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How is Pandas&Python more powerful than Excel_Webscraping Example.ipynb
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| { | |
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| "metadata": { | |
| "colab": { | |
| "name": "How is Pandas&Python more powerful than Excel_Webscraping Example.ipynb", | |
| "provenance": [], | |
| "authorship_tag": "ABX9TyOXr2LyPojtbwxldaZ8s1xD", | |
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| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/ejs94/62bf7037ac30bf6fa84c4b0d532ef581/how-is-pandas-python-more-powerful-than-excel_webscraping-example.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Yu9tTVymiUSd" | |
| }, | |
| "source": [ | |
| "import pandas as pd\n", | |
| "import matplotlib.pyplot as plt" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "gqAiYCEzi3dN" | |
| }, | |
| "source": [ | |
| "url = 'https://en.wikipedia.org/wiki/Estimates_of_historical_world_population'" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "rQqpCxx6i9IO" | |
| }, | |
| "source": [ | |
| "df = pd.read_html(url, header=0)" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "7K12Y9i9jHVL" | |
| }, | |
| "source": [ | |
| "post_war = df[2]" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "54_XLDmajIRG", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 597 | |
| }, | |
| "outputId": "89313dff-dc31-4c5c-a34b-67615d9d4c0a" | |
| }, | |
| "source": [ | |
| "post_war.set_index('Year')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
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| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>United States Census Bureau (2017)[29]</th>\n", | |
| " <th>Population Reference Bureau (1973–2016)[15]</th>\n", | |
| " <th>United Nations Department of Economic and Social Affairs (2015)[16]</th>\n", | |
| " <th>Maddison (2008)[17]</th>\n", | |
| " <th>HYDE (2007)[25]</th>\n", | |
| " <th>Tanton (1994)[19]</th>\n", | |
| " <th>Biraben (1980)[20]</th>\n", | |
| " <th>McEvedy & Jones (1978)[21]</th>\n", | |
| " <th>Thomlinson (1975)[22]</th>\n", | |
| " <th>Durand (1974)[23]</th>\n", | |
| " <th>Clark (1967)[24]</th>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>Year</th>\n", | |
| " <th></th>\n", | |
| " <th></th>\n", | |
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| " <th></th>\n", | |
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| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>1950</th>\n", | |
| " <td>2557628654</td>\n", | |
| " <td>2.516000e+09</td>\n", | |
| " <td>2.525149e+09</td>\n", | |
| " <td>2.544000e+09</td>\n", | |
| " <td>2.527960e+09</td>\n", | |
| " <td>2.400000e+09</td>\n", | |
| " <td>2.527000e+09</td>\n", | |
| " <td>2.500000e+09</td>\n", | |
| " <td>2.400000e+09</td>\n", | |
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| " <td>2.486000e+09</td>\n", | |
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| " <tr>\n", | |
| " <th>1951</th>\n", | |
| " <td>2594939877</td>\n", | |
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| " <td>2.572851e+09</td>\n", | |
| " <td>2.571663e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
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| " <th>1952</th>\n", | |
| " <td>2636772306</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2.619292e+09</td>\n", | |
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| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
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| " <th>1953</th>\n", | |
| " <td>2682053389</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2.665865e+09</td>\n", | |
| " <td>2.665959e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
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| " <tr>\n", | |
| " <th>1954</th>\n", | |
| " <td>2730228104</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>2.713172e+09</td>\n", | |
| " <td>2.716927e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
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| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2012</th>\n", | |
| " <td>7013871313</td>\n", | |
| " <td>7.057075e+09</td>\n", | |
| " <td>7.080072e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2013</th>\n", | |
| " <td>7092128094</td>\n", | |
| " <td>7.136796e+09</td>\n", | |
| " <td>7.162119e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2014</th>\n", | |
| " <td>7169968185</td>\n", | |
| " <td>7.238184e+09</td>\n", | |
| " <td>7.243784e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2015</th>\n", | |
| " <td>7247892788</td>\n", | |
| " <td>7.336435e+09</td>\n", | |
| " <td>7.349472e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2016</th>\n", | |
| " <td>7325996709</td>\n", | |
| " <td>7.418152e+09</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>67 rows × 11 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " United States Census Bureau (2017)[29] ... Clark (1967)[24]\n", | |
| "Year ... \n", | |
| "1950 2557628654 ... 2.486000e+09\n", | |
| "1951 2594939877 ... NaN\n", | |
| "1952 2636772306 ... NaN\n", | |
| "1953 2682053389 ... NaN\n", | |
| "1954 2730228104 ... NaN\n", | |
| "... ... ... ...\n", | |
| "2012 7013871313 ... NaN\n", | |
| "2013 7092128094 ... NaN\n", | |
| "2014 7169968185 ... NaN\n", | |
| "2015 7247892788 ... NaN\n", | |
| "2016 7325996709 ... NaN\n", | |
| "\n", | |
| "[67 rows x 11 columns]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 17 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Pjd68LmYjdXi" | |
| }, | |
| "source": [ | |
| "predicted = df[3].set_index('Year')" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "ReGoHqubkeXZ", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 616 | |
| }, | |
| "outputId": "8374b87e-e3de-4919-888f-83c473540bfa" | |
| }, | |
| "source": [ | |
| "fig, ax = plt.subplots(figsize = (10,10))\n", | |
| "\n", | |
| "post_war.plot(ax = ax, linewidth=7)\n", | |
| "ax.set_xlabel('Year')\n", | |
| "ax.set_ylabel('Global Population (Billions)')\n", | |
| "plt.show()" | |
| ], | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
| "image/png": 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3IOd37/79+2i1WgwMDIiJiaFWrVqFvsa8Nm7cSNeuXSlTpozO9vT0dAwNDQt93tChQ2nUqBEfffSRsq1mzZpK0J+SksLmzZsLDA4FQRCeF+29e5wb4E+ZC1eL3feXNyWiXLLYcOsu9TML+AzOeADbR8B72+EffnEtKTEsWAxjY2MsLCw4ePAgkBNY7d27lzfffLPEbVSsWFFnknfr1q1ZvHix8nPupGBPT09+/vlnAPbs2ZMvqAO4efMmJ0+e1Hlu3bp18x0n98O7evXqpKSk6MwDyrtfkyZNuHPnjhJAZGZmcvbsWbKzs7lx4wZeXl7MnTuXpKQkUlJSdPoycuRIVq9ezfHjx5VtW7ZsIT4+njZt2rB48WJl3tipU6eKPEd3794lOzub7t27M2vWLOU1WllZERERAaDzGq5cuUL9+vUZNWoUnTt3JjIyssj2b9++zdWrV6lbty7m5ubcvn2bhIQEHj16xK5duwp8TmHnBuDBgwdYWFiQmZnJunXrlOfk7e+OHTvIzMzM166JiQlZWVnKNcrIyKBr16707dtXmV8FOUG0l5eX8rpXr15dYCBbkPXr1+sMCea6dOlSvrtfc02ZMoWkpCQWLlyosz332gB8/vnnDBw4sER9EARBeBaZN29ypqdfsYFVNrDCV6KiQwrr4m4VHFgBlKsMjr2hkJGoF+H1yFwFJr3Uw69Zs4YRI0bw8ccfAxAQEECDBg1K/PxOnTrRo0cPtm/fzuLFi1m0aBEjRoxApVKh1Wrx9PRk6dKlBAQE0Lt3b+zs7GjRogV16uRPYWZmZjJ27Fhu3rxJ+fLlMTU1VeZD9e/fn2HDhmFoaMixY8cYMmQI9vb21KhRAxcXF6WNJ/fLvZMuKSkJrVbLRx99ROPGjXn33XdJSkpClmVGjRqVL1thbm7Ohg0bGDt2LLdv30ZPTw9PT0/atm3L1KlT+eijj1CpVGRnZ1OvXr1CgxiA2NhYBgwYoPMhDjl3qr399tssW7aMDh06KPtv3LiRtWvXUqZMGWrUqMHkyZMLbNfLywt9fX0yMzOZM2cO5ubmAEybNg1XV1dq1aqFtXXBd5GULVu2wHNjZ2fHzJkzcXNzw9TUFDc3NyVYHTJkCJ07d8bR0ZG2bdsqWbAntW7dmqNHj/LWW2+xceNGQkJCSEhIYNWqVUDOxH+1Ws3cuXN55513mDJlCk5OTgwaNAiAEydO0LVrV+7du8fOnTsJCAhQAr/o6Ghu3LhBy5YtdY4ZHx+PoaEhNWrUyNef3LtQra2tadq0KZATPA8ePJjg4GAmTZqEJEl4enqyZEnBk0oFQRD+qYcXL3JhQB8ME4te0kerB8s7SPSsnoDHvfyjMooG3uD3DVQuWdb/eZEKuiPtZXF2dpZz7wzLdf78eWxsbF5SjwThxTh58iQLFixg7dq1pXbMBQsWUKlSJSVAMzY2zpeNfBbPqx1BeJJ4///vkGWZ2z+vJX7OXMpkFr12VXoZWNEZPjS8Q+MCRgcAKGsMrWdBs/4vNGMlSVKELMvOT24Xw4KC8BI0bdoULy8vsrJKb8XgKlWq0K9fP+XnSpUqKYuIPovcRURzs4GCIAjPQpuYyJX3h5A48/NiA6sH5WFd9ywCyt0qPLCq+yYMDwXnAaU6FJiXyFwJgiAIryTx/v/vlxISwo2JEyEx/xzjJ92tCIc6ZzAuKwHDgmIXA0N4KxBch5baxPXCMlevx5wrQRAEQRD+NbLT07n9xXzu5bkhqCgx1eBKu4dM0d4veMjN0gW6LIXqDZ9rP5+VCK4EQRAEQSg16efPEztuHBl//lWi/f+0ANknmfe1Bczt1C8LXp9Ciw+hFGsHFkcEV4IgCIIgvHBydjaJq9dw56uvkAubL/WEY7Zg75SAq/ZR/gctHHOyVea2z7mn/5yY0F4C+vr6qNVq7O3t6dmzp1JH7nnJWz+vMAsXLtQ5bvv27ZXivv9EYGAgtWrVQq1WY2try/r164t9zqJFi7CxscHf3/8fH/9FiI6OxtDQELVajaOjIy1atODixYsvu1uKU6dOKXfsXbhwgebNm1OuXDllNftcX3/9Nfb29tjZ2emsPdWrVy/UajVqtRorKyvUajWQUzond7ujoyNbt24ttA+5a5jZ2tpiZ2fH119/rTyWmJiIr68vjRo1wtfXV1lvrai+3r9/nx49emBtbY2NjY2yNtjYsWOVNeIgZx0wBwcH5ff9m2++oWHDhkiSxN27d5X9goODqVy5svJ6ZsyYAUBaWhpqtZqyZcvq7C8IwqstM/42NwYP5vbcuSUKrFLLwaqO0LLZbVyzngis9Ayg1WQY/NsrGVjBa5K5cljtUGrHOtPvTL5thoaGykKf/v7+LF26VFnzqrQsXLiQd999VynCu3v37ufW9pgxYxg7diyXL1+mWbNm9OjRI9/K3nl9++23HDhwoNB6fk/KXWG8NDVo0EC5Zt9//z2fffYZq1evLvHzs7KyXliJl88++4wpU6YAULVqVRYtWqQUZM4VFRXF8uXLCQsLo2zZsrRt25aOHTvSsGFDgoL+rrH1ySefKKWE7O3tCQ8Px8DAgLi4OBwdHenUqVOB597AwIAvv/ySpk2b8uDBA5o1a4avry+2trbMmTMHHx8fJk6cyJw5c5gzZw5z584ttK8Ao0ePpm3btmzatImMjAzli8CHH37IkCFDdFbPzy1JBPDGG2/QsWPHAssSeXh45FsbLfdvsaC6jIIgvJqS9+/n1pSpZCWVbM3Kc7VhT5tsPku7g1nmE3dUm9lB1+9yslavMJG5ekoeHh78+eefJCYm0qVLF1QqFe7u7soK4YGBgbz33ns0b96cRo0asXz5ciDnm3jHjh2VdnJrtT1p+PDhODs7Y2dnR0BAAJCTKbp58yZeXl54eXkBORmA3G/uX331Ffb29tjb2ysZjujoaGxsbBgyZAh2dna0bt2atLS0Il9bo0aNMDIyUjIVX3zxBS4uLqhUKqUvw4YN48qVK7Rr144FCxaQmprKwIEDcXV1xcnJie3btwM5i2D6+fnh7e2Nj49Pkft169aNtm3b0qhRI8aPH6/0Z+/evTRt2hRHR0eliHBh7RQlOTlZqdO4atUqRo4cqTzWsWNHpXSNsbExn3zyCY6Ojhw7doyffvoJV1dX1Go177//vrJsQkHX6MlrEh4eXmDA8ODBAyIjI3F0zHljMDMzw8XFJV8we/78edzc3DAyMsLAwICWLVsqJWhyybLMxo0blZXYc/eFnBX6C6uLCWBhYaEsFlqxYkVsbGyUotDbt29Xlmzo16+fEkwV1tekpCRCQkKUbFzZsmWVBWfr1q1LQkICt27dKrAfTk5OIlAShH+p7IcPiZs6jdgPR5UosNLqwbpWehzoksnXqfGY5V2qRtIHj7EwNPiVD6xABFdPRavVsmfPHhwcHAgICMDJyYnIyEg+++wz+vbtq+wXGRnJwYMHOXbsGDNmzHiqdYRmz55NeHg4kZGRHD58mMjISEaNGkXNmjU5dOgQhw4d0tk/IiKClStXcvz4cf744w+WL1+ulJq5fPkyI0aM4OzZs1SpUoXNmzcXeeyTJ0/SqFEjzMzM2LdvH5cvXyYsLAyNRkNERAQhISEsXbpU6cuYMWOYPXs23t7ehIWFcejQIcaNG0dqaqrS3qZNmzh8+HCR+2k0GoKCgjhz5gxBQUHcuHGDO3fuMGTIEDZv3szp06f55ZdflPNTWDt55a7B1KBBA7766qsSZRpTU1Nxc3Pj9OnTVKtWjaCgIEJDQ9FoNOjr6ytlbgq6RiUVHh5eaPmZvOzt7Tly5AgJCQk8fPiQ3bt3c+PGDZ19jhw5grm5uU7R6uPHj2NnZ4eDgwNLly4tUcYwOjqaU6dO4ebmBuSs5J5boLpGjRrEx8cX+fyrV69iamrKgAEDcHJyYvDgwTrXpGnTpoSGhhbbjycdO3YMR0dH2rVrp6w+LwjC6yHtTBRXu3Xn/uP37uLEVoVP++qjb/+QRXfuUCHvUgvVm8Dg/eAzFQzKvqAeP1+vxbDgy5Y7zwNyMleDBg3Czc1NCVa8vb1JSEggOTkZgM6dO2NoaIihoSFeXl6EhYWVuNDtxo0bWbZsGVqtlri4OM6dO4dKpSp0/6NHj9K1a1elzEq3bt04cuQIfn5+1KtXT+l3s2bNiI6OLrCNBQsWsHLlSi5dusTOnTsB2LdvH/v27cPJyQnIKdh7+fJlPD09dZ67b98+duzYoczBSU9P5/r16wD4+vpStWrVYvfz8fFRhrZsbW25du0a9+7dw9PTUymQXVw7T66Fk3dYMCgoiKFDh7J3795CzyPkzK3r3r07AL/99hsRERFK2aC0tDTMzMyAp79GecXFxWFqalrsfjY2NkyYMIHWrVtToUIF1Gp1vmHKguoHurm5cfbsWc6fP0+/fv1o165dkQXCU1JS6N69OwsXLqRSpUr5HpckqcgMGOR86Th58iSLFy/Gzc2N0aNHM2fOHGbOnAnkZLyedqHSpk2bcu3aNYyNjdm9ezddunTh8uXLT9WGIAilT87KIuHHFdxZtAi0hdT6e8J+J4k13noMSk1i2N1k/n7HkaDFSPCaAmUKfx97FYngqgTyzrkqiSc/jCRJwsDAQKmbB38XVs7r6tWrzJ8/nxMnTmBiYkL//v0L3K+kypUrp/xbX1+/0GHB3DlXO3bsYNCgQfz111/IssykSZN4//33izyGLMts3ryZJk2a6Gw/fvy4Tl29ovZ7sp/aIv4gC2unKH5+fgwYMACgyOtQvnx5JYCRZZl+/fopNQ5zFXWN8rZd2HUzNDQs8TUdNGiQMtQ2efJknTluWq2WLVu2KEWin2RjY4OxsTFRUVEcP35cGZ6GnPqHI0aMIDMzk+7du+Pv70+3bt2Ux83NzYmLi8PCwoK4uDglqCyMpaUllpaWSuarR48ezJkzR3k8PT0dQ0PDEr3mXHkDvfbt2/PBBx9w9+5dZa6WIAivnsy4OG6On8DDEydKtH+yIXzXQY/TDSUC7ybSOSXPKETV+jl3AtZxe0G9fbHEsOAz8vDwUIaJgoODqV69uvKBsH37dtLT00lISCA4OBgXFxfq1q3LuXPnePToEffv3+e3337L12ZycjIVKlSgcuXKxMfHs2fPHuWxihUrKsWBn+zHtm3bePjwIampqWzduhUPD49nek1+fn44OzuzevVq2rRpw4oVK5SacbGxsdy+fTvfc9q0acPixYvJXek/d0jyWffL5e7uTkhICFev5lRFT0xMfKZ2ICe7l1to28rKCo1GQ3Z2Njdu3CAsLKzA5/j4+LBp0yblNScmJnLt2rUir5GVlZUS7BQ2BGtjY8Off/5ZbJ8B5djXr19ny5Yt9OnTR3nswIEDWFtb6wRcV69eVQLTa9euceHCBaysrBgxYgQajUb5b8SIEciyzKBBg7Cxsck3ZOrn56dM/l+9ejWdO3cusp81atSgdu3ayh2Zv/32G7a2f9/Bc+nSpRINheZ169Yt5RqHhYWRnZ1NtWrVnqoNQRBKT/KePVzp3KXEgZWmnsTYwfpcqyfz3a3buoGV2zAYFvraBlYgMlfPLDAwkIEDB6JSqTAyMtK5E02lUuHl5cXdu3eZOnUqNWvWBODtt9/G3t6eevXqKcNteTk6OuLk5IS1tTW1a9fmjTfeUB4bOnQobdu2VeY75WratCn9+/fH1dUVgMGDB+Pk5FToEGBxpk2bRp8+fTh//jznz5+nefPmQM5k759++ilfFmPq1Kl89NFHqFQqsrOzqVevXr47vJ5mv1ympqYsW7aMbt26kZ2djZmZGfv37y9xO7lzrmRZpmzZsvzwww9Azt1p9erVw9bWFhsbG2VS95NsbW2ZNWsWrVu3Jjs7mzJlyrBkyRLc3d0LvUYBAQEMGjSIqVOnFjiZHcDa2pqkpCQePHhAxYoVuXXrFs7OziQnJ6Onp8fChQs5d+4clSpVonv37iQkJCjHzju0vGHDhnxDgkePHmXOnDmUKVMGPT09vv3220IzPaGhoaxduxYHBwdl6Pizzz6jffv2TJw4kbfffpsff/yRunXrsnHjRoAi+7p48WL8/f3JyMigfv36rFy5EoDMzEz+/PNPnJ3zVYcAcm7WmDdvHrdu3UKlUtG+fXt++OEHNm3axBeVZrQAACAASURBVHfffYeBgQGGhoZs2LCh2OFJQRBKX1ZKKvGzZpFUwF3EBcnUh5+89NjrLPHWwzSmxiZikjuaUKUOdP4W6j1bguBVImoLPmeBgYEYGxszduzYl90V4RW1YMECKlasyODBg192V164rVu3cvLkSWX+lZWVFeHh4f94eO95tSO82l639///mjSNhpix49DGxJRo/+vVYVFnfe5Vk5mckEiH1Id/z69yHgi+M6Gc8Qvr74tQWG1BMSwoCKVs+PDhOvPM/s20Wi2ffPKJ8rOpqSk+Pj7FLppbmNybSzIzM9ErpcKsgiDokrVa7nz7LVf7+Jc4sNrtLDGpvz4WFR+xJTaOjrmBVaVa8O4W6LjgtQusivLCMleSJDUBgvJsqg9Mk2V5YSFP+VdkrgRBEITnQ7z/v3oyYmK49skYtKejSrT/faOcSevn6sOYe/fpnZzyd1ZH/S60/QzKV35h/X3RCstcvbA5V7IsXwTUjw+uD8QChdfjEARBEAThlSTLMsk7dxIbGIj0sOgFqXNFNJT4rr0elgYZbLyZQP3Mx3eCVzADv0XQpN0L7PHLVVoT2n2Av2RZvlZKxxMEQRAE4TnISk7mVuB0knfvpiS3lWQYwBpvPX5Xy4y8f49eySl/Bxv23aH9fDCq+gJ7/PKVVnD1DlBgRWBJkoYCQwHq1KlTSt0RBEEQBKE4D0+cIHb8BLRxcSXaP9oMvu6sj2P5h+yIvYdp1uM7AQ2rQocvwb5b0Q38S7zw4EqSpLKAHzCpoMdlWV4GLIOcOVcvuj+CIAiCIBRNzsjgzjdLSFi+HEo4N3unq8Sx5tnMSLqN64NHfz/QpD10+hqMi16Q+N+kNG63aQeclGW56AJlr6jo6Oh8CyAGBgYq5VcKEx4ezqhRo4CcRUZ///33pz523kLAT27PLdMCsGnTJvr3719kWxqNht27dys/79ixQ2cV7eetVatWNGnSBJVKhbW1NSNHjuT+/fsv7Hi5nvVcl8ZxHj16xFtvvYVarSYoKEjnsf79+yvlitRqNS1atHie3f3H2rdvXyrXD/IX184VHx9Px44dcXR0xNbWlvbt2z9T+9OmTePAgQNF7tO/f382bdpU4GNarRZTU1MmTpyos33cuHHY2dkxbtw47ty5g5ubG05OThw5cqTQ4wwePJhz5849/Yt4bNu2bcyYMQPIKeBua2uLSqXCx8eHa9f+noWxevVqGjVqRKNGjXTW5Pv000+pXbs2xsa6d2mtWrUKU1NT5fcxd524O3fu0LZt23z75S4rkpCQgJeXF8bGxvmuYUZGBkOHDqVx48ZYW1srC+0uWLCAOnXqFHjNhZfj0dWrRPfxJ2HZshIFVonGMO9tiWpOyWyMj8M1/XFgVa4ydP0e3vn5PxVYQekMC/amkCHBkjpvXXp3i9hcOP9c2nF2dlYWTgwODsbY2Pi5fmBGRERw7tw5nZWwi6LRaAgPD1c+kPz8/PDz83tu/SnIunXrcHZ2JiMjg0mTJtG5c2cOHz78wo6n1WpfyLkuyLMcJ3c1+cJKKX3xxRf06NHjufTvecsbmL8s06ZNw9fXl9GjRwM8VcHsvHKDkWe1f/9+GjduzC+//MLnn3+uLG66bNkyEhMT0dfXZ8OGDTg4OChBSWEKezwrKytfLcmCzJs3jx07dgDg5OREeHg4RkZGfPfdd4wfP56goCASExOZPn064eHhSJJEs2bN8PPzw8TEhE6dOjFy5Eid4t+5evXqxTfffKOzzdTUFAsLC0JDQ5UFdPPuV758eWbOnElUVBRRUbp3k82ePRszMzMuXbpEdna2UnVhzJgxmJiYPPPyHMLzI8sy94M2Ej93LnIh5dKedLyxRIRXJrNTE6iZlPX3Aw3fAr/FUKnmC+rtq+2FZq4kSaoA+AJbXuRxXqZWrVoxYcIEXF1dady4sfItNTg4mI4dOxIdHc3SpUtZsGABarWaI0eOcOfOHbp3746LiwsuLi6EhoYCOd/6WrdujZ2dHYMHD6aoZTI++eQTZs+enW97WFgYzZs3x8nJiRYtWnDx4kUyMjKYNm0aQUFBStYkb3YgOjoab29v5RtvbkHl/v37M2rUKFq0aEH9+vWVb/JxcXF4enqiVquxt7cv8ps5QNmyZZk3bx7Xr1/n9OnTAPz000+4urqiVqt5//33ycrK+aM0NjZmzJgx2NnZ4ePjw507dwBYvnw5Li4uODo60r17dx4+fKj0cdiwYbi5ufH222/nO9f9+/dn+PDhuLu7U79+fYKDgxk4cCA2NjY62b59+/bRvHlzmjZtSs+ePZWyP1ZWVgQEBNC0aVMcHBy4cOFCgdc0r8TERLp06YJKpcLd3Z3IyEhu377Nu+++y4kTJ1Cr1fz1119FnrNcKSkpDBgwAAcHB1QqlfJtf/369Tg4OGBvb8+ECROU/Y2Njfn0009xdHTE3d2d+Pj4Yq9xSc5P3izqmjVrUKlUODo68t577+Xrc0G/g5CT5ejWrRtt27alUaNGjB8/XnnOypUrady4Ma6ursrfw5Pi4uJ0yv3kFsuWZZlx48Zhb2+Pg4ODTlZw7ty5ODg44OjoqGSa8malZsyYgYuLC/b29gwdOrTIv7lc69evZ/To0dSpU4djx44BOV9WUlJSaNasGXPnzmX8+PFs374dtVpNWloaw4cPx9nZGTs7OwICApS2WrVqpQQVxsbGfPLJJzg6OnLs2DEmTpyoZKIKWpT40qVLlCtXTllI1cvLCyMjIyCnfFTM4/WH/ve//ylF1E1MTPD19VWKmLu7u2NhYVHsa86rS5cuSumvJ1WoUIE333yzwGLhK1asYNKknNkhenp6YgHYV4w2MZGYESO5FRhYosAqvQwsbafHLZ+HLEi6TU3t48CqbEXotAj8N/1nAyt4wcGVLMupsixXk2U56UUe52XTarWEhYWxcOFCpk+frvOYlZUVw4YNY8yYMWg0Gjw8PBg9ejRjxozhxIkTbN68WUmpT58+nTfffJOzZ8/StWtX5QOwIG+//TYnT57MV6fO2tqaI0eOcOrUKWbMmMHkyZMpW7YsM2bMoFevXmg0Gnr16qXznA8//JB+/foRGRmJv7+/MpwJOR9oR48eZdeuXcqH088//0ybNm3QaDScPn1aKZ9SFH19fRwdHblw4QLnz58nKCiI0NBQNBoN+vr6ypt1amoqzs7OnD17lpYtWyrns1u3bpw4cYLTp09jY2PDjz/+qLQdExPD77//zpYtW/Kda4B79+5x7NgxFixYgJ+fH2PGjOHs2bOcOXMGjUbD3bt3mTVrFgcOHODkyZM4Ozvz1VdfKe1Xr16dkydPMnz4cObPn1/gNc0rICAAJycnIiMj+eyzz+jbty9mZmb88MMPeHh4oNFolFqHeY0bN04ZhvH39wdg5syZVK5cmTNnzhAZGYm3tzc3b95kwoQJHDx4EI1Gw4kTJ9j2uPREamoq7u7unD59Gk9PT6Vgc1HXuLjzk9fZs2eZNWsWBw8e5PTp03z99df5XkdBv4O5NBoNQUFBnDlzhqCgIG7cuEFcXBwBAQGEhoZy9OjRQofJRowYwaBBg/Dy8mL27NncvHkTgC1btii/iwcOHGDcuHHExcWxZ88etm/fzvHjxzl9+rROMJdr5MiRnDhxgqioKNLS0oosyQQ5RagPHDhAp06d6N27N+vX5yTld+zYoRR4nzBhgs7fm6GhIbNnzyY8PJzIyEgOHz5cYNYtNTUVNzc35Xd869atnD17lsjISKZMmZJv/9DQ0ELLN/3444+0a5dzm3tsbCy1a9dWHrO0tCQ2NrbI1wk59TFVKhU9evTgxo0bynZnZ+div1A9KXdIeerUqcoXmNzAX3j5UkJCuOLXmZSDB0u0/58WMHmAHp617jHx3r2/h8DqecIHv0OzfvAfL1clagsWo7B6Znm3d+uWc/dDs2bNSlTT78CBAzofIMnJyaSkpBASEsKWLTlJvg4dOmBiYlJoG/r6+owbN47PP/9ceRMFSEpKol+/fly+fBlJksjMzCy2P8eOHVOO+9577+l8CHXp0gU9PT1sbW2VN0MXFxcGDhxIZmYmXbp0KVFwBShZgd9++42IiAhcXFyAnFW3c2sW6unpKcHfu+++q5zbqKgopkyZwv3790lJSaFNmzZKuz179ixyCKVTp05IkoSDgwPm5uY4ODgAYGdnR3R0NDExMZw7d04Z5sjIyFBqKoLu9c09T0U5evSokmHy9vYmISGB5OTkYp9X0LDggQMH2LBhg/KziYkJISEhtGrVClNTUwD8/f0JCQmhS5culC1blo4dOyr93b9/P1D0NS7u/OS9vgcPHqRnz55K1qFq1fy3Uxf1O+jj40PlyjkLBtra2nLt2jXu3r2r83p69erFpUuX8rXbpk0brly5wt69e9mzZw9OTk5ERUVx9OhRevfujb6+Pubm5rRs2ZITJ05w+PBhBgwYoGRzCurroUOHmDdvHg8fPiQxMRE7Ozs6depUwNXJsWvXLry8vDA0NKR79+7MnDmThQsXFjuEt3HjRpYtW4ZWqyUuLo5z584pmbdc+vr6ylzKypUrU758eQYNGkTHjh2Va5pXXFyccs7y+umnnwgPD/9HQ/C5wWO5cuX4/vvv6devHwcff/CamZkpgW1JabVaYmJiaNGiBV999RVfffUVY8eOZe3atc/cR+Gfy05P5/YX87lXSCYy3/4SbG0u8VtzmS/v3qHpo8dzq8oYge8McB4EonICIMrfFKtatWrcu3dPZ1tiYqJOSju3lIm+vj5arbbYNrOzs/njjz/QaDRoNBpiY2PzTSgtiffee4+QkBCdb5VTp07Fy8uLqKgodu7cSXp6+lO3m1feMi25wZGnpychISHUqlWL/v37s2bNmmLbycrK4syZM9jY2CDLMv369VNe/8WLFwkMDCzweblBbP/+/fnmm284c+YMAQEBOq+rQoUKJXoNenp6Oq9HT08PrVaLLMv4+voq/Tl37pxOZuxpr+/LVKZMGeWclbS/xZ2fp1XU72De9p/lfFatWpU+ffqwdu1aXFxcCAkJeer+5UpPT+eDDz5g06ZNnDlzhiFDhhT797J+/XoOHDiAlZUVzZo1IyEhQQk6CnP16lXmz5/Pb7/9RmRkJB06dCjwOOXLl1eCNAMDA8LCwujRowe7du3SmUSey9DQMF87Bw4cYPbs2ezYsUM517Vq1dJ5j4iJiaFWrVpF9rlatWrK8wcPHkxERITyWHp6OoaGhkU+v6D2jIyMlC8qPXv25OTJk0/VhvB8pZ8/z9XuPUocWN2uDIH++px2z+LnW/F/B1Z134DhoeA6RARWeYgzUQxjY2MsLCyUN9DExET27t3Lm2++WeI2KlasyIMHD5SfW7duzeLFi5Wfc4dePD09+fnnnwHYs2dPvqDuSWXKlGHMmDEsWLBA2ZaUlKS8ca5atarQPuTVokULJTuybt26fMNcT7p27Rrm5uYMGTKEwYMHF/smmZmZyaRJk6hdu7Yy52fTpk3cvn0byDmnuXc2ZWdnK/Nhfv75Z+U8P3jwAAsLCzIzMwud71Hc6yyMu7s7oaGhyhBrampqgZmTkh7Hw8ND6WNwcDDVq1enUqVKT9WnXL6+vixZskT5+d69e7i6unL48GHu3r1LVlYW69evp2XLlkW287TXuDDe3t788ssvJCQkACiTkvMq7HewMG5ubhw+fJiEhAQyMzP55ZdfCtzv4MGDyly7Bw8e8Ndff1GnTh08PDwICgoiKyuLO3fuEBISgqurK76+vqxcuVJ5zpN9zQ1MqlevTkpKSqF3B+ZKTk7myJEjXL9+nejoaKKjo1myZIkyNFjU8ypUqEDlypWJj49nz549xZ6TlJQUkpKSaN++PQsWLFDmKuZlY2OjMy3g1KlTvP/+++zYsUPJBENOxm/fvn3cu3ePe/fusW/fPp3Mb0Hi8qxptGPHDp0SNJcuXcp3B3VxJEmiU6dOBAcHAznZ65LejCM8X3JWFgk//MDVt3uRUcK5n0fsJMYP1Kd21TRWx8VjkZUFBobQdi702wVV67/gXr9+RHBVAmvWrGHmzJmo1Wq8vb0JCAgocM5MYTp16sTWrVuVyc+LFi0iPDwclUqFra0tS5cuBXLm6oSEhGBnZ8eWLVtKtKjqoEGDdL79jx8/nkmTJuHk5KSz3cvLi3PnzhW4DMDixYtZuXIlKpWKtWvXFjiPJq/g4GAcHR1xcnIiKChIuXvrSf7+/qhUKuzt7UlNTWX79u1AznDQrFmzaN26NSqVCl9fX+XNvEKFCoSFhWFvb8/BgweZNm0akDP3yM3NjTfeeANra+tC+/bkuS4JU1NTVq1aRe/evVGpVDRv3pwLFy4U+ZyijhMYGEhERAQqlYqJEyfq3PpelLxzrtRqNRkZGUyZMoV79+5hb2+Po6Mjhw4dwsLCgjlz5uDl5YWjoyPNmjWjc+fORbb9tNe4MHZ2dnz66ae0bNkSR0dHPv7443z7FPY7WBgLCwsCAwNp3rw5b7zxRqG15CIiInB2dlau0eDBg3FxcaFr167KBHtvb2/mzZtHjRo1aNu2LX5+fjg7O6NWq/Mtn1KlShWGDBmCvb09bdq0UYapC7N161a8vb11sm+dO3dm586dPHr0qNDn5f6tWFtb06dPH2X4uSgPHjygY8eOqFQq3nzzTZ05gLk8PT05deqUklEeN24cKSkp9OzZE7VardwNXLVqVaZOnarcQDNt2jRliHT8+PFYWlry8OFDLC0tlQzyokWLsLOzw9HRkUWLFukEyYcOHaJDhw6F9t3KyoqPP/6YVatWYWlpqUyBmDt3LoGBgcrv4JdfflnseRCer8zYWK73H8Dt+V9CCaaMpJaDr/30+KaTHgPSkvjy9l2MZBlqu+dkq9yHiWxVIV5Y4eZnIQo3C8bGxsqdeoIgFG306NF06tSJt956q9SO6enpyfbt2zExMWHVqlWEh4fnW7LhaRXWjnj/f36Sdu7k1vQZZBfw/ppezoTyj3RHSs7WgW866lOmQhaf3UnAJf0RGJQH76ngPhz0il8q5L+gsMLNIuQUBEF4TU2ePFkZ9iwNd+7c4eOPP1ZutjE0NGTPnj3KHc/PYsGCBXz++efPPHQuFC0rKYnYjz/h5rjx+QKr9HJViLIdyB9uATwsnzOPWKsH61rpMaO3Ps76D9kUG5cTWNVyhvePQIuRIrAqAZG5EgRBEF5J4v3/n0n94zg3J05Ee+uWzvZsSZ8bll5EW7UnSz9nmLva3TNUi1vKYj99bpnJTE64R+eUVKSyFcH7U3AdKoKqAhSWuRJLMQiCIAjCv0h2RgZ3FiwkcdWqfOVrEqs05lKjt3lYQXfx2ITqDmxwd6RCpZNsik2gjlYL9j2gzWyoWKMUe//vIIIrQRAEQfiXSL94kZvjxvPoiTueH5WtzOWG3bhtli/JonjrWlcGVf0Nw+r1oMN8qN/qxXb2X0wEV4IgCILwmpOzs0lcuYo7Cxci57kTsKAhwMJImaacMV2I67AeYFD0vkLRRHAlCIIgCK+xzJs3uTlxEg/DwnS2FzYEWJTTf9VGrdWnrIgO/hFx+gRBEAThNSTLMsm7dnFrxkyy8yxqnGlgyOWGPbhVw/2p2qtrXw2PXo0oW16EBv/Ua3EGlwwrWTHJ52HEUu982yRJwt/fn59++gnIqZNlYWGBm5tbsYVe82rVqhXz58/H2Vl3zDvvGi9Lly7FyMiIvn37/rMXUghZlvHx8WHbtm0kJSXRt29f4uPjkSSJoUOHKguCJiYm0qtXL6Kjo7GysmLjxo2YmJggyzKjR49m9+7dGBkZsWrVKqV47Pjx4/n111/Jzs7G19eXr7/+GkmSeOutt/jll18wMTEhOjoaGxsbmjRpoqxMP3DgQHbt2oWZmRlRUVFKX3v16sXFixeBnMKvVapUQaPRcOTIEd5//3309PR09hcEQfivyLp/n1szZpC8W3fF/wQTGy5Y+/OoXOG1aZ9UsVp5PN5uhJWqeqH1dIWnI9a5KoEKFSoQFRVFWloaAPv37y+2NtezGjZs2AsLrAB2796No6MjlSpVwsDAgC+//JJz587xxx9/sGTJEmU15Tlz5uDj48Ply5fx8fFhzpw5QE5ZnsuXL3P58mWWLVvG8OHDAfj9998JDQ0lMjKSqKgopXAu5NRA/Pbbb5U+NGjQQAmsIKdu4N69e/P1NSgoSKn31717d6UumYeHB7t3734xJ0gQBOEVl3LkKFf8OusEVlr9clxo3JvTjiNLHFjpG0g4d7CiT4Ab9RxNRWD1HIngqoTat2/Pr7/+CuQUb+3du7fyWFhYGM2bN8fJyYkWLVoo2Za0tDTeeecdbGxs6Nq1qxKcAaxcuZLGjRvj6upKaGiosj0wMFAp07Fo0SJsbW1RqVS88847QE5GqUuXLqhUKtzd3YmMjFSeN3DgQFq1akX9+vVZtGhRga9j3bp1SqkUCwsLJetUsWJFbGxsiI2NBWD79u3069cPgH79+rFt2zZle9++fZEkCXd3d+7fv09cXBySJJGenk5GRgaPHj0iMzMTc3NzAPz8/Iqsv+bp6amU4yiILMts3LhR55wLgiD812SnpXFrxkxuDBmC9nFtVoB7VRoR5jyZmzVLXvO2rn013pnmhlun+hiUFetXPW+vxbDgq+Cdd95hxowZdOzYkcjISAYOHKjUlLO2tubIkSMYGBhw4MABJk+ezObNm/nuu+8wMjLi/PnzREZGKoFMXFwcAQEBREREULlyZby8vHBycsp3zDlz5nD16lXKlSvH/fv3gZz6g05OTmzbto2DBw/St29fJQt04cIFDh06xIMHD2jSpAnDhw+nTJkyOm2Ghoby/fff5ztWdHQ0p06dws3NDYD4+HgsLHImQdaoUYP4+HgAYmNjqV27tvI8S0tLYmNjad68OV5eXlhYWCDLMiNHjlQW/zMxMeHRo0dKsd+ndeTIEczNzWnUqNEzPV8QBOF1lxYZyc3xE8iIjla2ZemV4a/6fsRY5p/OUhjjquXw7NVYDAG+YCK4KiGVSkV0dDTr16+nffv2Oo8lJSXRr18/Ll++jCRJZD6+DTYkJIRRo0Ypz1epVAAcP36cVq1aYWpqCuTMLbr0xJokuc/x9/enS5cudOnSBYCjR4+yefNmALy9vUlISCA5ORmADh06UK5cOcqVK4eZmRnx8fFYWlrqtJmYmEjFihV1tqWkpNC9e3cWLlxYYAkKSZKK/SP8888/OX/+PDExMQD4+vpy5MgRPDw8ADAzM+PmzZv5jl0ST2YKBUEQ/ivkzEzuLv2eu0uXQlaWsj2pUj3OW7/HQyPzkjWkl41z23o0bWtFGZGpeuHEsOBT8PPzY+zYsfk+6KdOnYqXlxdRUVHs3LmT9PT053K8X3/9lREjRnDy5ElcXFzQarVF7l+u3N/rkujr6xe4v4GBAdnZ2crPmZmZdO/eHX9/f2VOE4C5uTlxcXFATqbNzMwMgFq1anHjxg1lv5iYGGrVqsXWrVtxd3fH2NgYY2Nj2rVrx7Fjx5T90tPTMTQ0fMozkHPzwJYtW+jVq9dTP1cQBOF19ujKVaJ79+HukiVKYJWlV4bLDboR4fRxiQOrypZl6DOtOW5+DURgVUpEcPUUBg4cSEBAAA4ODjrbk5KSlAnuq1atUrZ7enry888/AxAVFaXMj3Jzc+Pw4cMkJCSQmZnJL7/8ku9Y2dnZ3LhxAy8vL+bOnUtSUhIpKSl4eHiwbt06AIKDg6levfpTFTxt0qQJV65cAXLmMg0aNAgbGxs+/vhjnf38/PxYvXo1AKtXr1bmafn5+bFmzRpkWeaPP/6gcuXKWFhYUKdOHQ4fPoxWqyUzM5PDhw8rw4KyLHPr1i2srKxK3M9cBw4cwNraOl8GThAE4d9Kzs4mcc1arnbtSnqeO6LvV25AmPNkbtT2Aan4j29ZLxvXzlb0mfQGJjUqvMguC094LYYFC1oe4WWwtLRUhvnyGj9+PP369WPWrFl06NBB2T58+HAGDBiAjY0NNjY2NGvWDMiZSB4YGEjz5s2pUqUKarU6X5tZWVm8++67JCUlIcsyo0aNokqVKsrEdZVKhZGRkRIAlVSHDh0IDg6mYcOGhIaGsnbtWhwcHJQ+fPbZZ7Rv356JEyfy9ttv8+OPP1K3bl02btwI5Ezs3717Nw0bNsTIyIiVK1cC0KNHDw4ePIiDgwOSJNG2bVs6deoEQEREBO7u7hgYFPzr1rt3b4KDg7l79y6WlpZMnz6dQYMGAbBhwwYxJCgIwn9G5s2b3Jz8KQ//+EPZlqVXNmduVa2WJQqqACrUkOg0xJ1qtYxfVFeFIkjyE0UdXyZnZ2c5PDxcZ5uoiv58xcXF0bdvX/bv319qxxw9ejR+fn74+PgQHR1Nx44d//H6VM+rHUEQXl3/pfd/WZZJ2rad+NmzyU5JUbbfq9yQ89bvkm5oWrJ2pGzUbWvTvGMj9PXF4NSLJklShCzL+Qo2vhaZK+H5sbCwYMiQISQnJz/VcOI/YW9vj4+PD5AzFywpKQm1Wq2z1tXTOHLkCB988AHVq1d/nt0UBEF4KbQJCcQFBJBy4Le/t+mX46/6nYmt1bLE7ZSrlo3fUFfM6pbOe7tQOJG5EgRBEF5J/4X3/+T9+7kVEEhWYqKyLSdb9R7phiX7AimTjcNbtXijc2MMyogJ66VJZK4EQRAE4RWRlZxM/OzPSNq+/e9temX5q35nYixblbidCqYS7Qa5Ym4lslWvEhFcCYIgCEIpSjkaStynn6J9vDgzPP3cKqRsmraxwrVDffTLiLlVrxoRXAmCIAhCKchOTSX+iy+4vyFI2abcCWjpVeJ2qpjp4zvIWcyteoWJ4EoQBEEQXrCHJ05wc/KnZOZZhDmpUj3OWfclzcisRG1IUjbN2tbDuUM99A1EtupV9loEV1/26lhqx/okaFe+bcbGxqTkuTV21apVhIeH07lzZ6ZNm8bvv/+OJElkZWXh7OzMD5jZrQAAIABJREFUkiVL2LdvH8uXL8fU1JTU1FQcHByYNWsWtra2ALRq1Yq4uDhl1fKGDRuyadOmfMfetm0bkZGRTJs2ja+++ooffvgBAwMDTE1NWbFiBXXr1gVyFvqcNWsWAFOmTFGKLkdERNC/f3/S0tJo3749X3/9NZIk0atXL6XA9P3796lSpQoajYYzZ87w5ZdfKouhBgYGsnz5cgYNGsSMGTNYt24dc+fORZZlKlasyHfffYejoyMAVlZWVKxYEX19fQwMDMi9OWHcuHGsXbuWsWPHMnbs2H98jQRBEF4X2enp3Fn4NYmrV8PjG8hk4IalN3816IIslWwCelVzA94a5IRpnacvISaUvtciuHpV+fr68uOPP/Ljjz8yePBgFi9ejLOzMy1atGDfvn2MGTNGCSaCgoLw9vbmzJkzSk3BdevW4eyc7yYDHfPmzWPHjh0AODk5ER4ejpGREd999x3jx48nKCiIxMREpk+fTnh4OJIk0axZM/z8/DAxMWH48OEsX74cNzc32rdvz969e2nXrh1BQX+npT/55BMqV64MgIODAzExMVy/fp06deoA6LyOevXqcfjwYUxMTNizZw9Dhw7l+PHjSluHDh3Kt0TCF198QYUKYnVgQRD+W9IiI7k5cRIZj6tiAGj1y3Pe+l3umDqVrBEpG+e2Vjh3qC+yVa8RcaX+oQULFvD5559z9uxZvvnmG+bOnVvgfr169aJ169ZKOZySuHTpEuXKlVOCFS8vL4yMjABwd3dXiiT/73//w9fXl6pVq2JiYoKvry979+4lLi6O5ORk3N3dkSSJvn37sm3bNp1jyLLMxo0bdVZB79SpExs2bCiwT/9n777Do6q2Bg7/zswkmRRCCoQShBBIgEBIgFBEekeK0gQroYmiIFxFUVBR4AMVjf169aIoRVAR5CIigkSB6xWIhA6hBUiBFGpInZnz/THkyEjKoUwkyXqfx4fMnrP32Qk6ruy9z1rt27fH19f3mjkIIYSws+Xnk/ZWDIkj7ncIrLI8a7O91bO6AyvfAAPDprWh7T0NJbAqZ2TlSoecnByHEjVnz55l4MCBgD0p5+TJk7nzzjt599138fPzK3acli1bcvDgQe31gw8+qG0L9uzZkzfeeMPh+q1bt9KyZcsix1qwYAF9+/YFIDk5mTvuuEN7r06dOiQnJ5OcnOxQk6+w/WqbN2+mRo0ahISEaG1RUVHMmzePZ599ttjv5a9zAFAUhV69eqEoCuPHj+fRRx8tsb8QQlQ0Ofv2kTrtefIOH3ZoT63RhkOh92MzupY+iGKjVe96tO7XQJ4ELKckuNLB3d3dIZt44ZmrQk888QTTpk0jOjq6xHH+mrC1tG3B1NRUbQvxaosXL2bHjh388ssvOr+D4n355ZfX1O4LCAggJSWlxH6bNm1iwYIFbNmyRWvbsmULgYGBpKWl0bNnTxo3bkynTp1ueo5CCHG7U/PzyfjoX2T8619gtWrtNsXE4YZDSQ7sqGscn2oKPcdJlvXyToKrW8BgMKAoSqnX7dy5s9QzVldzd3fnwoULDm0bNmxgzpw5/PLLL7i5uQEQGBhIbGysdk1SUhJdunQhMDDQYdsuKSmJwMBA7bXFYuHbb78lLi7O4R65ubnailpRdu/ezdixY/nhhx/w9/fX2gvHDggIYNCgQWzbtk2CKyFEhZd76BAp054n78ABh/Ysz1ocaPQwl7zr6Ronoltt7hwUKqtVFYD8DZaRFStWsH79+mtWiUrSpEkTjhw5or3euXMn48ePZ/Xq1QQE/Pnobu/evVm/fj3nzp3j3LlzrF+/nt69e1OrVi28vb353//+h6qqfPHFF9xzzz1avw0bNtC4cWOHrUOwn/Vq1qxZkXM6efIkgwcPZtGiRYSGhmrtly9f5tKlS9rX69evL3YMIYSoCFSLhYyPPuL40GEOgVW+ixeHQoazLeoFXYGVyRX6jG9Gh/saS2BVQZSLlaui0iOUBzExMSxevJjLly/TrFkzfv75Z4dtvqvPXFWrVo0NGzY49O/UqRNPP/00qqqiKApTp04lKyuLYcOGAVC3bl1Wr16Nn58fL774Iq1btwbgpZde0s5+ffjhh1oqhr59+zqckVq2bFmRwd6mTZvo169fkd/Tq6++SmZmJhMmTADQUi6cOXOGQYMGAfYVsQceeIA+ffrc0M9NCCFud7kJCaQ+/wK5+/ZpbTbFSFJgZxKD+mIxeegax6+2B33HN8enhr7rRfkghZtvc0899RQDBgygR48eZXK/vLw8OnfuzJYtWzCZTMycORMvL6+bzk91q8YRQlQet+Pnv2qxkLngUzLefx+1oMDeBmT4N+dIg0G6E4ICNGpXk84PNMLFVYotl1fFFW6W9cfb3AsvvEB2dnaZ3e/kyZPMmzcPk8m+qOnl5cXHH3/MSy+9dMNjTp06lcWLF0uuKyFEuZZ35AiJ9z9AekyMFlhledYmPmISe8LH6w6sDEaFLg82ovvIJhJYVVCyciWEEOK2dLt8/qsWC5mffkbGe+9pQZVNMZJYrw8n6vXWnWUdoIqfmT7jm8nTgBVEcStX5eLMlRBCCPF3yDt6lJTnXyB3926t7aLXHRxo/DCXvQJL6Hmtxu1qctewEMyeLrd6muI2I8GVEEII8ReqxULmZ5+R8d77qPn5gD1n1fGgPpys2+u6VqtqNaxKh2EhslpViUhwJYQQQlwl78gR+2rVnj1a28UqdTnQ6KHrWq1y9zHSaVgTGrSsrisXoqg4JLgSQgghKO5slYnjQXdzsm4P/atVJgtt7g6hRc+6mFzkwHplVC6Cq6Rpm8vsXnXm/VmiIDMzk+7duwNw+vRpjEajlqdq27ZtuLqWXiMqMTGR//73vzzwwAO3bI5Dhw7l9ddfJzg4mOnTp/PFF19w7tw5srKytGtOnDjB6NGjSU9Px8/Pj8WLF2vJQp977jm+//57AF588UWGDx/uMP6kSZP49NNPtfHef/99PDw8GD16NABdunQhNTWVN954g4EDB/L1118zc+ZMDhw4wLZt27Qs9Pn5+YwfP54dO3ZgMBh455136NKlC2AvQr19+3ZiY2OvK2u9EEI4Q25CAqkvTCd3716t7WKVuhxo/AiXPWvpHicg0sjd99+FZ1U3Z0xTlBOSiqEE/v7+xMfHEx8fz2OPPcaUKVO013oCK7AHV0uXLr1lc9q3bx9Wq5Xg4GAABgwYwLZt26657plnnuGRRx5h9+7dvPTSSzz//PMAfP/99/zxxx/Ex8fz+++/M3/+fC5evKj127FjB+fOnXMYa/To0bz33nsObUuWLNGKVzdr1oxvv/32mlI3n3zyCQB79uzhp59+4umnn8ZmswH2RKUSVAkh/m72LOv/InHIUC2wsikmjtYfSFzLZ3QHVtnu52j/WCDDHussgZWQ4Op6ffLJJ7Ru3ZqIiAiGDBmi5aCKjo5m0qRJtG/fnuDgYL755hsApk2bxubNm4mMjCQmJobc3FxGjRpFeHg4LVq0YNOmTYC9GPTgwYPp06cPISEhPPvss0Xef8mSJQ4lbNq1a0etWtf+x79//366desG2FeJvvvuO629U6dOmEwmPD09ad68OevWrQPAarUydepUXn/9dYexPDw8CAoKKjKIA3uZnkaNGpU4h4CAAHx8fPhrqg0hhPi75B5KIHH4CNLfflvbBrxYpS7bo6ZdV4qFtOCDjH6lKy0ir/0cFJWTBFfXafDgwWzfvp1du3bRpEkTFixYoL2XmprKli1bWLNmDdOmTQNg3rx5dOzYkfj4eKZMmcIHH3yAoijs2bOHL7/8kpEjR5KbmwtAfHw8y5cvZ8+ePSxfvpxTp05dc/+tW7fSqlWrUucZERHBt99+C8DKlSu5dOkSmZmZREREsG7dOrKzs8nIyGDTpk3afd5//30GDhxYZLAWFRXF5s3Xtz0bERHB6tWrsVgsHD9+nLi4uCK/JyGEKEtqQQHpH37I8aFDtfI1N7JadcEtnbO9djLj6XH4e/s5c8qinCkXZ65uJ3v37mXGjBmcP3+erKwsevfurb137733YjAYCAsL48yZM0X237JlCxMnTgSgcePG1KtXj4SEBAC6d+9O1apVAQgLC+PEiRPccccdDv1TU1Md6hMWZ/78+Tz55JMsXLiQTp06ERgYiNFopFevXmzfvp327dtTvXp17rzzToxGIykpKXz99dfExsYWOV5AQAAHDx4s9b5XGz16NAcOHCAqKop69erRvn17jEY53CmE+PvkHjhAygvTHQotX+/ZKhUbe2r+StTAeoxt8Q95ElBcQ4Kr6xQdHc2qVauIiIhg4cKFDsGIm9uf++w3kvn+6v5GoxGLxXLNNe7u7tpKV0lq166trVxlZWWxYsUKfHx8AJg+fTrTp08H4IEHHiA0NJSdO3dy5MgRGjZsCEB2djYNGzbkyJEjAOTm5mpFpvUymUzExMRor9u3b09oaOh1jSGEELeCmp9Pxr8+JuNf/4Irn632JwH7crJuT91bgBfM6Wxp+DWT+o+lT5AUpxdFk+DqOl26dIlatWpRUFDAkiVLCAwsOedJlSpVuHTpkva6Y8eOLFmyhG7dupGQkMDJkydp1KgRf/zxh677N2nShCNHjhAUFFTidRkZGfj5+WEwGJg7d672pJ/VauX8+fP4+/uze/dudu/eTa9evTCZTJw+fVrr7+XlpQVWAAkJCdx111265lgoOzsbVVXx9PTkp59+wmQyERYWdl1jCCHEzcrZt4/UF6aTd+iQ1nbJM5ADTR4hy6uOrjFUbOyp9SuHQ7byVo83iQyIdNZ0RQVQLoKrq9Mj/N1mzZpF27ZtqV69Om3btnUInIrSvHlzjEYjERERREdHM2HCBB5//HHCw8MxmUwsXLjQYcWqNP369SM2NpYePXoA8Oyzz7J06VKys7OpU6cOY8eOZebMmcTGxvL888+jKAqdOnXigw8+AKCgoICOHe0/T29vbxYvXqwVaS7J1q1bmTlzZpHvrVy5kokTJ5Kenk6/fv2IjIzkxx9/JC0tjd69e2MwGAgMDGTRokW6v08hhLhZtvx8Mj78kMxP/g1Wq71NMXCibi8S6/VFNej7X+AFczqbGiylabP6fNVuOdXcqzlz2qICkMLN5UxOTg5du3Zl69atZXZ+aefOnbz11ltacNSlSxfmz59/06kUbtU4QoiK6WY+/3P27CH1hRfIO/znCvxlj5rsb/wIl7zr6RqjcLVqf4NfeK79VPrV7yfnq4SD4go3y9OC5Yy7uzuvvPIKycnJZXbPjIwMZs2apb328/MjOjqa1atX3/CYXbt25dixY7i4SAFTIcStY8vLI+3NN0kcPkILrFQUTtbpzvaoaboDqwvmdL5r+h7GuzJYMfhr+gf3l8BK6FYutgWFo6ufUCwLPXv2dHhdeFD+ZhTm9xJCiFsle+dOUqfPIP/YsT/b3KtzoPHDXKjaQNcYhatVe4M38XS7KQxqOEiCKnHdJLgSQghRrtlyckh/513Ofv45XDnqoqKQVKcLR+sPxGbUV1HjglsGmxouIahRAN+0/4paXvrL3ghxNQmuhBBClFvZO3bYV6tOnPizzb06Bxo9xAWfhrrH2VtjMwdCfmFimycYFDIIgyKnZsSNk+BKCCFEuWPLzibtrRjOLVniuFoV2JmjwffoXq3Kcj1HbIMvadu6Gf/XcgW+Zl9nTltUEhJcCSGEKFcu/+93UmfMoCApSWu7kdWqg9X/R0aL/czr+CIR1SOcMVVRSTk1uFIUxQf4N9AMUIHRqqr+dr3jFJdfyRmKupfRaCQ8PBxVVTEajbz//vu0b9+elJQUJk2apBVp1iMxMZH+/fuz90r19VspNTWVcePGsWbNGjIzMxk6dCjbt28nOjqa999/X7tu+fLlzJkzB6vVSv/+/XnttdcAOHnyJCNHjuT8+fNYrVbmzZvH3XffDcDcuXNZsGABRqORd999l969e5Ofn0+PHj34+eefMZlMxMbGcs8993DXXXexdu1a4uPjefzxx7l48SJGo5Hp06czfPhwAI4fP86IESPIzMykVatWLFq0CFdXV2JiYoiJiWHgwIEOcxZCCGvWZdLmv8H5Zcu1thtZrbrscoFtod8xuEcvhjd6DqNBynKJW8vZm8rvAOtUVW0MRAAHSrn+tuTu7k58fDy7du1i7ty5PP/884C9xExRgVVRZWvKwltvvcW4ceMAMJvNzJo1i/nz5ztck5mZydSpU9m4cSP79u3j9OnTbNy4EYDZs2dz3333sXPnTpYtW8aECRMA2L9/P8uWLWPfvn2sW7eOCRMmYLVacXV1pXv37ixf/ucHXceOHVm7di0AHh4efPHFF1q/yZMnc/78eQCee+45pkyZwpEjR/D19dUKYE+ZMoVXX33VuT8oIUS5k7VlK8cGDnAIrHLM/uyMnMThkGG6A6vD1XZw4Z6dfDR2Pg80eUACK+EUTguuFEWpCnQCFgCoqpqvqup5Z92vrFy8eBFfX/uefGJiIs2aNQNg4cKFDBw4kG7dutG9e3eysrLo3r07LVu2JDw8nO+++04bw2Kx8OCDD9KkSROGDh1KdnY2AHFxcXTu3JlWrVrRu3dvUlNTAXuyzeeee442bdoQGhrK5s2bi5zbihUr6NPHXuvK09OTDh06YDabHa45duwYISEhWvHnHj16sGLFCgAUReHixYsAXLhwgdq1awPw3XffMWLECNzc3Khfvz4NGzZk27ZtgL1Y9ZIlS4qcT2hoKCEhIYA9EA0ICCA9PR1VVfn5558ZOnQoACNHjmTVqlX6/gKEEJWK9dIlUl98kVNjx2JJsX8mqkByrbvYFvUC53301SvNdrlIfIs1PPhkV+b0eFWyrAuncua2YH0gHfhMUZQIIA54SlXVy1dfpCjKo8CjAHXr1nXidG5cTk4OkZGR5Obmkpqays8//1zkdX/88Qe7d+/Gz88Pi8XCypUr8fb2JiMjg3bt2jFw4EAADh06xIIFC7jrrrsYPXo0H374IU899RQTJ07ku+++o3r16ixfvpzp06fz6aefAvaAbNu2baxdu5ZXXnmFDRs2ONz7+PHj+Pr6llpKp2HDhhw6dIjExETq1KnDqlWryM/PB+xbor169eK9997j8uXL2j2Sk5Np166dNkadOnW0JKbNmjVj+/btpf4Mt23bRn5+Pg0aNCAzMxMfHx+t7M7V4wkhRCFbbi7HBgzEclXd01w3Hw42epCzfvrrlNaJ9CKz1Sk+bPUaLgZJXCycz5nBlQloCUxUVfV3RVHeAaYBL159kaqqHwMfg738jRPnc8MKtwUBfvvtNx555JEiz0z17NkTPz8/AFRV5YUXXuDXX3/FYDCQnJzMmTNnALjjjju0IsgPPfQQ7777Ln369GHv3r1awk6r1UqtWn/mWBk8eDAArVq1IjEx8Zp7p6amaqtRJfH19eWf//wnw4cPx2Aw0L59e44ePQrAl19+SXR0NE8//TS//fYbDz/8cKlnw4xGI66uriXWWExNTeXhhx/m888/x2CQx5uFECVTrVYKTp/GevasFlipwOkabTgcMgyLyUPXOO6eCl0ebkZwZHWgjfMmLMRfODO4SgKSVFX9/crrb7AHV+XanXfeSUZGBunp6de85+npqX29ZMkS0tPTiYuLw8XFhaCgIHJzcwGuyfarKAqqqtK0aVN++63o8/6FK1JGo7HIM13u7u7a+KUZMGAAAwYMAODjjz/WahQuWLCAdevWad9nbm4uGRkZBAYGcurUKa1/UlISgYGB2uu8vLxrth8LXbx4kX79+jFnzhxt9cvf35/z589jsVgwmUzXjCeEqLysly5RkJyCainQ2vJdqnCw0f1kVNP/RF9IVHU6jWiM2UtWqkTZc9oygqqqp4FTiqI0utLUHdjvrPuVlYMHD2K1WvH39y/xugsXLhAQEICLiwubNm3ixFUJ7k6ePKkFUUuXLqVDhw40atSI9PR0rb2goIB9+/bpnldoaGiRK1pFSUtLA+DcuXN8+OGHjB07FrBvyxYebj9w4AC5ublUr16dgQMHsmzZMvLy8jh+/DiHDx+mTRv7b4GZmZlUq1atyBqB+fn5DBo0iEceeUQ7XwX2YLJr167awwCff/4599xzj+7vVQhR8agWC/lJSeSfOOEQWKVVi+D31tN1B1bungp9x4fTa2y4BFbib+PsPFcTgSWKorgCx4BRNzJIWaZiKErhmSuwb/d9/vnn2mpPcR588EEGDBhAeHg4UVFRNG7cWHuvUaNGfPDBB4wePZqwsDAef/xxXF1d+eabb5g0aRIXLlzAYrEwefJkmjZtqmuOnp6eNGjQgCNHjtCwoT3PS1BQEBcvXiQ/P59Vq1axfv16wsLCeOqpp9i1axcAL730EqGh9gOhb775JuPGjSMmJgZFUVi4cCGKotC0aVPuu+8+wsLCMJlMfPDBB9r3v2nTJvr161fknL766it+/fVXMjMzWbhwIWA/+B8ZGclrr73GiBEjmDFjBi1atGDMmDG6vk8hRMVjX61KRr1qVV5VDBSYPNnb7FHd4zSI9Kfzg01wr6LvyUEhnEVR1dvnmFNUVJS6Y8cOh7YDBw7QpEmTv2lG5cvKlSuJi4tj9uzZZXbPwYMHM2/ePEJDQ4mNjWX+/PmsWbPmpsZcuHAhO3bskDxXQlRw2tmqc+cc2q1GMzlmf44nJ7J98bliev/JzV2h0wNNCImqIUWWRZlSFCVOVdWov7bL6eIKZNCgQQQFBZXZ/fLz87n33nu1lS9XV1f27t2rJR69ETExMcydOxdvb+9bNU0hxG3ImpVF3pEjfwmsFPLcfMn2CEDVmX+qXjM/7n+5PaGta0pgJW4bsnIlhBCizNhXq85gPXfWod1qcCXX3R/bVakSEk8dLXblysVNoePwRjS+s5YEVeJvU9zKldQWFEIIUSasWVn2s1UFBQ7tea5VyXerqnucwNCqdBsZhre/+62eohC3hARXQgghnEq12bCcPoPlbKZDu83gQo7ZX3fpGqMJ2g8JIbxzHRSDrFaJ25cEV0IIIZzGlp1NflIS6pVKEIXyXaqQ5+YDOrf0Aup50WNUU3xrepZ+sRB/MznQroOiKDz00EPaa4vFQvXq1enfv3+J/YKCgggPDycyMpLIyEgmTZp003O5up6hXv/73/+IiIggPDyckSNHFntdbGxsqd+Ts7z99tt88cUXAHz99dc0bdoUg8HA1Wfw8vPzGTVqFOHh4URERBAbGwvApUuXtJ9xZGQk1apVY/LkyYA9p1jXrl1p0aIFzZs314pK79mzh+joaG3smTNnEhgYyEsvvQTYk8A2b96c8PBw2rdvr6WuABg9ejQBAQHX/D1MnTqVmjVrXlMsW4jKSLXZKDhzhrxjxxwCK1Uxku0eQJ7ZV1dgZTBAmwH1GfJslARWotwoFytXG39uUGb36t7t6DVtnp6e7N27l5ycHNzd3fnpp590ZxTftGkT1ar9vQVCp0+fzttvv03Xrl05fvz43zqXolgsFj799FP++OMPwF6v8Ntvv2X8+PEO133yySeAPTBKS0ujb9++bN++nSpVqmjlicBeIqiwXNDs2bO57777ePzxx9m/fz933303iYmJhIeHk5SUxMmTJ7WallOmTOGZZ54BoH79+vzyyy/4+vryww8/8Oijj/L77/ZiA9HR0Tz55JM88sgjDvN74403HLL0C1FZ2XJzKUhKwvaXqhEFJg/yzH6oir7f6w1GhaHTWlO9bhVnTFMIp5GVK53uvvtuvv/+e8Beg+/+++/X3svKytJWVJo3b86KFSuKHefgwYNadnNA+x89QFxcHJ07d6ZVq1b07t2b1NRUrT0iIoKIiAg++OADrW+nTp0cgooOHTo4rLAUcnV1JSkpCbAHDXqcPXuWe++9l+bNm9OuXTt2794N2Fd4Ro8eTZcuXQgODubdd9/V+ixevJg2bdoQGRnJ+PHjsVqtWK1WoqOjadasGeHh4cTExFxzr59//pmWLVtqhZybNGlCo0aNrrlu//79dOvWDYCAgAB8fHz469OlCQkJpKWl0bFjR8C+6njx4kXAnjW/du3a2rUDBgxg2bJlRX7/7du3x9fXF4B27dppPz+w/9wLa0gKIf6kqiqW9HTyjh51CKxUxUCOuRq57tV0B1buVVzxqOoqgZUolyS40mnEiBEsW7aM3Nxcdu/eTdu2bbX3Zs2aRdWqVdmzZw+7d+/WAgCArl27attVMTExNG7cmPz8fG0Fafny5QwfPpyCggImTpzIN998Q1xcHKNHj2b69OkAjBo1ivfee++awGnMmDFa5vOEhARyc3OJiLi2RESDBg144YUXrglESvLyyy/TokULdu/ezf/93/85rNIcPHiQH3/8kW3btvHKK69QUFDAgQMHWL58OVu3biU+Ph6j0ciSJUuIj48nOTmZvXv3smfPHkaNujZJ/9atW2nVqlWpc4qIiGD16tVYLBaOHz9OXFycQ81DgGXLljF8+HDt0eyZM2eyePFi6tSpw9133817772nXRsVFcXmzZtLve+CBQvo27dvqdcJUZnZ8vPJP36cgjNn4KoUP1ajmcsetbC46Cu2bDAq+NTwoIqfWVIsiHJLgiudmjdvTmJiIl9++eU1STI3bNjAE088ob0uXPEA+7ZgfHw88fHxTJkyBYD77ruP5cuXA38GV4cOHWLv3r307NmTyMhIZs+eTVJSEufPn+f8+fN06tQJgIcfflgbe9iwYaxZs4aCggI+/fRThzNEhb777juys7NZu3YtDzzwAIcPHyY9PZ2oqGvScjjYsmWLdq9u3bqRmZmprQD169cPNzc3qlWrRkBAAGfOnGHjxo3ExcXRunVrIiMj2bhxI8eOHSM4OJhjx44xceJE1q1bV2Ry0NTUVKpXr17ifMB+1qlOnTpERUUxefJk2rdvf00ZomXLljmsKn755ZdER0eTlJTE2rVrefjhh7HZbIB99SslJaXEe27atIkFCxbw2mv6lYNOAAAgAElEQVSvlTo/ISojVVWxnDtH/pEj2LKzr3rn+hOCmj1d8Kvthau5XJxYEaJY8m/wdRg4cCDPPPMMsbGxZGZmlt6hGMOHD2fYsGEMHjwYRVEICQlhz549NG3aVCvcXOj8+fPFjuPh4UHPnj357rvv+Oqrr4iLi7vmmh9//JFOnToRHh7OggULuOeeexg2bBgjRoy44fm7ublpXxuNRiwWC6qqMnLkSObOnXvN9bt27eLHH3/ko48+4quvvuLTTz91eN/d3Z3cv5zNKIrJZHLYVmzfvr2WHb7wPhaLxWEVbMGCBaxbtw6AO++8k9zcXDIyMggICCA3Nxd39+Lz5OzevZuxY8fyww8/lFqoW4jKSLVYKEhJwXrlF69CNoPrlRQL+gonKwaFKv5mzB5SaFlUDLJydR1Gjx7Nyy+/rJ2RKtSzZ0+Hs1DnzpVcC6tBgwYYjUZmzZrF8OHDAXsx5/T0dC24KigoYN++ffj4+ODj48OWLVsA+1NsVxs7diyTJk2idevWDitmhVq0aMHy5cvJy8ujY8eODBo0iDlz5jis7hSlY8eO2r1iY2OpVq1aiSVpunfvzjfffENaWhpgP7N14sQJMjIysNlsDBkyhNmzZ2uH1q/WpEkTjhw5UuJ8ALKzs7l8+TIAP/30EyaTibCwMO39v56FA6hbty4bN24E7Nn+c3NztVWyhISEYp+8PHnyJIMHD2bRokUOAZwQws566ZK9fM1fAqt8V28ue9TQHVi5upvwq+UpgZWoUGTl6jrUqVOnyHQKM2bM4IknnqBZs2YYjUZefvll7Wm1rl27altXzZs319INDB8+nKlTp2pnr1xdXfnmm2+YNGkSFy5cwGKxMHnyZJo2bcpnn33G6NGjURSFXr16Ody7VatWeHt7F3mWCeznsg4fPkxERAReXl40b96c+fPnM3ToUDZu3IiHx5/nICwWi7YqVXhwvXnz5nh4ePD555+X+LMJCwtj9uzZ9OrVC5vNhouLCx988AHu7u6MGjVK24oramWrb9++DtudK1euZOLEiaSnp9OvXz8iIyP58ccfSUtLo3fv3hgMBgIDA1m0aJHDOF999ZWWaqHQm2++ybhx44iJiUFRFBYuXKid49i0aRP9+vUr8vt59dVXyczMZMKECYB91azwzNr9999PbGwsGRkZ1KlTh1deeYUxY8aU+PMRoqKwJwQ9jeWsY/kam2Ii1+yP1eRWTE9HiqLg5euG2ctFzlaJCkdqC5ZzKSkpdOnShYMHD2Iw3NxC5DvvvENycjKvv/76LZqdfoMGDeL1118nJCSkTO6Xl5dH586d2bJlCyaTiZkzZ+Ll5aWlYrhRt2ocIW5Htpwc8k8loebnObQXmDzINfuBzicBTa5GvKuZMbmUfBZLPv/F7a642oKyLViOffHFF7Rt25Y5c+bcdGA1ZswYli5d6nAwvyzNmzdPSz1RFk6ePMm8efO09A9eXl58/PHHWhLRGzF16lQWL14sua5EhaOqKgXp6VcSgv4ZWKkYyDH7k+teTXdg5VnVDd+aHqUGVkKUZ7JyJYQQoli2/HwKkpKxZV92aLca3cgx+6Ma9J0uMZoMeFdzx8VNf1Aln//idlfcypWcuRJCCFEk64ULFKSkoFqtDu15rlXJd6uqexx3L1c8fd0wSLFlUUlIcCWEEMKBarVSkJqK9S+pYGyKiVx3f6xGfYfWDVdSLLjJk4CikpHgSgghhMaWnU1+UpJDsWWAApMnuWZf3Wer3NxNVPE3YzDK0V5R+UhwJYQQQqsLaElLB/48i6sqBnLd/HSXr5EUC0JIcCWEEJWeraCAglNJRRxaN185tK7vELreFAtCVHTlIriquSm+zO51umuk9nVmZibdu3e3t58+jdFopHr16iQmJlK7dm32799/y+/v5eVFVlYWKSkpTJo0iW+++eaW36M0qampjBs3jjVr1pCZmcnQoUPZvn070dHRvP/++9p1y5cvZ86cOVitVvr376/V35syZQqbNm0C7FnV09LStDI+RqNRy3Bft25dVq9eDdgLY8+aNUvLc1V43dq1a/Hx8WHYsGEcPXoUo9HIgAEDmDdvHgBvvfUW//73vzGZTFSvXp1PP/2UevXqcfToUYYMGcKRI0fIysoqmx+cEOWQ9eJFCpKT/3JoXSHPzYd81yq6x/HwdsXTx01Wq4RA8lyVyN/fXyu6/NhjjzFlyhTt9c3mlSpN7dq1/5bACuwBy7hx4wAwm83MmjWL+fPnO1yTmZnJ1KlT2bhxI/v27eP06dNamZmYmBjt5zRx4kQtWz3Y6wgWvlcYWAE8/vjjDslLC6+rXbs2AM888wwHDx5k586dbN26lR9++AGwl/fZsWMHu3fvZujQoTz77LOAvcRQfHzZBeVClDeqzUZBSgr5J086BFY2gwuXPWrqDqwMRgM+AR54+ZolsBLiCgmubpDVamXcuHE0bdqUXr16kZOTA0B8fDzt2rWjefPmDBo0SKsz2KVLF6ZMmUJUVBRNmjRh+/btDB48mJCQEGbMmHHN+ImJiVrdu4ULFzJ48GD69OlDSEiIFkBYrVaio6Np1qwZ4eHhWlHjkubw3HPP0aZNG0JDQ9m8eXOR39uKFSvo06cPAJ6ennTo0AGz2exwzbFjxwgJCdHq9PXo0YMVK1ZcM1ZR9f6K0rFjRzZs2IDFYrnmPQ8PD7p27QrYywS1bNmSpKQkwF5eqLCET7t27bR2IUTxbLm55B87dk0Jm3yXKlz2qKm7LqCbhwm/Wh64upeLTRAhyowEVzfo8OHDPPHEE1px5cLA4pFHHuG1115j9+7dhIeH88orr2h9XF1d2bFjB4899hj33HMPH3zwAXv37mXhwoVkZmaWeL/4+HiWL1/Onj17WL58OadOnSI+Pp7k5GT27t3Lnj17tPqCJc3BYrGwbds23n77bYf2QsePH8fX11erMVichg0bcujQIRITE7FYLKxatYpTp045XHPixAmOHz9Ot27dtLbc3FyioqJo164dq1at0toNBgMNGzZk165dJd73/Pnz/Oc//9G2a6+2YMEC+vbtW2J/ISozVVWxnD1L3tFj2HJz/2xXjGS7B5Bn9gUdq0+KYk+x4F3NXZ4GFKII8l/FDapfvz6RkfbzWa1atSIxMZELFy5w/vx5OnfuDMDIkSP59ddftT4DBw4EIDw8nKZNm1KrVi3c3NwIDg6+JjD5q+7du1O1alXMZjNhYWGcOHGC4OBgjh07xsSJE1m3bh3e3t6lzqFwi65wzn+VmpqqrUaVxNfXl3/+858MHz6cjh07EhQUpBWoLrRs2TKGDh3q0H7ixAl27NjB0qVLmTx5MkePHtXeCwgIICUlpdh7WiwW7r//fiZNmkRwcLDDe4sXL2bHjh1MnTq11LkLURmpVisFSUkUpKSAatPaLSZ3LnvWwmoyl9D7Ty5uRnxreeDu5SrbgEIUQ4KrG3T1yo7RaCxyO6u4PgaDwaG/wWAotX9R9/P19WXXrl106dKFjz76iLFjx+qeQ3Fzdnd3J/eq32hLMmDAAH7//Xd+++03GjVqRGhoqMP7y5Ytu2ZLMDAwEIDg4GC6dOnCzp07tfdyc3Nxd3cv9n6PPvooISEhTJ482aF9w4YNzJkzh9WrV5e64iZEZWTLySHv6FGsFy5c1aqQ6+ZLjnt11OuoC+hTQ+oCClEaCa5uoapVq+Lr66udZVq0aJG2guQMGRkZ2Gw2hgwZwuzZs/njjz9ueg6hoaFFrmgVJS0tDYBz587x4YcfOgR3Bw8e5Ny5c9x5551a27lz58jLy9PmvnXrVsLCwrT3ExIStHNmfzVjxgwuXLjA22+/7dC+c+dOxo8fz+rVqwkICNA1byEqC1VVsWRmXim4/GdS0MJD6wU6D60bTQZ8a3rI04BC6FQuTiFenR7hdvf555/z2GOPkZ2dTXBwMJ999pnT7pWcnMyoUaOw2exL/HPnzr3pOXh6etKgQQOOHDlCw4YNAQgKCuLixYvk5+ezatUq1q9fT1hYGE899ZR2Ruqll15yWLlatmwZI0aMcPggPnDgAOPHj8dgMGCz2Zg2bZoWXJ05cwZ3d3dq1qx5zZySkpKYM2cOjRs3pmXLlgA8+eSTjB07lqlTp5KVlcWwYcMAx/QOQlRmqsVCQUoK1osXHdrzXaqQ5+aj62wVgNnLBS9fs9QFFOI6KKqqln5VGYmKilJ37Njh0CZV0cveypUriYuLY/bs2WV2z5iYGLy9vRkzZgzwZ76vm3WrxhGiPLFlZ5N/6hRqQYHWpipGcsz+us9WKQYF77+5LqB8/ovbnaIocaqqRv21XbYFxTUGDRpEUFBQmd7Tx8eHkSNHaq+9vb2JjIws8YB7SY4ePUpkZCQ1atS4VVMU4ranqiqWjAzyjh93CKwsRjOXPWvqDqxczSb8anlKwWUhbpCsXAkhRAVgfxowGeulq7cBFfLcqpLv6q17HC8fN9y9b48nAeXzX9zuilu5KhdnroQQQhTPlpND/slTqAVXH1o3kWOuhs3oqmsMo8mAdzV3XNzkSUAhbpYEV0IIUU6pqor13DkKUlPhql2IApMnuWY/3YfW3b1c8JRD60LcMhJcCSFEOaRarRSkpmK9UhQdQMVArtkXi4unrjFuh0PrQlREElwJIUQ5Y8vNtT8NeCVvHIDV6EqOuRqqQd/HuoubEe9q7hhN8lyTELdauQiugqZ9X2b3SpzX75q206dPM3nyZLZv346Pjw81atTg7bffxtXVlf79+7N371794ycm6uqTmprKuHHjWLNmDZmZmQwdOpTt27cTHR3N+++/r123fPly5syZg9VqpX///rz22mvae1999RUzZ85EURQiIiJYunQpmzZtYsqUKdo1Bw8eZNmyZdx7772MGDGCWbNmERISAtizuIeHh7N27Vp8fHwYNmwYR48exWg0MmDAAObNm+cw5xUrVmjzjIqKYvPmzVpeq+v5GQkhimc5f95ewsb2ZwmbfFdve+4qnTx93PC4TQ6tC1ERya8spVBVlUGDBtGlSxeOHj1KXFwcc+fO5cyZM9c9lp4SOYXeeustxo0bB4DZbGbWrFnMnz/f4ZrMzEymTp3Kxo0b2bdvH6dPn2bjxo2AvbD03Llz2bp1K/v27dMym3ft2pX4+Hji4+P5+eef8fDwoFevXgA8/vjjvP7669r47u7uxMfHU7t2bQCeeeYZDh48yM6dO9m6dSs//PCDdu2lS5d45513aNu2rdbWsWNH1q5dez0/IiFEMVSbjYLUVAqSkrTAyl5wuYbuwMpgvJJpvapkWhfCmSS4KsWmTZtwcXHhscce09oiIiLo2LGjw3WJiYl07NiRli1b0rJlS/773/8CEBsbS8eOHRk4cKBDqReAY8eO0aJFC7Zv337NfVesWEGfPn0Ae9b0Dh06YDabr+kfEhKiFVru0aMHK1asAOCTTz7hiSeewNfXF6DI0jDffPMNffv2xcPDA7AHQxs2bCgyCPTw8KBr164AuLq60rJlS5KSkrT3X3zxRZ577rlr5iiEuHlqQQH5iYlYMjO1NovJ40rBZX31NN08XPCr5YGLW7nYsBCiXJPgqhR79+6lVatWpV4XEBDATz/9xB9//MHy5cuZNGmS9t4ff/zBO++8Q0JCgtZ26NAhhgwZwsKFC2ndurXDWMePH8fX17fUIsQNGzbk0KFDJCYmYrFYWLVqFadOnQLsdfoSEhK46667aNeuHevWrbum/18LKxsMBho2bKiVtCnO+fPn+c9//kP37t217+/UqVP063ftlqoQ4uZYL2eTd/QotuzsKy0KuW5+5LhX01VwWVEUqvib8a5mxmCUj3whyoL8CnOLFBQU8OSTTxIfH4/RaHQIpNq0aUP9+vW11+np6dxzzz18++2316xmgf28VeFqVEl8fX355z//yfDhwzEYDLRv356jR48C9i3Iw4cPExsbS1JSEp06dWLPnj34+Pho99izZw+9e/d2GDMgIICUlJRiA0qLxcL999/PpEmTCA4Oxmaz8Y9//IOFCxeWOl8hhH6qqmI9e5aC06e1NAs2gws57tWwGfQ93WdyNeJdzYzJRXJXCVGW5NeYUjRt2pS4uLhSr4uJiaFGjRrs2rWLHTt2kH9VBXpPT8fHoqtWrUrdunXZsmVLkWO5u7uTm5ura34DBgzg999/57fffqNRo0Za8eQ6deowcOBAXFxcqF+/PqGhoRw+fFjr99VXXzFo0CBcXBw/pHNzc3F3dy/2fo8++ighISFMnjwZsJ+12rt3L126dCEoKIj//e9/DBw4kL9m2hdC6KfabBQkJzvkryoweXLZo6buwMq9iiu+NTwksBLibyDBVSm6detGXl4eH3/8sda2e/duNm/e7HDdhQsXqFWrFgaDgUWLFmG1Wosd09XVlZUrV/LFF1+wdOnSa94PDQ0lMTFR1/zS0tIAOHfuHB9++CFjx44F4N577yU2NhaAjIwMEhISCA4O1vp9+eWXDluChRISEmjWrFmR95oxYwYXLlzQDseDPVDMyMggMTGRxMRE2rVrx+rVq4mKuqYagBBCB1t+PvnHjl2Vv8q+DZjr7q8rKajBqFA1wIMqfmYUSQoqxN+iXGwLFpUeoawoisLKlSuZPHkyr732GmazmaCgIIcAA2DChAkMGTKEL774gj59+lyzWvVXnp6erFmzhp49e+Ll5cXAgQMd3mvQoAFHjhyhYcOGAAQFBXHx4kXy8/NZtWoV69evJywsjKeeeko7I/XSSy9pK1e9e/fWrjEajbzxxhv4+/sD9sP3p06donPnzg5zOnPmDO7u7tSsWfOa+SYlJTFnzhwaN25My5YtAXjyySe1YE4IcfOsl7IoSDqFeuWXM5tism8D6ixh4+puooq/GaOcrRLibyWFm29TK1euJC4ujtmzZ5fZPWNiYvD29mbMmDEAeHl5kZWVdVNj6s3rJURlpqoqlowMLFeleLGY3Mk1++s6tI4CXj5m3Ku4VKgUC5X181+UH8UVbpZfb25TgwYNIigoqEzv6ePjw8iRI7XX3t7eREZGkpKSckPjbd68mQEDBlCtWrVbNUUhKhzVaqXgVJJDYJXn6kOOe3VdgZXRxYBvTU9JCirEbaRcrFw1btxYPjSEEBWOLS+PgpMnsV0pY6MqRnLM/lhN+vLFmT1d8PKrmAWXVVXl4MGDsnIlbmvFrVzd9meuzGYzmZmZ+Pv7S4AlhKgwrJcuUXAqCdVmP19lNZrJcfdHVXQ83adAFV8zZq+KtQ1YSFVVMjMzJSmxKLdu++CqTp06JCUlkZ6e/ndPRQghbp6qYs3KwnbpktZkMZqxmAqAS8X3u0IxKrh7uZB5uWKf6jCbzdSpU+fvnoYQN+S2D64K8zQJIUR5Z826TMq058jasBEjkO/ixb4m0ZzzawLkldo/qHk1uo9sgtlTX64rIcTf47YProQQoiLIT0zk1JNPkn/EXkXhXNWG7AsbRb6OosuKAu3ubUCLXnUr5DagEBWNBFdCCOFkWb/+SvLTz2C7dAkVhRN1e3Cs/kDQ8TSgh7crvcY2JTDUtwxmKoS4FSS4EkIIJ1FVlcxP/k16TAyoKvkunhxoPJJM/6a6+gc28qXXmKZ4eOtLIiqEuD1IcCWEEE5gy84mZfp0Lv2wDoDz3sHsazqaPDcdK1AKRN0dROt+9StkmgUhKjoJroQQ4hbLT0oi6YknyTt0CBWFk3d051jwQF1pFtyruNBzVFPuCPMrg5kKIZxBgishhLiFLv/3vyRP+QfWCxeubAM+QqZ/0cXQ/6pWw6r0GtMML183J89SCOFMElwJIcQtoKoqZz/9jLQ33wSbzb4NGDaaPLO+g+gte9ej7cD6GKToshDlngRXQghxk2zZ2aTOmMHFtT9c2QbsoXsb0M3TRI/oMILCpQanEBWFU4MrRVESsacctgKWourvCCFEeZZ/6hRJE54g7/Dh694GrBnsTa+xzajiJ2VehKhIymLlqquqqhllcB8hhChTWZu3kPyPKdguZV1XUlCAFj3r0vbeYIyyDShEhSPbgkIIcZ1UVSXz3/b8VaoNEuv14XhQP11JQd08TfQYGUZQc9kGFKKicnZwpQLrFUVRgX+pqvrxXy9QFOVR4FGAunXrOnk6Qghxc6xZl0l9YRqX1m8gz9Wb/U1Gcs63sa6+sg0oROXg7OCqg6qqyYqiBAA/KYpyUFXVX6++4ErA9TFAVFSU6uT5CCHEDcs7epSkCY+RfyKJs76N2N8kmnxXb119ZRtQiMrDqcGVqqrJV/5MUxRlJdAG+LXkXkIIcfu5+MMPpEx7Dmu+leP1+3Oibm/d24DdR4ZRX7YBhag0nBZcKYriCRhUVb105etewKvOup8QQjiDWlBA2mv/x9nFy8gx+7MvMpqLVYN19a3VoCo9xzSVbUAhKhlnrlzVAFYqilJ4n6Wqqq5z4v2EEOKWKkhLI/mJR8nZc4jTAVEcCh2B1eReekcFWvWuR5sBkhRUiMrIacGVqqrHgAhnjS+EEM6UvW0bSU8+Rt5lGwmNH+F0zba6+rl7udBjdBh1w/ydPEMhxO1KUjEIIcRVVFXl7EfvkfbuP7noVZd9UaPJca+uq29gIx96jm6KZ1WpDShEZSbBlRBCXGE9f56USeO4tG0fJ+/oybH6A1ANpZewURRo3b8+rfoGYTAoZTBTIcTtTIIrIYQAcv7YTvIT47mU7cb+iEmc9w3V1c/L140eo8IIDNVXoFkIUfFJcCWEqNRUVeXch69z5oOFnKnWikNRI7C4eOjqG9yiOl0faozZ08XJsxRClCcSXAkhKi3rhQukTniQs7tSSGg0kjM12ujqZ3Ix0OG+EMI61ObKE9FCCKGR4EoIUSnlbPuF5EkTSVPrsT/qBfLMfrr6+dfxoteYpvjV8nTyDIUQ5ZUEV0KISkVVVc7Nf5bTC9dytN4ATt7RQ1emdYDm3epw56AGmFxKP+QuhKi8JLgSQlQa1tREUiY8wJkTbuyLnEpWFX3F4t29XOg2sglB4VLCRghROgmuhBCVQvaqj0ia9Q6JPl04GnUvNoO+Q+hB4f50fbgJHt6uTp6hEKKikOBKCFGhqdnnyXz+IU7FZnCg8UTO+TbW1c/kYuCuYSE07SiH1oUQ10eCKyFEhVUQt4aUZ5/lWEFLEqIe051ioXrdKvQcHYZvTTm0LoS4fhJcCSEqnoJcsj54ghOL4thfN5q0GlG6uikKtOxTj9b962OUgstCiBskwZUQokKxndxJ+rOjOJIYxIHmL5Lnpi9zehV/Mz1GhVG7oY+TZyiEqOgkuBJCVAw2G3nfziFp/iIOVe3P8Yi7dadYaHxnTTreF4qru3wkCiFunnySCCHKPfV8EudffoCk2MvsC51Ipn9TXf3Mnia6PtSE4BbVnTxDIURlUmpwpShKAHAXUBvIAfYCO1RVtTl5bkIIUSrLb4tJfekVUs4Hs6fFJN2Z1uuF+9P1ocZ4VnVz8gyFEJVNscGVoihdgWmAH7ATSAPMwL1AA0VRvgHeVFX1YllMVAghHOReJOvdsSQvjeeUbxcSWgxF1ZG7yuSi0OG+UKkLKIRwmpJWru4GxqmqevKvbyiKYgL6Az2BFU6amxBCFMmWEEv6jAmk7zVxKHQUp2u21dWvRv0q9BjVFJ8AfSkZhBDiRhQbXKmqOrWE9yzAKqfMSAghimPJI3fRM6R89AOZBXXZ13IUl70CdXVt3S+IqLuDMEiKBSGEk+k5c/UU8BlwCfg30AKYpqrqeifPTQghNGrKbs6+FM3p3/I5XncQJ+/oiWoo/Zkcs4eJnmOaUrepfxnMUggh9D0tOFpV1XcURekN+AIPA4sACa6EEM5ns1KwZh4pb35KUl44h1qNIMcjQFfXgCBv+jzajCp+ZidPUggh/qQnuCo88Xk3sEhV1X2KnAIVQpQB9dwJLs55mJMbs0ioN4bTNdvp7tuscyAdhoZgdJFtQCFE2dITXMUpirIeqA88ryhKFUDSMAghnMr6389JfXUWCbkdOdJyEAUuXrr6mVwNdHmwMY3a1nTyDIUQomh6gqsxQCRwTFXVbEVR/IFRzp2WEKLSyr1I1ttjOLoymX1BT3MuqJHurj41POjzaDP8A/UFYkII4QylBleqqtoURTkDhF1JwSCEEE5hO7yV08+NZ8/FzhxrPgab0VV33ybta9FhWIiUsBFC/O30PC34GjAc2A9YrzSrwK9OnJcQojKxWcn+fBoJC7axp+4ULgbU193Vp4YHXR5sRGCovgLNQgjhbHp+xbsXaKSqap6zJyOEqHxs6cdJe+Yh/jjdhsSwF3RlWQcwGBVa9Q2iVe96cmhdCHFb0RNcHQNcAAmuhBC3jqqSu/YjDrz5Lbtrjyerfh3dXWuH+NDlwUb41vR04gSFEOLG6AmusoF4RVE2clWAparqJKfNSghRoakZxzkzYxw7TrbiZMizqIpRVz83s4H2w0Jp0r6W1AUUQty29ARXq6/8I4QQN8dqIffbuez/1xZ21RpFdt1aurs2bFWdjsMb4eGt/5C7EEL8HfQ8Lfi5oiiuQOiVpkOqqhY4d1pCiIpGPbWDMzOfZPvprpxsMBUUfeekPDwMdBnZlPoR1Z08QyGEuDX0PC3YBfgcSMSerf0ORVFGqqoqTwsKIUqXd4m8L59n3+IEdtV+iuw7auju2rhdDTrcF4qbh75D7kIIcTvQsy34JtBLVdVDAIqihAJfAq2cOTEhRPmnHviBtHnT+D2zP6caPKt7tcrLU6XbmBbcEebn5BkKIcStpye4cikMrABUVU1QFEV+jRRCFO9yBnlfTGLvt2fZVet5curoK7QMKuF31aDdsMa4miUZqBCifNLz6bVDUZR/A4uvvH4Q2OG8KQkhyi1VRY3/ijPzX2HbhcGcCh6te7XK29NK98dbU7uhj5MnKYQQzqUnuHoceAIoTL2wGfjQaTMSQpRPF5LJXfA4+9bmsyvwZXLq6D2AbiOic23aDWmEyVVfSpXxLOoAACAASURBVAYhhLid6XlaMA9468o/QgjhyGZD3fYpp2PeZNvloSQ16Kx7tapqFZUej7emZnBVJ09SCCHKTrHBlaIoX6mqep+iKHuw1xJ0oKpqc6fOTAhx+8s4Qs4nj7HvJxO775hJjq/+1arILrVpO6QRJhdZrRJCVCwlrVw9deXP/mUxESFEOWLJw/bzG6R+9AU78oeTFHIdq1XeKj0fb0ON+t5OnqQQQvw9ig2uVFVNvfLnibKbjhDitnd8M5f/NYld2+uz/47/I8+sL12Cgo3IrrVpO7ixFFoWQlRoJW0LXqKI7UDsiURVVVXl104hKpPLmVj/8zwnlv5GnGkkaSEtdXf1qQo9J7QhoJ58bAghKr6SVq6qlOVEhBC3KVWF+KVc/PfL7DjSmcN3zMVi8tDVVcFGZPdA2t7bSFarhBCVRkkrVyWu9auqevbWT0cIcVtJT8Dy9VMcXnueuCrPcaF+A91dfXwUej4uq1VCiMqnpAPtcdi3BZUi3lOBYKfMSAjx9yvIRd38JmeXfMLvZ4aQWLs3qkFfxnQFGy161KHNPaGyWiWEqJRK2hasX5YTEULcJo79QsGyyez5by3i/eZdR+ka8PUz0mN8lKxWCSEqtZK2BRurqnpQUZQiT62qqvqH86YlhChzlzNQf3iB09/9wn8vR3O6TlvdXY2KjdYDgonsHYTRKKtVQojKraR1/n8AjwJvFvGeCnRzyoyEEGXLZoP4xeR+PZPtezuyP2A+Fk9P3d0D67rRdVxLqlZ3d+IkhRCi/ChpW/DRK392LbvpCCHK1Jn9qP+ZwrGNZ/mNaVwIbKi7q5vJSscHmxLarhaKUtTRTCGEqJxKPKGqKEo94LKqqhmKorQDOgBHVFVdVSazE0I4R/5l+OV1sr7/lC0n7uNYdf0H1gFCw73oGN0Cs6eLEycphBDlU0lnrl4CRgKqoijLgB5ALNBPUZQuqqpOLpspCiFuqUPrsP3nGfbsqMcOtzfJrVFNd9cq7ha6jW9Fncb+TpygEEKUbyX9qjoCaAJ4ACeBmqqqZiuKYgLiy2JyQohb6PwpWDeNtM07+DVzHGd89GdYN6hWWnStSeshTSW9ghBClKKk4CpXVdV8IF9RlKOqqmYDqKpqURQlv2ymJ4S4aVYL/P5PCn58nd8S+rLfKwarj1l39xr+Vro92R6/WvoPuQshRGVWUnDloyjKYOxJRL2vfM2V11WdPjMhxM1LjoPVT3F8l8qv2XPIqlpHd1dXJZ+7hjakSbcGcmBdCCGuQ0nB1S/AgCtf/3rV14WvhRC3q9yL8PNssn9dQuyp0Ryv0tW+wa9Tw/oKnZ7ohruXq/PmKIQQFVRJqRhGleVEhBC3yIE1qN9PZW9CQ/5neZ/8KvoXmquYsuk6riV3RNR24gSFEKJiK+lpwYeApaqq2op5vwFQS1XVLc6anBDiOlxIhrVTORe/jY2pEzjjEQk6F54MtgIiW3vSZlQXjCY5sC6EEDejpG1Bf2Cnoihx2Is4pwNmoOH/t3fn8XmVdd7HP7+mCekempalLYWyCJZCWQoIZS2CbFIUUBhZxo3Rh11wYUQd8GEGdxjUmQcFxRUVURAQZCu7QFtKaYuFrnTf9zZNk1zPH7mZCUvDSXpOkyaf9+uVV3LOfZ9zfl72Tr5c5zrXBRwDLAW+UniFkprXUA8v/pSGR77Ji7OO5yX+k/ru2Qes79x9JaOuGkXVwKoCi5SkzqO524I3R8QPaVzmZiSwP7ABeBU4P6X0xtYpUdJmLf4H3HsJi6Yu5ZEl/8bKyt0zH1pZt4aRHx7IPqNdyUqS8tTslMwppXrg4dJXq0REGTAWmJdSOq2155HURF0tPP0DNj1xM8/OOYvJZR8mVZZlOjQa6nnfDis4+ssfpqKX6wFKUt6yr3fRepfT2NvVeytcS+r45o6Dey9hzvTEYyu+w9qKnTMf2mfTIkZ9aj8GjDyhwAIlqXMrNFxFxCDgVOAG4AtFXkvq8GrXwWM3UPvsz3hy3vlM7XoiVGQbfF5WX8PwIWs59OqzKKtwPUBJKlLRPVc3AV8Cem3uDRFxEXARwODBgwsuR9pGzRgD917GjNnVjFl9MxvKs68HuOOm2Rx36ZFUH7BXcfVJkv7He4ariNgOOBPYren7U0rXv8dxpwGLU0rjIuLYzb0vpXQrcCvAiBEjUqaqpc6iZhX87Vo2vHg3j8//LDPLj4aMHU8Vtas4dP8G9rv0ArqUZRuPJUnacll6ru4BVtE4HcPGFpx7JHB6RJxC4xQOvSPiVyml81peptQJTX0Q7ruS1+YM5sm1t7CxPPtUCbvWTeXYfz2FnnvuWmCBkqR3kyVcDUopndTSE6eUrgGuASj1XF1tsJIyWL8c/vpl1k/4K4/N/xyzy4/IfAO/e80Sjji8nPdd9DnXA5SkNpLlV/azEbFfSumVwquROrvJf4YHruYf897HU2t/SG15todsI9WzR5rK0dd/hG6DBxZcpCSpOVnC1ZHAP0fETBpvCwaQUkr7Z71ISmkMMKY1BUqdwppF8MBVrJv0JI/O/zxzyg/L3FvVc/18jhzVi90vvNjeKklqB7L8+j658CqkzioleOUPpAe+xD8W7MdT625hU/lmH659i2jYxN5dpnLkjR9nuwE7FlyoJCmr9wxXKaXZETEcOKq066mU0svFliV1AqsXwH1Xsm7yczyy8P8wt/yQzL1VfdbO5uhT+7PLOZfaWyVJ7UyWqRguBz4L3F3a9auIuDWldEuhlUkdVUow4TekB69hyoIDeGb9LWwq75np0C71tQwtn8rh3zuXih13KLhQSVJrZPnv5E8Dh6WU1gFExLeA5wDDldRSq+bCX65g3asv8vCCS5hXMSJzb1XV2lkcM3pnBp51mb1VktSOZfm1HkB9k+360j5JWaUE439BevCrTFl4MM9s+CGbKnpkOrRL/Ub2rXyNw286j/J+1QUXKknaUlnC1c+A5yPiT6XtM4DbiitJ6mBWzYN7L2XtP8bz8ILLmV9xcObequ3XzuCYjw5m4EcvL7ZGSVJusgxo/35EjKFxSgaAT6aUXiq0KqkjeHNs1V+vYcr84TxTc0vm3qqyuhqG9ZjGYTecR3l134ILlSTlabPhKiJ6p5RWR0RfYFbp683X+qaUlhdfnrSNWr0A7ruCdZOf4ZF5FzO3Mvu8VX3XTufYj+3OzqdfVmyNkqRCNPfr/jfAaTSuKdh0QeUobe9eYF3Stqk0bxUPfJGpc/bhyZpbqK3sk+nQsroN7NdrJofdeB5dq7KvIyhJal82G65SSqeVvg/ZeuVI27C1i+G+K9kw8XEenfsvzO5+FJRnO7R67XSO/ae92OmUS4qtUZJUuCzzXD2aUjr+vfZJnVZKMPH38OCXmTZrCE/U/Cc13bONkyqr28D+VbM59Nvn0bV3tnUEJUntW3NjriqB7kC/iNie/51+oTfgyrASND4JeN8VbJj8FGPe+DQzeh4P22U7tHrddI47//3seOL/KbZGSdJW1VzP1b8AVwADaBx39Wa4Wg38sOC6pPYtJRj3c3j460ydtTdP195CTc9sc1CV1W9k/75vcOh3PkHXXtlmZpckbTuaG3N1M3BzRFzqUjdSE8tnwl8uY/2U8Tw69yLe6HVU5t6q7Te8wajz92GnD7oeuiR1VFnmubolIoYBQ4HKJvt/UWRhUrvTUA8v/AQevY5JMw/iuYYfUtsr25OAXRo2MazfQo746sco69G94EIlSW0py4D2bwDH0hiuHgBOBp4GDFfqPJZMhXsuYfXU13hs/mXM63VY5kN71y7kg+fvzc7HfajAAiVJ7UWWaQ3PAoYDL6WUPhkROwK/KrYsqZ2o3wRP30TDmG8zYdYxjO1yC5syjpOKhnqG7rCUkV/9KOXdKt/7AElSh5AlXG1IKTVERF1E9AYWA7sUXJfU9ua/BPdcwpLXV/DYkm+wtMfQzIf22rSEUefvw6BjTyiwQElSe5QlXI2NiCrgJzQ+NbgWeK7QqqS2tGkDjPkP6p76L56dfSaTK86goUdFpkOjoY5hg1ZxxJfOoGtlxlHukqQOJcuA9jcn4fnviHgQ6J1SmlhsWVIbmfU03Hsps6dVMmbV91jbbVDmQ6vqFnP8RQey06F7F1igJKm9a24S0YOaey2lNL6YkqQ2sH45PPw1NrxwN2PmfIoZ3Y6Dbl0yHdqlvpbhe27gsKvOpqxrWcGFSpLau+Z6rr7XzGsJGJVzLdLWlxK8fCfpoa8yZda+PLfxR2zsnn3R5OqGRZxw2Qeo3s8lOCVJjZqbRPS4rVmItNUtnQb3X8mKKa/x6MLLWNRtf8g2tIqudRs4eH846OKP06UsWw+XJKlzyDLP1QXvtt9JRLXNqtsIT/+Auidu4vm5pzMxLqahW8ZUBQwsm8eoL3+Q3kN2LrBISdK2KsvTgoc0+bkSOB4Yj5OIals080m47wu8MaOCMSu/w5rtsq9BXlm7gpHHb88+nzi/wAIlSdu6LE8LXtp0uzQtw52FVSQVYfUC+Nu1bJjwEGPmf4oZFcdmXg8wUj179pjP0TeMprI6+3gsSVLnlKXn6u3WAY7e1bahfhO8cCvpsRt5ecERvFDzYzZVZJthHaD3xgUc87HdGXzyhQUWKUnqSLKMufoLjU8HApQB7wd+X2RRUi5mPwv3X82C2bU8vuQbrKjYPfN/TpTV1bD/zks59Jqz6dq9W7F1SpI6lCx/ar7b5Oc6YHZKaW5B9Uhbbu1iePjrbBh/H08tvIDXu4yCiuxP9O20cTrHXjKS6oNPKbBISVJHlWXM1RMRsRNwKI09WNMLr0pqjYZ6ePE20qM38MrCw/j7hh+zqSz7LcDKjcs57IDEvpd8iihzMlBJUutkuS34GeDrwGNAALdExPUppduLLk7KbO44uP9KFs5cy+NLrmV5+R6NN7EziIZ69uzyOkddN5pug7M/PShJ0rvJclvwi8CBKaVlABFRDTwLGK7U9tYvh0evp+bFu3hq0QW8xigoz34LsGrdbI768AB2OfvzRESBhUqSOoss4WoZsKbJ9prSPqntpAQTfkPD377OK/NG8HwLbwGW165m+A4LOfhb59K1T58CC5UkdTZZwtU04PmIuIfGMVejgYkR8QWAlNL3C6xPeqdFU+D+L7Bg6lIeX3oNK8p3z3wLkNTArhsmceRlx1E14oxCy5QkdU5ZwtV03jqI/Z7S9175lyM1o2Y1jLmR9c/+mqcWns+0OLZFtwD7rJnF4Ud2Z/eLLnXAuiSpMFmeFrwOICJ6lrbXFl2U9BYpwSt/oP6hrzNh9sGM2/hDNpX1yHx4ee0a9us5nYO/+wkqdt6xwEIlScr2tOAw4JdA39L2UuCClNLkgmuTGm8BPnA1syat48kVX2VNxcAW3QIcvPolRn7mA/Q9fnShZUqS9KYstwVvBb6QUnocICKOBX4CHFFgXersSrcAVzz5Z8Ys/CTzKw6GiuyH91kzk8MO7sIeF19Gl+0yLiIoSVIOsoSrHm8GK4CU0piIyH5PRmqJlGDSH9n4wPU8N20UU+ImUkX2JTDLa1czrMd0RnznXCoGDCiwUEmS3l2Wv1ozIuJrNN4aBDgPmFFcSeq0lk2n4b6reOWFcl6suY6N5S2YIiE1sOvaCRxx0Uj6HuNTgJKktpMlXH0KuA64m8apGJ4q7ZPyUbcRnv4BM+/5G0+vvIDV2w2G8uyHV62ZyQdGdmP3z15OlLfgQEmSCrDZcBURlcDngD2BV4CrUkqbtlZh6iRmPMHS39zAk6+fyIJu10ILhkdtt3EF+1XP46Drz6F8hx2Kq1GSpBZorufqDmATjT1VJwPvB67YGkWpE1i7mHV3f51nHunDtMovkrpln3eqS30tezRM4fArTqTX8DMLLFKSpJZrLlwNTSntBxARtwEvbJ2S1KE11FP33E958faxTIzTqevesmcjdlr7KkecvTc7nX6lawFKktql5sLV/9wCTCnV+YdMW6ph9gtM+e6PeHH1h1jf7dwWHdtz/XwOPbiMfT7/WaKiBXMySJK0lTUXroZHxOrSzwF0K20HkFJKvQuvTh1CWreMN759Lc+9vi/Lel8I3bIfW167mv36L+LgG86morpvcUVKkpSTzYarlJKLr2mLpPp6lt72Hzz3cB1z+p4JvbOvA9ilYRN7dJ3J4V86gV77OLWCJGnbkX12RqkF1tx/Jy/87O+8XnUC9dUt6KoCBmyazsgLD2KHoz9UUHWSJBXHcKVcrbr/t7x0x9+Z1v0oNvY7vUXH9tk4nyNOGcCQsz7jYHVJ0jbLcKVcLP/zrxl35yRm9jicTX1btkhyZe1KDj6oK/t/7hy6dPWfpCRp2+ZfMrVeSiz+4y8Ze/dMZvc4jIaqE1p0eFn9RobuspoPXHEaFb1drlKS1DE0N0P7GhqXu3nHS/i0YKeW1q9i5q9+w8Qn1zK/xwGk3oNaeIIGhvRazJFfOJneA7YvpkhJktpIc08L9tqahah9S5s2svS5x5j8wBSmL9mNmvK9oWfLz9OvbBHHfO4odtrvg/kXKUlSO5D5tmBE7ABUvrmdUnqjkIrUfjQ0sPLlZ3n98YlMfb0Pq9LOwIEtWlT5Td3TSkaetSd7ffA4B6tLkjq09wxXEXE68D1gALAY2BV4Fdi32NLUVmrnTWXaX8cwZVJXFtUMAfZp9bm6NaziwGP6sv/HzqCsPPs8V5Ikbauy9Fx9E/gA8EhK6cCIOA44r9iytLWldctY8sT9TH52Ma8vez+b0l5bdL7eDYs5+EOD2PuM0ZSVGaokSZ1HlnC1KaW0LCK6RESXlNLjEXFT4ZWpeHW1bJz0EK89+jJTZu7M0rohQAsHp79Ndf0cRnxkL/Y4+ePe/pMkdUpZwtXKiOgJPAX8OiIWA+ve66CIqASeBLYrXeeulNI3tqRY5WTDClaP+RXjHl/Ga6sPo44jtviUO9e9xiHnHsAux1+YQ4GSJG27soSr0UANcAXwCaAPcH2G4zYCo1JKayOiHHg6Iv6aUvp7q6vVlln5BisfuYNxz9Yzdf1IElu2fGSPtfPYtdd89v/saVQfNCqnIiVJ2ra9Z7hKKa2LiJ2AQ4HlwEMppWUZjkvA2tJmeenr3ebNUtHmT2DFw3cwdkJvXt9w5BaFqsqaZey4eBx7DuvB7td+kopBW3YbUZKkjibL04KfAb4OPEbjBKK3RMT1KaXbMxxbBowD9gR+lFJ6/l3ecxFwEcDgwYNbVr02LyWYMYZlf7uDsVOHMK3mVKB1A8u7blrHjovHstOy8ez6oUPo9++XUT5gQL71SpLUQURjB1Mzb4iYChzxZm9VRFQDz6aU9s58kYgq4E/ApSmlSZt734gRI9LYsWOznlbvJiWY9ijLH/wpL0zfl+k1I1t9qqoVrzFgwTPssPpVqs/6CNWf/QzlO+6YY7GSJG27ImJcSmnE2/dnGXO1DFjTZHtNaV9mKaWVEfE4cBKw2XClLZASvPYQKx+6lRdnDOO1ms/Qmp6q8to17Lzw7wxY8Cw9Yy3b/9O59P3nH9C1X7/8a5YkqQNqbm3BL5R+nAY8HxH30DhmajQw8b1OHBH9aZzGYWVEdANOAL615SXrLVKCqQ+w+uH/ZtyMYby64fOtGlNVtWIqg+Y/Rb+lE+nauyd9P30+fc/7BGVVVQUULUlSx9Vcz9WbawtOL3296Z6M594ZuKM07qoL8PuU0n0tL1HvqqEBXr2XdY/+P8bN2pfJ6y+hoRXr0lQvm8Rus/9Kn9WzKKuupvrqK6n6+DmU9exRQNGSJHV8zS3cfF3T7dJcV6SU1r77Ee84fiJw4BZVp3eqr4NJf2TdY7cyfs7+TF5/GfVs1+LT9Fv6MrvNfpDea96g64Cdqb7sWqrOOpMulZXvfbAkSdqsLE8LDgN+CfQtbS8FLkgpTS64NjVVVwsT72TdYz9l/PwRTF7/ReqpaPFp+i8ez26zH6TXunlU7LkH/a69kd6nnEKUt2I1ZkmS9A5ZBrTfCnwhpfQ4QEQcC/wEcpjWW+9tUw289EvWjvk54xcexpT1/9qqULXD4vHsNvsBeq5bQOXw/el30TX0PO44oovr/kmSlKcs4arHm8EKIKU0JiIckFO0DSth7O2sfeZOxi86iskbvkZDK0JVv6UTGTLrfnqtnUuPkSOpvuhGuh96iOv+SZJUkCzhakZEfI3GW4MA5wEziiupk1s1D/7+Y5b//W+8tOJEXtvwf2mILP83vVXf5VPYfeZ99F4/l94nnUT1p2+mcujQAgqWJElNZfmr/SngOuDu0vZTpX3K06Ip8OwtLBg3gXErRzO7rjRrRQs7mKpWvs7uM//C9rXzqTrrLPpeeCEVgwbmX68kSXpXWdYWXAFcthVq6XxSgllPk565hVmTljFu1ZksSme36lR9Vk1nyKz76RdLqP7n86g65xy6br99zgVLkqT30twkon+hmYWWU0qnF1JRZ1C/CSb/mfpnfszUGVWMX/0RVkXrFkDus3IaQ2Y9wI5VG6m+/EL6nHGG0ylIktSGmuu5+u5Wq6KzqFkF4+6g5tlfMnHe/ryy/lJqulS1+NYfvBmq7mfg+6qo/vfL6XnsMT75J0lSO9DcJKJPbM1COrSVc+D5/2bl3x/gpYUfZGr99dR32a41S/9RtfJ1hsx5kMFH7EX11/6dbvvum3+9kiSp1Zq7LTgaGJRS+lFp+3mgf+nlL6WU7toK9W27UoKZT8ALP2HBhGmMXXoGb5R9B6JLq0JV9bLJ7LrsGXY/5RD63vRflO+0U/41S5KkLdbcbcEvAec02d4OOAToAfwMMFy9m5rV8PJvaXjhdl6b1o+X1pzO8opPZ3su820i1bPDonHsmV5l13NOos/pt9Glh1OMSZLUnjX3J78ipTSnyfbTKaVlwDInEX0Xi6bAiz+hZty9TJh7DFPqr2JDRT9aMe8nXeo3MmDBM+w9cB2DrjqTHiO/5HgqSZK2Ec2Fq7c8x59SuqTJZn8EmzbAlHtg3B0smzKTcUtOZ0bFLdSXVUJZy09XXruGXRY/y9AR27PTv36a7YYMyb9mSZJUqObC1fMR8dmU0k+a7oyIfwFeKLasdm7BRBj/Cxom/J5pb+zJK+tOYWGPA6Bb63qXuq9fxG7rJ7DvKftSffa1lPXqlXPBkiRpa2kuXF0J/Dki/gkYX9p3MI1jr84ourB2p2Y1TLoLxv+CddNe5+UFJ/JalxtZ120n6Nm6U1atfJ33VS1mn88cS88jP+6tP0mSOoDmpmJYDBwREaOAN5/3vz+l9NhWqaw9aKiHGWNg4u9IU/7C3LkDeXn1qczp8WUaemzXunOmBnZcOYlh+1Ww+7WnUzGodZOHSpKk9inL8jePAZ0nUKUEC1+Bib+DV+6iZukKJs87hn+k61jZc0/o3brTltVtYJdNrzH8hCEMOOtzzqIuSVIH1YoJAjqoVfPglT809lItmsKCxbsxceUZzO4+kroerbzvB1TWLGOvvssY/okj6HPwqTkWLEmS2qPOHa5WzIJX/wJT7oW5L7CxpoLJ84/mH/UXsqLX+6BP609dVTOPYcMrGXrhCZT3rcqtZEmS1L51vnC15DV49Z7GQLVwIuvq+/DGsmHMWnkxc7p9gE3dW99LFQ31DOi6kANO2ZNdTz2PiFYsGihJkrZpHT9cvTmG6tV7Ycq9rF60nAW1Q5lXM5J5Gy5idZeBje9r5VgqgMpNq9lz8CYOvOBIeg85IZ+6JUnSNqlDh6s08ylW/OGbzF/ah/m1Q1lQexVrG5rMf7qFMx/0i8UMO2oA+5x9GmXlHbopJUlSRh06ESyv6c+dM76S6zm71tcwZIf1HHjuYfQfNirXc0uSpG1fhw5Xvaq2pyK9Tm0OSyFuzzL2ObQfw875IBXdW7FgoCRJ6hQ6dLha+9gj9F62hKX99m/V8WX1G9mt3zqGf+xgdj7QXipJkvTeOnS46jN6NFW/+lqLw1VVWsb7D+nLsHNHUdHamdglSVKn1KHDVVnPngw6cBDTljf/vu1qlrP9hjcYsHc1e5x5FDsMt5dKkiS1TocOVwBDzjuVJ38wk4ay/+2B6r5uIVWrplG1aho7Dqxk4LkfpteHLqFLhWOpJEnSlunw4ar70H3Ypf5hGuYvos+qaVStms525Q30Oe00tj/3Girf//62LlGSJHUgHT5cARz10d2Zf/WPqdhjD7b/3BX0GX06Zb16tXVZkiSpA+oU4arXiScw+I476H7oIS5JI0mSCtUpwlWXigp6HHZoW5chSZI6gS1cAEaSJElNGa4kSZJyZLiSJEnKkeFKkiQpR4YrSZKkHBmuJEmScmS4kiRJypHhSpIkKUeGK0mSpBwZriRJknJkuJIkScqR4UqSJClHhitJkqQcGa4kSZJyZLiSJEnKkeFKkiQpR4YrSZKkHBmuJEmScmS4kiRJypHhSpIkKUeGK0mSpBwZriRJknJkuJIkScqR4UqSJClHhitJkqQcGa4kSZJyVFi4iohdIuLxiJgSEZMj4vKiriVJktRedC3w3HXAVSml8RHRCxgXEQ+nlKYUeE1JkqQ2VVjPVUppQUppfOnnNcCrwMCiridJktQebJUxVxGxG3Ag8Py7vHZRRIyNiLFLlizZGuVIkiQVpvBwFRE9gT8CV6SUVr/99ZTSrSmlESmlEf379y+6HEmSpEIVGq4iopzGYPXrlNLdRV5LkiSpPSjyacEAbgNeTSl9v6jrSJIktSdF9lyNBM4HRkXEhNLXKQVeT5Ikqc0VNhVDSulpIIo6vyRJUnvkDO2SJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlFgU/WQAACdpJREFUSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkqLFxFxO0RsTgiJhV1DUmSpPamyJ6rnwMnFXh+SZKkdqewcJVSehJYXtT5JUmS2qM2H3MVERdFxNiIGLtkyZK2LkeSJGmLtHm4SindmlIakVIa0b9//7YuR5IkaYu0ebiSJEnqSAxXkiRJOSpyKobfAs8Be0fE3Ij4dFHXkiRJai+6FnXilNK5RZ1bkiSpvfK2oCRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOepa5Mkj4iTgZqAM+GlK6cYir7c5u33l/ra4rCRJagdm3XjqVr1eYT1XEVEG/Ag4GRgKnBsRQ4u6niRJUntQ5G3BQ4FpKaUZKaVa4E5gdIHXkyRJanNFhquBwJwm23NL+94iIi6KiLERMXbJkiUFliNJklS8Nh/QnlK6NaU0IqU0on///m1djiRJ0hYpMlzNA3Zpsj2otE+SJKnDKjJcvQjsFRFDIqICOAe4t8DrSZIktbnCpmJIKdVFxCXAQzROxXB7SmlyUddrztZ+BFOSJHVehc5zlVJ6AHigyGtIkiS1J20+oF2SJKkjMVxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo4MV5IkSTkyXEmSJOXIcCVJkpQjw5UkSVKODFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlKNIKbV1Df8jIpYAswu+TD9gacHX6Ghss5azzVrONmsZ26vlbLOWs82at2tKqf/bd7arcLU1RMTYlNKItq5jW2KbtZxt1nK2WcvYXi1nm7WcbdY63haUJEnKkeFKkiQpR50xXN3a1gVsg2yzlrPNWs42axnbq+Vss5azzVqh0425kiRJKlJn7LmSJEkqjOFKkiQpR50mXEXESRExNSKmRcRX2rqe9ioibo+IxRExqcm+vhHxcES8Xvq+fVvW2J5ExC4R8XhETImIyRFxeWm/bbYZEVEZES9ExMulNruutH9IRDxf+oz+LiIq2rrW9iYiyiLipYi4r7RtmzUjImZFxCsRMSEixpb2+dlsRkRURcRdEfGPiHg1Ig63zVquU4SriCgDfgScDAwFzo2IoW1bVbv1c+Ckt+37CvBoSmkv4NHSthrVAVellIYCHwAuLv3bss02byMwKqU0HDgAOCkiPgB8C/hBSmlPYAXw6Tassb26HHi1ybZt9t6OSykd0GSuJj+bzbsZeDCltA8wnMZ/b7ZZC3WKcAUcCkxLKc1IKdUCdwKj27imdiml9CSw/G27RwN3lH6+AzhjqxbVjqWUFqSUxpd+XkPjL6KB2GablRqtLW2Wl74SMAq4q7TfNnubiBgEnAr8tLQd2Gat4WdzMyKiD3A0cBtASqk2pbQS26zFOku4GgjMabI9t7RP2eyYUlpQ+nkhsGNbFtNeRcRuwIHA89hmzSrd3poALAYeBqYDK1NKdaW3+Bl9p5uALwENpe1qbLP3koC/RcS4iLiotM/P5uYNAZYAPyvdfv5pRPTANmuxzhKulJPUOHeH83e8TUT0BP4IXJFSWt30NdvsnVJK9SmlA4BBNPYs79PGJbVrEXEasDilNK6ta9nGHJlSOojGISEXR8TRTV/0s/kOXYGDgP9KKR0IrONttwBts2w6S7iaB+zSZHtQaZ+yWRQROwOUvi9u43ralYgopzFY/TqldHdpt22WQemWw+PA4UBVRHQtveRn9K1GAqdHxCwahzWMonFsjG3WjJTSvNL3xcCfaAzyfjY3by4wN6X0fGn7LhrDlm3WQp0lXL0I7FV6sqYCOAe4t41r2pbcC1xY+vlC4J42rKVdKY17uQ14NaX0/SYv2WabERH9I6Kq9HM34AQax6o9DpxVeptt1kRK6ZqU0qCU0m40/v56LKX0CWyzzYqIHhHR682fgROBSfjZ3KyU0kJgTkTsXdp1PDAF26zFOs0M7RFxCo1jFsqA21NKN7RxSe1SRPwWOBboBywCvgH8Gfg9MBiYDXwspfT2Qe+dUkQcCTwFvML/joX5VxrHXdlm7yIi9qdxUGwZjf+B9/uU0vURsTuNvTJ9gZeA81JKG9uu0vYpIo4Frk4pnWabbV6pbf5U2uwK/CaldENEVONnc7Mi4gAaH5qoAGYAn6T0OcU2y6zThCtJkqStobPcFpQkSdoqDFeSJEk5MlxJkiTlyHAlSZKUI8OVJElSjgxXkrZJ0ejpiDi5yb6zI+LBtqxLkpyKQdI2KyKGAX+gcU3HrjTO9XRSSml6K87Vtck6fZLUaoYrSdu0iPg2jWug9Sh93xUYBpQD/5ZSuqe0qPYvS+8BuCSl9GxpQs5vAiuAfVJK79u61UvqiAxXkrZppaVNxgO1wH3A5JTSr0pL7LxAY69WAhpSSjURsRfw25TSiFK4uh8YllKa2Tb/CyR1NF3f+y2S1H6llNZFxO+AtcDHgA9HxNWllytpXLJjPvDD0tIe9UDTHqoXDFaS8mS4ktQRNJS+AjgzpTS16YsR8W80rpU5nMYHeWqavLxuK9UoqZPwaUFJHclDwKUREQARcWBpfx9gQUqpATifxkWjJakQhitJHck3aRzIPjEiJpe2AX4MXBgRLwP7YG+VpAI5oF2SJClH9lxJkiTlyHAlSZKUI8OVJElSjgxXkiRJOTJcSZIk5chwJUmSlCPDlSRJUo7+Py9qU48ZFYbpAAAAAElFTkSuQmCC\n", | |
| "text/plain": [ | |
| "<Figure size 720x720 with 1 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [], | |
| "needs_background": "light" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "5obqDe88k8Yn" | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": null, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
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