{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Few words about Kaggle experience:\n\n> \"Kaggle has established itself as a prominent platform for data science and machine learning competitions, attracting a diverse community of participants from around the world.\n> Kaggle competitions serve as a catalyst for innovation by providing a platform for participants to solve real-world problems using data science and machine learning techniques.\n> Over the past two years, certain themes have emerged as prominent areas of focus in Kaggle competitions. One notable trend has been the increased emphasis on healthcare-related challenges, driven by the need for data-driven solutions in the medical field. Competitions targeting finance, cybersecurity, and environmental sustainability have also gained traction. This shift reflects the growing demand for data-driven insights in various industries. Notable competitions in these domains include healthcare diagnostics, fraud detection, climate change prediction, and customer churn analysis.\"\n\n>  thanks to **Preethi Raghuraman**\n\n> Extracted from : [AI REPORT 2023: Information Retrieval](https://www.kaggle.com/code/preethiraghuraman/ai-report-2023-information-retrieval/notebook)\n\n# Tabular and/or time series data in Kaggle platform.\n\n## *Notice: I collected only relevant data based in relevant results from three past Kaggle competitions about forecast and prediction for marketplace.*\n* AMEX - was a competition regarding to risk analysis to predict default payment from customers\n* JPX - was a competition to predict stock perfomance at JPX stock exchange\n* G-Research - was a competition regarding prediction about cryptocurrence trends.\n\n# LightGBM Classifier in Python:\n\nWhat is Light GBM?\n\nLight GBM is a gradient boosting framework that uses tree based learning algorithm. It differs from other three based algorithms because it grows trees verticaly so, this means that grows tree leaf-wise while other algorithm grows level-wise.\n\n![image.png](attachment:a327c0a9-140c-4d81-b9b6-2dbe19435717.png)![image.png](attachment:81b89d32-ead8-4e94-a700-2940fa417c90.png)\n\n\n## **See more at :** \n>[LightGBM Classifier in Python](https://www.kaggle.com/code/prashant111/lightgbm-classifier-in-python)\n\n>[What is LightGBM...](https://medium.com/@pushkarmandot/https-medium-com-pushkarmandot-what-is-lightgbm-how-to-implement-it-how-to-fine-tune-the-parameters-60347819b7fc)","metadata":{},"attachments":{"a327c0a9-140c-4d81-b9b6-2dbe19435717.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAtAAAAETCAIAAACQoaZMAAAgAElEQVR4nOy9d5Qcx5Xm+90bmVmmvUUDDY+GJQhD0MiLpEiKVhyJIkVJMxy5kWYkrY5298zsW/POzjO7e868t2/mvd2RmdFIpCiKAj1AJzrQE/QEQMKbhkcDjTbVXS5NxH1/ZFV1NYAmAQINgGD8Th6gqjozKzLrZsQXN27cIBGBxWKxWCwWy3jCZ7oAFovFYrFYzn2s4LBYLBaLxTLuWMFhsVgsFotl3LGCw2KxWCwWy7hjBYfFYrFYLJZxxwoOi8VisVgs444VHBaLxWKxWMYdKzgsFovFYrGMO1ZwWCwWi8ViGXes4LBYLBaLxTLuWMFhsVgsFotl3LGCw2KxWCwWy7hjBYfFYrFYLJZxxwoOi8VisVgs444VHBaLxWKxWMYdKzgsFovFYrGMO1ZwWCwWi8ViGXes4LBYLBaLxTLuWMFhsVgsFotl3LGCw2KxWCwWy7hjBYfFYrFYLJZxxwoOi8VisVgs444VHBaLxWKxWMYdKzgsFovFYrGMO1ZwWCwWi8ViGXes4LBYLBaLxTLuWMFhsVgsFotl3HHOdAGOxIzxuVVGFovFYrF8dLHtuMVisVgslnHHCg6LxWKxWCzjjhUcFovFYrFYxp2zIoZjrLiNsfaxKslyMhyPvY2yMal6Tae2LBaLxfJxwbbdFovFYrFYxh0rOCwWi8VisYw7VnBYLBbLWYqIfPBOFstHhLMihgOACLTWWhsDYmblsBo9WG6Hzi2nkNjeRITZUaqku/0ARFAOYtsTA5AAIGt9ljOBiBCVbE9HWjmq8lobTUSO41R2sFjOfuiMK2gRiQyM0aX37BDDaAFARIoRP1DVT5V1y1g+NNX2RkRKKSIYAwAOA0BkYLQoAjMdQ3DY6t1yejHGRFEEgIiYmBWLiNbaGENEihUrtrLD8pHgNAgOA3A8L+CYQkFEtBBQEhZC4PKeBjACAzCNOtYKDstYvI+lxRxpbwIiVNxp2kBrAeDEdbgVHJYzijGG+UhzPrrStoLD8pHg9AkOAShuCQQADEGA+PP+THTg0MFd3d0HDh7MZAbT6ZqGxobamtp58+Y2NjY1NbgEOIAqnzEuMqPkBRnn8ls+ShgYgGObVhiZ0RrbGwAT29vBgzt3dh84ePDw4cM16dqGhobadM30GTMmtLdPmJCOLY1jvUFCII4PFQBsNYdlHDAATJVUjqvHvI/6BAYK2LR5y4EDPfl8LpPJ5HLDqVSqo33CjBkzOtraOzrq48MoNn0yAAGiwVUfnpmrsliqGX/BIQCgCQACXxyJ3KQbfxwA72zve371G9279w8ODmWHMkU/z87Ik9Hc3NzY2Dhv3rzLPn3xnPakKfg1qQSAqFR0MMQKDksVxsBoOAFAgGfgmAhaI5EoRvAcvLtj8JlVL2/ZsSuTz+fDghYJgiCWwSxobGpqbmqa1Nl58UWLPnveBAOkgcAIMSlAIYAYkGddbJZTjQECACGSAoRRVOM4OcAAL7y9f8OW7q1bt/YP9BttCoWC7/tGdDrppJPJ2lRt2k1M6+z49KeWLVs8RXxJuyRhnhIKSOQAATxAGShrs5azgNMiOAhxgIYCgpzvJRM5X/ZmcssffmLLjl1D+aCn93A+lyvmc1oHokbKU19f7zpua2trc23688vOu/n6q2sSTtKhQADArcrHZGWHJcbAaHAsOKJsrj6VBpNvsHXf4IOPPLV5a3d2uJgZzuYKhWxhODLGj7SUQjXQ2tqaSCRc150xbUprU+q2r900b1JtfFoHYIkAA3Ks4LCcamLBwRqejo0NeHV778NPPLth677MUD6bzWkdDQwORmGojfEUKdZJ1016qYTjtrU019R6582fc/UXPndBV6tEIPbBVnBYzjpOR9CoATSgANYGQgVNa3f2/+PvHzjUP5Ab7M307s8N9gXFgg4DMCnPqSSCLBQKNbW1Ezs62ts7jObF5837zq1/0tnWmHAdhomHVIQYVnBYKsjI6IkCIiAEnntrxx8efOpg70Ax2z/Y1xNmM1GxEBQLIhQyaypVxorZiNTU1HRM6kw3Tmhvab32iksv/8TC9hSYyk5pst5pyzggpX8NIw88++quO5ffn8lmh/oPDQ8ODAwOBkEQ19WK2YF4JmASKNcoVdPY0toxhb3apoaGm677wteuXKgFHpkIBBAJWEBWcFjOAtTf/u3fjusXiCmFXEDADAi9tn73//j17/f2DQ4ODe/a9O5w734pZiUoitZitNLakUjpSOmIooAi/8DuXYVc3vWSmWx+S/feSVOntLfUO6KJBCiF/1nBYakQ17BM8I0ooodeWrPiyWf37R3o7+3bvu1d4w8NHu4xft4zpMQQQkKoJFQSIvLD7KCLqPfgQd83hZD2HTw8nC0uWTDdrZzdVtyW8YBKmiMiPLxqy/KH/pgZyu3esSVzcG+Y7aOwoCRMsvFIOxKyDuEXdRAEQa7g530d5XK+H8CAt+3aVTTuvDmdLhGLURJH4cNWkJazgXEUHCJS0gOVME+mjTt6fnbHH/b19vXu33Vo9xaT63MReY7DyhUvrZTjknFEswgZ4zIrQcrzJCgePrg/WduY4fr1O/YvmTe3tT6JyIfDIEVWvVsqlCtuYwBFK15ae9+jTx0+PLjlnbcyB3YqyZMuOkxMDsQDCBQxhUq0Es0SJR0mEyqgODxE5Bappnc4iAwvmDcRAUg0KRs0ajnVCCAAIyA88uKOe556eW/PoZ4dG/y+/eQPsQ6UaEe0Km8EkErCSbLHnquiwI8KuSg/7OdyifqanXv3eV7t/JkdijiehWXYhjpbzgrG28NBsdQgAyPI+Lj9nkc2bO0eOHy4r2dXmO13SBxWIGWIhZggntGOGJZSP7X0L8Cks4UgoxMCNz88uGTR/KTrBtkh5SWtj9sSIwZGIAAzhLF6474HH39m996eA7t35Q/vpyDLOiQiEgaYhIWEOFQICYZgWDTBKDFExmHODA8NBQLX29dzoK19ctfUBh2Kcq26tZxqCGGkA8Nv78jcteKJbXv27tm5rdi7qy6hJfSVCMcbgSAEAUGTI0QgTRCHWYmhoJgv5oo6JOX29w83tkyaOrGeiQ0BMGxdc5azgHG2QhIqiQYxwCMvb35zS08uV+jdt0PnBhIUKccR5UXkGLCSyDURAAPHwAG5Agfkglwh103U5IYz/sFtweC+19dueum9PXkDr7bJ+rgtFYRRDIshiQEyGk+8+Na2XYcGD/UPHtjvIVQUEsDGYXIBNhyBgnjaNgnHKgRgE0cFoYhoMBzcMdCztTdz+L4nnj4YQqfU8aw0a7GcEBrQrhoQ3P3o490Hdg8f7jbDuxENMAIhGOJ4E3D5dewNCUiYjaO044E9VxLsZw51D/bt3b7nwGPPv9FfQAiI7Y9ZzhrGv7UmAzLCFDH++PyLh4eH9x/YM9x/0IV2WDnERMQsDKMkUog4TnVwVMEig4TnOMXhwYO7i9o89dIbRQMc31Ljlo8Pvg5DGAO89e6ONes35XPFQ3u7OcgxaYfZdVyHmQSAAUWx2oBwHPUxshGKxUJtwklxNNCzQ5E5cOjgqpfX+YD+wBJYLCeIAYrA2o17d3TvzvQdGuzZyVHeVZLNZkVEYrdG7IUjmJJ+MAzDoyP+HTaOKRzevzuXz67fsOWd9XsMMO6TAiyW42YcBQeVEKPId/DS2s1DuYHccO/AwZ1NDamEm3TZdQxcE3k68kS7EAUilngDmfhfkAEMdMRiSAdDfb1DmYHdu/bu2DsE+zhZRlObrmOovgCbtu/IDmcG+/ZJsS/tRiwg5RJRLDUUiQIRKQjHHjUDx7Bn2DPKEfISXj20Yi0JUP+encN9hzZv35E31t4s44IfYvOGrcFAP2WHqBiwJkUpdpKGYMhUNilvAEqimSLhyBAMMcCtdXUmnwmHD4f+8Jp31+l4vFlrqeLMXqnl48z4ezhYKVAR2LKr2y9kC5l+RVrFeQ/ABCiBEqPE0MiDYMqeC1PayABxMIdhmNzQcKGQ37ylOxj30ls+agiYUAjQO5AJg3xQGHA5YhOygEq5ak2VgUEqCrfsuDZgCLMwG4eFlRh/eDDM53v7+vf25M/glVnOYQ73+j37ekyhUMxklIlz5bKAwSQjOuPo40qWLAQBA6zD0CMqDvWFhaGde/ft7TcMKOVYX7DlbGCcBUclsTSwbdcu1pQbHGJXhZBjPTyjiGe6lt0ko/YeHByMIr19x3YbvmGphgGSAMBgQe/Z3xcWsv7woKOcCGROYipTPpfXWvf19R8+fPjUFdZiGWF4ePhAT08YhplM5kOfRICCHzqOkx/u00G+p394/+FMnJWfrF/DchYw7k12MDwcas3AcDYfBYEOw1Qq/YFq4/0Jw1DrqL+vb8i6OCxHYEQAP9R9A4M69Iv5YXLYnJy9EVMURUNDQ9ls9hSV0mIZRSaTKRaLIuL7/smcxw+1UoqiSId+qCWbDwwQ5D68iLFYTiHOeH+Bl0r5Rg9BDQ0N6SgKw8hFpD74OKAqfyhTKdaaQESko0gph4jS3riV2/LRxHUSRYNsNpsvFEQkisIoIh49bj3KYVb9ksr/c7wAVokoikSEmV3XhcUyDriep6MIQDKZhEQf+jw1NTVBGEZhyMzFYjEMQwK8ZApMZKerWM404z8oIUYpxyO0tbQ6CS+ZTmlzsv69RCLBRE3NzaeoiJZzCibUpBJNDXWOl0yk6k0UKdDJjGEHQRjpCMDRC4VbLKeEVDJZU1tLRI5znN2xY8MwAMhLCLgmlair8QygtQ3gsJwVjHceDhiCw5xgTOuc5KaTqYY6E0Uu6GQ0RyqdJqZJEyfZx8hSTbxqj0NoqUt2tDa4qdpkfaOOtANdXra7itIEqLEYeTQcRyUSidra2oaGhvEquuXjTW1dXXNTEzF53od32xKgSBSzk6yDm+xoqp3QVBcJIlE2X5HlbGDch1QECoALtLe0ciLp1tRFhiEkBGNESqF8BECRUCkZeoXKQ1JqGwQwcNxESkg1t1gPh+VIIgERatOqqaFBJWoT6UbfdAMMMgaOMKOUfAN0tASphgmaAECcRLq+traltaF+Qkvj6boOy8cIBuqSidr6mpA849QK5VgAo4kF8XQVAgBTLRrKQdDlVBwMQOI6VbnGq6FEbUNDY0tTSgjKSZ7eC7JYjs24y15mJQADn/7sZx0n1do2OZlq0KK0hgGFzL5iXzkhsxbSQhFxyEdtIBgNow27xvHaOqdN6Jx6wYVz0uNdestHDSEIkPCweMklQUgNTRMclTAGBiyEkByfvZC9kJyytK3MkjUs8QYAxogfBoq8bEE3t85mblw4b+7kJscOg1tOOQS0N9LC+fNUw8SGyXMzwwVHxNGRq6G0w8Yj4xnxBI4mJ2QnZEcT6zj3aPVGbERyQVjfPtWrb5u7YEEyCQ8g9X6uPIvltDHugoMIWsBARy0WL5xnTDRpyqxhH6GIIQOj4xnmMGIIQqa6AahsROQkEsVIDLutHZMTrjOva9rkJPLGxkFZRqEAARxgWmfHvK6ZSqmmCZMLkdKlhNCGETEiholXsa/K3ziyscAYnaitzRppmjC5tr5x8qTOpfPmhsXjjXe2WI4fBhKERXNnTZsykZXqnDYzUwhFJZgdrqx+XNlZSl6NeKmpMgYwEIZXl6xvU67X1tI4d9Z0JXF2c4vlrGDch1Ti7yADML50+SXdWzfsMYZqWvzioaT2XSqthSVMAmMYCsJHPR8GHBpXe7Xpxo6W9gnT2tI3X/lJAK7YkUnLKBgQIA3M7XRv+MKnhg4f6DUzB/NhGORcExGKLAaAAQscAAwTf3LEacRRvmJTU984bWJTvfr0BbM/saAjyFl7s4wLijF/SvrqTy4Y6Oke5mkDmcFAfNE+QzMiAygBCanRdeMR3a2InEyopszoampu+9yF51/Q1aA0jDHKtdHOlrOC07CWCuIUj47gvM7aqy/9ZG1tzYy5C9I1jZGBmFBJ5ECzGFPS8ccokgEP5YNEXVNTS1vKc6+77FMzmuAAHBWterdUYIAAB3CApOAzF8y58Px5rRM7J06bo8mJPRxKIiUlD8dY2cAMgZLJwXyhrqWlprF+/uzOL3xmCQGJpO0tWsaR6z6/7BOL56qE1zlrXuQmc0Y0w1Apso2O2o7AELd0Tm9obp8zvePqz12cBlzRJvLJWq3l7GC8l6eHgREQCRhwCFOmTBoY9nft3jtt8pTs8PDg4CFSkfLYsBMhJfDYUawU2AE7QkzKLfiBr9HUMWX6rDmeq2784heu+dwldQmFKGAFMNvl6S0VCCU/MxNqXHTNmX/gcK5/MFOXTmaHM9nhYWMMSBn2jJMg5SgmZkXsEDsg5YdRMllTiIxK1zVN6myfOnPOzGl/+tWrFkxrUaiEm57ha7Scc8Rjx5RyacKkjl29maI2qZQnooeGhpLppAaGhoZTqTQREzFAIAYxsWKl8vkisUokkjPmzG+aNHXevDl/+We3zG/3xIDFuJ4Tpy8609dosYyz4DDlxZGFwALjR6L1kgu68rmwv2/Q9VLpmmQgGMwVQ6NEpQVuaEygdaARaOSKYa4YpOsap8ycPWX6LM91brzmim/cdFVTSpGOiAyIQLYFsFQR9+XiqP4wJOIFS7p6+3OD/X11dXU1NQ0BeLgYhQaBIYAh0IYi4UhYC+f9UHnJpgkTUy2t02bOnjdn3re+fvPCac2p+MxjdS0tlpNCKoZbX18zadbc3oHBTKavsbFBlMoW/EyuQE5CC0UaoYYWMnAiQ4VI54uRk0h3Tp3e2NLeNmnKzK7ZP/jO16c2OwkCBEQEEkDoJFL7WyynChrXxQPjvAgCGEABLqBzQZF15CYfePylZ158/cDBvmy+4Pt+MZ/LDQ8UCrkoGlmjqL29va6urqmpOZFITJ48+ZrLPvUnnz2/UAxUwnMAJRHIgBw7xdxSTWx1DCiji8WgwKlshPtXPrl2/aaDvQP9gwPFYjE7NJgd7NNBWH1gQ0NjU3NTXV2dl045NemLL77kz798dWdtbMNGlbwbdjjccuoxMFLqnlEO6PWx6tnVDz/6WK4YhaHxs7m+Q73ZwQyVI0aDKEyl0jX1tcl0uqGhIZVO1dfXL1t6/jVXXzGl3UsbJBQiAYBYVlsPh+Vs4HQLDgAS5shNBeA3Nu1//pU1a9/bMpTNBUHRLw4FYeC6pbmuBOM4CkbPmjVr6eJFn77kwhmd6XoGl3MtKEHJx20fJUsVI4JDDESKhtmhYY0tO/reWLPh1bfe6jlwyOjAJWGBQSxYDcg4iojF85wlyy5YuuyCZYtntSiYEK4Lg4hhCKzAbAWu5ZRiypVk/LoIGCAXYGv3vpdef3Pdexv279rnskuGILHtse/7ruelkp7rOa6iT37qkqVLly6Y09GeLPngivm8k04DUGIFh+VsYdwFR+XsNOKIkPJfnJwfvbdl94HDmXe3buvrHx7OFvsGhovFQkdrS0d7c3N97fnz506f2tk5sc51oASOACg9dCygeDFyi2U0cd1dzi7KceiFBgZz4fZd+3bt69nfc/hgT89QNjx8KONHuiblTups7Zzc1tRSM3vOjJnTpyUBB+KSYjHEWhAvAMeqtMa91RyWD8XR1S2NqidjuVzZVwN7DuzfsqV785adPT0D+aI5dHgwCpFwEjOmTZ00sXXerKmTJ7Z2zWpxFYp+5HoOYOIE5yCF8uiiGrNbZi3ZcvoYX8GB6qof1YPfGhIAALmAUwAODyNVh23duTt/v3ywb6A+7f3rf/XDiW2KDRIOTAiCqLK2GLX2ln1eLB9AZdYrARTX5j5w8HDwu7vv2bGjp7W19WDPnquuuvzqaz+dVPFwepiEsICIyAhViVqygsNyMhxLcGB036xUWQpAwhACF0U8op2Hc7/7/X37ew5/9aZb172z7r21737ntm985qLJWkMJwigEDDuOKInVcbXIsILDcjYw7oLjWMQejgjgOEkHAB8oAP/wP3/X0dFxzRevWPnQg4XhzE9++C0HiAySDACmrPyt4LB8OGLpUTTo7Ru+/bd3Ejk3feWr06c3b9i4Z+XKle0trTf+yQ319emkBy51LxHLjsoZVLWrzmI5UcYWHJU/Vu/CgB8a1+Wt3XtWPPJofWPDFVdd3dbW5BBeev6tZ59ZNWdW1y1f+ZPaFLELE8WZ7IxhAys4LGcfZ0RwlOaAxUF4sfTIRfiH/+9nyWTqm9+8tTadSrr4xc9/WSgU/v2/+SkDhShw2WGURlOs4LAcD8aYyvqulQrdAM89/8oTTz25bNmyy7/whWQy2eBxTqOnp/fhhx7JZIYvu+wLl1xyHgggU55hO2JxZC3OcjKckOCIg9WAl19ds+LRFfPmdX3l5q8AqPFS8XFbtu164N4HIM6NN/zJggVTlEJkAFjBYTlLOX2CQ0SIRr6OiPwwSLheBPQP+7/8xS9c1/3BX36/JhnnfxQAf/d//V1zU+u3v/MdjynS4ioyGmyTS1uOAxEx2gRhAHYSiTheGYNZf/ny5fv27bvumi8uWrQg4TmVQT8IhyE9u+r55198qXPqlJtv/nJHS31Ra6UUqsKPCEdG39kK23ICHIfg0ALf9+uSCQAHDw3fe++9+/bt/spNNy5btpgRVYYIDRhwBPzY48++8NzLCxcu+fo3ro+0Vq72fb8+WachXA4+GiU45Mhvt1hOD6dVcFT+hbAfhcVisa6hzvejX/zTP9fU1H79azenEq6rmMQAEMKhw4P//C+/bmpq+u53v5t0KLSaw3KCFItFIZVKuBp4b/OuRx55uCaV+IvvfttzlKtITFEkKqcocIg9MTh4ePA3d9w+MJT50peu/8xFy6IRSQKU6+fqWtoKDssJcByCI1/0XddJKPXmO+tWPbWqrq7mpq9+tbmx1nUFqLZHBhwDJ4iwo3vf3Xcvr6lJXXftZefPnydAwc+nE2mRY8RzWMFhOVOcAcERL7LsMCIgk8nefffdvu//1V/9lRLjMFTJB84gMoy+3uxvfnvHpM6JN335Rt/3a2pS7uiVD211b6mm2ja01q5SAPKBfujhp157463LLv3MFZd/jnSQTnokJgrzjltWr8IQDw6HxdDx3KdefP6pZ56+YMnSyy+7rL6+XillBYdlnKgYbcXDEYXhAyseWvv2O5d+7rPXXXNN+e8BjIGUcwEwA2zgBFprIdfhRx7/48svPrd08ZLrr722sa4ecX1bJTiMNVfLGeWMCQ4iFIPoN7/5zdDQ0Le//e321mZFQGRKlTkR4tSOCrv3Dfzilz9fumjh9Tdcl0qoUItSBCAuuJ1ibqmmWnBEUeg57vbuHY8/8UzfYP7Gr3y1a2anIvGYGCI6ZFQvN8xQXlwl+74P1+vtO/zQgw8ePHTo5ptvntPV5ajKJEMrOCynjGqLjeviPXv3rVy5Mpsbuummm+bO7IorwuzQYG1dLcSUJ7EwCCDWIC1iIBoGwJ7tO+/+/R90pL92680L5y8gIg1BleCAtVjLmeN0B436vp9IJAAY4L//978PguBHP/pRfX1tObRPqofIRUAMA6zfuO3ee5cvWrz4T268PgyjhOuIwBgRMcxUmbU4dmCU5VymusouFAo1qVQQhcyKmV9Z/cpzzz3X1NL67b/4PgAFEKAonvIqMBKHFpUOjg1JRqWSe2Dlwy+++PLi8xfdfPPNqZTL5a/L54PalAdYp7TlAxjLI2uAfL6YSiUBBFGUcp1CGK1evfrZZ1Z1dXV96Utfamqoi4NAGYakMiUbAEAUZ/jSEAE0JD63A0SBuf+++3oO7J85c+YVV15RW5uuDENHBg6PWR6LZbw5rYKjWCwys+d5mUzmn37160Ih/9Of/rS+tuYYu5bzdogpaY4t27rvu+++Cy+64LLLLk8wGcCYOBBVrOD4mFNdgRpjADjMBw/3PvrII5s2b77qyqs+/bnPUCn2U7FAkQCgeAqKqbIZLgUYGTGR0UTsKhVqOXSw97777y/k85deeuknLlkWGRgtnksVK7VY3oexGviCHxpjjNF1NWkAw0X/93fd1d3dfd0111588UWu6wAwJj7KAIhT3FYcHCjP9wPESElwSGiIyHNp44atD614IJ1OX3XVVV1dXa6rtIAIPHZ5LJbx5gxMi83n87fffnsmk/nxj3/sum4ymXz//bVAEQBs2dH9q9/8+ss33rh06dKkUrq0nNZI+a3g+HhydAW6pXv7Pffc4zju1265ZcaUqUUdxpGhsYUoIqCUXaPa/o8em/N933USce/woQdXrl23tnPSlD/90z9VjnKt4LAcH2aMzwsFP5lKKECAjVu3rVjxkKOcb37zm+2tbcwoFoNCodDQ0ICyEi454ACg1A1D1ZQVxF4PQhQKAWIEZP5w9x/Wr1+/eMnib3zjVgCFMEq5zljlseLDMt6cbsGRyWTuuusux3FuvfXW+vr64znElJdiEWDNu+/ee++9t9zytfnz5yWUitV9ZU8rON6fUcMHH3HiHBvxFVVXoAQ89MjKt958a978+TfffLPLqhj6YsRzXJQlxfEIjjAMXdcNw9BxHCIyGiKyd+/e++9/cGho6Prrr1+6dIlS5a+0WMbmfRp430iC6YGVD69Zs+b8RYtuuOF6InaZGMgV/GQyUYpUO0pwxMs7xIvMkqBixQ7DD0zCYwBiIIINGzY8s+qZIIpuuukrM6dPGy76NcnEWOWxWMaV8V2eHkChUHAcJ4oiCJj517/+tYj82Z/9WU1NjZSp3v/oFlHKVToDNfUNjQ0N9y6/p6O9fVJHBwMYFfVn6/4jMcYYbeIMKNX39qOuPIw2+XyemZVSUlrHFX39fb/+zW/27tl74w03fOGyyxlKBIrZUYqIKpfMY1z7qIyiSsX/EpGYuO9IDQ0NF118cbHov/zSS4cO9c6YMcv1FAC/qElx7G07Yvto3+VTRxiGSqliseg4zvt7lc49qiu4MIyiSHuOirQopoH+gX/82c/37Nlz/bXXffqTn0p7rhgwkwCu6xCBBVx2XX2dRhAAACAASURBVIy6U1T6pxTFTKWNCYzSRG8iEKN9Qtt55y3sHxh47LFHD/f1X7D4/EIx8BxV9MNsNpesEh/Wbo+JiIRhGEWRUiMxNB8Hux0Pxt3DUWnnhoaG7rjjDmb+/ve/r7X2PG+kEO/bEB7RP8gWimveeuvpp5/55je/OWnSxLqatC4/0dbDcUyKxWIymYw76/En58DTEoZh7ORwXTcyhpjefvvtBx94YNr06V/60pfa29sVKKp2N1ehjkNwVCNVJyAGBNu27Xz88cez2ez111+/cOF8YkQlUXLksbbXGKMjrRxVbYQx54ApfiAV8+Hy2ziQ4s03316+/A+LFi2+4YYbEolETSoBoDILL6bafRd/Wu3hiKmuwlX17awSDlrw7rvvPvLIo0R0661fmzVj+hFlOwJrtxV83xeRZDL5cRPK48G4ezhiYSgi9957b3d3909/+lPXdV3XHevHO6aHo/p1wnWmT51a9IOVK1dMmTK1rb2tIv2th+NojAaImAkCUSRxbPvITTYfxf6MiDBzPNjh+74W8+CDDz75xBNXXnnVLTd9ta6mtuj7ICLiuJNHRzDGacf8y2gTLBbDhoaGiy66aHBw8LHHHuvrG1h4/gIQRIDSDa4656m54o88Boh05LiuNoZHP+/V2YfPUOnGl+pV2WKfRKhl+fLlzzzz9KWXXnrLV2/yEomE6wDQAoCkaq4eVdne8RjWMRbPLg/ETOqYsPD8Rdls9qGHVgRhOGf2bIw27eM4/ccOHWkQHOVUFkmIOVdtdbwZdw+HjnQ2l12xYsXOnTt/8IMfTJgwIe6YxrMJSoU4bg9HXNbYsfXo40+89dab/+onP26qb6iea26pxi/qRFL151BXAw04ECrdwCOWiPqIUcmUn8lk/vEXP69Jp6+66qq58+bFNqAhBJKRZTdHwWOY/PF4OEQQRcbzSuL2vXc3Pfb4Y7ls7tvf+/bUqZONMbHIGfmuD32F5xaRgR+YVJJ9LZ4CC0govjvnvOA4Iqh5y7YdK1euFJHrrru2q6vLcZTWo3pf1a6yk/VwlA8r+CGAVMINtbz33ruPP/5Hx3FuueWWqVMnH7PM1m4BGGAw4zc1JAgIQ+0qBiClRFHnpq2ON+Po4YhHbZl5+fLl+/fv/8lPftLU1DQqwXmZ9xcccZ9Aql5HWivmGTNn5PPZB++7v6urq7G+IQrC6jE2S4zRGAror//3n0+YubSjmRXIKd1OIzDx01PJsnamC3tcBEGglIqt67nnnrvzzjunTJr67W99p6O9QzGVPTaV60JsNSxEQrH9HOnw+ADHx8gAebyL444oivYJrfMWLFAu33vvvQMDg3MXLCAiVenIRhrElXHxYwZ5fBxiPgwQafxv/+UfQknNnTUxArEIMY3Zvz63KvRi3teh9lxHNJ599rmHV66cPm3aX3z3ey2tzUQUrwcYb4AQQ1HZUI+wPQIqb6tqRRWHbtBR7o1yiIcYOEopVhogookTJyxYMG/37l0rH16RrElNnDTRYzXyjUC+UFCuU7HJj63n2AD/6b/+fPKMxY11DoWkWEACsBnJ/WQ5MU694BCRKIp8348D7n7729/29PTcdtttLS0tYx1yPMGM1VWTwxxqXSwW5s2bnx0efuyxx84777z6+npjzLlUT50SlEMh8P/8fMXLb7+3ZMmiVI2rGE7Js1UKxq1qmM9qYq9GFEWFQgHAr371q/fee++GG2644gtXup5rjIkirZxji87qSzwZIznyUIHjulOnTps8efLq1atfWf1KS0tLY0uLQwQgFFFVi8sez9ee7b/Bh0IAMH75Lw+uWbe9a/7SztakBpl8pFwWfeze9Ln0IPt+UFOTGhrKLl++/LXXXvvSjV+65povQkhK+WCq/GHEOJEG/njnZZdrTymFmEoqlVq29IK6hvqHVqzYtWtXS1ub43kJ1/XDINRROpkc7f88d36LEyIC/tv/u3xL98HZs+a1NLgcD3XFcvBjektOllMvOIgo9jRore+8885YbdTV1SUSiSPiNo7ZszwewRFp7SrFSrlKTZs2befOnW+//fbs2bNTqdS5VE+dIoyjaPmj7+za279v7+5F5y9KJpWrADBJvP4TlTtUZ3s8BxENDw+n0+nt27c/8MADuVzue9/73rx585RyjDGe5zCpI1qv6uj9eKbJKbcQIXYc1dHeduFFFx842PPC888HQTCna5ZvJKlGjd58bAWHARzgkSfXvPL6lv09mYkzupqbk06CSaLqCz6XZlFV43nu+vUbf3vHb8Mw/P73vz9nzmyjRTlk5EjBUeVHOy4+nOBwiBikIe3t7ZdddtnGTRuffvqphJeYNn26qxzgSFfJx1ZwhMC/3PfK1t39vb298+cvrEuzYiIIkfkY35WTYryGVHzfX/HQip27dv74xz9ubW1NJBKZTCZOah4zVoVyPIKDmWPNERkDkYsvvnhn987Vq1dfeOGF49GifJQxUVAM2X3g8XcGhvXBA4d27tw1b8Hc9gYPlVCGkRruI5DHipkffvjhp59+evbs2d/85jebmpoAEMMYITCr0x4EV+XKdh01d8GCCRMmPPnkk6++/vqECROaWpqrv/djKzgECIBHHl/b06sLAXfv2dM5ffrUtmRAhmXkrpyrguPee+9/+umnlyxectttt9XV18QTX4lwTMGBE7GBDyc4CsWC57oCOMpJOM6C8xc2NzU//8LzmzZsrKmtaWxsBEaNGXxsm9YA+PX9b/Zm9L59e7du2/aFyy9yCapcYx5R1ZxLFjt+nDLBcUSah9/97nd79uz50Y9+FGf3EpGK2qjWBCcwjj56ixeVZaJ4ll3X7K5NmzY9//zzn7jkE1prY4yN5wAACCvHCP3qD09nfdU5acb6DZu3d2/vmnt+W53LBlGE4WE/lXIw8gSdjY+NjjQz7927d/ny5bt27brqqquuvPJK13UrO8RqA0fYiZRHwce7eAIj0EaE0Nra+olPfvLAgf2rVq1i5smdna5ibcQYI0L8QWO/Z+PdP2kECAX33P/q4UGeNf/C9Vs2vvPeuhnnzZ3RXMtEuWz26HTDH9HqWwyMFmYKfKMc2r//0B2337l/34Evf/krl176WeZSThcAkFiqlryLTMTlOI3j5zj3j9tHKovjOD6j8keXVefESYsWL35nzTtvvvlmFEVdXbMVSGuTzWUVM39ce3EBcOdDa0Ounzxl2rp1727esmfJkmUNdWBFxhCOtW7ox/NGHT+nUnDEmqNQKNxxxx179+794Q9/2NzcfPQsmFPbj/F9v1gsptPpBQsWbNiwYdu2bTNnzkylUqfk5B95hEAkhNsfeH4o4GnT5xvDPYd69u7cs2jOBU21UAqO46g4yhFSDqg/i+5bJfT4zTffvP3229va2r7xjW/MnTv3iN3ofaLqx/9qRuY9EgAkXWfe/Pmdkzpffvnl1a+sbmhqam9rEylF4L2/VZ5Ft/7UIUBEuG/lmwf7pLVjauRgW3f3pm1bZs2bN7E5TcaIyLmRn8NoiXTkOEo59Nqrb911113t7e0//NEPOya0E6NYiBynylLHGE4ab2T0VwkAUCqRuOSii92E98ILL2zbvm3atGl1NTWO6zqOI9qc5hKeJUTAr//wqm+SkydP99LpzZs379jRfeGFy2pTMACJOfoX/BjepRPilAmOSkqfe++9d/v27T/84Q/b2tpQ9nwwhADByE9yqsY+4mQMhUIh1hxPP/309u3bly5dCvvbxxCM4I4HV2WLmDh5VjJd5/tm7659PTt2XLJ0aTIJpSAKQpUpFCfayxpfmLlYLD7w0Mo/PvHE1ddec8ON19XXHldGfOD0XYqU85vEZs0ELdLU1LRo0aJdO3c+//zzxWKxq6sLpflZ76c5xqO8Zzw2RwMhcP/Db/T2B60dU1NN9fXNLes3bNu0ftPCWVOmTWoNgsD3/bGSAZ4JDCDlGZAncBgzKVaZwaE7f/+H115/7Us3XHfDDdcqVUr9yTz6pz87BEfpQ4BBnZMnz+rq2rZt2wsvvpjN5WbPnq21ZiYxR47+jD/mjFdEIXD7H17KFWni5MmJmlottHHjpu7tuxYvuqChjvhYuZvPtN2e7XyA4DDlCZQo+6XNsebyGcBVKgLuf2jFe+s3fO97329ta3MU+37oOIrKeQyOEBwnX3oDFAM/4XkRiascdp0LL7pozbq127ZtX3DeeTT6W6pLTse4jnPLUCqdboIm3PHAqqxPtfUTjSS8RCqdSK1bs3bX7gNzzltS21RahpIQAjr2744+V3QKPR/myDt+TIMa+aKdO/f+8p9+k88Xv/Wtby9atFBgFDtjnv0MEfcRMTILAB6zq5hd78KlS9I1tS++vHrtuncnTppcV18PMdWag0cPBlP1uNaoP5xk8d7nbn/QI3B0XMz7F+ZY+2vgwZWre/v81o4pRrFK1CjX6z10cPN7a2bNmjlpUmvS80ys2iSeKnqiV3lKiO+PLt2QeFju6PZZpOqeUeWwMBSlaP3GLX+45x4Af37bbfPnzwmCyBgxRqJIG2OYq/Lcnk2CAwCDir7f2NC4bOlS1vLaK6+tXbdpzuwFjpMgxYgTGhCdrqndIzf2DFTQAgCa8Jt7Xu4fNk1tHUaQcFOul9i6Y8eOnTsu+/wypZiISCh+aIXjzDLnVjtyqhlbcBgAiOKWmRCGRhkQUwgYQuyDL4SIDEKDQKAZKx9f9dbadd/5ix9M7ewINBuDpKdIAIqbsXKH8xQJjtgWoZwQIMURxNd+jZvsnDHliSf+uL/nYNesOY7rSHkChh+aSBsNUkyALrevelTjfDKMPo0BgjByFGtIGIYkEEPQEENiUNmMoPptZYM+9ufHuT9pwMCIBEYPBrx8xaqBLLV3zDSUUMpxU2kk69d1d+88sHvqrK6mJs9FwAiC4rByXBGGcFkeGsAH4smLJ5UNqFJ3VL+rKL98LkOi2UlCIh1FIBDxI489+fu7VixefPG3vvP11qZ6EDGzIBRoAcWT4k9LTfQB9R6DhAQiBCEIlytlJhDQ1jFp6sw5B/sGn1r1HBPNnjE13id+KnTVqSHgklmX3RJy4uZ5lEwJwshVLKLDyAdFIhFMJBKJMWQ0jDZGi9FijBEtolF6q8VoiJA50tpEDCR214iIwAiksumj94fhEHji6bf39ww2t3UALthRKQWlduzpXbupe8a8uc0t6SQoCALHdeKrkPKVnK7GOF4mMq4TqpZipdFNtBFInMG3pEUiIaa400UPPr7qvvvvW3jewm9/609r62pIoJiVw0qx4yjHUSAhJqqaM3V64tyrv4tHEn+UYpzizUBih7ESmjZ5+sLZC7t39b3w0tvC6anTWxxFxTBg5USAFm0IgAjIlG9c9eNRpW6P+9KOstuhoRCsXIVQYIDY0I7YtBl5jVNdf/qC2x9YLcnG5ub2MDDpdK2XqKGEt2X7zjfXvLfw/CUtjY7DsRdfIipPmz2FP9s5x/t5OEw5MY8LaCFSxIw8kCQcDvDGuh0vrH79rXUbXnnrrRdff+e1NRtfemPNpz57+bIlczTgKrBCFCGOhBICKol+ToXgqF6aObY0AgQRkyIlc+fPf/ixP2aL/vlz5+jKerOKoFgzaUDBlJd3hgHJSCqdUwSBAFbsGzhEUCoS1qDYkitbRKh+O2qjkcrvQ+xvSvuTuOy4+N0DLxmqb2jqFHGFxBBTKk2et79n367dO5ZdsLgu6QKR0Vo5HoggCkB5vnncJqqTFBxy1DuCKd9xoxQDqljIKeWCnKFc7p//+ddbtu64+eY//eJVFyou+V7KbTTK67WVPhpnPtjVIFV7jZ53AGaqratduHB+a0vrs08//fILL0yZMjldW6eN0cZorUElV3vJuUQARrvz6cMODxEAOIp9DWYW5UZwtCgDR8MRcTUcDSciR8ONSGkoDaVJGZReG2IhNpUNbMARsQZFIF3ezMhrFrBBaX+ABRwS0gp3PfhiJqsnTurSRmnR7JGTSLJTu2dPz9btW2Z1zW5rSUPYFSqtDV2+3tMlOKp76RVTL9/6Ufdfl1ZiBRliUiiEKIbyT7fftWnz5pu/dusln/xEwuPKEdXFP9tc7kd7oxDPXyNKOcmln5gHXfP4409s37F/4uSJdQ21LlAIdRCG7DCPPIxCIC7fLB517g91vQQDOK5iB/kQpCBxZREr+qrNxJ0jhjBAVa+rPq/ezBif41jnCRn/ct8rPlLNTW1ag5WrxZDjpOtrt2zfvnPXrmUXLKtNg4mE4gj1qlrJciyOndrcVFfqgkoNkAHe3jTw4mtvb922kVgPDfX74XChMFTww1RteyrR3FjX7AktnDPr8s98YsGsGgKcqt8gzjVdGmHhDz+LpJLtVwAz8s44YIOoGBZZJXbu7//1nXddfNHFX7zic1zeWZfrsRSQACAmHkgAoMAn1ZxWKD9lBvA1WCFvIAzvWPuOtXJSzNHlOf79K69zAt/gm9/9h4ODPH3WBYacWIAFOkgmVKZnV/+BLZcsnPKf//0PprbCBTRCBmDixdxL11JecOqkMEf8D1NVThYRIcVABGzcuOXu5fe2t7dfffW1M6Z3AvAYxRDeyKyUUU/1+KdhHuvGV0ohBjzSI68q3eiyydDg0PL7H9q0Zculn/vkDdddHy9pVnkGTUl1QFU7Nri6DMd9rceyQ3pfOzwiA3flCseyw7FUGB/1uQbygr/60S/f29h73qJPhZT0EWmnyA655EbF4W3rV8+Z2vQf/+13L5zfLKFREo2agnT6GulRxhnXLVISgQwwx24do0UMoDTBVQrAc6+ve+yPT06ZOuUrN93cUscG8AAlx5jFcLYxeuGI+Cc1LAhzWZc9Mh6SauBw8e777tlzqOdrX7/lvPnTnfLPGiKKx1sZUCg32iPx2yf4XI7WJ3FdHQEK8Cv+7DEOwolUCEc/zEdbbEwAXH7LP2RN3awZ84PAeJ5njG+kSAgG+g/079/x6cXT/+Yn314wxTUCRcJiiOzsyPdjTMERAQCcsnfXIWw4dPjx51568fW1hSiKTAEUpNMKXAQFEEdQkxvWKa8+8g0Caayp/cQly6694vNTWpKqrDlYwJBTIjgq/R+pBJoASSAHHOwb2L5zz4FDg+s3bOo5eHDixA4x0tTc3NHR0dTSdt7iuY0JJAQJgUcAoMtdyVPWbsU3jeALHl21+u9/9i8NLZ0mciEJYKRTj7EHU2OOWgPkBPbn+CaTjowhTu3cl1Nu84y5SwSOoUgIw4Vs0vU80fn+A727N17+6fN+/Je3Tu90EgxlgFiMMY453vzhqHJHjXphyj3KIR91CTz53BvPrVp14w3XXXTRQhfQBg7D900iMcpiPhKCI26fCBpRETqClwoi8jzv1fd2PHDfPZ0TJ375y1/pbK8LK2cpR8olqjSH4dKpTlj2jWmHbrl0pR1QblYNVavAeKeK38awHL0/o2JspWsfeV31OSundu/eQaH6CZ2z3VStZkTkGzI60HWpZN+B3X37ts+b2fQ3/+bPl85vrgE0pJI07bQ22yNCLR41ia+H4xosfmtkZNAlV8SqZ55/5513rr32mkuWzWWU+maujF7W5GxlLMFBJDBiCpoTSTgA8PTqLX+47/5Pf/KSL37x8uY6FAy8sqEoRElUojy5yvxPhCrtEPd477z7pbvuXZmur42Uo8kxx5qKFkezHvFlR9ecow456nc5Yn8WxDcmpOShnFuIUtOnzYYwKwYMK82s835+uL8nc2DrBfM7f/Z//7jegYpbt7NeYp5Zxoy/c4EIYELeh5fAi+t6fvfAgwcG9sDtS6VzjiMCH1Q08MEBAGVSyUZP4EXpdOAnDkf5h199+fWN2/7i1puWzO1oJggQESDExCTmhHtsx4KBAChECAmi8OrWvhdefWvNuxv9QhGBH1dY/YMHMpmM53mpVEol0skVryw8b+51l10wf2LSN5Jggh+ohHcqYwHIAIbhuIT+jP/O5n2Tp7fCuKRjX4EApZw/4yg4CKxArJgVk6RSraAka61ZYrdQKpkGINqpb54E0c++umE4+O33bvvyZ85vIsAYiIAwsi7UyTxHQRA4jsPMoRZRFAC5ALkQuw70bt6xa2v33v5Mzg8o0hFCH1H+kqUXT5q9MAK0QAKkkwiZPSCq6gOdZY91XBceo1Ak0GGgFCPZCIjnUQaonzRzxrLL16xb/9x/+VlLS2vg+3X19S0tzfX1tRcsOn/m5KbptbF7WgNgqIIvqcSJS+KyHQLIZPXqtdu75jcznHLNbuIVwGKjiqVGLCZGpUcdEcjqWIIj3n9ECo7y7pSGhQwguVxvbU1jQ0NLKIZIl+2J2XGLPmrrJ0Oczd1b/tvf3/Ef/t13ls5qSIMKxUI8v/00MbrBM2ApD1AykPWhNbbt7N+8bfeGbbsGs34uMkwSFgeZw4uWLJ44bbZvkGIQEOaDZPqYvqSzjiMS8wIAlCEjgGFyatygCEQYKCAf1aWaZz724ruPvrzO85x0TaqtvWXSpAldXTOnTWyd06TCUKcS1Z2CE6zhqSrIiyDAwFCwfvO+ybNm5cIopKTAQ6XmPNaCf9V2O9YCjWaMiqPatkuv2RgEyvPSNWkTas9zdGSYJZLQkEmmGqjFBfDGhm3/9n+9/T/89FtT26A0VXthP9RdOMcZ08MRROI4JIADPPVa9/IHV27Zt6W5g910D/EgKDISgHxQBEQsYHgQT5OjJR2i3tf1YVQvfnJy3YQf/tl3uqY31Ckw4AoYmqSyjvIJ/xBmxCYhgA8UgS07Bu9b8fCGzdvZq+0fyh3Yt0fyuUqURjabTaXT9fV1yVR9Y8tEVmhrSlxwfteXr7l8UmM6Giqmkx4lT018sSlFhxjAKYB//8jr/8vf/cvs+Z+qTU5g45UCxHgkUuz9H4BjnP849o/vqYYGjCGwgDXFA5WaETI0Q4sAUGKURI7xh/p7hocPLZ7Z+Tff/cb5cx0omGhUcov3S3TxQVQGDoQoY5CN8Ngfn3tzzbuHh3KZvF/0dWA41HCIkw55ShprUy70/Nmzr7vy0tmTW2oSCELUeohGRKFU/1pngYcD7yOBoqAohtxkor+Izd3773v4yR37Dig3UfDDQiGfzeUcpZRyEomEq1TKSXa0NnzmovmXf2ZZR31SREwI5Z2waVbZoecDD6167yf/+X8suPDShGpkU24LhU1VvEi1aVXMyQiNMkUZ0RnV8neU2B11uwzIxN1QVszsCNgYo0UMx540JkMkTFGQGz7Q27PlvAUT/vrHty2bVUe+77oun6Khzg9GUI6AhIETAQXAAQpAJo9Vf3x5zZr1Bw71+YEUQuNrNspRDuko01SfrEklXeOfP3/O5z51ydLzpnoAfUQ8HMckHk8vAENDZv2GLX988rl9hw8P5DN1zY2DuSHAEJHneb4fep6b8FIp17n2c5d9/pMXt9eBAFVaj/rEm9qSa4HjkP5f3v7W//zn5XOXLNMqFVHSwIknnZerTwJAVRVTtaGOde/H8n1Q1V9Lr8lEOohCDVFQHsXXREY4ECYBa2N0WDD+wMDeLcsWTPnbv/5eRxNSzpG/uxUc1Rzbw8GAigJyPAKt23fgdw8+dKBvb/vUnJM+rCUTSUFEE0v12slxlcVigCLIsJv13EOiGrt3Z+64+97v3fb1eVNr3Di4SAx4dHTRh0UD/QGefWnzU08/OdDXO9R7aGCgr6+vT4e+6yoABkxMnuKoWDg4fFB02JCsqatv7qtv6RvI7e0pfuXaq5bNrY8EbpWVnKSJmFKdawQs7HKywattUeSxceL0aMYYIzJ65H4UY6mN49m/UvUTKc0cMrMgJaxGHCsKAhOH+iGARI6H5s7O8IDzxjs7f/Hze/72332jbSI4dqZzCMTNzIkOgY3cxVhtEFEIPPvGpof++OzBA/uL+awOg+zQYGZgIAj8IIgUs+Mm2HEndHSy42aGi++sXXflJy664rOfnj2rKY4yBTSVhvvcj8hTLI6XHNbYM2jufvCxt9/blCv4mf7eTM+uJJtcPpcZzIRhkEql6+vrk6kGJ91y+GD9zu49b7y15epLP/nFz86L/ECxCzXiOzhO+ywPwJh8gXOFsGDcQFIJVcvkHHGCUsfuWAKCRbjUEsdXM+LKGUNwmKqCaUDFk10hSsMExohEiDumpRXWWRgwBg63TJzc0NK4bsPb/+ff/er/+MlNF5431fd9ETk6D+m4UIpVKgIAPAOvFuiJ8Pzqjc88+2LvgUPZoWHR4WD/4aHBAR0GIoYVGRP2JhLNbe2tbRNeeXPtm+u3XrDsohuu+vysVi/NJQf7MYNjzhbGiOzMA937gtuX37N247sh5b2aSDUN9PprWzpqHSIiV2tKajcKuVDUA8PeP98/+Mzr6796wzVXLO4IywPogClHUp4wBij4UgxdQzXs1ipiIoiIGImq6s+Kh+N43BulMx9nfUuGFdxEAnCNFoB0yevLZAyTYYg4nuO01E2Y8eI7G//jf/3Ff/rX35k92bM5rt+HMWepKMfxtRlmvvP+lWs2vJusKybqeny930hBJKTqJRDiKR7EJACRkBCFRD5xTpFxpKZvINs/MLx46fkpFceQRicTz1saZgQMEAKPrvr/2XvvMDuu607wd869VfVCJ3RAIAIRSAogIBIAMymRJsUgMUukKCpTVvLIsuTx7tiz3+5+65nZ2d2Z9c74W1sey5bW1owVRtESRVk0Jcq0lRjECBIgMjqgc+6Xquqes39UvdevG91AdwNNtmSdr77u16/fq7rh3HN/98QXv/K1b8HFPSeO9Z44XBwfoqgYGBgSS8LkyIUaVyQuW7iAxI+LkxOjpQrIaxgvxYePnWhbs37jujwBDBGpi6NZQuNQDSaFAsaBntvf++g/PJ9vWhv4OVWkwXBMzGysYWvYmhnEnjGWjWVjzSnXQt5nm15EhtlzbMGGNGlSephUAqAEBTkiEWWF9f1GzwRHjhw6eOT4xq27Wju4ujIdkdDihUd2MQAAIABJREFU5isNlBOwAJEDmGLgK9/50Vf+9ntDw6PlqamezuM9xw5PDPeHE6Px1Hh7c8ZTp5VKWC4MDQ6NDA36gecqUf/JvpMn+3Mta1d1NBIlLgUxQQk137XXOEqlnk6r4Uj1MSTAkwe6P//Fb/zi5YM9/f3jI8NDvSfGeo5Fk2MaVSxcYIjiKC4XCpPjYdmVKpXYgck/cPDQVEUv2r7F96m6HRLm3SNmPVzTKQaTRwePj3z3R8+0rtkSmLyqESVRiLAqOZAqCSiR4bMvUVFIYisXqKqD1n6qkCoU04GwUBHV5ILAAaqIhWLnHGCsZWOrIR803QkiIaqELsjkAL+nq/vg/ue3bdu6bl1bkGYglYX1+ywp4VsS2BjcU8JXv/2j7z38d0N9/d3dXf3dXYcOvKRh0bgSSxHRlIZTFJfDcmF0ZKSnp6cSOjbe0PDYkSNH169d29rSmBy/NY1hIl1pgKPeN5lS17gICIEfP3P8c1/64rHew9RQaWgXm5uw/oSfmXQypBgDCswV4rKx5UxGM3lfrD8wMvrcC89NOe/iizYRYMmBEqfPBU8ZJdCVlOCAlw5NPr3vcNuazY49AUGJiImY2Rg21vrWeNbzrPWs9Yz1PDP9uv7P2sWeZ6b/NLZKZs7LM6oIQxdHMbGhRNNHCghIDQhkjM0YzydjrBccPnzs4KFDb7npSutVgyQAVeVfu3XU0dyAQ4CSYkL4sZ8f+rsf/SDbMJpvHFeeYBZDxpBhWNJk72KGTRJzKLGSgtLYJYawkjHqZ/zO3ok1a7ZuXLfKJ2dS0WmXJDvS81LJIWI88cyJb33965WJkd6uY91HDlhSj+AZMknVAKhRNaoWsGlYpxiA2TonI6MjZIg8/5XDnRu37jxvleWwDADEdaBh0Q5rKWARA5AQnn+5+4c/em79+gv9IFONeweRSYLIhEgU1ZQSycW111Ca+S8Smv1O/TXr8yBIdZKSAFdlApHjVLnEYFYD8Vg8cRYwXj5T4PCFE4cP95zs2PCG8zo8Abu44KKyZ4PFSEsFVIAY7ACPEQJ/8bWffO/xfyqO9Pfsf+nEq69oaSprOcMm8GzGD1zk1AkIluAzApLC2PDY0EBTvnF4onCod7ht3QXrOzIBWACGAZZSe2KpRAu46rbDVCXgQBwBP3jx6F/+1y8dOn5ifHTo5PGDE31HcxQFxB5bJuYkOyUxg42yRKGUi5XK5Oj4YNDU8OyBVyqZ/LaLNuaA6lGZNEmAcFr+pCR5LCAwCrx6qP/vH3969dptGS8vxNWoQq2xDKWBh7OiDrW6UQJI35o5Iul7dfBhGpxp9VzBRIY5jYtPW83JVfs2gZnICfl+1vqZwye6X9p/+KKLdrR35CxQLI15Xk7hdKabyLkmBrxYPEs8AfyX//7YD554UiaGOg+8ODU8SFEx51ujTsVBQCAig6SgE5EFihOjk0MDrjxhwS8cPL5hy84NbUGpLNawUhJ+j9eKYxdMSZs4BhycRGoc42cHBv/L5z9XdCM212+Ck6BuYNRADdgYNQnTqQMipIb1KcOjflBxoq/sP6gmt+2C8wPEkStY9heJshKHVcTA488c+fHTL7auXU+c0bkXHabhrWjdSxWd+526K/2309kfm74fkbHGWK96kAaREoOINdnylFQkH+Q9m2Ov4ciJnudfPXjx7r0tefKBSiUyMGdjjP7Vo3kBBxP6i/jqdx4/0XOsuXUKPKgIqwd4VFcNJbJj5jpSTIshZXZkMhMFvzgVXbtnZ7Nnq9k9lqbhUIDKkURMx4fx2c9/YXJooL/zeH9Pl4FYApGwCiHJVphKzNpPVjBBwUke/EKpEsbi5ZpGhwd279jWmAnIWFWtBmdQIlQW2z5UNdBKeP7lrn/4p5fWrN1qg0CIquPC9bK7jmbw5mzZf6aGzPl5StOpqJJqrQEAazJBhpShNvHwENZsRxNl/K6uvldfPXTJJZfnc/Csl0vRxsKHItkTIeAkTem3Hjv4rb97bGR4pO/w/uJIP+Iw53s2CYKYceCtQlWIUWeAsdFxeFnb0trZ3X3x9ovyOcswBMwuob1SiKZfECno1eHwTz73he6TJ4f6+4f7uhCVfYqMcwSiNOSfaj9JwRBoFEdRMSx19vW0rll3pOekl2m44PzzAqpOgaCmgpufP1NOTAyfrx7u+/7jv+hYt8XzG3S2CJS6o27tde1a7DDXa4NmPKgOmvGMv2qfJlYBGev7WfYznZ3dxw4dvnDrRes7co5tRCHI8DIX4yuWhHwqA1995IlvPvoj3/O6X3mpMjZkWRK2PBV0Jb8YmvVtXClJpVQJQ/JbTvT0Xrx9V2uzkUTJkepNlXSlZeMQUAS4OHTW9188Wfmzz3+urGOwI+QNkB1inmCqECzAibGYiEDKECLH5AgV8CQ4ZBMYL3vglWOZIL91y1rLxLC0WMABUiAEfvrCiZ8/f2Dt2s1sUvmT6llpQUfBU+WhzmCdlPdmJHWbgbVJkRTNpTpPkRr+JqSeAaTKCjY2m2tsPHTk0OHDhy+/7LLGLDxrXjMHpF8Wmnc8QuDEiaNHju1f1ZZPcjuCpOZUBWD6jHImUo2yOb+np+tEZzcDpwmNWSBZj33Gd77zSH9//9jY2PDIcBiGZywPyyqASLXLDInLhZOdx6ZG+ve/su+pZ/fFCXOBE5YSgixJtPE5DHhZBmI9jY2TfZNf17GlsWndSy+d+H/++K9O9qESGcDK4qQGSzoMMQEvHq187VsPlyZGh0+eGBkaiKLI9/2FlfMVZjpy9NWjr+7vOnHsm3/7bQJioOzixTTmtaHa9lk9jIFGQ3z5G98tFqOp4cHxkydkcty6yNpMBKNVe1Ut0z+Tpn5RJKAYLi5OjJ84crAwOvrY939w8GhPEj3rYk2TRBIp1S3IWZQgSLACrEgDL1YGJRyYXpi+ABCTipKxq1dv2bHzuhdf7fvf/+PnH3+qKxQvlqxL0/osI/k+E/Cz548+/sTPgrhy6IVnxsdHlM+c9Y6IVNRar1wuD/YP9J/s7O3p+ubD3yvrNJRbKRMwiygGQiAmz1SAr3712509XeQNkt8LMwkI1EItKAaFp+1EkfmkZ4fLxcI3v/H97v5JoEGXIu1nx2a/npR6Gp0O36gKEXnWy+dbOtq2PPeLI//u3//lsV4NAQACiTVUda9Jc1c6zTutMfDCC8+F0YRoUREteb2oOpHY81AJC6+8fLCSLL6zHvyTA8V9+14Ska6uLmaTz+WcO+NNU7GWushBsh6FU6PHXt1XnJr4/uP/OBEDSfxDVV+ttFJlxDKR8sR4uVLSjraNF1z4xp/8bN+/+fd/+urxQphkIJCFDoYAmu52rMBjj/+jUwx0dU4N9mWMyeVyQRAs8FaxCy30xKEDo4N9z7+0/7GfPucBgVnpMYcChMAzLx87eOjYYO/gxOCwVoqrcpmAEEciMencCitREiEBhBC3NeWnhodGenuGBgYeffwnRQWAWF2Can5VOZOYVMxUQeC1dKzfuf/46H/+86++sH8ippn6kGUgAWDQPVx+7ImfD49OTA32u4khF4VgPrN+UbVQLDJREARRWB4aODk2MrzvwKGnXziRpCRVCCflm1eOeoMAlqp7EEcc/PjJ/QePHFzV5sOOwA6DypQ6HzMgoHieXUBYhREbFFnHGxpAVr//+E/HoyVy6bSecFnneylUl5p0Jnm+73u5pobVa9dsf3Hfif/rjz774sHBEqCIo7i0gib9daV5AYcFjh47ZrwYXFSNVJ2qJh7miyASkYitOC1WwsKxI50JA6pbsvsUAaiE+twLLxaKxeHh4TAM4zhyIqfoWtKDE6d2VqNskpMKKygJB4XkrGppXCql0ZI8te8kgLQ+hCYWgfTPJTV1FtXnzp2jna85pk+fWDthKxORyXpZhsfk5Zvaz9+288UDJ/7s81956XgpjIEFYw5OXcU4Bu873POzZ54ZHR4Z6e/Ksgs8y8zVAZ6bEt8gSoLPIIGBj2hooG9scuqJnz1TAkrqVpogmjUuDhgH/v6JnxeL4cjAYGliqinXIGFkBEZg2TBzoiJEdQpSlS+pgRpyHjmP1LioMDQQFko/fXb/S0fGK0DgpUfGmhVkpZwFl0Rz1hMhMn6mKXKZbNum9vPfuL9z9I/+7K/3HSwUl1mxlYxn58n+F195dXysMNzbw5WC7yU5yObm/Pr2ZzIZUY1j51meHB7oO9ndPzrx7L5XmeHDWIDPKrp8Wah6jrQC3yN69J9+PFocCBoj8DhRkTkiVgM2YFYw0vz1iY9Dcod0IVNs4SxgudLcNCU0+E8/f65rIFryOqUq2qhXx9bLjdPLkOUgmotQHYE4jqLIBV5za9umjvO27zvU92d/+eXjPSMhYMxKm/bXjc6UBJbLoDIoxvy62zOREDtwqCRCad5COeN54bQUOe0fGoyjqFAspu2EGIP6MN0zEqmwhBl2nitOjY0UQh2YKJeRlAWTJIPFPz9KrGYQghAHuab2885/8rlX/uiP/+TgkRPMHIbhAm80XpxioAi8cOBgGIZRpZCxFFYKi5ojABBnyHkUlybHy7H2jY6/2tlnVmT+YKn77YDOfh0rxpNj46XJCVVleFALcEAISMyss1utBhaJsICEVFhiXx1XysXxyUKkBzv763fclauiP2tSJpCJjRfbXNC6tnHN+Ye6+v/tv/8PBw72LXeXx2O8fPhwqRSWCsXK1KSFWlbGQpFOGqupsJCwVBybqpzoHTw5MAaogTJ0RU1Z1WGHAR/w9x2f6h8eY7/kdAi0OHBHyqxsVAzKbIbBE1NR9OL+o+ekv6wrUNUxg6ZzHAiMl801rW7p2PjcvsP/xx99prOz1+fc69u8lUNnQl4Ug8NUk0ZuKSKOBEnKfYpriYbOhgSIJD7R2V2OwomJieRNTjwuMCPL8jxfZwEn/l8sUWBgNJ6cGCmErnNgpJT4OnI1KxfSONalNJRq7V0cEnot6VR/DkJqqVWSXEtDvrmp5KLDXV2j4+Mudgs3hTTkchEwEeHVE31QNzHUq2Ep41mkaGbeDGazWwixcD5ruTA5VSyPjJeOHe9Zgcu3foKdIgYOHO0aGZ0qjA5XJscAG1EmIh9qPYk9iVklVVEwCaGm05E6ZM8QoyJhaWpirBxj38FjU2U4pO4iS1xJ09U95XUDLamfiiTp0qeZUFnASdi2YxFDsfFiz29Zd55paBgcG+kd6F/WdglQdHjlwGFIND4wQGTIeIyYEdO8guXU8RRAAqNhpTReLHb1Dhw5cgRQhhONeIWhxES9AfFV8NIrXf2jYyY7WcEQkU/aBA1Ql0Z2+nVSp2+6v6wIoJ4VWC0TTzierGj5pQOvnDPPhTqeOaUHp+Hks+fwU3XP9e+kR9O6ZwgARxyxP1nhY50DvX3jlcgttyJybi6c/1rsfaZJz8quOa9HTyrOlKFMKpzihsR2POfYzepF8hkhSpwhagp8ABDVxR9Rp8MOo5j6B0fLMYqlcjPFRmNKc47NevpsYgUjBCBVpoldGFijqsUwGh6d1NRpeb4+Lo1WlohJaBbOmM4dmWxIClIZ6js5OnhiTWvjJz98/3VXXpIYQsSJsWeePQI7IHQ42TeAqOIqRZCQZ2QxxhCGsEoSM2XYhmEcC3p6B4ZjtJyt5/HyEZMABt39QxOlUnFqwroIZCSsVFmK59CfKachOpp2jAAVBYkliqIKwesbGEadeZtXJmMthmYla0oLjybJ4lRIYYyS6OH9L+Z57Hc++oG3/salyyq2FRgaLfYNjcaxK5eLGSbSU3e4MxNDiEXIlcvl8clCd/9gUmJF4hDeCmVcAY71DsI3xi/BjZEJAJuqPMkBwOlktggMkcQmShLCM/mZXNA/NKhIqrcvER6fPoXXguncyvN64sRvWxVJ3TY2cGFlqjAyOtzb0pD9xEffe/meXYE3wy7/2vtzJDl1iOoqVJw2skFnBfQkb8qMr6suxUA4L/cLsKa941DfQN5vonjAUEQaK0Fg5zqbSt3JCQAn2mMA7MGJc+KFYleva0/CqhY/4jUbqgGQyXjZhtXZVZaDjC1PZKQkYCWWGQWl6lLeVl8YCn2pgCSkjCMKiUKnLg4bVnkAgiAwCSQ6Sy6v7xzNCYPqP/E6eC9zNeOHUNWNjZLs5+rYxWGxLdM23D0w1ntydaP5+Afvvf+2PVydNbYL4jIVMGNyvFyZmrRShispczxzZNPIl7r35mCL9ExjAZSKpTgMR0ZGszaJu02/uRIcsqqDQoCqOoYZHxsvFSue52U9lrhsXZmIAI7IT0Ct1Hgjbb+nVLOIC0EclK1VSLlcZqejPYNREXE2LZrFFHP65LMUpsuHW+a7c7JCZ+jJEz4EQ8CsLOVKcy5XHB/rPPJcK6Z+6zfvffcdV1o91VXrHJOSN1WK2M+ErpKj0CBUxSkhWvP0azofK1TdVGG8WWMAI1NxBHhgs+Ki16SqG7aO0TU0OFYsbG33K5WiMSrEydmjmgPBYRoBJIrb6l0IYHEQgRhhP4pa8o1jA+W+qb6z8bJIA5fqn5jS6YdxPlXHuaJpZlASqS7Y0MVG0JJrGRvoGu87ZmXwf/79j916w0UNFsVCOZub1g2fW/AhQBTK88+92trWumnLGs8gcjCMUgnPPP3i6tVrdu5YEwOxIMlIsf+VE8Vice9lOzwLAcrlOAjss88+B2Dv3j0iykwAMeG5F54noh07dgSeDyBWJaV9+17NBdmLtm/SJcVwzg04CMgCl+y85CcvHZ2YLDRmrQFYWXCaua5XvdSmhI2xQaZlspQxoJ07tzGgMax3SombBVE1Qomxbt26Vwcmcg1NXOqjRQHYaggAiFWdEBvfBtlcLuOvW9OW9uPcCrWVak+Zk+JKGPh+YXxkcrg3b8Lf+egHbr/5gqA6tQtfHqqwQMaYXMYvQVALi19MyHAN2ibftQxLpjGfX9n23HSMchk/8G0BUEoc+IVhYlglxMSnqtaFkhi8RNcUCwEqSc4RAdS5pnzOMBhI6uMgqYBIKz1g5/RUXzQLJACDhBRNmSAaHxzpOrg6R+95532/+eBenyASMy1vZCyRyWRyk5MF43mISwwR5cUqk4REjVomz5JvOJdvFsCBzBLl3nIRA5IITwKAXGOWDKtzHnHVtLfwoRahJK29KFs4Z9lrzORVoYuvoXqOJ7heAs/22V8CTQ+LCImAFZ7vZTIZiuPx4ZPDfcca/fLvfOIjt95wUd4iilw24y+HhiOtUQX95re+9cX/9q3GhuZ//b/8y0t3XaAKS3jk4ce+8pVvOBd/8nf+xS23XEYEa/Doo//4R3/0mYZ8wx/8T5+67PJLVTSXsV/6yle//OUv53LZj370Y9ddd50xbK353vf//jN/9ifM/Pv/6vfffN11YRwZ4/30J0//8R//v6VC4fd+71/eeOObXLwgbXc9zTv6DLzxojeet+b8UllC9iMKRH0WS/NOGAMW6kMzSHN7AsqQnAuzKPC2defvvWSHBUTd4pM2UTVFrgKwBhdduMFCO5rbYvJj8mvqDZw2z4TAhokpHTAaWxcxw2Sbg8aWVY25CzevAyCJ4wYTLb58yOwmA0TJYltZmEPq8koCiRYhNoityKrcKpqKejsPdLTKH/z+Q7fcegGSWuGLfwoD2cBryGWF2BG76hzVUkotqKlA7Yts2DJaW5qWNzhySVSvZ2CGOrQ1ZhoCFiBi65hdIsSrisCaI8sMjxYS1mnjYILPHLFjiIYtLVnfgBOmpNpjF0uvpw9HdW1WH03pONSGhRAzYotyeXKwv+vgqhZ51wM3Pfjg3kRgVCrLbgv3SRuyvqp6QTZmdnSmgNjZvgXpkFovsDbwrfE907qqwQDigOXPI7J4mm5PW3ODx4hdBqapuuJPZY86nqnruBALMYtVMHwKIZZsa3PHOc1ytniOncPn49y0REmcKokaeBLBg49Qi6ND48NHWxrKv/Xx+2+/bXveInYVJyUyQirn3O/VWFMqlQYHB59+6qnB4YEnn/n50aOHIyBjUXLYf3D/keOHewd6B4b6BbAGoeLZF5/t6e0+3nXsqaeejqLYelSquKNHj3Z2dp440Xn06FEv8BJZ1DvQf/T4saGR4Rf2vThenLLWM4Qnn3y6p6e3u+vkU08+bSwtFm3gNMXbwgjNDf62TRuP9h4QaYko9DAhCHXuYePqHsAAaopPhY2ifHHcxVPR3mt3NhkAjiFJ/bAl6ReFAcNm47p2T8PGfMMw2Qg+gKrT6Om+rOCIfQYbjQGoCpNlL+dnc40Bb+5oIoG6GNZCz0Emy6qxRNyCM1gsK9Wj7JpuWgiAJAW6WGW0c2BiuHtdm3no3W+786atPmANVAWLDAxJ4p6znuZ842Aj8gUsaSrYhd+FxXiROMMsYMPGMppzOdIVp5ueRSzSHFDWqmNEZJWYJAKTkhNEqpbmWEfCykqCqn+GEAvVYEelocFn6xjGJadGIdDSUtO9zpTwoUtCG2pqeU4hCJEYyImjL7blzb133vTed++2DKeolKOMt7xV3AjwETUElhTG913JOrKkYniBCXmmP0TWYzHGsme0OZchQFTO8gizDDRtCWSgJZfxYeI4Y7wm0VFgoSFpya2q65rF5GIJLNnmXH7JUjRpmbrXX3LOMt0mKbwEUCWCJYVRsc5NjA/2db7S0Rj97ic/cPMNm31gsjKeDzzf2Eq56HvL4unue35HR8fdd9/dPzh+zbVX7b1stwdMRZUGL7j8it0v7Xupvb19+8UXWKAizmNzxRWX7X/lcD7XcMMNb85krHMQkVtvvfX48WMAdu/ebQFHrMAbd+26/s3Xi+ru3buz2ZyIKPHll1320osv5zKZG2+8EYCILLaY8/weTOTacuauW9+878DzvSNxQ3PWNg5Mjh8NrD8PxqxDxCRExvN8pubBwayU8js2bL3jxusFIogMEj+ORbWzRgLAh9m2ce21e3Y+8ZOn164/f3SoL66UK+ViQ2Clup8lt9eZ5wlJEy7axNLuZXORo03bLrKBf92enWub0MiQwKa5AZNSEGch0BUgJiJWVZG6XbJuy52ZAGq5V1ftuaxCDgAJVHzfqlQAqUyOm3Cs2ZY+9v4H7r71IgNwEhVBWHSWa3GxMQ0+XXn53sNHB3MtHV3HetfkmiQ+8xml5n/jGGAOIw1L5Xzjqpam5tXtbZdduotFlUnnUnS8vv4cibK1MDmebWy5bMeWRx+NVnWsHp+cCMcLRGQoyeoIBqROZ5Q6xyi4mn9UASUS58j3i2F5zfo17e2NO3Zubmk0ySeTnLjTqt26NpxeADiRReUM07k8tk5H8xwooyhiNp4xhhmpBGclOKW0bJi65pb8+OhQGBV7jh1u4KkPve89D9y/08WwDCINssvubsnA+o7MFbu27z/SaWx2KnR+kMl4HFZKi7qPEk9MFiloaMpnz1+/dtf2Cx2gZJbPd/EsiFHlnysuufjxJ/5uYhIcNEInicrpJxbQaNbE8VlE/f4hDTg7NjJ63f17z0Z+xpUQgMSOjbBHUr1XvT/j8qXiSGGxc1R9bvJOYmFLKmBAlFWCgEoTJ092vtTeiE999P43XbE5AByifGAYosK+n6m18twKKDYswJuvv279+s0NDbmmVVkFcp4fQ2+79fqrr7wqkwk8P6lf5Bjmpt9482V7Li8WSuvOawVAhGzWu/LyvVu2/J8AOtpaY4EBqWDv7j3t/+pf5RsaWpqbfeJYRUSvueaqnTsvzQYZz0uqNepiGXruNSyAQ+TDbFmXu/MtN/3Fl76BfFOhVGpo2VwJB06HfBNxI566wEkulhZXbvHReNctb13T5BvEySYM0UQnsvjRZ0A8oDlrrr96z6FDhwy7yXJYKA+wl5G0NHYSQX6awwSHMKIg4ZbV57H1d7zhwrfecE2eMD5RBKS5oQFYIiSqH39FkgCe0pL0VUHP9ZqG+gWzzN4eXB1tgRIlShwBARoR4smJsdHeE81S/INPf+jWmzdmAUXEiJemBzZgjTUwuGDzRj/f2Nja3jTWPjw60JINFmEQUY7VKJlsvrF5VYvv2/PWrlnTluc4ZF5p3v7TgCzf0ADWLeet2nxeR+94Kd/aPlWZiEsVi5hUCKpQhiezXIVIktMSAEfMgPWDQhj6ucZVHe2ZvH/R9vNDjTw4wK+W5gAkKcC2UGZNdEWL6NU5ko++7zuROIoqIl7gI3VHBBGUEj6U8dEhQuXEkf2tWfkXD73jgXt2+gTjIUYtEwYLljGJEgE5YMdF21a3d0QO4dSQSjl0FYAXKw4ipQu3bA08u7Z9VUuDTUoOqqTyb0WRpnHWeMOWhou2bHu5qxxFg56xC+8xKwTQtIJUxs+tR9i2bk3zti1rzFn44BORNaYhnw/yzWOF8VqqsXpn45mAQ+t+pv+edU855Z1Tv19/ZwJBtNo1TrSKSCqoqDNKrBIWR0cGDq1pdR/74L03X3/xqhwcnE0U3FqNn0gt7OcSbdTlQMPmzeuJQSyKSKEEa5laWwNVgODgDKlDRdXkc5l8LpsErSRQ0imampoAxAKidMxUdcOGDUTMhgEwsyrIoqUlY5CuBja82BCkuaW2AlmbGXeljAnu/I0r+kYmfvjzn5XCNRWhwJsyNCfgqNqn1RLyGjVHUUcctsZh7p333HfLm7YbB4UhEBbtjlR/tk6SWCJnsHvnxqsu3/XID3++fdel+577RWFsQBM/O4A1UUTPfgSrMCQmROw79hua21rXbtiw4bwH7rmjo8WzcZTLWN/3Exs6K6r1HRdJqZWaKcnowQTA932pjjbNu2CWF3CErgIgsX+5JJYHyXpy42MjJ7uPt2bjT33sgTtu3lgJUdRyPjBV5wSudmxho6FgUqfOEm/bsv6S3XuHJ59sbm0vjC06j0IsYD/b2NiwevW61W3t1159RY7hVmgaoOr4GAM4n8x1V+3dP1wYKZWLIyfjyoQQGIl1bY6JFsBAbNWBw4GjOCbjr123qall1aV7dm58DCnjAAAgAElEQVQ9fw2jXCmXAt/WTco864ik/r/1B6xFFtNaLM0VaZQwG4sy2BlRZRhO/e1YSBI+DKPiiSP7M1Y/8qF3PXjnjizAQKkS+UGycEKAgUAWdOReCiW33XHBph07to8Vw4415432Hi9VooB5UXlPBBxkG1pa29vb2q+/5mpDMIradnk2YaLLSqsY11973aFvdI0Wh5obF1TrKKVkE06TOvpR1B4V8zdct3fbxhydxS4bBAEbIyJRGHqeV4vq4jrz7gwAkWgNZxzbZi80PsUbrV6Fdyo8ERW4OKl1KTztc6qJapqkODE80vdya1Pltz7ytrffvCcDQGA4MacbqK9k0gpL5yjG91RiTqvqxQgVMQCCMDK1ngkihiqUCH41MDv1ORKoqrUWiTqHmKvpj4k8hYoTl+yq7DGntfVmIbOFT/G8x8RJVPIm6+Kij8z73/EWQB5+7HscWK+1HeonoIHrnL/SE4taaIZklYsa43LeRcE9t931ztt3AmCTQCeuS1q6KMyREEHhIlVLRvH2u28NnfneD59Yv3lzb7cpjA17Uq2YM1e4YJJAM4Qpq21c1b5pywVtrY1vveG6K3es01Josr4BXOw4ccxbyq6WjEbKlwwYgSexp+Wpoa6Y0tHmujufirjPKVV3L7JKnGtuqroHQDgGwCpGxBWnRntPtGbj3/34g/feus0DQlfJ+DwTbSySiIxqrM6yue6qvS+/coAqG7RcLI4OE+Jp/8o0SKEmSpIYjelwp1iIgyCbb2hpadn9xh1v2rulWA6zPs2fD+b1pJo0AlGlMP7ma/b+8Pkjg0PjxVXt45VyGBeMxjxtr6snAUkSdg5lJUB5crLQtm79hg2blPT2t9xoVTwyFRfXJ1+bx6UxxfScGptBykbFl3Csr7u+WuwZEa6qzrCWLpW8xMfMeGQ8L8hr4sABVoIRMMUGcc/xg6sy0Uc+9K733LlDnbBBpRLBJUzCIF5+e75AXD7wrr1yz5HOLorWjw31xaWCBQwlTn+JD+m8jvNCAFjAGzZsXtW06ordl16yfY1ZmfB4JjFQdLj+ii1PPLnhlWODKq0OYCpRWrDNJSc9STTHlOafq7+BwodkOG6tTJj1q9bdceObF68aTfk2mejAtyYuTY33OxmJKa4hAyKuW2qnYYq5/1WPOWYZDOu2meSnzXiB8TzOWEcqYGaTZOtLqsYWJ4enRk40ZMMPf/Dem968S1BWDdLq10IgU/NuXFaEqdDIgUgNWwAOArATRwkyUwEx4CyySc9cXZMswynFcQwggR3pPRXORVUNB4sTVY0dMS9ZYwUAdo5vUxIW6wNqbdaACPjNe2/Z2up97ZHvHu9yje1rXVTO5imfoziaCiuTUVRsaGyslFXCJksto6MlFXP++Wvvu/uum/du96vxV0rKWnOLIJo7WOFUFp0NQY1HIOQYgaXffM/NTO6xHz9rG1r6e/uKo4Ol0Z6ARERRLedGzMlOFpIpG3/d+VvzjasaG/OrcsH77r/7lmt3BAACD+IANsyJY+x0FeIFUqLYSAyf5EN8nzE1PO7G+qe694+W4pqgV06cjxSAS+yCpyybejR8Frwqqs5msrHN59pW51oa0j4ZF7qpuBJ2NLVNnBwqDp1c7etHH7rr/lu3WQCKfCaoecHMbMepa3iu1lFSgdwAzgJXvKGp761v+tp/H3brLjgZ0eTooBVkPetbA1FQWrFMVURiQNgSiYvjOCYv27Ix19y69ryOrZs33fO2m8khsCbxx63BlHp8bV43v7x0+gEwMYAg3xgBD73j3omhyYyYV0sYGuj2SAIYchXDsYFjwyrVOCaFUxObfBhqqVwK49K6deu3veHijJd//3vfta2lsYHgKfnZViUGpViD0hSYcwoBSSUjMD44aYtT/QdfmKqE9Zq/+sDjuj9nzfLZAg5WNAQNMTjXur517UYiIrVJxIpALIuEYW/ny000+fH33/3Ou3YFEMuiDr71YJOVyFCfCcubh0NFCmN+Y8c1b1w3NHz1N/52ZPsll73ywjOFsaGscQw17CWevMmJQlXhQERsfWYuhRGx5/vB6rbVG9dfuPG8zbe95WZSMIFUTbqkF22dWW6i2s8objT2obve8tm/OfliTznb0urc8cZcEVoCAWoF1VTRST609OCrUGttBtpSmGr0dG0bNd130427VrcA8RJOLFLl5vHB7vHBI73WlisONvlP1ZFiIa5FVfkww8OJCXMBjtkJlxNwCdvSsTpS3rJ9e6zKSellZTgTUHZyYmhy+FiGx3/vUx+46fptzQalcoVStcI01EiNKVzXoPoHnbkb8/ePKHmSqiYOYgAA3wIKJa5JQgaswki64TIl7ubVZxuCqVN7aNXWaXk6itszRlXJADO2xUU3n6YNY9PvAVUQlIihMIxyvgfgxWPdjz6176e/eLF/sMdYlwmIOSJ2TKpxnM20SJQbG61s23bBZbsvvea6Sy9oy3uANz3jijRABac5JZyuvTNBQHLIrQCPvdDzze8+9vKBQxZOS+OToyOTY5NxLC52bNgY6/ue53nkBfn2Di/wV3e0bdu0/l33vO3ira1+pC4sZbPZ6YckLJI2c8FjqgDiFHBoBmpjwcl+131yKBJWW1fhvZo6nYi1mjp9llaqfhSWbEBQksjFU5H+r//hM6FtXr3+QoUlIpBMFscacllblr7DB9sz8f/w2++96U0bGoP5Da5zb0WYh+c0yczlWELYohIIX/32U9/77g/iMOzp6hwb6NWwQnHIpIacSzyjmafzCqmqCmca179hj5dt2LphzUMPvn33jg0B4JGQitYlR18ZgENq/ndc95YAz+wf/vMvfPV4T9/YxHh353EpFxoDUFQgVESVibLZbBRFlUoljDiKMkGQ97NBENgLt1+Yyfhvu/OOe+64tsWAY2WTHp9Uq+FipyTz5+mHJ/oSTE5ivIAjxwasnzPWzpphqYMadfqSeeDF0tyM1AZ+5j/8p8/v7xrZufvaQlGhvhFmlUo0SSiPDR6TsP93P/HgXbft9Ew5B18kplrS1fqlcfbBY6cjAWI4KVNmvIJvPPL4d773aKw4vP8VVxrTqCLikix5SDZSssawgGOBUxMKmlraVrWtXt3WvnX9+n/xsQ/v3GwpYQkFUkv0yoqMrZ9OF0We57nY/fylA3/ylW8fG+pZt56MHQWNQ0IRAkR5rthU9RlNcC1SXlUalvtvv/cj918PVUII8hbTXwFEwA7sgJPDOHjkJJscs2+ZktQ1KtOwY6E3rWeZefinXsbWwm0cMn/wb/5zwZmtF+8qxbGY1GiEUMLJcHywu7mh/MmPv/OWG7bmGCzI1CzPNUpNL6jVyphF54oVzqyqnJk8dL7nTgMOzLsfnQ0tCHA40TiKsoGfFCc+0jPWOzD49HPPHzpyrFSpTBbKYSlc397enM9t3rx52wXnb7tgY3tbc5PPEVxQBVL1wP60rV9018pARdE7HP/4qeeefenlw0eOF8sRcVCpRFEUEZG11hhjrbUs7W2N2zauvfGavZdefOHqPHM1fQpOHYe0OQsXcMmkxwBDLRQu9RtFHMMYME+7QqSXphrv5KqnuRbAoskR1EMBuP09/3Zoymy+8HKhLAOk4gccTo33HDnc0agfef/N99x6SZMHg7kAx4wBWDDgACDqGBE4AkVARfHfvvzET3/6nEQyMT7ce/xoeWIYroy4TOyIiIxRa4VNoVTxsg3t7e3rN2zyc40bN218z333XHpRKwk8wCpqlaXkFFes1w9wzE1hpM7SCwf6v/bwY68cODk8OjZZ7C1N9NmojLgcx0kQEAEQERXDpjHf0Nbc3tbY3NDW2vjWm6575703ZgkuVsMETh1F6gBHPQQ41XrNiWElVFhCsYJcUM2FUiOa/vQy2SwcEAIf/vRnn93ft2X7FcwtEN8ojMbFwtDkWHep0PWp337P++7ZGQNZAIhYqGZ7fM0Ah1S9RixiL8hOhfqlv/27b//o6bGJYmG0rzwxWpgYF1fxDBmNjYoKVQQKqyZwJrN209Yg39zQ0rbrDW9471237rogU5hEe1MNg6Z+rysKcJxKqlqI5fmjPf/ff//68f5BBJGXm7K26HGsUmQqQqNUxKWCjlUbXNQRl22jCR64647bbriWJTY29mEAw4vpr0AUELADIkWGMCHIMbJn/ur8PVrAZ+bkqhi44Z7/e8I1bt6xo+hCZSJxGpejqYnJ4b5c4D72m2+/661vyAMOalyYMcEcz6u79esIOBb43Pnu85oCDqrzZE7+DIGJEpzAKWIBYqCE5kY0NMECZdUwKhJM4AembvhnAM15m7Qo7kQYKxkKCGUgBrqH4hP9owePdh3v7B4aGhobG4uiKJfLt7e3b9iwYU1b8+5db9jY4bf6iAtlC8cGxssqYQ7RljZnsYCj5rsEFaiCDVys0JgSi1IaWHWG+58Tt0jH7EBF4M73/9veEd6y40rRDKsQZGp4YHywp7WJPvSetz5w98XZmjvPuQMcqioEB2OACYHPmHB48pnev3vksWPHj0SlqXJxqlKYKE6NicaZjO9EQicwXlt7B1s/39DQ0tKyZ8+e+++5c20bDMAKo4nATs9YKx9wJB5VEzFODlW+9rc/ePr5l0YKI6SVqZGhytRkqVSK47hQKGQymVwuFwT59lVrGvJNLa2rGvLBO+657eq9O5oDxGHZ2gBEtaWYAA6lWVEkcwAOBWJRjw0DlSj02c5Zh0xnaDjOqXoDiCjDwO0P/eGhrsruK24tlT2o70lsEHYfeykbhB//2DveesuWDIOBsFz2CYHnM+ZalcsMOBxAgJUIDBchtN73f37wW4/8/cTI8MToyPjYSGFyVOKQkIbfhxGy+aamlrZsYzMZL9PQfNkVV739jhu3rYaN4QQZP523BHDwigccCU0BB06Offmbjz770guUKRsv8nxnTUgUsgrSCG6GJssxNzYs69rPe+i+u99y+c5EksSQqajQ5OWXBjgUiMQJoVwu53wvo8aoQ1W3sSjXt3o/J52Hf3iuA14Zwe0P/qeBUm7rrjeWohAkEpfjqZHyZD/HE7/7qYduu2lrAJTiUqP1LCiKK4HNzM6S+GvAUUfzAo7kwadGUNQF8RODEpcuqiUGYCg5kKiYJCepMECOqtsAz77fqbSIrjkgSixU6SbEDigDAhRL6Y2S4J9EwZD0zgCBwqgDYigr2zRKdO7mLFnASe0YWrObVMNfzhCaMsOestTHI50+KgF3vu8Pe0fsxXtuGBqeymV5bKjflktxoe93fuf+e9620wJWYTVkIsCbHYxyBsAxa760+rHkhU2EeO3dGBgads88++KP/umn45OFcqyFUknEjY6NBNZA4/bWVdnA8wxt27L55ptu3L1rUy0YI8k/kUQPycwojBqtvHIV6Vg4YNzhpQPHHv2H5/cdOKpAOQrL5XIUR4bZep7v+T4jB968tu3NV1961d6L17TlGWlPDeqg+7wiTDAbMVbdXAAg0Y/oqWljU3vK9BfmW5tLBBwOgQPe/8n/+Nz+4Usuv61UYufUp1J/90GZHPjtj7/n/vt3GU7s3jCJC5DKaw445nBDjoAIGJrQx//xJz944sdTxVK5Elk/MzQyVgojKLc3t/jWrGpudJXi5Xt3X3bprqsvO9/FCKqxQMIwBFfNAmjTqNgVjTlioAQ4oOT01VePPfydJ149cZwb7PD4GDR1yVN1xpLnmUwmk/Vx1y037Ny6eeem8/205huqBd8W6nRTz1s6zbe1F1otNr64iKHqDWsv5oDb88nbUOn2d/2nvvHMxm0XkvUVUWG0pzjaHXDxX/+PH33zdZubDCLAImSQgdEUUM6hQazv44qe+2WmRSQzSBw/axzAgAHDAMKphYAAikkdFFCTCIt6n/xzPtCUOueANYbGIDbwfYID2rJJaj+gZvBTJF671fzKnC7/M+QuXijVSWpBakJyqcdQGrCSKrNrGcBOL9frDYJLVHiQpkMkTApXrmR8KkwNTo12NUr4+5966K23bckBsYIRMymQWHeWXPscVXUYauJ71qRbYEOb2XDLnhtv2HPwxOjxrt4fP/nk4UNHV69efcHWzUN93RKG99z+1hvedHVjDh4nIPYUUgLxslkAziVJdWUYSLvhy3dueePOLb2jeOoXB0bGRgcHh8bGRsvlclNTU2tbW2s+c/nOiy/c2La2EeLAiJREl+R2VyPGzDHUGn6rfng22lguYmWoZYWTqFSaONF7oCUIP/Lhe977zl0ZQhKxnQKjRecTOlc0HR6VTBwDOWBdE739jjfdcMObBobGDx899vg//gTgjvPWW+MVxsYmR0feftfte3a+YUMHSBAAypDEF5gECiWtscEvBRHAcASsMubqi7fuWL91eFJfPvLKq8c7e/unaoBjVWvz+g1rLrxw26YNzesyCKAeoNVBpNqPpbcBQE2lx2nemkVKp1lHuzlzFM8nb4UQa2hs0NiQU6benu6J4b62XPx7n/zIDddubjHJcTcigFI/+V/TGWhx2ZMMUMcGaawxJa5+9UaXZEOvuXbScp1KGMISV6tYAWBQ6hsRQ1VdonkzbIhSfbRRAhBxggUMARYw50bQJjkckzBoYBrqcqJ7ZKoi9uoiOP24nL0bh4AMgYEkKKC5sWGqr6e7e//5q7O/9a533HnbFldBhaLAU0KS8yU1Bp0j0Zjkdqp1swwoI0hGps3Hzm2rfJSf/vHYpz/yzsv3XtKQwcR4/IX/+oWoMNHcAIkRxsj6022pSYEqrfQVnnCDAB5igkxVIj/Ie8D6VXjo5u0KRInRjeFRHaxQOAUZxGCAk3R2MpNb5vHbOPWdOnghQM0qUncrUwc4qqoEMw/CPSuQR5Kx4rNaQ3Ff79HmJnn/A2/7yH1XxQ5kkAXKSWwTkgiI13lyp31vVTxYCdHeiI7G5sCtfjmI3vW+u6+59hIDxA5/+dkvjncd2HTDG3xAHKJy2ctljLgULBKqEUzMmCM50AokgngIE5Uigdub0dFMW1ovuvuaHeqnYr9e5FsgcV4IVZU4OeQsPjHftGikmvDUalipwtC0iX8RN63Xjp3Wn+NUecuAk5L1Mk7LU2OTk2N9LXn5xEffdftvbPFTFU7Mif56Cd39Z0mL4H6qHtwTlWBtHhVwSVIUEgBKyflEkglcTOWMxZMCKrO8sQxgCUxk2HrG84zHlGrh0p2/2qLX5IDMVUtn9e+68SA93TXnVxb3bAWShaEWyv29J3u7D5/XYt73zlvefvulGYLRMBt4qdZKz5V1mWbsc0hOPa4qo0RESpVoohgOnez/8hf+8tq9O2+85pLWDIxDa6P94IP3d5849PnP/lffosFP7/XLYfeeh2o6hrwXZBJBXJy0gAfkGHmDLMFCWGPEZVQqCCtSqcRxJEoy7Wo8TWfkW54xaDzbS3QuSnaORPmXZOOa41Kw8pIuAKnt1Wjc33W4MRM/9MAtv3Xf1WGkeQMCQgeTWmbnioN4DUh5+pp+M0ULqwJQjP6uvm9/7UvX7Nl5/ZVvDBQ5IG/wgXffO3Ty6Ne/9PW4IqzqZX1orYCkoE5snjMkv8yUGLYS25ZNtcgum6XAlwziHOI8NA80Ag2AcVFULCIKEcUMqWpzANRGbxFUG6Jppl38TWb0pV7enlbkzv0VIifx5Gh/97GXAy7+y09+4N5btyfVPVhgBYjic6Uj/+dAZxTjkmDE6pE9vbieKassIqmzjxGCMglBWA0oMePNftKshb3k9rMPzoB9sJ8GO1fxtQWdeiXeFD4QAFkgsTgSI/nPHNdimkJggk/Jw8EgD2xAJjU7Vn1uzSIv4qVfAFSRy+bLxUp/z7H2Rvr0b97/sTuvMgoR8QMrEs/a0+epz1e/BzDOAAMoZY2k10nyKPFVA8AKmJlGhwe//MX/dvmll95/561ZgnOJJgZtrc0f/tAHpiZHHv7OIwI4pwCiKCqXyw7iIKqiKmnF+mqLp6+VRIwaKzBgiYyqGmBVrhGYJUYJxDAZWB/Wtzaw5HnKnoLA1RzE6RzwaS9K+TC5YGqzVjuNWoiBmOoCrvtyyjbzLIX53j7zRSBApGK4cuTAs4GMfvKDd330vqszQN5Lvb88A0NJiwxRcqX0Gs0W1V3TbzJg1XEsGOzp+dbXvrLnjTvedtstlokVsUAFHavyH3zoA9293d/93vfgE4jLpTJg0+x/CgIz2AMWFSH6uhIbBKzWUs2/fZpLFOwgAnVQB/WMzWezylaZDciQJtmm0u8tePY4xdbp/pJ+l6pcagBTlWm0uItntf5MVz0FQUthqtzTdWhtu/8Hn37vb1y13gCVqJwqf0Ae++kGV//dOXnpl/zgdE7o7LqvqYqwprE9OzC6eKLEddWCppM9n0YW17d8TvY6S6ouGDv9zBqoep22QgfnEeJKCAnXtOc+/YkPvOW6SyIHq3XnyDrwd+62bK5XYaqqgFQpFqhqZ2fXX/zFZ9evO+/Bd94DIIxmYM+OVY3vf++Dzzz1829+81vGEADP84xdWWBigVRTM9QYcPrVjA4REvV7FeYmjtiUKAwXw6Vz8fx0CXWBCEQhivR1cqH+ml1y/WyJFMUyoqgg0QRk5MMfvPf99+7KA6JFrtnd0tWiiR7lnDx3KaR1F1ApqyjI4viRo3/+mT/dfcmuu++8o/7j4+PjYezWrWm7//63v3xg/w9/9E8A2PerCUlTzGGSAKvXVDieJdVt/EAKiNM3U61VvQhVQpLYcIZcPSdLdq6d+yzudlqt8ilKj2KpEIWlNe0Nn/7EB37juq2tGTDEGgHFgICImFNM/Muiv3pd6TQLu/5EWy+PfuXonKKkqqCvSvtzu1oWTULQcoTxsaHWpuxDH7jn+uvWegZROGMeZyoIZJ5rsVTrs9SrHpyLOztPfO5zn9uzZ8+7H3wwed6pYGL16jUf/ejHXn755Uf//tFYBIBnA/yzoZp2qkbVORDMBgpLuv9rzpK+j2zGb8iFH3no3o/ct9NpkvIwlyLdxJW6TrM9S8v9upAKPEthGB989ehXv/rVG2+88eabb57xAdWmpiZjTBi7TZvOv++++x599NFHH/uBbw2msTsDc+jtVz4tSbd0tmf4Gd9fBjalxZAhaDi2ptX77Y+97y3XrckHVeM9nxp7L6/5afuXkhZkUnktGvJrWh4SFVZcsGX1b334nbfddF6WkQtgDM8RDn3uadoaW6O+vv7Pf/7zV1xx+f3veHvgpxopmclilShmpk2bNj700Id+8YtfPPaDxwBE1UT1vFylu34J6JdVphF8hu/HD33g7e9/4MoYcCFih0oler1bNptEpmPWVcAWnZ2dDz/88NatW296y00ApI5ZiSgMQ0OIY0eECy7Y+p53v/vJJ5987IeP19/zlwtn/JpqRMDaVv9Tn3jfbTesyQNhhMglcS5z4apzpxH8FSbzh//bH85+L/VaTwJNqklrpv95Cuac8fnkSvTCPNsJ4tSFN8daXGFqqRXWnEUSxU5EedOm9XfftBVVY6g1IAixUpJlvc5SvjCr+cIHhVQ1joXJsKHOE91/86Uvbt++/R3veEdy3lOAKc3HWrsscXIcbG5sWrd+3SOPPOKcu3DbBUwUxZFnzMTUZOAH1ZbMaMzyZr4+O1qoRwLVvaD0W1UV9WyT12K7O9/eN/99zsGAKsECrevX3vSmK30mSwgYrGoSg9nMdp3hWLucLh0uVkmK6RLCSET16LETf/2Fv754184H3vkOYxhAMhc1XjXGisIYA8Ay2levbmtr/+53H85lM62trUHgxy429dqqlVacfkl0qjIAdRqR19TzZtko8X3dsH7DzTdclAUKMTIeLKe+1alf0hzMuoCOz5Ol458DnQFwnEqnBxyn/uMM4/lrwLGcJAAxe4baWpvJ1BzOQYCS0lypARYmKRY6KKqqqgRmps4TXX/6mT/dcfHF73nwAcMUO8fV+IlZz6z/q72ttaWl5Zvf/Kb1/fM3b/aMBZAJAp5nX1rJgGPRRNM/6/z+5/jIwun1AhxTwHlr2po9ggt9kFFHREmemMXRcu5khDQe0xCsoZdfOfDFv/mbK6+66s477piGRvOPYeKm29rWns/nH/7Otzdv3tzRsdqwVZHpZfUrAThOT78CaAPVoN9Vq5qaPAMg4DQvS/UUMN/3Ftn3X4WhWgT9Onr4V5lqsq3BBwCHEoGATPLPORIrnlNK0AYAY6nzRPdf/fVfXX7Z5W+//x1I/DbMDDto/QKuX4ORc7t375mcnPyHf/iHttbW3ZdcCqAShdb6y9n215t+lcQQCYAsOIZGWgm8DGIFiNiBklTEWCHO+1RNNCfAK68c/PrXv/6Wm2++4YY3W07zU54eLaQBRExXX31VWC5+4xvf8DyzdeuWReX2/jWtEGLAQRuyHElo2GOQB7hp5J+46P3ahrI4+rWG40y0wpqzcJI0658otFKMPM8yKgQoakWH5zhfnisNRw1tAOg80f2nn/nTSy+59P777yfm2DkiLhQKvj83aKi/e6lSNsZs3bxZoI888r3WttaONWv+f/beM0jO6szj/T/PeVOHyTMaSShLSCiRozHB2AanBdskg3HCG+6t2rpVt2q/3S/7Zav21v20W7u21zbGNjbggI0zGAwYE2zikiWUUJYmz3R60znP/fB29/RIMzAjaUCC86u3Znp6us97uvv0Of/3OU9wVb3kaZY1q5X3lYUj41S3cJAITII0MrUCB0gNwA0vSjTMbLM+yzxfPcexcRS99vqbP/3pTzds2PDpT38iSbTrNNJPTfksjiQMI891ypWKMbL29DVE9Jvf/Lq3t69/4ULJEo/CWjhOIYQhWsdGa5ABiTSWv2wrGjgR69f7462aNc5MLzhT5aaetWaGLwkd/fjs9gxMc653/ev3gfmAG++sApDLZ+aEoOV+mtfCI4k2SilF2Hdg//fv+sFZ55x9w803KoJp+HgXi4XWz35KhYOWr3Exn89uXHXFlaWx8WIfZ6AAACAASURBVF/f/6u2QnH16tWKoFOtFBNI3k+bojN+HwHANAK/j5k5P/cEvJ3MgAt22QEApbK8LILGdtpJsAYbwBgjQqxo/8FD99579znnnHPttdcZA9dVqWnonEYGs0kaY1VEcp6vUynmc0mSALj88suHhobuu++XQZBftXKV1toYEwQnV3HBE8X7RWS0QgBNDY5jc8T/m6mZ59rwB5X3/qtueRdx3rVNNM9RijBWmvjv//7vRYsW33brLQCiJD2eNq+99tqNGzfee++9O3bsAKAcRUStphTLyQorsKonF2sGYE+TH+fdR0SyrRCHmRUGBg7fc8+9GzduvP5z182pnaajpBhxXTdJEhH5/Oc/f+aZZ951113DI8OO4wRBYIw1wp9aTElqY9fL44TefrJ+BwvHNI8H7KdiARItlUrl29/+Vld31y1f+GIuFwBQNCXGeq7jJI5jz/MeeeSRZ5999qabblq2dJlylE41q5bQ/ffhldYk9vs1H6TGOMzVKNy/f//37/zBpk2bb7rpRmnUdJ7iXUTADBYOoL5FaYwmJiIy2rBiIrr77ruHh4dvu+229rZ2Yvogx3W/3ziB+c0+GNihb5kXDh8+9J//+R9BLvjaV79WzAdZjvbjxPO8OI6vuuqqhQsX/vKXvxwcGgQwb5UBLR8UiElDhoaG7vv5z8877/xbbr7RGKnVqsfWWiZ/0zRlxWmaArj11ls7OjruvPPOQ4cPMXNm5NCpPoEvwWI5JXgHwcHT1Y56++ashPlA0ZL1ErU4AhCnycGBw9/73vcWLVr8D3//Tw6zFjSPWTE1vXQrmZ/pl7/85d7e3jvuuCMMQ2YmotSY90f0/9tjv18niiiKmj/TJBkcHPz2/3x72bLln7nu2lggTH4+31pMaVaFlY5KJqqUMsboVN988839/f333nvvwMAAM0dRpI2WFubhJVrmn7m4O1tgpy/LicPkPL9UKR86fPib3/zmihUr/+HrX8v57nH6bUwLEd1yyy09PT3/8R//MTY2BiBJT7qclZaTGd/3daq11gBGRkf/51vf2rR5061f+MIJaZyIlFKtMsLzvBtvvDEIgjvvvFOn2vM8x7EpCSwfON7Bh8NieXsMTDN9WJrqg4cO3X3XDxcvXnLrbbe5SiGLzp1S7nny9vGoXaOR6vSXv7xvaGjoa3//dVJstPEcVyllRfQHltn7uERRpLUOgmD37t133PmDTZs2feGmGwCkWcWao3w1qOWP2dRga51XMzuc7/txHP/wR3cnSfxPf//3PHWczmycOx6vJ4vl5MKOYMtxkQobsAZr8MDIxHfvuHPx4iVf+cpXUp1m1U9mGmHHOfJSnXqe87nPXZ8afOe7309TyvuBq96fMYeWOTFdvUEDoydz0wC+7wf5/M49+3/4ox9v2LAhUxvJbPf85kY+nw+CwGjDjvfZz99QDeP/+e53iSZr8mKqQLFY3q9YC4flHTgijK9Rxj7LsseVBMaBRzgwln73m99cs2Lx1265Hq0p+Y64Umy9kjvKx3tWV6jNHFiNutj/7//3X6ctWfGlWz+jAZ3VViLEYRoE01utrcp+P2LQyFPSHG5U/6wNxECkJecHh8DOPYO/+PnPFvT2fPVLN+Pt7BaGuGngODqo9Z1HUzbmTSNb9sDQ6HfuuHPh4iVf+uJNcaw9h0m0q5ibHZ/RD9qOXMupjR3BlrkjqJdjzrJBE8oa3/3Wt1etWFZXG++KB37mx2eAr9z+tQMHDv7Pd++rVmE0kjh1AN93ssjGZnyj5X1PNp1NV1SLwQziZoK5JMGPf/TDxYsXf/GLN799mycwDCoTQAt7u26//fYdO7fdd9/9RKS1dl2HwDKZAI1nOCyWUxtr4bDMFQMAYiAAOxMJQo07v/U/3R2Ff/jabQBMqkmxITQvB6daOFp2PWawcLQy3Sw7xV6u4Qiwf2Dkhz+4a8XS5V/8wmcTIyZJfcclmkyT8L4PYLEAmBwYU4ZWPQlyViQljeOBgYE77vz+0qVLv/KVrxDBtPhtZKMzG7E6czkiAcDNVLhk6vklp2H6+1vHXhiGQRAAeGvPvrvvvWftuvU3XPeZaqw9b/J7MU+7kBbLe4761389qpaKxQIAEJGWubJpEiYDEmIhToCKwX9/43uOxF//8q2e5yKJodxStep5btO23brU09F5rI/aY5nhn62PynbiNQCBCLirkOtauOCRRx+uVisb166FGJUFyU6GNVrB8UFAGj+ybORsQNlAMUCo4TOGS+Gd37+rr7fvH77+NSaEUaKUMgTOKs4DaI6alj9oykbNTEz/r8bYM4A4zJmK6exoD/JtD/3pEc3+2tXLTGsKMTri9zuf2GI5JbAWDsuMGGOyrIhpHIpO3VzRGFPTTC5S1I///K+fIIn+n//7y0igJPU8R4BqaIKAjtnC8U5XcqblyPxVndCkip3hweF7vn/nBeecfdXHPpadwKSJiDArEQOA67GI9lrx/ceRY6epMxIg0dApcj4GhuJ77v1xIZf/4i03d+fBQCkyrssu14ehyORwna7Gy9EjdPZRJJkhRWttDNiw6yts2Tfy7e/94OMf/cgnLz1by2RyvChJtTau6zo0jUS3WE5RbCy4ZUaYOTNyOF4A4OBoZe/BwVe3bNtz4HA11uVqXA1jY8y61Sse/evWM1av6GrzEw2l4AbzN0c25/fmrrbjApqdHEB9PZ/83Bd+fNePgu5FZ5+9MYqoLecpIAF0lPjKJiJ+/6OBcgzPgwHKGlu2Hjh8aGD37t2HDh1O02RiYkIptWbt2me37l28eNHSfqfN52qCNEXOg8L8uvuINiKiXF8BGigBC5d0X/O5W37x858W2ro2rltuNIjhefBcR7lIBTBwzMlQ3s5iOQFYC4dlRjILh071eCy/feq1x/724sToiE6icmlcQRQRsxLlCbFyfRi9fs3qj1/14cvOXOwCBiAc4TrKOKJA7awtHNm14eT9LZvomhAZTJTM8OjYi6+9+caeQwcHhwYHB33fzxfybcW2lStXnLFi8YXrFvfkHOUcGTfbOv7ttsspi8m8QTU5ERACh0v4y7PbHv/L45WRARNHURSlSRrkgiwfxlg1lFyXcv1z1q++/KKzL9/cXwCkMfDk7Rb447FwAEA1jIPAqwED49gzOLZj3+CbO3cPDg4PHtxTDPz+/oX5XK6nt3f58mXr1p22oB1FgwAfiCy6lg8CVnBYjsS03CiH8uyzzzz4yFOv7Z8oJxLVquWxobA8rqNqGlbSRDtBoaO3T5PT27MgF3hdbfkz16+5+spLN21YogCnZfM7+8Wtk/kcBIeZFBziADAEATSQAg//+ZXH/vLonn07xmpl7uglPyCm8bFxAK7rEhFHlXX9XZece/alH7pycX+PAlTDuGcFx/sCA0lBTgwOgV8/8sZjf31u2649Od8rDe6PKuPjY+OVaoVZKcVhLVT5Ys9pa9xcseA7eUc+9uELPnHFh5Ytau9ws8ZEpvM1qp8ImEFwzLwB0xjnCaCBQ2U8+fSLj/7lqbf2HfTybWPlKoDu9raoWh4bH+/u7hYRZl66dOnF55955fkbF3Z7DLgEB3U3KmM3BS2nJlZwWKaQ7XyniSGXx1Lc9ZM/PvPU44OHB0pj45VqtVauaJ0QDIthGBKIiCEI2BB3dvX19S/s6urMFYo33vqlD12wol3BB7SBofplo4IAoFkbiRvTeQqYalhR4uRybWi4sD704sBPfvmbw6OHDCZE9jleSD5IKQAihoizTfAkQWVME3X19a4/Z/M5f3fNh3ryqhPwZk64ZMXHKYWBTqG8XQP6F7975InnXinXKsNDe4cO7U1K44pM89NsfNwc1qJcoaNz4eK2rt6u3p4F/d3Xf/4zHz5zeScAo0WIiOr5MI51Iy77KjGgEg0ArhpJ8bundz3w2NMjQ4dMXB0ZOFgaGSmPDYlJJ6NggP6F/Z7r5fJ55fu9S1ZfdNFFN/7dJW0KbYS4UnEKhUqY5H23mbfDjlXLqYKNUrFMkvlhliM4Lo2G+OZdv33sqWejWuXw3rfKIwO6UkIaOhAlhiEKhkU70A6MIu0AE+NjpfGJMIpdr/jyGzt7eletWNLm1XdWJMtq3siRQDK7ObwhBwygU53mg2IU6WrKZUX3PPD4d+/6YTktp1wmb9zNjylvnJ0S8RirEnGJVclxqqzKRmrkOZqd0Uq0c/e+fQcOL1u20nMc3yHMUJPLTuKnFARWCXDnj3/3xF+fnyhPHNizc3jfW2llJKfIJXEJZDQbrcQoMa7onCLSUWlifHR83PH8Shy9snVbb1//4t5un4WIRWTKKJj7cJCGPYINhFTI+MVDf/v5A4/vOTAwOjK4d+eb4wMH0sooJ2VPEoe0Qpodgwf31crjaViO4ySCs39wbOfuw2vXntETwIhO4eQ81dojO1YtpwpWcFgmybaxhVE1+P0jz/zxz09VyhPbX3kuGh8Wo5nYUQ4aExwhq41JAhIigBItURylcQLF7LiHDh5csWJdUAg8BwQxRFn7meDAO83hZkqUrAGM7xSrSeJ6Hjn0vV8/9euHH2R3uL1tNOcd8L1BVhXmhDlm0kxC0EyiVCaMYkfFgZvkPO0Ae3eNDw1UVqxZmiv6DoFlmitFO4mfQmhgJMR3fvzHv73wwnhleMeWl8ujB7007u1o0zoxRrKK8BlEBFKsPCE2OkIaVUvjAGvQ3j37Nq5Z1dXZ7iiKk9RRXB+qxzQWCFCIGQbKTQh3/frx3zz45/LE+N7tWyYG9objh10TepJ4JEyGYQgQIgCe64lIpVwZGxstjY4UioWDo9XXt2xbu2p5f3c7QIpaw3TtWLWcMljBYZkkm1pDgy27x//7ez+O4mT39m3lgbd6iwERM03JG90wWWR1u8mAYUyhWFSM4cEhUq5S6vDg4IcuPTtgEGlTn4KbyQ7eYRqnlgL1CoYAA1VNhR1170N//fkffxPzeFdnlbDfdUeUqoAELKC0XqQChrKMIWQY2uHUVcbh1FOu4rY9ew4Njo1s2Lix3WVHpBmPM3l2O4mfOqTAQ0/t+eNfnhkYOrB755aJ4X3tgVN0nKhW02KMmCM+WQ3EWjMj53EucEeGh+Iodr2i0fBddebmdT4jiVPFRMyZz8SxjoYEoGqk7n/wyfv/+OexUmXv9q0jB3f7SPIKHhkHmqEJkkl2AmljjIiIUcrxHEentbHxCbfYFae6XBrfcMYZbT7rJCKedH+2Y9VyqmAFh2USA8QaNYNv/fAXO/fs2/3WztroQLtnHBgRlc26RJTZmokI5IBUdhBBKUUmhdGOUuVymZWrXd/1iutWLHTJMBGDWy8XZ5wmm9VSqG7nUDCASoQjUq/sHf/Wj78XOfv94rCrRhVPMCUgLfXm6/5+RJzVCReQCMgY0pp0ok0cxyFcd8+BskLukjOWqbpwapBJIjuHnwqUSiXf94cm5M77Htqx99DO7a9UJwYLLjk6Ji0M1iTETC0AIAI7isQQEqQJiHSik9h4nj8wNtHdu3DVsj4TG08xiDLLHOauOcQgNZFw8Jfn3/zprx8aGh8/uH9PZeRgQYkH7UAzJl03pJ6ljsSI4iwNezYMyRgThzUimtBOuRZdvHElK4fENDcDreCwnCpYZ2fLJAL4Clt2Ht5z4NDExERl6KCHyFWkReSoOU2IhSBgAQsBYBawQIlxJCUdlSsToxPhGzv2lKuhQ6xAXM8fPbcuAciybniESOP3jz4+XB7z3JLvjIInRCWajSYYak0I1pjHRTK3VgM2AChmqjreiJcvw4uffOavr+3cX6vVWjz2LKcSWZrwffv2HR44PDI+FscJGVGNVOWawczElB3NZzEJIyaVZA9zmD2XpTo+dOhgJTQPP/GsAdzAm1qCcM4kAKnCREJPv7T1wND44f17hvftdCVWSDkbosKG6oc0puLWfpKAWdgk8cTw0KH9hwZHX35jx6tv7oTEx94ti+W9wwoOyyQGKAHPv7JlvFxxSAeI8pxoIU0OAEzW0zbNxxvKNp+5pQ1DMIpMWK2MV6vbdu3ZtXsPwAySWc7f01TfYgBjId7aO/zcq1s7uroLiIsSstGaOHQ4dqDZCKdCRsg0y11lfwohVk6snJQYlDpuTDTa0RWPjW9/7rkn0zTNdJBVHacCk4JSRFzXBfD8C38bHTlQHj9MaeKRR3BBfsKcMDCpN6hFeRiFWEmqGam4onyH3IISU5mINEbK0ctvHhZCo7LKsXQx0tAEAl7ctufJF984NDRaGdrrp2NKjAEbsIGTsJOQp8nR5GSy4+imSKBAIrpcGh8b2L97146Xt+zU8MTmArOcgthRa5nCSAV79h2Ia9WxwcMBaxgNwICPNE1Q04ow7TJtXEXGpOVypTQxsWPHrjhN0KwwOxcmTyuA4Nnnnj90+C12q47SSgwRZcYVc2TO3CkDu2HhYCE2BOKEqBR45dSMbd+7dyySbO+m/mKsffokR7I0X0YLaeDgaGXrrn3VWrk0NuQxe0oBDGFdNx5M0wAL13NjiJNZF0TEIfZcNTExMTg8sm3HzmolOZ4+xrFOgRHguZe3lqthHNXiSslnEtEioiFastqxbMAzV4NrdBjEWktU1VG4dceeQ2M1bbdRLKcgVnBYjiQMa64inURZ0gIzWTi7fnGZXSgqkuZBLJwVdCMFVmBFRLVqKakMs0RRFAk7URIjnSI4zAzHEdRrfQpEsHvXzp6uisuHxIliIhFiTcqwMsziQBwil8glUq2HEuVCFJGQK2BQqlSY1A53deW37B96fe9obCACg6yWvUD0Ub2wnAzUpUZ2IwzDFAidwkjieEHO6IRhiDUoNZwe/WSGyg6wEuSAnIJiqVdNq6W6GkdII1fiOIwKba4WAGCpl5Wf3Wit4wU6Txgo6Z179+rKWHXgoILr5tohzNJIY2M0GU1GRIQbNVyYiAXNsQupG+sU0dD+A3GltvfQ6O4DY80TWwcOyymEFRyWKdRqca1WqdVq1WrUlBqUCY+j4Em7gEHm49mwJRgIYAgpITWEyUl7jnBLFc04Rq1W9pyQuCxksmSjEM4EB2TmA1yPPZTMcG0YEVMIiiupmQgNaH6LaFhOMGIAFPOBAqopJiqhAZMYYxKYLP2sAdD49I9+OgsciANhanhPGALAUa0aVithGIYhzDRbe7OCYRQZA0QJojBVErOJAIa4Momuf11a68RO21jDOyqpVSuV2thEODg2Mec+WSwnAbZ4m2UKJCCBAWtigWPqCcUNC+quG8Kt6Zy5eZuyeTy7bSZN2S2TPr2T6TijVdrU83UIDBDWMDFedlxXjGTb63TEI2dCsoTo2dm1YQNhSAykYS0slcqKIEZsaMpJD9ejpan5N5SAxDS1r7DJKr8aEOidhSQRTZdw2QDghp9Ei3mj5Y6WRx59fzaWklDXypGG1tBOXSbxEdqdsp4KATjaNbsVxWyMiaKoUq60dN5iOWWwFg7LJAy0BV4h5wf5gpdv08xESkFMmjQdRSdvADOalIVx9Ow5O7VxFJM12+JYqtWqUoHIMXrz1TvSEpSSpEmtVnXs3H3KwKC6hK1WqwIEDjoK+WNvriVcFkCQC3K5XBBk4S/HjgID0GEc18JUTEoGgGjztsYM4G2tHflCIQgCpRw7Vi2nKFZwWKbgOlh3+prUwCu01RIjYIJBEsKIaRyzacdzvVwu179gQS6f27hxkwiISPFchcKUnXJ20p7e7jQmhwrGKDFSP1qYsSVKgRRIiQjCRArilEs113G7urpDA2bUUy+hUUTDcpKRVScxYDADnM/nGSgG2Lx+jau4q7MziiIA2SgVEXmnsZrFoDKRYnaUEjE93d3FYnHNyhXT2X4bsU+z6CfABBTybm93l+MFiRYArjrSvHFkfwQAVCO5zRHoNNWpZqLunm5YiWw5BbGCwzKFfID1607v7uleuHiJCgoaYkzqMIyZm9N+FEWu67qet3zZsr6+XgDExzdDEto73e7utloVitvnZi8hA4rBMSgFjIgwfJgA4vX19ff0dKORc72O4HgSMFjmj0xz1PdWAAJ8hY3rTvddr7unJ07iTHPMkqYiMSLKcTo6OkWkv79/+YrlR7kNz22qzFxRiz4v7O9kx2/r6AMQJ+GcGml6kmYUikXf93t6e7s6u+bUjsVykmAFh2USAnzCGWuXnr5ufa5Q7OzqTQ10EimHeY7GCcd1ly5d2tPds3r1yr4FRUAUZl0idhJmOBAGGxDyOb1u7XKGH9XUTO5HR8zRDVJwFVwGxaAU4hB8mCJMftnSVact7iHK9tft9+FkJ5OCBoAwjDaAq7B+3eqNG9e3tbV1dXVrPed0KtqYNElcx+nr68vl8hdccP7iTqUAPlZDF9edptFRdFauWJTLd7W19Zo0icPy1B3Jo544/eit09XZmS/kly1d2t/fbo0bllMRO8FaJslCQgouLjv/nJ72Yl9fnyYnEobrIotJmWa6NFnur+xIGSlzwtzW0+/6haXLTvv0Jy5lAWcVV2QOA65uvK47qxpGmuro9DWrOoK2ymjIOiDkDLI8Co2nvINZwoBSABAHJq+l3Zjiou7uxV1HJXg61npdlncPgtYpAy6Q9/DhC89uK/gbN2/Kt3dlqbSAeqo6Q9AiOks4mx1sQCkhBaUgkxodGTFuUOzs2LR+1aXnnoFpPv+56RgyAkjBpUV93V3tHX6+qPyAfV+QxUk13FFlUmRkP1u/TZqhGabhDuUX2/xc0NPX2VM8njfOYnnPsILD0opROmxnXHnOgos3renp6lq1frMpdJe0IsUOw2EwZ4VJYAipmChNEp1oNuJwBBMBw9WKKna0L1zVt3jVFZddkvfhMlR2sZhNrLM7AJN5XTSjHDvc/HkbNnz4nLPNRMmRdp12aO2DXGECiwLRjKkhmU3AJmBhMqIQ1EK3knQsXLj2sx+5rNjIGjb5ZWjs18w264Ll3WKKFCQnu6fo4aqLz7jknA3Kz/evXB85uUgckAIQGR0Zna3cKWnNRrMxZHI51mkpCic0Eu2ge+lpK84+r71/4Rc/d82i9nokiSHM4M0z85htRTQBm9efsf6Mlb0LOhesXDMWI9Js4GSpcMkIjM6OLBuHFtIQDUlJp6RjEhP4ERDHYc+CHgn8viWLL7vkHG7EutjxaTm1sMXbLK2IjmpidOC4S5Yt275958j4REfvoiRFrVqJkzRKTGzECAsYDFbsuI5SbgpODGn2opT7l61atGSVn+u47rPXXnvFBhdQgIJkBVfmYjkQiLTYVFR23Vj0C/v2H9q+57Dy21zX1TpmR4Q0QEICgpBpmN7rR+MyUhlxRPJiekZGPei+a664+sqzlgUiTHTkds+kQDr6bst7g7RkvadGvT0DYaGAcNry5W/t3lep1fLFztHxiVJpTAClXFIMZlCW4osExMQmiVODSJRRfu9py1ev3eTlCp/8+FUfuXBdUM8zh6l6o3UsvPMoyGoiG2Lfo1y+49VXX/KDXBglYRgZY5g5k9RElPUIRJrYMBplkgkkQkTKLVUjuP6SFasX9C+8+iOXffi8lcHMNjg7Pi0nM1ZwWFqhMIpYkUbYUyisXrN0bKRUqTpCRcOOVn4sjhY2hkQMCUyqk8jECQn8FH5337K+01YvWrZ2Qf+Sz/3dp667en2ioQCX4BjK0nRhDo6jmePdlCXGAL29nUnqv7ErTKRNQVxHmGPDaewgVSYr9t1YWeqHYUQOpeSJKWrpraWLkXafvXrTVz93TYcHnrY2rBUcJx/U+MlT7yTAaNNdDNasWDo8NFhNyS92KscplypKuUwOs6vYI3IgCkYZUeVIk99Z7FnWt2xd/6IVvT29137i45++6twi11VqI2SpydwEByBCKtMOy3oLLqttu/YoL6eTMKpVRWtmImIhaHJS5lQpzWSIAGIwCZRhgiRJykFh6eaLch09l597xtdvvNoXcWd2LrHj03IyYwWHZQphonO5giQhO9Ld1rnpzLPiBCOlcr6tzSsW/XzB8fMgR5NT06LJJZUvtHV19y1c0L+4s7u3p7tn9co1X7z5hqsvXhQAJGhTddeNZi3tWfelub5Qc5VJ0zSNkzPOWBGZzq1v7oprYUdHZ6JhiDSLkCgRPkonGFIp8qnuEN2bRl3VcW/9ig3//OUvLupgv/VUR53cCo6TjWmv7Emg49CYtKerc+OmTbFGuVJ1XLezs8/3C0JulBhDrpAr5EB5Gk7/4uVdvQu7ehYU84WNp59+642f/8jFK5WBwyCpZxZTU840V8FRT6ihBC5h3eql+wbH9x8adFzPaFMLQy1CXBdOQjAs0igMBCiBAlwDN2hvW3XG+q7e0y4+78x/uvkzXYFi0XEUuq47rcOSHZ+Wk5mjU+xZPsAIdFY8QgQCMDRTDdg9OP6nP7/w5N9eMOByNSqFUaIlTRJXKU8kxyrnu55LK5YsuuC8cy69+Oz+dsSZRpC6IyoDlIUXzDkVxxRMGjMrTUoT7nvo2V/+4dEDo8Nem+Q6Qi83mKYDZCpM9ZDGSrnS0dHh+34tVCOjrucvH5/I+Shede65X7nh88s7AICNTGaubBVDduY+lTCQFGBDTvbZ7zpUevAvLzz+1xeHR8pGCFkwtIgx2mhj0qSzo9AeuBtWnnbJeWde+eEzCRACCRSDYbKM/q3K9dhCuk0mk+MKvHwF9KtHXrrvN38cG51Iw8reXduSSol0rCQVxJoN2BU4cULKLThu0cBZtWZ1osxpC7sv2Lzuqzf+XX+bS0gFjgEpOz4tpyBWcFimkEWH1h0nCMJak0nhVoHdB+Mtb27fs+/Q3oOHytV4tFQ2adxdzK1YtHjD2lXLFvefvnxBwUPOhZisMgW4aZ4GCBpkQGqWrspHeMAxACP18l0EsAvgsVeG7vvdw2/u2w63AmfA82uKEkIKgIlSnRJxmiTVGjy1MIpyixet/9B5F9/0sfM6PBidBEohq8hiBccpTVbrh2CQCQUkQBk4MI5XXt1zN+C/QgAAIABJREFU+PDgrl27BgYGkiTN53MdHR35wFu5fMnpSxedufa03gKyFDOagMyqQQbChqDoeAVHo3spyEmBEPjz83seePjxt3ZsT6JaEoelkZGxkaE4CZUSZhY4qWG/0NnR2efl8v2LFnZ0t11+4Vk3fOyCogNIAmFNSmh2CcgslpMMKzgsLQiyQqmN8rAgyTQIi6IICGPkPMRxlnwJjoc0hu8h1/DPbKk6kcIoiNuynM9ZcDSHJk0KjhQwEIZyS+WQ/SAS/PV/33zoib/87xuvFTva4zjOymoQURRFIuJ5XhAExSD30Us/fPmF57d5XneRs7CUJI1c9iZPaQXHqUlzqCgYiDHasONl99cAAbRGmsIYEEE5YIKr4AEM6IZTcZZEn0io4d/cypwFR8vYLYVJW+ACBqBQUyR46fW9v3nwkd0HhkerUTXWJkl72wsjAwcB09/X095eFOhCMX/e2WddfNG5KxfkPAOHjQgZUCaMHCs4LKcgVnBYmhggW9TrdV8BVgYwBhqhJELKdV2nMc+ZNNYQISjlKVBiYp3EJHAYTEJKQRgIJkML5m7hmFFwQAFOEieO54bahIZrwFgZr72566239g4dGhocGgTQ3d2Tz+WWLV+2cuXSzRs6PYM84DHiOCUS13Wt4Hh/kKUfZUCJgSTQlEAZVmAoAqFelk8gAFTjo62lcWrgui6DAMMwLPUMpnJUirq5WzimVHorhUmbL0hj4TwpnkjBDrYeNG/s2Ldt996J0dLO117passz0tLEyCev+eg5527uX9DVnUMW5AVAdGqUyqK2ssQ2VnBYTjms4LAcQTZRtsxmAogIQURap12iLPxU6mmJSDCZesvACJGqe26gITiAOflwHFmIM7OcZ3kmDWcxiwakG9kns4VlppXBkUy4TA74I19RM1020NLtufsLWt516qNWANEiJI3tFeJmCeNJ0ZBNelqEWsI9js4ad3yp+CcFh66nnxESk22INGyAdX79mz+/+vIrX/nSF/sXdP3oR/coyO1fv7VcjrvavPrepoAhEGoWYZ7iw2HHp+UUwQoOyxEcJTgaE3RzeTb1dZmAGat/t07f9eDWetqvuc2IR1UEN40unfiZ1QqO9wFH1PA7QiI3H4Oj5SZR819HP3fuHCk46qduadIBNPCb3/7hpZdevun669efsUYLxsfLd/3gBz3dPbfc8gXloPW5U75TrV9QOz4tpwjWLGc5gnlwR6Mpv+bEUUkcZ1uxc5Y000gDM2dTspxSzFUotJanb63Oeny9eOeBaoAnnvzbo48+es0116xdtyY1qFbC7s7iDdffsGfPnnvuuTeObO5Qy/sKKzgs7yYn73puTt6uWd6f/PkvTz322GNf/erXLj7/bEWIoqStGESxOW1J/+23375l65af3/fz97qPFsuJxG6pWGZF6ziRWVz8Td2Sabl9kq3rR7qJNJnN1+Ikey2WjJnmtFajxYnbOpmeI0wTzZOlRnSa+p77xFNPP/C731133XUXX3hBnOrWasyZX/auXbt/9rOfrVy96rrrrnMcpbU4UzaAZtEJOz4tJxnWwmGxWCzzSKv8SZMk77nPPPfcnx5++Lrrrjv//AsAOM6k2mgqif4F/TffdPOLL774+ON/sdO05f2BHckWi8XyLhH43l+ff+H+X97/iU9+4uILL3C4no000xlEEIFOBUC+ECxfsfSzn/3cQw899PAjjylFUww3rdUJLZZTBOe97oDFYrF8UHjiqaf/9PDD1332uvPPvyBOtVJKUT0Upak5iEinwkzEOPvss7ROH3jwQc9zP3zJpe9t5y2W48QKDsusmJqvYq5PPqFdOaHMaOI7iftseXtm45MxH34bGa3eG438p6hGoRj52zN/e/KJJz/1iasvuOD8sFYLgpyiyQwiWaSrGEgWLMMAQIJLLrqQBI/86ZGOtvbNmzZnzh5y9Gmy12Vt1paTGCs4LBaLZR6JkjjvB3967NE/Pfzwtddee+ZZZylQkAtUlq0uM280hAIxYCb/dF0F4JxzzgHws5/9DEBTc1gspxxWcFgsFss84rju40/85Q+///3nPv/5Cy68UIFSY4gpKxvw9qYWo8EKvu9efPGFoyOjP/nJTwCcddbmVn+OeTPWWCwnGCs4LBaLZR55/rnnH3300RtuuOHiCy+q1Gq+7xNTFEWeG0z7+KZ5w2hoowHFCkmiP/GJa5I0+dWvfrWwf2FfX9+79wIslhOE3fGzWCyWE0wtChlIdPLMc8/86lf3X3LJJRdfeJEBglyQFXDxfZ9hFAlDeIZQE1ZQrIggBo5SxPjkJz+5atWqb/3Ptw4eOsgKqU7jOH53X5nFcuxYwWGxWCwnmIIfpJBt27Y9+OCDV1xxxdUf+3hqTJJMEQezc26dvC0Grqtuu+3W1atX/9d//dfQ0AgAz/NmfLLFcpJhM41aLBbLMTJTsZNYJ9u2bfvpT396xeVXfOzKj6TGABARVpPXeFOKsc0gPprRKK3hJ0miv/u9O6rV2u233x4Egee5zX8p689hOYmxgsNisViOkZkEx9+ee+aBBx647MOXXX7FFQ5xksTMSsQwK2oUTJ6T4AAgAlaQRgzLt7/7vVqt9uUvf7m9va35mNbdmfkL/bVYjg27pWKxWCxzwLQcrWTFYcMkeuW1V39z/68+dNHFl19xRRRFAFzXU0opx1FECvVjNpVpiSePDGEYIDX4+tdv93PB975/J4BKpaIIiiarHxuCtDBvb4bFMgeshcNisVjmwExWDYHoNH1ty5af/OTeKy67/Morr2TH8Vi1zrDHf4WXnb1Wi3I5vxbFd911l2j9f/7TPwKo1CLfb91eaS32Zq0dlvcea+GwWCyWY6S1pAmBnnn+uTvuuOOqqz768Y993FGOz0rPT7GTIOdHSRr43uev/3ylVvvuD34AwM/583Eui+VEYQWHxWKxnABeeOnFhx566NOf/tRll304iiJXqRQieiaDyHGhANd1FNDR1XXbbbft33/gBz++uxZG83Eui+VEYQWHxWKxHCNZkvEwCt/Y+sZvf/vbSy/98DUfu9p13CAXaAiMsGJuuHecqNlWBCkAINMXXd3dt95yy969ex944AGH2RhtjHbYzu2Wkw47KC0Wi2W2iIhATAMADOzdu/fnP//5WWeddfVHrmIg1SkAMUJMNG9lAE1jr8ZnWr5ixS233rp1y5bf/v53SZJ6jhunyTyd12I5ZqzgsFgsltlCRArkMGeHBrZu33b3PXdfcP4Fn/vMtbU0FoBZzbfaaCUyYoxeunTpzTff/Ldnnnn66acBeI77jk+0WN5lbJSKxWKxvB2ZF4Y0bpeqqQELAcDufXvvvutH519wwd99+uoCIwXKlVrOcz1XKYgxhtnRAOqbL+b4r/GaBWY1kPXBB2KBR4gF27bv/PGP77n88ssvvfRS36+fiwECqJn5gyZflL3itLyb2OJtFovFMiXYtbkM61TX4iTIBUKoRBgtpa+/ufPNnbsPDY0eHhlJjQnDsK3QvWMo/f0Tr522oGvFksULi7kwhQJ0VFMMsJPlM88ZDaRg9zhXeQZA0JCsjj2yABmjoZRHWLJq1UUf+fRjTz+t2vqXLl3quq7vO4GHbg8GMFGNNKlCkGokBoF7IhSQxTJrrIXDYrFYJgUHT/7FACJAA1vfKj32+NN/e/a54dHxfLEtTk2iU2FyHE51Cp26ijraixvWrb3kogs3nr7stAIAQGKQFwJSFxwGrE7IEq/rZg4YkAfEQDUx23bu27F36K29B19//fU4iYkony90dnS0FfNnbjh96aK+M1YuafOAehCvxfJuYwWHxWKxtGIgKcBJKhVxK4T7H3jht797yBhTLU/o2sTw4QNpWNFRVZEu18rF9s5cWwe5ua6+hX5bV1tH9/rTV37mygs3r15UdACIFhICCVimlEQ5HloFx3A1fe7VHX99+c1nXngpIKpNTABIkoQVK1bKUUxOKii2ta3bePplF511+dkr2wCjEYdJULCuHpZ3Dys4LBaLpY4xhpkgGsQpePv+0g/u/+NLW94aGxkbHx0pjQ6ZcCKtTjgmYpNAEi9wg3wh0jRcCr1iZ/eipcXO3v7ent6i++Wbrr3snLUOAKOF2ICETkxwrAHihk+JBv7zjp889/KbA+XYpGZ07+64OjEyOuq5Xq1WDYJcsVjwgnyxc0HQ1mYct7+37crzN1770cuX9RUoBdtNdcu7iBUcFovFUieO46zge6SxY//gD3/6mxe37hmbmNjzxmsOUhIjIjBaoFkAGFECQMAAEm0g7BfynV19y1ev6SwWPv+pj3zyIxcHDBitSQnAdByCo+HymQAGqACvbB+652e/2LFjRxLVhg7t37djR5vnOUxKqWYJFREx4JrRbqGru3dRob23s7f/zE1n3PTpK9avaC/MfBaL5YSj/vVf//W97oPFYrGcFKRpyo4TAofH05/+6oEnnn62Ui69te2NwNR8kzA0RAgiwgIyBFCW+gsEoxhKYkS1Umk8MSyuPzJW6entW9bfRUQCohNSPp6ggYEIe0f0d+784e49e8aGR3a/+XppYH93m+eyKAGMhtEkhsQwDJEmRWTScKJULpXhFg8NjuzZv2f5slWLOgMCjEalWm0tc28Fh2U+sILDYrFY6hhQwjya4okXdt7/+4fiOHrrtRfcpOQxCIYxWTCe0JAcZAjCYhS0AikWQCaqEXv5mnETw2duOD3vMotmzN2JQwDAtCb0IGhgKMQvfv3Arm1vjA0c2Lf9NdY1jzUgRlgLGZDQ5EHELrtsjE5rouPy+CHPwURoKtXaGWtWtOdcYdTCyPO91rNYLCccGxJlsVgsdYiQCobK+P0jTxhjBg8fSKNS0XcyUwFgGCazHJAYJYZhWMBiWEACACxwSLFJDu59q1ytvvTG1pe27kkBsDqunkn2QzSQAg8//OTzzzw/MTi0b/sWjmoetKccMaSFDPERhzbQSQojucBrC5TURof27kjK46+88vqfn36hnIKBXC5AFpxjpYZl3rCCw2KxWOq4SrmEZ57bMjo0Vhk4WBs6wI6qGqNBWuoebwyjSBSJAikDFrAwCUMYwgYOCYoOUTQxdHBHnFQff/a1ClDRqKXpsfRJ6mojiWuGkAIvbT/8178+UxkZ27V1i9Rinx3SpFMH4rVO6Sz1AwAREZFJJA4Tnz2pVaqHdsWjA4898/Jre8c1kKYtVeZoXgrOWSxWcFgsFkudWEcHhkpvbt1WLZero8OURKxYy5FX/QyTHQCoYdtoqdHGLIZNEpfHxkdHdhwYeHl3EqYw+rj6ZowQiIBXt2wfHRmfGBtHopVkHXi78nBMRDT5EhTIgaSlserEyP7DQ69s31MDCra0vWX+sYLDYrFY6njKr5TL+/btK5VK4+PjWqeOcgCImVs0nyEASEqV6sj4wOjI7kMH2nzk/WNa1KneoJ/LJ0YPRdixY9fExMTY6BiArHtzRbGqVCsTExNJkuzZvbtcMXF9y8ZimUes4LBYLJY6pepEpVwBoJRKtWZmM/fEAUIQAhGxkVqlojynFoWV9Bi9IwzVa6ZoHTusdmzft3fP/lotKpVLruO2mi5a4Zl7LSLZDkulUh0bGzt06NDhQ4eTOJ2yj2Klh2UesILDYrFY6jiOa4weHh7RWhfyeSLO/DaIWwI4ZoHWRjlOGIYAJiYmypVKwUGazNmHw7TKCVEMVCtRHButtdHTeFo0PFgNGs6tRz8m66HruGmaEFFmzgl8p66sGi4j9RtHHBbLcWAFh8VisdRxHJXPF/KFvOMcew5OEpARxcy+5+WCnOe35QsGIHUMgSqmta4cAQBDnGzq1jB67ipgJqMINSNUbKCKZX6wgsNisVjquOx2dHa0t7dn+UaPHSPMzDnfayu0+fmeYnsKaDXX8A9zhOAQAOJAmvP2CUmVjilOsYSW9i2WE4nNpG+xWCxNKFcoFvIFpcgQDNWjSmWGUFEhHL3kZ0k7mBV5BTdXzAVeRz6vBea4i7QSoCRmigFjCAZgJjHNDkxRJy13Tulhtj1ktDGAARuwIWZABMjaJLt7YpkXrJK1WCwWADDARKjbc3TueWfn8/7SFUu0ESjP8fKGXa3U0YfhyUMTZ4cQ8oFXLpeXLFurVfHsMzdtWN8BQM9uFTdHWzYAAMpRAJYszC1dmA88zhXyUaINu5ocA0YjQJdgsgNkkKkmqd+uR/MyAJNKkopx8vm+JUu6evoIINYMI4CG3VWxzAtWcFgsFkudvK884JKz1i1b2JuQV+xfWq5EaRxPZzloYo44DKGSGvKLzE5/d/fmdatygEvHUEhlMrtGU6usXNbf19MWtLXn27vYcbU2NJngy0xviKEsR2qaHSCTCLSTCzp7DaGvr6+3t0OALJXqtEYSi+WEYLdULBaLBcjWdgKAjX106fkbdg+MVbmYHx9XaVkReLqIj1aaAbSanPHUW75m7aK+7kvPXH3+6QsDgUuQYykVO/kMDSGQz2rD5jOf2VkZnNC10cG0OhY4xhGTEvN0WiHrNhGxGCWpITZahSmh2NXdv7StUDz/zPXtPlK7GFjmH2vhsFgsFgCAAEkMCIx86spLNq9f3d3ZtfaMDU4wTRX3t22GV6zbVOzs6+/Ifeajl/bloashH3ep2Eq5nBgdi9mwYcPC/kW5Qr7QVnRdt/Uxb5N+A4AhhnAiXDNKe7liR8+m01ecs36V1jCNNKgnxg3VYpkOWy3WYrFYAAAEIUUCiMk5tGbZooGD+0ZL0YLTlg0PDoRhWI0SctxanBiQsEPsgB0h1mBD7HhBqVJ1vGD1+s3kdyxfvuyGay4/94wVLsN1GeBZOkYcrRmygFXH8wAwUS7n1XSwb+8+xyRpVEviiF0XRLVa1XEcqqcKaxxMEDA5IAXlJnAT8vzOvnWbz+nr7rrx0x/ZvKqnnWG0duq5RngyPlYap5/h7bJY5oQVHBaLxVLHAAQiEoh0tudXLF1yYHhs/+Hh7u7uMIpjA3Z9Q44Gh4mJUglTk2hosCHH8XL9i5csX7Wms3fhgkWL/o+v3vax81a6bCYzXAgwQw6MVmYyUshkCg1avLhrbLg0MjTgev5YqTI8NpGmuq2tIEYf2YBAxIggFqqlVDWO29615oyN7cX2S87beOMnL/AFWiesKEuOKhAGTWnDCg7LCaJe/9BisVg+4BggK5miBAQBiQiPxfjVg08++tTTY+Xa6OhYuVwqlytRFMVxrJiNiOu6QRC4rrNgQb/rOIVi8awN6z73mWs2LCk4aQoYrTwBFITEzKZI/UyuImZSBRAD1Qjf+tFvHn36+VqU7N7xZmlwn4fIc2k6XxMm5YTiVKmQ716weu269ry/Yfmi/+vvv7S4A2lcTQ2CIJe1X99PmSkVhxUZluPACg6LxWIBmpGoAgJYkIahGwRgjCbYc7j2+N+ef+mllyrlyvDIsI4TAKxUWKv5vl8sFoMg0MZs3rTpvPPPueCcZe0Mx8AxIRQb8lLAlRMmOJQYU6upfPGtYf3T3z7y7CtbhkeGy4MHRwb3h+XRo9OZC3G+0BHDDXoW9S9a3NPVedFZZ3zp2qsXdUDHITPY8TMpYeqxKlZwWOYFKzgsFoulTrZWc+MPAQyguf6v0ZJs3bLl9de31CrV8fHxSqVijOnq6l6y5LSenp7169Z2d3d1t4EAA6j6kwzABsxT255Tf46AYSAp4MTEIfDAkzvv/8PDew8OKJKBA3uTWimOE2bOSqUwK1HeouWrHcf1XbV8Ue/lF55906cudBJ4LkQ0AEOsGoJjzl20WGaNFRwWi8UyDZmlwBBEkBoww2XoLPe3QGsAcBgAiMCtl/6TGUVNy09u+TlbZhYcBoAhJwZKwEgVDz7yv1u3bx89fLhWLcdxnCSJMYaZFSsoJ2jv6e5sv/Tcsz5++ca+HAIARsAkIs36cNRivrCawzIfWMFhsVgs09AUHACqUcJEUMzEgZp5Y0EwOaGSEL397PrOy3qr4ODGPTz5H9ZAAsQGPmMsxc4dB3fv3nPwwKFypVIqlQr5fEdnR6FQPP+88zo7Oro7wQZtCpVaEriOcurzf/YaaRb7JVaIWI4HKzgsFotlGloFhwbEQESI6jVf01SIyFcwgNYQI4qIqBGGQgLgXRAcAHQqUZoo1zMG7CA1CBTKEYp+fUtIDLxGTG6ciCJiRpKmruMQo2nksILDMt9YwWGxWCwz0rrky5RfANA6fbIAZFqKv5vpCsGf2CXb1ONqRAOAsBALoV5aheq9mtIJqldp00aYybTKIys4LPOMzWZrsVgsc6BFRZhWRcFTsnSadyOiQzgrtdbomQFAwgoGwjSlBsuUzgjAbANOLO82VnBYLBbL2zNzpOp7QOOkWYIuUYYgjWjb5h4OC6RVELX8FlA9AzoJT2nRYplfrOCwWCyWt8HMcPukIEtjjqZPB9U1h2mxX0jD0MGNG4bAM2Y0tVjmC+vDYbFYLG+DwcxCY3Y+DfPr+WCOdiUBkKUjbTzg3euNxTIz1sJhsVgsx0zr8v3e2D8YkFZzBR15yyoMy0mCtXBYLBbLO3B8Fg6LxQLY74vlPeQkEbvS4L3uiOU9xg4Di2VesYLD8p7RnNyTJHk3T2qMmXZdkRbm2mwYhtkNnermy2neaTkJMWZ6s8W0Y4BnOCwWy+yxWyqW95goiowxuVxuvk+UlZYol8sDAwNE1Nvb29bW1rrqtKZpmi5l09zOBYDZLkknNUmSpGm6a9eunp6e/v5+TLW6HecYsFgsR2AnRMt7hoi8+uqrO3bsSNP0XThdpVL5xS9+8dGPfnT16tUbN2688sorh4aGqIVjazYzmSRJ0qyYJSLMbNXGyYxOtU6167r/9m//tnHjxm984xszGTwsFsuJwkapWN4ziGjz5s1BEPzoRz+6/vrrp31MZpZ4m0ay8hazOd1bb711++23j4+P33bbbe3t7caYUqnU09Pz9s96x/YzsVKpVNra2p577rlvfOMbCxYs+PrXv3766afPplfzxNHdzq7d5+OqfZZWgdaP8ojuzf5DPLbHT4tylDFmYGAAQJqmzJwkiePYKdFimS/st8vyXhIEQRiGWut3figAwBgjRpSjMHWdC8OQmT3PS5IkSRJm9n2fiKrVqlKKmV3X/cMf/jA+Pn7dddd95zvf8X0/TVPXdaddLKMo8jxv2iUtiiLf97PbzWUvSZJCoQDgiSeeuPvuu13Xvfrqq08//XSd6lSn2eOz5VZEjDZZ/1vJnAay9bjpQDCT3SVr5MmnnhwbG7vooov6+/tbO6xTTUzZ02u1muM4aZrmcrmszcytJAiCZstHb6oSUalUKhaLAOI4JiLXdWda4LOnNzucGXsAuK6bbWDlglwtrBWLxcyO5Xle9vgwDHO5XK1Wyz44EanVavl8Pjtp9rDmmxyGoeu4xMTMcRwrVtl72PpxZK89u98Yc8S79/rrrz/22GOXXHLJmZvPZMXElPUhO1H2SBGJ4zhrsFwuZ++AxWI5UVirr+Wkhpl1qrPdiiRJiEg5KtvFyB6QLRVBEDiOIyKu6+bzec/zoiiK4zifzzdXna1bt/q+f+GFF2bL7dHXstlKGcexo5xs7dSpJqIoirIHlMtl3/dbXVyzhVZrLUYAXHnllf/4j//4L//yL+eeey4AbbTv+3Ech2GYpmkcxyJCTNnOS9ZCdpbslTaX7VblMa0gGBoeuv7666+77rrf//73OOqKn5m11mEY+r4vIrlcLoqirFnHcXK5HBE1GzfaJEli9JQNhewtyqSG1jqKordx9hIRMSJGjDaZ1Gu+S4VCQTnKcRydasUKDcXDzLlcTqfacZxMGqZpGgRB81WHYRjHsU61iCRJEgSBNlqMJEmStRPHsTHGdd1qtdr8RJSjyuVyphuan1qtVqvVat/4xjf++Z//+d///d9ZcZIkYoSI8vl8Ux5lbWbvmIgUCgUbtGKxnFishcNy8pLN+MpRClNMAtlamC0GTZtHtkg3/8xWr/+/vTMPiuJM//jb3dPTM6Mcg4CAEaNCZDEEwQNxNWIERSt4IIopSXRddV3UrLhWYlKlZvOjNqvZqDFuDN7yU6MmRhBjQAPiAQ4EI4egAURRXAG5x7l6+vj98WDvBBPjxrC6vzyfSqWmmj7efmeS5/s+1ytJkrJWdnNzs9lskJ1qsVjgg6OdVqlUsLYGi6VSqTqN032ro9VoOzo6INUUlu+SJLm4uNA0LUqiZJeGDBmyefNmONlqtWo0GmWxDjcBewnmDaBpmtBEFERJlpTjYMIJ+deKoIuDQa/Xu7m5NTU1aTVanueVB8ESX5IkmqJZDcvzPHhxFDcAy7I/5iVSgOSGTteFJMNEOXodHoIoiKLUKSPAzdApFwQRnk5RlDLJ8M3CtwzvDsrJ0WkBfxIFEZ5Oy52yTK1Sg1bQ6XSg3mRZttlsPXv2NJvN4CmBWeU4ThRFd3d30F7wvdjtdvhR9ejRg2EYuFXPnj0hqoLpogjSHaDgQJ5GwKKDsDCbzQaD4euvv25ra+vRo8fIkSMjIyOdnZ3hTIqiZCJfv369wFBw8duLd+7c0el04eHhEydO9PHxgXN27959+vTpb775RqPRpKWllZeXUxQVFxcXFRXlmCCiuNN37NhRVlY2bdq0iIgIhmEYhiGElJSUHDhwwNvbe8GCBVqNltAEwiinT5/+9NNPo6KiZsyYUVFRsWPHDi8vr7lz57q5uRFC1Gq10Wg0GAzZ2dktLS3PPvvspEmTQkJCurxvzumcrKysxsZGd3f3UaNGRUZGurq6kvvVLmCGFTfGhx9++M0331y7do0Q8tGWjwoKC27W3pw7b25UVBRFUevfX9/Y2Lhx48aGhoaPPvqovr5+3Lhxc+bMIffVWGZW5tmzZ1tbW93c3MLDw8eNG+fs7OyoPBgV09ra+tlnnxUVFUmS1Ldv3+jo6LCwMOWEh6RQpP5v6tWrV1taWlxcXODdrVZrYGDg4sWLVSpV3rm8L75SsczNAAAXb0lEQVT4Aib2wIEDBoPB29s7ISHB19cXPBYXL140GAy3bt0ihAwaNGjkyJEBAQFarRaCRPv3709PT3/11Vejo6NpmoZgWVtb2xtvvBEQELBo0SIIgmi1Wp7nz58/f+zYsejoaJvNlp6efvbsWYqisrOz16xZU1dXFxIS8vrrr7MqVhAEURT1ej0hpLCw8NixY21tbYMGDZo4ceJzzz338JdFEOTfQ0aQJwf4IQ4dOtTluGAX4EN1dfWkSZO6FM3Gx8fX1tYqrv6dO3f6+fl1KQwZPHjwqVOn4Cbz58+HgyBiCCEcx23cuFEURceHQoGJJElLly4lhERERCjHBbuwefNmlmXVanVRUZEsy1arFZ4+duxYmqb/+te/yrKcnp5OCAkMDLxx4wZce/v27dmzZ4MhBDXj7u5+5MgR+KvJZIITFOcBaKzo6Oja2lplSMowgMjISHgLuAp8A++99x6c5uvryzDM3/72t6FDh8JDBw4c2NTUxPP8d999FxcXpzwL4hpTpky5deuWJEnKbBw9ejQwMJAQAkqLEKLRaJYsWQJfislk+sGv0mAwwFVwIXyz8EYxMTHt7e2iKCYnJxNCxo0bt3jxYvgTy7IwG/X19UuWLIGx9ezZU6PRMAyjVqsTExPNZrPZbBbswqpVq1iWnTRpksVike/HTY4dO6ZWq2mazsjIgFkC7TJixAhCSHJy8pYtWyCcBPPv5ORECImdHnvnzh1ZlhctWkQIWbt27YoVKziOY5hO/9OAAQPS0tLghvA4BEEeExQcyJME8gkOHjzoeFCwC2D8WltbX3zxRbVaPWfOHFjTX7hwYcKECRRFLV68WDGQI0eO9PT03LZtW3FxcVVVVUFBQXx8PCFk6tSpsizzPF9fX19ZWRkfH6/RaN56660bN27U1taazeYug4FkC1mWDQYDIcTHx6ejo0N5ysqVKymKYhhm27ZtkCEhy/Ldu3dpmnZxcSkuLpZl+ezZs2q1OiQkpK6uDq5KTk6maToyMrKgoKC2tjYrK8vf33/JkiVgtiVJmjlzJkVRsdNjDQbDjRs3ioqKfv/73xNCoqOjFdUFKIKjra0tJyfH19cXdMatW7dKS0sbGhrgNBAcIERSUlKOHj26Z88eWZYtFsvUqVMJIbNnz7548WJFRUVeXh5ondjpsYJdMBqNZrO5qKjIx8eHoqhVq1bdvHmzqqoqLS1t8ODBhJB169YpMssRURRFUQwKClKr1StXrjQYDJWVlXv27Bk4cCAhJDU11WazwWy///77ikJKSEhIT0/fvn17eXk5z/MgQTiOe//993Nzc7/66qukpCRQLWvWrIFv4dKlSx4eHhzH1dTU8DxvNpttNtu6desIIc7OzqtWrYLTzGZze3s7+LdAt5WWlr722muEkEmTJrW0tJSWll65cgXE3IIFCwghvXr14jhu1qxZmZmZBw8eDAsLYxgmKirq7t27soP8RRDkcUDBgTxJflBwKAvKlJQUhmEmTJjA8zz8T1+wC7dv3/b392cYJisri+d5URS//fbbLgLi22+/1el0oaGhFRUVJpMJrk1MTOQ4bsuWLZC8+YMIdgH+8fDw0Ol02dnZ4EcxmUxK/CUuLk55Vnp6OsdxY8eOBQFx8uRJQshvf/vbxsZGOGHatGmEkIyMDMVoNTQ0VFVVwefPP/+cpumXXnqpsbERRiWKYltb29ixYymK+vTAp3CayWSSHJBlub293c/PjxCya9cuRZ8BIDi8vLwUBw/P8zzPp6amajSamJgYwS4oQspqtT7zzDOEEDjZZrMtX76cZdl3331XeUeIdLi4uPTt27epqcnR6aJMWkVFBSGkb9++oijC42RZfuutt0BAyPdFyT/+8Q9we6xevVq+b8gtFkt2drZWq9VoNBkZGXAH+OvOnTsZhnF2dj5//jyMNjw8nBBy4sQJGFhTUxP4e2iajomJgbEJduHEiRM0TY8aNYrneYvFIknSsmXLCCEzZ84EpSjf9x4lJSWBBnrnnXeUaczLy+vdu7erq2tubq4syw9qUwRBfgZYpYI8STrTP6XvpS4qPv+tW7eCqWBZFpIcGRXj4eExdepUURRramoIIaIovhD0gq+vL1Q9wIWQANHW1kZRlEajgcIWQojNZjMajfDT7zISWZbtdjtFU5IsMSomPj7ebDYfPXqUpmmGZgoLC0+dOuXn5+fu7p6ZmXn79m24KiMjQ5KkuLg4qJEBhzzUv8iyLAqil5cXRVGHDh3i7Txc4uHhAVqBEJKamirL8sIFCz08PGDdL4qii4sLdCUpu1xGCLHb7Zyacxyq3W5vamqCp/xYk5I33njjpZdegs8sy7Is++WXX8qyPHfuXEbFODk5KaGlWbNmEUIKCgpkWb579+6ZM2fsdvucOXOUXFGKokJCQgYMGNDQ0FBeXk4IUeYZYFQMdLOA/FmYAZ7noTqmo6NDGScUpAQFBa1atUqSJMjMgMQanucTEhImT54MJTY8z0uyNH78+KCgIJPJVFhYKMsyx3FjxoxhWTYtLQ1KllpbW/Pz83v06OHj41NYWHjp0iUYT1ZWFniPIAoGpSvwpajVaoiSQPoqHJ83b97atWtpmrZYLDzPQ2qL0WiERJn/QBtcBPk1gEmjyFOBowKw2+0cx7W1tYGtWrNmzebNm2GV6ebm1tzcXF5ertFo2tvbO420IP7zn/88ffp0QUHB5cuXwScBHTjgbjRN0xRtMpkIIRARgNpXQ4Fh5cqVYCMZhrl3715sbGxiYiLLsi+//PKWLVuysrIIIWaLubKykhCSmJhYXl6+ffv2uro6Pz8/i8Vy4sQJu90+evRoqNVkWRbKX+FFKJr6wx/+kJGRsW/fvlOnTq1YsSI+Pt7DwwMM2L179+rr62VZ/p/k/9n6yVZCCPSeIoRARMZisUBdKMV8L2mRZVmop4C3UzpPOBbThoWFyZIsU7IsyzRN19XV3bx5U5Kkv//97ykpKSaTSRRFqPzMz88HG0xR1KVLl6qrqxmGeeWVVzw8PCDIAnN+5coVnueNRuODfUSMRmNoaKiXl1dVVdXXX38dGRkpiVJ1dfWRI0ecnJyGDh0KY6NpGqpzhw0bplSRiJLI2/nKykpRFMeOHStLMqGJJEkQTPHy8goJCSkuLm5ubgaFNH78+A8++CA9PX3dunXOzs7FxcVWq3X58uUWi2Xr1q2XLl2CguS8vDy1Wh0WFibLsiAIkN7rCE3TUMEEPWD69esHg4R6YLvd7uTkBF6ZB1t6IAjy80DBgTxJIItTkqUuByVJslqtsDC9cuWKq6tra2sr2CGQESqVCmIBhJC8/Lx58+Zdv34dii2V3hvq+zimWEKCoSRJjIoxmUwFBQWq+wiC8MILL4AFCg0NVavVtbW1JSUlwcHBBQUFDMNMmzYNjPqZM2fGjB5z48aNO3fuhISEQIqDI7Isg5UKej7o8OHD69evz8nJefPNN1evXr106dI333zT09PTZrMJgsBxXHV1dUtLS2trK5SS6nQ6URQZhnF3d2dUDCVRoig+ZgdMyLskhBQXF/fq1aulpYXjOKPR6ObmRlFUr1699Ho95FoajUZCSFlZGXgpwK8AZa7PPPOMm5vbg13LoE54+PDhGRkZkydP9vLycnFxqampMZvN8fHxUFECZhtCQmDFCSGiJKrVarvZbrfb1Wq1TqeDml6NRgMncBzn4+MDpSgwpZGRkUFBQcXFxbW1tcHBwbm5uT169Jg5c2ZdXV1KSkphYeH8+fNLS0uvXbs2YMCAgICAR5kcFBMI8p8BBQfy1AGLco7jYGGalpYWOT4SukxC706aps1ms5OTEzR3WrFiRV1dXez02L+8+5fnnntOrVZfvXo1PDxcCRwqfSTh3xD4kCRpwoQJFotFxajAiNrtdpZlwT/h4eHxyiuv7N27Ny8vLzg42GAwDBo0qF+/fhERETqd7rPPPluzZk1+fr4syzNmzKCph4Umhw8fnpaWVlVVdfz48XXr1m3atKmpqWnv3r2wyrfZbIcPH545cyZx8FKA3oITKIqiKVp+vOJMrVYLbhXHLvLwvvDZbDar1WqGYXr27MmybH5+vr+fv6ItYGBmsxkqTmWHxh5AcXFxfn7+yJEjhwwZkp2dbbVaw8LC5s6dO2vWLBWjIoQIggDdvQghoigqHwghHMep1WpBEG7fvg2NSqFbGlRE37p1i2VZqDEGsRIcHFxeXl5YWBgcHJydnc0wTGhoqJubmyzLZWVlFEUVFRWZzeaFCxfq9foHY2cIgjwpMIcDeZJAul8XqwB2SK/XQ7lEe3s7qA1CCKNioHbRxcWFEMJxXH5+fmlpqV6vP/DpAX9/fwht9OrVy2g0dvGEw2flCDTJFkVREAWl7ycsteEz+DPKysoqKysrKioiIiIIIQEBAUOGDKmtrW1ubj516hQhZOLEiQ8u+hUYVWeZpb+/f1JSUlpamiRJeXl5165doyjK29ub4zjIGBUFUUnIoGlap9PBQWiu+phbwfXu3Rt2QwU/BzgzyP2teu12O4gbb29vT09PSNplVIwSGwIXBZyjVqu7qA1CyIULF5qbm6dPn75p06bKysrLly/n5OTMnj2b4zhREmFWwY1ECGEYRqVSMTQDHbc4jnN3d5ckqaysTJY6pQy0R2tubs7NzZUkafDgwfBTYVl2ypQpFEUZDIb6+vqrV68GBwczNNO/f/+YmJgLFy5cuXLl+vXrgiCMHj36X7Et9GEgyFMACg7kSSIIgiRJPj4+jpnMSguHyMhIWZY//vjj9vZ2x808aZquqamBWDtYYpZlrVYr2GZCSPbX2dDGW7kEYvmEEI7jlFwHlmW1Wi0IAkmSwCIq6aWjRo3q0aPHuXPndu3apdVqIReBYZihQ4dSFLV3796jR496enqGhobabDZJ7gwZyLIsiiKoKGj5BdknMH4nJycozCGEaLXacePGybK8efPmxsZGyKBUuHnzJkifH9zFtGfPnsOGDYNxQp4HvJTNZgO5Bj3FjUZjp1tIEMLDwwVB2LFjR2trq0qlgrwWmI2ysjLICAkNDY2IiLDZbCkpKYQQmGFCiCiI9+7du3XrFvQf61KoAoNkGGbnzp25ubmHDh1KS0vLysq6fPnynTt3RFFU/ChWqxWyOGmaZlQMQzPgHIJanoMHDx7/8jhkpEKU7eOPP66vr3/++ecjIiLsdjs4tMaPH+/q6rpr166tW7eyLJuQkGDjbSzLRkREcBy3a9euc+fOubq6Pvvss9B5DB4dGBio0WhsNpvdbu8yJPhtwLxRFAUN12Ha7927p/RuQRDkMcGQCvLEAJe+zWY7cOAANJcETCbTiBEjQkNDExMTs7Kyzpw5M2PGjNdffx3W6CUlJbm5uXfv3t20aVNQUNDw4cP79u1bU1OzdOnS3/3udwzDfP7556mpqeR+hQXYfugxpXhTusRZugB21MXFZdy4cVlZWRs2bPD39x8zZgzEBSIjI1NSUpKTk3mef/XVV2HvMYvFQgjp6OhQnggFmZMnTx40aFBSUpKnp2dLS8vu3bt5ng8ODh44cCDP8/Pnz79w4cKRI0emT5++bNkyX19flmWrq6u/+uqr5ubm5OTkESNGgC3sksPBsqy3t7dWq92yZYter6+oqAgKCpo1axYkZkLogdwvr2BUjE6lmz9//rFjx86dOxcTE5OYmNinTx+NRnP16tVj6cdqb9ampaV5enpSFDV37tyMjIwPP/zw7t27r732mqenJ8/zJSUln3zyiYeHR2ZmJmylpohCYMyYMQEBAdeuXYuJiXHcnWTw4MHLly+fPXs2RVHgGpEkSdnlhGZonucZFTNx4sQFCxbs2LEjNjb2T3/605AhQ2w2W0ZGxvHjx9VqdVJSUu/eve12O0RndDpdVFTU/v37169fr1KpRo8erdPpbDbb4MGDaZreuXNna2vrsmXLPD09CSGwLbAsyzDhp06dWrdunaurK8MwsbGxXl5eELYD3wn0XKcZGjZ8oSgKJrDLFnEIgvxMHq16FkF+eXieV3aH5xwghMyZMwfsRGlpKXTxgi3ZlLXmn//8Z6XlZWpqKvS4hNUzx3FJSUmjRo3iOK6qqkrpbwENtdauXftg+06lHqEL27dvh8dFRUUp51ut1n79+hFC1Gp1bm6u0WiEjeJkWYat1Pr161dTUwP9Sd9++20wvYrFip0eW1ZWBkOSZfm7775LSEgg3y9w5Thu0aJF0HVKaRGmAI8zGAwBAQHKhKxevRreQq/X0zSdmZkpiiIUeSrPunjxIth+GBKk3+p0ukWLFrW3t8ML2my248ePR0ZGwm2VOdfr9dA8A8p8uvQFkWU5JiZGp9Nt2LDh4MGDBw8e3LBhQ0JCAiTtHj58GPp0vfvuu4SQl19+WekConwR1dXVf/zjHzUaDdh4mI3AwMBdu3Ypr6D0Mtm/fz/HcSzLDh06VLlDY2MjhL1Ylk1PT5fv9/mAy1taWuLj4yFPhRAyYcIEaJUGDcGWLl1qtVqhZBrOj4uLI4R88MEHgl14SOMWBEEenc4dsBDkiZCZmVleXg7ZiMpBs9kcFhbmuNHJyZMnL1++DNuX9+nTp2/fvuHh4ZIkCYIA0YGGhoazZ89WVlbSNB0dHR0YGFhSUpKfnz99+nRfX18IDRQWFmZnZ8fGxj7//PPKs+Tv766uHAfXeoexY9u2bWazOTIycsyYMVarFdpyZBzPKCkpcXd3X7JkCQwD7tDR0bFv3z43N7eEOQmQAyGK4o0bN/Ly8qBzxm9+85voidFKzgfsDCdJksFgKC4uNpvNNE3379+/f//+I0aMuHfvHhjsLv+RwsbuhJCampqTJ0+aTCZnZ+cpU6a493I3W8xffPFFfX39vHnzevfurWwur7yj1Wo1GAwXL15sbm52cXHx9fX18/MbNmyYzWZTqVSwyoedWi9cuFBdXd3R0aHRaEJCQgIDA3v37s2yLPilHIdEUdSmTZtWrFjx9ttv/+Wdv4iSSAiBHeTfe++91atXx8XF7d69W6vVFhUVZWdnBwQExMTEQKwHWqTAbEty5zyABBw0aFBYWJjeVc+oGNhTDb5ucLGkpKR0dHSMHTv2xRdfJPe9ZTk5OcePHw8KCoK9Y+C3oezlZjab9+3b19DQ4OrqOmzYMOghlpeXl5OTA/dRpkuSpC+//DIvL2/hwoXQLxVBkMcHBQfylCI/tC7jcX63jrf9d+8jiRLNdM18gr3dHzze5f4/9jqPcs6j8GMz9pP3hAHAq8my7NiHzTGz5MfuQ1FUnz59GhoaKioqBg4YaBc6E29pmt69e/fChQsXLVq0ceNGFaNyvJuSSaPc+cfmQTkO80wIoRkaskmUPz1kbA9/cczPQJD/GJg0ijylPJ2W4AdVBc3QP3ic3G+l+vDOUY9yzqPwuJfTncsPiqaUfx7lQp7nWZYVRTEtLY1maI1GA22+bt68uWfPHqgxgfQLRzpdrA5v/ZPzAPNM0ZQkSpAqq1z1M1/5qfyNIcj/V9DDgfxX8qQ8HP+NPKKH4yen4iFehI0bN65YsYIQMmzYsMDAQG9v75qamszMTKPROGHChH379rnp3brIly5Vyj85vAcPPsq1KCkQ5OkBBQfyXwkKjkenuwUHtNnYt2/fjh07zp8/zzAMbKQycODAefPmLViwwNnZ+cGbP6bgeERQcCDI0wMKDgRBfjHhdefOHeWzXq9Xs2rIkFUCKF3OR0GAIL8eUHAgCPK4guMhugF2USE/EgRBwYEgvx5QcCAI8gt4OBzvAHUuFP3T6ZwoOBDk1wN2GkUQ5Bfge11MGJQRCIJ0BT0cCIIgCIJ0O9iHA0EQBEGQbgcFB4IgCIIg3Q4KDgRBEARBuh0UHAiCIAiCdDsoOBAEQRAE6XZQcCAIgiAI0u2g4EAQBEEQpNtBwYEgCIIgSLeDggNBEARBkG4HBQeCIAiCIN0OCg4EQRAEQbodFBwIgiAIgnQ7KDgQBEEQBOl2UHAgCIIgCNLtoOBAEARBEKTbQcGBIAiCIEi3g4IDQRAEQZBuBwUHgiAIgiDdzv8BBO7pJGZd5ZQAAAAASUVORK5CYII="},"81b89d32-ead8-4e94-a700-2940fa417c90.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## **Forecast and prediction**\n\n**The software engineering challenge:**\n\n> *Every Kaggle challenge represents challengs regarding to put the proper amount of data and submit that to a specific model but taking in account the fact that is necessary to avoid that the notebook runs out of memory or out of CPU capabilities. When the competitos decides to use GPU it will sacrifice some of CPU availability*\n> \n> *There are some very usefull techinics to help to set all needed processing to make it possible, techniques like the following:*\n\n> For memory optimization we have:\n> * memory profiler usage\n> * line profiler usage\n\n> For speed up processing we have:\n> * Cython\n> * GPU\n\n**The machine learning challenge:**\n\n> *The machine learn approach has the aim to learn how to map Y = f(X) to make predictions of Y for new X. That's predictive modeling (aka predictive analytics) and the goal of a data scientist is to make the most accurate predictions possible. We have data and ML techniques that will be used to train models. Regarding to data the challenge is to  choose of the best algorithms to filter data, denoise data, augment data, cluster data in time or category; regarding to Machile Learning techniques we have a lots of models provided by tird part frameworks like Pythorch, Tensorflow, Hugginface and others. For example, the Long Short-term Memory (LSTM) method is a popular deep learning algorithm used for stock price prediction.The challenge is to pick the proper ML model and select the model that will fit to the choosen data baseline*\n\n\n## The **American Express - Default Prediction** Competition\n\n**The goal:**\n\n*By helping American Express to predict when a customer will represent a risk of default payment, the challenged competitor will help create a better customer experience for cardholders by making it easier to be approved for a credit card.* \n\n**The Machine Learning approach:**\n\n*Picked 3 samples from the top 10 (from undisclosed solutions) I detected the unanimous use of LGB model with some specific technics applyed:*\n\n* The 1st place used  LGBM and NN\n\n* The 2nd place used LGBM with DART\n\n* The 3rd place competitor also used LGBM\n\n*So, best scores in this competition used LGB with denoise and FE (finit element) technics for data preparation.*\n\n[American Express - Default Prediction](https://www.kaggle.com/competitions/amex-default-prediction/overview)\n\n\n## the **JPX Tokyo Stock Exchange Prediction** Competition\n**The goal:**\n\n*This competition was about to compare the developed models against real future returns after the training phase get completed. The competition did involved building portfolios from the stocks eligible for predictions (around 2,000 stocks). Specifically, each participant ranked stocks from highest to lowest expected returns and is evaluated on the difference in returns between the top and bottom 200 stocks.* \n\n**The Machine Learning approach:**\n*Picked 2 samples from the top 10 (from undisclosed solutions) I detected the unanimous use of LGBM model with some specific technics applyed:*\n\n* The 8th place used  LGBM and tunned parameters: num_leaves, max_depth, learning_rate and n_estimators. They also divided stocks and grouped in 33 groups for training that separately.\n\n* The 10th place used LGBM with walking forward cross validation.\n\n*I'm disconsidering the 4th place (they called theirselfs as a \"luck model\" and I got no paramenters to analise that) So, best scores in this competition used LGBm with some specific technique (grouping, cross validation) for data preparation.*\n\n[JPX Tokyo Stock Exchange Prediction](https://www.kaggle.com/competitions/jpx-tokyo-stock-exchange-prediction/overview)\n\n\n## the **G-Research Crypto Forecasting** Competition\n\n**The goal:**\n\n*This competition was about to use a machine learning model to forecast short term returns in 14 popular cryptocurrencies.*\n\n**The Machine Learning approach: **\n\n*Picked 2 samples from the top 10 (from undisclosed solutions) I detected the unanimous use of LGBM model with some specific technics applyed:*\n\n* The 2nd place used LGBM with cross validation.\n* The 3rd place used LGBM with cross validation.\n* The 9th place grouped data from 3 market places and used LGBM to build 3 different models.\n\n*I'm considering this three models and avoiding to comment exotic solutions (even if they are well succeded). These models was disclosed for competitors and delivers similar solutions along the competitions that I'm considering to discuss here.*\n\n[G-Research Crypto Forecasting](https://www.kaggle.com/competitions/g-research-crypto-forecasting)","metadata":{}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.020941Z","iopub.execute_input":"2023-07-05T23:43:30.021318Z","iopub.status.idle":"2023-07-05T23:43:30.056078Z","shell.execute_reply.started":"2023-07-05T23:43:30.021291Z","shell.execute_reply":"2023-07-05T23:43:30.054965Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# What we learned from this sample of 3 competions at Kaggle platform:\n\n* These three competiotions has the same study subject: forecast and prediction at marketplace.\n\n* LGBM has been unanimity, with great results, according to this three competitions that I analysed here\n","metadata":{}},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport numpy as np","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.057419Z","iopub.execute_input":"2023-07-05T23:43:30.058131Z","iopub.status.idle":"2023-07-05T23:43:30.062516Z","shell.execute_reply.started":"2023-07-05T23:43:30.058103Z","shell.execute_reply":"2023-07-05T23:43:30.060988Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\nperf_vals =    [0.999979, 0.999958, 0.999938, 0.996064, 0.995081, 0.998972, 0.998458,  0.995375]\nrank_vals =    [1, 2, 3, 8,10,2,3,9]\ntotal_vals=    [4874, 4874, 4874, 2033, 2033, 1946,1946,1946]\ncompetitions = ['AMEX','AMEX','AMEX', 'JPX','JPX', 'G-Research', 'G-Research', 'G-Research']\ndata = {'ranking': rank_vals, 'total': total_vals,\n        'performance': perf_vals, 'competition': competitions}\ndf_competition_data = pd.DataFrame.from_dict(data)\n\n\ndf_competition_data\n","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.063654Z","iopub.execute_input":"2023-07-05T23:43:30.063981Z","iopub.status.idle":"2023-07-05T23:43:30.113168Z","shell.execute_reply.started":"2023-07-05T23:43:30.063954Z","shell.execute_reply":"2023-07-05T23:43:30.112134Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Particular techniques used for competitors with LGBM in percentage.\n\nFrom this sample of 8 results, 2 was using grouping of data (by feature), 3 was using cross validation, and 1 was using DART.\n\n> **25,0 %** using grouping of data (by feature)\n\n> **37,5 %** using CV\n\n> **12,5 %** using DART","metadata":{}},{"cell_type":"code","source":"y = np.array([25, 37.5, 12.5])\nlabels = ['Grouping', 'Using CV', 'Using DART']\n\nfig, ax = plt.subplots()\nax.pie(y, labels=labels)\nax.set_title('LGBM features in competitions - from collected sample')\nplt.tight_layout()","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.115403Z","iopub.execute_input":"2023-07-05T23:43:30.116342Z","iopub.status.idle":"2023-07-05T23:43:30.282975Z","shell.execute_reply.started":"2023-07-05T23:43:30.116307Z","shell.execute_reply":"2023-07-05T23:43:30.282161Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Lessons from Kaggle:\n> The usage of LGBM has been unanimity in Kaggle's competition for this category (forecast and predictions over time series) however we have seen exotic models (they called theirselfs as 'luck models') achieve best scores in competiotions too.\n\n> The usage of cross validation, DART, grouping data to create multiple models can help to improve accuracy for trained models.\n> The fine tunning of paramentes can help to reach the best scores (regarding to accuracy of the model).\n\n> We encourage competitors to optimize memory usage and to make use of techniques for speed up the processing for the training of the models because competitions has memory limitation and time constraints.","metadata":{}},{"cell_type":"code","source":"%%writefile submission.csv\ntype,value\nessay_category,'Tabular and/or time series data'\nessay_url,'https://www.kaggle.com/code/barbosajaf/jafb-2023-kaggle-ai-report'\nfeedback1_url,'https://www.kaggle.com/code/preethiraghuraman/ai-report-2023-information-retrieval/notebook' # AI REPORT 2023: Information Retrieval\nfeedback2_url,'https://www.kaggle.com/code/johnlangenderfer/ethics-ai' # Ethics_AI\nfeedback3_url,'https://www.kaggle.com/code/umesalma/evolution-of-knowledge-insights-gained-from-kaggel'\n","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.284014Z","iopub.execute_input":"2023-07-05T23:43:30.284599Z","iopub.status.idle":"2023-07-05T23:43:30.291103Z","shell.execute_reply.started":"2023-07-05T23:43:30.284569Z","shell.execute_reply":"2023-07-05T23:43:30.290253Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sub = pd.read_csv('submission.csv')\nsub","metadata":{"execution":{"iopub.status.busy":"2023-07-05T23:43:30.292237Z","iopub.execute_input":"2023-07-05T23:43:30.292835Z","iopub.status.idle":"2023-07-05T23:43:30.315897Z","shell.execute_reply.started":"2023-07-05T23:43:30.292785Z","shell.execute_reply":"2023-07-05T23:43:30.315174Z"},"trusted":true},"execution_count":null,"outputs":[]}]}