chhi_gpp.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FoHsQnTVPyqM"
      },
      "source": [
        "#How to upload an image to Colab?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ryAQC-3gP0qC"
      },
      "source": [
        "# Use libraries\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "\n",
        "# Display\n",
        "from IPython.display import Image, display\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.cm as cm\n",
        "import io\n",
        "import os\n",
        "import cv2 as cv\n",
        "from PIL import Image\n",
        "import PIL\n",
        "\n",
        "# Import the necessary libraries\n",
        "from PIL import Image\n",
        "from numpy import asarray"
      ],
      "metadata": {
        "id": "lCZVSjk5iVAE"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RPVqkNhgPlv0"
      },
      "source": [
        "from google.colab import files\n",
        "from IPython.display import Image"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oXd5i9OvQN5p",
        "outputId": "bf372c55-2802-4a18-dfbb-48756af3b118",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        }
      },
      "source": [
        "uploaded = files.upload()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-4f0dcc56-11df-4f1e-b66a-8ed0293dc085\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-4f0dcc56-11df-4f1e-b66a-8ed0293dc085\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving chhi_gpp.png to chhi_gpp.png\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e3RuLhrCQbzI",
        "outputId": "82b39592-0048-41d3-c175-e9aabb18648f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "img = Image('chhi_gpp.png')\n",
        "print(type(img))"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'IPython.core.display.Image'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "im = plt.imread(\"chhi_gpp.png\")\n",
        "# fig, ax = plt.subplots()\n",
        "# im = plt.imshow(im)\n",
        "plt.matshow(im)\n",
        "plt.show()\n",
        "# resized_heat_map = cv.resize(im, dsize= (350,500))\n",
        "# plt.imshow(resized_heat_map)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "id": "eqosnbJp7hYR",
        "outputId": "27dfdef1-f8d1-4a87-85b3-e08c09638ca8"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 400x600.601 with 1 Axes>"
            ],
            "image/png": 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9G6BHYC6Ffbuca2QFTlpSauctwWoJvjnXRb4EuKeu0zkE3ON76utbn7brIRbbl/u3QP3pAbd1fNvtbQT5Zwa4LZ1Nfm4AcMflx77iK74CQFt+7LWvfe11X88qT2x8jzzyCG6++WacnJwAgLv1EJGzobXr2PnL7RQa6VioPBx77L5+26GX1RpCPGbt+CWztsseusa4vc/XIa1tZFXreR+v+UylyLjXrj+y7XiO1ZlDwG2fkQSM9U3SEpDi/ay+WbUbr70GdvJnID52UqSjShpGE9v118iBdQiSeoCKIBzzHoH76YL2su4tk+Tx4CErz4brOueYdAhUn861Yh16ptINkUpe97rX4VWvehW+8Au/EC95yUvwPd/zPXjyySfxtV/7tdd1HWsQpZRFA3vyySfxkY98BHfeeSc+8IEP4LbbbsP//b//F/fee+/R1z8WWK83jS9xvVIfd78+Xz0Q9wC+BqCHno9WjjlsMDkE3Ot5lLQlXx0C5Xj9rQaxBtxrQL12TLxnBPmRVcdninkyVr7GuOMzbTHu/rn7UWTbR5o/ISTjc8ey7oHbJJyk+UzdcZaHCNgjUB8D2ofIylonuXVsLINj0jMJ6M8k4I7v72O57g0B7q/6qq/Chz/8YXzHd3wHHn74YXz+538+3vzmN+Ouu+66ruvYg1slGlmRpVtvvRXXrl3DLbfc0p3fV4yzK9IzkcZrH3svYyOxMS+vsWTQy86HV6+x1KfXrjkOPUd5apnnQ7+38n8956/JYbEuHGLVZwH6CNLbQI9F/VvLO9GyA90CPtvXPx8N7za5JBJHAfa7VrtP6s5vHbC1k2VnMYL1GuNeA/p1gnB4VPcHlZ4OOI4d3vo1+992/DPJqM9K53LpMpvZ9Of+3Hdjmm7y7WMDHrcf7uXX9dURsJbs8GzNtm88wNn69Hj89jX6vERjWK9xr+dp+b3db00nHCWB8dnrasNdO2e94R42Tq6NINYAee3cLQA/a/vWtfrt5UwN0/K+BiYji23be4171LBHI6Rp3dEoGc9bare9xh3zk1KfL8tbznnByNc6o+WzSzmdDdjbenXsiMdzxtFQvFb73UYacVv8jOUT7Uzrxkvb3tsl7Pt6nsbnammen8Iv/uLXHTVj81x4lTydtGQrfQ+8NTzfSscM27fyEc+XbYePPW7bWYx7Hci2AXU5Ahnv0xhf+z1cffOa63lc5G41z/21ltc/pCOO20Y2PoKBAN66vHSokxgB5RBJGK936D30z9w+hWFTl39h2U37bvdYSgc98+5JgOzjVTlkSyJZe471Z1nfv9Xxbr3TrXO2AHKrzYyXGBn1+vXPGjmu/z6U1juk7XTugfvQSzwWCI+9zzEFexjYPrZ0bCPov4/gEH+vg4tV8mVlH0cKZw99nwngXivT+N7juzmUj8iCts5bY9zR02NMa0x93LeVpxHcRyBs0tgSuOUc8zapLo0YoPdAsC65jL/7fCw9YI4B7UPt66x94zvpzzumUz+7U5Tth0nbsW39RqZzDdxPF4QPXesYpnSj01n5iqB8NpuztBydrB3TbzuufPprHTrnmPLd7iyudxQVrxPfezRGxvusXfsQcJ+V1sBl/G5lNgKvfcbtttuyYAy8afB9p9zOW2Pcy87kWNDefgeHy8bq7VksfO289ZHW9jmxUzs2nZWfQ51CzOMz0Smca+CO6ZgGe0yFuN6Gf5hNHW6Yh66z9fvY49r3JeNeZ9/L80ZWfnb+tyvtoW0jIJ1VsSN7jtvW2dXTY3rbzK9Ph5j21r2Oz99yFDQCuEkkdi0zVsr1l/e383rwXQPh9VHA2Z3M2v2WzzOmQyPmQ+WpZx91vXbO2Yw65j225T/I9KySStbSMY1uWak+thdzyBAxHrfFhs9KhxqNfltsWx633Ykc6mDOZsvHnN/nce24rW2WrGgj4K4ft+5tsrZvvPdoWNrK3/W9c2A0Tp79/pcMW85vnyaRxGvaZRv4Lq/Xg/LS0L3FuNs9rpdtn/GkGx1ouyYdXd7tesfdT663ftz1gOlaGznmOk+HgX9CAffYoEZ2c1blWvayy+3jvmPSIYPGWflY+33c+dsd1zr73mLch8B4vPPZ8syh7cc9ZztmnEh16J3Z/q2OYgSFw0au5T2OG0av52E732moO1Z/LZyD+WGbHq1nJercBOP14mf0Dhk/R5/zrb+t89fT8XaiLQYe38NWua29q7NsYFv3bMfFa535CAfv+7EcZ+kTBrgPMbfxBds04DFtg/uafnb88OystMYej9Vrt8BvHZyPZcVbjXDM03rnsMUqtxhJzOtWatdOB0Hw7Aa4PSJbAwUD8cPR2mi1ro3XPsQo18EGnZ91c0NrLHFk2DE/Ecj1m3cEEXjtvj1Qj0B+eELNseRi67j2LteB+fC1Dh97TKcasxVZ+KGO/qzrPJMYMaZzD9yHKtPa721wzogBkEbmI2n0dW5ARLQWPCn6fm4Fj0orPXga2Kw1uGMDUNlvmxU3atm1O0a2m89q7RpQu459X54fr93Kdsu/fb0s5Zy8ua8/bl0mGd/rGiPbkinG68V7rOnpfco47J9u17NrLuvK8jyrA9G/vwHv0iiZtMzlfRNlpGSujeOoKk6cWZNJevmk9yZZAvkWeC/fQ1rZPsa/aX7QVofkODsX6OPn2HXX5Kh4Tt92bP+SBEQf73UWfxYxOATOIyl4uumcA3c/62tM28OnbVCRU/rKNFY8SYcrzzIvedhiIDhuG0FknCywfo7lNX7K8xjD4uEcA5oRdOR33N4aQA/mPeBjcY+Wj7WocD1ILzvKrQlRuWvUa+l4DXm89raB8uxrHXqeseGTg4lsGw2W6/UgfsZ4I3J+L22ZXJLSNExrz/7ZE4+eXccy6P96l8B43Np3+d3KZVm+KRzTl1/bV4fzcrhWPL6V3bJ92ohlrRMxL6Llfvt++PW38pXv11fvng6Qn3PgPj71ID4C2XjMMcyvsc8l+zsjCPoqOx4B5/A15J55ce8ecG1blCga4EYgjh1au0a/vTVy1kYVz+nvsfZ862Xe5zc2wK1OdmRmy/2LTXrs2TP3rmdovJ7yIt/2jtY6hpVchv0NnNsnD/U3SiUZxrYjaI9ySxsdGYhvg/cSuI/3316OaPvnk2PG95tDOzCwb8C5BOvYTiKDj9srerA/O5rfdhrzsp22GPgzIZeca+B+uo1sKRlspcgG1uNISy9tFuzta7YG0669rqEljEPhLaDfPi8y4sgi7LiRVbTK3oP58rjW6OM5PWD3o4tYHmNj6p8vhqDtz9kaAR1mwks5Yhz1rOXxY0/LIX9/j/EZ1u0Zo64dGSKFfW2IH0O3rscqafJLlEPWZ05uAXcf9ySe1z//VtnYtwbKfdqSOopfuz+nMettlh5HpesAvg3sfYrkqoUkGJ9xWw7Z+v2sNU6O6Zhh8rGaqqSENrw9i4n3aXw5Y6ztMVZE27cE+/Vh2DaQt2HcyIwjkJg8YqBs+wk9wPbyycgs19jztoSwdux4vUPHrqdjQb1PObxbS2ujlo/lXj3jHOvS+ogtdrI0bLP6aKM+0+LlU0A7SiXogLqV95bGvc24x2PWnn9LKhqfMYJy/+xjO9sC6wiePeg3ZlwwtpH+vEMMfB3ER0NknyraextlsLZtxIW4qMdZ6RMOuJ/eMGRbU12/rg1ZgTV5YDsPx1aK3kshsqbDTPxQGoE2gsLab0lj57bs7Nb077h/6/7b2w4F3O/zdhwwH6NTL1lvBNrtAGRbjGvtmHUDKA0AEBv6kjHbZwN+YX4G4qZnC2inBWNvZb5kzjHvh8B7PG585v5+dt3whAujZD8SapJWBNfiZTlq3CNDH9/ZNkiPv2O5rh+77OCX6dD+Z8IwCXyCAfex+uWhoel2ig1qafjozz8LuNfYVTSEjeBt14xMafu6rcFbZTZWZjIK0GvYBryHZshta5hL8AVGQFgzZm6Dfx5+t23HeJxsbTvL2r+9/ewOcgni6x5K63LbunEy3ncE4Bgp0LxJxM01q1Qy+So/KU2r1x019DUwPga8x+99Wpbd2si1H72gawt9Go9bniOM/FDHQZvb2rP054/7ZXQzjtDGc84G52etVHI9YH1M4ayxqKUr0FkvaEtnN/eyWAnGa5j2PeYrd8/S2FoPCrFh2TBazo9sZO0+y/1rQ9URXLddA0cjaW/MtGfqjxmlmbUO4XA6NEQ/Xjp5eql/F0tPBAHRNT/utr8B0JpXQzQw2vFieIwA3Twk0Eko8Xp65+4+ZwF3/5kX5239tmdbpnjvXpPeklDk0rFT7Fn5ctvWse26y9H02aM0IzPLznr9+GXn/LGx7nMP3NebPpbGexZbOjuZz/Y4dfc4jbuXTZYs0vYx16GB1eGa44zJNS0xLnG1DqaRQQugL8F8SwoZf2/p2eN+AcSnV+H/oIH7UIqjvC1g67cvJQ7fQy2udn9eO8eAXvTueuB62+zZ6lP/++kx7pGgjAC81KT7Z+7d+9btTU1CKUN92c7X1raeJIm3zsdTOtfAfT0NcWsI/bFqTdvGyCXz6ytvrCRrGvro67sE7GXlal4lwqYje15ef3tiTQP8Xt5Y9xppUsr68YfY+ho7X76rNdnmOCZ+HLg8M2mL3a9Lc1spAliLSRL3t89ouGzGSmPdjd2vAX3Tv/u8bS+MsM3AlwbOMW0x7r5NjPWlgfia73a8xtr5kkbWvm6T2GLKo8vk2XixLZmsse7jrrlM5xq4t9KhCjSCdS8rmGY2nj8WLK9+P16/XJtevQ3kMsSLw+MRsBF+U9c4sen6B2wBegT8sQOIDHqdcY+NKl5/7dzlRKD1UcDo5bHlcnh8OiSrHHPeUvJYv17bvu1xtJRV4rTzNbYc32vs5NtIywyV4iZo/t9RHlnKHuNzLNn1EtjXnr2lnnGPbSm6+ZkxMrLxdUPkWZ4na14qLZ8jSdp+79uSqHzfOm8J3melY6VcS5+QwH12WhoJx6Hc9aQtTTwy5HFfYz2+x7dbhWXuQWLsZA6xui1AWOrKo7Zt25ZD8MMAbox7ZNvU/V66DC4nDLV7jMbJ7Rmvfdr2AjmUrpeRH2aYo7fI2jHrTLw/dzn1vdWLnmWbhjv6ctt1IkO3/evGQxp+N9a5ZZyMx609Z7x2b3s55CFyPcAsx0YStAWua1r3KF2elbZ8uFtacwmMnyP5G5/1cDrnwC0Vbw3cttPhBrXGpmIv3YMyIL6XI2DSZqWxHr5nsnaf3AH5mJelX/d2R2DXbkPAcRq9HNOzc4Q8N/nkbAAHGmj3xsp17XpLp95m6O0ZtyWJtq8fXRw2MD0zaawXT+/Sa+8gftp3s4tElp1WyiVpvBK5Zi8JLPXcmA4ZH8f8nt0hjqNCoJ9EM0oca7LHYSmlbd8C+7PSGoF5euljl1/PTuccuP/gUg/WwijjUPSQLNIPqZayS39cBL9RPrGUFtsiM5Hvcn4/LF+y6L5z6ytrY86E6wHwKHv04H1Iyx5ZV/N+6aemx/Ib89Gn5fatOCrPdFo3gK1LcnzwnHjN/vPQtvF9RcYK17pHb5TlyO0w+xa2vS2ryO8l617z2ohT3c2AuJRDGghHiaQH7GPBfi0/8XqH68eh/dsjp6WMOkoiT1frflYAd6/7SjqbnTegOzuNvXUP4EsppeVnvdJEKaeNEBq77pm5PePyudbAG922Eax7Vj5OS18CeC+ZtBgn8tvus8W2142Sa8w9HrP2TraG7+EInMXAn16KEsZhzXsNrNefJYLfmg2kSWbyNerPBg5rdaCfwLKlcVu++vexfK4mm/R5267PCHlZGhBHcAYKtqa3b8smUTIZ79PbAY5N65r4M8fMr1ffBj7BgPsso+TZx243wu3KuN2DtuOM6QoYVtblpQhgaPwHBrbYPFGL9GbMenwOZgYjgJ5LJusatjS6BvoG4FHCab7jawAOrLv9RYmEsA7Ya9vXNezeOCfP8XSB9/pCHPR5OAxG7bhlWh+qLw2XcuzaSGuNdS8jDIrLWhuFAY2J2zWaDq45PvgM2+y6JxbL5xoNgujy1e5fV44f3f6WIGzAaec2MB5nBR8zm7k927FGyphGcrY+6l4ncFvHHZPOPXA/c+zpsBbW64PAWo9rkop8ZwfZ9uIqKveTI3w04A2ssZkm0QigrgF6J7fY/bzBL6WSlle533icgPioNTewXsoj4zagySbr8shyewSf2l2j3X+dgY/lcVxasviz0giwx92jZ67r2vzWtZos0m6d0AOzHWc2Ewq/bXKO1asRrKOksrz3WCRjftdGE+P2URaKndX4HNu+27HerrPrbYPmGtNfT2tM/HpZ8DHy6Rq7fjqa+LkG7o/FS+Aw04nHRYay1nPGirXGvgX0hBFLA6uoIAYSmRwhzHvJgKQyVZa98eWb37YBNgcm2q6SBuCwjmLUiZsMEre1IfEaC4zb7Vocth8jj6yx7TXXP+vA1lgqFsduv8t43tNj34dAe2l32Fp96Cx5ZV3Ltuu1U6LHSQSu/vgerP1OK89yqENqwLwmoax1bHHTslyAtVmN61H9DuvZI+NuBGo9oucx6Sx2PP4+5vi1/U9XLjnXwL2W1hrM4dQq5JoRZW1fz77XCruf8KCvBpWrkmIGU0Zlrdw8MgW5hrAU9VqhBKzMpJT8AGACYwsEeqNknD6/ZOVW6ZdlsTTwNe8NY+69RLIuj2z5bC8NkiPIb/l5j0P86xmFXe9MzLPIwrY3xtokj75urRki23erdw2sRxbbv/N2z16mGOO4r8kba/mIHc9Wh7Q2umgyzdq1m2zSrmHnj4B92IOkAXYZfgPX00Efw4i3QbuNIntZKH5ufX/WuAOup7O8DrYraqyky8rXhnVjTAnrLcmBVqQNwECw6m85KkGwQtm4Au+YauDhCQxQDQ13goFsYT2GIvBKI5f1BmkAxQjM7ZwezKOWPYJ8v31pGGz+3A0UK/pFBiLjJfQeKFuSyRpjbqU1puMBPOb/UOM5G9zG7T2J2CIGy3OW140sNnV1r38/jX1bHY2zKZf69GjAHt/5eP9mkFyC9/ozRb/0xrbHdmT5R/i+BnpP57MZzLdYbb95m/2ug3rt9h3StzuGjeqjcBkzP0uB+xBgW8WNQ70+jRW4Z9ZrQN5XLtm2YFlggDXWAQHEjDQcQxFICd01Wa/bbh3B0SFd8oplc9ta7acfdvbP3IC/DqAch8k8HB8Zdh/fe8m+R415DZzXtOxD+vbZ0sdxQL4u1WxNiV67dgTIQ+C2ZfBcHrcmQ0TWPHqLRDLR6rVp3k3/HldQ2jbCjvJIXy/WRqcjCVq2I/lu4Vp79m12kF4+WUolvavuaLDsO8Bex+7BtpW1HbPsxLdY9kHAtv9JOwfrTKFEzvO93amspXMP3GuNMQ4/r8fSv3bc0qjSQLbJMitBaDhpDyqsIpyFBYMlBldl9N779vBdifTMKsZHvxKDommT1lbkHqeut2SyyTrb3JJOrGxiI4g6a/yNYdtonFyfJr8c7Yxsfys14F0ftm+ndvyWzr51v7XrnO2JsmWgHIG63Tph7BSidLLUy2O9jO6dBmRj3qJ80ss+6/lf8zpZW9prLc71ms91BHGgl0qsRYw6dgnAaeUepRJgrTNv+9rx28esA/hZGrc9lzNq/7Tvtdu+bGPb6dwD91oaC3SbZa+nyLC2DZF27HI1G9nByqSV9QJI3BQRgUIGGODCImGDtcUICzesIrA0upTARACrux9lMAE5tWerbANg6gCwNdglELdjojwylltr7GvXtXjeS/AegXpZhnb9Bs48nIONc5apnQeMAD5+P3yNY9l5TxTG7fG3pXUpxOpqDsAX16lsTNuO7YNQxVC/dn587/J++gVxl2GG9SagxYisXWN9anusO3aZPq9NkrLOsWfd7b2NgK11wM8TkB9HFPG8NcYtedmOpb+2z0Yn474G3qXfZmWv/4+r2vQjg551Xwduf2IC9+G0xpDGIWM05KgcMTD4pXHSmMboSztWoDY0ion9PAYxgakCnBQLrTZoxRdkB4NBDFRmqBevg580sSVIRpBuBq11IF0bMkbJpJdNCA28m069XEUe4ZoR8Pvta/ds5XpsDV+y72OT5bvds+/IR3Bf1ouWh6Vxe2vty17Ttiyvx9boR3kRtOMocN1IuDRyWuo7gf7Zl3k85nef177djKx73RjpoM+sI872LONoTTqJyMp7otG/n1GbXht1NkK2AOnwuf49smnfM4D3daB1SOccuJOzjpiu16vAzlk3Wq7t56GBABGwbb9uhmsgzkAsAM340kLcEwdrCIiD1S3Q+bQcScraw7qJ5PezBmogvFVJeia+JrVEcF33LhnjQ3D3GUHdytOu154dYZ9tb0y9eZXwcKxu7TpfSx+L9m33XGPsS9ljGVhq3SNjW0e251gCZa8l9+FZpe71oN06mK1Y0tF+Y3U7dx3p8twU6sb6s6091/iMlvdREmn5NkBu7NrS6DkS9fzGbkeQ7SWUmKeRAbc8b7sSrm2PDDqOCCJwr+vZ4ZPWJZu1dM6B+5lNI7NZMp0xoNVaA4m9rjZkFiAXCKjiYWJsNRJOEUWEOet3ciC3axMwACchS4voRgdSkVPH7qJHwVZaZ9ryjGMDjdp4Y0CNlUewbvLJCOL9tTPWWPeYjzWQPmScFkNX2TxmO/WMc6kxj6MphN/La/XnrR8zSiX2fbxG1LxH0F6OFNvIZ5RTpLMe1308pGePoL0uDa2Xzbq00VLctua/3UskzKW7TwPwmIfR5xuIdctGGX1bb0SnbZc6uwnoel0jZpKXERN6wOb4eSGVHJuWjABo7Kl97xuHbO8rcgSSyBziS06m0RGBzKfbQNiwzM6D8x5l1mZEbKynMdN+KGZnskkuwZRJCvDuaCiZQD88jg0yMuOeMffSEqMBwBa7HUE7auDrw9Tt62y7//Wd7/FAfb3699h5LLXuPs/9dUagbPXNfrdLxxFMf70oI0XQjpJHD1gROI2lWx2yyT1jh7gO2ktd+2zGvUaMTOfuNetIBkZZhdHPtGyMu+npUQaxMo2MdnnMcpX1NaAeAJ7GGdJFGbWNqq1z1GM7EK/XDdiWzj1wXz+DOnx+tIyPIN1byXsmtDZUbr+tVxW9jZR7kzUSfaHECaAaXmSUJUYgDXmWI0HM0jv4VmglAlJq+eikBr9elJ22mWwfoMiePQ4bltJIv5rOMFoI25byyeh5srXwwlAem8y719ufDsCbXaA/Z52BWlrTvcffPUgDI1CvgWcvzfWg3csu0djLvt1Au9V1cxMETErZkn4OgXKUD8fnW9OY2zVGgF6bcNOzcOZZAXA8Zl0G6Rl4q7NrOrbv635TAGsAXANwyzN1QE7hCgyAOYC1tXWVT54tftxPB7S39Tgsto8W92WjjMP5CPbWmIYwqswGawClRZVQao2eRTdwdDWk01y5w1nS+xHCfam36jeJg4drrbGneN4IsPZY/ao5PZsevUnM3a+Be5Nbeia+ltbzeFyFHz1Vnh4bP0sSOQTK28evGR/XJI91MI/T4amrhz1g9tLUsuPqO4RIOhrDH2eGbhsve4+r2Mn37URScwVsDDy2hZ5xA8VFRfbysW3GeAPb5fGdRSZNDprc1T2zHUS93Mpk3c1PLtdYdJNL9DxuTNvmb0Rp89h0roH7mUjLhhHT6JM6gvPa+evsy3p6065lf+0qAgDxBCHutjELYMuKJdYADMxbxeYYf9pOTGLGtEZoDVgaSNKKqq6DBvakEDvIAA3E14C8AfAaWC917gjUWD3mGG18vcwttaHwYc8IA7LS/V6m0buoXWepWZ8N6Nu/lwbJQ/WsP69nudHDpI3aeKjP7VnPfo7+fscbJseZmxGM7Zjl7+i9Mdqb2vuStlJrZNg9sC7bdz/6jKDZvsdOxvaN26MBsvhpPhOjNePuOdpMjRXgPyJ9QgH3IQa19D7Y2k9+zLhfADRKEDzsXxZ8lyddnVu22PT1CGxowyjvMQCzYMr97YXHRm35FjnBzJrMjBScIgyUY2dEnQZewzV7Nh6fpYGXdUrrixv00kgb0q8z8vh967PP47KM1wF9vVos/Wu33fTivdZ9mLdYde+L3e9bO399YeD2fdlhmBTSs9sI2mv6dnMX7GWV9hwWlbIdL9fUOta1pyjHLJ9xW3LE4rgI1IukzyT/mmcWM1BrgQE9u3xhn6Un3Aujezu+nQMsOxfbFoG8dQBNEtE8clVWPcgnxry766C77lnpEwq4eza0nY7xox2NUMvG2UspW4x9OKNrGI0BA5TI6wTbdHIQhICTSyXSQBD+1nVpZwVS20MOABCFo62hGCA0dmTX9yNNhlmU75rXQM+2lyDeT8YZAb3/DCW4uPfI0g6lKBWcBdLbrH77XmtAa/frDd7ACNJyzlLrPgvMIzjb7x68o368Frd7bU6C1c++o4iupWt5HvPX9q8D8pqOvT4JRj7jnwBjrb33BjPrIsnQ33F2IgAH/Pbb9i2PNT9yfXoaO/uK5o4bvVtinrDI36GO69j0CQXcwDpoHwbysxp7Y9vLbYcLeul1YA2KF42FQA2wOz2QTPeASRq9ZBFliuY10jJR3fXQ7iNXU+bP5Lcg+0TS7fH5DneGfRrljbVlzcbJN+zbRle0/tyRXT9TYF2xxoyXnipjR7JkkWtupLJ9+Xv9uv33JZj3bn5rHiVrOrfF/mjbWoyPMd/mUtdGVW2mZnzu9TyvP8dWOmbkaiNV5gpwEVZbGfDfVbXtCIzGtO33ITa9NDL2qZ0rRbAcsTnhBrc8AhC93q6towW2NkitSj+b/LiPlUfattG4crxGB6wNqZe+vJ0m5sy3GSMaaw5TkNleYgDwbjKEuQBG9qN/4Xt87uaS1FgTo6ryYvFOzLvFJBq9d7IOwCpW9CkepaMGqJK/Ud/GIm+SopGwWfr78K3Aum/3GCtlK8V3dcjgaaC1briUn9vgNLLO8fcSjNbPOwzkS8NfA+0oj5ixEojgHA3Sss1YdWPd7RocymTZTtp9x7I6W3uXFN3/YryRKB9ErVmYtDNtdf2rPAd5RCe91FnBU1sfl8Cxq13crxy3uWcHGclRqSNo4uTnWsdhwG1yiUkugXG7vaWi1hIkUXgb5vqsAe44jBv2HMW8t4xUyx7ftq+x77a//WaLj70w/LBWdsn/mCXBTjlglCpSigcvgbt/Ru5/c4XP3NTKxx3oCnjBmDgaO4efxaAzG6aNDIB+uK0NIHigNBZtLNDyExm7bYt6t6VjWPdhKSV2Gs3r5Kx0Frtc/t6SRw57LkXD9jqQN9AdGXiMSxJju0d5Su5lIL+UW/r7bQH0qGEfLpfDaWx7AsoB2A0QuZEiRIA0EHcCFVl3vHYcWVgq8A7Km27pmLRNkWspGDXBeo0giZjvtoJ65YLKFV6/Lfs0XvdwOufAvZ56eeJ6hvh2zlgBqWsMjZU0JrItmxjDse9xWBiu79/0/xG4eQBSJcQub1A4OwBln9eWJxuudaMOiyWujb/T2uPzhHz3aWRWdbGtj2tix0UAHbXtEbSAswF7HazPMmIee52zz90G8SiPtBCp7cgRxJcjvD5CYH/sOHqMMUtih94D/lJeAawz7wG8Z+bXVwYI921Mux0bvzdvIMmxMW2VHRwYlWHDtkNBu6IHfDUUhjZihKG1y4pWL7VNdF4rAHX1IQJ/LNsghwBgGyWYPMJNd29G0ThCPi6da+A+C6Cvb9txAN8z7wjC+UDBc/fpgKzDMRs2ke9M7btff5lPbVoDy+7BO3YOWj0CE5MQsc66DSDUKi9RDandLDwOh+iHknpj5KFtvba9dBvsY2uPx/VplF7WQK3LuOdrLR0L6GudwZKBni0b9NtHXfwQ0+639aC8fM6zjMfo9i8BnDU/a8/Sp3EEcfaxvLItgLaxawPuigDc+ldtLdcA5lzQZlI2I6MRhKU0U7v2Zb7bLXu9i6Bta50w0OKTsLdpkXSapt3PqGzXYoa6Mx6XzjVwx7Q0BJ4F2stFD9ZTY4TrOmV7CRT1bnfCj0YN8T21aevWJhIlDyTVM9qR/Yzsfu0Z5TwrD6KeSTV2LmygJp2sg4TENUghJABumroyfjbGbDkM5d6D2JjHyKR6xj3Osmwaq+Wll03EB703rLVrLYrE72va79o+04bXzl03QDaZwQtIt6+7va2BPcI1lnLDujfJci5Bu24etkeAJv8+eqG0a7YRgWQxTkkfO4O1eDFr4G7nLHeIu2H0ALFyCMzVJQcAlpcKsPtMMzjq3JDfoodX32daMrSu9yOJqow46u/jyKIHW18r1stMgR7iacK1aIdjU+BLeBbWfFv7tPfzLALuj4Vpr19vjK/dX8N67WWl1X2JwNWGoM21yADVjYiRbcvp9l93nrHmnlm35xnd85ZGtXZcGzYGA2o38UAGeEmZRxvGkdZOGvIRQB5WEWMDr8N3Y4eRPY/yiBknl0xbGouBc8+Qlmkpc7TnWe7ri23tXB5+A2OnISm+i2U41v5YO27J2reZc7u25CPGGzl0XnsXI2i3xDA7B7sOe5YP+vVt35YULQfrLnMdw0Zk4WaAjAAejJWmSXMFmNSJqhEFNxICYJoDeLM+e8UIHdFWFX8318CYPxu9tvwbRBupOna0H9O5Bu7jwXgNzPoGBqwD9Vhxo2YcDxcwNsOjAdlaJaXuPdHwKRlxCNf/t0F763m3jmlDuzC8tpFBzfIMICDJipekwDk+iXjAtNFB68jWpBLe2B6/LzXt5koI9IbJddmk7cPG/n5fLJsYOXDpjmgd8RoDXkvrUso2aB3SxEcWHfePxsmRUcdy798Fc9S920rpvdxnHe06W25ExrbFunUIzMeRkm0vAq4RpCNQo4TvylpRlPYaizWw5EZKWIyOfi5xsyoZ8LssV7WJNt29f22MziDJDI8v5PlVnd07ITh4G8ExHOgJwLOIcY9pi3H2v9cr1ZbXyVLPHhl3asMxNzTY5/Y9CACT8G6sDv25ySpn5rUB9mEWPpZH7liLdTi1VpcOGCahxCG3fCWGsJgg49jahlY229+ByLj7DnWNlY/fW2rAu2a0a/GeLY+tLCKYt+GxHFO76zwTjHNtXy+BLVn1cvajfDbDJS+26xXCvrWOMt4Xw3HL+i7H0vCuY1tYjkbW5LOt/mvJtLU9BKCGA3lkTQ2kyY9Tl0D18mhp8L/2T9a6zLqQyazXC88OA/z2G8HoGPMqco3st9G2sXQ30NtowJ//WeMO2KfjQPvQOdsNbfQgWcbuDo1ASXWr5Gaxbuykseimjfe6W9+ARiDe+n1on93Z7zA0QoTvtVakZFCtGYuMmgmgBNC63h1lk2WIUqBf/zACyQik26AdAxatr39o2vboJVTCef3QeN2TJJaZvY/YCaxpvVusciuNOvAaEI+SSW98XGrio+GXh+/9fbdkHWPjkjiUQQ/WawPA5Sh2BO44EhvODf9sYCjE1vTi5i9dqxkAVdsOQNk6EmPTFIiKAb6yEJCyeMsDQsdRwxvSbxQNj7Z3Du+fwmcDbb2pT7bzPByZPqGA29L16d498+krZQ9y29cM56UMrubuYyCWQVTlahxnSwWfacfGtbjAngu/n91/lEQOg3Z8xjZ7bgQYaQjF80EpISU1YNrz0oSkQ77mebIEn3GB2h4wRmCOzHGUPEamPZ7Xnm88tzWobamkTfpZXrMfpYxAZF4UW41uS88e83f9oG0jAzmkB2h7x0s9O4J3ZNKt7CNQL8E8Ps/6ghbrx8Z3ZO1pnXo3+wuczbo0Elk3mn5s/LcfKbVPY7bdeNddU5WwM7A2e1FAuSyzS1XYuXcSFW1FesOR1lH1z72cD7JeGuvpnAN3glTgseJsyQTY3L7uGdHvH0G9bxTQN4MOEFsTsFXfgdjM2zXH30sgtt9nSSKHzh3ZqYOzZsoqONeqowJvEnK9BCTVvl0OAiAujFYhbVq/MVoz8iSsA3PvE99r23ZsjIFehhEPheO0rIchtzz7yHjXwNLS+rB1XY4Zj1pb6Xx57lmGy7OZtn1fq7Oj7WDJslntBk3fXnbgCNLYmYbFbgTT7QnHGJAtRzH9GertEwB7PMrqZXvvOpLyxhVHfXqGRsf0tqFtlTFvMN7armF3Zb2XhouwzqJ9WjtdID2a44HJJuvldFY618C9xSiPOU/SmsHnmBQZW2QdHCql9uZAiEEStFxqjKMxp555rQHx1h8AHGI/kWl3DcXrb+tojNWACUgZYEKtAKWqjQEAso4eoCvPc1vBnqyMlq52vR4aGTeF4yOAt/KWbMfjuTuOObqjtestJ7rUcEzsLJfs045baq/2rIdnWq53MGNa0+ytDHL3u+0f87ilY49GyLBKDFsc6jZq6J+zTRyzeuaeERQn7TTviMgu14HoDJZt+Q/+znqA37tBeN9mvA0xYJo3G5CidQZopknVs4eYIZ7NGh8m5GcZUEo+94v3tGyOVm8bWWnHnI1dls41cK+ls8Dr6W0fG1ZfwVNqYJgSYMHJxsh8MEAjG5q3mWnRn1WAfS0/47JlfV4PdVqtY+gnWCRENuK5FnZqxylAQ+MdVzASVVACGPLAlDLAMqows0uLJBf9t/sh8hh4yp5FOrhRGgEiEx9jmozA3Bh26wiWgIcwvF2TSerQ2SzLdFnu66O1HvCso1+GGF4C75Jg9N4m0dUzDsV5cS2Jwa6gyKTvTJlin+uujhshiZ9S/uaH3z9vf14oEste5fBD88gZzPt2/3gBHc2CzT+799YQQBdDIOnxBuISL81CrFp9NvKkHiHdSlMAKMysrEZpgDgRp8lMADDDZE6lAUguo3lphHu0zqBWu/+zZObkmnHw2N+Htx/25LCh0GhVZ2fUjW1HCXnpgmSNbSVfq/fmbo+A9eFRxtJoVn37+tCXu/Macwr3BSBugypVIfijI2GcUzky5L58OewHermjgfiy89zaBjRw6/ctteg4mzMeO4YahZ8XgXoNzNdTZMMNsNs1+nv1evN4HWPfYwe0xbDbKEtrG8DJ6yArshnYOERx/87bPdpnr1PLd9dxF3bdvq6tqy7DqMbIM5vGbPIOYFPW1/RskLoIqjEyhfrbwFalEYp1pTeUuuRnGXEPlV7u6OoLtbpfbUTKsczWnnuthA6ncw3cWyzzOBA/ZDRaNqb42xhrA2373YZtQJKwSIk9XoElGYWFOAgDC/U7KfITkUTrg7EAq4iE6Hq33pFFN0MFTGUoiUgD0McKFVivr4Up32UhCGsTBFAFZRtikwJ2AHBu+ZdGvVyvsg0ZLc9rS4vFYFOWok+3Xol7HXwoTSwZzai3W9ktt/dyx9ZI7FAaO6v11DP/0Ug53tekD/tO4Xszx7l6wDadXD4lljWUXRpks393SS88O0NHLvqLvS1pO7ARllVrf67hQTMk8qmPjqrfM8oQPhLQOtxGTfFPj+WKtgakgrbNwNXJOcLILd/wvIoNpnl2tXtYXTQvFi0JLxZrP3H6exstcAByDv/bN/Jrja6Qh9O5Bm6gZ0AANr8f2naW1r029Fsy1sGjonW1MJcmh2cGCAmMIi915YU57NLwG8bmBSblNj1w96OA2jWEdvyox7e7OMv2h60AdjbUCJ2UXTV2dan71ZdPP6xuBskRlNPwHjlcw9Jyoo2c0nTt/v0cZuitHm3NmjwsRfXpsIFu6/g1cF6y63Xj5hrL7twBefgEgam5RboZfSAY5B2AbqGed1P4JtVjLU/t+ZtBu8lT6wv0tjFAoyz9MS01o790LEZqTL9vxkjXvOVAGMDbdUyWinIiefiK1nHJPUPbsrrh60lCbT69UXX0QWfPF6+Uw3Y698B9fGOKKTb2xqDi93CHxf3aC22uV912AGCtTj51GA3Mg1QSe2S9qFaPBoCN0Tt2woCkY9krTxo9E1oja0f3On5fxVpaZ5bC3m24OQKT6fFLH+c4GlgaEAMTwtY7WUvbQN60fSuvtWOX2+y6Z2nYx6YGZJEI9LFAlro0wvbWqRqgC3u2UYZDFyz2hlEGtmNh2rCAEVPwlR6Ix2Ic2LFvzZdVdhuJQkdnQH822wd3fePCk2VjgowRCW83ypIxHk0MMoNreIJW6wmynl+XqXBAbaPGCNgeVC2OePvyIXs+DtvH0X44xzpGLYhVAreVzjVwr4H2IePkMef3aSmTALGhLV8K0Fe27nsX/Ss00MgunccYsyavCKZpS9775xg10+1no6EuMZYxqFn1PZvqLjr2Uk7S8mGGWir7gtBzrZNpiyzEfDb5pDdybQUBW5tU05jSeFzfIR3H3A9vPyttHb9slONIac1w2m8zH//IxhG+N5B20PYp5PGzKmCboU/ytx7VD17ZevaNts1HKko6VvCnPSMFCq1gbNd1T5AAtj4aiGnFiEdVSI8y6cZem7urGS/HjrNp0NaZ2c6BL5MtQmK7KSyqoPeytqgMizbAmP05bf7k8ikPpXMN3GPaAq01A9DH7hJ4KClAuU7WyErsWKwOLJiN57v/3hsMt59x3T2w6fEC9JKDWu3a7Vru3qUVz/eTBZnK6MrKM2+jhO0Osde55eS1d9G/yzVtG4jgGlnrcoalbYslvQ7MrcHH8lwCan/OOllYN0DGe4665hjQqQdt2+5gTgxwhiEhm45hniJslc62K3gnq5qsAK55iVkMgwOpbjrZm9XmYYBl4GS2k3EEib7bjF40TIbVPUulUIcMvLeSByRjr6Saac0Pm2QSovm10leUloWG9YLoje16jI3ICI7sYnuy92GyTD/KaD4mQ3l4+XHoM54ljNt005aWQ9Et5nlIG2+/R0MJh/0hkI8PIdsxXgkVK2qtNupCdc2NQWyrwsj9bZUbvz+MaUvjXHMJjB1Bf+/1jqzJLfIcrSMQ9pESACRULmjMt9dYXQcHQAFbPG9IXR6XZWspauKW37ECr4HmUrM2uaNn3+OkHCvHNQ18yeRjvo5J/aru1oEifO/rkV++2xSMj/G3M8PwLKyAbR4lURZhu0aQRyAGPBBQSRfbJVayyAps5NeJLnSeV0JYZAM2D0WYd23w04EVh7qieXHWGa5tU9erLzagOMmM5i3S6q/Fu5bRg3l9BFJgdwnZbzksEeP9vgSAkkqLjvSRRTUvsmpad2XvbiglfY72Uh2sQ92XTjA8zHVQ7nMO3NvAbGmLDR3SLUevE/u9tPryKl22YZ8xDKuk1O23amsGOwX8bgWU+J7lCpF5x2f0IwI7XBpVR8ZO2lGscSQBX6u04mGQtZ8a70/eQa1hXG+EbPeLbLrvZOJF1t/dkoQ1IG/Zk5mBkkdGXGWllcca875emaQ9+Fp13PIW8O0c72UsfLksmWDIKK+Zp0/QtJVhSxWrTSaBrtVIFVwhYQ2sA04N5jxCpD0Qka/qZVO8N9khoa/ngBcnA+q/PbBOY9wuC8VY29XbUH/VQS7h1vHYOpQyu7GRJDnMpq43JI8M2/NuIy8D9Qj+4R0zi4NB0o1VZRIChAEFDZu9h9Du19i6Y8SzhnEfz4T8DBqHoz0QrTNvA83ImtCB9lqhM9fmChh6W3LWRd7jh7M2n2tpSB3yHvJB4Zy1zkt+5qES2v1t+N3u4S5yfl8b7TQAcc+RhaFzHdBke94cGawbKi3ZuzNQOwt4C/qp/mXlmEMgvp3W8tU/f18WvWthz8IjyFc233P25zMK4AZsNjZNMGnAJACuwsZZwVrAo7FsAe2qw3kWF0/PVy+FLUwIwGCzsedc67ntgQLJUJbPnn8dCVhJdEuQ6UghlJF1RKI0VJdz2hqR0tMI4VAm7m21elbN1VWOs+tx20+tVbWoJABpftJQZ1OKHkJowG3SzUqx+LZnD+M++0nXQPl63AfXUwSmEaRGf+GkQ7zokN/PlltW97XnWrJtl1cGkZqjBkexMWI4t83cbJ3Tcr1Nokk6gK7T6CWbQOK1P8qrkg7R2Fmuv8NtTxR/SsRIa/Ic1sDXPEPGVdyjVPJMsG7NVRwerzDtQ/ujAc+hwlmofJpxsgGDTHhy0OaKquKxASKTGMaZavutZeH7OLh4UjNgs3YONiqo0csmCaQR1OtCFxDhrVerdYNrY9gOzAZqHWCju9DC11nrLQFgwnLpL+2oWv5DB2lDEpMsXZaCYjz74Z0UpBOBBr8U/wxczq+/hiqGA1LctOlEu5XOOXBfP+NuafQV3mZNMYSnLE0UNMdBx4q/oonDzrftbaqKyiUd2Hev3/O3yUg3mOm2/DCwaB0GNgnFUkbU1CO7phSiAmoeBMCH7WNeh3ytxRs/rjMV/d2OsXjch5l3QQRiIjsmyilPh3XHY89i2rTxHTCglnpmrqaEZvgyA6vp2soc2SZAKXutpf12pq3XJRYmTtxmnSd2sOIi5ZJIeDiRVYyWD3CEKbirHKcwZ3ahZATG62w7rNgeQrTaIgTmKx3vpQWmDL3JGRSgtLnz2eSd5btwBs9NHvJ8QusdW0mbe6Ud079T8uObHNJGAC0tqMegvRxPHM89cC/T02PQ13mPEZI7FjAM6wlADSAdfU9JeW7l0PbXQC9+X7LpkVVHl7Ftxp1Xyqr3G7ZYI3Yv2ZY9QybBEGWIMTKDUlKW0VwA1/M8+nMv39f2+4sLCo/Pa9t6kF4y8XU55WNl3VGKs+9bLHvtu2mdBtLt00C8scReKjEQUnkEtQfrwLQ5aZ5SY7x+/yTXr1aXqr3DJhsYCQfUuNb5jzNGpcUlEmOysbwSeRjkpvMqaOtXNzD6O+p5ro0a3aheATvLPF5sjUoZpGmPtUaX9dOdAXwVHe7ea3vf6Np/ovAOmBEJmdsT7Do2q7rGZzsunXPgXg5FLR3WrUc5oHcJjLq2GXb83IXPs2XFhrQFZr4hknm9UsfJh4cSpIkknjWJW5fF0TDVo6kfQY7QgEwj+27a+2ici88Tj11u670h7Dy5vxyUdQq+3UAadEqNkacBpFsDWL6P9VHB2UmOG2WOQ9JIPFc+l6DezpH92/XquNRAOI6e7Peaxh0lURnIyXmt/gUf7iifsJ0jvuxynRG0Nz7Vj7ugCKN0j7gmmRElmI80tDPvRgik/vc+MgAWgrjvCp1Y12k1/dqjArYBiX4JPtFkozryttPXXbtwG4naItisMbR9t3eYte9YmAPQeh8it7fhKVuHwq73J29f4Vn9WKsNrfvy6/LYpR1O5xy4mz/x09OtD/lwj0YmM87ZkM+s+1ZpeeXc1oPGF1WNpVBybcu0wt5vd01GWIv3EffTcCx35/WgH6Ma2v0a2xb2EPNvXibKwFxKsb/sQ2Vp8NBGlrp7N319HdTP8gSKMoM1kphasK/lNsvb4VgmvLLtcOrzzOhBum2Pn41lw491ORaMiiSrhcfrcLgCq/cHQ1glA72m3T5FFTDQtlVjZt2mYUoJ4GKjKO24NQIgV/HfFlZr7609W2+3iaCMANrDs3MAzI3OsmG3dhLI8FARxqq9YzBik70ei8SRmwRirN6brI1i7MNpl3cerOE+zXApfSN3GfSOg012JKSUJRaQ4gPB+hLphDiC+XWqA+ccuNWLYfHQ7bcVou/pjo3nRr1U3phUYLuOAo26+fmSQx7GkeU7t8A/tRKYM6C+oaUC1V2zJJucsvisamPxCHYpgRUICdJgRvBlz6/F+I5Nps129PMUeCPAsroPdr/12apJI4Cv/G4SC42/Uxr2Jc97K8f4PY4OKHxHV+7LNM6w9Dcd3rG9s9Jt639PeowgSy9xACNgH2bhNrljBOTtz61tFkujSRjStZt+DV+2q9XXasCoDNGMe7UKseDKqArWDt4oKKUEQ2Vj/QSA5hmUVQJT+StRBlcZLRK1SVzQ2lMDY+8KntQ/G9A2wtZc5L5G6FUGaXKJ81lvQ2YolIqcfB6EuNU2PZydXMmIwckzNf9sIngnJoGn2OdbGGmRdp40O9XbHZStN88a+ZSfpfO4sU7WvkdjrPU5tu3YdM6B++wh9jYTj5JHZO3CpNuhvX8tUW69NrwfDdewhqcxJLRi1SpAWMOQsZI61A2AB4fRljj4HvdM0oavQNxhbkqkr7hp0aSqjebXGaGxaWNSVg7GxFO7RgTuDGlARGKwVI2HXPaJ3jANtFtWR5Cmbl+3J9sz05II12WJSfUejb4YtsmzRi1ZymAajj3UqEYf7NErIsod7O/RGbbvkzrSFjVIfk3zGLHj2rnqQpdYJr8kBpcq/sRWF6NXSQ1SiYG5Are742ndlXUzGEkugpqAjNyei1qJ9tPvQwfoQTAbGJudjwhiDE22X07yQS2EbBAKGCSg6wZJM8hC9ykI1tYeiaoifYz5PlYc833XCT+jmEGyYJ/8zuDgY64V20G4FUwDaT8ulkvY1593fDrnwG2+w2OiM7+3oa0BbgzQT1iAhmmmrkWZ1kiw8WAzILUhNiOhckWpM2qtjXmEe1UiJOuBU8xXahVTK0DSe0fPp2os1GQPB1tl2wagVvm7iqT7ncFAZ0rLNXvg1mtm/ZQHAGUF7GSgbXX6EGhHlh071OFN9gOi9hZHnNa2GduAkKIUtFvb2eKSN4hoHW+fmuxytvZt4JTAPHsmD4O2/jae2W3TSTVsEzug7FNn4pr+nSq46MSaIiBUdTYfk7HpQd+uvWdK71GjRsaaQaSmNkp6qNQTEHz1mP51xDaG9kLInttmEEtFY7BO6mnHSo4TwHvn80Ssp9hwyrsMfW9xUpbamkhBm8VzyDmurStpWbMypwSk6k/AXd4taTza8LQ27b/JHYIJBtA9buhuBHqWEogZNR1vBD/nwB0B+HrTOHkEw3de2dd+s7Ps0fMgArhWVK6olVCtAQLisqXXSTWhEpDTBDWMS4wQLjI8tTaVdNjsAd5jOZiBsDdmukSBDCSrKkGmILthq3QCvGI0hX1PwUskm+sfOuCm1LZpb+F/TSqJny31LNtGAfDBwHYaLhTpIBSC9DV1uEsJqH3dacPrNfBGAO91GcUAV9IU2He7/vhdAIO733EtT5dMwlTyxswFrGuZlU3rb9ahemrng9Dr3nY1L5PlM1VdJ5Q4I6Usbn8EJEwKnFbGAorS+fed26Ff2mO410vb7xP35adR8EBO2vUEpOX9ZF2BSkHbJbAxD0kBN67mbiTM7DqtPIpp3F7ns9+zY9xScH61yKi9juh7GMfU18u8zzlwJ4weIof07p7ZjaC9ZZyMvxujEk0MAKvV3V6Y+dSyDFel8Slo14JabaKDMPhqw1ECEgpYB2PJNWp2wO4qiDNWY7MrDFnLp+FJr+lL5dWf3DosizPCuTFlyr1rIGVypk5EQFYwdsbdPGS6onchuz3HUhqh7tCjvfESIxJml5YUvBf7knYSxsjbhVpnqWXiOaToK26A07M/aaRWXwRYoodJZNsRyEsEba1qnX+2n6vsGhW1FhTeq6GxopYibNwYqgOjPqsbF5XtmkwhQiuC4iEqA8tsQgMtRkJFQaqts3dDnveyoeNtV9My7Sefxf6ZoL7l3s7G7/Gk9jKj3m4jPCkvncNL6OTNlqyTruFZGmGzuQFy3QFqaWWIN0gfVgpV8+CPEt6lHde37bPTOQfup5eiRLJMhxk3a/hSB22Ysciu2aLLMRNqKShlVtCGAjeQqIiTEkGNP1kkD3cbJFCtYCKZrZazdhJybQdUM5YAiMZL81oR4ErKes1QSUqMRDIwXdqVHwA0qcuVM22oAbIBtV9T70m2zctYwX2Fcbd34d/C79BEvPg7uox1cEBHmAmhXXVsWGGL+3OCHNkwF3Y9u+eQFdOhg/QZk/yWRj4CtnUstUqoIq4265GNjIK5wAbdVRm1sGs1LKYZpe5ReZa6hiLAXs2sx6EqE1BDx2u2Ag7PZeSWrFNTtm7SUpY4J+YdASZUFJVNdCKZFmSnOjkgxw+bi9tizRvbVs9uL0SPnbIBbyJlzuDwUqVrqhDvJwYwh9PZy1kIzbgSlF2z+jR23x9G+RXcV0PPa9X9a5lFK2f7OXYMZ6RPaOBeN0xGicR+n/XdfjfG7ezKjBvWsLpZbMa0BbCbxl1F164ZnNXdCkLxKNvkW7uPDt+cCtHyjwDXoM2v2d3x1GOkm3Bj91N2rexTY0jpIapFO3A346MBPfIA3LZNWn5UShBBux8UjSA+7DdTwnBcm34v21qDIwVi9o7IzuYOiA3Yye9DYDdyUgAINgd2M3wpwMTrs4IPLICdMyxlySABPAfvxhKrMWnLj58H8TgyyYNYZBCyaeEVFTNK2QvzxoxSikgnCW04brNcNWNMSSZ9Gbga0CreNGyT7VwrKInHR61qnPdJT1pP2QpWyYezGwNoG0nIs5KWBaEd2kNyk07ERZzDiCOAM1VEsI3zLlIyW5C581m42+Jt1v/xlrdSIDf2Wr1SZ7SFpu3+wdgL88wyMsZOZLpzhs9j0jkH7iVzZm4gbd9H+cS8Q/wqHQMf+73UHdevqqHDKGPAaQeuM0BJGc8Mi70gwB2MUyBQYpRSwTxjogxGhkiT4p/O5umR5FetLBNecgBhMjNm0oA56vWB7IANF7ODrGQxQ5iBnNqT6OOmqZUv5aB7ZzirNmmcAkITEmga2DMNYDwUcWTdxrziK3Gu5UMLyT4XY4fO19txnTQiIOlgbOsdRmA3XEuh+QT7JTOH4uOAK/JOZe1NBogdvL2/USmCM/u4uUlpyq7BCux6fZJp30wUmLZEu5OofjqK41nAm/coVeqaxYhmZlA2O4t2spOgs8k58s4NYNv/4PBeE2mcnYqMGaLfi7eHeH3UBorwnlrtOWYUZx2MVq+ORAAXY6zV6A/MJVLepU5hF8TUdlu0LUWCYzq31fPSZCewBuwKx7MycH33rW3Cr9NsF63Nk2naW3q0M4nWMXkHRWjntcPal+ug3OccuA+nbaPlyKwjG+eVY+S39Jgc9o1sI0H8uHXYVcWwUYpGZGNyxi3ts0kP1bW/Ck5NNxU3QPFTFQBq7Mw7HCIgZXhTdPBuz9WCO6VWQZWVMZE5l8g9DcxM4xafRWlsWa8b+4GOWSvw5rbdjunZdM+Ye2qM0CcHpj28kciK/b7exkhAuFqX1A+DpZPhMJZdUD69P1vY5nAfvXZY79nuzwAwsQnWMK2VU22/bUKMTj6pClpwF72q3hoG3g2sBdjUQwkC3MVkE1LfbS2IiorEQYtWbxIiUiFBUg3bkEgn4YRntvzCvFsqEjMqqV0Fba6CdxAU3q91fFiyzT7x8L0x6ha1z0DTZEpzYYwr+Qj4+0vxtlRb3SJGlDob2ZP2G/Nrsp9t7w3aAdD1fhz+fOAVj3fw1k4Aw0FHpHMO3Et3wB6se+bdHzNO3GlugX3FUi8SryxxYKMTAAzUAyU0q3xRYxFgFa5JKbUClMRPtjKDKvsMRp8VGuIfy3smcAFq1inm/jzqzw2TMrLWUcu/NZpWZEJODN6pbTelxYAbdpz+yw24KaI2Sbl4nsw9sAPtDcAO23xLGo/tEyfqRESDosbQqYF/5dYj6bFtv25zH2A7X/Od9Fj1wUd7zZKKySYBrMnEKFea5S+zjsYq4hEA68o0uo8ZnFQOoYJKBeCCCgHvalo2heMV4RwIrEQ8bGnArMzKYMNYhZQfJwp1uStxlU0ArubdlGRyGGzyWADn66CTsfms3dqnubHGR7EyY5IFP3yFGvZnt+nzZtxt7kV6NgO9Xaox9vWFe1PLyVomFeQTiUTKsPepu8Nx3gF55866eMRx6ZwD9/WnpWFy+d2OiQDe/LjtOGt0ZkpxyFLQZhQu0sCoOiOy12gB6cGqg2ndbmsDMsSn2GQTuT4poyA1mFFO3oCWHjIG2sKMPK4ESCezUHd4dNAR0E4C4KZdW6dggA0sdG6plAGwja2H27XvW8Dc8rU5aLKjwtyKOKSNt5POikTXRWtzIwunDAcf1IGlW4fXe63J/gkO3gaUDIhPtb1xB3V5fxUNVEAGXCKHeIAoMuaodhE0IGcUGf7DjuPOMGvl53lXUEYeRhbMsGWkDfEpEap5u/kwBlpXK0inv8tbr2A2khDIge51RsqNQAgTHVlrx0tbR+QFLxq7YJ4yZ3MhJIZIN2ZjquHajSlLaxUNzfVmEIgmXe1Jn5nIz/P8eR029t4KudYZy5Q8n3Z+VzONSBnZcVw5Lp1z4F4y7hV0GL4vWXb/fdC0I0tTK3N/ji4NAtMSdWirVv4KMUiWUlqlJQAaAtOm2SZqGpwZsGqFStSCCI0bWcUS17QGbhbRrz2H/04K2ikwYNNlI5D76cmZtjEJSsraUhtHk4Gra9x67ciyHYAjUJ/BvI+vwwOgjkgfAFjd/8QwFphm4ETubWKugowerLXP5oLA7vRCFq+fASQF5co2IdGDGrk/dRxWowSwVnCvshZiRZEp6ygNvGuVbbWIVm6+xllGBqYBG9OW+7NIOPY+mdqaGRWjC7bklUiNkV6caig0yUzN4ebzbfKJjWp91Nu7TcZJSbG3WcooAcAt5oeCdzuUh7/GjNvIpq8R3WibrW03oG4j7BWf/gDyXiwuebTRFQC/T8sqOxMPzXYYsZ+dzjlwH5ea3mZFdYwnybhU2XhczwZ8eExqZCLW6cesXKlqr2sgLKBNkBFcwYxMWUGuZyO1ErL22OSqGeCVmtuwddTsXa8Gu/TQjIoI24L+nAyclUnbVHaXRiCADtZPC0iE9j2Cd2D3W6C9YNaDvr2ewvvRPrRrjwHIyQFAn88Oqu2YVSYeCV+8sIKdAzVBkK/I+xWnC24zF6FgAwZPrAu12L/AnJOB9izsViUTi/EhLoMWSCrEH9GOgGqCyXSJkldbttpDOk6sAGeB1tYpSTlUrkg5uYeJkEFWcLcYHgi+4hVVGa+aIkGVkHSUB9DAKH1ogpFpL//au6rMck0x1QOUIA4AAqYWFxyJPFaIG+jBwrxhHUhzMRIZUtrP6CES3W0dXMMAcuxoDLyJSNwIV8CYteNkXZfSgPw6lJLzDtwmE2yz7HFm3JquvfY9uhy188MLZ8C8AwykxZvAWJPmJWlsEH9/FIBRATS8W8FeUsamLEkbmw33zMXPXcqCvGKsu3NvCgzZDW62LTDwbtBB5N4kxspkqA2XTjy/enpviBxeRWDdZOXRAXxMLS9LIEY7fwB2SnrR4ArYHdsxtNaJ+Q7G4PIXGLijB4Y+mwfw1m3QDhwI2jW7IdKmindKeJBH2nf1oIBJKLU7phqrN+Zuhm3tw63eAOpnlKhNVY/6K1n56LNb/dSC910UZA6GExE4o5Y/IS/Vj03IcLmo6tZhgpOBaleXtWzAFSK9W7vQs8JoqFufExp2gEXKtJg8MlaIKfbKMVAVXKuXWCnDOVzE4ydq1YCGErDH4m6/ZdfjCLlBNNaF49K5B+6eYcK/jy6B437ZF4G96cGNCcj2HsRDIyGJuiZ6tuiThWaUOktDI+XaBB8mG2BXAnI26sdIKYvrFjFmPkXGpHmblEXIc1SN923SBVNtcbCZnPmSseFYROYZmPS+Bs7eH5Hr3EmB2TVsa8gmnSTAgkvBLxdQHHr99rV1DKQeHd0rae/FZPL+dfmgG/axBurt2LDBAN/d7daZfGTa7bsiROFwH9HLmSGdGkPYqV6fE1D33PyuJwbPrd60lcmVXbPp1Robu84CwKSTt2waO5vWXaS+mXZrjNtYP8FtKGZsJMA7Cy9vNayTjQQVqHMyd1aWOgXINO0kXlEp6QuyYmRS8qDXJSkPq6eAALd7OhVlnVVetgGWGwS5KtmpoM6x3F6merCAQTQBZKxbZgZVNj1cg0JxEkNvld5WMEGBtFqH412Y/sUhlrg+wjoOlWkIRQ2RSe/jPUgDY1tzFnAWUYpcO1NbLu16pZLrURIBAL/wC7+AL/uyL8O9994LIsKb3vSmbj8z4zu+4ztwzz334KabbsIDDzyA3/qt3+qO+ehHP4pXvvKVuO2223DHHXfg677u6/DEE09cb1YAjKB8eH8P0lv6dn9MW11Oq8owNHWDI/eX5BQaClgM2vpnTNYNN0mXArNp5AnwUJSh8jNqY1Lqbxz9udtjsX+qnVD1bL2/at0IefLf0HaYIKBt+7OOEkLRUTi/f7721127uyfBJv0s87J1fvve9iH8Xh7X/U0A7dqfbJeyYuss7Hmo32/H+32n4drZjuV2XLZr8/Jvigy7SQMMmxyisyBJ3EONaQsRMNLQrmcdO2lH0w3hA7NeTnQJh+kowQKhRTAxoAR0Mhm4RRoM94r2Fv8kk39E5hHZEA0Iq3Rk0nc0pi2HZJX1RHYwLykAuvpOCxOL7tbseRi9yER+jGXUJse1SXIpnNsat9mf4s0kf9bQ2p9JLc1o305sz8363NZhHJeuG7iffPJJvPjFL8b3f//3r+7/Z//sn+F7v/d78YM/+IN4+9vfjltuuQUve9nLcPXqVT/mla98JX79138dP/uzP4uf+qmfwi/8wi/gNa95zfVmBcuWeezfeD5WttuLte/WABHYdgBvXw5K2ISf6iDEzq79OEisiJRJppgH9lH1GAMCcROkrk7WVBVgx0eRxjKCJBI8X40BC4jbb5kpr+Bo+Q/aOKDbI5vvXsUaSOtvP44HYB7AfgTFAIiH/kYwP/NvWvvj/nd4B/E305hP7n5z/E4Mzjo6ix5GpMZG3V5JjJHmWQISBl7VcGm/qk1SUblEnp36emD3Tkoa3KspdMyMBrxhUGnhUkHk8CfGTAGYZvBsnYQAXhF/cx0d9GtKypVqkdGFTB4y/3W5ta3raHe1ld856iFdsk6lAb12P5A5E4ze02gNvKsCbPJ7MmwUVFDU+Fu5atz8hs1sz+WjXEnmZYUI2l2Ow3cj6XFEekS6bqnkFa94BV7xiles7mNmfM/3fA/+4T/8h/jyL/9yAMC/+lf/CnfddRfe9KY34au/+qvxm7/5m3jzm9+MX/mVX8EXfuEXAgC+7/u+D1/6pV+Kf/7P/znuvffe683S00ytlNgkBt9mLxyNrST2F+WsJRqpfJtWFDJtlLzXZQVrEINSRowhnVRyAIm5hAioKDqRT2e+KWtmBTJK5oqo+oaPYKmvBAFcHbCNdROaG6B1Nlbx9Lvla+2zG8S0muv58UTh3t2+qHEbuG9zwnCTsC0esnKutpDFLuq/8qJVaX4Z7kXC9r6VeXFG8xG3+lDa/WLjNBQUHTSANuy3SG2MCk6lRfvTuQA1gKGxtW5Ci7mYopEAG/S5EECq8ppsFxhk59NtZWKTb1ZGtux3k19RnmyIBJFZVP+yvFZUEOtCIeYLC3bSoxwHldinu8drttfO3uYY8DKS8m/xR9zA7nFLoKMAyU2zrlc3EsrxVuZWGXpXQ4lECD0uFA71o2p9PSbkdnat69G2LV034z6UHnroITz88MN44IEHfNvtt9+O++67Dw8++CAA4MEHH8Qdd9zhoA0ADzzwAFJKePvb37563WvXruGxxx7r/iz7HMe3Z/z1x8bzlWWYLmV0BFphbZRjzM+A2YC44b0zIJY6IrJIThJdLyHcQ4bJUIZLxmDBslyVT20WblWoyD0R2FFgx5yh+E0ak4Mag4Xlm5z5ioSi4G3bjfluFWFGz7R9uw4NKZTRwVexco3Fflr5TcO1W1mPUkdju+17Y+SMY1l8x86NbY/MdkID9cByeVJjIVlnCyDIHqwsm3WCTSUFb8hsSAkeJa6AFQVuoLSZlaGMGFCXQXTynWEcd3W8yRtk9opRAgi6rBvYbLt1QFgm0bVjSChlq7XKvAaNEyL7qjynBmFzw6PBtHKgCjHyVZjUQjresE89pipL97vHBaXjM8fFQCTXNmIoxaJ4RtkkXqMijiaEuYvnl5E5v49fPf5noZf9J8wjfjVUykZ6RoH74YcfBgDcdddd3fa77rrL9z388MN4/vOf3+2fpgl33nmnHzOmN77xjbj99tv971M+5VOedh7XvEXWgNwbvR+ywrjtOKhUkqpvi5H0xDVIv+cA0spSyd+iXk//qho/bagoUQJlSCyrcbd1FWl8rBQYZJBxOtabDLx1koc9ow2v/Xrce5FoY/dOawDK6+hLV4CYV7aPfz3wb0kko059SFNfzzP3+6I0MvXncpa8m4TSjYpMuspN165UUVOTSGqVWZHFYpBgDsJIk0vin4ywWJk2RJ8OMVD6Y5WVauV1NjgOMzi8ewrKa6djO3XspAeuYaq4DrFaB6KfzAKQc5BVwA6KVUcS1V3lDMoNng0YHa5V2hhB259I26q8rOY7b/WZALK1VuFHAxJHaJ4tZIVFXUweLEwKUhtxG9KEwWScZtR7T9kMS5/R2nUkZ6dnFLj/oNLrX/96PProo/73u7/7u93+pdP+9j7yVg60VgjYUE0224ul1jCdcUOOS4BZ8JG0otq5dkUF6aSMmzIhTXI/tuFZao3ex4eAD/eEcRUFU6ucaKyH1pkjA2ow7IFRQEgArDFVNTa5Ls7egYACw9QORzTuxvalHASYelaLnhVavdwEyvHcQ9vXjtF8Zx2BBM1afnPYTq5jt23ojvXvseymkP+JvfzdOGvHa7ny1MpSjIwG8CKPMGmgKN6jQAJGVZp7Ro7qxu7GpoO9g4a/ym44lMGhMm0imNatGN1YYhoYnyEZkYQdtipHwJbmbF5FTTe3zGldLQqalZ3VtqQEhYuOOAugI08Vo2G9E0kPhTaDkgFu8wdCo4SBtRzTOgVh9yFCY20Q35i65LeUGWWuKIV15MC6KIoeY48QRzGknYuNRGF5i+WlHaOBdur3H0rPqDvg3XffDQD44Ac/iHvuuce3f/CDH8Tnf/7n+zEf+tCHuvPmecZHP/pRP39Mly5dwqVLl1b2NOCVOkb+2RfSWoGk4XsD5WCTbOc747bDB2VKj+fCDuRUEihXnYyQfMHWqpMyKEEaJysTsBmSSfXJRKGRVTAnYd0gwKQXNHcjlwpT++RkkxIk/5T1oKSdQ0oIMiFIw8y2DqofHcRP09Kd2EdDzOIVyH0ZwOg1uHg9XvbjjjAA1/dAbZN8tFbU/yZtYhSvow89YlC8loMhHOwsiBQzC3iX0IkYxgQUdHc87fydR6aKWnRUlSq4RAYqskLV8iIWLOuA2rJq3h2W8WyERQuyWtmzGxmRGKkaW7bnVaDWB3eviNzi65AP7BFGi8tXFaUaA0CL7U3hn+Xb4lPKpUgAG9UrJgE6O9QkHfXx5hYuolYE5qzZUl07UGIpkipTRSVbRtRMp246uZRLctCXS9SAMbGysPUViHq+5XcE+K7eje3ljPSMMu4XvehFuPvuu/GWt7zFtz322GN4+9vfjvvvvx8AcP/99+ORRx7BO9/5Tj/mrW99K2qtuO+++572vcfZkeMMqPbdJq7EF6msiPVYb1zKpLI2iiSs0jVGYlRlW1WvYesxAgBN+j6mBCRC3qUG6tAZZho3W4iDuHpJCM0QvY1K085TReEqUQc1HyWZVlpVrmF3F0wIw1ozbuo92DoOVCBVZ5UWmc5qB9lIwJm4NEBjmS7/+IQfdIBv8kT0JImufo19E5Z6dgDF+BeYbycJHNSuCb1MwujlFPvdPv0vI4xIwp/ZFrKUfVGdOmXIhCC7rrFs9/Iwg+QpkAoKC9MuVY2WGahZ6wRUQvBREQWvJmXzJqMpyCcm4Y36nquNAhjiz1x1m5NizasxW+LGtG06PUhjXAuIJSIFNIv9obKDkVfW+ys7jrKHyyNokgjDXBxF8in27IDPh1BhBBUWjkKBnVs4W8sreaMGWmwGGRkkj1EOndJv4G0dg0giVSdY2WpWIv+Y5GIA3+pxBaNU+WOodxi1YjZyw+qsgJRcVr0e5L5uxv3EE0/gfe97n/9+6KGH8O53vxt33nknXvCCF+Cbvumb8E/+yT/BZ3zGZ+BFL3oRvv3bvx333nsvvuIrvgIA8Cf+xJ/Ay1/+crz61a/GD/7gD2K/3+O1r30tvvqrv/ppeJQ0xr1O37ZZd5ssYp06t0sBquHa/gbs1hB8mBmzUtF0bJBEm9OGZL6kKSXMdQa0U6hUhVikpJZ7rcAQ0M0paw8ulcTXfFQgkSkUsnJKYgmQzxNrHApZSZ4AdelreqfUk+C2yA3YO8mF0IyVhH6/MXLrG0gbQgj3uvzUvHMg5/5qAvB3aaDEOgp2JqNAszjLQWnjOr5JmRGtH+rr/hJ8VqZH+WMWV79ZfZOzgRP7pR2wGC53MVV5T2DMc1EdW10FFRRKrbJqnYbDCVeFDR5sREUsgErQcK4p9fFKwGB976I0sCxQSwBVKJCFMQ17NBIBneAl0UKYrhQns06sadvcowTcn09xjoJustIz5jyObAPLlXwpI4ZNsOGYa5VGjS0HhgwrWPlu4WM7nVsBllj8x2tk4fZc4bmbjzd3xNCeoI0U4G2vebhsFOhGum7gfsc73oG//Jf/sv9+3eteBwB41atehR/5kR/B3/t7fw9PPvkkXvOa1+CRRx7Bn//zfx5vfvObcfnyZT/nR3/0R/Ha174WL33pS5FSwld+5Vfie7/3e683K6upqxibidqLNJBwfSmAtLGx8K7FLsJwWqF1gZjcNxY1XLe2c2tlv0+Xx6TuUSSSCqOKxFflxRIxaqogKgLAuWndJhNSJhQugqMsCkij2mi9vtVdA14zNOmfsERyCYRUn21+3ha/wQxvAXiNuVl5rgL3cv+iui4AvSV7L/Yca6DtjYDizYdjxs7Cv7aOwNveDi2AFAXAJm4RAG2RBKkMMipRIOHEwlp1NITaprRXc/0j9Vk2zxDW6xQ02YUk41w4uJYBKBXuBgr1TmRdKNfLieXdEgFZpqQnjAUcQJRZHY4MQaXO2gzKWGyJLKxDe7f+qqsCscY5JQ3F2zogC4Sl916TEZhX6wrZahoti7BFFOw86Sx02rtW4jatvbkGekHBoguKZ7jp5uT/GzDUEEM/gm8rR/iwo38WDljTZKruAmcm4kOWvY/T9Nhjj+H222/HAw+8BbvdLbCCagxOi9nrZb8fQK+jprjN9NPWszI11x+onOFWcLRAP7XKmncFRZeTmrGve9m2LyjzDAYwz3thOEmYTsoJVAk5JZkGH/U+Skg5IaeEKU3I+ifDPVl9GyTnTphk6vwkw6+UE9IuBVBuni3u+h2CTMnqOglpIqRJtAxfwV3PadPfqXmYWEyT6AecmrFo9XPVEKOMsGNr7XuTbbnfFhqAbvXfTg793HZMf422bdQkPZ666dqAMOywjTl+r6izRu0zg9Y8y3aeUfYzSjnFXE4x709RS8G8n8FlxrwvzhzB8I7ByocL+4rvRDJtnNgWUCBhhWwBjJKWgbyfxFkXfZYnzVXkBAK3UWHSlZQgU99hHhREQk6qSCQMCSTlCG3T15k72DJbQJ1Fu08eQ93qil5bl91rfLlox1f1WaWXNnnFOimf9u8aNOs29N+7zr0ZRb3Nlr27PTLPangkAEVKiCw8rBEm86Bpy5q1SKGtDnbRGXWY7qPdapEO5fgyX8NDv/WDePTRR3HbbbfhUDrnsUoOpzgc735H0LDJHqkdY4Y8Y9+yvTFxD8vp+KrUzyQHRlsV3UItEGssZG5AxyyuRUkqdNXhns2SRAUoiXGzoqKQeK4SWcAdYRCmz9Uk7INY1suptQUE8spl8ocCmTwXyWIBptsrGJBO2QZRM3LaKCR+kg7DEQo8SitE/XsAQB2Ioh1M7asd2x0S35OVqx/I3aHtfa5ere0f+5DQQbjbl13UwNtcLCeAZ3vpCt61KuM2W4i5WuqkmlR9co0vikDir+0VyJLZ1UK9M4lB7NaMpCyyGlhA3neFxs02tzSzVfqUdquwcCIpA0lhlDwWjtZdVGWfGQ7yNqLri1k7HWr1zyUYGw2pPuFxx6m94CYxST7awE11ySasCOO3Ec5QaYi4W3tSS8H3C/gmDa0MWVdTh1jMCUis7S3KTya1DENyhHABVgpBOupdAlv+VuvhgXS+gTs05I5d+/Bl+O7fuGdfJoEkwIfIBt6MoHFzM1AZ8JXaAJDhi2zo4pF+rEgKDJ4bY5Hsqp6dALBNIhC/bxvqV89kAVVyL4WaCMAMouS+5TbIswaNCqScPUiUdDYVFlpSjFBabollOE/J/ZAFBcKw2wyOgC86zymANqEF628tTVmTvoGEMAxFOzBFnjukEeg5smM9L421f+NattcPHa8VGp91TMaoVRLx6HoVwE7AW9z21GCVbDp31QBVysKpiDRi4J3UPS1zqzOWJWJZFpEssxaOldpsXZNhCOC9vn3TTdWLo4KR1XOJUluhyECX0eK4i7RQQWBf4MOBHwbAfblGPdzDNsRDeOWrd4gKymxEiP04AcgA+grQFN45R62aNFonyFuNEJsSwNZGz4CxeanQjcV7wDaEOqvbEwE1zlBNAvyagYFAkHTeXdn5RWH4pNDRgf1Z6XwDdzCSNSCQ74ANSfpTTKu15I03cwNv67VtmwG94YLVN7PUkzTmarqnNihzwzIaRJWQMlBULyWVJwDxHCGN3zvPRRqC7q/ESIkxTcCcKmoqyFlkkpwyUprARKg0A5RF8pgScsqYLlUwZpSJVHbJumAswTxckCFyjco2nCswSWfCCTpCSB4ZEDkJ0ICbF40FjbLGRWiav/lrEdDCyLYKvTRGpkWH3I+E0A0x23tznt2xrnWJDD2gcANsqRfN/auW6ozXhuuYlekVk0aCv2ARY6VIBFX3i1TCxaSSGeV0Bk+zMHZm1Fk0bVTyjoJOyOUKLgEQTcIwrzn1heNaQUgocwF2SYfjtWPovojHTmV3IrXbtAkhDW0MUFUuY4hxuWihqUE6GuclPLZJOvqpXjEysaaNCkzebjp0EoJTJSZ5ylk7ghW2zAB3MzF1ijtmJfJ2XJNMorwhYDmHhYebfaHr/pVQxQ4sJ5muf1pmtIUjpE0zw9s1kY4P2PR2K7cA5E8jfYIAdxuudYkioEvyDjEAtLumaaG2oDxobAu1GWBs4g2xutRBK50MQ20GJUNeWK0CcKXOykjhOiUgYVk5MSrP0qB0cgx0yrvJKDkn9d8W31/Keh6pP3YSRsAko4CagJIgjcEAM0Pcj4xha2hZVpc9zuTeKKwaPHISKcU9TeT6KSfptHxhYG3I2fgIwqioySkWRgDx3XQSSHNFtHcqHam/2NZYjaFR/7uvB43Rez3ojmNvrBaISauPPIeBo+vYalxUtz1n2KaRmgtgVQlEfYZRZx29FOC0gC4B2BNSriizxR2R2ZTEJO5tBnQMYCJQUSO34eus9RRic+C96NxuNOZ2XcoC5Ckn16uRSBagUD3b2QlDQvuysVgGsS00zXotradJ1lhUhHL3ulC6AtpBf7e6kM27QhdTrrWArFPX9gRrc14dVERhC6VKYBSNf94AXvojGYVUZe+litQoPuShPnlcE/Pegj57cZbAli+18ZRSkbOsnEOWOx2t+MhBMSPcyt+pehB4fbwOwn3OgduTvjyOQ5uN3izqnSZjGMMwvbsRN9kWLkd2vB5HDPeZ9sbk8pvKImqgop0yqcqd8bNSdYs/A/0yVASfsGMaNlJCzqI7FypIxEDKsKiAHn8iwQFb4qFYT6+NIMkIAESoWVY9qQ7KBOQqK3knBiYdamZj1nKOLKoABX/r0PTxcwBqKNy67VW1vc5IzOEdAubZYuW0plWb7cG/d6mV8ZLVD4m839ZGap8KQsXuJfXBwxsokLeO38C0CnDrzB2exX5hMUkY7DG+PdiYzh+w1XFQ4J289KShrtZGQrmKhsu1STnN84O8bFjrAyrUZTC3UaHeX94LpBPnNtGEiFSeaR2kae6mnljAq7hIgxElkxLlh3zW8L5sPdDUadxSZ5ouZFp4eMNBC4ceL0u5tfjZcIOijD7kvGhsJO/cbLjBhr0cvdTUCKyeXnb/+LmQ//Qpgjja7X+6viHnG7idcYcU8do1JaBD32iQtHKzSReQYz1gEPWntu8CUl5JTZ9Nei1jWWHmI2XqPAbkQ/4p3sk1lPUlUj9vfZZiUcoYyphniGuKSjQpgc3bZJK81URIyqzZA0nJZ0oJNemQLScFYp14sVNDlLJncUdk7QCUziXShRaUtU/GBGXUYKBNYHFBs6LTQF0ecY6CgSY1qcvfEULZog0xm/uZvRvrwPvGjdR8Z61CtAbDwUZhL9suZ++JdbkxBu9YwK5C2PckrpvQT2fjVAXAE4OLTl+fjamzGxlB7H7iPCtIJ7Slz2rVDhN+T7fLUehoiJX9m3FbiapCn017Z6vnAS8oQ+9D3iaS6ejtVjKKK+yDXI4ukwwBVftNML9EL0d7/6aJy+o+pN+rLNSAyNhDp68aeJspSX5t8zJpXiWsy74RKs9+71pnkC9jphJWqTrRSEmDuflFqK1NQmFDdH9261hCeVIrf/h59r66Ags1nWKtPzOdb+D2sCP6cn1szgiYEFIEbz0natsKHLDLqCTCrcbB43tYY4HNCKv+3eIkV5sOndUjIzIMm72pRklOpAxEZ8DZvcDCQkhmaUrgooKilyM1LqYk8oZ3Zpk1OmFBTSn4Z1dQykiTGrFyFSlEJQ/OAKiCTcfOxp71mpR0liCEsWWIdJKTSzG+liYpKBh8GIN2PZC1AwhsJDBoeU/DOx8MmEwjA+ut+j6pyN9/+OwAv7HEeAyjNsOjrYJTtPGWNnoyRsuF28IHCrwFM2rW+sHaoZdqSyXKb43KSCD3eYaG7HAPHO1bSO0pviqPPi9XgCbZoG7httyiuLSpUZVJV1+Kj5oCdKjRGQrebCCTkr7H5EBqqmHLn2Sy58GQ54uLyhBEy4cxdbl/KaWNCOO7cc1MlWhdlqzdmlHqrNcqIS9QIDegtfpRPFgUq0ugdU7M9swFRISZo7+25K3p4nCd3jqN9oAcJJAG1F4LuY0wr5d4n2/gBtCDdr9tNaXh0747cNu2AOBW+AqyPlykBtSVmvGlwtiPGiXMW8CuUa2iGsDo9HZl2mT6ui3TZ7JKkqGwTF8uCp5Jlk9KCSnJtGBnYzr1W+KPyDC5khzHKSMlRp4mAZoEl0EAQs3FJ9uYLzcnktgruq1mqdhpygBV1AzYSt+9O6AO021DDpU7NzYHLSIKMlIP3OR6OazsVmSS6MJnbow2K9UYaCe7cPsweUSkEzVKWhiBWRs9cVuwl9n3o7C7A8oUbY2ABxmSV/2MBmyznaCQhscFqCS5VmIxJCuIu01OvZYctwpkdR8m8ULRfsWYN9qgTYBWR1mp6P3Mt5rgBsZaNX6I1VcS1mtTtonFc8O6Ols4mNRYaSMBDEA2JpM6KleRcOrsS/G1blS/mQ7dXhZkabMGjm5ngOSnZSHGLmd47JWUxJe7yijJ47cgSjXc1a9ICinQZjNwQqUXXfBMR5Przz9e89h0voHbdNzhoRfGyG47L8FbWTSIO6CwFbpHLbwxbri13IZBnAPrLhpLJCvYdyCuQ2aW+6pRHwB8adIEFq0RDGTVlLNY7QvY5ZxC5McmBWGeAOSEkmZ1H5RGmKYEUBawzjJ5hxLAmXUCjjTMquVKKq2Ibi5yi03CSW7YVP/brFRPV36Hdj5SxOQxTgB4AC1n8/Y+GAKy1kkCQQfnAcjhnag3LqMvocOz/eLSGDrRdqZIWUhN+op6KuvIaYJo1aRD7QRn4vKbXduWqI4SohWZdRqsHhskNBAcpDGzjFggHTQKZJKLsl6pd9U7GCQpO5qgwC6jF1RIICydlCPSQ/V3iDjas0YyEheTJYjUfRVh1iSrjqd1Q+fN+6QYY7X2pyORwkBSomKDCmZh0ILbkl+XRGBAKO/Z5RxqHYYVRa2zXs/AWzyzxGe9OVKb4dH16yjFsfl7y/3M9dFDBriebWQxgZzda6EFTdUcI2zh7n4xY/iiwXItXJeXyScEcC8Idhy7hQ3dL2N1YQjk5WrR1ZIBtIKsf7aAPzIctm2qZRrjCg2wgpVJs1dmoFU084BRKJB9CUjUJr7YEli2UIKwb/XhpSSad0oeApaSGKDijEnOErRHps4rdpC4HXLKAsYJSFkm4Pi+DGE3iUA5i6eLdgScWCQXgrLGBKCq0TK1dwUow1bQTgFI47uL21iBPejZDhApNl724a50pMaZ/KJdR9IDtzLr3OJJt0Ve1YUtoUWUm1g6Za0nnCRes/jk60o1VIShK+jzbIG9uOFI0Y5sJsgCCwrQM5pEkUglGq0XmYPEBpVHtH6YsdDAngAqLEbiqnVGWTOxgKlIeAJCDlKExrK1w6cq9VFsc8YyyCUxIGlo1ND8EsRt0qUK9mBNrNP0zdcc0BgnkAlngDBVshcVmLOPilhKpckWAtjCsuU+ldU2gzar0/Z7IUHuC+g71s4ppeTVzt39tMNxjSNUpRZTm8MfeUfh0+sDHsU6Gjujs9L5Bm5Y2Z3VU3E7xoBetax+ajt7G4+NfwTuqowrwLMDurQCnVwhU8x8hZFOOjBmoN+TeQ9YZiCWf0oJFpDfFqRlXZmdSY2GSR0TtCMhqgLkADJJBRTfbhLtGlWBWrqIlMVIaa5+pOCfsjTymg2w1Z97AngSa1k1Y6cxP1IgtJXktWOB+WZbGeThMzA9P2ZD1nJwXQFuH0bHfdZwkyJmV12M+QaGDQWnKjNVazGw4aBns3p/6CxJA2jVtT3u9oywgo3WC2fYymIzAad93USFXF/9xb1ctG5SpTYrdwZgM7DsfDTJwiQPZvFJF5tJathiRU4yMiOIxJcs5K8dl5JMsfd6DDWiUpuIVpTFRj3b9AojKawujfYuDXRJDZOAuOxpHZL3LdPJbakx1l7LwRytTVnm2j7JcK2z+1fDJZZmCpfZphUWwrUxbvaOTTC9qN2VkVNyH+2mdZOXqbHsHqca847pWcW4ZbLHOrMGQiWLQysrtwEYbFUXG8p60HprmGSNMvxBGqFEdivi+VEthonBumnI8DDDwlTkumRMS5kHB3AqEK2RUpWZkiR9c9KV4RMlzDQjpQzWIW2CMI2c1Cd8ygIcKSNpPG7TTykbyFRUlURgMkiaxK8bbTGIRBJGNiXClCcgcXMLNF/xJO8kTUkrNDUjYtKXQkC/gHB4aTrRIwKzzfx0pgkO713AwPTGxCW+ba8amU3v7ptOipKIA0BFsvClgAT+J0LJ6tecCHUy6QO+ejlzFeOtLjnGxKhlhkf/AwsLrVJnXCYBgD06Fz+vfzbNfK9qCMhdBk0LbvKLAjjknAaOQKYkIFtlFLHTdU+JxPc7IWsdB2iX2oxuvY6XmeYnqZ+5L7irdVIWQgBMsgLJPbnU1gFCWLes2UiokE/SAvB3S8aKBegrz3Lv4KJnPtj2NkvZ6yiijSgqZo1zL+dI+6NWNhoS1vyyo+SGDA8T4DakZBHElZyhny9idbQRczuR9f7ccTk74th07oHbQ4huJK03i/Psk61D1mN8IkcEbmqgisFLgcHaaIssNcU67bnINGZjgKRMlKmKh4GyGBv2W+Aq6Avt5IIk7lKsftYGYpS0wSWCrBhOgnmJkDKh5gTSITg5S2eNo1KVIbQl1kAQw5DGzi40u+5tcclrNvYKlEn0T2TTyUXfTimpV4XmX8Ef3e/wubA5kDMYf2UK/CkYxBIbWOkWZVDJjViNSYKBzMb+Sa8VunhjhGCQBy6Sv8wVMwMVhIlFqyUGuFbMIA09oPVFp7zLOoQskkmqrXNimTBlroHIyqq1vnkEvn17x2yuh9ox+cQwKDDpQA9MsrBDhca80QLViTZGBpLFf/bFqoW9i/MSqUGU3AXRwdsaS/ykMDWc2bXjVqTsa066VFL7uu6LBWubMHB1QNaOtEklQO3AWr1s/H1q5+p+6DZMsHdahpFGmyWbiMGUwlyKBEbxuthYvJbboFMb0++eqVUyf245N9ALjkPNs9P5Bm4fFlpaDj/QVLL+MDfGaGXL7U12GqK5FOnkCJnxqOzKvQpKY9kmq+hIFMyuhfqIwHQ+cJ9/JUyWEQJ8Eg4TCWia0STBI/tJ5WKkLDMfWTVpNqBNVXVuVtlFrlHSjJQmaeC6yIFNoqlZjGkyIxOwhY1zmnwZtpqKAjVQp6STecQfHNCJReYOGEHavU7sk/VVmlGLkPW7fSZjYoEdJ5TW0LVMI2h7SbLZCqSA24CrB27Wa7pGytUbOnFy7EosHgvmK1w0KNPMwKySy7wjoBbpkI1VJ6j7n/6ZhS4BmNEMf+a2N7PIKdSeyDsi7Ywxk7oactOlE/nKPMYyiaWDcG8NkzVsyS/TrAkilZXm+9785TWWoK74wwr2rEZKi45IIAfratPerd4zhyXLaqdHa3OEr+pErPFUDPStuTBasCeHeUQjZHT788YFAoVg4VJvZHRGyQi2HqeM2sM1GKHyKzVC2Msg1st5vzbUxnYsUdTQuV3wiHS+gRveuXcp+kXGXs1TGJobe6k6+80AygHY+39dnYZ0yMsSQ7mSrcJdnX2b1hz/SdQ98cU2g0yMkOfBqSzfUfO16ejE7uEB9YEWLxEF90RuvIyfcWq7aOLsBkeeqnigKHMWTZpQEiNNJLM2FQikQstsS84VNOk1khgyMZE/u6C8ll7SoFnW0ajfdlKjYOIq34kEeImQUBuY628wO3CTTne2EY28Iw6yR3zdtWtc0l/EeqHfq0WEAwwsInAzKgoLOzUWnqrEooBNY1ZAn0ByDDFmNSgWAtrCwXANGxaF0WKRBKzhBNAsZYgE8eU/VWmkKiDrog5krdmWUgOr3EHuVkrmY63kxBynoDMtWUcFSWNuNB1bjjMwF4LNKjdYP6T6trq7sj8EtZme2kGYD3Oz9QA2CUvOq6jF2m+QstzdMLB2eWgFQgN99MeRgHYcXRKKMF02UG/hYD1Cp45oS5XtPl1e71yDRu61MNRLLwNtzA2b2H/Lo1E47ux0voHbFngdEocCWCsKB/vgHy3Ld8kZMca2++yioJSCosuIGYDP2INVvwQBJalnghmprAGZUaty7/5mTMr0b2Nglld1oWNi0ImcWJMamFRflkoJXRknAXkW2WRXhQlPyUO0it81yfaUkHLV/c3zhHJSqaUx5TQ1j5OaC+o0I087mYSzY9F8k0QqTGr8TNppCggTsg1HS1WZQ/YJsBKylkU8zxg3KbtO+m7sdzT0EgdnZ0ijzWZQ0PeeiTvwkfsEsNYDo1xSdLbrzECphFmBpzBQNJZHYcIOwr4ZFdeKePcJ2EtU55lkFDInxlwBzgUlJ5QK1Enc9mgHkTBOIUbHPbuWjj10ghNAlcB71nAICgBmrFTDpy8LZxEnIQCeqq4wXnThjqL++pwksJjZ2NXlLympoER6XcjIxepsOKfqiAEqu3BK4Lmqx0lSfV3eqLnVmbTEXHXlc5X3qsl5bSZjVU1dUvVAVoLFOqpyAFYSkBrLlw/pGVuQK4tVkhxIoQxelkOr1uW7zFNhMk9BXHasZ9jc7VM1TlM8vrkNHpvON3B7WsJzK6CVfVaWbJJGbf67QdsWgFZDk8ZMZgVsYdgiJzijRn+uu24BynKqMCZwM+TBmKgClBtKw0tUWYQ0JgiALi6ILXCAicU1Lavf6JRl3csdtVEGwWUUiT8ieZLogEmmpts1srFw1eBJIgeK7p1RE4H0ngkkbtwQ4M7qIZMVWHIEY/uuGmQCIwe23NYzNl27OGDHT6DppQLcc3uvWurZGrl575jBCoB4UJiOKvVADlX3QGVPuVbxaeCEpDr3zITE5KFs7PkNyNucK4lZN7OyXq4ykYUZM2RdyEJ6LiXQjjAXDdNL8l5wChQqjY1bbJLE8LXpMou27ZOg4CFhaZZODExucDQPJlYQjr6wBIBT0UBX0Hjw2o4m0pEB69BWQK1CH3iWl8dsIMlWodv4k5t7Hkz3NqaqDNvDGvutmkxpkgh7h6vPosGepA21DhyIANlkjDaignuE+OQd7QxM6oHFNoHzBbsymHvm3OKYhDbueQgdbddJxM+z0/kG7oSmUY/JC882BBZuddRifDC7axwG4G6z4KpE+mORR4qGkyysQG6+vmY8I3hFNYs8VNWoNiwEFMBlqOjD0dFoBwFfhs6kA8TgZUGf7PyM5r2iw716QshhoVtzK6xqMDNvEPMRl7gmhDzJJB1MyfPNqciwPItslFHF95azTrvPypoJiRWgWfVlpo5dO0gTO5gbiCdIw47ATapVts+5aa/Q50XxaHLyemdn0AC7gbNx7XY9OUwlG4RWZUauSmBKmECoCuAFArqAAPMM9UXmisKMxElmqnKV6lgZpQI7rvKcTLK+CieI30/CTBNSrjilCaCEelplbUqTCNxzxMAP0oo5AVMVdm0hFtR/m6YkGrrFSffnlfcjiwiQtxWZJq+ugTq2J4uVAq0zMllW24yWKMFlBMCYrMkiVcG8usdMLTaqKbD1MCUQFEsMEw/LCAA2wUelSGXErPPuxe7M2vU097tm1GygvUw1LBMo9yi6Ok2i5HKKuQ6Kl5Ru6+SOJvdY+fayCIUyEYO77WZ7H0em8w3cBljdCKMVlml0q9tNglDA9ZlwBvgaeU+AWH1wfWVu88sV4AYqaCKUWuBTmc2P2w37LIZBIp/SLd4dAqiJzAtBu37NEzIsiqSHcSXYLEbIvW2q+kQO4Dkl8ASQRRCcZFYgT1Lp00SgLKMEygl1Ihm6K9th9eEm07iTDS2rSOblGgg7JABTIqSasFPhPpPEV0lcRfZgAehoaLShbeKKidT4yKZHZ+kUFFSNXSdUoM766m3ILOVMkDgVvswYgneJ0j+yWXPawEktfyadpKqgTQRbWCATCwhTUiMkUCFhUbNKIx56lOGLZJxQQjHphFjBu2I2pk1yncIivRRl38QFXCeccMEpEuqkHiA2lV2Zp/UvDBatnKQ+00kC9jJCysmeRQDbQJx0en0yC7r2BaZ/g0U2sdmRto8I2JeKbCZCgrsNuuaeSGY4ChI1vRfKWDWAU6nVTToM6KzIYDg0bylnxupNNbgLMs+NyWqdkhEPBfmEZGQc2HnrmBsDrrXdM4FUMzcpRjuOCK7Uzm/MnRRjbIp9w58Ro2ol387sj3ZUOtfAbS+1d9UBFiDthROGh+YtohXeZzSqZFK9gasvLkRPtOk2SLrfp9+y1oXgv03mow0FXD1GgZDB7s5osULIOhVAGp2OKpCo+fuq5OGTVybNS1KjSobMalRJxGKctLUmWeKKJNkmk25UK88Aq7+vdTSZGakypgRQTchK9He1ICE5eGcI4yZkpFrcsJiF1jnjBsRWmnX/pENcAXzp9IyBkwK4eXwkLmLkna/p0LaAwMhJWFfiIlKOxWc28ZW5MXA0I6elhBYDWwyR5MCfKWFGxgRGVZZsbDnX4jJIqqJEFE7YVUY2YGYWwyeLT77MbhfmJb7lCakCFRmECuYZM084gUR6PEXWOO8Q6csWWphZ3r16CwEiY5BGbEwyQwupUA8KQlZh8UVspBccIsy9QxllG9VNyNKOCrfwxVDA1vZlerS1SeNOkYnWWoXoMPtN7bu50rnrHqA6s0ozZEy6nUva1hKM/KBdFwXN+m/JvIcskwYizSuJPRa4tlVlxq1Das8v4G8AlLTeNiLouo+NktBkVCubZw/jtoD19jsyb+0B2171FglgDQVXAW402URduqDfBbQrikokpm9bKEooy0bwtW36tQ68rYKHhXrZnGeTGGyaTzo3hms+0BoJkdDON88SA27zryZtzJzJgbtQQdYZksm8UqYEi+HNpqFnYSfCkFmBWKTNrJ8EwqRAPDGQWIAnpQkZhCkJPRSgNgmkIunst0wVVGxV+6ZvJ298szJwAnFxxo06C9MuM06feALzPOtiy6Qr/ugK3pXURVwaS+UC4r2AOAMZbWq7MGsdSSBp3A3SmBqtLmWehF1DmKpENtFp1EwC0hCJNzFEh4YtvCuyQNIFfLkKkMoCGhmos/iDo2DGTl4tKvaigcgILyfwJYD3bdKI/01aL0pQ77MYH7WiCeOEEgFrF0Xrpy6HJ/2ofBfJh3yNSSgWcgKoqBxi0/dZPGmiu59Jhx5z3PIammoCCUFy0DKm2h5Ooin6QdLhaofuF1aWixDnRF+b90nm922jSCuppI2z6CxZ9xExYNZ82aiMHLDtu5Y4AR7DBNKmtOX7/tCF9cS9UwyOS+cauF0XRj+CMbhmLcBmIKzOro1hND9t0ZuqzoiEa9VimKwaFL+SXbNNdTf921ZBcS3ZjC3ZYkAoezH3LybX6GmnlS8DgMkp3HTuiXzCis8iRNsWWThn07yF0cvMRojBMaF5tbiroFwvTcKCExVkVp1aOwuJ8CrMW3TpjCnJtlyBlBKmupdY4LV5iGRSDxIwiFuHIH1alfNJdG1AGbOOWpKC9WTeP3UPLjOuXb2C333fQzg93ePypUu4+eZLuPWWCZcvX8LJbkKeEqZJPSZIgBtcYMarzDXQP1k1SGBYq4VXJlVVuYKQxWdbzJAo+qoKk24nmYUIMVoC1ffVeUYuADipHJKQwKicwDWrR0pGQQVKAXMWWwpXVM44QQJRxj5lzFMWjdhaLgsZEOasADyze5IoajmCscZHIR316VRMxb8ewJFtMgm5xm3eGRZcSozW1RcLEVJcdbUbPV4XoXBgN5CH47GHWJVXwv5wDJWPAHCdlQQZWFf9XXR0WsFIPruZSPLXDIkuyo/9iNQNXTrQljUbQKUxMG4AHt2No/ERyAGsI7O2mCkN9Fs6YzZhSOcauMfhBjAOOSLrtmPNKAgfAkG9R8DcjIussxxhgC2Tlm2NO1liitWXW1TvnHSNPzMSqh5pYSFsSj1Mj9TA8ciMRBke60QZlPnUCrKwepYEoIZKHQbwBA0kJRWbzbc6a0PNLL7XWvE5VVBW4yASpmpeHwL0BroTIMZFFikjJQYVMdCZe/ZUgUQZE4CE7EzajZUoojEDjWFrQ5qo+DG2ncEQO+zsk2+47jHvr+KxD38YH3349zDRDvspo1xKOL084aabLuHW59yE59xyGfnmEy3vgp12klU7BeLWmGVSjlmPCZMzJbFLJK6uRYvvjBonuaLacj5MIGrAngCZ9l2loe4q60QdeUIxd4gyXzlBFP2MxAS2IN3i+gNCxp6zx5OuJJOdSCfv8KQjLGZdgkzcOb3+aIAqiwooniWkerbyWla7SVg8wWggQecPGBsn8lEpOW/VumcjkJQkuBWgXj9oQbsY6hJoMyq1TbDhpHn0NPsE+UhYsdP1F5MfVZLkKq6L5kGUPGsyElO+FqURedvVuTEPf1DJo9FilUS8b1/XsZuHSsOh3lWwncNsuRz3badzDdzuxRQTeQ1Qu4F9NyMJN72YWQG2yjJTCeryx+6WJGx6hrkhVQNuqspWFYfVoIgcJiKQzCqE/SnLbwGWtOdWEAWgbF33AbBlwpiqSCJj/GrzIIi/J5VdiME7vZ498wQ12kjDmBREM+9F8oD4Tp+ANasC3DZdPIMxsbj3ZW3MOREyETLPSEzYaT+SSAx4k3oBGCgnNTRliKeHb1cGXrl9dz/ZOqOUa7jy5CN46qP/D7u6xy6Lzlsq49o+I803YSrXcDJfwq7ehJPLE6aJsFPfq4oqOrdrsaqJKguajHnCDFTSgZQqbLyaos+kpFZAOjGBaaf6NmEGRL+tUN1dzk+c1LtEnlYMnlIGRcsONGGvk32sLTMU6MDYab8y7xR4KgM7nR1JkJmWrITBtF7TqJPWVfWg8FgxFpMErR67lCNDDm9LZITAl3KDdlxSv1gBG5lEb6cASCssuy1fVrtOxAhXBG4lxF4uZj8yCJBrFbfNSD3SK0dMVC8YM7YDGrpBO6J2qJE5Lcao6dv+gTV7nO/wLDXeG+p3o0Qhgv6zTuO21Ea47C/YNW7FbJtKaxXRZ07C3Ix0Gq7NioTOkKzFPUjs3kyMYnqcuRZaBYQBJiQjzeHXUK0NWRlSK1zusH1oUoi6YAEs4J2FNSF2DNDPTPJmVf82SUhiUcw6CUWeYyLxdc4EJN4LEKNiYtbLGoiiyR8wyZ0F+DkjM7CD5EkMdQKESacOT6p3G8vOVQArcwB0khjKO8gEGzHc6UKsPONaeRKnT3wEVx/7f9jxNeS6R84JOyLwPIOvVsyccWW+AtpfBd8iMgrtRCI6yWbQYi2q2spWn89CEySPawLsGcqj4V2MuPqJ10gBoZS9gKKyiblKGSQG5irbEhIyJUyJUFgkEmPZrMbKHclCk8xi4AKdgKutdK6AAAZTxpwTahLvkRamV+tZJrCubGfT0uVRyYRdiZHC7AxdvC+gro8w2ijPbnp2MjfH2u7VilSBqsUlgdpT1DMatdhkG+W4bIwzSC3aUZkB0eSIUpquTRqUCiQzJikV8eipVcmcZEomKbcZk6RAIeMdakCsIwnSa5gMI96dqrOb1GlSChEclck6JB+ygNmcIx2Y0Gi/GXADyTwet883cDc/SaArgPDdem3r0aoNcwy0oXpbUs2aLNKfhI2qKKhFQ0jVGQxl5gz390YSIJU4zHDvEHfR0nuRAi+SeW9YYHj4qiS2cIKtqC4oqPumoUMgaBjXJqG0VW8gFYyKMl/ji8KgwbNAUE06UGf1u1bXNSo40WvmoE1nrdxyvHiCTDgVeaQKK5qUrWU2GV0AXvyFW0dgE2l2VKRTUKBOmpesFVu8Svao9SqwfxypPIHLaZZodwycaJkQ71GvygSWq/MV4NoJ8ukl5FtOcHJJPV7I3MRsyrwYyTKpgVhBXHzClemBUJlQkV0ySZzVUCmGPJuMQ7qo766oKyAnZJAHqSp6TkZCpSziEBM4ZcyVsDc2loA9z9IRooBpp+A+ozKj1ArGDpiAqlPlk8cqAYgTylQxsUR1rEU7ogyPd22+/czw9VCpSvlwtlVwoOtPCugUm5ACrYOmX6v8Rgb41j7NUMnmAy0cWOQGvQAA5bSuoUdNXCQPA8TaJA1171SXHFh8eY9zorjAgLiDJh3JaDOsidx4nMxqC5n52mwgMiJ2Jm7DBSiG+OiNHGMAKwc7dGDldt2wra2zeVw618DtxkVPZvFtv62gLX6BiAFz8ByBrlyif1wBnS3JPKOiotRZJtyozm2CWOf3rVIMJb2eyjCUpILo2FvskTkwkbBoAyY7TiueBngCGWO2mB/6WyPxGYBbmci1ABBjx0U8P6iq90PVGY5V3e+AzEVYeC06q1EYN9eKnboY7gg+qUb8s7Mcn4R5Z95LB8HGyElDl5gkosxeq+sEUsZdMbH6ZqPKNnULFKeZAtQZjD3m+jhof4pd3WOivUe/00EFMhKIZtBMKCXh2n7Cbt5hKjdjuvky8s1AUg04q/tjrRU7WcRR5QYCqWEwM7kRceYm9hQm7Kuya32pRSqDeJMxoXJWMJeuSO5FSJxl8iEIhYsOv8UakInAM4FoB3BG5Ul8izHhBOweEwyZZbnDjHnaoZ7qc50k0KzTsov6cWsck5SVUxsLB5BmNWqqLSYhi8QABop62SS0MK02ooLIInUu8EkpIAdpIo3jDqh7pTLoRKhzgUVAlMk42ga59hH+GDq7s6AW1ZWptXE3CjKDC5ASMLOENybV5JHUsKyeJFVXxWnaCgCVlEpi18gNpKuSFNK8g0V28YiD0kw9H1Ib1AZgAzbzPrEOgEivq2Cv77NeB2hbnT+3qfmv6m/p7BojEO4qv63SK6D6CtXJ/LQt0twMjUwi/0pBUQD3uNpqNGSSiQ5J5ZDGhNlXbXEdPkPX61OWrK53Zsl3du4xt1UaUX0y6dRz07jNK4DBzfhI2h+gYGJZHTzzrE4sFVMATVKWneqpAq7pzWLAEzc/kTKmCmR16TPWPfGsfr16XDVWLXrhlJOybWHYEynjBmMimfJt94zGygyZui7iQEJGAWFG5VPMfA07/QP2Ll8IcBMmykjY6xAVmMpV1KsTrtQrwOkl7PgSLl8+wSWSISzp6CaT+egyyIxo1EBcJseQ+mTrC2UCI4kPdwVQSUc0OmbghIyEmcS/Xfy/JWZJYfHPzgRMRJjrrJ4rCTufxWgxcpoSMXHSbQz1XgdA2E+TMO29gAM0gBV0Qhe7VAANWyrbi2630buREPNnd3Cyxaq9nelIyOpzBjBb/A5GsXU3q6yiLu2y+Xlb1EAD6Rh/xACMNDSAeWKzI2Fg3tpByMxHlYsgoFlTBVncb5VToCNqY9lM6ktE4hcul/fJ/Y3/Od12WAkYE9g0O9rArZHOzpsh110K/ZxRPTg7nW/gtlELoRU8gDbkaEzbCzUxPCKOgravIWheIhA9u/Be5BJqoO1+oq6joRlIjRXYpw7dzOBosor4VpOy42BEMnkDurYkoJIKdHkq9mtaJ8HaGD1QE1WVGioyZkymT3Mx6bwxbui0dUoBPIvKH+z7JzAmZR8ines9dKahyRqTQslEdg+ZDSjgTKqHq65NNrmnYqKiUo4Ct1ryRRMvIBRUvobTcgVTvYIdXwV4RuKkoGvG0Syug/puUq2g/Sn2e0Y+Tai7T0JKGsgoFeTd5Oe71snFh9PZjZPwSTeJCTPLd/PTFlMLuWdIRkJloNKEjIR93aNC8ldAqJQhS5zNKOoiaEyekDHrc6uoJe+bSUeK8tIria98qQRMoqHxBF1ijB28ZQQoVT5JsHaVDuCgLQ8ewQiNPGgbo0SqSLAYJysaKeHWBlz90PcPQgvMVLWxuqwAHw379HsEIIMyeTvWuzCbdANn6TILVzs8FJF8lBITGLOu2E5w8xLA4k1GVRdOsM7FPEhCZ2NlI1eNYRK4lZV54gQENt1cZCITb6A+FOHa4fcx6XwDd67gKWhiBqRdwZkRRcGZWc4zLZslxl+hvTZTsfCXohNtyIJHoZdBzNgn87VhsxsBiIatoCzWfPbZXGki1aCF+VeVK2DLknEVw5JKIQCr3FJ1RpwZ8mSon4mRWXRhgk5oIcZEVX2yGTsFAps0I2BTkFJjv+bpQVywI+AEM6gUBUcB70TqeaEgHCfpJK440RmPYoRT46RKM6aHW/6SHWsGSr1Hx76JkHgGsQA386O4hR/HrXgStV5DQhJfckrYpYSdMq6kq5mkFIblVwue+sBjKLsT3HzzTbh0eSf+3rsJu0sJJ7tJvCjAQFG2W5XRVcaUNCSvemcUygq2Mht9BmGupmUnJGTUmjAzcIkmVI1bUlRWqfpXOKMkYeGVEibKmHGKRDsQJZzyJeQ64xQ7JJ6QcSKjEC4ATyh1j5oz5ksnoEKd8VGmopMDa90DlKsYF7PURZ5JGDJXTFlcGtlcDRXDUk7iw81Sx6kYS9f2VtmDVpEa5KoxKui0cZ39WktVmURGs7bAgksnxIBFZqwiT5ITpOrgJ52WTkUnAkjcM0n1ZfHthrJyXVDEOgkdHTv3stGW9t5uqFSPLusgCBVt1Rx5PgtCZcAcF1awCV+2KLYZN4N83kDbO6fj0vkGbmPU9is+uTFs07gVpN3zo9p3jUOifx5Zm7TnNwZt383zg1UrzNo4TP4wl6XEejz5dlKAJrP+W4TAidzQwurKxwz3IjHXwEwlMGsx5EFlEAHGqr15BbggJYiLnlYcCscmskBHovsRqnp6FNWpZdKDsfZJWbLIEhaLpDhwZ2LsVJ8mJGXWGqOEWPslnUnJcj+CTcopTYZBnGlJIAVu+7MZllBg9w4B+jw2e9KMREzijcBA2Rdcm68JCF1jpF3C7qSgnu6QbkrYXdIFb6vKA8w+YcWW27IJKpmKeMFoJD5moFJW5Y7c9zxDYtgQWmMnY4j66UM52slooBIyFx1JSOeTeJZyxawjpBkZhB0xCmYgTeA0SVVVrZ0vAWTLoelAk8mz0RY+UMnO+CxxElc+Z9xaVxOhzipZVMgMSmfKcABGlmtXwEeVTJCyJdIRrgFcAtciBlpAOwAZIshvaMOpKBUyh8AZrhE1fUAYaQvsmFkcDyq8AwAxbMk2wxGwzZukZq8yZxKTM9AkNcMc+6i2j9hHGgBUQ7eRCXfSlHd+DtzPEsYN2CxHTVo4AODT16FufqzAbDMeVf7wdQHtHynAW8B7M0ZGoA0AzqbxuXufMnP7TiTrNhLLbEiCT84RIKfWGUCvkwBzOSJlDVMEJ3WRI1QHOHO1o+4Tfk5mA2TRr+VWrOA9K3M3qULAYrL7UglyiEZfY0JOBtp2D+1UuChLN0OlgrEyexsxZBslQKQSgs2yTCDSsKIs09wlTkmLLJgSmtxCMp8REHc71l6V/DmViWUAc8X+2h4oQD7NqPMOPAMZk8zMq8A0TTLaKeKI7QapABgWhybbyCfpoN69FAQlZdhvSi1gc86NlcrEeKCIwCJyDMSIPukYMCutyMS6SMOMSgk7FBQtjwkz5rQTnapCJ940dkdaH7GHAGlVkDQp20iFdnaY1QVSOy+ujDxlmahWk6+16fMXZulwOBtz1hFxMU8XUkOnwh4pQIPBtgACAPaYIs2/1cuPQ57JgFm9VLTNRqXDQLzqJDgpB21XznCpnaMA2vyuGc07xfwpGzO3dyogrEZdbsBtnUCi5r3iz+HoHRLh6HSugdsNhd3GWChWayEVsNo0dZlEY9PbLVCUr8RtgK3XtrUAkdSZPwKwsWmrTBapzwynFssE3OQTne1Ik1aBBPcWMUOlGBsNlCXQUlbpgdRolAw4w/JM7kqnUokxXgHoqkxX3QNZZkEmLgKytkIIMybTukllFjTgThpdKDO7Hi5GR7n2pIBmAwZCk0AspHiLwV1coxfgl45EXpu4wiWyKcxQaYQ1nr+Vj/lHZ21r2rsq8SYkjbAo4E21ou7FIFhKRTmtyNhh3jN2eSfRDlPS+BUqV4E8aH+sD9CObkqTTqaRuBiJZdHZVMWVMIGdTBi31QXnoOZLVBavnMrkcwTmANQTimrtsq0QYcIs+wU9UaZJ2GVVtbi24X+atS7uhbikKQs7Nhe/1FhvNk+o2kYZrL8FYPU8IzE7fWPqfSEeLMpoC8PmOdh8idZWVf9FVvdLW9tNVqdpbDppWF7tdIhVNhRiY+uv2mQqOSdIKxxYL+vUGWogL4dIx1s1oFXr9LTcdDtRYN3czrXfFeYjbhNxmpuklB37OVGeiTLLWelcA7fOeOg2dQsi6Ev3uAgmkxjjpgq2wFG6ck0pNhFGwZfEG8RHsyQMwvylk81gU827EAOkenSCfE8CHrZoQyIGdN1GmPvRtEPhPbIOW3PW6eS6lFfmhF0qKHPFlGQ6eKlmcJRrJiJnphksQF/3oFoxZZVJUHzipkiD1Zk3cZEQq1QwoSCVggmEKQXgdcmEtQNoUklW46iFcCWY5AGJFpiyyiw6rV6UYOxY9EionplhsSxY86KR+BKDeQ/GrKy/YpJpPzIkTYTdlMEFmIu8e2L1ckni0SJLr02Yy4x5X1GuzaL91ivYXZ5w6+UsUstO3pHEYAcoJSQGylxanA+pXZhyRsWMhITLKeFaFWJLLMZLm7RhHR5p02ZinFZdNYgSLJxCyhJ4Kidg4gwmQq0zStUV5FiiFE4sTH2CeD4BMxIRriXp4UglERAJVSF14yRGnRlzKWq4zt6eCA3VamGkmnQyoviCZyQU7ReJCDUBdWZwWBkn6SxdSuoLnnQalS3wANY2BF3kwVi1sSERLWySDmmgFMG7hJQ0FoqWZCLS1dpY6gGgy+M1gBRWTY7WxrgNRJOu5iPN3uQSA/1Zr2NSiPxgFm8vkYsUB1Q6gmrrztiVqROAStI55JSVTBrUPEuAm9ViLj8agAtjVgB3F53ApIkbiCv4e5xjd+mD6tI6VZzI10q0qKdQyQO6gnpj3tKw2XRtZdqVNezqxH59M4LclAg0XcZp3YtMgOTasDHhzBUnO1Kf4oqTCUCROMZk+jEawyZmZ90UJArorEZhzG1yDbnrYEHiGTuy1eF61z1xYzNJpoH3BAGnSffDgVtnaep3YnGay2S6reQfZJ4kFuALaIsxVOwS4WQiTGIrE4ZdVYqYkkZnrGCdYm4rNhMgy7FVRqasszkJVCr284zT/Sn2V/c4uTZhKoTnnFyWQE3qH2wep81DgGy8C4DAFch5QuKCUlsHJnVGGrbo3EnZZVJmLjFq2pp15uPN6g5ZkeqMBCAzYYeKQmIky5g1EiEh8Sk4ZxBmFAZOph1OY5M4UeY3A4WLRHKcFKwLwZDIpslbZ+MRBifIBB6E0T2pTKjECPYIDPWYorZAchiVWnAqiUjIqOrxYvJIW4hA5DKRSiyao8hTRcvdksSUgbv4MsJ+ff+drQq9TEHaSTmIp+SThmqdYUbF5DKLjmaMuofbWflJXlUySbpUnB4q9v2wkjxaPTo2nWvgjuZZMx+sHKTWZGXayfTsghhAqs3+gnb83H26sdEBm2RbkqGaA75p1u5RAgDC2BORRuyTBj3lnVvPd0S4dHIJN9WEaZdx7fQpGUzzjCkRqO5Bk+i6l3SBWgJk0d4qz2kBoiZlvMK8Z53OLsGWSH213f8a7B4iZNtRMbFIFDIbUCQM9yKprDG5lYnr4gkmnWRlIMKqG/OetIomY8wgJLTJN8KOFbjJJjTY+QVTZux2E3Yp6zT0JgeYNCB6dNUJedxASCWUZHGqKctCFhpitewLTp+a8RSu4urly7g0ZdCUkXaCPNWMzgZWxqDUa0WAWJ55Uh9tVjSbUgJmWzxC/iqkI8iUxB0NFg+FwHVG4gzSSTHJNH6QrMCjfzuSlWNOuQIsC1KKDSCjJALvTO+3uwKGWT5Q1X6DwR7bm1impjvwuCGxPT8Ivt4kEhxJ3DhZofYahdGMBu7V/jQTiYFqfoQpHNQW/2Wu8MUvWeYECDjKeQIFBtzkLnlG26D1xJ5PXqVNpmmdsnnAVJ0FnHPWSUUmacBZtNctLZhoXGzHC6lLxvZVUM8MIKudQ9vvdSgl5xu4xc1OjYfcZJMWBVC9Rch8RYrGHNEJNTbkcjBe/xT/bgSXQDjjADVAZwpthNAMjUnyR5NarieZRZN2CeVawf7aHo+fXsF87SkkyiiZ8Zzn3IJLlzOunCbM+yuYM+MSAagFO9MiS1H3PJvBZjMOC0iNqsRFACDJ0NKXAasC4tlZrjA5ebSq0f2acVO01Ob+l1kn4mjDliCE7J1BUmMkJTU+EsOMqDIgqS7ZJGXUDaQF8pIeB8uHBbOijD1mtRtrvI+qnaiCMxkThMTWoKJ1JLGyKwBF2PFJnjAnwn6e8eQTT+HRaYc7br4FN90y6egqSVwP9xFHAzCLrT7LPsrAjmQ6vriOCdhygj6XWFjIhwIyCiOWxTtK1fU7FZwlcqIsziB2gYoJRSfWEBgzdlRQMINZZpPOmCWwV5qw1xV0mAE6EVsKzdCOTV0li6w6BO2cxBND9dcZqmtr29Kl0cDQ2bkBpJgUV0lcEYMNCBo3XZQ/Za9TUvmoDWtqafYaA2NJWWOG6DYDQZinR2PC1bGAdSKPSp3m1aEEzdT16MxhMeLFs1fAONt0ShgQS4fGOoJukksEb6so4mUFMm2c9JGaf7fr49eRzjdwEzevEpNHANW/AJsFaRyb0YJGGaC7i6DKIh3LjgAefguIszLuAM7EDt4O4mqoZF33kQgSe5sJc5lxeuUp7K+eouwI165cEUNfIlx98jHcc9cn4+bMwKXLuDpfAZVrMINGooq0E8CsM3TGl8kX4g4otxftOrHo3aYvT6x+1sa6CSAUMVgqOGQ0eUPAO7j/RQAHiwubG091GS6LAGiAzLUBOjVPGF9QGNzyDEheNOSrGJV0GnxqICGNVYFTF2cmIqScMO+LThkvqCkhK/M2zJRl1oBdmrCve8z7ivl0xpNPXsWtJzdh4oxaWJg5V7nfRM5afcFdIvda4CpgOlndgTC4XUpuvCQW8NZ4rLpSu9SfpNp/gqzqI2ucJg0+ZT5DVabL60BvRwUSabCxbk7i0VGJUXWCjtxDZAwnt5V1og7rc8loyWKQEBHq3sgRQpk31s0EQZIKj3nSZhiTBLHKFZiFgXv0S9OUdYRqLpfCtJuhsnmaGEAmddEzQy+JxAKW0bcDqWZbQdjj1Chgkho7iTSUBAzMpYPrJRdt2w4Edh1194Po2ax5t0T9GVZy8sdSz3O25x09LbbTuQZuEesas5LEqFQAc/8DN68RLqhkM+NM38Y6QNu2sJ2UfZtR1HWz4XgOnyaj2AIGU8oy8SURrl3Z4/TqFanzM+H02lWZ+Vf3mE8zfv/3Ky4l4OaTjOd98p24yoQr155Uh5WKkykJOOosS5hxi9XIx+JxQMpuzaskqU4q/VMRhafKhGwD2kk1c/f8gABXTg28d+qKltTaPkH9y4mU6QuYA31kQQtS1YyXzV2QtBFKcbo2Ia2vNsCGDdO7IbIA3VwLUk7g2bTzDJ/aXGSCkDEniXci3ibzxMBccfXKNTyxu4pbL1/G7tKEvcb6ACXUuQrjtHoB0WoNtGRLEllKh+llVoZJMoFDEVPqBrODkYxIRG5hJlQS423VOl1BmNTtzP5AjAl7d3ms9RR5J8MA5lOAZcwyn0yy2kxRCcLG5ZXEu4llxi5bZECNLlgTq8GPnKV6u2ElIQniqZIFfMmkk+YQ0pMbaLtJXhTy/ogHTxJyqcREDwtSJa/dtlkDbTwX0E4B5iQg18hmMHQwhwO3nSv+5hqyN6U2DR8NcCNjl8eRvOvDhUwY09DrB607JkLy+OHHpHMN3KZV27DFtjLHSTXhnzJsB120oa4xbZ8CHytWZNto2wyMzfiCrEDtOjc80BQRxNKfyV3omAquaIB37PeuJVMCar2G09MJTBXXntzjyhOP4Y+98I+CMOHKfArKFXWecSknjbkh7Ie4gFKVa0HZNglbJVLWzBUTVaRaxR0QbViZiLGjgokKPGyrugOKoXIObLtNfiG0VXIMkAkWv6OKtqyfmWxyirwziUgq71Fd3uWV2LBF3c7MQ8RtzKQgro1TouRJB51LFYmIEnLW6epI4CLXpCQ5m0jXUKQJN1+S9RmfOr2CK1euopxWPOfSCU5t9MKiGYuhLmTUvms9SZSw0/jqMgmluuBjgClT22USEUhsFgUMW4idtVOqJNEZi3qliPukhCiYlLTsuKCIewYKA8QZOwvKTgxZGI1wOmllTJBgWMa49XHc0MZW9qGcZwVWEecbcFvdYxI5KYt0QVWZtMpT+vjN6KlLxLkObhI3zKEgwpt14JIhIstDA06A5Z0SBx9/uXdK0jga41aw1k+9oDPxlCc1WMrs6WSdnBqmzV1Q2LyMUJqqE7VqG+ERzI0QLI+sYzUZMzCHwj8unWvgdqOjD40UqCVEm0+ndUbGPTCzlSK08hC6gE89cJMPfTGhBXlKrcBtpqQMB5Mzc+SEpA7MJlsAYuCbUsHVp64hM+NSYkzTDqgym/HKE4+iXLoEnk/x1JVruPxwRq4FN9+0wx2ffAeu7q9gX67i8uSrMkpjKtqBQKaz71AAjfxHSdm25kV06xYjRAhUxY5nYe02FZ3UW0RXpElgCeNKZtikFlQqpcaq2Vi50IlMNiPQJB9zY9TGwA0X4OBhrKZ5PDCzgwuxuBkaG5ZoeMkNh6wBkEgZOZPIEPJuzfdb/nYkgF5mWZH8JO1A81VxZWhtXDtXwNwYUiaP22x4MmmoA2LCrAbMGRUTkQCxGiUT6WqctWJmwqSMm9U4nIhwYnUQBJuHYPDGmVSzkI6qlGuYlExUZhAncAUmTOATfdOnLMaxmWVCTWKfus4k8gkIMhEnSYdFVcCZJgL2DJ6EaWNSmWMn76h5Z6n8YpiboKtGWfur6m6pow7VwmVdztL0ZI3mIuw5MFMSIM82mzKLu6HMrlRjcJIRnNVJ07gNSN1oCEJWbxIP7Zuzd1BNetEp9Kqxm2REOvJifdgW7a8bA/i9QTKaSHIjG3IcjX3nG7gNqM0xX3vrqsY6hvhQW2QxruIKRzYLhJIPNyXYk2hzKSVfjgwGxgRgYtevbUq8ATt3YE1CObIYZHKGu90RJZxkqYSnZQ9UcbuDGq9yvQqirO+RcHrlSeQkQ+innngUXCqefAqoZY8773gOPvnyrbiCq7hyegVTFn/lykUabKkSHTCJQT6h4ASz3kf9vLmq9myzJ+EGz4mqTM5JOuNSWflJViZfi6zubiBs+rJOo5eBhzSWCTPMlS5rGVnclFwba1IfM+Uz4jFjQYpKTahVrF7ECbUwcpb1JbkAecrCqMES6nOXgRriYwAoVYJTTdOERDIBZ5om8c82cwkS6p4xn+5lf5VYJFIXxPAJdR9LKm6zTquXviApiTUyIXWocMWOskofMvpQMUVCpyJhyhNOa9E4GRW7lEG1Yp9khmgtQK6EzAToDNe5SsAp0ATiU4CAUsXlcJcmoBapjygotaKkHehkAu+1g6vib00TfDTDiYFZgK/MOiqsALIZV0lCyDKjXqtArq6bVw/3AA1uxZipdZoOgimBcmkd5558cpMArTB5AWHTxQpsFfgGyLKfSMM8WAhbIyohxgkB4j+t9Y0h4G3xuO19tvoIj33TQbGCtktwaGDAYHh8bY0GVyswTcmuKiNgBWx2ODoejs83cJPp2SaDsI6orCdUQwBBa5AMjSxwo3mHuAyihkefBYnmi+oMXA2Yws7VD9XAW2UOtRjJogI6m7DNYJwxpQSqMzgTdplQ6h6EgjxNIleoP7Cwc5mqzlxFs02E+fQUH/7Qk5ivPIp77no+Lp1k3HbbHXjiymOYUXFyaQJOT1HqHkABKiOTxCyxSRbu8oeq09p11iXPsnpNlsk9bpBkWaXcjJ8SRIrV1VAa9qQNxjRv4uTSiUUgJPunhikAYANuG7JDFjWAFqWZMIgJKWc5V/tHnmXGockiPmStEixsQkLOGQBjPwuNLHNBmQumnMDzBEzSAGup2F871T43Yb66x/7aLENhmiGLV0INnnpdFi+VlLVSaIWzNURlooVY8GRZK/VUgK79CdVSc8KsMxh3ppcAQN2jQmJ1VyRQVndHrjit8ly57lWOswiDMwiyqLBMqFKQqMCsLp8zMXByudn01ego8adllqXbBLXKc2H3JGEEdj6hxUGxqIS26DUDXEQeSVMSiWayy1Zd/CFp+xL2LlJOci8ZQOq/AHZ2Ri1atVzJQrwmgurVMvTsNGw3JiqIG7N242Qod7QBn/YgHXe2GEh6Be+i3Viqxk5W6cTrup5vCxPLiKyx9mPTOQfuPZh2sOXGZAEEQNaNBABWJ3cz5AiT8LjaZNuAmhk21Txq3SCtwJOwiEItFKyKs7pfh0qZkJRhTza5JYkEgUzYJcIl2iPtEk5qxWmeURUkd2kvskWekFPCvN9jDwHwkx3AZa8GQBkqP/HEo/i9a0+h1FPcevkyXvhH78Zc98Iqs7AVrqeAsupdUl2bKnYkK+DIrGfGru5F01Z2fanOPg1+KrPo3El+76r4VCdmTFWeDyCVaJKybmFN0mASUrGRSGgbrN4AVMNEEB8B6whWq3OBrB7PCSfThCsMcV0m1okjCh4oElp1EoCvzJhPT5FTdgkkEWGHCZkJE2ekGRIsv7BIAIWRMrCrGbhScOnSCXgu2O/3mKmCs/j3ln0FJlkkGhC3LzJppzKQxMOD0qyrCBVh/WzQmsTrg6vMDNWOILHMgJzqHnOSzjzzHpkrTiETbYACSrIiD6aEwgX7ukehHSaecVr2SGkHxjUUnGCiE9Ss1grKKGmHkgg1nWCm5J2hDHREXsGeLfQh6BKAvYLTrG0E3FZcSiJjYF+RSaIP1lMNtaBeLJUSTjJQ9hV1rij7ijIV1FlkrloYvK8o+6Ja+SVUFn9E06lF4zZJyhi3gmNiPbaqDGL7lFm7xqIeSjmLzURjEJm60ToLHvy7G+cm3e+rJrF4QTFU9TCPIzNYSg8g/v46gnSd3HN1fDrXwA338gDcDQhsMC0V0Zb28uA2cqoFgmpxReDADgUMZ9lTM1a6PcQBHcFqrrqZhNKHudAlIo/IN9Ek4JcAPkm45aYd6tUrmGcJHH+yS6IDJzFk7ihhv59F9+aCwlCwbfo9asHp1Sfw/37/w3j+c+/ETbfego888mHskjhEJt6rLCEsZ+JZ81mRuegsSPHVzgryU7IgUYyMfYhJUmTaPOsIYiZ9bhYPBZ9lCsCmQbsHDnRasTYGyb0PZPwF6SuxiSHGmiYk7CiLq5bpsXpRTgq+UK8A1mXFiMBVVx2psy62kIBSMU0n2OlwNaWECRmn9RrqtQK66QSyWj1w7eopGIy5ziiJgZOEOkN1dJVvNKgVV+hsSbW5kQSPsmF1SjoBhNXH2FmWsMfEVbuAomzMgk1NyAk4qQXXKGNiC0OcdfUhMTpK3G5Zrqxgj73q7okqCu3ES4VO1AtF5KuJgLLbSYcLLbdiDQUiMc+azZ2+KGa1zZJIK6Zrq7skVfg0cmYgTUm9U1ikLn2npNJKTYQ6S6RrIjU0F5mibxWHtfGZxixSiBCzZG6GUJkl6Qo+qnX7sxgQB1uEMXKXcBRkwZpHG0gZ7rjvp8wDABpQ+21sKUG1gRijTiqjOj75Gc8qxl29NzXXKoJZ1rVUdOwsWrccI+5c1Nz5rCNWBBm9Sty4QianiOsUtALYJCCRB2TCS04CiCI3iBtSchCUhrnbJeCWy7jy+GPAPKPsi8ZzZpzsMqaUsdvtcMtJwtWrT8mMP5j3h0gWp6cFt0zSAB594jHw/go+5d678UmXL+Oxpx7BiS7OQFU7EdQmkxA7eEvs7tqWMeMKKrOCrAC5zcqUNSIBKsknnlgll85N2bXVbxtuu7uIYTSrnpq8AZmSaJKK6YzWWcpl1X2NGJjVJ7pKGdh6imVmB+SkL4/3BZwS8o4w5QkTxB84ATiZJpR9ES+Tssf+VNcanWUVl7nOmOeCspOheJ1rG1VkqShsq7pUQipo4IKk+r90RJWa940FyJAORkTiTBmlFvfIkUXVK0iDSU1gSFgsDZaGPWaedJUh0ing4knCEPfQSpcEoNlU9Sr2EI1jXimB8wzOk0xYqhD/9RligDRM2amshNaeDMTltSfUMoMm04V1NGz6OUjqr3RNQvDBKsCx2CQYaDUBXh+sSZO6rUiVMHAmSFTLjJQl3G5C1Q61NunCZZEmlZBq3AGPpWNVaZUt39GLCAxmCUxAgJlmgjTLOqJsI0kb0uQVzTySymPSuQZuELe1FlVfYjBSlV+wVaOD+1Ib7bCDcpRMZMyDxrbVOm7WY7Pmm5sXSFi/EHdddYbM/1nUr4l0BhxpmFNqbnS3XE64+XLGY0/tcSkzLp9cBvGMMu/BfArKwE2Xdrjt5hM8/thjmJT1S3zqirI/RaXL2GXRMh97/HF86P/OeN5z78Btly5hv78CaywG+BMsVCojY9aJLbOEaU0KzFywSwW2BuREtj6kGgxZ+cHchoriYktttEIMNjZO9k70O5vBCdKR6jkmkzBBvQdEhhDvkKp+2DL0JojdjXUFk6xGXW+YSfRa6TQJnCZ3fyMSRkcg5JxwQgm0yzjNe/B8FVfmq3jyyau4+eQm9XQgzPuC/SyR/3LWwOoVcDknNfevpEH9uUpgJh07oHLBlKUcSDsuGy3KjEmZfWBcIqu9Zsd77DFh4oLKWY+bsFNjPABUSJTEohU9YdL6CRSahZ+rp0ulPTjtUEnAu1IR8KYZVRdUEOJJjcwAqDvtUplBs3iJWDtJps1P9rwAIFPGMYkhutYqnayRIe0GiKw7yM6+QRlVY5mLDCJxS0ifFkrciMSt1bJrroBEtghD05nZbR4tNY8TSFvR+mn0oa14ZVcT7xGdbe/gLL7wGhaWVQ3Qq9go0kcacLO1H5OeLYybso5HYfpTsGjFHlsDuEtlJlRStj3OkLQel5re3bYr0IN9pqW9CQrMNSkjJmch5hKnq8akCSckuihxxW434Tk37/DUI8BuSriUpRLzNCFxxdWr13B69RS33nRJGIRG+mMDYjD25QpoP4F4jylVXLlW8ehHC+696w5dYUf9UXGq60LKmpESTW0Wj5dkPt7qFqigbX7bO723GASkODgsUUXRkJWMsQTXSvMEQBxyNvA21zEBdTleR/k+CaOW6pNwmFmG9GAxblKrBxJkipV1QWK9QKLaTZNMxuEicU8uTxMSAZemnbgD5oycMp546go+/MGPAnPFbbfdLu7PLGxyvrLHdHIiUon58FYEAxf5O7dgAma2qrXZQMyTgQuEmaaEiYF9LTIEV21buHfzxtlRgSxSM2OmSeQt9aeedaEFShNKFU+hOREKn6Jgp3qunFfIot4lkeVJwJ8JmNNNcBCTRiFHqgcPEkA70elZyU0VxoS8k9md8sAsETT3CXVm5JxbGFmushKUVxEpu6SG27kUTHmCRY1kBfYGsOJxAgBmpEyaF4Lq39p0bURHOvJjY8OA680ycrfjRNrRizt+mPunZCG5tGqgLTkTDzMmiLeRjhJBwf1QGX10AXzWhHVllUGsR7VWL+3eXkp1PZVgzKFprqBmiCRW9qe6eO06ApNQ9AWpy1MiBkpBSsJcZdKL/GWNc51IvAJkivmpsDyWMKfEe9z2nJvw2E0T6ulV1FrFxU6r0s0nMuW3zKe4+YRw7dqMWoBdFmOQLIQtU/tR9siZkU4mnF57Ah/+4FP4lE+5B489/vs4OSHsr0ECHpWroKSugtBZkFWMOplm9y6huWA3AYln8Jy0YbGuJkJKemycA3WHBGauyBba02URfWf6PRvbRvX45AwzaAoj8kBHYO8oEif1252UqZ4CVSavIO0BXAYVajE/ckYpFbs0YZcnTJSkfLni0pRxy+VL4spfgSln3HxyEyY8iTpXPLY/Rcbj2J3chEwFOSfcNJ3gqfka5munuHRpJ+6McwJPql1XAVHzIqnKzkAZXMToCLaVcXTdzARwJZSqwbSUmSfI+5XSIGTew0J1TTp42dU9WP2soYZMMbfsMU0n0mFzkQ6EZlSZnYIJFSWp5wvEQLyHjKSAhIxT7LOtWAp/jzK9nVXlEtBKgsESw3sn21ORkK+cpY4QFZnLAHFXJfXySCQ2UALr/AYBw8oV02ThXE1ykumYDPMkkXIxzVvcM8UoCWoTZ8ji31MESQZRdiJBEVS1vFlHbm50hFEPwKat2T0s6JiMC4QYMovXmTNu/4S4lZo3Scj7selcA3enTwM6PGmMzEpb8F1/qI5NZjAz1m3Ljqlxrene8l1imqjDTzawB8AFGXsNBlgcuCcd7iYAO5heKeC9S7ak1x5cZVmqO269jEcfuSrVYZ6x22Wc7k9R64yTLO5lly6fYErAtStPouwrbjqZJB4ysxioMqHsr+HKUzNuvu0mXHnyKXzS5YQnHptRTgsuJcIuzTJBZZ6RJ9aOBCCWKIJUGVOakeoeu0xItTqTTqwsROMA8azsgwRwq05SMUNUHGKaJcYYTdWJOvLa1IBMwoSrLuxaNbYy60iJ9NrTyQmmKppwYgEImjNyBaZL/P+T9yextmzrWTb4jCLKWa1y7332KW5lbGMDEiL5hRMlooHshmkgTJdComVdIwESQiBaSGAJpUTLQCdFJ0WHBkKiUAqRApJCQonyF7LhXvsW555q77VXNeuoRpGNMUbMWPuca99LKhvnd+wzz5pFzJgxY0a84x3v937fh4j1RYSLSeQyXJ6ZhCJTKASlLqmrAhXBXQuF9JJlJTmvC45Nw+5ouNsOnJ0NyIzgwR5C0Sp6INahljrO+x0gwud6RyjjHC9YKfxI2IgzBAEhEShOq21MVgoQ5TDoCJseLzTeOzRDaELsHTk+gLYMWreNNU20BC9OFQ0tDhubBHtpo3SSYcUQa2uLELiMwO7FwCACdTCZxIrYXV55ZC5GkqicDBdXHmepLnxB4QgDmROnwUxJnI6BRC/xQ2Cl1oVel9Y7nAx6vkcgMhDegYteQ2FIbunTjC3MDuNXwBMbZqSZzyn6F9wjYsqyIfngQ43yE6Mez8Xx3Iy1UeI6wdYp00ZOjFukuMUJc8aAo48aQNDyxn0int/jxfEjLl9u4JZJKpksfvI3UoRQkCZRhpAC6+Tkh5WnW+quPibYnIQpUiF4P4K/GyWHUxuxICtIkpYdbpmIDFAIsjS98yGpxcrg1silo1CaotAoAYtK0w8DxnRgB3CCXDpkkeFj8g6mx6dmCxLKqkTYlv12yzyXvP70B7x3dcWxO3JotkgPda5pmhacJVNizIYUsXi/8oZMGIQN3VuEjQXrEUEX9rFAvoPQNdyFxhCJfpnpTxFnQyKeuPHC8s7jYw815yKIp+CateFxYjoiug18YDOFVshMYNoIDpGJSy0CaKOwNgBUpiUaKAWsqgLnHYuqpsyKWLlQhim1F2hZgofL5Yzd7sB+23E0Le1hz2o5Z2haTKxTogcZ7ILG4yP9HYHBx8cuzYSTthSOQ9L5idN2FWdySvgxKKni4DbGC7wh8PQgrFopGMiCFVKFuaGVIRPRx7oqFhtLkotgkUUQTKAOJwYGQgp+0LgHnAAjUlOIjkGGuukoj4v1TEQmQoErxDigB0eJR2R+vB8kFX8aqBTI2PJMCGLRtVieeEq+iGApoxc6Hc/UiDV5FoUgsasYKg2SnThlNgqZZJR4JsbpXqrohwsMRMb3+Clwxn1DxKJRIvmtRXQ7hX3wb4M3p3W9CF2ixgFgItl8IZz9rgHu0293Gtlg1KFOjFuMz4k4Lxr7P0624+O05kn5zqiZpc9LZkOBj3WULdEPFS5CAuuW8RLLcEivGet+eE1qehuU1+CDXs5LzHELpsGLPLBW6ykyRaYyTBfal4GlygROabwZQCgGF1i6dx43GHItyLTG+4Hb+0dmUnB5MSOjpG13DHagyEMATfkO7wxK+UlKe5wKDw4tdSiJ6mKNBhcYRwoQRkE6sCotcUbgsMHb7NOgRwTseAxjxN0PkYVrEVONOWWpjaZaxtBF+KQgdWgZG6kJS54prPMM1uCt5+JiwbKaU0pFlkmqoqIua2bVAmstpjdURUnXdWiZ4XzoQymQ5OWc1VLwdV+Qc8vtwyPCWpaZRtVz1s2eXXfESM/QDeRZge0tSoULOTk50uwuuZ48p9lJsAwyBqkQHq+CW8Sm5KXoZrDpfS4QhYD5QbtXWJwTWBWgNiP4wb10IB3e91hZBIARSSW2WO8xCKQfSBUurYBBCJTo6X1kqL4FUeBRWJ0FeSCzIQiMP/1OWUQkB2SEMrs+aDypyULo4Um0C8YB2oRYj/OBdePA63A8nIiWRDdh2FHjPukNJxiAGGTEQyyFOxafwo/nlYgsOGTWJ+Ybfw+Sk2mKMVPDJhNJQ46/69T/MkopicFP9zEB8xPJ5sS6fxdVBwzanEDGv5Np0PTGW48lsa62GEdpN1r/kpwSL7JRjgmoL5SIZpJp9bxgudLepJycCNSBeWthUF4ROqFHR4fwMaikUBJmZyWuq3m8vUMjqfIaM3S4vsNH6SXTYAaPsyEZI2V5isSyXKj0Z/qBQga3hGs7Pnr1GV0z5xvvXnHUJfebA1IKMjGgBCFA6UMtEuUGpLBYI0MXbxHlABiDkYFViSiVCFI2qrdunKam1OV0AYuo+0LsBKTeMnxJ8Lggj4joPiBe8PF3FZEFFVkWgl5KM8Ta47MyZ6ZrZnnBBx+8z/nyPCSCWM8wWFCK7tCjdYaWkq41FEWNt46hM+SqQEmJ9Y7VWc2qvuBr73+d2/t7uq6hmheURcFyvuLV+g3r7sDu2LAsFLlQIPWYBu8joxbOjzO2EyiIiWMknpriZD0LafnBWSKIvX2FwopABkL7Rhfnd0Eq6YSI50M02OlEQmSshglGBEdGUogdhsFHxVgIBiGRkYULBEOMsrhUWAuJyTQ2lW+NLfuIBbeEA5eNl8kJxGM82+uIpz5MFANhlqcGDMKjXfieYXH4PGzXx15pgeakIiqCNLVLxzWlt4Mcg5Whto18AponyWQqpURgF6dz7e0EnFM52OQXS7JJkrtOp7Pw0Xk2ZeoJikZl5OTcEfwuY9xv+RQmr4m0yvRIndwgxNlXHL3FmNouQlcZEb3aitGjmcCF2HkcLKkxgRLJFx1sgJkIYaRgBYRMRi0uvh7sgMTUcYG3LWeLgmabgTfY/ohWCiEk1gygoNSC3sUe7xbwQ5zuh9Kufe/BWXItcabDWMuyyOiHlvuHO16cz1jOFHo1o2126Bgc0koz9E3QTbU8ZcxZgrY5+FBHwRFrfwR9UtoJwAoRglYxQOnh1NLNcApUhh/kJIdIAkg5EQYDTkGa5OtOF5PzsZengCLPOPQN0lquVmd89eVLLher8N29pGlbvBeYztA3LXmWIZ2kPR4pdM5xv8N3Fd56hqEnK2tUPqPvepy3YAVSK+azcy7Pr/ClxnuDHgYunWNYOza7HWWRoWWJ1mBjZ/VQy9YHuSQCaAy9jhOQdO4GLhEyA1WMVwzCYxP4RyHAeoEVilhlNYLvSYpxsQ63Ez5m8KYtR/uqCB5w66JUEg58pB9hUDA+pI0PQiDoY03ByGLow2+Qx4YGYToQa8sTU93jLCNVzHSMnW+EEEFSilmpwZoocL2LpVMdIhN4E3MivBz7VvrouwvJSaPiCWiESNfiiSxIBEKqSMpCoDKQjc8b7k5AHYKV0yUEGdN0MUodKdiIHJuwjDkFb8GQnCBTUsmefObktenzP8ry5QZumRjZaYm4cHr0hH1HpijC31D10o9SiUhySUrOiZ+RLIfIwHbCBRWdFyI2HRA+BidDQ91A1GXMNtRIHzvEEDLhUkKOjrYwLSNQlJrNeksuC+q8IM8Lhjboy1kWgk9tJ2IzXIeSOrhbPKhMYK1AeQPOobRnMD2lsBgz8INPPub5oubZRcEH7z7n4XGNMftgu1OhxZaOTobReufCIOGtR7h4EVtCxT3HqWO4DBl3LhX0UYLk5/OEC3jUGkWymfkns1+sDxd9khxU+MyQxBFBwUmElDw7X1CfX7IsaqoqpygrhMzohgQ3iqHvUdahjMOYI1lWIYG+7cl1jukNWmYUeUnfG0y/QwhJnpcMLlgV+7bDGoEyOvilRegE/3x1ybyq6Z0BF2t/q5BqHzrfBIE7ZAoGFujF6RicbE3hnEi5BHnmEMZhZCgkFYS4mB6PC7JFZIKBLXu0iPKdjKqS9KG7kwvJPqlbjsNjhA2BQJ/qawiMz5CiC7vlQzaoiMH0IVATQod2yaAVKp/IWdEOGQq4nZ4XihikDGDtVeRLKn53H1vVBdtVAPbBB4qOwKsgQQsfB3RPjHsMkfqkK1wDJkykhSCNFiFFfuI2i4Xhp+A4ZdjhtVMThCRXQRhMZRoY0qyeNHeK+JGsqU/A6KlcctrniayWcCkJ4D/i8uUG7gi4pyVqqpP006fAHd8W62V7/Kke9yiVuLERQtK7T+UGUpOCAJqhGUHQnoMNyUcHCVEiCXpghhlTn3UM8mlCAZwxlVxCWRf0ixn77RZregSaDEM5L8GaoKNmAukGGhu/ju1AgMSFhgpSgzEoBd5apLSgPaWUDO2Bgxx48AUvzuY8n2v2Q812fRu6wzgRSswKCYPA25DhJpG43p2SMlyo+SGsCF3AY6KNG2seyxCMCudnZF0xMUExJjwkO2f4ydJFFupLONwY7PFp0LTBAVCLgrPzGZXMAc/6cY3eNcznZ2RFHkAnU3THI8I4iqLAexi6lqqoMN7QtB04gXE9Wmu6pmM2qznsG7TuqKoZw/6APR7Iz+YMuy3d0KILjc4zMqm5vrjGYOlMx647oiuNEhqb7CNxmjyeoiKSgnixexGYnErp0SJWXkQiXTjDBncywCUATqzbE2aKvXfJ0IJHB6CTIjhL8Fjh4mTJo70LLhEhEe7kZDEJNLzARpmk9+BQ6Bic8Fh66XC5HhvdEmu8pPIPwgVC5LOwLW89ThHT5n0Y0K1HZipIaz4UyhIqWDi1kGDAKR8aPNgoWQgRa5UHoIaT+hEv5hE2BamBR2p06SKGRknlLfAO2xJjUlhKhfFx1pQqBo7GVx8/ZTLZF2mW+ZZD5Av1AB8Iox0D2jzxlf8oy5cbuBNCAtNJSXKGjGJ3OpZRYw2s2436tRMntq2kwqqY0ySiPps0KDeQ2oKF+h+hvsepsl4fotqIyLRjLWohyaSJskbqAp66v8iQnQg4O3C+KnHNgsPugPA9SoWLSCmYFRJrFHpeIWzHfggatSK6CVIJ1kyQC4WzFkGHRlIoQa5jJ/DB8OmnH3J1vuDr7zzjUToedzu6zqIqTXvoUAakUwGghST1bXRDsGwpL8OFYE7T9WhuQWWxr6MAlamQHi5FiA/4mAQhY1VpDb4LhYiElFjjRk+00NHBIAS5yilV8Ggr66mExDiBMZ6L8xfYvqfdbqCqKWdnmN4FbzHgbOhPmSlNe2xpj22Ynpvg/DDWMrQNW2sppcY1Db2XGJUxdAOVUYH9oXFG0Nie2XxOoXMOzZHz2RLZF3hhMcOA1MQsTRdki6hfIyLLi1N27zxKK1wEcO9lJBIuDl7hWAXoSQkoAdCtD0AemiMHYHXen7ov4TB4lNDkIhayEhInQnlZ64MbxXqBScWrRFC3hzjd1CJYA0WcYToPmcjoVXD1eBclkTy6J7wPTpJMjN8P44J/W3l8FlL/vY6TMS8hI8ROhEd5gXBZiFdJGbaZyJkLcSEPCJERWHYUHx0ImYwC4xuIIyVpthNmynK8nkfdehowJpVajTMhFQY8P0JM1Mgj8IQWiOLJAECMc0hB/A0noJy+E6cYx4hbPzpu/x8EuN8e1uLBS1oU6aTyQTNzhGmtVEk2CSe8k6lqIIQ2zCAVQUPzNrSUEhaERXgTalUTCjhpHxsMSE/mHdpLNILchwL2GtA+WJwq5WPqukQJExJzhAzFo4Sjfu+cTz7c0+33OCXIVIi+Z6KkKgQUJbP8jM3G07Ydph/wLkwXhbUhYUY4CmkppKcQAzmGeaaock1/XCMHS7+3fPq9lvPFGc+yJbPFnPbY8zjs2HQHjvuWPM+xvcMNDuElucoxvaUfDNorhImzfBWZVgRjEQR8TDugsiDnuDib8QKEliFxowOrYilnHTqZGyfQQpLLnMKFY+cbx/GwoaxqOtNSXjwjV5ruzT2HY0OeV1w+f8n9J6/YvbkLiTZ5zerFS+xguXn1iv1mS5lXXF1csVlvcIMjVxl9O5CpklIUCOXJsoruOLDb31KUBbubN2z3OxYXS6SWzBZzpBccNnukVhx2DYt6Rm96VDajdz3N0KCkwniLFjnJ4pbSoEmBbwQ6uaAkIHOsMGhpgw0yOgIDWKcaIVFtEEH79lhc1Gd9LK2Q2j4nicNGp4f1EuvARBnGesGAZsAzeMMgDIOwGAk9QW/vCY02lPBYnwU2XuR4LUMBts6HmWm80UW2GpOQwOMGP06IISbbRHz1afYbsnrwVoGJ6vwQUy18lJ8wcZATjI4uFWaFXqSEnTS9jusTs2UTiRM+aujJnCBGYE/ujhQoDAlxcqJ4hDtjUQKfsIYQbPUB8kOZDIGOiO9TsDION4m/J3kkZHP+LqnHPerPo+1nsozaEaffMGnZif2kGiQpMCkBFXUvRfyBHUlpDEVrQgq5j6+lok3hZmON6zAe68iGNAYZkoODc0PIEJyMbcNS5cCAdYJMO16+c82nH31Kd9iiZyVSarSEXEKeaWxW4/oG5XparzB+AJ/qPwfJRniHtF3cPrTNgXlRs6oLjsc9y+ISY3u26wdyNKqFXJU8X12hTYnZvaHdtSiRRQ9uYEeiB2Uis7ARQTwk1wjOxWOZ9EAfB8KQLAPghgErBEIHD3VgJ4HVSTJmRYnaW/rDjtY5VK6RWrHebsiV5vGzTynLOfPZguN2S7vZ0ax35EXB2eUzpPHc373hsx98yOrsEozj8uySh/tHrHUUWYEbWqqypigcu82OzvSIHpzWVFWNxHM47KmyguV8AR66Y8tgBoy11IsZXveUs4rDZstsOWO/26GLnMXynNbs0dqF2uIyOhzSherFeLimBdGc8MhYvChc+qFSpCOw2hCoZNTLQ0nYAAdOKETsa+kml4HDk+FjKN3jpA/NIYTHIkKBsai7eq8I9g87kpQwNwq3bLxvGGQWtGsVr5d00wSJQ/kxUCki6xZOhBLIhjG2kZo4eBt1Yk+odxK76mBE9BMkOSN2ck8gGPFvDAaKWJZwXGNi8xNx5i3gZCAXJ7abNhgxJdTNnsoyMWA+Aq4MM9sxbgPex1rr3iPGQSb6UL4IqzjJOD/q8n8A4ObJ9x3Jdxp042+UXvgc84m/ndDxx1XxzSoGllxqq+VjN/LwK8pU4CZq3mIC4MnNG2ocB8+3QsbzWoxFpoLnW8TnDVKEehlKCRaLkrNlxcObWwYtqHOFdD2z2ZI8VygBVX7N/a1ju9nQOBlTxH2wI7pQLEp4HzIMpWRWFzT7Hcb3LGcVzbFhWdZhFlDVgUF7wdD0PF9dkDvBzZs7jk2HtR5jkpskIkcKXBLSkhUEsI7saKww5z3OBAnHxQBkslMJG49TLLKfVwVLX2APA7v1jkxnZFVON4QGBzIGdmfVnDevbzjOWt7/2jdodntc17J+fGD9sGZZL1gtz+iGjoe7W4SXNE3DfDZj/bDm6vKS3XZP13eYPvjT+n7AG4HNOx4f17jBsqhm7A8Nq7M5VjjudzvOL85RSjL0PbnMsf1APzTkg0RYg7QKZQVn9SWHbovBhOzOhBMpKCYYp83Ci7Ffo5QyNBIg6LyJfzgREnMUMkZSGJOHEkCfnDsuZhSE88zFC0BGFs+0jGkEYofCC4MQOnSAEg4nouU1kpSAp+E5I8N2EmALFbOKlf8ckEsV1034JE58S0oxstHT7Ficjldk5qECaA7CxNI0AoSJ13n4fmJ8Q7re1ekgJ8A9IfyY8nHC7Rgojjv4BRCLIOVrJjiYrpcGAcEpCT6JAOnL+3HdJ8vvGo37hyzhuE3YHowaUwJsn3z8kV17dWI9IfLtkSIFIUPVtvCbhzZQMk7tVDyhT30bIXU4D+dAYN8y1k4ItUFOVQKlSJbA8OFKhBZg3nYsFgXNLsMNHUMn6UTPUGRkIkcXOatZgXIXCDugvKHr3VgjJaSJu2g1NFhn6VGsqoJM6lDwp9AY47BdhzCSMiuoMh2CmqJnpSv88ox7u2V/6NgdjjjtqPIq1NJw0SKVLpjk40u22Ti7SQBxciIE3VApiTMWX4Ya2/OyIkcx7BqGYSCrCrqupzsazpZLiqpgf9iy2W7Y7g6UZcn95o7uNzuuVhcY6yi1ZpYVHPYHhqJgMV9g7R4hszDLdlDXM4y1nJ2f0XUdWZ6hrMJKy37XkwnouhYpNFlZUM1qDvsN22bH6mzFfD7n0B4YrGGwAukEZTGjOQ5IFVpUHff3FHaGIGbqORcGsQRaI90+BStFrMPincdLhcOG9HDpRyXFi5A9oH2QQEJBrxQ8C69LPE7I2BEeoicCIutWMbqZGhJ7f/KZJ+kg1ZNPZEQlAI/gPcTqhycQFk+aKiAZH3vhcPKUQTtedzGxzcuUzhIJlQApXTyfxIlcCQ/egJCxl6aP7FoQmqiEi1pEKu/jMU1Z0CLFV+J+23FCPklN54Qbyf1xWibSRjzRp/7ut9eTCQ8SaEcWHq4FTg6j8ZOfPv7tli83cEdw+KIZxunw+ui2SfMYQpSbp+/1CbDjqJ9OKknouBEaEaQLKFgCQ1cTHw+4GFlJ6rko4udKL2JzAjmy7bFXo0hNFiTSDyipA9ArjahLzNmc29dv6I4D57MLTLtnoCITIQFnVijc2QLNwOFgMQYwA0oDXiBs+FwtLNgBrTLOFiv292skksVswe5xS9f29McBkzmqrKBpGuzRYo49hcpwGfSyxw2O3nfkeU5KtQ8zlcmPkLIpky4ZWYmzfnTxjMkMOlyc0glU62i3B9q+Iy9ycpnjcs1hf2S3PyCUIC9LznXG4+0DeTnjTK5YFDnbxztWl8+DdGAsVy+f0xx7jAka2d3rG16+fI+2aXHOcv/wwGI+5+7ujnk9pz02LBcL5Oh6Cenyr29uWC5qBttzcXmBzBQ3b24Y7MDz916wO+6wGOr5irqe4fxA2zVkZajWaE1gsD6WGFZKBT9xBCMrQoq+mJyIQgaQDCnzk76W4yEOgctQIiWk9DsRYgZOBI1VJfAWRHlFomI3KIsIAwTEBiOBMITBIIBnshg6kWaQp38Qz2EBRkcPoomJKhF4fSzUhmQE7ZDGzmmm7J4ycEQgOGFAERMicDLhhTLOYmy4LcYD46PfezoQhTR2Ea2PY/5G+g74ODxNgfsEz4kvi8mzJ9mDMUVeSnUiJTLijmNk3mlJwOxHB9Xpckl9NH/U5csN3L/d8kM8lCMLnNQ4CYG1KGTJRLqDJ1sIH0udprKacZLvw7QTH8E9pbHHmtcyjirJLih8nOZG4FYyXHiCUU4PvQYxKEQAdiU4W805btcctzvsMAOVUeowvQ1dXDKuz+ah3ZU3tM2RwUEmoxdXhFKhoVGPZ/u4ZjgcWRY1fd/jrWExn3HY7Kmymv1uT3lW0hxbcJKsyNkftjBYrpcX3N8/0B2Crc6KWBs5xhPSlB5ColPKHpMER4lzfqwKqLTCWIPKNYVUzHSB2fdYYyjKksH02H6gnlU4J1jvthyaI++8eEYmMpBhJqOkorWC63fe53Dck8ucbKZpug5nLZvHNXle4fCUdYkxhqZpmM0rjDWcn51RFRU4x6yu2R0eULlmXtVkWtF2A0oJnMgoq5re9FxcXvG4f6AsS5AwuAHnWprmQFmXzGcLBufRmcQ4Q6FD3y/rfejOQyKT8gSH8iRxIAQyZaemYFvCOBXsTzKCrBQRoAErTvW8XZTmvAggjvfhdZ+89eF9SB8rEJ6afjjAjCxSPGHcAjGRB5JbIu6rIgZSE1slgnHQzVMQMOFZknWEYKzEF2IB/kSqBKPP2yVCJJJfPNZZF8FNkhKdcGmAOd1GOPATiI47Ej0m4+wwlcUIJC59R/EWwAbC5kSYUTnn4gBw2vY0hf1USnYyFPjpaz8Uyb5w+XIDd9Ib4vJkvEr9J0kHyAd7VrwgRGQFCGJd3Lg9BCKyDBnBWTh7Ckz6UAdhZMvRmy3SujEoIpxFxAzM4DoMyqSO/SRlCq7IU6Pe9DNrGdqTSakRPmO5KDHHPcf9Hk1FEwFdKIX0oTj+1arGdnvc0JCjcNbFpr+hBVmdKZb1DGUlQ9uT6QIz9Ny/2XNxViO9oO8cZvA8bh8oB403AqTi2eUVN2/uaZuGs9mc+9sHrPUn/mVjD0YBmY5TYJkGOxk7foDSsRdh7KSTFxlCKy5VRX9s6NuOoqqoixqnLL3t0JlmPq9xxtDZjkN7ZLPfsCjm7PeHALb7LVVZsFwuOewbdg8PHPYHqqJguVqidc7ZcsHQD1TLM6Tc0h962qZDKUk5X1KUJU3bUtQ1282Gy7Ml7b6haRpWixlKCB4e7qmqCpErrq+f44sSPxikb8mrBa5rUVUFXjIMW0w4IFgForNkLuietgiUM9jPQuJMankmpBzT/oWISU8J1BOpEB4vwm/vhSAjMm7AEgY055NMaAOIj8lP8VIglJOVPljhLMkhLUeSMi2iatIAE8sO2zSYRGAlafiZCIXI7Il9IwmJYkk6iAN7vEzDe20sdSDciWHH7xtqsoXZanBt2BObBlIKuotlc72cAHaUSkScSfgUtSVJJpFVn1SM2C4tYIafDBSpWTFMQddFQBeEZCD/BTLIU7AOg4g/DXrj4PK7jHGfRrnTaJqmRmNd7jiioqOmmNwlUR4RKlCBlLoqYmEOSfB7j2w6umqnEgpE+QQfCuQT3QA+TJmcD2nsgROE9AYlo94tTj0pQ7f14PtWhIDOrNC48xW7h3s0hqFtaKWlzyV1VQb9Gii04vp8gTAtbWMwfiBTgdUKEepf7PYNszzn7GwZLi5j6Jxhs+0YzIAwDmE1/bFldv0C1wwcmiNVMcd2hsO+Aeepq4qZVLTYADhZOG4lMmw3y7DekRVZsKAJh1KxcbD1lEVBStIpZUa37xEio6pg6Ds65VkuVrSbI/cP98wXC168+4Jj32CcYe7mPLt6wSeffsKhb7m6uqLrO7x1tM3A43bDsq6pZ3OkUPRdS4dAqQxxbHGDQRQa3ztmZU133IfUfuMYjGE5r4MkVpW8ePGM/X7PclWzqGu6oSeTgsFYCiGZz2d4MnoPeVnQD4asrMnyAo8jn82RmeTQt2Gq7HyoqJ20fxksbCn9Hw9Shm40oc7HKbgVyW5k36GgVPA2x8qCJMYtIwcRyS8ySiXWB7KBCAKNRQbNGhlmhXiCup5YvoizwnjOx+smXDoep8R4AU7jSdMmGgk0xzZeIoEmT27CiVhL28dAZtLFT188SMUiXusnv/aYWTmWZIygGKWSsIMi+OqfsNsgfoZaJSNyhFfSKJewA576tUfQDT+cGFn55zHqizTtqfTyu0sqkYDw48h7OoFiICxpSmOacXw+Tk18+hHHru7Bionz4/QSUgMEifTBfSBF+HVUZNlylEcCaKfnIklHeDn+lT7ZAeUI1ukikGFcQcioISqJ1opCL7HvveTVD75Hnc/JtKTvjtjuQJEr6qpAZjPOlnMkhvs3PVb0YB2ZFwhn8YNj8J5d29BsGgqd8eLyGU707PsG0xj2my1niwsOh4bVvKVrOvbbA4Us6bue46Hh2LRczec8Xywo5wuGZsBi6WxPVZXkKqOJrc+8iwXzVez8LkP6urMOK3syn6O9wguLkJ55NUdlZ6F+tBAU1ZzB7+i6lqwIQVPvLX0/IDPN1dU1++2eQ9eE5KDesT80LBaL0GnFe4oyp21bhm5gVkgMA03XUtqCsig5mo5FUdFYh8oy5lKFjmRSIE3UfpVCKIWSEqVD2zIvJduHRxYXSwYjURkMQ89stWIYDFJnGDOQZzm73SPD0JGXOcYMlBSYwSILjYlVEU+UI8zSQlAyBHFHTZjJxS9EnKqrMWiZApZShPoeUxARgJUK4R0WNZ6fQRtWIZApfHSMMLJui5+UeYgNHLAIssTBT+4R0q6JKJGEYGzSu8cZ7nSnRJpNCFKjDiCYRaauknhsRm0lzFUmGzhJGpONkmrj+BEATq6P8P8E/GI8VlNgT4FFkaYAI7BPQdZz+gUngC540kQ4STanzxCcSs6KLwT8H7Z8uYEbxjMzTHfeAnE/HT/DkyLqcFKF2MjphIs2taRZC0Hq1q58sAM+YdvELufCjSwlMXIVvd/CESoJehk9vJF1Cz+6UGI10DFYGbrfWIRUscpgKEL//strfvCbv0GfK3rlKasClWswlu5oyIVDzufMioy+1DRWYdxAOctRwlLEPoKms/g2tMYahoHV2ZzzpuRRNvSHHtMdsXi2mzVC5gyDZbPd07Q9oQZESA8X3vK1q3dZb7b0tmc7HNB5zqyckznL9rhBKoUVFrxHZyqSk6hxe03hJbmyHIUfC903pqfb7yiqijwrKHRBUeVY5zn2hqpeUM4c3/3Od6jLmmfPrunbnleffMZqseLy+SX9IbDwx9t7Pvr4Iy4ur1jNlyErcxCU14swu3AgZMZxv0VKzayqQGn22z3mcOBsdcHN4cD51RnGhUGhWJTBB15WzKqcXbMlqxYIP1CUJc46yrKgdy1lVbPdbdECyjzHeofpe3rVoMsc2xt0nQd/s4zeX5GSOOwJGIO2kSJik6BdLMEgAju1QobGwqlGSgL3ICxExu7BRz02xj8gBDUtPjqfVPCMR4lBiMTEo4QTWXuq3B2w0ofZ7DBxj2hCecM4k02A/jZwi/GvCNfk9Hl/ep3R6+LTRol6E0RyNG44SSAJI+IoNjo8RtR46ilOgUM/QQ4pkl6dslSnzDtp51PGfKpa8kWhthPLnr7244ncX2rgFlMmAp+fo3ieHo9EViQTFwnBGhi381T6ABH7HUrM+BeIVsG33xOnVT6kOkgPzsmgdzsxYd/B5hW07WgLJF0cqfmCDZ05YuEqiaMuM9rmQKE8g/KUukBnGYWWmL5hv27x1lAVCoziaH2qXURVlCGphYzhaNhut1gLh90GrWZczFdU72V8/6MbfGPoZI/yIU382LYMzjIYQ9cOzOqCh80j3xCKq8srNtstZVmy7jZkWU6pcwYXquxlGrI8VIru2g4hBUpr5j5HmIHu2KGrirIoyPIcvKG6no2Db4Xj2O5xxqCk4Li+p8VQzSrm8znGGHa7HcvVkrv7O75xdsbi2YKHu3t2+x1CKVbzBe3Qs9/tePfFu2wPLZvdI/Nqxny+Yuh7qqKgaXu0UCyXZ7iqDz735YpqVtF1failUWRIEVLx15sN+bKkrEqGQ0NvBHVZ0HYtKiP0pOxDWvtmvSGvC4oixxiDGiTGOooqjynfEdC8ABmyVL1zp/hL1MGRMXgmg3wQMoGT/yGAU/BFhxM6FFUIUkli2wqLQYScKOlH62iQShi92wMi9CMdra5BipEy9nPyoeOMTxJIlCATfokpgJ2e/Bxwn27iBNJfxD5Tne24wnT7o7tplC4Iw9VU0UjX68QrPpVCptibBswTyMcw+2Q7p/en2EEaXU/fPW13GoBMPVTDfeLn+ODA+hGXLzVwf07+j6PqDxu7krbtffCwpr9pCSP8ybuaNG58yIoEG6QNH05k4jQyOUp09MdG81HcTtgmHnA+yiWp2UJwXKgUqBThsSTmLcT0ZYkA53jn2RmffPwpbePIhUWYlvmsIC8KpNZoqZBaMvTBazsvJHYQKK+xx1DJsKwl59crzpdLpNSs39wwNB3fWb/hol7wbHnGTb8OrErCMHicEyAlxhi01ngh6Z3j9e0N1+9/QDVbIozBuVBUy1rPsj7DeIsToQiTM7CsV8yLCmsMw26Hzktmzy7xyrPdbejtgGsNWdmjpWK9eSQvc5x3ZHXJYrGk6Trs+hGLR+jQ5LYoS8ww8Oz6mru7W87Ozzm/vCDLMnbrHbcPt1xdPoM5HPoG7y1FWVMvV+wOW3KtsEIwOzvnzfd/wNn1JfPFOcdjD9Zw7DoW81nMTpVs9zukliwXNdZ5Mq2wUkKmaY5HRCbQeR7SpXXGMDTUs1nspegp8hwhFblWtPsD+bwaz914JkYdN3aKF+G8CkHMGI9JmcDOo1TIjVR4rAecwXtxapbLyaUmBOH3JOm9QTeWsXO8wod0ndGhkoLQ4q3zegIykqegCyd9exI7mjLuUU6eMux0EaZBQJzemyYeYgLMoy0lDQvjDpw0lpTnOA4go0QRD0h8xfvE5J9KGyP3TgFQn9YJs5xwaYvJ+8apUfwv2gQTwE+UFs/09R+Pc3+pgTtp3MDppBfpcIvT7w/jiRJKTsaxOZUTjVlfUlhElD9Okklk116Mkfl00ipiQwRS+rsPAct4X0b2LbyINyYMOoI2QdtWMgBlkksS6Ot4Aisl+cr7L8G0bB4egs6Ooz0esF1LpgWZEszqGUp6LpcVuJzPdlu01GitGYzj5tUNy9mC68trCl2wePfr1EXG7as3vHrzBqkFV8sVDou2oT0YHoo8R8kDRjicEKzmKwY7MAwD5WzB/v6R1WyJ8Q5jLc5ZdCZDXWTpEVmGtHBc73DOUhQFre0Z9vcoXbK8eAbKcditQWkWqzlOSfI8ROrvHu55c3+DRDCbzdnudqwfN2wfN2Q6YzmfMytnKK25vbnBXz/HmIEsVyip6doWkec0uz1SCZ6/9wH7xy3LqsAi6BqLPzasrs7wzrLbbllcnKNFkAPaw47BGrTPmC/mdN0RWeR0TcNht8X2A/OzFbvHNfPFjN4ZqrpGec1h39F3LUVVoIsMoRSH5ojDUZ/NQ1VFVOjLiI8OExmLVMXsvilzTE4ML8JAbQ3OtSEQKQRehFyA0L3cxqQcG9l38Dtr4cGJMaCpCL5sG62vOoK2mbweksncuCMqBfLjtTgy7zGg+rQU6si2Jzg3Elj39PG0jdgYCBRJiw7n/tNO7RHk4xbSZ47asZvKI3GNtL6fzAIQI7imgOHJCZJGy7TtExR5f2LPYEdf95NuTmm9KVhP/vroWPtRli81cEsVZQ/SjwYQT3YXgw7xzBoP4ISCiICMuBgtTyVblQDvQo1t5YcA5hgEDh3T7xQG4XsyZQPLdqGQh8KExr3ilJwjrEBaj3QO6UB7FYpQedCEYlRZSlUXqV53KvcqQodxCfV8zs/+9E+yfbzjw+/+Fm1rOF+umJWaWVUinMN0W4TwHK1DC8U8P2e/3bJvt3jrsYPnxrd8+7fehBR558mlotSSZVlTKs3VxYqHmweyoiSbO7a7A4emo6hqmn6H8IIPX93xsnEslmd4r9GrJbiGbrOhaR9QMqc/WsoiJ48BSq1zWBSxoJTEd4oiKymfndF1Db4zSCewfsfjQ0dWVAymo233DEPL6uKSxhkeH+7pjgMXFxc8f/mC3d0js9mCcrHAdobLPOO43pDJnNXZGU3T8eb+nmdXl1Tzmr7tWb95Tb2Y0/U2NF6ez3BtQ28lZV0xDAbTHREo+vCj8eLZSw5NGCiXq3PabmCxWNH3R8qLa5rNFp0BpqPtWrTWqDxjtrigmM8wztINByotkU6EfWkG9CAZao8WOTKTkcwJXOplGe1xzjp0pjDG0PehsYHOM4qyjOCeroAQmHQuNkzA4oUikyF4qb3DxLR3jWPwmpxQMVD50Nw6pbWn4lKKUz6DcC6SnBCstKmbUUpwESCUHFvThSejuBGZrhQTu6BIvDhew45Q5EkyurwCo/cpnkpwgoRNn8qxhvmBG90m0XXjZShz/ESWmOyagLGzTsIIfwLmIG3ELxF99UHzdtGXH5n3E5COnn1BDFCmUdeP7wnbZlyf3y1SyTj346melpIcToEDxsfERK9TpDqy7di6PBWLCmnt4ceUsRt0OHlDgDL4uFMCRcqsDBUEhRDB2ocLPmtE8H+7QJ2kjzW7hYjd3kNxKS2DV1TFm5TptSDJKCw6Uzy7Osf1L/neb36HzeMdw0HR5ppZXVKWJbnOUEoxND1n8wpzPOKkxVqLVIJc5xRKkkuJ6cEOoUdk11kGLMdDy8ViwePjjiorqaqKvnOsNxukkDTHI2URgqNt30HbUMiMvF5irMIrSVmG4jtmCK3XpAhV7Lzz9GZg2Lb0tme2WNI9wGp5higlZu5o1gJESIiRxQWV6cn3dzD0rJRCXT6juBJs1hu8l4g859A3dPcNbrCslgt0ppFC8snrz1jMlszrGrxH5zlkwVGihcaZA3kh8LYNVeaEo7cddt+gVIZZ1ORGgCjYP27wypPlmqY7sDg/G+U2s12HeiRC03SO1cU57eEAucAOHV56ymqGMQNd5yirmrY9Ui3nKCnYtkdQgiIvo3YN3gTQViL2ZdSatmmx3pDnOToPl68zLmrgoWflyPSEJhSdCjkE3qsIbhItPd5O5MDIoKdadpp1nl4PTUJkSu5KIJYuLsHJbucTGxdjOQk/Aa8n1zCMFsNpUJAvwLFQnEs83QSRoX9BFsuJBX+ewU/tf8n9MX6fiQZ+AmM3Af9wTIL0dNrOuI14ezrD8JP3E8nmODp8/sv+NsuXG7hDEtmoJTHqVmneFWLq40GNP0RopOBj4kDSwAjacxxd04mrRulj4jYRPpTiTKw4TrlGr7e3YYrqPFK6Md1euFD5LbDxkI6spI/lXBNg2yep8Coy99AdPiZf4Hjn+TP26wfubl4jRRXcLIByUAiNlCEEhVVomVMoGMyAFFB4QYlgUVZcvFhSlTXOhAPatz3r+weuzi9wRtIfO7o2NNVVSHrT0xmHlJbdocO9vuHyzHBdFPStC5Y3V2Bsix0GmrZBK4lUBd45hmGgNwNSOp5fvUO2WHLsWmzf0R0bNsc9hfOUF3MOZk+7u2NRz1nOzmnaHVrD3DjWj1sGY5nPFX0v0FoxdD39fo+3juV8wXJ1xvk7LzluDxy3GwYvyLSkKmeYpmN9d0eW6ocgKfISrRT3r2+4vLjECYk5NgipMEOPlwIzOOqzBUJB33XkVYHUkv6wpz6/gEzTdQ1d26C0wjoHKLJMkekSoY5UVU4/9FSzMvQPzUoyq2NjAYHSkr4fggXSxbZbHo7dESkldTkLjQeMHc/joRuCpp5rtNIhwxIILc1i+dcIGiKCkYrPf1EAMv0d70e5MFhX3chIQy95OXZkHzMhxcmOGy5FMcXOJ6CcWtT56Xr+rffF30jEHprh2k6xgHFLnEB6+mGflzXivScsPKQhRVfPeAs7e5Jap++zgBoZuUjaLFPiOGXWb99PksvbutHvvHy5gXu0AsYDNU6ppq2VJvpV9GqLU0dfUsBSehsAN56YIrINRUpwsOPJLIWPUp6LlkAfa1ETAo3eBX1ShdeUCNr2ScMGpUI3JS2Dl/sE3AnEg4lLiVT69VT0xwO5clyfz2g2Ajv0eFWSSc28mpGpDBz0QnE8HENxe2s5Ho8MXSgzao1DyjWZ+IhZUbKsa0qpWc3noZ/jbs+8rjg6h1aazz57g/cWa0L2pxUCh0GIjMF23N29xgrPrCpwpqHpBw7HfdDvlaQ0A0Irtoc9CEmW5wy3t5ibT3nxla/Se0tWzHj/6oph6OiOB7rtLuioCnRdcNi8od/ukU7StD3zWc16u0YpzeXlOftdg80KjBW01uK2O2bLC86uLtESqvkZzgS25J0lrzK0CA4JXRTs1ztc07E8X2CxNIeGi9Ulu26HtYYiz7A2sFopBMY5joeW2aIkK3L6rgfXI4XFtgZZVwgHOqspsgxHmP6jBMIrjBkw3lPMNNKlrL7wV2caa03wQjto2oYsy8jLHGst3nhUprDGhEJZRUZZlmPqtbduLP0aOE0KdCrGorHxsnBejudWICrpfgBt6U8xHxlBK8V/mJSqJTojUsPoGJkPlx4ngPUT0Ao7ML2kk+zpnzwO6ZMxbXzcKift/8nGTvJFZHWcwNc/ZdXx78iIIzqnOcK4J5PnTq8REreelJD1URaKoc7Rx/124s8EsH/I499u+ZIDN2OQJiJ0eDpZp4gzuDiLGjUrkUZYEd9PAN/o3Q5PhxPXex9lj1i7BBdfTx5uh5BBK5YqJOoEoI5ALD1KgdYhkSeLTRS0SLW5Y40I+fRvsgSqGCAJXdjD50klMB4W85r5bMbh8YgfPM2+Jfc5ve7BwmF/xHSW3XaP6U20JAY3S1UXoTyqXnCxOuN8saTMMoa2ww4mTqgtbduQqYKL8zO6ztE1hrbt6aTBmIFqNufq+hmL2Yxf/9av83jryPKg/+VlTlVVHNsj7dAjfU5RzjDGIjJJP/SsFiuUhlxLvPOYpudue8eiKlmcX2KUIssKtg8PKOuZz87o+x7dteRaMpQV948b2u99yKKacXV1zXx5zsOb2yBRCc8Pvv89/NBzhabISsxgcNIj8yy0QssLml1DWVaxaJKj2R7JVMHgDVVZIxaK+7vXLM8vGaynbw/oPAOlOGy2+DIjF2C7hqbdcfHsGb2xKCHJZsFTf2w68qIEoZjNappWMxyO7LZ7yiyjtyYwt5gxqYXGOMPxeKSqKnSuscaS5Rl933PcNwgJs/kM7z12sOF8juf12DU81v8IWZRJ3pAjSQmZloFRJ0B+m32Lif6qhJu8FvYVz6hHj4RpvEjjEi85MX3uC5an3WTSc28z2lgdMM2pI2HyhBrlsSMDJ9/6ZNtvgXfaucSiR9Y9vseN++8n20hPiDgbmGrc43qJzT/xjsfjMtnGhM7/SMuXG7jjkgIb4ygYmUtq6TSdvsSCB5NsNBGA1zO6RlRkHCGDLWp8E9lEJDaiQkW1JJMogkc0kyH4JPBo6cmUIFOeTAbHSEi2ibq24AmAP/2bAkR2HAQkoXZKoSVqseDZ9TN+sP6IruvJZcZ+u6fICpRUZCoHaSnzis72WNNTlpJlWXJ1Ng8lXKXC9g5cixIaXeSoomD95p4Bz/X1Fcor7tyGq4szFIqbh0ecEWwOlv/3f/8O3/rW93jv5RUvnl8gJeybA/OZ5vLyEustKtM87nZkCmazOU3XUlcZeqkx1tI0hna/w7kWnUGRVQg8h2NDVuY4JcjnFbLSVFnJdveIMzPabkBrxWI247A/cLN7w6vbG95/5z0KnWGcozkeWFQFclmzXt9xdXYFqGBPXJ5zPOzYHQ+YvkMXOd555vUC33vKqsIBdjBIlXN2doGXiqLMkRg2uzWXz55zOG5QvWA/HBAm1vY2FlXm5KXGDD2d7VktL/Aa2qEDoZBCUFclTjqGoaM1LeXFHC9ARTNee2yp6xqtA2hLJTnujzjnKMo8PD8EF0NwSwWG6mxMsok9HoMea+NVIkdC4AmYYn04D4fo5Q4cPVwPcgTxaIMd3SWM18bJT/3Drk8xgvYpKMlT37YAb76AhfoEnglwEzMOAO29ZSzGRWTAaf0E3FOp5LTxE4ATh4C0jSl4T8A4IvJbvBtSaa0nrHk6AI3M/bQXqWmEIIa/fnTc/pIDd/DXkSLap5TX0+vJXfJkfhUdJT7el9HWB4y6HpF968jotQiALqQK7JeQCJHFj1Qx8hnaloGQISCUK0+hIdeCXIcUdq2CdS+Atpgw7NgNhzhV9SfwDo2Gh8j0Jc6AMHC+OONhuebhzT2ikqGYj4UiL1nMF2zXm9AUtjf01uGl5NAb5PZIpTXnszOGbqA1A31jUEJSzyrIJQUZ93ePlFlOXRUoFKXK6UxPs++QzmLJOPQD3/34DXkpWS5nzEqNMZabmzdcPrumM23wMzvDzZs3OAFKVkhZY6zhB9//Leb1jJcffICockzfI6uKi7Lg8e4z2uMDRT2jaxsetx9z/u47vNrsKauCQsL1xYr3P3iPZt/x8ccfkknBbDlnt9ujvaeaz+gGi5QC40Ni1G67Zehb3n3xDq8++wwrPbO6wA6e1hpkngUd1VlklSG8Z/v4SLlaUi5mbNdHzs5WwWOeZUjpGVrD2WJFPivo3UCW5+z3RxZn52iv8YAZDFJKlFQMdgB8kLIEzOoqzB51aIpx2O4oZhWZzrHOIISga0Jz6LqugeAcEcTaIM5jfGqkK6PfW4x255C4EzVqYsq4OAHr6CLhpG3LiCZJNsGnYOZTm9u4HRXjSkmGTJxpmrkSKPJIOEUEw5F8xuXEjtP6oeSVx4RYFFP2fALqk2/6xLafBD0jIJ8GgLflEAJb92Na0+fXSdt4ssPpuP6QJQY8n/i6J///cZYvNXCfplRxDhaejRp3OKih0lqqthaywsaIsfKn6VsETg2hNrQKmWUSiXQm1BDxMtj9CB7sIHeE0q0q9q9TwTkWGDyCQgtyJchVqKCXSchkAOzAvlNxqegeIQYk8aNHXEaHixIexqp8IXPND57VfMnhfk9/6KnnVUzkkdjB4UxIwKmyml4MdN1AdzDsth1SCg5zw9liQaFz8A5nLcMx+CR1XvDs2XNca7DOkNWa88UZIte8+uQ1W9lw2HecLSqeXa+4PFtw6AeOnaXKoC4KmrZDKEUuFd4MXD8/x1jHcb+mHxx5nfOzf+AP0BwO9H1Hpn2wIUrJdrOmGwSXF+9w9/oTur5l+fySrrfkOkhSH332irosOV80DMawWl0yWMPDZsuLl+/RrB/ZHVvOr16wv7nDVw6jBMvrFabtuLl5RVHk4ATDdoesZ0ivyVTGsDuw3TwyO79kGHZ419E1B/J+TlEUDNZQ1XOarqEsMubLM/Z9x2W+QrYDDkGelVgTGiwM/RGRSdq2Q0nF+dkVbdvR9zsQOW17hL5Dq5Lj4UBd1yiVBfbsQnOHvMzJsgzjIkAjcVhsH2QSpVQ4/ydAO2V6J/OFi+3i1Ogc8SMoM7qkhJcjUAvviF2TR50bQMTEIu89uChVJFCOXW/Ca1Em8VMwFCP4jigZb8750YmVpAQ3suLEuN9i4fH10ZQwYccjc35bJokH5ZRImYA91kYZQfrzIC8QMSknIZA7fc4Eo8LjE7efSj+jFn/K2f8dly81cAe54+mPEWQxN4KxFKEOtMdHx5IPTUJTMFEFVpv54GENZUhtzGaUaB/qekiSvzoycDwZInY8j51wRKj6l4BbI8mkRyqB1ppCK7QM7pBMpsYK/nOMewRtcdLRpSD4W5F465BekKmcKofrc0G3PfJw+0DTHlnWK7q2xw2ew6GhORwQXpBnOUMfLnhnLFIp3tyt6due9997gfKKsqzJsoz20CKsoT0caJqOPC+oygXWwU/95E8zr1Z8/8OPycU6ZDMaR1UvGDiS55aqLlEZnJ2vGKzjYXOPUhn3948MQ4+SnrPzFXlV8unHn7I7bKnKjMVsRrWYMWQFXmtWV2fstms625HlGmk968c7BueRxvPs6hrvPFleAILZ+SXaWJqHRz76zv/gfHVBv9tzLHKefe0bvP7ed1mdrYA5zhjmqwuapkMLhVpktOst5fkFh5s7Zss5WV9Dd8S0e4rVOR7F7s1nHPseLxyyKNg93DMMNcuzBb0ztLsdshAcdnvKMsdZyHXN4AyZLCizUJHPWoEocoQr2Nx+jFI5amgZbB9cPLLAO4O1lmN7oKrqENS0seywgN6a0U0ilQre7VRAKkTYJzNNwZjjEXXv4NIQY80dmVxRIot1UGIoySfyE+BJxSQ1nMGT6tD4EcTCRTll3RG2XGRK6Wn7lGYLGAeA8SJ2yeHhRsug9QmYAwtPWc+MX/ep9vCFgb/PBb8m640g7Rm7uH/BNrxPTeHGSUOYqfnxMOP95LiI0UtyetO4779LgNs7j3eeNBkKOt7bVbYkItYVSR05pCLYCHVo/CuRZCRAdiPTDm3JBMJHACcx4HDgtIDMC5QPW1B+QAPCBzklIzgqciWDTCJDswQtmbDt4C5J+mHwd6e0+1D/Oz0WKWDu4nUiFEVeID28eP4OtnPs1zuUVVR5jZWGAoXIyhCclJ46y7HCM4gBPJS5pipLbO+YzxdUsxlKaqqqwvqcfGWRj2u6/Y6mOaBlyXF/5OV7X0FLxZvXN7y+W3O/3vP9Tz5hsVjhXY+xjuXZjPVuR1nNqOdzNts9zntWF2fUdc38YsX27p5yVlPP5xz7IzIvOB4OII9U1RzjLaoqeXn5E9ih4+HuntVixnI+x3mPM8Ef3x+PKCXY3r0iUzmL63NqFEVeMj+/oj+29Kbn+r2XtMceY3tmdc3m4YEwDHuUzhAO+kMIPLbHlvlihmkazl68S3vY0ZkWpRQ6z8mrgs3tLUWZkwnP48Maj2VoG4rlnKLKOB5CXRWbGVSpsdYyqysGb7BYMifxImN1ds2rm0/p15bF5ZxMF/Smw9gOay11WSNjaVwQeOE4NkeU0hRlcQpOipDEJUQo/DqWNY4DP0QwjwHQEJh3Yywn5SuELOB4P4JOynUQPlTvFj50/PXTCS88lSUneJTw6cmqo4ZNxOGT+0I8kUlOEkhqdjA2nph8lp9ujC+Awi+SPN6STlLOz+m9KWOSL3zvKWtbTPZ1/MDP7cP4+MmBeEsf/x2WLzVwn6xVofylCGfhEz0tnObB0ypTqpUONz9huhKFxqO9RXgVATyAtvIW5VPXdoX2Dh1ZeIaYvFegY1BDOTHKIbkOwB1AeyKRyODPTk2ydfJsk1LpLVJEa6KTCBsGFxEC5ghAeYlQJfPSc3V+xf5hz/F4ZFbMUFawWqywzsZkmJBcY43DWkfTNJi2Y7dtGFrL48MWZxyZznjn2RWLxRVaSBbzJat6zm79GLuhDyyM4erqHdbrLS9eKPJ7SdP0bPc3LM5m/OzXvx6m0Hikynh8XCO14qvvvsehPfDw+MD6/oZ3v/Y+j+sNi0VJrgSvXn3KV37iJ5kvZ6GzjPUUmabdHrGuo64LnBnIdcHQ9ry5uUEgWJ0tEU6wqDNkpjm2DTQGV8+oFgv6fiAYGGF5fsn28Ya+i8lSWqPcQF3XHDy06w3z8wvcIfjLDZZMZWR5yZuHWy6eXVOR87hdh9hFXWPbjjJXwSteFhR1iReQS09/aMmXM3SWY/qBtg/gnymBkwKVaxbVGa/f3PDpJ7d8rawpzj2P9zdkeUU9q/DYMW27Nx3DMFCUBVLJ6CZJtUlCMwLnHKO4HfLfA7ClpEIAH0xrUkVikyQTGAuleZ+RktLC/ZTIY/A+DHgSg02lNUlMmRGYTqLCWzA2JdvegUlyRHwt5j8kcv2EwfP2+DCVJNKdqXxyem3KnqdQKcbPOIF4Wilo6p+PvKayseP3GWWTk7wy/YwxMeetz/5xQBu+5MAtotdPCBGKzo8nyGkEPLUMEiPjRoTgJMqjoxkqI5YV9gqddGwfajwoH3VrFNpbNKHimsaRRXYSpBMfgd6cHCGpBknUtrPo3U6ukmxMsPFv6dop8zJO56LDKUT042mR9D8LmS5YzJecn51z89kN9+6eRTUPswElcUNgS5lSmMHEtmWC1km8MTzstyEdX2uEdRz2LYvZPYXOUUpyvjqnKCuG3rLf7ZDDDcV1zqwuOd4fQ/tAKXj3nef8vp/9abK84HH9SFGWtH0XqgbWFZ+9esWh2XO+qHn28mts9xtmswJdlBw3O64vz+ibLZ89vMHYPvxuSlDPS47HA2VVYAV0XYd0guvrSwZrKbKSh/sHqkxhD3Bx/YLBdWweN2RlhbWWZVVjnaMfWrTOEU5QFwV9P3BoGrKqoihK/HxAFhm2H+iGAS0FfXvE4MjzDJ2VNPt76iJjebnCoUfp5NA0YcAtNE6Fio+yLDjud5SDYxhaZJVTVzO2my1yUVMUBX275YP33udb3/uIpv8u7768ZFbnWAydaFmdrbAeNpstWZ6RFzkg8NYjVfCBOBualiXW7d2JXYfrAYQ7NRI5Pe+j4yTUNpGjMyMmko0s1+LHZiKQShzDBLDUhDillPWwAqkuyAmcJyAdVnpyfY+W3bjvb9HgAKjpqc/R2mmgEVITvSfSyBRL0iZSXZQvxNHJgWQ6i0kfE5n5RPM+GRG/mFGPA8nk74+yyN95ldPyq7/6q/zhP/yHWSwWPHv2jD/1p/4U3/72t5+s07Yt3/zmN7m8vGQ+n/NLv/RL3NzcPFnno48+4hd/8Rep65pnz57x1/7aX8MY8+PsChDYg0g3JUIZTRWi6UJLpJahvZeONyURQiJ1qJ0hZbhlUiClQgkVmXDoZagV5DIEF7XSIU1cgUr2PkVsdBCDkFqSZ4I8k+SZpNBh/QTWozQiok0w+rS/+BZAOzQbjrWGnYgAnopWxTrfTqKFZj6b8/Wvf4MPMrzZOgABAABJREFU3v+A9cOW73//Q0w/RDkB8JArTSYVWkgyJZmpggzNIl8wr1doWSBVgdQFm4OlGUKSSdu0tH1PWc+ZLVYcWsNmfctivuTZ1Ts8v37G1776gq++9w7eOB4f78jLDK0ExvZY69isNwjpefflu9QXl+wPW/rDkb5ztNst+dmMvF5wPOzoTc/7H3wVlWd0w8DgPFfvvoearSjqOXk9I5vN2HQNg3W0TYsQoeK5Kkoe7u9ACy6fXZFpSX02Y71+pCwLDrs1ShU4KWjbjiLXnD9/QX9owiFWEucc+WJGXpZY4xn6jjxXZDoj05qu6/Ee7u8fsY5QU2XwLBYLhq7DIRjaI14o6tWC3Au67Q5jBrQH0/bkdY7Z7ukODf2xwZueuirZ7Y58+OErPv7wge996/tIL3m4f2R9v6asa8qqDNZNdCxGFSSGkNUrQxOGpEnE1xLxDP5GgpMlJYe4UzAyAbQYaa5DeEPoCBUygxM1fVIhEH44mogTmEcjWABWd9otTwDCEbrGWcEEzCaE10/+jY+nA8K4un/rfU//jh/3RI55a3mbNU9KOr+9H4k+Jl379O+pE2dk47/d5/42y4/FuP/9v//3fPOb3+QP/+E/jDGGv/k3/yY///M/z//4H/+D2WwGwF/5K3+Ff/kv/yX/9J/+U1arFb/yK7/Cn/7Tf5r/9J/+EwDWWn7xF3+RFy9e8J//83/m1atX/Lk/9+fIsoy/+3f/7o+180KK6NU+HbbQNimUsxTTEya8+ERO0cKho0NDc7I8JWuU9oG5pMBk0K/jfS/QCPIodWhAEQr4KEB7gRCaDBvsf1JEacRFhh5bmBHZ9yiPxG46CaCJf/0pIo/3QSqx4eQXLjAJaSUZOV/54GucLS549dmnHI8NZV6wmq/IMh2tjYpKFaGdWdNizBAufB8Yt+kHbm5uyXVG3xbY3vCwOaARaBXqZtjB0g89s8qRZxnvXK9oug1VlXPsGoTwdG3L/cMjWZkjlWS33lHWBbvDHkyPrHLm9QxdStrG0K93ZIWkqmryWc13fvAhs7rk+vIcM/TYrkdIQZ4vUR6cMczqns39A3jompYXz18ilWB3ONB3R4ahpR4qWuPI6oJ907BYzHFeonVG3w3sdhvOLl7g8RgM81nN4W5HsVyA88zOV3SDodnsmS1qjocdeT1jsBY3OD788Lss5yW2HdjtLZfXV9hhQKuMRV3x8OlrLAPPX77Lw/qem0/XvHzvfZrDEek8/foB6w0bs2foLYfdAeNqmm7Ly6sz/vv//ht85Wvv8xM/+VM0bYvAIbTARunMi9iiL806YwB9ZLcTdu2lP83WUuBPEZm2jfp1bKn3BMD96b4Pssr0unobtJ8044bJ9ckpF2W6/shyAzMf1c6kG5PY9xOK+3mi/YWSyedl9ykYv/0843X2+fWndUvCDEWM+z7965+8+em+PYnf/i+ANoDw/yvvisvt7S3Pnj3j3//7f88f+2N/jM1mw/X1Nf/kn/wT/syf+TMAfOtb3+L3/t7fy3/5L/+FP/JH/gj/+l//a/7kn/yTfPbZZzx//hyAf/SP/hF//a//dW5vb8nz/Hf83O12y2q14g/93/9v5PM5iOBnTcWMpFKjNCLiFOWJVKIDS9eYeBvI6SePTfBNiyE89gaBRfuwrhYmBioHSppx/QyL8sNYHTCsH4A714oiU2RSUecZhYoebinGXpOhdCbhRLNA1LOxAbj9EC5QQbhIpQ8uAW89SqqQvGBCOpDH4a3j//Fv/5/cvn4gV5Iyy7g6v+D66hIlFc2hpRt6rHH07YCxDqQg0wXOea4WOeeLJXVZcHN7z+ube7rB4pzhfLFglmt6B3We85M/+Q0+ev0xz58/Q+QF3nbc3W9Awfa4wwweLz1FoRmMpYwasHSO8+sLdvsdTd+xWs2xpkFJyMuMLAvtvaTOyOuCsqx4fHjg6vKK4/5Iczyy3+w57o5cXFxh3JGzasl6v0NawdnyIjQsyHOqYolFUsqMZnOHyKvAUo1DK0nX97A9ohZnoXb2vufY9qERQ7slX8wZjCeXhq4fuH98w+rZNbu7O1CSpm/x3tN0RxbnZwjpuX7+gmK1oN0cOO4fWJ6f0ZmB3WFDXc/CbER4ijwc4//Pdz9CFDl9f8S2UMxK/rf/7Q/QH7acL865uDhn366RpaaoF6HmTaHD+e9O7HJkoPE+Y6/F+DdlO3oX4j0FNL6kpaDzGZ2oOLqCloLGl/TktJQ8+iUNJY0vxudaSnqjoQV6EA3Qgu/CXxqP34a/rgGGKP0ZQqDdgjcizgII57wJ5zteRO3bEhwkQ0wMcjhv8BhCXWwLfggb9GbcuCe+L9ppko/6c1r720HKxN5FmrG8DdxhSdbH0zbl+NiRsjuBKcD/EOA2puW///f/K5vNhuVy+dti4P9PGvdmswHg4uICgP/23/4bwzDwJ/7EnxjX+emf/mk++OCDEbj/y3/5L/z+3//7R9AG+IVf+AV++Zd/md/4jd/gD/7BP/i5z+m6jq7rxsfb7RYAqVXQ1CD0M0wAHT3VI3g/CVaKU6lUTp7oEBxkBMaxGw1hm1oEnTu5T5LXOjlQslgISiHQjjHlXUvIpIhMW46e2ZBIE9YPrsbkffVBEklzyDBDDSf0pK53eM6BCdvwvQspo06CCA4Uay21zpmpKhYu6nnz5p6+G5hXC+Z1Ti4yDv0hulTCQNAPLTrT7DYd89oyu7jiZ168z/X59xhMz2bXUKgSKxybT1/z+v4BJxVfef+cej7DyAwlK+rOcmz3PLu+pmk73tze0g89eVaw3R/xWK6vLrm5eU1WZNR1gZCSopwhlMMZz8EMFLOM5dmc7WbP/vEB53pubz2vb98gOscH77zL2cWSZt/inGLfD1yeX6O857DbM5svGQZDJ3YIFK0oEEWJdwPBRwRdc0QYhZEhAenwuEVaQ6kVnW/pjYHjAVTG+tjhbMvV5TM+e/UGJRzH44GiKEJ9Ealx1uKsZ+gNP/j13yLPQw2P1obKk89eXLPZ7BACnr94wQ8++pSbxzXGeURvsL3EeMPLyxW7+w0Kz8fbT7m9v+Py4hx3aNBCQLVCDAbwuNR8QYQCZx5Odlk7AR3pA0imx7FOihCnImuhQ1osmiZSmnxoyZfiMVPsE/F/3nucEEE39+HJ1DszzJDjc2kGMAEuIaOEk9iuCPGbKYjiwAkXPy/KROMb/GjPS2nvQvgI7mL8DuP0wJ9A2qcvETXwUZofQfttfi5OQUYxeSklBsEI2k8Y+WlPv8C27d5+4ocuP5bG/eQjnOMv/+W/zB/9o3+U3/f7fh8Ar1+/Js9zzs7Onqz7/PlzXr9+Pa4zBe30enrti5Zf/dVfZbVajbf3338/7PwkOJn0vcSyR8AWKVwZH8ca3kl3S5ryyZ/q33pOfO45PdGspZQx2BiBOgK9ktOAozsBtkglYCfPEWqdJA1SeMCIwLqjrj1qg0mnNHEdH052IrBLAkNxxmP70Il8MauZlTWr+ZKyqhh6Q9N0tN2AkJI8K8LMxIWglPMWMww0fuDTT1/zyXd+k+Gw5dnzr/Hyg9/Dy/deMK8LSq24WM2oipzddov1cDg25GVF0+wpZzkCye3tA91gUEqzXC3x0mKGnuVywdD3rM4WVGXBrK5YrubUVc1+u8GJHingeGz55JMbnA+ZgVkZsii1AS8dDS3KeTLtOFvO6Zo9P/joQ17fPpLPFngcQ3tkff+AN57jYYtwJpZDFahM4qVicC2GnuYYXm9sh65ynLFYO1AUJUJ47NDS9wNN03C+mtObAWMtuQqNe9thYLVYUuY53/ve93j1+oaiyHj27CVKFzw+PvL69S1CaebzOTc393TGgFNIqXAOjDHURcXFasm7L99luTrHWMknn91xe78mzyu2611oYG3D9YgLmZ7OuOiDJpXsiIXGIkjF+yd/NITOTZPz0T9tBpCeg9MAkK4ZiQt6n2Bix41Zhy4kpEzJ0yhJPKWeT611TEA9rfc5pppamXGShVI/x6Rw++l24no8bVjwtEhWAvLTv7f3/XPa9BcGHSfbmQ5Op0978lpSDH7U5X+ZcX/zm9/k13/91/mP//E//q9u4kde/sbf+Bv81b/6V8fH2+2W999/fwxIQtKwgu+axLrfYtrjEROB5eoItKF9WGr6+1TnTg19T5XSJgkznkk9Ef8k4zHo4+liEChkTG4gSCnRmRJ0a/k0QhNZNlOgTvdNuj9l5mKcIaaAkxSSTOXM6xrXC6wLVkaU4Lg70HU9eM+iJviQM03X9jRNgxQyJDhYgROCx/WWef2GsjpSlBnny3P84hlvPvsYljVOlQg8+8ORn3j/A1ymUCLj/u41++OePFM4P7A6W3J3/4AXgrLIUVJSFJqmOTKb1wghuHn9Go8lzzKG3tJ1DUWdUc9nNG3L6uySolTsdp8hlGBe1uzWW3aDZzav2K5vsMbz/Ooaay2P9zfM6jnGO9abHYMNSU93N6+YL844P78myyV5keGEIstzzL7HZ5p5eUZ/bPFdi3cD292efmgBj8oyBjsgrEVqTb9v+Ky/J8tyus7z7Q9/wPX1FWW1QLUDfdfxP7/1WxSzgrIqub3dsLAOO+R8/OaB3jp2x46uHTAuAMsHX3mf8/kZm8ctMtMU8wVnWUFRLfns03us69B1yWp+gdI5CB+6xksRmH/yWJNGfX8CdO9jpmCIlyTQSjbAEKCMvVOxTJnmFOBPqfCMjoyEPwLwI6BH1j2NFKZ1hAj6SFJ6Yju1pCs81cQTa40ZiiJq+SnLUTzVjJ8WeBqBIl5M8vRcCuB+weImPSKfBD7HxJwveNN09ci2x8EksW1xkk/C5r5A/P8hy/8ScP/Kr/wK/+Jf/Av+w3/4D7z33nvj8y9evKDve9br9RPWfXNzw4sXL8Z1/ut//a9PtpdcJ2mdt5eiKCiK4nPPCy+DHjaO/KlluzhpwafzLQRs0m8lwjtCyu/pxxgZ++RfeC0EQaUMxeinzD40Tk2FM4OtUMTo/qTaQbwIwr1wgofQBunHj3Y/YALWE4COmuAY2E/rGP+EmXsfZhXKS4qsQKseAeRZgco0ykratg2V5mTG+fycTCuatmG73eKMx9jQveY4BJlqvdlyJT2HdUO/vOTqvQ84O7/kznT03RapYT5f0h627FuDcR0QuvD0vQUtado9VV3R9S1ZlrHfbmE5xxrHw8Mj9SxkbVbzOc3xCB7eff8lTdfgJbz77jsMzrDfrrm8uKB4WbF73LJdr/GZZ7WYU+QlQ2uZLxd4ZznsdhyPDcdjS+c9h8dHVvMaJwQff/qKTz654fd84wPmeYbxYHct+Nggw0NWhEbAIFCZoJA5Xnh+/X/+Bu+9+y5SCbbbHT3QNx1eKg6d4WxW8fC4xsucs7MVjfE0/YCsMpSXoDUfffSK99+/pjOO7f4AUmNibY1ZXSDwCKG5en5J5wc6PMZ77tZr2sOBvmvZtkf+2P/l/8xgLEIOQMis1EqFjOE0XXeMssm4RKzDxWC3jNa/8A5IbHMCLAofZmbj1DDIE6eaIHGRhCbcYdJ6ArCoD/hJuQmm70uXR5JSojwSgC99n1GMONUsmX4tHyWSNBgJJsB7+jAfa4ynsW1c3r4/YsiEmcd9GYtmTQD6bSCfPjeNPTwJIMP//xi3956/9Jf+Ev/sn/0z/t2/+3d87Wtfe/L6H/pDf4gsy/i3//bf8ku/9EsAfPvb3+ajjz7i537u5wD4uZ/7Of7O3/k7vHnzhmfPngHwb/7Nv2G5XPIzP/MzP87ujJY4fBqtTtORYCx+um74EoAQGJ2NJ6XDASqQWS/IhMGlgpcxsSBMmYiWpejYFDbUhSA1bAgjfzrJTqAvYiZbbKvk3QgOI8sgTjEn5Man19zpOeKUOAG9N08lFIHAmxgYESBFhneOWVaTZQVVPaOQGaaqQ21tqcmznELnZCKn0qHwk/PB4bJwju39A8pJutaRZRWma9nfv6Y59hy2R9pDQ+9abqqC+/vPePf9n2Qwx+Adtx5vHX0/kOc5ZjDBolgWDINlGCzOOZaLFdW8ZP245mG9Yb4oOVvOefXqFXlRkOcFm/Uj1axgNl/gDw37xzVn19csz85wfc/+ccNqdU5+ltMOFiEL3v/GT7F+uKOsZ3z7Ox8jpeThsy2FKmJmquM73/k+X//gGVJKbGNQWY5SiiKv6fuWw3BkvV3zTvSQbw97nj2/RuXBv73Zb8irOXVdcOyOoV63rpBesWuPtINhtrwADd3Qs28tX/3aV2i7jgGBU4LWDKAdWa4w1qAzhcNSL+f0wvKtb/8mv/lb3yXLc/CBzMzqGTe3W3rbkOUFNsY9VKaw1oRTJgmpCTyT5j0BaC8AmVzZMQLzBWDydlBv+jhJCCFgk4jJBNDiZyAmQCaYtCYLr3tjx2vURyBMzZLDdzi1/z1du+naE5MkmtNnhw2f/OgjDns57vfbLpBTIHECpkkWebKqHz/PE1Pbw0bHmFsKTD7ZJ/H54/njLD8WcH/zm9/kn/yTf8I//+f/nMViMWrSq9WKqqpYrVb8xb/4F/mrf/WvcnFxwXK55C/9pb/Ez/3cz/FH/sgfAeDnf/7n+Zmf+Rn+7J/9s/y9v/f3eP36NX/rb/0tvvnNb34hq/5tFyMQdsppxRgk+SLbUSTZwfftQ591h8SgsSILQT6C4BI6eIRGtR6PRYAfQpzaBxui8CoAsbDjhwbxJYF7KEofVJrYF29aTjP934sTQE9Gm9G7nV475T2cGHpi6Q4wU80t2CKXszMebx8QHkqdsSgrtAere7yVFFVJmQem67Qly0tSVUXb9GjToZYrdts1q9WcoR9wQtLv9wgj8K1lWVe8Wbd86ze/y//pD/4Ui/mKTz76EOMMSimcCeVXB9PjnCDXJd2xpcgLnHEYZ+n7gf3NjtXZEjKJd7De7LDOMKvnoatM7yirazb7DaZpOF+c0xwPXD97GTrI+NCB3ihFWVSsHzYcmyN394+szs457I/kVcn+2CMWJUqI4FAqS9aHhkIo3nn3JZuHLXVdc3v3wLyeUy5rVHfEYjm2A69vb/npn/o6948b7tZr3vvqV/n401e0xmJClI+77Qbv4fnzl+wPG243W6ocuqahw/Mb3/oNFrMlH9+8oZrNkJkir0oOtiOXGZdXF5RVwf3+jpvv3fHd7/0AISTDMOCBzvVs2x1KajaHNfN6gc4KhLJ4Z2MM5y3qmPTsBNYiPp7W/Ek3oXFefY5xOy9HeWLccjrnZCIb6XPEuO0kFfjIVLz043nspUek8zzFDa0P69h0RUhCrex038X6TxIR2c74DeKF7rEj0Tq9Hq8XkZh2ul7eWsSkK8+ERKfPSHPxL06qSZ/nJ48ZQT1IJaeEnCmn/FGXHwu4/+E//IcA/PE//sefPP+P//E/5i/8hb8AwN//+38fKSW/9Eu/RNd1/MIv/AL/4B/8g3FdpRT/4l/8C375l3+Zn/u5n2M2m/Hn//yf52//7b/94+wKQMgCm3RvThqRSAcn+bin57CLMx4BVqvx3HJCIb3DoQJoJ2btJV4oEqtOJ/z4Qeixu7XzhKJSyMioJR5F6vuXytGEE8bh44gvRsoxWSYgfdp3/3nNO0knE108XQTOOM6XZxwvLjhuG+ZVGQpjFSVNa1G6oKprcqVRUof2Vs4gncSYAWcNmcrIFyXOWfaPj5RFzXpz4OHOcnWxIs8LHu/WtMfQVOHZ1Tvcv7mhbQ5Usxnb3R6lc5TIGYYGpKcqCnQxG0t/2q7neNjz/MUzlss5Vd9y/7Dm0DYUZSieNCtqdC7pWsNuveenfvon6JqBu89uqModQ+84f36FNYKhD8FVj6WuK1YXl7y6eUBXBdt9gxOS9eMGXSj6wbD2DR+9WfOTX3mXpm357O6Ouze3vP/BB/zGb36X87MzqrqmMRYnBfPVnO98+AP6YQCluLl/YG8HKpWBlOyGI7XNQUi+8+nHzMqcQ9/jpaYqajJvybKMxvQMzmGOe3Qezru8zMljPRmv4Pbunu/+4AcRa0IA3qZmH1JgneH+ccfF5SXWxjhGlC6EfJsx8jYCPbEnhMT2U+9WCK3NHNNKVURiwxNGOpZJBsZu6FOGLSMQywloCzHeP4H3KbNTIEDFz4jFSU4auQzTTcBHUBfj/QSap1lDDNufnn8rEJoGlTEJKDlGSPJpAtx0GCdBx6Szx02P7xtn1G95vZmw7TjATSWUH2X5saWS32kpy5Jf+7Vf49d+7dd+6Dpf+cpX+Ff/6l/9OB/9xUuya6blczEIP5aVHFlDmDWNGZdOqyhuKJwY4TnGAUWU6ASZsCNwO+8imMf3RZYuRbwvPCI+K3ARsN24g86nH/J0ek2SsZ4y6/T37ZuP39350SLoLGPRfBk73dvBMC8qyC3SOqQOFKvKC6QscF2P9wrhNJnUKCEZhp7jZk81VwyNAGlYzJYMRrNf75AadusGgcAaz/EQbHgawbf+9/+JUwaLwJg9RZEzXyzpnaHrw9EcOotUju1+S1mFpg9CwHa9Zr/dkJUFpu9ZzCvyMuPhcYOzhmfvXIEwKO94/YOPma9W/Owf/EOs11uUNihVcdxumC3nPD52WHL2reOTV6+w1rM9HrAE50dZ5/StQWVZ0MD3HUoJLuclSE1e5wymZTbPWSwKPv7kM2Zn55hhoChyts2R8+trHh7vWe+PaCUQWajY987ZJfv2yLHpUFphBFSzHOMcj7sts0VJNZvTdIayzBi6lqIqEUpBoelNz7E5UOQZr1+/oaprlmcrhq5nv9ti+kBKPKCrjG99+wcsljXPnl3hnApMGouIMZ8njG70uTGy75CafpL1vFA4n+JF4bq3yU7n3anP6w/BgxRj8fin3nI/uS8CmCdJM3Wl8hN6+4Shjy3ATsw7NfMN13coJhf09wTW4zDwxWx2KgONhOqt4Cac2sElfBHxeiOKpvFYpiBmwowkh5y2lAaNuH9SjAHiEIT90e2AX+paJfhQO/t0YsTn41RJQJhqpZFVEMtaRkCXEoTHKM2ACmBOmA5a30e5RaWfByUCqCupx0nQiZGPKhepOyQiXEQCEzptiwjin5NwJhHu0cYlxsfee4RTgX27kVAFC6EXITjpBdKp00HoI2OwDmM8Q9/ToyhUTl3VGJehZE7XNnhrELJHEWyBve3Ybx4YmgItFMPQ0/cteV6GQclqMl1wWDcYZEgD7zrao8cvJN5L+sYilGO+WHA8Hjk2R7ySocN8FcrLSgeZ1pSlRuswz+5tz7wo0JnmYfNI17ToIgMtubl5w8X5gq99/QOMl9TzFZ99dsNitWB2dsnxsGV1fs7+0KBlTpkPHLYbri6WdIPnbr3DHFp668iyGcWsZL/bU85rmkPLJ6/vEO++i7cNjRl4PLbgHMfBYlXG69s3KJUh8wxdlmRlxrFvqKuCsshp7JHN/siAQZcFRW8pz2uEytjvjxjvkblmcJZPXr/i+vkLlLMYK6iXM5CK4+Yh2FWl4uGwhVzx/PKSpmkYTB+kGMnI0BfzGZdXEqlVKHuJxTqPUhnJLH1ijgmgQ1nYZMwI+rbHChnG/Wi1c2RRFhQ4D1bIJ+AW0ls8QjisT3NHj9AiJM9ArF0SvNeJRXsZZROXwDsCnfRgxakVWmLmhEvJ2VTmSUWP9DSwGMo3gzzJNOP1dRI4whNiJE0T20d4iwiumSRrSO/xSiBcYuAT5uyDSSEFTMPb07bDekKIEfiZvC7FqXlz2p6YDBi/0/LlBu7EuJ9Kbk+nQFOLTQqQyCixWB8vEoGXp74gTgSJI0jHU0iesOpk9EtM5QvcKGmq5IUihFEkOkVPSNOlcBlJn6aCfAHjPslBfuIeSanwTIF8MgMRgPYFdrA8PKz5bHfLcj5ntaw4OzvjfHWJk5K+jckcWSgAMJ/NcZ3n7uGBLNNBMwU26z1lUdJ2LQKJ1pLm2COlItMFZV1RZCX7w47DYc/L915w2O6RmeLq/IrO9HTDQLNvaPqe+XLO9fklu8OGobchU1LleATzeskwWLwIZVH3xwPtoUGLjKZtKGYXZEXN5fMKLXP6ww5hPDZz1POCm90jduhQCnCO9eYROwTNXQrNsT2ipKae1ygVpCEpcl7d3aOV4GK5AtfTNEes0hy6hmo+wzrPertFaGiGI3ldsVpdMK8cu2M4j47HFuMGyBSP2yOrsznd0NGZnrzMKPKaXJbsj3uWZ0uKKicvMrwWFF2Oc46m63hcP6BVzvc/+vDJbyoUOOlCzZSh5yd/+g8gkEgNzoRSwvgT2w3T8Hj+jBdK8LAnu1x0bwPE7qonDcVOsw0Ts4wgJ0bwjMg3lWeSXj0FJHli3aN7JFUvdFMZhROYjt88PjWRHIhZwqd1pp2wNPg+viSfMOzAmn0YyDyROZ/YegpCTh+P1zOn104By7dAd7Le9Ek/SrXiRNKefsUfaflSA3c6XifbXxpZJynuk2PjxUlHQxCKVMXElcCSEyArvEjTowTUPrYR9SOYhyL0iZHHdb09AbwPrhQhbARvO9nPcT4Yp04u1BxJv95U4xacLFsT0H6idZtIsFJugfDx1M25Pn+O7Sy/tfkeN28e2G817e6INJZZvUJ7Qbc/UhSh+3qzb6l1zmOzwfYOKQVSCWzvEIXA9pZZWZBnCpvBoe3x1tEejxxzxeZxx8WzszCdHAxFkTP0oa50kWmKckYdWd3mYY3TnqZpKEzGcrWgObbcrzcgBVWVsV1vOBwb6nnNcrXiMOy4qs/Y3t3S9YblvKZrOlRWcvPpZ3zjG18nkxKUIp8vedweMIPn2fUFn376isOxj+dAx7FrUCL4nTMl6duWui45dB277YaL1Rn7rsUJwa490A+WY99S5zMG72nahmYwXF+sODQti0VFUWka4fFO4oeOpmu4uDrj1Zs3yEzTW0NvBp5fnuPwvPvyOcemoahLju2R7W7P4+YR68HZPjDVqc4qCa4TbxFoLq6vOO4bjDPBgufFJH7oR0z1EfUSDxeJdUo3SiPOy3hteYyYBv55AkYiXoAiTfXTY06fQ8IzebqN+CbjuRqzJUUE/UTESO9zp79JzBmLccdzPJWnPS1RDw1HCx+/6wkh0jUixh2aDkCnBCNOBbGmWJIYMifyNS5vPX7KtE978HSdt+/8zsuXGriFFeMPLZhMPSBSk+nacXqSToaUzBIDi0ZlKA8Ihxc+aqEJpCVOhFZhLskghJPcCTmRUzxSBBnFeY8WFoHECxGtgyKyGhsZTUTnWDw+SCITmpFcJjEo+SRzMtn/DEHrS98ntnsaJ3bO4K3n7PyMFy+u+PjDG4ZecThYPvvkNavZkdlsRlFWiMHRdw3gqMuKq8tL3tzeopQkQ+MGR7trKXWJQjIra4beoRcFj5stUgrcYDhbLrhcnaMyxayukFqiMk3TNehco5Tkzd0DzgzMqoJ3vvIO+p2c9fqB5thg3MDQD8wWM+xgOe6PZLnmg/ffYzADi/oSI2B58Q5ODNjeUQhFlleUx0Mo+rSY02wO7A4t71xeB/eKd7x8+YymHbi9X+OB5tihCk137KDwqFxRVRWD7SlnFSjB4bhnsViy3q1xAurlHKEkh67h6tk1t3f3fP/1a5bzghyo6pr7x1uWyyUWQ14t2B8PLM8WeClw1iK1ohka3nnnHXpnsN5xaA7kZc7xtgmyShYjfs6NRZuS7XUwA3mRkWUZHsdsUWNtiMNICdaG4GQ89TlpuOk5FyZy3uNTkNifGHda100ITdpWOI/lyMLD2RaurSfM3vtTO7C0JBA3/km8CSLWKsaZwhicdEH7FiM7Pm3sxLbTl/OMXdlhBGY/uf82UvrTxTY+Sjp10tiTNDNdQjyA0wA4Be24/6F1Yvwu4eARapg8oW/hk3+3MO4xY/DJ148ejQlwj3KJJyVohSyZ5MqwYQQ3UiPjS0naGCURgkYdKphYXAxK+rekk3EvhCC1dBKERq8+su9wAkXe7j2hbHL0i3sfikql7/TEBiieOExEYt3Wnb7LkPYgnOzWmPA+I1jWS+b1jvXdHtNZ7LKk7dZkUQI5Wy1RmaJtO9q+oz00rOYLdtsdWa5RZcVut2O5WDJ0hv22CRKlc2QqVF3p256LyzmzsqSsy9jlPcN4w+5w4H59RzWvKbOSXXOkXC1xg6UZ9tRFRS/Ay5zlOwuObYPUkqIqMH4IcQkkKivpu5bWHbg8f8HD/jVVPmO/vWd3e8cwDOw3a2SW0eK5/eRj9ocj3nnKaoYcHM+fP8M6y+3dHZnOgFDfQ+c69nP0lEVOZwaquuLm9pZnLy552G7ozcBx33B+ccbDes3gDLqUZFVOP/S0pkfG1kbX1++y7w9kVpPloSb56zc36FyFDEkJOs9QheLNm1sG73HaszhfsN/tQs2QqP+PlTDjOaCzHKFCI4a+7cO5JsA4E2qw+5RdmKb8YYo2MvEJo3QRBG2gsCGnC/ckWOh9BPdR7os3H2lLmgHLSBrS5SAZO7uPr01ZNbGlWpJJIhsPuq84zUpHtJuw43Hn0hUz6jNMYXGa+TiC+IRxTweA4BEXo7tsuo2nbpDJMjra/OdeSvuenn86IMQEHt7OKf3tly81cIsmAeQTWRs4jaXhdXfSopVAOEm8BqLMIiAXWBl8qyZ0WaCgw070ai9CD5UgmwSDkcUyhiaFx5IR0uXjfkSNMUC+PWmJ6WQnnCjeWZyVwU7rPVgZANxFVpKKn9nErn2sBhhZd9L7DadpKqEjvDGeSi3JL0quzi4ZuoH145ZXr2/46KMbFIqzxZLH2w1KCYYhJh7pwGk0CmkI1sDlBV3f07U9fWPwzmGU5NgNWNejckVdWY67I/vdnn4YqOczjt2RfdOgdcH69oDONd4r7h839KbDecPl1QXHZs98UVMqBUXG3XrL9rBlPq/omw6Z52jp+PA3/yfXz59x17W0bUvrtmRK8M5X3+PmzT1ZVrFrWt79Pe8AkmfPnvP9736Ph/tH5saihGKz2TCbz3h83GCsDdJWppFlRq4zTD8gMkW1WlDNKlrT8OydKz57dYMuNb0zqFwxdAbTK7yWqEqyWq3Qh5Ztf2ReWeazJS+/8pLt9hFjDC/ff44xBqklPvN8/+Pvcf38mmJesH584OzyjMV8juQFj7s9h8OBtutHO6BUKiQIFQW77SOdbcPgaGzocSh8OE8jWJ4Yt+ftlHBiHCcYkkRwAxFzHHxwSJsIgiEz3oWOStEBMQKZM3ivorfan2yG6W/cFyc8pGY5mpiH4YPeHvdHyMC0nUmd3DlJK08AOmgtoTJgZNoiDSQCxq41nrGqFSewTsDvp2DOZH+nM19xSrKbHrspSou341cxCOm8iwOQj18lDEbWnVi++NzU5LdfvtTAnVimRIxTKT9hJpE8jFMsIcQp8GHi46gJJtnE5ckeKLGxYWqQSlQg+D4wcRmfAxHY98QiKCJMj4FNkf4CkX2nKmI+ftaopYXwfbD1WYIrxhGeS2wrBiL99PXJzeMjYwlzAUWoVidwaJGTFTXzdxY8u1pxdXnFd3/rQz57fQfeU1U5WmouzucMR0eRZ9RlztAN5FUFgNAFVsRWWl5y3Hd4pdAqwxrP7c2aw+GIlzCf1yAVWZExq4N/xjmLRXJoDmROsVrWrJbn7LY7qllJLjOOhz3HrmW333NoGp4/f4bWOYemocozLhYrcg8Pdzccmp6vvP8+n75+g1xvECLjzf0tX/3aT/B4v+V/futbFEXJt3/ru2gRgq1SwvNnV6zOzlidzRESDocDdVVSFAXeWZQWZFoxDCFZ6Btf/Tr7455XN2+w1mC9xTuHzBS9cRg87zy/5vXtDe+8eEF/55BkNH1LMWiyQrNczrHCs95t8d5z93DLvtlSH8rAcr3i2fN3KDJN1zSwb7h+/g7HY4OQgr4PvUKdd+wPLShFlmUMvUcowWhRk+IJDj3JcoxkIs3rrAvomiSSJJmMoOaDHZCJ1nLangGRRYxLKnxYxBPwDmAeZpdBzx5LUEStGy9CASAXBh8hk/MkyCVCihG8RzT3NoC59wipAXOSaSAC9glwn0BjYtw/xM2Rnk2p7cSvKCaaeiKGX7QdMR0kTs+E7X3BR/44nPtLDdw+AlpSpcYDHRn2xMAzJuP46NUeg3smvFMWoXs6VuKVwgSvB0LmCO8TB0EKjcOOoOwm3u3UQtuHljwxnSElDZyCpc57nEg1TQAbknHwgHPjdJAUQU0FG1Lw0YTvTQRxFwF8vLlwFNIBcWNlKjWW63QeMrXg6x/MeHF9xetXd3z66Rve3Nyxb44URU2lJbbtUXnOrJ7hfKjVkmUKJSUff3rPMAygNX3bIPMAKFmZU+YVi9WMssowbuCw2eOlAKVIleiWizmH5kjfDXy8+4TLq3NmVUnTtUjjWKxWHA1sDg3GOjabLd4rPtv/gHq+wPYeLzRts+e//8a3UFmF0gVNu2e92/GD1/8vHh839L1F61BtZvAm2EAdfPLqlr4fmM1qyjpD6yVFrjHGoLVmvqhRUoP0vP/Bu+z2Wwwgi4Ju16JtT29BZBm5MgzW8LBZ89O/5ye4ub9lPsvZ9wekkqHuOY6qysGaeL+gGY5k9Yz9oWHTdby8esa8rnhzd0eWF5TViq5vw6ngBEJovLB0TYcTnrPFDOsU1pt4bqsQn/YGgRrZZKoCOJZh8OYE5FJjCa3O7AgugbCEM0mN9r/EQycVJibAlkDdBRnPizEJKCkeWgp8HFRcKv0amapIRZdUJCb4k6wsCNfnW5+LCFnM+MS8p5JHjN8n5utCgvzYcNm7cG0LgXOnY+Mn7w8DAqNunmbyo/86eXHECX8SWQ/7L0OMQnDyokf5SohYWmD6fX7E5UsN3GOALsogT8pNJoZ9miuepmEpkBd17rHONaFOsFVB006JOF7okTkHpqzwuAjaMWApUo3AdILbEdTTPxubDJ/qhMfvIVJAJdYvEWFg8dY/Zd5JJnHxJEggnm5D/DueXm4ynDHaj04JGaGGc60X/J6vL/mJr7/P3d0Dn/zght/89vdQSlKXNYM5UpcFq1VNnmXgPLUuqcuSx7anbRucglk9w/Ydznj2h45D2yKVYzavOLu4wFiDERaLo+tDJ/iqKBj6gVyVbB93aCSzZYXxns3mgBt6Ci3ZNwOH9oDDcD7PufvkFdfPnnF3vwnBWZlxc/uAUIpj09ANA4djg9IZSMvP/v7fz8ObR4SEpml4XK9x1vPmcc25txRFhpSaSlcsZzPAs9lsKfKcn/qpn6Cez1mdrbh9eODQfAuVSfJZjs406/0h6Nezmt4Y9m1LZwcOTUc1n5HlGVme4YaOx80a5xw6z1gfdhzalqY1qOUZq7JGFDOOvcOrgt5YjDforODY9AxDG84ja3BeMBiQOuPQdqHOinWEftgqlFMVU9YdhL3EtF0EY6K0ESoDy5hYEsqheUIAPskV49k0Ac+RmITwQ/gkKUL5zGEC2kIg1OnMFDLp2pwY96RH5shX0qdMNWJB+M3Hk9lPVpbjeiNhQ4zNkxP5ZwLECSWmmve4WnLOjHtCMBvE2idPnSmTHUzbSB/gn6wwSkpvD04/6vLlBu4IWNNwwOd829NFMCYEoDjJJTpKJSH3PYCmSsp1iqwn9mKxQiHFyXHi4wjgpI6TMov3oV92+qHTKR5klrRjfhxxBUEeGQGZk+7lPaEprJUnScQSgPpttj32Eows5q2TPn5quoOUgmHoaFuLFJrV7IrVz5yjhOfN7Yb97kDX9PRVhbUuNF/QCilguViy2x7Qcbf22wNCCpz33N9vmC9rlssaZyWbxx0ikwx2YLAD9axC5op+6CnzDK+CqKOyHNMbbh63eCWROQiVsd4dabojFxdzvMyx0vLqdsPj4y6UC1VBjV+v1zGSL5FSB2kBeP3qNc9fvMuHH34PgcM6E+NTksf1DiVAZpLNZsdiXvPinWecX1yiJBwOO16/eRV+bykYTMfZxYr5co7zjspZWjPQW0NdF3zvk4+QSvLinZd85/vfYXm2QgjB4CzWW/JMI5RksAKhCsqy4GG353xxxu16y7HpEHmGMQbjbOhR6Qi9NdtjBCSFc47ZcglSxXKuOnYkC0lkoTeHQJLqaMvxmvDxvBREnzaBWbvEAnkK2qeTJ7By50MtnlEKTIG7CFIC/ySdfvR3i3Q9xByKGIw8gXi8PqeAlq5L6aIUmPb3pA+ezngQTFPgid8lzB9OCTNMrsL4IKXqx++Ztve2xW8qvTxZptgzDmzEZJtTtmt4+a3j+mMuX27gjo6Qp2A9mbLhn7LudNeF4lQBbwV+AF8E8BYqsForNVIm/3YWObaPnSKTPSolKjh8tAXiLQ6NFcEOaIMCHwBbnHrgaG+e/m7p5EhdbHz86yCltTvrwn7bk75NDFyO7HtIw00sgzlO/04nXyo2C2BsSOyXZAAM/YAAvv61r/D8WUd7bNhud2zWW3bbQ6h/slqSVzmH9ZY6q3CujUEsS6Y0WmtUppBIdruGvFBkZUatqpgEI2mbFt+CFRapoVAZw2A57I501vB43KOrgsfbHarQCC2Y1TXrhwO7vOXNw5quH0JRrAgiXWdCgFHKEGQ1Zrxg7u7veXN7H6bHeIpM4/AY63EuBOGscTjXkvWKN7d3DN3A1eU5da04v1hy//iI0Jp333vJodmzP+yp6hld11Euag7NkazMUHmO85Y3DzcUZcHgLFfPrnjz5k2oc56VbHc7ZrMFbWtpDwd8lnPoLZv9jn42pyxLbh/vWcxnZFnJMFjKqiYrC9qmpe976nnF13/iG1gPUudYY2IRvRMAhZILMSFnyii9QMYA4xNHlA+AHbIkT+fM9PW3KejntVkfGHGSQdJbE2FK52vydhtCLZOphzuNACpeG9InJTJ8Bw/RtB5nuwNvI6GPgcskqYwMetz3yUz9iSb+BdQ3BTx/GGin/foceEfAflvUTgrAJJ7w4yxfauAWNgLwkycnd1MSzvSFdHwUI3inRqvCh2BIstk5eUq+SQHKkxySClLp+CjWUBDB552mo6G8qo3jRThrR5/KqJNNGDhJGkmyiDg9toCJU0zjRq3bR/Ytoo/b28gVfLB0vb24JydXrIToY48+T2i5ZQa09SyqikVVcn1+we3dIw8PG+4fNqwWC1bzJRKFkJLOWrpjj0zVhhwMQxhV6llFpjR9O6C1Jss1TddhfQjwtYeW4+HAbFnRtA1v9k3Qca3n2BmUg6wQHNsHvFII5fj/kvdnT7IkSXov9lMzc/dYcjlrnarq7lmBOxjIcCAU4V3wQhH+3+QLX4lLyuWFkMRg0Ojp6eqqOnWW3GJxdzNTPqiae2T1DKbwWNJRciozIyMzIzzM1D799NNPj+eMCJwen7i+ubaNpYrWSup7jocjsB5StZj0TqIQQ2LYbeii8aPnKbPd3/Dx+2/ZbHsU5X/8H/8nUhf5h9/8V6Y6c74/83Q68Ltff8urV6+sCWZInKeRm9trslRyrqhUuj4RonHjEuE4TXy+/2yUQeiYcmXY7nk8jWhIhG5DVuU4zSiR05wp5cxchcNxZrvtCF3iOJ7RClNR9jdX/PJXXxjSroEgCqFDS3F+FYI3g60qC3UEbrLAopfrwJD0YjLlgayqOCJ3FE4L6GvWZhLXbjkTxKZf26N8KdpgkwtqoKHoFtgvZIAEFkOqy/tFwkUbvNlVNGcQ46ybjvBCJeL/JMiyRtpR057fwvX/mGNepIItBq+Tc/7JMCuXLLleUKAX8t71r9m9i9zSN81PvP2sA/eSKV3eZPnfBXnFkqZcDiO9DN4UTJ6UxRae2oldPWAXjR580xrM3c61BeiixQKX3yeSaaY94l2TVSIE+35cRkFVmvOZaFuQFoClGP9uXZNiqMR5b3WULZN91AJMbXH+iHfzmy4IyRGZFhAvVHn33DydmGdrxTyfJ/I0gwhdSry8vWE8Tjx8PnB6fERCsixiPrPpO6rTOMXbPEOCaTQUn/oECuNobfK7aPruUz5wc3NFcPlZR2CqlcPpxFwLYynkUyYNkRpmQlBS6pnnic1mAK2cTkdUzYJAa30uR3PutJ2TtSqHw4Hbqy2lTHz57iu+e/+J1y9f0g3W9fqf/u4/cTo/MQwbzudHNv3ADFQJfLz7zK/+5Gs+P97R9R2v37zg88M9Xb+lHzpO44muj/Sp48XLF6Rx5HCaKNLRdT0PhyOERCmFkHoY9nS1cswzu901nz7fc7MPlCocT4VcT6YLL4Wu61EKX/7iS/71v/lLpmkylU5WRBQJkZwzMWA8dQMGLWhroS56cA/G0voV1oBcJTpV0gLchSrlsqB2QZMsmW5D21ajX3j0FrBXD25dkXXrjoxqoNd/Z6tJ2aBvr/s0bkPbMVRXsLso7Py5eD+FFS79W+01XSgE1w3SvntRHbpE5Je3H3Hi6x9f449a/F7vavTnxdcqug5++Ym3n3fgbvSA356NKpOL4A2ryD2yygCzn+y5oVqnVpzv1iKLe2BduiO9JZ61QUfFWWvvOGj3VVdxWOra2uj/iZu/37YhXFXSBiqUYMG6WhBftNveNaqzItk/H/W5WyItLbxg8xaO0S+Pb2zbmCOCEKVHg1JKy0I80FchT4U824EzTY7PFPrQMeVCmQtxG+hDJPUDSmGe2pMSTqeRYd/TRyuEbbqBIjO7YYdEyOMTu65jOs6UohBaR2qkzoqmCiFwfX3F+XSkzOY/vdtuuX84IkCuZbGC0KrEaOZbtQ2SpRLF35U+cTg88tWXb7i53jGeT3z95VccTkc+fJx5//49m93AEODDx0+MeeblixuO44ntbutX1fxU7u7uiHNEIrz54i13D3c8nM70wwYZC6fjCYk9u/0N94ejdd7OhXGudN1A19l46u3+ikkV1chcCjpnNFuQOo5Hbm63vHz9iuN5BCyDAKN8as4EUXINP4orFrQLYQWESyRTiq/lQvCAXZcg5guFZktsQVnW4SSYUqk0N8IF6XooCpjzXaNAGkWyeAWxcNxLtmj4x4f14pSMB1A/jJtWW6hcbiz90UfAOpIvlWbtZfkDF7qk0SoXTn/rJv3nA2ubxKMXVK1d40ZYrk03AEFt/TWq6VmR8ifcft6B+8eIW55//swfoKk4qiPYrEvwNq5brcHFUcFCl2DUx6LlXtrVoZLs+7p+f+0ucF5wQTgXyPtHt0UV0wqL2QKmVF9AS6ONLPygTnafZitaatZVgXJxTWwdtuSswZIVOQXMDtMkVZ2jkIrOipZKqEpU5XSeOJ0nSoUQO6b5BNUoIS2V2Ae62FHUJpuXaWJTe8IQqXPlOJ04Hk/EwTr9AuaXLTOEPvDdd9+x3W9Jmx5CJUth2A3INFOoZEdqRZVN6n2KupGizSjp5ctXnKcTp/NpAWWmtvBKg3s7D13Hy9tb7h/uePfuC/78L/4ULZX3n95zc32Dhso8n0hd5PrGPMVfv3nBV7uv+e79e65u9ny6+8DV7Q3bzZacK4/HR3Y3O06nE9e31/z++2+J3YZhO/Dp7omQet68/ZK7xwPUSuwGpilTSqHb7BinzDZ25GKSvrvziSFEusFAgogwZ2XTD/zNv/tbXr15yTiN7snt6FSiN98Y3K2LBBCCqAdtQ47BVUwGRi7NT139X6tPylumSy5rpqHrVmBbsKjTG899Ui5OjyDPueymIGmfFw/wP+aJW0BvKL5JBWlw1pQfWv3vYdSmTb2p1GoH9RI22tO5eD3aPsfBTPt3AeOfAfPlqdn39TLTv7wmbbv5R3l2rS8UObRM+Kfdft6BuwVdnqPt1u++0gJ+n/NpGjxV8aJfU2lIsJNQvejp3AgltHFO1VMvW8hVvTAimUIgSSFrIApLkG4TcgqRpg5f007XsTZeWhvIUepsqFrcPCoUKK4ikWcSQKHkAk6XyAzrtrGtuRwVF6f7UitpihNhUcEEHE0VCDVQs9KHjm7XMY4z53GG2bhwCRYcp3Hm5atrDqcTT+ORGWGaLDfRYM0hsUuk1DFNypwLBOO4Oxno+i23N7eM5cy+GziOA4ecqaUSE3SdHXk1mAojiLAZtsyzTVjXnMn5wNsvXpPzDXOeyblwd3fPZjfwb/7qr/jf/t//kdvbG25e3jCOR/72//i3vH39ivF8Yp5n9sOeWgu///ZbSpl59+4L7h8/sb/ec//4yNM08vart7y4ueHj3Uf6IVGYuT8diannPJ25vr3iNJ4g9KR+w1wqYdgQU8dYCrvrGx4eH+k3W2rIHA4najWFSS2BOmf6bsO2KvM804kwbAbu70/cvrrmf/lf/oZXr284HkcUo1sQpeSK1jNRq1sWm02oDdOu1txT1Qq33izWArs6652BGoK3tUcLSg58GtXR2NpLnxJ/xEUAd08g8cAqAlGoUn1rrrRAo1r87nXluo++ZcROdYZWv2lngS7KIFBKrYRgm0iwMWI2E1YoWpfzoGUite0UYZELChjVBkgIy6EjIf6oiNka/sqi6ZYQlp9d/cMhiB2iIMvAZKt9rYFeELcD+Gm3n3fgvkTcfxi31zbStiLa4dm4t7xSJnYICHX2Bdq47gy1D64OCdhyXmmSsiCS5mnSgnxxK/tmab8qurPabJyKWlrfxP/twGiZVlG3n3UA0ND2ErjVVSZiaHv2x1wg7uoSrYUsWf3x7Wv/f70wcVeUasJeUkxcbffMc+V0HslTMcdAbCrQeBrNT2To+f77H9judlxdXTPlidN0JsqABCHGQK2ZOk3QBeIQ2A4Du92GUU9shsA0nZmLMpeJrkvE4h4oScg5I51tlNPhyM31tTVGBCGGjlKthfiH739gs93w5u1bvvjiC2IX+fTpE3/91/+GzX7LPI0EgS+/+CvTc9/f8eHDR+ZceHm7Z5omum2PTJVf/+bX9Jue81g4zzMPh0f+7OVfcH/3AAEOpwP7/Z5Xr19xOJ+9sBaROJARnk4T56kQu55yHOmGLZ1P/5nnTIg9sVPGKRNSB5LoN73ZH+ABtARkEkIM7PZbNCYeno4oNv2mTMWCFdYOb7YMlrlpqRbIF1ATEFUbEHJBlSwcdpP4qeWVxUvwy8p1JPlPhxddYOizQQTL31l7F4xS0JWzdhHVIidsjMyFEkPFsoDFRbBZ/vheq7Us82EXnaFHaIVFBvjjAuSP77ukWUTVuPHl9Xnmfln8DGtGUVsLe0tzLn6hwDPfk1Znujz4/ntuP+/AfYG4n62m4Oe5/2/5lkFqWov7Erxb9fqf+WfKPHP2K/5eNW2ILfI1QIelOg9B1c+DQrbkjfBsO1RaR1soPmi02nPyXh8Lzgolc6HVlmeNOVzSJBPP6JDlQ7sIrflskUK1jd3SQiBAHztDZbkwl5nz8cw8Z6JEaz4okCeTLOapUspIjJFxmi3T0MzQDQTFips1Mlx1DEOH9MIpT+SpctQz/TaR58Lj3T0zpiCh60hJEC/KppioWkzCppGnh3uub3a8fveK83jm6elEFaHULdM08l//y6/5/v23vHv3jr4f+OH996QA/W7g8f6eT3cfubu7Z54zp3li6AdDygJdSHy6+0wK1qNtdZEIUfjw6QOvb15wt+l48/aNu/Yp/ZA4PExMjydqSGhKlFJJw45pngmhYy7CfJ5I/UDXR6as3L58zdNpBBHmYlxt3/WMuRIlsomJ8+nAqzev+PqX75hLIcSOw/GIiLDf7ghBF0WNBX0HH27hKl6kDI68wQKZPfW2rq3Pt7iKpIiBkvZPsYys1SVXsuQ51dAg7CU/bGBTV2678dsXdAno0qiDqE2B97W4Pub55+IButZ2WPizVHV6sDrVaSKBZd5rK3xePscleCiN3Wlo3Nt21mC+PLY6PdOcCx11ezVgAYsLpdMS/4vNqI3agmeI61+4/bwD9+xyP3/Dlwsq68dn6KAtFO9MbAhcBEOrnr7IbI/RoEvKM3UBDc7pLrZnlck/KgLeSo74yDJHDZb11SV4t8BdqGjNxqUX8eHHnmZl9TmSgk6KzI68ZwitGHnZMTmpBe0JeIaKfoSPxAsobhMaG62kSgiGiOpcyXOmlMx0HslzRudiapGpILPQ00G07EGryQdP55lhMyAi9N2GPE7kXNhf73n75WuUwnkeSTEhKhRmalXmUhki/Nu/+ktqgu9/eM95qmgRcqjQ2yE7ViXQc5xObLYDJcPnj3ekLnK1G3j99iXffPuRIW148WLPNGWe7u+QFPnw4XuGoSMmc+n7/PSAUPniy7d8NfR8/vSB7z/ccToe0Vp5/foltRrKH09nigY2+4Hj6ZE8HXn3iy94/+kDm/01XTTUfPvyDaSOjx8/8vn+TOwG8vERYsdcMqoTczY03W92pJTYSs9prmx2V/R9IG2u6Pue3asvebj7hEjhzf5PuLoOxN2GmYE+9WyuO2qOTGR0mhwJl4XCiNpSf7EFXgviRfQotq6DL4/W81URSjVJYFN42yScuny/tkP+x9K5ttQiaK5LgCYC0WVvy9pj6ZdYXAM7R+OqS7OOqbtkKRu1DFgb5VlawBZCiFSdLygUP2RcOmLTcery/XZbaZ/n97f9bXyNB2ZZQeBCkbD6j9iQ7cLSut+uycWnzVeF9jO4ZHU5KX7a7ecduFu3o8gzOmDl0S5urVsrXvxcE/67ooQIOrKkY+30NwqjSamNKmma1/ZPkIUCaffZ8GFD6RlIom5GZa08BfVCyI+yq2UnyfMT/iIDoFTvnPQiZmVF3bCmh43XWxgjWX29vSVapFE1uqgF2oCJGKIpTIzVJ0og9hGRQDdHcqjWEThmypQ5V9imHbOeERFS13E6nPn13/9Xa31/fQNaiTEgNZH6jv1e+LM//ZJu0zN7uec333zDdBrtEKym/uhJaAyQlMNp5HgY6VLHsO1IIXA6fc/+xibRqygvbq6JQyJI5MOHD0iKaKh0HVxf7ZEUuN7t+O3vv6FkGwQhAfq+590Xb/ntN7+FDJvdjoenA9M88vrtLZTC57vPpH5LN2ypuUBIHM8Twy5BSOa3PWVSMp04IdmxHQNahfOUqbPy6fE917cvuXt4ohLIeuDq6orbmxvevvuKx8MTD8cTxMj+dsdmv2PMs2UCkilFiWJSvmXMnVhG1XjpoJXqEr0oFfVOyaC2RixpE7LIQpVoW8fuk6MX/zWt9zNe2xeZ6kUQcq8Sh/bLw1qwbqyGBqy4rqxywcvHLj+uizrs4o+uaNuL1JfFP5597s1y7Xetv2L5/e0OWVwUZdlPjXZZXD2VJbupWlk6oh0QWi3px6qS5wFaGrX1/Bn9i7efd+BudEbjxdrN05NL2RvUJXA1Prid2jJ7wJs9lcp22muoKx0higZo9YOWwWWs+BHFPIwNZFT/XLwQpF7YbB7clSKytPLYOnVj+tqyKl+QrtdW57OlmoqjvXazdJW10qLY62uXwtVfDV4tjmULVeKPc/2cVkMXKZg9bZu2kqds8yL7wOk8MZ5He2y7niXQhYHj+YiEyP7WfDz6oWN3teM8HamYlDChzLXQDz3n48Trt68YT5lchddffEVMcBwnYvfA58Mj5zpTpoJL3AkEXlybJK+Wwjid2FxfcfvimlxhnEeOxyO77Y5KZbffsdl2nM9HgsDL22tiZ9f7P/+X/8zhYIMLvv76Cw92lfuHz2y3A6kf+Hg4cpon/vpv/i2bTeLj9+/pwpYskc32ioe7O2YV5vPM95+/BwmcS0RSR+g6qDNTroQYCXFAKJQKU6lMGabPD4SQ6Ld7xpzZKNw9PPHweOTLL9/y4tU7np4e+PjxxDhbW32KAdUMIZJz8TNXwAthpmW3Q7ipTCwQWXgJvl4TeqH3btaul0MSbI1nDCFazWSdoYi0AGXzoWqT7ylIUFubrc7SqJJW8GvAAUfnixzQbq1wuaCyhdtuUpR1f9uvbCb79j37/bJYq/ojF3rHnsMSMC72wrqXGj+P6vo71Po3kBU9t6JtuJQh64+Csa6fGJ/fmp347779rAO3eEHRvlhPxfX9/BEaQJBYQYItqoLJ3oIQsi8uf+91dp4sgEZHqxFKsOB3ibarWCEp6IrEo785K/pu94sF7aXA0daIrv70VZDLJhs3nJJmPFVXGkWqmLqjSQXVs4+2HlpRpmLmPw5MEHNMu7S6ra51DUHMC/niOfShp6KMcyaFgPQ9OVtbec4jooEUk3HFhyOEyv52h0wzDw93DJuOrkvMYyGXSvRBAhnl//eff8PVLvK3f/NveXq65/7xnj5F+i6y222hJMZ5RkSZphER4TA+ocGQjgg8Pp04jTMhCNe3V5RcmMrIZtgwbDrevHnD4XjkPI0cTkdOn898vv/M1199RYiBu7t7uiGw3W65f7jz5aMcz0emeWLSzLDbcj6feDwcefHyLRIS41z4fPeIpo5+e0W3uebpeCZ0PSqRczb9foiJqkKeCyFEsqpr/TOqwRphzzMTgfB0pMzZlDPbLYfDt7x6+Ybz2Xywt/sdRdV07oLNrZfi6NjK481i2LB4cLlnNjOpqkRRkmDUh+JctiwFSmPjngeWigevhcB9fnvmQNi6IBeUDNoWZoClFu6FySVWNvVKuCgmNnR++bfWBU57wKpb9x3lKpAWcBdumxW44EDq4jf73ql+4DzveVx+VltW666EjeaRxu9f0CUXP3/5PFY0/98fvH/WgbvRA8/TtQuHjmWBXaZNQCno1KgQIJv8Dg/OOMctbeKMDZExjlfWQmRLGRvSTi4BbDxhQUjtDWVVeKyuYP6GFUGyskz0udwAAKqE4K+lis2mVKMyVC+oj2K0TJV1Z4Raaa3/5YKrwy4d6t4efumsNTxnuhghYM0rpZgveS70sWeezWel3bftB7qUqOeCBmXWicenMyEE5Gpjjotkeo1cX++YdWKaRmoRSlB2m4FffP2GokZ/bLqO8TAyjyOqmXweIVoTTghC7Dq6WilqxaGYErlUxnliv+l5Op2Yi1nZjuNM+XzHbrulhgoRHu8PzLUwDDs+fPzEdhjo+44//eoLiMLn4x3HuwObmz2imSef5H5398j379+z2+25O03MdUIlcP3uax7vH5DUWxejJMpswwyKFmLsKO7jXkWYKnT9gBDIJLJC9k7V0G2YSiJnswf4h9//wNV+4P54ZjqdeTorV7dX3FwZxy3AXCspRKNNYgdyJnRCLjBNkwXjfEa1EqMQA3aQeCrfTChBncO2aUbmGrhykH6uex3H1n6tlSq6SG8N7KyBWgKmdBF3LjTQv4wkE5XFmIxL1K0sXHajgNpUv+DNW8V12uJWFFXnRfW70CLQosGzSIBTSrUBmSWGNH7fDla7Ry9oEg8sSzhZ+zIa7SFAbRx4U8IsEch/j+izn13+zk+8/bwD91xdGyrP0LbAhfTm4nILq4eMB2Ja082gFvzm4EEbtFiBDFvLS0NOaekXbTK2dVR6TWZJAtpjWxBfvQvWoO1L/A+ZHnEt9YLCdS06O/+8aNDrel+zblG80HhBFwWWPbhWwkWWTQuCRLMEHecZJJDzxDxN5DkjVcmlcjyNnKcJIdKlhBSoOaOlUkuhTx3neeR4PBGikEiUmskZVAu7qy1D2tg1TaCD8NtvfqDMmX/1r37F4zhSFW5fvKA+PjINymkeTass4i3e6xzGkjPV5xLePZ6RCDEIsRNOeaavib//7W9REcZpavQ++6sBkcr2aiD1W07TTFGbd9nvNmz3O6byhAAvXrxiu92x3V3RDwNPxzO52Jt9PE/0mx3H88zD04mHowX02HUQEnmyTKDfbJjnzFwUiUquajLArKTNBlUoHoT6Yc+cZ0KMHE+V4/mOt29e8/WXX9B1kdP4RPCGIolQycQhUWvl8DRxPme0joQQKaXQx0BMgTAXYoqcx5lNbyBEYkeQwORBWtUGJ7TmkNZwdtkrsYQ5EVer2GIOMVCzL1RvtrGY7CqssAbIpt5Tb6hZgErgmQ663WfWD+v9NkA5ocwrry5w2QTX9n1T6rWhy4a0L6kS/VG99RKRr5h73TsXGcAF0rdDw4JMozxXvfbF71kB98U1/SMJ3LU1rvxTNMlyUS7SoHZKXuqeAYlGCcgsLNaRrdCX/d11F77qqDt4MM4qRBGSGDpptMkiEVxc1tZiT0vzrA3Y+brldLdbQx3LYq7+Ii+C91KsdKokcxmo1Z3iVqF/bdeINYjb4r1YMP6phkgXA1305pHzmfPxRC6FfrNhf31NRZjOZ8ZxIs7CZhgIJTDlMzFnxqmwrcpVN9Bvrcg5zyMxRLZDZATujyd+eP+RoYd3b1/xH//u79EYKBSO5xPSJ/rOzJxKLdCJUzqWDVhzQ7VikiO2EAJFC3NWYheZVIkaGMeJbuiQkuk3iWHTk/PE4/GBNEV+WyunwyP721vGnJnmCQ3Cdrvj8/0Dw+7apHzDhptuy/E8M5UKEhmz8un+idNULBiHZM03IqR+8OdkHLLERA09bS5pt4kgiSmbHe05Z2KIhJCYi5JEGPqB+6cD8cNnXrz616CRoo+EEAmhJ08nPn+8Zz6PpC6w3+/oU6Lr+tbLgg0OKEgIiB9+pWam80RNidD1TNVaH7WqDcj2rLJgFJw3XD4znmrBvlEEixmUZ44Lkm7rLDgnXHUJuIu6JK7BWaKsE3BygzhKrc4xt85L3/YX/SzPbu17uiDxsj7un3rwjwLs8lV7uc9Q1gWPow0Ntme6oux2zzMd+XqG/dNP/L9x+1kH7iV9WY5TVmapNd/whxdKwLjjdHGCFjEfDA3LKLA29UjKSmNQocZAUUt7K8KsNhG+dUpmkrXhiGHy9nVHprUPVypVIxqK6YR9QyzPNrA+N9bKNLAGby9eNnplsfK+RBv+uCZg/IMgLpYYt7/VfjSlRBDc27oyDAObYTAdd0x0KXE6nXkMcLXbUrXyw91HQlEkD/RlpuZi7nnsCCTipmPoBs7nkeM5c9KZsxZ2tz1RhP/yu28JQyKmDBFCguv9YHNCO+iIlGjPOTXtsnfTVS0gQogKodBJogaY50yKgcJMt410SUjdhjKPhKBs9gNaKv12w1gzb758y/39I6eaCbLhOM7E0BO7hEpkf33Nw+OBECJp2HB8OrDb7Tg9nTjPhdgNEJOh8SBI7JGYQAKlAiEQU4dIIFfXUGenFwRCtOlBeTxDsHVFVEPpufLt99/x9Hjgz//8T9jddKQw8e03H3m4f+Lt6xvevvuS1IvRgZrJxXxiYiuQV1uhIoEUAiFtiJ3yOFWmaSZ0nSNsK5yXhopaYJKWrnJB+V1uSV3QJ9IQrv6T63r5uhUdaYH/Epmvj1UxyerSQam2ho13jsvh1LJaadXQZfWvHuy2F3wNaaV14plApb3GFSnpBXq2n4P2jC8zeuOAdIlNwKrbbuoXu/PZ+fDs4vyE2886cK8+A3ZxL01v/BHLZ5cFCS1ANOnSKqFzr+vqF7zJ66r99IJwVTzgmq1rprNNIZVCh5kNKurfa04nyVhea4unxwagmXXaJcpo751NDJFl8VsWG56/+e288rFnijqPzbIB2upY8g5VwsV1CRIXqqTJw9q1bYVK/NmKb5TpfOZQjJ7YbDbEEDgeD2w2A+cJMoVN1zExkWtmLjM3w57QB47TkeP5xNWLa97eviDryMfTIzOtASmz6XokKDUU6AJjPpP6SOyEGpTTOKGiZGzmIx1IFUIX6VxBoGIbuPcVXqrSdZAGIQVL6a+ud5zHE2nTM2x65prRAK/fveP4/j33D0cO40yKe16+esU5Z54+35P6DXHYcDidqZKYq/JwOFI0OJ8tzKXYmVoUQrUO2diZ7a8kFDE6Kgq5Kl1SiAlCZJ4mQkq0iJjrRCQTQkJr5el04j/+f/4zb9/sjO6h4xdf/xJl4vPDA9sh0vcbV8p2UIstXaf4QuzRUpCg5JxRiQz9QJ6F85yXwurF5lnWRF2CnixSt7UBpSFi464D1vqu7fHBrwcrwv7xdi2tU/ESc7nuW11AsDwgYIV7DTwf1Nu6dH5MczTBnivMlgDdqJLAxSnFypEqLi1bnxBYHqKymsxdZvfLb758kauVq1zoue07P6rV/Qu3n3fgrtX9h1cRvC0Su+hy8SYrYeGVrXUacwxrb5DbutpEdV2VRa2F3BG4NAVG8y+RiEp0abgVoIp03mxjQxiUTNZER6FIj3KiGVepxFXn2oJ2lDXjas0I7aW0TeSVmrYAGlDws39ZdpfLxjayF4L861rXzknDHW0J2m+o1Tb3PE+g0IdkBm8xsttuCALTOCICw6bnXEaiRlIf2ISeicyUC0/nA71Edtcbbl7dELvKaToiKbHpNgRmzjVDUrIq43RmfzVw//QISQl9oNskjuOJ0Jv/dMiV4tQImGoml0zoAiVXQheIMZGrFaM328GKm/7+EQv9poMonMYDGjumUtlvdhzOE7vtNefHE11QHo82LKJU2HTC1faKp7HQ7zbkCio2vec4Tv6eGk1h/tszlUDXJUSS89xmqR5TRKjMxZBfkkI3bKzrMmCt/gT2N1ccDyfmYq3uAeU//d1n/tW/fs3f/M0vDLWT6MeOaZp4fHwkRuVqv7NsIY80642cR2LqmHKmi61zUizLyoE5z5B6qvsjtGBdfP2s3IQt20U62HBCMEBUm5Sv7ULRFU23bkdf+or+oVfHBRr3bewyOsVUUeGCtxDnsddGntpcLREP0mVBxVWrA+MmaWk/13C0uyuaINtRutjOWMQDHugX2kgWcNP26rPC5/oH7G80xRfrdfipt5934NbnF8Yu5vMT0y4Qy9cWlypLidq/XFA1rHyyvymtCLg0uQhmyWm5LQWbBl8lkkWdNklEqa7p7kiSySSnS+LFv0AMeVmk4rP67PX4QbMsPl0VJMpSwNHSWBN59jKC2uZpzmhGjyyzTJbq+aV9SfFGAnPVyyBCTJEYtyQxv+taLay3IJ+Se2wUoc8j0gmzZKapcD7PPJ0OXL0YuL25pqaKSqEWZdhuGXVGy0gtEzEK51qZxiPdtmMqMylFUheYa6aMNvordYlcldhHqz1EK3yFGOhSsusSgyNE6/57++6aOWfmeSRH+NM/+RU/fPxA6hJBBm5fveDDx3seD2c+P/6O2F+h0nGcA/sBphqY54lhu6cSeTyeOU2FftPz8e6Oon4Ii62LWqHMStaRLiWKBigQozJXC9oaIvM0Q0hGXfQDw3bHdrtlPB2tzf90ZjwfrfAdhWFzxedP33vBTfnw4YnjCUJICGdiF9mlAd1umM5HHh5PbAezGqhlMpATexs40Q41D1AFbGJ8WesyP9YhGxUR1uCkFtiVFlS9cN+44kb1qS7dmn/QJdj47yW+rVTJpSRwkRXSskiX7GpY6BFFqa3YQWu2aVxMs3VtT81jhOJGzRfouoUAcb3iEkeC0y2OwN269sLKbVGjLM/UadumYmvDFRrgpB18f5CC/PO3n3XgXm76PMlYUrd/5lI8qx5fFvvaiYmYdWQL2l5tlzYdx0/HLGnhrxvSjqgz2YVZE0HaCLOOqo3jNpSj0j4aglj0r+19v6BNVHH9XnsR9q9NALIzxaSJigXr2jaR/4g4zXIB5gnBnOGeceALBeV4JQRLsTH3MxVrNOhiTynZrABE6DYdQxkspT27M1sKSCdkLyBuu445VcZi6cxmmzjQudGWsg0Resg6M/uJNE9K6CwlHfoBTZU6FiTE5VBOXUJCILkLXSL4JBrYbDdM48hcMzevrulS4rsPnxnHzM3mhlwr//jdJ273N4x5Ziwzu/01Q7+hymfCMFBUOE+FYd8xFzg9nlEV7h+PbPfX5KeDWbDGakZcFWqubHdba3LNBekCJSvTXJHU2SHoE5NCCLy4veXf/5//L/yH//AfePnyJZ8/f2a8vycX5f37H/zgruSsxGCzjT59Hrl/eqALke22p4uCDUOf2eyu6LqOw+FIrcXsCNQ47+IC6uBrq82anGohpo5cWmEyYm524SJ9s6O+TdBZBl872qwNkLtLYKvThCDo4hfvHO8FaqexJ0ujzQWtoqzyXVjtKBaEa7bJWgvL4O3Wlml98o7IW4YZfO204C6IND47rE+MdgSsklnbIsm/Xfz+YJ7cwo/8TFhC8kq0eEdzEyoAz37gJ9x+3oHbKYS1UMB6isGzhSHtzVc7QK3xxL9Z/c1omst28reI13jw0CgWS5NULMWswYK2YBK5gPHdESVrZCbapEqJFOlQIrkmOql+youlseFiAV+kjRXTwNoavZABesONKAv9ocEd4pZqvZ3uwQ8KWGS2FtCdKqkSHA15buKV+0CjlKDGNtTAEXm1NKRoIXbRJpsfRw7TIyqVzaZHkzKWicfjgc/nLW/2N0QxI6mpFkpVXr26YcoTRSpTnTjXmWlWQhcZa6ZLiewOGmFITGVCkr1BXUrEEGyakZj9a4iDZUhkttuB0Aunc+Hdl295/+GeuQRC6tmm5K3hgc1mzz/+8Imu6+ij8PaLt3z/4RNoYB6VYzmx3W45nifO08nUJV1nnZqnyawQYrROWUY2uy2H02gGZRVyFZiy+ZZUoQ8dpZqDJECZM+Nc+L/+3/7vnA73HI8n67icM0Gr+aMZSWyBpbbDPPPu3VseH04cD2eQiZvrDUJPKUbR3Nxc8fh4QE8j2+2GWiYLqhWKCa3NqAlBfFr8QkC0tSR+yFd3DXzGw10GVjNeWzo51SisKnUJVPY7geDKsFp9P9nfydnQcWgHQmi8sH1fgmeZKBrsWtRarNdBxHTdaj44dq5His4OgCwoq5aLr41bF1coNXRc66rIamjb4orVT1a5X0PuzylKu9tsBDw4LT9v12s9Hqpfxp96+3kHbi5TqQvq49nNLuyq3gR59jhfHJVleMJlIVL843J1LykTQGMkY0gIMfQ9ayRIYSbRLGAzHbNmomYyYg0TKj6cISBkVwX6Im3USGhvtr++Cz0qwsVU+BV1izYdrgXiS0/ugOJOmjSfitbl2ejCVesqFpw9aJSSiWLosBYlYCLdEAIhBT5/eM/hfOTm1S0qheN4YjrOSDUK5ulwQGVmt++IW8tAzueZFy9e0G83nKcTZap0MfByf8OpjExF0KjkakqIOp+pWkh9D8GuT4iBfkikGJEUfOqNEEjs9mYr2/UDj4eJ6+sXjFmtMUUCecqQeqZ55jRD2nTcnc48HifujxNEq2FoUE6zMgyBfjPwdDzRVRi2e6bzBBKRkDifTnRdx3GcCcmKfCFFklTO55l+04MY7SKhoyqkFJhm5dv3HzhPxbKkqqSgJq3RSqnV5aM2btoGU2eG7Z7f/OYDQ7fh6npPLQceHs9suoHYmca6aOTqas/hcOB8Ho02qbPbN4TFOKoNwC4arCsVp5s8YNW6yv0WhC0sYGdRlEQzS2sPaPGoNqC1NNa0+qI847Klfa1W6LQJ7xd0irJ4vLfhI4JrtbUBuWgIWoWqJs5tu2SlT3zXqCtQFiAYLsanNfhyeWuIvGm47MWseu1GbotHm1bEbXeF9VppCy1+Iv3E2886cDcGzl5vWAPPRWB2jOmf6DpnroAEXWR+lnZ5oC6KZlm8FqTlcLr+VgXoYYydNxB0JH+L2rCE5Jru1nMlFIIoswyEmgkEV3IEhqQ28NeyOOtGC7rULRd+WxVKcF9uxWMns1Pjc0MBWBGu1delIfJL+sgXqk2NMulX8Beq2FkYQptSv04kLBVSCIZ0A8zjmcPxwO5qh6ZA6oSihevbPWkXCQfhrDOP45HhdqDEyJgz/X5g2285zKOjv0LuA6oTp3xGUyD2QpHKkAZO5Wz2A0E41hMxRnbDFg2VLJkQhZe3t9Q6c3P7gs0w8Ltvf+Bqe8P9wxPDbss4ZWoe6fa35Fw4zoWnu6N1Pcaez8dCShv+t7/7r1TpkNhzzsrm6oZxLhymikombq6ZSuZ8nJiyUkqxTs7QLTrmECKHudL1kaLK9ctXPB0n5lIQSYbm55k6+eBprVbYrtaqPlWsQNkCnAZiUF9JcHN9y36/Z7Pb8cUXV6TY8/lj5nh+JCZhHoU+BbQUap7oN1uimI/4dtP7e2qKm+KbpTqQKT5vMnubeuuirMGq9lovnLovFB3idgmo7ylvHFMs2AZraHWKzp/BRba7Ov/Zody03E2xp9X0+haTFQkgEbQI1tofDfmqbaQgERE7AIyycYvbYIVFES93Ob8jGpatvlBA1dN0oHHaTYJoyX6xXeVBGEfzRjE5f31ZhPQd2uxc/xBM/su3n3XgprK46wH/JOC2anV7Iy4PNeewn3HcrMoRVdQ9QzStSHzReHvTS+kCc6NHNBjKFtNugxDEnNkWr2OMey4abLKOujoFTwGdD6xaF8XIRa/XcjRoywiW9MuCamvACc53R2m1bwv8BV1mI0eRJUA3bq4pS9olbQuuTRIB7w6NgVJnTk9HpAu8+eI1v/7dP1JcIjVsB87zidQFdldb5lNmLIXD6UTaRG5vdsQhmoqk1iW3LCXT7TeIdEwlM9eJouanvNn20AVO+Ux24/zH8whaefvFO0RgKkLRxMf7R/qtEoc93358JKTEZjNw/fIV3/7wic32il//4++Z5kKtiVJgu78m9Rsrfmpgt98TY+I0zlzfvuDDpzvu7u7o+o2pQoqCByAIbPdX5gQIaM7MpdING3IVcoXTmJcGLS1KyTbDq9U9LOjYQU6IUDK5FZclYV4jwna7px86+s7UKw+PZz5+vOf2xZavv3rFdrPj/Q/fs992EHq6AJoi56MNP+66gWmuDL15qxu9EBbAUTDpXqM5TBUbXBrq60LiGmwuUvxF4tYyuJYZOsW2+IfU5wF/8STBgpi6Tt/oPnUKxueGujxWixJay/x8qSlvkjAWakRaWv0H/R2Nu27WzBYMRNWkmz6nVBYRbSvpO23imWALw+Jof0HUIVz8PV1BWEtZPC1WxWe7/rTbzztw09IiXBTvJ+QzdLxeqGVtNBWJfRctst7v6GBB3sGC90JcJbH7xb4v3i05aaQXM3jNmhCBqEqWxCwdUTOdb9pcsc+dY1xOY39aElwNE2RZvOABFteAthZ4hWYdu6Km9eb4aPlZl75iIrQ1YVyllPa5Sa1Y2pEbSokxIgrjNHI6HdnuB4bthlIyVc27IqWBlDpinVGZGbqOgQGpgaKVx9OBsFF2acduvyHVzP3xkVkzYUg8ng/MFIpUNFYkCWmIpE1i1IzQsx22zAWjb9KGh8OJ66srnibhdD5DCNww0w17+l0gzxOPZ+U33/6el69e8fvvPzJXIQ4DQRKblKgk5lo5Pp05z5kPn+6YizJs93zz/gNzVlK/oc6myT6eZ16+viVW4XQ8st1f8XD6xDiOpGEPQJVorfP3D5zGzHa7YYxlsVmtBFOVqPmEVBc+h9L8s62py2oOgRSh22zpovDp7o6/+NOv6YeOl69v+PzDI7/5zXv+9E++4OWrGz59vCOlDtVAlMru+ob5fHJpm3t3N1WERPf/aNmpHSgNOT7rC7igSASvuVzq/5ebtbVrbgDLKQ81YmbZvEFWu2VsUUqRxUCs/foluHvQs+AukB1Nt/FirM03tsqbZrpV+9vQSwvm9nKjIWUsKD8r4V8G8/YC2o5t1UpLB7jcfW2vPotFXOz1BR1ZXeCPRsf9oytCW1ELAJdlDa7f88dJbQvNfqKNTgqK0RBBFkSvTqdIhepe3ktgL1CTneqzX87o6DuLTxc3koRMZJa4WGfaRG1Zvp+krkgDP3B8rV0ib6qjEn9ZxZFy47ibdLbhAOO5a2Pinsn/8J+JF8hIGyfXZu8tGlah5EyeZ+Yys9/vSUNkmibiNjJsB8Y6I5GlYFnKTBBh6Hu0wsxM0cpxnsnnEydm4i4Qu+SOdIUQbTCaCpAC3TYR+sBYJmZxq4EaQaDbbkGtrnA4z9Q60vVbrm6uOU2Z43TkfD4TYkcumbFWHo9nHs6ZbrNnzDBPM2HOnOezFQNjR4zmGTLnzCYNoEK/tWG+qFCz8vrd1zw+PpLdD/3Dp3vOU/v5nqfjgdhHpsdHQuoQKhI7qtoUnEY/zHNBJVC8kxJgs90yTZMrV22ocwiBXDKPD4+ewleubl+x229JsfD2y47f/fYf+d//99/xt//uT9idJk7jxIvbK0p2TXjsoWZUOveQvuCwpal01udhB7qj60uqcOFmHbGuuIPWvNX2F+299HUt0Rtx1LLMZmGwSHdb9hvUnQOF2lriFx25d1j675YU1p97hqqNPvFKvh0YBC9ONg2uLPc3znu1oagrWDK47JfB/oZIG6JcHE1fvACwYqeDpmcySL24Vhf0yU+9/awD9xKEL17wYgu53POji9HsXVHnt70AcRGwW1C2Q9QRt1fhm4eJFRGB2fs2oxloFgKzpuUJihQmiQQivQfpKoGM0Ek01OW8HMF5PnexaxRF+xxkbQ32ir0WXTbKUjNVTEHixZymFjF6xB3fHH23mRK2pJsm1fXfISypXbu2k1MTV1c7EJinibgxhYQ1mAi5ZlLcEETou45zmbna7Um55/58D0EXZ7cQYdgGtt2eGpRzmZjKRA6VLEoOmbFMMClZKpMm5oxJ60qBPDIMWzZ9IhO52vV0fc+HD/cUrLOzxoFxmgjba875wHzKpM2Op9PIaZq5vroixA7Rkb3rtI9H004TOz49HLi53iOxo1UsSoXHw5nDaSR2G1BhnDJThr4P5FIIqYeQ2Gx6plzZ9MnGmKXOaiD9wF//1b8FlI+f7wkh8nCc+PKLN/z6179mmkavO3jHYq0gwQb/5srt9RXn85EPH+/46he3PN498Jf/w1/y21//A3//97/lz/70V3z84VvGyRptigbrMYgdgdk8S8AOB6v+AeIUge2t7PFMxKbjWOEwrVmfb7E1Y1zdOaXdrw0xt4e4EkOaqsS452cywIs6XRWllkpQcW5cvXU/UMUyh3gx/NjWasuwK76MuSxIrl2THpibPWvbDc0dS2zfB0fu9mJbFTWgtXV6OoXJRdFRVqpTuXz9yxNCtbp6JSyHwE+5/awDdwvKbQpZWyALI6wteNk94p+Htsz8AosHcKnLXQDGn7ncrqlJpKi1mNclYzPzqWDdk4hNGSmt8qyBNlg3i6GtrJFBglWvif7RObOwtgu397fUap7LtI1g7b8NeVda0HZ5FG3RGsduKhIzwzLaxJeY89biQT/Y+URVp1iK8YlBBGphnEZSDAzb3UKthM5KslGSF1UzyEAXOmoHp3mm3wz0+x09M4dPB+aakQDjPKEzDHFge7Vle9WhUjjXwufzPQ/HR/oUCQxMZeYwKedaUSJkm8kTQiB1iX/z13/Ny+sdP7z/zA8fPvGrX3xFTB2/+/4D19c3EBPffP8DY43oWOj7DUUq291ASANp2PDl9QsO54mnpwPzXIn9wDjPbPc7jlMlxmxcsy0HxtG00nNRCImSJ1LXM+cMURjnym7omXNlmgu7/cadASPTPHF8HPl//q//L77+1a/YX9/y6tUrTv/4Db/+zW+5uz8Sg7VyIUJwyiS2A1aU25dv+Pj5kX/1l1+y2+0pOfDx03t++We/4r/+/a/57oeP7IY9OSupi1CsCNrFbBmL5qXrc62EBKPJnDZpa8NotMYzF1TsPW9yRsH2mqo3dEXQ2QNkK6iGQsjNXMoArWQIwRpfavYgHoK5ChaHEtWkhRosgCNAVFeL+PqVlh062LIHGaLXaUHhptgJHtgbRAeJzp1rAQmE2LkgwK0LjDckhoBIohZ75bUKzfOk6dcbwl4ajy6oW2E98C6LlqpcDHv4l28/88ANf4CogWf5yDM0DlJ9gnkQcwW8/D48L0IWq2AvdJhgka0VQoBQTX+qRanJdKAz0RWEjiqYySSqTsykdTArXqhsz6ENOQ4XCBsPzmoI4/JlN78IEXV1onlug1nLFj8OghchG9ctHuhXgRTrsXCRDi+GVNX4va7r6GK0jSeOEkIgJFN+aK2kPhFSoN8mxjKjalPOu02PKuy2Oz4+fmKalaEfOJ5O1PvK/emB8Enpt4lhF0GUoe8Z60SMlb7rebG9JkvP41g4TdkCm1ZK3PDN9x+I/a/4s//hr9m/+J7ff/eeuw+f6IYt98eRw/EODRtSJ4xz4cPdE2/evOb1qxecpkw/DLy4vuX+H35LVuHq5paP9wdiSky5cjxbO+tmuyUlU36kfsNcMrEz2qPf2ADgkHrOU2bY7kj9hvPpiMSOw/FMGrbofKZNdJ/nmd/+7ltUv7UitaPdGIRSXfoXAtUVJlUrUgq3t9dstx25RL77/j0vXv0p2+2GGBOlnHn19jU1z8zzyIzJJS3YmvSwi4kmAW1hpBIX+qH6+9+kf1Xb/WHhRVRYAk9TSDSUbWO9nE5Yto9x2XU2KV+dvIfAC9qtYGnT1dUpSf+7smqqieIgSxcVStBADRWtrRjZ9IVGl7RuRXtOF2Q6xSW3zjPravqAc9rq3PdSoPRTZ4kyF4fAYjp1kale3lrcWIK5tC9Yw9ZPuP28A7fLjVp4ax/a62+L8tK2VIO3vTqKNpWIrkMZgiNpp0ZaiztOoegy5t1JhdlTQYw6mWNa0bxYipVJRqGQ6JxtLgSKBDLB7pO40mrL67hYrL6IgdaBu9AkVUzZYA1B9sctqCuZQFpYk7UAeZE0Gq/vf6YoS4u8opRiPOim7wmYrjtG40IlWu6SfUxWSDYFJwYLvCEpQ+gJfcdmvyGS2MxH4jlZE8uuIw6JqRR2nQ06OPl7UUJljgXpIlOunCflrLMpfNLGJhelgTlnPj8eyRqQ9JGikTdv3/FWI1NR7p7ObPfXkHp++PiESuLxdKbfbAmpZ3P9gjjZUOO//4ffMc3FpIEh0g2ZEAOH0wwSef3mNZvtFR8/3zHOZ4YkzMUajHa7PXkamUvl9vaGOFeKCk9Pj/TDDpFAUAV3V2xNTCqDaeIlcJ4zVW2eZ6mZ6G+M1oLEaFpuFW6ur/ji3RuqwNPTkX//7/8tv//mv/D111/Z0okdm6Hw6XDil794zTf/+A2bzcDQB6Ypk0Iil5kuWlOW0OwS1N/1uCJiMRliozzaR1sf1QrSS+huxc4mx7vYdxeqEVwFYoHUfl9V9envvh8dqTZvklVh0rJecaql0lgM45ObFtuei+11XZ6PqURaratBlhZ4A1UtV7bAXJzutK7IRi1dVIEW1Nwi8Qq4ZOX62yXTdiQ0k6k2od7uK3+sqpKFIpB/+jHYI3iOsu2iy2Iy499vRQNl0XovJHKwA4DAOsUD58vFJHlFAkGr0SNMFrxbIVIuCpMS7Gd8PppGfRa828Jui9tB/BrEL1B2e4qmwzXU02YLNlHSJcpWL0oaapKVcvJbzsbfpa4zjrxWQnKk0bhMUWopxD6ZSVGKpK6jHwZEitFLffLOP2F/s+em3PDxfmSqM0MYyDVz//jAcDPQxY7H6UTYdBA7KplJItvbazZxw9MkzOPMrIHxcCKkgSA9xwl+/fuPvL878idPI1e7LdLv6Td2KN4fZ4iJ41goBIbdFROJ9x/vmaeRcbb8pBCZtDKdJ85TQSnsr2+4unmBIHz3g6lLum6woD0XYtdxOJ05TwWJiYenI4SO0zix2WyZc6XUmdgNpNjR9TbK7nA88vrtO87jxOe7R5YhHZ6uN/f/QIBSbSzb9Z5Xr1/Tb7acD4+cp8LhfOCXf/IXvP/ud7x6ect4nhk2A8o981y4efGKh4cHXr68sQJntaHPrRGrLgU2R9RBl72w9CE0ereuxe8FfV/ur2Xr6PON5yh85aBXKqFJ/drfMG23/d5sRR37RvOxDy5XbN3MxbNowSkfl/EJNDO3pqIBlkYg/MiytrQVAltuq89/j8cIG6asXjR2/5NlnJtYQV8adfTs5V/EI31213qtfjrk/pkHbkcI/sauyPqfp0/aFGpbA00GqB6cAxLqotXGtdLLb6gsahPN9gYF57vbQAcUSoos3YcKmeio2FB3fRbAZdFyVyKxyZDC+vsu+TIKS4VbWss+TRLorbp+TaLzk0vDmTSuThsDT/sjFrZs+AN4kBah6zra2KDgCDuE1vllyz0k40JDisQYGbamhX58mohbQZI5zvVXPb0kbm6uOJYnzvlMFzqurrbMIVNrJkii6wdSH+i3kTDc8DpteDzNTBp5+2qHpC3TNx8oh6PNcVTzM+n7yPhw5P7v/pFffv2OL96+4bvPv2V6OjBnZabj4fBEv9nx+ekMnNlutszFqJinw6ONagvJeW9I/YZpLvzjN99ZA0wMpGFjPHWuXN285DTOVJTzPBNRhr7jcBq5efGSp6cnRBL9MDDOhd2+Y9ju7KCQaK6ACPvrGw6HJ2pWJCRKtiJKUJuSE0Nl6CLdsOF8PjGez7x6ccuL2455HvnwceTq+obj6cjQ70DbgTKz23TksuF4HNluh0U5glotRhrd4SgWNRqu1pbJ2QJq3tyLedeyp1b0ibqmonpm6nugARBBFkfKSvWiZ/V2el+oor5ea2M6oDqHHATJrgPnIgh6trDwym3iA9U5ZRfG+lpuofMZNbIEb+t2tsskxGAt83bVgu+Wll14KfaCKmmt+T/CiO0v/gGFsuDDH0/9+W/cftaBe2l3/4NAvQbpFsx/jMRlabSxxy/2jRpWZGDv4YK0tS2cJYDrauiOc3hJfKH6sASnRowuMTP+5uNdmZfv015FALcvsfsEp29W+qJJpJQ2dcd9SFwWaAvKqJNlKfhmlTXWu8mVOqVjF0mXi2Q2n7UWW8LilX+BUk3qZxpb23RKpes6ttstwzAwl9l4zArROfvQRTZpQ0nKdb3h/OlMKeZLIoNwdbOnpkoarNj0dDhRTyMv3u15/e6W8wSHEbJGQuoIseM0ZnKuxBSZxkqMiV6Fv/+Hb/jttz9QSqHrBpfnHSF2nHJTEZhda7/ZcZwK/WaP2a923N/fkbqOkHoOhye2O/veOE0cjhPb3QAh8XQ8ucRP6PqNjWhTQaJx46nf8ubtF3z33XcMm72hXDUzrBevrvj97791n5MOlUjqIyklpvMRdZe7YdOTUqDmkSkXbm9umccz/+XXv+XVy2t2+6/Qcub+4Y5Nt0GpnKbKZhiYZ6iDkGIEjG5JweZRSjQOvahQ1WsaYoi0uo6/Beo25d0CvP+M1CV4qu+xJqtt0HpF2Z6p5rb2HHA4QlX3LFmmQ/nflSjW6Lbwg2HJPtX98pvWvA2TMvpBCMGa32rFOyWtsmMxo7WolzVDWHax/a1FR1+r6+6NIbdGyurOm+0aCa4WwJB6iznS4OWSOayuhO26Nermj4UqWS6Of6ksjTjw/PN2E/GA3SaXtverqUacNlgC9jP07Rx4EJtwVrFp8J08Q90WVIWcOkfcyYK0RE/HE82LW7H7qvPcEa+OG5x3n5D2ZrN8r7kULm25uF58eVhY7FtUVodA2z92oPlSW0ueTRurSozhmVe3qrgRj9m81uoyq6VBRxi2G+jMIW/OM92Q6HcdYbchB+i6nqrKJm65lRc8jU/MjDbxnczhdKS/3gBK6oVN3HPMgd/87juG/S3d/paiEQ2Ru8PMcbRnH1OgButUnXOBkLi5fsXpeOQ8znQiJARCTxGYs8kQt5sdh/MZciHFjlkjx+OBlGbGWTmXwhfXO1ROpH5DrgpzodsY2h7nkZubK0q1UWnERJd6myIzj+QKX375FZ/vHri6ueU8Zs5T4fx0zzBsqGNmu78mdgO1VuYKD09HYjfw1evXjKcnHh+eOE8zu9Cz2d0QRTlPmc0w8OrNLTkfGYaOccpcX13z+e6JzfYG6kxIA+P4BHRMM1ztO2wqjpJibavMA5+56VWn9JZAozjFt7DYTkfIcpDjSHxZRg4gTMS1BmLA1B/R9oqFTZf1VUfwXuNo9Mwqd21oQy+TYAvsxaSE1uzjSFiCG68Z2jaQ14J3C5zQTKYaNy1iBcmW6eI8ue2CVpD0/FTMQ4Yl22hwahUvLJdxAZkstFC7xgvb9NPj9s88cMuKRC242Mc1kF/SJ/4DS6Rysxmf5G7FPGsMWPzZnUNzEvpZgVLFfs/i1V0u1hZGUWq24J3pyMzMRKNKMBlgdf6t0SSqwdB2wI2mWHi/Nqn9mSexNuPC4FLAdUhC47mjmGeJXKRzTQO+XMN/6tKKHz+O5FXV5WlQSjGu2046C/ApkfqEJmGcT4QuICkSusgwDFTNlJoZtgORDu2VF9Mtnx4+oAFSNzDHzMPTEwOBIWwoqaeGjtAnHs7KdHqgxj3DECiSqMleW0NrNSSbnINwOE8UEnFjwbrkylTtoAwpQuh4Ok/UCn3smCXweP/kQ30HG7ZRle/ef0BSx+F4InQDIfXLnMnNrud4mjlPpmEnJEqZSQTGufLnf/lLfvf779ltB5cBdrx89ZL7hwPjNDJstyhwPE+kmBinmWF7ZauhGzjf3zEMZrG6v74lT2dCZxnA3f3I3/7NX/HiJnCeJ2ouhG6g606M54l+E832oFrgDSEw5Woe8WIT3hOGrM3FLy2Z34IGneOu3tXXrKkLTWGyFueWjw69W6yt2lQiLAeBum6uePt61Wp9EdnBhDtaimd3IIRldmtd3D0liju26lJr0oXyCFRvRzd9dks1G2XS4oStY2X9uk27aSibaoVJ8yRhMaACMcls8D2yBHqjO8OlT3ldqSR/2DOuW9X20U+9/awDt+qFDKnpqvlnCpS0YOcqCuRiFhzUrNC5Zrmo5fd+4uMoG3Tpaq21IlkIaRXZS/I3NVslnARaBQ0RG1eVqBqpEq04eaEuaX7ILb2i9UP4G9348qWA7V8XDLW0+cfq18CSCkPg6imdIXdbtEHkkpEhOsJoNFvx6xTUFA+2oVyt0hwMBSsOUa31nEgcAlpOFKDvIrUWYkxs+55jOdL1HVEifZe4eXHDqRzZXnWEHmpInOaRQ5lJGqgK908nznFLjAN97Mi18v7hwFQNCc1NihMb0rNGk/FcXP1SSSm59DJDtPdADTwDwuFcKGUyX/GYeDob/SIipK5DUk/wSUdTORNSz9XVFY+HExVl2A5stwMPh5NJ9wi8ffclRQNPxxNv3rzhH3//LV+8/ZLzlElpQFLHPBceD0e7+GHPPM/c3l5zc31Fnmb2Vy+ZxjOxnAlJkAwvX+6Jb7d89cUrjscjm/1rPn78ltvrDdSZzW7P4eGRYdhTJC+dieaZ7nqI4L414rJRL7QpQrMBzkXIDRWuxRYU61htdIguEbmhyopKsIG+Goxmi7haw62AYQFQdV6Dt2IZLQW0VPcfwWjKpn2ul2BtBTjqAaBWpzNqs2nN5tuODYBoEcOC5WWgjB47Gge+om/BXQoJpuuuzU/IkLcVMMOCtlk8zFk8wyVYsdleZ/AAz3IA2BO6kPv+C7efdeCuPkC1oUOcT7oElO3rJUQ5ajCZn/qJ7VHPR2BpArKd7JouqAS11Mx6Cjydmizgo0adiK48ODNoB9Oud4Y7M5MpmqiSqNJhpqqGvrN09GmCYENRje/WBXVrMJpDsyLFeL2i7nGBFYBmj/YJdWuI1jQhxPCsIY2wVNftOjVnODv9LbjLsmFh6ayzBy9tzNY5rKQ+Il1gYEeZKqdy4Gq/QXrh+uaW3XBDDjOhC8xhoLvZsnlzxX/8u/8Hb756wZdffUGNhUkDU9zy+4+PDNsNL27ectbIb394IG1fs9nD9HggRNsmU1GXyvnpXWFWhdmylFghxcAsPXSCZgtSp9E3bjEP76qFMQcfPpFIITFLIkni6Twx9Imv//Sv+Ob3v+P7zwf6fiBuBh4ej8xEm3TURUg9m6sb/r//+df8T//+3/O//of/J7Hfsrl5xfuPP6BViF3H5vqar/70z/m7//Jbrm5v2d0ov/v2B7755geGYaDMZ0rOvPviC6pG/uqvf8X+uuN0eES6nsfzJ16Vif31DY+HB7Yba+rKCudssr/YDUzFDZRCopbZ6g4491oskBQ/8LK6IyCWsToL670HtlJqda8VV58Y2rTrXyurf3utPg/VwmWbzr4E+0rrKrdbSwobcPFmNEmGrMXf24ayjQa8oCWCFcq1KCId+JzOWt3MS6Eh7mcxQUBrXkETTarXCvAXmeqFkHZBVno5xdWaeJZn1VB14/D992htGvqW3ayP/Sm3n3XgXsJz44zUeG0zfjcBXFhCk93aQsOLGSYrct1GqV509EIHrMXm1rTjxLAtegugCEtqTQaNHukSSBGKRook49slUtVkX6XJAZ0y8fhMo30WSdHaIWv8uS9WKY2TduTtsFwxP27DCKY5DWJnALAUMhu9ovB8Vl67smtm97yw21CbiJ9UUEuhUuliT7fdEvSMZjhOZ3ZB6DY9sbfHhRTo+w2ahLRPXL18wd3TE/X7yp/8xa/Yba747vOB/dUNjyN8fjrxMCm76xcQeu6PZ2bCYiokoRKCSdlUK6XYMVY8E5qyEqvRRiFFSJFaKt3Q2YixUpmK0LZDBfAmqXnMvNpdMz9NvHh5zT/84zeM40Toeh6fzmx2e/rtjuPJprJL6pimzOE88+d/+a/59rsPnMbCu1cv+HR3z9X+ivvHE6KV+8cjn+4e+PDpnsPxSIiJWoVu2DLlmdev3vDui9fk8cRXX31BNyhDn5jmnn67ZbMZOE0jCYUQmWZrbZeYKFVpnZFRrWu2OL8XUPfzni94MlnfXf+0qrtYXh73IhcpX0PkXnfxekvrAGwTlxaTN/yQN2Ld1lB15Bna2vQML/gAgta/ELGeCX8MGIiiWoBfGI7g4Kr8qOAnEXFJoLWWPy9Urrfnre82pzKxmIWr0yLi6F0FCWtbO65mWS/Rmi3gRl5tNmatbgfbrvkfS8u7LYsmqG9o8QIJNiWGR6GFSvE7n0kC3QnQgrnSzNvF3t+1QAnroduCeFHa8IOFSksg2b/OUIdIdh6xiKfrnn43xN3S/EhZ/4a21xIo2TrMLuV4GhpVY2eLm4o+yzjs5eriSxL92oQL3qWoLku1KUuK6qLowmWUxs/p+otRqGrTa+aJbr+j7zd0pWeSjtP4ZBlgVGKf2MU99JVCIW0To8zcvnhBOCgk4e/+4Xe8fP0l+xdfkI8zTzlzPGeT5eXCqBNpd0PMTxepub/xtRJCJNdMkejGRKatzUXJEgwNutys7wdyrhQUtCw0URBLTcYM292WD5/uiV3PXJW52gExzzY67TxnhmFACdQqHE42od0KepH/+g+/tfc0JY6nmamc+HT/SBA4nArDkCAEpqwMAiEGbm5veHl7zXa3JVC5vd0S4sTrL77im9/9A31nk+FD15sF7Ti5ssfkhTFGQgzkbA1UdNFyMKfIajuVXQpofHMDEh6sWycjuhZvYKEFcE62Uk1d0oKpOOC4oE+azK3VaSxW6cIQLPtS1p9pXtyhmrmWtm5lD9ASrUAvyQKgFfHtcW0QcK1CiEoLwrKYaFUfJNyQ9Mp7X8oI2/eWGZGNZvFYY2MqMqIBleo8NrSeEpSF/8fR/CWmbtdR/TXrHwvH3WBxKyw0wLhiB6cZfCGpykqRNEOpcoE6y7Jz4fJn2/Vs1e5mhOPUiQi4Ft+aXpK0+oYF72oStkpkVuuibEH7Ug5oNpqYdWxr8PmDEMxSGDdE6eZWC+q+yEKAbBktulyFhiN8gzg6CroAliV4V5zzboXKpvO9vDkyyrlwGs9sVenTwOZqTx5nTo9n7p8eSTdbtAjD9QZKJW06NBRiCLx485pzPSG90sUNv/vhjnQ/c/PqHaEbGDYd0l9zPhWO55nT8Z7ZZ22WqlB9uKtEo4YkEJNAMYRVPTBpwQ2H1oyrakCC0g+RXGGaMtaMF0gpch4zxSe2f7p7IBdTLLSp6FWFx8MZ/H3su465VnKFj5/vydk8uO8fnjicJv7iL/6Mb7674/bFFa+2ic/3D2w2Hbe3rzkeT2y2W/4P/+7fcT49cj48Ukpls9uQYubx8YH99QvuPv9A6k5ISMy5ukeGaT2maSKl3oOXTcqRYM6EpaFbss1HxOoW1QuQrblEsaCsura3N+RcarWfaX7aHqit0O6ZYrDPKyCLw+TzoPVMGugZsAQxLUDA6EBpYMyLidGDYUPqoVrwFkPkDZm0yThN8rn8Qd882qSPXDj7tYihzTnwUkrcgvx6IC3+Ry1Hvmh7bzUA47e1/dXVQXEZkbZc2v/u2886cKufaFzK5S5O/MWfm3ZtjOtrwam5/plTvCwceSucNMq0USPS9NNl/Y1UoGCDUGeFzhdd66Y0qs3oEUn+MazNNxf/VM2fO7getL02Sz8xMx6voKuj4dY1uehil+tgV6H6wRZ0FUKFphRhLUK2V3RZf7eUUJbvtbmOy2I111pyrox5Qg8HXlCJQyKlDdfDS0pQ5jJRtFBKJZ8ym7RhnM90m0TfJ169fckkZz493qEqdNtrxiJ88+Ez0l/R7W4Zs5K6DVJ6s5b1hogiyTMAO52CE/lBrAuylGLXFqUGK9KVcjE6StYJ4SKBbtj4uKxKdjMkQuJwnAwhxUgpdTl4p7lYoFIL9qHrmI+T/SyQ+o4UE1/98hf85h9+z/fvf2DoEi9fvmaaMq/efkGIwvXtS0ouHMbC/eMD79//niFW/vqv/hKCkucTh3Fkuxm4fvGSz58/crXbmHtfVfoUyblYJ2kQ5mo1GjNwMjQdxLv+JKISQOdn7eyN+moUx2U38ipxuyhI+mGp4g1namjeaWKfAfmMWWk7sy2wZxQHlTU4S11plZlFwdUoOomyUCdEA0h6kRk0isWKh8+7opdi4mIOtQZse0yLEC2IwyolDO0VoBqcp/buTi9Q0nhr2qHW1loLRsYQLG6Gak9Y5KeH45914L4ghe1Lwa0U29fPg/dya9y2f74uGppZh0s0QN3QBvBxSbC0yDsaX9B3J8ZxJ5cLehQM1RB4icGlVBeKEtyBTZs8sB0g9p9prtuCwPj3NqhULE2sXlStutq/i3+e/LU3hJ38JSNC9Odd5Q+n6i3dX//EraWsqiYNnKaJcTpTO+uoCyGSQg8K1y9eUuNELpl+u2FyP+7UJTQKOSi3t9dIX5m/VX54PNOHyJQGHh4yuy6Rp0rY7JlOyjRVpNuiNTjqA/PMcHTZDnOMJrA4ZRO5a4smUqm5UtxwzMyyLDA0ftWmpVdKLtSQ3DrA5F/RhxOMc0FDXOoM3TAwzpntfsfXv/iSXJRf/dmfcPdw4Orqml/+4muKKrurmTFnH0wRGDZ7TocjRaxg+u1/+oZ/97f/ms0gHM5P3OyvkNRzrpXHw4H9duujxVzREBJTmc1jxj1NQsANwDrjtqsSk3XpilZHfEaXVS9Otu7eglz0GETnuls9JmHNZW29XhQHccSslgGHGM3Fb6EQsIMheHGuUZMts738fgpNMmWBGVmLhU6TqINmUVlQdpPSqjaIVv+A7mgSwDWAtF1jLoX2M951+Sx++M9d6LU9BWBp6FGxSfN+TaQ16i3UrStoFtpKF+rqucrlv337eQdut3SwWNcqtYYSgyMAvKKNrMWThp4JjlCLBd0yF2IfbLJNvAjMnubU4CwKjS/XZQYi1ZD2wm23uKcYMihQghj3qraB1GWAM7DRShvWirpjWahLNmFmQC7n87O8+v2NAWpjy6qf9k08EzyTRC5dAdftVmu14cJOGVVXqkRl0aiKt7WDZReN3yx1ItfMlJWkmZILIZnXuBJJ0kM/ID30u56+UzRl+t2GGgqaFOmFXf+S1zpw4geepkrKgTcvrrgbC3cPB+aHmRK2zAxUhGG7J1fI80ymeAALhvpKscJPEGwYgk34Tu6IV6pCjITg6MqDvboEMQRD7l2KdEMPEjmdJupkR+nstJi6h3IBUh/ZXV3x8PDAn/3lX/LlV18zzZXf/va3pBQ55cKrL95y9+mO1Pf8/v0nfvmrX3F4vGe76Xj6XPn+u9/wP//P/zP69Vtevb3m+PCJGeEwTuw3e9ATxMB5nrm62nI+neiHxBDUg6x7d9dC1YSowQRrpDKPkubcoS0bkRUhN6qjVhwsrMd5jNGplroEIXX/X3FY3UQBEvELxEJdSDIVmEmg16wxBmvY0tn2VPVgHDQso/xwCWANxRtu7LAOKaBjda24IDEsVsSxi9SpWr0CpV4gZpHiH53e0BbIm7Wr76MmOiprC46d8NWDrfE64h73gnPzGqAYfVfaLNuFKtIFjZdSfJK979c/lsDdih0tUC1NKgvX9CPI6KnScnPk3eSA1q4uC511uQBNdSGrU6SyqEZamqmKTUVq8TfrImUiQ+m7BalkwjqD0lou/CnF9eCnoUfbHOKvs9EzzZmtSbVW3LNmn81sqjp1EnGE7Yj62UQcbZSL69n9moZWVPLHtJ1eajE+uCpBIkULuWZDTVEIRBtumxRJtoH7bUeN9lhzwAtmUEXPzYst7+IePj+QH07sr18RR6U8nPh0KBSfclMCpCESQyQNCck2Nm1WCw6hHyxpKoVc8mIg1gZTFelsk/uAWi4CkQQr/qaUrEOUwHa7ZX9TqXQcT6MdJPO8LJKcCze3NxASL1694XA88+nukWkufP/+A3/2p3/GnJUffvhA59PY//xqj0qg32443H3m7Yu39HzJbrvjzZfveDh8tGerlTmbNjp2A2WayUXpYkfqlZxnYhK66DphESR1ULOhP4l2GNkkSZBEpSC1oCpeTrHhw01JJTQJaXUnw8BcvO172Wf+8WI/NVAUXDO+0CT+WGKlFghxzShtLXsnb7jgwWXd44gtZqEt6ouPsfGIGK8djU7Roos0cDWKWoO30SIs2bndnAbxQ3zh3tvSV9+D3uhjnaOmDLH90gYriKP8S0VJ433sPa0LJWOvz9boHwtVAujl0tE1eK1t75ePZCk0OiVlp2GL806B0CYJtK893stlttV+l0fMZaBpU6K0+/FCilrgyAgzcfXkFvMxmQnMeAAW//tJzC0wCQRH9xF71zolTkoSIfldSYTUDjFPxRLNPGpZJot+e7lfVu4xqCwIfWGiFnWOY4bqlftq/PY0ZaaciTlYkbYFwGgzKqtUqEqd2ygAmM5HSizsdzu0KF0f6BK8ennLKSvd9oYsPdoppIE0zNydlNQnDrMyl0yuSowJkUCMeIOD5RpBhNRFuq6jKXCOxwNDP5B840yzeYzbJHuXT3rm0XWmgc45kzpTfsTYMww9XT9wOB55eHy01v9o0rDT8chms+H3v/89L1++4MMPH7m6vmZ/c0WMkYdHIfVbhmGDno98fnji890jf/GLL/jVu1ekX75je/uap8/vudr01DFyzgpBmefZ1BXFFqPN2jRaBJeH2tWtPuDXDcEoS/CuokRRao1+WEXnX4XnHvE+ODhEr78ECAkhojUtKf9ymAseHK05JxTffw1tNgdNR5dL567gPHxYZICEunQjV54j0NAmMkkr9LVGMPGuSX86XqyUcnlfRLWhKss7Td+N3xeWWLF2W69dlxd42Q4cV5K0Q85qCXUpUi7yx8saka6Yz/YRqyrsn6El/7nbzzpwty5Gz/PW5N/pg6bKaRSa/5TDghVZA2vnZW30gPMP+A/XhiZk/TuV9US9qOotwZuVm5MqlKrMsm6GTGTWsKgeZqI7CUZEzAtag1rw7i2IkxR6rLlkErpsX/ZYDWe8uD6dWKNFwAJ5ci47qC7T31uAjheL05Be097az4pzvxIcZWlBizIdJ86nkeM0cn17Y23xPvYtaCsO2WLPpTKdZ8JG6FMHfUeZM33oETHP7zzB7c01nDLFG2a2Vx2bawifD3w+ZDQpuSSb0Vjr4iqnKCkJc8HHQYG6VjmGwNXVFUFsbqMCKZm3OGJV15oLXd+RUnT7U3NJLKUSJRJDYKozL1++YL/fmxnV0xFE2G23dIMZbr189Us2fc/LFy8JUXj56gWfP3yii4nD4cC3377n8PDE67df8PHDA/sOvn7zmtsXt6R+ZzTQ+EiKA306eXNRoeYMsXOlhqXn0SmfXIr7qIv7OldTjnix2/hUU1GZDsl+TsGVIsEDvHPXISIhUasVH5FEwKbj5Bq4tG1on1tW6HSFZ2aNhgG1PaaND1GjFMT2RqMbQwhrxtvQttM4rTexBUXUYZvXW0IUik/NCSFQ5rYpZTm8LTyssL0pSmR5on4ANc7ahwCrZ2bto+2TiDpCswDutFErboosdI80OW0DkA4QmhdQe6k/9fazDtyL/Sp2LVcOW9zgBueaWxT322W3Fk5Ga1hGkxHDMsYMXyjiRciW+i261WZ+fonEwaJoMtQg1eVJGWqCSWw+YlFDNnMJlGBdlFnM26RLFqA0eeDusKBtD7MgHqErhrIjHsD9OYp6J3X1cUtq3ZidX4bOqROhTcmxQLv0R+iiSFyvN34tayVP2QL2ceJ8HpnzTCISXS/cqCWpOCK1ADHPM33Xo0DEZjNqVWJI9DGRSmHoe14OV3z/8QGhY9P3pN2Wc41MnIiT8nQ42OvCNNK1VnLOzKUiTT0B5OxJbQheJMqgUEuhlMI8TVZEEws8sUZUIyXXpdNPROi6DTkXuq4nz4UQAsMwcBs7Xr9+RQrClCvDpuf1q9eM88zX795w//iEZMgnQ75d13P/8B3n48Tpu/dICpzPJ4Zk609rYeg21NM9FOhjz1RO1sINlLnQJ1exeFNRbVSdJGvDLjOqFrCjmh+JyQWr2yJYwXsZUBCCUyir2RmugIohgETm7AM7Fgvi9R802iSs0acV8CvNFdiCeAgQlJrDEpSXQLyotnShr1rQXh4DaxCWVUWljsCXP696sc8vm2qqe4I0bXdi9TKBVdZ3WZS0QF5Vlu7H4M+7XqJtPFBXlx43uhEHlZ4pLG36Cx1qQb9RUT/l9rMO3OrNL03ehiPEZTjoxXUQWKvQF0h7eXPbARDU9dw/uogVlw7aY1ZtHWvatxQx2u911FcUZgvyrTxU1CiSNh0naySL6YKzJPrUELagyQK1JqXxIpIEBkFm6KouiLtnHdojasx5wtZQYpUC2vcvkbelsdHX+6UR1aW3uNZKqYVpnDgdzpyPI3nOpl1XAQ3P6SZW5A1Qi20clUqZlG7Xk8dM6IwXTMH42tT1vH37ho8PZ07TxOlU6GPg9nqPPJ6ppWcuSs4F0ULQggTYps41yKu5UpNOnqpZdJZsQVsJXtXP1DqRug159sCu6gVKG34gksh5ZrMZqN5xN40jr968ZbsZuL2+4uPdA9dX1+y2WxThfD6Tc+Zwf88gkfePT7z9xZd88eqJ300fmOaR693A25fXDMOGIBnNE5pntsPA6XBgs+2p8xm0Ms4TEhzRhoYSzSemi74H1EeQLRSJhdcWvNX9ShqRokvgjDaLUYwWaQG5tcITrNhsFnzBegOc465+f6yeXRIuQIw4zei0iYJWMUsHQH2G5DIsWNWfI8+CdVuHC38nazFvlf9WoxKrWLOa66V12aiF5sffeG9w7vqi995oFQv0tU4emJcn4RE3+IHi9sZExKkYY8Dr0vewvAKPE9EPuLr8ypYJ/JEEbrn8pJFIwKULky2uxkthLn7NMKp5ioj4aW8/uyAE/HseyJ9dVn/M4sd98QZdttk3tF6rQlYrUKqQSagEinRUeoqOZEnM6nRJTKhMhD7AZKO8Qi/IiI3v6gUmgQ5SMZlfhwdn1kEJwQuR0T9aUmtIPPj3W3IXRBxl+0fFNb0XV1st+E7TxPk8MZ+ygxpFQjDOWc0DmWV6ql3XIFbJz3OmSxEVJU8zmip5EjabLSFX+qBMNTN0G968fsXD05n8eKZH6LKy7ROlJGQuhFpQzcxYoU01W3s3NoEooKYnDgnGs0sFAil11FLIxTKRvuvtRA/iw2ozTVWRUmIcx4U+SjFyd3fPfr9nv9vaeV6Vvh/ouh7E2vHvP39myoXD44G3r98SzpEXL16w7wZKqXzz7W/58uYVf/7VF3Tdxi9UQYtpw3uvs2y6nlNp6B8L3tWGUK+64YiQqQRSVPcMKR7sAsFMdLzC4GijvT3inLQEJCQPzqCS0GrUnsSEqPHbQYPZ6xK9oBYtgKllcNK8vC8K+Y2J8HC9cr/SAqAsCNpoOVOgNEXJjwP4IrfzjIgm5WVF29pGP7mEduk21hbo1zRZ/e+u0sCwPEYvnhM1XHD11uzRDlANyaSAfkg+8yK/iB8hNFFFWegX8Zzop95+1oE7+H9aKma96EK31vG0BG1ZEHeL6RpYkbVgqpIQnnPb7opnB7t3YpWl9P6ccik8W4DL2+QLNzgaoQo5JCoteEeK9OSSFpqkMlJIhDghC/J2lN0i9AR0VrBMIgztLsGKdv4MOrUkrhOreEesaCg+vipevJQmAAsuM4zRPb2VtTCpHrQPI3nMbvFqXt2BYPIu5x8b9G8in0hAojCWM6enkRwyobcOxThERI0GSKGjzpW5GoLZbweqdIRzZtQZCYkuBc5TZhxHzudxOSRqtYaKoFak05QWZBVCIEgkSrXAI0qfsI7LaK3VqSmCME9yXZRKxRpb8gxe6Hz37h2o0nU9Ra2UFrvOkF6xbtLpdOIwKWN+b5Pu+w1f3b5E6iNXm5E/ffOKL169BLHxbkatFUoQhn7DaTxjpmOBJD53smajh6aKxkhKAbMcNaRNiKbVxpGkiLVkt6yqFX+KfZ4xxB1iR5UEtaLSW+oeE2ha7F2XgcaYoZU6xdQCsdRAaIoMxesi0GSEAaFIMYrRF57mRldeIE8P9uLFu/ae2Bq8oD0vlGLNZRBdaYwW3teA3UDzqtNWtd4D1eJSyLVrczWWco8TaZx4dKTsvQISkVCpxX7OjMqqTaXHw0w70Py1SItRjbb8Y0HcdVaTtWFFEW0nrl0FFpZaVk5KQitSyFLUkKpogDIVgkYvKACYcoIo9s8X0KKf8zjf4lRsJ2ZlMb4RgBG0U8JsVMsUNsySmSiMdSaFTJKBsRYiA51kglb2w2S2lIN5NtRBrVJeqlftccpG2BxZF2lb+A44EEFK8WtgaFtEFqvXds4H58r9pfmwhEBMEaql5MfTifu7A/cPT0xjdpVTOwxgPD2xOW+QXpcUWLNpblEhELjZvUBT4Wl8oIZCnSoUyJN3XUZIudJTiBHGomyHQAk9adhS6DmezijK/f09n++VbpqZS6aKmFeJY9FOrAOy1sqmSz7NJNEBtSZzwnPOUUJCQqCUSnIDq2Djeygl0/cD4zjzdHzk+vrGLpQWYgx0Xc/TwyOJV1Azec5s+w2P94/U08RvPnzLn/z5nxHHE2W346t3b/nVmy8oMRJigiCk1DPOM2wicS6UYWBTJ2Yd0JKpArOARLOl7QcbaBG9KUG0ufEVkERIWCBv3Kua9qRaJDVVCub0pyQKnQXkYF46RSLVwQUk5743XqSMVDWrYiQtstjoB3UbCGb0mhcifXMkorW1T7oAH6mWkeH1iapGsS2B7kdjvZx58cC/gikRMdsHTyzE92Nrf7/05q7eo4G2cWrBaFbVhX8WSZZFNC7fD1HApkPFzum4Yo0e0axk2xNPnRuXVde/+3VpPLvA6j30PKf/b95+1oF7oTK8ILcuDU/xL1QRy7ncahTLNVopExVdnQKDol54XERF4o8JLEXJUC8ULPX5qWkG71hFObPIBGsnjqwDWSKlWut29iELM2n5N6SCdMZlawSNlZrUstkOxBG49EKcMKkbbtvpdEe7TEsy5gHaziB16sgeq06rtOtni1+oYsqF8TRxOp2Zx2yBTW1ieUwBKVDngmKB2HTsYdXYek1CtRAlsOk31FgYZfQGpkLoM0IyO/RSoWYCiS51bCSiWZgrUGeenp44Pt4zjSPn08hUQUsx10OJ7kfu+vVggwU09dRSrOtRlRRc+YKSczZ5oGB0gSNWReiHARBKKfR9T7/pacZA4zyT+p5QYTyfqbIhUdGu592bNxw/H8lB+PjhA59f/8CuC0gHGhMxJqr48wvBkF+x4GzNJJb1pGCzkaroQv219vIlu7sY+qu49E8jKWBOio7WNUTQjIa0yOiUZmdrxVkkYS3dzb2yceC6qEgMeXu7+1KIs6DYPNuNjnGQ5L4oZnGqCyoP2pphWMBX8KEgi5813jouuITRgrVx+CvCX7LDRsU0tF7tm+1bDX032iQsjoE22aZt+MUwqpnIkWhUj4j6e4b7t/tQhWLvkPH46/MI8vx5Ls/vMp79xNvPOnCviNO+bExS8DeoFTsa+l6ob8tJF7QoLpNaWnBRFgtX/FQWrLmmvb8N0DsN0vi55U3R9fm12Xjt3zqHMj4L1FVsFuWsk2tqow1jSNV47aYqaZXIpGgnNsAhKk14Yq/RmbPlo2+gBmJkHaTQFCRN/tcabiR6I0YtlFrIc2GeM/NsTS0RsQYaCUTMPD9PM3XKxG2iFiVVo7RKzUixnKTMFSKk2HGcZzb7jVELUyZtElGUoUvUEKnFRGd9DBB7iJFYhHnTk+dE2fRMc2bUQlSYa7YgRIHQWWB2L41KoJZMVnVDfD/DY7Lg3opEiDW8RAum0zRR/WPXd0iFoesRgS4lur63QmbfEVIkzzPHw5FS4YsXLxnmge8f73g6Hfn88T2/eHVFCYl+OxjK8wJLrcWKjCLMkwcqX4FNGdQFmCsEqeRqEsAm+TPFQnyGGqNY8LfaulJDcurQZlA6+gFtbewWkKsj5Kw2YanJBdXH77VhAM0jW7w9vYGpNlpvISu0dTb7GlSljZFs1IiN/rPP2zSY1lC3OBXCc6lT24rVEWtoyjIWwAB4Furf06YsMSq16c9b67oFb6VZwC6KFKm+d4w6saLlSsG0nwvuXQNrGVj8gANdmm+W6VK+J7ksgv4Lt5914FYf1ttKFRa4LwT+1SmPsNIcVkv3N7YF4PVgdJpj/d7lKWiW8/Ls8W1htPJCS9eWFLHI8jzrbF9nkqeh0ccrJEqFOVhhsg0Wzh7QuzijERhAspg0sAeZLGjTY92ZMwzZJ7uja6Yhly/TkHi85NU8WwlhbfdtnInJzIxqKKXY9PGspJiW7srWwFLmYi3o00wYEohSnSZRlOJNOrGzg9MaKYTH+0ekE66G6yWtjQJdtLR9qpFRIWB66hSFq/2WLlp7+8PDIyEIoVpRrxNTkyzIrL3uWpimTKketFWJsSNGsck0sQMJfs1kURNYQU7Y9AOn44mrm1tKLiSnUay7BfNyp1KmyufPnyi5cJs27K+uzF61Kk+HB4YImqwWkIKVC1sHng0fMC+RFJQaI7gsMXpAKE512d8Xp0Ns2o+0xN76wgkh2e6o2SkPt+qNTksQYZGuPZ+DqiqLprti0sBJbZqTSf/sZ0O92BBVXE0lyzgyXYJwsNciRplZRtpmTa77TAQ3rPLX09w4WyOPujrKD53WW9Bq4etgAs+Qm4baaZznu9r9XjyvFrFpOa1Q2YK3Ie+wFCXbAdB+VYwdeDdmjF5rqW2smfUR+EJc+ktAFmngj5/Vv3T7eQfuZtEqFwBYAUeKviMWVN44Mco6YGEppHljTcApDWlKlOeXU61/3BBGQ/UtU4WVV1M/AGwvO+LAnAIx1UMLzD02/WbWmYnIgEkCZzo6TXRd9g5CQ9ytm1I6b8yZMalgZ6oLr6Uu6Gd5Ds8WiRdRgiz71jZAS99W1N0Iv1oqWiqpqQ8w2VOohqDKnMmjBe4091bnLYVQrWg555l5mgl9oPp4t/12zzyP5JKpc6FMmdCP1GKBTUKgi9HtZb1YWoSSbRzbbjNwtdtwOp0pWqzhVYVaFHVJXJBK1cA0WRmuVmu97lJnLoKuJSfZhUghQuyIMZrvdRroU+Lp6YkUIy3uhRDoumjF1RCRGDkeT+TDxPF4RoBpnpl4IgaBkjnPI8fTgav93q5frkh0SiDMlGx2rHmeCJpBq4+csyHIosZNG3qNHujtXa3unGYDA6xWE6I3KUk006la7GAXr4VgaNTgT0PUydd2NH5OkhcVk9GHwkKTBB/mgTbJqKyIewFGYaEqjPpRH+eq1ojfuGYsGEpt1Imusxrtm+sUeb+FELxlvvmOeCadWd33ZKVJliYYaaoRV+C40syhCKsvt4EBu78sQdv+tq9R31elWJ9Ae8xKlejyeuxzjy9Nt96A5x+LjhssdCzsAL4gaxuy1C6Yf18t6KpH1nYqL/8Ky3G4MiGWWC6zLQvLGwcQ6tp0oCgyiwVZbW251nhDa0SoMNOM9sWDeKJIR/bq/USkI3o7S2KIWDdNtACtvcKEe4AI9GrG2xl08g61xjmaXIS6bKKL+x1qL9fNP8pyNe3h1X2FzbypOsI25Eet1IDN2ayVeZyYp4mubqmjob44WP9mwBpbylQYNgNFM+M0sd3sOJWjmSbtO+qcAaNnZi3UmMk6YJ3akZIjfQoE7dD9nuNuy8PDI1F6TlNmygVthaMoIMG6Dmu2IKKQghkn1TKRc2XoEyGmJaDFGEkxooKZVLmaZrMx2V4plRhtfdWqzFPm6fHAfDoRckvf4eHpgZMo282e/nTg8fDE0/GJXX5DQIjJglcp2bNHD8pamKYRSl4DjnhRmUQWBW1yv2R0Cy0AJrNwpfHRgkSfu+ioG7GhCQZILcC4UNSpPPPAaY9XMaGphHW49YqyvcwmHrQx8FO1rqBF1fzQtYXHCjW4Z44HVVa+ulElWnQp7BnGWot8zQGwusXg0vgFC6UpbV9GWZwGtbT9YWl5oyxCaMga5/eVZhxk+yK2l0gbkydYAK9l9sDcuFTLMJYBwOJRRS/iUuPNpTECf0SBG1XXfq4FkpYW0VIS/2gAWX1ReerVimfZ3lzNzTwm0EaiNLmnoW2M/mg0RNTlbzY3QgRTlai/WY601acdaKNFxCSAhY6i5wuO2/Tcndjnp9qxiyPqksAleGdgtoAeOjEt4IAv2Ms0ACMrW9t6o3Ma/+YB3SaP+I8prgRYOe5SCjUXS319EwFoqUbZVDU6ZTa+emIiVEH6QAqR0Fk79pwLch7p9z25ZI6PB7SrdF1ypKZIsIFZQayQFjQAHYTIbhDmYmPIaq1sh57r/Zb7pwPJCXsNFoBzKdSaXRon5FqJ4txlmVDMUKopBYIHpraWYogUDxZdl9hut1Sg6zpS35mJV5kYjzNPDw8wZ3qE4+nE1e6KMPRc7/ZsDpnjNHEaP3A8nwAodbbgRVyeH1qpJVsxMtiknVKqv2fBXO9KoUnwirauQkN/wdP3NtTXlnAmSstabL1ah7k3iNEG3NlYPaMHEiJmMDXV4MOtxWR0IVp7/SL7a8EHL8bbwlvmTbYALk4FVVkGIBSaykvXLmRfuDaGrlE+YUHg0ELu2jmKB2cpTRLonERoBweNpjYbiZaWchEz7MrYb1Zd4mhz8BdpDV0NjRu/3RwFxQ98C9b5IhbLkv3WWp9PurlgC/57bj/rwG1DOa0VWLwXvdFta7dfdbQsfkr7id9SRdVlFJIFWi8s+CTnhUpJ9iaEdmI61aBztZ9NLRUSdK6GhhtSz4bMJde1gzIEsl6a+nTkOlorvAfzrJN/ndB4tgMmKCEJNSpEtWDeGZdo6hKMZ1yzS+N/nYdegrZgjR4OIYyWwNCTTzCJIVDVrm8tlXmcQc1zhWKSp4ZAUkj0cbDuuflMPnWMYYasbDYdpRM0OLWqyjxn9OxUT6kcxieGOrC/3RHoKWUmqEndajE9d0hKLmYMlGff7Chdn+ii0KeA9DbRfSxQc/bBtabr1qqmhcb9mYOpJmIMxNSbAkWELiVSskBVS6WLidM4kbqerosUjP+OEolihc3H8xNTzlzHxNP5xFwy3Xbg1avXyJC4ryfrFeiF3bAhxkD290ejNVDNVdyaIJiJVIyU6GhaK0EiQjK6pszmPWJTdBGn9S67JUMDEn4wIC24G51WdaXOqgdt88kJqEv9KhhlIhFVQUOyzIlowVftQKGIrTtYFFbagnJjLavrygEJfgApoMHf45U6EMGn2NharcUn9vh2pDSKSE01I5a5tuk1y1xWMWAmxcUJ0QBLRR15sxQZJQS0rkMWGs99aYqFxxDLRG1vlUUJY/QhQHMHjGIUaZsmpRr8vTSPokXmqA4Yf+LtZx24V/7BUTGy/LfwXdIkPa1Q51U3dy2zd0DXWaBcBmxH0klWKqXx1hf/VIxCWSZOB0fDFdqcUS26IG5mmGMrREZm75hMah4mM5GJSNJIJ2YBO4kVKSXKEqxNYeIUyaz2t5Ks3GJd1toFRdKCuqx0ySXXBEsK1+62ItJaF0gSqU4TUEEidKEDoGRrh+92hiweHh6IMXC1uYEqlLky6UgnHZVCHzv22z3lXJjLRM2QfPBBqYUpZ0+PhTqdqRqZMoQ0mEvhPCO1MHSBbZcQrEmmlMro6pFAhBjp1M2VFIqbKcXoNEII9BKXNvkQog8SzkTnLLfDgLobYIrRkJzAaRw5nU8MIbHtNnx6eOCq3/Lq9hXddst5OvD+00eGXnhxfcv+6prURQIdpapveDDDVUOpWoKZRUlA1EbAhBgRL4iqI1QLHi2aVS/XhCVwrJnmWqStrra6YI9pHiXSkLeYPDB7hyTI0mxTPYjLJZ/tnzfQo749pQGlRt+pBStxtZEGQ+SL81+jQX6k2wYWFBxCMMdJR9r2PSN7ELFst0CUuNCdSHsuvtCbA2e9YCkuOGZplFIrXi7ZfFMtBNBM66a1DtK6xJtaV7nbEkuae2VD7q2aKp7d/vFQJU1jxxKMHG4/a9VuPJc9bqVU0KZu8MUkrWHFF3h7w/y9aj4PRoWwaL/b8AavZSx/tW0uVNFc18BdsGEK4hNHvHpfJCyDWmcis8RFKpilIw2zbYBGvWQvkmYxjtl9vxepVbwI4m1Rw4KSG0LiMkVtB1N7YCvCulIgSCD0ng66UDylZA04hGXDUmDYDoznmffvf2C42ZFCpNsn5nni+HQibSKhC6QhsN9dUVMxd7lcCVHokzCVylwUwcyTQhD6FDnnya5zzSRRuphIUkkBxlIRLUaJxNVX27TIukw7T4L5TacOQm9peVs1Yhx4SlZMDmINSyJC3/cE53wLwul8pkyZ682OXTCvlF+9+wXvXr3lFITT+USMyldfveQXX71gd/WCWYUhWvemSfjEZHwVJGR/rwTNZxty0f4RCFHogkkszXbb2OxmUhTEhkqoDxUQMLQsa2x4HrYNCVbxbkjCMugDdww0SaU129QaVmWErkDAgrP/wtLQvHj2ag01a/eyZRaG+tcBxFpWOuTSZGoJ+O2M8u8vc1DbAeVrXMWz6Krr/MrgXioRYnXqRVpNaA3UjRaxX1ycBnHdPPb5OuLMgnnwYlIbi9bon1pNi9bsc1v7vErTtvlrdb7+p95+3oFb/unPFV2kavb1+hDVshy4AFQ32lkq27IgGvv+xe923belak6/XGRRVXXRmC5vgep6vnhg1VmpWZg7b7RRC9DJJYBZo6mqWI2osmu6uUTbHUjGGnHafTOO9GX5u9IAUZD1MinPxj21gmbzQraHeFGoGpKu1RTSEoPvFeMXk7vzJYkEzAdEfCEPsefh4Y7z04EhbOi2idubW07lhCaouRDoCDFQHcWahFDoYqLvqw1oyIWaJ2qwtL6LG3fMq/QpcL3fQs2UhydrWyeabpkAoWMqFeps070lmcOeByYLGsU3eyR4M0wpxmvPBa72O2ujj5EYEyF0qAjH05F8PHObOjbdwHE8U4Pwq3dfULrE/cNnvv/wkU7gixcveHXzitRvmRWQSAw2EzME9wGpBdWOGFzYVzdISAsHa23j0QvOSheUCSu6mkTOwIX6718sHn4E5oxFuQzccUHaVf31k1CiuThejDJbVrcH0sUmQkFqWNfcxfoTz34bMm7KFnEpZVCjpX7coLLs27bHqvPlwbqJVwmurdfWqr4s8hZfG60cBHJdOp7N50SIXhRFns+jNAngagG71IYuOjBbrcgyBruvgcM2pWo5B1p8cbTd9tdlV+VPuf2sA7eshtwLQrRgopZiSpMF/ijt0lVZ8uOTrqHvS6OoxcKV9XS3n1ZaZ1X1N1qrFzkV91UVG2WWscDqVXaqoe7ZqREL3JFOowfqjsxskkE1OkW6i9/V9NsF+7pYYYbC6nssArMvIk8lJJgudonm2hD4il6EsDRMtAJRLnlxXDPdq22ehG3U2FlFXlSIkoipI9fCzfU1JU/kw0RMkaf4hHTXDJsB7aAbEkUzUiAkC9wBIU8FipJSYOgSpISUxKxCl3pmv3ZDZ+ZO/VCoqpzPZxuSUJTzlG1cVh4X/W6yiicXM+8IHkhCSGiIpGAKA83m2x1TIAYhhM55UEWjcJwnHu8f2RH5+tVbDtPE7z//AO518f3HH3j/6QeO48wvXwzc7Df0mx1FOoY+krMQUyKJIMHoGtxTxuSBkdRvQGZTnSxyMnt8ikKhEjVSLfpZAGk0Q1jXvfzoM/F1XRagYofu2uIel0xQmzMgLBSKMzOs8NY+Nmmibc0GfjxwlQaePGBrQ9bPlVlL046jZMuGW1BuWYX53kheXo2TpI66/bCoYo+liWm0KUx8b3oG3pQvayEyurTP3neoLvfTJXivB0RdqRq/uiEko0a4yDy8FmENQLg3UqNy2pr8abefdeDGBXXL8nQ+rZkCgaNMheIi++C8V3t8WzDLpJvafvNz1L78iFtOol6ovKAh1pTtIg1t9Eld/0YLsNbiPlsqJUJWb8aRjiLWhGMUSkcNXkl51nCjRtl0gZADsmEJ5M2YftmoC7fNUoQ0CdSKsI0KtAMvqAUFdRlgmS2YCKClEmMgJddzl0rfdcy50qdoJlEu4epix9XVFfk8cypnBt1SyNy+ubVnFpW4cQVPVfJU6ErnKb4sE8sphU4EQmKqmZwzIfZsBhuoUEohBri6ukLkAOeJ0d3XTB0a2XRrYDKvMPPVlmQNJUXFNNLOtcaYmIvrqKsifbKRYSFxrsrh8Yl8PNPtriAEHs5H7o+PbLqO8zzy+eEjx8MThJ5NCsR+S5FEP3Q20LdLy7oxfjYQUkRrtM8VGxnmjSC1GfpXS81DCNSa2sKktaEZ/bLSBs8X8AXKBtdUW5duGwasanM0a2t5NzN4VMU9SliDctNvu25bYNEnQ3jWoMblz7EiflPFOAevzzNkf4D1GxRzZrTDyenQH3dK1nZf+92+9hu/XmyTqwOZ4FRoXU4hHDmvA4Pt2vqB1Oio0GiSZyPqjdJTC/9ZHcwt2b0LIduf8eaj/x6k3W4/68Atsorf17RvvQxGaQC+iNFqrddiY5hsu0RUA5K75Y2XKIaaq20C2hgkMdmbBlsM6koUCuaXLY62xWfrpYbO1KiMEZPulQAzaIK575lD5exPNslMlDZL25PTEDgrHNmz3x2XQsqCpKMfGtFfe774/uyp2EVauwygaPe3Ycf+GNt8ihSl1kyeJ0oppK6jTBac+74jdQmJnUvDMvvba4b9jfG/Y6bbREYRYuzIeWQ6jtyfHng93nKezmyvt7z68iU62TXCD8vxaSRuI3nMSIbUBTYpMtVKrbO5vHQduU7Ms1LmmajC9RBJNULpyGWmDB1VA8fROOMaErmadl76DmJCgw8OULEhDEGQ2JEr1Fp89mQiSrJgSuDx6cDHhyf2JG6HLb99+MDfffstUxm52ez5P/3rv2YOFnhfv7jml19+zbu3b9jcvCBtOmLXMUhHodBO4aqOwIK5zEnsGeJAiB1dNzKPR6bp5Jvdu2PFbHTDvAaP7AU/BdNpt6KaDwBobdWLAkqMklO1VveiFqBLFQgBTRuqdFao1USdV+pPis0Vtc7EuvLTFe+Y1DW7rKbRhuiZshjV5eux5OrZmjsbuu5bPAhqCIQuLH7uBjg84GvTU7t8VZTYRVNd+RATFZuIE2KzpXXTNYVcs3U+BrsuNZu5XIxNYWNUobjxmIUatykOYgoo/x7uu1JKoRb72sOSI3TxDWqZa5vzCfzxDFKA6i2tzwstz26O3Ja0LNjPWdC2alDTz4YafEN48PLmFW38d7ATu41QagReOyra/Lv2C1qXV/DFQ4FItKnvTps0KqSTaBJAEoWZyamTWROxVlNhhJ5CJnSzpZ1FXE6nhrKzf+1VdaOCgqPragu9qnPa4oeR2oBdH9dmvDeevZiErmRDw1oyXTA+MEpw1CcmK1RliAObvqeokmtBJiUMwrDZwrkwPk2EbeTh/R3xHDidNtSQefWLV+hG0KmyH3pqsS5MiZWgpgGvap2SKZq8KueJeZyWQqNqgDJbVSBUdkOPEHg6jwy9FYFHddkXgEAXLfW3/eVD3oI1mYiahrsqxNSbz/hcOM5nDqcDO4R3+2sOpyNUtYJgnfjyxS94uXvNtMlMr99wKjM3L27YXl+Thp6YBkKM1uQj0RUNDQ20JeuT6rWgeSTPZ0qZPLusqE/DMbYnOmI1+aJlKtVDO9hqtSDcUG8hLPyqtIUuq0dJFVn4fwu0WPHS5X+1uBY7hKXxSosPF9awNJ5Rqrv8hUuYaXvOX+dKcVojjVmxuioM1oywyQvbmDqnQFsBk6UIuyL12lrkJVBQ99M2hBui7YsiSkzJ1nG255iSGXwFmvTPqI+qmRiTgRjTINoUothbw5cErJnIui1DTBSdn/PXLUZ4O7wZb/0zseu/cfvZB25ZJlzYi19SjwWAG3/RigfW41WX4owNttLFkp5qFeDQfuXFNV0qxf5bQJYFtfDfTYFySZV4YVJU3CVP1kKlWnt7JtERnnHbmZ4smUK1CTmu6e5644SZQTs13ntgUax4ntZ4HE9h7W/a4rfnKEkWLavUi+skWNYx+4Gn62ZpU+PnUqhB0FqJImy6jk23IWgg12om8UFJYQtdII+JcZp4fHzixfWOw+/vGcYrhps9x6cjm7Sl23ZoxYJ2MD+VmgvHpwntOuYamOnINXI4juSixK5HYmcpv/uppBjZ9KYgmXMkqjWQnE8zXUz8/8n7t1hbt+y+C/211vv3jTHnXHOttS+1d7mqdpXLl9guJ05QjoKLAwIsIEIRQsIPPEEeeEIRD0RCKBJCXBSBeEE8hDxFwEuEFCSkE5ScEDgiOuckVhITg+3Yldiu+23Xvq3bnGN8/dLOQ2u9f2Ptcly7zhES+3iUVu215mVcvq/31lv7t///3winvdnIMpziJw5NmBp5cU/wulUOFhPjtzPvPXvK0uCV68e8d/eMbz95lxf3d7RauTlec18Lv/nON/jpH/scr736Gi+scDhesawr65LRESTMM+YxCUYduNmbc+KFVE0LpAIl9AWOb3iy0pvj9ZrQ7pmgN8P8AJrr38Biq+/eGHoBUY/kI01myZh4czmiTMa81QGttVA8NpuNSCKDtGYX/7WJiffLZn3353Asm5jTKnPTDUzbYu+NIKzJZkNvQpu9k9QHQDTzCUF+FspsfiJ7Ja0W/O4ern1jYlOwdCTt1OKxVlSyVwnighu/d8FLl8TwNjHzPpt7ZsWEnEHN7IaQdjqjpMC9jd83knchmoNm2LRihEtjIcenLh5xsUZTwCI76OInrEvmZW8qBAZmZhMX8wLNIuGORR84neOL45Dw//YIqOkiYE9MvYKtMbpsMkjyZJQ0MlV6KCoXCoVFF3IuO9a9jufpLoSoUS3YHpSHYbxXeXsGMLr9s0E7EqPwgXmp2WWexWzhSldDxLIui2c/ns6RU8bEh+yK+fVZloVlWTg/OSOPbrk9POCd954gh2/xiU+9SjlXNCuaM53OqdxzuFpQE9KaPOM0pyGWAoe8sGRX/DXze3fISi++uVHhYMLWoZ6ri2/cYGTiv6I+hqtb90HK3cii1NZ96HB1u9ZmRq+Vp3fP0dp5Zb3h6bNnfPm973JXzp6hWuNVeUBv8Pb9B/y0/BjrIlQRjsdjTJN3i9VBBRv2o77ONIa4OHyhmiCLD8Awr3YE9xbX4AibGX0E5hhy0EeAMHNetjHpbA4LRpohRIbOpP4ZGTWjSQrM35MYf2X1RGBOcOclq17wfTMKUV9bI5kRr9gug/7llux7MN9bLk6PHPS7WTTLxW62EQcctuhD0avQohLwgOvvQ0MAZOpVppn7viRR6uaNyD6amMiulBbn9SNG736vHZYRZMxBlO5xI/a9Z9nMBmSzxuVjECdmjPkhHx/rwA3sN282Z5jmOXzoRu+LoEf2ElkzIWGXizKsXZRdxmRATYxLwcd1zWeYsMpsknCR6TbnWVtz6ERiE2BQZCHbNulX+yzKFpL4RheHUTZWVhp5rZ5Vr+yqySruk6IEzs3cSNJwSbxauPGP6+eHW8cbXhLvrdOCquUZ6OgjtOLsjdaNnoZPNTQztvsTOSnr8RpLAwbwe7OsCw8fPuLd5++zlcLjB9eku6c8+fa7tGZcL4dw/susy8J2f+bFsxfklpCzwOolfrGMyOq0PE0Oc8SMyaTK8epIM2HpwrJ6hXA6nWlbIacjKDGtxjkUFZmNprQuYJDTOieo58UbiXcvXqDNePX6llUzX3nyPi+aY+ulV9Y18yOvvsnt41d4x+44b4X1sHJzzORlQdPw2x7Ocv55Rn4pkzZmTDMtEVZVel2wutIxrDbadK2L3zZobVR53Q+jQciXOChm5Zkmvu3JiQftOa1dXNZecVXv4Hd7eT94yNCb+QCS5h9GeuDLw8AtJrnPQC2+DwQJtGTfly+5+YUFsqqM/nnsW5+y9GHa3EicHMoMtWMZzUmJQSEe1Ic62qO473FVv8+ttkh0ouI0mTMtB0nBYZHkkFG8BW8Qh3XueH/T9tXfW2ttenGLug0DF4w3j/UvpZc/8PGxDtxmzf9EhBrBZV5V2Xmj49+zdByZR8inzOpsOlgEdEH2mZLE92YtOLrp7JnpRZY9dQEqczH22p1R0nGl4yqOd2ehpRhdZpmEjzCr0mkUD95S3dOERjUHU5a1zOcZmbe02KzBZhl8UecID0+KHjCNIYvOZibR7FTCxD58i4fpvVu7dlq3WYYmg9pdMFPKGTsn1psjKoklpzCod0rZ7c0tj24f8eLFU54kY7FEts5v/uZv8gf/8M9ye7gl68KSM7fXj3j6opNVZx8jL4qQOfceo9ISMjjX+NCEHDMTSzP6uc2mNPj7T8kdAS02sw+BWBxrzJD14FSu0kjqOP77H3yAts7rV7ecauGr73yHp/f3CI6R0uATNw/5xOufoC2Z47nw5On7vPb6J1jSIcyLHDuPFYKbRfnC6qOMj3UrONwhQUmaSs7wjZZQPlbDI3ZYkWLd5fjRmK5R7Xh2vQfyHt7QPWTWDQ2pvOP9HaV1Z5uY7Nm2RMD1YRh9MpOsBfAymLl+mu5q5GY7rBLVq3uWxO9fsEvmYwT+kYzFX2elOBtRzKQriXp/BgtIhTmZabBbxu84fzs6ABaNTfOMGgIqqWMT29wDo/k4SgCRET9GNtfm3ycdOZS3MuPOiBWR9cXX9ilBP/jxMQ/cnW4FuLzpl7xsv9t741IQ04GgMRby+C0Pyk5D8WaXXqghI00SuXhe/NrLPPP3DH/851IgFVi3FUMOEbRDdlvzQreNGkKcFpn2yLjdAnZllcYmnWSFJRV0dZqUHJjmPSScTTLw9bFwx6JV/9zSxDOlND+Nex+rvy+LklxsBO59kyGu/Gytwbq4a0BtrOpYaJaEHJy1YepB4nB15LVXX6O3yrP75/z4pz4DtvHl773N73zpt/jJn/1JDukaswO6KMf1Cs2gq3Cq99StsPWK5CPrqnS6Y+34vEQNQZOh0TBt5CQcl+wCouncP0rhPQgYkBGSulMfHa6ub3hxf+bu7o63bl/haj3wXrnnRa/QG2LeYHr04IZP3r5KMeM3vvpb5KzcvnWFSkPzsg+miI3s01D2IKVR1nX2+ZiCKyGHelfUB/JqVtQytRV3UWwteNeDleDP35piGuwNkgeHyRP2mZsgYR6l/loMV0AJPU2nkWdwJqqbXs1VmV3DysEHHUjXgOX6FOTYRa9lGFDZgIlGktP6SwHXfcIvGpMDepiwEuP0i6Qp1mPcXkXc2pnA/XvQ/wZ3PKYjCQ6D9NZJWX1oR5AGvDISf2/xXiRMtdzbpF/EAt9obkDlUMqAQPrwAxohpA1KYEApnlXRrfMymPJ7Pz7egZuKWdpPwPjq/v3IwtlJ8BYh9lIdZeGz6+xtGBQeM2ZgI5o/kkbWEJl8l30wdCR308+7iXstN9DItEeD0r1F9uy7L0Ixt3JdRV/Cu6s4tj3k79kqhQMrlWWpMYeSXZBDBOeBpQ+RV8V9uytTf2LVgnIVTZaBvZvNQ2kv8R0HMnVRQ0fYeucKoXbjdrnieLwmp6P7qaTVN1CKjZqE25sH3J2ec/fkxJNnz/j0m6+xfu9t3nv7Hb796kM+vX6a9bjSq1HOG+f7k2dGB6FJJa2rz0o0t251P+sFZPF73DY3XzJYk3B7c0UzofKMujnW6Pxw/z0JXDjnxNV6RenG3fmMHK7ZauX+/p7HVze8evOQd+6e8fx0x1VeeGL3mAjHlLm9vuETr77BfW8UGtqhWGU5+pCGJckMFL/7QvY1q+I0sZkdR5Ug1jxrywvJcFZJN9RKwAcBc0S211pgrpp9zRvRgGTOm2wRTJ1/4ll3NQmLHZvBvAHS+2ykD1c9q54Q9do8MIcv+GxUWmTZmIvDAkoZuPhIBqx7QiAQjcwLt7/oT+15N7NSGJCHJ7eerQ47Z8k6mWBtJhp4Bd4M1cioI3aYWFRDHe1pVp3E74/BxmO/jkau2ww4lDImBvkeCcpl94bjPgVnxJ6wjx0Tf2b4+keukO97fPTc/P+Ejx6mLYNOMzEj2f8OzGxnLNWL6IqvgFDIxB+ZROf4+vT0iDKx+cJz6tP4mr3cLY/k3Yr5ST8akxGo5+8E7t0rFHO1WrFEDRl8jb9vrBRLnHue39/k4Lh1BlnjUFnMA3iOBZwNMuiiyCrOJ49RZzZI2xnnqgd/HcDEs8KkMcIrX6hLg13SuqdhzQxNmdvbR+R8RdLVhSopk5K76C2LC1cO+cD18ZpDWth65bAeuc1H+tb45je+wf3dPeVcsNY5LAe285myFcx88MHxkFzpWDesbywJ8rL4fMVWEKskC+mSuK/I7fUV18cDSceBLTFk19zXW1ymX9W4K2dYEq0X7k/35A5f+PSPcnxwTTEfGqGlk3MmH1eyJg45c18rL073SOvU88bDVx6xLJklr0EvbPgk9rFHPSj1EcAYy3UPVUKPpljQFKOp3urg1oeEn9FU9+ale0V7lj2y5xhcBOCOlAGrNHNIpUW23i1cEQfGPQzSIhBLBLKRaTuzIz5VZOQevJ3tNX8XAi7ZoQ9f9y/DIb32HfP+0GM893g46jn2v2dV3WSuS8e9xdlPiJc2aWepoHYRKiMWBJ3M7Q/iNS60IpJ35pWNJqzs+a/NxMffr6g3vy32i+A0SvXO68Toh6Dqoz5+qMD95//8n+fnfu7nePjwIQ8fPuSLX/wif/Wv/tX5/dPpxJ/6U3+K1157jQcPHvCLv/iLfPe7333pOb72ta/xJ/7En+D6+po33niDf+ff+Xeotf4wb2M+LDaDG8oHwyThX5MeJdcIypEhmPtbiDkftgc3ztkpHVW8yYAPvXW/jrbPrnNJGe6jrNCj2z7ifxkv57SjXj3wz//GZGsrFkE9cOkKaHautniQNvZ5lM0SpgtdMhuLuwha5mQHbCVGmyl6SO4xvnqj0iflRLAekmj17JcFZLF5rVD/mT7gkebvWZfsVqdJ52rdWudc4VzcdtW3qbIuBxcukEmiLCkjouQUoyFS5ub6Fk2ZeiqcW+et1z7JrRxop8pv/dpv8uyDJ2DCYTnyxquf5MH1QxZWtCds69AL9IqaD/td1I1LM50lCTl7k21ZEovCuig3N9dkVVcwWnPDq5Shmc95BM6lkk2xrfHi7p7tfuORXrGd3cL21eMVYsZ99zFjdr6HLLxx8wpP24l3z8855oXXf+QNPvHgMenqmrxG83PAMr16ALc9aExsOxp/yvA8jwCuQ0DWaLXQW6H3OrPcGsEA9WtulmitU1tAG6RoKEtg2ALqU9wrzg5qPXoXKFiiSwZZfM90n+5Sa4tmsGeoztzwpp0LYxwisF49AA+IsZtzunsDMVrrE8A0fL/0aSzFlKETh4LvwR6MoFE1R2YeTK9uzgzrOoJlJCWE2/hISCL4+t+7O1tmL6MT6v0B/6YH2eTvpas3Fi+9/jXmgLqSNU8YLJgLHvnRyLATojmYPAmVHKKfFHYHiZyXjxz7fqjA/ZnPfIb/9D/9T/nlX/5l/u7f/bv8wi/8Av/yv/wv8+u//usA/Nv/9r/NX/7Lf5m/9Jf+En/jb/wNvvWtb/Gv/Cv/yvz91hp/4k/8CbZt42/+zb/Jf/Pf/Df81//1f82//+//+z/M23jpMc1cen9pUsZL9dWss/bs++V/DwyNHUu7bBYNLKvP/QeBn81+5zgf2LHggQsPZ73ZrLh4eECP68NuWD/+bYw5gLhzYPxMk1Eeh+lTElB88aZOVHPMQSXqGbXj2exYPIRa0EUJ/sfx/mYtIInormtIj83tVHut9FZ9QgyGphXJXn6mlFjCbGpZMzl78FcRjoeVT7z6OnJc+d677/Cpz77Fj7zyOg8s8c3vfZff+NKv00vFTNFlJa2J2jfOdaNXIycu4BtXrqGDu+zXzh0LM2lZSXnh6njgcDySl0xaMsu6YALnWnzYgjlj41Q2np/uuXv2nNPTF3zju9/mr/763+E3vvo73sRKQmkFSqEYfPaVT/CzP/0zfObTn+ZTb77J4cEVn//c5zjc3jgFMi0+6Be4ZBBIJBBpNLZm1h3ryhfeLLV9jYcox/pcd918HJtjr97QHE3QUVBF/JrDMFprzhqxHXPvZlTzgFciA7w0QJrS9VjjYy841NHnAI0+xDjdA3Wvjn936/RmlG0M5PBsewa72Cd+KUam7gF9+HJPip3sgbcHZPN95lTBDhgZ+fCqkXlFgjZqEtD3PnVnd1S82CMRxMe6GzNZLTBqAJXkzKwJiezPM9777G2YH34aUGRSZ0l91McPhXH/S//Sv/TSv//sn/2z/Pk//+f5pV/6JT7zmc/wF/7CX+Av/sW/yC/8wi8A8F/9V/8VP/MzP8Mv/dIv8fM///P8j//j/8jf//t/n//pf/qfePPNN/kjf+SP8B//x/8x/+6/++/yH/wH/wHruv4wb+elLvQ4w906MhbZ7/F7DkP7RR+yVqKE9lNy3LgoneJ5py/ehxpbqDmXfDYsdvGAu0DHAqJjFjc3TvW9lzp22lhg4/36Ke4BN9gGwfeNd/f9/jQXH352sTWw7+FgKY7gxHArwLFrS77RmhlN+hQkpCWR1kQ+dwrNy/IejamUWQ4HNGck+3Qa/x0NyT+YJY7pgLXOK6+9wlkK/fyCd++f8vnPf47yO2fe447f+da3ePCl3+BnfvYPcH28plal1OZT7Xuj1Mq5CMvqNK4mPtXdHJR33nXgj5J88MBySDx+BPdboZ98BuPpXLHutrGcz5wM7u/PPHv6gg9enHl2d+JUO7IeeOfFM16/vmHNR5a0sNXO7WHlD3zux3j42mOevLtxfc688eYbHA8HDldHUjALxvCAPqE8cS52HDx+/QkcOuYwWnNvcOuupbI9QBkeFFur9CaQompE5n13wYoFHNMc9qBTzPnIzhgShptgCxx27BzDBU0SGbMEVbZ36CWYRiFrn0yTSQ+MfdE8oXLL4USLwQky4R1PePqwgA2MfCxOu0iA5gizMcty0AmFKfYZlg7DcngqnuOapUl3jKs1YLPh6T+ivsg0nbJoVI7DxQYqNA6cCW9JHJpRkcS9kC4THhuQ2Bjz5pCLvMSQ+aiP/68x7tYa/+1/+9/y4sULvvjFL/LLv/zLlFL45/65f27+zE//9E/z2c9+lr/1t/4WAH/rb/0t/tAf+kO8+eab82f++B//4zx9+nRm7b/b43w+8/Tp05f++LuXi5TXvzSD1OVjBLGLDTC+vse30ZDccbjLg2G+zMS+Bt3n4nvx971SEjT7IvXswZVuE2OL17h8zfF2Z6k43lPYj4531OdAiNgwWLCLBp4fmGOMb0IjAxPIKZFiQjgKpJB5j58btLWB7yXxYJwkuKn+JpN4ZpZy5urqBl0PfgjG8/QoUSU5WyOtmeWwkHNivTrwyuNHHI5X/Npv/0O++/R9PvO5t/jDP/qT/LG3/gBXCN/69jd498m7XN8+4PHtKxyWFTsIbWuU85mtbGxRdrdWadXnTQ5gDAlGQfDDHz645ebmIY8ePuTBzYP5Ocu2cXpxz7MPnvDOO+/wvQ+e8OTuOaVXkgqrrpxb53lpZDOOqliCH3/z03z6s29REhyvr/jEo1f47Kc/ze2jhzEdx3HVl3sszAw30stgjewqShjVWgToWrB29pKcOht6HjeaT/qJtaDhaz0CxUuV6FhL3bN2l8/32Wy3AaNg87CYTBwITLpFgL8I8wPa6M6RZz6f7QrKgN7GpKrZC4rKtVWbWPD4Xp9ZuFFbmyrMuUtM9h7AxaT5bsbUU3fwmaOeYBiR3WNzz3ricwlpjYTO/yTd8WeLJMcdBWOvROC9rOQ1msCxDIOCyqy+R7X44er+oz5+aFbJr/7qr/LFL36R0+nEgwcP+O//+/+eL3zhC/zKr/wK67ry+PHjl37+zTff5Dvf+Q4A3/nOd14K2uP743v/qMd/8p/8J/yH/+F/+H1fv8wwXiqTpgjQps3kZQbaAxa5/PqlVeMsbS6gFYssYv78hS3xOHgl8DbfHP2lm2NG4GWXcAtT9KPDWN0MHRF2HEahepzUp1gN85C+fD4NCXxcB7nMxISJ9YmJD/GusjMYBZDI3tMorcNnWwXNSloULY3cgtsrwuFw5ObmIZITllzMI2rk+HvKyXF2gYKxHBZag6vrI6dt5fmze375H/46X/ixH+MnPv85OBp2e6Clznv3H/CVr32F999/h8Mhsz668vt3uOZ0d0Jyh9qwvKLZRSqI47Edw9LRgyLCkyd3fO+9D3h+v3HaKu8/e87dBrU5i2LbGk/vNgqCpMxxWek9UcIs7IPnz0gJ7sqJhzc3/NzP/EEOD6459cLD6yue1cr7HzxhPRxYU6b2EHWoTKe+3tqMki7c8APQs7yoGjHqXFihVYgA3IfYiHF4d1qrQVHb8zBvwI7BfrEbDH8uCHiwu2oyqhXHjb1aGdTBXptXsRV66/seu4RQDJ8AFUlEs45VoxfniUt3r21RdXrgMKIy9iY9NtpVcz33GDfnwS727SgzxYPyMJ0SEXewNJvUwqHIHBlzD4dQH20Q634caKPpGXHELuLCpO5dQJ2DTprGMIj4nQkpRSY/qmpRiSlZe4B/KVjby9DMD3r80IH7p37qp/iVX/kVnjx5wn/33/13/Mk/+Sf5G3/jb/ywT/NDPf7Mn/kz/Ok//afnv58+fcpbb70Vpdul8IaXIAbYM2yNslUljzMT8MWN2O4ZEVxMeamxEFCKGmgsbOvjLjAOVz+CLTDii+CZoEuo1MxImtBVkDWwspHJJiZFycdPuVGN2sYoJGz/YC53fgm1i8WQ/Pvu/x4Hg8VrlYuSMAzkR7Y0ubfdD4Cu3vBp3Tc8qaOroEWRrZF6ZUnXPHrwGsfjA0gdU+c2s0CVxrL4iLKUnT51PFxBHSwIeJAfc1sfc2pn+vVKu8rkByt/79f+Lk/f/x5VjG9tz9m0+8zJtbrCNB05LAeurx/y6quv8eDRaxyvH5APcHp+4ul95cnzF9yfKy9OZ86l8+W3P2ArznuusoboxF0Dz80bd/nqSD1vJIHDzQ0Pbh/z/Nk9z1485Xt4oP38j/4o/+wf+78ihyN39/dYOQGJYp3rq2teffjYTbaSQu+0WrFhXhVw3OilqAq1Fi4FOg6DeMOvtYrVSm/e/chpRdV8xKO5ZW3C6G2ji49Cc3e/ilnYTfXqMnYV59UbdDftjeTWRU6eWzeaJWr1MXIOfxCNdqNvHrwHzbT3jpUeTXaFDvVcXK1YuwfdBtoSVjs0mYZrIgTJK9bjRSC2gD1Glj68QFr1/o00HDbBnQWV8Mipbkx2GYjb5kBQbQ3Bx85BMFgkgqqNiewXwVPFvc5DSo+KOxkOdsgI6hf4u0qi9ZifKd43sqgAJhaeXBk7J9mPOPFDZN0/dOBe15Wf+ImfAOCP/tE/yt/5O3+H/+K/+C/4V//Vf5Vt2/jggw9eyrq/+93v8slPfhKAT37yk/ztv/23X3q+wToZP/O7PQ6HA4eQVl8+RmZ7mRnPNHQEceGlsm40BXYi88WNiix3b37sJVU4f4aZwo5fjxNVY6r4eC8OQ4/f99mGRii0NAJuLBqLkj6ZkOj+3i5A6x1KG94GMNSADkkkkrS9whgRPgHbxWEm/jUNLvbIkBBmxhA1t2/8gW2Lb0gTRUypBZatc26VrO5RbQJdBkfag0PK4rj/WJTifYLlsFC3wqLKclg4PrjhxZMT73zwLp8rn6Q8uee7b7/Nd5+9C9cLdXGrTi9PldUyd8AH9cQH58p3n73g4YOn5HxgwzhVuC+N5/dn7rfmzdy0cj518nKkyep0xCifW++Bx0KRyqNHj3hw+yrL4Yp3nz7nnXfe8ar+sPDWq6/zx37iC6yHA3e18vVvfZPHD448fvgaD+Sa9eoKUQ8OvVSqepY36akXkAWADliD7kpXCB767pXe1e1bMaNshVpOlFIotYIJSRwOaubzMNswbopMVfDslfDS6AG5TeZqZKNuZ+b0wNEYFMNZIMEgsZFFBpbdA+d2qmtzppQ5bt27od0rxt56WDzYFKHYLD4i645DrUVmrzGHcbCzIi8n2Zjss2f8l7jzmKTuOHVk+6L+eYJRNRAZh6p2CLKNCTsBc41MuF94Z7+UHJoLcppEsA7jtTHIfe8a7PL4kdHPOPO7Pe8PePz/LMDpvXM+n/mjf/SPsiwL//P//D/zi7/4iwB86Utf4mtf+xpf/OIXAfjiF7/In/2zf5a3336bN954A4C//tf/Og8fPuQLX/jCD//aJiGp9jtneFMB3SGN8R0PlBrWiwOGiN+/7PQy8Cbxgmpk20bMLvQp6yZ9KhCHmsp/7eL01QiQuLevZUOSwyLjz3iXmjI6aqmoHlLKCFEGG4xZdj1ez2Jhmo3WrM3nlCQhtInRbCNLwg8KUfclNgHJcXiFQZPJ5u+jGym5b3Ba4uDJwnpM9KqI3rBmpdcTpRUWOcQhl6dNrGF+AGSfbFN6Ix/cxCh3ZZHMK7e3nLbnvP/sKaVXrq8yr33iTfKjI995/9uct04+HlwJKIktbm9G2Brc39/z9PmZfAixTYzhMk2saaWSWDRRtFE6SIrsKyk5J5blitNWuTocee0Tb5L0ihd393zjm99gM+OP/eE/zKuvvMaPvfVZ2unEe88/4O3f/hJPXzzn2eme890jro63zljJmVGBd/HgY9YceugdFUOsBh8IMIWUZ7BpISKxGBWmkpyjDhEQnMnTW92xWl0huXir2z69qVBoXdDk08dNgvKXFO2Gz/fxYN1i3dRoWNbYR/VcSGM2a6j7bHOPeJr5BB5xoy9p7rGNpehiuoeNhp2wiNNiZWDcRCY/qbadVlwMV0sLg6bRAO0uaJOLMWHDakKEWt35xQIyGaPn1E9CKt31CCrhDe4mXs5KitFkfuEJCgHhI3qR3MnkZu+9MplN3HFATuJBgOhtqF/jT++dJS+QbM459QTi/yCo5M/8mT/Dv/gv/ot89rOf5dmzZ/zFv/gX+V/+l/+Fv/bX/hqPHj3i3/g3/g3+9J/+07z66qs8fPiQf+vf+rf44he/yM///M8D8C/8C/8CX/jCF/jX/rV/jf/sP/vP+M53vsO/9+/9e/ypP/WnfteM+gc9Rpd2PMQsWBI7biuRou4ufiMTDzbIfIJd4DCAh8umgWG7UY3sUIgHcSZ+PBkrowoIYQuzKhjva2RhzKnVXjqnqWIcC2ZAJ60TFCIvq1OwU+BDp7XiakoMU0Pr4J/KnH7j7803kAsixbndsRxLK2ytoF1Rcy6v7OgQOfsAimqV83bPVk5cceOBnoakxQNFdVbKwuKlJo5ZqjqNMWliWReubx5wbme+8s2v84/93M/w4z/9U5z6Pc9/+RlP332HdLWiqu5dEqq+2rxsNfCNnipdDvPe9ubBycSnxCOZ66trN8EatqW6ktYDW+mUc6GcO9/83td5cneHqPILX/hj/GP/xD+BAN/97nd4+3vf4Xm5Jx8PvPfsCVupvPHKa5xL4erq4PAIjh8D0zbAb0u/SLpt0uSkx72RARsE80RcUFN7x3r1gzlllsOKaKaWjVqrl/oiI46Hr3UfuyKCj0MiA9br2MTBJWiUI9i4KIjZGGwxSs26eTBE6KV7o7LieyEEPDJYHUNNXPGeRwRrGRm0uZBn7Ik2IBIkGomdTlBlLQ4uc5l9ij7NEPQM6uAY5tDNYDQjbW8MD6plb52W3Lsnou08BGYXKbJsZYxq83V72aAaZlKxWec+FEkIcb9kZ6iMmz8Cv6+TUSBfioF+8OOHCtxvv/02//q//q/z7W9/m0ePHvFzP/dz/LW/9tf45//5fx6A//w//89RVX7xF3+R8/nMH//jf5z/8r/8L+fvp5T4H/6H/4F/89/8N/niF7/Izc0Nf/JP/kn+o//oP/ph3sZ8/CPPJ5tYCTAv5/5LI9BGLn4ZpCNXZpjEjIDf5eVX88Ab+JunTswmRDzFCPK+KZgLYDRLBqyABpk/VruIkAh60eXrARYLKbqlOy0K5kEwyjtHUvwQ0KwuuzdxVWXF5e4x+Nd9uQVRzzfOZeNcXZBySNmzqhgYLANSEefv3p1ecFvOOPfbh/z2aIu1VulitNrQY3Tm1UtXJXNIkErm+OCKQ73i2+98jze++Zirz77Ja2+8yeOv/wO+8d73eP78GaywXh2RdCStK6smyv15Zkxb6TQ7uzIQpVoOlaBz3qseIJ0pzVkT5+bfM01stVOrsr37xFWE5tnbO++/w7e+/lWefPCE75anPHr9VT53+yb39/c8P585nDf0tHFfN65zjk3J9BgxPHhnuPBG8TXXI5Okt/AiiWNYIhm4ZHWoM08WjKaLZ9y4r4oQ8xdV/Pwdqjw8OPbYD64W9Ix1SLRn8BCblMDmRjWTEdKHErJCLw2RNCsE9393LLpHg3K4Xkq4CdJiraFY8SEME4KIAIu5FH7aiZh6NWJ+6Fr1KlSFvZIbMAv7gTeTLRNvwHanCDPEM+wwaMeNrkbD0sz7CghRuVxMExoy+yinBiHLRoU9Qs7MrN2FUZKLenpk3maQ8Wp5vBclemD/R/G4/8Jf+Au/5/ePxyN/7s/9Of7cn/tz/8if+dznPsdf+St/5Yd52X/kw7PaC4LQRTmyZ9fMQL1HwYH7jgg+mB+Od+0nQmSzyb2Bx0JxeHwEZAvPafYO8ngvH2JbmllkqjaHnZpcBPDpLBZQhihqOiuIFBBPM6GJXOBnsmcLI3B71I73K9OdbQQN38QSG8orAx3BRIyyVZq5MhERdHVKXb2vnHsFhWYVxLPzu9PzeE73AxkZeg9IqQ31qXiQ0ICZlrzAvbDkhauba57XjS99/cv89JsP+ZHHb/GZH/083/zOt3jjtVd5dv+Mrz95h2oNinBz+4jr68Tpg2eYqmdtgI/gGtcnDtP4bKfTmdY3qmQP6CFkqpbp8zzMCELpwi9/+2u82zcOjx7wBz77WV59+AqnWvhf/+E/5NkHH/CZx6/y/Lrw6HggLcs80JnZmGGtOot4bswPZ1fmAYoUWbkiVv0z9I6EQ2PvrlJtrVNroZZCrTXG/KYo8GVWaNpdNGXhUWyTt23zZx0bj8AkzrX2STiR9UbAGhmvmTN2aEbqYWVaw2ys7/uBFuuy74E1RSk6zcrawM1trwLH2hRwZTQehGOw70xWalAim8zgPSz5PegShnIurkrjdYNSOLLg3iwEUhI9hv2Qm1dq9IJmESN7AnjRt/A7GROyVALff7m/Rh/Kzb3C8d6NTeHdR3l8rE2mRoSdMTkaYBM7jgDtjTGbC2ME9XHxBdlP0/Fk81rvwRCNbFn34G0Xp7zFqT1OXlV3sPO3JjG/wchL9uewOO27N440R6Ytezk9GSaB7zEyEh3+yV7yi0ar6eJw8vcMVrqbC+F4o0+9FrSJS+VhZk4Si7FGMwaBZXXVYz/5sIPlavXGU20IHnDX40rpFbEch6kvUst+SNVe0J7QZc86exxGaVEWEgdbOdcDz+od5/M99M7jBw95uF7xqYeP+fRP/CR/56u/xa9+4xtstfD++++T1yPL4YpeK+u6uGglr/S0hrLUp7rcF+N8juHHQ/Y2rpXFQYkEOyG8spvQFL7+3ru83uEftK9iX/4yS155/70nqCbOGK999tM8evVV8pK9uRUHp8MN1bHhkY3OOi/gG6B1I0lD5SK7E5sGRs0i+LdCq4XaKrUM6Xt8GiHMqFwqO2A36RfZoMWa7cFyYATIEaCiWSvOzmit7U3JMaIs5O1S4/m6XHC37aW5kyOPoHlmLSKOl0t8jf13XLCzwxTWRpURX+8BgwYEM4yogBn8x+3s1cVN6TJ5CiilDV8VmBbLItBbne9dgmE272HcE7FdOXnJDLqMFeOgEzwlb63Nw2vEnVF1D7z7kmb4UR8f78A9yiK5QHgj6/NvD8wpgt7F5JdxsffAfpmW7w1Kf0qbwf1SoSgifnoOBkkIT3aIujuzYwhbZhnn3sEdz2qSpnnSD8ns5dk7bvTIvsekHgJz9gAPlphz7LzmZGbBMnDAEdAj45ao+UTFjfHVWSCGZyKaldqqT3JPiXzI1L7RrZKW8KsI066UdQZDP8A8s+v4Rky9I7L44ZqinA3nPFUhibAsmVMTaq9gcPv4Ee9sT3nx9omvPv0u75ZtSrVRuD8XTDrXNw+4uX3I3f3GZhrDfqN53o1aO5hOC9TLK+x+08ygaZojgAupC4sl3nnyhPeevM/x6hjLRznkhTc++Wlef/iajzobFVcwCywcDCOChxLQXxHz9ZACcnLqnsMQSWPQgyhWCzUEM0rbNVPS6ToG2sY6V/98ag55+BCB5vMWGf2XGLHVfcp87R7sW5gzNZJTEI1dgWg7ljw9RRgQjMMnSRN98wx5MEucYrr3m3rtMVU99tswZoM9aIdP/KRL4n2U3t3Yy7jAtNvItfx5+lzgMgOuxXV2pSf4sIV4P8FeGZm39aHgtNnbGoG1mzc6PZEafQBDl4CVzGaV4rHh4sAYu1t8bfjPiA96njRkfiiTqY914B5Z9qUqjUuY5AI6mcFdHF+SIe+TgQd6cL+EXXYoZb/oM0sff5U4RYH5/4Gfqbx8I8YkDpVlNjt0HAjGRSi5fA9xcMQ33djmYjNZHBoDZ7OLd6I4Zj3ceBQvLUe53AyVFFCJRMXuwVZUkNXfb1cv7qs1kihZhbQIp9NGa8rd6QU8gcf1TTBFJc2uvBH4tiqtKGQXLRjEoeYNVNRISciHRK7KiYKJ8cYnPsn11Q2tnXh2uqdVF/TU4vfBosH34sULnr2484HLPbylRd3XPP4Noym0450WwwkMbwg2SbgwJdYKSkorSY2tFratYkl4cMj85Oc/z498+jMgyXnWuh+6zQYlDbdhVc+ErbfI1jp+djlrZ9LNxBWUPe5xib5C7yN99TXuGZv6+DZNk16mqmhMsne+sGEtzP6x6TsjI9O20cx0P+s+mUoeGAWw2mfWiFkM5LCJYXsjbw/WZhZsmhCmhEzdP6N69nwhVNE4XlpxnjXd2Sm9uI92K8HKGO9rQBfCbIK6j/pIGPwgqNKmqrPX0Sz2JMW1UXtZkDRP6KO3RtLsuH9v0SfaabvToldcRTTBkChi3CYlmqQq7ls+p+loWF/E7YyDYJ9h+dEeH+vADcwy0P9xgS/LaBTuWeAI704zEiZFwjQ42INZsgf/cWJfQiGjCdQHVCPq9MCLn3vpPY7T+4IqNN7vJTpz6dk8FuDl7ws466QPgYHs2cTA+caLhlhg4vEpsAndsxySRBYU8n0Jj48QGBDc9Y7j3iI+TSQtiavrI60Kz5+eqNU4b8r96QW2QFMlHZeYZr7P2+vdbVGt5xBgRFMrrpeG7Ph6OUDy4G4JHj9+he988yucrjqbhbmU4tS+qBq8xE/hCjeu9+5BAzIz6wEj9YtAjnjQwvZSWYENeFLuuTpe8fjhQxZNpOuVz3zqU/zoW2+RDyvKEpdcgimyH6r0xp5B7jJ2a4XOJc45srnqH5qwA41aPom58eQFzt27845zVhjS71jfCQ/EY4jD8NnokSGoumAFHJ92OnRAAORopHlQa9153Gpj3Jl5b0TV3S5FQmG5Z5miOq2OR5HXq7v3qTktz0JkNJIIcF64qjhdD5kHgZh676Re7i1/5oifJEk+kWjsH/bRZS2kmj0CrbBDSL7Qaux7AhMfEIqvzyXnXXxzUTkPW2m5gEgvq85LWHb2pGQX5oz7NdfLR3x8rAO3dYWcLnwBLPwGQlwTPOzRvIMRvEemHdn3SJ8t2A4pur7DsGrAHzPCekBLkmm90Wlo1ovAHuwJQFIwUsSbQ86J9RJUGeXdaIqOVR48WfNF3NuFiMW8BM4puWlO87LLE5AI8AMkj7LUm5ORVRcLLxEZRGPfFGKodFSgbg1ZEosYq2SOuiLdyKbRPnM8/dHtNSnBk+d3nMvmB1MyNEPKwRFPjjOOQFD7fr2te6npvdOOLJlFV86y+WxLcWukNz75Sb702/+AH/3UaxyOV7x/V/jtb3ywH6YEbj10yhfVi3gt/H0lTb8oZcdDxTzzNM+MKr62ki7cXh25efCAVx8+4NHjx3zijTc4HK9Y8+KDpoMG56IVw3qBVp3XDNMUyiuturMyAFH3K08x/5DIwlUTkg5Yb7TqNrYIF0MIuh8GjIZklPTqKlAPJDrhNyxgreRBvRrIBW+2mYZda58Ws23z4aVmRt0atnmuqKK0c/UMsvgsxjZENhADC0KRWW2Kbmrt5ORVY4ssWILBI+Zwpl0wO8QcH/dA598f2bv6pqAGnDGTH9ux8dodSuthQTHe21AUj0XRAoMf+2dUidZsjoobB0SL6qq3xiKJ3gMqckUPIuoNXHHZ+9Bs1FZZsveHevMkLucccNRHDnvAxz1wD2AS+D78WvZABh8KavKhCzWhkuGBOrJs3Rf2eE7dA7Spodk52BYeH6ISnGiCtyzzlz25N5qM8ktnlj1O7stm5/hsHsv3wHOJASZNFxN4LDJQPKsWYgHjgb+DJZnm9o6Vjukc7EwCOrVXkiRs8c+Rc/Ip9RFsF1W6wcNlQdaV59vJfUxyRnKeWHsf/zOHB6QJqftk7dabT4XPmdScoZCSstqB+/tnqDim+9Zbb5EPsJXCK69/mjt7isiT3elNRwZ/oYAbuPVcEmlWGmPCzGxUI1gMEBjQW+nO0T8cDrz62utcXx+4OV5xffuQ29tbjsdj+Cc7DOVK7FkAO9wQcvcd2hiVwIcrJKOVM01kToM3AkftLRqTHujVmh+yKqTsTn+kBGEdO/nCOP1urD2vqnooExWkgbjwp1maa8szevMBH8PIagTj+NNjpqSIzLVXS3PGBJFpi1FLnXTUFF7a3fBG51jPPfZx3BsnxXoyMdSUnkzp9DIRgTFBXgJi6MEIGSPWxmEzMt3ZoxrTbGJjzUbqyJYJLF69Ehm9HrPwEY/EbFA9B1/+0sjLK+MRJ+ZNRpDI2HX+ezQogTmY4aM8PtaB26/zyFgHln1xo77v52W/QTZgk9F5lnkz9sNgBOo+3fMcMriEG8O7WEZXeyyM+NdLB4T/o8VN1lkijyxqlMbMRTA71+wLa3zdQ6JXDqrl5c/KhRDEOXLsx4jMLGKILAZUMjy4HYo0am+c+hlLCY1GUzL3vUiHhXreePz4IQe7BvGDTJJSrUyJtB9ssbDVK5jaG7IopVU/JJbEuWyMK3e6v+frX/saP/ZTP8Wy+kDgnBe+8pWv8f7pNA9elcTWOnNc1Mi+41Z48I6GpIZqFWVvVCrVNHwvIvuKoHB9feT29hGPH96yLImb6xtub2+5evCIZT2Ql/VCYDOocB6QNXxBumjc74HT1rlehwpW6pnWncfrA409cNduWL1nqw2nqvtBn1LCC63q17h7BaSx7oY5kx/ODuuNwQwqjn/bXEM619OoiAalrw/DqKAi7pg1flCaQyTUyCC7oubQzkgOevPDWkhIeN84zOLKXffp9gr0ku5nAyMeniNdwsa2z+npl3uU4R5osZeaQcjnTaMCbX4wjBggIi9L3GOPjb03gnJrvh8uh1sg7P0pZPYoRhuMAbNcsEYkquecYz3Ow2JvVn/Ux8c6cA9sFvZgPcPTvg/9cfH3S1xzckcZGJTMDNRzKf9lif/vI0/S+RQzix9Y7TzlQ44+U5XIAFxAAMOoSpzwMDPu3psv8PG/yE7cotQ3ULNoYPEytu5ZhkSGPehGQFdPLEKYQLiV+bSboJ/F4utR5pbSXIYsFepCEiGLO+VhwkGVvHrwvbq5QZJQ+4aakcbBlbwqsKRY7hG0q4sfIitPSdlKc+w3uS1Ar8Lf+eVf5ne+/mVebHfktJDzSl7OLG0l5+qiGdMp/3dGSCLpOEyT+08Hdq2qlPCu6MTBhEvUPSiCpIXjeuBwvOL20SOOx2sePrwlJeX29iGPHr/C8eqKlPO0AR2l8zjOO55xafbtJW3HuS//+NCB4iIacYVq0o7VRu2dVgrn83M6CUkriy7RzPRFpmK0aPQm3Kvaz+Iao+XCf7p36ijj1Q2OZkUS77rZML+KHk9StBHrEIfcLvcQxFSbwIr7EHI5VNDtAtKYjUpxWb7swVJGPyn2VN98Go+YTjzbp/y0PfNveJLgrPfBDfQDo+9pq8Uh07HJ8TYZ2b2heYE+d+3u8mcO+QxmlN8b5mu4sV2HpNBfHvFrEU2mk2PoIvzjxSF+kRleJmi/f1glOhqQMrHsiXP9Lhm338mRXStCYphHS6iZPFtyL40ZnGNCzJzRqJ5RoSDZJ8aIQhO/SQMXt1AhjqWRdbAtooTrPWBtjVK/oiluuPaXqIfWG5Jig11kSaLDihMvyYd1S3Pe68CwGfJqJxO6NL2Hx4oZdSv02ihlo/aCLL7JrHVMoIQdKJZZkgtmyrmxlcq5Fuh3fOITV2i65ng40rTEbEsgj0y+c/fiBdvTM007V7dX6Ko8OT0hHzMpJ+7rPcfDkbwq9x8849d+/ddYHxx47ROv8OjVV7l5ZCxPX3D90C0AmiXOtXG3dY7XDzgcjp7lmswZnrUZpRpFDnTUlZMsPmRYE2hG0kI+3IBmdFl59MprPHz1DY7Xt0haMessScnrwT1kVKml+CzNRSPzasEk8l6JaCZnZYn5INYKtXigT8Bh6ZitFw3LjdPzJ5zunrKdziBKPhzRfCBrAnIEbSVrds8RcBvayPREogloQuuFNjL3CBfW+1RI9pGdR5PWJOhpKh5AW6MXmxnxcAmkgRVXVmoTrAS9tUn0XTyAWzXWZSVbQorj2tUa0sOCNTn7JEma2HGrfVYRrbrH65IzvUbl2TWoeeIzVbcah0PAXECtJcQ2XpFZDXaIKj2y32kla+PgdasKG69DIy/ZhU3dPVnA07o5ECMYWL71AraDUIA6Lq95HJADHrPdbVAA2sTfe/voc94/3oF7ghNjksj3E9nHz8wO7/j6S6XRh76GzDPRggkyzeIHPDNgDvZkXkVirvDFiTpKKiKjD5TGT3bPFlxlGNxfiRs8MmCJjNl2FsQ4sednDbyaSzqRA577Z1YQS+6tEqiKJN90yH7I1F69yZIF7QaiIdoZSk6ZPOX1eCCvB3It3NcTqLGVM1oXZLmgLFaoFKoVatso7YxI5ny6Z5GFrZ7ZToWrB9c+3iwJtze3vPPsHboZH7z/hNIrn/7s57lZr9DDFe2dZ6ALtRtXkrmVhdI6KWdIC1UyqTuzpDRDmqCW6OYqwyv1wD0OQl2vSOuBqwcPuX34CjePXuNwfYtJRvLimZwIKSx4/V6n2UQEvFmuseYGQyiazEJjaD8cJghgFUHEBxdXkcktTtnthH3oRfg+M8r3hCZlkURt+2CFHp/FrPt7uVgKozFpKXtDMcr8WXyKMCwWBv47s067YIDUAaN0ejEP+pGAaFSV2tPcK4oH7Ohnz0pURJDu17INqKQPePFS0t6Czhg4On5wSEr++p3dEXP29r1qHK8zP0PHG+vxuXv4rww0Ucb1iP01fHY8ORojJi6eo3Y0r2BjWpDDNm0C206NNRu+KeCiq7AWmAeIX/sfwmPq4x24YaAPl0H5MlBf/mD8nDC/z8CkLr8XPtjgG2zcpKGISqK7JaPspeaATJwWNG4x4SAYUIcRmKPsykshkGq3nTT1DdZbp4lnJchYaH3CJhPTBxjTceTiZB+LIOGWm+KBWroE5uwsa1GmKs6pgAFVdEPVr2tvPvoqJ5dt55SdkqCdw3pkYeUqPyDnzOG4kHJUH7H5JPvhmiSx5oXUhSqdSuXudMfz5885PLjiOvlU9lZPpHTNgwe31Fb4qZ/5Kf7xL/4TmCTeffIB7z/9Bo8ePqR2OG0NWa4orbOIomklHR+QlsMMyqcKpXa3ez0XEpmr6wek9chWKixX3D56heP1LSkfSIcHpOVIzgcqznhIKbvxk/piMmtoGvxoPzOHrW+YB7zUHEtYzOv0tTVFVODVXlOkCiULHA/0lqnVG5M+H/JMTx1Jq9vlxnzIWkusLaE2X0mtS6xjmV7Xqhr0SJs2CyMUtXguNwW7aJZFFJ+9IVNaryQTRBOaPOMmhX9O9QbeGJ6Qhptl969hHsjR0QB0qp7zo2O/zOTIH716j2Q2ISvTKK2L75NBw9QBLl883BdlD+CtBkRn4cwX+4q2O2uCN5NbbXQRZ0i1/TpqzJ7sNdg+qvNgb90rFU1KzoyT4IIiegGT9U6XRkpLfP7fJxi32T7oYJgC4QnOFKrAgFK+//dnM1J2jxEuDwKzGQydeuQLLC0pMu4wqgn3v+mzrRJuf55RSygQh/vOkDIzGpo2PEJ8EeUBd5gHVMex2b3HRyQ3AnhxWEVV9glOApIFO7mKwjOT7lLgJNC7O9m1gGEckPTgLSC4PFjNIHnTrfVGD4rXuiz4Txl5OZJuDvQl0XB8W5cwPloEpuw9eJQUajnTto3n9Z7T6R5TY7nPvPLK69iDhZSPPLh+FVXlp7/wk3z6s28BmePNA0pX/t6vfonbB7c8fO1V34wpUSSRl2sOVzes6xVdEpIXNkuYJd5/dsfduZGWlePNLXk5splDI8vhiOajY+K6gGZM/T6ZzEmjHsTFexfdfEL82PAmLTLiuODm+VmEJD+w8wEZU2hiHbZ69oS0G8fjDa0euLt7Bv1MiTmNSRdyWiDlqNIqtVRabUhKWFBge29Yv7Qj9ck2NoLmYHZg0Qfwz5VUqS2orCVELyhiPcC+yKBVsSIxdCNk+w16i+EAzRORnLJn2NWrNhousInMOqkf5OCZq+C9noFFt9rDAlaDbWHTz9srYM+PdG5aowZDRM2HGXiDM0atRWbt14gQNRWyJtqgcUbyljRFouYQUBvwyaB9RPbuWY/tTebZmNadYRMy+QVhq9Urp1DTtm7x/octwkenlXy8A/fAigOCuORNTGrOhyL2JTQCI/MeUEb8vJlnVxfZu2kwAQJSUE1eFqcdntHYABa+KA2bz9d7cLHH+x7PPTii+EEwVWjibIXendlhyaLxNN6Liy56L565m+N1IrIPAzbCyzs+U48APlZ8j88jTgFrvflhEp+BFBvEvBxtrbFVX2w6uLh9w5JAV66urpDD6oOBRXZL2xQDcaV7s7M3WjuxNc8Yt1pJVjgerrh9eMuz+zt+7R/8Ku8+f4+0HPi//9/+Ch+88x3e/Mzn+c67T/nyt9/mn/ynf4Ff+43fpJ3v+ORbn3dmCEqXjAQMkpYDthw5SKJ3JV8/5lwqSCKvR3o6cjR1iXvOkXlm0AiEqtG83J0bXRtgsyqz8IDx/vROR+RijX3fY0BfZiQHjuNeCdApbcPKidYqtZmz/aL5rOZimR5MD5ELSGoc5rY3tT3B3/fAh/nrJgSGq7HeguYXkMEI+HMthyCm904eIqFw4NvxYTzIxs/ahepzJECDzudNypcz2rq1WTF7/z4y9nFpW/SShq3rjHe75cBUSwbDZRhbWeztsbfmoJzoA+zOnZexYwhpdsrlrH4NtxoeTc74HY0pO15l7ba1YwHU6rTAUbF3s8n5/yiPj3Xg/j76zIeC9SXefRnI/caMSzbRbP8TcAlDpKI7DDMXU8Ask0Y3KFCXmPJY/Nkz4vm7sWkHlhZDcoLnDO5b0fbDSIYk1heB7GYj3u0ejdhBbwyP7RG8JctLEvnBNsHiV5J/fjfZb9GwDNpWB5FE1sAjkz9Xo1N6YdEc8vVK62evLBLoouiyYNl8hWnIrxF6rW50nxO9nehnIx2Vh49e4bVX3uSdD77Dl772W7R65vWHN5je8O6Td/ny17/B9cM3eXh4hc996oqvffnL/DP/1D/Ll776Ozx97wNeeeV1OgtNk2MzmrF8gJRdgq/KIR+R5IMDyEdEMiLZjbqi+ZeCJjjk7zIy5YHLqsvkk+yCjX3djeU0slH/dhbPwv3+Dhhr97fw8WAd7Y1z2djOL9jK2cvw5YplXcnLSsox2COw2RRJQ+ueEzvO7ZCcWbBAXzpBLgihAbWN9eyWvCkob77ufHJMrEHwwxyZlR/4dXH14z5MQC2gE2H33Lbdh2cqfWtclxr4b+DgIuKy/WgGDT71JQvFmnmjMV61R9Pzcq87puyvMZwOLSrbQW3s4ll1DQYIaqR1t3RuvZFCketUv4vDecJj6pYGFnNmCTaaXRh3tRbBPRrJZvM+jOZk679PMu5L7vZL0veLx6Viav5e/HfGdXEM1oLfO5d3NDUkMp5mjX26u80nGnTA0ekRcOYJgWGPQQqMY2JkR7Hhk3+NcIfzrGA8t72UyY2XaSNzEccJBRncxR1/V5vSckl79T4aLj4r0MYq88w/uOqGZ+ORekQAS/6ZgNKqbyCFQ84sh4QFywac8qf4oARZdlx9kWhcJlj7PfcJbq8ecfvoNb73/tv81lf+Pstx5Y03Ps2yLrA2Hr564xj08ZaK8trDT7C9+z1+4zd/jS/8kT/Gb/3Ob/P+O+/xyqtvoBqBOB9pFupYFNJK1oUuQmnmTUNxZWQX8Uw9mtwYIUoZIIc42wQY2PFYB1Hy+U+Nezz/HRlrTDDyqzqm0IPG31Rcudp6pdYNM3O2ynoAPZLWAyl4xM2gtkopzQO2uZ1t7cOzKcLG922IfU33EbRlGJYNpzsiCPYZYIe3hqrQyp7c6Kg8kvPVrYwJ834B+pgVGUF2YPqjn+LugOJDJIz4epjN9rA5NrdesOqdT01pBsIcVMt2digwkQLS8b2lKF1sqhQHhuxVpUwOtgbE5OsgsugeXkOhnPSvdyzonykFRIJNlo7Dqjoz9snpHwkTUckO64Fu7ug5D3qb048+yuNjHbjHYyyKy4bd95WQF18bPD8vd4PzB3j51LwBZfuiHxzOS1ntS3lMuOK5St4mjU/VPRIcmhhwCm7aFPi1Mk5sYVCDbPgt4GKdhkMlrfXpNSEy3q/T9UwTKi+f2B6wHYNkwDx7KhYMloq1zrYVF1sEbj8aqqYBsYhjl+4i4VSs1jwbcUalC286kJOSluQqUXNcU3PQvmJMV26JdTmi6Tmvv/FpzmXjt7/+G+S8crPcOKVKjQdXN7x++xqkhfN2hx2uoNzz6OFrFJwH/fkf+ylq/y1evHjGg0ev0XTxYP1hk6+U0CjdJe66f64I0pFp1hhjwchI42CXAFbHtYeROIwsKoJ23yuyD9+PSyiDMKIqZYPuVJ+cBAsZdDOnCtOrM0bEvbp7a1g01qxVShVqh9ojGGqOwQopKrQ4f9EJffWUGH2SlJQaMySTOgtivEc1N6qaIF/4V9OdqSPmh7eF7F8GPGIegCe00owcB5oF5zs4rDsPGyILZwb48f4xmQnYsJcd9wuYqt9hveqyfq9kvB+xw0rp0gIAAh4almgRS7uv3SR7fBiBebwPCYsKi3s7ki7/9R3zdqHT5TF6AUlxEad+T3zt5cdHZ3z/n/AxBnd9+HEZvC+VUACDjjNK11i7jLmNEPhh0H92aCSaDoZjv8rkb48SUD8M3XwYX1cYU1D2LJdYQLtk1gC1KK2iOVnayMh9tozF8xvErJmLCiSw93ktAlsfhkMzq44L0K1TWwvsubnaLC7TkMA3nMtarFKtgwrLYUGWRFpW0mFFl0w+LEjO5DWzHlYOxyPLuvrGSEJaMut64HCzcH284Xh9RVLh229/BRO4ffCQs5zZ6h2J6tBLbMTWhZUFacJVviKx8O7T98EaP/5jP4ktCyXEQxoyfQgGhDrrRtIS48XGdciktJfGg8ssyalcL0nVJU2IoM+ts7u62biXdomp4tY0SPzRix3s93tJbs+a00JKmSUvHNbMIScPJq3R6uYwU92w1pzz23a1bO+dWiul+hDh2kd1qN4I1ETWNKG12VA1g3FQ9WiGB3ac4meSJug2g9bgNo/roibBxfYsNUnyID6yes9oPPDhHjtJ4r1EjjAMqRgwiPXJCKF59t9b89/V5PCMubd9GgMgwsFwHlbjNce+sIBxInKM5Gncs5cgFggBkEy4RSLh2n1mjLwspCWFP1H0si4hqHnouR/PmACvob8Y/5uT7T/i42OfcV9m2jt+DaN0Hf+1yHT8/o1zNRpm4V8so2whBAeBoDESc0dS/HlUL17DT+PJuR7ICR5Ax4Ewgug4EUzH8F9vXuR4b3108mWHTD6cvY0Tev/cvATfmBmSdJ+CrSPnYiSLwXzxbMkTRfOMPmTpGkEptrq/xuY0xdYVS4nlcGC5OpIPR5Zj9qG1a6bH0Im0JDfaSh1L3uV3VsCR2hvX/QHvP/seL+6e8+YnP0Vt92QyXZ2PMbG/2iHjfibLNad65vr4iGfvvMfpfuP11z/Fj3zqc7zz9vd8UUtkXn0wKjyTVlUXvJlg5LhfO4btzSS/gSZCv9giEvfZry9EpKFH83Ke07Mi0uhL+H1KceiGy7Qf4uLXHWDME0UtvKaNXhseP3IwfpwlonTnC8vFgT3fl0MeEm6LXXxGjo2QNVR9mhlVXsdtDFoJ//B+kXSMfWSwLAu2OWfcmRNjfcs0dxoqXun4lJsBicCUsHvRIiB20bdhyt4lJujQmW6N0mP/dD/oiIBvZlEpzHfi/Rob0M4+jWbJzgjrbdyvWGNDA2B+QKgM+COubxiADSW0Jq/onO3bp0BnhukBmcAMzN36pCAaPYREngz61KjfJxj3eHwYJhmNP8+GwC/l5UUJlVNs2hnHZ1DHg/QI7gwS/54svZTVR1bXghroU819haXYiG6NKky+Ezs+an0fWmRGOA52LI0ys83sd6g3LTCxFupRYPJz9+ePzzFM4gMimRshCe1U3aVNvFHTrNHG5VLPdrOGZ3dkRYqb/qAdEi6GiEMtZQV1ds1LQybEN5RmJVnCrCGLsKSF9959j/Vw7cRGaz4QN+AW1ZXD4ZpT3UCMYolVPMg1No6Ha+5fnPhm+SZvfPrHOTx5MlVwHecal61ipODEDyz34t4HXGWkCzhjMDC8Gam0YNtoYNN7kBz/2PsW46AmSvBdvDHLYuekQavzNROd0t22tdZCrU7JbN17JS3gEwFq4NomnWqLw2ijxyIyHSrncGkTfIjtsExwTLrgjTPRRNJMkwEp+LrZJ7T7AZM102jBne4kc/OuFtkwI1g3C8jF4RkakPznpF6s0B5Vq+n0zB4Z87BeyKL0Fm2JcWHBlZUBlyhK14BXZIdoRhN0JD7LsoSRVpt4NHFfBgRqtZMPKaqYRl40Dnz3/JZYf5hNDrf1GPRwIYocr19rowa3e5pXmfvAqI0Y8P3J2e/1+FgH7lHGuql6MBcU+tgMWAhJws9i4I7WcSfAzlSfDpc8ywQzaj72oC17Odyb+1XjHWVJhFl+4F5B/5t4izqjFlFMgzpk5licWZRjzj1lTskoLjLIglj1TFy8USPCtH6dmfYYCzXfs02PYovggezNJzVzSmHg70m8qdW7G01JkMJFlEwcUqvPY/QFfHC8sPeYhxmQT1c0ewk8XuslTEvxaSTmB9qLFy94/fFjWtvoklhSci8QWRDp5EU56BVbF7I0rDZSdq6uiHJ1vOFr3/sWdCGvR1p3vN2sIrrS7exKwqhSsmbOMUlcNIyODETd70O6Xwe17vCIRiDAIaw5/YQh6NorHmFniYjKHJbg2VV1t79uzuWOTFzwlmVrhekdimd1zZw90sfzq1KqC09qbTR1eXupja0ZktzCQDG6ZMB56SkgGxVlSc4EOdXgfNeQdGuH6hg5UiduO7up5nBbjWy2dSbDZViXttL89zGwaJwHPNd7j+ELfc+4iew/hgZLcKw1K1J88o/1GPPVYDI3unvgDCaUb3eD5pPo+6AZ1hrv1TisywzWbtR18XsAdUx9CmOpgDyEYHRhLEtiyQvNwkUxDkFnh+yZv6pbDYxhCtag1ogj6mtXQ/E5K64P9WR+z9j3kX/y/6SPvbu/n1iX0MHEsS8wrItf3heQgYfWlyL2fL6XXmOUZGnP8Gdwv/hZ4mcmRspw/5OYW+nz+lpsVvcw6PNdGPgGb51mLosmvibWwIQskMQmPU1MXpIYT6MeCcyv42WwOTa5l9bM3xUbDRgJrK9Ttsp23ihboRWPYlvdqFv1sm80ixxzuXgume+LeA8eCBzLrOdC1sxxPaI4DpslhZNbKFVbZ0nC1WEhJ8WsuW+IGFldBEMp/O+/+ve4e/6UrEaio/iUmTVnrBXoFbpfOz9Lu2fDFpBRq1iv4UvuB1HCrVQJeGJEMB1iqm7u+AdoUAAveb7uzrireEc1OOlm0Wz08jpHtj/gBGcwpJxJ2QdTDMpfC6aMkTmXxmmr1M2zdInDVlWY2gALiT4u+2/mh+9W+1SYjvdct/qhIQi2r6dRztue1QJT8Dbw7xTNTzP30249qs8JifjfW+u+Rm3fW4IfCOuyBBbuSN+YyD5+9hIqnPsU52+PBisBn+acWNbF2ToDqx8wiEn0ph1wTynFtfPq1MVCHmeWvIQ5mO+3bfMERyUz6IOuUrVJe6y1Rs9jDGCOaUka0v7oqQ03wo/y+Fhn3CP7HUFGAkIYSkmLMhhsQiODBeCJdyw6URgLblzQl/xY46HMrB5l72xHJi9KMDICjohepiQhHxYsOwRSzWf6DUm9DdFLbZhUTKpnP72SkrFYiaARCkfzwbJZamR4zfmkTYLEC1mzl569Q5NQSHoWJOGr3Uun3ze2u43tvuAKzsBg2zC6d6fCZDKlxefzRisdVeNuOfG4Cw/SgcMt7lF+DNrXyFhEHFJBMHV5v5pnTdTOg/WaB8cHPD+/oNWCACkJ7b5RDoXD0lhvVpIYuiirADnRaGz9jnV9xCduHvC/vfe/8tlnn+Txw0dYK+hyhVDJa0J6obZ7Oomuq/uJx0lTrGO9IpJ8SLAYEipId81zGGOc6Z7RdsYic/ihx6BgD+QpJZYssyJ0+foWB9x+CKsIXRfoBateVaErafFg2c1oDc6lcN4q96fNTbJMnasuiVP129zFB10gidpASoPsFVUxqGZUhNqgNeH+XNxHPK/U0iin4pz3YlC8KrJWY/34Pa21+ZzRuBx1K2QcN64t1lrtqK7QldoayRLlvqKLwx4D027NaGUkPjgDJPDrJEq1xhIUPDpuUAW+hmN/D78TVTdEa1mm6tMaYfJk5CVxfTw4jBMsrh5iB83CedtISybnTO+NWnuog70z0ErlcHXl+2j4hMd6aN0Npca93ayQNJqZtaFJ5hxPP7Q943ZfmjQHo7QLJtsPenysA/fl46VGZB+cSuLkJTIP2YM30YRCB9gdX7MdpBqP0ZxkQCAXJPw01IfNO+aqoN5sGA1Cohw3FVcZ+jNNG0kX4TTo1RuF6lk1g1caWbUgJLX44x9asT7pXgAAAQAASURBVMj0HPaR6jQtM7vo1MfnuTT7aY791eZMBJcjB2+1DVvKwP+6N5h8NKRfiDE+TEnOiNCMkr3c6zJnWEIsdMUXPYN1sQfCR7ePOJ8L1o1Fs2e7PTK1rbKdNnRZyIcI3jlNzLyJUwKFjkhnEfHqwzqtnlnXTDcf1tBaRcWw7uwOs0qTBfMR98iSyRp+jhbNJ5xiNoTrGt6iPrFlBO0LnHR833pIz0eC4Z/XxkSceG4fbFB9Y9cNJKNpzJm8mDfpq5OcE81CtSgaFEBokU2YJFejm83qykQCH/fP3cx8mHJrtO7QRystFIa4TL2CFaMXmzL1VjupMN+TNaNVn3hEZMIEg6Z1I0G4+kUDsLgNhJjL2PuY7m4OLeWUvM9SGznllyA2kTDairUzLS2CK29jokzy4R+tthC0+KixJWUUF+roSKwYiR5e1YTfz5zr2phK6GVdfUqTuK1Ea40l1pSv6mheCtRSfJjIiCuz8g8aqhvbMDUoGh2Q3y8Z93jMcn8ouywaGRKBOaLXCM/+s8x/OdvHf7cTAw6GZewQx8AFljxKO0gj0CNhNBPPGxNw/MVsng+qQk+jROo+KnBROsVxVZ+zffFO97EfDol41uyLoHlZHwIIWvOMxyxKNc9+ZjCNT+Iub939lBu0zWmArrfxTVo3n2t4OVlem3MTsuzDCFqU1oQbG4ERS2dvEkkEguEl3p3qWM+VF8+e87mf+TwvXtzz1W9+mXVdqKXDYmh1jxdNGUkOI+RFWdfsmKwIRxFq27i/f86qcFwXxDpL2mElFWXNia1WOkpS3ySlC0YBSXTnsgAtHARj9BRQ0RmQx0Op+/qL/0/Du9oEeqEMVMGGIKPtsFnv9F4Cnmj0urlSslcaTn3s4o0CE296axbHp7VRGt60NKdvtmB06MXr9d58TZDCb2V30cSgNodIWq3Uc/OKrXb3fqlK3/zw1u73leYHd6vuEjjhoGr01DwRMqB7JSmmk6nilgluLJUiCxJcjQue4OS8UGtlq21ClnOmaAS1OfQ3II6RlGHeMPfA6u8lSHwsqsxBJdZJHrmR7l4rgiEpT6dBv04F6IjkoP969aA+rYKU3aK59xINSvEqsDo7pDYf61ZKo7Y6DxuDMOLyIORNT40D/Xep8v8Rj4954LZ54wYsMjLqUZb4Q176+/cLI2BMtpZhFCWye3BD1GURTs3CIZBoOgX2RkAl8XeP8Tbhmx4YqaqGV/VgJxiiRlbHnTWyxjQtXnHhiI3srWJsmGx09eA9cONORxuECQoyOv2dKSm+PIh6GxaYacqSTbwUVlxo4WfTPkqLKXTIWDfOL+54fvWM61cfkfVASxVtvmmlBb99sHta0C6rZ/xjcb/1mc/yO1/7bcq5Uq26lWxW9L6y5ELKG0mVkoVlOaBLp5myKDSrvPPe29yuBx7d3iLmLOuknV43NC+kJEhwaA1QzcQ8Cb/fKoFx+xe9nNXQLtUZSD7MKDGLr43zO9ZarW4cNCTNzou2i4Z6o3WHXVo500qht7MPAg7qHprQnMhRcktzaKL1HlN6nHd+bmdqMx/vpQ4fJHP4z/N0z8S7pMC6cd8n2yjdqKVRt+ZrpDjUsARTxLwt4J+zK9Q2rWeHv4jj4l6xOVTnB3fWXZTSW1SGPYfroJeaIgNfBszXw5J9+PKgkThH3CZ3fNL8Qpk5RDc5ZdSEs509GGqPJIcdtw7oxcyD/3iqZBKMGl8hOad4rU5OgWtHT0Ojb1W2LRqKDiGWc6GGPN9bAe4pXmqZPQfwxGkyuyJJ7G2U3h/t8bEO3Lsy8gL+mNDjjmtfBvjL32U2N2LU1Qz2AauMnyXkvOO5JCCO4Hr6XrfgdsbNGa+v4hPWzaJUi9l1wYSxRAzo9lFOqXtDbBcvOAQgAaWI52PzHFL6VN0JXn72atHU2w+P1owUGLh15wdb3RVlS0pIGAM5pzXRS5vGVB1DozkkEpadkU333uitcro7sRrkdAj0SSFBV8IG1mh4dl+2jXIqSBeeP33Oz37hDX7kk5/i61/5Kvm4sJ0Kh6sDinL//J67uztuH9/wSB+yrtcsS0VlRXqjbYV33vsun3zjda4PKwWHApIECwdoZXMmQe30VvAZlN4sNhVUm1Pv8EANDgkYguiYLcng5sS1bzMlsFGXiF+w1qpT0y4SARgQkVdEvfm1sFLoZXNxTRiMSV7duQ5F1DDcUXDMJi21UbuwFXH5O8KiMPn2BMQlnhR44EjBfFCWxWme57I5pm1C21rg2kZt0ItXa9YtWEDuwa0dP+j9aGewraTZnAnZQwzTw3zJAts1I8aF7aP7Utpnr6qA5OwHHVDOBckuAhrzIht9Dr+ezUUc1hDztbkcFlJOXjlK94EWKbtVWLwHjfdtEBVNBhG2bUPU53/6gerD3vyMN4QUB7Pv4eHqV2ud64QxoFjCc7zH4FcukFksYlKntW3CaB/l8bEO3HsKPPCjPpEMb1gO/FFmZjVI8bCzTMaFHFYLgkzOaBRyjm8R3rzsgpV5MHTmZG2/oRY0MqNXnwYznlDCB6nFAdGAtVeSOoWwG86AkIpKGLrnRkp9f/7eQDvWGpVKagpVpuCkthqBWB1tqd1jJ4IVH9LbavfMtzMzSqeqQTI33iEqC2eoeDXRAms8LkrSTNIFqe51XFvHThvIgsP5zusepXtphWIbp9MzTneFJFec755y//wFX/z5f4Z33vlLtFMhZ/elKL3CSUn2AjF4JiAH5fHNG6R0JrPy7e99F7PC5z75Ix7gWiXJQiuVnJXSC0mUdVmo7cxWKgkfsdYseyOybjRZ/PN2oYv4lHaWiWOLCDlcIgdnOlafw2B4k7PVAt3Nn0YFJWoMCb7j3n6A9HKmnO/p1bNt1cXtCxA289K9BsXNxKf1EI6OW2vc1coWlZgaNHMoq3XxXowm/ywIIguaHMe33rm6Mpol7su9c40jcEtP9FYQS86BLkEDLI2FTDPQPqifDjcMJaaIf09EHCJojjuXcibnTO2VRRdXQWa3qE2ibuvgqTgpude1qGGR+QpODOjWyZJp1Q/HZVkmFVEiabs5XrFtxe13o9rL4gMmNAzkfBJ7dS61CKj3p0qrrOtKLX7w+n538sDueRIeKhYT5ompO20fBOxV3fAjD45AN+eCmw8L71HF90FSvxQ9/YDHxzpw7xp/f3R2CrbjzR+GUgyn/Hk4tuEnHLaRFtife3qw80MnMM5uzxqZ9WVjyqqLShxiCRxTYzQRYRd50RQhOKPjJmOQIwBI4F/WjTX7u/MSy6ERicZWlcYSFpc9mCPW4hTphpQI5p3JkXWJsfNQa2nBPvGFb92FHD2wTqsd6eal96APNl945+ojzopWyrEgAq04/7duowro47JTKZy3E+d2YqudY1Jqb3zvu0/4+7/2v/OH/vAf4h//+X+K//f/46+jXck9cWwHXn30KqcXb1O3yvLijvrsIe1xY5UDHzx7l6999e/z4299jtdeeZNT3VBJlLqR8kotZxcCOQ7AYUmctxOtgCZnm5gRRmDVD+/BoW9xas1s0BuAo2zejZosMNhOLZVSykuGQdPmYPQeosHWWmHbgmJZ/TodDkOfEHgobSpoRYRlye6sSOFcSlAvQYesP9aWByN/HhEv62T8iYbZsQY23ATqPX1zsVJvlV6aT0CKhnYPf5FeR1Pdm3ctuNkDZkvqQhrrxjE7i6OctlgTlXVxn24kRE+OZriNcvSkBqTRWiMnf8/buTCpgH3sXSZP3H2ujawxKSgqmwFNdeuk4OT3vhs6+TBwm3FDGIIj36sqaTp3Dh69b4EWrn8FouLX4HAPU7haK60Gm0TEvdODlmjgwrzqJIas+aJr8oMf//8RuMUbDBClrFlAuXYRYOdv7dll/IYH+T4X0+/2cNOeIR6Q+TULgG5AL9Z8MaAXr6Q7tOybDAoDVRFEnHOs4ko5RvbWCoJzQJ25VAPfxrMdKxjFx401JfUUWHbggSEHdvOfKHmb/7vVGJ3k69v5v6F4a8W9S3p3M3uC/qQwfSSSJGpt3rgSg2fw8LyRRLzpdY5Bxc2xaktGqWdKPYN0rtKRuhZSO/FgveVb3/wG333/O/yhL/xf+Cf/6X+Wv/v3fpmnTz7gzU9+mh/5zOd478snvvfiHc7P7sm3G7kIL158wP/227/Cq48e8rOf/UmKeSAzOllXSjkjmrG24VOCMmJCVm9odlYUpdSzH+Bq+BiI6uISB4wxzROjtlC9EdgkJmFCZbtfyLb5+tDRDAxM+OKwt+7TU2rdnOfbWgTbBXU7Soc3lgUhI4tT1AhHR5/CUnxdmmP2qplhaStpwXT/o7oieXXYRxIZ4dgyahm5EqggRbirsJVCChVpqz69fSzkFnTTwXSJwaa+1pvFRHsjoeHM5+OXWqsR4Mb+iv00fIFM0JxcVFPC49ACI4/fmAN4zX9fdVTW+DUbeojaQpnqmywNdWNzN0MZz2UuwBJkKiGFMEaLA3skVM6kAbMaB3n3qrwHH71G/ypg19ranJnZeyMll9NbNPE1xYzJwNFr73x0oORjHrjHY2wkv8PeOZag/g1caTaTIo9xukhspPgBwXxgQWCbKfBJNPoGl70DvTiBtYc3R/g2dAuKYPysCCYBc4gfLjP7HurKKL3EXAAyKXMK9ILIuMkgYfnk467j4IiZgFJjM/SGVUMtxWcfB47NYa6t+HDWVhy79KTUJjUseGWzuYQEP7u5p4mYsFGDgbPx/MkTjv2W1Bdf9Ksim8MEXbsHyOzGQLo4K+VmuUZy4lG64kW755f+5v+LT7/1Fj/3B/8w3/rm1/j062/wxqfe5INv/w4ffOsph9duua6Vr37963z527/F1c2Rn/3xnyXnhS7FvZObc7KzqnO0W6FZhZwxc+WgH26NpMK5dVSqy9nNN1xtjmlZcsNQiSprNBp3k6ZgJojQap2sgpQzeQpZd2fB0WHukY31WvdGpqZpazCoYq00jA7m5kq6JKQZS+4seUGlclwWNC/enEtOz4RxcDi8oilB8sDtykjlWBOZ7MN8N5DqzeTUlHKO9RMBdnq4x14zM4js2zCvTqz7AYBSW0ejiRmrLnB9Cz2BUw17sHV04r8yKxMXtHRsGz2H3YjJ93gMKwgaX0rhJx6fffzd7WCZ1fmoehAh5dHf8idWVdLEqSX2sNK7s0y8TzHGzfuh0KJX5LfJaa21RYLVHFjNOuAxo1XvH1g3liVjrbFthWW5DDC/9+NjHbhHo2ZQoEZFennjk/rN7vu9APGRTP5QkMacwTiUBQhmw241nnYE0hG0I6iP1zTEuyuJ2XxSjQMlFG8uwd+fU8Qbm4JhdWPMw8Oqs0yiJHeMvYGM5qRFKejNSCnQt4pU8fl5Fk2trdO7f026zAYpOMbtzboIzP1icY8BriaB38dit+6jqoBFczRxE8uy0kujt8Jqayj9lNorp+3EuZwxGuv16jMtTciiVEkcUyIdrriSa46HK7761a/wm7/zD3nlzVf49I/8CIjw+M1P8I9/8nV+5Ec/wzvf/iZ/+Vf+n/zEj/8YP/rJt5BF2foLMFdettY5b/fk9UgSobdKTgt32wnSwWXQXRAapcbZaZVEptUzpfkhavk4m796ISU3DDELUVN4ewC9FqxvLo5SYpjAhW933HDr4cZYHZZwbruX36Vs7gmjnbCepLburD4Jrad5cNOsXkVoJqWMpgWZ03sSIgukxQN2OnhgS/7zKhlZ3aUvNYVrQ5qiRZDgcbvS13skXdz7elI+waG+sacIWAXvhag51c+aOqYbroG1NlLAEcWigWtgiUlnNUY1PaCqaA+pOE7eXLwyMOS8ZNcl4Fiy9yl8zSrsVWis69qd450Xr25qNIVn9p7S3kSOPWzWZm6YRB3KqV5huT7AIdZSnPrnGMBOkEiBkZ9OZ07biePVIfoAbcIu/aPH7Y934B6PqfW3S7oQRPI78alBAXBLxdFwckxtbEgiIMtoZNrOKDFsGjm9hHEH/tjoYVQzON2OmlkE+1kUgE9b36vG+FGJLNqz6W4W48O8q23hINY1GrHWPBu3FJ9NZtY9hhvHLgisGs8ia1QFZtTWfHp29ZisFzJ1hQgShC9DeC4He4FoapZaKZsvXop7iejhEAZbTjNs4fedV+fL9lKR1TgcDpjFPL5D5sHhip/67Of49jtv85WvfJ2vyBVvXL3Ot7/6Tb76na/xo1//DN/54Dv8kZ/9g7z1qc9QMIqc6eWM2BUsypKUrVbqdkLXYV4VVUg/BT0y2AC6kiTTA9I4R5NV8+oCLio1ppZfrq2d0bSvuWEelIJ1M4ye4kiP34s1c1H2my7OzDHnzadoPleCYx9w1pji3kVdKt/dO6M3bzqL2HwtVQ22TMLS6rMqNce/F7c1EDDppJQ55Cu4gn6u1FOBo7LdF6o0TI3UxQVkkSCNAkKTm4Z16dPMzG1dlSEB7727matIDNLNQQHc8XL3tXHxUzCrAZvycUHQnoIl5DayKWUPjCHEac1hpMFkGbGhtOr9qeZHUQvr1W6dWrfp2Id4gJek+/41o/f9/rbeyTnhNvfDX8b3w5zsY/trt9a80d6ajytT5fbhDbokalQb0oS8ZGq7/8gx72MfuC852WMie/TQQfaN4nAIM1uyGdDjiE7RtOsXpkiJOd9OEHeXG69pBMYZAV/2HqZPb/agayIMFopTA8cpHOyUoPqpuXJs6Dyc6+vMEodGhqKvzK8No6JmHYo5RSrUiRIoiuwjDaNSjw0WkEetja0UF1d0jUxUY1xTmxtAImvpCCmaRKP5ez4VWus8fLWgKUM+YSKk1affuP7IcW46tM3NlrK5LPy8KKklWmlzlNSrDx9jCHfvP+fX//b/yjeff5MvP3mb7z17zpufeoXHh0d88PQpDx4+cBZIA7V7Sm+sx2sU7xf0upF14e58T0pXlFoRXdBB10qGm3YFJasxaWpiriwUaYGd7w/Psi+8urtDdCoxouulrvZYfzuTqYdcvbGzFRyS8ha7329nWrTWY9oNziqRFMmBHxCasv9Rd2gxSXQSqgtk9/geePs8gBAQt7VtCj11kmSyZg7LQi0g6vYDQ7SQU8KyYdUTG+Z7xpMBXBU5GpSukXJPmjUvbHfbTLKIKmWM1Wvd5e559UEbIwhO97yLA9P9W5aLA9MnrftbCqjP2CtHMXJKVHNXQFFXVfthaTOrH/Bk1E+hafC1oMEuSdk92Wvb/H7rwMxtZtoDTum9hxe6lwApBdw2fG5a9Z/uw5/l9wkd8DJo7wyTPfAmfHbgS4tlYMfBd/WLbCDdIQuT6Tjm9qN+aqYwoW/W41R23E8QD9JRagkM7Ys/d/zPO+iOvY/RYWOx7O+pkqxjVhHxoLxtG4fcPVhLQ6zPSTsQmXqPjLiGerFYSIAVKd1LWwuHudadNhbG80mC21wi20OhVVJLk0ZoO23cvR6ijK1hiDXK//PdiWU9QO2c789ocR/uczmztcJydBlzLQ3pjdpX+sFIKVNUHGfGP8sYzfZMNsqTdzisC289/CTHm2uu8xUfPHvC1YMrXnzwlKuHD9hao6cKvdLKGQVKbS60EeXqsPDsXFjSwtYqYk7Nsl4xSVivOBHGaXOCeyd3DEnrzKbHwx0nhytcd/omhI1qNK8joxy8f79unU6wPdTXYG2709z5XECKZ9ZmmGi42IWSMp7DNCFpge5eIM4vdpxXsvuiS0pIZNsezJ1rrr7cw55B/fvJaFrCHMoTkow3SVHom2EKXY1m1ZuaGgItGYeaU/ms9hhi4Xvi+voazq5zaKVM4Y7InnXTWmgC9qG6Fo36YdTkMVbIcU9bq4Er23Qe7AFDEdl+a0MEtWfMYu4t4n2OHXJBfQK7mHjWzZ6Y5TSGRwwBVuDn4o19iF5OrYzxZKMa06Tz8DFzJk6PmOIHVgdVDuvykWPfxzpwj5usaTctH9kKRsyca47rEniVLE4bvOgWSxhVmxgacrouvpg0mCYtpNC+7XR2ppNGGa3eSJGwzOzS6NVChguGczV7yMhF8MWRwE2HvAIQ9UGpjqU5/t1bQ1OLwQAhuJGKWXFpbUkTFqlbI3X11w7cUfBOu+AiGy8phdJ64O5C7YrEpPeEOC/VhicFk1Lo2aGX5tWELEYSkKw8+eAZW9tYX6yQEyziMuDesCykfO1Z2CJAppSCSkMWWHPCZKHXQrHOYs7v6Jux5BVtJ67TivZKuXtB4hOc7u7p60KnsV5fsRVDU6ec70jLEWtnytm4vnFXPKxHRp2C6+2cZKyN2RGYiUMntdAVnxRvfmCOppZXQ4vDbUHLtB42rxrPbzaz8AH/ulCpubCpbtTtxLad6KVgAjmvIC5BN4wmi2PbmlBN7t+hB2oXztWzSlRZDGRZkeWA6AppwdKKhU3AOEZERrXoUA2mkVX6QaJ55bAcqIeN7VxpWr151xwqb1ultOoTg6Jqwwxrwb4YLCZJjnMvsORM3br72RycNdLPlWVdwYRSovFYG7oEzS6m24h5tVpD0arJVZXZEiUCZA5zqZRcKCEqDo0gruZUDXzah2H35p5C43DoPeyLu6LaHZe3TtYUSuGgWFsjRk1y6T6KJtLie9+dGb0RPaqAvDoFMWvivG2ct431ekGCoeP3MJL+vfX1Ax8f68A9MFrpY36bn3wuNVan40wWB9EM2BBdYtHhLmb08FFoaEze0KTh9hqNiS5oM/SQnOsbmW9rbWLYFv4MPmTX+dyE7FfCjU4WpUmndTxLZzjP1WiONlRdHizWvMnVG71XuhUXclil941OcTOdzbB7o995k7IW8QBpndSVJK486/WiCdk7SiJ3F2yUbXNTpNapJtjWJ/uExj5GKsRhw3QK71VR6Tx/cc+L0wlZ/OuS3bhpOWZubh/QlsZJTj58Obm0vp0L9yehScMElnXh6voIeiTbC27WG67XG053J5QKm9KuOndPXnB9e8PW/Bq8eH7H4cHRR6YdF0Q7XF1RmvHi+TPW4zVXy5GK+qZfwowpLXhXQblWODXHLkV1DHyknE+07ko5UQ9wInUKKFQEScM7BKeZ0UN04ba83bxxu5VKK5srR8sGdHI+kJeVw2EN4ZFSu1uuns6bw20amTOJasa5Fe7PG+jCw9tXkOM1mg90ErULFcFaC0ioeaOySzQG/XCRcPXTpGjOzgI6OmRGd+z6/nT2ijMllvWAlkh4rMMitFP3BuqpTmw7i3C4Wll1pZ4La0pkWZxm1xJnKqfTCZUcTd0hYmm0baPUjXVdJ9RCC/+hlMi6UDeHcBYJQ7KQjHc827YLPLuezy5fV4lGslcUvXdKKUioSPtwh2yd66trAO7unmPm7YEx/SYlpXWnC1bCTTGamCP56915/HlZUbzn0XuhbpsL6lpAikjcG2FZ0kuj6H7Q42MduMeYJH9EueLtbob3bdLE4EqOoaD+8C6umKdDJp6FSJj/uueuuE1pKLoG1DJY4xJDECbLK5BJoqmoeW+CKm6YZOp+v6bmDR1s2oGrdTyE9PlnyIkBpwm2QusFtLpZUovDIwQ4UpR+qg6NNG8KLQommUEoH7P4JAG5kzWDnR0Lb/iYKX8rDO9uBq49GkUibiIUb97M3egku3S/4+Iewbv+WTOHfIgJOVEmZ+itcT6dKVao3QckPH/+3JkibeMzb77F5z/5Wf7Bb//vvP3+91hShtY5Pb/HgPV6ZdvOHG8OlNPZN72tXN0Ix8MBtuaMmFaA7Eo7XWKOoZKWTGOhI5yKkWIKeCPgj+Bue82WAousvt40TTzb8GqtBcwwfF2Gk97MtpvTAM/nE1spNAsnvMi4om8WjosHsiT3NAnWSDNQ80CqeR2tyOjPBPQQDIUmRkrOJnJKH7v1vMS/w/LXOxuZrCs9N67WSjs0WqmcWp+MI8+g3bhruhaa498pmrgKHI4H+slx3nU5kKr3MCSWUq+dHtDYXOO9B/fZVYZiIejqTturtaLm1XU5beScyMvBrRM0GBq1T9qhxwjQGBw82AGD0ulkn07ZjJwiLjgpn+18otVKzqtzwGX4ZTuFsTPgGPMekQmtVx/iMD4js7tBKRXN4QekPqNSOljYSPtknI8e+z7WgdsMcnac0EsTV5C1uAIaaiqZ45gCH7SBsQ3ZjmNdDXwzekRHGvSkZFUS+CbuRldlppuycwYkxe4b/Gz/6nyvg5trGgEuJ5I2MtHQiiDpknv1IawYyWwKdKSPGYEe+MViE5SOFYHNG47SxL0mVGlZMKkkdRMea2MSCYgmb7houMFF+SttBOrA5oa9Z2RstTfmxw2qV05jejZOSRMgnAafP3uBibFuC5qV9XgIyClRz42tF85lo9FZsnKiYtZ4LT/nnfpdXjy/Q8QXfi+Ndq7UpbLVjePVgbsX99zcXlFOnu3UWjncwPHqhvN25nQ6kW6OXt2kA4sYKit5WSmmnIvTLB23rcE2MVo083rr4alhdNl9NTxYMy4UGQ/erRb6MJLS2Gax3kpr3J3OnM8nKsKDY2JdQmYuHfKKm555VedKj4RoRsjktbKSMPHBzR6APFjXZpTevTCShpoxVvmETWbLJzrqRhzCPr4sy8phPVKWSjv2EJcI53Nh6SmYHp7Ja6wJYp7ncIXMZE5WUUkseaVXF22ZtIAW01TojpmPYwpOzplyrn6Q1c6S4/qFgAb8Z4QI7OASdfUP543/UCxrmDuNJiRCrc7QilvC4OK31lBlMk1yzpcXK6qCMgkBLeCmYYE8exG9QVI0JTS7jN4wDscjp/vzDlWNBCj6X/2HiNwf68DtWYrToHofqsdQ7IkgkhiDcEeTf2RHZvjpyuj0e4Ct0ZgT8eCr3UdDSY8mn4hn6cBMhfGTvUcgkxQZmzmeK6vQkzmDJGhI1iNYh3pMrJPUyBIe21hk4D6tXOrIvN3elQjgztuGXsyd3LZO25x422swSJbkxu5LiDPUSGHM06PzqKizU8b1aI7/Mzy9/VsusBhiDAzTRNKB+0J8w2GGHqZa1Sinwp3ecXdS0I6k5MN/6Wzt7BUInWaNE522CmtSrvMDnj95yv3dCVncX6JXf3/XhytO/czp7kQ+Zp48ecb1zRV1q9zf3bFuZ25q4er4ABN3zvMBCI5hpuQGutYKtba5ody8tofi0Ev46dArjuuLMN3lxBo1FIW+zEKAYYM6Gp4hrVBa5+504tmLF25mlFeulkbrjdMGqpWE+1nULpBXNB/RfHA6X/e8f8nBNbfw2W7OOBpwjftuj9FhmSEWYUwBGZVUCNX8IHKmjKZEkoUlrxxSpaSNLah2ZkYvwXLZOlkX/4xhKetDMiTYH55lj0a4RFJjbTTqQvrfA2po3vynx4QZIItj+621KPg6ackhlKruMJkzddtcPBYKyVH1rNnH4JmVuTRVvayRGc/Fkx3ppLRSa0GTsKwLp/uz38eAYGr1/2rQiGtxf5JuFVUX8yRL5BzQkGYWVdJ6oHejbIW8uKLP+wree2kNft9MwBHReZCmtAsd9ni6i3LMeqxOm2Uf4S/RY4rGaG6YBbYbpvs0cGvkaFhw4T0yuL2xAFptLleOAQutNccMo7OtItPW0jQmqVy8P/ewtjhcDKygyaYEHqvTKbBWb0S2IPHTlLI12nnHp7t113LkmLmJu8PNTMI/pl+WYDe4n4kFOyXoiz1KcZ9Qi7Y4AIEm7jm8dXVpfga2FJWFhg1p41TPXolkAfXPbxibbd4YzuoubcmhlttXX+P24Su8+/bXnDlzbpj4c1k1EolHDx7ywbMnlHOhSWM7b9w8uua4Hrh79pxWNo4PKsvNI7ZWnN6lawirOtY2Wqkx7iq5L0s6Oo/awniqN3zqZp9+zYiQpLkFqxk0D5pAMFLcj1lTjsa5B5XzVnj+4o7nz19wLp3DEbY1o5urIEVAq9HEVY5djCUrKS101K814oMT0jIdHp0x4bat1YQ+GmmDwWJe3cjMkCN4hiOkf2Hw95WkC6suVHXc2lr1BnUb3Gtfq0O1GD1eRvHRenPGknYPVqFyHBasZm501pvFNJiAG0P1bGYsktBll9O7zQNYNc7ncwxWgLKd5yHgcJSzR7wBmS7MnyLTjog9vhY4TcSUOJzD3MqHycchMw8bfG6stel7ksIXppYz65rIWXhxt3F9eMD19RWn+zN3d/eoGsxs/9JbxZufH/XxMQ/cMALQS51ehoWkXfyc03VsuJoB2M5tHQFfAkMbWcRL4orAy2woZ5KXOi2G7aooLUejNMVCjNceY84G5o3hX8O9MzJjmo2La3Ko76R29GKqdh8H0Hg0vJsfWWgr7i/Sw56zV0PXoC1JJZHIq4QpkJClk8W7/WO8mQ0mSTAiPMONzNsEWnf/5xAHi1t6ePW3gM8mUG9OFpBFyZahGJWOZCFlZ/2YGE2bi5eqkJbEuh4wqzy+fczDR6/xjW/+FvW0kZaViuOi90/vOD0+8fjBY1559ApPnn/gOHmrPHnvCTe3VxyvDtyfTmzlHfJpY7l9HZXMkhtZV088Az6jFxQ33W/W6JaxemZrGz2tiBU0KJVuM7RgKXnmF5kovQVLJRqCOYXxEBDX2NlHYcvaGktffAq9nMCM9Xh0hhGVvCyseSHnJQ4Azxx7P4eXDC5CidUDYfwUGZyuCRtNSGKdh2mU+6UYY5wdzQG/Ib4ihvFmSax5ZaORklHuz34AkAgDzhn3RMTZJhi1VNa0+kiu1kONGBzqlFBtEyP3gBusLMHpheYH+fi+qk7oYqf17VYMtbrwqw1hHc5UOqwryBhe0KF5xXvp5Adh4RpVUkp+r2rbSMnl+7XWocbArGJN5kFxWNeAawtrzLQ8l43rqwNvvPYaL17csSRlzdkTIpEp9BHdVdwaVgUf5fGxDtyYB8tuPXC3tvfQuMhg2QO7/16MHgusToZhkiafkRd87D4Ws3rDTm1QeKJjn3TkrY4Rp6BCRVNRoypFuysl00hvZZpWDXxd1aGNHqIa06AqqltHHlXm4Frrnnn3HjS/7l11K+6xXUv1SWiloy2xtYY0RdbGQvNGV1dvqgxhTfXGrDRiyIHN+XouEIgsrQ7oZAgnalQy0YhpEhl1Q6qgi4Y1qWOQprjYZ7OoSvDrEozGZp2TFA4LvPHKm+Q10U8n2hmMjSaCSeP84p53334HMlw/uGZJC3cv7mKsmfD8+R2lFfIhQ6/cP/8APdyQ8oEkjW6VUqGcN8SE47pQGtxvhdI2qiWqJbL6yKoavP80xpz15s1HBOkOTbVaaG2jmrEsV4jG/MJQ9iVNHNLKcVnJy8L95orT51LJ4YSX8gEJKEk0IcsVul65WVSzyPYVJEcicQT1wN1K9bmSzamnRkfTwSlrJJ9MFI3MGfQ6uyfNaNrFVHW1TBYf6TVsGSA7XdVcK6DZR4INcVWkMN6kE1faprxQw93PM383r6qletXcYkgHkEm+ls0P9HVZ0D4SKGE7uUVvSikagRb4cJ/0urFaU/ahwNaaq6pVSDm7SRrR/6LTzFx8tCaWJXnfqBeHcMxphJoz59O9V/bqBtK1uV+MBUe8i3uP1JDfP7i9xmoB8wb5uRYk7z4yquJsFtXA+Xfo9Qc9Pt6BGyZcMW1QL/7tXfpBFbwoD20IcC5YKWJTWuuOgy+9iHfzJX6vd3p2TrVzrgM8686YIEWDcNk75lMdFZl8XjJdHf5Q7VirziIx/2OtzGYkVmh29u8P0/B4X17pBbIapdxw+GulI637xu4Oh2QSWTJLuKTNad4W2HWUzdY9Oxn4tg2myXgEpzvIPE6RFA/CYl5xQOB24SFvSZDswiVTc5xVYVgI+ETtRDlVluMVjx8+RkR5fnfnm6R70CErdWs8f/qCQuPm9oblyj0strs78iFYO72SSvJhrarU84nluHE+ndDFOG1Oy9R8YCsOs5y3TiVFgM/0AcNNZElcsTouQ2uU2ijbmdI8J9OUSWmhmfN5XVQ4KkEJY7IhInH4pHdBr9doqHfyuiBpIee8y9dNkKwkwwdFdwNJbKZuTSCJlAztRultUt+ka7jihWgssG3MdpTg8g8uXvPVnljzwiILpxae0yhWvSm9nTauD1dhbBZ0XKe+sOSV1qsH6tbQptTSQ8zUJ4S0S8Vnk2BCjxDy/bBWba1Gc9iz1ha2qKOC6MHg6lYRc6KCBN9+sG6mLN38/jv7rDv/vje/5+QQ3I07XVmGH3heY8/nYBh50rhkl/InUSwJKsZ9ObHVja0UzBpXx5XSfSJOjM5iDFPo/aMbu378Azdxn8dCeCmQX8yqC6tGGTc9LCNHUFfVGZfGjRUkMskIcrGuXBkZKqj4oll3spjGQgvfCIsRTZqidROLcZjapJguPzY22AVrJL5m4XgonnUnicZlyNmleYnba3hrV8NKD6GHZ710b0gm89fURWaDSuKzSo/g3YiJJwEZmeyBewTysdFGUCZaBhbXR8w531FOE3CimHogyZ71oYouAd3g762LcX284eHtY7Za2c7Fr1sJaCXMvtpWuXv+gvP55KrM1QPUqRXSKqyy0mrnvFVQY7t7NpWdUgulGJ0MtVIK3J8LpTrrRJYjh0UpohTz5nEnIb06NCGNGvjqqTRquUclocuRdTmiyau42py/W2NDl9IopbhaEqjVWMWHCvTuk2eclTHGZ4XnB8n7AOqMChPFumdpI/D5ukl0cQ2Cag4lZyZJYghuPElhZts2Dm1icZu5v7e4eVVmYV0WDnnlvm3OhMQbj1hAZG1gxh4IUWYG34rDItZDit5ioIF4Q3JEarXRI3DOtXXztZwD8jRmLypJphPzNkufhwYtPkJw8nqNAcXqcMlMsiJyuDTd969e+MvUWp2d1NxawqdWeYSopfgQ8KBl9u5Co8O60rq7Ax7yglnn2d3dS4llTgmpgQhMCEudwXRBdvhBj4914B5ZtYY5+mXght0hEBgx0Z2+ulPVtO8B32XOfuF8E0hAJBd+FGYu9okg0yOADy5z7U7DS5rQ5BvN/UW84edDLnpMg/bSMwWWncyQ7tkB3eXtvW2gFbozTtRsDgweY5dofTZQh3f2bGzWYABEM62YkrSxaKP0yqqLl6XDwnUcbOYl7dw8I9ucA4HZ+dvROPJNI1iOi91gqDYnbWHg+tLnhlURNAyIEm7y3zsc1iM5rTx/8QH97PzuJp02mGGl0bOiPft4KmusskIFXWQ2WY/pQMqJUzlxOt2jz5+ga6PKfXiFLGwdUl65WlbPpjSFuKrjCtUYuGE+DxKtGJ4Z19ogKGKafeBtzplSK72513bdztyXSm/G/anw9PkLTueNUhvWvWROXSmlUmol686Mcl6492ci5noTlUxKgvXiQh/DJ7cHEymljOriEEDYvfo0pKj7ogG+M4Yc5tonsjeSZoyVnAprWrhaOs/kDsPZV601P2hLYww06OG5k2K816imFJeTa9Kg6OlMhub+HAmUjX3o0OEhuaIr4UOU/bAKVz3rQU307JvOTIaGCEe9GPHsO97jUGg6m8RNozSGN1x6+PtUorDNCF+SslV8RpHTyNY14e4vjSVlqrnitJuxtc5h8Qb19eHIuq48ffE0bBb89FT1w3ZY236Ux8c6cM8K9PJrNgxb/FQbDUaVGEGEG/v3jm/cy8AUXM0hEBkPL2+ZpdzozLt/xE75qq2SVKnd0K7oGpJi9SG+tVYfuxR+CNag0liVEEjoxJIvP88I/F5GiosvuoQ0H9pLB06fBlKTbnVukBK1dyqdpo3SXY7LCAzmSsg+sh6TQbqZAVsGfQDmhh8BfDSarA14qO+bMXlGZ+y7dFY72UvbJGmKetTgeLhG00KQP8hdqeKiKJ8z4BO1rRi6+tgpFfVmVHb/7147Zaus1ws36Ya784k7A1kLxdyMqUnm3IT16hbNFfIRJGFto2M09fmZ1iqlDf9pP/ibDRdI4bCsSD44C9JauDMGlEVn2zaePX/B8+cnnt/fc95KlPHew9DqvZXRYPfhvkKazXPZ6YfhdeMQyIJxnolLJ9HMFZ4phd2rePZMUFyZ68V7QtJheooGlOKMLZ9TmWUhk0giHNeVu+dn2tZYlpV2qlRrrClsFkTRgChUBO3uI94jyC5xOAvMIQQpucMh4g06O3upJg3yMXM8HGM9hx6jFtrFWp886uJsDR/e4FmziE2XRMwPSafzOT6umiaDpJvbso4mYYtZrjV8alQ1Rq55gE0psbXK8bigBufTmZzDbVR9ynxvja6JJWUeHK84b4UlL5zLGQk/mp6Cvtt/n9ABd3MmmTQe5xP3KDH3bFljRNHorIuGF4INu0rPZrw5H4ySUJi8ZOE6MDLdM23A/w3eLGmdYI855qtOcWupudoSP/FzM5BK72dEG0lc8p6Dp51VULPAvj0LVxz3tvDX9gnYnpkk0ymldy8JT8W6hF+LGU0aJXXQSiaTCH+NpIy8wa1Da/B6X4ZIBh5OYPVOmySauTjNDz9UAEgWHst7gzMulP/r4gDQyGKSKVl8xFXrjVoqi6YZ+GXJPLq94f3tWViw+vuwGMWWo3vfa6OVxunOlW+WlNP5TD9vdF0oXUnLAdKBup2gutVskgR5iT6AcapnzsUzzDaCmqRohHu2Royrcj8MnweJudVob36A3N3d8/TFHafzxrl6YPdS2zO9rWa2as7GuVi3PRjSYkHTNOjd2SnjUXtk3Lh9g+OvgLnDHSKMwQOYBYRlTj2dksqonLrzUEy8mywx0zF1YSFBs8BzA68fVSc++cbMs1/t3sgrvVIiYA0IUqPa8h5ComufVNhp3KXK1dUVS8wf7T16Kdn57KBYLQg+UNuZIY1WSzBQovlvUMvwvY5GqO0Ve++NZolWXPnoKmuHSpAx6NeDsJlDVS0akhJN3cGWOW9n1mP26rp1Si1crQvXVyu9Vcp27/Ng6bEnfW5s70atv08k7xadFTdc91NQVSetSIZ6D2bgGB7BQ5mGSJipe0kfYYcRjTyL6RGkPYg1cQ7qGFvWcD9rmU5RBOOiBdMC93BIOahNLqBurdJ1EPsrmYq0On18O8PO0+bhsnNJDW1uSCV44MuqNEn+fsD55y1wc+1Y9tKwbAXE/PWiglgl01NHWg1lfMjxCb61WUAfMHTTYg6TTzTEzGEbbA/coyQnfi7uAdkP0Fmmmz/ZcNezrcO5cX72gh6Db3NKHI8HWJXj8Qrd7ii10YrhJl6OxZsauvoGreczUiEdEi3GvJ1Lo6eFTmaRxNXhCs2efXvXtaI0jNXFNbXQtnPMdPeDXsUl8IbfE6yxoHRzFkvZtiirG/d3J+5OJ05b4Xx2v5LaDET9eYJBVKrPkVyPq69llB6QAnHfayPYE2EF2zqtO1Zr3dg6lGYsGlm5Rpg0QTRG2wXrSZL3T1w5FmS3Hnerx+uLwyvJ1JWx5s5/1oTzdibFAauL37e+xdDfjg9QEDcKQxzCaFEJSixR1wzsgh1rEbgjEz8cVl/HFvqDalOBqV2iD+P7ixjOLSn7IUHzRGQK8iKI18pwDATfEyl5o7j36pj9SGKGo2fwvzWqIk9Uis81rTWon0qphaOsvvai6qi1ghmlbFPV7Y1jJtutNsfTP+rjYx243fwm+0l8QXkQSdO8RVQiq+mzg01kdj2aMBIlHSo0iQxkNDEHXmyOk03pfL/A0y0600s81zImQ0emHeOwaLEZhgWsJId0pltT0JasoZiLHuLvMqa+q3uYWAS8OfsPb4BqumgyAmNCS2+NTqa1TqWhSwh3xK9GEmUJzSYJikpkOBLTcIizTAM2IjYMUzE63gdE+T2+Mg4zcUolMH3D45RwkDZZ2BZkyv1GeXrPi3c/4JAW1sMVaU1c3z7g3DbqVmeTNMwdKecNWDEp3t1fPXss1UeXpWNGE+Sc2brhSuqGqHA4ZDQfqbpgurr6VbqPMAvznzFWdg7/FUHMfNABMb0IXx+9btRmnE4b9/f33N+f2M7elCzjckZ5br3Teopkg5BKH5A0VInQZxPbg0BMZXQ7mV5iyALzUHfanaLkwJN3DLXHFAT3lImbNXoWYi+zh2zXM0j4f2fUhzLHMAdrnXIuXC1HEKO0NjPxVnz9Lbo4RBgNeicJhL1AzGlUJFwU3WNoWVfA/dlN1SGgkQP03QK2R0I1vESIpKj16iPklhWhhKFczINsnVbLbC6aDduMYI1Zm9dJXOrJ1dU1pXjPA9zq1S+oUcuGMRTXQtnO9A6n05lDdifMrWyuDFX1g6LUmSx2i6b7R3x8rAN37wURL0sszJbGhGwYqkYJ578wp+8dkewBjeyhORqHrXcvy4AhLBAuYJaumHR0dRqFuK1cyH3da2Qs8EZHUyzCQ2TB3aZnsDXnamv3broaLMuRJOYYuZjzr3GlpNjKWRdvYlphPUJnQ3B5cF+Nem70pSPXIClUo+Fe5tSmAilTkkDMNZQl++TwwFMPJXuTMxk13ARbM/djrsPLhCl714Mw6CRdx3CIFkMkbDokanYmSV6S9xBU3CpXO+d+ovZEaolUMmlJPD19wG9/6df53tPv8epn3+TqcMWz0xNqb9yf77h//py2OOPgxIYWYo7lhlRX8+WUSYu/vmRlOS40yyxX11ynldqhoJRmcC4s6QozjQy2wyLIeqCfKlsPj4mo4rpAqR50WmucaqP7CGiaCffnjXNp1K3w7MWJZ/dn7s6VkylbiLwwpeKvJ909cY59YanK0iB1WE3BFkyEglFN2cwbdM7kTBQ5Uqhs3TiXwnZXyNKQvgYUpYiFxav5JJnB0ddmWFOHuVqHKt4jKc7a6efirKWmLGSHSzRRWdiaf77UEyVXsjRyF7QONz0XaWVVTuVMK26oZZ3w+fBBA620OQZviMCoLu3X0rm7PzlrKyWG901tDoP10j3jT0qvNXjXnayuYr65OTpzxNQDtaj7ydTqsx5rQ9Qomx96pTku3lsjL07v6+ZjDe9ePAeIwRQeV2q5c5hxyYhWjlcHzqcz96d7Sm0klLKdOIsfRg7BCDLGBYp714CwLr9PBDg7HBFEe5MwlfJAHJykOTzVoT3njrhJkoCl+Hkv3UcmNL03EtB9ILDVPtVikkKOoEEhGlcy8NvkXSpXB3aXZ/fh4lc7aXUph08z6TSErXaSehBvJqxpodczTbJnf5ZoZLaeWZJP+jYxLIGuGV0cEiF7YJUqSI0qI2AdU6PRSaJ0Gl3cCMeakoqCVUxg7YmU3XGw1k6R7tm5Bh/WgBpYaaCWGtRJGzJwiUZQgrS498PhuNLFgZiRJdUeQ1QDy9eeMSrfee9tuhaOyT23e608vzuHRJ7Zf0jq96fF+KxldT59aw1LynLIHK5XluM1tSuldc7nM6arjwdrJ7ounF/ckXL0J5ZrVFz+Who+BNg702Qxqoj7d9CpHc7dYl6l37tSO1tpzhTpl56PU7eL4Fi5SaJbwnp2PFsybvarbJZI3WIgiAf6HuulxVr2MkWw7lS9AT8oCTGFwqRj+h+5YJ+qNycuqZ5tH0wgyAXXX1y4EpPmpzJXncrWSvXhIxATcfz+lsCIa2tkXZythDkVNGx0EX+dVpsL6ZpT7NrW5gR1iwq7VheY1VIuPEw8uWpt+g4zHPwsnj++HOevv15tlUP2AQYSjZqUEoJDcz6h3SmPu0BmjGkbToYdq9U9SHAoZtsKZnB9PDiG3SxETDIx8dYatXuDOKX8fcSE3+vxsQ/cFphUztlhbhu0QMUnyTC/jgX1xna8WxRvRolnhC1Qbm8KeQkp4k0hn/UY3MsekEGIVrQrugRQICF/j5vivNUUgxCY2Q7NaKJUg0UTpbti/P9D3r+F2NpueV7gbzyH952HiFin77gPuTMrM62s7Kqyugps901fqFhI3pmXIiJeSSIeQEQQQUUULxSEFEREBS8ELxUvLOw227aqmiSLxjLrpFW1z/s7rW+tOMw53/c5jb4Y453rS8tuv7TabjcZm8XeOyJWrIiYc45nPP+jDOf0QmYMu+DaCzVQJIJGRoA0VUsFDAMNHZJhuThmRgKSvYh004R7MIlGaDJo2ul0QlLC3q76NMgx07oRLKF2JEINMJpcyxQIG6lo1++m7Yppi/jHk0FHaU5M+8x8mAkR22xWqKPR1XuC1IdFH+gq3J/vOexnzk8nhDONavnUYRB24vGa+s78g309bcqUJhA72GlKrJHbww0hZuoQvny8cL7YoUjaUZoS6YQciWkipEBplaVV/3eCoTliGHJTe9GVbtUa1WMAqmO4bZhcsDQv3CWiIaHivIffhmQb3HiIr0QrWk4TI8w2iMHiGkxOYziswyV6hUi8Ab0ZHJej5W9b9d672yPqG+2WUTLs71zhKie31XFlccXR9rmByJwsiCnnAN3JS/D/tujb4fBiGJbgN1yu2qOz0mKcTN0UcJueXMTQoD6oa+OsJqMMDlv2PqiuHy/FNmwJZr5qzaKBd1NCRJjnmdpWcPgqOlSk/sMoXGGkMbz4IASiBKYp0/tGfNqtTf3G1brJP7Obo1pv9vdlZzkp3fTqpmSxQT6mbDCL/6cPe750JztNpvz1Z9/P/OC2/2Ga23AlKN8REnEjBMVYbAPJhJS9X/GqGOlAJIX0rlvSuCiTR0UhbQqTjm21uBa1DTNNdpMCiRiubZu+wSM0CNM7Bn60gUa1QP8RaEMs1GcUckj0kal9YY6Z0QuVRCWRRidpoAwhMCHpYuShYEmEOUDrSHbcvvo2o/aEGcGIvO3nLkNIIzBtt4bkN46gTDmiwzbymAIpd9o6aM0sy+oGICSQgh1GVd1kIbaNhxxIU2Lez+z2E/OcybvEWor9W83yVbq+G2jdtcjnspDmgK6Vaz9kfIeFslno1d4v9k1QWkWrGlSChV2tvfDweE+YDuT5hrtnzwhT4e3jxZrViSQy1ErlQq+dJrYBr7V7xkygOfTWtFMHrM3Chrqn9NltLZmrz9/X/Sanvvaq14x5owRKvGLWEm1oa5qtRJjtVPLwKL+6d7prt61FppdGL51Wuqfj2ZKg7R25rPAuh+arg9u37O3PGK7z7uodmG646SartWINrnEIDLONd+2EbF2QrVmBxJQyKU+cz2eT2xWrj7Nsm2G9iz6wAopKIoRB1cZamht3rCZOBaj9WklmPJKpjVorBsltKphg5QRrWf31DTGHv8XvMeWM0phSdvPN5v0w+W7YKgadEEbVZb/R2q0wnXiM2eSBpb6LEhAxx+QYtO5wolpI1dgybjbxhBO0X/ftZ3pw914d07brx/Cksk0aCLaJMBx/HcPcZCKWtmaOBSQZmdN1WMi+bE/24M7Hja32FvWEkT/iV0exDUY9tN4wN7tmx5iuV7YwhI1/sGone+EKnd5Xe4FLpEsmhYY1DWQ6EyqFMQKNSJNM7StBAlMEJkGK0BuQQYs6XIIPYuwmsqXt+/fcZVClU2imOBArOZagLvk1q/cULe1sTJExmbSqtU5du20/YiWvE4GlN9Zmm69EsbyILEyHzOF2zzTbdkEETcOCp0I32aIOG8BqsMmihcOYbRhG8ZhMcwV2jGTtHsO6wQDiBG2pjS6dOc1MUyZPmcfzQlg742klTAfm/ZHbZ3ec1s65DFot9JAJZFQKZTSqJCcU3cFYKx1rqKm+IXa17AqLRRDP366OlQt1GKpkcAlsDJuE5L/3jGERyfsfLRlQiY6pRxrJcW31DTtQh1Cb0tZKq90ifbtl74haYW+XjqTuN02/jDfx0gw1A1e3b3CD8ehGOI7mOun2znRmw9wfr2o58CmadrwshYrlkvTWiSOSJ8s6qTkxqv0dgNGVtZgeXDZSb+CKL7tmtNpMp5+S334tZsLIPDPztDbooxGiEEOi9AXzb7iE0OGsa8wzBndKMKw7xEApyjzPvil3tuoxGyFbycHq7Tf22OWcHSBURrAiiS2uwFIDbbs2p7QdalcduvAOLgIXUmyvza/39jM9uIfrWs3wYYScDjsdt5jXMexJy9gacIadjkEYeWJ09YLU6DiwVXqpYioTl05ZLoK/xtyWbC428Mi46zDXPrxZpXsYTnsXMC/histteKSKbVp9VCRNZg0mIZIpWshYtnLRSCJQJZHU5IONzDQP2rLS8U17DvaCC8OUMGGTPqlD3erBTmokG42IQaXD0/1SDO8S44ZfKRWYhFEjrXbW1AmrYXnTLjFNiVQLYQWa3YhkEkIW6x+cE7vDbEFaSemS0DCokozQ7c0ODrGg+jKqFRKr6dWFcFXgjGDX5h6M2Nlcr9vtAuOxKKUQ1kDaZUY1JxsZZC08LR3STEgTISZOpXGpj8RpkKYjPU40bSzVpWQyKHVQt83JVTiqQogR0XfSvKV0ljpYmsEmrYvlYojY4y1ikEyMRiCPwQg2oFUiYxvqcULFCT3ttKZXl2Qfhiv35j2Nvj0n11j32ug0ZDQjh9Wlgd0zscc2pE3Zot31/1/xAOADfJPCqre361CP1pXrjbL1Rk8dGVYrNu8n9vMMXWlppoVm33/bEiyVnLJh7sPAiylENAprszk2hkU8RMyjsJUdmAYaeitICMzzRC1WojF5ccW6Fno3QjJP2U14NiSDmF7eZIiB4XDHdbYMs/BvA3W4vjwESCkaTIReD7QQA71bHom6QkSwykDYFCNWY7Yp21SbE5b2sU1B+3XefqYHt0Fl764y271jg0lSStcHP0STBer19LXBayy3Ac8xZAv7sfs4mGbDdJxwVYUYYWn4Lf49iJ/MAQ84cj2qDB+ctTMqxF36PS7EUQc1GslpFmwhB5MBNh1MwSJF2+g0EoVGGJUqiagV1NtxcnDisTOCEmfD8llN6G+9fZscEvsZop3+TQeVTo6REZVemkW9TtnyI3w7kwEheuqhCF0DfRjhlqbI8XZH6omwBsZlodTVJH6z/T5HcEVOt00kaaAFq7xC7MUvaql7KSfa6A65WC3Vlj0jwVpFiprkTtvwYHtzXw6GS/OULrbt1FKRdEMvjbYWOnZo0QpFK10yVQelCbEGdj3AJHTJKDZ02xiUPmij0zVANEguhWgwiL8Il9o4L5Z7UgeM3ilDbdiqD+6YCB7Z2lXAV4Th27s5JxMpZoZafsvANu7aOqsXXbRq6oq+DoN3iqHlZankZPyFjE7Ucd0Q2VQkTdHWr07bLXP9Kgd0uGR7/Hu3LBwdBnmMbkvOqHZwbKUHczaLehjiX9MOhnAtQjZ5ZUqJw7w33LoYN3G19g/DtUfrtODpg2ppi1sZc2uWYTNNEykGKg5BBait0lqxrzNZ+JZnIF9lhBJtQ8450np1aTCutR6esx2vAXF9mFLMjHlcJbkiSox2+wGrqbM4AJsfwXQK13q04TG3gGPkjovzByRkyqR83aI8g2+U0TY3xFtePHkLtaQvkUhvxWAKthKF6E8GPHxH7UkXsP9O5uQrat1ywRcQdaybbgqP6DVGJh/Ey2YdbxQ7WHrpMJnkqhdrhW8Iazd/XBPDMi1rXUkh0TTZk0CEpolKJNFsI2wV+mDOQtolSvEXohca6DR8GNhtJETbT4d0unhpgQpN7JkocaCT0hGaV0/FZEStutY8RiHshKgGp/TeGXEw7wKZiZBsOz1V0/SqKD3iaoiBZiUOsSowPwxU/CquDtN0U+Q8tjPPw8EUK8kkl90J1bUXvz1k685sQgqKZD9wYzCpV2tQGvtdMjt2VdrorE4ydhUaHY0TIWaGBs51WHxuVFZNjr0HShs0o0MIY6ASqKKm3hGDUHo30nJt5sir3coPGoaRg3hlXCKm7KaUaLdHb3IfHgjVWqQJFi8rlv3e1b5/LR4qVk2N0Wv3bRla6fTLStdMmJJFHGzXEGc8tRokIm7UGr4Ja/eEQc+gCWqchqjQaqUuinQL0VK1HOxdmswH0AZdKmnY81UnU2eU0mhrha5UNZfjPs0kCZRaHLY0x3NdQIPQ184QYUrRGqjEXnhbbRoo+8NEiNBGdYeoyWs3x+28mxB/wYYYqd3EACMoKSg5BPPt1EEbDcmGP4cB9EEPwjTPtMVKjwVr6TElk0NNDs+afh8LdnNYytRAhuUTJ/owlZst3cE/blEP9Q9KrKuZY4Zd/XDDC8Jmdb+C/fYbNFiCTpwnupfHioiVdEYzB0iwXF+8+HSgUDsk9eJWzzpuBjeMZpplmhInlyGpYX+R5JirOar6wILcmz1JQogm1ZqENoRldKKq5x0YdFKHGWOaTAwMZmiaaME2P4jWNEKFZARoqw2Naql7yTZ7QdyosilMQGXYFoxtgXj1mziEY8aagTpBI8Fx0C1oKgnBjTRDOiQjfXd5okinrZYlQsJ5A+yAVft3m3a6DIYXUYjLGKPLorQPSiuM3d62aLXHGHETxdYkMhrUwIjQu1WShUkgylVxUrsSuxGGY3SGJAjJrvED1t6hF5ooIQeiegQpmREmiNFyuftWPec3rrDxFgpUWrOB11UcIqm04eFIuGpHImqrGwTDgHVY/KtEi3NViVSN0Bs9WrN5H4MyDPaLBEfoxpWE3OCHTqeMwqoXhASarIkoqGW9YGTnptl+l7vOlawcbfjvVtA63pGX3tdY1xVtFnEaUjIIsHVKqcQ8sS7VWuEdBjETmLKUleiKly6D6JVoKQRGSqYgccltFLzIupNTptS6eXUc4hBiEJZi/Z4MX0rUInpTSkQ34OUc3aDbCcH15dGcZKb+MYlpFMtkQdSzu+0GmGO8Zr2rL8bBdQpfvcH3Vr+Ck1eHZTAOpFfHvY3/smrageDwSi9fe/b9TA/uLXdk29LMYKPXrddkQMOdiuMqNzKtjngLhlxVKCEOt79Xg0WCWwSTb4N0J8JMWSDVT1+1sKnePC61mzxOtti2gMMnA22ebBeMFNUGIdngFs20UVm72FlAJtPpkg0WCYk2kkEnZJZerLyVYOqP0NAMJLd+Y0l5m43YCCm7qRhJolcViWJX8Yigw24GMWwad3d6JnuhD8c9JTv+LYJG0GRW8xQDOzKVSgsuvpJOF9PoWj+nRQkMXF3jGOJX4a8QInV0ijYjhlojZLvONpfE2QvVps1oXBUUyQ0nIQV31iuXy4URJ+qwAog21MwwWKpYHUIbDbSYJE0iLQyqKCnNAK65NmngVqisrhAYKtQxWJtSh31fxS3qdYiTk6YesTwYkwIaGmFhZITEcDIybKRnq6CRtRoEELtayt9VvifXXBLBtNW1NVYWYphIZNoIQGJcM2HMym6kpEONGywythRIW4x0DDvMa2fLwEYgBtuGx+rMsBPMGpQ2BtKaaa49pXIMZVS9ph9a7sfElLMpLUajB49zUNjvd0iwkuZebBjGECmrD8QQPJfFYBi1tCxqa7TRSendAldbMyzZSDDylMkxcT6didE29IFdjM1Naa7LMMzYE+I7xVqMimojiMkQ5zyBqmPc+k4csSkRzAlnHwtyjWbYXnX4grnFxn6dt5/pwR3kK1u3iapRtSwQ1XqV4OAvFvvf0UmI5K03EMQkg4izwQN0RLTbRkj1kxwIk52Wow1aMCWJdk9UmzpStk1M0RCoa7WWnsSVqW+1I5M43GIvNHWMezi2VsXs1M2zJhqZLhOwUjSQemN0O4TMsRyYgr1oZOK6NUuWq41ZBs5km0rDSgnsV2MwkQ9oh3y6C3/DFgC0EZtgmwceHKUeXkUnSSQkGyqSXYLpV9PWK1UrmUgPpoPuYgoS08i65Mq3ZAmW83BuC8/mW7vC25ej0Z3kMBzbhpxf3asdBiEGpCc0JoYGSm3mIEQYGJ/Qe6eqOSiHDiRODImWgSJC1QZTht6RkI1IxOCl4HxBU9d2d3O9FicOt8ST6gqUoVh8p9hhMa5/DMFQhTICTSM5JEjZCcVIWQtRAh999C3efvIZl8sDjEhfmskBq/eFusxPZdCk0VKhSSEMO4TFDT6iivRgJPLw2ICBfZNfie81YtKfO83MML2Z0zFOzuFgWHv2cuAqjRTMdagOvWwRuOJVbm0pTPOOlDM6YCmr47yBVhoxiD3KfTBPO1QaMdrtJsggueyw90bcHq9WEYF1vdjzVFxyODrRK8xqq4QYSEnorWCyPzUzEJCSoKNfI5p1mBdgn/eouCxU1A8/u6TmnN71vuIwqhvQthzuayrhpoKDa956D5tw4uvPvp/pwb29bY022zJtD/CWHIgTDs7cBlASta5mbhGTFYrnACsOITgrLNle0L0MSIpWNWPb1lbdt8NDiaW7vlvsSpc84F2F7iYWFbtmBw3vMq+70vBBjbvyfJoGN7hEMWVJJxKHsGogayJostOfho5IjAaZMMl2e7ffgboZI5hGd0vxG2FczUaiZucWL8zU7hidAHSz+IsYJEOgYy41wwUHRStZIxKgjE6Vfk3lU5QaBrU3QjbL9vBN215k9lhtRpphqzxEYWmFo9oGNcawtvfSLRXQYRaCGYqCY+CjD2Izx+mWudLzjNZmhKMEd7cGarON3Og7tuXRgn/U+IIBZDGSrQ27mwyxrV4lMbDWmdpNQWCDXGgaaN600g1vwkXnV6jEvoaZiQjJoJKQrKVdvEUmTLRz4Xvf++vswkyUibWcbFCuzUqiO/RmyqEgmEkoVCqrRagGiCEDzYwyXe3WcCUlNzJykwDig3y4TM8WjSSZoVgOeq1oU+Y8GZQYuh1MDhlaQ41DYCGRghV8xCjsdzsiwfgVuBYC11o4Hm2LjWKKj+xwTOuNEGa78arzQmMwmrko85Q5Xc6+vHVKtZTLmAyOyDl6D2aj1GrO3Wbb/BhqbevdHK9xv7XgNELy24/3Uko03iNlnztjXEld8yMYbBtjZMrJeCKfR+ZNcsJJbcHqzSS2X/ftZ35wb1nF7+rJPHjGg5xw0mCzkwbZ4BMPA3KLPGqQgCLeY9lRDRZ9mgKlNevIw6RINjS4kjYh2bUtBjOstN7QtVqxQLfBNIpdtTY97GZioBuWXhUWteQ5244ik3SKk5FmfxaGRtBGlEAjgSTKqNhAiFcXZSD6FdMxae+U1I7H0lrcaReHgMS08CFjmSTmvbftQMI1xAq/yIQpksKgB8tiPreCFghBWbVRR6eJq3iS4YaVzkR2A40YBzAiI25pjQZJ6eZqnSJtdE7lxPPDLSEYNtrdAQo+C4M9zuZV8YGUGqPACGK1acFIQmg0ESTtSDkxCawjEAmm1giKqtCGbctaq2n6N2mXugFou+U6FGMDu1M7Rnz2d3j3Znm3k9FCPTvBiDQMAzVlSnL4JFj+Eo0hGR2FHIXvf+8nvLx7xqvdnrqai7A73DG60osaZipGuLbSaFKJ3RrTTS2VUKyP9PcUY1w3b70WbEjfDGS2YMQYiRHrGh0AlnGTJLEuhbo2wiGhfbCfJsbo1vbjr40RzEm4yzvbpPtWwetEnSf2SQikZP4Be/6amimmibGs1LICgVoNN95wZtQUIClaXrsIpCnajFSYp9nKLarZ0GuzGrHWPBt905C7Oah1S/5rvfvz0iR+MdmwNoelwzDBXkOKHUwCGH4H2rdkwcHQRkrB8lT6JjfsHtPx9d5+pge30gkhod2iJEMw5mL0YU3Xo/um4BpMhJYiOc/oCMSYaa0wNDLNE8tyRsJkZArJ7LqjEneZZHIMG8gSqM2G3XldmOeJ7Npi+7cjA8veDgixW29fGQ1tQj03ZGfX/bAzAiscAuswOEViRKmOuQWyCnjATtSJTGXLIo+jsdfEkB1VIbvsSEdFYoMd78inzVbsGHzAtlM35qEIVZqpA8agtYHm4L2aA/ogh2id4iIEjaQeSCMSW+PNZeFxWWG4isTt3XESUgpohhY6PSqkSNSMVrNNW9a1qU5ij1R1bGeASOCshXr+0mSIDHQvxIAdjD60QxIvHbYDoPZGZ6K3xgiB3i5o3kFwQ5ZHIoS0I6hw6Z0RI52IpGjXeI2ciqU76qiEqI5z2+9syHAICFrHTDFDKcNw8A70TS4o0W45kmiSHIePdIKVIIfEdLhD8p4mO4uCqQMdC6NU0rByg9PDyrOx5/y0WmZHUVoZZsDqIMHKE0YZNKolHMZBT50UJ6Y4WyF2z367csz1KwNbu9LXxqiNdl6tiLqYEEDacPeuRawOhceHixUbNeVhfeJ4c8DEsYE8z5zevHHddWOXJ+Y0cX56QlQorbGUrWnIpHK1FTRa7klZF+hQ+kJME+dLYbksVlTsOLcyromA+93EGOqE5GDjuuacYAyCwpSSHUTTzsoTgNYq1eGVJP5v6yBLpLaVlJJlE4HrwIUYhdPTQmsGlUiKMCz/foqJeUrMu5naKmBYe07JycxBrxVR5fZ45Hh8xv/4P3y92fczPbhjgC1QSmTbnA2D0quYXl06BE2VOR6QbVCpGnLtofNmpumomu64i0ngRmkM6aQpUZpcMa7R7ONtdEbpzHFnxbR1EKev6Ip7d0cgtqliZoiyFiMzVVnXAjm45MzrlEKgNMChkxnX33pJqZJIJNbRIAxUE2NE+rBwfxGB2EGqkX3RLb9gP6z33Nl2G3wo2sfyFO1rDlehDMOuTUEi/js0zW1UYY6R2JTS+jVfmmiYXoiBPJvpSQLmdYpC6F7eEALEgPRuP1eA7MSc6eoxpyDeLCPiTL2rFYJpvDcnmoJBQZLcN2IwWBlKaNZIosFQ5h7MoTccu+7+cYnZzBIIiMEW3V2DQ2x4b5v25qLcsO/hDlgNct0mbaM0ctAqwQxjNxmqK3qCufuKTMwhkx2CG4th17VVQlGKdGIfpJhBlWV4uJPa8zH586TLYGmmbs462DFIKKVUctoTxDbvLY/kq92ivVruzCid0Tut+nNomGprDMOWR4dWiz3e3Yl3iRwbls0tHhbVDYiapokcLWVwi3eNMRAjrKWjHXKKlHVF9xOtCufFYBBEGKWwlsWgPQbTFKkVRgdJkd4rU94xRnWlRmeaE7t5ArUMcZHAslZfFswj0ZtxKylY+Fv0NMspeFHJiDjOyu3xSN7PDBoPjw+knFn7IM+Zg0Te1k7Vzs3tkbtdZiCcvGBaxG7vEiEOuzG13rmZ9ux2+WvPvp/pwf0OHrG3Tf4XwrYl8o6xdeLNHoRxTQALnt1tNlULoVKHSXRYiI8mw95aMNvqKIPhhpcw2RC2rryBVpPk9WrY3rTf0UZltE6ao5FQoyEjItGImJ4s2S6IUK9XT3NIBlHiaNSh1BjQbilxqI2DRQNZEmEMGMEaSkibmdOIKECCG679tm46JsfjMY315gyTqxrHQbtgJpttY2cb2BJdCWI69rllRmzUuv0uLf9Eo8EakiLEYBranOzwjEq4bor2cG23JIYN+Hct3rCx84oRsfbwG2xlVTT2gw8/mIebp7qaHK2p5bUQGmhEkg3q7qobS/cz6lI10vx51vpwt6SRoWMjUzeycmw4Oahuv9WvQnjvEixFAk0yQTJCoqqYpj5ERsxGIKpLL4ttb0Gs3d1UT91wbGyASjcBQ/ADIEg0u/uwMo4qjd00MaLSwmAKMzQh59kiBIZeB/ZGUEofjLWipUGx0oKydjcp2RBKU6bXQYiJVmxQltYIwUxCF1U0ZVJpxJiotXGcZ+N70ruQNxl2Sxa2qkHDDEppfvOr1N5d194QnJ/ApLtjDCQYnNcaBvmpsi4Lu91sOnLPu2m9o2NQ6uolJdtz3GAUHWYCyjnaoayWhxJR2lq4ff6MF8/vWNaV6ovY9jWOxyNtWWi9YlWFhU5gWYtBLiKkmFjWQo6TFyc4myyKmze+1tvP9ODetJzhWlG2ZXCrEwDqkia9srx9VHpPxJCAToj5K19v2MkrQriK4wxfk2i4tLWCuPRpdOuTFCF2zzHO0NdK2rkLqzSYjRxNaiE4RgYNUgrU3onZCCxVM2nUASkKpVs8bNBEkGHbt4spdGyKBCe6tBtuoBZwtM20SL7KJgOKeHbFdt5t8Ue2SRvGbX4hHzjtK3bdEHzgexIdcoVciJDmQNy29q6OPZv1fkSFJOYi9QAqSaZKMKmlQhRCNwJvk06pW3+s2cYei+EYrmLcxDVPRo3vw7FCa6wx3sLuVmaQQc0Yw2ioWqiYitdX+WZdUUSb/x3LK9liVLtsChGXNKqZc3Rzk/rjuCX+IZvk0LJHLMrVHjvDy131FCIxJLZsd7Ox+wHWhKgWRFb7Ynj2Wul1eGjUpg8Ozp0MU9eIqaEuo7KOSuzCcdqzz3v2xyPdVUuumYQ+zChTC2W5sJ7OlFIYXTkvlimuKiaFa4Pm/36rFnDV2iCpskihoLCDOXcO+x01K30pTHEiRnMrSjfreoiC9GByzGHb8GWtDDdZbQoSxdL0EGVdK6qFGLFbaa2kHFhroa3VAs1yoqzFJKS9MoYdLkYEylUJsp8tLyYm68zcyhDEt2xGpzMY0im10luldDPk2XzpqBrh6fIrau+U0RkOse53B9hcfsNy7mtt7PY7pin7YfT13n6mB/cYzaysmyJBLV/A5IEehsM7jbfIwEBQ63wUIIRGCJNjYSagN5bAsA0Rw3st2hHLEdFhumWsHFXbO+VE0GCbSGtusrBAdw1KXRs5ZQ+YCqRgeSYiwSsqva1GrMyhdcPYAqaZvXQhDtMRp7Fd4900I9E6BTUZlCMeakX3OSY+RuyFmlO7Dr6tL3FTc4zgmxugweR1tsEbNo0aeXnVqrsWXoZdpWMw2MSXThSznQ+8HzIZPhhGsE1L8TRDt4Nvjr1hiXwEH9zGW9njGTyjxof2FZoxWZARuC77U4nbN2LPG+xgaMPCihiVjsfDIgwJfgszuMjak1wahl6VL9uQNvmz+OC2/z0k0MWrvwi2BITsNxaXA6r4wHczjUcm4Aogujl4R+mWdT2wzI42aKVRl0pdbXBa4XK+pjVGJz91KClltKkNsA5U0+C3qZJzNDJ+KFqtz3TUSl0vLHXhabX2nloafYCQiVbJw6idXhp1NdfmWgpb/dyyrjAgh0w8ndnFHc/u7ui7xrpciCleN3Tr6VTalsXtN4y1rvZaDoKI3eCSwzSwBcspIdpwDgFynhm1kKfIbrczSE38cO3DHvOBQYTdcPGUkiluYroWDevo7Pd702Y3ZV1X8i7TRuft0wO9NtZWCCFSavHXRHdlmjgXZjc/CcG/F2G5LHZotUqtJhy4vTnaJfgPSnWZ6rZ1GSGl4Bu2Y5+6vVZtvRxDiV7ea+qTTVnSkJCtH45hp6H3MQ4sFCfkgAyL0xzYJiSTwRRFC70NYkou7xNijsQUWS8rPXbSIdFqIfVkjHzPltGNsd8khaakHOkCVUAkUUa3ATVMJdK6EVQ2mCIb5mGmlUhEzLyBuDPLAtqDW29FguWBEMnS7eCS7XDjqsqwunIbZIY9vJNKQrwW9DJMYdE9UZFofyNOdme5NpRHZcTBViawxb6iLgvUd8qATRu+GRfi9jngSg6xYuUIPWyh/Pb4WjOaaeS9P8geezY5pR1RHS9PHsMhjo6OSI+C0umafWhzzRhpw9P5PDfE7ENWHwZKU3yTNnPNlreNB2RdpX8Iyrsc7i2/JImZqdj09lXR2hnVMqlraSb/K81ghAY6tib4ZJHEapka8pUu0ploz30s+VKGDb1aiklAA6Yc6R0LZen0VihlpfTG6lK1KObypNmQ3WrIrLzAbNulVGQyfmCsjQsLSQLH28QUEvEwM1rj8enRSGYJnC+r+QY25QZmJCq12Tbt82yXEzEKrYV3ZLS5XZCozNNMbQWhc3t7Q2/NOSyTY9pM6HRt9NYMsw+bsSZcPQIxwrwzySE90tTc0nk3Gwk5GmtZ7JLkB47leotLRcUDowx7CtGid5f1DJjZx+C3ys3NkWmORsD+QUkHxBsltrbmLSNuG9Z9g0nYMNJ3/YsSkyOStq1Z+asHwgxPIRMYGk3TOWzIquPEGjxJDbvKDhm0WpnSZENoWEpgbZWY7ardMIuvJoNlRjfIYvgNwVqxgulvVczuOxqqLg+TYIWrBMt8QH2+Bs8WgSZpu6D7eDAG2/Tgw2rQkCsuF72KK8brawDEdMxxsqGnbnCx35XtsSLxuvWaIc30zjYw7fcqaoRoCJGYTY4mAbO70yw6AFMSbCSo6bft8UNBXG8nQHQtsoqaRT/4Nr+VGUfHmIdlvrzbjE2LPvzu0dQw/E6i+WnQCIgMujaaZNNVj0Cn+tAWh0DiNQhqg4S7vMNl7aknftsyrbaEhGAJkDrUcircNakS3WDnhbwhkmJGug9Ezw/B8e7h8ERdB6PzLn+aYIUgQaA1+4niRAxCJiFBGZ6GlzSa5rpWSochzeEZoA16MaihrPWq584hI11JY5i23TmVVhVRu52Zectljb48qcJlrZzkzCHu6blzPB6RAF+8eculnK2Mubu5ZzRUzahT6koWI7XnKV8PiT5sqZom65AcoxHiO65qniZsMWuE5IXODrkNb6MZw+JorQnHul6tKLjy7PkzarVo2loKpQ+Ot0dCEOpS6KVQdDAfd/TSqb0xh4xqd5miXsOjaqloH7TaLK+7NnPSFmuin+dMb8Vuc39gBrdbneWab+zXJzbYhHcEm4/0MYzVnXAL8GhAMC1md1u42ovWMrWNZBxj2BocfSsd2LWoqYfGDBu6rZFCJMbkqpVghanRbgC1VEvx2xLRsn+fbo7RtgVPbQ5ku3IHFUoXkm7ko+GZjUiVgSV8RIIOPAAVQRmSPPBGELpj31b6OjSQtfvQFKLFg5t9X9Xda4JaAgD4wWddFLa9D91+704eKleOAYGQLHA+5cQ0T1fi0wKsgpGIsuHrTjhej17/Ov49I1iQl3Y0+UHiMk/10B9l0NRUJF1swzZCUfzq6s69DUrAygg2mKOLpQs2BKRTNVCDHYqq8hUu3H83klCHQvR/kkFCSAQxnT0IEm3jtV9mQoP9HRFPXlTM4Tg8QtfbgOhm0IhtGMbf1PDkYlzDFAMxRNImaPeyCVFTmEQN2y+R0TthRCIBrc1ifbW/s7g3U5GU1YoZtEHSyOQpmiEKoxr7s9bmpKL4phpJUzI45pobFBkNni4LMdxzd3MkR2GeJp7f3bK+XlnX1duhqg1W1a+0wFugU0oJGUpKQs7ZITIb1nQjdlspmxaBi0MSpqtvSIyet21czYiB0bvlwPmtfYzB/rCzxcUhkzEsmiJFoRR7IVzOKxIDfRqEYY5gw8jfjZrRh8lQmey5osK6VpZ1dR7Db8HDjFM5++d9zbef6cGt1yHhtne45vpuw2iwCSmCD3LLGKh9EKVdbe/IcOeUv6i0+8YU7KWv4lu4KxgEI+B802+uwkgaaa2RR2ZrlpdoOJhEoZXOyEpow4hLcHWE+jZvB0bFMhcMHw2MIYhjgKbcywQdFE9UkxAJkgjasTRvd33JcDGa2/Id6x4+4LUrwwyElug2TJwRklrYVrZtsld7QUWPT0VNpy3qEg6BLp0mnZHs9x9CsDyTKIQpMB0sfL62eg3U72oJfSbz40pIXuGfjVi2X5Hh6erJbAFr+Yl245FNYaLmRN3gkOFYePfUxq6e3ihCU9Mh9+CfG2yob/Z0n2d2sxDf3jFcWl1VEzAychvgiJHfGiYz1CAY45vYcr0V03abOCUS1Ihv7daMvkWijuZbYu1QLbRrNHuetmYlEhLElgU1nXhQU3pIw49zK8kwzbNzNl0Z0gzs0Y2gxIt4myUgYrEPlscuqBOZQceWFUbKmeoKDbADJDRPxvNcjlo6ZSl0bTAat4c9IoFaV3bzxNAj59MTrdk2KmL+CdJVgUcphSQwz9kNh8NTAu1wL3Wxn0EC67pazGzupJToqtYKJcI0JSMQvVYwBHu9gjDNkxU/RJ8Havj0zWFn7tFmsFFpjV3cGVCptknvdjvqYiFRIQRG81uYWn5LdZOOiPE6QYQQzd+Qc8LauOLXnn0/04NbHGawbkezjKt6mJPYNTuAY9pgJ6tZYSGa+00GvQs5m1vKsLCBqEmqVJUpT9YXNywWdnSTYxEtjCntsuVdy2BElwY2k50ll0FJsk0uBn9xdisF3pQoW8i9udEtQbAEuzpbqJHllQiDOtRMMhLomqjDIJCYTH2yhVxFTORvQxAQI7uCD5skvnnRTaMsQuqgUSzCJG5bNx45asqD7oRRkODJb/Z7r9H7FYdHCwTLMMnTRIpyDbQfdJp2g0lEoQ+7yvtGr94e5P+wX3HUA7LEUv+i/zzRtm5BLMtZBXUCVwdGEIKTiGaOMhzfFB2CFRPoGHSxSFd8M+/b0PfDgJCNBA421BlWwNGzbcgxZOpw5Uiw6iEbzqYYIUbnTBTL7nYppShJ3GjVjYhDLf+D7jG9Do2MYbeOoHIlKvOcbVOPttmDGaXaqAYJqdvX1ezmwQ+uXjcpmul6GBgcon5z7Wo8S6usFLRDktkgw9bojnUnDcRpx+W8EkZAow2qHBJ9bc7PBNZz5XV9pFOYwo5lbYh09hEqmUVXthKNroMEpuQKmdZWNCZCj9AaKUUnNpsvcOIQm1JWM/PkeLDLTW9uuBuspVBdqhu2m3OD/d58E4K5Qoc7XzWZe3e9FGobaG1MOSHendmxW8AuW1zwiPYazymSJ1v6xui+nFiGeE4mIDhMGfqgUpj2Myp/QPK4QdlqghDvpVO9koe9GwwQJTrOPcx0cIVY0lXK05o92J5l6piZbdpDC0gk5eQKiORh6upkpG17vXdCD2hSs+KKFwdEG8y9W25z93txSEaUWdi6524MsSS1PhjJru5BMirV5IQIlYjFziZiMMy04waTkFxRY5b44MDzu0iPYRuTY36mhg1kug89m5OWR54sGTA7bt2dVHQcW9iidG1z1OiYv9gLjiDWNpOwPsisSPas82aH7vCI1+tbEOs7dEUPBM8/v9LPGERs/64hA7bx+2Jum7DDTHwFbupbE7ih9Pa1JPqNSRyTdaiFwZCvSEWjQWsqCfWDr4vSQySoqYDqwNIIQ7pi3JYZ4qujRH+8HbP+SuFHEus7NRWTOtFiw1SbJ/KV5sYYG7qihmtHTeSUTaJ3fQ7jckL7xUg3wrKvZsGOEpFmz0sNzouoWH/qsBRLbdDWZi3mA7eIr9buVKzEYy2Vl7sbUHjqZ7uBqS9RmOIjRKGvhRgidS2cz/BUL4goOUIksd9P7G6fsSyVp/PZfnabyHaIDDPVbfwNaml8fZjkUXwpG32Qk1WaqScBjq70YV2Qm5LDXNWDGC1DaJ4ypS6kMNHaYC2Nrsr+cKDVYiajZlCOqpLyOyXafrJ6vRCFw342yLSYyqX7ph/w0o1kgXaH44EqUFpln3eklFjr+rUn38/04N5Ix6GGS/fhDzRcw53AB6rjgJYJMFnvIc5ke/BECBa8D2I4WN+aEnAUDwi2OW4b37bNpBApw91RvjGT8OQ/J9SG0rRSqeaMTPJOVeG6ZFVTCigmO1uxTd7qGW3DEzGDkBAR7exDpJOd1HSkzBfV4IN0wzyHDIJ2RAd2sd7CJSP04cFPHgQ/7OdN4pI8aQTVa9FrJzh56ANzIwnVbxE268yAk3y4BttgpAljfZe2Bv75oi7/4spd2O9/O5jxECW9molUOhoCYSgyEhGlqg9tH9jbwzd8UKsqGtxA5DxA9UwRBMOneafHVhJdh8nV0u5KThonGRAnIpuzDd21/4ITlWFrebd8GPFwMoIQhz1/ppgN1lJTaMQulgDpbTVbUYIpQPz2oSZJFVejbBruNpTqZKb2gRaDzNpaCSpW4ouRlCGEa+OMIowGoWME+5bXraAd1lbIQykezvRiPjCFyBdv70lqEkfxrJfNidmatcHUdSEfMkEDu32mtIXeB0MrEoTdnAghcVlOVrgrRnC2TQFCQEcAUZblQldPgHQ5iGHWEe3tarartbKWQnNz3Yahbxi2dpjmjIhe87nXpVFHI02RlOHy1ChroXmF2ximILOp0JlioLbVomRjRMcgJlOWTSFycQglJjMqzfPM8XBgWRbAFCx0GOc/IIOb7YVkeaVmc3cdN/ouF9eS/txeK6YesKuSWIyrRmIw+GPTgQ93MV2DXyRcY0XF5rzBMcGvc9Hx4tqNvZdBVO8SLE6YJjcquLa6JTbOdDtjbNCrb99qJU+COfSyBKpGItk2bTH5UQWyOKkoZgowP5IFZ0k3XNb3RMNF6dc8a5V32800PPTHyQFLDIyWbNgNH0/RdfJYF+DGNbDd1B2rliDW6xeweNkExEESC53SPq5hW/bLtqurRHscBDzR8N1hZDd75xnsYfGtH2tIdyIoBahquhqAq1kJYcvUVrXt2w6K5BGlpqPf/s71qaYW3zkksLRGDDOSMhUY6t9rMPjFnhh2LNp1y0jMYD8YgmEeV+xeIEdXEfnf1zaueTGtNDe42BVeFKKI5eVovGZki8LoQl2bPXdKo6zVvlbVazSrqZW6lzZH27L7uwMgYPpqs7sbAR+cHZFhlvkRoz2jxuDx8sR5WQ1GaoOq3ZcbcXigMc2Z0SOdwe1x5r3nz/nRpz/l4bIgMXLc7ZAxTD+925EnpZYFRWlqZdbdM0WCWJ+kYiXVMkyPHYOQQzDIT6CVwroWI2TFqt16M1guehroNCXef/+FkZxRWJcL62JpofvDnlE761pNitnsRa/Y99maLXky4HJZOZWVvIkSxE1DwwKzNllsytkkv8Oz6VPgsiz0UojjD4iOGzxbASME1JAHk6yJk4khmOlFB6M15nlH68OGfAg+qI3pHwzXdTubHSdzdBHs2YK5IaMEL6u1gHV1dQmYBJHqDc/RVkL14T5kuCLFihh6lXeHi2wbqqDVwpZkAgK0mBC1zslMpwlEUbKbgmq7gEAMiS5qTxQ8T0J9c1HfunlnxDE6zbZmEXsyqkSiW54Rse0uiB9YwtAKDNPDe1raECPMcOjnOq+i6XwlCzKJwUsBiEJKVgygwycX238ZeYeYkQN7l33NJqYT180ubYRZCHYjiMNiVCPQXIkjKoYx+xfqKn7P8MQ+v2ojIHGyG43in2dbuZUcRF7c3vCNb32Tv/L9T7h/LN6AYmRyd0gihISl70U/NFzH7dCJ7fCBPqyRPUXbc/MukWN2Wb6gXSwOoVSLTq3d8dhB0ECWbJrlEOjdOAiG4eB1tSz6XgfLpUA1xYq4o3Yrs9X0DuraGtF1WF78aHZoMLji6SKBS7PneBY4r4U3dUE0Mk0T61oJw2CYsD2mQJ4SXUByYDdP3Bx31LZwvlw4X1biHElduJw7pdsillNinva0XnEO37sZG0PEMntk+CDG4RTQNIzncdkvDFeFqS8uflMR85LdPTtye7OjLJXz+WIJh13JOZMk8nRerHatNYP/BFJOduAJTGmit8Fpsc8boUMKxGACxON+ZwXVwQ5pVbPC73cTx9u9mXZKgd5o1w3mf/ntZ3pwd3X9ZrOsUotsVQt075s3vPuJa5GkvRVyMsstiJFk3bijFANUzIQjMOdMjMkavCWiatdsiYGRxF/ghv+13tAgtNUYebvCQcwGz/RgeK4loPkPEMMVbrFKM4XZlCeajHDVAUtWNE8kGiknC8YhstA4xEzIOxgLa18ZumKIa8dS8sVVC8kEcGKadVHLLolqZQYNs3inYYdC7zZ2CoGJwBwGIXbQwjoaE/Z14qbgoVMkGqYtQo4m28o5k1MmTokQk5kuRifubbC2xUNT3Ooesss4MAycjWhXAcfHB2ZYEsH7KmFI8luFIDESO8QQ6G1rSoFKYmDFvxIC3VKwTCmi0DDIimCSS3BzTIj0rvz0/olz/Ql/5x/+I1xi4r/9nb9IChODQJHA+89eAMJPvjwh7l7tkgkhMqdMluzFEsM12pY9st/NHOcdu7hDRiSlHZIDcZ94uhSkCdKEpJl26SQi0S3wvSo9K6UVJwKFUjrn84W62LZOM/IzqnCYJpMJpsgcZ3KYjHNQoa6V2hp1rayXSh3dIRwzz/Q2GEuHDp+tb9nFmX3ccfaDYhez8RwNUCVLICYbdjFbkcWchTzBTz9/zalWDseZ3WHi/rJQl5VSCvM8sU/WrjPlHakGTpfFpLg66F09z6YTvIBAN+dsgbubncMijWXp12jZ5B2kEox3ev78jlfPbynryusv37AWczvudjP7KXP/5oF1Xe34nSYPTBOON0dCDJwuZw5p4vWbey69kwdc1hV2iX1MplBJE6FYvrdIZJ5nRltIKbCfZt4sb+lA3u1YTg9fe/Z9fXP8/w7ftqqfdyYcJ5y+Ohz94/Y+/comvsnNts1O3XJqONWcM6rNYl97dyzRVSFqVU7W3qHuwDNicbuOqZp6YAyv+RIhYIlywS3DrZkTDtc/m+TNlBujDUbxUHzPJWkKRc1so2FCYqaHCZP3ZjrJsG7JppCIk2Pf0Q06cnUBDpe1dTU9t2G2m4XbMNravJl8QCOZuzRZoa6kTEjGPA4iQ+M7YjBNxDwTpx15yqQpWwRnCkg0QnGE4Zs19iwMlheiX8GuDQbBeyY9T0W76xW5/tHg1naSqTk801pChmD/vSlGFDMzmaHGh7kGmpoee/v5jdDM16+FREpLvC6d73/+Gd948T7/h1/5I7wtK6MLHWW33/MLv/CHCCkzJFA92nWLIzALl3jMrv3BCUKDHYLlag9Tq6ln22gZ12heexaFa5pfkEjZLOdL4enhyaR3Va8wyWjWgbqVAde1Xp93ovLuY8NUJ7VYEmDEyM8UzfFZVwt7eqyFXZyMd/Gvk8Q+N/htyGrvjEg87GemKRMC7G5mJERq8cCnoNy7FJA+IBj8V0qhNbPHr2txc5G9TProVxmgkxzGcTWDhqZpur7ele4Gu+hhVEJIif3hwOFmz1pXSllZlovjdMK0mwwOGtY/mlNiv99xPB7YzbOZ3kZj9M7pdOK0nO05Or7C96jZ5NdlNZ5h2OxZ1oUcjaD85JNPSCHxrY++yWF3MOL5a779TG/cVizqovpo0iiT4nl5AJvG264+YHhbnmdjeYGUI615yLvrVXsbFrsYTYO7mWkAUtogCdxkYlgtXamx08YgVlMhaBj0qshsz7gUBEis5WKYb7O9OOUIzZ5U2gaI+hPfVR590GugTzu6FoZkmlZSnGjSiGlHpxLpVos2IPkVMWB1aATDtVuvRIVIJIxOMqcHquLNJuZK67pd6YUWhCxAsA1a+opZfzAiiEpRRUOyYtYUCCmRpx3TZDeWGCMhKGOIvUC1EmJEg6l5rqUXw+CkECxi1UgmnNj0g1fsd7TByV1mk+5FU3gwgok4NELMMCwbZdR3YU8NG9RmTzczTtfoZKbp9ze99ghC6xMxT5Qy+OHrB25/9GN+8ed/ju+9fuCnP3pN3h+4f3wkT1/ANBFq5iKRjKDN5GGJeHUIqgcNCRjh243MpptETkZEL51yaYy10JoQ2qCUxt08udQzWosLGAE4jEPpdYDXz406rth9kEAtVi9Xi7XjRBVy2tOqZZEs7vTTEQlDSVkYxTokT+vCqSmTREYdLLUhabhO3ctvYzAZnTTujkde3N3CGJzqhTbtmFOgrY3X6yOBQSnms229XZ3ErRVynFmKNdsYHGpRA1EhuuklTrYMMNT0/Go5IVkMKjPhgMEWfXR7HqbIvMvsp4jUwWWplDb8cLYbySwTD+Ns3oOaCFMi50BzGIkcuJwu3N7d8umPv6CPwDThjU8Q6qBEJWhk3wdrs37U2Do5Bp7dPeenX3zGfso8f/WSWQLLMGjl6779TG/cJid7N5y3ZMBr1oXiEIkxz1YjlIluctFhAztFYwmdV7sSC76/o9p8cFt+An7VBGPsR/d4yI7b3DvrWliXYhbX5nkjTixtFFBy5YLdHEyJsrkaU0gkSWSSbTIEy8rwrbJpZO22QTeNlgk9Ik2yXd2x4WTjPFHHlkSXfbPGtmwP9S8jWYnutnViSXptk+KpydzyfGB/+5xpd0Oa96RpR8gzKSZinshTJuaJNO3IOROnmTTN5JwJafZNPBGSx7oG3tndXdct0Wz/Es31aIYVwzI7Fhxm/N8WIuWhTkMofVipQci+fbvlPGQkJNu8/aZR1XO2fYg3xI01RgIPAiNMaJyRbHCJEng8Nf7mZ59yXgLf/ZN/ivnGeJO36+D7r99Qu7J2M8HocNmi36Rsu3YFSLMDNIds7sbhhqKBy86G4dbtHe6s3TDnLZmveX6JVqUstkn3PihL8dugDQPt9npopYNa4cFaB7vdHYf9LfM8I6rUxYZmKQVN0T6vLLRSkGE1YnW1zXaoFS+AHbQpZpfcwovbGz5+/z1SCB6JO2h1RYDL+UyvjSHBmoJKJzSTxApqCq1SKcVVFh71GtjUQIGQoj2/xHJYCJZK2YctLjKMCzHXLCBif2fORgZP09UgN0YnpowG2B0P1LERnRa9nKdE6crlsnBeL1xOC00H7909Y1lWVJVS3kVB92bVb70PTueTyVu7yW+PxwM/+eQnJBFujserrd6CvP6gtLz7ABziMEjYAoow6AKuUiHtnRECIVh3nWLxkCEEstu/v9o0vmnDcYWBaSg23TfmmsReYK13z+kwMse0pa47rgJJCT3QpUM26RdRDIs3nsQkjX1zJvr3DNccikGnjkgZBVFhCokkNqRopjOPkl1/7I46DQSpSLDUsz4c51ZlnzJzjkTp5gBrK71ZLbGINXWkYCW4KVgfw0RA8sxuP6NtRxoLrRbWYgOSVggpElNmnjJxmog5k6P9TDGYfLGJEVwxrq6rthuSbv8R14u7MkbUB7ziZRADgptrVKgdw8djgjx5ytwm+YlGxfraPhCqJobb4fHckS72M1TdWmoCg+QKnYTEQEwT2oVSG5+8LfyNH/6YP/6rf4w/+kd/hf/bn//vOO6PdhCq0GMgFT9gkpF7dNMZm+jb5G0BIaq5Hi3fRt/ZxWPyz7FWFRmGz2esgam1YbVldOpiShJzU0ZTIlX7t4wAfkdK1qUZ1LK75eb4jN4b62plvfubI+XUSCnb86535nmilcHbxyf6WlAvXLbnl5Dz5OouV6YkmFLm/ss3xBA5lZVCp5aFURspBm6fP+ft5/eW4w3kORIWex1ZONwg72ff5IVaiwWoiWnsY06EYN2RqG20SSx6YqmN0poPfF/AgpKy5Xgf9jsz8JRistbWkCDkmMxc1Ty7pJs67XK5cC6delnQJJTa+caH73N6emIMSC6S2LLEN9hW2yDu7VCe0kxtjafHC60PXj2/gQHLZWGaDoQQmabd1559P9ODG2zr3nDma56tqksCPVfD9dGCyftSih6Eb0FPthVUcpqNSRfHyccgJJdzDaWPRk47UwSsdq27bvnqVzbH2VtV00unwCi2TYZjgCbIzvAwHR7MA161lNiliUazYCeJV9VGbQOZAmUEG66uDoiq7BhXvbWpB6IlxgHSgwdJWc3SZrCRnJApEnohRiGmwHpRSld2YlfHIXZFLm0Q4iB3pXSQvON42DHaTG6NWC6sy0otCyEEg0WybdUSJ9e8C5ISOUBIE0Os6UfPCyrtnblGLAJWwrsUNcTw4Da63XREXWoWvI0nMs17247DhK6VWpUyLHRJNdpBGqINMjbbejRzjP//JkZeNjUViH3ccNs+IiPCiJEsE5cO3//sc16+95pf+kO/zF/70Wu+eHMi6ozIoFfIniFj2dhmJNm2Y4YLbAgOHXnmSjflzBiDXro9h4mkYLklvQ8mifQuVljRlLUW6qVe5ZKM4c8F2/JNrmpy1qh25Q9YWW9tq6X91WY8BEoZKzkazDPtZkYbfHY68bauzJKwcin3F0jylnPrYkz7TAjK6XJBmhlgJAfePj1wc7OzoThN7EKAUejSuZ0PpvPOA+2NMTopJ/KcqWuxw7q46kWVnI2TkmBwU06RZVkYrRKmbBkqYvnb3UsW5v3sz017fl7WlVEHtXonpMDN7sbq21zxo7XTGGhr1G5VfaVW7p7f8f7NHX/5e3/zWjwSENeRJ2/c8s7MGJEutFppzUoc7p7dEENgXVZizhQptux9hZf7X3r724JK/vV//V9HRPin/ql/6vq+ZVn4jd/4DV69esXNzQ2//uu/zqeffvp7/t4PfvADfu3Xfo3D4cAHH3zAP/vP/rOeF/D7e1M1c83o7wqCx9ZqoSAuTYsh+B/b+rYr1+onrqpSa7Gv5c0tMUZCfAe/9KFuFrAMkdYs04FhLstNmqhearF9P711RtV3brSu9v/dULFdgxmDKWR7IQ8lqrBLEzlY92UM0VLNsGv80qDUQVNh7cK5wlI6aw+sI1hJbTdScSPbGolGZoSZEaJ9TsjUYcl1IZr+sOFN4x47Wruy1M5SGqdlZS0VjTvidGQ63LI7Pmc+PmM+3JF3N6Q8QZzQkCG4LjpEUork+cDucMvtzS3HmzvStEOJlKZGGDKuppwNOhlB0ahIskySELywAKH2YWFNcfJNLRCzEag2oCPExIiWG7Kl8m2QycBicLfaMfWAqOrw0yDYASAJ1UQNFhaVUuTtZfA3f/pTLqfC3/Un/xRpOtD7MAJX5VokTTV9fysNLWoOVDfSxGHQmDalXZopQ6o6I2ytK3VtFjTlcEcWU8vU2ii1s14KrQ7WpbKu5u47TDvujrcEtaCpoEaKboUrvQ6ezo+cTw/c37+lD0Atk6ZrY58mnu2PBISn08rnbx7QDn1Rw83VtN0xWV9oypH9Yc+8m1GFUiv3pwunZeFyXrmcz5bTXRbqupJj4OWrO37hGx/z/Nktac7WFJ+2IKBBKas/D6z0d4gVi+QgHA87dvsJovL+B6/4O37pF03V1Qpau4WR1YZEIc0W4KSq7ObZTDlLobRGbVYMcdwf+M43vsWrZ6+sCanY77ZWc1jPKTksK3z03isYw4hnj4TYyoFLXYkxcjzsCGGrxbPHLUqgj26l1KVQSrXfVWssa7miBF/n7X/14P7t3/5t/t1/99/lj//xP/573v9P/9P/NP/Zf/af8Z/+p/8pv/Vbv8VPfvIT/sF/8B+8frz3zq/92q9RSuHP/tk/y3/0H/1H/If/4X/Iv/gv/ou/7+9h9H6ts0LlyjRv9VDbNWk7aVOMVzXJZhrZMpnnbGXBwaEK9Q1wy+Ho3bHDWj3yEbPF9v7OKQnXNMLgm479PSOMWunW0Vc6vZr2e+i7UCEG9DKujd2jD0LHcG6i5TO3LRsa1iHUYYOlubOyjUQbkToSxcodqWp/GtanRzDFRCNANCy4kx3fNZXINrRMzRIoTVlqYy2F01JYaoc4E2Im5Jndfk+cdsRoWzYhuQEhXLXTKva5ebdn3t9yc/ecw80tax+WGyI2kAfWAqTBpJltdAadPEVUOnW069AlJGKerb8xZ9rYinq9kCLk67AmRHrIroL5Co7t27Y6afnVg24rS1i6wygjWJ1Z2iEx8embe37y+RteHp/zR37ll7n0auSohzT11Yso2mYAseyRqAaRBIdHzBVpLtxRK30tjFJpl0JZLd61NbOtBxUz5LRBa2q+BEyNUmrlxbPnfPP99zns9gSFOdpCkLCkSrpJTk/LhbeP95wuZ9ZSKedKXyrPjjckDSxl5XwpfPb0xKjKTfKMah3XG91odpDupp2rOZS1Kk/nM30UJCbOl4XDbsdhzsxhgnnivVcveHm8JURhKYvFCidbmDZSvtZq7lnfgFu3f2uaEvOc2B9mdvvE6y9fs9/N/Py3vmHqEh2UXkmTwaJzTlZSPM8uUgBETBc+lFILP/eNb3G7P/Lw8MhyLlQPQcvJyi96rQiwm2fu9jvOfTEMPMD+MF/FC7vdzG43m2yxNQuVAvKUESxJdFkKj09nI5JVKd306yF/fQDkf9Xgfnp64h/6h/4h/r1/79/jxYsX1/ff39/z7//7/z7/5r/5b/L3/D1/D3/qT/0p/oP/4D/gz/7ZP8uf//N/HoD/8r/8L/lLf+kv8R//x/8xf+JP/An+gX/gH+Bf+Vf+FX7zN3+T8vsA58FhEn13temtGwSxZWD4cBY/qbfhHXMyJVkIXGplqYXDfm821rBZ5vv1wbjmofj7+/ANv1urhm3q/UpAhWAFqDklEhFRaxgZzbYVKyDwQ8br0GLwwuJhEZXi3YKqrkdeu2GdGmjDhsrahaV2qlpITyO7WiL6dm2bY5dkAUQhQpohZiMhw0QdxsAvrVO6G05CpEmgqhlahgcyrX2w9sGlNC6loxJoEszwk2amaSLkTMiTGZscetgG4QgRjclw73nP/uaOuxcv6eMrlV/qEsRm/lKDNBLzPHN3d8P7r14gU7ySpxpnusJaqx1kCGuzIC6ukapGUF6lgsFuE9vvaSNkt1aa5hLBrkIZTmI6Oawj04i0Eckpc+qR73/2hi+++JJvffQBN/sDrbo7sXAdbnQMLtkOZI3voC0JSDeOpS0r69OZy+M96+nJyMeuhI4ZXFTACb3uB7wiLiEcTGnivRcvOOSJsqyWGiiGegd3oxrk4MFbI3A+F55OF1a3YzOE83Lm4bzy+nThfC7GxywV1U6SwH6a2E8T0xSZnSsKboZaV8ukvjnaxt7H4MWrW148v+W9jz7kvWcveP35Gz67f+D+6WyknKduju31a6HlnjlkP68q1N4gQJqsYWHeTXQ63//Jj7ndz7y4u7UN2+MX5mmir5WbmwPHw56ABae965+0z3t+vOGnn3zCTz/9zGDLaDp+k0lCCBkJwvsvXqAq3J8vHA4zN7cH9vuZ25sDz+5uCSFwviwsayWlmda7lSPnyJDBcTdzOl+oXYkxo8PiXou1gn/t2fe/anD/xm/8Br/2a7/G3/f3/X2/5/2/8zu/Q63197z/V37lV/i5n/s5/tyf+3MA/Lk/9+f4Y3/sj/Hhhx9eP+dP/+k/zcPDA7/7u7/7+/o+Nt2HBdDo9UEwHaUNbR0Om7g8OIhlm2wQSGmr4VnDAmXGMFeluqFv+zywsoEQjKzs3SIatas1YG+aNXDFSGQ/WSbB8XhkzrurmiC4v137YDQzB10bthEzy4SEqqljarFuQekWziSDdzrlOFPJrMMgk6aJqpuKxDbr6ybpumSDCSKEzKqRqnCpnaK2gXe1Tda00fj2KbTaWGvnvBSWZbFNmW2wQ8yu347R9c/JbeZ4Wp5nVUsmTTvStOP25hZJroRpw4cJ71Qt6j2RHpV6d/OM/eEWi2q1NnbTtSeKHyx1QI8TBNNumwkmmzokZoOBwmSbuA/tOqCM4D9zvOq7VaJBOH1QmKgEdGRUhLUnNCXenhZ++uVrYml8+xsfe+xtIGm4qjk2rbQMM9OI6jURUot6qJPSS6OtC5eHB57evGEsphmVZnnQ2nz4u/16Q8pRqLVxc3PHlCae3t6zXBZ282w+B8U3emFdi2mfm3B+qixLpTRbSO4fHrl/eGIphfvzyuu3JyiD6IfqcX/gg/ffYzebNnuXd+z3B3Y722bHaHQdvHzxgl2aWS4LS7mw22Vuj0d2MfPXf/B9fvrJ55xPK0+nCw3hfLmwros5FDFxwehm9a+lWszu8K7RaEN+ni3i4O7Zc9ZW+fz1p6QpGdekFgugqsScuD3e2OuazQTnMKgrTJbTiU8+/5QwW0drr83ngidWBssavzvseP1wT06JMCdubm4se3tYB+ayVFqz9M9aBiFmUsqU1lAxwUDtICEz550vaMo7Y8LXe/t9k5P/yX/yn/AX/sJf4Ld/+7f/lo998sknTNPE8+fPf8/7P/zwQz755JPr53x1aG8f3z72P/e2rquf4vb28GAOoz6G214tE3eLGQVn0LWbScbhkGzh0FbL1CzKNKgx9Jd1NUmUBA8mG7al9WHssFiCWG9KG82TBYdZmZvLErsxThKE3W7ieNgRs6UFjpB4LBc0+BNPNo21YV4Di+vcpUwLg9IqlrpnxQ86LMlPrfjPHJ1TQtRsxoFA64Woja5GTm75vyqZqJZ6QppIWYBOG4VAoFczckgUuloAVu3VDynTTOMmhqUMprRyWi7szzue3+yuByYhM02RMbKXsRpBO8QUHpImQoxXg0okMc+FOE0sp4spavqge6aMdk99C8JjKXC2kK2tvT1IMo+o2BDvPdCqOFZtFWk9GBmpWNohQ33eeQiVbvrtiKrQN3mhK02UYBALGVWDjSygLHu0a6A15bP7Rz5+7zkfHo98Ns2cTxXCIEqyQC0FbYO6Wi516lYqN2pnBOipEBVS2LOUE6VVc3iOSHZ31lJgTzYZntjzgWDqJhRiTjy/2ZFr4394+0CYEq/2N5TThX4ZPPRmEFdV8l1Eu3K+XOi1MaeZ+9PJMHkRlMTpdIJinai1WQzDzX5HGqYFP7XBysKOzGF3ZFlWHk4Xnj878qwNvv/6S758PJHGYD9n4og8rW9Za+WpFHtNpWhY/sBDvFySG/QKf27hTilnc/4G43yaduIUaUthnhPnpZLEWnRGErs5tsqL4x2lWonBvJtpMtDUkR5pa+Hu5cRP37ymdCtwMAjDJIJBLJaitoVXt0canS++fMPdzQ05Csu6Fa2YvDambCUUzYKuWCDHiHTY5Zm1VXKYyNEiOhLKeRS6Dg76v1Ee9w9/+EP+yX/yn+TP/Jk/w2739aUrf7tv/9q/9q/xL/1L/9Lf8n6Rd5jyBpmo6rVHbpPlbNe44dKysLm6BFKMnitseFROictasFDzAQRnsieTJmFSp96hja1Iwb4PiSbeChqY48Q8ZdONZoEJLg+V1QeyKVeEHLM5qUSIwbeu0CFY5kNfzLIfkwW+B8fvo2esmNnMVDIpTVQPBNJRiJLNxj0qKh5FG5ThmlhiYPTC0ErQRJZOVSUM6xMEP1zUDDqiIB1KGyylsa4L65xIAQaRHMwlGIKpohmexRwFiZNFEmBwhQQTOca8Y94fuZxX2jACR4NcVUDij60KrK2z1kHtSiWRYmSIuUiHb8uWpCKuy94UI264kcSInoeoJic0dCvSnQ+wjl5P83N+IMSZw+5A7cLD2kwbPjyPvCe0C2/vL/zNH3+ODiMDU8hIbZZsGxOM4Zt2MFWGb+Fk254lRSKRulaDMpqZR3R0q70K2fO5lXppjHWYoSRACrCMxt3hwC7t+OzLB2op/PwH73EjGY2Jx7hS1TZrnTKTRsszaZ1E4vR0YQu9QoTaFuNb/NYwzZMNsDp47CtNItNuZp4T05Q5Pb7l8zdvmfLEe/MNP3rzI87nE3MONBnMIbO4YiSGSI7RZKbZeBcJQqwVjUKMhgeP0eit2s+NMhrEObGbMlMOlDqu0bghmSNyjMHaC4FEr1akUFqlLCtNlJATvVXmNHG+NFqpHI/v03tjN0+U1ZqZ2jCZL5gKLaXM7c0tX3zxmmWpMB7IU6YVu40Pj5FutXkaqVUeyqqM3SDPyRqvOsy7wDzNDIEp2bBe2+C953dfeyb+vqCS3/md3+Gzzz7jT/7JP2kZwinxW7/1W/zb//a/TUqJDz/8kFIKb9++/T1/79NPP+Wjjz4C4KOPPvpbVCbb/98+53/69s//8/889/f31z8//OEPrx/7asnsBmlsxaMW6oLjZXjglG1sDH2Ho+mgdSPeaqnklN+RGK7/zCl6aM3WJmPHrHRLyLNWEoNlYgzM88ScJvZpYk4m89tPu6tVOUkixUSK2aRgztIDJEm2+TSlrxWaR6l66A9NGcUkid2Jx4qZchqJ0obDJYkyomO0BlVsaorqNvgyAnXItZF8IyNtAzWooPv31dVUHKUNLmvjdCkspV37GDeJ3dYMgwS2HOoQzQov0QYoWHBTSJnDweCSTrBKsc12r2bT3zof6xDqUEQ2jNq+347b17t6a40HQ/GVSjGvFZP4DjLRkBgOmQyJTmoGV5LYH8Wutm0o8+HIfn9grcYHtBagYU3nC/zwx/d88faJu7sbQo/MafIbW7fYgmFD2qzv0UOlTEbWq9LaV+ATDU5oW2HBcjE1zy5mqn+NUazcd4vfffnsjnpaeVgK7z1/zoGJORhxfLyb+c437/iFbz7j5lmmR8vV0Q7rUlEVO5xjYq3N5XUG70z7mXk/8fzlLXlvNxIVMWhjLdSy8HD/wBQz33j5ijAGx+OB95+/5O4w8/HLFzyez1zKxbTRMphnVxnlZLGqUb2f1DKDYjRVTnNTmg5FdFhBQUoE2aR9iZQsQ1gHnC4LHbXIVDVTT+vVqvIClFaY5szz3YGgwyKHu9dFd8vlr62ZAWkMoheh7HczIWUuS6HVRmuD8+nC+XxhWVaWZTXntgSmnEwGKeaK7d5TGnTw7O7OGm/UlThz5rA/sN8fuNnvv/Ys/n1t3H/v3/v38hf/4l/8Pe/7R//Rf5Rf+ZVf4Z/75/45vv3tb5Nz5r/6r/4rfv3Xfx2Av/pX/yo/+MEP+O53vwvAd7/7Xf7Vf/Vf5bPPPuODDz4A4M/8mT/D3d0dv/qrv/o/++/O82ykyf/kzVL8bHBbIqDhRJZH0kzhIMlJSrFWi9owo2IwcbAL/De3pRGZto2I2NwJwVyW11ySJmZ4CdbwPYZlaEj3LBJ3PwbPlU4pMkxKbU3cYluyiMkUA4N5ms2WrcacR/X2dxVynhnS3ZyBZUehnhgqjGhB/WaIGKhk/1kqSvRh1owcDGohe0AZw+3XAQmDijXoSPAt20JPDUtVw1EDzUqJe2WtFp4zT8n5AuvmEzUDjKrrxwV3LzrujP3cqCJpYn/Yk6aZZTlZnrLazoz/uHZ1xx2JWFiVNuM24hYS5QcOgeqwx6YMGSrXga4bFBKSS3+sZGFrXu+SwVUnZodPNFdyrOtCmvZMbVB7NJjD4bJUhQu2Yd+8t+NzPbFcFn7ul75DOHV+/KOfErzmLahAgxaNAWh0Oh2Naq0x2gkk1nqhLCuigV6saX3eT6ZXFjFHrUcr3N3c8OrmGee3Tzx/fscHx2fk9eKHUuAwZ+r5iVmFlzfPuF865fIAVellU1BFSq/2M5EdkguUVq1sYEzsn93QlpmnhxNLqbT1QrlcCHniD337G9AHr8sb1vPK+XSiSudlvOFxuZCyMqcd8y4xnpTgjsI+LJKiK0Tfco38dzklLkJwB6QFTXXHv42PGt3C2jaddq0VxSKNZStiqA1EudndkLqQcuD5yzumnPniy7cWMqU2O+ZpMqy9NyTAcb/nfD5Tame/29N6oxZzUbdufoMULSXR1DDRD2pTo2m3EoWn5cRh3nGuCy92d0iw2/MchN7OX3sW/74G9+3tLX/0j/7R3/O+4/HIq1evru//x/6xf4x/5p/5Z3j58iV3d3f8E//EP8F3v/td/u6/++8G4O//+/9+fvVXf5V/+B/+h/k3/o1/g08++YR/4V/4F/iN3/iN/9nh/P/pTfUdHDKGklL0JLhOjLZZL8UY8dY6i65MuwkJidbxUHXDOktd2e0OZkaJQutiyWC+HQZv6m6efyDuqs/Jhtbzm2csdWWEYZuWDiMVe2OKM6enM/dvH9EAeWdVxTEEsiT2u2y4qQyaGl49Z2uukSny9vJAuRTiHK6GitFsW9CqkAKShBoDjMScIiEMmk5kKUiEQWWkQLXsQ4JCX1f6SEQdjB6Zk/EAKnbIJWCgFpC03QhUibWzpMSlVJ7WRpyUGBL0aimJxgxbnVpMlg0zH5FsEjpiNlwahRx48d43eTxXHs4/YqmDOdjQ5PpvAroFUHXmpKwaSHFP60rrsLYNl3ZFjZrypG/6dU30YIFbGozUU4JLm5U6/Baigd79ZiKZMSJVhcvamY47YmuggWPKlFU5ny9kSeb/LIPYB/W9QhiNHCa+8+G3+X/+P/4CYQTq2gkDXt0+5/R0oq2NpBD2QpwmaJYH/bheOF8Wns1HDjczrXReL0+EIaQu1GLmpCCRUjt3xx0fP38PWQERPrq95Vl+BinDWqkyOD1c+Os/+JT9/pa7eGCqJ6gBOuRsyZSlroQYuZmPPHs2c9zP7PcTl3Xh/s2Ft68f6HfGecg+kGOi9cbd7Q3fevUha1t5e37gdFq5rIXde0f+yDc+5CYlvv/Tn3C5FI7PLHnv/We3nJ7ODB0ccqL3zpwnRt7iIhqjwRj2nDLTnGWaXNbCpZhmfV0LrVarK+uDl3fPEAa6n7yztRsxXAdNB89jop0uXHJgups5EjiXlV7hOB95upzMEp8CMdmte60rOQqvH5/IeaKWQkcJwYxRIU6mNHPp77PbWy5r4byshJCZFGpIlNr54PkzfvTFF/yhb32TfYC/9v0fMU8Tf+hbH3JZ3n7t2ff/defkv/Vv/VuEEPj1X/911nXlT//pP82/8+/8O9ePxxj5z//z/5x//B//x/nud7/L8XjkH/lH/hH+5X/5X/59/1sxWiOG8k4Ab0SNS0LYoJKtSMHCeII7JwcWqK5YN2SIVhgKQggDVWuH1m7kW4jBrr1i+OZg0EpxttuGlTW8B+t29N7DsjaLpVSsKKF3ZIuIVauhGgjaOhoGKQcog5Qj8zTRxszlfLEhHUCDXm8aOkxeJl7WE+dMw+I47Rczo1Q0zBCNBBL1jklvdRGJTgyZnjkGU3WYYSBc1Tg2aqN3ArrEz2utCGAdmO5SHR1xJchmfAneAmNtMMGukwPTdD9/we7NW06v7wmqxsDb3n2VdG6wiYRIG3aAtmEmpD4wjbZv19vA3jJMhjhp6SoYz4S1ggijfR16SfZHhTFsM68aoQXWU+G4nxkKl0uhrx5lMAYWvhC4nCqPX565vb1hFw5Mkri/fyJjiXM3+5lnxyNvPv+Semns9kemnEkhMYo7HuVdjs35VGitcr6sJIme0W0JiToMpjvOB3aSeRoXmkJv8Pb8ls8+/RHLqXJpg8fHM7fHW5CJh1L54unMei6ICFOeSDmyC3tSSszTxPl8IkaYsvDq2R2HPDHlwNunC3UMa09fF26OO57fPbfhfn6i02lYCXGeYLmcGX1wWiuXh4U5JEpbeXx7DzFwPB65PexBrYzg4elkW/QwUxz4uY0Zj7JnCynqslthNOtRTXmits7hMFEW0233Uql9MHrjZt4jQTh1S0/sQDgcTGobhHU5k6JwPJqzEYTTeUFFzEg3rLMyiBnFwggEh1S3ZNLnd3d24z8vmO5t0Fwi/MHLZ6yXhW9/42NeHo/8tb/5N1hL53ibeFovLJf/H6YD/tf/9X/9e/7/brfjN3/zN/nN3/zN/7d/5zvf+Q7/xX/xX/zt/tO2abv8L4RwjW3Mfl3ZhlvrypQTOed3UqBNuufN34ZpC0MbKe84pANjXGi1IQSyRHq34J7ujkxV05fGZLGXMZhOXK6GHWFrjr+cFxAx6AVzR2odkMLVvCNx0FulR5inRBwDaZ2bec99uPBUToxoIUybQWjI9jVgSskGduhUNbdZF3vC7UTpEhAddBm0LsSQaLVYTCvVeyRdUy7G2m+yqrDh1wgqzcjeDY9GvNcTAv2qMFHw4ZgtN/2qy97aYSAITLsjd89fcvf8njcPFmi05UwYbaHgh0VDSNOMngutq4VFDa468IF9P9sf9cja7fscV0jE8HdrN7ehDpiMa+DZh2Y0JCW0grZO0UqeJ0oraB1IcfOXGrndRLn/4olf/MVf5jvf/GW+/1f+KqeHMzf7SC2N+e6OXZpIGnj+3nus9yemNDGlmWU5Xy3Yx8MNeQhznrncnyilk2eLEdYGa1nNYNTh+befM4XEef2Sn37yBZ//4DUvjntu9weef/SCh8cnbnc7PnzxATe7W+7PZz795DOWUhmtU1Njvzdr+6oLS4zsp1ueTsroK2UpzNPE7d0Nbx8WlIT2zuFwyzc+/JAv7+/59O2XBAa3hx1hDuzyjpgjj+tCDkLRQZoygpBCNjIxT8w5swvR7enl2uRjip93rzPElofeGr1W8m5mt9uRUuCCxQLUtVLqiizq9nPLUim1Gc902JF3AQ3K6XQxMYJEKsOw9SmxvzmAYBLE7mY6CTzc31NaJ8V8zdXJKRFFkZi5XBZevHjJ4bDj8fHJZY1iUcyt8t7tDQ9v7zn3zh/74D3OZaUh7Hd2WD6tCzL+N5QD/u/prRbLDtkSAmULlRn2Sx0Ypj3niSjBVBk50lvD4I9AbSZ76xgRlEJknsxAM2XTWM7T3vGqSg7Z20zsCRC8S1EQSxRL6SvFqiahKtpodXiKXSePZEqC2A07HtEC4VNiqYV+rtaekwL1ciZmk/eZ0xIsp0HM4OHDLc72c9MGYTJCcVVlEkAya6/kKUEyxUBMs12PNSG9QzA1DHQruB1KViFtsJAYpCB0y/VWw+PHVgMW7MDatOcjeDVXzJY/LpNpusX00ZsZREMg5JnD8QUffVBYTid+/MmXoFt4j/2KGkb0BBV2hyP93kpsqyZahZa37BI/ILxyrakZikyb7dp3D48KZOt7JFBUnZRVNGZUEk1NdXK4PZKAqQRKioyLKQ9gsLSVoNms9kEI2nl4HNzNdxzTnh/+9b9BjDNPS6WXhSiB+9df8p1f/CWOac//85PfJvEtpCltOTNKpmdzX94/FmaJEPeU+sCr/ZGydNa60gXWboT108MDX7458eOnR6IGPnr/Od/58EOSTCynJ2pMHO9uebx/4nJaub8sPDytrEthkokWGqcL7PNMbSf+z/+nXyPnzv/lv/1vUN0BmXVckBSoYbBeGikKP//Nj4gRilTubg88v71hypGlXNDWkRRZ68rltLCcL6SciALpJnGX3ucu7elUzlogQpom9gd7jtcyrsmGMQaCRPqotBopq9LHQsqQQmCXM3113XWywobhsRQDRXIgz5mQ4fbmSBCoS+W8VkpVUlIuHboq/fzIbpeYDjN17cw6GffQZpZ2RsXcnJMGLqPy3u1zzveP5JSQ3nj75p6zWjRx0si6Lky3Bx4vK/enE3/44495fToj68ohZVYp1FJ49fwF+aB8/0dfb/b9TA/uacpAQLwFIzreTAzoGKQQkWzOLZPLGdTRPAd5OEyAmnZTh0nO5m6diofdzLoURIzcmKY9qKtHgjHOuhbinKm9WfpYCHS1rfOdVd56HocYVDKaQhhMu8kyKqjsvZnE2kjMYbloo40GyZ5o9EDv1XFtCNn04NrUinqj0Ff7XsMUIEwMsSqoLhNdI9pMLyyS6VrIeSIHJYaBYFtGU4vO7G3bSK1BfpdsIMZg+SWlDVqtBhUNRYJHCkQxHSxGyJiZx3NBHFZxNtkkdZJI055nL17xzfbzrC3w2RdfsHaDnragwKFKc7XKptuuw6AOy2nyVD9xlYF4jZj3PeYwm6JELLO7aqA2sVsFRqKG3cyUd6hEL62IHA8H5iSUdbA/LXz06hYdnYfHhcd5z6Uo0uyW1GqnrIVn+5d8/vlPOF+eaMUgn6iZm2mH9M7H73+T//F3/zsykbpcGHWiFUXGoFY4nc/0xzM/fbiwm2amaWfNMmOwtG6HhVrF19vXZy7rSpTAYb/n8bRweizsJmVdCvN84Lw2Hp5OpJj48u0jhvJPxMlCQJ7vj/wf//ifYN7d8uXbH/CX//u/gqhwWQtldG4PByaEJIP9LvDeyztihvN5JRIIOfB0Xjg/nkBWfu79D9DReDpfeHt/4nRaEODhZs/Ht89JO4twuF8urHVxz4D1qEqAvBOexaMpxEYnBaVXKNIY48Q0R+b9TOsL87zjeHe0G2aHWotniptoYHfYMR8OTPtESMIuzezmPW8enojxzGHakYb9fg63e463d5weH1nWztrh5WEm5cxn97bw0c3ZS1R2O7h/Cykpb09vIewsHyVmnlrlcHPDnHac6gM/9+GHfP76gW9/82M+qwvn1lla42aeuL17xsPrz7727PuZHtym3fZeyZwsUc4TxPDw9SiBMqxFOmpE1auy3AKc83xtHJmmGQ3wdL5ws7OtMMeIMNjNM8Nbr+fZsNS1VINiSqf1Zl/L8fDu7S4SLBks50yTQQvVc407ba30LubMFiscnlMmxmADtCvkRBsdNNHK2a50O9ucY4rE2VQIZazQjCwFa+KRbNVZwiBHSxBsw6RmMSrTbk/UbHpqrdbOgjrkZDcWQzSqBS/14sWnpuWufbCsRhKJRIaaCzSKMu88eztNhDSxNcl0FaI6bINJ0AimMT8cBi9ffUjvQhvK6zf3tK7WfiLBMpr3NvwVy0+pACRTr0RzasY0kUKkSSKFTCczwkTwwd0lM4kFdWlVqgBYyzjTzEgTFRvupW56k0yMK8+f3/DLH/0cqp3Pv/ySn9w/cVOEdlEenx4ZzbvSe2U5P/Ls2Qvq5YFl6cxp4phnZJfYp5nzwwOvnr9EQma5LEQVJM/oeuE47XlgRRs8rRfef/8FujRKgdQzaUrMBLrAB6+e8cPXnV2JLE8rN9OO5XyilUS9FDQm3tw/2nO12YG5n2YoC4FErZ2ynlAK+5TpS+TcVo55zwhQeuX1l18yz5Hj3UzQhNbB9773farrsmtXK7Oog9spkkPg7flCqZ15nr2A11qCbvKen95/xpePJxbpHqo2WNYLl9qIXu6xPxwtXGuslGbP77pWokyU0in1jMTAvI/sDxm08/bNA+tysZ7ZNpCYDDINgyHC6bIQJ2GfE3PKJu6VwJv7e57d3fDhe+/x8PjEF/dP5Ji52e1NtqmB42HmshpEF0JEwuDh/sJSCvNIyLwnhEQW4XGsHOZkOHtvfPjqPd5+8Zan0gkJ3j6drI4uWrjW6fTEWv6AtLxb1ZiVJCTPaQ7Y8N603DGabA8365jHYMvmza69NoilrMXsu3nP+byw3+3oas01+51hlGvvBMmeAjjcTWi452YCkvBOU96bBQsRI12bE5Sedlbc7h4D0qCuKyNGdBepw5o2gga02uaQJbI/7pjmiS6dJg1tMB/3pGYFxqJAN9ORqLn+psmGaWkXx9kTIUGQzKgLDCOpcpwQUWpVptTodVinpprBQb3Nso1BFrtNLLXxdFlto+7L1fAkKRkWLfE6tK+a+RGvEkxBHGO3gTfvlefPO+9/cOFcGg/3JycqrUShiQ0JJFD7gGhfOwbLY8kxmUIj7phCgGSDeoSJQmbEmU6my2T5IWWw0ghj0EImxszImdGUpXW0CZd1gdm6F6sOzuVC7JHPPzvx2bIwxZlYG32F02VlPV14++YzSul885u/yAfH1/zu7/6Y4xQIzeCh15/8lOVp5Ru/8E0Se/v5L5Fzbez3R1IxA5ZopKzwwx+/4YPjHaFm0pzppfD27ROHw4HHtw88fH7PR6/epz95y9Ht4LKsRLXWm14Gt4cbSqkG8yjMcWbpCyHA+x99xI9++j3i+4Ff/vYvcdEzf/mv/Hfc5BtudgfyTaSXzumpcjcLX7y+5+3jifkwcXu0GN+1dgaN/c0NtQ8jhYO5PL/x8UsO+8SLV884ryufvn3gaVkhKrd5xxwzRQvSC8XrA3uz2Ne8S8wtM+dklWa9mqtWApKU+7f33Dzbk7MpT3QItVRCTKQsxKiMVnjz2hQo+qxws9+TiLRi7s/3X73k1fMbaq+UPtjPB3II1HLhUYUPnr/kg5T48SefWdBZqSQJlNKYkoJGWoF5Vkrr3N7sebk78MNPfsrzuxu+/OItX7w5sT/s+fTpS/pFyTEg6qazPswg9zXffqYHd4yR3kF7Q0c0Q4ybY1SV2htZYIrpSmQO1J8UlV/8xV/ifF75yY9/ShAYDN6+fsP772d2x5n7h0ezSvQtsCbSqrH5rfcrFCJASoneCjFF7wK0/JHldCEkUwOM0D3HwnKYp5SvzTxjNTxOR6Nif9IhI6Mz5cyL21vWNpNSRKM1rMgQGp1xWq0Rvtv3RRJCMtWLHDMjREIciGay66y7Nmq5EMawGixPMetqv9Monr4XDZfsoxnO6CRhFGFtnalVLsvFWfWOBJiyOUshmmPTGfdx9XsFxjDs0pyR/oSVRMw7pl3l7u4FL56dKU05nyy0KBDQmL0/LjHobtVPkCYkRuZpR5hnxGNl4zQzZLKNm53F2bpRabRABXIvhGolz8uidAbPnz0jx8bnXzwiw8LIqgROpfIX7n/Ii7xnSZGXx2c8ni+ktGMfhYe6sE+J3/2r/wO/8PG3Od6+4PNPvofWxjHf0JbCzeGWz3/yY8raiGGiLY2X73+D+vBI+/I15D2ZwT5Eu1KPYeXQvfPxN55RJvjkp18iKfD0tPKXvvgxSSKPvOX5zS2ffP4FfPg+Q1fOTwulDEZVFl2vSZU5Z968fs3Ns1f8wh96jx/94Ce8/vye8EsLx13gF77xCwypfP7DT2hrp9eVvirH4562Kjd3zzgvC+eHE+t5ATq7/Y4QJwTl4emJx9MDcYp8/PF7MDpP5xOPpydmETQZf0Gz0oyHyyOn9USIkZ1EAjDvIy9evgTgdDpRV4WgXC7V4nMDjHWYS7ZMNG2si+HWMSjzJOyPmf0xsT4OlqcLQWHJK710Lmth3h+ZcuTZzY01/egg+eKxFFtInk8zaUpIs5v7GIOf/4Wf49vf/pjP33zK5XLm/v7C6VS4rIPjLvPx3R2fv37k5nDgbn/D9x++QCQwZ/js8wdoiVUbUza9eErJbkFf8+1vK4/7/+9vDpWkFNnvZw77nbulPBzJN+DWuhtSxAP6DU65nM/cHPaM3pAwmPaZOR/5/LPXtF559vKWONn2W2pjXRt19C3SGElC6wXEjAQxWbdiTIkp5ys5ot0dml0IQaw527FbreZ+68UMNiHY10jOeE8kpmROrwm7PYxmWeKX80pZK31p1r5d1GzVXTyo3/Keex1GzOWdbaDujry0zmVtrHVwLsrTOljLoGsgxEzMyTds+3UPgkn7QnSlhn1sqZ1LaZRhFnw8jdCC5N85GTvyztW4vU8971zlXRpgSOwOR3aHAwTY3ezcpBNpqoRpb9f+gUv8BIhoyGZoCJE8Tczzjphmc/nmiTzNhLwn5ZkYJ9eUJwiz5XkTOF8q9/cXPnj2Ab/ynV8iSaRXaKeVxy8fuX8svH2Cnz4t1NZ5GXc8CweWy0psjWdx4psvX/FX//sf8eaLz7gV4bC7ITLY62yZ62Pw5vW91X4NYTffUi4L3//e95nSTFIrktaYKG2iq/CND17x4S98xDI6/dSIGsi7meOzmTTbzxjEyjQ6gYenzulSOJ8K56eV83nlslzo3aSvc5748OOP+Lv+rj/KZz/+gvvPHnh+2HO6VH7w2f9IXZ74zstvIzFzPj8QNXAuT7z3/Ibz5ZHPPv+EZ8+ecXtzw9PT2W63YtBAVqWXhRCFZ4c9e5SffvI53/vxF/zoRz9ltOpeiQoS+fLxxNNy4bCfeLmfeXF3QDL80rc+5uPDDZOqqaQCtF6QFJnmiWmaSdEqc1q1Ps7dPrM/WCtWniPzdOTxbeXhYWWXMy9vj6xL5ZPXD5Teubs78MF7L/nks8+5Py2cnhYzkFGJMbJPB2se8kjZ+TgTd0KeI89vbk1/vttz2O9Y1WDUX/n573C+FJpW5mnHaV0Z2vjWxy+4OSbWi3IphToa02wVatvc+rpvP9Mbt4RATub7n3K2hLTWbRvt5mQCTOY2xNvCwcwXwunpiQ/f+9CyQrCUPx2JaZr58ss3PHv2nNvbG0v9WisM5bI2Uu7YLT2T5onR1fWwJhVimDZ7vazklFm6EYtpshfXlBJzNtPG0ADVvu9aK5Mox92O/ZTZH2ZkspO5l8H5fEFXgSxGUKp1FuqwjUqjucfCsKyMLIkYopG4gmlva/MexMg6IkGTucPGsC0/DKZgA3aad4YrXjZp1SB6L6Apa6D2QYpG6h6yNWDHrdVn03pjmlj1NDt1V6Xln7hTExAZ12TCkDIyRT7+1sdIF3Z54nQ5c1qfDB/PM0q/HiKoSRKHa71NnulWd7e4IwnR5HJAYeDlG26NL8OiUtelIqXz7Lkdlg+PJ3pbSSNze7yxguqinB4q3ysXSuuclhO3aWKcOi+/9Qwtn/L9730CZ7sr3B1viJKYdjOvP/2chzcLKSeCWhjS5ctPkd7oXdBeuFyeeCydGpWXhzu+8fFL3jw+QM2sDxfu0kTfKUmE3Ys9tVrV7NNp4ZB2vD2dEK08PlxYlmo+A3Yc9xMB4eHhDX/i7/zj/N9/67/h4csTH3/4ijkLT6cnHv/6I21d+fDFt/nlX/wW3/te5eHLEx98+Iovv3zL0/nEaMoXX3zGzc2B73znG7z+8i2PT09859UtL1/cITznzcM9Dw+PPL595MuHC23p1F33ij4zEU2zMIeJnANTUFpZmXeJP/zz3+HHP/6E+9U6HXcEVrF8loA12O/nxG6343R54vXrt9ze7Pnwo1cEhDdvH2i98nj/BCNxezfT1oXSO+tQ1lZ59vyWnCJffPmGsjYOcUaDxffu0x5JkdN5oYVI643jYc8zMTj2iy8+5XfPKy8/eI+/8f2/yZu3T8S84+/4hZ/j/u09r98+8ux2Yr0U1tD58P2X3N7e8Onnn5E8d2iKkVEqMSeO+yMPD8vXnn0/04M7hcjx7o79PFnGbrNQmaUXlxDJO8xZDBOPrj7orTO6cnO85e7uhrdPi5lzBFKciTqzXAq13HM8HiALp9NCJ9Krifr7ZeH5s1cWgq8dbcGNLYPeKwNrtclAGY2Ibdm9NJgidDMRLOeFMiphjqSYSRLJCv1cGL1x6ZUlW3v2crl42a5J9fCm+Fa7kZzRVB1hCNIhS2JKE51KizOtdXq/MFqlNiW6DEo6aLScjOFOpq6Vjz/+BpeHt7z5/HN7sanlQ4Roqmj120vv3Zva5To8+zWlz/LFDcgyUjK4UUddR+2hh9d8koYy3xx4dXyPV7cv+NHf+IFFdO6sYDbv9kisTNPM0mxjtyxzI4jr2skyCHMgxokRd4xu+HgZg9KFtW4kq7LFwPQRoCoPr9+yI1AvF9bzSjsPXj6feG8+ct8rp/tHxhh89Ool9E75bHAuleVcyXczx93Mjz45Ecpra2Y/HDjuDqQ88fj2gb5Y5vN6uXBze0dzO3w7r2iIPD0tPJ4WQhBOtfDX/soPeHhaOIQ9opAifPDeSy6nhRiFIl7Scam8f7jlXiqTTMxZuX97QZNyF7NlW7fKr/wdf5jf+r/+t0wIH3z0Eo0WzjQ0MIfApz/5lPOl8vPf+A6vnr1kLSvv3z7nL//0r7GWRqAzTZ7d0eH22Z61LaQc6LXxeDnz2du3nM8FIZrLOAzW3lnWypRmnt3dsZ8zMgZffHnPeQye3+z46PlLxvnCZ/eP1B7MgJQjc8Raj5q1VD2dnlCt5HnHPO+Zp4mnx0cup8K83/Hs2Q0BqKvS+4LkiTf3Z9a+cnu748XxQCuVtQ+meUePSllWMpk6LkhOxDmyu4nEZDnmb17fszydubs98ubNa54/2/EL3/o2ZfyIP/zNb7CsCz++f+SDFy/4+KP3ab3x2cOXTNPEjz97zeP9yrPbPcvJslrWUvnwvfdJcSLI1x/HP9ODezdF7vYTACFlztVwNGKiDcv1jcFYY8Fw281QGPLMaCe+fPySESPNMdzDPHn2iDLnPb033rx54Obmjnl3JBaDTKQHtDWens4mC1RrOCFHBspaKnmKJoBma/Ye7I87c1OtFjLTtBEQ7qYdsjdljFZYI5yXQrtYTvK8ywbFaESLMrowRBkyaGNAUktgnYTQA3QrK93nGW2D3W7PYz/RgkWXtmpDcwwBtXYUHUrTQY7BzA8a6L3x6uVzvvj8taUJpoZ2sUopTVQqtMaMYfoxT2gUiBmi5X6bbd2bhbxUdbiSQxCrxHLN9uhKUStmjulAiBO3x1eU/BNO9w+UCHOOjAFdLN9iVXOOTiHSRIhiwVFPS2XWSo6d2gtl7ChjcG6NKpllCOcWWIdBE00nRr/QK/zgJ5/Saie0yM+/fMHpOHixmwmt8/DwwHopfPu9V7w3TXz65YnjnHiolfc+fg+q8OGrFxyeVj5+/xkjRupjI0+BN5/d88WnJ2pZkN3/i7z/eJJty+4zwW+Lo12GjqvFe/fJFMgEmSBgMFCzqq2rxbD/up73rMuqWSRBGskiBAEikZlP5VNX39Cu3Y/cqgcngLaeJYfP6GZ3FHYH4e6xzt5rrd/3DdguN4ymd+narkeEuh06zqkrQ1lVmEaghCNEKSJIJqOc48GYs3JF11mmWcTF2pD6fgC5XNfoEKNU4GqzZZQmDAdjNlVJV3cMpzF37t5ldr1g/2BCliW0dYNvDMIJTOjYNA1Kas42b2i6jof3H/Lp9BlvX76haR2d9f3WjDHEcYQxNXYLRwcHKOE5m9+wq3d4L4ijvjhp+luS84HGebIsomkUVVlRtQ6pNAfjglh4vnn9lk1jyLQkjwON0pR1i0xyori/ae/qfk335HDCIE3ZrBpWqxJ16yr1smZ6MCSJInbrHZEck0pFZ1tCLRlng75FITxt2ZLnEWVd0zYSFwVG4z7u39aB9bJkKxu0jrFty2g0BOOwXvFXv37JB0/3+aOPP2LbOr588TmKmL3JlCiRXJ5dUdeBtatpdjXDOOmH7VphjGNwi7+42cwou+3vXPt+0IVbRRGd7XtRwXs25Q7P7dYG9Fd6QZ+WvI289wNASGNB0zgWixtc6HtMUdTLeUFgTIsPoHWMt47lckGeD9BRQtfUWB9QOiaSgkhKhNC0piMYQefsbeRe9DD7PIPbgiWRCNFLH+q6IcojRsMxUSqx0vfrRqanwW3qHUEE0lGGsx4VKYL7/1lAwm3h7oXEHhn13N/gestOolNMY8mLpPdgNp7gJHUXCE4igkZKQXfrmQ0BUuXpnO0zlDKibg2ha3tMAL3HUqioZ5Lchp0EoG5xsUJppJK3yF3Xv9/0tC7PbRrydiPk72iI/RJiz6y2PiCc7tsYIlBWFX/z2d9wtl5hNw6hBcM0+//TiwWpIEpxQZDlCVk2YbXraDqDsx6/q/AqogmSLvydoMHRGkFnBdu6ow4SrEeJgEJjWolCkmYp42TAk+GAq+s1by5v2K0a0qhgqgacz1fsKsNokLFe7JieZsyXaz5+7wnbtoO65u3VinvTPbJBwZvvv2VT9eGXyX6MDBodNLumxTQd1+sN1knSLCERCW1oKJKEbVkzSjIGScJ8teg1aDksSxinGU3V+ynbznO12nJ/PEUZ2PqWg/0JZblG6ZyTkyNevHnN8mbBwf6Um9WadlujEQjpMI3BhAgpO7QTXK/WPLznsJ1j0VRYb/DWkiVxH3wz/hYl4yjXKwQNeTHALWTvZNUe40BpD1qReIcXDtsFrm/mdEHw8M6U46xgsWp4tbiianoZdhbnKKUYKkcqUkwwSK8YFzmfPL6LljCfLXl7tmDZGJK47/EPhxlp3v/deqnY35sSq4TtasUoz3H2lh6K6IfZWlNXnhAihkPJ3t6EpjXMrndsVhVCOabjCZGGLO973mXdsilbiASbSvLdi7fkuWRvOuXeySOwNX/5t19gnWVYDNisy/42ngUOCYwnBatqx2hYYIxhU25I8/h3rn0/6MItlKBzjkgqdusVxjp0EtE0HTL0HOQ+FdmfqP4+WSkVo1GOqQKb7Zrx9JjtuiJSGmP7BX5jPMpZutajdQw+0NYtVdMSxwnIPu4eKUFwBiE1URzTGXe7duhxAqK4lzEUWdLHXFsLkUNFmvgWqmX/jlym+uv+eldhfHcrdbB9bFD1kuFeWeVA9psjQgtC529zAa6PnkvABrIoRTmJbz2WHgFQ75r+51JjO4OkH5b25qDbbRUtsKEnn7mgKEZD4s0Ob2q0imiMJVYSQR+J9871J/nQixu06L2Nneuxtz3avG8LSXo7uVK6l+mKv6OE9GLlqm2o6yWN6W6t7JKL65Kdc3jbkcUpVgiSIiPNHXneQ/Lr1iFjePD4Qy6uZ1SuRGUZ802Njvp2UiNagkwwyJ6M6OUtkrZPoCoUgojO9TODWGqiWLFYrlEtzG62lCuDDikHw4LKNcyrlmmaEjpPEhVMihFv3twwOT3A23O+v16xnlU8vXNKFkUst1t2ZUNwgelwhA4RiYqRQmFauNnsUK2iy7p+6KgSgnWMi4JcZlxcXvPo0WPCak0UKZASu+0oBgXCC1brks2uJAwHHI4mXO02BBxP3ntAomNev3lJ2bQc7h1yfnmGDIpBniEAYxoacUs0V/1NaVwU3KxuyOKY0ShHukDdNpRlg5KCJIlobEcUJ0wGA8qmZlcuGY5zrq8XmMqRZLdIXdunbuumRuucfG/I+6MRU6l4c7Pkqt4SiCki1W+ycDvEax06ktw9mXI8nhJLwWK35O3NgvW2wztBHiuCczjZ0/z2RxPSJGa+WrINW2KtiaOYYjSgcb3qUMkeIxtEII5jrO2YTkYE77l4d03bORAQRQlJHBNFChc01W5H03ZEieaPf+/HnJ1d882rc06Op/zeB09ZNxV/89VviYIiK4bEaUpUVTgPeZIz2204lJLpeAQEjDFEUYJS/4O0Svo0pGa93WGM7TM3zvUMAdfH3uWt+7HqWnZNTSQ1AcP15Zyf/vQnvHp3SVVtkUJiupbK9MUsiiOSKGIymlLX1W3IRODagBCeVAlk8Xe6poCzns50GNtDl4KQmK6/igVhCTJQZBkeR3qb4kIJyrZmPlvQda736MmAShVFnNF1HQJBtWn7Xew87tGxpv9CiQAaTZC3ONigMI0hijS5yjA7Q6IzggxUTcdis8ErsNLTS5wSdOgAf2ur7sMxnbUYJ1FRShsAqdBZghNAaJARBO/ovEBa0fMGtaL1vTot0Tk2SExlKZsdcdyiddRvy+jbpKpviaOYKEpRMkUGx2qz5s3Fa5rOEReaNBuwvJ5hIo2yESFoysaxrAz5ZI9du6XxlkVnuXvnPn/wx3/Al998yzdvzkiyKVJoZDHCy5jttpc8B90Hc6xQtE7QekkWDRBlR2f7dUDhPdIHypuO1XrL+3fvcXW9RmtFHEUcFWOGacKbqxuOpntM8pjXZ3MeHO8zzsb84sNDfvXFb9hebblcrjg6PCCTlj/9T3/NVO6z8Jc8ODqgkBnvLi/46NlPUEZxcbmiUDkq07RtjTCObJww8lnvFk09STKi3Vru37nP5fkFIgSqzrBd7TAdFDqnqRp+89UlP/n4Hj/79D2+e/mW1eySKL01pCN5e/6O+wdjyqbsSYUB0nHK4SSj7SzlbsPxwSHCe66uZshYMB0W7B+kXM4afN2jTKUCRWAyTkllr46rmo7lrAXvuHP/mO12R9fVNJ0lzSRHB3d4NjriV6+/4Zefv0QET4g0SUQfmJIBYrDG85P3TtkvUpZNRwgacFwvNry9WlGZvtcdaxBB0wlPGmUoBNc3NzgLAsd4NCR2isV6RdcajPEYb0jzhGKYkWYxkVCkIWe12lIUBY8f32G5KtnVjigJJKmmqirKqibVGXIcM5gUfP7dKx7ef8A/v/+A337zBf/hv/6SUZ7x+x88YL1p+erNFWMv8EaTxQGpDLGIcDqiXbcMxgVeOOI0QQn3O9e+H/Q6YJqmtG2vuVdKEcc9Uc27fgxmg7/t1Qay9NaFSL+v3RnPi1fPuXN6h6aqESFgg8U7EOh+tSlO2d+bcLB/iHfQdQ6hII57+4o1hiA8Uolel+RvV61iTSR7AqEL/bTf+95TqXTUtxB6Oj/B9FsgKmgi3T8shmlKJPvUJk7gOk9TGVznELbvgffiWW6DQPQMFS+IUOwPxkwGI/YGk7/Hie52Ffg+9OO7gPA9ylPrXp7r0D05UN2KBVTfjzQuILUmStP+9BHHyFgzmk45PTlhPBoQxxql+paRlILO9kxnqSX6lg1jnKftDHXTsd6VrLYbbhZzdk1NoIcQGQKtt/2qpIxojSeJc3RS9MzxSFLked+2MWCCZl114D0f/uRDFusN3754Q5xkpEm/I79rDcuyxWvNzkpq/3cyiX5QqYTCmZ6X3FRt/zsEQWgMXd3iGs/VxTWu9eAVR/tTDsc5s9WWzawkD4LgNJt5w6QYkxBzkOzx5RevaRuHbTR7g5TWe+6NT6iNJYsjTsZjlrsKKSRV6xikQ54eHhHHPeBM65ijyZBnp3ewUYQMimKQMT0c4bcVwUKU9DiBIonZm4zIopS2M+ztTzk8nlA7h93sWC1nNF1Lt6upqxah4PhoTJwqdBYREpCZxOOYL5ZcX8zJ45TOGW5WC+qyoW0NpW3ZlFtc0yK8732SbYdWGiUjRqM99vf2sban/NW159X3bzg9PsTUHfdP9/jxs6dgGs52czobgepDcdrcJihl/70MIvDPf/oBbW35y9++4vJqQa5jtOxFxnVT9qlpobAu0Ib27+UKi+W6X4VsGuq6oWtaFustm12FRaCiiCzLybKUzvTbYl1jqaqazXbH9c2c1XLLzdWCzXqNtIG6bMFLtIh7tZnz1J3hwaMTTsd7nM/OOVvsSKKCVgj+4vM3YA0/eXK3rzfOEukE2wasVgyThGfvPSPLcoTsbVZtU//Ote8HfeKu64a67feodaQIPqCjGG/7BJ8DbPDE3vdMjijCNObvaYDX8yXHJw3HB8fUVcfF/AbnDLGWjAYFWRyTpyl4gdYRvjMEGfr1OdHjJRvbEckYFUVgWyIliaKUwWDMpizZ1DviKEZEPdWvsxYtbmH6xmBb09PhIojTiCiWRJGk7fqo8s7U2K4jynoynLz1MVpnCaZ3aepUg4Mk1YzGE7I4JpUK6SX7R4f89uV3tHUPw5eyH1p6388A3vv0Q67OX7NZLREywgbfR8OFQ0QKKzpaB1FWUG1r0L170gnBcDQkiyXb7abXbamIbdvRtCU6UozHI5IkBzQR/ftlAUtg23iquqLygjSdYLynQeJUTGscGRGDKCPfy/nm7TVGKOI8JYje0BIXMV5H7OqOj3/yDLKIL/76tyCG6GxIZT2ttbRB0xpJ03a8W3dARaRTBvmYSPcC57at8QjuHR+zXK1pdzvuHR/33JnrFauqhVCTRBmjOOJ6ccP19Qa8opx33KxnvHfvlOlkn6FKubp8Qaw0BMOgyCjyBLt1HE73eXN5wzQfIIqU9XcXFNOCRKUcHB2zOb/kZmdoTEMIilGWs11viNKI5aYk2miO7hywlDUXby/QaS+kHSUZeI8c98Nt4wwHg4xvvn9N7Bref/yQr759jpOKfBAxHA1Yr5asatNvUkUSZx27xZa8GHD/vWPyImW2WuF8wLqGyf4RB5Mp0lgOh/u0nWG2WmPahjiOGA1yDg72WW4WECSoABiUhy8++4af/PgJo0Lz9vU73q02fPz4IfePJlxu5tSrtk89CtjVDUeHU3708Ii/+PVvuV63KAHRUcrs+opNXbNuDNFgiPIOb8ytg1QSOsOmbbFAu61ItGKYJ1R1S2UNrXUYYUijBCWgbluQ/QFtu9ugowhjesdlEQvuHB8gE01X9/McZK8X3N/f53q1ZH69JNcxkdDcOXnI4f4pL9684vJygRaSL8+WvH/qeXIw5WUIGOPACfamGXcfPCZ0HU3dpylXyyX+FmP7u7x+0IV7W+5wvueUEHroVE8MjJCB2xaCBd+fqKQQWGtB6Z68rDJev3nJjz/5OV1z0SNIZQMYjo7G1NuS9eqapnVM9wZc3cyRIuoZ3gEQAUvAeYMMUGTp7VBQMx4VHJ+e8OLda+quYpAO+t6562FWwZke0CQFImh01PMwtJBEKFAxxre3Vp/+ZC2RqNtWg7Out38LgUKihSSPE7KoD3jYpqWINIM4RziJ8LcmEds7+py3fPjxexxND/jyq69J45Su6x94tnUM8wTlW+IsB5XQNDVxMWE4SljNzxDGcXF1w2CQ4aMMFwxOxFSdYV21GNPQohkUkjzN8A64bSuJJCaXip1xnM1X5PkaGUdsbMDqDDeOiYoU0Qm0TkgGNQkjdtuO+WrBeFAggqJxgmw04fHHn/L18xdczypKJ3g5u6I1qgdLFQVxmtM4iQ0ZXkg2Ldw0W4ZxyyjJiYNiPBgxHRWs5luk1zTbmrqx2NrjPMQIXGforGY1d7gSkkSx2JSMhzEff/A+2IjXr7/l+68vuLN/iLGSUdJDjLqNYTJJGU5SBmHAcr1Gq5hhOuhZ47VhtytRShIJQb1reHt1RZYOmR6M0UnM+nLHoMiQw5jFuxX379+lyCR2tWOzq5HAsIg5u9qyWq6YDHNuyoaR87x37x5XmyWBjnq9ZL3ZUbcVaZEiLLSripOTA+6eHrPabLiYXaBFTJL0OORHd4+xxvQD2yKhUWB9hncRWitOj4+IIo13HePRkH3Vr4PWrUMIy8HBmG+/+Z7z2Y5IKZZVw/5wyjgvaLcdPYKq4+Mnpzw5OebN2zOuyw4VawSW+WrBeq0IOLI8J1ExSgZUlGK953q5xgXPs/cf8/K7V0RxjJC9w8n3glE0PQOodQ2RVMhEkQ0GlMsd4NltS5yFNJPkeUQaR7w9v8I4yWA6QuI5OT2gLmsUgVFesNzuKFtDEt3w3r1nfPTwKdbWbLaGwyjialWRJ5ZJrLjY1HRB8ofPfsJyvmR+fYHIEgaDATfXM6L/UdYB284RJXGfVhSiD5wkinVbkTqJutUilXQUShEpSTpK+7CK8ahYUO0arq8u+lbGbWpQS8VqtWAwnLIut3RtPxlOoxgh+k0M7x0KhfK9DsyLQOUsWijSWCIFtG2NwfaOOWexrldODaKIZbmls70sQWAJKsZtG3AxuuiTcKGte0ehiG6tN44iSREavHZYaxBRv04nE9mfTBCkcYaIBHGS8Juvf8Ni3hLHrgcyxRFdVTPeH/Lp47v85vvnpBqSvKDFY1zX75OqnE3VobOEEokVMcenY1bzc0I8wLiGq51nUZUM8wzTegbjhFVtmG8d9x/eYb6p2bQ7pCqZDEeMvWZvfx+tFKodMvEp65s3vFvOKdIMKwwtMVFUYLxGBsU8xBzsHTJfbJit19RWoazg4rykcpJf/MGnbFvP25cbrpuO1kUYr/AypgySsR4x35Z0XiKjlNYqhIS0E5RbQ71eczgd8vHeAbu6ZrdriEXM9WxLonoGe2xTrDW0wlJXtqcIqv7m8t579/nwyX1MSDi//I4vvnzLZl3xv/yrf8i//Tf/Bx98eIe6NITKUmcdhc7xxnN//4SXiwvmszXlaoESkqrxeEuPW5UFQinwDcZk2E2LbQ1NaTkcj3BDhwwBjMf7XkBttGJ+M2e93iGAIklofM3biys+fPKQk8MhTdPy6voKi0OlCcI4VrOKew/u8MGjE77//g2v52ukCGhaVAwH+ydoAeeLBa40jArFbFOyrToGRcT7j5+SZUParqQqtzRNTTACtODuvX3uH+/x7Yu3TA9PONgX/aZS3N+8tBZYBUejER882GOQJHz21Xe8nW8ZZmlve0djraetb1OTAXzXoJHsHR5QNTWTEHj43h3McoOONDry6CgiUjFpHLF1JbVvUF7jLHTKMIwkiYWladiuaqrO8/j+AVpCZx1X13NUMmQ8iUkjzbQoWOy21I3h+PCY86srcBqcZr7bUdef8+DwmMPBPtXmgptNCRrK1uM7y+nJHgeHe1y9e8t8W3J37wjyPvI+HgwRwsLN71b7ftCFWykB3uONxCUC4y3WGLQQWBlQSiFsPzEOQrA3nPQGa+/Z7Wqss7hU8e7sHR98/Anh8gZvLHLQR6sXq3VP45N9qCDLU/oDu6JpAp3pI/AqikFJXDDYriWLI+q6orYW3/VWi22zQypFpG85HUKRxhqdRITII7WmvVWJWRewtsGaXj6K9yipkF5gug4Z9ZCm6FaSKkMgT3JUgGChaVoEClvDZlGhgsDbiM7VDLOC/dMhrbOcX19zfn7NYDAijTM62yc8fdXDrurO07Se+arl/oPHbJdz1hWkUUFnAoF+3c7s+ofTvLTcLEr+5b/6n/jq629Z7NakBdjOQZYzihI2lUXG/Qpckk+YTAyLzQKrPCZ4gkxxMgKXMtw7wCeSdrnk3eKKVZBkIgU5wDjBw/feZ3J8n1/+5re0RiP1sF/DVBHCevbHhwgh2GwUINH5kKRxdE3b39REH+5oG4cKUJcdmfcsdzuUFEDMSA/pvCUdjLBti2kNzge0kDx9cMyPnj6lQ7Ft18zOVwSjefzoIW+++JZBUTBIYpZXWyInmI48XScpN2vujPdY77a8vVxxMD7kycMnVK4mMzGrxpCNJNp7OhOzudximpYky3l8dMCmMTRdh1iXJElEW3msc9hg8L5nZTsnmG2WHBzusat2nF/fICNHniT8wY9/RtPV/O//7j+xqRruPznh5x8+5fXrN7yZ3RCrDCl7TMSwKNhWO+brfvC93FXEpFgPpbEcJGPSJGG9XTBfzJmtGxbrGqXh8Z27TKYjrhdr5ssNHsmdO/sE2yK8YJQWHB+fMBqmPNg7oNqt+bNffs+msQwHOTqTt7lbgRWCwbAgiQWximlNn5NIk4S7J6fk+znPv33Oi9fnfUtD9TdTHUfkiabuBNrEtM4RCTiejLA4Nm1NFOdYXfNHP3rGZl1yNlshlSAdjLh/sM+qrmjqhheLBUrFaB1xcXNDURS92V57okgSLMyXM4Z5wd2TE5bbfi+7s5bDg32Gw5x3b18S3Uo9bAqdrfGNp6pLhAq/c+37QQ8n8bcRjtDjEU0INF2PJ5W3PTNC//Ss2o7tekdbNdjO0pmOiJ7MJ5UECYOiQItep+QQfeFGoYUm+AAi0LQVp3fv9okx68F7nLHYziKCYDAckkYJi9WCi5sbcIKuaqnKhrZu8c6xqyoiFZFlCUIGNKpPXzpBXXWsVzvWq5Km6vDG90Mb0VvBQ6/86/vmQhDriDiKMZ3FdLcAHtvfNOaLDVpkpFHUi3uDoim3TAY5tm64uFr0Bp+gMVVLkaTkowlOxEitaZxmW3taH+NlyvV8R5yNKWtL6zWtSJDpEK9jrIxZVg1/8s//Bbuq5Yvv3mFkSp5P+enHv0+eTvn27QWX6x2NERiR0IYIExJ2jaAJGitSrMzZVZYom9DJmO+fv+G3b69ZtxJChkuHNAh0nHP6+BEXszUXNw2lUTRBYUWG8ZKQDsjzAes2EERMJ1PqXYfygiJKEV6gXL/bPy7GPaPcSaxWjCdDDod7PbO7C3x07z7PDg5odh3OCpqdY7qf8fOPf0pQEbObS7pdxfXlhoDk059+wPVix/QoI0jFetOQpwNGowlHwz32pnv82d9+gekCoZNcX12Tac0gnVJ2HrRGdBJTOTbLLdoFamtwtmO+WLLaLOmMv1Vp9VCl4bDo2Vsqokdb93mFZr0liWJuyg2T8R7XywW/+fI33Mxv+Oijx3zyyVN+/sF7nJ2/4/M3bxkWCQeHBXsHY47uHDIoelF12bU8e/yYpmv7wJJxiOAZj0d4Z3CmwxlL07YMBxk/+/GH3Ds54PWrd/zmy5c0rWW9LPnmqxcYL+mC43p+zf6w4OnRIbvViufnMwaTEffvHBLFPY3TOBBKk8cx+TAiERHOSpyTtJstw0lOvj9kdn7NxetzLL1yTwWIVJ/zMLYlSWO00NjWk2cx5tZbKSJNud3yRz96n5ubGz7//qwnfVpLs615N1+SaU2RZQgd03We3bZmtdtxdXXFcJhR7Rpc2wfpZos1q23DYDhERz0YLElz1usln3/xNbtKUBQj7h0d4YnYlobOSto2YOzvXrh/0CduLyBGomOF9wYlNE7K26eRIC8KFs2SzjSEAG3bEscRcdRHv5u2Jsh+v1MrRZYmvWzhFg3bdR1VVSN9LynNhz2svWtbjPPEqh+4udADj5IkZjQcsV8MuV6vWM/mSBfQKibVCS4ETGsxwVNk/caFjvp92V1T4oOnbSxS9+YVGzxB9JsftrMEG6FiRRzFtHREQSNCL/PtY+OBtrNkFLRVR1lWyLhnf4cQiJA8unfK/HrHwd6UXdMinaStanQkmY4nXG9WtEGhogwjYpaV5cmTe7y+XLGzAm8gH04odyusjVDKE9/ut/7k5x9ho4h/+6f/hWIyJSoidh189tsXzDYlKk9waYuXW0AhlWBZGValIR8N0GlM3fa0QplmfP7qJaYNROkYHQWqrmS5atk/yLlz9w6tjPj+9RX5YIwdSLbzHWUVMAgOihHGChatQ8cpwimGSUFXlngLqdZ0W0McxwyVZr3ccHExp2kCh4mmbR1V2RC8JRaBxWZHFucYY8mmip+/94xMZnz55a8RxYTQNSyXFf/oT37G+au3dHHgbjbCl45yXdEdClbrDXEkWC82KJ/QGo8QHi0U65sLLq9nDNIBJ2nOblNxva55eHhI59oeDpWkzOoW5R1H+3tY29CUjuVmzmByB4LoWTQBdBSQVmM6g9ISqwKbzYrHdx/w+Xdfc7G64pMHj/jo6QcsFzecL1fEUUw2GuAlxFpQDFJoWzoUq92O4knGeJJxvl4wLYY8vXMH6y3XizmJ6KPrB3sjJoeHJJ3h5fOXnC9rnO3dnvXOUtsWGZf85EdPCdWWYAyvLq45v1kh04TJMCZ4SPKEsm5oTYfxAVt3qKZ/MDV1SfCGD95/SlYUrK6uWd1cE5QimJZRNoIATddSZAMa02G9Qseak3SE9475piIdFoTgefLwlC+/e82m7DjeHyCFpPOCJJEMi4JiOCAynlXZ0rhbvZwA66DatoyLAd55ZjdrghSMpoLZds7NaoOOY6rVDV0FQkboBJ6/uubhw2MGBUjnqOqOLO/tQ7/r6wd94lYIpNbc7vCxK7ccj6cYY9gbjiHAptz9PZ87iP7qJFQPe3JB0FnHdlvR1Q2j0RgfQs872NWkSUxrLK3zPSjJe0ajgvlsju1qgvekkSRLYpI4xtgGvKEqt7RtQxor8A5xqzjrbR6hFxALiQueLE3J4gzpBdiACL0/0nTu7yPgtuvDMMEFTGcwrcHb/gpZxCmFzmh3NaY1SKGpm47NugLbg5a0ipAETvamKK8oS0O5a+i2LbHQYD2piujKjnJdE5zHqJQOTT4Y8ODx+7w+u0bFOUFE7O8fkGYFUZaDzhA6Y1t1EA/4q998xd333kdECaut4XxWcbFpMSLBmIir+Y5vz8+53tQs6o7KCjqV0MqY1kfsDCTplLV1zFtPMT4iLsaIYojTGYPxkCfPPmJ4cMTLiwXnsx06HTAcDsiGU6xKyYd7ZMWAs12JJKVxkhj4vU9/QqIzmtqQSkUkNTpE7Gc5TeNZbWt0LdjMdmx3DZPBgIPBgNVqjQ2KXPYCgk8fP+FofMzL51/z+fNzjvbHvPr+nIeP76JjYOeYygJ7Y7h6c83R0QmJjnnz6h2v37zm8voGSb+mGkcRi+2K67MrdjvD8Xgf01TMNmvuHx6QKMHF1ZKj0RgbBNWu49mTTxnEGdtNR9Ma9vb3Mc6y3ewIwd4KQhQykoRY0xjDKEo4u7pmlOU8ffCIJIkRXvLy7UuUjsjymP29lM4bmqYjSzWjNO5vdEExm2347YvnFMMCD8hY0dQVF5czrhdrjOvQWcT+wQHL9ZLPXr3kcr7tHRyRRNtA7VriBE72C4RpCNbT1g3rqmFeV3TtjvOrBRfLFduyYjTKOdgfMhpkiDSGVBNiz2iU83uffsJ4nHLz7oL51YJVs6N1ljzuZd9l1eADDNKcpnNcXq+IE8Xd431a0z+wo37cT9fWrDc1zS0hM4ske4OUk9Mj1qslN7M5F9c3tHVzy+OhnznJiN3OsFlusC6QFCl7+yOCgMubNVJKRipHoW9Db4FEK2Qas2hq6nLL3rhgOs5I4wjT/u4ihR904S6ylCRW6Dhhvd0xKnJSAZPJFCkV89Wi13ARODk+QiuNMD3NKE/T3tjh+7j3dr1lOBpyeuekJ4FlOYd7ez2wP/h+Q+UWSjUcZCRRhBCQZBlR3O9m9xsZpm93LDdIK3qVku0hRtKFfqApVM+/tgEZesqeutWt/Z25ndDLfOXt1U/LXryo0LjOI4LAdY5BnPH07kMent6jSDMkkmrX9KfFfvcO2xom6ZDJMOft63OapkGgoYNYJewNxuAE19crtIxQTtAGiU4jPv3Rj7merWg6sD7Gk+KcJknH5JMpcT7mZlnx9ONP+E9/9rdUJuZmV1NawaYCJ3KEHoLKaZ3metVQGs2u85S1IdIZIh9SkrDqJOvGE+Ih16sOazMuVxXLrkUOxsh0wJ0HDzg4PEUmYxbLmlanbGpLkk7J8zE6ydnbO0TEBXWQqCDZH4xpasP+aMryZkOsMoSFWCZIA9vlltmiRKkEqWDTORIXSDxMsgG+FaiqZdtZfnz/ESfFHquN4Wy55Phgr4eGec/Jw2PcRhGTMEkHzOc3bNaG+6cnhNbQdZ5mZ0l1TjZJQHhiFWNDwsHRKf/yn/whv/z1d7w9W3O0d8yT0wPOr+dMBmNwAbMt+YPf+wUn40O++vIbTOup2h1BCNbrEi0F4/GAPM8IwaMjDcIhgbrriFTMX33+Gc8ePOJ4ss+22RGlim6zpTMdXkmU9SQKysrw7t0VVdXhDSQ6p2xqxllOHidsqor5rmQ2K6kqQ4fFasE3L8948+qCatsnUwe54uP7J9TOMxxG/N5Hj3l095BdteP5xQXrcsf9u8ccHe+jk5i8yBBSsa1q6rIB41DeczqdcLQ3Yn845ZMPPiDWku+++o7X78652mzprCZJIvZGQ3ZNy84YoiQiQlBXBu/6v3lPIIkjDkYF948OSZKUq9kaS0KSCO7sD9BC03SG1WqNU70ly3iHjiOC7/fwhRA45/DC0xpY77acPphy994e1a5CeMX+aIQPBhwMhpo7p2MSmfLJp08YZAnzTR9KCsbS7ErCf4cs+AdduK33YD3bqiKLYo7GU76/eMdwOOZqMadpWook5qc//jFVXfWiUqXQMpDFEWmc3AKlPEkcU1Ybjo+OSeKEcrvDmpbgPJttSWccroePslqtEEKQJgmttdRdg9aCPE5R1lN3Da0x/SlZ9POyQsccTkfEkUbgabsacXuKrpuaPEqJVXSrXOvB6sH29L1Y95szTdVi2h7xKixMBmOmxRBnLV3bi4yxAVd3SOtxxuOtI01iRmnB7GrNaDhhOijwtt9giIRktdiyWpR9oKf1YAIHkynDyZTGeb5+dY7VKWUXKFuH0hnF+AAZ5Wxaz7Of/Jy7T54g9ZD5qqXsJDKZENIhayMoiVh0lkpI7j1+hncZy9JROoVKh0RZQe1idq3CypSOmE0p6FzM0gQ2VaC2Ap8OeHWx4PXVmnc3a5ZbQZxNyKeHXO88l8sKHefoNOLyZsd+NiZPI57cvUez8nzzm69pS49vPJtlTdN0jNOc62XN+UW/Ryu9585kwp3DI9IkJnOK89maN4stj/fHHO5P6TrPZnFJHhJOjvdZXJQc3btLSkzYrHn14hWvzs64WW34+U8/IBOK71+f8fbymnfnC6b5iNPJPjLWJFGE7DqiNGM5m/Ho0X3++I9+xuE45bOvX1PVjrppcFLz6PSEk+k+//r/8/+msR1CdBTFkF1VUVZl3yKJFUrdqrVCQHmBAHZthw6SxXbHX//qV3z43gdEScxYF3x3ccHVzQpbenSUgIXVvGS23rLcbQnBMcoLsiRmnBcI2UuKO+eJk4jBoMAKyfxqRVvVxF4TyYjgHEUSEUnPs/fv8tNPP+Rg7xCBojGW15dLFlUDIjAsMqwXIANZ1CdUq9qyKx3BgS8r7uR7fPj0Y8BzfvmW88WO63WD84a9YsD+ZExjDGXdgBREUjGbz7HOMx6lCCFYrNccTEZEUjJbLsiilLp1TMcRDw+GeC94dzVH6pTrTcnj07tIKZgMR7ds/34Qf3J8SKQhT2OOTvc4Pj2gLhvevLkiiTQH+0MWizWrZotONMNsQrNp8K5FSYWtWkb7e+SDEVVrQEri5H8QVonuYK06skTz/uEdvj9/h5OSs3fnzHZr8ijmR88+ZLfZsNluSJMULwU6BLI0JY0aNqFBK8Xl9RWDvQn7k5TxeMS712+R0uGcRojePF0Mhnh6OJSWveW77jqMtaRJxjDTDHXC+XaLzBT6VokWRxBLx2QwJJQNXdWBDqR5hvc9E1p4SHSCsQ5rDJJAkKIfSDqPsY44UlS7mjRPkUKzN54wHY45X89pTUfnHHVVEoIjThVRkuI6y2Q6Zr1c0AbFs6f32dsf83/89V8ShKCrGla7mtF0QtdtyfIEnUa4pmE1LwkPUy6XJUKllC5gfaAJAhcClzcr7j14wOHDh/z7P/8v7GqHUhnGKmQSEcUFpVHMVoYH9+/xP/2zf0xV1fxv//bfkyQJoRO4bY3OClznaGqLLAa4Fs53FcEAKqIjxRhHa6BsExYeLi7nOF0wSFMWJfz2xTlFkfLR/QMu5y3DLCePNWE45epswUdP7vPdV9+iiKm3NSJIBrkml5oXV2uCETw+OmAc5xxGKd9dX6O6Xrq8qw2/+PAp7z35mNA2/Oblb5kWI6bjEU7mmFCSJQp7s+Sbb89ZrWr++c+fcrUoqcuWt+s569mOxjviOGN2s6CuGmg8gzTmcG9Cngy5eTfn/cf3EJHCTEccKs9RO8VKz3Aw4HjvDn/5Z/+JdWeZTvZ6pnMsbrnufVFpGwVYpAxIFLUPGB9QxnG9XHIwGvL967c8fHAKwkOcwiDiTjTpN6Osw4uU/SijoiVSAikc0kvW6xXv3XuPEINselbO3mREkml2u5qcBDXsJcqd7VCJojKOZVWyNxmSyQjhPIaIgGI6GlBtG8zIYNqagMOS9O5VqWiN67MXbcdgWCCnOW1Z0pQ10/0DHrSCTdWwN805yAsuFksa0/NvsiRhmBW0riVynuPJgK6zSKUR1nG1WFKFwNHhKUoqEim5XrakmeDgeJ+26TgthlzdXDCdTlGAMxahFZ21DEXgeDImSInXntVyQ7C9PEREnthYhpMhs8UGb8D7Gm8ajvYmvD67YDI+YjiMWK62vD6b98Pp0e9ejn/QJ+5FWyON4dnxCZerOeum5Onde1xtNigPp4cHrLcrvn/xnDTN6Yyl6Tq61rJY9CAjBeRRxLqzdGWLsQZXbVFpRlUHaut6Y3wkSKKYtm2ZDodko4w6eDabHdtdSYpgmMRUzmCdZZRlJGlCFGmMMWzrjvl6S13XOGCQD/DW9at7QSFETyh0HqRUaC/Robf14CW266FHrbHYNhBJmGZjmrqP8wZr2SwqtusS03hCGwil4XR/gC0dTRNQKrBbbYml4mQywewaNouaPE6J8PjWsVu1TIYFl2/X3Ds4RgfV29qTglZoahfhdX/yHe7f5/ThQ/7df/wz1ltJiAu8Tth0mnVpqH2CjROefHCPP/qDn/PLL77j//n/+jeUPqJ2gTZoap/iZMqq9lw2jnE2pBQJSuTsrGC986w2BiszmhBz79ETir0jlhvBcud5PavZn0z4kz/6fT5+8hFKZqggSZzi9csZwkKzmfPTH/2C2CvGo4xhMiBCsZcOaEuHs55CxYx0xNFwyKYNbFct02TArm74+XuP+elHv492gfN356BypoNDzK3mSmUDCh/z5sWc9WLLx48OKa3h7nSCaTt2u47jk30m0QjTtBhnWF5uCc4hneSXv/6ef/2v/zc6FzBtyxefveC//dXnrK82vHs3Y5AWZLHg7OqM67Lhwd1DxoME4xqC7/DWE0cRPng609yKex1S9afDIkqJ44Q0TVCp5nh/zF/89V/z4N4Ttt0Wb2scEiE1caTRsUXFPXVQYqkseNnSdpY0TdBBsqkaHNA5x7t3M0IbONwrODw4JEklRZIwzFPSBPIkIslyIul58fp7zmZXnF1c4X1HWXeUxpCEmK7rN1MEgfEo5xcfPePDx0/42Uef8sHTH5GFAVW7pXEVnfU8fHCfj54+wFrD+WJBQJGpiKPJkOk05Xg6JOAYZDEqhkQHMDAvDXFakASJ85ZH9+9xMdvReiA4tHcoIbhYrYiyMYnOefn2DE8gjlJ8gJvVGrKYxbbk8mwFTuN9R9fVOOtZbSoQimdP7pOnmrZpidK+PsQohOw9tbtVBQ6Gk4Ks+N3VZT/oE/dwnDJMCr47v6JpO47G+7x6c8YkzygGBdfrFVVVkyQpbdOhpSBSPdsgiJ7ip7VCxpqD4QhnOsp6R54P2POeGQ3VtuZ4PMIbTxc8lTF42+G8ILi+2GZJTN21XG52VE1DQNM1DcH3VmrTOaIoIlYKdash2+1qqmaFVJAXeY+hdJZUK2SUYjpLYzuCdBwcjtkfnvDm5oqEhHGa8+zoLovrGWfbGSLE1GVD1+2wSJxpqSooRhnPv5vjgkWlEOmUbl3zy//6K1rXcXBwhGl6rsRqW2GFBOH56PFH/OqL33ByWPA3/+Vz4iLGBcve3j5CBt6sWn7vH/+f2K6u+dP//CtwE5z0DJKEEDx1aMiPjhgNYrqzBV++anh18St+/Ic/4id/+Id8/ptvcWg6n6L1kDfLksu15cM7TxhMj/jTP/9byl3d9xKzDN3AQEsePPuQVMdUa0ulRmjZr1H++Z9/R5LE3J+OeTdfsJ+OOX3wgPHpiO8+e8m/+r/+nzn77g2L0pA1giIfcmc6Zb5Ycbne8fjgkPfvHDAtDvmLX3/G1fWaj+8f8fbihmyQ8aM7D/iLv/jPPTpXZDw6OsU5j9ADqC3l+Zz5zYajvYLDYcKbyxvaao/B07ssZi/JdYpSoEYS0TiOTx+hfMnl63fMq5a7R0dcL0sSuebmr5c0Xd8eWC46EiW4upzx+Mkdrq8u+j7u4ZTtpqJICwIgZOiRA67fKlFakCWKzabBdV1fcBJFkaVY29J5w4MH91ndXGJjz2TQP2Aa0/VSDRlog2G53HCQDVAOyrZFBEEiFFoIxuOCf/bP/gkqOC4u58zmC0wQ5FnC08f3Ge0dkirFblcSK83l9Tlfnl3z4O4DikHM+fk5qU5Z1jtu1isen95j2bas1gsCOb5N+OrFOT969oBsOOHm/Dnfff+StjUUw5y6bqhag1YJ0zzm0ZNTBumQ716/xTtIkohF2/Dg/gNuzs+5ONtQ2X4YPMkTlJaYLOd6vcG3DWmuOdkbcXJ6hLSOl+dXvPfgMdt6y+dv36GihChN+vVjJ1Eomm1LkWQo2VLXHSDQOsaYXsgiPegoQkWSR4/uILVgdrMgGw5p6oaqbhASPvjgPTpT0Zn171z7ftCFezoY4WwvIxhkMV3X0BjDYFhgnaVpWpTSGGOJlCIE37vurCdOYuq6xFmHdY6mqpEi0HUNcZwTHOhIgg+MxgOMdbx8+Y7xdEroDO0taKYY5AglSbOc1vZ0QGc7nHUo2e9YW1P3QRkhGRQ5y92O3bakM5Y4UdjYIG0/iDSdZRLnDNKUlSlxGFKheXd+Q5pqogzunxyQCsmL1RohErq2IdgO73tAkjX9LWHvpODdaoZMIrqtQcqaJE6QOmG33pIjuHPnECUlZ5c3+BDIxprV/IZxPmAz26JkzCCKScYpk0lBWe74+KOf8OtffclkMiJEMU0wiNAHcO4/PObu4Yiz8xm/+fIcaTUqzxC5wqqU+XZDJyRt46Cp8SIiRJrRaI/p/jG//PY1jZdMT04pBglSSZqqZjAZI2TBYrHE4RhITbmpma8rHh8dcudwn7fPz9lcN5hYsN6+ZJzGfPDBU1IB8+tr8k5ColFVx+j+IbvWc9BJHh0ec5Dv8dvnL3j7ZskghiSZ8N77D7k7PuLVt18yHu+xPlvw/flbEp2S5DGj0R7b9ZLFasvR4SGpMFys1ugs5eTeCdfn59jKkucJh/mQF+sN+d6IX/z+J/zZf/jPKJkQp4K3b+Z89OwO1a6EsWbxZguRQHqPc5auzvju23MePd5ncbPj7bsLJsN98lRQdh3O9RIQKR1SaoSwGNsbiozpC4pXGtM5dNTf6JabFYNBxPHomLPLJW1Vk2d9QjQYhwgRUkrKrmVS5Cidslk2eBmY5CPevnvL//q//hs+enjM3ZNjjp89QemEzlpW6znffvE1i+2axw9PeHi4z99+9horYLp/QG1rNpuK0WiEMbCcb/jwfsTRZI/1uiQEj7Wef/jJJ6g05frmHWcXN1ReoeOIqvKsK0PXeqClMQ778pzpcAjWYQhorzi5c4dqteJmvSXEETpYYiEwputj87bFVA1RknAwidmb7BGE4N27GfP1hiTVjCdDOhto2gZnHcEH0iiG4LBGUDUN3oOWmul4ghCC9Wbb26+yhDwfsbfX4L2lrSzeec4vzogiTVpEjMdDjO1I4ggl09+59v2gC/f9e/f57PNvsW1LtDdkW1Uc7R9iQ0dTlkTy9tdTks60vcndO9I0wTnD4d6Uew8f883339M1tkeVujnDBwO6EEjjGKVr2q4hznK8C6wWCwSyP0EnMVL1vOlds6OtOozpE5taxQQfeoWZ9xhr6bqWweCUdxfXdLXp+dsWvAl4Y3ESnBXsthVZGpOnCRaNoE8xpoXmaDJlOhgyW8ypWoOyEc4bus4SnMRLQ9c4Pv3wAUUacbkW2NrhlcQ0kqaxONvR7DryJGU1W3MwHaNUTNNZRNwyO5uTjBKSLOHxqKDcbLh4veD89Rn/l//7/8y3X77gzffnHPzhPmXjEWQg4d6zU1xwvHyzYLt0RFGOihR11+BTzW7dcvF2jjURcaywNhB0SnCWgdZcXVyz3bUksUQFQVu3SCuIlWJYpJTzDcGYHnov4cGdYx5PHdv5lq9++xpfOzIxRJiOrvasTcOHHx6wnjXsDfd5/65l6wwfP3wPrwIX53OeHh5x92Sfdy9mfP7bdxRa8/GzJ/zop7/AzEvq2UuMldy8uOTt5Zy8KMhlzPVixcnxXb76/gucCKQZqDbl7p0HzMs1F29nvfFkOKTZNLxab3nvvU84jDO++Zu/YlXWbJuKZgFZqjjMc2yUMrc1B3dHVLOOJ88O+O67a4LvyLKc77++4HA/779v5YxRkeNVRNV0dKYn9hVFitIRm60h0jEmdpimxpkOHwmsFWgtKXcVm6YmW664c3LI9cwR6g4pNUr2Kd6YmDiWTMcZL99sWaxKalNx/8F94jQhloFqt+Wvf/MZ1gfGg5T7d46Z7j/k/R/9nO1uwSgKfPX9G6JBimgMySDl6nJG20F3O9+Jo5w4TwirJYNhhg2e5WJGSGKub664OHtJ7SKKQYJtDM6FWyKlB++QylNuK9ZlxeF4itAwLHLSKObl+YzOBJpg0AR0FrFYbznMU54+vc/N9YK6c7S1o6sNv/rtdz2wbajxXvP67BopA1naq+fqakfTtjSdp6rsLa9bMd0bkyaa5XxBliU8ePyIzjS8fvWKzhimkxFgGAwKzs5mHA7TW+G1JUsTvLe3coff7fWD7nFfnl+yXG+ItKRrDE3nbgWwHq00se4lBlJCHEUMBwVd27FYrah2Oz75+GPKckdd1X1fWfdOPhf6WPYgy8jTlM56kiTi8GCM6WwvBIZedOAdXdfR1DXOBoJ3WHMbvVfi1gbT718D7HZb6rq/dkZCo7VGeHoXYm1wNtA6R2tN3/PuLFeLJSrW5MWAh3sneCO53GyhC5imoS1buhZca3HGM80HvHfvhOVig298b91xgTzL8J1nPtsgrGRc5NhGsVlsyeKYtqyQTlFvHDpIjAmsZys2s5LdrOGf/PE/5eU3r5m9u+Lu8TGLmwUHxRHNtmU4GuJ2DW++PWd2WUNrSUSEtBrtI/YnU0QtaFe90d5WnkhE5DrDlo7lzYa6soyTEV0VaNYddhtoVx250CgLZy+uqNaO7XLLo+kJ7x3e4ezdgsvZDmyg2jS9hquWrM+XPLn3EGXBbbaYzZayrPiHH3+MRfKf/92f83DvmIcPH3JxMedXX3+DrQOxEhwfHKM7xer6guevnnN9U3JxsaQ2cG9yjG0t6WjEZrWlaTrSIGnrjoP9A5AgakNV1eRFws3smuVix+mdR5wODrh4+YYvvj3n5nJDQkyapPzf/uU/4ux6zup6S7WqUJHg5F7KzlYc3sl4/9kh+9Oc8TDm+t0KGUCpBI8g1n36U0pJCAbrDM4Z0jQjyyLSVJFlPQ1vty2py4r1ao1xDmctOlPsZQUnRycMBxlxDF56vLCYukaGQLVruLopkZFEBFDO8u78kl99+ZwXb2cEoZEywhJxfrPmv/36/+Dti18yFgIZjbn/wYfETmA8JBK2yxUKsF2HUoGP3n9M21Qo4RkOE1xrefLgHnVbcnP5hut1w25bEqmUqmqxIfR4B++QOiIOET4okijFIxikCUWWcnZ2zvVyAUIzyTKO9sd4Y8njBG89q/WaxrRczeYc3z9CJ5JBHDEdD/BSs9rVpFKA61n9nalI4hhJhJaKvf0hsZbkmWY4yiiGOY+fPub+gxOW82uW8wW7XUkSR0gBg2KI6SwPHpwyGA6x1qG1wlhDXdVE+n+QHvf1bE6cRtTGYlrXv6mxROz83xfhADRNQ5bGt29gwAhFJASXV5d8+/wlUurb3e2ESMS9kDeS/WqdcxweTNEyZjySLJZbnLekcY4Xt2AqZ4l0ipEe53p8o5P9Hq2zPVgqTSKiRLPebNBa9c7I4JEopJS9b9DfDru0xvqA2dUE0Q+askgzHYwYZgVnVze0nUcYgbUGazxd44iTCG8Cx+OC5c2G1+9uiAYxwXpGw4JESg6PDxBo6qZhOCp4++VbgjaMJh3jwRCpJSrSuM5xs1hinefmese/+l/+Bd225LuvXnK0N2G1XvLs5EeMowaEI04yXv/2DTpOiGJJVzlMt0NIwXQ6oYhHmLJB4UlERsCTqxi7qpBGcTI6YVeWXF7N8CFiOO2DMs57RuMx26uKZtXx9uaK05NTRG34m1dfY/FMs5RtaREuhc5Qm5rp3oAn9+5x/t1r9iYH6BCxWTZsZ2t+8+uvefroIccHU5ZXc7797g3eRHz67D7H+3tM8n1uzr6hKte8e2fRssJ4ifYBpOR8teSDex+yfHHG/qggK1JODh5Rbje8fnVO7jOqbU3qI+4ePuBokpHmY5bra2bNltYGtFDYxvCH/+BDLl9f8vLNjPfuHDBJE3ZVi58W3FzdcHrwgA+f/IhfffFXHJ5MaKodgyxjeNu+22zWQCBLY7wWeGdASbIsYzzKGJucpqoxraXtLNvdlqaxTIsCUzfYWw/oIC6weUloS+q6xJpAlGh224pmW0GkOD0+oKoMLkiuFlumgwG5klgsPlKQaRyWu3fvczI5RWjFq5dfsl6u+MXPP+VisUSogvWmxqFoWhiNCkaTjOu3l5RNhUGzl6c8ePyEb7/8DfNtje2g3FYUk4K6NShh2B8VxEZhvcB0BqcCe+kEKWAyHIIIPSNfwniQczgZslrvEE4gvWSz2BKcRWcZcZYziBQXN3OMhsaXHI4OiIPg8nqJFwETCcq6IVIZkYTDwxGj6R4vvn3D3bt3mE5HSBQX55fMZzOkUhwdn1A3Xe+ehR4g1nbEWYQ3Eq17WqF3Dh1FWFv9zrXvB33iXjc1bW0IXmClpMhjvDckMqJrOjpreielFGRJTNs0gEDEEbuy5NXr18hIQwiUdQX0pgvhJUrH7JYlIXRo2acUZ7MZQkBrDVXb0HYN1ppeKda63rASQOredt409a2WKGJQZBhrqdqaKI7RkUQr2cuBXR+Ft60FYwid6XVlQRHphEGcIYUkNo7FYs7VbIloLF3TCwpAksUaLyX7gxGTJOL16xneSrrWoSSIIKBTLG6uODnKefjwlNevbqh3FTqkYCW+M4zygo+fvddHxPWU1fWKf/ZP/oTNYsFv/uZXDPUA3zpiNWWvmFCkKUejA15+/gYtUrz1uHXLbl3hG8jlCO0UwVuW1wsSmVOkMaM0ZzgY0W4M90aHdLuazbykXDSYTcXdwzGTNGMwHbFrOs6+vyIKivcfPuTp/oivvnlHkaTcPz5B2YjdYkfkPZ0JSAP/+A/+EbvNmvMXr6nKHRkxh6MRl+8uuXd6h0mUcH12yYvXb/Gt4fHpHR4c7XEwGmJ3NV/8+resdhVxkbA32KOqOgZRTOc9WVGgrcQ5GCQR++MRtmr57vUrljcrZNA8vnvKT3/6Yz558ojz8yu+//a3aGNplh2jYU6aR6RZxCgbsN0pjk8PKPYGJLEiH2VsZ1vsrqPqNrz4/gWX75bUu4b96YDhIEOpATJSt3iGlrbr6LqO9WqDtZ663rErGw6mYx49ust4mpHGgUGRggy0lWM+W1LVFY3vcF2HjmOcDWA1wXuqpqGsHEbA9CBDWMPb83ec7u3z42f3GcSCZbmlNJbpeMhQa/aLESeTA5IYzt58z7uLS84WFX/6Z/+N4TDmcH/Cjz56wGia4YylyCNuFlecX6xYlx2m2vDg0X2iCL5+PkcnAx6c7KESiTcNwQtMC1XbcXw4ZTooEFpxON2naSs611FWDav1Fg3cu3NCEUdczJdczpasmpZlXRMPc+IkRXoYZTEXszXX5RrTWe4e3udgOuZivqAynrwYksQ5kU76v9ssYV3WvHr1hv3jCcNhQb0rmV1dUK5XBBvQOqHtGobDHCUjpIjYbDcQAm1rewSFTghBEMf9MsJ/R6fkh33iFp3DoxAiMBplxLlmNV+TRylN09JZx3R/zP07JyyvZ7QImuAoVzVSasrOkiQxnQ3Y1mOcYCAkRZbhlOLGzYjTlE3rmF29RriAihSJi6l3NaPxAOcDCIHzvUdQqp4l4hz9STyKyJIIERybsiEOGl3ExCqgBFgvsV3f3+oEBOOIjENIS5QrJqNRLyDQmk1Zsm4Di+UKvCPRCiUlWdp/8LHypAIuLnac7XZYF/gHv/gJv/rlryiSgvVyg1lY6q0FHTNfrUijGNt2VMEzyPfYHxwQWkGwguVqxi9+/lN81/JX//GX3H98F0xDHQxPH7yHbzzUgm8+f4kWGaascEHdOgI10/GQREkOJ1MyPcHtNmw2FfHSQS7pVi3ruuQ4G3J+tmSzbcAL0jTl9fMFHs+9R/u8e7Wg6gI/vf8QZxr++tdvKIoUfKDZNCznDcFqpO5j6R/+6DGZTviz//K3dOuGqO6lk3Gs6Zygnm+47hzBtWRqSJqliKrFtZ7Wl7x49S0Xs4qT6QkfPj1hOVuhjWCyP6FIcwbFANOW+KoiLjLMzrHcvWO1rJkODulMBS7j/PlbarNhW1lO9/dpjWXXOLrGMC1SYqv41a+/BQ0STWsNUQKr5Yr3339CJhK+evuSs9lbBtOCOI+wlWNXlox1DtZj2hIhAnGsQAmqrSQA1kJdrVnmiid3H1LmJU1bUbctUkqKQhGn+yyWG4JtUcQMR5P+/223LMsKUznyYUSeD1lvK96UO6x01F1N17bUbYeKNMPxgMq2ZFpwNDwgILm4vsaYjoPxlCxz0DmCl7x6+4rvX5xzdHTI4TRHaHh3s2Jja+4Npxyc7jGdTnn1/dd4BEoKghRkUUSiEhLdUtIyGCQUccx6U3E4nZJGkpvSkqNQSlO7jlRIIgezXYmXgqzI8NYzzFKUh+AkKtG0dY33gYPBhP2HewjXsatq3n/0iIv5JdZZJIo8zeC2LVXXXX9ICw5MTdPWSAXZoGDV7BgmMYMkw+Gx3lM3FUIpkqLAdB3jwZhY9YArIk+R59TV7y5S+EGfuIOQECArUpI8o6wMXetue0ca7+Fw/4DxaIwLgbpuqXZVzw8h3HJAesJakmq8N9StRWNJkoSucyRJzGa9oyyb3inZ9T+LIkld1YTg/r7HqPVtz5p+AKS17iFSStK0DUiPkxLTdiglEFKgtYDQBx9ca/GdJ9IRxSBnEGVEQRApyX6e0xlYrnYEE8AFQKBFjL+dSsdBU5WGateRy6T/HStFrDVpGuMaaDYd81mNCIYfP3uP4/0pB+MRqdbsjyZgA6ZyLC7WvHfvMbax/Mf//b+SKM12u2M93/Do+CGDZIDZlrx7/grXdj2mVgxpVy3KOMZphgqwW+8odzWb6zVRiMlkRLmrqWYN84sdacj4m89egI94dnKfaTwidYLtqmI4HRNbja89Qxlx9fotv/rb15SrHbZybC4rXnx7yXxWErt+AH1yNOG9J4/57utvGUQj7k3vkMaKznXEMme1LfEOCqU5yUYMlWC96UhTTVu3vH17zm7TcDwZsr9/xN07jzCNYzSZcnrnmIPhkGazo5lXHB8fkKoB19dLVssdonEUGra7Bl/vePn6gsXNlrtHB+SxwJmAFJI0EhyMx+gIQpBcXdZcvptxeT5jt+twlSK0LRfXZxzujxjvpTx5fESqI46OpwgCm/UCqSRVadFa0tQlsZY8engH5zrSVJBmA1bLXS8P8Y6Dg33SPKIYJYgIVosZ796+4+V3b7hezOjqBUJaWgsYiKOEIhuy2VRsVhXKC0zTkQ76xPCyapnuj9FSIg08mJyS5QO8gIvLK6b7BzSt6z2Necpkf4/tYkXTWp6/vqQsW4o84/7BHX7vk084uLPH3YdPsJ1nWxnyXJMXCa3vB/shSI7vTHn/wTE4wa+/e431jqO9IZtuh7OSPB/ivWMQKWarDa8u5zgUvvVUm7qn+9U1m6bFEFhtNqRFwXsPHjJfL1AI6sbRtCVZqlA+ZrWs8d6jlCdNVW/AQiKFpu0CxkOaFHSt5OWbOUfTKcf7+7R4isGA4DzBBwR9ijrPUqSC7W5HVVXcMk577tLv+PpBF24XPGkaE6cxxju2q5KucYTQJ8fTJEIJAQIMYJwjTzKiWPV+OqkxxuGdu8Vi9vCn9c2MsixRsUCgmc8XeCcIQiKl6nvR6nalDRD0w1B3Oxm2tsMYg5T9B7Le9MMgYQN1XXJ8MKQsWxpjb+lnHXGiKZKMPIm5d3qHNIlRHnxrwQXGccyuNLSdJxaaTMd01uJqi2sCtjWYrqNsGqRUDHXE3mDI5eU7jo/3MFXL4XDU7+w2BlML3n5/RbVt0CHiwel9MJ6ubKh3W4739wm149f/9UsSlWEai60Mw3TA3ZPHLC+u2C5KXnx/TkyBLw3/6Ge/xz/62T/gZP8E2QVc48njEbHMWV/uePv8AtdYtEiJu8D9gwk/ff8hgzjnn/7sH/L7n3yIVgJj4O7eIffHR+guxpYN9c7SNIJCRQz1gFho7NpxOtxjWOTYoBiKlEd3Trl6t+KwOOIn731I25bMLm8YREMublbEbcS0GDNJE46nJ9w5fszPP3wEUnE9X/LmbA42cDKekqUT4qBpqopPPn1KKhLm5xfEUYowgaubDd989RwdRWy3LetFy7uzFUJoZquGqmrYPz0hFoLlzQqCY7deM83H7E8n2AA+eEbjhD/5Jz+jGKbUqzVdtcEZi+k8X3/5nLPX17x6/pLl9YLtZsNoVNA0a6p616duA3hrKXc1Z2dnzK7nXJ5fsd6sqMots9mM6d6EF8+fY4wjjiOCgGI0JFcxpw9OGWY561XJIE3RqWI4zPBYBnnG3t70NoAWsa1L6rrFB0mUyp5uKB0PjvcYJJLZesaXX39F2fbSA2s9Wms6b0izBEQEvbAKqSOm+4eYtqbaLZnun2Ja3xMY05yAYz5fI0XMYJBTZBH7g4hpqgmhj/VrqVmsVnSlQSmIk5SqrTl/e81s0UvAA55hXpBnCVEkKAYFp3eOGA4z7t054e7hAZvNlpPDI1xw1KbmZO+Aq1kffgoB6romS1Om4zGyP5rRdR2jaU7dtKzXG8qm5cefvM9klPL5199QFCNm8wW7csdoNEQries6ojiia9segTsak6Qpxlm0in7n2veDLtxxFhFrSZYktE1LHic8vHcHY22v+MKjtcA5S900BARpkgFgnaPrDM71goQkjUFIdnVJKiOWizmj6RCCxJv+KhoCt9Lg/gmcZxqteiWY9w4pJd7b/oQTQu93JCCk7N2QQqN1xJOH99ibjIBApOHu3UPunh6TphF5lrOc9atkBIWkHzhuViW7sgEbiKS8fYJLpNQ4GxDGk0UJzvSnuBAc02JIpAWJyBCd5/0nj6lWFb6G5dWO0+Mp0kWETqCcotrU2LZjvVySpzGvX75lKIcE35JECUOd8vuf/gNefvcGZQOvnp9R7aDeGCInef3dcy7eveX+vbvcO7oPrcCVllSm+Cqggka2EBpJV0mu3qz47L+95A9+8mMOhkP+7C/+G8vFlkJnjEcDolZzuP+Y/XSEbiVl2RFpx/HpPtV1iXCaem15/959JoOE/ckBo+KI/WSMbz3/4d/+KSkZq6sdzkJbGh4enbK8mPFf//oFq01FpDwXl1fMz2dcX64wrURbaErDcLTPzdtX2LpmkiTQODQxeweHrHcl19cbnIem6QjWE6UJVWfZrUrKzpNE8N7D91jMSjarDmMapsMcszP89rcvsR66tuKTH79PaEuu3qypypr3H014/9ER6TDDGUEkI3arGtsZvPNcX89ACDbbDXXb4JwBFF3XIkRAiYRgBdW257r/+rMv+bO//EuazuJDQOLQSIxt2ZtM2TUVbd1ydrlCoshyRVJIBqOI7XZFEkekaYyMJJ2FSAg+/vgpd08OmI6H3D0+IE00Z9c3XFwt2OxKEJKmrplOp8RakBV5LwFJJdaA1oGHT095d3HBN89fMxrvUeQT6s0K71ts26JUxM31isXVEiUFGkcWZwgZ94jWvSlRpLlcrMhVgVAWoTWdt8zKllgnDFNNpAS1bVGJIs0TDg4mjIcFsRSkUuKbhtYZ7p3cRceaLE9YLracXa4ZjHMmkwIheteqNR5rPEpCnmdoGdF0BnAcHU1o6orLmwXFdI/dbsNut2MynSKASPUMFmP6+VscxwwGg/7mHUUgfvfa94PucQcRyPOUWGu6smGaDXjw4A5nl+ckaUqep1hre5Oz7OPjXdP26jHnURqiW6SlEOq2b1cTDwtMWTM92ePsxRVREiGExPoOUzdIFUiShCTJaOoarWI60yFVTw3TumdNSymx1iJv7ecq0sjW0pYlHzx9yM1iRpYkxPGATbmh7XrzXprEKKVpnWU335LnGTfXa4b7Y2y7pa4adByRpinOeoQWHE33uFkseou0C6hY8eD0Du/W52g8wzzj3/+7v8biyYeajz96grGGWEesF0uUDMR5Ql22BAHvFtckyYBuO6eICkaDrLdse8Wbly/45JMPWZ4viIWm2lUYKVirlIODCc1qzWpZMkkG7E0nDNOCKtpSxgkyBEzVUGQK1ymWNztWswV/+sVzqtLw0wfPkHHANg4vBdSKT578mM/K36BSQWUC333xmoN0TDOrWG4rTNNwOBrx8Uc/BVtz9v0bfvn5t7x//wQRJJttxfzqmrHSfPfVd7y6WDMdD4l94Muvv2JbxWRe44zjaDSiULC3f4I1nna742D/ENnFCLelmO5Rbra8eHFGJBVpktLsLD/9+Bmfff8G3yU4ayiXNb/44z9mc33FZ1+85KMndwldr7RTqWR32SCqHU8f3SWNIt68vSTQgpHYNuFmtsO1HXVd0VWSNI3QccCZlrbtEaTZICYvIlrj8N6SJJrJZMzL5++ItCZWGc52dMbx4P596rrh6uoG7wzFYADCUnUdWkh2xtA2LXXXkEcxZRDkmaKuWuqqREpBWdfsDwZ8881zalsRjMM1FhEnlM7jo4y2acjzQb9W6ywBy/07RzQOrt5doCPNz37yCUL37Y+3r8/Y25tyeHrKdrNiu5khlGK5KmlNR5wmCKXJ0oim7nhTr9hudtR1xWhUMJ6MSLuU9W5DkkdUdcV2vSNK856L4g229cgkIs8HHO4fIIVgMZuTpSkeyWq9IShPY6q+d20EIU6ItOL523ccnx7R1ilSCrbbHUl8K9VWEms6ApI8SXBth0hgcjSkNR4XWvYP95FCIEVPm9Na96gA0zLIIgQB6/r2q+n871z7ftCFO9ERB4f7bNcbhnnOdDLqjehJhI40Sqv+w7cWZxxaqf6DNIY87wcNRVGgo4jFYkHbWgSeIB1JnLBarPu+lozojIfgCfzdidZjbUfXWZzyKBX1JhDf29ZDAGM7wt99FkFS1zW27VspWdb3rpfzFcbMCDqmMy1ZmiCEwBhDZwxxpEjTAi8t5XrbC2s7Q1V3RHVDnMSM8hzTGlCKvYMJcaQ42JtwuH/I9fIC7TQvXl+TFQmT/RHWtpiqY7XaQKqJ0EwGYzblDiUlMtIsb7bsHYwYjoek6ZDN6pJP/uj3+e6rz3j/7vu8e3tFrHO6tiVPNft7Q7RWtFXLaDhmfX1F8I4sSvGNY3W14OG9u6zmW67KFVUn6NrA5GjMd5+/4fRgn4ePjjCtoewL+pJvAAB5mklEQVQsaRsxPppit1vQgsnokOcvvkeQ0C4F/+L/8Y+5eHfD2cUb8rzg8YMP8G3H57/6NVfnC7JoQIokSmJElHB9dYNvLLN5TZ4WfPTolKvLGcta0NU7KuvRaFIc3sfcOXlIu97y/fPXvPfBj3FoPvvVb3ny448RrWFvMCSWCV7C4nrBfz77NcenIxoE1zcbfv+jZ4wHGX/5l58hIoU1Hc2uZbNtmBwoDo8GtHXHg8d3+O1X39ASGE5T3jsZsnd4xKqq2R+MELJvy/UzEc9ms6XtDI0JxInk/sMjLq+WtK0mjsDYmiTTiNCr9EajgsvLBeW6om0r6rJDSpjNN+wf5Lhg2BsOKLeGrMipKkOeJJStQWuNij1RohkVCbGEjx894Hq7RlpYbTYMYw0+8Obqkkd3H+DsFUFpnPWkScpqcUNxtIf0EtFaxuO+R//87XM8MZN8xOP7d9FKslic0XYGFTosAaUVUioGk4xR3KvTtnWNimJEa5EqpascygZKbzkaHiM81DuBDQanQWUJe8OCYjgE70m0pG1ahoOCPC/Ybkuk1mSDIXVlWKwWRCQstiVxEtNaw3q1ZTTKcMFhXYdQEdL3wpbWRkQEYh1zfrNiWdYoLQjBsD8doeUtUVBrokjTth1C9yGn/obe6wmtsVhrfufa94NulTx99JjLqxl12/REsGLA9c2s3/QAmrZjtdkwm/cy1kjHWB9QSvLhB+9zeLCP94HtZkdTNchbFZjQinJT9e2QIicE17dChCKK4n7Lw7rb07Sm6zxCCpx1ZGmKcw5jDUpJbrnrmK7BGIv0Hh8Cm+0KKTXn1zfs2pqLqyuKIiOOI+qmZr1Z433H6fEBkYrY7XY44+laixIRWEGzs1TrCmmhrCq0kgyKlHGeoZzn3Zt3rG8sN1cLnn3wPj//vY8JnSERiu2qpi475pdLHt57hKkMo2xEIhO6uiPyikk6wFWBdlPx6fuf8Py7lyRRxPxqQ9c6gg2kKuZnH/2IkUrJ0xjXOL754hXKKhISbBd4/d0ZUYg5HE5ZXW8IHUyHQ5689xApFIN4wGRYUO12rCpLu7GEnUORUJclly/e8ODkEevrlsXVhljA3/z5X+G949P3fsKj/QeUuzWvvv+e7dzy/sPHHJ8MQUfMLyuWVxuCVmznhtF0xD/9h58yv9zw5mpB4hWRjOhaw6TIWc6X7O0dE6mEerNByYTzN2dcXlxwsH/CIM2hhUzHzGdLrDE8uX+XvYNj6o3l3es5B4MJ4/EeX3z2a1QUcbQ/wYrAqlqzWpVcnM9oui3PPnjK9c0VTkMcRwyyFCsUCsViOSNO6Bnt2uN9R3u7ydE2HlMHvv32HU29Y71ek6YKpQVKRRR5Tggebs1I3sNivgQCHvqficBmUzEe5IxGA+7fO2I4zijLGhXfcnViSZLG1FXJZJjz0XuPuVjc0Pqap+8/5cmje9y7e8xssWY2W6FlwDiPsQbjLHv7hwQZePv2HUdHx4xGA7w1fPXt17S290LeuXPE4cER6/Wa1XZO2/YkTKEEWZZhOsN6dcPx3pTJ/hRhbf8wixSxVOADg3zAZDTBmJa2a5BJTJJqskHK6ekJB/tTqvUG13V0TUNVlpS7Hbtdxc31FVoLBoOMm9kNbSNYbSv2pgWDUUZb9YC5qm5Zb0p8kEgpEfRmKqkteZbw4u05l7MF3hmC9zx++Ii90RHBCdrG4F3f2tQ6QgRBHCdoFfU+gCBo2o66/h9EpLBZrlmsN6g4QicRQmvW6x1plhGCIEDPKi4rBBJnHI3pyJKI1WrBbrdls96yWu5u+9cOrSQ+KJq2Q+ARQuGsJUr6YaaQvfRAKUkIFuhXADvTEkUa50zfLok1PoS+VXPbAtGZJE4VVdMSJxFv375ECMFu06CjfmBR1yWD4YD3nz3j6aN7pLFgu11xcDACLwhIhJfEIkJ4GOYFSsPeaMJhMSGTMdZ7tlXJarumrbYUxZDRIGV7uSU2MMknvH19w/VVxeFkn3E+QjpIVUKzq6nWJeNshLIKZQPeOIILXJ9dEvkR1xfXpCohE4JPnz0l8pZ6XdJsA9JGqE5iy448yns2ilPsj/c4f/6K0Dru3T0i1IL5i2uaWcXRdAxeEYkh0kuaZc2g2CfqUnwrabcW17S8d/cRtILMxwiVMJI5q/MZbWcZiAG5HPHRh49pjcCsBduN53qxJQmaaT4Bb/n5Rx/w6vUNF9dzIi8ZpTnhNgauTSCOxxwdnVLvWmzVcufkBFs1TAZDlHdID2cvLnn+9QXDcU6SRIS2I48cs3nJ3nDEflKQSsn+ZEqRp9C1FNMhXismwyH1zjIYT1lXV5y/u8SrQDrQRJFEqISuW4MweNcRyQjrPGAxXT+Qb0yNdzUAZ+/mZEmOoMcnaCWJIoHAExEY5DE+BDpv2bUNEPBBIITicG9EXRu+/tVLvn/xhlEuUaljW26RUuDw5FnWs+FNYL1Y8/z6mpvrJXFS8ODkDpcXl7w7nzEdT2jNDiKJjjRCCr7//iVCKg4PTwlCUJZrvnv+AlJJkqdkWcL+0SEmWK6uzlitOrab9W32QoHwjIc5T+7cw1SOdxeXuCCJkozDowlpodi1O9bbNQ7LeDikCzA+zjm4P2YwykgJXJyf03UO52C2WLFcb6kNNJ3FGI8Qmu3NkvObEi0VB8dDmrZjfbPlYG9EMUiRUpJlY1brita4XjuoI1zjmK22OBlRZBFxrHn45AldWSMIjAYjvAu3//zfF/3gLNZYkijGOUe5KzH/HYvcP+hWyZuzM4qkYDNf8eEH76O0JB3kpHi2VU2zq3upro5wviVSkswr0mJAHBfMbt4RZwmHRxOWsw0+CCZ7E5adJY4D1niEslghSEJ/gPH21rweevKXlBJpHZ0J7LqWrMhpm5r96ZCT4zECT7nzbHc1nbEEBNvdlvVyw6pqOTmYsm0MbWf7tUKh2KxXrBfX5FlG3ViyIkbufA9hF4IkUbS15e7hAVW7RYR+hzlOEiIRKHcVISQMhwPs0NNVHW++v2S7WnN0tM/b5+8YRiN2tuL+0T3MssRWgWWz6nVt1lO3NbtmzaN7j0AI/vavv+LwcJ961fLg+A6DOGO8F7N4c4Xan2Jbzfsnp3z51XcsrzYURUpxqOjeVRzkY7p1y83VlkREVG9L7t6/y8P3p+yqHbumj8f7AGbWMtJjhtE+ftewfrPm289ecfXyil/8yR9xp7jL/7e9/+q1LMuyM8FvqS2OusK0m6vQKZlBJkugu8ki6qn7vV/q1/BvFVDFJhqoRpNJJsnMZERkRniGC3N3U1cducVS/TDXPud6UHQE0ADbELYdBjdx7z377LPWXHOOOeYYv/ryF8R15K+v/44f/vCHvPn1N6SYefb4OT6MfLxquT5o3tzc0g41PgVe/v0VHz9+zv/xv/0FT599wv/9//a/8Nd/9a9QOZC7nsYuuLne8T/89B9jRwsm4MfAX/27X/DP/sk/xfeei8unfP23b7i5vuN7338MKfPB8gN+9qu/RUWHGhLPns35/qcf8urlK1588y0//KNPefjwDGM867dbPvhgxSc/eoSuB8YxcbfZsWwD33x1y3574Effe04aRrabO15mT1IDhyHT9RkYxNhaSbMtpcybb+/46BPF0I0kNLt+oKoMdgFxB9bUKMRzdDxo6qpB25HuIJO6kNnFkTq19NnRzJbkMFK3FXE7ElLP4mxGrQ37fc/3nz7hxx99SNff0O1G/vLvXqEVXDYNjxYP+evbL7AzywePn5JMRQodVat5/c0XZAKPPnzMOEQg8vjRI9qm5rPP/p6vv3mDUpHv/egPePjoghe//nvqYS6UwLMlKlVcLmcMcwvWMjMVr97eMCbLvDK4WcugIs8+fEp/6DjsO/a3G2I74OqG2taMQ2TWLsjJoLTm+uqKy0cPuV6vsbrFWTFyePPNLZ2PPH36BEzg+u2WxlmSimI6bB3zpmEYem5uJdF6+ughQ/A8ujznzcuXrLsD52PAOoV1Bh8CIQoEapwlozBGc+g79vsDoThl/bbXOx24nbP4cWQ1mxPGyFc33/L1N694/uQCrRSr5RmjH8kGKqd5tLzgdr2FBJ9//oVQkjIyNeaMME2Gkf3hwGpRs+kzSkectmiVRXlwMSeHjB8HOTWjpWlaUtwQqOj7A20rsq3XBppGM44ZpQ0PLs/ZrDv2h4HzsyWHlyOffO9TXnz7ms8++4rZvCH6Aa0TDx9cEHymqkQnobI149hTz5YSFFtHjgFSpmlqyMJsSSlhlAEU/X4gpowfE0PXUbuGzd2evkschjuePX1IqytevvkW6xxZBZJJDLueprLMm5q5rvn5538PSaPGjK01OWvUIbK+2vLJJx8TUsDELSZqCJpVs+LRg0s+fPARMQT2hzXbzY4nq3OW8zOaec2snvPixee0iwVxG+hGuFnf4ZTjwZMLXKrYb3Yc7rZ8//vfY9UsefnLX/PDP/hzVrXhX/7Lv+DTP/2Qbr2lux34/g++x9/87GfklPnBJx9js+Hp+RNe3dyReiBart+uMcnyj//Bn+MPHbWtePt2TW0a/BhZzRY4LdODKiTevHqJ7+DVl9/w9PkHNG7OuP6KJw/OUFnx+OIZu0NPGgKH7ciD83O+//3nXL16RVaBhx88wSdxGT+se8iBy4cL/u6zb3n5+g3GZp4/Osf3gXGQ6cVx3HF3t8FVllhkdvte5gdE2U/hXMXQ+zLABcYZYowoNEPniT7y4PyS0e5ZnFn+wT/8Hr7LfPbrF8xmis2dRymoasfsouX1VWBztyWQOH+0wvvEfrtm1izw3tP3PaadYZ3jxz/4Pn//i/+Ins35wcc/FCPrGFEqcxgGnj79gLMnc7p1xzAccK7m5etXaNuyOmvE3GG3QRvFmzcvefLwITfXt8xmC549XfLk6SO++eoF1s349OECVQnbK+63uKYl9QOL5YzbuzXNTJOUQ1nN7Kzi6cUTfB65Wm9Z7wcqt4CcOXQdW99jtGHcbFDKsFwuMVbEtFZnZ6iQeR3EWnB1cUbedozeE/qB2lX4MGKMpaprusMBq8Fqw8XFktXijOu7DU+fPqbb7dgfOubNjHEcQIkHptKakAIhJmL2WOdIwDB6YsqknAXC+i2vdxoqcdagyGhrePn2ii+/+pazsyWb/Q6nFJXWjEmEdx5fPuDpoyeMMfDN12/JOdNUltpakWtUMG8rlqsVMSYa2zKOPVpnKqPp9j1VZYl+pKq0mK0qzeXlGT/96U8ZPdhKeNsqywBQHwybTtOHTCKjcqTve1CK27tbPnj2BK00h90dZ6uW4ANKRR4/WNHUQiEcvOBe3XAgkwtW3rHd3nF7e8Pjx48YYwcaQvSgEkrDYdfR7wf63UgOEEZPv++5u92z34w4ZfmzP/pDvvzsCyoj4vgORw4K5cXy6mL5gJ//9S/Y3W75w+/9mIVp6HcHYh/oNz2Xy0eo0fL26ytMMmze3jGrap5dPuDZwwvGXeDbL75i/faa6xe32GBw2ZAO8Df/5m/o9hG8odsOXL29Y389MKwzV6/f4reew9s7bu7uWNUtHzz6iF/8h8+4e/2KcZf49INnDDeebz77muW85W/+3S/45vNr4h6uXl1xfv6QZ48/5MnDC5zSpDGz23p+9IMfouLA9vaKm+sbNus9Khr8fsDETFsvsVmxX98x7geccazvNqQRxnHg4WpJow19l3B1xYsXXwCGus382U9/yJcvXvLLv/+C3dhh28DN9VvquaZyDR9/+JQ3r1+z32ypTMsPfvApMfZczBY4Y1gt5iKstL4hqsx+6MsIuuLxg0d8+OQpH37wmEeXSy7OWi4vzpnNKkIQB5zoB85XZyxnDd1+i7KOwR+4vr7j8y9/zby1RJ/4+PkTPn72iO1hR1U7fviTH6KUxncHkvegNNZU3K23oAxV3bDerFEa9ts1r9d7fv7Lr2gbw2JlUTnz9PIZFx99yI/+6EOub16xXffUdc1muyZmSzfuSFELJJkiN9c3XL255vMvXqCMZj6vWc7OGHZ7Xvz6C75+9S3BR2Ia2V2/5ee/+IyvP3+DQvP69WuuDzv2fuT8fMX5+TnGJ9Z3N3z95UtefPMGZSh+kJFxD8MQCRHu7nr6fiBnSaaMc8QU0MD5Wcs49NzcbWnbmq4/MKtnGK0JIaKNxRhN0zYMw8jt7R3z+Yx+GHnw4AKVEtvDDls1+H4kK6Edey8U4ZQyWcHo5ffD6CX2ZMRI/PcFKlFZsVjMGeJIN0TaxuB0ZqQi+kBMgadPH1LVNWPv+Yt/++/Yh8j5xZx51eKM5m6/IwApRD78wSf4EUKIYkUURWQqppGL8wv2Y0eKke3o0cax3w78+Z//gH/1r/5fVHVN2zr2IXE4DJyfL1ivN2ituThfEX1gv9ujVCKTGH3gT3/6Y/7tX/xr0InV/Aw/Djx8eM5i7litLol5y91mjTW1DPekhCZinPA+5/MVm92adlmTVQA0GaEgjmFgNqupXcWh64kxYYxmv+uYNTO+9+lzXvz6S/wYISa0NsJJPhxolePh2SPevrqm23v+6T/7Z/zlv//XLGZVsbfqqZYzrLZcfXsFSTF0PW9ut+xG6aBfLGf4rMg+MxwCsQ+sWjEl/uwXn7HvPH/y6UeYZAljIMUMg2F/6Hj28BIVLWk/MjdnfPF33/Jo9Yz1NfztX/6Mf/o//1/58sWv2a8HPvrgIW++ueHrL694+OgRc9ewnF2QQma9vaa/3WPGhAqaGDX9bs+vfvELbq42XK9vmc8X6KSwyvHB4w/xfsRmy93NW7QWIaibtxvWD6+xtWHMkbv1lp/+43/Izc01Q9dzux/5o588ZTde0YWexcMzslb0Q09/CFRVpG1qbq+vGPuOx49a/uCP/wRde/7f/89vuLl+iw+J1XxGJNP7QOilyvoHP/2I5eyMWdOglOft1VvGQTMM4tFodWRWNyQVQWu8D4w+SFW3mmNQHPY91jZcnq/4+uu3vHp94J/8kz/jX//lz+i6A4vFnLq2AsNkUEaRVKJqLN732DExmzcoFTkctuAs45h5+fKKH//wY3abng8/fMLV7TU//9lfQ7I8f7bg15+/keGXZWJenQt1zoCrHTlmSNANA8vlgocXDzg/f8jdm5cElbmYzVFO47d7vv32JZ5E5eDOj5icedguWawusC7R+56vvrjjsBto65bl2TmzpmV/2GFNhTYGoyyjDzStzErs9mJicHt7y3w+ZxwGVmcLDmupmPuhRxEZhhFyJCWFUhrnDMYYxlHx6PFjdpsNyjramNgPnRhspIxrGyBJczhHUpBmptKAyozF6UcpoSnHKAH8t73e6cAdQsTHAV1ZcpYHdnG+4nZzoKlrHj5+wL7bc3ezZr874HNm3rZU1hJCwGjLrGnZHHrOzs4wKPZDYLVoSUNi6EbaxvH8wyeEQXHz4g6rFGA5HDq01nz2q1/RdZ7VRS1CUcGTlWF/OPDhs0tm1ZxhiFxt3lDP50INSp4//MMf8fXXX7De9lw+mOF9z/n5EgicrR6w2+158/YVzhlSCijtqGuHsgqlM8Za8fWzYhCbcxTNlChBW3Zg5vHlhRjBHhJh9NTa8kd/+EP22zV313e0Z3PEAzmjgsJGjTIaHWHsep5/+BH/2//6L/B9z+KHH9EPPYuFZb/dMQ6ijfzsyVPC168YhoHL1SVV7VjWFzTtnP3tNW9e3/D4yRlvX71lvdmSY+LHP/qUVXXGbtfhqNjvOxlpvlywmp8xDGtshrwPvLm5Y3f7lsZo9ncHdm/fsmrOUcOGuW14s4a6XoCOtPMGo2q6zZ717TW72548RNpFTWscxMTN6zXffHtNPW9QCIVxf7dnu95zcekhKva7LWGM1KYGpRhzYLi6JebIw8cPib7nl5/9mu1uYLWcMYTIZj9QLzTaW1IOpB40Cm0V/dDR9SNN05LzwL/7y3/L+ZMlIUmFVC9qshLqmFEabTSNM2Qd+Zuf/y3bu4621qScAAMGLh/MeHL2AGUS4+DZHzo5tPuAUQZrJSEw5i26qTk/P+fXX74GMj//21/x6OE5zhq6w17WVmUZQiBHRY4Box3RB/puxLk5u32HUxZipG0dV+tbHj24JIbIt29eoBKczx8R08g3X71hCCPL5ZzDPvHsrIKsGMZRpgRdw3I5p55brl7f0m96Pvn4E96GQNU2rGYLYh4YuhFbz/nJj56I9k9dkfvA6CPebzkcBroebq/EEvDxowU+j4Teo5Jl13cYrVBojNWMPrJYzjkcOvaHA03birhTBIYo9mK7novzFQ8fnPH551+XvWVJGXKWZK5uGjbbDUprLIrBDwxebOQSCucc/X6PsTKdbYwmxHgM0jGKKxaoIyXQVhXdbykQ+E5DJYIICa4aes/Zck7OmfPVgifPnnJ1fcfnv/6KmBPL8yVNUwlE4iz7oefbqxvZiJfnfO/TjwmjiM+PXcfoB374/e/z0bNnbLZ7vvzyBbWtCCmijObRg3P+L/+n/57rmytcpQneo3LGVZbVakZOGWctw9CJgW+Sbn6IkcVihqvgl7/6nAdPzpmt5ijrxDoqJjZ3GxmUSDJklGJGq4y1GeccOYsuxzB2mEq61FpBip4UI9FLeRZjwGrISbBwlRTPnz3D9x1NJTzSum2oC3PBGYuOYLVjv92xaFf87K9/gdGODz54xjiOWFsRfWJeLxi6gbqe4YdAZSr+5I//lI+ePefs/Iy7myv+/b/5V2yuBftTKPabjuQds/mKy+UZKRi8j2xvDly/umHsdtSNw8eatB/5q//wS371+dcM+0g4wGI24+2bA7/4j/+ReeV4cP6AN6/uaJeWtrIsl3Oq2kKCzd2a+WyFH0XSwOTMaj4TrnbTUlUVxEx/GIhj5E/++CdClssKPx7Yb0eqpsFVtmhzeOH1K833v/8xn/36c+62HQ8fXbCcO5JOxAwKDWiaumG1qLl8PMMaxWaz5u3NjpfXb4lo6rrh5bdrbNWglWF1NqNdzNC2QqH48PmHOKP49ps7Pvr0GR98dEk9b2kXc9plxdlqznjIvPjqpWDQxlK5GqUQd5YwkrKmDyPWVVir8KEI/1eW1287Hl6eF716S9U6rEvUlRYd+6TIWTP0HhXh229eo5Tj5ZsbKtvw8SePcDPFm6vXHLqB2fwMozT9fst2IxDLbF6DMhy6nuAz6MQwDPSHAR/E/anWhjwmVosZu80Nr96+5eHlAzARcKTa8vTjJ8zbFVk7/H7ED5HRe7r9nm4X+PzzVxhj+Ok/+JSzsxlGC6ThrEUrTcwyIj+btTx59ID9fkNVWT799BPB6EMka/AhiClGZbm8uKDfd1SNE+jIOcYxMHQDfhjZbnd0/UAiQ0r040C/7xh7T8yRse+IKYnscvDELDh2Skl0SZQmlz+D9C6M+e3D8TudcQ/J47TDH0ZmznJ2thTrphz55S9/yWE/YlxFNJp57WicYe07btcDMTmMq9n1A48ePWLY78EY+v2B4BP/4//5f6CpL/i3/+b/oEuWpnXEEHn+8XNur6/4yU8+5Zd/93NsVTEeBtFYCAPL5YzHD855FUZ+9fevePzkgouLOcoouq5n9Innz59zffst5xczTCUGwDEEspGTO7OCbAjxgAKMslhjGYYdtXPEEGQBKMppnQg+gJJFOA69aKfEyOZuXVx/LEOX6XY9lYOmsTR1Q1SJoRvoY4QG0ui5ePiQEDo+++Jrlu0SN2tRRuOcJiRp9nT7nsXFGW2zJI0jn3z4CV998SvevL3i4sklNRXZK4YhcL5M7A+e5WKO0S3ZBiwLQjoQw4FvX17z/NEDnj17QNKO2mhctWCxXDA/RHw3cPAdHzy44LAf2Y4j3z97zOef/y3JKg77kYcXC1arc5IPdN2a/brni1+/ZHm2xPcdYy+OLvt+w2K24PHjc65v1xw2B548fsjo91yePaKyLW83r1lvOsysxlqoWsPMwb6eC/Ml9NTNnD/8yRLvd8Rco20U/efRi01V0Ghn0FXF9Zs1s/mS599boStPfzdg9MB+P6AYeHq+ZHOzxdWG/+4f/Xf0+8Cvv/glf/oHf0R8/ZJxPNDMHSFBd+jROfL00VOc0jj3Kev+irfXt1SzFcY1LB/MRKipO7DZ3fD8w2fE0ZNS5E//7HuopIjZMGuXPHj8lF+//DWzZQUhUdWO3IgMsnMNrJaMfS++oyHRzmbMFi1Va9lsdyxmK+aVI/iRb69eYZQYW4ewY/HwMcMwoo2mGw7YJFINacxkElkFxg4eXT6knsGLLz+nck4G5Oo51+u3GDuncQ39dk3cbWkXFyQTCcPAiGbM8Md/8CmXFwt26zW70bO+26CMInpPjIlsLAnF3d2axbylbWtWqzMG3+NDT1XX9LtBDj3jqCvLmzevqZShcpaYMiEmcooQFckmqnYOZBFls4E8RmLIRDKNNngfyAlCCiQgeI/REqzhlLmTM2TxDZiC+G9zvdMZt0FjlMLqzGxeMQ49y8WSr9/eSAlqDDlnbMzobOg9qKwJCKXnYmb573/6D6mp+OabrwneE8LAP/2f/idyhH/xL/9Xbvd7XGXY9wOXjy6oK3jy6IzPfvUZ11db+l4WR1Xnku1krm+uRTpzZshenKuNTtjKoXNm6DeQHA8fnOO7jjCOZBTExG7bcfbwgh/85CMuVjXzqkFpQyagjXw/KVHXFjRoNCEnlBHlnjh4mcQKA96PKGeYLeoiqCUMgTwGTFDUjUP5wO4QiD2kMdM0LY1x3F2vWc7mnF8ssDlSOcftes/blzds7g48efQhjy+f4UiMw56//+yXvLne4mNm5uZ0m44xDDSzmsNuxMfMgCHkxHnVkOJA33W8fnnD5XLOxcM5X798TR4SM2fJJLrdAGPG1Jabq1seP3rKH/zhx5ydLej2a5JxOONYna0wrcOmhPGB7U3HNy+vSAqqqsLWFVVVMwwDNZbW1Hz07Cnff/qM2bxGV4rtPhLjSE6e/bbjbNVSO027FN/Ql6/ecnt7g7GK12/e0rSGt29ec33ToUyksQ1hDGijmNUNISW80mx3a7r+QDOrWCwdX//6FTdXG3xvsQRi0OyjfKYqRSpjefr0A1Su+frNt1TKcNgJdZAUMSlDNHz9zUu++vZL3l695PrqABhUjsxmjUihpiCsI1q6w0BGcXuz49d//4K/+uvP+Ptffc7lgye8+PobGTbLBtOIZo9KMntwe3vH25tb3t7dMQ5yIJ0/XNIPB+5utvgRxmFAk9lubjDKERXEHFien1GZhMqeunHElMg543MiEqm1Zq5nzNqa5x89IkZF1bbUyxZdGaJVXN/s8EPAb3e8ff0tShmcFbjldn3gsO8wKtGPB169fsMuJ3yMrJYLrHb4CMZVUgNpg0KJjMHg6fYHfC88+RQyVVOJTr42VG3DfDnDFg58jAmVIyl5fBIoNCfx88w5kkLC54hPHmONxB0AnfExkzMoJRIY5CxwSYqlf5akuRwz6feFDmiw1M7iSYQIzlj6fs/TJ09ICa6urtmst1izkg106LBOy8LO8OzpM+6u3/KzX33FvFbM2zkffPCUm/UVf/EXP0Nrjath6DqePXvGfGXY3BzwQ2C/2+EqRx9GHj95KEJDaRTs28ByscDqCgDvR/G5zCMff/KMzWZPCInZvKZtDPvDCHokBdDG8Dd//TMePbrgwcNLyJqvX7xiNluglExcdV1PKCpvxoJSQiVKKYKeMHCDJrNcrGhzYLd+ydANuKXFuQptNXFMDEMk5UhTVaicaWYt/aErRsaiq2CrOVev7tBW8fDiIR998owYR25urqlqzeEwcHsjo9jL5RxSpjv0NG5WzIszAY3pRwbfo1YfkpNifbvh+s0dyjV89quvef7kIR89fMx2u+HN9Vu2fcfifMFhs8H3gT4cRFlt33P19galNUrBvBWd5durDUbB9rCHDPPZHGMVdVWJ5rZLzNsZQ7/HqCUPLy+52a0Zu8BiPmMYA77vqRrDRb0ioDjs7mjaGqscFxdOTDf2B+qmpmkcY0icrxYMo+gzV7ZmtZjjc2QMnsVixacffciHzz5mfXeL3+65W29Y7285e3DG4AfGOMowRzbc3l3hnCL6jtdf7/now0dUlWOz71AZ6pnYkA39gYvzh/T9gQ8//ojXV2+IRBrnZDq4NuQg0Nnr11dYbVBoHjw850c/vmSxaIix4+7mhm7ssdrRnC+5ud5x2A50vsNYJ5zrJA3pdu5Yb3fc3exZLOe4WgGx6AFFQpQAdnn5gExivz+QIsW8Wqz+FApnLE0jCoXtfMZh6NFWE1JiSMKsePP6LeeLM7IfGfvM2fkZdTPnZn3Hm7fXdONISpmDGpg3DYvFnOQzwxiJIZFyEqepLANyKUXathGpixSJObHebTHaoI2lqiuMNuQUxSzBOsbRg5KgK5RHVWwLxfUqpQTKHg8lY2WqEqRvoQBjMjFElHUolRGANwNyIOScyWXSO6nffuT9nQ7cMSX6ocNpw2I2p/ee2zdvePToKV+++Fo2nLM0TUO/3hFSwqCF3ucD6+7A4faO5x98QIwHrg5ruuGOL7+6YXU2Z/Ae3yeaWrNaOe62e26vb0nZopRmGEZ+8IOPub65YX3Xy7RZSjhXEbxsmrZpGAYxKrZa8+yDB9zdHXjz+iWKFatFTXfoiAlAFsYwer788iUZmBXlwm4YcBZi8sRoyAmMTWgVMboCpNxSSrrXhiSCRhoUhhTFDFlrhbHyGv3g8aMiq0jrHM5Zxn5k6D05gdM1Y98xhC2VgdX5grpu+Zu/+gWrsxWXjy4YxxHQGF2Ro2cxW7BdbyApyIrtboepayKKKsNiNme+uCT7A1dXa/p9gKbn+bMP+KMffEy/3/N2t2G/3VI1DVonHl+eU88a+jjQHUbC6NkPI828ZnW2oNKWdtGyvdmx3ezwXvQ1lALnKlItmGhtNPvDgeW8xRlD7IKYXygjcJexrNfXHLoDMXt81Lx9c4trFC5qskpc32ypas2qXvHw0QOUSiQvk2+jD6yvbxnOV6y7NU075+rqmu31Lbev10S/5yc/+AifEn/zi88YYiZrUF4zdAPRWl68/JKx88xXLVdvd3z77Vvm52e07ZwUAjl56rri44++R3/YM+zh7etXOCdKlSkEVgthNPVBKi+tYegTzoH3PS9fvuTt6zV/9qfyM5p2wdgFvrh+QXcYmM8XQmXzUNcts1lLjJ62bXj99goVLev1lgcPRZIUBcbK0FKI0MWBjDi1hyB2fk1taZuKpjKkyjCfzzDW0g0DXT/SjyOJxKEfUQkqU9MfOp5/8ATvB/qu5253xWa7Z7c/EDNoLQNw3Rjxmz3KiJtUDJLJWueOFDulcmlOjihgu+/IZOrKsSg6JtYKHz6liPcjwzDiC11PKWk4qiIUpbUqU5CglUIZmZ0ALYeFFj0jrTSRiClfSy5MkniCRQQ+UUcY5be53unAHcKIURXL5Rnj0JO18DWHop0bY+Di/KwYH9TUtQSuLgcuz1ZczObMTINdzXj9ek+bMuvNgDGZxaqmezMQUyTnyDD03F6v8WNCm4BPovO93mzYrA9oo3DGCBaWIylRtLk983lL3VRUzvHm9RuWqyV1DWEYmM2WLGYNt9sBYzUheExVCR8b2RDaQojSbEphRCEedjoqjGmO2JnWmYDIy2YNWmdy9gzDgLOTx10AYPAj45gYu4RxmUwmR7i5u8OPkWZR4X3Hct5S+Yq7zZa7mx19f42yivl8SQwBZYBcqFLGEMeAH8SGabfbQcoYAnVTcbk849GDh7jKcfPmltevrun7yI++/yGXizmH/Y6Xb6/RdSWeh1bTVo4PHzzlEAZCSrx+dcPFYoFymtlsQe1akvfs9nsymWEMZPRR27gfeqy2+MET+gxa8NXgI7HzjD5S1xYVlWhdDJrDocO1lq7ryDmwWx/QMTJbzggJ2srho2d9t8PazGF/YIgZYwyrxZLVcsHdfsN+fxBz6u2Bly9fs1wuuNlueP7sAWeLmjc3O+KYGbsRY2Uk+vrmmhBgCIm6rUhjYrc9cF5ZjBXbrnEcGMPIkw+e8OKbNyznM4yzmErYKxkJUn4MOFsz+ANnq4ambXn57SusbclolvMlKRqu324wtRh/rJaXYv/nZlzfrlmdG4xNpBzphwHrWiKRMAYICp0NSsGhP7DbHwg+ExHesjYGpSQLrauK+XxGjCNWWxYz8YX0PnB1Jd6m2lr63R6l4HaQSrbznZgb9zKZ7EdPzBBDJumMsZCIhBTJgFEyS4Gi7AlZmznBOIyoIuwUgih8GuPQSpGgZMuZcRyFVjkGQpAGYipZsdbFPzJJYiTqL6L8J9S+TAhyWGQBQDFaEGlf+Nu2ssfG5BS0gd8pcL/TGPfZvOXRxQWb7Va6tj6SfOLtm7dYA0M38uDyjM36Dj8mlIm0s5aPLh4RQuC22/G223N19Zp53TD0I1fXGy4uVoRBMuamUSQCOVriGKhqePz0EVUt9KbbmztAo5W4uVdOHmmKCecM1gq27H2gqjRvXr+mqhwPH5wVo1/PrG0xJpBSwNUOYzPGRZqZQlsYfJCg1ItBAwpRi0OErXIKRVdFnksYB8ZhIKdMzCPRdzgrFLOURQBoDJ4QgtAoM6SYubnZsb7r8DGjtOLy4oJh9IQA203P0CdSUjTtDJSUwKDwfsQPPc5aDruesYt0h5HkEyGKhO7lYkZT1RjXkIaOl6+vOGwD1ig+fvaMxjm+/eYtCVMmyDQL1/DBgyf8/a+/ICV49eKKYTdye7tlMV9Q1TXBB3a7nu1hTyJgjGRZSiEGuQcvz22M+JjpR8/NzZbrmzW3my05yUMz1pBywhjDerPl0Hu6TjwOtRGVwTHEklQp7jZbuq7ncBiISdEdRoHE2oqXL1/hAzLtaA22apifL8lOEbLj5esdNzc7mspRmUzdVjLurDSHwwhEjDKcny+oZhU5Rw67HQaNRpECvH275ud/+zntciWBrBgLtM2MGCNN07Ccz0GN1JVBKcPmrmjypJ4nz864vrlluxsIyVDVlmEcuLlec3O95c3ra+azhhQ9m/WO4BNdd0BlSQoq50g+MmvmjENgGDwaROCsuD55L6W/MZq2rUmFgrtcnDGfL7DG4X3Aj56maiBEYkwsFktm8xnaCFWu6wKbbc8wBGICpSzKiMl2yoIXpyxBUOJrLs0/8XZUSpETDIMnp8wwePwYORTH+5ffvhLmRxT3LKHt5eOw0ORslbOwP6ZhGQm+mdEPjGNPSqEcCmKokieanzGkmIhF4rmytgwPlv8KHPO7XO90xl3ZmsGPnJ2tyEmx2dzx4MElu92W+XxGRlxphmEANE+fPMKPis3tHduUaJYtOQXu7rZ8/8MP+HZ7w9lFxWHvubnd8uTJIw79ltl8jtaay4szYvJ4L1m9NlC5lnEcqKsGpUVrZOgHBp+oqhnGKA6HLVol1hsZw9+sb/HjyHxZE6Jnv9+TQ2IYepQ15eRXGC3jxAUBo3Y1+92OusqQE8MQaAu+q4/ZtAwNxDGgyfjQE0MixABKAlrXdQxBsqicwftEGBuG0ePHTMoeo5b87c+/AqOkAsiQouDetRM1vboWaCUMHp2hqWr8GOj2Ij3buJqkFZcXKxZVI1mw0nSbDV9/fYsxlrN5jcHi2jOaxhOVJzPibEX2gaFLxKz55sUriIrKiGbGYrkkDJ67q1sJpioTvadpGyg2dYJtjhjE/7N2jYh0EdnsO6pk8dkTd5lcBZRpGAbP2cWC7aFnvd5JY8qA0oqUE0prGWlua8KY6IeRmMQQup3V+NgzBI8PMvCUYkLpyKxd4b0nxJF6PqfRc9Z3NyzmC5q24Rc//4K2qRn6EVspmnnLfrcnxJGmbhj7kev+mqZ1OGPpup4hJpy1tPMZ46FDM6NpKsiC/T983LLbar768jWsRGo0J1DG8sEHz7l5/VrcoWIHekHdOM6Wc549eUAIietbMUVwCciKmCK2yjhdQRrEfcpa7m63gGE2q9A5owMsFnP2hwM5SSWmEJnj1q1QiPmH1hrvRy7OzzDGcNhvaFcLopYx/rauCEMg+MTkNSUwhUGVIIhWx6xXIA1xFYoxkQuOHKOYHyglQTvHLJohxkFRSgQZXvJ+FIw8yq4TQ++M0YqUpYpOMZb1UJLFwgZJSqi3OQVQcuBLoJfsWhuFsw6lIkYnjJbelGDfGf07pNHvdOC2zqJtRfKB7XZPM2/E8fnxYw6HA9YayJnLiwfc3t0xa1s2Y0eXMlVj6fcD5/MWl84IMdMPA5erM9abEW0Mh+FQ5DEVr169ZL6Yk5Ti5upKTEMVqKLbWleG2axmHGVRzOoaV8njPT8/52y14ptvX9PWDTpr3ry55fHTB7Rtg7GKvuvJKTP2HmOMcGJzjzGGrEWvFyMqcVolhn4sI/g9IWQs0oDJQaRAc5KSL4QRPya6/UAiFvfpEZ/k/lFZxOqVou9GYohY53j9+pb5bA5o3t5e085aEkUHJUOOUezcgBxEmS5H6HYdYx9EmyFGlrMFlTbcXq/5eHWJzpm3r644HAYWq5Znz58ShhGN4fz8nJgGNvsb9psNt2/X+CeygcLgOV+ds955Hj98QOg865tb/ODJZdFb7TBOkyqD95qxS2idiSqdHJG0YzyMjDETgscTMTpziCNZJ0yZau0HT+Uq3EqhrMZaQ+1a9t0ecRU11LVld9iJs1JrMS6LwL51WAKozNCN4GHsBy4frfChp+tHfDakpKhnguV+8OwBfT9QVRUpidhR1dRYbTHFgDlESRqUEmelylkwlv1hR1U5Dn1PypGL83NiFC33i/OKF1++4vrtmvOLhrOzJev1jr/8i5/xJ3/yfb7/w4YQI642PH70mLpqWN+94eWXr1mvD2Qs43BgNmupm4aEx+Ya5SyucXz7+luMMTSuwUdPP/YYZ8hknBUKIUAInrZtpTLNQpOL0WOtmPummHj44JKb3Z7uMNBUjrpq2O8PArXUstaMkcnFjEMpeR0f4jEDzoUnDZBCJsSIUfoo6iRBPaJQpNJj0FpBnvaL7J3JwUpbi0xKIJoiR8xcHxVFj4wR1BFSySmD5h6MKZm3NgrIRfI5Y7LMaAgd8LfPut/pwH11c0Vdz7lYnfPpJ0+ISvPy1S3rvGG1XPLqm1f8YPER6+0G4xTrdcdhv+fQD5xXLctFRU6ZzXbNvt/zvY+ecH27oT1z9Emw4KZpOXQH6sbRdR3Was7PZ4BCa+h7T1NrjMmA8KUfXD7lcOi4W29omzk5Jb5+8TV3u56NO/Dxp8/o+o6bmzXK3PLk0UM++OiC7W5kt+8AxWa9g9yQk9CQwuh59ulHrDdrxl4CeiIxRk/aRwm+WREGj8oJ1zi55z4yxoF+3KKTJWUJACprxm7AGs2Di3OU0oyDZbBgjSWFRL/ZY6ua2jjiEKhmjtbWaJ+l1CvrzO96/H4gdJndrqMyFUZpGmswHu5erXn08Jw0jPzy82/49uUb/uAnH3O2WuG7kZev3xLGgfPZgrPzS87nj9jaAx89f8Z6u2NWN3hvGXcjf/IHPyFm+Pf/7mcYbWlmNfP5DJ0RLq4plLxZSw7CAHK2ksk4SuYXE8kHUhI5V60Ci+Wci7Nzrq6viEVwX9URY1riOLIZMoqOHCMDmcN+EOOMAq9kNZBzI/imiVRoqcScAyOmG3d3G8FCdSLnwOXDBzjn8Dax3a9pZ4VSiAIVWVQVqip+hzOL6h0pJfb7nhgiVVXjKnBac7hd8+FHz6lrx9h1NE1DW8047Nf8+McfkJTi7dUNbVOzWArUlVVg8D1aiyXfq9evsNYy9D3L1QpjHP0QUWrGbr+TIKgNTWNZLWd0u64wKxQvX7+iHyIXl+cyvTsO5KxIMZaMU6rE4A+QIATR6kBLMO77jsVsRt007Ha7MmkolN75oi0a+7LmtFGEmHHOYrSh60V/JMYEWjOOozjOmMIbzxlXaYw2xJQAyX5VzsLEKvtNG32ELbTRGKXls81C2VNZ2FohiOOQLgdojBGDNEqDF6glp4RSimREKlqIA4oYI4tZWyCTwDAIFTil/Psj6zqbL6lcQ4gBH52wOoLHGMvbt1c8eHhBVoq7uzuePnssguY54Yxiv+9Qyh6zHFcZbu7WYgx6EOU/axrqyjGMAymBUZlPPvmQ9d2eu7s1OSv5ULRBGcvh0HN+fiaZ1jgwm81QwGa7ES1eY4gxsV7fsd/tMVqJtOfNRhgwVvPg8oy79Y7FYiHKZatzbu5uqRvLdrehO/QFF4sYDH4cCR4p6bWGKE1JVxmcM3SHHU1dM581bHcj4zhSGwAnmHq7oK4d3idS9DhjSvNuZNa2gnGPAW0tRhlSiJAV2QfQjjgGDIbaNdyt92QvVYjKUJmKOEa6fUe+XDEOnu7QsZwvmLcznDFgNP1dR/IjuRL64DD0GKWZzVq2mw0XZ0vGWWK92VBVFa9fX5FCwtZF3XHwHIaBnBKJTFPXQuWsKlLyxJBw2orWepRNp5RChpMVWlkUhs22BCdbsd7eoZUhhqGU0pBzLGwAVUrn0rTKnuA1IfYyUEGGLBlWzhlb1WgjWZiU9YnZbAY5ixYGifl8Tj90kKFuGs7Ol5AgMdLOLzgcesYwkj1UtgKTqaoKZeDhwwuCX+K9VB+mfIbRe7Q1mGzQMXFxtqQfAt3ugB8DVa1o24bDoSeGAaWUWAFWlnEMWOc4a4XqaCvL0HdUrma5bKlqy1ggib4fynOzbLZbaQNoTYySAWttjpxlnRXeB5l/AIyzxBxIZLb7PaOXQFfVtdQ1WmOsRSUJkKL3oen6jhDE1SrGU0NQbAIl+9U6Y4wVJogrh7YPR8f1iekhtNJTtpsBUiJq0Fn+3lpNSpBSLk1JCdrS2JTPNaZESoGcY0lqIjHJ12VSMSiXhM8YcdKKUYv4VM4ofk+sy27vtiznkQeXF/iQWMwaVos5r66uhdrmg8i+rlby8HKSB6cSaMfoM6NPVLWi7wfa2ZKuGzAq44zCKk0iEJKndXMeXK6YzxvubtcF65KGh9aafhiorDSBdrsDVWWxVc12vZVOdhGVIQd2u724cxtNXVliCAx9ZnG2YrPdiAZLCLQzR4iSETlXMY6+8EPVsekSYoTiqmOMwWmNcxVN43BVxX7YU1eWtm3YbGRjGCdc1JwjbW3JOXDY7/F+xDiHc45RCeaelUZlhcqKFFIZPohkE0kKrNL4rLDKkL0EyBgCbdUwb2Zs+i2zdkYMAu9Mh0EuYjxWaUIfqG3F9m7Lo4eP0Vnx8OFjvv36W+ZVQ1NVVLVhDAKJ3d7eYZQRHRAl2UoYApUzkKamrUBcCiWBIQtWOavbIn/aMfSdhNGI0Ba1JivYbbbEkPFJgpmxUiyn0owSoTBhEMTopZRWtkyzCqPDaBHNN9rgrMYYW4JNQEfwxovnYYEMKAwE6wztvEEZGL3g3dZp6sbSNBVd0WS3VkxwlVUsFlKRHLqBcSzSvlbhyCijxJM1jJis2dyuOXQDZMUnD5+z3x3Y3O14+OiCxXxJDJH13YZ+HGnnMxIapZUcpItZyUJ1wZJlojAkMcRWGFKWhqBkpVPgjjJx6j0xjiJtGiNJ2+Nhpowlp0hV1+LZqnUJ9sLNyBrhWXNidwjzwxfWhzQSnRNnnYlzPbFa5J4V1lickaapEAoon7GEwlyG6CjslInyp5Qi5EBII2R1zLadEwgOCv6dI2S+w6gRi7JyWBgjr4vixAsvzJX4exK4nz16QNvO2B/2nJ+vOOz3LBcLvn1zxTB4jK2Oju85JepGjFwfP37Mty/fStbqNHVbwQibzZrRJ+azuWgJkNlsNjRtRRgDVWW5vrphs94QvCfnRCy0wJQCdTOj6/YoZcQBJwWqxuEHT/RACcCHw5bRB+bNkqadoZHTd7vZ0g8DRltiGOhSKItQfr62tjTX5AMXDrVknalgeUqL9rhzEjCapsIaI3xjhM86db61FrurYRgYRyn966bCaGnmKVvQQgXGKjSG6CORSHYVOsuGdkpUzypTYazBas28ackh44wj50xlHbE0cuqqosIQhpEcEzkrun3P08cPSSEyaxZ8+dU37O46Hlye44eAdprKONbXWzRG4I+UiGMkG9EHEfdtRwqQteQ51lnRKY+SFRulMEahjZLPvnLknNjtDoVCJhspFm1zRXn207iyiqB0wTyjNB+VEWw0R8iJmDROZ5LSWCdBqO9HcpavOex9wXrLNKEf6Q6ikW2doW4cxmSqukJbyhCJBB8JZgE3b6kbySz9OIranNLEJI34GDOHtEdnhbUVm424QK3mksljNW/fXJUmoVQGOQfWmw2Hw4CtKgmGiBkuZCk8ciK6SB8D+66j7wWa0tbifZKAdhznPiUYSk1aZuXfjPCdc9HynjLZlCIqFnPdDCGEIsSl0VYakMLNVmWAhZKxJtmPRQVzwp3l/1IhKS0+kSpPSVwJ3MhzT7mE4GPgBm0lGUo5CcOoZNpKyZyCNhqTxNwiJTmsc/kcjTYoXYKzkLhRCiEKSL5FjGLVJkyW3xOo5OGDc2KQD7Lr9lSmYhgidV0z+oEQAl3f4eqGmBM6ycl6fbMm58TZqkEZTcjiJ5lCQCvNerNl1jh2uz2Lsxk4xdgP7Pc7xpjxXj7EECNV3ZBiFlhEKXZ74XQv7Yy6aYEsQV5JMPQhM3v4hOB3hBDo+8jzZ88YhsDrN69JSdPODXUjgzmCtylc5cgonBPdAzm1MzGJLrmswIy1CucMlZNmTO0MIFx0Y0S7HCQYucqWTSOYpGy2iMbJBtCRrBLWiU2b9xqVInUlY8I6K8LoMcrQjwO1dZJtKkXyEeNq4hjEjzMmkk8yhZcjoQ8onfHBHzMeX+haOcLubkttK6q2wefETClcWfzdbiCMAeM0wxiI3gssASQTyCFjaoUyAltUlYWcMQo26w1KaYFTjGW1mAn7JEYGHxjHURquE0YZpaISrDSQKU3dKNl2LpUTYSyyExkVM9ppsk7kMRET+DFyfn5G38lUpwxw9eTyDHOEkAMLJVm4tYaqMnTdQEwBVYKx1gbrDGfnCx5crohjZCjrNmT5PoC+6zA2oSI0lZbKJEbqynJxvuIw9mKUq6Tx2nUjfS8iZ4vVAu8FxjHWkJU8izB6lu2MYRgKGykTY+F0lAAlZh5CbZRLMs4QElUln7MGQqHbCWUPaVQW+dWU4nFfxyBytTklgQTLiHjwuZjrqhK0JzgrlcOX4hOrSUBUEuy0VtRFYG0K8IXnVw7rQimcMnGNyN2GJJxwoyBNHOxEjPrIH7fWkHNFSkkgnfKjpyphCuDeh0JjRIaUokg2x99B1vWd5nErDaP37LZ7ckrMF0u++OqFcKyhNPZK4MwwjMKa8CnTziraxhL8yH53YBh7KaGHgDGZjC5ZjCEXDYHtbs/hcGAcPTFFtDHUdYWxiqZxNG0t2UaIgu/lWBakkmwsZdqmZb6Y07YNu/0WpWRRkyPL+ZKYAn23J0dfuKOpLPwRpRLGQNPUVEXKNqeAcxprBQKyxqC1sCxiHEuXO5VuvGyunOVkd1bhw8AwDmijWJ0ty7+lgtl5QhzQSvL8oTtw6A6EGElkDoeeFKDvPNvNjhwzKsHYDZBkMCWV9zx0A6OPxyyj66Sh1Pc9VkPlDNZIltTttzw8P+fB5Tm1M1jj6HZ7am1YzmZ03UDygexFNKuuK6w1+ODJRNDCadday2HmFLNZxTD4oziXKzjubncghsjZai6/lovjdJtCnn1Vu0LVKoMSKR2fIUAu8IBM3cm/TQpwMYnk6mKxgCSDP21Tk6MceAoKd3iUQ9raksXLga2VYuw9wzCScsZWrkgl1KVn4qmco7KVVAdRhl9CjHSHQETTeeFyX14syyGcaEyFypIG55JqKgxGO0JIx30zjAPRR1HF86GsH3UcujLW3ss2JTgpLTDBNAk8DZrEJFQmY01p1mlSzPhRzHRTlkonhIAPQSpLLc88psw4CCd/YqoYY4gxHKcjJ171/d+fZFRTic8yaFQ5+90JyJKR3+dUC9kkkYInJFH9Q8kBLhBXxI8DMXhCDIJjG5mx0GUATnDriFGF7pczY/AM40g/DoxhwAeJJ5nfk4z76uaO9d0OleH5h5/y8vVrXO1IydO2Nd7L+CqpmAuMkiE5Z3j08AxIbLcdIcFiUdNnT+00xhmGoaeqHClKGaOVqPsZ51AanDFoM7nwCByw2wlOXFUVfhyFZoRQgWIIfPj8MWOIGF1cvedzFrOWcegIcWR1NmPwI4euwzlLVUuZ7cugjKtm5BRxRsqwFDxdJ91tH2UqNMZA8ND3gvPGkHFuLt53VuNLOWa0wlWWnFWRiA2QArOmRiG6J8paqqpGGQqc4qkqkcbddwesNuRasT90+DHIwaJcYSlIy6auq6IhLSI6MWZC8pIdGrAKFtbitGbVtqQxQozonDEaQtcToiaMAe88tbM4LNW8Yn8Y6Q4jjx9XIqgFoBXaiEiVZNkyHIWCYRhRSibo1iGx23V0umPsR6picGutYTlv2ezk0DHGSCOybOhcymyFwmpzPCSg8HpTJBWjarGj4thzuLm+xRbFOWligTWGdjZDD2Kfl1Jk9IoqWYzNWKeJKTAOpTGa5VAdxhG2CavAGugGX/B+4UsnMk5b+nGkskZkTmvH5ayVScXB09aO5XKF1orB9+V7MykpUhIcWKWMDyOgpPmbE1VdEXwiZy/PwWiiaGChSk8kTkbaUxDUMr2YUi68aoFIcsxEL7KqGYUzpbGZEjGnEhAFIglBaKbWija2BO54b6pRH+GRXLjVE6tE5UycMG2tyUajcpYD1mqG0ZcsuKS9Wfo5KcgcRZpw6DwpjUiR6wsurVNCGyvj71qhVBGdk9zheBjknIuuSzxm7SmVnPx3yLjf6cC93h5QxvL9jz/h7Zs3ZKVwdcVsVtP3fckQ5Gsnh4kQAotFI7oT17eEmDHKgspFm9qy63eAJobI7fUdKM3Z+ZKkI9oomraSbCp6lM5YW2zGhgGlDGRN1w0orXBOE72wCKyJAg3gcQ6WiwZjFOvbW5p5w9n5SoYWylKpKqFEaSWZfYqeTCnDkGaPs3JQhSBB1fsRpRU+HYiFWz1rK1TRkwh+JGXJCKwtxgt+xFhL8pm+lwNLa9AmY6xkTOPQF+5qIqZAjkIb7LuOvuuJKdLUlpylHNdGNqlsvCCiVlFEgFIWXegM1K6iMVAZqKxi6A+MfVcOvYQ/9Oz2gW701I2hqRyaTAwD++2BWVOTolRJdVPhs5dhnNIAc9qAEuNnax0pJgZ/wO8PEjCMJbhMCgOogDb2mFnCZCklzSaUgphOLACtjhSynAWamoZBiu0nzlmxP1uvpQ/RVOQkU6veJxbLFqUT7awGPenvjBgnsIMYcwikFKNQ6mJQ9H2PoqaaNWUorKfvAinGwuLwDHFAZ/ApYduGQzdwvnScL5ds1Jans3MuHpzjx8Dbq8Bm17HvRlKOWFOV3kqEbBCmjPCYUzECsNaSEmAyJlvGXIKRygLllQxTGBkJVWDDsfQ6lBK1Pu8jyhpRuyx4ds7SrJOAmY/BzZTAbFAE4rG5N7nTaF2YQ1AibL6nVxJkOMkagTVAINRyQEx6IdNnL31KqQKmUfmUU4GBTvc1Db47LU3aXDJ1uV8jyo+lEZkyx1/5+CtPXdHfOva904HbqsyTx0/49tW3ZK1xdY1NPd1hR0waU1zYcwygKiG/h5EQPa9fdxATbWWYzxtSTjStYreXEq1yCh9Ebc9aUwKaoq4amYAbR9q2ETpeKN3vlEk5CXPDmiKFaamspZ1r1ncHUImhlwA+X8y5vr5FaRnTDn7kbLWgbWq22y1WW9F2cAptJXu2xsnAQfClTEbuE6GrhZTIYwY1BffEvutZLBY0rcZHiEEEeITO5kVzOGR2hy2rxZK6sWgl9EWj1bFySSmRjSKhJRNXMiEYfCCGSL2oqSqH1ZbB98heSAg4rQhjKhOYUfwvUHRqxCaNa2S8WjBFgMg4JnyEbBRKixY1KTOrDXe7nuWqom0bUhyLAFAgBxj7HkVpYqmAc466dVAn9jtPDJlxlIGNqtZCC1SamDQqytScylmyJi1NqqwVYRwLdlkgJxUxVhpXOk+GFyeFuOViJvjxekutDdpkalsx+h5rK0IeyDqLC0sQVbtxENMBRSa3NTnH488cxx6nLQJBQCYyhBGyoeukiRcLDq+MIQfBewcfUVoqkoMTI+jVrKZqWqyWgLvdHjgcRnxMxayj4LJoGaYKAQX0gy/MCEM2oC1l2CqINo5R6JhlorE0VVXRCwkpozPCRPFRaLxBGFEEqRyTnUSaFCnCWNT+hKGRC7sHwj0fR6UQeQkn8JTPGV324pSR5+J0jxNtkr4XxhAF3pGvKc9d6WPQzscGtWTWKhceuS9/VlMvU09nG4rMcZQ9C7MHKLpH8u9aQWQK2PKMfwca97uNcZ9fnHO7uSOkwNlqic6Zi7Mz0RZwpkwniaqXvjdPetgLLeuDD55xcXFGDGMRJTLiaFEaicZo6tqJJGthYZDFqICy2ftehmaGfhS+dxTdBKUy49gTwojWma7rmS9lEnEcOx4+vKA77PHjACodx2PbWc1i2bJctKgiNFVXE2afjvom4zCeGjIU/KwEGpSWBk+M+HE8ZiWVE0zPGqhrS06+4HGKrjuQszQjFZIlOSd1nvBSRcRK/i+l4JTVpiSwR1VJoA9xJMRAPwz4OJKVZE8hBLpDx267JYURo6VJOoYgTVMjkcDUM9CWYTgwaxzPHl2ymNegEu2sQTuhe7mqph/GIivq6Yde2COjuKYL5zzhnFQ+zlWS5YUgAlatk8MunIJAyoUtkqIE81LS+qHHlqEjaw1NY6iduO3kyDGrA3lPTeU4Pz8nxYAYWTTUTU3OnsPhgNaGp0+fIRCEPMtxGAXDTZlx9BwOXZETBWtFhU4qxyRc58KIORw6hmGk7ztiECx34k8rrQuEVtgLIYnMqFJFnyNwdGJR+TikMjX8JBuMR8hjst3KOWO0Pjq5HDnXSvRUVIEMjrzqY+V7wpwnfHpqQorpsRyA06h6iqnQ/WJh4ASiF6XLnCQ7nuh/QhEtVVKhyFJ2SCyVUiqmCL4kW7GY9qaUoFAP788v/ia/O3OCPibmivSPhLElk16y/8VTUnj7MoF92kuq7Fltpn2Vytf+dtc7nXF3XcfoI+fn5xwOHd3hgFKFdA/4WD5cd3r4QuiBxaxlu93y9PFDNptbXCWDCEpB5axMJiZpNIxDf9Qv6Ebxs9TKcH11TYjI8adAJrIcTV0x+hGtNW0jI8XaKGLy7A87Pv7oGcPQC0PAWlIamc8XxOQZDz11VbFcLmC3Z/AjmVDwMAq1TUTcp0BqrKKqa1ISqlFK4jk40UKdtViry2ITloVWoq5YVTWQy/dJKdz1B4xVpWs+HgN8SkgGjZSf2cuGr6zABMbKgTGMPdv9Aa0dTpsiAqTw3pOip6kMxESOhbXSVmhXgbZi/2UMtqqYzVsUUFWZWWvRZoF1it1+wDqDD5PolissBUVKBR8qGOikAZ1yBh1xlRELu1Qm2YIXfrEWJoSW7pQ00rJkYcM4YKzFGOG8ay2+jyml4tKdjhQxsZ9SRUNG+Nmr1VL+LYIPQksdg+fm5oqqro4ByftRRjViIkiRgrVCZTPGSBaaT2W3Qkruvh/oho6MwjiFSUWRboqXZaQ7hFQGfgzOaKwqCpYxUFUOHzPJ5yNTRut7+0apI7Yv+ygX1k08joFrpYQqWp6bQBjCX84pk8jEIsAkTcMpIEtikUvzNqeMNnKgKa2L4p9AczkL3c8YDSodg7cqfMMJi57uWemT6NskSjV6gRszSeYJSsatVEYn+fzuv4cj/pwLMVIV5U0ljeWJLw4n04QS3eW7s1D/JmhE+l5Kqpacj3t7YsP8Ntc7HbhHP7KYnXHoeunS+pEm1MSUZOEpCmdZAueJlK+4ud2QIizmc2btXLLTMKJdRUwRZ6vjIjfGkK1isz7QNIb5rGK93opSmYG2afA+iDlCWzF6j3OSaRwOO2bzOSprhnFkNp/hg6fr9sgCCcxmS4bRc9jtiq6yxjnLfNZw6LsCaZRGhngCA1LSusoyX4hLTtf1JSBmYmnQzOY1VV3GdqMEe6MVMXr8OEiDTWkRx0EaW/0gGG1K4hyvtLAwYpSsTORiS5OzBABIOKvZ7Dq6vpeGkJIyMaYiA5oz52fzAnuMcsA4mfCcpuckWwykNFLVDj+OHLodWQkOvN8d5DONHqUy7cwVHFLoZD5nVBmNVihy9IwjZOUxRlPVFq1n9IdRqp2cj+8TLQdjVTlc5Y6ZntIFE82T6pxIqwq7oZTxZax5EspXKBlVrxuiFz1wNGAUzlRoZwsDpjizj8ORQRRjQGlpHMcYIDvS0YjgVLoHL4YAY/D4mEtFULLAIu1rC2wTvOyDrh/QuqJ2Ml0akkgguMphxkgevXRYSmN2ovhNPGnnbMmiS7MyBMgymn5MSWGKUIUOJ1hyKo3CKUAJ3U4fvy6lVKQJMkpJteD0NNk4xUItJrtKoRgZi7aIZMzqSL2TwFggj5QEgtOnpiLlnihj7DHGctjlMoGbjhOWiunnikFCcXmVBnySKjffy+4zoo1Cln5Hypk8Be7ClNHlPuRZC900/75olaQMu/0BiqCRqwT/9T5QzWrp0gfByYQFokuDQPQV6try4puXtLVjvpiTtVDYtJEHPY4DcycylftdJye91mw2W7p+BAXLxRyQU7xtaw6HA5Bp6jnjOFJVjhBE9yRnqBvLzc0tRiuxtGpn5Jx5+/a6+NsFKldhjBHHbyt2RzolQgkwKQl22DSOtqmZzWrZlMRyuifII1obFvMGyPT9AUWmco7Rix5GDKKhkVElcyimx6rB6GndZayFnPWREie0r4y2GpUgB6Eb7vd7NpstlMVpbKHKpUyOgbqyPHx4TsqBEG7FeFlXjDFgw4gJPT4lNOIyE6OUvKpQ8ozW1LUtDieBqhbNbWl0iUh+tloWhlLEXBgH3qNNhbVZ0BilSVERgybphJ6ab8jQS1UbXBJNiqFPZapOIBWBK6ShBrFk2CeoYcryhrGjspaoopTlBXowTiRJpXKR7/W9B2LJqLNMqirpYPkxEXWQPkrB30NIRX1Q7kPupWSYSE9GAWOMWK3R2uAqDXmUJCBLtugnF5cJly0wWAqpZK3mHjVOoY2hKmYCkm3nY2VjjMXnwBTchEhUmBUqHzPN48RgCYcyzSiNv2lcX6ab1YlLbSRYysCLKoNIqQS9eBx3T8j4uS4HgtECnWRtsRRxKV0O2SzvGy3wEykJzIKsc+kX5nJYiMY9+lS9aTLxeDjJZ0ZhkU1URJmoLRl1Ku9e3f8lFZFSCJyYzG8d+97pwL3ZdFiXePr0ETF4uq7Dh8jQB3QlE2iCU47oEI+NpdmsIueKEAK1q3j04IJDP6C1ESODkvVppY9moVXtGAZPCCN1PUMPQqAfhg6tZMghhkDtRCfCaESEKCpiCngfmc9nhBhYtjO5F6N49fotSltmswa0wqfEYRgJKdENvXBNpVOCNfo4jTWftdSVwxhN3w/crdf0/YjWlikgWJtBJa5v3tC2c6FKIoMifTegSDIMExPWCXvE1oaE+GimfHKfVmTcccEFnKuZNxVaGfwY6bqe6/VdybATq+UcgBw9KinqSvHB00sePj4T6iGJb1+94dDtae2CTGS7vcGHxH43sN5uj7Q6YxTWKOq6oalrMpGqtmU0OlM3NWjFbhfpu0hAphnloJb69HDoGAfNbFaJNG0zY7Fs6LsRP4qIl6sr6qoqqo6KoR9JfsSnwjNOgpmTM7WzKCOfYcieFNIxGBnky0Ty1RybbUobtDUFzpHP1A8jmVhgmIRTSj7DUnLnpOl60ZiJsbyGCoUyJ0wIUMfqi1J6W2PRJIbel6xS6J/OuaIL0lOV/WCMo53NQBmqWtZsKNizGAYoXCNceeekkYYgS+I6oxQhCnf8aMVV3vNRza+wJ3KhMyo9ecaCVsIFn7JkqXwEShEEJJfoJk3QrveCiU9YeCraIIWnXVXVsWo12pQmJTiXpMIoDcdMgVCgwHaqYOPq2MxUWXRKpIqRQyz4iC8wWSyTnyCKnlmVTDuVgySfmCcTr10XDEvdw/+zUr9Tc/KdDtwKeHJ5yX6z5TAcxKasljI4hkAIgssKrzcfF0NdGVShTC2WLeMoglPjEE94V9Ef8MFDoRpZZ6itjFdPQU1rI5BMzGSEK97OGsaxLw0+w37fiaa3gegTxmRG33F9fSsLwlq00YQk9D6lM/vDHrQIIUnzLFLX0lxzVjJPReRwOLDedNIl14XiFIMcHNmw221BmcIXDcTkS+kp9xujLlhulIVexuNj9EyFolbmKMikKFZNTg6UnCLedxy6DqUh5Ujb1miT0MrigyeMEVs7qtoJDKAsfgzE4IXj3FqMgf0hcugGdnuRPhVrqYroQWXFIezFNVxBNhrvFVXtUKOIFVV1TQzyvkIKkrnKOygZnTpBDkrgH6MN3ln0Yoa1DmsFq+8OPXVlaJqabreTic8Q0CqXHggiCWAV0WuMmTDgfGTgWCuNO2uLKl1OxQUlnZqnZJSd4A2DmjLBLIMuwQsGP+Gg2hSOOJEYpTFmnUZpc6TYKWSoK0WZzJNzXwKMc8V9JZemYpEnBRnTzkqYSCmfsGJjNM6WwMqJWpsROCOWRuGRiVJMRQSLNke5gJxTgQjUEa8XDSGpJHOWwKeSKjAEYNSxGRjS1AwvvPFUpFalgJZeQIGJpPJB9lCUaCE0vGKQMGXLScZezMQUgmPQPmbSSgAQgU5OA0W5NBu1NsfvnbAhwbonzHuKVtOVgRMLRb7tt6cCwjseuNvasdt3bA8HlIKLsxW77R5ls7iPGFdKwQhRAqyUMgqVoHZCXdvvdthK4YwiFbxKhIE0fhCp1nZRMYw9fhhIScbKx9FDHrHGCishKpKGkBNOa2pX46Nkh03j2O0OWKsZQmK3FwGnlCOaQArlvowVh44QyqbkyNww2lFVGmdNqTAGtttD8cXLwo6x7ihqE3zAKvECjCmgswibphSF5kehJseI1WK95spIrzi/TO4hki3kIvhO2YixCO54PwjfGNEBaSqDUdI8DmOiqSuxmEqBlDx9t+Nuc4vIqjqMUwXnHen7XtghRzBfssVY5DeT9yixiBA4JAZiilTJSaVjNRUGCldYaxm0QJWg4yO+97jaYCsKXVBofNYlKucIPqBKExCVRaMlDYLtlkzJOCPc9DTxfgtUgkIbqfS01sfeSopyoKYY6fv+xMwwCqKmdhplJBGY2mLBhwJnSGKgtQxeWSdwkDHyniZdj5zFCSdbjuW6fH5B0uMEMcgBDVnoecXyy4/i0pSQDFupLDCZ1lgjB5yxVrDqbI6Yt2TfqrgpAYoyNWiOGHnOQn8zRf/HGFOglHIIkI+48ySzmpM8L9AoZ8la/DSPUA8IC8acAqPRsjesU2XgR3jXWil8zkW9Lx+DLnDsGE5SEFoJd/yI1StOz98oQorELJi/9DfusU6OFMrpzyddkyngT5OagPiNMh2e6sjc+W2udzpw+xDpBzEJbVpHjJ6U/RHkn4R9lBL62zTumhKMfmC1FOnUYRiwtpZS1dojna/vBykPq8WxGWWsoTKWtO/Rlbji7HZiXiqDHxGyLPRJgc9ow363L80uVeQ7Uxnc8YAViUprGUuGJfieI/jSGpkyfCXykn3XiQxpSIV2VURtlDo21foguiKylKZFJosuJuHjUmRGjRFPSqXTkdomB0AULRdtS0YjE5iulI9DPxR3HdAq0zYV1oJKpUWjhJnStq2M1/eOu7s7hnGQRo9OhYnii16KJyUvokBGRvmF0aLIWXQngveCfSt1dAiaNoWxFjWN/KdUuNUS2AY/EpIlRI0LljZJHwQl3OKMmOkGH0T+s3SytBb+ushy6qLhXQi8BbeVlpRchTgnAd4YRh8IfsD7KHo1XqYKcxZGhcHgyWhdYXWRKfWFHldG6I0RBlJVFemCEohiiZb++JmZUr5P0gbluahpUCgfM/OUE77Q88ZijCu4q5FGXZnQNWVgRWvD4GORxk2lAW2OkMpxcOUe6wVVuMpF1VKCdpbGoEIae+V7Mhwz95RO0EJG1P9sGa9XSSGUqROLQ+iARclQm/IhTCP3U1M0He97qiYmhcnp8E0Fo/5O/jsxPyjJR0xlMvMeo6XAmRlx61F5SnYmFUJ1j/Y3QY5TnyOW9/J7QgdsW0dVL1hv96A0Y/BcXl7y6vUNaFU8EXNxwil4U850u33R8U1s1ndSPqZMU9WMIZK9aCVoAxeXF2y3W4Z+4OLirOgNwLytZGAgRBG0KiWSniYpw4gu4uo+Cq+4qmrhdRtpYBmrsHHifUo5FoNn9APGVBgzLbAi+F+sjnzxWdwfhqJbLI0lW0TeJTDLBssk8QksuiZGK0KZcFOmtGO00Me0kVwvZgk6IhIvjVVxjHfUBSe1TguXNicJuClRNS2VhaYyhDGSk0cryQyNESbL3fqW9WZNiEUQSQnP2XuPjyOojBPSspTbNlNZC8oW/m0gGckcFQqdhWKmCm4qLJDS/FKlWw+ACNWHlARCK3hxnWsZ0c+Z6EXYPhY+8VRuO6uxriqDMCXDpUzzpXzEvbk3uKGNLtOWAieNoxzIOatSHqdS4iso+HhOEasdCiUSAgWaUkpTlWdeOVsU+BI5xBJopiB5Ek7S5YCdEks5JMvRkqfDPUuiMPrS/MxHnQ1bGo7aSNAWVxtN7KWaneACkbgtsMIEN+Rj3JRKQEnPYaqgRJNF47QTkaqJDpdyOYjlYJrYKxO0NcmeiklCUbxM5XmrEoCPwX4C4QVuhHzc//Le5TNT2hQJ1mmoabru/W4K9OX7chHIEu66Km/rBK8AR+9LeQwiS6uPAZvyvqbDStbD/df8/3a904G7riS7ss7gvefB+UXBAU96BRnJQnIWYr9oAmea2jGOnhAybSPYprWa/X6PNpq2qZkvFkX7Y5RGoNIokwljwDnDMIwcDjtCorABoK4rqqpi2O0xtYhBdeutNIViyZJMRBv5kIyRIIIyZQJThJi0ikhXXxaNs+bYpBxKs0oXUfYpcEuGP7l6JJTORCK6ZHcxCD1sGuJQnHRLtCkMkPKzZFOIvnBBtjEWquI2nnOQ9zMJ5KhM5RRNLcqEKmmc0ejKFGlTaSTt94LHi+6yvK4M0Eh1hAJbCcsjT1yywnYwSpGUkUO5qMrJoJUqWiO5DHOI0po0FDORwhGO0hTMRjDpGDQ5ydCPNgo/SkYcCpapEKpYXTmUM+jSJMtJDosjDU0oCMdyX9gZJWjkeCqNC94pB7AqGZpsXIUMtDSNMIRiiAQVUdGSTcRVGldEkZRS6KSJWiAI7ycqmy49CCBHgVQmLLswqchyuMUojTrvg1DqJnRgYn8odcSojZ2ydYhxGmYRqEQfM+ZpV06MkO+W/VPAMkZCjkoJPw2JxUCKJUDeOwAmDXQ90epSEgy83Mx9XPh+yBN1wnw6OAqLZlpT+Te/N+cTIyhTgKrp8yl89aItczIklmqBcghP93DM1r8DtRTFQmsw95glWhXM/ci6+e2vdzpw5yxaxG3diIC5gjAMuCLWM5U9QkfKx8xAWBKKQ9cXqpciBjFdcFYCk3UWjQym1FVFjpkQRmZVRedHxqzo+5ExyLCCUYIBN00lnXINbVtzt91KcyrIWLixgodbBGec4A8fJWhMm3iiYk2Nnok2lGLE+5FEwFWFVnbs2GemyS352UIprGuBkVTOqGzLs5KMS7DIks1LK1yeRyoTdVFgEqVEFhUVS5M3C16eI0qDRdE0lroyWANDiGgtwbyqjAhVjQMhlcNB56LOJvooMqSkRcck56O7jGDwFCeRksXqTJVkmtQaEW2qm0poYiVrDoMvzAiBM0Tcv+hFK8mCJr4zqtAOFUUHRoKcUlkyz7oCq07BK0x+m7F8LgqMKqylVKZXZY3KBi1uOLbszoJ7ey1DTzlmrLa0tTiz9734j/a9cLuzMie8nGl95OPUXo6SXcrgDAVak3UxOcBMmLqPUZziU0LqMY5NSqWL/kpRypOMW/jpkz4J9xpzcOIvqyLjqgorTqlpLDuXnoTEsgnSkUlaqYBSmVhEncShoDQQJ10YpY5a2feVGI/P+F5TMk69DaUEkrkPacAR556Giab3U8CXKbqUQAzHnP1e0M5qAsniKejm0/ccNU9yoShOr6P+MxE634vyv+X1TgduZ6TrPyZISbHb7um7QUTaCy8UpgcutknGGJq2YehFprKta7wXx3KlZPJQG8lsjJbsqqlr9vuDYM9IRuRjJuaiSpApk5FZFAVTZLlasD/sZWS5TK5ZK1S+hLAvtFJCA0uJ5KcRzLIY9ZS0FGNRkEbgJB+pKVADpCJzeTIyVYVzXYxKlRE1NiuDNtpoVBKXEqNNGbeHGCcPvZJtl4xV4IGSQZbNIlOKwgVWhfZVV6IDEUbRQUeJobNxlklLemqYySGpUcbQj17ggEqGaUKMBfJRuJK9hQILaCT7O+KuSjjerrKiS26dOKVkCIdYJDOnIMMRV3XWFk4y92hd+ui+okq6JmpvjqSKHgwlgy8b31hVXi/TNjVKZXwUnrwpYkmSuWuMrgqUIetSLMMSGDnkV8sFbdscs+rgR0JQJfEQyEupE8fZOCsHT87FVSZhtFQeKusyRDPtFgneKUZiOYEmIaYjRlzMbK0uDi6lUZ9i0YyOE1xRsP3fwLSPUICe5pNLyjtlneVOZO3kMlp/wrRTOh0GWiFCXdOOKBXzdE0H0RSglRJaooLjgT8ZPwj+ffr3qbyYJGMzEpDVEVS7B3JMWfFvBO3pzeQpQ88nxkrOJ966/NIkMqpAPSYVRyV1/2v/kyLlv3q904E7RE/vA9kYqqphtx2liZVCyVR1GQbIRYPDMGsbZs2M3XZbyjzRxzVmLsGnnRGDsCVGLyL6k4ZCzJl+DMR8yoAnnnPKqQgyeRazpojFR5q2oe96mroq48URY0RsPWuOger+dRqhlcWklaIyRvDZKOWiNie8clrsJS6V9y4bWasyARgj1layWcrrSGalysBBllWYpDE2LVZdmj7T+PPESVXaEVJgGD3aWHGaCRGvxHQixUg7b3GVJSWBqKrKHsWBbGXKZpQms3MabTU6qJKxHlPW6alIMA4T1U7k96QRqY7deqURrWk9ZX+KrhdevJ6w3zI+Lmp1QQTCMoSivKjLmHUu03Oy9UT575hhao2hBLrCwRYtkkjs47HsnvoslTVimyWdW1JMRB9IRmYElouWthWfRTtF21xgj3vYuTWGQhumruWgc9kS03j8PI/FfsGFZXIvHVkVciDpI9tEzGwnZyDJ7DWlJ1SGoIIPpBJwdYnJp4pQHbF1STIl05zgBxA4aKLgTZPA6Qi73Avcx8WpyNhj7PtPg+HpwJB1WZKXnLGFu6245yWZZQ1NldYpAZnogUn41WXI7HjocFp/0+tqIE2H3z3YZQra09dNW0okEiZmFMRpVN9M+LZAZ78LJfCdDtyHwwDasbpYiFks5fRMohY2fWixaHcYq1mtlvhBtDdAVM+api54qWO93x4pX6mU2toYCbjOgi7SkYgWMkfMjXL6Qy66vvPZjH0/YKyMAwuHeSLhlwWUhV9sigIbiPyqtaYML0gwEgw2fQfMCyEWmpgEpLJKZGHliU5VyyBDaWCFPPkBRhnSUFPgLxzZqMpouxx4030olJStagpc4rdJaQLGIEM4Kk2ZqBEaVgjHxTlVLUqBM8JjDYXKqEsD02hDzF50tcuGErhDanARZBL1xRA9qaQ/RjclcJep0rbGaItzFcYc6LqRrKGyrkBpqQTVMo4dM6nQ8axRpcGpZRQ/FtoZp7LcWnnGuhxqxjqppkI6njWxwF/kjDUFztEGrWQjA5AVVaNLpj0NnuQilVu0QSb4omTFOcoAjnP22GQ0VqMxJT4VTZMsUIGoJE7DIKWiM3paLigl4mqTeNh0b/ko9hQLD12GRYSXzXeyXT117ZmeE8ffF/DmiAFLEi7JxSn4KiYxpvsB+T78IAGO4+tMUNF0TdWB0cJcKVzJY4YtVcIp4As8UqqTAqnqe3BFyf8LLpK/8y8qn56nwLHcC7zqXjA/8cwncCWVYR89VYGy2X5/AndA0daVsBuCp24swUfGXjIM42QS0hZaU06SgYwhCFwRIm3TlKaPBM7lvJEx5nuO3k3dMDYj2oAtWKb3QTZDKJkOBUoIgeil++9TlCZWlgAGIvgkYlRy6htjwWSylqEIVTaGsZIVTtlPODaEKE3WdBRKUkqaeXIUQVYa70fIUnVM02+hsCBiPCnHTWWq90XrIU/KZffHbyVgxwmT19JIHWMsmVFCZeECV9aWCkQGG7KXw8WHyDBKkLHOMW1CHwKThGc2Gh/9MftPCPWRI/4JMUggFK/KyUk8ohgJCeraHGmLdWtwVUPTiLHsfieWW9rIRumHARDYJeZEZSpIAVs1xwBijD0KUZni2k6SUXKULkNPJ6nReE/XOaWIKVCPVtIYFiqlO7I1xH9RHWGosT+w2x0YukG4/YVVM3kmkkV3p64dqtA4QdZBCEF6AAV6U8YcP9+pYpqCLYoyen8PmigJiAQaoexJEzZhps6LlcEgY83x/R8xYyVQX06ZNDX7SpNXTY4CU5OxBDs1ZRmCpHM8NL6TuZ446ZOzzn1a4zF4p8m3UhhTMYt12ymj5fjzj7/LpSKPkyfrvXVfDo1UOPql7Ck7LR/Pg8w06zAdMOn+Kxz7AYoiXqakKjZ5OqBOlclve73TgTuleGzEVJUjp4zRluB7jC0NypSpKnPEkUYfOBw6cuKoO+y9R89bpsaHlOSTnKTYEa1WC8pHWFTuTuUZUDSHwVrRz5ioazkXPK6MzYtrh6jBTXKzumS3EwFfKcnARUtcMFNUkcRMkxZJlo2jJvF3CoVPPO1yyt/pdQjcV+hUWrLvGAvjoUA105+nBpMApOWZlDHhqUoI4VQ9yACPZLHG2ZKdFEw15cLeSfiQjyPQWgmtLJYJw+ngFInNfNy4E1dZFvakdT1lpvEYlCank5wdTa3KGLUwitrWMmth1i44HDr2+170uFGStfqMcxWawoVHplllcCZijAQjkmTY8Z5IvjGuQBCp+GeWoRcyKSSBXFIxGC6Zd1XJwaWbhmEYZLovRbrBs1lvy3SlfL5G6aPswQR/TFmjrIlYegKFeVHw6DTxjFHHdaCUQjsjlROnv5sCxylfPDUGhbZYPnvjTjohU2Ke70MW6cj8mDbclHGjkCnE8poZeZ4TbXOSOkWdIInJGX26r2n6UilzZIodx/L1KVeeRLF0ohx4qlD4JseZ+x6VpfGZMzqfGqHHfVPeZz6l/fIzymEyxYtTtvxfyJpzPj4XOYTi9Once36/Jxn30RZJKZpZizRgEl03FshiCixTwNIcDl0xBhC+ctaBqm0JXqya6roiRvG3k2xyMtqVCbJ9N+JHyWxyOTm10UeOrziqn0qoXJoz02SW956UT1nDkd51X/im1Jo5ZxGaL7ZkIaQjHAT343I50cv4coyhlNfymvfLzqlRM5V5YneVp5VZGnTigBMzpfQv5W0JGDlN8EZxPi/ZjC6cWDFxLdl+DsXrMWNsRVU5wfZKFDLlcJgGVQRHjccGk3Tj0/EZgTTBvA/HJiqctC3EkCJijaatXZG0lcZlVStsMVG+u5N+wSS2b51BG2nsgUxQKq0wymKNIkV9HGxxlfxeG8HZpz09ua/EFI4Yt48BlcXfU9bg6XPPKZ54/mPP2I/sD/1RjlaoeOWZl7WhjCgfTuYAKUji4YP0dTLymuR7juRaIKepiZyVHPyT7O8UrPKRjUHRMi/v6ThMdB8qkczzfsCfDpbvXBPGXdLTKelVZapwSjq0mkQmTsErT4fAvUuC73fxdVEADTKgA5OiKsKw0kLxK9X2/WA73VvKiL7Mvbipyr3L7JA6TWtOd5hPz+4+fHP/J8iPV6fvKtssTuv5WJUcc3N+2+udDtwSlE+8SW00fowFKywIVeZE8k9Smo2DmAcbR3FOkcylcg5XO+7utvSjqM9ZIxzxnBJN3ZxKtnJaGmuwpmSb+tTIEMGde+WZymUaL6ONaGBP2aMxklndxwJDFJZICrFkz+pooTQ1H2Ga2joNPkg2JNm7NPCKjdRxEZXOfxbeuVSshS9bNEyqIuGagmRutvgAavSJnmVkQ4jhgJSATd0QUy48aPmeUMSqrHM0xfUeEiFPVDWO+J6M7hdIMhfuawkkp6zxlHnJUBFk0ukwjpHRehrnCnQj+ttq1qJSKgqDjrPzBX0vPpqoSeZWmDpGU3RUrGS9eoKvpqCrgQpt9bHx2vWjVFNhlICZ8jETV1ka1SGEErjkGWWEw94PPeM4EkaB1aYZzEQuvHtZN1NVI+tVocoodigmzJkiE5DvD8GUoA/HNYuaCIVyGKSC/U6BdeKnT30YY+1xwGViSU2ZvCrwwdR41MYIi+f4+vK5TVDCNJgyZalSzf2nPObfzGSnw0qe/cRuSsd1nwtUdQyEx+cQy/vKx3uYMn5BhqaDt2T3U8at1DHkTv2hiRI4VXenhKnw8r8Tm+TNF9IPJURN2Ir8Xn83VP8uYMk7HbhDyoRupB+kRHVOJrGMM+Qk7trGWLQSx/b5rEUpRPTIGObzGYfDDg9Uxd1kt93RdQeaypYsyhIjDJ1n6ANVY1gt5+wPnUjF2tK4LI2SyXA0ZsGSTQnqIQShh5XBhaauhOtdV8Im0MLDHQZx0hHsNpdNkDFpCrsAMhk5vSZKGqgTfDBlRhKEFHVTo4FhEAxWFv8kNHVa+NzbTN77YpKs0SWAhRhJipKtn742llK6D1EsqIz8zP0woFDUTVOyNNFzNtZik9C7hI5oxe5Ni8qdwCyi33CkpJVSFzgNfWgJqoqT+tzoAybKAW6NHKpdH7i63jBvZ2gth20II8bk4k86AlokDbQlBhhSYOjDUbQ/Rk/btog+xj0cdOpvZMHrs3ME748HUd8Pkr37gKsrdt0BMwqk1veD9GTG8WRKPbm5GC2iT0kOz0nnI4RYMvLpc5KBoQSnCgiwZuqXKGJWR9pnTPcElKBQ28TIN6YIQfoy1jhCkYuQ15Y+S8wZnUuz9JgonKCbXIKkOvJZS0V2jFZyWE1O7afArY4/Y6oMJwrhVD2Lk49UwN/Fj+GY4WZpUArceKIL5onPXSBIUir3WL5bpe9qheTCnpF3cKwyUpw8NWU3nt7Xf3r4TMH71PAt95yOJcHxawSZ+j3JuKcTTzZ40XgIseDb+eh+4b1HK2jbln7oyCnh2pqUhS/c1o24gNQS+Ou6BqTZY/U9CUsNbVOfRq9zLk40kwZKZPRT+T6he7KarTXS8S6aE1qL07uzpmTbiF9kaUAapQnEsnjkZ5lC2zqVYfcwt6TLe74HaeRp2EgCbZpU3MqGmnitE/4Xs/CkdZ5sn9TxQIlJMLmp2ZbiBE2Ur82QRmGMWOwxY7bOlAxUvn/aSM5mURjURtyCSllqVBZBoSwZ0/EwScK+ER683MPUUFP3siPZQwrvR7pOgqb3ntms5fb2DfN5g9KZi7MVdV3x6vVrnn/wEa9evaZuLN4PxAKLhBCYzVpSzjx9+oj1+o66dmX6NtK27XHKUZHpu6GYNTTsNlsePniE0obXr78locq0awUovBcO91iU/6ZRal0gCa2AI4XRlM9ZgqAqmuwy0FEC5Wm1odVEIyyZY77XzOPkoiMMrDKclLIE0zyNhk+UxgxW1rBCpCNOY+r3xvbLwvsOI6R8IHkK3hPccMQcJGP4zjDPb37/9L4Ux2oDJrXL6dCYflwJkBM8UyCO6SBg2j3qNLl4fC11YsiYY8CdDocyZPOfCawKGbw7Tc5+N4c+QbbTPaij0ubvlGL/xvVOB+6qdgRfsoUY8VmkLN2ko4AwHXKiOJ+Iz17diMls3/cYo+mGkbNlK40oLbzjlMMRf85ZpvyMkQVNFnlMX7KfuhbKnSxKWZwirSrTkccufuEnGys0P1FekyZLKA1FYS0gGKU6OUYDxyxmygIVksVO05+yT4WeJo4tIn4veGb8zoBDpjTaStBO8Z7PoFZFtlafNnjmaIiglSkMj1h44ZIJSVDPgvMoc3Q3USW4TCJcSgtHQZTzoKoqslP0XY/WRegoS1aWKFkOkj2SNEfZi3vXcRgEmdBcLc/5+ONP+Pqbb3j48CG//Lu/489++o/45puvaeqa5x8+Z7/f8eCB5vLBEzKO7faGs/Mzckxia/f0OdfX18zalvn8jBBkkGu1WrFYLPjmxVcYU3F2ueTbly948vgJs/mcy8tLXr96xWyxIgPLRcsXX3xB5dpC+dSFGRTK8NQUPCh4L4XeJ6PWxpgjHsz0LLP0FNQUTLQ69iyEFVXC+T0IQBrg+qh0N1EJBXqYBNI4BlBTmE+6iLbp0vyeDgHpHUnllgpCbctYPhR44ggGFx78/Z+V7mHO9zCEY36q7gfDqYdzaixOtMQp253swwSiUEdxp1OCc1onJ92Q33j25Q9T8iPBfgJKOMKk/2Xq3un1pj9PQfv0fk6L9/79/w4J97ttFmycQpksWF1Spes/jYVHhqGclCU4dIcOgMVixoQxpyS6E8fuMyKsFAreOinfoRT94Nl3gW44NcZs4dIKllxKnphLZlLkH9Wp3JqyKaPk9UIMRSQ/MnjP6L04b0ziNUzZM0U0SBpadVWjtZKMfcKBEZGgiXs9mQyX2yt/DyDTfLEY0aaUilxnEeCJRVGuiPxk8nF4ICWBAMYykZjy1PydLK4mJbWpNtCEmAuvvGixRMG4UxDfSWcUrbO0tWUxr5jVtlhuKVJURQtGITIA+jTZOMWECQ9NGasdfZf40Y//mBAVf/iHf0yKmZ/+9M/54suv+NGP/4Af/vjHXN/e8sMf/YTdvqOdzZkvl1ycP+J7n/4By7NH/MM//x9BN3zv+z8WrLxecXbxkMVyRU6Kw37ggw8/4vlHn6BNw6ff+wMePf2QqzevuVvfMpvNub295a///V9hrGO2mIsKpanKoTf5N8pzShPXXnPi5DP5Zsp7TVkmJENKcriqLAdBlucsSqMnDFaVqtEX6dQUsyQy96AxXYJhKpDHcUCrBPopsciZY3CPZVx9MuX1peoQD85pb9xnXBRoN59guVRgwHx8AnCCE9QRhz9dE7Rwb9jqXvCdArVW5ojHaz0F4NM+koPsBKHI34vImkLd+5lCX5Q4W1hb3G8knn6mvFYZ9T8eMuo45CX3UySBUd9RljxBLP8p1PJfu97pjDuXYKSVYuwls3ZVGXcv47GC80FlrZi+VvbeSS2XKZlELDog04BHTInk5YOQTCkzjmP5ub/5Eco1iejDdwcUQE55o09TcClJ0ZTzNLJcBh0QCcjfPJmVUkX7W5qUk7zoNCw0NVaEYig/N8ay+I6lnGQluWQlIU7Sofk77+Y09q2Oz2rajBJACjyST7RIPQ06n3YKE2WLnFDaoicJUKPIOuOMFRlYq4+ynXpmC4YdGcYRFSTTFOU6Te0sPvOde89qqrBGrBEo4ptvvmI2+yFfvfiSf/QP/xFNU2Os4vWrV/R9J4M2JOrKklPAOsV+v+Gw37DfNazvbjg/m0mFYxUuG7SuiF4GmGII9H3PdrenqhzDnWfoO2HIDANPnzzig6dPuLq9Yuw7VqulaMYg6zZE0deZgh5KY9CFraSOwkjce8an9VCy0yzNRV0ooknJGI5Cns+kY64U0sgt/QjpHYj0QjpCH1MwmQ5DCSZaT+vgpOQXYzw26KZ1NzXxvgOZFI1yyba597PvmxH8Rog+wgvHv/mN308QxvT/03Oa9ub9wHw8iPIx//9OBjwFWVn35fdqOnB+897kWZz2SoFrmBqeU1DWv/E6p/cw7eWpUXsK2t/9jP9r1zsduKNP2MocT0VXaeqmwg8eVGQShF/MZ0XyM+G0IxW1MflgVLENiiU4SIZjnWMYx2MGMrEujqPgRQp1wvCOwfLewz9Odim5P61MgQ2miUB1LE39GOXvcmma/MaHOOkggDR3dOEb36fDnbKZdMStQbB+2az2iGFOwMLUaZ94sBMNzVp7XLjTxpB7TiUYy9tK99b1/UNqOpxiycJQCp0jvgR/azVZZ7AZW1lsjKhcDtEkwljGuMJwEZ2SWAaE6ro64sKJEpAKZTEqkeP97LNf4ceRX/3qlxgDf/Mf/5oPn3/IX/3VfzhiwP/i//G/c7Za8m/+zb9mtVoR40AMI5WzfP3i15ATX335OW0745d/93POzuZlY4tT0C/+9lfUdc35+SXffP0C21TEEPjii88ZuoGzizNSjGw2a5bLudC/jMjhhhhlcChP8qUCg4luzImTLNlzEjaHOjEgxCRA+iIpJia7Lw2IdaE6ZtFK56I8W4Zx1CmDPq6X/JufoTrCB5P8whRkTzojHCtKySw1kzLf/anIzD2I7j/zSwLXfYjhBCl8J1s+QhgnSYDpvqbrxEI5wZw53Xu9e/82QaHy9adfR7hjur97XwMch5FkIPg3K+P7Gi769G/6frDPx/+fIJLfg4x7+nCCF4xanu1E30tEldA6FYnGSNMYhr5HqUBOctLFEBnGnhQ91lT40KEQ3NA5UdAzJoFKpDwKrQeBTUSbV6GUEc9XAFTh2EaMKTibEsrSMeMp1KSEIilFTopcutWSwRTnaYTNcsTSymbxQYLuOHZFxa4sTHViXkh1MNmvSXY98V11wdynIQaO+N90jxpdOua66CjEEiByFvrg1KRMWaHSNG02ZRSprHdNzoYcKAfF9L5P4k0xCj82WosynqBKSa4K9VCrIvsqQSdmVd4/GBMgDUCkSHYVqERmhpxR7HfXWCcGxkYL5PK3f/tXxa5MqpXKOtbrHms0h/01xsLt3R5rJGhVtiGmxG5/wFWOoQ8MgwzveB+oasN6veXt1UsqV5F6aC3s7zbMZzOurr5BKWibBu/3RKWoK8sYx9I0Ezsx6amMTD2LFCe2gnxNSsI516VHooIpvY8CXaRAzkU+ocwITOt0ghGTmtgk0shWRVKVe8Hz9KusFQUTbxrEuyDneKQ5TlxuCuMjZyWuTkkz9VpO2eh3A/d9KOU+dfeUWU9skCmrPkENokXJUQLhhIPDxLYR6E4dmVbTgNBpvtiUdXqMKsfs+zsToDkxWZBNXzth8ipnsvoNnaHy76dsvwTsqSDIpSr/TsCefv7wnfj2X7tU/m2+6v/Prq+//pqPPvrov/VtvL/eX++v99f/z68XL17w4Ycf/le/5p0M3Ckl/u7v/o4/+qM/4sWLF6xWq//Wt/RbX5vNho8++uidu294d+/9Xb1veHfv/V29b/hvd+85Z7bbLR988MFxOO+/dL2TUInWmufPnwOwWq3euYUB7+59w7t77+/qfcO7e+/v6n3Df5t7Pzs7+62+7p2mA76/3l/vr/fX7+P1PnC/v95f76/31zt2vbOBu65r/vk//+dlPP3dud7V+4Z3997f1fuGd/fe39X7hnfj3t/J5uT76/31/np//T5f72zG/f56f72/3l+/r9f7wP3+en+9v95f79j1PnC/v95f76/31zt2vQ/c76/31/vr/fWOXe8D9/vr/fX+en+9Y9f7wP3+en+9v95f79j1PnC/v95f76/31zt2vQ/c76/31/vr/fWOXf8fvzDGn5fUlJEAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from skimage.measure import label\n",
        "import tensorflow as tf\n",
        "import io\n",
        "from PIL import Image\n",
        "\n",
        "#Binarize a saliency map using a threshold\n",
        "def binarize(saliency_map, threshold):\n",
        "    \n",
        "    #Get the dimensions of the saliency map\n",
        "    h, w,e = saliency_map.shape\n",
        "    \n",
        "    #The binarized version of the saliency map\n",
        "    result = np.zeros((h,w))\n",
        "    \n",
        "    for i in range(h):\n",
        "        \n",
        "        for j in range(w):\n",
        "            \n",
        "            if(saliency_map[i][j][0] >= threshold[0]):\n",
        "                \n",
        "                result[i][j] = 1\n",
        "                \n",
        "    return result\n",
        "\n",
        "#Donne la valeur moyenne des pixels dans une carte de chaleur\n",
        "def get_average(saliency_map):\n",
        "    \n",
        "    #Les dimensions de la carte de chaleur\n",
        "    n, m ,k= saliency_map.shape\n",
        "    \n",
        "    #La moyenne au départ elle est à 0\n",
        "    average = 0\n",
        "    \n",
        "    #Je somme pour chaque pixel\n",
        "    for i in range(n):\n",
        "        \n",
        "        for j in range(m):\n",
        "            \n",
        "            average += saliency_map[i][j]\n",
        "       \n",
        "    # ma moyenne c'est la somme divisé par le nombre de pixels\n",
        "    return average/(n*m)"
      ],
      "metadata": {
        "id": "G8yvTDwPXnkI"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "avearge_saliency = get_average(im)\n",
        "mask = binarize(im, avearge_saliency)\n",
        "plt.imshow(mask, \"gray\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "n85Jm4z8VrtR",
        "outputId": "72fb9736-1834-49f7-bd12-9cf3a0fff84d"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1f8ac0da60>"
            ]
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Retourne la plus grande boite qui entoure la composante connexe\n",
        "def get_bounding_box(image):\n",
        "    \n",
        "    #Dimension de l'image\n",
        "    n, m = image.shape\n",
        "    \n",
        "    #La coordonnée la plus haute\n",
        "    upper = 0\n",
        "    \n",
        "    #La plus petite coordonnée dans l'image\n",
        "    lower = 0\n",
        "    \n",
        "    #La coordonnée la plus à gauche\n",
        "    left_result = n\n",
        "    \n",
        "    #La coordonnée la plus à droite\n",
        "    right_result = 0\n",
        "    \n",
        "    #Pour savoir si la première bande supérieur a été trouvée\n",
        "    first_bound = True\n",
        "    \n",
        "    #Pour chaque ligne\n",
        "    for i in range(n):\n",
        "        \n",
        "        #Je cherhce le pixel le plus à gauche\n",
        "        left = n\n",
        "        \n",
        "        #et le pixel le plus à droite\n",
        "        right = 0\n",
        "        \n",
        "        #et je regarde si la colonne contient au moins un pixel\n",
        "        contain_pixel = False\n",
        "        \n",
        "        #Pour chaque colonne\n",
        "        for j in range(m):\n",
        "            \n",
        "            #Si l'image contient un pixel à 1\n",
        "            if(image[i][j]) :\n",
        "                \n",
        "                #Je sais que je suis à la première colonne\n",
        "                contain_pixel = True\n",
        "                \n",
        "                #Je compare quel pixel et le plus à gauche\n",
        "                if(j < left):\n",
        "                \n",
        "                    left = j\n",
        "                    \n",
        "                if(j > right):\n",
        "                    \n",
        "                    right = j\n",
        "                    \n",
        "        if(left < left_result):\n",
        "            \n",
        "            left_result = left\n",
        "            \n",
        "        if(right > right_result):\n",
        "            \n",
        "            right_result = right\n",
        "        \n",
        "        if(contain_pixel and first_bound):\n",
        "            \n",
        "            upper = i\n",
        "            first_bound = False\n",
        "            \n",
        "        elif(contain_pixel and not first_bound):\n",
        "            \n",
        "            lower = i\n",
        "            \n",
        "    return [upper, left_result], abs(left_result-right_result), abs(upper-lower)\n",
        "\n",
        "def make_matrix(mask, coordinates):\n",
        "    \n",
        "    result = np.zeros(mask.shape)\n",
        "    \n",
        "    for i in range(coordinates[0][0], coordinates[0][0]+coordinates[2]):\n",
        "        \n",
        "        for j in range(coordinates[0][1], coordinates[0][1]+coordinates[1]):\n",
        "            \n",
        "            result[i][j] = 1\n",
        "            \n",
        "    return result"
      ],
      "metadata": {
        "id": "H-PlsaLoMhAE"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "predicted_box = make_matrix(mask, get_bounding_box(mask))\n",
        "plt.imshow(predicted_box, \"gray\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "57xYbzgRMbnV",
        "outputId": "e8ac3946-c027-4290-ac6b-93e7d83b2b8c"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1f853981f0>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "uploaded = files.upload()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 38
        },
        "id": "sWf-Q7DPQVMH",
        "outputId": "70b3490c-75c4-4d73-9e2a-2a48f2d31e8a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-28e25d64-e483-4154-84d0-b76014210b55\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-28e25d64-e483-4154-84d0-b76014210b55\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def read_trimap(path):\n",
        "    \n",
        "    with tf.io.gfile.GFile(path, 'rb') as fid:\n",
        "        \n",
        "        encoded_mask_png = fid.read()\n",
        "    \n",
        "    encoded_png_io = io.BytesIO(encoded_mask_png)\n",
        "    \n",
        "    return np.array(Image.open(encoded_png_io))\n",
        "\n",
        "\n",
        "#Transform a trimap like the one above into a binary one \n",
        "def transform_trimap(trimap):\n",
        "    \n",
        "    h, w = trimap.shape\n",
        "    \n",
        "    result = []\n",
        "    \n",
        "    for i in range(h):\n",
        "        \n",
        "        line  = []\n",
        "        \n",
        "        for j in range(w):\n",
        "            \n",
        "            if(trimap[i][j] == 2):\n",
        "                \n",
        "                line.append(0)\n",
        "                \n",
        "            else:\n",
        "                \n",
        "                line.append(1)\n",
        "                \n",
        "        result.append(line)\n",
        "                \n",
        "    return np.array(result)"
      ],
      "metadata": {
        "id": "z7-ce3oSQmzo"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "trimap = read_trimap(\"chhi_mask.png\")\n",
        "binary_map = transform_trimap(trimap)\n",
        "ground_truth_box = make_matrix(binary_map, get_bounding_box(binary_map))"
      ],
      "metadata": {
        "id": "qtpj93Ws45YK"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(1, 3, figsize = (12, 12))\n",
        "\n",
        "ax[0].imshow(trimap)\n",
        "ax[1].imshow(binary_map, \"gray\")\n",
        "ax[2].imshow(ground_truth_box, \"gray\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 493
        },
        "id": "zZAg0eUS5Nfx",
        "outputId": "600fe233-05a8-4368-c7f5-612a76f38fe5"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1f8537e3d0>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1200 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from math import log\n",
        "from skimage.measure import label\n",
        "import numpy as np\n",
        "\n",
        "##The ground_truth (mask/box)  and the predicted (mask/box) must be in a binary format\n",
        "##Please make sure that the ground_truth (mask/box) exists (the entry must be a matrix that contains at least a pixel with 1 value)\n",
        "def IoU(ground_truth, predicted_mask):\n",
        "    \n",
        "    #verify if the two images has the same dimensions\n",
        "    # assert ground_truth.shape == predicted_mask.shape\n",
        "    \n",
        "    #Get the dimension of the picture\n",
        "    m, n = ground_truth.shape\n",
        "    \n",
        "    #The variable that will contain the value of the intersection of the two masks area\n",
        "    intersection = 0\n",
        "    \n",
        "    #The same but for union\n",
        "    union = 0\n",
        "    \n",
        "    #We iterate on pixels\n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "            \n",
        "            #If the two of pixels is equal to one that mean that the pixel is in both masks\n",
        "            if(int(ground_truth[i][j]) == 1 and int(predicted_mask[i][j]) == 1):\n",
        "                \n",
        "                intersection += 1\n",
        "                union += 1\n",
        "             \n",
        "            #If the pixel is in one of the twos without being in the other we add 1\n",
        "            if( int(ground_truth[i][j]) == 1 ^ int(predicted_mask[i][j]) == 1):\n",
        "                \n",
        "                union += 1\n",
        "    \n",
        "    return intersection/union\n",
        "\n",
        "#Dice coefficient F1 score\n",
        "#ground truth, preidcted --> (box/mask) must be numpy.array\n",
        "def DC(ground_truth, predicted):\n",
        "\n",
        "    #make sure that the dimensions are the same\n",
        "    # assert ground_truth.shape == predicted.shape\n",
        "\n",
        "    #Get the dimensions of the matrix\n",
        "    h, w = ground_truth.shape\n",
        "\n",
        "    #The number of pixel with 1 as value that are in both of ground_truth and predicted mask or box\n",
        "    TP = 0\n",
        "    #The number of pixels that are in the ground_truth but not in the predicted mask or box\n",
        "    TN = 0\n",
        "    #The same but for predicted instead of ground truth\n",
        "    FN = 0\n",
        "\n",
        "    #We iterate in each pixel in both ground_truth and predicted to see what does match\n",
        "    for i in range(175):\n",
        "\n",
        "        for j in range(175):\n",
        "            \n",
        "            #We verify if they had 1 pixels in commun (intersection)\n",
        "            if(int(ground_truth[i][j]) == 1 and int(predicted[i][j]) == 1):\n",
        "\n",
        "                TP += 1\n",
        "\n",
        "            #To count the number of pixels \"1\" that are in ground_truth but not in predicted\n",
        "            elif(int(ground_truth[i][j]) == 1 and int(predicted[i][j]) == 0):\n",
        "\n",
        "                FN += 1\n",
        "\n",
        "            #Same thing but for predicted\n",
        "            elif(int(ground_truth[i][j]) == 0 and int(predicted[i][j]) == 1):\n",
        "\n",
        "                TN += 1\n",
        "\n",
        "    #The dice formula (2*Union/(cardinality(ground_truth)+cardinality(predicted))\n",
        "    return 2*TP/(2*TP+TN+FN)\n",
        "\n",
        "#Localization error\n",
        "def LE(ground_truth, prediction):\n",
        "    \n",
        "    return 1-IoU(ground_truth, prediction)\n",
        "\n",
        "\n",
        "#Energy pointing game it is equivalent to the \"Pixel-wise precision\"\n",
        "def EPG(ground_truth_mask, saliency_map):\n",
        "\n",
        "\n",
        "    # assert ground_truth_mask.shape ==  saliency_map.shape\n",
        "    \n",
        "    h, w = ground_truth_mask.shape\n",
        "    \n",
        "    #The saliency contained in the ground_truth (mask or box)\n",
        "    ground_truth_saliency = 0\n",
        "    \n",
        "    #The saliency on the hole image\n",
        "    global_saliency = 0\n",
        "    \n",
        "    \n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "            \n",
        "            #We and the value of the saliency when we have a pixel of 1 in the ground_truth\n",
        "            ground_truth_saliency += float(saliency_map[i][j][0])*int(ground_truth_mask[i][j])\n",
        "            \n",
        "            #We sum the saliency of all pixels\n",
        "            global_saliency += float(saliency_map[i][j][0])\n",
        "\n",
        "    #The formula of energy pointing game\n",
        "    return ground_truth_saliency/global_saliency\n",
        "\n",
        "\n",
        "#The precision for the class of pixels with 1 value\n",
        "def precision(ground_truth, predicted):\n",
        "    \n",
        "    #verify if the dimensions are the same\n",
        "    # assert ground_truth.shape == predicted.shape\n",
        "    \n",
        "    #Get the dimensions of one of the matrices\n",
        "    h, w = ground_truth.shape\n",
        "    \n",
        "    #The well classified pixels\n",
        "    good_predictions = 0\n",
        "    \n",
        "    #The number of pixels with value of one\n",
        "    hypothesis = 0\n",
        "    \n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "\n",
        "            #If the predicted label correspond to the ground label\n",
        "            if(ground_truth[i][j] == predicted[i][j] and ground_truth[i][j] == 1):\n",
        "                \n",
        "                good_predictions += 1\n",
        "                \n",
        "                hypothesis += 1\n",
        "                \n",
        "            #If it's not\n",
        "            elif(predicted[i][j] == 1 and ground_truth[i][j] == 0):\n",
        "                \n",
        "                hypothesis += 1\n",
        "                \n",
        "    return good_predictions/hypothesis\n",
        "\n",
        "\n",
        "#The recall of class 1 pixels\n",
        "def recall(ground_truth, predicted):\n",
        "\n",
        "    # assert ground_truth.shape == predicted.shape\n",
        "    \n",
        "    h, w = ground_truth.shape\n",
        "    \n",
        "    #Well classified pixels\n",
        "    good_predictions = 0\n",
        "    \n",
        "    #The number of pixels with 1 as value\n",
        "    refrences = 0\n",
        "    \n",
        "    #Same thing as the precision but we calculate the number of references pixels of ground truth\n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "            \n",
        "            if(ground_truth[i][j] == predicted[i][j] and ground_truth[i][j] == 1):\n",
        "                \n",
        "                good_predictions += 1\n",
        "                refrences += 1\n",
        "                \n",
        "            elif(ground_truth[i][j] == 1 and predicted[i][j] == 0):\n",
        "                \n",
        "                refrences += 1\n",
        "                \n",
        "    return good_predictions/refrences\n",
        "\n",
        "\n",
        "#The beta F-score \n",
        "def F_score(ground_truth, predicted, beta=1):\n",
        "    \n",
        "    p = precision(ground_truth, predicted)\n",
        "    \n",
        "    r = recall(ground_truth, predicted)\n",
        "    print(p)\n",
        "    print(r)\n",
        "    \n",
        "    return (1+beta**2)*p*r/((beta**2)*p+r)\n",
        "\n",
        "\n",
        "#Calculate the fraction of the ground truth  that is covered by the saliency map\n",
        "def pixel_wise_recall(ground_truth, sallience_map):\n",
        "    \n",
        "    # assert ground_truth.shape == sallience_map.shape\n",
        "    \n",
        "    m, n = ground_truth.shape\n",
        "    \n",
        "    ground_truth_saliency = 0\n",
        "    \n",
        "    refrences = 0\n",
        "    \n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "            \n",
        "            if(int(ground_truth[i][j]) == 1):\n",
        "                \n",
        "                refrences += 1\n",
        "                \n",
        "                ground_truth_saliency += float(sallience_map[i][j][0])\n",
        "                \n",
        "    \n",
        "    return ground_truth_saliency/refrences\n",
        "\n",
        "\n",
        "#The F_beta score\n",
        "def pixel_wise_F_score(ground_truth, saliency_map, beta=1):\n",
        "    \n",
        "    p = EPG(ground_truth, saliency_map)\n",
        "    \n",
        "    r = pixel_wise_recall(ground_truth, saliency_map)\n",
        "\n",
        "    return (1+beta**2)*(p*r)/((beta**2)*p+r)\n",
        "\n",
        "\n",
        "#Calculate the \"1\" class pixels in a binary mask or box\n",
        "def get_cardinality(predicted):\n",
        "    \n",
        "    h, w = predicted.shape\n",
        "    \n",
        "    result = 0\n",
        "    \n",
        "    for i in range(h):\n",
        "        \n",
        "        for j in range(w):\n",
        "            \n",
        "            if(int(predicted[i][j]) == 1):\n",
        "                \n",
        "                result += 1\n",
        "                \n",
        "    return result\n",
        "\n",
        "#The saliency metric\n",
        "def SM(predicted, probability_class):\n",
        "    \n",
        "    h, w = predicted.shape\n",
        "    \n",
        "    return log( max( 0.05, get_cardinality(predicted) / (h*w) ) ) - log( probability_class )\n",
        "\n",
        "\n",
        "#The absolute mean error\n",
        "def AME(saliency_map, ground_truth):\n",
        "    \n",
        "    # assert saliency_map.shape == ground_truth.shape\n",
        "    \n",
        "    h, w ,v = saliency_map.shape\n",
        "    \n",
        "    result = 0\n",
        "    \n",
        "    for i in range(175):\n",
        "        \n",
        "        for j in range(175):\n",
        "            \n",
        "            result += abs(float(saliency_map[i][j][0]) - int(ground_truth[i][j]))\n",
        "            \n",
        "    return result/(h*w)\n",
        "\n",
        "#The mask and box accuaracy it works for both of them\n",
        "#Max value refer to sigma the second threshold\n",
        "def accuaracy(ground_truths, saliency_maps, thresholds_list, max_value=0.5):\n",
        "    \n",
        "    assert len(ground_truths) == len(saliency_maps)\n",
        "    \n",
        "    results = np.zeros((len(thresholds_list),0))\n",
        "    \n",
        "    for i in range(len(ground_truths)):\n",
        "        \n",
        "        for j in len(thresholds_list):\n",
        "            \n",
        "            if(IoU(ground_truths[i], saliency_maps[i]) >= max_value):\n",
        "                \n",
        "                results[j] += 1\n",
        "                \n",
        "    results = results/len(ground_truths)  \n",
        "    \n",
        "    return np.max(results), results\n",
        "\n",
        "\n",
        "\n",
        "def concept_influence(binary_segmentation_mask, top_k_binary_mask, k = 1_000):\n",
        "    \n",
        "    assert binary_segmentation_mask.shape ==  top_k_binary_mask.shape\n",
        "    \n",
        "    h, w = binary_segmentation_mask.shape\n",
        "    \n",
        "    top_k_binary_mask = 0\n",
        "    \n",
        "    relative_size_concept = 0\n",
        "    \n",
        "    for i in range(h):\n",
        "        \n",
        "        for j in range(w):\n",
        "            \n",
        "            top_k_binary_mask += binary_segmentation_mask[i][j]*top_k_binary_mask[i][j]\n",
        "            \n",
        "            relative_size_concept += binary_segmentation_mask[i][j]\n",
        "    \n",
        "    top_k_binary_mask /= k\n",
        "    \n",
        "    return top_k_binary_mask/relative_size_concept\n",
        "\n",
        "def relevance_rank_accuracy(ground_truth, top_k_pixels):\n",
        "    \n",
        "    h, w = ground_truth.shape\n",
        "    \n",
        "    result = 0\n",
        "    \n",
        "    for pixel in top_k_pixels:\n",
        "        \n",
        "        result += ground_truth[pixel[0]][pixel[1]]\n",
        "        \n",
        "    return result/(h*w)"
      ],
      "metadata": {
        "id": "VNOG0hXsQpHQ"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "LE(ground_truth_box, predicted_box)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1UK_RwPGRKJb",
        "outputId": "dfd12e0b-2a06-471c-ab67-3a84fec60f4a"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(1, 2, figsize = (12, 12))\n",
        "\n",
        "ax[0].imshow(predicted_box, \"gray\")\n",
        "ax[1].imshow(ground_truth_box, \"gray\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "id": "7eKjLKsrhB2x",
        "outputId": "b8eaa5f5-6997-4e7d-8809-636018e29e9d"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1f84c977c0>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1200 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "LE(binary_map, mask)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4fDpgarxhI82",
        "outputId": "81d623f5-a14b-4978-cd11-944057048bad"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.15573770491803274"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig, ax = plt.subplots(1, 2, figsize = (12, 12))\n",
        "\n",
        "ax[0].imshow(binary_map, \"gray\")\n",
        "ax[1].imshow(mask, \"gray\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 717
        },
        "id": "1inCczJhhOTN",
        "outputId": "9af5c590-8b33-4fbc-882c-7c01d6fef7b7"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f1f8520e130>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1200 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "1- DC(binary_map, mask)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cml_32RDhQpG",
        "outputId": "8278777f-c797-46d3-ee9e-e2c81f817efb"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6585700405783849"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "EPG(binary_map, im)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m0hTJYPFihY_",
        "outputId": "7987a502-28f5-4ea5-8203-ad3fb228902b"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.19404191884884414"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "EPG(ground_truth_box, im)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s2-Tl2SYihg0",
        "outputId": "c6d15742-59c3-4a15-ca5b-7cd2ef01f0a3"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.31130461711861546"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pixel_wise_F_score(binary_map, im)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cpK5busrnXt9",
        "outputId": "728cd5ba-0755-4260-e982-a90383e7f120"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.2920642747413153"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pixel_wise_F_score(ground_truth_box, im)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xNm29qYdHAvY",
        "outputId": "a7f0b397-7d50-4ec8-e44e-0f765db22680"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.3922277520071779"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "AME(im, ground_truth_box)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cnGfaZ32HH9-",
        "outputId": "8c55a7c5-81ba-4d82-ca5c-798ac2c89aa9"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.062356310009598376"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "AME(im, binary_map)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2vl7xmX-IFuC",
        "outputId": "66c581f4-ea0f-4d1e-d502-5eb151fc84c3"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.06079995407803997"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    }
  ]
}