sars_cov_2_pubmed_mesh_terms_network_analysis_viz.ipynb

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      "source": [
        "# Sars Cov2 PubMed MeSH Terms Network Graph Analysis & Visualization"
      ],
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        "id": "jeRcPyJHhnwz"
      }
    },
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      "source": [
        "# data handling\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "\n",
        "# plotting\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# netowrk analyis\n",
        "import networkx as nx\n",
        "\n",
        "# miscellaneous\n",
        "from scipy.stats import norm\n",
        "from tqdm import tqdm\n",
        "from operator import itemgetter\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "plt.style.use('fivethirtyeight')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# csv file path\n",
        "file_path =  \"/content/drive/MyDrive/04-Work/EDA-Comparison-21st-Epidemics-PubMed/all-covid-19-pubmed-metadata.csv\"\n",
        "\n",
        "# creating dataframe\n",
        "data = pd.read_csv(file_path)"
      ],
      "metadata": {
        "id": "UMeRjc9gEdQL"
      },
      "execution_count": 2,
      "outputs": []
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        "data.info()"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 204668 entries, 0 to 204667\n",
            "Data columns (total 17 columns):\n",
            " #   Column  Non-Null Count   Dtype \n",
            "---  ------  --------------   ----- \n",
            " 0   PMID    204668 non-null  object\n",
            " 1   TI      204668 non-null  object\n",
            " 2   AB      204668 non-null  object\n",
            " 3   AD      204668 non-null  object\n",
            " 4   FAU     204668 non-null  object\n",
            " 5   DP      204668 non-null  object\n",
            " 6   TA      204668 non-null  object\n",
            " 7   JT      204668 non-null  object\n",
            " 8   LA      204668 non-null  object\n",
            " 9   MH      204668 non-null  object\n",
            " 10  OAB     204668 non-null  object\n",
            " 11  OT      204666 non-null  object\n",
            " 12  PL      204668 non-null  object\n",
            " 13  PST     204668 non-null  object\n",
            " 14  PT      204668 non-null  object\n",
            " 15  RN      204668 non-null  object\n",
            " 16  SI      204668 non-null  object\n",
            "dtypes: object(17)\n",
            "memory usage: 26.5+ MB\n"
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        "data.head(5)"
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              "      <td>Journal Article</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>35051990</td>\n",
              "      <td>Neutralizing antibodies against the SARS-CoV-2...</td>\n",
              "      <td>The recent emergence of the SARS-CoV-2 Omicron...</td>\n",
              "      <td>Howard Hughes Medical Institute, Chevy Chase, ...</td>\n",
              "      <td>Pearson, Claire;Grubaugh, Nathan D;Monteiro, V...</td>\n",
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              "      <td>NONE</td>\n",
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              "      <td>Chen, Chunke;Chan, Karl C K;Lau, Eric H Y;Lam,...</td>\n",
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            "text/plain": [
              "       PMID                                                 TI  ...    RN    SI\n",
              "0  35052023  Does a Mental Health Diagnosis Worsen Outcomes...  ...  NONE  NONE\n",
              "1  35052021  The Opioid Epidemic and the COVID-19 Pandemic:...  ...  NONE  NONE\n",
              "2  35052020  Has COVID-19 Complicated Eating Disorder Treat...  ...  NONE  NONE\n",
              "3  35051990  Neutralizing antibodies against the SARS-CoV-2...  ...  NONE  NONE\n",
              "4  35051989  Neutralizing antibodies against the SARS-CoV-2...  ...  NONE  NONE\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
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          "metadata": {},
          "execution_count": 4
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "# entries where MeSH terms are present\n",
        "data[data['MH']!='NONE'].head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 582
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        "id": "aFTEpLVzDh6E",
        "outputId": "bec8ba4b-22f7-4f8f-ad6c-c924944fb292"
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              "      <th>33</th>\n",
              "      <td>35051318</td>\n",
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              "      <td>Tirrell, Megan;Katz, Joseph</td>\n",
              "      <td>2021 Dec</td>\n",
              "      <td>Am J Dent</td>\n",
              "      <td>American journal of dentistry</td>\n",
              "      <td>eng</td>\n",
              "      <td>Female;Young Adult;*COVID-19;Humans;SARS-CoV-2...</td>\n",
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              "      <td>ppublish</td>\n",
              "      <td>Journal Article</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
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              "      <th>56</th>\n",
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              "      <td>NONE</td>\n",
              "      <td>Kim, Patrick Jinhyung;Homsi, Haya A;Mufti, Asf...</td>\n",
              "      <td>2022 Feb 1</td>\n",
              "      <td>Adv Skin Wound Care</td>\n",
              "      <td>Advances in skin &amp; wound care</td>\n",
              "      <td>eng</td>\n",
              "      <td>*Telemedicine;Pandemics;Referral and Consultat...</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
              "      <td>United States</td>\n",
              "      <td>ppublish</td>\n",
              "      <td>Journal Article;Review</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>35048897</td>\n",
              "      <td>The Psychological Impact of the COVID-19 Pande...</td>\n",
              "      <td>BACKGROUND: This study aims to longitudinally ...</td>\n",
              "      <td>Complutense University of Madrid.</td>\n",
              "      <td>Munoz, Manuel;Ausin, Berta;Zamorano, Sara;Cast...</td>\n",
              "      <td>2022 Feb</td>\n",
              "      <td>Psicothema</td>\n",
              "      <td>Psicothema</td>\n",
              "      <td>eng</td>\n",
              "      <td>Longitudinal Studies;Anxiety;Depression/epidem...</td>\n",
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              "      <td>NONE</td>\n",
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              "      <td>ppublish</td>\n",
              "      <td>Journal Article</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
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              "    <tr>\n",
              "      <th>152</th>\n",
              "      <td>35048887</td>\n",
              "      <td>The digital divide: amplifying health inequali...</td>\n",
              "      <td>During COVID-19, health provision and informat...</td>\n",
              "      <td>Good Things Foundation, Sheffield, UK.;Psychos...</td>\n",
              "      <td>Mathers, Alice;Gilbody, Simon;Shiers, David;Pe...</td>\n",
              "      <td>2021 Oct</td>\n",
              "      <td>Br J Psychiatry</td>\n",
              "      <td>The British journal of psychiatry : the journa...</td>\n",
              "      <td>eng</td>\n",
              "      <td>Health Status Disparities;*Mental Disorders/ep...</td>\n",
              "      <td>NONE</td>\n",
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              "      <td>England</td>\n",
              "      <td>ppublish</td>\n",
              "      <td>Journal Article</td>\n",
              "      <td>NONE</td>\n",
              "      <td>NONE</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-116d678b-6d2b-4d92-9de2-4c3e8e54c017')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-116d678b-6d2b-4d92-9de2-4c3e8e54c017 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-116d678b-6d2b-4d92-9de2-4c3e8e54c017');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "         PMID                                                 TI  ...    RN    SI\n",
              "2    35052020  Has COVID-19 Complicated Eating Disorder Treat...  ...  NONE  NONE\n",
              "33   35051318  Increased occurrence of temporomandibular join...  ...  NONE  NONE\n",
              "56   35050917  Chronic Wound Telemedicine Models Before and D...  ...  NONE  NONE\n",
              "151  35048897  The Psychological Impact of the COVID-19 Pande...  ...  NONE  NONE\n",
              "152  35048887  The digital divide: amplifying health inequali...  ...  NONE  NONE\n",
              "\n",
              "[5 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def none_entries(column):\n",
        "  '''Returns missing entries count from each column'''\n",
        "  \n",
        "  return dict(column.value_counts()).get('NONE')"
      ],
      "metadata": {
        "id": "V9HwDxPNE6eS"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for column in data.columns:\n",
        "  print(f\"{column} Missing entries\\t-\\t{none_entries(data[column])}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AX43ETF5FLOP",
        "outputId": "72aff4eb-c553-42dd-e9ac-b291e49018a2"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "PMID Missing entries\t-\t2\n",
            "TI Missing entries\t-\t617\n",
            "AB Missing entries\t-\t56128\n",
            "AD Missing entries\t-\t10258\n",
            "FAU Missing entries\t-\t1838\n",
            "DP Missing entries\t-\t2\n",
            "TA Missing entries\t-\t165\n",
            "JT Missing entries\t-\t158\n",
            "LA Missing entries\t-\t2\n",
            "MH Missing entries\t-\t72505\n",
            "OAB Missing entries\t-\t204498\n",
            "OT Missing entries\t-\t81220\n",
            "PL Missing entries\t-\t23\n",
            "PST Missing entries\t-\t158\n",
            "PT Missing entries\t-\t2\n",
            "RN Missing entries\t-\t158321\n",
            "SI Missing entries\t-\t202877\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Selecting only those entries which have MeSH Terms available\n",
        "data_mesh_present = data[data['MH']!='NONE']"
      ],
      "metadata": {
        "id": "pDsLDFcSGMi8"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mesh_entries = \"{:,}\".format(len(data_mesh_present.MH))\n",
        "mesh_entries"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "HU5z9AjZGsUs",
        "outputId": "3a661d40-fea3-44e4-d357-c5a56412949b"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'132,163'"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Average Number of MeSH terms association\n",
        "\n",
        "- Average number of MeSH terms single PubMed articles have."
      ],
      "metadata": {
        "id": "ysa8vo0PG4x7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def mesh_count(entry):\n",
        "  '''Returns the count of total terms present in single entry\n",
        "  '''\n",
        "  temp = []\n",
        "  for terms in entry.split(';'):\n",
        "    for term in terms.split('/'):\n",
        "      temp.append(term.replace('*', ''))\n",
        "\n",
        "  return len(temp)    "
      ],
      "metadata": {
        "id": "zgJ5RPibG9Hi"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "term_count = []\n",
        "for entry in data_mesh_present.MH:\n",
        "  term_count.append(mesh_count(entry))"
      ],
      "metadata": {
        "id": "TX9q5oofG1bk"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.rcParams['figure.figsize'] = [18, 6]\n",
        "\n",
        "sns.kdeplot(term_count, shade=True, color=\"r\")\n",
        "\n",
        "plt.title(f\"Density of MeSH Terms in {mesh_entries} Sars CoV-2 PubMed Articles\")\n",
        "\n",
        "plt.xlabel('Number of MeSH Terms')\n",
        "\n",
        "plt.ylabel('Density')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "H4GNKQ0cHHbV",
        "outputId": "24799744-3d9f-4f27-9075-08d668b6a6eb"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Density')"
            ]
          },
          "metadata": {},
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- Right skewness in the distribution of MeSH terms"
      ],
      "metadata": {
        "id": "-6aoufVPSH0-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "np.mean(term_count)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SNuGwhhnIuqQ",
        "outputId": "fb994990-d72e-4f7f-dac9-25367e23ca99"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16.934951537117044"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- On an average there are ~17 MeSH terms per entry (pubmed article)."
      ],
      "metadata": {
        "id": "AImuMlawM0Uv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Creating MeSH Terms Network Graph "
      ],
      "metadata": {
        "id": "nkxrajgmQP8H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "G = nx.Graph()\n",
        "\n",
        "for pmid, entry in tqdm(zip(data_mesh_present.PMID, data_mesh_present.MH)):\n",
        "  main_node = str(pmid).strip()\n",
        "  G.add_node(main_node)\n",
        "\n",
        "  for terms in entry.split(';'):\n",
        "    terms_list = terms.split('/')\n",
        "\n",
        "    if (len(terms_list))==1:\n",
        "      primary = terms_list[0].replace('*', '')\n",
        "      if G.has_node(primary):\n",
        "        G.add_edge(main_node, primary)\n",
        "      else:\n",
        "        G.add_node(primary)\n",
        "        G.add_edge(main_node, primary)\n",
        "\n",
        "    else:\n",
        "      primary = terms_list[0].replace('*', '')\n",
        "      if G.has_node(primary):\n",
        "        G.add_edge(main_node, primary)\n",
        "      else:\n",
        "        G.add_node(primary)\n",
        "        G.add_edge(main_node, primary)\n",
        "\n",
        "      secondary = terms_list[1:]\n",
        "      for term in secondary:\n",
        "        term = term.replace('*', '')\n",
        "        if G.has_node(term):\n",
        "          G.add_edge(main_node, term)\n",
        "        else:\n",
        "          G.add_node(term)\n",
        "          G.add_edge(main_node, term)"
      ],
      "metadata": {
        "id": "bt5VjNDkI9Nd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7ce5296f-b3dc-4858-b314-85d1fca6e54b"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "132163it [00:08, 15970.71it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Shape Of The Network"
      ],
      "metadata": {
        "id": "4FT6aQtSNUrR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "G.number_of_nodes()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p3Zt47ZZ_55T",
        "outputId": "254c69de-2dea-4bd3-be7e-3927efa85790"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "146985"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "G.number_of_edges()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iGwZXYayDI9S",
        "outputId": "1c147cc0-689b-43c8-d0ce-03db051c3b95"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1882993"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "density = nx.density(G)\n",
        "print(\"Network density:\", round(density, 6))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pu68H8RrNZm2",
        "outputId": "4b10c0ed-03a3-4b17-9c76-645c06e65224"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Network density: 0.000174\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Centrality"
      ],
      "metadata": {
        "id": "aKVHMgQMH-Rp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "degree_dict = dict(G.degree(G.nodes()))\n",
        "nx.set_node_attributes(G, degree_dict, 'degree')\n",
        "sorted_degree = sorted(degree_dict.items(), key=itemgetter(1), reverse=True)"
      ],
      "metadata": {
        "id": "x-Q9mWVoIAMf"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(sorted_degree)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8CQBHfZDJvNy",
        "outputId": "e8eb9dde-9dcb-45c0-c369-0c0badffae39"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "146985"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sorted_degree[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lbHb3JwyJ0uZ",
        "outputId": "8a62db87-c2ad-4612-8d8d-a274b7f5ed79"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('Humans', 130253)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Plotting Top MeSH Terms (Nodes) Among 146,985 Terms (Nodes) By Degree"
      ],
      "metadata": {
        "id": "KGbRYAzPAtJ1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Top 50 Nodes"
      ],
      "metadata": {
        "id": "WNPgRLslRDFF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "top = 50\n",
        "print(f\"Top {top} nodes by degree:\")\n",
        "for d in sorted_degree[:top]:\n",
        "    print(d)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a1wBGB8SIFKX",
        "outputId": "46910413-a44b-4ca2-b203-f2b73b9e36cd"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top 50 nodes by degree:\n",
            "('Humans', 130253)\n",
            "('COVID-19', 127943)\n",
            "('SARS-CoV-2', 101980)\n",
            "('Pandemics', 67930)\n",
            "('epidemiology', 52684)\n",
            "('Coronavirus Infections', 40055)\n",
            "('Pneumonia, Viral', 39919)\n",
            "('Female', 36195)\n",
            "('Male', 33946)\n",
            "('Betacoronavirus', 33175)\n",
            "('prevention & control', 25135)\n",
            "('Adult', 23759)\n",
            "('Middle Aged', 23662)\n",
            "('virology', 20611)\n",
            "('diagnosis', 20406)\n",
            "('methods', 19589)\n",
            "('Aged', 19421)\n",
            "('therapy', 16705)\n",
            "('complications', 14891)\n",
            "('statistics & numerical data', 14222)\n",
            "('drug therapy', 13294)\n",
            "('immunology', 11367)\n",
            "('therapeutic use', 10976)\n",
            "('Retrospective Studies', 9935)\n",
            "('isolation & purification', 9832)\n",
            "('psychology', 9741)\n",
            "('genetics', 9313)\n",
            "('etiology', 9058)\n",
            "('Young Adult', 8866)\n",
            "('Adolescent', 8768)\n",
            "('Child', 8493)\n",
            "('transmission', 8478)\n",
            "('metabolism', 8384)\n",
            "('organization & administration', 8254)\n",
            "('COVID-19 Vaccines', 7754)\n",
            "('Aged, 80 and over', 7647)\n",
            "('United States', 7434)\n",
            "('blood', 7198)\n",
            "('Cross-Sectional Studies', 6969)\n",
            "('Risk Factors', 6826)\n",
            "('mortality', 6786)\n",
            "('adverse effects', 6355)\n",
            "('pathology', 6284)\n",
            "('Animals', 6277)\n",
            "('China', 6222)\n",
            "('physiology', 5939)\n",
            "('Surveys and Questionnaires', 5838)\n",
            "('standards', 5777)\n",
            "('COVID-19 Testing', 5684)\n",
            "('Communicable Disease Control', 5359)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Top 30 Nodes Plot"
      ],
      "metadata": {
        "id": "PIAYET1fRFT-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "top = 30\n",
        "top_nodes = sorted_degree[:top]\n",
        "\n",
        "mesh_nodes = list()\n",
        "degrees = list()\n",
        "\n",
        "for mesh_node, degree in top_nodes:\n",
        "  mesh_nodes.append(mesh_node)\n",
        "  degrees.append(degree)\n",
        "\n",
        "title_ = f\"Top {top} Nodes By Degree (Connection) In MeSH Terms Network Graph\"\n",
        "\n",
        "plt.rcParams['figure.figsize'] = [27, 9]\n",
        "\n",
        "plt.xticks(rotation=90)\n",
        "\n",
        "plt.plot(mesh_nodes, degrees, color='#c0392b', \n",
        "         marker='o', linestyle='dashed', \n",
        "         linewidth=2, markersize=8)\n",
        "\n",
        "plt.suptitle(f\"Based on {mesh_entries} Sars CoV-2 PubMed Articles Meta-data\", \n",
        "             fontsize=14)\n",
        "\n",
        "plt.title(title_, fontsize=22)\n",
        "\n",
        "plt.xticks(fontsize=12) \n",
        "\n",
        "plt.xlabel('MeSH Term (Node)', fontsize=18)\n",
        "\n",
        "plt.ylabel('Degree', fontsize=18)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 640
        },
        "id": "XN9gA5REBQAk",
        "outputId": "5f203bc0-1806-4771-ef09-3633f25a59e3"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Degree')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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t268DSCn9F7gEOC4idiitwk4Dnia3lGmpfA22u1dEnFH+vj4iNoiIL5Jbg11UknV6LTRZ99oR8YOI2D4i1oqItwGbU2kFWFWCOoeRuwT8RynTuuU8H0VuyQRduwZOJXdz+TZK95YdlHc4eQy+Zcljog2rnL9FaT10M7kl2bHlGtsPOLJBurnALyJiu3ItnA78m/n7Xe+j5DHQbm2y/IfANhHxm4jYsmx7r4j4LbzSneUp5MDpOyJiE/Lxaho8i4iB5KDgWSmle6oTOVA/inysOzIR2KUc12WbpDkGeF/krnM3johNIuJzETG0PmG5N84ExkbuLnKdiHhTRHwxIvYt5f58RHwgIjaK3PrtQGAaJdjdgu8BKwAXNll+ArA0cG5EbFvKsGtEnFSuq9p+b1rusZHlWHbr3iI/O48q+7sB8AsWDKI9D0wBPlLO+1vJrUarQfqnyS0Md4uIlSJ3nUkp08HluG9NbuE3G0mSJGkJZIBOkiRJfdGu5NYWk8kBhK2B96WUxgOUbhl/TK74vYs89tI369bRjxzYuxe4ihyQO7TkfwnYidwy5zzgfnLAYVly5TEppXPJre2OIbeC2Qz4WUeFLuvdDRhBHq/rEvJYTB/q+iFYyMmlHJ8jV3b/q0y1lmRzga8C/yQfk2+RK+YPq6zjY+RWKr9g/vGdTKViPyJ2jogUETtX8n2nbOvH5XNt22+qpDmEvK+XkVvULQXsUo5Jq+Wrdy/wIrlLvX+Rj+nB5K76vg8tXwuNvETuRvE8cqX/6eRAyg+bZShj621Fvl5+Q249No7cOuiTJU1XroHTyV1bPkbjVntVW5FbJW1cyls9f9t3krep0lrvIPJxu5vSjWyDpLPI98LvyfdkP2DfZq3RUkozS9ekzbZ7F/keHAVcR27FeCwLdrn4ReBacjD2WuAe8viUzbybHKhaaMy7lNJk8nVZ37Ku3hfIQbxHadKVaUrpCmAfYI+S5rqSp1l3lIeRA9Y/Il8748j7Xmtd+gK5peEt5NZuWwB7VO6dDqWU5qSUpjTrDjOl9AS5NdzLwJ/JgdUTyOe0Fhz/Hfl6vpXcqnKHRbi3flr292TmXytnVsrzMnksys3J5/QE8jU3q5JmLvBp8vl6gnwfQb6PXkceP/AcctB2YgtlkiRJknpddNx7hyRJkiTNFxGHkccO26CD7j8lSZIkSVIHbEEnSZIkqSveBXzZ4JwkSZIkSd1nCzpJkiRJkiRJkiSpF9mCTpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSZIkSZIkSZKkXmSATpIkSZIkSZIkSepFBugkSVKPiojUjWnsElDu7SPi1xFxc0Q8ERGzIuLFiLgrIn4QESt0kn/biLgoIp6OiJkRMSEifhQRS3ejLEdXjs35HaT7Ym8ev4gYX7a3c29sr1URMbbJdfVSRNwbET+LiJXbWJaXIuLJcm2dGBG7RYS/w7spIkaU43lTB2kGR8QRETEuIh4r9+T0cl+eFRH7eA4WTe36bnMZ9inl+FQ389fu16N7uGiNtrVz3XNhww7SjijXay3tmB4sx4YR8ZuI+E95Ns2IiEkRcUNE/DQi3tEgz8RWnv2V74hOy1v3PdeVaVR3970viogxlX3/ZwfpRpc043uxeEu0yrEbuxjWvWZEfC8ibiy/++ZExLTym+OMiDggIpbq6e0uDkvCs1ySpNeyAe0ugCRJetU5vcG8lYHdgOlAo4DTPxZriVrzLuBjwETgXuAZYDlga+DLwGERsXNK6b76jBHxAeAPQH/geuBx4M3Al4B9ImKHlNLT3SzXfhGxdUqpacWcXnEncEf5dwArAdsCnwMOLudhQhvKMpB8LW0GbAN8HLg3Ig5NKd3aS+V5Nfkm+dx+oNHCiNgGOA9YE5gL3Ea+LwcA65V8HwBuJd/fqlMqtA8FDkspjW1vaZpLKV0UEbcCR0fEmSml59pdpi4YA3ylybL9gaE9vcGI2B/4PTCI/D01HngeWAF4I7Ad8Fbgqp7edgN30Pj3wu7k+/t64IEGy19cnIVawr0pIkanlJq+uNNTStD6W8C3U0pHL+7t9RUREcDXyMdmIDAV+Cf5N+NQYB3gQOAgYHJEbJNSeqxNxZUkSX2AATpJktSjUkpj6ueVt+53A6Y0Wr6EOAM4KaU0qTozIoYBp5ArTH9DrrysLl+9LA9g75TSJWX+gLLO/YHfAvt0o0wvkSt8jgV27Ub+15qL6ysSI7dgvAzYEfgR3TsPPVKWUp6tgB+Qz+d1EfG2lNItvVSmPq+0nvk08PeU0rUNlr8JuA5YCjgV+Gp9cDwi1iRXsL5/cZf3VW6jdheg+A5wKfmcfrHNZWnFg8DywCER8fWU0rwGaQ4D5gF3AVv2xEZLK+JTycG5zwG/qm67tCh9S5kWu5TSxcDFDco5nhygO3lJDg63Qe33wPci4qIm140Wv58BnyUH5j4LnJFSmltNEBGrkF/E+TywDGCATpIkNWW3LpIkSUBK6f764FyZP53cEg5gx4gYXJfks8AQ4PRacK7kmwscAUwD9o6IjbtRrD8CTwK7NOp2TJ1LKU0lV+AD7NzGogCQUrqNHKw+n1zZelYJ5qo1nyC3Wji5fkFEDCTfM0sBv0wpHd6o5WpKaVJK6WPA3ou7sK9m5Zl5f7vLAVxBfk5+uLxQsaSbCZwDrAo06k7y9eSWbH8BnujB7e5FfubcmFL6RX2AJ6X0ckrpbyml7/fgNtVzxpMDthsAH2pvUV6bImJ38m++WcDbU0pj64NzACmlySmlb5JbzT/Zy8WUJEl9jAE6SZLUdhGxSUT8PiIejTz225SIuCIi9miSvjZu0JiI2CIiLi55ZkTEbRFxWA8XcW7lb/1b67VK/jPrM6WUppFbb1XTdcV04Lvl38eWrpVaFnlcvQsij9c1u/w9PyLe3EGekRFxfORxu2ZFxEMRcWxEdNjdWmQHRMRfyrmYFXlco981GzMoIt4ZEZdXxm95LiLuj4hTI+KNXdnXTtQqyAbWlXdCuY46Oh4XlDRH9lRhUkovk9+unwmsS4NrIyIGRsTHIuLvEfF8zB/X8GfRZDzEsk9HRMS/yr3wTERcGBGbRZOxeKrzI2L5iPhlRDxcrpeL69bdpfNb8q0REcdFHu9qRuQxeq4v2+3q9bwUuWJ6OnBBgyQHAWsDTwNHdba+lNLfGmxjZET8sFyHtfLeFBFHNgqk1h2/4RHx43L8ZkXE45HHtVyup/JV8m8UEaeUPDPLNXJ1RLyngzwDy/VxbbnXaudwXEQcVNKMijwW0aEl22mx4PhfYyrrazpuUW8dR4ASaDoTWJrctdwiW9Tz04LTyt8xDZYdVpemo3JuGxHnRH5ezy73/KUR0agV3Irlb3e7W14iRB7D89KIeKrs8+SIODsiNmuQdlQ5jxMjYkDkcVvvjDy+3/9Kmuq5XjbyM3BSuW7vi4iPVda3SUT8sWx7RkTcEhG7NSnnBhFxekQ8Usr5QinHRRGxXzd2PQFfLf/+VkQM6UrmyM/370XE3ZHH150eEbdHxOciv9xQTZvIXTjWtlV9BhwdEf3LM2dORAyvy/ueSto96paNKHmej7oxQCNirchjtD5U7rPny7Oq4T0d88cwPLrkPa3cB3Mj4hctHI9NynlOEfH1Vo4hUEt3fErp9s4Sp5QeTilNqdtu9ffr5hFxXuTfZvMi4rMlzfDIz+qLI+KByGNFvhj5u/3rzc59VJ7JMf+3wEsR8Wzk3wKbdlbmiNg/8rh6L5Zr9pomzxNJktRDDNBJkqS2ilyhfBtwCLnLoAvIY8DtBlwREd/tIPu2wI3ApuQxc24A3gCcGhG/7KHyDWJ+kOxP1belI2IEOcACeQySRmrzu9tN2e/IXaJtBbyv1UwR8XHg78C+wCRyi61JwH7A9RHxkQZ5VgZuJrdSGkTuNu7fwKeAa8q8RtsaWNZ/Nrl7tHtL3unAh4HbI3c9WM0zBriSPN7QAyX/9eSg1Rjgna3uawu2KX9fGT8wpZSAE8rHhsG3iFgNeA/wAnmMwR5TKu3+XD4u0IqmXFd/BX5NfgP/duBycvf0nwNujcZBsd+WaVPysby65L8ZeFOD9FUjydfqQeTx8y6hBDa7c35LvrcBd5O7pOxX9vdmYHNy8KHR+FMd2ZE8lt+NpWVrvfeWv+emlGZ1cd1ExHrkY30UOdhzGfA38jE8AfhTLNyCtmZp8jH/EHlsrb+QWyt9DLiqvgJ8UfJFxAElbS1YOY7csmZH4JKI+E6DPMuSu/78Lbl11r+AC4GHgR2AY0rSF8nn5cHy+fryuTY1GhOsflvtOI5Xl7/vbbK8u7pbng6Vbm3vJbeuXqY2vwQtDgGeI99jTUXEF8jff+8n36uXkM/PnuTuc+uf8bUW4ru0UlG/JIqI48jPkT3I1+jFwGTgAOCWiHhXs6zk3xbHkAOUte+2qmXIx3M0cBP598R6wK8j4ssRsV2ZvzFwLfn8bQ1cHhE71ZVzM/Lz9IPkrikvI3/fTSb/tlno+7cVKaUryN/rq5G/l1tSynMXOcC0DLk13nXAWuQuG/9UfuvUnE7+HqD8rT4D7ihB8fHk76Sd6za3S+Xf9V1zv7Xkuba8qFIr35vJ99fHy6yLyMdvB+DMyC9wNXuhY33y82w38vm7DPhfk7S17b2NfF+vDHwwpXRMR+lLnuVKeSB3X76odgBuIY/9OJ58Xb9Ulr2B+c/qJ8jX643k35vfA8ZHfmGlWVl/Tv79MJX8XJhC7t775o6CbeW74yxgNvk3x2PA24FryvUvSZIWh5SSk5OTk5OTk9NincgVOAmYWDd/ZXIFQgI+3yDP9LJst7plY8v8BBwH9K8s25bcrWQC3tWNsq5f1j+WXPH9VFnXLcCqdWk3L8ue72B9+5Q0t3ahDEeXPMeXzx8on/8LDKik+2KZP7Yu/xuAOeTWfu+rW3ZAmT8b2LRu2QVlfVcBwyvzVwP+UznmO9fl+0GZfx2wet2yT5ZlD9SV/aEyf/sG+786sHEXjlfteji6Mi/I4xgdTK6cehnYry7f0uSAxAxg+Qbr/U71PHS3LB2k/XpJ+4+6+eeU+ecBy1bm9wd+WJaNr8uzd+1aBN5Ymd8P+HHl3NVfK2Mqy66snvdFPL+rkIMMc8mtsaKybA1yhWoCxnTh2B5T8nynyfJJZfkhra6zLv8tJf8fgaXqylu7/o/t4PhdDryusmzVSpkO6qF8m5O7V3sB2KNu2SaVfG+rW3ZxmX8DCz/Hlmqwrtp13PT81MrfzuNYSbMs+R6fSuX7oLv366KWp8m2di557imfv1Q+f7ySZncWfPaPa3QeyAGqBDwObFu3bIdyHGYDr6/MH17SJ/L3w+XkIOquwNKdlH0iDZ79DdKN7+y6aeE4NVwHOSiagHuADeuW7V326XkWfGaOqpzHR4D1Gmyveq7Pq7tma8f5hXIMvlCXt/ZsvaZu/qll/lcbbO91wHZdOB618o0rn7cvn58DlqmkG03j74YhzP++/QoLPqeXI3/fN7oHjm40v7K89uz/Rd38e8gB46eAO+uW/aLk+URl3lLMv59+zoK/5zZl/m+wjzYpXyK/8DGog2M3tjLvIPIzdCqwSxfOwy5lXbPowjOmwXrGVsr9PaBfgzSrkwNj/ermLwP8qeT9coN8tfVOB3aqzA/yWMapHOulmuR7FtiqMr8fcFJZdsFDeaEAACAASURBVFV399nJycnJycmp46ntBXBycnJycnJ69U80D9D9Hw0CFJXlP2hUMVCp4HgMGNwg37e7W6FAbiGU6qargXUapK1VlD3WwfreUdL8pwtlqFU81Sppg/kBjY9W0jUL0J1S5p/ZZP21ANDvKvPWJFdwzwXWbZDn3ZXjsXNl/nLkt75fAFZssr1aJfO7K/Om00Fgs4vnrFrh1Wj6D7Brk7wnljRH1c0fSG7tkFjEYGEHaT9a0t5Xmbdx7V4BhjTI04/cEiIBm1Xm/7XM+0aDPAOBR5tcK2PK/NnAqAZ5u3t+a4HEHzbJ86ay/LYuHNvLS54PNFk+oyzfrdV1VvLuWPJOA5ZrsHz3yvJqBX7t+L0ArNwg31Fl+alNjntX851LXVCnbnmtkv6CyrwtKmVfoYvX8ZgO0iTqAnS9fRzr0tSCTxt04bzX9vPouvmLXJ4GeXZmwQDdyuTn7c0Nzu9WdffWmLp13Vzm79FkW7Xvhp/Wzd+I3DKp/hk5j9yiaP8m65vYIE9HU9PrpoXjNL5+HeSXE56gg+cxcHxZ/qnKvFGVMh3YJF/tXE8DRjZYfkdZfkODZcsxP2gzsDK/9qzaorvHoUH5xlXmXVLmHVuZ1yxA9/Ey/9wm61+V/Px/hgVfpDi60b1RWb5h9XquXNOJ3ArrbPJvihUry+8uyzeszDukzHu4egwry2uB2Ql182vlm0KDF0vqjt3Y8vmrpUyPUfn+bPE87F/WNbnJ8qHMf7mrOh1cl25sWc99dCPQR36JLAH/bLCsdq3/pMGy/uRWp4mFX/yo5ftkg3wrlWUzG50fJycnJycnp0Wf7OJSkiS101vL32Zd3Z1a/r4lIvo3WH5+atyVXa07wrdEg/GOOpJS+kdKKciVGWuSK4/WAe6JiNFdWVdPSSkl5o89881m449U1I7r2CbLa8d158q8nciBwJtSSg/WZ0gpNes26m3kN/SvSyk1G9vouvK32kXSLcAypeuqLTvovqor6rviuojcjdnrgRMiYpsGeY4vfz9aNybOvuTKxvEppXt7oGyN1Lb3cmVebcyecSmlGfUZUu4W7O/l43YA5Rrfvsw7q0GeOeQuKjtye0ppYoP53T2/ta7mzmuS5zZy68UtOuqqq05tDK1nW0zfFbV75rKU0nP1C1NKfyYHbIeTu5utd1tK6ckG8+8vf1dtst2W85XrsxbganY+G52L3cvfS1NKzzTJ11PadRwhtyiCXKHcUxalPB0q6/0zsE3kMQWXJXfReXdK6bZm+SJiJLnb3mnkLjcbaXQdkFK6L6W0NbmV3ffJXRc/T34WbQ+cE3XjVNa5kgWfsfXTUx3kXRRbkFvl/ruD53HDfa64qJNt3Jrqxgsrat26/rl+QbnGnyV3/7x8ZdEt5e9vIuIdHXTp2l1fI39vfCYiVukkbYfP4pTSE8AEcjfH67dagJTS/eSg6Sale2zIrb4gv9R0Nfk3xS4AEbESuUXc4yVvTe2ZcVb5rqo3lvzMW690O13v6pTSC50Ut39E/IZ8zd8DvDmldHcnebpqELm1eP3UbIzbS1LuKrShyN4SEV+LPDbfaeXe/EZJ8voOyrJQF5xlW2eXjzs3yTeuQb6nyM+IwSx4jUuSpB7SpQorSZKkHlarbHm4yfKJ5EqopcgVA/UBgmb5JtXl63KlYQmEPAqcERHXk9+iPy0ibigVWpADDADDOljV68rfziqQOivPnyPiOnJl1mfIrQub6ey4PlSXDnKXSh3lgdxF2DJ189Ypf/eMiNRBXoAVKv8+klwZdEiZpkbELeRKvd83qRTvzMUppaPrZ0bEPuSAxrURsVFKqTYWEymleyPianI3b7sDV1TKB/PHqVscRpa/1UBG7Xh+IiI+0Un+2vEcSa48q12zjTzSybqaLe/u+a3l+2cLsdflya2fOrN0+TutyfJnyN0orthkeUc6u2cg3zersOB9UzOpwTyYX9ZmQciu5FseGFH+/XQnx7V6LtYqf+9vlLCHtes4VtPUP6MWxaKUpxWnkceMO4z8fTeY5i9W1Kxd/o4A5nbhOnhFSukGcnentcDvm4Fvkcf+PDQiLk8pNQro/CClNL7ZxiJiPD0bIK2pPU826eJzqObpRi881HmsyfwXW1i+PAteCz8mtybdhRxEnRURd5CDiGcsanAopfTviPgDOQD0LXIrs2Zqx+68Fp7FK5C70m7VNeTv712AM5k//lwtOAf5u/Vs5gfvrqlbR4fPjJTSzIh4oqRbjYW/Kzr7boPctfcA8ssBO6aUpraQp14teLtsRPSvD66llP7H/H0mIo4mn5tmmpa7BDMvZP6LN42M6GBZR7+pYf7vvXodPe+WZdGfd5IkqQEDdJIkaUnQWYVbW6WUHo6IvwF7AbuRK1VhfgXLMhExIqXUKHCwRvk7sQeK8hXgRuDLEfHbFtL3xnGttWz8D3BTJ2lvrv0jpXRfRGxIPp5vJ7foeBu5S9BvRcR+pbXNIkspXRQRl5DHA/wUeeynql+RKxGPBK6IiE3JLQqfII/dtbjUWhBVK2trx/M28pv+Hfl3g3nNzvnLTebXNKu87tb5reQ7l9w1VkcatYJtpNaCs1nF5G3k+21r5rei7aru3jOdHd+eyFc7pvNo0EKiA+14vvb2cYT518Xzi7COeotSnlZcRm6BdTD5eTOXzs9t7TqYSufPp0YtwhZQXka5ISLeRW759UbymG7NWr+2Q22fHycHfzrSKBDdWXAOOj/XLV8LKaWXgF0jYlvyix87kFv2bQscFRHfSil9p9X1NfFNcuDp8Ij4aQfpasfucjq/HrraOvlqFg7QPVB7CSYiHmR+0K72tz5AV9PdZ0Yr5/bv5MD2KOD7EfHJ0jNBV9S6Oh0MbFY+L4qOyn0yOTh3PbkrzzuB/6WU5kTEIFr/zuyS8iyQJEm9zACdJElqp8fJ45isQ+NKm1HkrrdmsmAro+ryRtas5Oup7vBqXcO90jonpTS1VECtSw4KNNqHWreK/1rUAqSUboqIi8mVp1+plKne46VM65DHHKm3TiUddf8e1UER1mowr9Zi6+6U0pgO8i6kdGc1rkyULt6+RW4heAqNW9h0V+04bNRg2TjyG+d7RMQo5reeOymlNLcHy/CKiFiBHJwEuKqyqHY8r00p1QcSm3mWPIbQIHKAqtHb86O6Ucxqebp6fh8F1gO+m1JqFEjsjloL2mbdbF1Kvjf2j4gvNen+tpna9b9OB2ka3Te9aQq5UncIeaygFztJX1NrFbHBYinVgtp5HGvXRbOuWJc4KaXZEXEW+cWBVcjdkHZW/to9Oaerz9xOyjIvIv5KDtA1bHnXRrV9ntyT+7y4pZRupry4UAIrBwK/A46OiHNTSv9ZhHVPiohfA58FvkfzgOqj5Hv/1ymly7u7vSZqv3l2iYh1yb8RflNZfjW5++j1WbB1XVWHz4zSBfKqdWm7ahLwwVLeI4EhEfHhrgSkUkrPRsQN5GDrwSx6gK6hiBhG7pZ0HrBXaZlXtV4LqxlFDuo1mg/t+w6TJEkNOAadJElqp9qYMR9ssvyw8vcfTQIlo0ulV72Dyt/reyLAUsb42ql8nFC3+JK6bVbzjQDeXT52Nv5Nq75Grrj5FM0DWK0e1/GVeX8nvx2+XUQsVFEWEXvSuOu4q4E55NYCi9S1XErpeXLrtpeBVUsQq6esW/4uFNQolXQnkn8bf4lc+TYHOKkHt/+K0qXcieTuov5LDizV/Kn83bvV8RNLoPPG8vEDDbY3ENivm8Xt7vmt7cf7urndRm4vfzdusvxMcqvWFYEfdrayiNix8rF2z7y7BIrr0+5GDqC8SG6p1+vKs6xWud2V8TCvLH/fW8Yva8Xs8rerL3S25TiWba1M7ortgU6SL2lOJQfZnyW3nOlQSulxcqvbkRGxc6sbaXGczzXL32bdObbLLeTjs2VEtBKgWOKklGanlMaSWyIHsHkPrPYYcvfZ76PxmI7Q/Wdxp8+Aci3+h3zdfLzMrr6oVPv3EeTg0P2VLsJras+MDzT5zjuUfLweKNvrlpTSY+TfcfeQfwOd2dUxislj2AF8MiK27G5ZOrE0+bfICw2Cc9Dgt2Yraco4zgeUj+O7XTpJktTjDNBJkqR2+h25cuktEfHp6oKI2IkchAJo1n3T6sAPSsCjlm9r4PPl43GtFiQivtKo8joiViRXoK5LfhO9vtvFX5BbtRwaEe+p5BsA/Jbc7drFKaV7Wy1LR1JK9wG/J7eiOaJJsl+Su0r7QBl/7RUR8T7g/eSgyy8r651IDhT1B35d3uKu5VkV+EmT8jxFHqdtGeDS0m3lAiJiWEQcWMZVISKGRsTnmwTg9iT/Rp3G/C4NF0k5Bu8tHy9tkuwU4CXy2/XDyedsck9sv64sbyQHTEYD04EDq2PZpJRuJ3dbtx7wx4hYaKyYiFg2Ij5aV7n4q/L3ixGxRSVtP3LrijXphu6c3+LH5HP4tYj4RKOK0IjYJCL27UJxri1/t2tS1tnA/uTuvz4TESeX+7d+u6tFxPFUugdMKf0d+Cf53J8QEYOr6cn3OcDxKaXOuuxcnL5DvnePi4gD6oMukW0TEe+szUsp/YvcleJw4KKIWKUuz1IRsUfddmoV4Y1anDbVxuP4ZnIl/t/rx4Za0qWU7kgpjSzTZS1m+7/y94zqua6JiP4R8faIeHNl9pERcVpEbNMg/YCI+AjzA7/ndmknFrPyEsJ3yd9PFzfZh0ER8Z5Gz6jeFhFHRsRCLVbLyy+blI+tjJ3WoZTSFPJ3cwCfbpLsJPJvl0Mj4uiIGNqgXGtHxMF1s1t9BtReGvgE+eWav1aW/ZX84s8ny+dGvQycV8q3NnBs3e+5jYFvl48Nf4N0Rfk+25n8csAB5HH5Gr3k1Sz/FcDx5G4ur42IMU2+20aQu8HsjqfI3fQuExEH1q13d+b/vu3IkRHxlkq+IB/Hdcnn9YJulk2SJC0GdnEpSZLaJqX0ZEQcQq4MPC4iPkx+u3lVYEdyoOZ7HYxF9htyQOXdEXEruVuut5J/45zYhcpOgGOB70XEXeTuEOeRA4BvJAfDngL2LWPLVPfh0Yg4nDzm1cUR8Q/yWEJvJnf39ADw0S6UoxXfIneVtVBFWynTnRHxGXJF0oURcXPZp/XIXW6+TO4i7+66rEcCbwDeCTwcEdeRK6LeTj4vN9I4OHIU+Zy9H7gnIu4AHiJXzI0q6xxMruh7itwV40+BH0XE3eRWiS+TK4/eVPJ9uVTKdsXekbuorBlO7tqrViF6FnB2o4wppecj4gzmBz1P6OK2OyrLQHKAa3PyNQX5eB5aAnL1DiUHEvchd7t5J3kMwwHkbsA2J1dUn04OxJJSuiAiTgU+BPwzIsaTu0B9E7nby1+TWzjMpuu6en5r98XewPnk6/DrEfFvcveDy5ArL9cg3/sXtliO68ndPG4XEcNSStPrE6SUbo6ItwF/BA4nV0r/k9zF2QDyNfYGcoV2/Zh6B5KDgB8Ado6Iv5PvsbcBw8iVy0e3WNbFIqV0a0R8kPzSwNnkFxTuJXcBvAKwBfNbEP6lknUM+eWCtwAPlefUM+Tz+gbyeGajKukvIY9x9dnIYzI+Rj7fp6aUbuikmO04jrtWyv2ql1K6JCK+APwIuDIi/ktuyfQiuSXhluT77OPMv84Hkq+DMRHxJLmLvueA5cjPlFo3gj9KKdVaXS4xUkrHRcRawOeAmyvf1bPJrcm3JF9fe9B4HLredAQ5QP0Q+VlfOy9vIX//nZNSuqWHtvUzcnBsoZcRAFJKL0ZuAT+O/NvhU+XYPUH+jtyI/NvgZhYc//BK8ksr+0Yeg7f2u+jSlFL1RZdryvaXAm5PKb3SHXnpFvIO8rmBBuMHppRmRsT7yS39vgjsU57Zy5GfGQPJv696pEV7KdMuwBXkLpEvjoh9u/DCwKfJrTm/Th6P+BelvE+Tv5dXJ3/vDgYms/BLXZ2Vb15EHEMOSJ4ZEZ8kf/+vS/799n1yTwod+R1wXTlvk8m/Yzcgv0x2UEqplXH7JElSLzFAJ0mS2qpUNL4J+DI5EDSa3KruL8CvyhvLzdxMroj4Nnk8ryHkrr9OJLeI6opPkrs/2gJ4B7mibyq5W71xwG+adDdESunsUhH3VfL4JNuS3wj/MXBMSmlqF8vSoRL8OB74QgdpTiyBnS+UMm1Froy9EPhJSunGBnmeKC0Tvk1ucfYeciXeiWVew/FrSiBt/xLgOpxcibQ5+TxOJgcSLmH+OHAvkiuOdyYf793IlXCPk4Novyxj93TVG8pUM4cc0BkHjE0pdfbW+FXkitV/p5Su6yRtV8oyk9ya7GFyS6aLgatSSqlRxpTStFKBeCC5u803ks/f8+Tz8VvgkgYVih8ht176GDnAPR34B7lrs1pXq1O6uiPdOL+1fNdGxCbklrB7koPWA4EnyQG+E2k+blKjcsyOiJPJ4y+OJgcoG6W7MfKYR2PI1/AbyMdvHvOvsXOou55TSg9E7rbsKPL1/17yNfRvcqvVk7oRNO5xKaVzSoXwp8nPqreWRbWgy+XkwGg1z3ORu/T8CDlwtg25Avkpcve2Z9WlvyMi9idXmG8PvK4s+gfQYYCut49jacFyIPl5fVYnyV81Uko/i4hryPfXzuRrYS75nvwb+VlTDX6fQq7o35V8/jcjB3XmkAOwpwMnp5T+0Tt70HUppc9HHof14+TvtT3JQYfJ5Of8peTrud2+AexF/i2wPbkl/VPk7hx/Rw+2YCoBuO8yvxV1ozR3R8Tm5Jdw3kv+TtmeHKR/lPwMr39mPBkRe5ED9VuSg4tBvlaqAbpryS/Y9KNBAK7M27KkGd+kfDdFbvn9FWB3YF/yeb2RHJg7q9n3ZXeU8YPfSd6PPYArIuLdjV76aJA3kccQHEv+vbALef+WLmV+gtyl+aXklvhdDoallH4aERPJz99NgE3Jgd6DU0pnRkRnAbrPk198+ij5GpxJ/t3xzQYvZkmSpDaLHvydI0mS1CtKxcihwGFlTBdpkUXEReQ36o9MKf263eXpSRFxNbkicXQLgcolVkSsSa54vDmltFNn6fXqF7lr4UuAn6aUvtju8khSO0REAkgptTLepCRJWkI4Bp0kSZJe8yJiK3Jrq2fJrXz6nMhjug2tmzcwIr5BDs49Q+7Wq89KKU0ij524Y+nKUvo/cuvg77e7IJIkSZLUFXZxKUmSpNes0mXi64B3kV9e+2Yr3Vwtob5KHr/ndnJXjrWx3lYFZgFjXiVjz3wXOIQckGk0JqJeIyJiH/J4T5+ujn0lSZIkSX2BATpJkiS9lh1OHhvnEeA7KaUT21yeRXE2Odj4xjINII/N9HvyuIOvirFnUkrTgJXbXQ61X0rpIvK4WJIkSZLU5zgGXQNTp071oEiSJEmSJEmSJKlHLL300gu8YOgYdJIkSZIkSZIkSVIvMkAnSZIkSZIkSZIk9SIDdOoxEyZMaHcRepz71De4T32D+9Q3uE99w6txn+DVuV/uU9/gPvUN7lPf4D71De5T3+A+9Q3uU9/gPvUN7lPf8Grcp3YxQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8yQCdJkiRJkiRJkiT1IgN0kiRJkiRJkiRJUi8a0O4CqG+bN+Mlnj7/LKaMu5B506Zy94ilGbnXvqw4+kD6Dxna7uJJkiRJkiRJkiQtcQzQqdvmzXiJCZ87glmTHyfNnp3nTZvK0+efydTrx7P+z08ySCdJkiRJkiRJklTHLi7VbU+ff9YCwbmaNHs2syY/ztPnn9WmkkmSJEmSJEmSJC25bEGnbpsy7sKFgnM1afZsnv7jGfDyywxeYy2GrLs+Q9Zap5dLKEmSJEmSJEmStOQxQKdum/fCtA6Xp7lzeOqc0wEYsd2OrPPNHwAw94VpPHnmqSy15iiWWmMUS62xFgOWWXaxl1eSJEmSJEmSJGlJYIBO3dZ/+AjmTZvadHm/IUNZYe/3MXPSI7xusy1emT/zkYeZcsl5C65rxNIstfpaDF5zLVY+8DAGrbDSYiu3JEmSJEmSJElSOxmgU7eN3Gtfnj7/zIbdXMagQaywz/6scsiHF1o2cIUVWeWwjzFz0kRmPfoIMx99hHnTpjL93ruYfu9drHLw4a+knfSzY5jx4AQGr5lb2i21xigGr7kWg1ddg34DBy7W/ZMkSZIkSZIkSVocDNCp21YcfSBTrx/PrMmPLxCki0GDGLzKaqw4+sCG+QavtAorvf+QVz6nlJjz7BRmPTqRmY9NYsByI19Z9tID/2Xmww8w46EJC66kX39G7vleVj/yCwDMmzmDmY88zFKrr0X/YcN6cC8lSZIkSZIkSZJ6lgE6dVv/IUNZ/+cn8fT5ZzHl8ouYN20q/Ucszcg992HF0QfSf8jQltYTEQwauQKDRq7A8C23XmDZej/8FbMem5Rb2z32CDMnPcLMRycy+6nJ9B82/JV0M/57Pw98+ZMADFx+BQavuRZLrb4WS605isFrrMWwjTal36DBLZVn3oyX8j6Nu5B506Zy94ilGbnXvl3aJ0mSJEmSJEmSpGYM0GmR9B8ylFUO+TCrHPJhJkyYwPrrr9+j6x8wfAQDNtqUYRttusD8l2fPIs2Z88rnNHcOS629HrMem8ScZ59hzrPP8OK/bn1l+SZnXkq/5XKAbsq4C3l55gwGr5G7zRy00ipE//5ADs5N+NwRC7QKnDdtKk+ffyZTrx/P+j8/ySCdJEmSJEmSJElaJAbo1Cf1GzQYKi3ihr9xGzY8cRvSvHnMfmoyMx99JHeZOekRZk95igHLLvdK2imXXcDMSRNf+RwDBzF49TVZao21SC/PW6jLToA0ezazJj/O0+ef1XBcPUmSJEmSJEmSpFYZoNOrSvTvz+BVV2fwqqvDtjs0TLPC3vszY+KDzHx0IrMmPcKcZ59h5sMPMPPhB4jBgxcKztWk2bOZcvlFBugkSZIkSZIkSdIiMUCn15zl93jPAp/nTZ/OzMceYdajjzDpp9/rMO+8aVMXZ9EkSZIkSZIkSdJrQL92F0Bqt/7DhjFsg41Zbtc96D9i6Y7TdrJckiRJkiRJkiSpMwbopIqRe+1LDBrUcFkMGsTIPffp5RJJkiRJkiRJkqRXGwN0UsWKow9k8CqrNQzSDRg+ghVHH9iGUkmSJEmSJEmSpFcTA3RSRf8hQ1n/5yex4uiD6L/0MhBBvyFDAUgJIrxlJEmSJEmSJEnSojHaINXpP2QoqxzyYTY753KGHXcam51/JUPW24CXp7/ISxPub3fxJEmSJEmSJElSHzeg3QWQlnTRrx9rfuEbDBg+nIHLr9Du4kiSJEmSJEmSpD7OAJ3UgiGj1ml3ESRJkiRJkiRJ0quEXVxKXZDmzWXKFZcw45GH2l0USZIkSZIkSZLURxmgk7rgqXP/wGO/+hFPnHxCu4siSZIkSZIkSZL6KAN0UheMfNfe9Bs6jBduvYlpt93c7uJIkiRJkiRJkqQ+yACd1AUDllmWlQ44FIAnTj6BNG9em0skSZIkSZIkSZL6GgN0Uhet8N7RDFxxZWZOfJDnrrq83cWRJEmSJEmSJEl9jAE6qYv6DRrMqod9DIDJvz+ZeTNeanOJJEmSJEmSJElSX2KATuqGZd66K0M32Ji5zz/Ls3++tN3FkSRJkiRJkiRJfciAdhdA6osigtU++hlmPPwAy++2V7uLI0mSJEmSJEmS+hADdFI3DdtoU4ZttGm7iyFJkiRJkiRJkvoYu7iUesCc56Yw64nH2l0MSZIkSZIkSZLUBxigkxbRtNtu5r7DD+DRX/6IlFK7iyNJkiRJkiRJkpZwBuikRTT09RsRAwbw4p23Me2fN7a7OJIkSZIkSZIkaQlngE5aRAOGj2ClA8cA8MTJJ5DmzW1vgSRJkiRJkiRJ0hLNAJ3UA0butR+DVlmNWY9O5Nk/X9bu4kiSJEmSJEmSpCWYATqpB/QbOJBVP/RxAJ78w8nMmz69zSWSJEmSJEmSJElLKgN0Ug9ZeoedGbbx5syd+j+eOu8P7S6OJEmSJEmSJElaQhmgk3pIRLDqRz7J6zbfkmV22LndxZEkSZIkSZIkSUuoAe0ugPRqMmzDTVjvh8e3uxiSJEmSJEmSJGkJ1rYWdBFxakQ8HRH3VOb9OCLuj4i7IuKiiFimsuyrEfFARPwnInarzN+9zHsgIr5Smb92RNxc5p8bEYPK/MHl8wNl+aje2WO9Fs2bOaPdRZAkSZIkSZIkSUuYdnZxORbYvW7eVcCmKaXNgf8CXwWIiI2BA4BNSp4TI6J/RPQHTgD2ADYGPlDSAvwQ+HlKaT3geeDwMv9w4Pky/+clndSjZj/zNA9960s89H9fIKXU7uJIkiRJkiRJkqQlSNsCdCmlvwHP1c37S0ppbvl4E7B6+fd7gXNSSrNSSg8DDwDblOmBlNJDKaXZwDnAeyMigLcD55f8pwN7V9Z1evn3+cAuJb3UY/oNGcL0+//N9HvuZOqNf293cSRJkiRJkiRJ0hIk2tm6p3QvOS6ltGmDZZcB56aUzoiI44GbUkpnlGWnAH8qSXdPKX24zD8E2BY4uqRfr8xfA/hTSmnT0qXm7imlx8qyB4FtU0pTatueOnXqKwdlwoQJPbvTes2Yc91VzL7gTGKFlRjy1WOIAQ75KEmSJEmSJEnSa8X666//yr+XXnrpBRqLLZERg4j4OjAXOLPdZakePHVswoQJr7rjtSj7lNZem/tv+huzHn+UZf97Dyu89309XLru8Tz1De5T3+A+9Q3uU9/xatwv96lvajP+QwAAIABJREFUcJ/6Bvepb3Cf+gb3qW9wn/oG96lvcJ/6Bvepb3g17lO7tHMMuoYiYgywF3BQmt+873FgjUqy1cu8ZvOfBZaJiAF18xdYV1m+dEkv9agYMIBVD/8EAE+eeSpzX3yhzSWSJEmSJEmSJElLgiUqQBcRuwNHAe9JKb1UWXQpcEBEDI6ItYH1gVuAfwLrR8TaETEIOAC4tAT2rgVGl/yHApdU1nVo+fdo4K+pnf186lVtxJvfwrDNtmTeC9N46pzTO88gSZIkSZIkSZJe9doWoIuIs4EbgQ0i4rGIOBw4HhgOXBURd0TEbwBSSv8G/gjcC/wZ+ERKaV5KaS7wSeBK4D7gjyUtwJeBz0fEA8DywCll/inA8mX+54Gv9MLu6jUqIljtI58k/p+9O42ysyrQBfzuqso8QwJCQKYEWgQRRdFGW1FUUASV2K0o2ioOjQPXCW1txQlFW6Wx73WgbbpRQdSgzIoDzlM7Kw6QMMkQMqcSMlWqat8fOdARQ0gqVfXV8DxrnVXn7P2dc95drBXWypu9v7Fj0zZmbNNxAAAAAACAIaCxe9DVWp+/leH/3MrYPdefleSsrYxfneTqrYzflOTRWxnfkGRo3AyMUWHi3L/JQz97aTqmTms6CgAAAAAAMAQMqSMuYaRSzgEAAAAAAPdQ0MEgqb29WXHtNbnlA++M2x4CAAAAAMDopaCDQdK7YX3u/I9/z6rvfSudP/h203EAAAAAAICGKOhgkLRPnJQHnXJqkuTO8z+R3q6uhhMBAAAAAABNUNDBINr1acdn/IP3Tdddd2bZFZc0HQcAAAAAAGiAgg4GUWnvyJ4ve3WSZPHFF6R7dWfDiQAAAAAAgMGmoINBNuVRj83kw49Iz91rctdF/9V0HAAAAAAAYJAp6GCQlVIy+9TXJKVkzS9+mt5Nm5qOBAAAAAAADKKOpgPAaDRh/7nZ/70fyeRDD0/bmDFNxwEAAAAAAAaRgg4aMvWRRzYdAQAAAAAAaIAjLqFh3as7s2T+ham9vU1HAQAAAAAABoEddNCgWmsWnvHqbLj15ozZdVZmHP3UpiMBAAAAAAADzA46aFApJbOe/bwkyZ3//cn0btzYcCIAAAAAAGCgKeigYbscc1zG7zcnm5YsztLLvth0HAAAAAAAYIAp6KBhpb09s1/+miTJ4os/k02rVjacCAAAAAAAGEgKOhgCphz+qEx91GPTu35dFl94ftNxAAAAAACAAaSggyFij5edlrS1ZdnVl6Vr6ZKm4wAAAAAAAAOko+kAwGYT9tk/e770tEw88CEZO2u3puMAAAAAAAADREEHQ8huJz2/6QgAAAAAAMAAc8QlDFHrFl6f2tPTdAwAAAAAAKCfKehgCLrjvI/lhte+NCuu/VrTUQAAAAAAgH6moIMhaMKcg5Ikd11wXno3bGg4DQAAAAAA0J8UdDAEzXjiUzJh7kHZtHxZlnz5803HAQAAAAAA+pGCDoag0taW2ae+Nkmy5EsXZtOKZQ0nAgAAAAAA+ouCDoaoyQ87PFMf+/j0blifRZ/9dNNxAAAAAACAfqKggyFsz5eelrS3Z8XXr8r6m29sOg4AAAAAANAPOpoOANy/8Xs9OLOeeVJ6N21Kx4xdmo4DAAAAAAD0AwUdDHF7vuJ1KaU0HQMAAAAAAOgnjriEIW7Lcq52d6f29DSYBgAAAAAA2FkKOhgm1vzyf/KnV70wK75+VdNRAAAAAACAnaCgg2Gie83qbLzjtiz67H+kZ93apuMAAAAAAAB9pKCDYWL63z05Ew86ON0rV2TJ/IuajgMAAAAAAPSRgg6GiVJKZr/idUmSJV/+fLqWLmk4EQAAAAAA0BcKOhhGJh18aKY97ujUjRuz6DPnNR0HAAAAAADoAwUdDDN7vuRVKR0dWfmtr2XdwhuajgMAAAAAAOwgBR0MM+P23CszT5iXjhm7pHvViqbjAAAAAAAAO6ij6QDAjnvQC16aB51yatrHT2g6CgAAAAAAsIMUdDAMtU+c1HQEAAAAAACgjxxxCcNYz7q1WXTBeVl+zRVNRwEAAAAAALaTHXQwjK359S+y+OIL0j51eqY/7ui0T5rcdCQAAAAAAOAB2EEHw9i0xz4+kx76sPSsXpXFX/hs03EAAAAAAIDtoKCDYayUkj1f/tokydJLv5iuxXc1nAgAAAAAAHggCjoY5iYddHCmP/EpqZu6sui/P9l0HAAAAAAA4AEo6GAE2PMfX5UyZmxWfucbWXv9H5qOAwAAAAAAbIOCDkaAsbs/KLOe9fdJks4ffLvhNAAAAAAAwLZ0NB0A6B+7/8MpmXzowzPliMc0HQUAAAAAANgGBR2MEO2TJmfqox7bdAwAAAAAAOABOOISRqD1Ny9M54+/33QMAAAAAABgK+yggxFm/U0Lcv1rXpL2yVPykEO+kI4pU5uOBAAAAAAAbMEOOhhhxu83J5Mfdnh61qzO4osvaDoOAAAAAABwHwo6GGFKKdnz1NcmpWTZ5fOz8c7bm44EAAAAAABsQUEHI9DEOQdmxpOeltrdnUX//amm4wAAAAAAAFtQ0MEItceLX5kyblxWff/arP3D75qOAwAAAAAAtCjoYIQaO2u37Pac5yVJFl1gFx0AAAAAAAwVHU0HAAbObvNekJ41a7Lb37+w6SgAAAAAAECLgg5GsPaJk7LXq9/YdAwAAAAAAGALCjoYBXrWr8viL12Y5Vdckp671+R3U6dl5vHPyW7zTk77hIlNxwMAAAAAgFFFQQcjXM/6dbnh9FOz8fY/J7VuHlvdmSXzL0znD7+Tueecp6QDAAAAAIBB1NZ0AGBgLZl/UboWL7q3nLtH7erKxkV3ZMn8ixpKBgAAAAAAo5OCDka4ZVd+ObWra6tztasry676yiAnAgAAAACA0U1BByNcz5rV255f3TlISQAAAAAAgERBByNe+5Sp256fOm2QkgAAAAAAAImCDka8mcc/J2Xs2K3OlbFjM/MZzx7kRAAAAAAAMLop6GCE223eyRm3x+y/LunaOzJuj9nZbd7JzQQDAAAAAIBRqrGCrpRyfillSSnlui3GdimlfKOUsqD1c0ZrvJRSPlZKWVhK+W0p5RFbvOfFresXlFJevMX4I0spv2u952OllLKt74CRqn3CxMw957zsNu8FaZ82PSkl7dOmZ/d/OCVzzzkv7RMmNh0RAAAAAABGlSZ30P13kmPvM/bWJN+qtc5N8q3W6yQ5Lsnc1uMVST6RbC7bkpyZ5Mgkj05y5haF2yeSvHyL9x37AN8BI1b7hInZ45RTc+jFV2XSuf+VQy++KnuccqpyDgAAAAAAGtBYQVdr/V6SFfcZPjHJBa3nFyR51hbjn6mb/STJ9FLKHkmeluQbtdYVtdaVSb6R5NjW3NRa609qrTXJZ+7zWVv7DhhVujtXZfEXP5uNd97edBQAAAAAABhVyub+qqEvL2XfJFfWWg9pvV5Va53eel6SrKy1Ti+lXJnk7FrrD1pz30ryliRPTDK+1vq+1vg7kqxP8p3W9ce0xh+f5C211uPv7zu2zNXZ2XnvL2XBggUDtHpo1sbPn5/uH38vHU94Ssad9IKm4wAAAAAAwIgyd+7ce59PmzatbDnXMehptlOttZZSBrQ93J7v2PKXx7YtWLBgxP2+RvKa1p38ktzw4++l92c/yv6nnzGsj7scyf+dRhJrGh6saXgYiWtKRua6rGl4sKbhwZqGB2saHqxpeLCm4cGahgdrGh6saXgYiWtqSpP3oNuaxa3jKdP6uaQ1fkeSvbe4bq/W2LbG99rK+La+A0aViXMOzKSDH5bedWuz8ltfazoOAAAAAACMGkOtoLs8yYtbz1+c5LItxl9UNntMks5a66Ik1yR5aillRillRpKnJrmmNbe6lPKY1jGWL7rPZ23tO2DUmXnCSUmSpZdfkiaPuwUAAAAAgNGksYKulPL5JD9OclAp5fZSysuSnJ3kKaWUBUmOab1OkquT3JRkYZL/SHJaktRaVyR5b5KftR7vaY2ldc2nW++5MclXW+P39x0w6kw/6okZs+vMbLztltz96583HQcAAAAAAEaFxu5BV2t9/v1MPXkr19Ykr76fzzk/yflbGf95kkO2Mr58a98Bo1Hp6MiuT39W7vrsp7P08vmZcvijmo4EAAAAAAAjXmMFHTA07HrciVn3p99n1+NObDoKAAAAAACMCgo6GOXGzNgl+7/nw03HAAAAAACAUaOxe9ABAAAAAADAaKSgA5Ik6268IbecfWZWfOPqpqMAAAAAAMCIpqADkiQbbrkpq777zSz5yhdSa206DgAAAAAAjFgKOiBJMv3xT0rH9BnZcPPCrP39b5qOAwAAAAAAI5aCDkiStI0dm12POyFJsuzySxpOAwAAAAAAI5eCDrjXrk9/dtLWnlU//G66li5pOg4AAAAAAIxICjrgXmNnzsr0o56Q9PZk+dWXNh0HAAAAAABGJAUd8BdmnnBSkmT5NVek9nQ3nAYAAAAAAEaejqYDAEPLpIcelj1fdlqmPe7olHZ/RAAAAAAAQH/zt+/AXyilZLd5L2g6BgAAAAAAjFiOuATuV601PevWNh0DAAAAAABGFAUdsFVr/3hdrn/VC3P7//1w01EAAAAAAGBEUdABWzVml5nZcPufs+r712bTiuVNxwEAAAAAgBFDQQds1djdH5RpRz4utbs7y796WdNxAAAAAABgxFDQAfdr5gnzkiTLrr40vZs2NZwGAAAAAABGBgUdcL8mH/aIjH/wvulesTydP/xu03EAAAAAAGBEUNAB96uUkpnPbO2iu2J+w2kAAAAAAGBkUNAB2zTjyU9L26TJ2Xjn7dm0amXTcQAAAAAAYNjraDoAMLS1T5iYOR84N+P32T9tY8c2HQcAAAAAAIY9BR3wgCbO/ZumIwAAAAAAwIjhiEtgu3XfvSbrrv9j0zEAAAAAAGBYU9AB22XDn2/JH174rNx81ttTe7qbjgMAAAAAAMOWgg7YLuP2enDGzJyVTUsXp/MnP2g6DgAAAAAADFsKOmC7lLa2zHzmSUmSZZfPbzgNAAAAAAAMXwo6YLvtcszT0zZhQu7+7a+y/uYbm44DAAAAAADDkoIO2G7tkyZll2OOS5Isu+KShtMAAAAAAMDwpKADdsjMZ85Lkqy89pp0r1ndcBoAAAAAABh+OpoOAAwv4/feJ5MPPyJ1U3e6O1emY8rUpiMBAAAAAMCwoqADdtj+Z34obePGNR0DAAAAAACGJUdcAjtMOQcAAAAAAH2noAP6bN2CP2XJ/IuajgEAAAAAAMOKIy6BPulZuzYL3nxa6saNmfqYozJ+r32ajgQAAAAAAMOCHXRAn7RPmpQZRz81SbLs8ksaTgMAAAAAAMOHgg7os1knzEuSrPjm1elZu7bhNAAAAAAAMDwo6IA+m7DfnEw65OHpXb8+K755ddNxAAAAAABgWFDQATvlnl10y664JLW3t+E0AAAAAAAw9CnogJ0y7W8fnzEzd8vGO27Lml/9rOk4AAAAAAAw5HU0HQAY3kp7R3abd3I23nl7xs3eu+k4AAAAAAAw5CnogJ0268TnNh0BAAAAAACGDUdcAgAAAAAAwCBS0AH9otaa5ddcmQVnvCY9G9Y3HQcAAAAAAIYsBR3QL0opWf61y7P2d7/KymuvaToOAAAAAAAMWQo6oN/MOmFekmTZ5fNTa204DQAAAAAADE0KOqDfTHvc0emYsWs23Hpz7v7tL5uOAwAAAAAAQ5KCDug3bWPGZNenn5gkWXbFJQ2nAQAAAACAoUlBB/SrmU8/MWlvT+ePv5+uJXc1HQcAAAAAAIYcBR3Qr8bsMjPTH/+kpLc3y792edNxAAAAAABgyOloOgAw8ux20smZ8vBHZsYTntJ0FAAAAAAAGHIUdEC/mzjnwEycc2DTMQAAAAAAYEhyxCUwoHo2rE+ttekYAAAAAAAwZCjogAFz14Xn5/cvODHr/nhd01EAAAAAAGDIUNABA6Z3U1d6163N0svnNx0FAAAAAACGDAUdMGBmPuPZSVt7Vv3g29m0fGnTcQAAAAAAYEhQ0AEDZuys3TPtsY9Penqy7OrLmo4DAAAAAABDgoIOGFCzTpiXJFn+1cvSu2lTw2kAAAAAAKB5CjpgQE069OEZv+8B6V65Iqu+f23TcQAAAAAAoHEKOmBAlVLu3UW39rrfNJwGAAAAAACa19F0AGDkm3H0UzNh/7mZeNBDmo4CAAAAAACNs4MOGHBt48cr5wAAAAAAoEVBBwyq9bfclO7VnU3HAAAAAACAxijogEGz6ILzcv0/nZJlV13adBQAAAAAAGiMgg4YNJMPfXiSZPlVX0nt7m44DQAAAAAANGNIFnSllNeXUn5fSrmulPL5Usr4Usp+pZSfllIWllK+UEoZ27p2XOv1wtb8vlt8zj+3xq8vpTxti/FjW2MLSylvHfwVwug0+fBHZdze+2TT8qXp/PH3mo4DAAAAAACNGHIFXSlldpLXJTmi1npIkvYkz0vywSTn1FrnJFmZ5GWtt7wsycrW+Dmt61JKObj1vocmOTbJx0sp7aWU9iT/L8lxSQ5O8vzWtcAAK6Vk5jNPSpIsvXx+w2kAAAAAAKAZQ66ga+lIMqGU0pFkYpJFSZ6U5J6/0b8gybNaz09svU5r/smllNIav7jWurHWenOShUke3XosrLXeVGvtSnJx61pgEOzy5GPTNmFi1l73m6y/aUHTcQAAAAAAYNANuYKu1npHkg8n+XM2F3OdSX6RZFWt9Z6bVt2eZHbr+ewkt7Xe2926ftctx+/znvsbBwZB+8RJ2eWpz0hiFx0AAAAAAKNTqbU2neEvlFJmJLkkyT8kWZXkS9m8M+5drWMsU0rZO8lXa62HlFKuS3JsrfX21tyNSY5M8q4kP6m1fq41/p9Jvtr6mmNrrae2xk9JcmSt9TX3ZOjs7Lz3l7JggR0+0N96l9yV9R86Mx2P/buMO+kFTccBAAAAAIB+N3fu3HufT5s2rWw51zHoaR7YMUlurrUuTZJSypeTHJVkeimlo7VLbq8kd7SuvyPJ3klubx2JOS3J8i3G77Hle+5v/K9s+ctj2xYsWDDifl/WNEDmzk3PF65K+/gJ/fJxQ2JN/cyahgdrGh6safgYieuypuHBmoYHaxoerGl4sKbhwZqGB2saHqxpeLCm4WEkrqkpQ+6Iy2w+2vIxpZSJrXvJPTnJH5J8O8m81jUvTnJZ6/nlrddpzV9bN28LvDzJ80op40op+yWZm+R/kvwsydxSyn6llLFJnte6FhhE/VXOAQAAAADAcDPkdtDVWn9aSpmf5JdJupP8Ksl5Sa5KcnEp5X2tsf9sveU/k3y2lLIwyYpsLtxSa/19KeWL2VzudSd5da21J0lKKa9Jck2S9iTn11p/P1jrA/5X76ZNWfX9azN21u6ZfOjDm44DAAAAAACDYsgVdElSaz0zyZn3Gb4pyaO3cu2GJM+9n885K8lZWxm/OsnVO58U2BnLv3pZ7vjEOZn88CMy5wPnNh0HAAAAAAAGxVA84hIYJWY86WlpGzc+d//659lw681NxwEAAAAAgEGhoAMa0zF5SmY8+dgkydIrLmk4DQAAAAAADA4FHdComSeclCRZ+a2vpWft3Q2nAQAAAACAgaegAxo1YZ/9M/mwR6Z3w/os//pVTccBAAAAAIAB16eCrpTSXkp5USnlc6WUb5RSDm+Nz2iNz+7fmMBINvOEeUmSZVd+ObW3t+E0AAAAAAAwsDp29A2llIlJvp7kb5OsTTIxyYzW9OokZyc5P8m/9FNGYISbduRRmfLIIzPtMY9LenuTNpt7AQAAAAAYuXa4oEvyriRHJHl2kh8lWXzPRK21p5Ty5SRPi4IO2E6lvT0HvO+jTccAAAAAAIBB0ZdtKs9Ncl6t9bIkWzuLbmGSfXcmFAAAAAAAAIxUfdlBt2eS32xjfl2SKX2LA4xmm5YvzdJLv5Qyblz2eOHLmo4DAAAAAAADoi876JYnmb2N+YcmubNvcYDRbNPKlVky/8Is/coX0rNubdNxAAAAAABgQPSloPtWkpeUUibed6KUsl+Slyb52s4GA0afiXMOzKSDH5bedWuz8tprmo4DAAAAAAADoi8F3buTzEjysyT/lKQmObaU8oEkv0yyMckH+i0hMKrMPOGkJMnSyy9JrbXhNAAAAAAA0P92uKCrtS5M8uQk3Unek6QkeVOStyS5LcmTa6239WdIYPSYftQTM2bXmdl42y25+9c/bzoOAAAAAAD0u77soEut9Re11sOSPCzJPyR5XpJH1lofVmv9TX8GBEaX0tGRXZ/+rCTJ0svnN5wGAAAAAAD6X58KunvUWq+rtX6p1vrFWuuv+isUMLrtetyJKR1jsvqnP0zX0sVNxwEAAAAAgH7V0dc3llL+LslTk+ye5CO11j+VUiYneUSS39ZaV/VTRmCUGTNjl8x+5esyft8DMmbmbk3HAQAAAACAfrXDBV0ppT3JRUnmZfP952qSzyf5Uzbfl+7SJB9O8v7+iwmMNjOPf07TEQAAAAAAYED05YjLtyQ5Kckbkjwkm0u6JEmtdUOSryR5er+kA0jSu3Fj0xEAAAAAAKDf9KWge1GSz9Raz02ybCvzf0xywE6lAkjStWxpbvyXN+SGN7witdam4wAAAAAAQL/oS0G3b5Ifb2N+VZIZfUoDsIWOqdOy/sYbsuGmhVl73W+ajgMAAAAAAP2iLwXdmiS7bGN+TpKlfYsD8L/axo7NrsedkCRZevn8htMAAAAAAED/6EtB94MkLyyllPtOlFJmJHlpkm/vbDCAJNn16c9O2tvT+aPvpWvp4qbjAAAAAADATutLQXdWkrlJrk1yfGvssFLKK5P8MsmkJGf3TzxgtBs7c1amH/WEpLcny6+6tOk4AAAAAACw03a4oKu1/jzJSUn+Jsl/tYY/nOQTSSYkeXat9Q/9lhAY9WY+c16SZNlXL09v18aG0wAAAAAAwM7p6Mubaq1XlVL2TfKUJA9JUpIsSHJNrXVdv6UDSDLpoQ/LhP3nZsNtt2bdDX/K5EMOazoSAAAAAAD02Q4VdKWUyUkuT3JhrfU/k1zZegAMmFJKHvzGt2fMLjPTMX1G03EAAAAAAGCn7NARl7XWu5M8aoCyANyvCfvPVc4BAAAAADAi7PA96JL8OpuPtQQYdLWnO2v/9PumYwAAAAAAQJ/1paA7M8nLSylH93cYgG3p3bgxf3zZ87Lwzadl04rlTccBAAAAAIA+2aF70LW8MMmfk3yzlPKbJDckWXefa2qt9WU7Gw5gS23jxmXC/nPTtXhRln/1sjzoBS9tOhIAAAAAAOywvhR0/7jF84e3HvdVkyjogH4384R56fzx97Lsqkuz29+fkrYxY5qOBAAAAAAAO2SHj7istbZtx6N9IMICTD7sERm/z37pXrk8nT/8btNxAAAAAABgh/XlHnQAjSmlZOYzT0qSLLtifsNpAAAAAABgxynogGFnxpOelrZJk7P2D7/LuoXXNx0HAAAAAAB2yA7fg66Ucu0DXFKTrE/y5yRfT3JZrbX2IRvAVrVPmJhdn/qMdP74++nuXJVM3aXpSAAAAAAAsN12uKBLsn+SCUlmtV6vav2c3vq5NJt35j09ySuT/LCUclytde3OBAXY0qznvjBl/ITc+qF3p2d1Z343dVpmHv+c7Dbv5LRPmNh0PAAAAAAAuF99OeLyiUnWJfnXJLvXWnepte6SZPckH06yNskRSWYm+WiSxyV5Z7+kBUjSs35dbvrn12XpJRelZ3Xn5rHVnVky/8IseP0r0rN+XcMJAQAAAADg/vWloDsnyQ9rrW+ptS69Z7DWurTWekaSHyc5p9a6otb65iRXJTmpf+ICJEvmX5SNi+5I7er6i/Ha1ZWNi+7IkvkXNZQMAAAAAAAeWF8Kuicl+f425r/fuuYe30yyVx++B2Crll355b8q5+5Ru7qy7KqvDHIiAAAAAADYfn0p6JLkbx5grmzxujfJ+j5+D8Bf6VmzetvzrWMvAQAAAABgKOpLQffNJP9USnnefSdKKc9P8qok39hi+BFJbulTOoCtaJ8yddvzU6cNUhIAAAAAANhxfSno3pBkaZILSym3l1K+03rcnuRzSZYleWOSlFLGJ9knyWf6KzDAzOOfkzJ27P3OTznskYOYBgAAAAAAdswOF3S11luTHJbkI0lWJzmy9VjTGjusdU1qrRtqrU+qtZ7Tf5GB0W63eSdn3B6z/7qka2tPkqz64Xez4fY/N5AMAAAAAAAeWEdf3lRrXZHkjNYDYFC1T5iYueeclyXzL8qyq76SntWdaZ86Lbs+49npWbkiY2bOyrjZezcdEwAAAAAAtqpPBR1A09onTMwep5yaPU45NQsWLMjcuXOTJLXWlFLuve6+rwEAAAAAoGl9uQddSil7l1LOb92DrquU8qTW+KzW+KP6NybA9tmyjOtafFcWvOGVWX/rTQ0mAgAAAACAv7TDBV0pZb8kP09yUpLfJ2m/Z67WujTJEUlO7a+AAH21+OILsu5Pv8+Nb/s/2Xjn7U3HAQAAAACAJH3bQXdWkt4khyR5QZL7nh13dZLH7WQugJ02+1X/J5MPe0S6VyzPwn8+PV1LFzcdCQAAAAAA+lTQHZPk47XW25LUrczfmmSvnUoF0A/axo3Lfu88OxMPOjibltyVG//59GxauaLpWAAAAAAAjHJ9KeimJlm0jfmxSTr6Fgegf7VPnJT93/uRjN9/TjbecVtufPvr071mddOxAAAAAAAYxfpS0N2W5KHbmH9MkoV9iwPQ/zqmTM0BZ/1bxu29TzbcvDCdP/hO05EAAAAAABjF+lLQfTnJS0sph2wxVpOklHJSkucm+WI/ZAPoN2Omz8gB7z83e73mTdn1uBOajgMAAAAAwCjWl4LurCS3J/lpks9lczn31lLKj7O5mPtNko/0W0KAfjJ25qzMfMaz7329acXy9G7a1GAiAAAAAAAO38GJAAAgAElEQVRGox0u6Gqtq5M8NsmnkxyRpCR5SpKDknw8ydG11g39GRKgv2288/YseMMrc+sH35Xa0910HAAAAAAARpG+7KBLrXV1rfX0WuusJLsneVCSXWutr20VeABDWs+6dem+e006f/id/PmcD6T29jYdCQAAAACAUWKHC7pSyt+WUs4qpXyplHJNNu+ae22SI/s9HcAAmTjnwBzwng+nbfyErPzW13LHJ85JrbXpWAAAAAAAjAId23thKWVqks8nOTabj7W8r7eVUq5K8oJa65p+ygcwYCYdfGj2e+fZuenMN2fZlV9O2/gJ2eOl/5RStvZHHAAAAAAA9I8d2UE3P8lxSX6Y5CVJHplkbuvnS5L8KMnxSb7QzxkBBsyUw4/Ivm97b9LeniXzL8ziiy9oOhIAAAAAACPcdhV0pZSnJTkmyUdqrX9Xa72g1vqrWuuNrZ8X1Fofn+SjSZ5WSnnKQIYG6E/THvO47PPmdyZtbdn6BmEAAAAAAOg/23vE5fOT3JrkjAe47owkJyU5Ock3diIXwKCa8YRjMmHfAzJ+n/2ajgIAAAAAwAi3vUdcPjLJpbXWuq2Laq29SS5NcsTOBgMYbFuWcxsXL8qqH32vwTQAAAAAAIxU21vQzU5y/XZee32SvfoWB6B53as7s/BNp+WWs/4lnT/5ftNxAAAAAAAYYba3oJuaZM12XrsmyeS+xQFoXvuUqZlx9FOT3p7cctY7suZXP2s6EgAAAAAAI8j2FnRtSbZ5vGUfPxdgyCmlZI+XvCozn/mc1O5Nufndb83dv/9t07EAAAAAABghOnbg2qeXUh60Hdc9sq9h7lFKmZ7k00kOyeZi8KXZfHTmF5Lsm+SWJH9fa11ZSilJzk3y9CTrkvxjrfWXrc95cZJ/aX3s+2qtF7TGH5nkv5NMSHJ1ktMf6P56wOhSSsnsV70+vRs2ZMU3rs5N73xT5nzw3zNxzkFNRwMAAAAAYJjbkYLu5NZje+xs2XVukq/VWueVUsYmmZjkbUm+VWs9u5Ty1iRvTfKWJMclmdt6HJnkE0mOLKXskuTMJEe08vyilHJ5rXVl65qXJ/lpNhd0xyb56k5mBkaY0taWvU9/S3rWr0/nD76dG9/++jzkUxemY/qMpqMBAAAAADCMbW9Bd/SApthCKWVakr9L8o9JUmvtStJVSjkxyRNbl12Q5DvZXNCdmOQzrR1wPymlTC+l7NG69hu11hWtz/1GkmNLKd9JMrXW+pPW+GeSPCsKOmArSntH9jnjzNzStTGTDz1cOQcAAAAAwE7broKu1vrdgQ6yhf2SLE3yX6WUw5L8IsnpSXavtS5qXXNXkt1bz2cnuW2L99/eGtvW+O1bGQfYqrYxY7LfmR9MaXN7TQAAAAAAdl4ZardeK6UckeQnSY6qtf60lHJuktVJXltrnb7FdStrrTNKKVcmObvW+oPW+LeyeWfdE5OMr7W+rzX+jiTrs3nn3dm11mNa449P8pZa6/H3fHZnZ+e9v5QFCxYM5HKBYah36eJ0femzGXfKK1KmTG06DgAAAAAAQ9DcuXPvfT5t2rSy5dyO3INusNye5PZa609br+dn8/3mFpdS9qi1LmodYbmkNX9Hkr23eP9erbE78r9HYt4z/p3W+F5buX6rtvzlsW0LFiwYcb8vaxoeBntNN37mk1n/p+vS++mPZc4H/z0dA1DS+e80PFjT8GBNw8dIXJc1DQ/WNDxY0/BgTcODNQ0P1jQ8WNPwYE3DgzUNDyNxTU0Zcue11VrvSnJbKeWg1tCTk/whyeVJXtwae3GSy1rPL0/yorLZY5J0to7CvCbJU0spM0opM5I8Nck1rbnVpZTHlFJKkhdt8VkAD+jBb/yXjNvrwdlw88Lc9I43pmfd2qYjAQAAAAAwjAy5gq7ltUkuLKX8NsnDk7w/ydlJnlJKWZDkmNbrJLk6yU1JFib5jySnJUmtdUWS9yb5WevxntZYWtd8uvWeG5N8dRDWBIwQY6bPyAH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\n",
            "text/plain": [
              "<Figure size 1944x648 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Marker Annotation"
      ],
      "metadata": {
        "id": "bPe6JtNcKZ6u"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "top = 30\n",
        "top_nodes = sorted_degree[:top]\n",
        "\n",
        "mesh_nodes = list()\n",
        "degrees = list()\n",
        "\n",
        "for mesh_node, degree in top_nodes:\n",
        "  mesh_nodes.append(mesh_node)\n",
        "  degrees.append(degree)\n",
        "\n",
        "plt.style.use('fivethirtyeight')\n",
        "\n",
        "title_ = f\"Top {top} Nodes By Degree (Connection) In MeSH Terms Network Graph\"\n",
        "\n",
        "plt.rcParams['figure.figsize'] = [27, 9]\n",
        "\n",
        "plt.xticks(rotation=90)\n",
        "\n",
        "plt.plot(mesh_nodes, degrees, color='#c0392b', \n",
        "         marker='o', linestyle='dashed', \n",
        "         linewidth=2, markersize=8)\n",
        "\n",
        "plt.suptitle(f\"Based on {mesh_entries} Sars CoV-2 PubMed Articles Meta-data\", \n",
        "             fontsize=14)\n",
        "\n",
        "plt.title(title_, fontsize=22)\n",
        "\n",
        "plt.xticks(fontsize=12) \n",
        "\n",
        "plt.xlabel('MeSH Term (Node)', fontsize=18)\n",
        "\n",
        "plt.ylabel('Degree', fontsize=18)\n",
        "\n",
        "\n",
        "for x,y in zip(mesh_nodes, degrees):\n",
        "\n",
        "    label = (\"{:,}\".format(y))\n",
        "\n",
        "    plt.annotate(label, # this is the text\n",
        "                 (x,y), # these are the coordinates to position the label\n",
        "                 textcoords=\"offset points\", # how to position the text\n",
        "                 xytext=(0,10), # distance from text to points (x,y)\n",
        "                 ha='center') # horizontal alignment can be left, right or center\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 645
        },
        "id": "T5aGXMMbKZZ5",
        "outputId": "54e1b7f1-2ec9-4bb4-a854-14216e918244"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1944x648 with 1 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}