youtube (2).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Fine Tuned Youtube Search"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### This notebook uses the code and content in this article - https://www.pinecone.io/learn/openai-whisper/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Architectural Overview"
   ]
  },
  {
   "attachments": {
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     "image/png": 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ceeKJJzxmoccTfvLJJx6LT2AEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBMwmQLKV2XaM+fq0wNKlS2X27NnSrFkziYiI8Om5MjkEEEAAAQQQQAAB8wtERUVJZGSk2xZSrFgxOXbsWGK8nDlzytatW6VMmTJuG4NACCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgiYWYBkKzPvHnP3OYGqVavKzp07jXnpm17Dhg3zuTkyIQQQQAABBBBAAAH/EdCqVlrdyl0td+7ccuHCBYtwb731lowYMcJdQxAHAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAFTC5BsZertY/K+JLBkyRJp06ZN4pRatGghK1as8KUpMhcEEEAAAQQQQAABPxOoUqWK7Nq1y6OrKlKkiFHdqkCBAh4dh+AIIIAAAggggAACCCCAAAIIIIAAAggggAACCJhBgGQrM+wSc/RpgZiYGPnll1/kxo0b8tJLLyXO9ZFHHpGFCxf69NyZHAIIIIAAAggggIA5BaKjo2XTpk0yaNAgty+gcuXKVglcI0eOlMGDB7t9LAIigAACCCCAAAIIIIAAAggggAACCCCAAAIIIGA2AZKtzLZjzNenBCZPnix9+vQx5hQSEiLXr19PnF/nzp1l1qxZPjVfJoMAAggggAACCCBgfgF3Hx2YXKR69eqyY8cOi38uX768bN++3fiZl4YAAggggAACCCCAAAIIIIAAAggggAACCCCAQCALkGwVyLvP2l0WaN68uWhVAVutR48e8uWXX7o8BgEQQAABBBBAAAEEEEgQ0CSoGjVqpAvIhAkTpF+/fukyNoMigAACCCCAAAIIIIAAAggggAACCCCAAAIIIOArAiRb+cpOMA9TCjz88MOydOlSm3PXIwXHjx9vynUxaQQQQAABBBBAAAHfFahbt678/vvvXp9gzZo1pVevXtK3b1+vj82ACCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgj4igDJVr6yE8zDlAKdOnWSuXPn2pz74MGDZeTIkaZcF5NGAAEEEEAAAQQQ8F2B3377TRo3bpxuE6xTp45s2rQp3cZnYAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE0lOAZKv01Gds0wt069ZNZsyYYXMd7777rgwdOtT0a2QBCCCAAAIIIIAAAr4lEBcXJ61atUrxOGtvzHb79u1SvXp1bwzFGAgggAACCCCAAAIIIIAAAggggAACCCCAAAII+JQAyVY+tR1MxmwCffr0kcmTJ9uc9qhRo+T1118325KYLwIIIIAAAggggIAJBPbt2yf33nuvXTPNnz+/FChQQHbu3GnVP0+ePKLJW1evXrUrlnaqV6+ebNiwwe7+dEQAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwJ8ESLbyp91kLV4X6N+/v4wbN87muJ9++qm8+OKLXp8TAyKAAAIIIIAAAggEhkBMTIwsX75cYmNjJUeOHMYjZ86cxkdNrtIkK30ktKCgICsYvb5ly5Zy8OBB2bt3r+zZsyfx41NPPSXNmzeX48ePy4kTJ4yPZcuWlfDwcAkNDQ0MZFaJAAIIIIAAAggggAACCCCAAAIIIIAAAggggEAyAZKteEog4ILAkCFDZOTIkTYjfPnll9KjRw8XonMpAggggAACCCCAAALuE7CVbLVq1SojecpWO3XqlBQsWNB9EyASAggggAACCCCAAAIIIIAAAggggAACCCCAAAJ+IECylR9sIktIP4Hhw4fLO++8Y3MCM2fOlC5duqTf5BgZAQQQQAABBBBAAIEkAo4mW4GHAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC1gIkW/GsQMAFgY8//ljeeOMNmxHmzZsn7du3dyE6lyKAAAIIIIAAAggg4D4Bkq3cZ0kkBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgcAVINkqcPeelbtBYOLEifLiiy/ajPTTTz/Jgw8+6IZRCIEAAggggAACCCCAgOsCJFu5bkgEBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRItuI5gIALAtOmTZMePXrYjLB69Wpp2rSpC9G5FAEEEEAAAQQQQAAB9wlkypRJbt26ZRFw1apVEh4e7r5BiIQAAggggAACCCCAAAIIIIAAAggggAACCCCAgJ8LkGzl5xvM8jwr8P3330vnzp1tDrJx40apW7euZydAdAQQQAABBBBAAAEE7BTIli2bXLt2zaI3yVZ24tENAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIF/BUi24qmAgAsCCxculHbt2tmMsH37dqlevboL0bkUAQQQQAABBBBAAAH3CYSGhkpsbKxFQJKt3OdLJAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIHAECDZKjD2mVV6SOCXX36Rli1b2oy+d+9eqVChgodGJiwCCCCAAAIIIIAAAo4J5M+fX86ePWtxEclWjhnSGwEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABkq14DiDggsCaNWukWbNmNiMcPnxYSpQo4UJ0LkUAAQQQQAABBBBAwH0CRYoUkRMnTlgEJNnKfb5EQgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEAgMAZKtAmOfWaWHBNavXy8NGza0Gf3UqVNSoEABD41MWAQQQAABBBBAAAEEHBMoWbKkHDlyxOIikq0cM6Q3AggggAACCCCAAAIIIIAAAggggAACCCCAAAIkW/EcQMAFgd9//13q1q1rM0JsbKzkzJnThehcigACCCCAAAIIIICA+wTKlSsnBw8etAhIspX7fImEAAIIIIAAAggggAAC/iUQHR0t4eHh/rUoVoMAAggggAACCCDgFgGSrdzCSJBAFdi6davUqlXL5vLj4uIkU6ZMgUrDuhFAAAEEEEAAAQR8TKBSpUqyZ88ei1mRbOVjm8R0EEAAAQQQQAABBBBAIN0F9u3bJx07dpSdO3fK448/LrNnz073OTEBBBBAAAEEEEAAAd8SINnKt/aD2ZhM4M8//5Tq1atbzTpDhgxy584dk62G6SKAAAIIIIAAAgj4s4D+3Ko/vyZta9eulUaNGvnzslkbAggggAACCCCAAAIIIOCQwOTJk6VPnz6J10ybNk0iIiIcikFnBBBAAAEEEEAAAf8WINnKv/eX1XlYQCsDaIWA5C1Llixy/fp1D49OeAQQQAABBBBAAAEE7BeoXbu2/PHHHxYXbNy4McVjse2PTE8EEEAAAQQQQAABBBBAwNwCL774osyZM0fq168v7dq1k169eiUuaPTo0fLqq6+ae4HMHgEEEEAAAQQQQMCtAiRbuZWTYIEmcODAASlfvrzVsnPlyiUXL14MNA7WiwACCCCAAAIIIODDAvqmgSZXJW2afFWzZk0fnjVTQwABBBBAAAEEEEAAAQQ8K3D8+HEpWrRo4iDDhw+XoUOHJv6dylae9Sc6AggggAACCCBgRgGSrcy4a8zZZwRiYmKkdOnSVvMpUKCAnDp1ymfmyUQQQAABBBBAAAEEEGjSpInosYFJmx4rWLVqVXAQQAABBBBAAAEEEEAAgYAViI6OlubNmyeuv2DBghav7y9cuFAeeeSRgPVh4QgggAACCCCAAALWAiRb8axAwAWBY8eOSfHixa0i6L8dOXLEhchcigACCCCAAAIIIICAewVatGghq1atsgiqx2Lfe++97h2IaAgggAACCCCAAAIIIICAiQSSJ1sln7r+HhUeHm6iFTFVBBBAAAEEEEAAAU8LkGzlaWHi+7WAVq8qVKiQ1RrLli0resQgDQEEEEAAAQQQQAABXxF48MEH5eeff7aYzsGDB6VMmTK+MkXmgQACCCCAAAIIIIAAAgh4XYBkK6+TMyACCCCAAAIIIGB6AZKtTL+FLCA9Bc6dOyf58uWzmkLlypVl586d6Tk1xkYAAQQQQAABBBBAwEKgTZs2smTJEot/02qstiq1QocAAggggAACCCCAAAIIBIoAyVaBstOsEwEEEEAAAQQQcJ8AyVbusyRSAArExsZKaGio1cpr1qwpf/zxRwCKsGQEEEAAAQQQQAABXxVo166dLFy40GJ6J06csFmp1VfXwLwQQAABBBBAAAEEEEAAAXcLkGzlblHiIYAAAggggAAC/i9AspX/7zEr9KDA1atXJXv27FYj1KtXTzZs2ODBkQmNAAIIIIAAAggggIBjAp06dZK5c+daXHT27FnJmzevY4HojQACCCCAAAIIIIAAAgj4kQDJVn60mSwFAQQQQAABBBDwkgDJVl6CZhj/FLh586ZkzpzZanFNmzaV1atX++eiWRUCCCCAAAIIIICAKQU6d+4s33//vcXctVJrzpw5TbkeJo0AAggggAACCCCAAAIIuEMgrWSrNWvWSJMmTdwxFDEQQAABBBBAAAEE/ESAZCs/2UiWkT4Cd+/eleDgYKvBW7duLUuWLEmfSTEqAggggAACCCCAAAI2BLp16yYzZsyw+My1a9ckJCQELwQQQAABBBBAAAEEEEAgYAXSSrbavHmz1K5dO2B9WDgCCCCAAAIIIICAtQDJVjwrEHBRQJOtNOkqadMjWubMmeNiZC5HAAEEEEAAAQQQQMB9At27d5fp06dbBLx165ZkzJjRfYMQCQEEEEAAAQQQQAABBBAwmUBayVa7du2SSpUqmWxVTBcBBBBAAAEEEEDAkwIkW3lSl9gBIaDHCOpxgklbRESETJs2LSDWzyIRQAABBBBAAAEEzCHQu3dvmTJlSuJkg4KCrG4aMMdKmCUCCCCAAAIIIIAAAggg4D6BtJKtYmJipGTJku4bkEgIIIAAAggggAACphcg2cr0W8gC0lsga9ascv36dYtp9OvXTyZMmJDeU2N8BBBAAAEEEEAAAQQSBfr27SuTJk1K/HumTJkkLi4OIQQQQAABBBBAAAEEEEAgoAXSSrY6c+aM5MuXL6CNWDwCCCCAAAIIIICApQDJVjwjEHBRIGfOnHL58mWLKIMHD5aRI0e6GJnLEUAAAQQQQAABBBBwn8Arr7wi48ePTwyoNw1cvXrVfQMQCQEEEEAAAQQQQAABBBAwoUBayVb6e5P+/kRDAAEEEEAAAQQQQCBBgGQrngsIuCiQJ08euXDhgkWU4cOHy9tvv+1iZC5HAAEEEEAAAQQQQMB9Aq+99pqMGTMmMaDeNBAbG+u+AYiEAAIIIIAAAggggAACCJhQIK1kq/j4eBOuiikjgAACCCCAAAIIeFKAZCtP6hI7IAQKFCggWkY4afvkk0+kf//+AbF+FokAAggggAACCCBgDgGtvvrhhx8mTjZv3rxy9uxZc0yeWSKAAAIIIIAAAggggAACHhIg2cpDsIRFAAEEEEAAAQT8WIBkKz/eXJbmHYHChQvLyZMnLQabMmWK9OrVyzsTYBQEEEAAAQQQQAABBOwQ0Mqr7733XmLPggULWv0ca0cYuiCAAAIIIIAAAggggAACfiVAspVfbSeLQQABBBBAAAEEvCJAspVXmBnEnwWKFy8ux44ds1jirFmzpHPnzv68bNaGAAIIIIAAAgggYDKBqKgoiYyMTJx1sWLF5OjRoyZbBdNFAAEEEEAAAQQQQAABBNwrQLKVez2JhgACCCCAAAIIBIIAyVaBsMus0aMCpUuXlpiYGIsxFi1aJG3btvXouARHAAEEEEAAAQQQQMARgffff1/eeuutxEtKlSolhw4dciQEfRFAAAEEEEAAAQQQQAABvxMg2crvtpQFIYAAAggggAACHhcg2crjxAzg7wLly5eXAwcOWCxz5cqV0rx5c39fOutDAAEEEEAAAQQQMJHAqFGjZODAgYkzLleunOzfv99EK2CqCCCAAAIIIIAAAggggID7BdasWSPNmjVLMXB8fLz7ByUiAggggAACCCCAgKkFSLYy9fYxeV8QqFixouzdu9diKps2bZI6der4wvSYAwIIIIAAAggggAAChsDYsWNlwIABiRqVKlWSXbt2oYMAAggggAACCCCAAAIIBLTAxo0bpX79+ikakGwV0E8PFo8AAggggAACCNgUINmKJwYCLgpUrVpVdu7caRFF37TSN69oCCCAAAIIIIAAAgj4isBnn30m/fr1S5xOtWrVZMeOHb4yPeaBAAIIIIAAAggggAACCKSLwLZt26RmzZopjk2yVbpsC4MigAACCCCAAAI+LUCylU9vD5Mzg0BYWJhs377dYqpHjhyR4sWLm2H6zBEBBBBAAAEEEEAgQASmTJkivXv3TlxtrVq1ZMuWLQGyepaJAAIIIIAAAggggAACCNgW2L17t1SuXDlFHpKteOYggAACCCCAAAIIaZfLBQAAIABJREFUJBcg2YrnBAIuCtx3331Wb1KdO3dO8uTJ42JkLkcAAQQQQAABBBBAwH0C06dPl+7duycGrFu3ruhxGTQEEEAAAQQQQAABBBBAIJAF/v77bylbtqxNgsyZM8uNGzcCmYe1I4AAAggggAACCNgQINmKpwUCLgrUq1dPNm3aZBElLi5OMmXK5GJkLkcAAQQQQAABBBBAwH0C3377rTz99NOJARs2bCi//fab+wYgEgIIIIAAAggggAACCCBgQoFjx46leFJFzpw5JTY21oSrYsoIIIAAAggggAACnhQg2cqTusQOCIFGjRrJunXrEteaMWNGuXXrVkCsnUUigAACCCCAAAIImEdg9uzZ8uSTTyZOuFmzZhIdHW2eBTBTBBBAAAEEEEAAAQQQQMADAmfOnJECBQrYjJw/f345ffq0B0YlJAIIIIAAAggggICZBUi2MvPuMXefENA3qdasWZM4lxw5csilS5d8Ym5MAgEEEEAAAQQQQACBBIF58+ZJx44dE0HCw8Nl1apVACGAAAIIIIAAAggggAACAS2gr+fnypXLpkGxYsXk6NGjAe3D4hFAAAEEEEAAAQSsBUi24lmBgIsCzZs3t6gIoHfAnDp1ysWoXI4AAggggAACCCCAgHsFFi9eLG3btk0MSrKVe32JhgACCCCAAAIIIIAAAuYUiIuLkyxZsticfJkyZeTgwYPmXBizRgABBBBAAAEEEPCYAMlWHqMlcKAIJE+2KlmypMTExATK8lknAggggAACCCCAgEkEli9fLg899FDibEm2MsnGMU0EEEAAAQQQQAABBBDwuEBQUJDNMSpVqiS7du3y+PgMgAACCCCAAAIIIGAuAZKtzLVfzNYHBZInW1WsWFF2797tgzNlSggggAACCCCAAAKBLKBHBrZo0SKRgGSrQH42sHYEEEAAAQQQQAABBBBIKpA5c2a5efOmFUpYWJhs3boVLAQQQAABBBBAAAEELARItuIJgYCLAsmTrfjly0VQLkcAAQQQQAABBBDwiMCKFSvkgQceSIxNspVHmAmKAAIIIIAAAggggAACJhTInj27XL161Wrm9erVkw0bNphwRUwZAQQQQAABBBBAwJMCJFt5UpfYASGQPNmqQYMGsm7duoBYO4tEAAEEEEAAAQQQMI/AsmXLpHXr1okTJtnKPHvHTBFAAAEEEEAAAQQQQMCzAnny5JELFy5YDdK0aVNZvXq1ZwcnOgIIIIAAAggggIDpBEi2+n/27gXOpnL/4/iPLiIZl1NJcu8kCSNScozpqFDut1CZkVDRkCIpRkkUuXZCyUihNLmFFGE67vfbuNeIKApDKMT/9dv9Z87smT0ze2avtfZaa3+e/2v+yqz1PL/n/ez+/9mzv+t5HLdkFGw3gfRhKz2aRXcNoCGAAAIIIIAAAgggYCeBL7/8Uho3bpxaEmErO60OtSCAAAIIIIAAAggggEAwBYoXLy6//PJLhhJ0d+BvvvkmmKUxNgIIIIAAAggggIANBQhb2XBRKMlZAunDVg8//LDoB1k0BBBAAAEEEEAAAQTsJDBr1ixp0aJFakk8oW2n1aEWBBBAAAEEEEAAAQQQCKbALbfcIocOHcpQQqNGjWT+/PnBLI2xEUAAAQQQQAABBGwoQNjKhotCSc4SSB+2atWqlcycOdNZk6BaBBBAAAEEEEAAAdcLfPbZZ9K2bdvUedaqVUtWr17t+nkzQQQQQAABBBBAAAEEEEAgO4Hy5cvL999/n+GyZs2aiT64QkMAAQQQQAABBBBAIK0AYSteDwgEKJA+bPXYY4/J1KlTA+yV2xFAAAEEEEAAAQQQMFZg2rRp0qFDh9ROq1WrJps2bTJ2EHpDAAEEEEAAAQQQQAABBBwocPvtt8uuXbsyVN6mTRv59NNPHTgjSkYAAQQQQAABBBAwU4CwlZm69B0SAunDVk899ZRMnDgxJObOJBFAAAEEEEAAAQScIzBlyhSJiopKLbhixYqyc+dO50yAShFAAAEEEEAAAQQQQAABkwSqVKki27Zty9C7PrDy8ccfmzQq3SKAAAIIIIAAAgg4VYCwlVNXjrptI5A+bPXcc8/J6NGjbVMfhSCAAAIIIIAAAgggoAIffPCB6IMBKa1s2bI+j8lACwEEEEAAAQQQQAABBBAINYEaNWrIhg0bMkw7OjpaPvzww1DjYL4IIIAAAggggAAC2QgQtuIlgkCAAunDVn379pWhQ4cG2Cu3I4AAAggggAACCCBgrMD48ePl6aefTu20RIkS8tNPPxk7CL0hgAACCCCAAAIIIIAAAg4UqF27tqxatSpD5V27dhV9L0VDAAEEEEAAAQQQQCCtAGErXg8IBCiQPmwVGxsrAwcODLBXbkcAAQQQQAABBBBAwFiBsWPHiu7CmtKKFSsmv/76q7GD0BsCCCCAAAIIIIAAAggg4ECBiIgISUhIyFB5jx49ZMyYMQ6cESUjgAACCCCAAAIImClA2MpMXfoOCYH0YavBgwdL//79Q2LuTBIBBBBAAAEEEEDAOQLvvPOO9O7dO7XgggULyunTp50zASpFAAEEEEAAAQQQQAABBEwSSP97/pRh9D3U8OHDTRqVbhFAAAEEEEAAAQScKkDYyqkrR922EUj/JmzYsGHSp08f29RHIQgggAACCCCAAAIIqMBbb70leuR1Srvqqqvk/Pnz4CCAAAIIIIAAAggggAACIS+QWdjqpZdekjfffDPkfQBAAAEEEEAAAQQQ8BYgbMUrAoEABdK/CdMdA3r16hVgr9yOAAIIIIAAAggggICxAm+88Ya88sorXp1evHhRrrjiCmMHojcEEEAAAQQQQAABBBBAwGECmYWtBgwYIIMGDXLYbCgXAQQQQAABBBBAwGwBwlZmC9O/6wXSvwkbN26cPPvss66fNxNEAAEEEEAAAQQQcJaAfkAQGxvrVfSZM2ekQIECzpoI1SKAAAIIIIAAAggggAACBgtkFrZ6/fXXMzy0YvDQdIcAAggggAACCCDgQAHCVg5cNEq2l0D6N2ETJkyQLl262KtIqkEAAQQQQAABBBAIeYFXX31VBg8e7OVw/PhxKVKkSMjbAIAAAggggAACCCCAAAKhLZBZ2GrYsGHSp0+f0MZh9ggggAACCCCAAAIZBAhb8aJAIECB9G/CPvzwQ4mOjg6wV25HAAEEEEAAAQQQQMBYgX79+snQoUO9Oj1y5IgUL17c2IHoDQEEEEAAAQQQQAABBBBwmEBmYat33nlHevXq5bDZUC4CCCCAAAIIIICA2QKErcwWpn/XC6R/EzZ16lR57LHHXD9vJogAAggggAACCCDgLIEXX3xRhg8f7lV0UlKSlC5d2lkToVoEEEAAAQQQQAABBBBAwGCBzMJWY8eOle7duxs8Gt0hgAACCCCAAAIIOF2AsJXTV5D6gy6Q/k3YjBkzpG3btkGviwIQQAABBBBAAAEEEEgroE9jjxo1ygtl165dcttttwGFAAIIIIAAAggggAACCIS0QGZhq/Hjx0vXrl1D2obJI4AAAggggAACCGQUIGzFqwKBAAXSvwmLj4+XFi1aBNgrtyOAAAIIIIAAAgggYKxAjx49ZNy4cV6dbtmyRapUqWLsQPSGAAIIIIAAAggggAACCDhMILOw1aRJk6RTp04Omw3lIoAAAggggAACCJgtQNjKbGH6d71A+jdhc+fOlcaNG7t+3kwQAQQQQAABBBBAwFkCTz/9tOhT2Wnb2rVrpWbNms6aCNUigAACCCCAAAIIIIAAAgYLZBa2mjp1qjz22GMGj0Z3CCCAAAIIIIAAAk4XIGzl9BWk/qALpH8TtnDhQmnQoEHQ66IABBBAAAEEEEAAAQTSCjz11FPywQcfeKF89913UqdOHaAQQAABBBBAAAEEEEAAgZAWyCxsNWPGDGnbtm1I2zB5BBBAAAEEEEAAgYwChK14VSAQoED6N2GLFy+Wf//73wH2yu0IIIAAAggggAACCBgrEB0dLXFxcV6d8rOrscb0hgACCCCAAAIIIIAAAs4UyCxsFR8fLy1atHDmpKgaAQQQQAABBBBAwDQBwlam0dJxqAhERERIQkJC6nSXLl0q9erVC5XpM08EEEAAAQQQQAABhwg8/vjj8vHHH3tVO3/+fGnUqJFDZkCZCCCAAAIIIIAAAggggIA5ApmFrebOnSuNGzc2Z1B6RQABBBBAAAEEEHCsAGErxy4dhdtFoHbt2rJq1arUcghb2WVlqAMBBBBAAAEEEEAgrUC7du1Ej8BI22bNmiXNmjUDCgEEEEAAAQQQQAABBBAIaQF9CGXhwoUZDL766it56KGHQtqGySOAAAIIIIAAAghkFCBsxasCgQAFatSoIRs2bEjthbBVgKDcjgACCCCAAAIIIGCKQOvWreXzzz/36lvDV23btjVlPDpFAAEEEEAAAQQQQAABBJwioEcF6sMo6duSJUvk/vvvd8o0qBMBBBBAAAEEEEDAIgHCVhZBM4x7BapUqSLbtm1LnSBhK/euNTNDAAEEEEAAAQScLNC8eXOZPXu21xSmTJkiTzzxhJOnRe0IIIAAAggggAACCCCAQMACHTp0kGnTpmXo57vvvpM6deoE3D8dIIAAAggggAACCLhLgLCVu9aT2QRB4Pbbb5ddu3aljkzYKgiLwJAIIIAAAggggAAC2Qo0btxYvvzyS6/r3n//fencuXO293IBAggggAACCCCAAAIIIOBmAX1fNGnSpAxTXLt2rdSsWdPNU2duCCCAAAIIIIAAArkQIGyVCzRuQSCtQPny5eX7779P/SvCVrw+EEAAAQQQQAABBOwo0LBhQ/nqq6+8Shs3bpw8++yzdiyXmhBAAAEEEEAAAQQQQAABywR69Ogh+v4ofduyZYvo6RY0BBBAAAEEEEAAAQTSChC24vWAQIACt9xyixw6dCi1F8JWAYJyOwIIIIAAAggggIApAg888IAsXrzYq+933nlHevXqZcp4dIoAAggggAACCCCAAAIIOEWgT58+8vbbb2cod/fu3fLPf/7TKdOgTgQQQAABBBBAAAGLBAhbWQTNMO4VKF68uPzyyy+pEyRs5d61ZmYIIIAAAggggICTBSIjI2XZsmVeU3jzzTflpZdecvK0qB0BBBBAAAEEEEAAAQQQCFhgwIAB8vrrr2foJykpSUqXLh1w/3SAAAIIIIAAAggg4C4BwlbuWk9mEwSBokWLyokTJ1JHJmwVhEVgSAQQQAABBBBAAIFsBerUqSMrVqzwui42NlYGDhyY7b1cgAACCCCAAAIIIIAAAgi4WUAfRHn55ZczTPHIkSOiD1zTEEAAAQQQQAABBBBIK0DYitcDAgEKFCxYUM6cOZPaC2GrAEG5HQEEEEAAAQQQQMAUgXvuuUfWrFnj1bd+mPDGG2+YMh6dIoAAAggggAACCCCAAAJOERg1apTPI9b1QevChQs7ZRrUiQACCCCAAAIIIGCRAGEri6AZxr0C+fLlk/Pnz6dOkLCVe9eamSGAAAIIIIAAAk4WuOuuu2Tjxo1eU+jdu7cMHz7cydOidgQQQAABBBBAAAEEEEAgYIEJEyZIt27dMvRz9uxZyZ8/f8D90wECCCCAAAIIIICAuwQIW7lrPZlNEATy5MnjNSphqyAsAkMigAACCCCAAAIIZCtQtWpV2bp1q9d1PXr0kDFjxmR7LxcggAACCCCAAAIIIIAAAm4WmDJlikRFRWWY4l9//SV58+Z189SZGwIIIIAAAggggEAuBAhb5QKNWxBIEdAdrXRnq7SNsBWvDwQQQAABBBBAAAE7ClSqVEl27tzpVVqXLl1En+CmIYAAAggggAACCCCAAAKhLPDZZ59J27ZtvQiuuuoqr1MtQtmHuSOAAAIIIIAAAgh4CxC24hWBQAACp0+flkKFCnn1QNgqAFBuRQABBBBAAAEEEDBN4NZbb5V9+/Z59d+xY0eJi4szbUw6RgABBBBAAAEEEEAAAQScIDBv3jxp0qSJV6nXXXednDp1ygnlUyMCCCCAAAIIIICAxQKErSwGZzh3Cfz6669y/fXXe02KsJW71pjZIIAAAggggAACbhEoW7asJCUleU2nXbt2Mm3aNLdMkXkggAACCCCAAAIIIIAAArkSWLx4sTzwwANe9/7jH/+QY8eO5ao/bkIAAQQQQAABBBBwtwBhK3evL7MzWeDw4cNy8803e41C2MpkdLpHAAEEEEAAAQQQyJVAyZIl5aeffvK6t0WLFhIfH5+r/rgJAQQQQAABBBBAAAEEEHCLQEJCgkRERHhNR3/3f+jQIbdMkXkggAACCCCAAAIIGChA2MpATLoKPYEffvhBypUr5zVxwlah9zpgxggggAACCCCAgBMEihcvLr/88otXqQ8//LB8+eWXTiifGhFAAAEEEEAAAQQQQAAB0wRWrlwp9913n1f/5cuXz3AUu2kF0DECCCCAAAIIIICAowQIWzlquSjWbgK7d++WihUrepVF2Mpuq0Q9CCCAAAIIIIAAAipQrFgxOX78uBeGHpPx9ddfA4QAAggggAACCCCAAAIIhLTA2rVrpVatWl4GlSpVkh07doS0C5NHAAEEEEAAAQQQ8C1A2IpXBgIBCGzdulWqVq3q1QNhqwBAuRUBBBBAAAEEEEDANIGwsDA5deqUV/9169aV5cuXmzYmHSOAAAIIIIAAAggggAACThDYuHGj3HXXXV6lhoeHi/49DQEEEEAAAQQQQACB9AKErXhNIBCAwPr166VmzZpePRC2CgCUWxFAAAEEEEAAAQRMEyhQoICcO3fOq/977rlHVq1aZdqYdIwAAggggAACCCCAAAIIOEHA14PV9957r+jxgjQEEEAAAQQQQAABBNILELbiNYFAAAIrVqyQOnXqePVA2CoAUG5FAAEEEEAAAQQQME3g6quvlgsXLnj1X716ddmwYYNpY9IxAggggAACCCCAAAIIIOAEgZ07d4oeG5i21atXT/T3/TQEEEAAAQQQQAABBNILELbiNYFAAAIJCQkSERHh1QNhqwBAuRUBBBBAAAEEEEDANIE8efJk6Lty5cqybds208akYwQQQAABBBBAAAEEEEDACQJ79+6Vf/7zn16lNmjQQBYuXOiE8qkRAQQQQAABBBBAwGIBwlYWgzOcuwRWr14tupVw2kbYyl1rzGwQQAABBBBAAAE3COiOVrqzVfqmHybs3r3bDVNkDggggAACCCCAAAIIIIBArgV++OEHKVeunNf9zZo1k1mzZuW6T25EAAEEEEAAAQQQcK8AYSv3ri0zs0Bg48aNctddd3mNRNjKAniGQAABBBBAAAEEEMiRwNmzZ+Xaa6/NcE+ZMmVEP1SgIYAAAggggAACCCCAAAKhLHDw4EEpVaqUF8Gjjz4q06dPD2UW5o4AAggggAACCCCQiQBhK14aCAQgsH37drnzzju9eiBsFQAotyKAAAIIIIAAAgiYInDy5EkpUqRIhr5vuukmOXz4sClj0ikCCCCAAAIIIIAAAggg4BSBI0eOSIkSJbzKjYqKksmTJztlCtSJAAIIIIAAAgggYKEAYSsLsRnKfQJ79uyR2267zWtihK3ct87MCAEEEEAAAQQQcLrAsWPH5IYbbsgwjWLFismvv/7q9OlRPwIIIIAAAggggAACCCAQkICv90zdunWT9957L6B+uRkBBBBAAAEEEEDAnQKErdy5rszKIoGkpCQpW7as12iErSzCZxgEEEAAAQQQQAABvwV096qbb745w/XXXXednDp1yu9+uBABBBBAAAEEEEAAAQQQcKPAiRMnpGjRol5T69mzp4wcOdKN02VOCCCAAAIIIIAAAgEKELYKEJDbQ1vA14dWhK1C+zXB7BFAAAEEEEAAATsKHDhwQMqUKZOhtHz58skff/xhx5KpCQEEEEAAAQQQQAABBBCwTOD06dNSqFAhr/H69esnQ4YMsawGBkIAAQQQQAABBBBwjgBhK+esFZXaUECPXLn++uu9KiNsZcOFoiQEEEAAAQQQQCDEBfbt2ye33nprBoU8efLIpUuXQlyH6SOAAAIIIIAAAggggECoC5w7d04KFCjgxRAbGysDBw4MdRrmjwACCCCAAAIIIOBDgLAVLwsEAhDQI1fCwsK8eiBsFQAotyKAAAIIIIAAAgiYIpCYmCh33HGHz77Pnz8vV111lSnj0ikCCCCAAAIIIIAAAggg4ASBCxcuyNVXX+1V6rBhw6RPnz5OKJ8aEUAAAQQQQAABBCwWIGxlMTjDuUtAj1zJnz+/16QIW7lrjZkNAggggAACCCDgBoEtW7ZItWrVfE7l999/l2uvvdYN02QOCCCAAAIIIIAAAggggECuBC5fvix58+b1unf06NHy3HPP5ao/bkIAAQQQQAABBBBwtwBhK3evL7MzWcDXGzDCViaj0z0CCCCAAAIIIIBAjgXWr18vNWvW9Hnfb7/9JkWLFs1xn9yAAAIIIIAAAggggAACCLhJQHe20h2uUtqECROkS5cubpoic0EAAQQQQAABBBAwSICwlUGQdBO6AunfgBG2Ct3XAjNHAAEEEEAAAQTsKrBq1SqpXbu2z/KOHDkixYsXt2vp1IUAAggggAACCCCAAAIIWCJw3XXXie78m9KmTJkiTzzxhCVjMwgCCCCAAAIIIICAswQIWzlrvajWhgIFCxaUM2fOpFZG2MqGi0RJCCCAAAIIIIBAiAssX75c6tWr51PhwIEDUqpUqRAXYvoIIIAAAggggAACCCAQ6gL/+Mc/RHf+TWmffvqptGnTJtRZmD8CCCCAAAIIIICADwHCVrwsEAhQQI9cOXHiRGovhK0CBOV2BBBAAAEEEEAAAcMFli1bJpGRkT773bt3r1SoUMHwMekQAQQQQAABBBBAAAEEEHCSQIkSJUR3/k1pc+bMkSZNmjhpCtSKAAIIIIAAAgggYJEAYSuLoBnGvQJ65Movv/ySOkHCVu5da2aGAAIIIIAAAgg4VSCrsNWOHTukUqVKTp0adSOAAAIIIIAAAggggAAChgiULVtWkpKSUvtatGiRPPjgg4b0TScIIIAAAggggAAC7hIgbOWu9WQ2QRDQI1cOHjyYOjJhqyAsAkMigAACCCCAAAIIZCmQVdhq06ZNUq1aNQQRQAABBBBAAAEEEEAAgZAWqFixouzevZvf9Yf0q4DJI4AAAggggAAC/gkQtvLPiasQyFRAj1zZv38/b8B4jSCAAAIIIIAAAgjYViCrsNXq1aulVq1atq2dwhBAAAEEEEAAAQQQQAABKwSqVKki27Zt43f9VmAzBgIIIIAAAggg4HABwlYOX0DKD76AHrmyc+dO3oAFfymoAAEEEEAAAQQQQCATgazCVgkJCfKvf/0LOwQQQAABBBBAAAEEEEAgpAVq1qwp69ev53f9If0qYPIIIIAAAggggIB/AoSt/HPiKgQyFdAjV7Zs2cIbMF4jCCCAAAIIIIAAArYVyCpstWTJErn//vttWzuFIYAAAggggAACCCCAAAJWCNSpU0dWrFjB7/qtwGYMBBBAAAEEEEDA4QKErRy+gJQffIG7775b1q1bxxuw4C8FFSCAAAIIIIAAAghkIpBV2GrhwoXSoEED7BBAAAEEEEAAAQQQQACBkBaIiIgQ3fk3pS1dulTq1asX0iZMHgEEEEAAAQQQQMC3AGErXhkIBCjA0y4BAnI7AggggAACCCCAgOkCWYWt5syZI02aNDG9BgZAAAEEEEAAAQQQQAABBOwscM8998iaNWtSSyRsZefVojYEEEAAAQQQQCC4AoStguvP6C4Q0Cdbli9fnjoTjmFxwaIyBQQQQAABBBBAwGUCWYWtPv/8c2nZsqXLZsx0EEAAAQQQQAABBBBAAIGcCVSvXl02bdqUehNhq5z5cTUCCCCAAAIIIBBKAoStQmm1maspAul3tlq0aJE8+OCDpoxFpwgggAACCCCAAAII5EYgq7DVtGnTpF27drnplnsQQAABBBBAAAEEEEAAAdcI3HHHHZKYmJg6H8JWrllaJoIAAggggAACCBguQNjKcFI6DDWB9FsLz58/Xxo1ahRqDMwXAQQQQAABBBBAwMYCuvtq/fr1fVYYFxcnHTt2tHH1lIYAAggggAACCCCAAAIImC9QoUIF2b9/f+pAhK3MN2cEBBBAAAEEEEDAqQKErZy6ctRtG4EaNWrIhg0bUuuZM2eONGnSxDb1UQgCCCCAAAIIIIAAAvpAwCOPPOIT4v3335fOnTuDhAACCCCAAAIIIIAAAgiEtECpUqXk4MGDqQaErUL65cDkEUAAAQQQQACBLAUIW/ECQSBAgfDwcNm8eXNqL/Hx8dKiRYsAe+V2BBBAAAEEEEAAAQSME/jiiy+kZcuWPjt899135ZlnnjFuMHpCAAEEEEAAAQQQQAABBBwocOONN8rRo0dTKyds5cBFpGQEEEAAAQQQQMAiAcJWFkEzjHsF7rzzTtm+fXvqBD/99FNp06aNeyfMzBBAAAEEEEAAAQQcJzBt2jTp0KGDz7pHjRolMTExjpsTBSOAAAIIIIAAAggggAACRgoULlxYkpOTU7skbGWkLn0hgAACCCCAAALuEiBs5a71ZDZBELj99ttl165dqSN/8skn0r59+yBUwpAIIIAAAggggAACCPgWmDx5snTq1MnnN9966y158cUXoUMAAQQQQAABBBBAAAEEQlogf/788scff6QaELYK6ZcDk0cAAQQQQAABBLIUIGzFCwSBAAVuvfVW2bdvX2ovcXFx0rFjxwB75XYEEEAAAQQQQAABBIwTeO+99zI9KnDw4MHSv39/4wajJwQQQAABBBBAAAEEEEDAgQJXXHGFXLp0KbVywlYOXERKRgABBBBAAAEELBIgbGURNMO4V6Bs2bKSlJSUOsEPPvhAnnzySfdOmJkhgAACCCCAAAIIOE5g5MiR8vzzz/use+DAgRIbG+u4OVEwAggggAACCCCAAAIIIGCUwMWLF+Wqq67y6o4Z6PGbAAAgAElEQVSwlVG69IMAAggggAACCLhPgLCV+9aUGVksUKpUKTl48GDqqOPHj5euXbtaXAXDIYAAAggggAACCCCQucDQoUOlX79+Pi/Qvx8yZAh8CCCAAAIIIIAAAggggEDICpw7d04KFCjgNX/CViH7cmDiCCCAAAIIIIBAtgKErbIl4gIEshYoUaKEHDlyJPWicePGybPPPgsbAggggAACCCCAAAK2ERg0aFCmu1e98MIL8vbbb9umVgpBAAEEEEAAAQQQQAABBKwWSE5OlsKFC3sNS9jK6lVgPAQQQAABBBBAwDkChK2cs1ZUalOBG264QY4dO5Za3ahRoyQmJsam1VIWAggggAACCCCAQCgKZBW2eu6552T06NGhyMKcEUAAAQQQQAABBBBAAAGPwK+//irXX3+9lwZhK14cCCCAAAIIIIAAApkJELbitYFAgAJFixaVEydOpPYyfPhw6d27d4C9cjsCCCCAAAIIIIAAAsYJZBW26tatm7z33nvGDUZPCCCAAAIIIIAAAggggIDDBPT0Cj3FIm0jbOWwRaRcBBBAAAEEEEDAQgHCVhZiM5Q7BQoVKiSnT59OndzQoUOlb9++7pwss0IAAQQQQAABBBBwpEBWYasnn3xSPvjgA0fOi6IRQAABBBBAAAEEEEAAASMEDhw4IGXKlPHqirCVEbL0gQACCCCAAAIIuFOAsJU715VZWShw7bXXytmzZ1NHHDx4sPTv39/CChgKAQQQQAABBBBAAIGsBbIKWz3++OPy0UcfQYgAAggggAACCCCAAAIIhKzAvn375NZbb/WaP2GrkH05MHEEEEAAAQQQQCBbAcJW2RJxAQJZC+TLl0/Onz+felFsbKwMHDgQNgQQQAABBBBAAAEEbCOQVdjq0UcflenTp9umVgpBAAEEEEAAAQQQQAABBKwW2Llzp1SqVMlr2G+//VYiIyOtLoXxEEAAAQQQQAABBBwgQNjKAYtEifYWuOKKK+TSpUupRfbs2VNGjhxp76KpDgEEEEAAAQQQQCCkBLIKW7Vo0ULi4+NDyoPJIoAAAggggAACCCCAQOgIxMXFSVRUVJYT3rp1q1StWtXrmq+++koeeuih0IFipggggAACCCCAAAJ+CxC28puKCxHwLZAnTx6vb+ibtsmTJ8OFAAIIIIAAAggggIBtBLIKWz3yyCMyb94829RKIQgggAACCCCAAAIIIICAUQL33nuvrF692tPdjh07MuxelTLO+vXrpWbNml7Dzp07Vxo3bmxUKfSDAAIIIIAAAggg4CIBwlYuWkymYqzA8ePHJSwsTHTnqqxa+rBVs2bNZNasWcYWQ28IIIAAAggggAACCAQgkFXYSp/U1ie2aQgggAACCCCAAAIIIICAmwR27dolt99+e+qUGjVqJPPnz/c5xVWrVknt2rW9vvf5559Ly5YtMyXZsGGDlCtXTooUKeImNuaCAAIIIIAAAggg4IcAYSs/kLgkNAUqVqwou3fvloIFC0rhwoU9wauUr7T/PmzYMC+g8PBwmTJlSuo9hQoV8vr+nj175PDhw56/q1evXmjiMmsEEEAAAQQQQAABSwWyCltFRkbKt99+a2k9DIYAAggggAACCCCAAAIImC2Q/n1QyZIlZerUqVK0aFEpVqyY58/8+fN7ykhISJCIiAivkqZNmybt2rXzWWbXrl1l4sSJnu99+eWX8vDDD5s9HfpHAAEEEEAAAQQQsJEAYSsbLQalBF9g6NChsmjRIqlRo4ZceeWVov8eaNOdr/Lly+fp5vz583Lp0qXULm+++WYZOXKktG7dOtBhuB8BBBBAAAEEEEAAgUwFsgpbjRkzRnr06IEeAggggAACCCCAAAIIIOAagcWLF8tTTz0lSUlJhsxJf8evv8+/6aabRHfM+u2337z6rVWrlsyePVuKFy9uyHh0ggACCCCAAAIIIGBvAcJW9l4fqrNQYNmyZaJP9ae0ChUqyL59+yyp4Oeff5Ybb7zRkrEYBAEEEEAAAQQQQCD0BNKHrWJjY2Xz5s3StGlTiYqKCj0QZowAAggggAACCCCAAAKuFqhcubLs2LHD0jk2b95cvvjiC0vHZDAEEEAAAQQQQACB4AgQtgqOO6PaUECfOtE3Q8Fos2bNkpo1a3qejKEhgAACCCCAAAIIIGCGgO64mtIOHjwoeoQGDQEEEEAAAQQQQAABBBBwo0D79u1l+vTplk+NB6stJ2dABBBAAAEEEEAgKAKErYLCzqB2FIiLi5Po6OigldalSxeZMGFC0MZnYAQQQAABBBBAAAH3C+gOVwMHDnT/RJkhAggggAACCCCAAAIIhLTAzJkzZcGCBTJ//nw5duyYZRarV68WPVKQhgACCCCAAAIIIOBuAcJW7l5fZpcDgT179kiLFi0s31o4bYmXL1/OQcVcigACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAApkJvPDCCzJixAjTgYoXLy4xMTHy0ksvmT4WAyCAAAIIIIAAAggEX4CwVfDXgApsJnDbbbeJBq+sblFRUTJ58mSrh2U8BBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRcKbBw4UJp1KiR6XN7+eWX5Y033jB9HAZAAAEEEEAAAQQQsIcAYSt7rANV2Ejgq6++koYNG1paUcGCBWXRokVSu3ZtS8dlMAQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE3Cxw5513yvbt202bYv78+WXr1q1SoUIF08agYwQQQAABBBBAAAF7CRC2std6UI1NBNq0aSN6prtV7b333pNu3bpZNRzjIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQEgKvvPKKqbtOPfvsszJu3LiQsGSSCCCAAAIIIIAAAn8LELbilYCAD4Hp06dL+/btLbHRkJWGrWgIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBgrMDatWulVq1axnaaprd169ZJjRo1TOufjhFAAAEEEEAAAQTsJ0DYyn5rQkU2EDh9+rRUrFhRDh8+bGo1emygHh+oxwjSEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwHiByMhIWbZsmeEdP/bYYzJ16lTD+6VDBBBAAAEEEEAAAXsLELay9/pQXRAFunbtKhMnTjS1gm+//Vb0TR4NAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEzBEYOXKkPP/884Z3/s0330j9+vUN75cOEUAAAQQQQAABBOwtQNjK3utDdUEU+PLLL6Vx48amVdC/f38ZPHiwaf3TMQIIIIAAAggggAACCCCAAAIIIIAAAggggAACCIjs37/fc5rFxYsXDePQzw/mzp1rWH90hAACCCCAAAIIIOAcAcJWzlkrKg2CQLVq1WTLli2Gj6znwy9fvlzy5ctneN90iAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAt4CLVu2lC+++MIwlgULFkjDhg0N64+OEEAAAQQQQAABBJwjQNjKOWtFpUEQGDFihLzwwguGjzx//nxp1KiR4f3SIQIIIIAAAggggAACCCCAAAIIIIAAAggggAACCGQUmDJlikRFRXl9Qx+I/vPPP3PM1apVK5k5c2aO7+MGBBBAAAEEEEAAAXcIELZyxzoyC5MEjh07Jrq71eHDhw0boVevXvLOO+8Y1h8dIYAAAggggAACCCCAAAIIIIAAAggggAACCCCAQNYCJ06c8BwlePTo0YCplixZIvfff3/A/dABAggggAACCCCAgDMFCFs5c92o2kKBfv36ydChQw0ZsXTp0rJmzRq58cYbDemPThBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMA/gc6dO8ukSZO8Li5atKgcP37cvw5EpEOHDvLxxx/7fT0XIoAAAggggAACCLhPgLCV+9aUGRkskJiY6Nnd6sKFCwH3PHz4cOndu3fA/dABAggggAACCCCAAAIIIIAAAggggAACCCCAAAII5Exg7ty50rRp05zdlO7q//73v3LfffcF1Ac3I4AAAggggAACCDhbgLCVs9eP6i0SiImJkTFjxgQ0mga2dFerq6++OqB+uBkBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRyJ6BHCe7evdvr5rCwMElOTs62w06dOmXYGSvbm7gAAQQQQAABBBBAwHUChK1ct6RMyAyBX375RerWrSt79uzJdfe6NbG+EaMhgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAcAT69u0rb731Vq4GX7dundSoUSNX93ITAggggAACCCCAgHsECFu5Zy2ZickCH330kXTs2DFXo0RGRsq3336bq3u5CQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBIwRWLFihdSpUyfHnfXp00eGDRuW4/u4AQEEEEAAAQQQQMB9AoSt3LemzMhEgfbt28v06dNzPMIXX3whzZs3z/F93IAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALGCmjYSkNXOWmJiYly++235+QWrkUAAQQQQAABBBBwqQBhK5cuLNMyR2DHjh2e4wSPHz/u9wAtW7aUzz//3O/ruRABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTME9BjBPU4QX9beHi4bNy40d/LuQ4BBBBAAAEEEEDA5QKErVy+wEzPeIF+/frJ0KFD/e542bJlEhER4ff1XIgAAggggAACCCDgPoGkpCSZM2eOZ2LVqlWTqlWrSuHChb0munnzZklOTha91teX3tesWTNp2rSppw8aAggggAACCCCAAAIIIIBA7gR2794tFStW9PvmHj16yJgxY/y+ngsRQAABBBBAAAEE3C1A2Mrd68vsTBDYtm2bVKlSxa+eu3btKuPHj/frWi5CAAEEEEAAAQQQcJfA8uXLZfbs2aLhew1SGd3KlCkj+pW2aQhLQ1wp3yP0b7Q6/SGAAAIIIIAAAggggIBbBJo0aSLz5s3zazqffvqptGnTxq9ruQgBBBBAAAEEEEDA/QKErdy/xszQBIF69eqJfniWVbvmmmtkw4YNUqlSJRMqoEsEEEAAAQQQQAABuwmk7F6l4Sr9OnnypC1K1ACWfmkAS3+OHTVqlKe2mJgYz05ZNAQQQAABBBBAAAEEEEAgFAUmTpwo+sB0dk0faNm3b58UK1Ysu0v5PgIIIIAAAggggECICBC2CpGFZprGCgwYMEBef/31LDvVp2JSjooxdnR6QwABBBBAAAEEELBaQMNJW7Zs8ToeWsNVGsBPCVfpvzutadhq5MiRGXbIcto8qBcBBBBAAAEEEEAAAQQQyKnA4cOHPUcJnj59Ostb27ZtKzNmzMhp91yPAAIIIIAAAggg4GIBwlYuXlymZp7Ad999J3Xr1s1ygCFDhki/fv3MK4KeEUAAAQQQQAABBCwRGD16tMTGxnp2g0o5pk+PBbTLzlVGIGjoSr/02MH0RxMa0T99IIAAAggggAACCCCAAAJ2FGjfvr1Mnz49y9I+/PBDiY6OtmP51IQAAggggAACCCAQJAHCVkGCZ1jnC5QsWVJ++umnTCeiO1+98sorzp8oM0AAAQQQQAABBEJUQHeq0l+o685VTmtXXnmlXLx4MVdlR0VFeXa70qMyaAgggAACCCCAAAIIIICAmwUmTZoknTt3znSK+fPnl71798rNN9/sZgbmhgACCCCAAAIIIJBDAcJWOQTjcgRSBDp27CgfffRRpiC9e/eW4cOHA4YAAggggAACCCDgQIG0u1k5sPyAS9agle7mFRMTE3BfdIAAAggggAACCCCAAAII2FUgMTFR7rjjjkzL0x2AZ82aZdfyqQsBBBBAAAEEEEAgSAKErYIEz7DOF4iPj5dWrVplOpEnn3xSPvjgA+dPlBkggAACCCCAAAIhJJCb3axSjt47c+aMbN++XXbt2uUIsTx58ojugHXhwoVM69VjE3v27Mnxgo5YUYpEAAEEEEAAAQQQQACB3AhUrlxZduzY4fPW9957T7p165abbrkHAQQQQAABBBBAwMUChK1cvLhMzVyB8ePHy9NPP53pIBrEmjlzprlF0DsCCCCAAAIIIICAYQLZ7WZVunRp0aeay5QpIxpC0t2f9M9169Z5djT97LPPDKvFjh3pvOvVq+eZs7amTZt6LGgIIIAAAggggAACCCCAgJMFBg0a5NnZ11fbv3+/lCtXzsnTo3YEEEAAAQQQQAABEwQIW5mASpehIdC1a1eZOHFi6mT1gybdCSGl1a9fX7755pvQwGCWCCCAAAIIIICAgwX82c1Kd6+aPXu2J2CV0o4dOyYjRozwfF28eNHBArkrXS2WLl2aGr7KXS/chQACCCCAAAIIIIAAAggEX0AfnNb3dmvWrEkt5h//+Ifo+z4aAggggAACCCCAAALpBQhb8ZpAIJcCY8aMkZiYmNS7v/zyS2nbtq3o8THa3nzzTXnppZdy2Tu3IYAAAggggAACCFghoAGq6OhoOXnyZKbDdezYUeLi4ry+P2HCBM8v4vfu3WtFmbYdg8CVbZeGwhBAAAEEEEAAAQQQQCCHAsePH5dixYql3vXCCy/I22+/ncNeuBwBBBBAAAEEEEAgFAQIW4XCKjNH0wR0e2H9gK1Hjx5Sq1Yt0X/XJ2BKlSolGsaqUKGCaWPTMQIIIIAAAggggEDuBTRc1atXrwwhqvQ9pg1a6e5VX3zxhUyaNEm+/vrr3A/usjv1WEHd4Srtrl8umyLTQQABBBBAAAEEEEAAgRAR0Adt9Pf8eoT6wIEDOTo9RNadaSKAAAIIIIAAAjkVIGyVUzGuRwABBBBAAAEEEEAAAUcL6LGBzZs3l82bN2c5j8mTJ0tUVJSsW7fOE7KKj48P+Z2sMgMjcOXo/yQoHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCAHAoStcoDFpQgggAACCCCAAAIIIOBsAd3RKjw8XDRwlVkLCwuTsWPHyrlz5zwhq0WLFjl70hZVT+DKImiGQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEAiqAGGroPIzOAIIIIAAAggggAACCFgloEGryMjILHe0KleunFSvXl0SEhLk6NGjVpXmmnEIXLlmKZkIAggggAACCCCAAAIIIIAAAggggAACCCCAQCYChK14aSCAAAIIIIAAAggggEBICGjQatmyZZnOtUiRInLixImQsDBzkgSuzNSlbwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFgCxC2CvYKMD4CCCCAAAIIIIAAAgiYLhAXFyfR0dGmj8MAfwsQuOKVgAACCCCAAAIIIIAAAggggAACCCCAAAIIIOBWAcJWbl1Z5oUAAggggAACCCCAAAIegaSkJAkPDxc9RpBmnQCBK+usGQkBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEDAOgHCVtZZMxICCCCAAAIIIIAAAghYKLB582YZPXq0zJo1S5KTky0cmaFSBAhc8VpAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQcJsAYSu3rSjzQQABBBBAAAEEEEAAAdGgVWRkJLtZ2eC10KxZM0/gjYYAAggggAACCCCAAAIIIIAAAggggAACCCCAgBsECFu5YRWZAwIIIIAAAggggAACCKQK6HGBGrTSwBXNHgJRUVEyefJkexRDFQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIBCBA2CoAPG5FAAEEEEAAAQQQQAAB+wk0b95cZs+ebb/CQrwi3eFKA1eFCxfOUkLDcnPmzJGkpCTPzmQamtPjCGNiYqRMmTIhrsj0EUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBIItQNgq2CvA+AgggAACCCCAAAIIIGCYwKhRo6RXr16G9WenjiIiIjKUo0Gk5ORkO5WZZS0amtIjBTMLTel8dP2WLVvmsx+9T/vQr3r16knVqlWzDW85BodCEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBwhQNjKEctEkQgggAACCCCAAAIIIJCdgAZ1wsPDs7vMFt8vWrSo1KlTR3QXrsyCRxoo0p2ddIcn/eesdoRK2QFKDfRL77FrEEvnsmnTJs86aI3Lly/3zDMuLs5Td06b+umXhq+0bw1gsQNWThW5HgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMBfAcJW/kpxHQIIIIAAAggggAACCNhWQMM6GrTKTVjHqknVr19fOnToIHqcXnZH6RlRk5roTl/6Zbfdr6pXry7ff/+9J2RlVtPwVdogVtpxUsJp+nf6zxrS6tixo1ml0C8CCCCAAAIIIIAAAggggAACCCCAAAIIIICAiwQIW7loMZkKAggggAACCCCAAAKhKhAdHe3ZGcmOTUM8sbGxQdttSXeP6tmzp2cHKVrmArpGAwcOhAgBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgSwFCFvxAkEAAQQQQAABBBBAAAFHC8yePdtzHJ9dWuXKlaV8+fKeY+2ioqIs2cXKn7lrGE1DV3bb5cqf2q26RnfC0tBV06ZNbbNuVs2dcRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQT8EyBs5Z8TVyGAAAIIIIAAAggggIANBfQIuLJly5p6HJ2/077uuuvktdde8wSa7NrUS8NEo0ePtmuJtqhLj3nUdYyJiSF0ZYsVoQgEEEAAAQQQQAABBBBAIHcCZ8+elWPHjsmvv/4qYWFhUqFChdx1xF0IIIAAAggggEAaAcJWvBwQQAABBBBAAAEEEEDAkQIaHIqMjBQ9Ji/YTXdC0p2jNKTjhKZmGrqaM2eO55fN7Hble9V0PZs1a+Y5XlB3vaIhgAACCCCAAAIIIIAAAgg4R+C5556TsWPHehVctGhRqVWrluiu1Po7hYYNGzpnQlSKAAIIIIAAArYRIGxlm6WgEAQQQAABBBBAAAEEEMiJQHR0tCfgFMymQaVRo0Z5jgt0atPQmtavwSta5gJqROiKVwgCCCCAAAIIIIAAAgggYH+BtWvXekJUx48fz7ZY3elKr23RooXUq1cv2+u5AAEEEEAAAQQQUAHCVrwOEEAAAQQQQAABBBBAwHECdghalS5dWmbPni3VqlVznJ+vgjW4pq60rAUIXfEKQQABBBBAAAEEEEAAAQTsLZAnT55cFahhq2eeeUZat26dq/u5CQEEEEAAAQRCR4CwVeisNTNFAAEEEEAAAQQQQMAVAj179pTRo0cHdS5OOzbQXyw9XrB27dpy7tw5f28J2etatWolb7/9NscLhuwrgIkjgAACCCCAAAIIIICAHQUGDRoksbGxAZX22WefEbgKSJCbEUAAAQQQcL8AYSv3rzEzRAABBBBAAAEEEEDANQJ22H1p5MiRooEvNzYjfintRpfM5nT11VeLBu/GjRsnN9xwQyhNnbkigAACCCCAAAIIIIAAArYTWLBggTz88MOG1PXTTz9JiRIlDOmLThBAAAEEEEDAfQKErdy3pswIAQQQQAABBBBAAAFXCgQ7aBUWFibLli1zzbGBaV8kJ0+elF69eoka03IukDdvXomIiJDXXntN6tSpk/MOuAMBBBBAAAEEEEAAAQQQQCBggRo1asiGDRsC7kc7mDdvnjzyyCOG9EUnCCCAAAIIIOA+AcJW7ltTZoQAAggggAACCCCAgOsE9Hi7yMhI0VBQMJrbg1Zqq8a0wAXatWsn06ZNC7wjekAAAQQQQAABBBBAAAEEEPBbYObMmdKmTRu/r/fnwjFjxkiPHj38uZRrEEAAAQQQQCDEBAhbhdiCM10EEEAAAQQQQAABBJwmkJSUJOHh4RmCVldddZVcuHDBkuksXbpU6tWrZ8lYVg4ye/ZsiY6ODlqIzcq5WjnWTTfdJLVq1RI9crJMmTJWDs1YCCCAAAIIIIAAAggggEDICWgoKiYmJtt5X3+9SNlyIlWqilxzjch/E0Sye+6IB2qyZeUCBBBAAAEEQlKAsFVILjuTRgABBBBAAAEEEEDAGQK6k1Wwd13q2LGj647X49hA617/kydPlqioKOsGZCQEEEAAAQQQQAABBBBAIIQE5syZI82aNcsw47AwkTp1RR5qIFL7PpFy5UQKXpcR5tBBka8WijzTNXO0wYMHS//+/UNIlakigAACCCCAQHYChK2yE+L7CCCAAAIIIIAAAgggEBSBZcuWSa9evXweb1e8eHH5+eefTa+ratWqonUULlzY9LGsGkCPC2zevLnojmE0awQIXFnjzCgIIIAAAggggAACCCAQWgLr1/9XHn64vhw9+qfXxCPqiXz0ichNJfz3iJ8p8vogkRMnRI4cznjfJ598Iu3bt/e/Q65EAAEEEEAAAVcLELZy9fIyOQQQQAABBBBAAAEEnCkQFxfnOd7OV7vjjjtkx44dpk9Mj4Dr2bOn6eNYOcCgQYMkNjbWyiEZ6/8FNm3aJNWqVcMDAQQQQAABBBBAAAEEEEDAEIGj8lDDSvL1V7959XZtQZEFi0TurZ37QRo+ILJksff95cuXky1btsq1116b+465EwEEEEAAAQRcI0DYyjVLyUQQQAABBBBAAAEEEHCPgB4BoEcBpG+VKlWSEydOyJEjR0ydrNuCVrqLlYbXdJcuWnAEChYsKN999x2Bq+DwMyoCCCCAAAIIIIAAAgi4SOCy7JcP4x6UztHfZ5jV4DdF+rwU2GQ/ihPp7OP5r+7du8vYsWMD65y7EUAAAQQQQMAVAoStXLGMTAIBBBBAAAEEEEAAAfcInDx5UsqWLSv6Z9qmR/rdd9998p///MfUybrpyDcNWeluVrpTGC34AmXKlBHd4cpNx1IGX5UKEEAAAQQQQAABBBBAINQETp+rLnXu3SRbt3jPPLy6SMJKkXz5AhM5f16k0j9FfjyQsZ8VK1ZI7doBbJsVWGncjQACCCCAAAI2ESBsZZOFoAwEEEAAAQQQQAABBBD4W2Dz5s0SHh6egbk3xxsAACAASURBVOOee+6R1atXm8rklqAVIStTXyYBdV6yZEk5ePBgQH1wMwIIIIAAAggggAACCCAQqgKXZLYMebO5vPpyRoGPp4u0edQYma+/Enmuu8j3+zP29+GHH3p2j6YhgAACCCCAQOgKELYK3bVn5ggggAACCCCAAAII2FJAg0K6s1X6VrNmTVm3bp0pNYeFhXmO2KtWrZop/VvVKSErq6QDG0df3xs3bmSHq8AYuRsBBBBAAAEEEEAAAQRCUODU7/2lSuUhciDdrlNtHxWZOt1YkANJIs/3FJk3J2O/sbGxMnDgQGMHpDcEEEAAAQQQcIwAYSvHLBWFIoAAAggggAACCCAQGgIaeoqMjMww2QcffFC+/vprwxEiIiJk9uzZjg6+ELIy/GVheoeFChWS5cuXOz7gZzoUAyCAAAIIIIAAAggggAACaQTen9RUunSe62VSoIDIsv+KVMu4SXbAdu+9KxLT3Xc3S5culXr16gU8Bh0ggAACCCCAgPMECFs5b82oGAEEEEAAAQQQQAABVwuMGjVKevXq5TVH3XmqUqVKsmrVKkPnHhMTIzqeU9vJkyc9VnFxcU6dglfd1113nRQrVkyuvvpqOXPmjOj89E83N7ccXenmNWJuCCCAAAIIIIAAAgggYB+BBx64UxYv3u5V0KuxIq+atMnU7FkibVr4nn+JEiVk0aJFUrlyZfsAUQkCCCCAAAIIWCJA2MoSZgZBAAEEEEAAAQQQQAABfwV0K/5BgwZ5Xd66dWuZOXOmv134dd2QIUOkX79+fl1rt4s0hDR69GhPUEz/2cmtdOnS0qxZM+nZs6eUKVMmw1R+//13+fnnn+XIkSOeP/Vr3759Mm/ePPnhhx+cPPXU2jt06CDjxo1z9O5qrlgIJoEAAggggAACCCCAAAK2FkhISBDdnTptq1BB5L9rRIoWNaf0b74WefihzPueNm2atGvXzpzB6RUBBBBAAAEEbCtA2Mq2S0NhCCCAAAIIIIAAAgiEpoBuwa/Hq6VtL774orz99tuGgTRo0EAWLlxoWH9WdqRBNKeHrJo2beoJVkVFRQV0jJ6GrfQpYv1asGCBnD9/3sqlMHQs3bltxYoVBK4MVaUzBBBAAAEEEEDgb4EXXnhB4uPjPT97zpo1CxYEEHCoQN++feWtt97yqn7kGJFne5g3oSmTRZ7qlHn/w4cPl969e5tXAD0jgAACCCCAgC0FCFvZclkoCgEEEEAAAQQQQACB0BUoW7asJCUlpQLoEYKdOnWSkSNHGoaiuyI98sgjhvVnRUdTpkwR3fUrrY0V4xo1hu5gpbtXacCqcOHCRnWb2s+lS5dk6dKlsmTJEk/4auPGjYaPYXaHt912m6xevdoUH7Nrp38EEEAAAQQQQMCuAr7CGfozqR7nTEMAAWcJtGzZUr744ovUokuXEdlr8obHQwaLxL6auZM++NOwYUNnQVItAggggAACCAQsQNgqYEI6QAABBBBAAAEEEEAAAaME9Ei8IkWKeHXXsWNH2bNnj6xatcqQYRo3bixz5841pC8rOlm2bJnnWEX902mtatWqojuV6TGB+qeVTY8aVDMNYGn46rfffrNy+FyPxVPRuabjRgQQQAABBBBAwKdAyZIl5aeffsrwvRMnThBy5zWDgMME9D3m1q1bU6t+IkrkA5Nzk92fFpk43jfUXXfdJevXr3eYIuUigAACCCCAgBEChK2MUKQPBBBAAAEEEEAAAQQQMERAwzGRkZFefY0ZM0aee+45Q/rXTpyyq5XuYKUhq7i4OMPmbnZHugtZ2nCVHhVoh6bHC+prS78WL14s69ats0NZPmvImzev50jEhx56yLY1UhgCCCCAAAIIIOAUgeTkZLn++uvlwoULGUoeN26cPPvss06ZCnUigICIFChQQM6dO5dqEf2kyIQPzKVp0UTky3m+x5gwYYJ06dLF3ALoHQEEEEAAAQRsKUDYypbLQlFmCfxx4bJ4/ueyyGUR7z8v63f0L9N+L921//+9PCKSR//X///597/nkZS/T/0z9Rof35M8kjePSN68Innz/P3PNAQQQAABBBBAINQF9Jg8DRilbf/5z3/kmWeeMYTGKbtaqcGoUaNEd/pyQtPdx1J2rzLjiECjDXbt2iXffvutTJo0STZt2iSX9Q2CjVpMTIxn/WkIIIAAAggggAACORfQhxb0CG5tn3zyiezdu9dnJ/fee6+sXLky5wNwBwIIBE0gPDxcNm/enDp+pTvyy+bt/wtfmVHYrWVFDiRl7LlRo0Yyf/58M4akTwQQQAABBBBwgABhKwcsEiUGLnDpssjFvy7LhUuX5djpi351uHpFgqxZkZB6bclSpeXQjwe87j108ECGv6t0ZxUpVKiwVLqzqhQKKyyHfkzKcE1mBXgCW3n+DnJ5vuTvIFba8FbelGBXHvFscx0eXs3z/bRNdxSoVq2aX/PkIgQQQAABBBBAwA4C+oHIgQMHZODAgbJ8+fLUkvSIgPvvv19GjhxpSJl239Vq9uzZ0qtXL1EPJzT9uVNDQVFRUU4o12eNR48elQEDBng+iPv9999tMY8SJUr4POrGFsVRBAIIIIAAAgggYHOB6Ojo1N1hdVerY8eOZVrxrFmzPA8N0BBAwBkC+n45/YMpLVuLvBorUqmS8XNY9q3Ig//O2G/+/CLbt++XcuXKGT8oPSKAAAIIIICAIwQIWzlimexVZNoPv/RDIF8fBOmTBVY8ha9ho6rVqsmlSyKXLl8WDVX9pX96/v3vv9OdqlKCT4nbtsip5P/tDpC4Xf89ORV49Yr/fbBnL/XAqtHgVcoOA/pnShAr5e8JZwXmy90IIIAAAgggkDsB/Zlxzpw5ogGjlCdTr7zySrl48X/heN3hZ+3atbJq1arcDZLmLjvvaqU/U+uHQnrMnVOaBuH0iEM3hfxfffVVT7DvzJkzQV8G3XHLTbZBB6UABBBAAAEEEAgZAT2W2d+dS1u1aiUzZ84MGRsmioAbBEqWLJnh4ZQiRUR69xGJ6SWSL59xsxz4isibb2Tsb9E398iD9QP/PYVxldITAggggAACCFgtQNjKanEHjKcf9GzZssXzgVdKmCqzUJUDpkOJORSoV6+e5w79M20wSz9Mc8KRMDmcLpcjgAACCCCAgMUCGq7SQJEGrPzZvenjjz+Wxx57zJAq7bqrldOODNTF0BCcHvnoxp8P9aERfVJav5LTPJhhyIswB538+9//lsWLF+fgDi5FAAEEEEAAAQQQUIGrrrrK6wGO7FTWrVsnNWrUyO4yvo8AAjYRePPNN+Xll1/2WU14dZG3R4jU/ftjjoBaYqLIPXeJ/PGHdzcv9RcZMnie5JFHAuqfmxFAAAEEEEDA2QKErZy9fgFXrx8k6E5VGqzSD72s2pEq4MLpIGgCKbthpQ1jlS5dWsqUKRO0mhgYAQQQQAABBOwtkLJ7lQascrr76bRp06R9+/YBT7BBgwaycOHCgPsxsgP92Vt3s0rZ1cvIvs3qS3/u092sUgL6Zo1jh36DHbq65ppr5MiRI64MtNlhfakBAQQQQAABBNwroD9H/fnnn35PsG/fvjJ06FC/r+dCBBAIrsDp06fl7rvvll27dvksRI/4GxD7905XuW2rVoo81Ulkz27vHuo/KLJo0WeSV1rntmvuQwABBBBAAAGXCBC2cslC5mQaGq7SD7pSwlU5uZdrEchKgCAWrw8EEEAAAQQQSBEIJGCV0ofurFm/fn0ZMWJEwLB22tVKQzwpu1kFPDELO+jYsaNntyc37maVFaOuV8+ePWXKlCkWav891MCBAz07iNEQQAABBBBAAAEE/Be49tpr5ezZs37fUKFCBUlMTPTsiEVDAAFnCLz77rvSvXv3LItt2Vpk+mc5n8/E8SJ9XxQ587v3vdXvKijr138ieaRJzjvlDgQQQAABBBBwnQBhK9ctacYJ6YcDaT/sCoEpp07x5ltKSclb/Ntxac3KBFNorisUJpUqVzWlb387Tdy+RU6fSvb3clOu0yBW2q+IiAhTxqFTBBBAAAEEELBOQH/OTBu80WMBNZCiOx/5c0RgdpXqUXVr166VVatWZXdplt/Xn0E2bdoUUB9G3awPPOhuVkb4GFVTdv2E0m5WWVno61rXzsoWFhbm2fmMXWStVGcsBBBAAAEEEHC6QKFChUR3vslJmz59ujz66KM5uYVrEUAgyAItWrSQWbNmZVlFTgJXB38UGfamiIatfDXdyKBu3bpBnjXDI4AAAggggIBdBAhb2WUlDK5DP/jSD7pSdrAyuHvLu0sbmioUFiaV7vxfeEmDTIXCCqfWdM99xv2we+jHA3Lo4IEM8y2kAao0NVgOYtCAp5JPSuL2rV69HfoxKXXOidu2yKnkZDEriKYffOoRNPqn7lyhf9IQQAABBBBAwP4CGv6IjIz0HAk4efJkKVKkiGfHIw0SGdlmzJhhyAce2k/btm2NLC3HfTl1NysNvOnOSqG2m1VmC6zvr6KioiQ52boHGewUFszxC58bEEAAAQQQQACBIAgULFhQzpw5k6ORW7duLZ99lostcHI0ChcjgICRAvrfuQauvv766yy7zS5wteK/IjOm/f2V2Vs9ffhGd3umIYAAAggggAACKQKErVz2WkgJWOmHAHZutWr/LxB1T500/3zf/3Y7qlS5ileIys7zCYXaUoJnGsA6dDBJErdtFTN2zNLwVdoAFk/xh8KrizkigAACCDhJIG3Qyuy6NcgV6E5C119/vRw9etTsUrPsX82aN2/uqN2sNAivATr9uYzmLaDrqS5WBq44TpBXIQIIIIAAAggg4L/ANddcI3/++af/N4hI3rx5ZceOHVKxYsUc3cfFCCAQXAF9v9+sWbNsd8TWwNXTz4gcOyZy6JDI4Z9Efv5Z5JefRb5dkvUc6tevL998801wJ8roCCCAAAIIIGA7AcJWtluSnBekOwikhKz0iflgtZQAVdqdp9LuOmXkjlPBmiPj+hZYvSJBdEcsDV+t/m+C7NzhvVtWIG66i4J+mKVvmPToQcJXgWhyLwIIIIAAAoEJWBm00qPr2rVrJ0OHDg2o6IYNG8qCBQsC6iOQmwcNGuTZGcopTY+t69mzp6NqDoat/regO1xt2bLFsuGXLl1K+M0ybQZCAAEEEEAAAacKfP/991KhQgW5fPlyjqfwxhtvyMsvv5zj+7gBAQSCK5CUlCRNmjSRbdu2GV5I586d5f333ze8XzpEAAEEEEAAAecLELZy6BpqqGrOnDmeD0H0B0mzW0qQKmUXqpQQlVuO0zPbLxT71wDW6hXLRXfC0n8+fcqYo1b0GBUNXjVt2pRjB0PxhcWcEUAAAQSCJmBl0Eonqdvz79mzJ9unU7MD0d2xNBRjddOf0fXp1/3791s9dK7H05+vdDcrwu3+E+prSx98saLpumzatIkjHa3AZgwEEEAAAQQQcKyAPqzRr1+/TOvPkyeP6DGDp0+fznBN9erVZcOGDY6dO4UjEMoChw8f9oSiJk6cKPrPRjQCmEYo0gcCCCCAAALuFSBs5bC11Q+5Ro8eLXpMoJG7WN18SykpeUsZqXTn30f33fP/x/mxG5XDXiA2LlePIfSErwzc/Up3vdLgle58pR8O6r/TEEAAAQQQQMB4AauDVjoDPcbOiF2DfvjhB0vDQ/pAhP5Cdt26dcYvhEk96i5iGrLSn6toORfQncD0PZoVLSYmxrNWNAQQQAABBBBAAAHfAhqY0oB6Zi1fvnzyyCOPSHx8vM9L5s+fL40aNYIXAQQcKmBE6Kp8+fIyYsQIz2cONAQQQAABBBBAIDMBwlYOeW3ohzb6S3U9MjDQprtUaahKd6cqWaqMEKgKVJT7cyNwKvmkJG7f6glg6dGDa1Ym5KYbr3vSHjeoO2DREEAAAQQQQCBwAauCVtdcc4388ccfgRecpgcNEVmxC6w+BKG7G+kvYw8ePGjoHMzsjCMDjdHV92iRkZHGdJZNL7q7lQYIaQgggAACCCCAAAIZBfR36Nk9QKC7WunP7V27dvVJ2KVLF5kwYQK8CCDgcIELFy7IL7/8IkePHpXp06fL8OHDs51RiRIlRP9vwFNPPSX6zzQEEEAAAQQQQCArAcJWNn996Ic2gRwVePsdVaTSnVU9wSoNVek/0xCwo4CGr75eMNdz5KD+Geixg/pBlO4yoE+fcBSOHVecmhBAAAEEnCAwaNAgz8+iVrQbb7zR84tQI1tERIQhDyv4qkkDVrqbke6sqUZG7jprpEFmfXFkoLHK+hrQ/16saLpTAw8WWCHNGAgggAACCCDgNIEOHTrItGnTsiy7SJEisnHjRqlQoYL89ddfGa7V9yU7d+4UvY6GAALuEfjmm28879lWrFiRYVKErNyzzswEAQQQQAABKwUIW1mp7edY+mS0hqxyelSgHgWox/9psEpDVexY5Sc4l9lSIHHbFvl8xkeeXa927tgaUI36RFtUVBTb/gakyM0IIIAAAqEkoLtBNW/eXHRXK6ta0aJF5fjx46nDGbHTlVlHrlm125cZ9no8o+6YqzuC0owViIuLk+joaGM79dGbWa9r0wtnAAQQQAABBBBAwESB3bt3S+XKleXixYtZjqJhqp9//tlzVODChQt9Xjt58mTP7xJpCCDgPoGtW7d6Ape///67J3SpD2rrl/4OgoYAAggggAACCOREgLBVTrRMvDbl6BH94MPfo06uKxTmCVQ92KiJJ2RVslRpEyukawSCJ3DoxwOe4wZ1x6tvFs7LdSH6pkl/UdKxY0d2u8q1IjcigAACCLhdQHdrcuJOTb7WZeTIkZ6dLo1sTg1a6ZGB+l6DD42MfDVk7EtD/np8jZlNd1M7ceKEmUPQNwIIIIAAAggg4DiB119/XQYMGJBt3SVLlvQc/a3vFZ5//nmf1+susPogNA0BBBBAAAEEEEAAAQQQyEyAsFWQXxv6i3h946ZPQfvT9FjAe+powKopO1f5A8Y1rhT4+7jB5fL59Km5Pm5Qd3NICV65EolJIYAAAgggkEMBDfzrrjy6y6pb2tKlSw3dwUkfkAgPD/f74Qi7OA4cONATOtOQDs1cAX2NaMA/OTnZ1IHYbcFUXjpHAAEEEEAAAQcK3HnnnbJ9+/ZsKy9Xrpzs379fEhMT5Y477sj0ej1KsGLFitn2xwUIIIAAAggggAACCCAQmgKErYKw7vpBlh4TqAGr7HaxYveqICwQQzpKQINX+hU/Y2qu6tYPHTV0pcex6AdjNAQQQAABBEJRQANWemygBkXc1IwOW6mRk55w1908dZcyfsax9lWt5oMGDTJ1UHZbMJWXzhFAAAEEEEDAYQIzZ86UNm3a+FX1bbfdJrt27fJcqw9jLl++3Od9Q4cOlb59+/rVJxchgAACCCCAAAIIIIBA6AkQtrJwzfXIEf2luz8f0Nx8Synp1PU5adXucSkUxhPoFi4TQzlU4FTySU/oSne7WrMyIVez0NCV7vzAB5K54uMmBBBAAAEHCujPp7169XLFblYFChSQs2fPeq2CkWErPYJPrZzQIiIiPCEr/fCIZr2AVbtbbdq0SapVq2b9BBkRAQQQQAABBBCwmUCrVq0kPj7er6oqV64s27Zt81z7xhtvyCuvvOLzvnvvvVdWrlzpV59chAACCCCAAAIIIIAAAqEnQNjKgjXX3as0ZOXPUYG6k1Wnbj2kZ59XLaiMIRBwp8ChHw94glcfThgjPx38MceT1NDVyJEjOWonx3LcgAACCCDgJAH9GVWPxHPLbla6S+Xo0aO9lsCosJVaVa1aVU6dOmXrJS5durRoKKxZs2a2rjMUirNidysNWmngioYAAggggAACCISywIYNG6RGjRp+E1SvXl30Hm3r1q2Tu+++O9N7dderunXr+t03FyKAAAIIIIAAAggggEDoCBC2MnGt9YMrDVnpBx7ZtZSQVaeuPdjJKjssvo9ADgQSt22Rz2d85Nnx6vSpZL/v1OMF9UMy/eCWhgACCCCAgBsF9OjAyMhIV0ytUqVK0rp16wxHtxkVttKn2levXm1bq7CwMM/PLT179rRtjVqY7qQWHR3t+VODQrqjqFuDYfpesEiRIl7rkTdvXrl06ZKha6Q/q/rzftPQQekMAQQQQAABBBCwkUDv3r3lnXfe8buiWrVqef1sX7NmTVm/fr3P+3Vn25z07XcRXIgAAggggAACCCCAAAKOFyBsZcIS6i/W9al6/aV3djsFELIyYQHoEoFMBHS3K/2KnzHVbyP9IFB3ueIYHr/JuBABBBBAwCECGnrxZ+dVJ0xHQ1X6c3fz5s29yjUibPXWW29J3759bcmgISsNWOmXBsXt3PS1ph9WpX9/pKG/9E136HL6sc5WhhmNeJ3b+bVDbQgggAACCCCAQGYCv/76q1SpUkWOHDniN9K//vUvSUhISL3+5ZdfljfffNPn/eXKlZPExETJly+f3/1zIQIIIIAAAggggAACCISGAGErg9d5ypQpng87CFkZDEt3CBgooMcM/r3b1Ud+HzOo/11r6IqGAAIIIICAGwTcFLTS9Zg+fbo0aNDAs0uSHvWR0vT/dwey29POnTtFn3Q/c+aM7Za9Y8eOnt2s7B5K0vdFGrLKTbDP6aF3DeunfT2a9SLS14AeJ2j3wJ1Z86dfBBBAAAEEEAhdgTFjxvjclT5//vxy7tw5nzD333+/LFmyJPV7GlzXv8uszZgxQ9q2bRu6yMwcAQQQQAABBBBAAAEEfAoQtjLohZGUlOQ5EsPXk9nph4ju2l169nmV4wINsqcbBAIR0MCVHjG4ZuX/nmjLrD/9wG/WrFm2/1AzEA/uRQABBBBwv4Dbgla6YimhKg0f6THeKU2PqdO/y2177bXXPEfdWd2uvPJKuXjxos9hIyIiPMElu4estPi0xwbm1lB//tIgkRObBs00cLVlyxbTy4+KipLJkyebPg4DIIAAAggggAACdhLI7LjvUqVKyY8//uiz1Iceeki++uorr+/ddtttsmfPHp/Xa9BKA1c0BBBAAAEEEEAAAQQQQCCtAGErA14Ps2fP9gStstvNquWjj3tCViVLlTZgVLpAAAEjBVavSJBRw17PNnSlOwboB1m6cwYNAQQQQAABpwnoLk963LXb2ksvveQ5+sPosNXgwYPl1VdftYzriiuukL/++svneBqy0vk55WhjfZ0FsqtYWgQn73ClgTNds+TkZNNfR/pQAD+jms7MAAgggAACCCBgE4G5c+dK06ZNfVZTo0YNWb9+vc/vNW7cWPTetK179+7y7rvv+rxejxDUHW/Lli1rk5lTBgIIIIAAAggggAACCNhBgLBVgKvgz84AhKwCROZ2BCwUSNy2RT6cMFbiZ0zNclQNXOkOAjQEEEAAAQScIqC7IenPrm5sKbv6pA+TBbqz1ZAhQ6R///5BJStdurQnZOWUnzv0AZTmzZtnuuOvzufAgQO5MlUDXVMn7OqVdoJW/benDwXoMTgaTqMhgAACCCCAAAJuF3j00Ufl008/zTDNu+++W4oUKSKLFi3ySdCiRQuJj4/3+t6cOXOyDK2PGDFCnn/+ebeTMj8EEEAAAQQQQAABBBDIgQBhqxxgpb1UP0To1auX5wiPzNrtd1SRAUNGyD331c3lKNyGAALBEvBnpyv94DMYRwsFy4RxEUAAAQScK6C764SHh9tyAlkdmedvwQ0aNJCFCxd65qhzTWmBhq2GDRsmumtWsFqg9Vtdd1Y7/oaFhXlCYxqI0zXSLz2Kfc2aNbJy5Uo5deqUX+VqoEj7iImJEf1npzTd3Wr58uWml6u7O+g60BBAAAEEEEAAATcL6DHNmQXMX3/9dVm1apUsWLDAJ4GGtKZPn+71vbNnz0r58uXl559/9nnPv/71L0lISHAzKXNDAAEEEEAAAQQQQACBHAoQtsohmF6uQavIyEivD3LSdnNdoTAZ8MZwadXuiVz0zi0IIGAnAQ1dvfZyb9m5Y6vPslJ20rBTzdSCAAIIIIBAeoH0IaRgC11zzTWiu0bpTlt67FmgIRT9oEV39NEn2NO2QMNKb7/9tvTp08dyrqpVq3oe6nDKDkXZPYiiRyDqfNLuSKUffqnvsmXLcuWrfY0cOdIxx+ZpsKxixYry559/5mq+Obnp8uXLObmcaxFAAAEEEEAAAccJ6AMR+mCEr6ZBrFdeeUXmzZvn8/uPP/64fPTRRxm+98QTT8jUqZnvdP/dd99JnTp1HGdFwQgggAACCCCAAAIIIGCOAGGrXLhq0CqzDwUeaNhYho/7QAqFOecp61wQcAsCIScw6q3X5cPxY+X0qeQMc9cP+nSHBRoCCCCAAAJ2FLDqCDN/537//ffLkiVLUi83Ysef4sWLy3vvvec5vi5tCzRspceFvPDCC/5Oza/r8ubNK5cuXcr02kBr9qsIAy/S90UamtMwUfqmu1np608DdSlt7969npDV+++/b0gV+vrRn8WcEEyrW7eu6Id0Zjbd8WvUqFFmDkHfCCCAAAIIIIBAUAU06F+lShU5ePBghjoefPBBz/GB+r4gs90+O3XqJJMmTcpwrwatNHCVWdNjBPX9AQ0BBBBAAAEEEEAAAQQQUAHCVjl8HXSMipaPpmQ8OlB3s9KQ1YONmuSwRy5HAAGnCBz68YC80L2zrFmZcdtwDVvpB300BBBAAAEE7CZQtmxZn0GYYNSpT5jrsR5pmxFhK+1PQ0qDBg3y6jvQ4JKGVvTocCNanjx5JKsdh9y2m5UeZ6dBq7RH/WnISr+OHTtmBKlXH/qzmK63nY8W1A/2Jk+ebPjc03aoO7zpf1M0BBBAAAEEEEDArQL6kMUzzzzjc3pjx46V7t27S6tWrSQ+Pt7nNd26dfM8qJG+6RGCepSgHinoq5UrV04SExMlX758bqVlXggggAACCCCAAAIIIJADAcJWOcDKLGhVq3ZdT9CqZKnSOeiNSxFAwKkCusvV6LcGZyhfPzzTYwVpCCCAAAII2EXATrtajR8/Xrp2AMvhuwAAIABJREFU7ZqBxqiw1b333iurVq3y6j/QsNWYMWNEdwoys+nuT7GxsY7aJVN3CdDdrHRXgfStdOnSnpBV2sCPXq8hq5UrV5pJ6QlaqaXZa5bbSbRp00ZmzpyZ29v9uo+wlV9MXIQAAggggAACDhbIbLdQPap8165doj+Ptm3bVj777DOfs+zRo4foz/m+mu7IOmfOnEx1ZsyY4embhgACCCCAAAIIIIAAAggQtvLzNTBgYKy8/pr3k/J6a3TX7jLgDbYP9pORyxBwjcDqFQnSrukDGeZD4Mo1S8xEEEAAAVcI1KxZU9avX2/5XK644grRnZo0XKI1VK5cWW644QafdRgVtipRooQcPnzYa4xAw1bjxo0T/TDGrBYREeEJJpUpU8asIQztV8NVGrLK7EgWDTlp2Clld6kdO3Z4QlZTpkwxtI7sOtMjBXXHUbvt8NSoUSNZuHBhduUH9P1AX/P/x955QElRbV//KCAoCKKoCAoiKBkEkRweGSVHiSI5SpSowgeSVBSRIEEySkayJEHyABIlSBAYcoYhZ761i3+PHaqqq7urqsPss9as96RvOPdXt2e6q/bdJ6DJ2ZkESIAESIAESIAELCawZMkSKV++vOosNWvWjBVY1a1bV6ZNm6barnPnzjJ48GDV10aMGKE4Y2kFvt/MmDHD4lVyeBIgARIgARIgARIgARIggXAgQLGVgas0bvwEadqksUfLb4eNlRp1tOu4GxiaTUiABMKYwOxpk6XLp808VkBHgTC+qEydBEiABCKIQP/+/QVl++yOChUqyJQpUwyXczNLbKW2zkCFJ3olSgLhGo5uVkOHDlWEVEbcrO7evas8wBowYIBmGZZA+BntC2cCiK5CRcym99DP6Jq8tQt0z3sbn6+TAAmQAAmQAAmQQDAJNGjQQKZOnaqawuTJkwWvI/Tade/eXQYOHKg6xuHDh+Xtt9/WXOLTTz8tOFCQKVOmYGLg3CRAAiRAAiRAAiRAAiRAAiFAgGIrLxfhwL9HJe97ueVajGuJDAqtQmD3MgUSCAECzRvUkBW/L3TJBA/0duzYYfghcwgsgymQAAmQAAlEEAGIYYoXLy47d+60dVUQEMGlCQIXXyKUxVajR4+Wli1b+rIcr23Dzc3q2LFjipvVn3/+qbo2dzcrnPSH0CoYjmpa8B2lBR2OW14vkkUNVq1aJSVLlrRo9CfD4nr88MMPls7BwUmABEiABEiABEggGAT27dsnOXLkkIcPH3pMnzp1atm/f788//zzymuffPKJprtqr169pE8fzwoWjkG9uZF+9dVXQTnUEgzmnJMESIAESIAESIAESIAESECbAMVWOrvj/sPHUqFSFVm+ZIFLq9IfVJQxU2ZzX5EACZCAIsQsnOsduX4txoUGXQW4OUiABEiABIJFAEIrLWGMVTlVrlxZEVr5I2YJZbHV2LFjpXnz5qZgC0c3KzyEgnDHiJvV9u3bFZGVVrkWUyAGMAjE8BBdNWzYMIBRAu+aJk0aOXHiROADaYwAMZ/d73/LFsOBSYAESIAESIAESMCJwJdffin9+vVTZdKmTRtBCXBHNGnSRMaPH6/a1ptYatiwYdKuXTtN9iiXbvfBFm4EEiABEiABEiABEiABEiCB0CNAsZXGNXksIlv+Piz5c3jaBq/bflBeT5M29K4mMyIBEggKAbVygnjYfPToUb8eOgdlEZyUBEiABEggIghAZAGxlV3hr5uVc36hLLYaN26cNG3aNGCc4eZmhYdHcLPSeojk7GZ1/fp1+fbbbwUPrcIhsN9QWvDdd98NSroorfj5559bNjfFVpah5cAkQAIkQAIkQAJBJHDr1i3Jnj27HDlyRDWLlStXujiI4sAEDk6oxaBBg6Rbt26aq1ErJVi6dGlZsWJFbJ958+YJDpwwSIAESIAESIAESIAESIAE4i4Biq00rv31O4+kfYf2MmH0fydi0LR67QYyePjPcXfHcOUkQAIuBKI2rJX8hYpKjrde8XC3mjBhgmJbziABEiABEiABuwjolcsINIeECRPK3bt3Y4eB0ArirkBFK6EstoJbF0RHgcbq1asF6wz1gIPV0KFDFQcotUibNq3iYOZYy5QpU2TgwIFKyRZfA8J0NccsX8fxtz3eKxBd+ePG5u+c6Hf+/Hl59dVXAxlCty/FVpah5cAkQAIkQAIkQAJBJPDzzz9Ls2bNVDPImzevbN682eW1Vq1ayahRo1Tbf//999KxY0fd1biXEoSLa+7cuWP71K9fX/BZmEECJEACJEACJEACJEACJBB3CVBspXHtL1x/ILmzZZCTx6NdWixevUWyZM8Zd3cMV04CJBBLoGPLT2Te7GmK0937+QvJbzN/daGDMjV4IMkgARIgARIgATsIHDt2TNKlS2fJVEmSJJEbN264jL1jx46AhVYYMJTFVpMnTzal7Fw4CLAhnIOwDPtILZzdrKKiohQ3q7lz5wa032rXri3Tp08PaIxAOkNoBWEZ1mZnwJVhz549lk35+DF8mhkkQAIkQAIkQAIkEDkESpYsKatWrVJdEJxDe/To4fJa27ZtZcSIEartUSYQr+uFeylB3OObMWOG3LlzR+mWKFEi2bt3r7z11luRA5krIQESIAESIAESIAESIAES8IkAxVYauI5duifpUiR0eTX1G2lk/Y5DPgFmYxIggcgkcOH8OcmbJU3s4goU+Z9sWveny2LpLBCZ156rIgESIIFQJWClq5X7mnv37q3pfuQrn1AWW02dOlUaNGjg65I82pvJK+Bk3AaAuxRO9msJxJ3drC5duqSIrL7++mvT0kidOrUkTpxYDh48aNqYvg705ptvCgRxdrmPWV1KkGIrX3cA25MACZAACZAACYQyAZQIRBk/rYDLaqZMmVxehpj+xx9/VO0Cx6sWLVroLtm9lOBzzz0nvXr1ku7du8f2w2firl27hjI65kYCJEACJEACJEACJEACJGAhAYqtVOA+ePRY9h27IDnTu5Z3YAlBC3cihyaBMCOwfWuUVP+gWGzWefIVlL82b/RYBR92hdmFZbokQAIkEKYErHS1ci8faLaY2EqxFcrEdejQwe+rOm3aNKlbt67f/R0dQ1VsNW/ePMXNSqucn7Ob1bhx46Rv375y/PjxgHm4D1ClShWBqAslDIMZyAN7BuIrq+Opp56ybAp+/rQMLQcmARIgARIgARIIAoHGjRsrwni1qFq1qqrbaqdOnZTPdWoxfvx4Q6XC3UsJ/vHHHwKHLUfkyZNHtm7dGgQinJIESIAESIAESIAESIAESCAUCFBspXIV7j54LGdi7ns4W7Xv+oV06PplKFw35kACJBBkAgf275VyRXLHZpG/UFGJ2rDWIys+7AryheL0JEACJBBHCFjlapUsWTKJiYlxoXj06FFTxSgQuMyfP9+SK7V69eqA3IpQKgSl7gKNypUrC4RNoRIQ50FkhdKBauHsZrVmzRoZNGiQLF261PL0P/jgA1m/fr1cv37d8rn0JnCUFkSZQasCY7u/t8yai58/zSLJcUiABEiABEiABIJNIDo6WrJmzSo3b95UTWXSpEny8ccfe7zWpUsXGTx4sGqfKVOmSP369b0uzb2UYK1atQTfhZwFVkbH8joZG5AACZAACZAACZAACZAACYQdAYqtVC7ZYxE5fvmevPmSaxlBiq3Cbn8zYRKwjMCpE8elcK63Y8fPmDmbHNi/x2U+lMU5efKkZTlwYBIgARIgARIAAStdrdwJW+HQBGFLnz59LLmYgYqtZs2aJXioEmiY7QYWSD5wjwJzb25Wt27dUh5QaTkCBJKDt75JkiSRGzdueGtm6etwt8LaIQa0IsqUKSMrVqywYmih2MoSrByUBEiABEiABEggCAS+++47+eyzz1RnTpkypfzzzz+CAyLugXJ/WqWvcaDCyGd891KCr7zyirRu3dqlnHqpUqUs+0wXBNyckgRIgARIgARIgARIgARIwAcCFFtpwLp444G8myW9QFDhCIqtfNhZbEoCEU7g6pXLkuvt12JXmTjJ83LzhqsLQ8aMGZWbPgwSIAESIAESsJKAVa5W7jnnzJlTdu7cafpSQllsNXfuXKlevXrAa3733Xdlx44dAY8TyAC4dnCz0rqGuL4TJ04U5Dpy5Ejp1auXXLp0KZApI6IvylxCdAUuZkauXLkseT8hR4qtzLxSHIsESIAESIAESCCYBAoWLCibNm1STaF58+YyevRo1de++OIL6d+/v+pr+IyP8oNGokSJEoIDHI6AIy9csZydWBcuXCgVKlQwMhzbkAAJkAAJkAAJkAAJkAAJRBABiq00Luad+4+l/scNZc70KbEtGrVoK736fxdBl59LIQES8JfA/fv35Z3Xkuh2//DDD2Xx4sX+TsF+JEACJEACJOCVAMrAFS9e3Gs7MxoE6hKllUMoi61Q+s/ogxhvjIMlgIGDFZzDfvjhB80UHY5lcFrq16+frF3rWRrZ2/qMvg7ngQ4dOijNrXI0M5qLL+2QMziZVVrwqaee8mV6n9oGa6/5lCQbkwAJkAAJkAAJkIAXAvhsCjdQrdATOeFzW9++fVW7Llq0SMqXL2+IPz4bf/nll7FtP/30U7ly5YpMnTo19t9q1KghcMRlkAAJkAAJkAAJkAAJkAAJxC0CFFvpXO8GTVrK1PH/nY5JmuwFWbf9gOB/GSRAAiSQKXUyuXv3jiaIESNGKPbiDBIgARIgARKwggBENOnSpdMsB2fmnA0bNlRcj6yIUBZbLViwQCpXrmzKsoMhgIFYrGPHjkqpSbVAeUPHdUWZlVGjRpmyVq1B8NALoiWHYAl54b/hEBAOgbwhWsP7IdCwUmwFFzWznbgCXS/7kwAJkAAJkAAJkICvBFq0aCFjxoxR7ZY5c2bZt2+f5pAQ9eN7hlosW7ZMV8Tl3GfDhg1SuHDh2H/KkiWLUp6wYsWKLkOvW7fOpZ2va2V7EiABEiABEiABEiABEiCB8CNAsZXONcuTN79s27rZpQVLCYbfJmfGJGAVgfcyppbLly5qDr9+/XopVKiQVdNzXBIgARIggThOwMoyZM5o4UQEUYxZjj7uly2UxVZwqDSrJIidYitcL4isILZSC1xTcIfQCeKhHj16yJ072gLyQN9qECdhvjfffFN1KDi0IZddu3YFOpUt/SFkQmlBlBj0N6wUW1nlQufvWtmPBEiABEiABEiABHwlcPbsWcmaNatcvnxZtWu3bt1k0KBBmsOihCBKCarFqlWrfHIHzpQpkxw4cCB2KNzv++yzzyQqKir235o2bSpjx471dZlsTwIkQAIkQAIkQAIkQAIkEMYEKLbSuXgFCxWSTRs3urSgu1UY73amTgImEyj2XiY5Hn1Uc1Q8MMyRI4fJs3I4EiABEiABEhBFRGNWeTtnnk8//bQ8evTIBTFEJY6yb1awD2Wx1e+//y4oC2xG2OU2NHToUEXYBOcztYBTF9yscEq/V69esn37djOWpzqGwzlLS2Tl3gl5Ya/FxMRYlpOZA3/yySeK6MofIaKVYiur37NmMuRYJEACJEACJEACJKBGYPjw4YKSfVqBz7IFCxbUfB1CLBwoUAtfD0fCtf6nn36KHQquWfj81759e5fhd+7cKTlz5uQFJQESIAESIAESIAESIAESiCMEKLbSudD58uWTLVu2eLTIX6iYTJu/PI5sES6TBEhAi8CHxd6X/Xt3awI6cuSIUt6JQQIkQAIkQAJmEyhevLjADcjqwAMEOB9ZGaEstkKJkXLlypmyfKvdhrAf4GaFhzxqkTZtWuVaouQKTvpPmTLFlHWpDQKRFa6rP85PEImhL0Rj4RB40IZ83R+26eWOa4X3sJUxYcIEgRiMQQIkQAIkQAIkQALhSACfI9esWaOaetGiRTVfc3T49ttvpWvXrqr9N2/eLHnz5jWMZdasWVKrVq3Y9pgf/wan4dOnT8f+e7t27cLmM6zhxbMhCZAACZAACZAACZAACZCAJgGKrXQ2R+7cuQUn0NXiy36DpXFL7dM13HMkQAKRT6BEvqxy9N/Dmgu9cOGCpEiRIvJBcIUkQAIkQAK2E7DSFcexGAhm7BB0hbLYauXKlVK6dGlTrq9VYiuIk3C6Xk8UByEQXKzGjBmjecLfjEVC0AV3Kn9EVu7zoxQixEJaD9nMyNfMMeDeBYGTkbXbIbayQyhpJj+ORQIkQAIkQAIkQAIOAvjcXKJECU0gEOVD2KQX33//vXTu3Fm1CZxdIZQyGhcvXpS33npLrl+/Htvln3/+kenTpyuie+c4ePCgvP3220aHZjsSIAESIAESIAESIAESIIEwJkCxlc7Fy549u+zZs0ezxbfDxkqNOh+H8eVn6iRAAv4SmD1tsnT5tJlu97t378ozzzzj7xTsRwIkQAIkQAKqBKwqIeg+mVXiIPd5rBSeBLqGVatWScmSJU3ZiYHmopbEpEmTlLJ7WiUDUcYEIqzLly9Lz5495cCBA6asxX0QiKzwoMkKJyXsD4wbHR1tSe5mDwqxVe/evXVFV3a8h+lsZfaV5XgkQAIkQAIkQAJ2EWjVqpWMGjVKdbpkyZLJ3r17JXXq1LrpQJClVQod9/uzZs3q03KqVKki8+fPj+2DsoKVKlWS999/38XdqmXLli4lB32ahI1JgARIgARIgARIgARIgATCigDFVjqXK1OmTF4fSCxevUWyZGct9rDa9UyWBAIkMGH0cOn7ufrpOMfQ8eLFkwcPHgQ4E7uTAAmQAAmQgCcBCE8gsrEyGjZsqDgU2RGhLLYyM7chQ4ZoPvDxlTNKBaJkoJ7zGAQ/1atXV0RQc+fO9XUKQ+3xsAsPsfCDcnpWBkRjWEtMTIyV05g2tp7oyko3NywA4jc4gzFIgARIgARIgARIINwI3Lx5U9KkSaMcFlCLxo0by7hx47wua/jw4fLpp+pVKXAA4Z133vE6hnMDfBbF529H1K5dW6ZNm6Y4zLq7W+GQANbAIAESIAESIAESIAESIAESiGwCFFvpXN/06dPLkSNHdHdA0mQvCByuynxYKbJ3CldHAiQg12KuyldfdBG4WnmLRIkSye3bt7014+skQAIkQAIk4DOB5MmTazoZ+TyYSgcIaCDUsFo845jaTEGT+3ICdZNau3atoJyiGQHxk/uDGF/HNVIyEPmOHj1apk6dKv369fN1CsPtsR47RFbOCWH9mNNqsaFhCAYaqomu3J0RDAzjUxMz9ppPE7IxCZAACZAACZAACZhEwF0kBQcqOFk5YvHixfLhhx96nQ3OU61bt1Ztd/ToUUEJaF/ir7/+UlysHIHvTGfPnlVEYe7uVoF+B/ElL7YlARIgARIgARIgARIgARIIHgGKrXTY40Tw8ePHDV0dlhQ0hImNSCBsCURtWCtfff6Z7Nuzy9AakiZNGjbOC4YWxEYkQAIkQAIhQQCORrly5bI0F7uFGqEstlq/fr0UKVLEFN6BckXpOZym13IswgMfiLleffVV6dq1q5w8edKUvN0HgesZ5vH1AZWZyeB9ANHVmjVrzBzW0rEguoIrHfg99dRTls515coV28SSli6Eg5MACZAACZAACcQ5AgULFpRNmzbFrhufO/H5Fz9ly5aV7t27G2IyZswYadGihWpbfE72VoZQraN7FYzff/9dypUr5+Juhc/iy5cvlxw5chjKk41IgARIgARIgARIgARIgATClwDFVjrXLlWqVHLmzBnDV7dxy0/ly36DDbdnQxIggdAnADerod/2k/GjhvmU7EsvvSQXL170qQ8bkwAJkAAJkIA3AlaXH7Pb1QrrDWWxFR704IGPGeGv2MpIycDKlSsr4qNBgwbJsmXLzEjXYwx8thk/frxUqhQ6jr4QoGHdKNUSLgGRmpUl/uwsARouzJknCZAACZAACZBAeBDYvXu35MyZ0yVZuFplyZLF5wWg1GDTpk1V+507d05eeeUVn8fEeM4lDHEQ4vvvv1fG+fXXX+XQoUNK/nAxZZAACZAACZAACZAACZAACUQ+AYqtdK7xyy+/7CGWGDJkiEt9dvfuWbLlVMoKZsnu+sUw8rcSV0gCkUdgzvQp0vfzz5Tygb7Ga6+9JqdPn/a1G9uTAAmQAAmQgC4BuFpBfGNV+CsICiSfUBZbbd68WfLnzx/I8mL7+srWSMlAOPEOGDBAUNYE31OsjmeeeUbq1asn33zzjaRIkcLq6QyPDxHiDz/8QFdREWHZGsPbhg1JgARIgARIgARCjADES/hM54iaNWvKzJkz/cpy4sSJ0qhRI9W+/rqAopQ1nEod8dZbb8m///7rV37sRAIkQAIkQAIkQAIkQAIkEP4EKLbSuYYvvPCCyw37+PHjy/3790Xvy5pjuA5dv5T2Xb8I/x3CFZBAHCQAkdUP33wlJ4/ruyTkypNPdvy1WZVQmjRpwsplIQ5eZi6ZBEiABMKOAMQ3yZMntzRvfx88BJqUVWXVAhWebN26VfLmzRvo8pT+vjgODR06VCnVh2uuFe3bt5f06dMLRFy4bnYGviehLEv//v0lXrx4dk6tORdYweUKD8HiakB8Z6VrVlzlynWTAAmQAAmQAAnYQ6Bu3boybdq02MkgtILgyp+YMmWKfPzxx6pdb9y4IYkTJ/Z5WAirMmTI4NLv77//lmzZsvk8FjuQAAmQAAmQAAmQAAmQAAmEPwGKrXSuIb503bp1K7YFSj4cPXpU+e/vR4yTzm3VrYgdHV5Pk1Yguqpeu0H47xSugAQinADcq+ZMnyrjR//oVWQFFHCwi58ggXRs+d+JNmdEePh5+PDhCKfG5ZEACZAACdhJACXTqlatatmUxYoVU0r6BSNCVWy1fft2ee+990xBYoQv+OMEvp5gBoKaLl26yPTp02X9+vWm5ObvIHAChuCqWbNm/g5hej8whFBtzZo1po8d6gNCgOfsBhHq+TI/EiABEiABEiABEnAm0KdPH+VzHKJMmTIBlcdGWT84sqrFvXv3JEGCBH7BL1CggERFRcX2PXjwoLz99tt+jcVOJEACJEACJEACJEACJEAC4U2AYiud64cyGXCyckSRIkVk7dq1yn8ev3xPNq5fK80b1JDr12J0d0H+QsUUl6v8hYqG925h9iQQgQRW/L5Qli9ZoPwYKRf4fNJkMmbKbOX9vHLpImlWv7oqlcyZM8u+ffsikBiXRAIkQAIkECwCePCABxBWRTCFGqEqtkLJRpRuNCP0xFaYB2VTvIndILKKiYmRMWPGmJGSaWOgfDKcuwYOHGjamIEOBDdivGeio/WdSgOdJ5T6T5gwwaW0TSjlxlxIgARIgARIgARIwAgBx/cdfLbEwWd/Y8aMGVK7dm3V7o8fP/Z3WOXzevHixZX++fLlUwT+CRMm9Hs8diQBEiABEiABEiABEiABEghfAhRb6Vw794c+sDL+5ZdflB7Rl+4Jvpbt+3uXfNa2qezfu9vrLqDTlVdEbEACthDYvHGdLF8yX2ZPm2JIYOVIqlGLtopbXdJkLyj/tGn9GqlbpYxqzjly5JBdu3bZsh5OQgIkQAIkEDcIFCxYUDZt2mTZYn/77TepUqWKZePrDRyqYqvdu3dLzpw5TWGiJraCgxUeKEEYpBfIAaf7UV4QJ/FDNZIlSyb4zjRgwABBqcFQCAiu4PYEkVqkR6BlMyOdD9dHAiRAAiRAAiQQdwjMnj1btQQhDlffvXs3IBCXL1+WQ4cOKWIrBgmQAAmQAAmQAAmQAAmQQNwlQLGVzrV3f+jTrVs3GTRokNLj2KX/HnLADeeHb76SCaOHG9pJEF3VqP2xUl4Q/59BAiRgLQG8R+FgFbVhrWEHK+eMUr+RRgYPH+fhTrd75zapXKqgavJ58uSRrVu3Wrswjk4CJEACJBCnCFglSHJARLnsQE6PB3IxrFpboOKTPXv2SPbs2QNZWmxfZ7HV1atXFeGUo0yK3gQNGjQQ5LFjxw5T8rBrkJo1a0rPnj3l3XfftWtKzXnAu0OHDjJp0qSg52JlAoG4NFiZF8cmARIgARIgARIgAbsJ4CBJtWrVPKZNnDix3Lhxw+50OB8JkAAJkAAJkAAJkAAJkEAEEqDYSueiuj/0GT58uLRp00bgNBx92fNEOYQcn7VtIqdOHDe8Vcp8WEnwA+EVgwRIwDwCcK+KWr9GEVhFbVjj18AQWcHJqkadj1X7Hzl8UErmV38AW6BAAdm4caNf87ITCZAACZAACbgT2Lx5s+TPn98yMGnTphW4LAUrrBJbBSo+2b9/v2TJksUULBBbzZs3TxFZwWkJAiC9wLwQvy1ZssSU+d0HwUn8TJkyWS5AQin2zp07S+XKlS1Zhy+DolwjRFco9xJpEez3cKTx5HpIgARIgARIgATCm8CCBQtUP3/CffXKlSvhvThmTwIkQAIkQAIkQAIkQAImEcBnYxzyhftr5syZg3YY26Tl2D4MxVY6yN0f+syfP18qVaokDx+JnLiiXr4DDjrjRw+T8aOGyfVrxktVoCyZQ3hV+oOKtm8ETkgC4U4AJT0VgdWGJwIrvBf9DYisILCC0Eovzp09I/mzvanaRK1UkL/5sB8JkAAJkAAJlC9f3jLRDeg2bNjQayk7K69C8uTJvYqP/Jk/ULHVgQMHFEGSGZEyZUq5c+eOoXWWKFFCVq1aZca0umNAzFW1alVZunSpQFhmZWAuOHlhrwU7/vzzT/nkk08kOjo62KmYNj/EbBDzMUiABEiABEiABEiABEQWL14sFSpU8EDxyiuvyLlz54iIBEiABEiABEiABEiABOI8gZ9++klat27twgGHvvPmzRvn2RgFQLGVDil3sVVUVJRSi/3Bo8dy8sp9Xcb+iq4wKIVXRrcv28VlAmaKqxwc8xUsKjXqNNB0snLnffPGdcn2ZgrVy1C2bFnlwSWDBEiABEiABMwgED9+fHn48KEZQ6mOMWTIEMXxJ1gRqs5Whw4dknfeecc2LBAkQSBmtwioYsWKkjRpUvnll18sX2soia4mTpyoCMDs5m1NpFUnAAAgAElEQVQF5N69exsqS2nF3ByTBEiABEiABEiABEKNAO7JffDBBx5ppU6dWk6ePBlq6TIfEiABEiABEiABEiABErCVgNYhY9wLR3WAZ5991tZ8wnUyiq10rpz7Qx9sOmyw+w8fy6mr+mIrx7Anj0fL7OmTfXa6cvSH8Cp/oaKK6xWEIK+nSRuue415k4DfBCBe3L/374DLAqolABcrvL8at2jn1/srXYqEquuCS8TcuXP9XjM7kgAJkAAJkIAzgSRJksjNmzctgwKr4Hfffdey8b0NHKpiq3///VcyZMjgLX1TXoeD1j///GPKWO6DtGzZUmJiYmTatGma46OkChzUcHrp8OHDluThPGioiK5QzhFlHfEDRuEaq1evlv/973/hmj7zJgESIAESIAESIAFTCaxYsULKlCnjMWa6dOnkyJEjps7FwUiABEiABEiABEiABEgg3Ajs2bNHsmfPrpr2zJkzpWbNmuG2pKDkS7GVDnb3hz7nz5+Xl19+We49fCynDYqtnIefPe2J6Gr/3t1+X+ws2XJK/sIQX1WWfAWL+D0OO5JAKBOAaxXeJygHiP+/b88uU9N9Pmmy2LKdEFoFElnTvCi3bnk+/K5bt64t7hCB5M6+JEACJEAC4UMArkPXr1+3JGF85n306JElYxsd1CqxVaAClGPHjgkeyFgZr776qmWlTNKmTauUh3SIcFA+Dw5mu3Zpf7bKkSOHvP7665aWrXTmCZEXhE7BLi8I0RXYTJo0ycrLbdnYgZbMtCwxDkwCJEACJEACJEACQSCAktwlS5b0mBkHqXGgmkECJEACJEACJEACJEACcZnA7t27JWfOnKoIPvnkE5kwYUJcxmN47RRb6aByf+hz//59QQmXuw8ey5kYY85WasNDPDJ+9DBZvmSBXL8W2Onp/IWKKc5X+QsXo/jK8LZnw1AiANeqzRvXKaIqRVy1Z5fg38wOh4MV3jOBCqycc8uT+Q25dOG8R7pNmzaVsWPHmr0MjkcCJEACJBBHCVglRnLgDLZQw6r1BSq2On78uECwZFU8//zzlono2rdvr5SVg5jJPSDAgrBIz8kpd+7cgsMmdpVZCRWnKwjswC3cRFfBdqez6j3CcUmABEiABEiABEjAHwJr1qxRdf3MmjWr4BQ/gwRIgARIgASsJoCDjbdv3479uXv3rlKWC8+Z79y5o/w7/g3tUOb2lVdesToljk8CJEACsQRwLxH3f9UCh3H1DusS438EKLbS2A1XrlyRF1980eVVx0OoO/cfy9lr/outnAeF4Ao/URvWyKkTxwPam46Sg0/cryi+CggmO1tCwLkcIERV+EGpTasCpTchrIIgMUt2dXVuoHMXfS+TnIg+6jFMu3btZOjQoYEOz/4kQAIkQAIkoBCwSozkwHv27FmBw1Kwwqr14QQOTuL4GxAavfHGG/521+wHp7Jr166ZPi4GdHez0prEUT6vT58+mnkkS5ZMcfbauXOnJbmqDQrR1ZAhQ6RKlSq2zak2EVzAILrCg7pQD1wnXE8GCZAACZAACZAACZDAEwLr16+XIkU8q0LkypVLtm/fTkwkQAIkQAIk4JUAxFBbtmxR7slBJJUwYUKJFy+eIpS6dOmS8oNDamfOnBHcV8MP/v/ly5f9PrhWqFAh5XBc9erVLb8X6BUAG5BAHCUAAeS9e/eU97xV96xDAe3WrVslb968qqlA/Hnu3LlQSDPkc6DYSuMS/fvvv5IhQwaXVx1iq9v3H8m5aw9Mv7gOZx+IrzZvXGvK+HDxyZI9h+B/UXYQgiwGCdhBwG5hFdaUOWsOpcymw/HNjv1erkhuObB/rwfSbt26yaBBg+xAzTlIgARIgATiAAE4IN24ccOyleKkCk6sBCus+uLau3dvRTDjb5w+fVo5XWhWQAgF8df8+fMtETDpuVlprQFOTriRh5y0IkWKFILvQriRaFeg9CGun6MEol3zus8TqqKrLFmyyKlTp+Tdd99VyjDifxkkQAIkQAIkQAIkQAJPCGzatEkKFizogQMPlDZv3kxMJEACJEACJOBBAAIL3CPZu3evLFmyRH755RfL3Mi94W/btq38+OOPES308MaAr5OA3QQgPho5cqTMmTNHee9DcARjje7duytCy0iLqKgoKVCggOqy8CzCqoPCkcaRYiuNK/rXX3/J+++/7/KqQ2x1694jOX/dfLGVeyooqQbHq6j1a00TX72eJq3A+crhfpX69TSCf2OQQCAEgiGsQr5wrnKICeFeZYe4yp1TtbJFZMe2LR744BLRq1evQLCyLwmQAAmQAAnEEsiWLZtys8eqWL58uZQuXdqq4b2OG6piK5zgSZkypdf8jTaAeKhWrVqC8iVmhlE3K705ISqCECw6Wtt1FO5ndp9qgsMVnK7geBXMmDdvnrRo0UI5tRoqgesF9zYGCZAACZAACZAACZCAKwE4keTLl88DS+HChWXdunXERQIkQAIkEEcJoGzf0aNH5fjx44qwCv//yJEjcvjw4ZBzPpw6darUq1cvjl4pLpsE7CXwzz//KC5PEFm5R/PmzWX06NH2JmTDbBs3bhS46WmFQxdjQyphPQXFVhqXb8WKFVKmTBmXVx2b6ubdR3LhhvViK/fUHM5XSvm1v3fJ/r27Tdt8EF85yhBiUJQhfP75pJaVXjMtcQ5kO4FgCaueT5osthygw7nK9sWrTFivWjnZuHa1xyvffPONdOnSJRRSZA4kQAIkQAIRQKBkyZKyatUqy1YyefJkadCggWXjexvYKrFVsWLFBCIif+PChQvKKSazAvnUqVNHWrZsadaQ4o+bld7kcEmCG1hMTIxms+eee05u3bpl2hqMDARhEURXL7wQXKfeYcOGSc+ePS11mjPCw9GGgitfaLEtCZAACZAACZBAXCGAUoHvvfeex3KLFy9u6fequMKX6yQBEiCBcCFw5coVxdEQDi5r1qwJ6B6R3WvGYb0ZM2bYPS3nI4E4SQCfG/VKTY8ZM0aaNWsWUWxwAKFo0aKaa0Ip1USJEkXUmq1YDMVWGlTxB6x27dourzrEVtfvPpJLQRBbqaUK9ysIr6wQYDnmgwjriRgr2f/97wuxIiyUJmRENoHNG9e57DHsNasDwqon7mtFY53YQtWBrVn96rJy6SIPJMOHD5c2bdpYjYrjkwAJkAAJxBECFStWlEWLPP/emLX8b7/9Vj777DOzhvN5nFAVW6FsHkromRUQCn344Yfy66+/BjykGW5WWklcvXpVKU0Hp06tSJAggdy/fz/gdfgyAPih5CEEZsEWXTVp0kQmTpwoKDMQ7ECpxd9++y3oTILNgfOTAAmQAAmQAAmQgIMAyqSrlVnG4eply5YRFAmQAAmQQAQSuHfvnuzfv1927Ngh27ZtU8S1+/btC9uVli1bVpYuXRq2+TNxEggXAhcvXpSXX37Za7pwTnWviua1Uwg3WL16tZQoUUIzQ7j/4f4zQ58AxVYafEaNGiWtWrVyedUhtrp256FcvvkwZPcWxFcnT0THCrAgjjl14ril+cJpCIGSbkmTvqC4ZGXJnlP5t8xZswelvJulC47QwR2OaU/Ee7uVMpZWR+asOZRSltgv2Eevv5E2rEpbtm/+sSyY63m6YPz48dKoUSOr8XF8EiABEiCBOEIAp9lmzZpl2WohtILgKlhhldgKpedgCe9vQHSUPHlyf7ur9nvjjTfkxIkTAY1ptpuVVjL4Ug1x0/z58zXzffrpp20XHOG6wn2rYcOGAXEMtDNu2sIRTu/kW6BzGO2Ph4m4SRJsEZrRfNmOBEiABEiABEiABKwksGfPHsmePbvHFBUqVJCFCxdaOTXHJgESIAESsJEAnKsgSFqwYIFMnz7dxpmtn6p06dKyfPly6yfiDCQQxwnAvT9x4sReKaD6wV9//SW4txsJsXLlSsHvGa1wruCEEqz//vuvoNxidHS0nDlzRrm/jR8IXV988UVJliyZPP/88wrLpEmTKi6zlStXFqvu+4fKNaDYSuNKDBgwQD7//HOXVx1iq5jbD+XKrdAVW2ltLghprl2LUQQ0J49Hm16K0NumdjhkoR3ENRDVIFCyEJH69TRhJbLxtt5QfN1RAhC5Ra1/IqSCsOpazJN9YWWkfiONvP7Gm4pb1RNB1ZtKWcBwj+4dWsqMqRM8ljFt2jQPd7xwXyvzJwESIAESCB6Bvn37Su/evS1LoGrVqjJ37lzLxvc2sJVfugKpL3/t2jXli2KohJVuVnprRClGiJtguR9KAYERSgvC2SmY8fXXX0v37t1tTSFevHjy8KHrd1IKrmy9BJyMBEiABEiABEgghAnA2SRLliweGQb7e08II/MrtbNnzyrlxd966y2/+rMTCZAACfhDAA7TuD+BA+9Tp071Z4iw6NOlSxeB2IFBAiRgPYH06dPLkSNHvE6Ez5fr1683/XCu14ktaAAxJxz09AICs2eeeUZOnjzpVwY9evQQaG4iOSi20ri6+CM2ePDg2FdxYttxM/vq7YdyNQzFVlobGaUIIbRRHLGOR8v+vbuDvuefiLHejM3DWZSjvJbmv9ficilDXLPr168pnE4eP6ZcP0fgujriiaDqquXX1VH+78k1SquUAISwyuFyZnkCQZig7+edZcLo4R4zwwGiUqVKQciIU5IACZAACUQigbFjx0rz5s0tW1qePHlk69atlo3vbeBQFVvduHFDOZETCgEXJ5StC2ZgfoiucIIplKJKlSqK6AqOV8EK3OjFYZ0NGzbYlkKiRInkzp07LvNRcGUbfk5EAiRAAiRAAiQQwgQOHjwoGTNm9Mjwo48+ijjnEysvw6ZNmxT3htdff91jmvr168svv/yi/HuqVKmkcOFc8t57RZXyjSjXyCABEiABswngYf+UKVNk5MiRfj/4NzunHDlyKGW24sePrzi5pEyZUiBOcPw8++yzgsNSeMaMHwTugTnug+GAoOOQIERk+HE8iy5YsKDSl0ECJGA9gcWLFwscUI0ESu/98ccfRpqGdJsffvhBOnbsaHmO58+fN1Sm0fJELJqAYisNsE2bNpVx48bFvvrcc8/JzZs3lf+GqxXcrSI5INSBkAciHQh4Nm/8T7gTyut2F2k5clVzUHIXbamty0y3LWdXKfe5FNcxFTHUtWtXlXJ+zmG1A5WR65uvYFFJmiyZIqKKJJcqI2t3bzO4fy8ZMeRrj64rVqyQUqVK+TMk+5AACZAACZCABwE4JtatW9cyMjiJDCvgYARK1aVLl86yqVFazV/nI6M20pYlL6I4a+HL7yeffGLlNIbHRmlF5IOfmJgYw/3saAghGEosBquUHiy1Ibj67rvv7FiuMkeSJEkEokDnwAOuCRMmKA+6GCRAAiRAAiRAAiQQFwngu02GDBk8lg6BEB7UM/QJ4L4mDvvgu5ojILiC8ArlGbdt26b8aEXVamWkTeuuUrJkSaImARIgAVMIXL58WTlgdf36dVPGC2SQ8uXLy+TJk5WyWQwSIIHIITBjxgxp1qyZod8zf//9t2TLli0sFn/79m05dOiQ7Nu3T/bu3Su7du2SzZs3C0RQdsSpU6cUYX6kBsVWGle2WrVq8ttvv8W+mjx5csEfc8Tlmw/l2p3IFlupYYkVX52Ilqj1a+XkiWNy6sTxSH1vxNl1OdypAAAl/xBwqEIZyCfCqiflHxlPCEBoBcGVe8DdoGjR8C+TyOtMAiRAAiQQGgR8OV3jT8YQp1y5csWfrgH3QYm64sWLBzyO1gCBiK0gnoF7ULAiZ86ciptVKIpmILqCuGno0KHBwqM6L/ayQ3QVrMRmz56tiK7gqGB14BTt7t2ezsTggL0finvHaiYcnwRIgARIgARIgAS0DnQ0atRIKTvFUCdw//59+eeff2TRokXSs2fPgDFB3NaqVSuBOwuDBEiABAIhMGjQIEE5KjMD7lNFihRRHFfgao7DTCiXNXfuXF33d5QQK1SokJmpcCwSIIEQIYCDt6NHj5bevXvriq5C0XADYqpRo0bJtWvXlJ8zZ84opRHtElVpXcKLFy/KSy+9FCJX2Pw0KLbSYIoHPnjw44jXXntNTp8+rfznpRsP5PrdR+ZfjTAd0eGCBfEVXJjghnX9Wmidcg9TtJam7RBVQVAVF8r9WQUTJQRRStA9UEKGNxKsos5xSYAESCDuEbBakASiDttyu+lavTY4/PjrCoWHDbjRFoxA2UC4RwXLpcnomvEgq0OHDoISyqEUOPGKa++vq1mga0F5A1hxQ3hldVSuXFmVPwVXVpPn+CRAAiRAAiRAAqFK4MSJE5ImTRqP9Fq0aKE8hGI8IXD27FnlGYhDWODsZGUmI7hE9OvXTymrxSABEiABfwigDOzMmTP96RrbB67ulSpVUg7J58mTR3HrU4vly5dL2bJlVV+DKAuHFVneL6BLwc4BELh06ZIcOHBAEdLADR9/W1E6OWHChAGMyq7uBOAGNWvWLBk+fLiq+BL3/VKnTh0y4NauXauUQQwF9z8HFPzOxb3ZSDcmodhK421QoEABiYqKin0VpU2g/kNcvPFAblBspfsLBKUHT56IVkoRUoQV/N+1FFZZdw1mTJ0g3Tu09Jhgy5Yt8v7771s3MUcmARIgARKIUwSsFiQBJm60v/rqq7ZztXptOIkEpyN/4uHDhxI/fnx/uvrdJ9TKBhpdCK4jTq7DGjqUAmIrfLGH+CoYUbFiRcUZwOooXbq04FSde4SC05fVa+f4JEACJEACJEACJOBOAIem1R6AtW3bVoYNGxbnge3cuVP69Okj8+bNs41Frly5lHLbVroa27YYTkQCJGA7gQ8//FB+//13n+aFMOqDDz6QcuXKKQex8JzXSGgJdtH3nXfeUYQuDBKwmsCjR49k+/btsmPHDtm/f7/s2bNH0S1oiWmaNGki33zzDctbWnBh4HYF1yiwf+655yRx4sQhVUIQlZaCddgUuPG7Nn/+/JIpUyblB78nUc4bgta4IEyl2ErjTYcP//jS4YjMmTMrbyTE+esP5NY9Olv58/vqWsxV2bdntyLCunbtakiWI0z9Rhp5/Y0nD2PCsVQi8odTVZbsOZ/8b7acLP3nz2Y12GfB3BnSvvnHHq3xIQi/RxgkQAIkQAIkYAYBqwVJyBH12lGSzO6wem2BiK3g9vX000/bhiRt2rTKA49wLf0GURse2oRiwH0LeyEYTmFlypRRFUKZyQki/3Pnzsnx4+pl3rHuo0ePBmX9Zq6TY5EACZAACZAACZCAEQL4XJQyZUqPpp06dVIEP3E54J6Lz+woC253JEiQQL7//nuB6I1BAiRAAr4QaNq0qYwbN85rl9dff13atGkjJUuWVJ7P+HOATu/gHQQFmzZt8pqH3Q0gzNm6davs3r1bKRmGv4P4gdsRBA/ggp9UqVLJ22+/LUmTJrU7Rc5ngMCDBw8UQdVvv/0mU6dO9bn8Gw78LViwwMBM4d2E+931+pnh/OfLjsA9yMKFC0u+fPkUl0A4WD311FO+DBFRbSm20ricWbJkUZSijsADD6hHEeeuP5DbFFuZ/kZ4IsCKkagNa0QRZf29O6TETq+nSRsrwlJbPMonIm+7wuFWlSV7jv8TVL0p+QsVtWt6zvN/BFYuXSTN6lf34IEPtdmzZycnEiABEiABEjCNgNVfWlauXKncjLI7rBZbFStWzKU8uK/rs5q7Ix+Ugps4cWJYi2FCWWwFzsF0eYJl9rp163zdfj61r1Wrlm5Zhfbt2yulKRkkQAIkQAIkQAIkEOkELl68KC+//LLHMrt16yaDBg2K9OWrrs8sN6vXXxdp30mkfUeRZb+LLF4kMmeWyIULxrGynKNxVmxJAiTwhMC2bduUh/p6AReryZMnS4oUKQLCBsELxKFqgTmWLFkS0Phmdo6OjlZErNOnT/dJmFO7dm3FnRwu2c8884yZKXEsHwlAOIQScHPmzJFJkyYFXAbur7/+kvfee8/HLHxrjsOpBw8eFLjAoawmRH0oZ4j3HhzkrHIz4n5Xv045c+ZUhJZWBK4r7jdiT8GtCiJWOHsx/iNAsZXGboAKDyd/HeGsVj577YHcuU9nKzvfSA4hlrMjFubfvHGtnWkEZS6H01b+wkUladIX/s+xKockTfZCUPLhpK4ENq5dLfWqlfPAAic8OOIxSIAESIAESMAsAlaLfubPny+VKlUyK13D41BsJTJkyBCB81K4R6iLrRx8UVIQpQXtttjOmzevctLUyvj8889l+PDhEhMT4zEN1u38HdfKPDg2CZAACZAACZAACQSTAB78vfjiix4pfPnll9K3b99gphaUuQN1s8IztSLFRCpXEalcVcRdxwChFQRX+Fnzp7Elli1bVpYuXWqsMVuRAAmQgIjMnj1batas6cGiSJEi0rNnT8HvFTPund2+fVspFaYWEB3MmDEjJK7HoUOHFHcZOFn5G3C7wv2RUqVK+TsE+/lJAJ9VfvnlF+We4JEjR/wcxbMbym2idKYVsX79ehkzZowsW7ZMd99BlAgXTTggmRWRtN8hVjt8+LBi+nPt2jVFqIb3Yvr06RXhmq9hldgKn5txHc34verrmsKpPcVWGlcLVopnzpyJfRU34levXq3895mY+3L3weNwus4Rn2vUhieiK4cY6+TxaMEPIhwEWZmzPhFPQVCFyF+omCRNmkwRVjFCm8DObVukatkiHklC1Q07VgYJkAAJkAAJmEXA6i82+IJft25ds9I1PI7VYitnh1rDSTk1tJJ7uJcNdOcZLmIrR95VqlRRbmpBhGRXWHUDxJE/BJPFixeXjh07qi4Jbs3hWqbSrmvEeUiABEiABEiABMKfAB5cJUuWzGMhEFrhwVFcCjwUhZOUr5E3n0jhIiKFCj/5efElYyOs/VNkymSRSRO8tw/0u5r3GdiCBEgg0ghs3rxZmjdvroihKlSoIBB15M6d29RlXrp0SdMdC3OPHj3a1Pn8GQyH/fHdPxChlfO8zZo1k6+//lqSJ0/uTzoR2+fWrVuCe11//PGHwvrevXsCMR7K9cEpEyUafQnoDiBUQqk/lAq0IuCSBQGimYGDg+3atVNKHPoSLVu2lB9//FHTKc7oWJGy3+FiNm/ePOnRo4fiDOYezz//vFSvXl2qVaumVJ/QEn2690PbVatWGcVpuN2sWbOkRo0ahtvH1YYUW2lceZx8garUEVCBQg2KOH31vtx7SLFVuL1pHO5YyNshysL/dxZmKf994picOnHclOXlK/hfWT+U+4OgyuFOhQlY9s8UzEEd5MD+vVKuiOeHebgG2PngLqgQODkJkAAJkIAtBKwU/WABuAmPmyt2h9ViK6wHJ4b8Dau4R0LZQHem4Sa2cuSPvFFiD2UG7YiMGTOq3lQxa26c9v3qq69k165dHkOylKBZlDkOCZAACZAACZBAKBO4efOmJEmSxCPFgQMHSvfu3UM5dVNzwwNdo+4WMFIoUUqkRMknP9lzBJYKXK6+Hiiyc4f+OClTpnQ59B7YrOxNAiRAAoETgOOM1kH6Ll26yDfffBP4JAGMcPr0aaWUl1lCK0cqcNaZNm2a4pYVSNy9e1eQ46lTp+TkyZPKD0RKeO7+0ksvxf7gv1HyN1GiRIFMZ7jvjRs3YvMw0gn5lylTRiD0UQu4EW3YsEEprWYkRowYIW3btjXS1O82EOtcuHDBL3ckrUmnTp0qDRo08Dun8uXLy8yZMw0Lh9wnCvX9bgQM7kuj/Cgc+Hwp99e/f39F5Kb2mdZ53o0bN0qhQoW8poL3OA6evvPOO4pQ8OzZs9KqVSvNfosWLRJcP4Y+AYqtNPig3iQUq47AwxCoDRGnrt6X+xRbxbn3liLKOvHELUstsmRjab84tylE5ET0MSn6XkaPpaNWMf5wMUiABEiABEjALAJWiX4c+bVu3Vrwxd/uiItiq969eysn4yItwlVshesAoRXKqzRs2NCWywJRfnS09neLQJLACTg4NuDmq3uwlGAgZNmXBEiABEiABEggXAjcuXNHnn32WY90v/vuO+nUqVO4LCOgPPFwGCW18JBbL6pUE6lU+YnQKlWqgKb06HzjxhPB1dcDvI8byAEZ76OzBQmQAAkYJ7Bt2zbJkyePaodgOyTiuTVci7Zv3258QT62xD2rL774QuLHj+9TTwiPxo4dK5MmTfKpH0rNffvtt1KsWDGf+hltjPJzn3/+ucClBwGRFERP+Lenn35adZjjx48r4hVvf0MhWvnrr78EIie9gBsaXJ6sDoisIRAzIx48eKAwMkNcCJZw81Ir8ayXayjvd6OM79+/L40bNxaI1vwJ7Ff83sEYCRIk0Bxi3bp1ijDq+vXrLm3wnBqVLOCYhfea+/MFPQf+lStXKg5bDH0CFFtp8IkXL57Azs0RH330kUyfPl35z5NX7suDR/6fjuemJAESiBwCly6clzyZPa1CYQeKk1kMEiABEiABEjCLAE6cePuSH8hcderUkV9//TWQIfzqa4fYCo61/roWmSlyQ9nAiRMnCkqUR2KEs9jKcT1QygSlBe24RviseO7cOUu2wooVK2T9+vXSp08fj/HpwGoJcg5KAiRAAiRAAiQQQgTwYOuZZ57xyAilbD799NMQytSaVFBGESWOUEpILWDoWre+SN16InnzW5OD86iLFoi0aCpy4YL2XHgQiNL2DBIgARIINgGUjCtVqpRqGsF2SIQLzahRoyxHBHHM3LlzFWGSt7h8+bJ07txZud8VSMDwBMYnZgccHiFCcg/cL+nVq5fHv0PgU6BAAcMORBBuDRs2TDNt8MHBN3cRjC/rhGAGjmMQAaZJk0YRLeEHZR9Rag4Cc/z4KpDTyuHq1auKQMdR8cuXXLXaZsmSRREJJoSVpsEIxf1uMHWlGfZSrVq1ZPHixb50U2371ltvyfDhw5XSqVoBNzYIsxDYwxBmpk+fXnfupk2byrhx41TbQMAVqNNdwAsPgwEotlK5SLAzdH+z44Sz4w/FiSv35SHFVmGwvZkiCVhP4Natm62haUEAACAASURBVJI1zYseE8GqM0WKFNYnwBlIgARIgATiDAF8Kd2/f79l68UX9q1bt1o2vtbAdoitVq9e7bd4xiyxFU7oYa2RHJEgtnJcn08++URwmtPqstAQAcbExJi+LXAzZ8aMGQLxmHs5QYjJOnToYPqcHJAESIAESIAESIAEQoUADlHjMLV7/PTTT7Y4SwSbQ4sWLZQy8WrxaQeRDp1E3vA8O2pp2qjCVKemyH71akzK3HB9qFevnqV5cHASIAES8EZg9uzZUrNmTdVmAwYMkB49engbwpLXd+zYIblz57ZkbLVBIfCBSAn3I7XCqIuikaRRqg6uWGbdh3PMmTRpUlWhU/78+WXTpk0eqfkj8MFhN60ybnCG6tatmxEELm0gdIOI7eOPP7bV2AGHAuGO5Uu5O6OLgyjNaCnFUNzvRteJdhC+V6hQQSBYMjMGDx6s7AuzAntTy71s1apVUrx4cbOmithxKLZSubR4AyRLlszllebNmwts/hDRl+/JYxpbReybggsjAV8JpEvhqcQOxEHD1/nZngRIgARIIG4Q0LP1NYMALK/xOdjuoNjKbuLWzQeBkq928dZlE/jIeE/gBkb79u39dkYzkgVOH6LUjdkBkSHC/cYIBFi4acUgARIgARIgARIggUgmgNJA7qXpcHIfZVgiObTKX2XMJNJ/oEilKsFdfcn/iaxbo51DVFSU5MuXL7hJcnYSIIE4TWD8+PHSpEkTVQb9+/eXnj17BoVP0aJFDQk3UEoMwtXs2bMr7ke45/Dw4UNBWbhjx44J/k7g3o2RA5e4L3Lw4EFVsc/y5culRo0aATk2uYOsWrWq4CBfjhw5TGOsJbbCBO6fE+DmhXJrvgYchLTcJH29VwYHo6+//lqqVKlimlOV0fWgfCLuIR05csRoF5/aoezigQMHDPUJ9n6HK9WaNWvkxIkTykFMX8sz6gnfDQHQaYR7lRBdmREQkKJcpFosWbJE10nLjPkjYQyKrVSuIhxp3K0R27VrJ0OHDlVaH7t0LxKuPddAAiRgEoHMr78gd+7cdhntxo0bkjhxYpNm4DAkQAIkQAIkIALx/9ixYy1FEYzyYnCPbdSokaXrorOVpXhjBzfD2Qrl2/GAJTo62p6kDcyCEp4oOYMbXVaF2Sc3kaejFAvynj9/vkvqwXivW8WO45IACZAACZAACZCAGoEECRIoD5adY/LkyQLnjEgOtYd7uEW57A+RvCGiYfqqj8hX/0/9KkBohYd7EAgwSIAESCAYBFCqS6vkbL9+/TSFCVbmumfPHkU85S02b94sefPm9dZMeX3Dhg3y2WefKfdg9AIu+5kyZXJp8vPPP0uzZs0MzeNPI1yDNm3a+NPVow/KqWmtEZWu8HkB8e+//0quXLn8Fo/BEUqt7CLuc82cOdPwWs6cOWOrk5UjsUuXLinu6CdPnjScK9y8sGZwxD4xItI6f/68vPzyy7pzBHu/J0qUSCnB58wC5TvxGctIwOkM/a0Msw4QjBw5UvO95suarVxrqI9NsZXKFYJKETVPnaNr166KkhSGVtEUW4X6vmZ+JGArgVxvvyZXr1x2mRPuBL7UHrY1YU5GAiRAAiQQlgT8tZ32ZbETJkwQnLiyM/73v/8pJ4WsDH+FJTjxly5dOlNSYxlBYxhRug8l7n744Qfp06ePsU42tcJeRQk+3HyyIuCubLa7HOzKYf3vvo9ZStCKK8gxSYAESIAESIAEQokAHpTdvXvXJaXp06cLHnpGami5Wv0yQ6RmrdBadeUKIr8vVs+pdevWMmLEiNBKmNmQAAnEGQL4vtypUyfV9fbt21e+/PJL21l89913ijBKL3BITEskptUPZXenTZumrBciGLXA3xbn8oX4/Wy0FJxjPNyXgKsR7k3AJQg/ONiG+yxaAYGSVjlHXy4AXMrgVqYWN2/elOeee05Onz6tiGOMiIW05oZbGEr+uce8efMEjl1GA+vOnDmzZMuWzWiXgNtBnI6SdygbaSSwX1BuMUOGDLHN4RKG6gVgoCfYUhPvuc8Z7P0+a9YsGTRokAcK7JPXXnvNK6Jy5coZZuk+GNzkrl+/7nUONEAZTJTDDCRQwlnrIALuz+L3IUOfAMVWKnwOHTqk/NJ3jl69eik3+x89Fjl+mc5WfGORAAn8R6BA9nRy9sxpFyT4cBIvXjxiIgESIAESIAHTCJgp/NFKqnLlyoKbAHaGHWIrzAEhGW7m+BJmljik2MoYeYit4JCFwJ6H+M9qMZ6xzP5rhZxws+GFF17wtavX9rjZ6MspQm8D4iYXbvi529bjvQARIoMESIAESIAESIAEIpUAHOdRAsY55syZI9WqVYvUJSuOC2PGjHFZX/9BIl26hd6Sb98WeftNEbVn+y+99JLA1SJlypShlzgzIgESiHgC33//vaBMl1rgOTGeF9sd3kqqoXTgwoULxV/XbFRqgZvUlClTZN++fS7Lu3LlSuz9D6NCKzxjh8gJf3Nx/yF+/PgeyPAMzeEqpcYTY+zduzfgUnodO3ZUDvSpBcRWMTExiugL5RIDCa17qlgnHMcXL9ZQGGtMij0IYR8O5lkdKI/5xRdfeJ0GojmsQ6/M48aNGwWOV1qxa9cur2Uig73fIapUExnBlAfmPHqBMonuTnBewYpIlixZZMaMGYrI7u+//5Zu3brJ77//rtsV1wM8A3ED/e233zQ/G9eqVUvJiaFPgGIrFT5q9nQOtfLDRyInrlBsxTcWCZDAfwSKv59Fjh39N/Yf8IEWJwIYJEACJEACJGA2AdygsLK8GsQjuIliZ9hRRtCxHpzIgZjHqEjGTLFVMNjaeR0xlxllBBs2bCjYE84BASDEQrgBFiqB64nylFa4XOHGCm4omhU46YYHVe7uVsFwsjNrTRyHBEiABEiABEiABLwRSJo0qYczAB5Ew7khEkPN1QqV+P75V8SCMwKmIPxjpcgHpdWHwoPx9u3bmzIPByEBEiABXwgMGzZM2rVrp9olGGIrb6IkJOqvo7vaIjEfDr+hLF7y5MkVEQgCJcXgZqQXcOWBUxbEX95CzfjEvQ9cd+rVq+dtKN3X0f/XX39VbXP48GH58MMPvQqtIB5KnTq113KAEK1B7O0et2/flurVq3sVz7j3Q4k+uDxhDf4K6bzBQ/nAFClSeGumOCjhc5SRtmXKlJEVK1aojrl161bJkyeP5nyhsN/h3KUmtoJzHBzk9AKOWD169PDK07kBxH4oofzss8/G/jM4QCgIEaReQOQHwZS/+2PRokVSsWJF1Slq166tvJ8Z+gQotlLh89dff8n777/v8gpUnT179pQHjx7LySv3ua9IgARIIJZAuaLvyYF9e2L/G2p81ChmkAAJkAAJkIDZBH7++Wdp1qyZ2cO6jGfmDRojiV69elU55WaXkAYiGYiCjNy4N1NsBRaw1I7kMENspeUAhn2C8YcOHRoyCK10gitYsKBiB25GNG7cWMaNG6cIw3DizRF0tzKDLscgARIgARIgARIIVQI45e9+kGTp0qVStmzZUE05oLzUDrHUqScyaWpAw1re+as+Il89MbZ1CXwe3rBhg+XzcwISIAEScCeg596E+xI4xGdneHO6b9mypfz000+WprR7927JmTOn7hxwO4Lo46233jKUy4IFCwT3VfQCY8EpSM0Zy9AkIlK8eHGlvJ1awBnIm7s4hFZwGEqSJIkiwtMTv0C4oiU0u3PnjtSvX1/gsulrQLMARzWM7a+oRmtOmM1429MQfe3cudNQCT3Mg89bH3zwgeqUUVFRki9fPk0EobDfu3fvLnCxcg8j4iOUq0YpSKOBPbh9+3Z5+eWXPbrgPjKeA+Cenl5AEIXc/Ak9Z6u6devKL7/84s+wcaoPxVYql3v9+vVKbVbncFjD3X/4WE5dpdgqTr1LuFgS8EKgSpnCsmv71thWiRIlEijVGSRAAiRAAiRgBQGzy4y554gvWbC3tjPcS5zZMTeEJnD2wekhraDYyrcrYaXYypEJrgkcypxFQ75laV5r55KH5o3630h58+YVnPgzIzAOvufiVJxz0N3KDLocgwRIgARIgARIIBQJ4KHVxYsXXVL7448/pESJEqGYbsA54aD4wIEDXcaZ/ZtIJXu/2vm8jm1/iRRwPfceOwYebpcrV87nMdmBBEiABAIhMHr0aIGASS0gwnD/XRvIXEb6rl27VnAwTSsgTkmbNq2RofxqA2MBiH0guNIKvL5q1SpFkGQ04P4DFyBvEeh9i4wZM3p1rtLKwSG0gmMXAhVtMmfOrDkehFht2rTRXRLKskG0dV6tjq4XGBC0obRg1apVJV68eN7QeX0d68Gh1OvXr+u2xWFAOFsZjYcPHwrKQB45csSlC/YJygzqieeCvd+RMIRtX331lcdyoR1BfnqRPn16j3XrtfdW4tpIGcrSpUvL8uXLjV4el3bYj1pCLYqtjCGl2EqFE750lSpVyuWVwYMHKzV67z14LKdjKLYytr3YigTiBoE6lUtL1Ib//sDiA6W3DydxgwxXSQIkQAIkYAUBfC7t0qWLFUMrY1otIFFL3NupJcsWK6IIy2ANDfGVe1Bs5Rt5O8RWjozMmMu31bm2xolO7A+jJSn9mQunBnPlyuVPV48+zZs3V2zM3UsJ0t3KFLwchARIgARIgARIIAQJoIwySiA5x7p166Rw4cIhmG3gKdWsWVNmz54dOxBKCJ69FPi4doxQ8n8i69Z4zoRDOXjIziABEiABOwnARaZp06aqUzZp0kTgOm9nTJkyRT7++GPNKSFsefrppy1LyZvzEZx5cMALf3eNhjfRkvM4GP/ff/+VZ555xujwLu3UygobGQjiomXLlgn6O0e/fv0UwZNafPHFF6oiHfe2cN78/PPP/XYkg5AJ/eGilDBhQiPLUW2zZ88eyZ49u25/iA9xT8nXgDgPRjYoUwiGODwMEVOyZMl0hwr2fkdyKGXsflgR/w7RHSozaLmLXbt2zev6nBePEp1///231/cvnjdnyJBBV6B36tQpSZUqla+XSVCqs0GDBqr9atWqJRBjMfQJUGylwmfx4sUetdsdNcLvPHgsZym24vuKBEjAiUCjjyrJn38si/0XPHRztyknMBIgARIgARIwk8Brr70mZ8+eNXPI2LGsLI2ml3Aw3K2c83GUFnQWz1Bs5dsWM0MApVVGUC0TiJGwb4LhcgURFGy+rQ7sRzNKbOLG67Zt2xRXsDVrXJ9krV69Wtfhzeo1cnwSIAESIAESIAESsIJA6tSp5fTp0y5DeytdY0Uedo3pXjK6ek2Racar2NiVpuo8w38U6dTe86WsWbMKHgQzSIAESMBOAnpij4oVKwrK39kZ3333nXz22WeaU1optoJo2ZuIat++fYrbky+xcuVKgRuP0Rg5cqS0atXKaPPYdnAFSpAggc/9ILRCKTw1YRDEMXCYUgtfxXhweUKZODD0J1DeDwdyIQ705zDgmDFjpEWLFppTgznY2xnB3O+OdaIsH1yd1ELPSQ6fMwsUKGAY19y5cxWXMiOhJ4pCfyOuamrzjB8/XrBv1QK5IUeGPgGKrVT4YONUr17d5ZVhw4ZJ27Zt5fb9R3Lu2gPuKxIgARKIJdDqk49k6aJ5sf+dIkUKuXDhAgmRAAmQAAmQgGUE+vTpIxC2WBG4Sb9jxw4rhtYd00wXH3+Tx40JHLJo2LChMgTFVr6RtFts5cgOAqKhQ4f6lqwJre0ouWmmCLF169aK9X+jRo1cVo9SmhBcMUiABEiABEiABEggkgikSZNGTpw44bIkiM9z584dScuMXctzzz0nt2/fjv3vL/+fyJe9w2Opt26KvKBSeSpx4sRy48aN8FgEsyQBEogYAtOnT5c6deqorgffqbds2WLrWuGiBDclrXj8+LFl+YwYMUJ5Nq4VEKVolSDT6gMBVL58+Xw6wAZHoejoaEmePLlPa0WpvldffdWnPnDSgiuT1lzgDQGaWhnADz74QJYsWeLTfCjTOHPmTPnxxx8VhzB/o1u3boobky/r9XYfD65UL8Iq08YI5n53LFOtAprjNYgtIbpUC7jeQTxnJOBOtn//fq+uVo6x4AaHg59a5TzhPgYXMl9j1KhRmkLG8uXLy6JFi3wdUvnsBqEm3kN27x+fkzWhA8VWKhDVFIsO1eyte4/k/HWKrUzYexyCBCKGQMeWDWXe7Omx68EHrTNnzkTM+rgQEiABEiCB0CSA01WwJ7Yi4NDoz4moQHOB6MPddSfQMf3pjzxQThFRvHhxf4ZQ7WPlDTDTkgxgIG83aYwM7YuzlfN4EMZBmISbb3YF3oNXr161dLqJEyd6iKP8nRCW+3jAiNI57m5ZEFhCaMkgARIgARIgARIggUghgPLJcB9wDrhRZMuWLVKW6LIO95I2cLWCu1W4RIVyIsv/KxwQm/bRo0dVS76Hy7qYJwmQQPgRwMGqatWqqSb+1ltvKSXt7Iw2bdrougtZea+pUqVKsnDhQtXl+ivu8Cbg0mLbtWtXpSydLwHHKLgk+hIQPOXJk0e3C5ykUG7SPeB4FYj7OoR8P/30k+BekL+BUoYQXRkRucC5CmIbtYDAzar7znprC+Z+d+QFQVPOnDlV09Tbh59++qniMGUk/HHJ6969u+Z7oGzZsoobm6+hd9+xSJEisnbtWp+GbN++vSIcdMQ333yjuK9FclBspXJ11TYWrPSgRrx575FcoNgqkt8TXBsJ+EygR8eWMn3KhNh+sCk/efKkz+OwAwmQAAmQAAn4QmDIkCHSqVMnX7oYbmuHY49aMmY7SRlesEbDcuXK+fVFVWteK2+ABbpWM/oHU2yF/CF8guBq/vz5ZizH0Bg44QkXZKsCa/L15KZeLu3atVOEVpMmTXJpBje3QG7mWbV+jksCJEACJEACJEAC/hLIkCGDxwPxf/75RzJmzOjvkCHdz11stXOvSJYsIZ2yS3KtmouMG+uZL0teh881ZKYkECkEFi9eLBUqVFBdTjAEKPXq1ZNff/1VE6+V95rSp08vR44c8Zi7Vq1ayj2EZ5991qfLjvK+eH7mbxw6dEjw991o+Hqf0VHlytv4WoIxs/YHXLMmTJgg0Cao8feWH/KA0xXEP0mTJtVs3rlzZ/n+++9VXw+GsBCJBHO/O0DATCNVqlSqXOCQioOMaoH7yMuWqSjHVRqjjOby5cu9XUqX19Uqszka+Hu9cOgZh47VAu5bBw4cMJyjliMYeHorR2p4khBsSLGVykVRs0yDQrVx48Zy4+4juXiDzlYhuJeZEgkEjUCfHh1l4tj/6hanTZvW4+Rc0JLjxCRAAiRAAhFNAKeU4EJldlSpUkUguApGzJs3Tynl9+abbyruWqgdf/369WCkYvqcVt4AMz1ZPwYMttjKkTL2D07x2RG4gXX8+HFLneDMdHxDeRlYnpcqVcoDT7Ac7ey4TpyDBEiABEiABEgg7hGAqOrgwYMuC8cDSzheRWK4i63uWVdVyhJ8A/uJ9P7Sc2g8bMaBCgYJkAAJ2EUAAgi4xGiF3fd2IPyCAEwtzBL3aK3V/W+Lox3ck7766iufLsmtW7cEYpR169b51M+5cdWqVQWCE6Mxa9YsgTDMSGDsOXPmiNaancfQ2yO+CsK85bZx40ZBab1Vq1Z5a+rxOkoiYk158+ZV7durVy/d63j58mVTDwAaWUAw97sjv/v37wvc4bVCiwvcsLTK/KmNdfPmTcF9OqMRFRUlBQoUMPV3AZz6tASMvv5+0bp2cGtr2bKl0WWGXTuKrVQu2dChQ6VDhw4ur+Dk78cffyzX7zySSzcptgq7nc6EScBCAt/07Sk//fhd7AxQ+x8+fNjCGTk0CZAACZAACTwhMHbsWIFttxUB5yz3z8RWzONtTJT+wM31UCgv6C1Xb6/bfUPOWz5mvx4qYiusa+fOncrJLPdyeWavGeNVrlxZIBK0KswsJYgccXLx4sWLHu5WKJ2Ja8ggARIgARIgARIggUggkCVLFtm/f7/LUk6cOCF48BiJ4f5wOPqUyGvqpgwhufypk0UaN/RMDZ9PHSXeQzJxJkUCJBBxBCBqKVmypOa67ty5IwkTJrRt3chFT2hj1b0mHHzUckUqUaKEwMXGaEBoVaNGDfn999+NdtFsB7eqYsWKGRoHTlVw+PYW+GwAkYxRZ3E9gcrUqVMVdyazAyI1CNxWrFjh89AobYfyfO4xcOBA6dmzp+Z4EB3ifleiRIl8ntPfDsHa7+75Yu9rHf5dsmSJfPDBBx5LfPXVVwWuZEZD67po9Z8+fbrUqVNH9eVXXnlFzp07Z3Tq2Hb4fabnUAfhWfz48b2O+/DhQ812tWvXlmnTpnkdI1wbUGylcuVQPxL2es7h+OV47c5DuXzzYbheb+ZNAiRgAYEfv/lKhnzTL3ZkX60VLUiJQ5IACZAACcQhAilSpJBLly5ZsuJQOkWML/cQXdkhnrEEpohYdQPMqnx9HTeUxFbIHSX4ILjatWuXr0vxqT1u8uFmn1VhdilB3DAaOXKk1K9f3yVluMkdPXrUqmVwXBIgARIgARIgARKwlUD27Nllz549LnPiIRQeRkViuIutov4Syf1e+Kx07Z8ipYp75vvdd99Jp06dwmchzJQESCDsCaxdu1ZXzHPq1CnNEmNWLL5w4cKyYcMGzaEfPHgg8eLFM31qCJTTpEmjOa7R0rwoHQgH/a1bt+rmiHsURYoUkRYtWui2g9sODmTmypXL65rheg73c28BvgULFvTWLPZ1ME+QIIFq+9atWwvKDFoVcLrq16+fz8I1tb+nU6ZMUYxm9KJ8+fIye/Zs2wRXwdrv7gz0XKq6d+8uEKo5x6NHj/x6H8J9vmLFioa2C+b9+uuvVdv6W0YQg+kJy3BY86WXXvKaH+4nIge1aNu2rUD4GKlBsZXKle3bt6/HaQko7qC8i7n9UK7cotgqUt8QXBcJ+ENgzLBvZWCfL2K74uTc3r17/RmKfUiABEggYgk4hAgQPuB0cebMmSN2rXYvDO5TcGa1KlavXq1Zu92qObXGhegEgqv58+fbPbUp81Fs5R2j2cIl7BmIwOAOZZVQz+yc1Shh38Nt2azA4SLYj7s7xoWSwNKstXIcEiABEiABEiCBuEng3Xff9RDdB6Mcjl303cVWY8eLNGxk1+yBzzNmlEjbVp7jjBkzRpo1axb4BByBBEiABAwSgJilUKFCmq23b99uSOhjcDqvzd577z3BnFpx4cIFwUFMs+PevXu6Dl4QiMBpR6sMGhxzxo8fLxCIaDkEOXKGSGPLli2KqAP3K2CK4i1wKBNO43rx4YcfehUlNWnSRH7++Wdv03m8riXGscuMAeI1OF0tXLjQcO4QVzkfvIMQLnXq1F77Q3AFU5oXXnjBa9tAGwRrv7vnrVfOEI5fS5cudely5coVefHFF/1aPhzfUGJTL3CQFJ9ttSJHjhx+HzbVE5YZ/X23aNEiTdFYpAvnKbZS2ZWff/65DBgwwOUV1HWFxeHVWw/l6m2Krfz6bcFOJBChBKb8PFx6de8cu7pA/qhFKCIuiwRIIA4TuHv3rnIabPPmzS4U8uTJo5xqguVu7ty54zChwJeOcmlGTnP5OxO+SENwpfeFzt+x/e0Xri5XFFt5v+JWCZcg9LSqFKUd5few56tWreodoMEWuAGEk5bu9uN4v+MGEYMESIAESIAESIAEwp2A2sM6POxNkiRJuC9NNX93sVXd+iITp4TPUjt3EBmmcoYID/I/+uij8FkIMyUBEgh7AjiYVKBAAc11LFu2TMqUKWPbOjNmzCgHDx7UnA9OXHCEsiIqVaqkK+aBKA1CJQiMnn76aYHj099//y0QXnz77bdeRVbIGSX8IHB74403lCWgHBl+78+ZM8frkuDy07VrV8126dOnlyNHjmi+DpesQ4cOCcq/+Rp6rll6bkAoqYj7uGnTppVq1aoJhEyOtfuaA9rjnjvuS2FfGgmUS4T7pyO8le1ztAOrwYMHS+PGjQ2VlTOSi1qbYO5353yaN28uY8eOVV0GnmeglKBzHD58WN5++21/ly0zZ86UmjVrqvbHexyv6ZUoxH1P3L/3JyD00to/v/76q2bpQsdc2NPYU1rvtfXr1+sKWP3JOZT6UGylcjU+++wzgcrOOebOnavc3L5866Fco9gqlPYwcyGBoBOYNXWcdO3QOjYPiAa2bdsW9LyYAAmQAAmEAgF8YcUXbq2AzTWsZFE3PpAvJKGw1mDmoHZq28x8IMDYsWOHoMxYqITDschKVy+z10qxlXei4Si2sssNCu+/6Oho7xANtsAhI5TWcXeKw3s9lMSVBpfDZiRAAiRAAiRAAiTgQiBv3rweJYtwGOiZZ56JSFLuYqvXXhOJPh0+Sy1fVmTFcs98Fy9eLHAmYZAACZCAXQTgsJQvXz7N6SDAaNq0qV3piDfB0MiRI6VVKxVrQBMyhOOO0d/BcKfSEzappQOh1bp16zzuN0K8AfGIt9KDGLNdu3aKCEitrJ9eeTT0RWkz3Jf2J6AbqF69umpXiM0golKLPn36KA7szgGHLjg5BlLqGIIWuIjplZzEnHAkQ+k6R+BZJg5FGw3c50clsNKlSws+a5n9uSqY+92ZAa4RrpVa1KpVS2bMmOHyEvYqeAQSeLaMso5gjGcmx44dU+ZZtWqV12HdXcu8dnBq0KBBA8W5TC0+/fRT+fHHH3WHQ7nnIUOGqLbBexz3MiHGjNSg2ErlymLjDB8+3OUVR83MSzcfyvU7dLaK1DcE10UC/hBYNGeafNrik9iu+IPq7uDiz7jsQwIkQAKRQGDfvn3Kaa9Tp07pLid58uSK4ApfcP05TRQJrAJZww8//CA4UWVlQHwBEUaoBUpUosSamSIUq9ZIsZV3slaJrfA7BgI9K8KuUpsohdiokXm1YHATr169eh43RBo2bKiUXWSQAAmQAAmQAAmQQDgTgCsJ3Emc49GjR+IuSgrnNTrnrraudZtE8uUPjxVmSCty/Lhnru4OHOGxnYStewAAIABJREFUGmZJAiQQzgS8iSZQ2hTCGLvCm/hETfhhVm5wmcLBr5MnT5o1ZOw4EGHgnh7WpxZnzpxRxCtG5obwB6IU3Pvx9rfR8ToELTiApibSMrJY5JcqVSrVplp7BPcFU6ZMqepQBOcorAGuSf4Gxp89e7Yi5sI9ea1wdxqCAQ2MaPwJOC7BGQniuHTp0gX8OSuY+915/RBVwt1KLSDwcz/8q1d+FA5w3kRw/rB39IFIa9OmTX4L3+B6DydRtcC9Q7wH1d4n+P0AQRrKWWrF999/b/kzi0DYmdGXYisVivgl6F6f1XGC4uKNB3Lj7iMz2HMMEiCBCCGwcslv0uzj2rGrwc0c/GFlkAAJkAAJPCGgdmJHiw2+lEH43r59+4g+8WD23sBJF7CzOuwol+bvGvROHPk7ptn9rl27Jrh5EqlhxjWwSmxl5UM1lN2D+5sdAZv542pPofycHLzdyytadQ38TJHdSIAESIAESIAESMAvAoULF3Z5sIWHRPfu3fNrrHDo9Nxzz8nt27ddUu0/UKRL99DPfvUqkbIlPfPEA/6jR4+G/gKYIQmQQEQRgBBFrywfRDoHDhywbc0oMacnOMJ9ppiYmIBFLloLgnhHq7yZvxDAF+N6c3Lav3+/4jKGMsDeAhx69uwprVu3FjhaIapUqeLh5u0Yx4xykHrCoBs3bkjixIld0sb9oxdffFF3KRD49OvXT15++WVvS9Z83dsexmFnuHo5B3QR0EcEErgGKOOMMok5cuRQSstly5ZNEiZMaHjYYO93R6JLly7VFL4NHDhQcRFzDji0FS1aVHWdcJ/D4XItJzTDcFQagjkOR2uJFo2MrWZC5NwP79fRo0dL5syZBa5z27dvV+4ljho1Svd3E97f+ByHz6iRHBRbqVxdWLTBbs05HL90L9x4IDcptork9wTXRgI+E9iwaqnUr1U5th/+8KCGLoMESIAESOAJAZz2atGihU843n//fcUGun79+j71i8uNrSglCIGKuxtTKJcYg+gMLlfu4pFQ2ReHDx8O6MtvqKxDK4+4Kray07HMbHcr3Ly7cOGCyyWF2BVueQwSIAESIAESIAESCGcCEJA735/Dg56bN2+G85J0c8cDTTh0OEeZciKLfg/9JbdsJjL+Z8881R4Gh/5qmCEJkEC4E4B7dYkSJXSXAefsZMmS2bJUb+ITJAGHGSvLdKGUIEoKmhEtW7ZUXIGMlp/TE7Go5QMxHFx+IGqCMARl89zLsMGFCdc50Jg1a5bAWUwt4JDmXp7v9OnTkjp1aq/TQkDTo0cPqVq1qmTKlMlre0cDiMoxLwRbes5W2N9//PGHx7h66zGchErD/PnzC9ydIJyDCxNKTmodigyF/Y4lnDhxQtKkSaO67MmTJwtK7zkHXNqKFy+u2t5RenThwoVSqVKlQFC69AVLlLPEwcxAYtq0aVK3bt1AhlDta2WJU9OTDWBAiq1U4H300Ucyc+ZMl1dWrlwpJUuWlPPXH8ite3S2CmDPsSsJRByB7ZvWSPWKZWLXZdYHtYgDxQWRAAnEWQKoU48vtv4ErJM7d+6sfA5j6BOwo5SgI4MOHToIXK7scvPx9dpDkIIccbIvlAKn9qw4xRQqa4yLYivc0IDIz64wW2yllrddZRHtYsZ5SIAESIAESIAE4iYBPEh0fpCKh+JWlZUOBcKVK1eWBQsWeKSyc49IlqyhkKF6DjCuyp1dRE0HN2fOHKlWrVroJs/MSIAEIpLAli1bFFGIXly6dMmrQ5FZcOrVqye//vqr5nC456r2+9+s+TEOHLYhJDly5Ijfw0JAhJJiTZs29XkMCL0g+DIaO3fulJw5cyrNIbTG/WWIthzhXkbP6Lhq7SC2gkjJPdTK4D548MDnsoUotwhHIRyWgztSihQpFKEfDv5BZIcSyefOnVNEVu6iMq11gceSJUtUX16+fLkiJDp//nwgWHT7Yi/gOSqqBOHvfMaMGWPbh8J+dySD5xFqTHHI193FCuK1UqVKqa570qRJAqMfxK5du6RChQqGymPqQcQ1grOUGa5RcEbF3jLiIGd0U+AgPd5zvriaGR071NpRbKVyRdS+mDhuOJ+79kBu36fYKtQ2MvMhgWAS2LZpjdRwElvR2SqYV4NzkwAJhCKBbdu2eZzk8TXPjh07Kl/IGdoE7Col6MgATlq//faboLRDKAYepEBwhS+0oRSwMIdzEG4qRFqEqtjKyveG3SX3zGDsbd9RbOWNEF8nARIgARIgARIIBwKlS5cWHKB2BB5SWvngMNhMOnXqJEOGDPFI46sBIt16BDs77fkHDRDp9bnn63A8OXXqlPJQmUECJEACdhKAcCVlypSaUzZp0kRQcs2ugDgD9+C0Yvjw4dKmTRvL08HfUAhjNmzY4PNcvXr1Uu7RJU+e3Oe+jg74m46/7d4CQp6LFy+6OGdBRNKtWzflUCbEUdABmBX4WwVBlHMgBwjyUMLYPbyJiczKS28clAtEJQqtgEDtxx9/VMoyWh0oNYdykY7yiqGy37FuLacvtRKREKmVLVtWFRfEknXq1Il9Db9jsB/9uWeNwwT4zFe+fHlTL823334rXbt2NWVMXFM8D3J/X5gyeAgOQrGVykUpV66coGygc0B9hzrvZ689kDsUW4XgVmZKJBA8AlvX/yG1qvynqs+bN69s3rw5eAlxZhIgARIIMQJGLZK9pQ0baJzY0LLk9dY/LrwO4VN0dLRtS4WzFYQZejd9bEtGYyLYOOOGDr6sh1JAbAV3sEgRXYFzq1at5J9//gkIsxXiJT0r74CSFVFu0M2bNy/QYQz3t0NsNWHCBKUcJ4MESIAESIAESIAEwpmA+z3+VKlSKeKdSI0RI0YIyu65R778Ius2he6q4WrlVv1QSRYOJosXLw7dxJkZCZBARBOA405UVJTHGiEigGvSa6+9Zuv6GzVqJHC6dg+Iek6ePClJkya1JR84Kc2fP1/69OkjcG7SC7CqX7++dOnSRVe85kviuLcHoYmegxPKqqH8np0xbNgwadeunTIlyuUNGjRI0RSoBe7blilTRg4ePGhnii5zGXX2gsCuf//+ivDKyujbt698+eWXsVOE0n6HqMlZM6J1IFzPfQ2irRo1angg3L59uyJoc9ekuDfEMxGIrHDfNUeOHJZcChxaRtnEQN2t8L5HlRM4W8WVoNhK5UrjAR5uyDsH6ruipuiZmPty98HjuLI/uE4SIAEDBKLWLJc61f8rj4UHzjt27DDQk01IgARIIO4Q0KrD7g8B1LvHia2aNWtK4sSJ/RkiYvtAIOHPqZhAgEBwBYerUBcNQaSCUouhVloQAjnk1rBhw0AuQ9D64ss4boKYJTgKN7EVBHO4fnYFOFt909DuNdnFjvOQAAmQAAmQAAnELQJ4OOZcIgefu4+iZl2ExtKlS5UySWqxeq1IoSKht/DOHUSGDVXPiwcAQu96MSMSiEsEtNx14OpUsGBB21HASQeuUitWrHCZe/To0dK8eXPb88GEFy5ckH379smePXsUMTPu0cKdCOXIIA7JmjWrmHk/2HmRCxcuFPydgNsVxCEQeMAxCmKUt99+23YeEKHBnQkivJdeesnr/Cjb1q9fPxkwYIDXtmY3wH7BYWZfrs2JEyeUUpbjx4+3RCSG+1wQyTkilPY7yjTCtWrv3r0SP358gSuYWuk+PbEV7uXpuandunVLGR8Cxjt37ijiRJSKfOONNyRdunQuLm1m7wfn8UaOHBmQS17r1q0VIWZccyWl2EplV6LOpnPtVjRBrVM82Dt19b7cf0ixlZVvZo5NAuFGYMOqJVK/1n9KedRPxodMBgmQAAlYQQAf8FGTHf/r/v/1XtPqE8i/O8/nbZz/z955QEtNfV380FGKoPxFmkhTmhQRVJrSm1IEUZAqCIIgVUQFkSqIgAio9I70Jh1BqQooxYIgCNI7SO/wrR2/eUxJZpKZZJLM22ett9D3knvP/d3MTOZm332qV69uOg7s2ipcuLA8+eSTii2tPxPkhBroRYoUMb1vpzaIXW4QvtgRblgMRzk5CNLWrFljB6KgfbpRdIXFAlxvEFyZFRRbBScJ1pHY7uuZp2i7denJiceQAAmQAAmQAAmQgFEC+A6Kh7GewMNXO10kjOZv9Hg86E2ePLncunUr4NSO74r0/9Roi9YeP+MbkYb11fvAdyM8vOfmKmvngK2TAAkEJwAHJ5S/O378uGTNmlU+/fRTWzca3rx5U1AyECUMUSYP61twHYIAJL4GPvOuX7/u2s8LfNa99dZbYZVmDGfOGzZsqAimIrlm4My1ceNGWbt2rSJC2rdvXzip+JyDaxrlOb3Dbdd7sDKCcHoyu+xfxNBVGgDz/PnzG7pfhrseRFYQ8WXPnt2KtBzfJsVWKlMEVTKcrLwDLjVwqzn87025RbGV4y9sJkgC0SSwbsW30qj+PQvIHDlyyN69e6OZguG+YGsKpXiiRIkkYcKEPj/+vwv1/zg/nGP0nBdOfmrtRrsvNRGMU8QxoQQxdot39OSnJSjyPtdO0ZHVfRt+wfMEpcyd012XzJomiImw48WugMMPXHGcHnCxxaJUNEsu6mXiBtEVrjOIrPzdgPWOMdhxbhNb2SEyxPuZlYJBurSacSWzDRIgARIgARIgAbsJwCXB2301b968imtALAfccidNmhQwxMefEPk9smrfpmNLmVzkxnX1ZlFyCqIGBgmQAAmQAAnEOgE8S5g5c6YipINzmhWB0nODBw+WcuXKmd780aNHlUo/v/32m8ARDqXxjIjbIdTB80o8w3NzwGWtQoUKqkNAmUCUjnRD7NmzRymBiRKSwaJu3bqKmxzGBbF/fA6KrVRm/5lnnpHNmzf7/AVvElDzHTp3U27fobNVfH7RcOwk4E/g+2Xz5Y0Gr8b9GtaOBw8edBQoPBTFA1HPQ+VolrtxFAgmQwIkEC8JuEUAZNbkoKyfnaXyatasqTgdbd++Xdq3b+9o8ZVTSwviWnCq6Gro0KFK2Twz3ay8r323ia3sEHPidYV5sDIgYGaQAAmQAAmQAAmQgJsJ1KlTR+bMmRM3hPggKJ89e7a88sorqtM2aqxIkzecMaNlnxdZv1Y7FzybKVq0qDOSZRYkQAIkQAIkECUCcLrCpr4pU6aEFLuESgmOQ3BTgns57g1gbBCtuHz5siK+gvsVnkuuX79eKffoHRCADRo0SMqXLx+ttCztB+uDZcuWVe1j1apVmn+zNKkwG8eaL8R/GBMqv2HucD1hfChnimsKZQ4Z/xGg2ErlSkC5wF9++cXnLygJhtJgB8/eEGqt+PIhARLwJrBq0Rxp3uSe7zXqQ584ccJRkFq2bCmjRo1yVE5MhgRIgASiRQC7l7GLOb4EhDCoj+6UwEMNLBTgXycGBMkQr8Ae3okB0RVcuNq1aycQ0tkVEM/BzQr/WhkUW4WmG43XuB0istAj5xEkQAIkQAIkQAIkoJ/Aa6+9JjNmzIg7AeId/w3W+ltzx5EXLlxQSricOXMmIOESJUW+X2fvOE6eEKlYTmRnEIMxlrS2d47YOwmQAAmQgDMI7N+/XzZt2qTcu8DcAeUsjx07JpcuXZKkSZPK/fffLylTplRKKKZLl04yZ84sGTNmlEyZMilrsPny5XOUW9S1a9eU56ZXrlxRckae0RSAWT2rEJZhTVMtIDjT+pvVeUXaPpzXcF/50EMPOep6inRcZp5PsZUKTbwJwerOO2B5h7ruB87eEG7yNfMSZFsk4H4CKxbMkJbNGsUNBA9Cz50756iBJUiQwFH5MBkSIAESiCaBlStXxswuGb3cIIj5/PPPZeLEiXpPsfw4pzuMObm0ICYH9xd2OIVhN5PHzcryi0REWXwwuzwh2itTpowl6WPxC4K4aIaV4/GMY8iQIcr1xiABEiABEiABEiABtxJAaZNp06bFpV+iRAnFWSHWo23btoobgVpMnS7yyj1z/qiiWLdWpP6rIieOa3eLh8d4WInKIwwSIAESIAESIAEScAsB3GOWKlVKNV3c22j9zS3jY57aBCi2UmHz5JNPCqz6vGPfvn2SLVs2+efMDV5PJEACJOBDYOm8adL6zaZxv4OiHDaZTgo6WzlpNpgLCZBAtAmMGDFCUP89PsaECRMUNyKnhNNdrsAJIjUIw+wsxRhsvqJZXhCiHlw/cP+KVlghtsKcdujQwZIh2FFuLxpiq8aNGwvePxgkQAIkQAIkQAIk4FYCjRo1ksmTJ8el/8ILLyjlUGI9Dh06JCVLllRcMPyjQiWRxcuiT2D4FyLvdRa5eTN4307foBN9cuyRBEiABEiABEjADQQ2btwoEParxbp165R7M0ZsEqDYSmVeUWbmzz//9PkLvpxkzpxFcbZikAAJkIA3gUWzJknbVm/G/QrWl7du3XIUJDwkxYO5AwcOKFaPcLrCj+e//f8N9rdIzzfar9HjjYxFrW0zxg5rTe8fPIj1/x3+X+33kfxOrU0r+o4kd08+3nmF+m+1v4dzjn/ewXIJ1b53W9HIz1FvKC5MBhbKXbt2FezwjY8Blys8WHCSeMjpi+hwc4KrTyhnMOy8vnHDnu8HVoquMH6UooRIKdphhdjKyrJ7doitMCdWu5bi+oJrF4MESIAESIAESIAE3EoAmwa8xeMVKlSQFStWuHU4hvKGs5XW99+Zc0RqvmyoubAP3r1L5OOPRObMCt0E3Kzg/IDvWAwSIAESIAESIAEScBOBrVu3SpEiRVRTdnMZQTfNgV25UmylQv7xxx+XPXv2+Pzl6NGjkv6RDHKQYiu7rlX2SwKOJbBg+nhp3+Ytn/wgtoqlesOOhc/ESCCeEPCI9aIlVgslJgv1d38B2po1a2Tw4MG2z5ZdogjbBy4iThRcucHlCtwgusI1HCxSpkwply5dsmWqzRZdzZ8/X3GzguDKjqDYSh91q8VWyAJlsVG+kkECJEACJEACJEACbiTQvHlzGTt2bFzq1apVk0WLFrlxKGHlXLFiRVm5cmXAuY9mFfl9l0jy5GE1q/ukcWNEen4kcuxY6FOwhjpnzhypUaNG6IN5BAmQAAmQAAmQAAk4jAA2LGbPnl01q++++07KlSvnsIyZjlkEKLZSIZkjRw5B2UDvOHnypDz4UDo5dC6E161ZM8N2SIAEXENg7tTR0qldG598UUYQ5QQZJEACJEACIiNHjpS33vIVpUabS4ECBWTHjh3R7tZR/TlRcAVATne5Qo7YgdSkSRPFITJYPProo6rlOqJxIUQquoILJkrtQWxlZ7hJbJUrVy7566+/bMEVDbEVyuzAFY9BAiRAAiRAAiRAAm4k0LJlSxk1alRc6jVr1pR58+a5cShh5YzN5A0aNJDNmzcHnF/rZZGxE0VSpgyr6aAn/bhRZMwokckT9bUNcf+0adOkSpUq+k7gUSRAAiRAAiRAAiTgMALYtJo2bVrVrJYvXy4QwTNikwDFVirzigcV/g9Szp49KylTp5Ej/1JsFZsvBY6KBMInMGvS19KlYzufBugEED5PnkkCJBB7BAYOHChdunSxZWCZM2eW8uXLy7vvvisoFR3fA4KrZ599Vq5fv+6DAsINO52/cP89fvx4xws7UFYP4rBQJRnh2gXWdgTEMT169DDE0lMy0C43K29ObhJbFS1aVPXhVTTmPRpiK1xHuN4ZJEACJEACJEACJOBGAq1bt5avvvoqLvW6devKjBkz3DiUsHM+fvy4NG7cWLN8YvMWIg0aiRQvEXYXcSfOnycybbII/tUbWbJkkSlTpkjp0qX1nsLjSIAESIAESIAESMBxBLCunjBhQtW8xo0bp1QRYMQmAYqtVOYVD+WOHDni8xc8UEmeIpUcpdgqNl8JHBUJREBg+vgR8v67HX1aOHHihDz88MMRtMpTSYAESCB2CHTv3l369OkTlQHhPu65555TfiAqwr8MXwK5c+eW3bt3B2DBF0KUiLQz4B41ZMgQR5cugyAJoisIlIJF6tSpBY5q69evtwUpRFdgCeGXVsCxC1/24WrllHCT2ArvMT/++KMt6KIhtkIZF7udzmyBy05JgARIgARIgARigkDbtm1l+PDhcWN5/fXXFWFPfIsrV64ogqvZs2drDv2FMiJVqokULixS7FkRvWb9O7aLrPlBZM4sEThaGYk8efLIpEmT5OmnnzZyGo8lARIgARIgARIgAUcSSJ8+vaBSmn907NhRBg0a5MicmVTkBCi2UmGYIUMGwa4P70BJsERJ75Nj5+lsFfllxxZIILYITB39hXR7/12fQR08eFCwO4tBAiRAAiQg0r59exk6dKglKBInTiwQZ+AHu2HxLyM4AVgaazkYJUqUSG7fvm0rQpSRgMsVynw4OSBQguvPxInB62NAkIMxLVu2zJbhQMAGhyK4h3nCKSUD1YC4SWxVsmRJWbdunS3zGg2xlRVzYQssdkoCJEACJEACJBAvCfh/D8V9Mb5nxNcYO3as8v3l8OHDQREkTy5S+Kn/fuB49VwJkXTpRM6eFTl7RuTcWZEFC0RWfyfyx+/GaeL7KFzH8JMxY0bjDfAMEiABEiABEiABEnAgAawTbtiwISCzsmXLyqpVqxyYMVMygwDFVioU4UZz6tQpn7+g1MqdBEnk+AWKrcy48NgGCcQSgUlfD5Ye3d73GdLevXslR44csTRMjoUESIAEwibwxhtvmLqonS1bNqXOuUdglSlTprBzi28nwqWmVq1aQYftBIcrJAhnJjwM8RYJOXG+UC4QD3LWrFkTNL06deoofw+2o9zK8eHBSrt27RThI5y5nFAyUG28Vgh8MPZQTmThsK9evboswJMmGyIaYiuIBFEam0ECJEACJEACJEACbiTQqVMnGTx4cFzqLVq0kJEjR7pxKKblPHXqVGnQoIFp7RlpKFmyZHEiq5w5cxo5lceSAAmQAAmQAAmQgOMJoHrAhAkTAvJMlSqVoIJaNNbyHA8pBhOk2EplUh988MGARWXs8L9+W+TEhVsxeBlwSCRAApEQGD9ioPTq0c2niZ07dwrssBkkQAIkQAIir7zySsQCEzhYQSSEn5dfflmwUMswTsBKlzHj2YQ+A2IPj0go9NH2HoGSfMg1mOgK48GOelhKT5s2LeoJJ0+eXK5duxb1fo106CaxFRzDMOfRDizcYAEnGnH37t1odMM+SIAESIAESIAESMB0Al26dJGBAwfGtfv222/7lBU0vUOXNIg1y3z58kUt23Tp0knt2rUVoRXKrDNIgARIgARIgARIIBYJ9O7dWz766CPVof3yyy/y1FNPxeKw4/2YKLZSuQQeeOABuXDhQtxfsLsfYqsrN+7IyYsUW8X7Vw0BkIAfgTFffCJ9e/k+aNu2bZsUKlSIrEiABEiABESkUqVKsmLFirBYoASbR2SVK1eusNrgSfcIwC0qlAOTE3nhMxUuV274bIXoCqK2HTt2aKKEW1ebNm3k999/V93x5MQ5iFZOFFuFJo1rrEyZMqEPjPCIrFmzCkpOMkiABEiABEiABEjAjQTef/996d+/f1zqHTp08HG6cuOYzMoZgqu6devKH3/8YVaTPu1kyZJFcaPGT9WqVSVlypSW9MNGSYAESIAESIAESMApBKZMmSINGzZUTQciLCtc950y9vicB8VWKrOPm//Lly/H/QXOCdgBfvn6HTl1iWKr+PyC4dhJQI3AqCF95JO+vX3+tGnTJilWrBiBkQAJkAAJiCiiAIgD9EbmzJmlZs2aisgKNc0Z5hFwu10xRExwE4JDlNMD7kNwPTpw4IBmqhC/tWzZUpYvX07R1f9Totgq9JWNEpBp06YNfWAER0BohesXTmwMEiABEiABEiABEnAjgW7duknfvn3jUofT1YABA9w4FEtyhuBqzJgxiuPuiRMnIuojSZLEUrBgIalQoYJUq1ZNSpQoEVF7PJkESIAESIAESIAE3EYAG2+1Ngo//vjjsnv3brcNifnqIECxlQoklNe4fv163F9SpEghly5dkkvX78hpiq10XFY8hATiF4GvPuspn/bv5zPotWvXSqlSpeIXCI6WBEiABDQI6BFbJU2aVGrUqKH8QGiF+y+GuQS2b98uhQsXNrdRG1qD0AouV7hO3BDREF0VL15cOnbsKMOGDXOlc5n3PFJspe+qtlo4OWTIEMWhjUECJEACJEACJEACbiWATRq9evWKSx/iK5R3YfgSgNAKgqu5c+fK4cOHlZ9bt7Q3nD/yyCNSsGDBuB88VMybNy+xkgAJkAAJkAAJkEC8JoD7pyRJkmgywNo87qEYsUWAYiuV+cQLwfsLBcoKYvfwxWt35MxlOlvF1kuAoyGByAkMH/CRDBrouzPu+++/F7hVMEiABEiABLSdrXCPVb16dUWcWq5cOcmePTtxWUhg/vz5iltYrAQ+ZyG6Qkk+NwT4f/7550HFUEadrlKnTq3szn/rrbcUBNiZ3qpVq6APR5zOimKr0DOE0n7ZsmULfWAER7AkdgTweCoJkAAJkAAJkIAjCKBci7e4CuIrOHcyghO4ffu2HDlyRPlJmDChpEqVSikD6PnBRikGCZAACZAACZAACZBAIIEXX3xRFi9erIqmQYMGMnnyZGKLMQIUW6lMKL5E3L17N+4v6dKlk1OnTsn5q7fl3JXbMXYJcDgkQAKREhja70P5fPBnPs1QbBUpVZ5PAiQQSwT8na3gwPPSSy9RlBrlScaDhVisDY9x4cGJWwIlNZHzmjVrNFOGgKxNmzby+++/a5YXbN26tYwYMUJpA+KbZs2ayerVq92CQTNPKx6CWXXtW5Grngm0Wjjp2WykJxceQwIkQAIkQAIkQAJOJfD+++9L//7949Kjs5VTZ4p5kQAJkAAJkAAJkEBsEBg4cKCgdLVW/PXXX5IrV67YGCxHoRCg2ErlQvAvyQBr3GPHjsm/V2/LvxRb8aVDAiTgR2BI767yxdAhPr+l2IqXCQmQAAncI+AvtuJ7pD1Xh1WCE3tG49srxElwuXKTq6QR0dU1J5D0AAAgAElEQVTWrVuV0h6IkiVLyldffSX58+dX3HfhbOX9EMkJ8xFJDlYImMAa70Nmx7x582wpZ4nyfkOHDjV7OHHtNW7cWFPkZ1mnbJgESIAESIAESIAETCbQqVMnGTx4cFyrEF/169fP5F7YHAmQAAmQAAmQAAmQAAn8RwBruEWKFNHEgc2yqEzAiB0CFFupzKW/2Cpz5sxy6NAhxdUK7lYMEiABEvAm8NnH78qI4V/4QKGQgNcICZAACdwjADclT7kGiGL2799PPDYQgBApmJuSDSmZ3iXGOGTIEClUqJDpbVvV4IQJEwTimfPnz2t2kSZNGmnSpInky5dPmjdvrhwHsc0HH3wgV65csSo1W9p1k9jKrvs9lBCEm5lVAeEirjcGCZAACZAACZAACbiZwDvvvCPDhg2LGwJcBrBRgUECJEACJEACJEACJEACVhEoVqyYbNmyRbP5y5cvy/33329V92w3ygQotlIB7i+28jwUPHv5tly4RrFVlK9RdkcCjicwoHtH+fqr/8r4eMKuh2+Oh8UESYAE4i0BiEl27NihlD3LmzdvvOVg58CtFmjYOTb/viEUgWgH9/FuCDhUff755yHLPEJ09eyzz8r27dvl+PHjjhtao0aNZNKkSRHlRbFVcHyY+8KFC0fEONTJ586dE1xrDBIgARIgARIgARJwM4G33npLRo4cGTcEOF199tlnbh4ScycBEiABEiABEiABEnA4gW+++Ubq16+vmeX69eulRIkSDh8F09NLgGIrFVL+YivUzkQNzTOXb8nFa3f0suVxJEAC8YRAvw/byeiRX/uMlmKreDL5HCYJkAAJuIQAxDxp06Z1SbbmpQlHtXbt2rlGOAK3IgjF3OZA9txzz8mXX36plDWMtFwfxVbBr3+zSwhmyZJFcXH2RMGCBRUxH4MESIAESIAESIAE3E4AZVrGjRsXNwzcR8EFl0ECJEACJEACJEACJEACVhG4du2aPPzww3Lx4kXVLg4ePChYj2PEBgGKrVTm0V9slSdPHtm5c6ecvnRLLl2n2Co2Ln2OggTMI9C7axsZN2a0T4MUW5nHly2RAAmQAAlETuCHH36IWAQTeRb2tACHHjxYgYjHLTF//nwl5wMHDjg65ZQpUyqlWTwl58y4zii2Cj7lZjvUZcyYUY4ePRrXqRX8HX0RMzkSIAESIAESIIGYJQDX1cmTJ8eNr02bNj5lBWN24BwYCZAACZAACZAACZCArQSGDx8ubdu2DcghVapUcuHCBVtzY+fmEqDYSoWnv9jqySeflF9//VVOXbwll29QbGXuJcjWSMD9BHp2biUTJtzbKYcRUWzl/nnlCEiABEggVgjALQkl6oYOHRorQwprHCgpCKerxo0bh3V+tE+CS1SVKlXkp59+inbXuvqDKAeCMO9ycxRb6UIX9kFmlxBEaZ2vv/Z1Z922bZsUKlQo7Bx5IgmQAAmQAAmQAAk4hcBrr70mM2bMiEunVatWihsrgwRIgARIgARIgARIgASsJoB7T/91t5kzZ8orr7xidddsP4oEKLZSge0vtnrqqafkl19+kZMXb8kViq2ieHmyKxJwB4GPOraQyZMm+iRLsZU75o5ZkgAJkECsE+jQoYMitGLcI/DCCy8oLlf416kBZyvMHYRyTosaNWoo1xTEa/5BsZW1s2UGX0+GEFShxGbTpk3jkn7ggQeUUpAMEiABEiABEiABEogFArVr15a5c+fGDaVFixYycuTIWBgax0ACJEACJEACJEACJOBwArdv35ZBgwbJ1KlTBU71WI8uXLiww7NmekYJUGylQsxfbFWsWDHZtGmTHL9wS67dpLOV0YuMx5NArBP4sN0bMm3qVJ9hUmwV67PO8ZEACZCAOwj439e6I+voZFmzZk0ZMmSIqmgoOhkE9gIxTc+ePQX/Oi2yZs0qEyZMCCpSM0MMZEUZOzPyUpuPaN/voVzjxIm+Av9wr5PZs2crZXUWLFgQ1wRc3zDHDBIgARIgARIgARKIBQIvvfSSLFq0KG4ozZo1kzFjxsTC0DgGEiABEiABEiABEiABEiABBxCg2EplEvwfShUvXlw2bNggx87flOu37jpg2pgCCZCAkwh0bdNYZkyf7pNStB++OYkHcyEBEiABEnAOgWiIrUqUKKHcK7s1UFoQDj/e5fCiPRY4WEFk5UShC9yOwAglA0OFGaImiq3UKeMawS44M+LNN9+UUaNGSdq0aX2crObNmycQITJIgARIgARIgARIIBYIVK5cWZYvXx43FAjXx48fHwtD4xhIgARIgARIgARIgARIgAQcQIBiK5VJ8H8o9fzzzyu7y4+evyk3KLZywGXLFEjAWQTebdVAZs+a5ZMUxVbOmiNmQwIkQALxlQBKvR04cMDS4d+9e1cpKwdBzvnz5y3ty6rGkydPLl9//bXA2SeagZJtQ4cOVfg5sXwbRGiYV71CNIqtrLt6zHK1gkPZxo0b5eTJkwHW5efOndM919aNlC2TAAmQAAmQAAmQgDkEypYtK1if80TDhg1l0qRJ5jTOVkiABEiABEiABEiABEiABOI9AYqtVC4Bf7HVCy+8oHwxO/LvTbl5m85W8f5VQwAk4EegY4t6Mm/uXJ/fUmzFy4QESIAESMAJBOBGBDGPVeHZlID24bwDQciaNWus6s7ydiFOGzdunJQpU8byvlAODkImcHNa1KhRQxGAgYeRgGAMbkmRBJ2tAumZ6WoFRys4W+Hag5uaJ7xfy5HMH88lARIgARIgARIgAacQKFWqlKxfvz4unfr168vUqVOdkh7zIAESIAESIAESIAESIAEScDkBiq1UJlBLbHX43E25dYdiK5df80yfBEwn0K5ZXVm4YIFPuxRbmY6ZDZIACZAACYRBYP78+VKrVq0wztR3CkQ56MM73O5yhbEULFhQVqxYIQ8//LA+EAaOgvsTRC7412kBwQ1EONhsEm5EWrrSCrGVmWIlby7Rut/Da9j/dRbO/NSpU0dmzZqltOX/vjBkyBBdpSLD6ZfnkAAJkAAJkAAJkIAdBJ599lnZtGlTXNevvvqqTJ8+3Y5U2CcJkAAJkAAJkAAJkAAJkEAMEqDYSmVStcRWh87dlNsUW8Xgy4BDIoHICLRtUlsWLVrk0whcPUqXLh1ZwzybBEiABEiABCIkYIbTULAUtIQxELfAVWuBnxg5wuFE/fRy5crJwoUL5f7774+4bzCByGrChAkRt2V2AygtB5EVnMkiDSeKrTCmSPNS4xINsZUZpRk9ucPZIV++fJItW7aAspXbtm2TQoUKRTr9PJ8ESIAESIAESIAEHEPgqaeeEtzjeMIjPHdMgkyEBEiABEiABEiABEiABEjA1QQotlKZPi2x1cGzN4RaK1df70yeBCwh0LphTVm6dKlP2xs2bJDixYtb0h8bJQESIAESIAEjBFAK7sCBA0ZO0X3svHnzpGbNmprHQygCAY9V/etONMIDGzZsKMOGDZMHHnjAcEsQvKGU46effipXrlwxfL6VJ2A8EMXhJ02aNKZ0FamoyQpnq2vXrsl9991nyvi8G7FabIVrp3DhwqaUmkyUKJGcOnVKuRa9ywdiPLgO0BeDBEiABEiABEiABGKJwJNPPim///573JDg7Dl37txYGiLHQgIkQAIkQAIkQAKqBO7cuaOsA6VPn96xhNyQo2PhMTHHEKDYym8qbt26JUmSJPH5LcpoYCH9wJkbwiKCjrl2mQgJOIZAy/ovKaWGvGPz5s1StGhRx+TIREiABEiABOIvAdzLwnHRirh7V9/dMVyT/AUeVuRjdZtvvfWW9OnTRx566CFdXU2cOFFat27tOJEVkm/cuLGg5KNZIisPEKNiq4QJEwoWVzxhhdjqyJEjkjlzZl1zZuQgq8VWZpYBxcNGuLRBvOUvrMK14ETHNSNzwWNJgARIgARIgARIwJ9A7ty5Zffu3XG/rl69uuuddznLJEACJEACJEACJBCKwJ49e+T111+XLVu2yMMPPyy1a9eWbt26ScaMGUOdGrW/uyHHqMFgR64mQLGV3/RdvXo1oEyIR2z1z5kbrp5sJk8CJGANgeavVpVVq1b5NL5161blYRaDBEiABEiABOwmANciuNlYEUZKj6GMHlyurBJ+WTE+rTYhoOrevbs88sgjqodAZNW5c2c5ffp0NNPS1ReENRC/wfHMijAq7kuVKpVcvHgxLhUrxFa//vqrFCxY0PThWi22wusF15IZUbduXcXdy7+9559/XhFaWXU9mJE72yABEiABEiABEiCBcAhkz55d9u/fH3dqtWrVZNGiReE0xXNIgARIgARIgARIwDUEUIVgwYIFAflCfPX00087YhxuyNERoJiE4wlQbOU3RRcuXAgoD4IHBqtWfy8oI8ggARIgAX8CTetUEpRJ8g481IODAIMESIAESIAE7CZgpatUOGITuPVAAOb20oKY1xYtWiiiK49rEu4H4H7lvYPe7vn39A9RDa4FfLexMtDP2rVrdXcBZy1vpyUrxFa4TsuWLas7J70HhnP96217+/btpgr3cV1+/fXXPt2jfCBEkGa7m+kdI48jARIgARIgARIgASsJZMmSRQ4fPhzXReXKlWXp0qVWdsm2SYAESIAESCBeEsA6GNy006VLJxDRpE2bNl5ycMKgUUJZ69lklSpVZMmSJban6YYcbYfEBFxDgGIrv6k6c+aM8mHgHXgg8d2q7+XQOYqtXHNlM1ESiCIBNbHVzp07JU+ePFHMgl2RAAmQAAmQgDoBM0uR+ffQrl07pRSd0YC4Bufh5/z580ZPd9zxNWrUUARWu3btclxuWbNmVZyLrBZZeQZeoEAB+e2333RzQElGfAfzhBViqzlz5kidOnV056T3QCvFVmXKlAkQ8+vNS+24vHnzCu5PvWP8+PGK2xyDBEiABEiABEiABGKRQPr06eXkyZNxQ6tQoYKsWLEiFofKMZEACZAACZCAbQQGDx4snTp1iusfGxLhJGmFw7htg3RRx2PHjpXmzZtrZnz58uWACl/RHp4bcow2E/bnXgIUW/nN3fHjxyVDhgw+v8WDiZWrVsvhczfdO9PMnARIwBICCRKINKkd6Gz1119/Sa5cuSzpk42SAAmQAAmQgBECcFuCcMOKQOkx79IcRvuA6AouV2aVSjPafywfD5EVnKyiLaZJgJsjA/G///1PTp06FXeGFWKrUaNGScuWLQ1kpe9Qq8RWECF26NBBXxJhHgUHMn9n1jCb4mkkQAIkQAIkQAIk4EgCDz74oJw7dy4uNzidrlq1ypG5MikSIAESIAEScCMBOEZWrVo1IHWU8sVGvPvvv9+Nw3J1zh07dpQhQ4ZojgEO51gztDPckKOdfNi3uwhQbOU3X4cOHZJHH33U57cQW634brUc+ZdiK3dd3syWBKwnkDCBSGMVsdW+ffskW7Zs1ifAHkiABEiABEhABwGjAhgdTcYdsm3bNilUqJCRUwKOxRd9iK4WLFgQUTs8WZSS6GAJoZUdYfRae+SRRwQbXjxhhdjqk08+kQ8++MB0HFaIrcwuH4hBJ06cWG7duuUzfjNet6YDZYMkQAIkQAIkQAIkYCKBVKlSyaVLl+JapNjcRLhsigRIgARIgAREpFixYrJlyxZVFnv27JGcOXOSU5QJlCtXTlavXq3ZqxOq8rghxyhPG7tzMQGKrfwmDwKJHDly+PwWYqvlK1fL0fMUW7n4WmfqJGAJAS2x1cGDByVLliyW9MlGSYAESIAESMAoAaMCGCPtY7cUxD1mBJx2IBJas2aNGc3FuzYgVMJcpEmTxraxG73WMmXKJEeOHInL1wqxVefOnWXQoEGmMzFbbAWnt8KFCwvEh1aGFYytzJdtkwAJkAAJkAAJkEA4BJIlSyY3btyIO7VkyZKybt26cJriOSRAAiRAAiRAAioE8Azs8OHDqmzOnDkjcJlkRJdA6tSp5eLFi5qd/vnnn5I7d+7oJuXXmxtytBUQO3cVAYqt/KZr9+7dAW8yEFstW7lajlFs5aqLm8mSQDQIJEqYQBq9XDGgDMvRo0cDSpJGIx/2QQIkQAIkQAJqBIwKYIxQtGKH+IQJExTR1YEDB4ykEm+PxRyAGco62h1GrzVYl3vPsxVCoDfeeEPGjx9vOhqzxVa1atWS+fPnm56nd4NWvF4tTZiNkwAJkAAJkAAJkECYBBImTCh3796NO/u5556TjRs3htkaTyMBEiABEiABEvAnEEw0c/v2bcFnMSN6BE6cOCFwkA8Wu3btkieeeCJ6Sfn15IYcbYPDjl1JgGIrv2lDDdkCBQr4/BZiq6UrVsnxC76lF1w540yaBEjAVAJaYquTJ0/K//73P1P7YmMkQAIkQAIkEC4BowIYo/14P8Qwem6w4ym6Ck4TJQPBqGbNmmZij6gto9da9uzZBe7CnrBCbFWjRg1ZuHBhRONSO9lMsdXnn38uHTp0MD1H/wbNzNnyZNkBCZAACZAACZAACYRJ4ObNm5I0aVKfs1HqaNOmTWG2yNNIgARIgARIgAT8CWitAT388MMCUQ0jugTg4Fm6dOmgndottnJDjtGdNfbmdgIUW/nN4NatW6VIkSI+v4XYasnyVXLiIsVWbr/gmT8JmE0gccIE0lDF2ercuXO2lvAxe5xsjwRIgARIwN0EjApgjI52//79lroqUXQVOCPt2rVT3L/sLBnondWxY8ekXr16hktA5sqVS/bs2RPXlBViK5SM2bBhg9HLOuTxZgmXmjZtqojmvAMPB73L3oRMRscBBQsWlO3bt+s4koeQAAmQAAmQAAmQgLsJXLlyRVKkSOEziKeeekp++eUXdw+M2ZMACZAACZCAQwjcuXNHEiVKpJoNTE127NjhkEzjTxrjxo2TZs2aBR0w5sXfdCaahNyQYzR5sC/3E6DYym8Osbvl2Wef9fktxFaLl6+SkxRbuf+K5whIwGQCSRIlkAa1AssIoiZyypQpTe6NzZEACZAACZBAeASsFlvNmzcvKu5KEKTgZ82aNeGBiIGzUAYOLkiFChVyxGjOnj0rzZs3F1wD4UTu3LkFu+o8ARcqs0vp5cmTx6ePcPJUOydSsdW///4rZcqUiZoACsI8bAhgkAAJkAAJkAAJkECsEzh//nzApgQKz2N91jk+EiABErCWwLVr1wTf4/EZkyRJEoF7U3x+BqQmbPbMQIUKFWTFihXWTghbDyDw0UcfSe/evYOSWb58uVSsWNE2em7I0TY47NiVBCi28pu29evXS6lSpXx+C7HVt8tWyelLdLZy5VXOpEnAQgJaYqurV69K8uTJLeyZTZMACZAACZCAPgJwP+rZs6e+g8M8avz48dKkSZMwzzZ+2g8//KC4OsUn0RVKBmLM7du3Nw7MgjMuX76slL0bPXp0RK3nzZtXdu7cGdcGxGSYXzMDpZ1Pnz5tZpNKW5GIreAwVatWLfnnn39MzytYg3RfjSpudkYCJEACJEACJGATgVOnTikPwb0jf/788ttvv9mUEbslARIgARJwEwG4d2/cuFH5QUUkOCNig71/4LMG1ZKwIe7JJ5+U6tWrBzgrumncRnJFmcBHHnlE9ZQGDRrI5MmTjTTHY00gULduXZk1a1bQlqK9huufjBtyNGEq2EQ8IkCxld9kr1q1SsqXL+/zW4itFi5dJWcuU2wVj14bHCoJ6CKQNFECeV3F2ermzZuSOHFiXW3wIBIgARIgARKwkgBEUBMnTrSyi4hEJ5EkBqEKBEhWjy+SHM04t3HjxoqblRNKBt66dUvee+89GTx4sBlDUxYjvR96WSG2Spgwody9e9eUfL0bCVdsBTEZhFbYERvNsHtBLZpjZV8kQAIkQAIkQALxm8DRo0clU6ZMPhDgduot8o/fhDh6EiABEiABbwJwq1q6dKmyqQ+OTPv27QsLEDaULViwQHLmzBnW+W46CZ+p+fLlU00Zm/PMWjdyExO7c02fPr2cPHkyaBp9+vSRDz/80LZU3ZCjbXDYsSsJUGzlN234EKxZs6bPbyG2WrD0Ozl7+bYrJ5lJkwAJWEcgaeIE8nrNwDKCVjzQs24UbJkESIAESCCWCUDYgVJlVka7du0UMZBdAdEVHJ9wLx9LgVIn4IrvI04IOKTBjvz2bfO+F2H3J1yePGG22AqCprRp01qCLxyxFcpgNm3a1JJ8tBqFKxr69f+eG9Uk2BkJkAAJkAAJkAAJRJEAvh9ky5bNp8fHH39cdu/eHcUs2BUJkAAJkICTCVy/fl0RVk2bNk2mT59uWqqpUqVSRFuFCxc2rU0nNrRu3TopXbq0amoDBw6Uzp07OzHtmM1JTWiuNthOnTrJZ599ZgsHs3KE2UWCBAloeGHLLLJTfwIUW/kRwYfq66+/7vNbPNyYv+Q7OXfFvIcKvBRJgARig0CyxAmkvp/YCo5W+LBnkAAJkAAJkIBTCEBkYbUQadu2bYptup0xf/58pZwhdiS6OSCOgXgMrl1OiP79+ysiqytXrliejtliq7///tuyHaVGxVZ2CK0wYXS0svyyZQckQAIkQAIkQAIOI7Bnzx6BuMo7cuTIIXv37nVYpkyHBEiABEggmgSuXr0qP/30k1JqbcqUKaqlAc3IB59Bf/zxR0yLQebNmycvv/yyKi48a69Xr54ZKNmGTgKLFy+WF198MeTRdoqtIsnxxo0b8sUXX8jMmTNly5Ytyjih3xgxYoTAUY5BAnYRoNjKj/yoUaOkZcuWPr/Fi3Xe4u/k36sUW9l1obJfEnAqATWxVfLkyQU37QwSIAESIAEScAoBuFtBhHTgwAHTUkqSJImPuBj3zBCf2B1wMsJYrRaXWTXOGjVqKG5Wjz32mFVd6G4XeUBkdfbsWd3nRHqg2WIrLMAUK1Ys0rRUzzcitrJLaNWjRw/HiPYsmQQ2SgIkQAIkQAIkQAIqBNRKG+H+ev/+/eRFAiRAAiQQYwRQZQSO2UuWLJHjx49LkSJFJHfu3JIsWTI5deqUwE3n4MGDsn79elm5cmXURn/48OGAkrZR6zwKHY0ePVpatGih2tPq1astd9mPwhBd1UWvXr0Ea0Chws51okhybNWqlXz99deqw/vzzz+V1zyDBOwgQLGVH3XUkIWq0zvw4Gju4u/kPMVWdlyj7JMEHE0geZKE8lr18ootrCdSpEghly5dcnTeTI4ESIAESCD+EYhGOUHsanNKqTIIheAM5RaXq6xZsyql3pxQMvCrr76SPn36KAuS0Q6zxVbLli2TKlWqWDIMvWKroUOHKtcihIDRDJSh9C7RGM2+2RcJkAAJkAAJkAAJ2EkA90D+5ZuyZMmiPGxnkAAJkAAJxA6BXbt2KdWKtm7d6rhBxbrYqm/fvtKtWzdV7hS/RP9yxMbTiRMnhuwY66Xt2rULeZwVB4Sb49KlS6Vq1aqaKcFJbvPmzYJKAQwSiDYBiq38iKupKvHAY86i7+TCNTpbRfsCZX8k4HQC9yVJKLUql5Yff/wxLlV8oEf7YZrTOTE/EiABEiABZxDAfa23QNjsrODKhFJ+Tol//vlHcbmycsyRjtVJJQPHjRsn/fr1E5TesyvMFltNnTpVGjRoYMlwQomtcP116NDBltcEris8ZHSCQ5ol8NkoCZAACZAACZAACQQhoOZumjFjRjly5Ai5kQAJkIAhAljn79+/vwwYMEA5D+sqcIZxwkYpQwOJ0YOx4c+pzuaxLraCYAdl3dTi3LlzkiZNmhi96pw5rMqVK8vy5ctDJmdnicdwc+zYsaMMGTIk6Nhq1aolc+bMkQQJEoRkwANIwEwCFFv50ezSpYsMHDjQ57e4aZr97Uq5eP2OmezZFgmQQAwQuC9pQnmx7HPy888/x43moYcektOnT8fA6DgEEiABEiCBWCNgtrtVwoQJ5c4d33tkJy6oONXlyiklAyFIgsgK5VaiGSi9fO3aNZ8uzRZbYeHPqh17WmIrLPRCdAinMrsCi1Dt27e3q3v2SwIkQAIkQAIkQAK2EtiwYYOULFnSJ4f06dMr5aUYJEACJKCXwJQpUxSh1R9//OFzCp4Z4vsgw34CeK/He77ZUaBAAUVQ98QTTyhuORAO4d9UqVIpYo7r16/LjRs3lOdCWt+9Y11s9eqrr8rMmTNV0aO0IyO6BPLly6drXQ+lNMuXLx/d5P6/t3BzjKT8oC0DZafxigDFVn7T3bp1a0HZDO/AB+rMb1fKZYqt4tWLg4MlAT0E7k+aUCqWelp27NgRdzgXb/SQ4zEkQAIkQAJ2EfB3t8KCkZmOjE4VeTjJ5copJQNnz54tn3zyiW12++nSpQsQqON6hGDPrED5vp49e5rVnE873mIrj8AKIiszX0/hJG62YC2cHHgOCZAACZAACZAACdhJQG2TCe49T506ZWda7JsESMAlBH7//Xfp06ePzJgxQzVjiq2cM5F6xRuhMs6bN6+88sorUrx4cSlatKikTZs21Clxf4fgCuf4R6yLrUqXLi3r1q0LGDdKuu3evVs3Px5oDoHUqVPLxYsXQzaGZ5kQE9oR4eY4ffp0qVevnq6UR48eLc2bN9d1LA8iATMIUGzlR7Fx48YyadIkn9/ixmnGwpVy5Qadrcy46NgGCcQSAYitXnimgKAGtScyZcokuJFmkAAJkAAJkIATCag9eMBOwPXr14eVLnb0+e9Yw/3zvHnzHGkZbqfLlVNKBn777beKyMq7DHJYkx/hSZkzZ1a9Z8K1g1IAZkTbtm1l+PDhZjQV0AYW3/fu3au4WNktsPIkx/KBlkw1GyUBEiABEiABEnAZAbg2VKxY0SdrPDg/e/asy0bCdEmABKJN4KeffpJGjRrJnj17NLum2Cras6LdX5EiRcLeQPbwww9LkyZN5LXXXpPChQtHNKi1a9fKiy++qIhd4H7VuXNn+fDDDyVRokQRtevkk3PkyCH79u0LSLFChQqyYsUKJ6cec7mh6oDeaw0unzCMiHZEkiNc8XFfpybuUxvHmjVrBGJABglEgwDFVn6Ua9otruEAACAASURBVNeuLXPnzvX5LW6cpi9YKVdvUmwVjYuSfZCAmwikSJZQihfOozxo8wTcKuCewSABEiABEiABpxJ47LHH5MCBA3HpYefe5cuXfZwaI80dmxjsLKMWLH87XK6cUDIQi10QWUFw54RQKyOIvMwsRVm/fn355ptvnDDcqOTgVGe5qAyenZAACZAACZAACZDA/xNYvHix8tDbO+CmcP78eTIiARIgAU0Cq1atkoYNG8qxY8eCUhr8eU65dfMBuXQ5hSSQ1JI6dQZJnTqzPJA6q6RO/YgkS5bM5/xChQo5cjNaLFwKEGBAYGsk6tatK2+++aZSJjBx4sRGTg16LEoLXrlyxZArlmmd29AQNl+qBQRs48ePtyGj+NvlzZs3JWnSpLoA3Lp1S7cwS1eDOg+KNEesFTZt2lTgLB8q8BrXciYMdS7/TgJGCVBs5UesUqVKAYpbfOB+s2ClXKPYyuj1xeNJIOYJQGxVNH9OnwfW2bNnl7///jvmx84BkgAJkAAJuJcARFD4guodgwcPlvfff1+wOGRGoBzc/v37Hb2gGA2XKyeUDMSOLoisli9fbsbUWtpGjx49BKX/zArwP3jwoFnN6WonYcKEgh170Q6WD4w2cfZHAiRAAiRAAiTgVAJwHq1Vq5ZPeilSpJBLly45NWXmRQIkYDMBPMBv0KCBZe8TEFzBwRnfeRnmEahTp47MmTNHV4MdOnSQd955R7ABkREZAYjK8LmqFh988IH07ds3sg54tiECuL+Bo1qogMP8oUOHQh1myd/NyhFlO7FuCGG9Vjz77LO2u/lbApGNOpIAxVZ+04Jd/f7lNCC2mjZ/hVy/ddeRk8ikSIAE7COQMllCKfD4oz67XViT2r75YM8kQAIkQAL6CKDkGRaXvHd2454XO39at26trxEdR7nBZccqlysnlAxE+QOIrBYuXKhjtuw/BO5feDBmZmCX6u3bt81s0pFtsXygI6eFSZEACZAACZAACdhEYNasWcp3G++Aq+rVq1dtyojdkgAJOJXA0aNH5auvvhKUiY9GZMyYUUaOHBngvheNvmOxjwEDBkjXrl2DDg3Pa6ZNmyYoOcgwhwDc8rVEa8OHD5e3337bnI7Yii4Cp0+flv/9738hjy1RooSsX78+5HFWHGB2jn/88YeMGDFCpkyZopTv9I62bdvKF198YcUw2KYGgbt378qRI0dk9+7dcuHCBXnwwQcFn3coN4pNqbEcFFv5zW7+/PkFL1DvwIOnqfNWyI3bFFvF8ouBYyOBcAikSp5Qcj+WQXCj4Im8efMGvI+E0zbPIQESIAESIAErCbRv316GDh3q08X3338v8+bNM+0LKRZe4G7lhjDT5crukoHbtm2T/v37y8yZM92AXskRDlTbt2831QkNQrps2bK5hkEkibpB2BjJ+HguCZAACZAACZAACRghMHXqVMWhxjuSJEkiN27cMNIMjyUBEohxApMnT5Zu3d6XgwePRH2kO3fulDx58kS931jrEGK5TJkyaQ6rbNmysmjRIrnvvvtibei2jgfuQkWLFlXNYfr06fLqq6/aml986xwiF7hWhYrGjRsLqh3YEVblCJEPHO337dunlHBNlCiRQGCZNm1aO4YZL/q8du2aItqDngafZb/++qtgw69awHGte/fuAmdBM8u2Ogk0xVZ+s/Hoo48GWOhBbDVl3gq5SbGVk65d5kICjiAAsVWOTOl8nEEKFCggO3bscER+TIIESIAESIAEtAioCVFw37tq1SqpUqVKQGntcElCvAWrfDcEHL+aNGkiKB/giYIFCwp+j117ocLukoH4gguRFRaM3RZWXCc//PCDlClTxm0oDOfL8oGGkfEEEiABEiABEiCBGCegVjYdu+rjg+NpjE8th0cCphH4uGcT6fnxRF3twTAmcxaR1KkDD//3X5Ed23U143NQqVKlZO3atcZP5BkBBFq1aiVff/21Khk85O/VqxepmUxg6dKlUrVqVdVWly9fLhUrVjS5RzYXjMDevXslV65cISHBCcrMigYhO/Q6wA05GhlPfDv28uXLsnLlSpk7d25Y686DBg2Sjh07xiQ2iq38phVKRzxM8Q48dJo8d4XcukNnq5h8FXBQJBABgdTJE0nm/6XysSF/6qmn5JdffomgVZ5KAiRAAiRAAtEhABGUt7AIvcLd6uGHH1YEV9gZZCRwL33u3LmAe2m06aZAKTs4XeF7wMcff6ykju8IcF6CgAdCtYkT7y3KooQbjoNbmB3x999/KyKrMWPG2NF9xH1iZx14p0mTJuK2vBvAAkDt2rVNbdOJjeE1ZzY7J46TOZEACZAACZAACZCAXgKjRo2Sli1bBhx+584dSZAggd5meJwLCMDVBt/PUD4JP7wvdsGk2ZziXdktO//sKPnzLlHN5JVXRXLnEXn+eZFMWURgFpMsWfCk8Uhx3VqR7dtEZk4X2b1L3yBnzJgRUPJU35k8ypsA1rW0NvnF8gN+O68CNVGzJx843DzzzDN2phd233DAhAPTiRMn5ObNm5IhQwbFiR3umE4OOAyhcleo2Lp1qxQuXDjUYZb83Q05WjJwFzd65coVWbx4scyePduU6gnY9BCLJQUptvK7yGEvhy9d3oGHLBPnLBdqrVz8jsDUScAiAqnvSyTpH0gut27diusB9qmbN2+2qEc2SwIkQAIkQALmEVBz/sG9L8RRZgpVUNauUKFC5iXugJY8ZRitEgrpGeLhw4cVkdVXX30V8B1Gz/lOOMaK8oGecZUvX15xaovlsNMCPpa5cmwkQAIkQAIkQALuJgDnhjZt2gQMAg9Rnf7A1N3krc/++PHjMmfOHKV8zZYtWwQbT7yjS5cuMmDAAOsTYQ+uJXBLyki1yj/IiuWBQ+j+sUj3HpENDY8JZkz/T3S1dHHwtuhuFRlrz9nBxFbYKNeoUSNzOmIrcQQ+/fRTee+991SJ7Nq1S5544gnX0MLaGkTa+GyBY7xaZM+eXSpVqqQIueGA77SA+cPTTz8dNC2MAe5SdonO3ZCj0+bVrnxwb4UNvbifvnjxomlpXLhwQVBWMNaCYiuvGb106ZLqJOOB04Q5y+Uuja1i7frneEggYgIP3JdIHkyR2Ked5557TjZu3Bhx22yABEiABEiABKJB4LHHHgsokTd+/HipUaOGZMqUyce9Mdx8ILSCgIu7jMMl6HveqVOn4kRWV69eNadRm1rBdYHvW1YEHNrAKpbDSn6xzI1jIwESIAESIAESiG0CcE3t0KFDwCBx75w8efLYHrxLR3dX1sldWf3/2eeUBFJUEsjjcaNZtvxzmTtnp/Iw/OzZs0FHWaRIEfn5559dSoJpW0ngrvwjM2Zlk3p1A3tp2kxkpMlm0e+8LfL1l9ojypkzp+zZs8fKIceLtoOJrRYtWiTVqlUzhcPdu3fl5MmTcujQIeXn/PnzyiZ8CHnxAyckuLakTJlSUqRIIVhvK1CggKRWqz9pSkb2NdKpUycZPHiwagJgkxmWcA4PbAyFaGz69OmGMi1RooT07t1bypQpY+g8Kw/G80jkFSw+++wzwbzZFW7IMRgbuDyhqgE2deJ9AK953Fe+9NJLyhptlixZ7EJrSr9//vmnLFmyRObNmycbNmwwpU3/RmL1PpxiK6+ZhuUsHij5Bxb/x89WkblbcqmxURIgATcRUBNbcUeKm2aQuZIACZAACWhZf2PRoV27drJ27VpTIPXo0SOuJJ8pDcbDRrADCLu04WTlX67RjTiGDBliWelF2NZDAB/LgfKVKG2JBVwGCZAACZAACZAACZDAPQJajhvYbI0H4AxnEIBoasnSj+X02RnyRO6TUr6Cb14JpJzMmJZNhn6+TbZs+cVQ0rhH3r9/v6FzeHDsE7grP8grdcvInFm+Y61QSWT+tyJmVwq7fl2kYlmRHzX2ZUOUY6ZrSOzPoPoIg4mtIBooXrx4WGggrkAFEzjpYaPT6tUeQaix5iD+7devX0yJfV9++WVFlKEWx44dk0ceecQYpCgefe3aNUUshTmJJD766CPp3r27JE7sa8YQSZsQ8ECrgI2D999/v1IeFxsJQwWuzXLlygU9zKx5cUOOoXjhfhDjePDBB0MdqvwdpSUrVqyo6XyGOcJ7DQS0bguIRJs0aSLTpk2zNHWI0hYuXGhpH3Y1TrGVF3lYG+bJkydgLii2suvyZL8k4HwCC2ZNkfatmvkkWrZs2ZgvWeP8mWGGJEACJEACRgiouVvhHhg7ggcNGmSkqaDHYoc5BFwMYwSuX78eJ7JC2Qw3x/PPP6+I7uByZmVpyVatWsnXX3/tZlSauUNkVbNmTcHriW5xMTnFHBQJkAAJkAAJkECEBPr27SvdunULaAUuJLHoMBIhLltOh5tyr17vyT///OdEC8OxpStFSpT8L53Nm0SGDJIAUYyRZPHwEP0wSMBDYM26rvJCad8yk3nz/Se0eiybNZwWLxKp9ZJ623S2Mod5MLHVb7/9Jvnz59fdEcqsrVixQhEFLF9ungkH3LUgTnJSKVusNUFgkS1bNilWrJgi7tEbOXLkkH379qkefubMGd0iFr39mXXcjh07pH79+pqiGaP9vPPOOzJ06FCjp/kcD44zZswQbIb966+/AtqCkAdCn9dff10qV66s2tfixYvlxRdf1MzjlVdekZkzZ4adpxty1DM4OAl++OGHMmvWf4pbsEXZafwOrnRqcfDgQcU1DOUmg8Xjjz+uuGq6rUxevXr1DLu76WHtfQw4o4ykGxzvjI4Nx1Ns5UUNNb7xgeIfuXPnlqXrd4TDl+eQAAnEOIHP+vaQEUP6+4yySpUqit0igwRIgARIgATcQmD+/PlSq1atgHSxS6tXr16mDgMiLiwwUSSiD6vHyerAgQP6TnDoUaVLl5aePXtaVjLQf9j4Ao+dZ7EUWbNmVYRqeGjEIAESIAESIAESIAES0CYAV1217zFwUkqbNi3R2Ujg119/VdxE8GDZPx5/QqRnb5EdO0SGDhbRqphetdp90rx5c9my5YhMnjxXDh/SHhDEVrx/tnHCHdZ15cpPyPLl98QMqO42f5FIyVLWJlq5gsjq7wL7aNu2rXzxxRfWdh4PWg8mtoIrVbDyanA5QnkzCKuwNqYmdjELIdZEsM5mZty5c0cpaYhA5Sa9LkunT58WuFOtW7cuLp2GDRsqTuqhHCD//fffoJ+lThU263F/CmduRo8erXwmGQ3ck0DkY2SjYN26dRVxl79z2Ny5c6V27dqaKXzzzTfy2muvGU1RKdvr9ByNDApiNTURpdZrE+52cM3HvYuegHBr2LBheg7VfQwqG+zevVt5b4LrGdzOULIQ5kGRli404zWBUqnPPvusFC5cWNKnTy8PPfSQIrbERtH77rtP+UEJ70SJEukes9sOpNjKa8agVq5UqVLAHEJp/NexS26bW+ZLAiQQBQL9e34gI4f5On7AaUDLQjUKKbELEiABEiABEgiLAERQa9as8Tn3mWeekU2bNoXVXrCT4GgEC3YKrrQpwbUIi1xWLvSZPrEqDeKLPx50RfMBx/Tp0wU7s2IlsEDRvn175YevmViZVY6DBEiABEiABEjASgIffPCBfPLJJwFdoCxPunTprOyabQchMHDgQIHrGB7Ea0W27CL71c1S5KF0Ihkz/veTAf9m+u+/T57IKb0+3qvaJL7TosQ4gwTwHRvl3Lzjs8Ei7/j+yhJQc+eIvFbHt2kIGPr06WNJf/GtUTgCNW3aVHXYKF1VtGhRRZAEp3AIhSBQQty+fTuq7w94/rxs2bKIp+fWrVuKMAzjXrt2bVwpyuzZs8vs2bMV0UOwwMY0bIhTc6aCcAIuScEcaCDQwvla4cTP2jlz5kidOn4vwohn4r8G4GSEEn2hRGre3S1dulReffXVsMqIYo5+/PFHHyeyqVOnSoMGDTRHhDnPiA9MA+GGHA0MRzkU7qZqpVshFgJT/wjHNT+UwFNPznfv3lXc9XA/u3PnTs1T8P4GgVf58uU1nbmC9aclPguV41NPPSUdO3ZUNm4bccQL1a5b/06xldfMTZw4UfUhQJKkSeWvoxfdOsfMmwRIwEICfbp3kbFf+dqE4iYJD/kYJEACJEACJOAmAtu3b1dch/wXvrFYo2UNHsn4KLhSpweBFX5gde/mwAIGdoZBIBTtgCU8du3FQhQsWFBZQLWy5GIscOIYSIAESIAESIAESMCbwLvvviufffZZABQ8aMeue0Z0CaB0TJcuXQQOCnbElClTlPJLjPhL4M8//1TEIXDz8Y6Nm0WeLmo9l4MHRHI+5tsPhB+eUlbWZxDbPTRq1EgmT57s+EFqia0grFi5cqXiMoXqS+XKlQsqYMiXL5+mAAPlulAKUauU2eXLl5XXwtatWzV5hSo5B2elYGs9f//9t+K4g5JtKL128uRJOXHihPIDpySIXfBz6dIlRfwCl6YMGTIon8/4F/nBvcesgDECXLyMBDgib70xfPhwefvtt3UdPmbMGHnzzTd1Hat1ULNmzQTteGLs2LGa7lq4Fi5cuGCoPzfkiOscZfvgTofXFq6dUKEltsJ5eB16Ryi3MK2+SpUqpYggww047eGeacOGDbqbgCvduHHjdDvbeRrGa87IdV6hQgVlQy3EaYx7BCi28roaUKKja9euAddH0qRJZTfFVnzdkAAJqBD4+P0OMnH0lz5/wc09xJsMEiABEiABEnAbAZQog0DGO2D/e+bMGUuGwpKC97CivAVEViht7ubAIg52N9nlwoQHaLly5VIW7dwe7dq1E+y+ZpAACZAACZAACZAACRgjgPsotdJc4Tg7GOuZR/sTWLRokfJQGffpdkX+/I/Kb7+5uyy7XexipV88iIbozjseTi9yOIqXZdpUIpe9vqYmSpRQ9uzZK9myZYsVzLaNA8IeiHrsDKyFqDnmeOekJcj57rvvBCIGT2DTI0qd5cyZM2BIoUr44QSUKvRf28Pv4eiFMnRweQoVECjmzp1b9bD33ntPPv3001BNRPR38IAgEc49ekQ0Wp1hjQ0CNj0B7nBfxFolBGCYTwi1Ro0aFVL4UqVKFVmyZEnIbiZNmiSNGzcOeZyeA7xLI6MUIVyY1MKo2MoNOfrrOR5//HHFmQrl64IFSgJquV3euHFDUOkMAcEgHOJCvaa1+oKwEII9IwH3PWhUpk2bZuS0uGPx2sbnnGcMehoJJj7zPx8OgRCC6S1Vqqf/WDmGYiuvmcQDAShy/YPOVrFyuXMcJGA+gW6d28rUCaN8GkZ9ZtRpZpAACZAACZCAGwk89thjcuBA9Bai47vDFb5EQ2QFm2m3BxaMINjDNWRXBFtgMiOn5MmTK7vmIo1EiRIpJQvUAmUDIbKKZunFSMfD80mABEiABEiABEjASQRat26t3GP7x8GDBxW3DUZ0CFh9b25kFJMnfyENGrQ1cgqPjRECKNsGIYR/1KotMmN29Ab5fAmRHzf69jdo0CBlsxIjfAL4Xh2th/8QdECsAREG1rKyZs0qadOmVVykEiZMqAwC6wXnzp1T1nhQBmzBggWKYAMCJayXYE3BP9ScuVCmC66A/qGnHB5EHhB7+Ee/fv0E5Sv1xDvvvKP6vBzndurUSQYPHqynGVOOgYgEQjWjbldY24TQSo9zz4gRIxRhsJZQZfPmzYrwS6stLebeAODEhM2BZgUEeRUrVlSaq1mzpnKtqYURsZUbcoRLF9bN/APvpXhPDRZwBIMDlFrA9Q0l8Y4ePSpwp4qkygPMOPC61hNw1BoyZIjyuoo0IDgz4joFZuhbT+TNm1fwHlKiRAmW5PYDRrGVFxCU/po5c2bANZUkSVL56xjLCOp5sfEYEohvBLq2f0tmTBnvM2zYheLmj0ECJEACJEACbiTwww8/SJkyZaKaenwUXGGBDA+AVq1aFVXWVnT2/PPPK6Xu7BRZecZVtWpVWbp0qRXDVNrE4t6pU6fCbh+uydgtpxVYMMJrkGUDw0bME0mABEiABEiABEhAKaWDkjr+sX//fkfcs8aHKYKzGBzGQkXatCLlK/73ky+fCP4/Tdr//k2cOPDs/ftF/tkvsn/f//+7X2TXnyI7tgfv6b77Esu6dT9JkSJFQqXEv8cYgXr16sn06dMDRtW3v8i770VvsAvni9Sp5dtfqVLFZe1a/aWiopete3qCMCJTpkyWJYzyZLVq1RKsNYQj1oWb1K1btwRrAVoBByc1t6ljx44pDkueOH/+vEDwFUo8pCb80RIdauWENtC/R0TmfVyHDh2i7sINwRDGULx4cV1zDQEL5g7lGYNF5syZFVEcBHShAoKsNm3aaB4GEZBW+UZcAxDwaLkq+TcKly1EMMEPNunhc3bbtm0CcZ5W6BVbuSFHjBHlYLWEd9evXw/6Wgt27UJshdcYnM3++uuvUJdD0L/XqFFD5s+fH7IN5PvWW28pa6pmBESeEEPpDbx/PvPMM4acAXE9oVT3G2+8ETWhq97x2HUcxVZe5PGQQK2OJlTRe45ftmuO2C8JkICDCXRu01zmTPetB16tWjWBRTaDBEiABEiABNxKINiOKKvGFF8EV7hHgMhKj724VazNahffn7AzEwsRTgjsNMQigVsDPLEYkyZNGrcOgXmTAAmQAAmQAAmQgCMIwHEVZXD8A44NOXLkcESOsZzErl27BPe2WoKAp4qIVKwkUqacSJmy5pA4cljk+9UiM6eLLNPYe1GocA5Zu2ab5sNwczJhK04iEEyI881MkdqvRDfbD94T+cyv+tr48ePpahzBNPz888+C8lZmBYQEEEpUr15dKe0Xje/nWmIrlBcsV65c3ND0utD4i60g2MGam9GSaGCrJlCF69WwYcPMQq67HczNpk2bJE+ePCHPgcASQstggetm8eLFuh2zQonMvMvQ+ffbu3dvpbxjqMD62pdffhk3RojG8FkK7QJyRVlEuKdBtwCnfMzPyy+/rJQ7DBaY+5QpUwY9xg05YgDYAKlVos9foOg/4Ndff12zTB/uESGqDCW0gpgJAk818x7v/i5duiQpUqTQZI4ykLVr11Y2XJoV/u8ZaPfKlSvy66+/yhNPPKE48fnHP//8owgBjZZihcAPAkQjTlpmjdNp7VBs5TUjUATv2bMnYI4SJkokf5+44rS5Yz4kQAIOINCuZSNZOGeGTyZQnaOmL4MESIAESIAE3EoAX7SwEIMdPdEMLCqgdBoWtqKxoBXNsWE3HcpozJ07N5rdWtIXrPIhsnJambvOnTuHtAyPBEiGDBmUnZ1mB9ysUNIeTBkkQAIkQAIkQAIkQAKRE6hfv7588803AQ3t3r1bcQVhWEugYcOGMmXKlIBOILJq3uK/HytjxjciXw4PLNmGPrt27SqffPKJld2zbQcR6Nmzp+b3rJ9+FsE1Ge2oXtVXEAiH6O+//56ue2FOxJo1ayLeAAYRD4Q5r7zyipQuXTqoM06YaQY9TUtshc+x1157TTl369atup35vMVWcOuBGxTEFkZjzJgxgrJr/oHKLhAE2RFwooIY5r777tPs/t9//1WEJcEcwCCYgXhJrRydf8NwJxswYIB88MEHmn0GKyMYynnK0yhE4g0aNJAECRLoRot5LViwYMjjQ5W1c0OOnkFirVprzfiPP/4QlLvTClRy0BI34doKJTjCdQM3fQjXIDoMVuEIm21hzKEWcLSCwAniOSOB96ps2bJpvp537tzpI9SbMWOGvPvuu3Hjwro78oZbn3egzDbEpaGEZmq5oswnXht6rkMjY3XTsRRbec0WLlIoDf0Db2z7Tl1z07wyVxIggSgRaNX0NVn2baBqXE1BHKWU2A0JkAAJkAAJmEIAwg8sTNoR+NIMd60ePXq4fsERu88gslJ72GMH20j6xCIUrgsIg5wWsGvPnz+/HDp0yLLUsKCIXVtmBFjCJhzXulOcwcwYF9sgARIgARIgARIgAScQ0Hpw7f0Qygl5xmoOag+KvxxpvcjKn2fvniK9VfYzQNjCe/BYvfp8xxVMbHXi7H/lKqMdI4aJdHjHt1dsZILDFcM4gdWrV/u4PxlpAcJciFvKli0ryZIlM3KqqcdqfWahVFenTp2UMoQQTOkVZniEP7dv31YEZKFcj7QGAyetQYMGBfy5devWimN7OAE3HDgf5syZU3GUgksTSvzCRevbb7/V1SRctYKV83v//felf//+QdsCl9y5cyt5VKxY0adco+dEiKyWL1+uCHTXrVsXtD2IjNUcNXFSo0aNZPJk3+o43o0ZLZHofa7eygQQ1wTb/OmGHD3jhlOTlmNUqM93iPDCERShb4/QylMqEtcHXNa02oMQC+uIaoHyjyi3rCdg7oHPMlyn3o5eKKf422+/KeKvAwcOCN5HcF17Aq9dbEpVC08JSu+/4bX46aefKmvx4cRLL70kH374oasrDoQzbpxDsZUXOdi+wVbUPwoVKSbzlgd/Iw13AngeCZCAuwk0q19LVq9YEjCIcePGSdOmTd09OGZPAiRAAiQQ7wlghyW+sNkZWATHFz23LYajpB0WnyCocXt4nJcgsnKq49jYsWOlefPmlqLGvZ0ZC+AoawPRGl5fDBIgARIgARIgARIgAfMJwCl34cKFAQ3joRQE+gzrCAwcOFC6dOni08H8RSJV1c0drEtERC6cF8mUXuT6dd9u4N6wYsUKS/tm484gEExsdeOuPTnu3SuSN1dg33x/Cm8+9JSL828Z5eDg9gL3aieEltgKrlbYuGdEmIHxeMRWcJuJxMmvUqVKsmzZsgBEbdu2Dero438CxGxYB4EYQ62Mmed4CKJxDMoeBguIXeA6ria4we8zZsxoeFrhMgRnHqx5oV2UBIQbVKhcPB0tWbJEqlSpEtBvsJJ3OBhjWb9+vRQoUMBwzhDRoYSg3oBISc0RzA05+o9Ry/0LGyQhBtSK1KlTGy6nibZQKg/CO5zvHX369JHu3burdtetWzdBaUb/mDVrlsANSk+MGjVKec6MspFGAmv5wdYcg90HwQX22FQIvgAAIABJREFUrbfeCru8Idp+7733FBGrEZc2I+Nz2rEUW3nNCC5YtYch9Ro3l36DzNnB7LQLgPmQAAlERqBhnWqy/ofvAhrBA7RwFcCRZcSzSYAESIAESMA8Arg3dop42C2iK1hvjxw5UvmJhXCLMAiLgFY+MMFDOdiJw44+nEDpRYjVsOuQIqtwCPIcEiABEiABEiABEtBPAA881R4Qb9++PV6XOdFPMPwj/Uv0fNxb5INu4bcX6ZkN64nMmB7YiscxJtL2eb6zCThRbAViZUqJbFjvyw6O2C1btnQ2UAdmBycWPNhXCzzsh5jll19+Ub7Pw1UJZbXgZuSk0BJbIUeIOSDaMBIQW+E9Dm5FwQJs8Hk5c+ZM1cO0SuPpFX9B+IxnZIULF9adPtx6sG6yYcOGoOdovV7gxjVkyBDd/ZlxIMY5f/581abgdoV1Na1Ayd3XX3/dcBpnz55VXJWClUr0bxRiIbgj+YcbcvTPOUuWLKol/958802BQEkt4BCXJEkSw6whtMI9pVrJSYhktYRyKMGJUpzece7cOXnwwQdD5oCShgsWLFDes8IJvP4hKNUKvDeuWrVK8+93795VxIYoOXjx4sVwUlByh/i+du3ahsViYXVo40kUW/nBx5tN5cqVfX7b4b3u8s67xj7MbJxTdk0CJBBFAq9VryCbNq4N6FHtgzSKabErEiABEiABEjCFAIQlwXadmdKJwUZKliwpsAwvVKiQwTOtPRxfsCGwwoIPrNrdHrB1h9jODcIgLMLhurAySpcuLSgJaSQgsMIiIUpCOO16NTIOHksCJEACJEACJEACbiNQvnx51YdIeOAe7oMrtzGwK19/F4Pv14qUKGVXNiLLlopUrxrY/6OPPio7duxwrHOvfcRiq2eniq0+7S/S7X1f1sHKkMXWrJg7mlatWinrMGqBSkZOca8KNupgYitzad1rDWIOrHFg3SJXrlyaDk5YF/QXmegRNKGMn5YILtSYrl69Kk8//bTA6Uor4LzjX8owXFerUPmE+juEfKicpRbBrk8IXr777ruw3H+wzgQxjJGAcGbo0KEBp7ghR/+ksQaoJsiD8Amf7WoBYVr69OmNIBO8Tn799VfNtXGIkh555BFV0RuEjHA8845QIigciz5/+uknzWtKzwD8he/+56jlptbumTNnFMHY4MGDDQn7vNvCeFDa84033pDkyZPrSd91x1Bs5TdlixcvlhdffNHnt206dpVOH/R03eQyYRIgAWsJ3L59S+rXqCSbf/LbhiIiWhar1mbE1kmABEiABEjAfAIQi2A3jdMCtsTYrQRrZCwO2SUK2rVrl7Kwh5/r/vUpnAZNRz4QWcGh001lG+EYpbZgpGO4ug8pUaJEyJ2VaAyLkHjNICcKrHTj5YEkQAIkQAIkQAIkYCoB3NOqCeVR6rto0aKm9sXG7hGA+4F/iZ2zF0VSprSXUqrkgaUEkRE28bRp08be5Ni7pQTgNlOrVi3VPtZsEHmuuKXdaza+9geR8mV8//zqq68KSuIxjBEoV66crF69OuAkLVcmY61H5+hoi62yZ8+ulAiDOxACzkrTpk1THSzW3CBO9Y7OnTvLoEGDNOGg/b///jsieEuXLpWqVVWUsv/fqpozD97TISiKZkyePFkaNGig2SVKE0Ksoxbh3pOo6Rj0jBmvCQgQEyVK5HO4G3L0Hx/K8KEcn1rA9Utt4zDEe/ny5dODKu6YLVu2KMK/YNG8eXMZO3ZswCFqwq/nnntOEVJpBdzmtm7dGpH73vnz50MKyVFitG/fvrpZwBUM190XX3yh+n6rpyFcf/369VMc98JxGNPTh13HUGzlRx5KWP96nhBaQXDFIAESIIGAD/VqZWTLpo0BYKDSVfuAJUESIAESIAEScBsBLMBgR4zTA+Ig7OwKZs9t5hj27t0bJ7K6fPmymU3b0hYEaxBZgaGbAosoKPGHHYxWBso5BCsNiQd6YOc2flYyY9skQAIkQAIkQAIkYBcBrYdZGzduFPyNYQ2Bv/76S5544gmfxk+fF0md2pr+9LaaJ6eI2nN/lAb68ccf9TbD41xIIJhbd81aIjPn2jMoNbEVHkLD/YNhjIBWObFSpUoZdqc21rN5R4cjtoIoI5zyXnCZgSOQt4CqV69eSrk/tfj555+lSJEiPn/q2rWrDBgwQBNAqBJleshhnS1lEKWumpiuWLFiAnGMWuB4jKVTp06aIh09eXkfs2jRIqlWrVrQ03LkyKHpGoYNm0mTJjXULVybcG2HM/foaM2aNQLndu9wQ47+kNq2bSvDhw9XZac1L0bXt/UKskeMGKEq3MZr9MKFC3E56iljCDfGjz76yNA14X8wSvcNHDgwaBtz587VFCKH6hyiNayPjh8/PqzrEGJMvOdAYJw4ceJQ3bni7xRb+U2TmvL1w16fSvPW7VwxoUySBEggugR6vt9JJowO/FCHrWKHDh2imwx7IwESIAESIAGLCGzfvl1xOsLuGKcHvsyiHny7du0scRb6559/FJEVvlhi4dbtAScmiKzgxOTGwFzA8tzq+P777xXHKrwGwCxNmjTK/ON34GeXs5rV42b7JEACJEACJEACJOBGAnAhQMlA/1i3bp3l5afdyMusnNUeZG7/QyRvXrN6CK+dCmVE1vygfu6cOXPk5ZdfDq9hnuUKAlrlppD89FkiL9eJ/jB69xTp/bFvv8uXL5eKFStGPxkX9wixilZZKr1lspww/HDEVnCgr1GjhqH0ITiCwBRiB++YOnWqpjsT3IOQn3eEKoWGdblz584FOCgZSRYbHFHeMFighJsnQh3vcaC6c+eOfPPNN4rYAwLhcAL8Fi5cqMslCWXrUL7OP1DSWO0+JVg+e/bsUYRvwYRWcO+EU5nWGh/Wz7788kufbtyQoz+XPn36SPfu3VVxoXwlylj6B65lOGLpCTgi4v7AvzSy2rkrVqxQKh2pBeYsZ86cyp9u374dUlykVh5TT76eY+D6r2d9V8v9y0hfEI/Nnj1bPvzwQ01BYbD28JwBjnpuKPUaigvFVn6E9u3bJ1BxekfvgV9Ig6YtQ7Hk30mABOIhgZHDBkn/nh8EjBy1lmFhyyABEiABEiCBWCHgJsGVh3m2bNmUHVv4F1/iIik3ePjw4TiR1enTp10/rRAM4Qs4fiAccmtgxySEUFYGXKvw4AhCuwkTJigCK5YItJI42yYBEiABEiABEiCByAholcTBPR3u7RjWEMAD7Pr16/s0vniZSAX1Z5DWJKHSatpUIpcvqXeHzbLYNMuIXQIol/TJJ5+oDjBFCpHlq0SKPRO98c+eKVL/Vd/+sF5h9ffa6I0wej3hOzrWe9QCjkNwuDErrly5orjUQOhy9epVuXHjhvKDclhwYILAKEWKFMq/Rt1ajIqtIJiBqMKoKxLK2T355JMBSFDWTMv1EaIViFe8A+5IuGaDRaTPx4I5F6Fff9egMWPGyJtvvqmaEoRNcLXyFs5A+IIyoxBdaZX5828Mghr08eKLL0qyZMl0XVoorasmjmrWrJkgZ72BNUnMEf7VCriWbdu2Te6//37lWlQLcDt16pRP/m7I0X8so0ePlhYtWmjOt5qQTW+ZSXDENaFWilCtQ5TM9Aiq/P8+ZcoURfzmCZQxhDNUsFi1apVgrdNI4P0JQi2ICkMFHBThpGhWQHSFEri9e/c2LGCEABSCLbi1uTkotlKZPdjHbtq0Ke4vA4eNljr1Grl5npk7CZCARQQmj/taPuoS6Hx3/PhxgSKcQQIkQAIkQAKxRABCk6ZNm7p6SBAWQSgDJyLPj1bpwdWrV8v69euVRU98P8CCWiwExhsLbkx6FvjMmC+P2MqMttgGCZAACZAACZAACZCA9QTy5Mkju3btCugonAdY1mcbOz0MGjRIOnfu7DOgkWNEmjazb4w/bhR5vsS9/gsUFPl1x73/h6sV3CsYsUsAjlGVK1fWHGCGjCIHjkRn/BPGibRQeT2wSkZ4/CGggZOPWrz00kuK+5B3wNUI5ekuXbqk/Is1nmvXrsnNmzfl4MGDilBg9+7dihjlxIkTAvcXuFsbLdkG5yOUVC1QoIDkz59fqlevLhC0aIURsRXaRik5iH2MiK3gCt6ypbqpCJyXtJ5lqYmCIDrDBr5gAcEKBC8QUxgNCIYgkAoW/s5lwUSVEDVhHGoBd6zNmzcLxGFw/dq/f79gg2W6dOmUtcO8efPK448/LihRiA2cRkPLGalJkyZKGTY9gZzwHhbKiWvr1q1SuHBhpUkI8jDnavHtt98qgjFPuCFH/3FgDHhdaQWc1fw3lkJc/fnnn4dEjjKbxYsXD3mc54Bg5QFbt24tKDPoiVAiQs9xauUe1RKCyAoudxBF6hUNWvXsGhxwP4UyiKGuVf+xYO29RAmvmzXd9J1xIMVWKvOAmph4+OCJL0ZPkZdqveKMGWMWJEACjiLQ96P3ZMyXvh/QuDmGJSWDBEiABEiABGKRQCwIrvznBQsmWOTArrYtW7YoD2bwxTzWAqIhzF+slLx77bXXZMaMGZZPE8VWliNmByRAAiRAAiRAAiRgKgE4DMBpwD9Q6qVChQqm9sXG7hHAwz44JnhH949Fuvewj1L/fiIffXiv/2Zviowdfe//IYaAcIER2wQaNmwocBjRCjhbrf/JWgbDhop0ah/YB0Q4ELvodcqxNkt3tR6sfBdGAsEOhFX//vuvaim3aI02VNk5I2IrCIJgGAKBmF6xFa7/SZMmBR2ulrsRxEZ//PFHwLkoebly5cqgbUI8sXTpUsWFSm8sXrzYRwikdZ6/41a9evUUdx21wHs83uvtCC2uEKNBRBXMBQ1CMKxVagnFvMczduxYeeONN+J+tXHjRk3xCkrpea+luSFH/7mDQO6ZZ7QtCT2vE+/zqlatqlyPwcKo45inLS1HVQj1IOD0BASIKHWtJ9q0aaOUloXw68EHH1Sc2SAQhbsZrh2sYX/11Vd6moo7BqLEvn37GjrH6MFwjYMADGUeQ7l4edrGewREbmrOe0b7t+N4iq1UqEP9CZUqLgjEqMmzpUKVl+yYH/ZJAiTgcAItGtaRlUu/9ckS9rXhqNwdPlSmRwIkQAIkQAJxBGJRcBXL0wuxEDaThLJ5dxMDWL336BGdpzYUW7npymCuJEACJEACJEACJCDy6KOPyqFDhwJQ4CFbMIcbsouMwJdffilvv/22TyOVKot8G/zZZmSdhji7UnmR71fdO2jSVJFG9yr6yH333SdwhmDENgE888MD6+vXr2sO9PkXRFZaVKG+Xx+Rj7urd/3OO+8oJeEYxgm4aW0qWFlDvWKrbt26KaW6EHrFVhBLQZiiVVbOQx0uQXALUguI1fydrOAEpUe8DGHYkiVLgpZkgyMOyvx+9tlnAie6UAG3rL179/qIuPBMH5sn1QL9wwnLjoDDmZbLD0oSjhw50qe8oSfHY8eOKU5kWnPiPRY1MR2EWhCe79u3T3XYcHLLkiWL8jc35Og/iAMHDgTdSIrSmP5irBw5cmjyQPsQ/OzZsyesikXBXLPglPbQQw/FDSGYMDDYNYr8jLrsebeH88EtWHlEuGOVLFlS4AxYs2ZNRewVysVOK2dobObOnSt439LjdAUBIo7DfZnbgmIrjRlr37593A3OpFmLpVSZ8m6bW+ZLAiRgMYH5s76RDq2a+PTy7rvvyqeffmpxz2yeBEiABEiABOwn4KZFLftp2ZMBxN8QWcGePJYCttRYjIxWUGwVLdLshwRIgARIgARIgATMIZAhQwZBmRT/WLRokeCBN8MaAnAOwkNf70ifXuRQ4FRYk4BfqydOiGR5xPeX+w+JZPvv+bIS/q4TUUmMndhCIFiZMU9CzxUXWbPBvPRu3BBp31ZkzCjtNlEyDeXKGMYJqLnpGW8lOmfAZQuuNmqhR2wF0RSuFY+blV6xFZzbIaYJFUOGDJGOHTuqHvb9998HbN6DmAfXrd7SZcgfJRUzZswoKVOmVJzcIH6EuAJCaCMiElSV8V8T0nIWwoAghEGpTjuiTJkyipBMK3BddOnSRSmHCUEOXO5wr4LNhXqY4Dy0f//99wd0MWDAAOnatatq197CPTfk6D8IODypjdlz3O+//y758uXzOU3Lwctz0LBhwwRuUuEEREW1a9dWPdX/3hOlSTHvWkK4cPrXc46/G5z/OXhNY/1z3bp1Pn/CZyeuR71Oev7tQkwJ1zk4n8KVK1i4taQuxVYaswr1IlSPKB/yWPaccuPGdblx/b+f6///359+MVrq1PP98qDnguYxJEAC7icwbeIY+bCT704tjAo3iOF+6LifCkdAAiRAAiQQ3whQcOXMGceuI4issIEk1gILhVhEu4FV6ygFxVZRAs1uSIAESIAESIAESMAkAunSpZMzZ84EtIayJnDvYFhDYOHChVKjRo2Axn/fJfJ46Gf9pie1fKnIS1XvNZsho8jSFSKF8t/7HRwmpk2bZnrfbNB5BE6dOiXPPfecaolR72xTpBQ5/a9IokSRjWH3rv+EVqu+025n1KhRAncbRngEIA6CSMgN4V+6zTtnPWKr9evX+5SF0yO2QulAfwGsFiu4vxUpUkT1zxDtQBDkH8HOsWpO4OwFoZB/BHPmgqMPnJzSpEljVVqa7TZv3lxQ4s+KgGAHQjU4fakF7oNwP6QWYAJROgRLbshRbQzBxFMYW3qovb0CZfi0AsJrCLSSJEkS1lTBiQxCQrXAezze673DSDnBsBJSOenIkSOaOeJwlDvMnTu3ane41nCvpEe4qZUvBHJwrxs+fLhmWVc7X6uRcKbYKgg91JPs06dPUL7Dx06VajWit6s6ksnmuSRAAuYQGD3ic+nX472AxuxUyJszMrZCAiRAAiRAAsYJUHBlnJlVZ0BkBYEVfuxYRLJqXJ52YV2fPXt2ZUNMNINiq2jSZl8kQAIkQAIkQAIkEDkBrQdwcB6oVatW5B2wBVUCcNeAQ4Z/jJ8k8roNe9ZHDBPp8M69bMqVF8nyqMiEcfd+169fP8VtgRE/CKiVulQbeerUInv/EUmTNjwuy5aItGsrsl+9gpfSaK9evQTPIBnhE7BSJBJ+VoFnVqpUSWbMmKFZjiuU2KpZs2YyZswYn4bhQoM1IC33oxYtWigl6owEnIB27twZcAryX7ZsmWpTEBJhHqIRWOvSEteFEt7Z9XrTW27RKD+4dMItCC5hwQLjhiuRWuCawrXlhhzV8g9WOhJixMSJ/4+9OwGzsX7/OH7bd7IllL1sIYUsLaRIKLJkSVRaJNG+R/X7lzaklOpHCBUlS5SUJS2EbGWXFKJQ1hTpf32+NfMbM2d5zjpnZt7f6zrXYL7b83rOmHPOcz/3nfOEYSqLp6B7X03lK1UyL5IWqEzhwYMH05TyfPPNN61bt26RLOl5rMpoqpxmoKYMXCofGKgpWKpfv34RJRzR664HH3zQ7zK+Mtd5PtB06kiwVQB41ZO88sorTXdkBGp3P/SY3TIgbeBFOp1TlkUAgRgJKN3hiCGDbdjT/9TFTt1+/PFHU11ZGgIIIIAAAllNgICr9D/jPXv2dNmsKlSokP6bidEOdJel7pyMd9Pd+VOnTo33sqyHAAIIIIAAAgggEKZAvnz57MiRI2lGZ8QLOGESpMsw3RRRrFixNGvfcZfZ4Gfiv6WbbzAbnSI+od8AsxeGnbgPvc73lY0r/rtlxXgJPProo+69c7BWoaLZJ/P/CdDz2lQh6fkhZs8HSbYUTiCM1z1kpX433XRTmowx8Th+ZRIqX768uxZUtmxZly1GGYRUBk6PokWLJn8NVOosaa/KPqUyrL6aMr2o3JivDEX+SmOqtNynn35qefPmDYlDwVk333yzzzEK7vLXvP5MhbSZVJ1Tlr3zNY+y5SgIJFBbsGCBXXDBBZFsI+Sxuqao54jKA0ar6f+PESNGpAkm8jW/blosV66cz6C8pNKWGWGPvo6tT58+NnLkyDTf0s/nLtURTtUOHz7sgonmzp17wneaNm1qKpUZadNrTGWw89WWLFli9erVS/MtlQZVsGWsSwq+8cYbdvXVVwc8xED7TzlQWcBUnvKyyy5Lkz0s0AIqn6jAvtQlQFOPURKkQMFYkZ6nWIwn2CqI6v79+61x48b27bffBuzZuXsve3Loy5Y9e/ZYnCfmRACBdBaYN+cDe3HIYPt6ySKfO+ENUjqfIJZHAAEEEEh3gUABV/pwyN/ddum+8Qy+AV0YGDZsWKYOstIpuuSSS9yb8ng13R2oO8/UdBeglw/j47U31kEAAQQQQAABBBAILJAjRw47fvx4mk7KAnHVVVfBF0MBlZjZsGHDCStc3MJs1uwYLupn6nPqmK1e9b9vTptpdkXr//29YcOG9uWXX8Z/Y6yY7gJeg0Pqnm328qtmZ/uurnbCcSjASoFWCrgK1O68805XSokWuYACCK655prIJ/IxgwJRlOmpRo0a7qHgKpUlU9BT6ow5kW7gtddeM11f8tVGjx5t1157rc/vKcD1vPPOOyEbVZcuXVwWrAIFCoS8LQVDnHbaaT4/vwsUbKWF3n333aBBFCFvyMyVyFMgVadOnQIO37FjhwtqCtT02aT+z9d5jWcLlsknlL2EE4iirJ4dOnRIs0zKoKSMsMfUB7Bw4UKfwXOBgqcOHTpkyvKksUktdYnOUM5H6r4KtlLQUuq2atUqq1Wrls+pFRB33XXX2XvvvRfJ0gHHekkUsmjRIldqN5RWu3Zt93On/xv1fNL/jwow1f8XCuJTUqPvv//evvjiC883zz7zzDN21113hbKNdO9LsJWHU+DlP2lNc27j8+3xZ16w06tW9zArXRBAICMI7Nn9i7045Ekb8+oIv9s9/fTTTS9YzjzzzIxwSOwRAQQQQACBmAko6EdldX01fdCj35nbtm2z3bt3x2wPWWVilbZTAJA+RMjszd+HFbE6bn1IoAtxusv9rLPOsl69esVqKeZFAAEEEEAAAQQQiLKALuz4uxA+YcKEuJVsifJhZZjpFMw2adKkNPv98SezUqfE7zB+/92sSP7A63nJ9BC/HbNSvAW8BlxpX71vNLvvAbNy5U/c5cdzzKa8Y/bJx4FLBmrUhU2r2YMPDHc3EtGiI6BkGcouFenNfRdddJE1b97c6tSpY9WrV3c3s8UzsYay8JxyStr/IJs0aeIyVAXai8qlqY+CKUqWLOmyzWTLli1sYAV8qOJT6hYs2Er9N27caI8//rjp/9ZImwKj7r77blNwopfsYFpPARrPPfdcwKUVEKKM6cECsyLdf8rxel2irEL6nCncpn3rJlcFCoXT7r33Xnv66adPGKqfHT1v1DLCHlMft4Lq9fOaOsBbn5X6K52oOfT/hTwUXKjPG6OZ3XL79u1pqh/pubxnzx7LlSuX31Onn685c+bYypUrbfXq1bZs2TKfJT2TJtCcCnSqW7euuy6tbF2+XnupvzJRrV+/PujTRhlhkz63D9o5hh2U5a979+4xXCH6UxNs5dFUdWq9RLuWKl3GHn1yqLVs087jzHRDAIFEFXhv0kQbMXSwbd4Y+BeRouF1JxQNAQQQQACBrC5QsWJFd8dKoFakSBH3IZY+/NEbSX04RvMuoLspFdTWrl3WeL+hOzj1gVI8G5ms4qnNWggggAACCCCAQHQFdLFIZQR9tXHjxpnKNdFiJ+AvgOXNSWYdAicmieqmPp1vdnGz/015+ukKBPjf3y+++GL3fpSWtQX0HHj44Ydt8eLFMYMoVCivPfDA3XbffY/FbI2sPLEyYKcOYAuWXV2ZqhS00qJFC1NAUzhZoKJt/uqrr5rKIiY1HYNKjylbYLybEguoRFtS6Tv9v/7II4943oYCO5588kkbO3as5zFJHRX41rt3bxcA4zXIKmnszp07rXTp0kHX1Pl/8803XbBKNJsyFG3ZssWUwEXBNfq8U69HlG0sT548LsBnyJAhIS95xx13uJst9ZwItynLkF7/pAz40n4GDx6cPKX6JPoeUx+/r59/fS6tz07Tq73wwgt22223ueX1/4uMlYEunKZzouAwZeRS1tbChQu7n4vUAZX6mRk1apTPJQYMGGBDhwapbfvvSHkq2DLSANZwjjVpjNZWtYGM1Ai2CuFszZ8/35o1S/EKPcDY1u06Ws/et1j9hk1CWIGuCCCQCALvT51s77w5zhZ88lHQ7egNmd6c0xBAAAEEEMjqAitWrHB31HhtJ510kvsARW+A582bZzNnzrQ//vjD6/As109O+nAlq2RZ0odUypIW70Ar3cmq5zINAQQQQAABBBBAIGMK6OKmbvDw1V5//fUs83o6vc6eLjLXq1/Lftqx94QtPDzI7OGB8dtV/1vNXvZfqMCV68kqN7DETz1jrqSL2Aq4Uum1aF5gzps3rysNdcMNN7iMybTYCWzevNkWLFjgSlddeuml7nfAU089ZQpgUvaexo0b2znnnGMqDVilSpWQg3hit/MTZ1Z2IQUMKWOPynH5CxyOx34UuJyULUuf34XTfvjhB1u6dKl988037nMWZe35888/nb/OkbI1FStWzCU6adCggTs//n5/e11fASf6rNFL69evn/ucTXsIt61du9aVjXv77bf9ZiJKmWlp3bp1dt9999m0adMCLqlAsG7dutn111/vngvRavrsVZmDFJSmnxFf2ZYywh5Teuh5piChX375xf2sn3/++dHiCmse/RzreSHj4sWLhzVHqINU/k9lAH216dOnW9u2bT1Pqddxt956a0zLGvrbTEbNOEqwleen1z8dFXClwAr9sHhp3Xrd4IKuzqhWw0t3+iCAQDoJKN2qAqz0+HqJ719KqbemaGBFBdMQQAABBBBA4B8BfQCjNMyhNI3R71PdObNw4UIXdDVr1qxQpsjUffVBk3z0CPcDrowGpLsfdbwKuIpnk7U+AFTJABoCCCCAAAIIIIBAxhRQNgl/FyYVTKELl7TYCvjKblWmrNnqtWYRJOYIadPn1DFbvcr3kL59+9qLL77S6X+pAAAgAElEQVQY0nx0zvwCyuIzY8YMF4ig64DhNl1cV5CVsjSrxBUNAQTiK6BA2mDBTEk7UrYolR5UYJOXDGeHDx92ZRtnz55t77zzjm3bti3owXXq1ClNiTfNoyAhZWFSwKc+j9L/HQpAU5BOPMtY+juAjLDHoPhZpIMyXvkLFt67d68VLVo0ZAn9Przllls8PcdDntzHAL0u0+uzjNgItgrjrOmFVteuXV2EsZeWv0AB69m7r/W84RYrdUrwFIZe5qQPAghER2Dvnt3/Blm9YRvXr/E8qdKMKv0nDQEEEEAAAQT+J6APCXTHll4vb926NWQaZW1SCTfd6aagKz0++eSTkOfJLAPOPfdc+/DDD7NMkJWeP/pAOpIPtiM599zdHokeYxFAAAEEEEAAgcQQ+Omnn6xMmTI+N/PKK6/YjTfemBgbzcS70E2tl19+kX344WcnHKVOy5jxZk29FQ8JW+jdyWZdO/serhJVWfk9ZtioWWzghg0bXAm3TZs2ubJg+vr555/7VFCAhsqSqdybsibpPW25cuWymBiHi0DiCOzevduVb9PPcSitdevW1rBhQxfspOCn3Llzu3JtCuLeuHGju0FUj1Cbr2CrUOegPwL+BAJldK1fv7599dVXYeMdPHjQXnrpJVNpRC+BheEs1L59e5dl7XTVe86gjWCrME+cajjffPPNIZWYKF32VJflqtcNfS1P3rxhrswwBBCIhsA3q5bb++9NtmnvvmU7d2z3PKV+OSnQqnLlyp7H0BEBBBBAAIGsKKCsRAqaSXooXbjXlhR0pQxDq1evTg68+uyzEz+s9zpfRu6nDE/KppnZm6+73+N5zP3797dhw4bFc0nWQgABBBBAAAEEEIiBgDJFqAS3r6YLRn369InBqkyZWkAX5a64oqV9/fWJN7fmy2f2wktm1/SKndkFjc0WfZl2fgXhbd/u/XPg2O2QmTOiwB9//OEyh+ihi9v6WrZsWatYsWJGPBz2jECmFlDgddOmTUMOuIoFCsFWsVBlziQBfW6uspO+mm5o1k3RkTaVNp03b56NHj3aJk6cGOl0VqlSJVfyVRnlFBiZ0RvBVhGcQV1A0kWBUD+Ur1azlnXvdaO179TNChQsGMEOGIoAAqEKKMDq/amTbfbMwDWRfc17++2325AhQ0Jdkv4IIIAAAgggYOZKwk2dOtU9vKbzPuuss9yHI3pceOGF7k4ylRicM2eO37tKMyO2gs9ef/31zHho7vmg11jKapVerU6dOi4oMKuUaUwvZ9ZFAAEEEEAAAQTiIbB582aXXcZX0535t956azy2wRpmNmHCBLv66qt9WijY6p77zM6oGj2q2R+Y3Xu32Zpvfc+p7MtkHIqeNzMhgAACiSyg6lSXX365y1KXXk1lCpW1//zzz0+vLbBuJhdQuT89z301fdapz9Oj2Y4dO2Zr1qyxRYsW2bJly0yBjfpZ01dVqlBGOJU1VNZHPf9VGlOByXqcdtpppioO+pqZGsFWUTibukCgoKsVK1aENNtp5StYu07dXNBVxcoZNz1aSAdNZwTSQWDL5k0uwEqBVhvW+Xm3HWBf11xzjatNq18CNAQQQAABBBCIXCCcwKukVRUQ065dOzv77LPtr7/+so8//tgFX+kNXWZuCjhTmbvMEhCkN/x6D5VeJQOTnisEWmXmnxqODQEEEEAAAQSyosDatWtdSS9fTTdNK6MpLT4Ce/fudWVh9NVXK17C7L77zfrfEdl+9uwxe+lFs8cDJG/4dOGrdv55N0S2EKMRQAABBDKUgAJD9Lv/7rvvjvu+9bml4gcyW2BJ3CFZMKCAnt+6idVXO3z4sOVTSlFaTAUItooSb7hZrrR8njx5rV2nri7wqmGTC6K0I6ZBIGsL/H38uM3/ZLYLsJoxdbIdDeMCbMeOHV2QVbNmzbI2JkePAAIIIIBADAX0OnrMmDHuEUqpwaQtJQVe5c2b1938oOCrn3/+OYY7Tr+pFWilDFc65ozaEiXISn5FihRxwV7KoEZDAAEEEEAAAQQQyBwCq1atMgXU+2p63afX1HXr1rXrrrvOzjzzzMxx0Al8FCrbOHLkyIA7bHmp2QMPmTUKsZLMsWP/BFnp8d1m/0ssWtLQzq3no65gAruxNQQQQACB6AmsX7/e7r33Xs+Z9iNZuW3btq482hVXXEGgSySQjPUk0K9fP3vxxRfT9NVNuyr9R4u9AMFWUTYON8tV0jaaXXypC7q6vMNVUd4Z0yGQ+QWOHPndPp07xz6dN8cWzp1jP2zdEvJBK8Vh+/btTdmsLrvsspDHMwABBBBAAAEEwhdQKTm9ng438KpChQouPbKCaHT39OLFi13pwczWFGylLFcZpSmgTqUjdV7TO5NVSjMFrqlEIw0BBBBAAAEEEEAg8wgsXbrU6tev7+mAGjRo4IKurr32Wlf2hBZ9AZWaUbWAgwcPBpw8Rw6zBx4263yVWdVqgffx8y6ztyaaTRhvtvzrwH0XfGZ2XpORlt1uiv7BMSMCCCCAQIYSUOmzRx55xGXIj1a75JJLrGXLltaoUSOrXr26FS1aNFpTMw8CQQUuvfRSmz17dpp+ynY1ZMiQoOPpELkAwVaRG6aZIZIsV0mT1ahVx5UXVOBViZInx2CXTIlA5hDYv+83F1yVFGS166cdYR2YXghdeeWVLtCqcuXKYc3BIAQQQAABBBCInoCCcpQKWUE64TYFX9WsWdP2799v3333nW3fvj3cqRJunAKuhg4dajrGRG7PP/+8DRo0yPQeKZFaz549XfAXDQEEEEAAAQQQQCBzCXz55ZfWuHHjkA+qR48eLvBKmQBo0RW4//77bfDgwZ4mzZnT7KouZp27mDU536xw4X+G6e3E2jVm777zT6CVAq6CtQ8/Nmve/HTLaZ+bWclg3fk+AggggEAWEdBnhBMnTrQ333zTFBQcSqtdu7YpwKV58+bWpEkTK1CgQCjD6YtAVAVUpnLbtm1p5hw1apR7XUuLvQDBVjE0fv/9923s2LH2zjvvhL3KSUWLWdPmLe3Ci1u6r/o7DYGsLvDtqhW2ZNHntvSrL+yLT+fZr3v3hEVy6qmnuuAqPSgVGBYhgxBAAAEEEIi5gLJdDRgwIKKgq5hvMh0XUNCVsjMpPXmiNZV1VImWRGsqK6NgPpWQoSGAAAIIIIAAAghkLoFPP/3UZbsNt1WqVMldnNKjdOnS4U7DuBQCuulFF6VVxinUdvY5Zr/9avbdd6GNnPq+2WWtzXLabMtmLUIbTG8EEEAAgSwjoJsDly1bZps3b3ZZ8n/99Vf7888/LXv27JY/f34rXry4lShRwqpUqWIKtNK/0RBIBIEjR474LVWpmw8aNmyYCNvM9Hsg2CoOp/izzz5zQVe6c/qYComH2Qi8ChOOYRleYM/uX1z2qkWfLbCli7+w7zZtCPuYypYta0rrqYdqJxcqVCjsuRiIAAIIIIAAAvERUNCO7jDft29ffBbMgKsow5UCr/r3758Q2a4UzKSsVioLmUiNQKtEOhvsBQEEEEAAAQQQiL7AgQMH3MVQ3bQRaWvVqpULuurYsWOkU2X58V988YW7QWT37t0xtTitnNkzz5ld2dEsh71k2a1PTNdjcgQQQAABBBBAID0EvvnmG6tVq5bPpRU0yE2m8TkrBFvFx9mtoid9UtBVpG8qCLyK44ljqbgL/H74sK1cvtQFWC2cN8e+Wbk8oj1UrVrVWrRokRxklTdv3ojmYzACCCCAAAIIxF9Ad5rp5gV9VSCPvq5cuTKuGylSpIgL+jrrrLPcV10sUInCRGvam7Jd6QKT3lirZJ7XN9hr16616tWrh3VIWi/p/U6gi1u6O/D48eNhrRHJIJ0/PXd0/mgIIIAAAggggAACmVfgpZdesilTptjq1avt559/jvhACxcu7IKurr32WhfIRQtPYNasWda6devwBnsY1aWb2aDHzKpUvs2yWwfLZhd4GEUXBBBAAAEEEEAg4wlMnjzZOnfunGbjJ598su3a5aHecsY75ITcMcFW6XBaVDtTF4p0IWLTpk0R74DAq4gJmSCdBVavWOaCq1Z+vdRWLV9qG9aFViPZ1/br1avngqsUZKULjjQEEEAAAQQQyJwCCrpS5is1BfikDvLR9xRgE0lWLAVVKXhJmaNSNv2bXtNnhKa9KshID2V3UsbdVatWpXkcPXrUpUR/4YUX3AUlL00GymDlJYuV5j58+LCXaaPah0CrqHIyGQIIIIAAAgggkCEE9uzZY71797bPP//clQb666+/It63PnPU6+Srr76ajPlhaH711Vf24osv2htvvBHGaN9DSpQoaI8+1tn69Olk2ew8MysYtbmZCAEEEEAAAQQQSESBRx991AYNGpRma6rqNH369ETccqbcE8FW6XhaDx486IKuJk6caKqdGY1WsGAhq133HKtdt557nFO/oZ18CrXlo2HLHNER2LxxvQusWvX10n8DrJbY33//HfHkFStWtAsvvNAaN27sHjVr1ox4TiZAAAEEEEAAgcwjoCAsBV3pqwKwFKS1YMECvweo4BwFKA0YMCBgWT7NpTe206ZNyzxY/x5JwYIF7bLLLrMaNWr4PDZZKsBKlsFauXLlbPv27VG5wBVsLV/ff/311935pCGAAAIIIIAAAghkTQG9dp0xY4Z7zJkzJyoI3bt3d4FXF110UVTmy0qT6BzoBg+dj0iaboh57LHH/JbRiWRuxiKAAAIIIIAAAokqoNehijFJ3R566CF7/PHHE3XbmW5fBFslyClVtisFXH322WfuzZ7Kd0Sr1ahVx+rUrWd1651rDRqdZ+UrVo7W1MyDgF+BbT9stY3r19jG9Wtt47p/vm5Yv8ZUIjAaTem7L774YmvevLk1atTI6tatG41pmQMBBBBAAAEEsqCALrwo45OyXynISgFWengtvScy3UShMZFk0Mps9Llz57Y///wz3Q+LQKt0PwVsAAEEEEAAAQQQSCgBZXhVkM/7779vixYtinhvFSpUcEFXPXr0CHijRsQLZcIJfvjhB5s5c2byw8shKluuLjBec801dt55ymRFQwABBBBAAAEEMp6AbgQeMWKEixEpX7686cbXoUOHWvXq1YMeTIMGDWzJkiVp+r355pvWpUuXoOPpEB0Bgq2i4xj1WX788UebO3euLVy40D799FPbuHFj1NYoe1o5q3vOuVa/URNr0PA8q1azVtTmZqKsJxDroKok0QIFClj9+vVdgJXKA+qXCA0BBBBAAAEEEIiWQFIJQgVdhRJklXJ9ZblS9qSVK1dGa1vME6EAgVYRAjIcAQQQQAABBBDI5AIqMZiU8WrNmjURH23Lli1d4FXnzp0jnisrTrBu3TrTQzej6+uOHTvc+7OkR5UqVVxpyBw5cmRFHo4ZAQQQQAABBDKBgCo+9e3b115++eU0R1OoUCEXRFW1atWAR6qkJAcOHEjTR59L165dOxMoZYxDINgqY5wn27lzpwu6Sgq+0t030WoFChayWnXqWqnSZazUKWXc11P+/Zr091y5ckVrOebJgAK/7t1rW77baFs2p30c+f33mByRAquSHgqs8le+JiaLMykCCCCAAAIIIBCmgErqNW3alICrMP2iOYxAq2hqMhcCCCCAAAIIIJD5BT788MPkwCvdDB1JU2YCBV0p+9I555wTyVSMRQABBBBAAAEEEMhEAv/973/thhtu8HtElSpVctmuTj75ZJ99lBlUmbB8tUOHDpmygNLiI0CwVXyco76KflB0p8233357wlfdkR+LVrxEyeRALAVgnaKArDJlrXSZU6102VOtdJmyVrBQ4VgszZxxElDQVJpgqn8DrBRsFctWs2bN5MCqpACrWK7H3AgggAACCCCAQCwFCLiKpa63uevUqWPKNEZDAAEEEEAAAQQQQCBUgSNHjtj06dNdmUFlvdLr+0iagq0UeHXVVVdZ8eLFI5mKsQgggAACCCCAAAIZXKBFixY2Z86cgEeh6+Xz58/3GTj12muv2Y033phmvIKzdu3alcF1Mtb2CbbKWOcr6G5TBmEp1e6mTZvcQ2UIf49RBqKkTSnY6p/gq3+DsMqcSkBW0DMWvw579+y27dt+sB3bfkz+umPbD7Z924+mr7t/+Tnmm1FQXrVq1a1mzepWo3p1V3NWvyxUIpCGAAIIIIAAAghkJgFdkFFJwq1bt2amw8owx7J8+XLnT0MAAQQQQAABBBBAIBKBn3/+OTnblQKvjh8/Hsl01q1bN+vZs6fpIhsNAQQQQAABBBBAIOsJqETghg0bgh5427Zt7e2337Z8+fKd0LdNmzY2c+bMNOObNGlin332WdB56RA9AYKtomeZ8DNt377dBV0p+EoZsRQNGe+7vfPlz2/Fi5e0YsVLWLESJa34v1/d34uXMGXQSvk9smV5e1odO3bMBUz9E0j1T/BUUmDVju3/BFfFqtyfrx2Wr1jZTj+jmlWrXt1q1qhhZ55Z3WrXrGGqH0tDAAEEEEAAAQSyioBea6uk4L59+7LKIaf7cSqF9tSpUwm0SvczwQYQQAABBBBAAIHMJ6DP1RVwpYxXc+fOjegA9bpV2a66dOliZ5xxRkRzMRgBBBBAAAEEEEAg4whUrlzZvvvuO08bbtiwofuss1SpUq7/yJEjrU+fPj7H9ujRw8aNG+dpXjpFR4Bgq+g4ZthZdMf9559/bqtWrXKP1atXu0CsRGm58+T5JwhLAVol/v1avISdVKyY5c9fwPLlL+C+qvZovgJJfy5wwp/1vew5ciTKIXnah4Kn9v32q+3f95v7uu+33/75875/vu7Z/bPt/GmH/bR9mwus2rXzJ0/zRrNTjhw5rcoZ1U541KhRw2qdWd0K589jeXJmi+ZyzIUAAggggAACCGRIAQKu4nfa+vfvb8OGDYvfgqyEAAIIIIAAAgggkGUFlElVgVd6LF26NCIHZbnq1auXXXnllZYnT56I5mIwAggggAACCCCAQGIL3HffffbUU0953mShQoWsd+/eVrRoUXvkkUf8jhs4cKANGjTI87x0jFyAYKvIDTPdDH/99Vdy8FVSAJa+ZuQan3ny5v03KOvfAK0C+d3f8+TJa/qe+5onz//+/O+/Kdjrf99X3zwnjPnr2DFTYJQefx07asf+Svpzyn//989/qc///v3ggf0pgql+TQ6k2v/bb3bgwP6EeF7lzJnTSpUuY6VOKWMVK1exKqdXs8ouwKq6Va5SxfLkym55c2azvLmyE1yVEGeMTSCAAAIIIIBAIgoQcBXbs1KkSBEbM2aMtWvXLrYLMTsCCCCAAAIIIIAAAj4EFixY4LJdKfBq/fr1YRsVKFDAZbvq2rWrNWrUKOx5GIgAAggggAACCCCQuAIHDx606tWr27Zt26K6yXfffdcF79PiJ0CwVfysM/xKCrZKGXyVlA1LwVm0jCdQvMTJVqp0aRdIdcq/AVWlTimdHFylICuVdcyZPZvlzJHNcmY3y+W+ZnNfc5O5KuOddHaMAAIIIIAAAukm8P3337tgoJUrV6bbHjLjwnXq1HGptCtUqJAZD49jQgABBBBAAAEEEMhgAklBV/q6Y8eOsHd/9tln27XXXusumJUpUybseRiIAAIIIIAAAgggkHgCH330kbVs2TKqG9u7d6/LfkWLnwDBVvGzzrQrrVmz5oRMWLqQtH37dlOJQlr8BQoWLPRvwNQ/gVRJman++fq/f1PWKrXs2RQ8Zf8LqkoKrPo3yCr+R8CKCCCAAAIIIIBA5hTQ62OVB5k2bVrmPMA4HxVlA+MMznIIIIAAAggggAACngV+//13d1NAUqlBZTAItynTVbdu3axNmzbhTsE4BBBAAAEEEEAAgQQTUIyFPitesmRJxDtr1aqVzZo1K+J5mCA0AYKtQvOidwgChw4dcunvFHilh68///TTTyHMmDW7Fi1W3IoVL5HqUdKKFf/fvxctXsKKFy9hJUqUtAIF8lv2bP8EUWXPrq///jnVv+VQMFX2bO77NAQQQAABBBBAAIH4COiCS/v27eOzWCZdhbKBmfTEclgIIIAAAggggEAmFVDFCL0PULYrPcJt5cqVc2UGle2qVq1a4U7DOAQQQAABBBBAAIEEETh27JgNHz7cBg0aZAcOHAh7V/PmzbOmTZuGPZ6B4QkQbBWeG6OiJHD8+HG/AVkpA7T++OOPKK2YftPkypXLChcpYkWKnGS6QHRS0aL/BEiVLOnK9ZVwf/4nYKpEiX+/lizhgqaSWtIf9S8umEoBVNmzmf6dmKn0O7esjAACCCCAAAIIeBWYP3++NWvWzGt3+qUSoGwgTwkEEEAAAQQQQACBjCywadOm5IxXn376adiHcskll1j37t1d4FWhQoXCnoeBCCCAAAIIIIAAAukvoBKAvXv3tvfeey/kzSjISsFWtPgLEGwVf3NWDEPgzz//NKVe1uPIkSMnfI3k3xQtGm7LmzfvP0FTJ53kHin/nPLvSf9eoECBcJdiHAIIIIAAAggggEAmEtCdSmPGjLGtW7dmoqOK/aEMHDjQ3eVFQwABBBBAAAEEEEAgMwh8/fXXrsS4Sg0uX748rEPKnz+/y3bVoUMHshmEJcggBBBAAAEEEEAgMQT+/vtvGzlypN1yyy2eN6Sge5UjPPXUUz2PoWP0BAi2ip4lMyGAAAIIIIAAAggggAACngVWrFhhynQ1bNgwAq8CqJUvX94Fp5EK2/NTi44IIIAAAggggAACGUxA7wsUeKUyg8p+FU6rW7euXX311S7bVYUKFcKZgjEIIIAAAggggAAC6SywatUq69Spk23YsCHoTmbNmmWtWrUK2o8OsREg2Co2rsyKAAIIIIAAAggggAACCHgW0MUVBRSNHTvW85is0PGKK65wLsocS0MAAQQQQAABBBBAICsITJ8+3fRQxquff/45rEPu0qWLdezY0QVeZcuWLaw5GIQAAggggAACCCCQPgKHDx+24cOH2xNPPGEHDhzwuQmqAKTPuUm5KsFW6X8O2AECCCCAAAIIIIAAAggg4AS+//57Vypv6tSptm/fviyrolLcchgwYECWNeDAEUAAAQQQQAABBLK2wO+//27vvvuuC7rSQ38PtamkzDXXXOOCrs4555xQh9MfAQQQQAABBBBAIB0F9u7da08//bQ99dRTJ+xi3Lhx1qNHj3TcGUtLgGArngcIIIAAAggggAACCCCAQIIJ/Pbbb668oB5ZLeiqTp06LpvVWWedlWBnhe0ggAACCCCAAAIIIJA+Art27UoOvPrwww/D2kTz5s2tc+fOLvCqRIkSYc3BIAQQQAABBBBAAIH4C2zfvt3Gjx9vNWvWNL2my5cvX/w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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "![openai-whisper-2.png](attachment:97aa66a7-9479-4415-bc72-d4a981bf1193.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "block:"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: tqdm in ./.local/lib/python3.8/site-packages (4.64.1)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "!pip install tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: datasets in ./.local/lib/python3.8/site-packages (2.7.1)\n",
      "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from datasets) (1.19.5)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (5.4.1)\n",
      "Requirement already satisfied: pyarrow>=6.0.0 in ./.local/lib/python3.8/site-packages (from datasets) (10.0.1)\n",
      "Requirement already satisfied: huggingface-hub<1.0.0,>=0.2.0 in ./.local/lib/python3.8/site-packages (from datasets) (0.11.0)\n",
      "Requirement already satisfied: dill<0.3.7 in ./.local/lib/python3.8/site-packages (from datasets) (0.3.6)\n",
      "Requirement already satisfied: tqdm>=4.62.1 in ./.local/lib/python3.8/site-packages (from datasets) (4.64.1)\n",
      "Requirement already satisfied: responses<0.19 in ./.local/lib/python3.8/site-packages (from datasets) (0.18.0)\n",
      "Requirement already satisfied: xxhash in ./.local/lib/python3.8/site-packages (from datasets) (3.1.0)\n",
      "Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (from datasets) (1.4.4)\n",
      "Requirement already satisfied: aiohttp in ./.local/lib/python3.8/site-packages (from datasets) (3.8.3)\n",
      "Requirement already satisfied: multiprocess in ./.local/lib/python3.8/site-packages (from datasets) (0.70.14)\n",
      "Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from datasets) (21.3)\n",
      "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (2.28.1)\n",
      "Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (2022.8.2)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in ./.local/lib/python3.8/site-packages (from aiohttp->datasets) (6.0.2)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in ./.local/lib/python3.8/site-packages (from aiohttp->datasets) (1.8.1)\n",
      "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (20.3.0)\n",
      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (2.1.1)\n",
      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (4.0.2)\n",
      "Requirement already satisfied: frozenlist>=1.1.1 in ./.local/lib/python3.8/site-packages (from aiohttp->datasets) (1.3.3)\n",
      "Requirement already satisfied: aiosignal>=1.1.2 in ./.local/lib/python3.8/site-packages (from aiohttp->datasets) (1.3.1)\n",
      "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (3.8.0)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (4.3.0)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->datasets) (3.0.9)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (1.26.12)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (3.4)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->datasets) (2022.9.24)\n",
      "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2022.2.1)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "!pip install datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: pytube in ./.local/lib/python3.8/site-packages (12.1.0)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "!pip install pytube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: pinecone-client in ./.local/lib/python3.8/site-packages (2.0.13)\n",
      "Requirement already satisfied: pyyaml>=5.4 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (5.4.1)\n",
      "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (2.28.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (4.3.0)\n",
      "Requirement already satisfied: loguru>=0.5.0 in ./.local/lib/python3.8/site-packages (from pinecone-client) (0.6.0)\n",
      "Requirement already satisfied: python-dateutil>=2.5.3 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (2.8.2)\n",
      "Requirement already satisfied: urllib3>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (1.26.12)\n",
      "Requirement already satisfied: dnspython>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from pinecone-client) (2.2.1)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.5.3->pinecone-client) (1.16.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->pinecone-client) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->pinecone-client) (2.1.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests>=2.19.0->pinecone-client) (2022.9.24)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "!pip install pinecone-client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting git+https://github.com/nficano/pytube.git\n",
      "  Cloning https://github.com/nficano/pytube.git to /tmp/pip-req-build-6fq4ez1x\n",
      "  Running command git clone --filter=blob:none --quiet https://github.com/nficano/pytube.git /tmp/pip-req-build-6fq4ez1x\n",
      "  Resolved https://github.com/nficano/pytube.git to commit 84faec34c8a66f502ac635a5610445dbff160654\n",
      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n",
      "\u001b[?25h"
     ]
    }
   ],
   "source": [
    "!pip install git+https://github.com/nficano/pytube.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading package lists... Done\n",
      "Building dependency tree       \n",
      "Reading state information... Done\n",
      "The following additional packages will be installed:\n",
      "  i965-va-driver libaacs0 libapparmor1 libass9 libasyncns0 libavc1394-0\n",
      "  libavcodec57 libavdevice57 libavfilter6 libavformat57 libavresample3\n",
      "  libavutil55 libbdplus0 libbluray2 libbs2b0 libcaca0 libcdio-cdda2\n",
      "  libcdio-paranoia2 libcdio17 libchromaprint1 libcrystalhd3 libdc1394-22\n",
      "  libdrm-amdgpu1 libdrm-common libdrm-intel1 libdrm-nouveau2 libdrm-radeon1\n",
      "  libdrm2 libelf1 libflac8 libflite1 libgl1 libgl1-mesa-dri libglapi-mesa\n",
      "  libglvnd0 libglx-mesa0 libglx0 libgme0 libgsm1 libiec61883-0\n",
      "  libjack-jackd2-0 libllvm10 libmp3lame0 libmpg123-0 libmysofa0 libnorm1\n",
      "  libnuma1 libogg0 libopenal-data libopenal1 libopenjp2-7 libopenmpt0 libopus0\n",
      "  libpciaccess0 libpgm-5.2-0 libpostproc54 libpulse0 libraw1394-11\n",
      "  librubberband2 libsamplerate0 libsdl2-2.0-0 libsensors4 libshine3 libslang2\n",
      "  libsnappy1v5 libsndfile1 libsndio6.1 libsodium23 libsoxr0 libspeex1\n",
      "  libssh-gcrypt-4 libswresample2 libswscale4 libtheora0 libtwolame0\n",
      "  libusb-1.0-0 libva-drm2 libva-x11-2 libva2 libvdpau1 libvorbis0a\n",
      "  libvorbisenc2 libvorbisfile3 libvpx5 libwavpack1 libwebpmux3 libwrap0\n",
      "  libx264-152 libx265-146 libxcb-dri2-0 libxcb-dri3-0 libxcb-glx0\n",
      "  libxcb-present0 libxcb-shape0 libxcb-sync1 libxcb-xfixes0 libxshmfence1\n",
      "  libxss1 libxv1 libxvidcore4 libxxf86vm1 libzmq5 libzvbi-common libzvbi0\n",
      "  mesa-va-drivers mesa-vdpau-drivers va-driver-all vdpau-driver-all\n",
      "Suggested packages:\n",
      "  ffmpeg-doc i965-va-driver-shaders libbluray-bdj firmware-crystalhd jackd2\n",
      "  libportaudio2 opus-tools pciutils pulseaudio libraw1394-doc lm-sensors\n",
      "  sndiod speex libvdpau-va-gl1 nvidia-vdpau-driver\n",
      "  nvidia-legacy-340xx-vdpau-driver\n",
      "The following NEW packages will be installed:\n",
      "  ffmpeg i965-va-driver libaacs0 libapparmor1 libass9 libasyncns0 libavc1394-0\n",
      "  libavcodec57 libavdevice57 libavfilter6 libavformat57 libavresample3\n",
      "  libavutil55 libbdplus0 libbluray2 libbs2b0 libcaca0 libcdio-cdda2\n",
      "  libcdio-paranoia2 libcdio17 libchromaprint1 libcrystalhd3 libdc1394-22\n",
      "  libdrm-amdgpu1 libdrm-common libdrm-intel1 libdrm-nouveau2 libdrm-radeon1\n",
      "  libdrm2 libelf1 libflac8 libflite1 libgl1 libgl1-mesa-dri libglapi-mesa\n",
      "  libglvnd0 libglx-mesa0 libglx0 libgme0 libgsm1 libiec61883-0\n",
      "  libjack-jackd2-0 libllvm10 libmp3lame0 libmpg123-0 libmysofa0 libnorm1\n",
      "  libnuma1 libogg0 libopenal-data libopenal1 libopenjp2-7 libopenmpt0 libopus0\n",
      "  libpciaccess0 libpgm-5.2-0 libpostproc54 libpulse0 libraw1394-11\n",
      "  librubberband2 libsamplerate0 libsdl2-2.0-0 libsensors4 libshine3 libslang2\n",
      "  libsnappy1v5 libsndfile1 libsndio6.1 libsodium23 libsoxr0 libspeex1\n",
      "  libssh-gcrypt-4 libswresample2 libswscale4 libtheora0 libtwolame0\n",
      "  libusb-1.0-0 libva-drm2 libva-x11-2 libva2 libvdpau1 libvorbis0a\n",
      "  libvorbisenc2 libvorbisfile3 libvpx5 libwavpack1 libwebpmux3 libwrap0\n",
      "  libx264-152 libx265-146 libxcb-dri2-0 libxcb-dri3-0 libxcb-glx0\n",
      "  libxcb-present0 libxcb-shape0 libxcb-sync1 libxcb-xfixes0 libxshmfence1\n",
      "  libxss1 libxv1 libxvidcore4 libxxf86vm1 libzmq5 libzvbi-common libzvbi0\n",
      "  mesa-va-drivers mesa-vdpau-drivers va-driver-all vdpau-driver-all\n",
      "0 upgraded, 109 newly installed, 0 to remove and 23 not upgraded.\n",
      "Need to get 62.6 MB of archives.\n",
      "After this operation, 490 MB of additional disk space will be used.\n",
      "Get:1 http://archive.ubuntu.com/ubuntu bionic/main amd64 libogg0 amd64 1.3.2-1 [17.2 kB]\n",
      "Get:2 http://archive.ubuntu.com/ubuntu bionic/main amd64 libxss1 amd64 1:1.2.2-1 [8,582 B]\n",
      "Get:3 http://archive.ubuntu.com/ubuntu bionic/main amd64 libxxf86vm1 amd64 1:1.1.4-1 [10.6 kB]\n",
      "Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libapparmor1 amd64 2.12-4ubuntu5.1 [31.3 kB]\n",
      "Get:5 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libelf1 amd64 0.170-0.4ubuntu0.1 [44.8 kB]\n",
      "Get:6 http://archive.ubuntu.com/ubuntu bionic/main amd64 libslang2 amd64 2.3.1a-3ubuntu1 [424 kB]\n",
      "Get:7 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-common all 2.4.101-2~18.04.1 [5,560 B]\n",
      "Get:8 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm2 amd64 2.4.101-2~18.04.1 [32.3 kB]\n",
      "Get:9 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libnuma1 amd64 2.0.11-2.1ubuntu0.1 [22.0 kB]\n",
      "Get:10 http://archive.ubuntu.com/ubuntu bionic/main amd64 libusb-1.0-0 amd64 2:1.0.21-2 [43.3 kB]\n",
      "Get:11 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libva2 amd64 2.1.0-3 [47.6 kB]\n",
      "Get:12 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libva-drm2 amd64 2.1.0-3 [6,880 B]\n",
      "Get:13 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libva-x11-2 amd64 2.1.0-3 [11.5 kB]\n",
      "Get:14 http://archive.ubuntu.com/ubuntu bionic/main amd64 libvdpau1 amd64 1.1.1-3ubuntu1 [25.5 kB]\n",
      "Get:15 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavutil55 amd64 7:3.4.11-0ubuntu0.1 [191 kB]\n",
      "Get:16 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libcrystalhd3 amd64 1:0.0~git20110715.fdd2f19-12 [45.8 kB]\n",
      "Get:17 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgsm1 amd64 1.0.13-4build1 [22.4 kB]\n",
      "Get:18 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmp3lame0 amd64 3.100-2 [136 kB]\n",
      "Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libopenjp2-7 amd64 2.3.0-2build0.18.04.1 [145 kB]\n",
      "Get:20 http://archive.ubuntu.com/ubuntu bionic/main amd64 libopus0 amd64 1.1.2-1ubuntu1 [159 kB]\n",
      "Get:21 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libshine3 amd64 3.1.1-1 [22.9 kB]\n",
      "Get:22 http://archive.ubuntu.com/ubuntu bionic/main amd64 libsnappy1v5 amd64 1.1.7-1 [16.0 kB]\n",
      "Get:23 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libspeex1 amd64 1.2~rc1.2-1ubuntu2.1 [52.1 kB]\n",
      "Get:24 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libsoxr0 amd64 0.1.2-3 [65.9 kB]\n",
      "Get:25 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libswresample2 amd64 7:3.4.11-0ubuntu0.1 [55.2 kB]\n",
      "Get:26 http://archive.ubuntu.com/ubuntu bionic/main amd64 libtheora0 amd64 1.1.1+dfsg.1-14 [170 kB]\n",
      "Get:27 http://archive.ubuntu.com/ubuntu bionic/main amd64 libtwolame0 amd64 0.3.13-3 [46.7 kB]\n",
      "Get:28 http://archive.ubuntu.com/ubuntu bionic/main amd64 libvorbis0a amd64 1.3.5-4.2 [86.4 kB]\n",
      "Get:29 http://archive.ubuntu.com/ubuntu bionic/main amd64 libvorbisenc2 amd64 1.3.5-4.2 [70.7 kB]\n",
      "Get:30 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libvpx5 amd64 1.7.0-3ubuntu0.18.04.1 [796 kB]\n",
      "Get:31 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libwavpack1 amd64 5.1.0-2ubuntu1.5 [76.8 kB]\n",
      "Get:32 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libwebpmux3 amd64 0.6.1-2ubuntu0.18.04.1 [19.6 kB]\n",
      "Get:33 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libx264-152 amd64 2:0.152.2854+gite9a5903-2 [609 kB]\n",
      "Get:34 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libx265-146 amd64 2.6-3 [1,026 kB]\n",
      "Get:35 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libxvidcore4 amd64 2:1.3.5-1 [200 kB]\n",
      "Get:36 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libzvbi-common all 0.2.35-13 [32.1 kB]\n",
      "Get:37 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libzvbi0 amd64 0.2.35-13 [235 kB]\n",
      "Get:38 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavcodec57 amd64 7:3.4.11-0ubuntu0.1 [4,600 kB]\n",
      "Get:39 http://archive.ubuntu.com/ubuntu bionic/main amd64 libraw1394-11 amd64 2.1.2-1 [30.7 kB]\n",
      "Get:40 http://archive.ubuntu.com/ubuntu bionic/main amd64 libavc1394-0 amd64 0.5.4-4build1 [16.1 kB]\n",
      "Get:41 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libass9 amd64 1:0.14.0-1 [88.2 kB]\n",
      "Get:42 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libbluray2 amd64 1:1.0.2-3 [141 kB]\n",
      "Get:43 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libchromaprint1 amd64 1.4.3-1 [36.8 kB]\n",
      "Get:44 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libgme0 amd64 0.6.2-1 [121 kB]\n",
      "Get:45 http://archive.ubuntu.com/ubuntu bionic/main amd64 libmpg123-0 amd64 1.25.10-1 [125 kB]\n",
      "Get:46 http://archive.ubuntu.com/ubuntu bionic/main amd64 libvorbisfile3 amd64 1.3.5-4.2 [16.0 kB]\n",
      "Get:47 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libopenmpt0 amd64 0.3.6-1 [561 kB]\n",
      "Get:48 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libssh-gcrypt-4 amd64 0.8.0~20170825.94fa1e38-1ubuntu0.7 [172 kB]\n",
      "Get:49 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavformat57 amd64 7:3.4.11-0ubuntu0.1 [953 kB]\n",
      "Get:50 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavresample3 amd64 7:3.4.11-0ubuntu0.1 [52.6 kB]\n",
      "Get:51 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libbs2b0 amd64 3.1.0+dfsg-2.2 [10.5 kB]\n",
      "Get:52 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libflite1 amd64 2.1-release-1 [12.8 MB]\n",
      "Get:53 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libmysofa0 amd64 0.6~dfsg0-3+deb10u1build1 [38.5 kB]\n",
      "Get:54 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpostproc54 amd64 7:3.4.11-0ubuntu0.1 [50.3 kB]\n",
      "Get:55 http://archive.ubuntu.com/ubuntu bionic/main amd64 libsamplerate0 amd64 0.1.9-1 [938 kB]\n",
      "Get:56 http://archive.ubuntu.com/ubuntu bionic/universe amd64 librubberband2 amd64 1.8.1-7ubuntu2 [86.7 kB]\n",
      "Get:57 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libswscale4 amd64 7:3.4.11-0ubuntu0.1 [150 kB]\n",
      "Get:58 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libnorm1 amd64 1.5r6+dfsg1-6 [224 kB]\n",
      "Get:59 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libpgm-5.2-0 amd64 5.2.122~dfsg-2 [157 kB]\n",
      "Get:60 http://archive.ubuntu.com/ubuntu bionic/main amd64 libsodium23 amd64 1.0.16-2 [143 kB]\n",
      "Get:61 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libzmq5 amd64 4.2.5-1ubuntu0.2 [221 kB]\n",
      "Get:62 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavfilter6 amd64 7:3.4.11-0ubuntu0.1 [875 kB]\n",
      "Get:63 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcaca0 amd64 0.99.beta19-2ubuntu0.18.04.3 [203 kB]\n",
      "Get:64 http://archive.ubuntu.com/ubuntu bionic/main amd64 libcdio17 amd64 1.0.0-2ubuntu2 [58.8 kB]\n",
      "Get:65 http://archive.ubuntu.com/ubuntu bionic/main amd64 libcdio-cdda2 amd64 10.2+0.94+2-2build1 [17.7 kB]\n",
      "Get:66 http://archive.ubuntu.com/ubuntu bionic/main amd64 libcdio-paranoia2 amd64 10.2+0.94+2-2build1 [17.2 kB]\n",
      "Get:67 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libdc1394-22 amd64 2.2.5-1 [77.5 kB]\n",
      "Get:68 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglvnd0 amd64 1.0.0-2ubuntu2.3 [47.0 kB]\n",
      "Get:69 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglapi-mesa amd64 20.0.8-0ubuntu1~18.04.1 [26.6 kB]\n",
      "Get:70 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-dri2-0 amd64 1.13-2~ubuntu18.04 [6,920 B]\n",
      "Get:71 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-dri3-0 amd64 1.13-2~ubuntu18.04 [6,568 B]\n",
      "Get:72 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-glx0 amd64 1.13-2~ubuntu18.04 [22.1 kB]\n",
      "Get:73 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-present0 amd64 1.13-2~ubuntu18.04 [5,552 B]\n",
      "Get:74 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-sync1 amd64 1.13-2~ubuntu18.04 [8,808 B]\n",
      "Get:75 http://archive.ubuntu.com/ubuntu bionic/main amd64 libxshmfence1 amd64 1.3-1 [5,028 B]\n",
      "Get:76 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-amdgpu1 amd64 2.4.101-2~18.04.1 [18.2 kB]\n",
      "Get:77 http://archive.ubuntu.com/ubuntu bionic/main amd64 libpciaccess0 amd64 0.14-1 [17.9 kB]\n",
      "Get:78 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-intel1 amd64 2.4.101-2~18.04.1 [60.0 kB]\n",
      "Get:79 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-nouveau2 amd64 2.4.101-2~18.04.1 [16.5 kB]\n",
      "Get:80 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libdrm-radeon1 amd64 2.4.101-2~18.04.1 [21.7 kB]\n",
      "Get:81 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libllvm10 amd64 1:10.0.0-4ubuntu1~18.04.2 [15.4 MB]\n",
      "Get:82 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libsensors4 amd64 1:3.4.0-4ubuntu0.1 [28.3 kB]\n",
      "Get:83 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1-mesa-dri amd64 20.0.8-0ubuntu1~18.04.1 [9,333 kB]\n",
      "Get:84 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglx-mesa0 amd64 20.0.8-0ubuntu1~18.04.1 [139 kB]\n",
      "Get:85 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libglx0 amd64 1.0.0-2ubuntu2.3 [28.1 kB]\n",
      "Get:86 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgl1 amd64 1.0.0-2ubuntu2.3 [86.2 kB]\n",
      "Get:87 http://archive.ubuntu.com/ubuntu bionic/main amd64 libiec61883-0 amd64 1.2.0-2 [23.5 kB]\n",
      "Get:88 http://archive.ubuntu.com/ubuntu bionic/main amd64 libjack-jackd2-0 amd64 1.9.12~dfsg-2 [263 kB]\n",
      "Get:89 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libopenal-data all 1:1.18.2-2 [102 kB]\n",
      "Get:90 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libsndio6.1 amd64 1.1.0-3 [23.4 kB]\n",
      "Get:91 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libopenal1 amd64 1:1.18.2-2 [266 kB]\n",
      "Get:92 http://archive.ubuntu.com/ubuntu bionic/main amd64 libasyncns0 amd64 0.8-6 [12.1 kB]\n",
      "Get:93 http://archive.ubuntu.com/ubuntu bionic/main amd64 libflac8 amd64 1.3.2-1 [213 kB]\n",
      "Get:94 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libsndfile1 amd64 1.0.28-4ubuntu0.18.04.2 [170 kB]\n",
      "Get:95 http://archive.ubuntu.com/ubuntu bionic/main amd64 libwrap0 amd64 7.6.q-27 [46.3 kB]\n",
      "Get:96 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libpulse0 amd64 1:11.1-1ubuntu7.11 [266 kB]\n",
      "Get:97 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libsdl2-2.0-0 amd64 2.0.8+dfsg1-1ubuntu1.18.04.4 [382 kB]\n",
      "Get:98 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-shape0 amd64 1.13-2~ubuntu18.04 [5,972 B]\n",
      "Get:99 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libxcb-xfixes0 amd64 1.13-2~ubuntu18.04 [9,352 B]\n",
      "Get:100 http://archive.ubuntu.com/ubuntu bionic/main amd64 libxv1 amd64 2:1.0.11-1 [10.7 kB]\n",
      "Get:101 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libavdevice57 amd64 7:3.4.11-0ubuntu0.1 [75.1 kB]\n",
      "Get:102 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 ffmpeg amd64 7:3.4.11-0ubuntu0.1 [1,587 kB]\n",
      "Get:103 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libaacs0 amd64 0.9.0-1 [51.4 kB]\n",
      "Get:104 http://archive.ubuntu.com/ubuntu bionic/universe amd64 libbdplus0 amd64 0.1.2-2 [46.6 kB]\n",
      "Get:105 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 mesa-va-drivers amd64 20.0.8-0ubuntu1~18.04.1 [2,376 kB]\n",
      "Get:106 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 mesa-vdpau-drivers amd64 20.0.8-0ubuntu1~18.04.1 [2,496 kB]\n",
      "Get:107 http://archive.ubuntu.com/ubuntu bionic/universe amd64 i965-va-driver amd64 2.1.0-0ubuntu1 [925 kB]\n",
      "Get:108 http://archive.ubuntu.com/ubuntu bionic/universe amd64 va-driver-all amd64 2.1.0-3 [4,376 B]\n",
      "Get:109 http://archive.ubuntu.com/ubuntu bionic/main amd64 vdpau-driver-all amd64 1.1.1-3ubuntu1 [4,674 B]\n",
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      "Preparing to unpack .../075-libdrm-amdgpu1_2.4.101-2~18.04.1_amd64.deb ...\n",
      "Unpacking libdrm-amdgpu1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Selecting previously unselected package libpciaccess0:amd64.\n",
      "Preparing to unpack .../076-libpciaccess0_0.14-1_amd64.deb ...\n",
      "Unpacking libpciaccess0:amd64 (0.14-1) ...\n",
      "Selecting previously unselected package libdrm-intel1:amd64.\n",
      "Preparing to unpack .../077-libdrm-intel1_2.4.101-2~18.04.1_amd64.deb ...\n",
      "Unpacking libdrm-intel1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Selecting previously unselected package libdrm-nouveau2:amd64.\n",
      "Preparing to unpack .../078-libdrm-nouveau2_2.4.101-2~18.04.1_amd64.deb ...\n",
      "Unpacking libdrm-nouveau2:amd64 (2.4.101-2~18.04.1) ...\n",
      "Selecting previously unselected package libdrm-radeon1:amd64.\n",
      "Preparing to unpack .../079-libdrm-radeon1_2.4.101-2~18.04.1_amd64.deb ...\n",
      "Unpacking libdrm-radeon1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Selecting previously unselected package libllvm10:amd64.\n",
      "Preparing to unpack .../080-libllvm10_1%3a10.0.0-4ubuntu1~18.04.2_amd64.deb ...\n",
      "Unpacking libllvm10:amd64 (1:10.0.0-4ubuntu1~18.04.2) ...\n",
      "Selecting previously unselected package libsensors4:amd64.\n",
      "Preparing to unpack .../081-libsensors4_1%3a3.4.0-4ubuntu0.1_amd64.deb ...\n",
      "Unpacking libsensors4:amd64 (1:3.4.0-4ubuntu0.1) ...\n",
      "Selecting previously unselected package libgl1-mesa-dri:amd64.\n",
      "Preparing to unpack .../082-libgl1-mesa-dri_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
      "Unpacking libgl1-mesa-dri:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Selecting previously unselected package libglx-mesa0:amd64.\n",
      "Preparing to unpack .../083-libglx-mesa0_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
      "Unpacking libglx-mesa0:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Selecting previously unselected package libglx0:amd64.\n",
      "Preparing to unpack .../084-libglx0_1.0.0-2ubuntu2.3_amd64.deb ...\n",
      "Unpacking libglx0:amd64 (1.0.0-2ubuntu2.3) ...\n",
      "Selecting previously unselected package libgl1:amd64.\n",
      "Preparing to unpack .../085-libgl1_1.0.0-2ubuntu2.3_amd64.deb ...\n",
      "Unpacking libgl1:amd64 (1.0.0-2ubuntu2.3) ...\n",
      "Selecting previously unselected package libiec61883-0:amd64.\n",
      "Preparing to unpack .../086-libiec61883-0_1.2.0-2_amd64.deb ...\n",
      "Unpacking libiec61883-0:amd64 (1.2.0-2) ...\n",
      "Selecting previously unselected package libjack-jackd2-0:amd64.\n",
      "Preparing to unpack .../087-libjack-jackd2-0_1.9.12~dfsg-2_amd64.deb ...\n",
      "Unpacking libjack-jackd2-0:amd64 (1.9.12~dfsg-2) ...\n",
      "Selecting previously unselected package libopenal-data.\n",
      "Preparing to unpack .../088-libopenal-data_1%3a1.18.2-2_all.deb ...\n",
      "Unpacking libopenal-data (1:1.18.2-2) ...\n",
      "Selecting previously unselected package libsndio6.1:amd64.\n",
      "Preparing to unpack .../089-libsndio6.1_1.1.0-3_amd64.deb ...\n",
      "Unpacking libsndio6.1:amd64 (1.1.0-3) ...\n",
      "Selecting previously unselected package libopenal1:amd64.\n",
      "Preparing to unpack .../090-libopenal1_1%3a1.18.2-2_amd64.deb ...\n",
      "Unpacking libopenal1:amd64 (1:1.18.2-2) ...\n",
      "Selecting previously unselected package libasyncns0:amd64.\n",
      "Preparing to unpack .../091-libasyncns0_0.8-6_amd64.deb ...\n",
      "Unpacking libasyncns0:amd64 (0.8-6) ...\n",
      "Selecting previously unselected package libflac8:amd64.\n",
      "Preparing to unpack .../092-libflac8_1.3.2-1_amd64.deb ...\n",
      "Unpacking libflac8:amd64 (1.3.2-1) ...\n",
      "Selecting previously unselected package libsndfile1:amd64.\n",
      "Preparing to unpack .../093-libsndfile1_1.0.28-4ubuntu0.18.04.2_amd64.deb ...\n",
      "Unpacking libsndfile1:amd64 (1.0.28-4ubuntu0.18.04.2) ...\n",
      "Selecting previously unselected package libwrap0:amd64.\n",
      "Preparing to unpack .../094-libwrap0_7.6.q-27_amd64.deb ...\n",
      "Unpacking libwrap0:amd64 (7.6.q-27) ...\n",
      "Selecting previously unselected package libpulse0:amd64.\n",
      "Preparing to unpack .../095-libpulse0_1%3a11.1-1ubuntu7.11_amd64.deb ...\n",
      "Unpacking libpulse0:amd64 (1:11.1-1ubuntu7.11) ...\n",
      "Selecting previously unselected package libsdl2-2.0-0:amd64.\n",
      "Preparing to unpack .../096-libsdl2-2.0-0_2.0.8+dfsg1-1ubuntu1.18.04.4_amd64.deb ...\n",
      "Unpacking libsdl2-2.0-0:amd64 (2.0.8+dfsg1-1ubuntu1.18.04.4) ...\n",
      "Selecting previously unselected package libxcb-shape0:amd64.\n",
      "Preparing to unpack .../097-libxcb-shape0_1.13-2~ubuntu18.04_amd64.deb ...\n",
      "Unpacking libxcb-shape0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Selecting previously unselected package libxcb-xfixes0:amd64.\n",
      "Preparing to unpack .../098-libxcb-xfixes0_1.13-2~ubuntu18.04_amd64.deb ...\n",
      "Unpacking libxcb-xfixes0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Selecting previously unselected package libxv1:amd64.\n",
      "Preparing to unpack .../099-libxv1_2%3a1.0.11-1_amd64.deb ...\n",
      "Unpacking libxv1:amd64 (2:1.0.11-1) ...\n",
      "Selecting previously unselected package libavdevice57:amd64.\n",
      "Preparing to unpack .../100-libavdevice57_7%3a3.4.11-0ubuntu0.1_amd64.deb ...\n",
      "Unpacking libavdevice57:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Selecting previously unselected package ffmpeg.\n",
      "Preparing to unpack .../101-ffmpeg_7%3a3.4.11-0ubuntu0.1_amd64.deb ...\n",
      "Unpacking ffmpeg (7:3.4.11-0ubuntu0.1) ...\n",
      "Selecting previously unselected package libaacs0:amd64.\n",
      "Preparing to unpack .../102-libaacs0_0.9.0-1_amd64.deb ...\n",
      "Unpacking libaacs0:amd64 (0.9.0-1) ...\n",
      "Selecting previously unselected package libbdplus0:amd64.\n",
      "Preparing to unpack .../103-libbdplus0_0.1.2-2_amd64.deb ...\n",
      "Unpacking libbdplus0:amd64 (0.1.2-2) ...\n",
      "Selecting previously unselected package mesa-va-drivers:amd64.\n",
      "Preparing to unpack .../104-mesa-va-drivers_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
      "Unpacking mesa-va-drivers:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Selecting previously unselected package mesa-vdpau-drivers:amd64.\n",
      "Preparing to unpack .../105-mesa-vdpau-drivers_20.0.8-0ubuntu1~18.04.1_amd64.deb ...\n",
      "Unpacking mesa-vdpau-drivers:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Selecting previously unselected package i965-va-driver:amd64.\n",
      "Preparing to unpack .../106-i965-va-driver_2.1.0-0ubuntu1_amd64.deb ...\n",
      "Unpacking i965-va-driver:amd64 (2.1.0-0ubuntu1) ...\n",
      "Selecting previously unselected package va-driver-all:amd64.\n",
      "Preparing to unpack .../107-va-driver-all_2.1.0-3_amd64.deb ...\n",
      "Unpacking va-driver-all:amd64 (2.1.0-3) ...\n",
      "Selecting previously unselected package vdpau-driver-all:amd64.\n",
      "Preparing to unpack .../108-vdpau-driver-all_1.1.1-3ubuntu1_amd64.deb ...\n",
      "Unpacking vdpau-driver-all:amd64 (1.1.1-3ubuntu1) ...\n",
      "Setting up libpgm-5.2-0:amd64 (5.2.122~dfsg-2) ...\n",
      "Setting up libxcb-present0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libglvnd0:amd64 (1.0.0-2ubuntu2.3) ...\n",
      "Setting up libxcb-dri2-0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libxcb-dri3-0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libxcb-glx0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libtwolame0:amd64 (0.3.13-3) ...\n",
      "Setting up libraw1394-11:amd64 (2.1.2-1) ...\n",
      "Setting up libx264-152:amd64 (2:0.152.2854+gite9a5903-2) ...\n",
      "Setting up libxcb-xfixes0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libopenjp2-7:amd64 (2.3.0-2build0.18.04.1) ...\n",
      "Setting up libllvm10:amd64 (1:10.0.0-4ubuntu1~18.04.2) ...\n",
      "Setting up libasyncns0:amd64 (0.8-6) ...\n",
      "Setting up libwavpack1:amd64 (5.1.0-2ubuntu1.5) ...\n",
      "Setting up libaacs0:amd64 (0.9.0-1) ...\n",
      "Setting up libnuma1:amd64 (2.0.11-2.1ubuntu0.1) ...\n",
      "Setting up libelf1:amd64 (0.170-0.4ubuntu0.1) ...\n",
      "Setting up libflite1:amd64 (2.1-release-1) ...\n",
      "Setting up libsoxr0:amd64 (0.1.2-3) ...\n",
      "Setting up libssh-gcrypt-4:amd64 (0.8.0~20170825.94fa1e38-1ubuntu0.7) ...\n",
      "Setting up libxss1:amd64 (1:1.2.2-1) ...\n",
      "Setting up libxshmfence1:amd64 (1.3-1) ...\n",
      "Setting up libass9:amd64 (1:0.14.0-1) ...\n",
      "Setting up libbluray2:amd64 (1:1.0.2-3) ...\n",
      "Setting up libvdpau1:amd64 (1.1.1-3ubuntu1) ...\n",
      "Setting up libshine3:amd64 (3.1.1-1) ...\n",
      "Setting up libva2:amd64 (2.1.0-3) ...\n",
      "Setting up libiec61883-0:amd64 (1.2.0-2) ...\n",
      "Setting up libglapi-mesa:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Setting up libspeex1:amd64 (1.2~rc1.2-1ubuntu2.1) ...\n",
      "Setting up libxvidcore4:amd64 (2:1.3.5-1) ...\n",
      "Setting up libopus0:amd64 (1.1.2-1ubuntu1) ...\n",
      "Setting up libx265-146:amd64 (2.6-3) ...\n",
      "Setting up libopenal-data (1:1.18.2-2) ...\n",
      "Setting up libdrm-common (2.4.101-2~18.04.1) ...\n",
      "Setting up libbs2b0:amd64 (3.1.0+dfsg-2.2) ...\n",
      "Setting up libxcb-sync1:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libnorm1:amd64 (1.5r6+dfsg1-6) ...\n",
      "Setting up libogg0:amd64 (1.3.2-1) ...\n",
      "Setting up libsodium23:amd64 (1.0.16-2) ...\n",
      "Setting up libmp3lame0:amd64 (3.100-2) ...\n",
      "Setting up libusb-1.0-0:amd64 (2:1.0.21-2) ...\n",
      "Setting up libcrystalhd3:amd64 (1:0.0~git20110715.fdd2f19-12) ...\n",
      "Setting up libapparmor1:amd64 (2.12-4ubuntu5.1) ...\n",
      "Setting up libwebpmux3:amd64 (0.6.1-2ubuntu0.18.04.1) ...\n",
      "Setting up libsnappy1v5:amd64 (1.1.7-1) ...\n",
      "Setting up libavc1394-0:amd64 (0.5.4-4build1) ...\n",
      "Setting up libzvbi-common (0.2.35-13) ...\n",
      "Setting up libxcb-shape0:amd64 (1.13-2~ubuntu18.04) ...\n",
      "Setting up libpciaccess0:amd64 (0.14-1) ...\n",
      "Setting up libxv1:amd64 (2:1.0.11-1) ...\n",
      "Setting up libsensors4:amd64 (1:3.4.0-4ubuntu0.1) ...\n",
      "Setting up libvpx5:amd64 (1.7.0-3ubuntu0.18.04.1) ...\n",
      "Setting up libgme0:amd64 (0.6.2-1) ...\n",
      "Setting up libbdplus0:amd64 (0.1.2-2) ...\n",
      "Setting up libxxf86vm1:amd64 (1:1.1.4-1) ...\n",
      "Setting up libzvbi0:amd64 (0.2.35-13) ...\n",
      "Setting up libsamplerate0:amd64 (0.1.9-1) ...\n",
      "Setting up libsndio6.1:amd64 (1.1.0-3) ...\n",
      "Setting up libvorbis0a:amd64 (1.3.5-4.2) ...\n",
      "Setting up libtheora0:amd64 (1.1.1+dfsg.1-14) ...\n",
      "Setting up libmpg123-0:amd64 (1.25.10-1) ...\n",
      "Setting up libslang2:amd64 (2.3.1a-3ubuntu1) ...\n",
      "Setting up libgsm1:amd64 (1.0.13-4build1) ...\n",
      "Setting up libmysofa0:amd64 (0.6~dfsg0-3+deb10u1build1) ...\n",
      "Setting up libcdio17:amd64 (1.0.0-2ubuntu2) ...\n",
      "Setting up libwrap0:amd64 (7.6.q-27) ...\n",
      "Setting up libvorbisfile3:amd64 (1.3.5-4.2) ...\n",
      "Setting up libzmq5:amd64 (4.2.5-1ubuntu0.2) ...\n",
      "Setting up libopenmpt0:amd64 (0.3.6-1) ...\n",
      "Setting up libflac8:amd64 (1.3.2-1) ...\n",
      "Setting up libdc1394-22:amd64 (2.2.5-1) ...\n",
      "Setting up libcdio-cdda2:amd64 (10.2+0.94+2-2build1) ...\n",
      "Setting up libdrm2:amd64 (2.4.101-2~18.04.1) ...\n",
      "Setting up libdrm-intel1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Setting up librubberband2:amd64 (1.8.1-7ubuntu2) ...\n",
      "Setting up libcdio-paranoia2:amd64 (10.2+0.94+2-2build1) ...\n",
      "Setting up libva-drm2:amd64 (2.1.0-3) ...\n",
      "Setting up libjack-jackd2-0:amd64 (1.9.12~dfsg-2) ...\n",
      "Setting up libopenal1:amd64 (1:1.18.2-2) ...\n",
      "Setting up libdrm-radeon1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Setting up libvorbisenc2:amd64 (1.3.5-4.2) ...\n",
      "Setting up libva-x11-2:amd64 (2.1.0-3) ...\n",
      "Setting up libdrm-nouveau2:amd64 (2.4.101-2~18.04.1) ...\n",
      "Setting up libcaca0:amd64 (0.99.beta19-2ubuntu0.18.04.3) ...\n",
      "Setting up libavutil55:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libdrm-amdgpu1:amd64 (2.4.101-2~18.04.1) ...\n",
      "Setting up mesa-vdpau-drivers:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Setting up libgl1-mesa-dri:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Setting up libswresample2:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libsndfile1:amd64 (1.0.28-4ubuntu0.18.04.2) ...\n",
      "Setting up i965-va-driver:amd64 (2.1.0-0ubuntu1) ...\n",
      "Setting up libswscale4:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up mesa-va-drivers:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Setting up libpostproc54:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libglx-mesa0:amd64 (20.0.8-0ubuntu1~18.04.1) ...\n",
      "Setting up vdpau-driver-all:amd64 (1.1.1-3ubuntu1) ...\n",
      "Setting up libavresample3:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libavcodec57:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libpulse0:amd64 (1:11.1-1ubuntu7.11) ...\n",
      "Setting up libsdl2-2.0-0:amd64 (2.0.8+dfsg1-1ubuntu1.18.04.4) ...\n",
      "Setting up va-driver-all:amd64 (2.1.0-3) ...\n",
      "Setting up libglx0:amd64 (1.0.0-2ubuntu2.3) ...\n",
      "Setting up libchromaprint1:amd64 (1.4.3-1) ...\n",
      "Setting up libgl1:amd64 (1.0.0-2ubuntu2.3) ...\n",
      "Setting up libavformat57:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libavfilter6:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up libavdevice57:amd64 (7:3.4.11-0ubuntu0.1) ...\n",
      "Setting up ffmpeg (7:3.4.11-0ubuntu0.1) ...\n",
      "Processing triggers for libc-bin (2.27-3ubuntu1.4) ...\n"
     ]
    }
   ],
   "source": [
    "!sudo apt-get install ffmpeg -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading package lists... Done\n",
      "Building dependency tree       \n",
      "Reading state information... Done\n",
      "Calculating upgrade... Done\n",
      "The following packages will be upgraded:\n",
      "  apt base-files bash dpkg e2fsprogs gzip libapt-pkg5.0 libc-bin libcom-err2\n",
      "  libext2fs2 libgcrypt20 libgnutls30 libhogweed4 liblzma5 libnettle6 libpcre3\n",
      "  libseccomp2 libsepol1 libss2 libsystemd0 libudev1 login passwd\n",
      "23 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.\n",
      "Need to get 8,438 kB of archives.\n",
      "After this operation, 44.0 kB of additional disk space will be used.\n",
      "Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 base-files amd64 10.1ubuntu2.11 [60.4 kB]\n",
      "Get:2 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 bash amd64 4.4.18-2ubuntu1.3 [615 kB]\n",
      "Get:3 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 dpkg amd64 1.19.0.5ubuntu2.4 [1,137 kB]\n",
      "Get:4 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libext2fs2 amd64 1.44.1-1ubuntu1.4 [156 kB]\n",
      "Get:5 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 e2fsprogs amd64 1.44.1-1ubuntu1.4 [390 kB]\n",
      "Get:6 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 gzip amd64 1.6-5ubuntu1.2 [90.3 kB]\n",
      "Err:7 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 login amd64 1:4.5-1ubuntu2.3\n",
      "  404  Not Found [IP: 185.125.190.39 80]\n",
      "Get:8 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libc-bin amd64 2.27-3ubuntu1.6 [640 kB]\n",
      "Get:9 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 liblzma5 amd64 5.2.2-1.3ubuntu0.1 [91.1 kB]\n",
      "Get:10 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libsystemd0 amd64 237-3ubuntu10.56 [205 kB]\n",
      "Get:11 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libudev1 amd64 237-3ubuntu10.56 [54.0 kB]\n",
      "Get:12 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libapt-pkg5.0 amd64 1.6.14 [809 kB]\n",
      "Get:13 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libnettle6 amd64 3.4.1-0ubuntu0.18.04.1 [111 kB]\n",
      "Get:14 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libhogweed4 amd64 3.4.1-0ubuntu0.18.04.1 [140 kB]\n",
      "Get:15 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgnutls30 amd64 3.5.18-1ubuntu1.6 [646 kB]\n",
      "Get:16 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libseccomp2 amd64 2.5.1-1ubuntu1~18.04.2 [43.0 kB]\n",
      "Get:17 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 apt amd64 1.6.14 [1,207 kB]\n",
      "Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libcom-err2 amd64 1.44.1-1ubuntu1.4 [8,696 B]\n",
      "Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libgcrypt20 amd64 1.8.1-4ubuntu1.3 [418 kB]\n",
      "Get:20 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libpcre3 amd64 2:8.39-9ubuntu0.1 [231 kB]\n",
      "Get:21 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libsepol1 amd64 2.7-1ubuntu0.1 [250 kB]\n",
      "Get:22 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 libss2 amd64 1.44.1-1ubuntu1.4 [11.2 kB]\n",
      "Err:23 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 passwd amd64 1:4.5-1ubuntu2.3\n",
      "  404  Not Found [IP: 185.125.190.39 80]\n",
      "Fetched 7,313 kB in 3s (2,832 kB/s)\n",
      "E: Failed to fetch http://archive.ubuntu.com/ubuntu/pool/main/s/shadow/login_4.5-1ubuntu2.3_amd64.deb  404  Not Found [IP: 185.125.190.39 80]\n",
      "E: Failed to fetch http://archive.ubuntu.com/ubuntu/pool/main/s/shadow/passwd_4.5-1ubuntu2.3_amd64.deb  404  Not Found [IP: 185.125.190.39 80]\n",
      "E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?\n"
     ]
    }
   ],
   "source": [
    "!sudo apt-get upgrade -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "block:",
     "prev:transform_metadata"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting git+https://github.com/openai/whisper.git\n",
      "  Cloning https://github.com/openai/whisper.git to /tmp/pip-req-build-rsjqxqap\n",
      "  Running command git clone --filter=blob:none --quiet https://github.com/openai/whisper.git /tmp/pip-req-build-rsjqxqap\n",
      "  Resolved https://github.com/openai/whisper.git to commit 4179ed2475cc84cba66868b516232ef1b74dacdf\n",
      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from whisper==1.0) (1.19.5)\n",
      "Requirement already satisfied: torch in ./.local/lib/python3.8/site-packages (from whisper==1.0) (1.13.0)\n",
      "Requirement already satisfied: tqdm in ./.local/lib/python3.8/site-packages (from whisper==1.0) (4.64.1)\n",
      "Requirement already satisfied: more-itertools in ./.local/lib/python3.8/site-packages (from whisper==1.0) (9.0.0)\n",
      "Requirement already satisfied: transformers>=4.19.0 in ./.local/lib/python3.8/site-packages (from whisper==1.0) (4.24.0)\n",
      "Requirement already satisfied: ffmpeg-python==0.2.0 in ./.local/lib/python3.8/site-packages (from whisper==1.0) (0.2.0)\n",
      "Requirement already satisfied: future in ./.local/lib/python3.8/site-packages (from ffmpeg-python==0.2.0->whisper==1.0) (0.18.2)\n",
      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in ./.local/lib/python3.8/site-packages (from transformers>=4.19.0->whisper==1.0) (0.13.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->whisper==1.0) (21.3)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->whisper==1.0) (5.4.1)\n",
      "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->whisper==1.0) (3.8.0)\n",
      "Requirement already satisfied: huggingface-hub<1.0,>=0.10.0 in ./.local/lib/python3.8/site-packages (from transformers>=4.19.0->whisper==1.0) (0.11.0)\n",
      "Requirement already satisfied: regex!=2019.12.17 in ./.local/lib/python3.8/site-packages (from transformers>=4.19.0->whisper==1.0) (2022.10.31)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->whisper==1.0) (2.28.1)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in ./.local/lib/python3.8/site-packages (from torch->whisper==1.0) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in ./.local/lib/python3.8/site-packages (from torch->whisper==1.0) (11.10.3.66)\n",
      "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch->whisper==1.0) (4.3.0)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in ./.local/lib/python3.8/site-packages (from torch->whisper==1.0) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in ./.local/lib/python3.8/site-packages (from torch->whisper==1.0) (8.5.0.96)\n",
      "Requirement already satisfied: wheel in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->whisper==1.0) (0.30.0)\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.8/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch->whisper==1.0) (65.4.0)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.0->transformers>=4.19.0->whisper==1.0) (3.0.9)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers>=4.19.0->whisper==1.0) (1.26.12)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers>=4.19.0->whisper==1.0) (2022.9.24)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.8/dist-packages (from requests->transformers>=4.19.0->whisper==1.0) (2.1.1)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers>=4.19.0->whisper==1.0) (3.4)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "!pip install git+https://github.com/openai/whisper.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: sentence_transformers in ./.local/lib/python3.8/site-packages (2.2.2)\n",
      "Requirement already satisfied: huggingface-hub>=0.4.0 in ./.local/lib/python3.8/site-packages (from sentence_transformers) (0.11.0)\n",
      "Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from sentence_transformers) (1.19.5)\n",
      "Requirement already satisfied: transformers<5.0.0,>=4.6.0 in ./.local/lib/python3.8/site-packages (from sentence_transformers) (4.24.0)\n",
      "Requirement already satisfied: tqdm in ./.local/lib/python3.8/site-packages (from sentence_transformers) (4.64.1)\n",
      "Requirement already satisfied: sentencepiece in ./.local/lib/python3.8/site-packages (from sentence_transformers) (0.1.97)\n",
      "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.8/dist-packages (from sentence_transformers) (0.23.2)\n",
      "Requirement already satisfied: torch>=1.6.0 in ./.local/lib/python3.8/site-packages (from sentence_transformers) (1.13.0)\n",
      "Requirement already satisfied: torchvision in ./.local/lib/python3.8/site-packages (from sentence_transformers) (0.14.0)\n",
      "Requirement already satisfied: nltk in ./.local/lib/python3.8/site-packages (from sentence_transformers) (3.7)\n",
      "Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from sentence_transformers) (1.6.3)\n",
      "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from huggingface-hub>=0.4.0->sentence_transformers) (3.8.0)\n",
      "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from huggingface-hub>=0.4.0->sentence_transformers) (2.28.1)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub>=0.4.0->sentence_transformers) (5.4.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub>=0.4.0->sentence_transformers) (4.3.0)\n",
      "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub>=0.4.0->sentence_transformers) (21.3)\n",
      "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in ./.local/lib/python3.8/site-packages (from torch>=1.6.0->sentence_transformers) (8.5.0.96)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in ./.local/lib/python3.8/site-packages (from torch>=1.6.0->sentence_transformers) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in ./.local/lib/python3.8/site-packages (from torch>=1.6.0->sentence_transformers) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in ./.local/lib/python3.8/site-packages (from torch>=1.6.0->sentence_transformers) (11.10.3.66)\n",
      "Requirement already satisfied: setuptools in /usr/local/lib/python3.8/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.6.0->sentence_transformers) (65.4.0)\n",
      "Requirement already satisfied: wheel in /usr/lib/python3/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.6.0->sentence_transformers) (0.30.0)\n",
      "Requirement already satisfied: regex!=2019.12.17 in ./.local/lib/python3.8/site-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (2022.10.31)\n",
      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in ./.local/lib/python3.8/site-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (0.13.2)\n",
      "Requirement already satisfied: click in ./.local/lib/python3.8/site-packages (from nltk->sentence_transformers) (8.1.3)\n",
      "Requirement already satisfied: joblib in /usr/local/lib/python3.8/dist-packages (from nltk->sentence_transformers) (1.2.0)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.8/dist-packages (from scikit-learn->sentence_transformers) (3.1.0)\n",
      "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.8/dist-packages (from torchvision->sentence_transformers) (9.2.0)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.9->huggingface-hub>=0.4.0->sentence_transformers) (3.0.9)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (2022.9.24)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (1.26.12)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.8/dist-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (2.1.1)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
      "    extend(render(renderable, render_options))\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
      "    for render_output in iter_render:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
      "    for line in lines:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
      "    for segment in segments:\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
      "    renderable = rich_cast(renderable)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
      "    renderable = cast_method()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
      "    pip_cmd = get_best_invocation_for_this_pip()\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
      "    if found_executable and os.path.samefile(\n",
      "  File \"/usr/lib/python3.8/genericpath.py\", line 101, in samefile\n",
      "    s2 = os.stat(f2)\n",
      "FileNotFoundError: [Errno 2] No such file or directory: '/usr/bin/pip'\n",
      "Call stack:\n",
      "  File \"/usr/local/bin/pip\", line 11, in <module>\n",
      "    sys.exit(main())\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/main.py\", line 70, in main\n",
      "    return command.main(cmd_args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
      "    return self._main(args)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
      "    self.handle_pip_version_check(options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
      "    pip_self_version_check(session, options)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1446, in warning\n",
      "    self._log(WARNING, msg, args, **kwargs)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1577, in _log\n",
      "    self.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1587, in handle\n",
      "    self.callHandlers(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 1649, in callHandlers\n",
      "    hdlr.handle(record)\n",
      "  File \"/usr/lib/python3.8/logging/__init__.py\", line 950, in handle\n",
      "    self.emit(record)\n",
      "  File \"/usr/local/lib/python3.8/dist-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
      "    self.handleError(record)\n",
      "Message: '[present-rich] %s'\n",
      "Arguments: (UpgradePrompt(old='22.2.2', new='22.3.1'),)\n"
     ]
    }
   ],
   "source": [
    "! pip install sentence_transformers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Load Youtube Metadata (YT Metadata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": [
     "block:load_metadata"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using custom data configuration jamescalam--channel-metadata-f05dcb73250ab96b\n",
      "Found cached dataset json (/home/jovyan/.cache/huggingface/datasets/jamescalam___json/jamescalam--channel-metadata-f05dcb73250ab96b/0.0.0/e6070c77f18f01a5ad4551a8b7edfba20b8438b7cad4d94e6ad9378022ce4aab)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "222"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "meta = load_dataset(\n",
    "    \"jamescalam/channel-metadata\",\n",
    "    split=\"train\",\n",
    "    revision=\"9614cf8\"\n",
    ")\n",
    "meta\n",
    "len(meta)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Transform YT Metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'videos_meta' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn [12], line 8\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;03m# where to save\u001b[39;00m\n\u001b[1;32m      6\u001b[0m save_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m./mp3\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, row \u001b[38;5;129;01min\u001b[39;00m tqdm(videos_meta):\n\u001b[1;32m      9\u001b[0m     \u001b[38;5;66;03m# url of video to be downloaded\u001b[39;00m\n\u001b[1;32m     10\u001b[0m     url \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhttps://youtu.be/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mrow[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mVideo ID\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     12\u001b[0m     \u001b[38;5;66;03m# try to create a YouTube vid object\u001b[39;00m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'videos_meta' is not defined"
     ]
    }
   ],
   "source": [
    "from pytube import YouTube  # !pip install pytube\n",
    "from pytube.exceptions import RegexMatchError\n",
    "from tqdm.auto import tqdm  # !pip install tqdm\n",
    "\n",
    "# where to save\n",
    "save_path = \"./mp3\"\n",
    "\n",
    "for i, row in tqdm(videos_meta):\n",
    "    # url of video to be downloaded\n",
    "    url = f\"https://youtu.be/{row['Video ID']}\"\n",
    "\n",
    "    # try to create a YouTube vid object\n",
    "    try:\n",
    "        yt = YouTube(url)\n",
    "    except RegexMatchError:\n",
    "        print(f\"RegexMatchError for '{url}'\")\n",
    "        continue\n",
    "\n",
    "    itag = None\n",
    "    # we only want audio files\n",
    "    files = yt.streams.filter(only_audio=True)\n",
    "    for file in files:\n",
    "        # from audio files we grab the first audio for mp4 (eg mp3)\n",
    "        if file.mime_type == 'audio/mp4':\n",
    "            itag = file.itag\n",
    "            break\n",
    "    if itag is None:\n",
    "        # just incase no MP3 audio is found (shouldn't happen)\n",
    "        print(\"NO MP3 AUDIO FOUND\")\n",
    "        continue\n",
    "\n",
    "    # get the correct mp3 'stream'\n",
    "    stream = yt.streams.get_by_itag(itag)\n",
    "    # downloading the audio\n",
    "    stream.download(\n",
    "        output_path=save_path,\n",
    "        filename=f\"{row['Video ID']}.mp3\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "meta[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# import and load Whisper model (for transcription)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import whisper\n",
    "import torch  # install steps: pytorch.org\n",
    "\n",
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
    "\n",
    "model = whisper.load_model(\"base\").to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Transform - Get list of MP3s and their IDs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "block:transform_mp3_and_ids"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "108\n",
      "['mp3/8bOrMqEdfiQ.mp3', 'mp3/FzLIIwiaXSU.mp3', 'mp3/c_u4AHNjOpk.mp3', 'mp3/JLKUV-LiXjk.mp3', 'mp3/GyJtxd14DTc.mp3']\n"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "# get list of MP3 audio files\n",
    "paths = [str(x) for x in Path('./mp3').glob('*.mp3')]\n",
    "print(len(paths))\n",
    "print(paths[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'8bOrMqEdfiQ'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we get the IDs like so\n",
    "paths[0].split('/')[-1][:-4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Add metadata with assosciated transcriptions to dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm.auto import tqdm\n",
    "import whisper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4696839489704783850a92e1539cf315",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/108 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jovyan/.local/lib/python3.8/site-packages/whisper/transcribe.py:78: UserWarning: FP16 is not supported on CPU; using FP32 instead\n",
      "  warnings.warn(\"FP16 is not supported on CPU; using FP32 instead\")\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "\n",
    "for i, path in enumerate(tqdm(paths)):\n",
    "    _id = path.split('/')[-1][:-4]\n",
    "    # transcribe to get speech-to-text data\n",
    "    result = model.transcribe(path)\n",
    "    segments = result['segments']\n",
    "    # get the video metadata...\n",
    "    video_meta = meta[_id]\n",
    "    print(video_meta)\n",
    "    for segment in segments:\n",
    "        # merge segments data and videos_meta data\n",
    "        meta = {\n",
    "            **video_meta,\n",
    "            **{\n",
    "                \"id\": f\"{_id}-t{segments[j]['start']}\",\n",
    "                \"text\": segment[\"text\"].strip(),\n",
    "                \"start\": segment['start'],\n",
    "                \"end\": segment['end']\n",
    "            }\n",
    "        }\n",
    "        data.append(meta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "with open(\"youtube-transcriptions.jsonl\", \"w\", encoding=\"utf-8\") as fp:\n",
    "    for line in tqdm(data):\n",
    "        json.dump(line, fp)\n",
    "        fp.write('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# load datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:load_data",
     "prev:add_metadata_and_transciptions_to_dictionary"
    ]
   },
   "outputs": [],
   "source": [
    "from datasets import load_dataset  # !pip install datasets\n",
    "\n",
    "data = load_dataset(\n",
    "    \"jamescalam/youtube-transcriptions\",\n",
    "    split=\"train\",\n",
    "    revision=\"8dca835\"\n",
    ")\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# build larger chunks of video transcriptions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:build_larger_chunks_of_video_transcription",
     "prev:load_data"
    ]
   },
   "outputs": [],
   "source": [
    "from tqdm.auto import tqdm\n",
    "\n",
    "new_data = []\n",
    "\n",
    "window = 6  # number of sentences to combine\n",
    "stride = 3  # number of sentences to 'stride' over, used to create overlap\n",
    "\n",
    "for i in tqdm(range(0, len(data), stride)):\n",
    "    i_end = min(len(data)-1, i+window)\n",
    "    if data[i]['title'] != data[i_end]['title']:\n",
    "        # in this case we skip this entry as we have start/end of two videos\n",
    "        continue\n",
    "    text = ' '.join(data[i:i_end]['text'])\n",
    "    new_data.append({\n",
    "        'start': data[i]['start'],\n",
    "        'end': data[i_end]['end'],\n",
    "        'title': data[i]['title'],\n",
    "        'text': text,\n",
    "        'id': data[i]['id'],\n",
    "        'url': data[i]['url'],\n",
    "        'published': data[i]['published']\n",
    "    })"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Hugging Face model for search - encode them with a QA embedding model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:encode_data_for_qa_embedding",
     "prev:build_larger_chunks_of_video_transcription"
    ]
   },
   "outputs": [],
   "source": [
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "model_id = \"multi-qa-mpnet-base-dot-v1\"\n",
    "\n",
    "model = SentenceTransformer(model_id)\n",
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# initialize the vector database "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:initiaize_vector_database",
     "prev:encode_data_for_qa_embedding"
    ]
   },
   "outputs": [],
   "source": [
    "dim = model.get_sentence_embedding_dimension()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#  first initialize the vector database where vectors will be stored"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pinecone  # !pip install pinecone-client\n",
    "\n",
    "index_id = \"youtube-search\"\n",
    "\n",
    "pinecone.init(\n",
    "    api_key=\"e18ea13b-25b1-48f7-82d7-c80765a396bb\",  # app.pinecone.io\n",
    "    environment=\"us-west1-gcp\"\n",
    ")\n",
    "\n",
    "if index_id not in pinecone.list_indexes():\n",
    "    pinecone.create_index(\n",
    "        index_id,\n",
    "        dim,\n",
    "        metric=\"dotproduct\"\n",
    "    )\n",
    "\n",
    "index = pinecone.Index(index_id)\n",
    "index.describe_index_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Encode segments and then insert the embeddings (and metadata) into index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:encode_segments_and_insert_embeddings_and_metadata_into_index",
     "prev:initiaize_vector_database"
    ]
   },
   "outputs": [],
   "source": [
    "# we encode and insert in batches of 64\n",
    "batch_size = 64\n",
    "\n",
    "# loop through in batches of 64\n",
    "for i in tqdm(range(0, len(new_data), batch_size)):\n",
    "    # find end position of batch (for when we hit end of data)\n",
    "    i_end = min(len(new_data)-1, i+batch_size)\n",
    "    # extract the metadata like text, start/end positions, etc\n",
    "    batch_meta = [{\n",
    "        \"text\": new_data[x][\"text\"],\n",
    "        \"start\": new_data[x][\"start\"],\n",
    "        \"end\": new_data[x][\"end\"],\n",
    "        \"url\": new_data[x][\"url\"],\n",
    "        \"title\": new_data[x][\"title\"]\n",
    "    } for x in range(i, i_end)]\n",
    "    # extract only text to be encoded by embedding model\n",
    "    batch_text = [\n",
    "        row['text'] for row in new_data[i:i_end]\n",
    "    ]\n",
    "    # create the embedding vectors\n",
    "    batch_embeds = model.encode(batch_text).tolist()\n",
    "    # extract IDs to be attached to each embedding and metadata\n",
    "    batch_ids = [\n",
    "        row['id'] for row in new_data[i:i_end]\n",
    "    ]\n",
    "    # 'upsert' (insert) IDs, embeddings, and metadata to index\n",
    "    to_upsert = list(zip(\n",
    "        batch_ids, batch_embeds, batch_meta\n",
    "    ))\n",
    "    index.upsert(to_upsert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# check everything has been added\n",
    "index.describe_index_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Encode the query using the same embedding model we used to encode the segments.\n",
    "# Pass to query to our index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "block:encode_query",
     "prev:encode_segments_and_insert_embeddings_and_metadata_into_index"
    ]
   },
   "outputs": [],
   "source": [
    "query = \"what is OpenAI's CLIP?\"\n",
    "\n",
    "xq = model.encode(query).tolist()\n",
    "\n",
    "index.query(xq, top_k=5, include_metadata=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Create user interface"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## working on UI for Q&A - find answers in youtube\n",
    "reference material\n",
    "https://gradio.app/docs/\n",
    "Gradio example - Franco Vega's medium article: https://medium.com/@franco.vegam/how-to-run-whisper-speech-recognition-model-and-create-a-simple-app-8426890299d8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "!{sys.executable} -m pip install gradio -q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import gradio as gr "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def question_answer(query, answer):\n",
    "    query = \"what is OpenAI's CLIP?\"\n",
    "    xq = model.encode(query).tolist()\n",
    "    return index.query(xq, top_k=5, include_metadata=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "gr.Interface(fn=question_answer, inputs=[\"text\", \"text\"], outputs=[\"textbox\", \"text\"]).launch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def interfence(audio):\n",
    "    time.sleep(3)\n",
    "    audio = whisper.load_audio(audio)\n",
    "    audio = whisper.pad_or_trim(audio)\n",
    "    mel = whisper.log_mel_spectrogram(audio).to(base_model.device)\n",
    "    \n",
    "    options = whisper.DecodingOptions(without_timestamps=True)\n",
    "    result = whisper.decode(base_model, model, options)\n",
    "    return result.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "gr.Interface(\n",
    "    title = 'Whisper-app',\n",
    "    fn = model.transcribe,\n",
    "    inputs=[\n",
    "        gr.inputs.Audio(source=\"microphone\", type=\"filepath\")\n",
    "        ],\n",
    "        outputs=[\n",
    "            \"textbox\"\n",
    "        ],\n",
    "        live=True).launch(share=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def question_answer(context, question):\n",
    "    time.sleep(3)\n",
    "    context = whisper.load_audio(context)\n",
    "    context = whisper.pad_or_trim(context)\n",
    "    mel = whisper.log_mel_spectrogram(context).to(base_model.device)\n",
    "    options = whisper.DecodingOptions(without_timestamps=True)\n",
    "    result = whisper.decode(base_model, model, options)\n",
    "    return result.text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "gr.Interface(fn=question_answer, inputs=[\"text\", \"text\"], outputs=[\"textbox\", \"text\"]).launch()"
   ]
  }
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