_5_의미_연결망_분석(Semantic_Network_Analysis).ipynb

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  "metadata": {
    "colab": {
      "name": "_5 의미 연결망 분석(Semantic Network Analysis).ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8w_tpqGaAyVO"
      },
      "source": [
        "# 의미 연결망 분석(Semantic Network Analysis)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3vwuLxVfMRiB"
      },
      "source": [
        "* 사회 연결망 분석(Social Network Analysis)는 분석 대상 및 분석 대상들간의 관계를   \n",
        "연결망 구조로 표현하고 이를 계량적으로 제시하는 분석 기법\n",
        "* 사회 연결망 분석은 사람, 장소, 물품 등의 객체 간의 관계를 분석하는데 효과적이며  \n",
        "주로 친구 관계, 전력 공급 등을 분석하는데 사용\n",
        "* 사회 연결망 분석 기법을 텍스트 내 단어의 관계에 적용한 것이 바로 의미 연결망 분석\n",
        "* 의미 연결망 분석에서는 일정한 범위 내에서 어휘가 동시에 등장하면 서로 연결된 것으로 간주, 이 연결 관계들을 분석\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M29i6PFkWzDc"
      },
      "source": [
        "## n-gram"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KOfhuY4-aBdF"
      },
      "source": [
        "* `nltk` 라이브러리는 편하게 n-gram을 생성할 수 있는 함수를 제공\n",
        "* 많이 사용되는 `bigrams`의 경우에는 별도의 함수를 제공하니 해당 내용을 참조하여 n-gram 생성"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s4kJbCxWYmZa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e0caab27-239c-4a7d-b43f-e2480803256f"
      },
      "source": [
        "import nltk\n",
        "nltk.download('punkt')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vCbTuM2oX6I8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a2aff9ff-aec0-463e-e1f6-f9ee81b03a44"
      },
      "source": [
        "from nltk import word_tokenize, bigrams\n",
        "\n",
        "sentence = 'I love data science and deep learning'\n",
        "tokens = word_tokenize(sentence)\n",
        "\n",
        "bgram = bigrams(tokens)\n",
        "bgram_list = [x for x in bgram]\n",
        "print(bgram_list)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('I', 'love'), ('love', 'data'), ('data', 'science'), ('science', 'and'), ('and', 'deep'), ('deep', 'learning')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bRoIscVjZFV9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6125ec33-b475-40f3-cf57-1b1c42fcf852"
      },
      "source": [
        "from nltk.util import ngrams\n",
        "\n",
        "tgram = ngrams(tokens, 3)\n",
        "qgram = ngrams(tokens, 4)\n",
        "\n",
        "tgram_list = [x for x in tgram]\n",
        "qgram_list = [x for x in qgram]\n",
        "\n",
        "print(tgram_list)\n",
        "print(qgram_list)\n",
        "\n",
        "# 앞뒤를 파악하기 위해 / 관계를 가지기 위해 묶음"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('I', 'love', 'data'), ('love', 'data', 'science'), ('data', 'science', 'and'), ('science', 'and', 'deep'), ('and', 'deep', 'learning')]\n",
            "[('I', 'love', 'data', 'science'), ('love', 'data', 'science', 'and'), ('data', 'science', 'and', 'deep'), ('science', 'and', 'deep', 'learning')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JkWZYBtuW1Gb"
      },
      "source": [
        "## 어휘 동시 출현 빈도의 계수화"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6iMwMrupGj0I"
      },
      "source": [
        "* 동시 출현(Co-occurrence)란 두 개 이상의 어휘가 일정한 범위나 거리 내에서 함께 출현하는 것을 의미\n",
        "* 단어간의 동시 출현 관계를 분석하면 문서나 문장으로부터 두 단어가 유사한 의미를 가졌는지 등의 추상화된 정보를 얻을 수 있음\n",
        "* 동시 출현 빈도는 Window라는 지정 범위 내에서 동시 등장한 어휘를 확률 등으로 계수화 가능\n",
        "* 예를 들어, 단어 뒤 잘못된 단어가 온다면, 이를 동시 출현 빈도가 높은 단어로 교정 가능"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xdeJzfWKefM6"
      },
      "source": [
        "* 어휘 동시 출현 빈도 행렬은 하나하나 측정할 수도 있지만, 바이그램 개수를 정리하면 편리하게 만들어 볼 수 있음\n",
        "* `nltk`에서 제공하는 `ConditionalFreqDist` 함수를 이용하면 문맥별 단어 빈도를 쉽게 측정 가능"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j37YObgSumih",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8487c59e-8e23-4b02-bb0e-a32e686d042a"
      },
      "source": [
        "from nltk import ConditionalFreqDist\n",
        "\n",
        "sentences = ['I love data science and deep learning', 'I love science', 'I know this code']\n",
        "tokens = [word_tokenize(x) for x in sentences]\n",
        "bgrams = [bigrams(x) for x in tokens]\n",
        "\n",
        "token = []\n",
        "for i in bgrams:\n",
        "  token += ([x for x in i])\n",
        "  \n",
        "cfd = ConditionalFreqDist(token)\n",
        "cfd.conditions()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this']"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CMbM_XrMluEL",
        "outputId": "a98f42cc-33ad-4f65-efca-6f8c34a308eb"
      },
      "source": [
        "print(token)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('I', 'love'), ('love', 'data'), ('data', 'science'), ('science', 'and'), ('and', 'deep'), ('deep', 'learning'), ('I', 'love'), ('love', 'science'), ('I', 'know'), ('know', 'this'), ('this', 'code')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5nLFrqh0bDDu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d0157441-7fa0-4f4d-f7ad-42cdc17c5995"
      },
      "source": [
        "print(cfd['I'])"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<FreqDist with 2 samples and 3 outcomes>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1qi_TGyUbEye",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7718f7e5-2843-4709-b94d-709e18f144ba"
      },
      "source": [
        "print(cfd['I']['love'])"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "212HozdE76Ne",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b255ef76-4a86-444f-ecf5-f346014e76f3"
      },
      "source": [
        "print(cfd['I'].most_common(1)) # I랑 동시 출현한 건 뭐냐"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('love', 2)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8W76iFvWy5i",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bf63fb54-4e0a-4d78-8147-8ad020b944c6"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "freq_matrix = []\n",
        "\n",
        "for i in cfd.keys():\n",
        "  temp = []\n",
        "  for j in cfd.keys():\n",
        "    temp.append(cfd[i][j]) # 동시 출연한 비율\n",
        "  freq_matrix.append(temp)\n",
        "freq_matrix = np.array(freq_matrix)\n",
        "\n",
        "print(cfd.keys())\n",
        "print(freq_matrix)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "dict_keys(['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this'])\n",
            "[[0 2 0 0 0 0 1 0]\n",
            " [0 0 1 1 0 0 0 0]\n",
            " [0 0 0 1 0 0 0 0]\n",
            " [0 0 0 0 1 0 0 0]\n",
            " [0 0 0 0 0 1 0 0]\n",
            " [0 0 0 0 0 0 0 0]\n",
            " [0 0 0 0 0 0 0 1]\n",
            " [0 0 0 0 0 0 0 0]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IdfUT9Y_wXID"
      },
      "source": [
        "* 해당 동시 출현 빈도 행렬을 좀 더 보기 쉽도록 데이터프레임으로 시각화"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PpSGjtsjXnHT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        },
        "outputId": "0a1b0624-d31d-4bc9-de21-a06f18af9129"
      },
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.DataFrame(freq_matrix, index=cfd.keys(), columns=cfd.keys())\n",
        "df.style.background_gradient(cmap='coolwarm')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "        }</style><table id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >I</th>        <th class=\"col_heading level0 col1\" >love</th>        <th class=\"col_heading level0 col2\" >data</th>        <th class=\"col_heading level0 col3\" >science</th>        <th class=\"col_heading level0 col4\" >and</th>        <th class=\"col_heading level0 col5\" >deep</th>        <th class=\"col_heading level0 col6\" >know</th>        <th class=\"col_heading level0 col7\" >this</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >I</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col1\" class=\"data row0 col1\" >2</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col6\" class=\"data row0 col6\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >love</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col0\" class=\"data row1 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col1\" class=\"data row1 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col2\" class=\"data row1 col2\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col3\" class=\"data row1 col3\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col6\" class=\"data row1 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >data</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col2\" class=\"data row2 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col3\" class=\"data row2 col3\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col6\" class=\"data row2 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >science</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col1\" class=\"data row3 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col2\" class=\"data row3 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >and</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col1\" class=\"data row4 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col2\" class=\"data row4 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col5\" class=\"data row4 col5\" >1</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >deep</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col0\" class=\"data row5 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col5\" class=\"data row5 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row5_col7\" class=\"data row5 col7\" >0</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >know</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col0\" class=\"data row6 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col1\" class=\"data row6 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col2\" class=\"data row6 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col6\" class=\"data row6 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row6_col7\" class=\"data row6 col7\" >1</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >this</th>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col2\" class=\"data row7 col2\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col5\" class=\"data row7 col5\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col6\" class=\"data row7 col6\" >0</td>\n",
              "                        <td id=\"T_b7c63f10_298e_11ec_a9c6_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7ff8930fb090>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BGGjGxUrwi2b"
      },
      "source": [
        "* 동시 출현 빈도 행렬은 인접 행렬로도 간주할 수 있음\n",
        "* `networkx` 라이브러리를 사용해 해당 행렬을 그래프로 시각화"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n02wBj9d1lfg"
      },
      "source": [
        "* 앞서 만든 데이터프레임을 그래프로 변환\n",
        "* 넘파이 배열 등으로도 가능하나, 이 경우 별도로 라벨을 지정해줘야만 함"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NP_fVs57wjK4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ecd3fc4c-d0af-4eb6-ed8e-36ca9bd8536e"
      },
      "source": [
        "import networkx as nx\n",
        "\n",
        "G = nx.from_pandas_adjacency(df) #인접행렬을 바로 부름\n",
        "\n",
        "print(G.nodes())\n",
        "print(G.edges()) # 관계가 있는 것들"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this']\n",
            "[('I', 'love'), ('I', 'know'), ('love', 'data'), ('love', 'science'), ('data', 'science'), ('science', 'and'), ('and', 'deep'), ('know', 'this')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VVffevvX12lg"
      },
      "source": [
        "* 각 엣지에 접근해보면 각 엣지의 가중치에 각 단어간의 빈도가 사용된 것을 확인 가능"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5_ip9oSd2AOY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dd3e8662-2615-4ee1-f176-465683b2ff43"
      },
      "source": [
        "print(G.edges()['I', 'love'])\n",
        "print(G.edges()[('I', 'know')]) # 얼마큼 들어있는지 가중치 포함"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'weight': 2}\n",
            "{'weight': 1}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I2TNV9401ke7"
      },
      "source": [
        "* `nx.draw`를 통해 간편하게 그래프를 시각화할 수 있음"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2bt9zZ0P1aCc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        },
        "outputId": "cc8ab98c-a5a0-49c5-f202-a633fc7d29ca"
      },
      "source": [
        "nx.draw(G, with_labels=True)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MrafXR_vaqd9"
      },
      "source": [
        "* 어휘 동시 출현 빈도를 이용하면 어휘 동시 출현 확률까지 측정 가능\n",
        "* 어휘 동시 출현 확률 계산에는 `nltk`의 `ConditionalProbDist`를 이용"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dOfiGSVL8I38",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2c73a8ba-53d1-4358-ec7a-c2539bb11a99"
      },
      "source": [
        "from nltk.probability import ConditionalProbDist, MLEProbDist\n",
        "\n",
        "cpd = ConditionalProbDist(cfd, MLEProbDist)\n",
        "cpd.conditions()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this']"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aliwTDpm85V5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "324d4608-b658-4142-c91f-34512f69c080"
      },
      "source": [
        "prob_matrix = []\n",
        "\n",
        "for i in cpd.keys():\n",
        "  prob_matrix.append([cpd[i].prob(j) for j in cpd.keys()])\n",
        "\n",
        "prob_matrix = np.array(prob_matrix)\n",
        "\n",
        "print(cpd.keys())\n",
        "print(prob_matrix)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "dict_keys(['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this'])\n",
            "[[0.         0.66666667 0.         0.         0.         0.\n",
            "  0.33333333 0.        ]\n",
            " [0.         0.         0.5        0.5        0.         0.\n",
            "  0.         0.        ]\n",
            " [0.         0.         0.         1.         0.         0.\n",
            "  0.         0.        ]\n",
            " [0.         0.         0.         0.         1.         0.\n",
            "  0.         0.        ]\n",
            " [0.         0.         0.         0.         0.         1.\n",
            "  0.         0.        ]\n",
            " [0.         0.         0.         0.         0.         0.\n",
            "  0.         0.        ]\n",
            " [0.         0.         0.         0.         0.         0.\n",
            "  0.         1.        ]\n",
            " [0.         0.         0.         0.         0.         0.\n",
            "  0.         0.        ]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DELaFrOLQyTY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        },
        "outputId": "5250f103-6013-4024-abfe-bab81b35b0e0"
      },
      "source": [
        "df = pd.DataFrame(prob_matrix, index=cpd.keys(), columns=cpd.keys())\n",
        "df.style.background_gradient(cmap='coolwarm')"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "            color:  #f1f1f1;\n",
              "        }#T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col3{\n",
              "            background-color:  #dddcdc;\n",
              "            color:  #000000;\n",
              "        }</style><table id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >I</th>        <th class=\"col_heading level0 col1\" >love</th>        <th class=\"col_heading level0 col2\" >data</th>        <th class=\"col_heading level0 col3\" >science</th>        <th class=\"col_heading level0 col4\" >and</th>        <th class=\"col_heading level0 col5\" >deep</th>        <th class=\"col_heading level0 col6\" >know</th>        <th class=\"col_heading level0 col7\" >this</th>    </tr></thead><tbody>\n",
              "                <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row0\" class=\"row_heading level0 row0\" >I</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col0\" class=\"data row0 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col1\" class=\"data row0 col1\" >0.666667</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col2\" class=\"data row0 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col3\" class=\"data row0 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col4\" class=\"data row0 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col5\" class=\"data row0 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col6\" class=\"data row0 col6\" >0.333333</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row0_col7\" class=\"data row0 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row1\" class=\"row_heading level0 row1\" >love</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col0\" class=\"data row1 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col1\" class=\"data row1 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col2\" class=\"data row1 col2\" >0.500000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col3\" class=\"data row1 col3\" >0.500000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col4\" class=\"data row1 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col5\" class=\"data row1 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col6\" class=\"data row1 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row1_col7\" class=\"data row1 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row2\" class=\"row_heading level0 row2\" >data</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col0\" class=\"data row2 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col1\" class=\"data row2 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col2\" class=\"data row2 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col3\" class=\"data row2 col3\" >1.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col4\" class=\"data row2 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col5\" class=\"data row2 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col6\" class=\"data row2 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row2_col7\" class=\"data row2 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row3\" class=\"row_heading level0 row3\" >science</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col0\" class=\"data row3 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col1\" class=\"data row3 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col2\" class=\"data row3 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col3\" class=\"data row3 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col4\" class=\"data row3 col4\" >1.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col5\" class=\"data row3 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col6\" class=\"data row3 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row3_col7\" class=\"data row3 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row4\" class=\"row_heading level0 row4\" >and</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col0\" class=\"data row4 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col1\" class=\"data row4 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col2\" class=\"data row4 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col3\" class=\"data row4 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col4\" class=\"data row4 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col5\" class=\"data row4 col5\" >1.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col6\" class=\"data row4 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row4_col7\" class=\"data row4 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row5\" class=\"row_heading level0 row5\" >deep</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col0\" class=\"data row5 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col1\" class=\"data row5 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col2\" class=\"data row5 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col3\" class=\"data row5 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col4\" class=\"data row5 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col5\" class=\"data row5 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col6\" class=\"data row5 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row5_col7\" class=\"data row5 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row6\" class=\"row_heading level0 row6\" >know</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col0\" class=\"data row6 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col1\" class=\"data row6 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col2\" class=\"data row6 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col3\" class=\"data row6 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col4\" class=\"data row6 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col5\" class=\"data row6 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col6\" class=\"data row6 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row6_col7\" class=\"data row6 col7\" >1.000000</td>\n",
              "            </tr>\n",
              "            <tr>\n",
              "                        <th id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002level0_row7\" class=\"row_heading level0 row7\" >this</th>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col0\" class=\"data row7 col0\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col1\" class=\"data row7 col1\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col2\" class=\"data row7 col2\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col3\" class=\"data row7 col3\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col4\" class=\"data row7 col4\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col5\" class=\"data row7 col5\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col6\" class=\"data row7 col6\" >0.000000</td>\n",
              "                        <td id=\"T_b806549c_298e_11ec_a9c6_0242ac1c0002row7_col7\" class=\"data row7 col7\" >0.000000</td>\n",
              "            </tr>\n",
              "    </tbody></table>"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7ff88a1a9990>"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5uS2j0rUytbk"
      },
      "source": [
        "* 확률 행렬도 인접 행렬로 간주할 수 있음\n",
        "* 그래프 시각화시 빈도 행렬과 동일한 결과를 얻을 수 있으나, 확률을 가중치로 사용시 부정확한 결과를 얻을 수 있음"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qvK09OMeytiM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5a92411a-58ec-4ffb-fc2f-8f70de2f97a2"
      },
      "source": [
        "prob_G = nx.from_pandas_adjacency(df)\n",
        "\n",
        "print(prob_G.nodes())\n",
        "print(prob_G.edges())"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['I', 'love', 'data', 'science', 'and', 'deep', 'know', 'this']\n",
            "[('I', 'love'), ('I', 'know'), ('love', 'data'), ('love', 'science'), ('data', 'science'), ('science', 'and'), ('and', 'deep'), ('know', 'this')]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NDwhyWPN3YOa",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2180874b-8271-4ba1-b71c-bd6a2740194c"
      },
      "source": [
        "print(G.edges()['I', 'love'])\n",
        "print(G.edges()[('I', 'know')])\n",
        "\n",
        "print(prob_G.edges()['I', 'love'])\n",
        "print(prob_G.edges()[('I', 'know')])"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'weight': 2}\n",
            "{'weight': 1}\n",
            "{'weight': 0.6666666666666666}\n",
            "{'weight': 0.3333333333333333}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R-P_YSj23YgN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 319
        },
        "outputId": "6f70ff46-6a03-443e-cd5c-01af2a8162be"
      },
      "source": [
        "nx.draw(prob_G, with_labels=True)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ecrrZMfTzo-a"
      },
      "source": [
        "## 중심성(Centrality) 지수"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UD_m6Jr34IDY"
      },
      "source": [
        "* 연결망 분석에서 가장 많이 주목하는 속성은 바로 중심성 지수\n",
        "* 중심성은 전체 연결망에서 중심에 위치하는 정도를 표현하는 지표로, 이를 분석하면 연결 정도, 중요도 등을 알 수 있음\n",
        "* 중심성 지수는 나타내는 특징에 따라 연결 중심성, 매개 중심성, 근접 중심성, 위세 중심성으로 구분"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yeWdLGGtzv3y"
      },
      "source": [
        "### 연결 중심성(Degree Centrality)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-KlB1zAYoZIr"
      },
      "source": [
        "* 연결 중심성은 가장 기본적이고 직관적으로 중심섬을 측정하는 지표\n",
        "* 텍스트에서 다른 단어와의 동시 출현 빈도가 많은 특정 단어는 연결 중심성이 높다고 볼 수 있음\n",
        "* 연결 정도로만 측정하면 연결망의 크기에 따라 달라져 비교가 어렵기 때문에 여러 방법으로 표준화\n",
        "* 주로 (특정 노드 i와 직접적으로 연결된 노드 수 / 노드 i와 직간접적으로 연결된 노드 수)로 계산\n",
        "\n",
        "* 여기서 직접적으로 연결된 노드는 서로 엣지 관계인 노드를 뜻하며, 간접적으로 연결된 노드는 서로 엣지 관계는 아니나 다른 노드와 엣지에 의해 도달할 수 있는 노드를 말함"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V6Wpl3ctqJIr"
      },
      "source": [
        "* 연결 중심성 계산 수식\n",
        "\n",
        "$$ degree_{ik} = \\sum_{i=1}^{N} Z_{ijk} = Z_{jk}$$\n",
        "$$ outdegree_{ik} = \\sum_{j=1}^{N} Z_{ijk} = Z_{ik} $$\n",
        "$$ C_{i} = \\sum_{j=1}^{n}(Z_{ij}+Z_{ji}) / \\sum_{i=1}^{n}\\sum_{j=1}^{n}(Z_{ij})\\qquad단, 0\\le C \\le 1$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0MfaWMTTsjlh"
      },
      "source": [
        "* 해당 수식을 직접 계산할 수도 있으나,     \n",
        "`networkx`에는 해당 라이브러리로 구성된 그래프의 연결 중심성을 쉽게 계산해주는 함수가 존재   "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kAuXf3rhzwG6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6f34e764-d81d-4539-fa28-fba9687a6047"
      },
      "source": [
        "nx.degree_centrality(G)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'I': 0.2857142857142857,\n",
              " 'and': 0.2857142857142857,\n",
              " 'data': 0.2857142857142857,\n",
              " 'deep': 0.14285714285714285,\n",
              " 'know': 0.2857142857142857,\n",
              " 'love': 0.42857142857142855,\n",
              " 'science': 0.42857142857142855,\n",
              " 'this': 0.14285714285714285}"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CcXMGpXkzwOC"
      },
      "source": [
        "### 위세 중심성(Eigenvector Centraility)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9hCmeXpGwYZE"
      },
      "source": [
        "* 위세 중심성은 연결된 상대 단어의 중요성에 가중치를 둠\n",
        "* 중요한 단어와 많이 연결됐다면 위세 중심성은 높아지게 됨\n",
        "* 위세 중심성은 고유 벡터로써 인접해 있는 노드의 위세 점수와 관련되어 있어 직접 계산하기는 쉽지 않음"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7gzAhV3Exw1K"
      },
      "source": [
        "* 위세 중심성 계산 수식\n",
        "\n",
        "$$ P_i =\\sum_{j=1}^{N-1}P_iZ_{ji},\\qquad0 \\le P_i \\le 1$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iLprc5-fyPqa"
      },
      "source": [
        "* 위세 중심성 계산에는 `eigenvector_centraility`를 이용해 계산\n",
        "* `weight`로는 어휘 동시 출현 빈도를 이용"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PynA3AxvzwTI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "54dc4a0b-4aa6-442b-e568-a15a666e1578"
      },
      "source": [
        "nx.eigenvector_centrality(G, weight='weight')"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'I': 0.5055042648573065,\n",
              " 'and': 0.15933837227495717,\n",
              " 'data': 0.35703593885196566,\n",
              " 'deep': 0.055886131430398216,\n",
              " 'know': 0.20216573350291445,\n",
              " 'love': 0.6195557831651917,\n",
              " 'science': 0.39841035839294925,\n",
              " 'this': 0.07090581134630142}"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ucp7jIuVzwZ6"
      },
      "source": [
        "### 근접 중심성(Closeness Centrality)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "37sMX-YOydX2"
      },
      "source": [
        "* 근접 중심성은 한 단어가 다른 단어에 얼마나 가깝게 있는지를 측정하는 지표\n",
        "* 직접적으로 연결된 노드만 측정하는 연결 중심성과는 다르게, 근접 중심성은 직간접적으로 연결된 모든 노드들 사이의 거리를 측정\n",
        "* 근접 중심성을 측정하기 위해선 다음과 같이 계산\n",
        "\n",
        "  (모든 노드 수 - 1 / 특정 노드 i에서 모든 노드에 이르는 최단 경로 수를 모두 더한 수)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pe-cPBjI0Dgi"
      },
      "source": [
        "\n",
        "$$ C_C(A) = \\frac{1}{\\frac{1}{N-1}\\sum_{x \\ne A}l_{X,A}} = \\frac{N-1}{\\sum_{x \\ne A}l_{X,A}} $$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2GuKUAJH05ap"
      },
      "source": [
        "* 근접 중심성을 계산하기 위해선 `closeness_centrality()` 함수를 사용"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zllK1iK9zwiM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "49f409ce-3baf-4c47-b8a7-3d5dcb9aa196"
      },
      "source": [
        "nx.closeness_centrality(G, distance='weight')"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'I': 0.35,\n",
              " 'and': 0.3333333333333333,\n",
              " 'data': 0.3684210526315789,\n",
              " 'deep': 0.25925925925925924,\n",
              " 'know': 0.2916666666666667,\n",
              " 'love': 0.4375,\n",
              " 'science': 0.4117647058823529,\n",
              " 'this': 0.23333333333333334}"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G1l7sHdtz35g"
      },
      "source": [
        "### 매개 중심성(Betweeness Centrality)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yEXo-gzV2sQQ"
      },
      "source": [
        "* 매개 중심성은 한 단어가 단어들과의 연결망을 구축하는데 얼마나 도움을 주는지 측정하는 지표\n",
        "* 매개 중심성이 높은 단어는 빈도 수가 작더라도 단어 간 의미부여 역할이 크기 때문에, 해당 단어를 제거하면 의사소통이 어려워짐\n",
        "* 매개 중심성은 모든 노드 간 최단 경로에서 특정 노드가 등장하는 횟수로 측정하며,     \n",
        "표준화를 위해 최댓값인 (N-1) x (N-2) / 2로 나눔"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ogCMdFoL1Ch4"
      },
      "source": [
        "* 매개 중심성 계산 수식\n",
        "\n",
        "$$ C_{B}^{'}(P_m) = \\frac{\\sum_i^N \\sum_j^N \\frac{g_{imj}}{g_{ij}}}{(\\frac{N^2-3N+2}{2})}, \\qquad 단, i<j,\\quad i \\ne j$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "efWuZV2P39hc"
      },
      "source": [
        "* 매개 중심성을 계산하기 위해선 `current_flow_betweenness_centrality()` 함수를 이용"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q0rYR3wQz3-D",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3e793145-8422-40a6-a816-973abad12324"
      },
      "source": [
        "nx.betweenness_centrality(G)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'I': 0.47619047619047616,\n",
              " 'and': 0.2857142857142857,\n",
              " 'data': 0.0,\n",
              " 'deep': 0.0,\n",
              " 'know': 0.2857142857142857,\n",
              " 'love': 0.5714285714285714,\n",
              " 'science': 0.47619047619047616,\n",
              " 'this': 0.0}"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lhdU3ocgtNt-"
      },
      "source": [
        "### 페이지랭크(PageRank)\n",
        "\n",
        "* 월드 와이드 웹과 같은 하이퍼링크 구조를 가지는 문서에 상대적 중요도에 따라 가중치를 부여하는 방법\n",
        "* 이 알고리즘은 서로간에 인용과 참조로 연결된 임의의 묶음에 적용 가능\n",
        "* 페이지 랭크는 더 중요한 페이지는 더 많은 다른 사이트로부터 링크를 받는다는 관찰에 기초"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6aJCEibHsn0x",
        "outputId": "36791750-9019-409e-a1e8-0ac521ed68fd"
      },
      "source": [
        "nx.pagerank(G)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'I': 0.1536831077679558,\n",
              " 'and': 0.12417333539164832,\n",
              " 'data': 0.10481873412175656,\n",
              " 'deep': 0.07152392879557615,\n",
              " 'know': 0.1224741813421488,\n",
              " 'love': 0.19501225218917406,\n",
              " 'science': 0.15751225722745082,\n",
              " 'this': 0.07080220316428934}"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EpC8ajLCr6a1"
      },
      "source": [
        "def get_node_size(node_values):\n",
        "  nsize = np.array([v for v in node_values])\n",
        "  nsize = 1000 * (nsize - min(nsize)) / (max(nsize) - min(nsize))\n",
        "\n",
        "  return nsize"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n-owk0_FsOSL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "42a85733-4ccd-42a4-dde3-49dbccc77cba"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('seaborn-white')\n",
        "\n",
        "dc = nx.degree_centrality(G).values()\n",
        "ec = nx.eigenvector_centrality(G, weight='weight').values()\n",
        "cc = nx.closeness_centrality(G, distance='weight').values()\n",
        "bc = nx.betweenness_centrality(G).values()\n",
        "pr = nx.pagerank(G).values()\n",
        "\n",
        "plt.figure(figsize=(14, 20))\n",
        "plt.axis('off')\n",
        "\n",
        "plt.subplot(321)\n",
        "plt.title('Normal', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16, alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.subplot(322)\n",
        "plt.title('Degree Centrality', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16,\n",
        "                 node_color=list(dc), node_size=get_node_size(dc),\n",
        "                 alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.subplot(323)\n",
        "plt.title('Eigenvector Centrality', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16,\n",
        "                 node_color=list(ec), node_size=get_node_size(ec),\n",
        "                 alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.subplot(324)\n",
        "plt.title('Closeness Centrality', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16,\n",
        "                 node_color=list(cc), node_size=get_node_size(cc),\n",
        "                 alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.subplot(325)\n",
        "plt.title('Betweenness Centrality', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16,\n",
        "                 node_color=list(bc), node_size=get_node_size(bc),\n",
        "                 alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.subplot(326)\n",
        "plt.title('Pagerank', fontsize=16)\n",
        "nx.draw_networkx(G, font_size=16,\n",
        "                 node_color=list(pr), node_size=get_node_size(pr),\n",
        "                 alpha=0.7, cmap=plt.cm.Blues)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MG0ebpGNjY0lISGiY6kRE5JSom9Cx9J4SEWk6TvSe0gBxERERERFpEAobIiIiIiLSIBQ2RERERESkQShsiIiIiIhIg1DYEBERERGRBqGwISIiIiIiDUJhQ0REREREGoTChoiIiIiINAiFDRERERERaRAKGyIiIiIi0iAUNkREREREpEEobIiIiIiISINQ2BARERERkQahsCEiIiIiIg1CYUNERERERBqExdsFiMjpq9RWw6rdhewrqqTc7iDIz0LriADOTY0kxOrj7fJERESkgSlsiEi9yyysYPHGHL7cWYDL5cYwwGwYON1u3G54fcVeLkiLYli3eJIjA71droiIiDQQdaMSkd9t+vTpjBkzps62ZTvyeeD9DSzdkU+ov4WoYD8ig/wID/QlMsiPqGA/QvwtLP3xuGU78r1UvcivW7p0KUOHDqW0tPSEx8yfP58rrriiEasSEWle1LIhIvVm2Y58pv13J2EBPvhZzCc8zmIyERXkh93hZNp/dwIwoH10Y5UpckILFiwgOzubBx544JSOv+qqq7j00ksbuCoRkeZLLRsiUi8yCyuYsXT3SYPGz/lZzIQF+PDSst1kFlY0cIUiJ7djx47fdLzVaiUsLKyBqhERaf7UsiEipyQ/P5+XX36Zbdu2ERQUxNChQ+vs/+fq3exdvgB7XgbVleUERkTT9pyLiWrTyXOMrbyEXV8vpiQnkxpbJSHR8aSeNwxXSBwfbTxIJ/Yzffp0pk2bxquvvkpWVhahoaFcd911XHzxxY39yHKGefzxx9myZQtQ24XqaOtGQUEBzz//PDt27CAgIIAbb7zR8//H+fPn8/7777No0SIANm7cyLx589i3bx8Abdq04ZZbbqFDhw5eeCIREe9Ty4aInJKpU6eSm5vLM888w6RJkzh48CDr1q0Damed+vvMaVQd3E37C6+mz00P0aJVGhs/mk3JwUwAXE4H6xa8SsXhQ3S55CbOvuGv+IdF8sOHr2GtLuXLnflUVDsAeO211xgxYgQvvfQSvXr14pVXXmH37t1ee3Y5MzzxxBPExcXRr18/5s6dS01NDQBz5szhqquu4qWXXqJ79+688sor5OcfO9aovLycSZMmkZaWxowZM5g2bRoJCQlMnDgRm83W2I8jItIkKGyIyEnl5OSwc+dORowYQadOnUhMTOSee+7BbK7tLvX+56s5kpNBhwuvIqpNRwLDo0k973KCo1qy74flAOTv2UxlcQGdLrqB8IS2BLWIpeOga7H4Wcnd8i1Ol5ut2UcAGDJkCN27dychIYExY8bg5+fHihUrvPb8cmYIDg7GZDLh5+dHeHg4Pj610zMPHjyYnj17Eh8fz9VXX43b7WbPnj3HnH/w4EFsNhv9+/cnLi6OhIQE7rjjDp566inP3xURkTONwoaInNSBAweA2i4hR5lMJlJTUwFYv3U7BhCRmFrnvPCEFMoKDgJwJG8fFmsAIdHxP13DbCE0LomyghwMA/LL7QCkpaV5jvHx8aF169YUFBQ0yLOJnExKSorn9yEhIQBUVVUdc1yrVq2Ijo5mypQpLFy4kL1792KxWOjQoYMnuIiInGk0ZkNETuroBys/P7862/39/QEoLavAAL5+4+k6+10uJyaTmfz8fMpKinHYq1g287G6xzgdBIRHYzIMqqqdAAQG1l17w2q1Ul5eXo9PJHLqfH19Pb83DAOAyspKxo8fT1JSkmef1Wpl6tSpLFy4kCVLljBnzhyio6MZOXIk/fr1a+yyRUSaBIUNETmpoyHDbrfX2X40AIQEB+IGzvrzA5jMx/6zUumASnsNPtYAzrr+/mP2GyYTFW43/r61XU1+2b+9qqqK6GhNjStNR0BAAElJSSxevBi32+3Z3qJFC8aMGcOYMWPIzMzkgw8+YOrUqbRu3ZrExEQvViwi4h3qRiUiJ5WQkABQZ5B2dXU127dvByC9UwfcgMNeRUBYpOeXYTLhGxBMeEQEbv9Q7FXlGCZznWMA/AJCcLshOqg21GzdutVzn5qaGvbv3++pQaSh/Tw8/JqRI0fi6+tLZmYmbreb3Nxc1qxZ49mfnJzM3Xffjdvt9nRFFBE50yhsiMhJtWrViqSkJN599122b9/Ovn37ePnllz0tHtcN6UNoyzZs+fw9Du/bRVVpEYd2b+L7d6eTtWYpZpOJhA49MPkFsfk/71ByMJOq0iJytn7P6nkvkL11DWaTQaeEUAA+++wz1q1bR05ODq+//jp2u53+/ft780cgZ4igoCD27t3L3r17KS4u/tVjTSYTl112GZWVlfzzn/8kNzeXyZMns2TJEvLy8sjNzWXhwoX4+vrSrl27RnoCEZGmRd2oROSUPPbYY8ycOZMnnniCkJAQLrvsMkJCQlizZg0hVh9uu/ch3nl7Dls+nUeNrRK/oFAS088jufcgAKJiYjnS8xLMhbtZ/++/46yxExAWSbvzr8CvTQ8uTIsmkNruUyNGjODdd99lz549hIaGcv/996tlQxrFVVddxcyZMxk7diw33HDDSY8/GiQ+/fRTRo4cyd13382iRYuYPXs2Pj4+JCUlMX78eCIjIxuhehGRpkdhQ0ROSXx8PM8999wx22+//XYArumTyqp91xBsNR93BfHg4GDM1kBSLvhTnQHgdoeTcruTod1asnfjfgASExOZOnVqAz2JyIn17duXvn37ev581VVX1dkfHh7ORx995PnzDTfcwA033EBWVhbjxo3jySefZObMmY1Wr4hIU6duVCJSL5IjA7l/YCollTXYHc5j9htAZGQkhYWFnm12h5OSyhruG5BKcmTgMeeINBdJSUk88MADPPfcc+Tl5Xm7HBGRJkNhQ0TqzYD20Tw4OI0ym5OCcjsOl6vO/sjISA4XFVHtrN1fbnfy4OA0BrTXTFPS/PXq1YvrrruOiRMnaqpmEZEfqRuViNSrAe2jSY4M5KONB/lyZz5OlxvDAJNh4HKD4R9CbmEJw3q2ZWi3lnVaNAYOHMjAgQO9WL3IH3PZZZeRm5vLc889x8SJE7FY9JoVkTObWjZEpN4lRwZy38BU3h51Fn/p35ZLu8TRLyWSS7vEcW3nMPraf+C+geo6JaenUaNG4e/vz6xZs055Gl0RkdOVvnIRkQYTYvXhki5xdbZVVbVk5Mg5HDlyhNDQUC9VJtJwTCYTDz/8MI8++igLFizgmmuu8XZJIiJeo5YNEWlU/v7+nHXWWSxfvtzbpYg0GKvVyoQJE/jPf/7DypUrvV2OiIjXKGyISKMbMGAAS5cu9XYZIg2qRYsWjB8/nldffZWdO3d6uxwREa9Q2BCRRte1a1dKS0vJysrydikiDapNmzY88MADTJ48mUOHDnm7HBGRRqewISKNzmQyqXVDzhi9e/fm2muvZeLEiVRUVHi7HBGRRqWwISJeMWDAAL766iuczmMXABQ53Vx++eV0796d5557DofD4e1yREQajcKGiHhFfHw8MTEx/PDDD94uRaRR3Hbbbfj6+vLKK69oSlwROWMobIiI1wwaNEhdqeSMYTKZGDt2LBkZGSxcuNDb5YiINAqFDRHxmvPOO48NGzZQVlbm7VJEGoXVamX8+PF8/PHHrFq1ytvliIg0OIUNEfGawMBA0tPTWbFihbdLEWk0kZGRjB8/nldeeUVT4orIaU9hQ0S8auDAgepKJWeco1Pi/s///A/5+fneLkdEpMEobIiIV6Wnp1NQUEB2dra3SxFpVL179+ZPf/oTTz/9tKbEFZHTlsKGiHiV2WzmggsuUOuGnJGGDh1Kt27dmDJliqbEFZHTksKGiHjdwIED+fLLL3G5XN4uRaTR3XbbbVgsFl577TVNiSsipx2FDRHxutatWxMeHs7GjRu9XYpIozObzYwdO5Zdu3bxr3/9y9vliIjUK4UNEWkSBgwYoK5Ucsby9/dnwoQJLF68mG+++cbb5YiI1BuFDRFpEvr378/atWuprKz0dikiXhEZGcm4ceOYNWsWu3fv9nY5IiL1QmFDRJqEkJAQunTpooXO5IyWkpLCfffdx6RJk351Sly3201VjZMjthrK7A5cGushIk2UxdsFiIgcNWjQID788EMGDx7s7VJEvObss88mLy+PiRMnMnXqVAIDAwFwutzsLapi48Eyckpt2GpcGEbtOQYQHeRLx5ggOsUEEeBr9t4DiIj8jFo2RKTJ6NmzJzk5OeTm5nq7FBGvGjZsGJ07d+b555+npqaG3QUVvPrtAf61+RBZxVWYDINgPzPBfhaC/SwE+Jopqqxh2Z4iZn6zny/3HKbGqdndRMT7FDZEpMmwWCycf/75LFu2zNuliHiVYRiMGTMGw2xh0rv/ZcHmQzhcboKtFgJ9zVhMBsbRZg3AZBhYfcyEWC0E+Jj5/kApb32fQ2FFtRefQkREYUNEmpiBAweybNkyrTcgZzwXBimXjaTQHUjVkcP4WU7tlW02GYRYLZRXO5n3Qy755QocIuI9Chsi0qS0adOGgIAAtmzZ4u1SRLzqi91F5JQ6SG3VkkN5eRQXF/+m8wN8zThdbj7YmIetxtlAVYqI/DqFDRFpUgzD0JobckYYPXo0L7300nH3ZRVVsTG3lGCrGT+rldTUVLIyM6moqPhN9wjwNVNR7WRZRlF9lCwi8pspbIhIk3PBBRewevVqbDabt0sRaXRut5vPdxXiazZh+nFcRmBgIMnJyezevZtqu/03XS/Iz8zm3HKN3xARr1DYEJEmJzw8nI4dO2olZTkj5ZTaKalyYP3FGI2w8HBiY2PZtWsXTuepd4syGQYGbtbnlNZ3qSIiJ6V1NkSkSRowYACffPIJAwYM8HYpIo1i//79PPLIIyT17M/3GzYT0SKSxLTOrP3vIipKS4iIief8K28iKDiYjD17aJuSwvplH7N9zQoqS0uwBgaR3KkH51x2DT5+Vt5+9q906nMhvQYPw9/Xwve7c3jpoZH069ePRx991HPfESNGMHz4cK666iovPr2InK7UsiEiTdJZZ51FZmYmBQUF3i5FpMEdOXKEiRMn0qdPH9pfeAVmk8Gh/Rlkbv2Bi2+5hyvvepyaajvLPniL1q1b4wY++cfrrP/qP/S55E9c//Akzr9qBHs3r2Xp+38HICGlI3n7dgNgMRlkZ+wgJDyCbdu2ee6bk5NDcXEx3bt398Zji8gZQGFDRJokX19f+vXrx5dffuntUkQaVHV1Nc8++ywtW7bk3nvvpbCiGpNhYKsoZ+B1t9EiLpGohCTa9zqXokM5OGqqSU5qzc7vv6Z1l7NITT+b0MgYkjul0/uiK8nc8gMVpSXEp3Ygb1+GZxrpvL07ST+7H5WVlZ6FM7du3UpoaCjJycne/BGIyGlMYUNEmqyBAweydOlSrbkhp7Xp06djt9t54oknMJvNOFxuDCA8piU+flbPcf5BwQDYqyopKyrA6ueLT3A4RUU/zTQVk5iM2+2mMGcfCSkdqbZVcTj3AACHMnfRJq0D7dq187RubNmyhW7dutVZIFBEpD4pbIhIk9WuXTsMw2DHjh3eLkWkQaxatYqVK1dSWlqKw+HAMAzMJgM3YPHxrXvw0UDgdlNtq8IwmWiVlMy+ffsoKysD8ISTapuNoLAIwqJiyc3cTVV5KUcKD5GW1p6OHTuydetWoLZlIz09vbEeV0TOQAobItJkGYbhWVFc5HQUFhbGSy+9hNlsZubMmQC0CPDBdZLWPF+rPwBmA9q2bcuePXuoqqyk2lYFgJ9/7f6ElI7kZe0mJ2MH4bEJxEeG0rFjR7Zt20ZhYSH5+fkaryEiDUphQ0SatAsvvJBVq1ZRXa01AuT006lTJ5KSkvjrX//Kt99+yxdffEFCqBWn69fDRlhUHL5+VvKydhMSEkLrVq3YtWsX2Xt2YBgGkfGtAUhI7Uhe1h5yMnYSl5xKqNVC+/btyc3NZcWKFSQkJBAZGdkYjyoiZyiFDRFp0iIjI2nbti2rV6/2dikiDaZLly4MHz6c119/nQh32UmPN1ssdOk3mM2rlrJz7SrMOKkpyeerf88npXsfAoJDAYhP6UDFkWL2bPmBs9O7YhgG/v7+JCUlsWTJEnWhEpEGp3U2RKTJGzhwIJ8uXU5FeCr7iioptzsI8rPQOiKAc1MjCbH6eLtEkT/s5ptvZv369Xzw5iv4mIJMJ4sAACAASURBVMBxktaNsy66ErPZwvef/YuK0hICgkNp16MvsZ374HK5MJlM+PkHEBnfioP7Mhl2fm/PuZ06deKjjz6iW7duDf1YInKGM9wnmOYlOzvbMxNMQkJCY9clIgJAZmEFH67bz+xPv6NV6yR8fCyYDQOn243bDWaTwQVpUQzrFk9yZKC3y613+rf4xE7nn82uggo+3HyIEKvlt80U5XazNzMTh8NBamoqhmFQZnPQLiqQKzpFadYpEal3J/u3WN2oRKTJWrYjnwfe38DyPYeJDAkAWymRQX6EB/oSGeRHVLAfIf4Wlv543LId+XXOf/zxxxk3bpyXqhf5/VIjA+gYE0SZzfnbpn42jNo1M9xusrKyqKp24GsxMbhdCwUNEfEKhQ0RaZKW7chn2n93Emw1ExXkR3RUJIWFhfzyY5fFZCIqyI9gq5lp/915TOAQaY4Mw+CitEhiQ3wpt/+2wGEYBikpKVTaazhUUMC13WII9DU3YLUiIiemsCEiTU5mYQUzlu4mLMAHP0vth6Sg4GBcbjeVFRXHPcfPYiYswIeXlu0ms/D4x4g0J34WE9d1jyMpwp9Sm5Map+uUznO53VTUuGmbnEzJt/9iw0pNHS0i3qMB4iLidQUFBbz11lts2LABu93OoRpfHIm9iDy7PwD/ffFBOgy8Bvu+PSz/4m38rX6EJ7Sl46Dr8A0IAqCsIIdtX/yTw3nZ3LAkmmcfvMObjyRSL6wWE9d0jWFzXjlf7D6MrcaBxWzgZzFh+lm3KLfbTY3Tjc1RG0g6xwYxMCWCIx0eYOzYsYSGhnLuued66zFE5AymsCEiXvfCCy9gs9mYPHkybosfNz3/Hge/+TexMdFEJnUAYN8PXxGZ0hV378tJjo9h88dvs3f1Z7QfcDUup4MNi9/CNyCIc66/j/JqF1+tWMmBAwdISkry7sOJ/EGGYdA1Lpj20YHsyq9g/cEy8srsuIGjccPlhlCrhfSWwXRtGUyYf+0MbdaYGJ566ikmTJhAaGgonTt39tpziMiZSWFDRLzuoYcewmKxEBERwSebc4nscDaHNy/n8L6dnrBhDQ4nrd9lbN+xA0t4DOEJbTlyaD8AxdkZ2EqL6XrpCELjWuEos9Ozdw+2Pf+INx9LpF75mk10jgumc1xtl8IjVQ6qnS7MJoMQPwu+luP3jG7Tpg1jx45lypQpTJo0SQFcRBqVwoaIeF1NTQ3z5s1j69atbNibS+6RKixuJw5bleeYkNhEACLCw6koL8c3IIjKkkIAyg/nARAU1RIAw4B8OyQmJjbyk4g0DpNhEB5w6uvLdO3alTvuuIOJEyfy/PPPEx0d3YDViYj8RGFDRLyqqqqKxx9/nKCgIO68804W7arkh/0lZHw6u85xZosvABaLhfLycgx+6q/urLaDYWC21H74MhkG5TYHVqu18R5EpIk777zzKCkpYcKECfzv//4vwcHB3i5JRM4Amo1KRLxq8+bNFBcXc++999K7d28SEhLwCWlBja3yuMe73O5j1gsw+/iC243TUeM5JshqoeIEM1eJnKmGDh3KOeecw8SJE7HZbN4uR0TOAAobIuJVDocDgJCQEABaRwRQlLUdh70K9zGraoDb5cJkqvtPV0B4bZeQ0h/HcLjdEGbYOHDgQEOWLtIsjRgxgvj4eKZOnYrT6fR2OSJymlPYEBGvSklJwWQysWjRIg4dOoQpfye565cR0jKJisN52MpK6hzvPk7LRkSrVHwDgtm9YgnFeQewFR3kh0/mExYW1piPItIsGIbBvffei8vlYtasWb9thXIRkd9IYUNEvCo6Opq7776bNWvWcPfdd7Pyq6Xceue9hLY/h4qifDYuqTt2w+VyYfyiZcNs8aH7sFG4nE6+nT+d0m//yaALLyA1NbUxH0Wk2bBYLDz22GNkZWUxb948b5cjIqcxDRAXEa8bMmQIQ4YM8fw5s7CCNYfcJHfq4VlB/KijLRudLvpzne2hca1Jv+5+yu1OXry2O8mRgQwePLhR6hdpjqxWK0899RSPPvoo4eHhXH755d4uSUROQ2rZEJEmJzkykPsHplJSWYPdUbdPucvtrrNy8lF2h5OSyhruG5BKcmRgY5Uq0qyFhoYyceJE/vnPf7Jq1SpvlyMipyGFDRFpkga0j+bBwWmU2ZwUlNtxuFwAuF3uOt2oHE4XBeV2yu1OHhycxoD2Wj9A5LeI+XGV8VdffZXNmzd7uxwROc0obIhIkzWgfTTTr+vOoPYxlFY5KCizU+6AKodBYbmdgjI7pTYHg9rH8OK13RU0RH6no6uMP//882RlZXm7HBE5jWjMhog0acmRgdw3MJVbz01i1e5C3v9PFtbgcNI7x9EqPIBzUyMJsZ76Ssoicnxdu3blzjvv5Omnn2bq1KlaZVxE6oXChog0CyFWHy7pEsfuL4tIaxvFRee39XZJIqedfv36UVxczIQJE5g6dapn/RsRkd9L3ahEpFlxOBz4+KglQ6ShHF1l/JlnntEq4yLyhylsiEizUlNTg8WiRlmRhjRixAgSEhJ4/vnncTgc3i5HRJoxhQ0RaVZqamrUsiHSwAzD4J577gHQKuMi8ocobIhIs6JuVCKNw2Kx8Oijj7J//36tMi4iv5vChog0K+pGJdJ4jq4yvmrVKj766CNvlyMizZDChog0K+pGJdK4QkJCeOaZZ1i4cCErV670djki0swobIhIs+JwONSyIdLIoqOjeeqpp3jttdfYtGmTt8sRkWZEYUNEmhW1bIh4R3JyMmPHjmXq1KlkZmZ6uxwRaSYUNkSkWdEAcRHvObrK+MSJE8nPz/d2OSLSDChsiEizogHiIt7Vr18/rr76aiZMmEBpaam3yxGRJk5hQ0SaFXWjEvG+oUOH0rdvXyZOnKhVxkXkVylsiEizom5UIk3DzTffTGJi4klXGa9xusgrs7O/uIoDJTaO2Gq0SKDIGUR9EUSkWVE3KpGm4egq45MnT2bmzJncf//9GIYBgK3Gyfb8CtZll3K4sgaT8dN5bsBiMkhtEUCPhBBahvh5zhOR049aNkSkWVHLhkjTcXSV8ezsbN555x1cbjfrc0qZ9c0BPt91mLJqJ8F+ZoL8LJ5fwX4WfM0mtudXMO+HXN7dkEdJVY23H0VEGojChog0G263W2FDpImxWq1MmDCBb75bw9RFq/lsZyE+ZoMQqwWrxXTcVguzySDYaiHYz0zOERt//z6HnfnlXqheRBqawoaINBtOpxOT6fgfXkTEe6wBQfS44a9kFVXhqCzDx3xqHy8MwyDIz4KP2eDfWwvYocAhctpR2BCRZkOrh4s0Tf/dfZiiaoPUVi3Zv3/fcafEXfP5v3lt7Ojjnu9rNuHvY+KjbQUUVlQ3dLki0ogUNkSk2dC0tyJNT2ZRFZvzygn2MxMQGEhK27ZkZGRQWVn5m67jYzZhAEu2FeB0abYqkdOFwoaINBuaiUqkaXG73Szbcxhfs4Hpx+6NwSEhtG7dml27dmG323/T9QJ8zRwqryazqKohyhURL1DYEJFmQ4PDRZqW3LJqCitqsFrqfpyIiIggLi6OXTt34qg59ZmmDMPAbDL4/sCR+i5VRLxEYUNEmg11oxJpWjIOV+J2u487aUNMTAzhERHs2r0bl9N5ytcM8DFxoMSG3eGqz1JFxEsUNkSk2VA3KpGm5UCxDV/LiT9KJMTH4+/vz549e0551XDDMDAZaKC4yGlCYUNEmg21bIg0LYWV1b8+za1hkJSUBIZBQUHBKV/X7YYSm+OPFygiXqewISLNhqa+FWlaXG442ao3hmGQkpKCy+WmsqqqNkmcyrU1I5XIaUFhQ0SaDbVsiDQtPmYD1ymEB5PJRHRUJE6ng/379588cBhgMWvxTpHTgcKGiDQbmo1KpGmJCfKlxnlqLRAms5mgwCDKy8tPGjgMIMJff9dFTgcKGyLSbGiAuEjT0irMH4fz1GeNMgyDtLS0Xw0cR7tPtQj0rbc6RcR7FDZEpNlQNyqRpqVdVAAYxinPNAVgtlh+ChwHDhwTOCqqnXSIDsRiUjcqkdOBwoaINBsaIC7StIT5+5AUbqWi+uTraPQeMpw7p74J/CxwlJXVCRwutxs30CMhpCHLFpFGpLAhIs2GWjZEmp6BqS0AcPzG2aOOFzjK7bWtGnHBfg1Rqoh4gcKGiDQbGiAu0vREBvpyXnI4FXbHKc1M9XNHA0dZWRmZ2Qfx9zExKLXFcVckF5HmSWFDRJoNtWyINE1ntwqle8sQymxOnL+jhaNVm1QqKyow7VqBv48+moicTvQ3WkSaDY3ZEGmaDMPgorQW9EsOo6LaSUW185QGjTtdbo7YHIQF+PLIZT3J2LyOt9566zcNOBeRpk1hQ0SaDbVsiDRdhmHQLzmcW3q2JDLAhzK7k1KbA7vD5ele5Xa7cbjcVFbX7rM5XPRtHcbI3vG0jg7j2WefZfPmzQocIqcRhQ0RaTYUNkSavtgQP27p1ZJberakR3wwwX5myn8MHqX22m5WiWFWLkprwT19Ezm/TTg+5tqPI0FBQUyaNInNmzcze/ZsBQ6R04D6I4hIs+FwOLBard4uQ0ROwjAMYkP8iA2pnVXK6apt0TAZYDEZvzoAPCgoiGeffZbx48cze/ZsRo4cqQHjIs2YWjZEpNlQy4ZI82Q2GfhZTPiYTacUHIKDg3n22WfZuHGjWjhEmjmFDRFpNjT1rciZIzg4mEmTJilwiDRzChsi0mzU1NRoNiqRM8jPA8ecOXMUOESaIYUNEWk21I1K5MxzNHBs2LCBt99+W4FDpJlR2BCRZkPrbIicmY4GjvXr1ytwiDQzChsi0myoZUPkzPXzwDF37lwFDpFmQmFDRJoNDRAXObMdDRzr1q1T4BBpJhQ2RKTZ0ABxEQkODmby5MkKHCLNhMKGiDQb6kYlIvBTC8fatWsVOESaOIUNEWk2NEBcRI4KCQlh8uTJrF27lnfeeed3BY6KKjs5+SXszy0it+AINntNA1QqcmbTW1tEmrRSWw2rdheyr6iSzUZrFmw9Qro9l3NTIwmxqpVD5Ex2NHA8+eSTGIbBTTfd9KsrlFdU2Vm+ZherN2ayeVcO+UVlmE0GhmHgdrtxudzEx4TTNS2efj1SOKd7G3x99FFJ5I/Q3yARaZIyCytYvDGHL3cW4HK5MQzINyJYkVXG6pwMXl+xlwvSohjWLZ7kyEBvlysiXvLzwAEcN3Dk5Jfw/n/WsvjLjTgcTiwWEwH+fsS0CK5zrMvtprS8is9WbuWTr7cQFODHtRf34srB6YSHBDTqc4mcLhQ2RMTrRo8eTbdu3bjvvvsAWLYjnxlLd+PGTXiADxZTbY/PHJediEBfrH5+OFwulu7IZ9mOAu4fmMqA9tHefAQR8aITBQ6n08WH/13PzPlf4nC6aBEaiI+P+YTXMRkGAf6+BPj7AmCz1/D3D1fx/qdreWLMJZzfK/VXW05E5FgKGyLiddOmTfMM/F62I59p/91JWIAPfpa6HwpcbjemH1/0FpOJqCA/7A4n0/67E0CBQ+QMFhISwqRJkxg3bhwAl1x+JeNm/JuNO3NoERaIn+9v/8hj9fMhzs+Hiio7j7/4Lwad04EnxlyC1U9dOEVOlQaIi4jXhYaGEhAQQGZhBTOW7j5u0ABwu1zHfKvoZzETFuDDS8t2k1lY0Vgli0gTFBoayqRJk/hq5XdcfvsUtu45SFxUyO8KGj8X6O9HTIsQlq7ewV+nfEBFlb2eKhY5/allQ0TqxcaNG5k3bx779u0DoE2bNtxyyy106NCB6upq5s6dy/Lly7HZbKSkpDBy5EjatWsH/NSNyt3pYty4qTlSyLaVH1Gatx9nTTVhLZNJu2B4bcuGycTBbd+z9bP36HvrY+xYtpAjuftwmv2YlH8pbz59j6emLVu2MGfOHDIzMwkLC+OCCy7gz3/+s2dGq+3btzNv3jz27t2L2+0mPT2d22+/nYiIiMb/AYpIvXCbfCj27cDBQ9uJiwYIqZfrmkwGMS2C2bQzh8en/YsXxv5Jg8dFToFaNkTkDysvL2fSpEmkpaUxY8YMpk2bRkJCAhMnTsRmszFr1iy+/fZbHnnkEWbMmEFsbCwTJkygqKjIcw1bjZMvdxYQaFSzbsEsnNV2ul9xG72uvRcMg3ULX8VZbavTsrF96QJapfenz00PE5/WjY8Xvsv6LdsAOHDgAE899RSdO3fmpZde4q677uKTTz5h7ty5AGRnZzNu3DiCgoKYMmUKTz/9NHl5eTz11FO4XK7G/QGKSL1wu908//fPOFRUQfcuaRQXl5CTk0N9LcNhGAYxkcGs2bKPdxavrp+LipzmFDZE5A87ePAgNpuN/v37ExcXR0JCAnfccQdPPfUUNpuNL7/8kptuuomuXbvSsmVL7rzzTnr27MmhQ4c819hbUI7T5ebQtu+psVfR9bJbCI1tRUh0PJ0vvoEaWxVlB3ZgmH76Zyu+09lEtelIQFgkKX2GAPDR1z8AsGTJEiIiIrj11luJj4+nZ8+ejB492nPu4sWL8ff35+GHH6Z169a0b9+eBx54gKysLNatW9dIPzkRqU9ffreT5Wt2Ed0iGB8fH9q3T6O4uKjeA0dURBCz//UNu7IOnfwEkTOcwoaI/GGtWrUiOjqaKVOmsHDhQvbu3YvFYqFDhw5kZGTgdrtp27at53g/Pz8eeeQROnTo4NlWVFmDyYDSvP0EtYjFNyDIs8/XPwj/8CgcZUU4nU7P9pDYRM/vffxrp789kF/bWrJnz5469wQYOHAgo0aNAmDnzp107NixzorkrVu3Jjg4mL1799bHj0VEGlF5pZ3n//4poUH+nokkagNHe0/gqC8+FjM+FjPPvvqxVi8XOQl1NhSRP8xqtTJ16lQWLlzIkiVLmDNnDtHR0YwcOdITDqxW669eo9rhxGwYOKptlBUcZNnMx+rsLy09gm9ES7IyM/H/cZvZ4uvZf7R7la269n7l5eUkJiZyIlVVVXz//fdcc801dbbb7XaKi4tP6blFpOlYtno75VXV5GxYRGhkPCndBwA/BY4dO3ZgGBAfH18v9wsPCWBvdiGbduXQLS2hXq4pcjpS2BCRetGiRQvGjBnDmDFjyMzM5IMPPmDq1KncdtttAFRWVv7q+b4WM3a3G4ufP8FRLel62S2efcXFxeTl5ZHWoSNZ2blUlx454XWsvrWzWIWGhv7qPQMCAujRowe33377cfeJSPPhdruZt+R7Av19j7v/54ED6idwGIaB2WTwwSdrFTZEfoW6UYnIH5abm8uaNWs8f05OTubuu+/G7XYTEhKCxWJh27Ztnv0Oh4Mnn3ySb775xrMtIsAHlxtCYhKpOlKEb0AwAWGRWAJDOVRSTqvERAJCwmjbti0FBQU4XU6Op0Vg7YeNtm3bsmPHjjpdHL744gueeeYZANq1a8fBgweJjY0lLi7O88vhcBASUj+z14hI49iVdYjc/CMEBfid8JijgaOoqP66VEWEBbJi3W7KKmz1cj2R05HChoj8Ybm5uUyePJklS5aQl5dHbm4uCxcuxNfXl86dO9O/f3/mz5/Ppk2byM3N5W9/+xt79uzxTH0L0CYqCLPJIKZDbwyTwZZP53Hk0AF2bv4BCvayceFMig/swd/fn6ioKCoqKuvMGuVw1v4+LTYYgMsvv5yysjJeeeUV8vLy2LBhA2+//TYtW7YEYOjQoeTn5zNr1iyysrLIycnh7bff5r777uPAgQON+NMTkT9qV1Y+Lrf7mHV4Ko4UsG31R3z3nzdY/fHf2LF6MbEtAikqKmLX1nV8s/gVyorz6pxTVnyIbxa/QnH+fgBKi3LZ+s0ivv/0Tb7/5O/sXPsZ1bbaNX3MJhOGYZBxoKBxHlSkGVI3KhH5w3r06MHdd9/NokWLmD17Nj4+PiQlJTF+/HgiIyO58847eeutt5g6dSp2u53k5GSeeeYZIiMjPdew+pi5MC2KpTvy6XXNPez6ejHf/GMatsoqYpNT6XLpCFq0TgMgNCwUs9lMdnYO7UJr18QorqohMsiPgB8X74qPj+epp55izpw53HXXXYSGhjJw4EBuvPFGABITE5k0aRJz587loYceAiA1NZVnnnmGVq1aNeaPT0T+oI07szGb635/Wm2rYOs3iwiJjKfzucMxTGYOZmxgzw+f0+GcK9ifU0CN001RbibB4bGe8w7nZuDj509YVAKVZcVs+3Yx4dGt6dx3OE5HDZlbVrBt9RK69b8GwzBR43CRsb+A7u1PPEZM5EymsCEi9WLw4MEMHjz4uPusVit33XUXd91113H3v/nmmwBkFlawbEcBPqFRdLr0Fti2jQ7t2+Pv71/n+PiOZxGT1pOtW7ZQVFxMYHAIJsPgo48+Ijky0HNc9+7dmT59+glr7tixI1OmTPmtjyoiTcy2jFwCrD51tuXv34HL5SSl+0AsPj92r+x2ISUF2RzO3kmHjuey+uBWDmRspnXHczznFeXupUXLFAzDRG7mJswWX1J7DMZkrh0PltJ9ABu+ep/i/P1ExCTh62Ni8+4crh7So/EeWKQZUTcqEWkykiMDuX9gKiWVNezOzCIuNvaYoHGUxWymbdu27M3aT2FpFfcNSK0TNETkzFFRacfyYxg4qvxIPgHBEZ6gAbWDuoNCI6k4UoiPjw8duvelorSI3ds3UV5eQWnRIWwVpUTFp9Zeo/gQwRGxnqABEBDSAouvH5VHCgEwm02UlWvMhsiJqGVDRJqUAe2jWb16NQvcZixBEThcLiymY78XcThdVOFDaItoInNX0z/1fC9UKyJNgcvtOmab01FdZ3rso8wWX5yOEgBaxLQiJKwFB7O2Y3eaOLx/M/aqGrIPlWA9YqO87AhHig5RlPcaJrMJg9oxIU5nDdX22tnuDAycrmPvLyK11LIhIk1KdnY2Wz5/j9du6cOgDjGUVjkoKLNTWG6nqKKawnI7BWV2Sm0OBrWPYc6dA0j2q+S9997zduki4iV+vj51JowAsFj8cDjsxxzrcFRj/rG1wzAMAiMSMGpK6dy5M8FWNykde9KyZRwBAf64MWH4huAb3RUjrD2+0V0ITuxFTPsL8Y9oQ3l5OdU1Nfhbjz/lroioZUNEmhCn08m0adO46aabOKtDMmd1gFvPTWLV7kL2F1dSbnMQZLXQKjyAc1MjCfmxj/aDDz7IAw88QNeuXenSpYuXn0JEGlvbxEi+35xV50N/YFgUxfn7cNTYsfjUTonrdrmoKMknIq6N5zifoCic2TsoKcjGVl5CbK+LCAgJJTQ0lPJWKZQW5tD9rHNwudzY7TZsNhslh/OoqLJRVLKP4vJqnIe382jeauLj40lISPD8b0xMDBaLPmrJmU1/A0SkyViwYAGBgYFccsklnm0hVh8u6RL3q+eFh4dz//33M23aNGbMmKF1MkTOMN3bt2LFuj11tsW06sjBjA3sWvdfWnc8BwPI2bMeR42d2KSfvpRwGlb8A0PYt20VASEtCAhp4dkXl9yFggM72LtpObHJXTCZzJQd2smhjI10638tAcERFBSV8+TtA4kLM5OTk0NOTg6bNm0iJyeHw4cPEx0dXSeAxMfHEx8fT0hIyDFT9YqcjhQ2RKRJ2Lt3Lx999BHTp0//XS/gHj16cN555zFjxgzGjRunl7jIGSQ1KRrLL6a+9fHzp1Pf4WRtXcXmFQsBN0FhMXQ8ZxgBweEAuFwubDYb0Ylp5GVuonWHPnWuERAcQcc+w9i/YzWbVywAICgsmo59hhIQHIHb7cblcpHeOYXoiGC6du1a5/zq6mry8vLIzs4mJyeHLVu28Nlnn5GdnY1hGMcEkMTERGJjY/HxqTuzlkhzprAhIl5XU1PDtGnTGDVqVJ21N36rESNGMHbsWJYsWcLQoUPrsUIRacq6tovHz9cHe7WDnoNu9mwPDGlBp3OGnfC8yspKrFYrbTr3ok2Xfsc9JqRFHJ3PvfK4+0rLbaQmxRAdEXzc/b6+vrRq1eqYtXvcbjelpaWeEJKdnc3SpUvJyckhPz+fyMhITwD5eRgJDw/XFynS7ChsiIjXzZ8/n7i4OC688MI/dB2LxcIjjzzCww8/TKdOnWjTps3JTxKRZs/Xx8I1F/Xg7UWriY089W6UFRUVBAb+/imzbdU13DT0rN98nmEYhIbWjgvp1KlTnX0Oh4NDhw6RnZ1NdnY2u3btYtmyZeTk5OBwOI4JIQkJCbRs2RJfXw1Sl6ZJYUNEvGr79u0sXbqUl19+uV6+sYuLi2PMmDFMnTqV6dOnY7Va66FKEWnqLr+gK+8s/o4ahxMfi/nkJ1AbNoKCgn7X/Spt1QT6+9GvR8rvOv9ELBaLJ1CcffbZdfaVlZV5xoVkZ2fz9ddfk52dTV5eHuHh4ce0hCQkJNCiRQu1hohXKWyIiNfYbDamT5/OnXfeSWhoaL1dt3///qxfv57XXnuNBx54oN6uKyJNV8voMG4adjZzF31LbOSp/XtSUVFBTEzsb76Xy+2mpKyKZ+8dhp9v442vCA4Opn379rRv377OdqfTSX5+vqdbVlZWFitXriQnJ4eqqipatmx53EHq+jJGGoPChsj/s3ff4VGVaR/Hv2d6ZtIzmSQkpJFGaBEQARtSRFBYxLK67q4FF11FUBHbvrur2AVBFlbFiq59ZQsqoDSliQhKDQmBBEgmgUkvk8xkynn/QLNGQIokE8j9uS6uNVPOuWc2mZnfPM9zPyJg3nzzTTIyMhg8ePBpP/btt9/O3XffzRdffMGQIUNO+/GFEB3PTeMGserrfByV9USEmX/2tj6fD7e7maCgoJM+T3lVPRf2S2PYwKzj37gdaLVa4uLiiIuL49xzz211ndPppLS0tCWIrF+/HrvdTmlpKSEhIUdMyUpISCA6OlpGQ8RpI2FDCBEQW7duZcOGDcydO7dNjm8ymbj//vv585//TGZmJnFxP98+Vwhx5jMa9Ey/ayy3/fVtGhrdBJuNx7yt0+nEbA5Cozm5D9XVi3zodQAAIABJREFUtU4iQs3cf8vIM+IDucViIT09nfT09FaXq6pKeXl5q0XqGzduxG63U1dXR5cuXY66SP2XrHERnZOEDSFEu3M6ncyZM4dJkyad8nzpE5Gamsp1113HjBkzePbZZ2VzLSE6gYzkGGbcfzX3Pv1PQCXYfPSpQqeyOLyqxonJqGfe/12PNaLtXrvag6Io2Gw2bDYbffv2bXWdy+VqtTZk06ZN/Oc//6G0tBSTydQyAvLjMGKz2dBqT2ytjOhc5J1XCNHuXn31Vfr160e/fv3a/FxXXHEFW7du5a233uKWW25p8/MJIQKvf48k/vanX3PfjI9wVNUTHRF8xCiE0+kkPDz8hI7n8/spr2ogOjKEOQ/9mqQukW1RdodhMpno1q0b3bp1a3W5qqpUVla2CiLfffcdJSUl1NTUEBMTc9RF6iEhR28NLDoHCRtCiHa1ceNGtm/f3mbTp35KURSmTJnC5MmT6dOnT7sEHCFE4OVkdeXdGbfyzKtLWf9dIaHBJixBhpbQ0dDgJD4+4WePoaoqtQ1NNLk8jBuWwx3XD/nZqVlnO0VRsFqtWK1W+vTp0+q65ubmVmtDtm3bxuLFi7Hb7S0dtn66SD02NlZGnDsB+X9YCNFu6urq+Pvf/860adNOaVHmqQoJCWHq1Kkt7XAjI8/ubyWFEIfZIkOYOe1qPl+Xy/wP1+CoqkOj0WAx6fD5fEftxqSqKs0eHzX1TaCqpCXZmHTDJfTvkRSAR3DmMBgMJCcnk5yc3OpyVVWpqalpGQkpKSlhx44d2O12KioqiI6OPuoi9dDQ0DNiTYw4PgkbQoh28+KLL3LRRRfRs2fPdj93z549GTlyJLNnz2b69OnyJiZEJ6EoCiMv6MGl52fz3a5i/vnZZlZ+tR1FF0RFdT1+9fAHYo2ioGgU/D4/ocFBXHFxT8aP6Et6kk1eL34BRVGIiIggIiLiiNd+j8fDwYMHW0ZDdu3axfLly7Hb7fj9/iOmY8XHxxMXFycbGP6Iqqo0NPuobvTg8atoFYXwIB1hJl2H+b2VsCGEaBerV69m//793HPPPQGr4brrruNPf/oTCxcu5Oqrrw5YHUKI9qcoCn2zE+mbnci7MU1U1MTRb9BQ6hqa8Hr96HVaIsMtpCVGExkmHZfag16vp2vXrnTt2vWI6+rq6lp1ylq5ciUlJSU4HA4iIyOPukg9IiKiw3zAbmvVjR62ltWztbQel9fP/5qqKaiqilaj0N1moW98KDEhhoA+LxI2hBBtrqqqipdffpm//vWvAf1GSqvVct9993H33XfTq1cvMjMzA1aLECJw9uzZw/Dhwxl8Trfj31gERGhoKNnZ2WRnZ7e63Ov1cujQoZZF6nv27OHLL7+kpKSE5ubmo7brjY+Px2g8O9baNHv9rC6qZnNJHQBBeg0hRu0RYcLnV9l+sIHtBxtIs5oZmRFFsDEwH/slbAgh2pSqqsydO5dRo0Yd0ec9EKxWK5MmTWLGjBnMmTNHesYL0cmoqsru3bu54447Al2KOAU/LDaPj48/4rqGhoaWkRC73c7atWspKSnh4MGDhIWFHXWRutVqPWNGQ6obPXyw9SC1Li/BBu3P7hGj1SiEmnSoqsreikZerXFxVa8Yuoa3/67xEjaEEG1q+fLlVFVV8etf/zrQpbQYOHAg3333HfPmzeP+++8/Y95ohBC/XHl5ORqNhqioqECXIk6z4OBgMjMzjxi19vv9OByOliCyf//+lp3UnU5nywaGP52a1Z6NTI6npsnD29+W4fb6CDWd+Md3RVEIMelweXx8sKWMX+fEtXvgkLAhhGgzDoeDBQsW8OSTT3a49oYTJkxg6tSpfP7554wcOTLQ5Qgh2klBQQHp6enyJUMnotFoiI2NJTY29oj2542NjS1Tsux2Oxs2bMBut1NaWorFYjnqInWbzYZGo2m3+n1+lX/tOMSy91+hqngvNzz4zEkfw6TX4vL4WLj9EBPPS8BsaL8NGDvWu78Q4qyhqirPP/8848ePJymp47WMNBgM3H///TzwwANkZ2cfdYGiEOLs80PYEALAbDaTnp5+xO+EqqpUVFS0tOu12+1s2rSJkpIS6urqiI2NPeoi9baYmruxuBZHfTMG7ckFnE9efY60nPPI6n8BcDhw1Lu8LC+oZGwP22mv81gkbAgh2sTHH3+M1+vlyiuvDHQpx9S1a1duuukmnnnmGWbNmiXtFIXoBAoKChg/fnygyxAdnKIoREdHEx0dzTnnnNPqOpfLRWlpactoyLfffsuiRYuw2+0YjcYj1oX8sIGhVnvyowlur591+2qwGHWczGCcqqo4DhSRlnNeq8uDjVp2OZwMTm7Gammf9zwJG0KI085ut/P+++/z3HPPtetQ86kYMWIE3333Ha+99hp//OMfA12OEKINqarKnj17ZGRD/CImk4nU1FRSU1NbXa6qKlVVVa0WqW/dupWSkhKqqqqIiYk56iL10NDQI87hcDiYO3cuX327lWqvnr4XjWh1fWVZMRsWf0RZ0W78fj/h1hj6jRhLt179AXjx/lsAWPnBa6z84DXumPEGPq+Xr5cuJHfzBj72NZGeYGPw4MHceOONbfplm4QNIcRp5fP5mDVrFjfccANxcXGBLue4FEVh0qRJTJkyhfXr1zN48OBAlySEaCMlJSWEhIQc9cOdEL+UoihERUURFRVF7969W13X3NxMWVlZSxDZvn07S5cuxW63o9FoWk3FSkhI4I033sDj8XDZLVOp9evJX7+MA3nb0RtNqKrK4tfnEG6LY/yk/0NnMJC/aR3L3n6J8LsfISougV/fO50PZv2FC8ZeT1qfAQBsWr6I3K+/ZOj1txMZG8+oeJgxYwYGg4Ebb7yxzZ4XCRtCiNNq4cKFmM1mRo8eHehSTpjFYmHatGk89thjpKenEx0dHeiShBBtoKCggIyMjECXITohg8FAUlLSEWsYVVWltra2ZSTEbrfz0UcfsXTpUpKSkjBWuzHqfaQOGErB1k2g0eLxeBg78T6M5mBMlmAA+g0bw+blH2Pfu4uouASCLCGHzxtkxhwaDkDvC4aT1f98QqNs1Lt9ZGQncu655/Ltt99K2BBCnBmKiopYtGgRzz///BnX6SUzM5Nx48YxY8YMnnrqKbRaLXUuD+sKKthf1UiD20uwUUdSpJnz062EmvSBLlkIcZJkcbjoaBRFITw8nPDwcHr27AnAhg0byM/P57nZc/hgrwetz43L5SLYGkv1ITs7duyg9pCd4u0bqa88hN/TjEarwe/z4m50HvNcWp2eXRs/o2jnd9TV1LAm1IAOX5u3gZawIYQ4LTweD7NmzeLmm2/GarUGupxTctVVV7F161bmvfkhJPVjVX45fr+KooBWUfCpKqoKL68pZEhmNGP7xJNilU0BhThTFBQUcP755we6DCF+VlNTEwDGIDNGQxMhJjN+n4/IKCvu+mrCg82sfutDLBHRpA8agaI34vX52bH0vZ897vJ352Pfm8cFv/oNIbFJXJUTz4pFH5GXl9emj0fChhDitHj//feJiYlh6NChgS7llDz//PPk5uZyxcQH+NN764it3E8Xayi6oyxw9/r9rMhzsDKvnCnD0hma1X4tBIUQp8br9bJv3z7S0tICXYoQR3A6nRw6dIjy8nI2btzIgQMH+PvcOTizL6O5vga/30+ZvZimpiYKt29G9XkZdeMkwqNsGI0GfJ5mitb895jHdzc1sj9vGwNGXkn3ARfR4PYS36ULbre7zR+bhA0hxC+Wn5/P559/zty5c8+46VM/VlrTxMtflZKSEIf9wD7iInvCUcKGTqOheNmbRKX1ZtYyP4AEDiE6uH379hETE4PJ1L67Jwuhqip1dXU4HA7Ky8tbQsWhQ4dwOBw4HA78fj8xMTHYbDZ0Oh0Gg4GELnE0d4lBo01Ar1HZtmgBYWFhWK1RGE0m4hIS0X6/YW7eN6tbzvWTkx/+H78fVVUxWUJQVRW/CppmJ1u2bGnzhgkSNoQQv4jb7Wb27NncfvvthIeHB7qcU1bZ0MwOey0XmPUYdSaanFEUFRaRnpHOT+OTqqrUHjxAbGYO4WY9f1tZQIrVIlOqhOjAZHG4aCuqqlJdXX1EgPjxP71ej81ma/kXExNDr169iImJITo6muDg4FZf1pWVlbFjxw5yUvpR7FTZve4zdN+3p41JPNxy97tVi8nsN5gDu3ewf9c2wiKjqSg9QGN9LYYgM4qiYN+bjzU+ifDoWMKibOR9sxZrYjpaTxNPPfExgwYNYt26dezfv5+EhIRT2gvkeCRsCCF+kTfffJO0tLQzah70D/3Lc3NzCQ4OZsyYMeworUEFjDot9eWlVGxayoG8LezR64iM7UrKeZcSk364leHy56cCsPOz9+Gz98n5w1P859sDhJV8xerVq6mtrSU8PLxd+pcLIU6MLA4Xp8rv91NVVXXMIFFRUUFQUFCrMJGYeLjTU3R0NDabDbPZfFLnfPDBB5k3bx7/fekZKrx6zrlwGCZLMPt3bSUuJYMBl17JjvUr2PLlEhIyejD8+onkbVrHxs/+xZp/v83I399JzkWXsX39Cvbv2sq19zzK8Osn8sXCN/loziP06JbIQ1PuIDo6mh07dvDAAw/wwgsvEBkZedqfPwkbQohTtm3bNtavX8/cuXMDXcpJefbZZ6mpqWH69OmEhoby3ocfsWnTtwQFHe5fvmXRa1gibFx44/3sKdxHiK+W7YvfwnLDVIKtcQz87X1seHsmmUPGEZORg9ak55133yOxYRf/9/BDJCYmUlJS0i79y4UQJ6agoIBRo0YFugzRAXm9XiorK486vcnhcFBZWUloaGirMJGens7gwYNbfjYajae1pvj4eJ566in8qsr8r4pxef2Y9Fou+NVvAOg/Yiz9R4xtdZ+ci0eSc/HIlp8HXXEtg664tuXn4PBIrrr7UdxeP3cO7kqQ/vAoxhtvvHFaa/8pCRtCiFPS2NjInDlzuOuuuwgJCQl0OSfMbreTn5/PtGnT6NGjBwA9hl8LH37eMoTd76o/ojcGoQ+ygDGYkuLiwzvDFu8h2BqHwXy4r7nOaMJoOTzXNbrHYK7qN56+fXMAsFqt7dK/XAhxfC6Xi7KyMlJSUgJdigiA5uZmysvLjznNqaamhoiIiFZhokePHgwZMoSYmBisVit6fWDanWsUhcuyovlgaxkGnQbNL1gXqaoqzmYvw9KiWoJGe5CwIYQ4Ja+++irnnHMO/fr1C3QpJ6W4uBiA1NTU/11W4yLY1hV/fTmKouBxNVKw5mPqDhXjcTVS39CA6vPgcR27f7lGp2PZ8mWs/ed8qqur8fl8eDyeNu9fLoQ4/CGq5FANew84yN1bRl7hQRpdzaAoBJsNRJoVdKEJlFc7iYsOC3S54jRzuVytgsRPQ0V9fT1Wq7XVeomcnJyWBdmRkZHodB33I3FKZBB94kLZWlZPqFF7yo1YGtw+4kNN9Eto2wXhP9Vxn1khRIf1zTffsG3btjNu+hT8qH/5j4a8G9xedAYjzUBjbSVff/A3DKFWwrMG40aLBYXydQt/9riFK96npK6EmX+eSkZGBgaDgbfffrvN+5cL0Zk1uZr5ctNu3v54I/vsFWgUBb9fxWTUo9UqqCr4/H7KDpbj8+m45u75ZKd14YYrBjAoJxWDXj4GnQmcTufPLr52uVwtayN++DdgwICWxdeRkZFojtJZ8EwyIiOKhmYveyubCDFqT2qEQ1VV6t0+osx6ruoV84tGR06F/JUJIU5KfX098+bNY9q0aQQFBQW6nJP2Q8j4obd4c3MzDdUV1FVX4q6tYcOyRdTX1tJrxE1E2mIJCQlBUX18+c2iYx7T426ien8eY666lhEjRrRc3h79y4XojFRVZcWGPJ597TMaXc0EGfXYIkOO+Y1vxSEv1qhwrFEh7D3g4E/P/4eIMDN/um00A/ukHvU+on2oqkpDQ8Mxg4TD4cDn87UKEjabjczMTKKjo4mJiSEsLOyMbrt+InQahSt7xrCyoJJvS+sxaBVMOs1xH3ez10+Tx0e3KDNXZEe36/SpH0jYEEKclBdffJELL7yQnj17BrqUUxIeHk5NTQ1z587F7/dTVFQEXfvgLC8mJDiEpK5d8RWHkJaZhUZ7+CXywJY1h+989Pbl4PcDKokx/9s5vaampl36lwvR2VRUN/DMa5+x9ts9hIcEERN1/L8xp9NJfHwXFEUhPPRwV6B6p4t7n/knoy/qyZTfDSPEIvtvtAVVVampqTnq9KYf/mm12iPawvbs2bPlv3/aFraz0mkULs20kmmz8Hl+BVVNXgCMOg16rYJGUVBVFY9Pxe3zo6pgNmi5IjuaHjGBew4lbAghTtiaNWsoKiri7rvvDnQpJ6y8vJydO3eSm5vLzp07KS8vx+VysWnTJu666y5uvfVWPvr3f9loCUFvMBCZkEohsO+blcRl96dyXz4VRbsICouivtyO21mPzhgEikJ1yR5CbfEYQq2YwqJw5G+ipOQi6uvreeWVV9qlf7kQncmBsiomPf4eVbVOYq2hJzQdxOv14vV6jtjML8RiwhxkYMmaneTuLeNvD1+HNSK4rUo/a/3QFvZYQaK8vByTydQqTCQkJNC3b9+WaU4Wi+xRdDKSIoK49bwESuvc5B5qoLjGRUWjB58fFAUig3SkWc1k2SwkRwSh1QQ2qEnYEEKckKqqKubPn89f/vKXDrtvhKqqHDhwoFW48Hg89OjRg+zsbEaMGEFqaioHDx5k3rx5vPnmm4SGhnL55ZczePBgvvp6IxHxqXQbdBnFW9exb/MqopIy6XXZDZTmfsOe9UvIW/Uv+lxxI0n9hlC8ZS0VRbmkjbuLG269k7rNnzBlyhS6dOnChAkT2qV/uRCdhd1Rwx8ffYfGJvcJjWb8wOl0Yjabj/qtrlajIdYaSsmhGu587F1e/OsNRIbJB98f8/l8LW1hjzY6UVFRQUhISKtRidTUVAYNGoTNZiM6Olp2bW8DiqIQH2YiPuzwc9uyK7hChxsFkrAhhDguVVWZN28el112WYfagdfj8bBnz56WcLFr1y5CQkLIzs6mT58+XH/99XTp0uWIF94f+pf/2LlDndz9wRbcXh+pAy8ldeClra5P6jeEpH5DWn7OuHAMGReOwe310eD2cesVOaTcNJKfauv+5UJ0Bi63h3ue+hBno5uokxx9aGhwHveb8+iIYOyOGh6a9W9e+Mtv0GrP7MXEJ8Pj8VBRUXHMPSaqq6sJDw9vCRLR0dFkZWVx8cUXEx0dTXR0dIf9AqozURQFbcfKGC0kbAghjmvFihVUVlby8MMPB7QOp9NJXl4eubm55ObmsmfPHuLj48nOzmbYsGFMmjTplEcPUqwWpgxLZ9ayfMLNh3cSPx6310dNo4d7R2SSYpVvQ4VoKy//cw12Rw2x1pNfA+V0OrFaj9+C2hYZwvYCO/9a9h3XXHZmtfT+OW63+5gLrx0OB3V1dURFRbWa5tSnT5+WxddRUVEdui2s6Pjkt0cI8bMcDgdvvPEGTzzxRLu/4VRVVbVMh8rNzaW0tJT09HSys7O59tpryczMxGw2n7bzDc2yATBnRQF1eIkw69EdpV2i1+enusmDRlG4d0Rmy/2EEKffjgI7HyzZdMrrKZxOJ0lJice9naIoRIZZmPfuKgbmpNI1NuKUztfeGhsbf3bxdWNjY6u2sDExMfTv37/VHhNneltY0bFJ2BCik6tzeVhXUMH+qkYa3F6CjTqSIs2cn24lxKhjzpw5XHnllSQnJ7dpHaqqYrfbW4ULp9NJdnY22dnZ3HHHHXTr1q3NA8/QLBspVgsfby1lVb4Dn19FUQ7v4upXVVQVtBqF4VkxjOnTRUY0hGhj8z9cg16nRXcKU5uam5tRVT8Gg/H4NwaMBh01dX7+sWgDD08cddLnO91+aAv7c3tMeDyeI9rCpqWltUx5ioiI6HBz+EXnImFDiE6qqMLJoq12VuWX4//+A7VWUfB9/4H65TWFxFGFv1nL+PHjT/v5vV4vhYWFrcKFyWRqWcx99dVXk5CQEJA3yRSrhcnD0rnp/GTWFVRwoLqRBpeXYJOOxIjDQSzUpG/3uoTobIoPVvNt7gFsUSEtl21e/g/CrPGk5Qw97v1/WK9xMi8jUeEWPlu7k0m/GUJocNvuJaSqKnV1dcdcfO1wOFAUpdWoRHR0ND169GiZ5hQScuz9RYToCCRsCHEWmjBhAn369GHy5MlHvX5lnoM5KwpQUY85VcjZ2MTqgioSEy/hi90Vv3iqkMvlallvsXPnTnbv3k1sbCzZ2dlceOGF3HbbbVit1uMfqB2FmvSM6hUX6DKE6LQ+XrUVoFWL294XXo2iObE20k6nE4vl5KZf6XRavD4/y9bv4qpL+57UfX9KVVWqq6uPufja4XBgNBpbBYn4+HjOOeecloAhbWHFmU7ChhCdzMo8x/eLoPXHXAStqir79xWRHBtFeEgQs5blA5xU4KitrW0ZscjNzaW4uJjU1FSys7O58sorycrKIjhYetoLIY7ty28KCP3JZnt644mPNjidTmJjY076vCaDjjWbC44bNn5oC3usxdcVFRVYLJaWIGGz2UhJSWHAgAEtayakLaw420nYEKITKapwMmdFwc8GDYCygwfRaDTYYmJQgHAz/G1lASlWy1HXKKiqysGDB1tNiaqpqSErK4sePXowYcIE0tPTpT2iEAKArVu38vbbb7N//34AUlNTufHGG+nevTvNzc289dZbrFy5ihVrtxNpiyM5ezAhEYdDw0+nUTXWV7E/9ysaahz4fV5CImNJ7nEBQcEROJ1OGqtLyF39LucM/Q2F27+kodqBVm8kLqUX8WnntNRUW2nnQO4GnHUVaPUmDhWm0nT3WGpqaigvL+ebb75h0aJFFBcX43K5sFgsLftI/HiaU0ZGBhdeeGHLdfK6Jzo7CRtCnOUKCwtZsGABu3btYvfBOhoMkfS8aDTG5Cwq9+/m23+9xIDrphAWlwQc7myyb9dW6rcsxWq6HWtyFk2OA+z84hOu/qiKdFswOTk5jBgxgtLS0pZwodFoWtZbjB07lsTEROlwIoQ4QkNDA48//jgjR47k3nvvxefz8Z///IdHH32UBQsW8OKLL7Jjxw6uveEWCpu/oKk8n10bPibnkusxmFp/2eFxN7Fz/X8JCo6g+3mXoygK+3dtIPer/5I16Eq0Wm1LU4m9276gS7ccgoIjOFi0nf25XxESGYc+KJy66kPkbfgvobZuhCefR2N9DYU7NzJg0AUM6JeDyWRi7dq1ZGVlMXXqVIKDg/n000/R6/XMnTtXXuuE+BkSNoQ4i1VVVfHwww/Tq1cv/m/649z/r51U71zLlv++yoDr7yGyaxoGczCOPdsJi0vCr6oUFhZiclXhsYQSlZiBs+oQmxe+iCU2FU3PcYQ0buH111/nnXfeYeLEiZx33nnccsstREdHyyJFIcRxlZaW4nK5uPjii4mLO7wm6rbbbmPYsGG4XC5WrVrFPffcgyE8EUNQGLE9L8Tv8+JqrDsibDgO7MLrcZPZf2TL9Kr0c4azeflb2At3YDZH43Y14fF6MITE0eDWUlVfTqPPQm1dLVs2fUVYTDecjjzQ6LGl5GA0GjF07YbZEsyvL83m/x68lxdeeIHa2lreeOMN9PrDzSFycnKYNGkSmzdv5txzz23fJ1GIM4hEcSHOYsuXL8fj8XDPPfdQ6g3FEGaj56XXYbSEUrJtPYpGgy29N4692wEotdsxGIw0lO0lJCGDErudr5d8SG29k+CswehDoug14hr+9a9/kZyczMCBA7nkkkuw2WwSNIQQJyQxMRGbzcbTTz/NwoULKSwsRKfT0b17d/bu3YuqqnTr1g2v1weoaHV6MvpdSmjkkc0a6msOYQ6JbLWOQ28MwmQJp7zsABUVFdhLS3G73ahaMzqdjoiICFJS0wgJCSElOZE+fXoTbNIQm5BKfHw8VquV0NAQort2Z9xVvwYgPz+f7OzslqABkJSUREhICIWFhW3+nAlxJpORDSHOYnv27CExMRGz2cz+qjI0yuGNq0Js8dSXlwAQm3EOJVvXU7I3j6LScox+N47ifQR3vwCNVouuuYHUnv3o2as3FQ1ujNY4evbs1vImK9/oCSFOhslk4tlnn2XhwoV88sknLFiwAJvNxs0334zP52u5jU7nOe6XGD5vM866Cr5e/Mr/LvP5qK+rJSy6K+cNGkR5ST57aotITknBGPS/phQaRYOCCoDX48Yc3HoTP1VV0WkPr21rampi48aNXHPNNa1u43a7qa6uPvUnQ4hOQMKGEGexxsbGlh22G9xetN+/cesMJpxVDgDM0Qk0qwq7N60mffAo6go2EdM1hb6DLwGgCJWKolxWznuQZp+ffcFGlseEyJusEOKURUVFMXHiRCZOnEhRUREffvghzz77LLfeeitw+LUrPOT4Xad0OiOWUCsZ/UcCUF9Xx779B+jZJw5r9ImPuOoNQXi9za0u8/lVwkMPv36azWb69u3LH/7whyPu+8NrrBDi6CRsCHEWs1gsHDp0CIBgow6f+v23eG4XOoOJ0tIyDh4sIyqlB6qziq5du7JuxdvEZv2vQ4vOYCIqOYvMi8dR5XQzrHsMvxuYDMibrBDi5JWVlVFSUtIyKpqSksKdd97J2rVrCQ0NRafTkZuby5BLhuP1+fH5vOR9/SmxKT2JiuvW6ljB4TZqK0owGM1UVFZTerCCrOze6BQvBuOJvz5ZwqKpKjs8hUtRFDxeH40Vhcz/+2z++te/kpGRwbZt24iNjW0VYIqLiwkNDT09T4wQZylZsyHEWSwtLY0DBw7gdDpJijTjV8Hn91FRvJd6n5YGZwPZ2dlknXcJDeWlVB7YTWN1OXGZ/+stHxabSGN1OUFhURhDrfRKSyYuLg6v1ytvskKIk1ZWVsYTTzzBJ598wsGDBykrK2PhwoUYDAZ69uzJxRdfzLvvvsuegjyiW+I8AAAgAElEQVQiLLB7y5c01JYTHH7kfhm2xO6gKGxc+U9K9u0mJSme+vK9bP3yA2or7CdcU1xKLzzNLgq3fYnLWcvBkiIaD+4gPj4egDFjxuBwOPj73//Ovn37sNvtvPnmm0yePJni4uLT9twIcTaSsCHEWezSSy/FZDIxY8YMEgwNNDiK+eKdudTVVNHjotFkpKdjMpkIi0vGFBJOwepFBFvjCLb+byFm15wLcdVXs3PZh7iqD5JidsubrBDilPXt25c777yTpUuXcuedd3LPPfewa9cu/vznP2O1Wrn99tsZPHgwzz77LCVbPqWuqpzsgVe0Wm/xA0WrJyimN15PM80Vuexa/y8q7LvJ6DeCcFvXE64pKDic7uddTkOtgy1fvM/+HV8wdOhQbrzxRgC6du3K448/TklJCVOnTmXy5Mns2rWL6dOnk5iYeNqeGyHORoqqfj+v4idKSkoYNmwYK1asICEhob3rEkL8AhMmTKBPnz5MnjyZffv28dJLL7F8+XL2VbkISsii/2XXEBmf2uo+u1cvYv/mL0i74HJSzh3W6rpqeyHbv/gYc1M5abZg0tPTueGGG+jVq1d7PqxOSV6Lj02em7NfUUkFv3vgdWxRIUesv3C5XOzevZvw8HC6du162jrieX1+qmud/PfvdxIRKlNFhTie470Wy5oNIc5Cr732GnC4m0pRURFlZWX89re/ZciYa/nr0iIspiN3D8+4aCwZF4096vHMMUn0GPdHZl+bc9QdxIUQoi2kJFjpmRHP7qJDRIT974N/XV0de/bsJSEhHpvNdlrPWVndwKXnZ0vQEOI0kbAhxFlqz549zJ8/H5/Px8MPP0xmZiYAU4bpmLUsn3AzGHVHho6fcnt91DR6uHdEpgQNIUS7m3jNhUx6/D18Pj9arQaHw4HdbictrdtpXzfW7PGi0Sj8buzA03pcITozCRtCnGVqa2t56623+Oabb/jd737H8OHDW00vGJp1+FvAOSsKqMNLhFmPTnPk8i2vz091kweNonDviMyW+wkhRHvqm53IlcPP4d/Lv6O5sYba2jq6d++OyWQ6redRVZXKGid/vO5iUhKsp/XYQnRmEjaEOEt4vV6WLFnC+++/zyWXXMKLL76IxXL0kYihWTZSrBY+3lrKqnwHPr+KooBGUfCrKqoKWo3C8KwYxvTpIiMaQoiAunHsuSz4YAkuj5+e2dnoTmBU9mRVVDeQkRzD9aNlo1IhTicJG0KcBbZt28b8+fOJjIzk6aefpmvX43dhSbFamDwsnZvOT2ZdQQUHqhtpcHkJNulIjDBzfrqVUJO+HaoXQohjKysrY/r06fx2RA9W7vLS0Ohu2WzvdKmodhIZbuHZ+65qkyAjRGcmYUOIM5jD4eC1115jz5493HrrrQwcOPCkO7KEmvSM6hV3/BsKIUQ72759O88++yy/+c1vGDVqFNceKGfSE+/hqKonOiL4F3eg8qsqjsp6Yq2hzPu/67FFhpymyoUQP5CwIcQZqLm5mYULF/Lxxx8zduxYpk6disFgCHRZQghx2nz++ee89dZbTJs2jT59+gDQLTGa1x+/kcdf+pRvc4uJDDNjMp7aCGxjUzO1DU1cfG4G0265lMgwmS4qRFuQsCHEGURVVb766itee+01MjIymDNnDtHR0YEuSwghThu/38/rr7/Opk2beOaZZ1p28f5BXHQYc/90HYtWbWPOP1ZQW9+ExWzEEmQ47kiHqqrUO900uZqxmI08MeVXDBmQedr26BBCHEnChhBniAMHDjB//nxqa2uZMmUKvXv3DnRJQghxWjU2NvLss8/i9XqZOXMmwcFH7hoOoNFoGDcsh6HnZbL8qzze/vhrKqrr8asqGkUhyKRHo9GACj6/n0ZXM4fjhEJiXCS/HXseQ87NIMgkI8JCtDUJG0J0cE6nk3feeYcvv/yS66+/nlGjRqHVygJGIcTZ5eDBg0yfPp1evXrxhz/8AZ3u+B9RQoODGD/iHK4cnkPBfgd7i8vZll9C/r5DNDY1o1EUzEEGeqR1oUdaF9KTbCTHR8lIhhDtSMKGEB2U3+9n+fLl/OMf/2DgwIG88MILhIWFBbosIYQ47Xbs2MEzzzzDddddx+WXX37S91cUhYzkGDKSYxh1Yc82qFAIcaokbAjRAeXl5TF//nz0ej2PPPII3bp1C3RJQgjRJpYtW8abb77JfffdR05OTqDLEUKcZhI2hOhAqqqqWLBgAVu3buXmm2/m4osvluF+IcRZye/3s2DBAjZs2MDTTz9NQkJCoEsSQrQBCRtCdABer5dFixbx0UcfMXLkSF566SWCgoICXZYQQrSJxsZGZs6cidvt5rnnniMkRPa3EOJsJWFDiADbvHkzr7zyCl26dGHmzJl06dIl0CUJIUSbcTgcTJ8+ne7du3Pbbbed0EJwIcSZS/7ChQiQsrIyXnnlFUpKSvjDH/7AueeeG+iShBCiTeXm5vL0009zzTXXcMUVV8g0USE6AQkbQrQzl8vFhx9+yNKlS7nqqqt46KGH0OtPbQdcIYQ4U6xYsYI33niDe+65h379+gW6HCFEO5GwIUQ7UVWV1atX88Ybb9C7d2/mzZtHZGRkoMsSQog25ff7eeutt1i/fj1PPfUUXbt2DXRJQoh2JGFDiHZQWFjI/PnzcblcPPDAA3Tv3j3QJQkhRJtzuVzMnDkTp9MpC8GF6KQkbAjRhurr6/nHP/7BV199xW9/+1tGjBiBRqMJdFlCCNHmysvLmT59OhkZGTz44IOyEFyITkr+8oVoAz6fj6VLl/Lee+9x0UUX8eKLLxIcHBzosoQQol3k5eXx1FNPMX78eMaOHSsLwYXoxCRsCPETdS4P6woq2F/VSIPbS7BRR1KkmfPTrYSajr+Qe8eOHcyfP5+QkBAef/xxkpOT275oIYToIFatWsVrr73G3XffTf/+/QNdjhAiwCRsCPG9ogoni7baWZVfjt+voiigVRR8qoqqwstrChmSGc3YPvGkWC1H3L+iooLXX3+dvLw8JkyYwODBg+XbPCFEp6GqKm+//TZffvklTz75JImJiYEuSQjRAUjYEAJYmedgzooCVFQizHp0Gg17v1pK0cblDJ8yEwCv38+KPAcr88qZMiydoVk2AJqbm/n3v//Nf//7Xy6//HKmTJmC0WgM5MMRQoh25XK5mDVrFnV1dTz33HOEhYUFuiQhRAchYUN0eivzHMxalk+4WY9Rpz3m7XQaDdHBRtxeH7OW5aOqKsF1+3jllVfo1q0bs2fPJiYmph0rF0KIwKuoqOCxxx4jNTWVadOmyb5BQohWJGyITq2owsmcFQXHDRo/ZtRpMWncPPDWKnrUb+KeSZPIyclp40qFEKLjyc/P58knn2TcuHGMGzdOpo4KIY4gYUN0aou22lFRTzhoeH0+Su12KiorCbHGkTP0VnJystq4SiGE6HhWr17Nyy+/zJQpUzj33HMDXY4QooOSsCE6rTqXh1X55USYjz/krwKVFRUUl5QQHhZGr549UTRaVhdUMuFCzwl1qRJCiLOBqqq8++67rFy5UjruCSGOS8KG6LTWFVTg86vojrPJXoPTyf79+1GAjPR0LJb/daLy+VXWFVQwqldcG1crhBCB53K5mD17NtXV1cyaNUsWggshjkvChui09lc1ovmZ6cVer5fGxkYKCgrompBAlNXKT2+uKHCgurFN6xRCiI6gsrKSxx57jKSkJJ544glZCC6EOCESNkSn1eD2ov3JYkYVqK+vp9zhoKTEjqIo9O7VC6326Gs6NIpCg8vbDtUKIcSpUVWV0jo3xTUuimtc1Lq9oILZoKVruIn4UCNJEUFof+bbl4KCAp544gnGjBnD+PHjZSG4EOKESdgQnVawUYdPVYHDC78rKypwOByoQIzNRtfErhxwFBwzaAD4VZVgk/wZCSE6HlVVyT3UwNp9NdQ2eVFVFZ1Wg+77UFHn9nKgugmNRsGk0zAwMZy+CaEt1/9g7dq1vPTSS9x1112cd955gXgoQogzmHxKEp1WUqSZpiYXReWlVFVXExYWRlJSEiGhoShAQ+HPr+UAUFVIjDC3fbFCCHES6t1ePt1Vzr4qF0a9hmCj9qijEUH6w1+mNPv8rNxTybayesb2sGELNqCqKu+99x7Lly/nscceIyUlpb0fhhDiLCBhQ3Q6brebNWvWsHjxZxxUehEXFUbvXr1Oev6x1+dHq1E4P93aRpUKIcTJq2708M53ZTQ2+wg1HT1k/JRBq8EQpKHG5eUfm0sZlx3FR6+/QHl5Oc899xwRERHtULkQ4mwkYUN0GiUlJSxdupSVK1eSmZnJ76+/lm61oazMLz+lhY7VTR6GZ8VI21shRIfR5PHx7pYyXB4fIacwxdNi0NLQ5Gb2p5tIMIXy5JP3YDAY2qBSIURnIWFDnNW8Xi8bNmxgyZIlHDhwgBEjRvD8889js9kAsFY4WZVfgdvrO2Jjv26DLqPboMuOely314dGURjTp0ubPwYhhDgRqqqybHclDW4foae4lszpdLK3oIAIWxzR2WP481/+gl6n4/HHHz/N1QohOgsJG+KsVF5eztKlS1m2bBnx8fGMGjWKwYMHo9O1/pVPsVqYMiydWcvyCTdzQjuJu70+aho93DsikxSr5bi3F0KI9lBc42KXw0mw8fivY0dTVVXF/n37SE5OJjwigvKGZhwNzcSHy0cFIcSpk1cQcdbw+/189913LF68mF27djFkyBCeeOIJunbt+rP3G5p1eJRjzooC6vASYdYfdaM/r89PdZMHjaJw74jMlvsJIURH8HVxLRrlcEvuk6KqlJaVUe5wkJmVhdl8uOmFSa/FXuumS1hQG1QrhOgsJGyIM15tbS3Lli1jyZIlhIaGMnr0aKZNm4bJZDrhYwzNspFitfDx1lJW5Tvw+VWU79+0/aqKqoJWozA8K4YxfbrIiIYQokPZZz/IG/Nm4yjKw+tpJiQiij4XXkqPQZcA8MK0m7n4qhupqywn75u1+Hwe4lOzuOiq33OwvBK3201MRAhLXn2OirJiLKHh9B8+Bo/PT73bF+BHJ4Q4k0nYEGckVVXJzc1l8eLFbN68mUGDBvHggw+Snp5+ysdMsVqYPCydm85PZl1BBQeqG2lweQk26UiMMHN+ulUWgwshOqSnnnmWuspqfnXbNIxBFg7s3sHqf71FSEQUiVm9Adi6+jMyzhnElXc+RF2lg8UL5vLp26/Qb+R40tPSeH/GwwQFhzL+zodRNBo2fvZvasrLaLAGB/jRCSHOZBI2xBnF6XSyatUqlixZgs/nY/To0fzxj38kOPj0vRmGmvSM6hV32o4nhBBt7Vc3/pHYknqstmgAegwcwrcrP6V4986WsBESHkX/EWMBMFhC0QdH0FRTTrfUVIp376S+ppJLf/tHohOSARh23R947ZEp1Lm8AXlMQoizg4QNcUYoLCxk8eLFrF27lnPOOYfbbruNXr16nVD/eCGEONvVN7rZ/NlCqor34m5sQFVVvJ5m3E3OlttEd00GoKamhqKiImxd4qlzlIKiUHWoFICoLv9b42YMMhNhi8Pj87frYxFCnF0kbIgOq7m5mTVr1rBkyRKqqqq47LLLeOGFF4iMjAx0aUII0WE0NTXx2qzHqPfruWjcbwmz2tBoNHzyynOtbqfTGzh06BBlZWVkZGRQvXszdd9f53G7UBQFnb71nho6gxH5TkcI8UtI2BAdjt1uZ8mSJaxcuZKMjAyuvfZa+vfvj+YoHaKEEKKz2759O66GOgbfcA/Jmd1bLnc1OlvdrrKiEqPDQffu3TEaja2u0xmMLaMhPw4c7qZGTKHmtn0AQoizmoQN0SF4vV6+/vprFi9ezP79+xkxYgSzZ88mJiYm0KUJIUSH5vV6MWo1BFlCWi7bl7sVt6sRVT3cFrzR6cTldtG9e/cj9hsCCI+OBcBRXESX1EwAGmqrqXaU0SNJXoeFEKdOwoYIqIqKCj777DM+//xz4uLiGD16NIMGDUKvl65PQghxItLS0jAZtOSuX07Q0NFU2fexdfXnxCWnU1lWzJZNGwHo0qXLUYMGQEJ6d8zBoXz16T+5ePzvAPjq038SFBxKiEE+KgghTp28goh2p6oq3377LUuWLGHnzp0MGTKE6dOnk5SUFOjShBDijGOz2bhr0iSem7+A92eup2tqBiNuuA174W4+XTAPZ2MjZovlZxtq6PQGRt00mdX//gcL5z6OOTScXkMux2wyEmQ4tR3JhRACJGyIdlRbW8vy5ctZunQpZrOZ0aNHc999953U5ntCCCGOdOmllzLgwkt45esSTHot7qZG3DoLv//z89iOMR116K9vbfVzTFI3rrn7EQD8qkq928eDN19NSqTsIC6EOHUSNkSbUlWVXbt2sXjxYjZt2sTAgQOZNm0a6enp0rZWCCFOo/AgPUO6RbJoazGHDhSSkpxMeETEKR2rwe2jV2ywBA0hxC8mYUO0icbGRr744gsWL16M1+tl1KhR3HbbbYSEhBz/zkIIIU6JY9s6Du4qJ77nAMLCLKd0jHq3lyiLnmFp0mZcCPHLSdgQp1VhYSFLlixhzZo15OTkMHHiRNl8Twgh2piqqrz55pts2LCBv/7lr3xdoVBQ2YRZr0GvPbG24T6/irPZh9Wi59d9YjHpZa2GEOKXk7AhfrHm5mbWrl3L4sWLqaysZOTIkbL5nhBCtBOPx8Pzzz9PeXk5M2bMICQkhC5xKlvs9azcU0WTx4tZr0F3jNDh86s0enyoKgxIDOOC5PATDihCCHE8EjbEKSstLW3ZfC89PZ1rrrmG/v37o9XKt2FCCNEeGhoaeOKJJwgLC+Pxxx/HYDi8IZ9GUeibEEo3q5mt9jo22+tweb2oKvhUFQVQFAWNAooCveNC6Bsfii3Y8PMnFEKIkyRhQ5wUr9fLxo0bWbJkCUVFRQwfPpznnnuO2NjYQJcmhBCdisPh4JFHHqFfv37ccsstR52uGmbScVG3SM5PiaCy0UN5QzMNzYdDR5BeS3SwHqvFgEFGMoQQbUTChjghP958LzY2ltGjRzN48GDZfE8IIQJgz549PPbYY1x99dWMGTPmuLfXahRswQYZuRBCtDsJG+KYVFXlu+++Y8mSJezYsYOLLrqIRx99lOTk5ECXJoQQndamTZuYPXs2kyZNYtCgQYEuRwghfpaEjTNcncvDuoIK9lc10uD2EmzUkRRp5vx0K6GmUxt1qKura9l8LygoiFGjRjF16lTZfE8IIQJs6dKlvPvuu/zlL38hMzMz0OUIIcRxSdg4QxVVOFm01c6q/HL8fhVFAa2i4FNVVBVeXlPIkMxoxvaJJ8V6/F7rqqqSl5fH4sWL+eabbxg4cCBTp04lIyND2tYKIUSAqarK22+/zZo1a3jmmWeIi4sLdElCCHFCJGx0EBMmTKBPnz5Mnjz5uLddmedgzooCVFQizHp0miMX9nn9flbkOViZV86UYekMzbId9VhNTU2sWrWKJUuW0NzczKhRo5g4caJsvieEEB2E1+tlzpw5HDx4kJkzZxIaGhrokoQQ4oRJ2DjDrMxzMGtZPuFmPUbdsVvM6jQaooONuL0+Zi3LB2gVOIqKilo23+vdu3dL2JFRDCGE6DicTidPPvkkFouFJ554oqW1rRBCnCkkbJxBiiqczFlRcNyg8WNGnZZwM/xtZQEJYXrseVtYvHgx5eXlXHbZZfz973+XzfeEEKIDKi8v55FHHiEnJ4cJEyagOcoothBCdHQSNjqoAwcOMG3aNC6//HJ27dqF1WqliGi2/OsjFHcDwdZYsi65irDYRABUv5+ijcux7/wat7MOQ5CF6G49Sb9gDKpfZf3Lf2Hsv2P49eBMrrrqKtLS0rj55pvZv38/DzzwQMt5f//73zNu3DjGjx8fqIcuhBCdXmFhIdOnT+fKK6/kV7/6VaDLEUKIUyZhowOqra3l0UcfZeDAgfz+97/noYceYnvuLjZWFNB/3M1ogB1L32Hn5+8z+Pf3A7Bn/WKKt6wle8S1hMYk0lBRxtYl72LfX0RkznDCY5PwoTL1of8j1KRnzZo1WK1WcnNzW85rt9uprq4mJycnQI9cCCHEt99+y6xZs7jjjjsYPHhwoMsRQohfRMZkO5jm5mYee+wxunTpwl133dVyeVFpOclDriHclkCoLYEu3c/FWXkQn6cZv9dL8Za1JJ5zEZEpPal2uilt8GFJzcFdfoDu3ZLp1udcGh0lrN1dDsD27dsZMmQIjY2NlJWVAbBz507CwsJISUkJyGMXQojObtmyZcyePZs//elPEjSEEGcFCRsdzPPPP4/b7ebhhx9Gp/vfwJMhzIbeYGz5WW8OBqDZ3UjlwQM0ORuo92nZsWMHHo+XjIwMep57AQa9HmdlGZFdM/B5XHy3azcAO3bsoEePHmRkZLSMbuzYsUMWiQshRACoqso777zDP//5T55++mm6d+8e6JKEEOK0kGlUHci6detoamoiIiICr9fb6jpVo0OrKHg8HhoaGqioqKChoYFtW7ehNjfi8XoJj7SS2L0PWu3hxeONzY0AeJtdmELCCQqPpnB3PrW152C32+nevTv5+fns3LmTYcOGsXPnTq6//vp2f9xCCNGZeb1e5s6dS0lJCTNmzCAsLCzQJQkhxGkjIxsdSHh4OH/729/QarXMmzeP5uZmdu3aRUFBAWUlxewpLGTb9u04HA5QFIwmI9nZ2fTo2RuL2Uyw2dQSNOBwyADQGYMACInvRk1pEdu3byc5ORmLxUJ2dja5ublUVFTgcDhkvYYQQrQjp9PJo48+2tLiVoKGEOJsIyMbHYSqqsTHx1NUVER8fDyvvvoqixcvpl+/ftTX1xMbFYU+Pp4ukSEoQKmvFodOj16nwxAajtZgpKa0iOjUHi3HrC3dB4pCSHQCAKHx6dQXftEyhQogKyuLsrIy1qxZQ0JCAlarNQCPXgghOp+KigoeffRRevTowcSJE6W1rRDirCRhI0Dq6+vZvXs3+fn55Ofn88UXX2Cz2TAajfTr1w+j0ciWLVt48MEHmTNnDl4VCoxGfH7/ETuGa7Q6Es+5iAPffoklMobwLinUl5eyd8NndOneH6MlBK/PT0RCGv7dn/L1119z6623AhAUFERycjKffPIJ5513XiCeCiGE6HT27dvHo48+ytixYxk3bpyslRNCnLUkbLQDr9dLUVEReXl5LQGjtraWtLQ0MjMzGT16NHv37mXAgAFMnjwZgMsvv5x7772XWbNmoSgKRr2eSzKjWZHnIDrYeMQ5ug26DI1Gy96vluJuqMVoCaVLjwGkDRoFQHWThxG9k9hXnE5BQUHLyAZAjx49+Pjjj+nTp0/7PCFCCNGJbdmyhZkzZ3L77bdzwQUXBLocIYRoUxI2TjNVVTl06FCrUYt9+/YRFxdHZmYmvXv35pprriEhIaHVkPlPRxX0ej1z585tdVlRhZOVeeW4vT66ZA+gS/aAlusURSF14KWkDrz0iJrcXh8aRWFMny6kDJt1xPUTJ05k4sSJv/ShCyGEOI4VK1awYMECHnrooVZf+gghxNlKwsYv5HQ6KSgoaAkWu3fvRqvVkpmZSWZmJjfddBNpaWmYTKZffK4Uq4Upw9KZtSyfcDMYddrj3sft9VHT6OHeEZmkWC2/uAYhhBAnT1VVPvjgA5YvX85TTz1FQkJCoEsSQoh2IWHjJPh8Pvbv398qWJSXl5OWlkZGRgbDhw/njjvuaNNF1kOzbADMWVFAHV4izPoj1nAAeH1+qps8aBSFe0dkttxPCCFE+/J6vbzwwgvs27ePmTNnEh4eHuiShBCi3XSosFHn8rCuoIL9VY00uL0EG3UkRZo5P91KqEnfrrWoqkplZWVLsMjPz6ewsJDo6GgyMzPJyspi7NixJCUltWo32x6GZtlIsVr4eGspq/Id+PwqigIaRcGvqqgqaDUKw7NiDk+dkhENIYQIiMbGRp5++ml0Oh1PPvnkaRnlFuL/2bvzuKiq/g/gn9lg2EFBRFBBZABFBEXhcRfcKi01TU3FypJ+uWblVqaUmpGliZlZmo9R5laZS5ma+bhvuaGgyCKLCKjsyzDL+f1BTE6AYjqi8nm/Xrxk7jn33nOH6z33e89yiR4lD0WwkXy9GD+fycDeiznQ/3XjLJNIoPvrxnnl/iT08HbC021dTXbjXFZWVqU7lE6nM3SHGjFiBLy8vGBl9XDcuHs4WmFSmBde6OyOgwnXkZpbgqIyLayVcjRzqJsAjYiI/nbjxg1ERkbCx8cHERERD/zBFBHRw6DOgo09e/ZgyZIlGDdnCb46eg0CokqXoMTDvyL52G70mBiFPfHZ+D0+B5PDvO65S5Ber0dqaqphEPelS5eQmZkJDw8PeHt7o1u3bnjllVfg5OT00E9HaKtU4Ik2LnVdDCKix8qSJUtw4cIFrFy58l+tn5KSgvfeew9PPvkknn322Ye+LiEiMpUHGmxs2rQJ6enpmDJlCgDgepEay35PgFND+2oHOzdv3xNu/p0hl0rhZG0OtVaHT3ZdBIC7Cjhu3rxpFFgkJCTAwcHB0GrRr18/eHh4QC5/KBp6iIjoEXb27FlERUVh3Lhx6NatW10Xh4ioTj3Qu+v4+HhYW1sDADLzS5F8vRjdLRU1zqokNzOH3Ozvd0qYy2WwtwSW/p4AD0erartUqdVqJCYmGo21UKvVUKlU8Pb2xuDBg6FSqWBjY2OagyQionpr7969WLVqFWbMmAE/P7+6Lg4RUZ17YMHGzJkzERsbC6CiC1WzbkMAAPrSApzYGYP8zCuQmynh+Z9+cPP/D4C/u1H1mrwIAHAj9RISD/2KG1kZGLxeiT4hbdCvXz/o9XpDYJGRkYFmzZrB29sbwcHBCA8Ph4uLC5uwiYioWtnZ2YiOjsaFCxdgbW2NAQMGGKUXFxfj66+/xqlTp5CXlwc3NzeMHDkSHTv+/a6j69evY/LkyTh27Bi8vLywdu1avPTSS9+LuH4AACAASURBVPDx8QHwd9fhTz75BJ9//jlSUlJgZ2eHYcOGoV+/fg/0eImIHqQHFmzMmjULb7zxBjw9PTE8/EUMn/cNFDIJEvZvg3tQT1jYNUTSkV2I+30TGrp7w8K2gdH6mrISnNqyCg1bBqClfw/kFZVh5+7/YuPGjXj55ZfRunVrhIaGokWLFjAzM3tQh0VERI+4qKgo5OXl4b333oOtrS1+/PFHnDx5EhYWFgCABQsW4OrVq3jttdfQpEkT7Nq1C/Pnz8fChQvh6+uLsrIyDBw4EIWFhVizZg2aNm2KzZs3Y/bs2YiOjkbjxo0N+1qxYgXCw8Ph6OiILVu2YPny5fD09ISXl1ddHT4RkUlVfUGDidjY2EAqlcLc3BwXrusAqQwSSODq1xGO7r6wcmgE96CegBAoyEqHXq9HWZkaZX91i/rz6AHk3bgO2DeBhW0DODVriZnRa7F9+3a89dZbeOaZZ+Dj48NAg4iIai0jIwMXL15EeHg4WrdujaZNm2LChAmGmaMuXryIs2fPIiIiAh06dICrqyteeOEFtGjRAj/99BNKS0vxf//3f8jJycH333+Pzp07o1mzZpg4cSIsLS2xY8cOo/316dMHAQEBcHNzw7hx42Bubo79+/fXxaETET0QDyzYuNWVmyWo7NVk26ipYbmZRcUYDE15GU6dPo2c6znQ63Sws7ND68COcG7qjqIL/4M28xIkZfnI1cjh6+sLhYJTvBIR0d1LS0sDALRo0cKwTCqVGloaLl26BADw9/c3Wq9NmzZITk7GqVOnoFarERgYCF9fX0O6XC6Hj48PkpKSjNbz9vY2/K5QKNC8eXPk5OTc34MiInqI1Mn0S0VqLaSoiDak8lsChb8iEKkECAwIQLI6G8lX4w1v5O4wbCJSTuxF2pkDKMj7GYWHXeAnm4IuXbo88GMgIqJHX2lpKQDA3NzcaHllF6qSkhIAwJgxY4zStVot5HI5OnXqhBMnTmD37t0YOnSoUR6NRgNXV1ejZf98V5NSqURRUdG9HwgR0UOqToINa3M59BC3zSOVVm10UVrbw6fHIPj0GIQrKcmwzTyBqKgoNG/eHE2bNq1mK0RERDWrDDLUarXR8soAwNLSEgDw8ccf19iKbmVlBRsbGyxatKhK2j9f5FdWVmb0ubS0FI0a3du7o4iIHmYPvBuVEALNG1hC3D7WqKIk7zpyki4YPls2bIJRL46DEMLQDE5ERHQ33NzcAAAJCQmGZeXl5YiLiwMAqFQqABUzUrm4uBh+ZDIZHBwcDHkKCwshl8uN8gAw5Kl0/vx5w+8ajQapqamGMhARPY4eaLBhbW2NpKQkNJEXQFdaBHGH1o1bleRdx5mtq5F6ej8Kb+ZAU3gD2ef2wczMzFAZEBER3Y1mzZrB3d0d69atQ1xcHK5cuYLo6GhDi4e3tzf8/PywdOlSnD59GtnZ2Th06BCmTp2KjRs3AgCCg4Ph4uKCqKgoxMXFITs7G7t378akSZOwd+9eo/3t3LkTJ0+eREZGBlauXAm1Wo3u3bs/8OMmInpQHmg3qsGDB2PZsmV4f/bb8PPrgdSjtQ82HN194Bs2FKmn/ofYvT/DxcEKKcFtMHv2bMOYDiIiors1Y8YMLFu2DLNmzYKtrS2eeuop2Nra4vjx4wCAd955B6tXr8aiRYtQVFSEhg0b4umnnzaM0TAzM8P8+fOxatUqREZGoqysDC4uLhg7diz69OljtK/w8HCsW7cOly9fhp2dHSZPnsyWDSJ6rEmEqL5DU3p6OsLCwrBnzx6TXAiTrxdjyvrTsFHKanyDeHXUWh2K1Dosfi6g2jeIExE9Tkx9LX6UPUrfTeVL/b7++ms+ICOix8qdrsV1MvUtAHg4WmFymBfySjRQa3W1Wket1SGvRINJoV4MNIiIiIiIHnJ1MhtVpVCfihk4Pt2TgAJo4WCpgLyaWai0Oj1ySzWQSiSY2tvbsB4RERERET286jTYACoCDg9HK2w9cxV7L2ZDpxeQSACpRAK9EBACkEkl6OXjjAFtm7BFg4iIHjlhYWEICwur62IQET1wdR5sABVdqiaFeeGFzu44mHAdqbklKCrTwlopRzMHS3T2coStkm8JJyIiIiJ6lDwUwUYlW6UCT7RxqetiEBERERHRfVBnA8SJiIiIiOjxxmCDiIiIiIhMgsEGERERERGZBIMNIiIiIiIyCQYbRERERERkEgw2iIiIiIjIJBhsEBERERGRSTDYICIiIiIik2CwQUREREREJsFgg4iIiIiITILBBhERERERmQSDDSIiIiIiMgkGG0REREREZBIMNoiIiIiIyCQYbBARERERkUnIa0rQ6XQAgGvXrj2wwhARkbHKa3DlNZn+xnqKiKju3ameqjHYyMnJAQCMHDnSBMUiIqK7kZOTg+bNm9d1MR4qrKeIiB4eNdVTEiGEqG6FsrIyxMbGwsnJCTKZzOQFJCKiqnQ6HXJycuDn5welUlnXxXmosJ4iIqp7d6qnagw2iIiIiIiI7gUHiBMRERERkUkw2CAiIiIiIpNgsEFERERERCbBYIOIiIiIiEyCwQYREREREZkEgw0iIiIiIjIJBhtERERERGQSDDaIiIiIiMgkGGwQEREREZFJMNggIiIiIiKTYLBBREREREQmwWCDiIiIiIhMgsEGERERERGZBIMNIiIiIiIyCQYbRERERERkEgw2iIiIiIjIJBhsEBERERGRSTDYICIiIiIik2CwQUREREREJsFgg4iIiIiITILBBhERERERmQSDDSIiIiIiMgkGG0REREREZBIMNoiIiIiIyCQYbBARERERkUkw2CAiIiIiIpNgsEFERERERCbBYIOIiIiIiEyCwQYREREREZkEgw0iIiIiIjIJBhtERERERGQSDDaIiIiIiMgkGGwQEREREZFJMNggIiIiIiKTYLBBREREREQmwWCDiIiIiIhMgsEGERERERGZBIMNIiIiIiIyCQYbRERERERkEgw2iIiIiIjIJBhsEBERERGRSTDYICIiIiIik2CwQUREREREJsFgg4iIiIiITILBxiNk9OjR8Pb2rvHn3XffBQAcPXoU3t7eOHHiRB2X+NG1Y8cOhIeHo0OHDmjbti369u2LhQsXIjs7u66LdlszZsxA7969DZ+9vb2xfPnyOiwRERGg0+mwfv16DBs2DO3atUNgYCD69++P6OhoFBUVGfL98MMP8Pb2xrVr1+qwtA+fQ4cOISIiAsHBwWjTpg1CQ0Mxe/ZspKSk1HXRbis6OhqtWrUyfA4NDcXbb79dhyWiuiCv6wLQ3QkKCsKSJUuqTbOwsAAABAYG4sCBA7C3t3+QRXtg3n33XTg5OWHixIkm2X5kZCQ2bdqEiIgIvP3221AqlTh37hyWLl2KHTt2ICYmBs2aNbtv+9PpdAgKCsLWrVvh5uZ237YLAAcOHICVlZXJ90NEVBOdTofx48fjxIkTmDBhAhYsWAAAOHHiBKKjo7Fz507ExMQ8tnXWvfrqq6/w8ccfY9SoUZg4cSLs7Oxw6dIlfPbZZxgyZAhWrVqFtm3b3td99uvXD5GRkQgODr6v2920aRPMzMxMvh96uDDYeMQoFAo4OTndNo+Zmdkd8zzKzpw5g169eplk27/++iu+++47LF26FH379jUsb968OUJCQvD000/j888/xwcffHDf9nnp0iWUlJTct+3d6tbzwJT7ISKqyZo1a/C///0P69atM7op9vT0RFBQEAYOHIiYmBhMmDChDkv5cDp79iw+/vhjvPXWW3jppZcMy5s2bYr//Oc/eO6557Bo0SJ88803922f+fn5JmsxadCgwQPZDz1c2I3qMfTPblTl5eWYPXs2OnTogKCgIMyZMwfbt283aqrW6/VYuXIlnnrqKfj7+yM0NBQrV66EEMKw3dDQUCxevBirVq1C9+7dERgYiPDwcKSmpgIARowYgbFjx1YpzyuvvIJhw4YZyhIVFYW+ffuiTZs26NevHzZt2mSUPy8vDzNmzEBwcDCCgoIQERGB5ORkQxni4+OxbNkyeHt7Iz09HUBFkDBw4EC0adMGQUFB+L//+z+ji9iMGTMwYsQIrFixAoGBgdi4cWO1390333xj6Db1T46Ojti4cSPmz59vWHb58mVERESgU6dOCAwMxNixY5GYmGhIr+wSkJSUhBdeeAGBgYHo0aMHvvrqK8PfauDAgQCAsLAwjB492nCcixYtwvjx4+Hv74+UlBQIIfDFF1+gV69eaN26Nbp06YLp06cjNze32mMB/u5GVd1+hgwZgldffbXKOq+++iqef/75GrdJRHQ3vvnmG/Tt27fap++enp745Zdfagw0dDodli1bhtDQUPj5+aFLly6IjIxEcXGxIc/hw4cxfPhwtGvXDu3atcPIkSPx559/GtJrU+94e3vj+++/x0cffYROnTqhffv2eO2113Dz5k1DnsLCQsyePRuhoaHw9/fHwIED8fvvvxttJyYmBk888QT8/f0REhKCyZMnG3W/vVP6P8XExMDR0RFjxoypkmZpaYlVq1Zh9erVhmVZWVl4/fXX0a1bN7Rt2xbDhw/HqVOnDOmV9wenT5/GhAkT0K5dO3Tp0gUffPABhBBIT09Hx44dIYRAeHg4QkNDAVR0437zzTcxd+5cBAQE4NChQwCADRs2oH///vDz80NISAjGjx9vqJerU9mNqrr9TJ48GQMGDKiyzrx589CzZ0/o9foat0sPOUGPjFGjRokxY8bcMd+RI0eESqUSx48fF0IIERUVJfz8/MSmTZtEYmKiWLhwoejdu7dQqVQiMzNTCCFEdHS0aN26tYiJiREpKSli06ZNwt/fX6xcudKw3Z49e4o+ffqIOXPmiMuXL4vjx4+LTp06iXHjxgkhhFi7dq1o3bq1KCgoMKyTn58vWrduLdauXSuEEGLGjBkiKChI/PzzzyI5OVmsWrVK+Pj4iO3btxvWGTlypBg0aJA4ffq0uHz5snj55ZdFjx49RGlpqbhx44bw8/MTCxcuFNnZ2UKr1Yo//vhDqFQqER0dLRITE8WZM2fE0KFDRffu3UVJSYkQQojp06eLnj17itdee02kpqaKwsLCKt9beXm5aN26tVi6dGmt/h43btwQISEhYuTIkeLs2bPiwoUL4qWXXhKdO3c2fAebN28WKpVKjBo1Suzdu1dcuXJFzJs3T6hUKnH27FmhVqvFunXrhEqlEmfOnBG5ubmG7zo0NFRER0eLjIwMoVarxYYNGwzf1dWrV8XJkydFnz59xJQpUwxlmj59uujVq5fhs0qlEp999lm1+/n+++9F69atxY0bNwz5CwsLhZ+fn9iwYUOtvgMiottJT08XKpVKbN68uVb5K6+ZlXXTRx99JAICAsTWrVvFlStXxO7du0WnTp3ExIkThRBC5OXliYCAALFgwQKRkpIiLl++LN555x3Rvn17UVxcLISoXb2jUqlEnz59RHR0tEhOThZ//PGH8Pf3F5GRkYY8o0ePFt26dRO///67SExMFFFRUcLX11ecPHlSCCHE/v37hY+Pj/jxxx9Fenq6OHPmjBg2bJih3r5TenV69uwppk+fXqvvTq1Wi759+4r+/fuLo0ePikuXLolp06aJgIAAkZqaKoT4+/5g8ODB4ueffxapqali5cqVQqVSiV9++cWoTt25c6ehfhg1apQIDQ0Vs2fPFunp6aKkpEQcPHhQqFQqsWbNGpGRkSHOnz8vhg0bJoYOHWoo09KlS4Wvr6/R8cyaNava/ezfv1+oVCoRFxdnyK/X60WXLl3E4sWLa/Ud0MOJwcYjZNSoUcLX11cEBARU+5ORkSGEqBpsdOnSRbz99ttG2xo9erThgl5eXi4CAwPFvHnzjPIsXLhQhISECJ1OJ4T4O9io/CyEEHPmzBEhISFCCCGysrKEj4+P+Pnnnw3pP/74o/D19RXXr18X165dEz4+PuLrr7822s/EiRPFoEGDhBBCnDlzxqjsQlRUVlOnThWJiYlCCCH8/PyMAoIXX3xRDBs2zGibSUlJQqVSiW3btgkhKm7Cvb29DRVYdbKzs4VKpRIbN26sMc+tvvjiC9G6dWtx/fp1w7IbN26INm3aiG+++UYI8XfFuWXLFkOe69evC5VKJWJiYoQQQmzbtk2oVCqRlpZmyNOzZ0/Ru3dvo/3l5+eLy5cvGy1bunSp6NChg+FzTcFGdfspLCwUAQEBhrIKIcSWLVtE27Ztqw3GiIju1qlTp4RKpRKHDh2qVf5bgw21Wi0CAgLEJ598YpTn+++/F97e3iIrK8tQZ5w5c8aQrlarxcmTJ4Vara5VvSNExbXyhRdeMMrz8ssvi2effVYIIcTp06eFSqUSu3btMsozaNAgQ+CzcuVK0a5dO6HVag3pWVlZhpvnO6VXx8/PTyxZsqTG9Ftt375dqFQqceHCBcMytVotOnfuLBYuXCiE+Pv+YPny5YY8Op1OBAQEiA8//FAI8fff7MiRI4Y8o0aNEgEBAaKsrMywrKioSFy8eNGoDJV/v8oHbjUFG9XtR6fTiZ49exrKKoQQJ06cECqVSly5cqVW3wE9nNiN6hHj7++Pn376qdqfRo0aVcmvVquRnZ0NlUpltLxr166G3xMTE1FcXIyQkBCjPB07dsTNmzeNmnj9/Pwglf592jRo0AAFBQUAgEaNGiEoKAi7du0ypO/cuRP/+c9/0LBhQ8TGxkKv11e7n0uXLkEIgdjYWAAwmr3C1dUVH3/8MVq0aFHtdxIbG4vAwECjZR4eHrCxscH58+eNytq4ceNqtwEAEokEAIy6jt3O2bNn4eXlhYYNGxrto2XLloiLizPK26ZNG6M8AAzfW01u/Q4AQKlUYvfu3Xj66afRsWNHBAYG4osvvkB+fn6tyvtP1tbW6NevH7Zs2WJYtnPnTvTp0wfW1tb/aptERLe62+vqrZKSklBSUoKAgACj5f7+/hBCIC4uDi1btoSrqyumTJmCL7/8EnFxcVAoFGjXrh3MzMxqVe9UuvU6DRjXb2fOnAGAKtsJDg42XO87deqE8vJyjBw5Ehs3bkRGRgYaNWoEHx+fWqVXRyKR1Lr70JkzZ2BnZwdfX1/DMjMzM7Rr1+62dZJUKoW9vf0d66SWLVvC3Nzc8NnS0hInT57EkCFDEBISgsDAQMyZMwcA/lW9JJVKMXjwYGzduhU6nQ5ARZ0UFBR0XydloQePA8QfMUqlEs2bN691/ry8PACAjY2N0fJbZ/2onHbw9ddfh0wmMyyvvMDl5OQYbtKVSqXRdiQSidHF+sknn0RUVBTUajU0Gg0OHjyIyMhIo/0MHz7cUAEBgFarhUajQW5uLgoKCiCRSAwza9VGUVGRYcalW1lZWRlNqVhdnls5ODjA3NzcMAalNvuNj4+vEuio1eoqA/RvPZ7aVr7/LO/ChQuxfv16vPHGG+jUqRMsLCzw/fffG/XXvVtDhw7FiBEjkJSUBGdnZxw4cABffPHFv94eEdGtKuuO1NRUdOrU6a7Wrbx+//PhR+W1saioCJaWlli3bh2+/PJLxMTEYNGiRXB1dcVbb72FJ554olb1TuUDoNvVb5XbufVBHQBoNBooFAoAQOvWrfHtt99i9erVWLhwIYqKihAYGIi5c+fCx8fnjunVcXFxQVpaWq2/r4KCgip1Unl5OTw8PIyW3akur84/66TVq1cjKioKERER6Nu3L6ytrfHHH38YZhv7N4YMGYLPPvsMhw4dQteuXbFr1y5OHPAYYLDxmKucYk6tVhstv3VQcWUgMmfOHAQFBVXZhrOzc63317dvX7z//vs4cOAAysrKAMDw3ofK/SxbtgxNmzatsq6trS0aNGgAIQSKi4tr/XTdxsbGKKioVFRUVCXIuh2ZTIZ27dph7969eOONN6rNc/ToUVhYWMDf3x82Njbw9vbGp59+WiXfPy/k98P27dsxePBgoxlJNBrNPW2zXbt2aNmyJbZv3w5PT080bNiQUxAS0X3j7OyMZs2a4ffff8fw4cOrzbN79254eHjA09PTaHnl9buwsNBoeeXnyjrC2dkZ77zzDt555x3Ex8fj888/x9SpU+Hl5VWreqc2KrezYcMGo6lb/8nf3x9LliyBRqPBsWPHEBUVhVdeeQX79u2DVCq9Y/o/BQUFYffu3VCr1UatCpXi4+ORk5ODrl27wsbGBvb29li/fn2VfHL5/b/d2759Ozp37oypU6calv2bFqxbNW7cGF26dMH27dtha2uLvLw89OvX716LSnWM3agecw4ODrCzszPqTgTAqKtTixYtYG1tjezsbDRv3tzwY2trC0tLy7u6cW7QoAFCQkKwb98+7N69Gz169DBUCJVdsG7evGm0H6VSCXt7e8jlckPXoZMnTxq2mZOTgxEjRhjNLnLrBc3Pz88oDQASEhJQVFRUpVn8TsaMGYOEhAR89913VdJu3LiBmTNnYuXKlQAqmqHT09Ph5ORkdDxardaoa1Vt3ekiXV5eDgcHB8NntVqN3377rVbr3m4/Q4YMwW+//YatW7di0KBBRk//iIju1QsvvIB9+/Zh3759VdKSk5MxY8YMbNiwoUqah4cHrKysqlzfT58+DalUitatW+PKlSvYu3evIc3Hxwfvvfce9Ho9EhMTa1Xv1Ia/vz+Aiu6vt25HLpfD0dERAPDnn3/i7NmzACqmqe/cuTMmTJiA7Oxs5Ofn3zG9OqNHj0ZhYSGWLl1aJa2kpASzZs3C4sWLodfr4e/vj/z8fCgUCqMyAvhX0+HfqV7RaDRGdZIQAlu3bq3Vurfbz9ChQ/H777/jhx9+QN++fe/YK4Eefgw2HjEajQY5OTnV/tw6Rd+t+vXrh23btmHHjh1ITk7GwoULjaYNVCgUCA8Px5dffomffvoJaWlpOHnyJCIiIjBp0qS7LuMTTzyBAwcO4MCBA+jfv79heaNGjTBgwABERUVh9+7dSE9Px8GDBxEeHo73338fQEXg0LFjRyxYsABnz55FYmIi5s6di8zMTHh7ewMA7OzscPr0acTHx6OgoABjx47F2bNn8cknnyAlJQUnT57E9OnT4e7ubpi2r7Z69uyJl156Ce+//z4++OADXLhwAWlpadixYwdGjBgBKysrzJ07FwDw7LPPQiaT4Y033kBsbCxSU1OxevVqPP300zhy5Eit91n5ZG3fvn24ePFijfnatm2LX375BXFxcTh//jzGjRuHzp07AwCOHTtWpfWqtvt55plnkJycjP379xumxyUiul9GjBiBfv36YeLEifjss8+QkJCAlJQUbNy4EaNGjUKrVq0wefLkKuuZmZkhPDwc3377raFu2rlzJ6Kjo/HMM8/A0dERqampmDBhAmJiYpCWlobU1FR8+eWXMDc3h7+/f63qndpo27YtOnTogHfeeQeHDh1Ceno6fvvtNwwdOtTwAGrv3r0YP3489u7di6tXryI+Ph4bNmyAl5cXHBwc7pheHR8fH8yYMQNfffUVZsyYgdOnTyM9PR1//PEHRo0ahRs3bmDRokWQSqUICwtDs2bNMHXqVPz5559IT0/H5s2bMXDgQKOxeXdSWVccPHgQFy5cqDFw8Pf3x4EDB3Dy5ElcvnwZr7/+uqE72MmTJ+/4Xqea9tOzZ08oFAps2rQJgwYNqnW56eHFblSPmBMnTqBLly7Vpjk6OuLgwYNVlr/11lvIy8vDrFmzYGlpicGDB2PMmDF49913Dc3BkyZNgoWFBaKjo3Ht2jXY2NigV69eNXYnup0+ffogMjISSqUSPXr0MEqbN28eFi9ejPfeew/Xr19HgwYNMGDAAKOKZsmSJZg/fz7Gjh0LIQTatm2LVatWGZ5uREREYPHixRg5ciS++uordOrUCZ9++ik+++wzrF69GpaWlujcuTOmT59+2+bumkyfPh3t2rVDTEwMfvjhB2g0Gri5ueGZZ57BmDFjDC01DRs2RExMDKKiojB69GhoNBqoVCp88sknNf6NqhMcHIyQkBAsXLgQKpUKP/zwQ7X53n33XcyaNQvDhw+Hs7MzJk6ciC5duuD06dOIiIi440udatpPgwYN0LFjR2i12mq7GRAR3QupVIrFixfjhx9+wKZNm7Bq1SoAFS9LjYiIwPDhw2u8Vk+aNAlyuRyffvopsrOz4ejoiMGDB2PKlCkAKsZQREZG4r///S8++ugjKBQKeHt7Y8WKFXBxcQFQu3qnNpYvX46oqCi88cYbKCgogLOzM0aPHo2IiAhDWXU6HSIjI3H9+nXY2dmhffv2WL58ea3SaxIeHg4fHx+sXr0aERERKC0thYuLC0JDQzF27FhDy4q5uTnWrFmDDz/8EBERESgpKUGzZs0wffp0DB06tNbH2aJFC/Tv3x9r1qzB5s2bsX///mrzTZkyBVlZWXj55Zdha2uLF198ESNHjkRiYiJmz559xxaJ6vYjk8mgUCgQGhqKw4cPo2PHjrUuNz28JOJeO9jRQ6+8vBxFRUVGb+5ctGgRvvvuuyrN01T/3Lx5E2FhYYiKijKMryEiIqoL5eXl6NOnD1544QW88MILdV0cug/YjaoeWLJkCfr06YPdu3cjIyMDu3btwvr16/Hss8/WddGoDhUVFeHixYuYNGkSfHx8EBYWVtdFIiKieqqkpAQpKSl48803oVAoMGzYsLouEt0n7EZVD1Q2N8+bNw83btyAs7Mzhg0bxunk6rlvvvkGy5cvR3BwMBYsWFDtTChEREQPwu7duzFz5ky0adMGK1asuKsp8Onhxm5URERERERkEjW2bJSVlSE2NhZOTk5GL3ojIqIHR6fTIScnB35+fiZ5f8ujjPUUEVHdu1M9VWOwERsbi5EjR5q0cEREVDvffvtttS/drM9YTxERPTxqqqdqDDYqXwDz7bffonHjxqYrGRER1ejatWsYOXLkv3op1+OO9RQRUd27Uz1VY7BR2STduHFjuLm5maZ0RERUK+wmVBXrKSKih0dN9RSnnyEiIiIiIpNgsEFE4OkCuwAAIABJREFURERERCbBYIOIiIiIiEyCwQYREREREZkEgw0iIiIiIjIJBhtERERERGQSDDaIiIiIiMgkGGwQEREREZFJMNggIiIiIiKTYLBBREREREQmwWCDiIiIiIhMgsEGERERERGZBIMNIiIiIiIyCQYbRERERERkEgw2iIiIiIjIJBhsEBERERGRSTDYICIiIiIik2CwQUREREREJsFgg4gIwJ49ezBgwAAUFBTUmOe7777DM8888wBLRXWJ5wQR0b1jsEFE9damTZuwZMmSWucfPHgw/vvf/5qwRFTXeE4QEd1fDDaIqN6Kj4+/q/xKpRL29vYmKg09DHhOEBHdX/K6LgARUV2YOXMmYmNjAVR0l5kyZQoAICcnBx9++CHi4+NhaWmJkSNHol+/fhBCYN26dVi/fj22bNkCADhz5gxiYmJw5coVAECLFi0wZswY+Pr61s1B0T2523MCqOhGxXOCiKhmbNkgonpp1qxZcHFxQZcuXbB27VpoNBoAwJo1azB48GAsXboUAQEB+Oyz5biScQ0lGoFyrR5CVKxfVFSEefPmwdvbG59++ik++eQTuLm5ITIyEmVlZXV4ZPRv1facWL58ObKzs6usz3OCiKgqtmwQUb1kY2MDqVQKc3NzODg4QKFQAAB69+6N9u3bAwAGDR6MPb/vxeXLl+Ho1AgCgF4I6IXA1atXUVZWhu7du8PFxQUAEBERgbCwMMhksro6LLoHtTknnn32Wfzxxx+4fPkyGjVqZLQ+zwkioqrYskFEdIuWLVsafre0sgEAlJWWQq/TGZZrdQLNmjVDo0aNsHDhQmzevBlJSUmQy+Xw9fU13KTS4+HWc8LW1hYAUFpaiuPHj+P69esQfzV38ZwgIqqKLRtERLcwMzMz/C6RSCAAZGVlIS0tzSifUqlEVFQUNm/ejG3btmHNmjVo1KgRXnzxRXTp0uUBl5pM6Z/nRKXDhw9jy5YtiIuLw7Rp09CyZUv0798fFy9exNatWx/qc0IvBHR6AYlEApnE+LiIiO4ntmwQEdVAJpVAq9GgvLwcTZs1NSyXyypuzBo2bIhx48bh66+/xtKlS6FSqRAVFVUlMKHH06RJkzB27Fi0a9cOo0aNgpOTExISEpCUlITi4mK4uLggLy8P06ZNw9GjR6HX6+u0vDq9wPUiNc5lFOBYch7+TM3HiSv5OH4lHyk3SlBarrvzRoiI7hJbNoioXqvsAlOdgwf2IyMjHU2auEAqrehzL5EAUokEmZmZSE9PR4cOHQAAHh4eGD9+PA4cOIC0tDQ0bdq0xu3Sw+1250R1ZDIZ/P394eTkBDc3N0ybNg3FxcVITEzE2bNnMX/+fMyfPx/m5ubw9PREy5YtDT+urq4mb1UQQiC7sBypN0uhE4BMApjJJYb96oVAVoEaWQXlsFXK4elkCTM5n0US0f3BYIOI6i1ra2skJSUhKSkJubm5RmmnTp3Ct99+iyYuLrA0V8BCIYGZTALpXzdomZmZmD9/Pl5++WUEBQVBCIHffvsNZmZmUKlUdXE4dB/c7py4k3+eE05OTtDpdGjVqhW++OILmJubIzExEZcvX8aRI0cQExODgoKCKgFIkyZN7hiAjB07Fm3btsWkSZNum08IgfS8MmTklkEhkxha5W4llUhgJpdACIGCMi1irxailYs1lAoOaieie8dgg4jqrcGDB2PZsmWYNm0ann/+ecPyxMREfPzxx5g6dSrmz58PiaQiyLj1BrBdu3YYP348tmzZgq+//hoKhQLu7u6YPXs2HB0d6+Jw6D6o6ZyojdqcEwEBAQgICDCsU1hYaAhADh06hLVr16KoqKhKAOLi4vKvWkCyCtXIyCszasmoiUQigZkc0GgF4q8Vw6+JNeQytnAQ0b2RiBrai9PT0xEWFoY9e/bAzc3tQZeLiKhOZGVlYdq0aXj11Vfxn//8p66Lw2vxbTyu301BQQESExORkJBg+LekpASenp7w9PSEl5cXli9fjpCQEEyePLnG7Wh1evyZVgCZFIYWudpSa/Voam8BVwflvR4OET3m7nQtZssGEdFfCgoKMGfOHDz33HMPRaBB9ZOtrS0CAwMRGBhoWJafn4/Lly8jMTER//vf/3Dy5ElcvHgR2dnZ8PLygo2NDdauXYvBgwcjPj4ejo6OcPf2wzfffofC/Fy4uDbF0NFj0czDEwCg1+uxa9uPOLJ/LwrycmFlbYM27Trg6aEjYa5UYt6br6FTj96YMeFFSCUS5ObmIjw8HF26dMH06dMN5QoPD8fAgQMxePDgB/49EdGjgcEGEREAtVqN9957D506dcJTTz1V18UhMmJnZ4f27dsbXi6YlJQElUqFXr164cyZM1iwYAGkUil+/fVXpKamQqFQwPPKNYwaNwlmchlivlyGb1d9jpnzFgEAtm/+Hvv37MSwF8ehmbsnrl1Nx/o1K1GYn4+XJkyFd2s/JCbEI69EiwZWCsTGxsLR0REXLlwwlCkjIwO5ublG3cKo/hBC4GaxBul5pUjPLUOxWguJBHCwVMDNwQJuDhawNudtJjHYICKCTqdDVFQUXF1dMXr06LouDlGtWFhYoE2bNli3bh2efPJJzJkzB4WFhXj99ddxKSEBfQaOQGFRIfR6AVePlji451dkXbsGG2sb7N+zE916P4H2wZ0BAE7OjVGQn4eNa79Cfl4uvHzbYNO3XyOvpBwNrBQ4d+4cevTogW3btiEzMxMuLi44f/487Ozs4OHhUcffBD1IZRodTl7Jw47YLGTml0EqkUCrFzD01BMV04brhYCfqy36+DaCr4sNZFK+y6W+YrBBRPWaEAKff/45NBoNJk6cyJeb0SNlyZIlUKvVeP/99yGXy+Hg4AAXFxfYN2gID48WUMgl0JRrkJt9FYAE6WlpyL1xHdnZ2VCYW+LatWuwt3eAUmmO5h4tIYRAxpUUqFr5QV1aiuTkZLRw8kNsbCxeeuklXLp0CRcuXICLiwtiY2PRtm1b/p+pR2IzCvDlgRQUlmlhLpfCwVJR499fLwQuZBYiNqMA7g0t8UpXd7jYcQxQfcRpJoioXlu/fj0SEhIwc+ZMyOV8/kKPjoMHD+LAgQMoKCiAVqs1SjM3N0fl7C8KMwWsra2hVJqjhWcLtGjhAVsbGzRq5IyysjLEx8Xh3LlY3LyZC51Oh9LSEjg0aAinxi5ISriI/Px8ZGRkwNfXF61atcL58+cBAOfPnzcaV0KPL61eYM2hVHy86zI0OoEGVmawMpffNtCUSiSwt1DAwVKB1NxSzN4Sh30J1x9gqelhwWCDiOqtXbt2Yffu3Zg7dy4sLCzqujhEd8Xe3h5Lly6FTCbDsmXLjNJkf90EVjfhpNLCAhKpBAozOdzd3REQEAAPDw+o1WUoKSlBalo6UpJT0LSFF5IuxeHcuXNwd3eHlZUVWrVqhQsXLuD69YrWEY7XePxp9QKf70vCH5dy4GClgKXZ3b1/RfJX0GFpJsPXB1Ox83yWiUpKDysGG0RUL504cQJr165FZGQkHBwc6ro4RHetdevWcHd3x+uvv47Dhw9j9+7dhjSpVAJbCzk0uqrBRiMXVyiVFkhOuFixQAJYW1uhrLgAtra26Nq9J5QWFnBu0gw/bPgOH330EaRSKQoKCuDj44PMzEzs378fbm5ufKdMPfD98XScvJKHhlZmdz2F8q3M5FLYW8ix7ngGTl65uxdm0qONfQaIqN5JSEjA4sWL8e6778LV1bWui0N0T9q0aYOBAwdi5cqV8PPzMyx3sTVHQam2Sn65XI5uvZ/Avt92wLmJK1p4+SAjNQW/btmEDp26wbFRI2h1AmG9wnBg63dQq9UoLS3FK6+8Ag8PD+h0OmzYsAE9e/Z8kIdJdSD+WiF2x+XAwdLsvozNkcuksDKXYdXBVLRsZA07C8V9KCU97BhsEFG9kpmZiffffx+TJk2Ct7d3XReH6L4YPXo0Tp06hU8++QQSiQQymQx2FnKYySTQ6PRV8j856DnI5XLs+HEDCvJyYWNnj45duuPJQcMghIBOCHi5NISPjw8SEhKwcOFCWFpa4syZM7hy5Qr279+P8vJymJubIyQkBCqVigPFHzNanR4r96fAQiGFTCrBye3f4EZaIvq8OveetmuhkOFmcTm+P56OiG6cyaw+YLBBRPVGfn4+5syZg+effx7BwcF1XRyif23VqlVGnxUKBaKjo6vkUzlb4XxmEdr/pxuCu3Q3LJdIJOj79LPo+/SzRvmFECjXCjham6GBlQKffPKJUXqHDh2wbt06CCFw6dIlHD16FJ9++ikKCwvRsWNHhISEoG3btjAzM7uPR3v3hBAoKNMis0CNmyUaaHR6yKUSNLAyQ2Mbc9hb3H5wMwFnMwqQV6JBA6t/97c8uP4zuLVqj+ZtQqqk2VsocCw5F0Pbu/7r7dOjg8EGEdULZWVliIyMRPfu3dGvX7+6Lg7RA2FlLodvY2vEXyuCWitgJkO1N9kVrRmATlcRaLRwsrztzbhEIoG3tze8vb0RHh6OzMxMHD16FD/88AMWLVqEtm3bIjg4GB06dICtra0pD9GIWqvHuasF+OPyTeQUl0OKigHOkAASAchkEugF4GChQI+WDdDW1RYWirsb8Fxf/BKbBYXs3w3tFUIgN/MK3Fq1rzZdKpVAD+Bg4k0M8G98D6WkRwGDDSJ67Gm1WixcuBDu7u54/vnn67o4RA+UjVIOP1cbZOSW4UaxBgICUomoCCYEoBcAIGAul6K5gwWcbO6+f76LiwsGDhyIgQMHoqCgAMePH8exY8ewcuVKeHh4IDg4GCEhIXBxcTHJMQLApZxirP/zKorUOpjLJbBTymoMrEo1Wvx49hp+jc/BcwFN4OtsxZaOW1xJz8SGFR+hJCsFZhZW8Gzf3Sg9PzsD5/f9jBtplyH0elg3aATvzk/A1btidrKfPpwIAPhzewz+3B6DQTOWQa/T4vy+rci4cALqkiLILKyR7dcefRfPqPOWMDItBhtE9FgTQmD58uWQSCR47bXXeENB9ZKFQoaWjazQXKfH9aJy5JVqodMLSCWAuVwKJxtz2JhXf3N+t2xtbREWFoawsDCUl5fjzJkzOHr0KKZPnw5ra2tD4HG/xnnohcD2C9nYn3gTSrkU9pa3v7WRSCRQKmRQKmQo0+iw5lgaOja3x6A2jfmW67+8v+ADlBXcQOfhE2BmYY3Lx/YgK/EC5GbmEELg8KYVsGngjO6j34RMoUDquaM4vmU1bF6cAVunJgh9aSZ+X/0B2oQ9CzffdgCA+IO/IOX0QXQc+BJsHF1QcOMaDv+wGjHffouXXnyxjo+YTInBBhE91r777jukpKRgwYIFfGkf1XsKmRQudkq42D2Y/ZmZmaFDhw7o0KFDlXEeRUVF6NixI4KDg//1OA8hBH46l4UjKbmwU8ohvctgQamQwUwuxdEredBoBZ4LdKn3AUdGRgbi4i/Cs9NQODZtCQAI7DcCO5fPNuTpMmISzJSWMLOwAgB4d+qHi4d+Rc6VS7B1agJzS2sAgEJpAaV1xcnm2b4HmrUJgbWDEwDA0tYBTi1a49DREww2HnOseYnosfXrr79i3759+Oijj6BUKuu6OET1WnXjPI4cOXJP4zyOXsmrCDQs5P/6HRBSiQQOFnKcyshHEztzdG/Z8F9t53GRlpYGvQAsHZsYlkmkUti7NEdBzlVIJBJoykpwfu9PyM28Ak1ZCYQASktLUVKYX+N2pXI5rhw/hMxLZ1FWXACh16GsXIPmPs0exGFRHWKwQUSPpWPHjmHdunVYuHAh7Owe0GNcIqo1FxcXDBo0CIMGDTKM8zh69ChWrlyJFi1aGGa3qmmcx82Scvwcmw1rc9kdA43Tv/+Mc3/swOj3VlSbLpFIYGMuw6/xOfBxtoazjfk9H9+jqrS0FAAglxt/B3Kzis8l+Tew/9tPYefshnZPjoJOqkBaWhriflmDgsLCGrd74uc1uJ6agDa9hqBBE3dI5Qr8uWcLIOEL/h53DDaI6LFz8eJFLF26FHPmzDHpgFQiuj9qGucxbdo02NjYICQkBMHBwUbjPH6Lvw69EFDI7s9sUnKZFCjXY8eFbLwY3PS+bPNRZG5uDrlMAujLjZZrykoAAJkJ56DTliPo6RdwPa8QuXm58GipQrK5GbQaTbXb1JSV4FriBbTq9hTc23YCUNEFTqsph5n5v5vxih4dDDaI6LGSkZGBefPmYcqUKfDy8qrr4hDRXbp1nMf48eNx6dIlHDlyxGich3/7YJzOsYa18v7exlgrZYjPLkZuiQYOlvXz7dZubm6wUMhQkJUGuFUEXTqNBjcykmGmtIRep4NWq8WlpBTY2zugjV8bpJw+AKlUinKNcYACIf76RwAQMLOwNiQVF+YjPz0B8lZuD+rQqI4w2CCix0Zubi7mzJmD8PBwBAUF1XVxiOge3TrOY8yYMbh69SqOHj2KDXsO45pVC9gp5bC3t4e9vT3kinu/pZFKJBBC4FxmIbp5NrgPR/DoadasGVSeHthzdCcaOjWChYUlLh3ZBblcUTFtMBQoKSmGuJ4M5xbNkXr2MLISz8OmQSMUZl9FWXEBFOaWACS4npoAe+emsG7gDCt7R1w5dwSOzVqivLQEJ37dAL/AIORnX8SVK1fg5uYG2X1qpaKHC9uuiOixUFpaisjISPTq1Qu9e/eu6+IQkQk0adIEgwYNQpcnh6CFhwfs7e2Rm5eHM2fPIj4uHteuZUFdpr6nfShkEiReL75PJX40zZw5E15NG+N/3y7FwfWfwaahMxya+yA3Nxe2zs3Q4YnhuBZ3AntWLUB2SjyCBoyBZ1B3FGWn4tSv30OmUMArOBQZ8adwYN1SqEuLEDRgDHSacuz9+kOc3vk9WnR6CuPHhsPOzg7Tp09Hfn7Ng8vp0caWDSJ65Gm1WnzwwQfw8vLCsGHD6ro4RGRiqbmlsFQqYG7tCEcnR+j1AgUFBcjNzUVmZibkcjkc7O1h7+AAayuru9q2uVyKtNwyE5X80eDq6oovln6MWT9dgK25FOlpaVBaueCJbk9XTLjh7o5WXZ8yWserYxg0Ni5o+lfXK7+eg+DXc5Ah3dLWAWFjZwEAyjQ6SCUShLb3QZ+vv35wB0Z1gsEGET3ShBCIjo6GQqHAq6++ypf2EdUDxeW6ikHMf5FKJbC3t4O9vR0ggKLiYuTl5iI5ORlarRY3b9yETqer1bZlUgkKy2qX93HmYqeEh4Uaey9cRUNrc/j5+d2xm5OF0gJlZWWwsbGpMY8QAkVqLV7p6g55PX+nSX3BYIOIHmnffPMNMjIyMH/+fPb3JaonbvtMQQJYW1vB2toKbk3dUFamxpGkcygqKkJcXBycnRvDwd4ektvc6Nb3ZxbFxcX46quvkBQbB/fg0VBaWNXq+qpUKlFWdvtWodxSDdq42qJTi/o5JqY+4pgNInpkbd++HYcOHcK7774Lc/P6Oy8+UX1jbS6HVidqlVepNIe9gx1s7ezQ2LkxsrOycObsWVy9mgmtRlslv1YvYG1Wf5/FHj9+HOPHj4eZmRk+X7oYMwe0RblOoFRz59aeOwUb+aUa2FsoMLazO1uh65H6+7+JiB5phw8fxoYNG/Dhhx/W+m3DRPR4cHewwIm0fCgVtX9mKgHg0MABDg0cUFJcgqzsbJw9exYODg5wdnaGpZUlAECt0cPT+e7GeTwOCgsL8eWXXyIuLg5Tp06Fv78/AEBlAUzt5YklexKh0epha1HzlMA1BRtCCMN0wtP7qWBfT6cVrq/YskFEj5wLFy5g2bJlePfdd9G4ceO6Lg4RPWCejpaVr3D4VyytLOHh4Q5/f38olUpcSkhAXFw8bt7MhVYv0NLJ8n4V9ZFw9OhRTJgwAdbW1oiOjjYEGpVaN7HFO096w9HaHDeKy1Gu1Ve7HXNzc6jV6r/eq1ERZJSU63CjWIPApnZ4t78PGtXjt7PXV2zZIKJHSlpaGhYsWIA333wTnp6edV0cIqoDvs7WkEsl0OrFPQ0ylivkcGnigsaNGyM3Lw/XsrKg1ucgUR2HVg16PfBWUyEEEq5k42JyFs5eSsf5y5koLC6FXi9gbqaAu2tDBPo2hcrdGf4qV1goze5pf4WFhVi5ciUuXryIt956C35+fjXmbd7QEpFP++DX89nYEZuFouJyyKQSWChkUMgkkEgkkEqlkCsUKCwpgxYVYzwaWpnhxU5NEdTcgV2n6ikGG0T0yLh58ybmzp2Ll156CYGBgXVdHCKqI0qFDB2a2+NQ8s1avek7IPRpBIQ+XWO6RCpBgwYOkCqt4W6lQ8653Rg3bhw6deqEAQMGwMPD434Wv4qS0nLsPXYRMVuPIi3zJgQAmUwKS6UCcpkMUqkE6nINzsSn4ciZJMhlUijkcjwT1hbPhAageZO7H2x9+PBhrFixAl27dkV0dHStxr0pZFIM8G+Mvq0a4XRaPo4k30RSTglulmgg/SuQkFnYQqJVo4tPU3TybABvZ2sGGfUcgw0ieiQUFxdjzpw56NevH0JDQ+u6OERUx3qpGuJUej7KNDooFfc+E125Vg+FXIrnO7WEXZgf8vPzsXPnTsydOxdNmjTBgAEDEBwcfF9nvRNC4OCpRMxfsQOFxWWwsDBDo4Y2Nd6cK80VsK8sr0aL9b+cwIZfTmBI33YYN7QbLC3u3NKRn5+PL774AomJiZgxYwZ8fX3vutxmcik6ejigo4cDAKBYrYVaq4dEAny39jjcHPV4pnOXu94uPZ44ZoOIHnparRYLFixAq1atMGTIkLouDhE9BKzN5XguwAWlGj10+nsYwAFApxcoKtdhUBtn2P01ANrOzg7PPfccVq1ahSeffBI//fQTXnnlFWzevBmFhYX3XP7C4jLM/Wwbpi3aDL0QcHa0ha2VstatAGYKORo72qKhgzU27vwTI6etwrlLGbdd5+DBg5g4cSIcHR2xdOnSfxVoVMfKXI4GVmZwsDRDc7cmyMi4fTmofmHLBhE91IQQWLJkCaysrBAREcHmeCIyaO1igyd8nbAjLge25jLIZXf/DFWnF8gv1SLUqyHaudlVSZfL5ejatSu6du2KhIQEbNu2Da+88gq6dOmC/v37w93d/a73eSOvCJMXrEdyxg04N7SBVPrvn/3KZVI0drRFfmEpXnv/OyyYPBBdg7yM8uTn52PFihVITk7GzJkz71uQUR1XV1ccPnzYZNunRw9bNoioTgghUFCqRVa+GlfzypCVr0ZeiQb6fzyhXLNmDbKzs/Hmm2/eU4VMRI+nnl6OGNTGGcXlehSW6QwzIdVGkVqLQrUOT7ZqhH6+Tnd8mOHl5YXXX38dK1asgKOjI+bMmYO3334bR44cgV5f/QxN/5RfWIqJ879HauZNNHa0vW/XNTsbC9hYmmPmkh9x6FQigIrr7P79+zFhwgQ0atTovrZm1MTV1ZUtG2SELRtE9EBp9QI3i8qRXVgOrU7g1tsCCQCpBHC0MYOjtRl+3bENx44dQ1RUFMzM7m3WFSJ6fHXyaABPRyusO3kVmYVqSCWAtbnMMGj5VnohUKzWQS8ARyszjGjXBK72yrvan729PYYPH44hQ4bg0KFD2LRpE7788kv0798fvXv3hrW1dbXrCSEw97OtSL16E86O93+mKwulGYQA3v70Jyyb9Sx+3rwOaWlpeOedd+Dt7X3f91cdJycnFBYWoqysDErl3X2v9HhisEFE92Ts2LFo27YtJk2adMe85Vo9ErNLUKbVQyaVQCGv+kRPLwSyCsqRlJ6D3/cdQGRkJGxsbExRdCJ6jDjbmGNSd3ck3SjBwaRcxGcVVTzB+EdDhwDQ0tES3TwbwtPRErJ7mTpXLke3bt3QrVs3XLp0Cdu2bcPLL7+Mrl27on///mjevLlR/l/2x/4/e3ceHlV99n/8fWbPTGay7wkJIQkk7KCogOK+4VYtWiqKoKKtS7XU+rTKJlCRqhWt/bX2KShudaFUxeWhiqWKCBYVSMIWQvaN7JPMPnN+f0QiMawhyYTkfl1XLs2Zc77nPrlIJp98N7bsOEB8DwSNQ0JMBiprarnhrqX8z8zJzJ07t1f/WKMoCgkJCVRUVJCent5r9xV9l4QNIUSv8PoD7Kt24PUHMBwhZByiURTcDjsVlZX89O6HsEWc/JKOQoiBSaMoZERbyIi24A+o1LZ6qGv14AuoaDUKkWY9MaHGU9qb42iysrL45S9/SUNDAx999BHz5s0jJSWFa665hjPPPJO6xlaeWvUvwq0hPTb3zOPxUFRUjMvlwhqRjDVxZFB6hQ8NpZKwIUDChhCil5TWu/D6A0fszTic0+GgoKCAIRkZGE1GCg86yU6wyMRwIcRJ0WoU4qxG4np5x+qIiAimT5/OtGnT+Pzzz3nzzTd54YUXMMWPodXpJtzW/buTqyrU1dVSUlJKbGwMGRlDcHt8/O+az7nmgtHou2Fp4JMh8zbE4SRsCCG6VUlJCQ899BBTp05l165dREdHM3L0GP6y8mWaGxtITE7hplvvIDU9A4BAIMBH7/2Dzf/ZQGN9HT5/gDPPnkROTg46rYaH75/D9ddMZdatNwPQ0NDArbfeyuTJk3n44Yfb73vrrbdy3XXXcf311wfluYUQ4nA6nY7zzz+f888/n9y8fKb9ciUt9mYKNr9ObNIQss+8rFvu09abUYTb7WHo0CwsFgvQNpyqqraZLTsOMHl8Rrfc60QlJSXx7bff9uo9Rd8lS7sIIbpNU1MTixYt4uyzz+bWW28FYM+ePfz7P19w+z1z+eWji3G73bz8v39qv+a9t1/n4/ff4errb+LGmXdz4y23s3dXHqv/+kcAsnJG8M2OvPbzc3NziY6OJj8/v/1YeXk5DQ0NjBkzppeeVAghTlydQ0dUTCxjRo9Ao9FQXV3D7t17aGhoPKnVsw6nqnDwYC25uXmYzRaGDx/eHjQOMep1vP7B1u54hJMiPRvicBI2hBDdwuPxsHjxYhITE7nvvvvajzc3N/Pj2+7Hi/D8AAAgAElEQVQmOTWNQWnpnD35fCrLS/G43Xi9XjZ+/BHnX3IFtshYUgenc8HFl3HV9TeyfdtWmhrqyR4+kj17duP3ty0ruXPnTs4//3wcDgeVlZUA5OXlERYWxuDBg4Py7EIIcSxbdxahKAoGgwGz2UJSUiLR0VFUVJSzY8cOqqqq8Pn8J9yex+Nh7949VFdXMXToUJKTk9AcYR6KzWpix97yk2q7OyQlJVFRUdHlICX6FxlGJYToFs888wxut5vFixej033/oyUlJQWt3sih98FQa9sqLI7WFlpbW3C7XZgsVvR6PYMGDQJFITU9A1VVKS0pYtjwkbicTvYfOEBWxhByc3OZPXs2e/fuJT8/n4SEBHJzcxk9erTM6xBC9Ek79pRhNn0/UVtRFKKjozHpVAp2/Ie8PRvwej2EhseQMepc4lMyaTxYSv7m9xh57vVYI+KBtt6MksJd5H/xT4aMvYScnPG0NFaRt/1ftDbXgqoSFpPC4BGTMZgsaDUaFEWhpLKe9JSYXnteq7Vto8KmpibCw8N77b6ib5KeDSHEKdu0aROff/45zc3N+Hy+Dq8ZjR0nZx4KBCoqLqcTp9OJoihtq5Z895rJFAKAy+kgIjKamPgEduXn09TURHl5OdnZ2eTk5JCX1za8Ki8vj7Fjx/b0YwohxEnzev0UlddhNuk7HPe4Wsnf/A6mEDNnXzaDc664DZMlgm82rmHnN1tRdRb0xhDqKw8A4Ha39WaU7c8lPDKazOHjcLU2kr/5XXR6IyMmXkf2WVfhdjST/+U6VLWtN1hVVQrLanv9uWUolThEwoYQ4pSFh4fz7LPPotVq+eMf/9jpdZ1WQ+AIvektra34vD5iYmJQDttF1+l0ABBitqCqKlnZI9izexc7d+4kLS0Ni8VCTk4O+fn51NbWUlNTI/M1hBB9UqvLjQqddgqvKdlNIOAnY8xFWMJiCIuMY/yU64iJTUB1HqS8vBJnwEhZYS5VVVXk5eVitVoxadzEDRqGomioPLADrc5A5rhLMNuisEbGkzHmQhzNdTTUlADg8/lptDt7/bklbIhDJGwIIU7Z8OHDSUtL48EHH2Tz5s18/PHHHV6PsugJ/CBtNDU24fMHiIqOpriwoMNrBwr2oigKKamD8flVxo8by+7du8nNzWX48OEADBs2jMrKSj777DOSk5OJjo7u2YcUQogu8PkCHGmAZ0tTDWZrJDp9x+FVoeEx4HMyfPhwModPwGFvpGBPLkOGZBBm0eN2NBOTlNnWRkM11sh4NNrvl7Y126LQGYw4mtp6M1QVfP7enbMBEjbE92TOhhCi24wcOZLrrruOF154gREjRrQfj7ToqWpyt08W9Pv9lBQXM37CWVx4+VV8+n/vE5+YzJCsYZQWH+CDf77FWZOmYLWF4fOrTD5rHKv//AxbtmzhjjvuACAkJIS0tDTWrVvHWWedFZTnFUKI49HrtEecKO33edDqOm+4p9UZ8PsaURSITxlCeVQMBpNKSUkxoRo7RrMVa2T8d214aaguZssHf+3Ytt+Lx93WQ6zRKBh0vf/rXlJSEhs2bOj1+4q+R8KGEKJb3XLLLXzzzTc8/fTTKIqCVqvFoNMQbtbR6PDh9XhobWllUGoqFouFq66/Ca1Ox3v/+DvNjQ3YwsI5+9zzuer6n+APqJj0GmIjLAwZMoR9+/a192xAW4/Ke++9x+jRo4P4xEIIcXShZiM6nRafP4BO+/2AEp3OiMvZ3Ol8n8+D9rveDkVRiEocQnNdJRGJw9i7dSPpw8a1n6vV6wkPTSFtxORO7ei+CzI6rYaocEun13ua9GyIQyRsCCFOyd/+9rcOn+v1ep577rlO5yVHhNDsaCRu0BCe+stqYuPigLY30yuv/TFXXvvjDuf7/AE0isLgaDOKovD00093anPOnDnMmTOnG59GCCG6l1arITM1lqKKOmwWU/txS3gMDTXF+LxudPq2hTTUQIDWxhoiE9Lbz4tKzKCycCepRgXV58Lu1hEIBNBoNISGx9FcW47JbOuwGp/DXo/O0HYvFXp1JapDEhISqK6uxu/3o9X27g7mom+RORtCiF4R8Ht546/PYNQphEfF4A+oRx5aEFDxev1oNQqZcWaMevkxJYQ4vY3NTsHh9HQ4FjcoB41Wx95t/6K1uQ5Hcx0F327A53UTnzay/TxrRDyGkFCKd20iOi4Zsy2KgoICAgGVhMEjcTvtFO7YSGtzHc6WRop3bWb7xjdxtjTg8/vRaTUkxYb19iNjMBiIiIigpqam1+8t+hZ5FxdC9DhVVfnDH/5AmNXCZWePYFCkCb1GwedX8fgCbR/eAF5fAA2QEGFiWLwFk17+GiaEOP1NGDUYzQ/2AdIbQxg+8TpUNcDOz9aw47O3cTtbyDnnGszWiPbzFEUhOjGD1qY6YpKy2pYJBw4cKCQkNJKcs6/B2dLAzs/eZvvGN7DXV5Fz9tWYrZE0Njk4Z0x6p5WweosMpRIgw6iEEL1g1apV1NfXs3jxYrRaDVGhBiItehweP05vAH9ARasoGHQarCatbM4nhOhXxmWnEBVuodXpZvzFt7Qft9iiGH7ONce9Pm34RNKGT2z/PCMjgz179lBcXERqahojJv2o0zWqquIPqNx4+Rnd8xBdcChsnHFG8GoQwSc9G0KIHrVu3Tq2bt3Ko48+isHQcYlHi1FHdKiBOJuRaKsBW4hOgoYQot/RaDTcfNUEmltc3dZeVlYWra2tlJeXHfGcFoebhJgwRg9N7pZ7doX0bAiQsCGE6EFbtmzhrbfeYuHChVit1mCXI4QQQXPllJFER4R2W+DQarVkZQ2loaGBysrKDq8FAgHsrS7un3FhUP+AI2FDgIQNIUQP2bt3L88++yyPPvoo8fHxwS5HCCGCyhJiZP7Pr6LV6cYfCHRLm3q9jqFDh1JTU9NhInZNfQuXTMxh8viMbrlPV0nYECBhQwjRA6qqqliyZAn3338/mZmZwS5HCCH6hDOGp/Kji8dSXdd8xNX4usJgMDB06FAqKiqoq6ujsdlBhC2EX952cdCHpcbExGC323G5uqc3R5yeJGwIIbqV3W5n4cKF3HTTTbKztxBC/MADt1zEpLEZVNU2E+imwGEymcjKGkpBYSmtra2s+M1PCLeau6XtU6EoCgkJCVRUVAS7FBFEEjaEEN3G4/GwePFizjrrLKZOnRrscoQQos/R67Us/cW1nDs+k6qDTXi8vlNuU1VVWlw+0tPTiFP34Wyu7oZKu4cMpRISNoQQ3eLQXhpRUVHcdtttwS5HCCH6LKNBz9JfXMt9My6kye6ktqGly8OqnG4vVbXNjM8ZxFsrfs7ieb9i2bJlFBQUdHPVXSNhQ0jYEEJ0i0N7aTz44INBHycshBB9nU6n5adTJ/DyE7PJSoujps5OTV0zPv/xJ4+rqkpzi5Oq2ma8Xj+P3HUlf/ifG4mLsjFq1Cjuu+8+HnvsMUpLS3vhSY5NwoaQTf2EEKfs0F4av//97zvspSGEEOLYUhOjeGHRDHYVVvH2+q/5ePMuFMDnD6DTatBpNaBAIKDi9vjRaRUCKqSnRHPz1AlMOTMLk1Hfoc2zzjoLh8PB/PnzWbZsGXFxccF5ONrCxvvvvx+0+4vgk7AhhDglh/bSeOKJJ2QvDSGE6AJFUcgZksD8n01l7m0XU1hay/7Sg+QVVNDQ7CDgDxBiMpCZGktmWhxDUmKIi7Iesxf5ggsuwOFwMG/ePJYtW0ZkZGQvPtH3DvVsqKoqvd4DlIQNIUSX7du3j2effZaFCxfKXhpCCNENLCFGRmYlMTIriesuGnNKbU2dOpXW1lbmz5/P448/HpQ/CFmtVrRaLU1NTYSHh/f6/UXwyZwNIUSXyF4aQgjR902bNo1x48axaNGioO13IfM2BjYJG0KIk3ZoL40bb7xR9tIQQog+TFEUZs2aRWpqKkuWLMHj8fR6DRI2BjYJG0KIk+LxeFiyZAkTJkyQvTSEEOI0oCgK99xzD1arleXLl+P3+3v1/hI2BjYJG0KIE3ZoL43IyEhmzZoV7HKEEEKcII1Gw9y5c/H5fKxYsaLL+3p0hYSNgU3ChhDihL344ovU1dXJXhpCCHEa0ul0/OY3v6G6upoXXnih1wKHhI2BTcKGEOKEvP/++2zZsoV58+bJXhpCCHGaMhqNzJ8/n/z8fF599dVeuWdCQgLV1dW9PnxL9A0SNoQQx7VlyxbefPNNFi5cKHtpCCHEac5isfDYY4+xadMm1q5d2+P3MxgMREREUFNT0+P3En2PhA0hxDEd2kvjkUcekb00hBCinwgLC2Px4sWsW7eO9evX9/j9ZCjVwCVhQwhxVIfvpZGVlRXscoQQQnSj6OhoFi9ezKuvvsrnn3/eo/eSsDFwSdgQQhyR7KUhhBD9X2JiIosWLeLPf/4z27Zt67H7SNgYuCRsCCE6kb00hBBi4EhLS+PRRx/l6aefJi8vr0fuIWFj4JKwIYToQPbSEEKIgWfYsGE89NBDPP744+zfv7/b25ewMXBJ2BBCdPDSSy/JXhpCCDEAjRkzhnvuuYdFixZRVlbWrW3HxMRgt9txuVzd2q7o+yRsCCHaffDBB3z55Zeyl4YQQgxQ55xzDjNnzmTevHndulStoigkJiZSUVHRbW2K04OEDSEEAFu3buXvf/87CxYskL00hBBiALvooou4/vrrmTdvHo2Njd3WbmJiogylGoAkbAgh2LdvHytWrOCRRx4hISEh2OUIIYQIsquvvpoLLriAefPm0dLS0i1tyryNgUnChhADXHV1dfteGkOHDg12OUIIIfqIm266idGjR7No0aJumWshYWNgkrAhxABmt9tZsGAB06ZNk700hBBCdKAoCrfffjspKSksXboUr9d7Su1J2BiYJGwIMUAdvpfGVVddFexyhBBC9EGKonDvvfdisVh48skn8fv9XW7rUNhQVbUbKxR9nYQNIQYgVVV55plniIiIkL00hBBCHJNGo2Hu3Lk4nU6ee+65LocFq9WKVqulqampmysUfZmEDSEGoJdeeona2lp++ctfyl4aQgghjkuv1/Pb3/6WiooK/vrXv3Y5cMhQqoFHwoYQpxlVVamod7BpTw3vfFXKP7aU8M5XpWzee5DKBudx3wBkLw0hhBBdYTKZWLBgAXl5ebz++utdakPCxsCjC3YBQogTU3ywhfe2lbN+ewVefwAFBa8/gKqCooBeq6CqYNBruXJsIleOSyIlytKhjUN7aTzxxBOyl4YQQoiTZrFYeOyxx3j44YexWCxce+21J3W9hI2BR8KGEH1cdaOTFR/sZlthPQoQbjGg1x29U9LjC7B2aylrt5ZydmYM910xlCirsX0vjfnz58teGkIIIbosLCyMxYsXtweOiy+++ISvTUpKYsOGDT1YnehrJGwI0Uepqsr6HZX88cM9+PwBYmzGE5pfYdBpiLGZCKgqW/Yd5Nuiem6bFM/aFx6XvTSEEEJ0i5iYGBYvXsxvf/tbzGYzEydOPKHrpGdj4JGwIUQfpKoqf9uwnze+KCLcYsCkP/m5FRpFIdpmwu5w8/CLX/CjCT9iwoQJPVCtEEKIgSgpKYkFCxYwf/58TCYT48aNO+b5Lo+P5oCZHdUqK97ZgcsbQKtpe6/KTAojPc5GfESILFzSz0jYEKIPWr2xkDe+KCLGZkSr6fo6DmogQHlxITFhFrbVh/L2lyVMOye1GysVQggxkKWnp/PII4+wZMkSHn30UbKzszu8rqoq+SUNvL3pAB9vL0ejQJF2GK99uhej0QCo+PwqOq2GgKoSGxbCzedncMnYZGxmWcSkP5DVqIToY74urOPVzw8QbT21oAEqhQcOoNPrGJyaQlSokf/9pID8ssZuq1UIIYTIzs5m7ty5LF26lMLCwvbjxTV25vzxP9z1/Gd8/G0ZkaEGom0mIsxaQg0qMWEmYsJCSIg0ExNmIjbMRKvbyx/+uZNrFn/Ea//eh88fCOKTie4gYUOIPqTF5eWJd/KwGHXotKf27VlWWobH4yY9fQigoNdpMOo1LFubh8vb9R1ghRBCiB8aN24cP/vZz1i0aBGlpWW8vrGAW576lL1lTcSGmYgND2l/XzOZQnC5nJ3aUBSFUJOeuIgQrCY9f1yXx5w//ofiGntvP47oRhI2hOhD3txcTGOrl1CT/oSvOfDf9fz7hf/pcKymppr6hgYyMzPRHNY7EmY2UNXk5J2vSrutZiGEEAJg0qRJTP/pzVz/8F95eu23hJn1RIeZOs3BMJmMuFyuY7Zl0GuJjwihsNLO7c/+h9zi+p4sXfQgCRtC9BEur593vyoj3HLiQeNIGhsbKS+vYGhWFjpd57bCQgy8/WWJdE0LIYToVqqqsq0xmlbzYBoqi1E48iazJpPpuGED2no6omxGFFTu/8sX7JFhwKclCRtC9BGb9xzE5fFj0Gm73EZraysHDhSSmZmJ0WQ64jkmgxa708t/99d1+T5CCCHED63dXMS6r0oYmpZAVFQke/bswefrPGy3bRjV8cPGITazAUVReWjVl7Q4vd1YsegNEjaE6CM27TmIVtv15f7cbjf79u0lLW0woaGhxzxXAbbsq+3yvYQQQojDlde18uy7uURZjWg0CklJSVitVvbu3Yv/Bz3pBoMBn8/X6fixhFuM1DW7eW5dbneXLnqYhA0h+oj8skbMxq6tRq2qKnv37iEhIZGIiIjjnh9i1JFbKt3RQgghusfv12wnoAYw6tt65xUFBg0ahMlkoqBgH4HA90OqFAWMJziU6nAxYSbWbS1hxwHpmT+dSNgQog9odfuos7sx6k7+W1JVVVpbWwgLCycuLu6ErgnRaymtc8i8DSGEEKesqNrOf/cdJNrWNnx32z+epuCLf6IoMHhwGhqNlsLC/aiHTeEwGU8+bGg1ClqNwqsbC7qveNHjJGwI0Qe0unxoNEoXdk1VOVhzEEVRGDQo5YSv0mgUVBVZAlcIIcQpW7u5CBTa38NGXXkXaWdcDrQdGzJkCD6fn6KiA+2B40Qnif9QpNXIpvwqaho7L50r+iYJG0L0Aap65BU7jqesrBx/wI/ZYqFtJsaJU4CAdGwIIYQ4Baqq8v5XxUSEfr/bt95kQWf4fpESjUYhMzMTp9NJaWkJqgqmkK6FDa1GIRBQ2ZRf1S31i57XtQHiQohuZTJoCQTafmifaO9Gbe1B6uvriI2Npaxy10ndT1VVAqgY9fL3BiGEEJ1t376dV155heLiYgDS09OZOXMm2dnZeDweVq9ezcaNG2lobmFPtZbsiVdiiE4G2oZRhcWnkzHxOgAcjTUUf70e+8EyyhrqqIxLY8hZV7WHjZr931CwaS1jr72fwq3raKktQ2swkTDsbJKGT26vqam6iJKv19NQU8FjX8XQcsePmT59Ojpd26+zu3bt4pVXXqGwsBBVVRk7dix33nknkZGRvfmlEz8gv2kI0QfYQvSEmnR4/SfWw9Hc3ExpaRmZmVlotSe/VK7bGyDWZmqfyCeEEEIc0tLSwpIlSxg6dCgrVqzg6aefJjk5mUWLFuFyuXj++efZvHkzDz30EHc8MB+DJYJdH6/G42ju1JbX1Ure+lX4vR6GX3QLZ/7ofhwOB/kfv4ijpbnDPI79W94lIfscRk39GVGDcijetp6W2nKgLbDs+mQ1trg0Rk69m/Dhl/Lhhx+yevVqAMrKynj00UcJDQ1l2bJlLFy4kKqqKhYsWEBAuvGDSsKGEH2AoigMTbTh9PiOe67L5WT//v0MGTKEkJCQLt3P4fGRkxzepWuFEEL0bxUVFbhcLqZMmUJCQgLJycncddddLFiwAJfLxaeffsqMGTMYNWoUXn0Y0SMvJTwpE1dL51UOawq+xudxMXTKTYRGJxERl8KZV9+Jo6WZlsrd+Hzf75sRlzGeyOShhNiiSB45BYCWurawUbVnC4YQK6njLiU8Kg6XOYnZs2e3X/vuu+8SEhLCr371K1JTUxk2bBgPPPAARUVFbNu2rYe/YuJYJGwI0UdMyIjCfZwJ2z6vl71795KSkozNZuvyvXx+lTOGSLeyEEKIzgYNGkRsbCzLli1jzZo1FBYWotPpyM7OZv/+/aiqypAhQwBwe/1odHqyzp2GLXZQp7bstWWYw2PRmyztx0Jt4cQmDcbvaMBut39/PCqp/f91RjMAPk/bRPCWugoskYlA2x/oFOC8KRe0B449e/aQk5ODXq9vbyM1NRWr1UphYWE3fWVEV8icDSH6iCnD4/nLv/bhD6hoNZ3nbQQCAfbu20dkZBTR0THtxwefcSmDz7j0hO/j9QfQaxUmDYvtlrqFEEL0LyaTieXLl7NmzRrWrVvHiy++SGxsLLNmzcLv97efA6DXaeAYI4D9XjetDVVseX1Jh+MBn5eIiGQqK6uINrYd0+i+Dwrt8xe/G2fl87gwh+m/O6SiqnR4r3Q6nWzdupVp06Z1uI/b7aahoeHkvwii20jYEKKPiLAYmDI8jo151e1rlX9P5cCBQoxGA8nJSUe8/kQ1tLi5anwyli5uICiEEKL/i4qKYs6cOcyZM4cDBw7w5ptvsnz5cu644w4AHA4HAOEWA1rt0Rc20RlMWCLiyTrvxk6vKVo9+4vKsNs7z/X4Ib3Jgs/rBtp6561mPVrt9wN0zGYz48aN48477+x0rdlsPm77oufIMCoh+pBbz0tHq1E6DacqKyvH7fYweHA6J7vE7eGcHj9GvZafTEo7tUKFEEL0W5WVlXz11Vftnw8ePJh77rkHVVWx2WzodDry8/MBSI+3oagB8tavoq44r1NboVFJuFsaMIRYCbFFtX+oagBjiIWUlBQOHjyIeqzuEcASmUDLwdK2jWzdXoYlh/Pxxx/z2GOPAZCVlUVFRQXx8fEkJCS0f/h8vlMadixOnYQNIfqQxEgzcy7JpKHV0773xqElbrMyM9Fouv4tG1BVmhwefnHFMGI69ZwIIYQQbSorK1m6dCnr1q2jqqqKyspK1qxZg8FgYMSIEUyZMoXXXnuNHTt2YPDZqfjmI+x1FYR+t/Tt4WIzxoGisO/zt2mpK8fZXEd53ia2v/c8TVUHsNmsGI0mPG7PMWtKGHoWXreTwi3v0VRfS7R6kJdeeonExLZ5HFdffTU1NTU8//zzFBUVUV5ezksvvcT9999PaWlpj3ydxImRcRRC9DFXjUtma0EdXxXUYcRNaWkZw4YNQ3fYpLeTpaoqNU0uzh8ex4Uj47uxWiGEEP3NuHHjuOeee3jnnXdYtWoVer2etLQ05s2bR3R0NHfffTcrV65k+fLluN1uInRGNGffhNES1qktvcnCiMtup2jb/5G3fhUBvx9zRCxZ504jPDEDgJjYGKp3uPD5fBiPUlNIWDTZF86g+Ov1NOzexje1g7l26qXcfPPNAKSkpLBkyRJWr17N3LlzAcjMzOSxxx5j0KDOE9dF71HUo2xdXFZWxkUXXcQnn3xCcnLnpCqE6Dkur5+5f9vE+q17GJaeRHhY5x/gJ8ofUDnY7OKcrBgevWEkBp10aJ5O5Gfx0cnXRoi+YeveGn75v5uJC+/acuwARUXFKIpCauqxg0Gzw0NsuJlX5l5wwpvgip51vJ/F8luHEH2Q29GCc9srXDIqHrdqoMXlPf5FR2B3eqltdnHtmcnMk6AhhBCiB4wfEk20zYTd2bX3KoCkpCTq6mrbdxU/ElVVaXX5mHF+hgSN04j85iFEH+PxeFi6dCnnnzuZPz1wNUunj0Gv1VDT5MTu9HKUzsh2qqrS7PRysMmF2ajl97eO597Lh7UtTyiEEEJ0M61Ww8M/HkOL00sgcOz3qKPR63XExydQWlp21HPq7R4yE8O4ZKz0ZJ5OZM6GEH2Iqqo888wzREVFccsttwBwZkY0L94zkU27a3jji2LK6h0oQEAFo16DgoKKitsbQKNpW5I8LSaUGycOYuLQWEx6bXAfSgghRL93zrA4rjxjEB9tKyUuomvDqeLj49ixYyd2ewtWa2iH1zxePwFVZeFPx6PTyh/PTicSNoToQ1555RVqamr43e9+16GL2GzUccnoRC4elUBpnYMDNS3sLm+ipLYVr1/FoNOQGm1hWJKNwbFWkiJDpItZCCFEr7r/mhHsLK6nst5BTNjJr3qo0WhITk6itLSU7OxsDr2Nef0Bau1ufvWjUQyOl2VsTzcSNoToIz755BM2btzIU089hcFgOOI5iqIwKNrCoGgLU3LierlCIYQQ4uhsZgPP3TWJn/+/z6ludBJjM570H76ioqKpqqqmoaGeyMhI3F4/dXY3d1+RzQ2T0nuoctGTpB9KiD5gx44drFq1igULFhB2CitPCSGEEMEUGx7CX+49l+GDIqhqcHbapPZ4FAVSBqVQUlLGwe/mKv7mx2OYedHQHqpY9DQJG0IEWVlZGcuXL+fXv/41KSkpwS5HCCGEOCVRVhN/+tlk5l4/ihan96RCh6qqBDRGAnoz5oCdl+deyDVnp/VswaJHyTAqIYKoqamJRYsWMXPmTEaNGhXscoQQQohuodEo3DAxnUnZ8by7pZi3Pi+kqdVDIKASYtRhMmjRaBRQ2+ZkONw+fH4VRYERqZHcfVEy76x8isiQ64L9KOIUSdgQIkgOLXF77rnncskllwS7HCGEEKLbxUeYmXN5NjMvymJbQS27Shv4prCWomo7TrcfjUYh3GJgUnY8o9OjGJUWSWqsFYCaXWfz5ptvMnv27CA/hTgVEjaECAJVVVmxYkWHJW6FEEKI/sqo1zIxO46J2Se+uMlPf/pT7r33Xq666ipiY2N7sDrRk2TOhhBB8Oqrr1JdXc2DDz4oS9QKIYQQRxAZGcnVV1/NSy+9FOxSxCmQsCFEL/vkk0/497//zbx58466xK0QQggh4Ec/+hG5ubns27cv2KWILpKwIUQv2rlzpyxxK4QQQpwgk8nEzTffzMqVK1FVNdjliC6QsCFELykrK+OJJ57goYcekiVuhRBCiBN08cUXY7fb2bp1a4U9lcYAACAASURBVLBLEV0gYUOIXnD4ErejR48OdjlCCCHEaUOj0TBr1ixWrVqFz+cLdjniJEnYEKKHHVridvLkybLErRBCCNEF48aNIyYmhvXr1we7FHGSJGwI0YMOX+L21ltvDXY5QgghxGlJURRmzZrF66+/jsPhCHY54iRI2BCiB8kSt0IIIUT3SE9PZ/z48axZsybYpYiTIGFDiGNwujw0NDtotDtwub0nda0scSuEEEJ0rxkzZvDhhx9SW1sb7FLECZIdxIU4TOXBJj7fto+v80vJLaigrrEFjaatRyIQUImJsDI8M5Ezhg9i8vhMYiOtR2zn0BK3jz/+uCxxK4QQQnST6OhorrjiCl555RUeeOCBYJcjToCEDTHgqarKN7tKee39rXz5bSEBwKjXYjYZiI+2tQ9/UlUVt8fH5m/28++te3j6pY+ZPC6D6VMnMHpocnt75eXlssStEEII0UNuuOEG7rrrLgoLC0lPTw92OeI4JGyIAa2h2cHTL33Mhi93o9NqiIkMRaM58uhCRVEwGfWYjHoA/IEAX3xbyGf/LeCyyTn84paLUFSvLHErhBBC9CCz2cz06dNZuXIlixcvljmRfZyEDTFgbdlxgPnPvUur00NspLV9uNSJ0mo0xESEEggEWP9FPl98u594TSkXTJokS9wKIYQQPejSSy/l3Xff5euvv2b8+PHBLkccg0wQFwPSJ1/uYu4TbwEQF3XyQeNwGo2G2EgbRUUlfLbPz+Dh53RXmUIIIYQ4Ap1Ox6xZs1i5ciV+vz/Y5YhjkLAhBpxNXxcw/7l3CbOGEGo2dkub5eXlKKqXzPRUHnnmHbbuLOqWdoUQQghxZBMmTMBms/HJJ58EuxRxDBI2xIBSebCJec+9iy00pH3uxak6eLCW2tpaMjMzsZhNWMwGfvvMWg7W27ulfSGEEEJ0pigKs2fP5tVXX8XlcgW7HHEUEjbEgKGqKo//9UO8Pj9mU/fse9Hc3ExpaSlDh2ah17eFF0uIEbfby/KV61FVtVvuI4QQQojOMjMzGTFiBGvXrg12KeIoJGyIAeNfX+ziv7nFxESEdkt7TqeLgoL9DBmSTkhISIfXoiOtbPq6gP/8d1+33EsIIYQQRzZz5kzee+896uvrg12KOAIJG2JAUFWVlf/YRPG2tezf/ukpt+f1+ti7dy8pKclH3LRPoyiYTQZW/mOT9G4IIYQQPSg2NpaLL76Y1157LdiliCOQsCEGhNx9FZRVNaDXnfo/+UAgwL59e4mMjCAmJuao59lCTewvOci+4ppTvqcQQgghju7GG2/kyy+/pKSkJNiliB+QsCEGhHc3bKdtz59T2/hHVaGw8AAGg4Hk5GPvDn5ok6H3/r3jlO4phBBCiGMLDQ1l2rRprFq1KtiliB+QTf3EgLAtvwSrxdThWGvTQYp3fYm9vgpVDWCxRZM89EwiYgfReLCU/M3vMfLc67FGxLdfU7B7B4XffMiZF96EokBzfSWlu7fS2lwLqkpYTAqDR0zGYLIAEGox8t/c4l59ViGEEGIgmjp1Ku+//z7bt29n9OjRwS5HfEd6NkS/1+JwU13b1GGpW4+rlbwv3kGj1TFi0nWMOm8aIdYIdm/9gNamg4RFJ6E3hlBfeaD9mtraWqqKdxEeEU1E3CAc9gbyN7+LTm9kxMTryD7rKtyOZvK/XIeqBgAIMRoorazH7fH2+nMLIYQQA4lOp2PmzJmsXLlS5kv2IRI2RL9XXFGHTqdtH9YEUFOym0DAT8aYi7CExWC2RjJk9AXojWaqivJQFA1RCenUVRUC0Nxsp6SkFKPiJCY5C0XRUHlgB1qdgcxxl2C2RWGNjCdjzIU4mutoqGkbM6rRKGg1GkoqZYUMIYQQoqdNnDgRg8HAp5+e+mIwontI2BD9XqvT0+lYS1MNZmskOv33+20oikJoWDStTbUARCVl4Gppoq6mgoKCAhJjw/C5HcQkZba10VCNNTIejVbb3obZFoXOYMTxXRsAikbB4ZKeDSGEEKKnHdro7+WXX8bj6fz+L3qfzNkQ/Z7fH+CHnal+nwetrvPGflqdAb+vEQBbZCKK1sC3Wz4lY9S5eOyVGM1WrJHx37XhpaG6mC0f/PUH9/PicTvaP1dR8fsD3ftQQgghhDii7OxssrKyeOedd5g2bVqwyxnwJGyIfs9o0HVag0qnM+JyNnc61+fzoP2ut6O+vh6PEoLfWU9MTDR7vvyc6O96NQC0ej3hoSmkjZjcqR3dYUFGAQx6badzhBBCCNEzbrvtNubOncull156xP2wRO+RYVSi34uPtuEPdOxZsITH4LQ34PO624+pgQCtjTWEhsVSXl5OaWkZmcMn4He34Gmpx9nS2D6ECiA0PA5XaxMms40QS1j7hxrwozO0rXylqio+f4D4aPlBJ4QQQvSWhIQELrjgAl5//fVglzLgSdgQ/V5CTBhGgw6vz99+LG5QDhqtjr3b/kVrcx2O5joKvt2A1+PGrbHR2NhETk4OBksEJrOV4l2bMNuiMNuivm938EjcTjuFOzbS2lyHs6WR4l2b2b7xTZwtDQB4vH6sZhNR4ZZef24hhBBiIPvJT37CZ599Rnl5ebBLGdAkbIh+T1EUhg2Op9X5fS+G3hjC8InXoaoBdn62hh2fvY2ztQlT3HD0plCys4dhMOix2+1EJgyhtamuQ68GgNkaSc7Z1+BsaWDnZ2+zfeMb2OuryDn7aszWSABanW6GZyZ2WAlLCCGEED3ParVyww038OKLLwa7lAFN5myIAeGKc0ewfXcZ4y++pf2YxRbF8HOuAcDpdLJ3715ioqJISkrmUDaw2+1kjJ6CxXLFEdu1RSUwYtKPjnpfr9fPpRNzuu9BhBBCCHHCrrrqKt5//31yc3MZMWJEsMsZkKRnQwwIF5w1FL1ei9fr7/RaU1MTu3btJjExieTk74OGx+PB6/VhNpu7dE+3x4fJpOe8MzKPf7IQQgghup3BYODWW2+Vjf6CSMKGGBAsIUauuWA0dU2tHY7X1NRQWFhIRkYGMTHRHV6z2+1YrVa6OgKqodnBDZeM67BzuRBCCCF613nnnQfAZ599FuRKBiYJG2LAmHndOVhCDDicHlRVpaSkhKqqKrKzs7HZrJ3Ot9vtRzx+IlocbmwWEz+dOuFUyxZCCCHEKTi00d9LL72E1yub7PY2CRtiwIgMs/CbOy+nodnB3r37aG1tJScnB5PJdMTzm5vbejZOViAQwN7i4tGfTSXMGnKqZQshhBDiFI0YMYLBgwezbt26YJcy4EjYEAPKyCHRKI5yXF6FrKyh6HRHXiPB6/Xi9XpPer6GqqpU19q5+sJRTBo7pDtKFkIIIUQ3uO2223j77bex2+3BLmVAkbAhBoz9+/fz0EMP8Yubz+XqS87iYL2dwFEmi7XN1wg9qSVrAwGVytomzj0jg4dmXdpdZQshhBCiGyQnJzN58mTeeOONYJcyoEjYEAPCli1bmD9/PnfccQc/uelGnph7PVPOzKLqYDMud+fxm83NzVitthNu3+nyUFXbzKUTh7Pk/uvQ6bTdWb4QQgghusH06dPZsGEDlZWVwS5lwJCwIfo1VVVZu3Ytf/rTn1i4cCGTJk0CwKDXsfSB6/jtnMtxuDzU1NsJBALt1x1aiep4/IEANfV2XB4f838+lYX3XIVeL0FDCCGE6IvCw8O57rrrWL16dbBLGTBkUz/Rb/l8Pv7yl7+we/dunnzySWJiYjq8rigKV18wmjNGpLHi5U/4/OsCVBUsJh1utweL5cjzNVRVxeX20tTiQqMoTDkzk/tvuYjYyK6tXCWEEEKI3nPttddy9913s3v3boYNGxbscvo9CRuiX2ptbWXZsmXodDqWL19OSMjRV4VKiAlj2S+vp6q2mQ827mTVmk/RGMzUNbbi9QVQ1QCooGgU9DotPn+A6IhQ5kybzBXnjZSQIYQQQpxGjEYjM2bMYOXKlTzxxBMnNT9TnDwJG6LfqaqqYtGiRYwdO5bbb78drfbEhjXFR9uYfcMkfHV5mMwZ5Iw9h9LKelxuL4pGwWTQMyghkiEpMbKkrRBCCHEau+CCC3jnnXfYvHkzEydODHY5/ZqEDdGv7Nq1i8cff5ybbrqJqVOndqmNnTt3cu+99zJ0aCpnDE/t5gqFEEIIEWwajYbZs2fzpz/9iQkTJhx1KXxx6mSCuOg3Nm7cyNKlS/nFL37R5aBht9uprq5myBDZI0MIIYToz8aMGUNiYiIffvhhsEvp1yRsiNOeqqq89tprrF69mqVLlzJ+/Pgut5Wbm0t2drb8hUMIIYQYAGbNmsUbb7xBa2trsEvptyRsiNOax+PhySefZNu2bTz55JOkpp7asKfc3FxGjBjRTdUJIYQQoi9LTU1lwoQJvPXWW8Eupd+SsCFOW01NTTz66KMEAgEef/xxIiIiTrnN3NxcRo4c2Q3VCSGEEOJ0MGPGDNavX09NTU2wS+mXJGyI01JpaSlz585l1KhR/PrXv8ZgMJxymy0tLVRUVJCRkdENFQohhBDidBAZGcnUqVN5+eWXg11KvyRhQ5x2vv32W37zm9/w05/+lBkzZnTb+th5eXkMGzZM5msIIYQQA8wNN9zAjh07KCgoCHYp/Y6EDXFa+eijj3jqqaf4n//5Hy688MJubVuGUAkhhBADk8lkYvr06axcuRJVVYNdTr8iYUOcFgKBAH/729/45z//yRNPPNEjk7h37twpYUMIIYQYoC655BIaGxv56quvgl1KvyJhQ/R5LpeL3/3udxQWFvL73/+exMTEbr9Ha2sr5eXlZGZmdnvbQgghhOj7tFots2fPZtWqVfj9/mCX029I2BB9Wm1tLQ8//DA2m41FixZhtVp75D75+flkZWXJfA0hhBBiABs/fjyRkZGsX78+2KX0GxI2RJ9VUFDAr371K84991zuu+++Hg0CMoRKCCGEEIqicPvtt/P666/jdDqDXU6/IGFD9ElffvklCxYsYM6cOfz4xz/uthWnjkY28xNCCCEEQHp6OmPGjGHNmjXBLqVfkLAh+hRVVVm7di1//vOfWbhwIRMnTuzxezocDkpLS8nKyurxewkhhBCi77vlllv44IMPqKurC3Yppz0JG6LP8Pl8PP/882zYsIEnn3yy1yZr79q1i8zMzG7ZGFAIIYQQp7+YmBguv/xyXnnllWCXctqT2bCiT2hpaWHZsmUYDAaWL19OSEhIr917586dMoRKCCGEEB3ccMMN3H333Rw4cIC0tDSqWzxUNbspb3bj8PhRFAgP0ZNoM5JkMxIWog92yX2ShA0RdJWVlTz22GOMHz+e2bNno9H0bodbbm4uM2fO7NV7CiGEEKJvs1gs3HTTT3hhzf+Red5VNDh9gIoGBe13v6qUNDjZXgGgMCjcxDlp4SSHmYJYdd8jYUMEVX5+Po8//jjTp0/nyiuv7PX7u1wuiouLGTp0aK/fWwghhBB9V6PTS3PCGFrrQ6muayIq3HrUBWtUVaW8ycXfv6liTJKV8wZHYNDJbAWQsCG6wOn1U1TnoLzRRXGDE7cvgE6jkBhmIiXCRGqEmXDz8bsSP/30U/72t7/x4IMPMn78+F6ovLP8/HwyMjJkvoYQQggh2lXb3by1vRqPP0BSdCQV5SVERRx9yLWiKFgMWgKqyrflzVQ1u/nxqDhMem0vVt03SdgQJ6y62c2/C2r5sqgRVVXxqyp6jQZFARXYWdGMVqOgqpCTEMqFWTFkxlg6taOqKq+99hobNmxg6dKlpKam9v7DfEeWvBVCCCHE4ZqcXt7aUU1ADWA1alGN4VRXV1J7sJaYmOhjXqtRFGxGLdUtHtbm1nDj6Hi0mp5dvr+vk7AhjsvnD/DJ3lo+zK9BBUKNOnRH+sYxtv0noKrsqmohr9LO+JRwfjwmAYux7Z+ax+NhxYoVVFdX89RTTxEeHt57D3IEO3fuZMaMGUGtQQghhBB9Q0BV+WhPLV5fgFBjW6+EAqSkDGJfwT4ioyLRHmduqaIoWA0ayptcbCttYu2fn0Cr1bJkyZJeeIK+R8KGOKZWt48/byqmqM6BzaRDpz3++EONohAWoiegqnxd2sTemhbuOW8wFtwsWbKEmJgYfve73wV96JLL5aKoqIhhw4YFtQ4hhBBC9A17alopbXRhM3Yc/hQaasFmtVJVVUVSYuJx2zk0rGpTcSNuXwCzduAOp5KwIY7K4fHz3H8OUNnkJsKsP+ldvDWKQrhZT4vLxxMf7aLx3y9xyaQzuPnmm3t8R/ATsXv3bgYPHozRaAx2KUIIIYQIMlVV2VLShFGrOeLvKcnJKeTl5REbE4Nef/y5qTqNQkCFmhYPacaBuyyuhA1xRKqq8vdt5VQ0uQgPOfmgcbiAu5X9JeUMnjiNG39yTp8IGtA2hGrkyJHBLkMIIYQQfcDuogre/t/nqCnchc/rwRoRxejzLmXkORcA8NdH7mL4lCv5cOeXHDywG7/PS9KQYVww7TbMoTYAaitK+PTtl6itKMViC2fcRVdTbXeTGmkO5qMFlazJJY5oZ0UzTz7yAHv+9fdTCgc1NTXsLywkKy0FJSSMD3fVdGOVpyY3N1fChhBCCCEA+P1TT9JUV811dz/Ezb/+HWPOu4yN/3iZ4t072s8pzduGy+Nh6u2/5LIZd1OyN4+v1r8DgN/nY93KZ1FVlRvu/S1X3nYvRXlfU19dgdsXCNZjBZ2EDdGJP6Dy5jeVXHLHw4y/bFrXGlFVSkpKqK6qIic7G6vVis2kY8OeWupbPd1bcBe43W4KCwtlvoYQQgghALj85jlcNvN+YpJSsUVGM+Kc87GGR1GyN6/9nLCIaM675ic0Oz2kDhtF0pChVJceAKB8/25aGus477qbiU1OIzpxEJdMvxOv24XDO3DDhgyjEp3sqWnB7vJ1eaWoQCDA/oIC/IEAOTk5aHVt/8y0GgUV2FzUwNThcd1Y8cnbs2cPaWlpmEyyy6cQQgghoLnVzX8/WkNtSQEuRwuqquLzenA7WtvPiU1JIzY2loM1B2m22wmx2GiqrQagvroCgOjElPbzjSFmwmMT8AfU3n2YPkTCRj+3fft2XnnlFYqLiwFIT09n5syZZGdn4/F4WL16NRs3bsTlcpGRkcGsWbPYVGtEo4F3n3mEuPShnHXNrQA0Hazk23/9g/ryInxeD9EpQxh/xY3YouMBKPx2M5vXrmLoZTMo+e8G/C0N7AkxkzXhArInXQqAxaDlHxu+ZMPK/1BUVER4eDjnn38+06dPR/ddKNm1axevvPIKhYWFqKrK2LFjufPOO4mMjOy2r8vOnTtlfw0hhBBCAOB0Onn12aV4NSam/GgGYdGxKBoN7/71qQ7n6QwGNIpCQmICZWVlbevifsfjdoGioNN3XG1TazB2OG+gkWFU/VhLSwtLlixh6NChrFixgqeffprk5GQWLVqEy+Xi+eefZ/PmzTz00EOsWLGC+Ph45s+fT+6BCkJ+sOOl29HChhefxudxcd5P7+HiWb9CUWDD6j/gcTnaznG5aLG3UPHNvznr8hu4/O5HSMkey7cf/4O68iIAnA3VbHz1j6Rn5fDss8/y85//nA8//JDVq1cDUFZWxqOPPkpoaCjLli1j4cKFVFVVsWDBAgKBrnVBqqpKs8tHXauHBocXnz8g8zWEEEII0W7nzp14Wu1MvH4maTmjiYhNIDw6DtdhvRqHi4qKwufz4Xa524/pDUb4rjfkcF6XA4N24KYN6dnoxyoqKnC5XEyZMoWEhAQA7rrrLi666CJcLheffvopDz74IKNGjQLg7rvvprnVyZ6DBwkLj+jQ1v6vP8fjdjJp2hxMFisA51w/m3f+8BuKdmwhJnMMpWVlhJhDGHXuZSRltf0in3PuFezZsoH6imKiktLYt/XfmELDOP+aG0lKsJKUlMTtt9/e3vPy7rvvEhISwq9+9av2ZeUeeOAB7r33XrZt28aZZ555Qs/u9QfYXd3C1+V2KppceAMqigKobXNSSiNHU2NMoMHhJcI8cJejE0IIIQT4fD6MOg0hltD2Y0X52/E4HahHGAGlAElJSezY0MihlyNi2kZ61JQeIDF9KAD2xnoaayoxD03u4SfouyRs9GODBg0iNjaWZcuWceWVVzJ27FgGDx5MdnY227ZtQ1VVhgwZ0n6+0Wjk9nse4Pef7O+0AlVdeRFhMQntQQPAaA4lLCaBA7t20qyxkpyURF2ensjEtA7nAO29H/WVxYTFJdPq8bWfc9FFF7X//549e8jJyemwfnVqaipWq5XCwsLjhg1VVdlW1sy/9tbi8avoNAomnYaQw3Y8b26yExIWyZbyFraUtZATF8oV2TGEGuXbQQghhBiIMjIyMBt05H7+L0IvvpKDZUV8u3E9CYMzqa8ux95Y3+mayMhIVFXF42nryUjOzCbEamPTurc4/4ZbAPjPe28RFhaO/gQ2Re6v5LerfsxkMrF8+XLWrFnDunXrePHFF4mNjWXWrFn4/f72cw53pPQO4HW7aKwq463f/aL9mN/vx97cRHjiYOL1ekoLS2lpaeFgbR3oTVhCQ9Ee2jHzu4Y9TgeWsFiONk/K6XSydetWpk3ruAqW2+2moaHhmM/b4vaxZkc1B+odWAzaTkPBDrG3NGOzhBBm0qOqKrtqWtlf5+SGUXFkxliOeQ8hhBBC9D+xsbHcf9+9LP9/q3jl91+QMjiLy2bcRXXpAT55YyUfvvTHTtcoQJgtjKLKUlRApzcw9bb72fiPl3nr2SVYbOEMP/9KjDU2QCaIi34qKiqKOXPmMGfOHA4cOMCbb77J8uXLueOOOwBwOBwdzg/RawgcIXEYTCGExyczadqdBAIq1VWV1NXXk5CQQGxcPGZbBBafnZod/0FFpaKyktbWVkwmE06Hkxa7HY/Hg9Fixed2EaI/csI3m82MGzeOO++884ivHU2L28eqreU0OL2EmXTH3BvEbreTEN/W1akoCjaTDrcvwGvfVDJtVBw58dajXiuEEEKI/unSSy9l9DlTePXrSsx6DVqNgi0yhszRE456zdWz7yMvN5emxibCw8OITx3CTQ8uBMDp9WPUaZk9YcaA7tkYuE8+AFRWVvLVV1+1fz548GDuueceVFXFZrOh0+nIz89vf93n8/Hk0oXU7P220xJtkYmptDbW4fFDUXkVuhArZ55zLpEREZgsbbtmarRadHo9iQmJDBs2jHHjxpGWmopGq8He0kpeXh4On0JFQT75//2CAwcOEAgE+Pjjj3nssccAyMrKoqKigvj4eBISEto/fD4fNtv/Z+/O42ys+z+Ov87sZsUMZhgzDGYsQwYjJncqSysVFRGKLBnLje6KFjeluyyFQVRIRGVPWSoq1Z2yZh/LWGbGMoOM2WfOOdfvD/ecn2PJKGcO5v18PDwec671c50657re5/u9vpf/ZY/TYjWYv/U4Z3ML8b9K0DCsVrKzs/H1sw8Unm4ulHF3YdH2k6Rm5F3bGy0iIiK3hEp+ntweFkBWgQXjSt09LlB070Zqaopd24XFalBggQfqVCjVQQMUNm5px48fZ8yYMXz55ZecOHGC48ePs3jxYjw8PIiOjqZly5bMnz+f7du3c/z4cWbMmMHBgweJrlub3EKL3baqRjclKzubdZ9MpayXKxXK+XFg4/eseu91Th5OvOz+TSYTPr6+eHp6EhISTExMDLff/ziGuYDF82YxcuRI7r//foYOHUpqairbt2+nTZs2pKWlMXXqVA4fPkxqaipz5sxh0KBBJCcnX3Y/G46c5VhGHpu/mMNn44b/6XuSlZ1NGS+v/+/edQEP1/O/YizZfoJCS+l9+I6IiEhpdnt4WcLLlSEzv3iBo2y5chjA2bNngfNBI6vAQovqZalaVs/zUjeqW1ijRo2Ij49n+fLlzJ49G3d3d6pVq8arr75KUFAQ/fr1Y9asWYwdO5b8/HyqV6/O6NGjyfCsyLxNqbbtpKelkZKayu2P9eH49p/5bfEHWK0WylasTFzHXoTUqFvsmrwCK9N32AjSNq7i6NGjBAUF0bRpU6pWrcrcuXM5dOgQfn5+fPXVVyxatAg/Pz/q1avH6NGjCQsLu2R7WflmvjtwGl/PP2/RKJKZmYnf/1pIVs16lxq3NSWy8R22+T4erpzJMbM55RzNwv/aQw1FRETk5uXmYuLh6Iqs2J3OodM5eLu7/GnrhK11IyUVTx8/Ci0GLaqX4/awgJIr+gamsHGLa9OmDW3atLnsPC8vL/r370///v3tpuebrXy29Rh3936ZlCOHOXXqFLWjoijj7U3tBo2vuK+Ihs2JaNj8kulPjpwOnB8pygC6P3AnoV3vvew2CgoK2L9/P3v27GH37t3s2bOHM2fO8O2333Ls2DHq1q1LaGioLVj8fuwcFuv5UaeKI/PcOSoFB2MYBunJh6hxmX6YXu4u/HzoD5pWDcClmNsVERGRW4eHqwuPRldkx/FMvjvwB7mFFrzcTbi7mC75cdMwDDx9/DB5epObdY6n4iIJDVCLRhGFDbmEyWrG/8w+Np52JbRCEJUqVbwu283INRMd4keVP2lS9PDwoF69etSrVw84/wFOTk5m9+7d7Nq1i0WLFpGdnU1oaChJSUnsPn4WLx9/GrRobbedM8dT+G3NYk4c2odhtRIQVImG9zxEVoGJmn5+fDj8/A3yPyycxQ8LZ9H7rZlYzGY2rVnCwe2/kXnuHL+GV6LN3XfSo0cPPDw8LqlVREREbl0uJhO3VfanZpAPu05ksSU1g8wCKy78/9hSJhNYrQYVfT2oXt2Prz+fSZX7Jjqz7BuOwobY2bp1K9OmTaNGrVo0i36IU7nX596FvEILHm4udGpUuVjdnYqYTCbCwsIICwvjvvvuA+DMmTPEx8dz/GQaddo+jWEuYP+ubfyReogy3r4UFhayZs5kylYI5uH+I3Bz92Df5v/yzbxp3PZgN1xdXek4eBSLJ42kebvORDQ437qxdd0K9m5czz1d+uHqX4H6vgWs5x9W1AAAIABJREFU/mQ6Hh4e9OjR47q8DyIiInJz8fFwpWlYALFV/ckusHAqu5B8sxWT6fy8IB8PPN1cMIzKrF/mzs8//0yLFi2cXfYNQ2FDgPM3NX344Yfs2bOH/v3707hxY9Kz8pmwNonMPDN+Xn/9f5V8s5XcQit97wgjoMzff1p3bm4uWVlZDHrxVfZ7VsfbzYVzsc1YNGEEuXm5bP/9dyJaPEjZ8kFYXDwp4+1LzD0PsWHVInLPnADAy/f8aFQeXt54+53vU1kvrhW1Gt9BQGBFsvLNeFbwITY2li1btihsiIiIlHImkwlfT7crPgTYZDLRpUsXPvzwQ+Li4nBx0ThMoLBR6hmGwddff83cuXNp3bo1U6dOtT3or4KvJ4Puqk7CD4c4W4znV1xOZp4Zq2HQq1lV6oVcfujaa1U0KlVwaDj70sDF1YWyZcsSHlmXMydSady4MUcP7GXLtys4mZxEbvY5MMBiLvzT/+Fd3dxJ/OkbjuzaSua5s3i6QBU/NwIDA69L3SIiInJri4mJwcfHh59++ok777zT2eXcEBQ2SrHk5GSmTJmCxWLh9ddfp3r16pcsUznAixdb12TBllR2H8/Ey92VMu4uVw0d+WYr2flmKvl70r1pVcLKlbludefm5gLg6eEBJrNturvH+ZCUefY0a+dOJjAkjIeeGYRP2fKYzWaWTPo33j5XfjDgd59+wPGkvTRv9yR+IeFULudD4c517N2797rVLiIiIrcuk8lE165dmT59Oi1atFDrBgobpVJBQQGff/45q1atomvXrtx3331/+mEo6+1OvzvC2ZaSwcrd6ZzMzMcwDDzcXPB0c8HFZMJqGBRaDPLNFkyY8PF05eEGwbSsGXjdH2bj6ekJgCtmu+n5ueefhn5k9zbMBQW06vocPv7nh6/Nz8nGxJXHys7PzSE5cTuN2zxCVOw/yMwzU72yHzs251/X2kVEROTWdtttt1G2bFl++OEH7r77bmeX43QKG6XM77//ztSpU4mIiCAhIYHy5csXaz2TyURM1bI0DA3gyJlcEtOyOJCezbGMfPLNVlxdTAT7e1Krgg81gnyoXckXVwcNGxsaGgrA2WNHsFrDMQwDi7mQk0cO4Ontg9Vy/oGEXt6+tnUObNvwv7/sA0fRw3oMw4phGHj5nL+Xw4pBOZd8tm3bdsUnl4uIiIhcrOjejSlTpnDnnXde9kHCpYnCRimRkZHBzJkz2bVrF/369SM2NvYvbcdkMlEt0Jtqgd7cW+c6F1lMYWFhVKtWjYWff0bluztxzHBn389rcPvf8LQVwyIA+P2HVdRq1JyUfbtITtyBf/kKnD52lNzMc3h4lcFkMnE8KZGgKuEEBFXCP7Ai+zb/RHC1WpzOOMf8L1bRvHlzfv75Z44cOUJoaGip/8IQERGRq2vQoAFBQUF8//33tGrVytnlOJU6kt3iDMPgm2++IT4+nrJlyzJ16tS/HDRuJC+99BKBgYGs/3gi38yeSNkKIVSPPv/AweBqtWjc5hF2/7KOxRNHkrp/F3d1epa6ze8h9cAefv7iE9zcPaj/j3s5tGMTKz8YT152Fnd3ehZzQQGLJ49m15pP6ffsM3Tu3JmAgABefPFFMjIynHzUIiIicrPo0qULn376KWaz+eoL38JMRlE/koukpKTQqlUr1q5da+u2IjeXlJQUpk6dSn5+PgMGDCAiIsLZJV13hRYrE9cfxmKAl9vfz86GYZCRZ6ZTwxDqVPK9+goiDqbv4ivTeyMiN7pXXnmFli1b0qZNG2eX4jBX+y5Wy8YtqKCggPnz5/PCCy8QFxfH+PHjb8mgAeDu6sLD9SqRV2jBevncfE2y8i3UquBD7Yo+16E6ERERKc26du1a6ls3FDZuMdu3b2fQoEEcPnyYyZMn065du1t+2LVaFbyJqeLPuTwzV2ioK5bsAgte7q60q1vxmp8nIiIiInKxOnXqEBoayrfffuvsUpxGN4jfIs6dO8esWbP4/fff6devH7fffruzSyoxJpOJh+pWJN9sZfeJLPy83K5pJCzDMMjMt+Dl5kKPJpXx/xtPSxcRERG5UJcuXXjrrbdo1aoV7u7uzi6nxN3aP3mXAoZhsHbtWvr374+Pjw/Tpk0rVUGjiKuLiY4Ngrm7ViDZBRay8ovXypFvtpKRZyY0wIvezapS0c+zBKoVERGR0iIqKopq1arxzTffOLsUp9BPuDex1NRUpk2bRnZ2NiNHjqRWrVrOLsmpXF1MtKxRnqgKPny97xSHzuRiGAburi54uJpwMZ1/rF+hxUqB2YrJZMLHw5WH6lakUag/Luo6JSIiIg7QpUsX3nzzTVq3bo3H/4bqLy0UNm5ChYWFLF68mC+++IJOnTrx0EMP6fkPFwj296R7kyqczi5gX3o2h87kcvxcPgUWKy4mE0E+HoSX86JGoA/Vy5fBxUEPHxQREREBqFWrFhEREaxZs4Z27do5u5wSpbBxk9m5cydTp06lcuXKTJo0iQoVKji7pBtWoI8HzX08aF6tnLNLERERkVKua9eujBo1invvvbdUtW4obNwkMjMzmT17Nlu2bKFPnz40b95cIyaJiIiI3CQiIiKIiopi1apVPPzww84up8ToBvEbnGEYfP/998THx+Pl5cW0adOIi4tT0BARERG5yXTp0oXFixeTn5/v7FJKjFo2bmDHjx9n2rRpZGRk8MorrxAZGenskkRERETkL6pWrRp169Zl5cqVPProo84up0SoZeMGZDab+fzzzxk2bBiNGjXi3XffVdAQERERuQU8+eSTLFmyhLy8PGeXUiIUNm4wu3fvZtCgQezZs4eJEyfy6KOPaqQpERERkVtEeHg49evX58svv3R2KSVC3ahuEFlZWcyZM4fffvuN3r17c8cdd+i+DBEREZFb0JNPPsnw4cN58MEHKVOmjLPLcSi1bDiAYRhYrUaxnmBtGAbr168nPj4eFxcXpk2bRosWLRQ0RERERG5RVatWpWHDhqxYscLZpTicwsZ1YjUMsvLMJJ/J5WB6LkmncklKz+X42XxyCyyXDR4nTpzg3//+N0OGDMHb25vnnnsOHx8fJ1QvIiIiIiXpySefZPny5WRnZzu7FIdSN6rrIN9s5fjZfCxWA5MJ3FzAZDJhGAY5BRayCyx4ubkQXNYTNxcTZrOZZcuWsWTJEjp27EheXh7u7u7OPgwRERERKSFVqlShSZMmrFixgs6dOzu7HIdRy8bfVGC2kvpHHlbDwM3VhKuLydYFymQy4eZqws0F8s0Wjv2Rx569ifzzn/9kx44dvPPOO3Ts2BEXF/1nEBERESltOnfuzBdffHFLt26oZeMapKenM2vWLLZt20Z+fj4VKlQg7p77aXFPW9xcTPTq0pFuvfqSnnaSn3/4jsLCQmrXrUeP3s/h7e1L6vGTfLtyNenp6Rw7doxXXnnllk6yIiIiInJlISEh3H777SxbtoyuXbs6uxyH0E/q12D8+PEcO3aMMWPGMH36dB54qD0fz/qA3du32pb5euUKPD29GD7yDfoNHMKu7b/z6dyP2LFjBzk5WWzbuomQypUZN24cL7/8Mr/88gvJyclOPCoRERERcZZOnTrx1VdfkZmZ6exSHEJh4xoMGzaMkSNHEhERQcWKFbn9ztaUDwxi947fbcsEBgXRvsPjVAqpTGSdaIIqBbNrx3Zq1qxJXnYmf5w+zVM9elGjRg2qV6/O0KFDycnJceJRiYiIiIizBAcH07x5c5YtW+bsUhxC3aiuQWFhIfPmzWPXrl1kZmaSnW8mPz/frp9dtYiaGIbByZMnOXbsGOUDAzEXFuDn58uxlPMtGMGh1WzL+/j4ULVq1ZI+FBERERG5QXTq1Il//vOfPPzww/j7+zu7nOtKLRvFlJuby/Dhwzlw4AD9+vXjnXfeYeSY8QRVqGi3nGHArl27yc7Opm7degQElKXoiRl5eXmYTCbcPexHnvLy8iqhoxARERGRG03FihVp0aIFS5cudXYp153CRjHt2LGDP/74g4EDBxIbG0toaCiVq1QmKysLAKvVSm5eHsePHSM4uBIRETXw8vK024anl+f5B/6ZC+2m38ojEIiIiIjI1T3xxBOsWbOGjIwMZ5dyXSlsFJPZbAawa9rav3MrOdnZ5OXmsnPHTqwWC1XDqhIUFMTlHgBeKbgyACeOHrJNO336tG4QFxERESnlgoKCuPPOO1m8eLGzS7muFDaKqWbNmri4uLB8+XJOnjzJTz/9xNKFCwipUpXEvXvw9fXBx8cHV9cr3wYTVbc+ZcuWZd7cj0hKSiIpKYlJkyZRtmzZEjwSEREREbkRPf7443z77becPXvW2aVcNwobxVSxYkXi4+PZuHEj8fHxzJw5k5MnT1I7sib5+Xl8MnvGn65vNQzc3T0Y+eorWCwWhg0bxpgxY/jHP/5BrVq1SugoRERERORGFRgYyF133cWiRYucXcp1o9GorkHbtm2JjY1lxowZHD58mGHDhlGvXj3OZBfyR7YZFxdwuaj7VM++8VisYLVCRX8PalSsy8SJE+2WadOmTQkehYiIiIjcqB577DEGDBhAhw4dKF++vLPL+dvUslFMhmHwzTffMHDgQKpUqcLkyZOJjo7GZDJR3sedkLKeeLi6YLZCocWg0Gyl0GJgsYK3hytVynnh56VsJyIiIiJXVr58eVq1anXLtG7o6rcYjh8/zpQpU8jJyeH111+nevXqdvNNJhM+nq74eLqSb7aSX2jF4HwrRxl3F9xclelEREREpHg6duxI//796dixI4GBgc4u52/RVfCfsFgsLF26lGHDhtGkSRPGjx9/SdC4mKebC/5l3Ago44afl5uChoiIiIhck7Jly9KmTRsWLlzo7FL+Nl0JX0FSUhLPP/88mzZtYsKECTz66KO4uro6uywRERERKQU6dOjA+vXrSU9Pd3Ypf4u6UV2koKCATz/9lK+//poePXrQunVrTJd7aIaIiIiIiIMEBARw77338vnnnxMfH+/scv4ytWxcYOfOnQwaNIhjx46RkJBAmzZtFDRERERExCk6dOjAzz//TFpamrNL+cvUsgFkZ2fz0UcfsXHjRvr160ezZs2cXZKIiIiIlHJ+fn7cf//9fPbZZwwcONDZ5fwlpb5l49dff2XAgAEATJ06VUFDRERERG4YjzzyCL/88gsnTpxwdil/Salt2Th79iwzZswgKSmJYcOGER0d7eySRERERETs+Pn58dBDD/HZZ58xePBgZ5dzzUpdy4ZhGKxdu5YBAwYQHBxMQkKCgoaIiIiI3LAefvhhfvvtN44dO+bsUq5ZqWrZOHHiBFOnTiUzM5PRo0cTERHh7JJERERERP6Uj48P7dq149NPP2Xo0KHOLuealIqWDavVyrJlyxg6dCgNGzZkwoQJChoiIiIictNo3749W7ZsITU11dmlXJNbPmwcPnyY559/no0bNzJhwgQ6duyoh/OJiIiIyE3F29ub9u3bs2DBAmeXck1u2W5UBQUFfPbZZ6xZs4bu3bvrmRkiIiIiclNr164dvXv3Jjk5mapVqzq7nGK5JVs2du3axaBBg0hJSWHy5Mm0bdtWQUNEREREbmplypTh0UcfvalaN26plo2cnBzmzJnDhg0b6Nu3L3Fxcc4uSURERETkunnwwQfp3bs3R44cITw83NnlXNUt07Lx22+/ER8fj9lsZtq0aQoaIiIiInLL8fLyokOHDjdN68ZN37KRkZHBjBkzOHDgAEOGDKFBgwbOLklERERExGEeeOABli1bxqFDh6hevbqzy/lTJdqyMXHiRPr06XNdtmUYBuvWrSM+Pp6KFSsyZcoUBQ0RERERuaVc7vrZ09OTDh06MH/+fCdVVXw3ZctGWloaU6ZMISMjg1GjRlGjRg1nlyQiIiIiUmLuv/9+li9fzsHDyQQEVcJqgAnw9nChjIcrLjfI4Eg3VdiwWq2sWLGCzz77jA4dOvDII4/g5nZTHYKIiIiIyN/n4saQEa9zJrsArwADkwkw4KzZQkauhbJl3PD2dP6z5Rx2pZ6WlkZCQgK7d+/G19eXdu3a2c3Pzs5m9uzZbN26lbNnzxIaGkrXrl1p2rSpbZnTp08zc+ZMdu/ezcmTJzl16hQxMTGMHz+eypUrs3btWiZOnMg777zDe++9x+HDhwkICKBTp07cd999jjo0EREREZHrrrjXz5s3byHt9B8Eh1TmtkZNeLDdI/j4+IAJzpw5zfyPZ7MvcQ8FudlE1qpJz549qV27NkCJXz87LGyMHTuWs2fPMnr0aPz9/Vm6dCmbN2+mTJkyALz55pscO3aM/v37U7lyZb755hvGjBnDW2+9RZ06dTCbzbz88su4uLhQu3Ztzp49S6NGjThz5gwuLva3mkyfPp3u3bsTFBTE8uXLmTZtGjVq1KBWrVqOOjwRERERkeuquNfPnbv3JrBiMD//sI6lCxdQtlwgbe+9D7PZzFuvv4abmxv9BgzBz8+PH79ZwauvvkpCQgLBwcG2fZXU9bNDbhBPTU0lMTGR7t27U69ePapWrcqAAQNwdT3flJOYmMj27dvp27cvsbGxVKlShaeffpqIiAiWLVsGwC+//EJiYiIZGRlYLBZmzZrF1KlT8fb2ZuXKlXb7a9u2LQ0bNiQ0NJQ+ffrg6enJjz/+6IhDExERERG57op7/dyzV2+iGzamSpUqdOranVqRUXz37Rqys7PY9NsGThw7Rt/4wdStF03lqmH07hfv1Otnh4SN5ORkACIiIv5/Ry4utqS0b98+gEtGj6pfvz6HDh0iLy+PGTNmcPjwYeLj4xkxYgTly5fHzc2N2rVrk5SUZLdeVFSU7W93d3fCw8NJT093xKGJiIiIiFx3xb1+jqwbDYDpfzeA16lbn8xzZ0lJTeXggX34+PoSXu1/2zCg0HBx6vWzQ7pR5ebmAueH5bpQURNQTk4OAD169LCbbzabcXNzs3WTqlOnDu+++y7vvvuubZnCwkKqVKlit56Pj4/day8vL7Kysq7DkYiIiIiIOF5xr5/7PtsTs+V/N4Tz/9fPQYFB5ObkkJOdTe8eTwJgGODqAibD4rTrZ4eEjaI3KT8/32560QF4e3sDMGHCBNzd3S9Z38PDg7vvvpt169Yxfvz4S+YXNScVycvLs3udm5tLxYoV//oBiIiIiIiUoOJeP7/19jhyzCZcXeyHtg0MDMTb2wcfPz9Gvv4WABbDwNvdhQBvd6ddPzukG1VoaCgA+/fvt00rKChgz549AERGRgLn76gPCQmx/XN1daVcuXK2ZTIzM3Fzc7NbBrAtU2TXrl22vwsLCzl69KitBhERERGRG11xr5/NBblUCgm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nyM3NvaS+ixXVOGTIEFxdXW3Ti8JKenq67QRS1B3uwmO98L24kgvv2UlNTaVbt27UqVOHN998k5CQEFxcXHjwwQevup0rCQ0NJS4ujuXLl9OyZUtWr15NkyZNCAsL+8vbFBG5kTVo0IC3337b9trb29vuPLp69WqGDBnCY489xgsvvGD7we3C+x3Pnj1LjRo17LYbEBBg97q458sLv+eLu/8iF56nLneeBXjxxRfJz8+326eIoyhs3EQ8PT2pXr26rVXCz8+PqKgoJk2adMmyF1/IXqjovo3y5csTGRmJn58fjRs35vXXX+f48eOkpqbafunw8/OjRYsWjBgx4pLtFLUE+Pn5ce+999KrV69Llrn4i/bvKNpfv379eOihhy6ZX9TCExAQwJAhQxgyZAiHDx9mzpw5vP7664SFhXHnnXdedf7FmjRpgsVi4fvvv+f++++/ZL7VamXBggV06NABPz8/4Hyf2SZNmlyybKVKlf7We3CxdevWkZuby8SJE23bzsjIoLCw8G9t97HHHmPEiBHk5uayZs0ann322etRrojIDeniH/gu9tVXX1GtWjXeeOMN2wX8xffFeXp62t2DCOcDyIX+6vmyOPu/Fn379sXDw4Px48dzxx132LWYi1xv6kZ1EyksLOTIkSO2i8r69euTkpJChQoVCA8Pt/0zm82XDI174a8acXFxbNmyhY0bN9ouiBs2bEhycjIrV64kIiLC9ut7/fr1OXz4MGFhYXb7KCwstDXP1q9fn+TkZLv5oaGhmM1mypYte92O39fXl4iICI4fP263rwoVKuDq6oqvry8nT55k5cqVtnWqVavGyJEj8fX15cCBA1edfzlNmjQhOjqaiRMn2o0YUuTDDz9kzJgxJCUlERERga+vL2lpaXY1+vv74+3t/ach8HKu1tJRFCrKlStnm7ZixYpirftn+2ndujVeXl5Mnz6dEydOcN999xV7WyIit5rCwkLKlStnu9CHS79rw8PDLxnJ7+KHvv7V82Vx9n8t2rdvT48ePWjSpAnPP/88eXl517wNkeJS2LhBFRYWkp6eTnp6Omlpaezatcv2hdCzZ0/gfN96V1dXhg0bxs6dOzl69CizZs2iffv2bNiwAcD2/IQffviBxMREAG6//XZOnjzJunXrbGHD19eXqKgoPvnkE7v+m926dePYsWO89tprJCYmkpSUxPjx43nkkUdsF+c9e/Zkw4YNTJo0iYMHD5KYmMgrr7xC586dOXPmzHV9X3r16sWyZcuYM2cOR44cYceOHQwZMoQePXpQUFBAVlYWw4YNIyEhgUOHDpGSksKcOXPIycmhcePGV51/JePHjyc7O5tOnTqxZs0aUlJS2LlzJ6NHj+bdd9/l5Zdfpl69eri7u9O9e3c++OADli1bRnJyMps3b6Zv374MGjTomo41ICCA3bt3s2fPnis2dTdo0AA4P6JISkoKn376KT/88ANVq1Zl9+7dxWoiv9x+PDw8ePjhh/nwww+59957L2nSFxEpTRo0aMDOnTv5/vvvOXz4MG+88YatJXvbtm1kZWVx3333cfjwYaZMmcLhw4dZuHDhJcOF/9XzZXH2f61MJhNvvfUWp06dsutCJnK9qRvVDWrTpk20aNECOP+FEBgYSExMDHPnzrX1CQ0MDGTevHmMHTuWbt26UVhYSGRkJO+8845t3dtvv51mzZrx1ltvERkZyZIlS/D396du3brs2LHDrqtP48aNmTt3Ls2bN7dNq1mzJrNnz+bdd9/liSeewDAM6tevz8yZM203wsXFxTFlyhSmTp3KBx98gLu7O02aNGHu3Lm21o/r5bHHHsMwDGbPns24cePw8vLijjvu4KOPPsLDw4MaNWowZcoU3nvvPWbNmgVA9erVmTBhArfddhvAVedfTvXq1Vm+fDkzZsxg3LhxnDx5koCAAKKjo5k7d67d+zho0CDKlClDQkICJ06cwM/Pj9atWzNs2LBrOtaePXvy2muv8eSTT/Kf//znsss0adKEQYMGMX/+fGbOnMkdd9zB2LFjWbZsGRMnTmT06NGXDL14tf0UdRW79957+eijj+jYseM11S0icqvp0aMHBw4cYNiwYXh6etKxY0dGjBjBuXPnmDJlCt7e3nTv3p39+/czb948Zs2axR133MHIkSN54oknbM9o+qvny+Ls/0qDnPyZ4OBgRo4cybBhw7jrrrto2bLlX36PRK7EZPyV9jcRueWNHTuWn3/++ZJnboiIyKWsViunT5+2u7F8/fr19O7dm8WLFxMdHe3E6kScR92oRMTOiRMnWLhwIXPmzOH55593djkiIjeFH3/8kRYtWtgefrtlyxYmTJhA3bp1qVu3rrPLE3EatWyIiJ169eoRFBRE//796dSpk7PLERG5aRT9UJOcnIyfnx+xsbG88MILds+PEiltFDZERERERMQhrniDeF5eHjt37rQNKyoiIiXPYrGQnp5OdHT0NQ+dfKvTeUpExPmudp66YtjYuXMnXbt2dWhxIiJSPJ988sllHxRZmuk8JSJy47jSeeqKYaNoNIVPPvnE9oA3EREpWSdOnKBr1652I9zIeTpPiYg439XOU1cMG0VN0sHBwYSGhjqmOhERKRZ1E7qUzlMiIjeOK52nNPStiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGiIiIiIg4hMKGyF80ceJE+vTp4+wyROQ60udaROT6UtgQKSEjR45k7dq1zi5DREREpMQobIiUAMMw2Ldvn7PLEBERESlRbs4uQORmkJaWRkJCArt378bX15d27drZzT98+DBz5sxh165dWCwWqlSpQufOnYmLiwOgffv2wPkuGhMnTmTFihWYzWY+/vhj1q9fT0ZGBmXLliUuLo4ePXrg4eFR4scoUtpc7XOdnZ3N7Nmz2bp1K2fPniU0NJSuXbvStGlT2zKnT59m5syZ7N69m8zMTGrUqEHPnj2pXbs2AGvXrmXixIm88847vPfeexw+fJiAgAA6derEfffdV6LHKyLiDAobIsUwduxYzp49y+jRo/H392fp0qVs3ryZMmXKYBgGo0ePJjQ0lPHjx+Pp6cnatWsZO3YskyZNIjw8nISEBAYOHEjv3r35xz/+AcCnn37KmjVrePHFFwkLCyMlJYVx48bh4eFBjx49nHzEIre+P/tcA7z55pscO3aM/v37U7lyZb755hvGjBnDW2+9RZ06dTCbzbz88su4ubnx/PPP4+/vz+LFi3n11VdJSEggODjYtq/p06fTvXt3goKCWL58OdOmTaNGjRrUqlXLWYcvIlIinNaNau3atbRr145z585dcZn58+fz8MMPl2BVIpdKTU0lMTGR7t27U69ePapWrcqAAQNwdXW1LTNmzBj+9a9/ERYWRqVKlejUqROGYbB9+3YAAgICAPDx8aFcuXIAtGvXjokTJ9KoUSOCgoJo2LAhsbGxbNmypeQPUqSUudrnOjExke3bt9O3b19iY2OpUqUKTz/9NBERESxduowCM/zw0y+kpKYydOhQoqOjCQsLY+DAgXh7e7Ny5Uq7/bVt25aGDRsSGhpKnz598PT05Mcff3TGoYuIlKgSbdlYtGgRKSkp/POf/yzW8h06dOCBBx5wcFUify45ORmAiIgI2zQXFxdq1arFkSNHMJlMZGVlMXv2bPbv309WVhYAZ8+eJTEx8ZKuGUXc3d35+uuv2bBhA3/88QcWi4XCwkICAwMdf1AipdzVPtdF91g1aNDAbr369evz3182YDGs7NyxAx8fX7ttuLm5Ubt2bZKSkuzWi4qKsv3t7u5OeHg46enp1/24RERuNCUaNvbu3Yuvr2+xl/fy8sLLy8uBFYlcXW5uLgCenp5204u6WqSlpTF8+HAiIiIYPHgwFSpUACA2NpZVq1bx/PPPX3a748ePZ8eOHfTp04fIyEg8PDyYN28ee/fudeDRiAhc/XOdk5MDcEmXRrPZjKurG1aLlbS0k2RknOXxxx+3W6awsJAqVarYTfPx8bF77eXlZfthQkTkVlZiYWP48OHs3LkTON+Fqqh1Iz09nbfffpu9e/fi7e1N165dbTfNzZ8/n88++4zly5cD8PvvvzNv3jyOHDkCnP9FqkePHtSpU6ekDkNKoaKLkfz8fLvpRRcKv/76K/n5+bz00kuUL18egJUrV+Lh4YHZbL7sNrOzs9m0aRNPPfUUbdq0sU2/eB8i4hhX+1x7e3sDMGHCBNzd3e2WMQzw8nDDsFhITUlhzZo1mEwmu2Uu7GYJkJeXZ/c6NzeXihUr/v0DERG5wZXYPRsjRowgJCSEFi1a8PHHH1NYWAjARx99RIcOHZg8eTINGzZk2rRppKWlXbJ+VlYWb7zxBlFRUUyaNIl33nmH0NBQRo0adcmXuMj1FBoaCsD+/ftt0woKCtizZw+ALVD4+/sDYLFYbDeG5+Tk2H5BhfND4AJYrVYMw7CtA+e7XW3bts22jIg4ztU+15GRkcD5HwZCQkJs/1xdXSlfvhyuLtC2bWuysrLYvHmz3TKA7d6sIrt27bL9XVhYyNGjR201iIjcykosbPj5+eHi4oKnpyflypWz/VLUpk0bGjduTJUqVejYsSOGYXDgwIFL1j927Bh5eXm0bNmSkJAQQkND6du3LyNHjrzkFySR6yksLIxq1aqxYMEC9uzZw5EjR0hISLD9MlrUF3vRokWkpaXx9ttvk5OTQ2RkJG5ubuzcuRMfHx9MJhM7duzg0KFDeHp6EhISwrfffktKSgp79uxh9OjRNG/enLNnz3LkyBEsFoszD1vkllacz3V0dDSTJ09m27ZtpKWl8d///pehQ4eycOFCAOLi4oiNjWX48OFs3bqVtLQ0vv32WwYNGsR3331nt781a9awefNmUlNTef/998nPz6dly5YlftwiIiXN6UPf1qxZ0/Z30a+8OTk5rF692q55OywsjIoVK/LWW2/xwAMPEBMTQ/Xq1dWFSkrESy+9xJQpUxgxYgT+/v48+OCD+Pv7s3HjRurWrUvXrl356quvWLx4MYcOHeK9994jNTWVX3/9lRkzZvDhhx/y6KOP8uWXX7Jx40YmT57MsGHDmDJlCoMHD6Zy5cr06tWLChUqsHPnTl588UWmTZtm65YlItffn32uAV555RVmzZrF+PHjycrKIjAwkPbt29vu0fDw8GDatGk888wz9O3bl8qVKxMSEkKvXr1o27at3b66d+/OggULOHDgAAEBAQwePFgtGyJSKjg9bFz48LKiPq8FBQXs3buXRYsWkZuby5kzZyhfvjxjx45l8eLFfPnll3z00UdUrFiRZ555hhYtWjirfCklqlSpwn/+859Lpvfu3RuAzp0707lzZ1atWsUvv/xCbGwssbGxFBYWkpmZCcAzzzzDM888Y1s3KCiIhISES7Y5e/ZsBx2FiFzoap9rHx8fBg4cyMCBA6+4jaCgIObNm0d8fDxvvvkmYWFhl12uatWqjB079voULiJyE3Haczb+jKenJ0OHDqVbt24YhkF8fDyTJ08mNzeXPn36MHv2bCZPnkxkZCRjx461DWEo4kwFBQV8/vnnPPXUU7ZpYWFhHD161IlViYijBQQE8OSTT/Lee+/pnisRkYuUeNi4li/igIAAwsPDef/993F3d6d3796MGTOGxMREqlevTnx8PIZhKGzIDWHNmjVUr17ddmMpnA8bRaOnicit6/777ycnJ4f169c7uxQRkRtKiXaj8vX1JSkpiaSkJP74449ir+fn58ftt9/OqlWryM/P59///jdBQUEEBgbi4eFhd3En4gz5+fksWrSI1157zW56pUqVOHfuHDk5ObahNEXk1uPi4sJzzz3Hf/7zH2JjY22f91atWtGqVSsnVyci4jwl2rLRoUMHTp8+zQsvvICLy7XtulGjRgwcOJAzZ86Qn5/Prl27WLFiBW5ubuzYseOKzzMQKQkrV64kKiqKGjVq2E13cXEhNDRUrW8ipUDt2rVp3Lgx8+fPd3YpIiI3jBJt2YiLiyMuLs72ukOHDnbzy5Urx4oVK2yvu3TpQpcuXWyv27RpY/cANMMw2Lp1K4sXL2bu3Lk88sgjtG3bVk8dlxKVl5fH4sWLeeONNy47Pzw8nKNHj9qGyBWRW1ePHj2Ij4+ndevWVKtWzdnliIg43Q15g3hxmUwmGjVqxJgxYxg+fDi7du2iV69efPLJJ2RkZDi7PCklvvzySxo0aHDFCwvdJC5SegQEBNC1a1fdLC4i8j83ddi4UK1atRg+fDhjx47l7Nmz9OvXj+nTp3Py5Elnlya3sJycHJYtW2bXAncxhQ2R0uXee++lsLCQ77//3tmliIg43S0TNopUqVKF+Ph4pk2bRpkyZRgyZAjjxo0jKSnJYfsstFjJKbCQV2jRL1mlzBdffEGjRo3+9OFcVatWVdgQKUWKbhb/6KOPyM7OdnY5IiJO5fSH+jlKuXLl6NGjB48//jirV69m1KhRhIeH89hjj1G/fn3bAwT/CqthcPSPPHacyCQlI59zeWZMgAF4uLoQ4u9BnYo+1K7oi6fbLZfn5H+ysrL44osvmDBhwp8uFxwcTGZmpkakEilFatWqRdOmTfnkk0/o06ePs8sREXGaWzZsFPH29qZDhw60a9eO77//nmnTpuHt7U3Hjh1p3rz5NY+KdehMLqv3pnMu34LJBJ5uLvh5utrCi9lqkJqRz5E/8vhm/xniwgO4Pawsri5/PdzIjWnp0qU0a9aMkJCQP13OZDLZRqTSTeIipUf37t157rnnaN26NREREc4uR0TEKUrNz+7u7u60adOG9957jyeeeIKlS5fSr18/Vq9eTUFBwVXXN1sNVu09xWe/HyfPbMXfyw0/Tzc8XF3sWkncXEx4e7ji7+WGp5sL6w/9wUebUvkjt9CRhycl7Ny5c6xatYrOnTsXa3ndtyFS+vj5+dGtWzemT5+uLrYiUmqVmrBRxGQy0axZM8aNG8egQYP49ddfefbZZ1m4cOEV+9aarQZLd57k9+OZ+Hm64eXuWqx9ubmY8Pd040xOIXM3H+NMjgLHrWLJkiW0aNGCihUrFmt5hQ2R0qlt27ZYLBbWrVvn7FJERJyi1IWNIiaTiejoaEaOHMno0aNJTk7m2WefZdasWZw+fdpu2e8OnObgqRz8PV1xucZ7PUwmE76ebhSYrXz2+wkKzNbreRjiBGfPnmXNmjU88cQTxV5HYUOkdDKZTLabxbOyspxdjohIiSu1YeNCr7/+Om5ubkyePBmLxcKAAQOYNGkSycnJHP0jly2pmfh5uf2tm8p9PN04l2fmh6Qz17FycYZFixZx9913ExQUVOx1FDZESq+aNWsSFxfHvHnznF2KiEiJU9i4QIUKFejduzfvv/8+lSpVYvjw4Uxa/hOF+XnX3KJxOb6ermxNzeQPdae6aZ0+fZq1a9fy2GOPXdN6lSpVIjMzU8NgipRSTz31FD///DMHDx50dikiIiVKYeMy/Pz86Px/7N13dJRl2sfx7zN9Jpn0TholAQLSlCpFpKirWFcExQoIAoK+6rrrioqiIu++rqCIoqggoqi4i7IqKquAiIJI7wJJIL3XmcmU5/0jJoK0lEkmkOtzDufI5Jn7uWYODvzmLteYMTzzz4UYg8I4nnqYffv2UVxcDI3Y5KdRFFRge2ap94oVzeqjjz5ixIgRhISE1Ot5iqIQFxfHsWPHmqgyIURLZrVaueOOO6SzuBCi1ZGwcRrp6enccsstvPb2u2z6cBG5e36kIjuNZc//hX9MG8u7L/yNnPTfmwR6PB5+/vpT3n3uEV7/60SWPPMg6z95F6fDDsCSZx7k568/BcCi17DpYAajRo3ihRdeOOm+d9xxB5988knzvVBRL3l5eaxfv56bbrqpQc+XsCFE6zZ8+HAUReGbb77xdSlCCNFsJGz8QUlJCbNmzaJfv350GnodGo1CbvoR8o/9ytgZj3PjtMcpLy3ho1fnkp2djcftZvOXK9n23ef0u+rPjHl4NoNvvIMju35m7Yo3AYjtkEJ22iEAdFoN6Yf2ERgcwt69e2vvm5GRQVFRET169PDJ6xbntmLFCq644goCAwMb9Pz4+HjS0tK8XJUQ4nxRs1l86dKllJWV+bocIYRoFhI2TlBVVcUzzzxDTEwM999/P/kVVWgVBXtFOcNumUBoTDztOnel3/BrUKsqKS4qZNsvW9n8zWq69L+cpJ59CQyLpG2XnvS+4gaO7v6FitJi2iR1JjvtcO3Uec7RA/TsN5DKykqysrIA2LNnD4GBgbRt29aXb4E4g+zsbH744QduvPHGBo+RkJAgm8SFaOXatWvHwIEDeffdd31dihBCNAsJGyd46aWXcDgcPPbYY2i1WlweFUWB4MgY9EZT7XVmfytarZbYmGiiw0NwOhzY0ZGamorNZgMgMq4tqqqSn5FGbIcUquw2CrKql9DkHD1Iu+TOJCcn185u7N69m+7duzfqxCvRdD744AOuvvpqrFZrg8eQE6mEEFC9WfzHH3/k0KFDvi5FCCGanISN32zcuJHvv/+e0tJSXC4XUL2hGxV0esPJF9cEAlVFUT2YLWbaJyWj1+vZv38/Bw8exF5VPUaV3Y5/UAhB4VFkHT2ErbyUkvwckjt2IiUlhT179gDVMxs9e/Zsttcr6i4jI4MtW7Zw/fXXN2qciIgIKioq5EQqIVo5Pz8/7rzzThYuXIjHI72XhBAXNgkbvwkKCmL+/PlotVpeeeUVFEUh2KzDfY5TQwwmMwCq20WbNm3o3r07wcHBpB49TFlZGTaHA9Xjqd63kXqIjMP7CY6KJSYskJSUFPbu3Ut+fj65ubmyX6OFev/997nuuuvw8/Nr1DiKohAbGyubxIUQXH755eh0Or766itflyKEEE1KwsZvunTpQmJiIg8++CCbNm3im2++IS7IdM6wERQejcFoIju1ejpco9EQHh5OoFGDxWwBox87duzAFBRO5pGDZBw+QHTbJIJMOjp16kRWVhYbNmwgNja2Xk3iRPNIT09n+/btjBo1yivjyVIqIQRUf/kwZcoUli1bRmmpHIcuhLhwSdj4g4suuojrr7+eRYsWEeIpg3Mch67V6bho4Ah2bVzLgZ83UlKQy+FdP/Pz15/Spd9guvW8mI4dOxIYHU/W8TR2b/mBlKT2KIqC2WwmMTGR1atXyxKqFmr58uXccMMNmM1mr4wnYUMIUSMxMZEhQ4awdOlSX5cihBBNRufrAlqi22+/nW3btvHx2wvRKeD2nD1x9LniBrRaHZvX/IuK0mIs1kA6XTKQPlfeAIDZYqFj5xTaderKsSOHOLj5O57K2sf1119PSkoKq1evpnv37s3x0kQ9HDlyhL179/LAAw94bcz4+Hi2b9/utfGEEOe3W2+9lSlTpnDgwAE6duzo63KEEMLrJGwAixcvPun3er2el19+GYC9OUX/6R8AACAASURBVOV8uicXVVVrT4rqdMlAOl0ysPZ6RVG4ZMS1XDLi2rPe56opM2kfYuaajsGsX7+eRYsWodVqmTFjBr169fLyqxKNtXz5cm666SZMJtO5L66jhIQE2bMhhKjl5+fHXXfdxcKFC3nxxRfRaGTBgRDiwiKfaufQOcKPDmEWyhzuRo1jd3nQaxSu6BiG0WhkxIgRLFiwgHvuuYcNGzYwfvx4PvjgA0pKSrxUuWiMQ4cO8euvv3LVVVd5ddzw8HA5kUoIcZLLLrsMs9nMl19+6etShBDC6yRsnIOiKFzdOZwwPz1ldldtY776sDvduNwe/twtCn/j75NJiqLQs2dPZs2axezZs8nLy2PSpEm88sor8u23j7333nvcfPPNGAyGc19cD4qiEBcXJ/s2hBC1FEVh8uTJLF++XL5wEkJccCRs1IFZr+XWntHEBBopdbhwuet2LrqqqpTZXSiKwpge0cQFnXk5Tnx8PPfffz+vv/46oaGhPPbYYzz11FNs3769QQHHG1RVpdLhoszmpMrVuJmd88n+/ftJT09n5MiRTTK+bBIXQvxRQkICQ4cOZcmSJb4uRQghvEr2bNRRTeD4JaOU7w4XUel0YdBpMGqVk7p+q6qKy6Nic1YHkk7hfoxIDsVi0NbpPoGBgYwdO5abbrqJdevW8cYbb6DRaLjuuusYMmQIer2+SV5fTe2704v4YX8eO1IL+TWrFKfbgwJ4VAjxN5ASF0TPdqEMTokiPNB7exlakmXLlnHLLbc02XstYUMIcTpjx47lvvvuY9++fXTu3NnX5QghhFdI2KgHjaJwSWwgXSL92ZtTzvbMMvIrnGiU6mlwVBW3Cha9lotjA+gRYyXMr2HLcAwGAyNGjGD48OFs376dVatWsXTpUv70pz9x1VVXERgY6LXX5XJ7+Gp7BsvXHyGzsBIVsBh1BFj06LTVk1+qqlLl8rDl13w27s/l1S/20b9jJLcNaUfn2CCv1eJru3fvJicnh2HDhjXZPeLi4ti2bVuTjS+EOD9ZLBbGjx/Pa6+9xosvvohWW7cvqYQQoiWTsNEAZr2Wi2MDuTg2EKfbQ5HNhdPtQaMoBJp0dZ7FqIuafR09e/YkPT2dVatWMWnSJAYOHMh1111HXFxco8ZPyy3nuZU7OJBRgr9ZT3ig6aSZmhPrMOq1GPXVr83tUfnxYC4/7M/hzwMSuWdYMiYvvm5fUFWV9957jzFjxqDTNd3/GgkJCTKzIYQ4rUGDBrFmzRq++OILrrnmGl+XI4QQjSZ7NhpJr9UQ4W+gTaCJ6ACjV4PGH524ryMsLKzR+zq+2n6c8Qu+52hOGZFBZvxN+tMGjdPRahTCAkyEWI189MNRJiz4nqyiynrX0JLs2LGDoqIiLrvssia9T3h4OJWVlXIilRDiFDWbxd9//32Ki4t9XY4QQjSahI3zUGBgIGPGjGHx4sUMHDiQN998k/vvv5+vv/6aqqqqOo3x2ZZ0nvt4J1aznhDr6Wcz6kKn1RAZZCG3xM7URZvILDw/A4eqqixbtoyxY8c2+dIFOZFKCHE2cXFxDB8+nHfeecfXpQghRKNJ2DiPGQwGhg8fzssvv8yECRPYuHFjnfp1bDqQy/+t2k2Iv7F2WVRjhViNlNtc/M/bmymzOb0yZnPaunUrlZWVDBo0qFnuFx8fT1paWrPcSwhx/hkzZgw7duxg7969vi5FCCEaRcLGBUBRFHr06MFTTz3Fc889R35+PpMmTeLll18+pV9HSUUVz328A6tZj8FLQaNGiNVIbrGN19bs9+q4Ta1mr8Ztt93WbN174+PjpZeKEOKMzGYz48ePZ+HChbjdrefocSHEhUfCxgUmLi6OadOm8frrrxMeHs7f//53nnzySbZt24aqqsz/z14q7C78TE1zrGtogInPfz7O1sP5TTJ+U9i8eTNut5sBAwY02z3l+FshxLlceumlBAUF8Z///MfXpQghRINJ2LhA1ezrePPNNxk0aBCLFy/mrikPsWrjAUL863ccb9ov37Dh7b/X6VqtRsFo0PLGVwcaUnazq9mrcdtttzV430pDSNgQQpyLoihMmjSJFStWUFhY6OtyhBCiQSRsXOBO3NcRe/GfKCsvZ9eunWRkZOByNs3eikCLnoOZpRzOLm2S8b1p48aN6PV6+vTp06z3rTmRqry8vFnvK4Q4v8TGxjJy5EjZLC6EOG9J2GglXG6VXzI9dEluS6dOnXA6nezcuZOjR49is9m8ei9FUVAU+Hzrca+O620ej4fly5c3+6wGVL9Hsm9DCFEXt9xyC7t27WL37t2+LkUIIepNwkYrcSy/Apfbg0GnwWw2k5iYSLdu3TAaDBzYv58DBw5Un2DVgH4dp2Mx6fn515a9b2PDhg34+fnRq1cvn9w/Li5OTqQSQpyTyWRi4sSJLFy4EJfL5etyhBCiXiRstBJHcspw/yFH6PR6Ytq0oXv37oSGhnLs2DF27d5NXl4eHo+nUfczG7Qcy6/AXtUyT1Fxu90sX76ccePGNfusRg3pJC6EqKv+/fsTGhrK6tWrfV2KEELUi4SNVuJwdtkZu4wrGg1hYWF07dKFhPh4ioqK2LFjR6P2dWgUBa1WIbu4ZTb5++677wgJCaFbt24+q0E2iQsh6qqms/iHH34om8WFEOcVCRutRIXdiVZzjm/wFYWAwECSk5NP2teRX1CA2+Wu9xIrBQW7s3EzJE3B5XLx/vvv+2SvxokkbAgh6iMmJoarrrqKxYsX+7oUIYSoMwkbrYRWo1CfqHDivg6dVktFRQW7d+8mJzu7zmuGVVTOlW+8SVVVKm1VlJTZqLA5cLtPH3S++eYboqOj6dq1a/MVdxphYWHYbDbKysp8WocQ4vwxevRo9u/fz86dO31dihBC1InO1wWI5hFiNZ7xH99no9PrCQoKojQggISERPLycsnIyCAwKIjw8HACrFY4w+yA6gGLsen+iKmqyu5DmWzedZRte4+x72g2dntV7WyFRqPQLi6cnp3juDglgT7dElFQWbFiBX/961+brK66OvFEqpSUFF+XI4Q4DxiNRiZOnMhrr73G/Pnz0enkr3EhRMsmn1KtRLsoKzptIyayFLAGWLEGWHG7XOQXFJCeno7H7SYsPJzwsDD0ht+bBbrcHjQahZhgixeqP5nd4eSbTft497OfyMgpwuNRsZgM+JkNBFnNtde5PR4yc4v5NT2Xj9Zsxd9spFMbAxHR8XTs2NHrdTVEzVIqCRtCiLrq27cvX375JZ9++ik33nijr8sRQoizkrDRSrSLtHrrVFu0Oh2RkZFERkRQUVlJXl4eu3bvxupvJTw8nMCgQGxVbjpEB6Dx8jqq3YcymPXqajJzSvCzGIgIsZ5x34VWo8HqZ8LqZwKg0ubgw692kJgQz+frd3HVoK4+3bMBsm9DCFF/NZ3FH3roIQYPHkxYWJivSxJCiDOSPRutRFSQmbAAIxV2L57Rrij4+fmRmJhIj+7dCQoOIjMrkx3bd3A8M4dubUxeu5Xb7WHhB+uY9NR7FJZUEBUegNXPVK+wUFpSRGigH0EB/jyz8HP+54WPKCnzbkPD+pKwIYRoiOjoaK6++mrZLC6EaPEkbLQSiqJwy8C2VNjrf5RtQq/hDLr72bNeo9FqCQ8PJyUlhQ5JSaiqh7Xvz2PmzJls2LABZwOP0AVwudzMenU1S1dtIizYjyBr/Zdmud1usrKyiI1tg9lkIDo8gM27Upk86z3yi8obXFtjSdgQQjTUzTffzKFDh9i+fbuvSxFCiDOSsNGKDOsWg06rocrVtI32bG4tf76sG++9vYgRI0awZs0a7rrrLt588816/8NaVVWeW/QFX/+wj6jwQHRabYNqys3NxWq1YrFUBxVFUYgKC+B4ThHTn1vhsxmOsLAw7Ha7nEglhKg3g8HAvffey2uvvdaoL3SEEKIpSdhoRQItBiaMSKawzHHGBn+N5XC60WoUJoxIxmAwMHjwYGbPns3//d//YTQamTlzJo888ghff/01drv9nOOt+u8Ovtiwh6gwK5oG7q+ontXIpk2bNqf8LCLESmpGAXPfWtNk78nZ1JxIJbMbQoiG6NOnDzExMaxateqUn6mqituj4vHBZ5sQQtSQDeKtzI39Evjvzix+zS4lLMB7eyoAPKpKUbmD/7m2KzEhJy91ioqK4vbbb+fWW29l69atrFmzhrfeeouBAwcycuRIOnTocMr+i8zcYua9u5aQQAsaTcNzcXZ2DoGBAZjN5tP+PDLUyrc/HWD9z4cY0ju5wfdpqJqw0aVLl2a/txDi/Ddp0iQefPBBhgwZgtEazOH8CjJK7RTZnHg81UHDz6Ajwt9Au1ALMQEmrx/eIYQQZyJho5XRaTU8Pro7k1/7gZKKKgL9DOd+Uh2oqkpeiZ2BnSO55pK4M16n1Wrp06cPffr0oaCggLVr1/LCCy9gsVgYOXIkl112Gf7+/gDMXbwGt0fFZNQ3uC6Xy01OTjadO5/5aFmNRiHA38Rzi77g4i4J+FuMDb5fQ9T02hBCiIaIjIzk6utuZPFXm4np2A0AnUaDSadBoyi/zXB4SCuykVpkw6TTMCAxmNig038BI4QQ3iTLqFqh2FA//nl3X7QahcIyR6PHc3tUcovt9O4QxszRPer8jVloaCijR4/mjTfeYPz48ezbt48JEybw4osv8uXajWzZnUb61k/4dft/G1xbdnY2QUFBmM1nn8XxMxupqHTw3x/3NfheDRUXF0daWlqz31cIcWHILLGjduhLlSEAZ2UFfgYdxt+CBlQv19RpNVgMWvwMWtyqytpD+Xx/tBC3R5ZYCSGaloSNViopJoBXJ/UnOthMTrENZwO6iwOU2ZzkldgY1TuO2bf1wqiv/wZuRVHo3r07jzzyCIsWLaJ9+/bMnv8eaWmpVFbaGtT5HMDlcpGbm3PavRqn42cx8O6nPzX73o2EhATZsyGEaJDjxTa+OZSPVqOhTWQY6elpeDxn/8w0aDX4GbQczq9g/ZGC2qVWQgjRFCRstGLx4f68MfVSbh/SnpKKKnKLbVQ5z31SlaqqlFY6yS22YTZoefHuvvzPdV0x6Bp2UtSJAgICuOpPV6MPbk/H9gm43W4yMzM5dOgQxcXF9QoCWVlZBAeHYDTWbVmUn9lIdn4pew9nNbT8BgkNDaWqqkpOpBJC1Eu5w8W6I4UYtAoGrea3WVwz2dnZ53yuoij4GbSkFdnYnV392fO3v/2Nxx9/vKnLFkK0MrJno5Uz6LTcMzyZK3vFsvrnY/z7p3RKbU7cHhW9ToNBqwEFVBVsVS4UqqflE8L9GTMwkUFdojAbvPvHKDWjAI9bJSQkEKvVijUkhsDAQI7+upei43tQ3DaMBj3WoAhiO/YmOCKe4rxj7N30GRcNuhFrcBROp5O8vDwS2kTww6ev0rnfNQRHxFNamMWx/ZupKM0HVSUwPI62XQdiMPmhKApuj4cDR7Pp0iHGq6/pbBRFqV1K1bVr12a7rxDi/KWqKj+kFuHxqJgMv3/REx8fz549ewgNDT3nFy2KomDRa9mRWUp8sOzfEEI0DQkbAoCYEAv3juzIHZd14EBGCYdzStmZWkReqR2XW8Wg05AUHUBKXBAdoq0khPvXq3t3fRw5lo/7hGUAGo1CUIAfqXl7CQ+PxBicQHFJCWVlmez8/t/0GjqWwLA26I1mCrOOYg2OIisri5CQUMoK0tEbzQSFx1JZVsTeTZ8SHJFA1wHX43Y5Obp7A3t/XE33ITejKBoMei3b9x/nxhG9muS1nUnNJnEJG0KIuiisdJJd5sCiP3mBgtFoJCoqivT0dJKSks45jlajoKKyJ1tmVoUQTUPChjiJyaCle9sQurcN4cZ+iT6pYd+RrFOCTG76fjweN537XIlOb8Dj8VBQUMjOdcvZunEN7boNxhoWR0H2EaI7XExeXj4XXdSV3Rs2EBrTAUXRkHV0J1qdgaReI9D81hywQ4/L2f7dCopy0wmJTMRiMrD318xmf83Sa0MIUVd5eXk8+X+v8Mu27aguJ4EhYfQeegW9Bl4OwDvP/5VOfS/j4M/f8+vOrbhdTuKTOnPV2HvwswYAkHM8nS8/eJucjHT8A4O4ZPgoPB6VBvZNFUKIM5KwIVqcwpIKdLqTv60rL8nFYg1Bp68+qlej0RAeHkab+A5UlpeiKAolNoXi7OPs272NsLBonLYS7BWlhLep/navvCgHa0hUbdAAsASEojMYqSzJJyQyEZ1OS1ll40/oqq/4+Hi2bNnS7PcVQpx//vGPf5B6rIBbpz2Kv7+VI/t3sWbFOwSGhNE+pRsKkHFgFyGxbbltxmOUFObzyZvz+f6Lf3PF6Dtwu1x8vOif+FkDueN/ZqIoGtZ+9hEUZtA5qb2vX54Q4gIjYUO0OKc7itHtqkKrO7UniFZnQMFDXFwcMTFt+LH4MBVFmfgFhJKfmYXRYsUaEvXbGE6KctL46fM3Th7b7aTKUQmAAg0+/aox4uPj5fhbIUSdTJvxIJ/uyyMyLBRFUeh56VA2ffUZR/fvon1KdZ+NsMhoeg/7Ew4PtE/pRnxSJ7LSjgCQdmgfpUUFXH/PVKLiEgG44taJfPT8I756SUKIC5iEDdHimAy6U45i1OmM2G2lp1zrclWh/W22Q6vVEJPYmZL8TJxOJxkHt5GY1KP2Wq1eT5B/HIldB54yju63IONRVYxe3vBeF6GhoTidTkpLSwkICGj2+wshzh+VdgcbV39ETuohbJUVqKqKq8qBvbKy9prohLbEx8ezb/9+QkNCsPgHUJSXA0B+dgYAEW3ia683mS2ERTffwRhCiNZDjr4VLU77uHCcrpOP4PULCsdWVoTL+fsSJ9XjoaI4F/+giNrHQmM6UFlaQGSIBUdFCXbVRM1puf5BkdgrSjBZAjD7Bdb+Uj1udIbqpn92h5P46JCmf5F/UHMilezbEEKcjc1mY9bMv5NzLJWRN9/BXQ8/yfhHnyEwNPyk6/R6AwaDgYjwcNLS0k7aB1dlt6MoCnr977PFqgpG49mbnwohRENI2BAtTlJiJDrtyX80I+NT0Gh1HNz6NRWlBVSWFvDr9v/icjqISryo9jprcBQGsz/H9v9IeHQ8Ho2R1NSjqCpEt70Ih62MIzvXUVFagK28mLR9m9ix7kNs5UUAVNqq6Nk5Hl+QTeJCiHPZtWsXpSUljLjlbtp36U5oZAzB4ZHYKspPe31UVPVR4BUVFbWPGYxGVFXF6ayqfUxRwO2wNXn9QojWR8KGaHHax4Xh9qgnNfDTG810GXA9quph14aV7NzwMQ5bOSn9r8ViDa69TlEUwmI6UFFSQERsR5KTk7Hb7aSmHsXsH0JKv2uxlRexa8PH7Fi3grLCbFL6jcJirZ7N0Go1dGoX2eyvGaSTuBDi3FwuF4oCkaFBON3Vn5G/7t6Ow1Z52qaniqKQmJhIcXFxbWfxkIhoALLTjtZeV15cTH5O85/EJ4S48MmeDdHihAb506ltFKmZ+Vw8/Pbax/0CQunS/9pzPj+xywASuwyo/X1ycjIHDx4kNfUoiYlt6XrpDad9ntPlRlEUenSKa/yLaID4+Hh++uknn9xbCHF+6NChAxqNhiObvyW8x1BKs9PY/O2XxLZLJj87g9KiglOe4+/vj9lsJie/urN4QscU/KyB/HfVB1x5y1043R42fPYR4SHNv4RUCHHhk5kN0SKNG9UXR5XLK2NptdqTZjhO8+UfAIUllfxpcFcC/H3TSVeWUQkhziUiIoKpU6eSum8ny/73cbZt/I7r7prCJUNGUJCTxSdvvnza5wUFBVHlqKK8vBy93sBN987A43az5B+zWPnGfEYOu4zk5HM3ARRCiPqSmQ3RIl3aqz1+ZiM2exVm06lH3tZXTeA4cYbjxL6B1R3LVW4c0bPR92qokJAQXC6XnEglhDirkSNHMnLkSHZklLA9qxQ/vZag0HA69+p7xudce8ckBl5zM0ePHqVr1660SezA3X95GofLg16rcF3XKAza65rxVQghWguZ2RAtkkGv48E7h1FcZjvtOuSGONsMR35hOVcO7EJSgm/2a4CcSCWEqJ+u0QGEmA3YnHXrDRQSEoLRaCQru3o5lcuj4vKoDGoXikEr/xwQQjQN+XQRLdYVl3ahf4925BWd/pSVhjhd4CivtBNkNTN93OVeu09DyVIqIURdaTUKw5LC8DfqqKhy1emLmYSEBLKzsiirtGF3eRjYNpgoq7EZqhVCtFYSNkSLpSgKj064En+LkeLSynM/oY5ODByHfj1MWYWDJ6eN8tlejRNJJ3EhRH1YDFqu6hROXJCZiio3DpfnrKFDqzcQ0SaOzIwMhieF0i7UrxmrFUK0RhI2RIsWEWLl5cfGoNFoKPJy4IhPaEtphYPuMS4u6ZLgtbEbIz4+nmPHjvm6DCHEecSk13JZ+1CGdgjFatRhc3qoqHJRWeXG7nRjc7opd7iprHLj9qgM6BhL9vf/4vCOLb4uXQjRCkjYEC1eh4QIXn/qNiwmA9n5pXg8jdvDoaoqhcXlVNqdLHx6PEH6cubPn++1vSGNIcuohBANoSgK8cEWrkmJ4JoukQxIDKFDmB8xgSbig8xcHBvAsKQwRnePpnd8CFMnT+LNN9+kvNx7y1SFEOJ0JGyI80K7uHCWzb2HYf06kZ1fQlmFvUHhwFHlIju/lLjoEN5+9i7+NKQ7Tz75JNnZ2S0icNScSFVSUuLTOoQQ5ydFUQg26+kQ5kf/xGCGdghjcPtQukYHEBNoQvfbRvCOHTvSv39/lixZ4uOKhRAXOgkb4rwRZLUwa9oo5j50E1Y/E7mFZeQVleN2n/0kFo+qUlJmIye/FEeVi8m3DGHxM3fSPj4cAJPJ1GICh6IoMrshhGgWd9xxB5s3b2bfvn2+LkUIcQGTsCHOK4qiMOiSJD5+aRLzHxtD/x7tKCytJK+wnNzCMjJyisnKKyEjt5ic/FLyi8rJLSgjPiaEWfePYvXCqdxxXT/0eu1J47akwCH7NoQQzcHPz4+JEyfyyiuv4HJ5p4mqEEL8kTT1E+clRVHolRJPr5R43G4Px3OKOJyeR15ROY4qJwa9jgB/E+1iw0lsE4rJqD/nmDWBY9asWcyfP5/p06ejnNj5r5nExcXJiVRCiGZx6aWXsnbtWj755BNGjx7t63KEEBcgCRvivKfVakiICSUhJrTRY7WEwJGQkMCPP/7YrPcUQrROiqJw33338cADDzBo0CCio6N9XZIQ4gIjy6iE+ANfL6mSPRtCiOYUERHBzTffzKuvvurzQzKEEBceCRtCnMaJgWPevHl4PGffhO5NwcHBuN1uOZFKCNFsRo0aRUlJCevXr/d1KUKIC4yEDSHOoCZw5ObmMn/+/GYLHHIilRCiuel0OqZOncrixYspKyvzdTlCiAuIhA0hzsJkMvHEE080e+CQsCGEaG4dO3ZkwIAB0ntDCOFVEjaEOAdfBA4JG0IIX7j99tv5+eef2bt3r69LEUJcICRsCFEHzR04JGwIIXxBem8IIbxNwoYQddScgUPChhDCVwYMGEBUVBSffPKJr0sRQlwAJGwIUQ81gSMvL69JA4ecSCWE8BVFUZg8eTL//ve/ycrK8nU5QojznIQNIerJZDIxc+bMJg0cNSdSSSdxIYQvSO8NIYS3SNgQogGaI3AkJCTIUiohhM/U9N5Yt26dr0sRQpzHJGwI0UBNHThk34YQwpd0Oh3Tpk3jrbfekt4bQogGk7AhRCOcGDi83Wk8Pj6eY8eOeW08IYSor+TkZC699FLeeecdX5cihDhPSdgQopFqNo3n5+d7NXDExcWRlpYm66WFED41btw4tm7dyp49e3xdihDiPCRhQwgvMBqNXg8cwcHBqKoqJ1IJIXzKz8+Pe++9lwULFkjvDSFEvUnYEMJLvB04ak6kkn0bQghf69+/v/TeEEI0iIQNIbzI24FDjr8VQrQE0ntDCNFQEjaE8LITA8dLL73UqMAhm8SFEC2F9N4QQjSEhA0hmkBN4CgoKGhU4JBlVEKIluTaa6+V3htCiHqRsCFEE/FG4KgJG/ItohCiJdBqtdJ7QwhRLxI2hGhCjQ0cQUFBABQXFzdFeUIIUW81vTfefvttX5cihDgPSNgQook1JnDUnEgl+zaEEC3J7bffzi+//MLu3bt9XYoQooWTsCFEM2hM4Khp7ieEEC2FxWKp7b3hdDp9XY4QogWTsCFEM6kJHIWFhXUKHA6nm59/zSfdHcWr3+Ux7qV1jPnHd4x7aR1/WbKF99YdZvOhPOxV7mZ6BUII8bv+/fsTExMjvTeEEGel83UBQrQmRqORmTNn8swzz/DSSy/xwAMPoNGcnPmzi2z8Z+sxPtmUhsPlpqwcSopcGEKdKBoF1amys7SILYfy0WoVDDoN1/VJYFTvOGJCLD56ZUKI1qam98aMGTMYNGgQMTExvi5JCNECycyGEM2sJnD8cYbD7fHw0Q9HuWPeet5bdxiDXkNYgInY8AA8jnLMBi0mvRazQUeQn4HIYDNhASZMBi0rvj/CHfPWs3z9YVzuxjUSFEKIugoPD2f06NHSe0MIcUYSNoTwgT8GjtziSqYt+pEFn+/H36QjIsiMUa8FQK+rnoB0ulynHcug0xIRZCbAYuCNrw5y32s/kF1ka7bXIoRo3UaNGkVZWRnfffedr0sRQrRAEjaE8JGawHEst4SrH/uAg5mlRAaZMPwWMmopCmazGZvt7AHCoNMQEWTiaG45097YREZBZRNWL4QQ1aT3hhDibCRsCOFDDreGrLAhlDnclOVnoJzhurqEDaheQx0WYKK0sooH3vqJonKHdwsWQojTSEpKYtCgQdJ7QwhxCgkbQvjQK5/vJbfEQbdO7XE6XRw5cgROs+65rmGjRojVREGpnRc/3SPrqIUQzWLcuHHSe0MIcQoJG0L4yI8Hc/lqewZhASY0Gg1JyUlnDBxmsxlbZf2WRYUFmtiwN5v1e7K9WbYQQpyWX9bRbwAAIABJREFU9N4QQpyOhA0hfMDjUXnps734mfRoNAqbP5zLrxv/dcbAYTabsdntp531OBONomA1G5j3n71yQpUQolnU9N5YuXKlr0sRQrQQEjaE8IEdqYXkFtvwN1WfNNVj1BTa9b36jDMctSdS1fPbQj+TjuLyKn4+nO/dFyCEEKdR03vj008/JSMjw9flCCFaAAkbQvjAJz+modEoKEr1lnCD2R+dwQRwUuA4XBM4FAVLPfdt1NDpNHy8MdWb5QshxBmFh4dzyy23SO8NIQQgHcSF8JodO3awbNky0tLSAGjXrh133nknnTt3pqqqiqVLl7Ju3Trsdjtbs7Uk9bsKAhIA2PzhXIKi25M86CYA7KX5ONM2kXZkH4dVN9HtUjDG9sBmsxEQGEjOoa0cXL+Si//8IId/+JTSvGPoDGbadOlP7EWDa2sqzjpK6pYv2J6bScGGZC4fOpSxY8ei+22mZN++fSxbtowjR46gqio9e/Zk4sSJhISENPO7J4S4kFxzzTX897//5bvvvmPo0KG+LkcI4UMysyGEF5SXlzN79mw6duzIvHnzePHFF4mNjWXWrFnY7XYWLFjApk2beOSRR/jbU3PQWYLY980SHJWlp4zltFew8/M38Lid9L1xKlGXXE9RUTGZW1ZRXlZy0rW/bvw3MV0updf19xOW2IWjm7+kLO84AJXFuez56m2Co9uRfOVkbhx7F1988QVLly4F4Pjx4zz++OP4+/szZ84cnnrqKbKzs3nyySdru5oLIURDSO8NIUQNCRtCeEFmZiZ2u50hQ4YQHR1NbGwskyZN4sknn8Rut/Ptt98ybtw4unXrhkNnJa73nwhpk4yjrOiUsbIP/Iyryk6noWMJjIyn6yUDCOtyObbyEvIObz/p2qjk3oTGd8IcEEpc98sAKMuvDhuZezdhsATQtveVmALCCIhOZvz48bXP/fTTTzGbzTz88MMkJCTQqVMnHnjgAVJTU9m6dWvTvVlCiFZBem8IIUDChhBeER8fT0REBHPmzGHlypUcOXIEnU5H586dOXz4MKqq0r59ewAq7C7Q6Ok0dAwBkQmnjFWWfwxLUAQGsz9QvYejU9du6P1DKMpOO+lEKv/wNrX/rTf5AeBy2H4bJwP/0BgA3B6VCoeTYcOGcc899wBw4MABUlJS0Ov1tWMkJCRgtVqrN6cLIUQjjRs3jm3btknvDSFaMdmzIYQXmEwm5s6dy8qVK1m9ejXvvPMOERER3H333bjd7tpr6sJd5aCiMJuNS5866XGj6kRrsJCXl1f7mFZnqP3vms3mUB1GXFU2NLqIM97HZrOxefNmbr755pMedzgcFBWdOuMihBD1dWLvjfnz55/05YYQonWQsCGEl4SGhnLvvfdy7733cvToUT788EPmzp3LhAkTAKj8rSmf2aA9IRicSmsw4RcSRefLbz3lZ1VOF0fSjhNuOvcRuAaTH26nHajuuWEynPy/u8VioVevXkycOPGU51oslnOOL4QQddGvXz/Wrl3LypUrGTNmjK/LEUI0M1lGJYQXZGVlsWXLltrft23blqlTp6KqKgEBAeh0Ovbu3QtAXJgfHo+bnV+8SX7qqUsLrGGx2MuLMJitmANCa3+pHg/W4DAio6LIzs6hZgbjTPxCYyjNTUdVVTQKxIX68c033/D0008DkJycTGZmJlFRUURHR9f+crlcBAQEeO/NEUK0aoqiMGnSJOm9IUQrJWFDCC/Iysri2WefZfXq1WRnZ5OVlcXKlSsxGAx07dqVIUOGsHz5cnbu3ImmqoTMrZ9TlpeBNTzulLEiky9GURT2r1tBWX4GttICju/awC//mkdJ1hGio6Jxu9w4qqrOWlNMSn9cDhuHNv6bytICijMPsWTJEmJiqvdxjBo1itzcXBYsWEBqaioZGRksWbKE6dOnc+zYsSZ5n4QQrZP03hCi9ZJlVEJ4Qa9evZg6dSqrVq3i7bffRq/Xk5iYyMyZMwkLC2Py5Mm89dZbzJ07F4fDgb9qJGzwbRj9Ak8Zy2D2p9uf7uXo5i/Y+fkbqB43luBIOg0dQ3CbJACio6PI22OnqqoKo9/pa7IEhtNlxJ0c2PQflNTtvFrcjmHDhnHbbbcBEBcXx+zZs1m6dCkPPfQQUH16zNNPP018fHzTvFFCiFarpvfGt99+y+WXX+7rcoQQzURRz/AVw/Hjxxk2bBhr164lNja2uesS4oK2cX8OM5f/QkSgucFjZGRkUFFRQXJSEpxlD0husY2Zo3sw9KLoBt9L+I58Fp+ZvDfnn0OHDvH000+zYMECWa4pxAXiXJ/FsoxKCB/o0yGcALMem8PV4DFiomOoqqqioKDgjNc4nG7MBh0DOp35VCohhGguSUlJDB48WHpvCNGKSNgQwgf0Og2TruhISaWzweuXFY1Cu7ZtST92DOdp9m+oqkpRuYPxw5Mx6rWNLVkIIbxi3LhxbN++nV27dvm6FCFEM5CwIYSPXNkzlks6hFJQ6mjwGBY/P8LDw0lNO7nZH0BBmYOLEoK5vq/svxBCtBxms5lJkyaxYMECnM5zH+MthDi/SdgQwkcUReGR6y/CYtJRUnH2k6XOpk1MDHa7ncLCwtrHSiudGPVa/npjdzSaM+/nEEIIX+jXrx+xsbGsXLnS16UIIZqYhA0hfCgyyMyLd/dBq1EoKm/YDIei0dCuXTvS0tNxOZ2UVFahqir/e2dv2oRKcz4hRMs0efJk6b0hRCsgYUMIH+sQHcDLE/sRYDGQU2zD7an/Hg4/Pz9CQsPYc/gYZoOWeRP6khIX1ATVCiGEd4SFhUnvDSFaAQkbQrQAbSOtvHP/IK7tHU9+qZ38UnudQ4fHo1JQZsdoDSXUncWUvkaSY07t3yGEEC3NNddcQ0VFBd9++62vSxFCNBFp6idEC+Fn0vHgtV0Y2TOGFd8fZeO+XDyqik6rYDHoMOq1KEr1PnCHy02lw43L5UHRQP/kCG4Z2Ba9rS3PP/88fXp1kzPshRAtnlarZdq0acyaNYtLLrlEPreEuABJ2BCihekSF8zTY4PJL7Xz08E8th8tZM+xInKK7bg8HnQaDeGBJnp3CKNbQgh9k8OJDKppDhjC4MGDWbRoEQ8//LBPX4cQQtRFhw4dantvzJgxw9flCCG8TMKGEC1UWICJqy+J4+pL4mofU1UV5SzdwgFuv/127r//fn766Sf69u3b1GUKIUSjjRs3jilTprBr1y4uuugiAFxuD6n5laQX2jiQXUpxpRMV8DfqSI70Jz7UQvtwP+kjJEQLJ2FDiPPIuYIGgNFoZPr06fzv//4vXbp0wd/fvxkqE0KIhjObzUyePJkFCxYwe+6L/HC4mM935VDucOFRVbSKgk5bvc3U7VH58XAhWo2CTqswvHMEw1MiiAw0+fhVCCFORzaIC3EB6tq1KwMGDODNN9/0dSlCCFEnffr0QRfTlbsWruODLcfxqCohfgbC/I0E+xmwmnRYTTqCLHrCrNWPmfRaPt+VzcMf7mLVtkxcbo+vX4YQ4g8kbAhxgbrzzjvZvXs3W7Zs8XUpQghxVg6nm39+9Ss5ob0ozM/DX+fBVIflUXqthlB/I/4mHR9sPs4T/95HUSOapAohvE/ChhAXKJPJxPTp03n11VepqKjwdTlCCHFaDqebuV8e5OfUIqKCLMRGR5KamgrUvfeGXqshzN9AemElT62SwCFESyJhQ4gLWLdu3bjkkktYvHixr0sRQohTqKrK6+uOsjezjFB/A4qiEBkZidvtIT+/oF5jKYpCiJ+BwooqXvjiIE6XLKkSoiWQsCHEBe7uu+9m+/btbNu2zdelCCHESbYcLWLT4ULCfgsaUB0aEhMTOXYsHZfLWe8xgyx60gsq+WxHlrfLFUI0gIQNIS5wFouFadOm8corr2Cz2XxdjhBCAFDhcLFo/VF+ee85dq55/6Sf+fn5ERoaRnr6sXqPqygKQRY9n/ySSUaRfOYJ4WsSNoRoBXr16kX37t15++23fV2KEEIA8OPhQiqr3Fx2x8OkDL3hlJ+3adOG0tJSSktL6z22TqtBVWHN7hxvlCqEaAQJG0K0EuPHj2fLli3s3LnT16UIIVo5VVX5bEcWFr0Wo8WK3mg+5RqtVktCQgKpqal4PPXffxFo1vHdgXwqHS5vlCyEaCBp6idEK+Hn58eUKVOYP38+r7zyCiaTNMASQnjHjh07WLZsGWlpaQC0a9eOO++8k86dO1NVVcXSpUtZt24ddrudDh06cM2fbyWvzEGIn4G1i54iLD6Z7lfeCkBZQTb71q2iODsNt7MK1RSIWauS1KU7AMd2/8T2L99j6D1/Z9c3H1GclYreZCGx1xA69B5WW1NJ5hG2rf0Xo1aWkhgTzmWXXcbYsWPR6ar/6bNv3z6WLVvGkSNHUFWVnj17MnHiREJCQpr3zRPiAiczG0K0Ir179yYlJYWlS5f6uhQhxAWivLyc2bNn07FjR+bNm8eLL75IbGwss2bNwm63s2DBAjZt2sQjjzzCvHnziIqKYtZTT1JVWVq7KbxGVWU5m1bMx1XloM+Nkxgw9gECg4LZ+u/XKS0uPOnanV+voN3FlzH4jkeJSupeG1CgOrD8tHIh1uh2jJ3+BFOmTOGLL76o/ew7fvw4jz/+OP7+/syZM4ennnqK7OxsnnzyyQbNogghzkzChhCtzMSJE9m4cSN79uzxdSlCiAtAZmYmdrudIUOGEB0dTWxsLJMmTeLJJ5/Ebrfz7bffMm7cOLp160ZMTAyTJ08msm0KlcWnHm2bvmsTToeNi6+9m6CoBAIjYuk96i4MWoXt67/gxN4b8Rf1J7J9V/yCw0nqNxKA4ux0AFK3rcfoF0DnwdeSr1q5+OKLGT9+fO1zP/30U8xmMw8//DAJCQl06tSJBx54gNTUVLZu3dq0b5gQrYyEDSFaGavVyn333ce8efNwOBy+LkcIcZ6Lj48nIiKCOXPmsHLlSo4cOYJOp6Nz584cPnwYVVVp37597fVGo5Ehfx5PcJt2p4xVlJ2GNTQKo8Va+5jB4k9Ym0QqC7PJzv59w3dQVPzv15j9AXDaKwEozj5GYGQcOq1Cmb36+Nxhw4Zxzz33AHDgwAFSUlLQ6/W1YyQkJGC1Wjly5Ig33hYhxG9kz4YQrVC/fv3YsGEDy5YtO+nbPiGEqC+TycTcuXNZuXIlq1ev5p133iEiIoK7774bt9tde01duBx2SvMy+WLewyc97na5sITHcfDgAYK1dgC0ekPtz2uWY6m/TXw4HZVY9ZFnvI/NZmPz5s3cfPPNJz3ucDgoKiqqU61CiLqRsCFEKzVp0iSmTZvGpZdeSqdOnXxdjhDiPBYaGsq9997Lvffey9GjR/nwww+ZO3cuEyZMAKCysvKk64MtBtwe9ZRx9EYzAeExXDzqnlN+VuVyc/RYJvnHM845K2s0++OssuNyq1hN+lN+brFY6NWrFxMnTjztz4QQ3iPLqIRopQICApg0aRLz5s2jqqrK1+UIIc5TWVlZbNmypfb3bdu2ZerUqaiqSkBAADqdjr1799b+3OVy8Z+3X6Tw6K5TxgqKiqeypBCjXwB+weG1v1SPh4CQMDweD3GxsTgcDrKysjhxD8eJAiPjKMpMxe500zm6eknWN998w9NPPw1AcnIymZmZREVFER0dXfvL5XIREBDgxXdHCCFhQ4hW7NJLLyUhIYH333//3BcLIcRpZGVl8eyzz7J69Wqys7PJyspi5cqVGAwGunbtypAhQ1i+fDk7d+4kKyuL119/nYKsNPwj4lDVk8NC3EX9UBSFbf9ZSnF2OhVFeRze8l++W/I8hcd+xWQyoXo8WP39KS4u+a3D+KmBI7HnIJz2Cg6v/xg/dxnbt29nyZIlxMTEADBq1Chyc3NZsGABqampZGRksGTJEqZPn86xY/XvWi6EODNZRiVEK3ffffcxbdo0BgwYQFJSkq/LEUKcZ3r16sXUqVNZtWoVb7/9Nnq9nsTERGbOnElYWBiTJ0/mrbfeYu7cuTgcDtq2bcsLz83mjR1VFFc6TxrLaLEyYMwM9q77N5tWzMfjcWMNi+bia+4iPLETZUcOU1HiQNFoSEpK4lhWLkePppKYmHjSOP4hkfS67l72rFvFy7P/SkhwEMOGDeO2224DIC4ujtmzZ7N06VIeeughAJKSknj66aeJj49HCOE9ivrHrxV+c/z4cYYNG8batWuJjY1t7rqEEM1o/fr1rFixgpdeeumk01mE78ln8ZnJe3N++25/HovWHyXM31jn52RlZeF0OmsDgdvt5tChQ+h0Otq3b4ei/L5go6DcwRVdI7ljQILXaxdC/O5cn8WyjEoIwaBBg4iOjmbFihW+LkUI0Ur0bReC1aSjsspV5+eYzWZstt83m2u1WpKTk/F4PBw69GttQz6n24NGURjZ5cwnUgkhmoeEDSEEiqIwZcoUvvzySzljXgjRLMwGLZMva0eFw4Xn9IssTmGxWKistJ30mEajISmpA1qtlgMHDuByuSiudDK6dyxRgXU7clcI0XQkbAghAAgJCeGee+7hpZdewuWq+zeNQgjRUD3jgxicHE5+ueOUzeKnYzDo8ageXK6T93ooioZ27dphNpvZdfAoCcEGrrpIZjWEaAkkbAghag0dOpTQ0FA+/vhjX5cihGglJgxKpEdcEPnlVXWY4VAwm82nzG7UsIZHExlgoHjDEkpLir1frBCi3iRsCCFqKYrC1KlTWb16Nampqb4uRwjRCuh1Gh4amcTApFDyy6uwVbnPer3FbMFmOzlsVLk85JU5SIrw5637r+TyQf3561//Sm5ublOWLoSoAwkbQoiThIWFceeddzJv3jzc7rP/pS+EEN6g12mYMrQdD1/RARWV/HIHlVXu0y6tqp7ZqN4k7nC6f7vWxd0DE3hiVGcCzAZGjx7NqFGjePTRRzl+/HhzvxwhxAkkbAghTjF8+HCsViuffPKJr0sRQrQSiqJwSWII88Z25+5LEzAbNBRVOikor6Kg3EGJzUmJzYlLY6TE7qaoogqPCn++uA0vjenOFV2j0GiU2vFGjRrFuHHjeOyxx+TgCyF8SJr6CSFOoSgK999/Pw888AD9+vUjLi7O1yUJIVoJP6OOEV0iGZ4SQXqhjeOFNn7NLae40olHVTEo/vzn/dU8ef8VJIRa0GvP/L3psGHDMJvNPPHEE/z973+nc+fOzfhKhBAgYUMIcQbh4eGMGzeOefPmMXfuXDQamQgVQjQfRVFICLWQEGrh0qTQk362eVkuAVSi1/qfc5wBAwZgMpmYPXs2jzzyCD169GiqkoUQpyH/ehBCnNGVV16J0Whk1apVvi5FCCFqJSYmkpaWVufre/XqxWOPPcY//vEPNm3a1ISVCSH+SMKGEOKMapZTffTRR2RkZPi6HCGEACAhIaHeJ+Z16dKFWbNmsXDhQr799tumKUwIcQoJG0KIs4qKimLs2LHMmzcPj8fj63KEEIKEhIR6zWzUaN++Pc8++yxLly7l888/b4LKhBB/JGFDCHFO11xzDRqNhs8++8zXpQghRL2XUZ0oLi6OOXPm8K9//YuPPvrIy5UJIf5IwoYQ4pwURWH69OmsWLGCrKwsX5cjhGjl4uLiyMzMxOVyNej5kZGRzJkzh2+//ZYlS5actp+HEMI7JGwIIeokJiaG0aNHM3/+fPmLWQjhUwaDgfDwcDIzMxs8RmhoKHPmzGH79u289tpr8rkmRBORsCGEqLNrr70Wl8sla52FED7XkE3ifxQQEMCzzz5LWloa//znP3G73d4pTghRS8KGEKLONBoNM2bM4L333iMnJ8fX5QghWrGGbhL/I4vFwqxZsygtLeX555+nqqrKC9UJIWpI2BBC1EtsbCw33ngjL7/8siw7EEL4TGM2if+R0Wjk8ccfR6fT8cwzz2C3270yrhBCwoYQogFuuOEGKisrWbNmja9LEUK0Ut5YRnUinU7HI488QlhYGDNnzqSiosJrYwvRmknYEELUm1arZcaMGbz77rvk5eX5uhwhRCsUHR1NUVGRV2chtFot06dPJzk5mb/97W+UlJR4bWwhWisJG0KIBklISODaa6/llVdekeVUQohmp9FoiIuL89pSqhqKojBhwgT69u3Lo48+Sn5+vlfHF6K1kbAhhGiwm266ieLiYtauXevrUoQQrVBCQgLp6eleH1dRFG677TauuOIKHn300UYdsStEaydhQwjRYDqdjgceeIB33nmHgoICX5cjhGhlEhMTvbpv449uuOEGbr75Zv72t7816X2EuJBJ2BBCNErbtm256qqrWLBggSynEkI0q/j4+CYPAVdeeSXjx4/n8ccf5+DBg016LyEuRBI2hBCNdsstt5CXl8d3333n61KEEK2IN4+/PZvBgwczY8YMnn76aXbu3Nnk9xPiQiJhQwjRaDqdjhkzZrB48WKKiop8XY4QopUICQnB7XY3y6lRvXv35i9/+QsvvPACW7ZsafL7CXGhkLAhhPCKDh06MHLkSBYuXCjLqYQQzUJRFK91Eq+Lbt268cQTTzBv3jzWr1/fLPcU4nwnYUMI4TVjxozh+PHjfP/9974uRQjRSni7ud+5dOzYkdmzZ7N48WJpbCpEHUjYEEJ4jcFgYMaMGSxatEiaYQkhmkVzhw2o3ivy/PPP8+GHH/Kvf/2rWe8txPlGwoYQwqs6duzI0KFDee2113xdihCiFUhMTGySXhvnEhMTwwsvvMCaNWt47733Grx8tMrpoqC4nJyCUgpLKnC53F6uVAjf0vm6ACHEhWfcuHFMnz6dH374gQEDBvi6HCHEBaxmz4aqqiiK0qz3DgsL44UXXmDmzJlUVlYyYcKEc9ZQ5XSxafsRNu9KZfv+Y6RlFqAoCgpKbWBpGxtGj05x9O3elr4XJaLTaZvj5QjRJCRsCCG8rmY51Zw5c7jooouwWq2+LkmI/2/vzsOjqu7Hj7/v7JPJzGQne0IIhEAgAUQUAQXUIioPahG/ouCKVkHE+lW+rbVqrT+rlr0oWKQqFRdwRYsLUgEBBSRAIGFPQkJ2si+z3t8fSDQCsmUyIfm8nofnITP3nvO5gZm5nznnc47ooCwWC4GBgZSWltKlS5c2799ut/Pcc8/x9NNPM3fuXKZOnYpGc+LEkfLKOj76OpN3/7OV+iYHiqIQYDIQHhzY4niP10tJRQ3vf/UDH3y1DWugif8ZPZAxw9OxW81teWlCtAqZRiWE8InU1FSGDBnCokWLTnhOVVWqm1yU1DooqXVQ53DLClZCiHPmj7qNnwsMDOQvf/kLZWVlvPjii7jd7ubnVFXlyw27ueX3r7J4xbfodBq6hNqICLESGGA8ITHRajQEBhiPHRNqBVXllbfXcvMji1i3ZZ+8V4oLjiQbQgifuf3229mzZw/ff/89XlXlYEUD720vZta6PBZuKuDNrUd4Y+sR/rHhMHPW5/PxrlIOVzXJh6kQ4qy05fK3p2IymXjyySdxuVw8++yzOBwOauubeHzm+zw5/xP0ei1R4XZMRv1ZtWs2GYgMt6Eo8NjfV/DUP1bS5HD56CqEaH0yjUoI4TMmk4mpU6cy69U36O8Mp94FGgXMei1m/U/zmlVVxaNCTlk9OaX1RAQauK5XOGEWgx+jF0JcKBITE9myZYu/w8BgMDBjxgzmzp3LjD88SZm2O4cKjxIZZkNznvUkFrMRs1HPlxt2U1JRw98f+y0Ws7GVIhfCd2RkQwjhM6qqUhEQQ/CQ33Io/wg2k45Aow6tpuWHrqIo6DQKVqOOQKOW8nonr20u5IfCGj9FLoS4kPh7GtXP6XQ6Jt//AJvzdazdmEmIzXzeicZxGo2GyDAbO/cW8thLK3A4ZYRDtH+SbAghfEJVVb7cV8Gm/GoSoyKor6mkuur0e28oioLFqMOs1/LFnnK+Pyz7dQghfl1sbCzFxcUtaiX8acGyb/DqbXQJs7FnTw5Op7PV2lYUhS6hVrZlH2bJBxtarV0hfEWSDSGET2wvquWHghqsRi06nY6uXbuSm3sIzxneDOg0x5KONfuPklfZ6ONohRAXMoPBQEREBAUFBf4OhS278vhwdSYRoVbi4+MJDQ0lOzubpiZHq/WhKArhwYEs/fg7dh8oarV2hfAFSTaEEK2uusnF6n1HCTBom6cP2Gw27EFB5B8+fMbt6DQKBq3CJ7vL+N/HZ/DEE0/4KmQhxAWuPRSJO11u/vLyp1jMRrQ/rjIVHR1NZGQkOTnZNDa23hcnOp0Wg0HHMwtW4vV6W61dIVqbJBtCiFa3Ma8at9eLXtvyLSYuLo6a6mpqqs98apRJr6XO6aasrvWmIQghOp7ExES/Jxsbth2goqqOfZveY3/m182Pd+nShdjYWHJycqivr2+1/oJtARSUVLJ1d9vvoC7EmZJkQwjRqppcHrKKarEYTlzsTqvVkti1K4dyc/F4PGfcplmn5UiNQ5bEFUKcUnsoEv/3yu8x6k++0GdYWBgJCYns2bOX2traVutTq9Hwzn/8vxKXEKciS98KIVrV9gOH+XrZK5QdzMHlcmINDiV96NX0vnQ4AP9+9mF6XvYb/pO5gbJDOXg8LmKSenLFuDswB9oAKD+SzzfLX6e86DAWWxAXXXk9Lq+XBueZJyhCiM7F39OoDhdXkn2wiIgQ6ymPCQkJRqvVsG/fPrp164bdbj/vfkPsAWzafpCKqjpCgwLPuz0hWpskG0KIVjVn1kyqy2sZc9//YjRbyN+bxdr338AaHEp8z74AFOVswxgWw1WTpuJ1NLDqjX+w+cuPGHbD7Xjcbv6zZC7mQBs3PvgHFI2G7z//gKrSIurD5YNUCHFykZGRVFdX09DQQEBAQJv3vze3GAUF5RfL3NZXl5GXvYnao8WoqheLLYwusb05cOAgoTY9hbvX0mfojViDI5vPqa0sYee6FaRech3BEfHUHC3icM731NeUg6piD4+ja9oQDCYLGo0GjUbDvrxSSTZEuyTTqIQQrWr4LZNmIw9AAAAgAElEQVQZdcc0wmISsIaE0fuSKwgMCuXw3l3Nx9hCwrnytxM5WlNPbPfeRCelUJp/CIAjB3Korapg6NgJhMcmEhYdz8hb7sXV1EiDU4oghRAnp9FoiIuLIz/fP/ULu/YXnTDV09lUz64NH6HR6ki7bCx9h43DbA0mf9d/iYsKo6LGiUdVOFp0qMV5FUUH0BvNBIXH0lBbye6NH6PTG0kbPJbUQdfhaKhh96aVqOqx90S328O+vNI2u1YhzoaMbAghWlWT08mWVe9Tlr8fR0MdqqridjlxNP5UFBkel0hQUBDVVVUUFBZiDrRRXV4CwNGSIwCERsc1H280BxAUEY1XajaEEL/i+FSqnj17tnnfO/cWYjYbWjxWmp+D1+shOWMkOv2x57qlD6eqrICa0gOkpg5ic3E2BQd3kdDr0ubzjhYdJDQ6GUXRUHRoB1qdge79r0Kj1QKQnDGCzP++Q2VpPiFdEjEZ9ezY4/9lf4U4GUk2hBCtprGxkeXz/x8urYmhY2/DHhaBRqNh5at/b3Hc8Q/d2NhYdmZl4XD8tP68y9F0bEdxfcsPbZ3BcMLO40II8XP+XJGqtr4J3S9W4KurLiXAGtLi/UxRFALtYdRXl2M2m+nV7zK2rH6b/XuySOzWE0d9JU31NYTHdD/WRmUJ1pDI5kQDIMAWis5gpKG6nJAuiei0Gmrqm3x+jVUNLvKPNpB/tIGjDS5UFQKNOuJDzMQGm4m0GU+YRiaEJBtCiFazc+dO3A21XHLbvST2TG1+vKnh5Es9anU6uiZ2ZefXH6P8OGqhMxibR0N+/gHtbGwkwHD+xZRCiI4rISGB77//3i99e1WVX95me9xOtDrDCcdqdQY87ioAQiMTCLQFU3hwF1W1DlzVeXjQohisqCp43C4qS/L47rNXW7btceF0NPz0s9c3I79ur8qOgmo+21nMgbJ6NIqCx6vy4zYieLw0fxEUHKBndJ9ILukajMUot5jiGPmfIIRoNW63G6NOgznwp9VYcndvx9HUwKlmQNmD7JhNJsorigEICj9WJFl6+BDRSSkA1FYdpbqsCEuPGN9egBDignZ8+VtVVdv8G3aTUU91bctN+3Q6I02NNScc63Y70f74ZYqqqqh6O2adk/79+7H5i51YQmI5dOggLpebuvoGLNZQevQbjk6v/0X7x9rwqirmkyw3fr7yjzawcG0uR6oa0WkVggP0p/y9qqpKo9PD0k35rPihkDsHx3NRQrCMdAgpEBdCtJ7k5GQsRh05G77iaHkp+7d/z9bVnxCV2J3KkkLqqo6e9Lyg4GCcLhdVVVXEdk8lINDGxk/fo7wwj/LCPFa/8xpWux2zXt6yhBCnFhwcDEBVVVWb990tNpwmh6vFY5agcBprK3G7fpoqqnq91FeVEhgUAUBxcTH2Lom4G2upqTiCx9lAz76X0KdPH3r37oU9NIraqnL27M/lYG4BFZW1uL1avB43OoMJgCaHi+6JXVrtWlRVZVVWCU99kkNprYPgAD0206kTDTg2Pcxs0BJiMaAA89cc4pVvDuF0y8IenZ18cgshWk1ERARTp0yhPj+bt196guzv1nLVhPvoM+RKKkuLWPX6/JOep9Eo2KzWYxtyKRquueMhvB43K+Y9y39en09srwEMSEuVb8iEEL9KURS/7beR3jMWt6fljXWX+F5otDr2bv2S+poKGmoq2J/5NW6Xg8jEPjidToqLi+memoHBHEje7m8JsIUSYAsFwGg00r3vYEwGDUG6WsKCLDgaatixaRVrP36V7KxtlJWV4XF76J0c1SrXoaoqH2YWsWxzAYFGLTaT7qzfe016LaEWPd8dqmT26v2ScHRyMo1KCNGqrr76ai67YiSvfndsZRSjToMtJJzk9ItPec6I8fcAkJ+fT15eHt26dWPcw08B0OD0EGjUctfA29Br5fsRIcSvO14knpGR0ab9JseHn7CIhd5opvfgseTu+pad61YAKoFBXeh16RgCrMEcOHCAiIgIzGYTYdHJHDmQSULqJS3aCLCG0OuSMeTnbKK88HMA7EERpIy8BVVnoaqqivLKOt5Y/A8K9gykf//+pKamotOd2y3etweO8mFmEUEBenTnsSiHoiiEWPTsPlLLkg15TB6aKF8YdVKSbAghWp3FoOWalFA+yCpFp1HOeBWp2NhYdmVlcfToUUJCQnB5vHhUlet7RUiiIYQ4IwkJCezZs6fN++3ZNZLAACONTU4GXHl78+MWWyi9Lx1zwvG1tbXU1taSmJgIQGLvwST2HnzStm2hUaRddsNJnzNbbHTvbuTx+4axbds2lixZwpEjR+jTpw8DBgygf//+REREnNE1VNQ5eWNjPlaT7rwSjeMURSHYomfjgaMM6hpMRlzQebcpLjzy6S2E8ImUiECGJQVT53DjPsNVUjQaDV2TksjLy6OhyUmDy8O1PcOIthl9HK0QoqPw1zQqnU7LLaMHUl13+iVoVVUlLy+PuLg4tD9b0vZc1DU4uO36QfTq1YsJEyYwc+ZMFi5cyODBg9m1axfTp0/ngQce4J///Cfbtm3D6XSesq03N+Xj9nox6k5/e5i9/lM+euGh0x6nURQCDFr+uT6PJpfnrK5NdAwysiGE8JlLE4Iw6rR8vb8CODbicbphdIvFQlB4FIcLj/C7q/uREhHYFqEKITqIhIQEDh8+7JcVqa4ZmsY/l6/H5fag1506iSgrK0Or1RISEnpe/TmcbvQ6LVdemtricbvdzvDhwxk+fDiqqrJ//362bt3KsmXLyM3NpXfv3gwYMIABAwYQFXWs1qOkpontBdUEB+hP1tV5MRu0HK13sTWvisuSz++axYVHkg0hhM8oisKAWBsJwSb+k1NOUc2xFVmMOg16rdJ8I+BVVVweFYfbiwJc1D2GtW/MpjDaRcqIEX68AiHEhSYgIACr1UpxcXHzjXRbCQ+xcucNg/nn8m/pEmY9abLjdrspKCikZ88UzicXUlWViqp6fn/HlVgtplMepygK3bt3p3v37txyyy3U1dWRmZnJ1q1bee+99zAajQwYMIDasD541V9fcep8GHUKn2WVMLhbiNRudDKSbAghfC7MYuC2/lGU1jnZfqSW3MpGKhvdP33QqhBq0ZMebSU9ykpIgJ6LbPfz5JNP0rdvX8LCwvwavxDiwnK8SLytkw2ACdcPYvWmHApLqggJspzwfGFhISEhwQQEBJxXP+WVdfTtEcMNV/Y7q/MCAwMZMmQIQ4YMQVVVcnNz2bp1Kx/vLqSuwUGFxYTdbicoKAiT6dRJzNkKMGg5UtVIdaObIB+Mnoj2S5INIUSbUBSFLlYjV6ccq79webw0/TiSYdJrTyhGTEpK4vrrr2fOnDk888wz8k2YEOKMHd/c75JLLjn9wa3MoNfx1IPXc++fl1LX4CAw4Keas4aGBioqjtK3b5/z6qOmrhGjQc8Tv7sW7XksnqEoCl27diUyJp6VdZkkGzXU1dVRVVXVXGRvt9ux2+3YbLbzqi9RFAWNRqGgqlGSjU5GCsSFEH6h12qwGnUEGk+96slvf/tb6uvrWbVqVRtHJ4S4kPmrSPy45IQIXvrfm2hyuKitP1YwrqqQl5dPTEzMOS9LC1Bd24jHqzL7/24mLjK4VeItrmlCqyjodDqCgoJITEwkPT2dlJQUzGYzpaWlZGZmkpOTQ1FREY2NDefUj9vjpaj69AX0omORZEMI0W5ptVqmT5/Om2++SVFRkb/DEUJcII5Po/KnAb0TmPvHW/CqKqVHazl6tAKPx01ERPg5tedVVUoqatDpNCz40630To5utVgdbi+c5Dsfk8lEly5dSElJoV+/fkRFReFyudi3b/+xVQMbGqmoqMDlcp148kkpNDhlRarORpINIUS7FhcXx80338ycOXPwemUXWiHE6cXExFBSUnIWN8G+kZ4Sy1sv3kO/nrHsPVhAeJfos54SqqoqdQ1NlJTXMHRAd9568R56JkW2apyaM4hJo9Fgt9uJj4+nb9++xETHoNVqqKysZOfOnWRlZZGfn091dfWvvFerrbJ/h7iwSM2GEKLdGzNmDJs2beLjjz9m7Nix/g5HCNHO6fV6unTpQkFBAV27dvVrLBEhVi5O8NBwcSRlrqBjoxNaDXZrALpfqbdwuz1U1jTgVVUiw+z8373XcPnAHj6pX7OadKhnth1SM51eh9FoJDk5GYD6+npqamooKipi//79WCwWbDYbNpuNwEALoKBRFGwmufXsbORfXAjR7mk0GqZNm8bvf/97BgwYQFxcnL9DEkK0c8eLxP2dbJSUlPDZZ58xd+5cgoND2Lo7n3dXbWFLVh6eH0cAPB4VFRUFBZ1WQVWPbRI4ZEAy435zERk9Y326SEaE1YhGAY9XRXuOIw8WiwWLxUJUVBRer5fa2lpqamrIy8vD4XBgtVrRWezoncGoaqgs+tGJSLIhhLggREVFcfvttzNr1ixefPHF8951VwjRsSUmJpKfn+/vMFi8eDFjx45tXsL74j6JXNwnEa/XS0FJFYcKyqmsacDt8aLXaQmxBZAUH050uL3Nbsi1GoWuoRbyKxsINJ7/reHxKVd2ux04trdIVXUN5dX1vPz351ioekhPTycjI4P09HSCg1un0L01eLwqDU4PXlQMWg0mnUYSo/MkyYYQ4oIxatQoNmzYwPLlyxk/fry/wxFCtGOJiYl+X8kuMzOTQ4cO8eijj57wnEajIT4qhPioED9EdqLhPcN4dV0eGE9/7NnS6XRozFbG9Ipn8mOvcuTIEbZv386GDRt45ZVXCA8Pb04+0tLSWnV/jzPR5PaQe7SB/eUNVDe5UBQFBfCiotdoiLQaSQkPJCLQIInHOZBkQwhxwVAUhWnTpvHwww8zcOBAkpKS/B2SEKKdio+PJzc312/9u91uFi1axD333IPBYPBbHGdqQEIwr2/Mx+n2YtCdfv2g1CHXkjrk2jNqW1VVVFXlytQIFEUhJiaGmJgYRo8ejcfjYf/+/Wzfvp3333+fv/3tbyQnJ5Oenk6/fv1ITk722Ui2V1XZW1bPtsJqvKqKXqshQK9tkVB4vCoF1U0crmokJMDA4MRg7CbZJ+RsSLIhhLighIWFcddddzFr1ixmzpyJXi9v+kKIE0VGRlJXV0d9fT0Wy4k7efvap59+SlhYGBdffHGb930ujDoNN/aL5q3vCwi16Fv1G/yqRjd9Y2wkhZ24a7pWqyUlJYWUlBRuvvlmmpqa2LVrF9u3b2f+/PmUlZWRlpZGv379yMjIIDr67Ff0OhmXx8s3BysornVg1mlPWaui1SgEaLSoqkplo4tPs0u5LCGYhJDz2wG+M5FkQwhxwRk+fDgbNmxg2bJlTJw40d/hCCHaIUVRiIuLIz8/n9TU1Dbtu7q6mnfffZfnn3/+gpp2c2VqBN8dqiSvoqHVdvlucnnQaxXuGJxwRr8Lk8nEgAEDGDBgAABVVVXs2LGDbdu2sXz5cgAyMjKa6z2CgoLOOiaPV2XN/grK6h1YfjGScSqKohCg1+L2elmfexSNBuKCJOE4E5JsCCEuOIqiMGXKFKZOncqgQYNISUnxd0hCiHbo+OZ+bZ1svP7664wYMeKCWzlPq1G4f1hXnl6ZTW2TG+t5LlPrcHupd3p4aEQSIZZzm0oWFBTEsGHDGDZsGKqqcuTIETIzM1m/fj0vv/wy4eHhzclH7969MZlM3H333aSnp/PQQw+dtM2dxTWUnkWi8XM6jQZVC9/mVjKml5EAgyxWcjqSbAghLkhBQUHcf//9zJo1izlz5mA0+qCqUQhxQTu+/G1b2rdvH1u2bOHll19u035bS4TNyIxrUnh+1V6qGlzYzbpzGp2pd7hxuL3cN6wr/eNbZ7Wpn9d7XHvttc31HpmZmSxfvpznn3+e5ORkDh48SGRkJB6P54R6j6pGF7tLak+ozTgbeq0Gl9PN94eruKJbaGtcWocmyYYQ4oJ12WWXsWHDBt544w3uvfdef4cjhGhnEhIS2LRpU5v1p6oqCxcuZOLEiX6pE2ktccFmnrquJ4vW5bK3pA6rSYfxDIrGAdxelZpGF3aznoevTKZnpNVncf683mP8+PHN9R7r169n3bp1TJgwgT59+tCvXz/S09OJjo4mp6wOVT2zXdN/jVmvpbC6kVqHG2srLBfckclvRwhxQbv//vuZMmUKgwYNom/fvv4ORwjRjhyfRqWqapvUTqxZswZVVRk5cqTP+/K1cKuR/7umB2v2lPP+D0c4Wu9Cq4EAgxadRjlhxaZGlwen24tGo3BlagQ39Itu8ylGx+s9evToQXp6Orfffjs7duzg66+/5sEHHyQuLg59ZBKh4eGkZlzExs8/oba6kvCoWEaNn0R0wrEVDr1eL99+/jHbN66lrroSc6CVlL4DGDF2PAajiTl/fIj+Q0bQf+R15B1tIMbkYeLEiQwZMoTHH3+8OZ6JEycyduxYbrzxxjb9PbQ3Z5amCiFEO2W1WpkyZQpz5syhsbHR3+EIIdqRoKAgNBoNlZWVPu+roaGB119/nfvuu++CKgr/NRpFYWTPcOaM78OU4Un0jrbh8UJlg4uqRhfVjS4qG1zUOz3EBQcwYVAcc27uy4RBce2iliE4OJiMjAwKCgqYOnUqC1//Nzqdjrx9e1j3xWf0uXwUV/3P3dTV1vDxm4uaz/vvJ8vZ+OWnDB8zjslPPM814+8gJ3Mzn/x4TGKPXhQc3IdOo6Go1kFWVhZhYWHs3r27uY3CwkIqKyvJyMho8+tub2RkQwhxwRs4cCAbN25k8eLFTJkyxd/hCCHakYSEBPLy8ggJ8e3mee+88w79+/enR48ePu3HH3RaDQMSghiQEISqqtQ0ualzuPGqYNJpCA00nPe0JF9wOp385S9/ITo6moceeojCWidGowmDVsN9jz+Fy+2huqaaqG49+f6rT8nauQO73c6m1f/h0itH0/uiSwEICe9CXU0Vq955ndrqSrqm9OaL5UvRKsdqQMp27uSKK65g5cqVFBUVERUVxa5du7Db7XTt2tXPvwX/k5ENIUSHcM8997Bt2za2bt3q71CEEO1IWxSJFxYW8tVXXzFp0iSf9tMeKIqC3awnJshMXLCZcKuxXSYaALNnz8bhcPCHP/wBnU6H26sCEBoZjdFkJjAwkJjoGHqkpGK32wmyWSkvKaKmugqHqmHfvn2UlJTQ2NRIVEISqqpSUpBHYkovHE2NlB05jNurkpWVRe/evenRo0fz6EZWVhbp6ekdZpTrfEiyIYToEAICApg2bRrz58+nrq7O3+EIIdqJ4yMbvqKqKq+++irjxo07pz0fhG98++23rF+/npqaGtxuNwC6Hzfu0+tbLsOrKMdqUGw2G2EhwVitVpJ79CA4JIT6hnr25Oxh34EDNDQ0UFpcjMliJSQiksMH9uKor6WwsJDU1FR69erFrl27ANi1axf9+vVr24tupyTZEEJ0GH379uXSSy9l0aJFpz9YCNEpHC8S95UtW7ZQUlLCdddd57M+xNkLCgpi7ty5aLVa5s+fD3Bs1ajTDDQYTcc26vO63YSFhpLUNYn0jHQSYmPRarU43R6ysrLQB9rZuW0LB7Z/T0xMDBaLhV69erF7927Ky8spLS2Veo0fSbIhhOhQJk2axJ49e9iwYYO/QxFCtAPx8fEcPnwYr9fb6m07nU5effVVJk+ejE4nZbDtSe/evUlMTGT69Ols3LiRr776CrtJjwKov3JeaJcoDEYTBQf3NT+moFB25DAmk4mBlw6hX/9+XHTZMMoL89n+7Rq+++47HnnkEbZs2UJOTg5r1qwhNjaWsLAwn1/nhUCSDSFEh2I0Gnn44Yd55ZVXqK6u9nc4Qgg/M5vN2O12iouLW73tjz76iPj4eJku04716dOHsWPHsmjRIspKS7Cb9Lh/JfHU6nQMvOJqtnzzJTu+W09leSk5mZtZ9+n79Ln4Miw2OwoKKWn9cTbVY9N5mTlzJnfddRcBAQHU1tby2GOPkZeXx7vvvsuePXvweDxteMXtj6ThQogOJzU1lREjRrBgwQJmzJghBXpCdHKJiYnk5uYSHR3dam2Wl5fzwQcfMHPmzFZrU/jG7bffzrZt25g5cybBZi01Ti9eVT1lYfvl192EVqfjm5UrqKuuJNAWRN9LhnH5dTc1H+PVG0lK6kZ1WQHp6ekEBQWRlpZGfX09H374IePGjaOmpoZ58+ZRXl5OWloa6enpZGRkEBsb26k+lyTZEEJ0SLfeeivTp0/nm2++4YorrvB3OEIIPzpeJD548OBWa/Nf//oX11xzDZGRka3WpmgdixcvbvGzXq9n3rx5zT9vK6xmV3EtFoMWRVHoe8lQ+l4ytPl5RVEYes1Yhl4z9qTtuz1etBqFf70yD4uh5a305MmTmTx5covHqqqq2LFjB5mZmXz44Ye43W7S09Ob/5zpdKvVq1cze/Zs/v3vf2Oz2U56zFtvvcU777zDRx99dEZttgVJNoQQHZLBYGD69Ok89dRT9OnTh9DQUH+HJITwk8TExFat49q9eze7du2SfX0uUH2irJTWOSivdxKg157VKIPb66XJ42VY15ATEo1TCQoKYtiwYQwbNgxVVSkuLmb79u1s2bKFxYsXY7PZmhOPvn37EhgY2Hzu8uXLKSgo4OGHHz6jvm688UZGjx59xtfTFiTZEEJ0WMnJyVx77bXMmzePP//5z51q2FoI8ZOEhATeeuutVmnL6/WycOFC7rzzTkwmU6u0KdqWTqNheLcw/nuwgtI6B2adFq3m1z8fVFWlye1FBYYkhhAfHHBOfSuKQlRUFFFRUYwaNQpVVTl06BDbt2/niy++YPbs2cTExJCRkUF6enrz5oBnymQytbv/l5JsCCE6tHHjxvHoo4/yxRdf8Jvf/Mbf4Qgh/CAmJoaysjKcTicGg+H0J/yKL774ArPZzNChQ09/sGi3DDoNV3YPI6e0jswjNXjdKgatBr1GafHFlNer4vAcq/EIMuu5LDGEILO+1eJQFIWkpCSSkpK44YYbcLvd5OTksH37du6//37y8/OxWCy8+eabTJ06FVVVKSsr429/+xs5OTkEBAQwYcIERo0aBZw4jWr79u0sXbq0efnnpKQkJk2aRGpqaqtdw+nIalRCiA5Np9PxyCOP8MYbb1BSUuLvcIQQfqDT6YiKiqKgoOC82qmtrWXp0qVMnjxZRko7AI2i0KuLlRvSIukfY8ek09Dg8tD4458GpweX10uUzcSI5DBG94xo1UTjZHQ6HWlpaUyYMIEvv/ySUaNG8Zvf/IaJEyfy/vvvs23bNu6++27CwsKYMWMG6enpLFiwgNLS0hPaqqur49lnnyUlJYU5c+Ywc+ZMYmNjefrpp2lqavLpdbS4pjbrSQgh/CQ+Pp6bbrqJ2bNn89xzz8lNghCdUEJCArm5uSQlJZ1zG2+99RaXXXbZebUh2h+zXkuvLlZ6dbHi9nqpd3jwAgatctY1Ha3JarViMBhITk5m2rRppKWl8eKLL3LttdcC8Morr1BVVcX+/ftZtmwZEyZMaHH+kSNHaGpq4vLLLycqKgqA++67j5EjR6LVatvsOiTZEEJ0CmPHjmXTpk188sknjBkzxt/hCCHa2PEVqc5Vbm4u69at4+WXX27FqER7o9NosJvb78QfvV7PTTfd1LyMc3Z2NnfeeSe7du3i888/b5EYxcfHExERwfPPP8/o0aPp168fXbt2bdMpVCDTqIQQnYRGo2H69Om8/fbbFBYW+jscIUQbS0xMPOdkQ1VVFi1axK233orVam3lyIQ4Oz+vO4qMjCQ8PJzx48efMLJhMpl44YUXGDRoECtXrmTatGncc889rF+/vk3jlWRDCNFpREVFMWHCBGbNmtXpd3QVorM5Po3qXHz77bfU1dU1F+EKcaEIDQ1l8uTJLFmyhLlz59KjRw9eeOEFDh8+3GYxSLIhhOhURo8ejclk4v333/d3KEKINhQREUF9fT11dXVndZ7D4eC1115j8uTJaDRy2yTanqqq53ReUVERmzdvbv65a9euPPjgg6iqKsmGEEL4iqIoTJs2jQ8//PCcv+UUQlx4FEU5p7qN5cuXk5qaSlpamo8iE+LUAgMDOXjwIAcPHqSysvKszi0qKuKvf/0rK1eupLi4mKKiIlasWIHBYKBHjx4+ivhEkmwIITqd8PBw7rzzTmbOnInb7fZ3OEKINnK2yUZJSQmffvopd955pw+jEuLUbrzxRioqKnjsscfOemStf//+PPjgg6xatYoHH3yQ6dOnk52dzZ/+9CfCwsJ8FPGJZDUqIUSnNHLkSDZs2MDbb7/Nbbfd5u9whBBt4GyLxF977TXGjh3bpjdmQvzc4MGDGTx4cPPPN954Y4vng4OD+eSTT5p/vvXWW7n11lubf77qqqu46qqrfB/or5CRDSFEp6QoClOmTGHVqlXs3bvX3+EIIdrA2RSJZ2ZmcvDgQcaOHevboITo4CTZEEJ0WiEhIdx3333MmjULp9Pp73CEED52fBrV6Qpu3W43ixYt4p577mmxzKgQ4uxJsiGE6NSGDh1KYmIib775pr9DEUL4mN1uR6fTUVFR8avHffrpp4SFhXHxxRe3UWRCdFySbAghOr3f/e53rF27lqysLH+HIoTwsdPVbVRXV/Puu+9y7733ttiNWQhxbiTZEEJ0ejabjQceeIDZs2fT1NTk73CEED50umTj9ddfZ8SIEcTFxbVhVEJ0XJJsCCEEMGjQINLS0njttdf8HYoQwod+rUh83759bNmyhVtuuaVtgxKiA5NkQwghfnTvvfeyefNmfvjhB3+HIoTwAa9XpUt8MqbwBPaW1LO/tJ7DlY00OD2oqsrChQuZOHEiFovF36EK0WFIsiGEED+yWCxMmzaNefPmUV9f7+9whBCtxO3xUlDZSGZBDU2GIIK6xFHb6KK60UVJtYPdR2pZs20/wV1iGTFihL/DFaJDkWRDCNFpzZ49m8mTJ7d4LCMjg4svvgq3WJcAAAlcSURBVJhFixb5KSohRGs4/vp2uDzsLqqjqNqBRgGTXovX7cTjdqLXajDoNGjwUlJRyeVjbqGgynHapXGFEGdOkg0hhPiFO++8k+zsbDZt2uTvUIQQ58HjVckprsfp8WLUadD8uLqU2WymobGx+biioiI+fGsxu3/4npIaB4VVslCEEK1Fkg0hhPgFk8nEww8/zIIFC6iurvZ3OEKIc1TncOPyeDFoW97umM1mGhsaAGhqaqKsrIyq8jIUBQxahaJqB7VNbn+ELESHo/N3AEII0RZKS0uZN28eu3fvJjAwkOuvv77F8/X19SxZsoRt27ZRVVVFbGws8fHxLFiwgBkzZqAoChUVFSxevJjdu3dTW1tLt27duOuuu+jZsycAq1evZvbs2cycOZOXX36Z3Nxc7HY748ePZ9SoUf64bCE6hZO9vt0eFadbRa9VKDycxyfLl3FgbzYejwdbUAgXDb6cmJibyM/P55UXn8FoMrJ08cssXfwyf//nMgqO1rNx1QrWrl1LdXU1QUFBDB48mEmTJsmu4kKcBUk2hBCdwgsvvEBVVRXPPPMMNpuNDz74gK1bt2I2mwF47rnnOHLkCA888ADR0dF8+eWXrFixgsDAQNatW8fgwYP54x//iE6n49FHH8Vms7FixQr+9Kc/MW/ePCIjI5v7euWVV5g4cSJhYWF89NFHLFiwgG7dutG9e3d/Xb4QHdrJXt8bv98M2mNJwcLZL9AlKppHnngWg8HIujVfsuLfr5HcIwWXR+XJv83mb39+nJv+ZxL9L74UvUbhvXffZueG1fzfjBnEx8dTUFDAiy++iMFgYNKkSX6+YiEuHDKNSgjR4RUWFrJnzx4mTpxI7969iYuLY8qUKWi1WgD27NnDjh07uO+++xg4cCAxMTHccccdJCcnEx0dzaJFi/j8888pLCzkkUceIS0tjfj4eKZOnUpAQACfffZZi/6uvvpqMjIyiI2NZfLkyRiNRtatW+ePSxeiwzvV69vlVTi+//fUx/7EHfc/RFRMHKHhEVx343i8Hi+b1q8lPiEBm80OgDkgAFtQMIqiMHTEKP781xfp378/YWFhZGRkMHDgQFkaW4izJCMbQogO7/DhwwAkJSU1P6bRaOjevTt5eXns3bsXgL59+7Y4r0+fPmzatIlrrrmGJUuWEBgY2KINnU5Hz549OXjwYIvzUlJSmv+u1+tJSEigrKys1a9LCHHq13dsYldKCgtQFIWGhno+encpeYcO0thQB4DX68XpdGC32aipqjyhXZ1ez1dffcY/Zm6lsrISj8eDy+UiNDS0bS5MiA5Ckg0hRIfX+OOqM0ajscXjx6dQNfxYKPrLqRFutxudTsf48ePJz89n48aNjBs3rsUxLpeLmJiYFo/9ckMwk8lEXV3d+V+IEOIEp3p9G03HXt8V5WXMff4pYuMTmXD3/QSHhKHRaHj2D9OJ+tn0x19a+up8Cg/mMO3B39GjRw8MBgNLly4lJyfHdxcjRAckyYYQosM7fhPicDhaPH48AQgICADg73//O3q9/oTzdTodERERWK1WXnrppROePz4d67imppbLZjY2NhIREXHuFyCEOKVTvb6bfvwSYee2LTidTu56YDr24BAAGurr8Hq9aLUnvw1qaKgne8c2br/9Nq666qrmx3/ZhxDi9KRmQwjR4cXGxgKwb9++5secTifZ2dkA9OjRAzi2IlVUVFTzH61WS3BwcPMxtbW16HS6FscAzccct2vXrua/u1wu8vPzm2MQQrSuU72+j+Tuw6uCx31sCVuL1db8/OaN6wFQabl53/HN/LweDyoqXUKDmp+rqqoiMzNTNvwT4ixJsiGE6PDi4+NJTExk2bJlZGdnk5eXx7x585q/EU1JSSEtLY25c+eSmZlJaWkpGzZs4JFHHuG9994DYNCgQURFRfHCCy+QnZ1NaWkpX331FQ899BBr1qxp0d/nn3/O1q1bKSwsZNGiRTgcDi6//PI2v24hOoNTvb5tlmPTqBKSkgH48tMPqSgv49s1X7F7xzbCwiMoyMulproKc4AFBYV9ObspyM9FozMQFRnF2v+uoaCggOzsbJ555hkuvfRSqqqqyMvLw+Px+POyhbhgyDQqIUSnMGPGDObPn88f/vAHbDYb1157LTabjc2bNwPwxBNP8Nprr/HSSy9RV1dHaGgoY8aMaa7RMBgM/PWvf2Xx4sU8/fTTNDU1ERUVxd13383VV1/doq+JEyeybNky9u/fj91uZ9q0aTKyIYQPner1/eU3G0hITmH02HGs+/oLvl71CT1792Xi5Cl8t/4bVr7/Nu8tfY27H3yEEaOuY+3qVWRt/4FHnnye/33097yxeCHTpk0jOjqau+++m/DwcLKysnj88cdZsGABISEh/r50Ido9RT3FeGBBQQEjR45k9erV8iEphBBn4PimfkuWLCEsLKxV2pT34lOT3404nSaXh+yiOryqil57+skcqqri9KiEBRpIDDWjKMppzxGiszvde7FMoxJCCCFEh2TSa0mJDESjUXB6vL9ab+HxHks0Qix6EiTREKLVyDQqIYQQQnRYAQYtvaKsFFY2cbTBCaqKRlFQFFA5NpqhqqDXaogPMRFhNUiiIUQrkmRDCCFayciRIxk5cqS/wxBC/IJRpyEpPIA4j4mKOidVjW7cHhWNBoxaDWFWAzaTTpIMIXxAkg0hhBBCdAp6rYZIu4lIu78jEaLzkJoNIYQQQgghhE9IsiGEEEIIIYTwCUk2hBBCCCGEED4hyYYQQgghhBDCJyTZEEIIIYQQQviEJBtCCCGEEEIIn5BkQwghhBBCCOETkmwIIYQQQgghfEKSDSGEEEIIIYRPSLIhhBBCCCGE8AlJNoQQQgghhBA+IcmGEEIIIYQQwick2RBCCCGEEEL4hCQbQgghhBBCCJ+QZEMIIYQQQgjhE5JsCCGEEEIIIXxCkg0hhBBCCCGET+hO9YTH4wGguLi4zYIRQgjR0vH34OPvyeIn8jklhBD+d7rPqVMmG2VlZQBMmDDBB2EJIYQ4G2VlZSQkJPg7jHZFPqeEEKL9ONXnlKKqqnqyE5qamsjKyiI8PBytVuvzAIUQQpzI4/FQVlZGWloaJpPJ3+G0K/I5JYQQ/ne6z6lTJhtCCCGEEEIIcT6kQFwIIYQQQgjhE5JsCCGEEEIIIXxCkg0hhBBCCCGET0iyIYQQQgghhPCJ/w+q3bxFkrsKTQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1008x1440 with 6 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QBZ_wVlLlDiu",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 811
        },
        "outputId": "2508fa55-1f4f-4596-9d68-12a5d3d4a78d"
      },
      "source": [
        "\n",
        "pl = nx.planar_layout(G)\n",
        "frl = nx.fruchterman_reingold_layout(G)\n",
        "sl = nx.spectral_layout(G)\n",
        "rl = nx.random_layout(G)\n",
        "sl = nx.shell_layout(G)\n",
        "bl = nx.bipartite_layout(G, G.nodes())\n",
        "cl = nx.circular_layout(G)\n",
        "spl = nx.spring_layout(G)\n",
        "kkl =  nx.kamada_kawai_layout(G)\n",
        "\n",
        "option = {\n",
        "    'font_size':16,\n",
        "     'node_color':list(pr), \n",
        "     'node_size':get_node_size(pr),\n",
        "     'alpha':0.7,\n",
        "     'cmap':plt.cm.Blues\n",
        "}\n",
        "\n",
        "plt.figure(figsize=(15,15))\n",
        "plt.axis('off')\n",
        "\n",
        "plt.subplot(331)\n",
        "plt.title('planar_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=pl, **option)\n",
        "\n",
        "plt.subplot(332)\n",
        "plt.title('fruchterman_reingold_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=frl, **option)\n",
        "\n",
        "plt.subplot(333)\n",
        "plt.title('spectral_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=sl, **option)\n",
        "\n",
        "plt.subplot(334)\n",
        "plt.title('random_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=rl, **option)\n",
        "\n",
        "plt.subplot(335)\n",
        "plt.title('shell_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=sl, **option)\n",
        "\n",
        "plt.subplot(336)\n",
        "plt.title('bipartite_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=bl, **option)\n",
        "\n",
        "plt.subplot(337)\n",
        "plt.title('circular_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=cl, **option)\n",
        "\n",
        "plt.subplot(338)\n",
        "plt.title('spring_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=spl, **option)\n",
        "\n",
        "plt.subplot(339)\n",
        "plt.title('kamada_kawai_layout', fontsize=16)\n",
        "nx.draw_networkx(G, pos=kkl, **option)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 9 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}