jupysql.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNUUItMbK9ec3NsRGJAZV5C",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/pea-sys/Til/blob/master/jupysql.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "https://github.com/catherinedevlin/ipython-sql?tab=readme-ov-file"
      ],
      "metadata": {
        "id": "lLlRqHTTXCmh"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Install"
      ],
      "metadata": {
        "id": "xnBs_qeJUJit"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "WL4XQBQnWo3K"
      },
      "outputs": [],
      "source": [
        "!pip install jupysql duckdb-engine --quiet"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Setup"
      ],
      "metadata": {
        "id": "5LNxHNyyUNmw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cry6eqpEx-Nt",
        "outputId": "3c401ad7-fd8b-4ddc-9999-81d9cfd31aab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path\n",
        "from urllib.request import urlretrieve\n",
        "\n",
        "if not Path(\"penguins.csv\").is_file():\n",
        "    urlretrieve(\n",
        "        \"https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv\",\n",
        "        \"penguins.csv\",\n",
        "    )"
      ],
      "metadata": {
        "id": "LKTSib2YX56g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%sql duckdb://"
      ],
      "metadata": {
        "id": "ObXW0TDvX-A0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "61caaac0-0885-4f51-e60d-91f0d019d3ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Querying"
      ],
      "metadata": {
        "id": "ocby-kz0XAVL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sql SELECT * FROM penguins.csv LIMIT 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "id": "FLYv9mgXYA7v",
        "outputId": "fe107cf7-ea6e-406d-893c-0ad330943aa4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "| species |   island  | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g |  sex   |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "|  Adelie | Torgersen |      39.1      |      18.7     |        181        |     3750    |  MALE  |\n",
              "|  Adelie | Torgersen |      39.5      |      17.4     |        186        |     3800    | FEMALE |\n",
              "|  Adelie | Torgersen |      40.3      |      18.0     |        195        |     3250    | FEMALE |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>species</th>\n",
              "            <th>island</th>\n",
              "            <th>bill_length_mm</th>\n",
              "            <th>bill_depth_mm</th>\n",
              "            <th>flipper_length_mm</th>\n",
              "            <th>body_mass_g</th>\n",
              "            <th>sex</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>39.1</td>\n",
              "            <td>18.7</td>\n",
              "            <td>181</td>\n",
              "            <td>3750</td>\n",
              "            <td>MALE</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>39.5</td>\n",
              "            <td>17.4</td>\n",
              "            <td>186</td>\n",
              "            <td>3800</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>40.3</td>\n",
              "            <td>18.0</td>\n",
              "            <td>195</td>\n",
              "            <td>3250</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT *\n",
        "FROM penguins.csv\n",
        "WHERE bill_length_mm > 40\n",
        "LIMIT 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "id": "HMrsAEpA2moL",
        "outputId": "df0751a8-5a42-41b0-ab86-647f20c73d9d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "| species |   island  | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g |  sex   |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "|  Adelie | Torgersen |      40.3      |      18.0     |        195        |     3250    | FEMALE |\n",
              "|  Adelie | Torgersen |      42.0      |      20.2     |        190        |     4250    |  None  |\n",
              "|  Adelie | Torgersen |      41.1      |      17.6     |        182        |     3200    | FEMALE |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>species</th>\n",
              "            <th>island</th>\n",
              "            <th>bill_length_mm</th>\n",
              "            <th>bill_depth_mm</th>\n",
              "            <th>flipper_length_mm</th>\n",
              "            <th>body_mass_g</th>\n",
              "            <th>sex</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>40.3</td>\n",
              "            <td>18.0</td>\n",
              "            <td>195</td>\n",
              "            <td>3250</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>42.0</td>\n",
              "            <td>20.2</td>\n",
              "            <td>190</td>\n",
              "            <td>4250</td>\n",
              "            <td>None</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>41.1</td>\n",
              "            <td>17.6</td>\n",
              "            <td>182</td>\n",
              "            <td>3200</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Saving queries"
      ],
      "metadata": {
        "id": "VnxjWO1-XLut"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save not_nulls --no-execute\n",
        "SELECT *\n",
        "FROM penguins.csv\n",
        "WHERE bill_length_mm IS NOT NULL\n",
        "AND bill_depth_mm IS NOT NULL"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "YkF4n-lC2qzI",
        "outputId": "64609a81-52e2-4f06-9f9b-38c8a6b8a8df"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Skipping execution..."
            ],
            "text/html": [
              "<span style=\"None\">Skipping execution...</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Plotting"
      ],
      "metadata": {
        "id": "4-bLawCYXPt5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot boxplot --column bill_length_mm bill_depth_mm --table not_nulls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "OYsyTYRpT5s8",
        "outputId": "dc87cc1a-6281-4a14-c9f7-e0b2b26fca78"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': \"Boxplot from 'not_nulls'\"}>"
            ]
          },
          "metadata": {},
          "execution_count": 113
        },
        {
          "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": [
        "%sqlplot histogram --column bill_length_mm bill_depth_mm --table not_nulls"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "RrAcXNdKUBIb",
        "outputId": "217f4f50-f74e-45e4-d56a-3a7970e84869"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': \"Histogram from 'not_nulls'\"}, ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 114
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### pandas integration"
      ],
      "metadata": {
        "id": "zszJ2xunXTGo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "result = %sql SELECT * FROM penguins.csv"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "ZFD56IvmUBbN",
        "outputId": "3ea13b69-c162-45e7-9aef-34fb3a266b97"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = result.DataFrame()"
      ],
      "metadata": {
        "id": "gm2ruCTBXc_Q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "GPrX-_IiXfo7",
        "outputId": "79f2ab8c-3e0b-4bcf-90c4-08c06cb0e82e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "3  Adelie  Torgersen             NaN            NaN                NaN   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "\n",
              "   body_mass_g     sex  \n",
              "0       3750.0    MALE  \n",
              "1       3800.0  FEMALE  \n",
              "2       3250.0  FEMALE  \n",
              "3          NaN    None  \n",
              "4       3450.0  FEMALE  "
            ],
            "text/html": [
              "\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>species</th>\n",
              "      <th>island</th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
              "      <th>flipper_length_mm</th>\n",
              "      <th>body_mass_g</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.1</td>\n",
              "      <td>18.7</td>\n",
              "      <td>181.0</td>\n",
              "      <td>3750.0</td>\n",
              "      <td>MALE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.5</td>\n",
              "      <td>17.4</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3800.0</td>\n",
              "      <td>FEMALE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>40.3</td>\n",
              "      <td>18.0</td>\n",
              "      <td>195.0</td>\n",
              "      <td>3250.0</td>\n",
              "      <td>FEMALE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>36.7</td>\n",
              "      <td>19.3</td>\n",
              "      <td>193.0</td>\n",
              "      <td>3450.0</td>\n",
              "      <td>FEMALE</td>\n",
              "    </tr>\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-33f05545-3a08-4b7d-8154-034719089bda button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-33f05545-3a08-4b7d-8154-034719089bda');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-e87a8548-f936-496a-b198-8fe582840323\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e87a8548-f936-496a-b198-8fe582840323')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e87a8548-f936-496a-b198-8fe582840323 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 344,\n  \"fields\": [\n    {\n      \"column\": \"species\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Adelie\",\n          \"Chinstrap\",\n          \"Gentoo\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"island\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Torgersen\",\n          \"Biscoe\",\n          \"Dream\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bill_length_mm\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.4595837139265315,\n        \"min\": 32.1,\n        \"max\": 59.6,\n        \"num_unique_values\": 164,\n        \"samples\": [\n          48.2,\n          49.8,\n          45.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"bill_depth_mm\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.9747931568167816,\n        \"min\": 13.1,\n        \"max\": 21.5,\n        \"num_unique_values\": 80,\n        \"samples\": [\n          16.9,\n          18.7,\n          18.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"flipper_length_mm\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.061713679356888,\n        \"min\": 172.0,\n        \"max\": 231.0,\n        \"num_unique_values\": 55,\n        \"samples\": [\n          201.0,\n          180.0,\n          212.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"body_mass_g\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 801.9545356980956,\n        \"min\": 2700.0,\n        \"max\": 6300.0,\n        \"num_unique_values\": 94,\n        \"samples\": [\n          4350.0,\n          4150.0,\n          3525.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"FEMALE\",\n          \"MALE\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Introduction"
      ],
      "metadata": {
        "id": "xGch_3YFYkJ8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite://\n",
        "CREATE TABLE languages (name, rating, change);\n",
        "INSERT INTO languages VALUES ('Python', 14.44, 2.48);\n",
        "INSERT INTO languages VALUES ('C', 13.13, 1.50);\n",
        "INSERT INTO languages VALUES ('Java', 11.59, 0.40);\n",
        "INSERT INTO languages VALUES ('C++', 10.00, 1.98);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "id": "v9mXEGDGXhtf",
        "outputId": "b44d2eaa-e5ae-4264-f358-e9f7f8cf1cab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1 rows affected."
            ],
            "text/html": [
              "<span style=\"color: green\">1 rows affected.</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1 rows affected."
            ],
            "text/html": [
              "<span style=\"color: green\">1 rows affected.</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1 rows affected."
            ],
            "text/html": [
              "<span style=\"color: green\">1 rows affected.</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1 rows affected."
            ],
            "text/html": [
              "<span style=\"color: green\">1 rows affected.</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "++\n",
              "||\n",
              "++\n",
              "++"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql SELECT * FROM languages"
      ],
      "metadata": {
        "id": "gnVlxTekYmkE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "1b06e8ea-74a6-4133-ae21-36b92ca3aa59"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+--------+--------+--------+\n",
              "|  name  | rating | change |\n",
              "+--------+--------+--------+\n",
              "| Python | 14.44  |  2.48  |\n",
              "|   C    | 13.13  |  1.5   |\n",
              "|  Java  | 11.59  |  0.4   |\n",
              "|  C++   |  10.0  |  1.98  |\n",
              "+--------+--------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>name</th>\n",
              "            <th>rating</th>\n",
              "            <th>change</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Python</td>\n",
              "            <td>14.44</td>\n",
              "            <td>2.48</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>C</td>\n",
              "            <td>13.13</td>\n",
              "            <td>1.5</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Java</td>\n",
              "            <td>11.59</td>\n",
              "            <td>0.4</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>C++</td>\n",
              "            <td>10.0</td>\n",
              "            <td>1.98</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result = _\n",
        "print(result)"
      ],
      "metadata": {
        "id": "Kq4XIx5lYqyu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6298920f-18c2-410f-a886-f2a7a8c82abf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Text(0.5, 24.0, 'Trip distance')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result.keys"
      ],
      "metadata": {
        "id": "Iz1bUXtpYwMP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "2f3ca980-b571-4a1f-d99d-6554ef386c54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "'Text' object has no attribute 'keys'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-121-bb762f7e1373>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m: 'Text' object has no attribute 'keys'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result[0][0]"
      ],
      "metadata": {
        "id": "NpokXjHBY3NJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "3584caff-1f3e-4a81-ec91-f8aa9db1805a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "'Text' object is not subscriptable",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-122-460da444203f>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: 'Text' object is not subscriptable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result[0].rating"
      ],
      "metadata": {
        "id": "NjQY_GndY5Q0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "cd1b30bc-cce9-4774-8dff-c7ec12815c5a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "'Text' object is not subscriptable",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-123-b1ae36c17a09>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrating\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: 'Text' object is not subscriptable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql select count(*) from languages"
      ],
      "metadata": {
        "id": "tfUTdFPPY7eo",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        },
        "outputId": "b0ecddd9-a880-452a-c4b4-4a72cdc56ea9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+----------+\n",
              "| count(*) |\n",
              "+----------+\n",
              "|    4     |\n",
              "+----------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>count(*)</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>4</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql sqlite:///one.db --alias one\n",
        "%sql sqlite:///two.db --alias two"
      ],
      "metadata": {
        "id": "v-pQyEgxY9aY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "e1e48249-e3d9-4f16-e6e2-b4f7bb4e0dd5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Connecting and switching to connection 'one'"
            ],
            "text/html": [
              "<span style=\"None\">Connecting and switching to connection &#x27;one&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Connecting and switching to connection 'two'"
            ],
            "text/html": [
              "<span style=\"None\">Connecting and switching to connection &#x27;two&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql"
      ],
      "metadata": {
        "id": "a_YJplFAZAD4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "6ea54a17-1f16-48a4-b9c5-a6225e7a677f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'two'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;two&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lang = %sql SELECT * FROM languages"
      ],
      "metadata": {
        "id": "9A2kZEhtZEw9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        },
        "outputId": "8ee4de21-0c46-4920-fbb6-bb4e63438946"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'two'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;two&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "RuntimeError: If using snippets, you may pass the --with argument explicitly.\n",
            "For more details please refer: https://jupysql.ploomber.io/en/latest/compose.html#with-argument\n",
            "\n",
            "\n",
            "Original error message from DB driver:\n",
            "(sqlite3.OperationalError) no such table: languages\n",
            "[SQL: SELECT * FROM languages]\n",
            "(Background on this error at: https://sqlalche.me/e/20/e3q8)\n",
            "\n",
            "If you need help solving this issue, send us a message: https://ploomber.io/community\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql lang= << SELECT *\n",
        "FROM languages"
      ],
      "metadata": {
        "id": "Ta1OHQtaZl1g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Install postgresql server\n",
        "!sudo apt-get -y -qq update\n",
        "!sudo apt-get -y -qq install postgresql\n",
        "!sudo service postgresql start\n",
        "\n",
        "# Setup a password `postgres` for username `postgres`\n",
        "!sudo -u postgres psql -U postgres -c \"ALTER USER postgres PASSWORD 'postgres';\""
      ],
      "metadata": {
        "id": "5fSlouatZqHr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%env TFIO_DEMO_DATABASE_NAME=postgres\n",
        "%env TFIO_DEMO_DATABASE_HOST=localhost\n",
        "%env TFIO_DEMO_DATABASE_PORT=5432\n",
        "%env TFIO_DEMO_DATABASE_USER=postgres\n",
        "%env TFIO_DEMO_DATABASE_PASS=postgres"
      ],
      "metadata": {
        "id": "5H0jqB2Mn-g1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### URL 文字列を安全に構築する"
      ],
      "metadata": {
        "id": "J4s4s-Q3dici"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from getpass import getpass\n",
        "\n",
        "password = getpass()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V1xPliazcWxU",
        "outputId": "9dd6a451-c32c-4ae9-adb2-f5299588c1a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "db_url = f\"postgresql://postgres:postgres@localhost/postgres\""
      ],
      "metadata": {
        "id": "dVPT_qgCcncb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sqlalchemy import create_engine\n",
        "\n",
        "engine = create_engine(db_url)"
      ],
      "metadata": {
        "id": "Ux8sVgn3dVS0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SQNrPeuCp5xW",
        "outputId": "6f76e1dd-3601-4a46-fe88-5c274bab69b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql engine"
      ],
      "metadata": {
        "id": "92RMsjZYp8Au",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6bd8fae6-6ca4-4430-f36f-d788afa2cd49"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "RuntimeError: (psycopg2.OperationalError) connection to server at \"localhost\" (127.0.0.1), port 5432 failed: Connection refused\n",
            "\tIs the server running on that host and accepting TCP/IP connections?\n",
            "connection to server at \"localhost\" (::1), port 5432 failed: Cannot assign requested address\n",
            "\tIs the server running on that host and accepting TCP/IP connections?\n",
            "\n",
            "(Background on this error at: https://sqlalche.me/e/20/e3q8)\n",
            "If you need help solving this issue, send us a message: https://ploomber.io/community\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### カスタム引数を URL に渡す"
      ],
      "metadata": {
        "id": "u6-Q2pblscPH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "id": "wG3x6LtAo4FO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%sql --connection_arguments '{\"timeout\":10}' sqlite://"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "qHt_vW2iseSz",
        "outputId": "4eaae97f-29e9-4d2b-9a27-88dfe19823a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 環境変数を介して接続する"
      ],
      "metadata": {
        "id": "tHG-w0WIsl93"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from getpass import getpass\n",
        "from os import environ\n",
        "\n",
        "password = getpass()\n",
        "environ[\"DATABASE_URL\"] = f\"postgresql://postgres:{password}@localhost/postgres\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RBKFdqYOsf9p",
        "outputId": "b48d4e18-309f-4146-fcec-bf985ac7beea"
      },
      "execution_count": null,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dKYkZyZRswiz",
        "outputId": "81833cca-6cb5-40fd-80da-ca5bee7b51f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "Bb1yaZIts78w",
        "outputId": "51accfd3-7469-4ddc-bbd1-9ea74872eab1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 既存のsqlalchemy.engine.Engineを使用"
      ],
      "metadata": {
        "id": "IT_VF3zztDLV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "from sqlalchemy.engine import create_engine"
      ],
      "metadata": {
        "id": "BnxoQSpGs92H"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "engine = create_engine(\"sqlite://\")"
      ],
      "metadata": {
        "id": "MI57hLMPtYx5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({\"x\": range(5)})\n",
        "df.to_sql(\"numbers\", engine)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TH3x_LBftbBD",
        "outputId": "517eb2ca-e006-4cd6-a9a3-064a526023b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-HuMPXB9uvlw",
        "outputId": "65094ca1-5bc3-410e-b178-5e883810191e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql engine"
      ],
      "metadata": {
        "id": "Hs3e-SFEuyFn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT * FROM numbers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 165
        },
        "id": "52OOcrgauz6o",
        "outputId": "b6da5479-073d-4530-bdb2-07606a6791b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+-------+---+\n",
              "| index | x |\n",
              "+-------+---+\n",
              "|   0   | 0 |\n",
              "|   1   | 1 |\n",
              "|   2   | 2 |\n",
              "|   3   | 3 |\n",
              "|   4   | 4 |\n",
              "+-------+---+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>index</th>\n",
              "            <th>x</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>0</td>\n",
              "            <td>0</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2</td>\n",
              "            <td>2</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>3</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>4</td>\n",
              "            <td>4</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## DBAPI 接続"
      ],
      "metadata": {
        "id": "Ua4D5PHEu8eI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import duckdb\n",
        "\n",
        "conn = duckdb.connect()"
      ],
      "metadata": {
        "id": "tbfRiWmcu1j8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%sql conn"
      ],
      "metadata": {
        "id": "hbknRvTqvANM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import urllib\n",
        "\n",
        "urllib.request.urlretrieve(\n",
        "    \"https://raw.githubusercontent.com/mwaskom/seaborn-data/master/penguins.csv\",\n",
        "    \"penguins.csv\",\n",
        ")"
      ],
      "metadata": {
        "id": "CwLfTZqpvB9W",
        "outputId": "39859d06-c816-435c-e374-6dd2b6e9b810",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('penguins.csv', <http.client.HTTPMessage at 0x7970b377f040>)"
            ]
          },
          "metadata": {},
          "execution_count": 145
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql select * from penguins.csv limit 3"
      ],
      "metadata": {
        "id": "hzTrIxRQvD7y",
        "outputId": "05b15f91-e3ce-428f-a537-f98487ed305c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'DuckDBPyConnection'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;DuckDBPyConnection&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "| species |   island  | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g |  sex   |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+\n",
              "|  Adelie | Torgersen |      39.1      |      18.7     |        181        |     3750    |  MALE  |\n",
              "|  Adelie | Torgersen |      39.5      |      17.4     |        186        |     3800    | FEMALE |\n",
              "|  Adelie | Torgersen |      40.3      |      18.0     |        195        |     3250    | FEMALE |\n",
              "+---------+-----------+----------------+---------------+-------------------+-------------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>species</th>\n",
              "            <th>island</th>\n",
              "            <th>bill_length_mm</th>\n",
              "            <th>bill_depth_mm</th>\n",
              "            <th>flipper_length_mm</th>\n",
              "            <th>body_mass_g</th>\n",
              "            <th>sex</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>39.1</td>\n",
              "            <td>18.7</td>\n",
              "            <td>181</td>\n",
              "            <td>3750</td>\n",
              "            <td>MALE</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>39.5</td>\n",
              "            <td>17.4</td>\n",
              "            <td>186</td>\n",
              "            <td>3800</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Adelie</td>\n",
              "            <td>Torgersen</td>\n",
              "            <td>40.3</td>\n",
              "            <td>18.0</td>\n",
              "            <td>195</td>\n",
              "            <td>3250</td>\n",
              "            <td>FEMALE</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 146
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "M4VgfuoMNvkN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from pathlib import Path\n",
        "from urllib.request import urlretrieve\n",
        "\n",
        "url = \"https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2021-01.parquet\"\n",
        "\n",
        "if not Path(\"yellow_tripdata_2021-01.parquet\").is_file():\n",
        "    urlretrieve(url, \"yellow_tripdata_2021-01.parquet\")"
      ],
      "metadata": {
        "id": "ZWpLN-r2vGIj"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VGCFsXFWNxPq",
        "outputId": "deb6d600-a423-463b-a9e6-0ece00efc056"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql duckdb://"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "UTFZCDsaOC8h",
        "outputId": "099e44ab-e04b-49aa-b688-f54fc9349d89"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT * FROM \"yellow_tripdata_2021-01.parquet\" LIMIT 3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "id": "juyb1Q8YOJpd",
        "outputId": "ebb33b39-1dac-4be3-9b11-d63cc9f093ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+\n",
              "| VendorID | tpep_pickup_datetime | tpep_dropoff_datetime | passenger_count | trip_distance | RatecodeID | store_and_fwd_flag | PULocationID | DOLocationID | payment_type | fare_amount | extra | mta_tax | tip_amount | tolls_amount | improvement_surcharge | total_amount | congestion_surcharge | airport_fee |\n",
              "+----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+\n",
              "|    1     | 2021-01-01 00:30:10  |  2021-01-01 00:36:12  |       1.0       |      2.1      |    1.0     |         N          |     142      |      43      |      2       |     8.0     |  3.0  |   0.5   |    0.0     |     0.0      |          0.3          |     11.8     |         2.5          |     None    |\n",
              "|    1     | 2021-01-01 00:51:20  |  2021-01-01 00:52:19  |       1.0       |      0.2      |    1.0     |         N          |     238      |     151      |      2       |     3.0     |  0.5  |   0.5   |    0.0     |     0.0      |          0.3          |     4.3      |         0.0          |     None    |\n",
              "|    1     | 2021-01-01 00:43:30  |  2021-01-01 01:11:06  |       1.0       |      14.7     |    1.0     |         N          |     132      |     165      |      1       |     42.0    |  0.5  |   0.5   |    8.65    |     0.0      |          0.3          |    51.95     |         0.0          |     None    |\n",
              "+----------+----------------------+-----------------------+-----------------+---------------+------------+--------------------+--------------+--------------+--------------+-------------+-------+---------+------------+--------------+-----------------------+--------------+----------------------+-------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>VendorID</th>\n",
              "            <th>tpep_pickup_datetime</th>\n",
              "            <th>tpep_dropoff_datetime</th>\n",
              "            <th>passenger_count</th>\n",
              "            <th>trip_distance</th>\n",
              "            <th>RatecodeID</th>\n",
              "            <th>store_and_fwd_flag</th>\n",
              "            <th>PULocationID</th>\n",
              "            <th>DOLocationID</th>\n",
              "            <th>payment_type</th>\n",
              "            <th>fare_amount</th>\n",
              "            <th>extra</th>\n",
              "            <th>mta_tax</th>\n",
              "            <th>tip_amount</th>\n",
              "            <th>tolls_amount</th>\n",
              "            <th>improvement_surcharge</th>\n",
              "            <th>total_amount</th>\n",
              "            <th>congestion_surcharge</th>\n",
              "            <th>airport_fee</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>2021-01-01 00:30:10</td>\n",
              "            <td>2021-01-01 00:36:12</td>\n",
              "            <td>1.0</td>\n",
              "            <td>2.1</td>\n",
              "            <td>1.0</td>\n",
              "            <td>N</td>\n",
              "            <td>142</td>\n",
              "            <td>43</td>\n",
              "            <td>2</td>\n",
              "            <td>8.0</td>\n",
              "            <td>3.0</td>\n",
              "            <td>0.5</td>\n",
              "            <td>0.0</td>\n",
              "            <td>0.0</td>\n",
              "            <td>0.3</td>\n",
              "            <td>11.8</td>\n",
              "            <td>2.5</td>\n",
              "            <td>None</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>2021-01-01 00:51:20</td>\n",
              "            <td>2021-01-01 00:52:19</td>\n",
              "            <td>1.0</td>\n",
              "            <td>0.2</td>\n",
              "            <td>1.0</td>\n",
              "            <td>N</td>\n",
              "            <td>238</td>\n",
              "            <td>151</td>\n",
              "            <td>2</td>\n",
              "            <td>3.0</td>\n",
              "            <td>0.5</td>\n",
              "            <td>0.5</td>\n",
              "            <td>0.0</td>\n",
              "            <td>0.0</td>\n",
              "            <td>0.3</td>\n",
              "            <td>4.3</td>\n",
              "            <td>0.0</td>\n",
              "            <td>None</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>2021-01-01 00:43:30</td>\n",
              "            <td>2021-01-01 01:11:06</td>\n",
              "            <td>1.0</td>\n",
              "            <td>14.7</td>\n",
              "            <td>1.0</td>\n",
              "            <td>N</td>\n",
              "            <td>132</td>\n",
              "            <td>165</td>\n",
              "            <td>1</td>\n",
              "            <td>42.0</td>\n",
              "            <td>0.5</td>\n",
              "            <td>0.5</td>\n",
              "            <td>8.65</td>\n",
              "            <td>0.0</td>\n",
              "            <td>0.3</td>\n",
              "            <td>51.95</td>\n",
              "            <td>0.0</td>\n",
              "            <td>None</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 150
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT COUNT(*) FROM \"yellow_tripdata_2021-01.parquet\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        },
        "id": "aPF5HMMKORZd",
        "outputId": "919742ee-02c1-4475-ab62-ac106e1bcfd7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+--------------+\n",
              "| count_star() |\n",
              "+--------------+\n",
              "|   1369769    |\n",
              "+--------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>count_star()</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1369769</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 151
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Boxplot"
      ],
      "metadata": {
        "id": "pFAHBo8rPKdo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot boxplot --table yellow_tripdata_2021-01.parquet --column trip_distance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "_zpcVXgGOVVp",
        "outputId": "14c95403-00e9-466f-a074-66b8a86fd2ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': \"'trip_distance' from 'yellow_tripdata_2021-01.parquet'\"}, ylabel='trip_distance'>"
            ]
          },
          "metadata": {},
          "execution_count": 152
        },
        {
          "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": [
        "%%sql\n",
        "SELECT percentile_disc(0.90) WITHIN GROUP (ORDER BY trip_distance),\n",
        "FROM 'yellow_tripdata_2021-01.parquet'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        },
        "id": "JIIYf3-zPNeb",
        "outputId": "4db49809-2aa6-4986-d3ff-e967bf55a418"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+--------------------------------------------+\n",
              "| quantile_disc(0.90 ORDER BY trip_distance) |\n",
              "+--------------------------------------------+\n",
              "|                    6.3                     |\n",
              "+--------------------------------------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>quantile_disc(0.90 ORDER BY trip_distance)</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>6.3</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save short_trips --no-execute\n",
        "SELECT *\n",
        "FROM \"yellow_tripdata_2021-01.parquet\"\n",
        "WHERE trip_distance < 6.3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "MYhamPZ-PRBN",
        "outputId": "bc7b7490-fb90-40c8-fc00-0f0cace35b93"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Skipping execution..."
            ],
            "text/html": [
              "<span style=\"None\">Skipping execution...</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot boxplot --table short_trips --column trip_distance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "vC79PbQTPT1h",
        "outputId": "c801cffd-880e-4515-dabb-a9f3d69bc256"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': \"'trip_distance' from 'short_trips'\"}, ylabel='trip_distance'>"
            ]
          },
          "metadata": {},
          "execution_count": 155
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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rX/9Ss2bNXPNmPBUdHa1Ro0YpPT1dN9xwg26++Wbt2LFDEydO1JVXXqlevXp5tJ4L+T1JTU3VkiVL9Morryg2NlYJCQm66qqrSvU6CiUlJalLly5upydLZ06Dl85cQ6VmzZq644471LRpU4WHh2vJkiVat26dXn75Za+2iUuUbecbAaX066+/Wt26dbMiIiIsSa5TMAtP/yzuVN+STk/u1q2btXDhQis5OdlyOp1WYmKi9fHHH5c608mTJ62hQ4daVatWtcLCwqybbrrJOnDgwHlPT964caPVs2dPq1atWpbT6bRiYmKsv/3tb26nc1qWZa1atcpKTU21goKC3Nb5888/W927d7cqVapkRUVFWT169LAOHjxYZLslnf5b3NfFsizrnXfesZo3b245nU6rcuXKVocOHazFixe7jVm2bJnVpUsXKyoqygoODrbq1q1r9enTp0h2T5zr9ORu3boV+5w9e/ZYd9xxh1WpUiUrODjYatmypTVv3rwiGSUV+Z6W9LNSUo7z+eSTT6zOnTtbMTExVlBQkFWrVi1r0KBB1qFDh867zcKMy5Ytc1v++uuvW4mJiVbFihWtatWqWQ8++KB17NgxtzEdOnSwGjduXGymkn5PPLF9+3arffv2VkhIiCXJdaryub4+JZ2ePHjwYGvGjBlWvXr1LKfTaTVv3tzttebl5VmPP/641bRpUysiIsIKCwuzmjZtak2cONHjvPAPDsvyciYXUE7Fx8crKSlJ8+bNszsKcElyOBwaPHhwme9hg39gjgoAADAWc1SAYpzvom8hISGua3IApuPnGeUZRQUoRo0aNc75eO/evTVt2rSLEwa4QPw8ozyjqMDveHLl2fNdEj02NtZHaYCyd7F/npn6CF9iMi0AADAWk2kBAICxyvWhn4KCAh08eFARERE+vfQzAAAoO5ZlKTs7W7Gxsee9UGO5LioHDx4s8imoAACgfDhw4IBq1qx5zjHluqhERERIOvNCIyMjbU4DAAA8kZWVpbi4ONf7+LmU66JSeLgnMjKSogIAQDnjybQNJtMCAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMYq1xd8A3BpKu4iUHzQO+Cf2KMCwCglXamSDx4F/BNFBYAxzldGKCuA/6GoADCCpyWEsgL4F4oKAAAwFkUFAAAYi6ICAACMRVEBAADGoqgAAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGPZXlR++eUX9erVS1WrVlVISIiaNGmi9evX2x0LAAAYoIKdGz927JjatGmja665RvPnz1d0dLR27dqlypUr2xkLAAAYwtai8uKLLyouLk5Tp051LUtISLAxEQAAMImth37+7//+Ty1atFCPHj0UExOj5s2b68033yxxfF5enrKystxuAADg0mVrUdm7d68mTZqkevXqaeHChXrwwQc1dOhQTZ8+vdjxY8eOVVRUlOsWFxd3kRMDAICLyWFZlmXXxoOCgtSiRQutWrXKtWzo0KFat26dVq9eXWR8Xl6e8vLyXPezsrIUFxenzMxMRUZGXpTMAMqGw+HweKyNf7YA+EBWVpaioqI8ev+2dY9KjRo11KhRI7dlDRs21P79+4sd73Q6FRkZ6XYDAACXLluLSps2bbRjxw63ZTt37lTt2rVtSgQAAExia1F59NFHtWbNGj3//PPavXu3PvjgA02ZMkWDBw+2MxYAADCErUXlyiuv1Jw5c/Thhx8qKSlJzzzzjMaPH6977rnHzlgAAMAQtk6mvVClmYwDwGxMpgX8R7mZTAsAAHAuFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwFkUFAAAYi6ICAACMRVEBAADGoqgAAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwlq1FJS0tTQ6Hw+2WmJhoZyQAAGCQCnYHaNy4sZYsWeK6X6GC7ZEAAIAhbG8FFSpUUPXq1T0am5eXp7y8PNf9rKyssooFAAAMYPsclV27dik2NlZ16tTRPffco/3795c4duzYsYqKinLd4uLiLmJSAABwsTksy7Ls2vj8+fN14sQJNWjQQIcOHVJ6erp++eUXbdmyRREREUXGF7dHJS4uTpmZmYqMjLyY0QH4mMPh8HisjX+2APhAVlaWoqKiPHr/trWonO348eOqXbu2XnnlFfXv3/+840vzQgGYjaIC+I/SvH/bfujnrypVqqT69etr9+7ddkcBAAAGMKqonDhxQnv27FGNGjXsjgIAAAxga1EZMWKEVqxYoYyMDK1atUrdu3dXYGCgevbsaWcsAABgCFtPT/7555/Vs2dPHT16VNHR0Wrbtq3WrFmj6OhoO2MBAABD2FpUZs6caefmAQCA4YyaowIAAPBXFBUAAGAsigoAADAWRQUAABjL9g8lBHBpyc3N1fbt28t0Gxs3bvTqeYmJiQoNDfVxGgBliaICwKe2b9+u1NTUMt2Gt+vfsGGDUlJSfJwGQFmiqADwqcTERG3YsKHUzytN+fBm/dKZbADKF4oKAJ8KDQ0t870W7BUB/AeTaQEYwdNPROaTkwH/QlEBYIzzlRBKCuB/KCoAjFJSGaGkAP6JogLAOJZluSbMbtiwgZIC+DGKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwFkUFAAAYi6ICAACMRVEBAADGoqgAAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsYwqKi+88IIcDoeGDRtmdxQAAGAAY4rKunXr9MYbbyg5OdnuKAAAwBBGFJUTJ07onnvu0ZtvvqnKlSvbHQcAABjCiKIyePBgdevWTZ06dTrnuLy8PGVlZbndAADApauC3QFmzpypjRs3at26decdO3bsWKWnp1+EVAAAwAS27lE5cOCAHnnkEb3//vsKDg4+7/hRo0YpMzPTdTtw4MBFSAkAAOxi6x6VDRs26PDhw0pJSXEty8/P18qVK/X6668rLy9PgYGBrsecTqecTqcdUQEAgA0uqKicOnVK+/btU926dVWhQulXdd111+mHH35wW9a3b18lJibqiSeecCspAADA/3hVVHJzc/Xwww9r+vTpkqSdO3eqTp06evjhh3X55Zdr5MiRHq0nIiJCSUlJbsvCwsJUtWrVIssBAID/8WqOyqhRo/Tdd99p+fLlbnNLOnXqpFmzZvksHAAA8G9e7VGZO3euZs2apauvvloOh8O1vHHjxtqzZ88FBVq+fPkFPR8AAFw6vNqjcuTIEcXExBRZnpOT41ZcAAAALoRXRaVFixb64osvXPcLy8lbb72lVq1a+SYZAADwe14d+nn++efVtWtXbd26VadPn9aECRO0detWrVq1SitWrPB1RgAA4Ke82qPStm1bbd68WadPn1aTJk20aNEixcTEaPXq1UpNTfV1RgAA4Ke8vo5K3bp19eabb/oyCwAAgBuv9qh8+eWXWrhwYZHlCxcu1Pz58y84FAAAgORlURk5cqTy8/OLLLcsy+OLvQEAAJyPV0Vl165datSoUZHliYmJ2r179wWHAgAAkLwsKlFRUdq7d2+R5bt371ZYWNgFhwIAAJC8LCq33HKLhg0b5nYV2t27d+uxxx7TzTff7LNwAADAv3lVVF566SWFhYUpMTFRCQkJSkhIUMOGDVW1alX97//+r68zAgAAP+XV6clRUVFatWqVFi9erO+++04hISFKTk5W+/btfZ0PAAD4Ma+vo+JwONS5c2d17tzZl3kAAABcvC4qS5cu1dKlS3X48GEVFBS4PfbOO+9ccDAAAACvikp6erqefvpptWjRQjVq1OATkwEAQJnwqqhMnjxZ06ZN07333uvrPAAAAC5enfVz6tQptW7d2tdZAAAA3HhVVO6//3598MEHvs4CAADgxqtDP3/88YemTJmiJUuWKDk5WRUrVnR7/JVXXvFJOAAA4N+8Kirff/+9mjVrJknasmWL22NMrAUAAL7iVVFZtmyZr3MAAAAU4dUcFQAAgIvB6wu+rV+/Xh999JH279+vU6dOuT02e/bsCw4GAADg1R6VmTNnqnXr1tq2bZvmzJmjP//8Uz/++KO++uorRUVF+TojAADwU14Vleeff16vvvqqPv/8cwUFBWnChAnavn277rzzTtWqVcvXGQEAgJ/yqqjs2bNH3bp1kyQFBQUpJydHDodDjz76qKZMmeLTgAAAwH95VVQqV66s7OxsSdLll1/uOkX5+PHjys3N9V06AADg17yaTNu+fXstXrxYTZo0UY8ePfTII4/oq6++0uLFi3Xdddf5OiMAAPBTXhWV119/XX/88Yck6cknn1TFihW1atUq3X777Xrqqad8GhAAAPgvr4pKlSpVXP8fEBCgkSNH+iwQAABAIa/mqAQGBurw4cNFlh89elSBgYEXHAoAAEDysqhYllXs8ry8PAUFBV1QIAAAgEKlOvTz2muvSTrzwYNvvfWWwsPDXY/l5+dr5cqVSkxM9G1CAADgt0pVVF599VVJZ/aoTJ482e0wT1BQkOLj4zV58mTfJgQAAH6rVEVl3759kqRrrrlGs2fPVuXKlcskFAAAgOTlHJVly5a5lZT8/Hxt3rxZx44d81kwAAAAr4rKsGHD9Pbbb0s6U1Lat2+vlJQUxcXFafny5b7MBwAA/JhXReXjjz9W06ZNJUmff/65MjIytH37dj366KN68sknfRoQAAD4L6+KytGjR1W9enVJ0pdffqkePXqofv366tevn3744QefBgQAAP7Lq6JSrVo1bd26Vfn5+VqwYIGuv/56SVJubi4XfAMAAD7j1SX0+/btqzvvvFM1atSQw+FQp06dJElr167lOioAAMBnvCoqaWlpSkpK0oEDB9SjRw85nU5JZy6tz+f+AAAAX/GqqEjSHXfcUWRZ7969S7WOSZMmadKkScrIyJAkNW7cWKNHj1bXrl29jQUAAC4hHheV1157TQMHDlRwcLDrUvolGTp0qEfrrFmzpl544QXVq1dPlmVp+vTpuuWWW7Rp0yY1btzY02gAAOAS5bBK+oTBsyQkJGj9+vWqWrWqEhISSl6hw6G9e/d6HahKlSoaN26c+vfvf96xWVlZioqKUmZmpiIjI73eJgDzbNy4UampqdqwYYNSUlLsjgPAh0rz/u3xHpXCy+ef/f++kp+fr48//lg5OTlq1apVsWPy8vKUl5fnup+VleXzHAAAwBxenZ7sSz/88IPCw8PldDr1wAMPaM6cOWrUqFGxY8eOHauoqCjXLS4u7iKnBQAAF5PHe1SGDx/u8UpfeeUVj8c2aNBAmzdvVmZmpj755BP17t1bK1asKLasjBo1yi1HVlYWZQUAgEuYx0Vl06ZNbvc3btyo06dPq0GDBpKknTt3KjAwUKmpqaUKEBQUpCuuuEKSlJqaqnXr1mnChAl64403iox1Op2uU6EBAMClz+OismzZMtf/v/LKK4qIiND06dNdn6J87Ngx9e3bV+3atbugQAUFBW7zUAAAgP/y6joqL7/8shYtWuQqKZJUuXJlPfvss+rcubMee+wxj9YzatQode3aVbVq1VJ2drY++OADLV++XAsXLvQmFgAAuMR4VVSysrJ05MiRIsuPHDmi7Oxsj9dz+PBh3XfffTp06JCioqKUnJyshQsXuj47CAAA+Devikr37t3Vt29fvfzyy2rZsqWkM5/z8/jjj+u2227zeD1vv/22N5sHAAB+wquiMnnyZI0YMUJ33323/vzzzzMrqlBB/fv317hx43waEAAA+C+vikpoaKgmTpyocePGac+ePZKkunXrKiwszG3czz//rNjYWAUE2H65FgAAUA55/aGEkhQWFqbk5OQSH2/UqJE2b96sOnXqXMhmAACAnyrTXR0efowQAABAsTgmAwAAjEVRAQAAxqKoAAAAY5VpUXE4HGW5egAAcIljMi0AADDWBZ2eLEkHDhyQJMXFxRV5bOvWrYqNjb3QTQAAAD/l1R6V06dP65///KeioqIUHx+v+Ph4RUVF6amnnnJdqVY6U14CAwN9FhYAAPgXr/aoPPzww5o9e7ZeeukltWrVSpK0evVqpaWl6ejRo5o0aZJPQwIAAP/kVVH54IMPNHPmTHXt2tW1LDk5WXFxcerZsydFBQAA+IRXh36cTqfi4+OLLE9ISFBQUNCFZgIAAJDkZVEZMmSInnnmGeXl5bmW5eXl6bnnntOQIUN8Fg4AAPg3rw79bNq0SUuXLlXNmjXVtGlTSdJ3332nU6dO6brrrtNtt93mGjt79mzfJAUAAH7Hq6JSqVIl3X777W7Lijs9GQAA4EJ4VVSmTp3q6xwAAABF8Fk/AADAWB7vUUlJSdHSpUtVuXJlNW/e/Jyf47Nx40afhAMAAP7N46Jyyy23yOl0SpJuvfXWssoDwCa7du1Sdna23TFctm3b5vZfU0RERKhevXp2xwD8hsMq5ScH5ufn65tvvlFycrIqVapURrE8k5WVpaioKGVmZioyMtLWLEB5tmvXLtWvX9/uGOXGzp07KSvABSjN+3epJ9MGBgaqc+fO2rZtm+1FBYBvFO5JmTFjhho2bGhzmjNOnjypjIwMxcfHKyQkxO44ks7s3enVq5dRe56AS51XZ/0kJSVp7969SkhI8HUeADZq2LChUlJS7I7h0qZNG7sjALCZV2f9PPvssxoxYoTmzZunQ4cOKSsry+0GAADgC17tUbnxxhslSTfffLPb2T+WZcnhcCg/P9836QAAgF/z+oJvcXFxCgwMdFteUFCg/fv3+yQYAACAV0WlX79+OnTokGJiYtyWHz16VJ06dVLv3r19Eg4AAPg3r+aoFB7iOduJEycUHBx8waEAAACkUu5RGT58uCTJ4XDon//8p0JDQ12P5efna+3atWrWrJlPAwIAAP9VqqKyadMmSWf2qPzwww8KCgpyPRYUFKSmTZtqxIgRvk0IAAD8VqmKyrJlyyRJffv21YQJE7gaLAAAKFNen/UDAABQ1ryaTAsAAHAxUFQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLFsLSpjx47VlVdeqYiICMXExOjWW2/Vjh077IwEAAAMYmtRWbFihQYPHqw1a9Zo8eLF+vPPP9W5c2fl5OTYGQsAABjCqw8l9JUFCxa43Z82bZpiYmK0YcMGtW/f3qZUAADAFLYWlbNlZmZKkqpUqVLs43l5ecrLy3Pdz8rKuii5AACAPYyZTFtQUKBhw4apTZs2SkpKKnbM2LFjFRUV5brFxcVd5JQAAOBiMqaoDB48WFu2bNHMmTNLHDNq1ChlZma6bgcOHLiICQEAwMVmxKGfIUOGaN68eVq5cqVq1qxZ4jin0ymn03kRkwEAADvZWlQsy9LDDz+sOXPmaPny5UpISLAzDgAAMIytRWXw4MH64IMP9NlnnykiIkK//vqrJCkqKkohISF2RgMAAAawdY7KpEmTlJmZqY4dO6pGjRqu26xZs+yMBQAADGH7oR8AAICSGHPWDwAAwNkoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwFkUFAAAYi6ICAACMRVEBAADGoqgAAABjUVQAAICxKtgdAID9HKf/UPPqAQo5vlM6yL9fShJyfKeaVw+Q4/QfdkcB/AZFBYCCT+zXxkHh0spB0kq705iroaSNg8K17cR+Sa3tjgP4BYoKAP0RXkspb5zQ+++/r4aJiXbHMda27dt1zz336O0ba9kdBfAbFBUAsioEa9OvBTpZqb4U28zuOMY6+WuBNv1aIKtCsN1RAL/BwWgAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwFkUFAAAYi6ICAACMRVEBAADGsrWorFy5UjfddJNiY2PlcDg0d+5cO+MAAADD2FpUcnJy1LRpU/373/+2MwYAADBUBTs33rVrV3Xt2tXOCAAAwGC2FpXSysvLU15enut+VlaWjWkAAEBZK1eTaceOHauoqCjXLS4uzu5IAACgDJWrojJq1ChlZma6bgcOHLA7EgAAKEPl6tCP0+mU0+m0OwZwycnNzZUkbdy40eYk/8/JkyeVkZGh+Ph4hYSE2B1HkrRt2za7IwB+p1wVFQBlY/v27ZKkAQMG2JykfIiIiLA7AuA3bC0qJ06c0O7du1339+3bp82bN6tKlSqqVauWjckA/3LrrbdKkhITExUaGmpvmP/ftm3b1KtXL82YMUMNGza0O45LRESE6tWrZ3cMwG/YWlTWr1+va665xnV/+PDhkqTevXtr2rRpNqUC/M9ll12m+++/3+4YxWrYsKFSUlLsjgHAJrYWlY4dO8qyLDsjAAAAg5Wrs34AAIB/oagAAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLIoKAAAwFkUFAAAYi6ICAACMRVEBAADGoqgAAABjUVQAAICxKCoAAMBYFBUAAGAsigoAADAWRQUAABiLogIAAIxFUQEAAMaiqAAAAGNRVAAAgLEoKgAAwFgUFQAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsYwoKv/+978VHx+v4OBgXXXVVfr222/tjgQAAAxge1GZNWuWhg8frjFjxmjjxo1q2rSpunTposOHD9sdDQAA2KyC3QFeeeUVDRgwQH379pUkTZ48WV988YXeeecdjRw50m1sXl6e8vLyXPezsrIualYA55ebm6vt27df8Hq2bdvm9l9fSExMVGhoqM/WB6Ds2VpUTp06pQ0bNmjUqFGuZQEBAerUqZNWr15dZPzYsWOVnp5+MSMCKKXt27crNTXVZ+vr1auXz9a1YcMGpaSk+Gx9AMqerUXl999/V35+vqpVq+a2vFq1asX+i2zUqFEaPny4635WVpbi4uLKPCcAzyUmJmrDhg0XvJ6TJ08qIyND8fHxCgkJ8UGyM9kAlC+2H/opDafTKafTaXcMAOcQGhrqs70Wbdq08cl6AJRftk6mveyyyxQYGKjffvvNbflvv/2m6tWr25QKAACYwtaiEhQUpNTUVC1dutS1rKCgQEuXLlWrVq1sTAYAAExg+6Gf4cOHq3fv3mrRooVatmyp8ePHKycnx3UWEAAA8F+2F5W77rpLR44c0ejRo/Xrr7+qWbNmWrBgQZEJtgAAwP84LMuy7A7hraysLEVFRSkzM1ORkZF2xwEAAB4ozfu37VemBQAAKAlFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsSgqAADAWBQVAABgLNuvTHshCq9Vl5WVZXMSAADgqcL3bU+uOVuui0p2drYkKS4uzuYkAACgtLKzsxUVFXXOMeX6EvoFBQU6ePCgIiIi5HA47I4DwIeysrIUFxenAwcO8BEZwCXGsixlZ2crNjZWAQHnnoVSrosKgEsXn+UFQGIyLQAAMBhFBQAAGIuiAsBITqdTY8aMkdPptDsKABsxRwUAABiLPSoAAMBYFBUAAGAsigoAADAWRQUAABiLogKgWGlpaWrWrFmZbqNjx44aNmyY6358fLzGjx9fptsEUL5QVAA/c3Y5KMmIESO0dOnSsg/0F+vWrdPAgQM9GkupAfxDuf5QQgC+Z1mW8vPzFR4ervDw8Iu67ejo6Iu6PQDmY48K4Ef69OmjFStWaMKECXI4HHI4HJo2bZocDofmz5+v1NRUOZ1Off3110UO/fTp00e33nqr0tPTFR0drcjISD3wwAM6deqUR9vOycnRfffdp/DwcNWoUUMvv/xykTF/3UtiWZbS0tJUq1YtOZ1OxcbGaujQoZLO7BX66aef9Oijj7pehyQdPXpUPXv21OWXX67Q0FA1adJEH374ods2OnbsqKFDh+of//iHqlSpourVqystLc1tzPHjxzVo0CBVq1ZNwcHBSkpK0rx581yPf/3112rXrp1CQkIUFxenoUOHKicnx6OvA4DSoagAfmTChAlq1aqVBgwYoEOHDunQoUOKi4uTJI0cOVIvvPCCtm3bpuTk5GKfv3TpUm3btk3Lly/Xhx9+qNmzZys9Pd2jbT/++ONasWKFPvvsMy1atEjLly/Xxo0bSxz/6aef6tVXX9Ubb7yhXbt2ae7cuWrSpIkkafbs2apZs6aefvpp1+uQpD/++EOpqan64osvtGXLFg0cOFD33nuvvv32W7d1T58+XWFhYVq7dq1eeuklPf3001q8eLGkM5/K3rVrV33zzTeaMWOGtm7dqhdeeEGBgYGSpD179uiGG27Q7bffru+//16zZs3S119/rSFDhnj0dQBQShYAv9KhQwfrkUcecd1ftmyZJcmaO3eu27gxY8ZYTZs2dd3v3bu3VaVKFSsnJ8e1bNKkSVZ4eLiVn59/zm1mZ2dbQUFB1kcffeRadvToUSskJMQtS+3ata1XX33VsizLevnll6369etbp06dKnadfx17Lt26dbMee+wx1/0OHTpYbdu2dRtz5ZVXWk888YRlWZa1cOFCKyAgwNqxY0ex6+vfv781cOBAt2X/+c9/rICAAOvkyZPnzQOgdNijAkCS1KJFi/OOadq0qUJDQ133W7VqpRMnTujAgQPnfN6ePXt06tQpXXXVVa5lVapUUYMGDUp8To8ePXTy5EnVqVNHAwYM0Jw5c3T69Olzbic/P1/PPPOMmjRpoipVqig8PFwLFy7U/v373cadvceoRo0aOnz4sCRp8+bNqlmzpurXr1/sNr777jtNmzbNNYcnPDxcXbp0UUFBgfbt23fOfABKj8m0ACRJYWFhdkdwExcXpx07dmjJkiVavHixHnroIY0bN04rVqxQxYoVi33OuHHjNGHCBI0fP15NmjRRWFiYhg0bVmQezdnPdzgcKigokCSFhIScM9eJEyc0aNAg13yZv6pVq1ZpXiIAD1BUAD8TFBSk/Px8r5773Xff6eTJk6438zVr1ig8PNw1z6UkdevWVcWKFbV27VrXm/mxY8e0c+dOdejQocTnhYSE6KabbtJNN92kwYMHKzExUT/88INSUlKKfR3ffPONbrnlFvXq1UvSmfkmO3fuVKNGjTx+jcnJyfr555+1c+fOYveqpKSkaOvWrbriiis8XicA73HoB/Az8fHxWrt2rTIyMvT777+79iR44tSpU+rfv7+2bt2qL7/8UmPGjNGQIUMUEHDuPyXh4eHq37+/Hn/8cX311VfasmWL+vTpc87nTZs2TW+//ba2bNmivXv3asaMGQoJCVHt2rVdr2PlypX65Zdf9Pvvv0uS6tWrp8WLF2vVqlXatm2bBg0apN9++83j1ydJHTp0UPv27XX77bdr8eLF2rdvn+bPn68FCxZIkp544gmtWrVKQ4YM0ebNm7Vr1y599tlnTKYFyghFBfAzI0aMUGBgoBo1aqTo6Ogi8zfO5brrrlO9evXUvn173XXXXbr55puLnNpbknHjxqldu3a66aab1KlTJ7Vt21apqakljq9UqZLefPNNtWnTRsnJyVqyZIk+//xzVa1aVZL09NNPKyMjQ3Xr1nVdf+Wpp55SSkqKunTpoo4dO6p69eq69dZbPX59hT799FNdeeWV6tmzpxo1aqR//OMfrr03ycnJWrFihXbu3Kl27dqpefPmGj16tGJjY0u9HQDn57Asy7I7BADz9enTR8ePH9fcuXPtjgLAj7BHBQAAGIuiAuCC7d+/3+103bNvpTm8BAB/xaEfABfs9OnTysjIKPHx+Ph4VajASYYASo+iAgAAjMWhHwAAYCyKCgAAMBZFBQAAGIuiAgAAjEVRAQAAxqKoAAAAY1FUAACAsf4/6tzLlNmHfVQAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Histogram"
      ],
      "metadata": {
        "id": "5E_bFkKhQvSg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot histogram --table short_trips --column trip_distance --bins 10"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 489
        },
        "id": "abzoMM0HPZZ7",
        "outputId": "102eef64-5438-4617-cf11-a615fb477f49"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': \"'trip_distance' from 'short_trips'\"}, xlabel='trip_distance', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 156
        },
        {
          "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": [
        "ax = %sqlplot histogram --table short_trips --column trip_distance --bins 50\n",
        "ax.grid()\n",
        "ax.set_title(\"Trip distance from trips < 6.3\")\n",
        "_ = ax.set_xlabel(\"Trip distance\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "-t-io0q4QjGs",
        "outputId": "806f6a69-d579-46a9-8106-91c2f6a28e11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Bar plot"
      ],
      "metadata": {
        "id": "aix0TSQ1RAi7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot bar --table short_trips --column payment_type"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 507
        },
        "id": "t0eAsPf8Q9Y6",
        "outputId": "b015dba6-4598-4963-932c-7f9e80cd41c6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Removing NULLs, if there exists any from payment_type"
            ],
            "text/html": [
              "<span style=\"None\">Removing NULLs, if there exists any from payment_type</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'short_trips'}, xlabel='payment_type', ylabel='Count'>"
            ]
          },
          "metadata": {},
          "execution_count": 158
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Pie plot"
      ],
      "metadata": {
        "id": "0F2HlHhofGoX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%sqlplot pie --table short_trips --column payment_type"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 463
        },
        "id": "c9ZbnVEFRCvF",
        "outputId": "57678917-9034-46f0-d21e-3d457bf64f31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Removing NULLs, if there exists any from payment_type"
            ],
            "text/html": [
              "<span style=\"None\">Removing NULLs, if there exists any from payment_type</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: title={'center': 'short_trips'}>"
            ]
          },
          "metadata": {},
          "execution_count": 159
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Organizing Large Queries\\"
      ],
      "metadata": {
        "id": "xpBAMnoUh7F_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import urllib.request\n",
        "from pathlib import Path\n",
        "\n",
        "if not Path(\"my.db\").is_file():\n",
        "    url = \"https://raw.githubusercontent.com/lerocha/chinook-database/master/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite\"  # noqa\n",
        "    urllib.request.urlretrieve(url, \"my.db\")"
      ],
      "metadata": {
        "id": "pUEXOf5-h0eh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext sql"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mjOL4aISh-mV",
        "outputId": "b3b54018-fcd6-4256-a60e-0495d8b49ee2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The sql extension is already loaded. To reload it, use:\n",
            "  %reload_ext sql\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%config SqlMagic.autolimit = 3"
      ],
      "metadata": {
        "id": "-QY_kpG7iAd1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql sqlite:///my.db\n",
        "SELECT * FROM Track"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "id": "-syosZTziD30",
        "outputId": "35342759-3727-42b7-f532-5c26fbb6465b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+\n",
              "| TrackId |                   Name                  | AlbumId | MediaTypeId | GenreId |                                Composer                                | Milliseconds |  Bytes   | UnitPrice |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+\n",
              "|    1    | For Those About To Rock (We Salute You) |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    343719    | 11170334 |    0.99   |\n",
              "|    2    |            Balls to the Wall            |    2    |      2      |    1    |                                  None                                  |    342562    | 5510424  |    0.99   |\n",
              "|    3    |             Fast As a Shark             |    3    |      2      |    1    |          F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman           |    230619    | 3990994  |    0.99   |\n",
              "|    4    |            Restless and Wild            |    3    |      2      |    1    | F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman |    252051    | 4331779  |    0.99   |\n",
              "|    5    |           Princess of the Dawn          |    3    |      2      |    1    |                       Deaffy & R.A. Smith-Diesel                       |    375418    | 6290521  |    0.99   |\n",
              "|    6    |          Put The Finger On You          |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    205662    | 6713451  |    0.99   |\n",
              "|    7    |             Let's Get It Up             |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    233926    | 7636561  |    0.99   |\n",
              "|    8    |             Inject The Venom            |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    210834    | 6852860  |    0.99   |\n",
              "|    9    |                Snowballed               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    203102    | 6599424  |    0.99   |\n",
              "|    10   |                Evil Walks               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    263497    | 8611245  |    0.99   |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>TrackId</th>\n",
              "            <th>Name</th>\n",
              "            <th>AlbumId</th>\n",
              "            <th>MediaTypeId</th>\n",
              "            <th>GenreId</th>\n",
              "            <th>Composer</th>\n",
              "            <th>Milliseconds</th>\n",
              "            <th>Bytes</th>\n",
              "            <th>UnitPrice</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>For Those About To Rock (We Salute You)</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>343719</td>\n",
              "            <td>11170334</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2</td>\n",
              "            <td>Balls to the Wall</td>\n",
              "            <td>2</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>None</td>\n",
              "            <td>342562</td>\n",
              "            <td>5510424</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>Fast As a Shark</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>230619</td>\n",
              "            <td>3990994</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>4</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>252051</td>\n",
              "            <td>4331779</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>5</td>\n",
              "            <td>Princess of the Dawn</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>Deaffy & R.A. Smith-Diesel</td>\n",
              "            <td>375418</td>\n",
              "            <td>6290521</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>6</td>\n",
              "            <td>Put The Finger On You</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>205662</td>\n",
              "            <td>6713451</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>7</td>\n",
              "            <td>Let's Get It Up</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>233926</td>\n",
              "            <td>7636561</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>8</td>\n",
              "            <td>Inject The Venom</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>210834</td>\n",
              "            <td>6852860</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>9</td>\n",
              "            <td>Snowballed</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>203102</td>\n",
              "            <td>6599424</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>10</td>\n",
              "            <td>Evil Walks</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>263497</td>\n",
              "            <td>8611245</td>\n",
              "            <td>0.99</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save tracks_with_info\n",
        "SELECT t.*, a.title AS album, ar.Name as artist\n",
        "FROM Track t\n",
        "JOIN Album a\n",
        "USING (AlbumId)\n",
        "JOIN Artist ar\n",
        "USING (ArtistId)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 410
        },
        "id": "GblyJRfFiFo_",
        "outputId": "c94fdcd5-565d-4d09-e872-ffb5335df64f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+\n",
              "| TrackId |                   Name                  | AlbumId | MediaTypeId | GenreId |                                Composer                                | Milliseconds |  Bytes   | UnitPrice |                 album                 | artist |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+\n",
              "|    1    | For Those About To Rock (We Salute You) |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    343719    | 11170334 |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    2    |            Balls to the Wall            |    2    |      2      |    1    |                                  None                                  |    342562    | 5510424  |    0.99   |           Balls to the Wall           | Accept |\n",
              "|    3    |             Fast As a Shark             |    3    |      2      |    1    |          F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman           |    230619    | 3990994  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    4    |            Restless and Wild            |    3    |      2      |    1    | F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman |    252051    | 4331779  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    5    |           Princess of the Dawn          |    3    |      2      |    1    |                       Deaffy & R.A. Smith-Diesel                       |    375418    | 6290521  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    6    |          Put The Finger On You          |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    205662    | 6713451  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    7    |             Let's Get It Up             |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    233926    | 7636561  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    8    |             Inject The Venom            |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    210834    | 6852860  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    9    |                Snowballed               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    203102    | 6599424  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    10   |                Evil Walks               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    263497    | 8611245  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>TrackId</th>\n",
              "            <th>Name</th>\n",
              "            <th>AlbumId</th>\n",
              "            <th>MediaTypeId</th>\n",
              "            <th>GenreId</th>\n",
              "            <th>Composer</th>\n",
              "            <th>Milliseconds</th>\n",
              "            <th>Bytes</th>\n",
              "            <th>UnitPrice</th>\n",
              "            <th>album</th>\n",
              "            <th>artist</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>For Those About To Rock (We Salute You)</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>343719</td>\n",
              "            <td>11170334</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2</td>\n",
              "            <td>Balls to the Wall</td>\n",
              "            <td>2</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>None</td>\n",
              "            <td>342562</td>\n",
              "            <td>5510424</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Balls to the Wall</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>Fast As a Shark</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>230619</td>\n",
              "            <td>3990994</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>4</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>252051</td>\n",
              "            <td>4331779</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>5</td>\n",
              "            <td>Princess of the Dawn</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>Deaffy & R.A. Smith-Diesel</td>\n",
              "            <td>375418</td>\n",
              "            <td>6290521</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>6</td>\n",
              "            <td>Put The Finger On You</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>205662</td>\n",
              "            <td>6713451</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>7</td>\n",
              "            <td>Let's Get It Up</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>233926</td>\n",
              "            <td>7636561</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>8</td>\n",
              "            <td>Inject The Venom</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>210834</td>\n",
              "            <td>6852860</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>9</td>\n",
              "            <td>Snowballed</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>203102</td>\n",
              "            <td>6599424</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>10</td>\n",
              "            <td>Evil Walks</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>263497</td>\n",
              "            <td>8611245</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 164
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save genres_fav\n",
        "SELECT * FROM Genre\n",
        "WHERE Name\n",
        "LIKE '%rock%'\n",
        "OR Name LIKE '%metal%'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "AjaNXJIqop-K",
        "outputId": "3b1c0cf6-562e-41b2-a04a-5fbdecd2014c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+---------------+\n",
              "| GenreId |      Name     |\n",
              "+---------+---------------+\n",
              "|    1    |      Rock     |\n",
              "|    3    |     Metal     |\n",
              "|    5    | Rock And Roll |\n",
              "|    13   |  Heavy Metal  |\n",
              "+---------+---------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>GenreId</th>\n",
              "            <th>Name</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>Rock</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>Metal</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>5</td>\n",
              "            <td>Rock And Roll</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>13</td>\n",
              "            <td>Heavy Metal</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save genres_fav\n",
        "SELECT * FROM Genre\n",
        "WHERE Name\n",
        "LIKE '%rock%'\n",
        "OR Name LIKE '%metal%'"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "2bwGaYE3osP4",
        "outputId": "d90c5725-5b88-479c-a9f8-028e72380a7d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+---------------+\n",
              "| GenreId |      Name     |\n",
              "+---------+---------------+\n",
              "|    1    |      Rock     |\n",
              "|    3    |     Metal     |\n",
              "|    5    | Rock And Roll |\n",
              "|    13   |  Heavy Metal  |\n",
              "+---------+---------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>GenreId</th>\n",
              "            <th>Name</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>Rock</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>Metal</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>5</td>\n",
              "            <td>Rock And Roll</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>13</td>\n",
              "            <td>Heavy Metal</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save track_fav\n",
        "SELECT t.*\n",
        "FROM tracks_with_info t\n",
        "JOIN genres_fav\n",
        "ON t.GenreId = genres_fav.GenreId"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 428
        },
        "id": "GjbVU2WMouIJ",
        "outputId": "fa246bcf-d202-4b4e-c95e-5e36d18bbbb0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating CTE with stored snippets: 'genres_fav', and 'tracks_with_info'"
            ],
            "text/html": [
              "<span style=\"None\">Generating CTE with stored snippets: &#x27;genres_fav&#x27;, and &#x27;tracks_with_info&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+\n",
              "| TrackId |                   Name                  | AlbumId | MediaTypeId | GenreId |                                Composer                                | Milliseconds |  Bytes   | UnitPrice |                 album                 | artist |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+\n",
              "|    1    | For Those About To Rock (We Salute You) |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    343719    | 11170334 |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    2    |            Balls to the Wall            |    2    |      2      |    1    |                                  None                                  |    342562    | 5510424  |    0.99   |           Balls to the Wall           | Accept |\n",
              "|    3    |             Fast As a Shark             |    3    |      2      |    1    |          F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman           |    230619    | 3990994  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    4    |            Restless and Wild            |    3    |      2      |    1    | F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman |    252051    | 4331779  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    5    |           Princess of the Dawn          |    3    |      2      |    1    |                       Deaffy & R.A. Smith-Diesel                       |    375418    | 6290521  |    0.99   |           Restless and Wild           | Accept |\n",
              "|    6    |          Put The Finger On You          |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    205662    | 6713451  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    7    |             Let's Get It Up             |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    233926    | 7636561  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    8    |             Inject The Venom            |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    210834    | 6852860  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    9    |                Snowballed               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    203102    | 6599424  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "|    10   |                Evil Walks               |    1    |      1      |    1    |               Angus Young, Malcolm Young, Brian Johnson                |    263497    | 8611245  |    0.99   | For Those About To Rock We Salute You | AC/DC  |\n",
              "+---------+-----------------------------------------+---------+-------------+---------+------------------------------------------------------------------------+--------------+----------+-----------+---------------------------------------+--------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>TrackId</th>\n",
              "            <th>Name</th>\n",
              "            <th>AlbumId</th>\n",
              "            <th>MediaTypeId</th>\n",
              "            <th>GenreId</th>\n",
              "            <th>Composer</th>\n",
              "            <th>Milliseconds</th>\n",
              "            <th>Bytes</th>\n",
              "            <th>UnitPrice</th>\n",
              "            <th>album</th>\n",
              "            <th>artist</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>For Those About To Rock (We Salute You)</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>343719</td>\n",
              "            <td>11170334</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>2</td>\n",
              "            <td>Balls to the Wall</td>\n",
              "            <td>2</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>None</td>\n",
              "            <td>342562</td>\n",
              "            <td>5510424</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Balls to the Wall</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>3</td>\n",
              "            <td>Fast As a Shark</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>230619</td>\n",
              "            <td>3990994</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>4</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>F. Baltes, R.A. Smith-Diesel, S. Kaufman, U. Dirkscneider & W. Hoffman</td>\n",
              "            <td>252051</td>\n",
              "            <td>4331779</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>5</td>\n",
              "            <td>Princess of the Dawn</td>\n",
              "            <td>3</td>\n",
              "            <td>2</td>\n",
              "            <td>1</td>\n",
              "            <td>Deaffy & R.A. Smith-Diesel</td>\n",
              "            <td>375418</td>\n",
              "            <td>6290521</td>\n",
              "            <td>0.99</td>\n",
              "            <td>Restless and Wild</td>\n",
              "            <td>Accept</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>6</td>\n",
              "            <td>Put The Finger On You</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>205662</td>\n",
              "            <td>6713451</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>7</td>\n",
              "            <td>Let's Get It Up</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>233926</td>\n",
              "            <td>7636561</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>8</td>\n",
              "            <td>Inject The Venom</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>210834</td>\n",
              "            <td>6852860</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>9</td>\n",
              "            <td>Snowballed</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>203102</td>\n",
              "            <td>6599424</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>10</td>\n",
              "            <td>Evil Walks</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>1</td>\n",
              "            <td>Angus Young, Malcolm Young, Brian Johnson</td>\n",
              "            <td>263497</td>\n",
              "            <td>8611245</td>\n",
              "            <td>0.99</td>\n",
              "            <td>For Those About To Rock We Salute You</td>\n",
              "            <td>AC/DC</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save top_artist\n",
        "SELECT artist, COUNT(*) FROM track_fav\n",
        "GROUP BY artist\n",
        "ORDER BY COUNT(*) DESC"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "od9aArneo1tu",
        "outputId": "ec2d1f55-f08f-422e-cbc7-b339c4b4d14e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating CTE with stored snippets: 'track_fav'"
            ],
            "text/html": [
              "<span style=\"None\">Generating CTE with stored snippets: &#x27;track_fav&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------------+----------+\n",
              "|     artist    | COUNT(*) |\n",
              "+---------------+----------+\n",
              "|  Iron Maiden  |   204    |\n",
              "|  Led Zeppelin |   114    |\n",
              "|       U2      |   112    |\n",
              "|   Metallica   |   112    |\n",
              "|  Deep Purple  |    92    |\n",
              "|   Pearl Jam   |    54    |\n",
              "|   Van Halen   |    52    |\n",
              "|     Queen     |    45    |\n",
              "| Lenny Kravitz |    44    |\n",
              "| Guns N' Roses |    42    |\n",
              "+---------------+----------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>artist</th>\n",
              "            <th>COUNT(*)</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Iron Maiden</td>\n",
              "            <td>204</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Led Zeppelin</td>\n",
              "            <td>114</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>U2</td>\n",
              "            <td>112</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Metallica</td>\n",
              "            <td>112</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Deep Purple</td>\n",
              "            <td>92</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Pearl Jam</td>\n",
              "            <td>54</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Van Halen</td>\n",
              "            <td>52</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Queen</td>\n",
              "            <td>45</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Lenny Kravitz</td>\n",
              "            <td>44</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Guns N' Roses</td>\n",
              "            <td>42</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 169
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_artist = %sql SELECT * FROM top_artist\n",
        "top_artist.bar()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 753
        },
        "id": "o0ROVy53o3-T",
        "outputId": "a2c83773-0657-4337-c22d-1fd8b8a7f06d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating CTE with stored snippets: 'top_artist'"
            ],
            "text/html": [
              "<span style=\"None\">Generating CTE with stored snippets: &#x27;top_artist&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sql/run/resultset.py:373: UserWarning: .bar() is deprecated and will be removed in a future version. Use %sqlplot bar instead. For more help, find us at https://ploomber.io/community \n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='artist', ylabel='COUNT(*)'>"
            ]
          },
          "metadata": {},
          "execution_count": 170
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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FpEmTXrmu5ORkMXz48A+RbCIiIqIP4l8HddevXxfXrl0TT58+Fba2tsLf318YGBi8y7RJ2dnZonHjxgKAmDlzpsa8xMRE+f+AgAChr68vOnfuLJKTk1+ZnqSkJI3vpaenC1dX1/eSdiIiIqIPoVBB3dWrV8XMmTPF8uXLxY0bNwQAOU9fX19UrFhRdOrUScTHxwul8t2U7KoDumvXrokdO3Zo5NIVpEyZMiInJ0dcvXpV+Pj4FLiMgYHBewtAiYiIiIrCW0dePXr0EIGBgeLKlSti1KhR4vTp0yItLU1kZWWJO3fuiE2bNonIyEgxZMgQERAQIA4dOvSfE6cO6C5cuCC2bdsmrK2t3/id48ePC6VSKezs7P7z9omIiIg+FW+dU2diYiIuX75cYGBlZ2cnqlSpIqpUqSKGDh0qNm/eLP766y8RHh7+2nU+efJEXLx4Uf595coVcfz4caFSqYSjo6No2LChOHr0qNiwYYPIzc0Vd+7cEUIIoVKphL6+vkhJSREHDhwQlStXFmZmZiIlJUX06tVLtGjRQlhZWb3trhERERF98hTIX4b6ge3atUtUrlz5pemtW7cWw4YNE56engV+b+fOnSI6OlocPXpUfPHFF+Ls2bMiMzNTeHp6ipYtW4rExMRCFa+mp6cLCwsLkZaW9sbi3cLyGLCxwOlXx9Z6p9shIiL6X/M+n9+fokI3lNi0aZMoVqyY8PX1FRcuXBDnz58XtWr9uwAlOjpavC6mfFO8GRISIvbv3/+vtk1ERESkTQrdmsHR0VH06tVLCCHEl19+KZydnd95ooiIiIiocAod1AUHB4uIiAjRsmVLERERIYKCgt5DsoiIiIioMApV/Fq5cmWhUCjEo0ePxB9//CGCgoLE7t27hUKhEDt27HhfaSQiIiKiNyhUULdz504hhBBNmjQRX3zxhdi+fbtYvnz5e0kYEREREb29Qhe/rlixQqhUKtGxY0dhbW0tVqxY8T7SRURERESFUOjWryEhISImJkYIIcTo0aPFvXv33nmiiIiIiKhwCh3UlShRQv7f0tJSWFpavsv0EBEREdG/8NbFrzVq1HirPuEeP34sxo0bJ6ZPn/6fEkZEREREb++tc+oaNWok4uPjhYWFhahTp44ICwsTTk5OwtDQUDx69EicPn1a7N27V2zatEnUqlVLTJgw4X2mm4iIiIjyeeugrn379qJFixZi5cqVYsWKFeK7774TaWlpQgghFAqFKFmypIiNjRWHDh0Sfn5+7y3BRERERPSyQtWpMzAwEC1atBAtWrQQQgiRlpYmnj17JqytrYWent57SSARERERvVmhujRp166dePz4sfzbwsJCODg4MKAjIiIiKmKFyqlbuHChGDt2rDAzM3tf6fmf4jFgY4HTr46t9YFTQkRERJ+6QuXUAXhf6SAiIiKi/6DQ/dQ9fvxYGBoavnYZc3Pzf50gIiIiIiq8Qgd13t7er5wHQCgUCpGbm/ufEkVEREREhVPooO6nn34SKpXqfaSF/uF1de5YH4+IiIjyK3RQV6FCBWFnZ/c+0kJERERE/1KhGkoQERER0cepUEGdu7u70NHReV9pISIiIqJ/qVDFr1euXHlf6SAiIiKi/6BQQV2VKlXeuIxCoRDbt2//1wkiIiIiosIrVFAXGBj4ynmPHz8WS5cuFZmZmf85UURERERUOIUK6r755puXpuXk5Ijp06eL0aNHC2dnZzFy5Mh3ljgiIiIiejuF7tIkvyVLloghQ4aIZ8+eiWHDholOnToJXd3/tEoiIiIi+hf+VQS2efNmMWDAAHHlyhXRp08fkZiYKExMTN512oiIiIjoLRUqqDt48KDo37+/2L9/v+jSpYvYtm2bsLGxeV9pIyIiIqK3VKigrmzZssLIyEh06dJFeHp6iqVLlxa4XI8ePd5J4oiIiIjo7RQqqHNzcxMKhUKsWbPmlcsoFAoGdUREREQfWKGCuqtXr76nZBARERHRf8GxX4mIiIi0QKFy6hITEwucbmFhIby9vUWDBg2EgYHBO0kYEREREb29QgV1x44dK3B6amqquHjxohg8eLDYsWOHcHNzeyeJIyIiIqK3U6ji1507dxb4OXbsmLh586bw8/MTAwYMeOv17dmzR9SpU0c4OTkV2AADgBgyZIhwdHQURkZGolq1auLChQsayzx8+FA0b95cmJubC0tLS9G+fXvx5MmTwuwWERER0SfvndWpMzc3F4MHDxa///77W38nIyNDBAYGiunTpxc4f/z48WLKlCli1qxZ4sCBA8LExETExsaK58+fy2WaN28uTp06JbZu3So2bNgg9uzZIzp16vSf94eIiIjoU/JOx/SysbERDx8+fOvl4+LiRFxcXIHzAIjJkyeLQYMGiXr16gkhhFi0aJGwt7cXa9asEU2bNhVnzpwRmzdvFocOHRJhYWFCCCGmTp0qatasKb7++mvh5ORU4LozMzNFZmam/Ds9Pf2t00xERET0MXqnrV/3798vvLy83sm6rly5Iu7cuSOqVasmp1lYWIgyZcqIlJQUIYQQKSkpwtLSUgZ0QghRrVo1oVQqxYEDB1657uTkZGFhYSE/rq6u7yTNREREREWlUDl1J06cKHB6WlqaOHLkiBgzZowYOnToO0nYnTt3hBBC2Nvba0y3t7eX8+7cuSPs7Ow05uvq6gqVSiWXKUhSUpJGS9709HQGdkRERPRJK1RQFxQUJBQKhQDw0jwbGxuRmJgovvjii3eWuPfFwMCAXa8QERGRVilUUHflypUCp5ubmwsrK6t3kiA1BwcHIYQQd+/eFY6OjnL63bt3RVBQkFzm3r17Gt/LyckRDx8+lN8nIiIi+l9QqKDO3d39faXjJZ6ensLBwUFs375dBnHp6eniwIEDomvXrkIIIcqVKydSU1PFkSNHRGhoqBBCiB07doi8vDxRpkyZD5ZWIiIioqL2r1q/rly5UixbtkycP39eCCGEt7e3+Pzzz0XDhg0LtZ4nT56Iixcvyr+vXLkijh8/LlQqlXBzcxM9e/YUo0aNEiVKlBCenp5i8ODBwsnJSdSvX18IIYSfn5+oUaOG6Nixo5g1a5bIzs4W3bp1E02bNn1ly1ciIiIibVSooC4vL080a9ZMrFy5Unh7ewtfX18hhBCnTp0STZo0EY0aNRLLli0TCoXirdZ3+PBhUblyZfm3uvFC69atxYIFC0S/fv1ERkaG6NSpk0hNTRWRkZFi8+bNwtDQUH5nyZIlolu3bqJq1apCqVSK+Ph4MWXKlMLsFhEREdEnr1BB3bfffiu2bdsm1q1bJ2rXrq0xb926daJt27bi22+/FT179nyr9UVHRxfY6EJNoVCIESNGiBEjRrxyGZVKJZYuXfpW2yMiIiLSVoXqp27+/PliwoQJLwV0QghRt25dMX78eDFv3rx3ljgiIiIiejuFCuouXLig0RnwPxU0NisRERERvX+FCuqMjIxEamrqK+enp6dr1HcjIiIiog+jUEFduXLlxMyZM185f/r06aJcuXL/OVFEREREVDiFaigxcOBAER0dLR48eCD69OkjfH19BQBx5swZMXHiRLF27Vqxc+fO95VWIiIiInqFQgV15cuXFytWrBCdOnUSP//8s8Y8KysrsWzZMlGhQoV3mkAiIiIierNCdz782WefidjYWPHrr7/KRhHe3t4iJiZGGBsbv/MEUuF5DNhY4PSrY2t94JQQERHRh1KooG7Hjh2iW7duYv/+/eKzzz7TmJeWlib8/f3FrFmzRMWKFd9pIomIiIjo9QrVUGLy5MmiY8eOwtzc/KV5FhYWonPnzmLSpEnvLHFERERE9HYKFdT98ccfokaNGq+cHxMTI44cOfKfE0VEREREhVOooO7u3btCT0/vlfN1dXXF/fv3/3OiiIiIiKhwChXUOTs7i5MnT75y/okTJ4Sjo+N/ThQRERERFU6hgrqaNWuKwYMHi+fPn78079mzZ2Lo0KEFjgtLRERERO9XoVq/Dho0SKxatUp4e3uLbt26CR8fHyGEEGfPnhXTp08Xubm5YuDAge8loURERET0aoUK6uzt7cW+fftE165dRVJSkgAghBBCoVCI2NhYMX36dGFvb/9eEkpEREREr1bozofd3d3Fpk2bxKNHj8TFixcFAFGiRAlhZWX1PtJHRERERG+h0EGdmpWVlQgPD3+XaSEiIiKif6lQDSWIiIiI6OPEoI6IiIhICzCoIyIiItICDOqIiIiItACDOiIiIiItwKCOiIiISAswqCMiIiLSAgzqiIiIiLQAgzoiIiIiLcCgjoiIiEgLMKgjIiIi0gIM6oiIiIi0AIM6IiIiIi3AoI6IiIhICzCoIyIiItICH31Q5+HhIRQKxUufhIQEIYQQ0dHRL83r0qVLEaeaiIiI6MPSLeoEvMmhQ4dEbm6u/PvkyZOievXqolGjRnJax44dxYgRI+TfxsbGHzSNREREREXtow/qbG1tNf4eO3as8PLyEpUqVZLTjI2NhYODw4dOGhEREdFH46Mvfs0vKytL/PDDD6Jdu3ZCoVDI6UuWLBE2NjaiVKlSIikpSTx9+vS168nMzBTp6ekaHyIiIqJP2UefU5ffmjVrRGpqqmjTpo2c9vnnnwt3d3fh5OQkTpw4Ifr37y/OnTsnVq1a9cr1JCcni+HDh3+AFBMRERF9GJ9UUDd37lwRFxcnnJyc5LROnTrJ/5cuXVo4OjqKqlWrikuXLgkvL68C15OUlCQSExPl3+np6cLV1fX9JZyIiIjoPftkgrpr166Jbdu2vTYHTgghypQpI4QQ4uLFi68M6gwMDISBgcE7TyMRERFRUflk6tTNnz9f2NnZiVq1ar12uePHjwshhHB0dPwAqSIiIiL6OHwSOXV5eXli/vz5onXr1kJX9/+SfOnSJbF06VJRs2ZNYW1tLU6cOCF69eoloqKiREBAQBGmmIiIiOjD+iSCum3btonr16+Ldu3aaUzX19cX27ZtE5MnTxYZGRnC1dVVxMfHi0GDBhVRSomIiIiKxicR1MXExAgAL013dXUVu3fvLoIUEREREX1cPpk6dURERET0agzqiIiIiLQAgzoiIiIiLcCgjoiIiEgLMKgjIiIi0gIM6oiIiIi0AIM6IiIiIi3AoI6IiIhICzCoIyIiItICDOqIiIiItACDOiIiIiItwKCOiIiISAswqCMiIiLSAgzqiIiIiLQAgzoiIiIiLcCgjoiIiEgLMKgjIiIi0gIM6oiIiIi0AIM6IiIiIi3AoI6IiIhICzCoIyIiItICDOqIiIiItACDOiIiIiItwKCOiIiISAswqCMiIiLSAgzqiIiIiLQAgzoiIiIiLcCgjoiIiEgLMKgjIiIi0gK6RZ0A+vA8BmwscPrVsbU+cEqIiIjoXWFOHREREZEWYFBHREREpAU+6qBu2LBhQqFQaHx8fX3l/OfPn4uEhARhbW0tTE1NRXx8vLh7924RpvjT5zFgY4EfIiIi+rh91EGdEEL4+/uL27dvy8/evXvlvF69eon169eLlStXit27d4tbt26JBg0aFGFqiYiIiIrGR99QQldXVzg4OLw0PS0tTcydO1csXbpUVKlSRQghxPz584Wfn5/Yv3+/KFu27IdOKhEREVGR+ehz6i5cuCCcnJxEsWLFRPPmzcX169eFEEIcOXJEZGdni2rVqsllfX19hZubm0hJSXntOjMzM0V6errGh4iIiOhT9lEHdWXKlBELFiwQmzdvFjNnzhRXrlwRFStWFI8fPxZ37twR+vr6wtLSUuM79vb24s6dO69db3JysrCwsJAfV1fX97gXRERERO/fR138GhcXJ/8fEBAgypQpI9zd3cWPP/4ojIyM/vV6k5KSRGJiovw7PT2dgR0RERF90j7qnLp/srS0FN7e3uLixYvCwcFBZGVlidTUVI1l7t69W2AdvPwMDAyEubm5xoeIiIjoU/ZJBXVPnjwRly5dEo6OjiI0NFTo6emJ7du3y/nnzp0T169fF+XKlSvCVBIRERF9eB918WufPn1EnTp1hLu7u7h165YYOnSo0NHREc2aNRMWFhaiffv2IjExUahUKmFubi66d+8uypUrx5avRERE9D/now7qbty4IZo1ayYePHggbG1tRWRkpNi/f7+wtbUVQgjxzTffCKVSKeLj40VmZqaIjY0VM2bMKOJUExEREX14H3VQt3z58tfONzQ0FNOnTxfTp0//QCkiIiIi+jh9UnXqiIiIiKhgH3VOHX1cXjUG7NWxtT5wSoiIiOifmFNHREREpAWYU0fvTEE5eczFIyIi+jCYU0dERESkBRjUEREREWkBFr/SB8FGFkRERO8Xc+qIiIiItABz6qjIMRePiIjov2NOHREREZEWYE4dfdSYi0dERPR2mFNHREREpAUY1BERERFpAQZ1RERERFqAQR0RERGRFmBQR0RERKQFGNQRERERaQEGdURERERagEEdERERkRZg58P0SWPnxERERC8wp46IiIhICzCoIyIiItICLH4lrcWiWSIi+l/CnDoiIiIiLcCcOvqfxFw8IiLSNgzqiApQUNDHgI+IiD5mLH4lIiIi0gLMqSMqJBbdEhHRx4g5dURERERagDl1RO8Qc/GIiKioMKeOiIiISAswqCMiIiLSAh91UJecnCzCw8OFmZmZsLOzE/Xr1xfnzp3TWCY6OlooFAqNT5cuXYooxUSv5zFg40sfIiKid+GjDup2794tEhISxP79+8XWrVtFdna2iImJERkZGRrLdezYUdy+fVt+xo8fX0QpJiIiIioaH3VDic2bN2v8vWDBAmFnZyeOHDkioqKi5HRjY2Ph4ODwoZNHRERE9NH4qHPq/iktLU0IIYRKpdKYvmTJEmFjYyNKlSolkpKSxNOnT1+7nszMTJGenq7xISIiIvqUfdQ5dfnl5eWJnj17igoVKohSpUrJ6Z9//rlwd3cXTk5O4sSJE6J///7i3LlzYtWqVa9cV3Jyshg+fPiHSDYRERHRB/HJBHUJCQni5MmTYu/evRrTO3XqJP9funRp4ejoKKpWrSouXbokvLy8ClxXUlKSSExMlH+np6cLV1fX95NwIiIiog/gkwjqunXrJjZs2CD27NkjXFxcXrtsmTJlhBBCXLx48ZVBnYGBgTAwMHjn6SQiIiIqKh91UAdAdO/eXaxevVrs2rVLeHp6vvE7x48fF0II4ejo+J5TR/RucTQKIiL6Lz7qoC4hIUEsXbpUrF27VpiZmYk7d+4IIYSwsLAQRkZG4tKlS2Lp0qWiZs2awtraWpw4cUL06tVLREVFiYCAgCJOPREREdGH81EHdTNnzhRCvOhgOL/58+eLNm3aCH19fbFt2zYxefJkkZGRIVxdXUV8fLwYNGhQEaSWiIiIqOh81EEdgNfOd3V1Fbt37/5AqSEiIiL6eH1S/dQRERERUcE+6pw6InqBjSiIiOhNmFNHREREpAUY1BERERFpAQZ1RERERFqAdeqIPnFvqm/H+nhERP8bmFNHREREpAWYU0f0P+x1uXj/JgeQuYNEREWHQR0RfVD/JZAkIqJXY/ErERERkRZgTh0RfTL+bS4fG5MQ0f8C5tQRERERaQHm1BERvUZRNCZhziER/RsM6oiIPiEsSiaiV2HxKxEREZEWYE4dEdH/iI+xKJn9HRK9O8ypIyIiItICzKkjIqJPDruwIXoZc+qIiIiItABz6oiIiP6/j7HeIdHbYlBHRET0kWJRMhUGi1+JiIiItABz6oiIiLQQc/H+9zCnjoiIiEgLMKeOiIjofwxz8bQTc+qIiIiItACDOiIiIiItwKCOiIiISAswqCMiIiLSAmwoQURERBrYkOLTxJw6IiIiIi3AoI6IiIhIC2hN8ev06dPFhAkTxJ07d0RgYKCYOnWqiIiIKOpkERERaRUWzX68tCKnbsWKFSIxMVEMHTpUHD16VAQGBorY2Fhx7969ok4aERER0QehFTl1kyZNEh07dhRt27YVQggxa9YssXHjRjFv3jwxYMCAIk4dERHR/wbm4hWtTz6oy8rKEkeOHBFJSUlymlKpFNWqVRMpKSkFficzM1NkZmbKv9PS0oQQQqSnp7/z9OVlPi1wenp6+mvn/Zfvfkzr5b68//Vq0zH6mPblfa2X+/L+16tNx+hj2pd3sd53Tb1eAO9l/Z8aBT7xI3Hr1i3h7Ows9u3bJ8qVKyen9+vXT+zevVscOHDgpe8MGzZMDB8+/EMmk4iIiN6Tv/76S7i4uBR1MorcJ59T928kJSWJxMRE+XdeXp54+PChsLa2FgqF4r1sMz09Xbi6uoq//vpLmJubv/W8//LdolivNu0LjxGP0ae6zU9tvdq0LzxGb7fedwWAePz4sXBycnpv2/iUfPJBnY2NjdDR0RF3797VmH737l3h4OBQ4HcMDAyEgYGBxjRLS8v3lUQN5ubmrzzBXzfvv3y3KNarTfvyvtarTfvyvtbLffnfWq827cv7Wq827cu7YmFh8V7X/yn55Fu/6uvri9DQULF9+3Y5LS8vT2zfvl2jOJaIiIhIm33yOXVCCJGYmChat24twsLCREREhJg8ebLIyMiQrWGJiIiItJ1WBHVNmjQR9+/fF0OGDBF37twRQUFBYvPmzcLe3r6okyYZGBiIoUOHvlTs+6Z5/+W7RbFebdqX97VebdqX97Ve7sv/1nq1aV/e13q1aV/o/fnkW78SERERkRbUqSMiIiIiBnVEREREWoFBHREREZEWYFBHRESkBQqqIs9q8/9bGNQRfaKeP39e1En4aOXm5hZ1Ev5n5A8aGEAUjdGjRwshRIEjIhU0bc6cOeL06dPvPV304TGoo3eiqG7meXl5Rb6tt933/N9X///OnTv/Ki3z5s0TQ4YMEQ8fPnzlMh/rA/af6VL/XVBw8G9+39zcXKGjoyOEeDE2dEHHIT4+XowbN+6t15mRkVHodPyvUCgUYtmyZWLLli3vfJjF/3IefGpel8t2//79Vx6DVatWiRMnTmi8yOTl5YmWLVuK5OTkl9a1d+9e0aVLFzFz5kxx/vz5d7kLH+09pyAAivzl75+/6bs4fgzq/oe8yxtjXl6exvoKczN/Vxd+Xl6eUCpfnMLjxo0T33///Wu3d/fuXfH06dP/vK2zZ8+K9PR0OV29748ePXrtOpRKpTh37pyYO3euUCqVYsWKFaJZs2bi5s2bL6X1TQ4fPiw2b94spk+fLm7dulVgetXpunz5snjy5MlbrXvjxo1i0qRJYsWKFe8tkFGn64cffhC7d++Wfz979kzk5ubKtOfm5spj/rrgNb+tW7eKYcOGCSGESEhIEN26dROZmZka+56dnS1KliwpBg4cKGbMmPHGdU6dOlWMGjWqwONc1NT7lZaWVmTbPnXqlGjevLk4efKkxvyC7jdvcw5eunRJPH36VOTl5Ynk5GTx4MEDkZGRIbKzs98qXQW9PL0u/fn/n3+fjh07Jv8+f/68uHz58ltt/20BEHl5eXIb6usgfyCrUCjE9u3bRcOGDcWTJ08KXE9cXJxYtmyZ0NHREevXrxdCCPH06VNRrVo10adPH7mcQqEQeXl5IjIyUixZskSsXbtWTJ06VZw9e/ad7E/+e86/pd73Bw8e/Oe0vMmDBw/ky9+2bdv+9Qv2v5X/mbJnzx6RnZ39bl6KQB+1a9eu4aeffsLXX3+Nc+fO4dmzZxrz8/LyAABnzpzB1q1bcf36dTx//vyl9eTm5sr/79+/HydPnsTly5c11vHP/79Kbm6uXG7BggWoWrUqgoOD0bZtW9y9e1cul5OTI5e7du0arl27hvv377+Unn8j//f79+8PhUKB8PBwPH/+HDk5OQCA27dvy+2vW7cOtWrVwooVKwo8Pm+7rcGDB6N8+fLYsWMHnj59KqePHDkSn3/+OS5cuPDKY5iXl4eJEydCoVCgU6dOUCgUWLBgAdLT0/H333+/8juvmt6/f38UK1YM0dHRuHfvXoHpHTJkCGrVqoVt27YhKysLv/32G4YNG4bBgwdj5cqVGuscOHAgAgIC0LJlS6xbt+7NB+ZfUKft+vXr8Pb2xpQpUwAAEydORL169VC1alW0a9cOaWlp8jvfffcdKlasKH/XV3n+/Dl69OiBsLAwBAcHw9TUFN9//72cn5mZifT0dLnsuHHjoFQqMWPGjNeud+DAgbC3t8eoUaNw8+bNt9rHvLw8+dvdvHkT586dw7Vr1zSunfPnz2P//v04ePAgHj58+Mb1/pN6PRs2bECVKlVw6NChQq9Dnd5/68iRI5g2bRqGDh36ynUuWbIES5YsAQCcO3cOO3bswL59+/DXX3+9tL4DBw7Azc0NP/zwA7p37w6FQoGePXuiQoUKSE5OLvB6UG/r8ePH8trevn07bt++XWCa1evIyMjQuJ+qp//8888oUaIERo4ciZs3b2LVqlUICAjA+PHjX3mdFlZeXh5yc3Oxc+dOjBo1CtHR0YiMjERMTAzat2+PrKwsueySJUvQqFEjjTT+M80AcPjwYbi7u6Nly5ZyWm5uLmbNmoXWrVsDALKysuTxmjdvHlxdXdGrVy+cP3/+P+3P7t278fvvvwMAOnTogCFDhrzVs6SgfdmwYQPKlSuHXbt2/au05D/3VqxYgRkzZmDZsmUay/z222/w9/fH5cuXkZiYCFdXV41n1/uW/9gMGjQIHh4e+OGHH/7zcxEAGNR9xE6cOAF3d3eUK1cO1tbWcHNzw5o1awBonrgrV66Evb097OzsUKJECYwaNeqVN5++ffvC0dER9vb2iIyMxI8//ojU1FQ8e/YMmZmZAN4usFOvy9zcHIaGhnB2doYQAs7Ozrhy5YpG+jp16gRzc3M4OjrCw8NDXvz/Vv519+zZE3Z2dhg9ejRKlSolb9Lr169HUFAQ1q9fj1WrVsHIyAhjx46VgWxB63qTpKQkODg4YM2aNTI4BYB+/frB0dERc+fOLfChv3DhQly/fl3+3bBhQygUCrRp0wZjxoxBxYoV4enpibp16+LHH3/E2bNncfXqVbm8+vdYs2YNUlJScP78eZw6dQonTpxAqVKl4OTkhGHDhuHBgwca2x0wYADs7OywatUq/P333/j5559hYmKC6tWrIzIyEgqFAu3bt8ft27cxdOhQ2Nra4uDBgxoPlHcp/3m1evVqxMTEwNbWFl26dIGtrS1mzJiB+fPnw9HREaGhofIBPXbsWFSsWPGV6x07diy++OILAEB2djZ8fHwghICZmRmMjIzQpUsXjBkzBjVr1oS7uzsSExOxZcsWHD58GB07doRCocC8efNem/Zx48bBzc0NI0eOxI0bNwpc5tatW/J8ysvLw7Zt29CkSRPY29vDyckJUVFRaNiwIbKzs/Hzzz/D1dUVYWFhcHR0RIMGDf5VIP3zzz/DzMwMQ4YMwZEjR167rPr4Hz58GHPmzMG0adPwxx9/FHqbardv30aVKlVgZGSEHj16ANB8kQNe3CNcXV0xe/ZsfP/993BxcUFoaCh8fHwQHR2NtWvXvrTe2NhYWFlZwcTEBM2aNYOTkxNKlSqFESNGvDItN27cgLe3N37//XcsXboUCoUCGzdufOUx2LhxI6pXr46wsDBER0djy5YtePz4MTZu3AgjIyNMmzYN6enpWL9+PYyMjDBlyhSNa/5d+Pnnn2FkZCTvneqPnp4e6tevL+/HycnJqFWr1iv3RS09PR1TpkxBaGgo2rRpA+DFy8uIESPg6+uL7t27y2VHjBiBgQMHwtraGjo6OujUqRMuXLhQ6H3Iy8vD33//DQ8PD9SpUwcNGjSAmZkZjh8//sp0vs6qVatgamqKkSNH4ujRo/8qPWoDBgyAqakpwsPD5f1WHbht374dn332GZydnWFlZSXvz4UNRP+rQYMGwc7ODrt379Z4Mf8vGNR9pC5dugR3d3cMGjRI5lo0bNgQoaGhAP7v5Lt8+TIiIyMxa9YsXLlyBYmJiShTpgx69eqFu3fvapykBw4cgJeXF/bt24eVK1eia9eusLGxgZ+fHyIiIlC2bNnXvrHl5ubKh9avv/4KFxcX1K1bF4cPH8Yvv/wCIQRKliyJYsWKyaCkRo0aUCqVcHd3h0KhQMmSJaGnpyeD0/+iXbt2sLGxwfHjx3Hq1Cm4ubkhMzMTq1atgomJCcaNG4eNGzfCx8cHs2fPBvDioZORkYHff/9dBmBvygECgKNHj8LT0xPbt28HADx58gRXrlxBUlISrK2tNXJJUlNTcfbsWfz9999IS0uDjY0NwsLC5PY6duyI2rVry8Bj3rx5OHv2LCwsLGBqagoHBwdERUXhq6++kus8deoUvLy8ULFiRbi4uMDX1xeGhobw9PREeHg4QkJCMHToUBnY7d27Fy4uLjhw4AAA4OzZs3BxcUFCQgLOnz+PvLw87Nq1C+bm5vjss88QGBiIFStW/OffpCD5c61yc3ORmJgIGxsbuLm5QU9PD6ampli6dClyc3OxevVqWFhYYPr06fL7v/32Gzw8PGROl3qd6n9nzZoFhUKB/v37Iz09HQ4ODqhYsSJCQkLQuHFjGBgYwMDAAKNHj8bIkSMRGBgId3d3uLu7o0mTJnBxcYFCodDYppo6wM3KykL79u3h4eGBkSNH4s6dOxrLff/993B0dMT+/fuRkpKCpUuXQkdHB0qlEgYGBjA2NoajoyOEEOjRowcsLS3l9pYvXw6lUolp06YV6riq7xH/TPepU6fw5MmTAr/z008/wdHREVFRUahZsyYUCgUWLlz4rx5meXl5WLRoESIiIuDh4SEfSurr6ZtvvoG9vT1SUlKQkpICS0tLuY8//fQTlEolxo0bJ9eXnZ2NQ4cOwcbGBrq6ulCpVLC0tMTWrVsRHh6OmTNn4vHjx7h06RIeP378Unpq1aoFa2trKJVKzJ07V6bxnzZs2ABjY2MMGzYMBw4cQHR0NJydnbF3717ExsZi2LBhAF6ULoSHh6N27dr47rvvkJGRgb/++gtz5swpMGB8W7m5ubh27Rp8fHzQtGlT2NjYoFOnTkhKSoKRkREUCgWEEHBwcEBSUhKSk5NRp04djRfQ7OxsjfWpX4BSU1Mxbdo0BAUFycDuwYMHmDhxIkqVKoWEhASMGzcOFhYW2LJlC/bs2YOpU6fCzMwMXbt2LXRgp07TX3/9BVNTU3lPq1mzJn777Td5/bzN+XXt2jUUL15c5t6rv3Po0CGkpqa+8fv5t3H16lVERUXh2LFjSE9Px759+2Bubo6GDRvKa3fIkCHymXT69Om3Tue7cu3aNYSGhmL9+vUAgL///hsnTpzA8OHDsWvXLo3SisJgUPcRysnJQVJSElq2bInU1FR5k1Rnr6tPyiNHjqBfv35o3bq1RlHgiBEjEBERgV69eskcu3nz5uGLL77A4MGD5XIzZ86Enp4ezMzMkJiYiJiYGLi7u8vARW3SpEkANIO6ESNGICoqCtHR0fjmm29gamqK2bNn4+DBg6hUqRLc3NyQnJyM0qVLo3v37sjIyMAvv/wCAwMDlCpVCvr6+gW+pb9O/pva48eP4ePjg8OHDwMArly5Ajs7O+zatQv+/v745ptvAAAXL15E6dKlMXHiRFy/fh3JycmoUKECHBwc4OjoiJMnT77Vtg8cOICSJUvi6NGj+P333/Hll1/C19dXBmJbt27FsWPHMHz4cBQvXhwuLi5o164dbt68iatXr6JkyZIoW7Ysbt26BeDFTcfR0VEGE+PGjYMQAk2aNMG6deswcuRIKBQKjbfrAQMGQEdHB2FhYdiyZQsWLlwIIQSioqLQsWNHBAcHY+jQoTh9+jT27t2LkJAQ/Pnnnzh27Bjatm0LXV1duLi4wM/PD8eOHQPw4o1VqVTC2tr6lTd09Y0u/zn2tvIHdHPnzsXKlStRvXp1HDhwADk5OShRogQUCgUaNmyI2bNnw9TUFLNmzcK0adMwZ84c9O/fH/PmzYOXl1eBLxy5ubnIzs7GDz/8AB0dHcTHx6Nt27a4du0aevfujYCAAPkbNWvWDLm5uRg8eDB0dHQQHh6OP/74A1euXMGgQYOgUCgKLIpdtmwZAgIC0LBhQ3h4eEBHRwfDhw/XKN7LyclByZIl4enpCSMjI4SHh6Ny5cpo2bKlzI1RKBQwMDBAZGQkYmNjkZeXhytXrqBYsWLo3LmzXJc6N+HixYtYvXr1K497SkoK/Pz8kJGRgUePHmHq1KmIjo6Gnp4emjRp8tLxOn78OOzs7OQLzuXLl6FQKDBw4MC3/i3Vxzx/mtatW4fg4GBUq1ZNpj0jIwP16tXD8OHDAbzI5S5Tpgxq1qyJmJgYuLq6okuXLrIY8tatW/I+N3jwYAQGBsLR0RH6+vr4/vvvERwcjObNm6NEiRKwtLTEl19+ib///hs5OTnye7/99hsUCgXMzc2xa9cuZGZmauQ65+bm4smTJ6hRo4ZM14MHD1CsWDE0btwYjx8/RsOGDdG6dWv89ddfSEhIgIWFBVQqFYyNjRESEoKKFSvCzc0NSqUSU6dOfavjVpCTJ0/C3NwclpaWsLW1xa+//oqsrCz0798fQgjo6OhAoVDAxMQEJUqUwFdffYV79+7h7t27ePDgAR4+fIizZ89izJgxaNiwIerXr4+dO3cCeHFvHDt2LEqXLo0WLVoAAO7fv4/x48fD398fbm5uSExMlMcEABYvXgw9PT107doV586dK9S+ZGVloUuXLtDV1YWtrS1iYmLg5OSEihUrYtWqVRolQK8Lmo4dO4YSJUrg7t27SE1NxaRJk1CpUiUolUrUrFkTJ06cKPB7R48e1Xg2JCcnIy4uDo0bN0ZGRoacfvjwYZibm6Nx48ZISkrCggULsGDBAjRq1AghISHyxTx/wPw+nT9/HmZmZti0aRP279+PDh06IDAwEC4uLnB1dZUvDoUNNBnUfWTU9Uy+//57JCcna8w7f/48TE1NcerUKeTl5aFDhw4wNzdHyZIlNeqJ1alTB9HR0ahQoQI6dOiAEydOoH79+jA3N5fFVJcvX0bZsmUxcOBAfPnll3BycoKNjQ1cXFxgYWGBrVu3AnhxoSkUCnz++edy/f3794exsTFMTExgZGQEY2NjzJw5U84fP348jIyMZHFCbGysnLdlyxbo6+ujdOnSMDExeale16vkz84fNmwYduzYoZHDdv36dZiZmWHRokXw9PTEuXPnULt2bdSvXx9mZmayWKNixYoYM2YMDhw4gKCgIIwaNeqlbRVUJPv333/DxcUFAQEBMDAwQMmSJdGuXTvMnTsXQghERETAwcEBLVu2xNy5c/Hdd9/Bzs5OBk9Xr15F8eLFUbZsWVnHytvbG2PGjIFCoZCBzciRIxEZGQkrKytUqlQJKpUKXbt2xYMHD9CiRQtERUVBpVLB3NwcFhYWsLGxgY6ODtq3b4+OHTvCzs4O4eHhWLRoETw8PFCpUiWYmpqicePGUCqVGDt2LPz8/PDzzz/LXEtHR0fY2Ni8dv+PHTuGZcuW/es6H7Vr14a9vT10dXXh5eWFH374AQCwZ88eKBQKGBoaQk9PD6NGjcKdO3dQtmxZlC5dGrq6uggKCoJCoUDp0qUxatQoTJ8+HYcOHcKZM2fkDa9fv36wsLCAkZERbG1tkZqaigcPHqBjx47Q09NDVFQUbGxsYG1tjbJly8Lf3x/W1tZYuHAhAODRo0fo0aMHFAoFFi9eLNP9559/QqVSYd68efLNeeDAgbCyssLw4cNx584d+dDKzs5GQEAAVCoVDA0N4e3tjSpVqmDYsGFwdnaGq6srbGxsYGZmhhIlSmDs2LFwdnZG586dNep+zps3TwZcenp6WL58udxGfvfu3YOJiQliY2Ph4+OD+vXrY8iQIdi2bRv09PTkMVave9OmTahduzaAF9e/i4sLunTpItf3qjpo+dfxyy+/oHnz5ggLC0OfPn2wf/9+AC9y3tR1wu7du4fs7Gy0bt0aFStWxPTp01G8eHG4ubmhUaNG0NPTg52dnXxJ3Lx5MwYNGoTdu3fj1KlTGDVqFL788kuUKFECQggYGxtDT08PVatWxZw5c1CxYkXo6+vjxIkTGnXiLl26hK1bt6Jhw4awsbFBq1atMHr0aI1cvadPnyIsLAynTp3C/fv34ejoiBo1asDR0RGbN2/G559/jtDQUCiVStSrVw81a9ZEYGAglEqlDIhTU1PRsWNHfPbZZ4W6HtTL5uTk4MiRIxrFrVOmTMGpU6fQo0cPGBgYwMbGBoaGhhBCyJy74OBg2NjYwNbWFp6enrC1tYW1tTU6deqEqlWrQqFQYNGiRRg7diwiIyNl0WKVKlXk7zt+/HiYmpoiMDAQwIt6purftlu3brC0tJQvRW+zL8CLYDowMBA7duzAuXPn4ObmBh0dHTg5OcHX1xdr1659q0BJfS8KDw+Hl5cX6tevj5EjR+LIkSMwMTEp8IWrS5cuGs8X4EXOt5GREYoVKyYzQNTbP3LkCExNTaFQKLB7924AwI4dO1CvXj2EhIRoVGH48ccf31k9u1edJ23btoWJiQlMTEzQs2dPbNiwAQAQEhLy1i9b/8Sg7iOSkZGBcuXKoXz58hrT81e49vT0lOX/WVlZaNq0KZycnDBixAikp6fjyZMnWL9+PTIzM9G/f39Uq1YNd+7cwW+//YYmTZrA0tISmzZtwsmTJzF8+HBkZGRg7969MDc3h7u7O9LS0hAZGQkvLy/88ssvyM3NxS+//AJra2s0a9YMO3bsgLe3N6ZOnQovLy8olUqYmprKXIGMjAzUqlULpUuXhlKphL29PYyNjXHgwAH5prZ161YYGBjA09MTdnZ2BRal5Kd+wA0ePFjeeM6cOaNxbNS5YTt37oSfnx8MDQ2ho6ODunXromfPnhg4cCBMTU2RlJQk11utWrWXirzyX3w7d+7EmjVrsHHjRuTl5SEtLQ2LFy/GrFmz4OTkhB07dgAASpQogejoaCxZskQ+GB89eoTg4GDs3btXBtxXr15FiRIlZDG3n58f2rVrB319fQghUKpUKRgbG8PFxQUODg7YuHEjunTpAoVCgWbNmqFnz54wNDREbGwsdHV15T4aGxtDCAErKysolUro6uoiICAAW7ZswcyZM7Fx40Y8efIEbdq0QXh4OEqUKIHVq1fL/fTz84NCocDSpUtfOufU/1cfw7e1ceNGeUNMSkpC9erV0b17d5iamsLIyAi6urpo3Lgx+vXrB0tLSwgh4Orqipo1a+LGjRt4+vQp4uLiEBsbizNnzqBkyZLw9fVF3bp14ezsDHt7e3mdfP755zAzM0NKSgoWL14MIyMj+fJy4sQJGfwaGxtDR0cH33//PUxMTBAREYG+ffvKfd26dasMsNUvG7///jvc3Nxk8YxaUlISdHV1MWbMGHk95uTkYPny5bCwsJDBiImJCVQqFZo0aQLgxQuXnp6efJi3bt1a4+Wkbdu26Ny5M9LS0hASEgJzc3OYmppiwYIFyM7OlhXd1efpgQMH0KxZM4wYMQKXL1+W66pevToWLFigkeYFCxbI3Ft3d3d06tRJrmfLli1o06bNS/Uy81u7di1MTEzQp08fLFq0CD4+PggJCcHZs2eRl5eHFStWyKoA9+/fR//+/VGiRAlYW1ujXr16MDExgb29PaKiolCvXj1Z/y4+Ph5CCKhUKhgYGEBPTw+TJ0/Gt99+Cy8vL/kQtrS0hLW1NfT09GBhYYGIiAh07doVz58/fynorVevnnyxnDx5Mh4/foy5c+fi9u3bqFixIjp16oRixYqhVatWaNasGSZPnowHDx6gbNmyaNasmbwvpKamYt++fahcuTKaN28ug4PPP/8cCQkJb5WLkr+qAPDiRQEAKlasKEtK7OzsYGFhAYVCAZVKhW+++QZ2dnZQqVRwcXGBkZERoqOjcfr0aaSkpGD37t1ITEzEnj17AADPnj3DwIEDoVAoYGZmhoULF2L27Nlwc3ODubk5+vXrh5SUFNy/fx8xMTFQKBSyekf+HNKIiAjEx8e/NljNH6Bt3LgRw4YNw5dffonr169j69atsLCwgKOjIz777DPY2NggMjISvr6+GDt27EvH5PLlyzh//jwOHjwI4EWDvy+//BJjx47FjRs35LZq1aqFWbNmFZge9f312rVrcvkNGzbAwMAA3bp108gpXLp0KZKSkuDn56exj+o6dv7+/lixYgVq1KiBkJCQd9JwIf858tNPP2Hu3LlYt26dnK6u35tfdHQ0vv3223+1PQZ1H5Hs7GysXbsWpUqVQnR0tPzRs7OzkZeXh9u3b8PNzQ379+/Hn3/+if79+8PHxwdt27ZFeHg4BgwYgIyMDHkifvPNN7KCbV5eHvbv34969eqhVKlS2Lx5s2w0kJCQgNjYWBlctW7dGjo6OnBzc0NGRgby8vLwyy+/wMjICAEBAbLC8vjx42FnZwd3d3dYWVlh/vz5qFKlCvz8/PD8+XMsWLAASqUSPj4+sLCwwNGjR2Vgt379erRu3fqlukn5nThxQiOHQF9fH2ZmZvICyN9aqmzZsvDy8kLbtm1hZGQEpVIJR0dHxMbGymz1+Ph4TJw4EU+fPsWgQYPg6Oj4yiLH/v37w9XVFeXLl4eDgwPi4uKwd+9eTJ48GX379kXfvn1x584dxMbGIiQkRCO3Rl3EExkZiV9//RVjxozBnTt38PDhQ1y4cEEGdomJibC0tESrVq2we/duzJ49G/369YOdnR2qVKmCnJwcTJw4EUFBQfDy8oKHhwe+++47zJo1C97e3tDR0YGBgQHMzMxgYmICXV1dhISEoEaNGkhOTsaXX36JL774AsePH8ezZ8/w66+/ws7ODsbGxliyZAn27Nkjc7gCAgIQGhoqA9X8bt26hYoVK2q0JH2dtLQ0hIaGwtnZGY6OjtDV1ZU5rUOHDpVBaGxsLCpXrixzLCwsLGBhYYGkpCRUrlwZpUuXRmZmJnJzcxEfHy/Pu7t37yIyMhKtWrXCmDFjIIRAq1atALwosqxYsSKEEAgNDcWVK1cwfvx4KJVKmJiYYOvWrbh06RIiIyOhUqk0gvwTJ06gXbt2WL58uXw47Ny5EyqVSgZ16uKc58+fw87ODoaGhhg/fjyWLVuG+vXrIyIiAt9++y1CQ0NlsKp+gZkwYQKys7Ph6+srA7tOnTohKysL6enpGDBgAOzt7WWVgDFjxiApKQlJSUnQ0dFB79690a5dO5QvXx7Tpk3DiRMnMHr0aIwfP15eu3l5eRg4cCAcHBxw5coVpKSkoFu3bsjLy8Pp06dRqVIlec7lv4Z69+6NevXq4dGjRy/9nnl5ebh37x7KlSsnqzVkZ2fD1tYWPXv2lOuYOHEiLCwsoKOjg8TERCgUCixZskRWOWjXrh309PRQpkwZfP7550hLS8OAAQNgaWkpv6evr4+SJUsiNDQU8+bNw+TJk1GyZEnY2trCzc0NQUFBKFGiBJycnNC/f3/MmTMHPXr0QO3atbF06VKNhkr16tWTAaG6GO/s2bOYO3cunJyc4Ofnh1q1aqFcuXI4ePAg4uPjoVAoUKxYMSgUCiQmJmLbtm3o06cPrKyscPLkSdy8eRP9+/eHSqXCqVOn3ngtqI/N5s2b0apVK1SrVg1CCAwaNAj379+X17GJiQn09fWho6MDXV1dnDp1ChkZGbh37x6aNm0KPz8/6OrqygY1CoUC7u7uSElJkdtav3497OzsoKOjg0WLFmHDhg0wNTWFn5+fLKUAXuRoBgUFwcnJCX/++ScyMjKQmZmJevXqYfXq1RrF7P/0zxcQa2truLu7o0SJEvD09ERkZCS++uorHD58GIGBgRoB+T8b4q1atQolS5aEv78/7Ozs0LJly5caIWVnZ8vGBJcuXZLTFyxYoPGiNX/+fJiYmGDHjh3y2l21ahX09fXRs2dPZGZm4tatW7CxsZEZBAA0iuf37t2LFi1awN3dHTExMYWqD/gq+b+bmJgIW1tbeHh4wM/PD59//rnGMX7y5AlOnjyJ2rVrIyAg4F8XAzOo+0iof9zs7Gz88ssv8Pf3l4Gd+sT47rvvoFQqUaJECZnroD6Jy5QpAyEE+vTpgydPnuDZs2f47rvvYGNjIyvMrlu3DsWLF0eZMmVQunRp/Prrr8jNzUVMTIzMhcnNzUX37t2xY8cOjYArKysLISEhEELAzc1NpnfYsGEoV64chBBQKpUwMjKCjY0NateujeHDh2PWrFlQKpUoWbIkLCwscOzYsZfqVhR00XTo0EEWFeXl5WHLli1QKBTQ0dHB4MGD5Q1i1apVMDY2xvjx42VxjbOzM7KysmQF+okTJ2LQoEGwsbHBhAkT0KZNGzg5Ob2yddWsWbPg4OAgGxlMmDAB+vr6+Pnnn/HZZ59BoVAgNDQUoaGhKF++vEzL06dPMWnSJFSsWBFhYWHIzMzE6NGjoVAoEBMTg8jISAQGBmLq1KlwdXWFl5cXYmJi4OHhgfbt26NPnz6wt7eHkZERsrKycPDgQdSoUQNVq1ZFmTJl4OPjg9GjR6NLly4wMDBAlSpV4OvrK3OX1MXAGzZsgI6ODho3biwbVdStWxfR0dEoVqwYoqKioFQqYWNjA29vbxw9ehRr1qyBnZ0dIiIi8NNPPwF4Uby3d+9e+Pv7Iz4+vlDn8sOHD6FSqaCrq4vRo0dj7dq18jglJiZCpVLJ3MFvvvkGPj4+cHNzg66uLpydndGgQQN5U8vOzsa4ceMQGRkpc6p++uknFC9eHEII2NnZoVGjRvj111/h5eUFPT09uLi4QAiB8PBw/PbbbwgODoZCoUDbtm3RrVs3+Pr6wtjYGHXr1sXGjRtx6NAhxMXFoX79+hovUwAQFRWF0qVLa9yAr169ilKlSsmibSEEKleujGrVqmHu3LnIyclBQEAATExMZC5UQEAA4uPjYW1tjaVLl8q6pWFhYbK4LP85+dtvv8Hc3BzHjh1DixYtZCDco0cPVKhQAbVr10aFChUQHByMhw8fYu3atWjUqBEcHR1lPaNRo0YhODhYNpzo27cv7OzsMGbMGNy6dQuXLl2SQcrr6pempaUhPDwct27dwuXLl+Hk5IQOHTrI+R06dICpqSnatm0r64O1bNkSmZmZyMzMRGpqKpYtWyYbMvj6+qJixYpQqVSIj49Ho0aNZHAfHh6O+vXrIzQ0FAsWLMC0adMQFhaGqKgohIeHIzQ0FE+fPsXq1athbm4uc83UdYP/+OMP+Vu1bt1angt9+/ZFdnY27t+/j4SEBLi7u8PMzAwKhQLBwcHQ1dWVDdPmz58PJycneHt7o1ixYjh27BjWr1+PVq1aoXjx4rJaxdtcC+q6xBEREdDV1ZV15pydnbF8+XJUqlRJXr9CCBgaGqJ9+/byelFXvXBzc5PVE3r06AGlUimv1dzcXPz222/o06cPhgwZAiEEzM3NMW3aNOzfvx+WlpYwMDDAjz/+COBFbuFnn30GQ0NDBAcHw9vbG97e3vKcL+ienD+ga926NUxNTTFlyhQ8fPgQ+/fvR/369aFUKtG7d28AL3LdypcvL4Mq4P+uqe3bt8suh9StjBUKBVasWCG3vX79esTHx790XWzduhVKpRJ9+/bFlStX5PSyZcuiWLFi2LVrl0ZgZ2BggMTERDx79gwpKSmyyyN190b5g6fs7GzcuHFD43n8Lly+fBk1atTAn3/+idu3b2P+/PkIDAzUaADz008/oVKlSqhcubIMKN+mEd8/MagrYv+syAu8OJE2bdqEkiVLolKlSgBenMiGhoZwdHREvXr15Jv+qlWrALw4aTw9PaGjo4MBAwYgLy8PqampWLx4MRwdHVGlShUYGhpiypQpmDNnDlq2bAk7OzscOHAArVq1gouLCxYtWoROnTrB2tpavhXl5ubKEysjIwPVq1eHEEIjJzE1NRX+/v4QQkBfXx9ly5aFlZUVdHV18csvv2Du3LnQ09NDqVKlIIR4624U1MdG/aZ/8OBBrFmzBrq6uhgwYAAuXrwIPz8/WWG5QYMGcHZ2xo4dO3DhwgW4u7ujTp06qF+/PlxdXXHgwAEcOnQIQ4YMeW0r3y+++EIWy/3444+wsLCQ9TkOHTqE5s2bQ19fH7169UJOTo6srJ+VlYWNGzciKSlJ4yZWv359KBQK1KxZE3FxcbC2toa+vj50dXVlwBcYGIjGjRujdu3acHV1RWRkpCyWFULA3d0d5cuXR2BgIOzs7KBQKBAXF4egoCBZ70a9fOXKlTWKKtq0aYMSJUrA398fwcHBCAkJgbe3N8zNzWVXIsCLLhYCAgKgo6OD4OBgFCtWDMHBwWjatOlL5+ibXLt2DSqVCvr6+jAwMIBKpUKNGjVw6dIl5OXloUePHlCpVFAqlahTpw4sLS3h4eGBZcuWyUYmf/75p7ypLly4EI6Ojhqt7YoVKwY3NzfUqlULTk5OMDU1hZmZGaZMmYLs7GzUq1dPFkurVCp88cUXaNCgAWrWrInOnTtj/vz5Mpjw9vZGWFgYjh8/jm3btmHnzp2yDt2JEyfg7+8Pf39/9OzZE3v37sXAgQMRFBSEWrVqQQiByMhI+Tu0atUKZ8+eRXp6OszMzGBoaCiLe0eOHCnPvZycHCxevBjjx4/HhAkTMGvWLFmtQK1Pnz6Ij49HiRIlEBsbC319fcyePRuWlpYoXrw4YmJiZD2cXbt2oVevXjh79qz8/t27d2FtbS0bBgBA586dERwcDH19fURERMDHx+eVQYq6G4/bt2/D09MTs2bNQokSJdCxY0d5jm/ZsgWurq74+uuvkZaWBjc3NxgYGMiuQLKysrB//360bdsWjRs3xuLFi/Htt99i8uTJKFu2LCwtLdG0aVNYWVmhcePGsvFG27ZtERERgdmzZyM5ORklSpRAQEAAzp07h6NHj8LDw0Mj99jU1BSWlpbo0KEDTp06Je9bN27cQFJSEhQKBSZPnoxjx47h9u3bmDNnDoKDg2FoaAhjY2OEh4dr9Bc4d+5cuLi44PPPP8elS5eQlpaGFStWaHQ39Ca3bt3CokWL0KpVK6hUKnz77beoX7++bN1qaWmJOnXqYODAgfL6ValUsLOzQ7t27WTR4sOHD9GpUycZxNy+fRvt2rWDoaGhrEqRl5eHO3fu4OnTpyhZsiQGDRoE4EW9ubJly0KpVKJ48eJyWeBFvbEpU6Zg8uTJ8lp7UyDRoEEDGBgYoEKFCvLeDLyo821lZQULCwsMGDAAVapUQUBAgGwVnb+IfPDgwejatSuAF7nrxYsXR6dOnTS2c+DAAQwaNKjAhhtz586Fq6srevfurXG+qxuybN++Xe7PmjVr5G+flZWFAwcOwNPTE1FRUXJfCwre3kXRK/AiF7FChQqIj4+Xv+fz589lA6x69eohLy8Pz58/x8aNG1+bprfBoK4IXb16FT179tQIctQttNQ5dqVKlUJ8fLwselEoFLCysoKbmxs6duwI4P8uUHVLOktLS9lSKC0tDbNmzYK+vj6CgoLkdnbs2IHBgwcjJycHd+7cQe3ateHt7Y3g4GBZvDl+/Hg0bdoUFSpUwKJFi3Dx4kVkZWUhIiICCoUCVapUQV5eHnr16iUbYeTm5qJVq1ZQKBSyHhHwIpdRoVAgOjpa4yIsSP5Ad+7cuTAzM0OvXr3w2Wef4dGjR1i6dCl0dXXRvn17uLq64vr162jfvj18fX1lJV11C8ATJ05g3LhxmD17NubPnw/g1ReLuo5P3bp1MW/ePBw+fBimpqYYO3YsTp8+jZycHEyePBkzZsxAgwYNYG1tjX379snALn/dx2fPniEnJwd//vknEhIS0LJlS5iZmaFfv35wdXWFvb092rRpAwcHB3h4eKBPnz64fv26bLlma2uL4sWLw9XVFYGBgYiKikJoaCjGjx8PQ0NDuLm5oXLlyoiKioKPjw+8vLwQEREBJycnCCHQr18/uV95eXnw9/eHrq4uunbtKo//tWvXUKdOHejq6spuMU6fPo1ly5ahe/fu+Prrr7F582aNc/NV/jlv8uTJsLW1xdatW2UOqhACO3fulMdfneOoUCjwzTffwNPTE/v27cPGjRvh6uqKtm3byvN49+7d8q121qxZ6NixI6pWrYqEhAQEBwejRYsW6Nu3L4KCgmQH1NWqVUNsbCx69eoFOzs71KlTBxcvXtRIZ3Z2Ns6cOYOzZ8/ip59+goODA4KCgmBiYoJWrVrJOkunT59GuXLloKurC0dHR7i4uODgwYNo3rw5YmNjYWZmBqVSCR0dHXTr1g2pqal4+PAh3NzcoFKp4OTkBA8PDwwdOvSl/s5u3bolc1vLli2L3r174/z588jKysL27dvh7e2Ntm3bIisrS3ZaXalSJSxbtgy2traIjY3Fvn37kJeXp3HtqM9HdfCkrssFABcuXMDatWtlgFOQ06dPw8jISBYzDh8+HHp6eoiJiZHLfP311zJwHTRoEAYMGCC79LG0tIShoaFsRKUO6J8/fy7PgRUrViAyMhJ2dnYoXbo00tPTMXz4cFlEVq9ePbRr1w6DBg1Cp06dEBUVhTt37uDXX3+VpQtXr16Fu7s7evbsieXLl0OhUOCLL77QKJrMy8vDsGHD5AvStm3bZFFtYmKifCH9Zz1EdY5q06ZNNYr/3sa5c+dgamoKGxsbCCFgbW2N7du34+HDh/KaUBe7mpmZyQYenp6e6NKlC5ydndG4cWNkZmbit99+w44dOzSqR/z999+IiIiAUqmUwW1eXh6uXbsGKysrdOzYUeZMNm7cGL1790aJEiU0Gp3905sCukuXLsHS0hLGxsbw9fWV55v69/z6669haGiI8uXLo06dOkhOTkbZsmU1GvLl5uYiLi4OgwcPxvPnz+Hs7IxOnTrJ8/Xbb7+VPSP8816d/z4zZ84cODk5vTKw27lzJ+bNm4evvvoKDRo00HjOHjx4EB4eHoiOjpb7/D66M3n+/DlGjRoFb29v+Pv7vzRv+fLlCAoKQsWKFTW2/29y6NQY1BWhEydOyAtYXfQxffp0BAQE4Pbt23j27BkWLlyIgIAABAYGYtKkSejQoQPs7OxeugjUD9+uXbsiNDQUKpVKPhDPnTsHKysrWFlZoW3bti+dvOoT6OrVq7JOzbBhw2BkZAQfHx9YW1vD1tYW8fHxGD58OOLj4xEaGipHcahbty78/f2xevVqWVm3Zs2aAF68US5btgy//fYbdu3aVeiTNTc3F0FBQXB1dcWyZcuQk5ODu3fvyg5G1Q8UPT09+Pj4QKVSwdnZGXp6evj6668BvKhE3KZNG/Tu3VvjbfFVQcqECRNgbGwMXV1dfPbZZwgPD4e5uTmqV68OLy8vDB06FBcuXEDTpk1hZ2cnHx65ubk4ceIE9PT0ZF9WZmZmsLe3x4YNG2RHt+qWg76+vvjqq68wcOBAeHt7o0+fPti0aROqVauG6Oho2Redq6srNm3ahMjISAQFBcliO0NDQ1kkHR0djYyMDNStW1cW7yxatAjAi5ahVlZWiI+Ph7u7O77//nuNc6BOnTqwsbF5be7l6254+UcGWLlyJZKTk1GuXDl07doVGzduRKdOnWQu1pYtW5CamooWLVqgUaNGcHBwkAGfiYmJfNBu3LgR7u7u6NChA/78809kZWUhLy8PX375JRwcHNCjRw/ZcrhUqVKyM1tzc3MsWrQI3t7ecHFxQVZWFnJyctC8eXP4+Pigf//+MnchfyC+bds2qFQqGdyuWrUKhoaGqFmzJrZt2wbgxXWyY8cOHD9+HOvWrcPNmzdx+fJlHD16FI6OjjAzM0OLFi2gVCrRqlUrdO3aFU5OTujevbusAF6qVCn8/fff2LdvH8aMGSOPW9WqVaFUKjF48GAEBwejdu3aqFWrFq5cuSI7k83Ly0PTpk3h4+MDOzs7pKamonLlyrC3t0ejRo3w9OlTbNmyBePGjdOoW7Zv3z54eXnJUR3e1pMnTxAdHY1BgwYhNzcXZ86cQevWrWFnZ4cpU6Zg2rRp8PT0lOebEEJ2lwK86GrCysoKenp6shHOxIkT0bt3b+Tk5GDgwIEoVaoUTExMYGBgoFGcOGLECCgUCjRq1AiBgYHw8fFBdna2zEm7desWzpw5g6ysLNSrVw9t27aV3ax4eHhAoVDA0dERAwYMkLmfP/30k+xLzdraGl5eXrIj9KFDh0JHRwfFihV76TjNnz8fERERGrlSr5O/8VZiYqJsxapUKtG5c2e0b99e5mKrpzdp0gSBgYFo27Yt2rRpg+LFi6Njx47w8fFBjx494OnpKesm9+7dW+7r7t27ZYOpmTNnyrrX6tIAd3d3+Pj4ICIiArdv30ZYWJhs8f2mnKDY2FjZgEHt2LFjUKlU6NChA+zt7fHVV1/J3+Tp06f47bffZHG1ui6m+tmWvxuc+fPnIzIyEjY2NujatatGPb527dohISHhpcYv/6wWAQCzZ88uMLCLioqSDaTq1q0rG87k70br4MGD8PLygr+//zvLlStoPQ8ePMDUqVNha2srM2LUnj9/jnnz5qFVq1bvLA0M6orYsWPHEBISgg4dOuDkyZM4e/YsXF1dUblyZdy+fRupqamws7ND/fr1UblyZdjZ2eGLL77QKPZr0aIF+vTpgzt37qB///7YtWsXatasKQO7+/fvIyAgAE2bNoVCocCoUaPkCbRjx46XWhXduHEDAQEBsLa2Ru/evWW9ME9PT5QqVQohISFo27YtQkNDIYRAuXLlEBYWhgoVKkCpVKJGjRrIy8vDs2fPMGzYMERGRmLmzJlym29z8o4ZM0Z2t3Dq1ClYWFjIhgLVq1fHTz/9hOTkZKhUKnh7e2Ps2LG4desWKlWqBAsLC8TExGDGjBl4/vw5kpKS4OTkpHHR50/D7t27sWnTJtm57YMHD9CkSROYm5vDysoKa9euxfHjx+WNUl1f6cyZM7KIT93nFvCifpGBgQEmTJiAXr16wdDQEP369UOXLl1kADNs2DAkJyfDysoKs2fPxsSJE+Hn54fo6Gj4+PjAxsZGptvU1BSjRo3Cpk2bULlyZVkPSN2xrfqhsWPHDjx//hy1atWCnZ0dhBAYP348FAqF7B6nW7duMsdBHWDfuXMHtra26NatW4HH53UGDBgAKysrnD17Vo5W0qRJEzmag7qPr/z1hqytrWFnZ4dRo0bB09MThoaGqFOnDg4cOCAbBQEvuuDQ19fHyJEj5TlhaGgIa2trtGrVCoMHD4YQApaWlhg6dChKlSoli/2EEBg9ejROnTqFx48fo2rVqqhRowaCg4M1AjvgxcOmW7duMnfzypUr8PLykq24K1asiF9//RXAiwfLgwcP4O7uDgMDAzg4OKBUqVLw9vaGtbU17O3tYWVlJes06erqQl9fHxs3bkRWVpYsiho4cCAiIiI0ukyIjo5GUFAQNm/ejG+//RaWlpbw9/eHi4sLSpcujStXriAoKAhTpkzB3bt38ezZM7Rq1Qrjx4/HrVu3kJWVhUmTJsHAwACVK1dGQkKCbEAxatQouLi4vHJUhFcF7UlJSQgMDJR1Gf/44w8MHToUrq6usmPekiVLyuLEX375RWNdR44ckcWMDRs2hFKpRHx8PMqUKQNTU1MsX74c+/btkzlOKpVK1vtauHAhqlWrBk9PT0ydOhXp6ekvdcj68OFDhIWFyRy2FStWQE9PD5GRkRg6dCjs7OzQuHFjzJgxQ/aB2Lt3b9lJrr6+Pvbt2wfgxcuPUqmEn5/fSy84b9MR7D9bue7btw9ffPEF6tWrJxtAVKhQAeXLl4cQAvb29jA3N5ddvLRv3x6mpqZYsWIFunbtCjs7OzRs2BD29vb4/fffkZOTg2HDhslhBtX1JH///Xd5Xahz4dauXYsqVarAwsIC1tbWsLa2xqJFi1CmTBkEBQW9sc/J3Nxc9O3bVwZWBw4cwP79+7F69WrY2NhgxowZ6NGjB4KDg9GlSxecP38eM2fORGBgICpUqPBSJ+Hqurnq47p//35ERUXB399fdovz5MkTDBw4EM7Ozi8Vuf6zj9L8nWsXFNh999130NXVReXKlQG8aEynUCjkOae2d+9exMfH/6ecsYLSmJKSgl9//VX2+pCdnY1vv/0WpUuX1uhGCCi4CtZ/waDuI3D06FGEhISgffv2OHXqFC5fvozixYujUqVKOHfuHGJjYzF8+HCEh4ejdOnSOH36tOxF/KuvvoJKpUJCQgKSkpLkm8jPP/+M4OBgqFQqHDt2DA0bNoSvry++/vprjRO4f//+iIyMRGpqquzRX/3mPWfOHAAvbk7qB7KhoSESEhJQvnx5tGnTBgkJCWjVqhWsra0hhECJEiXkus+ePQsnJ6eXWi69jdmzZ8PX1xdHjx7F/PnzUb58eURERMDFxQUlS5ZEcHAwDAwMMGrUKI1OIw8ePAgbGxsolUoEBAQgNjYW9vb2r2wU0bt3bzg5Ock6T1OmTEFOTg42b94MlUoFHR0deHt7y+5bZs2ahdzcXGRmZuLPP/9EsWLFEBQUhJYtW8obzfLly2Wrx4ULF6J79+7w8PDA2LFjERoaCiMjI/Ts2RP37t3D6NGj5e8xZswYlCxZUuaAVKtWDYMGDYKFhQW8vLzw6NEjrFy5Eg4ODujVqxe+/fZb9OnTBzo6OqhYsSLu3r0rx7NU7/eKFSvQvn17WFlZYdmyZS+Ne6u+6VapUgXNmjUrVBFEXl4e7t+/j3LlysluWNQ3aHWOoVKpxLx583Ds2DE0atQI+vr6UCgUaN26Nf78808EBgbC0tIS8fHx+Ouvv5CdnY3s7Gz07t0baWlpsnh73bp1MDAwgJeXFzZt2iSH/vH09MSPP/6IR48e4dtvv4WTkxMUCgVsbGzg6uqKiIgIBAYGQqFQYMqUKRg2bBjCwsLQpUsX2TF3bm4u9u3bh9OnTyM1NRUhISFo164dgBeNi0xMTFCpUiUZ2G3ZskV2RaFUKtG9e3eUKlVKdkmhznVUN2wwNzeHh4cHEhISMGbMGLRp00ZjKKX8OQ8VKlRA8eLFsWjRIjg4OGD16tUYN24cfvjhBzx48ADVq1dH69atsXXrVgwaNAg+Pj4v9aV18+ZNTJo0CYGBgXBzc0NSUhIWL16MWrVqySoI//z91VJTUzXS8+zZMzg7O6NPnz5y2qZNmzBp0iSsWLECu3fvRpUqVeDv7w8LCwt4e3trBHZ5eXk4fPgw+vXrh5CQEFhZWaFTp05QqVRwdHSULxJPnz6Fq6srdHR0oFKpsGfPHty+fVsOwTd79mxERUUhODgYYWFhWLNmDa5du4br16/D3d0dQ4cOxYoVK2RgnZaWhtzcXNja2sLCwgJ+fn4ICQnRaO0bEBAgqz+oj2H//v1hb2+PoUOHFjhU3+uuBeBFv4vTp09H2bJloa+vD3t7e3z33Xdo2bIldHR0ZJClq6sLd3d32eq7YcOGsLS0hKurK0aOHIlDhw6hTZs2iI2Nlff0NWvWwNLSErVr14aRkRE6d+4sS1YOHjwIlUqF0qVLY+HChbLu3Y0bN3Dz5k1MnjxZ5v6rGyS8br/yT69SpQqcnZ1RqlQpWFlZoVixYqhYsSJWr16NL7/8EmZmZrI0x8vLS/YdmD9AuXfvHooXL47g4GDZ68LPP/+M8uXLw8vLC1FRUahatSocHBxeulfnX8/XX3+N2NhYREZGarTWnjNnjjxPjxw5ghEjRmDevHny3mFmZoZZs2bhiy++gJmZWYEjGv2XwC7/8RowYAA8PDwQHBwMe3t7NGvWDCdOnMCTJ0/wzTffICAgAAkJCf96W2/CoO4jceTIEZkDtnbtWqxcuRJCCFlP7Nq1a5g7dy7CwsLg6+uL2rVro0aNGrIvLHWdoWLFiiEpKQk9e/aEQqFASEgI7OzssHfvXgQGBiIoKAiDBg3C7Nmz0bFjR5iZmeHHH3/E8+fPsWHDBly+fBlRUVEQQmDhwoXYsGEDLCwssHTpUqxYsQJCCAQEBKBBgwbw9fVF27ZtcfbsWZQuXVoOg1S/fn189tlnsLS0hJ6e3r8aw++PP/5AYGAg5syZgzFjxiAsLAw5OTkoU6YMnJ2dZQfAa9askRfUlClT0LhxY3lxDxkyBLNmzdIY7zX/xbdr1y6Eh4dj7969OHXqFNq3b4+IiAiMHTsWjx8/RkREBBYuXIiePXvCyMhIFs09fvwYo0ePlt1vqAOlnJwcrFixAjNnzsT8+fPRrVs3GBsbIzk5WR4Pd3d3dOnSBe7u7mjevDkCAwNx9epVOeKGmZmZbOARFBSEmjVr4osvvoAQAnFxcbhw4QICAwPx008/Yf369TA1NUXDhg3lsD8zZszAqlWrZIu3wMBALFq0CC1atICJiQmWL1/+UmCXlZWFyMhIOTzSm0ydOhVZWVny4Z+WlgYPDw+Ym5vjzJkzsrhV3cn0tm3bcPToUezZswcuLi6yqK548eIICgrC5MmTUaFCBbRq1Qo3btzAhQsXEB0dLdd/+fJlhIaGokuXLggKCsL06dNlca6uri46duyIVatWwc/PD05OTujWrRtiY2NlPTVLS0uMHTsWwcHB8tpQF2eqqXMkfvzxR4SHh8sWcOvXr0doaCjq1q2LS5cu4dmzZ+jatSuaN28ui/kMDAwwe/ZslC1bFvXq1ZM5tbVq1ULz5s1RvXp19OnTB/Xr10fp0qXRuHFjje56cnNzNd7Wo6Ki4ODgACMjI+zdu1fj2H///fey7qSnpyeOHDmCCxcuYMeOHfjjjz9kcKKuHzpy5Eg0aNBADj/VpEkT+fBKTk5Gt27d5HH+/fffERISgl69emkU306cOBFVq1bF5cuX0adPHzg5OcHf3x9+fn6wt7fHqlWrcPPmTVStWhVmZmbw9fWVlfdHjBiB8PBwfPXVV/Dy8sLBgwdli0T1OVKtWjUAL3JqLCwsZNWCsLAwODs7Y8qUKTA2Nsbo0aNx4sQJ1K1bF6ampvDx8cHNmzcxbdo0mJmZwcXFBWZmZti/fz/++usveHh44Msvv8TJkyehp6cHPT09/Pzzz/I+cPbsWdlQYsKECXJ/J02aBENDQ4wePfqtK6vn5eVhzZo1MDAwgLe3twzsS5UqBTMzM0RGRqJYsWKy3qW6P0lzc3McOHAAs2fPllVk1EOc3b9/X3Z6/fvvv8PFxUWONOPn5wchBBo3boxnz56hb9++sLa2lh1Wh4aGys6n1efY9evXceDAAQQGBiIuLu6t9uvrr7+Gvr4+jIyMsGvXLlksXqZMGYSEhKBr166IjIyEsbEx7OzsZD+H6sDu0qVL8oX+3r17CA4Ohr+/vww6Dx06hPnz56NLly6YNWvWS3Ve80tKSoKdnR1mzZqFTZs2wcrKCmXLlpVDiH3//fdwc3NDhw4dsGHDBly9ehXnz5+Ht7e3HHps+/bt8r6grlbxLk2bNg0ODg6yWH/gwIEwNjaWdSHT0tLw7bffwt7eXuOce5cY1H1Ejh8/Dj8/P+jo6MDLy0v2qRMSEiJzFXbt2oWJEyeiVatWaNeuHZydnTFjxgzY2dkhKCgIhoaGWLx4MS5duoQ+ffrA1NQUxYsXR1xcHJ4+fYoOHTqgYsWK8Pb2RlxcHH7++WcEBgYiIiICXl5eOHv2LM6dO4eYmBjY2NjA19dXjs/4xx9/yOJDDw8PGBoaQqVSoWHDhkhJSUGxYsXg5OQEfX19WFhYoESJErIvobfJVlb3SQa8uCkkJSXBwcEBAwYMkDf+nJwcODk5wdDQEFFRUYiJiZH7pO67Sd0VyeusWrUK7du3R9++feWN5PHjx6hWrRpKliyJYcOGoWTJkqhbty6srKxkZe/s7GycPHkSDg4OGk3PgRcVy9WVomfMmIFffvkFJUuWhL6+PszNzWXHwuqHqZOTE5o2bYpq1arBzc1Njvuq7ojU0NAQ7u7uqFq1KmJiYmRfdOqAyMzMTLZcrV27Njw8PBATE4PvvvsOAFC5cmWoVCpER0cjPT1d9l7+z8Du6NGjKFOmzFsNKP/999+jefPmGvs9YcIEhIWFyZcQdW/uCoVCDqWmHuvV3t4eZmZmsLW1xZAhQzTGCY2MjESbNm00erNfunQpLly4gJEjR+LAgQPyhSMiIgIdOnSQxZzFihWDl5eX7DR25cqVMDU1RZcuXVChQgWEhITIuorPnj3D7t27MXHiRLRv3x579+6VxbELFiyAj4+PrEuUkJCADh064Mcff0STJk0QHx+PKlWqoEaNGjh+/DhKlCgBpVIJfX19dOjQAcHBwbh9+zZ69OghgxN1Be2cnBxcvHhRNkz4ZxHTtm3bMGrUKOzatUtey8OGDXspsLh8+TJOnDiBW7du4eeff5Z9GAYFBaFRo0YvPRgfPXqEVatWoVq1ahqNJRYsWKDRCe2TJ0/Qq1cvVK9eHZaWljLH6Pbt21CpVOjWrRusra1l57dJSUmIiIiAjo4O1q9fj2vXrqF69erQ0dGRlcLr168PZ2dn+Pr6ok2bNli/fj0MDQ2hVCrh4OAgq3CoRwXo06cPqlWrhnnz5mHDhg04f/486tatK/sVU+f4VK1aVY5gcePGDRw5cgQ7d+7Enj17kJeXh+bNm8vc87y8PHl++vn54dSpU7L4cePGjXJYt/ydb0+dOvW1dUzV1MOcPXnyBE2bNsXMmTPh6+sLPz8/BAQEwNXVFSqVSubIqYM6X19f+Pj4yPqyv/76K8LCwqCvr48ffvhBno/qdA4cOBANGjTA48ePsXPnTujq6sLV1RWVKlXCggULYGdnh+3btyMwMBBCCJQuXRphYWEanYyrnTp1Cvb29vjtt99empe/McHUqVNRp04dfPvtt2jevDmMjY1hamqKGTNm4OTJkxgxYgRKly6NmJgY+Pj4ICwsDOPHj5dVDFavXo3AwEBMnz5dTrt79y6CgoLg7++v8bL9JuqXWfVIRxs3boS5ubnGuMdPnz7F+PHjZWtS9XLh4eHynpKSkoKePXtixowZ72U4sNatW8uX459++gkWFhby2fH06VPk5OQgNTUVK1aseCdFvgVhUFeE/nlS3bhxAw4ODqhbty7i4+MxbNgwrFy5Eu7u7oiKipIXhtrQoUNRvXp1AC/qzKjf4IAXAcrq1avRq1cvmJqaYt68eQD+b/Dnhw8f4unTp8jIyED79u1hbW2Nhg0byjesZ8+eISoqCjo6OmjSpAmmTp0qc1kWLlyI7OxsJCQkyCFn2rVrh8uXL2PLli1YunQpUlJSClWHbuLEiejTpw927dqFGzduoFGjRlixYgXKly+P2NhYNGnSBJmZmcjJycHff/8Nb29v+Pn5wcjICHZ2dnKsSx0dHflWBhRcvPDkyRNUr14dRkZGqFixInR1dbF8+XL0798fVlZWaNWqlWyCbmNjgzp16gB48VB+/PgxatasKfvG++d6ly9fjhIlSsg+zL788kv06NEDxYoVk33ONWzYEHl5efjss8/kDVhdlGhnZ4evvvoKCoUC1tbWcHR0lIPem5iYyP6m9PT0YGNjg8TERNlKUp1boX4QXLp0CSEhIRo9k7dr1w4mJiZYtmwZgBdvjgEBAbIz2jdRt+oFXnSzExcXB11dXRQrVkwG/I6Ojjhz5gxCQ0Ph5uYmGy2oVCpMnDgRw4YNQ5kyZVCiRAnMnz9frm/q1Knw9vaWdegePHgAExMTVKtWTRaFxcTEwNzcHHXr1sW6devg5uYmi7o3btyIGzdu4MSJE3B3d5cd5c6bNw+GhoYwNDTEjBkz8PPPP8PS0hLNmjVDvXr14Orqiq5du+Lx48dISUmBr6+v7A9N3Q+esbExWrRogRo1asj6UOfOncOJEydkDoxSqYSXlxe2b9+Odu3awcXFBSYmJrI+49GjR6FQKLB582YsWrQIERERePz4MbKzs5GZmYk6deogIiICHh4esk6kQqFAfHw85syZg02bNuHMmTOyntyWLVtgaWkpu/RR1xuLjIyUdYvy9wmZPxBXW7FiBXR1dWXfYurlatWqherVq8POzk6Opakecuqnn36CnZ0dYmJiULt2bdl35Z07d3DlyhU5zm3x4sVhYWGBr7/+GjExMXLoN0dHRyQlJcHKygpGRkYy57ZevXqoUKGCRsX5zMxMlClTBocPH8bDhw/h6OgoG4mtWbMGAQEBKF++vAyC1PWXIiIikJCQIIeCiouLg6mpqRz/uFevXrKPPnd3d0RHRyM2Nval4uk3yc3Nxa5du1C+fHn4+vqievXq0NfXh4mJiWyAlH/IRHUOnaOjI9q2bYv69evDzs4OXl5esLS0RLly5eDs7Iz+/fvLfkKzsrJkF0OTJ0/Gs2fPUKFCBejo6KBVq1bo1KkT6tati2fPnqFXr17Yv38/jhw5grp1677UyXReXh4ePnyIkiVLvtTR+LFjxxAUFIThw4fjyy+/lC/vP/74I/bs2QNdXV0YGRlhx44dyMrKQp8+fbB582bZ7VWPHj1QvHhxTJ48GWvXroWxsTG++eabl6oHqOt4BwcHv/U4swcOHICLiwsAyE6V1S+06enpaNiwIWrWrIno6Gh8/vnnshP+ZcuWQaFQYP/+/bh69Srq1Kmjca/7L4HdP59rWVlZqFatGjZs2IADBw7IOpzqed988w3Wr1+v8Z33EdgxqCsiffv2lRWC1a5cuQJ3d3eZdau2f/9+ORDx9evXZZ0vhUKBatWqYfPmzTA1NZVFIzExMfjpp5/w1Vdf4fjx4+jVqxfMzMw0xrQEXpyUs2fPRmBgoOzKIX/Lqr1798qbUXBwsOzxvXv37mjevDlUKhV++eUXTJw4EeHh4ejQoYNGBfQ3DeCc35AhQ1CzZk1YWFigTZs2KFmyJOLi4tC0aVO4uLigcePG+Pvvv2WO5bFjx/DFF18gKSkJPj4+aNasmQy41K278qcj/7/AizfG5s2bw9PTE7Vq1YKRkREsLS1x69YtPH78GM2bN0ebNm0wbtw42SdcvXr1ZBciBgYGWLduHXJycpCcnCz7C8zIyMCkSZOgo6MDBwcHAC9uHOrhfmrUqIHNmzfj7NmzCA0NRdWqVREbGyt7jLe1tYVCoZAVqs3MzGBsbAylUgkhBBISEtCxY0e0a9cOBgYGsvg9ICAAlpaWiI6Oxh9//IGcnBw8fPgQvXv3Rq9evTT2vUOHDrCwsMCcOXNQsmRJjbETX/d75W8tumvXLlmPsmfPnrIrFqVSCXd3d3h6esrWhvr6+vDw8MCqVauQl5cnx75s164dihUrJisuZ2dn48cff0ROTg6SkpLw3XffYf/+/fK4TZ48WY5nqW4Z7OjoCGtra3h4eGD69OmypVlUVJSs47hkyRLExcVh0KBBOH36NIoVKyaLuDIzM6FUKjFkyBC5n7t27cKgQYPw2WefwcjICH5+fnJEiAYNGqBXr17ygXf69GkcPnxYdiWjr6+PW7du4dSpUzhx4oRsqNKnTx/ZpQ3wog6UOqdC/bKmfqG6cuUKzp07h8qVK8txfV1cXGBjY4PSpUvjzp07SE1NlS9+wIvGLm5ubqhRowbKly+PChUqvNQg5lW/7bJly6Crq4t+/fohOzsbO3bsQEREBK5evYp169YhMDAQ1tbWMDY2hr29PRwdHWUXGunp6RBCwNTUVG5v4sSJsLGxga6ursw5XbVqFaKjo+Hk5ARHR0ccPHgQ7u7u0NfXh6mpqWyVamtrK4MAdXrj4uLw+eefw9PTE127dpWjeqSkpMDb2xvGxsaoWbOmvPeo+8VU13m0t7eHEAIjR45Ex44dYWtrK7elUqlw9OhRnDlzBmXLlkX9+vXfqlFEfhcuXJCjhzRp0kSOVax+IVBXTVDn6Kq7G3F3d0e1atXQpUsXNGzYEHp6evjzzz8xZMgQhIWFYeDAgbhz5w5OnDgh+/hUKpWwsrJC6dKlsWPHDlkS4+zsjCpVqiAsLEwet++//x5GRkYvtdpdsmQJFAqFRk5Zbm4u0tLSMGjQIFhbW8PU1BTHjh2TxecGBgaYM2cOmjZtCpVKhXXr1qFatWqYNGmSRr9q6jpt5cqVky+9T58+xe3bt7FkyRLZp+Lff/8Nd3d3VKhQ4aWXjYI6pn/48CGqVKmCpKQkmJqaytII4MXIFup+Q9esWQMjIyNUqVJFXv+NGjWSI4UEBAQU+HLzX0ybNk0eY3XGgIGBgUbx96NHj1C5cuWXMgLeBwZ1RaRHjx6yorT6xH369Cns7e3lcEhqqampCAsLg0KhQK1ateRFpO7EUgghW3/t3btXPujUA4VfuXIFffr00aggq/bHH38gICBAdt9RpkwZ9O7dW+YGjBs3Tm5DR0cHnTt3lgNeq/uJUnd94Obmhm7dur0xZ+5V8+/fv49169YhIiICfn5+cHBwkJ266uvrw9jYGA4ODggJCUHz5s3RokULJCQkoHLlyjhz5gyGDBkCe3t7jUYZ+bd18+ZNpKamanSoGh8fj+LFi0OhUMDY2FgWwTx9+lTmau7ZswetW7dGQkICJkyYgMePH8vRAe7evYsWLVpAR0cHmzZtAvDigV25cmXo6emhcuXK8PDwQPfu3bFt2zZYWFigRo0amDFjBurVq4eOHTti8eLFcHBwQPHixWVRrUqlQp06deQD85tvvkG3bt0ghEClSpXQsWNHnDx5EtOmTUPJkiXh7e0tR1jI39N/SkqKHO83P3X3KupcyNf9Lup5+ecfO3ZMNkhp1aqVLDr/6quv5APa1NRU/pZKpRJfffWVxg370KFDcHFxgaWlpUbnuN26dYOOjg4sLS1hbm6OL7/8EkZGRjAwMEBISIjs40s9TFfr1q3RuHFjeHl5YcKECRg/fjx8fX2xd+9e5OTkoE6dOhgzZoystB8WFgYAsqV5/uOVv9Pa9evXw8HBAaampjJnwcLCAs2aNZMjPKhUKpQpUwYVKlSQDYk8PDxkYHDz5k3069cPhoaGsphT7Y8//sDx48dRsmRJ+bBTpwsAFi9ejPDwcDn2cevWrTXO7c2bN2Pfvn148OABSpcujc6dOwOADCT9/f3f2Cek2tKlS2XH5U+fPtUYnu/BgwdYv349Fi9eDC8vLxQvXhz379/HhQsX4OzsjM8++wwlS5bEkSNHcPHiRdy/fx85OTno0qUL9PX1ZRHgqlWrZB220NBQVKlSBZUqVUJwcLDs9FpHRwdWVlaymA14EYR4eHggJCRETluxYoU8PwIDA2FjY4Nq1aph3bp1sLCwQL9+/WBvbw9XV1colUo4Oztj7969+Pvvv+Hg4AAvLy+4urqicePGMkfs3LlzbxzIPj/1MVq+fLkcDqtEiRJwcHCAiYmJrJ7StGlTlC1bFq6urrCxsUGFChVQrVo1DBkyBHFxcahSpYoMBNXdUA0aNAjBwcGIiIhAuXLlUKNGDTnknomJCdq3bw8AcoQEpVKJ8PBwWa0iLy8PO3bsQEhIyEsv2gcPHtTo5Dr/tV2/fn05IsuIESNkndKKFSviwoULyMnJQYMGDSCEQGBgYIEd5T579gzR0dFyeMR+/frJeqKmpqaYOHEigBf3+38Wwf7zHqT+Oz09HY0bN4aenh569eol5x8/fhxmZmYoX748cnNzZTdS6iJPtfXr1+OXX375zx37/lNmZiZKlCiBtm3bAnhROlKnTh14enri9u3bsh/YGjVqoEyZMu+tyDU/BnUf2D/fljdv3owlS5bIIGrkyJEICAiQQZp6+a5du2LQoEEYOnQoFi5cKC9U9diZLVq0wL59+/D7778jPDwcurq6smg2Ly8PFy9eRJ8+feRNPv/Yr+fPn0dgYCAiIyPRunVrlClTBr169UJGRgY2btyI4sWLw9vbG2ZmZrK7Bg8PD3h7e2PlypW4cuUKwsLC0Lx5c41hWwqS/6LdsGEDlixZIlvZqt27dw87d+5ESEiI7K5DV1cXlSpVQrFixWTLsbp166JGjRqYOXMmmjZt+tLQX/mP9bBhwxAeHo7ixYsjNDRUDqh8+/ZtxMXFITAwUI4VqU6Pur5MQelXN56YOXMm7t69i4SEBOjr68u+orp27YqQkBCYmJjA1tZWHvegoCCYmpqiatWqKFasGBwcHNCxY0c0bNgQY8aMgYODA8zMzGTXHOqi1hEjRuDq1auYNm2aDGjUPcYPGDBAjhqifpt/9OiRTGtycjKqV6+u0Z8cAI0A/00BXf6h6mJiYlCzZk04OzvD3Nwc9vb26Nu3L54/f47c3Fzs3bsXfn5+smL+3bt3oa+vDz8/v5cGjK9VqxYMDQ1hZGSE69evY82aNdDX10dISAh0dHTQtm1buLi4wNTUFBYWFqhUqZIMoBQKBaKiouDn5ye7/ahXrx6OHDmCyMhIuLm5yX6o8g/07e/vj1u3bsHT0xMdO3aUD7Xdu3ejU6dOuH79Or7++mv5MpF/pBR1jqiRkZG8FmxtbVG5cmVERESgfPny8PHxQVBQEB49eoTz589DoVBojDELvLjOdXV1sXbtWtSrVw9BQUHYsmULFi9eDIVCgV27dmHNmjVQqVR49OiRbETTqVMnmVOltnjxYlSuXFkGJ2vWrJGt0/95Pap/x/v37+PKlSvIycmRx+aHH36QgV1WVhZOnz4NhUIhg0X176WuP+jo6IjGjRsjJiYG/v7+iIiIgKWlJerXr4/MzEzs3btXjme6ZMkS5ObmYuHChTLQMjAwQGhoKA4ePCg7NV6wYAHatm0LW1tbGRjfv38fffr0gbe3N+rXr4/u3bvD2NgYRkZGsqP0OXPmIDIyEt7e3ggKCkJWVhYuX76MS5cuYcyYMQgMDET16tXh6+sr96d9+/ay5Wn+hiGvo74W7t+/j/v372PFihVyH9XnpLm5OSpVqiQbTNjZ2cHf3x8mJiYwNzfHgAEDEBsbi7Jly2Ljxo3Ytm0bhg4d+lL9t4YNG0JHRwcdOnTAqlWrcP/+fbRq1QoODg6wt7eXLbSfPHmCbt26wdDQELNnz8ahQ4dw8+ZNVK9eHVWrVn1j7rvaoEGDYGlpiZkzZ6JXr14IDw/HwIEDMWfOHFksHBoaiuDgYDg5OckSnX8GKo8fP0bLli1RpkwZ6OnpoUGDBvj+++9x48YNtGzZUqb7n/Kn8+uvv8bnn3+OKlWqYPHixUhPT8eNGzcQEhKCyMhI9OzZU46Lraenh6ysLNlSXV3kqR7u7Z/edWA1efJkVKpUSY5bu2bNGlSuXFmWoISEhCAiIuI/Df1VGAzqiliHDh2gUChkHadLly6hffv28Pf3x4ABA7BhwwZ0795dPkR8fX3h7e0NKysr7Ny5EwDkAOaWlpYICQlBXFwcdu3aBScnJ9nKqUGDBmjXrh3u37+P/fv3w9vbG507d5ZvpqdPn0apUqUQGRmJhg0bokyZMihXrhwcHR1Ru3Zt/PXXX/D394dCoYCtrS1+/PFHlCpVCi4uLnBxcUGjRo3euK//bPbt5uaGkJAQuLm5oUqVKi8FHdnZ2ShfvjwsLS1RrVo1nDhxAs+fP8eaNWtgZWWF0aNHA4C8Kb4qV2L48OFQqVRYvnw5ZsyYgU6dOkGpVGLkyJE4e/Ysbt68iUaNGsHLywsNGzaEmZmZxs1gzJgxsuK8+oK8f/++HElg7NixSElJkYNp169fH9bW1ti/fz+KFSsm+w1Tt9ps27Yt+vXrh3bt2qFUqVKwt7dHUlISZsyYIRtHqIeBK126NFq0aAE/Pz9ERkZi69ataNiwISpUqAB/f3+0atUKNjY2OHjwIHJzc/Hjjz++NIbn4cOHUadOHdlBtbqYT+1NOavq361v376yc+fOnTvDyMgIo0ePliMsqMdXfPr0KerXr4958+bJh/nXX38t63+pc0rT0tLw2WefYdKkSahevbrMiVD3wad+yKkbHajHjFUqlfD398eOHTuQmpqKDRs24KuvvkJAQAAmTZoE4EUR6g8//ICpU6dqDH+Um5srO85WdwSq3v/OnTsjMDAQK1euhI6ODuLi4rBq1SpZv83V1RVlypSBUqmEubk5atasifj4eJQvXx7FihVDs2bN8OTJE5w+fRpubm4oX748fvnlFygUCgwZMkSmIzk5GXZ2dvjll18AvMjZbdKkCUqVKoUVK1agXbt2OHPmDG7fvg03NzdZeX3z5s0wMjJCp06dNPoZmzRpEuzt7WVg0r9/f/Tq1eulYkT177h69WoEBATAyckJpUqVQmJionwgqQO7r776ChkZGVi+fDlMTEzk6DD37t2Dp6enrA4QEBAADw8P2RrV2NgYhoaG8PHxkcXv6qLIhIQEZGRkYOHChXBzc4NCoZB9uBkbG8uGCSkpKahSpQr+/PNPHDp0CM+fP0dGRgaWLl2K6tWro3z58jAwMJD3TODFvWLWrFkwNDSEubk5rl+/DgDyu4cOHYJSqUSFChXki4U6l/ttgzr1S966desQFhYGHx8f6OnpoXnz5jAzM5OjxigUChgaGmLHjh2wsbGRDUNiYmIwePBgmJubY926dahXrx5+/PFHODs7y9br6jQDL4pPra2tZWfqv//+O/Ly8hAfHw9DQ0PY29vLHLu8vDz07dtX1l319/dHWFiYDCQKusbzT1u9ejW8vb1lFZ2HDx+iX79+CA8Px5AhQ3D8+HEsXrwYlSpV0ihyVZ+HFy9exNGjR2VO4+PHj7Ft2zYsW7ZMI1esSZMm6N69+0uB5j+DS5VKhc6dO6Nx48ay0/y//vpLljqpO+hu06YNoqKiMGTIEJiammp0fn3kyBHUqFFDdnn1X73qPnnz5k3Y2trKusDAi+fD4sWLZW8E7zqH8HUY1BWR/Cd1165dYWRkJHsyv3z5MsaPHy8HY/f09ERERAQOHz6MJ0+e4OrVq7KvK/UJ26JFCzkkj3rd6t7GGzRogIULF/4/9t46LKu03fvnpru7uxtJQQEREBALRQywxg5MRB27Hbu7u3Ns1NGxu7u7A4P6/P7gt65936KOz35m7/fd757zOPax50FY97rXuuK8zvMbKCsr06NHD54/f87IkSOJioqiffv2IrE7d+4c2traaGtrCycFKysr/P392b9/P7/88gthYWEkJCSgqakpgMcmJia8efPmm5Wtb8Vvv/2GpaWluPe5c+cik8mIiYkRgPiSkhJKSkqIiYmhRo0aJCUlkZiYyIEDB/j8+TPdu3cnLS1NwXf1W/H69WuioqKoUaOGuHZpaalIhI2MjIiOjubQoUP07duXBw8e0Lt3bzQ0NMjNzSUhIQF3d3eF09XKlSuRyWQcO3aM2rVro62tjbGxMUZGRigrKyOTyZg5cybPnj0jNjZWAQxuYGDAs2fP6Ny5M82bN2f69OlCK2vEiBFYWVmJpEEC5N++fZtVq1aRkZGBTCYjMDCQsLAwunXrhr29PWPHjv1L7GLnzp0VbGr+VUuchQsXClHntm3bsn37djQ1NZkxY4ZgRRoZGREaGoqtrS3q6uqYmJhgZ2cnFv7+/fsL6Z3WrVvj6emJmZkZNWrUYNSoUVSrVk20+j09PUVyevz4cezs7NDX1xeeuWFhYdy+fZuCggJq1arFlStXyM3NxdLSUlS9oVymY9iwYSxcuFAkDRs3bsTPz4/U1FQePnzIwYMHFYShVVVVMTQ0FMnnmDFjRMXO19cXY2NjgoOD8fT0xNHRETs7O1RVVYWLiiRMLbVKV61ahaqqKkOHDmX48OHo6+uTn5/P8OHDxUHm/Pnz1K5dG19fX5F8P3jwAE9PT+7cuSPG3++//y4SO6lit2/fPqKjo/H39yc9PR1tbW1h7fV17NmzB01NTUaNGsXevXvJz88nOjqatLQ0kdhIOouDBg1i3bp1mJmZoaamRtOmTcXzcHZ2pk6dOnTt2hVVVVVBKqlUqZLAl5mZmTFjxgw6dOggDinZ2dl8/PiRpUuXYmZmhqqqKpqamgqWXv369UNFRQVvb29kMhlJSUmcO3eOzZs3M2rUKK5fv46fnx9jx46loKCABw8e8PbtW8rKykRr3snJSRx6oXyDNzY2xtfXVxi59+jRg5EjR1aoHn8rjhw5wtGjR2nZsiUqKio4OTnh6emJqqoqRkZGREZGoqGhQceOHdHT0xPVXXd3d5o0aUJ0dLQ4jEjVwUOHDvH582f69++PkZGRqCBKOpgLFiwQEIe4uDiR7N24cQM9PT3s7OwwNzdXsIs8ceIE+/btY+fOnT+dSPTq1QszMzOUlZUxMzMTOMh3797Ru3dvQkJCSElJITk5GXNz8wrXXbNmDba2tri7uwtij7y9IJQnOXl5eZiYmAhFhG/Fo0eP6NKliyC4QDmTPSAgQIj2fvnyRRxMnz9/LlrG8lqKnz59IiUlhdq1a/9tTg1SbNiwoQLJZPLkyfj5+f3Q1/y/o/UK/yR1/60hD9j/eqK1atUKTU1NBYuaL1++MGPGDKpWrUr16tXFIn79+nVOnDhBtWrV8Pb2Fjo9bdu2RUtLiw0bNoiBLImqwn8AZLt27crz588ZPXo04eHhtG/fXrRp9uzZg6qqKubm5nTs2JGIiAg8PDzw9/fH19eXnj178urVK37//XcSExPp3Lmz2Py+N3nkf/7y5UuaNWsmSCIbNmwQGBgrKyucnZ1FSwXKMX3R0dGsX7+etLQ0IiIiOHLkCGPHjsXb21ss0N+Lhw8fCjkRiSW3du1aHB0dCQgIID09XbRlT548CZRXIyZNmkRERAQNGzascNq9d+8eNWrUwMLCgvPnz7N8+XJGjBhB69atFWyvDh48yMaNG0UbRmrFHDt2jHbt2gmNP0k01NbWFhcXF5o3b05WVhYjRowgPDyciIgI7t27R2FhIbNmzUJDQwMrKyt8fX1RVlYWi/DXIc8gLC0tJT4+XsGa6l+Jzp07Y2tri4mJCWlpabx8+RJ7e3uqVKnC/v37WbZsGba2thgZGYlkLzAwEGNjY0JCQoRI6PLly+nWrRs+Pj6oqalRp04d/Pz8UFNTIzIyUmhIqaio0LhxY65fv87t27dFlbhRo0aEhISgo6PDiRMnSE1NJTMzk7KyMqZOnYqKiopgm27ZsgV1dXWho1WrVi2x2axcuRI/Pz/09PTw8vLCzc1NbLhSG83MzIwePXoIXKdEhlBTU8PT05NKlSqxePFili9fzowZM1BRUfmuztby5cuFz62+vj6pqan4+Pjg7e3NqFGjyM/PJy0tjQYNGhAUFMTmzZspKyujsLCQP//8k6VLl4rkY8eOHWhpafHLL7+IjWL16tV07tyZZs2afTOhkw4/7du3r9D+Wr58OVFRUfTt25exY8fSvHlzgoODRTV20qRJzJ49G01NTbGxDh8+HD8/P/E8lJSUGDVqlGCDampqoq6uzqVLl3j8+DGDBg0S2nTt27fn06dP7Nu3j969exMVFSUSmgkTJmBgYMDKlSt58uSJ0LRr0aIF+vr6LF26lHPnzmFvby9s8iQ7t1OnTonkSZpvubm53L9/n379+gnZp9q1a9O4cWN0dHS+y76UX7PmzZuHr68vzs7OGBsbExgYKFjXEo5SSiSVlJSoVq2a+K46OjoCnxsfHy+elb6+PtbW1hQXF/Po0SMGDRqEo6OjkG6RnoWSkhLh4eEKe8e2bdvIzMykWbNm2NraYmFhoYALlY9vJRLyP9u+fTuWlpaMGTMGLS0t2rZti0wmE4Se169f06lTJyIiImjUqFGFFuKff/4ppJVu3rzJzp07SUxMJDExUeBE16xZQ1ZWFi4uLpw+ffqb9wnlhx+ZTIatra0gC0pJkjR/OnXqRP369alevbpwArlw4QK+vr7ExcWRl5fH5MmTiY2NxdfX94eVyn81SktLefDgATY2NgQGBpKWlsalS5dEa9jX11fApv5uMsa/Ev8kdf9NIU3KnTt30qpVK+Lj45k8ebIC5qVVq1ZoaWmxfPly3r9/T2lpKXl5ebi4uGBra8uXL19Yv349zs7OeHp6CiNo+VNN27Zt0dfXr6AYPmvWLHr16sWGDRuQyWR0795dVOxcXV3p1KkTDx48YNiwYSxevJigoCCio6NxcnKiS5cuBAcHY2hoiJ+fHzNnzqR79+7Y2NiINsf3Jo18RUi6p82bN/P06VNOnDiBk5MT+fn5ODs7Y2NjIzYJafMtKCjAz8+Pdu3asWbNGjIyMrh79y6dOnWiRo0aCviiixcviv89evRoscHWr1+f+Ph4XF1diYuLY/r06UyePJm6deuSk5PD58+fhbK5hMmTbM4kUVopCZf+/7Nnz4iOjsbExERof3369IlatWphb2/PpEmTuH79OpMnT2bDhg1s27ZN6FXp6uri4uIiVMUl4dGQkBD8/f3p16+fYABu3ryZwMBADAwMqFy5Mk2bNsXZ2ZmePXsKGZHAwECxaX8dp06domPHjnz69Inhw4fTtGnTn6pMfF3JS0tLIzIykpycHExNTZkyZQp79uzB0NCQsLAw/vjjD1atWsX8+fOF6nt4eDgXLlzA29tbIbFbsGABKioq7Nixg6KiIt69eyeqdIMHDyY2NhZVVVWUlZVp2LAhN27coGbNmqipqVG7dm3y8/OxsLDAwMBAAS83ffp01NXViY2N5ffff6dly5aiHXPo0CFq1KhBtWrVFKoI+/bt486dO5w9e5YVK1aQnp6Oi4uL+HypwqqkVG6HV79+fZSUlNDW1sbe3l7ADk6ePImXl9cPnVPGjx+PkpISaWlpfPnyhadPnyKTyYTv67Fjx0SiGhkZSWFhIatXr8bIyIghQ4YoVDh+//13NDU1admypcK7+quqTHZ2NsnJyeJ/S/O2c+fOWFpaYmBgQNu2balatSpaWlr4+flx5coVCgsLBTygatWqQPkBLScnByUlJZydnYFyB46goCCRmEtJ09OnTxk0aJCQIBowYACFhYWUlZUxZswYoqKiqFSpEgYGBmKzlqJy5cp4eXnRvXt3zp49K2RN7O3tRaKtr6+PlpYW6urqjB8/nm7duomqubGxsThMDRs2jHr16pGamipahd+Lu3fvsmDBAkaPHo26ujrjxo2jV69evHz5klu3bokDgK6urhgnNjY2ODs74+rqKkgNEyZMoKSkhIULFwo8sr6+PufOnRPPXyJtmZiYEBsby8yZM9HQ0CAhIQEzMzMSExPZvHkz4eHhmJqaisRcqpJbWVmJSuqPQn6dzs7OJioqShDzJHmfadOmIZPJWLVqFR8/fiQxMZFu3bqJv5MfY8OHDxfjQQqJKCbdz9OnT5k3b95f4q3v3LlDTk4OMpmMtWvXsmDBApSUlNizZw8AxsbG6Ojo0LFjR+Lj49HQ0BAwmbNnz9K5c2e8vLyoUaMGrVu3rrBm/2fiW/vao0eP2LdvH2FhYULL9NKlS+Tm5uLu7q7QKfg/Ef8kdf+NsX79evT19WnevDn9+/dHX1+fX375RYjllpaW0qZNG2QymTC2/vz5M6NHj8bGxkZodM2YMYPCwkLBTE1PT1eYME2aNMHMzIyCggJR9ZLsqYYNGyYmS/fu3QWezMzMjIyMDLS0tIiMjKRly5ZCK61ly5a8efMGQ0NDzMzMMDMzw8/P7y+dIuQnxMiRI9HQ0FA4GU+aNImoqCi0tLTo27cvEydOpE6dOgKDJoVUfg8NDSUxMZGMjAz09fUFexjKN1VfX1/Gjh1Lx44dkclkXLp0ibKyMubNm0dkZCStW7fGzc1NSEzExsaSl5cHlFezKleujIeHB3/++SelpaXs2rWL9u3b07hxY2rXrs2IESMYP348x48f58aNG0RHRwtZkfHjx3PkyBESEhJQVVUlPz8fR0dHYmNjFXTz7O3tUVNTEyLCVlZWYkPQ09PD1NQUPT09kpKSxCl18+bNVKlSBRcXFzZs2EBJSQnv3r1jx44d6OjokJqaKqq1Xy9Cy5cvF4nHgwcP6NOnzw8lG75muUptjrlz5+Li4sLEiRNp2rQpUVFRzJ49mzlz5qCmpoaOjo6okEjYM+m0eunSJby9vQUOTiaT0apVKzZt2kRaWhp+fn5YWFigo6PD1q1befTokULFxcrKCh0dHbp160a9evUwMjKiUqVK6OjoEBwczKJFi9iwYQMpKSk4OzsTERFB06ZNiY+PVxhvR48eJSUlhYSEBCGvAuXt2JiYGGbMmMGKFSsIDg4WSYmKigoRERFCQPn169d06NABbW1tevToIfxqe/XqhaenJ8+fP/+mhI70HqWWXcuWLYWVkIaGBidPnhS4tuPHj/PgwQMKCgowMDBg1qxZCteS3onE9GvYsKFocX+rrX7s2DG2bt0KlGtb+vj4cPXqVYXfnTNnDvr6+sKSqqioCF9fXxwcHMjMzBQsc0lip0uXLkA52z4qKkq4GCgrK6OmpiakeaR2K5Rv7t26dcPBwYH4+Hh27dol7LzGjBmDh4cHNWrUEFIUX7584fPnz6K6lZCQgI6ODnl5eZSUlFBYWEjTpk2F3ZaKigq6uroCW3v69Gm6d++OqqoqGRkZCgbxX+NK5aOsrIyioiI6deokXHIKCgqEneOUKVPIy8ujRo0aVK9eHZlMJrB0EgO2efPmQs/PyMhIsOqTk5NRVlamRYsWCvfTo0cPYbOlra2NkpISsbGxGBsbCyastrY2ampqBAUFCYZyWVkZXbt2pXPnzjRp0uQvCU9StGnTRkAZpOrr8ePHiYmJwcjIiLCwMNzc3KhWrZo4OD148IDly5ezcOFCUXEbMWIEQUFB4jAtfcbGjRtRUVERkIcfYejk4+HDh9SuXVtIRmVnZwv/bcnBR4q8vDxUVVWFPBEgyFpS/F0J3bZt25g6dSpLly5VwCwvWbKEZs2aoampSUJCAjKZTEHE+v9E/JPU/ReE/ACWBsbZs2dxcXFRAHIaGhpiYGBA/fr1FcCcDRs2ZMuWLeJkXlRURP/+/TE2NsbLy4vz58+zZs0atLW1MTQ0RFtbm6ysLFGZWrBgAW5ubqLE36RJE2JjY2nevDlBQUEMGTKEefPmiURCMnyuWbMm79+/F96E7du3R0NDQ0gjREdHo6mpSbdu3YRe3M/EkSNHaNeunYJMAZTrCykpKdGtWzfevn1Leno6o0aNIiwsTKF0DuVg/6lTp1KnTh169OjxzRZTbm6uSA4kULEUgwcPFsKuxsbGaGlp4erqqmAgL9HTMzMzWbduHTo6OuTm5hIREYGKiopgsjo4OGBgYMCNGzfo0KGDaLkaGxvj7e1Nhw4dhFCnsbExBgYGBAcHC40iT09PgeeTtN4kUsTFixe5du0arq6u1KxZUyxKq1evplKlSkRHRwuWY2lpKa1bt0ZXV5dRo0aJxE6Khw8fEhUVpaDB9qNFTj6hO3v2LLm5udSsWZOUlBR+/fVX4uLiSE5OZujQoTRt2pTg4GACAgIIDg4mPz+fatWqYWRkhJeXl/gc6R2uWbNGOEE0a9YMR0dH1NTUaNasGd27d8fc3BxlZWXRHr537x4ZGRni2VhYWKChoSHezadPnzh+/Dg+Pj4ChN+7d2/u3r3LwoULqVSpEpqamiJJkeLYsWOkp6cTFhbGli1bWLduHZqamowfP57Lly/z4MED8Z7d3NyExl52djZ6enpcunSJ9+/fi2RBUtI3NDQUtnR//PEHjx8/5uDBgwqC4TNnziQhIYElS5Ygk8kwMDBAV1eXEydOsHXrVvr27atwyu/Zsyf16tUDyoHnEq41MzNTYNA2bNiAlZWVcKmQj7KyMj5//kxYWJgQXP348SOurq5ER0dz6dIlioqKWLZsGcrKymhqarJixQqRXHbq1ElUwpKTk1m4cCHPnj2jbdu2CgnEoUOHCAkJEYeTvLw8geWNjIykW7du4tD56tUrPn/+zPHjxzE0NBTJgVSxkw5f0vrSv39/TExMBLEiKSmJsrIyXr9+zcOHD3n8+DGvXr1i5MiRqKioCFKKNJ6hnEilq6tLgwYNRJX6W8nv1yb0u3fvxszMDA0NDSZMmMDTp09JTEwkLi6O0NBQkpOThciyVMk1NTWlUqVKODg4EB4eTtOmTYUo9fv378nLy2PYsGHIZDLy8vJ48eIF27dvx9zcnMOHDws3EknBIDExET09PSFovmvXLgXXHele3717p2A796OQpJ8mTpxIbGwsZmZmIlGRMG0WFhYYGhqSk5NDUVERZ8+exdXVFU9PT2EJJhUNZDJZBS/VH1Wu5e9v9erVTJ06lUWLFgl8aUJCAgYGBhgYGNCvXz9BTlJTU2Pfvn0K18rLy0NdXZ0FCxZ819f6341evXphZ2dH9erViY6OxtvbW0GDDsor582aNSMlJeW/DTv3vfgnqfubQxqwT58+VWjdHTp0iP79+1NWVsa9e/dwdHQkNzeXPXv2oKysTLNmzfjjjz/o3r07lpaWWFtbY2pqSv/+/Xn69CnFxcU0bNgQIyMjIe/g6enJx48fmTNnDsrKymRkZDBs2DA0NDSYPn06O3bsEPiOoKAgysrK6NSpEyEhIURFRQkwvmSiraysTHh4OAYGBlhZWREZGcmKFSvw8vIiJCSEzMxMBZPr78X+/ftFgimpvru4uIiqiTTot23bhoqKCmpqari4uODr68uIESOQyWRYWlrSpk0bYmNjWbdu3Xc/9+bNm1y/fh0oPzWZmZnh5eXF6NGjRbtv+PDhjBs3jo0bNzJgwADq1auHsbExERERPHjwQCGxKy4u5uHDh8KTdOPGjZibm2NqakqrVq24du0azs7O2NraMnToUAAuX75Mz549sbKyolq1auKknZGRgY6ODoGBgaLqVKtWLZ49e0ZgYKD4PQ0NDaKiopg1axZt2rShcePGtGrVCjU1NRYvXkxZWRmTJk1CJpOhpaWFvb09q1evFs8gOTkZDQ0NfvnlFy5fvsyVK1fYtGkTnp6e1KpVS/zejxY5+X/Ly8tDX19f+JpaWlpiaGhIzZo1ycjIEK1PAwMD1NTUBA60pKSEffv2CTLE16K3/fr1Q11dnSlTphAREYGJiQmrV69m8eLFaGtrEx0dTZUqVTh06BClpaUsW7YMbW1tvL29cXBwYOLEiVSvXp2UlBSR1Bw+fBh/f3+qVq0qCAkXLlxg586dhISEULNmzQp2SIcOHaJBgwYcOXKEgIAAoUxfVFTErl278PX1xdXVleDgYFxdXYWllZ6enkLLbvfu3cyZM4dff/0VGxsbwsLCBDnEycmJ7Oxs4d0qeW9aWlqirKxMUlISNjY2otqdm5tLamqqGLNQztqOjIxk6dKl1K9fn5SUFKKioqhVqxa2trYikZMqW9+LzZs3Y2hoKNiVjx49Eo4sXl5eVK9eXbCOLSwsmDFjhqiu7d27F0NDQ6ZNmybWtpYtW5KdnU1RUZFYz7y9vYWnqZKSEsuXL+fDhw/06dMHR0dHHBwcFGAi165dw9HRkdevX4txUlpayqhRo4iMjKRdu3bk5uaiqanJyZMnWb9+vdBwnDBhAunp6SQmJpKbmyvua/ny5YJk8/XY+/3337GwsKggxPt1PHr0iAEDBvDq1SvKysoYN26cEJMdOXIkjx49onbt2lhYWKCurk61atWErJSqqirp6enY2dlRt25dGjZsKAgkycnJCkb3kkVbXl4e06ZNw9/fn5KSEoUkd/z48RgZGdG5c2eR4EjxvcPZXyUy+/btw9jYWAiOb9myhfj4eAICArhw4YKAnURFRYkK/5kzZ9DW1qZXr148evSIbdu2kZiYKN5f165d0dHRYe3atbx48aJC5fp799erVy90dHQIDw9HU1OT6OhoBg8ejKurK+vXr6dBgwbIZDIyMjJITExESUmJpUuXKqzXgHDg+VqL8++IJUuWYG1tLTB+EydORENDQ2H9lUI+sf7vYLl+L/5J6v4L4vr165ibm5OdnS0m8rNnz7hy5QolJSVkZGTQrFkzgSkJCwtDWVmZ9PR0bGxsWLRoEUOHDmXOnDmoqKhga2vLu3fvePXqFSNGjBD6ZlKSNHv2bKKiojAyMkImkylYkbRu3VpUmV69egVAbGwsampqmJiYKMg1REVFCczP+/fv8fHxwdfXl4SEBFRUVDAxMRGD9XunwRMnTqCjoyPK7kePHqVevXpoaGgoAPqlRXfnzp2Ym5vj7OzMgAEDMDc3Z/ny5Vy6dImDBw/SsmVLIbzctm1bhZbFihUriIuLo3fv3rx+/ZqbN29y9+5dunfvTkhICMOGDePatWskJSVhYGDA7NmzxcS7c+cObm5uREZGisqENCGlxO327dsMGTIENTU1WrVqxeHDh8nIyCA4OJhmzZoRExOjUFm5dOkS3bt3F+0iJycnJk2axPr164Vnqbq6urAJi4mJQV1dHXV1deHL2qVLF/Lz8/Hx8UFTU1Mkjhs2bKBNmzZkZWVhb2+PnZ0drVu3FptA586dcXBwEMDxkJAQwYr70fv6OiZPnoyurq7wpJw1a5aoRNrY2FCjRg1OnjzJwoULqVWrFh4eHtja2tKlSxexqO7bt0/Y3X0dY8eORSaTYWpqSkhICJaWlmhqajJhwgSuX7+Os7MzQ4YMYezYseTl5dG+fXvevXtHQkICWlpaLF68mJCQEHr27AmUL55Hjx7FwcEBFxcX4VMM5SDw8PBw6tevL5IrKT59+sStW7dwdHRk//79lJaWMmzYMKKiotDW1kZDQwM7OzsqV66MjY0NqqqqWFtbK7A0obyiqa2tTV5eniCySOr1Bw8eVHjuRUVFTJo0CXt7e/Lz83n37h1XrlwhPz8fAwODClI0+/fvJzU1FQsLC5o2bSqwgFu2bCEqKkrMZ/n4Wo1f0lSrXbs2eXl5YkP88uULiYmJGBsb065dO3777TeUlZUxNjZmx44d4hpPnjzBxcWFlStX8ujRI/Ly8jAwMBA40rKyMj58+MDEiROxs7PD0NAQFRUVqlSpAiBsCNXU1PD29hbP7+rVq3h5eSlYmEns+RYtWqClpYWysjJVq1YVxK9Vq1ahrq6OTCajdu3aHD58WGE9AETlduDAgRUSu6/1/b4VEhs4Pz9fVL4DAwPR09NDT0+P4cOHc/z4cUGmMTQ0xNbWlvDwcEHiWL58OU5OTiQlJbFp0yaqV69Ov379GDduHM+fPxdjQsJnSutjbGysOHxDeTvUwsKCzZs3M3jwYPT09JgwYYK415+Z019bNUrWexYWFuJnW7duFVASV1dXsrOz8ff358uXLzx48ABDQ0MaN26scN3Zs2eLyvWXL18qVK5NTEx+CM+5evUqQUFBHDlyBEBo2IWGhuLs7Ey/fv2oW7cuhoaGGBsbc/r0aaH4sHv37grXmz59+t+SSH1d7ezdu7eQjVm7di16enpCB+/Dhw/f9Af+uyqE/9n4J6n7m0M6bcpkMsLCwsjJyVHQlCosLCQyMlJUB4qLi2nbti0tWrSgUaNG5OXlMWDAAEFmkDSepN//8uULVapUQUdHh/bt2/PmzRvy8vKYPn06LVq0wMXFRcHkGCAgIAAtLS06derE7du3qV69Om3atGHMmDGMHDmSkSNHkpaWhrKyMvXq1UNFRYUVK1bw5s0bevToQZs2bejcubOovv1o0J4+fRpHR0devnwpfu/ChQtkZGQQEhKigDeQFt1z584RFhaGTCb7pgH1gwcPWLdunQJQfM6cOcJX8msauVSRNDc3FxZj3t7eQptOSsTu3r2Lp6enUMiX4sWLF3h4eGBtbY2xsTGGhoZcvHiRkSNHYmtri7a2tti85ZMFaXGTpEt8fX0ZPny40KpzcnJCVVUVfX19wfaLiYmhXr16KCkpCWDx3bt3sba2Rl9fX6ivnzt3Djc3N3bv3s379+85ePCgYIJmZWXx559/smfPHo4dO8aOHTsqKMb/VZSUlFBWVkb9+vVJSkoSwOiNGzeKDVZyVMjMzKRr166YmJiwYsUKli5dSlhYGJ6enjx+/JiysjL279+PtbU1UVFRFd7NzJkzBd6qQ4cOmJqaMnfuXN6+fUvLli2pVq0aWVlZyGQyoqOj+fDhA2/fvqVTp06UlJTw22+/YWBgIFppp06dEvcouUVI8fvvvxMeHk5WVhYFBQUKY/fVq1ekp6fj7u6OlZUV6enpjBgxgufPnwvAu52dHWpqatSvX1+QdORZ0KampqKi8eLFC6Ht6O7urtAO//jxI/n5+cTFxTF8+HAMDQ2xsLDAx8cHLy8vTp06xYEDBxgzZgzt27fnwIEDwmf3a9X9vLw8IiMjFap68nH8+HEOHDig8LMxY8ZgbGzMo0ePWLduHefPnyc9PZ2CggLevn1LbGysYPpaW1vTtWtXmjVrRmhoKD4+PhQUFJCYmCjuFcorntu3bxfVnZkzZ+Lk5CRsuTIzMyktLaWwsJAOHTrg6OhIvXr1OH36NEeOHMHFxaVCorVp0yY0NDSoW7cuEyZMIDs7GyUlJc6ePcujR4+E/7SWlpaw5pM28/v375OYmEjz5s1RVlZm8ODBP90KKysr4+LFi2hoaBAfHy/A9h8/fiQ2NpbExERhaJ+VlaXAkHZ3dxd2bdK7nj9/Pr6+vrRv3x4LCwvhoxsfH8/WrVuZO3culpaWQs5ER0cHU1NThbXs3r17eHp6UlBQwJMnTxg0aBAGBgYKGN0fxdKlS2nevDmXL1/mw4cPAgrRrFkz1NTUmDx5sig67Nq1i7i4ODQ0NBRIEXv37hWC3/JJ2p49ezA2Nv5m5XrmzJkVxqx8DB8+nLp161K3bl0FbOOdO3dITU0VtpWamposXLiQ9PR0LC0tOXHiBE2bNsXAwOCbiR38fRUy6cDUp08fRowYwc6dOxW8XEtLS1m8eDETJkz4qcPCf2f8k9T9F8Sff/6JgYEB2dnZpKSk0Lx5czF47969i7u7O126dBEek7a2tiQkJKCrqys2+xo1aqCsrEyHDh3o2rUr0dHRAuBeUFCAsrIy2tragkl15swZHjx4QKdOnQgODmbAgAGUlpaybds2ZDIZWVlZBAcH06lTJ/T19dm2bRtFRUVig9qxYwdpaWkEBgbi6ekpFuTvOSp8Lw4cOICbm1uFgX769GkyMzOpXLmygmiodL3Tp08TFBREaGioAlD6W7F3717Mzc0reOfCfwh3rl69WrgY1KpVi2rVqqGpqYmqqirTpk0TulY3btygQYMGCtT3N2/eEBkZiZKSkjAC79atGzdv3iQ2NhYVFRVSU1Px9/fn/PnzvHv3TmzgN2/eFIxAZWVltLS0MDExITMzkzdv3lCnTh1kMhnq6upMnDiRN2/ecOrUKdEKb9SoEXp6ejg6OuLh4UFxcTGbN2+mpKSE0aNHU7lyZYFPOnPmDJqamkLEOSIiQpi7S/GjBPzixYsK8jFSUte8eXPu3bvHs2fPCA0NZeTIkURERAgnD319fczNzdm3bx9lZWXs2bMHLS0tBcAylFdhJS1BKZ48ecK9e/fo1auXkMFo2rQpbm5uzJo1i5SUFJo2bUppaSndunVDVVWVFStWiGv06tWLwYMHExAQIPBqDx48oGHDhshkMn777TdAUVJg+/btuLu7C4eFtWvXMnHiRKZNm8bKlSuZNGkSkyZN4smTJ+JzatWqRfv27YUp+4kTJ4Q0jBS3b98mNDSU9PR0Dh48yPXr17G0tBQHupo1a5KamkqdOnXw9PQUzhf379/n4cOHrFy5kqNHj/L48WOBka1RowY+Pj7Y2NjQokULBezosWPH6Nq1K4aGhgokIfl4+vSpGGPdunVTwBRWq1aN9PR0jI2NqVSpEhERETx69IgXL15QuXJlJk6cyKlTp3B0dBQsdHm7weXLl4uxt3btWkxMTOjRowf37t0T8ivTpk3Dzc0Na2trjIyMFJLLw4cPi0rQuHHjcHd3Z8mSJSxZsoTNmzezdu1a/Pz8yM3NBcoxoQ4ODrRu3ZqysjI2btxIQEAA48aNE2r9kgyRNDb8/f25f/++0L6Ur9x+Hd+aG0uXLsXe3p6qVasydOhQysrKqF69Ot26dRMyLUpKStSpU4cRI0YISRPpUChd89OnT4wcORI7Oztxj2vWrEEmk+Hv70+NGjUEAebSpUv079+fwMBAUlJSWL16Nfv27SMpKYmwsDAx5p48ecKQIUMEM/V78eTJE96+fYuLi4vAhrZs2VIwRY8fPy4sFxcsWMD169e5dOmSwIZGRESIA3xpaSl79uyhZs2ahISEcO/ePT5+/IiZmZkgmf2rIR3q7OzshEaqvKuLVMhwdnZm4MCBHD16lNjYWJydnfn48SNNmzbFxMREkH/+jti0aZNQcsjPzxdjUDq8S7g9Kd6+fUtCQgK9e/f+2+7h74p/krp/M+QXBvlTYc+ePalfvz5Dhw4lLCyMli1biord0qVLMTIywtXVVUz6PXv2kJqaip6eHgUFBWRkZBAXFyewctHR0RQXF4tEZ+vWrQQEBNCgQQPOnj0r7qNXr17Y2tqKdoeWlpYYjL169RJYLolFJH//u3btombNmlhZWeHi4sKXL18UEqvvJQjyJI/ly5djYWFRQT+usLCQU6dO0bBhQ6pUqVIhAYDyapSPjw/BwcEisZPfRKXPHzp0qACQA/z6668sXbqUoUOHUrt2bUaPHs2sWbMIDg5myJAhNGvWjMaNGwtGm5aWFrNnz+bly5d8/PiRnTt30qVLFzp16kT//v3p0aMH3bp1w9LSUmiiKSkp4ePjg7a2ttC4srCw4MKFCyQnJxMQEEBUVBT79+/n+vXrtG3bFhUVFdTV1aldu7Z4/qampoKo4eDgQIcOHXj27BlRUVGkpKQgk8mwsrJi586dfPnyhRs3btCoUSP279/P6dOniY2N5fbt2zx+/BgzMzOhT7Vjxw46dOhQoU3yvVi2bBkhISF06dKFGzduMHz4cAYNGkS/fv3Q1NSkWbNmjB07FhsbGzZs2EC/fv3Q0tKiSpUqTJo0CVdXVwoLC1m3bh26urrCa7GwsJAlS5bw4MEDhTbSnj176NatGzExMVhZWQlmtYQ9DAwMFEK08vCB5s2bo62tzezZs4X4a0REBFWrVlUYjw8fPiQjIwMDAwNRUZBO7WVlZezevZsZM2YIwL2uri6ampp4eXkp2GC9evWKfv36CWu33bt3U7NmTSpVqqSAd5Li2rVrJCcnk56eTs2aNZHJZAwcOJC7d+/Srl07MRd1dXUxMzMT81s+bt68iaurqwLLdfbs2VSrVo1ffvmFp0+fcv36dZo1a0ZsbOwPBU6ld7BhwwaqVq2Kj48PiYmJHD58mPz8fFJTU4WHq6ampgC4N23aVHiW1qxZEx8fHywtLdHQ0BAJtERQSEpKQl1dnfnz5yvg+SRixqxZs/D09MTT05PPnz9z/vx5IdFz5MgRXF1dRRW8UqVKuLm5icOkiooKK1eu5NmzZ9jY2NC6dWtx/bS0NKytrYHy8S69l6tXrzJmzBh0dXU5fPiwIFksWbLku0K30rry/PlzDh06xKBBg5g9ezYFBQUsW7YMa2tr2rRpw8WLF6lZsyZz5swRVUM1NTWR/JiamiKTyRg9erRCR+bNmzf07NmT2NhYduzYwZo1azA0NKRdu3aoq6ujrKxMly5dFCza7OzsyMjIEFXxuLi4Crpwjx49Yt68ed+tSPXr14/q1atz7do18vPz6dSpk3D+0NbWpn79+kybNo0+ffqgo6MjoC2BgYFERESwadMmUlNT8fT0VGCOS/PAz88PIyMjunfvXuFZ/ug5fx1Lly5FRUWFnj17Koyho0eP4uzszB9//MH48ePx8PAgPz+f48ePCyJFaWkpaWlpJCYmfvdz/5V49+6dkKdq2bIl2traCoemrl27oqGhwa5du7h+/TpXr14lMTGRkJCQ/6PYue/FP0ndvxHyC8PXScyKFStITU3lwYMHTJ8+nZCQEJo3by5afxcuXODgwYNCzqSsrIxTp06RmpqKh4cHe/fupaSkREzK0NBQgTkpLS0V15GfNH369MHU1JQJEyZQrVo14fawadMmoHyTkzBfLi4uCu1U6f92796Ns7Mzenp6nD179i8H7fXr1/Hw8KBhw4ZAeXXGxcVFoaz+8OFDmjdvzoYNGzh58iTVq1cXNPqv49y5cwQGBuLk5PTdsnavXr2Ii4vj2bNnnDlzBhcXF6pWrYqrqyu1a9dGJpMRHx+Pjo6OeC/S/YwePVqIgtasWRNPT0+0tLRISkoS+EJNTU3U1NRQUVHB3d0dTU1N0fIxNTXF1dUVR0dHnJ2dUVNTw83NjeDgYMzMzPD29ub+/fvcu3ePzMxMlJWV8fPzY8CAAVhYWAiV/EGDBqGqqsqyZct48+aNkEbw8vLCwMBAtKm7detGaGioAMVnZWXh5eWFmZkZzZo1+64m0o8qdHPnzkVXV5fJkydz7do1Ll++TLNmzZDJZEyePBkXFxe0tLQEs1pSr9fU1MTU1JRz587h5+fHmDFjMDQ0VGj3HzlyhHr16olxnZOTI/xhlZSU8Pb2Zu7cuezfv59mzZoJgL6Ojg6GhoYYGRlRrVo1Bc0tye1BU1OTnJwcYmNjxUFoy5Yt4h1L7VQjIyPOnDmjIPK9Z88eAbTv0qULI0aMICQkRGiKtWvXjs2bN5OdnY2tra1CBWj37t3UqVMHFxeXbyZUV69epXr16mhqauLr6yveo7q6OiNGjGD//v2sXLmSXbt2YWxsrIB1hHI3iW/h9WbOnImNjY1IJm/cuPFd4PmZM2dYtWqVSKihvGJz6NAhKleuTNWqVYVUy4QJE/j9999RVlbGzs5O4JrWr1/Pxo0bBX5NOpRERERQXFzMyJEjxbzS0NBg9+7dfPjwgT///JPWrVvTu3dvDhw4QGlpKePGjaNq1arMmTMHBwcHcnNzxeZ9+vRp3N3dSU9P58CBA5w/f57Pnz9TUlJCZmYmw4cPx87OjjZt2ohk5unTp4SGhqKvr8/169fFWlWnTh20tLRQVVXlxIkT9OvXjy5duvyU3+mlS5eIi4sjODgYCwsLQRbr378/s2fPxsbGhvbt22NgYCC8aiXtO2VlZfT09CgsLGTy5MmoqalRrVo1bt26Jdbo5cuX06FDB06fPo2bm5vAw0kSLLq6ukK6auLEidSsWRMoT/IfPHgg7vN7a/C3fj5p0iSqVq1KVlYWCxYsQE9Pj4ULF1KvXj2CgoIwMTFBJpPh7e2Nn58f3bp1o6CgQAH/uXbtWjIyMrh9+7bCc5QSOzMzM1Hh/9mE7vDhw2zcuJE//vhDtDZnz56NsrIy7du3Z/v27WzdupWYmBgCAgLE3w4dOlQkdlJVT7r23+kU8e7dO8F0lrDBUkHjyZMnAs9nbm5OSEgIMTEx/21erv9q/JPU/Ztx7do1rKys8Pb2ZuvWrQqK2WFhYeJEM2HCBEJDQ2nVqhWFhYUMHDiQiIgIzM3NSUxMZOHChezbt4/27dsLwLunpyc5OTlYWFigoqLCsmXLKCsrY+jQoaSmpips6Nu2bcPT01NsDOvXr0dZWRkdHR0cHBz4/fffBUg6NzcXVVVVsrOzBeVcmrxPnz4VOCIvLy9+++03hRPo1/H+/XvGjRtHcHAwrVu3ZtmyZaSnp3Px4kXev3/Py5cv2bVrF9nZ2TRo0IDZs2dz48aNH07IU6dOERkZ+V1cxpIlS3B2diY+Ph4XFxccHR2ZMGECM2bM4NChQ0ybNg0dHR38/PyoXr26EHIuKytj7969+Pv7C4KCra0tAQEBnDt3jtTUVHJycgQ5RfIi/e2334iNjcXKyort27dz5swZ9u7dK7TmAgICyMvLw8zMDCUlJSZPnkxZWRn3798XeDlJ90wS0FVTUyM2NpZjx47x/v17YbUTFRUlWvHx8fEYGBgoVGJv3ryJg4MDGRkZFSj8UvxoQzt8+DC2trasWLECKNfH8vHxoXnz5iIh6d+/P0lJSejo6IjvKOEELS0t2blzJ9nZ2aIqJUVhYSGpqamkpqZSWloq2Gupqak4OjoyfPhwZDIZCQkJnDp1iufPnzNt2jQhhbF161ZevnxJ+/btkclkgnEGCBLP+vXrWb16NaampuJ+q1SpwuzZs4H/SOwksVko3/xyc3OpXr06Tk5OPHz4kLKyMsGQjY6OJiAggHnz5jF27FjBppZ/jtu2bSMrK+u7Y/LatWskJiZSo0YNevfuzYwZM7h+/bpCW//kyZOYmJgogN2hnFxka2srRFblq+OOjo4KkjTfijVr1mBvby8kbzQ0NNi+fbvCHBs8eDDp6eloaGgwbdo0CgoK6NatGyoqKri4uIgkXPreffv2FYccDQ0NsrKyMDU1ZdGiRcI719DQkHr16lG9enXCw8MJDQ0lNTWVoqIiPnz4wJo1a9DU1GTu3LmibSs90xMnTuDm5kZKSgpeXl5C7qhHjx7IZDJq1KihcDCUZCWkpFSK33//naysLM6fP8+nT59o3bq1gmzU1yE9kzNnzmBkZERKSgqdO3fm+vXrTJ06lcjISKEjOHDgQAwMDFBRUSEqKop58+YJzKyKigpVq1blwoULzJ07F0NDQ9TV1RWkPaTPmjdvHq6urowfPx5ArAlaWlq0b99eiL43adLkp/Xcvg75v5s7dy4xMTE0bNiQRo0aCbLRgwcPMDIywszMDF1dXTGvJXkO+UTp6wqsFH9Vuf5W9OrVCw8PD1xcXIiPjycoKEjMwYULF4o1xtzcHHV19Qqs5lGjRuHp6Unfvn0rzL9/J7H7888/2bVrl3D1CAwMJDg4GFtb2wr7IpRjSHfu3MmRI0f+MuH+Pxn/JHX/RpSUlDBs2DBhjVS/fn2ioqLo2bMnjx8/ZvPmzTRq1Ijnz5/z8eNHJkyYgLu7O+Hh4Zibm7N69WoeP35MQEAAdnZ26Ojo0KpVKyIjI0WVZM6cObx7945+/fohk8mEWK98JQHKT/uSofCWLVswNjZm3Lhx1KlTB1VVVUxNTUlISKBbt24cOHCAKVOmoKamRlxcHJMmTeL8+fOsWrUKf39/YmNjWbBgAatWrRKaaN8KacC/f/+eyZMnEx4eLhi4NjY26OjoYGBggI6ODjo6OqioqAjSAfx4Qn4PTyfFnDlzBM39wIED3Lx5U2wyffv2JTIykpUrVxIWFkZ4eDhHjx5l0aJFuLm5kZqaKjTQTExM8Pb2Jjw8nEqVKvHw4UN69uyJsrIyVlZWWFhYYGFhwcmTJ0lISMDOzo5z584JzF3t2rW5efMmt2/fFm1aCwsLatSoQePGjQWo2tLSElNTU1F1kmRiVFRUyM3NpUuXLhw+fJjk5GScnJwwNDREQ0Ojgt7e27dvSU5OFrpj8u/hZ2LOnDnExMRQWFjI+vXr0dPTY+LEicTFxWFiYoKOjo6wklu5ciXTp0+nffv2uLq6CgmWTp068eHDB1JTUzEyMqJ///7k5+cTHx+Pj48PRUVFzJw5E21tbdq2bcvGjRsFniwjIwNHR0ciIyM5fvy4wJhqaWmxf/9+tm3bhp6enkjS5Ku1EitS+vdnz55x69Yt0dKfN28eUK7OL82Tffv2UVRURKtWrQgMDMTGxkZIe+zZs4eQkBCMjIxQU1NjwYIFFeQS5P9buhd57Tn5uHLlCsnJySQlJVVg25aWltK3b1/c3Ny4f/8+hw8fFok1QHx8PN7e3gpuHx8/fqRy5crfhCpIcezYMYyNjZk1a5a4B5lMJljTJSUl9OzZEwcHB2xsbIRry7x583j+/Dm9evVCRUUFNzc3gX/btm0bDg4OqKmpUbduXcLDw1FXVycnJ4cdO3bQrl07IeGRkJBA9+7dKS4uFuvH8+fPKS4upkWLFnTu3FnhOco/3+PHjwsdR/mEJi4uDm1tbTw8PIiOjiY7O1u01SXR3Hnz5onDpqQi0K9fPzw9PX8I0odyxrKuri6dOnUSjhOShVdycjKxsbEoKSkJrU8tLS1ycnI4dOgQzs7ONGvWTEiaBAUFoaWlJRK1Fy9eVJiP/fr1E4fM2bNnk56eLqAW1tbW9OjR41+CTnwv5NdTaZ6HhoYSEhLCq1evCAoKEoSHNWvWCAcPeXmOn3EG+qvKtXxMmTIFMzMz4RIyaNCgCgoNmZmZKCkp0bx5c65fvy70S6VDGZSL1xsZGQmiwr8bCxcuxNXVlczMTNFm/vTpE8+ePSM+Ph4bG5sK4+hrJ56/21P274p/krp/M+7cucOAAQOIioqiZcuWHD58mNDQUGrXro2/v79gCEpA4mHDhhEYGCiYW/v27RPWOdKAvXPnDlpaWnh4eBAUFCQwa1u3bmX8+PHfpFGXlpby8uVLCgsLqV69urB+efjwobCzcXd3F9WgMWPGiOqeZHMTHh6ugGH5mZAXv5w8eTKVKlXC3d2d33//nZCQEGrUqMHRo0fZv38/U6ZMEe2G/2xIE2nGjBloaGiwdu1a8W8HDx7Ezc1NMBklEH98fLzwZ7SzsxNYNQMDA8HC9Pf3R09PT2xI0oncxMQENTU11q1bx4gRIwgLC8PJyYlBgwZhaGhIdHQ0d+/exdjYGFVVVXx9fcVJXlVVFTU1NaysrNDW1sbU1BQlJSVBkX/9+rVgOEdHRwuV/BcvXnDu3Lnvbk4HDhxAXV1dtNV/Jvr06cPp06eZMmUKwcHBnD9/nvnz52NqaiokOypXrqxQnRs5cqSoBj579gxbW1ssLS3R0tLi2LFjlJaW0rVrV6HVlZKSIk64w4YNIzo6mitXrvDLL7+grKyMvr4+0dHRZGZmIpPJCA0N5cSJE/j4+KCiokL37t0V8HlFRUVMmTJFoepUtWpVlJSU2LRpkxh7klBxtWrVFLxQra2t0dLSYvv27UyePBl/f3/c3d3JyclhxowZogVvaGiIpqYmtra236xKy29oU6dOxd3d/btEhWvXrgmPYqlq3r9/f5ycnDAyMuL06dO8fPmSjIwMgoKCBGno6dOn+Pv74+HhwYYNG9i5cyd9+vTB2NhYVA6/dU8rV64kMzMTgFu3bmFra0u7du0U7tfY2JiDBw9y6dIlOnbsiJeXF0ZGRly5coW3b9/Su3dv8T4aN27M/PnzmT59Oq1btyY0NBRPT08hlePo6Cg6AEpKStjb2+Pg4MCrV68ELOLt27d8+fKFgIAAATiXv+fS0lLevn1LUVERJ06cYNGiRTg4OLBt2zYh+h0eHo6HhweampoYGhqKdt+1a9do0KABKioqNG3alPnz5zNx4kThPPAjb1EoPxR5eHjg4eEBlCdcmZmZGBoa4u/vL+SfVFVVsbS0pHPnztjY2KChoYGWlpYQBN+7d68CA9be3l6s02/fvuXcuXOCgf748WMsLCzQ1tZGXV0de3t7ioqKhEqCo6MjPj4+1KhRg1OnTrFjxw4OHTokDtp/Zev3vUPdrFmzqFKlCsbGxshkMqpWraqgSnD37l0SExPJz8//bitRvhL1M5Vr+XstKSmhZcuWjBkzBignI+jq6ooD24cPH7h//z41atSgffv2KCsr07RpU4XfkT/ULV68+G9pdS5cuBAtLS2WLFnyTf3TO3fuEBsbi729PVeuXKGoqIhGjRoJncD/05IlfxX/JHV/Q9y9e5d+/frh4eHBnDlzgHJsUbNmzVBRUREMmdLSUp48eYKXlxdr1qxh8+bN6Orq0qNHD7y9vSksLGTMmDHY2Njwyy+/sG/fPurXr4+lpaXAPEib2/bt2xk+fDgzZ87k7NmzolXx9OlTXFxcmD59OmVlZUIKo3nz5oLZ2aZNGyIjIxk5ciTPnz/nwYMHnDhxQoCZ4V/DCchX7CZNmkRQUBC//PIL+fn5hIeHC0sh+Wv/O6ecefPmoaKiwtatW8Vnf/z4kaNHj1K5cmXU1NSEdIIkVaCpqUmXLl3E98rPz8fOzo7U1FSxOGtpaWFnZ8eGDRt48eIFgwYNYsKECSI5q1OnDvPmzROOF+vXr8fBwUG0cqV2lqurKzKZDBcXFwGkjo+PF7Y8VatW5dChQ0LDyszMDBUVFZYvX/5Tz/3Tp08EBwcLuZO/irdv36KqqkpMTAzLli3D3d0df39/4UVrYmLCtm3bKCkpoUWLFgrtYklbMCsrC1dXV9LT09HR0SEnJ0e8wyNHjuDj40Pjxo1Zu3YtxcXFIunt1q2bIETUqlWLbt264eTkREJCAgEBAVy+fJk6deqgqamJtra2gsjtnTt3qFGjBosWLRJjc+HChRgaGoqTv7TpXLx4EZlMJgRunz9/Tnh4uLANu3TpEj4+PsJuycjIiFatWomqi0wmE7hQKb41Rl++fCkORt+rUly+fFnInyxYsABra2t0dHRIS0sTm+fBgwfJysoiJiZGeCK/fPmSGjVq4OzsjIODAwEBAZw6deqHc2X06NHExMRw69Yt7O3tad26tYJVU2BgIE2aNOHatWuChDN06FCSkpJITU0VcjEDBw7EzMwMV1dX4R1dVlZGVFSUMLKXGN0dO3YkNzeXYcOGsWPHDqKjo2ncuDF6enoKWMbs7GyysrIUcIBlZWUUFBTQrl07UfG8ffs21apVo0ePHgQGBjJx4kTxc2tra3EIkuLRo0eMGDECe3t79PT08Pb2Jisr65suM1/H2rVrmTlzJlpaWvTp04fZs2cTFBREZGQkW7duRVlZWbhoKCkpkZ+fz/nz5xXcI3755RcWLVokcMv9+/cXOMaZM2cK3TlNTU1++eUXITzdr18/wsLCiI6OZtmyZRQXFzNs2DDR4jYxMSEsLAxjY2NsbW3x9PSkUqVKP41bu3v3Lvfv3xdEEUk+yMPDAwMDA9EaLi4uFuvM1KlTcXNz4/Xr1+zZs0fYIvbu3Vsc6P6qci3FypUrad68ucLvNGjQgJkzZ7JlyxaFA1tJSQmzZ89m2rRpeHp68ueff9KtWzfR/YDybs2UKVMqEIv+ncTu0qVLeHh4CMF0+Xj06JGYn48fPyYhIUHY37m6uiow6v9vjn+Sur8p7t27R9++fXF1dRV2UEuXLlWowpSVlXHz5k1UVFREWX/mzJmcPHmSKlWqsG3bNjQ0NEhKShIDd8qUKXh6erJ7924FhquUSMhkMvT19UlMTOTu3btiY6hXrx49e/bExMQEbW1tdu7cKZLCV69e0bZtWyIiIhg9enSFSfK9k8iPFpevW7FBQUE0bdqUIUOGEBISonBi/5lJKX8P0mQqKyvj0KFDQupFisLCQpycnLC3tycpKYn9+/fj5ORE/fr1WbZsGaampnh5eVFaWsrx48dp3bo1mpqaeHp6Mn36dNEytra2FkBiV1dX4uPj8fLyQllZGSMjI2JiYoDyxVMC7Z45c0YQKHR0dGjYsCEtW7Zk8uTJQjBZX1+fnTt30rZtW7Gx2traEhwcTN26dfn48aNQRZevPP4o5EHDPwp5Mo+hoSE+Pj7Mnz+fqVOnMmDAAAIDA9HX1+fy5cusWLFCAMETEhIYPHiwwA75+Pjw6tUr7t27h4mJCdbW1kyePJlz585hZGREjx49uHHjhsJ769ixI+np6WJDTElJYePGjVhYWNClSxfRYl+6dClKSkoEBQUJ0sPRo0cJDg4mJiaGFStWkJycLCogKioqjBw5UuE73rhxA29vb06ePMmuXbtISUkhMTGR6dOnEx0dTXh4OKdPn8bPz08wYKX5o6KiosCmliRkvg5pHL5+/RpHR0fCw8O/m9hJ362srIxt27Yxbtw4IiMjqV+/vrjOkSNHaNCgAdHR0SKxg/IW6q1bt3jx4oV4f9evXyc/P5/GjRszd+5ckcwePXqUqlWrYmRkRLNmzRTeedeuXXF1dcXX1xeAgQMHIpPJ6Nmzp2AWSpWVt2/fMmHCBCFqraenJ1plISEhVK5cWZjRS8nxyJEjiY2NxcbGhpCQkArVy+nTp6Otrc2kSZNEAnf58mVBwlm7dq0YLzNmzEBNTQ07Ozs+fPjAw4cPsbW1VegcfP1eXr58yaNHj/j48eN38aXyceDAAezs7Lh3757wLO7Tpw9WVlZoamry9OlTWrRogaamJhoaGoIlLXl0a2pqYmdnR2RkJFpaWjg6OuLr60tubi6nTp0iKyuLgIAAWrduTcOGDQXGtmrVqmI8zJ49m7i4OMLDw0WVVlorevfuzePHj3n79i3v37/nw4cP4vl8a02WX48HDBhAeHg4xsbGNGzYkMWLF4t/GzlyJOrq6gQEBCgwWqHcyUQSTpZsEfv27Sv0E/+qci3FvHnzhPftrVu3xO907dpVkL/kxeefPn1KUlKSwIdnZWVhZGREixYtBGP5xo0bpKWlfdO94T8bBw8eJCAgQAFWtHLlSn755ReBY5aXhZo1axZTpkwR8+3/NlLEt+KfpO5vjPv379O3b188PDyoWbMmqqqqwicQyidhQUEBMpkMVVVVrKysWLp0KV++fMHe3l60B+UHjqRRJ512Dx06hJWVFUZGRuzcuZOCggIhaiuVudetW0dycjLu7u6Ympqira3NwIEDFRaBN2/e0LFjRzw9PSsAt/8q1qxZ883F5vXr13z8+JH3798zdepUrK2t6devH4MHDyYoKIiuXbuK3/3R5JC/5tKlSxkwYIA4Fd69e5fq1auTlJQktJoyMzOxsrJi8uTJogp44MAB7O3tUVZWJiwsDGtrazp37syZM2eIj4/H1NSUjRs38vjxY44ePYqdnR2qqqq0atUKe3t71NTUMDY2Ftp2fn5+yGQysSk/ePCAa9euUVhYiK+vr/B5ld6Npqam8AI1NDTk+vXrgkWlra3NihUrePr0qXgnHz9+ZNCgQd+VYPiZZyUf0iYq7+Uq4aRiYmKEI0Dv3r3R09PDw8MDbW1tnJyc0NDQQENDg7y8PFRUVLC0tBRtlp07d2JiYkK9evVwcnIiICCAbt26MX/+fNq2bUu3bt1YsGAB796948mTJ7x//55Zs2YJX051dXVUVFSE7Mj79+9JTU3Fy8sLVVVVqlSpQlhYmJgPXbt2RSaTCbwclCcAqqqqDBs2jDt37vDq1SvatGmDjo4O3bt3F4cjmUzG1q1b2bNnDxEREYSGhnLhwgWmT5+OtbU1KSkpmJqakp2dLRbtGzdu0LhxYwVLq28971evXgl/zx/hiqTrnjt3jgEDBmBkZETLli0rJHZS8iof8qB+KysrEhMTqVKlimBPQ3nVtkWLFlhaWjJt2jQ+fvzIunXraNmyJSYmJkycOFGQQAoLC/n1119Fq9vPz0/IREA5hOL169fcvXuXLl26oK6ujp2dHVpaWnTu3BlHR0chc6KqqkpgYCC+vr7cvHmT9evXC2N5SSgdEPIwtWvXJjs7m7S0NGH9FhERQVxcHGfOnOHRo0fUr18fOzs7xo8fj5WVFa1atfrme/lRovOjeP36tVhHz507JxI7yUVk9OjR2NnZYWZmRlxcHPr6+qioqODn50dWVpZgC1euXBktLS0SExPp0qULAQEBmJiY4Ovry44dO1iwYAH29vYsX74cMzMzbGxsiIyMJDc3Fzs7O9TV1bGwsBCkI0B4144dO1bokX49Dr4X/fv3F+tZQUEBaWlp2NvbK+DPGjZsiIqKimjNSwoK0dHRbN++XaFCKomfS3JJf3Uf0nzs16+fcOKR4u3bt/j7++Po6MjVq1d5/fo1R44coUqVKoSGhlJcXMz69euRyWTUqVNHJL+vX78mJSWF2NjYvzWR2rt3LzKZjD179vDlyxd++eUXwsLCSE1NZeLEidSuXZuwsLAKmHX4n5HQwT9J3d8eEkZASUmJBg0asG3bNuzt7RUWoMzMTMzNzVFTU8PU1JTq1asTEhIilOtPnjzJH3/8Qbdu3TAwMBCq3b/99hutW7fGzs5OLJzbtm0TINzmzZvz+fNnYd3z6tUrHj16RN26dQkLC1MQT4Tyjal79+4Kk/Cv4tGjR8hkMoWFG8qrC3p6eoSHh5OTk8OmTZuYNm0aJSUlfP78mZEjR1KpUiUBnIZvTxL5hePChQtUrlxZJJ4SI+v27dukpaWRkJBApUqV8PPzUzA0Ly4u5vjx46iqquLt7S2A+6ampjRq1AgXFxd2795NcXExHz584O7duwwcOBBjY2M0NDQYNGgQPj4+dO3alcjISJo0aULv3r0JDAxkypQp5Obmoq+vj4ODA4mJiaxduxY7OzuRuKioqGBtbc2WLVvQ0dFh4cKFQPkm9OTJE5o0aYKOjo5gd/7di0X37t2F0K4UPXv2pGbNmmhpaQndKgmb6ezsLNpN6urqhIeHizEszzYsKyvj2rVr3L9/nytXrtC3b1+8vLyoXbs21tbWNGvWjOTkZPT09DA0NMTBwYHRo0ezb98+cW2J5ZaSkkJWVpZgnkr4qpEjR5Kfn8+8efOEALe0EUnPqaSkhDlz5gitP3d3d1F1U1dXx8nJCXd3dzQ0NPDz8+Py5cts2rSJ9PR0wsLCuHnzppCQycrKUnh2PXv2VJCQ+TquXbsmpIB+NrFbuXIl/v7+ZGZm4urqipGREY0aNVJI7LKysvDz8xOOKtJ6cfbsWXR0dOjTp4+osqenp6OrqyswWx8+fKB27dr4+vqirq6OlpYWZmZmzJ07l3nz5hEcHCxEex8+fEi7du2ECK4kkyRJGklx8+ZNYmJixDNyc3NDQ0MDc3NzwZzU0dFh+/btrFu3TpAdGjZsiK+vLy1atBDfY+HChXTu3Jm4uDjatWvHhQsXeP78OVu3biU5ORlHR0fq168vWuNKSkpoa2tjb2/P5s2bKSws/Mv38q2Qqr5fm83funULfX19cnJy6NChA2pqagJHKrUqDQ0NycjIEP7HRkZGbNu2jR49epCfn8/FixcF5OXWrVsKzgpr1qxh8uTJ3L9/n5CQEPLz83FxcUFbW5vdu3dz+PBh4uLisLOzE2LZgMDYybvu/FUUFBTg5+cn1hJJCDw+Ph5nZ2dBsrlx44aC7p30rouKioQtonyFVF678XuVayhvN6uoqLBx40aKi4uxtrZm37594tpQXmV2cnLCw8MDPT09BRu+adOm8fnzZ6ZNm4aysjI1atSgevXqVKlSBX9//79dNuTLly+0atVKkPmcnJxYvnw5Dx8+BMpZ2Wpqagqi3f/T4p+k7m8OqSpRs2ZNQkND2bJlC/r6+ty7d09Um7Zu3UpmZiYDBw4U7MratWtTUFAghDklluyGDRs4cuQIJ06cEIuxtrY2e/fuZceOHQKnMH36dAWcyMOHD4XkyZ07d6hVqxZVqlSpkNj9q6fd0tJS2rdvT3Z2Np8/fxZJ2Jw5c4Q+l5ubG6GhoRgYGNC0aVNmzJjBhQsXyM/P/2kV7q5du4qKnKOjI1ZWVowZM0Z8p1u3blGrVi2MjY2/6YdYUFCgkEC+evWKmTNnCjbuzZs3OXToEJ07d8bLywtDQ0N8fX0JDg4mMTGRUaNG8fr1azw9PWnVqhWjRo3C3d0dNzc36tWrx8SJE5k7dy5eXl506dKFJ0+eCA08qZIhsQwBBXmG58+f06RJEwwNDcUC+HfGoEGDCA4OpmvXrty+fZuxY8diZGTE4cOHWbBgAd7e3mhqauLj4yOkXLS1tdHX12fmzJnMnTuX6tWrC12upUuXivaWPHvxzp072NvbC79QyddUSmwlv9tVq1bRpk0bVFVVhQZdbGwsOTk5jBgxQlRjioqKRDuwpKSE+vXrCwFuqVUln3xcuXKFTZs2sXbtWkaOHImnpydxcXE0a9aMxYsX4+/vL7CS9vb2eHl5YWpqSqVKlThz5gy2trbEx8cze/ZsNm/eTIcOHYSEzLfi1q1buLm5CXcR+OvE7urVq5ibmzN16lTRJhwxYgRBQUEKid3Bgwdp3ry5AnD71atXmJmZER8fr3DN+vXro6enx7Vr10SSU1RURK9evdDX1xcOGXp6elSpUgVdXV2MjY0xMzNDVVWVgIAAzM3N0dTUZMaMGWLOPHr0SOHzly5dioGBAZqamowcOZJz585x7949CgoKqFq1Kh06dGD9+vU4OjqKqtDly5cxMzNTEN3evHkzSUlJ+Pn5kZSUJJiPkuh3UlISTZs2FQcLfX19KlWqRGhoKIaGhlSrVu2H7+VbsWjRItLT0wkODsbLy0t4y0K5nVvfvn2Fc4E0TlRVVTEyMhJyI5aWllSuXBllZWUiIyNFG1Ce8CG/fk6fPp0hQ4YQHR1Nnz59SEtLIyYmhrVr15KamoqlpSVRUVF8+vSJx48f07x5c6KiohQSu8WLF/9QJuPr9frJkyf069ePL1++sH37dszMzJgzZw43b94UAtLS9aW//VpQ/sWLF8THx7N8+XLs7e1p06bNT1WuJTkiKWl+9eoVpqamguQg/5mfPn0iKysLPT09Bg8eTHFxMUlJSVhZWQnP4+3bt9OvXz86duzI1KlTxT383bIh79+/Z+/evaxevboCTu7SpUuEhYVVYK//T4p/krqfCGlgnj59miVLlnDixIlvmmnPnz8fmUzGxo0buX//Ps+ePWPr1q1oaGgoaF89ffoUT09PpkyZwtOnT6lbty6xsbFs3bqVz58/c+nSJS5dusTUqVPx8vJCX19f4Ev69++PkpISZmZm6OvrM3fuXMrKyjhw4IDAhhgZGeHr60uPHj1Etebu3bvUqlWL+Pj4n6aFf6/cLvmBfl2iHjduHM7OzowaNYo///yTDRs20LJlS6ysrAgNDcXOzg5nZ2dkMhnDhg377ueuWLFCMNmkRLhJkyYEBgYyduxYUbG7e/cuNWvWJD4+Xmgtyd/348ePuXbtGidPnuT69eu8ffuWGTNmoKysjIGBAdra2rRr147Vq1dz584drK2tGTFihIIsxc6dO1FVVUVdXR0NDQ2RoEL54li9enWys7M5fvw4ampq5ObmsnfvXmJiYlBRUSE2Nlbclzzu5/nz59SqVQsbG5sf6gD+KyG/4I8bN46goCCB72nUqBELFy7k1atX7N27F0dHRzQ0NAgNDWXFihVMmjRJnO69vb1xd3fH2NiYKlWqYGZmxrZt22jSpAmrVq0SC2FRUREREREYGBhgY2ODuro6mpqa9OzZk/79+6OsrCwEXKFcf1BHR4d69epVYJ09ePCAkJAQ0VaU/049evRAWVlZVDDkk5CysjKh0yaJJksAdyj3PJU2aUkPT0lJibt37woJEjc3N7y9valevfpfJg4DBw7E19eXPn36VEjsvvbHhHJ2u6WlpQKD9e3btwwdOhR9fX1at24tNln5xB/KW1C9evVCQ0NDfPcRI0aI1mfdunWxsbGhVatWTJs2jaioKMaNG8elS5ewtrZm5syZfPjwgffv3zNo0CCCgoJITU1l165dlJSUkJubi56eHiNGjCApKQlLS0uMjY0Fkevz58/C0UNTU5MpU6ZQUlJC7969adKkCa9fv2bRokUC93b37l2cnJxo3rw5c+bMQVNTk8TERNTV1YW0T1JSEkpKSnTo0EGIfkvSPpJFnfx7kfTfhgwZoqCd9lcxduxY3Nzc0NbWZtOmTUyYMIHBgweLisyVK1ewt7dHRUUFc3NzgoKCxNho0qQJYWFhLFq0iAsXLqCnp4efnx9paWkKrVH59bFfv37CPk9bWxttbW38/Px49OgRERERaGpqEhcXh7W1tRCffvToEc2bNycmJkaoFUjxrUTm6y6G1Er+9OkTZWVl1KtXjz59+oiqllT9bNq0qYLA/NchL37+s5Xrw4cPY2NjIzDAJSUlFBcXExISwrhx48T9ymOtExISRNdCKnZIxInvJW7/nS3P9+/fU7NmTRISEv6vlSv5mfgnqfvJWLt2Lfr6+ri4uGBsbEynTp0qsK0uXbrEli1bgPLN6N69e4I1FhUVxcqVKwVmatOmTfj6+vLs2TMuXbpE3bp1iYuLY8GCBZSWlgrJjvz8fMaPH0+dOnWwtLRkwoQJ4lRrbm7On3/+yYULF/D39xd+ee/evePXX3/F3NycRo0aiXbRvXv3iIuLIzU1VcFs/K/i4MGDAoMlRd26dcnMzOTDhw8KE2/gwIE4ODgwePBgkZB9/vyZLVu20L9/fypVqoS9vf0PsWMTJkzAz8+P9+/fi0Xh8+fP1K5dGzMzM8aOHatQsUtLSyMuLk6B0bRkyRLCw8OFAbiOjg6dOnXizp07TJw4EV1dXerVq6eQaEVFRbFo0SIFWYrJkyeTlZVFWloaN27cICYmRpzYS0tLycjIoF+/fuzbt49OnTqJ+z1//jwxMTGC7SqF/OL14sULscn8XSG/GEkivg4ODkJM+e7du8yZMwdvb2+BW/P09BRJx927dzl37hwjRozg6tWrFBcXk56ejpWVFb6+vpiamrJ582aRgLx584aFCxcyb9483NzciImJ4dChQxw6dEjIXmRmZooxcurUKbS1tcnIyBCJ3fPnz6lSpQqurq4cOXKElStXMm3aNO7duycSyB49eggBbiiXTElLS6OgoABDQ0MBB/j1118FS3Py5MmMGzeOAQMGCKJGkyZNUFVVFUBySULm+fPnFdh88tpq8jFixAg8PDzo06ePwBq+evUKPT09qlWrplAJuXLlCm5ubhWkfN6+fSvwizk5OQqfJx8fPnwgPz8fZWVl6tati5WVFZs3b2bLli38+uuvTJ06lYyMDAHnmDNnDtu3b8fR0VEwMj9+/Mjx48cZMGAAwcHB3L59m9LSUrp3746dnR2enp6isixJ80j4xOLiYnJycsQ6ZmhoiLKysoLp+7FjxygpKVHQT3z69Cmurq5ifD148IBWrVqhr69Phw4dhC4ZlCevksuCp6cnHz9+VHgvOTk52NnZiST1r0KaA1KbTU9PTzjEGBgY8Ntvv/H69WsuXLhAQEAAampqpKam4uPjI8TBZTIZ4eHh4vNr1aol2t1fv6vHjx/TpEkTTp06RcuWLalevTomJib4+Pjw9u1bLl26RHp6Ol5eXgwZMkRhvXzy5Am1a9embdu2P+yayP9b3759xUFWWr8KCwvx8vISshvv3r0jMzOT5cuXC9ykNJekCmnnzp2FFpwkh/OzletXr16Jw618pKeni9atVB2VfJxtbW15+PAhBQUFCkzYjx8/Mnbs2G/Ki/x3xOvXr1m3bh0pKSkKLd//qYndP0ndD0JeB6tmzZrMmjWLwsJCpk6dSlRUFI0bNxbJzrdOFHfu3CE4OBg1NTXs7e1p1aoVDg4OzJw5U/iISqbEFy9eJCEhgbS0NJYsWYJMJqNevXr4+vri4OBAcHAwenp61K1bl7KyMpKTk8XJUmqrWFpaUlRUxJMnT3BwcCA6Ohp/f38aNWokKnb3799XAEf/1fc/evSoYI/26tVLJLKrV68W5tmguPENGTIEGxsbhgwZIkySpXj58mUFSzUppEk0depUXF1dxUlU2iQvX76MgYEBkZGRTJ8+Xfxcai9LQOV58+ahqanJ1KlTOXbsGAUFBeTn5wtm8blz55g9ezYymYwePXrw+PFjatSoQVBQkHiPly9fpm7duvTu3RttbW1cXFwAGD9+PIWFhXz58oU+ffpgbW1dQTdQ+h7nz5+nSpUqAisixX8FNf5btjnPnj0jKChItJl69eoFlL8DSZTW0NAQa2trdu3apfD3JSUlCotb5cqVSU1NpUGDBhgZGbFp0yaF97hjxw709PTEczp58iS+vr5YWFiIhFF6tqdPn0ZHR4cGDRpw4sQJYmJi8PT0ZPny5RgYGBAeHo6Ojg4+Pj4KhwOJISwvwL1gwQIaNGggbKP09fWFkLLklrB582YuX74sNKckAojU0v1R7N+/n4kTJ1bQChs5ciQ2Njb07t1bzK03b95w/fp1du7cKTBOL1++pEqVKqSkpCgcAl+9ekW9evUYN25chTnydXz48IGBAweirKxMjx49mDdvHjY2NrRt25bVq1eTlZXF2bNn8fHxoX79+vzxxx84OjoKnbxTp04xaNAgzp8/j5qaGkuWLGHZsmVYWloyduxY8vLyUFNTE9qE165dw9TUFA0NDZH8Dhs2TGAUU1NTUVNTEwzk0tJS7ty5g7e3N9u3b6ekpISXL1+SmZmJtbU12dnZDBkyRPgYS1VTc3Nzzp8/T1lZGUVFRXh5eaGkpETPnj0rzJEGDRrg4eHxl4fR0tJSSkpKOHPmDMbGxoIAJVV6c3JyUFJSon///ly+fJnNmzcLTGZCQgI1a9bk0KFDpKWliarS2LFj0dfXZ+LEiYwYMYLXr1+Lz5szZw56enqEhIQIZun9+/cZOHAg+vr6eHt78+7dO65evUpycjIJCQmsWLGiAotXmnt/BYcZMGAApqam7NixQ4zJsrIyPn36RPv27QkNDRV6gZUqVWLdunXIZDIB89i0aVOFCqk0D362cv2te5R+lpWVRbVq1Th58qRYFxMTE3FxcRHtaF1dXQXi04MHD4TMy98R/0oyVlJSwqxZs4iPj6dRo0b/ZS3f/874J6n7izh27BgdO3akTp06CnpLCxcuJCoqikaNGn3zxALlA/3ChQvo6+vj4+PDunXrWLduHcbGxujp6YnToHTaunLlCjdu3KBt27ZCiuTw4cN8/vyZgQMHoqSkROXKlYHyk5l0Ek5LS6Nly5acOXOGx48f4+XlJVoiubm56OrqkpqaKip2P4pvTYjjx4+zcuVKnJyciI6OpkGDBly8eBErKyt69uz5zb8dMmQItra2DB069Lvg5u9NvidPnmBsbCxO/fKA8oYNG1K3bl0CAgJ49eqVuMaNGzfo2bMnp0+f/qYOUXFxMWvXrkVbW5ucnBzevHnDvHnzGDJkCGFhYVSuXLkCKPfLly88fPiQsWPHoqyszIABA4By3EtkZCR6enoKVlbyIe/JWbduXUxNTRXYv39nyLc5Jk2aRN++fcnOzubo0aMCOyT5qw4ePJgPHz7w+PFjIiIihExFbGwsJ06cqPBOJDaxdOL+9OkTYWFheHl5sWnTJpFYS7Z0HTt2ZN26dZiZmaGmpiZa9PIkh9LSUk6fPi3EnyU9NisrK2bNmiWqvxLzW8LgQDnuZvz48WIsjxkzhtTUVDZt2oSSkhJhYWHCd9PQ0BAlJSVRVZK39vlZCZlOnTphamrKlClTKkAu2rdvj7m5OV26dBGt2M+fP9OoUSNkMpnA5Vy6dAkrKytq1KjBggULOHv2rGhr/cixRT5evXrFr7/+KoD7K1eu5P79+1SqVAklJSXS09MZP348Li4utGzZEnt7exo3bszTp09JTk4mLS2Nly9fEhYWxubNmxk8eDBNmzYVLWmZTMbUqVP58uULb9++5ebNm2hoaGBpacnZs2cFXhfK54WkVScl3H/++Sd6enq4uroyfPhw8vLyCA0NJS0tDSUlJfr27QuUz22pUqempkanTp0EyaC4uFiQdn799dcKG+ujR49++Iyk9qJELunXr58QvtbS0iImJoZ79+4JfKexsTFubm5YWFhga2uLpqYmmzdvpqysTEhQQXkL0tbWlurVqxMZGSmSqtLSUp4+fUq1atVQUVFhxowZQoB42rRpeHl5YWxsjLm5OYWFhVy+fFkkdhJzXz7+Khm5ceMGgYGBFUD80n0eOXKEdu3aER4eTr169QRLv2XLlujr6/Pnn38ybtw4YaP2+vVr8vLyfrpy/aNWqHTvEhnL2dkZZWVlgoKC8PT0pKioiCVLluDq6kpCQoL4u/fv3/+tLFf5Z3jy5El27tzJtWvXvgmXkuLx48ecP39e/O3/FJbr9+KfpO4vYtiwYZiZmWFlZaWAi7l27RoLFy6katWqpKWl/bCdGBcXh6OjI4mJiURFReHq6soff/xBWlqaIC7In37u3buHp6cnTk5ODB8+XGDYZDIZu3fv5t27d5SVlTF58mRhPj9v3jzevXvHhAkTSExMFAKUc+bMwdfXl8zMTNGO+V7IT4jjx4+ze/fuCjiw9evXk5CQgJ+fH+bm5ri6uiqUzb9O7JycnOjTp0+FzetrgHHr1q0ZMmSIqC7s3LlTMKTc3d3p0aMHUVFRdO3aldevX6OkpCQSN/nP3LJlC56ent9l9E6dOhWZTMbOnTspKyvjzp07zJkzRyzikg/gtWvXxEm4ffv2ODo6oqmpSW5uLrGxsWLzkaq33wrpO759+1ZUBn+GJPKvhvQ58fHxqKiooKKigrKyMurq6tSrV48tW7YQEBAgjMitra2xs7PDy8tLVBSkZAgqbi7S/65bt67wpjUxMcHCwoJNmzYJgoOZmZkgSSgpKQm5Bvl3LVVSbt++zfjx46lRowZFRUVs2rQJZ2dnhTFaWFhI586d8ff35/Dhw+Tn53Pnzh0FoPrmzZuFi0dQUJACbigxMVG03fbu3atwL0VFRT8tIZObm4uTkxOTJk1SqNhNmTIFR0dHoqOjFYS77969S05ODurq6gJgfunSJRITE3Fzc8PW1hYHBwcFTOr38E7yIQkMy2Qyli9fzrt376hbty7Ozs6kpKQQHBxMXl4evr6+uLm5oaysjImJCY6Ojpw/f568vDyMjIyYMGECaWlpNGrUSLSr1dXVRRI1a9Ys+vTpQ61atVBVVcXQ0JD69esr3EtmZiaBgYF4enpSuXJl9PX1hXuBra0tFhYWrFmzBnV1dWxsbOjZsydPnz4VDHB3d3eUlZUxNTWlY8eO4mBcVFQkRLslX86fjbKyMrE2qKmpMWbMGCZNmsTq1aupXLky2traREZGcvjwYdE9Wb16NS1bthSyRUlJSfzxxx/imgsXLsTCwoIzZ85QWlrK9u3bK9hcTZo0CU1NTZSVlbGwsBCanPPmzcPf3x8XFxehK3n58mVSUlIICAgQXr8/G9euXcPCwkKMZfn48uWLWKs/fvxIWVkZly5dYtCgQdy8eZPGjRujpaVFSEiIwr3/TOVaXkPxR4mnhFe2tLRk3759ODo6oqqqKiqbr169on///ri7uxMUFERGRgYRERGC/Q7/XkIlP3969+6Ni4sLbm5u+Pr60qBBg58i2vxPbbnKxz9J3U/E5MmTcXZ2pl27dty5c4devXqRnJzM0aNHmTVrFsnJyT9MmHJyckhMTMTc3Fz4UcL3S7zFxcUEBASQkJCAt7c3qqqqaGhoCG/KkSNHigkYFBQk2haLFy9mwIAB+Pn5iapiz549GTZs2A9PKl9Hz549MTU1xcTERMgKSK02aeJMmzaNrl27oqysXMFAW35i5Ofn4+PjI5LMr/+9b9++mJqakpqaSnBwML6+vuzcuZO8vDwMDAwwNjZW8I2VTN89PT0VGFnSfQ0fPhxbW9tvfhaU0+uNjY2F84f835eUlLB+/Xq8vb1xc3PD09OTjh07snbtWtzd3fHx8REVgDdv3pCfn4+qqiozZsz4bmInxZs3b1iwYEEF8c9/N6Tv3ahRI/T19YXP7fTp04VEwy+//MLFixcFy69GjRqsXr2akpISfv31V/r06YO+vj6jRo1SELuVb79OnToVZWVl4bn6/PlzatasibGxsWC/3blzRwi3SrCCb7WaHz58KFr6UoVgx44d2NjYiIOT9HcfPnxATU0NFxcXZDIZbm5utGnThjFjxlBSUsL58+eFBdzq1at5/fo1Dx8+pHfv3piZmTFhwgRq166tICHzveRJ+nlhYaHAbErRsWNHnJycmDhxosBB9unTh2XLlilUNaRr3L9/nyZNmqCuri48VSUNuJMnT4oER/o8Kf7888/vbj7Pnj3D09OT+vXri+/bvXt38f0lBvOaNWvo2rUrdevWFUmWo6Mj5ubmuLu7k5WVRY0aNXB3d0dHR0fYtvn5+XHv3j2SkpLo0aMHXl5e6Orq4ufnR3p6uqg8jhgxAm1tbYYMGcKoUaNQU1PDzMyMAwcOcOHCBTZu3MiOHTvEOx4xYgQRERGCkd2wYUPhsKGhoYGpqSmdOnVS6HikpKSgrq7+zQTme7Fz50569eqFpaWlUAmQWsSnT58WhAV3d3fCwsJwd3fn2bNnfPnyha5du6KmpkalSpUULN6GDRtG165dKS0tZcWKFejr69OvXz9OnTrFlStXmD59OhoaGowZMwY3NzeMjY0xNTVl/PjxQDk+uHLlyuTk5IjE7ty5c3Tr1u2nxNzlx+q5c+cwMDAQ+Ez5uXXgwAGmTZsmiBxnzpxBJpOJ7//06VM6dOiATCYTpLKfqVxv3LgRmUymQOT41n0vWrQImUxG//79BWnIxsaGhIQENm7cyPLly3n06BGlpaXs37+fNm3a0KVLF3777be/veU5adIkLCwsxP7QqVMnDAwM/qWx9D85/knq5EKaQA8fPuTBgwcKvnajRo0iMDCQrl27MmnSJMLDw2ncuDGHDx8WOI+vNwtp8Ofn5wtdqKSkJJKSkij4/61PvjVBJBBzlSpVUFNTQ19fn7S0NKC8BZGSkiKYaKNHjyYkJIT27dtz6dIl5s+fT1hYGElJSdSvXx9tbW2uXLnyU98byjdXX19fdu3axY0bN8jIyMDW1pZly5YJkPL69euxs7NjypQp9OnTh5CQEIXW9NffS/7f5E9ily9fJjc3V4B1jx8/TnZ2NpaWllhbW3PgwAHev3/P+fPnmTVrFmlpaWRkZNCpUydcXFy+iQ3cvn07KioqCqfLr9+LnZ2dYGjJx549e9DV1WXChAl8/vyZWrVqCQzSmTNncHV1xcfHByUlJfH3UvviZxK7/yrPwNmzZ2NpaYmvry9NmzYlIyMDFRUVdHV1CQoKwtHRkdatW3PmzBkcHByES0RMTAz+/v48efKE4cOHo6+vz+jRo1m1ahXKysps2bJFLLSDBw9GQ0ODw4cPK7zD5ORk7Ozs2Lx5M8uWLUNPTw8LCwuSk5MVsEfyUVBQgLKyMqGhodSqVYvly5fz6dMnbG1tK5iaDx8+XLQUx40bR79+/dDV1RUtNTU1NapUqSKSAwMDA2JiYrC3txdM1J+RkJHezZYtW6hduzaurq706tVLEJ8AunTpItwUUlJSxNw6efIk1tbWouonj8XNyMhAU1NTeJd+HY8ePcLW1paLFy8K20BpbZCP0tJS4b+bk5NDdnY21atXx8fHBx8fH3Jzc+nRo4dwSrly5YpoD549e5YhQ4YIk/q0tDSqVatGcnIyGhoadOjQgXr16qGsrCzWm1q1amFqaoq7uzuHDx8mOTmZ9PR0WrVqhbm5OTt27ADKdcpCQ0ORyWQC+H7mzBm0tbWJjY0Vot+bNm2ic+fOxMTE0KxZM86dOyfei+SL/DX5rG7duj91CCorK2P27NmYmJiQlZVF69athZuDsrKyYEIfPXpUWNZpampSqVIlMb6lxE5LS4vw8HCRgDVv3pzs7GwKCgrQ09MTNm7Ozs6CXCJhwV68eEFQUBCamppUq1ZN3N+kSZOIjo6mefPmFZxg/kqr8+tD0S+//IKenp4Cy/rTp08kJSUJgsLFixfR0tIScBEp5MXPvz7gfK9y/eTJEyGJJH89+Xu8deuWkOD6448/kMlkREREkJycjKGhIcHBwQJq9L158He0PKWDecOGDRk+fDhQjiHU19cXig+fPn36lwoc/xPjn6Tu/w9pcK9bt47AwEBsbW3x9vZWsKkZMWIEgYGB9OzZk7lz5xIdHU2TJk1EUiJ/Hfk4cOAA8fHxFBcXc+3aNVJTU4mIiFDAY509e5aDBw+KVubp06cxNTUlJCSE2rVrY2RkRFpaGklJSURFRYnF6Pbt2xgZGdG/f39xrbFjx5KdnU2dOnUqsFZ/FHPmzGHo0KEV6PWNGjXC1taW5cuXs3btWnR0dJgyZQpPnjxhx44d+Pv7i8RNfrLLg3+lBV+KtWvXYmNjQ0BAgAID9OzZs9SsWRNlZWUF/SYo30DU1dXR19f/rnH3lStX8PT0JCEh4ZsLyK1btwgKChKtQek+S0tL6dChg5DfGDJkCDo6OgoinEeOHBG2S/ISKhLQfNasWRUqPP9VIf9sy8rKsLKyEvZLSkpKNGzYkPnz51O1alUMDQ0FG8/AwABXV1fU1dXR0dERz/Hp06cMHz4cIyMj+vXrR0pKClZWVmzbto0vX77Qu3dvVFVVBai/sLCQ0tJSfv/9d4HzWrVqFQ8ePOD69evY2NhQvXr177IVW7RoQWBgIPXq1aNKlSps3bqVw4cPY2pqSsOGDTl9+jTXr1/HwsJC4Bl1dXWxsbFh7Nix/Pbbb4Io5O/vT1ZWFrq6utSoUYNdu3Zx//59hZP/z0jIbNy4EW1tbfr168eMGTNISEggIiJCoc2/cOFCevXqRevWrQUW7MSJE6IlLx2gpPezZ88egWk8evRohc+U2JUSQ1P+MPJ1XLlyhfj4eHR0dISbx549e+jbty/u7u48fvxY+MYmJyeLhGj06NFYW1ujrKyMkpISsbGxVK1aVZAj9PT0UFZWFomQiooKHh4emJubc/LkSYqLi7l69SrVq1dHS0tLQfcsMzOTsLAw/P39Wb16tZD2GThwIMXFxUL0u1OnToBim7CsrEy8FyMjI6ytrcnNzf2X9OgAkQx369ZNJAfv37+nevXqIrEbNWoUUH5otbCwQElJifj4eDF/SktLKSoqok2bNpiZmYnOxM6dOwkICEBVVZW0tDSsrKzYuXMnL168EOzuWrVqiQPMixcv0NbWxs7OTuGQN3nyZNzd3Rk6dKj47t8K+fVz8uTJNGzYkHr16tG/f3++fPnCq1evqF27NioqKuTn59OjRw/i4+Px8fGhqKiI8+fPiwqpFPKJ4bNnzyqIn3/vXqRn+fHjR6ZMmYK+vr7CYVj+XidNmkRsbCxZWVl07tyZhg0b4u3tLazjjh49irq6usBW/l0hfw/S90hPT6egoIC9e/eiq6srEjpJhF7eM/z/xfgnqZOL3bt3o6mpyeTJk1m3bh2zZs3C2NiY9PR0oHwAjRo1CkdHR1q2bElOTg4WFhbUq1evAj7mW/8N5SXmy5cvU69ePXFq69OnD66urri7u2Nra0v79u159eoVe/bsEadlaQFWU1OjV69evHv3TiwaI0aMwNfXtwJhQ15a4WciMDAQmUxGo0aNKtx348aNsbOzw8/PTwDPP378SN++fVFXV2fWrFnfPQGtWrVK+N/Km41LoNoTJ04ofN6KFSvQ0tJCVVWVo0ePikVJEnL9K8LB4sWLhYSFlLwVFxfz7t070tLSqFy5sgK7U/rsnJwc5s+fz8uXL4VNTllZGfv372fBggVs2bKFkydP4u7uTq1atURbDf6jGvu1ev3fHV9Xdi9evEhZWRnz588Xm3JgYCDPnj2jtLSUq1evYm9vj76+Ps7OzqIKdOnSJWJjY3FwcFCoaOXl5VG9enXKysqE+OvWrVv5448/UFNTEzpW0n0cOHCAnJwcmjZtyo0bNxQYrnZ2diQkJCgkdtKGvnXrVpo1a8aOHTuoW7cuVapUYcmSJRw/fhwXFxesrKxwcnLCycmJ0NBQXFxcSE5OxsvLi0+fPrF//37c3NzQ19dHW1sbT09PIV0jLzr9sxIyV65cwdfXV2wAHz9+xMzMDA8PDwWfzsuXLwspE/l3cerUKWrUqIGdnZ2C9MXly5dp0KABnTp1+i5+b8OGDchkMjQ1NUWS/fV7fvPmjaiIGRkZkZ2drXCQy8jIYOjQoVSpUoWWLVuSmJhIZGQkHTp0wMjICAsLC6pWrSrEiNPT01FWVhYM4aioKMaOHcuCBQvQ0tIiMjJSdCqk+XHjxg0SExOpUaOGGPstWrTA3t4eR0dHbt26xf79+xWe/5s3b0hMTERXV5fOnTtXkImRxG8fPnzI8uXL0dTUJC8vjy9fvvzlxis/bz09PbG1tWXt2rViDH7+/FmoBCgrKwttzJycHNTU1NDR0eHYsWMKRKODBw+yYsUKzp8/T0FBAadOnaJ58+Y4Ozvj4eHBqlWrOH36NCEhISgrKwtsbXJyMi9evGDbtm0CswuKFSgJ8vAzkZeXh4mJCb179yYjIwMfHx8CAwPFgWT48OFUrVqVpKQk2rZtS3Fx8TcrpFJ8fcD52co1lGOeO3bsKMh9UhXs6+tOmTKFmJgYbG1tFdQLpGtVq1ZNkN/+7pg/f77o3GRnZwvnk0WLFonfefbsGXFxccIO7f/V+Cepk4vc3FwaNWqk8LMTJ05gaGgoTpoAVatWxd7enk6dOpGZmYmuri6ZmZkKJ/G/WpCkhGvcuHFYWFiIydW6dWsMDAwEWPfcuXMsXbqUnj17EhwcjKenJy4uLtjb29OjRw/Onz/PiRMnsLOzE62in1k4vofnkHBSkkCpfFSvXh1TU1MGDBjApUuXaN++Pa6urhgaGhISEkK3bt0UHAekkGepyoODd+/eTUJCggDCy0ft2rXR0tJSqIK+fPkSX19fhYkqH/KfO2/ePMzMzDA2NiYtLY3U1FSqVq1KUFCQSKZLSkrYvn27wHW1a9cOHx8f7O3t6dixI8XFxezatUsYd/fo0YPi4mKFxE4eVD1t2rT/Uiq8/Pc7ffo0Xbp0wd7ensWLF3Pr1i1iY2OFVETfvn05cuQIKSkpuLu7Y25ujq+vrwB8Q7mWlUTikSq6b968oaysjCtXrghWoLm5OfPmzcPExAQDAwN8fX0ZMGAAnTp1wtDQEG1tbdzd3bGzs6NDhw4ieTl58iT29vZUrVq1AhtZwofJC3BXrVqVrVu3CsuwnTt3CsZjfHy8cBv4+PEjLVu2xMLCggsXLpCVlYWNjQ3169enT58+mJqaKmxo8pWK783Lu3fvkpeXx8uXL7l//z7Ozs60b9+ekydP4uTkRFBQELNmzRKJlZubGz169FDwa71y5QpJSUlYW1tz4sQJXrx4wcCBA6lVq9YP9dUePHjAqlWraNmyJdra2iJhkp9/hYWFjB49muTkZIKDg5k6dSqVK1cmPDycAQMGkJGRgb29PeHh4ZSUlDB//nySkpLw9/cnOTkZZWVl6tWrx6JFixgwYACampp07NhReLx6e3sTHBzMnTt32Lp1K+bm5qSmpla412vXrglx7lOnTpGSkoKSkpKYk19X6p8/f05aWhrZ2dmYmJjQsWNH8R6+PlRBeeLztUTQ96KsrIzPnz/j6elJ27Ztad26NZ6enqxevVrMw5UrV4o2qaamJuHh4WhoaLB//36xdkuM1Z49e2JtbY2jo6Pwfq5SpQonTpygadOmmJqaoqOjg5ubG+rq6kyYMIHHjx/j6uqKiooKvr6+6OnpCfLb9/TO/mp9Pn/+PM7OzuzatUv87OTJk4SEhBAeHi6uK19xlq+QlpSUiArpjxK7nxE/l7x7ly5dyrx588jOzhauEN+67syZMwkMDKR27doK5Lh3795RqVKlH4rO/2fj8+fPGBgYiO/69OlT4uLicHBwoKioiPfv3/Ps2TNq1KhBZGTk/3h261/F/+qkTt5uCMoxHImJieLfpZc/fvx4QkJCePz4MX/++ScWFhYKrdOVK1fi5+dHRkZGBUX5H312aWkp9erVE+2MDRs2YGBgIFqVnz59UpgwL1++5OPHj7x48YLu3btTuXJl1NTUhHZRUFDQT7X/5BcZyWpIftORMEl79+6tMAEkEoWuri4ZGRnMmzePoqIiWrZsSYMGDRR+t23btgq4t2PHjiGTyRRAwjt37sTX1xdDQ0Pi4uJEFa6oqIiMjAwhpSCp3vv7+ys8k68XJPkN4tChQwwbNoxq1arRqlUrxo8fLxLDzMxMAQJet24dUL4YhIeHY2FhofCsKlWqhLq6Op07dxanz5MnT+Lp6UndunXZvXu3wj383Yld+/btFdrNPXv2RE9PT1QgzM3NmTJlihD1VFVVRU1NDXNzcywsLDAwMBB+ndL7kuLdu3ckJCSgoaEhZEJOnDjB77//zqpVq/D19cXOzk60OX19fcVnSF63ki1Q69atMTIyUpgb27dvF23SlJQUVq5cKdqCmzZtIiYmRghw16lTh7i4OKZOnSr+fvfu3aICXbNmTcHstba2Fq0d6d98fHy4f/++2NC+ruhKY+7FixdcvHhRwa+zpKSEZ8+eie/RqFEj0YLLysrC1taW9PR0Bg8ezLhx49i5cycDBgwQPq6zZs0SyXDTpk2RyWR4e3ujr6+vcJ/wH2P01atXPHjwQGGTbtSokQLmCcoTnfPnz/Pu3TsmTpxIVFSUgIWMHTuW8PBw8YzPnDkjsEW3bt0SmnCSVmGHDh04efIkERERyGQyxo0bR9euXQXe7vHjx5SVlbFp0yacnJy+SQCTxLklwWNvb2+sra0VsLvSd8zMzERTUxM7OztsbGzQ0tISvrDfeiY/E19X+8LCwsjMzOTw4cO0bNkSb29v1qxZw+bNm9HS0sLPz088HyUlJVGpefr0KQ0bNkQmk9G3b1/MzMzYv38/r1+/ZsuWLXh7e2NsbExSUhLXr1/n/v37bN68mYyMDJo1a0ZRURHFxcU0b95cSPjUqlVL3Od/NnnYv38/+vr6CpjukpISCgoK8PLyEod3+XVm3759FSqkf5XY/ZX4+YsXL4iMjFSw/Xr48CFDhw5FS0uLMWPGfPO7Tps2jejoaBo3bizkrFJSUggKCvrb10ZpLEydOpWYmBiuXLlCSUkJO3bswMvLCwsLC/z9/QkLC6NSpUp/u5fs/43xvzqpg/I2oARyXrx4MW5ubgIELMX8+fNxd3fn1atXHD9+HEtLS3G6k2L58uWoqKiQlZX1TZ+8r09rZWVlfPz4kejoaI4dO8bBgwcV+v9fvnxh4sSJCpWgr6/1/PlzgZvS1tbGyMhIbEw/E71798bLywsjIyNyc3MV7rty5co4ODgwbdo0lixZolAd27NnjzhFSpOjXbt2NGnSRLRNnjx5gpubGy4uLqLa8uzZMyZMmICZmZnQt+vduzcGBga4ublhamqKhYUFlSpVEhIR/fr1IzY2Vog9y0/KESNGMHDgQPE85Z/t96KwsJB169ZhYmKCpqamqLQUFRXx6dMnNm/ejL29PW5ubqSmplKzZk1MTU1p1KiRsLGST+wMDQ3/S2RK5O/X09MTV1dXLl++zLZt27CzsyM5ORmZTIajo6PA0k2fPp25c+eirKyMp6cnBgYGODg4sGnTJnENS0tLdu/erbC4vn37lo4dO1JSUsKiRYuws7OjY8eOXL16lTVr1gh5HakVW1ZWxt69e4mPj2f06NFAOUZS/kDy+fNnPn78yJ07d/D19RXsR3kB7pUrV5KWlsa2bdsoKyvj4sWLVKlSBSMjI3799VeRdEv/DuDn54eqqqpQ5pd/19IG9S0JGXlB6NDQUBwdHXFwcBCWTfJRtWpVunfvLv5369atGT9+PE+ePKGgoAB9fX0x/x89esTAgQPR1NSkcuXKzJo1Ro+p4gAAiHRJREFUi+vXr3Pw4EE2bNhQQVpHut8NGzYQExODjY0NaWlp9OnTh7KyMt69e0dOTg7a2trMnj2brl27YmxsLBLud+/eMXnyZHx8fOjYsSOnT58mLS2NtLQ08W6kLsDBgwextbUlMjJSaLJJgsPNmzcnISEBOzs7li1bRlxcHBkZGQos96+ri/Jr2JUrV0hPT+fChQts2rQJDw8PLCwsmDp1KkeOHBF+p0pKSvTo0YP379/TvXt31NTU/i1pH+n57d69m2bNmlG/fn08PDywsbERHtmtWrUSzH1fX190dHTw9/fHwMBAdGL+/PNPrl69yosXL2jevDn16tUTrUHpM/bt24eDgwM2NjY0aNBAHEaqVKlChw4dxPOoU6cOe/bsoWPHjkRERDBixIgK9/tX30f+vx89eoS7u7twSZHi1atXWFtbV/j596759u3bbyZ2Pyt+/ubNGywtLRkyZIjCzx88eEBkZCQymUxoF4Li+Jg2bRoxMTFkZ2cTHR2Nm5vb35JQfa/DdObMGezt7YUSQ0lJCR8+fGDq1KlMnTqVlStXis/9nyws/DPxvzKpk2enZWZmikTq3LlzJCcnU79+fbZv3y6qaT169CAmJoa3b99y7NgxzM3NBXZKfqB6enpibm5egWgg/d7Hjx958OCBwqBu2rQpdnZ2aGtrKyROz58/JzY2VqFq8fX9S/H06VOOHj0qBFC/F/ITYs2aNdja2rJp0yZGjRpFZGQk6enpbN++XfyOxPR0cnJCX1+fqlWrVmB43rlzhz59+mBgYFAB03fjxg2io6NxcnISG+7z58+ZNGkSRkZGNG/eHCcnJ7Zv386uXbuIjo4mIyODgIAAIiIixHXev3+vYMgtTcqRI0diZWX1Q0V+6R3KP7dz586hqqqKnp4eLVq0UCBUlJSUMHjwYDw8PAgICKBZs2ZCZiM3N7dCYnf16tX/8lPfmzdvqFq1Kl5eXjRu3JhGjRpx5MgRTE1NSUtLw9nZGTU1NSwtLVmzZg1TpkwRlk+enp5UrVoVb29viouLqV69unCQKC4uFpsbQIcOHVBVVWXEiBFiQ5ekHMzMzLCxscHMzIx169bx5s0bcSDZv39/hQPJpEmTxIHk2rVr1K1bl1q1arFu3TrWr19PbGysgh2ThMfcv3+/EHvV1NQUWDapIvvkyRO0tLTQ19dn375933328hIy0vs/c+aMsL8qKCigQ4cOqKuri02ypKSEwsJCmjZtSlpaGjNnzqRXr15YWVkpVKx69OhB48aNhVVaZmYmnp6eNG3aVDDWJ02a9N33+fvvv6OlpcXYsWO5ePEiXbp0QUVFhU2bNgHl0iddunTB0dGRSpUqCbyuNH7fv3/PlClT8Pf3p1mzZrx8+VJhIy8qKmLx4sXUq1eP8PBwPD09BZPbx8cHCwsLfH19GTduHHXq1BEHu/Pnz1fY8CZNmqQwF+XXECl5LCsrY9++fdSrV0+4N7i5uWFjYyPYzE+ePBFYZOm9/Gc9jyXLxsTERGxtbUV71cXFhf3793P58mVmzpyJoaEhkZGRVKpUCW1tbVHdvH37Nu7u7lSuXFmMjxYtWlCnTh3xHaXn+dtvv6Gjo0PlypVp0KABL168YMqUKSgrK5OVlUVQUJCYW48fP6Zjx45ERUX9FCHg6wRF2ksKCwtp2LAh8fHxQhoI/qOF+T34ybdCPrH7ERb5WxIqZWVltGvXjjp16nDp0qUKFoRRUVGkpqZW0KGUYvr06djZ2REUFCS+29+VUP3+++8VOiSDBw/G3t7+uxql8P92hU6K/xVJ3bey+yNHjpCdnU2VKlUUaPO7du0iJSUFBwcHIiMjSUpKQl9fXwEU37ZtWwwNDRVarc+ePSM7O5uFCxdW+LwdO3bQrl077OzsMDQ0JDU1lVmzZgHlQOrIyEh8fHwEE+vly5ckJycTFRX1XzIICwoK6NSpk7gH6R4lm7IdO3YIr9Vq1arx+PFjjhw5gpubG5GRkWID/uOPP6hSpQpeXl6iPSiZSktx48YNoqKicHJyYujQoQwYMEAkdnp6emhqagqM29GjRyktLeXMmTNYW1srsA6/p9sUFhYmGIN/9ayk9yJVXNetW4e+vr6Crlr//v0xMTGhadOmVK5cGXd3d4XnlJubS1hYGN27d1ewLPrvSOwkBwhJmLVbt24MGzaM4OBgNDQ0xGY6d+5cQkNDUVJSwsrKik6dOonFtKSkhMTEROzs7Jg7dy5hYWHUrFmTx48fC92w/Px80fqRCCV9+/ZFX18fExMTHBwc+PDhw790ILly5Qo1atQgMTGRq1ev8uHDBw4fPkxaWhpNmjRRaI3s2rULmUyGhYWFQtVDSqIWL16MiooKGhoa36xkSyE/Vq5fv46mpqbwxoRyJrS6urpCVQ7K50JycjIuLi74+PhUgFSsXr2ayMhISktLFbB90vecOHHiN11mysrK7ZyaNGki5CFevnyJjY2NAmZXitu3b1cgH30rsWvVqhVQjs9NTEwkISGBoKAgIQ4+bNgwfH19hXCx1MIOCQkR+LGvOw9SFBQUYGFhoYCv+xbjUIrz589z5MgRHjx4QIMGDVi6dCnPnz/H2tqa1q1bizVuw4YN4uD8vfjWv506dQp3d3c6dOiAtrY23bt3F760SkpKWFtbM3DgQI4cOUJISAi2traoq6vTokUL8dkvXrwQyW5GRgYPHz5k9erVyGQyhfFUVlbGypUriYiIYPr06URHR5OZmcnjx4+ZOXMmDRo0oE2bNgoH+8ePH9O0aVN++eWXn24pjxo1ijp16hAREcHUqVN5+fIlT58+JTY2lsjISNq2bcvcuXOJi4vDz8/vX15r/kr8XP59vn//XoFgt2rVKjw9PcnNzRVj+sSJE8THxzN//vxvXkP+vzdt2vS3VshKS0u5dOkS3t7e2NnZ0bx5c44ePcqXL194/PgxkZGRAtP4/3pF7nvxvyKpg3IgtDzrZfHixTg5OaGlpVWh3XrhwgU2bNhAy5YtSUpKolKlSvj7+5OQkMDFixd58eIFDRo0QFtbm0GDBjF+/HiqVatGTEyMmMjSQJ47dy42NjZ069aNUaNGMXPmTHx9fbG0tOTXX38FyjcJySczKiqK0NBQgoOD/0v6/+fOncPV1RVdXV1B85di586dJCQkEBUVRUBAAJmZmaL6V1JSwuXLl3F3dycyMlIkNFu3blVwlBgzZgwqKipC9BLKEzsXFxeUlJREefz58+eMGjUKZWVlIiMjFe7j2bNnuLi4VJBBgf/Y2KVo1KgRgYGBP/zO0juRnDgkBubr16/p37+/aF+uWLGC/Px8evXqxdKlS7l69Sq5ubnY2NgoCCw3b95cbBL/lSFdX1rILly4QGhoKOrq6oSGhtKuXTtCQkLYuXMndevWFYblTZs2paysjJycHGxtbZk3bx6FhYUKi1xwcDDp6enMmjWLuLg4MjMzqVevHgEBAVhaWpKXl8etW7fEgURPTw9VVVVsbW1FovWvHkiuXbtGYmIiiYmJQsgWyg9YEji+qKiIV69esWnTJkaMGIGnp6eCPtanT5948OABsbGxJCcn/xSovrS0lPz8fMzMzIQoLJQzCGUymbDYWrhwoRhfkofy1/qLUkievl9j+34mkpKShM2XjY2NgmzShg0bBHPye/hY+fE8bdo07O3tCQ4OxtLSkhEjRjB9+nRMTU3x8fHB2dmZLl26sGzZMrFOeXh4YGJigomJCb6+vtStW/e7TPnS0lL+/PNPIZMi//Ovfw9QEBlv3ry5SBw7dOggxt/Hjx/Jyspi6NCh3914peu9fv2amzdvivbzgQMHaNu2LbVq1aJz585C2kWyOtPQ0MDAwEBgBJWVlQkODgYQJK4+ffrg4uLCqFGjiImJITMzk4cPH9KlSxcMDAzEmvb69Wtx0C0rK2PevHkisZNIAPICvlL8lZer/LMbMGAAxsbGdOnShZYtW2JsbEzDhg25fv06z58/p1+/foSGhhIVFUX9+vX/03vC98TP5e9l3LhxJCQkEBcXp4B7nDNnDgEBAQQGBuLo6Ii6urrwJt+9e/c3D9z/KjnkR/GtosyDBw/YvXs33t7eREZGkpaWxu3btwWT/n9z/K9I6kpKSsjLy8Pd3V1ggKAcT+fj40PNmjW/eVLt168fFhYWzJs3j7Nnz2JpaUlkZKSY0P3796dy5coEBQVRs2bNCmyuGTNmoK6uzvLlyxVwDNeuXSMnJwczMzPR+nnw4AFjxoxh1KhRLFy48G873Xxrwi1fvhwvLy9iY2MVpFigvEri7OyMjo4Oenp6ooomTazLly/j4+ODh4eHUC//OiS7GGnznzFjBqqqqnh4eCi0YqUTs7GxsYJFzcePHwkJCWHOnDkK9z1jxgyaNWumwOC8ffs2vr6+gsH6ve//+++/k5KSQkxMDLVq1RIl+rdv3zJq1Ci0tLTQ1tYWOm+SLMWNGzfo1q0btra2CoDhnzXg/s+EpJsnxbx581BTU8PR0ZG5c+fi6uqKlpYWwcHBODk50bFjRypXroyGhgY6Ojo0bNhQAJQlOYRFixYptLvk29Jz586lcuXKeHp6EhQUxOTJk7GysiI5ORkzMzPatm0rdBKlA4lU8fpXDyTy7Mmvq2yHDx/m/2vvLgOqyr42gD+HBpFSBAxEsVBQUURCRQUDTAS7u7u7uxUDe0QdO7Bz1HEcu8FEMVFEFBFQ6nk/8N7zvxfQMUAQ9+/LODcP995zzjp7r72WjY2NvH+FhoZy/PjxLFWqFCdOnCg/bv369Wl+t/9FcdKuXLkyly5dypkzZ8o1+bZv305vb286ODiwQIECrFmzpjwVmpri+96/fz9LlCjBXbt2qdz+OUFBQXzy5Ak/ffpEb29vdujQgdbW1nLZHDIlGGjdujWXLFnCAwcOsG/fvp8dQVME0VFRUezZsyeLFy/ORYsW8cCBAxwyZAhz5cpFPT09WllZsXz58hw8eLC8aCkxMZFPnz7liBEjaGRklG4tS+XfR1BQENeuXUtJkuSSNmTafWDfvn2sUqWKnMj/9OlT2tvbs0CBAiqvO2rUKBYuXFil7aIy5fzHKlWqyB0xFKWU7t27Rzc3N7q5udHHx4d58uShlpaWvHgoT548XLlyJd+8eUM/Pz9KksTmzZuzQ4cObNu2LQ0MDOTR1zVr1rBq1aps1qwZL1y4wBEjRlBXV1euU1q+fHmVaWbF49u2bSt/nl9Tcy49jx8/5ogRI1QqAhw+fJgVK1Zku3btVPouK3Idye8/J3zpNzpixAiam5tzzpw5XLVqFc3NzVm7dm35mHH69Gl2796duXPnZrNmzbh7927a29vT3d1dpRdtRh8PlT/Dw4cPc9myZdy6dau8wj4qKorbtm1j3bp1WaRIEdapU4eSJH2x3mNO91sEdWRK0KQ4qCsvq968eTMdHBzYtm1blRPFo0ePWKFCBR44cIBkyiiWgYFBmtGjyMhIxsTEpMn32rVrFyVJkk8OytNfZEqwUL16dVasWPGzK5B+dIROeYeIiopS6Vu5detW2tvbs2PHjvJIgyIQuHDhAk+cOMH8+fPLnSzI/+2wQUFBdHR0VFmdldqyZcuopqbGNm3ayJ+DYiq2aNGi7NOnD+/cucOLFy/S29ubFStWZOfOnbls2TJ5miF1Qu/8+fNZt25d6ujosHv37ly/fj2Tk5NZv3599ujR47Pbsnv3bubKlYtjx47lihUrWKtWLebLl4/Tp0/n5s2b+eHDB/r5+bFAgQLyikBlISEhHDJkCNXV1VUOYJnRJ1B5qnnJkiW0t7enlpYW1dTUqKOjw/Lly7Nu3bo0NjaWp5wU9dmKFStGMzMz6uvry/0nyZQpcUXBZOXfamxsrNyLde3atfIq30aNGsmrAg0NDWlsbEwtLS0+fPgwQy5IFKsnldsxkSmrlcuXL087Ozs5sHv8+DEnTJjAUqVKsVOnThw9ejQlSfpsQPAlipynkiVLUkNDQ+VkqtjWxYsXs2PHjiqdDdLz8uVLFitWTGU6Nz2Krg4GBgZywerTp09TX1+f5cqVU3nsqFGjWLRoUfr5+VFPT4/Tpk2TC/EqX5zdvXuX586dk5vCHzp0iFWqVGHRokVZvHhxSpJEa2trrl+/Xl6dqiiaHhoayvfv37NXr160tbX9z+BYkXvbs2dP+bfo5eWl8veRKfuYrq4uZ8yYwbNnz8qf6Y4dO2hubk47Ozt6e3uzcePGzJMnz2erBCjnP+rr67Nnz57cuHEj27dvz7x587J///4kSRcXFxoZGdHMzIw9evSQe976+Pgwd+7c9PDwkEdZDx48yObNm7Nx48YcMmQIb9++nab8kZubG5s3b87IyEhev36d27dvV6krp3wsWr16NStXrszVq1erfDffQrEIKF++fGl6wB48eJBaWlr86/9rSirLjIvIwMBAlilTRv7eAgMDqa+vz9y5c9PBwYFxcXE8fPgwhw8frpIrqgiuMzuwI1NW/BcpUoQuLi6sW7cuLSws0uTUbdy4kT179mT16tV/26lX8jcK6sj/HdRTB3abNm2ig4MDO3ToINeau3HjBgsXLkwy5apcORE8Kioq3RVIigPSx48f2aNHD1pbW3Px4sXy/YoDhOJHf/jwYaqpqX0xL+h7KQccM2bMYLVq1VSmkMmUv7tixYrs2LEjd+3aRU1NTf7xxx/y844dO8Z8+fKpLNNXbLvyQe5zwc38+fPlhH3F1PeDBw+YJ08eSpIkjxDcv3+fs2bNYtmyZVm9enU2b95cniJNTEzkkCFDVBrO79q1i926daOJiQnbtWsnB47pfY737t1jxYoV6efnRzJl9CBPnjxUV1enpqYmx44dK/9NV69epa+vL0uUKKHS9JpMWRCxePHin5ZoO3z4cOrr68urKgEwV65czJUrF6dNm0ZXV1e52DAAmpmZ8dWrVzxy5AgtLS3ZunVrnjt3Tn69pk2bMm/evDx48CDJlECgTZs2rFKlCidOnMgrV65w7dq1cvV8ACxcuDDt7e3leoGJiYlMTEzMkAuS27dv09fXV6VtUnJyMv/55x9WrVpVZcTu6dOnXLx4MR0dHens7PzVZYPS8/LlS/br149ly5ZV6ViiPP34tSeEgIAA5sqVK91OEan17t2b9vb28oKLNWvWUJIkNmjQgK1bt2br1q1pZGTEP//8kxYWFnLAoKD4nNatW0cbGxvq6OhQkiR26dKFixcvZp48eXjy5Ek6OTnR29tbHq0oWbIkJUlipUqVWKBAAXk/iIiIkFelf05oaCjNzMzkKev3799zz549tLCwoKenp/y4ly9fsmLFiiopFwoJCQkMDQ1lv3792L17d06ZMuU/p8wV+Y/K+6aijZmamhr79evH6dOnU11dXS79UadOHero6LBnz57MmzcvbW1tOXDgQPk3pJhW/1w+oPLUauqL1dTHbZKsV6+eynHxvyjeV/Hf58+fy71Y08sBK1OmjErJkMy0a9cuudPF/v37qa2tzZYtW/Lvv/+mjo4Oa9asKR+zUy+2ePToEd3c3Fi7dm2Vmo0Z6Y8//qC5ubl8Abho0SJKkpTu+8XFxaUZYPnd/FZBHfn5wG7z5s20trZmjx49+PHjR3769IkuLi5yPpFysnxQUBCdnZ0/W42bTFmWrhgZVD7YKY/E3L17lzo6OiorTjNaelPIjo6OcsmQjRs30tHRkY0aNWLz5s2ZO3dulanQv/76i/ny5aOPj0+6r5+6B+C1a9f46dMnOeibMmUKAbBQoUJcsGABfX19aWNjwxYtWqQpSUGm7JTKeSoDBgyQq+0rTxPFx8fz4cOH7NixIz09PSlJEocNG5Zmmy5fvsxBgwbx06dPfPr0Kc3MzKihocFFixaxdOnStLKyUhmtuHTpEtu1a8fSpUur9P1UllmBnSKQ3bBhAwsWLMjixYszICCAZ8+elXOGFPl/jx494qFDh2hvb08TExNWqFCBzZo1Y3h4OI8dO0Z7e/s0gd3o0aOZmJjIXbt2UVdXl8OHD+fw4cNZu3Zturi48MKFC/T392e+fPmopaVFR0dHzpgxQ17hq/x9/egFiaL0xsuXL/nmzRs52ElKSuLff//NKlWqqAR2Hz9+ZFJSksrilO+lfAxQ3je/9SSgyO1TrsWY+reheM2TJ0/S0dFR/k0lJyezadOmLFOmDH18fDhixAjevn2b27dvZ9myZUmmBJrr169nrVq1WKhQIbq5uVFbW5utW7emmpoa69atS3Nzc7q4uHDatGm8ffs2TU1Nqa+vz2XLljEsLIwtWrTgxYsXmZiYKI+ipjeSMmLEiDTHsxs3brBAgQIqiz5Gjhwp580qSoAo2sIpfguKqeHvoZz/qLgQHDZsGCVJYpkyZZg3b16qqanRwMBA7imqq6vL3Llzy9OwV65c4eTJk+UFTcpFcFNvV+rArlq1amzTpk26faWVH9+rVy+2aNHiq7r2/Pnnn+zYsaO8QEghLCyM7dq1o66urspoXVRUFIsWLSoPImSkz30vjx49YnR0NF1cXFi7dm05p7R06dKUJImNGjWinZ0dnZ2d0+zzjx49YunSpVXKpmTENiqO48OGDZNHaHft2kV9fX35fBwdHZ1u9YPMznfOzn67oI5MP7BLSkri9u3b5fY/cXFxHDBgAI2NjeXVZWRK0FGvXj3Wq1fvP6ff/uvksX37drq6un6xJMePCA0NTXcKefny5Wly1Tp16sSkpCT269dPLiWhXK9JXV09TbN15dcYNWoUbWxsqKenx/Lly3PAgAHyyr2pU6dSkiSamJjQxMREPoErAoXUr6X4/4EDBzJv3rw8e/YsbWxs5L9D+fGJiYl89+4dR48eTSMjI3kKWXn0RDFV16xZMxoaGsoLRJo1a0ZJkmhpaamyAOPixYts164d7ezsuH379m/70L/T4cOHOWvWLJ45c4Zr1qzh9OnTWbBgQY4fP54GBgZcv349p02bRjU1NWpoaNDJyUnOe3rz5o2cF6eYQjp27BgrVKjANm3aqKzcvn79Om1sbOT8wNevXzNv3rxy14Rz585x3rx5LFCgAPPmzSs3Qycz7oJEsd8EBgbSycmJpUqVYsWKFeXpyeTkZJ45c4ZVqlShnZ2d/J1mJMW+6erqqtJu61spfjepG7U/ePBAZdEAmVKA1dXVVf7/nTt3yh1TFK9z6tQplihRgh07dmTlypXZsGFDdunShf369SMA+vj4UJIkbt26lVFRUSxXrhxNTEw4c+ZMHj58mJIksUKFCjx16hTd3d1ZuHBhrlq1iuT/As70Lko6d+6cpufq27dvmS9fPi5YsIBkyoVq27Zt+ffff9PGxoaSJLFJkyYMDQ1lkSJFVEb5Fd/xoUOHvnlq7unTp/IF8eDBg5k/f37WqVOHuXLlYo0aNaijoyMvCipTpgxNTU3p5ubGGjVq0NvbWw60pkyZwhIlSnDUqFFfPFYrb9PXTK2+fv2arq6uX9VXOyoqitbW1jQ1NaWdnR07d+6ssmo0JiaGLVu2pI6ODvv378+ZM2fKuasZPdKUuuj8gwcPVBZOBAcH08rKSv5Nzps3j2XKlJG7Cyk66Xh7e8tTtQovXrzIkIvd9ErmDB06lBMnTpSnhRUpUMnJydywYQNnz5793eVxcqLfMqgjUw7qjRo1oqWlpVxTKPWOf+/ePXp5ebFChQrs1KkTx44dSzc3N5V8r+8N7N6/f08vLy927tw5064qvjSF/P79e/bv3z/NVZdyYLd582Z5R/3777/TrJxSmD17NvPkycM9e/bw8uXLHDVqlBxgKEZWZs6cSQC0srJSmVb43OfXr18/GhkZyaNoZcqUURnlUPxX+UBSoUIF+vn5MSYmhtbW1mzbtq18X2xsLG1tbWlsbCyfvHr06MHAwED5Sl75tYKDg1mvXr00gWxmWLNmDQsUKMCePXvywoULfPToEZ88ecJSpUrRyMiIc+fOJZkyQqzoDGFgYMBp06apBLdr166Vp5AiIyPZo0cPamtrq5SYuXLlCtu2bctPnz4xNDSU1tbW7NatG/fv308rKys6Ojry33//ldvXFS1alDNmzEgzpfEtFyTpfcd79+5lrly5OHfuXJ44cYKDBg2iJEnyFbhiKtbW1paVK1fOlPzFsLAwdujQgR4eHmkCsG+xcuVKVq5cmSdOnCCZMnLh4ODA4sWLc+/evfIK8jt37rBEiRL8448/5NGs5ORkHjhwgAMGDODbt28ZExPDefPmsUGDBhw0aBCvXbvGjx8/smPHjvK0uCRJPH78OGNjY9m2bVuWL1+eZcuWpYaGBnv37s3ChQuzZMmSckmmiRMnfvXnd+TIETlXKSEhgb169WKNGjXkwCwmJobx8fGsU6cOZ86cyQcPHvDt27esWrUq3d3d05RyGTBgAD09PdPUt/wcxe8sLCyM1atXp4mJCdXV1amvr8++ffvyxYsX7NevH11dXZk7d266u7vTxsaGDRs2pLu7OyVJ4po1a+TXmz179hfrlqV+X/LrplZTr8L/nMTERI4cOZLLly/n5cuXOXv2bBoZGbFly5acPn064+Pj+fr1aw4cOJCSJNHX15dbtmyRR+0zKrBT/vvGjh1LBwcHWlpa0sHBQS7gHh0dTSsrKzZo0IDHjx9ngQIFqK+vz4kTJzIiIoKJiYm8dOmSHNilbu2o+Hu/1+HDh+VKCsOHD5fL/CxYsEBu0aac0/727VvWrl1briIhpPhtg7qPHz+yTZs2NDY2ZrFixeSDeuoVXXfv3uWcOXPo7OxMb29vDhw4UN7RvnaHUw7sFAFNo0aNWK5cOZXG1hntv6aQTUxMqKmpqdKSSKFRo0YsWLAgAwICvri6Kzo6mp6eniqrihMTE7l69WpWrFhRJfdwzZo17NWrV5oAN3VwRqbk4ym3xnJ3d5dHDBSUP7vk5GTa29tzzpw5TEhI4Jo1a+jh4aHSP9HBwYHq6urcunUr+/Tpw/z586c54D99+lSuuZa64GZm2LhxI/X09LhlyxZ5NbHiPWfOnEktLS22aNGCZMpFhiKZ3sHBgS4uLhwzZsxnc4MOHTrEXLlysVmzZiorlRVTS4pcLsUFSp06dWhkZEQ3NzfGxcXR3d2dRYoU+aELEsXfcvnyZbko95MnT+ju7i5Prz1//lxepSlJklzfLikpiefOnfuqk/L3evnypcr03Pe4d+8eS5cuTS8vL3lU9PTp0+zfvz8tLCxYq1Ytzpkzh+Hh4fT29pankhS2bNlCSZI4ePBgecQh9bFF0fvW2tqaFSpUoJGREceOHSu3aatZsyYdHBx44sQJvn//nseOHaOnpycdHR2/GICknipVjF4rAtRr166xZMmS8sKif/75hz179qSenh51dHTkEfGgoCCamZmxdu3a9PPz4969e9mrVy8aGhp+1YhW6m2ZPHkytbW1mT9/fgKgtra2XHoqNDSUvXv3ppWVFTU0NDhhwgTu379fvjDYtm3bV71feu9PftvU6tc4cOAAc+fOLV9MxsXFyd9dxYoVOXPmTB44cIADBw6kvr6+fDxWBHYZafLkyTQxMeFff/3F0NBQdunShZIkyYvl9u/fT2tra7louaLg+vjx4+Vz5KVLl2hjY8Nq1aqlW4/xeyg655QuXZodO3akgYGBShu/li1bUldXlydOnGBISAjv37/POnXqsGLFir9t7tzn/LZBHZlyMunatSsrVKjw2bw38n/1jZR96xVJWFgY+/btSxcXF+bLl48lSpTI8Dp0qQtAKk8ht2zZkhs2bOCKFSt479491qtXj56ennICfeoRu6FDh9LQ0JAWFhafLV2i2PZq1aqlm0/RoEGDNE3Bw8LC2Lt3b5Wq68rbvWjRIk6aNClNYrGHh4fKCtfKlSuzadOmJFMOxqdPn6YkSfKB/8WLF6xZs6bK1PnSpUsJQJ4KSW/l36RJk+TSCcqfZUbbvXs39+/fz+rVq6sspiFTrpivXr3KmTNnUpIkFihQQC62aWxsTBsbGz59+pStW7eWi5ymF9i1a9eOe/fupYmJCX19fVXy0RRTd4rVbB8/fmSnTp3o5+cnT3f26tWLjRo1Ys+ePb/rgkTxuV2/fp1qampykd9Xr15x3LhxDAsL44sXL2hjY8Nu3boxMjKSzZs3pyRJaQL47Eqx74aEhLBs2bKsWbOmSg2+kydPcvr06cydOzebNm3KqlWrUpKkNNNXW7dulRPRlVv97d+/n/Xq1aMkSRwzZow8ZWxpaUkAcoB47Ngx1qpVi+bm5nKA7OzsrLLg6EsUU24k2aZNGxoaGvLo0aNMTk7mlClTqKamRj09PRYtWpTW1tbcvHkzW7ZsyXz58sl/y+3bt9mwYUOWLFmS1tbWrFKlyjfX8CNTRj7btWvH06dP8/z589TW1qampiZtbGzki7Rnz56xbNmyNDY2Vrmg/K+uOv/lW6ZWv0WvXr3Yq1cv+f9Lly7Nxo0bc/DgwXLLvxkzZrBNmzY0MjJKd+Xr91DeN2NiYujl5cUdO3aQTEl/MDIyki+8FSVyXr16xTt37sjP7du3r9xJRxHYnT17li1atMjwY6OhoSH19PTkYvCKY0xcXBw9PT1ZqFAhGhgYsHLlynR1df0terl+q986qCM/Pz2q+LG+fPmSrVu3lrsb/MiImiIx1tPTM8Paphw7dkylN196U8hVq1alrq4ura2t6ezsnGYKuXHjxjQ1NeXff/8tX50OGzaMp0+fVjnBHD9+nJMmTeKwYcPkE1d8fDzbt29PFxcXPn36VOXzmT59OmvXrp3mile56rryzqiYgihZsqQ8XaN4vZ49e8pFWuvWrUsbGxuV1/33338JgObm5ty4cSNfvnzJW7duUUNDQ65hFxERQScnJ7mdkGL7FeLi4tikSZN0V/FlpPfv39Pb25u6urosUqQId+3aJX9vS5cupa+vLyVJkkuUAKC+vj5NTEzYr18/+TcTHh6uMrKs/FkqcoNWrVrFc+fO0cTEhE2bNpUD9NjYWDZs2JBeXl48duyYXMdRuZ2b4uT2PRckyqUpdHV1VaaAFe9PpkwFeXl58e3btyRTEvELFixIExMTlfZX2Zni+3jw4AHLli3LWrVqpSm38OLFCw4aNIgeHh6UJInHjh3juXPnGB4eLj//zz//lEfsXr9+Lfd/9vb2lutuPX78mH379qWZmRnz589PAwMD7tmzR649d+rUKS5fvlzOg1Levs+JioqipaUlhw8fTjLlt9S6dWsaGBjIr7N161bq6uqybdu2cmmkGzdusGnTpiqB3YcPH/ju3Ts+f/5cpbba11q/fj319fWppaUlT++tWLGCAKipqclChQpx+fLlHDRoEA0MDNiqVSs6OjqqHAN/9AT/tVOr32LVqlV0dXVlZGQk7e3t6erqKu+LT58+5ZYtW5iQkMAPHz6wUaNGLFCgwA/niSmfC54+fcrY2FgWLFiQp0+f5uHDh6mvry+Pin/69Im1a9emo6MjCxYsyHHjxvHvv/+WX6N///50cHDg5MmT0/QX/5HA7vz58zx16pS8GtvU1JTFihWjvb29XHBa+Rhw5swZ7tmzhxcuXEi38LMggjqSqoGdcluiFy9e0NXVlcWLF8+wH05kZGSG/Rg/fvzIbt260c7OTuVqVflEf+vWLRoaGtLDw4OVKlWSp5B37drFPXv2yNvg6+vLXLlysWXLlvT19aWBgYFKLbAVK1bQzMyMNWvWZPHixamnpydfNYeFhdHc3Jz16tXjnTt3GBcXx9jYWFatWpUdO3ZMd9vfvHmjskhi0KBBzJs3L7dt28by5cunCRBnzZpFd3d31qlTh9bW1nJQoRyUKU6Y7dq1k0cm/fz86OjoKE8TrF69mkWKFGGFChXkwq6JiYlyG6tKlSr9lIPEzZs32aRJE6qpqbFhw4Y8fvw4mzRpQjs7O/bs2ZOHDx/m1q1bWaxYMY4dO5aXL19W+d0ob6NyseLQ0FBu2bKFCxcuZN26deXcoPQCu82bN9PNzY1mZmYsXrx4mpFL5ZPb91yQpG7Npfg+//jjDzmobty4sUru44ABA7h27dovjg5nZ3fv3pUDO8UUpkJ8fDzfv3/PFStWyIGrg4MDFyxYIF/EKAK7IUOG8MOHD/KJXtmzZ8/Yt29fOjk50c7OTg7s0puu+5oA59OnTxw8eDB9fHzkQCwhIYGtW7emoaEhT5w4wcTERG7evJm6urrs3bu3/FzlwE55tO97nTp1ik5OTlRXV2fhwoXl8iIBAQHU09OTu0ZYW1vz6tWrGbbg5WeoVKkSJUmim5ubSs1QZQkJCYyIiPhsqaDvMXz4cHbo0IEvX75khw4d2KZNGxoYGKh0yenVqxc1NTXZvXt3Ll26lA4ODvTw8FDptjRw4EBaWlrKOYs/esG1fv16Fi9enF27duWdO3dIpvxeP3z4wHLlyrFcuXJyYKeQ+jee2ekxvyIR1P0/5cBu1qxZjIiIYI0aNVi6dOlMGeLNqB+jcqX81CONERERrFatGvv06aMyhTxjxgxKkqSSAE2mdMjw9fWlt7e3Sj7DihUrqKWlxW3btjEpKYmnTp2igYEBfXx85JPR3bt3WbBgQZYpU4a2trZ0cnJimTJl0nTZSO9z6N69Ow0MDHjt2jWGhYUxd+7caYrLzp8/n5IkqfQITUhI4IsXL+Qrx9u3b9PHx4fjxo1jQEAACxYsyPLly7NkyZKcNm2aHIQsXbqUZcqUoSRJrFWrFitWrEgnJyc6Oztn+nC+8ucQFBTE6tWry1Os5cqV45EjR+QpjuDgYBoZGam0kUpvu5SnORUBq5GREY2MjOjr6yuPaJ47d47Gxsb08fGRD44vXrxgUFDQV+WVfcsFyedac02ePJmmpqZyLtbcuXOppaXF8ePHs0OHDsybN+9Xtf7KSsrT3ZcvX+batWu5dOlSeapRMWJXu3ZtlWm05ORkPnjwgBUqVODSpUt5+fJldujQgU5OThw3bpy8Lyly7EaNGvXZ/UYR2Lm4uLB06dLMkycPN2/e/N0XJFeuXKG2trZKD9+kpCS2bduWkiTx1KlTXwzsWrZsSXV19W+qIaic5qK83VevXqWLiwsNDQ1ZpEgRObC7du0a582bR19fX7kkE5lxC14yi+JvDAgIoK2tLS9duqRye2a9H5kyTVq6dGl5f1uxYgUlSVK5uNu0aRNz5crFChUqMDExkadPn6ampibLly/P6tWrq1ycLFy4MEOOjevWraOuri7Xr1+vErgptv3ly5e0s7NjhQoVePv2bcbGxrJ58+Zyys6vMIKfVURQp0QxzVS5cmUaGhrSxsYmw6ZJM9PnppBv3bpFa2trbt++na1ateLGjRu5bNkyampqcsmSJaxVqxa9vLy4c+dO+TnJyckqo19nzpyR8z2U5c+fn1WqVGF8fLw8dRYVFcV169ZxwoQJXLhwYboLSlLvjBEREWzTpo18Mnj9+jULFy6sskiCTFnppAjMkpOTmZCQwCtXrtDc3Jy9evWSRw1Hjx7NkSNHMjExkf/++y+bN29OdXV1li5dWqWX5o0bN7ho0SK2adOGffv2ZUBAQIY2nv5aQUFBbNSoEU1MTFRqyr18+ZLOzs7U0dFJt9C1QuppztGjR/Ply5c8f/48tbS0VArskinT1MbGxmkWT3yLr70gUb7gWLZsGWfOnElTU1OV0jRhYWEcPXo07ezs6O7unuZ7zy7SO4ls375d3g8UeVGKsh6KHDsvLy95tOPatWscPXq0ShP4jx8/cuDAgaxcubJKYLdjx47/7Grx7NkzOY3Bw8ODderU+eq/JyQkJE0ANGzYMFarVo0nT57kqFGjGBoaysTERHbr1k0eSYmPj083sLty5Qo7dOjw2RXyqSn/hiZMmMDixYuzbdu28oj69evXWbVqVRoYGNDa2jrdunHKr5ERC14y27Nnz2hhYaEyG5SZ5s2bxwEDBqjk8pEpJaaMjIxYs2ZNenp6yv2e4+PjuW/fPhobG3P16tU8duwYjY2NWb16de7evVvlNX4ksLtx4wZLliyZbvHg8PBwOfc3PDyc5cqVY548eViuXDmWLFkyTZchIS0R1KWSGXlvP0N6U8gBAQFUV1eni4uLPIX89OlTeYXezZs36e7uTkdHxzQ1qhSOHDnCWrVq0cXFRe6316RJE+rq6tLDw4Oenp50dnbmzJkzeenSpTSfVeqd/+XLl3zy5AmvX7+ucrWtzMrKSt7hk5OT2aZNG7kSPpnyfezcuZPz58/ntGnT2L59exYuXJgdO3bkuHHjaG1tzfr169PDw4OvXr3ivn375ATq1AHJjy6AyQhBQUFs3rw5TU1N5SmsypUrU19fn46Ojir1/NKTeppTwdnZmaNHj2b79u25adMmuVzAuXPnKEkSO3TokOlXvJ9rzZX6d/Lu3bs004zZheIzioiIkH8/V65coampqTyF9fDhQ3kxg3IrwEKFCrFJkyZ89+4dfX19qa+vz8qVK6u8fmxsLAcOHEhXV1cOGjRIpZUb+eUgWjmv8mt/u8+fP6e2tja9vLxUctHOnDlDa2truQtF8eLFOWTIELkdmUJcXBw3b95MHR0dlQVS37JaVPH3de3alUZGRjQxMaGZmRl1dHTkPK9z586xfPnycq5sZtXz/JkWLVrEPHny/GfA/q3S65ShGGWtXLmyfOF9+/Ztvnnzhjt37mS1atXYqlUrLlmyhOHh4fzw4QOrV6+uUpRfkYOs6CSREceLU6dOsXz58vLxiEy5QOrVqxfz5ctHd3d3ubYimTKa7+fn981VJ35XIqhLR0bmvf1MqaeQ9+3bRzU1NRYsWJDx8fEqyfSKv2/FihWsVKnSFwu8Hj9+nA0aNGDlypXp5ubGihUr8vLly/z48SP//vtv+vn5sXTp0syVKxd79uxJMv2df+PGjaxatSotLCwoSRKtrKxUTgqKXLFSpUrJrXPq1q1LKysrlenjBw8e0NjYWM7tePLkCdetW0dNTU25obeamprK1PLnZHZOxte+flBQEFu0aMG8efMyT5481NfXl6eaExISvrggIb1pzunTp1NNTY0tW7Zk5cqVqaWlxQEDBsijlZcuXZJHXzLb51pz/Ur71tu3b5knTx55enLv3r1s0KAByZSArmDBgiqrsxU5USEhIfIFRUREBDt27EhLS0suWrRI5e+Pi4tjly5d6OHhIZ9glUeWv0Q5p/Jri+z+9ddfnDhxIgsUKEB7e3vOmzePMTEx7NGjBwsVKsR58+bxyJEjHD9+PI2NjdmmTRsuWbJE5fU3b94s5/99jyFDhlBTU5ObN2/mxo0baWdnRwAqxXmXLFlCIyMjlihR4odXtmYHDx48YLt27TL8uBMfH8/Y2Fg+e/ZMZTRr6NChlCSJ/v7+PHfuHPPly8elS5eyV69elCRJpSTJixcvWKRIEfnzDw8PZ6tWrbhp06YM3d6dO3dSU1OTly9f5ocPH9izZ086OjrS09OTEydOZLNmzWhra6syc6EgVrn+NxHUfcGvmISpPIWcO3duqqurs379+gwNDU33JDp48GA2bdo03ZVqyieBY8eOsUGDBtTV1WVgYGCax4SHh/P8+fOf3enWrFkjX4UfP36cp0+fZocOHaijo8N69eqpbFuTJk04a9YsNmzYMM1Ky5MnT3Lt2rXs27dvmvd6+PAhDQwMKEkSAXDq1KnZ5jtcsGDBf5ZJCA4OZvXq1WlkZMS+ffvKQe5/BT+fm+Y8ePCg/P306dOHuXPnztSab1/yX6vMs7tPnz6xcePGbNq0KT98+CDXYQwKCmLhwoXZrVs3lS4KHTt2ZHh4eJrf6Js3b9iiRQu6urpy2bJlKsHYx48f+fLlS86aNYs1a9akvb09vb29ee/evR86mSl+A9HR0UxOTpbzKT9+/Mj379+zd+/edHNzo7m5Odu3b08dHR3q6enJC4levHjBCRMmUE9Pj5UrV+aKFSvknNedO3fy9u3bX7Udyjl0UVFRLFOmDO3t7UmmzCro6OjQ2tqaderU4cOHD/n8+XOOGzdOpYh5TqBcMDwjHD58mD179mShQoVoZGTEevXqqbQY6969O3V0dBgQEMARI0bQ2NiYurq68mIlxffy7Nkzenh4sEWLFly5ciXr1q1LNze3r7pg+FZNmjShJEm0sLBgkSJFuGnTJvlCSJGzfeTIkQx7v9+JCOpyIOUp5M2bN1NLS4utW7dWGfKPiori0KFDaWxs/MUCkukFdpUqVZJz4BITE9Ps7KkPVleuXKG1tbVclkEhIiKCS5cupZ6ensoKyFatWlGSJJVFKsqrdBUNypVHMhSP8/LyYo0aNaimppYmn+xnuXLlikrHkZCQEFpaWn5Vu6sHDx7IpTy+NEKXmvI0p7q6ujzNqSiLsH//fhYtWvSnjc59aRt/hZWK6Vm8eDFNTEwYEhLCJ0+esEqVKjQyMmL79u1J/m9fGThwIL29vbl7927279+f9erV44YNG+RA6PXr12zevDldXFy4YsUKlf1n9OjRNDMz4/Lly3n+/HkaGRmxRo0an01V+C+KbTp06BAbNGjAmjVr0tfXN81v8cWLF5w1axaLFStGU1NTdu3ala1bt5ZXQDdv3pylSpVi+/btWa1aNWpqanLBggXfNR23fft21qtXjyVKlKCrqytPnjxJAwMD+vn5ccuWLXR1daWamhotLCyop6cnXwz9KhcAP9Pq1atZoEABDho0iDNnzqS/vz9tbW1pYWHBoUOHyo/r1q0b9fT02KdPHxoZGdHCwoJ+fn5pflcbNmygu7s7S5QowVq1an1156TvERgYyO3bt6e5aA0KCmLFihVV6j0KX08EdTmUYgo5MTGRS5YsoYaGBkuVKsVOnTqxe/furF+/Ps3Nzb9qtdrnAjtFUvt/Hdj37NnDcuXKMSwsLE2v17dv33LMmDE0NDSUVwoqGmCnl0MRFxfHnj17Ultbm3v37v3sdvbt25daWlppknEzO6iZNm0aJUniwYMHVeqXmZub8+nTp589OKb+DFMXwP4an5vmJCmP5Cn68WaV7L5SUUH5s1f+t729Pdu0aUMypVREvnz5OGPGDL569YqPHj3i8OHDaWJiwgULFjBXrlzs1asXW7duTWdnZ7Zs2VK+gHr9+jVbtWrF0qVLy9NdDx48YLly5eR+useOHWPu3LlVSk+Q336C3b17N/X19Tly5Ej6+fmxWrVqLFasWJoV5mRKXctXr15x27ZtdHZ2ZlJSEjt37kwzMzN52+/cucOFCxf+ZzcBxXYePXqU8+bNI5lSOqN+/fo0NjamJEm0trZW6SKSnJzM+/fvs0yZMnR2dv7qhRe/o+XLl1NLS4t//vmnypTrvXv32L59e5qZmamMivfp04eSJHHHjh0cOXIkLS0t5U4nypKTk/nixYssSUGKjo5m/fr1WatWLRHEfycR1OVwih3j3LlzbNKkCcuVK8cqVapwxIgRKgd15X6qqW9L/e9jx46xcePGLFy48FeVn5gwYQLNzMzSfS0ypRyKhoaGnK+kyP9TjFalfk5CQgJ9fX2ZJ08enj59mn/++SenTp3KqVOnqjSv79+/P3V0dPjHH3/w6dOn9Pb2lrtQZKZGjRrRzMxMXuUZEhJCa2trvn//nsnJyekmNWeU9KY5J0+eTH19/c8uhvnZsvNKRcV3k7oeluJ3OGvWLPkChSQ7duzI8uXLU1tbm5UqVWLJkiW5ceNGFi1aVE72fvv2rbyKs0mTJvKI+atXr9ipUyd5SvzKlSssWrQoyZScPeVezYqV5d/qzp07tLe3l4OmJ0+e0NLSksbGxjQzM5ODpvRWFVarVo1qamrMnz//N3eGUHyOipQCS0tL1qxZk7lz5+atW7d4+fJlmpqasmTJkixVqhT79evHp0+f8q+//pJXZGZmC8Vf3a5duyhJkpwKo/islBfpVK9enZUqVWJoaCivX78ur75WPHbQoEG0tLTkggUL+Pr1a5Ip7biUS4z8rMAqMjKSBw4coJeXF8uVK5epI4Q5nQjqfiP/Vf2fTJmu+1z9KOWD6/79+zls2LCvmh7csmUL9fT0VApZKktISGDBggVVmjUrgroTJ05wwIABcjFhxfYkJSXRx8eHOjo6NDQ0ZP369VmgQAGWL19eXqlFppRpkCSJZcqUUamblxmUX7t+/frMmzcvDxw4wFOnTrFSpUrpPiczEn8VgV3VqlXp6OhIHR0duTaW8N8ePnzIxo0bc82aNWmq+j99+pTGxsZyvayZM2eySZMm3LlzJy9fvsywsDCeOHFCri346NEjFi1alN27d+eKFStoYmLCZs2aySPkyvve+/fvWalSJQ4YMCDNCN3169fp4uKSbp9mhfRyny5evMhBgwbJHSeKFy/OLl26MDg4mCVKlGCpUqXS5MQp9vP9+/ezRIkS3LVrl8rt/yV13cRy5cpRXV2dAFRa8J07d45GRka0tbWVC5qXL1+edevWFe2fvuDjx4/s0aMHra2tVVoMKs+CJCcn8/Dhw1RTU2Pz5s1pZWXF3Llzs2LFiuzdu7d8HB0yZAiLFi3KFi1asFq1ajQ1Nc3QY2TqFobpSUpKop+fH52cnNiyZUuxyvUHiaDuN5LeyJvyCWD+/Pls3Lgxa9euzW7duqXbpia9HfS/DrwhISE0NDSkj48PHz9+nOZ5ISEhLF++vJwHprBz5065gG7fvn0JgGPGjJFrVu3bt4+6uroEwLNnzzImJoZTpkyho6OjSnmPv/76i/v27cvUOnTpXVHWq1ePhQsX5qRJk5gnTx42btyY7du35+DBg9mjRw96e3ur1GzLSGFhYezYsSOLFSuWbWu/ZVfBwcGsX78+NTQ0WK1aNY4cOZLv37+XR++mT59OW1tb3rx5k3/88Qc1NDTkHqxkyqKKhw8fMjExUf7OFftNpUqVmC9fPrZt25YfP35kTEyM/HuMiYlhz549aWBgoLKSNi4ujvXr12eDBg3S/Z0pd5AhmWZRgSLloEOHDirFqBs3biy3o0uvHMnLly9ZrFixNKVyvkS55IuibmJwcDAbNWpEXV1dlixZUmWVtqJuYvPmzXn8+HE+efLkl6w88LO9ePHis0XnFce5u3fvUktLi/ny5eOxY8d45MgRLly4kMbGxmzRooX8nLlz57Jbt27s0KFDhgRUf/31V7o16L60mvvdu3e8cuXKN5fnEdISQZ1AMiU/yNTUlIsWLeKqVatoampKJyenb6o99SWbNm2itrY2W7VqpdKOKiYmhvXq1WO1atVUTliXL1+mpaUlV6xYQTLlxKavr081NTV27dqVz58/p7+/P21sbNiqVSt5GunNmzccNGgQXVxc0l0xlxkHC+Xt3rJli0oplUaNGlGSJNasWZNdunRhr169OHDgQHbu3Jldu3bN1BNXeHh4tp3m/BVcv36d3bp1o7W1NS0tLTlkyBDevHmTly5dYqFCheQLBUUx3r59+6o8//Xr1yxTpozcezgqKoqtWrXi9OnT+fz5c06dOpUNGjSgs7OzPIp97949enh4sGLFiuzTpw8nT57M6tWr09bWNt0pKcW/Hz16xMmTJ7NKlSosXLgwW7VqxQ0bNsiPe//+PV1cXLho0SL5th49enDfvn188eLFZz+DgIAA5sqVS+5I8DXu3r0r103csWMHnz17RpJ0dHRk+fLlmTdvXrZt21auU/bvv/+mqZsopt3+2+dWlCuOKWPGjKGZmVmaC47AwEDmzZtXpQiy8nHxR45Jq1atooWFBadNmyZ3AiFTco0VU79fM3InfD8R1Am8desW7ezs5CXue/bsoYGBgZyHo/AjuS0JCQlcuXIltbS0WKBAAXp5ebFVq1asUqWKSg5FYmIik5OTuXfvXo4dO5ZkSh6QmZkZzc3NuWTJEqqpqXH48OH08/OjjY2NnNen2L7g4GC5tVFmU/5Mhg4dyqJFi3LSpEkqJ8pmzZrR1NRU7nqRmrgqzb4+fvzIt2/fcsiQIXR1daWmpibHjx/PvHnz0t7entHR0Z8N7J49e0YXFxf27t2bly5d4tixY1m+fHm+fv2ac+bMoYmJCceMGcO6detSV1dXHsG6c+cOp0yZwrJly7Jx48ZyeRtS9YSrOPnduHGDxYsXZ8uWLdmtWzdOmTKFRYoUYf78+Tlq1Cj58XXr1qWNjQ1PnDjBvn37slChQioj5+l59uwZq1evnm5Hh/QkJibKdRPd3d1pYWHBefPmccKECXKf43z58lGSJFapUoVv376lh4cHW7VqlaUrs39Vnwvsbty4QX19faqrq6u0GSRTftNdunRh06ZN0wRwP3KMP3XqFHPnzs0dO3akua979+6sXLmyPEgg8iQzjwjqBJ48eZKWlpYkUwI65QTt6Oho/vHHHxl29XT16lX26tWLNWrUYPv27Tljxgz5wKKcy/Hs2TNeu3aNnz59Yv369VmzZk06OzvTzc2NVlZWlCSJHTt2pLGxMXv06KFSZ+/OnTssW7bsN/Wh/FFLlixh3rx5eeHChXSneRWrjXfs2JFho5/Cz/Xq1SuuXbuWbm5u1NPTo5GRkbxy8HOB3YwZM1i2bFmam5vT0tKSly9f5oMHDzhgwAAeO3ZMftzYsWNpaGjIuXPnytO8X+rOotweTl9fn8OGDZO7BpApo2Vt27almZkZp02bRjJlStTV1ZWFChVi6dKlv3r/UJQ1+VrPnz+ns7MzNTQ0OGLECLnf74EDB+R6aOXKlZN7HtvZ2Yl94gcoB3azZ88mmTJDUKxYMTo6OtLa2jpNmsfEiRNZuXLlb/5uv8TPz4+VKlX67LnCzs5OZaSYFMFdZhBB3W8mvby6hw8f0svLi7NmzaK+vr5Kgvb58+fZtGnTb1799q3blJiYyKioKH769EnlZBYREcGKFSty69at3L17Nz08PJg/f37Onz+fwcHBPHToEDU1Ndm2bVtu27aN58+fZ926deno6PhThvEVK3TbtWsnj4p8rlink5MT69Wrl+nbJGQs5X3m9u3b7N+/P3fv3q2ySpBU7Yuq3G/z2rVrPHfuHJ89e8bAwEA5mEmdQzp27FgaGRlxwYIFaeqHpXfyS90eLvXFxIMHD1i3bl3a2trKK93j4+N59+5dvnnz5ns/jnQpb9+7d+9YrVo1enh4yHUT58yZw5YtW3L+/PkMDw/n1q1bmT9/fs6ePTtLei7nJElJSXLReRcXF+bLl08u2n7ixAlWrlyZDRo0kFfKRkREsFq1amzevHmGbseGDRsoSRIXLFjALVu2cNWqVdywYQMXL17MiRMn0sfHh82aNeOqVavo7+8vr7gVMpYI6n4jqaf5FAfR8PBwurq6UpIkTpgwQb4/NjaWnp6ebNKkSYYGSOkFlvv376eHhwednJxYqVIl/vXXX4yJieHjx4+ZK1cuTp06lbdv32br1q2prq7OatWqySeqv/76i+XKlWOhQoVYqlQp1qhR46cuiU9OTma1atXYpUuXNH9XXFycSrsbkS/y64qPj2elSpW+ui9q6hw7hX79+lGSJM6bNy/NYqTx48dTkqR0E82VKbeHW7hwoXx76jqQp0+fppqaWrpTYpkhIiKCsbGxtLS0ZLdu3dikSRMaGhrS0tKSVapUYZ48eTh9+vQ0dRNFCsL3UT6ezJ07l6VKlaKlpSUDAwPlbjRHjhyRe0k7OzuzSZMmdHV1lUeEM3K0bMWKFbS3t2f58uXZuXNnenl50c3NjfXq1ZPbQxYtWpTOzs7iO88kIqj7DaTOVZk9ezabNWtGHx8fuUTCw4cPaWFhwZo1a3LChAlcsWIFa9SoQTs7u0wPkPbu3UtdXV1OnTqVZ86cYePGjamrqyuf2JYtWyYXKtXW1qa5uTldXV1ZtWpVOZ/u9evXDA0NZXBwcKaunkt9AFQeqXNxceHz589VPqeHDx/S19dXbrlEisDuVzZr1qyv7osKQKWqv7JOnTpRT0+PW7ZsSVMTb+XKlV/121VuD6ec9K5ckigmJoampqZp8mMzw4IFC9i7d2+S5B9//ME8efIwd+7crFChAkuVKsUZM2awa9eutLOzy1Z1E3OCYcOG0dTUlJ07d2bNmjXp5OTEsWPHysfukydP0sHBgY6OjvTz85OflxnT3iNGjGDnzp3T3D548GB50UZmtB4TUoigLoebP38+JUmSW66MHz+epqam7NKli9xOa+PGjSRT8nDatGlDOzs7enh4sHPnzplaMyg5OVku16AYIXz27BmtrKyoo6PDFi1ayOU4Ll26RDc3N5YqVYqPHz/mgQMH6O7uzmrVqqWZBiMz52Ch/JqRkZGMi4uTc1IePHhAIyMjNmnShLdv32ZMTAzDw8NZr1491qxZUxy8coi//vqLBgYG/9kXNSkpSe6LunnzZk6cOJHz5s3jwYMH5ddq3749c+XKxc2bN6cJ7Miv2+c+lyivGAU5c+YMy5Urp7LiPLMsW7aMurq68v74/PlzPnjwQKVuooGBATU0NETdxAy0cuVKFilSRP5Mt2/fTjU1Ndra2nLEiBHy7+jIkSN0dXWlj49PprbgGjZsGEuVKqVy24cPH1i7dm1OnjxZvk0cEzOHCOpyuJCQEPbo0YP6+vr8559/OH78eP79998kU6ZXhw8fTg0NDbnsQnx8PGNiYlROMhkV0E2bNo2TJk1Sue39+/dy0vbbt2+ZP39+duvWjfv376e1tTWrVq3Ka9eusWnTprS1tVUJ4Pbs2cPatWvTxsbmi2UZMoLyAWjGjBmsVasWS5cuzUGDBsknzKtXr9LCwoK2trYsUqQIK1WqxPLly4vq6DnMkCFDvrov6pAhQ5g3b156eXmxePHiLFmypEqJiU6dOtHAwIBr1qz57qKvnwvsyJQ+tLVr187UHDrFv1++fEkPDw/Onj1b5bceHR3NHTt2sFChQtTS0lIZtRa+XUJCgsrxed68efJxVVHbc86cOezevTvz5cvHcePGySNyx48fZ9WqVenh4SGfBzKK4nfw7NkzFilShNWrV+fBgwcZEBBAT09P2tnZibzJn0AEdTnYhg0bOGHCBD558oStW7emtrY2ra2tVWpOxcfHc/jw4dTU1OSff/6Z5jUyMt9i1qxZlCSJc+fOVbm9SZMm7NatGy0tLdmzZ0/5gLVjxw7q6OjQ2NiYxYsXlwM35QPDli1b2L9//5+WnzFq1CjmyZOHa9eu5aJFi+jq6srKlSvLeXOvXr3ipk2bOGfOHG7cuFEkgedAX9sX9eDBgzQ3N5dTHF69esWFCxeyaNGiHDFihPx6Pj4+dHd3/6Ft+lx7OGNjY968efOHXvtLUucE9unTR2WUJikpiadPn2ajRo1Ys2ZNuTSKyKf6PocOHeLAgQPZpUsX+WLyzZs3fPHiBZ88eUJbW1u57/OdO3doamrKQoUKqaw6PXjwIGvXrv3VZWq+VWJiIo8cOUJHR0fq6enR3t6erVq1El1CfhIR1OVQ/v7+lCRJbg7+6tUr9u3bl5Ikcffu3SSpkns2atQoSpKkUmYhMyxatIiSJHH27NlyoLNgwQIWKFCArq6u8uOSk5M5cuRIFipUiBYWFvTx8VFpZ5TegSGjDxapT1h79uyhjY0NL1y4QDJlOkNHR4flypWjvb29fHvqQFgcxHKe9Pqips4T8vPzUykaTKYsJJgwYQJdXFz45MkT+faMGMVNrz1cRk+7Ko8QrVmzhjVq1ODff/8tjwTGxMSwZMmSKiOG0dHRvHHjhugU8YNWr17NAgUKcOzYsdy5c2ea+w8fPszixYvLRX/Pnj1LHx8fLl26NM3vKyYm5pvf/3t+o8HBwXz79m26bSeFzCGCuhxo/fr11NTU5P79+1Vuf/nyJdu3b089PT159ECxs8XHx3PZsmUZutMpDgLv379nWFiY3CZm8eLFlCSJs2bN4rt37/j+/Xt27tyZ5cqVY9OmTTl58mS2bt2ahoaGvHr1Kg8fPkxLS0u2b99eJbk6M6cz27VrR3d3d0ZFRcm3nTt3jgMGDCCZsrgjT5489Pf356FDh2hmZsZKlSplaq6KkPU+1xdV+QIgODiYJLl7924WK1YszYKAf//9l+rq6jx79qzK7RkV2GVWe7jDhw9z1qxZ8qj0smXL2LJlSxoZGdHb25sLFizghw8f2KNHD3bq1CndUX6RgvB9du7cSQMDgzSrrZUdO3aMpUqVop+fHx8/fsz69euzR48e8vegfHH5rTMwyo//888/uXjxYq5fv/6zj0/duk75NiFziaAuh1m7di0lSWKtWrXk25QDtfDwcLZp04a5cuVKE9il9/jvpdiB79y5Q29vb9apU4dDhw6V32vx4sUEQG1tbb569Yrv3r3jwoUL6enpSTc3N3bp0oVBQUHy4w8dOsTChQuzU6dOPyXp+/Tp08yTJw+bN2+u0m7szZs3jIuLY82aNeU8luTkZDo7O7Nw4cLs0KFDpm+bkPWU+6Ju2bKFU6ZMIUn279+fxYoVY2xsLG/evMkiRYpw4MCBcqssMmVRTdmyZTMttywz2sOtWbOGBQoUYM+ePVVK9JDk0aNHOW7cOBobG7Np06asW7euyiyB8GNiY2PZtGlTDhw48IuB0Zs3b9i2bVtaWlrSwsKCDg4O8ijxj6TRKD93xIgR1NfXZ+XKlammpsZWrVoxLCzsu19byHgiqMtBVqxYQTU1NXbp0oX58+dnv3795PuUA7XXr1+zbdu2NDAw4F9//ZXh26Hcvihv3rwcNmwYz5w5k2b5/KhRowiAefPmlU9CinIMygcvxUHl8OHD1NbWlk+gmUXxfufPn6eJiQmbNm2qEtg9fvyY+fPn55YtW0imjI40b96cO3bsEFejvxFFX9T+/ftTkiRWq1YtTQ7bli1bmDt3bnbt2pUbN27kxYsXWbt27Z9WHDsj/Pnnn3L5FeWR69RevnzJcePGsXnz5pQkia1atWJ0dLToGvCDXr16xXz58sldflJTHhX7+PEjL126xMOHD2dIPq/yd/fkyRO6ubnx6tWrjI6O5sWLF2lsbMzGjRtn+kI14euJoC6HUJQuUbSDWb58OfPmzfvFwK5evXo/nKD9Oc+fP6eNjQ0HDRqkcnvqE9n48eMJgKampvIVX3onO+VA62fmqJ07d04O7BQntIiICNapU4deXl7cuHEja9WqpVK25Fc5WQs/5sGDB3JfVEWOXb9+/dIEMbt27WLNmjVpYmJCW1tburm5/TIrosPDw1m9enWV2mZkSp7c+fPn051CTkpK4uzZs5kvXz4+evToJ25tzvTo0SPmz5+fGzZsIMl0V0lHRkayW7duDAkJUbn9e4+Vly5dSnfFv6+vr5xGQ5LXr1+nsbExvb29RWCXTYigLoc4efKkyurVd+/e0d/f/4uB3bt37zLtpLJr1y7a29vz/v37aU5yysVRt2zZwkaNGhEACxUqJLdHSr1dP2PxwbFjxzhv3jwOGTJEpZescmCnuH3Tpk2sVasWra2tWbt27V/mJC1kDEV+maLVV+/evTl06FBKksSpU6fKI7uK30NkZCQfPXqU6cWxM1p4eDhLly4t5w6S5NKlS+nr6yu3O6tatap8n/Lvv1KlSnILM+H7JSYm0sbGhh4eHiq3KTty5AibNm0q9yL+Ef369VNJ3yFTcvr09fVZuHBhOXhTnpExNTVltWrVGBER8cPvL/wYEdTlMMrBT1RUVLqBXeorvcwIRAYNGsRixYp9cRsHDBjAQoUKcfr06XRxcWGBAgVYokSJzwZ2mWnlypXMly8f3d3daWFhwZIlS6p8TufOnaOxsTF9fHzkFYDR0dF89uzZL3WSFn7cl/LLFCPmU6dOVZmqTF1s91cJ/sPDw1mwYEF26dKFx48fp4+PD+3s7NizZ08eOXKE27ZtY9GiRVVSIhR/W7Vq1VTaDgrfTvFZrlixglpaWuzRo0eax3z8+JFNmjT57OKU76E49j169Ej+9+HDh6mrq8vu3bvLNRoV73f58mXWrVv3l/ld52QiqMvhFIGdqampvHLzZ5g+fToLFSqkUrZBWXBwMPX19enj4yPfdvnyZTo4OLBkyZI/NbBbvnw5NTQ0uHPnTkZHR/P+/fssUKAAz58/r3KQ/Pfff9PNsftZ2ylkva/JL5s7dy7V1NQ4YcIEXrlyhQ0aNKCTkxPJjK37+LMcO3aMhoaGLFq0KMuVK8fjx4/LIzKRkZEsX748x48fr/KcCxcuUJIk0Qosg4SFhbFXr17U1tZmixYteOvWLYaEhPDgwYP08PBQKez7I78x5QvZgIAAamtr8+jRo/Jr7927l9ra2uzVq5d8cZv62CeOhVlLBHW/gaioKK5YsYKSJHHBggU/5T137txJSZK4atUqldsVB5y///6bmpqanDp1qnxfYmIiT506xVy5ctHJyemn5Gjs2rWLkiQxMDBQvi02NpYlSpRgz5496ebmxsWLF8u5QefOnaMkSWJa6Tf0X/llyuVs5s+fTxMTE5YuXZoVK1b87m4R2UV4eLhc/0xZZGQkq1atSn9//zT3iVWRGevZs2ecNGkS8+bNS319faqpqdHBwYENGjTItMK+VapUYeHChXns2DGVwE5XV5d9+/aVR+yE7EMEdb+Jt2/fcvfu3T91kUGbNm0+27R81KhR1NLSYs+ePdNsZ8WKFSlJEn19fTN1+z5+/MgePXrQ2tpaJdj19vamhYUFhw8fznr16lFTU5MjR46U/4agoCBRUPg39DX5ZS4uLvKFy9WrV3n27Nkc21VE0du4cuXKYn/IZMrFeyMjIxkYGCj3Fs7o9I+ZM2eyVatW8v/XrFmTBQoUUAns9u3bl253ICHrSSQJ4beSmJgIDQ2NTH+f4OBgDBs2DEePHkWnTp1QqVIlhIeH4/bt2wgMDISvry+CgoLQvn17dO/eHQAQFRWFLl26YPDgwXB0dISamlqmbmNYWBhmzpyJ8+fPo0WLFjhz5gwePHiAnTt3okiRIgCAdu3a4ciRI7h16xby5s0rP/dnfY5C9vD69WtUqFABdevWRcuWLbF06VLcu3cPVapUgbe3N6KiojB8+HC0b98e48aNU3luUlIS1NXVs2jLM1ZERARWrVqFM2fOIDw8HP/88w80NTVz1N/4Mz148AA6OjooWLAgkpOTv3jMIwlJktLc/l/P+xabNm3CpEmTsG7dOjg5OQEAPDw8cOfOHaxfvx7VqlWDhoYGzp49C0dHR3EMzG6yOKgUcrDk5GQ+e/aMo0ePlqcL1NTUaGVlxdmzZzMuLo7t27dnxYoV5Yr0il6qiqvPnzECoGivVKRIEZqYmMiFYhWtdPz9/VmpUqUML+gq/Hq+J78sp7l69Srr16/P/v37yyM3OW0U8mdZu3YtK1WqxICAAJU8XT8/P/k49LPzMG/fvk17e3suXLhQ5XYPDw9aWlpy//79Ksdl8d1nLyKoEzLduHHjaGJiwlWrVvHgwYOsXr068+fPz4iICL569YorV65k9erVWbVqVTZp0iRLyoO8fPmS/fr1Y8WKFTl79mz59oSEBNaqVYvNmzf/JZPchYz3PfllOY1yP08x9fp9tm7dSl1dXQYEBMi9c8mUGp+SJHHy5Mk/bVtS58ZNnz6dxsbGfPz4scrt5cqVY6NGjX7adgnfTky/Ct+F/z8N8PTpU0RGRsLIyAjGxsYwMDBQmQp4/PgxWrRogQkTJqBOnTo4ceIEGjRogMWLF6NTp04qrxkTE4NcuXIByJqpzZcvX2Lq1Km4cOECmjZtiiFDhqBhw4YICQnB9evXoaGh8dnpD+H39vr1a3Ts2BERERH4559/fptpSLE/fDuSiI2NRcuWLVGyZEnMnj1bvl3xWW7fvh3jxo3DgQMHYGVlpfLcjP68586di0ePHsHLywteXl4AgMjISDRp0gSenp4YOnQoEhMToaWlBSBjp3qFjCe+GeGbKQ4su3btQq1ateDr6wtvb2907NgRwcHBKju8pqYm3r59i/Lly2P37t1o1KgR5s6di06dOuHjx49Yt24dbt++DQByQEcyS/I0zM3NMXr0aFSuXBm7du2CmZkZ7t69i2vXrkFDQwOJiYniBCaoiIiIwIwZM9CxY0eEh4fj77//hrq6OpKSkrJ6034KsT98O0mSkCtXLiQlJeGvv/7Cu3fvEBUVhefPn+Pp06d48uQJ4uPjYWlpicePH+Ply5cIDQ2Vn/ujUo/jJCcn49mzZ2jdujU6d+6MAwcOwMTEBFWqVMHWrVuhpqYGLS0tJCQkAADU1NR+m9/3LymLRgiFX9zJkyepr6/PxYsXkyQXL15MABwwYIBKP9mHDx+yTJkyHDZsGI2NjblkyRL5vqtXr7Jhw4aZ0n/2R4SFhbFdu3b09PSUp4JF3oiQHpFfJnyP5ORkbt++nR4eHtTX12f58uVZpUoVWllZ0czMjA4ODpQkiYaGhtTX12eHDh0y5H2VU1qUe3EnJSXx2LFjrFKlCu3t7enl5cVjx45RW1ubs2bNypD3Fn4OMf0qfBP+/yjdyJEjERkZCX9/f4SFhcHOzg5JSUnQ1dWFuro63NzcsGHDBgDA1KlTMXbsWPTt2xcLFy4EkDLV2rx5cyQmJuLAgQPZbjj/7du3MDQ0hJqamljlKnzRu3fvYGhoCEmSxApQ4aspjqVeXl5o1aoVmjVrhrCwMCQlJUFDQwOenp7w9vaGh4cHqlSp8sPHIOVp0/nz5+Pq1au4d+8efHx8UL9+fdjY2CAqKgrBwcGYNGkSQkNDcffuXXTu3BkrV67MiD9Z+AnEmUr4Jorh/w8fPsDKygphYWEoXbo03r9/j3Xr1qFs2bIYPXo0Nm/ejDp16qBt27YYOHAgnj9/Dj8/PyQkJCAhIQEhISF4/fo1rly5AjU1tWyXp2FsbAwg5UAoAjrhS4yMjACknKRFQCd8i0+fPiEoKAivX7+GlpYWChcuDCAlv7dIkSKoU6cOqlatCuDH84wVx9cRI0Zg9erVmDRpEooVK4Y//vgDBw8exM6dO2FkZARnZ2ccPHgQBw8eRHBwMPr37//jf6jw02Sfs6iQbSkGc1+9eiXfZmhoiA0bNqBcuXJ49+4ddu/ejbZt26JUqVIAUupyPX/+HACgp6eHpUuXYuHChQgPD8f79+9RtWpVXL16FZqamkhMTMxWAZ2y7LpdQvYj8suEb0ES2traaNeuHf7880/s3LkTycnJuH//Prp06YI3b97AxcVFfnxGXFxeunQJgYGB2Lt3L3r27AknJyeEhISgXbt2MDIyUsm38/T0xODBg+V8YuHXIM5Ywhcppgj27t2LBg0aYMeOHQCA8ePHw8DAAO/fv4eVlRVCQkKQkJCAiRMn4vjx45AkCdevX8ewYcMwe/ZsREZGok+fPti+fTu2bNmCiRMnQkNDQ55qEARB+J0oLhgbNWoEKysrtG/fHqampvD29saHDx9w+vRpqKurIzk5OcPeMzY2FiTh5OSEHTt2wNfXF/Pnz0eHDh0QGxuL3bt3Izo6Os3zxDH61yFy6oT/tHfvXjRv3hyTJ09GrVq1ULZsWQDA5cuX4ePjg7dv3yI5ORmFChXCw4cPUahQIYwdOxbW1tYICAjAjRs3EBoaity5c2Pp0qVwd3fP4r9IEAQhc/Ebyo88efIEjx49wr1792BtbQ03Nzeoq6tneD7v33//jREjRqB3797o2bMnZsyYgZ49ewIATpw4gQ0bNmDkyJEoXrx4hr2n8HOJoE74onfv3qFBgwbw8PDA+PHj09z/8eNHTJkyBYcOHUJoaCiSkpJw69YtFChQAMD/knM3bNiAhw8fYtSoUeKqTxCEHE05R/j9+/fQ09MDkDLi9bX5w5m16KZSpUq4fPkyFi1ahD59+gBIOY77+PhAT08PW7ZsEWknvzAR1AlfFBYWBicnJyxfvhyenp5ITk6GJEmQJEnlSvTVq1eYNm0a/vnnH7Ro0QJDhgwBAMTHx8tFKxXECkFBEHIq5aBt9uzZOHnyJF69eoU6deqgU6dOsLa2ztSFYQcPHoSlpSXKlCmjcrviuHv37l00adIEenp66NmzJxISErB9+3aEhYXJNTmz28I14euJb034In19fejo6ODq1asAIK9UBYBz585h69atAAAzMzOMGDECzs7O2L59O2bOnAkA0NLSSlOoUgR0giDkVIpgaNSoUZg5cyYaNmwIX19fnDhxAl27dsWdO3dUjqMZKTExEePGjUPt2rXlou4KiuNuyZIlsW/fPpiammLhwoXYsGEDChUqhKtXr8p5ziKg+3WJkTpBphh5S05OlsszxMXFoUePHggJCcHYsWNRp04d+fGDBw/GlStXEBgYiNy5cwNIWYo/bdo0XL58GTVq1MCUKVOy6s8RBEHIEjt37sSYMWOwfv16ODg44PDhw2jUqBGKFSsGAwMDrFu3DiVKlMiUEbF3796hSZMmePLkCQIDA1G6dGn5vtR5fh8+fJA7XABZ055RyFgiHBcA/G9nP3ToELp06YLmzZvj6NGj0NXVxcSJE5GUlISpU6dixIgR2LBhA7p06YJVq1Zh4cKFckAHpLTaGjVqFKytrREeHp6mJY0gCEJOZ2Jigjp16sDBwQF79+5F69atsWDBAkyePBn3799Ht27dcPPmzUwZETMyMsKuXbuQP39+NGzYEMHBwfJ9ioDu2bNn6NatG6KiorK8PaOQscRInSA7cuQImjRpAi8vL0RGRuLkyZOYMWMGhgwZgqdPn2Lu3Lk4efIkEhISUKBAAcyZM0deCZtaZGQkjIyMoKamJpp+C4KQY33u+Pb69Wvo6enBy8sLtWvXxujRo5GQkAAnJye8evUKnp6emdqpISoqCg0aNMCLFy+wZ88eOcfu1atXaN68OYKDg/HixQsRyOUwIqgTAKQEYWvXroWuri569eoFAFiwYAEGDRqEGTNmYNiwYfJj3759Cx0dHejq6v7n64qEW0EQcirl41tERATi4+ORP39++f579+6hevXqWLlyJerVq4fnz59j8ODBaN68ORo1apTpx0ZFYBcWFoa9e/fKdfDevHmDa9euQVNTUyxcy2FEiC7gzp07sLW1hZWVFSZMmCDfPmDAAADAoEGDoKGhge7duyNXrlxyC62vIQI6QRByKsXxbcyYMQgMDMTTp0/h7u4Ob29vtG7dGubm5ihWrBjWrFmDpKQkLFmyBADkgO5HLnq/ZgbE0NAQe/fuRcOGDeHl5QUDAwMkJCTIAZ3Ioct5xBn3N6YYpC1VqhSGDBmChw8f4unTpyr3DRgwAAsXLsSQIUOwbt26rNpUQRCEbEN55eqSJUuwatUq9OvXD8uWLUNUVBSWLVuGefPmwcDAAF26dEF4eDj69euHxMRE7Nu3L0P6XSsCurVr12Lbtm1ptkvB0NAQgYGBMDc3R1xcnAjocjgx/fob+twV3pAhQ7Bo0SJs2LABzZo1U7lv+fLlcHNzg42Nzc/aTEEQhGztn3/+wd9//438+fOjXbt2AFJy6SZOnIgLFy5g2bJlqFixIiIjIxEVFYXChQtDTU0tQwIqkkhMTESlSpVga2uLDRs2fPHx0dHRyJUrV4a9v5A9iaDuN6MI6M6cOYNTp07h7du3sLW1RYcOHQAAAwcOxNKlSxEQEJAmsBMEQRBS3LlzRy4XMmvWLAwZMkQ+vr5//x4VKlSAr68vZsyYofK8jMozVrzOsWPH0KlTJ6xbtw41a9b86ucJOZP4Zn8zkiRh586d8PLyQkhICJ48eYI5c+agfv36AID58+ejb9++6NSpEwICArJ4awVBELKH1OMfpUqVQmBgIAwMDPDvv//i3bt38n0GBgaoWrUqnjx5kuZ5P5JDl97rlCxZEtbW1jh79iwApCn2npoI6HI28e3+BpR38ocPH2L48OGYOXMm1qxZg6lTpyIsLAxFihSRHzNnzhy0atUKQ4cORXR0dFZssiAIQrahaI8IpBToVahfvz5Wr16NvXv3YuzYsXj58iWAlF6q169fh6mpaYaVc1K8zqpVq7B8+XLEx8cDAAoVKoQGDRpgzpw5ePbsmVjJ+psT0685WEBAAJydnVGsWDF52fq5c+fQuXNnBAUF4fHjx6hatSq8vLywfPlyAMDp06dRrVo1ACn1jMzMzLLyTxAEQchSyjnI8+bNw/Xr1xEVFYWmTZuiRo0ayJ8/P7Zt24Y2bdrAxsYGpUqVwsePH/Ho0SNcunQJmpqaGbYtz549w8SJE7F+/XrUqlULdnZ2mDBhAmJiYtCxY0c4Oztj2LBhcn9u4fcjRupyqPv372PRokVo164dQkND5as3PT095M+fH+fOnUPVqlXh6ekpL7O/fv06Nm/ejKCgIAAQAZ0gCL815RG6yZMnY8KECTA2Nsbbt28xZ84c9OjRA48ePULTpk2xZcsWPHz4EHfu3EH//v1x5coVaGpqIiEh4YfeX1nBggWxcuVKBAcHo3z58jh8+DDKlCmDhQsX4tWrVzh//jzU1NQgSZLo5vObEkFdDlW8eHGMHj0auXLlQtu2bfHw4UMAKe1rHjx4ABcXF9StWxf+/v5ywPfHH38gODhYBHOCIAj4X/5ZaGgorl+/jj179mDBggU4deoUhg4dio8fP2LUqFF4+/YtGjdujA0bNiA4OBj79++Huro6kpKSvnukjqT8/ps3b8bUqVOxe/duPHv2DNbW1hg/fjyuXLmCjh074tWrV7hy5Qr27NmDpUuXAoAYqftdUchxEhMT5X9v376d9evXZ40aNRgaGkqS/Oeff6irq8sOHTrw5MmTPH/+PAcOHEhDQ0PeuHEjqzZbEAQh2/H396ehoSFtbGx4/fp1+fbk5GT6+/uzZMmSvH37tnz7jh07qKenx27dujE+Pv673jM5OVn+99ChQ2lqasoyZcqwRIkS9PX1VXk/kvz48SNPnTrFmjVrskWLFmleQ/h9iKAuB1LszEePHmWHDh3o4OBASZJYvXp13r9/nyS5b98+FilShAULFqSNjQ0rV67Mq1evZuFWC4IgZD+JiYl0dnamJElct26dykVzfHw8jYyMuGTJEpXnbNq0ifny5eOrV69+6L1v3LhBX19fXr58mcnJyQwICKCHhwfr1KnDu3fvkkw53iclJZEkT58+TXV1dV68ePGH3lf4dYmFEjnUiRMn4OHhgfnz58POzg7//PMPAgMDoauri3Xr1qFo0aJ49eoVIiMjoaWlhTx58sDIyCirN1sQBCHLfK6GW1JSEipXrox3795hzZo18mKyiIgIVK1aFePHj0eLFi1UnhMdHY3cuXN/97Zs3rwZy5YtQ+7cubF9+3bo6OgAALZt2wZ/f39oampi4cKFKFGiBJKSkuQ8OmdnZ4wfPx716tX77vcWfl0iqMthmDL6isGDB+P58+fYunWrfN/27dsxdepUGBsbY926dbC0tMzCLRUEQcg+lAO6GzduICYmBkWKFEG+fPmgpqaGpKQkVKhQAW/evEGrVq1QqlQp7N69GyEhIbh+/XqGd2iYMWMGAgICEB0djWvXrsHExES+b9u2bVi1ahUiIyOxc+dOFCpUCEBKndHBgwfj4cOHsLKyytDtEX4NYqFEDiNJknxgevjwocrKK19fX3h5eeHkyZNo3LgxQkNDs2grBUEQsg8qLUoYM2YMGjZsiBYtWqB06dJYsmSJXEHg6tWrKFSoEObMmYNTp07B3t4eQUFB0NDQ+M+iv1+SXs/WESNGoH///tDX10e/fv3w4sUL+b6mTZuidevWcHV1RYECBeTbGzVqhGvXromA7jcmgrocqkKFCvj48SNOnDghF6kEgEqVKsHR0RFlypTJwq0TBEHIPhQrRadOnYq1a9di5cqVePz4Mby8vDB58mSsW7cOjx8/hpqaGv755x84ODggKCgIXl5e8mt8T9Hf5ORkJCUlyQHllStXcO3aNVy6dAkA0K1bN/Tp0wePHj3CqFGjEBYWJj+3Xbt2WLBggTyKmJSUhKJFi6Js2bI/8lEIvzgR1P3iFLPnwcHB+Oeff7B//36QRJs2bZA/f34MHz4cx44dQ2xsLADg3LlzqFChAvz8/MTVnCAIv7UnT57IF73379/HqVOn4Ofnh1q1amHfvn3Yt28fnJycMHv2bKxevRqPHj2Cmpoa/v33XyQmJqJr1644c+bMd9eEe/DggRwMjhgxAk2bNoWXlxfq1KmDbt26ITo6Gr169ULLli3x4MEDjB49Gs+ePUvzOurq6qKThJAiixZoCBlAscp1x44dLFCgAF1cXGhiYsJatWrx6NGjTExMZI0aNVi2bFmWKFGCHh4e1NHR4a1bt7J4ywVBELLWxo0bWaFCBXmF6uvXr7l161bGxsbyzJkztLCwoJ+fH0myVatWNDc356BBg/js2TOSZFJSEi0tLenk5MS4uLhvfn8/Pz9KksTIyEjOmzePefLk4ZkzZ3j+/HkGBgbS0NCQjRs3lh+/aNEilihRglOmTMmAv17IqURQ94s7e/YsTUxMuGrVKpLkmTNnKEkSFy1aRDJlOf6uXbs4btw4TpgwIU19I0EQhN/NihUrKEkSJUni0aNH5dujoqJIkj169GC7du3kOnN9+vShra0tfXx8VEqIJCUlMSQk5Jvf39/fnzo6Oty6dStJsnXr1hw4cKDKY27cuEFtbW2OGzdOvm379u0qJVUEIbWMXa4j/HSXL1+Gq6srOnfujPv376N9+/bo0qUL+vbtC5KIi4tD48aN0bhx46zeVEEQhCy3YsUK9O7dG6tWrcLs2bPx/v17+T4DAwMAwOvXr2FoaIiEhARoamri5cuXWLZsGVxdXeX8u8TERGhoaKBo0aLf9P6bN29Gjx49sHHjRjRt2hRxcXG4e/euXLIEAOLj42FnZ4dRo0bh4MGDGDBgAIyNjeHj4wMAci9vQUhN5NT9ohSrpZ4/f47ChQsDAGrUqAF3d3f4+/sDAHbs2IGNGzfKOSMU1WsEQfiNrVixAr169cLmzZvRqVMn6Ovr482bNwBUj49ly5bFjh070KZNG1SoUAFBQUFwcnKCJElyP9jvKWHi7++PVq1awdjYGJqamnj//j10dXXRtm1bHD58GMeOHQMAaGlpAQB0dXWhrq6ept6dCOiEzxFB3S9KsVrKxcUFa9euhYGBAZo2bYrly5fLV5JHjx7FP//8g8TERACiF6AgCL8vf39/9OjRAzt27JBHvPT09HD16lX5MYrAbty4cRg+fDjy5s0LZ2dn3LhxQy5bkl5x4q+xdOlS9OvXD4GBgfD29sbYsWOxY8cOxMXFwcvLC5UrV8a0adNw+PBhAMC7d+9w4sQJWFpaiiBO+Gpi+vUXQRKSJOHOnTt4+vQpJElCuXLl0KBBA7Rv3x7btm2Du7s7JEnCmzdvMG/ePOzatQunTp2Cnp5eVm++IAhClrl37x5WrlyJnTt3olGjRvL0pYWFBd6+fQsg7UXviBEjVG5TTLd+jzNnzmDkyJEICAhA/fr1Ub9+fbRu3RozZ86Empoa2rdvj6FDh2LhwoVo0qQJChcuLI8GBgYGyt0ixIW58F9ER4lfgGJn3rFjB4YNGwZdXV0YGhri6dOnOHbsGBISEjBnzhxs2LABpUqVgq6uLsLDw7Fr1y7Y29tn9eYLgiBkuadPn8qdFxQmT56MY8eO4dSpU4iPj5enPbt27Qo3Nze0adMmQ977zp07iI+PR9myZeU8PQBo06YNLly4gNGjR6Ndu3aIjo7G1atXcfnyZZiZmaFFixZQV1f/oYBS+L2IoO4XcfbsWXh6emL27Nno1q0b/vrrL7i7u2Pq1KkYOXIkoqKicPHiRVy7dg1FixaFg4ODaAMmCMJv73P9XAFg4cKFWLhwIR48eCA/xsvLC7du3cLDhw8zLZBSDtIUgd2oUaPg4+OTJn9OLIoQvoUI6n4RS5cuxcWLF7F27Vo8efIEVapUQcOGDeHn5wcAeP/+vbxySxAEQfg8xezH5s2bMXz4cDx+/BhASkD38OFD3Lx5E5qampkaUCm/dtu2bXHlyhX07NkTnTt3hq6ubqa8p5DziYUS2RSVOkVER0cjMjISHz58QGhoKKpUqQJPT08sXrwYABAYGIh58+bh06dPWbnJgiAIvwRFblqRIkWQkJCAR48ewcvLCyEhIXJAl5iYmKkjZOrq6nK/2ICAAFhZWeHs2bMqpU0E4VuJoC6bkiQJgYGBqF+/Pm7evIlSpUrh5cuXcHZ2Ru3ateWyJcnJyThy5AhevHjxQw2lBUEQcgLlyafo6OgvPjZXrlyIi4uDh4cHQkJCcOvWLTmg+xk5bMqB3f79+7FhwwZ5UYQgfA8R1GUzip357du32LhxIwYMGAAXFxc0bNgQ+vr6iI6Ohq+vLz59+oSoqCiMGTMG27Ztw8CBA8UqV0EQfmvKK0QnT56M1atXf/Hx5ubm0NLSQoECBX56QKegrq4u1x1VU1OT6+AJwvcQQV0WS31FJkkSTpw4gQYNGuD169dwdXUFkFKMcseOHbCxscGQIUNgZWUFX19fBAQE4NChQ7CxscmKzRcEQchyc+bMQXBwMCRJkke+jh49CisrKwCfL7yeN29eTJ8+HSdOnMiSgE5BeSHH99bBEwRA1KnLUopVWa9fv8bjx4+hpqaGChUqoEyZMggJCcGrV6/w8OFDVKxYESShp6eHM2fO4MSJE7h9+zaKFy+OcuXKiVWugiD8tk6ePIl169bh4sWLmDJlCooXL464uDg8f/5cDubSG/lSHH87deoEIGXhgigbIvzqxOrXLKI4oAQHB6Nbt27InTs39PT0sHHjRujo6ODNmzdwcHBA3rx5sXbtWtja2mb1JguCIGRL69evx7p165AnTx5MnToVJUqUQOnSpbF48WK4u7sjPj4empqa8kheRi6AUC6ZkrpAsChHIvxsYpw3C5CEmpoagoKC4OrqCjc3N/j7+2Pbtm3Q0dFBYmIi8uTJg/PnzyMsLAy9evVCcHCwyvMFQRB+d4pctHbt2qF9+/Z4/fo1Ro8ejaCgIJQqVQr6+voAUkbqFMFWREREhr6/IqBbsWIFevfujc6dO2PNmjX49OmTvBBCsZ3KxHFcyAxipC6LREZGolGjRqhQoQIWLlwo36640lPkdrx69QoVK1ZEiRIlsGDBApQtWzYLt1oQBCF7UBwrlUfD1q5di4CAAAAp07IlS5aEJElQU1ODJEmIjY2Fl5eXXA4qowwbNgyrV69GixYtcP36dXz48AFmZmbYvXs3dHV15W2dPn06jI2N0aNHjwx9f0FQEEFdFgkODkbDhg2xZs0aVKlSJU1yrHIuyMuXL2FlZQV3d3fs2rVLbmUjCILwO1IeIYuJiYEkSfLq/1WrVmHDhg2IjIxE06ZN4eLigtjYWMTGxuLjx49o3br1D+fOKU+znjt3Di1atMD69etRrVo1AMDu3bsxc+ZMWFhYYMuWLdDU1ERYWBjatWsHMzMzbNiwQfRyFTKFyArNIteuXcPjx49RtWpVSJKUppWN4qry+vXrcHZ2xpMnTxAVFSUCOkEQfnuKY+W0adNw4MABGBgYwMPDA4MGDUKXLl0AAFu2bEFQUBDatGmDIkWKqDz/e3PdvLy8MGPGDJUZk9evXyM2NhbFihWTb/P09ERUVBTmz5+Pu3fvwtbWFhYWFhg9ejS8vb3x+PFjFC5c+Hv+dEH4IpFTl0WsrKygoaGBnTt3Akh/GfuaNWswfvx4xMbGIl++fChevPjP3kxBEIRsQzk3bf78+Zg3bx7c3d1hamqKKVOmoH///gCALl26oEWLFggPD0eXLl3w9OlTldf5noDu8ePHKFu2LEqVKqVye8GCBWFiYoKrV6/Kt2lra6Nu3bp48OABbty4Id9evXp1bNu2TQR0QqYRI3VZpHDhwjAwMMD69evh4OAg7+TKQ/KhoaGoWLGi6AMoCIKA/138njt3Dnp6eggICICnpyeio6NRvXp19OjRAySxaNEidO7cGTExMbh37x4KFCjww+9duHBhzJgxAwAwb948ODg4oFq1arC0tIShoSGWLFmCQoUKyaN4kiShRIkSMDIyAvC/Y7uHhwcApJmdEYSMIHLqstDOnTvRqlUrNGvWDCNGjEDp0qUBALGxsZgyZQo2bdqEI0eOoESJElm8pYIgCNnD2bNnUaVKFRgYGGDXrl2oUaMGACAuLg6bN29Gr1690L17dyxYsADA/4KpHwmilIsSf/jwAT4+Prhw4QL27dsHV1dX3L9/Hx4eHihWrBiqV68OW1tbLFu2DK9fv8alS5dEWRPhpxFBXRZKTk7GypUr0adPHxQrVgzOzs7Q0dHB8+fPce7cORw6dAj29vZZvZmCIAjZRlhYGP744w9MmzYNgwYNwoQJE+T74uLisHXrVnTs2BHz5s3DgAEDAKStH/ctlIPBAwcOwMPDAy9evMCYMWNw+PBh7Ny5E1WrVkVISAjGjx+P69evQ1NTEwULFsSOHTugqakp6tUJP40I6rKBCxcuYPbs2Xjw4AFy584NFxcXdO7cWeTQCYLwW/vc6FpYWBjWrl2LKVOmYMKECRg2bJh8X2xsLE6dOoVatWr98CpX5fefNGkSJkyYgOXLl6Nbt264desWpk2bhqNHj8qBXVxcHJKSkhATE4N8+fKplKcShJ9B/NKyAUdHR2zevFlcyQmCIPw/5YDq8OHDePfuHQCgefPmsLCwQKdOnSBJEqZOnQpJkjB06FAAgJ6eHjw9PQHghwIq5dG1/v37Y/369ShWrBhCQkIAALa2thg3bhwAwNfXF7t27YKLiwsAyEWPk5OTRUAn/FTi15ZNKF+NivpFgiD8zhRddwBg5MiR2Lp1K7S1taGlpYWlS5fiyJEjMDc3R8eOHeWivtHR0Zg0aZLK6/xIQKUI6AYMGICAgABcunQJ69atQ2hoqPyYUqVKYezYsVBTU0OVKlVw8+ZNlClTRr5fLIQQfjYR1GUTykGcCOgEQfidKY6Bc+bMwbp167Bnzx44Ojpi0aJFGDBgAKpWrYrjx4/D3NwcHTp0wPv373Hu3LkMuSBWHiHcsmULFi1ahGvXrsHa2hrq6up49OgRAODTp0/Q1taGjY0NJk6ciCJFiqQpdyIIP5u4jBAEQRCyBeU6dBEREbh48SKWLl0KR0dH7N+/H2PHjsXo0aMRFRWF2rVrIzo6Gubm5hgyZAgOHz4MSZJ+qKeqckB3//591KlTB0+ePJHLlJiYmCA2NhZASi06kli+fDksLS0xefJkuderIGQVEdQJgiAIWU55ynXXrl0wMTFB69at4eTkhEuXLqFXr16YOXMmJk+ejA4dOuD8+fMoW7YsYmNjYWJiIgd0GbHKdfz48WjUqBE+fPiAggULIjExEQBQvHhxfPz4Ud5eT09PLF++XCUfWuRGC1lJTL8KgiAIWUo5GJs+fToWL16M0qVLo2HDhgCAP//8E/b29mjTpg0AwNzcHO3atYO2tja0tbXl1/negE55UcTAgQOxbNkyACmVCQoWLCjn5unp6SEsLAyhoaHo378/Hj58iKCgIKipqYliwkK2IH6BgiAIQpZRDuguX76MoKAgrF+/HiVLlpQf8/DhQ9y4cQP6+vqIjY1FYGAgSpQoAX9//wyZ8lReFLF+/XqcOnUKTk5OiIyMVHmcqakp9PX1UbduXdy9exdBQUHQ1NREYmKiCOiEbEGM1AmCIAhZws/PDxEREZgwYQI2bdqERYsWISYmBsWKFQPwvxG0rl27Ys+ePShYsKDcdmvbtm3y62TElOf8+fOxfPlynDt3DuXLl4eJiQnCw8MBAAkJCXJBYUNDQ2hoaODixYtyQCfKlgjZhbi0EARBEH66lStXol+/frC1tQWQkq+mo6ODe/fu4ciRIwD+F6yVKVMGBw8eRNeuXdGxY0dcu3YNGhoaGbYogSTy58+Pmzdvonz58gAALS0t3L59GwCgqakJAAgODsbixYtx5coVEdAJ2ZLoKCEIgiD8VP7+/ujTpw+2bt0Kb29v+fYnT56gY8eOSEpKwsCBA9GoUaPPvsaPtN76Uv6bolRJ//79ERoaij179gAA3NzcULhwYfzxxx8/3EtWEDKL+EUKgiAIP83u3bvRs2dP7Ny5UyWgGzFiBBITE7FgwQKoq6tj+fLlCAwMlO9PPSqXEQHdzp07MX/+fPj7++PKlSsAIC+8KFKkCCIiIkASdevWRVhYGFavXi3n/4mATsiOxK9SEARB+Ck+ffqEw4cPo2jRonIRXwBo3LgxDh48CB0dHdjZ2WHevHlISEjAihUrsHXrVgAZVypEEYwNHToU3bt3x969ezFmzBh069ZNpSOFgYEBIiIiUKtWLYSEhKgsihCE7EokAwiCIAg/hba2NsaNGwdtbW38+eefIIkzZ87g8ePH2LlzJ/Lnzw+SKFeuHObOnYt27drh/PnzaNasWYZux549e7Bx40bs27cPlStXxqtXr7Bo0SLs3bsXOjo6GDZsGAoWLIj79+/D2NgYwcHBIodO+CWInDpBEAThp3r58iWmTp2K/fv3IyoqCjdu3ECBAgXkPDlFmZMHDx6gaNGiPzTVqVwyRfHvefPmYdOmTTh37pwcpIWFhWHixIl48OABjh49ik+fPmHhwoUYPHgwNDQ0REAn/BLE9KsgCILwU5mbm2PMmDFo0KABihQpgj///BNAyhRrcnKyHIQVK1YMampqP7TKNT4+HoBqcGdsbIz4+HiEhYXJ91lYWKB9+/Y4ceIELly4AB0dHQwfPlwEdMIvRQR1giAIwk9nZmaGkSNHwtnZGdu3b8fMmTMBpOS8pZ5A+t58ut27d6NLly5o1KgRli1bJvdtrVixIh4+fAh/f398/PhRDvZy5coFOzs7GBgYqLyOCOiEX4UI6gRBEIQsYW5ujtGjR8PR0RGBgYEYM2YMgO9v96VsxYoVaNu2LczNzREbG4vVq1fjxIkTAICyZcvC398f06ZNw/Dhw3Hw4EHcunULw4YNQ65cuVS6WQjCr0RcfgiCIAhZxtzcHKNGjcKwYcMQHh6uMk36vVatWoXevXtj27ZtaNy4MQCgfPnyeP78OeLi4kASrVu3hpaWFsaOHYutW7fCyMgIpqamOHXqlOjlKvyyxEIJQRAEIctFRkbCyMhInn793sDu4MGDqFevHjZs2IBWrVrJtzs5OUFNTQ2RkZHInTs31q9fDxsbGzx9+hRxcXGIiYlBuXLloKamJnLohF+WuAwRBEEQspyJiYk8QvYjI3X58uWDvr4+Dhw4IC+S8PX1RVhYGPr374/u3bsjOTkZderUQUREBAoVKoQSJUrA3t5efn8R0Am/KvHLFQRBELKNH53yrFixIk6cOIE6deqgQ4cOiIuLQ0hICE6dOgUrKysAgIWFBTp06IDr16/D3d09Q99fELKSCOoEQRCEHMXBwQGHDh2Cr68vnj59iuvXr8PKykqug2dlZQUrKysYGRll9aYKQoYSOXWCIAhCjnTlyhXUrVsX1atXh7+/P4yNjUES9evXR2JiIg4ePChG5oQcRQR1giAIwi8p9YKK9BZYXLx4EZ6ennB3d4e/vz9at26NkJAQ3Lx5E5qammKVq5CjiKBOEARB+KWFhITA2tr6s/dfvHgR9evXx+vXr1G6dGlcvXpV9HIVciRxeSIIgiD8sv744w8MHjwYANJ0olCoVKkS9uzZg2bNmomATsjRxEidIAiC8Mvau3cvGjVqhH/++QfOzs5f9RwR0Ak5lQjqBEEQhF+CIv9N+bQlSRLatGkDXV1dLFq0CDo6OhnSZkwQfkVi+lUQBEH4JSgWNERHR0OSJDl4q1ixIo4dO4a4uDhIkvTZaVhByOlEUCcIgiBka8nJyfK/d+/eDRsbG6xfvx537twBAAwcOBAmJiYYPnw4AIiROuG3JaZfBUEQhF/ChAkT5CnYgIAA5MuXD05OThg4cCC2bt2KixcvYu7cuShYsOAP9Y8VhF+VCOoEQRCEbEk5MPvzzz8xYMAAbNu2DdWqVcONGzdw7do1TJo0CUWLFkVkZCSuXLmC1atXo2PHjlm85YKQNURQJwiCIGRrhw4dwoEDB2BnZ4euXbuq3Pfx40fs2LEDZ8+exYoVK1ChQgVs374dhQoVyqKtFYSsI3LqBEEQhGxFOYfu5MmTGD9+PAICAqCtrQ0ASEpKkv+ro6OD1q1bY8mSJdi0aRPCw8Px5MmTLNluQchqYqROEARByJbmzJkDCwsLPHv2DCtWrED+/Pmxfft2mJmZqbT3Up6mrVevHoyNjREQECBy6oTfjhipEwRBELIF5RG6zZs3Y8KECXBwcMCwYcMwaNAgfPr0CaNHj8br16+hpqYmP16SJPnfWlpaMDAwUHktQfhdiJE6QRAEIVvZvXs3njx5AjU1NfTp00e+ff78+di+fTtKly6NadOmwdTUVB6lS05Oxv3792FjY4PLly/D3t4+C/8CQcgaIqgTBEEQso2IiAhYWVkhNjYWw4YNw4wZM1TuX7BgAXbu3Il8+fJh1apVMDIyUrn/7du3MDY2/olbLAjZh5h+FQRBELJM6nGFvHnz4sKFC7CxscHx48fx9OlTlccNGDAAtWrVQt68eWFgYJDmdVIHeYLwOxEjdYIgCEKWSEpKgrq6OgDgzZs30NDQgCRJMDAwwK1bt1C7dm2ULVsWGzduRJ48eVQWRChPuyoWTAjC707sCYIgCMJP9+HDBzmgmzp1Klq2bIkKFSqgZ8+e2L17N2xtbXH06FHcvHkTbdu2xZs3b1T6uir+LQI6QfgfMVInCIIg/FQBAQF4+PAhxo8fjzFjxmD58uVYuXIltLS0MHfuXFy7dg03btxAwYIFERQUBE9PT5ibm+Po0aMwNDTM6s0XhGxLXOIIgiAIP42/vz/at28PR0dHhIeH4/jx49i6dSu8vb2hoaGBy5cvY+bMmShYsCASEhJQpkwZBAYGwsLCArlz587qzReEbE2M1AmCIAg/RUBAADp37ozdu3fDy8sL9+/fh5ubG65evYoLFy6gVatWmD17Nnr06IG4uDisX78etWvXRpEiReTXEDl0gvB5Ys8QBEEQMt26devQvn17VK9eHV5eXgAAbW1t2NjYYPny5Wjbtq0c0AHAvXv3cPToUXn1q4II6ATh88TeIQiCIGSqlStXonPnzujcuTOCgoLQr18/AIClpSWKFCmCiRMnolu3bnJAFxMTg1GjRiEmJgZVqlTJyk0XhF+KRlZvgCAIgpBzLViwAIMGDcL+/fvh6ekJf39/jBkzBsnJyfDz88OqVasQERGBtWvXIi4uDpqamrh69SoiIiJw5coVuR2YGKEThP8mcuoEQRCETHPq1CmEhYWhRYsWAICoqChs2bIFo0ePRvPmzeHn5wcAGD16NO7du4fExESULl0aEydOhIaGBhITE6GhIcYfBOFriKBOEARByHTKhYPfv3+PzZs3pwnsPn36BG1tbfk5ysWJBUH4b+LyRxAEQch0ioAOAAwMDOSRuzFjxkBdXR0LFy5UCegAiIBOEL6RCOoEQRCEn04R2EmShO7du6No0aLo379/Vm+WIPzSxPSrIAiCkGXevXuHU6dOoX79+mJkThB+kAjqBEEQhGxBLIoQhB8jgjpBEARBEIQcQBT+EQRBEARByAFEUCcIgiAIgpADiKBOEARBEAQhBxBBnSAIgiAIQg4ggjpBEARBEIQcQAR1giAIgiAIOYAI6gRBEARBEHIAEdQJgiAIgiDkACKoEwTht2FlZYUFCxZk9WYIgiBkChHUCYKQ46xbtw5GRkZpbr948SK6dev2Va8hAkBBEH41osmeIAg5SkJCwmfvMzU1/YlbIgiC8HOJkTpBELK1Q4cOoUqVKjAyMkKePHlQv359hISEAABCQ0MhSRK2bNkCNzc36OjoYOPGjejYsSOioqIgSRIkScKECRMAqI6+kcSECRNgaWkJbW1t5M+fH/369QMAVK9eHY8fP8bAgQPl1xAEQcjuRFAnCEK2FhMTg0GDBuHSpUs4fvw41NTU4O3tjeTkZPkxI0aMQP/+/XH79m3UqFEDCxYsgIGBAcLCwhAWFoYhQ4aked0dO3Zg/vz58Pf3x/3797F7927Y2dkBAHbu3ImCBQti0qRJ8msIgiBkd2L6VRCEbM3Hx0fl/9esWQNTU1MEBwdDX18fADBgwAA0adJEfoyhoSEkSYK5uflnX/fJkycwNzeHh4cHNDU1YWlpCUdHRwCAiYkJ1NXVkTt37i++hiAIQnYiRuoEQcjW7t+/j5YtW6Jo0aIwMDCAlZUVgJSgTMHBweGbX7dp06aIi4tD0aJF0bVrV+zatQuJiYkZtdmCIAg/nQjqBEHI1ho0aIDIyEisXLkS58+fx/nz5wEA8fHx8mNy5cr1za9bqFAh3L17F0uXLoWuri569eqFatWqfXGhhSAIQnYmgjpBELKtN2/e4O7duxgzZgzc3d1hY2ODt2/f/ufztLS0kJSU9J+P09XVRYMGDbBo0SKcPHkS//77L27evPlNryEIgpBdiJw6QRCyLWNjY+TJkwcrVqyAhYUFnjx5ghEjRvzn86ysrPDhwwccP34c5cqVg56eHvT09FQes27dOiQlJaFy5crQ09PDhg0boKuri8KFC8uvcfr0abRo0QLa2trImzdvpvyNgiAIGUWM1AmCkG2pqalh8+bNuHz5MmxtbTFw4EDMnj37P5/n4uKCHj16oHnz5jA1NcWsWbPSPMbIyAgrV66Eq6srypYti2PHjmHv3r3IkycPAGDSpEkIDQ2FtbW1qG8nCMIvQSLJrN4IQRAEQRAE4ceIkTpBEARBEIQcQAR1giAIgiAIOYAI6gRBEARBEHIAEdQJgiAIgiDkACKoEwRBEARByAFEUCcIgiAIgpADiKBOEARBEAQhBxBBnSAIgiAIQg4ggjpBEARBEIQcQAR1giAIgiAIOYAI6gRBEARBEHKA/wOBCNGnti3gLAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final = %sqlcmd snippets top_artist\n",
        "print(final)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1bRPR8Kmo--T",
        "outputId": "9332b0dc-b2d9-495c-d3fa-0cf3b25caffa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "WITH `tracks_with_info` AS (\n",
            "SELECT t.*, a.title AS album, ar.Name as artist\n",
            "FROM Track t\n",
            "JOIN Album a\n",
            "USING (AlbumId)\n",
            "JOIN Artist ar\n",
            "USING (ArtistId)), `genres_fav` AS (\n",
            "SELECT * FROM Genre\n",
            "WHERE Name\n",
            "LIKE '%rock%'\n",
            "OR Name LIKE '%metal%'), `track_fav` AS (\n",
            "SELECT t.*\n",
            "FROM tracks_with_info t\n",
            "JOIN genres_fav\n",
            "ON t.GenreId = genres_fav.GenreId)\n",
            "SELECT artist, COUNT(*) FROM track_fav\n",
            "GROUP BY artist\n",
            "ORDER BY COUNT(*) DESC\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "{{final}}"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        },
        "id": "Q65p_k9ypB-Q",
        "outputId": "d9ff49a1-f155-44ac-abcb-cfd1214b8320"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'sqlite:///my.db'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;sqlite:///my.db&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+---------------+----------+\n",
              "|     artist    | COUNT(*) |\n",
              "+---------------+----------+\n",
              "|  Iron Maiden  |   204    |\n",
              "|  Led Zeppelin |   114    |\n",
              "|       U2      |   112    |\n",
              "|   Metallica   |   112    |\n",
              "|  Deep Purple  |    92    |\n",
              "|   Pearl Jam   |    54    |\n",
              "|   Van Halen   |    52    |\n",
              "|     Queen     |    45    |\n",
              "| Lenny Kravitz |    44    |\n",
              "| Guns N' Roses |    42    |\n",
              "+---------------+----------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>artist</th>\n",
              "            <th>COUNT(*)</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>Iron Maiden</td>\n",
              "            <td>204</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Led Zeppelin</td>\n",
              "            <td>114</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>U2</td>\n",
              "            <td>112</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Metallica</td>\n",
              "            <td>112</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Deep Purple</td>\n",
              "            <td>92</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Pearl Jam</td>\n",
              "            <td>54</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Van Halen</td>\n",
              "            <td>52</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Queen</td>\n",
              "            <td>45</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Lenny Kravitz</td>\n",
              "            <td>44</td>\n",
              "        </tr>\n",
              "        <tr>\n",
              "            <td>Guns N' Roses</td>\n",
              "            <td>42</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 172
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%sql duckdb://"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "id": "t5mstxuUpFCP",
        "outputId": "3ca49c7f-900f-4e76-d68e-dbc6081a4e6f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Switching to connection 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Switching to connection &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --save first_cte --no-execute\n",
        "SELECT 1 AS column1, 2 AS column2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "3ZBm3BHHpdnE",
        "outputId": "69c50a17-c794-4362-d22b-99ae9d06c3d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Skipping execution..."
            ],
            "text/html": [
              "<span style=\"None\">Skipping execution...</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT * FROM second_cte"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 260
        },
        "id": "G5rU0PQepfNX",
        "outputId": "f00e87da-168b-4095-b845-c36f4f988ad7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "RuntimeError: If using snippets, you may pass the --with argument explicitly.\n",
            "For more details please refer: https://jupysql.ploomber.io/en/latest/compose.html#with-argument\n",
            "\n",
            "\n",
            "Original error message from DB driver:\n",
            "(duckdb.duckdb.CatalogException) Catalog Error: Table with name second_cte does not exist!\n",
            "Did you mean \"pg_type\"?\n",
            "LINE 1: SELECT * FROM second_cte\n",
            "                      ^\n",
            "[SQL: SELECT * FROM second_cte]\n",
            "(Background on this error at: https://sqlalche.me/e/20/f405)\n",
            "\n",
            "If you need help solving this issue, send us a message: https://ploomber.io/community\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql --with first_cte --save second_cte --no-execute\n",
        "SELECT\n",
        "  sum(column1),\n",
        "  sum(column2) FILTER (column2 = 2)\n",
        "FROM first_cte"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "id": "8Ia6Y2Wvpnhe",
        "outputId": "79cc023e-0166-4a21-9cdd-a1306d13916a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Skipping execution..."
            ],
            "text/html": [
              "<span style=\"None\">Skipping execution...</span>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%sql\n",
        "SELECT * FROM second_cte"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 96
        },
        "id": "yrU6FCCmpz8A",
        "outputId": "6c2379cb-979d-40d0-9c37-1353c19ec388"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating CTE with stored snippets: 'second_cte'"
            ],
            "text/html": [
              "<span style=\"None\">Generating CTE with stored snippets: &#x27;second_cte&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Running query in 'duckdb://'"
            ],
            "text/html": [
              "<span style=\"None\">Running query in &#x27;duckdb://&#x27;</span>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "+--------------+-------------------------------------------+\n",
              "| sum(column1) | sum(column2) FILTER (WHERE (column2 = 2)) |\n",
              "+--------------+-------------------------------------------+\n",
              "|      1       |                     2                     |\n",
              "+--------------+-------------------------------------------+"
            ],
            "text/html": [
              "<table>\n",
              "    <thead>\n",
              "        <tr>\n",
              "            <th>sum(column1)</th>\n",
              "            <th>sum(column2) FILTER (WHERE (column2 = 2))</th>\n",
              "        </tr>\n",
              "    </thead>\n",
              "    <tbody>\n",
              "        <tr>\n",
              "            <td>1</td>\n",
              "            <td>2</td>\n",
              "        </tr>\n",
              "    </tbody>\n",
              "</table>"
            ]
          },
          "metadata": {},
          "execution_count": 177
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "obgD--uNp2Vj"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}