Intro_Fundamental_Python.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Intro Fundamental Python.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOKCSEqu1a2AjDfr4LR9kik",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/riskydav/Belajar-Python/blob/main/Intro_Fundamental_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_8OXYCClCEie"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YbH21zQUCGJp"
      },
      "source": [
        "# Introduction Fundamental Python\n",
        "![google](https://miro.medium.com/max/986/1*pimj8lXWwZnqLs2xVCV2Aw.png)\n",
        "![google](https://www.google.co.th/images/branding/googlelogo/1x/googlelogo_color_272x92dp.png)\n",
        "![python](https://www.python.org/static/img/psf-logo.png)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v-PhcfJ4CMv1"
      },
      "source": [
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HUta6BxLRst3EKXzKpztH4Cc/M1/T51pVIyRPv0WWnHiOP4oVZGRt1y+CuCjvWFiqMNm3+CEtH0CnugdC4qO4b8YoyvDM2neXNDSHNLHA8wRYhaDqGmO1x863O4bb4RU9w34yDR9H055v96k4fB1d71u9w3kSpELRsT70Gj6OgG5d9JPR9P1f71viCPmT707hnxj702rRGH0+gu76S2vRdKB8E+9ZWwx3HrH3rMdQQTa6LI0ThtJ0d9JR6PpOh+ktvuY/jH3qO5i6/WiNTzCj6f8RVTh9LyYfpFb3cRdfrQRRddvFEaTcNpToWO+kVPo6jtoDfxcVvd1GOf1oYo+v1orSbh1KfxL/OftU+jaQaGP6z9q3WsYBo63zp3ce9/rVGn6Po/kh7z9qzR4XSNGYxD6/tWcRR6EXPzq5LXDKSNfFEahoaJx/cm/Wno+i+Satnu4j/AP2gZEOf1oNbzGhH+SZ7lIo6L5BnuWz3cXh707uLw96DAKOj+Qj9yea0XKnZ9ELYDI/D3plj8Peg1/NqXlTx/RCt5rSfIx/RCz5YuZ+tO7hOw+tBr+bUvyMf0QrtoaY6uhjA/wBkLMGRtN7C6OMZFnO+tUYTBSbNhj+iFUUlGde5j+iPsWcRw2/apyRdEGuaWiH+Qj+iPsUimpDr5vGf+yFm7uJO7jQYPNqUm3m8Yv1YFHmtKDY08f0AtjLHyTKzogwmkorf4vH9EKvmlCf83j+is5EfRMsfMIMHmdGdqaP3Kww+k/Gp2ALIHxg6WViWO1OqCjIoIQRCwNB0UFgceSzBsZ5Ke7YeQQYREzoFbIy+wWURs6BWEbOgVGHI34q5TCmjuHWH436lpZWbXXJYa1ogNvjFBnypl8VksEsFBjyqcqvlCxyTwwkMfIMx2aNXH5hqgmwClQ2OsmN44BE0/jTHX6I195Cytw2I61Mj5z0doz6I/XdBrd+1zskDXTO6Ri9vadgsrKOsl1kkbA3o31ne/YfWt9rWsaGMaGtGwAsFKDXhoaWE5xHnf8d5zH69lsIiQERFoEREBERAREsgIiICIiDXxCqjoqOWqlNmsaSupYfhk/EFQK2vJEJd+DiG1lyXGk7vNqehYf3aS7vYFt4NdndMDcrGssPag5OmpaejiEVNCyNo+KFkcxkgyyNa4HcEKSDfZTYWUEoiKAiIgIiICIiAiIgIiICIiAiIgIiICIoJ1QSiA3RAREvyQEREBY5bizxyKyKHC4sgNIcARzTY7brFC7K4xH2hZjqEEAWPtS1tEGo8UNyLhNhbkotyU7i6H4yoj2pupPW6HdBH51G+ynn7UOm3NUR4qw6KEGiAd0VtCFXdZBEUbIMdTTx1UD4JRdrxb2eK65URSiOajm/dY2kX+MORXZVpYlRuqGNmgA7+L4N9Mw5tKlmx1BklxY7hSX6rZrsLre8dNBh9Q0nUtLQR7wVx5ir26OpXj3fap2q0p1zdVjzjoVIZXAf4s73j7VbLWW/xZ/vb9qaRUP8AAqc/QKHtry0iOmfm5aj7Vx76yujeWObYg2IN73V0ORDjuVYP8CuL8/rB0+tVNdXE3EhHgFNG3L5vAqc3gVwvntfyncnn1eB+7OCaNxzjDdwFuavK71RvqVwLazEHX/DuNvFQa6vv+7u96ujbmgfb7la56LhPP62/7s/3qPPsQ/KHe9NG45z1j+Kga8nouDNZiH5Q4fOhrcQ385d70TbnrP5aqRmtqFwArsQG9Q73qTXV/Kd3vQ258X6KzQb7Lr3n2IflDvenn2Ib+cPt7UNuyOdlFmglY9fiFde8/r/l3fSQVuIflLveht2IX+KUs6/wD7l13z2v/KnfSUee1/5U76X7UNuyWf0PuU2d8U+5da89r/yp/wBJPPK78qf9L9qpt2UNd8U+5Tldb4P1LrHntd+VP+l+1SKuttc1L/pftUNuztbITa1vaFc3ZoGkn2LqhrK3lUv+l+1T55Wbecu+n+1Vduzkybhp9yqWvvfKSV1nzqsP+dO+l+1Qaqr/ACpw/wC0ibdoAlH4hS8vxD7l1bzqq/KnH/tJ5zVflbvpIbdpvJ8Q+5CH9He5dWNVUflR+koNRUWv5076SG3afW+KU1O9wur+czfL/wDEq99NzqD9JDbtRcR8FpJ8VQl53uusGWX8oP0k76T5b/iQ27LmcD6oupEj/ij3rrwqqnQedW9yed1Nv8Z+oIu3ZGyu6BXa93iuDwx9RK+R7ahhdYCzrg266BciGVfy0Pvd9iDea89CsjQ4laDY6o71MI+Z/wBiysiqeVXF9B/2LQ3mtC5ijj7unaCNTquOw6jqXkOdJTyuGzS5zfzjVcqKWukNpJ4oW/6tuZx+c6D3FShI+OJueV7WNHMmwWNsk03+LUz3j47/AFGfXqfmC2oqGlid3gjzyfKSHM73nb5lsKDSbQSya1NU63xIvUHv3P1LZgp4KYWghYy+5A1PtO5WREBERAREQERFZsERFQREQEREBERAREQEREHUuMJxDidG5+rWtJt8626bG6Hu2nvQ3TmuN46Y+SupmRtLnGPQAXJ1XF0fD1dO5vnUraZp5ON3e5WS30np37D8TpcQae4la57dHNB1HitrW2q/O8RwypwJzKqmq3EX+ENCtrDuLa0nLWVuVo55QSpZ4+1ld8REWQREQEREBERAREQEREBERARNtyoJQTeyglQiAii4TMEEqbquYJmCC1wpXWMb4qELjSYW4OeNHS7geA6+1ddGL4mJO9FfPm65z+bZB+kouu4BxM2tIo69wbPsx+wf4eBXYb2QSii46Kb32QYJgWkPbuFma4PaHDmqkXFiscLsjzGdjqEGY6G6c/AoSDoVF1YJ2NuSDoo3TcJoSNNCo8EJ5qFRI6JqRryUKb63QNwo5Jsm3zoLNKg7qNjZTe+qlEE2VHuIVnbrHIoKl56rG6TKCSdBqVJK16k/gZP9kqDgcTnnrHkve7IPgsvoFxzorHZcpKy61nxqjS7sAbKcrbWAWd0ark8EGHu2uBaRcFYzRUpNzA0+JutrJYFSGcig1PMaX8nZ9ao/DKV7r5C3wabBb2XXZTlCDjxhNL8V3vT0VS/Fd9JchlsmUHkg0PRVJ8R3vT0VR/Ed9Jchl8Ey+CGmh6Jo/k3fST0TR/Jn6RW+Qoy+CDR9E0XyZ+kVPoqi+SP0it6ykBBojCqK2sR+kVIwui+RP0it3Kpyoaafoqi+R/4io9FUPyH1lbwCnKg0fRVB+T/WVb0VQfk/1lbllNgg0fRVB+Tj3lWGFYf+TD3lbluamxQaXoqg/Jh7ypGFUH5M33lbtkAQaYwmg/Jm+8p6JoLaUzfrW7ZTZXQ0fRVB+St+tT6LoPyVv1reslk0NH0XQ/krPrQYXQfkrPrW9ZA3VXQ0vRdD+SMT0XQ/krFvZeaZbKaGj6NovyVnuUejaL8lZ7lv5VOQJocf6No/yWP3KPR1H+TR+5chkTu00OP9HUn5NH7k9HUn5LH7lyPd+CkRaq6GmIABYMaLeAVhBf8AFHuW4IVkbD4INSOkZmzhgDiLXA5LO2lvyW2yIBXA6BBgZSN5gLOyFjdmq6sAgljbbLk6eQyRAu3GhXHDRb1H8B3tUo2ERFAREQEREBERAREVgIiKgiIgLUlxShhm83fOA/Yi2y210xsLnV8xkddrZDvvuunHh53tMrp3IEOAc0gg7EKVr0MjZKdoaNuXRbFj0WL0sERQ4hrS5xsALlQSsFXXU9EzNNJrbRvNcRifE8MF4aM5n/G6Lrz6iorZM0ji4nku2HDcu76ZuWvTlK3GDUzmSKNrXWyhwGtvascbA1pq62XJG3W5O61pJKTC4xLWHNIRdkY3K4OvxWpxGTNM7KwfBYNguueePHNYsyW+2fG8ZkxKQRR3bCz4LeviViwnCnV81i4MYzV7uns8Vo87rlKCqMNLLGw2Nsy8dvle29afpyIiiiIiAiIgIiICIiAiJcICaBQT0UG/NAJuiKCgE2UXKgnmVUlBJICguVSeixzTxU8Tp55AxjBcknZBlc8MaXvcGtaLkk6ALqWO8Suqs1HQOLYdnSbF/s6BauN4/NibjBDmjpgfg83+J+xcSiWiIs1LST1szaemYXPd7gOpRGIX3HJds4e4l73LQ4jJ6+0cpO/g7x8VtYZglLh8BY9jZZJBaRzhuOg8FwGOYC/DyammBfTE6jnH7fDxV0vcd7RdU4e4myZaDEpPV2jlPLwd9q7Wop4LFM38YbhZVDhcWQGOEjQ4c9/ah01WGM93IWHZ23tWdWCEQdE3VDmnOybhNSPFA8EHRQToCFPLMFA3Fim4sd1B6psb3QN1IIUHdOe6oOWKRZSbi6wy7LIxErBU/uMnsKzLDUfuT/YVkcS4XWJ7VlLjrssbiVoYSzwVCxZi53QKhJ6BBiLLJl6Laoo2TVTI5W3Ybkgc7C9lwUuPVBkeWU1O0ZjYZToPeg5LKpDTzXFNxuscbCGn+gftVxi2InVtPAR4REoOSyhLLinY3XNFzHT/ANGgxrECLhlOL/6tBytkC4x2L4my2eOBtxcXi3HVV9N4iHBuWn1/1QQcqQFNhZcUMYxM6AQHw7oJ6axL/Uf0QQcrogF1xLcbxJwzB0H9EFlfiWNRxNme2JsbtA4wixUHJ2tqi4c43ieYDvIdf9UFPpnFPlYv6Jqo5hAFw/pnFPlov6Jv2J6ZxX5eP+ib9iDmQFNlw3pnFfyhn9E37FAxjFvyln9E37ENuaspAXCemcW/Km/0bfsT0zi35WP6Nv2IObspsFwfpnFvywf0bfsUOxrF2i/ng3+Tb9iDngFIC4JuLYy9wYysLnE2AEbbk+5WlxPHIJDHNVua4csjfsV2ObtZTbwXXxjOMEn/AA52n8Vv2Lain4jmpH10dW4wsvc+rew3IHO102OWy+CkNXXXY1jDRfz9/wBEfYr+lMa7lk5xB4a8kN0Fzbfl4psdgspy+C4Kmrceq3mOnr5HOALjoNliOLYw0kHEZbjQ6D7E2OxZT0Uhp6LgKatx6smbT01dM+R2wFlE9bjlPlEuIyguvoCOSbHYch8fcpDPArrTMTxd7gwYnNdxAGq2Kt3EVFmNTXzMykD4Q1umxz3dnp9SuGeC6p6Uxb/9Sn+ktlj8ckpvORiU+Xlrofn+ZNjsgbbkrAeC6ccUxUAH0lOdfjLGcYxW/wD0hP8ATTY7uFYBde4fraqpeTUTvkPrC7t7WBXOBx+MfensZwrgLXDndT71cE9SqM43W3Rn1Xa81x+Y9Vu0Ju12qlG3fxS56qEUE38UuoRBObwUg35KqILXspVEQXRVzKbhBKIiuwTbUmywVlZT0EDqmqkDGN95PQLpmJY7iONufHTHzekYfWJNh855nwVHY8Q4nwvD7t7zvnjkzb3rrtHWmrnmqWs9WRxcB08Fw0tNBfR7nW3cd3fYskMjKbVrdNQfEEK453C9JZtzWJ1tTHSZ6OodGRJleQ7bRcbFU45M3PDXufzAEozH5r3V6Joq6Sshtc5Gyj2g2K0mU7XnLGC59/mCly32smnN0NRxV3gz1D44gMznyWcAP1nwU1vENTVgwtkcWDTa1/E2WGOaoZEI84YxotZugH2rJR4e2reJmZsvNzhofYtceUl7TKXXTThoJal2dugJ58/Yu04VgEcDWyVA1t8H7Vw2MYLiMrmT4bNnY0W7ouAIPh1WtTcZ4hQ0z6WeEyTN9VpkuCw+PVbz5bfxZmKnHE8UmKMp4rfgIw025HouuK880s8rp5nF73m7ieZVNeq4W7bifYtmnDjBUSNBytAaTbqsdNTy1MndxAXtclxs1g+M48gucrZcKpMJhwjDKptQ97u8qJWg2JCQfoKIiAiIgIiICIiAiKCeiCbhVJuh1RARFUkoGZQTZQTZVJQSSqE3Qm608SxSmwuDvZ3XcfgMG7j/AG5oMtZW01BA6oqZA1o26k9AulYtjFRist3+pC0+pGDt4nqVhxDEanEpzPUvvb4LR8Fo6BapIRLU3RRfXdchhOEVGKSerdkLT68hH1DqURhw/DqnEphDTt0HwnnZoXpHycPJvp+2CDHYoOKvQrsF81zvNB5yagzd7/rGZbd143zcra/k9JR09DCIKaMNaPeT1K9f+QH/AA7/AJr/AK0ufPlcOO5Y+3XixmWUlP7wP/8Adj/7D/6hfkXb/wBgA7DxgTXcVjHBjgqgQaDzYRCHuv8AWPzX73wtl530+i68j+X1/AX+dP6qvLwc/JnySZXp6OXjxxwtkeGMdwA0masoml0G72c4/wBn5lm4e4lNLlocQeTDsyQ7s8D4fmXZiOuxXV8d4eMOatw9l495Ih+L4jw8F79PI7kHBwDmkEHUEc1y/CGAffVxZgvC/nfmvpjEaag7/u8/dd7K1mfLcZrZr2uL23C/MuH+I30BbSVji6mOjXbmP9ngv2Dsee1/atwRJG4Oa7iHDSHA3BHnMazl1Lpce69DyeQKH/8A5r2P/wDgv/ULjOLvIpPCnCWNcUHtM869D4dU1/cehsne91E5+TN35y3y2vY2vsV7LXUe1796bjW/+juJfo0i+bj8jktnb23hw16fMR2mvRR4qSVXw9y+o8Kb216oCLqAm+6onmV638mjycOB+LezscWdovDZrp8UqnvoAauogyUrbNBIjczVzw8639XKQdV5d4T4cr+L+JcL4WwxjjU4pVxUrCGF2TM4AvIH4rRdx6AEr6i8P4JQcNYFh/DuFRd3R4ZTRUkDbkkMY0NFydSbDcryfL5LhJjj7d+DCZXdeOvKt7BuF+zrCMG4p4AwI0OHOmfR4izziae0jgHRP/COdYerI06gXy6arzSvqB2qcEU/aL2f41wfOGh9fTHzd7r2ZUMIfE7QjQPa2/UXHNfMOogqKSeSlqoZIZoXmOSORpa5jgbFpB1BB5Fa+LyXPDV9xObDxy3GPfQoh6p4r0uICsUuyyLHNtdSj1r/AHgP/wC7P/2H/wBQvM3an2eY52XcW4hwdjrC6Wl9eGcMLWVMLtWSsvuCNDYmzg5t7gr6qL8q8ofsTou2bgqSipmwQ8QYe10uFVUg0DtM0TiNcjwLc7GzrG1j83i+Tl5fvvT158M1+32+YTtyqOC3cTw2twjEqvCcTpn09ZRTyU1RC/4UcrHFrmnxBBHzLUX0XkYiFUtWYhUIQes+AfIQ++nhPh/jT+6p5r6awumxHzb0Hn7nv4WvyZ/OBmtntewvbYIfuZV3E/3bdzf/APDf/ql6x7Ff3m+A/wCTOF/osa7mvmZfI5JbNvbOHCzuPi5xtwXWcFcb8QcINmNcMDxSrwwVOQRd+IZnR95kzHLmy3tc2va5XHRuxuKERxskEYuALtsL7rs/b02Mdt/aCWPLieKsWLgW2sfPJfeunRk+i5hc275mnzFfRxu5K8V6unqLyXfJE4T7duAcR4t4p4kxnDZ6TGJcOjgoe5yljIYZM5Lmu1JlIt4BftEP3ODsla0tn414uf0yy0zfzwlbP3OD94/HP5V1P6HSL1Wvn8vNnjnZK9nHx43GWx5XP3Ozsemt55xlxvLkAay1ZSCwHtpz4Kr/ALnH2JnVnFXG4dawJraQj3ebL1Ui5/r8n9t/pYf08bcQfc2+E5YQ7hDtMxigqA698QpIqprm2On4MxEG9tddjprp+DdonkPdvHAzZqzDcHo+KcPj7x3fYRNmlaxvwS6B4a8uI1ysD7EEX2J+oSLePyeTH32l4cK+Is2F4jRTSUlVTthmge6OSOR7WvY4Gxa4E3BB0IKvLTYm+Jvetj7sbEyNAPLfnovqj29+S32edudBLWVlHHhPEzIiylxmmZZ9+TZmiwmZoB63rAE5SLlfM3tN7OOLeynHHcF8aYcaTEKOSQgtOaKeIn1JonWGZjtbHfcEBwIHt4ubHl/7eXk47x/9OtGiqSQ7NALf65v2qzaKse4NYICTsBM25+ta9O2mPeecvLbRksI5v5AqKXSqhP8ArG/nXZybLqKrjcWPNO1w3BmbcL072OeQT2i8c08WOdoVcOEMMe6N8dO6ITV1REQHE5MwENwSBnu4EG7LWv8AqXkPeTZRUNF/ds42w6Oetr5HnAKWeFwNLCHOaakh2hdJ+IbaMAcCc/q+zF4ub5Nl8cHq4+GWbyed8A8g3yecIpGU+J4Li2OStJLp63E5Y3O1va0BjaBy22531XLu8ifyZXNIHZsWk8xjNfce+dfuKLy/q537rv8Ap4f083cQ+QH2AYxAI8LpcdwKQOzCSixEyX0PqkTiQW1vpY6DXe/4F2n/AHPPtC4dhlxPs14gpOKadrnO8yqGCkrGszDKGkuMcpDScxzMvl0aSbD6HLr3aDxhQ9n3A+O8bYkC6nwWgmrHMBAMhY0lrBcgXc6zRruQt4c/JL1ds5cWFncfGytwfEcNrJ8OxIQ0lXSyvgngnfkkikaSHMc0i7XAggg6ghYo8MqaglkVRSuIFyGy30U4pisuO1dfjeMVclRiuIVT6qaUtA718ji57iBYAlxJ0Cx4XrUvB5wyf+Er6keFYUsrHBwraMFpuCJdirSU8sjzJLiFI9x3JlufzLj76fMrSuje8mFhYw2s0uv9aI3jhc8cYndV0YjkOjjLofZors86ZA6mZi1K2F5u5glNj9SwT/8ARlGejpR9YWqxzLPzgk5fVtyNx+q6K3W4e6dwhZX0Zc42AEh1PuVnUckI82kxGjGR1y0yE2PuWrQn/Dqc/wCtb+dRVerUzDpI785QbbIXROzR4rSMNrXD3D9S/aexvyQO1XtggixqDzbBOH5SCMTro5B3zSL5oI7B0o1HraMOvrXBC/ZPI+8kDCsbwqg7V+1XCo6ulq4xNhGETtD4Z4nAltRO03DmkEFjDoR6xvcL3S1rWNDGNDWtFgALABePm+T43xwejj4PKbyeWuDfuefZFgbYZ+K8cx3iGqbHlkaJm0dOX6Xe1kY7xu2gMh356Fd2HkVeTSWNbL2cvlLb+s/Ga++p8J1+4IvJebkv29E48J9PP+K+Qr5OOIU0sFHwtiGFvka5rZqTFqhz4ydnNErntuOVwR1BX4/x/wDc5KoQyz9mHaM+T1GhtBjsXw3B2p84iFh6uw7rcb2OnuBFcefkx+0vFhfp8dOPex7jvsxxqbAuN8P9GVEeZzJJY3dzOwWu+KS2WRozNuWk2JsbHRdUAa2PuhjdOGa6ZH6fUvsvxxwLwr2jcOVfCnGODw4jh1YwsfHILOYeT2OGrHDcOFiF8tvKS8nXH+wHiwUjpJcQ4bxJzn4TiTmgFzRvDLbQSt52sHD1hbVrfdw/InJ1fbzcnDcO56flppaZ2hxem/o3/Yo8xoibuxaAjp3b9fqWkpGy9Dj6eo/Jo8k6Ltt4NreM4e0VmFNpMUlw007cJNQHZYYn5sxlZb91tbLy3103u3jyVcd7FsCpeJ6TiD74cLkm7irmZQGndSPd8AuAe8ZHHTMSLOLRu4L9r+5xfvIY5/Kup/Q6ReoMWwrDsdwyqwbF6OKroq2F0FRBK27JI3CzmkewrwZ/Izw5LPp68eLHLCX7fIIeCuF+m+UF2LYj2L8avw4Ez4JiZkqMIqObogReJ38dmZoJ5gtdpew/MAV9DHKZTc9PLZcbqsgK3KA2Dlog2W5QHVw8EqP2jsE7BP7uPp3/AN7PQnoTzX/MfOe+77vf9YzLbuvG+blbX9b/ALwg/wDWx/8AYv8A1CjyB/4dfzZ/Wl63Xz+bmzwzsxr18XFjljLY+dvb52CHsP8AQX/vZ6a9Nedf5h5t3Pc91/rH5r974Wy876fkl1618vk2+8X+dP6qvI9z1Xq4crnhLk4cuMxysi1/FM3iqEhQXrq5smbxTN4lYS9VMtuaDYze1DK1ozOcABzK4PFOIIaC8UY7yb4o2b7V16fEquufnmmcejQbAe5B3OXGKGHR02Y9G6rUk4nphdsMLnEAkucbADqV1QyHYm6wVczhG2ljvnn1f/s30Hz7+5UbtVWVfEtdd7iymi2AGw9nUrDXsqIi2J0DqeFukbeR8b7ErkamnjwfB4mh5bO6QEFu+bmf1K9FikVS0U9YxoJ6/Bd9hXPPO4X01jj5RwjIC42AL/Dn/b3LPLRtbESbMLtLOKyVMlNRTPNJUOezofgjwPVaL5J615sbN5uK3uWMqwNvJ3ZlOT4Jy81zMMLYh3MUZLj+K3f5+i1cNpI+8LIXfBI7x9vWseQHJdkipIae8ULLa7nUk9SUk2vpq02GB4ElQQ8jaNou1vt6lcg1g20/OjGkG/Pb2/2/tsstri/5/wC39rrU6Rr1lZDh9M+pqCLNGgO7jyAXQq+umxGrkq5g0OedgLALtfE1PT1EMcck7myNN2MAGviVwTMMpdMznu9uizbro1a4nfQLmMD4eqMXcZS7uaZnw5nDT2DqfqWSrwundSB1C6IStd6zDcvd8+wCw4jjuJT07cMdII4YmhpZHpmPjZIVm4hqsJZBHhODNPdxuzSy/KO9vNcRC4RNJ66LGmuyWj9iREQEREBERARCfFVPVBJPRRoiICKCbKCUAnoqkoT0VSUAmyqdSl7rhcc4hjw8GmpS19SdCdxH7fHwQbGMY3BhceQWkqHD1WX28T0C6XVVU9ZM6oqZC97ufTwHgscsr5nullkc97zdzjuSqDfdGbQqFJC5/A+HXVGWrr2FsW7GHd/t8Ek2NbBcBlxFwnnuynB35v8AAfau4wwxU8bYYWBjGiwA2Cs1oa0NY0BoFgByCsAtel9AGq9c+QILff3/ADX/AFpeR1658gX+Hf8ANf8AWl5/k/xV14fzj1wvI/l9fwE/nT+qr1wvI/l9fwE/nT+qrw/G/ln/AL6erm/CvIyEcwpRfW08OnWMe4ezZq3Do9d5Ihz8W/YuyeT5jVRR9sPAtA+8kE3EuGMDb6scaqMXHh1CtZcr2WYDHJ21cBYjSBrHs4owp8rNg4CrjuR4rGf40x9x9XF1DthF+yTjcf8A05iX6NIu3rqPa/8AvTcbfydxL9GkXx8fyj6V9Pl/C/Oyx3boVc/mWuT3Mod+K7QrYX2o+aeKHe6bG3VPBUel/Ik4BdivF2I9oFZA002CQmlpC5t71Uo9ZzTfQtjuDp/lQvai/OvJ/wCAW9nXZXg2Cy03dV9TEK/ELhuY1EoDnBxGhLRlZfXRgXesWxSgwPC6vGcUqW09HQwPqKiV2zI2NLnE+wAr5HPn+pyWx7+PHwx0218/fK04BdwZ2r1eKU0DWYfxI30jBlbZolOk7d9Tn9c7fugX0Ba5rmhzXAgi4IOhC/DvK+4Bbxd2VzY9S0wkxDhmTz6NwDc3m5s2dtzyy2eQN+7G6vxs/Dkn+pzY+WLwN4KPBNxdDtcL6zwovyKo+zmkFXcefRUebaqD64IiL4b6byp5ZHk8TcU0j+1bgmgY7FaGL/2xSxMOesgaAGzNtvIwCxFruZaxuwB3hkhfZAgOBa4Ag6EFfPryt/J6d2aY8eN+EMMDOFMVk/CRRfBw+qcSTHlt6sTt2cgbt0s2/u+Nzf8A4yeXm4//ANR5yIVSFkIVV7XmfWDsV07HOAx/9M4X+ixrua6Z2LfvOcCfyZwv9FjXc18bL8q+lj6j449vL83bf2ggtaMvFWLDQWv/AIZLuuoRf9FVB6TM/MV3jtzrpGdtvaCwU1McvFOLC5hBJ/wuXddJbi1W1hibHTtY7UtEIsV9fH8Y+dfdfQ/7nAQew/HLf6V1P6HSL1YvLH3OiZ03YljbnMjaRxVUizGBo/xSk6L1Ovl8/wDJXu4vwjwp5ePbP2pcAdqOG8L8F8c4nguG1nDUNTNDRSiIulfU1LHPDwM7XZWMFwRa2ll5ow7yi+27DB5xB2w8YSVLHeoKjFp52WIsbtke5p32I033sR+2fdF6uWDtswSNjYiPvWpj68bXf53V8yvMLa1/o0z9xT9532TN3LdrX22Xv4ccbxzp5OXK+d7fvvZ95dnb5gWIFuPYxQcT0dg90FfRRxvDW3LgySEMcC4aXdnAsNNwfaPk/wDlS8A9vlPJQ4a2TB+I6WMSVOEVUjXOc2wzSQPFhLGCbE2a4W1aAQT8qmYrWxkmN0TCdLtiaP1Lf4e4z4k4Vxyi4k4dxLzHEsPmbPT1EMbA5jx82oOoIOhBINwVOT4+Gc66q4c2WN77faxfjXlR9gtD259nk9HR08DOJsJa6pwaqe3XOLF0BOnqSAZddA7K6xy2Xcex3tHou1fs6wfjalY2KSshyVcLSbQ1LPVlZryzAkHmCCu6L50t48v9j2XWc/x8QY8mG1k9NilHK2aLPC+J7croni4Ic12xB0tuFyPAeBt4q444d4XMrmel8VpKDM34Te9may4vz9Zfvvlo8Cv4C7cMVxCipo24bxJQDGqcCkDWRzklk7A7Z7u8YZDzHfNuOZ/KOxTGamHtl4DmmlaI2cT4W59mNHqiqjvrbovrTPyw8o8Fx8ctV9fsNw6iwfDqXCcMpo6ajooGU1PDG0NZHGxoa1rQNAAAAB4LJU1MNHTS1dTII4YGOkkedmtAuSfmCyrhuNMEn4m4Ox3hulq5KWbFcMqqGOeN1nxOlicwPaeRBdcexfI93t9H0+aPbX5WvaT2t4pi0mA45ifD3DNO9raCgo5zBI6PMRnnfGbve4aluYsbsL2Lj+G4Fj+I8OYkzE8JxGqo5mgt7ymmdG+x5XaQbXsbX5LaxZ/EWA4pW4HixkpK6gqJKWqgcG5o5Y3Fr2G2lwQR8yx4fiddJXQRyT52veGlpY2xB+ZfYxxxxmo+bllcruv0rgryte3fgKsMuE8e1+I0feGQ0WMvNdE4WtlvIS9g52Y5uvz3/Qu3zyxcS7YOx2j4Cq+HX4Ni9XWU9TiklM4Po6unjYXZW5/XjPf5HZPWsI2+ubkLzfNi2I98+1SWgOIAa0ADX2KhxjEzqa2Q+77Fm8WFvlrtZnlJrbWjqTHTywAH8KR7AB+vZbODMc+tLWscfwUmw/ilbcWK15wqaU1BL2ytaHEC4BB+xanpfExtXSj2FdGWkLtILmH1SLiyz19V55Ud8yB7BlAtb2rKcXxO9/Ppfet3FsUr46x0cVU+Noa0gM0GrQUGrPFL6GpX90+3eyC+U+Cw0VU6j729M+QSNy2sd9d/DXZZPS2Kfl8/0luYbiuIkVWarkeW07ntzG9iOaI4ygilNZTgQyE9438U9V+7+Sj2D/3Ze1yU47TP+9zhuRuIYkCxpbUEyEw0xB/FkLXZtD6jHi4JBX4d6VxMn/H6jX+OV9SPIy4Dk4J7CMEq64E4jxIDjVS8vc67ZQO4Gu1oRHcbZi7fc8Pkcn6eHXt14cPPJ+4sYyJjY42NYxgDWtaLAAbABcJxvxpw92ecLYhxhxTWilw7DYjLK613OOzWMbu5zjYADclc6vnT5fHbLi3EnaOOzHB6maLBuExG+pyCwmr5I8znFwOrWRvawAgEOMu4IXg4uP8AVy09nJn4Y7db7ZfLX7YO0TEqmj4RrKzhLh0SEU9PQ5o6uVgIs6advrBxsbtjLW2OU5rXP4Di2JcR8QVZr8crMTxKqLcvfVckk0lrk2zOubXJPzlZsJxGvdiVO19ZM5rn5S1zyQR7FrS4liJkcXV09yTtIQvqY4Y4TWMeC5XLu1+hYX22duHA+KMq+Ge0DiSntEy0b6l9RAdBe8UmaMm45tXtLyZfLQi7U8UpOAO0fBxhPE1VnFJWU8Tm0VaWjMGEOJMUpaDYElri02LSWsPzsnqq2FzGiuqDmY15PeHmL6LdpcZxajoIq2jxOqgqKesa+OaKVzZGOAzNLXA3BBFwQd1jk4ceSf61hy3Cvtauhdt/ZPg3bP2c4pwTisUInmjM2HVMjLmkrGtPdSi2uhJBtu1zhzXH+Tl2rM7ZOyTBeMJpY3Yk1hosVYwj1KyKwfcAnLmBbIAdcsjV+mr5feGX+x7+so+JdbgOMYFi9ThWL4NUR1WH1ElNUwOYbslY4tc0kXGjgR8yd2/b0BL9F/2L0H5enBdTwh24y47SPnjouKaKLEG2fZjZ2/gpWtA/2GvN+chXnJ09SIo5PO5iXlwI7w6Wt4+K+vhl54zJ87LHxy8X0X+50xSRdimOiSB8WbiuqcGuBGnmlJ1XqdeVvucr5JOxHG3SSOefvqqRdxJ/zSkXqlfL5/5K93F+EdN7WuzHA+1vgmu4QxprGPlaZKKqMed1JUgHJK0XBNr2IuMzS4XF18x+N+CeIuzviet4S4oovN6+hfldbVkrfxZGOsMzHDUH32NwPrUvw3yo+wKHtb4XOOcPUUX324PETSOuGGrhBu6nceZ1cWX0Dja4DnFdfjc36d8cvVZ5uPym57fOrMtugcczvYtWeGalmkpqmF8U0LjHJHI0tcxwNi0g6gg6WWbDz+EI8F9P6eJ7I8gX+Hf81/1peuF5G8gX+Hf81/1peuV8n5P8te7h/CPI3l+G33ifzp/VV5ELl658v42+8T+dP6qvILnL2/G/ijzc351cvWN0luao5yxuK7bclnzHkuJxvF/MIcjHXmk+CPijqt+WRsbHPebNaLkrotdVvraqSokPwj6o6DkEgB7nvL3uLnOOpJWdjreqFrR6e1ZWG4Ko2GnMbcjoT/b9qtg4ZU4o+rl+BCDIfY3b9SwhxbG5/QHW1+XVZMJDY8Or5XfJtZ7yqJrK+TFqpshzR08fqj2c/nKpNVtMjhAw+ubAXvpyC12NlqPVZ6kbdzsAsnnEVIe7po7yHQvcPzdFmrjjcrqM8VA91pax2Ubhn7FzMeF0r6bvInhz949fU/8A79q46nhnawyOu97xrfdZYppIXHunZSd2HZ37fFcc88pdx6b8e4zfsoyDXSNcG2ezUuJsCPYuyNd3kccoIIe0W0t/b9q4WHuaiRs7SWTR79R7RzHiubh1pxdwOXmP7abrfHyTLr7cMsdMgsf7f28f7baWI4tHRNMcVnznlyb7frWhiGPNa409CLnYy/qb9Wq4xozkk7nUk7rpllpmTbBLXySyvlec7idSTuVs07xJZw23PgsXmILvVNwDcC9lyFHhk07TFE0AO0c86ADmuXlv01qxqd73cElQed3fYuCJLiXHc6rvkvD1LNROpA5wkcBZ/Q+zpuuuYxggwaamBlEscwve1jvqumONZriI4pZXZYo3PPQC65ai4WxerId5uY29X6LvmHUdFT00ZpqWOO7QbhuvvW4qi1roiICIhNkC9lBPRQTdEAoiICgmyE2VSeaATzVblCbqEAmyqjyGgvcQGgXJOwC6njnEbqnNSYe8th2fINC/wHQINnHeJBFmo8NeC/Z8o2b4Dx8V1UkuNySSdST1UnbRVRm0UgEmwFyVMcckrxHEwue42AA1JXb8E4fjoQKmrAfUbgbhn7VZCRrYHw4GZazEGXduyI8vE/YuxorDZVoAspREBeuPIF/h3/Nf9aXkdeuPIF/h3/Nf9aXD5P8AFf8A3268P5x64Xl7y2+D+LeK/vM+9bhbF8Z819I9/wCj6GWo7rN5tlzZGnLfK6197HovUKL5nHn+nlMo9mePnNPl7/cf7Wv+q7i7/uSp/wDIn9x/ta/6ruLv+5Kn/wAi+oSL1f8ANy/px/48/t8vf7j/AGtf9V3F3/clT/5F2jsr7Ku07Du0/hDEMQ7OOKKalpsew+aeebB6hkcUbahhc9ziyzWgAkk6ABfRpFL8zKzWifHku9i6b20Tim7HeO6lzS4RcNYo8gbm1LIV3JdK7bonz9jHH0EYu+ThfFWNHiaSQBeXH8o75eq+X0NTT4hTNqKaQPY7Y8weh6FZaaTM0sd8Jv5l0LDsRrcDq3AMcBfLLC7QH7D4ruFNXU9VGyupH5mHRwO7T0I6r7MfNjkiLhfpHk9cAs7Ru1bBsGq6Xv8ADqV5xDEGkNLe4iscrgd2ueY2EW2f84/Ng64uNQdl7a8iPgP0PwTiPHtTrNxDP3FOLghtPA5zSdrgukLwdToxviufPn+nha6cWPllp6TX4Z5YvF33udkE+EQyyMqOIauKiaY3ZSI2nvJCdb5SGBhHMPsdCv3NeGPLV4ybjvaZScK08zXwcOUQbIMpu2ons94vsRkEO3O/sHz/AI+PlyT/AB6+XLxwr1N2BcYu457JOHcbmldJVMpRR1Tn2zOmhPducbfGyh3scF3nEKCjxWgqcLxGmjqKSshfTzwyNzNkje0tc0g7ggkELyj5CXF3qcS8CTyxgB0eLUrL+ubgRTHfUC0HLS56i3rZZ5sfDksi8eXljK+WvaJwjVcAcc43wfVtkBwysfDG55BdJD8KKQ209aMsd8+w2XXL2PtXqvy5+AzBiGCdpFLoyqb6JqxcfujQ6SJwFtSW94Dc/iN8V5TX0+LPzwmTxZ4+OVgSAsUhdYgaeKyrHJst2sPrkiIviPptfD8QocWoKfFMMq4aqjq4mzwTwvD2SxuF2uaRoQQQQVq8ScOYNxdgNfwzxBRNq8OxKB1PUQuJGZjhY2I1BG4I1BAI1XjbyNvKFlwjEYeyHjOvjGG1TiMEqpn2ME5I/wAGJOmR9yW3Is71dc4y+2105MLxZaYwymc2+WPbl2P4x2MccVPDdY2abDZrz4XXPaAKqA+I0ztJyuGmovazm3/Oyvql23dj+CdtHBM/DGJv83rIXGpw2tbvTVIaQCR+MwglrmncG4s4NI+YPFPDWM8HcQ4hwtxBRvpsQwyd1PPG4Ees06OFwLtcLOadiCCNCvfwcv6k1fbycvH4Xr0+pfYt+85wJ/JnC/0WNdzXTOxb95zgT+TOF/osa7mvnZflXtx9R8cu3cEduHaGCLH76sW/S5V0ZfoXbnHh57be0EyVcwceKsWuBCDY+dy87ro/dYZ+WVH9CPtX18fxj5uU7fRL7nF+8hjn8q6n9EpF6qXlj7nQ2BvYljYp5Hvb99VTcvaGm/mlJ4r1Ovl8/wDJXv4vwj5zfdHnM/u1YC0N9ccLQFx8PO6q3615eaL4Q4//ADA/8JXqT7ouyid224IamWdr/vVprCNgIt53V9SvNFHDRT0Zp4WVDx3ocHSAAF21tF9DhuuOPJyTfJdMGFREFz5qdr43gZc3Xa/uJ+eypieH1VNIal8QEMjvUczYdB4Gy7FDQZ5mxA3DQASuVxWkpGYNPBODlbGXutuLbfOty2lxkj1p9zs4nqZY+O+DJXR+b009FilOBfNnljdHLfW1rQw20673FvZi+fH3PHGGT9snEVFSPnjiqeGnzTRPa0tc+Kpp2sdfcECR4texvrsF9B1875M1yV6uC7wjyD90W4dgqOD+GOK7vE1FU1eHWBGVzZ4hJrpe4NPprzO+lvn/AIfWS4fXU1fTySRy00rJmPjcWua5pBBBGxuN19HfuhtRTU3Ytg8lTC6Rr+JYIvVsCA6kqr6/N+ZfOx9LhDaSOqL6wiRxaG+rcW31Xs+Nd8bz8/Wb7Bdj3aPh3az2bYFx7h2VvpOlaamIEnuKlvqzRagE5ZGuANhcWI0IXcl8vfJZ8puLsHxqfB8Ugr6vhTF5Q+shGRz6Wawb5xGOZygBzeYAtqAD9J+DeNeFu0Hh6l4p4NxumxTDKxmaOeF2x5tc0+sxw2LXAEHQgLxc3FePL/Hp4+SZz/X4p5SPkkYB2yir4r4YqI8F4wfT926Yi1NiGW2QVAAJDg1uUSN1ANnBwa0D52cVdm/HXZjxRT4Dx5wzW4NWd40sbO0GOUaEmORpLJALi5Y4gHTdfZlcRxRwhwvxthT8E4twGixaheQ4w1UIe0OGzm31a4cnCxHVb4vkZcfV7jPJwzPue3xUqRaolH8d35yrVNUagRAtA7tmU7eseZ/N7l7p7Zfue+FSMrOIuyGuqRKGulGBVU4IkcB8GGd+xNjYSG1z8IBeLOIMAk4Txqr4c4l4fxPDsToJO6qaWoeGSRu31GXYggg7EEEXBC92HJjyT9teTPDLD20If+iKkdJoz9RWCmmZC5/esLmPYWHKbEag6e5bjK/Co6WSkGHTlkjg5xM4vcbW0VqyDBqbustNVPMsYk/dgLA8tl0YcdPJ300k2UNzuLrDlcrbxm3nx8Y4z/whV73CAf8Ao+oPtqP2LejmwvF6xrJ6GWI93a7JeTRppboEVxPfA04p8u0hfe/ha31LawrV1UOtLJ+ZV73Cb+rhsxHK9R+xZ6XEMPo3PdFhRJe0sOecnQ78kDhrDavGuI8LwbDxGavEKyGkg7xxazvJHhjbkAkC7hrYr7WUFHBh1DT4fTNyw0sTIYx0a0AAe4L5FditPg03ax2eyNoZWvqOK8MhA74kN/wqLXx32X18Xg+Ze5Hq+NNSsdRPHS08tTMbMhY6Rx8ALlfFrifi2s4m4hx3iKeJsU2PYjUYjM3Nmyume57mg8/hnVfYDtVxKXBuy/jDGIGNfJQ4BiFSxrr5S5lO9wBsQbXHIhfHSsfhVNVS08eFFwjcW3dO4E2Wvhz3U+TfUa+FG2J0pv8A5VqwTaSvHRx/Ot2CvoqaVlRFg7A5puwumcRdZ2TYXVQVVZLhQEkZabNlcGkuP1L2vLpxtQ1jSwRuJBjadTfUjX2a8lnZrg8nhUt/8JUiooSQG4LESekrz+tbQqslMaZuCQGJzs5bncTf23ui6e1vuafEdVLhfHHCMpZ5vS1FHiUAAObPK2SOS52taGK3z78vbK+f33PPE4Kftb4hwKgoYooKvho1sshc5z88dRC1rRrYC0zr6XuBtz+gK+X8ma5K93Dd4R4w+6VcPxTcL8F8VAuEtHX1OHkDZzZo2yC/sMBt/tH5vBjhH3LXNNnhxDhffof1L6NfdFnRRdi+BTyU7JiOKKdga8mwvSVRvp7F87vP6b/9Jpfe/wC1ez413xx5uf8AN9D/ALnF+8hjn8q6n9DpF6qXln7nVKybsTxtzKeOEDimpGVl7H/BKTXUr1MvDz/yV6uL8I12YhQyV8uFMq4XVkEMdRLAHjvGRSOe1jy3cNcY5ADzLHdFsLx55TnaxxF2O+Ujw/xVgJE0f3tU8VbRPeWx1cBq6rMxx1sebXWOUgGxFwfVfCHFuA8dcN0HFfDVcyrw7EYhLFI06jk5rhyc0gtIOoIIUz47jjMvqrjnLbP6eT/LP8n/ACGftj4OoJHFzh6epohcNFrCrA5DQB9uofYeu5eQ8Od+GI8CvsDNDDUwyU9REyWKVpY9jxdrmkWIIO4IXzp8pDsBf2M8Xx4jgUc0nC2NPeaFzszzSSAXNO953sLlhJzOaDe5a4n2fG5tzwyefm49fuj9f8gP+Hf81/1peul5F8gP+Hf81/1peul5vk/y124fwjyF90BNvvD/AJ0/qq8gOXsD7oB/AP8AnT+qrx+4WXs+P/FP/fbzc351RyoVd26o7TVdnJxXEU/c4bIAdZCGLpwXZuKifNI7fKfqXWW7aKwZW7LLGLNG1z85WJouOQWZouOYHuComR12OBOuU7n9S3sBiFTS1dMRfNkNr76rWjEWQtN7OFrgAD5yVk4elMVe6nJt3rSz5+X1pBt1EcNM0sbIHOacrdLAOO3uGvuWOlp/O5muAIhpxlFz8J3M/Oqx0E+ITNjNxFETncRu4nU/m9y56GkbEwRxts1ugWK9vFhMZMr7UpYQHjS6YtQwCEziwLPWPsC3YoxGMx0suLxuaSe1G12VhIdK4bno0fnKLnncf3RxlPO+d9wDnBNnt/FXIxVbZY3UtV6veDKSDZr/ALCuPDwIxBAA1o+E5vM9Af1qW2a3IRdu1iuWfHvvF58cv7WqKF9KS5g7yPrbVvtVIzfW2q2aardCAHF0kfvc37QuSoIKETCpY1vrfB5tB6hYxz78c1uP3iigwt0obLUtys3Debhp7hquXY0MAZG0ANGg/t83vTNfw/t+36kB1/t/bovXjjMfTjbb7WG9rnXn/b2j3LrXGUcfe0kgkGd17s5gLsjSCbden9vFdW4jdT1mNQQ04DpmgMlcPjX2+ZaZruWH/wCJQ3+IFsrHTs7uBjOjQsinarITZQTrdQoJzKPFEQEREBVJ6ISqk9EAlQTdQsFTW09KQyRxdI74MTBme72Afn2QZyL6LTqsUpKRzo3SB8jBdzWn4A6uPL861q2aoEDqnEZjQ0w/ycbryv8AAu5ewe9dQr8RNWe6gibBTNN2xN5nq48z4lQbmN8QTYmTTwkx045DQv8AE+HguIv4KFPiqyLJTU09ZM2CnjL3u2A/OslBh9TiM4gp2X5ucdmjqV3XDMKp8Mh7uIZnu+G87uP2KyEjDg+CQYWzO6z6hw9Z/TwC5MBSBdTsrtTZSiIoiIgL1x5Av8O/5r/rS8jr1x5Av8O/5r/rS4fJ/iv/AL7deH849cL867Xu3ThLsW9E/fTh2L1Xpnv+49HwxPy913ebNnkZa/etta+x25/oq8j+X1/AX+dP6qvncOEzzmNevkyuONsdu/v5+yX/AEd4u/3Sm/5hP7+fsl/0d4u/3Sm/5heGbJYr3/8AE4nl/Xze5v7+fsl/0e4u/wB0pv8AmFyPDflldmHFHEWF8M4fgXFEdVi9bBQwPmpacRtklkDGlxE5IbdwvYE25FeCLHZdu7IB/wDFrgn+UWG/pMamXxeOS1Zz5W6fUJdR7YP3peNv5OYl+jSLty6j2wfvS8bfycxL9GkXzsPyj15enyoxvA4sUj7yO0dS0eq/k7wK6pTVVdgla4ZC1w9WWJ+zx0P6iv0BcdjGDQYtFrZk7B6kn6j1C+1Y+ZXLcD0NTxxi2H8P4A3vKvEqmOlhjff8G97gPXsCQ0XuTbYE8l9WeGsAoOFeHsN4bwuPJSYZSx0sIJucrGgAk8ybXJ6leCfuf/ZZVYn2l4rx7i1LKym4Xpu4piQ4Mkq5w5oId8F2WMPuNbGRh00X0IXzvl57ymP9PZ8fH9vkw1lXT0FJPXVcgjgp43SyPOzWNFyfcF8ruMOJqzjLinFuK67OJ8VrJatzHSF/dh7iQwE7hos0aDQDQL6EeUjWcRw9kWM4bwpgeI4riWMNbhrIaGjkqXtjk/dXFsYJA7sPGY6XLeoB8Gjsf7Wf+q/i7/uSp/8AIt/E1jLlU+RbbJHOeTpxieCu2Hh3EnyObTVlQMNqg0DWOf1ATfk15Y8219X5l9JV8v8A+5B2s/8AVdxd/wByVP8A5F9IOAMVxfHOCMCxXiCgnosUqaCF1dTzwPhfHUZQJAWP9ZvrA2vyss/LktmUX49sllcb2v8AA7O0Xs3x3hMRsdUVVK59GXuLQ2pZ68RJGoGdrQfAlfMaWKWCV8M0bo5I3Fr2OFnNcNCCDsV9a188/Kq4AHA3a1X1FJA5mH8QD0rTnK7KHvce+YCdCRIHOsNg9ugFk+Jnq3BPkY9eT8cJWN50KyO3WF697yvrqiIviPpvjgdzdfQ/yTvKB/uq8Nnhbiisi++rBowHkus6uphYCe3xgTleBfWztM1h87JJWNJu4La4a43xrgjiTDuKuG6o02I4XO2ogkBIBI3a6xF2OF2ubsWkg6FfT5sceTHX28XHcsLt9iV548rbyendqeAt4y4VgA4nwSFw7lrR/wC0KYamInfvG6lh21c07gt/SOxDtgwPts4Co+McIYKaoJMGIUJkDn0lS34TCRu06OadCWuBIBuB39fPxyy48tz29dkzmnTOxb95zgT+TOF/osa7moa1rGhjGhrWiwAFgB0UrNu7tZNTT5L9tPD9HWdsvHrnMcxz+J8Udma7mauTkvy7FcLmwqp83lcHNcLseB8Ifav1vtsxWGj7YOO8244lxMW//lSL80rZpcdc18g7uKIm3U+xfUwy1I8eeG69/wD3OL95DHP5V1P6HSL1UvMP3PaCGn7FsXjgZlb981QTre581pV6eXzua7zterjmsZHz2+6G4OK7tjwaq7/IWcM0zCCLgjzuq+vVeb6emazLHCLNZbL4eK9N/dAnPd2wYNEDoOGqd1v/AOVVLzbhzRI4NIt0uvZx39kjlljJla5GhzMGYRhzupWlxRM6mwiWMyXlncMxJ5XXMwsbG0aLpnEUOIYpiL54aYugjHdsdmFrDc79V6JHDKvVH3NfB4J+N+MuIHQ3mosKp6Nklz6rZpi9wttqadu+vq6ble/l5Z+57cBTcNdkmI8W10ELKjifEnOicw3caanvE0OPhJ39gL6HxIHqZfN+RfLkr1cM1hHkz7pBVNZ2RcOURd60vEkcoGmuSlnF/wDj+tfPuX/oilPSaQfUF7L+6R41JiGO8F8IUdQS6hparEamHvMrT3z2RxOIJAJHcygcwCds2vj2TDqk4XDCHwd6yVzyzvm3sR7bL3fGmuOPNzXedcfTR072TPqHlpYwFgBtck26Fdl7Nu0/jvsr4hhx3gXiOrwycyM7+Nj7wVLRcBs0R9WRtnOtmBsTcWNiuAbguIy/uccbrb5Zmn8xUxYVViVhc+maA4Ekzt019q7WS9Vyls9PoH2U+X/wXjdW3h7tWw08OV7XiEYlTh0tDK7QXcNXw3JO+ZoAuXBeqsLxTDMbw+nxbBsRpq+hq4xLT1NNK2WKVhFw5rmkhwPUL4sYlh801bPNDNTOZI8uB79o/OV+j9ifbV2odhGLR13DeIQzYJUTiWvwipqW+a1gtYkHXu5LWtIzX1W5szRlPk5Piy94PRhz2dZPrUvynygfJ74S7eOF5KDEoI6PHqSNzsLxVjPwkEltGP5viJtmb84sQCu09l3adwv2ucHUnGXClW2Snn/B1EBe10lJUAAvhksdHC4PQgtcLggrtq8UuWGX+vVZMo+KHFvDOL8G8R4hwtj1BNRYhhspp6mCUDMx4AvtcEcwQSCCCCQQVgxPUUZ60rPzlevfuiXZdBRcU4D2nYXBBAMaifh+JPc9kbXVEIBiedLue6MubfXSFo05+Sa6jbLHTCLEKJxihEb7zAa3J/Wvq8ef6mMyfPzx8b4uPjjjdFLJI9oLW+qM2pdccuYtdZ8H0xGMdQ4f8JUtwapkY6dlRSOYz4Tu+BA9qzYbSx01ZHPPiFG1jL3tLc7Loy4xtszQdtLrPXMpWTZaN+eIjQk678/7bK7sOGYhuI0RF9D3tr/UrzYPLTuDZ62jjLhmAMu467IO6dikwg7T+zuocARFxhhzt7bVMR3+ZfYNfGDh3EI+HK/CcYgxGjfVYViUOIsjMhDXGNzXAZrG2rei+zVNURVdNFVwODopmNkY4c2kXB9xXh+ZO5Xq+N6sde7TsJfj/ZtxZgUcpjdiOB19I14ZnLTJTvbcNuL2vtcXXxqxTTEakX/yrvzr7cTwx1EMkErbslaWOHUEWK+MfHfCx4d4xx7ADicNRNhWI1FDIAxzXF8UjmO01A1aeafDvVifIncrrby7u2ZiLa2013WzRG9BXf7MZ/4lnioIcjRMXvDdhewHsWzFSUxZLCyMxiZoa4h19jfmvX5xw8K4eF4ZMx3Q9VzUUkUtnWF/BYXcOZv3GtA8Ht+xW9D1FG3M+viy+DHut7gpf3emsN4+49cfc8MHjl7QuKceDn5qTBm0gAtlImnY8353/AC3zr3ovIv3O3hUUfBvFPGRkkkGK4hDQROLCxpZTsLiWgjW7pyCdRdltCCvXS+bz3edezj/AB6eWfuiNNUV3Y1glJTMa+QcSQz5b6kNpakGw5/DC+cLmOa4tc0gg2IIsQvoL5f/ABM6mj4N4XY9mSV9XXzC5zAtDGRnfb1peXL238YYxgFPizfOadwiqObgLh48R1Xt+NdYPNzy+W3uT7nGLdiGN/yqqf0SkXqpeW/udsMcHYtjkTJu8y8VVIcchbY+aUmlivUi8XP/ACV6OL8I8D+Xz+/Dg/8AJqn/AEqqXCeSh2+v7KeJ/vX4iqWN4VxycGoe828yqC0NbODb4Js1rweVnX9Wx5zy+B/8YcH/AJNU/wClVS81WC+jx4TPhmNeXPK48lsfYpj2SMbJG4Oa4AtcDcEHmFwnG/BmCdoHC2IcI8QwGSjxCIxuc0DPE78WRhIID2mzgbHUa3Gi8x+Rf2/ekKan7GuLKhxqaWNxwSrllv3sQ1NKcxvmaLlltMjS3TK3N65Xzc8MuLLVevHKcmO3nLyVOzfHOyrjDtG4Rx3LI+IYXLTVDBZlTA41eSVo5XsQRyIIubXXo1RlaHF4aMxABNtSBt+c+9Spnnc8vKrjj4zUeRPL/F/vE/nT+qryC4L1/wCX7twJ/On9VXkMjqvo/G/ijx8351gIIWN40Wy5qwvYV2rk4HiSEyYcXAfubw75tl1MEbkLv1ZAJ4XwvGj2lpXRZ4XU8z4JG2c0kFIVdj9NDb2C5WTIXAEm1+bnLDB6zsun1rcu1vwRcDm1oH1lUWbDA1rSfwjjyDdPrWGoZJSVDKpgy639hC2GAOkGaxFtMz/sWUwCaNzHN9V3xWWset0b8dxz2G1EVU1r22AkGa3Q8x71yQiaBcrpWHVcuG1BpZyWjNcHoeR9i7DWYr3kWVju7GW73X2UrphnuarJW17WExwuBLdzyC4SWV1QTr6hOp5u/YjvwzrgFsY5Hd3ifsUuFrXWWcsrkxgAaAaLLBTS1L+7jHib7BUsxzsjQS61yByA3XK0TomsknYwxtkccjTuG2FvzLUm2LWelw+nijexwz59C4ix3+paU1JUULu9p3BzHakcj7em+623VbGaF3v/AG+1VFa2R5iZ63I6Gw/Upnx45zRjlcVqPEmvGU5hb4TTuFvtmBAeDceHzLg6kUxeO7eGvHQ6g/MrwVj4yGTWF9A78V3t6FeaZZ8F1e462Tk7jmu+bHE+Z5JbGwuIB1IFtl1/A2PxrHpMSfHlYDmA6dAs+LvxKqpxS0Ebe7fpLl+GdfzLneH8LbhtE0Eeu7Vx8V6sc5nNxxssuq5TYWsh0RFagiIgIig7IF7KCbqpNlVBJPRY5Jo4rB5OZ3wWgXc72AKXskkIYyXu77kC5t4fassUUNM1zmgN5ue43J9pKg1zDWVA9Z5pY+jbGQ/Ps36yphpaeluIIg0u+E7dzvaTqVtgh7QWm4PNY5G3Sjp3GU8jqyGC57trMwHIklddXecewgYnCMhDZo7lhOx6grpM0MkEroZmFj2GzmnkkSqLfwrCKjFJcsYyxNPryHYfaVkwTBnYrMS+QNhjtnsfWPgB+td0gghpomwU8YYxosAFqQkY6Khp8PgFPTMytG55uPUrYRWAVUClEQEREBERAXrjyBR/+Ov5s/rS8kAeC9ceQP8Aw6/mz+tLz/Jv/wAr/wC+3Thv/wBI9bryP5fX8BP50/qq9cLyR5fH8Bf5z/qq8Pxv5Y9XN+FeR+WikFEX1Hzy2t127sg/fa4J/lFhv6TGuort3ZAP/i1wT/KLDf0mNZy/Grj7j6gLqPbB+9Lxt/JzEv0aRduXUe1/96Xjb+TuJfo0i+Rh+UfTy9V8vUUkeK/Q+wDgEdo3arguA1NN31BDJ59XtIBb5vF6xDgdw52VhH8dfayymMtr52M8rqPb3k49n7uzrsnwjC6qBseI17TiNd6oa7vZbENdqblrMjP+zyX6coAAFgLALQx/G6HhrAsR4hxSTu6PDKWWsndYkiONpc6wGpNhsNV8XK3PLd+30ZJjNOQRfPLEfug/bthlQaeo4U4H6tcKGrs4dR/hK3MH+6Fdq2IWhqOHOD4p+gpKqx9n+ELt/wAXkcv18H0BReFx5dPa2f4O8I/7pU/8wuW4T8uDjyt4nwqj4owThiDCairihrZoIZ43xQucA54c6ZwGUHNqDe1tN0vxuSH6+D2kvwTyyOAHcV9mI4loYGuruGJvOiQwFzqV/qzNBvoB6jzvpGdF+9AggEEEHUELWxPDaLGMNqsIxKnZPSVsL6eeJ4Ba+N7S1zSDuCCQuOGXhlMo6ZY+U0+TBPNYpDouydoHCVXwLxnjPCNaHZ8LrJIGucRd8d7xv0+Mwtd8661JsvsS7m4+fZrp9d0RF8V9J8Xqnr1Wm5jiT46LeqN7LUJDpBG54Zc2LuQX08Z9vJlX6t5N/a7iXYlxiOJoWTVWFVwFLidEyQgTQA3ztBOUyMNy0nq4XAcSvqNgmNYVxHhFHj2CVsVZQV8LZ6eeM3a9jhcEL49iOSmiYwsBYBYOYczSvT/ke9vreCMWZ2d8UV8jsAxeZraGRxzNoKtxt7RHISAeTXWdYAvK4c3H5funt048tdPeaJui8bu+P/bdlqu23tBYHm7OKsWaR0/wuVdcjYI4gANB05LuPbLTMi7ae0B2X4fFOLOPz1cq6fI7Lp7l9GXckjza17fQT7nu7N2MY0b/AMKKn9EpV6eXl/7noc3YvjR/+qKn9EpF6gXh5fzr0Y+ngfy+Iu87Y8H0v/7tU/6VVLz1R0rY23A1XrXyzOy7tB4v7RsP4k4X4OxTF8PpcBp6WWWigMxEoqZyWhjbuJAe0mw0Bv1X4VQdiXa9WzspIOzHidj5L2M2FTQsFhfV72ho25nw3Xt4bj4S2vPyW70/M+JsU9GUBbGfw1RdjD0HMrN2MdlPEfbRxDTcC8OERunqWzVdS8ZmUlM0fhJnC4va4AFxdxaLi91+zcPeQv22doGMCfiptBwjhUTzGJKqVtTUllr52QxOINzpZz2c/C/t3sb7D+Auw3h5+BcFYe8S1RZJX19Q7PU1kjW2Be7YAa2Y0BozOIF3OJvJ8jHCax7rGPFlle/TtnC/DeEcHcN4ZwpgNN3GHYRSRUdLHcktjY0NFydSdNSdSblcmSACSbAKV5r8tfygoOyzgSXgjh6uj++rieB8AayUtkoaJwc2So9XUONixmo1LnAnIQfBjjeTLUerKzCbeKPKp7QYu0ztv4h4go6vznDYHsoMOeC0t83iblDmEbte7PID/HX5QaZ4hE5a0MO1yLnle29ltYwR54L84oj/AMIWsahxhEByFrdiWi4F72v0uvr4yYySPn223dbOEaS1GXQmmk29i02R53NY0C7iABtqvbPkXeTTwd2gdlGP8UdomAedR8Q1Jo8MlzBssEEFw+aF7fWYXSuew30Pc2IIOvSu1nyBO1DhGplruzmRnF+ElxLImuZBXQN9YgOY4hslgGjMw3cT8BoXP9fDyuNrd4svGZR5bkhdEQ2RmUkZreC3Kj1sLogdg6X84W9xLwhxrw1J3vF3CuNYQ57gy+IUEtNd1jYeu0a2adPArleHuzXtC41w3DW8JcEY5izaieRkclJQSSRXLg25kAytFwQXEgCxuRYrrua2xq+npz7mzxTWQ8W8XcEGWd1JV4dFirGF9445IpWxOIbfRzhM25A1EYudAvfK84+Rr5OONdiHD2J47xlIxvEXETYRLSRyB7KKBmYtjLho6Ql5zEEt9VoBNiT6OXy+fKZcluL3cUuOEleUvuj0THdiuAzEeuzimnaD4GkqifzBfOyakmgY2SRgDXWLTe97i69yfdJeOqNtBwl2bQPifUunkxuqbn9eJjWuhh06OL5v6PxXhh9TLIwRvlJaDcAnS9rfmXt+NNcceXn7zbNNb0dWD+NEfrK14oJJy5sQuWNLyOdh0WxStLsPrSGkgCM3H+0tVkz4nZ43lp6gr0OS08L6eV0MlszdDY3WxihvPEetPF/4VqPe55LnEknmVyMlPJUBj36kMawacgFLdLJb6aINP3D7h3fXGU8rfavrD5JPaAztE7BeGMRkqBJXYXT+h64GbvXtlp/UaXnfM+MRyEHX8IN9z8qfRxccpavVvkG9rNJwLxfV9nGN1rYMN4okY6jMj7MjrwMrQL7d42zd9XNYBuvN8mTPDr6d+GXHJ9Cl87PLu7LajhHtPHaHR08jsL4tY10kgF2xVsTGsezQWGZjWPFyST3nJq+ia6t2mdnHDPaxwZiHA/FcEj6KuaLSROyywStN2Sxu5Oa4A6gg6gggkHxcefhlt6csfKPkC2ZpA2Kyju3at3X632teR/2wdmGIOGF4JWcU4O534LEcLpnSnW+kkDcz4iLak3ZqAHEmy/HnUON0WKNwSrwmsjr3PbGKUwPExc62VuS2a5uLC2twvbNZT9tcPXtlcZeui5PhfAcb4pxyj4e4foJa3EMQmbBTwRi7nvPt0A5knQAEkgBd14F8nnto48qmwYP2e4tDC5zA6qxCA0cDGuPws8uXMBuQzMbcjcX9z+Tp5LmAdikLeIMVqI8V4tngdFNVsLhBTMdlLo4Wm19Wj8I4Bx10aCQueXLMG5ht+j9lHZ/Q9l/Z9gvA9C8SDDacCeYAjvqhxL5ZNSSA57nEC+gIHJdtRfknlNdrY7J+zDEqrCqtjeJMUglpcGiDhnEpFnTgEG4jDs2osXZGn4S8klzy1911tmM28O+Vt2hR8eduuNy0UzJaLAwzBaZ7WkXEJPe3vv8AhnzWIsCLb7n82w6oc5mUnZdSovO4SY5InMAFxnaQbLsOHSEObY3vuvoSfp2SOG/1MdvoJ5CTWDskxhzGgF/ElQ5xA3PmtKL/AFBejl5w8hD96HF/5SVH6NTL0evDzfnXXD8Y8E+XuL9sGD/yap/0qqXmyy9K+Xr+/Bg/8mqf9Kql5tsF9Tg/jjx8v51alqaqgqoa6hqZaeop5GywzRPLHxvabtc1w1BBAII1C+kvk3dudJ2zcIXr+7g4jwkNhxKnDh+E09WoYN8juY5OBG1ifmxYLtHZpx5j3Zrxnh/F3DtS6OopJAJYs1mVMJIzwvHNrhp4GxFiAROfinLj/px8nhX1eRdc7PuPMC7SeE6Hi7h6VxpaxpzRyC0kMgNnxvHVpuOh0IuCCuxr5Nll1Xvl33Hkby+xf7xP50/qq8iFq9e+XyL/AHi/zn/VV5GIX0/jfxR4eb86wlqqRyKzkKpYu7k1ZImuC63xHg7nDz6Ft3NHrjqOvzLtZjVHxXFiLhND81Y5w+C4tO26zRGx+Dcexc7jPDT2udVYewkbujG49n2Lgh6ps9tjtqPtQZ2PI0zWA5XAW2ydpb6zMx8bn8+i02FZWNadTr/b5001MrFpYo6tmSUtY4fAfpp4WHJYY55adwpK1ti03aTt+0LYuTvsNh/ayl3dyM7mojzxjbkW+wq6ZZ2zw5cznBoGpHX2dVrTVTpjlhaQ3rzP2LG6gna0mkf5zGPxNnj5vsVIKp1O9xYxoflyjvBq3xHipMV3fTYdK2kiEPeN72VpEpB1Y34vtKiXE3FuRgsNra6LS7p41NyN77pdgOuh+dXaM5q5j8FxBPTRQ2qmYCA4gnU9frWEvaB6pVQJZNGxkkqDIHzzE+s4gaudrZviei5Dzmmh7qipc1WXfujgCBfo0HcK1DhuK10TaRriyG9y1otfxNt/nXaMJ4cpcPAe9ofJzUyxmU1Vl1dxwobV0Ia58cndHUHm32Hmubw7GQ5rWzuzNOzx+tcpLDFPGYpWBzTysuv12Cz0bzPRHMwnVv2/auF4suO7wdJlM+snYgQ8AtIIO1lK4XDazuvwZLw4fCYeS5eGVkzM7Cu83Z251dERVBVO6sqkdEFDuoVnbKjtiAbE80FHu1Bbe7TdUrqX0lSCITPY0n12t/ygt8Eqju8+DZ2mnqt+u5Vqd74ZLOHqP8b2KgzYZTTUlKKeaRrspOQC/qt5DXey2SLrjMbxOow+nb5tFeSTZxbdrddb2W/ST+c07Jw0tzi9iLIKyR3C4XGsFixKPMLMnYPUfb6j4LsDhzWGSO6aH5xHJW4PWXaDFNGbEHYj9YK7nhOLU+Kw52epK34cZOo8R4KmL4PDiUVnepK34EltvA9QunkV2EVut4pojoRsR+sFWVPT9CBsrLi8HxmDFYraMnaPXj/WPBck08lf9P8AVkRFVEsUTlsgbbqQFAF1NiEEr1v5A/8ADr+bP60vJA8V+5+TJ258Jdi/3yffTh2L1XpjzPuPR8MT8vdd9mzZ5GWv3rbWvsdufn58blx2Rrisxzlr32vJHl8fwF/nP+qrt39/L2S/6PcXf7pTf8wvw3ym+3PhLto+9v71sOxel9D+ed/6QhiZm73ucuXJI+9u6de9txvy8vBxZ48ktj08vJjcLJX4YiIvpPILt3ZB++1wT/KLDf0mNdRXO8CY7ScL8ccO8S4hHNJS4TitJXTshAMjo4pmvcGgkAus02uQL8wplOrFx6sfVFdR7X/3peNv5O4l+jSL8k/v5eyX/R7i7/dKb/mFwXHnlk9mPFHA/EXDOH4FxRHVYvhVXQwPmpacRtklhcxpcROSG3cL2BNuRXyseDklnT23kw17eN17R8h/gBmG8LYp2iVtLaqxiY0NFI4NJ81iPrlpGoDpbgg79y3TYnxcvZvB/lgdjPBvCuE8KYfw/wAXup8Ko4qRj3UdLmfkaAXm04F3G5PiSvb8iZ3Hxxjy8GplvJ6hX4F5Z3Gw4b7K28N00+Ss4lqm01my5HinjIklcANSLiNhG1pNeh0v7+bsl/0d4u/3Sm/5hec/KN7ZKHtl4uosTwOCvpsIw6iFPBBWMY2TvXOLpH2Y5w19QfC2YNl5eHgymcuU6ejl5cfG6r8cr6CmxGnNPUsu06gjdp6hdGxPC6rB6kNkJte8crdnfYfBfoZCwVdJT10DqapjD2O94PUdCvpe3jcBgfEIqMtJWuyybNf19q7CDddExjB6nCJxe7onH8HKPzHoVyuA8Q3y0lc+x2Y8/mKg+p/k6ceO7QuyPBMXqZ2SV9HGcOrrPDnCaH1Q51gLOczI+1vx+e6/S14D8mbyhcG7G4MbwviqkxWsw3EXRVFNHQRRPMU4Ba9xzvZo5uTmfgDRfuI8ujslP8HeLv8AdKb/AJhfM5ODOZ3xnT24cuPjN1+feXLwAygx3B+0agpcseKMOH4g9oaAZ4xeJzuZc6PM2+ukIGml/Ksuy9b9snlSdkfaj2dYvwczA+KoaqqjbJRzSUtMGx1Ebg6MuImcQ0kZXEAnK51tV5Im2Xs4PKYaynp5+XVy3i+uyLzQ7y/Ox1p14b4y/wBzpf8AmFjk+6CdjMXwuGuNP9ypf+ZXzv08v6ezyj58TuAc439iighbJOJJWPdG0+sW7rC58s0oayMkONr9FykTRDEGNtp+dfR3rF5bN5M5N5P8FML+ZaQYyf1H3LkKaAgiV9I9gHwsutx7QteiZmb67QVvEx0sTpQ8wgDUtNlMZ9pl109u+ST5SGGcb0sXZXxPi738R4dEfMJqnR1fTsF8tz8KWNo1HwnMbm1s8r02vjrg2K4xgGP03F2CYjUUNdRTNno52HLIxzdneI8DoQbHQ2X0D4B8tbsfxThHDa3jziQYLjxhDa+lbhtVIwSjRz2GNjxkcdQC4kA2OoXk5uPV3i9HHl1qvDvbaR/dj49sP4TYp+lSL8+qJF3DtWxzDOIO0ri7iHB6rzjD8Tx2vraWbI5neQyVD3sdlcA4Xa4GxAI5hdKhaaqqbGPgjV3sXpwnTna+h33PJjmdimMZt3cT1Lv/APUpV6hXgfyXvKd4C7E+z/EOFuKsH4gqqqqxiXEGPw+nhkjEboIYwCXysOa8TtLWsRr0/ZYvL17IJrFvDXGIB5mjpf8AmF5M8MssrZHaZSR6TRec2+XT2SO24d4u/wB0pf8AmF16u+6N9jVPLJFTcJ8YzlhLcxpqVrSR0PfnT5lP0eT+i8mM+3q1F4hx37pIKqpFDwV2Y5e9GWOqxSvvleb2JhjbqBof3QX1Gm689dpfladuXaaH0WKcXyYVh5JBocGBpInfCBDnNJke0g6tc8t0GlwumPxc776YvPjPT215Q/lj8EdkNJWcPcK1FNxBxiGZY6WMl9NRuN7OqHtNri1+6acx0vkBDl84eJeOeJeMcereKOJ61mJYriEvfVNTPC1z5HWsPAAAABosGgAAAABcAh2Xt4uLHinTzZ8lz9uaxfFJhURtbDT27pjvWiDjci+5U8Pw4vxLj2G8OYXDRGsxWrhoqcPhY1plleGNubaC7hqtHFdZ4T1p4v8AwrSXRzfargfhSh4F4OwXg7DSXU2DUUNGx5aGmTI0AvIaALuN3GwGpK5xfLzsj8tvti7Mo4sKxesbxdg0ejabFZHGoib6xtHUi7xqRo/OAGgNDV6c4Q+6IdjeNNii4qwbHuHKgxZ5XugbV0zX6XY18Z7x25sTEBYa22Xzc/j8mN37e7Hmws/p6nRfhbPLc8mN7czu0lzD8V2DV9/qgK0cV8u3yb8OppZ6PirEcUfG1zmwUmE1DXyEbNaZmsbc8rkDqQuf6Wf9Vr9TH+3oJdE7Y+2Xg7sT4Sm4o4rqwXkFlFQxuHf1k1tGMH53bNGpXk/tF+6QVlRDJRdlnA3mpc0Za/GpA97Tc3tBGct7WsTIRc6t018g8acc8W9omPTcT8a4/VYvicwDHT1Dh6rBezGtFmsaLmzWgAXOmq78fxcrd59Ryz55OsXJdovalxZ2mcZYnxpxDW5qrEZi9sYa0tgiGkcLNPgsbZo5m1zckldb9K4h+Un6DfsWoi98mpqPJbvtsnF8SAsKx4HgAP1LH6Wr7/42/wCr7FgOqxluu6qNz0pX/lkn1LdkxLI+IzC/eRNc5w69Vwu2l1nrDdtOf9UPzlSyX2sys7c/BUwyt9R7XewrPBLLTTR1lLM+KWNwfHIxxa5jgbggjUEHmuEw+IsjMrhYu29i34aoNIjedORXC469PTjludvo15K/lTYf2m4fTcC8c1sVLxfSxiOGV5DWYqxo+E3kJgPhM5/Cbpmaz0kvjBTVEtPKyppZnxSxOD2SRuLXMcDcEEagg816R7KfLg7SOCYYMI40p2cW4bGAxsk8ndV0bRlA/DAESWAJ9dpcSdXheTPh+8XbHP6r6HIvP/DPludiuOU/eYnLjGCSg2MdXQmQHTcGEv05a2Omy7I3ysOwFzQ77/SLjY4VW/8A/Fcv08/6a8sf7friL8Jxvy0ew7CqR9RQ4li2Lyt2go8Oex7jfrNkb47+/Zfg/aB90J4lxU1WD9nfCEWBA+rHiOIyCoqMpb8JsQHdscDtmMg01GulnFnfo88XrvtP7WuDOybBHYtxTiUbJnsc6koY3A1FW4W0jZva5F3bC+pXzz7T+1DiPta4nm4m4glDRrHSUjHExUsN9GNvueZduTr0A6LjXF3EPF2MS47xRjVZimIVBOeeplL3WuTlF/gtFzZosByAWSmkuF7ODjxw7+3DlytdYx2NzMUEJcS0Rgi55XKzYedARzOi2eKKJ7pIKyJtzYxP8BuP1rXoAAWtBvbdbz9nH+L6EeQkLdkOKj/6in/RqZejV4d8mrykOB+x/gSt4Z4lwrHamqqsVlrmPoYIXxiN0MLACXysOa8buVrEar9Sd5eHZCwlp4c4w0/+Tpf+YXk5OLPLO2R0x5MZjJa/HfLzF+1/B/5N0/6VVLzbbVfrnlMdrXDnbNx3QcT8L0WJUtLS4RFQPZXxxskMjZpnkgMe8ZbSN53uDovyWy+jwy44SV5OSy5WxACyU+kzfaFW3VXh/dG+0Lp9MP27yde22o7IuKu6xSeeThrFCI8QgaM3cu2bUNbvmbsQPhNOxIbb6E0VbR4lRQYjh1VFU0tVE2aCaJ4eyWNwu1zXDQgggghfJy116a8mXylcN4Jw2bgntKxeSLCKdveYXWGCSY0+vrQODA5xabgt9X1fWF7FoHi+Tw+X78fb0cPJ4/trmvL4F/vF/nP+qryRYr0V5XPavwD2n/ep942PekvRnn3nX+Czw933ncZP3Vjb3yP2va2vJed11+PLjxyVz5bLnbFLBRlCyWHRLDouzmx5VBZ4LLYdFFgqMJj8Fo12A0OIEvljyyWtnZofn6rlbeCZfBB1CfhCqiJNJM2QdPgn3bLXOCYnFo6jlJv0uPquu8BqmwQdIZhNaf8AM5r9A1bsPDtU8jNTuaOZe4Cy7Wio4am4ao47OnJcRyabfWtubBcLnZkmo2vt+MSc3vW8iaHATcG4a8l0E00Xz3CwHgwDbEXW8WLsyIOux8G0zTeSse72MAXIU3D2F01iInSEfHP2LktkQVZGyNobGxrW9ALKyIgIpsVNrBZ2OMr8LMgM9JZkll16ircTFaRLK9jm6Zdh7l3Sy156ClqJBLLEC9ugN0vbeGUxvcZkREYFBUogoqEdFkcOaqR0QYXktaSGk+AWF7gWevYZvjc/mWw4e4rH3cceoYBfnbUqC9NKJ4zHKAXMNyCND0Nlepr6WjMQqZgwzPDGX5la5IjeJNARyPMcwsNfg1NikzKvvXAlmUmwILfAHY6oOWUEKsTBHG2IOc4MaAC43Jt1V1RgkjuuLxXCYMRh7uQZXt+A8DVp+zwXNEaLC+PwWaPziaGtwisAcTHLGbtc3YjqPBdtwXG4sUj7qSzKlo9ZvJ3iPsWxieFwYhCYZ22I1Y8btPgul1VJWYTVhryWPac0cjdneIWpU9P0IHkpXC4HjzMRaKeoIZUtHsD/ABHj4LmQVpUpyRPBBIspVfYrBSpRERRBERWLBERVRERAREQEREBERAOyqpJ5KFIkYqinhq4XU9RGHxvFiCukY3gc2Ey52Evp3H1H8weh8V3u4VJo4543Qyxh7HizmkaEK+1dUwHiIwFtHXPvHsx/xf2LtjXBwDmkEHUEc1+e4rBSU1dJDQz97E07/FPS/O3VclgPED6NzaSrcXQE6HmxZNu5rWrHZIib6nRZmPa9oexwc1wuCNiFx9fNnl7tuzN/as5XUaxm60XDMbGypJTxucHOaXfmV81iTrosjQZG5iABZed6Wv3bGi4bt7lliY+QhoaQFjebuETSsrQ2IauPsCg3mzRwAM1c87NbupezvW56prQ0ahg/X1WCB4a0yWDG9eZVpHOnaAAQCdB1XSVizthnf5zIGtHqhY6qERxE22XI09KGD1m2O61cTcHM7tvNSzrdWXvUddqpNCVmwiEtjdMR60h09ixVdO4vbBbV519i5WkgysbYeq3RT60v22YoLmxHiuQggy2FlihYRZwFwVvRNsLlbxjGVaeLPkhoZI6c2llBY09L7ldP+9uoOven6I+1dnq5zUTkg+q31WqjV0jle3BUWAS0tTHUOc5wjdmsABc+9Uk4bkdI5zZXBriSAQ24+tdiCwNYxwzOaHE6kkXVZcH97Mvy59zftT72n86g/wDD9q53uovk2fRCd1Fv3TPohUcVWYJ506N7XmPJG2PV7TcDmtf72/8A5j/iaue7qP5Nn0QndxfJs+iEHBfe4OdT/wATVH3ut/KR9Nq50sjH+Tb7goysH4jfcEHB/e8y/wDjQ+m37E+96PnVN/pG/YubLWX+A33KLN+KPcg4T0BEP86b/SD7EOBQ/lTf6QfYuaIaOQ9yiw6BBwvoOD8qb/SD7FBwWn/Km/0g+xc0bW2VHKDhTg9N+Uj6f7FR2E0o/wA4H0/2LmXFY3FBwzsMpR/lf+L9imajppGsaSBkGUEOOy5F6xHmqNMuAaANLaLNTRMec8jrNHVXIB3F1LTbTZY8XTzbIkja+8bm5dra39qzWGhGoWm13itune0RZFjkxk7jfHlvqubw8h7Bro1crEbiy6/h01nZb6Fc7A/MAbq4Xo5J2xTARznTR2q47FMHiq296z1ZBzC5OuOVjJOjrH2FY2vH/ZKWT0k3O3XIhPTSCOpbY/iuGzlzlFMSBrqpnp45GEOZmYdxzHiFhippaf1o/wAIzkRuPmWJPGt3KZTtyk0LKmF0MguHD3LjIcNkpZCbBwGxC5CmlD22usxHgumpl25y3HpigcbarWkaDI641ut0Mbe9rFa0wtK72reLGTDkHRWyN6KUW2UZW9FZgAeCBzSxKsBqPag5BERZEJYKUQRlCZQpRBFh0Sw6KUT2IUoi1oEREBERAREQERBqUBFNrXUWKbBSB1RqlS0ERFAREQVuiIgImiIIOyqRorqrggxkclikYHsII9izuVCOag1u6eRYvDR0aP1lZKU9y7uS8ZCbtudjzH61Exc0Zm5bDe5ssTnue0d3mvyLRYD3p6GtXTY6MWY6nhf3ER9VjbZZgbXJ100v7LLnfmWCnl72MOIs8aOHQrWGN0hxIYYL5iPh/i5vi+3dByCgi6lFRgkjBC4/EcOp66B0FQy4OoI3aeoXLECyxPZdZ0Pzmvw+qwmpDXkixvHI3QO/auy4DxA2uDaWrcG1AGjthJ+1clXUMFZC6nqGZmO94PULpOJ4ZUYVOGuJLCbxyDS/2FalR+gBSuvYBxEKrLRVzwJtmPOgf4Hx/Ouwe1aVKsNQqqWpSpRE3WWREPgoLui1GolFAPsU3CbNiJyRTabEUbnYqSU2bEVbnqlyqqyKtz1S5U1tNbDuiKskkcMbpZXtYxgu5zjYAKqEDVziABqSeS6nj/EhqM1FhzyItnyjd/gPD86wY7xG7Ec1LRuLKUHU7GT2+HguENlNiLKUV4KeWqlbBAwue42Ciadw4aqXDBO9kc493I5ov81gPejruzSOO+/tVIKSKgp2UURJy6vJO7raqZSQ02XHky278eOptjiBLiAdFldKIwQogNwS3osMt3Oyt1K5urJTMzvMruSZmh5kfr0HJZyGwUpaT6x0WmLuOuxT0ntswDvnmSQ3Dfghb8IYCLC55krDR0znXc7Rql84ZKGM2232C1OkvfUbMjzpE3QnxXGG9ZiAiZ8FpsfAcytuqmMFO6X8d4yt8FGF05ghfUO+E8WF1b3dJOptqVlEZsQjljHqFhaPCxW42nEYDAPV5+BWSgZngF9SDcE8isj7Z8jd/wC2iSfZbrop2WGU7K9dN3FOQ0+s/wBULJA0WvyWhicuecRjZg+srcjnbtqNFlkA5qoHJWW2akbrFH8BqyjdYYvgBGV0RFQRFBNkEEqpVjuo3QVUKTuoQQQoU3UXCgqVVykuCq5yCrlhcpkmib8J4+bVYzJmF2skI65TZTa6qjzvosLllebaHQrC4qiCbKmayhzvFYy5VGYSLPTy65ea0C9ZIpcsjSTzUynlNNY3Vc3TPyvBC7BRv9UXO665CbOBXN0kl2C3JcML29Gc3HIVTe8p3jwutBjSGgjUHZchG8PbutOBmR0kJHqtcQPYt325T1pEcuVwa7ZZmsyuzR7HkteRtnZba7+1TDI9puNQjWttsMF87R7eqyggjdVbqA8fOrWsVpzTstapFpL9QtndYalurSVrH2la6sBZSi17ZEG6Kbfar6G+iAXGinKVkQiIgIiICIiQERNOa1sEREBERTYIiKiCQDYoXsYRncBfa6wTg2uDstSpLaqAxSEhzTmY4bgjmoOVRcZhmJGS9NU6Ss0PiORHgVydwoFkCIgIiICIiCqIiAiIgIiIKEKhHJZHDmqkc0GOyxSSMYbOcLna6zEc1jkjziwcWnqLKCjJhC8SXsDoTb61aPBsOZOZ20kYJcH2AsM29/HVU7mMesfWPVxus8Eji0xX1A9Un6rpBtXF7X16IuCwrD8YgxOWsq5IiJBlkLcwBA2DQd9eft3XOqgoIUogwvYtKso4aqF0E8Yex41B/P7VyTgsT2XWbB+eYrhE+Fy7l8Lj6kn6j4rm8A4j7zLQ4g+z9o5T+N4Hx8VzlVSxVEToZow9jxYtK6XjGDS4ZJnZd9O4+q7m3wP2qypp3xF1bh/iPLlocRfp8GOU8vA/au0rapB6qdgqpcqaTSSVCe0oqol+SIgkXKXvsoRNGgnol7oiAiIgIoJsteur6bDad1VWSBjBoBzcegHMoMlTVQUkDqmplEcbBcuP9t10LHuIp8Xk7pl46Vp9WO+rvF32clhxrGqrGZs0l2QsP4OIHRviep8Vxtis2hc9VIkeNiosei2sOw2oxGYRRNNuZQTRU9TXyiGCMuJNr2Xc6DDYMGpy8WdUOFs3j0Cy4ZhkGHQiOJoLiPWd1/YlQ/vZTY+q3QLOV1GsZusTQS7U+1Yqq49RvNZ2mwNhtuViy5pC53JcK9ERbu4rD5lSGNweMti4lZHuDn6jbZZmsFPCZn6OcLAKSG9KTAXJc7NYW9pWSipDKA9wsAVWigfUTB7x6o5LffI2IZGWHVak32luuoiolyM7qLe2q02FkbgXC7ld0gB7x2zdAOqpRMdVTufazBr+xL3SdRaSF1RLDnGjnXt4BblU4MiyR6EbBLtD2ut8EGwUZLu7x50BNrrTO/S8TAyIlotm19hVI/XlfJvlAashkbluL2/WrU8YbEGn4RNyqm/tYyMhidI7QAXXCmQyPdI46uN1s4tVWcKVp29Z36gtASDqtxitgEKbrX71oGpUidp/GCqNgHqsTCMg+dGytPNVY67fnP50jK6lVurA6KhZN1KIKlQrKqCCFVXVSgoSsbishCxPCgo5yxPJfZgJ10Ks9YXkhS+ll1dt2jo27mwA6rlYqeFws4i668ytmiFmkEdCLrYZjANu9Y4OGxaViY6drySualw6CQWLAR7FxdTgTdXRXHgFs0uKuLfwgseq3W1DZG33um5fR39uo1dHNTXLhcdVpuNt13OrpIapuUgb3XAYjh7GkttlI2ICsy17ZuEvccQXI11nA+KrMx8Lsrx7PFULtFtzdhjNwDyXMUbhkHU8ugXB0788DHDmAuTpHWaSTbqvNOq9XuOVppcshYdt1ne3KC4bnUrTzDe2gF1tQSecM132K6y/Tlf7UqIy5wI35HoQkLXF1y2zT9RWZzQ4Bp5uKtEAC4W0Ovzq67TfS7XNacoVj8JYZRlIIuswdmaCFUQdyqTi7AehWQ6qjwXRkdNVZ7ZrXREXRkG6soH51KDfbsPYpUM+C0+CE9FkQTdFCo+QN5oLqC9o5rVdU5nBjBcnYBXawnWQ3PQbIM3eAmw1U5wqXIFhoPBALqjIHt6FSHNPJUAVggtYIQeSDqPcpUFUVkIugqBdEIsisFHtuFx9REW3IXJbrFLEHDZSjrk7ZXSjuwWzR3cxwPwm82/rXPYXWx1dOCNHtHrt/WuPrabQluhGoI5FcBUYpW0NZnbG2MXu4N/GHX51cZcuh3xFo4XiEddTtkY7cf2C3bnolmroSiIoCIiCqIiAiIgIiICqbKyqWoKEKiykclQjRQas7ZM4c0vI+K0D86M71rw/1W5eW/vKznZYHyHOWBjtOew96g25quGClkq5Ce7ibncbbBaGB46MVzskjax4JczKbhzL29oP2rYpp2PcYiQ5rh0uPYtiKCmpWOcxrGDdzjp7yqMyLHT1MFXEJ6aVskbrgOadDZZFQVSFZEGF7LrVnp2SxujkYHscLOaRoQt4jkVjey6zodCxrA5MOcZoQX0xOh3LPA/atzAeI/Ng2ixB94tmSH8TwPgu0TQte0se0Oa4WIIuCF0viDAZKG9VSNLqe/rN5x/sVlTTvAcDYg3B1BHNSuj8O8SOoC2irXF1MTZrtzF+z8y7qx7XtDmuDmuFw4G4IW1XREQEtzREBERAvoiIgKDopXG4zjdNg0GaSz5nj8HEDqfE9AmxlxTFKTCabziqcSToyMfCefD7V+f4nilXi1SaiqfoNGMHwWDoPtWOurqnEah1VVyF73e5o6AcgsFis27IKEOnJcnhGCzYhJne3LE3cn+31KDHhmFT4jKA0WZuSdrLulBQwUUIhhbYczbUq1NSxU0QihZZo958Stj1WNLnGwCbFZpO7jNjZx0C0gdDbkFeWUyvzHYbDoqNtYjrouOV3XfDHUQ69st91SdjywNjdldfU+CygC4uVB1NiFmt6TSwhxvIbgam6ksdW1AH+TZoPFWYx7wImAAHdbkcUdOy9tVZNxLdIcWwNysbbktcusDc5nE3USyGQkuJA5BWigc4i2g5K7/pJP7Yu6dUOsToFuU8YpnWaPUOhV442xNtbdHyAG3VWTXaW76WflaSQfALC5xeMh2VyL2BKNaNxsiRMbMtrHRZHvbBE+Z97MBcfFTGFgxE5o20zW5i83I8Fr1D8q65UVM75HTPaczySpip6mfVxLQei5alwoZ+8lGY7gcgt1sEbSCGhZ7rWsY4iLCmgZpLud46ra9HR3aHNbe19tgt5wHeBo5WC13PMkoAP7q8/RamtLLaocPhcNANOawuoMoORx0W+HNtmGmpHuWpNWCJxaACVWffVa4imbu2/sU3OxWRlay+gB+dZ3MjqITKwWc3damX0zlh9xqi6aINkOq25IuieChAUEKUOqDGQqObdZSqkINZ7VgkYt1zbrC9ig0HiywOut6SO61pI1BemqGkhj9SNtd1ytBK58zTI8Wbs1vJdfc2xWWGtkZ6krjlOhINjZc7j9x2x5Pqu0smbKZJGn1bnL4gKksLahhcRqVo0tT6oLSLW9UDYLdjlDY2gnbUrO/qumv6dfr6RzQ5j26X0PRcTLG1n4xt7F3GuhZLGDbVy6xXUpZIW22K1MtdMZYyzbcoCRA1p5DRb0chaBc6X1WlSWETeQc0e9bTCDvuud9tz052K8o10zDRZI2uhfmYPV5rTpXudYXtouTY4FlrgkrePbOXS3eNeAAdVcbm3JceBJFVDX1PhHwW/C8SNzA7rcu2LNLPAe2yhhJBbdTctPrLBLL3c8bfjlWpO+m0EbzCnwUIjWc3K4t6FLHmslQ2zsw5rGF030ykIgRWI3WH1G+xCbBRH+5t9irK6w3WRSSW3Naksjje5WR5ubrBJspVjYpI8sfec3/mWdY6c3hYR8ULIqiQLqygbKRqqLAc1I3REgsBZLINlI10QQlkRQFBClEFVBF1J0RXY1p4cwOi4HFsOE7CAPWGxXZnC606mAOB0U9Dp2E4hLhNX3ctxG42I6Fd7pp2VEYkaQbjlzXUcZwzODLG31huBzThzGXU8goqh9hf1CfzLt/JN/aenc0UMcHtDhsVK4qIiIKoiICIiAiIgIiIKnqqELIVU7IMZCwyRRvcC9gNuqznZUIupRicWsG4FvqU1cBxKgkpmzvic/8AHZv7NeoWI07hIXMyj+MbuKy094HXLnOB3upsUwXCThUb2ecF4eB6trNFuft6lckuNxutqqPDXTUUL3yvIY3K3MWk87LLhFXNWUTJKiNzZG+q8uYW5j1AP9rqjdREVEOHNVIurnZVQYnsuteSMEFrhcHQgrcIusT23WbB0biDh11IXVtAwmE6vjH4niPD8yxcPcRSYa4UtUXPpXHTmY/EeHgu7yMGxC6hxBw2YS6uw9nqbyRAbeI8PBWUdxiljljbJE9rmOF2uBuCFdfn+A8Qy4TJ3M15KV59ZvNh6t+xd8gniqYmTwSB8bxdrhsVqDIiIqJCEjkoBsEQERcJjvELMOBpaQh9UdzuI/b1PgnoZsbx2HCmGNlpKlw9VnJvi77F0moqJaqZ1RUyGSR5uXFUkkfNI6WR5e9xu5xNySqrIG3QKpA6K1r6Bc3g2AOqS2pqgWxg6Dm72fagwYPgklc7vZgWQg7238Au2Q08cMbY4mZWt2AWWOJsbQxjQ1rRYAclkDVBQNAFzsFqTSGZ9m/BGyzSv7891GfUG56qmQRgghc8rvp1xx13WEM1VywBuoWRrb68uqPHILOm9tXKHEge9ZWRhxBGuiqGlpNhotmLJG2/PopJ21boYG07C95VHOfLZ5vY7BC0yvzP1A2b0WeOMN1O60x/2rHTAnM/VZ9ALAAID0Cki99FZGbVSbnwVTba11ctJCxvJ1ASgeVzbwV2jVY266rK0dCotZWWAuVBZnkzW5bqriCAL81LprDQLbOqs4tYHEdNAsAIYGg201PtWrUYmxhLYm94726LRkqaqY3dIWjo3RTVNyOSlqYoQ573gEa2vqtM1sbXNfGHOIAaNLe0rVEPM6krI2MdFfE80vqamQBrLMaCT1K1HwySOzuec3UGy3g0KuT85WpIz5VpiGX5U/OAVtU7pYWOZmBDhbbZXyC6kABPGHlQCyW6qUV0yiyiysiCiK1goIQVIUFWQhBjI1VHNuspaqkINd8V1gki02W9bwWNzAeSg4uWHwWq+MhcxJDfktSWDwUsGpT1T6Z1tSw7hctHVh8dmm4cNCuKkhIVYZX07+eQ7j9azljt0wz11XYTO2RzGg6ALVxCmbIHuaNQFibLcBzDcEaELfic11w62o964+ndxNI0uhLLasP1LahaJCNfWuqZBT1bT+JIMv2LdFMIXh42KX+yNinu2w5+C345MoWnCLjW17b/AJllY692ne4Wp0ze22WtkZc89FiL30rgW3LQdVaJ4IAPL6ykjDmvewGllpiNxrmStBCw1kRcwPaPWjNwtZrnwXLXXAW7DNHUs0PtCu99JrXcKabvY2uO6zHRaeU0ztPgrazAszDmrEqS0ObZ3Na5aWnwWSR2VmUHU6KrXNJyHZunzrUuks2qis5hafBVXSMNuM/gm+xYpjoskf7k1Y5QsDAdlhkG6znZYpBopVjJQSXjdGd2H6itlcdBJ3NQ0nQO9UrkVrEqw2VhuoGgUjdVFkCIN0gspG6hEgsRdVV1UiyghCiIBF1W1lbnZDsgqqvbcKyKjjaqnBB03XVcYw91PJ5xELC99ORXeJGBw2XF1tI17S1wuCkvjdwvbX4cxoVMYgmd+EaLG/MdV2IEEXC/OqmKfCqsTQkixuCu5YLisdfTtIIDtiOhXTOeU8ok66cmiIuSqoiICIiAiIgIiICqRorKHIMZFlQ7rKRyVCEGN22g1Wo6Z5dZ2VhH4oOZ3uC3SqFrQSbAX3KyLUkhe0teHA9CdwprsSpcOi76qccotfKLlaxna14EZzOHRMQwulxmGITl1oyS2zjbXe4G6QcmCHAOabgi4PgixUsEdLAymjL3NjGUF7sxt4lZVRBPJQhNyioKlldVO6zRjewFYHs5LaOyxuaoOn8QcOEF1dh8eu8kQ5+I+xcZgePTYRLkN307z68fTxHiu+uZfSy6xxDw73uatoGWk3fGPxvEeKso7NS1UFZAyop5A+N4uHD83gVmC/O8ExeqwioJF3QuNpIjz8R0K79SVdPXQNqaaQPY73g9D4rpKMyKLjqurY/xNnzUOGSWbtJMDv4N8PFNjYx/iVtPmosOeDLs+UbM8B4+K6iXEnMSSTqSeaIsggBJDWgkk2AHNTHG+WRsUTC97jYNG5XbsG4fho2ieqb3lQdf4rfAINTBOHrZaqubru1i7G1gAAAAA2Vg1XDeqgqB0WvUy69006fjfYs1RKIW2B9Y7fauPc+x33WMstdOmGO+2zBlvoFkfH3rgOQWGlcHXst5oAFrLM7avVa012s0FljjbnaVszN9UjrotZr7HI3VL7Wekhtj48lIZc3tqrNaDru7qsjRyO/VE2pHFlNne9XII+fZWDevJLW0srpNobZZGgBVDQDdWuBqVYlVcbLEWG5urvIcdb6KCSdVKsQ0ZQpDrb7rHNNDCLyyW6DmVoy4jI8ZYG5B8Y7pJabb09XFAPXd7BzXHVFXLU+qPUZ05n2rCGknM4kk7krIG2W5GbdqtZbkrhqkBWGirKAFKIpUWAVQL39pUgo3UEeJWoIspt4KUTYiyW5KTslgrsVRWS2lk2KopslimoK2CEK1lFk0KkFVIWRRYKaGMtVSFmICqW6oMBasT2A8ltFiq5vgg0JIButSWn8Fy7mArC+EFQcTHJLTOu3VvNq5CGdsozROseY5hUlp78lqvgfG7OwkEcws5Y7bxz8XITDvoiw6O5fMt2GTvGtD/hWF1xEVcfgVDdfjD7FttlNrsN7i65WadplL6cn3uW2m6hzi052u2PvWnHUktNxe26vJKx0RdG/UD5x/bZRem/FOCbWsFsd5mF+i4iGQmw5g23+pbscwJ1Ol7D+MVZUsbTWggC1rqr4JY/wtORfmORRrgCA43JWcSAN12WuqxdxjhrWVDckoyuG62YjcgD4IGgWk+APlztFhve2q2YiIxlsQD7yrN/ZZPpaUkOJHwjoPDqVRvwrC9r6KX63J5/2sqtNiDf2q7RthocyywvYWGx2WRjxbRWcGvFity6YsTELxhRINFeJuVmU8lVwVZayxvCyuFiqOCysakoXI0kvfQtedxo72haUovsr4dJkldCdni49oSXVavpyKkbqFI3W4wspbuoUt3T6EoiJBdHC4BQbKRqFBjRSdFCAic0QQQoVlBGt02IWCaIOGyzqCLhUdfxOgbPG5rm+w9F16jqp8Grtb5b2c3qF3ioiDgTZcDicD4x5xDGwvYCPWbfRXHK49Fm3ZKaV0tOyUjR4uNdbLMukYLjk8FT3VXMXMcdCfxSu6RSNljDgVcsddku0oiLAIiICIiAiIgIiIKk35KrhzViNVCDGQqPa17S1wuDyWUhUUGqKbQhz/AFeTWjKFngeIfwYAsdgEkDspyEA20vstMCSQhwzOPVwytHzblT0MeOtxl9TTHDWudG0iR1n21B+Dbn9fzLmmPe5jXPbkcQCW3vY9Fjp33jANrjQrTqMbpabEIaCUFpl0zOIFumm9j1Ko5FERUQdlUnwViVVZoHZUViVVQUIusbm5lr1WK09PIaeJrqmo+Si1I/2js351qOp6uv1xKUNjP+bwkhv/AGnbu+oIscPjOHU1bPJLhh7yZgJlyC7CembbMuMwrFarCagvjuWE2kiOgd9hXdWRMjYI42NYxuga0WAXDY3gQqgaqkaGzD4Tfj/tWpStLG+JH17fNaIOigI9cnRz/DwH51waOa5ri1wIINiDyRVn2hZIYZaiVsMDC97tgFalpZ6yYQU7Mzj7h4ldzwjCIMMjFhmld8J6Kx4NgcWHM7yQB87h6zungFy4ajQFkAQQGqk0rIG3OpOw6q80rIGZnnXkOpXFTTOkdmcdT9SxllpvHHyJpHOJcTdxWAXcd1Ju46LNHDbU7nVcvbt6jNC0RjQ6lbjH3aCdwtVlmkD5lkkOUXC3OmL2VE/4o5rCwW1VM2Y+tzWSNpDhY6FS91ZNNhg5/OsmW2t1DBbZWNthdakZ2g6aJzVm+KEeCptXXkVU67rHU1cNMLOdd3Jo3/YuMlr6qbQOyN6N+1TW025KSaKEXkeB4c1ozYlI+7aduQfGO/7FqZSTc3PiVcNA5KyG1crnHM8kk8zqrhvgpAUrTOwBWAUKfmsp7ZSlropBWhF0TdTooAHNSOftQWVTI1lw85ddL81YLeClU72Lm8J3sfx0FlKp3sfxvqKd7H8Y+4oLoqd6zx+iU7xv8b6JQWUqucdHfRKZ/wCI/wCiUEqVXMfiP+iUzH5OT6KCbKCCpu75KT6Ki7j/AJGT6KBZRZW9b5KT3KLu+Rk+r7VRBCqW6Kxzn/Iv+r7UOf5J3vH2qDG5qoWrKRJ8i73j7VUtl27k/SCDC5gKwvgBW0WS/Jf8QVSyb5H/AIgg46SlvyWCJksT3hh0BGnLZcq6OU/5IfSWNtK5uZz7ZnHYbALNiy6agqmAEPaW336KGObqY5L+z9azy0oPJaUtO5hzM0I5hYuP9OkzrbaZANXH51sMqS0g63Gt1x0VWQck2h5OWbO4W108Fzs06Y5SuWiqA4hxAFtvBbDKpp3K4QTZfxgD7ysjJz8JoPtKkumvbsEcua3O+wWYC40sTzPRcDT1ga8Z378huVzMMzZWaiw5Dr7V0xu3PKaVdK7YD1evMjwWRrgRcaBQ4B9/Hn4KgYWklu25CqNlpsRbZZQbrVjfcfUthrvHZalZsZWutrdWOqx36KQ42VlZsYpBYrG5Z5BfVYSESMLxp7FrOJie2Ru7TcLbcLrXlapWo5Zjg9oe06OFwrDdaeGyZoTETrGdPYVuALcvW2b0sg3RArEWRESC42UtVRsrNUFXixVVkeNLrGgX5InNEBERBVFYjRVQVc24WhVUgka4EXBXIqj23CDoeKYV5o8yw94WE+tmIOU+HguW4axp1xR1DvWGjSeY6LlK+kbIwgtvcWPiF06rppKGcFhIym7D+pdMMpf21LPt+jIoJsoJ6LmqyKtyovbmgtcJcKhcAMxNh1K1J8Xwymv31dC0jkHXP1IN9FxB4koHOyU7Kmc/6uIkfWtqOukmiL20c7X5bhj22N+l0G6i0qabEpLmooo4tRYNlzaLO980Vu9jOu5adAgyHdQqxyMlYJI3BzXC4IVkEOHNUcsh2VCORQUIWOR7I2l8jrAc1lVHDSwNr8+ig1xUFrg8tyx9XaX+ZZZ8LoKuZtVU00b5AAMxbqRyHsWPuY4/Xe4ucPx3nb7Fmp6m7cgBHQnTRT0NoOF8txfe3gpuFwYw/FG44K+CSHzcWFi52dzTvc8z0/MuaKbBQSsNXWU1FH3tVM2MHQX3cegG5PsXGyVWJV+kLXUMB/HcAZnDwGzfn1UVuVuJ0lCQyZ5dM74MMYzPd836ytF5xPEf8YkNHAf8lE68jh/Gfy9g96y0tDT0gPcx2c74b3G73e0nUrYDUGGnpYKWPuqeJrG72HPxPVZsoUgXSw6oIsOigjorkaKqqOJxXAKfEHd8x3dTc3AaH2hcTHwnWufaSeNrOo1JXaiETaybauHYbS4dFkhbcn4TjuVvNssXsCm5TZpnapklZCzO4+wdVoz1j4WuLIXOynLc6DN+tYHzSSHNKTrtcLN5JOo1jhavNK6Zxe8/N0WMi6qLk2WVrbrn7dvSYowBfmszhfSyxtJJuNlkD29VqM1DjlNjsq5i/Qqrzc6clkYwHkhrQxlyNFsMZbldVa25tsswGVWRm1IAtcbKR47KACdVYZnEBoutIaKchtosrIw3fUqcvirpm1xdVhXfOMsbg1x3B2K1fRdWPxGn2OC57KOaZQrpNuCGG1nybfpBWGG1XybfpLm8oTKENuF9G1XxW/ST0bVdG/SXNZfFMoVRw3o2q6M+kp9HVP8AE965nKEyhQcN6NqeZZ71Po2o+Mz3rl8qnKFRxHo2o+Oz3lPRs/x2fWuXyhRl8UHFDDZtzIz609GzfKt+tcrl8UylBxfo2X5VvuUjDZflW+4rk8qjRBx3o2T5Ue5SMNktrKPcuQRBx/o53yo9ykYa75X/AIVvog0Rhx5y/wDCqOwkuN/O5R4ACy5FEHG+iB+VzIcIb+VT+9cklh0Qcb6Ij/Kp/pKDg0R/zmf6S5OwUWQcYcFg+Xn+mrR4TFC7M2aY+BdcLkDooQanmTPjuUeZMH4zluWVSOSDUNGzk5yg0jOrvetsi6qRyQahpGePvVDSM6u963CLKpAUGkaRo6+9UdSjqVvEKhaLKLHHOpR1KxPo2HcLknMusbmDoo04iTD4juy6xGmEbcrNB0XLuZ4LBJCDyWbFl04d8TmG9lLXOIsXW9i3pIt7haskNthosWOmOW1GEMJyFcjSVbmeq5y4y1jqFlZJlOgKzvTbscNQ14096zG7hYbLh6WoA0J+tclHNmtZ3JdMctueU0zEZBcFXjceaoHg6FXAA1C1GKzA6KQVha5ZRsCd1UW30WJ7bK/6lJ1Fiiaa5HJYXjRbL2Futlic26EYqSTuapt/gv8AVP6lyy4WVp5brl6eXvoWScyNfamN+jKfbIg3RBuusZWREUgs1WAuqtVwpRUg2VFlOyxICINAiAiJa6AoI5qdk3QVRSQOShBhmjDmkLgcVoGzsOZu67GddFrVFOHg6JRsE3UE+KgmyoSgsXgLjsRxGeORlFQsa+plBcM3wY283O/UFukrVipGRVU9Y5xdJNlbrs1o2A/Og0W4AKu0uJV1XM87jNlb8wGy3aTBsMpNYqRhd8Z/rH61uM9YZR8yILtsNAAPYrKgVgdNUFmnVWrAMjXcrqmYDmrzvY6nzFwsN7lB1zh6SWnq6zCnvLmwPJZ7F2BcNhVJlxOvrg8OZK8BhBuDpquYBSiVVysoIugoQqEc1ltZVyqDBKwuAIALhtfYeKxtiDXd4fWd1K2i3wVcgU0L97GyPvHuDWjUknZaMuIVdV6mHRd2znPM3/wt3PtNgtosbzaD7VBHRTQ0oaGKKTziRz5pzvLIbu9g5AeAWxZXsOiWHRFVt0UgKUV6QUW12UoU3sVNuiKdb7qFBBF+arZXUadEVVQ9zY25ne7qpke2NuZ23LqtOSQvdmPzBZt03jjtgrZs7ozJHqCcrvipH3c7ZO6DgdA0CxuQdSfm6JLH3osTYFWp3S0hOVgkzNy66G177hcLN3brrTLG0gkrM1o15LUEoijcImvkebEtcdYwN7dQqsqamR4yZGg62fcnTfbX6luZSdJW4LDTkoGhPigDwGmSMsJaHWPQ7LIwW1AW09Ktbe1wszG7HojWgEussrQFZEtS1gBuOavYlArsjLtjotaY2q1pebBZ2sDBYe9SAGizRopWpNM27ERFUEREBERAREQEREBERAREQEREBERBBAKiysiChFkV1FggqitYKLIIRLWRAREQCLqpFlZEFEIUkdFCCvzqCLq9huqoKEKpFlkIuqkIKEXVC1ZCLKCLqDCW+Co4BZiFQhTSxgc1YnMW05qxuao005Ir8lrPj8FyDmrC+MFSwcXNDbULWc7JoSuVfH4LUnpwdQPmWLHSZMEdQQdPcuTpqs2FzvuuILch9ULLG89bLN6bnbsMdQCbaaLajkFtTuuCgm2Bct+CYZQC751rHJnLFyWm5VmuGqwMkBYBm1KyNNtl0c2W5CsCsYIGw3Vs1wERf2jdYpIrat1CyAknVTdBpSNWfDZLZ4T/ALQ/WryRB+rRY9OqwMzQytktsdfYk6uz/HJKWjmoFjYjUHVWC6Vg2RFI3SCwFlIJChQTZQS52lgqFTuoQEREBES3NAREQEI5oiCqgi+hV7BLBBhIuqkK6h2yDA42VFLjdxKi6CzHFrrhbTos9pGDR2/tWmtulkOR1vxdbINeeoEUvcNF3kE6ri34hWSHSQMHRoWZjnPxAvfuSVrButlRsUrZqiXNLK8sbqRfRcZj9S6pliwGhuXSFok1vYch+srbxTEo8GohazppPgN6nqfAKvDWFSQtOJ1t3VNRqM27QeftP5kHMUVLHRUsdLEPVjbb2nqs4ChWCgm9kKgjxUEoB3UIiAdlVCbogq5QpKhZ+wIuqKxNlVKCIigKD86lQbkXKCERQUXQqSSNjFz8w6pLKGNud+QWlJI55zOus5Zabk2mSVzzmd8yx359VBdruE1vouVu3aTS7bXurt3zclQnlZXbbSxVgx1ULiBLEbPbsVpwTVkBY5w9ZgsSRcnT+xXJj1vVdsp7sC5tdLjvtn/tSGUyQPme5ps/YEnK1bMLS1veE6FY46SJ5DrEHqDqsEsZbWhpLmFuzr/Cvt+sJ3j2e+m+yVmZjdu8+CToCszCCbjRaT6lp7qKXIRo+7TfKfDxtyWdlRaXu3h4bf4eXS63M/7Zsbccec35BZrAaBAGtZZuyLrHLexERVBERAREQEREBERAREQEREBERAREQEREBERAREQEREEEX5qtldQRz6IKoiX5ICIiAqkWVkIugolgpIsoQVI6KFe2iqRZBQiyqQshF1UhQUtdUIWQiygi6DER1VHNWUi6oRdRZWFzVic3wWy5qxlqjTVfGCtd8duS3nNWJ7LhSwcZNDm1A1Wq4Fu+65WSOy1Joc22hCxY3jk1myFvNbEFQQQLaeK1HNLTY8kaSNVnTcrnYKkm2q3mTAm1yuuwzi41tZcnDUaArUyS479OVY69tVkaRqtOGTM0EbdFsNeL2K3K52M1zyQaqmYX8FbNfZVFwfqVnNa8a7rErB4ugzQksGQ/B5eCzexa7XkFZWua77FqVmxdSDZQiu0TcqEt0RAREQEREBERAROd0QEREBERBjIO5VHmzCfBZCsNQbM05lBrk9FF0UXHVBNz1WekfaUNOztCte46qzHZXBw5IMU0XdV0Z6mx9qwU0YdM4u+Cy5K5DEGjvGSD4zXe9aExMGG1043DXWVHA0jDj/EL5pfWp4DoORA+0ruIGi6zwXEG08sv4zrA/wBvmXZhqpRKkGyhEFr32UHwUIgKpN1JNlCAoJspVT1Uog6aIiKCrlCk7qFKCHZFBIugg+1ERAWKWYRiw1PRRNMIxlHwlpueSb333WcstOmOO0veSS5xJKxOcdwjnHqjRqbrjvbtIAX3WQC226qBzusjQbXKsioKyRtuPaoLSdVdg5KpUhp2BV2sIKs1o6LLkvoQtxi0YLH2rI4B24udvmVQ3qs0URe7XYbrUZpBSsLTdvqH8W2lwswghblOQepssm2ignot6jnuoJREVQREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREFTuoUkc1HggIiICIiCCLhVV1BCCqgi6lEFTooIurnZVIsgoqkWWQi6qRdQYyOioQsigjmgxEXVCFlI1VXC6ysYC3wVXBZXBVIRprPZfkteSPwW6Qsb2XClg4yaHMPFaRbldY6Ll5I91qTwZhcD1gs2NytQac1sQzEEBxWsbgkbKNR43WK3K5qKouPVJK24qgNtm+tcDFM5g3W9BPcapLos25pkjnDT5ldr7dPYuNiqSCA11hzW2yQkZvrXSZbc7jW3munzLE2TbwV2vvvpotM6Xa/qsjXcwsJFjcfUrBxHsQbbJA4WKutQOWZkn4rirKzYyoiLSCIiAiIgIiICIiAiIgIiIKE8lgqT6g9qy3WGq/cr9Cg1ieai/iqlyi4QXupBKoDyVkGzVG8Ebv4o/OtSZnf4XXQN3s5bFa7LTsHRo+srBSyhlZLE74Mmio4Xg+YBk0BIuP1H9q7MumNc7h/H3xvBEb3XaerT/ay7ix7ZGh7DdrhcHqFKMiKAeSm4QEJsoJ6KEBEUE8gggnVQhRYBQ7ZSqk8lRCIhKgXVee6JfwRRYJ5wz1WEZvzKKioygsYdeZWkXknXqsZZabxx+6lzrnx8VUuUZrnXRRubX06rnt2kSNTtcK4bc3UBquBqoqWszDXQrJGDsjGi1jvyWVrLDbVaiVXKD7FkZGpDb7DRZALclvTG0sbbdXDVDQeiyNHKysjNoxhcbBbbWBoDQqsaGDx5qSb8luTTnbtN/FQiLSCIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiIKncqFJ3UICIiAiIgIiIKkdFCsdlVAUEXUogqqn2K5ChBjIuFVXIVSNVBjI5KqyEKjlKKEeCoQsqo4clGmMt5qjmrKR1VSEVrvjutWSPwW+4LDIy+yzYriqiDN6wGo5dVqG4Nr/AFLl5I1o1EO7gPas2NStYEjbdZopiNAsJBUXI2Wa3K5OF43vqtyGovpfS64VkpGhK2o6jYA6hTemvbm2Sc7LKJi619lxsc1/xrrOyQ2FyFuZMXFyDX3VrgharJLC2yyNkudCtyudjOLhXa73rG16nndVGxHKRodQs4IOoWm1x57LIyQtN73CsqWNhFDXBwuFK0yIiXugIiICIiAiIgIiIMSpOM0TgOl1dQbW1QcVmS4SUd3I5h5FUzIMoPVXYLkAc1hBWxSjNIL7DVBXFZLZWDqB7lqVJLKpzgeh+pMUc41AcdiCR71Ssd+GBvu1p+pUZMVwyLHqIFpDaiPVrvHx8FxWCYxPh85wnFAWFpsCeX7FylHVGCUG+h3U8Q4IzFqUVNMAKiMXY4cx8UoOUDgfnVl1vhrF3zA4fVG0sWjb7nwXYgVBZERBBNlUoUWaCIhQVJKhSTdQoCqfYl0QFgqJwwFjTqdz0UzziMWB1P1LQc++9zqsZZa6jrhjvuoe4nbZVB13UOdqQoDtbX16Lk6yLnKdt0DRoDqoHW26ytAAF0UF+hV4wXKQCbWWVl9AdlYUayx1GyzNBcegVRvZZWst863IxakDorhpHVAFYC61IxaDwWeJlvWI32VY2ZnX5BZluRi0REWmRERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBQVBIIS+iAfaoREBERAREQEREBUV1U7oIREQCLqqsqndBVyqdlkVCORUFFUjkrkaqrhzQY1DlZyhZajGQFCuVWxQUIVHNWVVIRWrIy61ZGeC5BzVryMWbFjiJ4Sw3GxWuRZcpNGCCCFx72FpLSsWNysd7LKySyxkaKuxsVNbalb8E5FityOQu1vsuHjfkItot+nmu2ynppyLJbDfW62Gygi53PVcc143ab9VlbKetwrMtJZtyTH8xb3rIH6dFoRzONtb/MtkSjfdblc7i2muBAudVYFa7HtuLEX6LMHFalZsZmPLTcFbDXBwuFqNcsjSWm7StSs2NhFDXBwuFK0yIiICIiAiIgIiIMSqSl7qpN0GlXs1EwHgf1LUuVyb2h7SxwuDoVx0sToX5XajkeoSA0rfpG+qXHbZccy5K5Jp7uNrOZ1KozVtHBXRNtZrm7FcZNhdUXXsXWAbouQa8jYq4eeqg4puFTENEkJvzI5/WtpkWIwtMNLo3TLmFyOq3MxPNZGPADiTyQdPx2ljw5oxMMPnZlbme02AHPT5l2GjnFTTxzgWztB+dcBxdK51LFA0EumlsPmC5rDoXU1FDA/wCExgB9qmxtkooBupU0CIiaBVO6knkqqAoKEkKFQWKeYRMvzOwVpJGxtzOOi4+WYvcSTusZZabwx2rJIXOuTclY763toUNlG411XGu+k3CgWJva56qQ0EWCu2O1yFIqW9bLMGNIykaKrW23F1mazNZWQQxtvVA06rMxotoEa21rrIBoDcnwW5GbQNuNN1kHjuoaLKzRfdbjACDssjGlxsBuoDeSzxsytvbUrUjNqwAaLBSiLbmIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICKD4KM3VBZQTZQTdQgtcKCoOqIHgiIgIiICIiAiIgIibICqbqyqbIIREQFBGl1KHZBVVIVlB2QUOyqrqtrKDG4KqyO3WNSqg2tuqqx9iqo0qR4opIuoKJ6UcFie2+4Wc6qjh4IrSkYtGpiJu4DZcpKy+y1ZGLFjUcS5oVXArZnjyuNhoVgI8FltRt+azRS5SsTh0UAkclLFjkGS5tCsokHitCOQ203WZsvXYrLTdZKRZ2uq2o57gFxXGd5YaHToszZc1tQrLocuyUGxO42WdpuLg6Li4pjpcLbiluFuZMXFuA221WVjuR1WuyQFZRZbjnY2GuLSCFmDg4XC1Wu1WVjrG425rUZsZkUA31BUrTIiIgIiICIiDWJ5KFLt1CCpCpJG2RuVwusigiyg02U7o5LnVo1usocXEuWYi6oQLq7EtVwSsRLgdCVNz8Y+9Blv1CxzPc2Mkc1BJ+MfeouXaEkoNTzWGomjnkZndCSWdATz9q3BoEAA0AUgXUoAHdWREnQKDopVXIIQoodsoIUEgC5NlK1a57g0NB0cdVm3U21JusFTUGR3q/BGi1wSdLaqrj6ysdBouFu3ok0gi+l9FZjb/tUDUArIwbFFS1g56LIGG6Aaq4Njp0QSG2+DzWRjSLaqGm4F1mAAWozaAWNwsjR0VWbFXvqFtiluV1drTzUBXbvZajNXjbc3OwWZQ0WapW4xbsREVQREQEREBERAREQEREBERAREQEREBERAREQReyXG6jmpdsgE2UZioRAueqXPVEQLnqiIgIiICIiAiIgIiICIiAiIgIoOyE2QSdlRTcqEBERARFBNkEEIpPJQgqRZVI5q7lUqChF1QhZDuqOGqKoVRXKqd1lUIQiHZFVVSOasiEYXNWvKxbTgsUgFipYRx00dwQtFzSDryXKSgWWhUAB2nNYreLW8FFvcpO6jYqNIbcG/JZGvsd1S2yAa2WasbDHmyu13gtZhKytOijTbZJfbktuGW9tVxzCbbraicbX8EX6cpFJzBWyx91xsBJ1utyJxO66SueUbrSCBYq7Xc7rXicXEg8lnC6TtyZWvy89FmBuLgrXbyWWM6kLTNi6INkVQREQEREH/9k=)\n",
        "\n",
        "### Note: Penggunaan Markdown pada Jupyter Notebook Atau Google Colab"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ib2vgDJZCTgd"
      },
      "source": [
        "# Belajar Python\n",
        "## Intro Python\n",
        "### List Pembahasan Python Basic"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8wAqn8wKCYsg"
      },
      "source": [
        "***\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fluLZlkQCad1"
      },
      "source": [
        "1. Basic Type Object\n",
        "    * Numbers\n",
        "    * Strings\n",
        "    * Boolean\n",
        "    * List\n",
        "2. Structure Data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mBbse58HCgAX"
      },
      "source": [
        "### 2. Basic Python - Aturan Penulisan Statement pada Python"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fo7UFKevChtH",
        "outputId": "f49555f9-f5e3-4ec6-9fc1-748bf71cace7"
      },
      "source": [
        "# 1. Penulisan satu statement di dalam Python tidak diakhiri dengan tanda titik-koma.\n",
        "print(\"Halo Dunia!\")\n",
        "print(\"Panjang = 100\")\n",
        "print(\"Lebar = 23\") "
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Halo Dunia!\n",
            "Panjang = 100\n",
            "Lebar = 23\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dYHBhWG-DJPw",
        "outputId": "f6b3496a-aca6-4177-ae57-df12e4956e1c"
      },
      "source": [
        "# 2. Statement pada Pyhton dinyatakan dalam satu baris. Jadi akhir dari sebuah pernyataan adalah baris baru (new line).\n",
        "print(\"luas = panjang * lebar\")"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "luas = panjang * lebar\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vZx_4I5jDzq8",
        "outputId": "8c9f1133-fb04-41ef-d5f1-df492a7c5213"
      },
      "source": [
        "# 3. Jika ada pernyataan yang panjangnya terdiri lebih dari 1 baris, maka dapat dilakukan dengan menggunakan tanda backslash (\\).\n",
        "print(\"volume = panjang * lebar *\\\n",
        "  tinggi\")"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "volume = panjang * lebar *  tinggi\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eZQaHewMEHXL",
        "outputId": "3c3b8456-d00a-4095-e266-f45a49540f60"
      },
      "source": [
        "# 4. Statement yang ada di dalam atau diapit oleh tanda kurung seperti \"[],{},()\" tidak memerlukan tanda \"\".\n",
        "nama_hari = ['Senin','Selasa','Rabu','Kamis','Jumat','Sabtu']\n",
        "print(nama_hari)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Senin', 'Selasa', 'Rabu', 'Kamis', 'Jumat', 'Sabtu']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ehGw-mj2ETW5",
        "outputId": "ed6bf09d-9557-4693-e0fc-3ed096112415"
      },
      "source": [
        "# 5. Python menggunakan tanda indentasi (spasi) sebagai penanda blok. Panjang spasi atau indentasi untuk setiap baris yang ada dalam satu blok kode harus sama. Bila spasi atau indentasi dalam satu grup kode tersebut tidak sama, python akan menamplikan sintaks error.\n",
        "usia = 7\n",
        "if usia >= 7:\n",
        "    print(\"diterima masuk SD\")\n",
        "    print(\"dinyatakan lulus\")\n",
        "else:\n",
        "    print(\"tidak diterima masuk SD\")\n",
        "    print(\"dinyatakan gagal\")"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "diterima masuk SD\n",
            "dinyatakan lulus\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MxcDuT5MEYZd",
        "outputId": "e41c8d58-657f-40b4-e280-416d06efbefa"
      },
      "source": [
        "# 6. Sebaga penanda string, Python menggunakan tanda kutip, baik tunggal ('), maupun ganda(\"). Tanda kutip tiga(\"\"\") digunakan untuk string multibaris.\n",
        "namadepan = 'Alvin'\n",
        "namalengkap = \"Alvin Agusta Wahyono\"\n",
        "alinea = \"\"\"Berikut ini adalah alinea\n",
        "yang terdiri dari beberapa baris.\"\"\"\n",
        "print(namadepan)\n",
        "print(namalengkap)\n",
        "print(alinea)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Alvin\n",
            "Alvin Agusta Wahyono\n",
            "Berikut ini adalah alinea\n",
            "yang terdiri dari beberapa baris.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F7EmQmqDEZ8B",
        "outputId": "fac63753-5695-4d8d-b92c-cc786165d848"
      },
      "source": [
        "# 7. Bahasa Python bersifat case sensitif, yang berarti membedakan huruf besar dan huruf kecil (memiliki nilai yang berbeda).\n",
        "# Contoh statement yang benar\n",
        "luas = 15*3\n",
        "print(luas)\n",
        "\n",
        "# Contoh statement yang salah\n",
        "#luas = 15*3\n",
        "#Print(luas)\n",
        "#PRINT(luas)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "45\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VwMv5TxNEfRN",
        "outputId": "adff5492-334d-42b2-e4ef-0f52b854aaed"
      },
      "source": [
        "# 8. Untuk komentar di awali dengan tanda \"#\" yang artinya tidak diproses sebagai statement code.\n",
        "panjang = 15\n",
        "lebar = 3\n",
        "luas = (panjang*lebar)\n",
        "print(luas)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "45\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T5HvZfG2EiS7"
      },
      "source": [
        "### 3. Python as Calculator (Numbers), Assignment, Comparison, Boolean, and Logic Operator"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xb-zhKdPEmbN",
        "outputId": "2082a2d6-5ec6-4e08-c3f4-90c6069eb7ff"
      },
      "source": [
        "# Contoh sederhana Boolean\n",
        "nilai = 80\n",
        "nilai > 65\n",
        "nilai < 65"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SVfkg3BtEqnA"
      },
      "source": [
        "#### a. Python Working in Strings and List"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lCNBjYVrEu4E",
        "outputId": "684a0cc0-525e-4bbf-8c0e-ad0260edabfe"
      },
      "source": [
        "#String pendek\n",
        "print('pendek')\n",
        "print(\"pendek\")\n",
        "print(\"don't\")\n",
        "\n",
        "#Tanda \\ (Menghilangkan pengaruh \"\")\n",
        "print(\"don\\'t\")\n",
        "print(\"\\\"Siap!\\\" kata orang itu\")\n",
        "\n",
        "#String panjang\n",
        "print('''\n",
        "string\n",
        "panjang\n",
        "''')"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "pendek\n",
            "pendek\n",
            "don't\n",
            "don't\n",
            "\"Siap!\" kata orang itu\n",
            "\n",
            "string\n",
            "panjang\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FLyA3-kSE58N",
        "outputId": "519749f5-c30f-48ee-da86-60611c61e1c6"
      },
      "source": [
        "#Operator +\n",
        "print(\"Py\" + \"thon\")\n",
        "prefiks = \"di\"\n",
        "dasar_1 = \"terima\"\n",
        "dasar_2 = \"tolak\"\n",
        "print(prefiks + dasar_1)\n",
        "print(prefiks, dasar_2)\n",
        "print(\"Py\" \"thon\")"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python\n",
            "diterima\n",
            "di tolak\n",
            "Python\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lD6MgLtRFBjY",
        "outputId": "b31cdf59-aa60-42a7-f57d-90a5fc350b42"
      },
      "source": [
        "#Tanda \\ dan r\n",
        "#Tanda \\ berguna sebagai penginterpretasi karakter spesial sedangkan r membuat string menjadi terbaca sebagai raw strings (apa adanya)\n",
        "print(\"ganti baris \\n ke bawah\")  # \\n turun satu baris\n",
        "#print(\"C:\\user\\folder\") # error\n",
        "print(r\"C:\\user\\folder\") # berhasil"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ganti baris \n",
            " ke bawah\n",
            "C:\\user\\folder\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "3l1pq4y4FTd8",
        "outputId": "e8603a48-6d94-4132-df81-6d72f5aad79f"
      },
      "source": [
        "#Indexed\n",
        "kata_sambutan = \"Hello\"\n",
        "#kata_sambutan[0]#\tindeks ke 0\n",
        "#kata_sambutan[:2]#\tindeks ke 0 sampai 2 – 1\n",
        "#kata_sambutan[1:2]#\tindeks ke 1 sampai 2 – 1\n",
        "#kata_sambutan[1:]#\tindeks ke 1 sampai terakhir\n",
        "#kata_sambutan[-1]#\tindeks ke 1 dari belakang\n",
        "kata_sambutan[-0]#\tindeks ke 0\n",
        "#kata_sambutan[:-3]#\tdari indeks ke 0 sampai -3 – 1"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'H'"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "S0fdLZNEFfcY",
        "outputId": "f02495ad-2e62-4885-def9-e935e07bc8e3"
      },
      "source": [
        "#Metode\n",
        "#kata_sambutan.lower() #huruf kecil\n",
        "kata_sambutan.upper() #huruf besar"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'HELLO'"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xhWGV57mFoeD",
        "outputId": "1cfae73d-86a1-4fca-e434-2cedd5892941"
      },
      "source": [
        "#Fungsi len dan operator in\n",
        "sambutan = kata_sambutan + \", Pak Febri. Ada yang bisa Elen bantu?\"\n",
        "len(sambutan) #panjang karakter len\n",
        "#\"Elen\" in sambutan"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "43"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WtkLWR3dGH9J"
      },
      "source": [
        "#### b. List"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YpWsdFS0GMre",
        "outputId": "eb5c8fe6-6e9a-4585-db8c-0eac1cc0a38f"
      },
      "source": [
        "#Create list\n",
        "akurasi = [0.6,0.7, 0.8, 0.9]\n",
        "kredit = ['macet', 'lancar', 'macet']\n",
        "feature = [1,2,3,4]\n",
        "container_1 = list()\n",
        "container_2 = []\n",
        "type(container_1) # mengecek tipe"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EyH2d4HvGRoG",
        "outputId": "a83eeb24-37b2-45b3-cc47-740f182c01ec"
      },
      "source": [
        "#Concatenating (operator +)\n",
        "akurasi+feature\n",
        "cacah = [1, 3, 5, 7, 9] + [2, 4, 6, 8]\n",
        "dua_list = [akurasi, feature]\n",
        "campur = feature + kredit\n",
        "isinstance(dua_list, str)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "61JRaVY1G4aQ",
        "outputId": "0a09c850-1741-4d68-9e8d-68b119a45274"
      },
      "source": [
        "#Indexed\n",
        "#feature[0]\n",
        "#feature[:3]\n",
        "feature[1:]\n",
        "#dua_list[0][2]"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[2, 3, 4]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9oYkPLHuHdAi"
      },
      "source": [
        "#edited\n",
        "cacah[1] = 3\n",
        "cacah[1:4] = [9,9,9]"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_AILwkdKHnin",
        "outputId": "b7fac4cc-a1a6-48c1-9e98-e5f6618a9a8c"
      },
      "source": [
        "lakes = ['superior', 'erie', 'huron', 'ontario', 'powell']\n",
        "len(lakes)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F5pyFlNgH0tB",
        "outputId": "6e66387b-0397-40cf-af8d-58e54ff9ec6c"
      },
      "source": [
        "numbers = [1, 2, 3, 4, 5]\n",
        "#sum(numbers)\n",
        "#max(numbers)\n",
        "min(numbers)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GFjOrtqaIHEs",
        "outputId": "0c3441ff-750d-4079-c889-e532637738c6"
      },
      "source": [
        "any([1, 1, 0, 0, 1, 0])\n",
        "all([1, 1, 1, 1])\n",
        "lakes_sorted_new = sorted(lakes)\n",
        "lakes_sorted_new"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['erie', 'huron', 'ontario', 'powell', 'superior']"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yVjPPA2lIaaS",
        "outputId": "598045df-7d1d-4e96-d0ee-e06dfd02c0a8"
      },
      "source": [
        "cities = [\"oslo\", \"delhi\", \"washington\", \"london\", \"seattle\", \"paris\", \"washington\"]\n",
        "cities.count('seattle')\n",
        "#cities.index('washington)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n-4ocHFsI3I0",
        "outputId": "da448caa-1f59-4c56-f80f-6fd0188bf973"
      },
      "source": [
        "cities.reverse()\n",
        "cities"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['washington', 'paris', 'seattle', 'london', 'washington', 'delhi', 'oslo']"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "08MzmTDwI88Z",
        "outputId": "d0d581f0-8a6d-430e-bade-68cb0c0b7c7e"
      },
      "source": [
        "cities.append('Ferari')\n",
        "cities"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['brussels',\n",
              " 'delhi',\n",
              " 'london',\n",
              " 'oslo',\n",
              " 'paris',\n",
              " 'seattle',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'DC',\n",
              " 'Ferari']"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y7-4KYkHJFnz",
        "outputId": "ee7b286a-bdf5-47fd-9cc6-130e0af0f77d"
      },
      "source": [
        "cities.sort()\n",
        "cities"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['brussels',\n",
              " 'delhi',\n",
              " 'london',\n",
              " 'oslo',\n",
              " 'paris',\n",
              " 'seattle',\n",
              " 'washington',\n",
              " 'washington']"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SeInfCFBJLi7",
        "outputId": "4a9cad41-3063-4133-f904-655781089385"
      },
      "source": [
        "cities.pop()\n",
        "cities"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['brussels',\n",
              " 'delhi',\n",
              " 'london',\n",
              " 'oslo',\n",
              " 'paris',\n",
              " 'seattle',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'DC']"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qIqHPay6JnJq",
        "outputId": "73aa81f7-0ddf-4321-eec4-3034350fa941"
      },
      "source": [
        "more_cities = [\"brussels\", \"copenhagen\"]\n",
        "cities.extend(more_cities)\n",
        "cities"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['brussels',\n",
              " 'delhi',\n",
              " 'london',\n",
              " 'oslo',\n",
              " 'paris',\n",
              " 'seattle',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'DC',\n",
              " 'brussels',\n",
              " 'copenhagen']"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rpBnAtnOKCxB",
        "outputId": "13727031-8353-4a5c-fc3b-eb881cc38887"
      },
      "source": [
        "cities.remove(\"DC\")\n",
        "cities"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['delhi',\n",
              " 'london',\n",
              " 'oslo',\n",
              " 'paris',\n",
              " 'seattle',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'washington',\n",
              " 'brussels',\n",
              " 'copenhagen']"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X3-IaMzpKLG7"
      },
      "source": [
        "### Thank You"
      ]
    }
  ]
}