ARIMA.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "mount_file_id": "1lZeCPPgDptU5TfDqFc1F3sGbWIggEcEj",
      "authorship_tag": "ABX9TyOs36bCkt/c1RWgXTJmt4ST",
      "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/heejjj/Sleeping_Project/blob/main/ARIMA.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://doheon.github.io/%EC%BD%94%EB%93%9C%EA%B5%AC%ED%98%84/time-series/ci-1.arima-post/#modeling-training-evaluate"
      ],
      "metadata": {
        "id": "_llCgb4-JN-I"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 데이터셋 로드"
      ],
      "metadata": {
        "id": "EofN97hL7WLS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "ePJNenjZJhYi"
      },
      "execution_count": 186,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('df.csv').drop(['Unnamed: 0'],axis=1)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "nhLPKaw7IW4g",
        "outputId": "5d3245e7-d0ce-4c89-8616-0db9f9d5d781"
      },
      "execution_count": 185,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   ds  y\n",
              "0      20230221000030  1\n",
              "1      20230221000100  1\n",
              "2      20230221000130  1\n",
              "3      20230221000200  1\n",
              "4      20230221000230  1\n",
              "...               ... ..\n",
              "45403  20230503075100  1\n",
              "45404  20230503075130  1\n",
              "45405  20230503075200  1\n",
              "45406  20230503075230  1\n",
              "45407  20230503075300  0\n",
              "\n",
              "[45408 rows x 2 columns]"
            ],
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              "      <td>20230221000100</td>\n",
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              "      <td>20230503075130</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
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              "      <td>20230503075200</td>\n",
              "      <td>1</td>\n",
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              "      <th>45406</th>\n",
              "      <td>20230503075230</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>45407</th>\n",
              "      <td>20230503075300</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45408 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-df7acab8-6184-4090-88ff-2756272dc935')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-df7acab8-6184-4090-88ff-2756272dc935 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-df7acab8-6184-4090-88ff-2756272dc935');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 185
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ARIMA"
      ],
      "metadata": {
        "id": "72XZCf8r8c2N"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20,5))\n",
        "plt.plot(range(len(df[\"ds\"])), df[\"y\"])\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 395
        },
        "id": "25x6Weuj8dXM",
        "outputId": "bcee4d6b-bb69-4cbb-99d7-9c8974b637dd"
      },
      "execution_count": 155,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "idx = []\n",
        "for i in range(1,49):\n",
        "  idx.append(946*i-1)\n",
        "\n",
        "idx"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EJtAkKN988Ef",
        "outputId": "1e338a4f-8bf5-4537-f122-2c2739286a31"
      },
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[945,\n",
              " 1891,\n",
              " 2837,\n",
              " 3783,\n",
              " 4729,\n",
              " 5675,\n",
              " 6621,\n",
              " 7567,\n",
              " 8513,\n",
              " 9459,\n",
              " 10405,\n",
              " 11351,\n",
              " 12297,\n",
              " 13243,\n",
              " 14189,\n",
              " 15135,\n",
              " 16081,\n",
              " 17027,\n",
              " 17973,\n",
              " 18919,\n",
              " 19865,\n",
              " 20811,\n",
              " 21757,\n",
              " 22703,\n",
              " 23649,\n",
              " 24595,\n",
              " 25541,\n",
              " 26487,\n",
              " 27433,\n",
              " 28379,\n",
              " 29325,\n",
              " 30271,\n",
              " 31217,\n",
              " 32163,\n",
              " 33109,\n",
              " 34055,\n",
              " 35001,\n",
              " 35947,\n",
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              " 42569,\n",
              " 43515,\n",
              " 44461,\n",
              " 45407]"
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          },
          "metadata": {},
          "execution_count": 160
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 훈련 데이터셋 정의\n",
        "df_train = df.iloc[idx]   # 마지막 수면 단계를 예측하는 것이 목표\n",
        "df_train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "tONqmKzR9n2h",
        "outputId": "8f86fe7a-1edb-471c-ad04-6f2740ede484"
      },
      "execution_count": 164,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bc8a0154-fb5d-4281-bfd8-5ef2e0b911af')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "      \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",
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              "\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",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bc8a0154-fb5d-4281-bfd8-5ef2e0b911af 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-bc8a0154-fb5d-4281-bfd8-5ef2e0b911af');\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": 164
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 패턴 쪼개기"
      ],
      "metadata": {
        "id": "jRGVtc-A-wMk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "result = seasonal_decompose(df_train['y'], model=\"additive\", period=24)\n",
        "fig = plt.figure()\n",
        "fig = result.plot()\n",
        "fig.set_size_inches(20,7)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 572
        },
        "id": "WpSS4-pC9rhY",
        "outputId": "da25d540-ad16-481f-c8fe-bdb3705b09a5"
      },
      "execution_count": 167,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x700 with 4 Axes>"
            ],
            "image/png": 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AZdd6pB6eJLxliLmgcTdiPLm17HrYLpR+dLkTrRYb4iINeHgaM2jkbqMvxv6wthPt1vDMWLTanHivxlttQ273hHSzBZOSkG6OQN+QEwfOt9/9B1RKvLd4fFa2N6b1zcGpYfOsqha/lixZAkEQbvp66623AABvvfUWDh8+fNPPlJeXw2634/Lly3j66adDPu5A0miG14ZW/gF6L1r7bP6Fi8c5uUVjYNLrsM53gg/Xvx85ET+DpQWpSIyWRwYN3V5CtNFf0iFcJ2U/rPX2PEuKNmJJQYrUwxkhIy4SCyd5+9GE6/nt/XNtsNpcyIqPxP15SVIPh+6CMS3QZrHhaK03w0v8txAz4g5caEPPgEOysUlp+M253Ig9MPeebcFAGGcs0kjiMSvGtNEmPVbNzAAAbAnThdLTV3pwrXsQMSY9VsxgGeLbWVOUAaNei0tt/TjbFJ6by8S/n7XFGTDp2ctd7ialxKB0QjzcHgE7y8OzHP6e6hbYnB5MTo1BUXac1MOhu9BpNf5F23Cdx7jSOYCPr/ZAqwE2+LI3xTh739lWxce0qlr8Iq+Ns7Kh0YRvE93t5U3wCMDc3ARMTIqWejikMOIJ/r2aVlhtTolHE75cbg+2iw1iZ8tvcotuTfz72V7eDFcY9qMRd/qvK8mEQSY9aIZ73Dcpu60sPMssiQsom2ZlMStcIRjTemPaORNvxLRT082YnmGG0y3gnarwm1Sqa7ei8nof9FoN1pfILyt81oQE5CVHY9Dhxr6z4d1jkbyGx7TDMwDEBe13q5phc4ZfmSVxgnF1YToijVzQuJ24SAOWT08DEJ4bQaw2J/bVsJe70jwe5hmL4j3h47OyodHwnkMJxGP28KUOdFjtEo8m9MQynYumpCDN7C1DPGtCvD+m3avwmFZ+MzM0blnxkViQ793RvD3MakMLgsAeQTQuRdlxmJwaA5vTgz1hXGZJakfqOtFh9TaIXVrA8hZKscS3o7mz344jteFVOrRv0In3fQ1i5Xr9WTEjHdFGHa51D+L0lfAqs9RuseHDS94MGpYfUY6wj2nFDKdPbALx91gMw92pYpbMkoJUJMWYJB7NzTQaDTaVhnfGIo10tK4T7b6YVsyQB4D785OQFR8Jq83ljx/CxZDDjd2++yy5xkxyIp7zd1Y0weEKr81le6tbYXN6kJ8SjZKceKmHQ6O0tsjb5+pCqxU1zeGVsXitaxCnrnRDq4G//xnJ3+TUGBTn+DIWK8LrnsPjEUb0JRWNiGkVfs/BxS+V8jfRDbOdFtVNfahr74dJr8Xqogyph0MK5C2zJO5UCq+LnpyIPQDWl2SxQayCGPXasC0d+m51MxxuD6amx2JGplnq4dxSlFGP1YXea+O2MPt8dlR4M2hmT/RmZZByhHNMW+uLadd8IqZdX5IJvVaDyut9qGu3SjTC0HN7BGwv9567xPKCciSWzjle34Wm3iGJR0NSE2PadcWZI2JarVbjnxgNt2vy/nOt6Le7kJMYibm5iVIPR/YWT05GSqwJPYNOHL4YXv1ohm9sZgaNcsRFGfDoNG/G4rYwm1MRj9mFk5ORHhch8WhoLJ6YdaNKSjg52dCNpt4hxN6iDPHwmPZ6j3KrcHBGUaXEJrpXugbDqomuuBq9fEY6zBEGiUdDSrWhNBMaDXCqITzLLEnNYnNiv79BrHwnt+jWxInq/efa0DcUPqVDxevPpllZsr45F7Oedle1hE2ZJW8GjVhyiucUpQnXmFa88b5VTJscY/L3FQynjTofXe5Em8WOuEgDlk6Vb1Z4dkIU7s9PhCAAO8IsY5FGsticeE8s2XaLMt7iNenD2k60W20hHZuUxPPWxtJsliEeBb1Oiw0l4be5rLF7ECcbuqFhBo0iiee3nRVNcIZJOXxBELCtnJWolOqxokwYdBqca7HgfEv4ZCyKG3DWFGUgwjCyDHF2QpS/CoeSY1oufqlUtEmPlTO9K7bh0kTX4fJgV6W398HjnNyicciIi8SiyckAwusGQy52V7XA7vJgSmoMCrPYIFZpZmaZcV9aDBwuD3ZXhUfp0PqOfpRd6/U2iC2R9/Vnfl6it8yS3eWfkFO7mmYLLrZZYdRr8ViR/HoE0Z2Fa0wrlly5XUzr77FY1gS3Jzwy4sRNBuuKM2HSy7tHkL+KwJnwylikkfbcJabNT4nBrAm+Mkvl4dHDr81iw9Fabxli3rOPnrh4evBCO3oGHBKPJjTETSAPTEpCZnykxKOhsXrwvhQkxxjRNeDABxc7pB5OSJy+0oPG7iHE3CKDhuQvIdqIR6b6eiwqvMzfaA06XP52L7fapDP88a0K7hvOxS8Ve8J30xUuTXQPXmhHz6ATqbEmLJ6SIvVwSOFulFlS7gleqYb3OJFzBg3d2sjSoeERNIo35w/el4JUs7zLW2i1Gv9kU7hkjIjH4aPT0xAXyaxwJQq3mPbQxRsxrbgZ55MenpaKuEgDWi02fHRZ/T0WrTYn9t0hg0ZuVhVmINKgQ33nAMobe6UeDknEX7LtDjHtjUml8Fgo3V7uLUM8NzcBE5NYhni0pqabMSPTDKdb8G/4VTNm0CifQafF+pLw6oEpzmOsLkxHpFHem3To1sRr8o6KZrjCIGPxvZpWDDjcmJAYhTkTE275nFUz0xFp0KGhcwBl13pDO8AA4eKXioVbE13xgrqxNAs6lk+gcVoxIx0xJj2udQ/i9JXwKbMktSudA/j4ag8bxCrcxtIsaDXAmas9aOgckHo4QeXxCNheLmZoKOPmXCx9eLS2A20WdZdZcro92FXhnSR6QiGfD90s7GJa3+TJhtIs6HW3vl0z6XVYW5wx4vlqtre6FTanB5NSolGcLf+s8BiTHqt8GYvh8PnQza52DeD0lZ67ZoU/VujtBXah1YqaZnWXWfKWIeaCxr0Kp81lH1/twdWuQUQbdf7sb1Ie8Zg9cL4dvYPqzlgccrixW8yg4flNsZYUpCAp2ojOfjs+rFV/xuLw1gC326QTPTymVej1h4tfKja8ia5SD9DR6uq349AFb/NXJewGJfmLNOqwupCTFqEm1hteNCUFaTLPoKHbSzVH+DNw1d7E/UR9l7dBbIQej05Pk3o4o5KbHI05ExPgEeBfuFOrwxc70DXgQEqsCYun3DqDhuQvnGLa7gEHDl30xbR3mTwRv7+vphVWm7p7LG4ZRQaN3Ij3JO9UhkfGIo0kZlcvnJyM9Ljbx7RxUQY8Os1XZknl57fqpj7UtvfDpNdidVGG1MNRnPUlmdBrNai63ofaNqvUwwkq8f57VWEGoox6iUdD92p6phnTMsxwuD14R+UZi/vPtaLf7kJOYiTm5iZKPRy6RwadFuvEHosqL7fe3DuEY77qEXe95/DFtO8qNKbl4pfK+ZvoXupQdRPddyqb4fIIKMyKw31psVIPh1RCzI7YXd2iyBO80ng8AraV37nHCSmHGCBtK2uCR8X9aMTJrceKMm9qECtn/jJLKu9H48+gKcm8bQYNKUO4xLS7KprgdAuYmWVGQfqdY9qSnHjkp0TD5vRg71n19vBr7B7EqYZuaBSWFb4gPwmZcRGw2Fw46NukR+HB4xH8m3+eGMXGzMdne4/rXRXNcKq4zJJ4TV4xIx3mCJYhHqukGBOWFKQCUHfpapvT7e8bzAwa5QuXcutbfOe3TaXZ0LISlaKJ5533z7ehb1C9m8u2lzdBEIB5eYnISYy643OHx7QHzisvpuUsgMrlp8SgdEI8PAJU3URXvJBu4oQ5BdC83ERkJ0Si3+7CezXqnVSSi1NXunG9x9sgdvl0lrdQuuXT0xBr0qOpdwgnG7qlHk5QDNhd2HtWvDlX1vVndWEGjHotatv7cbZJnWWWegcdOHDBWyJvEydPFC9cYtptYyijOqLHooqz1MW+igsnJSMjLlLi0YyeVqvBBjFjUcWfD93s9Bhj2genpCA5xoSuAQc+uKjOMksOl8ffq4r37PdOjDe3l1+HW6Wby/afa4PV7kJWfCTm5zGDRunWl3jbklQ09uJyR7/UwwmK1j4bjtV5M2h4flO+GZlmFKTFwuHy4N1qdd5zCMKwTTqjuOfQajXYOEu5VTi4+BUGhteGVuPu7kttVlQ39UGv1WBdcabUwyEV0Wo1/glTte9UkgNxYmhNYQYbxKpAhEGHNb6SNkoMkEZj39lWDDrcyE2KwuzbNIiVq7hIA5ZPV3eZpXcqm+F0C5ie4S25Qsqn9pi2ts2Kqutji2k3lmZBowFONnSjsXswyCMMPUEQsK1cLHmovAklMcv28KUOdFjtEo+GQkW8ro42ptXrtNgglllS6TX50MV29Aw6kRpr8pfGprF7eFoq4iINaLPY/ZPtaiPeE26alcUMGhVIiTXhofu8f/Nq3Qiyo6IJHgGYm5uAiUnRUg+Hxkmj0fhjTrUes5XX+3C5YwARBi1WFY5u47k4N/qBAmNaLn6FgbVF6m6iK56Mlk5NRVKMSeLRkNqIu+uO1nagzaLeMktSG3S4sEdsEMu+faohfpZ7q1sw6HBJPJrAEyeoNs1STg+a4cTPZ2dFExwu9ZVZ2uLbtMBzinqoPaYV+1otKRh9TJsZH4kHJiUBuJEhpSYfX+3B1a5BRBt1WDFDeVnhk1JiUJITD7dHwM4K9X0+dLMhhxt7qr0VI8aSASBOKh04347eQUdQxiYl8Z59Y6k3C4TujUmv82+OUONCaZvFhiO13uxHZu2rh7h5aXt5k+oyFgVB8J/fWKZTPTaUZEGrAcqu9aJehRmL4jG7ckY6YkdZhniSrwqHEmNaLn6FATU30XW5Pdg+hvIwRGM1MSkac3MT4BHgP9Yo8N6racWAw40JiVGYm6usDBq6vTkTEzAxKQoDDjf2qawfTVPvEI7XdwFQVg+a4RZPTkZKrAk9g04cuqi82t13Utfej8rGXui1GqwvYVa4Wqg5pnV7BOzwxRlPjDHDSYyBt5WrLyNOvDlfXZiBKKNe4tHcG3+PRRUuTtLN3qtpRb/dhZzESMzNHX3JtumZ3ixlh9uDdyrVVWape8DhjzO4IWX8xH/D92paYbWpqx/NjnJvBs3siQnIS2YGjVo8Mi0V5gg9WvpsOH65S+rhBFR1Ux9q2/th0mux2lf1hJQv1RyBB30Zi2rbXGZ3uYeVIR7bNVl8/haFZcRx8StMqLWJ7rHLXWi32pEQZcDDU1OlHg6p1PB+GmqbVJKLrWdu9O1TYgYN3ZpGo8GmUt+krMqCxh2+BrH359+9Qaxc6XVa/8LdNpUtJGz1Z9B4+6iQeqg1pj1a14k2ix3xUQYsHWNMu3JmOqKNOlztGsSZqz1BGmHo2Zxu7K5Sflb42qIMGHVanG+x4JwKMxZpJH9WeGn2mEu2Pe7vp6GumGlXRROcbgGFWXG4Ly1W6uEoXnF2HCalRMPm9GBvtXo2lwmC4P/74cZmdYkw6LDWl7GounsO3yLAihnpMI8yg4aUYXjGokdFGYsHz7ejb8iJdHMEFk5OHtPPijHthVaromJaLn6FCW8TXaPqmuiKF5p1xd4yOETBsLooAya9FrXt/TjbpJwTvFK09A3h2GVfg9hS3uiojVjy59jlTjT3Dkk8msBQU3kLcfwHL7SjZ0AdZZbcHgHby5gVrlbhENOa9GPrexll1GNVofp6LL5X0wqr3YXshEjMG0MGjdzERxmxbLp3QVNtk340UmufDUd9fZju5fqzvsRbErCisReXVVRmaav/mqzMTHm58faj8e2+V9E5pabZgktt/TDqtf6+waQe/nL4Z73ZsWrgcHn8GTRK3qRDt/bo9DTERujR1DuEEw3qyVgU7xU23EMZ4uExrZLuObhaECb0Oi3Wl4g7yZRzgN6JxebEezViPXVeaCh4zBEGLPf1mVDL34+cbPdl0MzLTcSEJGVm0NDt5SRGYV5eIgQVlQ4tb+xFfecAIg06/4SzUhWkx2JGphlOt+C/eVO645e70GqxIS7SgIenMStcbdQY01qHxbT3umAr/ty7lS2wOd0BG5uUxIzhTaVZY86gkRtxc8+Oima4VJSxSCONN6ZNiTVhia/M0laFlRS6nUttVlQ39UGv1fgzP2j8NpZmQaMBTjV0o7F7UOrhBIRYRuvR6WmIi2QGjdqU5sQjLzkaQ0439vp6fSvdoYvt6Bl0IjXWhEVjzKAh+Ysw6PCYbyFerFSkdJ39dhz2bR4ca5l1kXjPsbOiSTFVOLj4FUYeV1kT3T1VLbC7PJicGoOi7Diph0MqJ+5U3FnRBIdLGSd4JRiRQXOPF1+SvyfE0qFl6igd6m8QOzMdMSZl9qAZ7vFhn48aiL/H2uKMMWfQkDKoLqatHn9MOz8vEVnxkbDaXdh/ri3AIwy9NosNR2q9N+dq2OT2UEEKkqKN6Oy348Na9WQs0g0jSraNI6YVswe2lzfBrYIyS+K/ydKpqUhiGeKAyYiLxMJJ3sl2NcRvwzNonlDBOZ9uptFohpV2Vf4xC9y4J9x4Dxk0pAziPcfesy0YUEHG4q6KZrg8Aoqz4zA59d7KED94n7cKR2e/Ax9eUkZMy8WvMKK2JrrD60GzRxAF2+IpKUiNNaFn0Olv2EzjV3m9D5c7BhBh0GK1wjNo6PZWFaYjwqBFfccAKhp7pR7OuNicbv81VC0l9daXZEKv1aDqeh9q26xSD2dc+u0u7Ds7vgwakj/VxbQB6Hup1Wr8ZWbVkDGyo7wJHgGYMzEBucnRUg9n3AzDMxZVsnuYRqq63oe69n6Y9NpxZYU/PDUV5gg9WvpsOH5Z2WWW3B4BO8pZhjhYxEXWbWVNit9cdvhiO7oHHEiJNWHxFGbQqNXGWdnQaIAT9crPWOwecPjnhVjyUL1mT0xAblIUBh1u/z2mkt3YpHPvx6xBp8W6YmUtZHPxK8yIOy22KLyJ7tWuAZy+0gOtxrvLgijYdFqN/1hTw6SSXAxvEBvLBrGqFRthwEqVlA49cL4dFpsLGXERWDApSerhBERSjAlLCrzlAZXeO2JPdQuGnG7kp0SjJCde6uFQEKklpr3WNYhTV7qhCUBMK2ZIHantQJvFFojhSWJkBo16JpTEier3z7Whb9Ap8Wgo0MRjdsWMdJjHEdNGGHT+8oBKj5mO1nWizWJHQpQBD09lGeJAWzEjHdFGHa51D+L0lR6phzMu/h40JZnQ6zhNqVZZ8ZFYkO+9f1J6OfxdFU1wugUUZsXhvrR7y6Ah+dNoNP74WunX5AutFtQ0W2DQabC2aHxliMWY9q/nlFGFg1eVMCM20a1s7EVdu3Kb6Io9ABZOTkZ6XITEo6FwIV70Dvl2ptH42F3uGw1iuRtU9cQJzHcqW2B3KbcfzbYydZa3EGt+71B4mSV/GVVmhaueWmJa8UZ60eRkZMRFjuu18pKjMXtiAjyCt0yzUp1tsuBSmzeDZk2RerLCZ2TGYWp6rDdjsUr5GYt0w4iYNgALtuJr7Dvbin4Fl1kSr8nrijNh1HPqKdCijHp/5YxtCp6U7Rlw4OAFZtCEC/G+f5vCy+FvLROzWrkZX+3EzWnH67vQ1Dsk8WjunXhNfnhqKhKijeN6reEx7btV8u/hxwgkzAxvoqvUAMnjEbCt3Dv2JxgcUQgVpMdiZpYZTregijJLUjt0oR19Q06kmU1YyAaxqvfApGSkmyPQN+TEwfPKLB3aYbXj8CX19KAZbunUVMRHGdBmseNYXafUw7knjd2DONkQmAwakj+1xbSB2gTi7+F3RrllsMQFweXjzKCRI/HeRanHLN3aoQsd6B30xrSLAhDTlubEIz85GkNON/ZWy39S6VYsNifeq/GVIeY9e9CI/7a7q1pgcypzc9k7Vc1wugXMyDRjarpZ6uFQkK2cmY4oow5XugZRdk2ZGYuX2qyobuqDXqvBuhLec6hdTmIU7s9PhCDAX8pXaVxuD7aXB3bjuRjTKiEjjotfYUicsFNqE93TV7rR2D2EGJMey6enSz0cCjOPqyTlWQ62+HpebFBZBg3dmk6rwYZSZdWG/qSdFd7rZnFOPCanxkg9nIAy6XX+8gdK/XzE8ikPTEpCZvz4MmhIGZQe0358tQeN3UOINuqwYkZgYto1RRkw6rW42GZFTbMlIK8ZSg6Xx59Bs0mFu6nXlWRCp9Wg7Fov6juUm7FII/lLtgUoptVoNP5FDaVek/dWt8Du8mByagwKs+KkHo5qzctNRFZ8JKx2l3+xUWnEbAS1bSyjW4s26bFypjfm2aLQHpjieXnp1FQkjjODhpTBX/rwjDIzFo/UdaKz347EaKO/3cF4iVU4yq/14rLMY1oufoWhR6Ypu4mueKFZXZiOSKNO4tFQuFlXnAm9VoOq632obbNKPRzF6uq347CvQewTvNEJG2JpvcMXO9DZb5d4NGMnlrd4QoUTssCN3cPv1bTCalNWPxpBEPyZFCyjGj4UH9OeEWPajIDFtHGRBjw6PQ0AsEWBPUoP+0pLp8SasFiFWeGpsRF4cIr399qm8H515NXVb8chsWRbAK8/G0qzoNEAJ+q70dg9GLDXDZWtZ8SSYCxDHExarcZfdm2rAs8pde1WVF73ZtCsLxlfDxpSDvH+/92qZsVlLLo9gj/7h/cc4WN1YQYiDTrUdw6gvLFX6uGMWTDKEKfEmvCQQqpwcPErDCm5ie6Qw4091b7yCbzQkASSYkxY6mvYvEVhfz9ysrOiGS6PgKLsOExhg9iwMTk1FsXZcXB5BOysUFbp0HPNFpxvscCo0/qvoWpTnB2HSSnRsDk92KOwMktnrvbgStcgoo06/25SUj+lx7S7fX9ngS4JJk4q7apshsPlCehrB9vWYX0V9Tp13qqKn/f28iZ4FJixSCPtqvTGtIVZcbgvgDFtVnwkFuQnAbiR2awU17oGcepKN7QsQxwSYkbC0doOtFlsEo9mbMTMnyUFKUiOMUk8GgqV+/OTvBmLNhfeP9cm9XDG5GhdJ9osdiREGfDw1MBk0JD8xQzLWNyqsM1lfUNO7Pf9nQW6dZBYpWF7mbxjWnXeUdBdKbWJ7ns13vHmJEZibm6i1MOhMCUuvO5QaJklOdjKDI2w5S/jo7CgUTxmH5mWivgodZa3GFFmSWFlSMTPZ1VhBqKMeolHQ6Gk1Jh2/znveLMTIjEvwDHt4inJSIk1oXvA4c+yVoKeAQcOBiGDRm6WTUuDOUKPpt4hnKhXXsYijXQjpg38Io/4d7CtTFlllsR/k4WTk5EeFyHxaNQvNzkacyYmwCMoa6HU7RGwPcB9L0kZtFqNf2FcaZuXgpFBQ8ognqfeqVRWxuLuqhY4XB7clxaDGZmB7asoxrTNfTYcl3FMy7/UMKXUJrrihXFTaTa07BFEElk6NQXxUQa0Wew4Vtcp9XAU50KrBTXNFhh0GqxTaQYN3d7aokwYdBqca/FmUimBy+3BzorwKG+x0Vdm6dSVblzrUkaZJZvTjXcrfRk0Kv986GZKjWm3DOtxEuiYVq/TYoOvfJSSSuvtqmyG0y1gZpYZBenqzQqPMOjwmD9jUTmfD93sYqsVZ5t8MW1J4Be/Vs5MR5RRhytdgyi71hPw1w8Gj0fANt+CRqB3mNPtDd9cppSF0o8uezNo4iINeHgaM2jCjZgx8uGlDrRblZGxaLE5/b31Ap21T/K3YFISMuIiYLG5/Ju1lGD4xvNAlyEeGdPKdyGbi19hSolNdFv7bP6FBk5ukZRMep1/0UYpfz9yIk7EPTw1FQlsEBt2EqKNeGSqtx+N3GtDiz6s7UBnvwNJ0UY8VJAi9XCCKiMuEot8fXbEySu523+uDVa7C1nxkZifx6zwcKP8mDY4JcHEf5MDF9rQM+AIynsEWjhlhYu/496zLRhQUMYijSTGMUsLUpEYhJg22qTHqpkZAG6Uh5O701e60dg9hBiTHsunswxxqKwpyoBRr0Vtez/ONiljc9nwDBqTnr3cw01+SgxmTYiHRwB2liujHP6eqhbYXR5MSY1BYVac1MOhENMNz1hUSBWbhs4BnLnaE9QyxGJMu+9sq2xjWi5+hTGlNdHdXt4EjwDMzU3AhKQoqYdDYU48wb9X0wqrzSnxaJTD5fb4y3FsCoPJLbo1f23o8ma43PLvRyOWAFxXkgmDSnvQDCd+PtvKmhSxe1icfNw0K4tZ4WFKaTHtjoobMe3EpOigvMfUdDNmZJrhdAt4p0r+k0q1bVZUXe+DXhseWeGzJsQjLzkagw439p1tlXo4dA+Gx7TBzAB4fLb3mvxulTLKLImb3FYXpiPSyAWNUDFHGLB8undzmRI2glhtTuzzZdBsCtImEJI/cT5gq0JKu4rnt01ByKAhZRCP2cOXOtBhtUs8mrvb7rseLJ6SglRzcMoQD49p98o0plX/DA7dlpKa6AqCEFa7QUn+irLjMDk1BjanB3sUVGZJakfqOtFh9TaIXVrA8hbhaolvh3Rnvx1HauVdOrRv0OlvxBwu158VM9IRbdThWvcgTl+Rd5mldosNH17qAMAF9XCmuJh2WMnDYPJPKilgd6pY/m9JQSqSYkwSjyb4NBoNNim03wl5Ha3rRHsIYtr785KQFR8Jq83lj0fkasjhxu5qliGWirgIu7OiCQ6XvDeX7a1uhc3pQX5KNEpy4qUeDklkbZG3b9aFVitqmuWdsXitaxCnrnQHNYOG5G9yagyKc+Lh9gj+tghy5fEI/vg6mJt0NBqNv5KFXO85uPgV5pTSRLfqeh/q2vth0muxuihD6uEQ+U7w4qSSvC96ciJeDNeXZLFBbBgz6rX+nf1bZD7p905VMxxuD6amxwa8QaxcRRn1WF3ovdbKNYAViRk0sycmIC85OBk0pAxKiWmrm/pQ64tp1wQ5pl1fkgm9VoPK632oa7cG9b3Gw+0RsN3fIyh8JpQ2+iYKjtd3oal3SOLR0FiJE0rrijODGtNqh5dZknnMtP9cK/rtLuQkRmJuLssQh9riyclIiTWhZ9CJQxfl3Y9mSxB70JByxEUZ8Og0ZWQsiuNbODkZ6XHByaAhZXhCXOiRed/Wkw3daOodQqxJ788MDpYNpTdi2us98qvCwZnHMKeUJrpiSaMVM9JhjjBIPBoirw2lmdBogFNXunGtS34neLnpG3Jif5hl0NDtiU3Q3z/Xhr4h+ZYO3RamN+fi7rDd1S2yLbPkzaDx7WbjOSXsKSWmFReUl4cgpk2OMWGJr0+hnG/Qj9V1os1iR3yUAUunhk9WeHZCFBbkJ0EQbpSlIWWw2JzY7yvZFszd1CKxLNyHlzrQbrUF/f3u1RYxq7U0m2WIJaDXaf0LpXLuq9vYPYhTDd3QaFjykG6Udt1V0QynTMvhezyCvxfyEyE455O8rS3OhFGnxfkWC87JOGNRXLBdU5SBCENwyxCLMS0A7JBhFQ4ufoU5JTTRdbg82FXp7VUQipsLotHKiIvEosnJAOAPhuj29lS3wOHy4L60GMzMCo8MGrq9GZlmFKTFwuHyYHeVPEuH1nf0o+xaL7QaYH2p+nvQDDcvNxHZCZHot7vwXo08a3fXNFtwsc0KYwgyaEj+FBfThmjCT1wY3l7WBLdHnhlx4s35uuJMmPTh1SNIvLdRSo9F8tpT1QK7y4MpqTEozIoL+vvlp8Rg1oR4eARgZ7k8e/i19tlwrM5bypobUqQj/tsfvNCOngGHxKO5NbFv0sJJyciIi5R4NCS1B6ekIDnGiK4BBz642CH1cG7p9JVuNHYPIcakx/Lp6VIPhyQWH2XEI9O8m7XkutFg0OHCXrEMcYjm0cX32SrDmJaLX+S/+ZZrE92DF9rRM+hEaqzJv9BAJBc3yizJ7wQvN8N7nIRTBg3dmkaj8e/2lGuZC/Hm/MH7UpAaG17lLbTa4f1o5LmQIO4wf3R6GuIimRVOyoppF09JCcl7PjwtFXGRBrRabPjosvx6LFptTv8Cezj27Vs5Mx2RBh3qOwdQ3tgr9XBolPy9qGeHLqa9Makkz9Ku28u9ZYjn5iZgQlKU1MMJWwW+Mt1Ot+DfbCEngnAjg4ZZXwR4MxbXl8j7nlAc1+rCdEQaw2uTDt2aGLPuqGiGS4YZi/vOtmLA4cbEpCjMmZgQkvdc5avC0dA5gLJrvSF5z9Hi4hfh/nx5N9EVLzQbS7OgY/kEkpkVM9IRY9LjWvcgTl+Rb5klqV3pHMDHV3vYIJZG2FiaBa0GOHO1Bw2dA1IPZwSPR8D28vAuqScG9UdrO9BmkVeZJaf7RgbNE2H6+dDN5B7TbpMgpjXpdf4ei3Ls4be3uhU2pweTUqJRnB38DBq5iTHpsWqmdxe5HD8futnVrgGcvhL6mPaxQm9vsQutVtTIrMySIAgjykSTtPx9qWW4kPDx1R5c7RpEtFGHlTOZQUNe4jF74Hw7egfllbE45HBjT7WvzC3Pb+SzpCAFSdFGdPbb8WGt/DIWxU28m0pDt0kn2qT3n9fldv3h4hfJuoluV78dhy54m7Wy5CHJUaRRh9WFnLS4G/GGeNGUFKSZwyuDhm4v1Rzhz36QW8mAE/Vd3gaxEXo8GuQGsXKVmxyNORMT4BHgXwiUi8MXO9A94EBKrAmLpzArnLzkHNN2Dzhw6KI3pg11hpO4u35fTSusNnn1WNwiQQaN3Ij3OO9UyjNjkUYSs6EXTk4OaUwbF2XAo9PSfGOQ1/mtuqkPte39MOm1WM0yxJJbX5IJvVaDqut9qG2zSj2cEcT75VWFGYgy6iUeDcnF9EwzpmWY4XB78I7MMhb3n2tFv92FnMRIzM1NlHo4JBMGnRbrSsTNZfK6T27uHcIxX7WHUGfYiptS35VZTKvKxa+f/OQnyM3NRUREBObPn49Tp07d9rlvvfUWNBrNiK+IiPCbmB3RRFdGu7t3VTbD5RFQmBWH+9JipR4O0S2JO4B2V7dgyCGfE7xceDyCf6IgVD1OSDmG9zvxyKgfjTgh+1hRZtAbxMqZv8zSGXmVWRInTzaUZEKvU2U4S/dItjFtRROcbgEzs8woSA9tTFuSE4/8lGjYnB7srZZPD7/G7kGcauiGJsyzwhfkJyEzLgIWmwsHzrdLPRy6A4/nRobTExJszHx8tvfvZFdFM5wyKrMkXpNXzEiHOYJliKWWFGPCkgJvP5otMlootTnd/j6/zKChTxLnCbbIrNy6WGZ9U2k2tKxERcOI57H3z7Whb1A+m8u2lzdBEID5eYnISQxtGeL7h8W0fz0vnyocqpst+NOf/oQXX3wRr7zyCsrKylBcXIwVK1agvf32NxJmsxktLS3+r6tXr4ZwxPIwooluhXx2WmzjhDkpwNzcRGQnRKLf7sL+c/KZVJKLkw3d3gwakx4rZrC8BY20fHoaYiP0aOodwsmGbqmHAwAYsLuw76z3b/mJ2eF9/VlTlAGTXova9n6cbZJHmaWeAQcOXPAG08wKp0+Sa0x7YxNI6I9ZjUYjyzJY4lgWTU5GRlykxKORjlarwUaZ98Akr1NXunG9ZwgxJj2WTw99TPvglBQkx5jQNeDABxflUWbJ4bpRhpjXZPkQ49cd5U1wy2Rz2f5zbbDaXciKj8T8PGbQ0EjrS7wloSsbe1HX3i/1cAAArX02HKvzZtBwwZY+aUamGVPTY+Fwe/ButTzuOQRBuNGXVIJjdnhMu01GC9mqW/z60Y9+hOeffx7PPPMMpk+fjp///OeIiorCG2+8cduf0Wg0SE9P93+lpYVneSO5NdG91GZFdVMf9FoN1pWE9+QjyZtWq/GXMNoqoxO8XIg7ZNcUZYR1Bg3dWoRBh8d8JXLkMum372wrBh1u5CZFYdaE0DSIlStzhAHLZ8irdvc7Vc1wugXfDYdZ6uGQDMk6pvX13wq1TbOyoNF4N6Q0dg9KMobhvD2Cwruv4nBiHPnBpQ50WO0Sj4Zuxx/TFmYg0hj6mFav02KDWGZJJtfkgxfa0TPoRGqsCYsmswyxXCydmor4KAPaLHb/5L3UxAzBx2dlMYOGbpISa8KS++RVDn97eRM8AjAvNxETkkKbQUPyN2JzmUxaoFQ09qK+YwARBi1WFUqz8VyOMa2qFr8cDgfOnDmDZcuW+R/TarVYtmwZjh8/ftuf6+/vx8SJE5GTk4P169ejpqYmFMOVHbk10RVPHkunpiIx2ijxaIjuTMxOPFrbgTYZlVmS2qDDhT3V3vIWoe5xQsohHht7q1sw6HBJPJobE0qbZoVvD5rhxDJyOyua4HBJX2ZJjA94TqHbkXNMmxRjkmQMGXGRWDjJOzEth52Yp6/04Fr3IKKNOiyfEZ4bD4eblBKDkpx4uD0CdlZI//nQzYYcbuzxlQ2VMsNJfO8D59vRO+iQbBwiMWbaWOrN2iB5MOl1WFskn4XSNosNR2q92YobGb/RbYix/XYZZCwOz6AJdd8kUo71JZnQaoCya72o75A+Y1E8ZlfOSEesRGWIJ6XEoHSCvGJaVS1+dXZ2wu1235S5lZaWhtbWW5ciKygowBtvvIGdO3fid7/7HTweDx544AFcv377AMFut8NisYz4UgM5NdF1uT3YXs7doKQcE5OiMTc3AR4B/mOXgPdqWjHgcGNCYhTm5oZ3Bg3d3pyJCZiYFIUBh9tfblAqTb1DOF7fBSC8e9AMt3hyMlJiTegZdOLQRWn70dS1W1F53ZtBs75Emgwakj85xbRujzAsppX2nCJO3mwrlz4jTtzVvbowA1FGvaRjkYsbGYuMI+XovZpW9NtdyEmMxJyJ0sW00zLMmJZhhsPtwTuV0pZZ6h5w4NAFb1zAkofyI34m79W0wmqTth/NDl8GzeyJCchLjpZ0LCRfj0xLhTlCj5Y+G45f7pJ0LNVNfahr74dJr8VqX5USok9KNUfgQX/GorTxm93lxjuVvr6KEl+TxXn8LTLJiFPV4te9WLBgATZv3oySkhI89NBD2LZtG1JSUvCLX/zitj/z6quvIi4uzv+Vk5MTwhEHl1ya6B6t60S71Y6EKAMenpoq2TiIxmJ4yrPUk0pysfWMNwDwllviblC6NY1Gg02l8uhHs73sOgQBuD8/9A1i5Uqv0/oXAqUu6SBOCi8p8PY9IboducW08VEGLJU4pl05Mx3RRh2udg3i46s9ko3D5nRjd5U8bs7lZG1RBow6Lc63WHBOBhmLNJI/A6A0W/KSbeJC+haJJ9p2VTTB5RFQmBWH+9JiJR0L3aw4Ow6TUqJhc3r8lTikIHUPGlKOCIMOa4vlkbEo3vOsmJEOs0QZNKQMjw/LWPRImLF48Hw7+oacSDdH4IFJ0pYhfswX03qrcPRJOhZAZYtfycnJ0Ol0aGtrG/F4W1sb0tNHV+vSYDCgtLQUdXV1t33OSy+9hL6+Pv9XY2PjuMYtJ3JpoiuumK8r9patIVKC1UUZMOm1qG3vR3WT9Cd4qTX3DuHYZTaIpdERMxI+utyF5t4hScbAHjS3J/57HLrYju4BacosuT0CtvPzoVGSS0wrTp6sK86ESS9t38soox6rCr27l6Xsp/FeTSusdheyEyIxLzdRsnHITXyUEcumexdIpZ70o5Fa+oZwtE4+Me36Em+JwcrGXtS1S1dmaWuZPLJa6dY0Go0sMkprmi241NYPo16LNcygobsQj9l9Z73ZtlJwuDzY5cus5SYduptHp6chNkKPpt4hnGiQLmPRX4Z4lvRliEfEtGekr2igqlUFo9GI2bNn48CBA/7HPB4PDhw4gAULFozqNdxuN6qrq5GRcfuLsslkgtlsHvGlFnJoomuxOfFejfT11InGyhxhwPIZ3oV2qbMj5GB7eRMEAZiXxwwaurucxCjMz0uEIGHp0PLGXtR3DiDSoPNPEJNXQXosZmaZ4XQLkpVZ+uhyJ1otNsRFGvDwNGaF053JLqaVwYQ5cGMc71a2wOZ0SzIGcRJ20yzpM2jkRvx8dlY0SZqxSCP5Y9rcRExIkj6mTYk1YYm/zJI057dLbVZUN/XBoNNgXQkXv+RqY2kWNBrgVEM3GrsHJRmDWPZq+fQ0xEUyg4burDQnHvnJ0RhyurFXoozFgxfa0TPoRJrZhEWTpc2gIfmLMOjwmNhjUaKFns5+Ow77NvvJZUOKGNPuqpQ+plXV4hcAvPjii3jttdfw61//GufPn8cLL7yAgYEBPPPMMwCAzZs346WXXvI//1/+5V+wf/9+1NfXo6ysDJ/73Odw9epVPPfcc1L9CpKTuonunqoW2F0eTEmNQWFWXMjfn2g8xAvNrspmOFzhO2nhzaDx3ug8IZMJP5K/G7tTpSkdKi5ar5qZjhgTe9B8kr+0q0QTbXLKoCFlkEtMOzk1BkXZ8ohp5+clIis+Ela7C/vPtd39BwKszWLD0Vp53ZzLyYP3pSA5xojOfgeO1EqXsUg3jMgKny2fY1Y8v20vb4JbgjJL4jV5aUEqEqONIX9/Gp2MuEj/5L0U8RszaGisRmYsSnTP4XvfDaXSZ9CQMjzhiw/2nm3BgAQZizsrmuHyCCjOjsPkVHmUIR4e0354SdqYVnWLX0899RT+/d//HS+//DJKSkpQUVGBffv2IS3N2/T62rVraGm5sXugp6cHzz//PKZNm4bVq1fDYrHgo48+wvTp06X6FSQndRNdfz31WdnsEUSKs3hKClJjTegZdOLQxXaphyOZyut9uNwxgAiDFqsKR1d2lmjVzHREGLSo7xhARWNvSN/b5nT7r3mbuGB7S+uKM6HXalB1vQ+1bdaQvrfV5sQ+XwbNJk6Y0yjJJaZ9XEYxrVar8S86SZGlvr28CR4BmDMxAROTokP+/nJn0Gmxrlj8fKQvE0NA1fU+1LX3w6TXYrWMssIfmZYKc4QeLX02HL8c2jJLLrfHn6XPmEn+xLhpW1lTyDeXHfaVy06JNWExM2holDb4MhZP1Ic+Y7Gr345DF7zzOHLJ2if5mzUhAblJURh0uLHvbGvI31+M6eW0ycCg02K9LzNc6nLeqlv8AoC/+7u/w9WrV2G323Hy5EnMnz/f/73Dhw/jrbfe8v//f/zHf/if29rait27d6O0tFSCUcuLVE10r3YN4PSVHmg13hR9IqXRaTX+YzecSx8ObxAbywaxNEqxEQasFEuHhjhAOnC+HRabCxlxEVgwKSmk760USTEmLCnwlhvcEuLPZ+/ZVticHuSnRKMkJz6k703KJnVMq9EAG0ozQ/red7PRN5lzpLYDbRZbyN5XEARZ3pzLjZhd9P65NvQNOiUeDYnxiNxiWpNeh7XF0pR2PXa5C+1WOxKiDHh4KssQy92KGemINupwrXsQp6/0hPS9/Rk0JZnQ61Q5/UhBkBUfiQX53vuxUJfDf6fSm0FTmBWH+9LkkUFD8qfRaPybQUJ9TT7fYsG5FgsMOg3WFsnrnkNcQP7rOWmqcIh49aFbkqqJrtgDYOHkZKTHRYTsfYkCSbzoHfLtdAs3dpf7RnkL7paiMRInRN+pbIHdFbp+NP4GsSxvcUdiSYcdIS6z5J8wl1EGDSmDVDGtWCZt0eRkZMRFhux9RyMvORqzJybAI3j/lkPlbJMFtb4MmjVF8smgkZsZmXGYmh7rzViskqbHInmNiGlluGArjmnf2Vb0h7DM0vAyxEY9p5TkLsqo92cthnJzZs+AAwfFDBoZ/v2QvInzCNtCXA5fnJNkaWYaK3ET/PH6LjT1DoXsfcV2I49MTUOCzMoQT880D4tppenhB3Dxi25Diia6Hs+wHkEMjkjBCtJjMTPLDKdbwK6K8CtZc/B8O/qGnEg3R2Ahy1vQGD0wKRnp5gj0DTlx8HxoSod2WO34wFeHmjfnd7Z0airiowxos9hxrK4zJO/Z2D2Ikw3d0GhY8pDGTrKYtvzGgq0cDe/hF6pJJXGTwfIZ6TDLKINGjp6QuN8JeR260I7eQSfSzCZ/3yQ5Kc2JR35yNIacbuytDs2kksXmxHu+MsSMmZRD/Kx2V7fA5gzN5rJ3qprhdAuYkWnG1HRzSN6T1GPlzHREGXW40jWIsmuhyVi81GZFdVMfDDoN1pXwnoPGJicxCvfnJ0II4eYybxli+W7SAYbFtBJWxuLiF91WqJvonr7Sjes9Q4gx6bF8OnsEkbLdmFQKv8UvNoil8dBpNdg4K7S1oXdWeK9zJTnxmJQSE5L3VCqTXod1IS6zJGbQLJwkvwwaUgYpYtrGbm9Mu2KGPGPaNUUZMOq1uNTWj5pmS9Dfz+HyYGcFd1OPlpixWH6tF5c7QpexSCNt8fVdk2tMq9Fo/Oe3UF2T91S1wO7yYEpqDAqz4kLynjR+83ITkZ0QiX67y794GWzDs/aJxirapMeqmd6MxS0h6oEpHrNLC1KRKLMMGlIG/zzgmdBsLjtS24nOfjsSo414yLfZT27EmLaiUbqYlotfdFuhbqIrBuxrCjMQadQF/f2IgmldcSb0Wg2qm/pwqc0q9XBCprPfjsMXfRk0nNyieyQeO4cvdqCz3x709/OXt5Dpbim5EYP692paYbUFtx+NIAzLoJnNcwrdG6li2tWF6bKNaeMiDVg+PQ0AsCUEOzEPXWxHz6ATqbHyzKCRm5RYk38SY3sYbqSSg65+Ow5f9GagPyHjyfuNpVnQaIAT9d1o7B4M+vuJ57fHZ7MMsZJotcP70QT/nFLXbkXl9T7otRqsK5FXDxpSDjH2f7eqOegZi94MGt4T0visKsxApEGH+s4BlDf2Bv39xD7cci5DPDymDVUVjk+S578MyUIom+gOOdzYU+3dgcSSRqQGSTEmLPU1gA6nkjW7KrwNYouy4zCFDWLpHk1OjUVxdhxcHgE7K4Lb7+RcswXnWyww6rRYyx40o1KUHYdJKdGwOT3YE+QySx9f7cHVrkFEG3WyzaAh+ZMqppX7bndxcmdXZTMcLk9Q30vcTb2hNAt6HW9BR0O8J9pe3gRPCHsskteuSmXEtJnxkXhgUhIA+Cdug+Vq1wBOX+mBVgNsYEkwxdnk60dztLYDbRZbUN9LzNRZUpCC5BhTUN+L1Ov+vCRkxUfCanPh/XNtQX2vo3WdaLfakRBlwNKC1KC+F6lXjEmPlTO996zBLvPXN+j0/13IvXWQeE+0vUyamJZ3HnRHoWqi+16N9/VzEiMxNzcxaO9DFEriCX5HiMosyYF/N6jMJ/xI/h4PUW1o8Zh9ZFoq4qNY3mI0RpRZCnIZEnF32KrCDEQZ9UF9L1K3UMW0+895Xz87Qf4x7eLJyUiJNaF7wOHPcAmG7gEHDvlen/HB6C2blgZzhB5NvUM4UR/8jEUaSYwPxAUDOdtU6v272hbkHn7+MsSTk5EeFxG096HgyE2OxpyJCfAIwV0odXsEbJd530tSBq1Wg42loSmHL57f5JxBQ8ognvfeqQxuxuLu6hY4XB4UpMViRqa8+yqKVTia+2w4LkFMy79ouqPhTXSDubv7xs1FNrQyrKdOdC+WTk1BfJQBbRY7jtZ1Sj2coLvQakFNs8XbILaY5S1ofNYWZcKg0+BcizczKxic7uE9aHhzPhZimaVTV7pxrSs4ZZZsTjferfTGHvx8aLxCFdOKJQQ3zZJ/TKvXabGhJPgZce9UNsPpFjAzy4yCdPlm0MhNhEGHx3zx1JYwqiIgBxdbrTjb5ItpFZDhtHJmOqKMOlzpGsSZqz1BeQ+P50YZYrnvMKfbG765LFgLpcfqOtFmsSMu0oCHpzGDhsZHzIL+8FIH2oOUsWixOf298FjykMZrwaQkZMRFwGJz4cD54G0uu1GGOEv2ZYiHx7TB3tx8K1z8ojsavrs7WLU5W/ts/oUBTm6Rmpj0Ov8ikBQn+FATf8eHp6YigQ1iaZwSoo14ZKq3H02wrj9HajvQ2e9AUrQRDxXIs0GsXGXERfr79oiTYYG2/1wbrHYXsuIjMT9P3hk0JH+himmP+WNa+U+YAzcmeQ5eaEfPgCMo78Gs8Hsn/pvtO9uKgSBmLNJI4jG7tCAViQqIaaNNeqya6S3dHKx+TqevdKOxewgxJj2WT2cZYqVaU5QBk16L2vZ+nG0KzuaybcN60Jj08ux7ScqRnxKDWRPi4REQtHL4e6paYHd5MCU1BoVZcUF5DwofumEZi8G652joHMCZq8oqQyzGtHsliGm5+EV3FewmutvLmyAIwLzcRExIigr46xNJSTzBv1fTCqvNKfFogsfl9mCHLxjl5BYFijgpu728GS534PvRiCX71pdkwcAeNGMm/q1vK2sKyu5hcUH98VlZss+gIWUIRUzrEYC5uQmYmBQd8NcPhqnpZszINMPpFvBOVeAnlWrbrKi63ge9llnh92LWhHjkJUdj0OHGvrOtUg8nLLjcHn9JOCVlADw+2zv59W5VcMosiQuCawozEGnkgoZSmSMMWO7roRqMjF+rzYl9zKChAPNnLAaptOuNDJps2WfQkDKIx+zhSx3osNoD/vriotriKSlINSujDLEY0w453dgb4piWMz10V8FsoisIwohUTSK1KcqOw+TUGNhdnqCWWZLakbpOdFjtSIw2YgkbxFKALClIQWK0EZ39dhypDWzp0OENYnn9uTcrZqQj2qjDte5BnL4S2DJLbRYbjtR2APCWjyMKhJDFtAo7ZsXxBiNLXSzXt3RqKpJiTAF/fbXTaDT+LMJg9zshr6O+mDYhyoClCopp789LQlZ8JKw2lz++CZQhhxt7qrmgoRbiOWVnRRMcrsBuLttb3Qqb04NJKdEozmYGDQXGY4XePlwXWq2oaQ5sxuLVrgGcvuLNoNmogB6PpAyTUmJQkhMPt0fwt1kIFI9H8PeoU9I1eURMG+LKWFz8olEJVhPdqut9qGvvh0mvxarCjIC9LpFceE/w4qRS8BoLS028eLFBLAWSQaf1ZwoEut/JO1XNcLg9mJoei+kZ8m4QK1eRRh1W+67dgQ5gd/gyaGZPTEBusjIyaEgZQhHTri5SVky7riQTeq0Gldf7UNduDdjruj0CdogZNAopAylHG3yTccfru9DUOyTxaNRPLBuotJhWO6zMUqAXSt+raUW/3YWcxEjMmZgQ0Nem0Fs0ORkpsSb0DDpx6GJg+9GI8fqmWcygocCJizLg0WnecviBPr+J5/yFk5ORppAMGlKGG5uXAjsPeKLBGw/GRuixfHpaQF872DbOyoZG441pr/cEp2/4rSgnmiNJBauJrnjhWjEjHeYIQ8Bel0hONpRmQqMBTl3pxrWu0J3gQ6VvyIn9YgaNwna7k/yJTdXfP9eGvsHAlQ4dnqHBm/N7J+42213dgiFHYMosKTmDhuQvWDGtWH5kuQJj2uQYE5b4+h5uCeBGnWN1nWiz2BEfZcDSqcrJoJGb7IQoLMhPgiAA25n9FVQWmxP7FVyybZNvou3DSx1ot9gC9rriNXlTaTbLEKuAXqe9sVAawM1Ljd2DONXQDY3mxrFIFChipY5dFc1wBqgcvjeDxvs38IQCz/kkb2uLM2HUaXG+xYJzAcxYFLO+HivKQIRBWWWIs+IjsSDfV4UjSD1Kb4WLXzQqwWii63B5sKvS1yOIFxpSsYy4SCyanAxAnSVrdle1wOHy4L60GMzMYgYNBdaMTDMK0mLhcHmwO0ClQ+s7+lF+rRc6rQbrS9mDZjzm5SYiOyES/XYX9p8LTO3ummYLLrX1w6jXYo3CMmhI/oIe0yp0wk9caN5R3gS3JzAZcWLMs644Eya9sm7O5eZGv5Pg9Fgkr91VLbC7PJiSGoPCLOWVbMtPicGsCfHwCMDOisD08Gvts+FYnbf0NDekqIf4WR662I7uAUdAXlOckF04KRkZcZEBeU0i0YNTUpAcY0LXgAMfXOwIyGuevtKN6z1DiDHpsXx6ekBek0gUH2XEI9O8m7+2BWgecNDhwl7fnIhSr8liS4Nt5aGLabn4RaMW6Ca6By+0o3fQiTSzyb8wQKRWj/tP8NfhCdCkklwwg4aCSaPR+K8/gVo8Fm/OH5ySjNRYlrcYD61W4w9gA7WQsMW3C3n59DTERSorg4aUIRgxbc+gE6mxJiyekjLu15PCw9NSERdpQKvFho8uj7/HotXmxHtiBo1Cb87lZJUvY7GhcwBl13qlHo5qiVkwj89Wbkx7Y6E0MKVdt/vKEM/LTcSEpKhxvx7JQ0F6LGZmmeF0C3incvwLpYIgYFs5e7lT8Oh1Wmwo8W5aDNQ9ofg6awozEGnkJh0KPP/msopmuAKQsbjvbCsGHG5MTIrCbIWWIZYipuXiF41aoJvoiheaDaVZ0LF8AqncihnpiDHp0dg9hI8DWGZJalc6B3DmqrdB7AY2iKUg2VCSBa0GOHO1Bw2dA+N6LY9HwPZy5TWIlTMx0+VobQfaxllmiVnhFArBimk3KjimNel1/h6LgSiDtae6BTanB5NTY1CUrbwMGrmJNumxcqZ3V3qgdg/TSFe7BvCxL6bdqOCY9rEib6+yC61W1IyzzNKIMsRc0FAdf1/qAJxTPr7ag6tdg4g26rBiBjNoKDjEe4MD59vROzi+jMUhhxt7qpVb5paU4aGCFCRFG9HZb8eHtePPWBxehlipm3SGx7ShqozFxS8atUA20e3qt+PQBW9zVe4GpXAQadRhdaHvBB/A2upSEydgFk1JYYNYCppUc4Q/m2K8k34n6m80iF02TVkNYuVqYlI05kxMgEeAf2HxXh32ld9JiTVhMbPCKUiCFdNuUnhMK07+7KtphdU2vh6LW329wzbNylLszbnciPdM71QGJmORRhKzl5Ue08ZFGvDodG98M97zW9X1PtS198Ok12JVIcsQq8264kzotRpUXe9DbZt1XK8l3t+uKsxAlFEfiOER3WRahhnTMsxwuD3jzlh8r6YV/XYXchIjMUehGTQkfwadFuvEjMVx9tVt7h3CR5e7ACi/r+ITvpj23RDFtFz8ojEJVBPdXZXNcHkEFGbF4b602EANj0jWxEmL3dUtGHIof9LC4xH8EwVK7XFCyiFOym4raxpX6dAtvomgx4oyFdcgVs78ZZbOjK/Mkj8rvCQTeh3DVAqeQMe0M7PMKEhXdkxbnB2H/JRo2Jwe7K2+9x5+17oGcepKNzQKz6CRmwX5SciMi4DF5sKB8+1SD0dVPB7Bv7lGDTGt+DvsqmiGcxxllsRr8ooZ6TBHsAyx2iTFmLCkwNuPZss4FkptTjd2Vym7Bw0ph3h+2zLOcuvDM2i0Cs3aJ2UQz4vvn2tD3+C9by7bXt4EQQDm5yUiJ1HZZYjvz/dW4bDYXPjr+fFX4bgbzirQmAxvoruj4t4vNltVdHNBNFpzcxORnRCJfrsL+8/d+6SSXJxs6PZm0Jj0LG9BQbd8ehpiI/Ro6h3CiYaue3qNAbsL+856//aeYPmegFpTlAGTXova9n5UN/Xd02v0DDhwUMwKZ/kRCrJAxbTb/JtAlH/MajQa/+8xnolQse/LosnJyIiLDMjYyJexOCuwPTDJ69SVblzvGUKMSY/l05Uf0z44JQXJMSZ0DThw+OK9lVliGeLwIMbDO8qb4L7HzWXv1bTCanchKz4S8/MSAzk8opusL/GWmK5s7EVde/89vUZrnw1H67z9TdUQv5G8zcg0Y2p6rDdjsereMhZHliFW/jE7ogpHCCpjcfGLxuzG7u6me9rdfbHVirNNFhh0Gqwr4eQjhQ+tVuMvibRFBaUP/Q1iizKYQUNBF2HQ4bEib8mdbfe402/f2VYMOtzIS47GrAksbxFI5ggDls8Q+9Hc2+fzTlUznG7Bd4NgDuTwiG5pvDHtpTYrqpv6oNdq/P2ylM5bphA41dCNxu7BMf+8IAiqWhCUGzGO/OBSBzqsdolHox7ixMuawgxEGpUf0+p1WmzwlVm613LRBy+0o3fQiTSzCYtYhli1lk5NRXyUAW0WO475FgPGatuwSiDMoKFgS4k1Ycl94yuHL2bQzMtNxIQkZWfQkPwN31x2r8dsRWMv6jsGEGnQYbVKyhCLG7o+rO1Eu3V8fcPvhotfNGZiE92LbffWRFf8Y19akIrEaGOgh0cka2K247G6TrT2BfcEH0yDDhf2VvvKW6hg5wkpgxg07q1uwaDDNeafv1Hegj1ogkE8v+2saILDNfYyS+LkIyfMKVTGG9OKx+zSqalIijEFeniSyIiLxMJJ3onue1nIPn2lB9e6BxHDrPCgmJQSg9IJ8XB7BOwcR8Yi3TDocGGPCmNa8Xc5cL4dvYOOMf+8vwxxqTfLgtTJpNf5N2/cS0Zpm8WGI7Xe7EKl970k5RDPb9vvIWNxZAYNN+NTaKwvzYROq0HZtV7Ud4w9Y1E8ZlfOTEeMSR19FYfHtLsqxtfD7264+EVjNp4mui63B9vLfTuDVHRzQTRaE5OiMTc3YdxllqT2Xk0rBhxuTEiMYoNYCpnZExMwMSkKAw63v3zhaDX1DuF4vbdc4kaW3A2KRZOTkRprQs+gE4cujq0fTV27FZXXfRk0JerIoCH5C1hMq7IJP3EyaFv52Hv4iQuCqwvTVZFBI0fi8bZ1nP1OyGt/TZs/pp2bq56YdlqGGdMzzN4yS5Vjm1Tq6rfjkFiGWGXnN7qZ+Bm/V9MKq21s/Wh2lDfBIwBzJiYgNzk6GMMjuskj01JhjtCjpc+G45fHVg6/6nof6tr7YdJrVZNBQ/KXGhuBB6fc2+Yyu8uNdyq9m3Q2qWwe4/EQVcbi4hfdk3ttonu0rhPtVjsSogxY6muuShRu/JMWZ8Y+qSQXW894L9je8kjcDUqhodFosKlUnPQbW4C0vew6BAG4Pz8R2QksbxEMep0WG+6xdvcW3zllSYG3TwlRqIw3po2PMuDhqeqKaVfMSEe0UYerXYP4+GrPqH9uyOHG7mrx5pwT5sHyWFEGjDotzrdYcO4eMhZpJH9WuApjWnGz6ZYxTrTtqmyGyyOgMCsO96XFBmNoJCNF2XGYlBINm9Pjz4IcjeEZNDznUyiZ9DqsvceMRfH5K2akIzbCEPCxEd2OeJ7cXt4EzxgyFg+cb0ffkBPp5gg8MEldZYjX+qpwXGi1oqb53vqGjwYXv+ie3GsTXXGH4rpi7wFOFI5WF2XApNeitr0f1U3BO8EHS3PvEI5dZoNYkoa42+mjy11o7h0a1c94b87VmaEhN+K/76GL7egeGF2ZJbdHwPZyljwkaTCmvVmUUY9Vvt3QY1nI3n+uFf12F7ITIjEvNzFYwwt78VFGLJvuXXC9lzJldENL3xCO+vociZtr1GRdsbfMUmVjL+raR19myV8STGU7zOnWNBrNiB6Yo3W2yYJLbf0w6rVYU8QMGgot8Zjdd9Ybe4yG3eXGLl8mLCtRUag9Oj0NsRF6NPUO4UT96DMWxVh84yz1lSGOizLg0Wm+KhxjuP6Mlbru1ChkhjfRHe1NscXmxP4ab5kqXmgonJkjDFju64Mx1uwIOfA3iM1LRE4iM2gotHISozA/LxGCAH/Jsbspu9aLhk5vg9hVLG8RVAXpsZiZZYbTLWDXKEu7fnS5E20WO+IiDXh4mroyaEj+xh3TqnTBVvy9dle1wOZ0j+pnxAXBTbOyoVXZzbnciJ/PzoqmMWUs0kj+mDY3EROS1BfTpsSasOS+FACjXyi92GrF2SYLDDoN1pVw8StcbCzNgkYDnLrSjWtdg6P6GfGYWj49DXGRzKCh0CrNiUd+cjSGnO5RZyweutCB3kEn0swmLJqsrgwakr8Igw6PFXnvObaM8prc2W/H4UvezXlqvefYNKxveLBiWi5+0T3zN9G90DaqJrp7qlpgd3kwJTUGhVlxwR4ekaz5yyxVNsPhUs6kxfDyFk+o9OJL8uffnVo2utKh23zH7CoVNYiVMzEw3zbKxUlxwWFdcSZMevYIotC715h2cmoMirLVGdPOz0tEVnwkrHYX9p9ru+vz2yw2HK0Vb845YR5sD96XguQYIzr7Hfjw0ugzFukGQRD81x+xz50aiee3HeVNcI+izJIYMy0tSEVitDGoYyP5yIiL9C8GbCu/+6Ssw+VhBg1JanjG4rZRLiSI8xgbStWXQUPK8IQv3th3thUDo8hY3FnRDLdHQHFOPCanxgR7eJIQY9qugeDFtFz8onsmNtF1uoVRNdH1l0+Yna26eupEY7V4SgpSY03oGXTioK+htBJUNPaivmMAEQYtVhWmSz0cClOrCzMQadChvmMAFY29d3yuzen2X6N4cx4a64ozoddqUHW9D7Vt1js+12pzYh+zwkli9xzTzlJvTKvVavyLWKPJiNte3gSPAMzNTcDEpOhgDy/sGXRarPdl5bD04b2pvN6Hy76YdrWKs8IfmZaKuEgDWvpsOH75zmWWXG6PP6ue1+Tw49+8VNZ0181lh33lrVNiTVjMDBqSiJixeKK+G43dd85Y7Oq345Bv3oWbeEkqsyYkIC85GoMON/adbb3r88UY/AkVbywLRUzLxS8al9E20b3aNYDTV3qg1XgvUEThTqfV+P8WRrtTSQ62+f7WV7JBLEkoxqTHypm+0qF3+fs5cL4dFpsLmXERWJCfFIrhhb2kGBOWTvWWL7xbSYe91a2wOT2YlBKNYpVm0JAyjDWm1YRBTCs25j5S24E2i+22zxuRQcMJpZAR/63/eq4dfYNOiUejPGL8vULlMa1Jr8PaYl8Pv7tck4/WdaLdakdClAFLC1iGONysmJGOaKMO17oHcfpKzx2fKx5LG0uzoNdxWpGkkRkfiQcmee/v7lYOf1dlM1weAUXZcZiSFhuK4RHdRKPRYFPp6BZ6zrdYcK7FW4ZYLJeoVsNj2tFU4RgrXqVoXEbbRFfsAbBwcjLSzBGhGh6RrImTSod8O+fkbniD2E2c3CKJibWh36lsgd11+340w8tbsAdN6IgZI3crsyQujm1ScQYNKcNYY9pFk5ORHqfumDY3ORqzJybAI3j/lm+nuqkPte39MOm1WF2k3gwauZmeacbU9Fg43B68U3X3jEW6IdxiWvF33He2Ff13KLMknt/WFWfCqOdUUbiJNOr8WZB3yvjtGXD4K5dsUnE2AinDptIbpQ/vlLEo3hNuUvnGJZK/Db5j8Hh9F5p6h277PPE8/MjUNCSovAzx9EwzpmWYfTHt6Hr4jQUjGhqX0TTR9XgE/866J1g+gcivID0WM7O8ZZZ2VYyuN46UDp5vR9+QE+nmCCxkeQuS2AOTkpFujkDfkBMHzt+6dGiH1Y4PxAaxvP6E1NKpqYiPMqDNYsfRus5bPqexexCnGrqh0XDyhKQ31pg2XDKcxN/zTj0WxZvz5TPSYVZxBo0cPTGsByaN3qEL7egddCLNbPL3OVKz0px45CdHY8jpxp7qW08qWWxO7GcZ4rAnfva7q1sw5Lj15rJdlc1wugXMyDRjaro5lMMjusnKmemIMupwpWsQZ67eOmPxYqsVZ5u8GTTrSnjPQdLKSYzC/fmJEARg+23iN5fbgx0V4dW6YSzl1seKi180bndronv6Sjeu9wwhxqTH8unsEUQ03I1JJfkvfrFBLMmJTqvBxll3Lh26s8J7XSrJicekFHU2iJUrk16HdcXe8gy3+3zEMqoLJyUjIy4yZGMjup2xxLQrZoRHTLumKANGvRaX2vpR02y56fsOl8efQfM4F7FDbn2JNyYrv9aLyx23z1ikkbac8V5/wiWm1Wg0/vPb7a7Je6paYHd5MCU1BoVZLEMcrublJiI7IRL9dhf2n7t1P5pw2wRC8hZt0mPVTLG0663nVMRjdmlBKhJVnkFDynC3HotHajvR2W9HUrQRSwpSQj08SYgxbUVj4GNaLn7RuN2tia44Yb6mMAORRl2oh0cka+uKM6HXalDd1IdLbVaph3Nbnf12HL7ozaB5YjYnt0gexKDx8MUOdPbbb/q+eAMULrul5Eb8fN6raYXVNrIfjSAI2FbumzzhOYVkYrQx7erC9LCJaeMiDVg+PQ0AsOUWOzEPXWxHz6ATqbEmLJ4SHjfncpISa8JDvoxFJfWQlVJXvx2HL3ozxp8Io8n7jaVZ0GiAE/XdaOwevOn74vnt8dksQxzOtFqNv0zmrRYS6tqtqLzeB71Wg/Ul6u5BQ8oh3ku8W9UMm3NkxqLL7fH3A+M9IcnFqsIMRBp0qO8cQHlj703fF1sDrCvJhCFM+ioGM6YNj39BCqo7NdEdcrixp5rlE4huJynGhKVTvQ2lg5HeGyg7K7wNYouz4zA5lQ1iSR4mp8agOCceLo+AnRUj+52ca7bgfIsFRp0Wa9mDRhJF2XGYnBoDm9NzU5mlj6/24GrXIKKNurDJoCH5G3VMG0YT5sCNGH5XZTMcLs+I74mxy8YwyaCRI/F43F7WBM8deiySlxjTFmXHYUpa+MS0mfGReGBSEgD4J4JFV7sGcPpKD7Qa798yhTcxi/dobQfaLLYR3xOzJpcUpCIpxhTysRHdyv15SciKj4TV5sL759pGfO9oXSfarXYkRBmwtCBVohESjRRj0mPVTO898CfnAfsGnf7jOOzuOYIU03LxiwLi8ds00X2vxvv/OYmRmJubINXwiGTNf4K/TZklOdg2bDcokZw8cZva0OLE9bLpqYiPYnkLKWg0mhulXc+MnGgTP6/VhRmIMupDPjai2xldTJso1fAksXhyMlJiTegecPgzZgCge8CBQ77/3xRmN+dy8si0VJgj9Gjus+FE/c0ZizSSP+s4DI/ZG2WWRvbwEzN8Fk1JQZo5QpKxkXxMTIrG3NwEeISRC6Vuj4Dt5WIvdy6Sknx4MxZ994Rln7wn9B7D60uyYNRzCpzkQ5xbe6dyZMbiu9XezWYFabGYkRlefRWHx7THAxjT8i+fAqLkNk10xQvPplKWTyC6naVTUxAfZUC71Y6jdZ1SD+cmF1otqGn2NohdW8TyFiQvjxVlwqDT4FyLN9MLAJxuD3ZWeG90NpWG3+SWnGwozYRGA5y60o1rXd4ySzanG7urvLECJ8xJbu4W024szYY2zDKc9DotNvjKWw2fVNpV0QSnW8DMLDMK0sMng0ZuIgw6PObrsbiFpQ/v6GKrFWebfDFtcfjFtCtmpCPKqMOVrkGcudoDAPB4hGE9nLigQV7+0odnbiyUHqvrRJvFjrhIg79yCZFciFmrH17qQLsvY9Fic2J/jTdrfxPPbyQz9+cnISMuAhabCwfO39hcJm4SfXx2VtjNo0cYdP74LJCVsbj4RQExvImueIC29A35J/LDcWcd0WiZ9DqsC8IJPlDEMT08NRUJbBBLMpMQbcQjU739aMRj9cNLHejsdyAp2oiHwqRBrFxlxEVi0eRkADcmzd+raYXV7kJWfCTm54VXBg3J391j2vCcPBH/TQ5eaEfPgAPAsL6KjPMlNzxjcWBYxiKNJF6HlhakIjEMY9pokx6rZo4s7XrqSjeu9wwhxqTH8uksQ0xea4oyYNJrUdvej+qmPgA3jpl1xZkw6cOj7yUpR35KDGZNiIdHAHb4NkHurmqB3eXBlNQYFGbFSTxCopF0Wo1/0VY8v9Z39KPsWi+0GmBDSXjfc+z9RBWO8eDiFwWM2ET3ZIO3ie6O8mYIAjAvNxETkqKkHh6RrImTFu/VtMJic0o8mhu8DWK9vZQ4uUVyJQZIOyqa4XJ7sG1YeYtwaRArZ/4yS+Xe3cPb/BPmWWGXQUPKcLuYdm5uAiYmRUs9PElMTTdjRqYZTreAd6qacanNiuqmPui1Gv8GHpLOrAnxyEuOxqDDjb1nW6Uejix5Y1rf9SeMy3g/7itX925VC2xOtz/ra01hBiKNXNAgL3OEAct9PVm3lTXBanPivRr2cid5u7F5qcl3z3GjdUO4ZdCQMojH7AeXOtBhtfvjlAfvS0FqmJYhLs3xxrRDTjferwlMTKvKGaGf/OQnyM3NRUREBObPn49Tp07d8fl/+ctfMHXqVERERKCwsBB79uwJ0UjV5ZNNdLeW3UjVJKI7K8qOw+TUGNhdHuyparn7D4TIkdpOdPbbkRhtxBI2iCWZWlKQgqRoIzr77Xi3quVGg1hef2RhxYx0xJj0aOwewu7qFhyp7QDAkockX7eNacP8mH18WBksfwbN1FQkxZikHBZB7LF46x6Y5HWkrhMdVjsSogxYGsYx7f15SciKj4TV5sKuymbsqeaCBt2aeE7ZWdGEXZXNsDk9mJQSjeJsZtCQPD1WlAmjXouLbVbsPduK01d6oNXcKIlIJDeTUmJQkhMPt0fAjvKmYZtEw/eaPDymfacyMHOjqlv8+tOf/oQXX3wRr7zyCsrKylBcXIwVK1agvb39ls//6KOP8JnPfAZf+MIXUF5ejg0bNmDDhg04e/ZsiEeuDuIf6GtH6lHX3o8IgxarCzMkHhWR/HlP8GIT6qa7PDt0hpe3YINYkiuDTot1vn403915Fg63B1PTYzEjkzfnchBp1GF1oXf38EvbquERgDkTE5CbHJ4ZNKQMn4xpTXotVheFd0y7viQTeq0Gldf78IeT1wCE98253GyclQ2NBjhe34XrPYNSD0d2hmeFh3NMq9Vq/L1vvvfuOfTbXZiQGIW5uQkSj4zkZvGUFKTGmtAz6MT3914AwAwakre4SAMene4th//trVUAgEVTUpAWphk0pAzi5pP/OliLpt4hxEbo/cdxuBJj2lNXugPyeqqL+n70ox/h+eefxzPPPIPp06fj5z//OaKiovDGG2/c8vk//vGPsXLlSnzzm9/EtGnT8L3vfQ+zZs3C//zP/4R45Oqwcqa3ia7V5q3LuWJGOmIjDBKPikgZxDJLp65041qX9JMWfUNO7Pdl0DzB3aAkc+IErHj94TErL5/8fLjDnOTuVjGtOcxj2qQYkz8L3GpzIT7KgIenhm8GjdxkxUdiQb43Y3FHuXw2UsmBxebEfrFkGxds/ZnX4vlt06wsLmjQTYb3o7HaXNAwg4YU4IlP3nOEaa9WUo61RRkw6rT+Y/axogxEGMK7DPHwmDYQ9AF7JRlwOBw4c+YMXnrpJf9jWq0Wy5Ytw/Hjx2/5M8ePH8eLL7444rEVK1Zgx44dt30fu90Ou93u/3+LxTK+gatIlNHbRFfMFmFJI6LRS4+LwKLJyThS24mv/alc8qyINosNDpcH96XFYEamWdKxEN3NjEwzCtJicbHNCp1W488EI3mYm5uI7IRIXO8ZglHPrHCSv5tjWk6eAN5JpL+e926MYVa4/GyalY2PLnfh18evor5zQOrhyEabxQa7y4MpqTGYmcWYNi85GrMmxKPsWi8AYFMp79np1jbNysYvPqwHACyclIyMuEiJR0R0Z4unJCM5xoTOfjtiTHosn54u9ZCI7ig+yohHpqX6e7Zyk47X47OycfRcY0BeS1WLX52dnXC73UhLG5kemJaWhgsXLtzyZ1pbW2/5/NbW2zdVe/XVV/HP//zP4x+wSj01Nwdby64j0zeRT0Sj96k5OThS24mya73+G1KpfWp2DneDkuxpNBo8OTcH33v3HJYWpCI1luUt5ESr1eDJOTn40fuXsHpmOuIiwzuDhpSBMe3NHp6WiqRoI7oGHPjU7Byph0OfsGpmOv7Prhp0WO2yKqMtF5+aw5Jtoqfm5qDsWi8W5CdhQlKU1MMhmSpIj0VxTjwqG3vx5Fye80n+9DotHp+dhV98UI91JZmINIZ3Bg0pw5Nzc7D3bCvyU6IxeyLLEAPeKhz/aAzMJjtVLX6FyksvvTQiW8xisSAnh4GAaF5eIt58Zi5yEqKg0/Lmgmgs1hZlwOX2oLPffvcnh0BshIE7T0gxnn4gF8kxRk5Sy9QLSyYhJzESD08N7xrmpBzDY1q9jhlOAGDS6/CH5+9Hu9WGwmz2VZSbaJMev3tuPk41dEk9FNlhTDvSk3NyEG3SY25uotRDIZn76WdnoaqxFytnMoOGlOHry+5DQVosVszgMUvKsLQgFa9vnoMpaTHcpOMTbdLjy0sm4Ws/GP9rqWrxKzk5GTqdDm1tbSMeb2trQ3r6rU966enpY3o+AJhMJphMpvEPWMWWFrD+P9G90Gg0LBdKdI90Wg3Wl7A0mVwZdFpsZGklUhjGtDcrSI9FQXqs1MOg2yjJiUdJTrzUwyCZ02g0eKyIJaLp7rLiI5EVz3KHpBwRBh3nVEhxlk3nBtFPemZhPr4WgNdR1RZGo9GI2bNn48CBA/7HPB4PDhw4gAULFtzyZxYsWDDi+QDw/vvv3/b5REREREREREREREREJF+qyvwCgBdffBGf//znMWfOHMybNw//+Z//iYGBATzzzDMAgM2bNyMrKwuvvvoqAOCrX/0qHnroIfzwhz/EmjVr8Pbbb+Pjjz/GL3/5y1G/pyAIALzlD4mIiIiIiIiIiIiIiGjsxHUWcd3lXqlu8eupp55CR0cHXn75ZbS2tqKkpAT79u1DWpo3ffDatWvQam8kvD3wwAP4wx/+gH/6p3/CP/7jP2LKlCnYsWMHZs6cOer3tFqtAMC+X0RERERERERERERERONktVoRF3fvvYY1wniXzwgejwfNzc2IjY1lYzoaN4vFgpycHDQ2NsJsNks9HKKA4bFNasVjm9SKxzapGY9vUise26RWPLZJrXhsk1qN59gWBAFWqxWZmZkjEpnGSnWZX1LQarXIzmYzRQoss9nMix6pEo9tUise26RWPLZJzXh8k1rx2Ca14rFNasVjm9TqXo/t8WR8ie592YyIiIiIiIiIiIiIiIhIZrj4RURERERERERERERERKrBxS8imTGZTHjllVdgMpmkHgpRQPHYJrXisU1qxWOb1IzHN6kVj21SKx7bpFY8tkmt5HBsawRBECR7dyIiIiIiIiIiIiIiIqIAYuYXERERERERERERERERqQYXv4iIiIiIiIiIiIiIiEg1uPhFREREREREREREREREqsHFLyIiIiIiIiIiIiIiIlINLn4RBcH/+T//BxqNZsTX1KlT/d+32Wz4yle+gqSkJMTExODxxx9HW1vbiNe4du0a1qxZg6ioKKSmpuKb3/wmXC7XiOccPnwYs2bNgslkwuTJk/HWW2+F4tejMPLhhx9i7dq1yMzMhEajwY4dO0Z8XxAEvPzyy8jIyEBkZCSWLVuG2traEc/p7u7GZz/7WZjNZsTHx+MLX/gC+vv7RzynqqoKixcvRkREBHJycvCDH/zgprH85S9/wdSpUxEREYHCwkLs2bMn4L8vhY+7HdtPP/30TefxlStXjngOj22So1dffRVz585FbGwsUlNTsWHDBly8eHHEc0IZh/zkJz9Bbm4uIiIiMH/+fJw6dSrgvzOFh9Ec20uWLLnp3P2lL31pxHN4bJPc/OxnP0NRURHMZjPMZjMWLFiAvXv3+r/PczYp1d2ObZ6zSS2+//3vQ6PR4Gtf+5r/MZ67SQ1udWwr7twtEFHAvfLKK8KMGTOElpYW/1dHR4f/+1/60peEnJwc4cCBA8LHH38s3H///cIDDzzg/77L5RJmzpwpLFu2TCgvLxf27NkjJCcnCy+99JL/OfX19UJUVJTw4osvCufOnRP++7//W9DpdMK+fftC+ruSuu3Zs0f43//7fwvbtm0TAAjbt28f8f3vf//7QlxcnLBjxw6hsrJSWLdunZCXlycMDQ35n7Ny5UqhuLhYOHHihHDkyBFh8uTJwmc+8xn/9/v6+oS0tDThs5/9rHD27Fnhj3/8oxAZGSn84he/8D/n2LFjgk6nE37wgx8I586dE/7pn/5JMBgMQnV1ddD/DUid7nZsf/7znxdWrlw54jze3d094jk8tkmOVqxYIbz55pvC2bNnhYqKCmH16tXChAkThP7+fv9zQhWHvP3224LRaBTeeOMNoaamRnj++eeF+Ph4oa2tLTT/GKQqozm2H3roIeH5558fce7u6+vzf5/HNsnRrl27hN27dwuXLl0SLl68KPzjP/6jYDAYhLNnzwqCwHM2Kdfdjm2es0kNTp06JeTm5gpFRUXCV7/6Vf/jPHeT0t3u2FbauZuLX0RB8MorrwjFxcW3/F5vb69gMBiEv/zlL/7Hzp8/LwAQjh8/LgiCd1JWq9UKra2t/uf87Gc/E8xms2C32wVBEIRvfetbwowZM0a89lNPPSWsWLEiwL8NkdcnFwg8Ho+Qnp4u/Nu//Zv/sd7eXsFkMgl//OMfBUEQhHPnzgkAhNOnT/ufs3fvXkGj0QhNTU2CIAjCT3/6UyEhIcF/bAuCIHz7298WCgoK/P//5JNPCmvWrBkxnvnz5wv/63/9r4D+jhSebrf4tX79+tv+DI9tUor29nYBgPDBBx8IghDaOGTevHnCV77yFf//u91uITMzU3j11VcD/4tS2PnksS0I3pvx4Tfnn8Rjm5QiISFBeP3113nOJtURj21B4DmblM9qtQpTpkwR3n///RHHM8/dpHS3O7YFQXnnbpY9JAqS2tpaZGZmIj8/H5/97Gdx7do1AMCZM2fgdDqxbNky/3OnTp2KCRMm4Pjx4wCA48ePo7CwEGlpaf7nrFixAhaLBTU1Nf7nDH8N8TniaxAFW0NDA1pbW0cch3FxcZg/f/6IYzk+Ph5z5szxP2fZsmXQarU4efKk/zkPPvggjEaj/zkrVqzAxYsX0dPT438Oj3cKtcOHDyM1NRUFBQV44YUX0NXV5f8ej21Sir6+PgBAYmIigNDFIQ6HA2fOnBnxHK1Wi2XLlvH4poD45LEt+v3vf4/k5GTMnDkTL730EgYHB/3f47FNcud2u/H2229jYGAACxYs4DmbVOOTx7aI52xSsq985StYs2bNTccgz92kdLc7tkVKOnfrx/RsIhqV+fPn46233kJBQQFaWlrwz//8z1i8eDHOnj2L1tZWGI1GxMfHj/iZtLQ0tLa2AgBaW1tHnCTE74vfu9NzLBYLhoaGEBkZGaTfjshLPBZvdRwOP05TU1NHfF+v1yMxMXHEc/Ly8m56DfF7CQkJtz3exdcgCrSVK1di06ZNyMvLw+XLl/GP//iPWLVqFY4fPw6dTsdjmxTB4/Hga1/7GhYuXIiZM2cCQMjikJ6eHrjd7ls+58KFCwH7HSk83erYBoC/+Zu/wcSJE5GZmYmqqip8+9vfxsWLF7Ft2zYAPLZJvqqrq7FgwQLYbDbExMRg+/btmD59OioqKnjOJkW73bEN8JxNyvb222+jrKwMp0+fvul7jLdJye50bAPKO3dz8YsoCFatWuX/76KiIsyfPx8TJ07En//8Zy5KEREpwKc//Wn/fxcWFqKoqAiTJk3C4cOH8cgjj0g4MqLR+8pXvoKzZ8/i6NGjUg+FKKBud2x/8Ytf9P93YWEhMjIy8Mgjj+Dy5cuYNGlSqIdJNGoFBQWoqKhAX18ftmzZgs9//vP44IMPpB4W0bjd7tiePn06z9mkWI2NjfjqV7+K999/HxEREVIPhyhgRnNsK+3czbKHRCEQHx+P++67D3V1dUhPT4fD4UBvb++I57S1tSE9PR0AkJ6ejra2tpu+L37vTs8xm81cYKOQEI/FWx2Hw4/T9vb2Ed93uVzo7u4OyPEufp8o2PLz85GcnIy6ujoAPLZJ/v7u7/4O7777Lg4dOoTs7Gz/46GKQ5KTk6HT6Xh8U8Dd7ti+lfnz5wPAiHM3j22SI6PRiMmTJ2P27Nl49dVXUVxcjB//+Mc8Z5Pi3e7YvhWes0kpzpw5g/b2dsyaNQt6vR56vR4ffPAB/uu//gt6vR5paWk8d5Mi3e3YdrvdN/2M3M/dXPwiCoH+/n5cvnwZGRkZmD17NgwGAw4cOOD//sWLF3Ht2jV/7esFCxagurp6xMTq+++/D7PZ7C8RsGDBghGvIT5neP1somDKy8tDenr6iOPQYrHg5MmTI47l3t5enDlzxv+cgwcPwuPx+C+QCxYswIcffgin0+l/zvvvv4+CggIkJCT4n8PjnaR0/fp1dHV1ISMjAwCPbZIvQRDwd3/3d9i+fTsOHjx4U+nNUMUhRqMRs2fPHvEcj8eDAwcO8Pime3K3Y/tWKioqAGDEuZvHNimBx+OB3W7nOZtURzy2b4XnbFKKRx55BNXV1aioqPB/zZkzB5/97Gf9/81zNynR3Y5tnU5308/I/twtEFHAfeMb3xAOHz4sNDQ0CMeOHROWLVsmJCcnC+3t7YIgCMKXvvQlYcKECcLBgweFjz/+WFiwYIGwYMEC/8+7XC5h5syZwvLly4WKigph3759QkpKivDSSy/5n1NfXy9ERUUJ3/zmN4Xz588LP/nJTwSdTifs27cv5L8vqZfVahXKy8uF8vJyAYDwox/9SCgvLxeuXr0qCIIgfP/73xfi4+OFnTt3ClVVVcL69euFvLw8YWhoyP8aK1euFEpLS4WTJ08KR48eFaZMmSJ85jOf8X+/t7dXSEtLE/72b/9WOHv2rPD2228LUVFRwi9+8Qv/c44dOybo9Xrh3//934Xz588Lr7zyimAwGITq6urQ/WOQqtzp2LZarcI//MM/CMePHxcaGhqEv/71r8KsWbOEKVOmCDabzf8aPLZJjl544QUhLi5OOHz4sNDS0uL/Ghwc9D8nVHHI22+/LZhMJuGtt94Szp07J3zxi18U4uPjhdbW1tD8Y5Cq3O3YrqurE/7lX/5F+Pjjj4WGhgZh586dQn5+vvDggw/6X4PHNsnRd77zHeGDDz4QGhoahKqqKuE73/mOoNFohP379wuCwHM2Kdedjm2es0ltHnroIeGrX/2q//957ia1GH5sK/HczcUvoiB46qmnhIyMDMFoNApZWVnCU089JdTV1fm/PzQ0JHz5y18WEhIShKioKGHjxo1CS0vLiNe4cuWKsGrVKiEyMlJITk4WvvGNbwhOp3PEcw4dOiSUlJQIRqNRyM/PF958881Q/HoURg4dOiQAuOnr85//vCAIguDxeITvfve7QlpammAymYRHHnlEuHjx4ojX6OrqEj7zmc8IMTExgtlsFp555hnBarWOeE5lZaWwaNEiwWQyCVlZWcL3v//9m8by5z//WbjvvvsEo9EozJgxQ9i9e3fQfm9Svzsd24ODg8Ly5cuFlJQUwWAwCBMnThSef/75m4IsHtskR7c6rgGMiBFCGYf893//tzBhwgTBaDQK8+bNE06cOBGMX5vCwN2O7WvXrgkPPvigkJiYKJhMJmHy5MnCN7/5TaGvr2/E6/DYJrl59tlnhYkTJwpGo1FISUkRHnnkEf/ClyDwnE3Kdadjm+dsUptPLn7x3E1qMfzYVuK5WyMIgjC2XDEiIiIiIiIiIiIiIiIieWLPLyIiIiIiIiIiIiIiIlINLn4RERERERERERERERGRanDxi4iIiIiIiIiIiIiIiFSDi19ERERERERERERERESkGlz8IiIiIiIiIiIiIiIiItXg4hcRERERERERERERERGpBhe/iIiIiIiIiIiIiIiISDW4+EVERERERERERERERESqwcUvIiIiIiIiIiIiIiIiUg0ufhEREREREREREREREZFqcPGLiIiIiIiIiIiIiIiIVIOLX0RERERERERERERERKQaXPwiIiIiIiIiIiIiIiIi1eDiFxEREREREREREREREakGF7+IiIiIiIiIiIiIiIhINbj4RURERERERERERERERKrBxS8iIiIiIiIiIiIiIiJSDS5+ERERERERERERERERkWpw8YuIiIiIiIiIiIiIiIhUg4tfREREREREREREREREpBpc/CIiIiIiIiIiIiIiIiLV4OIXERERERERERERERERqQYXv4iIiIiIiIiIiIiIiEg1uPhFREREREREREREREREqsHFLyIiIiIiIiIiIiIiIlINLn4RERERERERERERERGRanDxi4iIiIiIiIiIiIiIiFSDi19ERERERERERERERESkGlz8IiIiIiIiIiIiIiIiItXg4hcRERERERERERERERGpBhe/iIiIiIiIiIiIiIiISDW4+EVERERERERERERERESqwcUvIiIiIiIiIiIiIiIiUg0ufhEREREREREREREREZFqcPGLiIiIiIiIiIiIiIiIVIOLX0RERERERERERERERKQaeqkHoAYejwfNzc2IjY2FRqORejhERERERERERERERESKIwgCrFYrMjMzodXee/4WF78CoLm5GTk5OVIPg4iIiIiIiIiIiIiISPEaGxuRnZ19zz/Pxa8AiI2NBeD9MMxms8SjISIiIiIiIiIiIiIiUh6LxYKcnBz/usu94uJXAIilDs1mMxe/iIiIiIiIiIiIiIiIxmG8Laa4+EVERKRAjd2DcHkE5CVHSz0UWekddGDI6ZZ6GAAAc4QB0SaGWkREREREREREocYZGSIiIgX68YFabC27jkenpeH5B/MxZ2LCuHfEKJUgCDh+uQuvHanHoYsdUg/Hz6TX4nsbZuLJOewLSkREREREREQUSlz8IiIiUhhBEDBgd0EQgP3n2rD/XBuKc+Lx/OI8rJyRDr1OK/UQQ8Lp9uDdqma89mEDzrVY/I8bZfD7CxBgd3nwrS1V6LDa8eUlk8J2cZKIiIiIiIiIKNQ0giAIUg9C6SwWC+Li4tDX18eeX0REFDJ17f341dF6bC1rgsPlAQBkJ0TimYV5eGpuDmJUWnLPYnPijyev4a2PrqClzwYAiDBo8eScHDy7MA+5MigFKQgC/t++i/j5B5cBAJ9fMBEvr50BnZYLYEREREREREREtxOo9RYufgUAF7+IiEhKnf12/Pb4Vfz2xFV0DzgAALERevzN/Al4+oFcZMRFSjzCwGjsHsSbx67gT6evYcDh7euVHGPC0w9MxGfnT0RCtFHiEd7sjaMN+Jd3zwEA1hRm4IdPFiPCoJN4VERERERERERE8sTFLxnh4hcREcmBzenGtrImvH6kHvWdAwAAvVaDtcWZeG5xHmZkxkk8wntT2diL147UY+/ZVrg93rDlvrQYPLc4H+tLMmHSy3sxaVdlM77x5wo43QLuz0/ELzfPgTnCIPWwiIiIiIiIiIhkh4tfMsLFLyIikhOPR8DBC+147Ug9TjZ0+x9/YFISnn8wH0vuS5F9/ymPR8Bfz7fh9SMNOHXlxu+waHIynn8wHw9OSZb97zDcR3Wd+OJvz6Df7sLU9Fj8+tl5SDNHSD0sIiIiIiIiIiJZ4eKXjHDxi4iI5Krqei9eP9KA3dUt/qypKakxeG5xHtaXZMmuBN+Qw42tZdfxq6MNaPBlrxl0vuy1RfmYnqnc6+zZpj48/eZpdPbbkRUfid98YR4mpcRIPSwiIiIiIiIiItng4peMcPGLiIjkrql3CG8ebcDbpxvRb3cBAJJjjNi8IBefu38iEiXul9VhteO3x6/gtyeuomfQCQAwR+jx2fsn4vMLcpEep44sqcbuQWx+4xQaOgeQEGXAG0/PRemEBKmHRUREREREREQkC1z8khEufhERkVJYbE786VQj3jzWgOY+GwAgwqDFE7Oz8YVF+chLjg7peGrbrHj9SAO2VzTB4fIAAHISI/Hswjw8OScH0SZ9SMcTCl39djz71mlUXu9DhEGLn352Fh6emib1sIiIiIiIiIiIJMfFLxnh4hcRESmN0+3BnuoWvHakHmebLAAAjQZYNi0Nzy/Ox9zchKD11BIEAccvd+G1I/U4dLHD/3hJTjy++GA+lk9Pg16nDcp7y8WA3YUv/74MH1zqgE6rwaubCvHknByph0VEREREREREJCkufskIF7+IiEipBEHAifpuvH6kHgcutPsfL86Ow3OL87FqZnrAFqKcbg/erWrGax824FzLjQW35dO9C26zJwZvwU2OnG4Pvr21CtvKmgAA31xRgC8vmRRW/wZERERERERERMNx8UtGuPhFRERqUNduxa+ONmBr2Y0ShFnxkXh2UR6empuDmHssQdg35MTbp67hzWNX0Gq5UWrxyTk5eHZhHnJDXGpRTgRBwP/bdxE//+AyAODzCybi5bUzoNNyAYyIiIiIiIiIwg8Xv2SEi19ERKQmnf12/Pb4Vfz2xFV0DzgAALERevzNvAl4emEuMuIiR/U6jd2DePPYFfzp9DUMONwAgOQYE55+YCI+O38iEqKNQfsdlOaNow343u5zEARgTWEGfvhkMSIMOqmHRUREREREREQUUlz8khEufhERkRrZnG5sK2vC60fqUd85AADQazV4rCgDzy3Ox8ysuFv+XEVjL147Uo+91S3w+KKM+9Ji8NzifKwvyYRJz0WdW3mnshkv/rkCTreA+/MT8cvNc2COMEg9LCIiIiIiIiKikOHil4xw8YuIiNTM4xFw8EI7XjtSj5MN3f7HH5iUhOcX5+Oh+1IAAH8934bXjzTg1JUbz1k0ORnPP5iPB6cks5fVKHxU14kv/vYM+u0uTE2Pxa+fnYc0c4TUwyIiIiIiIiIiCgkufskIF7+IiChcVF3vxetHGrC7ugVuX1rX5NQYuD0CGnzZYQadBmuLM/HconxMz+R1caxqmvvw9Jun0WG1Iys+Er/5wjxMSomRelhEREREREREREHHxS8Z4eIXERGFm6beIbx5tAFvn25Ev90FADBH6PHZ+yfi8wtykR7HbKXxaOwexOY3TqGhcwAJUQa88fRclE5IkHpYRERERERERERBxcUvGeHiFxERhSuLzYldFc3QaTVYV5yJaJNe6iGpRle/Hc++dRqV1/sQYdDip5+dhYenpkk9LCIiIiIiIiKioAnUeos2gGMKiZ/85CfIzc1FREQE5s+fj1OnTt32uUuWLIFGo7npa82aNf7nCIKAl19+GRkZGYiMjMSyZctQW1sbil+FiIhI8cwRBnzu/on4zLwJXPgKsKQYE/7w/P1YUpACm9OD539zBn/+uFHqYRERERERERERyZ6iFr/+9Kc/4cUXX8Qrr7yCsrIyFBcXY8WKFWhvb7/l87dt24aWlhb/19mzZ6HT6fCpT33K/5wf/OAH+K//+i/8/Oc/x8mTJxEdHY0VK1bAZrOF6tciIiIiuqVokx6vbZ6Dx2dlw+0R8K0tVfjJoTowcZ+IiIiIiIiI6PYUVfZw/vz5mDt3Lv7nf/4HAODxeJCTk4O///u/x3e+8527/vx//ud/4uWXX0ZLSwuio6MhCAIyMzPxjW98A//wD/8AAOjr60NaWhreeustfPrTnx7VuFj2kIiIiIJJEAT84L2L+NnhywCAzy+YiJfXzoBOq5F4ZEREREREREREgRN2ZQ8dDgfOnDmDZcuW+R/TarVYtmwZjh8/PqrX+NWvfoVPf/rTiI6OBgA0NDSgtbV1xGvGxcVh/vz5o35NIiIiomDTaDT49sqpeGXtdGg0wK+PX8X/98dy2JxuqYdGRERERERERCQ7iln86uzshNvtRlrayEbvaWlpaG1tvevPnzp1CmfPnsVzzz3nf0z8ubG+pt1uh8ViGfFFREREFGzPLMzDf326FEadFrurW/D0m6dgsTmlHhYRERERERERkawoZvFrvH71q1+hsLAQ8+bNG/drvfrqq4iLi/N/5eTkBGCERERERHe3tjgTbz0zFzEmPU7Ud+PJnx9Hm4W9SomIiIiIiIiIRIpZ/EpOToZOp0NbW9uIx9va2pCenn7Hnx0YGMDbb7+NL3zhCyMeF39urK/50ksvoa+vz//V2Ng4ll+FiIiIaFwemJyMP/2v+5ESa8KFVis2/fQjXO7ol3pYRERERERERESyoJjFL6PRiNmzZ+PAgQP+xzweDw4cOIAFCxbc8Wf/8pe/wG6343Of+9yIx/Py8pCenj7iNS0WC06ePHnH1zSZTDCbzSO+iIiIiEJpRmYctr3wAPKSo9HUO4QnfvYRyq/1SD0sIiIiIiIiIiLJKWbxCwBefPFFvPbaa/j1r3+N8+fP44UXXsDAwACeeeYZAMDmzZvx0ksv3fRzv/rVr7BhwwYkJSWNeFyj0eBrX/sa/vVf/xW7du1CdXU1Nm/ejMzMTGzYsCEUvxIRERHRPctJjMKWLy1AcXYcegad+MxrJ3DwQtvdf5CIiIiIiIiISMX0Ug9gLJ566il0dHTg5ZdfRmtrK0pKSrBv3z6kpaUBAK5duwatduR63sWLF3H06FHs37//lq/5rW99CwMDA/jiF7+I3t5eLFq0CPv27UNERETQfx8iIiKi8UqKMeGPX7wfX/59GQ5f7MDzvzmDVzcV4sk57ElKREREREREROFJIwiCIPUglM5isSAuLg59fX0sgUhERESScLo9+M7Wamwtuw4A+OaKAnx5ySRoNBqJR0ZERERERERENDqBWm9RVNlDIiIiIro1g06Lf/9UEV5YMgkA8G/vXcT/2VUDt4f7nIiIiIiIiIgovHDxi4iIiEglNBoNvr1yKl5ZOx0aDfDr41fx//2xHDanW+qhERERERERERGFTMB7fpWWlo66vE5ZWVmg356IiIgo7D2zMA8psSa8+KdK7K5uQdeAHb/cPAfmCIPUQyMiIiIiIiIiCrqAL35t2LDB/982mw0//elPMX36dCxYsAAAcOLECdTU1ODLX/5yoN+aiIiIiHweK8pEYpQRX/ztGZyo78aTPz+OXz87D2nmCKmHRkREREREREQUVBpBEILWCOK5555DRkYGvve97414/JVXXkFjYyPeeOONYL11SAWqARsRERFRoNU09+HpN0+jw2pHVnwkfvOFeZiUEiP1sIiIiIiIiIiIbhKo9ZagLn7FxcXh448/xpQpU0Y8Xltbizlz5qCvry9Ybx1SXPwiIiIiOWvsHsTmN06hoXMACVEGvPH0XJROSJB6WEREREREREREIwRqvUUbwDHdJDIyEseOHbvp8WPHjiEigiV3iIiIiEIhJzEKW760AMU58egZdOIzr53AwQttUg+LiIiIiIiIiCgoAt7za7ivfe1reOGFF1BWVoZ58+YBAE6ePIk33ngD3/3ud4P51kREREQ0TFKMCX98fj6+/PsyHL7Yged/cwavbirEk3NypB4aEREREREREVFABbXsIQD8+c9/xo9//GOcP38eADBt2jR89atfxZNPPhnMtw0plj0kIiIipXC6PfjO1mpsLbsOAPjmigJ8eckkaDQaiUdGREREREREROFOET2/wgUXv4iIiEhJBEHAD967iJ8dvgwA+PyCiXh57QzotFwAIyIiIiIiIiLpBGq9JahlD0UOhwPt7e3weDwjHp8wYUIo3p6IiIiIhtFoNPj2yqlIjTXhX949h18fv4qOfjt+9GQJIgw6qYdHRERERERERDQuQV38qq2txbPPPouPPvpoxOOCIECj0cDtdgfz7YmIiIjoDp5ZmIeUWBNe/FMl9lS3onvgFH65eQ7MEQaph0ZEREREREREdM+Cuvj19NNPQ6/X491330VGRgZ7SRARERHJzGNFmUiMMuKLvz2DE/XdePLnx/HrZ+chzRwh9dCIiIiIiIiIiO5JUHt+RUdH48yZM5g6dWqw3kIW2POLiIiIlK6muQ9Pv3kaHVY7suIj8ZsvzMOklBiph0VEREREREREYSRQ6y3aAI7pJtOnT0dnZ2cw34KIiIiIAmBGZhy2vfAA8pKj0dQ7hCd+9hHKrvVIPSwiIiIiIiIiojEL6uLX//t//w/f+ta3cPjwYXR1dcFisYz4IiIiIiL5yEmMwpYvLUBxTjx6Bp34m9dO4OCFNqmHRUREREREREQ0JkEte6jVetfWPtnrSxAEaDQauN3uYL11SLHsIREREanJoMOFL/++DIcvdkCn1eDVjYV4cm6O1MMiIiIiIiIiIpUL1HqLPoBjusmhQ4eC+fJEREREFARRRj1e2zwH39laja1l1/GtrVVot9rwlaWTb9rURKRWHo+AqqY+JEYZMSEpSurhEI1KXXs/bE43ZmSaeb6WoZrmPtR3DEg9DNmJidBj4aRkGPVBLU5EREREYSaoi18PPfRQMF+eiIiIiILEoNPi3z9VhFSzCT87fBn/vv8S2q12vLJ2BnRaTqiSetmcbmwvb8LrR+pxuWMAGg3wyNQ0fPHBfMzNTeCCAsmOIAj44FIHXj/SgKN13p7bM7PMeH5xPlYXZsCg44KClDweAQcutOO1I/U41dAt9XBkK81swtMP5OFv5k9AXKRB6uEQERGRCgS17CEAHDlyBL/4xS9QX1+Pv/zlL8jKysJvf/tb5OXlYdGiRcF865Bh2UMiIiJSszePNeBf3j0HQQBWF6bjR0+WIMKgk3pYRAHV1W/H705cw2+OX0HXgAMAEGnQYch5o1R7cXYcnlucj1Uz06HnggJJzO5yY2d5M14/Wo9Lbf0AAK3Gu3nB7vIAADLjIvD0wlx8et4EmCO4oBBKNqcbW8uu41dHGlDf6c320ms1KJ0Qz00kn3C5YwAdVjsAIMqow1Nzc/DswjzkJDLrloiIKBwFar0lqItfW7duxd/+7d/is5/9LH7729/i3LlzyM/Px//8z/9gz5492LNnT7DeOqS4+EVERERq925VM178UyUcbg/m5yXil5vncGc2qcLljn786mgDtp657l8wyIqPxDMLc/HU3By0WWze75c1wTHs+88uysNTc3MQYwpqMQ2im/QMOPD7k1fx6+NX/QsG0UYdnpo7Ac8szEW0SY/fnbiK3xy/gs5+70JujEmPT8/NwTOL8pAVHynl8FWvs9+O3xy/it+duIpu30J6bIQefzN/Ap5+IBcZcfz3/yS7y413Klvw+pF6XGi1AvAu5K6amYHnFuehdEKCxCMkIiKiUFLE4ldpaSm+/vWvY/PmzYiNjUVlZSXy8/NRXl6OVatWobW1NVhvHVJc/CIiIqJw8FFdJ7742zPot7swNT0Wv352HtLMEVIPi2jMBEHAyYZuvH6kHn893+5/vMiX2bX6Fpldnf12/Pb4Vfz2kxPa8ybg6YWc0Kbgu9I5gF8dbcBfzjTC5vQuxKabI/CML7PrkxsSbE43dlY04fUjDaht92aG6bQarC7MwPOL81CUHR/qX0HV6tqteP1IA7aV31goz06IxLML8/AkF8pHRRAEHKntxGtH6nGkttP/+JyJCXhucT4enZ7GrDkiIqIwoIjFr6ioKJw7dw65ubkjFr/q6+sxffp02Gy2YL11SHHxi4iIiMJFTXMfnn7zNDqsdmTFR+LXz87D5NQYqYdFNCoutwd7zrbi9SP1qLre53982bRUPL84H/PyEu/a08vmdGNbmbcn2PBSZo8VZeC5xfmYmRUX1N+BwosgCDhztQe//LAe759vg3j3Pj3DjOcfzMOawkwY9XcuwenxCPigtgOvH6nHsbou/+Pz8hLxxcX5eHhqKrRcULgngiDgeH0XXj/SgIMXbiykF+fE44uL87FiRhpLpN6jC60WvH6kATsrmuB0ew/83KQofGFRHp6YnYNII8svExERqZUiFr/y8/Pxy1/+EsuWLRux+PWb3/wG3//+93Hu3LlgvXVIcfGLiIiIwklj9yA2v3EKDZ0DiI8y4I2n52IWSxKRjFltTvzpdCPePHYFTb1DAACTXovHZ2fjC4vyMCll7Au4Ho+Agxfa8dqRepxs6PY//sCkJDy/OB8P3ZfCBQW6Zy63B+/VtOG1I/WoaOz1P760IAXPL87HgklJd12ovZWa5j68fqQB71Q2w+XxTgXkp0TjC4vy8PisbPZzHCWn24PdVS147Ug9apotAACNBnh0WhqefzAfcyYm3NPnQzdrs9jw64+u4Pcnr6FvyAkAiI8y4HPzJ2LzAxORGssMdCIiIrVRxOLXq6++it/97nd444038Oijj2LPnj24evUqvv71r+O73/0u/v7v/z5Ybx1SXPwiIiKicNPVb8ezv/4YlY29iDBo8ZO/mYVHpqVJPSyiEZp7h/DW/8/efYfHUZ7r47+3r3rvXe69SnLFBDsYm2LT3AumpLdDCpD8TiDJN4dwSAhJyEkAAwZ3DAZTTcBgXLAlW7bcm6zee5d2tbvz+2N2VpJ72dXM7N6f6/IFXq13Xtkzo3nf53mf55sibMwuQavFBgCICDBixeRULJuUjIhAk1uOc7SsCat3F+LjY5WwOwMKA6MD8ei0NMwfl8CAAl2zNosNbx8oxet7C1HWKAZqjTot7h2XgEenp2FQTJBbjlPZLF4bG7JL0NolXhvhAUYsm5SCFZNTEOmma8PbtHR1Y2N2CdZ8U4TKZrGSjdmgxYMTkvDwtDSkRQbIPELv1WG1YcvBMry2pxAlDR0AxGtj/rh4PDo9HYPddG0QERGR/FQR/BIEAf/zP/+DZ599Fh0d4sOJyWTCL37xC/zhD3/w1GH7HYNfRERE5Is6rDb8YP0h7DxTC51Wg2fvHYUFGUlyD4sIx8ub8eruAnx8tNK1u6U/glHlTZ14Y08hNh0oRZsz2BYZaMTySalYPjkF4QFGjxyX1K+quQtrvinC+uxiVzAqzN+A5ZNSsHxyKqKCPBOMkoJtr+0pdO2KNOq1uH98Ah6Zls6ytk5ljR14Y28RNve5tk1YOTkFSyfx2u5PdoeA/5yowqu7C3CopMn1+ozB4q7IqQNvbFckERERKYfig192ux179+7F6NGj4e/vj/z8fLS1tWH48OEIDPSuB2gGv4iIiMhXddsdePLdY3j3UBkA4Be3D8YPvzWQC0/U7xwOAV+dEcsQ7i/oKUM4OT0Cj92ShlsH919fo5aubmzOKcUbewtR0Wt3yP3jxTKL6TdQZpG808mKFqzeXYAPepUhTIvsKUPYX32NbHYHtp+owqu7C3GkV5nF24ZG49HpaZic7psBhSOlTXh1dwE+PV7l2tU5KDoQj01Pxz1j47mrU2a5xY1YvbsAn52ogvOfB8PigvHotDTcPebq/fCIiIhImRQf/AIAs9mMU6dOIS0tzW2f+c9//hPPP/88qqqqMGbMGPzjH/9AZmbmZd/f1NSE3/zmN9i6dSsaGhqQkpKCF198EXPnzgUAPPPMM/jd737X588MGTIEp0+fvuYxMfhFREREvkwQBPzvZ2fwr53nAQArJqfg6btHQMd+R9QPurrteO9wOVbvLsD52nYAgF6rwV2j4/Do9HSMTAiRbWzddgc+OSb2BTpe3tMXaObQGDw2PQ2ZaeE+GVDwdYIg4OuztXh1dwH25te7Xs9MDcej09Mwa1iMbP3iBEHAweJGvLqrAJ+fqoa0WjAyIRiPTU/H3FFxMOi8O6DgcAjY4eznl9Orn9/UgRF4dHo6bh0cxetWYYrr2/H6nkK8fbAMnd12AEBMsAkPTUnDksxkhPgbZB4hERERXQ9VBL8mTpyI5557DjNnznTL523evBkrVqzAv//9b2RlZeHFF1/Eli1bcObMGURHR1/0fqvViqlTpyI6Ohq//vWvkZCQgOLiYoSGhmLMmDEAxODXO++8gy+++ML15/R6PSIjI695XAx+EREREQFv7C3E7z86CUEA5oyMxV8XjmVWPHlMfZsFa/cXY+2+YtS3WwEAQSY9lmQlY+WUVMSH+sk8wh6CIGB/QQNW7y7AjtM1rtfHJIbg0enpmDMyFnovDygQYLHZse1wBVbvKcDZ6jYAgE6rwZyRsXhsejrGJIXKO8ALFNa147U9BXgntwxd3Q4AQFyIGaumpmJRZjKCzd4VUOjqtuOd3DK8vqcQBXU9gfR7xsTjkelpGBEvXyCdrk1ThxXrs0vw5jdFqGm1AAD8jTosmJiER6alISncX+YREhER0bVQRfBr+/bteOqpp/CHP/wBEyZMQEBA3+av1zvwrKwsZGRk4KWXXgIAOBwOJCUl4cc//jGefPLJi97/73//G88//zxOnz4Ng+HSD+bPPPMM3n//feTl5V3XWHpj8IuIiIhI9NHRCjy++Qisdgey0sLxyoqJCPHzrgVSktf52jas3l2IrYfKYLGJC/IJoX5YNTUVCzOSEKTwBfn8mja8tqcQ7x4qg/WC8S/KTEagSS/zCMndGtutWLe/GG/uK0Zdm7ggH2DUYWFGMlZNTVX8gnxDuxXrLxh/oEmPRRlJWDUtDQkKCjTfiLo2C97aV4x1+4vRIAXSzWIg/aEpqYgLUff354ssNjs+PFKJ1bsLcLqqFQCg1QBzRsbh0elpGJccJvMIiYiI6EoUHfz6/e9/j5///OcICgrqOVCvsgCCIECj0cBut1/zZ1qtVvj7++Odd97B/PnzXa+vXLkSTU1N2LZt20V/Zu7cuQgPD4e/vz+2bduGqKgoLFmyBE888QR0OjEL+ZlnnsHzzz+PkJAQmM1mTJ48Gc8++yySk5MvOxaLxQKLxeL6fUtLC5KSkhj8IiIiIgLwTX4dvrM2F20WG4bGBmHNqkzEhpjlHhapmCAIyC4Ud059cco7dk7VtVmwdl8x1vZecDfpsdi54K6knWt0Y4rq2vHankJsyS117ZyKDe7ZOaW2xICubjs+yKvAq7sLcK6mZ+fa3FFxeGx6GkYnhso7wOuUX9MqBtIPl7sC0Ylhfnh4ahoWZCQxEO0FBEHA7nN1eHV3AXafq3O9PjElDI9OT8e3h8ewRDMREZECKTr4pdPpUFlZiVOnTl3xfTNmzLjmz6yoqEBCQgK++eYbTJ482fX6r371K3z99dfIzs6+6M8MHToURUVFWLp0KX7wgx8gPz8fP/jBD/CTn/wETz/9NADg008/RVtbG4YMGYLKykr87ne/Q3l5OY4fP94neNfbpfqEAWDwi4iIiMjpREUzHnrjAGpbLUgI9cObD2diYHSg3MMilZF6Zq3eXYhj5c0AvK9nVle3HVsPlWP1ngIUKKxnGV2/y/XMGhEv9sy6c7T6e2YJgoCdZ2ux+sKeZWnh+M70dNw2NFq2nmVXIwgC9hXUY/XuQnzZuwRpUii+Mz0ds0fEqC6QTtfmdFULVu8uxLa8cnTbxQszNcIfj0xLwwMTkuBnZJlmIiIipVB08Eur1aKqquqSfbhu1I0EvwYPHoyuri4UFha6dnq98MILeP7551FZWXnJ4zQ1NSElJQUvvPACHnnkkUu+hzu/iIiIiK6utKEDK17PQWFdO0L9DXhtZQYmpLDUEF1da1c3Nh8oxRt7i1De1AkAMOm1eGBCIh6Zlob0KO8LpDocAr46U4NXdhUgu7DB9frk9Ag8dksabh2s3IACATa7A5+dqMYruwtwpLTJ9fq3hkThsenpmDwgQvWB2ks5UdGM13YX4oMjFbA5xKWF9KgAPDItDfePT1RM38duuwMfH63Eq7sLcKKiBYAYSP/2sBg8dks6JqaEeeW/D12suqULb35ThPXZJWju7AYAhPobsCwrBSumpCA6iDvViYiI5Kb44Fd1dTWioqLc9pk3UvZwxowZMBgM+OKLL1yvffrpp5g7dy4sFguMRuMlj5WRkYFZs2bh2WefvaaxsecXERER0aXVt1nw8JsHcaS0CWaDFr+4fQj7GtFlCYKAV3YV4KUv89FqsQEAIgONWDE5FcsmpSA84NLP797mWFkzXt1dgI+PVcLuDCgMjA7Eo9PSMH9cgmICCgS0WWx4+0ApXt9biLJGMVBr1Gtx37gEPDItDYNiLl1NxNtUNndizTdF2JBdgtYu8doNDzBicIwyAtVFdR2oaukCAJgNWjw4IQkPT0tDWmTAVf4keasOqw1bDpbhtT2FKGnoAAAYdVqMTQqFlpv/LvJfswYjKz1C7mEQEZGPUHzwKyQk5KqZUw0NDVf8+oWysrKQmZmJf/zjHwAAh8OB5ORk/OhHP8KTTz550ft//etfY8OGDSgoKIDW+fTyt7/9Dc899xwqKioueYy2tjYkJyfjmWeewU9+8pNrGheDX0RERESX12G14QfrD2HnmVoAQJBZjyWZyXhoairiQtjXiEQ2uwP/ve0ENuaUAGCwBwDKmzqxZm8hNuaUoq1XMHD5pFQsn+w7wUAlqmruwhvfFPYJ9oT5G7B8UgqWT05FVJBJ5hHKQwoGvran0LVrUykiA01YOTkFyyalIIzXDjnZHQI+P1mFV3YV4FBJk9zDUax/LR2POaPi5B4GERH5CMUHv1588UWEhFy5Pv3KlSuv63M3b96MlStX4uWXX0ZmZiZefPFFvP322zh9+jRiYmKwYsUKJCQkuHZslZaWYsSIEVi5ciV+/OMf49y5c3j44Yfxk5/8BL/5zW8AAL/4xS9w9913IyUlBRUVFXj66aeRl5eHkydPXvPONQa/iIiIiK7MZndg88FSvLa7EAV1PX2N7h4Tj0enp2FEPPsa+bKubjt+vPEwPj9ZDa0GeOaeEViWlcIyf04tXd3YnFOKN/YWoqJZ3L1i0mtxv7MM5AAvLAOpVCcrWrB6d0GfMn9pkT1l/tg3SGSzO7CvoN5VVk5u/kYdpgyI9NlAOl2bY2XNKG5ol3sYijQhJYwJS0RE1G8UH/xyd88vyUsvvYTnn38eVVVVGDt2LP7+978jKysLAHDrrbciNTUVa9ascb1/3759+K//+i/k5eUhISEBjzzyCJ544glXD7BFixZh165dqK+vR1RUFKZNm4Y//vGPGDBgwDWPicEvIiIiomvjcAjYcboGr+4uQE6vvkZTBkTgsenpmDE4igEPH9PUYcWjbx7EweJGGPVa/H3RONwxMlbuYSlSt92BT45VYvXuQhwrbwYg9i2aOTQGj01PQ2ZaOPsWeYAgCNh5thardxdgb3696/XM1HA8Oj0Ns4bF8L5FREREROQmig5+6XQ6VFZWeiT4pUQMfhERERFdv6NlTXh1dyE+uaCv0WPT0zBvrO+WuvMlFU2dWPl6Ds7VtCHYrMfqlRnITAuXe1iKJwgCsgsb8OquAuw4XeN6fXRiCB6dno65I2Oh17Fpzc2y2OzYdrgCr+4uwLmaNgCATqvBnJGxeGx6OsYkhco7QCIiIiIiL6To4Jcnd34pEYNfRERERDeurLEDb+wtwuYDffsarZicimWT2NfIW52tbsWK13JQ1dKF2GAz3nw4E0Nig+Qelurk17ThtT2F2HqoDBabAwCQEOqHVVNTsTAjCUFmg8wjVJ/GdivW7S/Gm/uKUddmAQAEGHVYlJmMVVNTkRjmL/MIiYiIiIi8l6KDX76GwS8iIiKim9fS1Y1NOSV4Y28RKp19jcwGLe4fL/Y1SmdfI69xoKgBj6w5gJYuGwZGB+KthzMRH8peIjejvs2CtfuLsXZfMerbrQCAIJMei7OS8dCUVP79XoOiuna8tqcQW3JL0dUtBhLjQsxYNTUVizKTEcxAIhERERGRxzH4pSAMfhERERG5j9TX6JVdBThR0QJA7Gs0a1gMHpuejozUMPY1UrHPTlThJxsPw2JzYEJKGF5bORGh/tzd5y5d3XZsPVSO1XsKUFDbDgDQazW4c3QcHpuejpEJITKPUFkEQcDB4ka8uqsAn5+qhjQ7HhEfjMemp+PO0XEwsIQkEREREVG/YfBLQRj8IiIiInI/QRCwr6Aeq3cX4stefY3GOPsazWFfI9VZn12M/37/OByCGMx8ack49nbzEIdDwFdnavDq7gLsL2hwvT45PQKP3ZKGWwdHQ6v13SCyze7AZyeq8cruAhwpbXK9ftvQaDw6PQ2T0yMYZCciIiIikgGDXwrC4BcRERGRZ+XXtOK1PYV491A5rL36Gj08LQ0LM5IQaNLLPEK6EkEQ8OIX5/C3HecAAIszk/CHeSMZvOwnx8qasXpPAT46Wgm7Q5z+DYgKwKPT03HvuASfCkC2WWx4+0ApXt9biLLGTgCAUa/FfeMS8Oj0NAyMZt85IiIiIiI5MfilIAx+EREREfWPujYL3tpXjHX7i9Eg9TUy67EkMxkPTU1FXAj7GimNze7Af287gY05JQCAn84chJ/NGsRdNTIob+rEmr2F2JhTijaLDQAQEWDEismpWDYpGRGBJplH6DlVzV1445tCbMguQWuX+L2HBxixbFIKlk9KQVSQ937vRERERERqwuCXgjD4RURERNS/urrtePdQGV7bXYiCup6+RneNjsOj7GukGF3ddvx442F8frIaWg3w+3kjsWxSitzD8nmtXd3YfKAUb+wtQnmTuPvJpNfi/gmJeGRaGgZEBco8Qvc5WdGC1bsL8MGRCticu97SIwPwyPQ03D8+0ad2vRERERERqQGDXwrC4BcRERGRPBwOAV+eFvsaZRf29DWaMiACj01Px4zBUT7d10hOTR1WPPLmQeQWN8Ko1+Lvi8bhjpGxcg+Leum2O/DJsUqs3l2IY+XNrtdnDYvBY9PTkJkWrsodeoIgYOfZWqzeXYC9+fWu1zPTwvHY9HTMHOrb/c6IiIiIiJSMwS8FYfCLiIiISH5Hy5rw6u5CfHKsp6/RwOhAPDY9DfPG+lZfI7lVNHVi5es5OFfThmCzHqtXZiAzLVzuYdFlCIKA7MIGrN5dgC9O1bheH50Ygkenp2PuyFhV9Gfr6rZjW145Vu8uxLmaNgCATqvB3FFxeGx6GkYnhso7QCIiIiIiuioGvxSEwS8iIiIi5Shr7MCavUXYdKCnr1FkoNTXKAXhAUaZR+jdzla3YsVrOahq6UJssBlvPpyJIbFBcg+LrtH52ja8tqcQ7+aWwWJzAAASQv2wamoqFmYkIchskHmEF2tst2Ld/mK8ua8YdW0WAECgSY+FGUlYNTUViWH+Mo+QiIiIiIiuFYNfCsLgFxEREZHytHR1Y1NOCd7YW4TK5i4AgNmgxf3jxb5G6V7U10gpcgob8OibB9DSZcPA6EC89XAm4kP95B4W3YD6NgvW7i/G2n3FqG+3AgCCTHoszkrGvLHxMOnl30nZYbVhy8EybMktRVe3GKiLCzFj1dRULMpMRrACA3VERERERHRlDH4pCINfRERERMol9TV6dXcBjpe3AAA0GqmvUToyUsNU2ddIaT47UYUfbzwMq82BCSlheG3lRIT6c5ed2nV12/He4XKs3l2A87Xtcg/nskbEB+M7t6Rj7qg4GFRQopGIiIiIiC6NwS8FYfCLiIiISPkEQcD+gga8ursAX57u6Ws0xtnXaI5K+hop0br9xfjttuNwCGJQ8aUl49hjzcs4HAJ2nq3Ba3sKcaKiRe7hAAA0AMYnh+GR6WmYnB7BIDYRERERkRdg8EtBGPwiIiIiUpf8mlaxr9Ghclh79TV6eFoaFmYkIdCkl3mE6iAIAv76xTn8fcc5AMDizCT8Yd5IBhGJiIiIiIjohjD4pSAMfhERERGpU12bBWv3FWPt/mI0SH2NzHosyUzGQ1NTERfCflWXY7M78N/bjmNjTikA4KczB+FnswZx9w0RERERERHdMAa/FITBLyIiIiJ16+q2Y+shsa9RQZ3Y10iv1eCu0XF4dHo6RiaEyDxCZenqtuNHGw7ji1PV0GqA388biWWTUuQeFhEREREREakcg18KwuAXERERkXdwOAR8eboGr+4uQHZhg+v1KQMi8Nj0dMwYHAWt1rd3NjV1WPHImweRW9wIo16Lvy8ahztGxso9LCIiIiIiIvICDH4pCINfRERERN7naFkTVu8uxMfHKmF3iI/MA6MD8ei0NMwflwCzQSfzCPtfRVMnVryeg/yaNgSb9Vi9MgOZaeFyD4uIiIiIiIi8BINfCsLgFxEREZH3Km/qxBt7CrHpQCnaLDYAQGSgEcsnpWL55BSEBxhlHmH/OFPVipWv56CqpQuxwWa8+XAmhsQGyT0sIiIiIiIi8iIMfikIg19ERERE3q+lqxubc0rxxt5CVDR3AQDMBi3uH5+IR6alIT0qUOYRek5OYQMeffMAWrpsGBgdiLcezkR8qJ/cwyIiIiIiIiIvw+CXgjD4RUREROQ7uu0OfHKsEq/uLsDx8hYAgEYDzBoWg8empyMjNQwajff0Bdt+vAo/2XQYVpsDE1LC8NrKiQj1943dbkRERERERNS/GPxSEAa/iIiIiHyPIAjYX9CA1bsLsON0jev1MYkheHR6OuaMjIVep5VxhDdv3f5i/HbbcTgEMbj30pJxPtnrjIiIiIiIiPoHg18KwuAXERERkW/Lr2nDa3sK8e6hMlhtDgBAQqgfHp6WhoUZSQg06WUe4fURBAF//eIc/r7jHABgcWYS/jBvpOqDeURERERERKRsDH4pCINfRERERAQAdW0WrN1XjLX7i9HQbgUABJn1WJKZjIempiIuRPl9smx2B/5723FszCkFAPx05iD8bNYgryrlSERERERERMrE4JeCMPhFRERERL11ddux9VA5Vu8pQEFtOwBAr9XgrtFxeHR6OkYmhMg8wkvrtNrx442H8cWpamg1wO/njcSySSlyD4uIiIiIiIh8BINfCsLgFxERERFdisMh4KszNXhlVwGyCxtcr08ZEIHHpqdjxuAoaLXK2FHV1GHFI28eRG5xI4x6Lf6+aBzuGBkr97CIiIiIiIjIh/hs8Ouf//wnnn/+eVRVVWHMmDH4xz/+gczMzMu+v6mpCb/5zW+wdetWNDQ0ICUlBS+++CLmzp17w595IQa/iIiIiOhqjpU149XdBfj4WCXsDvERfGB0IKYNjJR5ZKJd52pRUNuOYLMeq1dmIDMtXO4hERERERERkY/xyeDX5s2bsWLFCvz73/9GVlYWXnzxRWzZsgVnzpxBdHT0Re+3Wq2YOnUqoqOj8etf/xoJCQkoLi5GaGgoxowZc0OfeSkMfhERERHRtSpv6sSavYXYmFOKNotN7uH0ERtsxpsPZ2JIbJDcQyEiIiIiIiIf5JPBr6ysLGRkZOCll14CADgcDiQlJeHHP/4xnnzyyYve/+9//xvPP/88Tp8+DYPB4JbPvBQGv4iIiIjoerV2deP9vApUN3fJPRQAgJ9RhwcmJCIm2Cz3UIiIiIiIiMhHuSveonfjmDzKarUiNzcXTz31lOs1rVaLWbNmYd++fZf8Mx988AEmT56MH/7wh9i2bRuioqKwZMkSPPHEE9DpdDf0mURERERE7hBkNmD5pBS5h0FERERERETkdVQT/Kqrq4PdbkdMTEyf12NiYnD69OlL/pmCggJ8+eWXWLp0KT755BPk5+fjBz/4Abq7u/H000/f0GcCgMVigcVicf2+paXlJr4zIiIiIiIiIiIiIiIichfVBL9uhMPhQHR0NF555RXodDpMmDAB5eXleP755/H000/f8Oc+++yz+N3vfnfR6wyCERERERERERERERER3RgpznKzHbtUE/yKjIyETqdDdXV1n9erq6sRGxt7yT8TFxcHg8EAnU7nem3YsGGoqqqC1Wq9oc8EgKeeegqPP/646/fl5eUYPnw4kpKSbuRbIyIiIiIiIiIiIiIiIqfW1laEhITc8J9XTfDLaDRiwoQJ2LFjB+bPnw9A3Nm1Y8cO/OhHP7rkn5k6dSo2bNgAh8MBrVYLADh79izi4uJgNBoB4Lo/EwBMJhNMJpPr94GBgSgtLUVQUBA0Go0bvlvyZS0tLUhKSkJpaelNNfQjUhqe2+SteG6Tt+K5Td6M5zd5K57b5K14bpO34rlN3upmzm1BENDa2or4+PibGoNqgl8A8Pjjj2PlypWYOHEiMjMz8eKLL6K9vR2rVq0CAKxYsQIJCQl49tlnAQDf//738dJLL+GnP/0pfvzjH+PcuXP4n//5H/zkJz+55s+8FlqtFomJie79ZsnnBQcH84ceeSWe2+SteG6Tt+K5Td6M5zd5K57b5K14bpO34rlN3upGz+2b2fElUVXwa+HChaitrcVvf/tbVFVVYezYsdi+fTtiYmIAACUlJa4dXgCQlJSEzz77DP/1X/+F0aNHIyEhAT/96U/xxBNPXPNnEhERERERERERERERkXpohJvtGkZEbtXS0oKQkBA0Nzcz44O8Cs9t8lY8t8lb8dwmb8bzm7wVz23yVjy3yVvx3CZvpYRzW3v1txBRfzKZTHj66af79JUj8gY8t8lb8dwmb8Vzm7wZz2/yVjy3yVvx3CZvxXObvJUSzm3u/CIiIiIiIiIiIiIiIiKvwZ1fRERERERERERERERE5DUY/CIiIiIiIiIiIiIiIiKvweAXEREREREREREREREReQ0Gv4iIiIiIiIiIiIiIiMhrMPhF5AHPPPMMNBpNn19Dhw51fb2rqws//OEPERERgcDAQNx///2orq7u8xklJSW488474e/vj+joaPzyl7+EzWbr856dO3di/PjxMJlMGDhwINasWdMf3x75kF27duHuu+9GfHw8NBoN3n///T5fFwQBv/3tbxEXFwc/Pz/MmjUL586d6/OehoYGLF26FMHBwQgNDcUjjzyCtra2Pu85evQopk+fDrPZjKSkJPzv//7vRWPZsmULhg4dCrPZjFGjRuGTTz5x+/dLvuNq5/ZDDz100X38jjvu6PMentukRM8++ywyMjIQFBSE6OhozJ8/H2fOnOnznv58DvnnP/+J1NRUmM1mZGVlIScnx+3fM/mGazm3b7311ovu3d/73vf6vIfnNinNv/71L4wePRrBwcEIDg7G5MmT8emnn7q+zns2qdXVzm3es8lb/OlPf4JGo8HPfvYz12u8d5M3uNS5rbp7t0BEbvf0008LI0aMECorK12/amtrXV//3ve+JyQlJQk7duwQDh48KEyaNEmYMmWK6+s2m00YOXKkMGvWLOHw4cPCJ598IkRGRgpPPfWU6z0FBQWCv7+/8PjjjwsnT54U/vGPfwg6nU7Yvn17v36v5N0++eQT4Te/+Y2wdetWAYDw3nvv9fn6n/70JyEkJER4//33hSNHjgj33HOPkJaWJnR2drrec8cddwhjxowR9u/fL+zevVsYOHCgsHjxYtfXm5ubhZiYGGHp0qXC8ePHhY0bNwp+fn7Cyy+/7HrP3r17BZ1OJ/zv//6vcPLkSeH/+//+P8FgMAjHjh3z+N8BeaerndsrV64U7rjjjj738YaGhj7v4blNSjR79mzhjTfeEI4fPy7k5eUJc+fOFZKTk4W2tjbXe/rrOWTTpk2C0WgUXn/9deHEiRPCY489JoSGhgrV1dX985dBXuVazu0ZM2YIjz32WJ97d3Nzs+vrPLdJiT744APh448/Fs6ePSucOXNG+PWvfy0YDAbh+PHjgiDwnk3qdbVzm/ds8gY5OTlCamqqMHr0aOGnP/2p63Xeu0ntLnduq+3ezeAXkQc8/fTTwpgxYy75taamJsFgMAhbtmxxvXbq1CkBgLBv3z5BEMRFWa1WK1RVVbne869//UsIDg4WLBaLIAiC8Ktf/UoYMWJEn89euHChMHv2bDd/N0SiCwMEDodDiI2NFZ5//nnXa01NTYLJZBI2btwoCIIgnDx5UgAgHDhwwPWeTz/9VNBoNEJ5ebkgCILwf//3f0JYWJjr3BYEQXjiiSeEIUOGuH6/YMEC4c477+wznqysLOG73/2uW79H8k2XC37Nmzfvsn+G5zapRU1NjQBA+PrrrwVB6N/nkMzMTOGHP/yh6/d2u12Ij48Xnn32Wfd/o+RzLjy3BUGcjPeenF+I5zapRVhYmLB69Wres8nrSOe2IPCeTerX2toqDBo0SPj888/7nM+8d5PaXe7cFgT13btZ9pDIQ86dO4f4+Hikp6dj6dKlKCkpAQDk5uaiu7sbs2bNcr136NChSE5Oxr59+wAA+/btw6hRoxATE+N6z+zZs9HS0oITJ0643tP7M6T3SJ9B5GmFhYWoqqrqcx6GhIQgKyurz7kcGhqKiRMnut4za9YsaLVaZGdnu95zyy23wGg0ut4ze/ZsnDlzBo2Nja738Hyn/rZz505ER0djyJAh+P73v4/6+nrX13huk1o0NzcDAMLDwwH033OI1WpFbm5un/dotVrMmjWL5ze5xYXntmT9+vWIjIzEyJEj8dRTT6Gjo8P1NZ7bpHR2ux2bNm1Ce3s7Jk+ezHs2eY0Lz20J79mkZj/84Q9x5513XnQO8t5Nane5c1uipnu3/rreTUTXJCsrC2vWrMGQIUNQWVmJ3/3ud5g+fTqOHz+OqqoqGI1GhIaG9vkzMTExqKqqAgBUVVX1uUlIX5e+dqX3tLS0oLOzE35+fh767ohE0rl4qfOw93kaHR3d5+t6vR7h4eF93pOWlnbRZ0hfCwsLu+z5Ln0GkbvdcccduO+++5CWlobz58/j17/+NebMmYN9+/ZBp9Px3CZVcDgc+NnPfoapU6di5MiRANBvzyGNjY2w2+2XfM/p06fd9j2Sb7rUuQ0AS5YsQUpKCuLj43H06FE88cQTOHPmDLZu3QqA5zYp17FjxzB58mR0dXUhMDAQ7733HoYPH468vDzes0nVLnduA7xnk7pt2rQJhw4dwoEDBy76Gp+3Sc2udG4D6rt3M/hF5AFz5sxx/f/o0aORlZWFlJQUvP322wxKERGpwKJFi1z/P2rUKIwePRoDBgzAzp07MXPmTBlHRnTtfvjDH+L48ePYs2eP3EMhcqvLndvf+c53XP8/atQoxMXFYebMmTh//jwGDBjQ38MkumZDhgxBXl4empub8c4772DlypX4+uuv5R4W0U273Lk9fPhw3rNJtUpLS/HTn/4Un3/+Ocxms9zDIXKbazm31XbvZtlDon4QGhqKwYMHIz8/H7GxsbBarWhqaurznurqasTGxgIAYmNjUV1dfdHXpa9d6T3BwcEMsFG/kM7FS52Hvc/TmpqaPl+32WxoaGhwy/kufZ3I09LT0xEZGYn8/HwAPLdJ+X70ox/ho48+wldffYXExETX6/31HBIZGQmdTsfzm9zucuf2pWRlZQFAn3s3z21SIqPRiIEDB2LChAl49tlnMWbMGPztb3/jPZtU73Ln9qXwnk1qkZubi5qaGowfPx56vR56vR5ff/01/v73v0Ov1yMmJob3blKlq53bdrv9oj+j9Hs3g19E/aCtrQ3nz59HXFwcJkyYAIPBgB07dri+fubMGZSUlLhqX0+ePBnHjh3rs7D6+eefIzg42FUiYPLkyX0+Q3pP7/rZRJ6UlpaG2NjYPudhS0sLsrOz+5zLTU1NyM3Ndb3nyy+/hMPhcP2AnDx5Mnbt2oXu7m7Xez7//HMMGTIEYWFhrvfwfCc5lZWVob6+HnFxcQB4bpNyCYKAH/3oR3jvvffw5ZdfXlR6s7+eQ4xGIyZMmNDnPQ6HAzt27OD5TTfkauf2peTl5QFAn3s3z21SA4fDAYvFwns2eR3p3L4U3rNJLWbOnIljx44hLy/P9WvixIlYunSp6/957yY1utq5rdPpLvozir93C0Tkdj//+c+FnTt3CoWFhcLevXuFWbNmCZGRkUJNTY0gCILwve99T0hOTha+/PJL4eDBg8LkyZOFyZMnu/68zWYTRo4cKdx+++1CXl6esH37diEqKkp46qmnXO8pKCgQ/P39hV/+8pfCqVOnhH/+85+CTqcTtm/f3u/fL3mv1tZW4fDhw8Lhw4cFAMILL7wgHD58WCguLhYEQRD+9Kc/CaGhocK2bduEo0ePCvPmzRPS0tKEzs5O12fccccdwrhx44Ts7Gxhz549wqBBg4TFixe7vt7U1CTExMQIy5cvF44fPy5s2rRJ8Pf3F15++WXXe/bu3Svo9Xrhz3/+s3Dq1Cnh6aefFgwGg3Ds2LH++8sgr3Klc7u1tVX4xS9+Iezbt08oLCwUvvjiC2H8+PHCoEGDhK6uLtdn8NwmJfr+978vhISECDt37hQqKytdvzo6Olzv6a/nkE2bNgkmk0lYs2aNcPLkSeE73/mOEBoaKlRVVfXPXwZ5laud2/n5+cLvf/974eDBg0JhYaGwbds2IT09Xbjllltcn8Fzm5ToySefFL7++muhsLBQOHr0qPDkk08KGo1G+M9//iMIAu/ZpF5XOrd5zyZvM2PGDOGnP/2p6/e8d5O36H1uq/HezeAXkQcsXLhQiIuLE4xGo5CQkCAsXLhQyM/Pd329s7NT+MEPfiCEhYUJ/v7+wr333itUVlb2+YyioiJhzpw5gp+fnxAZGSn8/Oc/F7q7u/u856uvvhLGjh0rGI1GIT09XXjjjTf649sjH/LVV18JAC76tXLlSkEQBMHhcAj//d//LcTExAgmk0mYOXOmcObMmT6fUV9fLyxevFgIDAwUgoODhVWrVgmtra193nPkyBFh2rRpgslkEhISEoQ//elPF43l7bffFgYPHiwYjUZhxIgRwscff+yx75u835XO7Y6ODuH2228XoqKiBIPBIKSkpAiPPfbYRQ9ZPLdJiS51XgPo84zQn88h//jHP4Tk5GTBaDQKmZmZwv79+z3xbZMPuNq5XVJSItxyyy1CeHi4YDKZhIEDBwq//OUvhebm5j6fw3OblObhhx8WUlJSBKPRKERFRQkzZ850Bb4EgfdsUq8rndu8Z5O3uTD4xXs3eYve57Ya790aQRCE69srRkRERERERERERERERKRM7PlFREREREREREREREREXoPBLyIiIiIiIiIiIiIiIvIaDH4RERERERERERERERGR12Dwi4iIiIiIiIiIiIiIiLwGg19ERERERERERERERETkNRj8IiIiIiIiIiIiIiIiIq/B4BcRERERERERERERERF5DQa/iIiIiIiIiIiIiIiIyGsw+EVEREREREREREREREReg8EvIiIiIiIiIiIiIiIi8hoMfhEREREREREREREREZHXYPCLiIiIiIiIiIiIiIiIvAaDX0REREREREREREREROQ1GPwiIiIiIiIiIiIiIiIir8HgFxEREREREREREREREXkNBr+IiIiIiIiIiIiIiIjIazD4RURERERERERERERERF6DwS8iIiIiIiIiIiIiIiLyGgx+ERERERERERERERERkddg8IuIiIiIiIiIiIiIiIi8BoNfRERERERERERERERE5DUY/CIiIiIiIiIiIiIiIiKvweAXEREREREREREREREReQ0Gv4iIiIiIiIiIiIiIiMhrMPhFREREREREREREREREXoPBLyIiIiIiIiIiIiIiIvIaDH4RERERERERERERERGR12Dwi4iIiIiIiIiIiIiIiLwGg19ERERERERERERERETkNRj8IiIiIiIiIiIiIiIiIq/B4BcRERERERERERERERF5DQa/iIiIiIiIiIiIiIiIyGsw+EVEREREREREREREREReg8EvIiIiIiIiIiIiIiIi8hoMfhEREREREREREREREZHXYPCLiIiIiIiIiIiIiIiIvIZe7gF4A4fDgYqKCgQFBUGj0cg9HCIiIiIiIiIiIiIiItURBAGtra2Ij4+HVnvj+7cY/HKDiooKJCUlyT0MIiIiIiIiIiIiIiIi1SstLUViYuIN/3kGv9wgKCgIgPiPERwcLPNoiIiIiIiIiIiIiIiI1KelpQVJSUmuuMuNYvDLDaRSh8HBwQx+ERERERERERERERER3YSbbTHF4BcRERERkQwEQYDF5oDdIcg9FACAVqOB2aBlD1siIiIiInI7h0NAl80OQRnTHxh0Whj1N95PipSPwS8iIiIiomsgBavaLTa0W+xos9jQbrW5ft9usYmvWWxot9qdr9t6va/vax1WO2wKCXxJ/Aw6RAebEBNkRpTzvzHBJtdr0cEmRAebEWTSM0hGREREROTFHA4BHd195zltFhs6LHa0W3u/ZkeHc87T1mte1GHtNW9yzn+UJjzAiOggcY4TE+Sc9wSbe14LNiMq0MQgmUox+OVFalstOFbeBLNBh0CTHgEmveu//gYdtFouUBARERE1tFuxv6AebV09k7K2SwSmXIEsBQer3K2z247i+g4U13dc8X0MkpESHCltQmOHFQEmPQKM0txHhwCTHiY9dzESERERAcCxsmYU1LV5RbDK3RrarWhot+J0VesV38cgmTox+OUlHA4BS17dj3M1bZd9j79R5wqI9f5/8b86+Bt7/r/nfeIEUnpfgPP3AUY9g2lERESkOoIgYNWaAzhS2nRTn+Nn0PV5bhKfk/o+X136NZ3zeapnod6gU8YEyeYQUN9mQXWLBTWtXa7/1rRYUN3ShZpW8b+tXTYGyUh2OYUNWPDyvst+Xa/VwN+o63s9Oq8/V4KgSYdA4wVJg9Lcx/k+6fcMphEREZEaHS9vxj3/3HNTpQa1Glw0z5HWknsnH0nPVQG95kjSc5X0mr9RB61Cnqk6rPaeeY9zvlPTIv6+2jkPqmntQrddYJBMpRj88hK78+twrqYNJr0WSeH+fbajSgnKHVY7Oqx21LZa3HJMKYAmLer0DqwFmfW4a3Q8pg6MdMuxiMg9BEFAZ7eUxdOzy6H9gl0P7c4t7J0KyvIZkxSKByYkyj0MIlK5vNImHCltglGnxdSBEX0ncRc801z6NXGSp/PSJKBAkx4pEQFXfE9n70mim4JkZoMWMcFmV5BsRHwwvnfLACZbOdW2WrA+uxgrJ6ciLMAo93AU4Y29hQCAmGAT/Aw613NMZ7f47GJzCGjpsqGly+aW4+m0GgQ4g2n+vRZ9pCBZZJAJ358xgP8+RApjszv6lCKW/r/37u7er9nsytjhrddpsDQrGQOjg+QeChGp3Fv7iiAIQHK4P4bEBl0UrPK/IKFPWtvtXVXMW5OAzAYdwgOMGBp7+fcIgoDGju6LgmTVLc75j5uCZA9MSERWeoSbv0P1+tOnp93yOQx+eYm1+4oAAIszk/HMPSNcr0u9KdquUMbH1aPigp4VvRfDO1z9KuyupuyuYNplxvTx0Upk/3oW/Iw6D3/3RN7reoNVbZZLXcfO7erO96i1Ytfa/cUYER+MYXHBcg+FiFRsfXYJAOCu0XF4YeFYeQejUn5GHVIiAm4sSNZ7stgrSNbV7egTJPv4aCXSIwNwx8i4/viWFO+ZD07g42OVKGnowAsLxso9HNlVNnfiPyerAQBvPZyFIbE9i8N2h3BRyZ7ePfcu15fv4lKndnRYe8r92K8hmGa1OfrMxYjo+l1vsKr3XEi6dnvPmbq6HXJ/Szcsr7QJ7/1gqtzDICIVa+7sxgdHKgAAf1kwBhmp4TKPSH00Gg3CA4weD5LtPFuLb568TTFVQeRU22rB5gMlbvksBr+8QGlDB3acrgEALJuU0udrGo0GZoMOZoMOkYGmmz5W72BaR69G765mh84H0NW7C1DR3IUPj1ZgwcSkmz4ueac95+rw9x3n8P/uHYnBMcxoA4Ca1i78YN0hlDV2uiZsnghWaTTos+084MISp87dDn4GnSKye74+W4u80ias3V+M/7l3lNzDISKVauqw4kPn5G/pBc9M5H43GiT75FglPjlWhXX7Sxj8AlDT0oXPTlQBAD46Uolfzx3mlud6NduYXQK7Q0BmWnifwBcg7tAKMhsQZDa45Vi9g2k9i+t9E42K6trx6u5CvJtbhl/dMQT+Rk6z6WKCIOB3H55Ep9WOZ+8bxZ2tTu8dLsPfd+SjpbPbo8Eqg05zyf6AARe0f1DCoqMgCPjX1+dxuKQJx8ubMTIhRO4hEZFKbT1Uhq5uB4bEBGFiSpjcw/FqNxokq27pwv9uP4PaVgv+c6Iad47m/GdLbim63bQTm0/lXmBDTgkEAZg6MAIDowM9eqzewTRc4VBdNjv+d/sZrM8uYfCLLkkQBDzz4Qnk17Th+c/O4NUVE+UekiK8tqcQB4sbL3r9WoNV19prxs+gU9WEe1J6BBa/uh/vHy7Hk3OGIthNC1pE3s7hENDU2Y1gsx56BSzmyO3dQ+Ww2BwYGhuE8cmhcg+HnC4Mko1JDMWnx6uwJ78OhXXtSIu8cvDM2719sBQ2ZyaM1e7AppwS/Oi2QTKPSj5WmwMbD5QCAFZM9nwQ+1qCaQ6HgP+crEZxfQc+PFKBhRnJHh8Xqc/B4kas+aYIAHDHyFh8a2i0vANSAKvNgT9+fBp1bRe3ZrgwWNW7H5+r14yrl8wl5jx9Al161fVWKarvwAdHKrB2XzGee2C03MMhUg2LzY5Oqx2h/ixDLAiCq+rF0knJikhspksHyUobOvCPL/OxPrvY54NfdoeADdnu2fUFMPilel3ddmx2Tv6WKyiDecHEJPz187M4UspMJbq0vfn1yK9pAwDsOFWN8qZOJIT6yTwqeXV12/G283r+w/yRmDYwUrXBKneblB6OQdGBOFfThq25ZXhoaprcQyKSlcMhoLHD6mrEW3tBr6XqVgtqnb+3OQQMiwvGRz+e5rV9qq6FOPkrBiDulOfkT7mSwv1x6+AofHWmFhuyi/GbO4fLPSTZ2B0CNuaIzwYzBkfh67O1WLe/BN+dMUARuxPk8NmJKtS2WhAVZMLtw6+QVtuPtFoNlmQm49lPT2Pd/hIGv+iSpMAXIJbzZvAL2H6iCnVtFsQEm7BmVSYCTT2BLpPet9snrJicgg+OVGDbkXL8eu4whPgz+Y98m8Vmd5aM61tOrnfv2ZrWLjR2dAMAnrl7uM+vG2QXNiC/pg3+Rh3uHZcg93DoChZlJuOfX+Xjm/P1OF/bhgFRnt3comS7ztWirLETQWb3PAcw+KVynxyrREO7FXEhZswaFiP3cFwiA024Y2QcPjxSgfXZxXj2PmYqUV+9J38OAdiQXYxfzh4q34AU4OOjlWjs6EZ8iBmLM5K4S6MXjUaD5ZNT8NttJ7B2fzFWTknlwnU/s9kdYv8Ua68+kM7ytx1WG4bFsR+bO1xvUOtanapswRenqjF7hDIWiuWwr6AeBbXtCDDqMJ+TP8VbNikFX52pxZbcMvz89iFi1QEftPNMDcqbOhHqb8A/lozDbX/eiaqWLp8uibJ2nxjEXpyZrKidHA9MSMRf/nMWx8qbcbSsCaMTQ+UeEilIVXMXth+vcv3+qzM1KG3oQFK4v4yjkl/v3uV8juxrQkoYhsYG4XRVK7bkluLR6elyD8mn9G75cake23aHgNuGRrutxK4vu96g1rX6v53nsSQrRVHPCv1N2vU1b2w8z1WFSwj1w21Do/HFqRpsyC7Bf9/lu8l/6/eLz/rzxibipBs+j8EvlVvrPCGWZCYrbqF8WVYyPjxSgfcPV+CpucNYpoxcxD51YpPyX9w+GH/+z1lsyinFT2YO8ukMv7ec1/PSSSmKu56V4N5xCXju09M4X9uOfefrMWVgpNxDUrTewar2XpO2tl4NwNstfZuFd1h7vi71dJT6O1psV+6/4G/UYc8TtyE8gOUlLsVTQa3IQCOigsyICTYhOsiEmGAzooPNPf8fZMKb+4rw8tcFeH1PoU8Hv9bvFyd/88clINDER2Clu3VINBJC/VDe1IlPjlXivvGJcg9JFuuczwYPTkhEsNmAxZnJ+MeX+XjzmyKfDH6drmpBTlEDdM6dVkoSEWjC3FGxeD+vAuv2F+N/HwiVe0ikIOuzi1196kx6LXafq8O6/cV4au4wuYcmm1OVLThQ1Ai9VoPFCruelUCj0WDF5FT8+r1jWLe/GA9PTfPpSiBXc2Gwqu2CuY34ml1M4rP2nRt1WMWvtfd6b7vVDvtVnsnvG5+AFxaM7Z9vUIU8EdQy6rSI7jXviQk2I6rXvCcm2IzwACPu/Ptu1LRa8MmxSp9NeqtttWD78UoAwNIs5VQKo8tbmpWCL07V4J3cMvxytm8m/5U3deLL0zUAgAUZiXjWDZ/Jmb+KHS9vxuGSJhh0GizMVF5frcy0njJl7x8ux4rJqXIPiRRi7f5iCAIwfVAkvjdjANbuL0Z1iwXbj1dh3ljffDA5WtaEI6Xi9cw+eZcWZDbgvvGJWLu/GG/tK/b54NfBogas+aYILV29dmL1CmhdLVh1o4w6LQJMOvj3ahZe0tCBujYr3s0tw2O3MCsVAL7Jr8Ob+4pQ1eK5oFZkoOmaMhkfmpKK1bsLkV3YgBMVzRgR73uliGtau/DZCTHjnpM/ddBpNVicmYQ//+cs1meX+GTwq7ShAzvP1gIAljjP26VZKfjXzvPIKWrAyYoWDI/3rZ0S0q6v24fHIDbELPNoLrZ0Ugrez6vAB0cq8Js7hyPEj8l/JC4Ab8wREzAempIKg04Mfm0+WIr/+vZgn1zcAnoSeWePiEVMsPKuZyWYPy4ez35yCkX1HdidX4cZg6PkHpJsBEHA/+08j7zSJldwqv2CQNfVglU3yt+o69NP22zQIbe4ER8dqcRv5g5DRKDJI8dVE4dDwIs7zuFwSaPHgloxwSaE+BmuqQLMskkpeOHzs3hjbyHmjY33yaoxW3JL0W0XMCYplK1oVOKWwVFIDPNDWWMnPjpaiQcm+N78Z1NOCRwCMDk9AumR7in9yOCXir3lLBFwx8g4RAcp72FRo9FgaVYynvnwJNbtL8Zy9tcgAJ3Wnj51KyenQq/TYklmCv76xVm8ta/YZ4Nf0mLO3FFxiAriw/PlLJ+cgrX7i/H5qWpUNnciLsQ3+8TZHQIef/sISho6rvreSwWrpIbg4mvOyZzrNV2vZuEXv3apYMuG7BL8+r1jWJ9djEemMSvVZnfg51uOoLK566KvuTOoda3iQvwwd5RYinjN3iI8/+AYt322Wrx9oBQ2h4DxyaE+FyxQswUZSXjxi3PILW7EqcoWnyuJtTGnBIIATBsYibTIAABAbIgZs0fG4uOjlXjzmyI894DvlBZv6erGe4fLAYjPA0o0MSUMQ2KCcKa6FVsPlWGVj/caIdHHRytR1ya2Krh9eAw0Go1rZ6uvLm61dHXjfYVfz0rgb9Tj/gmJWPNNEdbuK/Lp4Nfe/Ho8/9mZa3rvhcEqaU5z8WvS+6S5T695kFHvmkNdqmfu3f/Yg2PlzdiSW4bvzRjg7m9XdXaercHfd5y76PULg1rRQSZEO4NbvV8L9b+2oNa1WpKVjJe+yseRsmYcKmnChJQwt322GtgdAjY4Sx4uy+LOWrXQOXdCP//ZGazbX+xzzwfddgc2OdeLl01y37MBg18q1dzRjW15FQDERqhKde/4RDy3/QzOVrfhYHEjMlLD5R4Syez9vHI0d3YjKdzP1eR5cWYS/vGluLjli7sSGtut+OCI8q9nJRgcE4SstHBkFzZgY3YJHr99iNxDksV/TlShpKEDof4G/GbusOsOVrnbvLHx+B9nVuo35+sxbZBv78r74lQNKpu7EB5gxLP3jfJYUOt6rJqaig+PVGBbXgWemDMUkT6UoWp3CNiYIz5Ec9eXukQHmTF7RCw+PlaJ9dnF+H/zR8k9pH5jtTnw9kHpvO27aPHQlFR8fLQS7+eV48k5QxHmI+Vm3ztUjg6rHYOiAzE5PULu4VySRqPB0knJ+O22E1ifXYKH2KOUALzp7HW8rFdp8yVZ4uLW2n1FPre4BQDv5pahw2rH4JhAZKVxjeBKlk9OwZpvirDjtG/3iXtldwEAcefv3FFx1x2scrdlk5LxxLvHsCG7BN+Znu7zyX9vOZN57xodhwUTkzwW1LpWkYEmzBsTjy25ZXh9b6HPBb92natFWWMngs163DU6Xu7h0HVYMDEJL35xFnmlTThe3uxTu/Y+P1mN2lYLIgNN+PbwGHR1tLnlc9lURqW25JbCYnNgaGwQJir4Jh7iZ8A9Y8QbrdSzgHyXIAiuyd+KSamuh9LoYDPuGCn2ofHF8+Sd3DJYbA4MiwvG+GTlXs9KIZVQ3ZBTCquHSvspmSAIeHmXOPlbPikFD05MwpxRcbhlcBQmpIRhSGwQksL9ERZg7LdAS4BJj3udtdR98Rq+0Nr9RQCAhRlJmD0iFmOTQhEf6idrs+XxyWEYkxQKq93hygL0FTvP1KC8qROh/gaf7JGkdlLg571D5Wiz2GQeTf/57EQV6tqsiA4yYdbwmD5fm5gShuFxwbDYHNjsDJB5O0EQXCXSlk9WdjWJe8clwN+oQ35NG7ILG+QeDsnscEkjjpQ1w6jXYlFGT2nzhRlJMOq0OFLWjCOlTfINUAZ9rmdWh7mqAVGBmDYwEoIAbMjxrWc4yanKFuw6WwutBvjvu4Zj/rgEfHt4DKYMiMToxFAMiApEbIgZQWZDvwS+AODuMfEIMutR0iCWpPRlxfXt+NpZpvkXtw/BLYOjMCQ2CGEBRlmvb2n39fbjVaho6pRtHHJY77zHPjAhCX5G3yytq1ZRQSZXn+71PjZvX58tnreLMpLcunbC4JcKORzqmfwBPVsVPz1Whfo2i8yjITnlFDbgdFUr/Ay6i/paLXeeJ+8frkBz57XXhlY7h0PAOucNfoUKrmcluH1EDKKDTKhrs2C7s4ePLzlY3Ii80iYYdVpF9VJcOklcoP78VDWqWy4u9+cr8mvasDe/HlrNxbs15Pbw1FQAYo8NXwocS5OGB8Yn+mxfFTWbPCAC6ZEBaLfasS2vXO7h9BvX5C8zGQZd3ymbRqPBQ1NSAYhlkz3V40RJ9p2vR35NGwKMOleyhVIFmQ2uMt6+tmhBF5MS/+4eHd+nL1BkoAlzR4mLW2t9LHHom/P1KKhtR6BJj3t9sJ/jjZDWVDYfKEVXt13m0fS/V527vuaMilPMzjd/ox73O8/f9T52DV9ofbZYpnnG4CikOss0K8Hw+GBMSg+Hvdcaqi8ob+rEl6drAIi7jEl9pHv+trxytHb5xvpoQa24jqLRAIsyk67+B64Dg18qtDu/DsX1HQgy6TFfBf2RRiWGYHRiCKx2B7bklsk9HJLRm84+dfPHJSDEv28D8My0cAyJCUJntx3v+NB58vW5WvF6Nusxbyy3o18Lg06LxZniQ9y6fb7zECt5xbnr677xCYrqDzc0NhgTU8JgdwjYlOMbOxEuRdr5dtvQGCSGKWNyLpk7Kg4xwSbUtlrw8bEKuYfTL0obOvDVGU7+1Eyj0bj+7dbtL4EgeH+gJ7+mFfsLGqDVoM9Okd7uGRuPMH8Dyps6seNUdT+PsP9Ji1b3jk9AkNlwlXfLT0p+2H68ErWtTP7zVTWtXfj4WCUAuALWvS13JjF9eKQCje3WfhyZvKTe5feNT0CgiZ04rsWsYdGIDzGjod2KT49Xyj2cflXZ3IkPnC0/vjM9XebR9CU9n3zh7Efti7q67a4yzUps4SDt/tqQXYJOq28EjjfllMAhAJPTIzAwOlDu4dANyEoLx8DoQHRY7a7+mN5Oqk5z25Bot6+jMPilQmudD4v3T0hEgEoeFpc5e2xsyC6BwweyU+liFU2d+OyEuDizcsrFD0UajcbV7Hjd/mKfOU+k4M0DExLhb1TH9awES7KSodNqkFPUgNNVLXIPp9+cr23DF85FzkcVNvkDejKUNh0ogc3uOzuLJO0WG951Bu+V2LzdoNO6dtm+sbfIJ4IImw6ImahTB0YgPYqTP7V6YEIiTHotTlW24LAPlAeTdgvNHBaD+FC/S77HbNBhYYa46CYlF3mryuZO/Oek+LNv+aRUeQdzjUYmhGBsUii67QK25PpuQoiv25RTim67gPHJoRiVeHHPjvHJoRgRL5Yw9ZXzpKKpE587r2d3NrP3dnqd1hVoecvHkv/W7C2CzSEgKy0cY5JC5R5OH4NjgpCZFg6HAJ9N/vvgSAWaOrqRGOaHW4dEyz2ci8waFoOkcD80d3bjPR8IInTbHdh0wNkzdhIT/9RKo9G4EqnEnZXePW/v6ra7Nst44rxl8EtlShs6sMO5fVVND4t3jYljPWQftz5bLMszKT0cQ2ODL/me+ePE7L/CunbsPe/950lpQwe+dO5IWK6i61kJYoLNmD1C7IHiSxPA1bsLIQhi9qcSs7juGBmLMH8DKpu7XKUWfMm2vAq0WmxIjfDH9IGRcg/nkhZnJsOo1+JoWTMOlTTKPRyPstoc2Oyc/ElJOKROof5GV7Nub+8r2Gm1u4LoVyudumxSMrQaYG9+Pc5Vt/bH8GSxMbsEdocgVgmIDZJ7ONdM+vfb4Bw/+ZZuu8NVvnTlJXZ9Ac7kv0lS8p9vJIludO5ImJQejsEx6rmelWBhRjIMOg0OlzTheHmz3MPpF61d3a7dAN+5RXmJf0DPvX7TgRJ0+1jynyAIWOuciy/NSum3fmvXQ6fVYKVzl+2abwq9Pojw+clq1LZaEBlowu3DY+UeDt2E+8YnwmzQ4nRVK3KLvXve/vHRSjR3diMh1A8zBrs/iM7gl8psyOnJYFbiwuflsB6yb+vqtmOjMxPqUiU/JIEmPe4fL5by9IWAxrrsYggCMH1QJHck3AAp+/v9w+Vo8YE6yLWtFrx7SFwQfUyBu74AcSeC1M/P1/qcCILgKuOzbFIKtAqc/AFARKAJ9zpLJr++p0jewXjYf05Woa7NiuggE2YNj5F7OHSTljmzAD86WommDu8tD/bh0Qq0dNmQFO6HWwZFXfG9iWH++Lbz3PbW3V9WmwMbDyi3nNKV3D0mHsFmPcoaO7HrXK3cw6F+tv14FapbLIgKMmHOyLjLvm/e2AQEO5NEvz7r3eeJ1eZwzQmV1LdWLXqfS2t9YK4MiLupWi02DIgKwLcUuKsIEJP/IgKMqG6xYMcp30r+O1LWjGPlzTDqtVh4mTLNSrAgIwkBRh3OVos9hbyZlHSxMCMRRj2X/NUsxM+Ae8aIyX/evrayznneShWe3M2tV8Lf//73a/5F16+r2+7KYFZLyY/elrIess/66GglGtqtiA8xY9awKy9ASqXCdpyqRnmT954nXd12vC3tSOCurxsyKT0cg5x1kLf6QJ+4tfuKYLU5MCYpFJlp4XIP57Kkfmy7ztWipL5D5tH0n4PFjThd1QqzQYsHJyh38gcAq6alAgC2n6hChRffZ6UdQosykmDQcfKndmOTQjE8LhhWm8Ore4NKSWJLMq8tiC7tKNl6yDsTQT47UYXaVjGAMHuEujKYzQYdHnD+PGDyn+9585siAOIc+EoLkH5GHR50Jg6t9fLz5NPjlahrsyAm2OQK3NP1kZIAth0pR3OH993ze+u2O/D63kIA4q4vpSaWmfQ917AUePAVUuLfXaPjEB5glHcwVxBsNuCBCWIyvnROeaOCWjG4p9H0zMlJ3ZY6q5d87FxT9UYnKppxuKQJeq3GlUjtbm5dCfjrX/96Tb9efPFFdx7WZ3xyTDzZ40LMmDVMmVkvVzIoJghZPl4P2RcJguCa/C2bnAL9VRYgB0YHYXJ6BBwCsMGLHx4/PlqJxo5uxIeYMXOo+q5nJejdJ27t/mKvLmHQabXjLeeCyHemp0OjUebkDwBSIwMwfVAkBEHcrewrpAzceWMSEOJvkHk0VzY0NhiT0yNgdwheu8s2v6YN+wsaoNUAizj58woajcaVLOKtte+PlTXjSFkzDDoNFkxMvKY/Mzk9AkNigtBhtWPLQe8LCkr31sWZyaoMYkt9C748XePVSV3U1/HyZhwsboRBp3H1aboS6d721ZkalDZ4b+KQlJSi1utZCSakhGFobBC6ur2/T9zHRytR2dyFyEAT5jmrFijVksxkaDTA7nN1KKprl3s4/aKh3YqPjlYCUEcLBylZ6MvTNSj00n8jqUTot4ZEIzHMX+bRkDuMSQrFqIQQWO0OvOOl93xpV9vskbGICjJ55BhufeIoLCy8pl8FBQXuPKzPWOvKBE2+agBBqZY6fyj6Yj1kX3WopMm1FX5RxrUtQEoZbZtySmGx2T05PNlIgYylk64eEKTLu3dcAgKMOpyvbce+895bwmBLbimaOrqRFO6HO0YqP/NdylB6+6D3XsO91bZa8Olx5+RPJWW5Hp6WBkDsvdFhtck8GveTMm9vGxqD+FA/mUdD7jJvbLyrN6g33vOl83bOyDhEBF7b5E+j0WDFFGciyL4ir+oZdLqqBTlFDdBpNVii0iD2gKhAV1LXJh9KCPF1UuLfnJFxiA4yX/X9ab0Sh7y1r+GpyhYcKGqEXsXXsxJoNBpXyci1+4u96p7fmyAIeHmXuG64amoqzAadzCO6suQIf1epYl9J/nv7YCmsNgdGJYRgbFKo3MO5qvSoQNzmTDqW7tHepKvbji3OyghSqXDyDlIVtfXZ3tcbtM1iw7bD5QA826ObK64qcbxc3AZo0GmwMFPZ5ZSu5I4RvlsP2VdJDxb3jIm/5q3w3x4eg5hgE+rbrdh+vMqDo5PH0bImHCl1Xs8Kro2tBkFmA+5z9hP01h0sdoeA1bvF8gyPTktXZCPhC80aFo2YYBMavPQavtCmnBJ02wWMTw7FyIQQuYdzTW4bGo3kcH80d3bjPecDp7fotNrxrnPyt5STP68SYNLj3nFi9vc6L9sd3tLVjW15FQCuvxzy/LEJCDLrUVTvXT2DpF1fs0fEIDbk6gEEpVrmSv4rZfKfD2hot2LbEfFaXnmFXscXkgIamw+Woqvb+xKHpOf02SNjER2s3utZCeaPi0eQSY/i+g7szq+TezgesTe/HqcqW+Bn0LkWfpVOutdv8dJruDe7Q3AF6pdPTlF0VZLeVk1NBSD+G3lbqeiPj1aiubMbCaF+mDGYlYW8yT1je+75e8971z3/vcPlaLfaMSAqAJPSPdfaw6PBr7KyMvzf//0fnnzySTz++ON9ftH1kWrp3nGN2WNKZdRrsSDDN+sh+6Kali58ckzcDfHQdUz+9DotlmSKD4/eGNCQFnPmjopD5DVmdtPlSTttPvfSfoL/OVGFkoYOhPob8OA1lsGSm17Xs9Nz/X7vzn602R2uDE+17PoCAJ1W41qUe2NvkVeVkPvwaAVaumxIDPPDDGcWLnkPKaD5nxPVqGnpknk07vPeoXJ0dtsxOCYQGalh1/VnA0x6V438NV6SzdzS1ROYV3tv1G8Pj0FkoAm1rRZ8frJa7uGQh206UOLaDTE+OfSa/9xtQ6OREOqHpo5uVykxb9HS1Y33ndezGsqjKZ2/UY/7nf2L1jrXibzNK7vFXV8LM5IQ6q/cXlK9fWtIFOJCzGjs6HZVhPBWO8/UoKyxEyF+Btw9Ol7u4VyzaQMjMSg6EO3Wnv7r3kJKCluSlayKZFm6dv5GPe4b70z+86Ld4YIguHriLs3ybBDdY8GvHTt2YMiQIfjXv/6Fv/zlL/jqq6/wxhtv4PXXX0deXp6nDuuVmjt6MkFXqGhh7XJ8sR6yr1qfXQKbQ8CElLDr3g2xODMJeq0GucWNOFHR7KER9r/Gdis+OOI917MSDHb2E7Q7BGzM9q5AS++SH8snpcDfqJd5RNducab44J1T1ICz1a1yD8djvjhVg8rmLkQEGDF3VJzcw7kuCyYmItCkR35NG3af854sMqlu+JKsZMU2R6cbNzQ2GBNTwmBzCNjsJQsXgiC4ksJudPK3YnIKNBrg67O1KKhtc/cQ+93W3DJ0WO0YFC2WDVQzsfQ3k/98gc3uwDpnktvKKanXdS3rtD39wbwtoPFubpkruJ+V5rnMbl8iJVztOO19feJOVbZg19laaDXAI84y3Wqg12mxONM3kv+kliwLJibCz6jskpS9aTQarJoqnlNv7iuC3UtKyJ2oECuF6bUa1STL0vWRWgh9caoGVc3ekfx3qKQRp6taYTZocf94z563Hgt+PfXUU/jFL36BY8eOwWw2491330VpaSlmzJiBBx980FOH9UpbckthsTkwNDYIE1OuLxNUiZLC/TFjsG/VQ/ZFVlvPbojrKfkhiQ42u3obrfWi3V/v5JbBYnNgeFwwxier/3pWCqlUzIYcsfa4tzhY3Ii80iYYdVrX96gWsSFmzHTWVV/vRRlKF1q7vwiAmJlq0qtn8geIZUMfcGYOv7G3UObRuMfx8mZXWVlpJwx5H2n318acEq9YuDhQ1Iiz1W3wM+hwrzOz83qlRATgW0PEe67ad80LguBaWFNTOaUrWZSZBI1GLOXlDcFJurQvTlWjorkL4QFG3DX6+hNiFmYkwajT4kiZ+LPMG/S9nq8vIEiXNyAqENMGin3ivG1N5VXnrq85o+KQFO4v82iuz8KMJOi0GhwsbsTpqha5h+MRxfXtrhLLatyZfe+4BIT6G1Da0IkvTnnHbmwp8W/2yFhVVwqjyxscE4TMVDHhe9MB77jnS0kCd4+OR4i/waPH8ljw69SpU1ixYgUAQK/Xo7OzE4GBgfj973+P5557zlOH9ToOh/dN/oCeRna+UA/ZV316vBK1rRZEB5kwxxnEul5SWYz388rR3Kn+mswOh+Daju5N17MS3D4iBtFBJtS1WbD9hPf0mHr5a3Hyd9/4BEQFqa9EpjQh2nqoHB1Wm8yjcb/8mjbsza+HVgNXtrbaPDQlFRoN8NUZ79gtIu2quGMky8p6szkj4xDmb0BFcxe+Oq3+HrLSeTtvbDyCzTc++ZOSjd7JLUObRb333H3n63G+th0BRp2rx5vaJYb54zZncHKDl+1Spx5S2dHFmUkwG64/ISYy0IS5o5zJf16SOPTN+XoU1LYjsFfPRnIP6Tl78wHvWVOpbO7EB86qR9+Zni7zaK5fTLAZtw+PAeC9u7/W7S+GIAAzBkchJSJA7uFcNz+jzlWe3xuS/9osNmxzlpVVS388ujFS8t+mnFLYVN5DtrHdio+cLXKW9kMQ3WPBr4CAAFitVgBAXFwczp8/7/paXZ33lNbxtN35dSiu70CQSY/5Y73nYfFbQ6MR7yP1kH2VNPlbmpUCg+7GbjWZaeEYEhOErm4H3sktc+Po5PH1uVrxejbrMW+sempjq4GhV5mJdSrPeJecr21zZaM9qsLJHyDWVU+J8EerxeaayHoTqeb2bUNjkBimrsxUSWpkgGuHntp7BYk9RcTzbBknf17NbNDhwYneUUauvs2CT4+JSRtLs25u8jd9YCTSIwPQZrFh6yH1PjdJO9fuHZ+AoJsIBiqNtGixJbfMaxaqqcfpqhbsL2iATqu5qd0Qy507/T88UoHGdqubRicfqXf5feMTEGhST/luNZg1TFxTaWi3uvpsq92avUWwOQRkpYVjTFKo3MO5IdLP8vcOl6NdxYkol9LVbcfbB8XnCzW3cFgxOQU6rQb7CxpwskLdO/TeO1yOdqsd6VEBqi8TTVd2x8hYRAQYUdXShR0qT/57J7cMVpsDIxOCMSbx+lrk3AiPBb8mTZqEPXv2AADmzp2Ln//85/jjH/+Ihx9+GJMmTfLUYb2OVO/7/gmJCPCih0WdVuMz9ZB90dGyJhwuEctOLc668bJTGo3GVc983f5iOFRe2kgq3/jghCRV9W5SC6m5a05Rg1eUmVi9W8xEmzUsGgOjA2UezY3RajVYIt3rvSzTvd1iw7u56p/8AXDVvn8nt0zVu2zfP1yOzm6xR1Ame4p4PenesvNsrar7nWzJLYPV7sCYxBCMusnJn1arcd2P3vymCIKgvuemyuZOfO5M/FBbud+rmTE4Ggmhfmju7MbHR71joZp6vPmN+Jw/e0QM4kL8bvhzxieHYkR8MCw2B94+qO6+hhVNnfj8pHg9L1dheTSl0+u0PX3ivGCnYGtXt2tn7HduUWfiHwBMGRCBNGciyjYvS/774EgFmju7kRjmh1udu5nVKD7Uz9ViQ827vwRBcLUXuNGesaQeJn3v5D/1rq04HDff6/h6eSz49cILLyArKwsA8Lvf/Q4zZ87E5s2bkZqaitdee81Th/UqpQ0drmiuGmvpXs3CjCTovbwesq+Sdg/cOSrupmsOzx8nZgkW1rVj73n17hotbejAV2ek65k7EjwhJtiM2SPEMhNq73dS22rBu86s/e/cMkDm0dycByYkwqjT4li59/SvAMRyrK0WG1Ij/DFtYKTcw7kpUwZEYEhMEDqsdmxR6UKbIAiunXhLs5I5+fMBqZEBmD5I7HeyUaX9ThwOwbXQd7O7viT3T0hEgFGH87Xt2JOvvuemjdliH7estHAMjgmSezhupdNqXAvV61S+Y5H6au7oxvvOslMrbzJoq9FoXIGiddnqTv7bmFMChwBMSg/HIC+7npViYUYyDDoNDpc04Xh5s9zDuSmbckrRarFhYHSgq4elGvVO/hNLBKr3Gu5NEARXMu+ySeLOKTV7eGoqAGDbkQrUt1nkHcwNOlTSiNNVrTAbtHhgfKLcw6F+sCQzGRoNsOtsLYrr2+Uezg355nw9ipwV7u4Z0z8VsTwW/EpPT8fo0aMBiCUQ//3vf+Po0aN49913kZLifYEcT9iQUwJBAKYOjFBt1v+VRAebcfsI766H7Ivq2iz46IiYzSr1nrgZgSY97nc2f1dzQGNdtlgbe/qgSKRHed/1rBTLJ6UCEHeAtHSpdwfL2n1FsNocGJMUiozUMLmHc1MievWvUHt5MsmFkz+tyid/Go0Gq5wTwDXfFMGuwoW2g8WNOFvdBj+DDvdN4OTPV0gBo7cPlsJqU1/t+935dShpEMsh3+2myV+Q2YAHnNfAmyorZWq1ObAhRwzAL1f5jtrLWTBRTP47XNKEExXqXqimHm8fLEVntx1DY4PcsvN43tgEBJv1KG3oxNdna90wwv5ntTmw0Xk9e9suTiWJCjJhzsg4AD0lJtWo2+7A684dOI9NT1P9s/UDExJh1GtxsrIFeV6S/HekrBnHypth1GuxYOKNV/dRivHJYRiTGCI+e6h0F420jnr36HiE+HtPmWi6vOQIf9wyKAqAGDNQIylh9d7xCf1W4c5jwS+J1WpFWVkZSkpK+vyiK+vqtmPzAefkz7mY6428uR6yr9qUU+Iq3zMu2T2L9tICyI5T1Shv6nTLZ/anrm473nZdz965mKMUk9LDMTgmEB1WO7aqtE9cp9WOt5wPBN+Znu4VO1ikJqYfHKlAc4d6g5IScceymGX34AT1T/4AcZdtmL8BZY09JYrURHqIvmdMPIK9qEcQXdmsYdGICTahrs2Kz05UyT2c6yadt/ePT4SfUee2z13hTD7acboGJfXqKQn52Ykq1LVZEB1kwuwRsXIPxyOigkyYPVJKCOGc2BvYHQLe2l8EAHhoSqpbntv8jD2ljdQa0Pj0eCXq2iyICTbh28Nj5B6OV5PK3W7LU+9z9sdHK1HZ3IXIQBPmeUGv+7AAI+4aJQYl13lJord0L7prdBzCA4zyDsYNxOQ/sfT7W/uLVZdE1dhuxUfOXn9LucbkU5Y6qwhsOVgGi01dPWSrW7pc5c3dVfXiWngs+HX27FlMnz4dfn5+SElJQVpaGtLS0pCamoq0tDRPHRYA8M9//hOpqakwm83IyspCTk7OFd+/ZcsWDB06FGazGaNGjcInn3zi0fFdi0+OVaKh3Yq4EDNmDVPvlu+rmTIgwtWY29vqIfuibrvD9XDnjl1fkoHRQZgyIAIOAdigwp0jHx+tRGNHN+JDzLhtqPdez0rQu1TMWpWWmdiSW4qmjm4khffUIle7iSlhGBIThK5uB7YeVmdQsjdpF+q8MQlek2VnNuhcvTjVVvu+vs2CT4+JgQ9vLBNNl6fXabEoo6e0kJpUNndih3Py5+5yyAOiAl0lIdc6F+XVQNpRuzgzGQadx3M0ZbPMOdnfdrgcbUz+U72vTtegtKETIX4Gty7aSz/Pdp6tVVUQW+Ir17MSTEgJw7A4sU/cllz1la8WBAEv7yoAAKyamgqzwX3JIHKSAhIfHa1AU4dV5tHcnIZ2Kz5y9qr0pp2cc0fFITrIhNpWCz45pq5enO/klsFqc2BkQjDG3GTPWFKX24ZGIy7EjIZ2K7YfV1fy36acUtgdAjJSwzAktv/KIXvsKWTVqlXQarX46KOPkJubi0OHDuHQoUM4fPgwDh065KnDYvPmzXj88cfx9NNP49ChQxgzZgxmz56NmpqaS77/m2++weLFi/HII4/g8OHDmD9/PubPn4/jx497bIzXQmpYuiQzGXovfljUaHrVvlfpQjX1+PxkNapauhAZaMSdo+Pc+tlSQGNTTqnqshukXTxLJ6V49fWsFPPHJbj6new7Xy/3cK6L3SFg9W4x8PDotHTV11KXaDQaLHUu7q7PLlH1vb6mtQvbj4uTI28ry7V8cgr0Wg2yCxtUVY5rS24ZrHYHRieGYBQnfz5nUWYSdM7zNr+mVe7hXLONOaVwCEBWWjgGRrt/8veQMwlp84FSdFiVH2A5XdWCnKIG6LQaVyDeW01KD8eAqAC0W+14z9knitTrTeduiEUZSW7dwZnWq6+h2spGn6xowcHiRuh79T4iz7kw+U9tfeL25tfjVGUL/Aw6144GbzA+ORRDY4NgsTnwjkorkkg2HxDLS49KCPGqQItRr3VdO6/vLVTNHNXhEFw/F5ZmpXhFpRi6dmpN/rPZHdh0QNws0d8Jqx5bhc3Ly8PLL7+MOXPmYOzYsRgzZkyfX57ywgsv4LHHHsOqVaswfPhw/Pvf/4a/vz9ef/31S77/b3/7G+644w788pe/xLBhw/CHP/wB48ePx0svveSxMV7N8fJmHC5pgkGnwSIfeFj0xnrIvmqNs7fE4sxkmPTuzdj69vAYxAabUd9udWX4q8HRsiYcKRWv54UZ3lEeTemCzAbc52z4qrY+cZ+dqEJJQwdC/Q14cKJ39S26d1wC/I065Ne0IbuwQe7h3LDNOaXotgsYnxyKkQneM/kDgLgQP8xxlmh5Y2+RvIO5Rg6H4KrTv6wfSyeQcsSF+GGmc1e1WkoLddsd2JTj2cnfrUOikRzuj5YuG94/rPzqCtIukdkjYhAbYpZ5NJ6l0WhcpV7WM/lP1fJr2rD7XB20Gs9cy9IOi80HS9HVrZ7kPymRd/bIWEQHe/f1rBTzx8UjyKxHcX0HdufXyT2c6/LyrvMAgIUZSQj1V385PYlGo3HdFzaoOPnP3ivQsnyy9wValmQlw6jX4mhZMw6VNMo9nGvyzfl6FNV3IMikxz1u6hlL6iIl/x0oasSZKnUk/315ugaVzV0IDzD2e4UjjwW/hg8fjrq6/v2ha7VakZubi1mzZrle02q1mDVrFvbt23fJP7Nv374+7weA2bNnX/b9/UGqpTtnZByigkyyjaO/hPobcddo76qH7ItOVbYgp7ABeq3GI7Vb9Tqta5fgWhVlN0iLOXNHxSEy0PuvZ6WQduR8fqoalc3q6BPXu+TH8kkp8Df2T/PP/hJkNmDeWPHhXE0ZSr3Z7A5XY1lv2/UlWTU1FQDwQV4F6tos8g7mGuzOr0NJQweCzHrcNca9O45JPaTSQu8eKkOnVfkLxDtOVaOm1YLIQKPHelvptBpXH5g3vylS9KJbS1e3aweUN/c67u3+8YkwG7Q4XdWqmsU2upg0b585LAZJ4f5u//zbhkYjIdQPTR3drpJjStfc2Y33Xdezdz4rKZG/UY8HJoiJc2tV1CfuVGWLK4D8yDTPtkeRg1SRpKBOfRVJJDvP1KCsUSzt6o2BlohAE+Y5v6/XVZL8J82l7x2fgACTd60Z0LWJCTbj28PEfppq2R0u9bp9cGKi2zdLXI3Hgl/PPfccfvWrX2Hnzp2or69HS0tLn1+eUFdXB7vdjpiYvg1VY2JiUFV16Z0iVVVV1/V+ALBYLB77fpo7ul29r7x1Ye1SlnlRPWRf9aZz19fskbEey9hdlJEEvVaD3OJGVZTkamy34oMj4vW8woeuZyUYHBOErLRw2B0CNqqkofzB4kYcKW2CUa/1qlrqvUmB8c9OVKG2VfmBlQt9cUrMVooIMGLuKO8MtIxPDsPYpFBY7Q6sV0FCynrn5O/+8YleFzCmazd9YCSSw/3R2mXDh0eUv8tJmvwtmJgEo95z5ZAfnJgEP4MOZ6pbsb9AuTtut+aWocNqx6DoQExKD5d7OP0ixN+Au0eLi21quNfSxVq7uvGus5TZQ27sddybTtvTIkAtAY2th8rQ2W3H4JhAZKX5xvWsFNKayo7TNShtUEefuFd3i4l/c0bFeSSALLdAkx7zx4m9ANerZE56IamSyoKJiV7Tj+1Cq6aKgdftx6tQ0aTsxNnqli587uwZ64mkc1IP6Z6/9VA52hXeQ7akvgO7ztUCgCzlkD0225o1axb279+PmTNnIjo6GmFhYQgLC0NoaCjCwsI8ddh+8eyzzyIkJMT1KynJfaXMtuSWwmJzYGhsECamqPvv6XqMSwp1NWlVez1kX9TUYcX7eWKGn6cmfwAQHWx2bY9dq4JydtL1PDwuGOOTfed6VgopgLQhR6xRrnQvfy1O/u4fn+C1u35HJoRgTFIouu0C3j6ovobca/cXARDLsvR3tlJ/knZ/rcsuVvS1U9nciS9ckz/vLxNNl6fttUCs9OzHwrp27D5XB40GHu9tFeJnwL3jxUU3KUlJaQRBcO3o98ZySlci7Vj86FglGtuZ/Kc27+SWod0ZtJ0yIMJjx1mUkQSjTosjZc04ovAWAX2v51Sfup6VYEBUIKYNFPvESZUKlKyyuRMfOBO/v3tLusyj8ZzeyX81LV0yj+b6FNe34+uztdB4qLSrUgyPD8akdDFxVultEzbllMLuEJCRGoYhse7vGUvqMWVABFIj/NFmsbmS7pVqQ04JBAG4ZXAUUiIC+v34Hgt+ffXVV/jqq6/w5Zdf9vklveYJkZGR0Ol0qK6u7vN6dXU1YmMvXVIkNjb2ut4PAE899RSam5tdv0pL3bOA53D0PCyu8LGHRbEesrgAoOZ6yL5q84FSdHWLQR5PB22lgMb7eeVo7uz26LFuhsMhuMp4+tpijlLcPiIG0UEm1LVZsP2EsvvEna9tcy3iPzLNeyd/ALDMuUC9MacEdhU15M6vacPe/HpoNXAtsnuruaPiEBNsQm2rBR8fU+6D9KacUjgEICstHINiOPnzdQ9OSHQtEB8rU+7u8I3OBclbB0f1S5b7Sudz039OVqFcgdnM+87X43xtOwKMOtzrzI73FWMSQzAyIRhWJv+pjqPXAumKKZ6dt0cEmnCns0WA0ku/782vR0FtOwJNep+7npVCqh4kzs+VXQZ4zd4i2BwCstLCMToxVO7heMzw+GCMTw6FzaG+5D+pvN4MmRas+5O0+2tjToliS2jb7A5sOuDZnrGkHtpeLWfWKbiHrMVmd9375EpY9Vjwa8aMGVf85QlGoxETJkzAjh07XK85HA7s2LEDkydPvuSfmTx5cp/3A8Dnn39+2fcDgMlkQnBwcJ9f7rA7vw7FzqaFUl8UXzJvrPrrIfsie6+g7copng/yZKSGYUhMELq6lb1Q8PW5WlcfGl+8npXAoNO6surXKTyDa/XuQgDArGHRGBgdKPNoPOuu0fEINutR1tiJXWdr5R7ONZMmf7cNjUFimPeVZenNoOspvfn6HmX2CuruNflbyskfQVwgnjNKTF5T6u6vrm47trgmf/1z3g6JDcLk9Ag4hJ4yoUoiBRDuHZ+AILNB5tH0L42mZ9FifXYxHCpKCPF1u87VorCuHUEmPe7rhyCPtMj54ZEKRe8SlHbI3zc+AYHsQyOLmUOjER9iRkO7FZ8cU26fuNaubmxwlgH8jhfv+pJI9/qNzl07atBptePtg+J6iy/075s1LAZJ4X5o7uzpQ6o0X54WS/CHBxhdFZHItz0wIRFGvRYnKlpwRKHJf9uPV6Gh3YrYYDNmDo2WZQyeKzIPoKmpCX/5y1/w6KOP4tFHH8Vf//pXNDd79h/j8ccfx6uvvoo333wTp06dwve//320t7dj1apVAIAVK1bgqaeecr3/pz/9KbZv346//OUvOH36NJ555hkcPHgQP/rRjzw6zkuR6njfPyHRJ5sWBpr0rtIsaq2H7It2nKpGWWMnQv0NmDfW85M/jUbjymhbt1+5CwVSWcYHJySxD42MlmQlQ6/VIKeoAaerPNNv8mbVtlrw7iFxYvGdWwbIPBrP8zPq8MAEsVywUheoL9Rusbn6evhK/77Fmckw6bU4Vt6M3OJGuYdzkR2nalDdYkFEgBF3jODkj0TSAvG2vAq0dClvd/inxyvR2NGN+BAzvtWPk7+VzpLUmxS2E6CyudPVt8Jbe11ezT1j4hFk0qOovgPfMPlPNaQyog9M7J95+/jkUIyIF1sEKHXnSEVTJz4/KV7PvrBQrlR6nbanT5wCEx4km3JK0WqxYWB0IL41RJ7F0P505+g4hPobUN7UiZ1nauQezjX58GgFmju7kRjmh1t94N9Ip9W4dsu/sbdQkcl/0jrpgxMTvboEP127sAAj7nL2IldikhvQ09t2UWYS9DqPhqEuy2NHPXjwIAYMGIC//vWvaGhoQENDA1544QUMGDAAhw4d8tRhsXDhQvz5z3/Gb3/7W4wdOxZ5eXnYvn07YmJiAAAlJSWorOzJgJkyZQo2bNiAV155BWPGjME777yD999/HyNHjvTYGC+ltKEDO06LPwSX+8jC2qWouR6yr3rTGbRdmJHUbw1Q7x0nZhMW1rVj7/m6fjnm9Sht6MBXzodaqZwnySMm2IzZzoVxpdbvXruvCFabA2OSQpGR6hu94aRJ+ZenaxRZhutC7+eVo9ViQ2qEP6YNjJR7OP0iPMCI+c6Ehjf2Fsk7mEuQAqcLMpJg1MvzEE3KMzElDINjAtHZbcd7h5SXtSuVQ16cmQydtv/KIc8aFo2EUD80tFvxoYJ6AmzMFsvfZqWFY7CPli4N6JX8t06hixbUV1FdO3Y6d673V9BWo9G4km/WKXSX4IbsEjgEYFI6SxHLbWFGMgw6DQ6XNOF4ufJ2AnTbHXh9r1j14rHpadD2489DuZgNOjwwPhGAOu71giC4knmXTUrp12cWOS3ISEKAUYdzNW3Yk6+sdaaS+g7sOif+7Fni4Z6xpC5LnWuOHx6tQHOHspL/zla3IqeoATqtBosy5DtvPbZa8F//9V+45557UFRUhK1bt2Lr1q0oLCzEXXfdhZ/97GeeOiwA4Ec/+hGKi4thsViQnZ2NrKws19d27tyJNWvW9Hn/gw8+iDNnzsBiseD48eOYO3euR8d3KeuzxeZvUwdGYECUd5e8upJhccGYkBKmynrIvuhcdaurB05/ZvgFmPS437lQoMSAxrrsYggCMH1QJNJ9+HpWCmknwPuHyxW3E6DDasNbzgnQd29J95necAOjA11luDYpvCH3hZM/X5igS1ZNSwUAbD+hrF5BRXXt2H2uDhoNJ3/Ul9hDVpm1709VtiC3uBF6rQYLM5L69dh6ndb19/LmPmWUMrXaHNiQIz7r++quL4mU/Pf5qWpUM/lP8dbuF5/zbx0ShbTI/uuBc8+YBASb9Sht6MTXCisbbbX1lCL29etZCaKCTJgzUtwJ8JYzUVVJPjpagcrmLkQGmjDfh3rDScl/O8/WorShQ+bRXFleaROOlTfDqNdiwcT+fWaRU7DZgAcmiEFKpSX/bcgR14xv8YH+a3R9xieHYWis2BpGqiikFNJutFnDohEbYpZtHB7d+fXEE09Ar+8pA6DX6/GrX/0KBw8e9NRhVamru6f52/JJqfIORgGkBnhqqofsq6RdX7OG9X8PHGmH5I5T1YpalO3qtuPtA9L17Lu7OJVkUno4BscEosNqx1aF9Yl7J7cMTR3dSAr3c+1Q8xVShtKmA6XotjtkHs3lHSxuxOmqVpgNWjw4wXcmfwAwNDYYUwZEe0Sn5AAAd/JJREFUwO4QFLV4ssEZMJ0xOApJ4d7df42u3/xxCfAziFm7B4qUU7JT2q14+4gYRAf3/+RvoXOX5PHyFhwqkf/vZfuJKtS1WRAdZMLtI2LkHo6shsQGISM1DHaHgE05TP5TsnaLzTVvl8qJ9hc/ow4POhehlfQzGRBLuta1WRETbMK3h/v29awU0k7BbXkVaOpQTp84QRDwyi5x19eqqak+VbotPSoQUwdGQBCAjQpP/pNKZt41Og7hAUaZR9O/HpqaBkCsUFJY1y7zaEQWW8+asbReSiTRaDSuHtjrs5WT/NdhtWGrsxLHMpnXRj0W/AoODkZJycU39NLSUgQFcRt8b58cq0RDuxVxIWbMGub9tXSvZu4o9dVD9kUtXd2uG9lD/Tz5A4CB0UGYMkDcObJBQX2DPj4q9vNICPXDzGGc/CmBRqNxBSLXKmgngN0hYPVucfL36LR0nyknIbl9eCwiA02obbW4ekQokbS7dN6YBIT4G2QeTf9b5ZwAbsopRYfVJvNoxASDLc7J37IsJhjQxYLNBswfFw9AOaWF2iw2VxlGuc7b8AAj5o0R/17WfCP/38s65711cWYyDDLV/1cSaVFg04ES2BScEOLr3jtcjtYuG9IiAzBjUFS/H186T3aerUVJvXJ2jkg75JdkpvB6VogJKWEYFif2iXtHQcl/e/PrcaqyBf5GnU8u4kvPAG8fLIXVpsx7fUO7FR8dFVvF+OJOzrTIANzm7Mu6xlmeU27bj1ehod2K2GAzZvZjz1hSj3vHJSDAqMP52nbsL2iQezgAgA/yKtBqsSElwh9TB8jbOsJjTyYLFy7EI488gs2bN6O0tBSlpaXYtGkTHn30USxevNhTh1Wlt1wPi8myNX9TErNBhwcnqKcesq/acrAMHVY7BscEYvKACFnGIAU0NuWUwmJTRgN3qYTdkqz+7edBVza/18PAPoU0lP/sRBVKGjoQ6m/AgxMT5R5OvzPqtViYoex7fU1rF7YfFyd/vtqP87ah0UgO90dzZ0/Cg5w+PS4mGMSHmPEtTv7oMqQycuJuBIvMowG25ZWj3WpHemSAbM9MQM9OlU+PVcpaXu90VYur/v8SH1z8vJQ7RsYiPMCIyuYufHmayX9KJAg9u6CXy1QGOS0yANMHRUIQenaTyu1kRQsOOku6Ls70rR3ySnZh8p9S+sS9vOs8AGDBxCSE+vvWjiIAmDU8BtFBJtS1WfHZiSq5h3NJmw+IgbnRiSEYmxQq93BksWpqKgCxSosS2iasd/aMXZSZxDVjuqRAkx7znGVk1ynk+WB9tnjeLs1Klr11hMeumj//+c+47777sGLFCqSmpiI1NRUPPfQQHnjgATz33HOeOqzqHCtrRl5pEww6DRaxb4XLkqyerDal10P2RQ6HgLXOyd+Kyamy9Sn69vAYxAabUd9uxafH5H94PFrWhCOlTTDqtP3ez4OuLMhswH3OJsNK6BMnCAJe3lUAQFxA8Tfqr/InvNPizGRoNMA35+txvrZN7uFcZHNOKbrtAsYnh2JkQojcw5GFTqtx7e5d8438vYKkyd/iTCYY0OWNTAjBmKRQdNsFbDkob8a7IAhY5zxvl2Qly9rbcWRCCCY6e+tKE1I5SD+HZ4+IQYwMJSCVyKTXuRJh5Py3ocvbd74eZ6vb4G/U4QEZk5aknRibD5aiq1v+5D+pPNrskbGylHSly5s/Lh5BZj2K6zuw65z8feJOVbZg97k6aDXAI9PS5B6OLAw6LRY51wmUEsDuze4QXOOSu0yZnKYNjMSg6EC0W3taWsjlbHWrK2FoUQbXjOnypJ2lnx2vQm2rvMl/R3r1DXxAAa0jPBb8MhqN+Nvf/obGxkbk5eUhLy8PDQ0N+Otf/wqTyeSpw6rO2v1FAIA5I+MQFcS/F0laZACmDYxURT1kX/T12VoU1XcgyKzHvTI2qdXrtK6M4bUK2DkilfyYO0os50bKIu3c+fxUNSqb5e0Td6CoUQyU6rU+WU5Ckhjmj28NEXfvbFDYYp/N7nD1lvLlfyMAeHBiIgJNeuTXtGH3uTrZxnG6qie7nAkGdDVSOaUNOfJmvB8ubcKpyhaY9FpXE3U5Sbu/NmSXyFJyqaWrG+8fFneRstdxX0uciZC7zimrpB2J1nxTBAC4f3wigs3ylUG+bWg0EkL90NTR7SpNJpfmzp7reYUPL5Qrlb9R7/q5o4QqC686E//mjIrz6Z6tizKTodUA+wsakF/TKvdw+th5pgZljZ0I9TfgHmepZF+k0Whcpd/XfFMEu4zPkeud1+6sYdGIDWGCAV3e8PhgjEsOhc0huHrEyUUKot85Shl9Az2+X9Lf3x+jRo1CSkoK/vOf/+DUqVOePqRqNHVYsS2vAoDvllO6kmWTxAmgkush+ypp8rdgYhICTPLuWFmUkQS9VoPc4kacqGiWbRyN7VZ8cITXs5INjglCVlo47A4BG2UOtLzinPzdPz7B5xMfpHv9O7llishglnxxqgaVzV2ICDBizqhYuYcjqyCzwbV48rqMte+lXV+3j4hhdjld1d2j4xFs1qO0oVPWjHfpvL1rdLwiSjzdMTIWMcEm1LVZ8Mmx/l8435orls0eFB2ISenh/X58JUuJCMAtg6MgCHAlX5AylDV24ItTYn/SlVPkfc7vXS5UqsQhl3dzy9DZLZbBz0zj9axE0u6dHadrZK2oU9nc6Zorf/eWdNnGoQTxoX64bajYG1xpO32lndkLJibBbNDJPBp53TsuAaH+BpQ1drru//2tw2pzlZ335Z14dO2k3V8bsktkC9o2d3S77vdK6e3oseDXggUL8NJLLwEAOjs7MXHiRCxYsACjR4/Gu+++66nDqso7uWWw2BwYGhuEiSlhcg9HcWYOU349ZF9UUNuGr8/WQqMBViggyBMdbMYdI8WF6bUylrPbklsKi82B4XHBGJ/M61mppB08G3LkC6qfr21zPUA/Ms23J38AMGOwmMHc3Cl/BnNv0s7shRlJMOl9e/IHAA9NSYVGA+w8UytLicp2iw3vObPLpX5ORFfiZ9Th/gnylpFr6rDio6POyd8kZUz+DDqt6xqSkpn6iyAIrp36yyenyFoCUqmkRYK3Dyqnny05eyYJYimsgdFBcg8HizKSYNRpcaSsGUdKm2QZg1jSVbqe5SuDT1c2ICrQVVFHzkDLmr1FsDkEZKWFY3RiqGzjUArpmeDd3DJ0WpVxry+qa3et8yhlwVpOfkYdFjt3ZL8hU/LfB3kVaLXYkBLhj6kDImUZA6nLnaPjEOJnQHlTJ74+K08P2a2Hy9DVLcY6Jigk1uGx4NeuXbswffp0AMB7770HQRDQ1NSEv//97/h//+//eeqwquFw9Ez+5OyZpGQGndbVB02J9ZB9lZQN9K0h0UiJCJB5NCIpoPF+XjmaO/u/IanD0dPPYwUXcxTt9hFSUN2C7TIF1VfvFnd9zRoWg4HRgbKMQUl6ZzAr5V6fX9OGvfn10GrgGpuvS40MwMyhYonKN/t5wRwAtuVVoM1iQ3pkAKYMiOj345M6SUGeHaeqUdHU/+VupUS34XHBGKegpvGLM5Nh1GmRV9rUrwvn+87X43xtOwKMOlnLZivZzKHRiA02o6Hdiu3HmfynBF3ddmx29nyRyobKLSLQhDtHxwGQr/T73vx6FNS1I9Akbxl8ujqpKsnbMvWJa+3qdpU3/+4MJv4BwIxBUUgM80NLlw0fOpNk5CbNw2YMjlLMOo/clk9KgU6rwf6CBlmqDEkB66VZydCy1zFdA7NBhwel5L/9/Z/wIAhCn/NWKWujHgt+NTc3Izxc3Pq+fft23H///fD398edd96Jc+fOeeqwqrHrXC2K6zsQZNJj3ljfraV7NYsykhRbD9kXtVlseCdXbByvlMkfAGSkhmFITBC6uh2u8fWnr8/VoqRB7IF2D69nRTPotK4MrnUy7BSsbbXgXWfpgu/4eMmP3h6cmAi9VoPDJU2yli+VSJnMtw2NQWKY7/YkuJBU+/6d3LJ+TTTonV2+REEP0aR8A52l9RwCsKmfG5YLguBa7Fs6SVnnbVRQz8J5fwazpQSq+8YnIkjGnklKptdpsShT7Gkox6IFXWxbXjmaOrqRGOaH25xJIEoglcD68EgFGtut/X78t5wlF+8bn4BAmcvg05XNHBqN+BAxqC5HudtNOaVotdgwMDoQtw5WzjUkJ23v5D8F9GPrtNrx9kFxHUUJ1X2UIj7Uz1VlaM3eon499pHSJhwrb4ZRr8UDE9jrmK6ddG/58kwNyhr7t9xtdmED8mva4G/UYb6CEmM8FvxKSkrCvn370N7eju3bt+P2228HADQ2NsJsZp8GaRHn/gmJsvdMUrL4UD/MHKbMesi+6L1DZa7M++kDlbPtWqPRuDLa1u3v/8b2UrnFByckwd/I61nplmQlQ6/VIKeoAaerWvr12Gv3FcFqc2BMUigyUpWxBVwJooPMmO2cWMh9r2+32PBuLid/lzJlQASGxAShw2rH2/0YSMgrbcLJyhbn5C+x345L3kFaIN6UU4Jue/+Vu913vmdXxLyxypn8SaQkpo+OVqKuzeLx41U2d+JzZ8lf9ka9skUZydA5n1POVjP5T06CIGDNN1K1FnEHgFKMTw7FiPhgWGyOfm9sX9HU0wNnOfvQKJ5ep3Uthr7Vz8l/3XaHq1/sY9PTuHullwUTk2DQaXCkrBnHyuRN/vvwSAWaO8Ug/wwGKPt42Jn8t+1IRb88L0mknXh3jopDeID8PWNJPdKjAjF1YAQEQUw+6E9SrGPe2ARFJbp5LPj1s5/9DEuXLkViYiLi4+Nx6623AhDLIY4aNcpTh1WF0oYO7Dgt1t7k5O/qpHrDSqqH7IsEQcCb+3omf0p7cL13nJh1WFjXjr3n6/rtuKUNHfjqjHg9L1NIPw+6sphgM2aPEAMt/TkB7LDa8JbzYeC7t6QraheAEkj3+vcPl6O1q//Ll0rezytHq8WGtMgATFNQkF8JNBoNVk1NBSD2CrL1UyBBKit71+g4hPpz8kfX5/bhsYgMNKGm1YId/diwfJ1z0WL+uHhF7ooYmxSKMUmhsNod2NgPSQcbnY23s9LCMThG/p5JShYbYsasYeLioxJ2BPiyA0WNOFXZArNBiwUTlZV5r9FoXEk667L7N/lvQ3YJHAIwOT0Cg3g9q8LCjGQYdBrklTb1a6Dlo6MVqGzuQmSgSVG7AJQgMtCEO0aKu7DlLP0uCALecvY6XjZJWUF+JRifHIoxiSGw2hyuHf2e1tzRjQ+OOHvGsgQ/3YBlztLvmw70X6/72lYLPnO2FlHaeeux4NcPfvAD7N+/H6+//jr27NkDrVY8VHp6us/3/FqfXQLB2TB3QBT7vVzNLYOikBSurHrIvmhvfj3ya9oQ0KuBvJIEmPS4f7z4QN2fAY112cUQBGD6oEik83pWDSnx4P3D5Wjpp0DLO7llaOroRlK4nyv4Rj0mp0cgPSoAHVY73s+T514vCIJrJydrq1/a/HEJCPMXm+h+0Q+BhKYOKz5y/uxfxuxyugFGvRYLM8TnlnX9VEaupqUL/zkhXh9S3zElemhKz8K5J3fFWW0ObHBmnkp9WunKpPvd1kPl6LDaZB6N75LKgt47LkGRyRf3jElAsFmP0oZOfH22tl+OabHZsemAeC9lIq96RAWZMHeU1CeuqF+OKQgCXtkl7vpaNTUVJr2uX46rJsucC8Tb8ir6bU56obzSJhwvFyssKC3IrwRi8p+4+2vt/uJ+CSRsPVyGrm4HhsYGYUIKq8XQ9Zs1vKfX/ecn+yf57+2Dpei2CxibFIqRCSH9csxr5bHgFwBMmDAB9957LwIDexaE77zzTkydOtWTh1W0rm67qywBF3GujVarwZJM8e+K2Y/yWeOc/D0wQbl9GqQJ2I5T1Sjvh8b2Xd09pb9Y8kNdxMzzQHRY7djaD33i7A4Bq3eLk79Hp6Uzo+4SNBqNa5F4/f5iCEL/li8FgIPFjThd1QqzQYsHWVv9kswGnat0zuv9UPv+ndwyWGwODIsLxrikUI8fj7zT4sxkaDTAnvw6FNa1e/x4mw+UwuYQMCElDMPigj1+vBs1d1QcIgONqG7pydT0hO0nqlDXZkF0kAm3j4jx2HG8ydQBkUiJ8EerxYYPZEoI8XWVzZ3Y7rwulNTruDc/ow4POherpR5cnrb9eBXq2qyICTbh28N5PauJNF/dlleBpg7P94nbk1+HU5Ut8DfqFLcLQCky08IxKDoQnd12vOfsC93fpMS/u0azvN7lzB0Vh+ggE2pbLR7vmycIgqsNwFL2OqYbZNBpsShDfD5Y1w/r6HaHgI054nmrxFiHR4NfZWVl+L//+z88+eSTePzxx/v88lWfHKtEQ7sV8b3KWdDVLZiYqJh6yL5ILNUp9WlIlXcwVzAwOghTBkTAIQAb+qF0wMdHK9HY0Y2EXr3pSB00Go1rAri2HwItn52oQklDB0L9DXhwovJ2TirFA+MTYdJrcbqqFYdKGvv9+NKu0fljExDir8wgvxIsn5Qq9s0rbMDxcs/9TBYEwVVeZNkkTv7oxiWG+eNbQ8Tnbk8/H/Sd/Cl7sc+k12FJpjhGaYeLJ6xz3lsXZybDoPPo9NNraLUa12Kx3L0wfdX6/T2lOofGKjeILS0y7Txbi5J6zze2lxbKl2Sm8HpWGSkhw2Jz4J1+SP57ZVcBALG3lRJ3TiqBmPwn3ev7P/mvod2Kj46KwRzuzL48o17rWjt4fW+hR/+dsgsbkF/TBn+jjqVC6aYsykyGVgPsKxCreHnSrrO1KGvsRIifAXeNjvPosW6Ex55WduzYgSFDhuBf//oX/vKXv+Crr77CG2+8gddffx15eXmeOqziSQtrS7KSoefD4jWLCDRhjgLqIfsqMTgglvYbGK3s0n5S7ftNOaWw2DzbI07q37QkK5k7eVTo3vGJCDDqcL62HfvO13vsOIIg4GXn5G/5pBT4G5XX+0UpQvwNuHtMPID+K08mqWntwvbj4uRPidlKShIbYsYcZ+mcNzy4+2vf+XoU1LUjwKjDvLGc/NHNkQJRW3LL0NXtueeDr07XoKK5C2H+Btezq5ItnZQCvVaDA0WNOFHh/mD26aoW5BQ1QK/VuHaN0rV5YEISjHotjpU340hpk9zD8Sld3XZXEFupu74kaZEBuGVwFATB8/PkkxUtOFjcCL1Wg8WZ3CGvNr37xK3d79k+cacqW7D7XB20GuCRaWkeO443uHd8IvwMOpytbsOBov5N/tt8oBRWuwOjE0MwlhUWrmhJVjKMei2OljV7NElT2qUzb2yCYisukTrEh/rhtqFikr6n+9VJzx8PTEiE2aC8Ercei7489dRT+MUvfoFjx47BbDbj3XffRWlpKWbMmIEHH3zQU4dVtGNlzcgrbYJBp8HCDE7+rteyXtv05aqH7Is6rXZsdpb2W6mCbKBZw2IQG2xGfbsVnx7zXAmfo2VNOFLaBKNOi4UZnPypUaBJj/vGi7uwPNkn7kBRo3iu6LXMqLsG0r3+Y+dO6f6yOUesUT0+WXk1qpXo4ampAIAPj1SgttXikWNIux3uHZ+AQBODxnRzZgyORkKoH5o6uj1asmadc/L34MQkRU7+LhQTbMYdI8U+lJ7Y/SX9fJ09IhYxwWa3f743Cw8w4s5RTP6Tw8dHK1HfbkVciBm3q6C0n7QjYfPBUo8G99c6F2Vnj4xFNK9nVZo3Nh5BZj2K6zuw65zn+sS96kz8mzsqDknh/h47jjcI8TPgHmfyX3/e6+0OwRVoYQuHq4sINGH+WPHfyVOl32tbe8pQs1QoucNSZ/LfO7ml6LR65vmgvKkTX56uAQDFJrp5LPh16tQprFixAgCg1+vR2dmJwMBA/P73v8dzzz3nqcMqmtRYdM7IOEQFmeQdjAplpIZhcIy89ZB90ft55Wju7EZSuB++NVT5pTr1Oq3rhrvWg7VtpZIfc0fFIjKQ17NaSX3iPj9Vjcpmz/SJk0p+3D8+gff+azAmMQQj4oNhtTnwTm5pvxzTZndggzPDmwHKazMuOQxjk0JhtTs8kklW09LVa/LHCTndPF2vnUeeKiNX2tCBr8+Ki4mLM5U5+buUh5w7W7blVaDRjUkHLV3deP+w+MzOHbU3Rlr8+uBIBZo7mPzXHwRBwJvO/lnLJqWoolrLbUN7gvtSCTN3a+7suZ5X8HpWLX+jHg9MEJP/PNUHprK5Ex8cEXsVfueWdI8cw9tIC9SfHqtCfZtnksoutPNMDcqbOhHaq/IGXdmqqeIuxu3Hq1DhgR7zbx8UkzHHJjEZk9xjxqAoJIb5oaXLho+OeqaH7KacEjgEYMqACAyIUmalMI89yQUEBMBqFSdPcXFxOH/+vOtrdXV1njqsYjV1WLHN2axY2mpO10eshyz+3clRD9kXCYLgygJeMSlVNaX9FmUmQa/VILfYMyV8Gtutrgf65byeVW1wTBAmpYeLPVo8sBh6vrYNX5wS++U9Mo2Tv2uh0Whci6Qbsks8WpJF8sWpGlQ2dyEiwIg5o2I9fjxvscq5+2tddrHby8y+fbAUNofg6k9B5A4PTkx0PR+cqmxx++dvyClxlYlOiwxw++d7yoSUMIyIF/vAbDrgvqSDrbll6LDaMTgmEJPSw932ub5kQkoYhsYGoavbga2HPd+jh4DDpU04WtYMo76nWbzS6bQa1+L5Wmfgzt3ezS1DZ7d4PWem8XpWM+k5e8fpGpQ2uL9P3Jq9RbA5++WNTgx1++d7o9GJoRidGAKr3YEt/dCPDejZmb1AJTvVlWBYXLBr7cDdlWP69ozlGhO5h7ZX8t86D6x3ddt75g5KTlj1WPBr0qRJ2LNnDwBg7ty5+PnPf44//vGPePjhhzFp0iRPHVax3sktg8XmwNDYIExICZN7OKp17/gE2eoh+6LswgacrmqFn0GHBRPVMfkDgOignhI+az1Qzm5LbiksNgeGxwVjfDKvZ7VbPikVALAhpxRWm8Otn716t7jra9awGMX3y1OSe8bEI9CkR1F9B/ae93zCjLQze2FGEkx6Tv6u1dxRcYgJNqG21YKP3ZhpLk7+pIdo9eyeIeWLDjJjtvP5wN2lhaw2B94+oM7zVqPRuPoardtfDJv95n8WCoLg2oG/fFIKNBp1JFApjZj817Njkcl/nicl/t09Oh4RKqrusHBiEow6LY6Uub9HnCD0Ko82OZXXs8oNiArEtIGRzj5x7l0Mbe3qdlUE+O4MJv5dD+le3x/Jf0V17fj6bC00GvU9s8jtYefur405JW4tI7frbC3KGjsR4mfAXaOV3zOW1GPBxCQYdBocKW3C8XL3bg74/GQ1alstiAoy4fYRyi0T7bHg1wsvvICsrCwAwO9+9zvMnDkTmzdvRmpqKl577TVPHVaRHI6eyd8KPizelGCzAfPG9n89ZF8lTf7mj0tAiL+6mm1Kpcukso3u4nAIWLdfKo/GxRxvcPuIGMQEm1DXZsH2E+7rE1fbasG7zhKtLPlxfQJMetw3PgEAsH6/Z5uz5te0YW9+PbQa5daoViqDrqeP3Rt7i9y2KNu7DMvcUZz8kXtJizzvHSpHm8Xmts/dfqIK9e1WxASbMHOYcid/l3PPmHiE+RtQ3tSJHc66/Tdj3/l6nK9tR4BRh/njEtwwQt81f1wC/I065Ne0IbuwQe7heLWa1i5XT0CpHKhaRASacKdzwdTdpd/35tejoK4dgSY97uX17BWk6iVvu7lP3KacUrRabBgYHYhbByu/ZYKS3D1G7MdW0tCB3fmeTf6T1tJmDI5CSoR6dqorwcxhMUgK90NzZzfeO+y+dizSv8kDExK5E4/cKjLQhDtGeqaHrJQYs3BiEgwKLhPtsZGlp6dj9OjRAMQSiP/+979x9OhRvPvuu0hJUe5WOE/Yda4WxfUdCDLpMX8ca+neLGkrZX/WQ/ZFFU2d+M9JsVzbyinqu2YzUnvKxLzjxtIBX5+rRUlDB4LMeswby8mfNzDotK7eLOvcuFPwrX1FsNocGJMUioxU7hC8XtK9/vNT1ahq7vLYcaQHttuGxiAxjA25r9fizGSY9FocK29GbrF7dmRL/yYPcvJHHjA5PQLpUQFot9qxLc+NixbS5C8jWdGTv8sxG3RY5PxZKCU/3QypHNB94xMRZFZXApXSBJkNrmdOT/XoIdGG7BJ02wWMTw7FqET19VuRAhofHnFv/763nKUU7x+fgECT3m2fS/KZOTQa8SFmNLRbXQHfm9Vtd+D1vYUAgMemp0GrkpYJSuFv1OP+8Z7txwYAnVY73j4oro+wJcv102k1WOlK/it0S/JfeVMnvnQmHjEZkzxhmfO82pZXgZYu92wOOF/bhm/Oi0nEixV+3np0ZtbU1ITVq1fjqaeeQkODmKV26NAhlJe7b6KpBtIPrvsnJMLfyIfFmzUqMQRj+rkesi9at78YdoeASenhGBqrvn4rvfsGrdtf7LbSAVIZxQcnJMHPyEVZb7E4Mxl6rQY5RQ04XXXzfWA6rDZX1u13b0nnDsEbMCQ2CBmpYbA7BGx2Yw+a3totNryby8nfzQgPMLqywKUFj5tR2tCBnWdrAQBLFFw3nNSrdw/ZdfvdU0buXHUrsgsboNNqsDhTPWWiL7Q0KxlaDfDN+XqcrW694c+pbO7E585+l+yN6h7LnP2cPjtRhdpWJv95gtXmcJWAW6myXV+ScUmhrv59bx90z7NTeVOnq38t+9B4D71O61pkd1fvoo+OVqCyuQuRgSbu+L1B0u70HaeqUdnc6ZFjfHikAs2d3UgK98MM7s67IQsykhBg1OFcTRv2uGGX3qacEjgEYMqACAyIYqsEcr/MtHAMig5Eh9WO9920Y1EqcfutIdFICPVzy2d6iseCX0ePHsXgwYPx3HPP4c9//jOampoAAFu3bsVTTz3lqcMqTmlDh6t0CCd/7rPU+eDdH/WQfVFXt93VtFBtJT96u3dcAoJMehTWtbulb1BpQwe+OsPr2RvFBJsxe4TYB8YdE8B3csvQ1NGN5HB/1+fS9ZMWqDfmlLilB82F3s8rR6vFhrTIAEwbGOn2z/cVD01NBQB8dqIa5U03N1HfmFMCQQCmDYxEWiTLsJBnPDA+ESa9FqcqW3DYDb1xpAXzmUOjERei7MnflSSG+ePbw8WSjTez+2tDdgnsDgFZaeEYHBPkptH5thHxIRiXHIpuu+C2oAb19enxSlffijkj1VlyV6PRuJJ51mW7J/lvY7a4KDs5PQKDeD17FXGnsgZ5pU04VnZzfWAEQcAru8QkqFVTU9lD9wYNiglCZlo4HAJc/W/dSRAEvOXsdbw0KwU67s67IcFmAx6cKCY7vbG36KY+q9vucK29LWXiH3lInx6ybkj+6+q2uypsqSExxmPBr8cffxwPPfQQzp07B7PZ7Hp97ty52LVrl6cOqzhiY2JxEYcRfPe5e3Q8gvupHrIv+vBIBRrarYgPMWOWCvtWSAJMetw/QSwd4I6AxrrsYggCMH0QF2W9kRTQfP9w+U1tBbc7BKzeLU7+Hp2exknFTZgzKhbhAUZUtXS5SkG4iyAIrp2cS7OSWZrlJgyNDcaUARGwOwRXaaQbYe2VqS7tciDyhBB/A+4eI5Yiv9nSQh1WG949JE7+lqpg8nc10o6XrYdurGeq1eZwLdhJPQHJPXonhNiZ/Od2UsB3aVYyjHr1lS6V3DMmAcFmPUobOvG1cyf1jbLY7Nh0oKfXMXmXqCCTq7fqWmdA5Ebtya/DqcoW+Bt1rgVWujHSQvKmnBJ0uzn5L6+0CcfLW2DUa7Fgonp3qivByimp0GiAL0/XoKC27YY/5/OT1a7Ei9tHqHftjZTv3vGJ8DPocKa6FQdvsl3BR0cr0dzZjYRQP9wyOMpNI/Qcjz3VHThwAN/97ncvej0hIQFVVVWeOqyidHXbey3i8GHRnfyMOldQg7Xv3UsQBLzpXLxcNjkFehX2rehNWkDdcermdiR0ddvxtjMjZzmvZ68kZqiLW8G33kRJ1c9OVKGkoQOh/gY84LxP0Y0x6XV4ULrXO3dWuMvB4kacrmqF2aDFgxM4+btZq6amARAzxDusthv6jM9OVKGuzYroIBNmqjjxgtRBejb/6GglmjpuvDfOR0cq0dplQ3K4P6Z7wQ7SyekRGBIThM5uO7bcwA6j7SeqUNdmQTQXcdzurtFxCPEzoKyxE7tuMqhBfR0ra8ahkiYYdBrV91vxM+pcOxJuJiEFALYfF38uxwSbMGs4r2dvJM1rt+VV3NTPwld2FQAAFkxMQqi/0S1j81WzR8QgIsCImlYLdjhLjrqLlPh39+h4hAfw3+lmpEUG4FtDxLKRN7NbXlrPXDgxSZU9Y0k9QvwMuMeZ/Lf+JtfR12eLf35JVrIqkr09dmWZTCa0tFzcN+Xs2bOIilJ+VNAdPjlW2Wv3DGvpult/1EP2RYdKGl3ZQIsy1D35A4CB0UGYMiACDuHmbvAfHa1EY4eY2cBFWe+k0WhcE8C1+4tvaCu4IAh42Tn5Wz4phX0e3UBahNp1thYl9R1u+1xpN+j8sQkI8Te47XN91W1Do5ES4Y+WLhu2HrqxOuLSQ/SizGRO/sjjxiSGYER8MKw2h6tsx41Y12vy5w07SDUaDVZM6flZeL1l09Y6F9sX8zp2O7NB50qqke6X5B5S4t/cUXGIDjJf+c0qIAX3d97ks5O0UL4kM4XXs5eakBKGYXFin7gtB2/sZ+GpyhbsPlcHrQZ4ZFqam0foe0x6HRZkiAHs9W5M/qtvs+Cjo5UA2MLBXR52Jv9tyS27od3y52vb8M35emg1wGKVJ16QOix1bg745FgV6tturIfsiYpmHHYmDKllB6nHnmDuuece/P73v0d3t3gD0Gg0KCkpwRNPPIH777/fU4dVFGlhbUlWsup3zyjRwOggTEr3XD1kX7XmG/G8nTfGe7KBpDIdmw+UwmKz39BnrN2vrswGujH3jk9EgFGH87Xt2He+/rr//IGiRhwpbYJRr2W5JzdJiQjA9EHibor1Oe5Z7Ktp7cL24+Lkjzuz3UOn1WCl85x/Y2/hdS+Y59e0Yn9BA7QaYFGGOh6iSd00Go3r+hfLlF9/wsPRsiYcLWuGUad17VL1BveOE8umFdd3YOfZay85e6qyBQeKGqHXqn/3jFJJf69fnq656R6LJKpvs+CDIxUAesp+ql1aZABuGRwFQbjxQOnJihYcLBav58WZ/LnsrdzRJ+5VZ+Lf3FFxSAr3d+v4fNWSzGRoNMDuc3UorGt3y2e+fbAMVrsDoxNDMDYp1C2f6eumDoxwVY65kd3yG5zBzW8NiUZCqHp7xpJ6jE4MxejEEFjtN578JwXlZ4+IRVSQyZ3D8xiPRWT+8pe/oK2tDdHR0ejs7MSMGTMwYMAABAYG4o9//OP/396dx0dV3/sff0+WmRDCJISQDRJIZJNdthBF1CaVxbpSi4hWrYVri/eh1VpBa7lt7+/iz/b2ti61Lj+1dUNRwbpxi6yKASQQIIAREExYAkjIAiH79/fHZI6MbEmYJDMnr+fjMQ+TOd8z85n4mS/nnM/3fL+t9bYBY8veMuUVeSqhU21w90yg8s593xrzIXdEB8ur9NEWzwVhu5z8SVL2hQlKdEfoyPEafbSl+dOubt5b6ilohIZoKhdlbS3KFaYbRrR8nTjvlB9TRvQImgOBYOC9QL1g/d4WF7BP9sa6ItXWG41IjdHgHtHn/XrwuHFUT0W5wrTr8PFmr8fpPYjOujBByZz8oY1cMyxZUa4w7f7muD5rwYCHV9d48nbSkER1i7JPnx/pDLNGcnoHRTWFd6DQhEGJSnAH/90zgeiC7lHWjAbz1/l3OuCOav7nRaqp81wQvshGF4S9sxm8sb5IVbXNP3byrgE1YXCi4vk+29q1w5PVpXHAw6odzZtS9UDZCat4PHN8emuE1yGlxEbqssZ1dF73Q19f32Cs6fVYwsF/HA6Hbr/Yc/fXS5/tadZ6nFW19VbxgcGYaEveWdReW1fY7AEPFVW1WrRxX+PrBE/etlrxKzo6WkuWLNF7772nxx9/XHfffbcWL16sVatWqXPnzq31tgHDe7A4aXASF0Bb0YRBiYqLap35kDuiV9cWqq7BaFSvrra6IBwWGmKNlG3J3PfeIsjkIYmKs9HFLZyedxqIJc2cUnXnoWP6uLEf+umlnPz5U9aAeCW6I1RyvEaL889v3dC6+ga9ts67eHtvP0QHry4R4bpxlKd4/OLq3U3e70RNvd5uPPljkXS0pc6uMN0wooek5t8dUXai1rrgZ8eLFj/O9CzkvurLw9rVhIXcy086GWY6pdblzbf5nxcx+O881dU3WNOi35bZWw6HfWZ3+N4Az50EpZW1eq+xr2qqshO1WrTRs8+Pbdi/wVekM8yaUvXlZg7+e3H1HtU1GI1Nj9XQnjGtEF3H5b2wvKCFBeyTLW+8WzgmMlxXN675A/+4/qIeion0rMf5cTOuSb6/+YDKTniW1Rjfr2MsDYTAcPWwbwc8fNrMAauL8varsqZeF3TvrLHpsa0Uof/5vfiVk5Oj999/3/p93Lhx6ty5s/76179q2rRpmjlzpqqrWzavZLAorazRu3mNB4uc/LUqZ1iINTLVn/Mhd0Q1dQ3Wbdd2uuvL66YxKQoLcWhDYany95U1eb+jx2usE8ZbuVDeIfRL8EypWt9g9Hoz+pX/96nnrq/sCxN0Qfeo1gqvQwoLDdFNjVPueO+0aKmPtx/UgbIqdevs1KQhif4IDye5/WLPBfMVBU27YC5J723er/KqOqXEdtL4vpz8oW15Ly79a+tBHSqvavJ+Czfs1YnaevVLiNKoXl1bK7x2k9otUt9rXMi9KRdD38ndq8oaz98jIy14ToaD0fcHJqh7F5cOV1RryTYG/52PJdsOan/jMcEPhiW1dzh+FRrisNb2eKWZ6x6/nevp3/ondNEYvs8dgreovqzgkIpKmrZOXHlVrXX9gLu+/O97A+KVHB2ho5W1+qhxuvaW8t6Z/aNRKYoID/VHeGjUyRmqaWM8fe0LnzZ98N+ra1lWA+0j0hmmKY2zHTXn+MAYYw0Ymp7RK6gGDPm9+PW73/1OW7dutX7fsmWLZsyYoe9///uaPXu23nvvPc2bN8/fbxtQ3srdq+q6Bl2Y5NZIG54MB5pprTAfckf0Uf4BfXOsWglulyYOtt8F4fguEdbnak4HvyC3SNV1DRqY5NaI1JhWig6B5taxvSVJr63zTIVzLocrqvX2Bs+Id07+WsdNoz0nBuv2lKiguKLFr+M9+Zs6OkWuME7+/K1Xt87KGuC5YP7S6j1N2sd7EH3zmF4K4eQPbax/YheN7t1VdQ1Gb3zetPUajDHWoKtbxgbXyV9zeAdDvZW7V8eq687Yzhhj9a232vjvESjCQ0OstRGbW9SAr5c+2yPJcz5px2OCqaNS5AwN0aa9ZdpUVNqkfRpOmh7tlky+zx3FBd2jNK5PXOM6cU0baPbGuiIdq65Tn/goXd4vvpUj7HhCQxy6aYy3gN3ywX97vjmulV8elsMh3RJE05QFk1vH9lJoiENrd5do6/5zD7Teur9MGws9y+R4B/MDbck728rSLw41ebajDYVH9UVxhSLCQ6ziWbDwe/ErLy9PWVlZ1u/z58/XmDFj9Nxzz+m+++7T448/rjfffNPfbytJKikp0fTp0+V2uxUTE6M777xTx46dfdTx5ZdfLofD4fO46667WhxDQwMnf20tJTZSl/txPuSOynvyNz2jl8JDW21G1HblneJsUd4+lVXWnrO95+TPOz0a3+eO5MpBCUpwu/TNsWot3nruafb+kbNHNXUNGp4So9G9GfTQGhKjI5R9oefE+rUWLt6+89Axrd55RCEOaTrT+LSan1zimfv+7Q17VXbi7H3tlr1l2rS3rPHkL7gOomEf3ru/Xl9X2KT1GtbtLtGOQ8fUKTxU113Uo7XDazfj+sQpvXtnHauus6YmPZ3Pdh3RrsPH1dkZquuD7GQ4WN00JlUhDu/fvml32cLX9gPlWru7xOcOKbvpFuXSVUM9d7Q1dS3bz3Yd0VffHFeUK0zX27h/w6m8U9a+8XnhOafZq61v0AuNU1zPvDSdwUut5KbRKQoNcSj366PafqC8Ra/hLWZf3q+7UrtF+jM8NEqO6aRJjQOtmzL4z1tgnjAokWVy0C76Nt7ZXd9gNH9d0wb/ea+NXj00WdGR4a0Znt/5/Qr30aNHlZCQYP2+cuVKTZo0yfp99OjRKipq2h+2uaZPn66tW7dqyZIlev/997Vq1SrNnDnznPvNmDFDBw4csB6PPfZYi2NYteOwvj5SqS4RYbruIubSbSve2/T9MR9yR7R5b6k18sR7y7Ydje7dVQMSu6iqtkFvbTjzRRyvlTsOq7DE832+djgnfx1JeGiI9V145RwXCypr6qxBDzPHp1MkbUXeC9TvbNin42e5C+FMvCd/WRcmqEdMJ7/Ghm9lXtBN/RO6qLKmXm+e404a75QfkwYnqRtrKqKdTBqSqNjOTu0vq9LyLw6ds733osV1FyXLHRFcJ3/NERLi0G2NA4f+nrPnjItie6dFvGFET0W5wtoqvA6tR0wnfW+Ad0AIg/9awrsO8MRBiUqKtu8xgbeg8d7m/Tp6vOac7b1/lykjevB97mCyTppm78MtZ59m7/3N+3WgrEpxUS5dy3WvVhPvjtCVAz3XV5u7NqnkWVd3QePgFdbjbF13NA7+ezdvv745dualfipOWiN1OnfioR19u4ZsoerOsYZsyfEafdD470IwrnXs9+JXQkKCdu/2jACpqanRhg0bNHbsWGt7RUWFwsP9f5K4fft2LV68WM8//7wyMjI0btw4PfHEE5o/f7727z/7Aq+RkZFKTEy0Hm63u8VxeC+s/XBkT0U6OVhsK5f39yzo64/5kDsi711fVw1JsvXIE4fDYXXUr6z5+owXcby8F3NuHJmiTk77TYWCs5s2JlVhjdPsfVF85pF2b+XuVWllrVJjIzVhkP2mDA0k4/rEqVe3SFVU1zV78fbjJ925cGsQHrAFE4fDoTsu6S3J8+/LmQ6my6tqrTVSg/EgGvbhCgvVjSMb574/x8Wlb45VW8eaHeGixZSRnoLWV4ePn3ZR7ANlJ7SkcYF3Lqy1LW/+vZW7l8F/zVRaWaOFjRcf7b5G90UpMRqU7FZNXYPeXH/2ASn7Sk/o48bvM/8udzxhoSG6uXEqrLPdKWiM0bOrPNf87rikty2nDA0k3u/iwg37zjoF8em8t2m/yk7UKiW2ky5jaspWNSI1RsN6RqumvuGsg1IW5e1XZU29LujeWWPTWVMR7WfCoAR16+zUwfJqfbz97IP/3sr1LAcyuIdbQ3tGt1GE/uP34tfkyZM1e/ZsffLJJ5ozZ44iIyN16aWXWts3b96sCy64wN9vq5ycHMXExGjUqFHWc9nZ2QoJCdHatWvPuu+rr76quLg4DR48WHPmzFFl5dkX+KyurlZ5ebnPQ5L2llRqaeNoUQ4W21ZoiEPTxnjnvmf0Y3N8c6xa72/yXMTxru1gZ9df1ENdXGHa/c3pL+J4FZVUanmB5/vMxZyOKcEdYRWzznQCWN9g9PwnnpO/n16axmK1rSwkxKGbvXfkrf1axpx7ejKvRXn7VFFdp7S4zhrXJ661QkSj6y7qoa6R4T4X0r5r4YZ9OlFbr34JUUwXinbnveC38svDKio587nAgvV7VVtvNCwlRoN7BN/JX3NFucL0w8bC4N8bB0ud7LW1nqkix6bHql9ClzaOrmMb36+7enbtpLITtXp/M4P/muPN9UWqqm3QgETPtD925nA4rALfK2u/PuvUrq+vLVSDkTLTu6kv3+cOaeroVIWHOpRXVKote0+/dtGnO7/R9gPlinSGWuvGoPVkpndTWlxnHa+p17t5+5q8nzFG/1izR5JnrS/OU1uXw+HQT8Z57v56ec3Xp1033BhjrXU8PYNlNdC+XGGh+lHjGrJnu7O0ocFYBd1bgjRv/V78+v3vf6+wsDBddtlleu655/Tcc8/J6XRa21944QVdeeWV/n5bFRcXKz7edyRDWFiYYmNjVVx85vVabr75Zr3yyitavny55syZo5dfflm33HLLWd9r3rx5io6Oth4pKZ5keTN3r4zxjEy/oHvU+X8oNMuPRqco7DznQ+6I5q8rVE19g4b1jNZFqfa/+NjZFaYpjRdxXj7LIuGeC+vSpX3jlBbXua3CQ4DxFj4Xbdyn8qpT1y76363FKiypVExkuHVxEK3rxsbF2/P3lWvzGU7Kv8sYY93JecvYXqxL0AYiwkOtYsILp5n73hhjHWRz8odA0KtbZ13aN07GSK+dYQ3Zhgaj19Z587bjXPDzXjhfVnBIhUe+LQzW1DXo9cZ1Am4d27s9QuvQPIP/PHnYkumwOqr6BmMNarr94t4d4t+fa4b1UHSncBWVnNCqLw+ftk11Xb3mf/7tWsfomLp3cWnyEM86cS83Fk6+69lVX0mSfjQqRTGRztO2gf+EhDisY45X1hQ2efBfXlGp8veVyxkWohtHpbRmiGg0aXCS4ru4dLiiWh9sOXWWkg2FR/VFcYUiwkOsa1JAe7p5TKocDumTHd9ozzfHT9tm9a5vtOdIpbq4wnTN8OCc5tbvxa+4uDitWrVKR48e1dGjR3X99df7bF+wYIHmzp3b5NebPXu2HA7HWR9ffPFFi+OdOXOmJkyYoCFDhmj69On6xz/+oYULF2rXrl1n3GfOnDkqKyuzHt41zBZuYC7d9hTf5du7NDgBbJra+gbrTrmOcNeXl/fOzKXbD2pf6YlTtlfVfrtODdOjdWwZabHqlxClypp6vZPru06cMUbPNJ78/XhsL6a6bSOxnZ2aPMTT179ylgL2ydZ//e2Jxg9HcKLRVm4d29szdejuEuXv8y1Ufr7nqL48eEydwkN1/QjWVERg8B4fvPl50WlH7K7acVhFJSfkjgjT1UOD8+SvJdK7R2l8v+4y5tv1gCRp8dZifXOsWglul64clHDmF0Cr+dGoFIWHOrSxsFRb9zdtQEhHt+yLQ9p79ISiO4V3mDV9Ozm/ndr15O/wyRbnF+ubYzVKcLuUPZDvc0fmLX6+m7dfpZW+68Rt21+uT3Z8oxCHdGfjXS5ofVNG9JQzLETbD5RrY1Fpk/bxDvy7emiyYjtTpGwLzrAQ6/rRi6v3nFKo9F57u2ZYsqI72XfNWASPlNhIXdavuyTp9TMM/nu1MW9vGNEjaK95+b345RUdHa3Q0FPn/o2NjfW5E+xc7r//fm3fvv2sj/T0dCUmJurQId85Kuvq6lRSUqLExKavwZKRkSFJ2rlz5xnbuFwuud1un4ckHa2sVXJ0hLIGMJdue/GOiGnJfMgd0b+2HlRxeZXiopy6amhSe4fTZvrER+niC7qpwci67fxk728+oKOVteoR00lZF3Ly15E5HA7rAPblNb7T7H2+56g2FZV6DnIze7dThB2T9wL1e5v3q6zy1Dvyvss7wvu64T0UHcmJRltJjI6wRg+/+J27v7yDVK4dnix3BP9PEBiyBsQr0R2hI8drtHjrqTNHeC9aTBnZs8OtBXr7xY2FwfVFqqzxHGO/3HgRfdqYVIWHttppJc6iexfXSYP/mPq9KbzTd940umOt6Tu98dhpxZeHfe7g9PIeK908phff5w5uRGpXXZjkVnVdgxas9x389/wnnoF/k4ckKSU2sj3C65C6dnbqB43Xa15twjIfR45VW9Phcidn27o5I1XOsBBt3lumDYVHredLjtfogy0dZ81YBA9vPnqmhPZdQ7a4rMpa23d6EN8YEPBHNd27d9eAAQPO+nA6ncrMzFRpaalyc3OtfZctW6aGhgaroNUUeXl5kqSkpJYVAm7OSFUYB4vtJvOCbkpvwXzIHZX35G/amNQOt1Ct9yDwjc+LVF3n28F7p0O8OSOVubGh60f0VJQrTLsOH1fOriPW894pP6aM6KHuXVztFV6HNLJXV/VP6KKq2ga9vWHvWdseqqjS4nzPiQZ3Zre9Oy7pLcmz4PbhimpJnhPyj7Z4Cguc/CGQhIWG6KbGNWS/Ozhmf+kJLfui8eSvA+bt5f3i1atbpMqr6rRw4z5tP1Cuz/ccVdhJU++hfXgHhCzauE8Vp5miGd/aeahCn+703LXS0dboTovrbN3B+d1ZUrbuL1Pu197vM9OjdXTfXSeuoXGduANlJ/TPTZ6p3GaOT2+3+Doq77HH+5tPvSPvu95cv1c19Q0a2jNaw1Ji2iA6eHWLcum6xqnhTp76/a1cz6wCQ3rw/wSB5XsD4pUcHaGjlbVanO87+O+Nz4tU32A0pndwr+1rmyrNhRdeqIkTJ2rGjBlat26dVq9erbvvvls33XSTkpM9Hc++ffs0YMAArVu3TpK0a9cu/f73v1dubq727Nmjf/7zn/rxj3+s8ePHa+jQoc2OITzUoamjOflrTw6Hw1pjpDnzIXdE2/aXa92eEoWFODrkRZzsCxOs0d3ei7CStHlvqeduntAQTR3NyR+kKFeYbmicls07KnbnoWP6uHEEzE8v5eSvrTkcDt0y9tt1Ts7W17+xrki19UYjUmM0KDm6rUJEo4tSu2p4Soxq6husi20Lcvdaa00O6cn/EwSWm0Z7Br6s3V2iHQcrrOfnrytUg5HGpseqT3zHW9s3JOTbO6H//tkea6DQhEGJSnBHtGdoHV5GmicnK2vqtSjv1DVG8K2/f+bJ26wLEzrkXSs/bvwOv/Gd0d3eaaQnDk5UPN9nyHNnfpeIMH19pFKrdnjWiXtx9R7VNRiNTY/V0J4x7RtgBzQiNca6I++t3DMP/qtvMNZ3miUc2scdl3imBF2cX6z9pSc8a8Y23p3dkdaMRXAIDXHopjHe6+jfDo6pq2+wpkKcPja489Y2xS9JevXVVzVgwABlZWVp8uTJGjdunJ599llre21trQoKClRZ6bnN3+l06uOPP9aVV16pAQMG6P7779eUKVP03nvvtej9v39hAqP/A8APR/aUq5nzIXdE3ru+JgxOVGJ0xzvJCQsNsQqlJ8997y1uTB6SqLgovs/w8I4OXrL9oA6UndD/+9Rz11f2hQm6oHvHuwgaCK67qIcinaHadfi41nxVcto2dfUNem2dd/H23m0YHU72k8Y1IV5ZU6iq2vpvT/44IUcASoyOUPaFninMvdPI1dY3aH7jWqAd7W6Rk904KkWdwkP15cFjmt/Yt3JHbftzOBzWxbRX15x9QEhHVl5Va90tfnsHWuv4ZFcMiFePmE4qrazVe4138JSdqNWijZ6fuVAOr0hnmH7YuE7cyzlfq7yq1jp+466v9nFyX//a2jMP9F7+xSHtKz2hmMhwXT2s46xPGkguTHIrM72b6huM/pHztVbv+kZ7jlSqiytM1wzn/wkCz02jUxQa4mhcK71ckmeN1OLyKsV2dmri4KYvJxWIbFX8io2N1WuvvaaKigqVlZXphRdeUFTUtxcle/fuLWOMLr/8cklSSkqKVq5cqSNHjqiqqko7duzQY489Zq3h1Vw3MUVAQIiJdOoHjYuQN2U+5I7o6PEaLWqcFrKjnvxJnu9seKhDGwpLlb+vTEeP11gngqzhhJP1S+iisemxqm8wenzpTr29wfP94eSv/XSJ+Hah+u9O3+P18faDOlBWpW6dnZo0JLgP2ILZpMGJSnRH6Jtj1Zr99mYVllTKHRGmq4dy8ofA5L0j/u0Ne1VZU6ePtx3UoYpqxUW5dOXAjtuXRHcKt+6EbjBSv4QoZaTFtnNUkKQbRvRURHiIviiu8FljBN96a/1eVdbUq2/j2r8dUWiIwxq97R3d/XbuXp2orVf/hC4aw/cZJ/EWQ5cVHNIf/7dAx6rr1Cc+Spf3Y4379nLdRT3U2Rmqr77xnY7/ZP9o/G5PHZWiiPCOtbRFIPFO/f76ukI9/8luSdINI3oo0hnWjlEBpxfvjtCVAxMkfXsd/ZXGAQ83juoZ9Mvk2Kr41d4uSu3a3iGgkXc6rKbMh9wRvbG+SNV1DRqY5NaoXh03b+O7RGjiYM/6fq+s+VoLcj1/l0HJbo1IjWnf4BBwvHcOvb6uUDV1DRqeEqPRvTvu9ycQeEc//u/WYms9qZN5p+WaOjol6A/Ygll4aIh1d4h3Sq4pI3uqk5P/JwhM4/rEqVe3SFVU1en9TQesO8Cmju4pZ1jHPn06+S7aW8f2ksPB2qiBILpTuK5pHOH/CoP/TtHQYKyZHn58ce8OnbdTR6XIGRqiTXvLlFdU+u30aJl8n+ErvXuULu0bJ2O+nR1l5qXpCmFN7HYT5QrTdRd5BqG8cprBf3u+Oa5VXx6Ww9Ex1ycNJJ7pdTup7EStVn7pmTqUWS8QyLyzW3jX9l3lzdsxwZ+3lJz9iIPFwDE8JUYDk9zadqBcb+XubZM1eeobjCpr6nS8ul7Hqut0vPFxrLpOlTWe52rqGlo9jqb4R+OUh7d38JM/yXPh5r1N+7Uob5+6dXZZz3X0vwtO9f2BCUpwu3Sw3FNkmTk+nTxpZ4N7RGt4Sozyikr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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 특정 주기는 없어 보임..Trend와 Seasonal을 보는 것이 맞는지\n",
        "# Resid가 모두 -0.02 이하."
      ],
      "metadata": {
        "id": "0Zztc3oP-hp9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# ACF, PACF"
      ],
      "metadata": {
        "id": "H5UBUzsHB-oQ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "- 상관도표(Correlogram)는 autocorrelation function(ACF)와 partial autocorrelation function(PACF) 중 하나를 그래프로 표현한 것.\n",
        "- Correlogram을 활용하여 현 시점의 자료와 시점의 차이(lag)를 가지는 자료를 비교하여 어떤 관계를 가지고 있는지를 분석할 수 있음. \n",
        "- 즉, Correlogram을 활용하여 시점의 차이의 영향력을 알아볼 수 있습니다."
      ],
      "metadata": {
        "id": "wVh7BbPNCul9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://direction-f.tistory.com/65"
      ],
      "metadata": {
        "id": "6KXqL-VCDas-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## [자기상관함수(Autocorrelation Fucntion, ACF)]"
      ],
      "metadata": {
        "id": "V2D-Uy0aDQpQ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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4AorUaEj3GBufUp056VgN6TZnBPsIjJETUvsSGZqfrgVpc0M6C1DQf+LePw8gUenSzw3aUQ8UrFHI3dbdFtlDtYAmI9s6mP0s24SjhWCibI6YTQ/Ofu+0/TRBiE9M7g0zKixFucl9zS5rXlYyageoX7YNi/8Ulm7Y5dseI0xkJ4blce+xXvzZcVrQiPg+WPy+LeDl339l4o3pSa/fLcMbbtbHnCf1eDGXGAwuLmhhX6x9B07ZNeGFebaxvj8+jH73vwrXiul0Ox97Fjwvrz8UrnUG6WTh+XuLdvk7j9znyVw7NPrM3ntx08cN/9fIBe/bEHwRgLBesuSDKw28t7O5VkfD+JwztfYuTh1/V2ENs653kBKTRf1YyjxWjGGSQvE6zsed61MBM7TmjHk0w9bxJcxqf2CdGZTJWlG/UxRmBzCeDM6TJpc8PN2go5TOG2TsRCan71BM133ZQjm9Okw2DuHDknFNA3v0hoGjDIe7HyVFJLPSminoYhH2EcVa7xXzktYE10pktgdOX2qaBHP2SoCF2Gqi2a6CaoJL+nYfS6C4lKQfErHcCuRDRvVzYPz7rRNmBRdb3HeqF1BmlfSZ+26tVSB79JJw2kFdUej1JYUJc6lAqYrTxBKeUlt40g/sJPn3BL4mamkxUfb1jllarzAXmls025k0+CFn/zaV8WaP/NNf+y3bwV896SctFE5Y9Bc5A0aH8VbLBf3Be9MC5NH5KtBIaVUU8hxOemCigtettiUNMBH8Rb3pRdy6rkpkX92fyQyKae+O2kubQzHlNPhlQ+vcwnS60x3in3+axLO+RqTVRMYBoGe0JCumHOh2HETHwF3srqRfmPl/TRnbcTQemQwr6GS4Z4LlUNGJ8jVAd0cF2MI9i5bbt6Lf1xD0PczODHaKmND83OsIescCRmik2F8hk4juZL1e7OJjjDsAuUfPct7aY0ChqaKUtGsAeA9e7FRCZcGV5MiF6QqtO9hmqZzR/Lc2/p4hQrmHnPcUMXwCg2yIG/fGGc5d7wLFvTSBqH1BQgQ37aFTSAxHsbQ0fLzxpgkGvTDIuuto2i7Um3GxXWmfsy4qGkn6pyBsowds9x7eWD9gmn7uEiBXfPUqO+l/L6W5iYlT1CWYiadsQOtOMJqCRSCeCeCTzWsKhLOsVHzXjcxKd/4u8Aymm+UpKX2VUD5iWPmU4MxaPorBo0x9vj6Rf1y6TTuUTJpDB1bSozPV9i3AiaOy7FneDFfLq0W0pSRby+S/iI2Unn+uBz/jvl30cXSZ7SG8leGZevmTbLxvWYcPRd8BQXKe+WDdc+AUse8HqSmZo3cBQahGVthuVtZr5ae/lhlpubcvBSbsRMfAXdHg8hxEG01hNPd7e+Y36aP5pbEhMgxbwUO05nGpWc6naXuSJtfzL0GmVC184h3slT16g6nXUGVpnFzeyHLK8bk4LQtDSpgV8xAeUcBaKbz0JkDow4DrEaBw5s+aJSrYQyAESus8ih4PuRfivX2Bx7Bkf14nY2gszLE77YTpGjW7JhZFAibLWKMBNNZ3Ft57ysN66lzr8PYHavSFv2HsQKx13RoFFv3nqmbfO3LgHCKs5kg6lIiK20bfK+5vhPgjUc7EcVFa6xRNiTr9pMSlWRkBEpH+q6tJWvwJ043hdRbB4Ohk1Urs6TVdwQbOaMv0E7uPQNjY6htlRd4ySubKrUTm1LrXsdhjIlMt2mdIWm91PS31Sl9NDMJaZgem445Fhh/TlBax8bRkZr3isfJlaSx3jSnKhGvJUvCZt2knPi2m4xfcaks/cERGd76gJyc+qFMss5t4iH54AceksVvukM2LLg/cXzUyxbkwuXudXZOfdcXcmmN8Vnd3GWJXLrkrBwZ3iwPfPef5YfPmEKeMyUPbdsoD124Wu7YcFUlmpebE8flhPmnd4kxHI0suPvLC2X1sh/KgQdNXyGFdczJYVKt6oyHQA7atvO7FrtPkgm8/L1Gvof7fO75sk1zrt9d26YMlpJMnuDZhWNHk2SN3wW8mOihjdwYwyy9TGkYxdpucmbaq03ZLb6MQUSuvoz+Qd2NszRmkILnwrBDhN006+88kHvMIUl9167tpVw1soZxN2T+n4d2ydgUKtkhQVAluH/KnmV3ziy6GyT3pyS92VNanq0e7J4jIf2lDlOnqwoZ6Y1p0+MOogRCOirMvfcscatcFL4tRjFHKe9l6so62H0aZu3C/zBewLAJwCp3bZsCup/JxxwJCvnY2JjRW1ro8NYAaDyt5cIqxu51EnnkUOZBlYT5/ZYBOVhmdzD3VpQsZW6EMdqCxeIJ/QdCBlfcNuQ2/zrT1vYB9KpkWq23DiZHewUTlfsjM8XWnU+/qjc0nNFiWjI89pNoJPTTKeqe4uVnEul9NANuoq3ZdKoGr7DyvZL5z2DG2cCyEaPcEx1JUJyN7BwzbZEkEjqC8Ix49nEZI0pl6O/vF3nxPBn80ArXv5+VFTdul7WVjMi88sz0Q/cqN+dUN03hGXuPjzmD75JLpf+c+TJvcLussA6tEXn2ikHZ/s5w2mZzlMfHzZXmS9/UYbn7wV65+dar5eTOjTL54uXyqiWmR1w2JIN2qCWNp8hYyNhJrcLqXjdNW+Zc59wwOsTY6mTnnTcA4+aeysOZi4oe2tTTEXOt9DIl4yLvgW2VDbuEJZC1mfBltHsolCLGToHPEnb9v2VZGEehc6G751RDirEzFARB2GinlNBfitCpph1jSGIks7xmwry+byynQdnYgZzYBkXVVy750pYeWceMpmJm2uSCSjMN3WsaPjOpOy85XOpl7SYADCAEIl6LaHpUECofts9NmZ7G6WpMuyUadTNFx4X6o9DvjCGRcFiPeKPvuDkWYRb3uT3chBe3q23lKCT9YIYYM8aFqSv7wNfIJkx+O/CSMUzK+3c1TIHEQxpN3ak9uisiW+kXKak9gVGcsJOfo+dCPguyGzwo4XZ7bWMMR2Wkva6RnS2trW0bS+Ty5UG64onHRu3OmFPfPyI779gjbBdCXVzcV9k2JYjinbOkZvfJ6WDJsuXBbpRPPCajtpBn5MgnNskeQmmG3r6+6uYuLoq35JJwIc/I6Od2y+5P1R4PfVfk5Jfq39/7df+g9ikZH+dsZ+XYl07Jq966UnrmLZCr3mP6//YbZLkNA/amGHWzEaMr2PRE5DEypQpZJJX+b5RHu4lONNXcyCgbpTEKfVEZO7RBkPZaXybGapaxF+x6G3msQZqR5PUojMngnQb4MhJpCZcR/Yq/jaIefSRIC8QvxYk7ukSOt22p0Ezg+yltbowvBgLZLd2se7SE1+1aX5rRIZunFIvPEw+EVBKB15n0ptqtdQPP4tC1QQpNVdklZdR91sDLr0wTNkrApGKUxiRFlUmpIjyKmzDaQ9C/4ieebIdXEubq7o6BAWH6AgrTje45gpsDQclnfs3B4I1euWhdiHYTE0+6KTPJyeGi4DXP/owhWLBvZG1kq3YbYTEKr0ScBiix1kjuyH41T/rfuUlueM0ikWO75RZT3vVbD8mzL3Zm0kv6ZamvC7/W7Gculf5w4GwamPfKG2TTb66QRecck923mHq9eUgOPXueM+YWSP8rqjV7/ARRvKVy6b8NF3KhLH/rDXLDu2qPa14mcvHr69+//rKF7ncn5Di7f140ILe8baEc2X6LvH84MIDnNNZTz3p9r5AFBw+K7nlyzMw5AVYWR8eEkVF2POSKTmQhmEMGl9WWKVhTPErQPB1niNY4/TbzzLykx/OEDVz//UaKeVwZjX4lpCJmTN+fNQRLgNINGuopug9Fd1Nd5x6KuBFBQ4HxG3Y1uW69a5koO6O99bXqL/iRwb1uisoap4y0nN/u8ptbPk+HgvJJ2Djo7Axo0/mLyHe29TZRHUSF1aNbJ4lQbklpa+U8rp7cX1FSUzVzUts+7s2mKKreOo/i6ihK2nhw9YlkrPk89L6hti+E+k30nG58ZKaIMZp6f9lpX/3PNOnjPI5s8m1Kpp6bJ/Mqz66D07Lvtq1y6GljMr3hVtn+FrcpyRN75JaPHpHz37Jdbn/DAhl/ZI+UX75WVhibMB/525rdK+edW2tNnv7iJtn60BljfK6UWz+0RoJSHpc9t+yQIz+1RrbftlIWjB+WPU9eLGtfF19I5vDHSqaeLnNvRBnfJxu3HZKfMAYKSv/o8DrZPVaSG+4dlPn3b5LHl90p14c3c8lCofN4a7K0bXOuMnM0k4rZhjbPLotr56k6iipbw3HXLhkLtedO08tq7IqEew/qNmsLN07ZbEghMmt69L6WDTtFKYbp6fCtMnuV5llON6zvKgjtozmYOCw7tu+V4z8Q6X/XPbLhCmc4HTMG3M4jcvacPrn+rlvlqpcEbwd1OyWrbr9TVhlpte3TIu+8dUAWtTV6V5bDd39Y9p44K/LKG+Sedy8PonTPH5M9791pH1je99btcuvVbmsUp9ROvel2uXO1yEhQSBlIKGQjw27ykW2y8XMTsmLDDlnbf0YObt0kI8+tkqHbe43x+w25/IOD4jJZZ4jumDsURZnrqGGnKIqiKG3jzINbZdMDp+3rimF3dkyG7xiWsR/Mk0Vv3iS3XxOafp8ZleFte+T0gotlwXlLZODXVsnSpreazMj3D8rWO0bElrJi2J01BtkmGT56VuZdtEY23bYypCRMyuh9H5Q93z1PLj7vPFly3Ttl1ZLkQjYy7I5/dr3s+OZy2XDXWpt+enZsj9z5qRMyr2ee9K18j6y9rN0VoCiKomRFDTtFURRlTjL16E5Z/6ljsvA1G+TWd/bLi74/Knt27pbR78+XpW99v9xydQfEf54blZ2/u1uOvWSFbPiAMa5edEZGP7tDdj96RuYvuV7e/7tXSW8Lq+UbpmIqiqIoXYMadoqiKMoc5ayMH9gtu//qmJzhQdvz5suiV66U1detlNJL25pfmYuz3zkouz95UI49PWX+mifzL+qXlW9aIytLC93mKc0zdXZSpl64QObXrDFUFEVRuhE17BRFURRFURRFUbqcWfm4A0VRFEVRFEVRlLmEGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoY8Oybt06GR5zfxfOmAyb86+7r20XUBRFURRljtNVhl35wJBRvobk4IR7Y05RloObjWK4+aB5lQOnsFaPpPpr8vwRimujNirCEwdlyJx76ECzd+rqypetCKOgzYZFervMhNHRoL/V9dsGR4v9tmNo0Dcbjq+2G6gZKawcxfXNdswfY/fR/4ZNKZshg8zNWI9BORKOto7rFtvH3l+oTYroN+0cA03NHcXMrWkU0rfbWW+KokwbHWPY1U9MxU7AcxFbp8MTMrBll+za5Y4ty2XUTDLZJyY3caccnTARBBNbfPn80bwh16k4haHmPptVMjuM0mC1z6YeQzLQ436TiYT+7Drx2HDMZzF1mqW/zZq2AKf0JR65ldZo380r77tDLrUdr4wfLclg7PgYlNLRJhX2aJtPq+Mnnrhx12o7pxrFHC3f94Scom9PnDKvppf235uiKJ3GzBt2zgM2/OSADIUnpMEeGcllgHQjjZSTFoxbMykPH0U/HpJVYcW3Z5UMDZakvH9XvnMvi1G0zXly0UaPYO/qofry+WPLgPS67zXE9cf6tjBHTuW1ofLfyqRqyzkkIxfWtsvgsqBPTbtS20jx98eMKxLxCvDQtUEP6b02rh8Z5dh+WiXa34Lf99Y6UWJ+17UkGtruHi/szT7GrNyr7btD14qV97n7bRFyqWnG5DEjY+2/M9GtkQFUmK2DpL4W9PfBZQzR7I4GK7vMuUuDvl6HZOBJM8bzyMAUmZBfPgVybWh/T+34NbJ9AmdMC3KldGPofJFz21F9YS7PUR1j9/l6N/eQsZzB3FGUczvJ6DfHjbNGQimK4phxw25s/4iUe4xRt2VVrWJgFAmUpdwGSFeRLHC9otksY19nAinJ5XFyu3S5+aQso0dns9FcT88FGeoUw7euPZpRXtOMzVYV/rIcvNeNm8jEXLoxiGCNPdC+tJ9Yooq/V4qihlJWRSKroYiB0Kp8MAryrv1BbZWNPGpGRZx4srnarvOobzbtat4v7484BdqYxtUSY4/Z+ipdlr1HW0U30ncZK9b4mO5+2wLlA9W+ksdoqqPZSE75lK2rLHXfY2SXKWU2A9SNB8Zu1UbulVU3mTE9MSK7sjpb45wBTRrdQV0zX0Zkp3NUytHhwp1Z5aOjpn57ZfmyZufiICodOFjdvRM97dSxrCjKrGCGDTvn8UxQmHuXLTfvzz0DBAJFsUd6W3MWplKrPBagIHcqTgHqGCbKVpFr2hM8MSaj5gS9y0sx46ZXSsvNuxOjMjYL2rMaMWhwRB1DWcGAtMaUVxqbiXj6yE1ZRvZXf1gbsY1X/BOjBdGj2ftrK0ZxfYC7SnAgxRLUVVzfLV0bGA4jBSno0bTaIWe8FwEGOeezjgvrxKDf5DTu3DimTkaayUzpXWzrMHDipRPMJ72yOEMnCgyakgysjnzZGFEDxvguj45Nszwty9iouWLPYjMjxmAdldnqITumTegvPculFHPR6twZH1ULHDbBnIoMs/Yshi4vTB+3WSGaBqkoShto0rCbktMP75SN6xFe6+WW7ftk/Kz7yPP0qOzdvlV2PjK9U0CYqdOHZOcH1lsBvP6922TfdyKFfP6MjN6/TbbuPCzl5917HUFZyk+af5YFE1YzBF7cBA+t87LXRlPyrlXqVNzanZBXtPwUM282pSYWV1/W2+om85aMYGtotuIJbhOV+2t8FO0dTyJ+zVvckSNtKZxuy41UUtnCaWvZzxtEE4xBTXuGIge1EdvGUdq61N0WPPvZ6635SFP5wC6nuJp7C9cpR1IHcWMpNnre02sV94mnipkzok6BVrMgLO4+icIgP4cwfogaVYy7rMsHqlF3ayw1EykORauS29E5KmzUKJKWn4A1AhOMKBv5myVOo2S8kd4rAzfFO1Sqc2eoTkNjgPr2acLWqPO4KCYyJjyfzN6sJEVRppumDLvyg8YYelDkui0IqCk5+51DsvvB0+7TgLEv7pbD3zktx07Uvl9LjyxGKB4difd6kaZp/s2UQhfFCNltdx0UQQAbyTr1g3E59MmDUlOab+6T3V8el9PHjte+P9OMjQQKU470pjrMBBIoqJFJg8kHpcsoFOuiHtlZSlL0s+p1TVdufVprNW22FSPYRTkSPMGZ6CnJcvPbeM+5927nOX9ySnDSUaOsxNFqlDQujSv1yKa0Wk+6S3esKP516azufXuTZbv2K9G7PjbsIjfrZPDGdUEabHTMNSRwRkTXDw1eiGc/57ly11tjgzMOjFAbATPKq62maApzagdJd7KUn8xVee0nbLRWorvGUAzLT3f/yNxwJkSSkVcxiq9bJauIVGJMNGPIVwyFwIDz160eRrbFGRiJOKdiUhbNBc0KrVYwZbnQ/JMQzfUpsa2uhbPYFHBn1G3JJlMqRMdAStp5baQ+53UURVFSyG/YPTcq+/Y/LaV3DMqK8yflzBn3fg3H5fEngleLLuoLXsTi8vajylPIK1pRHCq47/pJy71by5SMfnFEni6tlcHXLJTJp2MLKcf//kTwYtFi6Zvx1YZVUtfH+TQOjgaKgJ083CY0lYneKCbW2G1rale4jVr0RoajSE2mrgSTaL0CW/W6pim3Ls2uhehpDalplOgVvt7SomLV9S5DkToZu8+l/xiFsX3t25ggSmr+nfa0rXTCClVDRTdsJMUoaX6DiaqTxLTLFvqS6/9ZFXXryEGRrO2HwXpJc65QemdAgeMrN94INXeGwZB1zaTD94uuwijs6641xkUGeVHpX0TwEpxnPo2zxijmhZPtyeM+mVpDIXLkbKOmiJPTcetkY28u1J8Tbr50Y1DnVj5WxpWLkNqUyfq6zhd1d8a4G89Dc9jYyjYHKYrSqeQ2Zya/9ogcO2+FXFOaJ3L6ITn8Pd7tlRUrFtnPLePH5HGb9bhAli5ZaN9KxHq5XATETw5hj3rdpBTeeS5hgp08Io98a4GseENJ5slpeehLQTyud8UKqZZyXI4dC1IzFyxZKg1K2QTjMrJ1k2x6LwJyo+z9jnu7EWYyDNJ8BuLvzU467v6zGGcxHvwaT3NbCLdRixOk8zbbYzoUlAg+zW7g2iKu7dKvTMvWrV9xhNPHUg0PP27Yqc5NwnYidrvLNjRa2oqLGkLOtK26dMS8Rwvpi9kJKZT0z5px6KI5pP0ZRT3LRhOBIyduPa1bL3nUpQJXKHB8ZSYw6FCSg/TL5sZjEPEpy6mUaikk8lIwpNXmkpuMz6h8doaOT+OsqT8rp6vGy8wp1C469mQ5dhwlGuYpcjqaEstRK59C/TlRcFXTpKvOzcCxa+syZi6sXjdljLg2sWPZXaMpp2c4qtvUMd0OmmQyz0GKonQkL/iRwb3OzfgXNsq2hydFLloj229bacy4gEqazvwVcsuOtbLUvT/1zLicnlokfS81RmEsLrc9wRMcnFfMJJBDmRnfJxu3HZJJY9Kt+dDtsvIl7n0EsTUg58uK390ha1/h3p+alPHT/ySL+hYao7BVzshBY9yNPL1CNnxkrfQ3MqN9mTDe6iYXFCujVEncZ+0kpU2YFI0GwkTgJ4DUNor5fjLpfSFMpb9lgbq9SWSXi1ymKmuuvFZpubbs+ksIX7aM94WnPljrEvO9XHWTn9h2qYyBZkEhS2pnnp84IKc2mzbskP7s679pwn1xwii+PfHpavEk9+egXCiV9Y6qoN1I0Qw+SxpfucZAHLFt5Aj1E5ToTAZOYn8O6mEi7jyxv0mqt8ZyKZ6EPjtNlMdMuUrx0fpY4uqkXePWEe1zYWxfxXlU6SuN2yFVptnvICtcebL8ppHsyHSOziZpnCeR9P002VLHLKg3RVFaMuyOy55bdsiRsyJ9b90ut17tzbopObJzvew5Zl72r5V7NqxwBpL7/k/VGoG1pEwShrzCDo5/9hbZ8RVTyJdfL9s3XlW57tTXdsr6T9tCytqPb5AV5wbvB98/v9YIjPL9Q7L1vim54fYGCulzR2TnzXvk2JK1suM9K4wJmUJlsk4Sws0qwu53Wb2BdQpevok7tY1yTRzpfaElXF2nGna+PdKMEp7DRdky3Jc3KhIV41kzqUbazd1X/X1Pv2HXsdg6Cim3FerrqBkZ2Hbi+m5Kf643DgLi30+SA/nkEjRXd+467q9m6LoxnSQfY9/P3w41RPt+lt80kh2ZzhEl5zzZjnkpRN6+mvR9NewUZe7R/MqyJ0ZlzGYy9snly0Jm2vPH5PFvBy/7+i+tRr1ceuaCvosTjLp2cFxGjwbpln2vflXNdY8dw6gzvPxSudQZdZX0zJdcLBef596K4/kp+efnptwfKYyfNGcUWfTKS9ONOgSqNerwpGYQwLlg3U81tSL56IBdMVEc1q2b+YfSV9rDTIgtGx0oDIFRhzKQaEi2Qkq9MeFPX5oP94oSbPqxT10tBZv4sKFEnnYNyh2XspRwTEsKZhoouDHlckfqvZcGgrV0tu6qBOslTV0m7MzXaWTdzdKul4qsD6W9bTR7hteG1oNSHCcvg8OmBjb6ToxAR+GO6ydJh9G3pw+3ppAxW72u6d/O0VXUplvliZkdsbHgyItpw7oj0ahzciDDevCgDzTpNHAyv9l152HKBw42VwZFUTqSpiN2Zx7cKpseOC3y0lUy9EE2QHE8sUdu+egROYtyF/IeTT6yTTZ+bkJWbNgha/t5J5+HDI//OtmVz+P6/YOy9Y4ROS0LZdXmO2XgAvd+KNpYE0mYPCzbNu6ViddskB3vtIWMB6H6iSlZF77vGMr7NxmF7p/kqo3b5foLjsm+T+yTY08/K/K697trhuugkVfNfbdtEY6k8zf2WIc9fKmeRucRTMVMrIM3laTUM5HsCU4kYx3Fep4h1B6xkTqP+16jiF3ofhumsCWdIwuJ92NOaz22tW1UT4rXPSuuDKhqcdfy5cDREPSNovpz3vOE2jgrDeqlcm9J36vUTa1MjBKMnZCyG9MHU8cXtNKPmqTh/ccSbYekuknqm/nkEjSsuyYI7j1jRKQZUtuzgHGbRkh+WWKvk1KG6O8jWJl4wYj5TnrErio7MkA5Lnsspc6SKEoeZW+TtL5TJwtiMWNmcJ2USqa0CX07W925sVeeftmhKErxtG7YRZSP8c9tlG2PTIq8ZKXc+qE1Ig8Myb2P/qP88NlJmXp+nsx/yYvkx869XG7YvEaW5owX5p6YK4ZdRGn4zl7ZuP2wTMoCWXnrdlljxPnQfV+Vfzw7KZPPicx78QJ50byfkMvfOSRr/Nq7MJkMu0k5vH2j7B03gvvjA1LedrecXL5azjuyT448v9IYw8tlzCk2DZV+S/MTT66JMdWgaUxxylMzSkurk3PZroEZecq0WWp7uOukGXYVpSaj0hd3joxU2reu7ULKb2o9tqogVq+TWn5zj0NPXS7rlpWkt4Fhl02xCdFiv40nQ72kGNW1tFrHAQ3HVwv9qCnc9Xp7em0EpvjrFlNvEFd3lX7W5PnTlPNCSG3P4uqmeVosg72/vKmYDWjqHE4eZXT4JJ/b1Yf7qzHF9J1C5t0i6l5RlBmn6VTMhaVXySJ+PTEqo0+Zf5+flONf2BoYddB3sfCgg77rhmT7XW8TG/+6aEC2fGi7bN+S36hripeW5FV2G8yyjLpd+iZP7JOtH8GoM5xzsVz8MvNvn1EKTbneZgu5SAZuN2X8UIJRl5XnT8px8jAvPE9O3bdLTr3xDtnQV7Y7BC664lWy0KigPkWysVFXBEwgkXSSuKNw5bib6JXe0qoGRl1GKruRtknh85jJGKOuxLOwIrswjt2HgmHanVn6aPXB2cVT7VupCoGpk6HVGHXu74bgkAn1zbSjW/ptwm6DXYlTBDGq1xmFMnhuZgekUucgeMal6WeF7HqrdD04iOLkS+RoaPhg6Mb8LnwEabxdAmOd1M8ZT3lXFKURzZtXPavkPe8dkP7zz8jBLWbA33Sb7DaGjF/H1t8fSmU88biceN5Mn+a96VtfB8Z4es+tMtC/UM48GKzZue1TJ0X8+rlLLg3tVOmevddj3gutr5vi4euf2l17fPEb8uwzY7Iv+v6nDsm4X3r33ZNy0tyznD4soy8ekDWvNHf+8utlx6575PbViwrYcVOZ6xAtsIq1USIGV1fXxaBY+yheadAYlm6dm30+UQFrMpQQRg4OuDWEiXVLVM968Y0B0SXr5dIhKuH6XihSyrPU/HrKaV8X1hTuYdy5HuavKHOPymMuJk5JxqCmoigzRPO7Yj43JVPnzqsxUKYe3SnrP1W/02TNWrOXB+81Q+50g+dNGf+vKWO4kM+Nys7f3S3HjNHV/857ZMNr3IdPjcimLQfln66+Vba/Ne2h6oYMqZhBqurTsvyd66T30V0ycuI8WbV5KLTOLy/TlIppyJYaGk8hKSGWZlJ88qXTBBGhVstpKCKFJec5fJtG26qSWmZI/KyuTvOmD2EwtnCvloJTMQ3FpxDl6YPpddjKmArTcHz5KFpmcqSC1Zw7bezU1kVr7dKMHIinru4yp9Em0xGpmO6vLMzsGInB3l/3pWImj5u8bVJM32koF7JQRN0rijLjNGHYTcnx+4dkx5fPiJy/Um6/a4176PekHLpro+z7nsj8190iO97hn17n1po95Z7l9uyY7PvKPFl1bX/6TpEtMvXEXhn6+GE58/xCWXn7nbLGPZl88uGtsvELp0VevEJu2b62khJau7nLpIx98RGZ98YB6X9x8HkNDQ0798iHb5fkho8PyvL/GRiNsnpI7lx+TLZ9YZ7csOGqNjwUXVEUZTZRnGHXDtpu2M011LiYObTuFWVW0EQq5gk58hVj1EUoH/i4NepkwQq54S3eqIOTcvw75p+XL5Ulxsgb/dN9cqZ3cVuNOjjxKEad+8Pz1EH5+BeNUXfOAlnxzutr1vmd/AcWxPXJ0iXGyHv0ftn3dK8sbrqQJ+Wkfc7BxbKUgOCZM0KNLertldNHDssPL1qiRp2iKEpDMJp2daRRB6Sftn0d7VzCrU1Ww2IG0LpXlFlBE4bdeXIeD+4+t0/WrF8ji9g05cAO+fB+Hn2wQjZsWSv9lefCQb9cs7pP5o0/JHdvv1eO/9wtcsNl7V9pd94CTKd50vfm9TZaN3nioOz4SPDogxXv3iJrX1m7yq3/Dauk79xxeeij2+TeE6+SW961XBY0UTuWpyek/H/mydJ/XwrWFPavkoGXz5eT+4dk97gxfN/UekqWoiiKoiiKoiiKp7k1dk+Pyp5de2X0e2eFvULmnd8nK970Nlm9YlHzxlDRPH9GRj8zLHu/flrOUshzF0rfFavkbb+wQha1aldmWGOnKIqiKIqiKIoyXTS/ecpc5vkpOfuDKZm3YL7ubqkoiqIoiqIoyoyjhp2iKIqiKIqiKEqX0ymJk4qiKIqiKIqiKEqTqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoiqIoitLlqGGnKIqiKIqiKIrS5ahhpyiKoiiKoiiK0uWoYacoiqIoDfg//+f/yN/8zd/IwMCA9PT0yOc//3n54Q9/aD/7p3/6J/nKV74iv/zLvyy/8Au/IJ/85Cft+80wNTUlp06dkre//e3y3ve+V7785S+7TxRFURQlHTXsFEVRFKUB/+Jf/Av51//6X8vP/dzPSalUkpMnT8o//MM/2M9+7Md+TP7tv/238vrXv17WrFkj11xzjX2/GTjXi1/8YvmJn/gJufDCC+X88893nyiKoihKOmrYKYqiKEoDzjnnHHnRi14kvb29snr1avmv//W/yje/+c3KZ//qX/0rednLXiZLliyRf/Nv/o19vxle8IIXyAtf+EIpl8s2MnjBBRe4TxRFURQlHTXsFEVRFCUj5557ro3MkYZJxO7MmTPy/PPP239/8id/Us477zz3zebgXM8995w17Dgf1+P1d7/7XXn66adtqqaiKIqixKGGnaIoc5If/ehHVoH+wQ9+4N5RPBgP//t//29bR93A//pf/0u+973vWePnySeftIbQxMRE6vHUU0/J6dOn7W/+23/7b5WD9W2Tk5PuzFX+7//9v/YganfRRRfJz/zMz9jrHj16VP75n/9ZHn/8cZs22WqEjbr///6//0/+5b/8lzZ6R1m5xkMPPSR///d/b9slDtqKtX6UHeNwLkGdcO9Zoa6o52effda2qdIarD89e/as+0tRlJnkBUbAdcfMrSiKUiBEXI4dO2ajLtdff71VopUA0gz/9m//Vt761rfaiFGnc/fdd9sDZR2DC6No3rx57tN6mPYwgDCannnmGWvge1760pfK7/7u78rg4KB7J+B//I//YY1G6O/vl6997WvywAMP2DVxH/zgB+3rK664wqZjttKXvv/978vhw4ftRi2XXXaZXbtH+R599FGb4vna177Wrr2LwnfGx8ftZiv051Yjh90CRuzevXvt2kfqKgvUFUb9wYMHbV391E/9lPtEaQY2DvrHf/xH+fmf/3n3jqIoM4UadoqizEn2799vlfv/+B//o103pVQhkoFxhzHBLpCLFy92n3QmGEJ/+Id/KCMjI3LdddfJW97yFhtVS4Jpj0gNCj4KKQYeEbc/+7M/k//5P/+n/MZv/Ia8733vqzGgcAJg3F1++eV2YxP6zs6dO200bevWrfL1r39drrrqKmvYhfnqV79qN1oJG49hMAI53+te9zpZtGiRdTTs2rXLXo+1fG94wxtsFJA2wcjGaI0ztlGu+Q27ctKfMTjnArQl9Us7YKCRJtuI0dFR27fpK6xjZGMcpXkYP/Q9jGV2c53p+iTy/hd/8RfyjW98w47Za6+9Vn7lV37FroP1MB6RcX/+539uxw4ybsWKFfa4+OKL3bcUpftQw05RlDnH3/3d39m0NhTgVnYwnK1g9LBmjC39iYC98pWv7OhNPCjrww8/LB/72MdsBIfHBGCwZ9lRkjRKUvn++3//7zI2NmYjZexKuXLlSmtYeTAciKa96U1vcu+IfOELX5C//Mu/lEsuuUTmz59vP4sadhhqGItcJw4MOxThn/3Zn5WXvOQltm9u2rTJGpB8Rv2/5jWvkb6+PveLeujLGKZsuoJR26187nOfs/WcFYz39evX2zRM2p/o67/7d//ORlSTOH78uHzrW9+y0V2MEKUKdU8b5OGmm26yRtG3v/1tayAROb300ktlwYIF7hvTD/Lgscceky9+8YvypS99yY6lG2+80coED+MRo+/IkSPy0Y9+1Bp/V155pbz85S/XCK7S1bxwyOBeK4qizAk+85nPyMKFC+XVr371jCognQq7PBLxITKEgvTjP/7jdQZLJ4FRRTtiCGFoobQTiUHh5F7S8Ltd8igDjAKMfQw91gzRPzykYRKlY9dLD4YU6+EOHDggr3rVq+xnbHgSBuOSSBxGSNJBiiVlwKDGEPzP//k/23RQNkshCgKcgzJxTY4wRB2IQJCmiXHYraBkY6Sy7jXLQb8kSurrhDbCwECRT4L+gQHI78IRHEVsKi/R77i6TjqIcJG+jLzAWKJ+ly5dOqN1izxg/DN+GMv8i/PkP/yH/+C+EYx7HDgYcUQciegxhomeK0o3oxE7RVHmDCjOpN69//3vt9GYX/zFX3SfKEnccsstNmLHejuMj06GyNi6detsWiTPk7v55pvlp3/6p92n2WH9HBuwvPnNb7YRQDZJ4T0MAuoBJRYjEmMKRZY62r17tzUEo4ZdHuibRAy3bdsmf/Inf2IjCkRBMCjpq1wXY9U7I5i++c2HP/xha/j91m/9ln1/rkIqLevmWG+Jch81gKmrj3/84/az3/md33HvKkWBE4I+eMcdd9j1oTOVkomcZ8weOnTIjuO/+qu/sinMf/RHf2QNN8YusOkLn5OaSyq0PlpEmQ1oxE5RlDkDCvJf//Vf20keYwVPs5IOu02y0QybkcRt2tFJEGHEuGJdG4YYihsplXkhykaEEsUUjz9GFgYDhgFpl3j6fVSTNEDqhxRI+lUrEP1D0eS8RN+IJpBWduLECRsd4T0fmQQiJBiCGDBsHIJxN5fB8Ka+aCf6KhE9D0YwRjJK/yte8YqOjkB3K4wFjDvqms17Zurh+sh5drslek1bs5aOMUQ6MxFyb/Az3r7zne/Y9EvmgpleG6goRaCGnaIocwZSbv7Tf/pPds0SaXN47pV0SP9jcwoMC1KVOhkMHowu2pW0PNZT+fVrabtkRkHx43f8y+9QBukzHKRq8p43rojQsaYIxbBR2mcjuCYpoawRI1WYv7ke65ZwRJDeFr4GhiubxlA+Pp/racUYFijrpHQuX768pj4wNj75yU9aY7lUKs2ZXUOnE/8MRtYwYlTN1CYkrIV94oknrLyivUlv5m/GC+mYfvMhIuLf/OY3rTMIueHHtKJ0M/ocO0VRphXS5dgggqgKi/XZsIKJl9SZMHjeSZEhnYaoBClvKGwYZx6UOLyxRGfY8py/gUgGntiNGzfa3dqY0AEjhTQ9lI44JZjfUxa2+ud8rM3wEJWhrGxrz3dahXVgeLfZ9IJ7Y5e+MGzmwXoXIkVEGWYKPN4ozHi8Ox0UM5S2q6++2m6EQD9gPSWKJoZpVjCevFeffzGuMA6J8nD+sAKIEcn7RNlaBUOOvknkjfNxbYw50kkpgy+Th37BvfG7uOgIkQuMcsYbG0kQffXwW9ajsT6Qft0pECFlrReygbWG7HDowThDQWdMxG2yglFMqirygKhdGH6LLKDt4jbHoH9wXXZSJKWTeguDk+DBBx+08mM2E5VLyMIwOEyQS/QbxlcYUrVJweRZkDwncqZAXhG9pTwcOD2I1iFjGRNenlJ+5Drjp1WnjKJ0CtqTFUWZNlDKmFxRoJhcOVC2ePYWmyZ4MMrYtANjgsmX76F4oYCi1AEKCB5XDEWOT33qU1YZ80YcEzu7OqKQeSWP8zCxM9kzmYfx5+PAqPzjP/5ja8D58/E7rk35uR6gLKJE8G8e8GxTJpRWjE3OiQGLcevPhdLNjm7UC98H6iKqTOXFl5lrogCjhKWBEuzrplvACCIFk40dqD+MdOraK3SzBdoSQ4gIYjjtEOgnOCZQsOnD+/bts0agHwt8joKOg8U/nw/oG76/TTeUCecK5aHPYWAx5n2ZKRdOHsoc12+JuhCJQ75wH1GQIRjH0bWi/ro4U+gjPDYDAy/sDOCapHKGjWPK2Gqf4ve0E+vAMMDDzqTpJiqXkMHIJWRpVC4ht6P3jjOCFFjuIeqom04oV1guEwFnYyTaDoOVMQMYc+Hou6LMBtSwUxRlWmCy59lxKEcYC0RUSJdCmcCA8goTCgFKDt8jesEW8kRg2KqaNB8MLpQOzocSQuSNNDgMFRQzPLAoGKx3IsqC0sYkz2TPwfejkQ/gupyXz9lRjWihPx+gDFAuIjQ+2ofCjOHAM8aiSk4a/A5FEsWQaA/n5jw+4ggYwSioRG+84kG0knqKU1qzgrJDPbJVPweKWiOowyKU2OmEyMHb3vY2+7iAz372s9YgIEVrtsC4oR+wGURcmimOCPoVBh9riGhnFPawYYdDhfP4HQxpX8Yijg0+n24oL+XG6cLOijh2GANeEaesGFjcN6mqcfj+Tfm9Ys+/vq6iDh0IX5cINXWAk8hfl9/7NZvhaB/fwcnTSl1xTxjfbOpCRDBsZE83YblEei/3jwHHe74ucZRx38ilpCgXv+fg3qYb3+70ey83MTZZG0u0nTkIOUofoXy0p0brlNmE9mZFUdoOEygTKmlMpIxhqHnY9IEHBbPrHxMyz6NCicLzzsOWPRh5KGYYdBg9HERmMMK8EkYaFt8D1j7xcGeUWn6HQovCilc/zrBD6SWVi53RiBii6KG8+POh9HBNUnr4HrDRxW233WbvK0+qH0YkETDqgdcodigdnNsrI3yO8sH6La948NBdIpN81qzSxLmoGw622c+yIQplo864R6/gdQMo6b/3e79n65Qd8ehbswX6Bv0PBTYuDRSnBJEpbyARdcEB4jcMov8wblBsGTeA8fMHf/AHNiKDs2K6YRxgXCETGGsYFBhwjHGg72HoYYgmbX5CP2WM45DxDhDqivrAAI4zgqlHfsdY89dFTiFfPMgHnEXhXVZ5QD3pitRts1AeHEWMR8a/lzczAW2O0cOjIHhNvTD2WSvnZZA3ioiAxclRwPlF//JOsekEuU27I/fD5UOus/Ml6b0Yz6SbMh+wfrWINGpF6RTUsFMUpe0wyZMOh6KJQhAGTyprIFAGUNz4HsoEE24YDCsOD+k1KKlM0kQjMOJ8JA2Y1FGWUM4w7PAg+2hFHCiTnA/lEi/161//+soGCxhfccYeCg6KINdBmcwKyjT3jLKEUUi9UA8eonLe2IsqVSiRGJb+vSjUBdFLypsGnneUShSgRmA80D7dBu1CfyNyhxE7myAygaGdZOATqcRgw0gh+s148gYS44D2933JOyqI2NFvUHTTNhfhe2w6sX37dvnt3/7tzAdGNmtUGUdx0NeJFGFUPPLII3aM+y3oMRIoszf2fJmjMO4pe1ipp45w/CRFnDGoMNgoF8Y/DgHv8PAOHRxKYSMTMPYgyRijnklnZDympTKTKUCGAMZq0n1FYddHdmuNq+e0g8dyJMkG7o/xgmwhLRT5g1z0IJcw9jC+w3IpCvKW384EGGy0VdRgoz2vueYaa/Qh32lT6p35Iek+FKUb0d6sKEpbwaAiBQ5DBQUqrCgABgOKAMoX3/ORMxTTMHjq+QyFAeUPZQrDBE88G6gMDAzUKaModygh/MvvUPRREOOUYcrAdzEUmfSvvfbaisKGokB0g9ROvPYogChsbCCA0YMxhdGVFcrN9QDDjnKHd5xEgcXIxRih7KwnYt2Pj0yiVCcpqSgrfCfJW8698x3ahTpB0WHdCamKXDdO6fbpTRig3bQexRs/GAM8t/Df//t/7z7JD/WFId8K1CHtQgSNyAEbmjQLfYi+SPvF9QXaivbl3klfZEdPb6zQP1hvh1KLMk+Z6FOf+9zn7H0yznxqdBwowhg4REAYJ1kPFGufEhcHY4kDRwrr/0jVxpECtCPr3pANOEYYq3HQvzHGuIZX7PmXKB/9gSOKvy59n8ehMBaRMYBxxkYtXJODPoBhsGfPHvsZYxPZFIc3KDmo1zgoD/VPGyILkTXcJ5uWYLwl9TlkE0ZYXD2nHewAmfQYAi+XGOMYdjjKli1b5j4V22+5J9qE+kqCPkkfSWrndkI/oV2iu1z6+qINWbeJzKPe6UfdJNMUpRFq2CmK0lZQXPyaHRTJOI80Sg2TLN/jX74T9owDiiiGH1uVo4x6pQ1FCC8ySiaGG6DYMbmjgHgFEEWEz1HekowiyuiNUJ4Z5s/HOhqUN9ZteYUB5ROjEs8wClBery9KPkobRim/5/ELHgxFlCK/XTjX4/q8h1c/HI3Ii1fc/boqIgko/yg6rC3ivqJQL9RZkjLdqXBvGAhEY0gvyxKdTIJ2wkBCSY9zDGSBOsRgov795jXNghJOGzJekowGrkfbYrATIUapBcYAyi19jnPQvzD2+R59DsU/rT/zfcboFVdcIT//8z+f+SD1GOdImsJPmemDGE8YgV5eoLBjbFA+fx9xMK4wLJAPfpzwGpmBXEirKyKFyBnSV8PRTaJp9CEi+tw745bxQkSU91qJ+NAWyBzui+sjz5A/nJ8xn2TY4QwiohlXz2kHxk1ShBG8XEIWROUSDi9kgJdLSVDH1JOX0dMJsoojCuWmTZHhjGWcZJRRUWYbatgpygzjIygYJ3ETUhaYjFFiOU8n4r23TPTRyRTFBmUGBcp/DyMMxdXD5ygVGFVr1qxx7wagrHHfKFne8CDFjAgaSgyRC+DanJf6pp7jlHPeR4HkfChylAUlBUULRcAbdihGKIooVxgMGJV+PQ5tQZnwtlPuJCPAK6AosXjJURD9b1FquTYKFPWAgcp3ULK4HhEFlFaUUa6BseAP+hF9gTKH3+c6fJ/z+zQrjALqikgOynycIkYZuVaah74TwUmAkk5dvv3tb09ck5UVIrTs0kj/oJ2agd9haDEGvIHQLLQJfZv+RbvG9TPeD7cxfYg+Tt14w452x4GBAUWfIKrJs77Ca8mmE19m6okxRdl8P6ffYpwnGXZ8j/vjPsPGFq+9HEga+7zHdbkOBgBGDeej7mh7b9gx/vmccYk8oK4oE23LuRl/fswRzUMOMR5xAoXHIzKGa+I0wqAm5ZQxy3k4fzT7YLrg+l4uEUGMyqU0w85/j34Ult/TBXMI8jrJ0OZ+WLfNGMZBQxsrymxDDTtl1sAkzMHkkgW+x0TMRMDBaw7O4T/3SlMSfJ9JEAWNI3wef14+Z7LjdZxCwWeseWA7ciabMHyf3/lzJ8H1SAvEw5tW3pkAhQoPOIoRdYHC5tuKAwWTVCfuFUWT71EPKDl8zr2x3obJGKWTXTLDoOBikPA9f05v2KHMhqNMKBukN1IOjigYL0z+/MYrgih6pCARZfEPsgUUMoy98HtAO5HOyS53bEKRZGyjfKC0ci0UIe6BvsAaEdLiKEtYgSKKx3dJZ/WgiJJCed9991UOUvzYZIX+FH6flE/Oz4GCjKFMW/hzvvWtb7V16zfS8HCf1EU3rVGjD7BWirr5lV/5FXt/eQxTxn74oG8RVaEuUHR9JCgv9D9SInE44BhoFfoQBgFlpF2j0LYYOVyX+8eYJCqEvKGPecMOfBSPiFpSqt504MvsHTG+zIw1UhQZE0l1h9zgIN072t6cB4OJOmPcRKGOonVFnXBdxgtyyRuUGBAYezgL6A+A/EJGhccdO/gyFjlYDxcejxh3yAr6FPKP6yArkAk4bn71V3/VrvOdbuOjkVzivSTDzss+6nk6+5AfoxieGNG0Ydxci2xHxlE+HBmzbd2tosALhwzutaJ0NX/6p39qPZ9MhI28nRhKTKR+nQsTN5MCB+dAEURB4H2U+rgULia7PXv22J3R7rnnnspDbZmkSd1hwwK2r77//vvl93//9+2Ew2THpBIG5ZP1FGvXrrXl9t5GlAeU+R07dsiHPvQha6iw3oEJNwpKCAoGD/BGAW0l5awdUD7K5I0k/qWuiKhQbhQxlDUUZpQGr8hxLygTKFhEqvCORxU2r5BR75yXNBvqECMQJSSMNywxVIi6JfUTfo+Si6H8X/7Lf7Epc5TpAx/4gFUOuB/6Bgbnhg0bKu8B18Brzxb7KHq0d5oCgVLCuXncAfdM36FPoNTxLDZvRAwPD1ulm3rw76F0Ec2jX5AWx4HySf/l/vFO+/epV+6b+8foJPJJWb0RiRHs+14YysN9sOYxnJbVybAeEUWUfkWfoR/49skC/Q3nAMoiCjgbftAHUFxpa9Zf0e+ahfqk79Puq1atcu/mB+UVuUI/wLmQZPDQvvRl+hcyDnmDbOEB/vRN2p3PPvnJT8rg4KA1FuP6wnRCPRPxwghlbFBmxuL73vc+a2TFlY+24ruMOdbnIRc8jDPGJb/j3N4gi8JnGCekIlJHXBenyHvf+14rw/g9nyOXb7zxRjvWeI/+hWxmjHJtxhwGPOsgSSllcyfGsx+PRCP5PsYqj514z3veU5HfGFZJ5Zsu6FtRucSchvxhrWScc4M5C9lFfyNN1K/pbDdEF5mDMZhZI0lEmrmWfhwuJ23EuKX9SOmnneLuQ1G6GTXslK4H7zyCGqGOkoMC6ndSi4O1C15RQ0FgjRS7oKH4orChGDOJYahhTDFxx6VxMUmgBKBsoIAwif3ar/2avT7n5XcoAhychzJxDZ+yBxgjKCMoIpQjrKxwfhQ2JleMCL4TVvTD8F2Udu4fxR0FNHydmYby+fRF6om6oJ5RXniNgcW9hr+HwslneFapf+o0zhBDecO44by0H9/n3v0asijUE8oU1+d3UTgf5+H6XBelAYORc/7SL/2SrX8MIhQelL93vOMd1ghEEcKpQBtiSFBe7gPFLu46HsrB9YiUce+cEyUUgwTliPPiyefh6H63PpRzykNZuBZl9gcGiT8vfdC/jxLJWKEvsvMoO0VSV9wbihBl4F4hbDzj/EDRxFDkXjoZb6gyfuk71KFfQ5YHFHnkBOvSqF/aBGcQ9c86MdqJa/EdlHLvFEo6+C3loI9DUYadlxE4o+gLGBVRKD/9mP5FGyMbiIbTpm95y1vsmOI95BCOCvozBhBlm6nIHWX2Y4J/vYxH3hKBTRrb1CkylUenMD6ixjdjE0OR+w3vQuvh+1zPH4xDUigpD3XFmMLYpyxkSJDiy5hh/PAZ50e++DFH2zC+GE+cjzKFP6MczB/0o5tvvtk6FDgX94vsIJrHPft+M52E5RL1zRhAFjGmeCxEHNQFzs7LL7/c1i/3OR1Q7zg2cOSwNpqoOPMw8jg69vku8w6fd7o8U5RmmFmXnKIUAJMjyhOpZX5dUxx8j/QZFFUmKRR3Ul6YCFgrgRLHZIRyhCKNd5JJNin6hSLF95l0UZKImuABxBPIwd9MMDxYm0XrRDuiEx0KJJHB8I6IHpQMJlQmLJR5lPC0KAGfMbEx+eI17TRQUDBsUY5RFjj4O6zwQvh7KKRMwH6SjoP6wYChzvmXI8nbjdKFUkK7ctAnwtA/OLgW56PNaB/qFgXcKwn8i0LMdehLGNMo+kC/4J7wapOCmqSUoQQRzcUQw/DDiKONUfIwosLRMZQR+ivXIBKFZ7wZMDC4H+oXRwF1Qf9GecU4pd9zLfAee69copR2MrQl0Q4eIk+7MKbylBklnvph3BM54b5R6DHieB9Fl/GNwU6bUk8o7Iz9Rgffy2tcZoG+Rj+h3TDYfR/04HwggsH1kQ2MKdoVwxJDhbIBZaONGW/0BeqRe54JMFJpQ+oe+UqZgXFCunCSMk4dMA5Js0SG8/sw3CNyhDrCcI3WFZF+nkmHA4Rxy3VpY+QETpCwMUl9eocdzrS4NNgsMBYpl5eDRPKQPURXmc/oZ+3oN2kw5nH8UJdhucQcS/momzioT9qIvsP3w/XVbmhr5lsM+l/+5V+WK6+80jp2vCyLwpjhc0WZjahhp3Q1TKhM0igqwKTuIxZh+B6TJWsemKCIjpH6yIQaVbz52+90iPKOURUHiiAKNtE6rwzEweSCwoT300ec+C0GqFceUdrjwHNLBALlEkOoEXwH44XUGc7N75UqtC1RCOob7zie9zAo9SiV9CHaiCgG/YY6xQHgFQUMPdqU9XUodvSRqCLDOVC8kwxSPueh2Siy9E/Kg3LJNTEqMSCAa3J9jAr6AeWi3zaj8KHUo5SiABERQAFDgaVvomRyfq/so9jT9/gO90cf71S4LxRKovAYzCig3iBIg/HBGKYNSRHGCLr33nttO1AnHsaTr3cP9cE1eIxCowOjKmpoFAF9gDajfYgk4dgKQ/uReYCs4V6J1BGx4rtE/zHmgHGBoY9CTH3Ql2n3mQD5zDo1DCrKiXyn/umPOMjC61nDIIeR/yjtjJc4pR6jEIWetuScYUi7/PznP1+5LkYbdYXByLosL7upK4x8HHY4E3i/WacHbYIsIu2atmTM06eof+53JsYd48fLJeozLJeYF5F7cSDPqFP6OjI2Oq8qijI9qGGndC1MzihkKOMo3UyKvBeNZvAeygGTNimYb3zjG+3zfJj842BCIpLBkRT5ASZlojVMfEzs4QgLn6FsAhM2SgaTtVfyUQjYOh2PKBNhEpyHCE5Www5Q0CgPG3c0G9mZ7ZBChcJGG4SjdrQRyjsHihXrNnkPQwhlLgztxnok1pzwOhpJIAKG4hzuF2EwDml/FDmUQ9LISLf8zd/8Tdv3otFdUtCIsmDgoVzFKa6AMcm5+TcKRhvrfn7jN37DKrgYG/xNGphPzQT6Looamz5wf1yzk8Gxw1qoXbt22agORivlb3QgF6j3P//zP5c/+IM/sHVMmzNOSScD5AcGETCuiEzwHgd9B+W30cH3+H6UuPeagbWUyAgiTuFr0d7eWOA9+hf9no05uJew8k1f/J3f+R0rH+kT0f4+XWC4UWbGFLLTO1ron5SZvh2FNiH7ge8zttPg/rhX2ty3JfjrEqFibB06dMg6xzgfYyV8XcYJa+Iw+DB2koxgykMd89u48cr8gjH95je/2X6OvKB8yBWM2KQx3k4oL/WDoxKZhqFN2ukNN9xgs1riDGsMYTaXYskAD0Hn94qizAwvMEKtmJlFUaYZFG/S0kg3wnu6adMm+5oUuPe///3uW8H3UA7e/e5324dYs+DdT95p7N69207YKE1xEGXhgb4f+9jH7ML4u+66qzL54+0kMoICjnGGtxMvJgojkz0GF2Vkm3wUZ4yxODAaSedEWWXtS5K3NAxeU9b9kFLIElqUIaUWFBEMZvoPhtuKFStsu2AMY6xjVGEs0IY+JZPXeeBcGONJqbxEUUh5Qvn2jgD6CGu4eC/OMMsC/Z1z8ftmvf30V/oPBhKKK0YD9dOpEOH5xCc+USkz956lvNQTfQEFn3qjzWkDxuYtt9xiZQTv3XrrrVZmXHfddfb5cyjdwGsMikaQFso49sY60SDkC2OVDUtaxTuZiKzgsKI/YySgaLPeEMcBMgf5hMKO4eajdZ0Ga85IhaXPUWYMDVIrGYdxZaYNMWiBscaRJtupKyKbGCyMD+oKuYw8IIXdX5c+ROombdfsWjHKRr8C6j5sSHcqpGAilzDgwnKJeYp6ipNLOLGoUwxg6ov77GR5oSizGTXslK4FIw5POgoXns8777zTTsxMLB/+8IfdtwJF4dOf/rRd1M1OhVk3gSC1h4hGkjeWyZ9rsuEAm2qEjUm8wShTLDRniOG1R4nwEzsGG0bm+vXrbTQoTgFHoSSagKf6jjvusP8C6YOsgyF1znuYw/hIFOVhPSFrzpR6qD888iheKLsoIqRh8T5tRuQDJRmlphnFjnPz+6TUMYwJ+i/XQoHi+nyXvjzTShH1gHGHI4F+3OkKKWUlbY40slbBgMeQx0CgbTD8PvKRj1jFnCgeii7/ouDSxklresPgPPDRfwwwjAiyB0gfve2226wBQYQsr/MgDOOedkMxJ0KH7GK9FH/7++A9ZB9t2qkgG6lTX2ZkI2VOktl8DznJPVHHWQxW5DHXIOODuuI3/rrA2G903dkK984ck0cuMf6Yr4jU4ZSaafmlKHMZNeyUroTUHLzTKMdEveCjH/2oTRlBIWOdjIfUKlK0mLi/8IUv2ChKnNcxL5yPKBqTIFEWNtdgIkRZxyOPgck6ljj4LV5/ts8nLTQOzsOjGDBKN2/ebNdhoLihTKIQ8pwujDrS6qKQnoqxiec7KRXQQ5n5Hgogr7OCso8H1z+0uxvBqCPy2smK7kzAuMJQoF5aUdKIFpHuiIKeFaItKIdEaDCqOwEigfQVnDzUCUZYMzKE8YVThgMDj75HmivrrDAg4hw8eUApR8GmjDORxjdTYMBiFOdZx0ifRA5TV0XMB3MZZAUOj26dBxRlNjF3JL8yqyCFDsMivJmB9xQScQnjDS3WB7SS4hYGBY3rECXAuEEhw2vJRhs8QwuPcJKnl9/yOVGgtEgISgcpLkTcUFjwLmPYoYjwHvfKeeLw3m4OJtw0+C71iaLJBhJZD75PVBNlsluhXqlPpRYfrWjV845Rl7df+Y0aMHo6BSJ0RN9xkpA23awM4XdsykL636//+q/btVQ4gIiGtGrUAVFFUgnnklEHjOE8Rh0ge4mkqlHXOkQ81ahTlM5AI3ZKV0F3ReEjWoUCw1oRz/79++16FTy3RO48H/zgB23Ui8gW6+waKfJcg4gFE3/SpE8aJuk/bLbwW7/1W/b5daRFYmix1of0HhS2uPVteDdRdknBYrMC1gTGwdqddevWWY8+a/jYIY0JFAMVrzy7uGGoxj2Pid0BKRtGJhtxFKE0NguGHwapMntAIc6rSLcLIs1+HZOiKJ0F8yjrXr2TiDmyiJTpbkPXuivThRp2SlfBpMDObnj1MfD8ZiWAt5/UL1Ixo4Ydm5y8733vs7sKNvIsYtSRyojBlCSMiQKyfm3Lli2yc+dOWbNmjZ3AUDBJ9yQ9kXLEGYZE+jAKt27dajdoSDLsDh8+bNM7MewoNxvEEKHknhm2GExMluE68JA69q53vUv+5E/+xO4uN5OGHQ8DT9qARulOSG/2KdAzDenQbFSjKErnQXbJgw8+aJ2QgLPxpptusq/nEugMijIdqGGndA2kFeLpY4MUolfRyBu7nO3Zs8dGxDBo/O54O3bssIYdxhE7YpI6mQTr1zBEWNuDYZaUTsnDY9lQAQNq+/btlV3ySHsk7ZPfJS3ix/hjBzEmN4xNjLcorKFjAiSih2FKdIR7Jw2M7fAbQcSOzVaYUEkfm8nULMpNeZTZA84GxlcnwM6PjBdFUToPlhyQeuyXHZCezRKDuUbcPK8o7UANO6VrwOgi0sUGBqxT8R5AD+vdeBYVKYp/+Id/aD2FRLOIrBFhIFLHbplJGzIQDWTNGJMO62nYICEuGgZsc86OluwCxlboPBA5Kxh/pCayK+bv/d7vxW6ewk6eRP54jhj3gmHGTps8K4hHGHBd0jExXOMMVTZDIRWTqB877qXBmj8ej8COcHk3T8G4ZpdRXV+hxIFBj6c67+Yp9Gke/t4pxuNsgWwEMhswhpFBRDtZ34ccQf6xthHHGY4p0twbbbykKIqidBa6eYrSFbCRCFEujDe2YI8adYAygoFBiiK7ZvpNQ0hFJDWSjU2I6nGuKOyqhlHHeh3SHTH+kow6zo8RhBLEuVlvlAcUV9YBokxhSMUZU3g1UYh59hW7eKLkYsyhjHlF2W+mEoXy8Tn1kSVSh2/Hn9fv2Jfl4PsY23mUdmVuwXjK26/YZZYIHEaIUizIRDZK4uHbZDXgxPLyEDnEax7fwnM4cRwpiqIo3YVG7JSOBiMFBeOb3/ymjdZhbL397W+3hp1fjE0XJr0R44SIHettNm7caNeuYaARWTp69Khd04bRxno4olgYPd7wwehDqeS8PIg1CcqCQcU6PzY/IQ2TRx1gfPHMsqxwHjZdoSw8EiEadWOzFx51wL2+6U1vsp/zDD4ieKRn4kmnzKS5sFFLGIzOv/3bv5XPfOYzNl2UrdSVmYP+idLMhjs4HuLWXTYL/Ygx0SkbmSidD7L0oYceshs44fwhaseGTIAxTTo7qXNRuaIoiqJ0Pi8cIq9LUToUomh//Md/bDcowZhCkSVNEgPMK8gYf6yLYx0dnmg80nj8UagvuOACmy5IuhGbjxA9YIMVUsQwFEnbJO0RAxDlBoMpTfHmocL333+/3ZUTQxDjkkgiinWeB4HjOccAo4wo+5QvDDticu+ke1J+DFDKxXVOnjxpf4txyjWjUTkMPtYAkq7Ks8DyGJxK8dA/iULt27cvNoW4FdgJFqNRd1xTsoJjinXIPMKB53uScskD+gG5RFYE2QF5MxEURVGUmUcjdkpHw7oP0hJJ+SMqR+QK44tURh+xQxkhhYiIHQYP38NYYo0cB98FFGA2NkGpAQwlb8RhPBH9Skq/9PB70jwxMInA8MgFDCcMw6S1e3GQvvj4449bQ/Rnf/Zn5brrrnOfBGCAksaGwkUZuVfKzX3iVcfAo8z+3sJgAH/1q1+1u2JiSMzkjpiK2HQ30tt4YDyOhiKja6y5xKnBRj1EdhWlEUTs6DesC37nO99pMxuQPziX2G0YlQCHkRp2ynSBs5KdrJFlOB5++Zd/2WazML96mNdZH4ozi/mNJRmvfe1r7XKFPE7VImEexwFL2dlIDYfI7bffbuWx108UZbpRw05RZgCGHY89+PjHP243g1m7dm0hCj8GJxMf0UgexYBRpxPMzEG6G4o0TgBS3tKiwc2Akc9mF0QEibzwzMKir6FMD2Qc0FdoPxxSyIO0NbI4qnjkC+uDcYD5NcWMd5w+KMfRdEqcRawNpt/QXz72sY/ZzAPSyVGS6UtshsT1i3QIcT2uww65PN9zroA8JvuCNdJJkXraBOMg3Jakz/ObuQKOWzYkY6MzllJgrLFU4fWvf737RmBE4VjFqKPf4igje4flFfTXmcBn3vzlX/6lXSqBc3jv3r067yoziqZiKsoMgNBHcSMyhyeS1zzKoFXYHIbJj8dB/NzP/ZxOLjPMX//1X9uIMwoKEd2i2wMjgIPUY9aR8hgCv6240l382Z/9mTXuUFwx2sg6wCBC0Y87cBZgCJCpgGKMcYBDhywA+gKGG49sCWch4GggNZg1wRgaZECwcy7voSCThoncQEEtkr//+7+3KeL0Va49VyDLgrR4DDyyK6L1iuwnlR+5zRxAe7I0gHnBZ4HMBRlOveDgxMjF4YmxRH2En5WJk4MxwU65yNS3vvWtbemreaBtuD7lxXGBQ4VdrnXeVWYSNewUZQZhbRSTAooP3nWUsGYmBR8BxOPO5MczczQFc2ZB8SYFE+W8nZM9G2CgCOI1JvKCApkW6VE6E5RCFFtS0ZYtWybvfve77fMxr7zySqvgRg+iFawb5uH/jHfWzJFOSao4BgKGGqnY4ZRK0r+RMaR400dwJvGoEyJppL1hMF5yySWxKd7NgFyiLKSHY9TNtXRh6pr0PJ5JyvinvsOGNu3NDqQYKjyehl2WMRBI38ZYJ3o6F8YyjgyMYOQYhhupwsjPN77xjTVzIoYw/Zt+xZKMItcrtwKyF4cqc3ieRx8pSjvQ2V9RZhCULjZt+emf/mlrBPj1f3khTeWv/uqvrOJACs9MejGVAFKwaN/pSKlCGSI6g5KO4qN0H8iB1atX2/VC7Gj7la98xSr+WWCdL4rub/zGb9jI3wc+8AHbDzDkGoHhyO9RTosGucSGUxiNfufNuQTGLMYH0VPSpYmkhiH9kvVl7GLsV8Wwdgy5gXHj35vtsHaciDMbguHMwCFBJJPnsdKHPHyPzdGI1OEI6RRYmwqsl1eUmUYNO0WZQfBEkjbJuhMUurA3Nw8oEHjaWWNVREqn0joYWXiip2NhPylbRGjUsOteiMzwmAHW2+KY2bFjh3UOEKXIAr8nDZeIPRtPYOhF5QmGRPR8RPpIySRlEMW0yEg/a5BQzrkfDJZuBQMLo5n2yXps27bN/hYZT4o0KbNsDhKG9EPaavPmzZXIHMYL1yNltV1R/k7DG3bIMJyc/Evf4bEcZDx4+B5rRJnjiooqFwHGJm1FdFZRZhpNxVSUGQZljEmKnbTwnDc7mfN7FLS5mILJ5I9HnEkf5QnjBoMZUGZ5JiBrV1CWogoBKaxER/CckwbH3yi/nJO6ROEinYwd2dj5jHQ1vMikTPHoDNa38TnfDT9aYnh42CopbAQQVbBJM6K8eKU5J21O1M2DBxilnnSsLMoC56dMu3fvlje84Q12902l+6D/EOGhL7E+k75Iv8jjHKAvYdz5dbtENjgPSjKPeUHe0C/9OOBfUuAYJ6QD8tsi0v9YV0aKOecmtZQoTLdCnSIPaAecZ1kOokrUM1DHpFwiJ2hPv3aOtqC9/d+0Ae3E90ixZRMV3p/tIEOReTg4qSv6K4Ye/YcdWxkX9Em+xzpQ+lOzTtAiQeaydpS1sWRM0GaUi9Ra1rMyZ9CW6mxVphM17BSlA2DSQhFrdhLndyiDRO7mGkTFUARQnIBnDGI09ff3WyWByfdP/uRP7OekRIUNKIwzIgooFd6wJv2NNS484xBllGgDBhYRDT7DQETBQAnjuryPx5b0KTzwHh4yz5oLvPVhKA/ee4xQ2gulAGUApdEb5TyInjLwN0oisMEFxCnd/B6D8+6775Y3v/nNc2qDitkG/ZB+h6OBzVDo3xgI4X6bBQw61l/SXzBKOB9ygr6BweANO/ogBgaOEPpaEUYdsOaItFAyCRgHOJ26Gda/MZazHt6o87COETnCmuqkja3YGRLDhfZfuXJlRxgv0wH1Quop9UJfRA7jZGMjINassXaU/orDDplNP+V7Mw1zAFkSpNhibOLE8+tkOXDaYaDyvqJMF5qKqShKV8PkymSKwYQyxeSPUeZTElEIUFpZ50OkzENEgbUtf/qnf2oV3auuuspuSoHC8Od//uf2QfQoYax7xGjCs07aGrsIMplzXqJjGFxM3nhmgTQqIn4oJ95QC0MZSClCoUbhxeOLMsd7HhQ8jMbwg+tRfFAWuM84uC4KPJ/PlbU5sxH6DFHa9evXWyOMKBvbwNMf/CMNsoCjyDt7MPJ4/AHnZA0TBl8YjBaeZ1ckjD+cLNwLTo8o9FXuCScHjhHvuAD6sFfiw2N2pvFlRi4w5vnbgwFOmXEqIVuikIqKzCDKHx2f3C9jm8wBIj+00Vxx0nHv9GvvaADkMbKR/svGM9QNMpXv4eAoyvnQKrQ/GSI8boFyMQ/RLyg3Y5c+wd+KMp2oYacoSleDMoWihZHFv0QKMKrCHnOUhMsuu6zGUCIihqcVJRelN/wwXKImeN1JSyPSh0eZNUuklXE9UoZ47hff47zvete7KptDoKCi3GEgxhl2lA/FjnOQrkOZuXY4fZIUTQxJ1pp4SO0kkofyEAfKDuXF0M26LkvpTIjU0L/o0zgW9u3bZ/tqN7Ur5SYVjb7NOInCWCLdmKge69EYYx6cJKQkss6QqGWnQIrd3/3d39kNYe688077twfHDIbsRz/60bq1dIA8YkzzaIOoYceY3rNnj3UcsbMthjjGzFxw0NDW/nEbYWMW445dQen71DMGErLSR/U6AW/YIXdpK+Q2TkDuhagrqZm/+qu/6r6tKNODGnaKonQ1pD+SdgmkvqA8sZ17GLzBrGMJG3bsQorRhgEXTotCwSSKhsHmN33AqMNwwttOahm7t3FOFFaUMSZyJnfAq4xXH29tHEz4fJ9IBOuo8ND71EkUd8qUZOxxzrjoB1A+0t06RelRWufXfu3X7Lo3nAmsmohGtjoZlHT6Y1x0hb6P4cLnjCVS7tjB00e96f9EavwY6wQoMynYyAQcRZSZB8rTNkCqJUYqRjnfiYO2i0YgkTekgiNjOC/jHqMXWTYXDDv6NHVImnzYsCPLgnRUZCJ9A7mI0cR6tSwRO36HM2Tr1q3y27/925kPNrJ58MEHMzlRiDaSbUHZcObhyMNhx7/0W9qT+1KU6UQNO0VRupqwIoUyhAGHVzcMhhvf8xE0FAmfIhOeePGck/5F1AuDDWMN5ZOoHu9h2LEWDoML5YIDQxIF1Csl/IvxxaTPEYXvcpCuhWHHehG/OQbXIJKIcofBiiJIWilrBFF6UR5QJOJACUQZ4R7nytqc2Q6OCFIkOVjb+Ud/9Ed2rVyngwKOc4OxEVXCcXww9hhTpK8xFonI+HEEjA3GAU4Q78jgd0QB+XcmQC4gC2gTysxYRD6QHQCUjWgeBknSekjqAseLvw/qiLRuon/33nuv3HrrrTI4OCif+MQnrBE5Fww76oD6oC7DDjZkoF8TjYGGcYd8jMuCiIN6Rk6TYs9zRLMePBuS3WEbOcgoNxFp/i2VSrZv8BxZZDX3Q1tj3HmHn6JMF2rYKYoyayC1EUWQKIAHJQzlC0XBg3cd5RFlEqPKKxR4j/GgY1ShFPBblAk+J9WKtDAieOFNUqJg2GFckqYTXoMThsgbCgHKChE7v4MnCjHpaaxL8jupcQ7St/hOmrfaG3ZcP+z5VrobvP48345+goKLwt/p0I8ZLyjhYWUd+BsDjr5M32bM0t9Zp8S6QH7LPWLsEdn2hh1OF1KRiWYljSvgMwxHImr79+/PfLB2lkh9EpSNcc/YJcLmy8y9ICMoM8YeKZeM/zh8JIdximFHXWAQcJ8cvPZ1Q7tH6242Qn3GRaGp797eXps5QUQsrW3iQAbye1KaWbOY9eDB/7RFIxnK3MB8QB9gbTbPK+U+SNPF+UI/Jjrro9CKMl2oYacoyqwBgw3FKZyuyKYjeE1RxDwYR0zcfNdvJIGCQTSMCdsrVSidbO7AJM3aOJRL0iaTFDfwnlrwGwNE4T3OScoZEQAUOq5P+YkKesOOSCQGJgohu66hdMQ9BNcrR3xfjbrZBX2JPofiyCYn9JVmoZ+0GvHCgUBfY5ygbDMuovAdrsP1ojCuMH5YR4YBxpgjIukjG4w3zotiT9/30XgMvZ07d1rnS1wk3INhx3fZ7ZaIeNaDcce5k8Chg6wgcsdOuBgB3AMgF1DmGaeM26QoDbKB7xANoh74Hvd+zz331By33XabXWuX5MSZLeBcoy8lySza/hd/8RetkwAjqZW+XzT0fx7HQFQRmUyGB2mYGPj0X6J29AscEYoynahhpyjKrMGnz6D4oVRyoDyiRHkDDkjxQmkkkue/SwSNiZq1P3zOexheTNBE8VBAWbtHalCWVEe8+z7tKgq/R6njXzz0KHBcH4WAqAyGnY8KYgCS4sVmAiiNcXglgvJ5RViZHeDxp+/RNz7wgQ/UpRnnAUUaBbmVFD/GC0otu3Vu377driuLQt/GuUKfTjMkMaRYO0oKnFfaGX+MWSI1jE/K6scnjhai7D79MQ6ujZLNmsSPfexjmY/3v//9cuWVV7qzJENUjnL80i/9UkWmeGXeb7iUBEYM45l7mMsOGNqUfkQmAu2NHIzrJ8gyotXIPQ5kYKeAE45IIhu8+NRb5hkMd8rNawxSxoqiTCdq2CmKMmu4+eabrRL4hS98Qf7qr/7KPpic9Q/hHTI97IRJyg3PfiNtC0WVqNgb3/hG62Vli3nS3zCyMJw42KXQe+kbgWKKsoLCFwcpPKyp4ZELPPOOslIOyk90wEcdSdsiQkBkLxyJDEOUA+WfiF7YgFW6H/ol6bkYKkntnxUe4cHjPcI7UOYFA4vykH6IkcK/UVBuibih2NKf4/ARa4xNHBJ8H4gAYthhJBGtZCySgrl3716r3JMyiTE4E/gyc19souQNTAw7MgMwKNWx0hicUDgFiEx+5CMfsX2SCGs0EovDC0OZdXKkVHaSYUdZMdSRud6wY555xzveYdfe0U+hFUeMojSDGnaKoswaXv/611sPLw+EJW0Now5l0CuNYVDM3vSmN1ljjdfsrEm6G++xRTVpNaTAoVyyvo3zvu1tb0vcGCEKhh2KIJufxIGB+Na3vtWmdOH15VqUk6gBRhzRPpQHDDsfpUB5JKoYBa833m+UjPBaQqW7OXjwoHUM0C95nAYGUysQYfAblTQLhgtjhbWp9Mm4SIuPXGCIkhoZVdiBKI1PNSS1mQgWBhMOinDEDkcF5UXB92uZ0lKh2wll9pE2ysAYxdClzIxNjNEkw47vEalCllA/cxnqiBTUW265Re644w759V//detki0s9pb7f8pa3WJlO/XcKzC84Wyi3n1+Ya3jEARuwYNBhiPq0fEWZLtSwUxRl1sDEyvo4DtIp2UQlzqgDDCsict6A4yD9kWgZkTt+61OmUC4x/sJe+kYw4ROtiNvsAWWdh6CjyLDNOedFaUHpRokhmgcogJQfJZooC9GMaIQE4xEPOIoj96OKRPdDJIA1X0RqMSCuuOIKa9jEKb5JEGEmGsZBH2T3Rf5tdd0P/ZEoNuVKMzQpL8ot0Sz6ZhSMIiIcROt4ID+7fnLPOCjo4xiypCljBHDfGEUYdnx/ptZaUWbkCoYtZWbnTl9mUlxZb5U0/qhzDFz/vMu5DO2KjGX9HJkTOKRIjU/q37Q5G6F0Esw1ZHcwR/hyMzfQP5h/kNlZszsUpUjUsFMURWkDTOpeWWFNTnhdE6k6pJYRaUOJR/nF60/EAk+2j7phVKJAE4kkMoKy7HfQ9LCZA+uwMA69Eqx0LzgBMAL+8i//0vYDIlTNpKDRn0hZJOKLMfelL33JOgpQPulvgKGBM4GNPxod9LG09XJRKDvRZ/q6v14UDD8iHHyHsmIgUVb6OIeP0ODUoJ8Tgc/qWGkXGHXXXXedjX5SZiLolI/y0k5Jxi51iLFNuuZcj9gpitI+XjhELFlRFEUpHLy6KHNES1DQ8fij1KFMY9Tx8Gne44G4KH6kZZKCFk45IgKAMsjOa3itMe48GIWs5SAiwsOsUXpVaexeMP7pF+zSSB/ByPcP388Kxhd9jnVLRJHoOzgZ2KKfNGK/Xolr8TnrOjH62Lo97cBQ8xsH8VucEKwP5dykyUWhX/MZkWmiGBzhvkmkGUcEDgn6PFEOH5HmnolSAtdineE3vvENu4bWG5cz4cCgbIzHcJkx6qhv3qMe4sYfZWaM8z2MwqQsAkVRlFZR166iKEqbIIWTtRgoqhhg7KQGpFqS8snzsz772c9ahY/tzVeuXFlZw5MFDEYUTRRKlGQ16robjCUiQBharDvCcMgDETiiY7fffrtd8+VTwUgJ/uY3v2nXvJFyDPQVnASkw2EwNTpIMySFLisYL0SsiUByX0QOwwwPD9sNNMJrUL/yla/Y77LO1YMxxZhgzGAgPfzww/K9733PfTq97N69W37/93/fRhY9GJ1sXkQ9Jo0/2oS2IYWUcaooitIu1LBTFEVpEyikRNmI1hG985E41iixGQubppCuRqolinNepY9z+/WEmoLZ3WDA/M3f/I3dHfCd73ynbdNGm6UQzcIpQLQXg4dt+2+44Qa7oyt9g/WbgGFHxI71QOGH69NnMO4w+BodGHV5HAd8lwgya0aJQrKTZhiMNAwdxgLl+/znP2+dFEQTvfEJ1AFlpgysa6MceQzMIqGc1KEvH/VMZJK1f7RXEkRgSdOcC8+mUxRlZnmBmRiaf6CNoiiK0hAUQtYoociiCBYF0Q0U35lSdJXiQPnfs2ePjWCxKQMRryyGFJEwtuD3a+WIJmF88KDrN7/5zbZv8DkG1vve9z6bQki/YXMgfsv6NiJOjeD73jmBUcaatw996EPWoOGxHXH4lE0iy4wB1sgRqQZSRUkhZp0dRi2plnzG32HDDthsiHWqGEeMIdadJm1S0k54JAl1haOGumPzFNbWUWZ/X2EwulmLR5sStSd6H06zVhRFKRo17BRFURRlhuEZc6RgYqC1AsYga+He/e53WyMOgwpj5D3veY+sWbPGGiKsrWOtHevcSCXkQeGNYK2e35Kehy6zOQsRQowwzk3aJ0ZkXESK1Eke7I1Tg0cCAOv2eI/yYdhRZtap8aiPTgWjmbrCsMVoo8xEzDF44yD1GoMdoxgD2KfGKoqitAs17BRFURRlFoMBd9ddd9mURtIzMTLYjKcZMOoee+wxu80/G6Ng1PBQZozItF0hiVjz6AUMy7kCUT0im9SLbpiiKMp0oIadoiiKoiiKoihKl6OreBVFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17BRFURRFURRFUbocNewURVEURVEURVG6HDXsFEVRFEVRFEVRuhw17JSupPzIThnafkjK7u/CeOqQbNu8Uw4/5f5WFEVRFEfb5p5ZxZSMfXqTbL3/mJx17yiKMj284EcG91pRuoLyg1vlzv0iq+64XVZd4N4skPKBrTL0oMjAbe05/6zj+wdl6x0jctr96Vn0lu1y+xsWuL8czx2RnTfvkWPuzzCLrrtTbn/TQveXoihKZ9HuuWdWcXZMhu8YlpP9g7LlXSWZ796eGc7Iwa2bZCQ6SV20RrbftlJqZ6kpObJzveyJnaQG5M7bV8nMzVLHZPfNu+X4/B8zr/9ZfvjMWTnvmtvlzjcvCj5WFMMLhwzutaJ0PFPf2i1Dn3lCfmbtFnnHJfPcu8Xykz/7avlXJz8vn3/wSfk3r3u19LbnMrOHF71MXn3V1fKGa/pl6huPynd/GLw9+T9Efu4/XiLnBX8G/FivXHrl1XLZxWflH/7utPzgnIWy/O0b5Ld/7Tr5D0teIvNe6L431xkblnVDfyhP/ptflFf3uveUFijLwc3vkz84/EJ59dU/Iz/p3p0Z2l+W8oEhed9HDssLL7tKfubF7k2lJaZj7plVzOuVV//Mc/LlP/28/N05r5b/8LMzOermy8tedaVcvfIa6f/nMXn0uy6O+Oz3maTkkppJ6oXSe6n57mUXy9n/+ndy+gciC69YKxvWvUOuu3KJvGRGJ6mXyqWve428ZvEP5G++/A/CVLvk6rfLqy8MPu0MOknWdjvN1eU0pWJSuHWybvNB86pFUHjWrZPhMfd304zJsDnPuvtaPlF3UFi9zSDPHZM9nx6VsxetkXe+pp3+v/my4h1rZNEPxmTPZ8dkyr2bxth9pi/Rn+KOGe1jbuzFlSvhyN1Hzpkn8xcskAXnPi1nnja1N9+1zdNH5JE6r2fw3UWlS6XH/NX7C+vlhtf1yULz3vyMuhJK67p1Q3JwIv7v5mifPAj6xrC5QqfQujyurfMC687KqVBbNpRbyfdi672IOaeG2TRvNLiXwuaMAuf/mWLa5p5ZRt8aud7U1+n9u9Ll8zToJ/NebOaoBS+Sp//nGSYpF0E8I0e+VB+amzfffHdRSS7FYOoZkPXvWiF9LzXvZZ2k2oi9jx8+K5P2r0Wy+CL7oj10oN6YeT51ZU88CpfhgTwdOuClXLa5oh3zVGupmBMHZWjzSLVAywZl140l90cYBPuQjMiADG1ZJS05oGks08tKg7tkMO5SDhSPof0iA1uGZBUaZB1UuukciWWOkv37NNTw0ZIM7hqU+m+687i/spB2r8G13B+WhOtmrLdO5vQXN8nWh87Kig07ZG2/e7ONHPv0LbLza/Nl5e13ypqkTAdXr4n1HmrvPHUf9N8cQ91MPvFjq8Cx14hv7ZZ1nyjLwFsXy6HPHQnWVrzyBrnn3cuNORdhfJ9s3PaYXH7rdlnT597LSHRsNxrrcXVZ3xZ55EGWMVztD0XLg9i+VumHSYR/k6FP1Jyvt65ua+s8T901wF53onq9hnIr+V5svT/p3882Dhr1JXPWXPca1/ca0Xut+c3qmjvJ1EfCv2t8H9DgXhrWfVamUQa1iemee2YVzxySrR/YJ6eT5gIorK814pjsvmmnlH/heln88F45wiR1Tr/c8NENsvzc4BtVxmXfB7bJY8tule1vyTlJtZnjn71FdnzFFH7+Crllx1pZ6t7PQr3OWE+lHRq0SyHyLWpH1FE7/6TPp4bQ+ZL7U1WmFtfngnNOVO4v21xRO09FaU52Nh+xo8FN5Ym5iV27dpljSAae5L2clifnCVvRdUfjCa0boXMH9ZZypPY2Oo3rEKHfDF07Yd+veg1mCc+NygMPnxF5yQp57TRNrP2vWyEL5Iwc2j8aH7VDgKD8MnCThIxVqI3gWEZXz9uXg9/W9Im6w4y7RMVtehk/cdy0z1JZevXVsuJ89+a3HpLDz7jXISa/d1Imz7lYLn6Ze8PBRBEvB8yR28MWjJGh/T219bhlQCaGmzmfJ71daOvsxJ9r6NpAhMfLiZi+VqIPRr8X+m7PYhshzYSdzDGu3Dm2LJfRzQXI4RRZzzCajfSuTmu/hLavMeog+j33eyt30n7XRpB9pt1m3TwTxwzMPbOKl1wlV1Nv3xqpX+M23Ywfl+PPL5ClrzBleq1bKff8MXnoK0H8q4bJU3LSzF0Xv7yzjDqU/RMnXCppn5lDg1eZKd0YliWRI6eFU4h861lVo8NWD6/b9EhvDh1nbD9GHcZgmsFG2YLzjz2QxWYJdIm4uau1yF9Zyk+afyZOSUsJRxGaNOyMFfmAuRkzsVQbqVdWbTENOmEGb577TFRI8ipI08TRRoZoY29IEYzdh6JlOmfEimegUW9l07lnk640NfaYHHteZH5/v0ybmO3rl0vJ1zj2mIw9F7xVQ/mUFQilyxoLw54LaaUxeWyWKrBmFpRT3zWTo5lo+mSRXPN6H+I8LYe/VD+bn/yHcfPdpXJxRALFThTGEKP2ei/MZ8FWxkjUEGIiQeKbsdw2gyKPIRXFKM27nBe05XE8UbYTRu/yUkZvn5ftA9VIj6mvgWVjMlKQEo+HNNrGefSJWuN/SEa4QTPvYGj49zvZ4Aj6pX3VXJ26Ns1LvdPElaNuTivAiJ9FzMjcM6uYJ5f2U3NnZGx0Zi27sENx0euvMjNVwOkvPVS3+ZecPC7jpsWX5rWc2s3kCTn+/eDlopcviY+AtkSvLM42WcTSsnyrMCGnEHTLLq+dvxsQ6Fo5yGNURZxp9mgpS8Xdo/m33IxQT6A5w27MGG+mEPUKbUkGru2VMbzhNROFm3xz4SzZVhSkdhDXsJGj/QapMRAwHhM6fNAus8uIOPatIA9+yZI8SQetslSWLjH/PH9MvvHt4J0aehdbZXns640reuJJBFxrArOjef64HP+OsdV+JpgFF7zuGul30uXM0ccik+a4nDR23cIlSyK7kaXTc0GeynPyI2lSKAXvZ2m7fLjrNovLhCib0gUGqYvMN1VMY6TdG5xrIC6aEzKGKobQxJiMxsh2Jsvy6Jg518wT7yWuPaY1epUZ0moCx59NRzJzZXm/MbZyZrmUj44G3z86Elq3VOtRjkuPylJvwRFxhMxxZmbumV0sMHVHfOzMtx6fURly/ETIofiSq+SaVwbvy9NGX4pYduPfOSny0qWyJM8kNR1YgxPmy+KXFbs/Z/mpVqyLYuSbJzAQe41NESeNQvIuEjHrXb1OBnrKMkJZEudNfo9dQmRvBuXd2GOmJFCW0aMptRQ3V6fQlGEXNH5JLo+pjd4LMMOCMGh1omgiXcwpGNk9zUphTB6TvVvWB4Nm/ZDsPebC/vDUQdm63rx/07b6FLupMzJ6/zbZdLMbcDdvk30nynL6K/tk36NnQumMZ2X8i1tlPd+5ab0M8aybqdNy+L4hWX9T6D33bSOO5fEn+DdtofCUnH54p2ykbOvWyy3b98l4qNiWp0dl7/atsvOR7GKm76LAp3fyO4EorSEU+Un2cjvF3Ai70mDaepc2E4lopB1NRTtOHJcTZupe6mfBc5fL1VckbKLyfWMEPjNflvxMtpEdKLJ5jWLvCWszLr2wOoG46xpDKHNxXVqbrX9OVEntDVJZgjRe3z7ZN4kZM+PJOuAGEyYu1mU6GV0xhGwUur6urVyfGJWx6ajTzNQaM50aaWINhW+7QJEI6tsaWkSjw2OzYVrPmIxgtC2jdxjl5V6vNAV9xc+5PpU3kbq02M6su6lnjsuhT22Toff6+egWGdp5SE7X5cZPyeQTh2T4rluCecV9d+unR+VM6LtTpw/Jzg+4c23cUfO80rNju2Uj889798jx592bWeae5yfl2P3VuWvTfUfkTOX3AWe/Q9m21s6lLdGe+a5tXHCx9KFtTpyU8bjsF0d9UCDpaKa/mnnnRNihOE+WX7kiYROVM+a7kzLffDfXtDMNWIPTsiRwPAO616e3yi1WN9sou8ey9DMnP0MyJ3BA50x9LFS+BZBdEBiI6xJ0ppC8q4uYkT0YfHb5133Zosdjcrn9/QzqZEZy2+wYMw8POiM40RCNm6tTaMqwCxo/jbKcalGWeK9kPi+9pyxjo/w6ZAWHlSd7NDmRdUQqpjGqiQoe9dZ+LUEUIt7wbsjzx2XPlp1y8pL3yI7Nq2ThVFkO795nRGLA+GE3qT4/Ll81xlqFpw7Ljg9skt1fm5LSu7ebDniP3PkLIofuHpKtnz0kh/70oHhxJE/sk50PnyfXb79dVi2ckvKXd8r7b9kqI1MrZeiuW2VgyYvMe7tln51QDZMTUrZyaqH0vtS+U0f5wW2y9UGR68irXjZlJ9LdD9a64Ma+uFsOf+e0HDuRPR1kYU/gEZucKMevs3OpxIPLokqmP0w/c1HenOnrBVEVclmPZqIdZ757Ss7OXyJLQs926jfKZzBpnpUjX66uU5wyE9Np6ZOLM+U1ubHcs1xKuQRw+hjxnrIsabS58KmPdWmj1f4RNpztpBha6G3bIDJRVdZE2A4UeCLTJ8iqMwHPaSH9zkWnOwYrz4fFzO7Vvjso5r5b2R214HnD/dbOB5WJOaJIVNaXOOennV+S7gGPONc3Ss2NgzJIw6I0ZVSWPLbPhddQmsOvzW4uMtwOMFx2yG237ZB94wtl1Xt32HLe+at98uyxfXL3/SElfOq0mWfeLxs/uk9O914vmz7OPZn558198vTXdsumbcb4xdB65rDcfddBuy/APb9p6m7yuOz9k8Nud8GzMvrIqEzyvR8ckSP+9A3nnik59unNsnO8X97zEdOGL52SM0f3yN7R8Gxh5tDP7JOx75m5Z/xZ915rtGu+ax/nu/o7FZ/RkLIkJ/5oIsry/XE5dTbiULzkVVJy/sezjz4io97ofO6EnDTV1tfXaXmYgcFpeflSWYoGf/aY7Pl/h+QLP7xaNvzuGim9eFJGHzZ9OfhWDpKz5CoGdzj6Vrh8gyDqZzMOapZ6NUfyesKZz0oIHK/GEL5plZRslDGo5yJkcFOGXftxXknTWQaaqv2qt76SPlTpYM02bK1HtPHR3o5TMhO7TdOKhLm9pyPRS9+A03/2GTly7kp5m5kU5506ZcRILX3XbZCr3MCd9+P/InhhBvjWD+6V4z+YLyvefbussVGbebLwmrfIypcEX6ku8p2SIw8fEbnialmxgIdsBkyZtn7/TSvkzIGdMvJERCT9wG3t+5KFtc9E8zw3Kvv2Py2ldwzKivMn5Uy00BbveRVZdFGOlRLnLQy8e2eerauLMKkLklvKwe4GpuSEUSDqFnL3x2+icnJ83DTCxbKkbheyGBIj987AMRNL0q5clTESVcbt5iDmHTNxFG5sOzlTPyFV5Uf4s3C/aViWsPIT26e88RjcL4ZiqxNjLY3rvBiq17HtFINdIB+dH0rmb1Jw9od+U/EWB9HLdAqeN8K/bbijWdgBE+dFpm0jEVjTH2xkzjkbMykERlaP2Pmh9hp4121kOGYjgXAUpSWlI+y5b5CeVT5gDJcvHJfJl5o63HKDLL9gnlHMD8rwZ4NMjrPfPxPMCc8bRXDbVtl34qwsMgbbne9aLr1Wrpj55+rVsoL55/SI7Bs1htv9e2X8kjVyw2sWysSpqLEzX65651rpt0r+fJnnFy41mnvMufc+ep4M/OYa6fvxp+VMnDY9eUIed/2q72UFjMd2zndtw9Sf9ZGa8hZj2+Ym1qF4Tn/8JirjJ2VcFsnFLy9+BVtLOIMTFrxssSzAqPv9YTl1xSbZ/q55cuAj+2Qsrg9mwsmgGFlVcTqGPytUvgUGnZfTdtOwnHpT6sZrWY4mU0aj2PRTe84kJ2DY8eojktSP28zFyttWHJRNGnaNFye2tpaofCDYMKB0XaPOEk/we6NIWY9mp6UPBVQbP+VInUUDRXHwwtBkaQ6/A2BzCutpeezoGVn0+muk75wpGTsauC3n/9yrqtvpzu+TNW9ki6sFcvFFmDyTcvgzI3IaT+dFq+S6V/Alz1l51gnxvv5Lg0W+ZlL6hjntkleac1QWARuDkLY2vXHxvzUK/EsWyKIrb5A1/lz/oxwYVefOlxfZN2qZ/Nojcuy8FXJNyVzhtDEgvse7vbJiRegZBePH5HHreV0gS5fkyEufP19+gn8L3rUoG15RTzuyKKzt5qRdM1e/kDtuE5VgRy+/5iIdI+wT14hV072T086CMeKjEZU6M+PKTlSzxeCuRJWCicTvpFmo0epSNBvXeRFUrxO/S5vzLNelu5q/ee7Uk+bz4A0zWVU9yY2WA3TqvBEoLLRtUC/hKgnWzQWGXpZdd9PSmm30Oua+w5vdtNSnKm1hjhRFkAeBf3g/smKhrHzngJ0XLOf1yVIz5yzo6Zfr336Vdbgdv//DwU6L56+Ut70pesYXyXznPBr/rw/JY98y88zVpN4F8xwsKr3KpeUZzl8hq1/DXyHlv8Hcc/zLR+RM/0pZafrW1Ogjbvv8krx2eVUSTh173K2J6q+mzrVAW+e7rPzgiAzfscmlgu4I7juVeZW2mHiqCPU5P0kOxbhNVMr/cELOssNzQobQjGENzoCLe87I7s3GqHvle+Q9dn6cL+e92Pwzb4GseMPyar/uaLyO4/QYl93UjEMy+xrihKOhcZoNP//GOgHtXF2V5bX36YxfhOyy5fW/zUE1ZJKDYB1dsDlHKXJ1vxkBHtcR+ypEg4nVMjZcCcM2N4n4NQgDpmw9ZjI3Hebeg1JqttFoiNRnbDSCBgx7KAJlM4p9lkXaszkSsB5/97p1Fsmau9zZJg/LI9/ihRESr6vd43ke7ky/Vf2xB2TkO8H7/VcFk20Fu7UwL2rXXt2wvYTsMTftFwEvkaWX2Bcyv7RWhnK2+4Krb5VdVwevxx99LJiIL1ohrw31t/ITxwLP6/xLxW7Q5Zh6ZlxOTy2SvpfWmiSpFN4n6rFCarX7w+OuSypRY8GHwGys6KWBQpdpDD51Qk6cXSClGAXCbqLyxd12Vzm7icrKhdaYz7KFdMM1YhmJrcumia9X62Vzr8NQh5e711GCMe/+aAYmQYzTnlWybktJenuySrhgAlnl/qrBplyOBan04fFj11XnW3vRXXTuvEH/HVpmzLHE9o2fU7qTSTn8F6PB+urzS3J5WEycu1TW3LZd1rg/eT7aPp7lZVi47PJgDVcNz1YiaGf/z0WyYdeO4I8njAH2NC/65erX1aq/Lzr3X5hufrH0ZckmMCx9xw43/07Jka87R+gVr5VSqCzHjrm8zpdfKpeGzjv11LhMvLhPFuXUwKd9vovjxStk8IPn2WfCjV7kdo9uApwWLUX/cRZkGqPOofjKGIei3URln+xG37GbqFwjC0+YWrU7POfg2B5Zv/OI6QnNgO51u6z0GS4JWIPTvR777B7pu+5WufVNiwKH6rn9snb7LllrP40nds6xEX/3Ogzzy2XudZTC5JuRXebfspFtWeVssTrvNGOjnLEzbxUyc1pReAxNGXZByouZCDHiaiy7YLdGuyNOjeJJmNVMlO6vRHyKFIO1KW8610HpMp3F/X7VdSUZGWYdQm9zHvoGDdGsQdbpTBol3Bpd519eO7kajn37hMgla+yuh8f/y5gTNPVpC3ZrYV7UrL2aJ/MXBN87/vfmPOBzxVvmuHz1a8FM3vfvLw8ZmVMyPu5EUE264HHZ+//ukCM/tUa237Yyu4cry+CccaZP2Zs8cVzOxDyTznKuUc762VnOvH76iDz0Z0tMv+qT62tyNuvxE1Bha8QKI3+9jn3dvYhQ5ARllX432faEDPJAcSKK7+WTl8UJCpGZaJf3jERke3WdY2fYdS4yZ9dPsomIJ5h/ZFmgJGQPuE3/vJGX7EZ7QJIzo3fZcundP1JnuINfmz2jxvv3vyqP2QiUMWBKr6pEUuI4Y4yaICttgemqMd+0DqfgZXjN6/Gjbs565eWRh1JPGiPsjCzoX5pZyawweUS+au23+VJaHnaEBjsAg02dC16a7x+Wu7fslYnXbJAd76x1nGanTfMdBsrXLpV7GvV757hdYK6Ree6MUKzTLQWXHRTvUJwnpWWmDezup2fkyMMPyBLTZn2/0mCSitK/Vu7ZlWZWtcqkMU6DSLOcb4xzI+HGH9gq6x/sldKbb5AbrnQGXgq555yxx9yLCEXKN2vUBQ7T6sO9DdYeYC1w1QmeRd/O7SzwDtKOJMUJm0KT6rS5mJn4sPSrGwG4ydEYZeuaCKPSYBWjrikvqVNYoh7+8DqEgnJoZz+T8o2/C2ajusmVrf//y1npv2y5ESJnZPy7buasS1uYksePuRntFZdWUzkrlGX8H4Lf1kx4cfz4fDNdZuCJUQk2g+qTy5eFzmjK/Lh7XEElJRRcukqmiWl+fCqOIonPpAsI7zx2Vka/ZsZ46hbSjOOqUddMSkY+zISiciGEke03DUivkZc+E7x8YFcgV5tMjc9GOddzfErXmjLSdqGNQ9K3x06iO+eN9PUk9RHlCkYhG7C7rNau4eB8jLlWo+NVUNRMWXJu7CJPnnLGWuOo/unT7pvnmLkn5qvlsbEgmiULpf+Vvucel9GjwbzTXyrVKsLPPGaMyoVy+RWhk2WceyqO0PklWR5ejjBxXI7ZtcXz3bPcAnx65uK+9HtMpV3z3dRZmXq+cdwpcNzW3lcWXjTfLm6YXho8k27e8qtlhWvos48ekbHnQ1lGHcOpipOgd8UNcutd98j23yzJ/OfKMnb/3bLXBYbnOtZZYFMhGx1FyTojayaanyFSZXle+eloLmIHhAu34CE2hdrv3mvG8g2HdJu1nEPniPPw09D2v/0j5nvSpOHoUrA6zbp3Uc7MaXOZqAqQi19WK7TZOerIOSvkltAaAosxzmq+GZpc+vv7zd+m/t69R+bfvEPWMvFVFpRnmBjcwvWzbp1bUtvZnRl5ETUcTjwuJ2xKaK9c+orqB35iWpF2ffcQclkQt3i+Q/tEDU5xTYrQtEzgkV6wLMU4t5uoHJFDNv3JtHjSFtKhcdxaf64q61noNe3XFIWMvXxltTTob/VpoTlDMHhjtxg5yWJ291aR8iUpbdUa8qFdVVOxHuNeO/7M/OfImTkxHfOGz0LJTIM07UqZ+d6u2O9ZrzaVktBPrNeectUsl6DuhnIrOnatuJ//6zDnvLbH1m9mnCF11txf4jp9Y3ScnZpnDITgm/LSXqnLYHt+XI4cCa48/4rrZcB7J+3OiLxYKItfVjuHjT98WE6/fKXcHPZkZpx7Tn3XTZhLjJEZvLJMPuGe23bOErk0tL7OrveSRWZuzGI2xtOW+S4H9plw5m7tesSnjsjwHx+S0888K4ve9mEzliL6gakFvxvmef8yZqZoix5TxT4i4CWXy+KkScptonLkIRcRi+zw3BFUlrYskP5XBD1xwWXXyIovjsmhZ87KqdOm7P0L5fSBrfLx8dfKrRuuqk87rVCQ7lKwfKuXJ7klbntJSlu1AamcZa3I8iTZG+gGXC+vk7t5ww5aDccWpchRDqObHexdldhh2hXy75p8XwzxzAX9MZn34+YfO2uEODsme754TPrfvMOlTi6UvpeZiem0+eI5tYK8/OABGbNCyE2g3zaTjSyRtX5yqzxkM8O29z29VjXlgQNn2Y640fqHSFnGv/l4cCsv6Zel5kTjDwzJvY/+o/zwWdJY5snYZzfK4+deLjdsXlOXEjr1Q+e57F3YaSKmM3Ae6aVL0hox2ETl0BcCD3viFtKtypMKzaQvNOcZy0K6jMhTVjcZu7+SCMvSIC0leG1xu4yKsEmGMVQS5GVxbREiiwzK1QxMiC1I3+mYN3LI3bq2isHuBmrvO9mApb8N2XPxAPNS/L3lmg9iyNU/ytmbtW+p9J1zRI49/49yNjr/wNlx2Xf3Njn04rWyncjaV46JPHdWfug+9pQfvD9wJC0akPe/s78atTKGY9TksDx1UO7/ksjKjZF14i3NPWfl8TFn8F1yqfSfc1aODG+WB777z/JDo4jLOVPy0LaN8tCFq+UOo4Rz3fIjO2XXX50SMe+te/dV1Y1j0ihwvstO8Ew46VliZnAjl3Y8IgtXleSHBw/KmN18YXnwtQo/DOrP6AO9/9q+MY2U5fgxc+/G6E6dpdhE5aF9QcS4JoW1M6gubQmtm7TPhOWFf1j5aXnsyGk57/WvSjHqctBIThQs32oMGGs0hj2eLtWef+liCQIwuE4ud1IGssw1uSavDLI80A16cdSZ746tzu60bHpYF4KdHIKwaMtemlLy5NwZoJS58GrMESxobfCdfP2mBZbK8mWBJ3Hs8KHgAa+Tx82EOiwnlgzKDa+pehmXvmGlLKIXPfGYjCJ1pibNxLFJhr70rCyo9C4zoT1yRGTFVZVF5dX1dbULyuNZJIutFzXhGTiOhaSNcv6JURnlwbPPT8rxL2yVbY9YcWiFNfKw77oh2X7X28SubLhoQLZ8aLts3xI/yZ1+0kyyhunaMjo1LO+cIKk7qk5L2phRciYn5cz4Edn9iaBMp799XM6Y984mZPDYTVRs/XbgFtJzhnKwy2hPSUo8FqDycOs5TMfPG63Q+vNkp51zl8uaX2Kt0KQcun+k8iDyqbNn5PjDwzL0/m3y2MK1cufNK2TBFWuCSNwzh+T+/aeNVDI8V5bRTw/Jnebv+UsG5Nb3rKo1jha8Si5/OS/OyOihY/a5dVPfPyI7PzIi8gvrZU2dmM829yxZttxGGu08iFU1dUaOfGKT7HHTXG9fn7mn+bJi0Mw1v7vSKt3zrxiU7cw9zqhj/h/53DEpPzMp5WN7Zc+X3byVQDvmu8xMjNsHos9/6ZQc/ugB6b35VrnmnHE5/oMFRneoX3hBu5QxQM7pk4unKRI2dXZSJr8/Lkc+dU+QEfHdx+X49817SZOU3UQleFm/w/PMY5c8QNjoXLhYFtuO92My/9wpOb3/03LoueVyXWRToNlAkGpv5i6bSt7IwRlkNNSnX8YcM5JtVY1gt4NWhraSi8Dij+1YGY92pCgksfRtm+SGK/tk4el9soktjW/bLSdfsUG2kNPtvmMxxvmtt62R/nOPye6N5nvrb5P7n1kht2zeLlvwOJ57Rg5uuUX2/u9VsuEtXuCfkdNBPowsNEKqsQhaKJe+gqlwUk5+L2WyM2V5z3sHpP98rmnKctNtstvIQn9+mxLqcekqvea95OtPyqnvcr2FsrS/EP9XQ7LnhyccbUm3jPD9Q3L3xo2yadseGbWPqzBi6pEdssm8t/towqRpFLarrzA9pxO3kJ4T+JRPM+HdNCiDrJFu4uHWysxSWVuY8pwjUjFb21l6Zum95nYZ+s2rpO/sIdlqt9NfJ+s/sE32jS+Wgdvuke2DK2Sh1Vx6ZdVtd9p56ocPb5X1OLZ+9075wpM9smrwTvmwMer6aiYrWCBXvftWWbNskZz9+k7ZeJM599ZDMu/a2+XW2FSnbHPPvFfeIJt+c4UxtMw8eIspx81DcujZ85xxUE2dA5+eueSS6LMPlsjlzqEK498NnIqJFDDfnfn6Xtn9qd21x8OnjRXxSP37nxt1axaN0TR+0t7D2W8dklOlt8nKnnmy4MpbZNe92+WGy2JmVL9Nf/+l5i6ngzNy6O6NsvGObbLnUVfqicOy4w7z3qfGAidAHX49eJseEdESk3L2rOlN5yyQFVeyv4HjnH5Z8+6V0vfiH8qhbetl29fOk+vfe4PRx9znswS/mRprgAe9DOzqtfFuLbuV5UlGKnN2cN+95p7ziPIX/MjgXrcRp1QUsc6nsFxsV6GZc4zTGiCeduWL15A3x9nmAk+D8t8Atl0+MbFAlphJM5NnDAPTTMBn2Hlqw4r43zw3JVPnzqv5bOrRnbL+U6wq7pe1H98gK5zAK+/fJEMH/kmu2rhdrrce3BieOyI7b94jx85fKbfftUbCSy8COrRP1OAVevdnFlrNu59mfIpH6tqkhuSVB4a8Y6/lem1QxlBqey290tsTbE5S0/98+ZuQCbV13kTdJeHSbyptWZi8L2oOKvBeI+Tpx+npRumpmpnpuLqfITLMPVNm7pln5p4wp7+4SbayZuslK+XWD62ppAGODq+T3WNLZe2OWyobdoSZOntWRvfcInvO3SC73hUyzqIUPd95aPfHXiW7BqPplFWOfWqd7Hx0kQz87jVSvn+3jP6gJDfcOSjLY+4Hxr+wUbY9PCn977pHNlwRU4NeFmWmoD4+Z8mru7Re3+nyLak81bmrJk2zZn1abbnSZWM8xehlwT1Ud/bMNleklrfJeWaaDLtOpH0TtNIOJuXQXRtl3/cWyZoP3S4rX+LetkzJ8fuHZMeXzSRaY4T534jMf90tsuMdPmI4KYe3b5S9T62QDR9ZK/3Pjsm+r8yTVdf210QjJx/ZJhs/Ny59b90ut16dHNdTZgMqD5QsaD+Ze6TNPWU5fPeHZS/PVXjlDXLPu1005fljsue9O+2Du2vnj+Oy55bQIwfGD8ueJy+Wta8Luw3HZd8HtsnJNybNO+2Z7yo0NOyC8h06d5VRroMddNf90ZiUftMox+fukU3fXi53vjWcjunumU3Xtq9tLQVUUZSGzOEh5lIjdXLuEhbIyl8iTeK0HP6S3xDbc0KOfMUniVQpH/i4neRkwQq5oZIGCiflOA9Vf/lSWWImvdE/3SdnehdHJrnT8tChcfsg1oEr1aib/ag8ULKg/WTukTL3fH9MvuofllfhrIz90W5r1M27aI2sDRtnbm3awkuWyoKp0zJy/1flvJdFwhdPfFWOPLNIXvVzSfNOO+a7HEyekpPPGOOx72K7fvHMGcqyUHovnJLRr4zJoosXB99zTD16KDBwf+E6NeoUZRrQYaZ0D68wk+Sy+XLm4QfsRFHlPDkPL+q5fbJm/RpZxCLyAzvkw/vNJPzSFbJhy9pIznm/XLO6T+aNPyR3b79Xjv/cLXXrAs5+7QE59PR8Wf7O63UyUhRFmcskzT3nLZTzmB/ON/PMry2XeVNnZPRTd8rw0bMyf8n1sukDK2tTT3teK6uWLZBnRz8tO+5+QOa95WYZWBRKTXy+LAe/eETkdWsikcEwxc93ueBZg+cskNKyYLXcwitXy4rzn5XRXdvk4Iuvl7eF1gny2ImR/ceE3UlrDFxFUdrGHE7FVLqS54/L3lt3yOHFa2XHBv/ga8PTo7Jn114Z/d5ZuzB63vl9suJNb5PVKxaFdufMyNkjsvO9e+TZN9wqt76Z3cwURVGUOU3C3HP2Owdl9ycPyrGn7cwj8y/ql5VvMoZZKeP68RBnHt4mQ49eKptuW5X+qIMi57soGdbYZWX8C5tk26M9csPtG2R5oqGqKEqRqGGndB9nx2T35t1Sfp0xvK5la+wCcec+fskNsuVdkR1AFUVRlLlLO+eeTmHqrEw+N08WvLi1uys/uFXuPCCy6rbbZVWnPexbUWYxatgp3QmTzw9FXrQg4YGzzdKu8yqKoijdj84RmZj6waRMzVsg82fZ1vuK0umoYacoiqIoiqIoitLl6LYQiqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdzgt+ZHCvFUVRFEXpcs48uFWGvvSsvOiF5o+zkzL5XL/ccM8GWT4v+FxRZh0TZSn39Eqv+1NR5ioasSucshzcvE7WbT5oXimKohTBmAyvM3LlvjH398xTPjAk69YNycEJ94bSMSx8w3vkrjtulWteilFn3njpYlmkRp3S4YzdZ2TcumEj7XIyNmx0riHZdWDuaF1N15Uy65nzhl2gnPjBkU15KmZAOQOQ68UerSlM6UpX68anrYPK79undBanPBZRxpkw2ouq22LLXki7MBmbextu6tYy3E+R52/pXFXaZgwVVL6AYvpcUYrH9Csw6fcftCFlyngUIRfztu+8+bJgwZScfcb93XdxYZGMtvVhR2Hn78DxH6Wovt3uNpkWTB0PH+2VgS2DUnJv+XofamSwlQZl6NpeKe8faV1OTByUoSzXNKTKgmnVE5qn2L7TytwR/LZS720ac3VjuwWKqbuidLwqP+b+bREKFi+cSoO7ZLAySuOhcob256jingEZ2rKqa0PuCPPho+YF97Er/j5snZjON9Ll91pPcl/x9F5r7n31NN0xQnzzSMoAZ6IZklU97s9OAsGXJvWa7juujZYNyq4bGwzeLqYyDqGQcVZgvSW17VEmO/faUpLBXSFFKI2Yc2aRzwFMhkMyEjOBjSCn3GtLp/abmPtvXtYUJBei8qdIeT95Qo5/P3jZ97LFwYsupma8JpK9XYof/0XSaJ4svv9llQXx+lq0PPnn+bGvm28b2dHsPfWuHpDS/mF5zJymFLmPhn0nr8yq1Bv3vSumzIG8HFo3klnGZNODc8j7OpldUJ/pRBrpQtN97w3Lk6cd89OiYVftOHTeXdHOazu/sUQbVGrvan7r/kjFXc/9lU6yIjKjHdzUyQgCpoEgsXVyAZ1jREbGVmVUvopgmuqtZeWvWONj+ozJmPrlHi57LL/SXTK/2+Ve15BnnMwcdiL3/0Zn4jZjJ/onjTLnHCt2Ur2vt3MMksS2bY5AsWH8hpQQL58zKbW9sorfur+mjzF5zCpk5t8Wukny/Q/JutEZUurd5M84H7L3FYzboXWnipn0TxyXcftigVx80QL7KolGim8r8rGoc5du3CXhIRGctzkFyf62DeO/XjmnfJfLY1Ejp+G8xe/iBUBwDfdHi5SPjkrZjP+BC42e0UgOe2OGsu+q/Z6tz83D0htti6wGs9OLSi0pOiW5fJnI8AMHpVyqvWa071RwY7D3wjxKjdE9qIfUewvkZcm21S45uKyx3hTVg307N6dzOf2IMvrgAfdq5P2pzM68uP4cT8Mx7PuO+7OGrH0kA9kdlfG0Vuf1tFqeZmkhFdMrqIEAim3UnlWmU5kbW1aWEfPd6U0TCAbWLnP98DFoBr4pmPQ23WhlKT/pXjZDT6+5ej4mnmo0sBjERkELHcFgpN4j7zdML2hXvSk1WIHr6jc0wSMIKnU+AwJh2nATueXocPPpFhOnJLdY8UrEddXJxHp7j450YCoTcrZ2DNsjT9qGmdBRrEuDkckK+Uwnm8B55N7LApN0tDwNvPPNUj5QTa0aG27yGkXffyEYmY1CaRSi6jhH9qIYj8lIAWuFjp84Ebw4Z6ks7QteJmEVXy+PwseWgZYVrkbn7rmglStMSDnvmG37+A8cCMF9hgwdaxC59zvCgVSWsdGy9C4vSelCUxNHH0sZX86YSTBIgzZu3hlhDUwMsxarpXSZOcHEqIxlbMfyU3yxV5Yvy9EHJ8p2zqHeGv2q9wIETllGj+YfzxNPNi8Dxu5DVhrdPGwwlQatHpdHjlpj0/dZDieswnoKR0PHjLMFwr+p9BfT93LUvpKB5g27iTEZNb27NNh4MJdu5DvNde7OY0JOWaEReJDzYwYbg4OUqpQcXzwHNoJjBGljb2ZgXNcOmvgji2e0HmfM9izObZQqSh3Wc+g8nruGZMB0qrHhdfmMOyd/GId5leB4JaJHFvd0mozCYUPkNeQEsIeRpw3kR5ggMpqgNJUuN5/47zTGyiXTdmIMkrBcGVwWlLVeMQ45nXKuISAKgIMK4ycwAjhXfuOuyPsvjDGU6DiFsiQDhawVKsv4P5wNXvZdLE0nYpZP2T7WmvGVgDt3c/hIbv4x2z3jv804GUrb9i5bbsdXkk4TGArGYL02bhC1jjViitAvehebUpblVJZmNAb+LhzgywZiozPl/ayfQnZF5JpzzpdHxxr238BwbGb8VPv3yP40SRAnX4Pf9l47YGVbmJJ5L62dpxVvIOeKlipZaN6ws0K5VxZn6q8ITfOTJ+tmfYtVFnznTD2SUgSz4gdLdTBkCTPXYCdk95KQv3tdx8RIxatdFyWzaVZGIbpJZJf7TvTYJebgO7k9e/Ue/iyLgNNxxmyRnhW7Vqi2nJWjwEWkSifh+iYWXCX9gihF1bjLZqyY89wbGIYDy8xfOZXgeCXClORCc64Mk/W04WRNOLIQECj/cdFKW4eMobYs3A88/HHOJu+8q1dCQk6nrLLMRQSJslVSfPD4Voy7ImRaq9RnQyQeMW0RGJLxGRCBl7+JSFSY58blpPv9wiVLxCdiTp44KDtvW2/Ltf4uU67n3QcJBIpp65GUOFo5dxDJNWMWvWK2jv82U2PgOmMl1sHhIpxJBlDrOMdxHv2ikjUQb3RlynKyqYFGPiXIJetQsrIrmpZHJMzIIqvjJWWiBXOdd0xVo/LZ8P27hOMnNaMlRr46gynWmExr5+mmDU6jyvwXc+RyHHc5zRt2eTwjzjBIt8zD6QsNjmbzcb2iFAojs5NSdowwcFE0G5I2Aztxe91Qql1ilCw2PN3gN2lYYWeM3wtDKR+7BqUHz1Mrip6vN9IcWqY2uhjUf6Ttcxuzc5TK5BY9WnSAeOdFKDWH6En4GtkdImFHQ1AuO/5qxrBL/3VjqnJPCX22fGBXcB5j8KxyHsjhAgyZHtKRWqHQejP4aFKdA2nMGFDmHavBBO94KrItVL/BuE3w0hY6tlsg3Je9woV8CMtBJy9JJ6p60xsbeUXff116UqMjab5KjVBknVsTOHFcjtkX82XJzwRXLz+yQzbv/Ib0vu09Mnj1IpHvHZJDLlszHtfPlgX9sBnSnLZ2LDQTpRkbDn5rDI0hl7raTCQ3Ssvjv1DqHbQ19dYyzklTqX9j4LHcIi4d0yng7YusZNEPw4SMsjqjKz2IYCFjxPYX9I7GGWexOFk0dG2weVR9O1UzLfLqcsE6LwzCdcboXJc/oyU16BLUT7P4CGQRpGZS5MUHS+wROIprlruYI69x3c00b9j1lGS57XCNBaoP4+fKY24DrXUkP3m4dATTkYLtdc3ElSnCxO/jBED2o9HAHtvv0ttqDKOqd6luHUkGJdoMZTn4QPDDsDckbTH8rCdTvRVMJcJZ7yGsehYjR5xCmcVwqgjvqjIcXSeT3SFijLabTP8LCdlEAVsRzghmM85uqi+/T8/DuWLPwwQbMghb9spV6ie/cVxsvUGguAwYFaHSZvYwcgjnEkpJlkm6srYi0ncwppyjKtuk1yul5ab8pi9GjamWU7VMO64zdVPty8kKV6VOkWumX61rpDg1un9zjoEmi90cLa7TzsC4MewC+uTiPnNFY9R9+C9eJGs/fLtcfmK3DD9yWqbcNxJJNXrDEcukqIXpMTb6GMY58VyHY53SRA7nR2WJQmWec/Obm19ncvw3T1U3qHNShORm7RG3uUO2NrG4NMzwOrHAsK13gBSpzMeSFmGqA4PXyZq8Rpk16Ezd2E4SZxTmJ9XJkzsAUY3yVbMiIhktBTgw4snWd/y6v5Yjfkb2Bmvsw3pxu+6tSwhnsbWYtdbCrphBh5PNQ7ZhKikzYZg4rWeFQdj6IGoJ15Hi8o4b4T0o3HP4PhjU9r/9NAj6Q5pXAEFS4DZ3dRiBbNMlYtIZrBEes+sVk0YD4VOJjkTuze6ClVM5qdZjPQiV2l0cg7rO21bTQoZ6KxwU+SIimQ3LHnjpe68dlOWjw413SssCxtcW9zoTTraEYVJ2WludrLEGoXO84NlMHYfJBClavn6YZPG6ZqUN9WYJopmr7ARo7q/JfmCNIbu2sXacMa6DHRmzYRWZZch1o2DX7MyHfGvS++0I5GkOcvSrIu7fyrxWHFqVtgvS/uRokEobPxazLnOIY1JOfXcyeLloscx7eKvc+aXz5PrbTPvMN3L4J18k9lnlfStl5RL7rRhMf0s1ejPO6XZsutcVzNi6l7FckgEzjkti2ib4wBLME+4PT0WXMETHgI2elILxasb/UJwukoHWxn8rtD52ArLrWUEapvl+yNlu19mR1pogu5pKmbOGcn0txuqLGRi7LzC46zZCquDGlmlLInpcoVbvyF5H04uT7+ZVfd0Ec0Cww2awpryUVnc2m24siPjX3adfVhP8VSVLvTgdE2xkt9Rkn2X8+4hruN8HdZBgUybgxmnsj2L6nh3frY+0tlCUjmdoYVdMCDpcJd3PW5v+MIK4x0yc8d6lKDnWLDTyRtVhOowL3Q+sFusV8edK8w5azIRiF9jSIWLuI/DYDMmAUeiaUSY7Gn/vpsMVcW+p3q26oxOF7+zH5/YvX1aSVdeZRk/N759GjII4NGgO0zfiFYLAcULfadRXrWe6bn1aE+s8QnRsvYWxSnbtOGtqXFtFuvY8cRG2ILJWhMJaEC3efzT6mvsITdpBFCx+HV3gDW9hB+Lnj8vx77jXpw/K7iO9Mnj7BllxfvBW7zW3yz2mPPfcagyYWA0AZQkl0yh7MVHzVqk6C3P0Dfqc+b4d47HKj9dFkuRDlXaM/+7CpWFG+5jLwkraHbPxurUYrN4UGgPuaMaow0CzjpWc+kjvaqPnub6RSa9w8q2+jBgeYT00/5E8J1Tnr6S68fpTw7pLW2fooqPNpN4Hc5wpp4+QNxlVamr8J1Id95mO6XbIzxAtGnaeaqeMHlkGYKzCbzuP+ezaOGMgj9IfmqRs6L62IzRMjfJKTGqHMOdcnbWL5hUOWY1YlyNvPVURfNpFnhx57yFFMBfkRWgGbzirkTcNjAVrV8jtt/VdGnApIHkdKVWia8xyH6HJo7fUeHvpGpwiH5VBsTvANTNGPNNSb4E3tyZdwx/TvNkQClZdGRIPV+5U2qkwNYObz9op9+z6ybhdGAOveDOZJRVOHJdg6dx8WdS3SOZPjsrOD6yXjdv3yTEXyEum6gFPjoo0TyV60oyz0Iz/XD+ZrvHfbbh7rR93PvJRWzc+nTZ13VorZNnw5MmRwMkMqY+liDPQzWtzgUBuheURfd3cd1h+oveYuohft5us52Y9cvf5FJIdZ4EuGLepkF2uw+d5y+Gc/FYuGZ2YtPlmnJd+/KPXF1kX+XA2wCw28lp8QHmng+AKBnI7JqnmCIRDFoJB4P7IgN3K1hhjtQ9aNXXgDbSMXrLK5EtZ29T5g7Qm6iLda+ProJn0ieAaRaRejMnBAz3GeHd/dhWm/e8TGbyxQQX4VEfTT6prlhCAg3LKjCGi6XkebOqxk497XYe7ZnoKcz15U+Lqzm8nplEZYn2w7X9mgvepIRnHSIWZqLdYSmaSdy/bjHW2ZBgL2dspXSZmlRVZST6fmy+aSYnJ3ZfN9c0X1xnjf/gC/xvvhGyiH4Y4891TYh90cM4SWb3R3OP/PS0j27bKwe8ckp33nCfbb1tZ2SWzlup82Q7FqzKvtOos9GMuI20d/zMMa1vlxsH6jLsUKmmYcfOic+haI6vk6sKl9pVD6Y3TTfloIGOHtvTKCHL13oNSitVN3EYsNvTYneSb3+Llot2l2NQTm4r5pReMP86bP1LmdMjQ+CAKOjA6ZFOfsy19qDqMcOo0E7FtTFb57crC5jZ59Vsf8GhmjohiznWwvEpWtXiaOAqK2HUedOLAO4MAy69YxcKE0tA7PIPeABtdHJKBJ4NyBsewTBD1zFgehIr3qHZUGlUScREMdwRpG8sz3UN4l736w0wkRXsrw5uY2H4aULtdb/X9NBqVfSwuihuCNg8UJSO46/pJdeLItTNXG8mcEpcy6DFOhq6dcB5rJpz4CTKNbqs3U5Lgfqc5wtc1uDSl2KyHBvgNJnKlqxFR2jIgE5Ux75SNluTulJz4zung5SWXSj8z/LxFsur1/cF7p0/JKf59blR2f2CT7H3CvhuaLylWc6lyyQT9rjKvFDQ3Us7Yce+PNo//ZGqXlVTGfmSuyiQTauaJ+mP4aN7HYiSkYXpcOmbNYx+MXsFjZfI8+DsfGXayrMhY8y/tauoldkfyhhuxOBloD2do5AbDwPy+TRunZZ3f2BAqGfpz7cZbgYM8py5sdV6vR4fHB3pu1k1dqPOgru2YbdUgajspy8KsgWvq4rKeTG1fq89FDnOu0WbSmzPwgh8Z3OvOwlnGPAi3mUmmPDEmY2YiKd2YPokEXsQeJ9QbWPy5vbJxuGu4vxpTRMQpSgseC4f1Kj3pf9+g3mLI55Uqog7yl7Ge1ustH0bBnJgwQqbVckNa2c1nByZypBObX9hx01wktUIh4ymFls4fqa/Yc7W/3oLvZxf+6fdaxBgwuLrIRusKcyArClK8vcfVvIzWVbWu88qbsExvh7w2ZO7Lx2XPLTvkyFmRvrdul1uvDmJzxz61TnY+al68/HrZvvEqedGjO2X9n54nGz6yVs5/0N23jYg0lmt5+nBYzmcdhw3Pn7Uu2j7+W6OMEbKfKErrfTtzm2SIOMSey/8usY8Yg9EMgJKP8vkxkatPeT0shKv32g1FXNtMxIw1+/2J2Hqov4Y7D4+HcnURfKfRWIj0DffudFOUXEzsOxVZmS7T+P3IBetkoJeU11bmmOC3BCJsW+cec2E5nIGMfTONxLrLRSt1Fk8TETsKEWN95jhMW1molLjP7eEm39RoRIrHpLenJKsaGHUzCo0Y44WpP1rpMJ0OQinunqtHvu3hZxKEfdAvff9unWBtQPvpzWWcKJ7211vs+uO4oyhtMwdMuLFlqTkKMMYKw4zR0IPtax7VY5SYYA3JoAz0lG2qV9LcUotXJpBleLDx9ja/trJlJsZl3OZhLpCLL6omXC5etCh48ePz5McmR2X3F47JomtW2ohepY+1QUkt3RhsLMb5Z6CLdjS9PdM/twVpmKZdUjbPCNbURdZ/kg3Evgc2ghhVnhkDxkAlrbjJuS9Y95g1+mjkLo/QMWUc2R8pCRsP9SzP9hiYKF4GLCvZ+0x8RvFcwWaAIcPTdVDkx6Ax6KdHV8lAQ906iDR2B97eyjenNGHYNVbGGx1ewGdWWpKOGfSWKEotbhthXrUpvK4oSpPgfbbpQL12p8dVrEHxRlkoGrHOGOpWabQKbNpk6idcb9RxPp+e5FN5ogrwNPCDs/KPZlafd9E1sqLPvWdY8PpBWbtsocz79h655dY9MrFsg7znTdMxe6rTqHNwD5w3PTV18wy7sQ9O9cjmG07RH1zm+74/TD8n+sFnzTa1TQGN20woAZ8eSnprJbXcbTwUejZfZsIywMgGzk1QoTgnraI0gV8eIOXg8RUZ6dxUzBnBTfRJIVEXGs5M7HncNdxfmUBoFmrEFp1K0KDeYtBUzKwUUW4otuyFpCC0Ib2phpbOH6mvgspaTOpGDJnKl1f2JIy7QuRgdlpOOfJKW8UA84TrI+mzSB1E7j2xvivXDGi5jxfU/4qgbX3Y0fD8Oftfc3XWnvEfpe3pdF1EcA8x6ZhZsW0kib8Pzh+jHff0Sq9RoKPyweso9c+Vc30jRwSl/hyt05l9pyh9xZB7zOWc3wrQq4upuwLrzKGGnaJkppsNu2IpRKB1kLI6XRQ7iYaYxXVZlALT1czBsTIX0L4dJpjrKmuschHMzaPLm/mtoswkatgpiqIoiqIos4zA8dVE1G7soAw9cEpqd25UlLmJGnaKoiiKoiiKoihdThObpyiKoiiKoiiKoiidhBp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiKoiiKoihdjhp2iqIoiqIoiqIoXY4adoqiKIqiKIqiKF2OGnaKoiiFU5byhHupzE0mTB9wL5Vm0DGkKIqSlzls2I3J8Lp1su6+Mfe3oiiKY+KgDBn5MHSgGdW8LAc3D8nQ5mEjZZSuZmxY1pl+MJy3Iek/9IFZPb/Qz80cuvlgGwxYHUOKoijNULhhN3afEfTr2iSMm51klY6jfGDItOWQHJyrHtnC+nI7laswc8kRYur03hEpLxuUodW97r089MqqLYNSMnU20pRhOJ0U2H9mnXw2fd7cTO+1QzJYcm85g7/hOOhZJUP86OjIrJVx5QO7ZGSiJINbVpkenxXX3xrqCEWPoU7r5+pYVhSlPbzgRwb3uhAw7IaPGmG/C6FcMAhUI01Lg7uqE60DQ2FofyORHS4XgtVMLkZ523VjekmDe3J/hMnw22zlCtEzIEO5JspQ+bL+1tVjlGi9Ni57XDu7enV/WWLKFZxbZGDLkKzqcW8mYb3fRtF2f2YjQx9MPG9vtnIlkqFvJfXlhLaJgrIZGB0oLEMyIvFtX1z/yz5emqZy71nrP6avQaSMufux7Rejsjy2DK6+Q8p6tS1qsdcdXZ57PKfj77lx/47KrTi5mdx/6u8zSt19p8jn7ISum7WvZZRniXLcE+379rwS0zcCo79x2YJ7GV0e3z+aIiSzstVzQjtG7zWDjK29XrP35suTQT4bGo6huLaPbRt33QQ5mYukfp7QD6uE73ka5KmiKHMTDLum+Ma9P7rxxhvzHbu+4X5c5am/2Bz/XX+Ef+OueW/9aeoIzrv5RwfK7o06vvGje6Pnj1Ap2/9z4EdPufeqPPWjA/9PUMbNf1H/aX7c+WKvlUZwH/f+xYEfbU69X3D3HHONuPry95+lvsF/P1of39hFPcWdu1F500m6XmNcPSTdW6Vv32u+2QyN+1bmvlymXdPusdl+E6XReTLcU4vYfrLrgC1HozaN61OWmPrK24/tuePqIaEtGn0/63Ub4s7XuG/GtKXrb/X1mtTuKf0hqU/mkM+J2HObdv0LztVo/OWTZ4l9JhZ3/9H+7tsg4zgIytGsHKnHns/c7wE7VtLPmtzvY8ZyzvsK2roZ+e3qNWuduHLV34M/T7QMDd6P6895+23S93Odp/3yVFGUuUnzqZilQdm1a1fdMbjMfiiDMZ/FeaZ6Vw/Vf88ejb15aUw8mSNKEYP38uOV27UlzsNHqoj5bLAk5f3muzOVcjX2mPXeX766V3qkLKNHk8qBx3JYxhIiMkE7tBClmjgou0x9xUUvSjcOyUBPWUbuLTJdsCxjo8HZyqNjOc7rPKXUg+lnsR5v27cpc0JEKCumD7Z8v+VT9hzlJ2dpPleFMXnsqKn6y0zfvDC9TRmbw0cTonqkwJl2bT5CEpSjd3kpMkZMX3CRmvr+bWTVxEj9eqqekiw35Rv7etM9qEolotIrvQ3GaGyKnOnTQ9f2Glk10nx/ngbKR0el3LNcSssWm7KbtkgsbLvl2ZiMmiFXuqy1aErvsuUN7iMPgcyjb5YuNHd8FNmfwNhwZf6ql3Fufm4hUmT7NO3UbP1mJWkMjY3YKGRpMNrGPoXTzDf7C6l0RVGUrqLYNXZG+RixqS4F5MVPlAVVtvfCZmaOQDljIgwLdxRCcuODI01hd0aDUeJiFf8wRmHCmM1nXBRHMMEuNkadMe5SyhEoe6a418UZqQVgDZBeWb4s7uy9Ulpu3p8YlbGC7JPK/SwzDWSU6l1Z+5s1hI1RcFOjejAKwk0D5v9NKGX2Gobw/aKYV/qeOVJTdjxGeX3AfW8Wr9WxuHZZbBrFKtNJfcU5EGTZQPNKexpO7vRcUNs7ygcCgyhe0Q/GXr2ibYwwY6S2bOCT4mWNOhTydbLcvR2Pl12Xm2/X0rt6wLxX3Lo/HFpVeZq1T6fhym6Mlt4GRvF0yTP6Y0v04HAz3eqpAurcGZv0zXSDccyuDSTdcqDR/NUUpj8/af6hnYI32kj8GCo/xShNap8eWUylF+FYUxRF6TIKNOycR9uoDiUMDDPptzTPpxoK6QRKWEkGrjW/PTpcKUdtdDAtIjghp8y8kdWo7MF7OnHKKoRRao3JtCN9PUs8gQHrowtBOeIUYqPMoQy3baL3E+30wFoZvNF2U4MbfSTC1HOGhehBOXsaRj0sTSllzhgzvzWlqjoWXCSp0v8aegwMIa90sxHPwvufGU/xv68/8oz/mghAL9Ga+Ojz2P4gajVwbbs6crxCH2QAGAMu4bKBwVevaKfJhqyUewdk8FoizBmyGJzyHy+7AoW3qOgv468qTzP26TRqomROoY+NSk2XPMsoJyxE9+P6fXF1bqOZvg862RRn+FacEO0yenPOj1lBrlvZEZHjcWOo9wKuXZZTsQIxKN/0GJ6KoiidRTGGHR5lGwEjPWrQKNsoorxthHRTu1B55biJVA+XgtJrFKFVq9e5cuTdfTHfZGyVPhs1S4J6CSlAaUds2mcCLjLkowuBFzdGIXZRiHZOdInXtjhPfEupO6ReOcWJlL3BarqdNdhRKr3R0bDPTWR7PlJC9CaNaiTBGFTOsdBMmq41yNAQbdTYRQ9J92tqJ9Ei+l9CenXKkV3PdxF23z9dtKY++uwiBbkU7nzEK/T+uilYY9R0mYgTIFBAQ/0tGrlNOMLGQa9R4kur8ynpqX22QyMZgeFSNaqTjOXpkGeNZXoYlxZqSsM4q+33zkAN17mdL+PbvXpEx7mXob5MSVFiV/ZQPRZOE3KxEUF6tSk1zoJIimjdGIKSMerN2+gYtYZ0qC3a5fxRFEXpYJo37MIKCpLVrlny+e7B+jMiKaTJ+e9lVnC917lunUuANRjdOcNC3Xr8nDIcKP2hfPtcWx271MFQtC8RM0nbCSmhrO0k8NaGogjOi1unELt1Wm2lZ5U1ZOrXGzLREg0yE23D9Md4Ak+uiyixi1ic0eDWfNo1nr7PxUTwgnS0LNEvU262vA/XbwNQTuzuiy6FF4PTpukSTcza99y48uepKDk24hfqy62s/es0nIOimubolOG66LPzxLeReIXeXTeDot/QGRSN3CYc2Y3iCNMx1ttCjPPHGct1Uam236Mz5DMajmP3BbKpfr1XAgnr02uPyLli5kQbyTIjp9bwzeCEaJWEqHbTOGdsdd7OQqBj4NAL6wN2nrgwWCPdllTtoglnQOijDxRFKYAmDTuv9Bqcoh3n6a+kPm5hrZL51f5dGaINVYV6IEHI2w1N3AQYKEBBGozdyjqsDFuCSIM3MrOuxaLs/CY56ojBYj4zll/chiHtx0U5atbSOC9uwvqkZlNnaidOf9QbFkF7D0pPzdobM9GyxXQLE23pxmp7N1rw3/i7bCrho19Rb6/DetSdMWodA+n4dMc6Y8xgy0MnzRhtq6QaorTUld9FzUz5BwYzpOV1CXUOCkNg5CVEgDNHUmrJ2o8LxaWVxqeMtYGEyGENbYx0NU2cM89FbpM2CWlOnnnHSORoKrMkGPs+0pRkjBeSjuuimeGlCUGWhB8/UZqMaiekWjd0cBq8HKw/UuQejixOjmM4SbanjaE4I7nBHNFReP2p28qtKErHUvhz7FrFP2sodjcvFG4zCcTv9JUXjEGj1NUZgvX4MtWR4beVKE5mUOozGEGuLuqMyrj33XtZyhvGl72Y+q4lOHfG59i1AxSK1Oc2ZWwHC0b+LpGbctxLoX05mZb7X8N6akSjenTjEMWuxjkU9757zxq42Q3bPP3YjvUns5Qlgq+n6Bhz7/cU1s70NZwOSXXgPidqER3rrixSIzPc95OeYxf33K8GfaKZPp3URrHvNynPAjmeZVw3rkPbzpc9FpQjrV8YgnvoydVna0lq87j3/Xt55Jchqf/GYet/It/5K4TLfLk8Zsdzg7IWPoYi5JXFSd/PdZ7s+oeiKEoeOsqw8wZUYgQsrwDuVGIVrHwkGpuesLLhJ+0GCkiUPApxXoJzNzbsGt5nI5ImzpQ2yFq29uIVIPdnI/K0bQH9rzDcmE4mrPQ1p7Tm6cfxSnicAh0hqU7t/TWrBMfRuCzx99Dg3pow7OLvtRn57O/J/RlHeBw3Kc+yG3buu3UGvsFfe1lJSkfHjHoekHbPiefKir+m+zOO8PW9zMzVDpX7ymBouO82Z2hV+29pmak/L9vTrps6hlL6aQ0p38vbb5O+n+s8atgpitIemkjFREDGpVtkP+r1uOCcVoE3gq4lZRPhGnPNxKMr89p9GqaZFMIpKO4I1pmFUn/c2rtW04GKAOWyvv2TqUmtjB5u9mQijf2cY6YmzdR+mGUDFLeGJO6eao5go6Juxadhxm7MYts3nILl1t7VvDcd+OumbLrj1n1FN5So24wFpTi2T9QeecZIlF67aZRRHMPphaY/YtyyqVTHqZE+DdMYinV9wPfv8OYjnSDPrFFHv/UbhRF5iiNmvV6mOaoqI3waZuwGSG6ZQzj1Nlh7V/te5xEYdchuu0wiZT17/h1KiwYjzLRJk+m6NZjxf7CFsa0oitKIJgy7dIUz9QHl7qjzctn1TG5ib1URz7QwnSPB894NuM0mktaY1O8m5x79UPNegeQwpokYLO7tZIWjVZwSYD3Mcf0ORUZybubTCbj7KtQR4hwUSWvmSsH60fAaopIxTGxPjl1X1DqxO/AZAmU52aCMWycIdZuxtHvzFEsgowcvrG5c5SMJuZ1moc2vKkeD6FFeAsPFVE3sLotxz8BsszwzNF4Xh6HFHGLq2j3vcjh2bMQ8GiDX5iluU5kkwyZmB9lgg6ja9wrFGdatGo7M9/TzwBFhWjPBOM60Q2lcP605GkSEDfFrcDmCcpWWZxuUyecxhxk7ox1tcCuK0u0U87iDZsEgsG66wBCc8bSwLiFQIlOe8RejEPvJPtmzbD4bS/qkAZmNaY5Bo7DM3nYOniGVnu5VeTyDUUZGEqs8a2S8scLSsXgHReKOsm4zoPDmGcYwGrDvpexYa/pxkz3ZjZ36TVsq4+eBGGN84qCM2Ah69KHg+XZXLJpotDufsdg4YpxJXlcilMkRrcBwSd59Nu5RKm2VZ4b0B4Abwg/IT+uTrT4awEUz4x44H5Bi+Br5krhZmDlv3AZb2QjGZWuGY3hzNNPXrrOtGWMcZxxDpOXG9NHqkZLZkHH+GjTlTS1DxvOonqMoSjuZWcOuIgg7J3rG+oR4BTrj4SYmUg5jP+dwHm+7DX7c5xyJ0Rwf5Uh7JlzwHL7a3eT8mhwiL/XPSLKpsEZJauaZa11BNAUupQ1IWaNOanfPy5I+mZ+GXu+GCos7IutG2tf/iqOhg8IQt6U7BguZAXjGo/3V3rfpxzVpiLlwSmvdYwvM+PG7qdac24wn6pN2imYbOKW8+hiHOYhLUU1MAW1ouBhiH+PSZnnmImFZo1KlG4M5LGr41zxUvAl8NDOtD/mHddcavkM2xdGO8aixhEN1M2Mk2ShuhC1PkamwRhew2T5HR2rbck6OIfo0crg9c46iKLObwjdPCRZu+0m3YFyEL9vi5EYgPM3E1mWLl4MNEFgrE9m4IELa9/xntdS3mf9eMfVdS3DuFjcoKbQ/FIXrV+ZVUrkq9Z+6+QPKaZZNAaaLgscLhrY3iNLuL+17/jP3pyda77n7se1XkiDDXLuEFK6ksRhct5XdED3VPhVLozpMpcB+FjMeG43zrBt9pH2vMp5qqJdnwTmyb7xjzzu6vLZefJ+LGQeVclTaw9Vt3O6amfDt3mg+TftefN+p67Mp9xVPcF5zwWxjqoIfPzFlrYznahs1HkNZ+297+3l+XLvE1XdIrrV2DUVR5iJq2HWZYTdbaKTwZaIjDTtHgtERkEW59AqQ+zMD7a2HeAUxje5VSoJ7nWjgPEknaL/R5a2cYzpop8Jb4LlnAjeGm9v90WB/PyrLW5FxHYyd61vZ7bMhWcZQTjnZkhPE0W7DTlEUpQW6y7BTZg2FGHaK0iYaRwoaYJW/pKhfJ9HlxlebacV4sb+VWay4t2r4NqJrxlAzqGGnKEp76LgHlCuKosw8rUTtjLF03y45deE6u+GC0sU0a7yY3w3fe0oW38RmUe69WUj7onY6hhRFUZpBDTtFURRFURRFUZQuZ2Z3xVQURVEURVEURVFaRg07RVEURVEURVGULkcNO0VRFEVRFEVRlC5HDTtFURRFURRFUZSuRuT/B6ZTiSaX+jm0AAAAAElFTkSuQmCC)"
      ],
      "metadata": {
        "id": "XD0ANcbKDgy9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "d-Bp0acOEn0V"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "## [편자기상관함수(Partial Autocorrelation Fucntion, PACF)]"
      ],
      "metadata": {
        "id": "dE1MS3kGDSFG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "W_umnJwlDz18"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "AwQV82NsFLcQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import statsmodels.api as sm\n",
        "fig = plt.figure(figsize=(20,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(df_train[\"y\"], lags=20, ax=ax1)   # correlation 과 신뢰구간. \n",
        "\n",
        "fig = plt.figure(figsize=(20,8))\n",
        "ax1 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(df_train[\"y\"], lags=20, ax=ax1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        },
        "id": "Y7y_RiWv-e6J",
        "outputId": "5bbb3db8-de2a-4112-ef50-1982ca5cca86"
      },
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/graphics/tsaplots.py:348: FutureWarning: The default method 'yw' can produce PACF values outside of the [-1,1] interval. After 0.13, the default will change tounadjusted Yule-Walker ('ywm'). You can use this method now by setting method='ywm'.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ACF 안정적임. 정상 시계열. q = 1\n",
        "# PACF q = 1\n"
      ],
      "metadata": {
        "id": "NPH5uhIKCB4A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Modeling, Training, Evaluate"
      ],
      "metadata": {
        "id": "8LQph8hNFtmA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from statsmodels.tsa.arima.model import ARIMA\n",
        "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
        "import itertools\n",
        "from tqdm import tqdm"
      ],
      "metadata": {
        "id": "XKNIm9HZ-NbD"
      },
      "execution_count": 170,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "- 최적의 파라미터를 찾기 위해 위에서 구한 범위에 들어가도록 grid search를 진행."
      ],
      "metadata": {
        "id": "Aut5D9-jGfGQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "p = range(0,3)\n",
        "d = range(1,2)\n",
        "q = range(0,3)\n",
        "\n",
        "pdq = list(itertools.product(p,d,q))\n",
        "\n",
        "aic = []\n",
        "params = []\n",
        "\n",
        "with tqdm(total = len(pdq)) as pg:\n",
        "    for i in pdq:\n",
        "        pg.update(1)\n",
        "        try:\n",
        "            model = ARIMA(df_train[\"y\"], order=(i))\n",
        "            model_fit = model.fit()\n",
        "            aic.append(round(model_fit.aic,2))\n",
        "            params.append((i))\n",
        "        except:\n",
        "            continue"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V1hC6a8IFpQG",
        "outputId": "7c51ae5c-8bac-4722-96ba-c0f6bde8c26f"
      },
      "execution_count": 171,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "  0%|          | 0/9 [00:00<?, ?it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            " 22%|██▏       | 2/9 [00:00<00:00, 19.62it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
            "  warn('Non-invertible starting MA parameters found.'\n",
            " 44%|████▍     | 4/9 [00:00<00:00,  8.46it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            " 67%|██████▋   | 6/9 [00:00<00:00,  7.17it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            " 78%|███████▊  | 7/9 [00:01<00:00,  5.09it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "100%|██████████| 9/9 [00:01<00:00,  5.66it/s]/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
            "  warn('Non-invertible starting MA parameters found.'\n",
            "100%|██████████| 9/9 [00:01<00:00,  4.97it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- 9개의 파라미터들에 대한 탐색 진행"
      ],
      "metadata": {
        "id": "7_dS60eKGtEp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "optimal = [(params[i],j) for i,j in enumerate(aic) if j == min(aic)]\n",
        "model_opt = ARIMA(df_train[\"y\"], order = optimal[0][0])\n",
        "model_opt_fit = model_opt.fit()\n",
        "model_opt_fit.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 511
        },
        "id": "uy_awakp9qEO",
        "outputId": "5826a72a-ceee-4709-bd96-478530c0f55d"
      },
      "execution_count": 172,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<class 'statsmodels.iolib.summary.Summary'>\n",
              "\"\"\"\n",
              "                               SARIMAX Results                                \n",
              "==============================================================================\n",
              "Dep. Variable:                      y   No. Observations:                   48\n",
              "Model:                 ARIMA(0, 1, 1)   Log Likelihood                 -32.981\n",
              "Date:                Sun, 11 Jun 2023   AIC                             69.962\n",
              "Time:                        15:35:48   BIC                             73.663\n",
              "Sample:                             0   HQIC                            71.355\n",
              "                                 - 48                                         \n",
              "Covariance Type:                  opg                                         \n",
              "==============================================================================\n",
              "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
              "------------------------------------------------------------------------------\n",
              "ma.L1         -0.9994      7.706     -0.130      0.897     -16.102      14.104\n",
              "sigma2         0.2195      1.658      0.132      0.895      -3.029       3.469\n",
              "===================================================================================\n",
              "Ljung-Box (L1) (Q):                   1.03   Jarque-Bera (JB):                 8.07\n",
              "Prob(Q):                              0.31   Prob(JB):                         0.02\n",
              "Heteroskedasticity (H):               1.01   Skew:                            -0.74\n",
              "Prob(H) (two-sided):                  0.98   Kurtosis:                         1.62\n",
              "===================================================================================\n",
              "\n",
              "Warnings:\n",
              "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
              "\"\"\""
            ],
            "text/html": [
              "<table class=\"simpletable\">\n",
              "<caption>SARIMAX Results</caption>\n",
              "<tr>\n",
              "  <th>Dep. Variable:</th>           <td>y</td>        <th>  No. Observations:  </th>   <td>48</td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Model:</th>            <td>ARIMA(0, 1, 1)</td>  <th>  Log Likelihood     </th> <td>-32.981</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Date:</th>            <td>Sun, 11 Jun 2023</td> <th>  AIC                </th> <td>69.962</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Time:</th>                <td>15:35:48</td>     <th>  BIC                </th> <td>73.663</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Sample:</th>                  <td>0</td>        <th>  HQIC               </th> <td>71.355</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th></th>                       <td> - 48</td>      <th>                     </th>    <td> </td>   \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>    <td> </td>   \n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "     <td></td>       <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>ma.L1</th>  <td>   -0.9994</td> <td>    7.706</td> <td>   -0.130</td> <td> 0.897</td> <td>  -16.102</td> <td>   14.104</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>sigma2</th> <td>    0.2195</td> <td>    1.658</td> <td>    0.132</td> <td> 0.895</td> <td>   -3.029</td> <td>    3.469</td>\n",
              "</tr>\n",
              "</table>\n",
              "<table class=\"simpletable\">\n",
              "<tr>\n",
              "  <th>Ljung-Box (L1) (Q):</th>     <td>1.03</td> <th>  Jarque-Bera (JB):  </th> <td>8.07</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(Q):</th>                <td>0.31</td> <th>  Prob(JB):          </th> <td>0.02</td> \n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Heteroskedasticity (H):</th> <td>1.01</td> <th>  Skew:              </th> <td>-0.74</td>\n",
              "</tr>\n",
              "<tr>\n",
              "  <th>Prob(H) (two-sided):</th>    <td>0.98</td> <th>  Kurtosis:          </th> <td>1.62</td> \n",
              "</tr>\n",
              "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
            ]
          },
          "metadata": {},
          "execution_count": 172
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- 탐색된 파라미터들 중 aic가 가장 낮은 모델을 최적의 모델로 선택하였다.\n",
        "- 최적의 파라미터는 (0,1,1) 이고 모델 학습의 결과는 위와 같다."
      ],
      "metadata": {
        "id": "tvLJyKiIG4hW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# model = ARIMA(df_train[\"y\"], order=optimal[0][0])\n",
        "# model_fit = model.fit()\n",
        "# forecast = model_fit.forecast(steps=24*7)  # 일주일을 예측하는 것이 아니라 하루의 마지막 수면 단계를 예측하는 것으로 하려면 어떻게 해야할까..?\n",
        "\n",
        "# plt.figure(figsize=(20,5))\n",
        "# plt.plot(range(200,744), df[\"y\"].iloc[400:])\n",
        "# plt.plot(forecast)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 924
        },
        "id": "GNP1JSk28s77",
        "outputId": "ab087d61-b287-4cb0-fe03-5c9ac4699215"
      },
      "execution_count": 173,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:471: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.10/dist-packages/statsmodels/tsa/base/tsa_model.py:834: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`.\n",
            "  return get_prediction_index(\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-173-48ad07676717>\u001b[0m in \u001b[0;36m<cell line: 6>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\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[0;32m----> 6\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m400\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m744\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"y\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m400\u001b[0m\u001b[0;34m:\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[1;32m      7\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mforecast\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2810\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0m_copy_docstring_and_deprecators\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2811\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscalex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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[0;32m-> 2812\u001b[0;31m     return gca().plot(\n\u001b[0m\u001b[1;32m   2813\u001b[0m         \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscalex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscalex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscaley\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2814\u001b[0m         **({\"data\": data} if data is not None else {}), **kwargs)\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1686\u001b[0m         \"\"\"\n\u001b[1;32m   1687\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1688\u001b[0;31m         \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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[1;32m   1689\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1690\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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[1;32m    310\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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[0;32m--> 311\u001b[0;31m             yield from self._plot_args(\n\u001b[0m\u001b[1;32m    312\u001b[0m                 this, kwargs, ambiguous_fmt_datakey=ambiguous_fmt_datakey)\n\u001b[1;32m    313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[0;34m(self, tup, kwargs, return_kwargs, ambiguous_fmt_datakey)\u001b[0m\n\u001b[1;32m    502\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    503\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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[0;32m--> 504\u001b[0;31m             raise ValueError(f\"x and y must have same first dimension, but \"\n\u001b[0m\u001b[1;32m    505\u001b[0m                              f\"have shapes {x.shape} and {y.shape}\")\n\u001b[1;32m    506\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (344,) and (45008,)"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "n_1_UaWbHBRD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "gjE8GGtitkRq"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}