24_Pandas_Snowflake_Connector.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "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/luasampaio/data-engineering/blob/main/24_Pandas_Snowflake_Connector.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "*texto em itálico*## **Initial Setup**"
      ],
      "metadata": {
        "id": "pePqyFBlOQDx"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "34TcZl1sNbAu"
      },
      "outputs": [],
      "source": [
        "#requirements:\n",
        "# - Python >= 3.6\n",
        "!pip install \"snowflake-connector-python[pandas]\""
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Snowflake Pandas connector helps you create your analysis by using the most famous pandas dataframe. In the next steps we'll guide you through how to setup your pandas to work with snowflake.\n",
        "\n",
        "We would like to show you an image that refers to the datatype mapping from snowflake to pandas:\n",
        "![Screenshot from 2022-05-16 18-18-06.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABNIAAAKQCAYAAABaT1eOAAAABHNCSVQICAgIfAhkiAAAABl0RVh0U29mdHdhcmUAZ25vbWUtc2NyZWVuc2hvdO8Dvz4AAAAmdEVYdENyZWF0aW9uIFRpbWUAc2VnIDE2IG1haSAyMDIyIDE4OjE4OjEzFagtnwAAIABJREFUeJzs3Xt8k/Xd+P/XbCMxKXcCdGuBDuhBm2qL9KC0ctBiRSo47EQmFu8hCvNGuZmIt4eJ/jY84EAcQ7idnQ5vrTqEIQNEsdIBxbauB6VVWuxBaqF0C5B8ISEY4uf3x5W2aUlKCgVP7+fjES3Ndfhc1+eQXO9+Dj9SSimEEEIIIYQQQgghhBDduuCbToAQQgghhBBCCCGEEN8FEkgTQgghhBBCCCGEECIIEkgTQgghhBBCCCGEECIIocFsNHHixHOdDiGEEEIIIYQQQgghvtV+JIsNCCGEEEIIIYQQQghxejK0UwghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIIR+0wn43nG1sGPdGt4qrqH5mBudLpyseYuZndjC2scWkt8IJObylwczMffWOSvzmL6sFAcmsh9+ltmX9taBxXePmx3L/4vnyoCI8Sx+ZirxId90moQ4B8pWMXV5BW7CyV64mNmXfNMJEkIIIYQQQvwQSCCtVzkpf3Upz+2wt//G7bFzxOX+BtMkhBBCCCGEEEIIIXrDGQbSnDSUFbHjo93U7Guh+bATh8sNITp0BgMR4QOJuXg4GWNHkz7U0Lsp/jZzVlHwkTeINmgMD869iaT+wAW6bzRZ3yw3DTs2UXx4KFfflELU+T5962buf3A9DZ7uN9MZTPSPGELS5SlkZY0h3nR+kie8TpNPOp2BC00moiIHEhOfREZGOkkR575e2T4rZPMeN5arx5Mafs5P11mXe2LOnMeLM5MI9qpbN/+Ou99s0v4REs7kRxczI+6cpPSbMSidqTcN5ARGLOc7b4QQQgghhBA/WD0OpLkPlPLiinwKmp2nvulx4z5qp/monebGGnZs3UTM+BksvD2l94Yxfpv9+wDN3s5n8ZkTSY+SaAyeeras2UyBM4XYG1OI+pYOM3Q77bQ2VtHaWEXBu1sZO2MO944aGHTQQpxbbrcTt9VJrbWF2uoKtqx7nai0Scy4fSKp/c/ZWdn9/hrWlhnITvgGAmld2MpKKL8tiXR9MFu3UFDUdK6T9M0alMKUm1O+6VQIIYQQQgghfmB6Fkg7WsGLS/IosALoiEoeTVbGcCw/HYjZoKPP104O/6uF2uoSCj6ooMHppGFrHov6LGDx1Njvf1DC7aZtEGeYSYJoALTW03CMb8WyFuYrc3koe8ipb3zl5Ii1id1lJeyobMHhamFH3nIuDHuMey7/AfWo/Jbwl09fOewcsbbQULubksp6Wl1umsvW80Ttbqb8eh65l5yDfPI00fDFt2FYtg6dzo37aAUF5U7SRwVxrY072dkC6HTofNolIYQQQgghhBBnp0eBtOZ/bPIG0Qwk5T7Mwglde+yYMIcPJObSFLLHlfLcojx2HHbT8O56CsYtIPsHNPzmex80DJJjXx1fevhWBNIwDyE+LjbAm0mkj53I1I/yeGhVKa0eKwVvFTL58onnfzjqD103+TT22onMcDZR8OZqVhc24Thaz9pnV9H/8QVkD+rldNjrqTnSy8c8EyEmLPFQVW1l945SbKNOt1CJm6rtpbR6wBw7hD719bSep6QKIYQQQgghxPddDwJpThpqW7Qf+yYx+drTDHsLH8nsqeXUrmnBPMjEV4fdEN62R8cKlubMefxlZhLu5lLWrN/GztomWo+50fUxETHMwtUTcpicHB7wXG5rDQXvbWP77nqa/23H4dbmu4qIiiXpijFMvjYJ36mUbFufZvar9bhDYpm97GGy/QwLq81/iIfetQIQn7uYxRP8RAD3rWfu45tp9hgYPSGG0nerO/X6KFn1X+SsAtCRPu+PPJjW3c3ycrVQ8sE2tlfUUNNixeF0475Ah7n/QGIvTSV74nhSz2heKDe1655m4dtNuDEQP3UBi24c0vmeHq2nYMs2duyup+GAteM+Dosl9cpx3HSNBXNPhmW2r6jXloQKnplxl/bz0BxWPNE5QNXTfDxXzFdOZUphBSur3dC8m3LrRKK6Zv+Z5lPb6qohscxY9jCTTXaq3n+bt4p203DAjgMdxv4DsSSP4bafZRLT138a3QcqWPP2e5R81qStDNuprgTTE9JJQ/F7bNlVRc2XVlrtTtzoMJrCiYqxcPW1k8hODHwc295C3i4op6qhiS8PO3F/7c2rgd68uiaJiKCGH54hwxCyZj5MzI+X8tiaehzOGv7yylZSHh5PhN/07mTztlIq6lr48rAdd3vZtpA6ahy3jIrF6Fu2jxby2Nx8qtrna7Oz5em72AIQYuGeFQvI8skbt7WKgvd2UlzdRIPVjsPlRqc3aHPupY1h8viRRJ1NhzmPm6jLR3Jkz1aaa3eyvTWTyf4utI2rhh1ldsDA8EuHUFtf3+3hzzT97l3LyX2hCndILDOWPsxkQxM7/r6Jd8pqaLA6tToREcvwq8Zx24SUU+rv2e4feNXO3vp8sVP7wSbe2l5FTbMVx9c6jOFDSM24nlsmphBFKU/MyaPcDfG3P8vi8dILWQghhBBCiB+CHgTS3Dg83rCIzkBYED2MjKPm8MIof+/o0HmfXBwuN7bqNSxavpUGl8/ZnHaaPysl/7MqamY+xqOZpwazWovzeCKvtH1eMgCdzrvv3gqa91ZQUDiSe+fPYqz3wdOcOJyfhtTT4Glid52b7Cu7PkK1UFVrbf9XQ209jgnhGLtsZautodkD6GJJHmbmc5OJE187sR11e2+RCaNOu9Z+uiAiQAd28sySVyixdvm9x42ttYny1ibKi0rInruA2UEFSzq07shj8dtNuNERNX4OC7sE0RyfrWfR85upPdrxu/b7+FkFzZ9V8E5hJg8+kEtqsKfWGelvMnHshB2HC0CH0WTQzttX1+n8Z5KP546JmOhwqG4Bj5XWw4Bv0TubfLrgQu8PbtzOFgpeXcrKMrvPBm4crU2Uv5vP7t0HWPh4LkldAhiOvWt4bEnnuoK7o66U3TyHLHQQaDCfq4kNy5eyurrrHIduHIdbqD3cQm1ZKdtvmsfCm2O7lHsnVWuW8szGJhxd9z5qp/loW16NYf4jvyT9nMYVdMTcOIvczxbyYrUb92fb2LA3k9mX+JYsJ1VvLuWZzX7S621fmj8rZXvxVBbNH09U+64G+vUzYXY6sTm99bmvCeMFgM7AhT7HsX30Cgtf2Nmp7AK4XU5a99XQuq+Ggu3l3PebOYw9mx65Uamkhm+lubWJgqImJt/sZ4iyl2P3TortQN8kMuKg1gMECIKfTfp1fdpumJNj/6pi9aur2OB7II8bW3MNO9bUUF4xkYUP5hCv7739A+uFzxePlYLnn+5cP0PcOFrr2fH2Koorx7NwlpmvvtbeujCYNl4IIYQQQgjxvdCDQJqJqAgTVNvhcBUFu53EJ59pNwtd+8Oo+1A5f8qr4HDceO67eRypUSYu/NpOQ9lmXnx1Jw0uJ+Vvrac8YxapPg9R7ro1HcGX8CRyc3PIunwIZh1wtImSD9az+u0qWg+U8vyKcKIezyFGB0RYSOoHDVY3jbVNcGWXIWRH69jdDJjCMTut2D6vocEzkqROD6Juamq9E3lHJ5AyajzjRgF1a7j7ia20eiB1xmIezAj24aqFtS+8rgVndOGkT80lN8NClEkHLjsNle+x+tWtVB1tYUveGoYvnUV6kLfeUZ3PE6srsAERGTNYdLulc3DkwFaeWb6ZWifoBqWQe2sOWcMHYgwB99EWdv9jPXnrK2jdV8gzf/wxyx4ZH9yCAZf/khee9+ndp0vi3uVzSO+y7xnn43mh48JOAeOzzKeQtiG/Tur/nkd5tYGxuTO4JcNChAEcrTUUrFlNfqUd94FCVhdez7MTfR7wXTXk/683IKAbyNjcGdwxNhazDtyH69m+OZ/Vb69mQ3igGbHc1K5b5Q2i6YjJvI0ZE1OxRBjQeZy01pez4f9eZ8s+J7Ub88hPWtQ5MLV3PSu9QbSI5Bxm3Tya4VEmdCHgtjexu/g9Vq8rpfnATp5fbSFp3shTAtC9K5ysCemsqd6JDSvFpU3MvqSjPjvK8lnmDaIZLxnP7GnjSI0OxxjixnGgnh1vr+YvxVZs1Wt4bnMSz940UNux70jue25kRw9CTGTd+yyzL+1y+sM7eT7PG4Tqn0Tu7TlkJQ7BrPfejx3reX5dFTZrBc+/VMjwB083JDMQN26GkJUWzobNVpqLdlJ7Uy7xfuuhk/KiKhyAOTmdpIt2cyLQYc86/d6y4XFS8eZqGuxDyJ6Zww0psUT0cXO4pYotb65hw2d2HHWbeW7dcFbk+s6Vebb7B3L2ny+t7+fxojeIZrxkPPfeMYn0KAM4rZQXriFv3VaW/V8sYd7tL/yWLqIihBBCCCGE6H09mrkqKXO0N4hhpWDF73hiTSm1h89wGuu2EN7eUqoGTWXxgqmMjQvHqNehM4QTP/aX3DfR2+viaA3lDb472ylYV6g9AOpjmfHAPKakeYMvAH2HkH7TPB69Wet55d63ldeLvT0LQoaQdKkW3Wj9vIbmLsly19bQ4AZdzEiyooBjdexu6bKRp57dddp1xyQlnf2KpI07KWjSjhdx7SwenJCkBWcA9CZiMqby4O0pWlDiaAUFlX5WTPXnQCHPrNLukzFxKo/OGtklrU52vLWJKifQfyTzH5nD5OSB7cPcdH0HknrjHH57exJGwL13E28Fe+6gnEU+njN2Ghq93c104UT82Oet3sonj5WSj5xkzXuY+7zH0Ol0mKOSmHJ3LuneYYMNu6uw+ezm+Oi99oU+4m+ex33XxrbfK13/WLJuX8B9Y6E50IRY7hoKdnmvLXoS980cQ1KEt5dgiIGIS8Yw+9c5xOu0NO7YXtNp94aPq7S5tgwpzJgzkdShWhANQGcaQuqEWSy6zYIuRAdf1lDj4pzTXZrEcG+w0vZ5jc9cYE7Kd2gBZPQWZvy3t30JAdBhHGQh+1dzmOwdX9xQtJMGDz3SWlxEuQvAwNgZc7Sy6w3G6ExDSL1xDvPHat3y3HtK2N61F2NPeHTEjB5JTAhgraCgOkC7e7jU+144GVdbMJ48h+kPwRuwstPQpCP73gXMztQCyzq9gYjokcy4bxbZ3l6krTveo9zZi/t352w+Xzz1bCmo1/p09h/JffdP1YJoAIZwUifOYfGdKbC3XuuVLIQQQgghhPhB6dmqnUNz+J87rTz+UimtbivlG/Mo3wjGiFgs8bEkxcdhibcQH9GDnmoh4WTdnEmEn7/oR10aS8S6Jlqx02x1At7jHi5l+x7tQdJ85SRuCDDJeNS115P69zxKXG52f7Qbx9gxGNFhSYxFt6MKd3MdNUchyme+o4baehxATHw6w/9dxNrGFmpr7RDlM06tZQ9Vdi3tSYkDg7/WQKIm8dsn0rH9Pye6wf4nWTdemkBMSAVVHjfNX1qBwEO7ALBXsHJZPlVHQTd0PAvn+g5da9umnIJPtCfTmPE5AYfiRYy9nrFvV7HlsJPyj2pwp6X0zmIKZ5WP54atbA1rvWnSXZxKhu896cV80iVOJDfRTz0xxJI6FEqqgX8d0CaMDwFwU/VJjfZwr7Nwg5+hzmAgdeIYYnas9x8U0lnIfXwR2XY7DsMQ/4sohCeRFrGG2mZwHGihlaT2eccczrah3cb2AFpX5sx55I/VBXy/1+kG8tMfA/uAw1b+5cHblhjImLGImBw7R9wGLP7KdsgQhsebWNtsh8MtNLvRAlVBisicxYpEO46jYI73VyO8bU1hBW5PC8376TxMuKeixjA2djMNe+0U76pixuUpp9SD1uISqtzAoBSyYnVQe37Sr4u/nqmX+jmG3sINVw9hy5omcNZQ/rmb9MtP3e5s9w/oTD5fmndT7g0aRo26nlQ/1dQ8KoeJ71WQ33ia87sOsjZ/Ky9+ehRzwpU8etsVDD+33TSFEEIIIYQQ51jPAmlAxKhZrIhOZcPf32PzR/XY3OBorae8tZ7yHVsB0PUfwvDEJNIzxnB1YuCFAgAISyA1OtB7Zq0HiQe+cnY86Ljr6ryBAh2xiZbAxzfEYhkCJXvB/UUDDZ4xJIWA8dLhWHRVVLnrqW1wk9X+YNY2P5qJ+IsHEmMegu6DKhpq63Ff2xE8stXW0+oBTAkkBUp7T+gMREQN8TtRese1GLQ5mjyA+zS9AF1NrP1DHgWtQMRI5j8wlXh/k4V/rvW+0663myf8kFgsMTq2HHbjaKjjS09KjwIOgZxtPvbY0QM07PNzFrebI4ebqKnYyZaSJhweQDeEybeO7tyDrxfzKSZxeIBgoIGwvt45zk6c5Ku2X3taqG+bP2pQHDGBYtXhFpLCocFvrzQd5oiBmCO6C/4aMLYd2+3uNNPaT386EB123PYSXs+3EHHrSKJOmbPqPAbRADBgbLuRJ77qNBearn84Uf3Du1111djXANjhazdfuYGeLJJgCCdqaPeRMZ3BiBGw4eYrt5uzW883nKtHW8jfW4OjcifFR1M6LXoALews1hYWiMkYc/o62ovp/2miJWDP3KjYoZhpwoaThmY7XH7qOc92/4DO4PPF0dykte8YiLk4UF0ZyJgrhpDf2BT43K5mnl+Sz8KaUK5ICmPvjnf4WdNR3npoHFdIME0IIYQQQojvrB4H0kCbS2vK3SlMudNOw2e7qdpTQ1VtPTX7tNUe3YebKN/RRPmOzeTHZXLHrKmMHRTgAdL8H/QL9MB3oc7vY9vhf1u1B/wQE1E/7u7B1ETEAG9Q4piN1hNok7ebLAwfBFX7nNTUtsDlbUN8vPOj6WMZPgSMpjh+GlJFw+d7aPCkeOckclPzWRNuQBefxPBeDBq4D9dTXKythth62InD5e4IpOCk1RvVCDjnEcDXVnbkLSe/zg19LcyePytgT7PDVqs38GBnyyLvqoSnY7fyLyAmmG1P46zzsYdsxa9wf3EQG/aNZcqv5pAb7T9NZ59POvr1D3QB2jDPtsUCOo5r5V+HvVv0Dw8czAsJJ2IAEGh4J4DLStVHpRR/VqetkHrCzVftPdjcHAuwr3lUDjcULGVDs5uGD/KYu2s98cOTSEscTkqShZjwXumn2ENuvmobvniBvzCPk+bKUrZ/Ukdjq5UjR50+1wpu+9mMt9TYGiso/mcVu5v+zZH/58Tt9ikPLnv78NyvAuzfE+aRY0h9s4YSZw07iu1k+a4U2biT7c2ALpaxo4PvKXv26dfxk4huglsDwukfAjYPOA7bObVb29nu340z+Hw5ctje3i79pJt2KWLIUIycupCF5iQ7Vv+VhTV6bp/zS/44ysy//vk3bvzjTm5ZouPvvxnDcFmfQAghhBBCiO+kMwqktdOZiLl8DDGXj2EygMdJc30NVVXlFBdVUGV1Y6sr5LmnrPC7eYzt7+cYF1zo55fdczja+skYCOs2oKLDaPD2OMGprR5pABhIUkI47LPSXF+PjSGY6ZgfjYsTsOgBnYX4ftBwpJ4aK8RHAJ4mdjdok7VbEoOZ+DoYbhreXcXv11S1B2HO9Di165dTsNc7j5jLyeETgXuROBxnMN+Zx9tzpxcCiGefj71HZzARMWgIlpQxZF+TQkxff1v1Vj7puLCnBcft1nrKAej9BwA0Box9Ah/GUb2eRS9spvZMpprTxzLjkQX0ezWftz5qwuGyUvtRIbUfFZIPGAdZyMgYQ/b4kYF7zPU2j50jbdfS19Q++TsAhyt4cdlqtuzrzXn9fLhbKMhbzovF1kBrpPY+QwpZyQZKdjmpKiqiefxEb487N7VFFTR7QJeQztXBxJp6Lf0GwgzdFGi9ob335TGXv7w42/27cQafL18dbzuHgbDu6qk3SOfwN4zaY2XH3mPoR/yMJaO0vnY/ueLnbJztYuzKD/nzxxn88Yqz+/gVQgghhBBCfDN695t8iIGoS1KIuiSF7JvslL+5nGfebcJtr+Ivb1eRMTOplwJPPfB1x4++j1QxiQkY392J44s91LgySddDwx5tfrSoS2K1YUYhQxgeo2PLRy1U1TqZHGGA1hpqj2jvpV4aoKtXDznKVrMo3zuxfH8Lk2+6nrFJsfy0n6FjmJynlGdm5VHS7ROvk4a9TtAZMIY4cbiaWPvCetJ+O5V4P0PW2u9HyECm/PYxck+ZRM2Pb2p1ugD52BPm8Q/zl9v9z20WjN7Lp3PJzVdfB3jLWshzK7QVWtGFkzoxh8kjLcREmDC2Z72dLU/fz4ufBThG31gmz3mMG3KbKC8toXh3Dbtrm7C5wHGghoJ1NRQU7CT31/OYEnceavuxJhraeupFDuxYUdbTwto/5LFlnxZIjho1idysFCyDwjH7BG0a1i3k/re7riYSDDe1a5azsljr0WaMG0PuzzJJiRtIRF+f665+hTue2dlp0Yizo2P42JFE7CqktamE7fsmkjsUbSGJUitgIHV010VFzn36g83pQMN+z3b/3uWTmjM9X0g4Iy8J49mdO3hgVzR/TD/GEw/k8/5/eHOmR8v8CCGEEEIIIb5Nzt3X+RATqbfmcoN3DJqtdg9f9tIKZ8a2p36Pk2PddlBw42jrwXCBAaNPMEl3sYUkPeBsYncT+M6PZolvmyBe5/3ZTU2ttoqbo+06IrS5qM6elR1bSttXF5z9yAJmZCYRE27o/NDoJrheI31jmbJgEc/PTNEepg9s5bnXq/wOPwprmwzL48Th0GkPjad79aLeyMfzp5fzqad0uvbVVHG5uzmHE8dx/+80bNvmXfXQQPqsh3n05pEkRfkG0aDTUMnukmMaQvr4qdy34DH+8sIfWfHwLHJHDdHSaK8hf+XrVJ2HVTttFeXUeG/GTxMSOuad27OVzY1tK6zOY/HdE0mPG9gpiAZoc9mdCWcFb//DOyx06ER+98gvyU4e0jkI5T1+b5cHXfwY0gcBnhZ27tDmRHN8UkKxHeibxNX+ZsfvqlfTrw1vDsjlbG9/+vTxl7az3b93XXhR2z1w4+6uDB/9fxwLWH5CuW7GL3j0YhevrnqF/952FHO/k+yuOUhr/wSmXHaSvVV7eL/Kil1W/hRCCCGEEOI7JfhAmstO894KCj7Qhg8FpW2+JgDH8QBzyfRc/4i2BQzsNLd2F4Gx0/pv7wOaKZwI3yFvBgvDYwCs1H5uhaM17D4A6IeQ5DMBmPniWKJCwFG3hy89bqr2aPOjmRMTemXCfTxN1DRrP+oSxjA20ORXrQdoDdTTqJ2BsbMWkHupCXPGDH41Susx11q4mhfLTh3LZ44I9wYe7DQ3n8lYv7PTK/l4vvRqPp0JE/28HSDdh62Bp0DzWGn2+6aThiZvz6u+qWRdGaA3pbslwP7dCDEQdelIptz9GM/e5l00wlpOwZ5z3C3PXc/b77atZBrL2JEdke3Wxn1a0DMknPSrLQEWdnDS3HKGc6QdqKPRG2SJHz2GmABdqmwtB3qt3WsXMoSsDC3Y31pRQq3HSfmuChyAOW0MqcEEmns1/W5ard20H4esHPZ+ZpgH+Pvrw9nu37v6mUxaGfZYae2mK15r84Hue+rpo7j/gVwWWVy8+tIaFn56koj+YegPV/Hf85cz8sk1TH1yJSOf2snu8xB0FkIIIYQQQvSOoANptW8/zdxFq1i5ejX5JUEGXdwtNBz0/tzdpM89pLs4AYsOwE1NVU3gHhNH91C1T/vRGBPXJfBlIilRexj9snYPtto6bX60qITOK1xGJWAxAK311B5pouZzbXW34YlnPkSwk6/R5hwDLuxrCPDA76ZqR6lPADPQFesw9ml7IjaQ/p8zyI4AsLPj5dXsONxl8ziL9z5CTWVFNw+Fbho+2kl5o71Xe9f0Tj6eJ72aT2cgZCAxbQt2HKij5miA7Zp2U3XMf9raFxE1XES/ALs7KndqPZv8HeFoC7Wf1NDczUN/RNpwb/44OWI7l4E0J+X5eWw4oP3LnDGJLJ8Yi7stszDRz+98d8DhUgqqO9LYo9R+dbJ9MYmwvgGCkp4WCorqe3LUoEWNTideBxyponhPFcWfuYFwrh7bzeq3vno5/Q2f1QcMuDXXe4OamIgZ4v9cZ7t/bzIOCkebztNJQ2OgYb9WSv4ZxL0xRnHvI/MofWgq//ebeyhd9nPu+vFJ9h12YbpsHGtmJWCq2cbUxdskmCaEEEIIIcR3RNCBtPixbb0WnJTkr2Lt3tNM+uyxU/5mPtu9wZuo4aneSbF7gSmFsZdqj4uOj97jnQP+NnJTu3kr5W7Q5g1KOeUBMyrBQkQIuPc1UFCtPchFxFs6r4ioiyU+RqctMlC6m5ojgD6W1Phemv/pgo6eRo4DLX57Gjk+WcOLO+ztQwjdjiAf+Q1J3DF7vDZv1NEqXswrpNW3N2HfVMZerkUN3dXvkV/pP4LibtzEyhde4YnHHmLhu2e6yqGbY12XseylfDwvzmU+BcXA8MQh2rW7a9jyD38P+FYK1hd1zmOf/fuZvHfO3kKzv+p7uJQX36jiq7YeTS5Hx0Tq9kIWzVvIQ0uX8/z7gecUcx9o8Z7fQET/c5RTzia2rHqaZz7wlsXwkdx7a1Kn4Ga//h29ipr3+8kHdwtb8tZT016anHwVsElz4zjR5RhmbSVJgNYv/d0PN7Vv5/F2a9vCEG7czl4sD+EjybpUBx4r5Ru3UeUEokYyNjrI/Xs5/e7q97zz0XV9o56CoibtZ9NwUi8+N/v3qqHDSfIGXxs+3Kn9gaUL20dreHtvkMcL0XPJiARuTApH/2klb/1bzxWWcPRHjmO+Ziob5yRh+nwn/7n68+5XZBZCCCGEEEJ8KwQ/tHPQeO7JidUeVo/Wk//UQ8xdls/aD0op/6yehn1NNDTWU1VZypZ1r/DYgw/xxNYW3IBuUCazJw05zQl6wkTWLZO0wJ67ntVLlrO2sqX9od99uJ4dby5l8bvaA6IxMYfbkv081A9NICkMsO+moFKbqDs+fmCXjQxY4gYCbmoKSmnwgC5mOMN7a6oe30UL6t4gRKtQAAAgAElEQVQjb3N95+tYt5z7lxdx4XW3cYM3aY663dqDcxB0l+Rw341aAMZRvYbn3vV9aDYw9pZJ2lxxWClYtZTn3q2i+aj3yfFoC1UfvMLCJZu1h8nwdG4Z27OhVWZz23jEenZsraHVbqe12YrNA72Wj+fDOc6nYJgzrifDBOCmYf1ynthYQcNhJ26nnda6UtYuW8qL1Sbio/3dIx1Jl3t7K7mqeP3VnTS0pc1lpaown8cey6M8Moc7MrzXaa2hrLltSO1IbrjSBLipXbeUx/ILKd9npy1W6La3ULtrPYvyvBPTh49k7JkGm21N1NbVd359VkXJrq3k5y3l7nm/48VirW2hfxKz759BapdeZ8ZLh3sD/3a2v/k6JW3LrHqcNH+ylZWLnubFLy3Mvtm7AIqnhfJPugSJzSbCvL3rdu8ootZqx9baQutRICKpfY7E5sJ88j9p663pxrGvgrWrfsfCjU7G3j6pvQdlzSdVvbjogImMUVrwsNnbmyvmqjHB99bs1fQbiPqxlTXLlpNf1tRRL1qrWLtiVXuvwZisTFL9Fomz3b+X6SxktbVzzVv5/aqtVFm95cdlperdPBbmVRCWnETEGfaOjRyTS82y8VwRAj8ZdQMPJIWyb28jtTJfmhBCCCGEEN96PVi1U0fMjQv4nWE1z71ZSrPLSXNlIfmVhd3uE3H5JO6ZNZGk3p4jeuhEFs6xsvBPO2m2VpG/rIp8QKejYwgbYLxkIg/OycTvlFa6WJIu1lFQZqf1sPffflYajLpkKGaasFm1B+2YREsQq+IFS0dqzk2kfvIK5XY75W8+zfR1OowhbhzeoT4RGbP4n5tT+JfzbTY026G1kMfuLcI4dBKLH594mp5+OmJumsHU6qfJr3NTuy6P/EsfJrct2DJoPA/Os7FoxVZqnS3syF/Ojny0hQV8H+rCk5j969sIZh5zXxGXDydmXT0NbidV65Zy9zogxMI9KxaQ1Zfeycfz4lznUxD6pnDHjDHUrtpJq9tK+ZpVlK/x3cBA/K3zuOXfq3ii0Q6ezl1pjOk55G6rZ/VeJ63Fr3D/R69j7AMOb08jXVQmD949HkttHfmFFTg8Tax9/L/Z0MfC7KXzyPrPWUxpXcXaOjtV7+ZT9W6+/3SaLOTeM9UboO0520f5PPTR6bbSEZE2iXtmTCTJ32i/iEzuGL+ThZtbcDfv5JkFO9EZdOD0LtRgiGXK/TPICi9lx5oKqtxuql59iKlvGcj41bPcl6aDqFRSwreypRVsZfk8VJYP6Eif90ceTBvCLbljKFm+k1ZnPWuX3s9avQGdx6mV2xATqbfN445ROjZsXU/tPnB8lMfsWflEXDOPFblnPzTcmDyGDFMFBXZAF0vWqB4EuUN6M/06km7OxbImj7XLf8da/NTfxKncNzHQH1POdv/epiP+ZzOY/MlyNjS7aS1bw2Nlazolypw4lYU5Dp7bXdWjI/cZcRULLvucB15+hf/W/5I/jjKzb+ffWVJ1kqFjoon/plZFFkIIIYQQQgStB4E0AB0x185iRcYkyot2UlJdT82XVo7YvT1TQnToDAYiIgYSEzec1KtGMjb63M1pY077JcuGjaTgvW1s311P87+1dOj6hvPTobGkjL6em0YNCTCfFbTNdaYr887PFRXXPqSnkxgLFv1OSlxASDhJiV17rZ2l8DE8+v+ZWbt2E9urm2g95uarEBNRl1pIH9txDRE3zyLXupq3P7PyVYiBiJ+GExbM8UOGMGVWDrt/u4YqZxNrX1hP2m+nEu8NdBgTp7J4aSoFW7axY3c9DQes2n00mOg/aAgpaWO44doUos4kMBI1nvvutPHi+lJqrE7oY6J/1BD6+cQrzz4fz5NznU9BMKf9kmcXxvDW3wspqW2h9agbncFExDALV0/IYXJyOF+uMQB2cJ/kK9+dQ4Yw+YGH6ff39bzzUQ0NVicOtwHz0FjSRo5jynUpROiBK3O5d4Kd1TvqaXXr6D9ooJZfegu5jy4ibdc2Cj6qouZLK612p9brtI+JiKghJI3wlpVzsLiizmCif8RA4uOHkzF6NOlDuzuJjvhbH2ZxxHpeL6yiptmK4wQYw4cw/PJ0Jv8sk6T+OmA0s2c08fy6EmrtcKFpID81ewunLpY75ubiWL2J4kY77gsMmH88hFjv+8bkX7L4fwaSv3EnZQ1WbCecEBZO/MUpZE28nqw4re2bfOdU6l/cRHmLVv6jInvp5ugtZI0Mp2CrFd2loxnbv2e792r6zSnc87uHif/7JgrKtLKFToc5Ipa00deTOyEJc3dBorPdv7cZLMx4/GFi/r6pva640RERbSFl9PVMvdaCuWV9z48bEsldD+TiWpzPwlUvUbMtjKaag2AZx5oZF/NNrKMihBBCCCGE6JkfKaXUN50IIYQQ3zGVeUxfVooDE9kPP8vsS8/z/t+0vfncvaiQ1vZeij0Yd+o6yKv5W3m15jiRl13Jo7cmc8kZ9uAUQgghhBBCnF897JEmhBBC/AC47LQ6dUT099+D0PZFk7boSEg4UZE9nLxNH8ntd/4nt591IoUQQgghhBDnmwTShBBCiHZ2CpYuZOUnTug/kkefnnXq3JDuet7+oF77OdxCWi+P9hdCCCGEEEJ8ewW/aqcQQgjxvWci7UrvCtWHS3luST4Fe63aaqIeJ611paxevNy7mqiBpOzrZZEAIYQQQgghfkCkR5oQQgjhwzx2Bvc1LOWZD1pw1BWyclEhK0/ZSkfUtbOYf20PVksVQgghhBBCfOdJIE0IIYToxETqjMdYkVbIhg/KqWpo8a5Qq8NoCicqxsLV115PVmI4PZwdTQghhBBCCPEdJ6t2CiGEEEIIIYQQQggRBJkjTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIEggTQghhBBCCCGEEEKIIISe7xMqpc73KYUQQgghhPhB+dGPfvRNJ0EIIYT4XpIeaUIIIYQQQgghhBBCBKHXeqRJTzMhhBBCCCG+HYL9bi4914QQQoie6ZUeaRJEE0IIIYQQ4rtHvscLIYQQPdPjHmnyYSuEEEIIIcT3h7/v99JTTQghhPDvtIE0CZwJIYQQQgjxw9L1GUACa0IIIYTGbyBNgmdCCCGEEEKINr7PBxJUE0II8UPWaY40pZTfINqWX/Xnggsu6P71H9P520lg/XQMF6byZPX5uoTgbJsziAsuWUDxyW42+mIlWQYDk/5iO6tzud6YgsEwimdrzuowvX6s3rZtfiwXxNzLtu7u6bfdt7S8nm/t5azuPJ3Q+g6PXh9Lf8MF9J/8EgfP02mD46Jx/ZPcNTGV2J8YMFx4AYafDOKysVNY8JdKzq516E2N/G3OKGL/w4DhJ3fxjquSR4dfQP873+nRUYJqG3tR44osDIZJvGQ9P+cTp9o2Z9Cpn+EXGuh/ySimzH+JyvNZyE9u494hFxA7v/g8nvRbdH4hvqMCPTMIIYQQPwQXwOk/DDPmrqXgvQLvaxNLc8wQNo4nNhR0/H7d/YzrtTVAA3NtnM6gsc/SeO5PJb6HiudfxmX/4/vAJF8CAfRXzGHFyvu5IfL8nO/gG8tYVqjn53/axa7lN3OeThuUxv+dQuovVrJn6EyW/PUDdlWU80H+UmbGNfLyr65lypI933QSNR+/xJN/riTy7rXs2vYbrmprf7+nRfrUuvvtONb54tqY27uffWE3sOi9Ago+8L42v8aSO4bR+Nosrv3Zk1S6eutE31PWl5j0k0m83gtBx17PWyHOIwmoCSGE+CEKDebDz5w4jnGJPr/YpIfQSCzZ485J8Ky7NO0prsRGMih1Zs+LSnH6Sz67LwUdKQvmXOfvWOdMUPf02+ALPvykEVL9lbHvyjWcI7GZzIyF83UfjtiO4NKP4IYp6Vj036Lh5Cc/5qW8d3Bl57Fp5UzMbb+/bATpWeMYeHIiz/5zG3vcFizn4Q8H3Tpiw8ZAsrOzGXEZcPLj9rfO6H6e73rco/N1V3d7qjePdf7sKf4YGyln/tnXVaiJhGsyyfQpx5lZOUyMtHPpr1aysnA+eRP0vXGm7vlczDeSH2d4fldlMRUuuK0X6k2v5634Qfi2Da1sqz/ftnQJIYQQ58IFp9/kDIQC/97Gs7mpxPY3YPiPQaT+4km2WTv+cqWO7eH1/7mZ1Ev6YzBoQ0pyH3uHRnegr5EHWTXBSOriPbiKHiA2xMjoP2h/v3XVvsEDN48mLsKIsY+RAbFpTHrwDWq6/EVdHwpH/rGM6aPiGGDStpuyuLBjWJnq9D/t2F9s4anc0cQNNmI0DSBu5BQeeG0Pwfyx3vXlehbenMbgAUaMEXGMvnMVJZ3+em3j4z/PZVLqYAYYjRgHJ3Ldncso9DfOzSdRjZueYvrViQw2GTGaBpN49XQWbmrU0lSzjNHGAUx/2yeFtjeYYgrBOPIpfPvSfPx4GsbYuRT6HdLlYs+bDzBlZBwDTCGEBLh2fageV/nLzLo6rv0aJj24noO+x7R9zMvzJpEWOwCj0Zs/97TdCxdb7hx8atp+k0hIiJ/rGGDkuhcOwslGtjw+ndHxgzEaQzAOGEzaxLmsKg3QPeDkeqabYnmg0MWepaMI6ZPIwnLve6HAvwtZlptG3ADtnqb94ikKfYeeHdvDGw9OIS3eew3xo5n++BYauxsOd/JjFqYaibt/PYV/mM7o+AEYjQOIu3oWb9TY2PPaXK67fDADTEYGj5zOqnLfO3uQwj/M0t43hmj5nDWdZf/ouD7b6kkYjZNY9Y83mDvBWx685ezjts1OlvDAZUbi5q2ncOn09jwYnDqJhZs6+j+43pyC0TiaZd6hnYX3DMY46ikKvfVlsKkjb32v2fVpx7kHDE1jyhNb2LN6CkbjdazyO15Tq8eXPV4Jx95gijEE44RVHPxiGdcZBzD9tUKemhiH0dSRlm7LO0DzKu++H/PyPdeRGOHNw1+u4mNbI1t+M4m0oQO0fSd3yddTuHAdI0CvrgimvVJG2V/naEG09vzdQsmf53LdZVpeDoi/jrld6omr5g0e+IW3jTIOYPDl1zFraaFWT9ry6P4Snz0aWXa1kRDjJF72uY+ugrkMNqYx97/SCLl2FY0nG1l1bQghpums91MWXTX+28Y93TZgB9nyq0SMgyex6hPvhmdS/r3n9y0fkx58g0YXXW7wacp6N3W3vWwMMBLiva9z//xx4OG3fo71X3PTMJomsaq5y7ZWrb1Je/xjqFvGaKOR6atLWHWn936aBpM4YS5vdPmgOfiPZcxqq48DBpN4SrsUXNvqe38CffZ137aemYjkDKKx8UVz20FO3xa118E39/DG/d76ZhxA3Cg/7dpibztkGkDc1dNZVnRqQxFMvtrKVzF3Ypp3m2DLZHDnP1292fNEGsbrX+bgsXeYPiAE481vaGnzzY8+IVp7/Iun2PJF4PSckrdP/4npg0OIm1d4Snn4+DeJGCOm8IYVttw5AOPIp9jy9kImpQ725v9opi8u7Fz+g6m7BwtZdud1JA4eoF3vKd9FbLxxs5GQgN8XxDeh/ft0N69vMl1CCCHE99rXX3+tevoqmBupMN+m1n7l5/1105Q+NFoljL5BzX9ll/p076dqV/4clRyGir63QDk8HuXx1Ku8SZGKyHHqkXXlqm5/nSpf94gaF6lX0XdvUoc8HuXx83LY69SKSXqlT1+kyloPKYfDozyOAjU/DmUePV+tLa1WdfvqVNmGR1RmuF4lLCjyns+jCu6OVIRHq4TMmSrvvTJV92mZWvtQpjKHmlX2S/u1c9SvUJl6vcp+6ZD279a1auYwvTKnz1Gvldap/fuqVcEzOSpaH6lyXtnvN40ej0c58nOUPjRSRY/IVPNfKVLVtdWq6BXtHkTO6Li+siczlFkfrXKeKVDV+/arul2vqTnpZqVPe0QVOXyOpc9QSz7V/n1o8xwVrTerjF+/popq96v99WXqtV9rx5mz+ZDynChTjyTqVfSvizrSs2GmihwWraLDslXe/rZ01qkV1+hV5IxN7feo02vXfJWgj1TZv92kymr3q/21ZWrtk9kqWh+t5n/g0O7pr6MVkQkqI2umyvugutM9nfZX7z08Ua2WZJmVPi5HLXmvWu3fv19Vv7dE5cTplfmaFar6hEcdys9R5i5pWzLarKLjolX0vQUd1/HeHBWpz1BLaj2q+pkMpTdnqPl/LVLV9ftVXfkmteLWBKWPnKbWHgqQL/vXqmnhWjncf+iQcpzwKE97ec3uyKtTymudt7xmqkfWlam6/XWqbN0jKvM05dXjqVaL0vRKPyxZTXumSB064VGO2jyVE4UyJyar7LvXqjq7R3kOFalH0vVKn75EVXv33f+nbGUOjVbTlhdo1/dpkcqbkaD04dkqb59vOTOryLRpakWpdr/3b1+isiNRkTPWauk6UaYeSUTpI6NV5oJN2vns1WrtXQlKH5ahFn3SpZzVeuvLvdGK8GiVPGWRKtjnUB6PQ9W9NE1F++atvUDNsaD0I+ao13bVaWm8K0MlJ0Yr9NkqrzVQPT6kih5KVoTlqLz9h9Qhu0N59ml1LyE9W017ZpMqKq1W+x1BlHePR3n256lsPSoyMUc98t5+5fB41P51M1VCqF4ljMhU0/5Upt37T5ao7HBUwoKiAPnlUR6PQxX8OkHpQ80qecYStXZXnVZOTpO/2W331rFfbbo7QRGWqVZ488mz7zWVE4mKnLBIrS2vU/v316mil2aq5DC9Sn60SDk8DlVwV6TSpy1qz39Pa57KNker6DizmrbO0X7OskcTlN4yXxXZD6n9G2aqyNBINXPDfnXokKM9r80zNmnb96RtjJuvik54lMdzSBU9mqHM4Rlq0a62855h+XcUqfkWvdKndbSfm57JURnDIjuVj6DKur+6+8kilaHXq+S7XlNFn9ap/fXVquBZrX2eueFQ4Pa567Hq81R2mF5lPFPdabv9L2Urc1imVifqV6hMPSpyWKaa+Uq1Vp7qN6n56WYtP9ra6w/mqwS9XiXMyNPKa22BypueoPTmzPY2PJi2NajPviDa1kD3oODuSIV5mlrrZxvHhpkqMtSspm1wBJ0/bXUw2pKt5njvj6e1QGvXRixSZSc653Wnz7ysBBUZRsdnVjD5at+kZkbpVfSUFargE22bovz5KjNcr5KfrA543UGdP5h64zikyp7MUHp9tlpRe0gdsmt1Z+30SEVktlq0uUzV1dd5P9M7t+2nz1uHKvh1tNJHzlSb7D7bntDqU+Rd2md2wV2RCnOkSpjkbaNPHFJlf9La6PbvNEHV3f0q7yaz0o+YqfK2a9db/UGemplmVuYJeWp/W7v45DSVc1det+VKXt+N15l87z/TlxBCCPF9dWaBtHv9B9I8Ho8WmECvxq2s9/ngPqTysvVKP3qJqvN4lGfH/C5f9rRX3fJMpQ/LVCvqA30BOKReu8nnON4vePvrq1Vdp4d2h1p7q157MPV+6Xv/7khFaIKav8tnuxNlatEIlD5rhfZlsUsgrfrJjE5BrPY0TDEr/YhH2h8Our4c+TlKT9cHM4d6/95ohXmaeu2QR3nsa9U034BH26v8EZWsN6tp+Yc6jtWehv1qxYTO19V2HY8kovST8tQhj0e9f290p4fyol8nqMi7lqhH0iLVtL96H9QOvaZyzGaVk+//gfPQS9lKr/cJBnivvW5XWfu9fv/X0YrQZLWo3Gcbh/aQ2h6sKJjTOfjSdvxXcpS5LT/2rVCZYT4Bg/15KtucqRY9k6PMPtda9lBC+33fON1PHtjrVNkuLQDjt/yc2KhmRnYJpHjLa+bKus7ldYJPOdt+puVVC7TQKZ0OtXaKXhGWo17zKbPVTyYrfdg0tbYt7Yf2q7pP93cOcn6ySCXr9e152FbOMld2TlfRggSFOUcrZ96ywbA56n3f+9Kap7LDUMmPlnUuZ7U+eevzby1vN6qZPnnr2OQN5Gzyefg/UaYeGUG3gTSPx6Oqf5usCPN5kPc+iJtves2nPgRX3tsf4u9+v+N+nXhfzYmiS1uxX8vXtvoe6OWoU2sXZKvoMBSgMEer5AnT1PxnX1NF+3wDHd78tbQFobyvXfNVQqhZzdzQca36sK51yaE23hWtiJypNjo8yvHXaZ2CyY4N01TkiPlqyd3RKvre97371Kkl1+g7rrNgjooOjVZzCjrfF/OMjT1vG+Pmq6ITDlW9PFtFmpPV/Hd96usZln+/5cOzX+VN0ncuH0GUdb9113FI1dXWda7vJ95Xc4bhc8+CaQe0AEjn9kQrK+ZJeT6fDSjzrZ3ba4c3mDnnXZ9r8wmsael8X80Z1pFvwbStp778fPYF07YGuAfvtwXSHB7lOeF9OQ6puu0r1LREvdJb5qv324I4weRPWzB7xsZO29U9owWbtLyuU0tGd/381spXQqhvICuIfP10icrQm1VOfufA46FPilRZfaAgapDnD7Le1D2rXdtrPn+4ceyvU9Vdzr9/ZaaW3/v9pSlA3n6ySCXru3w+b5+vovUd+ap9p+ny+dt2jW1tXDB190SRmh+n79x+ejzKs69MFZXv9/+HNnl9r14SUBNCCCF67iyGdirvHDd+upCHRpN+xTCfbc30GwCuYy5sJ6Hxn8W0hCYw7prOU4xHXzOOhJOVfPjPwOOOVPt/2ujR2yp5+f4sRl0eR9zQwQweGstdm1y4jh3vPMTBnEHmCJ9/hyYwYoQZV80ePvMdrqAAbFT+sxJXXCaZcZ0OQmZmMtQUUxxoiJjS7kHG6IRO6UwZYUF/rIbGL4CaCj626sm4JrNjHiaAxEwyIm2UFFecesEnK6gsc2FOSyfBd36m0AQy0sy4qiupOAlXZWVirvmQ4oMAeygsaiFj9G1kpl1Eyc4PAXAVb6P4ZAY3XNPp7B1XOfrnZIYVsnDyFB74w+ts+/ggLsxEpycTHe6zYXgy6b7z54WaGBgGR1zHAWj8pIKW0GSuSu98HnPaVVhCG6msPghR2dxwuYuSnZXtaauMyiBzyjiS67Z5h5c0UrizkYHX3EByKKRMymZg9TJuv3kuy/7yDpVfuCAsmuT0BCJ7Mq1PW16lRfumDnO4T3kt+5CWUMsZlVcAfVyCT37p6ROmh6gEhvncEn2YGU66ON52qDBofPdJpo9NIzE2jsFDBzP4+mfZ4wJX20ZtaR/ROV0JiRb0x77Qylnb8UdkkOJ7X8wJJEfBnhrvEMlTKxaYkxkxzOffof0wmzvytuXTz7CFJpOR7HPg0GR+PiGBYHU+ox5LxoiO+hBkeW/bd1hCNB0puQhzGOgtFjpy1ow+DDju4nh3idJHk/PMJur211H0dh5L7spk2JESXn5wOqMvS2TKC12GNycmk+ybvrB+6ENdHD/uAmxUVu7BFZdBRqds0nNVugW9tZKP60B/zTgyKGZbsXbkysISSMvkttEjOFJSwp6TgLWYD8v0pGddRXBFvAdtI9D4xl3c+JsvuOHPm1hyXUfhPNPyr5WPBJKTfFMbSUZGQuf0B1PW/V6eHlfVGyz8xSgS4737xd7Cy81wxNWTmfLNZM+4jYE1b/B6iXe/5r/xepGZ7Bk/91kIQ4/lihGd2mu9JYFhoTb21B+EkxUUl7iIHJ1Jhu8F6q8iM11PS1kJjSd70LZ20bWKBtW2dsemDa0O6eN9GQcQd/UDlITPIW/DIsaFebcLOn/0JCR3ztuLzGbAhcsFnNzDnhoXA0eMwLe1JS2DEWG+hwkiX+MyueFyWH//tUx/fBV/K9yD7SSYEzNIHub/My3o8wddb5TPf717hh6kcMVdZI1MJC52MIOHDib18WJcHNeGjAdwSvObOJM517jY8urfvFNPuNj21npaLr+Nmek+25mTGeH7+Us0Fou+/TtNUHU3NJnsSdG0rJ7NpF89xcsbi2m0AVHJZIyIDLKtEd9l6jwMBz2XxxZCCCG+CedmjjT0XNQn8Lu2Iy5crmIWXmbEaPR5jXySSpeLg4f8T/DS6TO47UO/bhXTr7+dlw9mcP+fNlJUWk55aTkrJpk7bQeA2Uy/EN8vDH3Qh/UDlwuXUvhO86uUiyPHgJqnGG3qnM7Y+wtxnTyC7WCAeSkAQk30M3f+fZ8w7aHiiEuhjtg4gov1dw/ufA9MN7KqGVoO2jjeaeJhhXK7OOKCfuaLupzTex3HtOvoMyaTjNBithUfRzVvY1tdMleNiSBl9AiOFJewx62o/EcxtrRxZEYEuIbYO3hr10Z+Mxo+/N+5XJc6mAGxo5j1h20c9L2nen2XgOpF2pxjaF+cbEdcuDBjDuty/LA+XAQctx1HqWFkZkbTUlzIHqX48B8lkJ7JiMEZZAyr5MPi4yjrNrZ9YiYzawRKKSKmvErRu78nO2wPLz90C2mxAxh85RSe2tjYzXwhvsXHJ6/ow0X6AF8k267BVRK4vFptgc+ngFB952OHavP16X1/pwBcWj6r42x7MIsbHy+k37Tf8+oHRZSXllP+1zlY9D7p95azi7qWM72+o5y1XUqYHlOntJm5yAi4jnjLvk85a89buuRt5/tnO+rCFapH3yVvzZHaw5eiu3lb2iYkbMsH7d8XGft1bBdkeW9PfchFXdKqR9/13ndtP7p7GYeRPukO7lv8ImblpJUAACAASURBVG/t+pzm2o08knaE9Q/O5aUvAudvx9Wp9nZEb+yHOaTz8dvbg2MKNSCT7DQXJUWVKPceCnceIWP0VUSMySS5bhvbDiqOFxdSHJrJDZl9fMpuR56dUr7rVgbfNh58mbn3vkGj6wgt1uOd0nmm5V8rH6fWfb3e3Jbq4Mu6n7pre+susm59ls+GzSRv3fvafrteZeawLnU8iHagz+iZzLyshddf3cZxpWhc/zeKI3/OzAmmTuWzn2/5VAql97Zjx463l9eDq2/pfJ+MA7h9rQ3XwRZagmxbu0tzW74F17YGqn9AWDZLdpVRVup9lVdT12rl84LfMy3WW8aCbov81UHVUc1RKJeNIy7Qh3W5hyF6LvI5VlD5GjKCh7cW8dbcFGxblnH7hEQGRMSRdc9LVNoC3MMgz9+jeuNb/9yVPPWzLB7YBDc8+irvb9f2K3g4wxuMCj5vlYrg5zNyMBe9xOt1CnX8Q9ZvOkLG7TOx+J7fbKZfl+Pp9R3faYKru33IXFpE0QvTiG5ex8Lpo4mLGEDi5Ad4vSZwGZLX+Xudb9/UeYUQQojvkqDWneuND1TfI5j7mdHr0/nNe38m55S/wOvpFxER4Jyqy//hi435FB5L53crf0dObNtvbRw/5qdHwjEbR7r8ynXsCITptS+67YdVQB/6hQHx83lrzczOf8EGCOlDZJSfJLY5aed4l79Au47ZgD6Yw4BQM/3Qk7y4jCXXnbp7H9MwtHCIzxWH6ukXBkdsXfvTuLDZjmhfqgFMmWSnu3i66GNsrkIqB2ewZDCY0jNJrl/PtuYcXDsbsdyYzbBuLkEfm819f8jmPsBWV8KW1U/ywIO30GL8JxvvOuWO+GUy69Fj48hRwOTzxjEbx4F+Ju0RY8Q12Qz8w4d82PwxX+w8QsYDyehDzWSm9+ONomJs+hIq9ZnMHN3x9/GIa+bw+2vm8HtcHCzfwstLHuPJW6egSv9/9u4/Lqoyb/z/yxxvD7f4cGixhk1XxsJlNA00TCy9FRc3cXFXLDch+6yh7RZYmVh3iW0PI+/9+KPd29D6KFSrC3ZrYKsr7uod9sVdsKVlTNJhpXU0LNigGBeKY4xd3z9mgAEGGH75o97Px2MeMOfndc65znXOec91Xec9nhnnU/Kaec3h7jw4zBiApk3hmT9lENcuvw7GeOON3VuulxGtsp7zCLvesGG8Zz+bfzGzpUbAWZ2LzjYzd5XPmiav13GAR20aB7UXgJAAPGPe3TnVNU1Dc+o0NABDWoY7amrRCepk42k/TnkZ4Wt+9zZvp1SnUzrO2mGEGWOb0lEbNYdnHp/D1nsOctwGjOpojZ5DXeWIXl2Lw0mrElevd4Ch6TgFE/WDUJ7cn0/ZeSP5/whn/l3D4MapRI56lqIiBxPfK8IxZQUzh9ExzxpL+7NdZWP6WuY316rtoGwkmPjf/Y7579xP7H/ez7qI/+WZ21w5r6f5X/PX0Jztz31HrUf+6E5eb8VB3ht7qbrlEd7c+CBTmvarTqc1fzpkCGXJsplsei6bg45Q7G8VEXrfBmY2JcidjNr6z1tvTL2rdqPfEM1VpvuD6Sfb+d+nw9utYvBAI0HudHa/bG259jX952vZ2vE2GwmeFEZYZ3cBvh6fDs7B1pdUI5rBfc31pDtcP1oB3TquQ0KZ/9Rm5j8F1JRx5K2trEl9iB/VB/DB6/NpVy/Np/X7ft6olkPi8n4u2X+Dma9sZ8WPWtb+ZWND6+nbaX9sAYb96EHiTbFk7Snj4bBd5NbPZMM9bc61dvc0eqt7Gt/P3WGE3b+WbfevBb2K4+/ksnX1syz+MZiOr285D8QV0ZN78L54c2bb9fblMuXNnkIIIa51ndZI69GvUm0DBJ7LUIBSBE8Jx8xZ7HXBhH4/tOVzk5HBQ0zc2EHLDG+raajX0Qkg6DseIz/MZtefdVB66+TUlGD9wHOADWupjhYa1rrpGABGwqaEoX1sp3JYaOt0DhvM4EAzxs5uLp12ioo9m9boWD8oQzdasIwCvh9JZCDYK2tbL/v7JowDjQS1bZ+oAEM4U8I0HEX5WD2bojqtFBU7MIaFu94miImZM8KoLMon+50itGkzXcNHRDJllJUjf8jjyMlgomaEdpj8qvcOsvedlrc6Gm+ZwqLn1rJknI71vbOdbHjrDGCOmEqQ08qRP7euZVhVVESZM5iwpmaJU2Yy09/KkbfyKPpHODPdzZXC7wqj9mg+2e8cQb8rhpn+AA5sf9zFkea35WmYJs3nmY0PE0kZ1tLOm3V5DaN0kM0VYJ4STjBnOes1vwZh6jC/dh5J6nCsU6ehHoyBRo9mNQ6O7MpzNfFrNa2doiK7xwAd63GPfOZej368CGurl+eVYD2vEXpraDea7rROcXCoGc1ZxvEPPBbstJF3sKybS+qAz/nd+xp6Ev/X31rMLaERLH7d7nV85Yd2dIIJHuFaRwer9mAk7PYwtH8UUdjqrZA6RX+2ogdOJdL9A0DojCiCTxaR99YRrKOmEDkCMIQyMzKAY+9kk3/UTtgPZtK6kVbrFXuuWm8qGz0foDsqG01RLLo7lJlp23lmXBnrHniWI+5Ttqf535U/bK3zB3YKj3nkj+7k9VZb6K7p9x0TN3rkgaq3ssmrAXx4s2DbM9B0z4PM4SDZ6S+TezyS+PvD2syhU3bsWOs3R5ZaKXMGET7eBAYLU27XcNgrGfz91tcM0+DBBAS7amr2vGxtzeeytTe6eXw6ZQjG8n2NSquVViXWsSKON7cv9+246meL2PtWUcsbtwNDmbl0M8/fY8JhLfH+5k6f1t/N8wZamonXOdDRCPI8IXQrr+457tNbvtvRZrLkZ6GU7XmVF9/Iw+8nD7b/4bGmhELPexqnvdU9jU/nbr2dI28exNqUjTQTYXc/wuZVM9HOW7F20UJYXJ36o3ZbX9ZUkxpvQgghrnVeA2ldXSzb1wvzmK95jLdluL/f8TArfgDZjy/mxT9asVdVYX9vL+vun8b4HzzZ/ADXnobmr6H/o4iDx2zYzuqYb5+I2VnEq6/kY6+pwnZ4Kw/94giWH4Wi/dOG9UMHulOhnIDxAtmpq9j7np2q8zbyf/UkW983Muf+GG5UrR+rlFKE/mwl8caDPLt0jXseO9aDL7J41nim/WJXh81wADAYOfvactYdtFFVVYXtrTWsed2O+Z4lzBmiUEPu5uHkMKq2LOehjHxs56uoKiti11P3cvvtP+KF9/Q2+0+h1I3EPbaE4L+/zPKndmE9W0XVh0Xsenw5r34cxpLk+c3N94J/MJPQk6/x6//VibwrnMFKoQZamBkZQNHLL1MUOJO7J3XclKD2f19g8X2LWf56PrazVVSdtZH/+svs/btG5BSLe7qmdHl+3L+8N32f6jrWB3+5jBcPu/fFwXUsSzuCdvcTPNiUhsGRzLxL59hLr1F08xQib3INd9Wie4Ot+ysJ/8FM9/bVUpS+nNifLmPrQSv281XYy4rY9etsrIYwIsMGd7BdRoYNgbPvHSH/uA17jecx7+BmUynUHQ/zxA8g+7HFvHiwTX6dtYr8jpoSeW2y47FOrze3CjU4jPDbNcr2v8auD6qoOmtl7+rFrHPOZI6/js1aQlVT7QiDhu21R1n3B9e+tb61hjW/88hn7kVr+kHWPf4qRR+68szWlF9zRIvkwXtCveQz347t4BlxzDHZyf7lGvYer6LqbBG7Hn+UPIK87tMO96+Xc8/18TG/e53X23Ht4Hh4fAbPfYa1P9A4+PhsYlduZdfBIores1J0eC9bn4pl9nPHCbpvNQ+O8+H40lKOzDceYV3yOvI+qHKVPa8sY9WbOlOSH2bGYPd8YXczM9DKyy8fISByJpaBCqUGu4LJh7fy2slQYmYEt9uPHW2zeZL3sjHUs2xsdKfXfXDV4DCezlzLzH++yEOP73WVcT3M/4NnLGHRqCqyV6/i1T/bsJcVsXf1o2RXeOQPH/N6+3P3RiInBaO/n83WP9ipqrJT9PpyFv/OSMwdGnq5FWuV7ns5oBRq2ByW/DSAg7/aStldi4i/uf0x1d7bwvJ0V3ltf28XTz6/F33cfSya7Mqv8Y89TPD761i8cpfrXDtrIz/jIX5wewT3vmLvRtna9tP+2udz2ert08V50Pzx9fh4PQfbliuhLFoUCe++yKO/ysP6oR3r4a0sez7fVVVWgVK+HVfsuay5/14Wr95FUVnLtXnrHx0ERUa6z522H1/W7/t5E+AfAM4yjv3Biq2sCv3WSMKMDvIytmI976DqeB7rfvYkZ6fMweQ8i/U9Ow7dx2PrHhd6/yPM/MdW1r1l5Cc/u9t1Hfc8hv5V7P3PlnuavI1t7ml8OXf147yaci8Ll65j73s27Oft2N7bywuvF8HNYe5rsU7+rxZz7y9exdbYRZ6RT48/l0NfrLev0ns5t1sIIYToc+3euunD53Cy641fey5eUk6ns/XnzUVKM4Spte+3Hr7nfk1x21pVrLuHOUrVzpXzVViwUWkGlGYKVVPuW6v2ldWrxsbGDj9176xVM4M1pRlNaspzR1VjY7U69Nx8FWbSFJpRme98UG0+Vq0aj29Wc4I1pY2YqdYfb1T7fmZU2qSn1aH9a9X8ScHKqGnKGDxFLdp4VFU3Lf/Dza63dmZUt6zvw31q7X1TVLBJU5pBU8abp6j5K3eo0tqO01id4Xor2+Z3dqsVPwpTJn9NaYHBambiNlXcar5qdfSVh9Wc20zKqKE0f5MK/cEStf5wRcv6d85XmjZFrf+gZb7y/WvVojuDldFf8zpPY2Ojamw4qlbcjEKbqTaf9UjbzvnKCMr0s32qrpP93NhQofalLVIzx7nShmZUwbfNUQ+nt+yvQ48FK4IfVoca2q/XlHSoZVh1sdqWNEeFjTAqTdOUMTjM6z6seGWO0kAF/9xj3oZi9fQ4FG32QWPlUbU5cU5L/jG698PBio63qbFRlf5mvgo2akozhaqH99epxj3u/Hq89XS7m/Jr07bVlqodXvNrXSfrK1VrJ2lKu293q329L9GotHFPtyy7sVGV/2am0rQ5ake1+7h/sE0tuTPYlS9MYWrOU7tVeV212vdYmDL6G1Xwz/epanfeWLt3h1pxd6gy+dM+n7n3n/H+berQxkVqSrDrGJhum6+e3u8ln5V179hWv7NeLbrDfT7dPEUt2nhIFbu3ZVt1J8fhuTCF/yK1u2n5FdvUHE1TM9PbH78u87u3eRuOqqe/rymTZ15qrFM77tGUdud6Vd5Z3q8rV4c2Pqzm3xmqTEZNYXDt19AZi9SKV46qiuZ94v34Nh5fq8I0TS3a1ZI36j7YrZ6+J0wFB2pK04zK1OZcakrf7vuNCoxq0a6WMshVLqG4eYU66nk8Dj+sgg3B6uHDbY71z/Y1ly+eZWPwnUu8lo2Hfm5qt+yKnYtUsMGk5rxS3ov836jq3tumlsxw5Q/NFKrmPLZbFWfMd5WPFb7n9Tpv525tsdp8n7t8NQarsPvWqkMVrrSHGjVlmvR06/3VWTnQvE9XqGCDSS3Z22a7mq4Nvzmktv18pus4+ptU6N0r1O6yNuXY4fVqyQ9Clclf81pu+lK2et2X7a59vpetbT+Hfu66hu/uYP+0Wq8vx6eD87fiFfe18KzHtq+er8JGuM6D4DsWqfWHD6mnx2kquKlc8em41qnyXU+7zlF/FD5em31av4/nTWPlPrXiDpPS/I0q+EebVWljoyrfs0LN/L5RaQZNmb4/Uz38eqmqqzuq1t5pUpoxWC3K8H598npsGxtVY2OF2na3prQ71qpSb8fw+yvU7r1r1fzbTO7j3+aexsdzt+69bWrFj1zlEwbNyzTVasdPtPbXBPlcFZ929+G9+Fypt34KIYQQ15oBX3/9tbtCQvd+Feru9L2dTwjRmv7GQoYvq2Rt8VFWdNRK13mcZ2+P4OXb91GdMafvE1HvwIGxpT824Nh/jif6f2ayr3wzM33qhVGIq4HOkeTxzPvzIo6+t7Z132FnX2b2+CfRXqpg38986HtAiL7w4cvMjnwW469L2X1/66a6R5JHMvt/F3H0g/UtfckJ0UZP+yLr7nx90eeZ9JsmhBDiWmLo7wDa1RQ4u5rSIkTfUXSctT0ar/Z1/v/iHR4Lm80u8wq2Pb+EMBNU/fllnsw8S/DPFxE5sLN0CXGVuHiBs2ftHM/5JU/+FhbtfILb2uXdfjyPhGjj4sdl2D8s4tcpz2Id9wQF93X0Aibcb7+9zAkU3XIlA0Rt842vaWmar7+m72gZEkwTQghxrejTt3b29gFDHlCE8F1TT0ednjUdvE2vTwyZwf99awda6os8GfsyZ+vBdHMYMx77H9Y+NaXV20CFuGp9uJWF0/6Ls98JY/6vd/PfP/bxtahC9Audg6nTWfh7CP2Ph/lt+n8SOrD9VP1ZtIu+1d/3tt0JPnlLS2fze07vy3p6GwyTYJoQQohrxYBLly51/hzuww3AtVxLTQghhBBCiG+S/mie2Z1l9iYgJsE0IYQQV7sOa6R1Fey6XLXU+no5QgghhBBCXCt6Eljqj9pn3WnCKbXLhBBCfJO1q5HWFwG07gS9JEAmhBBCCCFE7/R1jbGupunrWmx9MZ8QQghxOTQH0nobQOuPJqCXa1lCCCGEEEJcDfoyiHQ5AmZ9EXDry/mEEEKI/jbg0qVLqrOgVE/H+TK+t9MLIYQQQgjxbdXXfaF1Nr6n43wZ31fzCCGEEJfDAKfT6TV6dbUE1/p6fiGEEEIIIa52vQ0kXe6gmdRME0II8W3hNZDWUbCqu8O7GtebaYUQQgghhPg266t+0bobHLucwTQJpAkhhLjatAqk9VUArT9qpUmQTQghhBBCfNv0R/CpvwNnvWkG2lfzCCGEEP2lOZDWnaBYXwfWujudEEIIIYQQ33a+Bpj6IhB2JYNpEkgTQghxNRngdDq9vmygN8M6G97VuN5MK4QQQgghxDfRlWjG2ZthPU1HX00vhBBC9JcBjY2NPvWR1nZYXwXVfBnfFQm2CSGEEEKIa9WVerGAL0ExCaYJIYQQrRnaDuhJwKw7QbWuxnVnGiGEEEIIIa513bnv9RZMajt/22k8x3uOaxredlh3p+lomBBCCPFN1KpGWlcBsp4G0KSZpxBCCCGEEN3Tn805e1Ibra9rq3U1ri+mF0IIIfragMbGxnZ9pPVFAK27ATVfxvf1fEIIIYQQQlxpPQ0O9aRJZ0+CYf0VYPNlXG+mFUIIIfrDgK+++qpVFKq3QbW+qKXWnWmEEEIIIYT4NvAliHS5ap/1ZTBNaqUJIYS4lrQKpHUWFOuPAFtnw3s6nRBCCCGEEN8UvgaNfA1S9eZ7d8Z1Z1hnw3s7rRBCCNHXmgNpPQ2i9VUNNV/G9eU8QgghhBBCXA16EhjqbZ9ofRUw624wTZp4CiGEuNYN+OqrrzrtI82X/3vyvaNhvozrKQm4CSGEEEKIy6U/gj39GUBr+92X/7szrrNhnQ3v7bRCCCFEXxpw8eLFDvtI683/vnzvariv44UQQgghhPim6slLBbwN723QrK+CaVIrTQghxLWsVSCtr4JovamNJn2mCSGEEEKIb6u+7hPN27C+CqD1JngmtdKEEEJcq5oDad0JkPVnc09fxvVmWiGEEEIIIa4mfRU86utmnJczsObruJ5MJ4QQQvSlARcvXlR9ETjrj9ppXY3rLgm4CSGEEEKIy6UvAz192TdaT/+/XME0qZUmhBDiambwJYh204MbLnvChBBCCCGEEFfex6+uYsCAASilmgNXHf3vqaPhXY3vaj4hhBDiSrqu6Z/OapEJIYQQQgghRFfPDJerpYkQQghxpVzXdoAE1IQQQgghhBCeuhNAk+cJIYQQ32TXQecXQ7n4CSGEEEII8e3V2XNBd58VuvPysZ4sTwghhOhv13X2cgG5MAkhhBBCCCE6e07ozgvKurs+IYQQ4mrTro80uWgJIYQQQgghOtLbGmp9XStNCCGEuJza9ZHWRAJrQgghhBBCCF+eC7rTb1p31yuEEEJcTVr1kSZNO4UQQgghhBBtded5QYJmQgghvsk6rJEmhBBCCCGEEL7qTlCtLwNnEoQTQghxOV3X1a9LcmESQgghhBDi26uvnhf687lCnlmEEEJcLl5rpEkQTQghhBBCCNHE1+eD7jxH+PLSAXkeEUIIcbXx2keaEEIIIYQQQnSkO7XS5BlDCCHEN4m8tdPDsPFR/P43T1H5xi+pfHE20//dwvbtv6T2jcfYEGrwaRmDx8Vw/I1fUrs9jthB/ZxgIYQQPhs8I57KN35J7a+iGDPwSqdGCCGuHT19LpAaZkIIIb6JDJetT7ShI1i6cDqLw0Yy5noNDSf6l/WcPl1Oxp5D7Dzr7J/1+szI4gWRTDcZ+LS0iJeOlXPua+0Kp8lNC2f39nlEewbmGnU+/czB+ydPsH1/MYerurP//Fm6+jE2DC3ijtX5nL7U3QQZiE16jB3T/DudqviNLcx+q6a7CxdCfANFJCRxKDaw9cBLTi5ccPDXvxWy4Q0rxV9cmbT1LSPJzz3G86Eeg9zbefofdnb/sYCMk/XdWuKYhT/n3R83sOoXO8io60GSTNM4tCmKiM6Ch3WlPPBILvsbe7B8IcS3jlKKAQMGdPlXCCGE+CbyWs2qz4NqAwNJXvl/eD7UgF59nsNHK/nnJY0x4yxMnxTBZrOG46lc9vfkAaGvDNS4cYgB0Hn3nXzS/+KEQZYrmCBvnJwrt3P6XzB4SAChwSaiZ5mInjKB9Jd+y5rjum+Lud5CbIgBqnqejiq7ncP/7g40DhnOtFAjGjonSiv451euwX+v8jE9Qohvj7oaCk7XchFAG8ptY0xER89j8nAD/7GhmHPdDuxfvfSq8xz9uAE0P0bdZCIiIoKIiRZi9/wPC98679oHXRkYyMIwE2DvRUJqeLekHIe7DvqNN4cwwQh69XmOftTgGvhlZc8vCUKIb4XeBsl6E1yTwJwQQoirSatAWr9Vv/53M9EhBrhUw5ZfZ5J2xj18SAipj0Qw5st6jEagzp/kNSt5fpyT/ZnZFITOZtUkEzdQT/GxfJIzrZx2/1p+w7hIUuMm8sObA7lhkJML1VUUFBayZq+Nc1jY/tJC7hliZ9XyHWQ4YNiMeMp+EYKGg4znt7DqpBOCo3j3hWmM+bicY0EhTBkEoBG7fDW191n58VPl7bdlyAiWLv4hyZNMjBpqQHfU8NdjBazKKm1OWysDjSxensjmKf6c+0suP95ayjmMRC+YTeo0M2Ou1+BLB389VsCaLCsnOo096RS8tZtH/+aufWY0s3L5QlLHmUhOnE3Bqn0c1mFwcDhpCVOZF9Kyb/YdOMCqw1UwI56zvwhBAwiexrtZkRx+5f+y8B2N6XExpM40M/56Da2xnhMnrWx8PZ/91e1TUpyXy8I81/+Dx8Xw7poIRl2qZOfmbDLqYHDobN59biXJejmrHs8mw+Gadkzcz3l3oQm97BBTNtTz/JY4YgdVkf7qKUZFTyb6Jn/4ooo/7DtASt55Lrj3Yc/2lxDiqvNxCY9uKOKc++uwSfP4/1aFM2r8RO65sZhNn8CoKVFs+Ek4k2/yZxg65yrs7MzKY9PJesDX64Q/0QvnkRZtZozm5NzpUjadbJ+czsrLiwCDArln0WyWTxnJmGEaWqPOubPlZOzJI/1k5wXQR8V/YmHWedeXQUaiE37KjrtNTF8wl1Un/p/rWtjZNcUYyaHfzHbXJDOzYfsvWfVONhNeKcfU6T5qw2FjzSab+4vG0tVPscEI/zyez+JMOxc1C9t/s5BDO6fy5m/+m2XHXNeYwaExvPtcBKO+KOfRx/cx7HHXfi/I3ceJ0dNZGBro2u9/ySf59Zbr87DRETy/aDI/DAnkhoE6n1bY2bY7j03Hu1cTTwhx9fAWyPI1uNXVvG3HS9BMCCHE1a7VywY89WkTz8Z6Pv0SGGgkdm4k0cH+DAb4opy0Ddk8sOUQOysAnOhfAxi4Y34MC78uZ9thG6cH+hMxI4YNs4wADB43m/3/OZvFoRrnjh0l7felvP9vJmLjFvL7n4UwrNFOwT+cMGg4d4QYAAPTx49Ea3SiY2TyeFfzohtCRvC9gXDu9CleyirisMOVhhNvH2JVTill7QJjGvcs+ykbZozA+LGVNa/n84cvjUy/ex7b55vab/dAjekJCayf4s+nxw/xwCulnLtkYHpCAjviLIxy2Hjh1X1sPOFkcvQ89vzMwrDu7FeHnU3bCyhuBIaHEDvOAJqZtMfnsXS8kapj+ax6o5RzQ0ew+Gc/JW28gYuni1nzThU6QHU5m3YcYvtpJ6PujmPHQgsRAyvYkpXHppNOJkyaxraHIhjVnTS5XSwvYecZJ2hmYiPcTUAHBhIbbgKcHP1LKee+csIl1/ClsSM5/cc8lufY+OcQE/ckLCB1vPvY9dX+EkJcdS58VM2nlwAMGIcAo6PYkTSN6Jt0CvbmseZwJX6jLaQ+HsM9Q8HX68QNM+axPS6EMVo9h98u5M0KI8lzzLRqsN9FeQkwYf4CXooJwVRZysasPNb80c7Fm8fz/OPz3OnxUaODwzsPkPEJMMhEbOQIurym1Nl5aY/N1fz+Ug1vvpFH2l+qudjlPuomvZydxxyAP9ERIc3l6oTJZkYBnx63sq+uZb9P/uF0RpUVkPL6UQp0fyJmxbRcA4eHs/3pGBaHGnj/j3k8mmWlzGgh9fGfsjK4B2kTQlxVOntmuGzdxQghhBBXWHONtH696Ok2NuywMuZn4Uy4cza775yNXufg9EeV/PWkjd35pRQ7Ws8y2F7I/VusfIqB00ZXf1y3hQQx+I86C2MiGDMIPn1nH7GvlHMRSLc5eXd1BKOmR3JvTjmHy6rQJ41gws2BcNyP6WM09H9Y+YMxnB+FmhlFDRPGDEdDp/iDD8grDiRyViTRRifnThWT4a1p50CNT0sLWXPayd+PF3P4Exg1aAz3JIxgwvdHcgNVrhpU7l07cNzAvgAAIABJREFUKnohKTGBXCw/yrKXijjRCGgWlv5HINqlGjKyDrH9rBP+qjPKspDFU8KZl2VjZ3eauH5WxfufQYTJn1E3anC6kXcPHeIcDgrybZzQDVwMHc/mSUYmWwJhdzk7T4bz/AwTfFHF7j8Vc/oSjAmysTGrnAtnbewsdUB5ALFhkYwJMRMxqJhz3e0351INO49UkDLazOTJFm44XMynw0P4YTBQV87uY66aCRe/dk3+1wP7SHunHrDjFxLC5klG5t1pJrVc69v9JYS4egwN5J55Exk/EKir5v1PYPDwSvbsPsQeRwU7j57nwiAHY6aaWWwMYnqwgTdLW2bv+DrhZN40M8OAc+/sY/Hrdi5ioGBQEr93B9oAGNRFeVlaw6gbjWjARxXlvJlfzjndyv6/mRl1qZb3u1sj9lIVf7Xr8F2N75kCGDywvvNril7M/ncqWHqvhTHU8e7bxeysg8HBXe2j7vY56qTgnVJORE9jwoTxRA+x8aY+gnlhgYCDPx0t54JHBfaLx/NZ/paNC8CJoWaOJ4xgQsRYJuRUwczJRA8F/W8FJL9VygXgXW0k7943gsUzRpD+uo9NWoUQVzXpC00IIcS3mcGXX5b6wumj+/iP4kKmR4QwfcxIJgQHMXmMhQnjLCydPZ5VL2STUdEy/bl/VPApAE7OVbua8wz+NwMMCmLC9wyAk/fLK5pvyC+WV3K6EUYNGs6EmwxklNr56NIIvnfzSG4YOZTp18NHfynhT8Mt3DPJzHSjnVHB/qCXU3DSx4eOSw7OfTGU5GgLKQtnM2yQR8vYgQb8oCWQ9u8hrL7PgIaTEydP8W5TJ9qm4YzScPUb99xTJLdawXDXtvmanuZ1u/9+DdQ5uKBN5aHp01m9KA7tOkPzeG1Qx28ePfeZk1F3T2beT6JYrxlctTYGAl8b8BsI9KAD6k8LrRxeaCY21MK84cUcjhjL+EHw6bFSV394zS9PcHCioumJVKfsEwdMCuSG7xjRTEP7fn8JIa6c0Nkcf2N262GX6jm8O583vwCog+9NZenc6ax+SEO7DncZZoB/az1bx9eJ4Xz/O67rxOmzle7rhJN3y6vRZxlbaqV1WV46KThm49zkcMbcHc/xaCefflLFu2Wn2HPQzoUelIuD3cu/eAmfrineXKz2fR/57GwJO09FsmG8mXlhGm9WjmX2jcAnNnaWOvHsCeJ0RWXzta7qk2o+ZQQ3XB/IqOsMDP6uq8a3Nmkef399XqtV3HhTEBoSSBPiWtVZ8Kw3zTyFEEKIa03HkRW3Pq2hptdQcLSGgqNFru/Xh7DhyYUsDQ4hebaZnZmVzZM21VTqPndQ5WM7BZ9PY+nIIH44YThjBjrIOFnF4Rsq0O8cyfRJZm4wAWftFNTREozqzHcj2Z4UScQgB/t37Oalsjr8In/M72O9NeuEj/5WDhNCmHD3XJL/kskmj0Ahl2rI2HqI/f/yDAI1UvVRN4NCJjOTrwdwcPpjnRtmxLF9oYVhdXY2bT7Knz5rZPqi/+NuJtmBgSNITZrH0pFOTr+Tx7K3K2m4YTLbl4f3qFlnsy9sZPzVQeyskcRGmGCCCQ0Hvysob/MgZfBobmUAbwG/vtpfQogry/NlA187qfqskoK/WHmzvB4wEL34pzw/zR+9vIjlL53i9FdBpKyMIdbYflHdvU5obcr5G2bEdFleXijex3+sKWfxnSFMHh3EhOARxEaPIHZqCKvW7HA11fTVoJHcEewq7c59UsnF7lxTmnVvH/nOwZ6CclLHW5geEULER2bGDIQTx05Q3OYFEIOv8yijrzO4umr4uqksdgXdLhzPZ9mBNkGzL6qRbi2FuDb1NgDW1fy+LN/XaQAJ1gkhhOhX13l+6a++DEbNWsi7rzxF5YYYpg/xGPF5JSc+c918+13XZUzPpbGaEx+7btRvCxnpuoEHBoeOZMwgQK+muMIJjRUUnNZh6EgWTzZBXQUF5U4unLRTekkjYsYEbhsEp0/amzu97srg77nXUVfBnsPlFJ+pYfDQpv6/2kxcZyPtN7tZdbgGtBEsfyCCMQOBqmrO6cBADeNXdgpK7RScqqVB0xj8tRPHlz4mBmComdTECCYMBCps7C6D0JuDGAbo/yhlQ7Gd4gowfqeDfTsQVwDr34OY8F2Aeg69U0pBeRXnBvnTq2cyAJwUvF3K6UsGJk+OIna0wZXOU22DX/7cFuLf/P8dI13/n/u0Br0v95cQ4sr7uIRHN2SzcEM2Czft5tHXj7qDaMBAI3d8z3X+l/7tr7x58jwnvjBgGtLJ8rxprObvn7muE2OCg9zXCQOTQ4JaBe27Li8N3BA8gsnD69j/xj4eeP7/EfaLLawpdcKQkcy2tOpxrXMD/YlOmM39JkA/z54/13TvmoI7ENhX+8iLC8VW9lXDsHHjWRUeCI3n2VPQ/l2eo24eyQ3u/7/v3od85uDc105Of+Lqp2HYEDh3ylVmv+swMEyDhi+dUhtNiG+Q7vSX5uv8QgghxLXAAP3/soFzJ8r5+70WxoyM4H82mflruatz6RtMI5kcrEFjDfuOufqw6Vo9u/cXkzwukjHT5rG70UpBnT/TZ4QzCien84vY7X5pwLtlFeh3hhAxGvTjdgp0oNpOwSewMsQEONh3ssbn7bj4qYN/XoJhQ80snh/BjYNCWDbGyafADaYQFt9ZwW9b9fXmpGBvPjsjFrJ4fBRpM8pZ+LaNjKM1RN8dyI8eWMjzN9m5eNMElk4zMbg8nx8+V+VuquSNxvSfLGR3FKANZUywiVFDgC/Osykzn+JGJ6M+rUfHiHbzRFLvNnBx3GRmX+cAjHwvdAKLx9Wz+0sn/wI003hS72tk//ufc+4CcL2R2LsjORcylIWzhuOog2FDhxMdbeH9fBsnvugwYR07V8LO8kieDw1hOk5OHChpV7sBYPycn7J9yCnOfWcsS8e53vC6v7CCizq92F9CiGvKpXrKPtNhtMb4KdNJ/qKW22ZO5AaHE4b7c0dEONMrbV0vh3oOH6vgwjgzo2bMY2djCScGmYmd1HKN0XByrqvycvy/Mewni3h+HJz4SxF7yurQhwwn+iZXGfX3jzqvX/W9iB+y+7sNMNDAjd8byYTrDa5mrG/8nu2fwEWt62vKtuO6q+bdoJHcuziKwcc/9GEfWSn4pAe1dfVydh6rYXFsiKufs+Mn2N0+jsbg0On87hcB/KkukIXRgYCT4mMnOHEJKCjhcHQM0SFT2f6LQez5WCN6VgTTr3fw5m/+H8VelieEuHb0pllnb9cjhBBCXC2uazvAM4DWZ8G0aivLnttN2lE7H33tz+SJFu6ZYmHyd5ycLrWyZv1vWdWNzpEvnjxE7Pp83ix3ctu0aaT+eDyh+nnezMomdoe9+RfvT09WUOoO2pSetLv6dLlUQ0GZO9pVV0lBeTceNs4UsOr35Zz7QiM6Nork0Q42bMxiQ7EDfaiZpXeP4ca2e7TORlqOjQtoRN87m3uMTgqysnjoLRunB45k6X2zSZqocfov+fx001HXg0iHDIwKCSF6UgjR40zc2FhDwdF8HljzW9LKXNtx7vCfeOFYDRe0ESTfN5XpXxSy7Ff57PzEiTY6nOSI4XDyr2wrdaBfZ2Ra9GSiA8+xaUcRBdVORkVMJ3W6kYLXf8uyA3Y+bTQSPS+cyT15ExzAJQe7j9pdzXkaK9hz1Fvgsp49e08wOGwySVNNDP78PDtfzSHtpBPozf4SQlxbdPbvPsTOM/UwMpzVC8ZCUQ4/zizmxBcw5s7pLDb70g4fzuXvY3menXNfGYmOnso9pio27C53XQcGugJqXZaXkwayfctu0o5VMWxCJM8nxrBhwXhGOcpJ3/o/pJV3ngbNNMJVXoeZGTNY50SplTW/ymThH2tc1ykfrikm3cb2P57n00YDEyZHsDh0CIe63Ec+1vD2ovhIU1NOncN/KfX6Q0VpfgEFQy0sv9vC9y45KPjjPpbtd5ftVcUsW5/HzpM6o6ZM4/l7wwnVy8l4JYvkYmnYKcS1rF+eEYQQQohr0ID6+nqllPJaFbvpf/Mv/vuKJVBc6wxEJPycQ7GBXCjOZfImjwezQRa2b13IPUMdZDy3hVVl0t+ZEEJcScMmzeOvq8K5odrKwlX7ONwc+9JYuvopNoyH4je2MPst32tzCyGuffZXHgNcfY811RTz/NvR/97+djWso+8dDfNGarMJIYToT15/tpZfnETvGZh+dxSxN49k3tRA0KvI2Ou9doMQQogr64awSJZPGsn0KRZuQKdgX4FHEE0I8W3n2dSyL14cIIQQQlzLet7+Q4hOGRgVFsHSMAP65+fJ2JVD2pkrnSYhhBDeGEePZWn0CLQvHBTsz2PZYUfXMwkhhBBCCPEtNKCurk6B9yadTf+PfnjzlUuhEEIIIYQQ4oo58/KjPjXh7KpZZ1dNOjtr6tnRMG+kRpwQQoj+1KprfGnSKYQQQgghhPBGnhWEEEIIL2/tFEIIIYQQQoirjQTvhBBCXA3aBdLklyYhhBBCCCGEJ1+eEeTZQQghxLfBdSAXPSGEEEIIIUT3yXOEEEKIb5sum3bKxVEIIYQQQohvr+4+D8jzgxBCiG8yr4E0ufgJIYQQQggh2pLnBCGEEN92zYE0uSgKIYQQQgghfNXV84P0pSaEEOKbSN7aKYQQQgghhOiVvg6OSbBNCCHE1UoCaUIIIYQQQoh+I0ExIYQQ3yQSSBNCCCGEEEIIIYQQwgcdBtLklyMhhBBCCCFEk94+H8jzhRBCiG8CqZEmhBBCCCGEEEIIIYQPJJAmhBBCCCGEEEIIIYQPrvOsYt22urVUvxZCCCGEEEJ09pzQ2fNEb9YhhBBCXI2kRpoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED4Y8K9//UuB63XTTa+cbvq/6fv1119/5VIohBBCCCGEuGI+//xzAAYMGND88fze1f++/G3i+b3tuI6G9WQaIYQQoqekRpoQQgghhBBCCCGEED6QQJoQQgghhBBCCCGEED5oF0hras7Z0XchhBBCCCHEt0d/Ph/Is4YQQohrjdRIE0IIIYQQQgghhBDCBxJIE0IIIYQQQgghhBDCBxJIE0IIIYQQQgghhBDCB4YrnQAhhBDffB99/MmVToL4lvreTd/tl+VKnm6vv/a1EEIIIcTVRAJpQgghLgt5yBaXW38HuyRPt5DAohBCCCG+LaRppxBCCCGEEEIIIYQQPpBAmvjmc9rJjBvNxCfycfT7uvJYOtyPBTv7fU2+c9rJnHeZtl+I3qjJZallFps+7P6s9pdnMfaB3E7zuOO1ufhFvICtxwnsmv5BJgmRowkY6sfUDfZ+XNO3kZ1NUX74DR/N1AczselXOj0+OJtL8rTR+A0awAC/uWTWAOhkL/RjwIABDBjgx9T/6s8cefVwHElhonkuW8pc3+07lzIxyI8BwxPIvRaOZW/IdVgIIYT4RrlMgbQqtsxuumls//GLycQB6HsS8PObxZbzADq2DbMICGq56WpWX0RqhB9BC7OxAzhzSRjqfdkDBgxgQEACuU7v6fALCGJ0xFyWPpuNtabzrbA9P9F902ttP/LPKYweOpds9x1S0ROj8RufitXpZUEHlxLgN4stZ93fjyQzetCAjh/wqrJZEOC5HU1p6WibW27MvU43yI8A80TmPrKFIs9tPr+FWX5+JOxpfUerf5DLCw/OYqI5AD+/AfgNH83E2Ut5Ya+Nzu59HccyyTxS1ckUl4dtQwIpFfFkrovCeKUT028cFL20lFmWIPz8/AiwzGLpS0WuG3aDmcRtaVj2LCVl77V/C99lvnKfT8353c+PAPNYZi1MYcthe+s823baDsqmJj6dC04rL4T7EfRovnuAu9wZFERCB/u/6JmxHT9Ql21iqt8ABoSkkN/uhHMt229hdqfn4rXC+nIa+ZErSbql+/OaF69k6tE0Nr7X8TRaSBSJ88IJ6GH68h4MYPQT+Z1MoZO/OZW8gJUUVjZQuMrcPMbx3haWRo0lwK8pELSFou6cjo4iNj00l6mWAPwG+DH1116CdDVFbHloFmOD/PAbGsTY2ank1/u4fL2ITfGzGGsOwG+QHwEhU0nY4PnQ76DopWTmRowmaKgffkFjmftoJjZfl9+0mg8ySY4Z617GaKY+mou3s1l/L5WJQwfgN8/zHDSzMr+B2qKVBOxPZdOR7q37Ssh/MYWsgJWUVNZSW51DYiCARvzuBpSqJWNO/66/8+Cxjn1vKgsiRhPg50eAeSoJr3mbsors+CAGDBpLyrEeJqQml5SHsjCvyyQpFMBG9uYsHHOyqLRnEaf1cLltNd0PmhPIbXdP5yAzxo+xTxa505TJXD8/FuzyVnra2TTNj6BH8j2W68eslzoOjtuen4jfyGTyvd33fcOuw0IIIcS33WWtkabNSeeU/Qxn2nzsOxK8BDg0LKuy2DKthNQlL2Btvs9xkP9MIpvqE8ncGo/ZY/rItYXtln3GfobK0i3EePQGp8Wmc6aiksqKSk4dzSX9kak07E9iasQCMss6fxzVTEbs65N44Xgf7BBPBhPG81lk/rn9KPueTPI1U7t9pJniySpvv71n7HZyl1taT2d3bW9lRSWV5afI35yAdjiFmPgtdFZnwnEwmanTEsisiiRpaz4lpWco2Z9O4q12MuOnEvV8UQcP8Dr5W1PZcqSy+/uiL53PJOXFKhasTSW8r27Ur0JVryUQs/YU4evysFfYKVwXzqm1cSS+5n5ENcWT9oSZnGfSKLqmIy4+5iuDhZV5Z1z53XaK/J1pxJmsbJo3kaltawQYLCTleTuPWpdNPT8XXEwmyHstp33QQM8na08tJpP37S3aloktOpE4PYvM/d/gBzA9n8xXHcQsjqJHp6p/DPHzHWRvy+vwOGh3rSR9TQxed3Wf0KmschAUNhWLv+fgfFIXpVA4YiV5NjunDqYxtjiFuCc7Tms7zlp0/6kkPJNKXLC38Ta2xMeQZgtn5av5FB7OIm3RxG4FDY2WOFK35pBflE/OMxOxr1tAwvaq5uUfOFiJ5YE0Mg/mk785AfYnM/fRPN9r2FRlkzAnhUJTEpkHC8nPTic5Mqj9dHoRaSvyCbjV+08fWvBUpo5wUFl1Gc8Hb8GRLjmoOl+JOSIKS6ARo//VdRFyHExh7oO5ELeRnCOF5G1NJmpE+zRW7VzJxqqxWHrcq65O0fpUskwpbFzkPvucDmrrwTQ+HJN/53N3nxGTnkvKE53XUL3svjHXYSGEEELwr3/9S/3rX/9SFy5cUA6HQ9XW1qra2lr1+eefq88++0zV1NSo3qtU6dGa0u7NUg2dTNWwO15pWpRKr/AYWPu2SrpVU5blb6tapVRtbqIyGyNVWrHHkhpzVLy/pqI2n+l5OuoK1eopmtLu2qhOdTD3qbXhSotOUxlLzMp4V5oqafQYeXSlMvvHqKxa19fCFWal3bq69TRN8hKVUYtS6Xb39/wkZfaPUYlLzMq05EDrtDWeUmm3m1TMkjhlMsarnEaPtIxIUm97W37bNHcwXW12XOt0VKSrKE1T8bvdKag7oJKCUaZ7s1Sll2Wf2Zao4h7OUKfaLbtSZcQalWZA4W9UxhGJavPqcKXdkqTebmg/nXFRjqo9ulKZ/aNU2u40FX9XuLLcYlKmW6JU0qunPPZHpXr7xUQVFWpSmr+mjMGRKm5NjjrTyT44tS6y3XGoLU5XidEWZfLXlOZvVObb49TqfS15p8GaoZKaxgdaVNTDGaqkrnluVdiUBg2lBZpV5JJ0Veg+7qrxgEoM1FTcjtrm5Z3Zt1rFTTEro7+mNJNFRS7eqN72tkOb5h9hVMZAbx+TinvV24ynVNrtmrI8XdJqaMnTFqXdntaSn6uzVFygScXndnYWdraPa9Xbyy1KC1utCpsXcUalRxuVaX6GK480VqoDa+NUeLBRaZpRmW6PU2l5HmmuLVEZD0cpi8moNH+jMoXFqJU7Wo7xqXXhSrt9pcranKiibrcoywiTMk+JV+lFtcpbvjrg7djnJymzFq5WW71s3Y54ZTKYVWJeQ5fTttKdc6GxRKWFacq0/O3mfZoeranwJYkqyhipNtpaz1u7O16Zbo1XiXdpKnJdm9KnNkfFm0wqPrdSvb3crIzR6ap1Kedb2Xo1OHf+407HNxxKUiZTojrQdkMaD6hEk0klHWoZdGptuNJiM1Rtm0kb8hKVaYSXZeQlKiMooPU54XbmxUilzVyp0lfEqPBgozKawlXijpY9fWCZUeGev+XjUVY2q1UZczQVvqb1uajsG1WUv0WtLGoZVLLGorS7NqqurlrtNBaq1aGainyx9ZwN+UnKbIpXWdXdXWBHGlTOIk0ZFx/ocIoz6yN9ug41ObU23Esebr/ewqcjVeTaQpWzxOj1ODeVeTGvth/TVof5rvGMOrA2XkXeYnSXdeEqblWOOtN0SItWKot/jNq4e7WKHKEpc/P57MOyVa3Kmq+1zzNajMqobj1dxhwv571SSqkGVbI10ZU+zajMdyWq9GKP7a0rUenLYtxlraZMt7a+XtbuiFNauzxLm3LJ2D6vtlWRoeLC4lXW0Y0qsk0e9nl/1OWoeJOx5bro/u5Zluc0KKWq31Ybl0Qpi8l1bTbdGqOSXi1puT6sj1TalDSVtT5Gmf29nX/KfT9oVklb01SU0azicz3ziGt/W1YVur5WZ6gYTVNx2d5KzzNq412aMj38tsdyO7/P9Om+zKfr8NWppqZGffbZZ+rzzz9vflZwOBzqwoULqulZoq6uTtXX16v6+nr1xRdfqC+//FJ9+eWXqqGhQTU0NChd15Wu6+rixYvq4sWL6quvvmr+NDY2Nn+cTmfz59KlS+0+X3/9dZcfIYQQoj9d/X2kGaPY+Foqxp1LSdrwAomPHsCyLovVt/fxL7v+kaQ8EYf2Xg65bZuSenIaiVqfzoKqjSRt6Mt+TTQi740jYH8muZ5VVo5lklUVRUJ0QJ833dIMrn3Y0XL1I7nkVFlIfDLeaw0O87IMcrYmevmV2kTivkJSwzTCV+RTW5HB8qWJTK3KIfuwx9rO55B9JIAFi2MwGkDTC0nfqZFysIRT5ZUUPmsi79EENn3gmty2IY4F2xqI32Wjoa4B+/5kAvYmsODZjmoC2ck/bCVoZhThTWl0Wtm4JIWSsHSs1Q001NrJeUgj+6EUsmuAmlwSY1MouX0jhRW1VB5Nw1KUzAJ3rQt9fwpxz5RgWV9IbZ2itmgjE4tTSHg232sa9D+nMPeBPIKeOEBlXQMNpVkk6FtYEL/Je1MbQxQbi0ooKfb2sZJ5r5cj4bBSUqYxNdLSarAlcipaWQnWpp/kA6OIiXCQf7Cww2Pe+T42ErUukyS2kLTOig7YtyeTVh7Dlq2JmADrf8WwYIdG0h4btdU2cuN10hfGsanMdTwyH4gh9XwMmdZaGuoqKVxrofDRuSQfdCVSM2jwQSbplYnkFJ/iVIWN9HArKYvTyNfb56uYbtaQMC1KJfnWSnJ2daMmEL05FzyWYYohLtJG5o4ij6FV5OzMwxyfgMXLPPZdW8jzX0DiHBNRD8ZjLsoku69rw14l7McKcYwPZ2IvinYtPJKxjkIK25bhczKoVYraV2M6nrkol8KIdArttZSsM3PgyVRy3c0WY7bVopTiwBIj5hVvo5RCqQay7m2bWB3dCfi1GW6aSviISgrzinA4AUcReUcqscyM8qhV3Tv2PxdSGzEWNs9l4sgggjybd/eA471Msoo0JoZ7y5nuaep0MAXhpU6ZF1UUHrVhuV0jN34qo4OCGB2ZwAuHW9fR1P+cStKRKDatikTr5HzSDICzp1dFHevaBSx4VSdhl91d1iWh7U1gbtP1xKCBs4TMPZB2tJKS9VHdWL6R+Fx3081YjfC1p1x5puGAu2ln1xz7k1nwZAkT1+VjLy9kY0QJqfOTyG06oHolDmMMqTsLOWW3k/dsOIVPLCDVXavduDiHBnee125P45RSKKWo3OzejvpCCq1BTB1ZyNJpowkKGs3EeSnktuqf0E7mo5vgiU3E96YaZ1E++fUTiYp21zD0jyOrIo+kYI3ItSXUVmQQp9nYtHABaeejSC9uuj6YKXx0AcnuppCa5gdnM8mqTOSAvZLM+R0VFg3ot6wk/RkzeU+keGnieQX5cB0WQgghxNXv6g+kAdrtq8laZyHvyVTyIzaR+bC3Rw+d/CfH4ufn1+4z8RkvfZp5YbSMxYwNe6f9Q+sQGMPGFxdQtT6RFz7oyRZ55xeZSEJwPpm7mhKgk7cjF31+IjFeWrjo57cwd2j77fULWNDcV1tHHGW5pKzPhcgYYoK9T1N51o7DEM7EW3uzVW7BCSRG6+S81tLUwr43l8IRcSRGN90MG5m7LIlwdzMP86JEYgJtHDhoA2cRmdusTHx0E4lhrp1hvDWetEemYtuVRaG3ZjdOO1YbWMZP9BhYi8MB2tAAjBpgMBK+LIszlTnEB0LV3kxynQtIfTYGs1HDGBpH2mtZpMW6HhW1OenY7PlsjDWjGUC7JY6E6CAqrVbaNzbUyduWSeWcVDbea3E1VwsMJ+nZRMzFWeR6zTsaxhFmzMHePiaM3prA1FRSSRDG4a0fKrThRoKopLL5IcLE2FuDcNi8pRXf9rF/JGnbk9BeTmLT3i2kPGtj7uYtxJlc82ftsBH+SBqJt5vQ/E1Erkgna2sy4ZoOZdlkHgkied1KIk2ubTXHppEyp5acnR6BSMNUEp+IdDepNBLzUAKW87nkddL3lc8MZizjNXS7vWUfOK28EOnlPBoaxNKDrkn65lwwk7AkhtpdmeQ19Sv1YRaZRRNJWOSlTHNaydxWiHlRIlEaEJZIQoSNzG3eg7bXOrvdjmYK6l0/hoFBmLVK7PYe7KFb4km514wGmOcvYGq9DVsq/ELJAAAgAElEQVQ3X3qgl+WQV2rEEtrmeGqRpO3dwti9UQQM9cNveBRZ5i3kPBve/XR2oLKyEr0onfTzcWw8mE/usxZKno0jaU/3Qml5DwUxYNAAAiJTqVyUQ9aKDkJ9Vbls3FlJzCOdB5CbOSuxV4PttS0URqSRcziPjdFVpC9MaOkvtD6f1OX5RG1IJbLTgKoZi8VIycGcbvfR5kpLIZk7bYQ/lEbS7U1lXSJpD4VjbyrrDKChE74olahgo+t6cdno5O/KoWF+KhvvDcc0wkLc2jQWOPPIcv/oQGAMq9cnEXeXBbPJRPi9KSRF2iks8vEHPkclVfWVZL2Yi+mJHPIPZpBgyCVh0QvNfbvatyezybmSjYt71xjaXmbDYQpnYmdBxOO5ZBUFkPjsanfzUg3z/DSSZrp++GjOxfUW4p6MwxJo7DTQChqWFemkjsgh5cmrqYlnF9dhIYQQQlwTLmsgTd+T4HpzVauPH2OfKepiziqKjtpghAmKc8g/720ajchVByixlrT5nCLniY5/Ufe2nM5vzlyMsRvZOL+KjQ9vwtajvlO8MFiIf3AiJTsyXTeyNblk7jcS/6D3TvI1UzzpxW23t4SS4i3Eec5wPpO5AX74DW35BIQnUWhOJWfHSq81YfqekbhlC9AOZ5J1FsBO7u5CLPGJRDbtb0MQ5hCPpxVDEEEmqKqoBMcpbOd18h8JatUZfNAj+ehVduze7pL1KmrrNYyBHjvDEMXK9Qnom6cSFDKVBQ+lsmlPEVVNDw42GwSbMXskwxgWR/z8cNcx0O3kbU5k7vjRjDaPZnTIaOJeqwSn7iW4YcdWruPYtQA/z07sx6dirbd3EbDtH8bhJnDUumrFtOXjPtZuT2PLE5C2MAXb/Aw2xho95tcwB3s+eJuJWhxPVLAG5aew1VtJHd/6xRgLdjlaB7ZMFsZ65t8RJldAsLKPwkdOHQZ55jMLSdleziNrIWkz+2aVTYyxiSwwHGju68y6Iwv7zEQSvPRLpB/eQvaH4SQ80BRscQfi9my5umpY9BHdqYNB61n/aM00MLhrhXXX8CCCmsoifw0NnVqfs5zd9dIHSzIlEWmkxbbZCqeNzCdTKYlI5+3iEkoOpTPVmsSCtZ33q9ddOlGkbE4k6lYLkYs2kjYf8vZ0ow8zIGptPqeshRzYmgA7k0nd6+VVAPVWXohPwjonk8wl3Qmy6Ojjk9iyIorwW8OJezaNhMBCcvfbAZ38Z5PJm7aRtLu6ygUaMc+kMdWawtihfszy9uKFztTYsVdpmNsEPINuMaPV2LE3nV8GM2NDrkS/ZnZsdh2zxdJyPvhbsNyiY/+wqaR0YN2ewoJpExltDiJoZDgpR3VXLUFfOAF0zA+kkzY/HEtYFCvXJRFelkXOB8DZTJLXQ9KLib2uNemoroTAAIyd1di1n8KGBUurF40YGXtLUOvrQ6AZs4+1+jBYWPlyCqa9KVdVB/+dXoeFEEIIcU24zC8b2EiJ9RSnWn1KOPBoZ7/K69h+nUBSUSSZRYVsDC8k6cEtXoNXfsPNWEItbT5mzIG+3QhXFRdiYywWnyJLRuLWbyTmfBqJv/by9kqD1kFwBfT6BtdwL8ky35tI1PlsMo/qVO3JJN+SQGJYB0kwBGBut70WLLeYWi/aFEdmccv+zllmQRsxl9TNq4ka0fEWBoWaMTqtFHZWE6gbN4JadCIJIwrJ2mWDsmxyPphK4mKPnW3wskNaLb/pTWeq9aer5jJtbt7NizIoqbCT/2IiU/3t5DwZhSXS4+12HW6TTv4zc0ncoxG/q8TVIX35GXKXdfyYoQGm5W+3T7OqJSPWywzOPJaODCBguLdPEAte8/JQGxhEEJU4qtu8bbXaVVMtyNeHDneKu97HDirtVWj+GpUf2qhstb90Om4s7AdaFOkVbfeFoqFoZccPa03L73FH157LslJoBWOopdWLSoz/P3v3H+LEnf8P/LmQwgRWmHBbmNxtjx1RcBYFs1RoQvuHkS2YxYNNsNCEFurYQs0qnJsWTnP+4UUPbNaC3ViwTgUlK1Q2QsUIHzH7hyUpWDYFy0ZQnP2ee5dAtZu2e93puXfv7x9Zd5NNdhutP1b7fMCgm0xm3vOeeU92Xvt6v99qo3akQpm9JB9aW5C80F93InMiCXMqA+N0GT1v+Rs8YJaQ/GQYppVH1DUfAFd3pFG+na7KWn12yLITVrn86zJHrDImp2Q4HyR96FddXyrC/zeN6auD6LoSRfTcgjYwkkBsxIXI4UqQS9uoI77HC/PjwQYzsT4Yh+yApFT/EUCCU3HAuj2JyfvYjqRo0Na64Xt7EIl3JCQPGbXd0K0CEsEADCWG80d8zWcQ2mQ4HBLkVep892ibAvUFoFgsAzCRu2yi8ElPZWZTux2BE2VYF/rgdIQwVJN5ZiF9MIrsujjGfpzGpcWy5h7A05LtWTqtw7cvD22XgUuX88hfySD2itT8d7JcCWzV/OGj3QknJlH6FkA+g8x4BpF1sxm66yLITRUwsNGOrn3NZfk/EjYJ9vtZf+1eJN5XMLw7gtTtBWfXZocEwLIanPUZC9YUYH8Y3ztERET0zHm8XTtbndDWanWLqiz+0FMeiSK0v4jQsQT87Sr0Ywn4rkeh/z3/cH/hLWcQP5yBtDmIwBLBpRptfiQO+1A6qGPgem1cTFunQRrPIlPXNaiMzMUc0LFIN4c2P/ReIH3agDE0Cs8boV8/ho7NAWWVCnWVCnWVBt9BA9G2JMI7DJhL/NItvRJEoL0A42CjwKWFwsc9cK7rQ7rZJ1+bG/qbLuRTSQydHEZhYxCBjupNmjCvW7U/TwCKqgJyJ7R2IJ9f0G3ldgmlxbr2SAocrRbKt2sLaN0uw5IUuLbo6D+cRPZyHF3XEhgaAVRNA8bHaroLWV8PYeDDNEyYyF0pwrmlD/rcbHImRr9eLKihQlstoZzP186MapVRKi1y9T7IGGmyC561FrKXqx9uLORH8rDWe+CuetItf1uae4Cq305zdVw6E0bfORfil4cRuhVF34eF+c8rQOFa9dGWkPloAENflYHVKjSMIX+19tjLE6Xav8yXChirPmXjJkyoUF/49Zkh5icxGOMqQm967utzD7MtuN4MoetKCkOnhpCWqrs2V7mWhHFRQvDYaN0fHobfdiJ7zJjrfvWs6FynAeZYg3uSBEkCqp91i8VFOkXdKMBs+o8hD0LC9BJfPNLaAHzrygvaAGCVi3UBQskGwLLqslKscgmlUvm+v99Ul6uSTTX3QQvF0iTQ5qiduXPGQrlUQrmZLpF3AUxNz2f4zZgw3uzBAPpx/lMd6mJBBquMUmlBu4YK1xonyuPm/My1MyWYRcDplAFoCJ+pXOP3skIHe2VIG6PIXBmAv6Zbu4lCoYyuLYHa2VGb1aZCVay682ReMwHlPjKeHgK7BFh1F5UKTZVQKFT9kW6qgMINCeqqyjADY5ezsDb3I7rVBbVdgdJmoXirwQ5sEjAzXZ+l2VrJ/iqOV9VBqYgiHFAcALoHMFaoytD9fC9ckgr901EM77q/BiY/7wRuL52BJa3uhIaF3alLGLtRhLRa+1W/B7neSyCiDCPyfgbl6tvtbB2MXs7UB/BvpHH+hgTN1fkr9tzYkt/DRERE9FRY3mOklVIIbzOAnQbi9wapVfxIHA2hfCiEyMXaX32myyWY42b9MlFCufr3VGsSxYkSShMlmNfyyJw6gNDGABKWH4nDesPBxBcj9w4gvqWE2L5UzXgXcm8E4bV5xLaGMHA2h8INE4Wv0jB2+aCfAvz7IvNdGmtI8G3zQzoXRfyGD3rvEqWZmUSp0fGOm4sHagBAcmHvJzF0jkSwvVE23dx6XsSO9kPN9cG7sQ+JsznkrxWQ/yKFxA4vvLtH0bUrDG/DlITKw29x3ERpar6rlfaGDu+NBMKfFOF7I7Cgri1kPo4hUwKAMvIfJTA85UJgs1oJwm1zwfwkggMjpUre03ga0V4Nnt2LdF2ydcKlAYWro/OvXRuAd7UHfSfys9eEBfNKAUWoUF8AlC0h+KUUYntSKNy2UL6WQvTdMOJ5Cw44oTolFL/OID8FYMpEek8E6WlnZZyyuoqU4H1Hh/pVHJGP8pWHiKkCUru90LpjyDWs+AcYIw0aQrt8mDzRj8iZPEq3S8ifiSB8YhL+XdWB2BLGvilC1rTGg4M3U8cTQwjvzsB1MAF9rRexIyEUD+o48JUF2NwIbdNQOBrFwBcllMsl5D4KY/ueJEybDKwJQu+2kNwXRepGJXOt9MUAQm4X9FPVmXajMA6mKwGBqQKMI0MwV/nRs75SP42uq3oWrKKJ0kQJpQkThS9TSOzaBM/uLLQ9BmIvSTXrlouN25E5MRvQ+FVtYYFVIQQ3jiK+7zyU6q7NVeXJHUsg3x5C3+vabAB8PhDu36VDu2EgUT1xx9Tk4mV/SijdXnjGc8guTLq0dcK1zkLm3OyEH9cMJM41jliWchmY633wNfvHkPukqk6Uc2lkShYaJbHMDQ2wIDAibfDCY0sj/v4QcjdMmF8OIXIoDbzig7umTVtI71DhXB1GukHAtvRNAfmvTZRmAKtYQP7rAszZe73cHUJASiH2/hDyN0zkz0YROwv4ehcMDXBtAN4XnPB+WBswt0YOYPueBFIXc8h/lUP64z6EPy5A7e6ZHQOthNS2TYgUvNi7xwPrWh75r/PIf2PW3X9LJwJQX/Agern2dc+bfqiXD6D/4xwK4wVkPoghWfLAv7lyl5I7arPKnTIASanPsgYqbb9RFnMzbF7o2zQUjkWR+LpS+vI3BmKf5ivfUY8twCFDW6uhcC6J9LUSSrfvtVkJ3tcDcJyNIXI6D3M8j9S+KIZtPoRmfxdSVRVWPjM7mYyF/MdRGDfqL0q53QnneA7pr8uVa3Yuw9eFUNCF/NEIDlwswLyWQ2JPAvlVfgTWA2hVoK6qytBVHZBslezdZrP871HXaJBLBYwt1SV9bRD6K5Mw9h9A7nblmMwzMQyMOBF6y/frunzbXJUunmf6kbhS+3rf+z7gdBiB9w1kvjZh3iggd+YAAr1RFNZGEHu99reURr9nlqoz3Rr9XlbzO+gvfA8TERHR0+HelNXff/+9KJfLc1Naf/fdd+LOnTvi9u3bD2Fy0KIY7JaEtDUplprwe/qzoJAkrxi8JYS4OyYGu2Uhb4yLsbqpxKdF9j2XkDqCYrgoZqclr5/mfX6RhZ6eL0fNezZJKGvcwv/ecTH67cL91Brb7xLSxriom/y8OCyC7ZWp7ZM1M62PiuPv+YV7jSJkCUKSVeHarIv4/xVrP58JC7XVL5I/zu1JxF6ShLrz0nx9pXUhy0ExfHe+LIsfL4T0cqWcS03HfvOoT8itLtF/eXYvtwaFV6qfUn66MCxib3mFq6MyXb3UpgrXlrAYzBTrN1pdX8f8QpUlIXf4xXFzrlLE8OuyQEdYXKreTa5faK1usfdkXARfUoUiS0Je5RXhoeraLopLh4LCvUoWUqskZEUTvp3HxdiPYlFjB91CWrtXjFYd/83P9gr/i6qQWyUhtcpCfdEn+ofG5up68spxEe7WKu+3qcL79qAYnbxXF8eF/pIipFZZKGu8Qj82KiavxoW3XRLymn5xafq80Nsk4T85fyHc/Hyv8L80uz9ZFa7evWL4+lIt4UFMitFjYeFdIwtJkoSyxivCn47Wtrdvk8Lfpohgaql9L1XHN8XxLYpQeo+L+TM/KS7t1IS0vl9kfxRC3L0pzv/VX7lWJEko6/1i7+dV53ByVAy+6xWaIgmptVJO/UhW3Kutm4fcQloTFsePhYV3jSLkVlmoL+vieH6+zI2vqyqZsFBtC9pD22zb+/xmbZ00WLdmWdCmm2oLd0dFbL0klJ2X5up0sFsS2l9G57fzuS6U1tl7XeXIRfxlSbgPjgkxOSyCiiTch8YWPUfHN8tC7k2KYqN72r2ldf5+sRz8v4l//sIaRXF8iyK8R+rusGI6Pyj8a2UhK5X2E9/pEtKW42KyZq2bYrBbEd6jC+9LlftpXf3YVBHOzH7ysFtI3YPz1/XdYRFs1UR/bmERz4u93ZqQJQig/l4pxKQ4vqX2XM999P9iIviSWvkuaFOF+/WYuFR3C618Hqv6RXbhubt7XuhK/Xl2/XV+X5NXBoX+sipkSRJSu0sED11aUEdCiMv9QrXJwvfpgp1fPS70LS6hKpW2K3e4hP8vw+LmvUO8OyyCcqPrrPq7a7bGD7mFJLlFvLBw59Ni7GTVfWq9T+z9fPHvkfNvyw3Os5hrY75P696ps+h1d7cozu+v3OvkVlnIq9wiuP+8KN6r9/xe4Wp1idjVB9j2nMr5dO1frC0LISazIrZFE7INApJXDJrznx09ogt3hywkSRbqS0ExmKs63h9HxfG33EJVFKGucQnfn4+LWKNr7+5NkXzXLVS50gbm70uV987/xSdciiQkSRZad1gkC4t8P1yPC3ejNlFl0fr48bwIKnLN96K4mxX9qyThPlzV3r/NivhbXqEpspBlWagv+kX/Z/PfzTePeIXUqG3UHO+wCLYqQv+/hW9Mi9H9biEBQnsvW/P6zXRc6JtdQm2T5n4nDP4lOfe9P7/dRX7fmr13LPp7WdW9prnv4eXp9u3b4s6dO+K7776be1Yol8vi+++/F/eeJX788UcxNTUlpqamxL///W/x008/iZ9++klMT0+L6elpYVmWsCxL/Pzzz+Lnn38W//nPf+aWu3fvzi0zMzNzy3//+9+65X//+98vLkRERI9Syw8//CAA1IxXtPDn3/3udw8rbke/dTMFDGz0IPlqFqN/reoe8mUEnd1Z6Pks+lct/vH7NmGgx3UAzpNjOL75SQwavXyYH21C11EX0vn4L8yI9+SYH3jQ+akXmauxRTI26Wn1j3/+C3/8w++XXMcaiaBrt4TklRhc93v+v46i6/Uy4lcG4X2Q7n4PhYX0NhWhUhTZz8L33+3QSmO7GoK5ZxSXdj68cb+qmR960Hm0C+fzj6qeyhjyO9EvGSgMBX/dLKyLsG4kEHDH4DxZxPHNS6/bzHX3oB7ltp9Gi9eHhdz7XfB9pWM0s8R4mL8BT8P38GLu3LlTMxERgEV/bvT/pf5t9v9LvfYg6xARET2o5d21k54p1pSJ9D4dsQkfou8+nrlC0a4j/r6C4X0x5J+mfm4PW2kI0cMmfAejT90v7/TbIW2MwtjhRLHBnBq/pPStE+Gj0ScYRAMACd5dUfgmB+B53g7PB/c5KcQ3WWRbQ+h/61GFGsrIXTbh2dH/6OrJyiJzRYO++1EE0UwMeO1wbBjA5OYowg95Vl16VCS4348jcCuO6OkHaNzPCn4PExERPTOYkUaPxxcRrOxOYHqNH5GPE+h/acEj1qPKSAMqA2S/tgmJjuPIHPY+kgyJZW3GhOHfhMSq5X/8zEh7djF7h54EZqQ9Pr9UH+WRCLzbCtAvnEd4zWMs2HLwFH0PL4YZaURERPMYSCMiokfuH//815MuAv1GPcpAGtViYPHZxUAaERHRPOZ8EBHRI8cHbHrW8JomIiIi+m3iGGlERERERERERERNYCCNiIiIiIiIiIioCQykERERERERERERNYGBNCIiIiIiIiIioiYwkEZERERERERERNQEBtKIiIiIiIiIiIiaYGtmpfHx8UdcDCIiIiIiWo5WrFjxpItARES0bDQVSOvo6HjExSAiIiIiouXozp07T7oIREREywa7dhIRERERERERETWBgTQiIiIiIiIiIqImMJBGRERERERERETUBAbSiIiIiIiIiIiImsBAGhERERERERERURMYSCMiIiIiIiIiImqC7UkXgIiInn3/+Oe/nnQRlp0//uH3T7oIRERERER0nxhIIyKix4KBo3kMLBIRERERPZ3YtZOIiIiIiIiIiKgJDKTRs2/GhOFfia7dGZQf+b7S2P68HYFTj3xPzZsxYfzpMR0/0QOzkPsggM7n7WhpacHK3bnKy19H0fVcC1paWtDiCCE182RLSUREREREv22PKZBWQuLVysNRo8XuM1AGYJ0JwW7fhMQEAFgofLAJDmcPEtcWbG4qh+gGO5yvDcEEgJkUQisab7v24au+HHaHEys39GD7viHkby99FIW/daGlxQ7P3/P1b34RwcoVPRiajVTkdq+EfV0U+UYPfRe2w2HfhMT47M8jfVj5XAvsGw6g0LD6hhBw1D5EVsqy2DHb4fl7YfH1nrPDoXahZ0cCuepjnkhgk92O0BmrZvfWNykc2LYJXaoDdnsL7M+vRNer23HgbAG1a9Yqf2nAGCktscbjUfgghMitIIyDXshPujCPTBm5j7Zjk+aE3W6HQ9uE7R/lKoEzmwr9WAzame2InH36Q2m/eF3Ntqe5691uh0PtxKbXIkhcNGuv2YXrLnJvuqeptjCTxwGXHc5dmdkXZu87zzkRWqT+c3s6a9ptjWsD8Nhb0LI6gkxdg6ts2/7a0JJt8akwYSC6vwDfSROTk9MYO+iuvL4+htG7AuJyP9RHuf+ZHCKaA6Gzi7x/O4fEO5vQ6bTDvsKJzlejyEw1WK+cQZ/WgpbntyPNoB8RERER0TPnsWakSZsHMWbexM0Fi3ky1CDAIUF7L4nEK6OIvnUA+bmnxDIye3QMTOkwjgarHqwkuPdn67Z907yJ4tUEfFWjwUlbBnHzVhHFW0WMXU5hcIcH0+fC8GwIwLi29OOopMgwD4Vx4OuHUCHVbArkiSSML+rfMs8YyEhKXR1JShDJ6/XHe9M0kdqp1a5nVo63eKuI4vUxZI6EIF2MwBdMVIKRiyhf6IPnlRCMkhvhoxmMXr2J0XOD0NeaMIIeeP+WW+QB3kLmaBSJkeL918XDNGEgcriEwP4oXNKTLUpTZvIY+ij1i0HdhUonQvDtH4PrYBrmLRPZgy6M7fdDPzEbcFKCiO1WMbwnhtxTHXFp8rqyaehP36xc74UxZE7F4FfyGPhTFzwLM/NsGsLpRu2o9t704G2hQlGA9Ilh1IUArQySZyahKI2PN3fMQKFbh99Kwjj39AdCFzVhoggXPBsVyLIEaTm115kCEkEfYgUX+j/NIHsxidjrXXDUrVhGek8EBacLy6n4RERERET08Dzerp2tDqgdat2itC32yKEgeCyJ0FQMofcrD7/lsxFsPyUjeioOX1vt2nZZabz9drn2oUZywNmuQGlXoK51w/fWXiQvp9GvpNH3dqJxVtg96/oQ6y0hvvNA42yzB2XrQs9mC8lP07UP4zMFDJ0cg2ezp/7BzOaA0uB41Q4FSuuC9WaPV2lXoHSocG3ph7HfB1xOIT2+SJmm0ojuSKDYbSCbjkHf7IK2SoX2kg/hw5dw6UgAzuIYzLp6KMH4kxOh0yXkP/TC8cJ2fBTtgn1134KMmhKMPzngCKZQ/iKClSs24cCZAwi90oXO1U44V29C34nqrLcSMh/OZl2tsMOhehDYl2qw/3mFUwYyShDh7vnaK3+VwPZXO+FcYYd9hQMrNwQQPTcfTrS+NtB37/3nO7Fph4H8XOZJGbl7ZZjNSPJsSyC3RHzDPBdFwL0SjhV22J2d8Lw5gMyiCVUSpq/E4Vu9Ep43D2Doi1ITmUYFGEczcL6dQLzXBaVNgdYbR+JtB9JHjbnrWX1Dh/d2EoMXltriUnVcRmZXJ+yuaFUwzkTiVQecfqMSIJopIf23wGzGlgPODQEcuFB1sOU8jB2b0Ol0wL7CAaerB5FT8+e48Pcu2DdEMPTRdmza0InOF5xY6Q4h8WUZja6rxTN+JEhOdf56f9mP8JFLyB7zofjRdkRq6kCC7GzUjqruTQ/cFuY5u3vQddlAckGGbfmcgWHJi55VDT5UTmPw9CR8b8UQ7rUj/UlyycD3U+mrKDqfa0GLewCFqSEE7C21XTubYRUwtGsTOp+3w+5wouu1AzVtzDwXReCVTjgd9kqbDVa9P5NDVGtBy3MeDFwrY8h/L5PxXnY0YF1OYOCqDwNn49A3u+F6yQv/W364WmuLUT4XQXRcR/yNR5o7R0RERERET9DyHyNN9iJ+Igr51HaEPzgAfdd5aAeT2PviQ/57f6sbkd1+SF8NI7WwK2m1GRneQ4MIlOIIf7BkyO0+SXBv9cNxzkCqOsjypYFkyYtQt+Ohd92SbJU6XGy71kgKwyUN+vtBNEqWUd8+juGjOrS6uV8V6J9nEV0vwfXnDCZvHcfO7To8pWEMXaza28QwhkYcCLzhg2wDJCuLwVMSIhdGMXa9iOw+BeldIQx8U1m98IEfgWPTCJ4uYPrHaZjn+uA4G0Jg32KZQCYyF/NwbvTCda+MM3nE34pgdP0g8t9OY3rSxPA7EobeiWDoNoDbKehbIhh9MY7srUkUL8eg5foQ2JWudD8+F4F/zyi0Q1lM/igwmYuj60oEoX2ZhmWwvoig5800nLvPo/jjNKavJhGyEggEBxoHbG0a9JNZFAvD6NNMGG9oUDcEEPk4A7NRNzIAKOcxek2Cx63VvKy5PZCujSJ/L8jX5oVvQxmZC9lFz/nSdSzDe9BAGAmED+ZhATA/6UPsug+JozoUAPm/+xA4KSF8poDJbwtIBS0MvubHwLXK+TDe9CE64YORn8T0j0Vk92vI7upB34VKISWbBHxjYLCoY/jKGMZuFTDoyiPyRgwZq/668t3nvMPK61H0rS1i+HT6vtrTg7eFqm0oPvjdBRgnqwNEJQyfSkMNhqA1+Ix5OoF0awD6ZgXebUGoOQNDDzsb9kl7MYaxuwIi1w+tNYjhuwJCCNw87G5yAxZy+wLQLyrovzAGM5dEoBxH4B1jLvuvXLLQ9c4g0ldMmLnjCFjG/Ps2N2IFAXE3i/41MoKpyv7F9CWE2yufN7/IYnJDJ3CkB10vOOGs7jp9z+00IntMhA6HoXI+bCIiIiKiZ9byD6QBkF7ci+RBDen3o8hsGIDxbqO/9lvIvN8Ju91et3TtaTCmWQOy1gkVBZhLpnxYQJsP8cMBlA7pOEqnBfwAACAASURBVPDNgxxRY3a3jlBHBsbpewWwkD6ZgtWrw9dgcC9rIoGeFfXHa3cE5sZqW0z5WgqRQynA7YOvo/E6xXETZZsLXWt/zVHN6ghB77YwfCI19/Bpnk0h2+6HPpctJqPn7fBclof6ug5fWwHnLxSAmRyMY3l07RqAvr5SGfLaIGI7PCicTiLbKBNoxkS+AGjruqpenES5DEgrHJAlADYZrreTuFkcRrANKJ01kJoJILrPB1WWIK/xI3YiidgWJ4BK9+SCmUF8iwrJBkir/Ah1O1HM51Hf2dBC+piB4uYo4lu1SkZhmwvhfTrUK0mklrp2FBeCfzmOS9dNZPZ4YJ3rQ5faib5GXftuF1GEE/LztcFl6XkZThRRnOsmqqBzrRPlQqOyork6bnUj9kkY0sdhDJxNILKvgJ4jCfiVyueTJwtw7YhBf1GB1KrA/edBJI/2wSVZwLUhGCNO9B3sh1sBAAnqlhgimycxfKoqEGnzQN/tnu1SKcP3TgjaRArpr5aor2bZVGjrJFimOV8HM3kccDdoRyuc2H6hssrDaQsqQm/5MHnaQPpeUPRGEkauC6HXG9zTZvIwjmWhvq7DKwFYryO0oQDjWOOg7W/WTBbJMya8uwegv6hCWePF3v06nCNDGB6vrOJ6O469b3jhWqVAWeVF/04/HLkMRpusyGKxCCs3iMEJP+IXMkjt0zC6z4/wmXvtsYzU7gjGgoPoX/MoDpKIiIiIiJaLx/p3c+tMCPbnQgtelaC9l5kfWLqhEnKXC0C7AlwZRmYiiGD7wnUkuN87DyPorHtdalv42lIkSE3UirwljnhvF/R3B+Af6W+YTXLfbBqC27oQP2YgvzMGVzkF45yM4AUv5OJQfUmVIAYvRuFZWF6bA2p14G3CQI/DqFnFmpHh2hLF8OGHVPZfJMP/dgD9rxlIjgcR7jCR+iwLLTgI973y25xQV1cFg2xOOBWgdKsIlE0UJixkdjjRsmPBpiUJZhnAgq6+sEqYnJIgt1VVhs2L/kMhBHZ54DzpgnejF57uHoR63VBsgFkoAB0eqFXFkNf7EVx/b5sm0keiMM7lKxliNmD6dhFYYzUIbpgoXLdQ/jIA++n6+ugyAfxSYMYmQ93ggSc/iuyVFMzSrwuhyM8rQHkS5RnUt/7yWFN1LL0YQ2K3B57XIlDfPo/sFrnq8xLUjuqgkArvvW5u58ZQmMojt64F0YWbf6kqsKVo6Ky+ftuVSkCw+JDCRzMW8Fz1daYhPDSM8MKGYJPgqLvP/DryFh2BPSEY58rwvS4jfzIJc2MEoXYJxoJ1rYsJDN1wIfyma/aVSiAutjuB1H4vgguv99+qsgnzthOaVpUruKYLGlIomAA6AIyncWB/AsO5AspT05ieKaNk+SrtoEkWvIgc0eFtBbA2jtjFYYTOpFHeGgTOhBG9HkLy2OO5mxIRERER0ZPzWANp0uY4sod8dWN9SW1LjSdjofBhCOGcG0YuhskdHoS3JeBKh+u6UdmfV6GtefCxaUpXsiigE3pTz0Iy/IfiGN6gQ//Qh8zCOKBNAmYaBVcAa2q68nqD3qnqVh3efVEYl6OIXjOQ0UKIrwcaphDZHFDXaEt2JwMAKH4YI7HZgJWFwtEQAue6ED2yF96GA5xXONeokGeyyH4F+F9eZKVGAZlFSN06Qu1eJE8XEO5NYfgbD/RTVZVta1AhNQ+6EoKfTSK59T679S4on/r6cYz2xpC/eB6ZkQyG3/cidqgfwyMx2Ov2Wc1CZk8P9AtuDJ4dhb62Eu3Jvd8J7+XGn5AAKDsvoXjEe39lhgVzJInExwkkL5ahbtEROTsA/8sNTlibE04UUf7WQvVFZX1byVRz3lfApZk6LqNoliC1SijeKKA444U8V8fW7NLo83ZA8mLw+nyXuYUaJoPeOx8P4241k0c2D8gbtZqJSmRVg7ZEJtFDawuSF/rrTnhPJGFu0WCcLqPniB+ybWEDLyH5yTBMy0LUZa8JPFpTgHHaRHAnx+Fqykwe0d4AUuviGDwziM42O5CPwfNa8xOhOGQHJEWtCrBLcCoOWF9OYhKAmcuh8FUKHkds9n0LlgUEHBnoqZsY7H7Ix0RERERERE/MY55swAltrVa3qMriD+3lkShC+4sIHUvA365CP5aA73oU+t/zD7d7UzmD+OEMpM1BBJrNQmnzI3HYh9JBHQPXa0MH2joN0ngWmRt1O0LmYg7ocKGrUYCjzQ+9F0ifNmAMjcLzRgi/+nHZ5oCySoW6SoW6SoPvoIFoWxLhHcaSg6NLrwQRaC/AOJhAoW49C4WPe+Bc14d0sxMJ2tzQ33Qhn0pi6OQwChuDCHRUb9KEed2q/XkCUFQVkDuhtQP5/IKRxW6XUFps7DBJgaPVQvl2bQGt22VYkgLXFh39h5PIXo6j61oCQyOAqmnA+BgKVdu0vh7CwIdpmDCRu1KEc0vfXBANMDH69WJ9gVVoqyWU8/naAJFVRmnRzLISMh9F0LPOia4dKVjuKNLXbyJ7ci+CLyuNZwKUXfCstZC9XN2F2UJ+JA9rvQfuquyu8rclQHZUBb6qt9NcHZfOhNF3zoX45WGEbkXR92Fh/vMKULhWfbQlZD4awNBXZWC1Cg1jyF+tPfbyRKk2M6hUwFj1KRs3YUKF+sKvHxfR/CQGY1xF6E3PfX3uYbYF15shdF1JYejUENJSddfmKteSMC5KCB4bxVh+rGoZxfDbTmSPGQ93spOngU2CNFMJUNWQVahtRRQKVYNLXhtFASo0FUApi9wNF/Q9YXjXqlAUBdLtIiYb7sSCNVPfNlWXC9JtE6Y1v16xNAm0OeAA4NlzCTevjmI0X1my+72QZD8Gc5cQfeUhHDsRERERES0by3uMtFIK4W0GsNNAvHs2GqD4kTgaQvlQCJGLtU+t0+USzHGzfpkooVz9bGRNojhRQmmiBPNaHplTBxDaGEDC8iNxWG84mPhi5N4BxLeUENuXqkkak3sjCK/NI7Y1hIGzORRumCh8lYaxywf9FODfF5nv0lhDgm+bH9K5KOI3fNB7lyjNzCRKjY533FwiUANAcmHvJzF0jkSw/cPC4gFJyYvY0X6ouT54N/YhcTaH/LUC8l+kkNjhhXf3KLp2heFtMH4bIEGSKmNLlaYsWLMP/dobOrw3Egh/UoTvjcCCuraQ+Tg2O5teGfmPEhieciGwWa0E4ba5YH4SwYGRykyW1nga0V4Nnt1pNIxf2Drh0oDC1dH5164NwLvag74T+dlrwoJ5pYAiVKgvAMqWEPxSCrE9KRRuWyhfSyH6bhjxvAUHnFCdEopfZyqzeE6ZSO+JID3trIxTVleRErzv6FC/iiPyUb4SLJoqILXbC607VjXzZZWZMeSuSPAfGUWxcB6Df/bD9YsZZRpCu3yYPNGPyJk8SrdLyJ+JIHxiEv5d1YHYEsa+KULWNDTs7NxMHU8MIbw7A9fBBPS1XsSOhFA8qOPAVxZgcyO0TUPhaBQDX5RQLpeQ+yiM7XuSMG0ysCYIvdtCcl8UqRuVzLXSFwMIuV3QT1XPsDEK42C6ErSYKsA4MgRzlR896yt12ui6qmfBKpooTZRQmjBR+DKFxK5N8OzOQttjIPaSVLNuudi4HZkT5dns0V/TFhZYFUJw4yji+85DCeoN7gMWcscSyLeH0Pe6NhsAnw+E+3fp0G4YSFRP3DE1uXjZnxVrOuGSshg+kYdZKqN8L7hr8yC0VUXmcD+ML02UrqUR3Weg+EqwMv6jrEKVTWRzswHeiTSiRxrcM2yVe0D+QhrmgmtL7g4hIKUQe38I+Rsm8mejiJ0FfL1eyKhkVatrNGizi6rIgM0B5xoVS/ydiIiIiIiInkY//PCD+OGHH8T3338vyuWymJycFJOTk+K7774Td+7cEbdv3xa/XlEMdktC2poU00usNf1ZUEiSVwzeEkLcHROD3bKQN8bF2N26NUX2PZeQOoJiuCiEuDssgq0QwGKLLPT0fDlq3rNJQlnjFv73jovRb5c+irH9LiFtjIubdYc3LILtEJB8IjlZ9frkqDj+nl+41yhCliAkWRWuzbqI/1+x9vOZsFBb/SL549yeROwlSag7L83XV1oXshwUw3fny7L48UJIL1fKObbfJaT2sLhUV4dC3DzqE3KrS/Rfnt3LrUHhlSQR/Kz2LE0XhkXsLa9wdchCskFIbapwbQmLwUyxfqPV9XXML1RZEnKHXxw35ypFDL8uC3SExaXq3eT6hdbqFntPxkXwJVUosiTkVV4RHqqu7aK4dCgo3KtkIbVKQlY04dt5XIz9KBY1dtAtpLV7xWjV8d/8bK/wv6gKuVUSUqss1Bd9on9obK6uJ68cF+FurfJ+myq8bw+K0cl7dXFc6C8pQmqVhbLGK/Rjo2Lyalx42yUhr+kXl6bPC71NEv6T8xfCzc/3Cv9Ls/uTVeHq3SuGry/VEh7EpBg9FhbeNbKQJEkoa7wi/OlobXv7Nin8bYoIppba91J1fFMc36IIpfe4mD/zk+LSTk1I6/tF9kchxN2b4vxf/ZVrRZKEst4v9n5edQ4nR8Xgu16hKZKQWivl1I9kxb3aunnILaQ1YXH8WFh41yhCbpWF+rIujufny9z4uqqSCQvVtqA9tM22vc9v1tZJg3VrlgVtuqm2cHdUxNZLQtl5aa5OB7slof1ldH47n+tCaZ2911WOXMRfloT74JgQk8MiqEjCfWhs0XN0fLMs5N6kKDa6p91bWufvF8vB/5v459Ir5PqF9gtlvnlSF26lcrzKu5fm35geE8mdXqG1SUJqVYRra0xcqjolxfRe4VujCKVDE9rLQRE/EhZazT23YvJyXPjXKkKyQUCqPj9CTF4ZFPrLqpAlSUjtLhE8dElMisYmT/qF1KaL80scyy/WBxHRMnL79m1x584d8d133809K5TLZfH999+Le88SP/74o5iamhJTU1Pi3//+t/jpp5/ETz/9JKanp8X09LSwLEtYliV+/vln8fPPP4v//Oc/c8vdu3fnlpmZmbnlv//9b93yv//97xcXIiKiR6nlhx9+EAAghJhbFv78u9/97tFG8+i3Y6aAgY0eJF/NYvSvVeOjfRlBZ3cWej6L/lUPcX8TBnpcB+A8OYbjm3/bqSHmR5vQddSFdD4O9zKtCvMDDzo/9SJzNbZIxiY9rf7xz3/hj3/4/ZMuxrLB+iCip8mdO3fQ0tIytwBY9OdG/1/q32b/v9RrD7IOERHRg1reXTvpmWJNmUjv0xGb8CH67mOa3a5dR/x9BcP7Ysg/U/3c7lNpCNHDJnwHo8s2iEZERERERES03DGQRo/HFxF0Pt8J/YKK6OkE/Pc1k+Svo/05ifgLQ9D3ZBqPpfasmzFhvBNFofc4Er3NDOJFRERERERERI2waycRET1y//jnv550EZYddu0koqcFu3YSERHN4yhERET0yDFoREREREREzwJ27SQiIiIiIiIiImoCA2lERERERERERERNYCCNiIiIiIiIiIioCQykERERERERERERNYGBNCIiIiIiIiIioiYwkEZERERERERERNQEWzMrjY+PP+JiEBERERHRcrRixYonXQQiIqJlo6lAWkdHxyMuBhERERERLUd37tx50kUgIiJaNti1k4iIiIiIiIiIqAkMpBERERERERERETWBgTQiIiIiIiIiIqImMJBGRERERERERETUBAbSiIiIiIiIiIiImsBAGhERERERERERURNsT7oARET07PvHP//1pIuw7PzxD79/0kUgIiIiIqL7xEAaERE9FgwczWNgkYiIiIjo6cSunURERERERERERE1gII2IiJaRAg647dj0cemhb7l8ogf2DQdQeNgb/jqKruda0NLSghZHCKmZh70DIiIiIiJaLh5TIK2ExKv2ykNGg8XuM1AGYJ0JwW7fhMQEAFgofLAJDmcPEtcWbG4qh+gGO5yvDcEEgJkUQisab7v2waa+HHaHEys39GD7viHkby99FIW/daGlxQ7P3/P1b34RwcoVPRgqV37M7V4J+7oo8o0eqC5sh8O+CYnx2Z9H+rDyuZbFH/BKQwg4ah/QKmVZ7Jjt8Py9sPh6z9nhULvQsyOBXPUxTySwyW5H6IxVs3vrmxQObNuELtUBu70F9udXouvV7ThwtoDaNWuVvzRgjDz8h+Hm3d/5brZOAQAzJWQ+jiDwSiecDjta7HY4NQ8Cuw3kqg95YZ3eu1ZX9MCYaFRmEwOv2NHy3EpEvmhwRCd64GhpgfPNFMoL3xzpw0p7F6Jf33dFEf0mSKu90P/kguNhb3h9DKN3BcTlfqgPe9tERERERLSsPNaMNGnzIMbMm7i5YDFPhiDXrw3tvSQSr4wi+tYB5OciNmVk9ugYmNJhHA1WPbRIcO/P1m37pnkTxasJ+KpGg5O2DOLmrSKKt4oYu5zC4A4Pps+F4dkQgHFtqdAQICkyzENhHHjYwQqbAnkiCaNB8MQ8YyAjKXV1JClBJK/XH+9N00Rqp1a7nlk53uKtIorXx5A5EoJ0MQJfMFEJRi6ifKEPnldCMEpuhI9mMHr1JkbPDUJfa8IIeuD9W26RYJqFzNEoEiPF+6+Lh+x+zndTdWoVkPC70LMvA8efYkiOjOJmPovkvh5IIxF4XwlhqGGQ7B4ZSmsWxqkGYdOvDSTHZSgNRy8swDiWRdcbQTjOJZBcch9EtJD0cj8G/+qD8qQLQkRERERET63H27Wz1QG1Q61blDZpkQ8oCB5LIjQVQ+j9DMoAymcj2H5KRvRUHL622rXtstJ4++0yavYgOeBsV6C0K1DXuuF7ay+Sl9PoV9LoezuxdLefdX2I9ZYQ33mgcbbZg7J1oWezheSn6drA1EwBQyfH4NnsQV0t2RxQGhyv2qFAaV2w3uzxKu0KlA4Vri39MPb7gMsppMcXKdNUGtEdCRS7DWTTMeibXdBWqdBe8iF8+BIuHQnAWRyDWVcPJRh/ciJ0uoT8h144XtiOj6JdsK/uQ8ZauJ4DjmAK5S8iWLliEw6cOYDQK13oXO2Ec/Um9J2oznorIfPhdmzSnLCvsMOhehDYl2qw/wXu53w3Uafmx32IjDjRfy6L4+/54V2vQV3jgvf1vUiODKPfBZiFpTLxJHi3eFE4aSBXU3YLmU+HUN7Yg64GgTRrxIBxzYPgwQhCq7IwTjTIjCR6Cpln+rBptQN2x0ps2pVCcWGbLueQeGcTOp+3w+5YCc+bA8gtSMm0vjYQ8XXB6bDD7uzEpm3G/B9gLmyH415W6sLM36khBBxd6PF3weFYicDfE4i84oTd6UH0i9kNTOWReKdnNivXDue6hfcmIiIiIiL6rVj+Y6TJXsRPRCGf2o7wBweg7zoP7WASe19cLPj2gFrdiOz2Q/pqGKmFXUmrzcjwHhpEoBRH+IOHOdKOBPdWPxznDKSqYzBfGkiWvAh1Ox76Q5tkq9ThYtu1RlIYLmnQ3w82zOBQ3z6O4aM6tLqgjwL98yyi6yW4/pzB5K3j2Lldh6c0jKGLVXubGMbQiAOBN3yQbYBkZTF4SkLkwijGrheR3acgvSuEgW8qqxc+8CNwbBrB0wVM/zgN81wfHGdDCOxbLCtuCc2e7zomUqkspM0RRF5qcA3KXsQ+S2Jv99I5L/buEHxTKRjV9TGVhnFWgn+ruz5oijLSnyQxvVlHoN2F4JseFE4aCwKTRE+hbw4gtC0NeXcaY1fPIzwzDKMm49dEIujHQNmH+IgJ88pxhKwE/DuqujdPDCG0OYLsqghSV0yYlw3oSnk+ILf5OCaFwOSnvsZlmClC3pJEZo+K9H4D2JfB8NYyjE8zlXuLVURZ9iF6Kosx00R6nwvZ3QFEG2QQExERERHRs235B9IASC/uRfKghvT7UWQ2DMB4t9EoNBYy73fCbrfXLV17msvckbVOqCjAXKqvIyygzYf44QBKh3Qc+OZBjqgxu1tHqCMD4/S9AlhIn0zB6tXhq+/7CmsigZ4V9cdrdwTmxmpbTPlaCpFDKcDtg6+j8TrFcRNlmwtda3/NUc3qCEHvtjB8Yv7h1zybQrbdD737XthIRs/bYbhmM7/U13X42go4f6EAzORgHMuja9cA9PWVypDXBhHb4UHhdBLZB8gObHS+f7FOZ0wUbgDqOleD7sj3odUHfStq6qN0Nom0EkLIba8PDI4nkThnR+AtH2TM1k05icTZXzjRRMtc/rNh5NeGEXvXDbVdg/9gBL7qjNovE0hc8SB2rB++tQqUVV6E9+lwXkwiPXv5F07FkW6PIHE4CPcqBcoqN4IH+2u3sxRbJzwbNbhecUGVu+DdqMHr1mCVipX22ebD3kNh+F/WoCoKXFsjCLtNZHMPfdoCIiIiIiJa5hqOxPSoWGdCsD8XWvCqBO29DMYOupf4ZAm5ywWgXQGuDCMzEUSwfeE6EtzvnYcRdNa9LrUtfG0pEqQmakXeEke8twv6uwPwj/RD++WP/DKbhuC2LsSPGcjvjMFVTsE4JyN4wQu5OFRfUiWIwYtReBaW1+aAWh3lmTDQ4zBqVrFmZLi2RDF8+CGV/RfJ8L8dQP9rBpLjQYQ7TKQ+y0ILDsJ9r/w2J9TVVblYNiecClC6VQTKJgoTFjI7nGjZsWDTkgSzDGBBV9/m1J7vX6zTGcyu/ytTwWwSvG/qUDfO18fwiQy63ozDZcvVrZ4/lkC2I4j4xtn6afND7+1H4JMkzNfDHOCcnlIWzPECJE2bvw+1atA6gHutoHy1APN2GiFHC2q+PSQvimUAsoXC1QJklxuuB/5GkyBJACQJkiSh8l8JsCxMV0qB/CcxxE5mkJ8oYnoGsMoWnC8yJZSIiIiI6LfmsQbSpM1xZA/56rqtSW1LhQEsFD4MIZxzw8jFMLnDg/C2BFzpcF2XQvvzKrQ1Dx5SKF3JooBO6E1FlmT4D8UxvEGH/qEPmYVxQJsEzFgNwy3W1HTl9QY9A9WtOrz7ojAuRxG9ZiCjhRBfD6DRmP02B9Q1WoOulQsofhgjsdmAlYXC0RAC57oQPbIX3iV6IDrXqJBnssh+BfhfXmSlGTR9FUndOkLtXiRPFxDuTWH4Gw/0U1WVbWtQITWZZhKCn00iufXhdOtteL5/qU5tKtTVgHFlFCW4Gg9a3mydrA9Cd8VhnMpD703DuOpF5DMV8yGEWVNpJE4VYJUG4HEMVO3HgjWTgPFVGLEXm9gf0bK0oD3bJNgXtp81/chejc8H3R+lmn1U7uCl0zp8+8rQjxiIu52w2yYxvK0LiYc5TiYRERERET0VHvNkA05oa7W6RVUWD4yUR6II7S8idCwBf7sK/VgCvutR6H/PP9wxw8oZxA9nIG0OIlCX7baINj8Sh30oHdQxcL32cVBbp0EazyJzo25HyFzMAR0udDXKoGrzQ+8F0qcNGEOj8LwR+vXZRjYHlFUq1FUq1FUafAcNRNuSCO8wlhyoX3oliEB7AcbBBAp161kofNwD57q+ue5Vv1wON/Q3Xcinkhg6OYzCxiACHdWbNGFet2p/ngAUVQXkTmjtQD6/oCvV7RJKU03uv9qDnG8AgAr/Vg+kiwOIXWxw4Lcz6HM5semjZrp8qQi95YX5WRLGp0mUt+jwN7gmSmcSGJ7yIp4bw1i+arl6Cf3rTQwdS3PQc3pKSVBXq7AmTMwNDTnb7u+R12lQJ/LILjpLrQRtnYbylczDnQCmytjlLKzN/YhudUFtV6C0WSjearCiTYI0Y8FigyQiIiIiemYt7zHSSimEtxnATgPx7tm+ioofiaMhlA+FEFkQyJgul2COm/XLRAnl6gcbaxLFiRJKEyWY1/LInDqA0MYAEpYficN64yyjRci9A4hvKSG2L1WTNCb3RhBem0dsawgDZ3Mo3DBR+CoNY5cP+inAvy+ySHaFBN82P6RzUcRv+KD3LlGamUmUGh3vuIlSaYknOcmFvZ/E0DkSwfYPl5h5TvIidrQfaq4P3o19SJzNIX+tgPwXKSR2eOHdPYquXWF4Gw4WVukqVRw3UZqyYM0+4Gpv6PDeSCD8SRG+NwIL6tpC5uMYMiUAKCP/UQLDUy4ENquVINw2F8xPIjgwUoIFwBpPI9qrwbM7jSVjefdzvpuoU/XtQcQ3WzD8HgT2DSHzVQGFb/LInIoisLEHhi2A/teb6zAr9+oIlA3ETgP+bd76JMWZAoyjGUhbwtBfvBcMvbd4EdnmRfGsgdTt+TosFxeWvYQSh1KjZcrVG4Arn8TgF2UAFgqfJDB8u2qFl8IIu0cReyOCoS9NlG7kkTkzgL4dxtzsm9obEfhKCei7DORulFC6kcPQvgGkHyTI3oCqqrDyGeTLAGAh/3EUxo0Gd841nXBJWQyfyMMslVF+SPsnIiIiIqLlY/kG0mYKSLypI61GkdxXO4uhvDkO410JxjvhqhkuLeT2ebBSXVm/vKAhMjL/eetcH1a+4ITzBSdWrvMgdPA8rO44srkkgh33W1AF/kNx+GGiXJ0N0epG7GIWg5stDO/xw7NuJbq6+5C40YnI51kkX18iQPaSjlCHBcfWxpMMzB1HaQih1Q2OV10JdWsCS86ZsLYfxw96MLo/hOgXiwfd5O44srlh9K0uwNjtg2ddJzy9ERgTXYim8zj/rtaohyoAFb43fbCfC0FbF0LyXjZJewD6ZqDcGoC+ecHBSRqCrztg9K6E0+GE95iF0LEk+tdU3tb+ksL59xWcf0eDY4UdTncEeVcc5w/7lhz4/37Od1N1atOgf5ZF5pAPuBhDaGMnOjd4EDqUg9RrYPTyIHzNjtfW6oO+1YmyEkKowSyg1uUEjG9UhN7xNzxG5XUdflsag6dmz/ZMAQnfwrI74WsqQ47oCVi7F8kjXci9pcGpdkG/osFXM8GJivBnacS0PGK9nVBdXmw/lIG1uhNzo1+2B5G8EIdnfAB+lwr1FR1GSYZqA4ACDrjtaGlpgWNbGtZXUXS2tKDluZXoG1lYmMbUdxMYdGUR0pxYqXkQNf3o6240a28QS2dszAAAIABJREFUscM9KB70YKXTAe39zK+pGSIiIiIiWoZafvjhBwEAQoi5ZeHPv/vd755oIekZMlPAwEYPkq9mMfrXqqytLyPo7M5Cz2fRv+rJFY+IHo1//PNf+OMffv+ki7FssD6I6Gly584dtLS0zC0AFv250f+X+rfZ/y/12oOsQ0RE9KAe62QD9NtmTZnIHNQRm/DBePfxzBVKRERERERERPSwLN+unfRs+SKCzuc7oV9QET2daDioPhERERERERHRcsaunURE9Mj945//etJFWHbYtZOInhbs2klERDSPXTuJiOiRY9CIiIiIiIieBezaSURERERERERE1AQG0oiIiIiIiIiIiJrAQBoREREREREREVETGEgjIiIiIiIiIiJqAgNpRERERERERERETWAgjYiIiIiIiIiIqAm2ZlYaHx9/xMUgIiIiIqLlaMWKFU+6CERERMtGU4G0jo6OR1wMIiIiIiJaju7cufOki0BERLRssGsnERERERERERFRExhIIyIiIiIiIiIiagIDaURERERERERERE1gII2IiIiIiIiIiKgJDKQRERERERERERE1gYE0IiIiIiIiIiKiJtiedAGIiOjZ949//utJF2HZ+eMffv+ki0BERERERPeJgTQiInosGDiax8AiEREREdHTiV07iYiIiIiIiIiImsBA2n0p4MAGBwKny0+6IEREzxgLuQ8C6HzejpaWFqzcnau8/HUUXc+1oKWlBS2OEFIzT7aURERERET02/aYAmklJF6tPBw1Wuw+A2UAhb91wf5CHzK/8KBU/mYIB7ZtQpfqgN3eAvvzTnR6Q4ieymPRENe1AXjsLWhZHUHGmn1tJofI6sZlmivbqwmU7m1jPIPMjS54X5GBkT6sfK5qXbsdDrUTm16LIHHRhFVXAAvmuQH0/akLK50O2J+zw+HshOe1CBIjpZo1c7tXwr4uinyjeriwHQ77JiTGZ39eWI7nZuvj1RAOXKja7kgfVtq7EP16sQpa+hy1PLcSkS8W+ywR0a80YSC6vwDfSROTk9MYO+iuvL4+htG7AuJyP9RHuf+ZHCKaA6Gzi7x/O4fEO5vQ6bTDvsKJzlejyEw1WK+cQZ/WgpbntyPNoB8RERER0TPnsWakSZsHMWbexM0Fi3kyBLnJbZTObofHrSNZdiN8LIPRqzcxeiGJ6EYLqR0edAWHYNY9vFjIHTNQ6Nbht5Iwzs2G22xuREeK82X5NAhZcmFvpqpsQzqU2a2UR9IYXeODt332BZuG/vRNFG8VUSyMIXMqBr+Sx8CfuuDZnfn/7N1/aJP3/v//eyCDK6CQMAfJOfXQqyiY4mApE07D8Q8jHjBlB0xwYIPCjBO29gzethPeLh//8ETfsNPugGs2UC+FSTqYNMJHFuEri394SAaOZrDRCIpX2dwa+FQadoRe8C70+0d/16rxV1vn4wYXttf1uq7rmR81ySOv1+uaF+rVKByJ0PJ2hsqGJH0XiwxVBin0p4mvKZD6a4i2TytLhG91ml+HfZuhKxYd68qk307MBW51etBjdNsukvrzkxYoIvIId2xGCBHe5sfrNTCMlS5onokKmfYo6UqIrrMFileypPe04LuvYY38kW4qgRCrqXwREREREXl2lvdiA2t8mI3mk3/AGM3R9b6Fs3uA4tnYbMAFJsE3I0Tf7CQc66D7ywgDe+e2UsvT9+UY0c/SJBsLxE9nsXd3YALeBv9ciOf3AAa+9SZm4+KTOxSuDhLYliY4u87ACJj4p4M1f6NJ6C8x4lsShPYfoHvHEGd2GjhXUxz4l03kZJGBd+f1qdgQJLQtSrghTORIksyOIl2bnuSOWVgHDSYdh4tYF/up2MB9t+UhnvYxEhF5HN+laG49TmX6C5C4px8A87+K3P6ktb5jOBX6D3eS/rKIPeEluKOTnpMfEZl+GbAvpej+OEfxR5uaO0BoR5L0J9PbJ0qkXg9z/Mb0sWIu+gGMCH03v6GjAZxrGXp/iNL7Qw/t66aahZb4YqF2qZvUcBJrb4Hw4Se8P0REREREZFV7oeZIq13Jkq+10nF4fog2x7uzi45Wh/yXXzN/sKT9ZYb8mjjJnX4i+9sxSxb9Dxzi+ABOkcI1D5EdoUc29e9J0bl5hIEv8zhA8cIAI40Jut9ZamCSQeuhbqLuMtmLlccs6kG12uS/yGM3RolteTaHFBF5Lt5MM/S/k0yWugiuaWfgfyeZnJysP0TDoXQ0TvKKn67LQ9ilLPFaD/GD1uzrQK3q0HKwj/x1G7t0hrhjzW13t5KuTDL5v0W6Nnlpz02df3J8KkQDsP9dZGxLM5xso2V9gEBwOwc+LS2cSmA0T/cRm8QnHZi6HraIiIiIyO/WCxWkjdyycdY0E9zwoBYmwc0BuFmZG945UcY6VcTckyRiAG8kSWypYJ0qPN5Qyu/zFJwI0XqCKbdJ8HUDx7YZoUrlVg2CLQQf9OHKG6JlA9gV+3EqmjNRpnebD99rU4tnbRPxyyap8z1E1jzeoZyLSXweD55Fiy/SyxNWJyLy/EwUyV6wiRzqJfmmiX9ThI+OJQlc7WdgeKpJ6N0ePtobIbTBj39DhK6/x/CVCgzW+SIwMjKCU+qj706MnssFckeDDB6N0XFhJkqrkTvUzVB73xP2KhYRERERkRfFsgZpzoUEnlemJsSfWzw0HynVd4B6v+Wf1865kqH/VojEvpmeZCaJd6KMXciQG62/9srVAiOtEcL1BlMTDrwyNUDSeFTdM6Hfk/ZicAdJ9g8yeH1qGSoXyR40sHa20Hmp+uj95zF2pCmWBxlcvHyRfL4TfYuIPImajT0aIBic1095UwtBbGa/mxjOc3x/Gy3BJprWBwi0Z7Adh9pjXAzAIUL3ySSRzUFa9/SQ3gX5C3lqQO1CB6mbCTL/FXzkcURERERE5MW2rANQjJ09FD+O3jf/lrGuvojG3BDEuDdI+QZENy/Vwqby4whsDE73/qqSPT2A7TikQh5S81o698D60qb97/Wc26ZwxaZld6S+iyJMlCmWwbstiIkfc0MALhcZdNqnesUtdq/M4C0Ivj39IcxtwISzZI8559741PoFxzHwBubP62Zibg5h/GAS/zhL11uPcbW7NQGCm4KaI01Efh8myqR2xcm93kPfhT6a13mgnCb89kjdh/B5fRh+E3P2P0aDgN+H8+0YY4BdKlH5LkfYl57e7uA4EPcVSOZu07fjGd8mERERERFZMcs7tHNNgODm4H2L6a8vtjF2JIj7y/Sd6Gepfla1K71kSl5ie+NTgdeNLNYVg/ZTgwyVh+Ytgwy8G6B4yqJcT4+E0QL5cpDotqVmZruffTqNNWyS2BcGINwew7yT5fjppeZAcyh/2keeMIndU3FX8PUgxnCRwq37biGFKyVoDNGyrq5S4N7j9boQEVmV3AbGxFRAtYDXxFw3QqUy71XhxiAVTIImUC1SuhUieaSDyGYTv9+PMTrC2JIncXAm7v8KwwyFMEZtbGeu3Uh1DNb58AHhI99w+4e5HrzFYxEMb4y+0jektj6D2y4iIiIiIqvG6psSeWKM6rCNPb8ytwffOj9eb5T0yQ6K7UnCfxvio/fihDd64Z5N+bJFz8c52Juld7cXcCidylBuSNC7JzivJ8EU84MkwfN9ZK6kOLPz4UGec7XAYEOE9H1zszk4IzbVdR5gnLE7ZQr9GdKnBwkeyZP+8/TQzj+nsD4sEj0cYfvNFF3tEYLrDGrVMoUveug5XyX62Td0NE4d1burm46TEdK7ExjHOom+7odaheIXaVLnIXa2m1b3g+oAnBGGrmZIXawROhwl5J5rVxuxsRd0q/Pg8frxz6y7N4Y9bC/RI21ROxGR5bSpmZBhMXCuTOtuE98aL941gHvqS4jIJ11Yr6dp81boO2oxsrWHaCNwz8T02hRLNl2bTLiTJ3UyT43owuO7Tcz1kLucx94ZJWAYs8PyvTsSxI046cP9mIda4YcM6YsQ/Wy6l/I6E3Pelxu1615w+whsMvGvvldZERERERF5CqvuYgNOtZ/ExiaazPlLmNT0NGr+t/oolizavSUy70doCTbRsi1B+ipEPytSPDV9Rc9anr4vRwjtT9K6VE62OUnHNoeB07kle7fNq4ji1RKebZF5gdS0iQq90SYC6wME1jfR8lY31i2T7q8GKfyf1nlhlJfWYwUGv+rGvGXR+VYLTcFmwrtTDNTCpK8OMjD/ip5rWklfKdK302HgSIzw60207Ogkc6uZ7v9bJLvH/5A6AgRej3DgsxHCxwrk/zu0oF0muvi+DRD9dK6nnHO5k2ZzcZupdpETdc5lJyLyrHnbSX/SxsiJME0BH8HDhekNBq3HBrB2VOl9qxlzS5K8t5uBs9PzOq6Jkj6VxPk4TMBspnlPFnNfkvtnM/OTOJomdL2DZp8Hz9rtZO7MnDtKz4UeWn5IEXm9mfAHBcwjWazF/xeLiIiIiMjvnuu3336bBJicnJxdFv/+6quvrmiRIiLyYvvpl1/50x//sNJlrBq6P0TkRXL37l1cLtfsAjzw96V+fti/9f78sHVP0kZERORJrboeaSIiIiIiIiIiIquRgjQREREREREREZE6aBpkERFZFj/98utKlyAiIiIiIvJUFKSJiMhzp/nARERERETk90BDO0VEREREREREROqgIE1ERERERERERKQOCtJERERERERERETqoCBNRERERERERESkDgrSRERERERERERE6qAgTUREREREREREpA7uehoNDw8/5zJERERERGQ1Wrt27UqXICIismrUFaQ1NjY+5zJERERERGQ1unv37kqXICIismpoaKeIiIiIiIiIiEgdFKSJiIiIiIiIiIjUQUGaiIiIiIiIiIhIHRSkiYiIiIiIiIiI1EFBmoiIiIiIiIiISB0UpImIiIiIiIiIiNTBvdIFiIjI799Pv/y60iUs8Kc//mGlSxARERERkReQgjQREVkWqyW8Wm2hnoiIiIiIvDg0tFNERERERERERKQOCtJERERERERERETqsAxBWhXrbz48f81gL7ndoXSoGc/GTgrO9KqJEt1BFy5PC8d/vH+Pyj9acLlcC5dXPPjMFtrez1AaXbTDRJXC593EtzYT8HlweTwEgmHihyxK1YXH9azvpDBx/zlr5+N4PG3015a4hefa8LlcBPbluG/z1U6aXnHdV6/ntSbCsW76f3TuP6CIiCxQO9eGZ8txKitdiIiIiIiIvNSWIUjzk3gvjveahfX9Eptrefq+tAnu7yBiTK+61EfWiZHcZmOdKrBU1GT428naI4z8PL3cHKJwMoFxpZto+7zQzqmQiYVoO1rA97c02auD3C4XyR5tw7jaTWRrgv47T3P7KlinirTsbcd3KUN2qWO5g3Tlb8/V+vNtBi+midzLktiRpL+6xD4iIiIiIiIiIrKqLMvQTmNHB8kNFfqXCMWqFy3yToSOvcGZNQyczuPb1U36nSjjFyzyS/QCw+3D3+CfWxpNQm91YR2LwrUc+eGpZvbnnXRfDdB1qciZD2NE3ghibgoR2fMR2asDdIXArjx5kuVctbBuhGk/0U1iQxHrXHmpewAjYM6r1yT4l3bSp1JEajkGri51A0VEXg61q8dJbGnC5/HgCTQT3mfN9jyrnY/jcbnw7c/jfJeiebpXb+CDwoJjFD5oIrDfIv+POC0BDx5fgJYjhftPJiIiIiIi8hSWZ440d4jkwTAjFzLkFgy7rJA9VcDY1UGiYXrV9xaZayaJfa3430oSN3Jkvlx6UOhSDPdUt7apwM4mlyti7Oym+8/G/Y29EdJfZfloh//Jbhc18qezjO9MEm8I0b4vTOULa26I6qPMXDN1iaGkIiIvhYkCqf09VHeeoXjTZuhKH51bfLP/L3r3DjA+OcnY2SjGm2mGJieZnJxk5GTkvkPVLveS+U+CbGWMsZsF0tsCy3xjRERERETk927ZLjZg7u0g5s5jzQ/FvrWwvjdJvh9lJv4qnLKobEnS/gZgREjuMSmesijXETbVbuTo/jgHrVGijcCETeUWmK+H8NZZp3Mnw3aPC9crCxff/tz9Q0yHs2QueYi/E8ULmHuSRGtZMhfr6GE2WsY6kqHojRLfUW91IiK/M06VkVEfwa1hgg1+zM0R2v8eI+h+9K4LjcO6GOkTMYJeA2NdkOiO4KN3ExEREREReQzLd9VOb5TkngDFs/3ToZhD/lQWu7WD5JvTbUZzZC6MEX0njjm9KrQ/SehWP9bVRTHWHYs2nwfP2rnFF+qgaKYY+KKLmY9PhnvqXPUy/O2cuT7EUHnhUjwWYXGftvKpDMXGdpLbpresi5HcZZA/nV14YYWJMr1bF9bqCoQ5fjNE+qJF+5N2iBMRedGtiZDYbWC93cz2tztJ/bOf0p0nuwiLEWp5ggBORERERESkfssXpGEQOZgkdMuaCsWqWaxLEHs3MRua2ef6yI/WyL9vzoVOoRRlxyZ7etEVMf0xrNnAa5CBd4MYDW2kTn5EZGaYqNvE3AiV64M8cBa0xT3d3D7MzUGCi5eGRb3G7uXJnK/g3OglPBvo+Yifr+Jcy2B9N/+YQZL9c6Hc4KkEphEkdsKi68/qjSYiLzM/sbOD2Ff6aN9iYH/VRWRL4gkuwuLBMIz7vvAQERERERF5lpYxSAM2JUnuGGPgfJ7KhX7y3jjJXdNBklMic7ZM4L0BBhf1Bhv8LIZx2cK6Ne9Ybh/+DSbmBhNzQ5DoCYvUuiwd71vYs+GYSWx3GONKL+krSwy3HC3QGQqw/dPK/dseoXohw8C9CD2lRb3XfviGrjds+k/l5/WDM/Cun6nVJLinhzPvOGQOdpLTFTtF5KVn4H8zSvLDHrLXLBIU+Lq0qInbgIlxHM0pKSIiIiIiK2h5gzT8JN6N47ncQ+fZIqH9HUSmuw/ULveRHQ6R/CBGcMNc6GRuMAnu7SDhL2KdXeqKmNOMEB+dTtN8tZsD/6rMhljmu3307HSwYmHiR/spfFeh8mOZwvkU8W1tWO44XXsecx6diQrWZwWMtzpIvrmwVnNDhO79EUYuWosurDCfl8gJi641i4M/EZGXzGie3qMW+e8qVKs25Qs5iveCNG9c2MzbECAwXCL/fQ3HQRdpERERERGRFbHMQRoYOzpobyhRGI6QfGcmwKqS/TyHsyNJctNSO0VI7g9in8+Qv/eQg2/u4syJMIPHEqT+PR2luYMkvypS+DgKV9IktjXTvCVM4uMSxi6LwWt9RNc93m1wrmWwfjRJHIwteRED/54kMXeevvMPudromlZSp1OYVxYGfyIiLxW3ATcsuneFMc1moh+PED1l0bV5UbutXaT3jGPtCODxuAgcKqxIuSIiIiIi8nJz/fbbb5MAk5OTs8vi31999dUVLVJERF5sP/3yK3/64x9WugxgddUiIvIiuHv3Li6Xa3YBHvj7Uj8/7N96f37YuidpIyIi8qSWvUeaiIiIiIiIiIjIi0hBmoiIiIiIiIiISB3cK12AiIi8HH765deVLkFEREREROSpKEgTEZHnTnOSiYiIiIjI74GGdoqIiIiIiIiIiNRBQZqIiIiIiIiIiEgdFKSJiIiIiIiIiIjUQUGaiIiIiIiIiIhIHRSkiYiIiIiIiIiI1EFBmoiIiIiIiIiISB3c9TQaHh5+zmWIiIiIiMhqtHbt2pUuQUREZNWoK0hrbGx8zmWIiIiIiMhqdPfu3ZUuQUREZNXQ0E4REREREREREZE6KEgTERERERERERGpg4I0ERERERERERGROihIExERERERERERqYOCNBERERERERERkTooSBMREREREREREamDe6ULEBGR37+ffvl1pUtY4E9//MNKlyAiIiIiIi8gBWkiIrIsVkt4tdpCPREREREReXFoaKeIiIiIiIiIiEgdFKSJiIiIiIiIiIjUYZmCtCqZv3pwuVxzi8dDYGOY+CGL8r25ls6FBB7PdjJ3pldc7aTpFRe+v1nYiw87kSPh83Hg8hJnPNeGz+UisC9Hban91roW1uNy4VoboHlrgtRFGwdgosLxrb6lz41D6UgLnvUJ+qtPer+IiEg9aufa8Gw5TmWlCxERERERkZfasvZIM97q4/bPI4z8PMJIZZDcsTC18weIHylMBVcP3NGPUUrRefr+OGtpFaxTRVr2tuO7lCF7Z6k2Bq3HilO1TC+3S1m6QjaZ9ja6rzjgDvLR6RQt17rp/HzhuZ1v03R8WiN2spd2f51liYiIiIiIiIjIC2t5h3YaPgINfvwNfvyNQVr3pEluMxi5Ubm/19h87gjdx8IMHu3EGn70aZyrFtaNMO0nuklsKGKdKy/ZzuOdrmV6MTdHSH6SoWOTzcCF4lSjTV2cOdZC8WgnmVszJyiRfq+X2p4+MruUoomIPI3a1eMktjTh83jwBJoJ77Nme57VzsfxuFz49udxvkvRPN2DOPBBYcExCh80Edhvkf9HnJaAB48vQMuRwv0nExEREREReQorOkda7TuLgZKXyK4oD42jJhwCe3pItw6S+mCpYZYLjkr+dJbxnUniDSHa94WpfGFReGiXt/kMPG5gXh85870z9LQOkvoggz3hUDrWQa+T5MzHUbz1HlZERO43USC1v4fqzjMUb9oMXemjc4sPJqY2e/cOMD45ydjZKMabaYYmJ5mcnGTkZOS+Q9Uu95L5T4JsZYyxmwXS2wLLfGNEREREROT3zr2cJ3MuJQm81jH9i0PN8dL69wy5d81H7+w2SX6SJteaovN0hK8ftM9wlswlD/HcVMjl3ZMkeqyDzMU0kT2PiL2cKqXPU1g/Bmg7Fl547pNp8q3dHDhYZOSCQ8f/7SGiFE1E5Ok4VUZGfQS3hgk2GNDgx9z8JAcah3XtpE/ECLoBgkR3PNtSRURERERElneOtG09FK8PMnh9kMEfBhnMpwn/2EHob71U6ukx1pik71jLQ4d4lk9lKDa2k9xmTK1YFyO5yyB/OruoJ5tD4XAznrWeeUuA6Gc1op99Td/ORSlZY5LMxxGGzucw3rNIzxxfRESe3JoIid0G1tvNbH+7k9Q/+yndqbsL8QJGqGU6RBMREREREXk+lndo5xofZqM5vQQJ7UjS81k35tU0vVfq++BkvttHesv0EM+JRWHWvTyZ8xWcG72EfTPhmI/4+SrOtQzWd/MbG7R+WGCoPDS1XO0hus5Ly8Eeet4JslRM5t8aodlt0LKtdcntIiLyuPzEzg5iX+mjfYuB/VUXkS1PcjVkD4Zh6P9mERERERF5rlZ0jrQ5DuN1d0CYGmbZUkrRec7GM+9TU/VChoF7EXpKQ3MBWXmIoR++oesNm/5T+QVXB/W85sfcYE4tb3aQORnFPpYkdfXJekOIiMiTMPC/GSX5YQ/ZaxYJCnxdWtTEbcDEOM7EihQoIiIiIiICLHeQ5owxcqdK9U6V6h2byrc5jh/KUF4XI/44QyWnh3gWj6b5eibzmqhgfVbAeKuD5JvmXEC2wcTcEKF7f4SRixa50Qcf1r87Q9+eGpmDnQ9tJyIiz8hont6jFvnvKlSrNuULOYr3gjRvXNjM2xAgMFwi/30Nx2H2YgQiIiIiIiLLaVmDNOdSJ03rAwTWBwiYTbTsSvH1mnayVyxi6x7vWFNDPB2qteljX8tg/WiSOBhb8kqa/j1JYu48fecfds1PL9GPz5A0snQcfNTVQUVE5Km5Dbhh0b0rjGk2E/14hOgpi67FFxzY2kV6zzjWjgAej4vAocKKlCsiIiIiIi8312+//TYJMDk5Obss/v3VV19d0SJFROTF9tMvv/KnP/5hpcsAVlctIiIvgrt37+JyuWYX4IG/L/Xzw/6t9+eHrXuSNiIiIk9qlcyRJiIiIiIiIiIisropSBMREREREREREamDe6ULEBGRl8NPv/y60iWIiIiIiIg8FQVpIiLy3GlOMhERERER+T3Q0E4REREREREREZE6KEgTERERERERERGpg4I0ERERERERERGROihIExERERERERERqYOCNBERERERERERkTooSBMREREREREREamDu55Gw8PDz7kMERERERFZjdauXbvSJYiIiKwadQVpjY2Nz7kMERERERFZje7evbvSJYiIiKwaGtopIiIiIiIiIiJSBwVpIiIiIiIiIiIidVCQJiIiIiIiIiIiUgcFaSIiIiIiIiIiInVQkCYiIiIiIiIiIlIHBWkiIiIiIiIiIiJ1cK90ASIi8vv30y+/rnQJC/zpj39Y6RJEREREROQFpCBNRESWxWoJr1ZbqCciIiIiIi8ODe0UERERERERERGpg4I0ERERERERERGROixDkFbF+psPz18z2EtudygdasazsZOCM71qokR30IXL08LxH+/fo/KPFlwu18LlFQ8+s4W29zOURucd/UICj2c7mTtLVHauDZ/LRWBfjtrijRM5EmtduMwEudHFG2tYUQ/Nh0tTtW503V/PvMXz1wzV+u4sERFZQu1cG54tx6msdCEiIiIiIvJSW4YgzU/ivTjeaxbW90tsruXp+9ImuL+DiDG96lIfWSdGcpuNdaqAs8Ruhr+drD3CyM/Ty80hCicTGFe6ibY/KLSbr4J1qkjL3nZ8lzJklwjawIvfydF9aImgbYa7ldTVEW7bt6eWs+14jRAfFW7PrrP7k/gfWY+IiIiIiIiIiKxmyzK009jRQXJDhf4lQrHqRYu8E6Fjb3BmDQOn8/h2dZN+J8r4BYv8UimW24e/wT+3NJqE3urCOhaFaznyww+vyblqYd0I036im8SGIta58hKtfMSPpjAvddNx8YFRGt4GP2ajObX4PYCBb705u86/znh4MSIiL7Ha1eMktjTh83jwBJoJ77Nme57VzsfxuFz49udxvkvRPN3TN/BBYcExCh80Edhvkf9HnJaAB48vQMuRwv0nExEREREReQrLM0eaO0TyYJiRC5lFwyQrZE8VMHZ1kGiYXvW9ReaaSWJfK/63ksSNHJkvH92/bIbCnkNWAAAgAElEQVThngqtlurFNqdG/nSW8Z1J4g0h2veFqXxhzQ0tnTWOs6GLviMm+UPdSwzxFBGRpzJRILW/h+rOMxRv2gxd6aNziw8mpjZ79w4wPjnJ2NkoxptphiYnmZycZORk5L5D1S73kvlPgmxljLGbBdLbAst8Y0RERERE5Pdu2S42YO7tIObOY80Pxb61sL43Sb4fZSb+KpyyqGxJ0v4GYERI7jEpnrIoTzz6HLUbObo/zkFrlGjjQxoOZ8lc8hB/J4oXMPckidayZJbsdWYQ/K8+Ug0DdB9+yBBPERF5fE6VkVEfwa1hgg1+zM0R2v8eI+h+3AONw7oY6RMxgl4DY12Q6I7go3cTERERERF5DMt31U5vlOSeAMWz/dOhmEP+VBa7tYPkm9NtRnNkLowRfSeOOb0qtD9J6FY/1tVF3cXuWLT5PHjWzi2+UAdFM8XAF1087ONT+VSGYmM7yW3TQy7XxUjuMsifzi49t5o7SNfn3fgvdtP9kCGeIiLymNZESOw2sN5uZvvbnaT+2U/pzsP7FD+IEWp5ggBORERERESkfssXpGEQOZgkdMuaCsWqWaxLEHs3MRua2ef6yI/WyL9vzgVkoRRlxyZ7elFvMH8M6/oQQ+UhhsqDDLwbxGhoI3XyIyINS5x+xr08mfMVnBu9hGeDOB/x81Wcaxms7x6w3+aPyBz2M3Com9zok33IExGRxfzEzg5iX+mjfYuB/VUXkS0J+h/7UsceDMNAM1KKiIiIiMjztIxBGrApSXLHGAPn81Qu9JP3xknu8k5tc0pkzpYJvDfAYHkmIJtaBj+LYVy2sG7NO5bbh3+DibnBxNwQJHrCIrUuS8f7FvZDhoFWL2QYuBehp7TwHEM/fEPXGzb9p/IPnF8t9GGGbv8A3YcL1PRpTUTkGTHwvxkl+WEP2WsWCQp8XVrUxG3AxDhOHcP8RUREREREnpflDdLwk3g3judyD51ni4T2dxCZDqRql/vIDodIfhAjOBuQTS3BvR0k/EWss0tdWXOaEeKj02mar3Zz4F+VpcOwiQrWZwWMtzpIvrnwHOaGCN37I4xctB58UQF3aGqI54UuMtef8q4QEREYzdN71CL/XYVq1aZ8IUfxXpDmjQubeRsCBIZL5L+v4TjMXoxARERERERkOS1zkAbGjg7aG0oUhiMk35mZyaxK9vMczo4kyU1L7RQhuT+IfT5D/t5DDr65izMnwgweS5D69/1RmnMtg/WjSeJgDO8Su/v3JIm58/Sdf/BVQo03usgcNhl5wjl8RERkHrcBNyy6d4UxzWaiH48QPWXRtXlRu61dpPeMY+0I4PG4CBwqrEi5IiIiIiLycnP99ttvkwCTk5Ozy+LfX3311RUtUkREXmw//fIrf/rjH1a6DGB11SIi8iK4e/cuLpdrdgEe+PtSPz/s33p/fti6J2kjIiLypJa9R5qIiIiIiIiIiMiLSEGaiIiIiIiIiIhIHdwrXYCIiLwcfvrl15UuQURERERE5KkoSBMRkedOc5KJiIiIiMjvgYZ2ioiIiIiIiIiI1EFBmoiIiIiIiIiISB0UpImIiIiIiIiIiNRBQZqIiIiIiIiIiEgdFKSJiIiIiIiIiIjUQUGaiIiIiIiIiIhIHdz1NBoeHn7OZYiIiIiIyGq0du3alS5BRERk1agrSGtsbHzOZYiIiIiIyGp09+7dlS5BRERk1dDQThERERERERERkTooSBMREREREREREamDgjQREREREREREZE6KEgTERERERERERGpg4I0ERERERERERGROihIExERERERERERqYN7pQsQEZHfv59++XWlS1h2f/rjH1a6hId6GR+Tl8Vqf+6JiIiIvMgUpImIyLJ4mT7cvygh1cv0mLwsXpTnnoiIiMiLSkM7RURERERERERE6qAgTUREVq+JPAdea6Lzah1tnRzxtc2kvnvuVT2dCRsr1kTLoQK1x9ovR8LnIX7+AXt9n6JlbQvHf3wWRS5W4Xirh+2fV5/HwZ/ORInuoI/ExZUuBBi1aHtuj8Fz9m03zWvD9N56UIMaVtSD72B+OauacidHItjMgYur8PknIiIiL51lCtKqZP7qweVyzS4eX4CmLW0cONpPefQBu02U6A66cHkWvinN7Vt4rPuWtQlyE8DVTppeeXA7T9R6vA8xIiKyerlNIntjtKx7PofP7/fRdKjw1Mep/DNB98/tWCcieB9nR3eE1KUC6Z0ze9nk/5WjMvHUJT03tXNteLYcp/KkB6gnJHP7admVILL+SU+y8p7Vc+v58tL2cYH8ofAzOp5D5UKG/HAdTRtiZE5GKL6fxKqnvYiIiMhztKw90oy3+rj98wgjP48wdC1H3/thxi91EN4Sx7rh3Ne+dqmPrBMjuc3GOlVgpkX0E5sR+za37dvcLvcQMQwinwxN/W7f5nYlQ3Rm9jd3kI787blt8xb7i8TjfYgREZHVyx2i47M0scaVLuQh7lh0f1IlfixFyHjcnb0E/9JKcCYovNFP+lh2VQdpy8Ok/UQfyTdXuo7fP//mVlo3PaN3ThNlrCO95G/W19y7I0WqtUjqWF5fgoqIiMiKWt6hnYaPQIMff4Mfc3Mr0Xc+InstT5c/T+e7mUXfWFcZOJ3Ht6ub9DtRxi9Y5KffORnr/PgbTcxGE7MxgAF41wWmfzcxG7zMfT4x8AbMuW3zFv+6x/4UIyIiz1jt6nESW5rweTz4gtvpPF9h8VcrY/8+Tvx1H561AVr2ZSjfm7fxVi9hz3Rv41eWGtpZpfA/CcKmD4/HR1OkE+vHRWcYLZE5uJ3mgAePL0BztJPc9BC3/EEfLpeLtnM17H9tn+7V7CFx4f4vgB6lct6i4G+nY4cBEyVSQQ/bP7VntzsXE/heWTh8s3Y+js/spHBv3tDOq900t6Yp1fIk1gfY/s+ZV1ADbvbT+ddmfGs9+Na3kPi8fN/9WQ/7QifbN/rw+JrY/kGOkQWBXY3CPxNsDzXNnqftcA57Yq5mj8uFb38e57sUzdM9wQMfzO919ZDHZaJEKujC9UqY3hs1+mPTj69nO5k7sxXSu9Uz93gs6LVm0xvxEI7Fafb5aN7fS+ZgC761TbR9Ou/dRm36cX/Ng8fXRHhfL6XHSmmq5I+2Te2/PsyBc4ueuzf66YyFaQr48Kz10bT1AJlv505Q13PrqWucNmGT/0eC8EYfnrUefGYL8cM57EVPDqec4UDr9N/jxvl/j/cP7bQvpYi3Tj0HPIFmwvt6KcwffTlaondfmKbXPHjWBmj+Wze5Ww44OQ6sj5C5ZWPFfARiFlUcKue7aQsF8Hmm/g5bot30z37R6if2bhwuZBjQCE8RERFZQSs/R9qaVroPxTC+GyB3Y9767y0y10wS+1rxv5UkbuTIfGk/8DAiIvICumORfLuH6s4+ijeHKBw2KbwfJ/Xv+Z/ubXJfDBE9PYhdyhD+oZv4kbleymzoojg+yeT4ALH7vh9xKP8jRvwrD8mzReybRfq2VUjt7qYwE8ZNVOh9O0p6uJX05SHsHwr0vWUwMv1hPXpqjMnJSb5+x4v5X98wOTnJ5OQ42d2P+2WMTeFKmcC2CCE34G4lsiPA4LXSbA+b4tUS5htBileL07fPoXitiLEtSnj+6bb1MHQ2hrEmSvbnEb75MDh9W2ys04NEPikyMmKTP+gjf7gb6w6P58fjJPbn8R7KM/TD13RMDGB9P7/BGNX/mLSfGKBYsRm80EHgUpLEdKDn3TvA+OQkY2ejGG+mGZqcZHJykpGTken9H/G4uFtJVyaZ/N8iXZu8tOem9p8c/4aOhpkaTLqujU+3WfqxqPkTDOQ6ML5MkTMzFD9rpXLKojQx9Xhk2mP01qL0XLWxr58h4WSIvZ+ru8dT9XSSxGmHxFdD2FdS+C9bFOYHjqMj0NrNmcuD2JUifX+1Se/uIDd9gkc/t56+xtn7+1ic+FmHxJc24/8Zx77UgXExQdvR0tzf0kQF67RN9NwgI//PZmAfZN9P0rvEnG/Ov7tp25cncOhrRv4zzvgPWRJOhnh77/QXozaZfVF6anGy10cYs/N0eXMkdqUoEeNMuY/IGj/J3BgjuST+WxmS7+cJHCkyMj7OuF0g1Zin4wOLmXd/xtYoEaNI/qr6pImIiMjKWfkgDfAGmzGpYM/mZA6FUxaVLUna3wCMCMk9JsVTFuXHHcIyUeZ4qwePZ9GyNsCBy8/2doiIyOOpXuon702SPhol2GASeqeHrm0jZPuL81oZhD9Ik/yziX9zjPThGGMX+inU083KKZD5rEri4z6S24L4G4JE//sj4hMD5ErTbb61yFxvIXUqTewNE39DkMh7PXT85Rnf2AmbcgWCr7fMrgrvaMUoFRl0gIkyhWsGkfejmNcLU693E2UK1xzCO8LUG9tF/p4mttmLscZP654owQmbSp3D52aUvxqgvLmD9HutmA1BYie6ia6Z38Kk/Via5M4QwQY/5p+TdO0zKZeK9QU89TwuT80guDVKcGuYFq9J645WglvDmNWRqd5132bIXA+TPtVFdLMf/4YIHUeTBK5kZ3vAP1yVgQsFAnvTfLTNxL8pSuq/E5jzm/yli74PY0Smn1fRDzuIOCWK9V6M4KlrnDZRxDpfIXQwTcebU0MzvZuTpA+GsL/MUpx5bzUBre+liW2aev5EPuwivqbM15cXf5HpkD9lMbIzRc/u4NRzc12IjqNJzOtZcj8CP/ZjXQuQONJFa6MXY12I5MdZrMMRvEu9l7s3hjMBhtc3dTxvkNhnQ4z9fx1z9+maIC0bHCo/6ItVERERWTnuRzdZLgbGTDWjOTIXxoh+Ep998xTanyT0aQbraoq+HY/RC8AdpKN/gI7g4vUGvoYl9xARkWVi37Qh2E5w9tXIS/PmALXvKlSJ4J9eF9w0F094gybmvRL2KPCo/8eHywzVbEp/9ZBZsMEgVq0BXqo/lBlpbCX8vF8TnCpj9wy86+bmmDK2thF2eijcgIi3QKkWpmt3BOdEisItaKVAsRomua3OeancAcz1814jDQOPexwe60soB3u4ghEMMvvSuSZIsBHmZ1zVq72k/zVAoVJlzBmHezUIOYzBo+cfreNxeRYMwwAMDMPAYwCGgTHh4ExA7YcK9miehM9FYsFOEUbqKWFiCPsmmHvm3mAYwSCme14IfK9C/4k01uUy9ugY4zjUagbJ8frqf+oaZ4za2FUDc9OCmI/ABhNj1J76WwJwmzQH5z9/TMxGKPxsA755e9pUbjrUvo3j+XLxyby02ABD2BMmwQ3zNvlbad87/fO9Rbu90Un6vQLJvwXIb47Qui1C284YsW3mvBA5gPc1GBsdAUJ13ngRERGRZ2tV9EirXi9SoZng9HtR+1wf+dEa+fdNPGs9U0soRdmxyZ5+3OEMBl4zSHDTomWDiV9TpImIrLzFIc8Soc+TzPE1y91Kz83poYGzyzgDe1focjPzv8LyRoiEbErXbKpXCwxtiRBeEyayxaZ4rUr1WpFKKErEv9xFLnqBdBt45td9K0MilsFuTZG9UqR8vUzu7yEe65FaDY/Lpi6K/7uohvFv6GqsZ2cPuJn7EhDAPf9+cygcbqPjio/kpwMUr5cplzLEvI/5fH6qGh9tQS3u+t8YGYD/798sevwmmZwc48xb8xrWHeL6iX5SxLaLnPkggjmaJx1rpuVgDk2JJiIiIqvJygdptQI9nxQwdrYTbwCcEpmzZQLvDTBYHmJo3jL4WQzjsoV1a6WLFhGRZ8HcaMLNyrwrT9YYumHj3RBkLjuqYd+YG8pVq1Swvebc1SsfpjFE85oKxYfMzu5/PURguETxkfOIGYw/TaJn+PGtcaiNzq/FT3RHkMFrBb6+Okjz1la8GIS3tjB47Wu+vjpIcEdk4XDB587A3Gji3LHnAgzHxp53/zjXCxTXxUh9GCXU6Mfv9zJWXWK4nduAiXGcxWFKHY/LvLPhTDxVlLok7+tBzDvlOh53cEarVO/UFoVOJqYJ9vDI3LrhytxFGSYqFEojhN9P0/6XIH6/H//ECNXFPbGABz23HqfGh1pnYvodKjcWPkb2DRv8JubM39KEjT3/6gOOjT0MfnPxM9AkuNGgVi6z4IhOjWp1en9zatqOyvwrSY2WsP5pLbwgwYwJh9qog+EPEdnbRfrsNxRPxRj70uLrmR5zjFD7f+BbF3i82y8iIiLyDC1vkOaMMXKnSvVOFftGmcL54yS2xck4MTKfJPEDtct9ZIdDJD+IEdxgYs5bgns7SPiLWGfLj3NSaiM29vASy+I3xSIisqz8b7UTqVmkjuap3LEpneum96pJYnd4XiuH4mcprG9t7O9zpD7OE9jdvnDy/QcxInS8a5I/kuD4pTL2sE35aj/H93fTP/Nh/s9JOrYMkt6fIvedTfVOhcK5FJlvFx7KNAPUSnkKVQfnSV483M2EglD5YXDhcXdEMK9nyFwL0Lp1KrDwbw0TuJYhUwoQ2bF4boKZ43kwJkao3KhRu/dsX81Cu+KEyln6/l0DHCqnMwyMzm03TBNztExx+oqKtX+n6b14fzribQgQGC6R/742dZ/NhEz1PC4wFVath/LlPPY95/5A7mn8uYOO1kHSe7vp/9ameqtM4UIvne9b911F3Go3CWxNzc0lBoCf+J4Idn+GfBWYsOk/mZsLhd0BTNOgcq1AdQJwbPqPZhYdY8oDn1t11/gI7gjJ/UEqp1Jkvp8KL2s/WqTPlgnuTRKZ6VU34VD4dObKmzXKn2f4+l6I+M7FQZpB5GAS87seuj8tU5sA7lXIHYoQ3JGm5ACb20luHcP6R4rCcI1atUz/4SSdZytTQ1KNqXPYt2ycew7V83HMLQky31an3ps5VQbLNjW/iTkzP9+9CoO3IBhc3mhZREREZL5lDdKcS500rQ8QWB+g6fUwiRNf4+zooVjK0t4IUCX7eQ5nR5LkpiUOYEy9EbTPZ8gv+Y3uEiYqZKJNNJlLLBsTs1fOEhGRFdCQxPqqG++VJC0bm4mesImcHCC9bX5KZhLb10z+3Raat3ZQfL2H7LFInZPvG4SO5fn6Ay9fH4rQHGwm+n4fg2uCBGc+nLuDdH2VJ7WhROqtZszXI3RfcAgs6vEWfDdN12t54ubURWsSFx43vPIT2RFi5Eph4YVzNrcRcZcpEyayeXrdplbClCm7I0TeeMDhtraTfMMmvdUkfKz4gEZPaPNHZE+2UHonSMBsIXk9SHTzvO1/TmEd8ZLdadK0sZnoJxB7p3WJGrtI7xnH2hHA43EROFSY3lDH4wKAn8TRNKHrHTT7PHjWbicz0zvrUgKfy4XrlTC9N2r0x1y4XC48f83UORTQpOOrPOlgmfSuZsxQhAMfF3A2NlNvfyf/OxbZXTbdWwI0vR5noDFC6+wT00/y4wzR4W5C65tobj1AobWD2BI9KR/83Hr6GmeE/jvPwH6D7G4T31of5i4L9g2QPzo919gEOEaYjncNrF1NBHwBIp85xE9l6VriPZnxlx6+/ioJ/XFMnwfP+jbS1SjWxdT0fWDS0T9AqqHAgS0BAhuj09vTRAzA2zZ1IalDzZh/62Vkr8XAQYPs3iA+jwdPIETndy30fTndHnBKBUpOhGi9cwaKiIiIPAeu3377bRJYML/F4t9fffXVFS1SRERebD/98it/+uMfnu9JRi3azAzha4N89KDwaZk88PbesWgLHSfwxRBndq7sRJ3L8pjIsnt+j2sVK2rS3TDA2Knoczj+o8/f/3aILiND5YvYM7ochdTr7t27uFyu2QV44O9L/fywf+v9+WHrnqSNiIjIk1r5OdJERESegnOvRm20Svl8bqpH04ZH77NiGpL0HPYzcDRNWXMLyAvEGR2ibINvje/RjZ+D2pU06WstpI8pRBMREZGVpSBNREReYFWsWADfawHCn4wRP5kmtubRe62k4H9l6VnfT/JI4TGvQi2yQoYztJnbyU5E6dq/xBDe5+1Ojo4PCoROWiQbl//0IiIiIvNpaKeIiDx3P/3y60qXsOxW+7DJl/ExeVms9ueevHg0tFNERGSO+9FNREREno4+2K8+ekxERERERB6fhnaKiIiIiIiIiIjUQUGaiIiIiIiIiIhIHRSkiYiIiIiIiIiI1EFBmoiIiIiIiIiISB0UpImIiIiIiIiIiNRBQZqIiIiIiIiIiEgd3PU0Gh4efs5liIiIiIjIarR27dqVLkFERGTVqCtIa2xsfM5liIiIiIjIanT37t2VLkFERGTV0NBOERERERERERGROihIExERERERERERqYOCNBERERERERERkTooSBMREREREREREamDgjQREREREREREZE6KEgTERERERERERGpg3ulCxARkd+/n375daVLEBF5qD/98Q8rXYKIiIi8ABSkiYjIstCHVBFZrRT2i4iISL00tFNERERERERERKQOCtJEROTlcimBz+ykMLHShdyvdq4Nz5bjVFa6kJU2muNAcDu9t1a6Dou2tS0c/3GF61jKjV7Ca9uwqitdyANMFOg0XbhcLlwbuyk967+3iTwHAtPHfz1F+b7j1+hvb6btc/sZn1hERERedssSpOX2eabe6DxoWZsgNwHOhQQez3Yyd6Z3vNpJ0yuuB3+oqPYT97lw+ab2B6j8o+Uh5/IQ/p+X/uOJiIgsl4kCnesf/PrnO5hf0NzYGCH5txC+FSp3tQR55c/TFFq76NiwwoU8ofx+H02HCk9+gHpCMm+Qtr0RTOPJT/NAE1UK/5MgvNGHZ62PQKiN3u+Walilvz2A65Vmur9dskiS+Ukmb/bQ+qwnE3FHOTMyyXh/jKXvAi/th2KMfNJL4d4zPreIiIi81JZljrToJzYjx8YZB6jlONCaghODnNk1/dbH7SPwoErcfrx3slj//oievyzcZF+wKBh+vM7C9Ya/Hetaeok3bR486/xPfXtERETq4g6TujJE0nEAG2tvgsLWLNmDJmBgrDMXNDf+0kXfX5Y80svDKWCdrRE9G3lAQCIA+KN89Fn0ORzYoXwsSvx8gI5jA/QGPYzbQzhr7m9ZPd9FT7WZoHvkOdTxDLyZIO4Nk7mYJrLXu9LViIiIyO/EsvRIM9b58TeamI0mZmMAA/CuC0z/bmI2eB/8ZtndQttOh+zZPAvysokK/V8MEd4Zvn9ft2/e+eYvfvxLvBEUEZEV8u9umnxtdB5po2VjEwGzhfg/S9RmG9Qo/DPB9lATvrUefOtbaDucw56Y294f89D8fi+pWAtNAR++1+Nkvp/3ilEr0ft2C4G1HgKhBL3XF337cqOfzliYpsBU75umrQfIfFtb0KR29TiJLU34PB48gWbC+6w6e20Z+DcFCb0RIvRGkIABxjpz9vdgw/Qr2OUD+KZ7qd3XI+xeP3FfC22xFny+JuL/k6F7awBPIEzq33O3xfmxn+5oM4G1HjzrW4j/o8D8Dk0Puw2183E8Lhe+/Xmc71I0T9cS+GCuV5V9KUV8azMBnwfPa02E249TmDlBHTVW/ieMZ+sBUu1hms0AgWAbqcv3d7lyruUYcCJEWxe9uk/kORAIkPifXhKtzQR8PpqixynMPlQ1rKiHln3dHNjaTNP6AE2RTvofa3holfzRNppf8+BZH+bAucrC9x73ymQOttFi+vB4PARe307nvDb5gz5cLhdt52rY/9o+2xs+cWHh8zFzcPvUOXxNhPf1Upq5Dbd6CXtcuILdlO7NG7oYOj43dLHWT5tner1nUa+1Z/FcqeXpOV0jcWqA9N4IrW+2EtmdJLpp0V11x6LjE+g+FsX7mF/L2v8K44l0kzk0dV/6Ai0cOL9wCOaT/83NFyS6I0DhYp7aoxuLiIiI1OUFmCPNoHV3DN8li9z8N4vfWmSrERI7fDgP3FdERFa9e3kKtQ7yN28zcrUDPovRcXHmY+8Y1f+YtJ8YoFixGbzQQeBSksQ/F36krlwsEDhW5PaITba1TOpIdjoYqJH7IEb65wjWdZviJy0UzuUWfqgeHYHWbs5cHsSuFOn7q016dwe5mUYTBVL7e6juPEPxps3QlT46t/jgWc75tPMMY5OTjJ19QA+jiRG8b2UpHDHJH7PgaIGB3TWss4Wp18BqjuRbXZTfTJP/wWboQge+rxIkZuaHesRt8O4dYHz6/MabaYYmJ5mcnGTkZGS2hFrVoeVgH/nrNnbpDHHHIn7QmgtgHlUjwLcF7J1ZhuwRyh8HyO1LYg0vvKn2t0Vqr4doWfIbtir5Kw6dl4cY+TlP+/9Lk/p84XOhfLlC8PNBbv9cIfvnQTr2HqdS52NVPZ3k/2fv/uPbuO87z7+QB70d3NEJkMh3QCulHFZqBNbaCnxYdyLPulbQKVeBD2Urskor4qRWguI7m4yuFWmnsVG1VSi5K5PyrUPYV8mQ92EvqD3rQSqN1lCyWkN3Kx+pPuQjlLWPUGs9CjZRQvQil0iqfWiSoOX9QVIkSJAESJAipffz8ZgHgZkvZr4z/AIz85nvj8Bpi8DbA6QuhXBdjOT2pWcNkXH4Cb3Vy0AqReyIl97DDYTeG13sPzXMyMgI7+x3YP7Bu4yMjDAycpfo7vGdSRFurKcj46f9corUtdcJWGHqnxkrk2tb6L07wkiynZry0aaLIyMjjCRewDserHI08s54mnwBrIWWlUScPmrwpENs2+DGvaaKbc9ESOY0j0wROdQBhztonG9F/74eejd10psapv+4yTvPhegZ30YJv3Merxeu9dK/DPtEFBERkZVpBQTSwF4TJFARJ3J2/GmlRezNHqxdQfx5aupbt8LUPWrHbp8yORvo0iNJEZHlpayG4GE/LoCKIK277MTOjtcgMWk82kZwhxfPahfm5iAt+0wSfb05wTDXziaCjxuAA/8uH0YywUAWyMSIXoCG59vwr3dhbm2hbb83tybzky10PluPb6OJa7UH/7NN+Kw+esc7mLfSDN124tlSO5qHx300frkez5J0jjCmrIrarR68W7yYjmp8Wz34aiYOSKwAACAASURBVDxY6SEyQOqtdnrMEK8frcdbMXqc2g5V0X8uRqpE++D9Ujsv7PXhXevCtdZHy5frcfbF6R+Pks2RRwDW1tO8Z7Q5q2tnC4GKOF0XcmsipVIpDJeb/A3xDHz7m6hxAOU1NGw3SX6QW2vMtbOJprGyUHMoSO2H3UQLGiwgTfe5OO69bbyw1cS13k/oqwFyGt+u8vPCiSbqn/Rgulx4d7fSVJOit6/AulJXw4Sv1dJ2qgX/46PHselIEPelKLFSXZ8ssKxYt4cYuhOj4xQET8eJv9mC63Izdc9PBERTp5vpyLbQvncB3WWsbaR1t4kBmLsaqL2TJDlee7CE3zljjRt3JkVK138iIiJSIkt5GzB/ZR4aD1TTfipC4stteDM9RC44aLzowzHUNS254Wqk81KI2ql7V+bEVBcZIiLLi2Firp546zJNrCsphgAHkL7cQdvL3cSTaYatu3AnA16L4bHlAG6XeyI4ZhjY71ijN/23UqSyJrXrJkJnng25/ZJxJ0nX8TYiFxOkbg9zF4tMxiB4d2x5uY/AboPAF6tIbvdTs6mWuj311Kxeyh68DAwDMAwMw2D0pQGWxV0sEh8ksS43U2lrzv3Y4zVksiXah8EYx46G6e5Lkrlzl7vZDGnLP7r+OfM4Zo2Jee/cbGKakPooBZPCVVbWgjJjxg7k3a6JE7lhN7DuDGPBvfRu05z47CoTszxFKmXBxjn2NTtA6iMw93gm1u/xYJb1TkqUIXG6jbY34yRuDXE3C1bGwv1EYXXjMx8kSd2OEXDaCExeYPgYysAM0cMiLaysuLOA5cR/tI3GzQbgIfxcD+7ne+g96cN3K0LzCWi6GMScvvHCPeae6B+33MDAYnj8MJbyO1dmABaWmi+IiIhIiayIGmkA5u4gvltdRK5YpM9FiHsCBDfOkLjMibneg2fqtNaljotFRJabrIU1udlV9u7E65thAvVhUjUhopd6SVxL0PNlLxTbqH/yg5WcII1F/Lk6mi45CX69m95rCRJ9Yeodk7fgov5MP6lLnTRuMki93YJvU4Cu2UZUXEw5D4kmcunY/85YU8JJ0wdtY00CF7gP2QShXQ1Es37az707epzOzBJImSGPuay8TfUcDjdWJjP/Pq1+Nnl7FlbBZcUOZWBMKSuTpc8G8R9J4DkU4d0rCRLX4rRtMYprcri+hd6fTfk/3X2Xlooi1lGoeZQVY5UTR5mJZ9JwoI7Vbhx3hkhbQCJOfDBO64ax2v4bWum7k6Rjq53qI4l55m2qEn7nhjMM48CpB6kiIiJSIismkMaqeoK7IHY2QqSrn9q9gYU9CRURkeUhm2Tgxvgbi2QyhWGauAHrWpzeVfWEnvXjrXDhcjkYTqdmWdkUFR48RprU9yZmDd1MTYQUsknifUPUPtNG45MeXC4XruwQ6TtTV2TgesJP8Nl2olciBIjzTt/UNBaZWynSt5e66ouBZ4MHK9E70SH9DOnm3IcyA7J3cwObAOle+m56CT7fhO9xE5fLhXF7iOFis5pMMjB+eLIpBj4Cc13u2bxqgwdSA5MGlChO6kZyIgg3mGTgjgfTzA2IWbfTpG9lckNsZWM15AYnjUA5mGRoUj4GrvRi7WghtNuLudqFa5XF0PfIw+BunmLg2ODBvJWg99YcO1EGYE3/PyxYAWXF46WqLEVqUh4zt4bIlDtxGcD2DgaS/fQnxqZvvoDXMAme6af7kGeGlc4vr3N/5+aWvpkks74ar56kioiISImsnEAaBv4D9RgXQrTf9BPcNUu/HNlh0oMpUnmmdFp1+0VElpVsisjRY8RvpEheCNF2Dvx7/DgAwzQxbyfovTH62515r42O80VUSyn30bATYq9FRgMzt2N0vNk3EUApc2OaBskrcdJZwErRdSRM7+Qgw+0YHUcixN5Pkk6nSJzrofeOh6p1U/cjRpOnEvNQbMkHwfHsbab+dpjgMxHiN1KkPuwj9vVWDr7UV9Q+OFa7cQ/2EbueGW0KN34cHCamI0Vv31gQ81aM0CvzGAkxHSV0JEZyMEX8pRCRtI/GnbmBNNd2H7WDffTOs8Zf5mI7obMJUjf7CB8Jk3i8gcDjOZkg0mji3hLK/T/jomGPj1RXmFgayKboeqUnZ6AC0zSxEnESGQCLxGshIjen/7dN002mL0Y8PaVJ4eYmmmr6advbStfVFOmbCeLnOmh+ZsqIlC4T0xggfiFJxspfc2++5iwrqxto3D5M5Ksheq6nSF3tovVkHPeuxtEuM8pdmGsn1fY3nRhlBg7Tg7mqRNGqQr9zc8rQe6Ufc6tvafs0FBERkQfaCgqkAZuDBCosnLvzDzIwzkp3EVhXSaU5fTJ3hymiLoOIiCy2cj/BrQO0bq2i+qk47ud6CO8a+5HfHCLyvIPoDpPKdVX4T0L9/poiVu6g/mSUJsLUrqmkcnsYY6t/UldULoInwvgHW/GuqaSq5iDxmibqV01aRZkBNyK07qrFNKvwnxjCfypCy+PTtzY/SY7V2LHZbDgPxLDeD1Fls2F7pJLmywWuwtVI5GIYXzpMYFMVVVsDhC4MYT5uFrcPW1po23OXyHY3drsN9+H46PxyP22nglgnanGbVVTtiWLuC1J0/aOtQRoybfg2VNHwJgTPRAhWTElTEaBxywA95+d3tvbuD2CcbqDa66cj7Sfy1gsFB1Fc+yNEd6Vo3eSmckMD3RU+aibFhsynw3R6ewl43FR6agml6mnePj145PlSGy2PxWgwR5s/Bs6NR9NMmt6O0eZJ0LarCtPr4+CJONa6KtyTV1DuJ3TcR+p4NU67HdumY/dqkPUdrsRms2HztNJ3J8ZBtw2bzUb11woc8GCusoKL4KluWtfEaN1aRdWOEAOb2uk+4Vu67jFK9Z3LxOm+bBLYV8xvhoiIiMjsbD/+8Y9HgJx+Mqa+/8xnPnNfMykiIivbd7//Az77Cz8/fcF7rVTuHKL9h1HqVWPkgZZ8sZbqK0GGYsE5+9S3LrdSfdggem28j7dCZIj43US29NP71VI2MZR5ycZpXteA9eowr+9YvM1YZxtwHvfQm5heVlJf38a2K0F6325krvFFZ/yNEgA+/vjj0QDu2ATM+D7f69n+Fvp6tnnzSSMiIjJfK6tGmoiIiDzwjK0hIs+4GbpfAzpIiWSI+G3Y1rXSV+r+3rKjtfHsjT0zNKXOkC6vp/PE3EE0ERERkWLo+b+IiIgsMw5qvtR0vzMhC1HmozM1Queird/P60MjvD5jAgc1+1WGREREpPTUtFNERBbdd7//g/udBRGRWalp58zUtFNERGSCaqSJiMii0w2qiIiIiIg8CNRHmoiIiIiIiIiISAEUSBMRERERERERESmAAmkiIiIiIiIiIiIFUCBNRERERERERESkAAqkiYiIiIiIiIiIFECBNBERERERERERkQKUFZJocHBwkbMhIiIiIiLL0aOPPnq/syAiIrJsFBRIq6ioWORsiIiIiIjIcvTxxx/f7yyIiIgsG2raKSIiIiIiIiIiUgAF0kRERERERERERAqgQJqIiIiIiIiIiEgBFEgTEREREREREREpgAJpIiIiIiIiIiIiBVAgTUREREREREREpABl9zsDIiLy4Pvu939wv7MgIjKrz/7Cz9/vLIiIiMgKoECaiIgsCd2kishypWC/iIiIFEpNO0VERERERERERAqgQJqIiDxcLgRwms3Es/c7I9Nl3qjDvukYyfudkfvtdg8HPdvouHm/8xGh7tFqjn14n/ORz40Oah+tI5K+3xmZQTZOs2nDZrNhW9dKX6m/b9kYB91j698QIjFt/Rm6Gquoey1V4g2LiIjIw25JAmk9++yjFzozTY8G6MmCdS6A3b6N8K2xD15upvIR28w3FekuGpw2bM7RzwMkv1Y9y7bs1L44sSbrwy5CjbVUrXFif8SG3emmsqaB1tMJMgDZPlrXzZJvmw3758Pcu4bN9tHqsWGz57/oHs9b5eE4Vp7dsS4exP2IDbs/Mrp90oQ/P/3Y2R+rpPaLIbpu5FvLDMaOpfMLEaZdUmZ7CDidHLxYxD5nYxx8bOY01UcSc+fpw2NU22ffVvXXRv9f8UNu7N5j9y6US3Us702PVNL63vjxSBN/uZm6TZU4H7Vje8SO06xm275jxAZHk6RP12GfrUw/Uknz5Yn8pN+ow2mz4d7XM5afKcf/URu2R+uI3Jq6ECBFxxZ7bh7H/p8527Q7cW/YxsGX4xRzX5X8WjX2NXmCCoX+f0pRFkQeVNk4zWtm/n44n4rlJDfW+Qh+wYvzPmV3uQTyEq+1Ea9poWntfc7IPMUOOKk8HJ//CgoJkjk81O31YRrz38yMsmniLwaoXefE/qgTt7eOjvfzJUzT1ejG9kgVrVfzZpJgbISRj9qpKXVnImV+Xh8a4W5XPfkPgYPGw/UMnewgfqfE2xYREZGH2pL0keY/mWLo6F3uAmR6OFgTguP9vL5r7NKnzIl7ppyUuXDcihJ57wXan8xdlDoXIW64cEyJpBiuRiJX2vJctNmxr3KNvkx3EdweJLG9nc6LDVRXOCCTovdciNZDPpJlSd7ZX0Po8hBN2bujn7kcovqZJE2xboLm2BrL3YytkcyFTqJWPcGtcSKn4rS84pt2cWe4XNw9FyF2xEe9Y/KSDD1vvAPj+Zv8mZ2dDLzagB2AuwwPJogebyKwI4VxLUr9qhmO3bQVuTD6QjSf9vHOl8z8acoK3OcyaE8M8cJ4ujGpUwEaTtsJftE7d37WtxD7qJG7YwGcxIltBC75iV5swVsGYMfumH48JnZnHsdyRyf9r/qnX3SX2XGOJU8c9VN32knLK1E6t3hwGxZDN+KEn22iYecw8Wvt1OyJkto+PFqmSRHZXUd4XSf9x30T67v3f0kSOdVL9d5Ghi6Eid6qp2n11Aw4cJX3EnkrSfCrntxF1yNEBx24ppbnMg8t33yH1g2jJQNriIFLYVqfq6Pe6qd36nqKVej/p8xceFkQeVCV1RK6NEDQsoAUkb0B4luiRJ8yAQNjVe5vsfFkC51P5l3Tw8OKEzmTwX9m+jlUJnH5eeFV/yKs2CJx1E/DW26ajnbT4bFzNzWAVT49ZfqtFtrTVXjKhhYhHyXwRIAGRy3h82349jrmTi8iIiJSgCWpkWascuGqMDErTMwKNwbgWOUee29irnbMfLFcVk3dDovomVhuzaNskq43B6jdUZsnKOKctL3JkwvX+IVgIk48U0vwaBO+x104yg0cqz34/yBK9M12AmMxCMdq18TnXXbAwLlmYp2uVeNbT9N9OoZzVytt+/2jAZ5pVY8ATx11jhiR81MeM9+KErls4tuepx6C4cS92oVrtQvXahPPk/W0vdqKLx2j+0oRtdLKfLQeraX/SDORwZmTFbbPRm66ChNnKkzraxkazkRperyQ/Bi4Vk983l1uQJkD9+T/12zXvfM5luXOPOXCxFztwlEGkCL+XhLHzhbadtdguhwYDhfm5kba3+qm87APRxYod+SUMacBlLtz1zdWNKzLESI3amk83kpgbS+RN/LV0DLw7fSRfDMypfmLRfxMF5mtdVRPCwwbGG5zrFy4cK314nu6k7Y9DhI9PQuvUVLw/6cEZUEeXu+1Uumso/n5OqrXVeI2q2l4qW9Szc0M8ZcCbPOO1hB1rqmm7rkeUtmJ5V31dqqe6SBUX02l24lzQwPh65N+GzN9dHyxGvejdtzeAB3Xpvxu3uiiub6WSvdo7ZvKLQcJX839Ac9cPkZgUyVOux27u4rafZECv2MGrvUevBu9eDd6cBtgrDLvvfesHvuhuHgQ53it36k1wu500eCspq6+GqezkoYXw7RucWN31xJ6b2JfrA+7aPVX4X7Ujn1NNQ1fy62dOts+ZN5qwG6z4TwQw3o/RNVYXtyHJmpVpS6EaNhShdtpH60Z3XiM+PgGCshj8sVa7FsOjtYEN924PXWELk6vcmVd6aHb8uGvmXJ2z8Y46HYTeLGDQE0VbqeTSv8x4vf+VRkifjvV+1o5uKWKyjVuKn3NdBXVPDRN7EgdVY/Zsa+p5eAbydxrjzsJwk/VUW06sdvtuDdso3lSmthTTmw2G3VvZEi9vO1ebfjAudzyGH5q2+g2nJXU7uugb3wfbnZQa7dh87TSd2dS08VJNbLJdFE3XlvYPqXWWinKSiZG++kMgVPdtO31UfNEDb7dQfzrpxyqWxGaTkLrUf/Y+bNwqZdrsftaCR8ePZZOdzUH38qtLz//79xkHvzb3cTPx6bXBhcRERGZpxXQR5pBze56nBci9Ey+WLwaIZr2EdjuzNu0b07rvFSV9RM92UMy5+rKwLs7SOPmmWtC5XU9QviKSWBfDa6dQRqMHsJn8/XL4aG+0UPvmWhOE8vkW1H6NwVoKHSzZQZgQTF9jmQt3HvaaavpJ3QoTxPPhRiMENwXwflclM6dRR67eSvRsczhxrveTeZShI7L6dyyVeEjuN+PJ89T+ZlliJ2OcndHkIbVXhr31ZJ8M0I8T6G1bw/gv9ND5NKkhXdiRM4b1O+uKbBmhoFh2EfLxf3q/+m+lAVZ0e7EiGeaiH30NwxdboJX62k6P/7DPEz6H0waj3fTm0zRf64J94UggZdyb6mT5+O4j/byN0MpojUJQs9HxwIDGXoO1dP2PR+Rayl6T1YTf2NKE+vbQ1DTyusX+0kle+n8fIq23U30jCfKxgkdaCe943V6P0oxcKmT5k3O0n7HdrzO8MgIw2dmqGGUHcKxM0r8eZPY0QgcidO9O0PkzFjz9nQPwZ0tJJ5oI/ZBioFzTTjfDhAY7x9qjn1w7O3m7tj2jSfaGBgZYWRkhKFXfPeykElbVD/VSexailTf6zRYERqeikzq3mCOPAJcjZPaEWUgNUTihJuefcFpD3ZSV3vJbPBSnfdHL03skkXzxQGGvhej8YdthF7LLQuJi0k8r/XzN99LEt3cT9PeYyQL/F+lTwcJnLYIvD1A6lII18VIbrN3a4iMw0/orV4GUiliR7z0Hm4gNNbs3n9qmJGREd7Z78D8g3cZGRlhZOQu0d3jO5Mi3FhPR8ZP++UUqWuvE7DC1D8zVibXttB7d4SRZDs15aNNF0dGRhhJvDBWExhwNPLOeJp8AayFlpVEnD5q8KRDbNvgxr2mim3PREjmNI9METnUAYc7aJzvz3xfD72bOulNDdN/3OSd50L0jG+jhN85j9cL13rpX4Z9IoqIiMjKtAICaWCvCRKoiBO5F5iyiL3Zg7UriD9PjSXrVpi6R+3Y7VMmZwNd4zdGa5uIvt2KeSVI1WNOKjfVETh0jPD5PtJFR+Ys4qciJDcFadwIGD6Ce0x6T0XydH4Lnj1Baj+MEBnvbyTbR7QrhX9/AHchm8sk6Toaptfhp25LkQ1fykyCJ9uovhai+XSJQml3+gjtaSWxNUL0q94lbYpT7LG0zgdHn25PmZy+jrFgnIHvRDedOzKEv+DG6a6itv4grS91Eb8xj+fZg1HCF+w07PfjAMw9QfyZKOHzedZV7ie4G7on3eSnz0eJuQIEauwFBIwt0pePcezcEJ6dfjxL0nB7ivtYFmQFK6sheNg/2ky+IkjrLjuxs+M1SEwaj7YR3OHFs9qFuTlIyz6TRF9vTjDMtbOJ4OMG4MC/y4eRTDCQBTIxoheg4fk2/OtdmFtbaNs/pWw+2ULns/X4Npq4VnvwP9uEz+qjd7yvSyvN0G0nni21o3l43Efjl+uX9jtWVkXtVg/eLV5MRzW+rR58NR6s9BAZIPVWOz1miNeP1uOtGD1ObYeq6D8XG/1tK8E+eL/Uzgt7fXjXunCt9dHy5XqcfXH6x3+c5sgjAGvrad4z2pzVtbOFQEWcrgu556JUKoXhcpO/QrKBb38TNQ6gvIaG7SbJD3Jrjbl2NtE0VhZqDgWp/bCbaEGDBaTpPhfHvbeNF7aauNb7CX01QE7j21V+XjjRRP2THkyXC+/uVppqUvT2FVhX6mqY8LVa2k614H989Dg2HQnivhTNX4t9PhZYVqzbQwzdidFxCoKn48TfbMF1uZm65ycCoqnTzXRkW2jfu4CHJWsbad1tYgDmrgZq7yRJjtceLOF3zljjxp1JkVKVNBERESmRFRFIo8xD44Fq+t8cC0zd7iFywUHjAV/eC23D1UjntX76E1Oma+GcvrRcO16gOzHMcDJG5yEfZraf6HN+THMboUtFXHHd7iF8bhj//oZ7F9zeA0G8N7uIXM4T/ljdQHDHMF1jT4ety1G6rAaCO/PfNljngzgftWMfm2yPVdNyzUvbucj8ngRXBOk8Wj1nE8/CpOl6KkCYJqKv1rPk9Y+KPJbG9jZ6p5aLRD/9bwYnbpbKvQRffZe/+eEQ/V1tBDc5GLrcTsDrpqoxQrKIQGviVJjeikaCW8du21fVE9xlEDsdnV4jsMzAty+IeSlCdBAgRfcbcar3NU7URJgsm6Bjy0S5sNvtuL8QgT1Ruo/cj37J7nNZkJXLMDEn9RvoMk2sVIrxXpfSlzto/kItVesqca9x4zuRhDsWw5NW4Xa5J4JjhoH9jjV6038rRSpr4lk3ETrzbJjSR+SdJF3PB9jmHW0O6F4XpCdzF2u8279yH4HdBpEvVrHti82EXuqi79a86kIvgIFhAIaBYRiMvjTAsriLReKDJNblZionDWTgfipO5odDZLIl2ofBGMcO1FHtqRw9To1hUpY1uv458zhmjYl57/fMxDQh9VHur6GVtaDMmLEDefekNv+G3cC6M5wTSHOb5sRnV5mY5SlSqQL2NTtA6iMwPRP9Sxoez6T8AmRInG6lYUs1laYb9xovrVcsMv9Q2LHMfJAkdbuHgHPSoBMbQiTuZBgqWaBngWUlC1hO/EfbaNzswbM1SPg5H0PneujNAoMRmk9A08kg5qz5mMNj7on+ccsNDCyGxw9jKb9zYzX4raX+yoqIiMgDa2UE0gBzdxDfrS4iVyzS5yLEPQGCG2dIXObEXO/BM3Va68p7Ye5YW4N/bwttr3bTm0wS2Z6i41BbwUO1p97oJHY7Q+wZcyKo4Q2RsFJET+cZpbHMgX9/A5yPjH7ujW6M3UF8M1TfMba3058YYCAxwMAHAwwNDTOUiNLy5Pw7zjW/1EnbprEmntn51huySHytnqYrXtrPtlFTVJPHEinyWFLunl4u1nswV+c5loYLz9Z6gl9tJxrrJ3UlhONCK6FzBd7t3IkRfiuJdaODWud4wMtJw1tprCvhiVp0k21sJOjtJ/JWAuvDLiIfjNZuzL/vHoJdY+UiMcDAR0PcHf4b3j1ZP+XGbyksg7IgK1fWwpr8ezt54IqbYQL1YVI1IaKXeklcS9DzZS8U26h/8nciJ0hjEX+ujqZLToJf76b3WoJE3+hDl4ktuKg/00/qUieNmwxSb7fg2xSgq5jhcUsp5/s9kUvH/nfGmhJOmj5oGwvEL3AfsglCuxqIZv20n3t39DidmSWQMkMec+XvnsDhcGNlMvPv0+pnk7dnYRVcVuxQBsaUsjJZ+mwQ/5EEnkMR3r2SIHEtTtsWo7gmh+tb6P3ZlP/T3XdpqShiHYWaR1kxVjlxlJl4Jg0H6ljtxnFnaLTGfiJOfDBO64axWt0bWum7k6Rjq724UZpnPU+V8Ds3nGEYB06NNSAiIiIlsmICaaM1eSB2NkKkq5/avYEFPAm1SLzWTOBIns5ny1zUbHDB7UxObYeZV9VH+EwC99PdE8Gusan/1XqMixEieTo6NrYGaVwVI/pWhOglk+C+WWoQlTsx15qjU84ABwthEnyljeq+EM1vpLDPY5Xp8800nLQIvhkhWFGCLM1TUcdyLoM9hA40E8nTDMh43EtVucXQ7YJKBulzYbrv+Gjvyy0XAx+8S8vGFF2nYnlu70wC+32k3o4SORMlszM4y6isBo415kTZWO3KvQFcQsulLMgKlU0ycGP8jUUymcIwTdyAdS1O76p6Qs/68Va4cLkcDKeLaJZe4cFjpEl9b2LW0M3UxHcvmyTeN0TtM200PunB5XLhyg6RvjN1RQauJ/wEn20neiVCgDjv9E1NY5G5lSJ9e+lrq3k2eLASvXm7E5icbs59KDMgezc3sAmQ7qXvppfg8034HjdxuVwYt4cKO09OlkwyMH54sikGPgJzXe7ZvGqDB1IDkwaUKE7qRnLi3D6YZOCOB9PMPclZt9Okb2Vyf4PLxmrIDU4agXIwydCkfAxc6cXa0UJotxdztQvXKouh75GHwd08xcCxwYN5K0HvrTl2ogzAmv5/WLACyorHS1VZitSkPGZuDZEpd+IygO0dDCQn1ej+5gt4DZPgmX66Dy1wtOgpeZ37Oze39M0kmfXVeNXXgIiIiJTIygmkYeA/UI9xIUT7TT/BXbM0HMsOkx5MkcozpdMWYOBeNUzfS0EaDkeIX0+Rvp0hPZgk/kYrB08mMPc0UltAUCJzsZPooJfgoXo8aycFNdaaePY2EXD1EjmT5wltmZfgPg/x423ENwUJTB0NaymMNfHsPdLGO0Xe91nXOwg81Y3r6XaazOE8x3nsNuZ6hNZDHcRvlz779xRzLO9Mz+volCadAVwm9mSU5t0NHDvXR/JWmsztNKmrMTqeaiWarSWws4AQbjZJ5NU4xs4mgk/klgtzrY/WAz6GzkfoyXNcHLuCNGQitJ2F+gO+pelnLN935laaTAHlYlmVBVmZsikiR48Rv5EieSFE2znw7xntV9AwTczbCXpvjBbGzHttdEwdqXc25T4adkLstchoYOZ2jI43+yYCKGVuTNMgeSVOOgtYKbqOhEebsI27HaPjSITY+0nS6RSJcz303vFQtW7qfsRo8lRiHsoXJF9cnr3N1N8OE3wmQvxGitSHfcS+3srBl/qK2gfHajfuwT5i1zOjTeHGj4PDxHSk6O0bC2LeihF6ZR4jIaajhI7ESA6miL8UIpL20TjlN9W13UftYB+986zxl7nYTuhsgtTNPsJHwiQebyCQM3pwvEo0tAAAIABJREFUmkijiXtLKPf/jIuGPT5SXWFiaSCbouuVnpyBCkzTxErESWRg9KFciMjNPI9ETDeZvhjx9JQmhZubaKrpp21vK11XU6RvJoif66D5mSkjUrpMTGOA+IUkGavIgYXmMGdZWd1A4/ZhIl8N0XM9RepqF60n47h3jV0Xlbsw106q1W06McoMHKYHsyQP+ij8OzenDL1X+jG3+u5Pv6EiIiLyQFpBgTRgc5BAhYVzd/5BBsZZ6S4C6yqpNKdP5u4wKcC1O8q732zFczPMwR1VmG4n5gYfzadSeJ5/h/jJ/P2v5UoTfa0Ha3uQYL7gjeEjeMBD6q0wsWm1G8DcG6Q2C/79DfetP6nRJp4W6SLvhpI9UeK3M/S9uC3vcXZvbx992p2KEz7dTSLP/pdSocfSuthMVZ78VppufMf7wPDywsU4kV0G8aMBaj1unG6T6j0hYtQTufwOTWvnzo91JUzkQ5PAU/V5y5FrT5D6shidb+WpWVPuJ7jbTcYVILB5aR6h5//O1BIq4On/cisLsgKV+wluHaB1axXVT8VxP9dDeNfYN2dziMjzDqI7TCrXVeE/CfX7a4pYuYP6k1GaCFO7ppLK7WGMrf5J30sXwRNh/IOteNdUUlVzkHhNU25N0DIDbkRo3VWLaVbhPzGE/1SElsenb21+khyrsWOz2XAeiGG9H6LKZsP2SCXNlwtchauRyMUwvnSYwKYqqrYGCF0YwnzcLG4ftrTQtucuke1u7HYb7sPx0fnlftpOBbFO1OI2q6jaE8XcF6To+kdbgzRk2vBtqKLhTQieyVOLtSJA45YBes7Pb0Ac7/4AxukGqr1+OtJ+Im+9UHAQxbU/QnRXitZNbio3NNBd4aNm0s+w+XSYTm8vAY+bSk8toVQ9zdun/057vtRGy2MxGszR5o+Bc+PRNJOmt2O0eRK07arC9Po4eCKOta4qd4Cccj+h4z5Sx6tx2u3YNh27V4Os73DlaN9mnlb67sQ46B7t56z6awUOeDBXWcFF8FQ3rWtitG6tompHiIFN7XSfWKIHO1C671wmTvfl0RHVRURERErF9uMf/3gEyOknY+r7z3zmM/c1k7KSpYnUN8GpboIzNlGUh4PKwsPsu9//AZ/9hZ+fvuC9Vip3DtH+wyj1qjHyQEu+WEv1lSBDseCcD6qsy61UHzaIXmvLP9hKXhkifjeRLf30frWUTQxlXrJxmtc1YL06zOs7Fm8z1tkGnMc99Caml5XU17ex7UqQ3rcb53xgOeNvlADw8ccfTwyQYbMBzPg+3+vZ/hb6erZ580kjIiIyXyurRpqsPIPd9Fi1+BQ4EZUFESmQsTVE5Bk3Q/drQAcpkQwRvw3butaCB3AqWHa0Np69sWeGptQZ0uX1dJ6YO4gmIiIiUgw9/1/proao3jnaXHUmxs4oqTP+pWuSMVlFE+/E7seGJfXyNmqP98/SV5OB70SC7v1LdIuhsiAiBXNQ86Wm+50JWYgyH52pEToXbf1+Xh8a4fUZEzio2a8yJCIiIqWnpp0iIrLovvv9H9zvLIiIzEpNO2empp0iIiITVCNNREQWnW5QRURERETkQaA+0kRERERERERERAqgQJqIiIiIiIiIiEgBpgXSpvYpoD4GREREREQeXot5f6B7DRERWWlUI01ERERERERERKQACqSJiIiIiIiIiIgUQIE0ERERERERERGRAiiQJiIiIiIiIiIiUoAlCaT17LNjs9lmnh4N0JMF61wAu30b4VtjH7zcTOUjNuybjpHMt+J0Fw1OGzbn6OcBkl+rnmVbdmpfnFiT9WEXocZaqtY4sT9iw+50U1nTQOvpBBmAbB+t62bJt82G/fNh0uMrzPbR6rFhs1dz7MPp2R3PW+XhOFae3bEuHsT9iA27PzK6fdKEPz/92Nkfq6T2iyG6buRbSx4fHqPaPvt+VH8tCdkYBx+bJc2RRGHbExERERERERF5AJUtxUb8J1MMHb3LXYBMDwdrQnC8n9d3GWO5cOKeKSdlLhy3okTee4H2J3MXpc5FiBsuHFPiSYarkciVNmqmrdOOfZVr9GW6i+D2IInt7XRebKC6wgGZFL3nQrQe8pEsS/LO/hpCl4doyt4d/czlENXPJGmKdRM0x9ZY7mZsjWQudBK16glujRM5FaflFR/GlBwYLhd3z0WIHfFR75i8JEPPG+/AeP4mf2ZnJwOvNmAH4C7Dgwmix5sI7EhhXItSv2qGYzdufQuxjxq5OxZsTJzYRuCSn+jFFrxlY8fF4YIyk/bEEC+M7++Y1KkADaftBL/onWNDIiIiIiIiIiIPriUJpBmrXLjGgz0ZNwZgrHJjVuREkvLW0qKsmrodSaJnYrQ96Z8ITGWTdL05QO2OWvrPT/2ME1eFiTnb3iXixDO1tB5twlcxNq/cg/8PorhXR0muGZ3lWO3iXi5ddsDAucbErJiyPtJ0n47h3BWjrcbAeyhC7OjUYBngqaPuh91Ezqep3z8paHYrSuSyiW9Hhp7bUz5jOHGvdt3bd9dqk7ZXU/R52ui+YlG/a2q4burxMHCtNidyWm5AmQP3tGNk5O4vkLncSsNrGRre7KHp8dk3IyIiIiIiIiLyIFsBfaQZ1Oyux3khQk960uyrEaJpH4HtzvwBuLms81JV1k/0ZA/JTO72vLuDNG6eXjNsVtcjhK+YBPbV4NoZpMHoIXw2lSehh/pGD71nokxemnwrSv+mAA2FbrbMACzIFpfNogxGCO6L4HwuSufOIo+HiIiIiIiIiMgDZgUE0sBeEyRQESdyLzBlEXuzB2tXEP/UGl+AdStM3aN27PYpk7OBrvGg2domom+3Yl4JUvWYk8pNdQQOHSN8vo900ZE5i/ipCMlNQRo3AoaP4B6T3lMREnkCXZ49QWo/jBB5f2xGto9oVwr//gDuQjaXSdJ1NEyvw0/dljlqo83XnT5Ce1pJbI0Q/ap3WhNVEREREREREZGHzSdsNtu9N5Nf53t/35R5aDxQTf+bY4Gp2z1ELjhoPOAjTxwNw9VI57V++hNTpmvhnKaWrh0v0J0YZjgZo/OQDzPbT/Q5P6a5jdClTJ41z+B2D+Fzw/j3NzDegNJ7IIj3ZheRy3micqsbCO4YpuvM6KAD1uUoXVYDwZ359gas80Gcj9qxj022x6ppueal7VyExkWpKJam66kAYZqIvlqP6qKJiIiIPNxmu0+Y7X5iIdsQERFZjpakj7RSMHcH8R0JEbkSInQjQtwToH0jMJQncZkTc70HT4F751hbg39tDf69LZBN03WgluChNuo+aM8zYMF0qTc6id3OwDMm9mcmLbAskqd7aNvemBvwK3Pg399A674IsaPV8EY3xu4YPgP68qzf2N5O/ytj/cOVjQ1wsGqx6ohZJL5WT9MVL+1X2qgpX6TNiIiIiIiIiIisMCsmkMaqeoK7QjSfjeBO9lN7IIo596dmYJF4rZX2IT/ho/4pQS4XNRtccDHDcEGr6iN8JoH76W7eOZzbBNK63IrvcITIzUZa1uZ+zNgapHGVj+hbEbhkErwyy4iY5U7MteaSNK9Mn2+m4aRFsCdCsGIJNigiIiIiIiIiskLMGEiz2WyMjIwsZV7mYOA/UI+xK0Q7fiK7ZmlwmB0mPZgilWfv7IYbl8vAvWqYvsNBGu608cI+H1WrnXBniIHLEY6dTGDuaaO2gDBj5mIn0UEvzYfq8UwJlrG6icCJOiJnErQcnxIoK/MS3Oeh+ngbbGonvH7ubS0263oHgae6cT3dTZM5TGowN5RoN5y4XPmbn4qIiIjIg22hTS/VdFNERB4EK2KwgXs2BwlUWDh35x9kYJyV7iKwrpJKc/pk7g6TAly7o7z7zVY8N8Mc3FGF6XZibvDRfCqF5/l3iJ/M3/9arjTR13qwtgcJ5guEGT6CBzyk3goTuzN9sbk3SG0W/PsblkU/ZMmeKPHbGfpe3Jb32Lm3t+cdPEFERERERERE5GFg+4d/+IeRkZGRe7XP8r3+9Kc/fT/zKCIiIiIi98nf//3fY7PZ7tUoK/T1TPOmLp86b6b3M82bTxoREZH5Wlk10kREREREZNkpdfBKwTAREVmu7vUCtvz6RJOCXA1RvXO0uepMjJ1RUmf8SzJYgYiIiIg8HOYKds20XEEyERFZye417YT8zTrVtFNERERE5OE1uWnnQpp0ztWcc7ZmnnPNLzaNiIjIfM3ZtFMnIhERERGRh1ex9wO6fxARkQfZJ0AnOxERERERKZ7uI0RE5GEzrUZaIVWqRURERETk4VGqZpciIiIrnUbtFBERERGRZU+BOhERWQ5yAmmqjSYiIiIiIvnoXkFERAQ+oZOgiIiIiIjMV777idlG6sz3Od2TiIjISqGmnSIiIiIiIiIiIgXIG0jT0yEREREREYHi7g107yAiIg+6e4E0nfRERERERKRQ83n4rnsOERFZ6abVSFNtNBERERERmUz3CCIiIqM+AXN3/ikiIiIiIg+3pbpn0H2IiIgsZzk10nTSEhERERGRucx3pM7ZPi8iIrISlM2VQCc5EREREZGH10LvB0oxQEGp0oiIiCzUJwp5miQiIiIiIg+v2e4PNNCAiIg8TKaN2qkTnIiIiIiIzET3DSIi8jDTYAMiIiIiIjKnYvpF072EiIg8qOYcbEAnQRERERGRh1epm3NOnjd1ue49RERkuftEvpl6kiQiIiIiIuMWen+wkPsK3ZOIiMhy8glVwxYRERERkULN1ZxT9xMiIvIgy1sjDXQiFBERERGR+d8XqNsYERF5EOUMNqATm4iIiIiIzKWYWmi6xxARkQeJ+kgTEREREZFZFXp/UMx9RCEDDeh+RERElpsZ+0hTME1EREREREp1v7CY9xW6ZxERkaUyYx9pIiIiIiIihSqmRlkpA18KoomIyFLK20eaaqOJiIiIiMi4Yu4X5nMPofsOERFZKTRqp4iIiIiIzGi+AwpMnqfgmoiIPCjuBdIUOBMRERERkbkstDZaIYMMiIiILFefyPekSEE1EREREREZN9t9wmzzpr4udnsiIiLLTU4faZMpmCYiIiIiIqXsD63UtdF0ryIiIkttWh9pC316JCIiIiIiD5a57hFKWRtNRERkOZvWR9rU1yIiIiIiIlBcQK2YZSIiIiuF7Sc/+cnIyMjIvRn5Xs+1vNDX+d7PNK+QZcUq5bpERERERGZTysDRQkbMnPp+vq8Xso5C3s81f6FpRURESsH2k5/8ZASKC4rNN2hWSFCtkGULSSsiIiIispyUKnBUbOBqMQNn8w2izbVsPulERERK6V4gDUpX82whtdAKDYopeCYiIiIiD5qFBpGWqnbabK/n836u+QtNKyIiUio5gTRY3ADafINnCpqJiIiIyMNqroBRoUGpxQqoFbNstvzOtWwhaUVERErF9tOf/nRktoDXYjbjXKq+0RZznSIiIiIi+SxGoKeUfaXN9X4xgmgzzZtt/kLTioiIlJLtpz/96bQ+0qa+n++yfO9nmlfIslJ+RkRERERkOZhPUGgxA2qlWlbIdgtdtpC0IiIipXQvkAalDZiVqllnselERERERB4Upe4zrVQ11OZaVsy82eYvNK2IiEip5QTSYHECZsXWSismjYiIiIjIw6CQANJ8A1qL/X6mebPNn4kCaSIicj/Zfvazn83aR1oh7+ebptjlpf6ciIiIiMj9Nt/A0HwGIZhPwGsxg2hzLVtIWhERkcVg+9nPflZQ085C3hczr5BlC0krIiIiIrKSlSrAtFS11IqZV8iyUqQXEREptZxAGixN7TM16xQRERERKd58m3fOtqwUtdSKmVfIslKkFxERWQxlU2fYbLacINb4CWvqvELSjJsaFJt6EswXNCvmRKmgm4iIiIisVAsNEM2niedM8xcjYCYiIvIgsWWz2Wl9pMHCm22qOaeIiIiISGksZjPPmeYv5kicqo0mIiIrlS2bzY5AcQGxYoNnhQbDFDQTERERESlMocGlYgNdpQiWKYgmIiIPqnuBNChdgGwxRudUkE1EREREHjbzCSKVsqlnKecXkrdSfUZERGSx5ATSxpUycKZmnCIiIiIipXc/mnvOZ36hy0v1GRERkcX0iXwz852wLjev4Z/9s0/y3/zRX2LlSf+dI7/Kp6r+kKvZ6csmT7OZmjbfJCIiIiLyoFvodfFcaQtZNtN6i5lf6HIREZGVomzqCJzj8o3ESZnF9fCz/G97rvDVX5l5tM3x82Qho3FeffZX+Z/L/pzvvLi5oBppOgmLiIiIiJS+r7H5NslUTTQREXmYfALmPjGOLzf+2/3s/9x1Tra+xmB29idZkz87c5pBrn5ncMb0qpkmIiIiIg+TUl4PF5K+0OWzbWOuPIiIiDxI7jXtnPskCeDhmT97Gtd7RzgUTecun7SecYPvvMi+rf+cz376k3zy05/lV32/y5/E/paf2GzY/vEv+N3PfI6v/F8WN07+Gj/3X/4qf/z/jH7O+ttv8Wf7fo3PffZTfOoz/zWfq/1tvhK9kdOk9Ef9f87v/4vN/KLLgeFw4PqVX+f3jn6bv/3HsYuBf/w2T/+igeN3/2J0e5o0adKkSZMmTZo0LfNpvopZVzFp5rt8PM18LOQ4iIiILLZpfaTNelLMgrHlBV76PSeX/+Q5zqfzJ7PZbPzo2/8rn9/zMoNPPM/b1/6av058k+efGOS1PZ/nK9/KQNlvcmrgbX5nFVQ0fZvv/uA/8vxGG7aP/4Lf3/7bvDzo5eg3/hN//cF/5M9/C77xzOf53ejfjW7gzrf4w91f4Vvl+3kz/h2++5/+kr/4482kT/02v33yxlguXGz8jd/kNze6MEpwoEREREREllqpAnCFpi1FAG083XwoiCYiIstd2UwLxk9iuf2WWVDmYMefnGDXv9vLV/70W/j+9x18alrfZmnOht8g/SvPc+HP9rC+DMDNnj/7Osn/sImX//w8f/ob+3Gs+jnsZWAYdlwOBwA3Iic5+3cb+dN/96/4nc+Nrs3Vcoqj7/8yT/2r1/jO7/wpG39wg+THBht/cz9bHx8Nk7kqTvD2hnoGy92jeX/Ey9On3+bpEh0oEREREZGVoNhgVKkDYwqGiYjIgyzvqJ2T5T0RrtrFS3+yleF/8xzH/29r+pOpbILE+xaOJzaPBdHGlK2n5gkH1v97nev/OPkz468zXH//OtYvbWXrL03eoINf/3Uv/NVV+m4Dv7SVHb8K33j28+z709f4xv95g0wWHL+ymY2/6Cj+KIiIiIiIrDALbR5a6tplpWieKiIistzNGUiDsZPi6It781z/0yscfXKIVw8f57p1L+Fo2n/8CRkLnM7/YsqaDIxyB9yxcvo7m9jOT8j8Z+CvXuS///Qn+eQnJ6ZffvYyVnaYH/1/NmyPeHn+W1d4u9nLj771Mvv8/5z/6ud/mf/xy/+a7/yo9H1OiIiIiIgUazn1p1bs54vdzkKvtXWtLiIiK0VZ/iacMxsPqo2UmTzzLw/T9WvHae6sp7Ps5yat1cBZDsOZu1NOihaZH2XgUw6ceddu4CgHPvcHvP1/HMCcllsD1y+MvS5fz66vvMKurwC3b3D5L17lSOgpdv5nBx+8sYt89dJ0ghYRERGRh8FS9VFWiutrXaOLiMhKkjNqZzFsNhu2jS20/y/rud7+LF2TBx4o87J5o0Gm7zLXs5PmZ69z9f0MDm81nkds94JyE0+7HHg3b8T4/iDpT61n/ecmTZ8yMD5TgcMA62+vcv4bV7m3yVXr2Rp8haMNLjKJBIOTtykiIiIi8gAq5eif863ltlAKoomIyEqT07Sz+BOoQc1X2znguMyr/+bGpOaaLup//wDmX71K8x+e5fpgmvTNq5z9/WbO3NrIgS+P1xhz4iiH1PtxLn8nyeDHNjy/10Kj4yJHvvTHfKN/kL/7/iDf+fbL7Nu+gS1P/1v+zmbDNnieP967m31/9G/5y78aJH1rkOvfepnXvp3BtblmtF+27HVeO/hF9nVcLcVxEhERERFZFEvRtHOu7c7nc6XYvoiIyEqTd9TOopp7OrbytX+5h57fPjtaQ8xmw2YD5/avc6HbzR8dP8L/sHEICwfmZj/Pf+Moh/87Y2zrm9nfvIvzf3KcnXVnOfD6NV75jV288h/OURE6xnP/4iRDt8Go2MjW3zzNpdAeXAC/fpRv/muD575+nN/qTJK2DBwVG9n6W6e5EPJjtwG2NNe/fZ7zP2nkJzYbRimOloiIiIjICrScAl8KoImIyEpm+6d/+qc5o2WF9p9WjMVYp4iIiIjIw2wxglSlXKeCaCIistLlrZE21dQTXimCYPM5iSr4JiIiIiIPi/sVdFruwTgREZH7qaBA2lTFjvRZKjoBi4iIiIgsDl1ri4iIzG1egbRxi1FTTUREREREFt9SBM4UnBMRkQfNggJpUymwJiIiIiKyPC1lUEsBNBEReVCVNJA2Vb4TqIJrIiIiIiKL634GshREExGRB9miBtLyKeTEqmCbiIiIiEh+yzVQtVzzJSIiUkq2kVH3Ox8iIiIiIrICKYAmIiIPkzK4f6NwioiIiIjIyqQAmoiIPIxymnYqoCYiIiIiIrNRAE1ERB5meftIm3xyVFBNREREROThpuCZiIjIqDkHG5h60lRgTURERETkwabAmYiISH5Fj9qZ76Sq4JqIiIiIyMqkoJmIiEjhPlGKlejkKyIiIiKy8ug6XkREpDhF10ibSaEnYdVeExERERFZXAqQiYiILI6S1EgTERERERERERF50JWsRlqh9HRMRERERERERERWItVIExERERERERERKYACaSIiIiIiIiIiIgVQIE1ERERERERERKQACqSJiIiIiIiIiIgUQIE0ERERERERERGRAiiQJiIiIiIiIiIiUgAF0kRERERERERERAqgQJqIiIiIiIiIiEgBFEgTEREREREREREpgAJpIiIiIiIiIiIiBVAgTUREREREREREpAAKpImIiIiIiIiIiBRAgTQREREREREREZEClN3vDIiIiIiIiIg8zL77/R/c7ywsS5/9hZ+/31kQmUaBNBEREREREZH7TEGjXAouynL1UDbtTH19G3Z7Ncc+nJhnXe2gzuPE/oid2peSBa4pybFNduyNPViLklMgmyb+cjN1NZW4nXZsj9hxuquorW8m/F56sbZavNsxQp+vxGm34fxChPRgmG12O3VvZApfRzZBaIMN54HY4uVzitGyUEfk9pJtctmLP+PG7gnRl53/OqyzDdhtNmwzTe6DxLIAFl1ftGNb13pve6nX6nA+UsnB83nKTiZG8zobTl8HySz3ysyM27HZsD3aQI81Q74esWF/zE3VlgaaX4qRvFP4vtnH8zDVpYO47bV03Bh7fz1E9SOzfBfGviu1L6VG39/bJzvbXpvpO56hq96JzWaj+khiyufmeSzGJ7sT94ZtBF6MkZr8w5aN07zGhn1fz/RjcjNGx6EGaj1unI/asT/qprKmjuaXp6zjfrgeovoRJ4ELxXxoCX7bl0KpflOzCUIb7DifWrrf5gfb6O+eveYYM15tjP0uNLyVufeZ5OkA1W47NnsVre8VuKnzAeyP5F7vLEfxZ9w554HFZJ1twG6vpePmAlYyGGab3YbN3UDXrTzL73TR8Oik3/2x388Zv4tj31X7FyLc+4+fbcD+SOXs/+vx88eLhV63Fid+uBKb2Ux8Cf4vhVsZv8/3ytmNudMumH6jF9fY97fycN/9zok8TPS9XvYeykDadBY9J0PE7vhov9xPdK+ZP9ntCHWP1dFVRGxoYdL0HKil7mgvjvo2ohd7GbjWS/erTVT/sJvmHX5C7y2Py4j02Q46Lhs0nOql95UGXPc7Q4sqybEaNwcvLrd1lUZVYwedR+rwLLS+apmL+pPv8O6/f3f61NVC7QzrN5/upH3nXSKHmujJiSNliD3fTCTjp+1US07+jM0tdMfybOffv8u7PSFqjdx8Nb7yLu/GR5d3v9pGwGsRP15H9aYAkUIuesvAutJG6xup4o9LQQyMcujtipJ3C+luopctjHJj2qJ5H4vxqSdCaDv0Ha1j21M9zBWuT19sxbepjtDFDNX72oh0ddN9po3gBovu5+uo3h6i7/9n7/1D2zj2v993QIURKLACl7t6rnvxGhcik0LWJBAJ+w9vSCEyPhCZFCKRA6nSQiqn9yZ2w23tkz9ylB7IkVto7fTe1k4gRS40SIEaK9DgzR8uUiFBKiRIgQQrz5M8j3RJQIIYtBDD5/6xa1s/7ZXz+3vmBSLE2p2dnfnMe2Y+mpnPK9PMLfLKtf0twyJh6Mwkpg73vO6c/OfQpmDkwiQCLkH//0oCU2dnkftgHAvJKEZ3Nb4teaob3af5ZG8j2J4gJi+MwvMiBipPYhj5Kob/GtLx5o1HAHB9NgPX6Dq0OT8cfRONx1AvhVfYfrQsZv7eA8f2bdi2bf2Hwtz3+9Z+ILV6Zv6L6NLr49XbUA1bbddvmWa+zeMWvrUTAFBCuQQwp4KhXmdTJ5CWTiKlAf5Xla1HUUxdyUM+u4DIF+vOPecuGUq/BBwYR3oxDa3Xhfrp9KulWCpCYzI8h1xwMgAPXnOGXialNFJ3NNjftLReEGKvD4EXkpIV0h4PlN5W75MQuDAF1TWE4OcDcP/qgwigdG0Uw5fK8FyYRLCr5ha7E8oBBYLJfDlkpSpfnkMBjHw2A//+Yxg+LKE7GYJro0bFPAgeymHmzChmB6PwvQTPsdSvADcimL0zgrGd1d/lrsxCFRUoUJGvvfE5ywIAlAMe9Fh64P4+jMgZL0Zqy3uVRzMIfjyB9I4xqNdCcFU81HMogMDgMJSPziHw9QAy512mcvQ6eOXa/tYhQD4UgPy6s9GMFfzXG83YnPAcdVb8oYRiCZD6vFB2OZvclEPirxyw+1Vk8C2mS0Ggmaa1gkWE94gbiZ9HMX5EweR+c6r7xvIGjkcArs/meMM1+lVi9AfZZBolvELH4itsP9pcCKOLTkylVXiLcnEYAAAgAElEQVTa9B9eAUA6sYDyCSD7Lzd6Fl9iBu5OwL1HReDePAINxr/anRmMnp5AdDGHks0B+VAYse+8dfNr7dY43P3nkO2fRv63gMlx66vjldtQHVtr12+kZjYdp73d4xa+Ik2LYWi7A8eua9CuD8OxbRt6/lm/RD77zx5YP5xBYTkOv30brN7ZdU+/RUPul1Hsc9phtVphd+7D8M/ZqiXnhRsTOPZhNxzbrbDaHej2DGPqz01cxcsllPVM1n8neDCZTGH+S8OJ9mgK+6x2+H/JYvbUAHres8NqtaPT5cfUrer7c3Pn4O8z8rLdge4+P8bncvpT7k7AbbXDf7XintIshrZvg3VP9TaU9JkeWKWP8X/ut6L7TFrfymDdBuuHUw1Xsaw9125d2z42/FN6419MSkmMu+yw962vatEexHHO50anwwrrdjs69wxhtKa8G6HdncWwUQf293owcHq2wbazAtRvj2HfBw7Yrdv08lH8mLhhPPzGMDrf9SO2XMKMp3KL4ib3NaJBWv/vuR5Ytw9gqnaryJNZDNmt+ja++xNwW63wX0pi6mM3Ot816vHDYczerX6hrdhd7dbO0q0pDHt6jHqzwv6+G/4zceRe5lYP0YupCwFY50YQ+CkHPIlj9PMIygcnMHW0yYrR54TtCGDqay/YnSlMzm3SNlcY5K9C8LM4xr+Kv5xf/bo88HRkEZlN13yRQ+zXBKQDCqSXVgcMsksGW8kh97D5VdlLU4g9cWLk22on2iriYBjzixmoZzdyoploO2b1rZRebxP2TvR8dA7xDfIPPL+2b02PNGR/GcXQnk7Yt2/Dtib35a6dg9/VqW+XfbcT+z6egFohrtrdWYx6jfd9xwq7pOtadqOHL2cxe3oIPe8b72SmPddtLzCX/+rn6v1I/Zbj6m1pm5ankZfOUzHET7vh2G7F0C9GjZXSmPl8AD2S8W5SDwY+m9rSishN+6uVNMZlKzpPxZH8aRj7jG3N9vfrbSQ3N44B2QGr1QqHcx+GL6WNvn0DKrd2Xh+GwzqE2WUgfaYb297pxPCNmutXYvBv78ToDQ3Zf7ux7Z1ujN8yvrMAeKxiwteDTrveX/R8dA5q1ZEGJaR/GsaA7IDdaoXV0V1nb7Vk/6n3VzO11xRmMLDdujaWatlOV5IYfX8bHJ+p1X//cxTd7zhw7Pr6n7bS/uq2dhZUTHy8D90O/XgPu4l31/OpwT4YRmh/ETOnQki+GRsEtkbTsQ3ALAzarRkc6+tcs42B0zEUKjXDhK6onzlgdZ2DemMCflenPi4x0mqmP69cn0sx+N9tvIUveaoT2971I1YCtjLmK10agNW6D1MPqv6Kmb9ZYVUqVr28Lo2G/l7Jb49hn9NhaKgbQ/+sfrZ2dxajHxnt2dDGY/9W1+3BhDZqN4bR+U7NXAOAvqrLWjGP2FyX9PY8gKkbUxhy2mGV/y+M7rei519ZaH+MonObFe5vcy2UbQHqv/x6P7Ldjs4+PyYWNxGDDdrPhnOuLZJ/lIP2vhtKlwBBYGBv0g9JhVn4D4wiIQYxcy0BdXYSwy5H/XVaEqGTKuw7X6D7rIV+eWM7LmDqwyY21IBNxwstzNHr3qeyXZtIp7lmmuvjc1crxisfDGD0ShaxTx26D2CtnWyelvqprvfxn4+hx2GF47MG21MbjFv+7/9nVNeGK7VamsOEomtDbiWJUacVnZ/HoP7bvzbmc8gDGJ+rrqet+gxMQ28Rt2/fpt7eXgJAvb29dPv27S2ls/SdQozJFDJuLz/OULifEesPU+ZxkYrlBjeVi5T62kWMeWjyXpGKT4mIMhTazYjtkEk5Eqb5dIaW0gsUPigRbApNPjRuVUfIyRg5j05T4l6e8vcWaPqIk5igUDi7QUafZSi0lxFsTvKejVDiXrH5tflp8jCQtMNDwcsZKj4joscLNLaXEdsVotQz/bJiPEgSE8h1MqLnJZeiyEkXCUyiYLxI9CxFYzsZSScT66/+W4DEDokkm4em82ulSJP9jMSj81R8WqTElzLB5qXpfJGKT8tEuUlSGCPPRSPPt0PkYozkTyKUyC5RPpehhW+8JDGRAr8Z1zxL0dhOkHB03nhwhiYPiMR2BWn+sfHYx1EKdDAS9gYpcnOJ8g8ztHBeT8d7eS1zDeovQSM7GLHd6/fNn/eSq0MkMA9NG+nnf/SQYJHI990CZXJ5WsomaPqok1ibh6YfEtGzMhV/HyGnRSDfbJ6KhrFsel/D+m2Q1sNp8tgYuc5nqqv3oocEm0Lhe2SULUjsUChg1HU5N08jewViO0YoYdjvVu1u4bhIbMcYJZ4R0dN5CrQzkg5N0sJtvd4SsyOktDGSv840TaM86yVmkWhksflzjCspcogRukb059V8t3DSSaxNId+gRKzDR9HaKjZshh2YpHy5TOW6DxFVpLtpvooR8tpA4vGFjd/NsJn8ZS+JzElBtUI0fg+QyFzrZZweI9lS0RZqMdqK6/xSxTsxkk4uUOofMrGuEVqo1KTbIZJtMo0lF2iki5H8j9RLKYvM164qnaRnCxRsB7EjUeMPeZrczwg7GtWdeUy1HVP6VqToEZHQptDYbxnK55coFRsjzy6JBItAvt+aZOA5tH3LepQcIScTyXN2nlL38pS/l6Lo1x6SmEQjhi0Vfw+Sk4mkfBmlxO0MpdRJ8u1kxHrDlHlGROUFGukCCb0jFL2ZoaWHS5T6bYyUNkbOLxJUJqrXVFqi6UGRICo0FkvRklFGishIOj5PTXsYwyaFT+ZN579BQVM+t0RL91Y/KZo+IhFsMo0ly+bL81mKQrsYCbtc5PlkmhZupmjpMRE9y1B4v0Csy0vh3zOUz+cp83uYvF2MhP5JvczMYqa/WrWRDpk8X8zT0lMiKudp/riz2kZuh8hlY+Q8Mk2JXJ7y2QWaPKKQ1A5ie0PUVEUNXfBeLup9RX6avDaQ/GWCisUilRu8TzkfJV8bSDqxQPnVa2I+YhaJnL0eGrmcoMy9DCVmgyTb9OtWayv1tT4O8J5foMzDPC0lIxTcKxDbPbbWp9SRDZOLMfL8WG3r+R89xJhL76/M2Cnp/c5aP/AsQSNdDXQ4OUJOi0iB343/b7H96Rpu5I/yNH1QILYrQNOLev4y6jQFdgskHJimpqnkJklhhq5kw6QIjFxnU+vfP42Q11ah+4Z+rrfFGlb1e3B6rR2a6kdX+48N+mNTNBnbLJyUCKKTXPsDNK1maCmbouiXiq6pv67m1JyuLJyQCG0SyYdCtPCwTERlWrroI6kqrRpeuT6Xaf6oWD8mMexY/GSeymSu31qzM2MsULzoIcYUmsxVPq9I04P6/GOphbKsr78Xo9Gpsy5igouCFxcolc1Q4nKQXEJFW30YIa8IEg+EKJpeonx+iRIXAyTbGMn/WG3PJrTxWYJGdoCEI1Gqys3tEMlMIK/RbszoUvlXHzGLk+T9Xhr7NUGp23kqPl2iyUFGbG+IUo+L+vjHZNmu1m3VM/c7SbSham5UXf6N28+mc64G/PdH/7NZLdPSNy5iAKHqUz++yXztInZgurG9PJynsUGZRBsjJjrJ82WUltZsvUgL532k7JJIsDES2mXyfFHx/b0wuVjt80GomGdmzsok7J807LkZZUp86SLX2QRFjwpVutdqmdS8ubl+2YQdlxvaUAPMjBdMztHrqG3XZtJpqJkm+/h0iGTGyHl4khayS7SUjNBIv0zOHaxqvGImrYUTErEOmZTBEYqoKUrlGtdw3bilrNehMFjT/94Lk4sJxpjI6C9FiZTVen6aoegnTmI21/q8Zatj9BZ4qxxpq0601U9vb++W0ql1pK1OCNn+yeaDJjIEjHkosmYLemWjK1g90V0cIckiUOA3Pe3pQWOyWXlNeYGCHYyk4wvUrG0SEdHDBQodcpJg0d+ZtcukHA5S6OICLVXeaDQu8eh8VXpL511rk36iPE0eYMR2h6onFTUDuIUTkn6N8XXipJPET8I0tlsk369G6sUIeQWBvLN6YWTOygSbj6Kr6dY60spFWrq3RPnKzD1boGCH3ngq8yEcnSd6tkSRIxKxHQGKVjii9Mm9q8YRVKTIIYHYrrGmYlSOB0i0iBSIVxWaXjcVjjQq5mkpm2/QsbP1d785Rk6LQIF4ZRZM3NeIurR0Z0D1u+Rp+kCFqBiONOFwtKrjKf+mv2Pw94p324LdVTnSsoZwzVZfXbydaCqKROsTgODvRSo/Ldd/1pLbyJFGRE8TNLITBIvYeKBt2Exdp17xWXM0kYmJiTGBYwcjTTv1Skca0RJNHtBtb62cX5gjLUHlbJhcrNpuU1869Q6tnGjoSGu5LNSy7mBb/TzNU2p2hFxtIOHA9PpgqNaRtua422CyaQYzbceMvj3WnaDOL1OVKVHmvItYg4FmJVvT9q3r0dqE6mH1fUtJwylktHnWG64ajJbVEPmOjtH8QyLdMZUxrl+7gqKHKzS+1pFm5N9zsbrGlr5TiNlqJ3gV1AzmNs//5hR/C5DEBFK+WXcAmCtPo246AjT/tOIyNdhwQl687CXB4qSRpLl8EZG5/mo1H7WO5KQ+mVq1kdSXToLgpUhluTydp4DYgiONiOhZlHw2kHx2A4fJMz1d5xcVk72YjxgYKRcqLalYbV9Po+QTQeLR6j6F0mMkM4F8s83UcEn/EbJKA2rHUybslLbmSNvyeKDSkfZM19G6PvFhihLpfPPxWaUjjchwQFT8SPW2OdKIGo5tFk5KBItMoXTFdWV94rNmZyZ1ZeGkRFhzYK6mNU+BthqbreFV63M5HiCRSTSiVvxNDZLEpPUfzUz0W1typL1OjX4aJZ/h4K4k9V2AfCcjlCF9rM9stemWaf4TiSAGaL5M1Io2sjYfRSt0PHVW1v9WJPO6tKpx31RrXORgTR9qqmyXKNxb3/fS4gg5LRs40ogatB9zc65azDiNls67NpyzNnekZSjcy0gcDNPCvTwtLU6St6NSP5Yo8o8xmo6nDAfJNAV2CPX6kg2Tq2pxxfo7T+9n5PpymsKHXSSJIkl7fRT6vfrC8uIIyXv1cfP8Jy/ekbaZ7Zmz4wY21Agz4wVTc/QGNHGkbZZOnWaabEuJLxqMV3KTpNgqxism09L7DieN3dyo8KjhuCX/o6dO7zJfu4i1G+O+1flOR00f8HiaPLb1uc5W+4BWeKu2dv7xxx8b/v91wWR39QHegh2CRUNZ04CVFJJJDWKfUn3mEnNDcTHkbyY3Xq7drmDs1wzyD1OYvxzGyAEJSEcQ+ngfut/fh3N/VC59ZOiWnVXnpVkFOwANmgZgJYX0TQ3CHlf1QfIWJ9x7BGi300itAO79CoS7CSQKAJCFupiHu88PZY8VycUEAEBLqkisuOHpN7kklzFot2cx/pEb3e93wvGeAw5pCDOPgKJWs8ByJY/46SEEFmVMzk3D2776RQnpm2loXQqUqvNNBCj9PcDdJBJNom/m72RQsnRD/qCydES4XdXlBRuQuxaCv68H3ZKRz/1hZDVAq83ni7ivDgGeo3447s4i8qdx36MoZhcFeI5WBnFgcO6Rq84TYE4nJEsJ2fuF57e7VboUDOwCYqcU+M9MIXYji9IKIOx0Qe7YpO5Xcpj60A7rdmvdx/63xtt/a9HuzEN9wMBYAeqVeNN7WO8Y5pMJJOo+KUQ+bXaeUCPKa/v4zZ07KCF4fhzy/QmMfPvio6axHV74+0qY/8XYPrqSRORKDu6PfE2DQbRUFiv6Uult72xb/2x3oOfjCHAgjPhsAJtupF15zgXSptvOJvp2P4WsxiDL1e/o3N0Dxxa3PWyo7c+hR0KfF4pNxfjgEEa/nYX6VwEaBEh7ZUht0NvvTQ0OWa4qf9Y/hsjFEDztenmwUhozp/bB/UEnOt9zwPGehMCcBm253HC7ce5mAnmLE0p/9UklUr8C50oKiZvm6nLT/G/GgxkEPp1B+UAY0ydX66u18mQfuOC2VbzbXynkLT1w1+wxFva44bTkkL7dQpTrFvor9kEP5Er7stnBKmwkdScHdPVArsyWrQcu+RWebGqR4NpTaUkC7G2AtqyhtALgbgrpJwzu/pqzFXcqcIslJJOpJglL8B9yA4uziK4eR/Agitgig3J4tb9q3U7NsfX2V4VFhmdQQv7SMQx8eg4zc0nkSgDaZbh2iabPn5W/mECwPYHQ6ZnXdzD1y6KtB67KczotAhw2oKjpG5Rb0hWhB3JHZVp2CMJ6Wq3wsvSZ9fsw1J5HbG51a7GGxJUo8h1e+PuMB76wMV81r1Wj76aQLgHynuoTmeQT04h844MTJaTTWWhdLrirssf0sfSTFNIVkXA31kZA9vnhXI4jem01sm0a0V+zEAb98AhoTZcsDsiujUcrpsp2JYvs3fq+F7vdkG1oDZNzrlfKnRgif8kYPj8CpUuE1BtE+DMZ6dkI0isAIMF3NoTAARnOdhHS3gBG/i4hnUyY0+qVPHKP9WM/EntCiF6PI7y/gMmP/OtbmpdVjJ9Qofx7fOOziJ+DzfrlVux484eZHS9sMoY1/8DW0zHVlkrI3M2BdfVArtSIDg88e1iLaRkIbrhrzng2g3goAK8tgZlfjHnVShaxWBrSoQCUinbIZDd6qvqAbsjtQPZuDtqLGiNswlvlSOvt7d3w/68NywZKsKKhqAGFS0OwWq0VH33/r1bI1x8W3gAmyvAcGUHoxygWskXkFsNQoGL8RNgQv9W8WDfNi12ovYaB2ezAsgYNAOtT4LYkoCY14JEK9X4P3H0ievpkFJNJZFeA9I0ESnsUKCYPWS9dCUD5KIxMRwAzVxeQvplGOhlBoKPBtXOj8H+fhlbKo7BctaMdxWUAd8/Bvd1aVZ7SKRXaShGlJnOl0lMNmkWAvaYjZKzyWFAN6mkFA2dU2H1hRG4k9HxeCeoBFJqy1fsaw/oCCOzMI3JZhQYgdzWGhDiEwIHqCaLdVnOkKWOwAigvl1+Y3cEiY+x6AtHPe1C6NgH/h92wv9uJfZ/NIL1Zr2oR4buwgMRiou6jfmMismtJxfgnE8jvn0RiNgjr3AiCl5pU8HYJ7r0uuOo+MpztLVTCkxyyBUDqkMwH8NgZxNRJJ9LnhzHVSue7yoqmn5fU0NkjYeiwAm0ugvgTQLsRQeyJAt+hDQaMrZSFRYTvYgKpmyn9k4wg0MUg7A8hcnmk4bln6/c6IL3HoOVyz3FeXottZyN9e6qhCAZrbSTT7cLWg7FspO3PoUfoCiCanMd4H5C4EMQ+2QG75Maxb1XdWWy0X1bbxiu5PwX/fj9mCi6M/jSPxM000jfTmBpsXmmlogZNS2LcWZ1f654Q0pqGwhOTbo3N8r8RK1lMfDqKuC2AmR8rHbUtlqfNXlWvpaIGDfUaD5uhiyXzE/VW+qvNbETTAMZqz7ARYH2lEYLYxs8rllCEpp+DUmkXxnmd+UKp6Xki4kEfFEsCsTm9cnJXI0jYPPAfNBR+C3Zqjudof1UwKN8kkPjRB+lRFOM+NzrftaP7b6N1Z45unIwL498EYL8+jvFfNnhw0x8eNONHnA007nXBao3HWtVftaQrL9LuX5Y+MwX+gxLyczGoGoBlFbNzJTgP+eGy6Gm/yDFfJa9Vo4ulxn3oGnqZMpsdQs14hdmEte/X2LB+AOz0wr9LQ/yqqjtp/ooidt+BocOKbiYt6VID7a/BVNlqpcZ9r2UTDW2EyTnXKyWXQc4iVTmzpZ3dYA/Wx3GFGxMY/tu6U0g5nwWWNRRNP0SD9kEQUycVyDtleM+E4G9LIDaXA6BBPTOMeF8Yod6X2Ama0AbTdrwJrY0XXpC+t5qOqbakQVtGgzGzA462VtMysG3x/D7Bg8BhB7KXZ/Tzuu9EEL3rhP/jmuCKNlYToEKA1QZAK0J7YWOEjXmTjifclB9++AHHjx/HH3/8gd7eXvzwww+vO0ubYzhvxIMzUL+qj7vBLPbmqyVWNBQelSB01P8qKvaOYPzQFOI/ZZFdhrmIHhYGuw0o1k0oNJRKRUAQ9GgzggKPS8O5xTRKmopUuwvhdkBwKei5H4P6yAttMQfn3zybr1YBAJQQ/yWGQlcQsW8CxkAEgAa90dbARA+mfhlG7oQHoSPjcC2GoQgAoOcfO0YQvdJgpYyFwdFel5ye5nYGtlLSG1VFqysVi9BgHIK5omL2lyyEQ/OYPK6sl/kDDdqGh7xu8b5mWJwIfKogfCaCeMmJ3NUEnIfDUGqMoLhcrH6ZZd0hY7VZn8/uarE54f1yEt4vATzJQr06hfGvjsGzbEf2sneDKDtWOD5Q4NqSv7uE+OljmCp5MPNdAHJ7CZNH4xg6HcBM/3zjDuoFkLs6C3VFQuBAKzFyGOTTYQSvDGD89Aw8x2sqqs0Bu0VDPpdDw5b6MIfCCoMsNjiMFYB40A/P6SAiczkIi1EU+ycw1A590vXcWOF43wV5LVqOjPA3KlTvKIZ/UjD/yUYtXIS7Twa7HkPkRgiu/Y0GLhqSP0wg80EAgd4GrtMX2XasDFZoKC9rqJqtFUstDABbYet6BACsy4OR7zwYAVC6n0T8Yggjp4eQt6Uwf3RVq5vnPDcXgbrsQuhCCN61X9tKxvs3RrDbwZgL49dn4K1blcBgF82Hn90w/03tRkPyjB/jSQnBa5PwVOXh+cpTsDMw1Gv8atCe+slMM1rrrzaGgTFAe2zY85rmlloaqL907ALsYOg5n0J4f/3XTNjghwVxCP79owhcjaLwiYLYr2kIg+PwGnWwFTsFoJdVrQasVIZeej57qUaAfCSE6SMhQCsgfSOKqa/G4R8ExNv1fW/TVPaHED4Uhf+rccT7lJpv7RDaAK2QRwGo/yFpOY9cARD6xTcuct1mvEhdeXE8n324PvJC+n4WsaQG93IM809kjPqM/vuFjvm0Kjt/rRptF2CHhmKppg+tfL4N0B4X9ZWsFWNIbbm0NscwjxNenxvjZ6NQS144fo0h1+GFv59V5GeLutQAU2XLBDALoC3X9L3aFjTb7JzrTeL+FPzeKbDTk4h81wMHA3IXvFD+MOnyswiw2xmELmld4ywipPeAeL4EQENyMYfsnQHYfzK+X9GgYRgOu4qZhxH4Wl351zIv0o5f5HjhJWKqLWn6bybF2h/O8ihWrtx6we2yMQzKxwE4f5pB9M8QWDyGnCsIX+3qtmUNJVQO+fTo5njfDvZCxwjNeatWpO3cuROLi4sgIiwuLmLnzi2sF3wBtLQA3dIN1x6GUi4PtsMJZ8XHwRjsDZxkqyRPd8PxgRcTdxoJWAGZB0WgzQHRbIO36NtJSkm1ehXbShqJmyUIco+x/FiE0i8jn1QRuZEA61P0v7e74epIQZ2LQ70jQek3u2XO8P63OSBWCFbhagTzT1A3WGYuP3y7XBi7FIbyZArHPo8Zv6AJeiTBRznkheqydAoMrE2C0KQwpR0S2EoG6dtVsdSQ+LNiO96KhvIyYG+rXOlQgjobr4hUUlluW7yvETXXiYcC8CCOyPdTiKbd8P+91gGjIZtMVi21Lt1OIbvigPyB+Fx2V/WUB0nEribXf8Fsc0L5ZBKhQyJK6dRLi9xZuBLE8KUyvOen4GsHAAGerycRaFMx+tnUS3mu9tcEhs+qYP0jCPa12A3YFIyf98N+bRyj14qwVjop2xV4djGkr8xArf0xeSWHme+jyAkKhho6ogAIXvgHGRJXzyFyHfAc9rzUiZYwGEL4EEP8q2HMPNj4WufRYXjacpg5NYx4g192CleHETgVwtRvTSJUvYi2s0qXE06mIZ2u3mKbXkxUR5fbgNY2F21djwq34ojdWN8AJnS59O0UOzWkbubWtLpQo9XajXHscw1h6o6+LU+DvfqXwvsRzC5qaBjpGYDkkiEhh9xTqTq/7XYwmwOiScPaNP9NKF0bRuDbHNxnIg1+jd56eQKAtMcNx0oK6mJ1IyskE8iuSJBlsxPQ1vqrjRHQ3eUAHqSqV/A+UaGm36AQjzvccLcBuXyputx3OGC32OEQN9JDQdekZBzzizFE/6pYUYKt2emqA7K0XD2gL9xOV6ykfj57WWM5B/VKfL1+mAj5QBCTpxWwR2mkW/rFWoD36xA8yxGMfp2q/qnaImNgvxPaYgQzf9W+t4bsT1OILUsYOuhu5YEvhxa190Xpyma8Kn0GAOz2w78zj/iciviVeZRcfnh3GN9tsd9i+iwVpcoJtpZBuiJ87WvV6B09kAUN6cVEVbtLfzsA94fnkFwRIO+Rwe4nkaiKLK8hsZiC1uaGqwstIR30QdHiiF6PIzqXq1j1h+fUpQbPMlO2FgndOxjy6XTVFm0tmYBpyV61AdNzrhcPYwC0Bive3uuGtJJF+sH6n3J3MtA6JEgWQLupItHmxfgXHsgdIkRRQLHQwF6MlZn1jmMJ8g4HSg9y6/OGlQJyecDhEAA4EbySQSadQsr4TB4UwPrHod6cgPelO9EA4EXa8YscL7x41jTTVFsSIHU5oN3PIFupUY9UxCu3lL/gdtmUnQEE+4qIXZ7AzNU8lCP+OmeYlk4gVTVISCH9iMH5gRPsRY0RNuGtcqS9buw2O7CSRXIujezdgskluSL8J4OQ/grBf2oWyfsFFB5kof50DIrcg6Efmk86XKdC8LWlMb5fwbF/zyJ+I4n0rSTUqzMY9ykYnWPwnA5CMS3EIoZOBiDdnULw9CzSDwoo3E9i9vMgZh7JCHy+vrpI2q/AeWcGE9c1uPt69MGCxQnFZUfiwhQSbQo8uzd4VM1z3bslaH9FMDWXQ6GQQ/LSMPw/2zGwl0G7l0a60KA0uwKY+c4L/BJE4Ce9nJxHR+EX4hj/eByxWzkUHuWQvjYBf3833J/ONj9Dqz8Af0cBka9GMfNHFrm7ScS+GkbkYcUqICajZw9Ddm4Gs3cKKDxII/aVH+dWFHhsGrLplL7V1GaFYNGQuhFH+k4OBYvJ+xpRm9aq6AoeBA7bEf96Ctk+H/wNRJ3dnETwexXZRwXkbs1i9GwM2k4f/Hv1Mr/uHtQAACAASURBVN+q3VWRi2Lc54X/q1kk766X99S1Ehwu98sZBDyYQfDzWeDwFCYOV0x+BQ9C3wXguDGOY9/XnEdWzEK9pkK93vhTPRkqI59Wod7QP/GrM5j4fAA9/aNQ2wKYuRjc0nsJgyGEBoHYDzHkqzpPJ4LfjsBVmMJQvx/jP8UQvx5H7OcJDHv2YXjOCu/5MHxNz5bSzxuyX59BDAPwH9hkJN1SWTRChPd8CF5LHKOfb3Lej+jDzOUROB/NYEh249g/pzA7F0fslymM/90N2ReBdiCMyFlXY8et2TZnBnEA/gMisj8FMXoljez9LNRLwxidK1UNcBqxNW3fuh4Vr4fg/8iP4Usqsg+MtnlpCrG7DG5XNwARQyd0rQ58PgP1rzTS16YQ+HwCKYsbyg5A2t0DaSWBmR9U5J4UkL0+hWOfqnAOOsEKWaTul+oHuXuDGNkPRD73Y+JaGrlCAblbMZzzudHdP1rv6N1y/hvwaBaBT2eQ2x3E2CBD/n4OudXPE+25yhMA0Ku/W/xMABPXsygUCsheO4fAWRXswAgCRn9VujIMd98Qpu42S2iL/VUTXD4fZC2O0OdTUO/kkL0Vx7nPJpF9ESO4OuwQbEDulgr1ryxyZs//sHkQ/FxG/vsgjv2k9ymFu0nMnh6CLHsQurXx+wr7/RgQEpj6KoJ0e8WKEmzRTi1OuGUR2o0IIsb2ysKfExi5nNPHKMb1z2Uvq2hpzJwawtDH5xC7lUXuUQ7ZWzGELiWALhnuVn+xbg8gfMaN/E9TiNesSHCdDiPYlcb4AQXH/jWD2DW9/zn3sQLlqwSko5MYr/tBpYzczXgDLU8it1YtGkr3EohvoPeb2z2aj0c24wXpSjNetT4bd8P3kYz8XAih6xqUw0Prk7gt9ltMdkNGFtGLql62yznEvpqAWtk7vk6NtnkwfFxG/tIwAt/Hkb6ThnppGMGvVZR2KZAtepl6BRWhz84hfqeAwqMs1B8CGL2iwfV50PTqzTXaB+DtB9Tz44g9kjHkq/jR+Ll0iYHZGLT7CcT/zCL7QDNZtk74fG7gzzCG/xVH+n4O6etTCJxVsekvmHXtx/yc60Xj2NkDRzqGmRs5FAollFaLaqcX/p1ZTJ6egHq/gNyNCYxeSEP2+SFbACZJkJ6kkTB0t/RHCBNXG7QUUYLEMlDnsihp1asq3X/3Qlo8h5Efksg+yEL9dwiRghveA3oLEjqqHZkOAQAT4eza5Af+lTQm/uaG+3T8ubfEmrPjBjZUXxAvdLzwoqjTTJNtyf2RF85SDCHDXnN/xTD+6Szylf3gc44XGuS2ybhFxNBRD8o/hzCzPITAwfrWwrQ4zn0+o89x7ycxdWoCKnMjcEhf6GO2Dyj8cgzuPj9mtnI8z/PHK3j72GrUTno8TyN7RWI2gaTBScqshtk93Ch8c3W0xrwapsB+J4k2RmACSbs8FLyQ2DBKiX5jgqa/8JGyUyLBBoKFkdDuJNfBIIV/X1p/bn6aPIyRcqFRGPrqyCRL8RD5evXQxswmknN/gMJqzZsbUbNQc29x1ksC6iOGbBq182mKJg8b4ZYFieTDIVrIE+VnfeQUGIm7xyhRrokwpz+RFk44iQkuCqWNSEi5eQoddpEkMmIWRkKXi7xfRChTGcGtAeX0NAX6JRKYEfL5ZJRSF716+RivX85OU6BXIoGBmCjrYaHLRZo/KZNgE0g6Pk9lWqLIUZkExkjo8lEkb/a+RtSntYY6QpJFpMBvNXeulu13CzR9XCGpzajHAyMUvVd96VbsripqJ5Vp6dcx8vbqob9hsrxNRRvTr6yO2vksQ5P7BUJHgKINo9gUaeG4bg/h22QqUiXA1qKOlme99aHDmUDSLoUCZ6Ob2tBaGs2i7OSmydMGPTJZtua+21EaO6KQs10gZgGxNolcB4M0Wdf21qN2rv8tQSM7GEknKiLLPWs9amddWWxQR0s/ekiwCOT5cTWaaE3Uzsp3uzdP4eMecnWJ+rsJIjn7fTR2MbWpxplqO2b17fGCHilKYMQEkeSDYzS/GCZls+i5z6HtW9KjZ3ma/9pHyk6RBIambXPptzHy7TW0uk0i19EwJdbsrkgLZ70ki0bb7g3Q5M0i0e1J8nQwYu0Khf9qoKlPMxT5wktyh2GHopNch0M0f2+D8qmNHGUy/1X85iOhiV1W2tTm5dmkboiIiimaPuEhuV0gxhgJHXJdXeQvKMQ2iyRlpr96ZtZGypSZHSHPDlHP0w6Fgj+mKPqJWB/NrZKtRO0kosx3Xt3+RScF42U9op2lcryjEz3CCLtCFVGripT4MUieXXqdNh0bNKRMC8clAkDOf6RqvjNhp7dronYSET2cp7FBve9ibRK5DodoIRkmha1HXiPaWvuritpJ+thgZFAmqY0RLMxcm6iJ2lnFswyF9jICGkRrfpyi6S+85NphaKVNJGevj0YaaGXD/mqt3zL6GCOKdzO9X32+KbtvMB5ZOCnpkdGqog4aUVVPVERVNaErptOq5VXr8ypGtLq6KHZkrt8q1kTtJCpT6kKAXB0CMZtA4k6FgpcNLaiMDPi6NJqIiPK0cD5AyqpedbjId3ae8hV1Vs5GaeyQ3l4YE0isS9d8/RCtzyvWIpdWf7u5LjXRuPJiiJQOfSzgOmuMp8yU7bM8zf/DS3K7/n7SXh+F1QV9XLaRnTYZz5uac1XwIqJ2EuVp/guFJFv1uI+IiHLRdW0VneT5IkpLlf3AeS/J7SJJXU5yHRyjyS9cDeqmTJkffSS3M11rqvqSMmUuB0nZoffD4i4Pjf3WPKemo3YakTDZwUjzaMqtaMOmdtzEhmoxM154aH6OXkXDqJ1mxsK1mklkro8vU+rHACldgm77u70Uimcocqg2eunmaTXU+ybUjVvWytaIEF0bLXc1Iv2RaVr4xqdrKmMk7vLSWLwmQqyJPmDpG1dDDTHDNiKiLfjfOBzOS0WD+lk3BhZ9SKRD1dFnHkxhn3MU7EIe80ffttNUOBwO53VSwJTHD+3CAkY6XndeOJxXBbd7Dudt4H/8z/+F/+N//2+vOxtvFGtlcmMYPVe8SF2oPYOS86LQnpQAQagIEpDFhKsHofdmkP/V90LjxWxG4ZchyJ+WMJpewEjlzqyVNMblHkztmUfxoucV5qgevrWTw3mT0ErI3U0j9s8hHLsE+M+OVjvROBwOh7N17swgpnng6XjdGeFwXiHc7jkczltNCbFLCfQceAPOkfyvyq1xuN9zwP35DNQ7OeTupxE7M4zwXw4MHfG8IieahsL9LJK/jML7eRz24yEEWzx78VXCp+gczpvE/SkMuULItckY+i6KyQZ7wjkcDoezRXaOYUF93ZngcF4x3O45HM5bjQDv5RS8rzsb/5XZHUJ0Fhg9fw5DrmMorQiQdinwX5xHaPAVzUdXEggfGMBUSYL7SASRr5ucsfyGwLd2cjgcDofD4XA4HA6H8xr5H//zf73uLLyR8O2unDcR7kjjcDgcDofD4XA4HA6Hw+FwTMDPSONwOBwOh8PhcDgcDofD4XBMwB1pHA6Hw+FwOBwOh8PhcDgcjgm4I43D4XA4HA6Hw+FwOBwOh8MxAXekcTgcDofD4XA4HA6Hw+FwOCbgjjQOh8PhcDgcDofD4XA4HA7HBNyRxuFwOBwOh8PhcDgcDofD4ZiAO9I4HA6Hw+FwOBwOh8PhcDgcE3BHGofD4XA4HA6Hw+FwOBwOh2MC7kjjcDgcDofD4XA4HA6Hw+FwTMAdaRwOh8PhcDgcDofD4XA4HI4J/iMdabnv98Fq7cG5O+t/0/6cwIDTDus7Vrj/nX19mePoPJjCPqsVQz+XXndOOC+DJ3GMf9gJu3Ub7H+bwX//ZQhWqxsTd193xupRT3VimzQMdeUlpf+ZA9u2bav+vGOF/X03hk7NIP28TeCqH9Z3qvWO85ZTmMGA1Yp9PxRed044rwBtVR/vv+6ccDgcDofD4XCA/1BHWj0aYt+MI76sIHwjhcgR6XVniNOmYOTCJAIu4XXnhPMSKPwygYkbDEM/JpD4bgj/2+vOUAXJU93oPp18tQ+1eRD6fQELqvGJRxD+WELu52NQBs8hrZlP6rXk/z+aLM65HDh27eU9QZvzw9E3gdzLewTnDaK2DbM9QUxeGIVHfI2Z4nA4HA6Hw+GsYXndGXgzKKFcAphTwVCvE3ys+gZgc8Jz1Pm6c8F50awAsADFUhEak+E55IKTAdob4/fJIfFXDtj9ih9rEeDsV6BUKvJ+LwbEEpyfTmLqxgimDzATCb2m/P8nU0ojdUeD/SU+IptMo4Se50/IaH+cN5kGbbhLQaDrtWWIw+FwOBwOh1MDX5GmxTC03YFj1zVo14fh2LYNPf9strWzAPXbY9j3gQN26zZYtzvQrfgxcWN975V2ZQhW6wCmbsUx/lEPOt+1wrrdgZ6PzkF9oqcx47HCuuccsjVbxbRrx+B4pxPD15svP8ldOwe/qxP27VZY3+3Evo8noFbu7imlMfP5AHokO6xWK+xSDwY+m0KyYnuY+pkDVtc5qDcm4Hd1wrHdCqujGwOnY8itACjF4H93GzpP1Xs3kqc6se1dP2JGeoUbEzj2Ybeeht2Bbs8wpv6seNiDCeyz2uH/WcU5Tyes243tKQUVEx/vQ7dD305rd3RXv0uDrZ3a3VmMfuTWy9Rqh+ODfTj2bxWF1XJcSWNctqLzVBzJn4axz+mAfbsV9vf3YfjnLDZb1LNZ2Wp3ZzHqNZ7/jlG2p2eRrUg4/rEd2z4YR7qyblfiOPbuNnR/lV5NCdlfRjG0pxP27duwbbsdnXuGMFqTx03LdiWH+Bk/3O87YLVug9XuQE/tNY3YxEay/+yBdfsAZmp3jRVmMLDdut4+lrOYPT2EnveNdN53w38mrtuQgfqpbmvxn4+hx2GF47MIpj60ovtMGliexZB1G6wfTuH/a5DNDev77gTcVjv8VytKrDSLoe3b9LZVkU76TA+sZrZmrsTg396J0Rsasv92Y9s73Ri/pX/FLAzarRkc6+uE3breXgqVaZooj1YRZTcklJB7VEL2X3q9TD2quejJLIbsVvSMTzTNPywAHquY8PWg016rSatU6pveBtzeUczeWS/jzfVtA1bt7j27Xp/yAEZ/qbb53Nw5+PsMm9/uQHefH+NzubVrTD2/BR3QHsRxzudGp8MKa5N2CBSQ/PYY9jkdRntxY+ifRr3eGEbnu37ElkuY8WzDNscxxFfMvUtTbax59tSHVvT8Kwvtj1F0brPC/e36ujSGPOJnBtDj0NtIp8uPqVvrua9vf/HqumioARriHzvq29FX3di2rUGbsxtbTLeoR2Z0ddM+a6P0N6nj0tVj6LR2wn+1Ip9aEuOyFfYPp9b6ae1uDKPe9fbT/eEwZm5VvlsJ6Z+GMSA71jSitg+Jf2yHdc85xK+OY0Betyf/v1SUgKYa1Ghr56b29WhKt69fspg9td7uam2Ew+FwOBwOh7MF6C3i9u3b1NvbSwCot7eXbt++vaV0lr5TiDGZQsbt5ccZCvczYv1hyjwuUrHc+L78jx4SLBL5vlugTC5PS9kETR91Emvz0PRD46KYj5hFJKnXR5M3i0REVEyHSWkDSScWqExExV99JDInjSQrUy/T/FGR2M4xSj1r/Pzi70FyMpGUL6OUuJ2hlDpJvp2MWG+YMs+I6FmGwvsFYl1eCv+eoXw+T5nfw+TtYiT0T+rXENHCCYnQJpF8KEQLD8tEVKaliz6SLAL5fi2u5QVdI5SozEt5gUa6QOIn81QmorI6Qk7GyHl0mhL38pS/t0DTR5zEBIXCWeOeh5OkMEbOvR7ynZ+nxM0M5ct5mj4oENsVoOnFDC09XKKMOk2B3QIJB6YpT0SU0+/zXi4a6UTIK4LEAyGKppcon1+ixMUAyTZG8j8SpFdZhkK7GbEOmTxfzNPSUyIq52n+uJNgU2jyITVl07I13l3oHaHoTT3Pqd/GSGlj5Pxi9flE80cFQm0dPpunQBvI+WVK/39yhJxMJM/ZeUrdy1P+XoqiX3tIYhKNqHpKZso2c95FTHDRyK8J3R7T8zR52ElM9FG02ORFzdhINkwuxsjzY77q1vyPHmLMReF7RERLND0oEkSFxmIpWsovUSo2RorISDo+T6uPXzghEeuQSRkcoYiaolSuSOWnRUp8KRNsXprOF6n4tEzlWa+e9prdbFLfz1I0tpORdDKxbp6/BUjskEiyeWh6LetLNNnPSDw6T02adRXlfJR8RlvNF4tUfka0cFIiiE5y7Q/QtJqhpWyKol8qJKy1F/Pl0YiF4yJB8FG0Qbsv/xYg0SKQ77cy0cNp8tgYuc5nquvloocEm0Lhe43zr2uSRM5eD41cTlDmXoYSs0GSbeuaRFSmxD9kYjaZAj8mKPNQt6fQAZEgeinSgr41ZokmDwjEdvpo8vcUZW4nKPoPhUSLRIHfjHTiQZKYQK6TEd3mcymKnHSRwCQKxostPN+kDjyOUqCDkbA3SJGbS5R/mKGF816SmEjey6sGVKbUWb2dBS8uUCqbocTlILkEo90/K1Px9xFyWgTyzeapaHQept6loTY2sIGnSzQ5yIjtDVHqcZHKZSLKT5OHgaRdCnnPRimR1TXUt4MR2xVa059G7c+MBhRnvSTUtKNwr0BSl0TSiYX1vP0eJNHQhC3pkUld3bzPaoKpOi7S/HEnsa4AzRtJpb526f36PeOSfJR87YykgyGav5mhzM15Ch+UCG0ems6t3yMwibznF/T2k4xQcK9AbPcYJYwXWfhEJAgiOQeN93hWpNSP+nt4Lur5adSG1/TRyI8p+1q1kR0eCl7OUPEZET1eoLG91TbC4XA4HA6Hw2mdt8qRtupEW/309vZuKZ1aRxpRnib3M2L7Jym/0Y3FPC1l89WTxdshkhkj36/GX2M+YmBrg2LjRpoe1J0yS0TG5IGRdLxi4vk0Sj6xfpK8Tp6mD1SkYVBWQ+Q7OkbzD4lIDTacWBQve0mwrDvuFk5KhIpBuZ6Q4ez5QndMlOMBEplEI2rls4IkMYmCalnPzyAj7BhZmySQ8W7Bjop3MwbzwsHIujPhWaL+/YmIHqYokTbKt8aRljkrE6tzhpVp/hOJIAZovky0OoHGjhoHYFKf6AZ+a1K0ZsqWypTPZWjpcfXzo4cZsd2hNSelGUda8aKHGKt9lyItJVNG+ubKdv6IQGxXzbOeLlEq2XhCTkQmbWRJdyyvOjWNMqpqI4sjVZO/VZa+U/R6yun/XzgpESxOGrtZnY3MWZlgW3ce1TrSzNT3wglJL3vj28RJJ4mfhGlst7jeHosR8goCeWc3cmVV8GyeAuJ6O1h/B5lC6cqs6JPdtetMlkcj1hxpZSJ6ZnzKRVpaNJy5O0Zo4SkRUZGiR8SaOtdtVxg06qpB/lc1SblQad3Fapsvrk/eq0wnFyaFMXKdX6pKa0N9a8TiCEkWkQK/VaaeocgJHwUvpIgoT5MHqtsSERE9S9HYThAbnNb1w9TzzelA5mtXtfPWSCtyqKJdPY2Sz3DqVJL6LkC+kxHd9m6O6enGV781+S6NtLEhRYocrCnf1XsPR6vu1d/JQ9OGTjVsf2Y04OEkKTaBfLHy+vMEhULnvSRUvFfqS+daWW1Jj0zqqpk+qxGm6piIqLhAIzsZOU8sUPF2mBRBJO/FpYp0ZGJVjkUiykdp7EiAwmrR6L9B4tHq+qD0GMlMIJ+hPwvHxXotoSUK91Zoa4M2XO1Ia82+an9EWDpfbSMcDofD4XA4nNZ5q7Z2/vHHHxv+/6VjA3LXQvD39aBb6oTjPQcc+8PIaoCmVWyVsEiQP6g8aU2AXQC0ZQ2lFQBMQeBjJ/JXZxA3doaUrkUR1xQEjjQ5F2wlheRNDQ5ZRmUoBNY/hsjFEDztQO6vFPKWHrhrDugX9rjhtOSQvl2xx0TogdxRcZHFDkEAilrZSNeHofY8YnOqcYGGxJUo8h1e+PuYnp+kBrFPgavy6CbmhuJiyN9MVmy5YXC6ZKzlyiLDMyghf+kYBj49h5m5JHIlAO0yXLtE1J8EVUI6nYXW5YK76gA7BrfLCfYkhXTFlhf2QQ/kynOAbHYwi4ay1mQ7i4myBRhYKY2ZU/vg/qATne854HhPQmBOg7ZcRiuBFYU+LxSbivHBIYx+Owv1rwI0CJD2ypDaYLpsewY9cNyZgN87jIlLcaQfaIBNgrzXCbHJcVrmbESC/5AbWJxFdHUb4YMoYosMyuEhiAByNxPIW5xQ+qtPFJT6FThXUkjcrChrwQ33zhYKyGR9u/crEO4mkCgAQBbqYh7uPj+UPVYkFxMAAC2pIrHihqf/OYNWtPXAVfkOFgEO23p7aak8Gr6yvs112zvGx2pHZ98oku8GMTMXgmIDAAGeo3447s4i8qeR3qMoZhcFeI4ObXy2o0WCa0+ldQuwt1Vo0t0U0iUG2eWubn/tbsjtGtLp9PqWsc30rQF6+XRDlitTd8L3XQSTx2VgJYX0TQ3CHheclW3X4oR7jwDtdhqp1bRNPn9jHSghfTMNrUuBUnX2lAClvwe4m0TiyWq5APIeuep95BPTiHzjQ0O1buVdarWxJRh6au61t9kBaKiSupr2Z0oD2j3w7NKQXNS3o2tJFal2F5RDCnruq8Z2xRzUxRwc/QOQLVvTo5Z0dZM+qx6TdQwAgoLQD0GwS8fgPhRC5sAEpo5KFelkoXW54W6rSEb0InR5GiP9gm4nTxjc/Up1Xe5U4BZLSCZT1e9RpYcSnE4GLZtFxsw28Bbtq1t2VrVpq9DARjgcDofD4XA4LfFWOdJ6e3s3/P/LRYN6WsHAGRV2XxiRGwmkb6aRvhKEs26SwGDd5Fxw55EglOU4IlcLAEqIX4mDDQYw1Gw2vKKhqAHM1vxI61JRgwYBdlvNFzYGK4ByqWLCsdm55UyB/6CE/FwMqgZgWcXsXAnOQ364LOv5KVwagtVqrfjY4b9SglbII1+RnLUq3wzKNwkkfvRBehTFuM+Nznft6P7bKGbvNhrdaygu6+8u1ByUzWzC2vdrWMwcyl6BibLF/Sn49/sxU3Bh9Kd5JG6mkb6ZxtTgFqbAXQFEk/MY7wMSF4LYJztgl9w49q2KQkV+Nitb8VAEid/D8NiymDk9hB7JDseeIZybax7bz6yNiAd9UCwJxOZ052vuagQJmwf+g+J6OloS405rdR73hJDWNBSelKrSZi0dcG6uvlmfArclATWpAY9UqPd74O4T0dMno5hMIrsCpG8kUNqjQHneCCKs1qasVYe2t1QejbB5EE6mkLppfNIZLD0uYkkNw9e1/mzWF0BgZx6Ryyo0ALmrMSTEIQQObGaHm2jS0xKKYLALtRcZtrJcrDg3bHN9q6Wp3a1i2LxdsNblm9nswLLW+vM31AFDM+6eg3t7dZ1Jp1RoK0WUCgCKerlYbS28cEvvUquNLWKpfUYDatqfOQ2QoPRLyCdVZAEkbiQBlwK53Q1XRwqJpAY8UaH+JUDZrzsZt6JHLelqizZnuo5Xk+8Nwr8rj+x9O4aOeisc06t6tIGOFUsoQkPsU0d1+zfONMwXSut1Lgh1gSkYswOaBlO+rRbty5SNcDgcDofD4XBa4q2K3/XDDz/g+PHj+OOPP9Db24sffvjh1T18RcXsL1kIh+YxeVxZH9M/0KBt5TDx9iEEDo7Df2UehUErojfsGJr1NF+ZYGGw2/Roh80Q7AwMJX3yUJnQcgllNBp4b4zrIy+k72cRS2pwL8cw/0TGqM9YmWHRJ2LiwRmoX8l19zKLHY4NrUuAfCSE6SMhQCsgfSOKqa/G4R8ExNthKNWpwW4DtMdFfcVJRbracmmtbLaMibLNzUWgLrsQuhCCd211QwnlZRNTnxUN5RobYV0ejHznwQiA0v0k4hdDGDk9hLwthfmj5stW7A8i3B9EGBoKt+KYOT+O0EdDwM0UxhqsAjNtI+IQ/PtHEbgaReETBbFf0xAGx+EVVtOxgzEXxq/PwNtW8xAw2MXn8VyZrG9Bgcel4dxiGiVNXzETbgcEl4Ke+zGoj7zQFnNw/s1TtdLwZfDc5WERIO2Wq1dQNbzOicCnCsJnIoiXnMhdTcB5OAylZSdDDXYBdmgoljRUeyx0W2GCvXU/RgVrdlcCGorcWhusXV2koVQqNnQ+PB+GDe0YQfRKoN4+LAyOdgArzcplA175u7SGWQ2Q+z1wfJtA4lEaucUi3Kd7wCwCFJcdxxYTKLEkUkzBVN96ubSqR8+lq5tiso5X83JpFOG7Mrz7C5g5HYJ/MQSXbT0dLV+vR2vYBdjB0HM+hfD+BjkRpHXrWS6huqfRoC0XdYenmdd6w+2Lw+FwOBwO5z+Bt2pF2s6dO7G4uAgiwuLiInbubGm/2POxoqG8rG+dWR/slqDOxuuib5rD2Ka1OIvJ7yJQRR8C/RsMoy09cMkMhaRaFRFSuzGOfa4hTN0BpD1uOFZSUBerV78UkglkVyTIcovOjd1++HfmEZ9TEb8yj5LLD++O1fx0w7WHoZTLg+1wwlnxcTAGe0ejLZoGyzmoV+JIr2aTiZAPBDF5WgF7lEa6NlokBMh7ZLD7SSSqIhZqSCymoLW54eqqvacFTJSttqxBgx2OSifJ/QhmFzWgcq0MY/UTpbtZZCtWzBVuxRG7sb5KQ+hywXc2hMBODambOZNlW0L22izUtRV8DOJuL8a+CcKNLFK3G09EzduIAM9hD4RkHPOLMUT/cmDo8LoDWXLJkJBD7qlUlT9nux3M5oD4XDspzda3CKVfRj6pInIjAdan6FudjFUz6lwc6h0JSn+T7dIvkJdbHtWIhwLwII7I91OIpt3w/73e2doyO3ogt2lILyaqV7M8SCDxiKFnj/xcjrQ1u6sMH4wcZv7uhvtUHJrRBks1bRAraSRuliDIPdXb2J4bAbJLBnuUQ16obmNOgYG1SRAY9HIR6ssl/e0A3B+eQ7Iqr8a/r/xdWsO0BrgUKLYU1KtxJO/3bMzp3AAACH9JREFUQDG2gvb0ySguqojcUKH1DRjbjremR2Z1dWuYrGMAuD+F4dMqur+aQfRyGN7SBAJnVCMHAuQ9zno9KsUw3OfGsZ8LwA5922cuX6p+zg4H7BY7HJV7W///9u4ntM37juP4Z+DDb6DDE/BBhRwsyCEyHUSmhVrEh2jkMIUeJtOCLTJIlBUSOYbUamGpt0Mm55DaPaRWA2mMD8PawdiFFiswY+3QIRcarEBCFJiJfDBIsIIDHVjQwHcHuYns2vETJ62b9f06S8+f3/P7fWV/9Dz6frOk0t2W7TyqqnynIReOqNPPvPiZzy8AAIBfgpcqSNtXLqKu150qX0wof7eu+kpZsxeTGnkUUzzQUKW8pPozfovuelJKHS5p7MOiwn9I7XI3SlC951MK3c8pNTih4u2yyjdzSg2OaaktqthhSUfTGjouFf6S0th8RfV6XZWbI0pdKsr9bkip1571pMPqfzui2hdZZecbivX1tnyrH1TyQlqh21kl381rcbmu+kpFxU/PKBbpUu+1pzzO0yhr4t1e9Z4e0eytiqqrVVVuzSo7WZIORRQ9+MO3hE9llPCKyp4bUeFuXfXViorXUspMN9Q9mH7OO3J2H9vQa10KPSpp4lpR1W/qqszndOadosJvhuXqFS0tP1TjkdT5epe81YLyn1XVkNRYLWr40owetjwatjafVfLtpAYmi6qsbIzbZE6z952i3Z0+x3ZNpY/TOvFWSrmbZVVX66reX1T+oykttUUUjewwIM8wR7zjSZ3wSspdnFL5YELJ1qD3jeZ2pgaTGrtZVrVeV/XWrEb6o+o8llHxWX40bht+r3foeEzhuxMam28o2tPVDHvawop1H1Dpk5xK7THFvz+n5Qkle6I68/cfJLUtDsgLSNVbRRVvV1T95ikvbfUjj8cmXlypvgMqXM6p0tOv5KYQeY/HH4grc65btb9lNDC5+Pj4h98ZVflgUkN9z3lP3xspDR2TCheTGvlsUeXbi8pfPKPh6bo6j0XlFFTvheYaTL+fV3mlrvryovKDaU2sRpQaTOzxd8R2Fj6VUdIraPj0sGZvVVVfrap8c0zJY52KvpNvPmYdiGvgbES1yQGlPi6ofLes4uSA0peLengk1qzZgV/La2to6Z8Fle9WVX/0os/FyQWcGsslFb6qqLLynAGT3xrgoor1NLR4dUKlQ92P63Lzjs+8cl/U1HX8+98E21s98ltX98rXNX5UUe7csEq/Gdb4+bDUntDYlYQa1waUmW8u3PDJjOLtRWVPZ5T/V1nlr2Y1cjqjieUD6u4JSoG40oMR1T5O68ynRVVW66rfX1T+/V5FInFlb7Vcs0BNs+9nNo6nosKHGY3f9hQ/eWLjcdLd1vALnl/3c+rtiWpg+kUWKQAAgP9z+93tYD/stWvneuWGpY6GzHMyF4xY/E8z9mB9zeYuRMwLeBY6O2frs/3m2lq33TRz0pm2aTl/73LEnLelG9jTjv3zD6z/jZB5AWeuPWTdp0at1Np9a23JbpyPW+SgZ8458zoilnhvyu59++QlCxdCpo60LWzq+FWyoUOy4PmFzTusjlssIJOXsKltunzViqOWOh62YMCZnGehI3FLf1J60rmsdsPizlnsk80nuF6+YUNvRizU7kxtzlwwbN19WZv79/qT/bZ07TQzW6/M2AdvNd/jnGfBrfva6Nbn+mae3ll1T2O7ZguXEhYJbpzn0ZSNf71mdmfc4h3O3MGYjd4xs+8e2NT5mIXbnTkvaOGjKRv/csE+eLWl8993NZu73G+xV4PmOW0/bn7G9j8lG/9j3CIdnrk2Nfd3PGWj/9hlMvmYIxsjbgtnQybJwn9e+uF2vr1nU+8lnux/6zW0Heaa7d6108zP9bbH81ZbuqCu5RPmaUvHujtZi7Q5i13dsbdk89iuJizkNedkurDuf734GI/tPO7a+d1TX7ZZcbsumNsfv/muSTUrfZSy2KtBc25jDWw9/mesb5uslWz8bMzCQWfOOQseidtQ/t7mjoKFrPUf3ViDgY35XGyZz772778OrFfnLNvXbaGgM9fmzDvUvc1aqNnClZTFDgc31ku39V+as9rjc31gU6ci5jln3qF+m6r5PJcdauN21r/MWqyjWVO6L5V2fG/t+uaOwDutP781oHY9bk6y0NmWeb7RHVJbu2HuqR75q6vP9Jm1dex2ucb3rsTM8zbq95Mzt5m+oLlDKZvb+AxYvzPV/Mzyvr+eabvxdWs1WrPS9bTFjzTr+nbXfOFs0HR4yGY+z1riSMt8+mhzXdu6hjd37Wza6/zaOkeaXWf9zUMAAAA0/crMbL/DvF+sRlnDPVHlIzO6dz3+XI9OAdhd+a9RZTsKmjn5ou9v+ik1VDzXqRNf9qtUzu7+u2oAfhaK517Rb+eTKlVGm017AAAA8FLiT7n98LCuysqSClcyGluNaXyaEA340f23qKnCK4p/9pKGaI2Hqq5UVZ4eVmZSSuYzhGgAAAAA8BPj37B9UJ9OqetcUd6RhLLTOaU69vuIgF+AQEyji7HdX/dztZxTb3dW1faIeq/OaPz3L2kgCAAAAAAvMR7tBAAAAAAAAHygaycAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAOADQRoAAAAAAADgA0EaAAAAAAAA4ANBGgAAAAAAAODD/wDiOvFoFVnPUwAAAABJRU5ErkJggg==)\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "Zy1U9RNlSRzc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import snowflake.connector"
      ],
      "metadata": {
        "id": "KIPkDYX5Ou10"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# fill in your snowflake params\n",
        "params = {\n",
        "    \"user\": \"<your_snowflake_user>\",\n",
        "    \"password\": \"<your_password>\",\n",
        "    \"account\": \"<your_account_id>\",#don't forget to put your region. e.g: account_id.us-east-1\n",
        "    \"warehouse\": \"COMPUTE_WH\",\n",
        "    \"database\": \"<your_database_name>\",\n",
        "    \"schema\": \"PUBLIC\",\n",
        "}"
      ],
      "metadata": {
        "id": "6w8EQ7TrN-Jo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#create a connection and a session for your cursor\n",
        "conn = snowflake.connector.connect(**params)\n",
        "cur = conn.cursor()"
      ],
      "metadata": {
        "id": "HXmd6xVcOLF-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#create your sql command and transform it in a pandas dataframe\n",
        "#As you already have your schema configured, you can just run sql without specifying any schema.\n",
        "#But, if you need to perform SQL queries in another schema you can just use the following EXAMPLE: SELECT * FROM <database>.<schema>.<table>\n",
        "sql = 'SELECT * FROM HEALTHLAKE.PUBLIC._VACINAS_DO_ESP_RITO_SANTO LIMIT 100'\n",
        "df = cur.execute(sql).fetch_pandas_all()"
      ],
      "metadata": {
        "id": "UXVPiWJjONGN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 200
        },
        "outputId": "db5176f1-8bdf-4cf1-f077-d07f8b469355"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-2-cb3b502d64e1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m#But, if you need to perform SQL queries in another schema you can just use the following EXAMPLE: SELECT * FROM <database>.<schema>.<table>\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0msql\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'SELECT * FROM HEALTHLAKE.PUBLIC._VACINAS_DO_ESP_RITO_SANTO LIMIT 100'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcur\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msql\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfetch_pandas_all\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m: name 'cur' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#now you can just use it as a pandas dataframe\n",
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "agyJVLTvONnf",
        "outputId": "178e1294-93db-40e7-e12c-fa5ff1551cb6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(100, 34)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "aWhkSEQ1OpX3",
        "outputId": "21cbee8b-db22-4bd1-d8e6-e4e591581567"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 DOCUMENT_ID  \\\n",
              "0  f9907e46-621a-4ac1-992d-59fdf5ae26cb-i0b0   \n",
              "1  59772fbd-cd52-494e-bde3-bb8585eac2a9-i0b0   \n",
              "2  10d761f7-6746-47d4-8f82-ff466ceb11dd-i0b0   \n",
              "3  639ea0ca-4979-45c9-9c2d-3601de267004-i0b0   \n",
              "4  7bbcb366-f065-4faf-8e18-53ab41d0e8a4-i0b0   \n",
              "\n",
              "                                         PACIENTE_ID PACIENTE_IDADE  \\\n",
              "0  7d1c5e46ce3da4d69188bad28f76794237a1e3947df452...             28   \n",
              "1  ab992f324c42c1ca1eca00d2b15eb6e0e163ff8368bafa...             29   \n",
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              "4  47e426ab60e62647b686a4c27912681522adfebf987be9...             38   \n",
              "\n",
              "  PACIENTE_DATANASCIMENTO PACIENTE_ENUMSEXOBIOLOGICO PACIENTE_RACACOR_CODIGO  \\\n",
              "0              1992-09-16                          F                      01   \n",
              "1              1992-02-24                          M                      01   \n",
              "2              1968-11-11                          F                      01   \n",
              "3              1970-06-05                          M                      03   \n",
              "4              1982-07-29                          F                      03   \n",
              "\n",
              "  PACIENTE_RACACOR_VALOR PACIENTE_ENDERECO_COIBGEMUNICIPIO  \\\n",
              "0                 BRANCA                            320130   \n",
              "1                 BRANCA                            320370   \n",
              "2                 BRANCA                            320450   \n",
              "3                  PARDA                            270830   \n",
              "4                  PARDA                            320130   \n",
              "\n",
              "   PACIENTE_ENDERECO_COPAIS PACIENTE_ENDERECO_NMMUNICIPIO  ... VACINA_LOTE  \\\n",
              "0                        10                     CARIACICA  ...   202010018   \n",
              "1                        10                  MUNIZ FREIRE  ...     28230BD   \n",
              "2                        10              SANTA LEOPOLDINA  ...  214VCD055W   \n",
              "3                        10              SAO JOSE DA LAJE  ...  217VCD228Z   \n",
              "4                        10                     CARIACICA  ...      FA9094   \n",
              "\n",
              "                      VACINA_FABRICANTE_NOME  VACINA_FABRICANTE_REFERENCIA  \\\n",
              "0                          FUNDACAO BUTANTAN   Organization/61189445000156   \n",
              "1  PFIZER MANUFACTURING BELGIUM NV - BELGICA                          None   \n",
              "2                      FUNDACAO OSWALDO CRUZ   Organization/33781055000135   \n",
              "3                      FUNDACAO OSWALDO CRUZ                          None   \n",
              "4                        MINISTERIO DA SAUDE   Organization/00394544000851   \n",
              "\n",
              "  VACINA_DATAAPLICACAO  VACINA_DESCRICAO_DOSE VACINA_CODIGO  \\\n",
              "0           2021-02-01              1ÂªÂ Dose          86.0   \n",
              "1           2021-08-19              1ÂªÂ Dose          87.0   \n",
              "2           2021-05-18              1ÂªÂ Dose          85.0   \n",
              "3           2021-08-24              1ÂªÂ Dose          85.0   \n",
              "4           2021-07-10              1ÂªÂ Dose          87.0   \n",
              "\n",
              "                                         VACINA_NOME      SISTEMA_ORIGEM  \\\n",
              "0                Covid-19-Coronavac-Sinovac/Butantan            Novo PNI   \n",
              "1  Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...  VACINA E CONFIA ES   \n",
              "2                       Vacina Covid-19 - Covishield            Novo PNI   \n",
              "3                       Vacina Covid-19 - Covishield  VACINA E CONFIA ES   \n",
              "4  Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...            Novo PNI   \n",
              "\n",
              "  DATA_IMPORTACAO_RNDS ID_SISTEMA_ORIGEM  \n",
              "0  2021-02-01 14:09:51           16341.0  \n",
              "1  2021-08-24 17:31:42           21955.0  \n",
              "2  2021-05-25 16:57:40           16341.0  \n",
              "3  2021-08-24 15:54:13           21955.0  \n",
              "4  2021-07-10 18:22:57           16341.0  \n",
              "\n",
              "[5 rows x 34 columns]"
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DOCUMENT_ID</th>\n",
              "      <th>PACIENTE_ID</th>\n",
              "      <th>PACIENTE_IDADE</th>\n",
              "      <th>PACIENTE_DATANASCIMENTO</th>\n",
              "      <th>PACIENTE_ENUMSEXOBIOLOGICO</th>\n",
              "      <th>PACIENTE_RACACOR_CODIGO</th>\n",
              "      <th>PACIENTE_RACACOR_VALOR</th>\n",
              "      <th>PACIENTE_ENDERECO_COIBGEMUNICIPIO</th>\n",
              "      <th>PACIENTE_ENDERECO_COPAIS</th>\n",
              "      <th>PACIENTE_ENDERECO_NMMUNICIPIO</th>\n",
              "      <th>...</th>\n",
              "      <th>VACINA_LOTE</th>\n",
              "      <th>VACINA_FABRICANTE_NOME</th>\n",
              "      <th>VACINA_FABRICANTE_REFERENCIA</th>\n",
              "      <th>VACINA_DATAAPLICACAO</th>\n",
              "      <th>VACINA_DESCRICAO_DOSE</th>\n",
              "      <th>VACINA_CODIGO</th>\n",
              "      <th>VACINA_NOME</th>\n",
              "      <th>SISTEMA_ORIGEM</th>\n",
              "      <th>DATA_IMPORTACAO_RNDS</th>\n",
              "      <th>ID_SISTEMA_ORIGEM</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>f9907e46-621a-4ac1-992d-59fdf5ae26cb-i0b0</td>\n",
              "      <td>7d1c5e46ce3da4d69188bad28f76794237a1e3947df452...</td>\n",
              "      <td>28</td>\n",
              "      <td>1992-09-16</td>\n",
              "      <td>F</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320130</td>\n",
              "      <td>10</td>\n",
              "      <td>CARIACICA</td>\n",
              "      <td>...</td>\n",
              "      <td>202010018</td>\n",
              "      <td>FUNDACAO BUTANTAN</td>\n",
              "      <td>Organization/61189445000156</td>\n",
              "      <td>2021-02-01</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>86.0</td>\n",
              "      <td>Covid-19-Coronavac-Sinovac/Butantan</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-02-01 14:09:51</td>\n",
              "      <td>16341.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>59772fbd-cd52-494e-bde3-bb8585eac2a9-i0b0</td>\n",
              "      <td>ab992f324c42c1ca1eca00d2b15eb6e0e163ff8368bafa...</td>\n",
              "      <td>29</td>\n",
              "      <td>1992-02-24</td>\n",
              "      <td>M</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320370</td>\n",
              "      <td>10</td>\n",
              "      <td>MUNIZ FREIRE</td>\n",
              "      <td>...</td>\n",
              "      <td>28230BD</td>\n",
              "      <td>PFIZER MANUFACTURING BELGIUM NV - BELGICA</td>\n",
              "      <td>None</td>\n",
              "      <td>2021-08-19</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
              "      <td>Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...</td>\n",
              "      <td>VACINA E CONFIA ES</td>\n",
              "      <td>2021-08-24 17:31:42</td>\n",
              "      <td>21955.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10d761f7-6746-47d4-8f82-ff466ceb11dd-i0b0</td>\n",
              "      <td>72aad6df7aee4def12350352b9df623e810ecbff9a1bd3...</td>\n",
              "      <td>52</td>\n",
              "      <td>1968-11-11</td>\n",
              "      <td>F</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320450</td>\n",
              "      <td>10</td>\n",
              "      <td>SANTA LEOPOLDINA</td>\n",
              "      <td>...</td>\n",
              "      <td>214VCD055W</td>\n",
              "      <td>FUNDACAO OSWALDO CRUZ</td>\n",
              "      <td>Organization/33781055000135</td>\n",
              "      <td>2021-05-18</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>85.0</td>\n",
              "      <td>Vacina Covid-19 - Covishield</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-05-25 16:57:40</td>\n",
              "      <td>16341.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>639ea0ca-4979-45c9-9c2d-3601de267004-i0b0</td>\n",
              "      <td>151939921098730953ccd52a918aa6f18473ae4c012a75...</td>\n",
              "      <td>51</td>\n",
              "      <td>1970-06-05</td>\n",
              "      <td>M</td>\n",
              "      <td>03</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>270830</td>\n",
              "      <td>10</td>\n",
              "      <td>SAO JOSE DA LAJE</td>\n",
              "      <td>...</td>\n",
              "      <td>217VCD228Z</td>\n",
              "      <td>FUNDACAO OSWALDO CRUZ</td>\n",
              "      <td>None</td>\n",
              "      <td>2021-08-24</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>85.0</td>\n",
              "      <td>Vacina Covid-19 - Covishield</td>\n",
              "      <td>VACINA E CONFIA ES</td>\n",
              "      <td>2021-08-24 15:54:13</td>\n",
              "      <td>21955.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>7bbcb366-f065-4faf-8e18-53ab41d0e8a4-i0b0</td>\n",
              "      <td>47e426ab60e62647b686a4c27912681522adfebf987be9...</td>\n",
              "      <td>38</td>\n",
              "      <td>1982-07-29</td>\n",
              "      <td>F</td>\n",
              "      <td>03</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>320130</td>\n",
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              "      <td>CARIACICA</td>\n",
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              "      <td>Organization/00394544000851</td>\n",
              "      <td>2021-07-10</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
              "      <td>Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-07-10 18:22:57</td>\n",
              "      <td>16341.0</td>\n",
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              "  </tbody>\n",
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              "<p>5 rows × 34 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4b6578b5-f14b-4e6d-9a86-f4e6e1c7d90a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4b6578b5-f14b-4e6d-9a86-f4e6e1c7d90a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4b6578b5-f14b-4e6d-9a86-f4e6e1c7d90a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.sort_values(by=\"PACIENTE_IDADE\").head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 647
        },
        "id": "xiJGxk2eO4Vk",
        "outputId": "0abe5b4c-bba3-48b1-91eb-d5e0e1ea58f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                  DOCUMENT_ID  \\\n",
              "11  7fd62de0-9dd0-4766-b645-ce627c9e9107-i0b0   \n",
              "32  245dcbcb-aae1-4b83-964a-6540d871eba7-i0b0   \n",
              "94  8646890a-b166-4863-bfac-5b3ebba8266e-i0b0   \n",
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              "75  872369dd-ef9e-4930-9246-699e20fbacf4-i0b0   \n",
              "\n",
              "                                          PACIENTE_ID PACIENTE_IDADE  \\\n",
              "11  61896c04600f2366b16b917ba5b49c0df4f4346305c72a...             18   \n",
              "32  c9eb812f2a13532fcc114567b50fc8b19048e0ca116e2f...             18   \n",
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              "75  dd5e5d296f8b6241a5c82acddb19a94c0465f1089da449...             18   \n",
              "\n",
              "   PACIENTE_DATANASCIMENTO PACIENTE_ENUMSEXOBIOLOGICO PACIENTE_RACACOR_CODIGO  \\\n",
              "11              2003-07-24                          F                      03   \n",
              "32              2002-12-31                          M                      01   \n",
              "94              2003-05-14                          M                      04   \n",
              "88              2003-06-22                          F                      03   \n",
              "75              2003-03-29                          F                      01   \n",
              "\n",
              "   PACIENTE_RACACOR_VALOR PACIENTE_ENDERECO_COIBGEMUNICIPIO  \\\n",
              "11                  PARDA                            320530   \n",
              "32                 BRANCA                            350970   \n",
              "94                AMARELA                            320350   \n",
              "88                  PARDA                            320320   \n",
              "75                 BRANCA                            320332   \n",
              "\n",
              "    PACIENTE_ENDERECO_COPAIS PACIENTE_ENDERECO_NMMUNICIPIO  ... VACINA_LOTE  \\\n",
              "11                        10                       VITORIA  ...      FD7208   \n",
              "32                        10              CAMPOS DO JORDAO  ...      210335   \n",
              "94                        10                      MONTANHA  ...      FD7210   \n",
              "88                        10                      LINHARES  ...     28230BD   \n",
              "75                        10                    MARATAIZES  ...  217VCD235Z   \n",
              "\n",
              "                       VACINA_FABRICANTE_NOME  VACINA_FABRICANTE_REFERENCIA  \\\n",
              "11  PFIZER MANUFACTURING BELGIUM NV - BELGICA                          None   \n",
              "32                         INSTITUTO BUTANTAN                          None   \n",
              "94  PFIZER MANUFACTURING BELGIUM NV - BELGICA                          None   \n",
              "88  PFIZER MANUFACTURING BELGIUM NV - BELGICA                          None   \n",
              "75                      FUNDACAO OSWALDO CRUZ                          None   \n",
              "\n",
              "   VACINA_DATAAPLICACAO  VACINA_DESCRICAO_DOSE VACINA_CODIGO  \\\n",
              "11           2021-08-24              1ÂªÂ Dose          87.0   \n",
              "32           2021-08-06              1ÂªÂ Dose          86.0   \n",
              "94           2021-08-21              1ÂªÂ Dose          87.0   \n",
              "88           2021-08-24              1ÂªÂ Dose          87.0   \n",
              "75           2021-08-21              1ÂªÂ Dose          85.0   \n",
              "\n",
              "                                          VACINA_NOME      SISTEMA_ORIGEM  \\\n",
              "11  Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...  VACINA E CONFIA ES   \n",
              "32                Covid-19-Coronavac-Sinovac/Butantan  VACINA E CONFIA ES   \n",
              "94  Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...  VACINA E CONFIA ES   \n",
              "88  Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...  VACINA E CONFIA ES   \n",
              "75                       Vacina Covid-19 - Covishield  VACINA E CONFIA ES   \n",
              "\n",
              "   DATA_IMPORTACAO_RNDS ID_SISTEMA_ORIGEM  \n",
              "11  2021-08-24 18:27:00           21955.0  \n",
              "32  2021-08-12 10:56:20           21955.0  \n",
              "94  2021-08-24 17:27:21           21955.0  \n",
              "88  2021-08-24 15:28:51           21955.0  \n",
              "75  2021-08-24 17:36:59           21955.0  \n",
              "\n",
              "[5 rows x 34 columns]"
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              "      <th>11</th>\n",
              "      <td>7fd62de0-9dd0-4766-b645-ce627c9e9107-i0b0</td>\n",
              "      <td>61896c04600f2366b16b917ba5b49c0df4f4346305c72a...</td>\n",
              "      <td>18</td>\n",
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              "      <td>1ÂªÂ Dose</td>\n",
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              "      <td>245dcbcb-aae1-4b83-964a-6540d871eba7-i0b0</td>\n",
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              "      <th>94</th>\n",
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              "      <td>78b4272f155e6107b6f76c81ee750ecb76ecc0b8c65b85...</td>\n",
              "      <td>18</td>\n",
              "      <td>2003-05-14</td>\n",
              "      <td>M</td>\n",
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              "      <td>FD7210</td>\n",
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              "      <td>None</td>\n",
              "      <td>2021-08-21</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
              "      <td>Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...</td>\n",
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              "      <td>2021-08-24 17:27:21</td>\n",
              "      <td>21955.0</td>\n",
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              "      <th>88</th>\n",
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              "      <td>a927dd06bbf3fb4c12ce1e270afaf48e913907cbabcbb3...</td>\n",
              "      <td>18</td>\n",
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              "      <td>28230BD</td>\n",
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              "      <td>None</td>\n",
              "      <td>2021-08-24</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
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              "      <td>2021-08-24 15:28:51</td>\n",
              "      <td>21955.0</td>\n",
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              "      <th>75</th>\n",
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              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>85.0</td>\n",
              "      <td>Vacina Covid-19 - Covishield</td>\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Other ways of creating a pandas dataframe**"
      ],
      "metadata": {
        "id": "h4_NZ5sYPBFY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "#you can also use other sql statement\n",
        "sql = 'SELECT * FROM HEALTHLAKE.PUBLIC._VACINAS_DO_ESP_RITO_SANTO LIMIT 100'\n",
        "cur.execute(sql)\n",
        "dat = cur.fetchall()"
      ],
      "metadata": {
        "id": "qGX4JEAbPFu4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_columns = [column.name for column in cur.description]\n",
        "df = pd.DataFrame(dat, columns=new_columns)"
      ],
      "metadata": {
        "id": "Q8yvvRhLPRlN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "id": "wTsK_SzlPRp6",
        "outputId": "13d56801-1dd3-476f-c8bd-9640cf69f121"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "3                      FUNDACAO OSWALDO CRUZ                          None   \n",
              "4                        MINISTERIO DA SAUDE   Organization/00394544000851   \n",
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              "1           2021-08-19              1ÂªÂ Dose          87.0   \n",
              "2           2021-05-18              1ÂªÂ Dose          85.0   \n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DOCUMENT_ID</th>\n",
              "      <th>PACIENTE_ID</th>\n",
              "      <th>PACIENTE_IDADE</th>\n",
              "      <th>PACIENTE_DATANASCIMENTO</th>\n",
              "      <th>PACIENTE_ENUMSEXOBIOLOGICO</th>\n",
              "      <th>PACIENTE_RACACOR_CODIGO</th>\n",
              "      <th>PACIENTE_RACACOR_VALOR</th>\n",
              "      <th>PACIENTE_ENDERECO_COIBGEMUNICIPIO</th>\n",
              "      <th>PACIENTE_ENDERECO_COPAIS</th>\n",
              "      <th>PACIENTE_ENDERECO_NMMUNICIPIO</th>\n",
              "      <th>...</th>\n",
              "      <th>VACINA_LOTE</th>\n",
              "      <th>VACINA_FABRICANTE_NOME</th>\n",
              "      <th>VACINA_FABRICANTE_REFERENCIA</th>\n",
              "      <th>VACINA_DATAAPLICACAO</th>\n",
              "      <th>VACINA_DESCRICAO_DOSE</th>\n",
              "      <th>VACINA_CODIGO</th>\n",
              "      <th>VACINA_NOME</th>\n",
              "      <th>SISTEMA_ORIGEM</th>\n",
              "      <th>DATA_IMPORTACAO_RNDS</th>\n",
              "      <th>ID_SISTEMA_ORIGEM</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>f9907e46-621a-4ac1-992d-59fdf5ae26cb-i0b0</td>\n",
              "      <td>7d1c5e46ce3da4d69188bad28f76794237a1e3947df452...</td>\n",
              "      <td>28</td>\n",
              "      <td>1992-09-16</td>\n",
              "      <td>F</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320130</td>\n",
              "      <td>10</td>\n",
              "      <td>CARIACICA</td>\n",
              "      <td>...</td>\n",
              "      <td>202010018</td>\n",
              "      <td>FUNDACAO BUTANTAN</td>\n",
              "      <td>Organization/61189445000156</td>\n",
              "      <td>2021-02-01</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>86.0</td>\n",
              "      <td>Covid-19-Coronavac-Sinovac/Butantan</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-02-01 14:09:51</td>\n",
              "      <td>16341.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>59772fbd-cd52-494e-bde3-bb8585eac2a9-i0b0</td>\n",
              "      <td>ab992f324c42c1ca1eca00d2b15eb6e0e163ff8368bafa...</td>\n",
              "      <td>29</td>\n",
              "      <td>1992-02-24</td>\n",
              "      <td>M</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320370</td>\n",
              "      <td>10</td>\n",
              "      <td>MUNIZ FREIRE</td>\n",
              "      <td>...</td>\n",
              "      <td>28230BD</td>\n",
              "      <td>PFIZER MANUFACTURING BELGIUM NV - BELGICA</td>\n",
              "      <td>None</td>\n",
              "      <td>2021-08-19</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
              "      <td>Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...</td>\n",
              "      <td>VACINA E CONFIA ES</td>\n",
              "      <td>2021-08-24 17:31:42</td>\n",
              "      <td>21955.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10d761f7-6746-47d4-8f82-ff466ceb11dd-i0b0</td>\n",
              "      <td>72aad6df7aee4def12350352b9df623e810ecbff9a1bd3...</td>\n",
              "      <td>52</td>\n",
              "      <td>1968-11-11</td>\n",
              "      <td>F</td>\n",
              "      <td>01</td>\n",
              "      <td>BRANCA</td>\n",
              "      <td>320450</td>\n",
              "      <td>10</td>\n",
              "      <td>SANTA LEOPOLDINA</td>\n",
              "      <td>...</td>\n",
              "      <td>214VCD055W</td>\n",
              "      <td>FUNDACAO OSWALDO CRUZ</td>\n",
              "      <td>Organization/33781055000135</td>\n",
              "      <td>2021-05-18</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>85.0</td>\n",
              "      <td>Vacina Covid-19 - Covishield</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-05-25 16:57:40</td>\n",
              "      <td>16341.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>639ea0ca-4979-45c9-9c2d-3601de267004-i0b0</td>\n",
              "      <td>151939921098730953ccd52a918aa6f18473ae4c012a75...</td>\n",
              "      <td>51</td>\n",
              "      <td>1970-06-05</td>\n",
              "      <td>M</td>\n",
              "      <td>03</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>270830</td>\n",
              "      <td>10</td>\n",
              "      <td>SAO JOSE DA LAJE</td>\n",
              "      <td>...</td>\n",
              "      <td>217VCD228Z</td>\n",
              "      <td>FUNDACAO OSWALDO CRUZ</td>\n",
              "      <td>None</td>\n",
              "      <td>2021-08-24</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>85.0</td>\n",
              "      <td>Vacina Covid-19 - Covishield</td>\n",
              "      <td>VACINA E CONFIA ES</td>\n",
              "      <td>2021-08-24 15:54:13</td>\n",
              "      <td>21955.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>7bbcb366-f065-4faf-8e18-53ab41d0e8a4-i0b0</td>\n",
              "      <td>47e426ab60e62647b686a4c27912681522adfebf987be9...</td>\n",
              "      <td>38</td>\n",
              "      <td>1982-07-29</td>\n",
              "      <td>F</td>\n",
              "      <td>03</td>\n",
              "      <td>PARDA</td>\n",
              "      <td>320130</td>\n",
              "      <td>10</td>\n",
              "      <td>CARIACICA</td>\n",
              "      <td>...</td>\n",
              "      <td>FA9094</td>\n",
              "      <td>MINISTERIO DA SAUDE</td>\n",
              "      <td>Organization/00394544000851</td>\n",
              "      <td>2021-07-10</td>\n",
              "      <td>1ÂªÂ Dose</td>\n",
              "      <td>87.0</td>\n",
              "      <td>Vacina covid-19 - BNT162b2 - BioNTech/Fosun Ph...</td>\n",
              "      <td>Novo PNI</td>\n",
              "      <td>2021-07-10 18:22:57</td>\n",
              "      <td>16341.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 34 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a01820b7-7bb9-4660-b4ec-a6120d415205')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a01820b7-7bb9-4660-b4ec-a6120d415205 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a01820b7-7bb9-4660-b4ec-a6120d415205');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Saving your results back to snowflake**"
      ],
      "metadata": {
        "id": "WnLv-WR4PjMQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from snowflake.connector.pandas_tools import write_pandas"
      ],
      "metadata": {
        "id": "9Kd_Kak5PlFx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#This SQL statement creates an empty copy of your table to save your work. Just remember that your\n",
        "#table schema must match your pandas df output. If you want to create more columns in your current dataframe\n",
        "#don't forget to create the same column in your snowflake table\n",
        "sql = 'CREATE TABLE IF NOT EXISTS TEST_PANDAS LIKE _VACINAS_DO_ESP_RITO_SANTO'\n",
        "cur.execute(sql)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z-7p_JbwPn8f",
        "outputId": "67d7a052-b598-4dc5-81d2-f91d5944e519"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<snowflake.connector.cursor.SnowflakeCursor at 0x7f83b3ec7350>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#do some transformations with your data\n",
        "df['VACINA_FABRICANTE_NOME'].replace(\" \", \"_\", regex=True, inplace=True)"
      ],
      "metadata": {
        "id": "s6EMIqEiPxMz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Save data to your snowflake table. By default this method will append data to the end of your table\n",
        "write_pandas(conn, df, 'TEST_PANDAS')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "owe_0S2CPzCg",
        "outputId": "7940e2ce-bb7a-4649-eeba-a529c01f88e3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(True,\n",
              " 1,\n",
              " 100,\n",
              " [('rnicu/file0.txt', 'LOADED', 100, 100, 1, 0, None, None, None, None)])"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    }
  ]
}