Compare_Patent_Datasets.ipynb

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      "source": [
        "import pandas as pd\n",
        "from google.colab import files\n",
        "import matplotlib.pyplot as plt\n",
        "import re\n",
        "import pandas as pd\n",
        "from google.colab import files\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import random\n",
        "import matplotlib.pyplot as plt\n",
        "import random"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "upload = files.upload()\n",
        "df = pd.read_csv('/content/compare_datasets.csv')"
      ],
      "metadata": {
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              "\n",
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              "        style=\"border:none\" />\n",
              "     <output id=\"result-cd4a92ba-f1aa-415e-8735-08c221044282\">\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",
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              "    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",
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              "\n",
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              "  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",
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              "    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: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
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              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
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              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
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              "    }\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 compare_datasets.csv to compare_datasets (1).csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.fillna(0, inplace=True)\n",
        "df.head()"
      ],
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   year  patentcity  fleming  kelly\n",
              "0  1836          23      0.0  108.0\n",
              "1  1837         112      0.0  436.0\n",
              "2  1838         147      0.0  515.0\n",
              "3  1839         114      0.0  404.0\n",
              "4  1840         127      0.0  458.0"
            ],
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              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 186,\n  \"fields\": [\n    {\n      \"column\": \"year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 53,\n        \"min\": 1836,\n        \"max\": 2021,\n        \"num_unique_values\": 186,\n        \"samples\": [\n          1949,\n          2000,\n          2005\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"patentcity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 24618,\n        \"min\": 23,\n        \"max\": 127423,\n        \"num_unique_values\": 186,\n        \"samples\": [\n          7177,\n          60048,\n          55757\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fleming\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 66822.90178534607,\n        \"min\": 0.0,\n        \"max\": 319641.0,\n        \"num_unique_values\": 93,\n        \"samples\": [\n          62855.0,\n          20138.0,\n          62069.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"kelly\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 54401.926704552025,\n        \"min\": 0.0,\n        \"max\": 300677.0,\n        \"num_unique_values\": 181,\n        \"samples\": [\n          1879.0,\n          12345.0,\n          95546.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming 'df' is your DataFrame\n",
        "# Filter the DataFrame for years 1836 to 1925\n",
        "df_filtered = df[(df['year'] >= 1836) & (df['year'] <= 1925)]\n",
        "\n",
        "# Plotting\n",
        "plt.figure(figsize=(10, 6))  # Adjust the figure size as needed\n",
        "\n",
        "# Set the positions for the bars\n",
        "bar_width = 0.35  # Width of the bars\n",
        "index = df_filtered['year']  # X-axis values\n",
        "index_shifted = index + bar_width  # Shifted positions for the second set of bars\n",
        "\n",
        "# Plot the first set of bars for 'patentcity'\n",
        "plt.bar(index, df_filtered['patentcity'], bar_width, label='Patent City', color='b')\n",
        "\n",
        "# Plot the second set of bars for 'kelly', slightly offset to avoid overlap\n",
        "plt.bar(index_shifted, df_filtered['kelly'], bar_width, label='Kelly', color='r')\n",
        "\n",
        "# Add some labels and a legend\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Values')\n",
        "plt.title('Comparison of Patent City and Kelly over Years')\n",
        "plt.xticks(index + bar_width / 2, df_filtered['year'].unique(), rotation=90)  # Set the position and labels of the ticks\n",
        "plt.legend()\n",
        "\n",
        "# Display the plot\n",
        "plt.tight_layout()  # Adjust layout to not cut off labels\n",
        "plt.show()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "zgI4IZqNMnBY",
        "outputId": "91e1f9bc-4e81-4a4c-822c-16c11f6703b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_filtered = df[(df['year'] >= 1836) & (df['year'] <= 1925)]\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 6))\n",
        "\n",
        "# Number of bars/groups\n",
        "n_bars = len(df_filtered.index)\n",
        "\n",
        "# Locations for the groups\n",
        "index = np.linspace(1836, 1925, n_bars)  # Generate linearly spaced positions to match the range\n",
        "\n",
        "# Width of each bar\n",
        "bar_width = (index[1] - index[0]) * 0.25  # Calculate width based on spacing\n",
        "\n",
        "# Plotting the bars\n",
        "bars1 = ax.bar(index - bar_width / 2, df_filtered['kelly'], bar_width, color='blue', alpha=0.3, label='Kelly Dataset')\n",
        "bars2 = ax.bar(index + bar_width / 2, df_filtered['patentcity'], bar_width, color='red', alpha=0.8, label='PatentCity')\n",
        "\n",
        "\n",
        "#plt.title('Comparative Analysis of Patent Counts Pre-1925: PatentCity and Kelly Dataset', fontsize=12)\n",
        "ax.set_ylabel('Patent counts')\n",
        "# Setting x-ticks and labels for every 10 years from 1920 to 2020\n",
        "tick_positions = range(1830, 1930, 10)\n",
        "ax.set_xticks(tick_positions)\n",
        "ax.set_xticklabels(tick_positions, rotation=45)  # Rotate x-axis labels for better readability\n",
        "\n",
        "# Setting the x-axis limit from 1925 to 2017\n",
        "plt.xlim(1836, 1925)\n",
        "\n",
        "# Additional customizations\n",
        "ax.grid(axis='y', linestyle='--', alpha=0.5)\n",
        "ax.grid(axis='x', linestyle='--', alpha=0.5)\n",
        "for spine in ax.spines.values():\n",
        "    spine.set_edgecolor('black')\n",
        "    spine.set_linewidth(0.5)\n",
        "    spine.set_alpha(0.5)\n",
        "\n",
        "ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), ncol=2, frameon=False)\n",
        "\n",
        "# Showing the plot\n",
        "plt.tight_layout()  # Adjust layout to not cut off labels\n",
        "#plt.savefig('before_1925.png', dpi=300)\n",
        "plt.show()\n",
        "#files.download('before_1925.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 609
        },
        "id": "bIKb9gumNYRq",
        "outputId": "1bf52417-d808-4d78-aa2c-dcc8f3971348"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_filtered = df[df['year'] > 1925]\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 6))\n",
        "\n",
        "# Number of bars/groups\n",
        "n_bars = len(df_filtered.index)\n",
        "\n",
        "# Locations for the groups\n",
        "index = np.linspace(1926, 2017, n_bars)  # Generate linearly spaced positions to match the range\n",
        "\n",
        "# Width of each bar\n",
        "bar_width = (index[1] - index[0]) * 0.25  # Calculate width based on spacing\n",
        "\n",
        "# Plotting the bars\n",
        "bars1 = ax.bar(index - bar_width / 3, df_filtered['kelly'], bar_width, color='blue', alpha=0.3, label='Kelly Dataset')\n",
        "bars2 = ax.bar(index + bar_width / 3, df_filtered['patentcity'], bar_width, color='red', alpha=0.8, label='PatentCity')\n",
        "bars3 = ax.bar(index + bar_width / 3, df_filtered['fleming'], bar_width, color='orange', alpha=0.8, label='Fleming Dataset')\n",
        "\n",
        "\n",
        "plt.title('Comparative Analysis of Patent Counts Post-1925: PatentCity, Kelly Dataset, and Fleming Dataset', fontsize=12)\n",
        "ax.set_ylabel('Patent counts')\n",
        "# Setting x-ticks and labels for every 10 years from 1920 to 2020\n",
        "tick_positions = range(1920, 2020, 10)\n",
        "ax.set_xticks(tick_positions)\n",
        "ax.set_xticklabels(tick_positions, rotation=45)  # Rotate x-axis labels for better readability\n",
        "\n",
        "# Setting the x-axis limit from 1925 to 2017\n",
        "plt.xlim(1926, 2017)\n",
        "\n",
        "# Additional customizations\n",
        "ax.grid(axis='y', linestyle='--', alpha=0.5)\n",
        "ax.grid(axis='x', linestyle='--', alpha=0.5)\n",
        "for spine in ax.spines.values():\n",
        "    spine.set_edgecolor('black')\n",
        "    spine.set_linewidth(0.5)\n",
        "    spine.set_alpha(0.5)\n",
        "\n",
        "ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), ncol=3, frameon=False)\n",
        "\n",
        "# Showing the plot\n",
        "plt.tight_layout()  # Adjust layout to not cut off labels\n",
        "#plt.savefig('before_1925.png', dpi=300)\n",
        "plt.show()\n",
        "#files.download('before_1925.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "hoZ5CHjDPdKb",
        "outputId": "8aadeaf9-55ba-4f43-d4bf-cc9e2e25bca1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming df_filtered is already defined and contains the filtered data\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(10, 6))\n",
        "\n",
        "# Number of bars/groups\n",
        "n_bars = len(df_filtered.index)\n",
        "\n",
        "# Locations for the groups\n",
        "index = np.linspace(1926, 2017, n_bars)  # Generate linearly spaced positions to match the range\n",
        "\n",
        "# Width of each bar - consider reducing this for more space between bars\n",
        "bar_width = (index[1] - index[0]) * 0.2  # Slightly narrower bars\n",
        "\n",
        "# Adjusting the positions to make the bars more separated\n",
        "offset = bar_width  # Increase the offset to separate the bars more\n",
        "\n",
        "# Plotting the bars with adjusted positions\n",
        "bars1 = ax.bar(index - offset, df_filtered['kelly'], bar_width, color='blue', alpha=0.3, label='Kelly Dataset')\n",
        "bars2 = ax.bar(index, df_filtered['patentcity'], bar_width, color='red', alpha=0.8, label='PatentCity')\n",
        "bars3 = ax.bar(index + offset, df_filtered['fleming'], bar_width, color='orange', alpha=0.8, label='Fleming Dataset')\n",
        "\n",
        "#plt.title('Comparative Analysis of Patent Counts Post-1925: PatentCity, Kelly Dataset, and Fleming Dataset', fontsize=12)\n",
        "ax.set_ylabel('Patent counts')\n",
        "# Setting x-ticks and labels for every 10 years from 1920 to 2020\n",
        "tick_positions = range(1920, 2020, 10)\n",
        "ax.set_xticks(tick_positions)\n",
        "ax.set_xticklabels(tick_positions, rotation=45)  # Rotate x-axis labels for better readability\n",
        "\n",
        "# Setting the x-axis limit from 1925 to 2017\n",
        "plt.xlim(1926, 2017)\n",
        "\n",
        "# Additional customizations\n",
        "ax.grid(axis='y', linestyle='--', alpha=0.5)\n",
        "ax.grid(axis='x', linestyle='--', alpha=0.5)\n",
        "for spine in ax.spines.values():\n",
        "    spine.set_edgecolor('black')\n",
        "    spine.set_linewidth(0.5)\n",
        "    spine.set_alpha(0.5)\n",
        "\n",
        "ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.1), ncol=3, frameon=False)\n",
        "\n",
        "# Showing the plot\n",
        "plt.tight_layout()  # Adjust layout to not cut off labels\n",
        "plt.savefig('after_1925.png', dpi=300)\n",
        "plt.show()\n",
        "files.download('after_1925.png')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 609
        },
        "id": "7JpOufE9Qifs",
        "outputId": "02cb91b0-98ef-45f6-9d3b-31f55602d720"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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JdEEQaMuWLerbt2+zn3dA+pGDfWTgBnKwjwzcQA72kYEbyMENYTOyLZL6ysE3TTvL6qT7T3/6015v7969u2bPnq3Zs2c3u87gwYM1f/78vW7npJNO0ptvvrnXdaZNm6Zp06Z9pVoymTFGVVVV6tOnj+1SujRysI8M3EAO9pGBG8jBPjJwAzm4wRgjY6rkeeSQCl6eAAAAAAAgTZh0AwAAAACQJky6ISnsRJiXl0dHSMvIwT4ycAM52EcGbiAH+8jADeTghrB7eZ5S7l6+YNTupmtdkPXv6YYbfN9XUVGR7TK6PHKwjwzcQA72kYEbyME+MnADObgh7F5ODqniSjckhZ0IN27cqCAIbJfSpZGDfWTgBnKwjwzcQA72kYEbyMENYffyjTKGHFLBpBuSwk6E1dXVMsbYLqVLIwf7yMAN5GAfGbiBHOwjAzeQgxvC7uXVksghFUy6AQAAAABIEybdAAAAAACkCZNuSAo7ERYUFNAR0jJysI8M3EAO9pGBG8jBPjJwAzm4IexeXqCUu5d3cXQvh6SwE2FBQYHtMro8crCPDNxADvaRgRvIwT4ycAM5uCHsXk4OqeJKNySFnQjXrVtHR0jLyME+MnADOdhHBm4gB/vIwA3k4Iawe/k6upeniEk3JIWdCGtqaugIaRk52EcGbiAH+8jADeRgHxm4gRzcEHYvrxHdy1PDpBsAAAAAgDRh0g0AAAAAQJow6YaksClCYWGhfJ9dwiZysI8M3EAO9pGBG8jBPjJwAzm4IWykViimkamhezkkhe3/8/PzbZfR5ZGDfWTgBnKwjwzcQA72kYEbyMEN4VeG5dsuI+PwEgUkhZ0I16xZQ0dIy8jBPjJwAznYRwZuIAf7yMAN5OCGsHv5GrqXp4hJNySFnQhra2vpCGkZOdhHBm4gB/vIwA3kYB8ZuIEc3BB2L68V3ctTw6QbAAAAAIA0YdINAAAAAECaMOmGpLAT4cCBA+kIaRk52EcGbiAH+8jADeRgHxm4gRzcEHYvHyimkamhezkkhZ0Ie/XqZbuMLo8c7CMDN5CDfWTgBnKwjwzcQA5uCLuXk0OqeIkCkqR4PK6VK1cqHo/bLqVLIwf7yMAN5GAfGbiBHOwjAzeQgxvi8biMWSljyCEVTLoR4SsY3EAO9pGBG8jBPjJwAznYRwZuIAc38HVhqWPSDQAAAABAmjDpBgAAAIAubu7c8Aftj0k3JIWdCIuLi+kIaRk52EcGbiAH+8jADeRgHxm4gRzcEHYvLxbTyNRwbyGSlUUzexeQg31k4AZysI8M3EAO9pGBG8ihgy0YFf40Qg6pYtINSWFjivLychpUWEYO9pGBG8jBPjJwAznYRwZuIAc3BEEgY8olkUMqmHQDAAAAAJAmTLoBAAAAAEgTJt0AAAAAAKQJk25ICjsRlpSU0BHSMnKwjwzcQA72kYEbyME+MnADObgh7F5eIqaRqeHeQqSurs52CRA5uIAM3EAO9pGBG8jBPjJwAzm4ghxSxaQbksJOhBUVFXSEtIwc7CMDN5CDfWTgBnKwjwzcQA5uCLuXV4ju5alh0g0AAAAAQJow6QYAAAAAIE2YdCNCYwo3kIN9ZOAGcrCPDNxADvaRgRvIwQ2eRw6pyrJdANwQi8VUWlpqu4wujxzsIwM3kIN9ZOAGcrCPDNxADm6IxWLyPHJIFS9TQJJkjNH27dtljLFdSpdGDvaRgRvIwT4ycAM52EcGbiAHNxhjZAw5pIpJNySFnQjXr19PR0jLyME+MnADOdhHBm4gB/vIwA3k4Iawe/l60b08NUy6AQAAAABIEybdAAAAAACkCZNuSJI8z1N2drY8z7NdSpdGDvaRgRvIwT4ycAM52EcGbiAHN3ieJ8/LlkQOqaB7OSSFX8EwZMgQ22V0eeRgHxm4gRzsIwM3kIN9ZOAGcnCD7/vyPHJIFVe6ISnsRLht2zY6EVpGDvaRgRvIwT4ycAM52EcGbiAHN4Tdy8khVUy6ISnsRFhZWUlHSMvIwT4ycAM52EcGbiAH+8jADeTghrB7eaXoXp4aJt0AAAAAAKQJk24AAAAAANKESTckhZ0Ic3Nz6QhpGTnYRwZuIAf7yMAN5GAfGbiBHNwQdi/PFd3LU0P3ckgKOxEOGjTIdhldHjnYRwZuIAf7yMAN5GAfGbiBHNwQdi8nh1RxpRuSwqYIVVVVNKewjBzsIwM3kIN9ZOAGcrCPDNxADm4IG6lVyRhySAWTbkgK2/9XVVXR/t8ycrCPDNxADvaRgRvIwT4ycAM5uCH8yrAqSeSQCibdAAAAAACkCZNuAAAAAADShEk3JIWdCPPy8ugIaRk52EcGbiAH+8jADeRgHxm4gRzcEHYvzxPdy1ND93JICjsRFhUV2S6jyyMH+8jADeRgHxm4gRzsIwM3kIMbwu7l5JAqrnRDUtiJcOPGjXSEtIwc7CMDN5CDfWTgBnKwjwzcQA5uCLuXb6R7eYqYdENS2ImwurqajpCWkYN9ZOAGcrCPDNxADvaRgRvIwQ1h9/Jq0b08NUy6AQAAAKArWTAq/EGHYNINAAAAAECaMOmGpLATYUFBAR0hLSMH+8jADeRgHxm4gRzsIwM3kMNXM3du+PNVhd3LC0T38tRYnXTfeuutOvroo7XPPvuoX79+Ovvss/Xhhx8mrXPSSSfVh7v754orrkhaZ+3atZo4caJ69uypfv366ZprrlFdXV3SOi+++KKOOuoo5eTkaNiwYXrooYca1TN79mwdeOCB6t69u0aPHq3XX3896fYvv/xSU6dO1b777qtevXrp3HPP1aZNm9rnzrDM930VFBTI93kdxiZysI8M3EAO9pGBG8jBPjJwAzm4IexeXiDPI4dUWL23Fi1apKlTp+rVV1/V888/r127dmncuHGqqalJWu+yyy7Txo0bo5/bb789ui0ej2vixImqra3V4sWL9fDDD+uhhx7SzJkzo3UqKio0ceJEnXzyyVq+fLmuuuoq/fCHP9Szzz4brfPoo49q+vTpuuGGG/TGG2/oiCOO0Pjx47V58+Zonauvvlpz587V448/rkWLFmnDhg0655xz0ngPdZwgCLRu3To6QlpGDvaRgRvIwT4ycAM52EcGbiAHN4Tdy9fRvTxFVr+ne8GCBUn/fuihh9SvXz8tW7ZMJ554YrS8Z8+eKiwsbHIbzz33nN577z394x//UP/+/XXkkUfq5ptv1rXXXqsbb7xR2dnZuv/++1VcXKxf/epXkqThw4fr5Zdf1p133qnx48dLkn7961/rsssu0+TJkyVJ999/v+bNm6cHHnhAP/3pT1VdXa0//elPmjNnjk455RRJ0oMPPqjhw4fr1Vdf1bHHHtuotp07d2rnzp1Jy2praxWPx6N/e54n3/frd2DT4vLw1SWv2eUNt51YLqnRA9Sey+PxuD7//PP6joQmaf1ELc0tb23tHT2mhFgsljFjqqur0+eff666ujrFYrFOMaZMyykej2v79u0yxnSaMTVcniljangsdOvWrVOMKdNyCoJANTU1isfjnWZMmZhT4vk5Ho93mjG1tXZbY5Kk7du3R8/NnWFMmZhT4lgIgiDaTqaPqaXl7TmmcJJslCjJM558zyStH/7Hl5QYU7i/q/7xx/M81dXVyZjPJdUpHo/Jr/9TQUtjrd9WTNrLmDwF8pUostkxGV++5ExOrWF10r2n6upqSVLfvn2Tlj/yyCP6y1/+osLCQp1xxhn6z//8T/Xs2VOStGTJEh122GHq379/tP748eM1ZcoUvfvuu/ra176mJUuWaOzYsUnbHD9+vK666ipJ4UR42bJluu6666Lbfd/X2LFjtWTJEknSsmXLtGvXrqTtHHzwwTrggAO0ZMmSJifdt956q2bNmpW07PTTT9fo0aOjf+fl5amoqEibNm2Kxi9JBQUFKigo0CeffJJ05b+wsFD5+fn66KOPVFtbGy0fOHCgevXqpdWrVyftCMXFxcrKylJ5eXlSHSUlJaqrq1NFRYWkcOfZunWrJKmmpkbr16+P1s3OztaQIUNUXV2tysrKaHlubq4GDRqkLVu2qKqqyrkxSWGOpaWlGTOmVatWacuWLVq1apV83+8UY8q0nBITPkmdZkxS5uX0+eefR8fCgAEDOsWYMi2nffbZR5K0efNmff75551iTJmYUxAE2rJlizZs2KDBgwd3ijFlWk5Dhw7Vrl27oufmzjCmTMwpcSwkXozqDGPqyJykTTKmWok/XWAOUIH3cdKYjJE8r1BS/ZjiY8KVy8ujMYU1bpG0SuXlvorVU1na2fKY4mPkK65S7WWuYfqrMihVoshmxxQMU5HkTE6t4RlHvuwuCAKdeeaZ2rZtm15++eVo+e9//3sNHjxYAwYM0Ntvv61rr71WxxxzjP72t79Jki6//HJ9/PHHSW8V37Fjh3JzczV//nxNmDBBpaWlmjx5ctKkev78+Zo4caJ27NihrVu3av/999fixYtVVlYWrTNjxgwtWrRIr732mubMmaPJkyc3unJ9zDHH6OSTT9Ztt93WaExNXel+4okn9L3vfS/6tyuvqMXjca1atUoHHXRQ9Hf3rIVXCdM/psST+rBhw7jSbWlM8Xhcq1evVmlpqfaUqWNquDxTcqqrq4uOBa5027vSvXr1ag0dOjTppCKTx5SJOSWen0tKStStW7dOMaa21m7zKtbKlSs1dOhQrnRbvtK9atUqlZaWKhaLdYoxtbS8Pcf01FPhle6JE+uXP3dseKV73OvR+vPmSZKvM8+sH9Oz9fOicYujMdXW1uqZZ1ZJGqbTT4/Jfy68mBiMe23vY3ruuHBME15rfkzPHB1e6R63eO9jeq5M/oTXncnpscce00UXXaS9ceZK99SpU/XOO+8kTbilcFKdcNhhh6moqEinnnpqdCLgspycHOXk5CQty87Ojh6wG2ruVZJUlze17dYs931fAwYMiHa+ptZvbnl71d7eY2ooU8bUrVs3DRgwIJpk7G39TBlTpuXk+76KioqiY6G1tTe33IUxtVRjqss7YkxNHQuZPqZUlrswJt/3VVhYqKysrCaPhUwcU3sv74gxJZ6fs7Ky2rV2cmr9cmOMioqKGj03S5k7JinzckocC7FYLOXaXR1Ta5a315gSjc+iX/FMo/Ub7t6+70teXMm/pPrjYICkborFPCWamLc4Jm/3xLb5MRnFFE/6e02OyQuaXt7c+i0sb4+cWtK66+FpNm3aND399NP65z//qYEDB+513cRbs1etWiUpfLvAnh3EE/9OfA68uXV69+6tHj16qKCgQLFYrMl1Gm6jtrZW27Zta3adTOZ5nvLz85udZKBjkIN9ZOAGcrCPDNxADvaRgRvIwQ2e58nzyCFVVifdxhhNmzZNTzzxhF544QUVFxe3+DvLly+XpPrPJkhlZWVasWJFUpfx559/Xr1799aIESOidRYuXJi0neeffz56K3l2drZGjhyZtE4QBFq4cGG0zsiRI9WtW7ekdT788EOtXbs26S3pmSoIAq1Zs6bJt1Sh45CDfWTgBnKwjwzcQA72kYEbyMEN4Vu014ju5amx+vbyqVOnas6cOfr73/+uffbZJ2oGkJeXpx49emj16tWaM2eOvvnNb2rffffV22+/rauvvlonnniiDj/8cEnSuHHjNGLECH3/+9/X7bffrsrKSl1//fWaOnVq9NbuK664Qvfcc49mzJihSy65RC+88IIee+wxzQs/uCBJmj59uiZNmqRRo0bpmGOO0V133aWampqom3leXp4uvfRSTZ8+XX379lXv3r31ox/9SGVlZU02Ucs0xhjV1tYmfc4BHY8c7CMDN5CDfWTgBnKwjwzcQA5uMMbImFp5Hjmkwuqk+7777pMknXTSSUnLH3zwQV188cXKzs7WP/7xj2gCPGjQIJ177rm6/vrro3VjsZiefvppTZkyRWVlZcrNzdWkSZN00003ResUFxdr3rx5uvrqq3X33Xdr4MCB+uMf/xh9XZgkXXDBBfr00081c+ZMVVZW6sgjj9SCBQuSuqLfeeed8n1f5557rnbu3Knx48fr3nvvTdO9AwAAAADIdFYn3S29UjVo0CAtWrSoxe0MHjxY8+fP3+s6J510kt588829rjNt2jRNmzat2du7d++u2bNna/bs2S3WBAAAAACAE43UYJ/v+xo4cGCzXf3QMcjBPjJwAznYRwZuIAf7yMAN5OCG8NtdBoppZGqc+cow2OV5nnr16mW7jC6PHOwjAzeQg31k4AZysI8M3EAObgi7l5NDqniJApKkeDyulStXNvpyeHQscrCPDNxADvaRgRvIwT4ycAM5uCEej8uYlTKGHFLBpBsRvoLBDeRgHxm4gRzsIwM3kIN9ZOAGcnADXxeWOibdAAAAAACkCZNuAAAAAADShEk3JIWdCIuLi+kIaRk52EcGbiAH+8jADeRgHxm4gRzcEHYvLxbTyNRwbyGSlUUzexeQg31k4AZysI8M3EAO9pGBG8jBFeSQKibdkBQ2pigvL6dBhWXkYB8ZuIEc7CMDN5CDfWTgBnJwQxAEMqZcEjmkgkk3AAAAAABpwqQbAAAAAIA0YdINAAAAAECaMOmGpLATYUlJCR0hLSMH+8jADeRgHxm4gRzsIwM3kIMbwu7lJWIamRruLUTq6upslwCRgwvIwA3kYB8ZuIEc7CMDN5CDK8ghVUy6ISnsRFhRUUFHSMvIwT4ycAM52EcGbiAH+8jADeTghrB7eYXoXp4aJt0AAAAAAKQJk24AAAAAANKESTciNKZwAznYRwZuIAf7yMAN5GAfGbiBHNzgeeSQqizbBcANsVhMpaWltsvo8sjBPjJwAznYRwZuIAf7yMAN5OCGWCwmzyOHVPEyBSRJxhht375dxhjbpXRp5GAfGbiBHOwjAzeQg31k4AZycIMxRsaQQ6qYdENS2Ilw/fr1dIS0jBzsIwM3kIN9ZOAGcrCPDNxADm4Iu5evF93LU8OkGwAAAACANGHSDQAAAABAmjDphiTJ8zxlZ2fL8zzbpXRp5GAfGbiBHOwjAzeQg31k4AZycIPnefK8bEnkkAq6l0NS+BUMQ4YMsV1Gl0cO9pGBG8jBPjJwAznYRwZuIAc3+L4vzyOHVHGlG5LCToTbtm2jE6Fl5GAfGbiBHOwjAzeQg31k4AZycEPYvZwcUsWkG5LCToSVlZV0hLSMHOwjAzeQg31k4AZysI8M3EAObgi7l1eK7uWpYdINAAAAAECaMOkGAAAAgM5gwajwB05h0g1JYSfC3NxcOkJaRg72kYEbyME+MnADOdhHBm4gBzeE3ctzRffy1NC9HJLCToSDBg2yXUaXRw72kYEbyME+MnADOdhHBm4gh+bNnRv+94wz0v+3wu7l5JAqrnRDUtgUoaqqiuYUlpGDfWTgBnKwjwzcQA72kYEbyMENYSO1KhlDDqlg0g1JYfv/qqoq2v9bRg72kYEbyME+MnADOdhHBm4gBzeEXxlWJYkcUsGkGwAAAACANGHSDQAAAABAmjDphqSwE2FeXh4dIS0jB/vIwA3kYB8ZuIEc7CMDN5CDnPg6sLB7eZ7oXp4aupdDUtiJsKioyHYZXR452EcGbiAH+8jADeRgHxm4gRzcEHYvJ4dUcaUbksJOhBs3bqQjpGXkYB8ZuIEc7CMDN5CDfWTghq6Yw9y5u78OzBVh9/KNdC9PEZNuSAo7EVZXV9MR0jJysI8M3EAO9pGBG8jBPjJwAzm4IexeXi26l6eGSTcAAAAAAGnCpBsAAAAAgDRh0g1JYSfCgoKCrt0R0gHkYB8ZuIEc7CMDN5CDfWTgBnJwQ9i9vEB0L08N3cshKexEWFBQYLuMLo8c7CMDN5CDfWTgBnKwjwzcQA5uCLuXk0OquNINSWEnwnXr1nWpjpAuIgf7yMAN5GAfGbiBHOwjAzeQgxvC7uXr6F6eIibdkBR2IqypqaEjpGXkYB8ZuIEc7CMDN5CDfWTgBnJwQ9i9vEZ0L08Nk24AAAAAANKESTcAAAAAAGnCpBuSwqYIhYWF8n12CZvIwT4ycAM52EcGbiAH+8jADeTghrCRWqGYRqaG7uWQFLb/z8/Pt11Gl0cO9pGBG8jBPjJwAznYRwZuIAc3hF8Zlm+7jIzDSxSQFHYiXLNmDR0hLSMH+8jADeRgHxm4gRzsIwM3kIMbwu7la+heniIm3ZAUdiKsra2lI6Rl5GAfGbiBHOwjAzeQg31k4AZycEPYvbxWdC9PDZNuAAAAAADShEk3AAAAAABpwqQbksJOhAMHDqQjpGXkYB8ZuIEc7CMDN5CDfWTgBnJwQ9i9fKCYRqaG7uWQFHYi7NWrl+0yujxysI8M3EAO9pGBG8jBPjJwAzm4IexeTg6p4iUKSJLi8bhWrlypeDxuu5QujRzsIwM3kIN9ZOAGcrCPDNxADm6Ix+MyZqWMIYdUMOlGhK9gcAM52EcGbiAH+8jADeRgHxm4gRzcwNeFpY5JNwAAAAAAacKkGwAAAACANGHSDUlhJ8Li4mI6QlpGDvaRgRvIwT4ycAM52EcGbiAHN4Tdy4vFNDI13FuIZGXRzN4F5GAfGbiBHOwjAzeQg31k4AZycAU5pIpJNySFjSnKy8tpUGEZOdhHBm4gB/vIwA3kYB8ZuIEc3BAEgYwpl0QOqbA66b711lt19NFHa5999lG/fv109tln68MPP0xa58svv9TUqVO17777qlevXjr33HO1adOmpHXWrl2riRMnqmfPnurXr5+uueYa1dXVJa3z4osv6qijjlJOTo6GDRumhx56qFE9s2fP1oEHHqju3btr9OjRev3111OuBQAAAACABKuT7kWLFmnq1Kl69dVX9fzzz2vXrl0aN26campqonWuvvpqzZ07V48//rgWLVqkDRs26Jxzzoluj8fjmjhxompra7V48WI9/PDDeuihhzRz5sxonYqKCk2cOFEnn3yyli9frquuuko//OEP9eyzz0brPProo5o+fbpuuOEGvfHGGzriiCM0fvx4bd68udW1AAAAAADQkNU35C9YsCDp3w899JD69eunZcuW6cQTT1R1dbX+9Kc/ac6cOTrllFMkSQ8++KCGDx+uV199Vccee6yee+45vffee/rHP/6h/v3768gjj9TNN9+sa6+9VjfeeKOys7N1//33q7i4WL/61a8kScOHD9fLL7+sO++8U+PHj5ck/frXv9Zll12myZMnS5Luv/9+zZs3Tw888IB++tOftqoWAAAAAAAacupT8NXV1ZKkvn37SpKWLVumXbt2aezYsdE6Bx98sA444AAtWbJExx57rJYsWaLDDjtM/fv3j9YZP368pkyZonfffVdf+9rXtGTJkqRtJNa56qqrJEm1tbVatmyZrrvuuuh23/c1duxYLVmypNW17Gnnzp3auXNn0rLa2lrF4/Ho357nyff9+s9HmBaXhx0DvWaXN9x2YrmkRp9/2XO5MUZDhgyR7/syxiStn6ilueWtrb2jx5QQi8UyZkyJHIwxisfjnWJMmZaTMUbDhg2T7/udZkwNl2fSmBLHgjGm04xpz9pdHpMklZSUSFKrnrcyYUyZmFPiWEjoDGNqa+22xuT7voYNGxY9N3eGMWViToljwfO8RjVm6phaWi7F6ve7+uUmJk9Gfv39sfu+kSRPkq/A1K/RaF8NJJnEYnnGk++ZpNrD//iSEmOKhSvXn5Mm7nupwblq/bCDlsZav63YHrUn1+gpaKL2RnkYX75a/3iY/pxa5sykOwgCXXXVVRozZowOPfRQSVJlZaWys7OVn5+ftG7//v1VWVkZrdNwwp24PXHb3tb57LPP9MUXX2jr1q2Kx+NNrvPBBx+0upY93XrrrZo1a1bSstNPP12jR4+O/p2Xl6eioiJt2rQpetFBkgoKClRQUKBPPvkk6e32hYWFys/P10cffaTa2tpo+cCBA9WrVy+tXr06aUcoLi5WVlaWysvLk+ooKSlRXV2dKioqJCk6sR0+fLhqamq0fv36aN3s7GwNGTJE1dXVSWPNzc3VoEGDtGXLFlVVVTk3Jik8OEpLSzNqTPF4XLFYTJ7ndZoxZVJOxhj1799fffr06TRjkjIvp+3bt0fHQlFRUacYUybm1LdvX23ZsqVTjSnTckqc2Pbu3VsHHHBApxhTpuVUUlKizz77TJs2bZLneZ1iTJmYU+JYOPjggxWPxzvFmFrKSSqVVKPy8voxxcco29uhIVLSmIyRPC9X0iBtMQeoKhgs1f+NxJikTTKmOrFYBeYAFXgfJ40p3E6hpPoxxceEK5eXR2Nas2aNpFpJMZWXeypWT2VpZ8tjio+Rr3g4ouZyMv1VGZRGtTebUzBMRZJDObXMM3u+rN2CdevWyfM8DRw4UJL0+uuva86cORoxYoQuv/zyVDaVZMqUKXrmmWf08ssvR9ueM2eOJk+e3Ohq8THHHKOTTz5Zt912my6//HJ9/PHHSZ/P3rFjh3JzczV//nxNmDBBpaWlmjx5ctKV7Pnz52vixInasWOHtm7dqv3331+LFy9WWVlZtM6MGTO0aNEivfbaa62qZU9NXel+4okn9L3vfS/6tyuvqMXjca1atUoHHXRQ9Hf3rCVTXyXMpFc+d+3apVWrVmnYsGGKxWKdYkyZllM8Htfq1atVWlqqPWXqmBouz5Sc6urqomOhW7dunWJMmZZTEARavXq1hg4dmnRSkcljysScEs/PJSUl6tatW6cYU1trt3kVa+XKlRo6dKhisVinGFMm5pQ4FkpLSxWLxTrFmFpaPn9+OKaJE+uXP3dceKV7wutJY5o3T5I8nXmmr+CZo8Mr3eMWJ9X+1FPhle6JE+vH9Nyx4ZXuca9HtYfb8XXmmfVjerZ+XjRucTSm2tpaPfPMKknDdPrpMfnPhRcTg3Gv7X1Mzx0nSYpNeK35nJ45OrzSvUftjfJ4rkz+hNedyemxxx7TRRddpL1J+Ur3d77zHV1++eX6/ve/r8rKSn3jG9/QIYccokceeUSVlZVJDcxaa9q0aXr66af10ksvRRNuKXxVora2Vtu2bUu6wrxp0yYVFhZG6+zZZTzRUbzhOnt2Gd+0aZN69+6tHj16KBaLKRaLNblOw220VMuecnJylJOTk7QsOzs7esBuqLlXSVJd3tS2W7s8sU3P85pcv7nl7VV7OsaUkElj8n0/2if3tn4mjam1y10ZU+JKRmca095qTHV5R4yp4bGQyCPTx5TKctfG1B73gWtjao/lHTUm3/ejGjrLmL5KjR09png8HtW+522ZOiYpM3NKTJJSrd3lMbW0PKl2L97k8vqnybAWz0iKS432Vb/+byQWmEa1J23H93f/vUbnpL48r/548Fo5pmZqT67RKNZE7Y3uXy9oenlz67ewvD1yaknrroc38M477+iYY46RFM7qDz30UC1evFiPPPJIk1/DtTfGGE2bNk1PPPGEXnjhBRUXFyfdPnLkSHXr1k0LFy6Mln344Ydau3ZtdEW6rKxMK1asSOoy/vzzz6t3794aMWJEtE7DbSTWSWwjOztbI0eOTFonCAItXLgwWqc1tQAAAAAA0FDKV7p37doVXb39xz/+oTPPPFNS2FRs48aNKW1r6tSpmjNnjv7+979rn332iT6XkJeXpx49eigvL0+XXnqppk+frr59+6p379760Y9+pLKysqhx2bhx4zRixAh9//vf1+23367Kykpdf/31mjp1alTnFVdcoXvuuUczZszQJZdcohdeeEGPPfaY5oXvoZAkTZ8+XZMmTdKoUaN0zDHH6K677lJNTU3Uzbw1tWS65l79QcciB/vIwA3kYB8ZuIEc7CMDN5CDGxJXzdF6KU+6DznkEN1///2aOHGinn/+ed18882SpA0bNmjfffdNaVv33XefJOmkk05KWv7ggw/q4osvliTdeeed8n1f5557rnbu3Knx48fr3nvvjdaNxWJ6+umnNWXKFJWVlSk3N1eTJk3STTfdFK1TXFysefPm6eqrr9bdd9+tgQMH6o9//GP0dWGSdMEFF+jTTz/VzJkzVVlZqSOPPFILFixIaq7WUi2ZLBaLNfkZVnQscrCPDNxADvaRgRvIwT4ycAM5uCH82Bc5pCrlSfdtt92mb33rW7rjjjs0adIkHXHEEZKkp556KnrbeWu1podb9+7dNXv2bM2ePbvZdQYPHqz58+fvdTsnnXSS3nzzzb2uM23aNE2bNu0r1ZKpjDGqqalRbm5u9PlJdDxysI8M3EAO9pGBG8jBPjJwAzm4IfzGoxpJuYo+0I0WpfzegJNOOklVVVWqqqrSAw88EC2//PLL9bvf/a5di0PHCYJA69evb7JjJzoOOdhHBm4gB/vIwA3kYB8ZuIEc3BB2AF8viRxSkfKk+5RTTtHnn3+uPn36JC3v27evLrjggnYrDAAAAACATJfypPvFF19M+lLxhC+//FL/+te/2qUoAAAAAAA6g1Z/pvvtt9+O/v+9996LOo1L4fcXLliwQPvvv3/7VocO43mesrOz+YyMZeRgHxm4gRzsIwM3kIN9ZOAGcnBD+D3p2eLz3Klp9aT7yCOPjL6M/pRTTml0e48ePfTb3/62XYtDx/F9X0OGDLFdRpdHDvaRgRvIwT4ycAM52EcGbiAHN/i+L88jh1S1etJdUVEhY4yGDBmi119/Xfvtt190W3Z2tvr166dYLJaWIpF+xhhVV1crLy+PVxAtIgf7yMAN5GAfGbiBHOwjAzeQgxvC7uXVkvLE1e7Wa/Wke/DgwZJEx8BOKggCVVZWap999uHFE4vIwT4ycAM52EcGbiAH+8jADeTghrB7eaU8bx9J5NBaKX9PtySVl5frn//8pzZv3txoEj5z5sx2KQwAAAAAgEyX8qT7D3/4g6ZMmaKCggIVFhYmvb3D8zwm3QAAAAAA1Et50n3LLbfo5z//ua699tp01ANLPM9Tbm4un5GxjBzsIwM3kIN9ZOAGcrCPDNxADm4IG2vnis9zpyblSffWrVt1/vnnp6MWWOT7vgYNGmS7jC6PHOwjAzeQg31k4AZysI8M3EAObgi7l5NDqvxUf+H888/Xc889l45aYFEQBKqqqqJRnmXkYB8ZuIEc7CMDN5CDfWTgBnJwQ9hIrUrGkEMqUr7SPWzYMP3nf/6nXn31VR122GHq1q1b0u3/5//8n3YrDh3HGKOqqir16dPHdildGjnYRwZuIAf7yMAN5GAfGbiBHNwQfmVYlTxv7znMnRv+94wzOqCoDJDypPv3v/+9evXqpUWLFmnRokVJt3mex6QbAAAAAIB6KU+6Kyoq0lEHAAAAAACdTsqf6Ubn5Hme8vLy6AhpGTnYRwZuIAf7yMAN5GAfGbiBHNwQdi/PE93LU5Pyle5LLrlkr7c/8MADbS4G9vi+r6KiIttldHnkYB8ZuIEc7CMDN5CDfWTgBnJwQ9i9nBxSlfKV7q1btyb9bN68WS+88IL+9re/adu2bWkoER0hCAJt3LiRjpCWkYN9ZOAGcrCPDNxADvaRgRvIwQ1h9/KNdC9PUcpXup944olGy4Ig0JQpUzR06NB2KQodzxij6upq9evXz3YpXRo52EcGbiAH+8jADeRgHxm4gRzcEHYvr5bnkUMq2uUz3b7va/r06brzzjvbY3MAAAAAAHQK7dZIbfXq1aqrq2uvzQEAAAAAkPFSfnv59OnTk/5tjNHGjRs1b948TZo0qd0KQ8fyPE8FBQV0hLSMHOwjAzeQg31k4AZysI8M3EAObgi7lxeI7uWpSXnS/eabbyb92/d97bfffvrVr37VYmdzuMv3fRUUFNguo8sjB/vIwA3kYB8ZuIEc7CMDN5CDG8Lu5eSQqpQn3f/85z/TUQcsC4JAn3zyifbff3/5Pl/fbgs52EcGbiAH+8jADeRgHxm4gRzcEHYv/0TS/mrHTyp3eilPuhM+/fRTffjhh5Kkgw46SPvtt1+7FYWOZ4xRTU2NjDG2S+nSyME+MnADOdhHBm4gB/vIwA3k4Iawe3mNPI8cUpHyyxM1NTW65JJLVFRUpBNPPFEnnniiBgwYoEsvvVQ7duxIR40AAAAAAGSklCfd06dP16JFizR37lxt27ZN27Zt09///nctWrRIP/7xj9NRIwAAAAAAGSnlt5f/v//3//TXv/5VJ510UrTsm9/8pnr06KFvf/vbuu+++9qzPnQQ3/dVWFjIZ2QsIwf7yMAN5GAfGbiBHOwjAzeQgxvCRmqF4vPcqUl50r1jxw7179+/0fJ+/frx9vIM5nme8vPzbZfR5ZGDfWTgBnKwjwzcQA72kYEbyMEN4VeG5dsuI+Ok/BJFWVmZbrjhBn355ZfRsi+++EKzZs1SWVlZuxaHjhMEgdasWaMgCGyX0qWRg31k4AZysI8M3EAO9pGBGzo8hwWjwh8kCbuXr5ExHA+pSPlK9913363x48dr4MCBOuKIIyRJb731lrp3765nn3223QtExzDGqLa2lo6QlpGDfWTgBnKwjwzcQA72kYEbyMENYffyWrqXpyjlSfehhx6q8vJyPfLII/rggw8kSRdddJG++93vqkePHu1eIAAAAACk09y54X/POMNuHeic2vQ93T179tRll13W3rUAAAAAANCppPyZ7ltvvVUPPPBAo+UPPPCAbrvttnYpCh3P930NHDiQjpCWkYN9ZOAGcrCPDNxADvaRgRvIwQ1h9/KBont5alK+t373u9/p4IMPbrT8kEMO0f33398uRaHjeZ6nXr16yfM826V0aeRgHxm4gRzsIwM3kIN9ZOAGcnBD2L2cHFKV8qS7srJSRUVFjZbvt99+2rhxY7sUhY4Xj8e1cuVKxeNx26V0aeRgHxm4gRzsIwM3kIN9ZOAGcnBDPB6XMStlDDmkIuVJ96BBg/TKK680Wv7KK69owIAB7VIU7OCrMNxADvaRgRvIwT4ycAM52EcGDnjuOAUreVetC/i6sNSl3Ejtsssu01VXXaVdu3bplFNOkSQtXLhQM2bM0I9//ON2LxAAAAAAgEyV8qT7mmuu0b///W/9f//f/6fa2lpJUvfu3XXttdfquuuua/cCAQAAAHQtfIUXOpOUJ92e5+m2227Tf/7nf+r9999Xjx49VFJSopycnHTUhw7i+76Ki4vpCGkZOdhHBm4gB/vIwA3kYB8ZuMFXXMWxpZ03hwWjwv+ettRuHS0Iu5cXi+7lqWnT93RLUq9evXT00Ue3Zy2wLCurzbsD2hE52EcGbiAH+8jADeRgHxm4IUs7bZcASV9hCtll8RIFJIUNQsrLy2kUYhk52EcGbiAH+8jADeRgHxm0v8Rbx1MRKKby+JhOk8PcuW27H2wLgkDGlEvqHDl0FCbdAAAAAL6yTJ1IAunGpBsAAABA+1swavdnlTvj3wNaKeVJ90svvaS6urpGy+vq6vTSSy+1S1EAAAAAAHQGKU+6Tz75ZG3ZsqXR8urqap188sntUhQ6nu/7Kikp6bwdITMEOdhHBm4gB/vIwA3kYB8ZpFkrr077iqsk9kpSDrydveOF3ctLxBumU5PyvWWMked5jZb/+9//Vm5ubrsUBTuaegcDOh452EcGbiAH+8jADeRgHxm4oU58RbEbOB5S1ep+7+ecc46k8Hu6L7744qTv5Y7H43r77bd13HHHtX+F6BBBEKiiokIlJSWKxWK2y+myyME+MnADOdhHBm4gB/vIwA2BYqqIj1JJEJCDRWH38or6q93k0FqtnnTn5eVJCq9077PPPurRo0d0W3Z2to499lhddtll7V8hAAAAAAAZqtWT7gcffFCSdOCBB+onP/kJbyUHAAAAAKAFrZ50J9xwww3pqAMOoEGIG8jBPjJwAznYRwZuIAf7yMANvuK2S4Akz+N4SFXK99imTZv0/e9/XwMGDFBWVpZisVjSDzJTLBZTaWkpGVpGDvaRgRvIwT4ycAM52EcGboh5cZVmvUIOlsViMXleqTyPHFKR8pXuiy++WGvXrtV//ud/qqioqMlO5sg8xhjV1NQoNzeXTC0iB/vIwA3kYB8ZuIEc7CMDNxgj1aiPcpv5JiVnJb4O7bSldutoJ8YYGVMjKVdSBuVgWcqT7pdffln/+te/dOSRR6ahHNgSBIHWr19PZ07LyME+MnADOdhHBm4gB/vIwA2BYlofP8yt7uWdbELdGmH38vV0L09Rym8vHzRokIwx6agFAAAAQCZITDgBtCjlSfddd92ln/70p/roo4/SUA4AAAAA18ydG/50Za29D7ivsKeU315+wQUXaMeOHRo6dKh69uypbt26Jd2+ZcuWdisOHcfzPGVnZ2fWZ2Q6IXKwjwzcQA72kYEbyME+MnCDJ6Nsbwc5WOZ5njwvW3yeOzUpT7rvuuuuNJQB23zf15AhQ2yX0eWRg31k4AZysI8M3EAO9pGBG3wv0JDYUomvb7PK9315HsdDqlKedE+aNCkddcAyY4yqq6uVl5fHK4gWkYN9ZOAGcrCPDNxADvaRgRuM8VRt+isv07qXdzJh9/JqSXnianfrtemlotWrV+v666/XRRddpM2bN0uSnnnmGb377rvtWhw6ThAEqqysVBAEtkvp0sjBPjJwAznYRwZuIAf7yMANgXxVBqXkYFnYvbxSEjmkIuVJ96JFi3TYYYfptdde09/+9jdt375dkvTWW2/phhtuaPcCAQAAAHSQBaPoTA60s5Qn3T/96U91yy236Pnnn1d2dna0/JRTTtGrr77arsUBAAAASC86bQPplfKke8WKFfrWt77VaHm/fv1UVVWV0rZeeuklnXHGGRowYIA8z9OTTz6ZdPvFF19c3yFv989pp52WtM6WLVv03e9+V71791Z+fr4uvfTS6Op7wttvv60TTjhB3bt316BBg3T77bc3quXxxx/XwQcfrO7du+uwww7T/Pnzk243xmjmzJkqKipSjx49NHbsWJWXl6c0Xpd5nqfc3Fw+I2MZOdhHBm4gB/vIwA3kYB8ZuMGTUa63lRwsC+dkueLz3KlJedKdn5+vjRs3Nlr+5ptvav/9909pWzU1NTriiCM0e/bsZtc57bTTtHHjxujnv//7v5Nu/+53v6t3331Xzz//vJ5++mm99NJLuvzyy6PbP/vsM40bN06DBw/WsmXLdMcdd+jGG2/U73//+2idxYsX66KLLtKll16qN998U2effbbOPvtsvfPOO9E6t99+u37zm9/o/vvv12uvvabc3FyNHz9eX375ZUpjdpXv+xo0aJB8OkJaRQ72kYEbyME+MnADOdhHBm7wvUCDYivIwbKwe/kgeR45pCLle+vCCy/Utddeq8rKSnmepyAI9Morr+gnP/mJfvCDH6S0rQkTJuiWW25p8sp5Qk5OjgoLC6OfPn36RLe9//77WrBggf74xz9q9OjROv744/Xb3/5W//M//6MNGzZIkh555BHV1tbqgQce0CGHHKILL7xQ/+f//B/9+te/jrZz991367TTTtM111yj4cOH6+abb9ZRRx2le+65R1J4lfuuu+7S9ddfr7POOkuHH364/vznP2vDhg2Nrs5nqiAIVFVVRXMKy8jBPjJwAznYRwZuIAf7yMANgfFUFQwmB8vCRmpVMoYcUpHyV4b94he/0NSpUzVo0CDF43GNGDFC8Xhc3/nOd3T99de3e4Evvvii+vXrpz59+uiUU07RLbfcon333VeStGTJEuXn52vUqN3NHsaOHSvf9/Xaa6/pW9/6lpYsWaITTzwx6fPn48eP12233aatW7eqT58+WrJkiaZPn570d8ePHx9NqCsqKlRZWamxY8dGt+fl5Wn06NFasmSJLrzwwiZr37lzp3bu3Jm0rLa2VvF4PPq353nyfb9+BzYtLg9fXfKaXd5w24nlkho9QO25PB6Pa/PmzerTp4+MMUnrJ2ppbnlra+/oMSXEYrGMGVNdXZ02b96s3r17KxaLdYoxZVpO8Xhcn376qfr06dNpxtRweaaMqeGx0K1bt04xpkzLKTHRyMvL6zRjysScEs/PeXl5nWZMba3d1pgk6dNPP42emzvDmPbMyRgpCBJj8hTIl+r/xu6xBpJMYrE848uXkmoM/+NJSowpvL8UjzcaU2I7vpE8T43GZIxf/6v156qmmzbHD1R+EDTYTrT5+jFJgWJN1N5yTnurvbn7wDeePM80ysmYBjntcR8k8mhYu+/70h611ydVf1/V125i8mTkS43yi2o39Wu0mJ8nf4/aw//4krxm86urq5MxmyX1Vjwek18/jqCF/BL3Q2yP2pNrbHrfa3TcNLHv7W39jniMaEnKk+7s7Gz94Q9/0MyZM7VixQpt375dX/va11RSUpLyH2/JaaedpnPOOUfFxcVavXq1fvazn2nChAlasmSJYrGYKisr1a9fv6TfycrKUt++fVVZWSlJqqysVHFxcdI6/fv3j27r06ePKisro2UN12m4jYa/19Q6Tbn11ls1a9aspGWnn366Ro8eHf07Ly9PRUVF2rRpk6qrq6PlBQUFKigo0CeffKKamppoeWFhofLz8/XRRx+ptrY2Wj5w4ED16tVLq1evTtoRiouLlZWV1ejz5yUlJaqrq1NFRYWkcOfZunWrpPBt/+vXr4/Wzc7O1pAhQ1RdXZ003tzcXA0aNEhbtmxJ+jy/K2OSwoOjtLQ0Y8a0atUqbdmyRatWrZLv+51iTJmWU2LCJ6nTjEnKvJw+//zz6FgYMGBApxhTpuW0zz77SJI2b96szz//vFOMKRNzCoJAW7Zs0YYNGzR48OBOMaZMy2no0KHatWtX9NzcGca0Z07GSB99VD8m01+VQalUv63EmKQtMqYqsVh5wTAVSUljMkbyvAJJ9WOKjwlXLi9PGpMxtdF2BqqPemlrozFJxZJ2jymIH6ctZlD0YlRFRUU0cV29un5M6qP18cOi2lPJKaw9T1J9Tg1qT+QkfSJjaqLaC01/5XuVjXKSBkqqz6nBdhrmlKi9vLw+J/VURXxUVHu4r5VKqlF5ef3xFB+jbG+HhkhJYwprz5U0SFvMAaoKBkfbSex70iYZUx3VXmAOUIH3cdK+F26nUFL9vteg9sS+F+5LWyStUnm5r2L1VJZ2NtHrqkRSncrLK6LafcXDETX3GNHMvtfoeGpi35PsHU+t4ZmG0/1WuOmmm/STn/xEPXv2TFr+xRdf6I477tDMmTNT2dzuQjxPTzzxhM4+++xm11mzZo2GDh2qf/zjHzr11FP1i1/8Qg8//LA+/PDDpPX69eunWbNmacqUKRo3bpyKi4v1u9/9Lrr9vffe0yGHHKL33ntPw4cPV3Z2th5++GFddNFF0Tr33nuvZs2apU2bNmnx4sUaM2aMNmzYUL/Thr797W/L8zw9+uijTdbb1JXuJ554Qt/73veSxu3CK5/xeFyrVq3SQQcdFP3dPWvpLK/mujymxJP6sGHDuNJtaUzxeFyrV69WaWmp9pSpY2q4PFNyqquri44FrnTbu9K9evVqDR06NOmkIpPHlIk5JZ6fS0pK1K1bt04xprbWbvMq1sqVKzV06NBOe6V73jzp9NPrx/TM0eHVxnGLk2p86qnwSunEifW1P1cmf8LrSTXOmydJns48s35Mz5aFK49bnDSmp5/evR3/udHhle5vvJZU47x5Ye0TJ9afqz57glbFy1Q64TbFYjEFQVD/96SJE+vH9Myo8GrxHrW3Jqe91d7cfeA/d2x4pXvc60k5zZsXjvWb34xLzx2XdB8k8mhYu+/70oKjk2qXpPnzw5wS94GeOy680j3h9Ub5RbU/c3R4pbvF/I4Nr3Q3qD3cjq8zz/Saza+2tlbPPLNK0jCdfnpM/nPhxcRg3N7zS9wPsQmvNf8Y0cy+1+i4aWLf29v66T6eHnvssaR5ZFNSvtI9a9YsXXHFFY0m3Tt27NCsWbPaPOlujSFDhqigoECrVq3SqaeeqsLCQm3evDlpnbq6Om3ZskWFhYWSwlc2Nm3alLRO4t8trdPw9sSyhpPuTZs26cgjj2y23pycHOXk5CQty87Ojh6wG2ruVZJUlze17dYs9zxPffr0keeFXeKbWr+55e1Ve3uPqaFMGVNWVpb69OmjrKyspN/N5DFlWk6e5yk/Pz964G5t7c0td2FMLdWY6vKOGFPDY8HzvL2unyljSmW5C2PyPE95eXlJLwC2pnaXx9TeyztiTInn58Q6nWFMX7XGjh5TEATKz89v9NwsZe6YpOTaPU9K/CnPM4opLu3xO4nGWdFiL2hUo9egobXv+5IXV/IvJSY6DbfTdI3eHss9r059/I3RRCk8PpI373lqpvaWc2pN7Y3vA9NoO41qb2I7TdWu1tTuxZtcnlS7Z6RW5de49tbcB+Hzch9JWYrF/Fbn11ztyb/T9L7X6DhoYt/b6/otLG+P46klrbse3oAxJjoBauitt95S3759Uy4gFevXr9e///3vaOJbVlambdu2admyZdE6L7zwgoIgiN7CXVZWppdeekm7du2K1nn++ed10EEHRU3ZysrKtHDhwqS/9fzzz6usLHx1p7i4WIWFhUnrfPbZZ3rttdeidTKd7/sqKipqdmdExyAH+8jADeRgHxm4gRzs61QZLBgV/mQg3wtUFFvZOXLIYOGLHkWie3lqWn1v9enTR3379pXneSotLVXfvn2jn7y8PH3jG9/Qt7/97ZT++Pbt27V8+XItX75cUtiwbPny5Vq7dq22b9+ua665Rq+++qo++ugjLVy4UGeddZaGDRum8ePHS5KGDx+u0047TZdddplef/11vfLKK5o2bZouvPBCDRgwQJL0ne98R9nZ2br00kv17rvv6tFHH9Xdd9+d1Djtyiuv1IIFC/SrX/1KH3zwgW688UYtXbpU06ZNkxS+GnPVVVfplltu0VNPPaUVK1boBz/4gQYMGLDXt8NnkiAItHHjxibfUoWOQw72kYEbyME+MnADOdiXyRnMnRv+dAaB8bUxXpqROXQm4Vu0N4ru5alp9dvL77rrLhljdMkll2jWrFnKy8uLbsvOztaBBx6Y8lXfpUuX6uSTT47+nZgIT5o0Sffdd5/efvttPfzww9q2bZsGDBigcePG6eabb056y/YjjzyiadOm6dRTT5Xv+zr33HP1m9/8Jro9Ly9Pzz33nKZOnaqRI0eqoKBAM2fOTPou7+OOO05z5szR9ddfr5/97GcqKSnRk08+qUMPPTRaZ8aMGaqpqdHll1+ubdu26fjjj9eCBQvUvXv3lMbsKmOMqqurGzWmQ8ciB/vIwA3kYB8ZuIEc7CMDNxh5qjaF6pdaOyq0M2OMjKmW53E8pKLVk+5JkyZJCt9qfdxxx6lbt25f+Y+fdNJJSR9m39Ozzz7b4jb69u2rOXPm7HWdww8/XP/617/2us7555+v888/v9nbPc/TTTfdpJtuuqnFmgAAAAAAkNrQSO3rX/969P9ffvnlHu3xpd69e3/1qgAAAAAA6ARS/gT8jh07NG3aNPXr10+5ubnq06dP0g8yk+d5KigoaLJJHjoOOdhHBm4gB/vIwA3kYB8ZuMFToAL/46+eQwY3k3NB+E1HBYralqNVUp50X3PNNXrhhRd03333KScnR3/84x81a9YsDRgwQH/+85/TUSM6gO/7KigooCOkZeRgHxm4gRzsIwM3kIN9ZOAG3zMq8D9uUw6dpZmcC8Lu5QV0L09RyvfW3Llzde+99+rcc89VVlaWTjjhBF1//fX6xS9+oUceeSQdNaIDBEGgdevW0RHSMnKwjwzcQA72kYEbyME+MnBDYHytix9GDpaF3cvX0b08RSlPurds2aIhQ4ZICj+/vWXLFknS8ccfr5deeql9q0OHMcaopqZmr43tkH7kYB8ZuIEc7CMDN5CDfWTgBiNPNaYPOVgWdi+vkUQOqUh50j1kyBBVVFRIkg4++GA99thjksIr4Pn5+e1aHAAAAAAAmSzlSffkyZP11ltvSZJ++tOfavbs2erevbuuvvpqXXPNNe1eIAAAAAAAmSrlrwy7+uqro/8fO3asPvjgAy1btkzDhg3T4Ycf3q7FoeP4vq/CwkKahFhGDvaRgRvIwT4ycAM52EcGbvAVqNBfSQ6WhY3UCtWGa7ddWqsn3UEQ6I477tBTTz2l2tpanXrqqbrhhhs0ePBgDR48OJ01ogN4nsfHAxxADvaRgRvIwT4ycAM52EcGbvA8o3yvUuKr26wKvzIs33YZGafVL1H8/Oc/189+9jP16tVL+++/v+6++25NnTo1nbWhAwVBoDVr1tAR0jJysI8M3EAO9pGBG8jBPjJwQ2B8rYmPIgfLwu7la+henqJWT7r//Oc/695779Wzzz6rJ598UnPnztUjjzzCjt9JGGNUW1tLR0jLyME+MnADOdhHBm4gB/vIwA1GnmpNT3KwLOxeXiu6l6em1ZPutWvX6pvf/Gb077Fjx8rzPG3YsCEthQEAAAAAkOlaPemuq6tT9+7dk5Z169ZNu3btaveiAAAAAADoDFrdSM0Yo4svvlg5OTnRsi+//FJXXHGFcnNzo2V/+9vf2rdCdAjf9zVw4EA6QlpGDvaRgRvIwT4ycAM52EcGbvAV18DYCnKwLOxePlB0L09NqyfdkyZNarTse9/7XrsWA3s8z1OvXr1sl9HlkYN9ZOAGcrCPDNxADvaRgRs8T+qlrXQvtyzsXs7xkKpWT7offPDBdNYBy+LxuFavXq2hQ4cqFovZLqfLIgf7yMAN5GAfGbiBHOwjAzfETUyr48dqaDxODhbF43EZs1rSUEnk0Fq8LwAROtG7gRzsIwM3kIN9ZOAGcrCPDNwQMMlzAl8Xljom3QAAAAAApAmTbgAAAAAA0oRJNySFnQiLi4vpCGkZOdhHBm4gB/vIwA3kYB8ZuMFXXMWxpeRgWdi9vFhMI1PDvYVIVlar++ohjcjBPjJwAznYRwZuIAf7yMANWdppuwRISqEXN+ox6YaksEFIeXk5jUIsIwf7yMAN5GAfGbiBHOwjAzcEiqk8PoYcLAuCQMaUSyKHVDDpBgAAAAAgTZh0AwAAAACQJky6AQAAAABIEybdkBR2IiwpKaEjpGXkYB8ZuIEc7CMDN5CDfWTgBl9xlcReIQfLwu7lJWIamRruLUTq6upslwCRgwvIwA3kYB8ZuIEc7CMDN9Qpx3YJkCSlcDyMGhX+dHFMuiEp7ERYUVFBR0jLyME+MnADOdhHBm4gB/vIwA2BYqqIjyIHy8Lu5RWie3lqmHQDAAAAAJAmTLoBAAAAAEgTJt2I0JjCDeRgHxm4gRzsIwM3kIN9ZOAGX3HbJUCS59UfD3xWu9WybBcAN8RiMZWWltouo8sjB/vIwA3kYB8ZuIEc7CMDN8S8uEqzXpFiMduldGmxWEyex/GQKl62gyTJGKPt27fLGGO7lC6NHOwjAzeQg31k4AZysI8M3GCMtN30IQfLjDEyhuMhVUy6ISnsRLh+/Xo6QlpGDvaRgRvIwT4ycAM52EcGbggU0/r4YeRgWdi9fL3oXp4aJt0AAAAAAKQJk24AAAAAANKESTckSZ7nKTs7W57n2S6lSyMH+8jADeRgHxm4gRzsIwM3eDLK9naQg2We58nzsiWRQyroXg5J4VdhDBkyxHYZXR452EcGbiAH+8jADeRgHxm4wfcCDYktlfj6Nqt835fncTykir0WksJOhNu2baMToWXkYB8ZuIEc7CMDN5CDfWTgBmM8bQsKycGysHs5x0OqmHRDUtiJsLKyko6QlpGDfWTgBnKwjwzcQA72kYEbAvmqDErJwbKwe3ml6F6eGibdAAAAAACkCZNuAAAAAADShEk3JIWdCHNzc+kIaRk52EcGbiAH+8jADeRgHxm4wZNRrreVHCwLu5fniu7lqaF7OSSFnQgHDRpku4wujxzsIwM3kIN9ZOAGcrCPDNzge4EGxVbQvdyysHs5x0Oq2GshKWyKUFVVRXMKy8jBPjJwAznYRwZuIAf7yMANgfFUFQwmB8vCRmpVMoYcUsGkG5LC9v9VVVW0/7eMHOwjAzeQg31k4AZysI8M3GDkqyoYTA6WhV8ZViWJHFLBpBsAAAAAEBo1KvxBu2HSDQAAAABAmjDphqSwE2FeXh4dIS0jB/vIwA3kYB8ZuIEc7MuYDBZ07iuTnozyvEr3c+jkwu7leWrX7uVd4Mo63cshKexEWFRUZLuMLo8c7CMDN5CDfWTgBnKwz9UM5s4N/3vGGXbr6Ci+F6gotpLu5ZaF3cvdOx5cx14LSWEnwo0bN9IR0jJysI8M3EAO9pGBG8jBPjJwQ2B8bYyXkoNlYffyjXQvTxGTbkgKOxFWV1fTEdIycrCPDNxADvaRgRvIwT4ycIORp2pTSA6Whd3Lq0X38tQw6QYAAAAcMXfu7reOSwo/q93JP68NdHZMugEAAAAASBMm3ZAUdiIsKCigI6Rl5GAfGbiBHOwjAzeQg31k4AZPgQr8j8nBsrB7eYHatXt5F0D3ckgKOxEWFBTYLqPLIwf7yMAN5GAfGbiBHOwjAzf4nlGB9zHdyy0Lu5dzPKSKvRaSwk6E69atoyOkZeRgHxm4gRzsIwM3kIN9ZOCGwPhaFz+MHCwLu5evo3t5iph0Q1LYibCmpoaOkJaRg31k4AZysI8M3EAO9pGBG4w81Zg+5GBZ2L28RnQvTw2TbgAAAAAA0oRJNwAAAAAAacKkG5LCpgiFhYXyaU5hFTnYRwZuIAf7yMAN5GAfGbjBV6BCfyU5WBY2UisU08jU0L0cksL2//n5+bbL6PLIwT4ycAM52EcGbiAH+8jADZ5nlO9VSnxlmFXhV4bl2y4j4/ASBSSFnQjXrFlDR0jLyME+MnADOdhHBm4gB/vIwA2B8bUmPoocLAu7l6+he3mKrE66X3rpJZ1xxhkaMGCAPM/Tk08+mXS7MUYzZ85UUVGRevToobFjx6q8vDxpnS1btui73/2uevfurfz8fF166aXavn170jpvv/22TjjhBHXv3l2DBg3S7bff3qiWxx9/XAcffLC6d++uww47TPPnz0+5lkxmjFFtbS0dIS0jB/vIwA3kYB8ZuIEc7GtzBgtGpaegLsrIU63pybHwVY0aFf60Udi9vFZ0L0+N1Ul3TU2NjjjiCM2ePbvJ22+//Xb95je/0f3336/XXntNubm5Gj9+vL788stone9+97t699139fzzz+vpp5/WSy+9pMsvvzy6/bPPPtO4ceM0ePBgLVu2THfccYduvPFG/f73v4/WWbx4sS666CJdeumlevPNN3X22Wfr7LPP1jvvvJNSLQAAAOia5s4Nf1JaZ8EoJudAF2D1M90TJkzQhAkTmrzNGKO77rpL119/vc466yxJ0p///Gf1799fTz75pC688EK9//77WrBggf73f/9Xo+pfsfntb3+rb37zm/qv//ovDRgwQI888ohqa2v1wAMPKDs7W4cccoiWL1+uX//619Hk/O6779Zpp52ma665RpJ088036/nnn9c999yj+++/v1W1NGXnzp3auXNn0rLa2lrF4/Ho357nyff9+rdqmBaXh80LvGaXN9x2YrmkRm/F2XN5PB6P/t8Yk7R+opbmlre29o4eU0IsFsuYMSVySNzeGcaUaTnF4/Gk/+8MY2q4PFPG1PBY6CxjyrScEuvsue1MHlMm5pQ4FoIgUCwW6xRjamvttsYkhedGTZ2/NRxT+Kc9SYkaY1L97+xeP5BkEovlGU++Z5JqD//jS/J2b0eSGjwehs9V0eKwdiMFe4zVmMT5Rf2Y6rcVkxrVHgSJGj0F8ltRuy9faqL2Pe6DPWpPrJ/Yjm/Cj2nvmdOetcdNTIHx6q+0Ju6z3fdBuO9JgZq6303SfeDJpFR7c/eBbzx5e+SXqD3a9/a4DxT93Sbya1C76pNqrvZm9z1Tv0Zz+cVi9fkFe9n3pKB+X9gzvzCnQMbEFY/F5Jvw7zS779X/vcSF8T33PUnyfF9+EDS77zV6LGhi39vb+h3xGNESZxupVVRUqLKyUmPHjo2W5eXlafTo0VqyZIkuvPBCLVmyRPn5+dGEW5LGjh0r3/f12muv6Vvf+paWLFmiE088UdnZ2dE648eP12233aatW7eqT58+WrJkiaZPn57098ePHx+93b01tTTl1ltv1axZs5KWnX766Ro9enTSdoqKirRp0yZVV1dHywsKClRQUKBPPvlENTU10fLCwkLl5+fro48+Um1tbbR84MCB6tWrl1avXp20IxQXFysrK6vRW+FLSkpUV1eniooKSbt3ft/3VVNTo/Xr10frZmdna8iQIaqurlZlZWW0PDc3V4MGDdKWLVtUVVXl3Jik8OAoLS3NmDGtXr1adXV1Wr16tTzP6xRjyrScjDHad9995fu+ysvLO8WYpMzLafv27dGxUFRU1CnGlIk5DRw4UFVVVZ1qTJmWkzFGdXV12rhxow444IBOMaZMy6mkpET77rtv9Nzc3JiMkTwvV1L9mOJjpPq/kRiTtEnGVCcWq8AcoALv46QxhdsplFQ/pviYcOXy8qQxJT5TW15ePybFmvjoY4mkOpWX148pPka+4iqVknIyRvroo/oxmf6qDEqj2hM5SVtkTFVUe14wTEVSUk5h7QWS6nNqUHvDnIypjbYzUH3US1sb5SQVS9qdk4kfqzp1lxRexKqoqIgmrqtX1+976qP18cOi2hM5SdUqL6+M7oNcb6sGSUn7Xlh7nqT6fa9B7Yl9T/pExtREtRea/sr3Khvte9JASfX7XoPtNNz3ErWXl9fve+qpivioqPZwglcqqUbl5euj2rO9HRoiNb/vmQNUFQxuft8bE9ZTYD7ey74nfXTUUaqN94yKTOx7H330kaQ6SatVPmaMirVUWdrZ/L5X//cUV5P7niRlH3WUhixd2uy+1+gxool9T7L3GNEannHkgxGe5+mJJ57Q2WefLSl8y/eYMWO0YcOG+h0l9O1vf1ue5+nRRx/VL37xCz388MP68MMPk7bVr18/zZo1S1OmTNG4ceNUXFys3/3ud9Ht7733ng455BC99957Gj58uLKzs/Xwww/roosuita59957NWvWLG3atKlVtTSlqSvdTzzxhL73ve8ljdulV3M74yvUjIkxMSbGxJgYE2NiTOke07x5kuTpzDPra3y2TBq3OGn9p54KrzZOnFi/neeODa82jns9qj3cjq8zz/R2b0eSxi1OGlO4njRxYn3tC45WMO61pNrnzfPr16mv/bnjwjFNeK1R7aefXj+mZ44Orza2WHuZ/AmvJ93vTd4He9QeBIGefnr3dvznRodXur/Rutr9016Ncmp4H8RiMZlnRoVXixvVbpK248mkVHtz94H/3LHhle4G+SVq9zxP3/xmPKo7cR80VXuUX4PaJWn+/HDfa6r2Zve9Z44Or3Q3l9/Pw3q8G4Pm972bjg6vdM/yGuWXtO/9/Dj5N9Zf6W5u3/v5seGCG8P/7LnvSZJXVhZe6b7Za3Lfa/RY0MS+t7f10/0Y8dhjjyXNI5vi7JXuziAnJ0c5OTlJy7KzsxVLvM2igeZeJUl1eVPbbs3yeDyu1atXa+jQoYrFYk2u73leWmtv7zE11Fztro1JUlIOe1s/U8aUaTnF43GVl5c3yqCl2ptb7sKYWqox1eUdMaaGj0mJK0uZPqZUlrswpng8rpUrVzZ7LGTimNp7eUeMqeGx0J61k1Prl+95jhR9Bvu0pUlj8hp8k5Xv+5IXl/bYluf59X8jscA0qr3J7ST9UlhjYr3d22pc++516pd78Qa3JdeeKMHzjGJqTe1Bm2oPJzrJdSfV2EztcUmr48dqaBBE56p73geep2Zq95q8D1KtvTX5Nao9lfxSqL3Zfc8z0t7yiz4f0MJ9EATROntuS1otaWi4rZby2+PvNRqTJNVPYpvb9xod203se3tdv4Xl7fG415LWXQ+3oLAwfGvDpk2bkpZv2rQpuq2wsFCbN29Our2urk5btmxJWqepbTT8G82t0/D2lmrpDPZ81QZ2kIN9ZOAGcrCPDNxADh2oicZm8+ZJ779PBi4IlPpkB+2PrwtLnbOT7uLiYhUWFmrhwoXRss8++0yvvfaaysrCt3uUlZVp27ZtWrZsWbTOCy+8oCAIos9Nl5WV6aWXXtKuXbuidZ5//nkddNBB6tOnT7ROw7+TWCfxd1pTCwAAADJLazqOA8BXZXXSvX37di1fvlzLly+XFDYsW758udauXSvP83TVVVfplltu0VNPPaUVK1boBz/4gQYMGBB97nv48OE67bTTdNlll+n111/XK6+8omnTpunCCy/UgAEDJEnf+c53lJ2drUsvvVTvvvuuHn30Ud19991JjdOuvPJKLViwQL/61a/0wQcf6MYbb9TSpUs1bdo0SWpVLQAAAHBH0oSar+YCYJHVz3QvXbpUJ598cvTvxER40qRJeuihhzRjxgzV1NTo8ssv17Zt23T88cdrwYIF6t69e/Q7jzzyiKZNm6ZTTz1Vvu/r3HPP1W9+85vo9ry8PD333HOaOnWqRo4cqYKCAs2cOTPpu7yPO+44zZkzR9dff71+9rOfqaSkRE8++aQOPfTQaJ3W1JLJfN9XcXFxs591QMcgB/vIwA3kYB8ZuKHL59Dg89P2+PK8LpyBI3zFVRxbSg6WhZ/JL5bDb5h2ktVJ90knnZTUQW5Pnufppptu0k033dTsOn379tWcOXP2+ncOP/xw/etf/9rrOueff77OP//8r1RLpsvKoq+eC8jBPjJwAznYRwZu6Eo5JK5Mn3GG3Toa6zoZuCxLO1teCR2A4yFVvEQBSWGTlj2/kxgdjxzsIwM3kIN9ZOAGcnBBIGPIwLZAMZXHx5CDZeHXbpVLIodUMOkGAAAAACBNmHQDAAAAAJAmTLoBAAAAAEgTJt2QFHYiLCkpoSOkZeRgHxm4gRzsIwM3kIMLfHkeGdjmK66S2CvkYFnYvbxETCNTw72FSF1dne0SIHJwARm4gRzsIwM3kIMLyMAFdcqxXYLbRnXUd9FzPKSKSTckhZ0IKyoq6AhpGTnYRwZuIAf7yMAN5NDY3Lm7v1pMUvhd3gvSOdkIZAwZ2BYopor4KHKwLOxeXiG6l6eGSTcAAAAAwG2jRnXg1fz2xaQbAAAAAIA0YdKNCI0p3EAO9pGBG8jBPjJwAznY53lk4AJfcdsl2OHYFV6Oh9Rl2S4AbojFYiotLbVdRpdHDvaRgRvIwT4ycAM52Od5MUmlisVsV9K1xby4SrNeEUHYFYvF5Hk8JqWKlykgSTLGaPv27TLG2C6lSyMH+8jADeRgHxm4gRzsM8bIGDKwzRhpu+lDDpZxPLQNk25ICjsRrl+/no6QlpGDfWTgBnKwjwzcQA4uCGQMGdgWKKb18cPIwbKwe/l60b08NUy6AQAAAABIEybdAAAAAACkCZNuSJI8z1N2drY8z7NdSpdGDvaRgRvIwT4ycAM5uMCT55GBbZ6Msr0d5GCZ54XHg0QOqaB7OSSFX0cyZMgQ22V0eeRgHxm4gRzsIwM3kIN94dcjDRHf3GaX7wUaElsqgrDL9315Ho9JqWKvhaSwE+G2bdvoRGgZOdhHBm4gB/vIwA2ZkMPcueFPZMGo8KeTCLs1u51BV2CMp21BITlYxvHQNky6ISnsRFhZWUlHSMvIwT4ycAM52EcGbiAHFwQyhgxsC+SrMiglB8vC7uWVont5aph0AwAAAACQJky6AQAAAABIEybdkBR2IszNzaUjpGXkYB8ZuIEc7CMDN5CDCzx5HhnY5sko19tKDpaF3ctzRffy1NC9HJLCToSDBg2yXUaXRw72kYEbyME+MnADOdgXdi8fRNNsy3wv0KDYCrqXWxZ2L+cxKVXstZAUNkWoqqqiOYVl5GAfGbiBHOwjAzeQg33GBDKGDGwLjKeqYDA5WBY2UquSMeSQCibdkBS2/6+qqqL9v2XkYB8ZuIEc0qfJr3dqAhm4odPmkFFfK2bqJxmdLIMMY+SrKhhMDpaFXxlWJYkcUsGkGwAAAGnX6AUfAOgimHQDAAAAAJAmTLohKexEmJeXR0dIy8jBPjJwAznY114ZtPbt7Ggax4ILPHkeGdjmySjPqyQHy8Lu5Xmie3lq6F4OSWEnwqKiIttldHnkYB8ZuIEc7CMDN5CDfWH38iKaZlvme4GKYivpXm5Z2L2cx6RUsddCUtiJcOPGjXSEtIwc7CMDN5CDXXPnSk891SCDjGp61blwLNgXdi8nA9sC42tjvJQcLAu7l2+ke3mKmHRDUtiJsLq6mo6QlpGDfWTgBnJwwd4zaPJt40zM2x3HgguMjCED24w8VZtCcrAs7F5eLbqXp4ZJNwAAAAAAacKkGwAAAACANGHSDUlhJ8KCggI6QlpGDvaRgRvIwQUdlwFvVW9ehx0L3Od74cnzeDyyzVOgAv9jcrAs7F5eILqXp4bu5ZAUdiIsKCiwXUaXRw72kYEbyME+zyMDF6TzWEi80HHGGWnZfKcRdi8voGm2Zb5nVOB9TPdyy8Lu5Tw3pIq9FpLCToTr1q2jI6Rl5GAfGbiBHOwzhgxcYPtY4F0Iie7lHAu2BcbXuvhh5GBZ2L18Hd3LU8SkG5LCToQ1NTV0hLSMHOwjAzeQgwvcy6ArTv44FlxgZAwZ2Gbkqcb0IQfLwu7lNaJ7eWqYdAMAAAAAkCZMugEAAAAASBMm3ZAUNkUoLCyUT3MKq8jBPjJwg+s5dI3PubqdQVfh+rHQNfjyPDKwzVegQn8lOVgWNlIrFNPI1NC9HJLC9v/5+fm2y+jyyME+MnADOSRr1GU6McE/bWna/iYZuKEtOdjYXzqz8Cuq8sU3VdnleUb5XqXSHsSo+uPllvT+mUwVfmVYvu0yMg4vUUBS2IlwzZo1dIS0jBzsIwM3kIN9xpCBCzgW7Au7l5OBNaNGSaNGKTC+1sRHkYNlYffyNXQvTxGTbkgKOxHW1tbSEdIycrCPDNxADi7ovBl09McDvsrf41hwgZExZGCbkada07Pz5VD/okKmCLuX14ru5alh0g0AQBp0jc99u6fJ+x0AAIuYdAMA0AkwyQeQUdrzCm+GXS1G18OkG5LCToQDBw6kI6Rl5GAfGbiBHFxABi7gWHCBL88jA9t8xTUwtoIcLAu7lw8U08jU0L0cksJOhL169bJdRpdHDvaRgRvIwT4ycAM52Bd2L+9F9/JUpKEDuOdJvbQ1/d3LsVdh93Iek1LFSxSQJMXjca1cuVLxeNx2KV0aOdhHBm6wmUPS27S78Fu0jeFYcAGPSfYZE5cxZGBb3MS0sm4MOVgWj4fHgzHkkAom3YjwFQxuIAf7yMAN5GAfGbSsIz5LTw728fVIbggUs11Cajrp58w5HlLHpBsAAAAAWovGbUgRk24AAAAAANKESTckhZ0Ii4uL6QhpGTnYRwZuIAcXkIELOBZc4MvzyCBi6Sqvr7iKY0vJwbKwe3mxmEamhnsLkawsmtm7gBzsIwM3dJUcXG7c1lUycB05uIAMXJClnbZLgCSOh9Qx6YaksElLeXk5zVosIwf7yMAN5OACMnABx4ILAhlDBrYFiqk8PoYcLAuC8HiQyCEVTLoBAAAckO4u6AAAO5h0AwAAZIiO+IoyAED7YtINAAAAdGZ8xRVgFZNuSAo7EZaUlNAR0jJysI8M3NAwB5cbjXVuHAsu4DHJBb48jwxs8xVXSeyVtufACw/tIuxeXiKmkanh3kKkrq7OdgkQObiADNxADvaRgRvIwQVk4II65dguAZI4HlLHpBuSwk6EFRUVdIS0jBzsIwM3kIMLyMAFHAsuCGQMGdgWKKaK+ChysCzsXl4hupenhkk3vjKaugAAAACwztGPETDpBgAAAAAgTZyedN94443yPC/p5+CDD45u//LLLzV16lTtu+++6tWrl84991xt2rQpaRtr167VxIkT1bNnT/Xr10/XXHNNo89GvfjiizrqqKOUk5OjYcOG6aGHHmpUy+zZs3XggQeqe/fuGj16tF5//fW0jNkmGoS4gRzsI4O966h3tpCDfWTgBnKwz/PIwAW+4rZLgDge2sL5e+yQQw7Rxo0bo5+XX345uu3qq6/W3Llz9fjjj2vRokXasGGDzjnnnOj2eDyuiRMnqra2VosXL9bDDz+shx56SDNnzozWqaio0MSJE3XyySdr+fLluuqqq/TDH/5Qzz77bLTOo48+qunTp+uGG27QG2+8oSOOOELjx4/X5s2bO+ZO6ACxWEylpaWKxWJJy5t86zjSprkc0HHIwA3kYJ/nkYELOBbs87yYPK8LZODo23ITYl5cpVmvdP4cHBeLhceD55FDKpyfdGdlZamwsDD6KSgokCRVV1frT3/6k37961/rlFNO0ciRI/Xggw9q8eLFevXVVyVJzz33nN577z395S9/0ZFHHqkJEybo5ptv1uzZs1VbWytJuv/++1VcXKxf/epXGj58uKZNm6bzzjtPd955Z1TDr3/9a1122WWaPHmyRowYofvvv189e/bUAw880PF3SJoYY7R9+3YZY2yX0qWRg31k4AZysI8M3EAO9hljZAwZ2GaMtN30IQfLOB7aJst2AS0pLy/XgAED1L17d5WVlenWW2/VAQccoGXLlmnXrl0aO3ZstO7BBx+sAw44QEuWLNGxxx6rJUuW6LDDDlP//v2jdcaPH68pU6bo3Xff1de+9jUtWbIkaRuJda666ipJUm1trZYtW6brrrsuut33fY0dO1ZLlizZa+07d+7Uzp07k5bV1tYqHt/91hjP8+T7fn0nQNPi8vC78bxmlzfcdmK5pEadHvdcHo/HtXbtWh100EHR35XCBzjJk+TLGKPAxKT6v5Go0ZhAkkkslmd8+V5gfUwJsVgsrL3B8t21N728tbW395h27dqltWvXatiwYYrFYp1iTJmWUzwe17p161RaWqo9ZeqYGi5vr5zi8frlJiZPRr7UrmOqq6uLjgVjujUYU/0r6/F42va95Mc9T4H8Nj3uNdxOc7Un73uSbyTPU6MxGePXr7P7fpckv/53w+1Em68fU9jtt3HtRlKQXHu0jd21GxNo/fr1Gjp0qPwGtTd3H/jGk+eZRrkas0dO9c8jDfNoWLvv+9IetTfMqaV9r8n7vcX8PPlN1N6a46k1tTeXX6yJ2oMgUWO478XrnxdKSkrUrVu3zrPvNcivtbV/pX1vj/ugqdqbyy/c1jrt2jU0vMqa5n0v/I8vae+Pe03W3lx+iavD9b/T5L7n+/KDoOXHvfpteWZv+YXbM8ZrVHti/cR2fBPf+75Xv17cxLQ2frhK43HFYrHk/GIxxervk+b2vYb3wd73vca1N3cf+CbY+74Xi0X3ebP7XiwmPx5vZt+LNVt70/ueFJj6NVrML9jLvtd8frt27ZIxayUNC2s34d9p674nSV4L+15U4172vWj9RO0N6kn3uVFrOD3pHj16tB566CEddNBB2rhxo2bNmqUTTjhB77zzjiorK5Wdna38/Pyk3+nfv78qKyslSZWVlUkT7sTtidv2ts5nn32mL774Qlu3blU8Hm9ynQ8++GCv9d96662aNWtW0rLTTz9do0ePjv6dl5enoqIibdq0SdXV1dHygoICFRQU6JNPPlFNTU20vLCwUPn5+froo4+iq/WSNHDgQPXq1UurV69O2hGKi4uVlZWl8vLypDpKSkpUV1eniooKSeHOs3XrVklSTU2N1q9fLyk8+DwvW9IQVVdXqzI+RqrfVm5urgYNGiRpi4ypSixWXjBMRbGV1sckhQdHaWlp0pgkKTs7W0OG1I+pfl9oOKYtW7aoqqqqw3NatWqVtmzZolWrVsn3/U4xpkzLKTHhk9RpxiS1b05SjcrL68cUH6Nsb4eGSO06ps8//zw6FqQBkurHFB8TrlxenrZ9L+lxz/RXZVDapse9cDsFkupzalB7w5yMqU0s1kD1US9tbTQmqVhSgzHVb6ukfn+tqKiITuBWr64fk/poffywqPbEvidVy5jKqPbc4BANkpJyCre1jyRp8+bN+rxB7YmcpE9kTE20nULTX/leZaN9TxooqUFO9c8jDXNK1F5eXp+TeqoiPiqqPZV9L7zfcyXV73sNnrcS+560ScZUR7UXmANU4H3cpuMpPJEN/0RxcbGyFFN5g78ZKpFUp/Lyiqh2X3GVqvFz7kcf1T9G1O97Qf3zwoYNGzR48GB1mn0vPka53tYm9z3Py5NU/xjRXvteg+2kuu9JQyXtip6b073vhdspVEuPe03ue3s87kX73pj6bcTV/L531FEasnRpy4979dvKCypVJDWz70mfHHKIauJ9otr33PcS2xmoFXvf9+rXC+K+tphBCoJA8Xg8ed879liVvvLKXve9hvfB3vc9adOwYaqOF0a1N9r36rdVaFbufd879lgF8Vi0nSb3vTFjVPLKK6pTThP7Xv3jXoPa977vSVvMAaoKBje/79Vvq8B8vJd9L9wfauM9o9oT+174HLpF0iqVjxmjYi1Vlna2ed+TpOwW9r0op73se1L9eYTq970G9aT73Kg1nJ50T5gwIfr/ww8/XKNHj9bgwYP12GOPqUePHhYra53rrrtO06dPT1r2xBNPqKSkJPq354WvIPXv31/9+vVrtHz//fdv9IqMJB144IFNLh86dGjS30ssb/g3E8uzs7Oj5fF4vP7kNtzBE8tXrpQSr5zl5eVpn9grUskdSTVKfeV5fZT4E17FqibHNG+epzPPrB/Ts2XhwnGL0zamhhqOqWHteXl52meffRot79u3r/r06dNoebpzGjZsmFatWpV0pTvTx5RpOcXjca1evbpTjanh8vYYk9RgTBWvyKt/+bo9x1RXVxcdC6tWdds9pg9fCVcuuSNt+17S4563SfvEPm3T417D7ey///4y7zSu/cADD9Q775j6eiW/YmuTY1q5co8xVbzSaEzh35MSv5qrrSpp8jE7T563T4Pa3w1H1CCnlStVf0L/ufr166fC2O7ad29nf3meibbjV2yKxtRw30vUHo2p4pWk+6Bh7SUl9WPSjqTad2t532t4v/ft21d9mrwP+svz+jW4D9aGI9rjeJo3z9eZZ9aPqYnnraFDhyrx+nuidineqPbwPshulJ/UeN878MDkfS8+7JdatWqVBgwYUP8bnWTfa5Dfnvteovb+/furX3vte6sb3wet3ffCjLtp2LD6K91p3vfC7TR4LG/mca/JfW+Px7do33ulfhvf2H1bo33vjTfCMbX0uFe/Le8bYb3N7nvvvivzba9R7Yl9L7Ed/xvxaEyNa1e0XnxsTKviZfJ9X7FYLHnfq/9o6d72vYb3QYv73qpV6hdbHdXeaN+Lag+iMTW57736qnSaGt0HSfveK6/Ij8eb3Pc+/DAcVVO1N7vveWvVJ7a++X0vyi+svdl97403ZM5qnF9xcbE++CAuaVhYe31+bd33JMlrYd+LctrLvtdw/f3ffVemwfbTfW60bNkytcTpSfee8vPzVVpaqlWrVukb3/iGamtrtW3btqSr3Zs2bVJhYfgKTWFhYaMu44nu5g3X2bPj+aZNm9S7d2/16NFDsVhMsVisyXUS22hOTk6OcnJykpZlZ2c32QCiuVdJUl3eXHOJlpZ7nqfu3bsr0SV+9/Ld63qep5gXj97asXu5X7+txIKgyRoT2/J9X/LiSv6l9h9T8t/2UlreXnmkOqasrCx1795dWVlZSb+byWPKtJw8z1NOTk70lqbW1t7cchfG1FKNieWJpolnnFG/cMEoxSTptKVJ6ybV7sWbXt6KWubN8xv9PUnyT1uadCwknkSbe+xo730v+XHPKKa2Pe413M7eHvcS68ViSpwzNarR23N5Ylv1N4SNbZI373lqpnZPUqwVtXvRc5bfRO2N7wPTaDvN1r5HfnvWrr3U3tK+1+T93mJ+e699b/tea2pvNr8mak+UkNj3vPpjYfc6nWTfa3AfpFp7m/a9r5CfFMjzcnY/N6d532vNfdBs7c3lF72fveFte+x79Vf6Wnzc22NbzdYeBLv/XhP73p7baal2zzPq7tdEbwlOug+idfby2NHEfZBq7a25DxrV3sR2mqp9r497rcgvqt0zUhrzC5+Xu0vKShpfW/c9SVIL+15UYwv3e1LtKZyPtMd5REtadz3cEdu3b9fq1atVVFSkkSNHqlu3blq4cGF0+4cffqi1a9eqrCx8NbqsrEwrVqxI6jL+/PPPq3fv3hoxYkS0TsNtJNZJbCM7O1sjR45MWicIAi1cuDBapzPwfV9Dhgxp9VskkB7kYB8ZuCEdOTT5bQx8I0OzPI9jwQU8Jtnneb48jwxs871AQ2JLycGy8EWPIeJrw1Lj9L31k5/8RIsWLdJHH32kxYsX61vf+pZisZguuugi5eXl6dJLL9X06dP1z3/+U8uWLdPkyZNVVlamY489VpI0btw4jRgxQt///vf11ltv6dlnn9X111+vqVOnRlegr7jiCq1Zs0YzZszQBx98oHvvvVePPfaYrr766qiO6dOn6w9/+IMefvhhvf/++5oyZYpqamo0efJkK/dLOhhjtG3btqS3XKDjkYN9mZiBixPJrzrBzcQcOhsycAM52Bd2ayYD24zxtC0oJAfLOB7axum3l69fv14XXXSR/v3vf2u//fbT8ccfr1dffVX77befJOnOO++U7/s699xztXPnTo0fP1733ntv9PuxWExPP/20pkyZorKyMuXm5mrSpEm66aabonWKi4s1b948XX311br77rs1cOBA/fGPf9T48eOjdS644AJ9+umnmjlzpiorK3XkkUdqwYIFjZqrZbIgCFRZWal99tmnTW+ZQPsgB/vIwA0Ncwh7naLjNTgWbJfShfGY5IJAxlQqCMjApkC+KoNS7RME5GBR2AG8Up63T8srI+L0pPt//ud/9np79+7dNXv2bM2ePbvZdQYPHqz58+fvdTsnnXSS3nzzzb2uM23aNE2bNm2v67iiqc9lSmr0uUwA6Cx43AMAAK5y+u3lnZYDb/9s9NbP546TVv3eWj0AAAAA0Bkx6YYkyZNRrre1wdcK2NHk50C7EM/zlJubaz2Hriix70UZPNd5GiVmIo4FF5CBCzgWXODJ88jANlfOVbu68JuOcpXUjhwtYtINSWFHyEGxFXSEtMz3fQ0aNIgcLIoyqP8anoboft1xOBbs8zwycAHHgn1h93IysI1zVTeE3csH0b08RdxbkCQFxlNVMFhB0HiigdZpj8lYEASqqqoih3aU6kQ5ysB0rldwM+0FA44F+4whAxdwLNhnTCBjHM5g1Kjwp5PjXNUNYSO1KhlDDqlg0p1h0vX2ayNfVcFg2v+nWUsTH2OMqqqqyMGiKAMeHq3iWHABGbiAY8EFpn6S0cEZdJHJdGtxruqG8CvDqiSRQyo4q3REpl2FAgAAAAC0jEk3Mk5nf4Hiww+lefMaLOhk4+sKOvP+CQAAgNQw6YaksCNknlfZqTpCZuLEJ+wImSc6QtrjeZ7y8vLk8bYpq6IcOtFjUuYhAxdwLLggfG4mA7s647lqJuJctW2YdENS2BGyKLaSjpCWhR0hi+gIaZHv+yoqKmqyezk6TpQDj0nWeB4ZuIBjwb6wezkZ2Ma5qhs4V20b7i1IkgLja2O8lI6QloUdITe2qiNk0tvsM+RKfiYIgkAbN25UYHh4tCnKgccka4whAxdwLNgXdi8nA9s4V3VDKueq2I2zSkiSjDxVm0I6QjahIz9DHnaErBYdIe0xxqi6ulqGt01ZFeXAY5JFZOACjgUXhM/N7ZoBnclTxrmqGzhXbRsm3ejSOntTNgAA0MGYUANus3CMMukGAAAAACBNmHRDkuQpUIH/MR0hLQs7QhaIjpD2eJ6ngoICeeKzSjZFOfCYZBEZuIBjwQXhc7N37LFcwbaIc1U3cK7aNlm2C4AbfM+owPtYoiOkVWFHyALbZWSMxEcDzjijfkHiowGnLW3zNn3fV0FBgeTxWSWbohxgjeeRgQs4FjpIYjJ9S+Obwi7NBfL5LLFVnKu6gXPVtmGvhaSwI+S6+GF0hLQs7Ai5jo6QFgVBoHXr1tG93LIoBx6TrDGGDFzAsWBf2L18nQIme1ZxruoGzlXbhkcPSAo7QtaYPnSEtCzsCFkjOkLaY4xRTU1N2ruXN9nED5EoBx6TLCIDF3AstIOv/Jbw8LnZ8LZmqzhXdQPnqm3DpBsAAABuoQM4gE6ESTcAAAAAAGnCpBuSJF+BCv2V8vm8klVhc4pCcWja4/u+CgsL5dO93KooBx6TLCIDF3As7EWHXQ0Pn5t9PktsFeeqbuBctW3oXg5JkucZ5XuVEp9Xsir8Gob8dtteOrp7d3ae5yk/P5/u5ZZFOcAaMnADOdgXfkVVvjw+S2wV56puaO9z1a6ClyggKewIuSY+io6QloUdIdfQEdKiIAi0Zs0aJ7qXN9lsrYs0XIty4DHJGmPIwAUcC/aF3cvX0L3cMs5V3cC5atvw6AFJYUfIWtOTjpCWhR0ha0VHSHuMMaqtrU1793LsXZQDj0kWkYELOBZcED43073cLs5V3cC5atsw6QYAAAAAIE2YdAMAAAAAkCZMuiFJ8hXXwNgKOkJaFnaEHKiOPDS78ueGm+L7vgYOHChfcduldGlRDjwmWUQGLsioY6HTfrd2+Nzsx3lesIlzVTfYOFftDLi3IClsBNnL21rfoRO2hB0he5GDRZ7nqVevXjRHtWx3DgRhCxm4oVPmkGET8+i52XYhXRznqm7gXLVtmHRDkhQ3Ma2sG6M4r+JaFY/HZcxKGUMOtsTjca1cuVJxE7NdSpcW5cBjkjXGkIELOBbsMyZ8bo7HeF6wiXNVN3Cu2jZMuhEJxJOJC1z9Coakt6F38reg83UkbiAH+8jADeRgn6vPzV0N56pu4HhIHZNuAAAAAADShEk3AAAAAABpwqQbksKOkMWxpXSEtCzsCFksDs1muqp3AN/3VVxcTPdyy6IceEyyiAxc0CHHQoY1Nut44XMz3cvt4lzVDZyrtg33FiJZ2mm7BEiSsmwX0OVlZZGBC8jBPjJwgxM5dNqvA2stBzIA56rO6CLHQzs+7jHphqSwMUV5fAzNWiwLgkDGlEsiB1uCIFB5eTnNWiyLcuAxySIycMFXOha6/ES5vYTPzQHdy63iXNUNnKu2DZNuAO2mybeEd+Iu5wAsYCIJAMgwTLoBAEDXxAQeANABmHQD6FBcDQe6qI6e4Lo4oXaxJgBA2jHphqSwI2RJ7BU6QloWdoQsEYemPb7vq6SkhO7llkU58JhkERmkJE0Tao4FF4TPzXQvt4tzVTdwrto23FuI1CnHdgmQJNXZLqDLq6sjAxeQg311J58sHX303lfi6m3aNXkscL93MB6PXMC5qis4HlLFpBuSwo6QFfFRdIS0LOwIWSE6QtoTBIEqKiroXm5ZlIPrj0md+i3TgSpGjerYjs1MJBvdBxlzLHRq4XMz3cvt4lzVDZyrtg2TbgAA0snViTkTXAAAOgSTbgAAAAAA0oRJNyI0jnKD53FY2kaTFjdYz4GrwDSOcoT1YwE8NzuCc1U3cDykjnsMkqSYF1dp1iuK8Xklq2KxmDyvVJ5HDrbEYjGVlpYq5vHEblOUQ1d6THJsku95MZW+8opiTLyt6pLHgmM8L3xu5liwi3NVN3Cu2jZMuiFJMkbabvrIGGO7lC7NGCNjtpODRcYYbd++XURg1+4cCMIWY4y29+mjLp+A5c++cyzYFz032y6ki+Nc1Q2cq+6hlc8PTLohKewIuT5+GB0hLQs7Qq4XHSHtCYJA69evp3u5ZVEODR+THLsS3PkFWn/YYXRstqzJYwEdLHxu5liwi3NVN3Cu2jZMugEAAAAASBMm3QCA1PF1UwAAAK3CpBuSJE9G2d4OeZ5nu5QuzfM8eV62JHKwxfM8ZWdny+PTex2niQl8lEM6HpN4waCVPGXv2CGPz+1ZldZjAa0UPjdzLNjFuaobOFdtGybdkCT5XqAhsaV8LYllvu/L84bwVQwW+b6vIUOGyPe68GeV2nNS2sZtRTmk+pjEhLrdeJ6vIUuXyufzk1a1+VhAu/G88LmZY8EuzlXdwLlq23BvQZJkjKdtQeFX60TIye5XFnaE3EZHSIuMMdq2bZuMybBXcDvZ8bc7B44FW4wx2lZYKMNVJas4FuyLnps5Fqxql3NVfGWcq7YNk+6O9n//r+0KmhTIV2VQ2nxHyPY6oe9kE4P2FnaErBQdIe0JgkCVlZUKOuvDY4Ycg1EOXFmyKFBlaakCripZxbHggvC5mWPBrhbPVdEhOFdtmyzbBQCAU447ThozRvqG7UIAAADQGfCSXWfWmitarl71crWulrS27kzOJlM58DllAAAAdD1Mul3TnpO2FHgyyvW2ZlZHyPacuDoyCQ47QuYqpY6QTP7alWeMcrdu/erdy5mYfyWe5yk3NzezHpM6HS88FvjcnlUcCy4In5s5FuzKyHPVTqhN56pg0o2Q7wUaFFtBR0jLwo6Qg+gImap2nOD6QaBBK1Z0XPdyJudN8n1fgwYN4jHJIs/zw2OBz09axbFgX9i9fBDHgmWcq7qBc9W24d6CJCkwnqqCwTSnsCxsTlElY9o5ByZ2rRZ4nqoGD1bgUvfyLphfEASqqqriMckiY4LwWOCqklUcC/YZEz43cyzYxbmqG9J2rtrJMemGJMnIV1UwmPb/loVfw1AlfdW3NrdFF5zYNcX4vqoGD5bh4dEqY4yqqqp4TLLKhMcCV5Ws4lhwQfjczLFgF+eqbrB6rprBePQAkJqOnpjzYgAAAAAyGJNuAO3PkcZ0AAAAgG1MuiEp7AiZ51XSEdKysCNknugIaY9njPIqK79693J8JZ7nKS8vj8ckq7zwWOCtnFZxLLggfG7mWLCLc1U3cK7aNlm2C4AbfC9QUWylxOeVrAo7QhbZLqNL84NARStX8lxime/7KiriWLDJ8/zwWIBVHAv2hV2ai+hebhnnqm7gXLVt2GtTNHv2bB144IHq3r27Ro8erddff912Se0iML42xkvpCGlZ2BFyIx0hLQp8XxtLSxUYHh5tCoJAGzdu5DHJImOC8FjgBNcqjgX7wu7lGzkWLONc1Q2cq7YNjx4pePTRRzV9+nTdcMMNeuONN3TEEUdo/Pjx2rx5s+3SvjIjT9WmkI6QloUdIatFR0h7jOepurBQhkvdVhljVF1dzWOSVSY8Fngrp1UcCy4In5s5FuziXNUNnKu2DZPuFPz617/WZZddpsmTJ2vEiBG6//771bNnTz3wwAO2SwMAAAAAOIjPdLdSbW2tli1bpuuuuy5a5vu+xo4dqyVLljT5Ozt37tTOnTuTt2OM4iYW/iMel+d58n2//i0aRvFYeJtnAvmeqX8Lx+5Xkozx5XmeAt8PX3E14XbCz1d4isfjSqwej8Xkx+OSkQLFpHg8aTuJdSQpbmIKjFd/m4neuhNuq36554Vvua3fTvO1G/le0ETt4XYC34/+v2HtDddP1O5Jijeou6naEy+0+fW/27D2eCymWP190vA+2F27kRTstfaG98GetSe2k1g/sR3fBPL2kl9ztYdjDWRMfK/5xWKx5NpN2GDE30t+gedF991X3veayK+t+17iPojtpfavsu/tLb/m9r3EqDt835Os7Xvh+i3nl9j3Gm4nHftePB6P/mt13zOeAnXcvuebuDyvbftew/ugPfa9xFsHA99Xg4Oi2fsgpX2v/j5oqva07Hst5tf8497e8kvHvhf4vvwgiPa9xLEQBEH9fdBJ9r0G+aX6uNemfa/BPpzqvpcYeEfte+F/2rjvtTK/1ux7rXrcSyG/Pfe93fm1bt9LnKuGV1pNyvteU/m5v++14XHP1K+Rxn0v6VzVhH+nrfueJHkt7HtRjXvZ96L1E7U3qKfR416Un2kwJiWtL0lBovb62xvmtzuimFrDM7xHo1U2bNig/fffX4sXL1ZZWVm0fMaMGVq0aJFee+21Rr9z4403atasWUnLTjzxRF1xxRVprzdVu3bt0t///nedddZZ6tatm+1yuixysI8M3EAO9pGBG8jBPjJwAzm4gRwae//993XTTTftdR0m3a3Ulkl3U1e6c3JylJOTk/Z6U/XZZ58pLy9P1dXV6t27t+1yuixysI8M3EAO9pGBG8jBPjJwAzm4gRzahreXt1JBQYFisZg2bdqUtHzTpk0qLCxs8ndcnWADAAAAADoGjdRaKTs7WyNHjtTChQujZUEQaOHChUlXvgEAAAAASOBKdwqmT5+uSZMmadSoUTrmmGN01113qaamRpMnT7ZdGgAAAADAQUy6U3DBBRfo008/1cyZM1VZWakjjzxSCxYsUP/+/W2X9pXl5OTohhtu4O3wlpGDfWTgBnKwjwzcQA72kYEbyMEN5NA2NFIDAAAAACBN+Ew3AAAAAABpwqQbAAAAAIA0YdINAAAAAECaMOkGAAAAACBNmHQDAAAAAJAmTLoBAAAAAF8ZX4zVNCbdSAkHkn1k4AZycAM52EcGbiAH+8jAnj3ve7LoePF4POnfQRBYqsRNfE839mrLli2qrq6WMUZDhgyxXU6XRAZuIAc3bN68WZs2bdIXX3yhY445xnY5XRLHghs4FuwjAzd8+OGHeuSRR7R27Vodf/zxOv7443XwwQcrCAL5PtcXO8L777+v3/72t9qwYYOGDx+u8847TyNHjrRdllOYdKNZb7/9tn7wgx9o27ZtysrK0rBhw/T73/9eBxxwgO3SugwycAM5uOGtt97S+eefr7q6Ou3YsUP777+/7r77bh111FHq2bOn7fK6BI4FN3As2EcGbnjvvfd03HHHaezYsdq4caPi8bg++eQTPfTQQzr11FNljJHnebbL7NQ++OADjR49Wt/61re0fft2ffbZZ3rppZf0hz/8Qd///vdtl+cMXv5Bk9avX68JEyZowoQJevjhh/XLX/5SVVVVOuGEE7Rw4cJGbyFB+yMDN5CDGyorK3XOOefo/PPP15NPPqmnn35affv21be//W3993//tz7//HPbJXZ6HAtu4FiwjwzcEI/Hdeutt+r000/XX//6V73yyiu6//77NX78eI0fP17z5s2T53m8zTnNfvvb3+qUU07RQw89pL/+9a/6y1/+omuuuUaTJ0/WfffdJ4m3+0uSDNCEF154wYwYMcJs2LAhWlZXV2cmTJhgioqKzJIlS4wxxsTjcVsldnpk4AZycMPSpUvNsGHDzAcffJC0fPLkyeaAAw4wc+bMMUEQWKqua+BYcAPHgn1k4Iba2lrz9a9/3fz0pz9NWr5582YzZcoU07179+hxCelzzjnnmEsvvbTR8l/84hfG8zwzb948Y4zp8scEV7rRpKqqKm3YsEF9+/aVJNXW1ioWi2n+/PkaMWKELrnkEhlj+KxMGpGBG8jBDZ9//rm2bdumbt26SZJ27NghSXrggQc0ZswY/fjHP1ZVVZUkXlFPF44FN3z22WccC5bxeOSGbt266dBDD9WiRYu0devWaPl+++2n6667ThMnTtTNN9+szz77zGKVnd/hhx+u5557Ths2bJC0e5//yU9+ov/4j//QT37yE1VWVnb5t/nzzIgmTZgwQfvss49+/OMfS5Kys7NVW1srSfrzn/+snTt36r/+679sltjpkYE9Dd+KRg721NXVRf//9a9/Xf37949y6Nmzp3bu3ClJmjNnjvLz83XzzTdLUpd/Ym9P//73v/Xpp59K4lhwxUknnaT99tuPY8GiE088Uf369SMDB5x44on64osv9OCDDya9rX/QoEE644wztHz5clVXV1ussHPa8zzpgAMO0K233qrNmzdHb+nv1q2bzjvvPFVXV6uystJitW5g0g1J0vbt21VdXR29Gti9e3f95Cc/0SuvvKI77rhDUniCFQSB9t13Xw0cOJADqJ2tW7dOr7/+evS5SDKw47333tPPf/5z7dy5U8YY9ejRgxwseO+993TJJZfok08+kRSeuP7yl7/U8uXLdeWVV0qScnJyoknfEUccwYlVO3v33Xc1evRovfzyy5LC/Z5joeN9+umnWrZsmd5++219/vnn8jxPt99+O8dCB9qxY4eCINCXX34pSfJ9X7fffrveeOMNMuhAH330kf7whz/oT3/6k5599llJ0re//W0df/zx+t3vfqe//OUv2rJlS7T+0UcfrZ49e/IZ+3a0bds2SeExkDhfPeaYY3TGGWdo8eLF+q//+i998skn0TueDj74YOXm5qqmpsZWyc5g0g299957Ouuss3TyySerpKRECxYsUFZWls455xyNGTNGjz76qG666SZJ4UGWk5Ojvn37Rm+r4q1TX92GDRt0yCGH6D/+4z/0v//7v4rH48rKytK5556rMWPG6LHHHiODDvDWW2/psMMOU3Z2tnJycuR5nmKxWJQDx0LHWLFihU444QTFYrHoCV6SxowZo2nTpumZZ57R5ZdfLimc9CXk5OQoCAJyaAdvvfWWjjvuOH3yySe64447tG3bNmVnZ+u8887jWOhAK1as0Ne//nVNnjxZRx55pG6//XZJ0vHHH69p06ZpwYIFHAtp9s477+iss87SqaeeqiOOOEL33XefPvnkE5122mm68sorNX/+fDLoACtWrNCoUaP0wAMP6NZbb9V5552nyZMn6/PPP9dvf/tbnXDCCbr33nt18803a/Xq1aqqqtLDDz8s3/fVv39/2+V3Cu+//76OOuoozZw5U5IUi8W0a9cuSdK1116r008/XS+99JKmTJmit956S6tWrdI999yj2tpaDR061Gbpbuj4j5HDJStWrDB9+vQxV155pXnsscfMZZddZgoKCsy2bduMMcZUVFSYGTNmmOLiYjN27Fjzy1/+0lxyySWmV69e5v3337dcfeexatUqM3z4cFNYWGhKS0vNkiVLzJdffmmMCTO49tprzYEHHkgGafTWW2+Z3Nxcc8011yQtr6urM8YY89FHH5kZM2aYIUOGkEMabdmyxRx11FFm2rRp0bLt27ebjRs3GmOM2bFjh7nvvvtMUVGR+drXvmamTJlivvvd75qePXuad955x1bZncry5ctNjx49zHXXXWfmzp1rhgwZYv71r39Ft69du9bMmDHDDB06lGMhjVatWmX69+9vrr32WvPRRx+Z2bNnG8/zzMcff2yMMaaqqopjIc1Wrlxp9ttvP3PVVVeZxx9/3Nx4443G8zzzrW99y7z11lumtrbW3HfffWbAgAFkkEaff/65KSsrMz/60Y+MMcZs3LjRPPPMM6Zv377m1FNPNZs2bTLGGDNr1ixzwgknGM/zzMiRI01hYaF54403bJbeaaxdu9YceeSRpqSkxBx66KFm1qxZ0W07d+6M/v/BBx80EyZMMJ7nmUMPPdQMHjyYDOox6e7C1q1bZ772ta+ZGTNmRMtef/11c9ZZZ5mNGzeayspKY4wxNTU1ZuHChWbcuHHmlFNOMWeeeaZ56623bJXd6QRBYLZs2WK+973vmc2bN5uysjJz0EEHmWXLlhljwhOvIAjMP/7xDzJIkzVr1pg+ffqY73znO8aYsPvyL3/5S/PDH/7QnH/++eaf//ynMcaYzz77jBzS7OOPPzZlZWWmqqrKxONxc+6555oxY8aYnj17miuuuCLqRLt69WozadIkc/7555sf/OAHZsWKFZYr7xyWLl1qsrKyzP/9v//XGBM+Po0YMcKcd955Sett2bKFYyHNrr/+enP66acnLZswYYJ5+eWXzcsvvxw9R69Zs4ZjIU2uvPJKc+GFFyYtu/jii0337t3NOeecY9577z1jTPh4dPHFF5NBmnzxxRfmqKOOMv/zP/+TtPzDDz80BQUFScfJpk2bzDPPPGNefvlls27duo4utVMKgsDcdttt5pvf/KZ57rnnzA033GAOPvjgZifexhjz2muvmXfffTd6wRxMuru0l19+2fzwhz+MXjU3JnyS79WrlznkkENM3759zYwZM8ynn36a9Hu1tbUdXWqXcOqpp5oXX3zR1NbWmqOOOsqMGDHCTJgwwRx33HHRVe8EMmhfc+fONQMHDjRXXnmlWbp0qTn55JPNySefbCZOnGhOO+0043me+e1vf9vo98ih/b311ltmwIAB5v333zfnnHOOGT9+vHnqqafMPffcY04++WRz2mmnRS9IJSTejYCv7rrrrjNXX321MWb3/fqXv/zFFBcXm5deeskY0/TXvnAstL8rr7zSTJgwwWzZssUYY8zNN99sPM8zRx99tOnfv78ZN26cWbRoUdLvcCy0r/POO89MnTrVGBO+6GqMMbfccosZN26cKS0tNT/72c8a/Q4ZtL/t27eb/fffP2mSl3jMSbxL7cYbb7RVXpewceNG89BDDxljwhc2EhPvhvc7zwN7x6S7i1uzZk30/3/6059MLBYzDz74oHn//ffNgw8+aHJycsyTTz6Z9Dtd/Xv22lviCfq73/2uuemmm6LlBQUFJhaLRQ9yDZFB+5szZ44ZOXKkKSoqMhMnTjSVlZXRE8jNN99sunfv3uits+TQvuLxuFm7dq059NBDzb333mu+/e1vm3fffTe6/cUXXzQjRowwf/zjH40xu+9/cmg/TU0YVq5caQYMGGBuueUWY8zu+7vh93GTQfu77777TG5urjnvvPPM/9/evcflfP//A39cHaWDDkSRrnBVTkkOw2cO0VbM9hESGnL4DFPmkMNno4PD2sxh2iynj9CNNcxiKOck9RmaahNpDQ3RktNFKvX6/tGv98+F5NDVdX3yuN9uu63e3ofX9X68rvfV83q/36+3n5+f0NfXFzt37hRKpVKkpKSInj17irlz54qysjK+F9Rk+vTpwsbGRiiVSiFEReFhYWEhDh48KCIjI4WRkdFTZ1OZgXosW7ZMNGvWTPz888/StMrP6EWLFom33npL3Lx5U+W4ROpz7dq1ZxbesbGx/OKpChxI7Q3n4OAAoOJ5qyYmJkhKSoK/vz+cnZ2l/x86dEhlGT7+ombp6uoCqHgMTOVop2PHjoW+vj4cHR2xdOlSHD9+XOXxDMyg5o0YMQLTp09Hly5dMG/ePDRu3FgaFCowMBCmpqZITExUWYY51CwdHR3Y2dnBw8MDU6ZMQWxsrPT8W6DisWEKhQIHDhwA8P/3P3OoOZXHo8ePNwqFAgEBAVi5ciXOnz8v7e/Hn8fNDGrepEmT8MUXX6Bz584oLi7G+PHj4e3tDWNjY3Tr1g0tW7bEiRMnAPC9oC7Tpk2Dg4MDrKys0L9/f7Rs2RJDhw6Fh4cHfHx8YGlpicuXL6sswwxeX15eHk6ePIn9+/dLI2QPHjwY3bt3x5IlS6TPgMrP6IYNG+Lu3buoV6+eynGJXt2zMgAgDQ5oY2ODjz76CL6+voiJiUFoaCimT58Ob29v3LhxQ4Mt1156mm4A1Z6srCxs3LgRV65cQYcOHeDh4QFXV1cAkEalrTxYCSFw69YtWFlZoXPnzhpsdd3yvAzMzMyQmpoKPz8/HD58GMnJyWjRogVatmyJmTNn4tixYzAyMtLsC6gjnszB3d0dnTp1gp+fH1xcXKBQKABUvA9kMhkKCgpgY2ODVq1aabjldUtVOaxYsQJ3795FVFQUDh8+DIVCgQYNGgCoeB6uk5OThlted1R1TNLR0UF5ebn0mdCvXz9ER0cjKSkJzs7OKCsrkwp0en1P5tCnTx907twZAQEBACqKv8rjf+VxCQDatm2rkhO9uiczePfdd+Hi4oL9+/dj1apVKC8vx4cffgg/Pz8AQG5uLurXry8dm6hmZGRk4IMPPoChoSFu3LiBJk2aIDQ0FEOGDMHs2bMRFhaGefPmobCwEMOHD0dpaSn+/PNPWFtbqxSH9OqezMDGxgbBwcHw9PSEpaWl9KWsra0tJk6cCCEEFixYAHNzc5w6dQq2trYafgVaSqPn2anWnD17VpibmwsfHx8xadIkYWdnJ9zc3ERkZKQ0T2lpqcoy8+fPFwqFQly6dKm2m1snPSuDjh07ilWrVgkhKu6RadmypXB0dHxqpMfHbwOg11PVe+Hbb7+tcpnPPvtMuLi4iGvXrtViS+u2qt4P3333nRBCiJs3bwo/Pz+hp6cnAgICxJdffimmT58uLC0tpcGL6PW8yOfC45cJfvjhh8LBwUETTa3Tqsqh8rNBCCEWLFggjI2NRWJiokhOThYhISHC0tJS5fYLenXPysDV1VWsXr1amufJy5Znz54tXF1dnxr3hl5dfn6+cHZ2Fp9++qnIyckRV69eFb6+vsLR0VGEhYWJhw8firS0NDFp0iShp6cnOnToILp16yYsLCzEmTNnNN38OqGqDFq3bi1CQkJEfn6+EEL1NopRo0YJMzMzHo+qwaL7DXDv3j3h6empMkr5lStXhJWVlWjcuLFYvHixyvwHDhwQgYGBwtzcnMP815DqMggPDxdCCLFjxw6V+4af/CKEXk91OVTes1opPj5eTJkyhR/oNex5OVhbW4vPP/9cmr5kyRLh6ekpXF1dxcCBA0VaWpommlznvMznQuVx6OjRo6J9+/b88qkGVZfDwoULhRAVBZ+vr6/Q0dERjo6OwtXVle+FGvKiGVRKTEwUgYGBwtTUlJ8LNezs2bNCLpeL06dPq0yfM2eOaNu2rVi6dKkoLy+XxjVYuHChWL16tcjOztZQi+ue52XQvn17sWTJEnH//n1p+vr161kvvCBeXv4G0NHRQWFhoXQZ84MHD9C0aVP07dsXhYWF2Lt3Lzp27Ij+/fvj3r17yMnJwdmzZ3H8+HG0a9dOs42vI6rLIDY2Fm+99RaGDBmispyeHt+iNam6HPbt2wc3NzfpvZCVlYXU1FQcO3YM7du312zj65Dqcvj555/h4uKC9957D7NmzcKUKVOgp6eHsrIy3mJRQ17mc6HyONSpUyccOnQI1tbWGmx53fIix6ROnTqhf//+iImJwZQpU2BhYQFra2vmUEOqyyAuLk7KoHL+R48eISUlBW3bttVgy+ue0tJSPHr0SBrLo6ioCEZGRvjiiy9QVFSEb775Bu+88w5cXFzQrVs3dOvWTcMtrnuqyyAyMhKenp5wcXEBAAwcOBB9+/aVxoiiqvEmoDpOCAGlUomrV6/i6tWrACruibxy5QrOnj2L0aNHQ6lUYufOnQAAU1NTjB8/Hjt37mTBXUNeJIOioiJs3bpVwy2t217lvTBp0iTExcWx4K5BL5LD/fv3ERsbKy1jZGQEAwMDFtw15GXfC5XLmJqastCrQS/6Xvjxxx+lZXr27Il27doxhxryKu+Ff/zjH1i+fDkLbjXo0KEDbGxsEBISAqDi2F9cXAwAWLlyJRo1aoTw8HBNNrHOqy4DKysrKYOysjI0btyYBfeL0txJdlKnJ4fr//bbb4VMJhPjxo2TnsX9r3/9SwghxPbt24VcLhcFBQV81EINYgbagTloB+agecxAOzAHzXvVDHjLV81SKpXi7t274s6dO9K0X3/9VVhbW4sRI0ZI0yr3+4wZM8T7779f6+2sy5hB7eGZ7jrowoUL+Prrr5GXlydNmzx5MqKiovDbb7/h9OnTmD9/PtauXQsAuH79OiwsLGBpackRUGsIM9AOzEE7MAfNYwbagTlo3utkwFu+ak5mZiYGDx6M3r17o3Xr1tiyZQsAoHXr1li5ciUOHjwIHx8flJaWSn0/Pz8fxsbGePToEYQQmmx+ncAMahePHnXMH3/8ge7du+PWrVu4efMmZsyYgYYNG0JHRwdjxoyBr68vZDIZDA0NpWWysrLQsmVLFBcXw9DQkM+YfE3MQDswB+3AHDSPGWgH5qB5zEA7ZGZmolevXhg9ejQ6d+6M1NRUjB07Fm3atEHHjh3xwQcfwNjYGB9//DFcXFzg7OwMAwMD7N27F//973/55UcNYAYaoOlT7VRzlEqlGDdunPD39xerVq0SMplMzJo1S+VxFo8P8X/u3Dkxbdo0YWpqKjIyMjTR5DqHGWgH5qAdmIPmMQPtwBw0jxloh5s3b4p3331XTJ06VWV6nz59RGBgoMq0u3fvitmzZ4sJEyaIgIAAPpKqhjADzeDXFHWIjo4OOnXqBCsrK/j6+qJhw4YYPnw4AGD27Nlo2LCh9A3tvXv3cPDgQZw5cwaJiYkcKKqGMAPtwBy0A3PQPGagHZiD5jED7VBaWorbt29j6NChAIDy8nLo6OjAwcEBhYWFACoGuBP/b/DGL7/8UmU+en3MQEM0W/NTTVMqlSq/x8TECJlMJoKCgkRBQYEQomIAkRs3bojS0lJRWFioiWbWacxAOzAH7cAcNI8ZaAfmoHnMQDtcuHBB+rmkpEQIIcS8efPEqFGjVOZ7fHCvx69CoNfHDGofz3TXMcbGxgAqhvHX0dGBr68vhBAYOXIkZDIZpk2bhqVLl+LixYvYunUrLCwsNNziuocZaAfmoB2Yg+YxA+3AHDSPGWgHhUIBoOLMqb6+PoCKM6v5+fnSPOHh4TA0NMTUqVOhp6fHe+lrGDOofSy66yhdXV0IIVBeXo7hw4dDJpNh1KhR2L17N3JycnDy5Ek+81bNmIF2YA7agTloHjPQDsxB85iBdtDR0YEQQirmKi9dDg4OxqJFi3DmzBkO2KVmzKD2yITgeO91WWW8MpkM/fr1Q1paGhISEnh/Ui1iBtqBOWgH5qB5zEA7MAfNYwaaV3mfcGhoKPLy8qBQKDBv3jwkJyfDzc1N0817IzCD2sGvLuo4mUyGsrIyzJo1C0ePHkVaWho/TGoZM9AOzEE7MAfNYwbagTloHjPQvMozq/r6+li3bh3MzMyQlJTEYq8WMYPawSHo3hBt27bFr7/+ChcXF0035Y3FDLQDc9AOzEHzmIF2YA6axww0z9PTEwCQnJyMzp07a7g1byZmoF68vPwN8fj9GqQZzEA7MAftwBw0jxloB+agecxAO9y/f18a7I40gxmoD4tuIiIiIiIiIjXh5eVEREREREREasKim4iIiIiIiEhNWHQTERERERERqQmLbiIiIiIiIiI1YdFNREREREREpCYsuomIiIiIiIjUhEU3ERERERERkZqw6CYiIiIiIiJSExbdRERERERERGrCopuIiIiIiIhITVh0ExEREREREakJi24iIiIiIiIiNWHRTURERERERKQmLLqJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiOh/lEwmQ2xsLADg0qVLkMlkSEtL02ibiGrbxo0bYW5urulmvHH69OmDadOmqX07crkcX3/9tdq3Q0SkTnqabgARkTr8/HPtbu/9919ufn9/f9y+fVsqmgFgx44d+PDDD7F48WLMnDmzZhv4AkJDQxEWFgYA0NXVhbm5Odq0aYPBgwdj8uTJMDQ0fOF1JSQkwN3dHbdu3arVgig0NBSxsbGa+/Khc+fa3d7p0y81u7+/PzZt2gQA0NfXR/PmzTF69Gh8+umn0NN7/p8EGzduxLRp03D79u1Xbe1z2/Xk+6HS0aNH8dVXX+GXX35BUVER5HI5+vfvjxkzZqBp06bw9fXFgAEDpPk13gdeVHwt9xWvV+8rj8vOzkarVq1qqlXVOnXqFIyNjdW+HblcjsuXLwMA6tWrh8aNG6Nr166YNGkS+vbt+1Lrel5/Vie5XI5p06bVypchRPRyeKabiEgLrF+/Hn5+foiMjNRIwV2pbdu2yMvLQ25uLo4ePQofHx+Eh4ejR48euHfvnsbaRTXHy8sLeXl5yM7OxsyZMxEaGoqvvvpK0816pjVr1sDDwwNNmjTBjz/+iMzMTKxevRp37tzBsmXLAABGRkawtrbWcEvrpsq+8vh/Dg4OtdqGRo0aoX79+rWyrQULFiAvLw9ZWVnYvHkzzM3N4eHhgcWLF9fK9omo7mLRTUSkYUuWLEFgYCBiYmIwduxYafquXbvg5uaGevXqoUWLFggLC8OjR4+qXZ8QAq1atcLSpUtVpqelpUEmk+GPP/6oclk9PT00adIEtra2aN++PQIDA3Hs2DH8/vvv+PLLL6X5oqOj0blzZ5iamqJJkyYYOXIk8vPzAVRc6u7u7g4AsLCwgEwmg7+/PwAgPj4eb7/9NszNzWFlZYWBAwciJydHWm9JSQkCAgJgY2ODevXqwd7eHuHh4dK/3759GxMmTECjRo1gZmaGvn37Ij09HUDFmdiwsDCkp6dDJpNBJpNh48aN1e6vN42hoSGaNGkCe3t7TJ48GR4eHti9ezeWL1+O9u3bw9jYGHZ2dvj444+hVCoBVFy5MHbsWNy5c0fat6GhoQCA4uJiBAUFoWnTpjA2NsZbb72FhIQEaXuVl3/v378frVu3homJiVTMARVnpjdt2oRdu3ZJ605ISMCVK1cwdepUTJ06FRs2bECfPn0gl8vRq1cvrF+/HsHBwSrrr/z5WX1g3LhxGDhwoMp+KC0thbW1Nf7zn/+od4f/D6vsK4//p6ur+8x5X7Qf7NmzB05OTqhfvz6GDh2KBw8eYNOmTZDL5bCwsMDUqVNRVlYmLffk5eUymQzr16+Ht7c36tevD4VCgd27d6u0Zffu3VAoFKhXrx7c3d2xadMmyGSyaq/SqDyeNW/eHL169cLatWsxf/58BAcHIysrCwBQVlaG8ePHw8HBAUZGRnBycsLKlSuldVTVnwFgzpw5cHR0RP369dGiRQvMnz8fpaWl0rLp6elwd3eHqakpzMzM0KlTJ5x+7GqWpKQk9OzZE0ZGRrCzs8PUqVNx//59ABWX+1++fBnTp0+XtktE2oNFNxGRBs2ZMwcLFy7Enj174O3tLU0/fvw4Ro8ejU8++QSZmZlYs2YNNm7c+EJnXGQyGcaNG4eoqCiV6VFRUejVq9dLXxrq7OyM/v37Y+fOndK00tJSLFy4EOnp6YiNjcWlS5ekwtrOzg4//vgjACArKwt5eXnSH6X379/HjBkzcPr0aRw+fBg6Ojrw9vZGeXk5ACAiIgK7d+/Gtm3bkJWVhS1btkAul0vb9fHxQX5+PuLi4pCamgo3Nzf069cPhYWF8PX1xcyZM6Wz9Xl5efD19X2p1/omMjIyQklJCXR0dBAREYGzZ89i06ZNOHLkCGbPng0A6NGjB77++muYmZlJ+zYoKAgAEBAQgJSUFMTExCAjIwM+Pj7w8vJCdna2tI0HDx5g6dKliI6ORmJiInJzc6Xlg4KCMGzYMJWzqj169MD27dtRUlIiteFJz7ptoao+MGHCBMTHx0uFPgDs2bMHDx48YB+pIS/aDyIiIhATE4P4+HgkJCTA29sb+/btw759+xAdHY01a9Zgx44dz91WWFgYhg0bhoyMDAwYMAB+fn4oLCwEAFy8eBFDhw7FoEGDkJ6ejokTJ+Kzzz575df1ySefQAiBXbt2AQDKy8vRrFkzbN++HZmZmQgODsann36Kbdu2Aai6PwMVRf3GjRuRmZmJlStXYt26dVixYoW0LT8/PzRr1gynTp1Camoq5s6dC319fQBATk4OvLy8MGTIEGRkZOCHH35AUlISAgICAAA7d+5Es2bNpLP1j/d1ItI83tNNRKQhcXFx2LVrFw4fPvzUPYNhYWGYO3cuxowZAwBo0aIFFi5ciNmzZyMkJKTadfv7+yM4OBgnT55E165dUVpaiq1btz519vtFOTs748CBA9Lv48aNk35u0aIFIiIi0KVLFyiVSpiYmMDS0hIAYG1trVIcDRkyRGW9GzZsQKNGjZCZmYl27dohNzcXCoUCb7/9NmQyGezt7aV5k5KScPLkSeTn50v3ly9duhSxsbHYsWMHPvroI5iYmEhn6+n5hBA4fPgw9u/fj8DAQJX7QOVyORYtWoRJkybhu+++g4GBARo0aACZTKayb3NzcxEVFYXc3FzY2toCqCg64uPjERUVhc8//xxAxZc0q1evRsuWLQFUFGgLFiwAAJiYmMDIyAjFxcUq687OzoaZmRlsbGxe+DUZGRk9sw/06NEDTk5OiI6Olor4qKgo+Pj4wMTE5CX33Jtjz549Kvunf//+2L59+1PzvUw/iIyMlPrB0KFDER0djRs3bsDExARt2rSBu7s7jh49+twvQ/z9/TFixAgAwOeff46IiAicPHkSXl5eWLNmDZycnKRbJpycnPD777+/8iXilpaWsLa2xqVLlwBUjIVQOfYFADg4OCAlJQXbtm3DsGHDquzPADBv3jzpZ7lcjqCgIMTExEh9Mjc3F7NmzYKzszMAQKFQSPOHh4fDz89Pep8qFApERESgd+/eiIyMhKWlJXR1daWz9USkXVh0ExFpiIuLCwoKChASEoKuXbuq/HGbnp6OEydOqPyhWFZWhocPH+LBgwfV3uNoa2uL9957Dxs2bEDXrl3x888/o7i4GD4+Pq/UViGEyuWKqampCA0NRXp6Om7duiWdqc7NzUWbNm2qXE92djaCg4Pxyy+/oKCgQGW5du3awd/fH++88w6cnJzg5eWFgQMH4t1335X2iVKphJWVlco6i4qKVC5Rp+erLKRKS0tRXl6OkSNHIjQ0FIcOHUJ4eDjOnz+Pu3fv4tGjR9X2t99++w1lZWVwdHRUmV5cXKySU/369aVCCwBsbGyk2xGq8mSfe10TJkzA2rVrMXv2bNy4cQNxcXE4cuRIja2/LnJ3d0dkZKT0e1UDmr1qP2jcuDHkcrnKsa9x48bV9g0XFxeVNpmZmUnLZGVloUuXLirzd+3a9bnrq86TfXHVqlXYsGEDcnNzUVRUhJKSEri6ula7nh9++AERERHIycmBUqnEo0ePYGZmJv37jBkzMGHCBERHR8PDwwM+Pj7S/kpPT0dGRga2bNmi0q7y8nJcvHgRrVu3fq3XSETqxaKbiEhDmjZtih07dsDd3R1eXl6Ii4uDqakpAECpVCIsLAyDBw9+arl69eq90PonTJiAUaNGYcWKFYiKioKvr+8rD0h07tw5aQCl+/fvw9PTE56entiyZQsaNWqE3NxceHp6oqSk5Lnref/992Fvb49169bB1tYW5eXlaNeunbScm5sbLl68iLi4OBw6dAjDhg2Dh4cHduzYAaVSCRsbG5X7RCvxkVEvrrKQMjAwgK2tLfT09HDp0iUMHDgQkydPxuLFi2FpaYmkpCSMHz8eJSUlVfYbpVIJXV1dpKamPnWv7+OFVOUlspVkMhmEEM9tp6OjI+7cuYO8vLyXOttdldGjR2Pu3LlISUlBcnIyHBwc0LNnz9deb11mbGz8QrejvE4/eNa0yi/jqvIqy7yqmzdv4u+//5aOfzExMQgKCsKyZcvQvXt3mJqaSqPrP09KSgr8/PwQFhYGT09PNGjQADExMdKAgEDF/eAjR47E3r17ERcXh5CQEMTExMDb2xtKpRITJ07E1KlTn1p38+bNa/ZFE1GNY9FNRKRB9vb2OHbsmFR4x8fHw9TUFG5ubsjKynqtR/MMGDAAxsbGiIyMRHx8PBITE19pPefPn0d8fDz+/e9/S7/fvHkTX3zxBezs7ABAZbAfADAwMAAAlQGRbt68iaysLKxbt04qdpKSkp7anpmZGXx9feHr64uhQ4fCy8sLhYWFcHNzw/Xr16Gnp6dyn/eT2318m/S0ZxVSqampKC8vx7Jly6CjUzHcS+U9qpWetW87duyIsrIy5Ofnv1YB+6x1Dx06FHPnzsWSJUtU7nutdPv27Wd+2VJVH7CyssKgQYMQFRWFlJQUlUEL6fXUVD+oCU5OTti3b5/KtFOnTr3y+lauXAkdHR0MGjQIAHDixAn06NEDH3/8sTTPk1faPKsPJicnw97eXuX+8spHlD3O0dERjo6OmD59OkaMGIGoqCh4e3vDzc0NmZmZz/1M4PGPSHtxIDUiIg2zs7NDQkIC8vPz4enpibt37yI4OBibN29GWFgYzp49i3PnziEmJkblnsDq6Orqwt/fH//+97+hUCjQvXv3apd59OgRrl+/jmvXruG3337DN998g969e8PV1RWzZs0CUHFWxcDAAN988w3+/PNP7N69GwsXLlRZj729PWQyGfbs2YO///4bSqUSFhYWsLKywtq1a/HHH3/gyJEjmDFjhspyy5cvx/fff4/z58/jwoUL2L59O5o0aSI9uqd79+4YNGgQDhw4gEuXLiE5ORmfffaZVPTL5XJcvHgRaWlpKCgoQHFx8QvvrzdZq1atUFpaKmUaHR2N1atXq8wjl8uhVCpx+PBhFBQU4MGDB3B0dISfnx9Gjx6NnTt34uLFizh58iTCw8Oxd+/eF96+XC5HRkYGsrKyUFBQgNLSUtjZ2WHFihVYuXIlxo8fj2PHjuHy5cs4ceIEJk6c+FSfe3xdVfWBCRMmYNOmTTh37pw0XgK9vprqBzVh4sSJOH/+PObMmYMLFy5g27Zt0lMMqrtd4d69e7h+/Tr++usvJCYm4qOPPsKiRYuwePFiqdhVKBQ4ffo09u/fjwsXLmD+/PlPFfXP6s8KhQK5ubmIiYlBTk4OIiIi8NNPP0nLFBUVISAgAAkJCVI/P3XqlHTZ+Jw5c5CcnIyAgACkpaUhOzsbu3btkgZSq9xuYmIirl69ioKCgprYnURUUwQREdW6MWPGiH/+858q065cuSIUCoXo1q2buHPnjoiPjxc9evQQRkZGwszMTHTt2lWsXbtWmh+A+Omnn4QQQly8eFEAEGfOnFFZZ05OjgAglixZUm2bQkJCBAABQOjq6gpLS0vx9ttvixUrVoiHDx+qzLt161Yhl8uFoaGh6N69u9i9e/dT21+wYIFo0qSJkMlkYsyYMUIIIQ4ePChat24tDA0NhYuLi0hISFB5HWvXrhWurq7C2NhYmJmZiX79+olff/1VWufdu3dFYGCgsLW1Ffr6+sLOzk74+fmJ3NxcIYQQDx8+FEOGDBHm5uYCgIiKiqr2db9JntXvKi1fvlzY2NgIIyMj4enpKTZv3iwAiFu3bknzTJo0SVhZWQkAIiQkRAghRElJiQgODhZyuVzo6+sLGxsb4e3tLTIyMoQQQkRFRYkGDRqobOunn34Sj/8Jkp+fL9555x1hYmIiAIijR49K/3bw4EHh6ekpLCwsRL169YSzs7MICgoS165de+b6n9cHysvLhb29vRgwYMBL77s3zfP6ihBC9O7dW3zyySfS76/SD0JCQkSHDh2eu117e3uxYsUK6ffHjxeVGjRooJLzrl27RKtWrYShoaHo06ePiIyMFABEUVFRla/H3t5eOv4ZGBiI5s2bi2HDhokjR46ozPfw4UPh7+8vGjRoIMzNzcXkyZPF3LlzVV5HVf151qxZwsrKSpiYmAhfX1+xYsUKaZ8UFxeL4cOHCzs7O2FgYCBsbW1FQECASptPnjwprdfY2Fi4uLiIxYsXS/+ekpIiXFxchKGhoeCf+ETaRSZENTdVERHR/6zjx4+jX79++Ouvv9C4cWNNN4dIo5RKJZo2bYqoqKhnjpdAddPixYuxevVq/PXXX5puChG9oXhPNxFRHVRcXIy///4boaGh8PHxYcFNb7Ty8nIUFBRg2bJlMDc3xwcffKDpJpEafffdd+jSpQusrKxw4sQJfPXVVyqXYRMR1TYW3UREddD333+P8ePHw9XVFZs3b9Z0c4g0Kjc3Fw4ODmjWrBk2btwIPT3++VOXZWdnY9GiRSgsLETz5s0xc+ZMaSBIIiJN4OXlRERERERERGrC0cuJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiIiIiIiISE1YdBMRERERERGpCYtuIiIiIiIiIjVh0U1ERERERESkJiy6iYiIiIiIiNSERTcRERERERGRmrDoJiIiIiIiIlITFt1EREREREREasKim4iIiIiIiEhNWHQTERERERERqcn/AftqObffsz+2AAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_4996117b-0671-48e6-95ae-364fbc068323\", \"after_1925.png\", 133406)"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}