYA+RPnDxLTl4a7EXC5eOtxxzEQ8EpDkeQ7sU7R4texae1j2gPED4l27Z6+Z4QMEYO/Jd0pJdo4mLiEPYfD9kSv7U6qIHDlva2DZZLHlxYFrOS3C/YXc6B5uCm0t2+pzaZR6OejbfopUFvH0NCws9k1wcv3V+2u9cB+0bPf+rAHNtEe8zW+I1a3up96+a+S+e+e197W5g70a1ineI97sF2Eh4wx0smD/EItmvvl/qzeenewaSHn/wDs80/F7t3+WI+x/FoXPSEenbZMcoOdL+l8RfaiYXd/qAcXg6Z/jbP6/QVb7MQX3/uIssssW4Ifl+YU5e/f/qT2f56RA4LusfggTt/Frc/ggWnT4L4F9rPDfrT+55PiRwGfCj2ceInxkgzeX9WOF668za22xU7cjGssrEcGe4vlvliQxB/th+CG4R773geV91w8wlu9ZvEcI0OF+wu90lzXRZZ6B2mbLJj9MuttvZY3aY9iKRtMJpR5p7ywI6re1BJh7/6uMfxLQP7JbwGS1B95KeYfjWG6h3aPwtUsdEneAUW0uUhEuzAAEF5NiAJyXy/1KJbb0l4rjNsfwY/5H2QQm4+kGBPcQ9ixcpJbPEIID0IB7xXzwTS32LZv8t2T/M6MuPkjZ4QWLFxMZIjtA7zvpLHE4gjvfNP5Sc95XJFMbVIPzaTt979yJfJ/N838z778y2N+ZQpgXnHowd3vQ8QlVicNCebDgyplpVwRb4b4kh8zrzGHNt4LTvscjWW02QNn5euwPSexMEr5SZhEwNEPwRxWI6A1ZJbb0DtJJZZKSnpyz1AqzlzS7/57yXhcLTondG/MRrbNnsWr8yvePkvIkvEe1auS+GMdrHtY9r45Pa9lHwiHMSydl2AuSS4Or37lovx122PN+4/yGEXh6dWun3wstW5Zy5U63IvyF+DIcZGq8y0ubBOb8x5LKco7x2gd0WwlAI4+mybcXFixYsWlp1/e9GLCWcZrYCwjO8i27GK71eyeu/tF2eRk48EdpBdLBn5s4cz5ixjXEX7S7n6xd3rmwgkk6s/Rzy6DacLLssmUHayNwlPASU8Qe1d58SMFhHWEB/8AZABwkPBdgCH3JbsS/YsbBY9oN8dAYHwSjYMJ3m4huYFr2mdtuLi0f3mMncn0bll97/JbDwOg5sssLCOCWWQQnMvsu8GbvsjGD7iX4yeastrhypdJL4jIxHBbHRAOWdFtj0Mel5ji4uLbbmywsOvK+duZdzI13kEnoNcmezeF3QkiTgtu0hdgJd4Wnxb3i3W/mec3fsnKQuziMzAIMwSBgXvcmCHs2MNzU8BZZZZEOJ5ma6FSrdu3bss6mlp6Czv1jvG7Y3g7gcS9qMf4sRGxM/8AtkNhPE/dLf8AaX/7XsMYdk+xj2MYdstxARewjftns5lPGL2pe10k4Q2sOPt8se7FRoMxB2OuWXJD83+dF2YIPXhYQtYzGJORYb9y7P7RD1mE0PQDh/yec0ter59oXXi5hm2DhkeGEJ1stxu9dAL4uKD2gri7IyuTa6WGZtg4towEeN5ko2T4ll4WgbKD6eWfR/8ANuPQvOm5N/4feKIQJY8pkhzHYkSYmEipm9NB6nCL9uiHtYLxj20L4T7efawuxfEh/Ge+EvxkPbcuxMHaLVTD+8UaDUhkXBZZZZZ3Ex8z/IbCaSCEOu22LNzjWSS46FzE/UkafYiHFlnU1agOJqLl2jf+OcL42HPRC52OR5uXQh3L0I44i7ojxPDC7XlPRd5nfNo83JJVpBMW4TM84aIxBOPGTrBOPm3zbQIGPdDZ1yy16GWXFpaXFhYWFhEQE5U3dGK8UpW+d7tBdAOxy7sZZFxgyyzozsEtC23quEo8Z5W2x0CIS230iZ/Xf1ed7QTFixYtLTo3qM3Fx1Fj+X+oAFllllllln/L/e9OIW4y7aNpOVi8Nz9LWOldW3p5SJ+CabSgkK9vXR7fSz0Hbrtv1wtyMW+8iHNK9hEThYJPwuDjYh82XbqDM4nTARMZllixLsjYwNu3O4d+ldjY2iMXC0sQGxHNktyMggnc/wBXZynRC7RD/tdt62BdyieMeYwL2wPjb+Np43wb4f5vhQ3IvBiwxXt1yyyyyzqatWv+KAGLm9yG7dIo2O6eMhLXmQWRE6a+LXdETkRAiEtKzxZS5L2UhPEYICbQQ5Okzj1yyZIMh9OLHpDFixYs2bFjqtAZ/wCrf+Lcepx3ss6oSE7OYhEmZZZZZZYsegH0jegVjEIQj0Dmo7jvUq1qnheAynjLr0PaXxL4X4vh2nhGPZfAvgwnjduqhrkj8If/AI9ZvbShih0miLlyRvxDviFDyWSHpsE25NjoSQToez0nj9PLOuWWWfTDyTp0HwT4I99llqyWQkvCIEJIn6IcXFlzsLCwsJITtojSIZgFll2wECyMdIbv2tSb5gzzCQdTHplkhOrsa+sDH/CY+mHCVtrsmyElhYLgwlM/hJXsJc7WUDIgeq/FfFEnsQ3xaeJBkOMNvE9J42rXr10ZZatWWWWWrX/BWWNrJYj6u2ww9d6HoY+kRM2WWWRCbb6TGx9O2/8A5Zbuy9SLPTrvx9P4r4uqkl5YPR9v7/30Hj/x8s+r29LIRH1V5thj0vQ9D6CJvPpIP/2QvJbLIICwsWLFixYsWLEBB0vp9v7/AN9B4/8AL//EACgQAQACAgEEAgIDAQEBAQAAAAEAESExQVFhcYGRobHBENHw4fEgMP/aAAgBAQABPxAnbUCjmY+X4SniPLAUAJW5aA3mHhEfcstvVAwbSXGknuldUbO2Ii7Q3MCGzGNR5S5nqc1Jd9DtbU81Ge0FPVGWCzYZ3D5b12QHpRBdnA1Xm4eHAZD4cS2qqS3V1Kig9jvNPNP1XUMRsD8wLAWThhg6BJJ7NV7mPnWIjVyrrXmo1YFD2EzjrpFuoanXl8xPEpjpFElVs7AO5S+ZdDoWSO4lwrLhwuKN2h9xCe7Rp06evMM+Gx9Dl45iuFTNq3kx8sbesFJTqM12RjHVuTv/AIgE1gOiKvrhxNpLj9jU9R6JYLbPRt+CJ5cuUXS5nwRYQBsrkzUTEL4IHd1Lj6HFKXa8JYm6WoetL4YmPRqMkgFFdbHIWTI6WU4lwrXXvxTr1xPx2qGi3TEWMUtBDkVR0mIvic0e93ZGUpycAW9Y/uc3QamK6/xAJe8So7M4efyL+4rcyw9QO9B9IN10vhSWC4TcukbHygge/wDi0dY/7pL7uCfZ/qGLsZhbWM/mDTnvjbmcVFBb0m/QRmmQIXCsJ6h1vuMgrY11Ikiq42EALa4R9YwuzAwUO4IjLaOkVJ3VzySkPREOCAu+F13lak7m0LbovGTMajJYWGEKppsb2lMXUk9LJvVbizFy9kMjFbPrmZKLXTSMsq5ZK18KM6BrpB4oQwho43EVMNLjvTDuHhsUKoXPRebjtTAsEayNyyiBzgjOeeLjwCnOyVP3AMSarlbt1gFgETNufHeZaDjGbo+ajf8ALwf3GXY5mCYZbOjqXJtcV2ljrVSo5pll/YhiKA2vTMx2Iv0XU8tRDFhoHA8y/wBXdyEXOFwJt3xifsJwls0SleLy+0XuNF9Lhhro2YlA4ss1FyqWhq+kXG4xxXXweZafv4dfsRTZa6qd4aGPi0JF9WfMWo/YC5lEmgA6/wDIvOW0xhcy7ZseAOhDVzY2CicS2lGFqvyicWJ+VHqdA3f6hLUZliiUav1BKkFq9ZMWj3Xc4E2gHMai6JhBlKjFTFS1rXuKaPyKP1OOmYvtcAm9NfcHWVnO2oyXSZj00ZJQDeKiO4d5B/UI2gtXsYzdeKfwrTw2lu5f8FurMwpzBLfUuL8XkiHcMRllC3MLy/rcKoZphDFiiOTHaWDLdAFX5EpJjunUu6q2LXmIuouvrOJbdIG4CnfLAHyB80/jouD4io7NTs0gH0V9walrC+xX9qjpmoPovCWRsoNLuOo3Gp09pQaXi+bhsLPoriDmhcKNNy6Q0uXHYYflkFO5Dk5PHFwDCY/wy/PEz7hVw6aWk5C1oNUUXJq4C5YsUl8nWHDCTOCUXSk56TUk2fl5XU/MMNU/fC+N7YZvLr8W5bEBgV8N036gpeExqlq4HpfGyo8wEW9NHs3XvEVUfODNYOIXfGzS6a2doMFTBhj35gGDTyaduPUT3vFs3g+EMANURd7tb7I8YyMXkVB2w0k+3VpqNDk9KN56jEuKsNA7Q5O1xYaOhSLWRtFmS248wxB0slZh3iCxkT9v9QzhzOhgDpJycRILQo+bw4+W38VU5D8doHJ4ve6nRGOewQ1qi8+SX3aSWnTMCl4Qxmk1hKqmYdGW3ZWbhhbINqTO2lo1+yAC/UVElNRyNd+77SywWs/0BaxwvXFEUAqmcNaY3XfGlO1oo9xjrOAgwOObc3CiIWUaZcq6q7C8RGCmGQul8b+GVSzvJBV2lwEWtWnzUVF5F79IrBITZpZ4iFvrd+67wXuGT0Osb2BfQceEPY0uy9A5iXGUeTGCmu0erUmiYAgA8tRslSM77ufqOXLNNi153CUAYgXt1XzEoEOSaSwbrNrheesuQQW0W/riYLj8Y/UwQYNtbgIopLeqjuBNw6qTBZfRSyPccuqIXOPsn+pk0HY81BbUpFi1eWDxcT1urMW1E4jW+r/uJSunTrV15gjoViyljpYsW+nj5mZifJ3ENJY2FTdDmCT0F9ir+2VHH2ZdC6y9Es2Ks7wGgvq45DIqts4g1UH7G/iPiasWEp2kQ14+vuZ3peQGCZg7y/iXw1HqelS6+Ulq31Kr6f8AUANqj9Ijfij5l/dLe6uWlsbvIv6jev4Ds7KXFi1zUIpzMb7ReXX1gZGAiObiZujCcJP0l3JCsY5xcV4BZ569TF2egErZB5I9FytIYyqX5OjD2l7UqWCiKns8SxSg3WY0EiDak8YDl4VQG7KhJnQHGo1x5CMnPiEXpjGb6IKwBe0mSoza6wxcnMN3hUGxqGleYJLrt8QThLzcTf8AOZVlFdB/SGkyFo6ZzrYZhV0LzbUu3+u8zjvv6jz3qtVhvzce+gUGBPHuObSUfMQUG6xAfC1BpL2PMvTK86pT6DFjO0XVrLYcJh8jcsdPMVK3L0HD8ROGRXtoEoXEciOwfuoBLHBKx22uEbsB6lKZ+4xC1G9a6M3kEONSeTMqZXMe8Bv4GURG7QDtCn+ClVud/UqAcZdBq9zkiymiHK6Df1FlyCw5QnSKnTB2rANEyCjFtZzELRDsbFdZnZ+nblQrfi4dB17jxOo/Q5qkDnzUK/mKCdLV5gCpL4niXzBIPBpFFQm+tFrVpzLh1KDBx4Nj/FVQct2jBSV4zBOBYp3qvxCpOoPWaaAGuJVHDZXfGXLhsIRYsA4qFrNELnsQK5xI5Qb3pf3FbyV/EGAtKB1Z0RkyFVbrpjvCLz7BcKSFPZhdeZnTXwOcVGBYrjrUulfU0fEFh1xxCs5MH+FNVXeJ8HL37ECm3WFVOyhY0RrR2go5Wa3B3hwR8LVbAe3SHkkjbHiw1zONPEdEzR1QOIDb/VS5cF4AYauGa21E7rrM2ZoxzxmZaDnNh+L1LjDJK6u3SNFC4KtqjvGcgEvvMYX8jIC0hVvoiATB5hsLJFuTrNniLJzDMUTHkBedJmw2PCtq8zGCNTDBXYpcKwaiW3jrvUsYdfmsJXFx2rfIqH1CLFCsvuUmgMWJC4rADB/1KNe/+iNXSAaYwY8S5NWJRShaxrc/NAqd2OtS88zXirQfXd8IwbUV+a6RZVOFW7vL1FSRs1IBBKUOHEJ8aV26VqPDH/6uIxDGHynB4jSix8A4lVUf4CV0EMAtFUgV3/SjPnGRan7l+ZNaYDvEIrhV+Z6v8wlQ4ScucSlsI9JYjR+UAZ0vMFpevMENSoGViSBLWTsRCbhqfjItXP8Aeo6sanyIxHnyjRbdSdr/ALl2kYl4lcVkXb8wj5dgafMtKuu5KQlJqm/MHq5Z7Trej3U2iim6ekHZnmRlMEc1ElXHmC7uSvCNy2skBpa7PSdVXzvxPEiHdAMPIxOI5HcYhJKF1YiDUqn7eI5aiVdGZQsAP5zLVARFKl5mZ3gCopOxz0gikNYH8Q1UF2uPxHnE0yW0cc5+GBZHY/4mAYxzXGoQrIWdLUxz2HeawzA+dyl55c52w+5d94WLLbLPuEkydKoDHxA6FZUFMQU4RFSKbGNng5NlIuJOA/NT9QV4CvwpdPfxGD5mJ9Lz5qbJUD7gcfkLI1cumz/5i28+cUVA+RE0f0TqGrjHY07gWj4ip5IjENLLjJodFIFfcXXut28Hk8waEeTLFfla7MUiAW8X4X7SqMpnF2CvqPF8pC1OankIFS+UlDl3zxC/TZzetDuCofhyvLvJjmoIq47ViiDlDl2bW1WQ6lWtbBGL8Qz2VA6EzH3pkFgnDy5+YnHaUyrCl+risMD/AIFRmbld4xezzjAb+ozx2U3h8Q6c3AnMFpFum5U/Hwrn6iX+P+X9wUcNb7/qX63tOmETb1CRVgb6m4U5b5g2BSCJGstah6ooUdIprPeo26tmU/8Acme0WwkFxo5AviV0X7gTY/EfeOnTdFmkuL0vNsV3OZYRrgI/qjQWXyTNV9H1Eix5hzhzZEPxUTHkDnpBVdDeyzWcxpK61wHIihqUlnsi5SAb1zbVQWMV1feZVpouIs9MwTwyOEzHTEBTABLsAqvtisAUYOSCEv1QXi2EtlgYJKJwvJ8Svmosz001A8IbnaWlFCq3NPIiGuE/BNnXpAau+UagqKwlKfzLyO8Ega+JlwLHWLw4tAP2x8ZADqWqM7io4JkTrl1Koqrt/vmr0xHSp1niX7RMpbLsekTqV+pqF3md6nWIbpk7XjfL4nKThTTKdZwZFnZeFdHa4zv7BBNEScGHHRy9pX66A5eBg+Zk4PZL73HQgfMcpMt69ZfEnBR5RFWKtxGOLKh2nsMUmxpyw2BnD8Sd8lfcvsWjmQckvfFRwPX9QtjVXxH4Tr48ylLPWH5s1eRefuU7m5shSwA3ZSQXE17Taj4S/UqZbEN4iMQm9TtBSoNPUHbQx9CMziovaLe9Dw7O8t5n1AbfDsxFRUA0/j8xbKB3gEWtFzDq2dwHYP4YRqzxBDCgHaxcyqSzW25PwjbUd1xhd2eYmJVSE+WzUvIRNm6iO4Ha33g9RYMK7DvC1Ic4KqVLgdViECAtjUqEe9EEU6Mttgrmv+QoLj8PeLkLHYQbWeZzrErWD0kgvnTkcNI9QUGJTd7QlKCXTJOUQjLXQN/8gaEhRyecw+QpPopaFY4O8rOT+9SgO7PxBMwzBNftDMMqY8Of/kBAsA9K8KJVvmX0GOsA94r6/wBw+8L4l/il0q5eViu0yKzi0ywJ+YXDE7cyMPyPcp1gfcNPqXhDtHRXFyvpfeVtr3UYQguPWDY1nF9n0S6ieK9ZZaTaGXOeHf1DQFtdk6kal/tUuuLnrHdwqRuRrPmFwXVlnO2HHjvDkVWG3rthJY9yZyIv2EY5lmi6fylYiyO37nJLhg4RffT/ANg1yYUSHUvP+VMOxIvo3+IB/FTLcQQOfqVyCgOJuAcBgrAOYJYgNdEID0Xdjw/3LNYQZGx+KcV4G/KKINjid4RigEJc4i0OI3Y+QmMJhQDVoLeA1Adk6HP7EUf+QOeDmusb8IZJlMmMQVFiPEIO8AmDcuNr8VPQFQyxO6KdVdfDEoot6kpMjkqywDtAUu61gSqPKTuHa9QwzUPh6ltnl3n+pUJQYujWF4cRNtNdWBTtA4jAKPVDaHhlmWWQBOEO017EqpV3VNwQW9egspvmW31lYpf9ywuELmVWIOGnPZFqo8rP7EDjEXvwPcJKqKZSt4pTPDyjBuH0QrLKQQugJb4923zKuM1gxEMKmzrCWKzLx9xPrU1SDV1+cvEKgkAujT5hQZWgG2y/lxFosAixOE4iOUuJA+VhlhwGdxekIDtC+KGkuVnJf+DrCzP0i+cr7CAXPlIH4QI7Wl5h7jMLzRvG8QyKp3pZWdpjWZfMIIiJ5VoHaKWwCrALMm34SgHPWIvkSGr5iX8fwxyz+6K1dTaDlnJ+Uvu5WUKMKDfe5nDMosfcUnLdNf5hk4N2o8wDnzXiZ9ou3UqoOjv0/qHhrQ4Icd8I45S6Hli5cdZus4hniYSaQupjhi3Aa6veGkC9u2yzrHDbSt8s49TUB5hqN5IG/GZiKpXIxwut1HSEBjzO7aEUPiH7vTAQfbIv6nsAH9E2ZGkWXyqFXQBbG2twVVAHlOkZGpsHl79okoCDsE285x+FIjGyldO+EOIyy6CWe1ECXstUQ24Wo1rGFfTV81ChXhSr+555WZq9yqFqgYklMJsGLeZtgr8HvnUPOUgPJyksRV9BdqRHLFK3GpaHjDgoH9xYhu4gPJXHPVM8alwjimU7wOzkXzEDc5/wLPuAZ2lbBziPS1fSOdj+v9R0xYZ9jj70jhDipvyRnwUg4/DULCQBTvMzDnL6GKZ2aECYUCBR1gn0aOy0GV3aGmpYveeGOkx1KVTuJYWIqOax19Qxu0R9iUKCN551FZSErUF7fcNOIICWJqhe8BtC1kDhvdQfWxw31VqvDK7dbSvRpwRMwBftNYWHuVJUKt96cdiKQoA0D0Bog9Hmqmx9V/GEpLMVEiPVnxcVTaXlWLlbJXvfxcfpSZWO1NwXmSvw/MFpxs9ozZG49YPMVTIZsP1DNvo4MrbHhZl9FS7Di0YsaABx6lJSEXpG3AxBS1pLu7Hs9oa8LC5I9Jh4NuyAYenVBGoJo4Rz0MOfEsYAxtSO1Legu4VvmkcE+QFINMBf3NzK3N5D7hgt8aVffSusr4buyDlQojEi+Y/uDbGWrvB0lcLlDloPkmqAMVhec7jFDLEIegwRReOMxRLorIXPzKJcQErydINKECwsvXPuAQ73kUNPzDdoqKHReCyBPNUEY/2hiI6+BFR5eO8eKpUyLV3tletRfErgUdfSRSQM818uZmemu++xcEO09c4izkHRbx5nHAJcIv0Goa06tpfAf1M6J0ryvVPMuU2B7k4Rqb9iMC41bYD8lQwGpWrTMuwDsIHucs5YT4q4CG2nA7VpEH8fcyHEIkI9M/wx0lYdpum6fMfDz8SajKjdkiUxiD5fwce5pPC5wXPyh8ygtua+YSx7tVyc8zI9mus2qoK6NXpiAldxjvCAAMKi1QcgG02Q3bL6F1vbw4jGllJv3TgL1L7KeZhRXXSA2ipU65nWztvRAKDK05mlzgaaRr4mv7oxsMvuAOyjzkx9w1DguIWh07ysQxirPNSyhD0di5e+yCsJId2j+qop6LAs/wBzvqNdWH+uJkUHRUcqs4SpqvITC/byQjnvf2kXUsZq7YUuEc51QD2pl3SdRg5mCpo+ZoqVRX4S3GPHBTmPwiyoaNBMw+6KiZttsQXXI0mEs9UQhHpW0E5Xp4BFSoq6raOYSwOoMZ6Q7NB0E3LsrVu9xYZHR19F/c87YEKiywt1PR7QIG1V9ZbWDLKAWAejrKwCgHRKV5mTWV31UtWH4Q/dn1GYp0V7lXT4l60q6hoGa/6i2tVfHmpghmxx4uMiyKg07sHxBZqktJ6VZUqb+hNTipCtrO4ZkTQ7hozFv9x2tnbkjGGrRRKqtv3MBKNwLvEEh6gRZa+2AYuZabshXuVQVw2l6+YyHKXGu+WIzXXmxtGahfJfVAd2FCqvNBCC1+43v1vLiOKlgFNyjivcWGTQWVHwWcTnuRwC2wMurFWigr7xCz4l3wlU6dL40nvee85XAgnDEOkNI0B0WbPtCA6fr/qChafeKcvNfXJlzB/q5WiXwb0hE+4QKsKsAf3MtS3PHUvfMoi4yq7pXx8kvHijkSzXaMonBDvbyj8iFQZZNVovZEYhKMFWrvJ5gwXEVuMSF40zHhd50x4gk0RMRBYtHuHNNsx9o5ZC87T7QwvUoZcoRpdjwRbYqQ3QOTGV0UWr1lpKPHU5xHerUndBv9hEoM86lTPuCJRQ6ENPwLKq4KXc6YbCiKthaYJG8rGfx1grJAUwKX74l26XgGJ3uJys00cByQNIyb0GnQIoWJbN4XcgNGFC5WQKBQJMQkwLlqd+tSd7R3o0l2GQgs1gUuaRVN2J2FEEFA2D03X3FKBaCFu2vxcINeQHqePKvMdS7ZD1eSNmrcl+0chuYehuH2vatfKPgDwTXpFqOpEDuEDEVD6aZbIX3vVz/C4lbdlY1frynA8p2u6/lBvYAcy9ubp0Isyge/8AAjCX0hZde+rx+YtkrDTETBwfPT1N5GBzcoQKboqVrWuxzCO+CUUNPDDzMzzQOD31laVUCouZYIEYAUcLpLcjEURxrt95UWdlgbrV1l8yoIgtKaqV1EU0hEkGlMfEZ9YyOKa5lWTqYabPcRunrEiM1Y0+sxLAxVrVqtbjyUc5gBjviMacyhzW8d4wKHkMDSVV4i8YoYGy9RzmPnKRtisX+5l0LL1j4IQLvRfbUcPH3j3YP7BGofkTnCeH8OUyu0kA18hdGwQ8mUzVQ6R1dJcKwBbYLQ37iaDIYSnWNqoIVKvrcMCqIQtHONkCdtc131+4R4llDhu+SALdqWdJArGjf+xd4CUE7jJ9AlocpZBzwzzRbRAefWz8bl2hQbAvrhHdMlt5U96lSqO+sEu+BqdT9EULLQCekGL3tNkJxDxdnUzqFFJFSdy6+5XNDd746SkMLDAVxtMmvlYVKCX1hXRwz7R1MppTXCDAhXxfcGHRVRNusMrC8j5NS4tUvMYVZUy32UWd2xQn3KI2wQidqyqy3DWmUeSL8ag+Ez14Y5UYUPuA8r6Mf3JDkzpV3W1C3Fx5e/K0AVI7Lx6udsqya32mitArFeFgGrrdLGy+MTX7I8Xq3MbdyaiilOzMoGoUOCpxLDtGBCBZjUwgtuI6cAFrpZMgH0Lken5lvMICV0R8QOUg1xd/5nUrEPCjH/nX9cHtvqnATAPciJigi6JlVZOIod8YJgmjjlJ1gzaKyJbxyTE5ClnY/wAmYoQl6cTl4mRh9QV0qquUTaETUiqxCDjhmCw5HJmq4ENnKQVzAaEEaHVw0J6agddvFyv2hQ8PMbbHUD3RHAx6CDKKrrfWX8yre+ZkOGd1CJi64+iPtJQmuRPVqXaNINUsAKF3yn6l2d47Z4PmBG0ErFa/qYaa+2VwtGPDh43ZA1LjlgNPMDecjji4qPMaPLBSl5A241FsdpHCKukPeFl89OwkZkCDTrf5FfJOQavAX+b8Sg0EJ3f4MYwTdtpNN7wK8gm/Jyyo5iE3ZjQKUYB4Q4rv07uuPO1EwtdXwjJKngHFv6lSTt1v9fuWN3QndVlealV1qDJvHeKrsugfqZGtsD3lqBf/AEEwxU+VuxqZIVAYHCrnxIrbiCL+Ii5ELycolmHuM3IIxt8SrvgiuEijBqcSNfHswniC3rqCfiFWsWM5hspyzoHkUyibUYjmqWlfX+YMQupLlbzvmBGgJc0UZ+oB2c1LHTeWWNQEpboIaTrGGMq+jz9U5IXKhz6d2NXkUOaGviGt9TsL17zHd+Nj49wKO6IoMOyzcKtVmLKt8amdmkp1bM4MzEIHSTBxDLSgxno4z0YlQFal54dekoYKdbwn5jK7RBlxdGseYxRK6LlIQ9GonhflgO/lnAWdj6nWt9zYF9RdvUMv1M0AoCLl0aaFfcahgq29IluCPLVBhiLRop181HNimkuKVM7ggEABTlst7j/HcgDSgmxktNm4WFGppeUCdYwDVTOdQ0zDFBw+hhnUMyAlnZKFTKC8KMUUbrvdMdi43dfKO5lcLgepZH6rZ9kStJL5auFUrSJGkWwF06VrvSV5BdS3mUUrELsGq8SgsEXxmP6ZwB95+4lCiovpyxLwQZQsiUW3XH5joi32s/UVtgpFAWwDk+iZECZajPTCt2fgtAfA+4Hs/ddSwrAmD8sVgeVOPGC29IUEUDKLK8Xms/UPCRIg1bN6l8CQuKeKdfMADFpimEGooI3ShmJoUFyXemrjoGEuD5/1LfTs1dQyMIynanK8S8kr6/x0lVtqr3IuzzESBQMsNeoeIsJf3Gj+Fk5psD1gYHWQLKhSnEby/D/UvgvlC7+ZNEPEAV4He3w7scZHXe8f6nH6/MEakzcvU5VwNN8vGCKHMzr+8T3m22aV9RUr0r9KSoHNpCFFEER4bgpnWvFd7hy0MayXVxDvKyAvdnMU8gSuRtCtYrJF6hWwl1HNsUtNoXR5iFOLwOMRXaWwNMdLo4llj7OwfNwVUjA4v1BuUDq7gj5Ifw2ou4AEL4lpKe3+gCu5jpMjWI3sP8j+4SIaSavhiVJg3vtlStA+JYkYPpeDX3K469u1KZ3Bv6HwIxes4yXNvSoV5WLXUflxBCkRBXDW5RLYMgB36eSR0SGuf+L7x84atBVGw5q96w1LRIWrlPDLxWCgb6UzTELTxdLqWABV/wCWAYUIHLlTifLgsMCrYv8AvgS8+4tk4C0Occw4m1BbrpuBTatu4DwwJ5enXmJ7WgvMR8LxVsc+ISCUG6jymHdxd9rzf3Gf6CbULqBsOSYWVYcBljxuyYX7z4gKXEuBEu1Up0LwqBYoXriM2HrHer4lyF8H7lBY3rKOviPBzMK17YmFoHfMUUTmOLD4DP8ADK6dnRjr0CW7IbNH/Agm6TMJD8QLuvWnX3CGniLbCKXMq5AbvtBE/ufBvsTIMHlsquvYim5EkDcEdmhurb3NzVuKFmVeIvwaIp94umTUCRd6ccQLK7KUwHplBV1T+QmbIdrR+yL3P4YCiXNlmVlXSZFyRZ/HZ0nCIFQZr7hC9ssXmNN4pzBrKYi36gMyrYmgAhUD+onKkws9BLdnnWRZ5MtRM0+8q10B2g7VmniFeOhJhI4M5UVrbYls+oQUaieLrkiIn2yfzFINnqRnE/EAd+8U4VUrLfiOHzk8/nEeAiFWTiBMUYsRMcyoi0W8KiJ2DDnvHE+Yu2bKUcgTDwMBDjQcfR+pcmu1FyyV9wbLJdhsN6Liza8Rs+IqZhUZqOyEEwznxDO5QK8KhY0acFFEQeOkJ/pJTKFihwDrKaq5Sw7tBe+IFyrpNpD6aeJXUMVNnEZINkWg44al9sfrqk/Hojiy4dDtaMtVG1bIRH/z2NZv3DV8lZNcxM7mv2P3LEnix44BfuYcCJXue2HdQWhcbxLxYhkDUcPiFboF3J/U29nI/qIfw0DQ7oNuIVleKsL0uC5VujKw+gzqHwlNPQY1BceQm6NQ6EeC2/P6llVsnci0AjSTVl4wMfGUeAXmDAABlpGO4RrBu+K7F9xuIvRTHBDS6XcXhpwBwrM+BmSOgE2s1WsymEzrkv8A1KVr7IpywlO6gCyaLFjW7nWK9SqKuTkhhgIO6O8trqEpluFqotKbHxFBxy7jQ5UP4Ms6mXTTYLdy5jDRkODOuq5gIJYAdL0bPhnfte4wVNZ7qHoBVLJTSXc0Z6lBJUDA1WyY/EMx8hCJLLwXS+ZhbsKroTEaoCrZNb6Y7fiW7OUdPw13xG1MYgGt9MPS4B6mrhB5MHEvZSfYYT8RoFFkeE0HNEwRa1c6gqWv7mIYgxZwJdPeU1V6r/1xPaIW3m5ajay6TZ+HhrvG6oSSpLrG9w5BjjUhn5laSkOK4+ovlrl6+IA2r5i7zvpUOMwKhPgXqBZOZVT5ikbtqn5jWc3Z6SfquZ9mkZ6Q5DS8MC3Oh8wULmwV5uGc0Z/+pdSIyOYS/f8ARHdOzgyu3eJe0O/ZTO4qnwEV7mSSzlQfcsZbQM3HpUzlzd371EhaF9cRiRgtTNEbQNjYcHWFyl0csYAGu0UgIq8sRkN546TBWfNTz+oDoWef4VkIM8ZGNVGgXwxMEo9L6SxupW3JXGYrBxFEAu63DpOkEUvEuu88UruQ/wCD0TGAArE40xKAtEvzApwQVuFKjZWYP9uGS2C77Q6cTWhazZ3Qk1qMcOcmpiyEdu8m+ktZr2hAAV2Lj1kjAFYYbv1FiUCwrWxxFpwQKHOQmEDCgBmP781Y6JoIEnOY2YTG1dIn0ey+0sBwtr3zJ/i1zQcfMXcpUXaAWNImz2oh9i+6j3BKvqgu13ctJdmecUArlX5CoBBcvsBV3EHzTVAOzLlbAsOLY8o1joNTDtKvnSB9BVC/mRyxtArGKyF8ZvZEFO6yz7YD7JdpbyCusQkAGBO8UEIpRNLRi/EYRvFP3L/UZBuo/wBDlaHeSyFzZV8pNTNC58xQT1sjxdal0OMmlHSLphpYbJoy8QZEMrh0QNWvKPJF4jJ0Z0dZXI+BBMiwXDp7gzDi50ZXHPMORNhnRcxZ/CA7dmd8YhyK9NkMWtYvMIr8IzxONKXVhIeE4hJKEDhTkV0ha1XwH5YMHJUtxI3jrUKiHdlDyTpFzuRVrSUwl/1h3gi61Wk3ArHLSqnhqWOxbFpSF/UKANZ3R+5RFPVltitC7PD0iUKApCCdIi+gqE3G0m3m6LrHWMwwZB4rjvO0sTvcfXYyl2wLKnDU7NpNnuLDyTKnIvEFqUlBw5R4F7QyBjTCKQo9xWWmh5l4CKrqV0q2JQlkHQYCHQHOupZVJ2SUGRmSZ5jU6FbWNI42oBrcH/cd4ydSh2n5wzE0vDv0ZvzKEoo74p6iutZMwpeK1iI14MWGKTbYv5OpmXGjuE/Mqp1lPSK8aTjzUsBdkW90ggK3BeiL8mAeFa3VblKeC55v7URyxQUXlSCGSReDKEF9n0obpfaQeLbvhVeIAARCq2pucFvHmILAVonOpZiqKXNJzBoJRYinBDgeuZxFEBe6YT4LUm4zuvSoQkLxUfdXMWD2/qVgWOrULLn6qdd+ULI4CMrFvlFfJC/lHdSQR82X6mLGiPKroPuXPI619GLhWA20O7TnxPAx6xcG40jEKt67Q5+Wqx5Q6NnQuOHQ6f1RHEkQA49Roabv+uf43/U/xv6mQVih2OJclGZaz8RRFMSzxap/qPVT/XaA5J2/o/hgN/i+pTZLjUwnH3/C5xWy8EotxOozOpHRL5RZGdUj5S+S8J7SvoAjJ4i1LDkBbg4qjrBuQbTqXXwPxLYiGEXVHXUvCzt16eEb0bsk81AthlHiHmJyaqGIK6hfBJk4lQ71ABZ0yQ2+ztMaawX5lsyNnrG8StXb1mYuIpLgNcI1xiRVM2GXoxLEOUxqb+IJjoVjL65CmaqNE1FC+LB9xwJF0iT6XfhMrtmvUGlC9Dc/Fxhw2IevV1BiEhxwbqNWKCnxcZ0F7z5V+IGUSKBvou8wMwU7kpFmugSp9L86tgPK1jBWeV12QqnMuORnbVylsJkGNJ30/u5XHEtR1jtAluqj1qQPhpMMK3rBZgKt+/8A1oVyMt+w/cCWgVAPaUhlbQ7QBcTrZthX/JdVW7oh2i4B7vPihlN/FQ1b3WoYCFHELb2hFVVhyDKX9fzEIy0xVvs6RpsQ6g0x/wCIrNicj+PFiwqrbN/ZxBRjdIOluymKEBL08de8JRaus9VXfqG0V8V0MysqmCFjYb8Rp4YhbfQj9awJXl4mFgF2KesyGiVvB/uMGjnRiXynUhLa4NB/zL1nsLlEgUCTCpid92PLPWPwqXQp+o2iNkLY6r0hNtzYpSUdFvMVSb1XMVNUpCvQjcMbk6ELRLt0IY5dBu0B7GzxtYXnjMXzgz8Mu/vZjCPITEdmEuSl8HRek5UKnhOmiV2HUtYlX0VTacHr3xKEPqEpdYL+cTNphEPoHLufmPWd3bpcN5ZnVqRLyV55oM94lIZcnphcqgij84UEWnSWwevqZTVo0ZQso0If1ALVPEq0bwZF6ZQyquZLupd1veQ6VmDiibSjGYXnGcXaXwQb41AughZOkoq1+SPJbvbNCa1yseTATa1fx7tOzvRxQY6zgBQ8XFi5k0Gkr1b1hrV+RXzk7Fso50uWnDS1BB2lCDuWm8NOKbls8sPDDlKfOS2e9Ex2iNQ0TAIu71Q9IMNFyImyiE3JbMMqwU9orrT2xzOywCDP5qCLNd49QKOkqKrDpAOZ9aGZ+LnG/wAMrLsg3lIuAal9vuYRqNz+FAJW0vRytQ5Q3CteZs3iPxicfmLBMLHExCesyqcumtNzbBhGyaPS2G3wsvDTxo4l+OmLDOaCpvOoBRJm9P3KZ+snx/cvoiS2XxBBTiVYbWukAXLFVX5hvbNeH+CJbUQyCx84lo1lSMCK+Ki1dagFA1X5kickLkjzRtwK3EOMHhrKdw6YC8O9QL+oee0ueVwDu81CVin7OGJLIv5ZV7jVelnslqZnrdcwoxRgJGgv3NJZqfMRD7gSr4V4NNRBhBdNm11TMOnmdiOASxjkbxFdIxFO8qN6ouEBOFnmIAk6U5UH0T3HYHRiAYnNDrYppxawGKsLo18UZ+pjanVF+5hgf5KI/aOengYYlrY+8GDIUrWlKyc53MWLALerdRyxMsVPS2XdtZ0Ww1Ua74Wlnox/ouzY075grqoU3QVxLQ0L+5TNol4u7cyoEVzpuIcMbo/xCbz7C0/czFdxEQ5urEtXpIby4THWAsR5BYCdbiyAxcM0A9XiMSq4CbszPiIW1cyWxo4ClzeoVpqpZtagMpArvIDbKG8tRF9poOZcilabWqDWjrBhMWFtB3Q49bLq4Ou+Dn1ZweJtIC6fV/p3jgn2I+vrVH4QRZhf5e9EJ0Gao9CBZUL55VoUE58xKwgdAE6zFJWH1II/GVDKaNq8XGXokumb3lNBEOFONDKJ9H8gkEmoS1V6Y5leHYZDWuHffaBSL906k4sAKrZWGtZzctPwT1r9R1oWJ3ih+B6kQB+IgKCwXjafjQqP4rYrw/EzGEQV6MkL7FdYKgVbwFpvXzjsYueUuGAC/UH7Jn0/Yh4jdIBHnH+Py3Ak32ZaD1N51BhJLIKqvFEXz6V2KNImyoFM1erSF5sybIK5DKrrUGyGU4v+LZ1iKVgDqwUqzhZXcLocB3hgtgN0xw13qCW3ii4JpSNXYlMeZZxrwwYcOf1CBb/1qYWIfAP+4mwdd1mA8vPWcJhX1NNxvLXx2MqaNxm7Yzv24HEMKv3Eav8AQa/jwbPBNFMO/cK17xmGiy7Rcaui9mMjgeA05hTWZXiSlZ3FX8WVfmAlgKIlmKv5gzFTAxcZWFhrDVtMyhWqPx1LDgxjiGjtquTtVQhaFjj4WOLQ4JtuiFBMKlF1xviCSbuDzCgZNZxaeYWN8rCtdL6xcWImLO0HxeiN2g6kPPn+AeY+CvUeahaKjerteUTHi9gPzRms9K8PuYc0YWu8xm0We0ICx8yFYDCrkzxe+wlMBbKPJb6mHK7ILZPXoV5nFSvyHrUFU07hOBY2O0mZBtWD4itJ+l2/COAwXZD2PSLrpu7AGpcenSuW4ybnI4nANTJyunZNlb8aLOZRlUApOXiKt16Y90H7gmbRKgw1s/CKXrhz2ivU/wABNqF9ylJ1kWut1g8wwsEHR9a0wpMqjlXW5huIGJrf30wlvVGn75fi5hMFWcL9Qhd4IiIr8jrBtubUURSn+DCape+seZe5WFm4qB2lBH92WZXnEwyJA1a9YviHCS3aIwJgvm5iWNY7q082RopAvfDAiiS7cW6wE7OFV+5KTk3DkExrIJo9rDzc1aswIvQRrwh3+meYJciB2P6gUpTRLjZLqK8LsnCMbxqAGndzOzQowQz75Kxg2jivuMjdRqdG2h73FS1UrLMrl6rSEyDyG8bOkwSvG3YCEM3npgNEV+4q7DxJGmwXyHOHKl1Uwu+XlfoXJ1m2Gg0HB6wEMXajHGeYN/is2L0mSky1lNdtxXq6LvgtYfF1K8DtQY6OeYl0YBSDucfkiogg4C27XrtFAER05mKcKLq7smYIELbQipcVc0gqvN2Rao0GnDHeDNx1pAaIEAmsQXaL/NaG1dNfZf4iWZzUfj7sTVgVBbWvMYSm2bpWicKsEpT0qB0B13BByLxWZcRAZo3LJWNuXKtpebGmFMheF4vCb91XeNY/AD2AXFpzz1xEDKq+JAqhdXRXLUOGGEZtg2vrhl9mKK0IK9FYLjkfmz8mTwKVLaM0srKhmCV+0G9KtLwZSaHdnfZxcgu1XK52BCgetWRGFrKZjN+oYoVigUyheBpi4LgtBlMjYU5Dcojskxjbx7bMISdAnxaIAA5j1TnnWbHqM2lxuuIl1YPyiuL3GTkee0R4S/aYlxL0asgsKiC0saGvDJXvTdc9Ib1AWKqOHVW4cw+IP1lFiW8+amLwYzKgYC0a8AlFoWg2LU2SvEfofWMamaClzHP3usHVHEcniBA3UygtTgzPeCHa6wcWeL+o7jWBLK4uIQidUQSIZEqNZZRdkWZl+JNw7m1m9w7f1EnovGMlJ2qcTl3uZm+E2lXfs9q+N1KtC3s69oOiuayfylKKEd2+tUU885r3DN2abK3BxLVdsrBgFHA3eXxAF0ewyv3s0vEQW4Ti4PxCJmhc+f8AU7vPcGWMbyk3yd93FUi7Ra3E+4YAm6r9alEHC6HGZIm+ULuYzvsty8MjqSt8w7g6A/LKxo0ZLycwm5xEetxqKoDsMN/mECy5pxXXeo+bcb5o/cSwgqX2sCeKfEpjQwW57L2ahyb0hh7guSmNuCdwzEBJj0ddWDloWZj4RZKGGAxrMhlQF7wxgYyq5h5LooXy1PRCosaAI2PuZeaww/PiFyxAArQMJc2WaTvRHMAxdvrclJgD4vJ0OkrsW5xe/mOHUad9m47hpSsiAD8RoOtkjTvHO5sbgm0yfUp+oApWKt6OZQIclY9BcUpfxUSx7i0VstdgfuUXzVNd49ZvwZlDLhFN0hDvNg8cbvRiD/ewVFL67cXMLcFXc5lpSnWl0Zmoqazqg3c2jMz+xzXuVO8XrGYlKKG+aH4xKjH4K0bULxodfEIcMFi6vtgOX2Ae6R3uWY2Klcfi4LdmBarqX4mcIa3bvGIowtgt2uFUCuD4wyzPSGBwladXT77QNrIS0DR1yfaVzKVyH/JjnNI2dB1IkFyWSgu/Eo5AqhYeTOp3ZLW+4sd3l/MKQ9df2IVB5WBdnuCNzY181wp9wBD/AEzK6aFjvCKRHd1HgmhAq9MTZo07cxyDh0YkS0qzpxLgSwpdBzL4GFH0CEdJFHKdVzWxZ2zkhjcLSyMllzTxCEEGHci9pkGa1FTtUIsbm8KR42YG7b9MFG+8CNaXWXbngjiaGaUVyWhSXxAKgjRgZBXU6pifdZILTDS7QCswBpnUW9zFzdfJL6JgofTbWGLwbGYtpqcQ1gsN1ywFDfCq2gyaPbtVEG7Q0bdjAN74YmBjFMWtozitUIkrxBEOcYt+5e7AY6nzDCZpCXiAWXxdFiPgDXcPENNujjzZiI11wuY72pZK4Kia3ax9SBTNNY9v8d8uIS51LU8E0TOggO+pLd+lx6gOzRBT36xUlWAs+PMqbrHqrGt6lZFATycZKa9ywk0mXjHdrMZqnTCXWsIrVIopiko6JSHW5ifbUztFH0b1GtdwwcZX4jMVwGuUoyci2JXCamWWeaumMYdEL8ozBOGrb+4QEujjs8kdUoMNDr4hNzGBymFdx2GohOGmpzlN18QqtnVRFj4L/wCxLOir1DW7gzuKtuh7i2yrcuBk2A11i08llma0zMNat118wMs55XjCEsG3gf71iYxzRou0CyYJ9xps5km61HWpSoJknK0AkypK6HGAfEy4RJpWKzevUSxhiv4w0SvEASfm3Ac/uIntjZy9rtEds0Wirw/Fy4cmaJ8NxgQj3upx5RyFepFr1fSCkgSXnVNaeJhQASUXwunhd3EJpUW3flgkV18HvTM1TyQ26RVvo9B09bmclmcTausEtjMGzrmF1nmWVQN8ReYysVcGSyvaY5s9hurFzBBaRm5YVL9YrUjTMQMFmOJqu0oqUlOFA/UKFFHVb365gS8MtmrH9S/DAFROSkM9DQFvAB4MsYzOLyJcukB0BRzERAraModfErOSUI6VwjmKu5gvcLe66ot5pQpfiDkRvg1qynz4wzOwxKnxJ8yv111nIl3c0wXgsqjOXzHFeoRr0Q1RZw7TcWghoN9PMeMeViylN6orRWFzABsBZBo7u8zas9OiaIYBAckyC9opqhm+74jbWIUcFX1DzFdsuPJjUAjZDAOnr2lf4Vc1viWIODledEsdbVQFIRe6NZg+iYG16+I3IjggkRXWzmNaWPX+yWqLtRsd0qV01qdc4O8qZ6RJ4FII04JHrRSacL5hiUuZaKbvaVd0gL+41fqABfMHkxQnnziVwtxax0CVlFj/AHBS0lxY94pZVxc0zw9PZCb5uTuNK26QB16s4BUByWTVRH2k9jZw+LTtFMqtflzkrjOtw/cEWJR6NF3UOT4KMIUpaFBvkyjC1Ei/RB5yD7GHIgcsKrK0quEuLHo7MUWQ1IhiO+XB+1g5SIdd3rqg2KHfOV+kAtODyiA7FW88zopK0gSQJLMVZ6kFvaWEIdoBIKtkeilr1LLbh1NrSr7jqy5t51xlL7ryUoAMvMzEwFr27xhlVp8hwzDH4SPqMZG4RlzGuDYvFWzAeeisfwrxhxtyYYXSEVTmX9IUbZhn6R+S5f8AgU24zi5ljh3kH5jtr0/qCEnGdPUaCosHaZZoCoGfcTWJeGj98xh4X+DDEFQJlbt6hAPtqvidwxw8qlYq7Xf1DxuvZzYmgzQXRGx7W4CrK15sy3P0TEqKFOrvbiGQPUtVNmYMxxBAjms06neBlORQ4LcJHEuxWOm7gyZcBxyqU6WiDWnMwguz/cqJwYLt1zDSIonB+4jY8fBfSNUiKqCzhqXO1h5lfBiIrNgHX1dGJjq0YQTSnjZlUYSfSZrNRR2/XHWG+GDLj29Ifz8AZuXFGaYqJ9RLwONExJm+XNQlVjruCgIpZTxhDgra49HeYSylIOXFTK94CN0uoVBi06Aeeq6iu8iaG7LeYQbkopOpSpZwkEUK0Xr54lv0IFpGjVnmo8qmwEW6S9IriINqat64qZGQbVD9rAxQLdjfd6zHybW71xm5TvKf5f7gBKKbW/7lE70z/UBhXBHad/8AX/FJ3ZgRbLRfTKNjEQUDfEA0+mWvVNe2/DEICaUr9ulUbuKkawydqlRN0nizCApGD6josoljzqGyYKU1jh0iIGFZSpTBvIvko8AuoBOnENQ2Sd09XYuZ+wkR6O0y9zuUp/3Jbm68MxZv8/6ltAKsQM/5+IAAxt6w/wAocChXmZ/ERv7c4wELzwVKt+1Esu+VEzgmFeJSZk4AdEEaBRsJFTfwtbi78jKEiwd9njDknNHDmSlRQnyqyIeY+WNyj/p/cVBQ4uT+ULRBM2bvr/yNki5TKXVV72a5idDXALVYdX1vELrHK200c9KcRzAV1qgFOHxHr8Jlbha1jncZZ4ilHCHHkzFbbj7kpuPTYrdJy4gaTMgrZnmTlmEuBKN85MyYBVJZ+2se8Cz+o3BFNcChb8Q/Sf74cv8Al7z/AB/7ireT/PM/zf7n+P8A3C0MFJHqbZwmp/p8z/F/uZb/AMPmf7D9zSDx7/mZj6kvqgfLt6kI1Kszl2G1zsdwU/8ApAGwj4ScCt83H3TIxqlWIiFbhYuI4kZp/wAQr2VzOraJxlG6NXaJ9Asd2A+sMvqShZ64iQKp9ZXHSPO1MvM/sPAKP/lqXR8qvOuIMo+qShjPiaeDrepUR3zi+PkQEM4/pRGRO3ZwxNITT0r4tEA9WUbcQC0Ne8Vcs60oXsqUOb9T+qV/U5bfmAugq1m3pCJg1LVF5iO8eUAwwa5p9xrf3D+lRRTr/G5lyeT8SUMdCD7YRk1l5gBOZVA+qlIDs/7xNP8AP5n+k/csmMBVPuG+TksY1qoulNa/vg7aubzNzBuVSBtekypmEqNdOlQJRGAfxxBZMZv4U+CjktNjdThZdub8wF0XFqu86PudUIp1rg+sxDrtRUt2e4QUXdGAdRe0oQrpklSvERU2lRsVJlpBJKO//CASjCEficgrbimhR/rmUN4lhgJtYClH6lWs9+rWZ0DKDB4EKoDR0Fq8ebjmq9Suarb/AL0gWq3l2Op2ghJS0ZOtSlLwF+s/1rcLqFgKiwHm4XNZq65qb1i2ku74PviPozFRp3/jMeEX+GgbT47SNUIF97/3LrUZw1VHBUGw2vVG/wCvcorVr1eL8X/swCA9Tb63BvWenHq4a1JdWN8h+yYzmq6kTJvEoXbTWuIzMb6Eg08T0fMhN+X+KMAOeAPl8zlKz/6KiTfEuF0GrYSCytYWlc2KVm6gGsmTrz07+o0CoKy818Qb4RxQ7b/rPxAKl5Gq+f6fiV4HVmphz2/PSFtF4vGZZ1zdV3/fqLkujm+1+vcvF/RlidYg4e3edZK4XFwCKygrWcHOIAYBLLN8ntM1vtMCrQLdn+r5mDfjBeeCBcx04sCIw6VXNm6q1/UWJaHorBuPgdMJLtnxdBV+5nYo1RytCz6nxut5LrLLco0yrVKvESfKLxUu/eqWMRD0ZezVlnSu+o3Y9VsB2VcfMt7Snt8THeV3Sjt8TiqldpT2+J3H4JXr9f8AZXZCmOIGPra4Kr/yoCH10HKDqmqaAbOgGUZ6sS87iHLgLXkQpXPuDnKDXZpleyRqp/lcv8B8ZPuHVr8wAoMXeYlq88b/ALm9v5/uUuwCKaGqDFRK4VO7HgZf+z/ct6/n+48S9r/cwuuYbtLdnemNemXEWV6F+EylNMyDmkNAcMUq3uOF8xbPqPJNYpPbnUpZMtTFYdY/kBFNgD+IZvZW+38XKtq8kHOcQy0b3Nv6z+IA856VNv8A9WxsD0ttlNPDLivNXRl/76jRdquKzfx6+SWPN0W9vMSYyvYv/wA99Ji+Nof+8a6wQo2V1xzX+8y/ELUsGH8iVGRBtjB1TrXpiMy5I6H/AHhimTs/Pw+vkiTa1Q1OcXj+Aku2sV/ecAQEVc9Yen8qAU1L1Q8wB4X58QQmjRQuUaYKSjlMNxQHNUXqKDS5q9MwQX1WSyruztBFCgnVI4FhE6zJA2wuqqEE4sE+Fwj5APJjddc/DB6l27K+gYsVshWOBZbsPjVJfMFcaGNYbbbM+zLGgbdANTi3rRqHD4emh2QOPMuXDHi9iMTTvtLkN4RgP7aC4YyBs9TDm6qnH9zFuCZmNlyvaXVwG/xO7L3ibtxXJyzJM09CzkAuzm6auB5GlQZUNoZwYi6wFWoy19URqphmXps49lvhtbgtRLM17jCXbDVDGy5a0qFf0luOn4jgqXVKc9ooi0pSBptqYvXylOcYuKDW3pKfWowFsMsL73FzgaXMpnnKw4d2UXwdq+HimilguvhF2e0EstVFNUC2BQrRcHz629yiisJWecRG/EEil9PHJnDc6EEiHoFnhj4WGFukqTQ5NBiIGY9uiiEoADWzO6aKemIatChtpMauJrELUK7Xw8y23h29LIXpQ+q65ghUHrRwU1yq4HxA1FaWK9agpLvSWEI58AYRKlpBz7QPPWcmqoURW2BcYsYDCLDRvj6wsCDSxbAwewppYwBRZi1g/deZQckGf0LGfJmFoWa9QKJMVKbaf4mpxVyO5OY9nE8QjPGRKZYnm7yJP+eECsDqYOncTuDe3BG7Le6WzWUnfHf+HBKHK2Zo0o6rmLQKNueJTeUeeZlVMavgXrz6i0oyLQjea4/mu0+/45/jn+Ti+WoFysVN0tOOdXCvagLzJ9B6S+0VZF71jGpWLM4YdW/6ihZQHAxaB5eOYI0P5IJSi9faH7nRYOCnG9fMSLRVWd4iVYg6vmVO2aLcvrcRxzeu8Atq60gIsLOvuv4S/wAfpTBJBNF32gOXr/j5YhsZLgXMR5ihI1nBLNWOEoctwQQ8YbV+QBQQhbCfLY/JjBJlReyVtkcm6hXmsSrDqWydSrv1Fy7ogoXeFw014YknFVRGt4mV240HSXt9z5W4Pjr66k2dt9oImH6qCOLz06xQrvqyrnXisxAW4IT3l/34lSQnay4BqyDglArUtxAmygXlOh6x88aGjEoIQbtviVNvAfB0BQic5OaDwEJxK2kOg35A7RpFR15et8HHoGgOgXd9LMEki5Jbrz9EyWUDIsfx9ECyagun+fomMoT03+Fn8LtAIZvj9S0CKl08yYXCc0nITUKKniA3vH1KWqIjszcruA0tCyZq+syjvOG8Dp3R9wnWLF5b7PxE9lswt6bZdC+B0CzF19xXVQJEJlF6QpAbZTTb4OOsE21qK8LqZUspOyn6gDFlCkL5DtLTjgXp38/qJ2/hZJ3g0b3KMKKRo0pc+WmuIynu72hrtQ66otn4yhJtuvEJVtwjko9eSPC+JZ011xDJevMoDkzee18XFoXzWphWGMzNAdXnhjsRCVAGL0G44tpCUob8zMXFl6XX+WAuOL8oRnEZxHydGnUQbKkdIzUVERIa+1a0tGLKuCK+9Z2Fi71hdQ5m0lTTKKwOx0cTJOSNygw3fP5dWVVmB3RDfWEYpoJHDBS2YLSy6laWMlTKVlMt1siiIo+o1ZVrTlC7VcrNBk4CVpuQ55kpUu7UhgARiBW1vGIDhFKIsCKD7hmG/wAMoZeC34hafmAqa9pW38GSPJq6gFy95VqFuoE0q0dOJgRRaaJWR747yiZjBtQI8hyJFuZ2bV32td5Xf4OLQ65B9kVybqVHcF9U4wUHDaPDQuIpabwWu6vw0py36Mu5dgFo0UUMGoDMCmw6rKTvaXiV9Idw4eVqHWsm5hpz1XnIpYABullbzNEwgaya/CP2MuMA1bFql21dS1E0KoJXW6yZ7kNMK7sVp8kxKVlmOyOkXDFkZ5PDH5m/OFRw8osl62IVanniGS5g1RXVLz+vcqFUUhpz31KVlrfHRpigU4b4H+s+YksapduIsZ3Bkc/mpQREAChBbfNX/DmL12yXcbbcsFFvziZ5QONZy0VWubyQtOg9Fl00E4dL5hUViMWKEtwYj5hqFA2y8YlPWJRSbesiGfqXAH0yHNQNZtl7EK5a20fUPzgNds4PiXzglFKVdA95SLNlP8XPkKLjx7ltkqOsb49QB8W6cs36ichqq1fxn6isGQJ4uWP9sRklwD9r+5Q6NgflETPHdAUFWKvBO67v1K4VYLYVdyrtHns1XXqZoXRm4ovWdgmltxi51UbzK0nLUVXXww77JnR6qn1HKAqC7/39kwkZCVe1uvccmtjdZ9XU/g8Go1dNMDgzO3j8Uql2xKW3hldkG8k4N/BYzAm73ZR6kQ+lLrsIIz2PclgCHEfIStEO0FVa7oMT0xfQDRCkvjpBDj/VQDGeyjcaaNsOEysrHS5Vbee9G3nsVzKxVEdgfkwQcaEF6EXjnKm2q88SkHlE0Oej1cabr4pRfINSnIWylr14rPkiuc3M6qT8DqTCK7xCPSR1hQUAVTObdRBbD2qS6aEotFZdy9XGTDZGsWbZVhgFbmCK1xi/klaGOuH6RZAC5bj7lzeNFheAJ9xobXvYf3GGFVmlSsC7xvKP3FqJVqGrHj3LEhRaujPMva2oUuIFctWhmIo1lXwssFLrb+4P2Bklb7O8tq5j2XeFnCzL7W1drL9ieUPDYAHzHZkscovhvFQ9hTU9FrXxLT4UDN22p0JrHuwfeuYdFOGc5OPmO1zg7ktYCAItbrr/AFinRXa7V3cLzOa7WKm/J9wNRgIW8liv0TN4ZGmeBOA55i26kgaWNquPLMI7HZKspVhYRboekFCaWGuXSCjkymMruw6zIQtpxUx+egt0uBdHEQSrQd6eTZrkluau0ot8xbYDK62P3GmmzMOPFGauy4+RQ9I03ru6XahotVmb7UrXtqvOz3lOQsq04qPoxDgMhXq1WagXDB3jQkJjElz2CqmjvBXx1gYFWMkV0vDBp/Isqt3wCwxTZGisZ1sQIO9AwUS3ZSio4rWxxaeWCU9hABRQ48Y6RfSAjOjPG24hsteDLwvjE/aI8UY9CcRV4JVZKTXeUvQeSIWLsYtYTIwZOMkY6G8wg0rTJqLBylL2wgZLTVdshvchCt0HI2WxT6lDTm3qHfsA95zomr65Giq7ZzDtrMiyuz8FAfvoZBvAyaCEAFSvlbbf8BHLNo7LuPVXD90EYe5BeBuCFwUK1Jn6Ip4mxdq7xml2a7TJlugqUxV31wZ8wKDBZQTGGpWYMVwYFaq04uDUZoavUF9XmIC+usp8abmewsGvbpAINlWaQDnKIDqmYhqFAjaULO4Szr7cvmCgZMsxDi2960TGRCoXW8MS7uwFiV+7GhUKb7CVxBY1TJhstJvc6oq6SYNp8d2v4uODe8f1Hzb2JkGFN5gPirKuMHrwa3Cakqn12IM3UbjtbpLP7gCxqba9pT1grIaG9eQmHG4WfrGKNfAS1+f3BFcRh05CLRhm7SW1ptxaBM7LBAWv4lFlw0exMs+ILOWPREk6gpXZ7ZiudbXZUdOXL1FrrMxzri9okx3lYMpIqZy0vxHiswhS1O7X1dYCzK22XBXm4Q7qFft6lJJwqUFYdiCSvjGmOvrrSeVSJ4DppCrdneYxExEh/kpRZq82evtMasFyz3EXba+Vzp3/AIsHpGbZxJscZTnxLu5YzlfUpCoG2AOZXk15hqpmDWsLqVHOty4AFBIzNAf56yje5zL9xGDriJd2f3CMc2CfRF3wx5YzcOGQNe24LprdlRaXI7F8sSYRG2WVKbrXKHlxGrTGrKxg6JTdkdD5BwR/TYbgQK5ySzUZ76l38U9ylGcJlTk4RNaBIeNQkGILelKm9jikcfNsduClnF1Q9Ipy6CJZueQOVpbFUwQEYwLFBvQghzKRFqmH/e5VscVx1ng/ExXPy/qOBvD0pfxL7Pwy6lRsAWXdF5OeZ5pHwirzATTJBXPqdPt9764l5bCoT2EWsa514YQ8BMW+v/skrSfWLaIZ3KppT/E9rEDCS68inylQLj07b+WaUSVBCCLdAUmm1vL35lSJUDYpN33mNWsWqLb6pVn7ZQuIs/fND7P4MiNHeIt3ZcIX8hw0FXecOuwgFqPB1RKtxssBbY7x2ghC5sbM6sQcAWl8ZETRlS5ul+176Mw2DeDbiYlAWh+n3S+mKwD6IDAZXvHv7O+SUBtavVec6ap1emLTYb6Ar9QbI7NnSXm+YHc8mHaaG0rIpUtSn4MsOIAMOQV4nZntFgXZIhwMw+mHlU7zQV4qBIVNU41GHZzlzvcGHjI4Jvhi/TNSSjB4FY8nbgCEec3jpL5pcXRmN6WIOVP3FCw1dYLhQspdFZvx1jdrErdiQm2Hqg5qUrSPwxA0M5w15ll0C8Nf7x8wLtWJZXeLTytVOIVVjGMxabuq3cRqaFqGu3mKkso0pB+4U3S03ZR6YPxHAS2FT5/UH/KH5gWcoUKCgtYemzczWiCokg5FzeMVA+Eu3ffSJravhTlXJ1mHQ1GGlrZHV5OXgI6IXjGpGFD4C4BbUVLvCSNxkgaTrBygGmrM6spQOIbElns4YYf/ABmEUnpQABqqff8AFFBlYBD+YRQMAXZ/GHFYWEgZ0QpM4+4UXQcYW8TDQJ3Gvm4gqjVVbBohYu3rC47xuoHF89eI6kTkYK58s2UGEB2oZlKKqoez/wAlogHAzO/cK2ea78krMeiY26hHOdTVY1XXuWlML2Xr6jTdfMHf9y4wIrQG8TlLW5opgNkBxmH2H5lV3UFFpTKHHTVYEP5mgIG3FdGUITcyCS+cwVWOTpi5SmVfLuC2ceLxE9vLlHNi91txXZz8y1qpzzcSlbPnpX8UeanI3Hc7Rm85gd4pLpBArQYrhP71KRJQOsq62hGyMqhrBdeIMaVh8qbKlhRBvnwQd70CgiKgV8S6BdPMBbU+xl2WZO2ZV0/UUK2XV17qNAUUPMmD0iFB0WhKoFN5PM2e5RsfEBUataJmCdUtG9tsKpyV2F+CV6Pmf5Cf+xLdPuU6/BK9fimm0pmwui6XECsWBdV1iVUh5rACj10X9wgLdIXzJo5pzVZxUCiDTe05iZT15IQU14cUy6z2LJghsAqx7GDAatOrHmLZFxA/BBjuyLArojPdcwoiPsf6zBFtjW9Y1jlXiatCCoWm67JahAt0gjX4QywfAYYUFqvGZq7wHWImKRupemWnKJECQqmrVHkoY468wewKXrquqdY2PG0NDwswaJomeZXhEW6FF5wsYjzQiUwg1DtiZW9lo1GCr5Q7Xuqj+Y61tQn6aqzmCqVgBbw4f0QjbJsaLe3SANi7gixw2feYGnXUmS2fwQWSpSgkOs3sQwja2bistG8FGUENwgqtQaHir9SjfebdqhUthY2eD/f4YZAmL3EcJ81xcKeK84x1/wB1hTyGLzLqrxi34YfmUvY756R1sjrFisKoV+YA2jUy2ny2qGC5TKFdcLIDNUBq4sLZcX21WhVW7QkYYTk061ODT1B8k8nY2NPBCe+VRMBfVhxw71nEiD1I2svEoo3C4d1PNn4jEGCIus5eM1EN+0OehLiMJtY7XDbr8MKYAwBpOXnUPGaAQIVXZUHFSNIhYL0XAU7FhtFAyo/X9v4My956F9xjFLJVg3ztAhJGzrnw8Ti6NORhAmTGYXLhMQja1rllm0NJsvT/ALGa0xFesTg3ACzuBTCY7kJy1lkhE6OJaK2xh6LB/wBFL0HEjnwUR8urE0IWEIOZTQK6FRQHVbWqMhy4YO6gd3goRxBMFv0TSN30IbJfWJ2DHgSllVddvPwxbYNFr/cHLKhgvShiIhqxRi9XcfdtAJ6PeYr+5m4/SN1SSm6wt1VkTFt7jy9pQsaRu0nOMht/jyPmV3nRj5l67R2FKwtQC14slZHr3mByWcXM+ZDub7Ic5D5wHpQVr2C5h4Xt+ZezCwrXuDInIUa6+JaRCxkx4mG/oxoUfX+6KIKAVvRzF0YOjEBdfeVxt8ZZpTqGJ/0YxOhef7ZwZisG1naZ3BUMQcLz4SbOdqXdtshOi+ZcCoo5iaY7xe0mMBKOA2+ZeAMY4lRvGOpC/MramMG9p30LhQjb0PmOBW6mOolwWJSq0Iy6sUCLy2pwHXuh4dIP6gqGkRhjxEfiYQapN9yVZOKEev6nQtvtqJORXD1i1vEBol9LJlSs3NWq7MQDlQ7zCKgG8jzJUrO1836TVyqOXwQdJ8l/CIOtaPKC/wBQJOeJvwwqFLqngVZaj+hvompkFV9mEqIg71FGEglUVYq6Qe0oliAT2aZ4RJVrCvVh9EuvIMJ3ADs+pgU0eFM7neVwAoOB1IHZSnjJrpuHkDMveQCEw7g5J3GWFY/5e2+o6Qpa1TTvPRfiW+CZTwVX5nNnPBVpi7/sRaJdhfhqQhVJ1zCw8ORcMAQryBjZ1lGi+Lx4jeWOcMdfwfJHGJIbQqX4wxHg0FFFOsS7uXC9Uvq1HDZQTF/8g7QGkxEa6eQv8xGQ91RYujmsEajktQIMZN0koyp+vzMZy9DcEwKGr7HjpKgCFRsGsdu2pVxqQZ6jzb4YvZFzay8jIOWs9pjBmExtL0UUq+dRpxFHLFFtN3/gYbhJKSmErBXHJGRkunsouMzF8CNrZck8DG6AFleDqVqjcBDXBjrWyYeXnjda7yrEarXYS1IZ0BsB165Y7Y0ysPwgAOMtTDM0gq/QO9x1FtAp8Yg1KvaTRvlh8BeECwV0/MHD7s0Kt1pxyTKUT4FMU0TNdYUCHEdjt3j2AdS87f8ANJVcVCmpT0gVZ8vFMuioD2DmMG6TYkpJAC4Xz8Rz3gCJvdr/AMJS0IXOpJc/tyFynjUqB4tdwaErojbX2xS0GcvmW4gsDp9R2lO6x1xAKagsZ3pT7jEYYX+FD3cdz5yfLuuv4mdRRwVbc11iIVwoqIazWI1pU3La7GsahQ5OYo64vUJCBSxxbliCUA7IUBNP91MUt4NwLQyOMIlXEq2jywbrbiJIiN6pH3iMKfVBelEw8DM85aIaLF46ckHMpWFDl/rqcSKR8qtiCvFvSXUNmNw0lGK1kfMHHQSI6XjK5tcKnxD5haBPszHJS12YeZ3aKj7XgQJAIbV0TzDqACm96X05rZE1kNRdRn8aK1TZu/zYxLqkrByzrO9SFPRh+SQwMa1wOBywDxexgRanYBDRbOGGQBBpY8+IdVQ/ZCtnN7rMzk/G3wesfWMXKriG3trvGGtGYi6OsrxOogyeY+t3rX9QYAajJHmnpRBYsu0W+sev6l65BAe64xrPWkelaFkxoLoNNxM410lShB5lV7tUIFcQor3iWYnB6gq1KaVmG3RAHEHzGCpCrJltTRrVxuukyA2KFvtXUgmhbpWC6Chu3LC4LIewG/cSUGtYrRCOUAqOiVM0RKb75GG7Rm2rOelY1CFUAat0tmJSJLs4Lv8AUWfzAJpdg90GnuP0E69skvS7IDIqHHcgksKYa6Kd3jV7JZABgNHXCwayl5Kac8HEu2uBerp7Eq44hB8O893vn41vBuI4pSN21uo7xICgVBbXT1M9Bh5C4Z+oL/f9R8cGo+Dl9sKAXCzqFbDwUQS4+HHMWWlD6454hKOK2AuOWJ7fVqcfceHuUUZCK33mNiFifDapWzk2g2xs5S+M158C1qapd5N1jm4jkW/OtKbip6cuKPM0bFFoBs7xWrguyoOe7LmSAu0s5zIAjZPV/iYrBLZYahC2CyAS7LlSHHRY5HYxAYdTRho9Iqpy62zkXgaJUv8Auly3Jd0rxDDMHBZGNXAS4EDvIQVXGkdSDiBtEs781vChmpef4SSwEFtuiDfBB55Qk6UFDNKNptf0yPFDBYr2fkzzBU/RX6nBjgr5efqC5AsUGqn9XBoaCIhbIC1gU8wUJgk0q9jW+1yo65LX42cN0hWzKe0ETL/6GUF2FYF50mHefl1UHH7phJ6Ta/BAqgpwHwt7iloPmFudo3AgjJyGWFuCwNOZ2gIQQt1mvGcSrD+KcXXmAKngOD27QzWHDxCHjRg7Nwft5ViJ1qSygalSp6/QXNObi3jDorEFZK+yISLkbHADTPaKLGb8A7QKacdYCwDJ1+z0uU0ylhVeNiKKz5gVWYOK4aMp4myEtckfRKsmyoRKbALgX1L7a7w8kDLUcEs5clMRVLlA10s4yfMGPAGwJkxriGWOepnVv9S4xaBGA0BjnkoMxzm1W+4FqboPpAVT5c7hfMNU42sFl1CS21V/NQsWRpiNKM3yrx5ztlEzKCFh4h314g2V1jEdVP1DsopOrd7Nd2+0KRsTVbsl9gmPYFUcvHFitAWmADeHFbzMFE0/agt8od46xaaVVLwd3EdiIORZFLpesdaFqCXhc/XCyI6q/lJfiwPTrBS9YGKnsEPQAwrmXoDyYF/T7jNqNg0Bb7KgXRQL8MCe9YBZKbGcSwNHOUgkzrUopQHOo1S1vIDZusCsXvEtEl2y6lruFiEwi2Ix5hNbsqTgOBcmLc8bjh0kCXS5HfRno2j8WDw7HTEKAraFw9PtkpPfAWFKKlrroB6YghcUhVQhNiFQ1lAaWYWmNKmCnrpCDXLWXJvMAQoJRAt75gUEJmV9Q7zeA7EIpyFdtRIZHOP7m4BO0ht5BDBM1X6XLsp0EysZ7gzA+OFwL2hPpj/UU+m17MN2V0lJv9EIgj0JpseYXWU5+iBO/IES/wDJY5f8dJaj4LBDrKj0tesPDX3hohY2wul5M9pebmC1eZjLjxak74zMXkKViX3cNpUF7bT9S1rINYH58RCxmYisc1UG1+Yiy3fUivzlzpgqQ6EEvI72wz/O1LsYWgmvIsDtBdAT42reV4A66lDgKnB0XxGymAMZK57QqJY1saOK5f8AYJrv61ugxUBq2IDC3Ja6wiUJEr6Vr1L5c1eISiNAFQ9FVfNS4ch1GyKDXqKmCAjI9joLRw6w/wCmiiobtOO0vqK5Y7fMNHLCwxTJ+MIYanrhbI+HFR3mohk+IIFOyA+osrGVZFPiGLbRr4U7xqW8Rcy+jDFFGpQ94vwr3vg4kLAdr/kGWS6qymtjxCqiWK+R/uhCvAy1hL8IiCv/ABIgWnmXyAIwCmO8NESqNVqQhxim6P53AymC6XA3q0fR7DW475F91qB/PWFu1VWy/qOSVCbR0gap6QMHlOjsKkfBEnuVd+aE9wG3faDduIIRmCp+DESr2rjPevqXnVqaK11jdadWwII00POYT/thhWYgjv2CjiU2tZggeT0mY6uugBzS8A+pQdxJQ7gHn6wpizHsTidpb60jjpemYLnF1hpTJy9MxhYJkmK8MBSW2VPtcwSpAYH8oB77Y7/lKcCXJKbooL9whY10QZRv4QLn3o+iJg2JrTgLOkqH6jS81AwlD1HaGulnS+dwNAYVV7C/83NSweZqZXmt9SZHfnyb7nKM54ajsG3F7jJW1ALlEqcmxiFyP8SHHpnUp73HBuopSlBdV2dVnWUqAJNwD7SrSAqJpiCkN4MN5VvFV6dckfeOAFXhcy41LPKJnzUXUOcW6BzQfHtxkjcNA+Y+5aNv4FmgDZ+BYwjVYPvLMCBvAsWeTZTGgPSG8c3+pbz5MjYsV0RQCisJ91EhNPCLUsIrt0RRv0Y5OZfklxPNqUtS+EECK5wx5IAWQc9CFru+uWONWAA+ART/AA61a6y1MM+MqMW4V4A8zIp8MSAFpAMCK5MyodZBtgvfQIt5AZNlep3LNPWGjCNhk7sKd3uVS4FoWuC3jjvF3G2mA8n3ULijigq9C3Mwlpjzs/uDRy8/8JUiASK3damTHULR2giGtDMf6nDoFJTtaHuCNVfp2fcX+9NpDrALJcLFertEF3QOKs1+ZWq5imm7jdEOfPWZRU2vV9S7gzoKLGZTT0wiOuSx1YSCMTsN9x7gdudTb4YjQzpqXkuA9vwW/UU6f0h2MoDrY9lLil3qPdbcrTt7TMR8yFZQg0NvDFMB2Ze1O5Aqg7+HqIC2ssr/AImN8IZlVQXWbAHALuCHmTh+ZXkryl6heU7uU0T3JcAXZf5hCj4TpnDwy2S8kbjuy/jrv5UbfxKkLQ3Y10Lw1zKl6QdSEI4AJXoIF6TEktzNmqJasIqdghTY27pcRBNkoUq3LCeROCOsKC/PJBA0yYeh/wAeIZHwIHA1wOF09QheHGIOHYLsp3lCIgaaqp4UXHP8bDH5ZxFlpVTPiWnk6CENwE4y6fUPr1ygtrHSItY4VkCdxr8ysly9i9ZyGLutksC2iC8BeXzBXVB7Ktz/ADrTuob+UJWLr7hGttAXqKQf7dBgwWC7uX8z+1f/AATO382BKQSAcxgtWYJqA30yyZkwyXoAZ+pkKY/2UMpe2KR9piM/xX4c6vi4MNDA4TXuoyn8KW6ADkbYrq0FZ7QiXCNRuj1YxEeYW6A/XwiZ9JdVg9aJYJtTN9DQDtNQ+O2deoya1sV00lDORstXNXwfhhutUa3oOmpcgYHHTDqtoFBaqKlP+468pKIUB4xBxfjDN9yVRcqwL8gcxopi7lbLUsP0wADVoHf6REWxFj8olUDgX+YEWF2hNAPYwgAq84b8JaGkQ8JwF5viKofWOgEE8XKyRKFKFKt6Ru9IQMcXW/UznOro2FiAehuq5sNjfA4lMLuqBKqw1XFRHkcJxKVvheHegB3ShbvsuC+JAdxzkHi5XNHLZHJXWZehbWHNaOsKCwkCv9xFiqwA43rMOgC1oQkaipXgpcyt+XMHdbmYtkM4DlV9sI2DYQfctvm8NFujP8zTbX+J0QbfM32D7mI7RdeMPGFlyj9GWPXpJ1TFJ7VZHKRdbQEvhwOkyo5bqVQluBS43gOUt3f/ANx6y+8os5fRGGC8ZAT+CCWOd2fpmdfNIXvDKZxGecATIg0M6XdZK6kpGFKtUYX9y9L/AHtUq9o40ry5lJ9kyGX6mtNAgaIYN+TcADyUQW+iylXQdbqjrKGFNRbreK1EeGErJorxrV13hk1zW/onfccDyIrJ5ioClS6JQcvaIW7TG7HiYhrAKtKiTfoCIIao4sp+4gqjfFETPBgkaQoC1JwYnIXwLOBe0AW4YwccviYabDW2Fwg670xFbHEGttrEFekDnZO12Fse8dI0AF9Kh4l14/beIzSgmlVgL+IA9sXGHUse2wd3W9fcrNx2Fa8xEgZ41X5sPuHJO+JmCg9bnJ0iw24fHSJjTbs+YpROyg9RbONATDZ4iDHcWNmo9IfczAr6tqBTLb8RK2jNOoQnVh5cZedNMq2q/wCWI1VbQpic2MQQP2FhA1RVSm+ICj62O0HpGwF6xGSvZ/UF/hYwRpuD5hm++DE1I/CwH1EsyE6Pxha8YMMi7+41rCmTFZ/qFJzKMIB6uGMFaN2Iq/iElBS4EhTvcVwqlQ9MdYmZer42Avh+oXqA+5CcpxrbEFTWDRLZNLLLRWQzyJFs0W98QHmGNz+EB2haDHlAVco3rK7rW4rZaveLZoO+9Rn9NV+Q+5U0NcPzDvNTk0F6ysOx7hRMNCA8bhmTQ13wFfzLkDp/JqZnAHbHZlx0NWJXtDgQKgHDCSS4DvxbqYodcKD4h7WZrVCKOJQLOVO4UsR9+CX8vcZotrE+yxN4qtA6neImLElKvPclGqauCOgUOWMWwgiVDVhb27Q/e2HPnMvbKcUftEH5kJhNPv6QOjopVOYz4QGODA4LwsiLywmP1D/h10pS3lQJN55fVCJfQppMO3TgcvVe6LknaXd7PKUJJrAwohdd0uWA+PXBWfcIAwMY60WpXib9ELLibCPHfk+ghqnG2Y4E/Vmv8Rvs6kc8mKZvgCXR2Y7VnpBW9vVn4ZW8chNSrBlVjRKKrex7GI02k31pUmHtHTPJvZa8wVhFbBqaR8kpwAXTnhRlqUVTe+YzWosEb2Ez8BKr40DmmoPPJauoZMSt6cLSuzeu8HULfa21i39MtzWazZTyvH6l8cCt96QHlnK1F0yBknxQK9ABG4qGRL1wB0dpvH/9k4gQWNDhKaitHqvL497H6lyK6I/pNV/c/Sf48z4SNpVsi+oi6my34YC33DEB1D2hCBGOhF/I9w4zR0DWLxSlZqoK4MNovN3P8Fq8yp/lPx1KAHrL4RKtqNzqYY+KktDAM0w499G+rL8oo6VFNDUpEvJPeVPuGXblA+dQg6RHF/8AuigRL292jfwPBvfmDFW5dqlJqYBIV5o01sKwwEj30c92YO8DRkS/xEwbi9+CFge9hbq9oM1mCzW3i5dGFQTcz/FFr+pdc9d0yrN19e7f9wo9TEi/vM2h6LG/iYAHv/ZGDxpuVOF/u7RXP3v6hj1YxcZs/wAXaAQYDVBoyrxK1P1t38fewdr7CQ2NJflvgGbemOY6wKE4JbULeYcMRpWH3vTHsI7mTAOPYg+XLcizf+6MFllS01zEwy9IQ5RMw1OGPVALtFdpoBlzsIIux8QXgMI26PyWjqjBGtU2ejCBNlCaqAOnzK8to/Vyho+oBzDEzl4q4JwwLMt+5ibzNYMu7qPmik4jq9HF+yJUPE/nCWm6axDnONBi+0KAoAN26fUOXVurRFgOb4uped7j7YfMAt749kWey+0whiYFwiHSXbuFcbZnNuIHG9ltaZJ0CyKAHXFhr3sh8dlN9jpKxpVzXVmocm0GodoF+4P3UGm3R3+5UCgLAvsx1FY1X9kuAA1Rn5lGQHWkGAt6gn3DGWIes4D7iGhNoO5iNiz5+xHuoJHAzG5cn+alSkv7Go58Q2doeZc9oEXqZ+FvaL+1P3LashnK7qeuGJUzd9XppG8rGleJXtOWpmHaATTN8HeGMS2OmXfqVwzvKpecYo6Tfvah8oTHm939oaA1PVh/1DHEWiWfs1UorvLdCZ7SwxAHJ+UgBbDMV0sxKbWaBDbV/i4Y2gSlh3wVWMZmXhGhqFVjWv8Ae43PmhU81KEzqeG7LGJ9HpO+PtM4MDr1Ab8LBBb8umsx/wDhlldodhqZURZvAKKAuIZUDty2eT3QuMs3fdzzCxsW0RMkCCPUqSqBXb0l5gj6B1l8+74i+HjcaGVNGyqGIkkoFKKurON1iViniNsFzy9JfyN+dTUouQpdOh3gtj62+JSTEcnXxCyHXj4Y/YvnE776gAPdSP6zwX8An/lIL/Xn9A5lgTZX9TrnmCNK4hTsOWNhpypjZS9kMKrkZmt8ViP7mO5PK/xUCUuuC8S+R5vJ8MoAV3F8kQgPB/qdpSInQBzDdS55dKlxJT6WBlj5XyNQz/gnb9S0pwVI8vPjUY2BYGq4KuU/+kT1cztuJPxcCgWDD5HMOIUfU74lTMRqx8S0bcBvI8+Ia6lwI3AFsLw3p96mXPhRW3PpsT/GxGx53/cHUyCiWxXuU3YVQrSr9zQweENzzJU71bxFdflsV9wywmgcdEW/QLXfU14QIdNx+LmmbaolcFUNQUKVUFVJFY0IDK+NRoZO8Uo7KVMElUv/AJx2QN5MOZgdcFPPZDz79EgnJOjiZ0X7RtRksrU4IfEJeLg/ab8eYomFjh5jwNdLmD3qMWy9tbg3A8yqLnP1p/FxoWX1OLJesVhOFFPMs6RGi/Es3HRHlifVrBRnhNjDQpciGDSR05QgP7IAd0M+2bODSLRy2xou9uE36gHD1pmMRKwJ4TnxqJjlt6GPIzzBgZpKN1E9Hp0ulnw5llNaU57wVUpg4f8AuXTJirXsaZwo+HOXZ4hg2EoG0BcA3jlHAtgrp8y683mp3lT7lS/VOx3uv3Kp3LqnUpXuHUBt72C791B6waXZurxKC4tE8MSgQBfmnMe5sBbAmaHXtilpvA35CCfCBuei712Ya0awvmGwfMbnMNU98H3KsBfWDZgCLeEUBcnDKVHCWFy7xuXgiUVW9wCoP1AzD3TZAHWrJY1Glq13+Eu5APY6Y9kptK7Ol5i1uNJpZds6i5mmCJV3ZRv5lQDtCx8ii2Wk3aaICs+Y6qXOiXy8TaK6IHdC4/uIUrXPwCiNnTj9dAls8Uv3C/UQoPilwDiVYVp+TgqV8EPg4vBApnTheLIsCjWDcDvA19Zq8CSwOinBjb+H3KmDK5d16fMucsXFjVwsJlqazAwRJYWZ+4bHWD1TtD4Rsd/4hmG70Oh3grFIlLwS0h0uJlzAuHT3nJu934jo2hUQa/xr3lXKC5nSQRL9J0RKQvzHKFnRip1BlN8gWpxLdSA9ZbynQUxAoN1KeGeSXDfHJLAZQ76FARvk+q0Pz3MHnNYiJRVd9QL714spV0A9E7YBcl9gZ4jcIZb55PJc+IcrqwEe7BvimVhG8zqAa6Yi5H1Rdgf0d4gqoTg7IPuDJYVd+9/CElLyCphdfeK8mIL+e5CgYDp8/C9neCK1EL1y95mZ3kwTNqQJ0rTh63K/vhN7WVXJU9xEUKcPNRRXOMIjgDOOZccmLzxBxpYi7NY3GHKibybN+URGQIFk3mELQVqgaUOgB+mCXShvFjE41XmGi+SFSrfiluFROkFH6QboeyW7sgDmOYKc6R23+CBChw5JZRYHK5+vT+oSmwKvWVHuxZG+euKoixU8uD7iLcDkRgJYi8JNbr8xzZCusyWB2Z3ZmPYWCLVlD7RItQel4PqCtfptmsY6xHrLhOUpByAN01hqMVUGLJ2Q2dCDV0ux8Qm4LLR6jpCRUGCNgOI7AGJW6zRtBvSbYgusBFfqLFgwzUBO/N20q8xkjefMJapAxasLr1GlYOiO0BSXefY9wYpt3pzBGg+PsIrgCq5Ot8JdFdmC8LLPuDDL5HRKNqb2yVQf+BXGWG8o6RCMgS5d8dLfNqXeC/E3ehVKfQjfFRtL4knEcbJJqfwI8ySB1V+uGNsbUZ57TNXjU8ylIZCgfDa5VdM7wYVnRr9kAf8AqV6X6nm8SztnojWMp0WNqymT0wyAi0qsznCdhlNIaZdxDhLsQQbhBTKjoIaUb8wHY8cKLJmWNnaO+IXLGqhlWaGAgV4nE4Pp/Qj1dMfk3LGzmxPiwgYC5z/rLdft/ehnrT4pVQ4bF+qCIcu3oP8AxCJZWrYgRJvXdF1mDhvK7UQ4uyAzSzWh6x6gtXwYiA9ljUgB64RAeZWLjLFaYGfcCFE8WH4lZbysmXQV5cPmZImYYQDZ30iTohDYPHMIJlpVP1GrVcv9EHzFW2CEJ4Ny8KW+n9EMWMOqWYh/i+oH/V9RNpL2m0+bNiiecTSo7KilrsD+5uPe8H1EOsLpEvSA8QdP4xSiQ/uR3RM8QLqimErPTUqOjLd7SNd0Ns1gd2ihqgz3U2/r32gpahbfB18T4bTLbMTdYhAPLt6g06wazKEepUqZ2lrjW44wmMfBz+JWM2BDstxKV0VHgynDtDJXgLuBTvI/JJUCfB1dcS7A8IDebyQVemkfcbeFAdfmPr0ZqH5itCkiiO+YgpIFs9pevGpUj2znouDLmPPaSKWlRg5TzG3zjKewX6ju6LHaDqOf3GHKXM5R6jFZiL8EYpEcEek+8SJq9xj7knE3kP3Krk1Q2FZGsrJmr6xG20XOF+YigZh+J0CdGBcTtQfEHuo8JXiV49EVvU73bLDvTZeXRIMO/NMUQKI4U+y5RDyz/cIAWn/tMSh/rmLU/wCO0DYkcpavCoB3l+MSLIrgKFoq40dY4rghD7qI0bLgGc0gTQSYz7JCYSkOLvCVYna3kcPiaAUnZoc98R/qwyFvWUSDsif3nFSapN3aMnN/ow9OsTA9sQLqMpDxc4neZNr5FM3Ajh3J/cMBXlqD9wBPsgUI4sDfSEUtxs8TTIErCTq8XmWY1/sYU+rdXzzFT/xYsAS5Qb0n5RmyxhLsJ+aigYpqJNxVdOV6hUiS0x4NAHdH+4xfD+N79YTi6iFVtV8IAQt1BWCm98R+kDYfkxhl2BfieAx3cqNudl9MPUuzxeqliE4FsCN++IELFgwpxU9Lf1M3AdBMWx5/1HHYaIX/AMQElNmucR2JlGMwKltjX/YDCwAc9mZC43Y1EVA29mAeOKRcspbXqXdP/wCCQgCLqSdOf9WY2zdGfyY2b/dwtd7P4CPouf0TfgyjkgtwSbvnQ6GmHFbUAvKrUuAFfT+yG6PYflhufWn7j9heyj4b1/tGqODug3pdkvNwIiNsRIrEpwMXGIO6S+bC5n4Drcq93Emu6xkBPg4BgCVRXqqBUnyr/mXTrS2LvFSjb+ZBvyS/uci+ILYEBpA6wVyhkQycKC56ziXFaz/C3QiLZFv/AMinL+OqCGmN8zGbTJBRc3BSVP8AZr7nhCFroSxGVXqQ7pt9Qjbheb6Q9qVcS6hFEVuzx5iVLbj9Mi7xMtzoNPyQGWJx5eZiK9u2B1qY0NAiOocxys9Ki78mrmwTXAHCF/czERNzy6TnzIuuXjcfd2zr7IM4sxDWKyh0uNVWAynVqUbd0sPd7d99oktGwKPXPMv9Bsew7x9QYvbyU5IqE6zIe9GayzHXuFbNb6kt0J0bWcSxWa4oamfb6AfuDeDK/wBzaP6xtaGoB6L1jdaucixcUVPlTLQQrdniDtOy/ETnanZRDiE5ILklT2gOIuKeRKN/U7B4garL3bn5LZ0VLOGC1ixOHS5lHYfg/uUIN0HF3TDdxeXcvtOq5T0rzL7qIegzvk1A6FxvlZQ5AtXY8xea6CN/LLahgWprrLCy3IAcsbMkcPYcwcPWuT7ScGOFzv3C/VRfnRrXhm29IHnlsMp3doFD3wV7lGENyciPwYo8qdKubhIQ5671FLm6tleJo/gUfhqY2BnLvzCXeWX8VEFDGbepmNQS/HzBi1hTPh4gPHak/D0SprlRWFG9u2OmtxFRW2v1C4HaOjAUAuUuy6tWUF6oM1MncMSmsDTvG8cVD2VsfQW+5xREd8UZiwwQV2OsfnyQACHQv/ZiKxbaPaZjhTAnmfqF/MZU1gDEKqKEK5HQOHuBCoM4HLXGT4QV6ENfQN+oNhJKexjbBTiQRSJ6TrAQloRh2I7ND1bPxco+4dZ0FM/EdQQ/d6go/MFT9gL554mNSD1R+YrXFbckv4ipw8rhMabqCG6alRQ1rbcNAblTYYupUCeihiFy/Enn0vyzNCZWphdRfwMX98SE/wBktiZ16JlKsD1b+0DhzqM+IVzHrKbN6e45gfB+I3V7gjRANZXvK6KmGoK5yJ1p+KbHfE09v8EMrg1adxA6F8TUv/gx3/g3iGRqNUTheMqmHNIYK5HWdKr7gl0JvEVWUcu8VHQ1GxwKOgn9y4MwfbURamIAcLFLBoLGhjy7ntPQf3G3tVgd08sTruf20j97wS8JPFD+WYiCtFLjgWd39cAHDtRKYzp/ZEOU9oinzkdXZq8Q5TdY2eh2mZV+hDENjmNazwTjAOJcWLez6wFZg5pWT6434+YN+jEpAUWeZgNnspDWQ5X7m1P/ADywhV+1OAQ7IPCuIo0eN+SSjVxftHylPCJtD9b/ANQq/WP5EDtJNYGO0pLfnRP8b6nGH5f4IB/s+oHdHp/yiW0POPzGkQfMZQs8IChYjfTDkHrP4l7v5glM1cU2N+YrEOIPdUzZaOd6mYabLSGsHHdD2QqBLXAhYhhaB0NMv3ESMrqNgseajsSjE0U7fKGHU/5xH+JeVBMrPGNO6oiCCKxAUF/cD0iol4KKryk2Vpsh1yL81HsdtOETauEDb03HKP7UVlaRXd8xCsNDv9Q13INf3UqBjXSxGc9lbgGIxuXy5lNO4L2+oWmKRT4hayul9MI9PaNQXh//AIU469tvkYwe5YndoH3GyVwf7nAoSofiX7CLD3rrECcZo+aA1PZpD2Iqhpcq06lS4w6gLwqmDNxt1EsGTfR++INOquDuVXgDvChUVwPKmo5SXefkS6uh0EZ4cBJ5ZZbx40j5uDVJSHxKBl8Rz+4AEc9xeag2N/XDGR8+UtYoXnrDRq7z8fwqBul0ME5QVib1S9lQ6FzAHbaRwsgHOZWD9izvziauZAAnVtNe47hXnp0b34sDvKIr3kO6DWhvOA3go3RWYRqO/pMNim3tF2AiYSsxo6UyGMsJTDoduWCroElCKok6aPSLUdj+dY7m+U6R6H6gGihRoUd3/kTyPDG1V+Vxbdr5qd2F+GXGl73OQPz/AALIblY0XBSgJ7uLOX5lv8y3eHdOyy3U+Z7y5noyyK7wyvX+LP8A4C3BhT2GqEqOXulCV93jhmdcAzqwCfpN47hHLHUdzkHNRM4snjlFm17zZNTkvt/Gu2oWWmg2TyXEucg9sqUSW3qjrGtXOEE/c6ee5/cwQjoH9x9KnpD2EdmcD7zM/ebxfuK6hHQug8AlD9QvcwA/uM2cdQcI4AKKNdEvQfVR+Y/Res/m47bv9OJgymFzCuyh+JaodAfojkBxtnzKQj0z6mp/7HBLAX/NYgyx0O/eGhM6C/wlZb/qqakz/JUJUT3l+n2KOQHpaj8NP8jPnOBPt1EBol8f7hqjyn5qfVzA1Qumv8pNUP8A3hYjVL/XSbY/P9U/FX+6Ia5pX5Ms2tRro2oco74SxArV9W6nmpTsmPY2U1mX9Ml4ICmiTgT9GJ1Vwzj8u9K0b1fDHs8RfIaeLh6lyWWnnCpBXeXTHyAHqVPuVk/AIGq8ODyQ+46XtjI+oTZtgOf6gVZ1YJxbA/BKr7htNlWUxDGjp85hg5zBuStGFw2wVxHVmIJ4wrHleo5FFqv28SollRmagkJhA4d3AtVrqk0dtgFqYtMbflMZl2EHtLaqUp/cWbt7qpQOehT8yprZJu6KeohDWgKQY62R9IBb3hA09Y/rmfEdIZXD4M4ndB8dfcB0WxahafgW7/EOKVLtW4314gtpFt2r7+ojoDSdxiZVunPE/riwoBAAuVXiH/gSynyJRFwjbpD0H4mP0A9QpZAKaoL6J05kghjZMSPJ0gAeUDTaiVnULXQK8SpY76wBBOpzo3mEp8vAlqOv4AAyOvUG9zL1hco16Tm/zClPXI6+JaNpVAnEGjomFjM8JTrEOkR6QRgjzDPJG3WB7nn+KMa9JSeX8O0/wLcsGlOs8J7zynlBHmdhK9Yk5hvZlZw1mkLZe5VSRHHIOuYdrFBpPcTC+0xYKz0WTuJpF66GQcjiUtdi9bxMdineIcoTBTQaQ0A+sulh1J3cppWlCmprBAgnsR9R7p/5kJ9kxA6/DKwu/DNZ8corBdGFwYrN9B/qB2kIb5lQdkNIS83zNS5xX/KtpT3/AIW6D3GuyeMfuAsDvS42fOUi9oAfpniwGP3CML0o+YZlP9GIHXjyR3UWizouikuCei/ITHOmMhJIPVfsmprrf+IbAS6abDLXnJ+FFvUTmh9OILUjXDYYpldrX4qPqnxBtCI0Wv5uLg2nOv6gM3tmoCVgdow0vzG+PEoVop3OVuLagV3U6ydWhLroS/nQ4orzI8XUAxTeY3ROgi2yTatnJTKjMWxgbK5hhRcAKt6eY93yU8oj7gRAolfoVcEmcaN/GY9qaiYdz1l90aoblhBdFLuCuenwdfEsBRabaqKll0KyZSt7uqiFLwqr1ivJDLIstqu0KILoue92N4gJle8CPhZY9XcZhUWJdGjLGB62q93iJM9RJ10qUgtF2NQSN6e3yPi4wlhqTg/cGBiUOOidYUc+7Hfp5gEI2D9FwPS2jIHDwfMKYzCgOKLlrPRVsbc9OKh+zuWL21BC/HsFaKauF3AAwfn6nXFCPbiKlmgQ5d2HIQRgPSxuZ8YvMwK/pn9WM0xeRi365pw8n/P4b3VUwgSESDyuIJxGgDE7S8WLzCzPRlujO6fM8z5nTSdwiPP8RmNOI1lnWW6s80SdZ2JXvPLO5APLLRrLdZeO8xPn+E6ic/70rwOCWkfhYOYCyeCOrQ9SIqA4RwOnhZb2kK2TOkA7LTQrwyj3O1L8Qk7e9VMf3rSUr1c1Y+F/cI5I6RAP7cfuUjVeEo4H+Pmf5P8Ac6+8F/DDoIX/ALzLiJOyXiGYVwXXjMYTdVn+0XqdNS8czt7UKvRnvEo7iXgTrKykvPee01q5Rc6iOIFRvFDow+NvW4PQHdhW3HC/eK4XqNwEadT+ot/vuxFpbNVT5l0Wvhf4uLG2vitISm7HKW7R/wCyek9ZT+AUB4j0R2NF6B2Wg+YxKJQqo7IBbcPxEauor/MFr1EELpiDlLsQ/haFUysvA9IcVHDlLSdgBg/tMlR237R2T2iEZ45VSveFU2iv9Ik4iLr5Zr+pWT1Mblxul7n/AGKXZl5v6RYQttx1YaJy6deL3gugAus7juxG2oex1AGJlx3UvRqKWpfeLYZCA+4XXuAOVQqfKFeUnBPGMQhiEseXKVRDMxyAPNZ2SqfINAZdl5VoHpw/MXhuqgNrAzmtLng6MrRdr9m9RVBQYDqdYAcuAvoA5ZbmWlrOhALA2qQCPEHgP0/ozDG7bpec9zO2btK9rS0Clq1fW5mmkuBThTmHz+GWo/SHJwLb8EvMwRmxE72Ymdj11nO/qcb+J+pMLw9EFvyJole5an1AF2j0Ec2QQbxOqme6gPLGkrrlfwISmjKP4A/xbFT+SM8IFlkolXWdz+O3+FEo9Z7Rt/gas8zIuGCVYdiYkl9YW6l9Sb4PmNZUzsFY21Nd7WVvUzXb5gba/ZH/AN2alTcfwMdL5YB/zOtfE8iVojwo+Cd5EjDKOk3C+U3+PMUA8qjB2nYRSWKFd4Hhl/5PEvF/hlKS3p/G3/yHk/w82ektgX+C1FcX7nASe2DbJ5Uwm+rqEWg6jHAsNZUNu/UY73Ut/jbLy0tnenel4v4kmTou4WTYA8S7rErOeiGYccOq4SKNJnJ9sHZQthSIdRizzFxRseWZFp8zdFotjIL3F4lrgp3lZWjk+EDWjSHE3uOiqbq9EaaieLihbfiI9FIpp/jNBbk+SoP3NQRpagv5mH0g7PNbhJXQ3kjH1iPnu44Udy0dniJAv1vKtLHxF6Zu2r3c0oFehqjiEscvgeJwqno3CXxqSe7v4qUKH96Jh9PiwA5gCHRX7gI+WGlhmVpwz5uYFJ1ewYUQlg4CkfnP3BZLISkhc5Db3rQGY0pgFKt4JdBWAoe1izeirfLrG4FTsoU4h/D/ACI+x8fx6tFfxuSBOknRTtztwn/wNgu/5X8SQf8Ayo3+F/8AbR/NoSoLiOJXWTLZ0bFxD8zJ1xO0v1/gL/Ny5frKOhFF0lwPSwhByUtMEFhwIsV5BtVvcsRvGnP+K1VEp3/molH/AOFErKIJRBKIDsIE7Ec27nAEvXX7jn5A/qf/2Q=="
+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "![yolo-background-2.jpeg](attachment:yolo-background-2.jpeg)\n",
+    "\n",
+    "# Convolutional Neural Network\n",
+    "\n",
+    "## I) - Introduction\n",
+    "\n",
+    "Today, artificial intelligence allows us to do fabulous things...\n",
+    "\n",
+    "If I ask you to write **an algorithm that can detect a cat on a picture**, could you develop it?\\\n",
+    "Maybe you would have a result that works from time to time, and even that would be an achievement.\n",
+    "\n",
+    "The color of the fur, the color of the eyes, the position of the cat, the size of the cat, the perspective ... so many parameters to take into account.\n",
+    "\n",
+    "But let's go further, let's say I ask you to write an algorithm that can tell the difference between more than 1000 different species in an image.\\\n",
+    "You would give up, wouldn't you?\n",
+    "\n",
+    "Let me introduce you to **convolutional neural networks**, the heart of **Computer Vision**, used to manipulate visual data."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### What is Computer Vision\n",
+    "\n",
+    "Computer Vision, as its name indicates, is intended to give **sight** to machines, more concretely it is a field of artificial intelligence that consists in **interpreting visual data.**\n",
+    "\n",
+    "Today Computer Vision is a well-defined branch of AI, whether it is **classification**, **object detection** or even **image segmentation**, all of this falls under what is called **CV** (Computer Vision).\n",
+    "\n",
+    "> Today, CV is present in Tesla cars for example, but also in some cameras, in storage shed robots like Amazon's but also in our phones with facial recognition ..."
+   ]
+  },
+  {
+   "attachments": {
+    "cnn_background.jpeg": {
+     "image/jpeg": 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i31Fj8sbW7M3zbnZFZWYMrN83ylWY1bwcfDPw805rR0/tnw+h1CKdmwLifDNcbmVfuzbpNx2/xbtvy1cG4qaqfa92P9f+S/4ZB7vu8v2TT8CxfbfE/jHV/lKTXqWMBC/N5cEaq2W/67NP/wDtbq7tRzmuE+Dd3Fe/DjQ75G+e+R76ZcjKzTSPJMrf7SyO4b/aBruxxXJX/iyXb3f/AAE3pfAIMD2qNmz/ABfpTjkLyea8C+Lf7aXw0+EOoT6bd6tJrutQcSaXo0fnSo391mJWNW/2WYGuWpVp0Y81SXKj0cJgcVmFX2GEpyqS7RVz3pLgv90ZpxGRz19K+E7r/gqLbJMotfhneTwZwzTaxHG//fPlN/Ouy8Ff8FJ/h/rlwlv4j0nVfCRZtq3M6i6t/wAWjy3/AI7XnxzTBzlyxqH1mI4E4lwtL21bBS5fK0v/AEm59f8AFHasnw54l0zxdpFvqmjahbarp1wu6G7tJVkikHsy8Vrfw16h8O04uzFooooEFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAV5T+1l/ya18Y/+xM1n/0hmr1avKf2sv8Ak1r4x/8AYmaz/wCkM1AH57+OP+SAfsj/APYz+Ef/AEkavQvjT/ydn+zj9fEn/pBHXnvjj/kgH7I//Yz+Ef8A0kavQvjT/wAnZ/s4/XxJ/wCkEdfR/Z/8BPMf/wAkHxp/5Oz/AGcfr4k/9II6F/5SAf8AdMv/AHK0fGn/AJOz/Zx+viT/ANII6F/5SAf90y/9ytX9qX+L/wBtI+x/26UtY+KPxp8WfG/4heDvh7a+A49M8Kf2ful8SpeLNJ9qtvO+9C21vmWT+Ff4fvVf/wCMqf8Aqj3/AJVaT4MD/jLL9oz6+HP/AEgkqjrHxS+NXiv43/ELwd8PrbwHFpvhT+z90viVLxZpPtVt533oW2t8yyfwr/D96p+zzSl9oryL/wDxlZ/1R3/yq0f8ZWf9Ud/8qtH/ABlZ/wBUd/8AKrR/xlZ/1R3/AMqtP/wIX/gIf8ZWf9Ud/wDKrR/xlZ/1R3/yq0f8ZWf9Ud/8qtH/ABlZ/wBUd/8AKrR/4EH/AICH/GVn/VHf/KrR/wAZWf8AVHf/ACq0f8ZWf9Ud/wDKrR/xlZ/1R3/yq0f+BB/4CH/GVn/VHf8Ayq0f8ZWf9Ud/8qtH/GVn/VHf/KrR/wAZWf8AVHf/ACq0f+BB/wCAh/xlZ/1R3/yq0f8AGVn/AFR3/wAqtH/GVn/VHf8Ayq0f8ZWf9Ud/8qtH/gQf+Ah/xlZ/1R3/AMqtH/GVn/VHf/KrR/xlZ/1R3/yq0f8AGVn/AFR3/wAqtH/gQf8AgIf8ZWf9Ud/8qtH/ABlZ/wBUd/8AKrR/xlZ/1R3/AMqtH/GVn/VHf/KrR/4EH/gIf8ZWf9Ud/wDKrR/xlZ/1R3/yq0f8ZWf9Ud/8qtH/ABlZ/wBUd/8AKrR/4EH/AICH/GVn/VHf/KrR/wAZWf8AVHf/ACq0f8ZWf9Ud/wDKrR/xlZ/1R3/yq0f+BB/4CH/GVn/VHf8Ayq1j+MPDH7T3jjwhrnhy/l+EsNlq9jNYXEtq2qLKEmjaNmXcrKG2t/drY/4ys/6o7/5VaP8AjKz/AKo7/wCVWj/wIP8AwEXwZ8bf2hP2eIfgj4I8R23wzvvBt1rmieBY5tKj1GTUBCwWESbpHSPd5cb/ADbfvfw7a/RftX5feOPh1+0r8Qb7wfdajN8KreXwt4hs/Etits+pqslxalmjWTcrbo/mO5V2t/tLXX/Fv9q39q34NfDvVPGGtad8HrrTdNEXnQ2FvqrznzJlhXaGlVfvSL/FXj18PKL5qcfdO2FWL+KR+ilFFFcR0BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAfnt+zP8A8jH+0D/2VjxF/wChR15r+z7qV1pP/BN+4vrK6msb218O6/Nb3NtI0csUizXrK6svzKyt/FXpX7M//Ix/tA/9lY8Rf+hR15V8C/8AlGbqX/YseIv/AEZe19DS/hR/wy/9tPLn8Uv8SNz4Wfs13Xjn4Y+EPEl/8Z/izHf6xo9nfzpbeKWSJJJoVkZVDRs23c396un/AOGQR/0Wz4wf+FX/APaaP+bAf+6Z/wDuKrz/AOHv7JXwC/4Ub4O8YeL9BtLL7ZoWnXl/qmoa3dWsHnTQxbmY+cqLukkHHy/ep8sfd5Yj5j0D/hkL/qtnxg/8Kv8A+00f8Mhf9Vs+MH/hV/8A2mvOf+FGfsZf9BLwb/4W0n/yXR/woz9jL/oJeDf/AAtpP/kujlj/ACx/8CHr/UT0b/hkL/qtnxg/8Kv/AO00f8Mhf9Vs+MH/AIVf/wBprzn/AIUZ+xl/0EvBv/hbSf8AyXR/woz9jL/oJeDf/C2k/wDkujlj/LH/AMCDX+ono3/DIX/VbPjB/wCFX/8AaaP+GQv+q2fGD/wq/wD7TXnP/CjP2Mv+gl4N/wDC2k/+S6P+FGfsZf8AQS8G/wDhbSf/ACXRyx/lj/4EGv8AUT0b/hkL/qtnxg/8Kv8A+00f8Mhf9Vs+MH/hV/8A2mvOf+FGfsZf9BLwb/4W0n/yXR/woz9jL/oJeDf/AAtpP/kujlj/ACx/8CDX+om54t/Zon+CHwU8T3Hg/wCMfxa0Wz8PaPfX9hpdn4o+z2Uckcck23yo41+VpPmbbt+83fmvvP8AZp1a+1v9nP4V6pqd9PqGo3vhXSrm6u7uZpZp5Ws42eR3b5mZmbczN61+en/Cjv2NT/zEvB3/AIWsn/yXXM/FT4Mfsmab8MfF954d1Dwq3iG30e8m00W3i+SeVrpYWMOyP7S25t235drbq4a2H5/ejyxN4VbfEfsHRXy1+zT+0x8IND/Zy+Fel6p8VvA+najZ+FNKtrq0u/EdnFNBItnErxujSblZWXaVavqWvLOsKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAor4w8P/8ABTzwn4r0mDVNG+Dvxh1jTbjPlX2neGYZ4JMMVbbItztbDKy/8BrR/wCHkOjf9EK+N/8A4SEf/wAkVXKyeZH15kelGR6V8h/8PIdG/wCiFfG//wAJCP8A+SKP+HkOjf8ARCvjf/4SEf8A8kUezl/KHMj68yPSjI9K+Q/+HkOjf9EK+N//AISEf/yRR/w8h0b/AKIV8b//AAkI/wD5Io9nL+UOZGn+0R+zxr2k+LZ/jH8HoEi8cxxquu+HHby7bxPbJ/C3926Vf9XL/wABapvhJ8W9C+MvhGLXNDeSHbI1tfafeL5dzp9wv+st54/4ZFasvSP+CjHhbUPF3hTQb/4W/FPwy3iPWLXQ7K+1/wAPRWlr9puJPLjVpGuPfd8u5tqtheKv/tDfs9a9ofi6f4xfB+3jTxska/274bLeXbeJ7ZP4W/u3Sj/VyfxfdavNxmD9uuaPxHq4PGewlyy+E7qiuM+E3xZ0L4xeEotd0R5EKyNb3mn3S+Vc6fcL/rLeaP8AhkVq7Ovk5RlCXLI+ujKMo80QooopFBRRRQB5D8Yfg7qms65pvxC+Hmox+G/ipoUeyx1Bl/0bUYc/PY3i/wDLSFsf7yt8y17L+zj+0dpnx50K+gnsX8NeOdDkW28Q+Fbx83FhMedyn/lpC/3o5F+Vl96gryP4w/B/VdY16w+Inw8v4/DfxU0SPbZ3zKfs2p2/G+xvF/5aQtj/AHlb5lr2cHjPZ/uqnwnjY7A+2/eU/iPsyivGf2df2jdM+PegX0UtjJ4b8b6JJ9l8QeGLxs3GnXH/ALUhb7yyL8rLXs1fSHyoUUUUAFNZQwweQadRQByOpfC/wrqlwbibQbFLw/8AL3bxeRP/AN/I9rfrVcfDmWy/5BXirxBpo7RyXa3q/ncLI3/j1drkUZFX7WW1zPkicLcR+NtEt5JTquhatbINxW8tpLJwvvKrSL/5Drj/AAX4h1y91W58Z6v4L1Yy3sIt7MWNzFMltZr8w/ds8bM0jhpN3l7trRr/AA11njWSTxLrFn4QijZrO4jFzrDqy4js93ywuvfz2WSPj+FJK7dI1iRUjUKqjCgdq29qoQ96PvS/L/t0y5OaXuy+E5H/AIW14at1xqF5NoZx11qzmsk/76mVV/8AHqXVvH9u/wBms/Dsltrmq3a5to4ZleJF/imkZfuxr/4991fmq34p8Sy6bNBpmmwjUNdvFPkWrZ8uNf4ppm/hjXn3b7q81i6b8GvDUMLy3+m2+oaxO7S3OqmHyZ3kbqUZTujXn5VVvl/3stTgqKXNLT+vkVLn+GJveFvC0egQzTTTtf6pdFZby/kXY879vl/hRc4VR933YszdFziuL/4V29n/AMgjxNr+ljHCtefbV/8AJlZD+tBsfHengGHU9F1uLtHdWklpJ/39RpF/8h1lKKqe8p/1+RSly+7ynbDjvTStcYvjDxDp2BqXg29kx96XSLyG6iH/AH8aKT/xykPxZ8NwqRf3dxoLY5Os2c1mq/8AA5FVT/wFqX1eb0Sv+JXtEdxRVDS9XsdatvtFhfW9/D/z0tplkT/vpav1nsWcNp7j/hafii7kbFva6TYRbv7rb7p5P/HWiqf4RxMnwz8LvIgWSawhuJV9HkXzG/8AHmNcnrupNZad8ZdRSLdJZweSisP9Yy6fHIo/8jba9J0uCHRNGtrdpf3FnAsZkfj5VX7x/Kuuv7sbdPd/9J/+2Oanv/4F/wClHkP7RXx4b4Z6fb6HoXlz+LdRG6FJBuW0hzzM69/9le/P92vj1LSSS/n1K+nk1LVLpmkuL25bdJI1aGs+KJ/iD4u1vxXclmbUbpvs6t/yzt1+WNf++VqGvyPNMwli63L9mJ85isRKvU/uhRRRXhnAM0+a/wDDeuw674fu20nW4G3JcR/ck/2ZV/iVq+2vgP8AGe0+L/hhpXjSz1/TysOp2A/5ZSc4Zf8AYbaSpr4orqPg54ul+H/xh8P6gknl2erTLpN+v8LCT/VN/wABbb81fR5PmEsNWjSl8Mj1MHiJU6nJ9k/QHgDmqWp6pa6Lp1xe308dpZwRtJLPM21UVerM1UfE/iew8I6NcanqU5gtYhyerM3RVVerMzcBR1zXOW3h258eXtlrHiOF7awtZRcafoch+46n5Jrj+9J0ZV+7H/tN8y/p0Yacz+E+jlL7MfiOO8D6UfHv9raPeNLbeE9P1CSa309w0cl/DMfOj87/AKd/3jKsf8W35vu7W9mjt4re3WGONEhVdqxquFC+mK5K+I0X4p6fcdINb0+Szk95oG8yL/xyS4/75rtioq8RNzaa2/q4qUeU8R8A58Df2dcEbdMkuG8PaiO0U1vI0NncN/vRrHG3+9D/AHa9sG04wa88tdItL3xR478N36iWy1OO31AxE4+WWLyGC/8AArbd/vNWr8Pdaup7K50jVZDJrejyC1unPWdduY7j/tovzezbl/hrTE2qfvH/AFf+rfcRR933Sp8Y57ey+Her3k1z9lksxHcWsyqzkXSyK1uAq8sWl8tdv8W7Hej4SW8Vz4Rt9akVDqeuj+0b2THzCRv+WJPcQrthX/ZjFMkuP+Ey8fCFY5BpHh1/MkkbHl3V8ylVVfUQqzbv+mkkfeOpfBbf2B4n8Q+HW4g83+1bFf8AplOzeYv/AAGZZW/3ZFpNWoez67/1+Yv+XvMZ/j3SLbx34r0Pw7MzAWQbWZ5Im2TW7LujtmRv4W8xmdf+uJ3f3WxPG3iLU7PQbnwdr6M2oawY9MstXt02w3sc0ixSf9c5kjZmZf4tu5P7q9X8OFXURrHibYD/AG3debbS/wB6zjXy4G/3WVWlX/rt2+6tbx3ptn4s8WeGvD15CLqyAutTuISDhljjEK7v+BXSsvfdGrL901pCpGNSMHtH8/iJlHmjzR+0Pso08FeOG08KI9F1+RprXb8qQXirulj/AO2ir5i/7Ucn96u7ChApHOK8o8SwXelWT6D4gu5TpMrr/Zficj95Z3AbdCtx/tK23bJ91sbW2t9/E+MPxtuPBH7O/ibxWUSx8S6dCdPNt97ydQZ1i2r/AHl3MHX+8m1u9YV3yU/ay2OvB0amKxMcLT+KUuWP/bx83ftofteXl1q2ofDrwHqRt7S3LQa1q8H33fo1vC38BU8M3/Aexz8TwwJbptjXatPTzCS0kjSSyMWd5G3MzN95qU9QBX4zjsbUxtXnkf6L8K8MYPhjARw2Hj732pfalISiiivLPvD0b4GfHfxJ+z94pGpaK7XOjTuv9paNIf3dyv8AeX+7Jt+63/svy1+tnw68faN8UPB2meKfD9yLrStSi82KT+Ic7WVl/hZWDKy9itfieOmK+0P+CafxOlsfEviT4fXExe0uYf7X09D0jKEJMo/3t0bbf9lq+0yLMJqf1ap8J/Mnivwfh5YSWeYSPLUj8f8Aej3/AO3fyP0Mooor78/kcKhmmjto2kkZY40XLMx2qoqavyH/AGpPjJ+0R+118R/iR8NvAGjXWj+APB19qWm6rPp0rQwXkdvI0bfa7ptqtuVCy269VZsrJt3UAfpx4Z+PHw28a66uheHviF4V13W2DY0zTdbtrm5O3737uORm+X+LivQK/Bn/AIJO/wDJ7HhP/rx1H/0lkr95qACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACvKf2sv+TWvjH/ANiZrP8A6QzV6tXlP7WX/JrXxj/7EzWf/SGagD89/HH/ACQD9kf/ALGfwj/6SNXoXxp/5Oz/AGcfr4k/9II6898cf8kA/ZH/AOxn8I/+kjV6F8af+Ts/2cfr4k/9II6+j+z/AOAnmP8A+SD40/8AJ2f7OP18Sf8ApBHQv/KQD/umX/uVo+NP/J2f7OP18Sf+kEdC/wDKQD/umX/uVq/tS/xf+2kfY/7dE+C3/J2v7Rv/AHLf/pBJS/Bf/k7P9o36+G//AEgkpPgt/wAna/tG/wDct/8ApBJS/Bf/AJOz/aN+vhv/ANIJKa+z/il/7cKX2v8AD/8AInIeA0+NHxn174kXmlfGX/hFNM0Lxhqeg2mnf8ItZ3mIYWVlzI21vuyKvzbvu/ersP8AhTHx4/6OM/8ALGsf/iqP2QT/AMls/wCym63/AO0a8u/Zm+CmrfGj4IeG/GOtfGP4qWmp6j9o82LT/E7LAnl3EkK7VZWb7sa/xVlH7P8A8kbbHp//AApf49f9HGj/AMIWw/8AiqP+FL/Hr/o40f8AhC2H/wAVS/8ADIA/6LZ8Yf8AwrD/APGaP+GQB/0Wz4w/+FYf/jNX7OX8v/kxlePf/wAlE/4Uv8ev+jjR/wCELYf/ABVH/Cl/j1/0caP/AAhbD/4ql/4ZAH/RbPjD/wCFYf8A4zR/wyAP+i2fGH/wrD/8Zo9nL+X/AMmC8e//AJKJ/wAKX+PX/Rxo/wDCFsP/AIqj/hS/x6/6ONH/AIQth/8AFUv/AAyAP+i2fGH/AMKw/wDxmj/hkAf9Fs+MP/hWH/4zR7OX8v8A5MF49/8AyUT/AIUv8ev+jjR/4Qth/wDFUf8ACl/j1/0caP8AwhbD/wCKpf8AhkAf9Fs+MP8A4Vh/+M0f8MgD/otnxh/8Kw//ABmj2cv5f/JgvHv/AOSif8KX+PX/AEcaP/CFsP8A4qj/AIUv8ev+jjR/4Qth/wDFUv8AwyAP+i2fGH/wrD/8Zo/4ZAH/AEWz4w/+FYf/AIzR7OX8v/kwXj3/APJRP+FL/Hr/AKONH/hC2H/xVH/Cl/j1/wBHGj/whbD/AOKpf+GQB/0Wz4w/+FYf/jNH/DIA/wCi2fGH/wAKw/8Axmj2cv5f/JgvHv8A+Sif8KX+PX/Rxo/8IWw/+Ko/4Uv8ev8Ao40f+ELYf/FUv/DIA/6LZ8Yf/CsP/wAZo/4ZAH/RbPjD/wCFYf8A4zR7OX8v/kwXj3/8lE/4Uv8AHr/o40f+ELYf/FUf8KX+PX/Rxo/8IWw/+Kpf+GQB/wBFs+MP/hWH/wCM0f8ADIA/6LZ8Yf8AwrD/APGaPZy/l/8AJgvHv/5KJ/wpf49f9HGj/wAIWw/+Ko/4Uv8AHr/o40f+ELYf/FUv/DIA/wCi2fGH/wAKw/8Axmj/AIZAH/RbPjD/AOFYf/jNHs5fy/8AkwXj3/8AJRP+FMfHr/o40f8AhC2H/wAVWD4+/Zb+LPxP8JXvhrxN8fhqWh3uz7Raf8IZawmXy5FkX5o5Fb7yq33q3/8Ahj8f9Fs+MP8A4Vh/+M0f8Mgf9Vt+MP8A4Vh/+M0ez5/s/wDkwub+/wD+Sm/8P/H3xy8C/tW/B/wd4v8AjD/wnvhrxcdYN3Zf8IxY6dt+y2LSp+8iVm/1jI3ysv3P4g1ffZ461+bcv7FNhNr2l65J8XPiw+s6YJRp+ov4mH2mz8xNsnlyeTuj3L8rbfvLXW/sv2HiXwD+29qHgm5+JPjjxroEvw6k1hYPF2uSX4juf7Shh3qvyovyp97bu+Zvm+avHxGHlT97l9076VaM/dR980UUVxHQFFFFABRRRQAUUUUAFFFFABWD4u8VaZ4H8L6v4l1m7+xaLo9pNf31yI2k8mCFGkkbaqszbVVvlVS3Fb1eU/tZf8mtfGP/ALEzWf8A0hmoA8qP/BUX9mT/AKKZ/wCUHU//AJGo/wCHov7Mh/5qX/5QdT/+Rq8h8LfFHSfgz+yB4J8Zazb3l1pum+GNGM0Wnxq87CSO3hXarMq/ekX+Ks3/AIa/H/RE/jD/AOEmf/j1en9Tivikcvt5PaJ7f/w9E/Zk/wCimf8AlB1P/wCRqP8Ah6J+zJ/0Uz/yg6n/API1eIf8NfD/AKIp8YP/AAkz/wDHqP8Ahr4f9EU+MH/hJn/49S+p0/8An5/5KP20v5D2/wD4eifsyf8ARTP/ACg6n/8AI1H/AA9E/Zk/6KZ/5QdT/wDkavEP+Gvh/wBEU+MH/hJn/wCPUf8ADXw/6Ip8YP8Awkz/APHqPqdP/n5/5KHtpfyHt/8Aw9E/Zk/6KZ/5QdT/APkaj/h6J+zJ/wBFM/8AKDqf/wAjV4h/w18P+iKfGD/wkz/8eo/4a+H/AERT4wf+Emf/AI9R9Tp/8/P/ACUPbS/kPb/+Hon7Mn/RTP8Ayg6n/wDI1H/D0T9mT/opn/lB1P8A+Rq8Q/4a+H/RFPjB/wCEmf8A49R/w18P+iKfGD/wkz/8eo+p0/8An5/5KHtpfyHt/wDw9E/Zk/6KZ/5QdT/+RqP+Hon7Mn/RTP8Ayg6n/wDI1eIf8NfD/oinxg/8JM//AB6j/hr4f9EU+MH/AISZ/wDj1H1On/z8/wDJQ9tL+Q9v/wCHon7Mn/RTP/KDqf8A8jUf8PRP2ZP+imf+UHU//kavEP8Ahr4f9EU+MH/hJn/49R/w18P+iKfGD/wkz/8AHqPqdP8A5+f+Sh7aX8h91fC/4o+GPjN4F03xh4O1Iax4c1LzPst55EkPm7JGhb5JFVlw8bD5l/hrsMZr80f2Sv2wrb9mP9mDw34O8X/B74tfafDsF9Pf6ha+GB9iSN7qe43eZJNHhVST5mZV+63av0F+Hnjay+JXgLw34t0y3uLfTNf0231W1iuwqzJFNGsqLIqsy7trDdtY157i1udJ1VFFFSAUUUUAFFFFABRRRQAUUUUAFFFFAH57fsz/APIx/tA/9lY8Rf8AoUdeVfAv/lGbqX/YseIv/Rl7Xqv7M/8AyMf7QP8A2VjxF/6FHXlXwL/5Rm6l/wBix4i/9GXtfQ0v4Uf8Mv8A208yfxS/xI9BH/KP/wD7pl/7iq89+On/ACjL03/sWPDv/o2yr0If8o//APumX/uKrz346f8AKMvTf+xY8O/+jbKqqfD/ANuijv8A9vHqvxR8K/s//Brw/BrfjHwV4P0fTJ7lbKOf/hGI58zMrMq7Y4Wb7sbf9815WPjj+xp/0DfB3/hFSf8AyJXoX7X3T4J/9lN0T/2tXoXxo+NOlfA/QNL1PVdJ1fWTqepw6Pa2WhwLcXMlxIsjKqxsy7t3lsvy/NuZacvil8IQ+E+eP+F5/sZf9A3wb/4RMn/yJR/wvP8AYy/6Bvg3/wAImT/5Er0b/hr3/qifxg/8JT/7dR/w17/1RP4wf+Ep/wDbqnmj/NH/AMBK1/qR5z/wvP8AYy/6Bvg3/wAImT/5Eo/4Xn+xl/0DfBv/AIRMn/yJXo3/AA17/wBUT+MH/hKf/bqP+Gvf+qJ/GD/wlP8A7dRzR/mj/wCAhr/Ujzn/AIXn+xl/0DfBv/hEyf8AyJR/wvP9jL/oG+Df/CJk/wDkSvRv+Gvf+qJ/GD/wlP8A7dR/w17/ANUT+MH/AISn/wBuo5o/zR/8BDX+pHnP/C8/2Mv+gb4N/wDCJk/+RKP+F5/sZf8AQN8G/wDhEyf/ACJXo3/DXv8A1RP4wf8AhKf/AG6j/hr3/qifxg/8JT/7dRzR/mj/AOAhr/Uj5u/ad+Kv7M/iT4H+I9N+H1l4bi8YTfZzYtp/haSzmXbcxtJtma3XbmNZP4u+2v0S8K/8FFf2e/G/izRvDmifEH7drOr3kGn2Vt/YuoR+bPLIsca7nt1VdzMvLMBXz8P2vgf+aJ/GD/wkz/8AHq86+MHx51Hx/q/wvutN+DnxWhj8LeNtL8SXyXHhV1aS3tSzSLHtkbdJ83yq21f9pa4cRTjL3ub/AMlN6c3H3eU/WCivkbSP+CjPhbUPF3hTQb/4W/FPwy3iPWLXQ7K+1/w9FaWv2m4k8uNWka4/4F8u5tqtheK+ua8vY6wooooAKKKKACiiigAooooAKKKKACiiigAooooA/MP9kfxb/wAIF+wZpPiY2v27+xdL1nUfsnmeX53k3V3Jt3bW27tu3dtatLw9+0J8Z/Ffh7TNc0n9nv7Xp2pWqXtrMPGlmvmQyKrI2149y/Ky/erivgV/yjL1H/sWPEX/AKMva6Pxr4/134Xf8E+vD3ibwzff2drdj4Y0H7PdmGObZ5n2SNvlkVl+6zL92vo1KUacfe+yeW4+9/28dB/wuf48/wDRuY/8Lqx/+Jo/4XP8ef8Ao3Mf+F1Y/wDxNH/CmPjz/wBHGD/whbH/AOKo/wCFMfHn/o4wf+ELY/8AxVV+8/vf+Smfu/3f/Jg/4XP8ef8Ao3Mf+F1Y/wDxNH/C5/jz/wBG5j/wurH/AOJo/wCFMfHn/o4wf+ELY/8AxVH/AApj48/9HGD/AMIWx/8AiqP3n97/AMlD3f7v/kxxHxL1v48fEbVPAF4fgJ/Z48KeLNP8U7T4ysJPtRtSzeR/D5e7d975tv8AdavpL4b/ALanj3X/AI6eBfh542+Cw8CHxd9v+yal/wAJXb6jt+y2zTyfu4Yf9lF+Zl+//FtIryP/AIUv8ev+jjf/ACxbD/4qsqf9mv4xXXjrwz4xl/aDL+JPDX2v+yr0eCrMfZvtEfkzfu/M2tuj+X5lbb/DXJWw0qvvcsub/t06KdaMfd/+SPor9oT9nzXdC8W3Pxh+EFuieMljUeIPDO7ZbeJrde3HC3Sj/Vyfxfdap/hR8VtC+MPhKLXdClkC+Y0N5Y3K+Xc2Nwv+shmj/hkVv4awP2KviR8TvEHxb+Nfgn4i+Ov+E8PhL+xPsF7/AGPa6dtF1bzzS/JCvtGvzM33P4d1a/7Qf7PuveHfFlz8YPhBap/wmARR4g8Lk+XbeJrdf/QbpR92T+L7rV8tjsH7X/EfR4LG+w92Xwnc0Vx3ws+KmhfGDwlBruhSyCPc0N1aXK+Xc2Nwv+shmj/hkVv4a7GvkpRlCXLI+ujKMo80QooopFBRRWLdeNNBsPFdj4auNXs4PEF9byXdrpckyrPNHH95lX73/wCy391qAPOfjD8HtX1jXLH4h/DnUo/DHxW0WNls791/0bU7f+Kzu1/5aRt/e/hb5lruv2d/2wdN+K2lX1t4p0mXwX4t0idbLWtPuG3RWdx6M3WNW6qzfu2/hdm3KOmya8h+L/wd1LVNesfiH8PruHQfidpELRQ3Ey5tNXtv4rG8X/lpG3977yt81e1gMbGj+7rfCeHmGB9t+8o/EfZEcqyorIQysMhlPWpT9K+Z/wBnr4oWfxW0C8uPCLN4N8XaROLbxF4A1Y74bG4/2VHzRxt96OSL923Pys2cez6T8QbefUYdK1i1k8P61JwlpeOPLn6f6mYfLL/ur8w/iVa+n5OZc0NT5Xm5ZcsjsqKKKzLGjGKyfEOvW3hvRr7Urvebe0hadxEu52A/hVe7N0Ve5rWAArz7UbZPHnjaK2lhMmjeHZkumk3fu57/AP5ZhSp58ldzMrfxPH/dq4JSfvbGc3yrQ0vh/wCHbnRtPub7VW367qkv2y+Pm+YsLMvywRt/zzjX5V/4E38VL4q8Zf2PdWmk6eiX3iHUN32OxY4VUX780h/hjX+9/Edqr8zVD458cnw80Gl6XB/ania/yLLTw2FA/immb+CFf4m/4CuWNP8ABXgtfDi3N7e3J1TxBflZL/U5V2tIeyIv8Ea9FT+bEmtbf8vqvy/rt/XpH/TumXfC3haPQIppZp2v9Uu2WW8v5F2vO/8Au/woucKv8I9WLM3SdqOM06sJScndmqVgooopFCAYoIzQDmsrXfEmmeGrZZ9V1G102FjtV7mZY9zf3V3daaTbsg2MjVPht4W1S4a6uNAsDeH/AJe4oRHP/wB/F2t/49VU/Dg2ak6V4n8QaTkYAN79sH5XSy01fiMdVbZ4c0TUde5wLryvstoPRvOm2+Yv+1CslK1h421yNxNqdh4ZgI4Swi+2XAPr5sm1F/3fLb/erp/exVpy5f8AF/kYe5L4Ynk+rweKLfwv4rY6lpup2eoeIYbGZrq1aGSRmmt7Td5isy7flVW/d/Ltb72NtXPHHx4ebwV4lsk0STUrj+zblGvfDNyupWcDeWy7pJtse0L/ABfL8tQ6R4E0rUNM8KvfefrNxqfii6LNqMzTxyIsl3N/q/8AVj5Yh8yqv/steh/GuGVfhVrGnafHHFNqHk6TGqgKv+lTR2/4f66vQq+ynONCpG95f4ey/wDbTijGp7OUoyPg3QU2aHYqv/PFavVUsdPn0OW90S8GL3SrqSylULt+ZW+9Vuv5+rR5akonzcvdkFFFFYkBWZ4gna109biL/Ww3EMkf+95i1p1f8IeHpPGnxI8KeHolZ1uNQjubjaMbbeP95J/6DXThY8+IjE1pxlKUYxPqDwL4zvfHzW3i+88F6vrjhz/Z0drcWHk6cp+XaqyXSt52G+Z2VWx8oVf4vRT471sdfh74j/8AAjTP/kyuO8OeG7zw/ea5a+HmitNb0e42rbyEi31Gxf8AeW6yD+FlUtCsn3l8n+Jflr0Pwn4ss/FFjIypLZ3lswjvNPuVKz20n91h36fKy/K38NfuWIcXLmhH3fn/AJn1dFy5eWcveOB+I3jLWRo0Gqt4F16zGh3Uepm4kn09lWOP/X/dumbmFpl+7/FXVL491th/yT3xGw/6+dN/+TK6y+sodRsri1uUEkNwjRSKf4lYYI/Kub+F17LceCdPgunMt5p2/TJ3bq0lu7Qs3/AvL3f8CrJzTp/AtPX/ADNLSU9zi9Y8Yazp3j3w9qT+BdehFzBc6WY2uNP3TyMFmj24uivyrDP97H3qw/ip8S9Y8G3Vj4ptvBmp2V8FfT5E1C6sVhuo2VpFVvLuGbMbKZM7fu+b/er0n4rH7H4WTVVGG0i8t9RZv7scci+cf+/LS1T8Nn/hN/E+oa5Kvm6PZGTTNOikiI8w7ttzN6OrMqqrf3Vf+9XRTqQSjVlT92Pu/a1/H+8YThJv2cZFHwfrmp+GfD9pYw+AvEV0yAyTXf2jTN1zM3zSTN/pn3pGZm/4FXFfGnxhrUFvpd9b+E9Y0i7uJJdIM91Pp58yGeNiyri4b5laNJF3LtXy23fLmvSfAc8nh6/vPB9wzMlgv2jTJWOfNsWb5V/3om/d/wC6I2/iqjq2lJ8QfHerabdx+boml6c1m7g/eurpf3ifWOHy2/7ePptKdRU6/tJxXfr/AJjlGUqfLGRa0/xbqel2FtaW3w48RQ29vGsMUa3Om4VFG1V/4/K5rRfGGtX/AMQNf1L/AIQbXZltYLfTEgWWwDW77WnkLMbra25ZoOF3bdv+01d18OdYuNW8KW329gdUs3exvm/vXETeW7fRiu9f9llql8J1Sfwu+qKF3axe3GpbkGA8ckjeS3+1+5WL5v4vvd6yTVONS8V/L1/+S/umtubl94gvPFmp38UkNz8OfEE8TqyPHJNpjKynqCPtnNfDP7aMt3oGkSaBHbX2k6bfS295JYarJbTTw+U2yPa0M0ny7ZAo8za21FXcyrhfubXfGU1/qF1ovh+aE3tsP+Jhqsy77TTV/i3Ho023/lnu+XcGb5fvfJnxx+FbfEr4aeP9Z063vY7mw06HVLVLtT9ouD52fMmT+KZoreST+H5ZoV2/LtVTT+pYjmWnJL+b/t09nIa0cPnuAquXw1I/+A83vHwrRTUcSKrDoRTq/Atj/T+MuaPMFFFFIsXqa94/YVuJoP2q/CCxL8sttfxzf7K/ZpG/9CVa8HzxX1Z/wTi8FT658Z9Y8TshFloGnG2EhXhp7g+v+4r/AJrXt5TCUsbT5T808QMVTwnDOMdT7UeX/t6Wh+mNFFFfrB/nuFch8TYki+GvjJkADyaTdsxA6t9nZf6V19cr8Uv+SZeLv+wPd/8AolqAPxD/AOCTv/J7HhP/AK8dR/8ASWSv3mr8Gf8Agk7/AMnseE/+vHUf/SWSv3moAKKKKACiiigDxL9pLTB4gvfhjo015qFnY6l4nWC6/s69ktJJI/sly23dGyt95Vq9/wAMt+C/+fzxV/4VGo//AB6j46f8jd8H/wDsbk/9IruvX6APIP8AhlvwX/z+eKv/AAqNR/8Aj1H/AAy34L/5/PFX/hUaj/8AHq9fooA8g/4Zb8F/8/nir/wqNR/+PUf8Mt+C/wDn88Vf+FRqP/x6vX6KAPIP+GW/Bf8Az+eKv/Co1H/49R/wy34L/wCfzxV/4VGo/wDx6vX6KAPIP+GW/Bf/AD+eKv8AwqNR/wDj1H/DLfgv/n88Vf8AhUaj/wDHq9fooA8g/wCGW/Bf/P54q/8ACo1H/wCPUf8ADLfgv/n88Vf+FRqP/wAer1+igDyD/hlvwX/z+eKv/Co1H/49R/wy34L/AOfzxV/4VGo//Hq9fooA8g/4Zb8F/wDP54q/8KjUf/j1H/DLfgv/AJ/PFX/hUaj/APHq9fooA8g/4Zb8F/8AP54q/wDCo1H/AOPUf8Mt+C/+fzxV/wCFRqP/AMer1+igDyD/AIZb8F/8/nir/wAKjUf/AI9R/wAMt+C/+fzxV/4VGo//AB6vX6KAPIP+GW/Bf/P54q/8KjUf/j1H/DLfgv8A5/PFX/hUaj/8er1+igDyD/hlvwX/AM/nir/wqNR/+PUf8Mt+C/8An88Vf+FRqP8A8er1+igDyD/hlvwX/wA/nir/AMKjUf8A49R/wy34L/5/PFX/AIVGo/8Ax6vX6KAPIP8AhlvwX/z+eKv/AAqNR/8Aj1effHv4C+HfBPwb8X67pGpeKLXU9PsGuLeZvE1++2RenytNtNfUFeU/tT/8m7/ED/sEy0Ael6eP+JdbZ+b90v3v92rdVNP/AOQda/8AXFP/AEGrdABRRRQAV5T+1l/ya18Y/wDsTNZ/9IZq9Wryn9rL/k1r4x/9iZrP/pDNQB+e/jj/AJIB+yP/ANjP4R/9JGr0L40/8nZ/s4/XxJ/6QR15744/5IB+yP8A9jP4R/8ASRq9C+NP/J2f7OP18Sf+kEdfR/Z/8BPMf/yQfGn/AJOz/Zx+viT/ANII6F/5SAf90y/9ytHxp/5Oz/Zx+viT/wBII6F/5SAf90y/9ytX9qX+L/20j7H/AG6J8Fv+Ttf2jf8AuW//AEgkpfgv/wAnZ/tG/Xw3/wCkElJ8Fv8Ak7X9o3/uW/8A0gkpfgv/AMnZ/tG/Xw3/AOkElNfZ/wAUv/bhS+1/h/8AkQ/ZB6fGz/spuuf+0aP2BP8Ak0vwL/2//wDpfc0fsg9PjZ/2U3XP/aNH7An/ACaX4F/7f/8A0vuaVP4o/wDb3/tpVX4Zni/7K/7K3wb8c/s0+HfGnjXw7DLfSQ3s2oapc6rdW0axw3U67m2zJGqrHGvzf7NdKPgX+xpnjUfB3/hay/8AyXS/AoH/AIdm6iP+pY8Q/wDo29rrPA3gb4MeB/2ZfBfjTxn4M8Kx2Ufh7S59Q1O58PQ3MrSTQwrufbG0jM0ki/N/tVilHlj7sfhLblzS945H/hRf7Gf/AEEvB3/hbS//ACXR/wAKL/Yz/wCgl4O/8LaX/wCS6P8Ahen7Gf8A0DfB3/hEy/8AyJR/wvT9jP8A6Bvg7/wiZf8A5Ep/uf7ovf8A7wf8KL/Yz/6CXg7/AMLaX/5Lo/4UX+xn/wBBLwd/4W0v/wAl0f8AC9P2M/8AoG+Dv/CJl/8AkSj/AIXp+xn/ANA3wd/4RMv/AMiUfuf7oe//AHg/4UX+xn/0EvB3/hbS/wDyXR/wov8AYz/6CXg7/wALaX/5Lo/4Xp+xn/0DfB3/AIRMv/yJR/wvT9jP/oG+Dv8AwiZf/kSj9z/dD3/7wf8ACi/2M/8AoJeDv/C2l/8Akuj/AIUX+xn/ANBLwd/4W0v/AMl0f8L0/Yz/AOgb4O/8ImX/AORKP+F6fsZ/9A3wd/4RMv8A8iUfuf7oe/8A3g/4UX+xn/0EvB3/AIW0v/yXR/wov9jP/oJeDv8Awtpf/kuj/hen7Gf/AEDfB3/hEy//ACJR/wAL0/Yz/wCgb4O/8ImX/wCRKP3P90Pf/vB/wov9jP8A6CXg7/wtpf8A5Lo/4UX+xn/0EvB3/hbS/wDyXR/wvT9jP/oG+Dv/AAiZf/kSj/hen7Gf/QN8Hf8AhEy//IlH7n+6Hv8A94P+FF/sZ/8AQS8Hf+FtL/8AJdH/AAov9jP/AKCXg7/wtpf/AJLo/wCF6fsZ/wDQN8Hf+ETL/wDIlH/C9P2M/wDoG+Dv/CJl/wDkSj9z/dD3/wC8H/Ci/wBjP/oJeDv/AAtpf/kuj/hRf7Gf/QS8Hf8AhbS//JdH/C9P2M/+gb4O/wDCJl/+RKP+F6fsZ/8AQN8Hf+ETL/8AIlH7n+6Hv/3g/wCFF/sZ/wDQS8Hf+FtL/wDJdH/Ci/2M/wDoJeDv/C2l/wDkuj/hen7Gf/QN8Hf+ETL/APIlH/C9P2M/+gb4O/8ACJl/+RKP3P8AdD3/AO8H/Ci/2M/+gl4O/wDC2l/+S6P+FF/sZ/8AQS8Hf+FtL/8AJdH/AAvT9jP/AKBvg7/wiZf/AJEo/wCF6fsZ/wDQN8Hf+ETL/wDIlH7n+6Hv/wB40/2X9X+BXwI/bdv5/DHivwt4d8G3Pw8kV76XxHHJatfNqUOY/PmmYeZ5cat5e7O1d22v0a8DfFfwT8Tze/8ACHeMdA8WCxEf2o6FqcN79n8zds8zy3bbu2Nt3ddrelfml/wvX9jP/oHeDv8AwiZP/kSrP7JX7XvwA+Cnxw+OepSeIrPwx4Q8QHQv7DWw0K6SGXyLaZbnbDDB+72ySfxKu7du+bmvLxFKMfejKJ3QlJ6cp+q9Fec/Bj48+B/2hvCt14j+H+uHX9Itrx9Pluvsc9vidY45GXbNGjfdljO7bj5q9GriNQooooAKKKKACiiigAryn9rL/k1r4x/9iZrP/pDNXq1eU/tZf8mtfGP/ALEzWf8A0hmoA/Pj45f8oz9N/wCxY8Pf+jLKvdPj/wDGPUfg14f8O3mleGh4r1LXddt9BtdNOoLZbpplkZf3jKy/ejVfm2/e+9Xhnxx/5Rn6b/2LHh7/ANGWVeg/tff80T/7KZon/tavouaUObl/lieZv+In/C5/jz/0bmP/AAurH/4mj/hc/wAef+jc/wDy+bD/AOJrov2l/ih4q+GPh/wf/wAIdb6Rca34h8T2fh+P+3I5mto/tCybWby2VvvKv975d3y1z/8AxlT/ANUf/wDKrWsubm5eaX/korX+yhv/AAuj48/9G4/+X1Yf/E0f8Lo+PP8A0bj/AOX1Yf8AxNO2/tV/9Ue/8qtG39qv/qj3/lVpe9/NL/yUn3P7o3/hdHx5/wCjcf8Ay+rD/wCJo/4XR8ef+jcf/L6sP/iadt/ar/6o9/5VaNv7Vf8A1R7/AMqtHvfzS/8AJQ9z+6N/4XR8ef8Ao3H/AMvqw/8AiaP+F0fHn/o3H/y+rD/4mnbf2q/+qPf+VWjb+1X/ANUe/wDKrR7380v/ACUPc/ujf+F0fHn/AKNx/wDL6sP/AImj/hdHx5/6Nx/8vqw/+Jp239qv/qj3/lVo2/tV/wDVHv8Ayq0e9/NL/wAlD3P7o3/hdHx5/wCjcf8Ay+rD/wCJo/4XR8ef+jcf/L6sP/iadt/ar/6o9/5VaNv7Vf8A1R7/AMqtHvfzS/8AJQ9z+6c98QvHfx48e+APE/hr/hn37AdZ0y604XZ8a2Enk+dC0e7btXdt3btu5a3NH/bO+LP7MfwD8OWvib9ngjRfCGjadpFzq3/Cb2n7zy0jtlk8mOGRl3Nt+X5tu7r3qT/jKv8A6o9/5Va474ufC/8AaU+Mvw91XwdrNz8K7bTtS8oTS6fJqaTjy5lmXazKy/ejX+GuWtR9pH3uY1p1OX+U/UsYpa/Ov4uftXftW/Bf4d6r4x1nTvg9dabpoi86Kwt9VeciSZYV2q0qr96Rf4q/RPPGa8epTlTlyyO+Moy+EWiiisygooooAKKKKACiiigAooooA/Pb9mf/AJGP9oH/ALKx4i/9Cjryr4F/8ozdS/7FjxF/6Mva9V/Zn/5GP9oH/srHiL/0KOvKvgX/AMozdS/7FjxF/wCjL2voaX8KP+GX/tp5k/il/iR6CP8AlH//AN0y/wDcVXnvx0/5Rl6b/wBix4d/9G2VehD/AJR//wDdMv8A3FV578dP+UZem/8AYseHf/RtlVVPh/7dFHf/ALePQ/2vv+aJ/wDZTdE/9rUftf8A3fgl/wBlN0T/ANrUftff80T/AOym6J/7Wo/a/wDu/BL/ALKbon/taqq/aCH2Dovjj8cdd+GPizwT4a8M+CP+E31zxT9u+z2n9qx6d5f2WOORvmkjZfuszfeX7v8AFurnv+FzfHkf826f+XzY/wDxNHxn4/ay/Z0+viP/ANII6Pij8Ufir/wv6D4c/Di38HY/4RhfEE0/iiO6/wCfprdlVoW/65/w/wB75qqUpc0veCMVZaCf8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWl7380v8AyUn3P7o3/hdHx5/6Nx/8vqw/+Jo/4XR8ef8Ao3H/AMvqw/8Aiadt/ar/AOqPf+VWjb+1X/1R7/yq0e9/NL/yUPc/ujf+F0fHn/o3H/y+rD/4mj/hdHx5/wCjcf8Ay+rD/wCJp239qv8A6o9/5VaNv7Vf/VHv/KrR7380v/JQ9z+6N/4XR8ef+jcf/L6sP/iaP+F0fHn/AKNx/wDL6sP/AImnbf2q/wDqj3/lVo2/tV/9Ue/8qtHvfzS/8lD3P7pxHxM1v47/ABG1T4f3n/ChfsH/AAinizT/ABTtPjGwk+1fZSzeR/D5e7d975tv91q+kPhv+2r481/46+Bfh342+Co8CHxd9v8Asmpf8JZb6jt+y2zTyfu4Yf8AZRfmZfv/AMW015N/xlUf+iPf+VWubvvAv7TF78V/AnxBkm+E41jwd9u/s+BTqf2aT7ZD5MvmLt3NtX7u1l+b+9XFiMP7X3ve5jppz5fdP08C0o4r49/Z2/aM+Mnib9pW++F/xQsvA6JH4Sk8SwXHhKG8Vi32yK3VHa4k/wBqT5dv935q+wugryJRlCVpHbe4tFFFSAUUUUAFFFFABRRRQAUUUUAFFFFAH5QfAv8A5Rl6l/2LHiL/ANG3tHx0/wCUZem/9ix4d/8ARtlR8C/+UZepf9ix4i/9G3tHx0/5Rl6b/wBix4d/9G2VfQ/8uf8At08z7f8A28eq/tr+I9V8I/sx+MdU0bU7zR9St/sXk3thO0M8e68hVtsi/Mvysy/8CrPP7IQx/wAls+MGf+xr/wDtNJ+31/yaZ46/7cP/AEvtqoftveH7HxZoPwm0PVYPtOmal8RNJsbqHew8yGRJ1Zdy/Mvys33a0qcvNKUiYfBAv/8ADII/6LZ8YP8Awq//ALTR/wAMgj/otnxg/wDCr/8AtNYHiz9kv9l/wF9mHiXS9H8O/ag32f8AtbxPdWvnbdu/b5lwu7buX/vpa5z/AIUd+xt/0EvB3/hayf8AyXUcv92P/gRXNf8A4Y9C/wCGQv8Aqtnxg/8ACr/+00f8Mhf9Vs+MH/hV/wD2mvOf+FGfsZf9BLwb/wCFtJ/8l0f8KM/Yy/6CXg3/AMLaT/5Lo5Y/yx/8CHr/AFE9A0b9jO28Naxq2qaT8Yvi3pep6t5X9oX1l4nWGe78tdsfnSLDuk2qzKu77tej/sJSeItJ+OX7QPg7V/HHivxtpnh//hHjp8vizV5L+aHz7a4mk2lvlXc237qrwq/3a+e/+FH/ALGrf8xLwd/4Wsn/AMl0n/Ci/wBjQ/8AMR8Hf+FtL/8AJdc1bDxqR93lj/28bQny/EfW/wC0B+z/AK94a8W3Pxg+ENqjeLQq/wDCQ+Fc+XbeJrdf/QbpV+7J/F91qs/C34o6D8XfCMGv6BNI8DM0NxZzr5dzZzL/AKyGaP8AhkVv4a8S/wCCdPxh+EXwk8A/FHw/d+P/AAl4Y0+P4iaq2k2uo+ILeNpLARWyQSRtJJukj2oVWTLbtvWvTvir8L2v79vjz+z/AHum+ItRu1Y63o2kXcc1h4rt42ZWMcke5Vuo2VlWRfvMpVq+UxmD9v70fiPocFjJUHyy+E9OorlPhf8AFDQvi54Ttte0GdjC7NDcW06+Xc2cy/6yGaP/AJZyK33lrq6+VlGUJcsj6yMoyjzRPFf2lP2krH4FaJBZabYS+JvH2rRt/YvhyzRpppdqtunkVfm8tdrf723av8TL4p8Of2V9C+O3woHxGuvHU+s/FXX5I9Xt/G2mzsP7LuYxiO3hj+XbHH/q2jba3y/w7V2+9/Cb9nnTfht4t8SeMdU1W58YeN9duJGm1/Uo1WWG13fu7WNV+WNVXbu27d23+FdqrgeN5fh5+yMfF3xNu9Su9HsNcVWm8NWjr9mvdQ+b95DD/DcSL8rMrKu1Szf3q9GMowXJQ+I8+pTlL95W+E6Dwh8TdT8A/DPRbj43X2jeFvEct9/ZTTLeKYb2TzNscy/3fMVfM2/wr8zbfur6zXyN8HvhJr/xj8cab8ZfjgqWt28u3wj4LuWxb6arfMskit964bbu2n5vl3Njaqx/XNc+IhCEtDpoSlOPvHkfxb+E2r3fiOy+I3w5vYvD/wAUNHj2w3Mn/Htqtv8AxWd4v8Ubfwt95W+avW/gb8cPDP7S/gvUbXUNIGmeItLk+yeIfCmqBXn0+4/3f4o2+9HIvDD0YHCkYryT4tfCfVrrxFZfEj4cXsOhfFHSI/Lhnl/49tXt/wCKzul/ijb+FvvK1d2CxsqUuSZ5uNwMa0faU/iPoxdE8ReDDnRJ31/SVP8AyCdRm/0mJf7sNw33v92Xd/10Wtjw94103xK01tbTSWup24DXGnXsZiuYfdo2/h/21yrfwsa4b9n79oPR/j74XuJUtp/D/irSJRaa/wCGb1v9K0y5/ut/ejbG5JB8rL/wJR6B4k8IaZ4qih+3wEzwNut7qFjHPA396ORfmWvqueM/j+8+U5HH4Sv478R3XhzRlbTrNdR1q7mW10+yaTy1mmbnlv7qqryN/sxtXNXd8nwy0PTfD+i2v9teKdQ3tFG/yG6m4868uGUfKu5tzN/tBV/hFcA3jHXtA8SjU2hk8aRhLqw0CON9t2wQ/vrmaFI9pj3RiPzl+bbt2o3m16X8MrHTpNPm1i31SPX9Yvn23+pBdp3L/wAsVT70KR5wsR5XJLfMzMemVL2EPf8Aej/6V/8As/1/d541PaS90v8AgnwSvhpbm8vbo6n4gvysl/qcqbWkP8KIv8Ea9FT+bEtXYH5qimmjt42kldY0XqzHaK4yb4raLJKINI+1eKJ8/wDMDga4i+9ht03+pUr/AHWkDVy2qVpXN/cprlO26dTQx98D6VxL3XjfW1AttP03w3BkfvtQla8nPPzDyo9qL7N5rf7tMg+Gpv4VPiTXtU8RybAHikl+y2rfLhh5MG1WVv7snmUezjHSUv1/+1/8mDml0iaOqfEbw3ol81jcapDJqQH/ACD7XdcXZ/7YxhpO/wDdrPl8XeJNUwujeFJI4m/5e9buFtY8Z4/dr5kmdvZlX3210eg+GtI8M2n2XR9MtNLts/6q0hWNT2/hrWOelHNTW0fvDlnLeRxTeD/EGrADVvFU8afxW+h262cZ9izNJJ+Kuv4VpaL4B0Dw9cG6stLh+3MNr39yWuLt/wDemkLSN/wJq6akxmk6kmrByRA8CjoKTOetYvjO7Fh4R1q63eX5NjPJux02xsalK7sW9EeZeBmW/svhOgJLTaVc6y27jOY41LfXddj5f9r/AGa3fibHHqXir4e6EXZGn1k6gwUcGO1hkl5/7aeT/kVF4Rs/K8WaJaldg0fwtDFs3Z2edIo/9tfb7v8AF/DauQdX+OmnRvao8Gi6DNOJyudkl1cKq/Q7bWT/AL6avQlJOrzNfCpf+3W/GRxxj+75f8J4v+1X8HLyLVX+IWgQNdYjWPWbKGPc7Kv3bhf91flb/ZX/AHq+frW6hv7dZoJFlib7rLX6WkBlNfPXxL/ZF0bxHfT6v4UvW8LarK3mSwpH5tpM3vH/AA/8B/75r4DNMnlXl7eh8Rx4rA+1l7SnufLlFd/qP7NnxX0h2SLRtL1tF+7JZagsW/8A7+bam0r9mL4p6zOEuLLStBhIy011eec4+ix7hXyv9lYzm5fZHlfVK/8AKeYX9/DYQ+ZK33m2qq/M0jf3Vr6t/ZY+C954MtLnxd4ih8jxDqsSxRWrD5rG367G/wBtjtZv91f9qtj4Tfsv6B8O9Sh1nUZpPEviSLDJf3S7Y7duf9VF91f97lvpXt2BX2GV5R9Ul7at8R6+DwfsvfqfEcN4kH/CP+O/D2tL8lte50a8x/tZkt3P+7IrR/8AbxV7xR4QfVZ49T0y5OleILZdtvegbkkXr5My/wAcbf3eq/eUq3NXfGmgjxP4X1PTBKLeW4i/cz/88Zl+aOT/AIC6q3/AaXwX4g/4SjwvpuptELee4i/fQf8APGZflkj/AOAurL/wGvruZ8inHpoelyq/LIoeFfFja00mmaja/wBleILZQ1zYM25Sv/PSNv8AlpG397t91trcVV8PY0f4heJtMwBFfpBq8PH8TL5My/h5Mbf9tK0/FfhS28SWkA817HUbZjJZ6hb/AOutpP7y/wB5em5W+Vv4hXnepeL7rQfF/hSTxQkWmatBLJYTXkZ22l5azL/rI2Y/L++jtt0Z+Zd38S/NWsIKpdU/uM6kuXl5jqfipJcarpcPhWwTzb3X1ltZGV1za2mNtxcYb720Oq7f70i1f+FMyzfDnw2qxLC9vYx2kkKdIpIl8t0/4CyMv4VW+H0Vxrk174tvhtl1NVjsIDG0bW9iuWjV1b7sjMzM3/AV/hqT4fD+ztR8V6OcKlnqslxCvrHcKtxu/wC/kky/8BqZ+7TdP+UcdJ8/8xD8UYxZaEvie3kWK/8ADwkvkdm2rJCq/wCkQt7NGrf7rKjfw0vwmP2zwRY6tIVN3rJfVLjy2yoklbd5f/AF2x/8A55pvxElfV73Q/DMUW9dTuvOu2z9y1g2ySf99N5Mef8Apr95W21Do88fgbxZeaPcusWi6p5mo6fJI21IJl+a4h9FX/lsv+9L/dqk1Kjyr4t/+3RW5avMYfj/AFmX4f6n4olgbyxrumNc2WX2/wDEwjVYdu7+HcrW3/ftq0NG1OTX7K38M+FZGt9F0uFbK6123VQnyLtENr/C0ny/M33Y/u/M33fOfjLrc3xOs/Dr6dpbXXhu11H+0luHZo5tRht4WlkaH+JU48tW+8zSKy/Ku5vcpta0rwv4SOpRLGmkW1r58a2kY2tHtyojVfX+ECuitDkpU+aPvS//AGTKnLmqS/lOQ1rQ7NJNO+H+j6bHHpUw+1au6NxDas7Hawbl2uGSSM99vmt1rZ+GaDU9J1XWpFB/tq/muFDchoV/cwn/AIFDFG3/AAL+L7zYlxDrPhf4c63quoGFPF+sMqt9nZjFDczFbe2iVupVN0a5/ibc38Veg6LpVvoOj2WmWg2W1nBHbwp/dRV2r0+lc1SXuW/r+9/7b9xrTj73MflP+1h+zdefs/8AjW4vrCF5/BGrTNJY3KR/LZyMdxtn/u9fl/vL/utXhpwOlfuL4i8NaX4v0S70fWbKHUtLu4zFPaXCbo5F9CK+Hfip/wAE2S93Nd/DbX0tIWO5NG1pWeKL/ZSYbmx7MrH/AGq/PcyySc5urhv/AAE/rDgrxUw1HDRwGeycZR+Gpvzf4v8AM+HKORXvF7+wr8crS4SNPCVnepn/AF0GsWyqP++mVq6/wR/wTl+JOv3at4m1XSvClkG+ZYG+23BHsq7V/wDHq+ejlONlLl9mfsOJ8QOGcLS9o8bGX+H3pHzX4Y8Nat438RWXh/w/ZSajrV6/lw28Y+7/ALTH+FV+8zV+uP7OPwMsfgJ8MrLw7DKt3qDk3Oo3qps+03B+83+6BtVf9lVpnwL/AGcPBvwD02SLw7ZtNqVyqrdatdkvcz49T/CP9ldq+1erO+N3zYxjt0r7vK8rjgY80viP5S4747qcU1I4fDx5cPHZfzf3pfoiaiiivePyQK/JX49/8EnfjF8V/jb468YWHizwc9hrus3eo2q6je3i3McEkrPHGyrbMuVVlX5WK/LX61UUAfir/wAOVvjd/wBDT4A/8GF9/wDIdfdn/BOz9kLxT+yR4O8Xaf4t1fTNSvdZv4biKPRp5ZYI4449u795HGdzMzZ+U8KvNfX1FABRRRQAUUUUAeQfHT/kbvg//wBjcn/pFd16/XkHx0/5G74P/wDY3J/6RXdev0AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABXM+PvG1l8PPCt7r+pQTz2Vp5fmx2iq0p3SLGu3cy/xMK6avO/jzf6VpPwo1y61jRzr2mR+QZbD7U1t5v76NV/eLyu1trf8AAaAE0H4u/wBvf2ljwX4v0/7HZyXv/Ew0ryvtG3/ljH83zSNn5Vo0H4u/29/aWPBfi/T/ALHZyXv/ABMNK8r7Rt/5Yx/N80jZ+Va9FooA860H4u/29/aWPBfi/T/sdnJe/wDEw0ryvtG3/ljH83zSNn5Vo0H4u/29/aWPBfi/T/sdnJe/8TDSvK+0bf8AljH83zSNn5Vr0WigDzTSfjTBqFpq11c+E/FWj2ul6fLqM0+p6b5KOsfLRo275pP9n/ZapPBXxy8L+O7600+ya9tNQvIzNb217ZyRNKm3cWVsbf8Ax6ug+If2L/hAfEv9p/aP7N/sy5+1fY9vn+V5bb/L3fLu2/dzTfAMenSfD/w4unpM2m/2Zb/ZftwXzfK8ldnmbfl3bfvbaANfSNf0zXoPO0zUbTUouvmWk6yr+a1pVw1l8IfCGk60mraZodtpWoJHLGJrAGHasi7Wwq/L/hWb4a+GeteELu4ex8bavqth9nkSGw1tluMSbfkbzfvDa3+zQB6XXlP7U/8Aybv8QP8AsEy1d8Nal8RtMkvV8U6bpOp2dtaSTRXGiPIs08ihdsflyfxN8391a8/+M/xGfxz8E/iFosvhrW9D1ZNFklMeo2u2I/MqjbJ91uW/8db+7QB79p//ACDrX/rin/oNW65fwZ448P8Ai+xhGj6zZalJFEvmRW06tInb5l+8v411FABRRRQAV5T+1l/ya18Y/wDsTNZ/9IZq9Wryn9rL/k1r4x/9iZrP/pDNQB+e/jj/AJIB+yP/ANjP4R/9JGr0L40/8nZ/s4/XxJ/6QR15744/5IB+yP8A9jP4R/8ASRq9C+NP/J2f7OP18Sf+kEdfR/Z/8BPMf/yQfGn/AJOz/Zx+viT/ANII6F/5SAf90y/9ytHxp/5Oz/Zx+viT/wBII6F/5SAf90y/9ytX9qX+L/20j7H/AG6J8Fv+Ttf2jf8AuW//AEgkpfgv/wAnZ/tG/Xw3/wCkElJ8Fv8Ak7X9o3/uW/8A0gkpfgv/AMnZ/tG/Xw3/AOkElNfZ/wAUv/bhS+1/h/8AkQ/ZB6fGz/spuuf+0aP2BP8Ak0vwL/2//wDpfc0fsg9PjZ/2U3XP/aNH7An/ACaX4F/7f/8A0vuaVP4o/wDb3/tpVX4ZnnnwL/5Rl6l/2LHiL/0be0fHT/lGXpv/AGLHh3/0bZUfAv8A5Rl6l/2LHiL/ANG3tHx0/wCUZem/9ix4d/8ARtlWX/Ln/t0r7f8A28fSvxR+LvhL4M6BBrnjHVf7G024ulskn+yzTbpmVmVdsas33Y2/75ry7/hvr4D/APQ9f+Ue/wD/AIzSftfD/kif/ZTdE/8Aa1dn8Yvj9pPwZ1nwxpd34d8R+JtS8Q/avsNl4asVupm+zrG0n7tpFb7sm75d33WrolUlzS94zhCHKcb/AMN9fAb/AKHn/wApF/8A/GaP+G+vgN/0PP8A5SL/AP8AjNH/AA18P+iJ/GH/AMJP/wC3Uf8ADXw/6In8Yf8Awk//ALdWftJfzf8Akv8A9sV7KP8AIH/DfXwG/wCh5/8AKRf/APxmj/hvr4Df9Dz/AOUi/wD/AIzR/wANfD/oifxh/wDCT/8At1H/AA18P+iJ/GH/AMJP/wC3Ue0l/N/5L/8AbB7KP8gf8N9fAb/oef8AykX/AP8AGaP+G+vgN/0PP/lIv/8A4zR/w18P+iJ/GH/wk/8A7dR/w18P+iJ/GH/wk/8A7dR7SX83/kv/ANsHso/yB/w318Bv+h5/8pF//wDGaP8Ahvr4Df8AQ8/+Ui//APjNH/DXw/6In8Yf/CT/APt1H/DXw/6In8Yf/CT/APt1HtJfzf8Akv8A9sHso/yB/wAN9fAb/oef/KRf/wDxmj/hvr4Df9Dz/wCUi/8A/jNH/DXw/wCiJ/GH/wAJP/7dR/w18P8Aoifxh/8ACT/+3Ue0l/N/5L/9sHso/wAgf8N9fAb/AKHn/wApF/8A/GaP+G+vgN/0PP8A5SL/AP8AjNH/AA18P+iJ/GH/AMJP/wC3Uf8ADXw/6In8Yf8Awk//ALdR7SX83/kv/wBsHso/yB/w318Bv+h5/wDKRf8A/wAZo/4b6+A3/Q8/+Ui//wDjNH/DXw/6In8Yf/CT/wDt1H/DXw/6In8Yf/CT/wDt1HtJfzf+S/8A2weyj/IH/DfXwG/6Hn/ykX//AMZo/wCG+vgN/wBDz/5SL/8A+M0f8NfD/oifxh/8JP8A+3Uf8NfD/oifxh/8JP8A+3Ue0l/N/wCS/wD2weyj/IH/AA318Bv+h5/8pF//APGaP+G+vgN/0PP/AJSL/wD+M0f8NfD/AKIn8Yf/AAk//t1H/DXw/wCiJ/GH/wAJP/7dR7SX83/kv/2weyj/ACB/w318Bv8Aoef/ACkX/wD8Zo/4b6+A3/Q8/wDlIv8A/wCM0f8ADXw/6In8Yf8Awk//ALdR/wANfD/oifxh/wDCT/8At1HtJfzf+S//AGweyj/IYf7Ff7cvwR+Emh/Fe38WeNv7Kk1z4harrmn/APEqvZhNZzLB5Un7uFtu7y2+VtrccrX6DfC/4o+GPjL4E03xh4O1Iav4c1LzPst4IJIPN8uRoW+SRVZcPGw+Zf4a+Ff+Gvv+qJ/GD/wlP/t1Zn7Jf7YVt+zF+zD4b8HeL/g98Whc+HYL6e/1C18MD7Ekb3U9xu8ySaPCqknzMyr91u1eLWo8nvRlzHoQnzfEfpdRXLfDzxtZ/ErwF4b8W6Zb3Fvpmv6bb6rax3YVZkimjWRFkCsy7trDdtY11NchqFFFFABRRRQAV5T+1l/ya18Y/wDsTNZ/9IZq9Wryn9rL/k1r4x/9iZrP/pDNQB+evx0/5Rlab/2K/h3/ANGWVeiftff80T/7Kbon/tevO/jp/wAoytN/7Ffw7/6Msq9E/a+/5on/ANlN0T/2vX0Uvhl/hieat/8AwIT9sDp8E/8Aspuh/wDtaqP7TFlq3iv45fBLwdZ+LfEfhTTde/tz7dJ4a1FrOaQQ28c0fzL8rfMv8St95qvftgdPgn/2U3Q//a1Hxp/5O0/Zy+viT/0gjrSp8Uv+3TKP2P8At4Ufsgf9Vs+MP/hWf/aaX/hkED/mtnxg/wDCrP8A8Zrj/ih8I/CXxm/bZh0TxhpX9s6bb/Dtb2OD7RNDtmXUmVW3Rsrfdkb/AL6rr/8AhgT4Df8AQi/+Vi//APj1L2fN8Mf/ACYvnt8Uxf8AhkEf9Fs+MP8A4Vn/ANpo/wCGQR/0Wz4w/wDhWf8A2mj/AIYF+A3/AEI3/lXv/wD49R/wwL8Bv+hG/wDKvf8A/wAeo9nL+X/yb/7UXtY/zh/wyCP+i2fGH/wrP/tNH/DII/6LZ8Yf/Cs/+00f8MC/Ab/oRv8Ayr3/AP8AHqP+GBfgN/0I3/lXv/8A49R7OX8v/k3/ANqHtY/zh/wyCP8Aotnxh/8ACs/+00f8Mgj/AKLZ8Yf/AArP/tNH/DAvwG/6Eb/yr3//AMeo/wCGBfgN/wBCN/5V7/8A+PUezl/L/wCTf/ah7WP84f8ADII/6LZ8Yf8AwrP/ALTR/wAMgj/otnxh/wDCs/8AtNH/AAwL8Bv+hG/8q9//APHqP+GBfgN/0I3/AJV7/wD+PUezl/L/AOTf/ah7WP8AOH/DII/6LZ8Yf/Cs/wDtNH/DII/6LZ8Yf/Cs/wDtNH/DAvwG/wChG/8AKvf/APx6j/hgX4Df9CN/5V7/AP8Aj1Hs5fy/+Tf/AGoe1j/OUNf/AGIdJ8V6PcaXrPxY+Kms6ZcY86y1DxGs8D4bcu6N4drfMqt/wGqXjXwb4q+C/wAQPgxqOn/Gj4qa8mr/ABE0TRr2w17xVNcWk1vLMzSK0aqu7d5W3a3BVm+WtsfsC/Acf8yL/wCVi/8A/j1B/YF+Ax6+Bf8AysX/AP8AHqyqYeUo/DEqNZRl8Z+jYoNfmT4H+A3gT4H/ALc37Oo8FaD/AGMNT/4SH7Zi7uLjzPL0xvL/ANc7bdvmN93+9X6ajk14lSnKlLlkejCXPHmQ6iiisigooooAKKKKACiiigD89v2Z/wDkY/2gf+yseIv/AEKOvKvgX/yjN1L/ALFjxF/6Mva9V/Zn/wCRj/aB/wCyseIv/Qo68q+Bf/KM3Uv+xY8Rf+jL2voaX8KP+GX/ALaeZP4pf4kegj/lH/8A90y/9xVee/HT/lGXpv8A2LHh3/0bZV6EP+Uf/wD3TL/3FV578dP+UZem/wDYseHf/RtlVVPh/wC3RR3/AO3j0P8Aa+/5on/2U3RP/a1H7X/3fgl/2U3RP/a1H7X3/NE/+ym6J/7Wo/a/+78Ev+ym6J/7Wqqv2gh9gPjT/wAnZ/s4/XxJ/wCkEdC/8pAP+6Zf+5Wj40/8nZ/s4/XxJ/6QR0L/AMpAP+6Zf+5Wn9qX+L/20n7H/bpR+KWsfEvxZ+03B8PvB3xC/wCEE02PweuvSP8A2Jbajvm+2NC3EnzL8rL/ABfwfd+ar4+DPx5wf+MjB/4Q1j/8VSf83/f90y/9ytcD8LPhVqvxw1/4q6nqnxW+JGi/2X461XSLax0LxGbe2jt42VlVUZXxt8xl+X5QqrWf2v8A7YvaJ3v/AApf49f9HGj/AMIWw/8AiqP+FL/Hr/o40f8AhC2H/wAVS/8ADIA/6LZ8Yf8AwrD/APGaP+GQB/0Wz4w/+FYf/jNX7OX8v/kxF49//JRP+FL/AB6/6ONH/hC2H/xVH/Cl/j1/0caP/CFsP/iqX/hkAf8ARbPjD/4Vh/8AjNH/AAyAP+i2fGH/AMKw/wDxmj2cv5f/ACYLx7/+Sif8KX+PX/Rxo/8ACFsP/iqP+FL/AB6/6ONH/hC2H/xVL/wyAP8Aotnxh/8ACsP/AMZo/wCGQB/0Wz4w/wDhWH/4zR7OX8v/AJMF49//ACUT/hS/x6/6ONH/AIQth/8AFUf8KX+PX/Rxo/8ACFsP/iqX/hkAf9Fs+MP/AIVh/wDjNH/DIA/6LZ8Yf/CsP/xmj2cv5f8AyYLx7/8Akpm6P+zp8ZdD+JLePbH9oPyPFh0r+w2v/wDhCrNv9C87zvL8tpPL/wBYu7dt3f7Ve3fsV/Ej4m+Ifi18avBPxF8cnx5/wif9ifYL3+x7XTsfareaaX93AvtGvzM33P4dxryT/hkH/qtnxg/8Kv8A+01Bo37Gdt4Z1jVtU0j4xfFvS9T1byv7QvbPxOsM935a7Y/OkWHdJtVmVd33a5a2FlV+GPvf4johWUfikfpFRXyN/wAE59Z13UvAfxS0/XvFev8AiyTQfiJqujWd/wCI9Rkvbv7PDFbLGrSP/wACbau1dzN8ozX1zXibHcFFFFABRRRQAUUUUAFFFFABRRRQB+UHwL/5Rl6l/wBix4i/9G3tHx0/5Rl6b/2LHh3/ANG2VHwL/wCUZepf9ix4i/8ARt7R8dP+UZem/wDYseHf/RtlX0P/AC5/7dPM+3/28eh/t9/8ml+Ov+3D/wBL7al/a/6/BT/spuif+1qT9vv/AJNL8df9uH/pfbUv7X/X4Kf9lN0T/wBrVpU+KX/boqXwwM/9oTw7pPiz9p39nrS9b0yz1nTbj/hIfOsb+3WaCTbZxspaNvlb5lVv+A12Pi34e/ALwGbX/hJvDXw38Pfat/2f+1tP0+187bt37fMVd23cv/fS1zvxo/5Oz/Zz+viT/wBII6pftCeHNJ8V/tOfs+aVremWetabcf8ACQmaxv7dZoJNtnGylo2+VvmVW/4DRL7Uv73/AMiJfYL3/GKg/wCiPf8AlKoI/ZUPb4O/+Uqs/wCKWrfswfBbxBb6J4x8MeD9G1O5tVvI4f8AhEVn3QszKrbo7Zl+9G3/AHzXFf8AC9P2M/8AoHeDv/CJk/8AkSp5ox+LlCz/ALx6Ln9lT/qj3/lKoz+yp/1R7/ylV51/wvP9jL/oHeDf/CJl/wDkSj/hef7GX/QO8G/+ETL/APIlHtI/zRHyv+8ei5/ZTPX/AIU7/wCUquu/4J1ftA/CzwP+xt8PdD8RfEjwh4f1m0Ooefp2qa7a21zDu1C5dd0ckisu5WVuR0NeGf8AC8/2M/8AoG+Dv/CJl/8AkSj/AIXn+xn/ANA3wb/4RMn/AMiVy1qca/2omsJOn9mR9Q/FP4YPd6lJ8ef2f7rTfEd3eKz67omlXkc1h4qhjLKzRSR7lW8jZWCuv3mUq3fd0fwx+JuhfFnwlba/4fnaS2kZo5radfLns5l/1kM0f/LORW+8tfOP7CP7dnwN+DH7KXgbwd4y8cf2P4k00X32qyGkX04j8y+uJk/eRwMrfJIrfK38Ve1/E34XXk8ln+0F8CVGp3Ot2MOoat4aRGhh8U2MkayRzRqyq0d4sbblZl3N91vRvlMZg41480fiPpMHjJUJcsvhPT818qfFX4W2Xgvx54q+PPxg1j/hKtC8LRrJ4Y8PW0O2Cy3MqruVvlaZpGVVb7u7a38KrH9BfDT4laF8WfCdv4g8P3LTWjs0c0E6+XPazL/rIZo/+Wcit95an+IngPRvil4J1nwp4gt/tOk6rbtb3C/LuX+JZF3fdZWVWVv4WVa+epTlRn7x9LUjGrH3T511Hx/p/wAZdM0vQv2gfg8PBOia3/yBdXv9SivLcTSL8sbTR7WtZmX7u7buZf4W2rWl+x38Wn1TwL4pttZ8TprXhfQPETaDoPinVphFJqcO5fJWSRv9ZJukWNWX725a5vxn+zx8XPiFq9p8LPEHjiTVfg4kEN1qGrSafb2+oXMUczNDYhlZvMkXy42aby4/u7vm+61T4lGy+OO/9nP4RaZp9n4O0by4PEniI2yz2mlRo277Pb7v9ZdMy/e+8rbvm3bmXu5aUo8n9RPP5qkZc39SPqPwj8R/DPjy91208P6xb6vPol39h1H7LuZbe427vL3fdb738O75ty/eVq6brXx74X8b6X/wT18EzeDvGqPe+HjPeXXhzWdJsGMt+flka3uv4VuN0m1W3bWjj+by9q7vqPwJr2o+KfBmjaxq2iTeGtRvrWO5uNJuZPMls2Zd3ls3y/d/3V/3Vrgq0uT34fAd9Opze7L4jg/iv8KNZk8SWXxI+G93DoXxO0iPyo5Zf+PTWbf+Kzul/iVv4W+8rVsP+2HonxI+GX2Owi/sLx1cXX9kax4X1SdYZ9Jk487zWb/lmy/Ksy/e8xWVWZWQeiV4p8b/AII6pr2tWfxE+Heof8I78UNHTbDdxu0cWrW/8Vnc7fvK38Lfw16+V4+NCrFYn3onk5jl8sRTlKh8R7b8NLZPDFkzaToepeJNcuIo4ZdQktvsFpDGq7Y4Y/tG1lt48bdsayN/E25m517z4deI/EGsrrM+oWPhXUiNrS6FEZp3X+FZJpNqzKvo8P8AjXDfAL4/av8AFnwvcXVvAuq6vpMv2XXfDd75dlrOlXH/ADzZf9TMrc7ZP3KsvPXco9h0b4haNrN2untPJpusHppuoxtb3De6q3+sX/aTcvvX1lSrNylUp+95/F/X/gJ8jGnH+HI8+h8M2nha7aXx9pb+IIgWI8RXEkl5aqvfzLeRm+y/8AVo/wDaWvYdOura8s4pbKSKWzdd0UkDK0ZX/ZK1c6muGu/AD6Tdyah4Uu/7AunbfLaBPMsbhv8AbhzhWPeSPa397d0rCVRVv4krfl/9qbRp8nwndDFLXC2XxA+xXMOm+J7Q+H9QdvLimeTfZ3Tf9Mpv/ZZNrf7Jruc8ZrKUXDctSUthaKKKgoKKKKAGVxfxhG/4W+KoM/NdadNaIP8AalXy1/8AHmFdpXF/FX954QFsMH7XqWn2jD/ZkvYVb/x1mNaULe1jfuRU+CQnhiNH+IfjC4VVUQxWGnDaMALHHJNt/wDJg/nVHwC39rfEf4hautwJrZbq10iHj7v2eDfIB7eZcSD/AHg1aHw7Anu/GN9/z967L/5Chht//aNZXwNaG68ByazDC0Mmt6jfanJlixbzLiTy/wAoxGOP7tdUrqM5/wCGP9f+AnMtJRX+KX9f+BHpdFFFcJ2BRRRQAUUUUANAwtcR4a/4p/x14h0Vvktr/Gs2ef8Aa/d3CD/dkVZP+3iu4zXD/Ec/2RHpPidfl/sS633Jx960kHlzf8BXcsv/AGxrWn7z5O5E/wCY7baMDmvIvjt4fn+JWmy+CLBN88ludQupyit9nVd32dfm+75kisu5fm2xyV6R4h1228OaNfaldFzb2kLTuI13OwH8Kr3Zuir3NY3gDQb/AEnTLm+1jy/7d1Ob7VepFK0kUTcKsMbN/Cqqq/725v4qqhL2LVZbx2JqR9p+7MDwH46u00/RotfcS2+qRRy6ZrG3bHdeYu5Ypv8AnnP7fdb+Hn5V2Cf7K+LAYEeXrOkbf+2lrN/MrdN/37qn4M0myu9K8R+FNQgjubOy1CaPyJV3K0Ex+0R8f3V83YP+udeefFzWNc+D2nabqk0smt6dpt239n3sz7p03wyR/Z7n/nou5kZZPvfu/m+b5m64UY1q7p0vil+P8pzyqSp0+aR3+j6laf294p8Xahdi2sLQ/wBlQPK37qOOBv3zf7zTM6/xf6pejblrL13w/qfxk0uWW5tjomlxHz9It7qLdJPMv+ruLmNl+SP+HyfvMrNu67Vn+G/gO6XR9Gn8QKwi02NTYaW779jfe+0XH8LXDN83Hyxn7vPzV6nkYrCVRUp+5uXGDqR948t8Ia5H438awXn2ZrY6PpHkXFqwx9nupptskP1T7H/3zIvZqyfCNlcav4lfwbKWXRfBd0skiHa6Xe799YR/3l8hfLb/AHkjrLTX73wfr+v+KrWEXlt4p1R9LtLQ/KqXsP8AotuzMP8AlnI0cm5v4flNdPpXh1Phr4m0CYTy3K6ssmn6nd3B3NLcMzTQyM3+800a/wDXVF/hrrnGNPmUesfd/wAX2v8A278zKPvfEb/ihf7V8aeF9IBzHBLNrFxt/uxL5cak5+X95Mrf7XlN/tV23UVxHhZv7V8aeKNXZcxQSw6Pbhv7sS+ZIwGPl/eTMp/veUv+zXcDnNebU92yOuGuotFFFZmgUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAeQfHT/kbvg//wBjcn/pFd16/XkHx0/5G74P/wDY3J/6RXdev0AFFFFABRRRQAUUUUAFFFFABRRRQAUUVE08attaRVb0zQBLRWXc+JdKs5mhn1OyglX7yS3Cqw/DNc5qHjXw6t3IreINJVt33Xvo/wD4qgDtd6+orzn49ato+mfCrW7nWNKXXtPi8nzdO+1NbmU+dHt/eL8y7W2t/wABrLuvH/hdLqXd4m0Vfm/6CUP/AMVXyT4/8UaPea5rkcWpWep7ryTbBBfK3mfvP9lqAP0L+2wf89o/++qlVw65ByK/LfVPFel/bLnbrVn97/n8X/4qv0B+HPibR/8AhXfhrdrGn/8AINtv+XyP/nmv+1QB6TRUUTq8asrBlI4Yd6loA5j4h/Yv+EB8S/2n9o/s3+zLn7V9j2+f5Xltv8vd8u7b93NHw8+xf8ID4a/sz7R/Zv8AZlt9l+2bfP8AK8tdnmbfl3bfvYo+If2L/hAfEv8Aaf2j+zf7MuftX2Pb5/leW2/y93y7tv3c0fDz7F/wgPhr+zPtH9m/2ZbfZftm3z/K8tdnmbfl3bfvYoA6eiiigAryn9qb5f2ePiBj/oEyV6tXlP7U/wDybv8AED/sEy0AdLH8N/DF9plwr6JaRNqNmtreSW0fkSTx/L8rPHtb+GsnQ/hJ/wAIfY6nD4c8S6zZNc2/k263s/2yCzf+GSOOT5fwrvNP/wCQda/9cU/9Bq3QB5vo8XxG8P6bqjand6T4rnjhUWKwx/ZJJZd3zeZ/Cq7fmo0n4p6hFo+r6h4n8Ian4bXThHuUFbrzmZtu2Ly/vc7f++q9IooA4zwx8VvCfjPT7q/0jW4Lm1tNn2iSTdD5W5mVd3mBdu4qRXM/tXOsv7K/xhZWDK3gzWSrDv8A6DNXea34S0XxFp13Zalp1veWl0yyTxOnEjL8ylvyrxj49/C/w94C/Zm+LZ0e2uLCzTw/fahcWcN1IYrhYbeWRoW3btscnzKyr/C1AHxJ43/5IB+yP/2M/hH/ANJWr0P40/8AJ2n7OX18Sf8ApBHXBeMCj/BH9nG+vXeSO78S+HbnSdPs41jW0kazka2gZm+9CrbVZvvba6T4s6zqVt+0p8Bb/WdMaCeyXxE6W1lIsz3StZwr+7X/AIFu/wB1Wr3ub3fe/unmuP8A7cbPxoGf2tP2cvr4k/8ASCOjH/GwD/umX/uVrN+J3iG01z9pz4B6pD5kNlp//CRG7luY/LW33WcKqW3fd+aWNf8AgS1btbqG8/b58y3ljni/4Vl9+Nty/wDIVrXmjKXu/wA3/tpnyy5f+3Sb4Lf8na/tG/8Act/+kElL8F/+Ts/2jfr4b/8ASCSk+C3/ACdr+0b/ANy3/wCkElL8F/8Ak7P9o36+G/8A0gkrRfZ/xS/9uFL7X+H/AORD9kHp8bP+ym65/wC0aP2BP+TS/Av/AG//APpfc0fsg9PjZ/2U3XP/AGjR+wJ/yaX4F/7f/wD0vuaVP4o/9vf+2lVfhmeefAv/AJRl6l/2LHiL/wBG3tHx0/5Rl6b/ANix4d/9G2VHwL/5Rl6l/wBix4i/9G3tHx0/5Rl6b/2LHh3/ANG2VZf8uf8At0r7f/bx6F+2B0+Cf/ZTdD/9rUfGn/k7T9nL6+JP/SCOj9sDp8E/+ym6H/7Wo+NP/J2n7OX18Sf+kEdaVPil/wBukL4F/wBvGl8Ufj74t8J/F+D4feDvht/wnepSaCuvSP8A27Dp3lw/aGhb/WR7W+ZV/i/i+78tZ3/C5/jz/wBG5/8Al9WP/wATS5/4z+9/+FZ/+5Wl+KPxR+Kn/C/oPhz8Obfwcf8AimF8QTT+J47r/n6a3ZVaFv8Arn/D/e+alzS+LmKtH+Ub/wALo+PP/RuP/l9WH/xNH/C6Pjz/ANG4/wDl9WH/AMTTtv7Vf/VHv/KrRt/ar/6o9/5Var3v5pf+Sk+5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lo+PP8A0bj/AOX1Yf8AxNH/AAuj48/9G4/+X1Yf/E07b+1X/wBUe/8AKrRt/ar/AOqPf+VWj3v5pf8Akoe5/dG/8Lp+PX/RuP8A5fVj/wDE1g/EHx98d/HvgDxP4a/4Z9NgdZ0y604XZ8a2Enk+dC0e7btXdt3btu5a39v7Vnr8Hf8Ayq0bf2rPX4O/+VWp97+9/wCSh7v90j0j9tD4s/sxfALw3a+Jv2eSNF8IaNp2kXOrDxtafvPLSO2WTyY4ZGXc235fm27uvev0d7etflt8XPhf+0l8Zvh5qvg7Wbj4WW2m6l5Qml0+TUknHlzLMu1mVl+9Gv8ADXbfFv8Aau/at+DHw71TxjrOnfB6603TRF50Nhb6q858yZYV2hpVU/NIv8VeRWw8ou9OPundCrzfEforRRRXEdAUUUUAFeU/tZf8mtfGP/sTNZ/9IZq9Wryn9rL/AJNa+Mf/AGJms/8ApDNQB+evx0/5Rlab/wBiv4d/9GWVeiftff8ANE/+ym6J/wC1687+On/KMrTf+xX8O/8Aoyyr0T9r7/mif/ZTdE/9r19FL4Zf4Ynmrf8A8CE/bA6fBP8A7Kbof/taj40/8nafs5fXxJ/6QR0ftgdPgn/2U3Q//a1Hxp/5O0/Zy+viT/0gjq6nxS/7dM18C/7eFH/KQL/umX/uVrjvih8I/Cfxl/bdh0PxhpX9sabb/Dpb2OD7RNDtmXUmVW3Rsrfdkb/vqux6f8FAf+6Zf+5Wk/5yA/8AdMv/AHK0SjzfF/MPb/wE47xD+zX+yP4T1abS9aXw5o2pW20TWN/4vmhmj3LuXdG13uX5WVv+BVm/8KL/AGMv+gl4O/8AC2l/+S66bwL8PvCvj79rH9oEeJfDOkeImtP+Ee+znVtPhu/J32DbtvmK23dtX/vlazPEXxU/ZD8Ka9qei6rovg631LTbqWyuof8AhDGfypo2ZGUstptb5lP3az5afxcsSnzL+YzP+FF/sZ/9BLwd/wCFtL/8l0f8KL/Yz/6CXg7/AMLaX/5Lo/4Xp+xn/wBA3wd/4RMv/wAiUf8AC9P2M/8AoG+Dv/CJl/8AkSj9z/dD3/7wf8KL/Yz/AOgl4O/8LaX/AOS6P+FF/sZ/9BLwd/4W0v8A8l0f8L0/Yz/6Bvg7/wAImX/5Eo/4Xp+xn/0DfB3/AIRMv/yJR+5/uh7/APeD/hRf7Gf/AEEvB3/hbS//ACXR/wAKL/Yz/wCgl4O/8LaX/wCS6P8Ahen7Gf8A0DfB3/hEy/8AyJR/wvT9jP8A6Bvg7/wiZf8A5Eo/c/3Q9/8AvB/wov8AYz/6CXg7/wALaX/5Lo/4UX+xn/0EvB3/AIW0v/yXR/wvT9jP/oG+Dv8AwiZf/kSj/hen7Gf/AEDfB3/hEy//ACJR+5/uh7/94P8AhRf7Gf8A0EvB3/hbS/8AyXR/wov9jP8A6CXg7/wtpf8A5Lo/4Xp+xn/0DfB3/hEy/wDyJR/wvT9jP/oG+Dv/AAiZf/kSj9z/AHQ9/wDvB/woz9jP/oI+Dv8AwtpP/kuqfgax/Z9+Cf7ZPwL1rwN4i8MaRo4Gu/23qK+JVubaD/iXstv5skkzLHuaR1X7u5j/ABcVc/4Xn+xn/wBA3wd/4RMv/wAiUf8AC8/2Mj/zDfB3/hEyf/IlZVI05R5VymkZOMub3j9IvBXxt+HfxJ1WTS/CHjvwz4p1KKFrmS00XWbe8mjiVlVpGWN2YLuZV3f7S+td7jivyT+CX7UP7PPwp/bKuvGGlarpvhnwPP4CbSmn0zQbmCJtRbUI5Nvkx2+7d5KL8+3b8u3dX6J/BD9qH4ZftIHWv+Fc+Jf+EiGjeT9vxYXVr5XneZ5f+ujj3bvKk+7n7teNOPLLlO1PmR61RRRUFBRRRQAUUUUAfA9n+zB+0l8P/G3xKufBN/8ACufQfFPizUvEkK6/NqbXca3MmVVvJjVV+VF+X5vm3fM1eM/Az/lGbqX/AGLHiH/0Ze1+roFfmn45/YQ+JfwL/Zg8a6fpv7QH2jwloPh3VrptBHgy2T7VD5M000P2hp2kXzNzjd823f8ALXbRxHs/iMpw5tjQH/KP/wD7pl/7iq89+On/ACjL03/sWPDv/o2yr0If8o//APumX/uKrz346f8AKMvTf+xY8O/+jbKvWqfD/wBunBHf/t49D/a+/wCaJ/8AZTdE/wDa1H7X/wB34Jf9lN0T/wBrUftff80T/wCym6J/7Wo/a/8Au/BL/spuif8Ataqq/aCH2A+NP/J2f7OP18Sf+kEdC/8AKQD/ALpl/wC5Wj40/wDJ2f7OP18Sf+kEdC/8pAP+6Zf+5Wn9qX+L/wBtJ+x/26K3/J//AP3TL/3K0n7IPT42f9lN1z/2jSt/yf8A/wDdMv8A3K0n7IPT42f9lN1z/wBo0o/xP/Ai5/AePfsi/sjfCb4ofs8+FPEvibwp/aWt332vz7v+0rqHf5d3NGuFjlVfuqq/dr2H/hgP4DZ48C/+Vi//APj1H7Aef+GSvAo/6/8A/wBL7mvEP2Zv2aPgl4k/Zk8N+OviDpFnHdTm5+26vqGs3FnCu28lhi3bZljXpGtZpR5Y+7H4QlKXNL3j27/hgP4Df9CL/wCVi/8A/j1H/DAfwG/6EX/ysX//AMerzz/hRn7Gf/QS8Hf+FtJ/8l0f8KM/Yz/6CXg7/wALaT/5LquWP8sf6/7dFeX80j0P/hgP4Df9CL/5WL//AOPUf8MB/Ab/AKEX/wArF/8A/Hq88/4UZ+xn/wBBLwd/4W0n/wAl0f8ACjP2M/8AoJeDv/C2k/8Akujlj/LH+v8At0Ly/mkeh/8ADAfwG/6EX/ysX/8A8eo/4YD+A3/Qi/8AlYv/AP49Xnn/AAoz9jP/AKCXg7/wtpP/AJLo/wCFGfsZ/wDQS8Hf+FtJ/wDJdHLH+WP9f9uheX80j0P/AIYD+A3/AEIv/lYv/wD49R/wwH8Bv+hF/wDKxf8A/wAerzz/AIUZ+xn/ANBLwd/4W0n/AMl0f8KM/Yz/AOgl4O/8LaT/AOS6OWP8sf6/7dC8v5pHof8AwwF8Bcf8iL/5WL//AOPV7h/wS+/5MX+GmOn/ABM//Tnd18mH4G/sZn/mJeDv/C2k/wDkuub+KfwZ/ZL0z4Y+L7zw7qHhVvENvo95NpotfF8k8rXKwsYdsf2ltzbtvy7W3Vx4ij7T4eWJrTqcuj5j9hKK+Wv2af2mPhBof7OXwr0vVPit4H07UbPwppVtdWl34js4poJFs4leN0aTcrKy7SrV9S15B3hRRRQAUUUUAFFFFABRRRQB8JftC/8ABOv9nvwR8BviT4j0T4ffYdY0jw1qWoWVz/bWoSeVNFaySRtta4ZW2sq8MMV8f/FX9p34a+If2G7L4f6b4k+0+MI9B0axfTTZXKlZoJLdpl8xo/LO3y2/i/h+Wv2sH1r5m/4KL+E9b8b/ALG3xC0Pw7o2oeINYuzp/kadpdrJcXMu3ULZ22xxqzNtVWbjstbU6sqfMo/aIlBSPn79voZ/ZM8df9uH/pfbUn7X/wDzRP8A7Kbon/tavLf2wfjpqPi/9nPxbpFx8Hvin4XguPsm7VvEfhdrOxt9t5C372bzDt3bdq8feZVr1L9r/n/hSf8A2U3RP/a1e5KpGrzSj/dOCEZR5FIPjR/ydn+zl9fEn/pBHSfGn/k7X9nL/uZP/SCOl+NH/J2f7OX18Sf+kEdJ8af+Ttf2cv8AuZP/AEgjrV/a/wAUf/bTKP2f8P8A8kO/5v8Asf8AVM//AHK0tz+2NpJ17xBpmlfDX4keJBomqXOj3V7oegrdW32iFtrKsizf7rfNtbay0mP+M/s5/wCaZ/8AuVpP2QeP+F2f9lN1v/2jUx5ubliW+Xluw/4a/H/RE/jD/wCEmf8A49R/w1+P+iJ/GH/wkz/8eqhY/tL/ABL8V6/4ss/B/wAEj4n0zw9rt3oMmpf8JXb2vmTW7bW/dyR7l+Vlb+L733qvf8Lo+PX/AEbkP/C6sP8A4mn7SX83/kpHL/c/8mF/4a/H/RE/jD/4SZ/+PUf8Nfj/AKIn8Yf/AAkz/wDHqT/hdHx6/wCjch/4XVh/8TR/wuj49f8ARuQ/8Lqw/wDiaXtJfzf+SjtHt/5Mc18VP2lLrxx8MPF/huw+DPxZjv8AWNHvLCB7nwuyRJJNC0asxWRm27m/u133wx/4KD6B8CvgJ4K0Txb8Ivizpy+GdA0/Sr/U5fDUcdmskMMcJZZJLhflZ1AXdt+8vFZB+M/x4/6Nz/8AL5sf/ia8++PN/wDHj44fCbXvBX/CiP7G/tPyf9O/4S+xuPL8u4jm/wBX8u7d5e3738VcuIp+1973v/ATppvl0PrX47/AjX/Bvi69+Lvwks1n1uVVbxP4QU+XD4jhX/lpH/zzvFH3W/5afdb/AGrvw2+JGhfFfwnaeIfDty01lMzRyRSr5c9rMv8ArIZo/wDlnIrfeWvKPH3/AAUK+LPww8JX3ibxN+zX/Zuh2Xl/aLv/AITy1m8vzJFjXKx27N95lXpXpPx1+Bev+CvF978XPhJYi41qVd3ibwgh2w+IYV/5ax/887xV+63/AC0+63fd8pjcDKr732j6LA432Xuy+E7gGvmn4eeH5v2H/hP8Q7nxJNp2o+BdMvDqelXFhGy6pdGZtrR3W75Wk3NBGsm75l+9t+Va9v8Aht8SNC+K/hOz8Q+Hrn7RZTbo5IpV2z2sy/6yGaP/AJZyK33lq3418HaR8Q/CWqeGtetBf6PqcLW9zCW2ZX/eX7rfxbq+ZhPk9yZ9PKPtf3sT5l8Ffs6z/tFx3PxJ+Pdn9ok1SxZdD8I+dJFBoFnIu7c33W+0Mu1mb+H/AHtqx9Z8Pf2qPgn4TTSfh6nxZj8Rarp6LZLqeqNJJ9pb+HdeLGsMnVV3bv8AgTfNXH/tP+D9S8H/AAl+F/wl07xFrsnhzX/EFvoOr+ItSuvNvVs5JGbymmVVX5txRdy/Msar83zVU8dadafspfCfxL4I13QJPFnwf1C0uF0W4t7ZZLmxu5NzLZ3e1fmWSRv3Nzt3K21W/havQ5Y1Y+9/27E4OaVOXu/9vSPsWivH/gZqzfDP4M/C7w18QdXtdL8VX1lDY29pfzqk8syruWFdzfMyrsVv9r/eWvYK8ycOSR6UZc0TyT4p/CzWl8T2nxK+GtzDo3xM0uPy/wB/8tprdr/FZ3a/xK38Mn3lb/x32L4PfF7wn+074Ina40kW2rabP9l13wvq8atc6Vdrn5XVuqnllkXhl9DuVYCMV5N8T/hdrUXim0+Jnw1uYdG+JmmQ+Uyz/Laa7aZ+azul/iX+7J95W2/8B9TBY6VKXJM8jHYKNaPtKfxH0cfBer+HwX8M67MsA5/s3WS13b+mFkLedH/30yj+7SH4hvoRC+KtIudBI+9fxE3VgffzlXMa+8qx1ifAT49aF8ffCs99Ywz6Pr2mzfY9c8O3/wAt5pV2PvRSL/EvdZANrL/wJV9UI9DX1LmpfGrnynJy7GaDp3ibSMf6LqmnXUf+zNDKv/oLLXKnwnrHhA7/AAtdC609euhanIzRL/1xm+Z4/wDdbcv91VqzefDjTTcSX+kyXHhzU3O97nSW8pZG55kh5jk/4ErGoW1Lxh4bBGoabB4ns15+1aT+4uQP9q3kba31WT/gNaU9F7kr+Uv6/wDtiJf3omh4e8dafrd+dNmjm0rW0Xc+magvlzf7RT+GRf8AajZl966h8noM1xf9o+EvibbPp8zQ3s8J81rK4Rre8tm7N5bbZI2/2vlqu1t4n8F827y+LtGXrDMyrqMA/wBlvlWZf9ltrf7TVMoKT5X7suzCM5f4j0Ck4rB8N+LdM8VW8jafdCSWBvLuLeRWSeBv7skbfMjf71bp4HNZOLi7M0UubYUdK4r4lt5n/CL22CftGuWvH/XPdN/7SrtR0rz74k6j9h8ReD5SjSLZ3N5qLBf+mdjOmP8AyNWlL4tCKnwmZpOuv4b+Bmt+IEdEdU1TVYWb7uZLieaPP/fS12HgHQ5fDfgbw5pEwAm0/Tre0cA5+aONVPP/AAGvM/E2mwwfAXwZ4aupJGfU5NH0ppIsbmJkhaRvm6fIkjfWva4+greva111kzKluv8ACTUUUVxnUFFFFABRRRQA1aq3+nwatY3Fpcos1tcRtDLG3RkZdrLVvqK53xrr0nhzQJrq1hW51B2W3s7ZiQs1xI22NW/2dzDcf4VDN/DTim3ZEtpL3jzzwhBqXi6+0zRdTkf7B4QlEeoPKm/+0LyNv9Gbd22xrHcN/tTR/wB1q9kb5gK8s8I+Hh8MvFFjp7Xdxexa9bMJ7u5Ys0uoR7pGYt3aSNpP91bZa6bxd4sl0Mw6bptm2seILkZt7BH2KqbgrTSN/wAs41zy3f7q7m4rqrr2k7U9v6uYUfdp+8c54t11PA/xBhu0trm/l17Tmto7KzG6We5t5N0aqvT7k0hZ2wqrH81cT4x8B618QNUaDXLlZ9cs9Nn1FbK0fda2kkiyRWkIU/e+bzWaRtu5oF+Xavy9T4n8IyeGdEi8X6pcrqfiXTLmG8udRKeWsdurbZo4Vz8kawyTfL/E3zNuroPhWv8Aaml6j4mZ2Z9fujdwmTqtquI7df8Av2qt/vSN977zdUakqMPb0/8ADzf1/dM5U/aS9nIxvDN9P4O0XT9XsTLqHge+t47oWy7pJ9KWRQ26P+KSD5vu/ej/AIdy/Knc6v4os9O8KXuvJNHPYwWb3qypIPLeNY9+7d/dx/FWP8KyLPw9caQ3D6Rf3Ngq/wB2JZGaAf8Afloq83+NOkzeErKHSPD8lwtp4qu/ss+kW8PmeR/y0nuLdfuq21W/d/dZm3f3t2Kpwr1/Zv8ApD5pU6PMW/BHga18faPaRam63ml6VYf2fbSx/IZL5l/0u8jZW+X52aNf7rRyba3NT1GbXPhf4jtNanjt9c0CNmurn7qrNAomgulH91tscn/fS/w12ngifS5/DOn/ANjTx3GnpHsSRP4ivDbh2bdnd75rzj46wJo1xo+ped5MOp3UOl6uu3IksVbzndv+uaxy/N/dmk6/KKuE5Vq/s3/N7v8AX9e8KUY06PMdn8Hz5vw50O4bi5u42u7pcfcuJZGkmX/gMjyL+Fdpt4NcT4QB0Dxf4h0BuLa4k/tmyB/uzMfOX/gMys3/AG2Wu5wK4aus5S7nTD4LC0UUVmaBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB5B8dP8Akbvg/wD9jcn/AKRXdev15B8dP+Ru+D//AGNyf+kV3Xr9ABRRRQAUUUUAFFFFABRRUMtxHF9+RV/3qAJqqy39rbvtkuYYm/uvIq1zniL4peEPCN8tnrXiTTNLvHj81Ybu6WNmX+9XjXxE/aT+FNj4kaK5+InhuCXyVbbLqEatQB7df/EHwtpVy9ve+JdJtLlfvRT30aMv/AWavK/FXxp+Htvr93HL468MxSq3zK2rW6svy/71fn/+0F8YfAOt/FjV7yw8XaLfWskcO2eC8Vlb92tfCPxd1Gw1b4ja3dWlxBc2ssyvHPG25W+VaAP0A/aR+InhHVPjBrVxZ+JtFvIGjh2zwX0bK37tf4t1fJPjnXNJuPFmoSRahZyxNJ8rLMrK3y188XO3zm2/dqzBo17cRrJFayyRt91lWgC94itpJ9dvpIYmkiaZmVo13Ka6/wCBeg67ffFLRINJv5fD99J53l6k1mtwsX7mTd+7b5W3L8v/AAKu58I/s+/E3XPDGm6hp3gHxBfWFxbrLDcw6fI0ci/3lavR/BHwM+JXh7XLG8uvDuteFYoVbdql3prNFb/u2X5t3y/N93/gVAHxw6NFIyupVl+8rV90eA/Euh2/gHQY5dW0+KWPTYVZWuI1ZW8ta+Zbr4I+NfEXjHxBpunaL59/pskbXcf2uFfL85d0XzNJtbcv92tXSfgz4u1K/wBT0a20ZZNV0mOFbyD7VD+58xd0fzbtrbl/u0Af0NeBtVsW8E+Hyt5b7f7Pt/8Alov/ADzWunr5N8KfEjw34c+HfhP+0dSWDdp8cC/uZG+aGNY5F+Vf4Wr2q8+O/gbR9A0fWb3XRHp2rCX7HN9jnbzfJbbJ8qx7l2t/eoA6H4h/Yv8AhAfEv9p/aP7N/sy5+1fY9vn+V5bb/L3fLu2/dzR8PPsX/CA+Gv7M+0f2b/Zlt9l+2bfP8ry12eZt+Xdt+9iuK8efGXwDN8OmuNQ1a5bSPEVneW9s1pbSedcKuY5Fj3L8rbm2r5m1cn0qv8PfjFo0eleG9Ds/Dni20smit7KzvNR0vEckW1Y4pGkViu1vl+agD2SivOT8cvCaeKR4fnvLm01Vrz7Asc9lNtkm8zy1VW27fmPfOKvR/GTwbLr7aGuv239qrd/Yfsjblbzt23Z93+98tAHcV5T+1P8A8m7/ABA/7BMtdhH8QvDEuq/2WniPSW1Lzmt/sX22Pz/MVtuzy927durgv2oNbsJ/gF8QbWK9tZLldKmVoVlVnX/gNAHrGn/8g61/64p/6DVuqmn/APIOtf8Arin/AKDVugAooooAK8p/ay/5Na+Mf/Ymaz/6QzV6tXlP7WX/ACa18Y/+xM1n/wBIZqAPz38cf8kA/ZH/AOxn8I/+kjV6F8af+Ts/2cfr4k/9II6898cf8kA/ZH/7Gfwj/wCkjV6F8af+Ts/2cfr4k/8ASCOvo/s/+AnmP/5IT42RLd/tT/s9Wkq+ZaTr4hWaBvmjk22EbfMv8XzVhXXgjTZf26X0+3jk02Bvhx9o3WLeWyyf2nt3bv8AP8Nb3xoOP2tP2cvr4k/9II6P+cgH/dMv/crRKMZSlzfzf+2kRlKMf+3TG+Fdhq6/tKfHqw0nUo47izTw9HJcX0fmNcr9kmZfMb+8u5V3f7C0z4Sanq+lftNfHySTSf7TvW/4R1btbGTasbfY5drR7vmZdu3/AMerd+C/H7WX7Rn18Of+kElN+Cw/4y1/aN/7lv8A9IJKUafw8v8ANL/24py+L+v5Sp+zJrum+FI/io2pX1vF/aPxD1W6j8ss3ktJHbyeTJ8vyyLu2sv8LK1a/wCxDpV34e/Zi8GaZqdtJZ6hbm+WS3nXbKn+nXDY2/7rK3/AqpfshxLLH8bI5FV1b4m63uVl/wCuNVP2NtIg8ffsreBLrXpLjUr6P7fsup7iRpVP2yZV+bd/dVf++Vp0+bmj/X8o52984n4F/wDKMvUv+xY8Rf8Ao29o+On/ACjL03/sWPDv/o2yq58L9TufGH7BQ8Q30qWtrHoeuyahp1hCsMV5Csl3uj+X/Vsyq3zf3m3VJ8YoLPU/2DtFtbi6GieEbnw/ozyahLG1xNZx+ZbNAvlr/rP+Wat/wJqy5v3f/bo+v/bx2X7X/T4J/wDZTdD/APa1Hxp/5O0/Zy+viT/0gjpn7TbXGuW/wjkltv7N+weNdK1q6+1vsWOGHzN0at/FJ833V+aj4pzDWP2nv2d9UtFkn02KPXZJbhY28uFZLFVjLN/DuZW27v7taylHml/26ZxjLl/8CJP+cgf/AHTL/wBytH/OQP8A7pl/7laP+cgf/dMv/crR/wA5A/8AumX/ALlar/5If/yJ9A0UUV3HIFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFfPv7fv/JpXjr/tw/8AS+2r6Cr59/b9/wCTSvHX/bh/6X21Y1v4MjSn/Eifo7RRRXyR7gUUUUAFeU/tZf8AJrXxj/7EzWf/AEhmr1avKf2sv+TWvjH/ANiZrP8A6QzUAfnr8dP+UZWm/wDYr+Hf/RllXon7X3/NE/8Aspuif+1687+On/KMrTf+xX8O/wDoyyr0T9r7/mif/ZTdE/8Aa9fRS+GX+GJ5q3/8CE/bA6fBP/spuh/+1qPjT/ydp+zl9fEn/pBHR+2B0+Cf/ZTdD/8Aa1Hxp/5O0/Zy+viT/wBII6up8Uv+3TNfAv8At4X/AJyB/wDdMv8A3K0f85A/+6Zf+5Wj/nIH/wB0y/8AcrR/zkD/AO6Zf+5Wj/5If/yInwW/5O0/aN+vhv8A9IJKP2P+nxs/7Kbrn/tGj4Lf8naftG/Xw3/6QSUfsf8AT42f9lN1z/2jRT+KP/bwn8D/AO3R9z+2NpJ17xBpmlfDX4keJP7E1S50e6vdD0Fbq2+0QttZVkWb/db5trbWWm/8Nfj/AKIn8Yf/AAk//t1H7IX/ADWz/spmt/8AtGsLwD+1J8V/if4SsvE3hn4Bf2lod7v+z3X/AAmdrCZfLkaNvlkjVvvKy/do9pLl96X/AJKVyQ/kN3/hr8f9ET+MP/hJn/49R/w1+P8Aoifxh/8ACTP/AMepP+F0fHr/AKNyH/hdWH/xNH/C6Pj1/wBG5D/wurD/AOJo9pL+b/yUm0e3/kwv/DX4/wCiJ/GH/wAJM/8Ax6j/AIa/H/RE/jD/AOEmf/j1J/wuj49f9G5D/wALqw/+Jo/4XR8ev+jch/4XVh/8TR7SX83/AJKFo9v/ACYX/hr8f9ET+MP/AISZ/wDj1H/DX4/6In8Yf/CTP/x6k/4XR8ev+jch/wCF1Yf/ABNH/C6Pj1/0bkP/AAurD/4mj2kv5v8AyULR7f8Akwv/AA1+P+iJ/GH/AMJM/wDx6j/hr8f9ET+MP/hJn/49Sf8AC6Pj1/0bkP8AwurD/wCJo/4XR8ev+jch/wCF1Yf/ABNHtJfzf+ShaPb/AMmF/wCGvx/0RP4w/wDhJn/49R/w1+P+iJ/GH/wkz/8AHqT/AIXR8ev+jch/4XVh/wDE0f8AC6Pj1/0bkP8AwurD/wCJo9pL+b/yULR7f+TDh+1+P+iJ/GH/AMJM/wDx6ua+AX7TNx8LPjj8Z/GWr/Bf4uXGmeMv7G+wR2XhZmni+yW8kMnnK0iqu5pF27Wb/gPAro/+Fz/Hr/o3L/y+rD/4mj/hdHx6/wCjcv8Ay+rD/wCJrOpH28eWUpf+AlQl7N80V/5MfX/7Ov7Rmh/tLeENa17w9o2u6BHpGrz6Hd2HiO0S3u47iKON5FZEkk2485V+Y7tyt8teuHFfml+zl8TPjx+z9pvjm0/4Z4/t7/hJ/Ft/4p3HxtYW32X7QIl8j7r7tvl/f+Xdu+7X2r+y98bz+0f8C/DfxFGjf8I+da+1Y0/7V9q8rybqWD/WeXHu3eVu+6PvY7V4U6cofEekpKR61RRRWZQUUUUAFYPi7wrpnjjwvq/hrWbT7bousWk1hfWwkaPzoJkaORdysrLuVm+ZWDc1vUUAfCX7Qn/BOr9nrwR8BviV4j0X4ffYtZ0jwzqWoWV1/bWoSeTPFaySRtta4ZW2sq8MMV80fGf4qeCtV/4J56f4csvF2gXfiFfD2gwtpMGqQyXayRyWnmL5Ktu3Ltbcu35drV+t+saTY+INKvNM1O0g1DTbyF7e5s7qJZYbiNl2vHIjDayspKlW4Ir4n/4KKfs+fC3wP+xt8Q9b8O/Dfwj4f1m0/s/7PqOl6Fa21xFu1C2Rtskcasu5WZeD0Nb063s4yX8xEoc3Kch+18M/8KT/AOymaJ/7Wo/a/PHwTH/VTdE/9rV5d8a/2nPhp8Z9f+D2ieDvEh1nUrb4iaNeyQGyuINsKvIjNuljVfvSL/31XqX7X/T4J+v/AAs3RP8A2tXtylGXNynnQjKPJzCfGn/k7P8AZx+viT/0gjoX/lIB/wB0y/8AcrR8af8Ak7P9nH6+JP8A0gjoX/lIB/3TL/3K1p9qX+L/ANtJ+x/26K3/ACf/AP8AdMv/AHK0n7IPT42f9lN1z/2jSt/yf/8A90y/9ytJ+yD0+Nn/AGU3XP8A2jSj/E/8CLn8AfsBf8mk+Bf+3/8A9L7mvnuT/lEuf8/8x2voT9gL/k0nwL/2/wD/AKX3NfPcn/KJc/5/5jtZy/gR/wAMv/bQ+3/28fS3xR8K/s//AAa8Pwa34x8FeD9H0ye5Wyjn/wCEYjnzMysyrtjhZvuxt/3zXlY+OP7Gn/QN8Hf+EVJ/8iV6F+190+Cf/ZTdE/8Aa1ehfGj406V8D9A0vU9V0nV9ZOp6nDo9rZaHAtxcyXEiyMqrGzLu3eWy/L825lq5fFL4RQ+E+eP+F5/sZf8AQN8G/wDhEyf/ACJR/wALz/Yy/wCgb4N/8ImT/wCRK9G/4a9/6on8YP8AwlP/ALdR/wANe/8AVE/jB/4Sn/26p5o/zR/8BK1/qR5z/wALz/Yy/wCgb4N/8ImT/wCRKP8Ahef7GX/QN8G/+ETJ/wDIlejf8Ne/9UT+MH/hKf8A26j/AIa9/wCqJ/GD/wAJT/7dRzR/mj/4CGv9SPOf+F5/sZf9A3wb/wCETJ/8iUf8Lz/Yy/6Bvg3/AMImT/5Er0b/AIa9/wCqJ/GD/wAJT/7dR/w17/1RP4wf+Ep/9uo5o/zR/wDAQ1/qR5z/AMLz/Yy/6Bvg3/wiZP8A5Eo/4Xn+xl/0DfBv/hEyf/Ilejf8Ne/9UT+MH/hKf/bqP+Gvf+qJ/GD/AMJT/wC3Uc0f5o/+Ahr/AFI+bv2nfir+zP4k+B/iPTfh9ZeG4vGE32c2Laf4Wks5l23MbSbZmt125jWT+Lvtr9EvCv8AwUV/Z78b+LNG8OaJ8Qft2s6veQafZW39i6hH5s8sixxrue3VV3My8swFfPw/a+B/5on8YP8Awkz/APHq86+MHx51Hx/q/wAL7rTfg58VoY/C3jbS/El8lx4VdWkt7Us0ix7ZG3SfN8qttX/aWuHEU4y97m/8lN6c3H3eU/WCivkbSP8Agoz4W1Dxd4U0G/8Ahb8U/DLeI9YtdDsr7X/D0Vpa/abiTy41aRrj/gXy7m2q2F4r65ry9jrCiiigAooooAKKKKACiiigD57/AG8Phh4l+Mv7KXjnwd4O07+2PEupfYRaWXnxQ+Z5d9byv88jKq/JGzfMw6V8W/tB6v8AF+91b4NR/ED4Oj4e6N/wsfRmh1M+J7PU/Mn3SbYRHD8y7l8xt33f3f8AtV+q1fOf7afwJ8Z/HbwX4KtfAl5oVnr/AIb8W2fiWM+I5Jo7R1t451Ct5MbM3zSR/L8vy7vmranUlT2IlBSPm/408ftafs5fXxJ/6QR0nxp/5O0/Zy/7mT/0gjrm/GvhH4weFf2tP2f/APhbD+CJfOOv/wBnHwa1633bFfO877Qv+1Ht2/7W7+Guk+NP/J2n7OX18Sf+kEde9GpGpGU4/wA0f/bTzZRlGXLL+X/5Ic3/ACf/AP8AdMv/AHK0n7IPT42f9lN1z/2jSt/yf/8A90y/9ytJ+yD0+Nn/AGU3XP8A2jTj/E/8CKn8AfsgdPjZ/wBlN1z/ANo15/8AAWw+O/xw+Eug+NT8d/7G/tPzv9BPhCxuPL8u4kh5k+Xdu8vd93+KvQP2QOnxs/7Kbrn/ALRrif2fdRutJ/4Jvz31ldTWN7a+Hdfmt7m2kaOWKRZrxlZWX5lZW/iqY/DH/t4rrI7b/hTHx6/6ONH/AIQtj/8AFUn/AApf49f9HG/+WLYf/FVzPws/ZqufHHwx8IeJL/4z/FlL/WNHs7+dLbxS6RLJNCsjKoaNm27m/vV0/wDwyAP+i2fGH/wrD/8AGarllL7P/kxle3X/AMlE/wCFL/Hr/o40f+ELYf8AxVH/AApf49f9HGj/AMIWw/8AiqX/AIZAH/RbPjD/AOFYf/jNH/DIA/6LZ8Yf/CsP/wAZo9nL+X/yYLx7/wDkpg+P/wBlv4sfFDwjfeGfE3x9GpaFfbPtFp/whlrCZfLkWRfmjkVvvKrferoPEXjv9oX4SeOfhNJrXx0/4TDRvEPjnSPDt9pv/CI6fZb4biT95+8VWb7sbL8u1vmyG4pP+GQf+q2fGD/wq/8A7TVHVP2I9N1uTT5NQ+LfxXvpNNvI7+ya58TLK1rcR/6uaPdD8si/wsvzLWFTD+0j8Pvf4jaFVR+0e/fHj4Fa74F8W33xf+ElkbnWZgG8UeDYzth8Qwr/AMtof7t4q/dYf6zp9772n8NfiVoPxZ8JWniLw5efabG43IyyLtnt5F+9DJH/AMs5F/iWvn3wL4d8TfCT9sb4F6InxZ+I/i3RvEf9u/b9O8VeI5L22k+z6ezx/u/lX70m75t3zKte3/Hf4G694B8W33xe+ElkbrVpgH8UeDI2KxeIYl/5bQ/3bxRnaw/1nT733vkswy/nl/ePo8Bj/Ze7L4Ta8eeA9C+J3hPUPDXiXTo9U0a/j8ua2l/8dZW/hZfvKy/MrV5L4o8bW37HHwov73xV4s1fxzb/AGr7NoFlexxteyMy/u7UzKu6T7rN5knzbf73yrXqfw3+I+g/FnwjaeJPDl59r0+4+VlddstvIv3oZF/hkX+Ja3r/AEmx1ZYFvrO3vEt5luYftMKyeXIv3ZF3fdZf71fMRnye5M+plHm9+J8g/D/9lPxX8bdXHxU+MHiLX/DXji5ZZNG0/wAOXn2V9AttrbY/mVsM275l/wC+tzMy13/7GvxK8S+O9B8c6Vr2tJ4uh8LeIrjRbDxNHHt/tKFTuVmZflZl3L93+Fl+995rv7QPh/4j/FvxPY/Dbw8s/hbwJeWn2nxB4uidfOmh3Mv2G3X+GRtp3M38Lf8AAZPENb+Nd5ofiG1+Ffwcmt/hh8NfDeoLoWp/EK50v+0ILe+bd+5Xd+7+aT5Wkk+8z7ty/L5noe9Xh/XunB7tCXN/Uj7rHFGO9eB/Dvx3478A/GK0+F/xG1uy8YHV9Ok1PQ/EtrZLYyzNDtWa3mt13Lu+bcrK33f975ffM4rzJw5D0qdTmPJvib8MdbtPFlt8Tfhlcw6R8StOh8uSOf5bTXbX+Kzu1/8AQZPvK23/AID7l8B/jzoPx68KTX9hDPo+uabN9j1vw7fjbeaVdj70Ui916lZB8rL77lXGryb4m/DHXLLxXbfE34Zzw6T8StOhEM0M/wAtpr9rn5rO6X/0GT7ytt/4D6mDxns/3dT4TyMdgfafvKfxH2TRXlXwE+PGg/HzwjLqGnQz6RrOnTfZNb8PX/yXmlXa/ehlX+73Vvusv/AlX1WvpT5cwde8JaR4siiGqWEN00XzQyMu2WFv70cg+ZG/2lasL/hG/E3hsbtE1r+2rYD/AJB2vNlvol0o3L9ZFkrucjFGRitFUaVuhnKEZO55Tr2raDqt1by+J7O98E67H+7t9WcrHjn7sd0u6Nlb/nnJ97+5WvF4h1zwmANcg/t3ScZXWtLi/eKvB3TW6/8AocW7/dWu4mhjuIikiLJG64KMMqRXGn4ZWumSNP4bvbnwvOeTBaHfZN7Nbt+7H/bPY3+1W0KsJx5Zf1/7dH/yYiUHH3onVaRrFjr2mxXunXcV7aSrujngfcrD6ivK/jpM0lwLaInzD4d1fy2A3bJZGtII/wD0c3/fJpuqaNrfh2/m1RtOksL6U75tZ8LI08E7f3rvT2+Zv96PzJP9pa4LxH8SYdd8TQx6lJZqM6fZzXtm7NabW1KOSRZNy7rdmjhk3Rybfu/eb71dmFoN1VUh70TmrVfc5ZHrvjNGl+IPw70mG2D20E13qch258tYbYwr/wCPXS/jtr0NBgnNeb6WE1f466vex3KPFpWgWtqYlG795cTSSN83+7DF/vbl/u16O54rz6/u8qfb/gnXT+0zJ8T+KtK8H6Jc6vrN7FYadbJulmmbCqP6n2r5B+IP7U/ivxxPLb+EyfC2gltsd66K97cL/e+b5Y/p97/aqh+0d8S5/id4/udEhm3eFtAm8nyl+7c3i/6xm/vKv3V/+yrzyvz/ADbOKiqewwx4mMxsub2VIq6jZXGuuz6xqmqavM/+skvbySTd/wCPVNpb6j4ckEuia7qujzDobW8kVD/wH+KpKK+T+sVubm5jx/aS+LmPavhl+1prPhy7t9N8fqmo6U7bV1+1j2yQ/wDXaNfvL/tL/wCPV9Zadqdpq+nQXtlcR3VncRiSKaFtyurfdYNX5xuiyxMrrvVvlZW/ir2n9kv4mXPhzxK3gDUbhpdKvla40hpP+WMi/NJDu/usvzL/APZV9hlGb1KtT6vidz3cHjJTl7KqfXykHPHNef6OkXjbxq+vhorrR9GMllpjj599xt23E6Pn7vWHH96OT+9Wl491a5SxttH06WSHV9Zk+yW88Y+a3XG6abPQeXHuZd33m2r/ABViS3V9cQxeF/B7Lb29p/o9/rbIrC167lj/AIZLjI+b+FWbc3Pyn72lCSjzd/y/r3T1akve5Sr8YNXvdUspdJ8KWw1HxTpbx6mrBv3diU+ZfM/2pF3Ksf3mVm+6vzV03w60mxsPD9tfWt3Nq0upxR3U2rXHMt4WVdrt6Lt+6q/Kq1reH/D1n4c01bSzVipZpJJZW3STSN96SRv4mb+9WB8PSNFu9e8MP8v9mXXn2q462c+6SL8Fbzox/wBcqpzTpuEPsi5eWpzSG/FeYXHhpNAQlbjxHcLpUYT72xwzTN/wGFZW/D7y/eW18LLmS58DaXDPg3VirafcYGP3lu7Qt+bRk/jVPTruPxP8SdRuUbz7Tw/F/Zy91F1KFkmx7rH5A3f9NHX5fm3TeGiujePfE+ldIbvydXgz/tr5Mij6NCrf9tKqX8P2f/b39fgL7fN/26M0yePQfiL4ogmdYbe9tLbVQzHALKrQzH/gKxQf99Vx/h6N/GfxY0jxLdRTRqLK4urGGV/9TbrthhbarbWMnmXUm7+60a1P8WXs9W+JHhDw+Zgr36TWupKoz/oMm2Ty2/2ZpLXyf91pK6fwbBFc+MPFt7DCIobaS10iEou1THBH5mF/2VkuJV/4C3tW+tOn7T7Uo/8A2ph8U+T+9/8AbC6z4UutI1efxB4aCxXsnzXulSNtg1Af3vRJvSTv91uMFcrRdYsviP46eRYZDaaLp7Q3Fpdx7SlxcNho5E/vLHD/ALu2b+Ld8vpnQDJ6V5J4b8Kz62t7400i6+weINQu5pYpJctDdWit5cEUyjqpjjRgy/MrOfvfNvwpT5oylPfa5tOPK/dKDTSeCtR0+G5kd5fDE6os8jZM+j3LeXlj38llj3f9eyt/FXtjHAPtXkPiu7tfHmj3FymnyJ4k0WOSLUNClwZ5rWVdtxCv/PSORV3Rsvys0S+jLWn4P+Jlhb/CF/EWqaiktro1q/22+H/LRYV/13/bSMLKPaRadeN6XtZdPiCi5Sn7Nfa+Eq/HP9oPwv8As/8Ahr+0dfufOv5gy2Gkwc3F4687VHYcjLH5R+lfnR8U/wBsv4pfFS7kWPWX8I6MxxHpuiP5cm3/AGrgfvGb6bV/2a8++K3xS1n40ePtR8V61IxadjHZWpxttLYH93GuO/8AeP8AEzNXJ9+elflmY5zVrVPZ0JcsT+2eCvDTAZbho4rNaftK8ukvhj8hbuW41GdZru9vLudTlZZrqRmX/gW6uv8ABXxn+IHw4uFn8N+MdWswrbvs087XNu31jk3LXHZ9KMk189DE1aUuaMj9lxOTZbjaXscRQjKPblP0X/Zr/bw0/wCJd/D4V8epB4f8STMEtL6Jttpft/dGf9XJ/stw3b+7X2CyA5yM5/WvwmdfMXacg/eBU/MD61+n37Df7QNx8YPhzNpOv3P2jxR4eZLe7nb711E2TFMf9r5WVvVkLfxV99k+ayxb9jW+I/kTxI4ApcPr+08t/gS+KP8AL/8Aan1BRRRX1R+ChRRX4c/Ej9tz9qD9onxr4g0bwFL4ittMs55I10jwJpsrzwR+Y21mmhVpi21fvblX5TtVaAP3Gor+ejRf2zv2jvgp4weC+8feLotX0+XZdaP4slmutrcbo5Ybrcy5X/dZc/Ltr9rf2S/2grT9pr4F+H/HEVuljfzlrXUrKNsi3u422yKD/db5ZF/2ZF/izQB7VRRRQAUUUUAeQfHT/kbvg/8A9jcn/pFd16/XkHx0/wCRu+D/AP2Nyf8ApFd16/QAUUUUAFFFFABRRRQAVzPiXWtP0+6ijvL63tnaPcqzyqm6umr5S/a48UaPofjPQ49S1K2sZZNPZlWeRV3L5jUAeB/tyeMPD6/F7T/M1zTV/wCJTD966j/56Sf7VfnP8eNUsdR+IMk9reW9zF9lhXzYJFZa6n9u7WNP1z4wafcaddw3kC6PCrSwNuXd5klfN9AFrUWVrxyvzLVWrUWm3VxH5kUEkif3lWtS18DeIbyBZoNFvpYm+6y27bWoAyorG4nTdHBJIn95Ur2/wP8AC/xlq3hLT7yx8J65eWckbNHPBps0kbfM33WVa0Ph18BfiVrXhGzvNP8AAviC7tZGk2zwWMjK3zV+vf7IfhLXvDn7N/gjTdU0q90+/traRJra5hZZYz50n3loAtfszaHqmm/s+/D61vNPvLa5h0eFZIJ4WVo2/ustdtLuWZlbcrbq9X0dGi0u2WRSjLHyrV5NrmvafFrV8r31urLcMrK0n+1QB+EP7Yv/ACdJ8T/+w5cf+hV45XsP7YEsdx+0/wDE2SJxJG2uXG11/i+avHqAP3m+HP8AyT3wr/2CbT/0StfXlt/x7xf7q18h/Dn/AJJ74V/7BNp/6JWvry2/494v91aAJqKKKACs2XRNNlu0upLC1a5U7lmaJd6t/vVpUUAczJ8PfDEuq/2o/hzSW1LzluPtv2KPz/MVt2/zNu7duryH9p74UeErX4N+Ptfi0K1TWRY3F0bxd2/zG+83/jzV9CV5T+1P/wAm7/ED/sEy0AWdJ+BXg221m18RQ6bLDq/nLevMt5MyyTbt25lZtv3qlh+DdhD4pXXYNf8AEdvc/bDeyWseosttK+7cytHj7rdNvpXe6f8A8g61/wCuKf8AoNW6APPIfhnqtv4p/tVPHPiCS3a6+0Pps8iPAV3bvLUbflX+Gm2vgfxpbeJUvW+IUk+kfavOk0qTSIcGPdny1k+8o2/LXotFAHndtofxFt/E6zS+JdLu9B+1b2tmsNs/k7vu7l/i2/xV5V+1JN8UIv2f/i+t5B4Wn8Pt4W1n5reS4W5jt/sc3975WbbX0zXlP7WX/JrXxj/7EzWf/SGagD89r5Zb74MfsyQay8em6fb674Xk068hDzfa5lgxHCy/8s9y7m3fw16F8R2n1P8Aab+CtzfRrpV1p02tpaWkr+a2pRyWqrIysv3fLXazK397/Zrz7xv/AMm//sj/APYz+Ef/AElavQvjT/ydp+zl9fEn/pBHX0PL7vxfynlt/wDtw34jmTXf2nPgtfui6aukTa3EtvfHy573zrVY91sv/LRY/vN/dX5qbbytL+2p/b3kvFZ/8IV/YfksB5/nf2j5nmbOvl7f+WlSfGkf8ZZ/s5fXxJ/6QR0mP+NgP/dMv/crVcsub/t4Pd5f+3RPhSRpn7Tnxq1S7HkWXiGTRotLl+99oa3tWjm+VfmXa397bu/hpfhGV079qL46ajcssFjrMmgxabOzfLdNDatHIsf97a3y0nwZjRv2s/2jSV37T4cZf/ACSm/B+GOf9q/9oGOWNZI7M+HXt1Zdyws1i7Nt/u7mprm93/FL/wBuCXL73+Em/ZUU6JP8XbbUAbK4vfiNq91ax3H7priFvJ2yRqw+ZW2ttZaT9gs+X+yl4FjfCyhbw7W+9ta+uGVv/Hqj/ZWtl1m7+Ll5qO6+urD4i6va2cly3mNbwx+Xtjj3fdVdzfKvy/NVX9iLRrXxH+zt4F8R6lG93rf+lYu3kbf+7upo1/75VVX/AIDSp814/wDb3/to58vLI4n4F8f8Ey9S/wCxY8Rf+jL2j46c/wDBMvTf+xY8O/8Aoyyqt8MNPTxT/wAE/NV8TX08zapJ4Y11X8uTy4m8v7XGv7tfl+6q1W+NPh6Oz/4J522sm/1GZZvDmiSfYHuP9EVpGtPux7flVWbcq/7K1hzS9n8P2R+7zf8Abx6t+1+efgn/ANlN0T/2tR8asS/tMfAjSWLf2bq0eux3turbVuFjso5I93+63zL/AHdzf3qqftI6YPD958KptQurnXYrr4h6RBbQXEm37HI0kjLMu37zKqsu1v71TfEOJ9M/ac+CcOrzNrV/dSa2+mXO1YUsVW0VplZV/wBZuXavzfd21tU96UuaP8oR6BfxNcftf23hewMOlQWvgBbyG/tof9MVVvvL8nzP4o/4trfxKrUapcSWv7YEEOnW327xVH4AXzLi5k2wTWf9obWXav3ZPM+b+7t3UWqPF+2jFHO4n8Rf8IR5kk23bbLp39o/6tV+953mfxfd206yEn/DaCyXQU+If+EI8poYP+PYad/aP+s3fe8zzPl2/wB1qX/yQz1/VPGM+hzKt5ouoSweWrSXNpH5iqzVel8Y6Rb332O41CG2udqt5Vy3l7d3+9VS11vxE2qLb3Ph2NbNpNrXcV8vyr/e2/eqm+oNrmoLZ6p4RkaJm8v7TKsciqv8LV0+0l/UTn5TrUfeu5fu0V51dW2m694kbdpviTRdQmZY/tcCtHG235d275l2/L/dpsviy/vPEn2fSdY8pZpNsdje6e21dv8AdkX727a1Htg9mej0V59/wtqGXxE2n2tj9ugaTbDPBN8zf9s2X/erai+Jfh2XUJbFr7yp1k8v5lbazf733auNanL7RHs5HT0VzWvfEPQ/D1v5kt5Hcvu2rBaMsjVa8L+MtN8X28slhI2+Pb5kUq7WWq9pT5uXmJ5ZcvMbdFFFaEhRRRQAUUUUAFFFFABRRRQAUUUUAFfPv7fv/JpXjr/tw/8AS+2r6Cr59/b9/wCTSvHX/bh/6X21Y1v4MjSn/Eifo7RRRXyR7gUUUUAFeU/tZf8AJrXxj/7EzWf/AEhmr1avKf2sv+TWvjH/ANiZrP8A6QzUAfnr8dP+UZWm/wDYr+Hf/RllXon7X3/NE/8Aspuif+1687+On/KMrTf+xX8O/wDoyyr0T9r7/mif/ZTdE/8Aa9fRS+GX+GJ5q3/8CE/bA6fBP/spuh/+1qPjT/ydp+zl9fEn/pBHR+2B0+Cf/ZTdD/8Aa1Hxp/5O0/Zy+viT/wBII6up8Uv+3TNfAv8At4X/AJyB/wDdMv8A3K0f85A/+6Zf+5Wj/nIH/wB0y/8AcrR/zkD/AO6Zf+5Wj/5If/yInwW/5O0/aN+vhv8A9IJKP2P+nxs/7Kbrn/tGj4Lf8naftG/Xw3/6QSUfsf8AT42f9lN1z/2jRT+KP/bwn8D/AO3Rf2QP+a2f9lN1v/2jXlvwh+KGrfBf/gm3pXjHRLezudS03zjDFqCM8DeZrLQtuVWVvuyN/FXqP7IH/Nbf+ym63/7Rr57P/KJb/P8A0Hqz5uWPN/dkVL4/+3on0R/xlV/1R7/yq0n/ABlUP+iPf+VWuv8A2m/ijq3wW+B3iXxjotvZ3Wp6d9m8mK/jZoG8y5jhbcqsrfdkb+KuRH/DVOOf+FP/AIf2rW0vcly+8SnePNoJ/wAZWf8AVHf/ACq0f8ZWf9Ud/wDKrR/xlZ/1R3/yq0f8ZWf9Ud/8qtT/AOBD/wDAQ/4ys/6o7/5VaP8AjKz/AKo7/wCVWj/jKz/qjv8A5VaP+MrP+qO/+VWj/wACD/wEP+MrP+qO/wDlVo/4ys/6o7/5VaP+MrP+qO/+VWj/AIys/wCqO/8AlVo/8CD/AMBD/jKz/qjv/lVo/wCMrP8Aqjv/AJVaP+MrP+qO/wDlVo/4ys/6o7/5VaP/AAIP/AQ/4ys/6o7/AOVWj/jKz/qjv/lVo/4ys/6o7/5VaP8AjKz/AKo7/wCVWj/wIP8AwEMftVHp/wAKe/8AKrXP/DvXP2mv2Qf2ef7C0ofCbUfDXhGyvr/dd/2nLeyR+ZNdSDK+WjNlmVeF/h/3q6D/AIyqP/RH/wDyq1j+MfC/7Tfjjwhrnhy/l+E0Nlq9jNYXEtq2qLKEmjaNmXcrKG2t/drGpTjVj73MaRqSifefwR8Z3/xI+DPgLxdqscEOpa/oNhq1zFaIywxyzW6SMsaszNt3Odu5mPvXf1+Zeu/Hf9p79k74AWElxZ/CbUPDXg7TbDS4/Li1SS8kiUxWsRbLxqW5Vm+7/Fx/DX6Z54zXi1KcqcuWR3qUZfCLRRRWRQUUUUAFFFFAHyN/wUW0fXdR8CfC3UNB8K6/4sk0L4iaVrN5YeHNOkvbv7PDFctI6xp/wFdzYXcy/MM18sfHn4vX/wAQdc+DWnXPww+InghI/iLo063/AIv8PNYWkjbpF8tZNzbpPm3bf7qt/dr9Xunevkj/AIKL6NrupeA/hbf6D4V1/wAWSaD8RNK1m8sPDmnSXt39nhiuWkZY0/4Cu5tq7mX5hmuinWlT0RnOCl7x458aB/xln+zn9fEn/pBHRn/jYD/3TL/3K1xGt/E27+Iv7WfwD+1/D/xv4E+x/wBv7f8AhMtFbTvtW6w/5Y7mbzNu35v7u5f71dt/zkB/7pl/7la9uMoz96P8x53LKPxfyjm/5P8A/wDumX/uVpP2Qenxs/7Kbrn/ALRpW/5P/wD+6Zf+5Wk/ZB6fGz/spuuf+0aqP8T/AMCKn8AfsBf8mk+Bf+3/AP8AS+5r57k/5RLn/P8AzHa+hP2Av+TSfAv/AG//APpfc189yf8AKJc/5/5jtZy/gR/wy/8AbQ+3/wBvH0J+19/zRP8A7Kbon/taj9r/AO78Ev8Aspuif+1qP2vv+aJ/9lN0T/2tR+1/934Jf9lN0T/2tWlX7QofYOi+OPxx134Y+LPBPhrwz4I/4TfXPFP277Paf2rHp3l/ZY45G+aSNl+6zN95fu/xbq57/hc3x5H/ADbp/wCXzY//ABNHxn4/ay/Z0+viP/0gjo+KPxR+Kv8Awv6D4c/Di38HY/4RhfEE0/iiO6/5+mt2VWhb/rn/AA/3vmqpSlzS94IxVloJ/wALo+PP/RuP/l9WH/xNH/C6Pjz/ANG4/wDl9WH/AMTTtv7Vf/VHv/KrRt/ar/6o9/5VaXvfzS/8lJ9z+6N/4XR8ef8Ao3H/AMvqw/8AiaP+F0fHn/o3H/y+rD/4mnbf2q/+qPf+VWjb+1X/ANUe/wDKrR7380v/ACUPc/ujf+F0fHn/AKNx/wDL6sP/AImj/hdHx5/6Nx/8vqw/+Jp239qv/qj3/lVo2/tV/wDVHv8Ayq0e9/NL/wAlD3P7o3/hdHx5/wCjcf8Ay+rD/wCJo/4XR8ef+jcf/L6sP/iadt/ar/6o9/5VaNv7Vf8A1R7/AMqtHvfzS/8AJQ9z+6cR8TNb+O/xG1T4f3n/AAoX7B/winizT/FO0+MbCT7V9lLN5H8Pl7t33vm2/wB1q+kPhv8Atq+PNf8Ajr4F+Hfjb4KjwIfF32/7JqX/AAllvqO37LbNPJ+7hh/2UX5mX7/8W015N/xlUf8Aoj3/AJVa5u+8C/tMXvxX8CfEGSb4TjWPB327+z4FOp/ZpPtkPky+Yu3c21fu7WX5v71cWIw/tfe97mOmnPl90/TwLSjivj39nb9oz4yeJv2lb74X/FCy8DokfhKTxLBceEobxWLfbIrdUdriT/ak+Xb/AHfmr7C6CvIlGUJWkdt7i0UUVIBRRRQAUUUUAFFFFAHzj+1H+y7rvx78WfDvxL4Y+IZ+Hut+DTqIt7r+w49T837ZHDG/yySIq7VjZfut/rP4dtfK3xA+DXjv4R/tZ/s+f8Jt8Uh8Svt//CQi0I8O2+lfYvLsV8z/AFLN5m7zF+993y/9qv01LdK+c/2o/wBlzXfj14s+HfiXwx8Qz8Ptb8GnURb3X9hx6n5v2uOGN/lkkRVwsbL91v8AWfw7a2pVZQlH+UiceaJ84/8AN/3/AHTP/wBytH7IJ4+Nn/ZTdb/9o1l+G/hp4t+FP7d76T4y8en4i6nN8N/tUeqf2NDpnkwtqgVYfKjZlbayM27/AKaf7Nav7IP/ADWz/spmt/8AtGvco1I1JRlH+8cFSPKuUT9kH/mtn/ZTdb/9oV538C/+UZWpf9iv4i/9GXteifsg/wDNbP8Asput/wDtCvO/gX/yjK1L/sV/EX/oy9oj8Mf8Mge//gJ03jTx9rvww/4J++H/ABN4Zvv7O1ux8MaD9nu/Jjm2eZ9kjb5ZFZfusy/droP+FM/HnH/Jxn/ljWP/AMVXnvxy/wCUZ2mn/qWPD3/oyyr0P9sa51U+H/hppel6/rHhr+2/HWmaPc32hXzWlz9nmWZWVZF6/wALfNuXcq0f4v5YiI/+FL/Hr/o40f8AhC2H/wAVR/wpf49f9HGj/wAIWw/+Kpf+GQB/0Wz4w/8AhWH/AOM0f8MgD/otnxh/8Kw//Gav2cv5f/JiLx7/APkon/Cl/j1/0caP/CFsP/iqP+FL/Hr/AKONH/hC2H/xVL/wyAP+i2fGH/wrD/8AGaP+GQB/0Wz4w/8AhWH/AOM0ezl/L/5MF49//JTKn/Zs+MV1478M+MZf2gi3iTw19r/sq9/4Quz/ANG+0R+TN+78za26P5fmVtv8Nep/s0/EL4wWX7XV78N/H/xN/wCFg6MfA8niKE/2BZ6Z5U32+O3X/UrubC+Z/Ft/efd+WuC/4ZCH/RbPjB/4Vf8A9pqtZ/sXWeneJT4itvjB8WrfXzZ/YG1SHxQq3X2fd5nk+d5O7y93zbfu7vmrmq4X2kfdj73+I2hWUfime8fHb4FeIPh94uv/AIv/AAjsPtuq3H7zxT4Ki+WLX41/5eIV/hvFXP8A10/3vv6nw3+JGg/FjwjZ+JPDl59r0+4+VlZdstvIv3oZF/hkX+Ja89/YRk8RaT8cf2gfB2r+OPFfjbTNA/4R46fJ4s1eS/mh8+2uJpNrN8q7mK/dVfur/drqvjx8Dde+HXi7UPi/8I7A3uoXP7zxX4Kh+WLXol5a4gX+G8X/AMif733vkcdgva/D8R9Lgcd7D3ZfCegCvlDwTpNn+zfrniv4deNfDs2pfDvxlrU17pviGOza6tppLzbG1neRqv7tvl2rJt2sv93bX0P8N/iRoPxX8I2fiTw1efbNPuvl+ZdssMi/ejkX+GRf4lrqK+ahOVLmjI+nlGNXllE+K/EWj6X+zN8XIH0S81r4s/Ei+07+yfB3hGWT5tE075pG86bd80e75Vkk+bau35trMvqPgT49eOtE8aab4Y+MfhLTvCM2r2lxd6bremXvnWTG3jaaaGdm/wBSywq0m5m2sqtXEJqdv+z9+1p8S/GnxD03UTo/inT7VdE8U2NhNfQW0MKqs1rKsMbNGzMsTfd/5Z7t1cb4riuv+Ci3xB0+z0WGfSPgr4UupGuPEbRtDdavMy7WjhVvurt+X5l+VW3N8zLHXqOKn8fw2+I83m5P4fxc3wn0H8Df2j4/j54v8VR+HfDt3/wg2kFbez8VzSbY7+4/5aLHGy7tv8W7/vrbuVa9prK8L+F9I8E+HbDQ9DsItL0mwiWG2tbcbVRf8/xfxVq15NXknP3D1KXNGPvHk/xN+Guu6f4rtfid8MbiLS/iNp8XkzW07bbTX7RcZs7ofh+7k+8rbf8AgPufwH+O2hfHzwhLqOmwz6TrGnTfY9Z8P33y3mlXa/ehlX89rfdZf+BKuJXk/wAS/htrun+LbX4nfDK4i0v4jafF5NxbTMVtPEFquM2d0Pw/dyfeVtv/AAH1MHjPZ/u6nwnkY7A+0/eU/iPsiivLfgT8d9B+PnhJ9S0uK40nVrCc2etaDf8Ay3ek3a/ehlX/ANBb7rL/AN816lX0p8wFFFFAEZPWvAvG/hTTfGvxrtIbq3DOZ7a2eeBnjnjijs7yZtrr/D5klv8AX5f7q1771rxjR5Y5/jvrM8nlpFbyXUxnPy7VjtNOjXd/wKa5/wC+fxruwknGVSS/lOOvGMuWMv5jjPhx4P8AFvhvVvF2q+Cbq0u7CLVn09tI1WJYvtCW6qu5JI1VU+bzFVVVV/vbq9Dv/jnYadomqJrdnP4T8RW1lNcx6brAVVmaNc/uZv8AVzfN/dbd/sitb4Ew3Mfwm8O3N4++6v4X1OV+pLXMj3Hzf7X735vfNQfHi3Gr/Du70WHT4dT1DWm/s+0gmVWxIyszSLn+KONZJF/3KvETWIrSp1F/d5vwJp05U6PNGR8H+Hlb+x4JJWaWe4/fySN95mb5t1aNZnhyXzdDs/7yx+W3+zt+WtOvwWp8Uj5OXxBRRRWYgqMaq/hzW9C1uJvLm0zUbe4Df7PmfMv+7UlVb7Tn1y70rSIw0k2o6hb2kca/xbpFrpwn8aJdPm5vcPsDRbXUfi74g1XWrOWfSNCuQ+nR6nEzLNPYq33bb+FfMk3yNP8Ae2tGq/MrMvsml6bZaFpsFhZQJbWkC7I4YxhVX0ryvwD8LvBSJe+H9V8H+H7jVtGZY2mk0u33XNuwPk3H3f4lVlb/AGo5K7E/BrwAR/yI/hwf9wmD/wCJr9wxDjKXIn7vp/wT62jF8vM/iOxJGOtedfEvV7bwJqeneMbnzF06GOSw1Ly13MYm+aFtv8TLMqov/Xdq0P8AhTXgFevgjw6P+4TB/wDE1wPxJ+Dfg7xBdad4U0jw3omm316JLy4urbT4o5ILeNcblZVyGaZoVx/EvmfeCstGHjR9oueT5fT/AIJVVz5NInpHw80i50jwvapfJt1W5Zry9Uc/v5XMjjdxu27tv+6q/KOlY3xM1SHwdq2geKp1k+y2n2ixvBCNzGGaPcu1f4m86GFVX/poao+B/h34E8TeF7DULjwN4aivHTyruJdKt/3dxGxjmj+7/DIrL+Fcf48+EmgeK9Uv9L8O+ENFs49Ft2uJru3sLdfNvvL3QWrDbu27WWRv96MfxNWlKFKVd+0l/i/q5nUlU9j7sTpNd0q5sPhnq/iTUUKa19oj8QzqV2tCtuyyRw4/2YYwrL/eaRv4q6T4QR7PANjeyxvFcao82qy+aoWTdcSNN83uqyKuP4doXtXGeMfh/wCAdT+FJ1TSvCGg202sW1vFYzxabbrIkl0yRRMrbflbdMvzVofDH4VeCdR8C6V9t8IeH7q+t1axuZpNLgZpJrdmhkZvl67o2q58jw7u/tdv+CKN/bafyna/EbVZtG8FanNaPs1CVFtLNj2uJmWGHp/00kStnRtLt9C0ay0y0XZbWcEdvEv91FUKvT6V5b4g+Evgq58aeHNItfCGgwxjz9RvPK0yEBoo18tY2+X7rSTK23+Ly2/2q6wfBzwAengnw7n/ALBMH/xNcrjSjCK5n93/AATePO5SfKWPFPg6218W93Gz6drdnuNnqcC5ki3csrL/AMtI243Rtw2OzBWHxH+1b4j1r4ceCfG3hGewbT4/FEttOPJBa2+WYed5Lf3ZP3Xy/eVf3f8ACrN9feIfh/8ADPw5ZpLe+C/Dm+RxFDbx6TbmSeQ/dSNdvzMfSvj39sb4aXUHhHU9Zs9C0rRLfSI7aa+s9GtY4vsiTTqsUcjov7yT5WZm+6v7vaqhi0hUlD6liIyl7vLL+t/5j3eHo82fYD3Y/wAan/6UfGPTpRRRX4Gf6ehRRRQAo619G/8ABP3xFPof7S1nYLIVt9a025t5YuzNGnmq3+9hG/76avnIda+gf2CdGk1X9qHRLoIXj0nTr27dj/AWj8kf+jK9nKub67T5D844+jSlw1jfbbcsrf4vsn6uUUUV+tH+eYVg+FvCejeCNLGleH9IsNC0xXaVbLTLWO3hV2YszbI1VdzMSzVvV8l/t0ftzaH+yh4WbTtOaHWPiPqcO/TdKLbltlzt+1XOD8sf91fvSMu0fLuZQD8+f+CxXi/RvEP7Utjp2mCGS+0TQre01KaP73nNJLMsbf7sckZ/4HX39/wS2+HF/wDDr9jzww+pxyW914guLjXFgl6pDMVWFh/stFHHJ/20r8+P2Ev2JfEP7W/j+X4lfEFrl/Aqai17e3d2WM/iG68zdLGrfe8tm3eZL/vKvzbmj/b2GGO2jWONVjjRcKqjaqigCaiiigAooooA8g+On/I3fB//ALG5P/SK7r1+vIPjp/yN3wf/AOxuT/0iu69foAKKKKACiiigAooooAK+DP8AgoH8IvGXxD+I/hi88NeHbzWra30loZpLYLtVvOZttfedc74i0u6vrmNoI9yrHt+9QB+A/wAfv2dPiVaeNII5/B2pRP8AY1bayr/eb/arjtL/AGTPi9rdn9qsPAOq3MG7b5kar/8AFV+x/wAf/gl4z8Z+Nba90fRmvLZbNYmk86Nfm3N/eatX4X/B/wAW+HvCa2t/pDQT+dI23zo2+X/vqgD8pPCX7G3xs/sOD/i2+tfeb/lmv97/AHq958EfsqfF218L6fDL8P8AWIpVX5ldV/vf71fqJ4b8ManY6PBDNbbZFZty7l/vV3GlxSW9hBHIu1lX5qAPnf8AZr8AeJfCXwb0XS9X0i50/UIZJ/Mtp9u5d0jMtfQuhQSW+k20cq7ZFX5lNaFFABXx1411S1XxhritMqst9Nu/76r7Fr88PiT4/wBBs/iJ4lhlvlWWPUrlWXy2+VvMagD8tf2mpFm/aC8ftGdytrE+3/vqvMK9B+P15BqHxp8Z3Nu/mQyanMyv/e+avPqAP3m+HP8AyT3wr/2CbT/0StfXlt/x7xf7q18h/Dn/AJJ74V/7BNp/6JWvry2/494v91aAJqKKKACiiigAryn9qf8A5N3+IH/YJlr1avKf2p/+Td/iB/2CZaAPS9P/AOQda/8AXFP/AEGrdVNP/wCQda/9cU/9Bq3QAUUUUAFeU/tZf8mtfGP/ALEzWf8A0hmr1avKf2sv+TWvjH/2Jms/+kM1AH57+OP+SAfsj/8AYz+Ef/SRq9C+NP8Aydn+zj9fEn/pBHXnvjj/AJIB+yP/ANjP4R/9JGr0L40/8nZ/s4/XxJ/6QR19H9n/AMBPMf8A8kHxp/5Oz/Zx+viT/wBII6F/5SAf90y/9ytHxp/5Oz/Zx+viT/0gjoX/AJSAf90y/wDcrV/al/i/9tI+x/26J8Fv+Ttf2jf+5b/9IJKX4L/8nZ/tG/Xw3/6QSUnwW/5O1/aN/wC5b/8ASCSl+C//ACdn+0b9fDf/AKQSU19n/FL/ANuFL7X+H/5EP2Qenxs/7Kbrn/tGj9gT/k0vwL/2/wD/AKX3NH7IPT42f9lN1z/2jR+wJ/yaX4F/7f8A/wBL7mlT+KP/AG9/7aVV+GZ558C/+UZepf8AYseIv/Rt7R8dP+UZem/9ix4d/wDRtlR8C/8AlGXqX/YseIv/AEbe0fHT/lGXpv8A2LHh3/0bZVl/y5/7dK+3/wBvHoX7YHT4J/8AZTdD/wDa1Hxp/wCTtP2cvr4k/wDSCOj9sDp8E/8Aspuh/wDtaj40/wDJ2n7OX18Sf+kEdaVPil/26QvgX/bwv/OQP/umX/uVo/5yB/8AdMv/AHK0f85A/wDumX/uVo/5yB/90y/9ytH/AMkP/wCRPoGiiiu45AooooAj+zx+Z5nlr5v97b81U/8AhHNJWZZhpdn5ituWT7Ou5a0cD1owPWp5Ylnhnxf8Ff2RqEGoaZY+VYyR7ZvIX7snzNub/gP/AKDWh8DNDvIr6+1R1aOzaHyI9y/6xmbduX/d2/8Aj1exikrj+pxjW9obe2l7PlCiiiu45gooooAKKKKACiiigAooooAKKKKACvn39v3/AJNK8df9uH/pfbV9BV8+/t+/8mleOv8Atw/9L7asa38GRpT/AIkT9HaKKK+SPcCiiigAryn9rL/k1r4x/wDYmaz/AOkM1erV5v8AtC+GNV8dfAT4keHNDtvt2s6x4a1LT7K1DrH5081rLHGu5mVV3MyjczbaAPzq+OYz/wAEztO/7Fjw9/6Msq9A/a//AOaJ/wDZTdE/9rV43+0Rpvxz8G/sXXXhXxh8E/8AhG/Dmj6ZpenXXiX/AISuxu9nkzW0at9nj3P+8kVV2q3y7vRa9l/a+/5on/2U3RP/AGtXuxqRqxly/wB04OWUZR5vMT9sDp8E/wDspuh/+1qPjT/ydp+zl9fEn/pBHR+2B0+Cf/ZTdD/9rUfGn/k7T9nL6+JP/SCOuip8Uv8At0wXwL/t4X/nIH/3TL/3K0f85A/+6Zf+5Wj/AJyB/wDdMv8A3K0f85A/+6Zf+5Wj/wCSH/8AIifBb/k7T9o36+G//SCSj9j/AKfGz/spuuf+0aPgt/ydp+0b9fDf/pBJR+x/0+Nn/ZTdc/8AaNFP4o/9vCfwP/t0X9kH/mtn/ZTdb/8AaNfPY/5RL/5/6D1fQn7IP/NbP+ym63/7Rr57H/KJf/P/AEHqyf8AD/7dkV9v/t6J9C/t9/8AJpXjn/tw/wDS+2rR/av8Y+LPC3h/wFZ+D9f/AOEY1PxD4wsdBfUvsUF15cNwsyt+7kXa3zKrfw/d+9Wd+33/AMmleOf+3D/0vtqT9r7/AJon/wBlN0T/ANrVtU+KX/bv/twofDAT/hS/x6/6ONH/AIQth/8AFUf8KX+PX/Rxo/8ACFsP/iqwvij4Z1X4n/tdQeDv+E88Y+EdEh8CprHk+F9Yay8y4XUGh3MvzL91v7u75Vre/wCGQB/0Wz4w/wDhWH/4zS5f5Y/+TCt/XKJ/wpf49f8ARxo/8IWw/wDiqP8AhS/x6/6ONH/hC2H/AMVS/wDDIA/6LZ8Yf/CsP/xmj/hkAf8ARbPjD/4Vh/8AjNHs5fy/+TBePf8A8lE/4Uv8ev8Ao40f+ELYf/FUf8KX+PX/AEcaP/CFsP8A4ql/4ZAH/RbPjD/4Vh/+M0f8MgD/AKLZ8Yf/AArD/wDGaPZy/l/8mC8e/wD5KJ/wpf49f9HGj/whbD/4qj/hS/x6/wCjjR/4Qth/8VS/8MgD/otnxh/8Kw//ABmj/hkAf9Fs+MP/AIVh/wDjNHs5fy/+TBePf/yUT/hS/wAev+jjR/4Qth/8VR/wpf49f9HGj/whbD/4ql/4ZAH/AEWz4w/+FYf/AIzR/wAMgD/otnxh/wDCsP8A8Zo9nL+X/wAmC8e//kon/Cl/j1/0caP/AAhbD/4qj/hS/wAev+jjR/4Qth/8VS/8MgD/AKLZ8Yf/AArD/wDGaP8AhkAf9Fs+MP8A4Vh/+M0ezl/L/wCTBePf/wAlMHx/+y38WPih4RvvDPib4+jUtCvtn2i0/wCEMtYTL5ciyL80cit95Vb71dB4i8d/tC/CTxz8JpNa+On/AAmGjeIfHOkeHb7Tf+ER0+y3w3En7z94qs33Y2X5drfNkNxSf8Mg/wDVbPjB/wCFX/8Aaao6p+xHputyafJqHxb+K99Jpt5Hf2TXPiZZWtbiP/VzR7oflkX+Fl+ZawqYf2kfh97/ABG0Kqj9o/SjAzR2r85vAvh3xN8JP2x/gXoifFn4j+LtG8R/279v07xV4jkvbaQ2+ns8f7v5V+9Ju+bd8yrX6MnpXi1KcqUuWR2xkpR5oi0UUVmWFFFFABRRRQB8f/tq/Df4na/8Wvgp42+HXgQ+PP8AhEv7b+32X9sWunbftVvBDF+8mb2kb5Vb7n8O6vAvAt945vf25Jn+IHgQfDzWv+FcssOl/wBrwan5kP8AaS7ZvNh+VdzeYu3737v/AGq/Tv71fH37RP7Ofxk8TftK2PxQ+F954Hjjj8JR+Gbi38WzXisW+2S3LOi28f8AtR/Nu/vfLXTh60qcuWXwmU4c55N/zf8A/wDdMv8A3K0fsg/81s/7Kbrf/tGsPwj4d+JHhr9uya1+KD+FZPEMnw3Mlu3hI3LWv2b+0lVd32j5vM3LJ/s7dvvW7+yCP+S2D/qput/+0a9mjKNSXNH+8cVSPLDlE/YC/wCTSfAv/b//AOl9zXz3J/yiXP8An/mO19CfsBf8mk+Bf+3/AP8AS+5r57k/5RLn/P8AzHaUv4Ef8Mv/AG0X2/8At4+hP2vv+aJ/9lN0T/2tR+1/934Jf9lN0T/2tR+19/zRP/spuif+1qP2v/u/BL/spuif+1q0q/aFD7AfGn/k7P8AZx+viT/0gjoX/lIB/wB0y/8AcrR8af8Ak7P9nH6+JP8A0gjoX/lIB/3TL/3K0/tS/wAX/tpP2P8At0d8Ufij8Vf+F+wfDn4c2/g7H/CML4gmn8UR3X/P01uyq0Lf9c/4f73zUv8AxlVj/mj3/lVpv/N/3/dMv/crWDdXPxY+J37QnxU8NeGvir/whGh+Fv7K+z2g8PWmo+Z9qtfMb5pNrfeVm+833v4dtT/8kUb+79qv/qj3/lVo3ftV/wDVHv8Ayq03/hS/x5/6OO/8sWw/+Ko/4Uv8ef8Ao47/AMsWw/8Aiqr3v5Zf+Sk+5/dHbv2q/wDqj3/lVo3ftV/9Ue/8qtN/4Uv8ef8Ao47/AMsWw/8AiqP+FL/Hn/o47/yxbD/4qj3v5Zf+Sh7n90du/ar/AOqPf+VWjd+1X/1R7/yq03/hS/x5/wCjjv8AyxbD/wCKo/4Uv8ef+jjv/LFsP/iqPe/ll/5KHuf3R279qv8A6o9/5VaN37Vf/VHv/KrTf+FL/Hn/AKOO/wDLFsP/AIqj/hS/x5/6OO/8sWw/+Ko97+WX/koe5/dMTw74Q/ab8NfG6T4o2svwmk1+Tw7/AMIy1vM2pm0+zfaFuN+0Lu8zcv3t23b/AA17n+zv+0V8ZPE/7St98L/ihZeB0jj8JSeJbe48JRXisW+2RW6o7XEn+1J8u3+781eT/wDCmPjz/wBHGf8AljWP/wAVWbpH7Onxm0L4lN49sf2hPJ8WNpX9htf/APCFWbf6F53neX5bSeX/AKxd27bu/wBquKtheZc0Yy5johWUfikfpaBigjNfIH7FXxJ+JviD4tfGrwT8RfHR8eHwn/Yn2C9/se107b9qt55pfkhX2jX5mb7n8O419fk4ryJRlCXKzu3FoooqQCiiigAooooAKKKKAPnP45/sV+Gvjt8TLXx5ceNfHHg/xDb6OmhiXwjq0dislss0k21mMLMfmk/vbflX5flr5s/Y38PL4Qt/jPoEd9e6rHpXxL1mwF7qc3nXdwsfkx+ZNJ8u6Rtu5m/iav0fr5m8V/8ABOr9nvxv4t1nxHrfw++3azq97PqF7c/21qEZlnlkaSRtq3Cqu5mbhVxXTh63sJcxnUp+0jynz5+yBx/wuz/sput/+0a8++Bw/wCNZ2pj/qWPEP8A6MvaofA745/CH9mDWvjB4D1jWx4Zi0/4hazFpun/AGS8uvLso2jhh/eLHJu/1LL8zbvlz3rQ+B3/ACjN1I/9Sx4h/wDRl7Xr06kZRj/hkcslKMvuI/jp/wAoytN/7Ffw7/6Msq9E/a+/5on/ANlN0T/2vXnfx0/5Rlab/wBiv4d/9GWVeiftff8ANE/+ym6J/wC16qXwy/wxM1v/AOBGD+1L4C0L4nftC/ALw14lsf7T0O+/t8XNp5skPmeXawyr80bKw+ZFb71J4s/ZJ/Ze8BfZh4l0vR/Dpug32cat4nurXztu3ft8y4Xdt3L/AN9LXQfGj/k7L9nT6+I//SCOqH7Qnh7SfFn7Tn7Pela3plnrWmXH/CQ+bY39us0Em2zjZS0bfK3zKrf8BpyjHmlLl+1/8iRGUvcicV/wov8AYy/6CXg7/wALaX/5Lo/4UX+xl/0EvB3/AIW0v/yXXS/FDUPgp8MPH8Hg4fAIeLdcm0xdY8rwv4Os7zy7dpmh3Mvyt95f7u350rnP+E3+FH/RpHjD/wANra//ABVTan/LEtKT/mGf8KL/AGMv+gl4N/8AC1l/+S6P+FF/sZf9BLwb/wCFrL/8l07/AITb4U/9GkeMf/Da2v8A8VR/wm3wp/6NI8Y/+G1tf/iqX7v+WIWl/eE/4UZ+xp31Hwd/4W0n/wAl16n/AME6fi/8IvhH4B+KPh+68feEvDGnx/ETVW0m11LxBbxtJYCK2SCSNpJN0ke1CqyZbdtPzV5d/wAJz8Kv+jSfGP8A4ba1/wDiqP8AhOPhT/0aR4w/8Nra/wDxVc9SnGr/ACxNoTlE+i/H/g22XW9X+OH7O2qaT42jluNni7wr4e1CG6ttaZVVmmhaNmWO+RWVtv8Ay0Vv7zfP3vw2+JGg/FfwjY+JPDd4t9pl0vddssMi/ejkX+GRfustfK/7IH7ScP7Ofhr4gaNqHwM+Ky2uteM9Q1/S7bRPCP7i2s5o4VhhZWlXay+Vjau5VG3DGvSUt5PGfhSz/af/AGf9D1JtN8QtNN4l8BXiRwyaxHDNJDJdQxxsyx3itGzfK37xf9r73yuOwXtfej8R9Dgcb7D3ZfCe2eLvCem+O/C2r+HtYia50vVLWS0uoEkaPdGy7W+ZfmWn+FvC+keCfDthoeh2EWmaTYRLDbWtuNqov+f4v4qz/hz8RdB+K/g+x8SeG71b7Tbpf7u2WGRfvRyL/DIv3WWulr5eXND3D6yPLL3ohRRRUFBRRRQB5R8SfhtrumeLYPih8MZodO+IlhD5VxaTsVtPEFqv/Lndf7fH7uT7ytt/h+77r8CfjroHx68Iyappcc+m6pZTG01nQb4bLzS7ofehmX8Dtboy/iBg15L8Svhxr+j+L4Pih8MJodN+IllD5V1YztttPENovW1uv9v/AJ5yfeVv9n7vsYPGez/d1PhPEx2B9p+8p/EfZVFeXfAf476B8ffCL6rpKT6bqdlMbTV9BvV2XmlXa/ehmX8Dtb7rLXqNfSny4xuAK+Y9U1FLS3+MF+AFK6fcQRPGu4tPPdXVuu7/AHWt4/8Avr/Zr6cc/LXy54Wjm1uGW2hVHGq+OLeG5jkVcGONW1SRfm/2mb/e/u/NXp4KyjOb2938zhxPxRifSujaVBoWj2WnWuRbWcEdvEWOTsVdq1ykDv4j+J9w+z/QvDtv5Cvu+/dTqrN0/uxeX3/5b/d+61dVrOq2+haNe6ndnZbWcElxK/8AdRV3N1+lYHw30y403wvDNfRvDqmoyPqF7E3WOaZvMaP6R7vL+i1wr3Yymzpl8UYnxn8b/h9N8LPiffQiFl0DXJmvbCbb8qyN/rIf+At/46y1yNff3xD+Hei/FDwxcaFrsDTWkjBlaNtskTr910b+Fh/Wvi/4g/BHxr8LLmQy2M/ibQFb9zqenR+ZKq/9No/vL/vfdr84zbKqlOpKvQj7p4WMwcoy9rSORorMi8R6bL/y+Rq392Rtu3/vqnv4h08SLHFN9pnZtqxWy+YzN/wGvlvZyPH5ZGhXqf7K/wAPZvHPxD/4Su4hb+wtA3JayMvy3F2y7fl/2Y1/8e21nfDX9nHxV8TrmCbW7W48K+FmO6Tzvlvbpf7qx/8ALNW/vN/49X2b4W8L6b4O0Cy0fSLZbPTrSMRRQpn5VH8z719jk+U1FU+s1z2sHg5c3tapgfEC2k0We08XWsTPLpSut9DEu5rixbHmKB3ZdqyL/usv8VdhbTxXcEc8EiywyKGSRWyGX1qc4OQe9cJ4JceE9cu/CEpCW0ateaNxjda7vmhX/rizBf8Adkjr7/44ecfyPc0jL/Ed4wwtcN4GMmu+IfEHiSTD28039nae3J/0eBmV2/4FM0nP8SrG25l27dH4ha3eaF4Uu5tMEb6xOVtNOSXGw3UjbIs/7IZgzf7KtWl4a0S38OaJY6Xa7jb2kSwq0hyzbcDc3qzYLZojpT5u4bzPP9Z8QS/DzxJ4gsraFbmbWVjv9Htm4WW8Zkgkj9dvmNBIzdlkkbotdt4L0GTw54fhtbqZbnUHZri9uVUhZriRt0jL6LuY7V/hUKv8Neb+MXu9U8TL44SfOieDrpoY4Qit5/8Ayzv7jd/0zjaWPb/ehk/2a9mV1Zdw5FaVvdhH8TKl8UjxrRUH/CQ6P4LJIfR9curxk/6c44/Ohx/sq15bL/wBlrr/AAav9n+KPGWkHhVvY9QhX/pnPGN3/kaOeuds7mMftJ3zCLbFLoy2XnAf8vCMszL/AMCikjP/AGyb/ZrZ8S6rD4O8fQa1dOY7C70a6S5f0a1PnR9f+mclyf8AgNdVTmbs95R5v/bjOGiv/LIteFm/tbxp4o1cjMcMsOj2+7n5Yl8yRh/d/eTMp/veUv8As1peIvGFp4fntrNQ17q98W+x6bF/rJtuNx/2Y13Dcx4XP0Fcn4Z1y78O6FpHhy3tftvi66g+3XcALLBaPNI0kkkzfwr5jSbV+9JtP+0V6nwt4Ph8PG6vJZ5dR1e/Km81G4GHk2/dVV/5Zxrltsa8LuPVizHlnGKleXyNoSco2iZ+i+ERp+oyeJ/Ed5Hf655LKZ2+S2sIerRwKfur/ekb5m/i+UKq8/D4Gtvil8MNfttcgeIeM4pXuNv3oYXXbbhQ33WWJY2x/wA9Nzbcsa6D4lM2p6VbeHYy6za/cLZSeWcMtvtLXDD+7+7Vl3fws6/e4Vuwt4IreBIYkWOJBhUVcBR6VM5Xpe99r/0n+vyKpOVKrGdP7P8A6UfiN4z8Gax8OfF2q+GNdt2h1PTZijbhhZY/4JF/2WXa1Y4681+rv7Tn7LWhftCaUt0Jf7J8W2MTLYaui54PPlTL/FHn/gS5JU8sG/Nj4pfBTx18FtRktvFfh65t7deV1K0zcWcg/vCRR8v+621q/KsxymrhKnNTjzRP7s4K8QsBn2FhQxdRU8TH4oy+1/ej/kcR+NJUMd5C3/LRPzq/omn33ijUVsNE0291m/bpb2Fu0zn/AL5rwo0pzlyxifrNXG4fDU/a1akYxK0kgiVnc7VWv0a/4J7/AAOufA/gO98aa1bva6t4lKPbwzLhobRMiP8A77zu+m2uE/Zo/YFvG1G08T/FS3jjS3ZZrTw3HJ5gLdd1wy8dR/q1/wCBf3a+92bbuAbAGOMV99kuVyoy+sVviP5J8TePsPnFP+yMslzUvtS/m/ux8ixRRRX1p/OpkeI7640fw/qd7Y2rXt5b2sk0FqikmaRVZlX5f7zcfjX80Hjb4ga745+JWqeMPF+db12+1BrzUI78yKkzbvmhZUZWjj/5Z7VZdq4Vdu0V/TtRQB+I/h7/AILCfFrwrodjpGj+CPhxpmk2EK29rZWml3kcUEartVVVbv5QK+6v+CdH7Yvjb9rzS/HFz4x0XSdLOhT2cVrNolpNDBMJlmLqzSTSbmXy0OF27d69d1fZ1FABRRRQAUUUUAeQfHT/AJG74P8A/Y3J/wCkV3Xr9eQfHT/kbvg//wBjcn/pFd16/QAUUUUAFFFFABRRRQAUUUUAFFQvPHE21m21k3/i7SdLuPs91eLFLt3bdrUAblcfrHxa8IeH9RnsNQ1+zs7yA7ZIJXwy1x3in9rD4WeDtZn0nWfFkNlqEKq0kLW0zFdy7l+6tfDPxw/az+FF78VfEE0Pi2No2mXa32Wb/nmv+zQB+hDfHfwAjbT4r0/d/vNTP+F9/D7/AKGzT/8Avpq/LG6/ai+GL3DMviiPb/16zf8AxNQf8NPfDP8A6GiP/wABZv8A4mgD9Vf+F9/D7/obNP8A++mr8sfi1430G8+KnjG4g1S3lgk1i7aNlb7y+Y1Qr+1B8MR/zNEf/gLN/wDE182eKfiR4bvvEmq3VvqSyQTXUksbeW3zKzf7tAHlXxPuI7v4heIJom8yKS8kZXXvVOHwTrk9uk0Wl3DxSLvVlX7y07XrCfVNXvLy2jMttNI0kcn95a+yvBH7KXxU1vwLod9ZeE5p7O60+GeGX7VCu5Wj3K33qAP0X+HPgbX/APhXvhX/AIlNx/yCbT+H/pitfUVuu2BFP92sHwNY3Gm+CPD1ncp5dzb6dbxSLu+6yxqrV0dABRRRQAUUUUAFeU/tT/8AJu/xA/7BMterV5T+1P8A8m7/ABA/7BMtAHpen/8AIOtf+uKf+g1bqpp//IOtf+uKf+g1boAKKKKACuB+N3gy/wDiR8GfHvhHSngh1LX9Av8ASbaS7dlhjkmt5I1aRlVm27nG7arH2rvqKAPyc+Lvwe+Nnwg0T9n3RfiHdeAbjwhpXjnw9pNi/ht75tQaSNWWMyGZVj2+XHJu24+bbXpHxn/5Oy/Z0+viP/0gjr6m/aw/Z1v/ANpPwh4Y0nSfGH/CE6poHiK08RWupjTFv9s0EcyoPLaSNfvTBstuHy42ndXx78QPg147+En7WX7Pn/Ca/FEfEn7ePEP2Qjw7b6V9i8uxXzP9SzeZu8xfvfd8v/ar0sPiNeSX80TmnD7UTb+NP/J2f7OP18Sf+kEdC/8AKQD/ALpl/wC5Wj40/wDJ2f7OP18Sf+kEdC/8pAP+6Zf+5WvU+1L/ABf+2nF9j/t0T4Lf8na/tG/9y3/6QSUvwX/5Oz/aN+vhv/0gkpPgt/ydr+0b/wBy3/6QSUvwX/5Oz/aN+vhv/wBIJKa+z/il/wC3Cl9r/D/8iH7IPT42f9lN1z/2jR+wJ/yaX4F/7f8A/wBL7mj9kHp8bP8Aspuuf+0aP2BP+TS/Av8A2/8A/pfc0qfxR/7e/wDbSqvwzPPPgX/yjL1L/sWPEX/o29o+On/KMvTf+xY8O/8Ao2yo+Bf/ACjL1L/sWPEX/o29o+On/KMvTf8AsWPDv/o2yrL/AJc/9ulfb/7ePQv2wOnwT/7Kbof/ALWo+NP/ACdp+zl9fEn/AKQR0ftgdPgn/wBlN0P/ANrUfGn/AJO0/Zy+viT/ANII60qfFL/t0hfAv+3hf+cgf/dMv/crR/zkD/7pl/7laP8AnIH/AN0y/wDcrR/zkD/7pl/7laP/AJIf/wAifQNFFFdxyBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABXz7+37/wAmleOv+3D/ANL7avoKvn39v3/k0rx1/wBuH/pfbVjW/gyNKf8AEifo7RRRXyR7gUUUUAFFFFAHiH7Y/wAF9b/aH/Zv8XfD/wAO3FhZ6zq5s/s8+pyvHbr5V5DM29o1ZvuxsPunkiviT9o7wN8evC+p/Bi7+KMvw7fw+/xI0aK3Xwg9+139oLSFQ32hdvl7Vl/2t22v1JBFeF/tYfs6ah+0p4P8M6VpXi//AIQjU/D/AIitPEVrqY0xb/bNBHMqDy2kjX70wbLbh8uNpzWtOcoktKR8sftfjj4J/wDZTdE/9rUnxo/5O0/Zy+viT/0gjrnP2mvgF8S/hZd/BfVvGPxm/wCFh6ZN8SdGtYtMPhe30zypmaRlm8yORmbasbrt/wBv/Zro/jR/ydp+zl9fEn/pBHXuRqRr80o/zRPNlB00oy/vC/8AOQP/ALpl/wC5Wj/nIH/3TL/3K0f85A/+6Zf+5Wj/AJyB/wDdMv8A3K1p/wDJC/8AkRPgt/ydp+0b9fDf/pBJR+x/0+Nn/ZTdc/8AaNHwW/5O0/aN+vhv/wBIJKP2P+nxs/7Kbrn/ALRop/FH/t4T+B/9ui/sg/8ANbP+ym63/wC0a+ex/wAol/8AP/Qer6E/ZB/5rZ/2U3W//aNfPY/5RL/5/wCg9WT/AIf/AG7Ir7f/AG9E+hP2+/8Ak0vx1/24f+l9tS/tf9fgp/2U3RP/AGtSft9/8ml+Ov8Atw/9L7al/a/6/BT/ALKbon/tatanxS/7dCl8MBB/ykC/7pl/7la474ofCPwn8Zf23YdD8YaV/bGm2/w6W9jg+0TQ7Zl1JlVt0bK33ZG/76rsen/BQH/umX/uVpP+cgP/AHTL/wBytEo83xfzC2/8BD/hgP4C/wDQin/wcX//AMeo/wCGA/gL/wBCKf8AwcX/AP8AHq+gqK6PY0f5TD2lT+Y+ff8AhgP4C/8AQin/AMHF/wD/AB6j/hgP4C/9CKf/AAcX/wD8er6Coo9jR/lD2lT+Y+ff+GA/gL/0Ip/8HF//APHqP+GA/gL/ANCKf/Bxf/8Ax6voKqOvS3UGh6hJZbvtkdvI0O1dzeZt+X5f4vmo9jR/lD2lT+Y8L/4YD+A3/Qi/+Vi//wDj1L/wwJ8Bv+hF/wDKxf8A/wAer1XwvpviRv7PvtS15p4pIVlm09tPjjZWZfu7vvfK3/oNWtI0TxBZahFNfeJv7Rtl3eZbf2fHHu+X+8tZRp05f8uv/SS+ef8AMeP/APDAfwG/6EX/AMrF/wD/AB6j/hgP4Df9CL/5WL//AOPV7BpOieILPUIpr3xN/aFsu7zLb+z4493y/wB5aNJ0TxBZ6hFNe+Jv7Qtl3eZbf2fHHu+X+8tL2dP/AJ9/+khzz/mPH/8AhgP4C/8AQin/AMHF/wD/AB6j/hgP4C/9CKf/AAcX/wD8er1/SdE8QWeoRTXvib+0LZd3mW39nxx7vl/vLWD4Zl8UeJvDemapb65DFJJHIskU9mrbmWRl3bl/2dv/AHzU8tP/AJ9f+klc8/5jz8fsCfAYf8yL/wCVi/8A/j1Yngf4C+BPgh+3L+zsPBWg/wBjDU/+Eh+2Yu7i483y9Mby/wDXSNt2+Y33f71e9ak/iq3+zfYl0u8VbdftHntJGzSfxbf4dtec+Kbq5sv2rvgDqLQm81+xh1trDRLYn/iYyyWO24VZm+WNY12yfN97O2sMVGnCjLlia0ZSdSzkfoHRXnXiH4qzeFpbNbrwd4kvVlto5pZtLsvtK27N96N23fw7fmNN1744+E/CclnHrU95pYurWO7DTWUrLGr9FbarbW/2f9qvBPSPR6K5G++KnhDSZ7W3vvEFhYy3Vul1Cl1MI98TfdYbq2I/EGlu0SrqNozTRrLGDOuZFPKsvqtAGtRRRQAUUUUAfK37QH7IXi34qfHCz+Jvgz4rn4danF4cXw5JCPDcOp+bCt1Jcs26SZVXczrxt/5Z/e+avBv2MtJv/Dll8YtK1XUxrWpaf8SNZtLrUxbrbfa541hVpvLX5Y9zKzbV+7ur9IAcCvknV/8AgnP4W1Dxd4r16w+KfxT8Mt4j1i61y9sdA8QxWlr9puJPMkZY1t/fb8xZtqrluK68PW9jPmZjUp+0jY8b/YD/AOTSvAv/AG//APpfc18+sf8AjUuf8/8AMdr1L9if4xeAPCP7MPg3S9a8c+HNH1K3+2edZ3+r28M0e69nZd0bNuX5WVv+BV5Y/wDyiXP+f+Y7Xqc37mP+GX/tpx/b/wC3j6D/AGvv+aJ/9lN0T/2tR+1/934Jf9lN0T/2tR+19/zRP/spuif+1qP2v/u/BL/spuif+1q2q/aJh9gPjT/ydn+zj9fEn/pBHQv/ACkA/wC6Zf8AuVo+NP8Aydn+zj9fEn/pBHQv/KQD/umX/uVp/al/i/8AbSfsf9ug3/KQEf8AZMv/AHK0vwV/5O0/aN+vhv8A9IJKRv8AlICP+yZf+5Wl+Cv/ACdp+0b9fDf/AKQSUvtf9vf+2h9j/t08t+Cn7Mnw0+M+vfGHW/GPhw6zqVv8RNZso5xe3EG2FXjdV2xyKv3pG/76rZ1D9nr9j7SdQubG+n8KWN9aytBcW1x4xmjkikVtrqytdblZWB+Wu4/ZAGP+F2f9lN1z/wBo1zH7NPwt8FeOdR+M1/4k8I6F4gv4/iTrEEdzqelw3EiRho2C7pFZtu5m+X/arKNOPLH3YmnNLml7xhf8KL/Yz/6CXg7/AMLaX/5Lo/4UX+xn/wBBLwd/4W0v/wAl0f8AC9P2M/8AoG+Dv/CJl/8AkSj/AIXp+xn/ANA3wd/4RMv/AMiU/wBz/dF7/wDeD/hRf7Gf/QS8Hf8AhbS//JdH/Ci/2M/+gl4O/wDC2l/+S6P+F6fsZ/8AQN8Hf+ETL/8AIlH/AAvT9jP/AKBvg7/wiZf/AJEo/c/3Q9/+8H/Ci/2M/wDoJeDv/C2l/wDkuj/hRf7Gf/QS8Hf+FtL/APJdH/C9P2M/+gb4O/8ACJl/+RKP+F6fsZ/9A3wd/wCETL/8iUfuf7oe/wD3g/4UX+xn/wBBLwd/4W0v/wAl0f8ACi/2M/8AoJeDv/C2l/8Akuj/AIXp+xn/ANA3wd/4RMv/AMiUf8L0/Yz/AOgb4O/8ImX/AORKP3P90Pf/ALwp+Bn7GeOdS8Hf+FtJ/wDJdep/8E6vjB8IvhJ4B+KPh+68f+EvDOnx/EPVW0m01LxBbxtJYCK2SCSNpJN0ke1CqyZbdt615Yfjn+xn/wBA3wd/4RMv/wAiUn/C8/2M/wDoG+Dv/CJk/wDkSsKtOnV+1GJpTnKP2ZH6ceDPiF4V+JWmTap4R8SaR4q02GdraS80S/jvIEkCqzRs8TMu4K6tt/2lrqK/L/8AYb/bY+A/wK8J/E3SNd8WweHLbUvHmp6to9pbaLeGM6dJHbrAyrDAyxriNl8v5WXb90V+h/wv+KPhj4zeBdN8YeDtSGseHNS8z7LeeRJD5uyRoW+SRVZcPGw+Zf4a8U7zsaKKKACiiigAooooAKKKKAExxivx08F+NfFfwv8A2K9W+Huv/BX4p2eo2+gaxDPqsvhSaPT7dZzcyeZLM7KVjVZFZmK/LtbrX7GV5v8AtDeGNU8c/AX4keHdDtvt2s6x4a1LT7K1DrH5081rLHGm5mVV3My/Mx21pTqSpu8SZRUviPzq+OYz/wAEztO/7Fjw9/6Msq9A/a//AOaJ/wDZTdE/9rV43+0Rpvxz8G/sXXXhXxh8E/8AhG/Dmj6ZpenXXiX/AISuxu9nkzW0at9nj3P+8kVV2q3y7vRa9l/a+/5on/2U3RP/AGtXsxqRqxly/wB04uWUZR5vMPjR/wAnZ/s5fXxJ/wCkEdJ8af8Ak7X9nL/uZP8A0gjpfjR/ydn+zl9fEn/pBHSfGn/k7X9nL/uZP/SCOup/a/xR/wDbTnj9n/D/APJDsf8AGf8A/wB0y/8AcrTvEv7RXjr/AIW14z8FeCfhN/wmh8MCyN3enxLb2GftFus0f7uaP/eX5Wb7v+1TR/yf+P8AsmX/ALlaPgx/ydl+0X9fDn/pBJUe98Mf5i/8hv8Awuf49/8ARuP/AJfVh/8AE0f8Ln+Pf/RuP/l9WH/xNS+Jf2jPHn/C2vGfgrwT8JP+E0PhgWRu70+Jrewz9ot1mj/dzR/7y/Kzfd/2qb/wuj49f9G5D/wurD/4mr5v70v/AAH/AO1I5P7v9f8AgQ3/AIXP8ef+jcx/4XVj/wDE0f8AC5/jz/0bmP8AwurH/wCJpP8AhdHx6/6Nx/8AL6sP/iaP+F0fHr/o3H/y+rD/AOJov/el/wCA/wD2ouX+7H+v+3hT8Z/j1/0bkP8AwurH/wCJrE+Afx2+NP7Iv7N2meFdV/Z//tfTPCltfXt1rP8AwmlnDuhaae6ZvJWOQ/KshX5S27b+A2/+Fz/Hr/o3L/y+rH/4msH4g+Pfjx4+8AeJ/DX/AAz6bE6zpl1pwuz41sJPK86Fo923au7bu3bdy1hVpxqfHKX/AID/APam9OUo/DynrOu+BvEFv4d0D9o/4SaA8cvivR7PXPFvw7t5fMTUI5oVmaa2bav+mR7+yr5237u7hvS/hz8RtB+K/g+x8SeGr5b7TLxflb7rRt/FHIv8Mi/dZa8I8F/tYfGj4CfA7QdK1P8AZxNzpvgzw5b2t1qf/Cc2S+ZDZ2yq83lLGzDKxs21d3/Aq6jXPBOvWHh/Qf2j/hH4eYL4r0iz13xb8O7aXzFvkmhWZri0bav+lx7+yr5237u7hvj8dl7qe9y+8fTYHHey92XwnuvSiuZ+HXxF0H4q+D7HxL4bvl1HSrxflb7rRt/FHIv8LL91lrpulfJ/AfWRlze9EKKKKRQUUUUAeR/Er4ceINC8XQfFH4XTRWHxBsoVivNPnbbaeI7Vetrcf7XH7uT7yt/s/d96+BHx28P/AB88Htq+kLNp+o2kxtdX0O8G280u6X70My/hlW+6y1g15B8S/hx4i0DxjF8VPhZLFZeP7OER32mzPttPEdqP+XW4/wCmv/POT+Fv9n7vs4PGez/d1PhPDx2B9p+8p/EfYl3KtrFJO+diAs2K+afgDaJrF38P98wa4tLTUtTnVF5aRfJsVb/gW2f/AL52/drq/CH7Qnh741fArxR4l0cSaffaZY3MOr6LqKlbvS7qOJt8M8f3uxwf4l6e1X9mmw+03l/qUlv+7tNKsLO2uPm+ZZhJfSH/AHm+1Q7l/wBla+5w0nHC1Jr+vs/+3HxNX3q8Y/1/XunonxCzrV9oXhgKxj1K6Nxdsh+ZLW3KyN/31J5EZ/2ZT/FtruhwK4TwlEdd8Y+IfEJdmjST+xrRdw2LHCzec2P7zTNIv8X+pX7vzLXd9c159T3bROyHve8OooorIs57V/AXhrxC7San4e0rUpH+895ZRys313LUujeDNC8Ntu0nRNO0xsY3WVpHD/6CtbYFBFTyq/MTyoWiiiqKExxiuR8faLd6ppkF9paq2taVN9rsgTt8xlHzQs392RSyn/eVv4a6+q9xcxW0Mk0sixxIu5nZsKo9auLcXdEyjzKx5zp+tw/EfxXoD2J8zRNOtP7VmEy4b7VJujhjZT0aNfOZl/hby+nFbvj7U7i10y20rTDs1bV5vsdsytt8lcbpZvby41Zl/wBrYv8AFXDfDO6/4RfU5NS1SOGwsPGLzarDKy+WsE3zMsLMf71uFk+b+JZvu7gtdV4Itk8S6veeM5wr/a0+y6UxXlLENwwI+8JmXzs/3WjH8NdVaMac7/ZX9fmctOUpR/vSOk0rwtY6V4dt9GjjMtjFbi2Kznc0i7dp3t/EzfxHvmsb4X3EqeHX0e7ZpL7Qp30yVnGGZU/1Ln/fhaJv+BV2ePevKviLrknw61q/1u3DbNX0qaBVGPmvrdGkt1Gf4pFaVf8AtktYU1KteH2mbzcafvGTk/8ACLS+NtnlyJ4kbVmJ4b7Ksn2Nmb1/0Vd3Tsq/w7qx/j/4vsNen0Tw9YGSeeLW4Yb3UYk3QWW5WWSN/wC83kySMy/wj72Nyq3Q6TZ3HirwzB4M0ZXj8L2lmum6hrjj/j6Cr5ckdru/1m75laY/Kv8ADubJXB8KeHl8daI2gpGlsdH8P3Gl3BjXbjUJmaGST/eU2rNu/wCm38W75fVp+zhU9tP7P5fZ/wCGOCfNKPs4/aPYfDXhXT/CVnJFZQuZZ3865upTumuZO8kjfxN/kVvkjFYPgvX/APhKPCWj6syhWvLSKZl/usyjcv507xf4ij8J+GNT1mSF7lbG3ecQR/fmZR8sa/7TNhR/vV5DUpT5ZfEeguWMeb7Jz+jp/b/xI1jVTGzQ6PCulWj53KXk2TXLL/5AX/tm33ui973Ncx8P9Em8OeE9Osrhme82tNds3VriRmkmbq3WR3/ib/ebrXTZzmlUacrLoOHwjqieNZUZHUMrDayt3qWioLOAvfgf8PtRuFubzwN4duZ1ORLNpUDsPxK10+h+HdK8M2httJ0600yEncYrOBYlz/urWrtFMJI6cUJJbGk61SStOTZNRRRQZhRRRQAUUUUAFFFFABRRRQAUUUUAeQfHT/kbvg//ANjcn/pFd16/XkHx0/5G74P/APY3J/6RXdev0AFFFFABRRRQAUUUx5Vj60ADSqvWsbWfF+maDPHDeTNG8i7lxGzVjeK/iXovhTUVs7/7R5rRrKvlQ7vlr5Y/aZ/bg+Gnwu8U6RYa42rpPcWfnx/Z7LzF2+Yy/wB7/ZoA9S+LH7b3wk+EXiSDRfFOuXdnqElqtyscWmzTL5bMy/eVf9mvBvHP/BR/4D3XiBpE8Saht8tf+YTcf/E1+f8A+1/+0P4S+NXxQsde8NtfNYw6XHaN9rt/LbzFkkb7u7/arzrw38BPFHxY0tdf0IWP9nyO0K/aLjy33L975aAPd/jt+0d4D8ffE7Vda0TUri50+4WFY5Ws5I2bbGqt8rV8teOIW8S+LNR1Kw/eWlxJujdvl3fLXuvhv/gn18WNf0iC/tF0PyJC23zNS2t97/dr1Dw7/wAEsfjlqOi21xDH4b8qRfl3ap/tf9c6APj3R/hD4l1yxivLSzjaCT7rNOq1z+reHL/Q9SnsbuJVuYW2yKrK2K/Tbwf/AME9vi14a0CDT72PQ/tMbNu8vUty/M3+7Xxh8ffhF4g8FfGDxRouora/brO4VZPLm3L/AKtW+9/wKgDwR0Ktg9aSrep2slnf3MMv+sjfa2KqUAdtp0q/2TB/1zr9ovgp8Z/CunfBnwPaz3kyzw6HZRyL9nb5WWFa/Ea11u3is4423blXb92vsPwf+134A0Twfo2m3Tan9ptbGGCTbabl3Ku3+9QB+2ulXkNzplpNG26KSFHX5f4dtaNeIeD/ANoLwnP4T0ORPt22Sxt2X/R/+ma/7VeyRX8cqK67trLu+7QBbooooAKKKKACvKf2p/8Ak3f4gf8AYJlr1avKf2p/+Td/iB/2CZaAPS9P/wCQda/9cU/9Bq3VTT/+Qda/9cU/9Bq3QAUUUUAFFFFABXhX7Rf7KGg/tJ6x4Q1TV/E3ivwnqfhb7Z/Z974T1COznH2lY1k3SNFI33YVX5dv3m617rRQB+aHxN/Zys/2fv2s/wBnkWnjvxv40/tc+ISf+Ez1db/7L5Ngv+p2xrt3eZ83XdtT0rUz/wAZ/f8AdM//AHK19gfG/wDZf+Gf7SB0U/Ebw1/wkX9jed9gzf3Vr5Pm+X5n+pkj3bvKj+9n7vFfEGt/Dz4T/sh/t0DStC/s74f+Gb74c/aW/tTVn8qS7fUyp/eXUjctHCvy7sfL/vV6OHrX5aUv5jmqw+0bvwW/5O1/aN/7lv8A9IJKX4L/APJ2f7Rv18N/+kElUP2evEWk+LP2nv2htU0XU7PWdNuP+Ee8m+sLhZoJNtlIrbZF+VvmVl/4DV/4L/8AJ2f7Rv18N/8ApBJXrL7P+KX/ALccMvtf4f8A5EP2Qenxs/7Kbrn/ALRo/YE/5NL8C/8Ab/8A+l9zR+yD0+Nn/ZTdc/8AaNH7An/JpfgX/t//APS+5pU/ij/29/7aVV+GZ558C/8AlGXqX/YseIv/AEbe0fHT/lGXpv8A2LHh3/0bZUfAv/lGXqX/AGLHiL/0be0fHT/lGXpv/YseHf8A0bZVl/y5/wC3Svt/9vHoX7YHT4J/9lN0P/2tR8af+TtP2cvr4k/9II6P2wOnwT/7Kbof/taj40/8nafs5fXxJ/6QR1pU+KX/AG6QvgX/AG8L/wA5A/8AumX/ALlaP+cgf/dMv/crR/zkD/7pl/7laP8AnIH/AN0y/wDcrR/8kP8A+RPoGiiiu45AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAr59/b9/5NK8df9uH/pfbV9BV8+/t+/8AJpXjr/tw/wDS+2rGt/BkaU/4kT9HaKKK+SPcCiiigAooooAKKKKAPIP2if2ctD/aW8IaLoPiDWNd0BNI1eHXLS/8OXaW93HcRRyJGyu8cm3HnM3yjduVfmr4f+NfwV8P/sq/tOfs/anqPxM8V63pl9/b/wBovviF4gjuIbLZZxqvlyMkax72mCt/e2x1+nucCuQ8c/CnwR8T2sj4y8HaB4s+wiT7KNd0yG9+z+Zt3+X5iNt3bF3beu1a0pzcJcxMlzI/P7wv4y8P+OP265b7w5rWneILOP4b+RJdaZeR3ESyf2qrbN0bMu7ay/L/ALVa+P8AjP7/ALpn/wC5WsX47a78Kv2Tv267S4lsdI+Hvhu9+G6x+Vouj+XDLdtqknzNFbx/eaOE/Pt/5Zr/ALNZPww+LvhL4z/ttTa54O1X+2dNt/h21lJP9mmh2zLqSsy7ZFVvuyL/AN9V7NGtGpH/ALeOKcJRkdd8Fv8Ak7T9o36+G/8A0gko/Y/6fGz/ALKbrn/tGj4Lf8naftG/Xw3/AOkElH7H/T42f9lN1z/2jXRT+KP/AG8YP4H/ANui/sg/81s/7Kbrf/tGvnsf8ol/8/8AQer6E/ZB/wCa2f8AZTdb/wDaNfPY/wCUS/8An/oPVk/4f/bsivt/9vRPoT9vv/k0vx1/24f+l9tS/tf9fgp/2U3RP/a1J+33/wAml+Ov+3D/ANL7al/a/wCvwU/7Kbon/tatanxS/wC3QpfDAT/nIH/3TL/3K0f85A/+6Zf+5Wj/AJyB/wDdMv8A3K0f85A/+6Zf+5Wj/wCSF/8AIn0DRRRXccgUUUUAFZviX7R/wjuq/ZfM+0/ZZPJ8j727a23b/tVpVm+JftH/AAjuq/ZfM+0/ZZPJ8j727a23b/tVMvhKj8QeGvtH/CO6V9q8z7T9lj87z/vbtq7t3+1WlWb4a+0f8I7pX2rzPtP2WPzvP+9u2ru3f7VaVEfhCXxBRRRVEijoa5z4eavda54P0++vpvPuZPM8yXaq7tsjL/DXRjoa5z4eavda54P0++vpvPuZPM8yXaq7tsjL/DWf/LyJp9k6M9a8h1//AJPp/Zg/7mj/ANNtevHrXkOv/wDJ9P7MH/c0f+m2uXGf7vI1w/8AEiffFFFFfNHrmNqPhLQ9ZTbqOjaffLt2/wCk2scnH/AlrE8QfCHwd4tmik1Xw9aXMkMK28bYaPy41+6i7dvy12lFAHnfiL4I+H/Ed5BdedqmmTQW8dvE2nX8kO1I/wDV/Ln+GjxH8M9S1a7gn07xvr2irFbx23kW8iNEwX+LaV+8396vRKKAPOdf8M+PnvIptC8aWdvCtvHE1ne6YsitIq/NJ5gbd833ttJ4il+JljqCvokPhrUtOEMe9Lt5o7lpMfPt2/Lt/u/71ej0UAeceI/GHjjQ9SVLHwIdesGt0drm31SKFo5P4o/Lb5m5/ip/iT4syeFtTFrdeDfFF8ojjka70ux+0wrlcsrMrfw16JRQB8zeJPAf7Mvg3UfsOv8Awo8E6XL5aSBpPBVuy/Mu4LlYG+b/AGa/PjT3XUv+CYaeGrEPfa/JuKadbRtJOdut7m2qv3jtVm/3a/Z7PSvzt/bY/Y9+FP7PX7KPjbxj8OtD1Dwv4k0r7Etne2viDUm8nzr63ik+R7hl+ZJG/h71rTqez5iZLmK37WcyX0nwXW3ZJ3j+JOiTSLH822P958zf7PzL/wB9Uv7YHH/Ck/8Aspuh/wDtauX/AGg/if4K8Q6v8L4PB/i3QdW1XU/G+lWGowaNqUNxPJYyeYsissbM23/Vru/3a6b9qOFNAvPhjdWilJ9X8c6Vo9w0g3+XDJ5nzR7vuyLt+Vq96Upe8edGy5B3xp/5Oz/Zy+viT/0gjpP+cgH/AHTL/wBytJ8ZUEf7SPwasI2b7Xq41n7NfyNul0vybNGbyP8ArovytupurmWX9sxrLTo44Nf/AOEEW4XVJ2ZlFl9u2tb+X93d5n7zzP8Aa20SlLml7v2hcvu/9ukh/wCUgA/7Jl/7laPgt/ydp+0b9fDf/pBJUerzPb/tnSNp0Mt14o/4QRfKWdlWzbT/ALd8+7+LzvO3f7O3/ap3gmZdD/aX+N91osT+IdQuv7EOpWS/uTY7bJvL2s3+s8xW/h+7to5ve/7e/wDbQ5fd/wC3R37IPT42f9lN1v8A9o0fsg/81s/7Kbrf/tGs79mzXE8Lt8Wdtnfaql58Q9buXfTbfzFtW85Y/Lk/uttjWT/dkWj9m3xFp3gyX4sR6tc+Q+ofELW7uJFiaTC+asfzbV4bdG3y/wB3a38VFOpH3RzUvfIP2OPFFr4H/Yd0DxHfRzTWWkWWq388dsqtK8cN3dyMq7mVd21f71aWm/tm2urWFtfWHwf+LN9Y3UKzwXVt4YWSKWNhuVlZZtrKy/xV5x8BdZsp/wDgnZdaGtwjavN4c12GKyGfMeSSW78tQv8AEzbl2/71fQ/7PF7b/wDCh/hnD50fn/8ACL6Z+73fN/x6x0U5SlGMYy+yTUik5SkcL/w19/1RP4w/+Ep/9uo/4a+/6on8Yf8AwlP/ALdX0Fk0ZNdPLU/mMeeH8h8+/wDDX3/VE/jD/wCEp/8AbqP+Gvv+qJ/GH/wlP/t1fQWTRk0ctT+YOeH8h8+/8Nff9UT+MP8A4Sn/ANuo/wCGvv8Aqifxh/8ACU/+3V9BZNGTRy1P5g54fyHz7/w19/1RP4w/+Ep/9uo/4a+/6on8Yf8AwlP/ALdX0Fk0ZNHLU/mDnh/IfPv/AA1+P+iJ/GH/AMJT/wC3Vm/sl/thW37Mf7MPhvwd4w+D3xa+0+HYL6e/1C18MD7Ekb3U9xu8ySaPCqknzMyr91u3NfSgrz79oc/8WB+Jf/Ysan/6SyVzYjD+0j70jopVuXSMT6y+Hnjaz+JXgLw34t0y3uLfTNf0231W1juwqzJFNGsiLIFZl3bWG7axrqa8p/ZN/wCTWvg5/wBiZo3/AKQw16tXzh6YUUUUAFFFFABRRRQAUUUUAfMv/BRfwprfjb9jf4haH4d0bUPEGsXZ0/yNO0u1kubmbbqFs7bY41Zm2qrNwOi18c/Hj4u3/wAQdd+DWnXPww+IngiOP4i6NOt/4v8ADzWFpI26RfLWTc26T5t23+6rf3a/V8HNfLv7e3w18cfErwJ8O5Ph/wCGP+Eu1nw54407xFJpn2+Gy8yG3jud37yZlUfM0a/xN833eK2p1ZU/dRE4cx4N8aTj9rP9nIe/iT/0gjpPjQP+Mtf2cvr4k/8ASCOuT8U6h8Tb/wDaz+AX/Cxvhj/wrjYdf+wf8T+11X7Z/oC+Z/qf9Xt/d/e+95n+zXW/Gg/8Za/s5H38Sf8ApBHXvRqRqRlOP80f/bTzeWUZRjL+X/5IG/5SAj/smX/uVpfgr/ydp+0b9fDf/pBJSN/ykBH/AGTL/wBytL8Ff+TtP2jfr4b/APSCSn9r/t7/ANtF9j/t0b8Fv+TtP2jfr4b/APSCSsLw18Ufj78T9e8ef8Ifb/DeDRfD3ie/8PR/27HqC3Mn2dl2s3lsy/dZP7vzbvlre+C/H7Wn7Rv18N/+kElH7IHT42f9lN1z/wBo0R+zH/EN9f8At0Uf8NV+nwe/8qtH/GVfp8Hvz1WvPvgPp/x5+OHwm0Lxr/wvj+xTqfnZsf8AhD7G48vy7iSHmT5d27y933f4q9A/4Ux8ev8Ao43/AMsWw/8AiqI80o80eb/yUPh35R279qv/AKo9/wCVWjd+1X/1R7/yq03/AIUv8ef+jjv/ACxbD/4qj/hS/wAef+jjv/LFsP8A4qn738sv/JRe5/dMnxj4X/ab8c+D9c8N38vwmhstXsJrC4ltTqiyhJo2jZl3Kyhtrf3abrnx3/ad/ZP+AGnyXFn8Jb/wz4O02w0tPLi1SW8kiXyrWItl41Lcqzfd/i4/hrY/4Ux8ef8Ao4z/AMsax/8AiqwPH37LfxZ+J/hG98M+Jvj8NS0O92faLT/hDLWEyeXIsi/NHIrfeVW+9XPVo+0Xwy/8lNoVFH7R718c/gh4g+DnjHUfi/8ACLTZNRgvW87xf4GtvlXVF/ivbRf4bpf4l/5af733ur+HPxG0H4q+D9P8TeG75dQ0q8XcrL8rRt/FHIv8LL91lrxn4f8Aj745+Bv2rfg/4O8X/GH/AIT3w34uOsG7sv8AhGLHTsfZbFpV/eRKzf6xkb5WX7n8Qau5+OfwQ1/4K+MNS+L/AMItOk1G0vW87xf4Ft/u6mv8V7aL/DdL1Zf+Wn+9975HMMvlOX94+mwGP9l7svhPUzxRXOfD34h+H/ip4P0/xN4Z1CPUNIvF3RyL96Nv4o2X+Fl+6y10eOcV8n8B9Xzc3vBRRRSKCiiigDwf46/BXXJ7zUfHfwymj07xzJYtYappztttPENmy7Wt7n/ppt/1cn8P3W+X7vdfss/Fex1v4B69rem7l12K/axuNBu32Xem3arHZ29rOv8ACf3cW3avK/dDN8td9ivD/i78INX03xnZ/Fb4aRwwePtMaOS90iaRo7TxFBH92Gbb/wAtF/5Zyfw/db5fu/Q5fmUqUfq9b+GfO5hl0a0vb0fiPsPwh4ej8J+GdN0eOZ7kWcKxtNJ9+Vv4pG92bc341uYrzH4C/Hfw7+0B4O/t3QzNa3VvJ9k1TRr0FbzS7tc77eeP+FlPf+KvTs8V7rbbuz563LoLRRRSAKKKKACiiigCPG2uJ+Jm/UtItfDsZdZtfuBZSeWcMLfaWuGH9392rLu/hZ1+9wrdvkCvOTfW03jTXfEt1uNl4ctf7Nt3DcNJJtluNuThm+W3T/eRl3Z3KulD4r9v6RFT4bFX4raTF41tLPwFY/6HLdJ9qluUhytlbw/dZf4dzSeXHt/utJ/drqfAetrrfh22Z7aOwvLVms7yxj+7bTx/KyL/ALPdf7ysrd6q/D/Spre0vNb1KGWHWNakW7uYZWObdfuww4ztBjj2q237zBm/irK8V30Xw68R/wDCTzPJFoeoqtrqpAZhDOvywXG0D+L/AFLbR826L+7W91Uj7CPT/wBK+1/X+Zl8P7yR3l1eQWUEtxcSJDbxIZHkkbaqKv3iTXg3xcvte+I+nafBpVmkWiXF6p0+K4X97q7RxyXG7+9DDthZd33pPM/hXG/0C00fUvHt8mpeIEax0BHWSx0Bhh5gCCst4PXcoZYui/xbm+VbF1/xN/i9ZQnJj0bSZLhkIPElzJsjb/vm3nX/AIE3+zVUJrD1Odayj+AqilUjynR+F72w1Pw9pl3pqomm3FtHJbIqbFEbKCo29vlI+WvPfgzel9d8W7o1jTV7w65aN/ft5GaFf/SdZP8Att+NFzqtx4M0Hxr4ftWEd5bzI2kHP8N9IVh/75uHkX/dVa19T0y38Ga94Fls1EdlBG/h9s/wxSRq0P8A5Et41/7aUKCipR/m/wD2jO6lKMv5f/2S/wDDH/QrHW9GJBbS9WuIVA6LHI32iJf+Axzov/Aar+K5jrvjDw94eCM0ccn9sXbbfkWOFl8lc/3mmaNv4v8AUt935WqzZH+zPirqsHSPVdMgu41/6aQyNHK3/fMluP8AgNRfD5DrN9rvidjldUuBDaoTkpbW+6NAeP4n86Tb/D5v97dUS0cq3T/26X9SNvs+zO7ooorlNwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPIPjp/yN3wf/AOxuT/0iu69fryD46f8AI3fB/wD7G5P/AEiu69foAKKKKACiimM+371ACPII68o+LX7QPh/4SavY6fq9nqE891B58b2kasoXdt/iatP4ofG3w18J7rT4dea8R76NpIfstv5n3fvf+hV8Bfts/td/D+68ceHmSTVNq6ay/NZ/9NG/2qANz9pP/goN8PdB8eW1vcaT4gZmsY2+W3h/vN/00r8/v2vPjzoPx+8X6HqugWt9ZwWOn/ZpFv41VmbzGb5drN/ermfj7430z4n+MrbVtD85rSOzW2Y3EfltuVmb/wBmqP4Zfs5eLvi5pd3qGgLY/ZrWb7PJ9qufLbdt3f3aAOd8K/C/VPGGmve2U9rHEsnlbZmYNu/Ba/Rz9iv9l3xVrPwNtriC+0tF/tC4X5pG/vL/ALNec/AD9g34pXXgu6ZI9F2fbG+9qH+yv+zX6Qfso/CLX/hT8IoNA11bVNRW+uJm+zTeYu1mXb81AEPgH4Da7ofha1s57vT2ljZtzRSNt+9/u1654fmXwzpFrpd1801uu1mjHy/3qbc+NdN8PTtYXnnefHjd5ce5fmr52+I/7dHwx8EeN9U0PU5NaF9ZyKswg0/cn3Vb727/AGqAF+M37dvgT4SfETUvC+r6Tr09/ZrG0ktpDG0Tbo1ZfvSf7VflR+038fvD/wAQvjv4v8R6dZ6hFZ6hdLLGtzGqyr+7Vfm+b/Zro/2uf2gfCnxB+PfiHXdJN99gnjtlQz2/lt8sKq3y7q+bdY0W68SancapY7fs1y26PzW2t/doAw9YmGp6nc3cY2xzSMyhq9h0L9knxX4h0TT9UttQ0pbe8t47mNZJpAyqy7um2uk8I/sFfFPxl4U03XNMj0Y2GoW63MPm6hsfY395dtfoL8Pv2NPiPYeBPDltLHpPmw6fDG22+/i8tf8AZoA/Ly//AGbvElhfT2r3mmtLC21tsjf/ABNeZanp8ml6lc2krKZIJGjZl+6StfrFrv7CXxSu9cu50j0XbJMzLv1D/wCxr5J8W/8ABOv4uT+KtXZY9D+a8l/5iX+1/u0Aeo+Gv+CgHw+0bw3pFhPpPiB57OzhgkZIY9rMsar/AM9P9mvtrTv+Cj/w3njs4V0XxJuk8tV/0eH/AOOV+Ol1+zb4xsrueGQWHmwyNE225/iU8/w129h8XPD9hcW3mtdf6PIvmbYf7rfNQB+63/C7NF/59r3/AL9r/wDFVo/8LS0v/nhdf98r/wDFV+b/APw8c+Dv/PfXP/Bb/wDZV0K/8FNfgr8q+dr/AP4LP/sqAP0Ag+JOmz3EUKw3G6RlVflX/wCKrsa/Pnwr+3v8K9c8VaLptrJrn2m8vobaHdp+1dzSKq/xf7VfoNQAV5T+1P8A8m7/ABA/7BMterV5T+1P/wAm7/ED/sEy0Ael6f8A8g61/wCuKf8AoNW6qaf/AMg61/64p/6DVugAooooAKKKKACiiigArgfGvwR+HfxJ1WPVPF/gPwx4q1KKFbaO71vRre9mjiVmZY1aRGYLuZm2/wC01d9RQB+aOpWd3+zX+1V8a10D4H+OL7wZrX9iHSP+EC8JNLp6eTYfv9uzy4/9ZM33d3zeZu+aqv7MniaXxl+0f+0BrFx4f1zwrPcDw/u0nxJY/Yr6322cq/vIf4d23cv+yytX6bDAFfnN458Q+JvhL+2R8dNcf4T/ABH8W6N4j/sL7BqPhbw5Je20n2fT1SX958q/ek2/Lu+ZWr0MPiOWUYy+E56tP3ZSjuN/ZA/5rZ/2U3XP/aNP/YH/AOTTfA3/AG//APpfcVn/ALEeqSa3ofxb1CSwvtIkvPiLq87afqkPk3dqzLC3lzR/wyL91l/hZa0P2B/+TTfA3/b/AP8ApfcV69D7P+GX/tpxVftnnXwL/wCUZepf9ix4i/8ARt7R8dP+UZem/wDYseHf/RtlR8C/+UZepf8AYseIv/Rt7R8dP+UZem/9ix4d/wDRtlWP/Ln/ALdK+3/28ehftgdPgn/2U3Q//a1Hxp/5O0/Zy+viT/0gjo/bA6fBP/spuh/+1qPjT/ydp+zl9fEn/pBHWlT4pf8AbpC+Bf8Abwv/ADkD/wC6Zf8AuVo/5yB/90y/9ytH/OQP/umX/uVo/wCcgf8A3TL/ANytH/yQ/wD5E+gaKKK7jkCiiigAooooAKKKKACiiigBfxzQTmj8KypfFmi28zwy6zp8UsbbWVrqNWVv++qnmjEs1KKzbrxNpNhcPb3WqWdtOv3opLhVZf8AgNF14m0mwuHt7rVLO2nX70Ulwqsv/AaOaIuWRpUVU/tnT/7Q+w/brf7d/wA+3nL5v3d33fvfdrKXx7oMuqPpq36/blm+zeW0bL+83bdv3f71T7SMQ5ZHQUVlJ4r0eW+azXVLX7Ysnl+Q0yq27dt27f726rSatYvcNCLy3adW2tGsy7lb+7Vc0Q5ZFuimo6vu2tu2/K1OqiQr59/b9/5NK8df9uH/AKX21fQVfPv7fv8AyaV46/7cP/S+2rGt/BkaU/4kT9HaKKK+SPcCiiigAooooAKKKKACiiigBMcV+df7V3xb8J/Bf/goHp+ueMdW/sfTLj4YR2Uc/wBlmm3TNqszKu2JWb7sbflX6K0hxWlOpKnLmiTKPNHlPzG/Za8faF8T/wBoT4++JfDN/wD2nod9/YBt7vypIfM8u1mjb5ZFVh8yMv3a3v2Qf+a2f9lN1v8A9o07x34i8TfCX9sf46a4/wAJviP4t0bxH/YX2DUfC3hyS9tpPs+nqkv7z5V+9Jt+Xd8ytWf+xHqkmuaH8XNQksL7SJLz4i6vO2n6pD5N3asywN5c0f8ADIv3WX+Flr2sPUjU5f5veOGrDlUy9+yD/wA1s/7Kbrf/ALRr57H/ACiX/wA/9B6voT9kH/mtn/ZTdb/9o189j/lEv/n/AKD1U/4f/bsjP7f/AG9E+hP2+/8Ak0vx1/24f+l9tS/tf9fgp/2U3RP/AGtSft9/8ml+Ov8Atw/9L7al/a/6/BT/ALKbon/tatanxS/7dCl8MBP+cgf/AHTL/wBytH/OQP8A7pl/7laP+cgf/dMv/crR/wA5A/8AumX/ALlaP/khf/In0DRRRXccgUUUUAFZviX7R/wjuq/ZfM+0/ZZPJ8j727a23b/tVpVm+JftH/CO6r9l8z7T9lk8nyPvbtrbdv8AtVMvhKj8QeGvtH/CO6V9q8z7T9lj87z/AL27au7d/tVpVm+GvtH/AAjulfavM+0/ZY/O8/727au7d/tVpUR+EJfEFFFFUSKOhrnPh5q91rng/T76+m8+5k8zzJdqru2yMv8ADXRjoa5z4eavda54P0++vpvPuZPM8yXaq7tsjL/DWf8Ay8iafZOjPWvIdf8A+T6f2YP+5o/9NtevHrXkOv8A/J9P7MH/AHNH/ptrlxn+7yNcP/EiffFFFFfNHrhRRRQAUUVVa+t1l8priNZenls67vyoAtUVjv4q0VNQXT21iwW/ZvLW2NynmM393bu3ZrOX4keFJNUi01PEWlyanJL5C2kd5G0pkzt27VbO6gDqaK4lPjB4Nk19dGj1+1k1Vrj7ILZdzP5m7bt/76qlB8d/BF34mXw7BrQm1k3H2UW8drN/rN23bu27f/HqAPQ6wvFHhLRfHeh3OieItIsNf0a5ZftGm6pbR3NtNtZWXfHIrK21lVv95RXKwfHDw1e+J10O2/tC5vGuvsbNHZSeXG+7b8zEbdv+1T7X4wQXfiVdEi8LeKWf7V9me9Omf6NEd23c0m77v+1QB8f/APBQX4YfCz4GeEvhL4u0bwX4Y8GLY/EjSHvtT0XRIbaZbRY7mWRWaGPcy/u1bb/srXi3xr/ac+Gnxn174PaH4O8RnWdStviJo17JAbK4g2wq8is26WNV+9Iv/fVfpTa/FPULvxIukr4H8RRxNc+QdRmt1S2C7seZu3crt+avm79td/F/jvw/4Lkt/h74kmsfCnjmy8QK2k2jalcX6Wvngxrbx/NHvViys3y/dXd8y100q0qceUxnCMvePOPjR/ydn+zn9fEn/pBHSE5/4KA/90y/9ytc9rXjJvHf7SnwWutT8N+J/Bmo2I1f+zrDxDod1Z/blktds3zTRqu6GNdzbdy/MvzfNXQRO7/tqLM6+V4g/wCEK8v7Nu3Qf2Z/aP8ArN3/AD28z+H7u1a9f2kZe9H+Y4eSUfi/lHH/AJSAD/smX/uVo+C3/J2n7Rv18N/+kElNiV2/bUXzmC+JP+EK/wCWSj7I2mf2j/tfP9o8z/gO2j4V77j9p74zpZlLTUrebRm1iRv3kd1G1q32ZY1/h2x/K3+1V83vf9vf+2hy+7/26O/ZA5/4Xaf+qm63/wC0aP2QP+a2f9lN1v8A9o039myE6hqnxQuNDuX0axtfH+qw6haSRrN9uuFaPzJlZv8AVq3y/Kv3dtH7NcC65q3xRurAvokFh4/1W3urS1fet9MrR7rht33d25flX5flopyl7vujk/jPO/gXaQH/AIJv3d/5EX26Dw5r8kNyR+8jZZLvayv95WXau3/dr2v4FeB9D1X4G/DW5utNjluX8NaUzS/MrN/osf8Adrwr4U6S2u/8E97/AFlby606JfCut/8AEtsn8u23R/a4923/AGtu5v8AaZq9w/Z78GWp+Dnw11NrzUN58P6dcfZvtDeQrfZ4227f7v8As1lT97l937JVXaXvHfaj4D0/UtSlvvOvraeRtzeRdMq/981HqXhm4l1RriDxJfWfmNu+zblZf+Ar/dqWLwBpMWrLqX+kPeed5/mtcN97d/dp1v4A0G11T+0ItPX7X5nn+Y0kjfN97d96uz2f905+b+8Ub/8Atb+3G+y+KLFYJJNq2MsK7o/7yq33maoL3xXqia81rZ33h25tWk8uOD7VtuV/3l3ferct/BmiW999sTTrdbnzPM8/b827+9VqLw5pMV59qTTLNbndu89bdd27+9uo9nUFzROUuvic0XiT+y4dPt7yJpvLWSK+Xd/37/vf7Ncd4y+L+rRa9Pb6TIttZ2snl/NDuaTb97dur2CLS7G3k8yKzt4pd27csaq26vNPGXwbuNZ1ye+026t4luJPMkin3fK38TLtrmxEcRy+7I1pyo83vHY/DzxXJ4w8NLeTrtuY5Ggm2/dZl/i/8erpaxPBvheHwhocWnxN5r7mkkk27fMZv4v/AGX/AIDW3XdT5vZx5jmly83uinrXn37Q/wDyQH4mf9ivqf8A6SyV6CetefftD/8AJAfiZ/2K+p/+kslKp8Mhw+M+hf2Tf+TWvg5/2Jmjf+kMNerV5T+yb/ya18HP+xM0b/0hhr1avkT3QooooAKKKKACiiigAooooAKKKKAPlj9r39n/AOJXxT+IXwp8ZfDK78KQal4M/tfzYvFkt0kMv2yGGIbVt42ZsKkn8S87fvc18zeNfCXxg8KftZ/s/j4sP4Il8/8At/8As3/hDWvW+7Yr53nfaF/2o9u3/a3fw1+n2BivDP2iv2UNB/aS1jwhqureJvFfhPU/C32z+z73wnqEdnOPtKxrJukaKRvuwqvy7fvNnOa2p1pU9PskShGR8s5/4z9/7pn/AO5Wk+C//J2f7Rn18N/+kElU9I+C1t8Cf28n0C28V+KfGEdx8Nft5vvF2orfXaM2qeX5aybU2x/u923+87f3qu/Bf/k7L9oz6+G//SCSvapVPacsv73/ALacFSNlKPkN+C3/ACdp+0b9fDf/AKQSUfsf9PjZ/wBlN1z/ANo0fBb/AJO0/aN+vhv/ANIJKP2P+nxs/wCym65/7RrWn8Uf+3jN/A/+3Rf2Av8Ak0rwL/2//wDpfc15d+zJ8FdV+NPwN8NeMNa+MfxUtdT1L7R50en+J2WFPLuJIV2qys33Y1/ir1H9gL/k0rwL/wBv/wD6X3Nee/Arj/gmZqP/AGLHiL/0Ze0ly8tPm/l/+RKXxS/xHoX/AAyCP+i2fGH/AMKw/wDxmj/hkEf9Fs+MP/hWH/4zXn/w9/ZI+AX/AAo3wb4w8YaDaWZvNC068v8AVNQ1u6tIDNNDFuZj5you6SQcfL96m/8ACjP2Nf8AoI+Dv/C1k/8Akupt/dj/AOBF6/zHof8AwyF/1Wz4wf8AhV//AGmj/hkL/qtnxg/8Kv8A+015z/woz9jL/oJeDf8AwtpP/kuj/hRn7GX/AEEvBv8A4W0n/wAl0csf5Y/+BC1/qJ3cv7FNhNr2l63J8XPiw+s6YJRp+ov4mX7TZ+Ym2Ty5PJ3R7l+Vtv3lq34F8O+JvhJ+2P8AAvRE+LPxI8XaN4j/ALd+36b4p8Ry3ttJ9n09mj/d/Kv3pN3zbvmVa89HwO/Y1/6CPg7/AMLWT/5LpD8Df2NP+gj4O/8AC1k/+S6wqUY1Y+7y/wDgRcJ8sup9MfHL4Ia/8DPGGpfF34R6ZJqen3r/AGjxj4Dtfu6io+9f2S/w3a9WX/lp/vfe7P4efETw/wDFbwfp/ibwzqEepaRfR7o5F+8rfxRsv8LL91lr5E/Ze1X4E/Ab9t2/n8MeKvC3hzwbc/DyRXvpvEcclo1+2pQ5j8+aZgJPLjVvL3fdXdtr13xxpej+FvF/iD4s/s567onxA0sSJc+OvAvhjU4L3z1YP/p1ssbN5d18jfL/AMttrfxLz8lj8Dzy5o/EfSYDHey92Xwn0DRXOfD34haB8U/CGn+JfDV+mpaTex7kmj/h/vKy/wALL91lro6+V+A+s+MKKKKRQorkvil8UfD/AMIPB9z4j8SXXkWkX7qOCNd091M33YYY/wCKRv7tL8TfiboXwj8Jza/4gnaO3jZYbe2gXzLm8mb/AFcMMf8Ay0kZvurXJ/Db9mjxZ8S9Ttvir8UVt7XxZGC/hzwXdotxp+i27LtZbhf+WlxIrfNIvzR/Lt+7tr0cHg/rFS8vdiebjMZHDR934i1+yP8ACrxA/wAWfG/xV8cWX/CMeLtYs7W0h8NWMm2K0smHmR/atv8Arrr5fmZvu/Mq/wCz9clRtx614F8J/Eg8OfEvWfD+qG7hNxa2cdsL5ctayK1zttZJv+Wny/6uT+JVX+Lr78e1fY4igsNJQjt7tj4qFaVf95P4gJCqa+eviX+11o3hu/n0jwrZN4p1WJvLlmSTyrSFveT+L/gP/fVcx+1X8Y7yXVX+HugTta5jWTWb2GTa6q33bdf95fmb/Zb/AHq+frW1hsLdYYI1iiX7qrXxmaZxKhL2FD4jysVjvZS9nT3PRNR/aT+K+ruzxazpeiI33Y7LT1l2f9/N1TaT+098U9GlD3F7pWvRgcw3Vn5LH6NHtFedUV8r/auM5ub2p5X1uv8AzH138Jv2oNA+ImpQ6NqMMnhrxJLhUsLpt0dw3P8Aqpfut/u8N9a9uyK/My/sIdRh8uVfutuVl+Vo2/vLX1b+yx8aLzxnaXPhHxFN5/iHSolliumPzX1v03t/tqdqt/vL/tV9hleb/W5exrfEevg8Z7X3KnxHtvirW4/DPh7UdWli85bKB5/KX78jKvyqvu33fxrzXwzoC6nd2HhO5SG6tdJC6lr+WLedqEuZlhZf4l3SGb7zfcjFXvjF4mis7/QdNWG4vXW4XUntbZdzStDIgt49v+1cNG3+7DI38O5dK31OL4b6Fp2lSn+2PFWptJOLS1yHvLlm3TSf7EKs33m+VV2r/dU/aQjKFK63f9fgdkpRlU1+ydN4k8R2PhqxM93JIXkYJb28A3TXMn8Mca/xMf8A9eBXKn4fP43aTUPGCNOJYmjttEST9zYBl2s25ceZNj/lp/D/AMs/7zavh7wY0Gpf27rcy6j4jddnmgnybNT1jtlb7q/3m+8+35uyr2WMVj7T2X8N+93/AMjbl9p8Rx3gDVrq4s7vRdVkL63o7rbzysf+PiPrDcf9tF+9/trIv8NQ+Av9P1nxdqucpcambWH08uCNYWH/AH+Wfn/gP8NQfEIHwvdWvjSBGZNOjaLU4o1y0tieWb/eibEn+75i/wAVaHwwtHsPAOim5H+l3EAvLjadw86Y+dJ838XzSN83erny8jmuv9MmPxcsvsnH/FFrW2+KPgC7lV2jgkl+2snCrGzRxwNJ/wBvEkW3/tp/tV2vxI0m41bwPqqWiB7+CNby0X1uIXWaL/yJGtc9/YsPjzVfHQu2dbaZE0GCRD80apHvkkX+63mTMP8AtivtXSeBdfm8ReE7C6u1VNQVWt72NeiXEbFJl/77Vq0nPlVNr7P/AO0ZqPNKX97/APZOD+LOtTX2i+D9e8PXP2a81eX+zLa7H/LFL2Hakn/AZFgb/gNeqaTpVtomlWmnWcYis7SFIIY1/hjVdqj8hXz9f6TfalDr2kKN0XgBZrywg4w9z5n2iyA7/u7dVj7f64/e/h+hbK7h1CzguYGDQzossbeqtzSxMVThGMf67FUZc0pSLlFFFcZ0hRRRQAUV+J2u/wDBYr41XHiue90fT/DFpogmb7NptzYSSZh3fKssnnbmbbt3FWXnptr9hfhb41i+JXw08JeL4oTbR6/pFpqqQN96NZ4VlC/+PUAdZRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHkHx0/5G74P/APY3J/6RXdev15B8dP8Akbvg/wD9jcn/AKRXdev0AFFFFABXC/Ej4o6X8NEsDqlvdTi8ZvLNsqsQV2/3m/2q7qvi3/go18btN+Ddt4DbUNNvNQ/tCS7WP7Myrt2rH97d/vUAeOft7fta+EbPXPB+/T9W+a1uPuwx/wB5f9qvzq+PHxH034ta/pl9pMNzb29ta+RIt2qq27du/h3Vt/tUfGnTfjJqPh2bTtPutPXT4ZopFuWVt25l/u/7teK6fL5SN/vUAe2fBX9lbxZ8Y/Ck+t6Ne6Xa20N01sy3c0ituVVb+FW/vV92/sefsf8AjLwh4L163vNQ0eVptQWRfImk/wCea/7NfMv7J37Q+k/C/wCG95pN7pN9eSyalJcrJbMu3ayqv8X+7X1H4A/4KQeD/Aen3NrdeEdcuWuJvMVoJofl+Xb/AHqAPq/wNP8A8Ke0eXRdZ/0m5kma5VrT5l2sqr/Ft/u1Q8UftveB/hzq7aLqWm61LcrGs+62hjZdrf8AbSvjj4m/8FRPBN74gikXwX4gX/R1X5pof7zf7VfNHxW/bF8PePvF8urWug6nbQNDHF5c0kZb5aAPtP4n/wDBTb4Y2Xja+hfRfE25Vj+7aw/3f+ulfBvxs/aK8OfEH4qeIPEOnWWoR2N9Mska3EarIv7tV+b5v9mvGfHnjCDxb4outSht5IIplVRHJt3Dau2vSvBP7Ket/ELwpp/iC11rT7aC9VpFhmEm5fmK/wB32oAXTf2ffEPxisl8V6LdafbafeFhHHdyssi7flbdtVv7tfQfw8/4JwfErXPBemX1vrHhtYpo2ZVluJt33m/6Z19GfstfsTeJF+CWhj/hItJ/1lx/yzk/57N/s19mfD/4UXvhHwZpmj3N9bzz2qMjSRq21vmZqAPNfg9+zp4j8I/Cvwvot5eabLc2OnxwSNBI21mX+78tfRuiWkmm6RY2su1pYYUibb/srU+n2ps7KGFm3tGu3cKtUAZNxpkstw0isu1mryPVvgrreoateXUdxYpHNM0ihmbj5v8Adr3KigD88dW/4J+/EO91K+uI9U8P7ZppJF3XEn8Tf9c6+HtR/YF+IEUl5I2reH/3bSN/x8Sf/G6/e7tXzhf/ALMes3S3O3WNPXzt23csn8VAH4Zf8KE17/n6sf8Av43/AMTVi0/Z/wDEFzeQRi60/dJIir+8b+Jv92v07/4dkeNf+hw0H/vzN/8AE1NYf8E0fGdre20zeLtBdI5lkK+TNztb/doA8W+H3/BOL4leHvHnhrVLjWPDbQWOqWl3IsVxNuZY5lZtv7v/AGa/X2uItfAt1BcRSG6hPlsrfdau3oAK8p/an/5N3+IH/YJlr1avKf2p/wDk3f4gf9gmWgD0vT/+Qda/9cU/9Bq3VTT/APkHWv8A1xT/ANBq3QAUUUUAFFFFABRRRQAUUUUAFFFFAH5y+HvAf7Qvwk8cfFmPRfgX/wAJho3iLxzq3iKx1P8A4S7T7LfDcSfu/wB2zM33Y1b5trfN93ik/YFOf2TPAv8A2/8A/pfc1+jQFfnZ8Iv2UP2rfgx8O9K8HaLqPweutN00S+TLf3GqvORJM0zbmWJV+9I38Nehh8TyS/eHLWpc8bRPNPgX/wAoy9S/7FjxF/6NvaPjp/yjL03/ALFjw7/6NsqPgX/yjL1L/sWPEX/o29o+On/KMvTf+xY8O/8Ao2yr0f8Alz/26c32/wDt49C/bA6fBP8A7Kbof/taj40/8nafs5fXxJ/6QR0ftgdPgn/2U3Q//a1Hxp/5O0/Zy+viT/0gjrSp8Uv+3SF8C/7eF/5yB/8AdMv/AHK0f85A/wDumX/uVo/5yB/90y/9ytH/ADkD/wC6Zf8AuVo/+SH/APIn0DRRRXccgUUUUAFFFFABRRRQAUUUUAFcf4a8L6DdT65KY7PWJW1SZpGns/mhb5d0fzfe2/3v9quxxzXOeCrW1tf7c+y3n2zzNWmkm/ctH5Mny7o/9rb/AHqwlHmlE0j8JoXXhnSb+4e4utLs7mdvvSyW6szf8CouvDOk39w9xdaXZ3M7felkt1Zm/wCBVpUVryxJ5pHK6tZ6Tb+OPD1w8MkWqzfafJlgVdsm2P5vMb7zfL92uma3jlZGeNWZfusy1g63/Z//AAmHhr7R9o+3f6T9l8vb5X+r+bzP4vu/d210Y61lT+KRUvslB9B02W6W4fT7V51k81ZWhXdu/vbv71Vm8H6K2oLfNptv9sWTzvPVfm8zdu3Vr0VryxJ5pHOP8PvD76wuqf2f/p3nfafN86T/AFm7du27tv3qE8C6emsf2kk14s/neftW6byt27d93+7XR0VPs6f8pXtJHOw+DWi1b7cmuax/rvPa2a6/cfe3bdu37teGftu6Td6V+zf491C51KXU7RhAv9n3ChYl8y7jVWXHzfu2ZWX/AHa+la+fv2/P+TSvHX/bh/6X21YVqcfZyKpyl7SJ9rxeFvHkHic3b+OLe50NrozHTTo8cbrCW/1KyBt3yr/Efmot7H4kx+JVkn1Pw9c6CbrfJC1vKs6w7/uqw+Xcq/xf3q9For5c9o84s7/4mL4mSC80vw9JoLXLK1zb3EqzrDu+Vtrfxbf/AB6nW/i3x4PEqWtx4EhOjvdeV/aUWsR7o4d2PMaPbuY7fm2rXotFAHndt8QvEkviUaXceAdSgtmufK/tJbqN4fL3bfM/9m20WvxcM/iZdFl8HeK7bNz9nGoy6d/of3tqyeZu+61eiUUAeeWvxs8P3PiddCaDVba+a5+yK09hIsTSbtu3f92nWPxx8Eaj4kOhW+vI2r+f9l+ytbzLmXdt27mXb96vQary28UzK0kaO0fzKzL92gDmLP4oeEb/AFptJh8Q6c2pi4a3+yfaFErSL8pXb/FWjb+M9Au7o29vrmmz3Qk8vyI7uNpN27bt27vvbvlqVfCOhi9W8Gj6f9sQ7luRax+Yrf722sqH4WeELbVodVi8N6XBqMUvnR3MFqqOsn97K0AdNFcRTMyxyI7R/Kyq33asV5/bfBDwTbeJY9fh0OMavHcNdrdefN/rWbdu27trVHZ/BHw5pniWPW7VtSiuFuPtRh+3yNCZN27cyM3NAHoY6V+c3h3wJ+0L8JPHHxai0X4Ff8Jho3iPxzq/iKx1L/hLtPst8NxJ+7/dszN92NW+ba3zY28V9raf8JBpXiddYh8X+K5gs7T/ANm3Gp+baNu+8vlsv3fm/vUll8ONfsfEcep/8J9rF1ZJP5zabcxRtG0f/PPK7f8AvqtadSVKXNEmUYzjyyPh79imTVJNH+LkmtaX/YetN8RtXe+0v7Qtz9jmxD5kPmL8sm1ty7l+VtteCH/lEr/n/oPV9hxfs1fG7wXr/jifwR/wgEFvr2u3muLJq2q30n2m4mb5ppoVtfkZ1Vd0ccm1f4enzfHmqI83/BM+WawItvCxhUi0l+a5WT+19v3vu7Wm+b/dr04Voyhy/wB2RyShyy/7ePoX9vv/AJNL8df9uH/pfbUftfdPgn/2U3RP/a1Yf7cMniNv2ZfHSarFp40oLaHzrRm83/j9h8v5W/2tqtWl+0gb7U7z4VRa6kGjW1v8Q9Ins549032ybzJFWHav+r3KzNub5fl/2q66lT3pf9umMF7sCz/zkA/7pl/7laP+cgH/AHTL/wBytJZl5f2001Sdfs2pf8IR9gOk7t0i2/8AaO5brd93y92F2/eotTLcftorrkqLAzeCP7J/s5j/AKWv/Ew8z7V5f/Pv/D5n975aPaR/8mFyy/8AJT6EzQK5y18dWN1qi6ebe+tp2k8v9/asq7v96sLxL8X9J0iznWwb7ZqayeX9maNl8tv4t3y11SrU4x5uY5/Zykd/nFFeWeCvjJNrOsQafqtrDE9xJ5cM9tuVVb+FWVq9UxSp1o1480QqU5UviEqprNvcXmj31vayeRcyW8kcMu7btZl+Vt1W6K0EcrZW/i6y8OwW/maTPqscix+bO0zK0Kr95m+95m6rH/FXf2P/AMwX+1ftH/TbyPJ2/wDfW7dXR7qN1R7P+8PmOcz4u/sf/mC/2r9o/wCm3keTt/763bqM+Lv7H/5gv9q/aP8Apt5Hk7f++t26uioqvZ/3g5jnf+Ku/sf/AJgv9q/aP+m3keTt/wC+t26qGjf8JtbtbQ6iul3MSybZrncyysu77yqqqv3a7LdRuqfZ/wB4OY5zb4sbWfmk0ddNW4+6qyeY0O7/AL53ba89vhcR/tmfAS3vTHNqFxda3LpV3GNv2OFbPdcRyL/y0aSLEe7+H71eyda8j17n9uv9mD/uaP8A02Vy4yP7mRvh5fvD6xXwZ45Pif7dJ8Qj/Y327zxpEejw/wCo8zcsPnfe+78u6l/4V54hk8Uf2rL491NrJbz7QulxwRrD5O/d5Lf3l2/Lur0WivnD1Tzo/Cm4k8U/2zL428UsqXn2yPTY9Q8u0/1m7yWXb80f8O3+7R/wpnTG8U/27LrXiCaf7d9vW1k1JvsySeZu2rH02/w7f7tei0UAedp8DvCieKf+EhNneNqf2z7flr6bb527zN23dt+9/D92pI/gb4Hh19dbTQYk1Vbz7etz5snyzeZ5m7bu2/f7Yr0CigDkI/hV4Qj1ptWXw7p/9qNdfbftZhBk87du8zd/e3fNV2LwN4bj1FtQTQNMjv3m+0tdLZR+a0u7d5m/bu3bvm3V0VFAGbFommxXb3UdharcsdzTLEu9m/3qvqqqPlGO/FPooAKKKKACiiigD5Y/a9/Z/wDiV8U/iF8KPGXwyu/CkGpeDP7XMkXiyW6SGX7ZDDCNq28bM2FST+Jf4fvc183+EPDvxI8Nft1zWvxPfwrJ4hk+G5lt28JG5a1+zf2kqru+0fN5m5ZP9nbt96/TU8Cvlj9oD9kPxb8VPjhafE3wZ8Vz8OtSi8OL4ckhHhuHU/NhW6kuWbdJMqruZ1/h/wCWf3vmxXTRrSpy1+EznDmieGf83/8A/dMv/crSfBb/AJO1/aN+vhv/ANIJKzPDfw08W/Cr9u99J8ZePT8RdTl+G/2qPUzo0OmeTC2qBVh8qNmVtrRs27/pp/s1p/Bb/k7X9o36+G//AEgkr2qdSNTllH+b/wBtPPnHl5o/3Rf2QPu/G3/sput/+0aP2Qf+a2f9lN1v/wBo0fsgfd+Nv/ZTdb/9o0fsg/8ANbP+ym63/wC0aql9kJ/bPPPgX/yjL1L/ALFjxF/6Nva+hP2d/wDkgHwz/wCxX0z/ANJY6+e/gX/yjL1L/sWPEX/o29r6E/Z3/wCSAfDP/sV9M/8ASWOij9n/AAkVNpf4j0Ciiiu45gooooAKKKKACiiigBT1rz79of8A5ID8TP8AsV9T/wDSWSvQT1rz79of/kgPxM/7FfU//SWSsqnwyLh8Z9C/sm/8mtfBz/sTNG/9IYa9Wryn9k3/AJNa+Dn/AGJmjf8ApDDXq1fInuhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAHiHxp/Y2+EP7QviiDxH4+8If2/rVtZrYQ3H9p3lttgV5JFTbDMq/ekkO7bu+b2r4t+HVl8Lv2Wv2rf2gPB9pqmj+BvDcP9gf2bZatq+zcGsWmm2vcS7pP3k277zbdy/wCzX6gDpXnPij9nr4XeNtcutb8R/Dfwj4g1q7ZfP1HVNCtbm4m2qqrukkjZm2qqqMngCtaVT2U+YmceePKfDn7PfiLSfFv7Tn7QmqaLqlnrOmXH/CPeTfWFws0Em2zkVgsi/K3zKy/8Bq9+yD/zWz/sput/+0az9B1f4d/Av9sr9onQ5L3wx8PdH/4pw2GmtNb6Zbf8g8vL5cfyr96Tc23+KT/aqz+xlqNrqun/ABivrC6hvrG6+JGsz29zbSCSOaNlhZWVl+VlZf4q9vD1Obll/iPPqx5VMn/YD/5NK8C/9v8A/wCl9zXnnwL/AOUZepf9ix4i/wDRt7Xof7Af/JpXgX/t/wD/AEvua88+Bf8AyjL1L/sWPEX/AKNvauPwx/w//Ikv4pf4h/xx/wCUaGm/9ix4e/8ARllX0F/wz18LP+iZ+Dv/AAQWv/xuvn344/8AKM/Tf+xY8Pf+jLKvsGtqcYyfvfyx/wDbiZtqOhwH/DPPwr/6Jn4N/wDCftf/AI3R/wAM8/Cv/omfg3/wn7X/AON16Bg0YNa+zj/KYc8zz/8A4Z5+Ff8A0TPwb/4T9r/8bo/4Z5+Ff/RM/Bv/AIT9r/8AG69AwaMGj2cf5Q55nn//AAzz8K/+iZ+Dv/BBa/8AxuoP2FvDmk+FP2nP2ntL0TS7PRdMtz4Y8qy0+3WCGPdZ3DNtjXhcszN/wKvRulcV+xj/AMnaftTeo/4RX/0gnrz8wjGNM68LKTm7knxu+CPiD4AeLtT+Lvwj0yTVNFv5PtPjDwHaL/x+f3r6yX+G4Xq0Y/1n+9XcfD34heH/AIoeD9P8S+GdQj1LRr2PzIZo/wCH+8rL/Cy/dZf4a+kiM18Z/G/4Ka9+z54u1T4ufCTTJNV0HUZPtHjLwFaLj7V/e1CyX+G5Xq0Y/wBZ/vV8djMH9Y96PxH1OBxvsP3dT4T14da5D4o/FDQfhH4Sn1/X7hlhVlgt7SBfMubyZv8AVwwx/wDLSRm/hrndW/aT8Bab8JbT4ixauNS0K9VUsIbJfMuru5b5Vt44/vedu+Xb/D/FWz8APgBr3iXxXZ/F74v2qL4sVW/4R7wqD5lt4ahbuf8AnpdMPvSfw/dX28fC4KVaXv8Awns4rGRoR934jivh98DPG3ib4neDvij8R54NJ8S3Iuh4f8Lzwfa7Pw8uxZIzIu5d90yLJuZWXbhVX7vH1KfEXinQxjV/Di6lAp/4+9BuPMY/7TQSbWX/AHVaSn/EfFqPDGpY/wCPLXLXn087da/+3FdkORwcivr48lOlCMY+6fFycqk5TlL3j5/8WWugfFH4hSWtrqJ0/V5NE8uJbuGSGVWWbdskhk2syt5nb5vl3KysqtW14C+Kd3on9oeGvG8bWmu6XbvPHMW3G/t0DNuVv4mVVPzfxY3fK25V6PxfoGna98SvDtvqdha6lZz6VqEbQ3cKyru8y0ZThv8AgVch8ZfgXpep+BdWmsNQ1OxlsLSe5trf7QZow6ox2r5m5o1O0DbGyr/s16EqtKVL2dTt7v8AdOPlqRlKpE+P7HUJ9clvdbvCDe6rdSXsrBt3zM33atVneH2VtDsdv/PFf/Qa0a/AqkpSqSlI+Xl70gooorMgKv8Ag/xFJ4K+JHhPxDEzKtvqEdtcbW+9byfu5P8A0KqFZniGKS60+KGL5Z5riGONv7reYtdeFly4iMv7xrTlKMoyifVOgeLbnxt8WNc1TTLCTULuGdrLTI5NrW8KRboTeTMrblVS1x5a8NJ58qqvDSV7b4d8HWnh2a6vCWvtXvtv2zUZf9bNtztH+zGu47VHC5+prmvg3p2leE9Fj8KwaadG1bT4V+020reY1yv3ftCyf8tlb+9/D90qv3a9K6dK/b8XUXPy09In1lCD5eaXxD6KKK4jqOG+LBF54QfSxjOrXUGmlS2N0c0irL+UfmNt/i27f4qzPDmsw/D6DWtB1N2Sz0e3k1DT5XP39PXkrz/zxb93/u+W38VaHiZ11D4h+E9NG5hZi41aUKvyqVj8iMMfc3DFV/6Zsf4awfjtp/8AaWj6ItrayXmsPfbbe2icqZ4hGz3ELH+60UbL83G7y/4torvpcs1GlL4X739f+AnLU91yqR+ydj8OdIuNF8E6XDdoY7+aNru8Qf8APxMzTTdf+mkj1iR6jbeA/Guvx30y2ukX9o2uLPJwsbwqsd1+G3yJP+BSV2Wia1a+INJs9Rs3820uolmjb1VhmvLP2iYra903QYZrc3pgvft9zbqm7dp8K/6Zu/2drKv+9JH0+8uVFe1rOE/tFVP3dPmj9kd8OrW40fxRFc6jE0c/i/T31C4jcj5J45M7Pr5NxHH/ALtt95vvN13wmJj8EWNg5Jk0mSbSmLfeP2eRoVb/AIEqK3/Aqg+JRSz07RvEUTBhpGowXbOp48iTMMzfQRzM3/Aal8JMNO8c+MNMHCzSW2qoo7LLH5Lf+PWzN/wKtZy9tTdR/wBcun/pMohCPs3ynb0UUVwHQFFFFAHyfr3/AATN/Z68R+M5vEt54MuftU93Je3VtHqlyLe4kZtzbk8z5V3fwrtHzY+7X1BpmlWeh6ZZ6bYW8dpY2cKW9vbxLtWONVCqq+yrX5TeJP8AgtlrsfjO9OhfDnTZ/C0cjLbLd30i3kyq3+sZlXau5R93a23d95ttfp/8NvG1r8Svh34Y8XWUE1vaa/plrqtvBc7fMjjnhWRVbbxu2tQB1VFFFABRRRQAUUUUAFFFFABRRRQAUUUUAeQfHT/kbvg//wBjcn/pFd16/XkHx0/5G74P/wDY3J/6RXdev0AFFFFABX5tf8FjNIbVLL4V7ZFj8ubUf4f9mCv0lr5V/bh/Zb1z9peHweui61p+kDR5LlpDfrI3meYse3bt/wB2gD8KvHGlNpc9orSeaXVj92ubjl8tfu199/Gv/gmf4y0O70tJ/GGgy+ZHIy+XHN/eX/ZrxPxJ+w74l8NXUUM/iLSZTJHvzGsn/wATQB434Z8cx6DYNbtaNNuk3blk21euPiVDO6t9hkX/ALaV6fpv7E/iLUYWkXxBpaYbb8yyf/E16Z8Of+CXHjT4k6dd3tp4y8P2i283kss6TfN8u7+FaAPnrRPAcvxStW1aG8j09Y2+zeXJH5n3fm3f+PV6H4S/Ytv/ABVpC36eKrW1DSNH5bWbN93/AIFX2H8Lf+CWfjjwv4ens5fGnh2ZmuGl3LHN/dX/AGa928CfsNeKPDOgLZz+JNHnbez74o5P4v8AgNAHxN4O/wCCUeseMNAg1SP4jafapMzL5baXIxXa23/npX2T8If2A9S8IfDjRNHfxnZ3LWsbL5q2LLu/eM396vovwB8HdR8J+F7XS7jULWeWFmZpI1bb8zbq9L0jTH07T4Ld2VmjXG5aAOb+E/gOT4deA9O8Py3cd89q0jecke1W3Mzfd/4FXaKNq0iLsWn0AFFFFABRRRQAUUUUAFFFFABRRRQAV5T+1P8A8m7/ABA/7BMterV5T+1P/wAm7/ED/sEy0Ael6f8A8g61/wCuKf8AoNW6qaf/AMg61/64p/6DVugAooooAKKKKACiiigAooooAKKKKACiiigD80vHX7CPxL+Bn7MPjXT9N/aA+0eEtB8O6tdNoQ8GWyfaofJmmmh+0NO0i+Zucbvm27/lrjfjp/yjM07/ALFjw7/6Msq/TX4ieCbP4leAvEnhPU57i30zX9NudKupLQqsyRTRtE7RllZd21jt3Kea/Oj9tL9hzQ/gd+yR4t13Svib8TNYtdFi0+C10HW9fjn0wxte28Ko0Cwr8qK25VUjayr/AHa66dfljKMjKUOZxsdJ+2B0+Cf/AGU3Q/8A2tR8af8Ak7T9nL6+JP8A0gjo/bA6fBP/ALKbof8A7Wo+NP8Aydp+zl9fEn/pBHXtVPil/wBunnL4F/28L/zkD/7pl/7laP8AnIH/AN0y/wDcrR/zkD/7pl/7laP+cgf/AHTL/wBytH/yQ/8A5E+gaKKK7jkCiiigAooooAKKKKACiiigBc81zngq1tbU659lvPtZk1aeSb9y0fkyfLuj/wBrb/eroutctF4S1CwtNQj03WvsM95qUmoNP9lWTarf8s9rN/49Wcubm5uU0j8J1NFc7/YniD+x/s//AAk3+nfaPM+2/wBnx/6vb/q9v3fvfNuo/sTxB/Y/2f8A4Sb/AE77R5n23+z4/wDV7f8AV7fu/e+bdRzS/lDlj/MGt/2f/wAJh4a+0faPt3+k/ZfL2+V/q/m8z+L7v3dtdFXOWHhS4+2affatq0mp31jJM0MqwrCu2RVXayr/ALv/AI9RpOg65a6hFcX/AIkk1CJd262+xxxq3y/7NRHm5vhCXL/MdHRXOaT4Z1Kw1CK4uPEV5fKu7dBLGqq3y0aR4Qm0vUI7qXXtUvlj3fuJ5v3TfLt+ar5pfyhyx/mOkwPWjA9a5zSPBMOkahFef2tq15LHu+W7uvMVvl2/MtJpHgax0bUIryK4vpZ493+vumZW3Lt+ZaXNU/lD3TpK+eP2+pU/4ZO8dRiRd/8AoHy7v+n+2r2TSfh9ouiahFfW9vJ9ph3eXJJcSNt3Ltb+KvAP24/h/oOi/sseNbqx09YLmP7GUk8xm2hr62X+Jqxre09jL3SqfL7SJ+ktt4k0m7uIoLfUrOaeX/VxRTqzt8u7hf8AdGap2fjnw3qeoR6daeIdMur2X5o7WC9jaV++VVW3fwtWfoHwk8HeFdUi1LSvD1nY38Jby54lwy7l2tt/4DVrRvhv4U8O3cd3pfhvS7C8jJMdzBZxpKm5drbW27hxXy57QzSviZ4S13VItO03xHpmoajKW8uC1uVlZtq7mxt/2Rmqeh/GPwZ4l1m20vSdftb7ULrd5UEG5i21dzfw/wB1a2dO8FeH9Inin0/QtMsZ4uI5La0jjaP5dvysq/3avWOiabp7eZaafbWrf3oIVX/0GgDjvD/xw8D+LfEFtomka/HfaldbvJgW3mG7arM3zMu37qtTfDPxx8KeMdettI0y5u5L243CNZbGaNflVmb5mXb0Wu9t7eG1XZDGkS9dqrtqegDzrw18Z9H8X6zBp2n6drYuJFZvNn05ookwu7azN93dtpPDHxdj8V6zFp8HhLxXYrMrMt7qGl+TbDC7tvmbvl+7t/3q9GooA878NfFC+8S6zBYy+B/Emjq6s32u/tlSJdq7tu7d/F92m+GviF4k8Q6xBa3PgLUtFspA4a/vLqMrGyruXcq5ba33d3vXo1FAHnXhfxn431fW7eDVPh62h6bKHLag+tQzbPl3KGjVd3zN8v8As5pfDPiP4g6nrcEWt+D7LRtOwzPcrqazNnb8qhVH97bXolFAHnnhjUfiVdaun9uaRoFhpjRtu+zXMkk6vt+X/Z27qb4ZPxQbVkbX18JR6WyNuXT2umuFbHy/e+X72N3tXotFAHnXhqw+JI1hJfEGp+HptPWNv3dhbyLI7bfl+Zv4d3zfhXwP+1h+ylq/7Pn7DfiOxtPF/wBr8L6M9qzaIbRcSrLqULbfOb95/rJN3/jtfp7XnHx5+C+iftC/CjXPh94jur+y0bWDD9om0uSOO4XyZ45l2tIjr96Jeq9KuMnH4QPgr9tvRtcsP2X/ABrNqXiL+1bNfsHmWn2GODzP9Ptv4l+7Vr9prStS0d/hG17rLav9o+IuiQx+fbqv2dvMZvMXb/F8u3/dZqh/bl/Yr074S/sueN/FsHxX+KfiSXT/ALDt0vxH4jW7sZ/MvreP95EIV3bd+5fm4ZVNbv7X/wDzRP8A7Kbon/tavWpyjX5pR/unC4unyxGaWj6b+2augSv9uuT4DbUG1af/AI+2Vr/y/s+7/nnu/ebf71GloNK/bMXw62b4DwI2orq12fM1D5r7yfJ87/nj/Ft2/e+al/5yAf8AdMv/AHK0f85AP+6Zf+5Wur2cf/JjHml/5KewaX4Gs9IvEulvNQup1VlVrm6Ztu6uX8W/Bq1vNPVtGZoLyNt225mZlkX+7833a9Korplh6co8vKc8akoy5jxbwJ8J9WtPEFtfavCtnBayeeq+YrNIy/d+7/tV7TS9Dikoo0Y0I8sQqVJVJe8FFFFbmYUUUUAFFFFABRRRQAp615Dr/wDyfT+zB/3NH/ptr149a8h1/wD5Pp/Zg/7mj/021w4z/d5HTh/4kT74ooor5o9cKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPlf9oH9kLxb8VPjjZ/E3wZ8Vj8OtSi8OL4dkhHhyHU/NhW6kuWbdJMqjczr/D/yz+981fP37PvgzXfh5+09+0NoHiXxV/wmuuWv/CPG41w6elh9p3Wcki/uI2ZV2qyr/tbd38VfpMTXy/8AEn9gjwx8R/ip4o+IEfxF+I3g/WfEX2UahD4V1uKyt5Ps8CQx/L5DM3yp/EzfMzetdFGtKlKMjOcOeNjwX9kD/mtn/ZTdc/8AaNL+yBx/wuz/ALKbrf8A7Rpn7G/h1fCFt8Z9Bivr3VY9K+Jes2IvtTm867uFj8mPzJpPl3SNt3M38TU/9kD/AJrZ/wBlN1v/ANo17tP3o0jz6n2zzz4F/wDKMvUv+xY8Rf8Ao29r6E/Z3/5IB8M/+xX0z/0ljr57+Bf/ACjL1L/sWPEX/o29r6E/Z3/5IB8M/wDsV9M/9JY6KP2f8JFTaX+I9AoooruOYKKKKAPPNG8JaH4yvtevNR0mHz4dUmtt0Ekke5V2/My7vvV0OrfDvw/rmoS317p/n3Um3zJfOkXdtXb/AAtR4K1H+0v7cxa29t9n1aaD/Ro9vmbdvzN/eb/aro+lc1OnTlH4TaUpcxzer/Dvw/reoS317p/n3Um3zJPOkXdtXb/C1Zvi7w94ftdc0rWLq3uF1C41K2jjntpPvSfw7lb5dvy/w/NXbYzXN+NP7P8A+JH9v+0f8haH7P8AZtv+u+bbu3fw0VKceX4QjKXMGkeErjSdRimXxBql5Au7dbXs3mbvl/vVwHxw0DXbH4JfEaS58SyXtqvhjVd9vJZxr5n+hyfxfw17FXAftDn/AIsD8TP+xX1P/wBJZKJU48ooSlznqv7Kdl4wf4Q/Cu9GpaYvgyXw1p0lvpnkN9pt7drJfIj8z+Jl/dhmP3vmrv8AwzN8UYtbt18R23heTSvmaeXSZLjzR8rbVVZP9rbWf+yb/wAmtfBz/sTNG/8ASGGvVq+VPbPN/C/iP4gza3b2uu+DrOz08iTzNQstUV/LYLuX923zNub5f/Hqf4Z+IPiXVtagstV8A6lokMiu73jXUc0SKq7h93+Jm+XbXotFAHnPhv4wjX9Yj0+fwh4q0PcrFrvVNN8q2XarM37zd/s07wx8bfDfinV1063XUre8aNpFju7CSL5VXczZ2+1eiUUAcH4Z+NPgnxjfx2Oj6/Bd3sisyw+XJGxVV3N95V/hFaej/Enwp4gn+z6X4j0y/ufmPkW95G0nAy3y7t1bZ0uzabzTawmXDDzNg3fN97msyz8DeG9OvlvbTQNMtrxVaNbiCyjSRVb7y7lWgC7YeIdM1R1jstSs7x2XcqwTrJlfX5a1K4rR/hH4O8Paj/aGmaBaWN4FZfMhUqQrLtb/AMdaqHhn4F+D/BerJqWh2Fxp1yqOo8u9mZfmXazbWZvmoA9Eorznwv8AByy8Iah9psPEPiTZ5ckf2S41JpYPm/i2sv3l3HbS+GvhrrHhvVkupfHOuavaxxsq2l+VkXLLtDM38W371AHotFedeGvCfjvQ9S83UfHUfiKz8uRVtbjSo7fa+P3bbo/mb/apPDun/EuzvmOsatoOpWJhfb5VrJDL5u35f+A7v+BUAejUV514avfiXHqJTxBpnh97FY5G8zS7mXc0ir8q/vPuqzf980mgeLfHl/fS2+s+AI9MhWF5EvItZhlWSQD5Y9u3cu77u7tQAnin9nr4W+Ntcutb8R/Dbwj4g1q7ZfP1HVNCtbm5l2qqrukkjZm2qqqMngCvzg+EP7Qnwn/Z28XfGzwh4g1m38LPD8SNbksdNtNLuGgitFkWKMRrBGyqq+Wyqv8ADtr9IPDvxN1nVdSe01XwHrejItvJL577Zo2ZOsfy92/h/vUvhz4w23iG8ktJfDHifRHSF5g2r6Y0CsqruIVtzc1vSqSoy5omdSnGpHlkfFH7AZ/4xK8C/wDb/wD+l9zXnnwL/wCUZepf9ix4i/8ARl7Wh+zt491r4D/BTw34I1j4aeM9b1rTWu/O/wCEds7e6Uq11JJu2+csm1VkXczLtX+KofhPazaB+wJrXhG/X7N4lh8Na8smm7g0i7mu2X7vy/dZf++q9inUpyjGPN9n/wCROFxlzS/xFf44/wDKM/Tf+xY8Pf8Aoyyr7DHWvjr453MMf/BOqDSPPiOq2nh3QIbiyDr50UizWSsrp95WVvlr6+gvLe6H7iaOX/rm26uqjLX/ALdj/wC3GNb4SaiimsyxRszttVfmZm/hrqOcdRXmH/C9dP8A7S8n+z5vsO7b9p8z5v8Ae2//AGVemxyxzwrJE2+ORdyuv8S1hTrU6vwmkqco/EOriv2Mf+Ts/wBqb/uVf/SCeu1riv2Mf+Ts/wBqb/uVf/SCeuPMP4J0YT+Iz7Qooor589Q+atY/Yf8Ah3ZeP/E/xB0TSXh8TXsElzYWRk/0Cx1Jl+a8hg+6s0hWLc3+x/tNXv3hrW4fEnh3TdVg/wBRe20dwn0ZQ39a034wD3rjPhmTYWOr6Gx+bR9UuLdQP4YZD9ohH/AY5kX/AIDWifNTt/L/AF/kR9sl+LUDy/DjxBJEm+a1tWvYV9ZIf3yf+PRrXU2s8dzbxyxMHjddysO4qO/s4r6zntp13xSo0br6q3Fc78KruS9+G/htp23XMdlHBMf+msa+XJ/48rVWsqPlF/8ApX/7IfbIfFR8rx54Jm/56TXdt/31btJ/7RrrZYY7iFo5FWSN12srdxXI+PVEWt+CLj/njrf/AKMtbiP/ANqV2dTVd4U/L/5JhH4pH5u6z4Xn+H3i7W/ClyGVtOum+zs3/LS3b5o2/wC+WqGvrj9or4Dt8TNPt9c0Ly4PFunDbC8h2rdw55hdu3+y3bn+9Xx6l3JHfz6bfQSabqlqzR3FlcrtkjavyrNMvlhK3N9mR8tisPKhU/ulqiiivDOAK6j4OeEZfiB8YfD+npH5lnpMy6tft/Coj/1S/wDAm2/LXKafDf8AiTXYdC8P2jatrc7bUt4/uR/7UrfwqtfbXwH+DFp8H/C7xPIl5r+oMs+p34H+tk7Kv+wu4hRX0eT5fLE1o1ZfDE9TB4eVSpz/AGTr/FfhO18UWUXzyWd/bMZLPULb5ZraQ/xL6j+8rfK38QrP8L+KL2K/TQPEkSWuuKrGGeLi31GNf+WkP91v70Z+Zf8AaXDV2YAxgVj+IfDdj4n01rG/RzGGWSOSNtskMi/dkjbqrL/er9OUo8vJPY+kcfe5omyOBQRmuE0LxDqXh3UYND8UusjTN5en6yo2xXvpHIv/ACzm/wBn7rfw/wB1e7yBUyi4sadzhtAzqvxF8V6hkNFZLbaTEMfdZY/tEp/4F9ojH/bP2ox/bHxTJGDBoenf+R7lv/Qljh9uJv4t3ynwpAufB8eqcbtXurjUgwGN0csjNF+Uflru/i27v4qd8M2N9pup643LazqE10rY6wriGH/yHDG3/Av4vvN0yTjKb7e7/X4mMbSjH/wIr6OP+EM8bT6Mx26TrbSXuncYWK5+9cQD/e/1y/8Abb+7SeGIf+En8Y+I9ZngVrK3/wCJLZsxz5ixsWuG/wC/xMf/AGx6L/FL8YFP/CBXtxCCup20kUumPGfmF55irbj6NIyqy/xKzL/FUnwmkiXwFpduolF1ax/ZrxJf9YlyrETBvfzNx4+XB+X5cUNfu/bddhfb9mZ3g/SotV8Ea14N1IvINN87RJzL8zSW7R/uW/2t0Mkef9rdWd4W1a4uNX8CapePi6vrK70TUP8AbvYfmP8A3y1vd/8AfVb2pf8AFPfErTr77tprsH9nz5Hyi4h3SQt/wJDMv/AY65HxKP8AhHrzxMAdq6Tqth4lg54S3mby7n/0Xdt/20reH7yX+L9fd/8ASjKXu/8Abv8A+0e1UUUV5p3BRRRQB8K+Jv8Agj98EPEXjG71qC98VaLaXMrTnRdPvbdbSLcwPlxBoGdY/vfLu/iG1l219oeF/Dum+DPDek6Fo9sthpOmWkVlZ2ikssUMarHGo3fN8qqor86dd/4LVeGNM8c3Gm2fw3v9S8NwXTQ/2wurxrPJGrbfMS38sq2fvKvmr17V+iHgfxdp/wAQPBmgeKNIZ5NJ1uwt9Ss3lTY7QzRrJHuX+FtrLQB0FFFFABRRRQAUUUUAFFFFABRRRQAUUUUAeQfHT/kbvg//ANjcn/pFd16/XkHx0/5G74P/APY3J/6RXdev0AFFFFABVS+szd7cNt21booA8p+JvwauPH91p80WqR2f2WNkbdCzbt3/AAKvH/Fv7Euo+JbyCZPFVrB5abNrWbN/F/vV9bUUAfIel/sNalptu0Z8WWr/ADbv+PNv/iq9d+EvwOuvhto99ZzatDfNcXHn71hZdvy7f71ev0UAZdho7WcLRtIr5bd92tCKPyk21JRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFeU/tT/wDJu/xA/wCwTLXq1eU/tT/8m7/ED/sEy0Ael6f/AMg61/64p/6DVuqmn/8AIOtf+uKf+g1boAKKKKACiiigAooooAKKKKACiiigAooooAK474ofC7wx8ZvAupeD/GOmjVvDmpeWbqyM8kPm7JFmX542Vlw8an5W/hrsaKAPzY/aw/Y5+EH7O7/BbxH4B8Hjw9rN18TNE0+W6/tS8ucwt50jKFmmdfvRR/Nt3fL71c+M/wDydj+zp9fEf/pBHX2p8Z/gP4H/AGhfC1r4c+IGhnX9ItrxdQitftk9vidY5I1bdDIjfdlkGN2Pmr4Q+OvwB+D37In7TX7Pup+FdNtfA2nakfEP9qXt/q8xgfy7KNYd0l1Myx/NMy/Lt3b/APdrtw9a37r+9Ewqw5veNr/nIH/3TL/3K0f85A/+6Zf+5Wsnwx4y0Dxv+3fLfeHNa07xBZx/DfyJLrTLyO4jWT+1FbZujZl3bXT5f9qtb/nIH/3TL/3K17H/AMkcP/yJ9A0UUV3HIFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFfPv7fv/JpXjr/tw/8AS+2r6Cr59/b9/wCTSvHX/bh/6X21Y1v4MjSn/Eifo7RRRXyR7gUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAec/Hj4L6J+0N8KNc+H3iO6v7LRtYMP2iXS5I47hfJnjmXa0iOv3ol6r0r4R/an/ZRsPgPc/BfXbb4kfEPxk9x8S9FsDZeL9dW+tI1YzSeYsYiXbIPLC7s/dZuPmr9NK85+M/wG8D/ALQ3hW28O/EDQzr+kW14moRWv2ya3xOsckatuhkRvuyyDG7HzVUZcrE1zHxT/wA3/wD/AHTL/wBytOP/ACf8f+yZ/wDuVrnta+Hnwn/ZD/boGl6F/Z3w/wDDN78OftLf2pqz+VJdvqZU/vLqRuWjhX5d2Pl/3qteGfGfh/xv+3XLfeHNa07xBZR/DjyJLrTLyO4iWT+1FbZujZl3bWX5f9qvdp1Pax5v7x5848svkfS1FFFeocAUUUUAFFFFABRRRQAUUUUAFFFFACnrXkOv/wDJ9P7MH/c0f+m2vXj1ryHX/wDk+n9mD/uaP/TbXDjP93kdOH/iRPviiiivmj1wooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPmbxV/wTp/Z68ceLdZ8R638Pvt2s6veT397c/21qEZlnlkaSRtq3Cqu5mbhVxXyl+zN4u+G/wQvPjJ4NuPEug+ErXS/iPrNrpum6nq8cMkdpH5cMX+uk3Mv7vbubd901+o1eW6r+zR8INc1S81PVPhV4J1LUb2Zrm6u7zw5Zyz3EjNueSR2j3MzM25ia3o1nQlzGdSHtI8rPzy+Bf/ACjL1L/sWPEX/o29r6E/Z2/5IB8M/wDsV9M/9JY6+LfhT+018NvDv7DF74A1LxGbbxhJoOs2KaaLK5YtNPJcNCvmLH5fzeYv8X8XzdK+0v2dv+Tf/hkf+pX0z/0ljr3MPKMuXl/lPNqRlaX+I9Aooor0DlCiiigDnPBWo/2l/bn+i29t9n1aaD/Ro9vmbdvzN/eb/arpO/NcpolxrVrrd5az+Hbe20+a6mk/tC2mjXcv8LNH95mbavzf7VWNI1vxBe6hFDfeGf7PtW3eZc/2hHJt+X+6tc1OXu8ppKPvHRVznjX+z/8AiR/b/tH/ACFofs/2bb/rvm27t38NLpOueIL3UI4b3wz/AGfbNu8y5/tCOTb8v91ayrh9a8TX2lR6p4Xmsba1vI7vz4NQhk2sv3dy/wAS/NRUqc0fdKjHlkdvXn/7Q/HwB+Jf/Yr6n/6SyVvavb+KpdQl/s6602Cxbb5fnxs0q/L83/j1cd8fLTVF+GHj68uL+OTw/HoN7JcaasO2SaFbdvMj8z+Fm+Zd38NVUqe7L3RQj759Mfsm/wDJrXwc/wCxM0b/ANIYa9Wr5l/Z58E+NNb/AGefhLcab8Q5ND0eTwdogj06LSIZGjP9nwbv3zfN8zfN+O2vVfFHw78Q6/rt1e23jzVNFsZCvk2Fpbx7YflVW+b7zbmUt/wKvkz2z0WivOvE3woufE2t3d7/AMJt4o0i2m2/6Dpd6sMceFVfl+U7fu7v+BGl8T/B608W65c6pceJPEtm023FtY6o0MEe1VUbVC/L93d/vM1AHolFed+Kfgh4e8X69darqM2pyS3G0vbxahJFCdqqo+Vf92meJ/gP4J8a+IbrWda0iTUNQuQgkdruaNV2rtXaqsv92gDurrVrKxDfaLy3gC/e82VV21Sv/FuiaXd/Y7zWLC0vOP3E11GknP8Ass1c9rnwY8F+KNfn1rVvD9vf6nPt8yeR5Pm2qFX5d237qrV3VfhZ4R8QancalqXh7T9QvrgqZLi5gV2baqqv6KtAEur/ABH8J+Hru4tdT8SaVYXkW3zLee8jSVd3K/Ju3d6q698WPCHhbU5LDVfEVjY3iY8y3lk+dPl3fMv8Pysp/GtG+8B+GtX1F9QvvDulXeoSH5rqeyjklPy7fvMu77vy1Zn8MaNdXctzPpVlPdTY8yeW2Vmk28LubbQBzPiP43+CPCOrXWl6vrsdjqFuyiWBreZmXcqsv3V/ustReIvjn4R8L6/daNf3t0moW7KkyR2UzrGzKrL823b91lb/AIFXefZIftHneTH52Pv7Pm/76qxQB55r3xo0rw74gm0WTS9bvbyFlWRrLTZJY13Krbt3935qj8QfF9fD+v3WmL4N8X6r5BCtd6bpXnW5+Xd8r7vm+8K9HooA868Q/E/U9G1+40yz8D6/qpjZVW+t4U+zPlVOd27tml17x/4n0zxBPp+neAr/AFeziZV/tFLyGJX+VWLKrf736V6JRQB51rvi3x5b+IZrDSvAMd/piSKqatLrMMasv8TeTt3DutLrut/EWPxDLFpHhrSptJWRUjuru/2yOv8AE21f/Qf9mvRKKAPOtcuPid/b00WiWnhf+x96mG4v5LjzdvG7cq/xda/OHSfhj8cvgt+yzqnhvxL8JbtdI0zQtTbWNYi1XSmkjt5POkmkVlumkbbGzfdXd8v3Wr9YhiuC+N3gy/8AiR8GvHvhHSngh1PX9Av9JtpLt2WGOWa3kjVpGVWbbucbtqsfarjKUfhJlFS3PzW+Iln/AGT+xJpPifVLeyvbH/hHdCnmigiMd3NIzWu1mm/veZtkb+9t2/xV9Fy/CyS31qW80vUodKgZfKWCKxVv3bL8y7t1fN/7UPwS/aF+FH7HeqaZ4wufhndeBdBstMsJn0Z9QfVHjjuLeGBl8xFi3bvL3fd+Xdtr7Sr28PGjXl/4CcFWVSkefxfCdbLVJbjT9autPtpPl+zR/NtX+7uZqluvhjJLb3MKeJNY8qSNlWCW43R7WX7rL/FXdUV2fV6Zye0kfNX/AArbxJ/aX2P+y5t27b5+391/vbvu19FaXp66VpdnYo3mrbwrArN/FtXbVulxU0cPGh8JVStKoJXFfsY/8nZ/tTf9yr/6QT12tcV+xj/ydn+1N/3Kv/pBPXPmH8E2wn8Rn2hRRRXz56gwccetcVDjRvitcJjEWt6Wsy+gltpNrfiy3Ef/AH7rtARx61xXxGJ0+bw3rakAabqsKSnuYrjdbsPpumjb/tnWlDV8vf8Ar8yJ/Dc7c9BXF/DMi2tde004DWGtXi7fRZJPtC/+O3C12o7VxPhs/YfiN4wsuMXEdnqg9y8bW7f+kq0R1jJCl8URfiePJ0nR7j/njrmnf+RLqOL/ANqV2SfdFcb8Wl2+CLmb/n3urO5/793UUn/stdkn3RTmv3cX/i/Qa+OQ/GBXB/Eb4N+FPilbomv6RHdTx/6q9jby7mL/AHZF+b/gPSu8NJgetc8oqa5ZDlGMviPl7Uf2IoN7HR/HOp2MX8Ed7ax3e38dy1PpX7EmmiVW1vxfq2pxAfNDbRpao59wC1fTWfejPvXmf2Xg+bm9mc31Wj/Kcr4D+Gvhr4baYLLw9pVvpsLf6xkXdJKf9p2+ZvxNdXjnNAzQTivTjFRXLE69haKKKsDP1jR7LXdNnsNQgju7SddskMi5VhXk/jzXdd+GnhHWrC5mk1LT7i1a20rWpm/eWs0n7uOO6b+7uZds38X3W+b5n9mxkVwvxDtYtb1HwroU0az295qPn3MUw3I8UEbSfMOjfvRD8vvu/hrooTSnaa90wqxduaPxEnjFj4O+G1xaaYzJcRW0enWDMPuzSbYIPu7f4nT7uK6XRtKt9C0ax0y0XZbWcCW8Sf3UVdq9PpXj/iNZ/A/jLw5pZmuL/wAHW0kmryRqjSzaXHGvlqHblmt/MmVl/iXy2+9Grbfare5ivLeOWB1mhdQySI25WHqD3oqx5YR89QhLmlI4zXt3iP4gaLo5Di20pP7ZuWQ/ef5obaNv9lj50n1gX3qPUgfBXjqLUgRHo+vyR2l4Oiw3n3YZv+2g2wt/tLDT/hmh1G21HxO8jPJr1z9phDN8q2q/u7cL04aNRJ3+aRvmZdtdF4j0W28TaRdabeqxt7mNonKNtdP9pW/hZeqmiU1TlyS22/r5hbmXMZ/xD0WfxB4Uu4LIj+0oCt3ZNn7txE3mR/gWUK3+yzVyHiSWz8XL4W1cEppXiSwuNHuAeCiXMPmR7vdWiMf+9LXVeA9butR0+fTtVbdrmkyC0vG27fOO0Mkyj+7Iu1v97cv8Ncbq2nS2mkeNPDtqm+706ZPEOkrx826T7QqD/t4ilX/dZa1o3i3Dt/7d7v8AkTU96PMd38PNXm13wPod7cn/AEyS0jFwPSZRtkH4MrV0v8VcF8J9QhubfXbWBg9rFqLXds/9+G6VbpW/76mkX/gNd8Oprmqx5ajNab5oJi0UUVmaH5n69/wRQ8JX3i65vNJ+I+p6X4dd8w6VLpkc80WW+79o8xdy8lfmj3cfxV+ing/wrp/gfwjonhvSozFpmj2MOnWsbc7YYY1jRf8AvlVrcooAKKKKACiiigAooooAKKKKACiiigAooooA8g+On/I3fB//ALG5P/SK7r1+vIPjp/yN3wf/AOxuT/0iu69foAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAK8p/an/wCTd/iB/wBgmWvVq8p/an/5N3+IH/YJloA9L0//AJB1r/1xT/0GrdVNP/5B1r/1xT/0GrdABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAVx3jn4UeCfie1kfGXg7QPFgshJ9lGu6ZDe/Z/M27/L8xG27tq7tvXatdjRQB+ZXx31z4Vfsm/t2WlxLY6R8PfDd78N0j8rRdH8qGW7bVJPmaK3j+8Y4T823/lmv+zWT8L/AIu+EvjN+21Nrng7Vf7Z023+HbWUk/2aaHbMupKzLtkVW+7Iv/fVfqUDkV8D/tQX3iXwB+27p/jW2+G3jjxp4fl+HUejNP4R0KS/Edz/AGlNNsZvlRflT7u7d8y/L81d2HxHLy05fCYTp83vHr+R6UZHpXh//DTOs/8ARvvxv/8ACKk/+OUf8NM6z/0b78b/APwipP8A45XufWqP8x5vsan8p7hkelGR6V4f/wANM6z/ANG+/G//AMIqT/45R/w0zrP/AEb78b//AAipP/jlH1qj/MHsan8p7hkelGR6V4f/AMNM6z/0b78b/wDwipP/AI5R/wANM6z/ANG+/G//AMIqT/45R9ao/wAwexqfynuGR6UZHpXh/wDw0zrP/Rvvxv8A/CKk/wDjlH/DTOs/9G+/G/8A8IqT/wCOUfWqP8wexqfynuGR6UZHpXh//DTOs/8ARvvxv/8ACKk/+OUf8NM6z/0b78b/APwipP8A45R9ao/zB7Gp/Ke4ZHpRkeleH/8ADTOs/wDRvvxv/wDCKk/+OUf8NM6z/wBG+/G//wAIqT/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c1rWvgb41Uafq9ldz3F7H4cvo0/dyW0fPlrJw21d2799x8sddp+xle+O/i3deJfjb4y1XUbXSPFjeX4T8KNdyLa6dpSyHy5ZLfd5bXEu1W8z5m2/dZVk20AfQvxB8Zab8OvBGv+LdYZ10rRLCbUbnyVDSGOGNpGCqfvNhflHrXyZ4W+N/7WPxX8Cw/EnwZ4C+G9n4PvoWv9O8N6zfXkmt3tryybZY9turSL93dt/2q+pfizpfhjW/hj4s03xlcQ2fhG70u5t9WuZpvJSK1aNllYyfw7VJ+b+GvzC8M/GD9oTwN8AvEOlfDmy1vxP8CbCdLLRvibFoyprNnpKyFZprazaaOSYIu5VkbbtWP5mj/wCWYB+if7L3x4sf2lPgr4e8fWVk+mNqIljurB5PN+zXEcjRyIG/iXcu5T/dZfu9K9drwj9i+w+G2mfs4+D7X4T3ral4QjhYrdz8XEtxuLTNcD+GXzC2V/h+UL8u2tf9qL4a+Kfip8INU0zwN4o1bwn4xtWW/wBIvtL1CSz8y5jDbYZmj+9DJuKsrfL91v4aAPYKK/OLw/8AtV+Pf21o/h/8JvCkmpeA/F8btefEzU7Hz9Pn0mG1uVR7e2k/1kckzL93+HcsbMf3m39ELK2WztYYUMrLGioGldpW4/vMx3Mf9pqALtFfnpqTfGL4u/t4/G34a+GPiZqXgzwZaWukXd7dRTSTXNlF9ghYRWEbN5cLTSSbpGVVb5fvfwvvfB+6+IP7N/7bGn/BrWviN4h+JXgrxZ4fm1nT5/E8v2m9s7iPduXzmbdtxbv8q4X96vy7gzUAey/GH4ifHkePLzwv8Jfhvotza21rFO/jHxdqMkentI3LQR28e2SQ7f4lbbuPzY2/Ny37L/7WXi/4g/F3xb8Hfiv4Ss/CPxM0C2+379KmZ7C+tv3a7o9zMy/66Nl+Ztys33WVhX034g8Qab4V0S+1nWb630vS7GFri6vrqRY4oY1G5mdm+6tfFf7HdleftB/tQfEz9pNo5YvB9zB/wi/hMzDy2uraJ41kuNu0NtZoT97+KSRf4flAPUvEvxq8V/Db9trw14F169S5+H/j7RJG0MSxRxfYNTtdzTxLIq7pPMj8ttrt96RVX/a+mK+K/wDgpL/xTw/Z/wDGcI36hovxJ0yOOLO3zFkWSR13DnDfZ1X8a+1KACiiigAooooAKKKKACiiigArw39sn43yfs+/s6eL/Gdoyf2rbwLaacrjrdTMsUbfeH3d3mH/AGUavcq+H/8AgpzdG9tPgR4ZlDfYNY+Ien/alHR1X5dp/vf63/x2gD6T/Z78Ja94G+CPgnQvFOq6hrfia30yI6nfaney3c8l3J+8m3SyMWYK7Mq7v4VVeOlfF37X37avxO0nx1PN8INVsLL4feEdcs/D2vas9tDcNqOpzMzSWsfmK3yxRx7WZdrbmb5vu19B/t5ftE3HwB+Czro15FZeMPFFwNC0W7u5BDDZyyfLJdSSN8sYiXLBm+Xdt/h3V8bftQeIvgp8Pf2LfBPw68AfELw/4n1DS/E1hqWovYX0dxc3cn7xrm6kVfmb5m/4Cu1f4aAP1korm/A/j/w38SvD8et+E9d0/wARaPI7RrfadcLNEzK21huX+KvnH9vv4RarrvgGy+Lfgu8j0b4kfDHzda03UGYKstoq7ruGXd8pXy1Z/m3fdZePMagD6yor8+/2bvGVx/wUH+Otn8V9XhOmeAvh0kEGieFp2STzdakj8yS8kXd/yz+Xyz/sxsu1lkr701XVbbRtLvNQvJPJtLOJpppNpbbGq7mOB7ZoA8O/ax+OmsfDLw9o3hfwGlvefFjxndjTPDWn3I3KjZ/fXci/884Y8tub5d23O5d1c5/wTv8AjF42+NvwGvda8fawmueIbPX7zTGvUtYrfzI4xHt+WNVXqzfw14X+zX+0P8LfiL8ZfGPx6+I/j/w5omqXMkmieD9B1XU4Vl0rSI22mby2fdHNMyszfxfNJt+WTFb3/BJ74m+Ern4WeIvB6eItPbxQ/ijUtQj0n7Qv2iW32w/vlX+Jf9paAPvqisnxDoVh4r0LUtF1aziv9L1K1ksry1nXKTQyKVkjb/ZZWZa/Lm6+LHxD/ZO1nxJ+yZoOptc6lrup2dp8PvE8k8af2TYX8x8wS/Nu8xNzLH/Fv3Mvy+WrAH6uUV5t8Afg1ovwA+E/h3wLoSq1ppduqS3LReW93O3zSzOv9523N/s/d/hr5h/4KX2mtX+v/s62PhzWP+Ee1698dwWVlqvkrP8AY5ptsaTeW3ytt3bttAH3PXlvx2l+KS+FrG2+ElvoP/CSXWoLBdX3iPzPstlaNHJuuFWNt0kissSqvzfe+ZdtfDP7Y/7JGifsn/C+3+Nnw88TeKLX4j+Hb2z+065f6tLNLqayOsL+d/vbl3Ku1WXcu3mv0q0q+/tLS7O72eWbiJZNuc7dy7qAPgj4lfF39ov9i/xd4H1z4k+NNH+Kfw98Raqmk6glvo8enzabLJvYeUY13N8u5l3bt3klcLu3V69+334r8X/Cn4beHfip4R1K/hPgrXLe71fS4Z2W21HTpj5M0c0KsvmYZotu77vzN/tL5Z8XdQj/AG7P2qPC/wAN/DrTXPw0+GGrf2x4v1N42+y3d9G22Oyj/vN/rI93y/K07Lu2jd9K/tiaVb6x+yl8X4Ljd5cfhTU7hQpx80NvJIv/AI8q0Aep6LrFp4k0aw1bTp1u7C+gjubaZfuyRuu5WH/AWrSrwz9iHVJ9Z/ZG+EdxcbWkj8O2luMDHyxx+Wv/AI6q17nQAUUUUAcTrajSfiZ4bv8A7kWp21xpUnP3pFH2iH8ljuf++q5Dwcfsa/Dq3+6LC+1PQwPaFZlX/wAdthXXfFdTD4Qk1RR+80a4h1VSOu2GRXlH/Ao/MX/gVccGFp4wWEHMdn4wWeEL/cudNfLf9/JpK9Kk70rJf1r/APJHHPSp/X9fZPaKKKK807AooooAKKKKAGZByK8B8K68kWpa54se3MsVlDdaikK7VM0tzN5duu7n5vs9rD833V8/qy/d9Y+IGsSeHvBWt39srPdRWkhgXft3S7cRru/h3MVGa8l+Hmhpqknh6wtmCWcl22rXLog/e2tlttbGP+L7zRxTbf4fLb+L5m78NGMaUqkv6/mOOvL95GKPYPA3h1/CvhfT9OnnF1dorSXVwFx51xIzSTSf8CkZm/GuiI4oGM0tcLbk7s6ox5VYaMAdaparqtnomnT399cJbWcC75JpDhVX1ql4k8UWPhaz8+9kYmRtkNvChkmnfskaLyze1c9o3hfU/EGqR654rEZkhk8yw0aJvMtrHH3ZH/56XH+191f4f7zVGOnNLYTf2YlW20/UfiafP12xk07wvndb6LcptmvfRrtG+6v8Sw/9/P7tegxxrFGqooVVGAq9qk4peMVMp83oVGPKLRRRSGFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUV51+0Nr8/hT4AfEzW7Rit3pvhjU72JlOGDx2sjr+q0AeI/sU/EDxD8dvE/wAX/itfaxfS+EdT13+xfC2km7kNpb2dmu37RHDuaNWm3KzN/eRv4ap+KvBf7YfjhdV1jTfiJ4N+HT2887aX4bs9HW8+1Qhv3K3dxMsnlyFV+bydy/N/wFd//gmnpMGlfsTfDSOAAmWC7uJGPVmkvJ2b+e3/AIDXVftZftL6f+zX8NX1DyJtT8W6yzad4a0S0haae+v2GI12r/CrMpb/AL5XczKpAOZ/Yh/ae1f9of4ManrHjDTotG8UeG9Sn0fWFtlcRyPDGsnnKvOz7+1ly3zI3ZlFeXfBzxT+0T+2R4Tu/iT4W+K+lfB7wte3dxBoeg2nhu31iRoo22briabG19yn7vHX5V+7Xq37FXwQf9lf9nPyfFt6g1++km8R+JNQuJWYRTSIGfzJG/55xxqrN/eVm/ir47+Hvgn4zeJ9N+JHiP8AZDuLvwr8GdXNwmm6d4ju1ha+uw22ebSkZP8AR13L5atIy/dbcysu2MA+yf2Lvjz4o+NPhfxrpHj620+Lxz4I8R3XhzVJtI3fZLtoW4mjDfd+bcuP9jd8u7av0lXyT/wTs8XfD3UfhDqXhLwX4e1Pwjr3hbUnt/FOia1Os2ox6g2VeaeYKvms7Qsu7an+pZdiqqrX0F8X/hjofxn+G3iDwR4kt/tOja1bNbTKPvRtndHIv+0kiq6/7SrQB2lFfkxofxV+JnjW3tf2IL7WDY+KoNXuNB1LxjE8TLP4cgt2k8uNFbc0jxLt2/e8tdr/ADNJt/Urwb4Q0nwB4V0nw3oVrHYaRpVtHa2tvGPlSNV2qP0oA8s+Oll8dPEWv6Xovwr1Tw34S0Ke1lfVPE+tWrXl3by52xra2+7YzfxN5i7ff+FvC/hp8cPjZ8Ff2sPDnwW+MWt6Z4/0vxdZy3OieKbGyjsJY3jSRykkUaqv/LJl2/7cbbvvLX2pqeq2eh6Zealf3EdpY2cL3FxcSttWONVLMzeyrXw78AY7j9sX9ra6/aDS3urX4b+DrSTQvBy30UsbahO3mLPeKrfLt/eSr/37X5Wj+UA774+/GT4keKP2kvD/AMCPhZq+neDtRuNEbxHq/ivULJb6S1tvMaJY4LZvlaTcqt83Xev3drbsHSPiZ8Zv2d/2k/hx8Pfib43074p+FPiCt5DYa1Ho0ek31jdQojFWhh/dtH80a/3v3jN8vl7W5X9ti0j+Iv7Qng/w58Hn1S3/AGlNItRcrrem3CwWWk6UW+b7ezK26NvN+WNV/wCWvzfeVZOc+E2q6/8ACr9tXT2/ad01tQ+I/iaP+zvBHjCxulk0CGMqqPa2kHlo0MrNIY2dvmYzKu1Vk8yQA/R+iivzt/aO8UXH/BPX9oab4t6NaSaj8OfiQLhPEHhq2ljif+1442eK5j3fMvmMzMzL9395u+Zo1oA/RKsDxd4kXwf4T1vXZLG91RNKspr9rLTIvOu7hY42k8uGPI3SNt2qufmbAr55/YX+Fmo6T4Kvfix4yv4tc+IvxOWDXr/UY1Urb2rRo1vaxsGb92sZX7vy/dX+Ba+paAPz90z9p/8AaAuv2xfhJ4c8ZaHYfDvwX4t+3tH4TXy7q+eGOCTbJdT7flk8xNyrEy/L8rK38X1H+1T4b8S+Jf2f/Gtp4P1jVdD8VW9g1/pl5o121tcNcW/75YlZT0k8vy2Vvl2yV88ftNf8pJ/2Yf8Ar01P/wBEy19zUAeRfssfGIftAfAPwX48Lwte6pZD+0FgRkjS7jby7hVVvmVfMjfaP7pX73WvXa+LP+CVeLL4HeOtBi/5B3h/x7qul2KnllhVbeRQzfxNukbmvtOgAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAOa+Ic1xF4A8SyWuftK6ZcNFtXc27y22/LXzH/AMEooVh/Yp8JuFCtLe6gzEDqftci/wDstfXc0MdzG0cirJG64ZWG5WFfGv8AwTat7n4d6L8W/g9qdu1pqHgTxdOsMLBg32G5XzLaT5vmZZPLkdW/iVloA7P9rn9pTWvh/Fpnw2+F9pH4k+M3ivMGmaTE2Tp1uytuvpv4VVNp27mVfvN8yxsK6X9m/wCBFt+yf+z7H4f06OTXtehhm1fVpo5HZtU1Jo8ybTt3bSUSNfl3bVXdubdu8M0n/gnz8T/CnxO8Y+O/C/7SFzo2u+Kblpb28l8Iw3dx5e5mSHzJrhm2LlV2rtX92ny/Ku33n4E/B/4p/DvXNSvPH3xrufifY3Ft5UFjN4fh077NJu3eZujkbd8vy7WWgD45/Zm+O3jD4V3/AI38ZeNf2evjF4h+JXjLVGvdU1Kz8KTNHb2ynbb2cLSfN5ccar/d/hX+BWre/wCCTnxfvJvCuueB28C+KYbO413UtUi8TnT2/suP5Yf9Hlm/hm+98vzfw1+jVeK/srfs7L+zL8PtU8MRa63iGO81u61hbh7T7O0azbf3W3e24rt+98u7+6tAHtVfjT8fLi2+E/x6+Ivwr8K67Npv7P3ivxTo0fjW8tLZjBodxM3mXFrHcbtqKyozPt+6sfl/8s2Vv168VWOq6j4Y1W00TU4tD1ee1kjs9SktftS2szKdsvk7l8zafm27vmxXhnw9/Ym8EeDv2btY+Eepl/EseurNPreuX8Q+03t/J/y94Zm2ujBfL+Y7fLXLM25mAPcfB3h3SfCPhTSND0G1hs9D060itbGC2YtHHCqhY1U9xtxzWb8S/iX4b+EHgnVPFni3VItG0LTY/NuLmY+v3VVfvMzNhVVfmZsYrn/2d/hjrnwV+Eeh+C/EHi9/G9xpEbW8OrzWf2SRrcH91Gy+ZJ/q1+Xdu+6q15P+2H+xvrP7U+v+Dbu0+JUng+x8NyNdxaZNoy6jbz3e5WWZo2mjRiqqV2urfKzf3myAcb+y18P/ABb8ffjPcftNfE3Rm8Ph7L7D4E8OuzF7CwbduupF/wCekiyNtz97zJG27fLrl/2xPE/izUP2qfAtprHwp8eeN/hZ4MhXXEtvCuhzX8Gqaqy7YzM2Fj2wrux95uWH/LT5fSNP/Zh/aItNQtprr9rC8vrVJlea3fwVaIJV3ZKbluNy7uV+WvrqgD8qfH37V+p6r+3d8MvG/wDwpP4l2dzpnhy8sh4ZvNDePVbpWWfM0EPWSNd3zf7rV+o2l3/9raXZ3hgntBcRLL9nuk8uWPcN21l/hZa8l8U/s7p4l/ah8F/GEa4bafw5pF1pR0j7HvW6WXzNr+dv+Tb5jcbW3cfdr2qgD4A/4KOxz/Db4mfCX4m/DljJ8bYrubS7HRre2a5fVrDyZGlM0atu8uHc3zD/AJ7f7Ksvo/8AwTU0jwzP+znbeMtH1H+3vFPi+8uNT8V6tOf9Im1PzG8yORf4du75V+XcreZ/y0r0Lwt+zLHZftLeIvjN4m8RN4o16ezXTNAtfsYt4tCsctujX943mM25v3ny/fk+X5qr/Br9l4fAz4yeP/EvhrxMLLwP4t2XR8ERaeqW9jfLt3XEMvmYVW/ebo1jX7y/N+7WgDqP2sv+TWvjH/2Jms/+kM1eJ/sC/AP4fQ/sfeD2m8JaXfyeJtOa41mW9tVna8aX5WRmb+HaqrtHy/L/AHq+kfiz4Fb4ofCzxj4NW9Om/wDCRaNeaOb0w+d9n+0QtD5nl7l3bd27buXpWf8AAb4WH4I/B7wn4E/tQaz/AGDYpZfb/s/kfaNufm8vc236bmoA+bv+CTRkg/Zev9Ma4e4ttL8U6jZ2ok6pGvltt/76Zm/4FWV/wUx/5GX9mr/soVn/AOhx177+yt+zsv7Mvw+1TwxFrreIY7zW7rWFuHtPs7RrNt/dbd7biu373y7v7q186/En/gnr8YPi6uiHxb+1BeaudEvV1HTnPgyCF7a4X7sitHcq26gD70r4o/Z/ljT/AIKWftNx25HktpuiMyxn5DJ9jh3f8C3M3/j1fQvwG+Hvjz4ceG9RsPHvxKm+KGozXfnW2pT6PHpzW8WxV8nbGzbvmVm3f7VfP37BNhJ44+IPx/8AjI6NNYeLvFclho12kn7u5sLNpI45Yzk5DBlXdu27o/l20AfadFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQB8N/8ABP4zR/tCftdQXUu65Txy0mxn3MI2nvPL/Db/AOg19dfFL/kmXi7/ALA93/6JavlvwZbTfBT/AIKSeNrW9eGz8O/FjQodR0wlwvnahYrHHJD975n2tPJ/20r0/wCPX7JGm/H7xXbazf8AxE+IfhQQ2C6edN8J62tlaSqskrGR42ifdI3mbS391VHagDz/AP4JRf8AJkfg3/r81H/0slrqv2r/ANpTU/hwmn/Dr4aQL4h+NXiePZo2koiyLYx7vmvLnJ2xxqu7bv8AlZl/uq1Y3wL/AOCe/hD9nbxTpOs+FPiH8RpLfTZ5Jl0O/wBbhOmzs8bRt5sEduu772f95Vqt46/4JxeCvG3xc8RfEhPH/wARvDPibXm3Xkvh7WYbVdu1R5an7OzeX+7X5WZvurQB6H+yb+zbb/s2fDh9NuLyPW/GWs3MmqeJNfwQ+oXkhLNhm+bYu7av/Am2q0jV7pXzr8Gf2N9O+DXjm28T23xP+Jvil4IniGneKdfS9sm3Lt3NF5K/Mv8ACwavoOWNpImVXaNmG1ZFHzD86APyW/4KGQX138e/iNqXwZOoGew8IrbfFGXRpY0gktJJUVYXO3d53lqPM27v3a/7My1+lH7P914Jv/g14NuPhzFHB4Ik02JtLjgj8sLHz95e0m7du77t27msz4Ffs3+FPgBoGtWGiy6jrF5r2oTanrWs6/KlxqGpXEjfM08iqoZRub5du35mb7zMzH7P/wCzn4e/Zs8PaxofhTUdYn0PUdRk1GOw1O4jlisGf70duFjXbH/stu/3qAPW6+GdJ/5S+a3/ANk9X/0ZDX1j8XfhzF8Wvh9qnhOfXtb8NQ6gYd2qeHLz7LfQ+XMsn7uXa23d5e1vl+6zV8uSf8Er/BEviePxC/xY+LreII4fJTV28Rwfa1j/ALnnfZdwX5m+XdQB9UfEv4l+G/hB4J1TxZ4t1SLRtC02Pzbi5mPr91VX7zMzYVVX5mbGK+U/2evhv4s/ab+NVr+0R8UNOOl+HdOSRPh74RvINstnbyN8t9Muf9Yyjcu7d8zbl2rHFXp3xp/Yj8H/AB6+E/g3wD4s8UeL7jTvC+1rfUI9Qha+vGWPyw9zJJCyyNtz821fvGuO/wCHbui/9F1+N/8A4V8f/wAjUAfX9fIn/BTSHwpqH7M15peuxyXPiq+v7eHwjbWRX7bJqpkVY/IGP7rN5n+wzKvzMtfUfh7RxoGhadpYnuL0WVtHbC6uyrSyhVxubaqruOPmwq8mvPPFH7Onhjx38b/C3xN1651TVNU8LW0kWj6RczxtptnNIctdLD5e7zvu/MzYGyNtu5FZQD5c/wCCbN1Kvj34z6f8SvOuP2hoNVT+3rzUNjzy6eI4lh8mRVC+TuX7q/Lt8n+Hbt+/q8h8Vfs1+GvFXx28K/Fz7bq+j+LtAtpLMNpc8ccOoW7bv3N0rRsZFXc23ay/e/2Vx69QB8N/8EtfD2nQeEvjLraWMC6vc/EXU7Ka9ES+dJBHHA8cbN/dVppW2/7TVb/ZQtYtM/b1/axtbVfKt5J9HuWiT7jSNDIzN/vbpG/76avoT4C/s/eHf2d9G8R6V4bvNUvbfXdcuPEFy+qSxyMlxMI1dU2Rr+7/AHS7d25vvfNT/BH7P3h3wD8YvH/xI0y51Jtd8ai0XUbe4lRraP7PHsXyV2hl3febczf7O3pQB8/f8FdP+TNdV/7C9h/6Mr698J/8ixpH/XnD/wCi1r5a+J//AATf8I/F/Wdfu/EXxP8AilcWOs30uoS6MuvwtYQu8rS+XFDJbsqxqzfKvO3atem/s8/svaZ+zmdVTS/G/jbxZa38UEC2vivVlvYrRYd23yFWNPL4bb/wFaAPF/Esq3f/AAVr8KCDMv2X4aSLNgf6v/S7n/4pf++q+1q+Lf2ZrOP4tftq/Hn4uwPFf6FpTQeB9GvOo8yGOJr1Ux95fMVW3Hd8snyttr7SoAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPiHw3DH4C/wCCs3i6K6eND458BwXtrj77SQtFDt6/3bOZv+ArUPx48I+Pvg7+2hpHx40XwNqnxP8AC0/h/wDsHUdP0CNZb/S/n3eZDCzbpiy7m2rt+86sy7lZvZf2h/gLrnjr4k/Cv4j+Cp9Ls/GfgzVWZ5NWklWK602aNo7uAGNW+cq3y/L/AHq9/oA/PP4433jn9vDxH8OPDOhfBrxn4B8O6F4lttb1TxT46sV0ua3hjVlaOCLdvkLeZ/A33o4/u/My/oZRRQB8WfFT4ZeIP2x/2lP+EV8XeH9U034EeAh58i6jby2n/CRauySKskDNt8yGJWb5l+X733lkXbrfsQ6Z4/8Agprfiv4D+L9J1nVPD/hYm78LeNXsJFsr2xkZW+zNN93zI2k+VdzHb5i/Ksa7vr2igDxL9sL4R6z8dP2a/HXgnw7crba5qdpG9mXICzSQzRzLCSWUL5nl+XuPyrv3V4V8Mf2rvHXwv+E/h3wPqv7M/wAT38ZeHtMt9K8nSNKWXR5jDCsaut4rbVVlXdtVW2t8u5vvV9xUUAfLH/BPb4D+JvgP8FtWt/Fmm2+ha34j8QXWvPodq6tHpkcixxx2/wArFflWHd8vZlX+Gu7/AGrPiR42+HHwlu5fhv4W1TxZ4+1SePS9Hh0+ya4jtZZP+Xm5b7scca7m3SfLu2q3yszV7ZRQB+cGrfsn+LP2KJfht8Xfhtaar458V2EK6T4+0bSoZr258QR3EnmXFxH95tyybf4f4I2b7rbv0R06+S+sLa5EcsAmjWQRTpslXKhtrL2b1FXqKAPkX4M+CvEOm/8ABQv9oPxJeaDqll4d1PS9HjsdXns5I7W7aO1t1kWKVl2yFWVlba3y7fyd8RfAniO9/wCCjfwl8V22g6nc+GLPwrf2lzq8Ns7WsEx+07UkkHyoTvXaG+9ur64ooA/Of9uP4g/Efx98a4PhndfC34jav8D9LaG51qXwXo1xNJ4jkMKzLD56hVWFWZVZVbduVv4gu33P4GftRjxN4j8N+ALD9nv4nfDvQ/La0t73VfDTWWm2EccLMqMy8Rqdqov+0y19S0UAfEv/AAUUWTxf4n/Zy+Hloxkv9c8e2+oLHu2fuLVds0m4rt+Vbnd6/wB1Wr7ar5/vPgJr/i39ruz+Kfii60qbwt4X0VtN8K6VbtJJcrdTf8fN5NuVVjbaWjVVaQMu1vlZefoCgAooooAKKKKACiiigAooooAK+Kv+CpWnS6d8FvB3j62hklk8DeMNP1iXYm4+TvaMqD/DmRofvfL+lfatcf8AFL4e6T8V/h54i8G65CJtJ12xksrgMgcx7lwJF3fxK21lb+FlVqAG+JvAPgj4waPpr+JfDeheM9N2rdWa6xp0N5Eu5f8AWIsitt3KetfLH7aP7EGg+OPhPp1l8J/hP4Ss/EkOvWdzcHS9LsdPlks13+cvmbY9y/Mvy7vm219L/AvwDqnwt+EvhfwfrPiMeLL3Q7NdP/tj7H9kNxFGdsO6Pe+GWMRru3Nu27v4q9CoA5/wh4H8PfD/AEdNJ8LaDpnhrSVdpFsNJtI7WAM33m8uNVXca8C/a7+GfxH+Pt14S+GegQSaP8OdVuftfjHxMl1CjtaR9LGOPd5haT+JlXb9z5tu9a+naKAPjmL9nLxR+zz+1joXjP4OeHEufh34rhi0nxn4egvIbS305IlSO3vII2Zd3lrubYqs3+uVf9b8v11eWUOoW0tvcxJPbyxtHJDIu9XVuGVl/iFXKKAPKP8Ahk/4I/8ARGvh/wD+EvY//Gq8Z/4J/wD7LMvwH8E6vL4w8D6No/jf+3b57TVI4rWa7+wP5YjVbiPcyxttb93uXH92vr2igDC8ValqGk+GdUvtH0h/EOq29tJLaaVHcRwNeTKuVi8yT5U3MAu5vu18P6X+wFrXxO+BfjLVvifdLH8fvFd8PEC6xayLu0a6hRlsrSOZd37tV+VtrY+barN5atX37RQB5b+znqfxE1f4R+H2+KmgL4d8c28P2bUYEvIblZ2j+VbjdC7L+8X5iu75Wz7V5h+2J8HvGHxV8c/AHUPC2j/2pZeFvHFlrGryG6hhNraxyRs8m2R13/KrfKu5v9mvqGigD5v/AG//AITeKfjl+y54n8JeDdN/tXxFdT2UsFi1xHCZljuomb5pGVV+VWb5mH3ayv2zdJ+Od78CNJ8MfBPSjca9qIFlq91FfW9rcWdr5PzeTJNIiqzN8u5cso3bdp+ZfqWigD4H+DWqftEfAT4f6b4O8G/sk6fp+kWIPzHx3pzSXEh+9NM275pGx8zfQLtVVWvXf24/H914V/Yc+IOr6vaPpmpX+hJp89kJFZoprxo7do9yttbb5zbtrN8qt96vpuvF/wBoL9n9vj/e+A7HUfEb6f4T0DW49b1PQ4rMSf208PMMLybv3cStu3LtbduH3WVWoA0/2YfBFx8N/wBnf4ceGbgKLuw0G0iuPL3bRN5atJjd833mb/7GvVaKKACiiigCnf2cOo2U9rOvmQzxtFIv95W4avnmwvJbSbSVuJCbmJ9Hs5Wb+Ke01NrGdv8AgXnR19I9cV81fFMDw58Q7mM/Kk9xHew+yyNDMy/9/NLkb/tpXp4Fe0k6a6nHiXyR5j6UyKOO9cp8RPiLo3wu8L3Gu67cNBaRsFVY13SSu33URf4mNfF/xB+N3jX4pXMglv5/DWgM37nTNPk8uVl/6bSfeb/d+7Xy+MzCjgo/vHqOviqeH+M+29V8feGdAdo9U8RaXpsifeS8vI4mX/vpql0fxpoPiI40nXNO1NsZxZXSTf8AoJr83ovDmmxf8ucbN/ekXdu/76p7+HtPMiyRQ/Zp1bcsts3lsrf8Br57/WT3v4Z5n9qf3T9OTxR1r4Y+G37R3iv4ZXMEOt3Vx4q8Lqdshm+a9tV/vLJ/y0Vf7rf+O19neFvFGneMtBstY0i5W80+8jEsUyfxKf5H2r6bB46jjY81I9WjiKddXgec/tI61c2PhDT9Nsfn1HVdRhgtx83yyKfMi3bfm2+csKn/AK6Bf4q1vg/pUS6Xe6pBIJbW5ZLPTgUVfLsbbMMK/L2Y+ZJ/22+6v3a85+O2o3WvfF/wpoFhcyxTQ20jqqr8vmTt5atuPy7o/L85fvNtV/lZW219AaTp1ppGm2mn2UK29naRLDDCn3URV2qv5V9JW/dYWnT/AJve/r7omNP95iJS/lL55Fcp4r8cW/hye30+GGTU9cu8/ZNMtz+8l/224/dxr/FI3yr/ALTYUweJ/F95HqI0Pw7ZpqWuna0zzti2sY25EkzD5vm2ttjX5mx/CvzDQ8N+FYPD4kneRr/VbkK13qUy/vLhv/ZV/uxr8q1wKKguaZ1tt+7Ez/DfghrXU31/XLj+0/EUw2iT/ljYp/zxtl/gX+833pP4uAqr2eOMUDFLUyk5O7KUVHYKKKKgoKKKKACiivybvvEfjn/gpn+1P4q8CWHjK98HfCTwmZpQumZ3XCxyeTHI21v3ksjMzLu+VY1bHzfeAP1kor8n/wBp39hW/wD2I/hvcfFn4F/EnxbpT6NcW51iyvbtN88LSrHG6+THGrqsjrujkVlZWZt3y7W9R+Pvx5n/AGhf+CS3iHx3Lst9WvYLG21JLYeWqXEeq28M21dzbVbbuC5+7JQB+h9FfIf/AASomeX9iXwWrsSsdzqKKrH7q/bZm/8AZq+WfEF5On/BcG2/fODHcW8S8/dVtAXcv0+Zv++qAP1ior8p/wBun/gnH8M/hB8DviF8WdF1zxVdeIYLqG7W2vry3a033N/DHINq26tjbM+35uy/ep37B/8AwTm+Gvxa+Cvw5+Lmt6t4oj8QS3k169nZ3dstkzW1/LHGm1rdpNrLCu75+7cr2AP1Wor8WfFnwP0b9pv/AIKo+OfBHiy91Gz0u8urhpJ9KljjnXybNWjVWkjZf4V/hrp9ItPE/wCwP+374J+GvhPxjqmveBvFN5pkEumavJuVre6ma1VZFXavmRfMyuqr91V27dykA/X+ivyd8QXk6f8ABcG2/fODHcW8S8/dVtAXcv0+Zv8Avqvrr/gp7I9v+w58S3jcxPt05dynHytqVqrfpQB9UUV+av7J37KHhX9rv9gX4YaL4x1XXLCz0bU9TubZtFnhjYs11Mu1vMjk+X5m+7tr5Y/4Yu8Ef8PI/wDhn3+09e/4QzGPt32iD+0P+QP9u/1nk+X/AKz5f9X93/a+agD90aK8O/Zd/ZL8H/sleG9Y0Xwfe6xqMGq3i3lxNrNxFJJuVNoVTHHGu3/gPevcaACiiigAooooAKKKKACua+I/hKPx/wDD7xP4XlZVi1rS7rTXZhkBZoWjP/oVdLRQB8i/8EtvFH9vfsfeHNKnDpqPhrUL/Rb2GVdrRSrcPMqMv8LLHNFXgPgzwt+1ZYfHXV/i343/AGfbTx54skQWuiLc+L9Ot7bQLb5t0drH5z4Zg2PM+997+8277R+Ev7P5+D/xT+JPiLSNdX/hG/GV5Fqh8Mrp6xrZX23bNMkyt83m43Mu2vZ6APnbwPefE/8AaB8BfELwf8XvhgfhXp+r6VJpdrdWGv2uptcR3Ec0U7L5e7y2jUqV3Lht3+zXjPwQtv2o/wBlr4a2Pwwt/g9oHxK07SPMi0zxPpvimDTolikkd18+GZfMkZWb+FV+XavzNuavu+igD5e/Y++AXjL4b698S/iP8SJdMi8dfEK/gu7rTNGbzLfToYVk8uJZG+8371g3zMv7tfmavYPjhq/jXQ/hb4iuvh3oP/CSeOfszJpNgbiGBfOb5VkdpmVCse7zGXd823b/ABV6DRQB+f3iP/gnzrmgfs+aFrHhzUGvP2jtA1J/FP8AwkUcyxtqmpTSJJcW0k0m3dGw+VWZl3Mu5tvmSLX2x8O9W8Q634I0S/8AFeiDw34luLSNtR0pZ0uEtbjb+8VZI2ZWXdnHzdK6migD4a/4KBeCPj38WvEfhjwn4G8FP4q+EwSG+8QWdtrtrpkuqzLM+6ykkklWRYQixt8q8tJ/eVdvU/DX4o/tF6Jf+F/Dcv7Lul+EvB0E9vYyy2HjDT2TT7Pcqs0cKt83lx7m2r97bX15RQB8XfEn4KfFr4Tfta678dvhP4e0z4hWfibSodO1zwrqGppYXJaNYo1a2mdfLVdtvA3zs3/LT5fmXbn638Kvjh+1b8X/AIa6v8SvA+jfCnwN4I1iPxAumJrMesX99cR7WSNnjXy9m6P5vu/LJ/Ewr7hooAK+PX/Zu8R/tEftF+L/ABj8adBjt/AWkWdx4d8GeFri4hu/MimXbc6i3lsyxySBfl/5aLuXdt8lWb7CooA+Xv2Mvht8TPgTB4s+GHimxk1HwBod4z+DvE819DJNc2U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+    }
+   },
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### What is a Convolutional Neural Network\n",
+    "\n",
+    "A convolutional neural network is a **deep learning algorithm** that takes visual data as input.\\\n",
+    "Its architecture is inspired by the organization of neurons and the visual cortex in the human brain.\n",
+    "\n",
+    "![cnn_background.jpeg](attachment:cnn_background.jpeg)\n",
+    "\n",
+    "In reality, an image is a matrix, thus a 2D array, which can be reshaped into a 1D array and given as input to a classical neural network.\n",
+    "\n",
+    "And honestly on some data it can work, but the **convolutions through their filters can perceive the particularities of an image**. Their great strength is to be able to **bring out patterns**, to classify them.\n",
+    "\n",
+    "> I advise you to look at this [article](https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53) before you start on the subject."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Torchvision - Introduction & Installation\n",
+    "\n",
+    "The Torchvision library is a part of the PyTorch project.\\\n",
+    "This part contains popular datasets, neural network architectures and visual data processing functions specific to Computer Vision\n",
+    "\n",
+    "To **install it**, run the cell below:\n",
+    "> If you prefer to install it with your virtual env manager, Conda style, feel free to run the command in your command interpreter."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip3 install torch\n",
+    "!pip3 install torchvision"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Like all libraries, remember to import it before you can use it in code.\\\n",
+    "Run the cell below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import torchvision\n",
+    "import torch.nn as nn\n",
+    "import torch.optim as optim\n",
+    "import torch.nn.functional as F\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "from torchvision import transforms"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## II) - Get the data\n",
+    "\n",
+    "Before actually learning about convolution, let's start by creating a fully connected neural network to identify numbers.\\\n",
+    "This will be useful to compare the efficiency of both AI.\n",
+    "\n",
+    "Torchvision provides **several built-in datasets** in the ``torchvison.datasets`` module.\\\n",
+    "You can find the list of datasets [here](https://pytorch.org/vision/stable/datasets.html)\n",
+    "\n",
+    "Today we will work on the **[MNIST](https://en.wikipedia.org/wiki/MNIST_database)** dataset.\\\n",
+    "This dataset is iconic and certainly the most known, and the simplest of the domain.\n",
+    "\n",
+    "You will observe that even with a fully-connected one we get nice results.\\\n",
+    "In this dataset you'll find **digits in the form of an image** that you have to **classify from 0 to 9**.\n",
+    "\n",
+    "Start by downloading this dataset, don't forget to split it into separate **train and test sets**.\n",
+    "\n",
+    "> You can specify in the function [torchvision.datasets.MNIST(...,train=false/true,...)](https://pytorch.org/vision/stable/generated/torchvision.datasets.MNIST.html#torchvision.datasets.MNIST)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_set = None\n",
+    "\n",
+    "test_set = None"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualize the data\n",
+    "\n",
+    "You now have two variables.\\\n",
+    "The training dataset ``train_set`` and the test dataset ``test_set``.\n",
+    "\n",
+    "A step that is sometimes neglected is to **think about visualizing your data**.\\\n",
+    "For example when working on a visual dataset, it can be interesting to look at what a sample image of this dataset can look like.\n",
+    "\n",
+    "Indeed, from an optimization point of view, knowing your data can allow you to adapt your architecture in order to maximize the efficiency of your model on these data.\n",
+    "\n",
+    "To visualize this data, simply execute the cell below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig = plt.figure()\n",
+    "for i in range(6):\n",
+    "  plt.subplot(2,3,i+1)\n",
+    "  plt.tight_layout()\n",
+    "  plt.imshow(train_set[i][0].reshape(28, 28, 1), cmap='gray', interpolation='none')\n",
+    "  plt.xticks([])\n",
+    "  plt.yticks([])\n",
+    "print(fig)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also look at different attributes like the number of images in the dataset, the size of each image or the label of an image."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image, label = train_set[0]\n",
+    "print(\"total images :\", len(train_set)) # pixels value\n",
+    "print(\"shape :\", image.shape) # pixels value\n",
+    "print(\"label :\", label) # Number represented in the image"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, we have images **28 pixels high and 28 pixels wide**, with **one channel** (black & white image).\n",
+    "\n",
+    "These images represent a number from 0 to 9, we have **10 different labels** (or 10 different possible output).\\\n",
+    "The first picture represents a 5, therefore its label is 5."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Using Batch"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**60,000** is a lot of images to process one by one, to make it easier for our model to process this data while training we are going to use ``batch``.\n",
+    "\n",
+    "``Batch`` is a hyperparameter that defines the number of samples to work through before updating the internal model parameters. In other words, before calculating the error and apply backpropagation after each image, if our batch size is 64 we will go through 64 images before doing it. **This improves the learning of our AI** by **applying the backpropagation on the error average.**\n",
+    "\n",
+    "As in the previous notebook we will use a [**``dataloader``**](https://pytorch.org/docs/stable/data.html), this time we don't need to redefine a ``Dataset`` class since we are using a ``builtin`` dataset in ``torchvision``.\n",
+    "\n",
+    "Remember to specify that you want a ``batch_size`` of ``64``."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_loader = None\n",
+    "\n",
+    "assert len(train_loader) == 938, \"Your training dataset of 60,000 images isn't split with a 64 batch_size\"\n",
+    "\n",
+    "batch = next(iter(train_loader)) # obtain the first batch\n",
+    "images, labels = batch\n",
+    "print(\"shape :\", images.shape)\n",
+    "print(\"labels :\", labels.shape)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now have `938` blocks containing `64` images each (and their equivalent labels).\\\n",
+    "This will **drastically decrease our training time** because with one backward propagation, 64 images are processed.\n",
+    "\n",
+    "> Pytorch is built to be used with batch, it is thus quite simple to implement it in our code."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here is an example of a classical neural network that works with batches of 64."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyNetwork(torch.nn.Module):\n",
+    "    def __init__(self):\n",
+    "        super().__init__()\n",
+    "        self.linear1 = torch.nn.Linear(1, 10)\n",
+    "        self.linear2 = torch.nn.Linear(10, 1)\n",
+    "        \n",
+    "    def forward(self, x):\n",
+    "        x = torch.nn.functional.relu(self.linear1(x))\n",
+    "        x = torch.nn.functional.relu(self.linear2(x))\n",
+    "        return x\n",
+    "\n",
+    "model = MyNetwork()\n",
+    "input = torch.ones((64, 1), dtype=torch.float)\n",
+    "\n",
+    "mse = torch.nn.MSELoss() # Loss function\n",
+    "expected = torch.ones((64, 1), dtype=torch.float)\n",
+    "\n",
+    "output = model.forward(input)\n",
+    "loss = mse(output, expected)\n",
+    "\n",
+    "print(\"Input  :\", input.shape)\n",
+    "print(\"Output :\", output.shape)\n",
+    "print(\"loss :\", output.shape)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, the model accepts and return the data and prediction in batch.\\\n",
+    "This also applies in every loss function, we can pass the batch of the predictions and the batch of expected values.\\\n",
+    "The final loss will be the average of each loss in the batch."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Probabilstic Prediction"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A key difference is going to be the output of our model.\\\n",
+    "In this exercise, we are using a probabilistic approach.\\\n",
+    "This means that are model will **output a probality for each labels.**\\\n",
+    "We have 10 labels (one for each digit), **our model should output 10 values.**\\\n",
+    "The label with the highest value will be the label predicted by the model.\n",
+    "\n",
+    "The ``mean squared error`` isn't meant to deal with this type of output.\\\n",
+    "To calculate the loss we are gonna need the [``cross entropy loss``](https://ml-cheatsheet.readthedocs.io/en/latest/loss_functions.html#cross-entropy)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "loss_fonct = torch.nn.CrossEntropyLoss() # Loss function\n",
+    "\n",
+    "output = torch.rand((64, 10), dtype=torch.float) # theoretical output of the model\n",
+    "expected = torch.ones((64), dtype=torch.long) # expected labels\n",
+    "\n",
+    "loss_fonct(output, expected)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> Cross entropy loss takes the output of the model and the expected label.\\\n",
+    "You don't need to calculate the label of the prediction."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## III) - Image & simple NN\n",
+    "\n",
+    "Now that you know how to work with images and batches.\n",
+    "\n",
+    "**Exercise :**\\\n",
+    "With all this information, it's your turn to build a simple model (without convolution) to identify the number in the given images:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyModel(torch.nn.Module):\n",
+    "    def __init__(self):\n",
+    "        super().__init__()\n",
+    "        # Define layers, the input of the first layer should be the number of pixels of an image\n",
+    "        # The output size should be 10 for the 10 possible output. For example you could define 4 linear layers.\n",
+    "        \n",
+    "    def forward(self, x):\n",
+    "        # Use your activation functions here, for example you could use ReLU\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "EPOCH = 2\n",
+    "\n",
+    "model = MyModel()\n",
+    "loss_fonct = torch.nn.CrossEntropyLoss()\n",
+    "optimizer = optim.Adam(model.parameters(), lr=0.01)\n",
+    "\n",
+    "for epoch in range(EPOCH): #training\n",
+    "    for batch in train_loader:\n",
+    "        optimizer.zero_grad()\n",
+    "        images, labels = batch\n",
+    "        output = model.forward(images.reshape(images.shape[0], 28 * 28))\n",
+    "        loss = loss_fonct(output, labels)\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "\n",
+    "total, correct = 0, 0\n",
+    "for image, label in test_set: #testing\n",
+    "    output = model.forward(image.reshape(1, 28 * 28))\n",
+    "    if (output.argmax(dim=1).item() == label):\n",
+    "        correct += 1\n",
+    "    total += 1\n",
+    "\n",
+    "print(\"Accuracy:\", correct / total)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## IV) - CNN (Convolutional Neural Network)\n",
+    "\n",
+    "Let's dive into the main subject.\n",
+    "\n",
+    "A convolutional neural network (CNN) is **a type of artificial neural network that is commonly used in image recognition and processing tasks.**\\\n",
+    "It uses mathematical operations called convolutions to analyze and process input data, such as images, and extract features from it.\\\n",
+    "The network then uses these features to make predictions or classifications.\\\n",
+    "CNNs are commonly used in tasks such as image classification, object detection, and face recognition."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Convolutional filters\n",
+    "\n",
+    "A convolutional filter is a mathematical operation that is commonly used in image processing.\\\n",
+    "It is called a **\"convolution\" because it involves combining two sets of data to produce a third set of data.**\\\n",
+    "In the context of image processing, a convolutional filter **is used to extract features from an image by applying a set of weights to the pixels in the image.**\n",
+    "\n",
+    "Imagine that you have a small grid of numbers, which represents the pixels in an image.\\\n",
+    "A convolutional filter is like a sliding window that moves over the grid of numbers, and applies a set of weights to the numbers in the window.\\\n",
+    "For example, the weights might be [-1, 0, 1] for a horizontal edge detector, which would look for differences in pixel values between adjacent columns of the image.\n",
+    "\n",
+    "Convolution can be described as **taken a filter (kernel) and applying it to a given image**. This might not make sense so let me illustrate it:\n",
+    "\n",
+    "<div>\n",
+    "    <center>\n",
+    "    <img src=\"./assets/conv.gif\" width=\"600\" style=\"padding-left: 20px;\"/>\n",
+    "    </center>\n",
+    "</div>\n",
+    "\n",
+    "Here are concrete examples:\n",
+    "\n",
+    "<div>\n",
+    "    <center>\n",
+    "    <img src=\"./assets/conv_exemple.png\" width=\"600\" style=\"padding-left: 20px;\"/>\n",
+    "    </center>\n",
+    "</div>\n",
+    "\n",
+    "**The result of the convolutional filter is a new set of numbers**, which represents the output of the filter. This output can be used to extract features from the image, such as edges or textures.\n",
+    "\n",
+    "\n",
+    "Each convolution layer has its own filter, with multiple parameters such as:\n",
+    "- `Kernel size:` size of the filter(kernel)\n",
+    "- `stride:` the amount of column / row we move to the right / bottom\n",
+    "- `padding:` column / row of zeros added to the edge of the image\n",
+    "\n",
+    "<div>\n",
+    "    <center>\n",
+    "    <img src=\"./assets/params_exemple.png\" width=\"600\" style=\"padding-left: 20px;\"/>\n",
+    "    </center>\n",
+    "</div>\n",
+    "\n",
+    "The shape of the output can be computed with the following formula:\n",
+    "\n",
+    "## CNN output size formula (square)\n",
+    "- we have an $n * n$ input\n",
+    "- we have an $f * f$ filter\n",
+    "- we have a padding $p$\n",
+    "- we have a filter $f$\n",
+    "- we have an output size $O$\n",
+    "\n",
+    "## $O = \\frac{n - f +2p}{s} + 1$\n",
+    "\n",
+    "## CNN output size formula (non square)\n",
+    "- we have an $Nh * Nw$ input\n",
+    "- we have an $Fh * Fw$ filter\n",
+    "- we have a padding $p$\n",
+    "- we have a filter $f$\n",
+    "- we have an output size $O$\n",
+    "\n",
+    "## $Oh = \\frac{Nh - Fh +2p}{s} + 1$\n",
+    "## $Ow = \\frac{Nw - Fw +2p}{s} + 1$\n",
+    "\n",
+    "Now that you know how convolutions work, let's try to use them\n",
+    "\n",
+    "**Exercise :**\\\n",
+    "By changing the convolution parameters, try to match the expected output size"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Expected :**\\\n",
+    "`torch.Size([1, 1, 26, 26])`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = torch.randn(1, 1, 28, 28)\n",
+    "filter = torch.randn(1, 1, 3, 3)\n",
+    "\n",
+    "# code here (modify stride & padding value to match expected output size)\n",
+    "\n",
+    "out_feat_F = F.conv2d(image, filter, stride=None, padding=None)\n",
+    "\n",
+    "assert out_feat_F.shape == torch.Size([1, 1, 26, 26]), \"The convolution does not match the expected output size\""
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Expected :**\\\n",
+    "`torch.Size([1, 1, 28, 28])`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = torch.randn(1, 1, 28, 28)\n",
+    "filter = torch.randn(1, 1, 3, 3)\n",
+    "\n",
+    "# code here (modify stride & padding value to match expected output size)\n",
+    "\n",
+    "out_feat_F = F.conv2d(image, filter, stride=None, padding=None)\n",
+    "\n",
+    "assert out_feat_F.shape == torch.Size([1, 1, 28, 28]), \"The convolution does not match the expected output size\""
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Expected :**\\\n",
+    "`torch.Size([1, 1, 15, 14])`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "image = torch.randn(1, 1, 28, 28)\n",
+    "filter = torch.randn(1, 1, 2, 4)\n",
+    "\n",
+    "# code here (modify stride & padding value to match expected output size)\n",
+    "\n",
+    "out_feat_F = F.conv2d(image, filter, stride=None, padding=None)\n",
+    "\n",
+    "assert out_feat_F.shape == torch.Size([1, 1, 15, 14]), \"The convolution does not match the expected output size\""
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From here you should be fine with the effect that a convolution layer can have.\\\n",
+    "Let's look at what is often used with this, the pooling layers"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Pooling layers\n",
+    "\n",
+    "The main purpose of a pooling layer is to reduce the spatial dimensions of the input without losing important information.\n",
+    "\n",
+    "This has two main benefits: **it reduces the number of parameters in the model**, which makes the **model faster to train and less prone to overfitting**, and it also **makes the model more robust to small translations** and deformations of the input.\n",
+    "\n",
+    "A pooling layer is typically added to a CNN after one or more convolutional layers, which are responsible for extracting high-level features from the input image.\\\n",
+    "By combining the outputs of multiple convolutional layers and applying a pooling operation, a CNN can learn to recognize complex patterns in images and use them to make predictions.\n",
+    "\n",
+    "> Multiple convolution layer can be added one after the other but it can be useful to add a `Pooling` after some convolution layers.\n",
+    "\n",
+    "A limiting factor of convolutional layers is that they record the precise position of features (objects you're trying to detect) in the input.\\\n",
+    "This means that small movements in the position of the feature in the input image will result in a different prediction.\\\n",
+    "This can happen with re-cropping, rotation, shifting, and other minor changes to the input image.\n",
+    "\n",
+    "A common approach to addressing this problem from signal processing is called down sampling.\\\n",
+    "This is where a lower resolution version of an input signal is created that still contains the large or important structural elements, without the fine detail that may not be as useful to the task.\\\n",
+    "This can be achieved by using `Pooling Layer`\n",
+    "\n",
+    "The most common pooling layer are `Max Pooling` and `Average Pooling`.\n",
+    "\n",
+    "They work similarly to simple convolution layers but instead of being multiplied by a kernel.\n",
+    "\n",
+    "**Here is an example of pooling layer with a (2x2) filter, and a stride of 2.**\n",
+    "\n",
+    "<div>\n",
+    "    <center>\n",
+    "    <img src=\"./assets/pooling.png\" width=\"400\" style=\"padding-left: 20px;\"/>\n",
+    "    </center>\n",
+    "</div>\n",
+    "\n",
+    "`Max pooling` will **take the pixel with the highest value in the kernel.**\\\n",
+    "`Average pooling` will **take the average of each pixel in the kernel.**\n",
+    "\n",
+    "Let's try a little exercise to make sure you understand how a pooling layer works.\n",
+    "\n",
+    "**Exercise:**\\\n",
+    "Get the value of a ``max pooling`` and an ``average pooling`` with size of ``(2x2)`` on this kernel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "kernel = [[2, 3], [5, 6]]\n",
+    "\n",
+    "# code here (~2 lines)\n",
+    "\n",
+    "max_pooling = None\n",
+    "average_pooling = None\n",
+    "\n",
+    "assert int(max_pooling) == 6 and int(average_pooling) == 4, \"You failed the test, try another approach !\""
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Torch & CNN\n",
+    "\n",
+    "Convolution and Pooling layer are implemented to highlight features in an image.\\\n",
+    "These highlighted features must then go through fully connected layers to actually have an output in the end.\\\n",
+    "After your convolution and pooling layer, you must flatten your data, to pass it into fully connected layer(s) to output 10 labels.\n",
+    "\n",
+    "<div>\n",
+    "    <center>\n",
+    "    <img src=\"./assets/full_model.png\" width=\"800\" style=\"padding-left: 20px;\"/>\n",
+    "    </center>\n",
+    "</div>\n",
+    "\n",
+    "**Exercise :**\\\n",
+    "With all of this knowledge, it's your turn to create a ``CNN model``.\\\n",
+    "Here is the list of useful functions for the creation of your CNN:\n",
+    "- A 2D Convolution layer: [torch.nn.Conv2d](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html)\n",
+    "- A 2D Max Pooling layer: [torch.nn.MaxPool2d](https://pytorch.org/docs/stable/generated/torch.nn.MaxPool2d.html)\n",
+    "- A Linear layer: [torch.nn.Linear](https://pytorch.org/docs/stable/generated/torch.nn.Linear.html)\n",
+    "- ReLu Activation function: [torch.nn.functional.relu](https://pytorch.org/docs/stable/generated/torch.nn.functional.relu.html#torch.nn.functional.relu)\n",
+    "\n",
+    "> Images are black & white, so there is 1 channel, keep that in mind to build your conv2d layer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyModel(nn.Module):\n",
+    "    def __init__(self):\n",
+    "        super().__init__()\n",
+    "        self.conv1 = None # Add a conv2d with a kernel size equal to 5\n",
+    "        self.maxpool1 = None # Add a MaxPool2d with kernel size and stride equal to 2\n",
+    "        self.conv2 = None # Add a conv2d with a kernel size equal to 5\n",
+    "        self.maxpool2 = None # Add a MaxPool2d with kernel size and stride equal to 2\n",
+    "        self.linear1 = None # Add a Linear layer with input of 16 and output of 128\n",
+    "        self.linear2 = None # Add a Linear layer with input of 128 and output of  64\n",
+    "        self.linear3 = None # Add a last Linear layer with input of 64 and output of 10\n",
+    "        \n",
+    "    def forward(self, x):\n",
+    "        x = None # Compute your self.conv1\n",
+    "        x = None # Apply ReLu function\n",
+    "        x = None # Apply your self.maxpool1\n",
+    "\n",
+    "        x = None # Compute your self.conv2\n",
+    "        x = None # Apply ReLu function\n",
+    "        x = None # Apply your self.maxpool2\n",
+    "\n",
+    "        # You applied conv & pooling previously, now we will pass that to our fully connected layers\n",
+    "        # For that the line below allow us to flatten the data.\n",
+    "        x = x.reshape(-1, 4 * 4)\n",
+    "\n",
+    "        x = None # Compute your self.linear1\n",
+    "        x = None # Apply ReLu function\n",
+    "        x = None # Compute your self.linear2\n",
+    "        x = None # Apply ReLu function\n",
+    "        x = None # Apply your self.linear3\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "EPOCH = 5\n",
+    "\n",
+    "model = MyModel()\n",
+    "loss_fonct = torch.nn.CrossEntropyLoss()\n",
+    "optimizer = optim.Adam(model.parameters(), lr=0.01)\n",
+    "\n",
+    "for epoch in range(EPOCH): #training\n",
+    "    for batch in train_loader:\n",
+    "        pass # (code here ~6-7 lines)\n",
+    "        # get images & labels from batch\n",
+    "        # compute the forward propagation and store the output\n",
+    "        # use your loss function and store it\n",
+    "        # reset your gradient\n",
+    "        # compute your gradient\n",
+    "        # apply your gradient\n",
+    "    # print your latest loss for each epoch\n",
+    "\n",
+    "total, correct = 0, 0\n",
+    "for image, label in test_set: #testing\n",
+    "    output = model.forward(image.reshape(1, 1, 28, 28))\n",
+    "    if (output.argmax(dim=1).item() == label):\n",
+    "        correct += 1\n",
+    "    total += 1\n",
+    "    \n",
+    "accuracy = correct / total * 100\n",
+    "print(f'Your accuracy is {accuracy}% !')\n",
+    "assert accuracy > 80, \"Your accuracy is not good enough, keep trying to build\""
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Congratz\n",
+    "\n",
+    "Congratulations for having reached the end of this lesson !\\\n",
+    "You have been able to create your own convolutional neural network using Pytorch."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.13"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "7d6993cb2f9ce9a59d5d7380609d9cb5192a9dedd2735a011418ad9e827eb538"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/AI/day03/README.md b/AI/day03/README.md
new file mode 100644
index 0000000..efb7039
--- /dev/null
+++ b/AI/day03/README.md
@@ -0,0 +1,32 @@
+# ~ PoC AI Pool 2024 ~
+
+- ## Day 2: Neural Networks from Scratch
+  - ### Module 1: Linear Regression
+    - **folder:** [1 - Convolutional Neural Network](1%20-%20Convolutional%20Neural%20Network)
+  - ### Module 2: Logistic Regression
+    - **folder:** [2 - My nn Torch](2%20-%20My%20nn%20Torch)
+  - ### Module 3: Deep Learning
+    - **folder:** [3 - VAE-GAN](3%20-%20VAE-GAN)
+
+---
+
+**Hooray : You've made it to AI !**
+On today's menu, we'll enter the wonderful world of machine learning with two major algorithms : Linear and Logistic Regression, followed by the modern approach of Deep Learning using PyTorch !
+
+> Here's a list of resources that we believe can be useful to follow along (and that we've ourselves used to learn these topics before being able to write the subjects):
+
+## Module 1
+
+- [CNN](https://towardsdatascience.com/convolutional-neural-networks-explained-9cc5188c4939)
+- [Custom nn module](https://pytorch.org/tutorials/beginner/nn_tutorial.html)
+
+## Module 2
+
+- [nn.Linear](https://pytorch.org/docs/stable/generated/torch.nn.Linear.html)
+- [nn.Conv2d](https://pytorch.org/docs/stable/generated/torch.nn.Conv2d.html)
+
+## Module 3
+
+- [VAE](https://towardsdatascience.com/understanding-variational-autoencoders-vaes-f70510919f73)
+- [GAN](https://towardsdatascience.com/gan-by-example-using-keras-on-tensorflow-backend-1a6d515a60d0)
+- [VAE-GAN](https://wandb.ai/shambhavicodes/vae-gan/reports/An-Introduction-to-VAE-GANs--VmlldzoxMTcxMjM5)