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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "gwRUTyfCE1i1"
+ },
+ "source": [
+ "# Topic Modeling with LDA"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fkBcAFY8FEl4"
+ },
+ "source": [
+ "## Requirements"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "T4zVqYJIAeyk",
+ "outputId": "0de7b496-7dfe-48e6-d528-5f9d980efe3a"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Requirement already satisfied: pyldavis in /usr/local/lib/python3.10/dist-packages (3.4.1)\n",
+ "Requirement already satisfied: numpy>=1.24.2 in /usr/local/lib/python3.10/dist-packages (from pyldavis) (1.26.4)\n",
+ "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from pyldavis) (1.11.4)\n",
+ "Requirement already satisfied: pandas>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from pyldavis) (2.2.0)\n",
+ "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from pyldavis) (1.3.2)\n",
+ "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from pyldavis) (3.1.3)\n",
+ "Requirement already satisfied: numexpr in /usr/local/lib/python3.10/dist-packages (from pyldavis) (2.9.0)\n",
+ "Requirement already satisfied: funcy in /usr/local/lib/python3.10/dist-packages (from pyldavis) (2.0)\n",
+ "Requirement already satisfied: scikit-learn>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from pyldavis) (1.2.2)\n",
+ "Requirement already satisfied: gensim in /usr/local/lib/python3.10/dist-packages (from pyldavis) (4.3.2)\n",
+ "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from pyldavis) (67.7.2)\n",
+ "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->pyldavis) (2.8.2)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->pyldavis) (2023.4)\n",
+ "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->pyldavis) (2023.4)\n",
+ "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=1.0.0->pyldavis) (3.2.0)\n",
+ "Requirement already satisfied: smart-open>=1.8.1 in /usr/local/lib/python3.10/dist-packages (from gensim->pyldavis) (6.4.0)\n",
+ "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->pyldavis) (2.1.4)\n",
+ "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas>=2.0.0->pyldavis) (1.16.0)\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install pyldavis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "PhkFwpioE2tP",
+ "outputId": "66c8d476-12d3-416e-fe15-dbbcc28400c7"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
+ "[nltk_data] Package stopwords is already up-to-date!\n",
+ "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
+ "[nltk_data] Package wordnet is already up-to-date!\n"
+ ]
+ }
+ ],
+ "source": [
+ "import nltk\n",
+ "nltk.download('stopwords')\n",
+ "nltk.download('wordnet')\n",
+ "from nltk.corpus import stopwords\n",
+ "from nltk.stem.wordnet import WordNetLemmatizer\n",
+ "import string\n",
+ "import pandas as pd\n",
+ "from google.colab import files\n",
+ "\n",
+ "import pyLDAvis\n",
+ "import pyLDAvis.gensim\n",
+ "pyLDAvis.enable_notebook()\n",
+ "\n",
+ "import gensim\n",
+ "from gensim import corpora\n",
+ "from collections import Counter\n",
+ "from matplotlib import pyplot as plt\n",
+ "from wordcloud import WordCloud, STOPWORDS\n",
+ "import matplotlib.colors as mcolors"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "j4gu7UQrFH77"
+ },
+ "source": [
+ "## Data Loading"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "m72W2i0HFNnO",
+ "outputId": "cf9d0197-8a7d-4feb-ac4f-6b213c71427b"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Loading complete data per speech\n",
+ "all_data_speeches = pd.read_excel('all_data+sent_per_speech.xlsx') # 82165 rows x 29 columns"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "gtNWY8g_lqnw",
+ "outputId": "11ce1a2b-77c4-4494-82f8-a019ef04d28c"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Loading complete data with SV\n",
+ "all_data_speeches_SV = pd.read_excel(\"Sexual violence speeches.xlsx\")# 5016 rows × 33 columns"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fhrli6q2FFwG"
+ },
+ "source": [
+ "## LDA Modeling"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fjDCuOc4mkqO"
+ },
+ "source": [
+ "### Data Pre-processing"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "tkw6A9Aimmpo",
+ "outputId": "81a47bd9-714a-4e7f-d6bd-0d879c05b35f"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Setting stop words, punctuation marks and lemmatizer\n",
+ "stop_words = set(stopwords.words('english'))\n",
+ "exclude_PM = set(string.punctuation)\n",
+ "lemmatizer = WordNetLemmatizer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "WRLfs4-2mr04",
+ "outputId": "1ee2f77e-65c4-4b7d-b222-d0b887f16a0c"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Pre-processing function\n",
+ "def pre_processing (text):\n",
+ "\n",
+ " # Removing stop words\n",
+ " stopwords_removed = \" \".join([i for i in text.lower().split() if i not in stop_words])\n",
+ "\n",
+ " # Removing puntuation marks\n",
+ " punctMarks_removed = ''.join(ch for ch in stopwords_removed if ch not in exclude_PM)\n",
+ "\n",
+ " # Lemmatizing\n",
+ " lemmatized_text = \" \".join(lemmatizer.lemmatize(word) for word in punctMarks_removed.split())\n",
+ "\n",
+ " return lemmatized_text"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "FTns8t3imuUy",
+ "outputId": "bd244a26-8464-476f-a3f3-6c43c08eeb6e"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Pre-processing all data speeches\n",
+ "all_data_speeches_preprocessed = [pre_processing(doc).split() for doc in all_data_speeches['text']]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "2dLXFXmQnDRh",
+ "outputId": "aa25b99a-e314-4f2b-e888-11f199793595"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Pre-processing all data only with SV mentions\n",
+ "all_data_speeches_SV_preprocessed = [pre_processing(doc).split() for doc in all_data_speeches_SV['text']]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "rpoTX-_3nYv3"
+ },
+ "source": [
+ "### Creating Dictionary and Document Term-Matrix of the Corpus"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "hQSE3j4AoXHL"
+ },
+ "source": [
+ "#### Dictionary and Document Term Matrix for complete data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "ohDT4oFbnUEr",
+ "outputId": "472f4896-381f-455f-fb95-1aebd5078a05"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Creating term dictionary for complete corpus - all data speeches\n",
+ "dictionary_unsc_speeches = corpora.Dictionary(all_data_speeches_preprocessed)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "p1PEXN7DnsgG",
+ "outputId": "4339e810-7437-4c69-c738-e6c1bd2ddb8d"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Creating Document Term Matrix of complete corpus - all data speeches\n",
+ "doc_term_matrix_unsc_speeches = [dictionary_unsc_speeches.doc2bow(text) for text in all_data_speeches_preprocessed]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "8mjfBFt9ocPW"
+ },
+ "source": [
+ "#### Dictionary and Document Term Matrix for SV data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "miYr7xq-ofxH",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "69f94aa9-21a2-4648-96bb-511e410f930c"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Creating term dictionary for speeches with SV mentions\n",
+ "dictionary_unsc_SV = corpora.Dictionary(all_data_speeches_SV_preprocessed)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "01PIusd3osmt",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "b35f8dad-355d-4e2a-8e56-4665a3daae3f"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Creating Document Term Matrix of speeches with SV mentions\n",
+ "doc_term_matrix_unsc_SV = [dictionary_unsc_SV.doc2bow(text) for text in all_data_speeches_SV_preprocessed]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "UJk056i8oCsi"
+ },
+ "source": [
+ "### Loading and Running LDA Model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "NfTeVpPVoFEX",
+ "outputId": "56a9d211-66aa-4482-f953-b52edc01a05e"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Creating LDA object\n",
+ "Lda = gensim.models.ldamodel.LdaModel"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Z3n1jOFmv28N"
+ },
+ "source": [
+ "#### LDA for Data Complete all speeches"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "YiAkFXGooG-g",
+ "outputId": "8c535d1d-76dd-4b2b-e844-47c350c9bf39"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Running and Trainign LDA model on the document term matrix for complete data set - all speeches\n",
+ "# Only 3 topics\n",
+ "ldamodel_allSpeeches_3 = Lda(corpus=doc_term_matrix_unsc_speeches,\n",
+ " num_topics=3,\n",
+ " id2word = dictionary_unsc_speeches,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "MB2m_56QvT1c",
+ "outputId": "97ec003a-150e-4634-c723-0af2ce6be8f7"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Only 5 topics\n",
+ "ldamodel_allSpeeches_5 = Lda(corpus=doc_term_matrix_unsc_speeches,\n",
+ " num_topics=5,\n",
+ " id2word = dictionary_unsc_speeches,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "2x6wxZw0vVtB",
+ "outputId": "f23510d3-e4ee-43f6-bc04-c127c668f836"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Only 10 topics\n",
+ "ldamodel_allSpeeches_10 = Lda(corpus=doc_term_matrix_unsc_speeches,\n",
+ " num_topics=10,\n",
+ " id2word = dictionary_unsc_speeches,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "66LXkYxhv7kk"
+ },
+ "source": [
+ "#### LDA for Data SV Mentions"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "0hv3At6YpJ4h",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "5aa0fe21-453c-44a9-9f61-fec7cb6fd34f"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Running and Trainign LDA model on the document term matrix for complete data set - all speeches\n",
+ "# Only 3 topics\n",
+ "ldamodel_SV_3 = Lda(corpus=doc_term_matrix_unsc_SV,\n",
+ " num_topics=3,\n",
+ " id2word = dictionary_unsc_SV,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Nhfoo91_vbNQ",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "8406ec95-a5c7-4bce-d868-1191f4f8c74e"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Only 5 topics\n",
+ "ldamodel_SV_5 = Lda(corpus=doc_term_matrix_unsc_SV,\n",
+ " num_topics=5,\n",
+ " id2word = dictionary_unsc_SV,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "KcB99LmVvc85",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "dc4aae11-542e-464e-fbb2-672138047520"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Only 10 topics\n",
+ "ldamodel_SV_10 = Lda(corpus=doc_term_matrix_unsc_SV,\n",
+ " num_topics=10,\n",
+ " id2word = dictionary_unsc_SV,\n",
+ " passes=10)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "3HsAczFSpYI0"
+ },
+ "source": [
+ "### LDA Results "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "i-1FI5ZvzYVW"
+ },
+ "source": [
+ "#### Results for LDA with all data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "mnGo-OPFpWiM",
+ "outputId": "2a453d29-29fe-4219-e1f0-fb5147dfa999"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "3 Topic Models for Complete Data\n",
+ "[(0, '0.009*\"international\" + 0.008*\"humanitarian\" + 0.008*\"council\" + 0.007*\"people\" + 0.007*\"united\"'), (1, '0.012*\"security\" + 0.010*\"peace\" + 0.010*\"united\" + 0.010*\"nation\" + 0.008*\"country\"'), (2, '0.042*\"council\" + 0.028*\"president\" + 0.023*\"sudan\" + 0.020*\"representative\" + 0.019*\"republic\"')]\n",
+ " \n",
+ "5 Topic Models for Complete Data\n",
+ "[(0, '0.011*\"peace\" + 0.011*\"security\" + 0.010*\"country\" + 0.010*\"support\" + 0.009*\"united\"'), (1, '0.013*\"security\" + 0.012*\"conflict\" + 0.011*\"woman\" + 0.011*\"united\" + 0.011*\"nation\"'), (2, '0.011*\"humanitarian\" + 0.010*\"people\" + 0.009*\"international\" + 0.008*\"united\" + 0.007*\"council\"'), (3, '0.059*\"council\" + 0.037*\"president\" + 0.025*\"representative\" + 0.021*\"security\" + 0.020*\"give\"'), (4, '0.011*\"council\" + 0.008*\"international\" + 0.007*\"would\" + 0.006*\"also\" + 0.006*\"work\"')]\n",
+ " \n",
+ "10 Topic Models for Complete Data\n",
+ "[(0, '0.019*\"council\" + 0.014*\"state\" + 0.013*\"resolution\" + 0.011*\"security\" + 0.011*\"weapon\"'), (1, '0.010*\"government\" + 0.009*\"afghanistan\" + 0.009*\"support\" + 0.008*\"election\" + 0.007*\"also\"'), (2, '0.018*\"child\" + 0.018*\"conflict\" + 0.015*\"humanitarian\" + 0.015*\"civilian\" + 0.014*\"international\"'), (3, '0.079*\"council\" + 0.035*\"security\" + 0.028*\"mr\" + 0.023*\"rule\" + 0.023*\"meeting\"'), (4, '0.069*\"president\" + 0.063*\"representative\" + 0.058*\"iraq\" + 0.056*\"give\" + 0.054*\"libya\"'), (5, '0.013*\"people\" + 0.009*\"humanitarian\" + 0.009*\"syrian\" + 0.009*\"international\" + 0.009*\"syria\"'), (6, '0.018*\"peace\" + 0.018*\"united\" + 0.017*\"nation\" + 0.017*\"security\" + 0.013*\"woman\"'), (7, '0.019*\"region\" + 0.018*\"country\" + 0.017*\"mali\" + 0.013*\"state\" + 0.012*\"regional\"'), (8, '0.013*\"republic\" + 0.013*\"peace\" + 0.012*\"african\" + 0.011*\"security\" + 0.011*\"support\"'), (9, '0.053*\"russian\" + 0.037*\"resolution\" + 0.035*\"council\" + 0.030*\"haiti\" + 0.027*\"draft\"')]\n",
+ " \n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# LDA for Complete Data all speeches\n",
+ "print(\"3 Topic Models for Complete Data\")\n",
+ "results_3_top_Alldata = ldamodel_allSpeeches_3.print_topics(num_topics=3, num_words=5)\n",
+ "print(ldamodel_allSpeeches_3.print_topics(num_topics=3, num_words=5))\n",
+ "print(\" \")\n",
+ "\n",
+ "print(\"5 Topic Models for Complete Data\")\n",
+ "print(ldamodel_allSpeeches_5.print_topics(num_topics=5, num_words=5))\n",
+ "print(\" \")\n",
+ "\n",
+ "print(\"10 Topic Models for Complete Data\")\n",
+ "print(ldamodel_allSpeeches_10.print_topics(num_topics=10, num_words=5))\n",
+ "print(\" \")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fcIe3XMdzbX9"
+ },
+ "source": [
+ "#### Results for LDA with SV data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "lZrZiyHrzeBw",
+ "outputId": "cbf0067b-ff7b-4bfd-aeff-d0690954dabf"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "3 Topic Models for SV Data\n",
+ "[(0, '0.022*\"child\" + 0.015*\"conflict\" + 0.012*\"armed\" + 0.010*\"international\" + 0.009*\"council\"'), (1, '0.029*\"woman\" + 0.018*\"violence\" + 0.016*\"sexual\" + 0.014*\"peace\" + 0.013*\"security\"'), (2, '0.007*\"government\" + 0.007*\"council\" + 0.007*\"security\" + 0.007*\"united\" + 0.006*\"also\"')]\n",
+ " \n",
+ "5 Topic Models for SV Data\n",
+ "[(0, '0.011*\"security\" + 0.010*\"united\" + 0.010*\"nation\" + 0.009*\"republic\" + 0.009*\"country\"'), (1, '0.011*\"sudan\" + 0.009*\"council\" + 0.008*\"south\" + 0.007*\"government\" + 0.006*\"crime\"'), (2, '0.018*\"conflict\" + 0.017*\"civilian\" + 0.016*\"international\" + 0.014*\"council\" + 0.014*\"humanitarian\"'), (3, '0.034*\"child\" + 0.011*\"conflict\" + 0.009*\"armed\" + 0.006*\"council\" + 0.006*\"group\"'), (4, '0.037*\"woman\" + 0.021*\"violence\" + 0.020*\"sexual\" + 0.016*\"peace\" + 0.014*\"conflict\"')]\n",
+ " \n",
+ "10 Topic Models for SV Data\n",
+ "[(0, '0.018*\"crime\" + 0.016*\"court\" + 0.016*\"international\" + 0.014*\"council\" + 0.011*\"justice\"'), (1, '0.028*\"republic\" + 0.022*\"democratic\" + 0.021*\"congo\" + 0.009*\"security\" + 0.009*\"country\"'), (2, '0.046*\"woman\" + 0.016*\"violence\" + 0.013*\"peace\" + 0.012*\"girl\" + 0.009*\"right\"'), (3, '0.071*\"child\" + 0.027*\"conflict\" + 0.026*\"armed\" + 0.009*\"group\" + 0.009*\"council\"'), (4, '0.048*\"woman\" + 0.024*\"peace\" + 0.019*\"security\" + 0.014*\"conflict\" + 0.013*\"resolution\"'), (5, '0.039*\"violence\" + 0.039*\"sexual\" + 0.016*\"conflict\" + 0.011*\"crime\" + 0.009*\"council\"'), (6, '0.014*\"united\" + 0.013*\"nation\" + 0.011*\"security\" + 0.009*\"support\" + 0.009*\"country\"'), (7, '0.017*\"sudan\" + 0.013*\"south\" + 0.010*\"humanitarian\" + 0.009*\"government\" + 0.008*\"people\"'), (8, '0.010*\"kosovo\" + 0.010*\"people\" + 0.008*\"council\" + 0.007*\"united\" + 0.006*\"one\"'), (9, '0.024*\"civilian\" + 0.019*\"conflict\" + 0.019*\"international\" + 0.018*\"humanitarian\" + 0.017*\"protection\"')]\n",
+ " \n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# LDA for Complete Data all speeches\n",
+ "print(\"3 Topic Models for SV Data\")\n",
+ "print(ldamodel_SV_3.print_topics(num_topics=3, num_words=5))\n",
+ "print(\" \")\n",
+ "\n",
+ "print(\"5 Topic Models for SV Data\")\n",
+ "print(ldamodel_SV_5.print_topics(num_topics=5, num_words=5))\n",
+ "print(\" \")\n",
+ "\n",
+ "print(\"10 Topic Models for SV Data\")\n",
+ "print(ldamodel_SV_10.print_topics(num_topics=10, num_words=5))\n",
+ "print(\" \")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "m8-YMkRHvIpx"
+ },
+ "source": [
+ "## LDA Results - Visualizations"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "### Word counts per topic keywords for 3-TOPIC-MODEL"
+ ],
+ "metadata": {
+ "id": "_ho_BUraOe2I"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "topics = ldamodel_allSpeeches_3.show_topics(formatted=False)\n",
+ "data_flat = [w for w_list in all_data_speeches_preprocessed for w in w_list]\n",
+ "counter = Counter(data_flat)\n",
+ "\n",
+ "out = []\n",
+ "for i, topic in topics:\n",
+ " for word, weight in topic:\n",
+ " out.append([word, i , weight, counter[word]])\n",
+ "\n",
+ "df_all_data_3topics = pd.DataFrame(out, columns=['word', 'topic_id', 'importance', 'word_count'])\n",
+ "\n",
+ "# Plot Word Count and Weights of Topic Keywords\n",
+ "fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12,4))\n",
+ "cols = [color for name, color in mcolors.TABLEAU_COLORS.items()]\n",
+ "for i, ax in enumerate(axes.flatten()):\n",
+ " ax.bar(x='word', height=\"word_count\", data=df_all_data_3topics.loc[df_all_data_3topics.topic_id==i, :], color=cols[i], width=0.5, alpha=0.3, label='Word Count')\n",
+ " ax_twin = ax.twinx()\n",
+ " ax_twin.bar(x='word', height=\"importance\", data=df_all_data_3topics.loc[df_all_data_3topics.topic_id==i, :], color=cols[i], width=0.2, label='Weights')\n",
+ " ax.set_ylabel('Word Count', color=cols[i])\n",
+ " ax_twin.set_ylim(0, 0.030); ax.set_ylim(0, 3500)\n",
+ " ax.set_title('Topic: ' + str(i+1), color=cols[i], fontsize=16)\n",
+ " ax.tick_params(axis='y', left=False)\n",
+ " ax.set_xticklabels(df_all_data_3topics.loc[df_all_data_3topics.topic_id==i, 'word'], rotation=30, horizontalalignment= 'right')\n",
+ " ax.legend(loc='upper left'); ax_twin.legend(loc='upper right')\n",
+ "\n",
+ "fig.tight_layout(w_pad=2)\n",
+ "fig.suptitle('Word Count and Importance of Topic Keywords for all Data', fontsize=22, y=1.05)\n",
+ "plt.show()\n",
+ "plt.savefig('word count all data 3 topics.png')"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 549
+ },
+ "id": "Ncmd8x0iOh16",
+ "outputId": "f7d21555-6a16-4d7d-d962-73b53f0cb340"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "<ipython-input-110-59370f808239>:24: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+ " ax.set_xticklabels(df_all_data_3topics.loc[df_all_data_3topics.topic_id==i, 'word'], rotation=30, horizontalalignment= 'right')\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1200x400 with 6 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 0 Axes>"
+ ]
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "topics = ldamodel_SV_3.show_topics(formatted=False)\n",
+ "data_flat = [w for w_list in all_data_speeches_preprocessed for w in w_list]\n",
+ "counter = Counter(data_flat)\n",
+ "\n",
+ "out = []\n",
+ "for i, topic in topics:\n",
+ " for word, weight in topic:\n",
+ " out.append([word, i , weight, counter[word]])\n",
+ "\n",
+ "df_SV_data_3topics = pd.DataFrame(out, columns=['word', 'topic_id', 'importance', 'word_count'])\n",
+ "\n",
+ "# Plot Word Count and Weights of Topic Keywords\n",
+ "fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12,4))\n",
+ "cols = [color for name, color in mcolors.TABLEAU_COLORS.items()]\n",
+ "for i, ax in enumerate(axes.flatten()):\n",
+ " ax.bar(x='word', height=\"word_count\", data=df_SV_data_3topics.loc[df_SV_data_3topics.topic_id==i, :], color=cols[i], width=0.5, alpha=0.3, label='Word Count')\n",
+ " ax_twin = ax.twinx()\n",
+ " ax_twin.bar(x='word', height=\"importance\", data=df_SV_data_3topics.loc[df_SV_data_3topics.topic_id==i, :], color=cols[i], width=0.2, label='Weights')\n",
+ " ax.set_ylabel('Word Count', color=cols[i])\n",
+ " ax_twin.set_ylim(0, 0.030); ax.set_ylim(0, 3500)\n",
+ " ax.set_title('Topic: ' + str(i+1), color=cols[i], fontsize=16)\n",
+ " ax.tick_params(axis='y', left=False)\n",
+ " ax.set_xticklabels(df_SV_data_3topics.loc[df_SV_data_3topics.topic_id==i, 'word'], rotation=30, horizontalalignment= 'right')\n",
+ " ax.legend(loc='upper left'); ax_twin.legend(loc='upper right')\n",
+ "\n",
+ "fig.tight_layout(w_pad=2)\n",
+ "fig.suptitle('Word Count and Importance of Topic Keywords for SV Data', fontsize=22, y=1.05)\n",
+ "plt.show()\n",
+ "plt.savefig('word count SV data 3 topics.png')"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 549
+ },
+ "id": "YteZ5Q0PQrbS",
+ "outputId": "2c613845-6e1e-4052-e913-6a93fc9cc637"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "<ipython-input-113-d41a81060662>:23: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+ " ax.set_xticklabels(df_SV_data_3topics.loc[df_SV_data_3topics.topic_id==i, 'word'], rotation=30, horizontalalignment= 'right')\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1200x400 with 6 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 0 Axes>"
+ ]
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "### Word Clouds per topic visualization"
+ ],
+ "metadata": {
+ "id": "uo3CWzhAJU4k"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "cols = [color for name, color in mcolors.TABLEAU_COLORS.items()] # more colors: 'mcolors.XKCD_COLORS'\n",
+ "\n",
+ "cloud = WordCloud(stopwords=stop_words,\n",
+ " background_color='white',\n",
+ " width=2500,\n",
+ " height=1800,\n",
+ " max_words=5,\n",
+ " colormap='tab10',\n",
+ " color_func=lambda *args, **kwargs: cols[i],\n",
+ " prefer_horizontal=1.0)\n",
+ "\n",
+ "topics_3_allData = ldamodel_allSpeeches_3.show_topics(formatted=False)\n",
+ "\n",
+ "\n",
+ "\n"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "_2M8v6AeJabm",
+ "outputId": "3a15032f-0db1-49d0-b017-bc0a9a322fd3"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "3\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12,4))\n",
+ "\n",
+ "for i, ax in enumerate(axes.flatten()):\n",
+ " fig.add_subplot(ax)\n",
+ " topic_words = dict(topics_3_allData[i][1])\n",
+ " cloud.generate_from_frequencies(topic_words, max_font_size=300)\n",
+ " plt.gca().imshow(cloud)\n",
+ " plt.gca().set_title('Topic ' + str(i+1) + \" for all data\", fontdict=dict(size=16))\n",
+ " plt.gca().axis('off')\n",
+ "\n",
+ "\n",
+ "plt.subplots_adjust(wspace=0, hspace=0)\n",
+ "plt.axis('off')\n",
+ "plt.margins(x=0, y=0)\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "plt.savefig('5 words for 3 topics all Data.png')"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 406
+ },
+ "id": "VfmGyU0OJ2BP",
+ "outputId": "3733fc65-3418-4c98-8f91-254170c99dd3"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1200x400 with 3 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 0 Axes>"
+ ]
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "topics_3_SVdata = ldamodel_SV_3.show_topics(formatted=False)\n",
+ "fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12,4))\n",
+ "\n",
+ "for i, ax in enumerate(axes.flatten()):\n",
+ " fig.add_subplot(ax)\n",
+ " topic_words = dict(topics_3_SVdata[i][1])\n",
+ " cloud.generate_from_frequencies(topic_words, max_font_size=300)\n",
+ " plt.gca().imshow(cloud)\n",
+ " plt.gca().set_title('Topic ' + str(i+1) + \" for SV data\", fontdict=dict(size=16))\n",
+ " plt.gca().axis('off')\n",
+ "\n",
+ "\n",
+ "plt.subplots_adjust(wspace=0, hspace=0)\n",
+ "plt.axis('off')\n",
+ "plt.margins(x=0, y=0)\n",
+ "plt.tight_layout()\n",
+ "plt.show()\n",
+ "plt.savefig('5 words for 3 topics SV Data.png')"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 406
+ },
+ "id": "_AcTO1OcMSvL",
+ "outputId": "724dc90d-758c-4d10-ae5c-3b9f3b01b1df"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 1200x400 with 3 Axes>"
+ ],
+ "image/png": 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P+7NgwQIAnnnmGSKRSJvnH3/88XZfV1lZCcDw4cPbPKe15umnn273dW63G4BoNNru803fiqSkpJCWltbm+SeffFK+yRCiC8fyteKjjz7inHPOiQdS9957b5+02x65VjSTa4UQx55j+VrRmTfffBOAcePG9Ul7cq1oJtcK0SuHuZC66KHOlm7Nz8/XgP5//+//6UgkEn9u165deuTIkZoulm499dRTdWVlZfy56upqPW/ePA3oq666qtXrOlu6dfr06RrQ5513ni4vL2/1fCAQ0EuWLOn18R/O1fdaLt26Zs2a+OO2bcdXnOhs6daerBjR0kknnaQfeuihVsvnNikqKtIXX3xx/Jy3fH9bCgQCOi0tTQM6OztbA/qXv/zlIfWnoaFBDx06VAP661//eqvlUtevXx9v/+Bj/s9//qMBnZeXpw8cOBB/PBqN6rvuuiv+mgULFrTaXzgc1m63WzscjnbPQTQa1enp6RrQjz/+eKvnli1bFn+uN++BEMeK4+1a8fHHH+vU1NR2+94bcq3omlwrhDh6HW/XigceeEDv3bu3zeN+v1//+Mc/1oB2Op16/fr13W5Ta7lWdIdcK0RvSCg1wHR08dBa648++khnZGTE/4G55ppr9Pnnn6+9Xq8G9DnnnNNmWc+mi8fFF1+sR40apdPS0vRll12mL7/88nhbY8eO1SUlJa1e19kym7t379bjx4/XgE5ISNBnn322vu666/T8+fN1ampqj5fmvPTSS/Xs2bP17Nmz9cSJEzWgPR5P/LHZs2frP//5zz1qs7OLh23b+rOf/Wz8wrRw4UJ93XXXxY/J5/O1ewHs7cWj6Q8qh8Ohp02bpq+44gp9zTXX6NNOO027XC4N6IyMDL1s2bJO27nlllvix+dyudpc5HrinXfe0QkJCfEg8Nprr9WLFi3SLpdLX3755e0ecyQS0TNnztSATkpK0hdccIG++uqr9fDhw7XL5dLf/va32714aK31lVdeqcEsF3vdddfpm2++Wd98883x51suFzt79mx93XXX6blz52qllP7sZz/b6/dAiGPF8XataPrwmJaWphcvXtzhbfPmzd1uU2u5VnSXXCuEODodb9eK4cOHa6WUnjRpkr7sssv0ddddp08//fT4NcTj8bQJKLpDrhXdI9cKcagklBpgOrt4aK313r179a233qpHjRql3W63Tk5O1nPmzNF/+MMf2k3Bmy4eixcv1qWlpfqLX/yizsvL0263Ww8bNkzfdttt7abLnV08tNa6rq5O33fffXrWrFk6OTlZezwePXz4cH3xxRfrf/zjHz065qZ/EDq73X333T1qs7Nz2OTpp5/Wp59+uk5LS9Mul0sPGzZM33DDDXrLli2d9vNQ/+Fav369fuCBB/RFF12kJ0yYoNPS0rTT6dQZGRn61FNP1T/60Y90WVlZl+2sWrUqfnyXX375IfXl4H41fZjweDx64sSJ+mc/+5mORCIdHnNdXZ2+88479fjx47XX69U5OTn60ksv1StXroz/Drd38aioqNBf/OIXdX5+fvyCefD79Pzzz+tTTz1Vp6Wl6aSkJH3SSSfp3//+99q2bbl4CNHoeLtWdHWNaLq9/fbb3W6zZbudkWtFc7/kWiHE0eV4u1Y89dRTevHixXry5Mk6MzNTOxwOnZKSoqdPn66/8Y1v6J07d3a7rZbkWtGzfsm1QvSU0lomUx7LHnvsMW688UYWL17c7lxnIYQQQq4VQgghuiLXCiHE4SCFzoUQQgghhBBCCCFEv5NQSgghhBBCCCGEEEL0OwmlhBBCCCGEEEIIIUS/k5pSQgghhBBCCCGEEKLfyUgpIYQQQgghhBBCCNHvJJQSQgghhBBCCCGEEP1OQikhhBBCCCGEEEII0e8klBJCCCGEEEIIIYQQ/U5CKSGEEEIIIYQQQgjR7ySUEkIIIYQQQgghhBD9TkIpIYQQQgghhBBCCNHvJJQSQgghhBBCCCGEEP1OQikhhBBCCCGEEEII0e8klBJCCCGEEEIIIYQQ/c55pDsghBBCiAFOa6gqgGBN+88rB2SPB6enf/slhBBCCCGOakprrY90J4QQQggxgGkbnr0Btr7c/vOeZPj825A+vF+7JYQQQgghjm4yUkoIIYQQXfOkmPApGoRYBOyoCasAYmFAvuMSQgghhBA9IyOlhBBCCNE5rSFcD6FaCDdAsBbKt8FLd0AkYMKqL70P6SOOdE+FEEIIIcRRREZKCSGEEKJzSpngyZPc/FhCOljyMUIIIYQQQhw6WX1PCCGEEEIIIYQQQvQ7CaWEEEIIIYQQQgghRL+TcfdCCCEGlnipw6b/VY3/owZWm0eL4/nYhRBCCCHEgCahlBBCiCOvqZD2/k+gcAVU7oJgjXnOkwypwyB3Egw+EVLzweHqOlTR2tyqd8Oud6FoDdSXgrIgeRAMnQkj50PKEPNYR22Ub4PaA+a+y2te53B3vl9/KZRuNj8ry/Tbl9Z6m+J10FBp7mePN/3oTKAaitaaFe9cPsg7qf2aTloDGhoqoHi9OaeVO83rAbypkD4Shs0yx+JJkYBKCCGEEEIcERJKCSGEOLJsG3a8Ae/8FIo3gB3pYEMF3hQTpFzwK8gY2XGbWkOgCj54EFY/BQ3lbbf5+BFIGQyzvwSzPgeuhPbDmfoS+NeNJiRzuOGiB2HqtR0HOZEGePF22PaKuT9iHlzzxEH9s+GNH8Kud8z9Cx+EmYs7Ph6A0k3w1JVgRyFjFHzhndaFx5uOu3QzrPwLbHsN6orM9u2xnJAzCRb+AMYs7DiYE0IIIYQQ4jCRT6BCCCGOHK1hy//g3zfDgdUmkHJ6zaihzDGQPgJ8Tau8aRMMVe4CT1LnbdaXmDY/+I0JpJQFCRkmzEkf0RjmaDMC6o0fwcvfNmHSwZSC4XPh1K8ACqJBePPHUL61xbS4lvu2YeWjsO1V83PSIDj3p2Y0Unv91La50U5bbV/QvL22O96s4D34+FGoKTSBlMMFCVkmxMsYCd40cyx21IzW+s8XYM+y9o9HCCGEEEKIw0hGSgkhhDhygjXwzs8gVGuCoxOuhJO/BOnDwekx4Uuw1kw/2/0+bH8dxpxpQpaOREPw6p2w8y1zP3MMzPsajJhvpq6hoa4Y1j8Ly/9gpg2uedqEVfO+1nbEkOUwo6n2rYStS6B2P7x2F1z5WOtwTGso/BiW/hJ0zPT/rLshZ3L/TY9TCiZdDB89bIKw8efByHlmup67sa+BStj8oulnoMrcf/+XkDcLnJ1MSxRCCCGEEKKPSSglhBDiyKncCRU7zc/Z4+G8+01w1DLE8aZC2jAYuQBOu6PzET1aw9aXYNN/zf2MUXDt05A1rm2bp38XknLhle+YUUMr/giTL4PM0W3bdSXAOfdC2RYzUmvHm/DRn+C0202IpRtrOL36XRP0oGDGYphyRf/Xa0oeDJ96xkxNdCWax1odewrMuRXcifDSN0yAtm+VCds6mxIphBBCCCFEH5Ppe0IIIY6csL+55pE3Fdwd1HUC87g70YxO6mibaAg++ouZBqgsE2IdHEg1sRxw4rWQPdHc95eZqYTthV5KmdFGZ99rAiptwwe/hr3LzfZ2DJb+whQVBzPqaMG32y9EfrgpBVljzcgopdo/dmXBxIubi6uH66F2X//2UwghhBBCHPcklBJCCHHkJOWaIApMkfNtr5mQ6lDrG1XuhOK15ueELBhzVucjldxJkD+7+X7BUjNyqD1Kwbiz4ZQvmVAnWG2mCfrLzLS+lY8BGhKz4bz7ICFzYK9q500xo6rAhGqh+iPbHyGEEEIIcdyRUOooprVucxNCiKNK+khT6wnMaJ3nvgj/vQ0KP4JIsGfhlNamcHe4sWB5Wr4ZfRWLdHyzo5Ca19xG9R5TzLwjlhPm3m6mEgIcWANLvgmvfx+iAbM635l3wZDpAyuQ0rr5Zscagz8bHM7W2wghhBBCCNGPpKbUUe7PSwvYeKAGgE/PzufkkZlHuEdCCNEDDhcs+pGZOla0trHo+FOw4T8m2Jl8GYw7xwRHyuo66KnYSXwlu/Jt8LeLu35NfUnzz2G/Cas640mBc38GT15h6jBter75uanXwInXHflASmszhbF6LxSvh7JtUHfAFI2PBsw0x0gASjYc2X4KIYQQQojjmoRSRzENLN9VwVtbSgGYNzabk6VGrRDiaKKUWR3vU8/A8t/Dmr+Dv9QEJ3s/hL3L4L37YcL5cNLNkDu583CqobL551At7F/Zs/5obUYQddXn7Amw8Afwwq3NNbFyJppRUo4jvIJdLAq73jaF2/d9bIIoZBSUEEIIIYQYeCSUEkIIcWQpBcmD4KwfwswbYN2zsPE/ULHDBD7+Ulj1GGx8HmbdbFa8cye3H0w1BUQAvoyeryaXmN3N4uQagjWtp7xFgp1P/eut7uRKsTAs/RV88KAZCQWmblbWGMgcC8lDTC0pdyI4PfDBb6Cq4PD1WQghhBBCiE5IKCWEEGJgUBZkjIIF3zLFxPeugHX/gB1vmAAoWA3vP2Cm213wKxOqHMyT1Pzz8Dlw5V97OJVOdR1KaQ37VsK79zUWRVeANuHOa3fBZX9qLt7el2Lhzus+aQ1bXjKhVCwEygFTr4I5XzGj0VqeL6VMe2uellBKCCGEEEIcMVLoXIjjVFNx/JjdsyL5Ta+Jxux2b1JwX/SaUqZA+dhFcPmf4IaXYNIlJrTSNqx7Bna/335Ak5rf/HNdY60oh7sHN1fnIZbWZrW9l78NDRVm25mLzXQ+gC1L4OM/dz0FsKe0hobyztu1I7DyryaQAhh/Llz4gJny6PKavjbdmtpsObJMCCGEEEKIfiYjpYQ4TkVimj+8s5OPd1dy4dTBXD1rGFY3R5Q88n4Br28qbvO407L40SWTGZeb3NfdFccjpUA5IXcKXPJ7CNXDzjfNCJ9db8PoM9tuP3iqCZdiYTMCqK4Y0of3XZ/sCLx9LxxYbe4Pnwtn/Qj2r4JnrjeF2pf+EobMgBGndR5wWY7mn6ONKw12tn3pZjqdwxesMcXdAVCm6LrT13GbYT/4yztuTwghhBBCiMNMRkoJcZwqKPfz8Hs7eX9HOb99awe1gS5WHGuhqCbAun01fLK3mpW7q/i46bankvqQjLwQfUwpUwNp5PzmxwJV7W+bOxkyRpufGyrNynh9NXpPa1Pvas3TgIbEHDjnp2ZU16jT4ZRbzGiuYA288h0TiHW0b2WZmldNKnZ0vu9IA+x6p/NtYmFzAxN4JWR2HEhpbYK0urbhshBCCCGEEP2lT0dKaa3RQEM4RpU/TG0wQszWeJwO0hJcpCW4cDssVDdGY2iticQ0UdvGUgqPs/l1Wmv84RhldSHqgxEcliItwU1GorvVdk3bhmM2MVvjcli4HBa21pTWBimvD5OW4GJwqg9LgVIKrTX1oSj7qgIoBUNSfSR7nd3ucyhqU14foqYhggaSvU6ykjwkuB3daqO99krrQtQEIjiUIivJHKfDOsLLjYujnlKmEg6A06F69Pt56xljuHJmHnXBKNUNEZ5esYf3tsuIC3EIQnXg9Jo6Tp1Om4tB2Zbm+8mD29/OkwIzr4dXv2emun34Oxh6Egw/tfOABm364k5qPYKp5TbF6+HNe0zwY7ngjO/CoKmN/zE54NQvQ+FyKHgPSjbAmz+Cix40x9ee3MmwvvHnHW+aWllJuW37qW3Y+BwUrev4/AC4Ekx411ABdgwqC8xIrjbtNU4FXPoLM/JLCCGEEF2K2lEO1B/AH/EzOGkwqe7UHv9915LWms2Vm9lbu7fLbcdljGNU6qhD3pcQA1mfhFJaa6obIizbVcHrm0pYt6+asroQoaiNrTVOyyLB7SA/M4FzJg3iypPyyEx0d/kf8W/f2s6S9UXkpHh5+DMzSfY6qfSHeXLFXl5ad4AD1UFC0RiWUvjcDvLSE7h02hBumjsSqzG00cC9L23mgx3lXHXSMG4+bSR//aCAvywtoLohQqLHwcUnDuEb54wnyeNk+a5KfvLSJnaW1oOC4RmJfO3scSyalNvh1CatNRX+MP9etY+X1hexp6KBQCQGGjwui8GpXs6ckMunZuczLN3X5XFrrQlGbF5Yu59/flTIzrJ6ghEbpSDF62LG8HRuPm0kM4en43XJYDdxaEZmJXL7WeNYtaeKy2cMJcXbvX8OlFJkJXnISjJFk7XWfFRQIaGUODTL/wj7P4YJF8GwkyFliJlyZlnmH3A7amo4rX3ajHoCcPlg9ML221MKpn0Gtr1qRhb5S+HZG2DOLWYfyYNM3ShtmylzDRVmWtzOt6B8O1z7lBn5dLBAtakjVd84smjyZTDtU60DH0+KGTn15JVmu/X/grxZcNKNZmTUwUafCe/db6b8VRbAkm+YqYBp+SYYs2NmRNiGf5ui6tjEi6q3x5MCg6dB9V6zzUcPQ/5sU+S8KYKOhaG4MTDbu8KEgV3VlTp4tJe2zS12UKAVi5ibstoeby8+tAshhBBHWkzH+Mv6v/DEpicIRoMMTxnOzxf8nNGpo3sVTD2/43n+vuXvXW53x8w7JJQSx6w+CaUKKwN84YmVbCupw27ns3IkFiMQiVHhD7NmbzUvbyji19dOZ3hmQqf/EZfVhdhZ5qe8PkxdMEplQ5ivP7OWT/ZUHfSR3Iwoqm6oYebw9DaffYtrguws8/NxQSWDUrz84rVthKOmWGy4webx5XtIS3BzwdTBfP3ZNRyobl7Se2tJHXf+Zz0jMhMYl5vcpr9aa1YXVnPXcxvYXFTb5k+FcMymLljPtpJ6/rfuAD+8eDJnTsjpNOCqDUa5+78beXHtAWIHndCy+hCvbizmw53lfOucCaR4XR2ePyE643JYfG7eSG6eNxIFvbqgCnHIwnUmQNr2mhmllDzI3DwpJvgIVEDVbqgvA7QJO6ZfD3kndRx0eJLhol/Dfz4PhR+ZYOqNH5lV6ZJzzYgiO2pGRgWqTG0lbUPa8Pan28UisPR+2LvM3M8aDwt/AI6DVv9TytS/OuNOeOnrjfWnfmqCoqEzWvdXKciZZOo+rXzUHNvmF2HPMlM03Ztq+le5E+qKTHh06ldh9RMmpGuPsuDkz5uALVxvRnb97SLIn2NGlkUCUL7VjLgK15tRVIOmwIqHu3iP/LD896YfoTpzC9eb6ZFhf/M2zywGXzp4EsGdbN6HhAyY/SVIyul8H0IIIcQAVhmo5Jmtz1AbrgVge/V2/rfzf3x1xlePcM+EOPr1SSiVnewh2evE1pDqczF+UDJTh6YyLCMBr8uitC7E+9vLWbWniqitWbuvhv97ZQu/uXY6bmfXfwgHIzF2ldfz2zd3sGpPFVlJHqYNS2VEViJuh0VJbZBNRbXsrWhg/tisDtvZcKCG3RV+ThuTxRkTclhXWM1zq/cTtTXPrCxkw/4a/KEYn583imEZPp77ZD+rC6up8Id5fs0BvnXO+Fbtaa3ZVFTLV55ezf7qAAoYm5PEgvHZjMxKRAG7Kxp4e0spO0rr2VcV4JvPruWhT89gzqjMdkOAmK154PVtvLB6PxpwWoqTR2Ywf1w2aQkuyuvCLNtZzse7q/jZy5vJS/f18N0SoplSComixBGVmGNGPkUCJqCqqIOK7e1v68uAWZ+D075qQpqOKGUCpqufhPd+DuufNXWeQrXm1h6nF3ImmlFULenGsOjjxuDInQjn/ARS89oPxZSCE6+FPR/Aun+aaXKvfBuu+0fbGk+WA868ywQ6G/9jRjE1lMOe91u36U2F0+6AWTebAu8dhlLKBE1n/8RMMwxUmppRG59rvZ3lggkXwnk/h8pd5tg6Gy0V9sNHf+p4v2BCvdKNbR93+uCEKyWUEkIIcVRriDbgj/hbPVYRrOh1u+eOOJfchFyqQ9XmFqymNlzLrppdVIeqe92+EEeDPgmlvC6L/7dgNGdNrGfRpFzy0hNwtahRo7Xmc6eN4g/v7uR3b23H1rB0exkF5X7GD+p6la5wzOa+l7ewtaSOa2YN49bTxzA03dSBahIIx9hRVs+orKQOR3yU1IYYMTKRX187jSSPk9DMPMrqQ7yztYyimiBldSF+fOkUrpk1DAWcNDyDqx9eRn0oGg/UXI7mtv3hGD/+3yb2VwewFHzmlOHcftY40hNcrY79i/NH8ZOXNvP86v1UNUT46ZItPHXzyaQmuFv1T2vNqj1V/HNlYTyQumPROG46bSTexlpZWms+P28k//5kHz/+32a2ldT37M0agHTjyIT6UJSyuhDVgQixmMbrskhPNDW0fC5T46Wz0TxNNbhKaoNU+sPYWpPmczMo1dtlTa+YrWkImz/K3A4Lj6udmjKNorZNIBwz2zotPM7mbbXWBCKxeC01t9OK96u4NkhFfRitNWkJbgZ3o1/tnSd/KEZpXTB+njwui/TGmmoJ7o7Pk601DeFYvJ2WHJbC5+p53TMheu3kz0P+KVDwLhSthdr9EKwzAY1SZvRU6jCzzbhzIXN0+zWfDqaUCULOuw9Ougm2LIHCFab9SMC04UmBtGEwZDqMmAe5k0yI0lI0CGVbYcrl5v6Q6WbqYGf/rTjcsPBu036kwYxgKl5viqEf3EdfOlz8GxPcbHrBBDuBGvN8YpYZEXbC1TDoBNPOtE+bEVZJOSZcOpjlgJmLYehMWPcPKPzYTFFEm3ArazxMvBDGLDTH6vKZ8xNpMEFbe1xe079gB4FeZxxu8Kb1/HVCCCHEAJLqSSXTl0lDXQMACsXYtLG9alMpxYzcGczInRH/fK7RxHSMe5bdw/M7nu9tt4U4KvRJKKWU4owJOZwxIafdP2pVY82nz502klc3FrO1uI6GUIwtxbXdCqW0hg0HarlqZh4/unhym2LmAAkeJ1Pz0rps64Kpg0nymMLlHqfFoom5vLPVfPs7ONXLOZMHxafWjcxKYGiaj60ldRTXBAlEYrgcVmOfNG9sKuHj3WYFqNkjM/nWuRNIPChkUEqRkejmu+dNYNWeKvZWNrDpQA1vby3jkmlDWm1ra/jHx4XxwGPBuGxuPm0k3hYBiVIKj8vB1bOGsfFALU+t6Low3kBma832knr+/tFelm4vo7g2RDgaw9bNQcmgVC8nDU/ntoVjyU1pWzBYN4Yt/117gGdWFrKztJ5AJIZurOmVn5HI5TOGcvVJw0jpoGj91uI6vvz0J0RiNtfMGsaXz+z4IrN+Xw13/HMNMVtzw9wR3Hxa8/zuqK35+jNr2bC/hsWnjuCGuSN4a3Mpf1lawObi2vh763Fa5GcmcO2sfK4+aRheV+cLAGit2VFqztN728sprjH11Fqep9wUc56+snAMg1PbjqCr9Ie54a8fU9MQbvPcicPSePCaaTgdEkqJfub0mOBl6ExAQyxqpr1pM8Uay2mCDWX1vC6RUqCcJsTJmdRYRypkiqajzKgoh8v83FHbTi+c/p227Xa135QhcP793euj0wNjzjJBUSzSvIKew9M8ckspczGc9blutGmZEGvQCY3thRrbc5lz2fJ4fekmuOuMJwXO+VnX+xVCCCGOUanuVL487cv8ef2fqY/UM2fwHC4Zc0mffaHb1I5q/D+rvVqUQhyj+mz1ve78B5nsdTI1L5WtxXVoTM0orXW3XpuR6OaWM8a0G0h1l8NSjM1prgullGJ4ZgKWMoHQ6OwkUn3N3zy7HBYZSW4ogUAkRihiQ2MmErM1z6/eT8zWWAo+NTu/TSDVRClFdrKH+eOyeHL5XmwNb24u4eJpQ1pNnapuCLNilxkG6lCKa2YNw+Ns/x8kh1JcMSOPf63aR6ixPtbRJmrbPPPxPn752lYq/M1BidNSWAqiMZuaqE1NIEJ9MMrtZ41r04bWmvL6MN97bj1vbi4lpjWOxhAUzNTPzUW1/HRJLW9tKeXnV0wlr51i8+GYTWFVA5GYpqqh89WoghGbwsoAMa2pCbTdtqQ2SGFVgJW7q7Asxf2vbCUQieFxWvjcDiIxG384xuaiOu753yZ2ldXzvQsmdTiVNWZr/r1qH/e/upWy+lCn56k2GOGrZ3UcqMVsm7pQlHDUJhKzicTMtzKDU30dlU4Won8oBShwugF3V1sfQtuYFfLcCYf22kPdZ4+2bwyonJ5Otunh/p3uxnPaxXbdaUsIIYQ4TimlOG/keSwYtoCoHSXJlSTBkRB9pM9Cqe5qGfo0/UHcHVPzUhmW0fXKdZ1xOcyopZZ8bicOS2HHNINSva2mBDaNpgITDLQsOl7hD7PxgJnKkOgxYVtXfRub0zwqbHtpPaGIHQ9PAAqrApTXm3AmxedkytCO21RKMSo7kawkD/urA904+oFFa80Lqw9wz/82EozYuByKU0dncd6UQYzKTsLjtKgORNhcVMuHO8qZNCSVzKS2f1gFIzZ3/3cjr20qwVIwb2wW188ZwZicJCwF+6oCPLtyHy+tP8CynRV861/r+MNnZpCW0Md/9Lbj/R3lvLe9jCSPky+fOYYFjXXBaoNR3thUwp+X7qIuGOUfHxdy1qRcThuT1W4h/f+tO8Dd/91IIBLD6VDMGZXJeVMGMyYnEY/TQU0gwpbiWj7YUcHY3CSyk9v/gzYj0c3fP38KgXAMfzjGgeoAt/9zDZX+tiOnhBBCCCGEEM2UUiS6Eo90N4Q45vRpKKW1RgMNoRjl9SEq/CFqA9HGUUYxglGbzUWHUJMCU0Dc0ctva12WhdfVOtFuGUIle9uejqanD67DU1wTjI+Sidma37+zs8NRTU12ljXXf6oNRghHW4dS+6sCRGJm1FNWkoe0hM5X1ktwO8lOPjpDqf3VAX71+jaCERuv0+I750/kulnDcB80Em7+2CxuPm0kMVu3KcitteaVjcW8ttEs0X7ulMHcd8UJ8emZAPkZCcwakcHQdC+/f2cny3dV8OTyPdx6xpjDXj+pPhQlzefi19dNa1PYfsKgZBI9Tn7y0iZCUZuX1hVx2pi2RfqLa4P84rXmkVbfOmc8nz5leJsRg/PGZnHj3PbPUxNLKdIS3KQ1DhTJSHTjdsg3PEIIIYQQQgghjow+CaW01kRimo93V/LCmv2s2lNNaV2QYCRG1NZg/r9XUnyNdT96wbIUDqvjNpxW9/9Ar/SHidgmQGoIx/jnx4U96kvM1tgHBV3VDeH4eUr2unB10R+HpdoN0gY6M/qnKB6mXT4jj8/MzsfZTkCilMLlULRXdzwcs/n7R3uJ2ppUn4vbzxrbKpBqer3bqfjcvFG8urGEHaX1PLNyH9ednE9mUgdTZPrQZdOHcko7Ky1aSnH+CYP4/ds7qPCH2VpcRySmW03h01rz8vpi9lWa83TxiUO4/tQR8bpmLXV2noQQQgghRNfaWwymSV99mak7+MPoWFpspqPzeLiOsb/3J4ToW71ONLTWVPjD/PSlzby0vihe38hpKVJ8LtJ8LhI9TrwuB16XRUG5n31VPR/Zo1B9UtZCdRZs9aD9UDQWv6A4LEVGgrtH/ctK8rTZPtJieqBZvbDzNpSi3YBioIvamncbi8v7XA6uPXlYp2FhRw5UB+Mj704YmsrIrMQOLz5pPhenj89mR2k9+6sDbNhfy4Lx2Yd+EN3gtBRntyicf7BUn4uMJDcV/jC1wQhR28ZN8/sZszXvbC1FYwqjX3dyPs5DOE9CCCGEEKJ9WmuCsSD76vaxo3oHhXWFVAWrCMfCOC0nKZ4UchNyyU/OJz8ln0xvJk6r/YVzOtwHGq01lcFKtlZuZXvVdkoDpYRiIXxOH0MShzAxcyJj08aS6Or482x76sJ1FPuL4/cTXAkMSRzS7TZCsRCFdYXxYMdluchPyW+3XlLMjrG3bi9R26xYPShxEMluU56k6TzuqNrBxoqN7K/fTyAawGW5yE7IZkzaGCZmTCTTl9nrWkxaa2xtUxGsYGf1TnbV7KK0oRR/xG/OgTOBTF8mQ5OGMjxlOIMTB8en3XV1XrTW8b53ZUjSEJnOJ0Qf6HUoFYqamj4vrSsCzBS4y6YP5bwpgxmZlUiy14nTobCUuf3wvxt5YvmeXnf8SHM5LBNiaRiS5uXpz51Cgrv7w1QspRpHfzVrOZUqErOxuxhepjWt6lwdLepDUfZUmIvGoFRvp2FSZ3aX+/GHzEVx4uDkLgObKUNSAXPONhXVMH9c2xpOfSnJ4yQ/o+OiypZS8T7b2ryfLfnDMQoqzLKzuSleRuckyTc+QgghhBB9QGtNVaiKJbuW8NKul9hZs5NgNGhGMrXDoRykuFMYnTaaRcMXcdW4q3A5Oi+10bSfvXV7eXrz07y19y3KAmXEdKzNdi7LxYjUEVwx9gouHn0xSa7ufe5bdmAZ33v/e/F+zx0ylwfOeKDzL+Jb2Fu7l8WvLCbcuPLrsORhPHn+k+2GLbXhWm558xbKGsyXy9+a9S2uGncVMR3j3cJ3+evGv7KlcguhWKjNay1lkePL4fxR5/PZSZ8l09t2JkFXtNZEdZTVJat5dtuzrCxZSVWwqt3zCWYwgtfpZVDiIGbmzmTxpMWMSB3R6T5iOsZPlv+ElSUrO91OoXjgjAc4behpPToGIURbvQqltNas3F3F6xtLADPq5b4rpnLu5EFmJe52ijYfPGXtaJWV5MFlWYRjNoFwDLfT6vV0sMxEd1PORU0gQiRm4+6kTlXM1tQFO18pbiDyh6LUN4ZJWUluvIc456y8PhQP7nKSvZ1e2JRSZCV5cChFTGuKa9teLPua1+UgwdPxsXV1GW4IRalvfH8zk9z4ZG6eEEIIIUSv2drmg/0f8MCqB9hRvaPDIKqlmI5RFapiZclKUjwpXD3+6q5fY8d4effLPLjqQUoaSjrdNmJH2F61nZ9/9HPe2PMGd86+kzFpXddAtbVNKBaKH0PE7tnfBhpNOBaOB0nhWLjD6XAHb7ulcgthO8yf1v2Jv238W7thVMt+FjcU8+iGR1lZvJKfzfsZw5KHdTuY0lpTHijnt6t/y8sFLxOMBbt1bIFogIKaAkr8JVw9ruv3DCBshzs9FjChlK2PzhXQhRhoej1SakVBBeHG4twz8tNYNCkXq4MRK1qbVeuOBUPSfKQnuiipDVETiFBQ7icn2dOrkSxD0324nRahqE15fZgKf5hET8dvUUM4Smnd4Q9X+lo0pok1Xuw8TkeH09u60lQUHsx0x644HSo+ui0SPfwXEctSh3xsYKY5RhtTN7fDQmbuCSGEEEL0TkzHeH778/xi5S+oj9S3ed7r8JLgSsBtuYnqKA2RBoKxYDyAcCgHF466EIfq/MvCmI7x7LZn+dWqX7WaCuZQDjK8GWQnZONxePBH/JQ2lFITqkGjsbFZWbKSO96+g/sX3M+EjAkDdqT8juodPL35aR7d8Gh8Sl+CM4HchFxSPanY2FQEKihpKIk/D7CufB33rriXB05/gARXx7MKmjRNqfvO0u+wtmxtm+edykmCKwGv04tCEYwGaYg2tAroTsw5kdFpo7vcl6Us5g2dR6o7lZpwDfXheuoj9QSigU5HZQkhDl2vQ6mK+uaQaVhGQqdTqKoawmw8cGir7w00GYluZuSn8/KGYiIxzYtrDzBrRAbdyEY6NCwjgUGpXvZUNFAbjLBqTxXD0n3tXoi01uworT8qQymXQzUWlY8RiMSwtcZxCEXsE1oEdg3hGFrrTi/awUgs/s1PT6ZaHiwSs7v1jVpvuRwqXuw+GIl1OZ1TCCGEEEJ0TGvNe4Xvcf/K++P1hwCclpMZOTM4b+R5TMmaQqY3E5flIqZj1IZr2VO7h9Wlq1letJyoHeXkQSd3+plTa80H+z/gwU8ejAdSCsXkrMncOPlGZuTOINmdjKUsYnaMikAF7+57l8c3Pc7++v0A7Knbw/c/+D4PLXyInIScARlMbSzfyOaKzUTtKImuxPjUw7zkPNyWOz5SaW3ZWv649o+sL18ff+2KohW8Xfg25488v8tjqw3XcveHd7cJpAYnDubcEecyd+hc8pLz8Dl98VCqpKGETRWbWF60nPXl67lo1EW4rK6nWyoUN0y+wQSE2iZmx4jYEfxRP3e8fUerYxBC9I1eh1IpvuYmmqZTtRfMxGzN3z8qZH9VQ293OSBYCq6ZNYy3tpQSitq8sOYAZ07I4cwJnV80mlYqbKqz1VKy18n8sdk8UbEHreGp5XtYOCGHZG/bYopRW/OPjwsJ98OIn76W5HWR7HVSE4hQWhvEH4qSluDucTtDUn04LUXU1uyr7rwYodaaA9XBeLCT10HY13L7jp6v8If7JSBK9DhJ8TmpbAhTVh+iPhQlw9nz8ySEEEIIIaAsUMavVv2qVSCV5knjjpl3cP7I8/E42s56yPRlMjJ1JAvyFhCMBqkKVZHiTul0P9Whan79ya9b7eeM/DO4e87dpHvSW+3DZbkYmjyU6yZcxymDT+Fb732LrVVbAdhatZWH1z3MnbPvxKkG3orbYdsMTkhxp3DPqfdwev7pbUaQuR1u5g2dx7j0cXzlra+wpXILYEaSvbTrJc4ZcU6nx2Zrmyc2PcHHxR/HH1Mozh5xNnfMuIMhSe0XdR+cNJgTs0/kmvHXUBYoI9WT2q1gr2kbhcJSFk7LiQcPXqcXt0M+hwtxOPR66bYT89Li04o+Kqhk+a4KbNusMNF0q24I8/B7O/n9Ozv6YXxJ/1BKceroLC4+cQhgind/81/reOT9AopqAoSjNratidmacNSmyh9m3b5q/ry0gDv+uYa6YLRNm5ZSXHdyPmmNBdBX7a3ixy9torQuhN14Lm2tqWoI84d3dvLftQcOYXzRkZfocTAmOwmAktoQm4vqOl2CtyMjsxLidbzW76shGOk4oNPAqj1VgJkKN3loaqvnnZaKF4RsCHc8LFdrHV/x73BLcDsZm2tWNCmrC7HxQM0hnSchhBBCiOOd1prndzzP7trd8cd8Th/fP+X7XDbmMjP1q4v6pD6Xr8MQpOV+lhQsYXvV9vhjw1OG892Tv9smkDq4/ZGpI7nrlLtIciXFH19SsIQtlVsG7GdAheLmE27mjPwzOpzSqJQiNyGXm6bc1GrlvS2VW6gJ1XTa/v76/fxr279azVI4M/9Mfjjnh12+F0opHJaDQYmD8Dl9PTwyIUR/6VXkrpRizuhMJg1JZcP+GmqDUW59+hPOnJDDuNxkFLC3soEVBZXsKqsnPdHNp07O59EPCo6JqUguh+I7502gvD7EO1vLqPSHuXfJZh5+dxf5mQmkeF3EtKY2EKG0LkhFfZhQ1GZIqrfDgu8TBiXzxQWj+eVrW4namn+t3MeynRVMz08jLcFNtT/MhgO17KnwMzTNxwlDU1myobjdtgYqh1IsmpzLu9vLCMds/vpBAdOGpeF1WT0ampyR6GHe2Cz+tWof20rq+Hh3JfPGtl1RT2vN3ooGlm43K4WMyUli4qDW33Cl+lz43A7CAZttJXWEona7BdhrAhHe2Vp6CEfdc5aCsyfl8ubmEiIxzV8/2M3M4en4XI4BOYRbCCGEEGKgqo/Us2TXklaPXTDqAs7MP7NPP1cFY0H+t+t/8RBFobh2/LXkJuR2uR+lFCdkncDC/IW8sPMFAPwRP//d+V8mZ07usz72pbzkPC4dc2mrsKk9Silm5s4k3ZNORbACMNPyygPlZPoy232N1po39rwR3x4gy5fF7TNuJ9F1aKt3CyEGnl6PlEr1ufjJpVMYnW2WDa1uiPCfT/bzfy9v4Wcvb+GpFXvZUVrPsIwEHrh6GotPHUGqr+v5vEcDpRQZiW4euGYaN88bSYrXidZQVh9i1Z4q3t5aynvbylhTWM2B6iChqI3DUgxJ93VYe8uyFDfNHcGtZ4wh0e1AA/uqAry4tognlu3hxXVFFJT7GZmVyC+vnsZ5Jww+6kZLKaU4d/IgxjeOAnpzSyk/e3kzZfWhViPsmkaG1YeibDpQSzDSegSTpeCGU0eQnuAiFLX52cub2VFa36aN8noTFpbWhXBaisWnjiDxoFXxspI9jMg0hRY37K/htY0l8RF/YC6K/lCU3721gx2lbYtiHg5KKc6alMvEwSZAe2drKT95yRxHe+fJH4qyqajteToSBuq3eUIIIYQ4Pm2v2s7eur3x+z6nj6vGXdVlwfKe2lu7l53VO+P3k93JzM+b3+0AxVIW54w4p1W/lh1Y1m5R9oFgzuA5pHvSu7VtijuFLF9W/H7UjlIb7ngGQtSOsnT/0laPLcxfSH5KvgRSQhxDej05WSnFiXmpPHHzbJ5ZWci728ooqQ0SiWm8TovBaT5OG5PFFTPyGJLmJRLTXD4jj8LKBkZmJXba9uQhKZw9KReAUdmdb9th/4Bp+WmAqdHjdbXO4VJ9LhZNyiUa04zNSWr9WgUzhqfjclgkeZ14XG0zPKUUqT4X3z1vIlfMyOPlDcV8VFDBgeogwUgMpcw0rNwUL5OHpDB3TBYz8tNI6mRVPY/LwW0LxzJ3TBbPrixkzb5qahoiOCzFoFQvZ4zP4aqZeQxK9bK7ooHzThhM1LYZkuY9pHN0JGQkuvn+hZO47e+rqfCHeWLZHt7ZWsYpozIYmZWE26moCUTYXd7A5qJaGsIxnrvl1Fajl5RSTBqSwh2LxnHvS5vZXFTHZx/9iAtPGMyUoak4HYqdpfW8tL6IbSX1KAWXTBvKJdPaDvX1Oi2uOmkYG/bXEorafO/59awoqGDWiAxcDovCqgZe31TCmsJqJg1JZUdJHcF+qOeV5nPx/Qsn8ZWnV1NWH+LvK/aydFsZp4zKZFR2Im6ng9pAhN0VfjYX1VIXjPKfW05lcGrrIcoN4Sgb99dSF4pSH4pSH4xQWmfqVAEcqAnw6PsFpPpcJHmdJLpNPaspQ1LxtDjnWmu2l9RTUhdsbCdKXTDK2n1m6LVta577ZD8b9teQ7HGS5HWS4HYyMiuRIWkybFoIIYQQ/U9rzYbyDa1WYxuVOopRqaP6NNzQWrOlckur1fbyk/PJTcztdhtKKcZljCPVk0plsBKAIn8R++r2MTFzYp/1ta9My5nW7W0dlqPVNDqNJhKLdLh9daiagpqC5tcrBwvyFsRLbgghjg19UjFPKcWQNB9fXTiW/3f6aALhGDFb43RYJLgdpl5P4z/4LgfcdcFENCYw6uxC8JlThvPpU4abffSif/9vwej4/g42MiuR331qRrv7UMCXzxjT4Wvj2ymFQ8HEwSlMGJRM1B5DIBwjErNRSuF2WHhcVnx0VHcufg5LMWtEOieNSCcQjhGMxrCUIsHtwO1onuY2IjOB331qerv9H8hMTa5MfnvddH7y0ma2FNeyt7KBvZXtF8LPSW5beBJMHa5PnZyPQykeeGMbxTVB/vJ+QZvtfC4HV87M45vnjMfjbD9cvHzGUDbsr+Ffq/ZRF4zy1Iq9PLVib4ttYM6oTO6+aDJfeHwlezroa19SSjF7ZAa//dR0fvLSJjYdqKWwKkDhqn3tbp+V5G73Qr2nooEbHvuYQDja7tTZfVUBfvbylvh9S5nA9oVbTyM/s3mpXlvDvUs2s3R7GVrTpkacreGJ5Xua+48Z/ffVhWO5beHYHh27EEIIIURf2VWzq9X9cenj8Dg8h30/w1KG4bZ6ViA71Z1Kti87HkqFY2H21u0dcKGU03IyLHlYt4M9hWqzbWcrWpcFylqNpEp0JTIqrW+DRCHEkdenyzgopfA4HXicHQ+DbV7RoOu2urNdd/rUWTtKdZy1H0oflFK4HAqXr9czI+N9S/Q4SexgZFVn/R/ommqSPfX52by1uZS3tpSys6ye2mAErcHrcpCd5GHy0BQWTsghPaH9aZ9Oh8V1s/M5eVQG/1m1n2W7KhpXgtSkJ7iZmpfKJdOGMnN4equA9GA+l4MfXjyZ+eOyeWHNfnaU+mkIR3E5LPLSfZw7ZRCXTBtKksfJpdOHsqO0nnGNUxCbjwlOHZPF4FQfGYluXO0tRdnIshTzx2YzKiuJnBRPh1M6m4KpJ2+ezVtbzHnaUVpPbTCK1hqvy0FWkptJQ1JZOCGHrKS2H3ySvU4WTcol0oPRXT63A5+79X/LCjhpRHqnI/3aMzo7qeuNhBBCCCEOA42mrKGs1WNDk4Yeln0dvJ9sX3aP23BZLtK9zVPiNJrShv6padoTLstFsju56w0PUUWggqjdvDhUijuly5UPhRBHn4G3tqg4riilSE9wc/mMoVw2fSihqE0oGkMDLqv7I8wspRiTncS3zh1POGYTjNjxwMbttLocldfUvtfl4Lwpgzhn8iCCkRjhmI1DKXwtRvxprbn9rPZH/TiU4uuLxnXr2J2WKZTfHUop0hLcXDZ9KJdOO/g8KTwuR6fnaWiajweuPrFb++q8H2b0oBBCCCHE0cLWNv6ov9VjhyPc0Ggaoq1H0ic4EzrYumNKqTarxfkj/g62PnIsZeGyDl+t4IZoQ6s6pT6n77DuTwhxZEgoJQYEpRRKtT86pydtAF2O1utOOw7VOEKtk/101ofu7udQ+nYo56mvhjnLcGkhhBBCHI0OXoTFUj1b9bnb+zloOtqh7uPguRCHbREZ3fkUuq4czs+GtrZb9U0+hwpxbOr9HDMhhBBCCCGEGKAUCrejdXmDQDTQ50GPou0Ip5ZFz7tLa00wFmz1mM91eBaMiepo2yKhA4Tb0bpWajgWxtaHf6EhIUT/klBKCCGEEEIIccyylEWaJ63VY4erRtPBNaQqghU9biOqo9SEalo9lunN7FW/OtIQaSCmY4el7d5K86RhqeY/V+vCdW2mRwohjn4SSgkhhBBCCCGOacOSh7W6v6N6x2EJY0amjmx1f1/dvlbFurujPlxPWaC5YLrLcpGXnNet1/ZkKp7WmtJA6YANpbJ92a1GntWF6yiqLzqCPRJCHA4SSgkhhBBCCCGOWUopJmVOwmrxp8+2qm2UB8r7fD8TMybidXjjj+2p3dOj0VJaa3bX7qYqWBV/LN2b3iZUa+K0WpcI7ukUt22V27q9bX/L8mUxKHFQ/H7YDvNxyceHr76WEOKIkFBKCCGEEEIIcUybnDmZdG96/H5lsJI39rzR5wHHiJQRjEobFb9fFazio+KPerSftwvfJmJH4venZk8l3ZPe7rbJ7uRWU9zKAmWEYqFu7ScUC7GyZGW3+9XffE4fJ+We1Oqxlwtepi5cd4R6JIQ4HCSUEgOW1ppozCbS4mbbR/abEa11q1tftBe1Wx9jR7cjeey2rVv1JWrb8i2VEEIIIY4aOQk5zBkyJ35fo3li0xMU1Bb06Wcar9PLhaMujBfo1mj+seUf1EW6DlK01hTWFfJywcvxx5zKyYUjL2wVPLWUk5CD19k8MquovoiCmq6PSWvNJ6WfsKVyS3cO64g5Z+Q5eBye+P1tVdv459Z/Dtgph0KInnN2vYkQR4YG7ntlKx8VNA55VoqvLxrH/HHZnb7usPVHazYX1fHsqkLqglHmj83mvBMG4XL0Ltt94PVtvL+9i+HjSnHbmWNYODG3V/s6VG9sLuGht3fE7582NotvnD3+iPRFCCGEEKKnLGXxqQmf4p3Cd6iP1ANwwH+Au96/i3vm3sPo1NEopTptQ2tNTMcIRoMkuhLb3V4pxfkjz+ff2/7NzpqdAGwo38DDax/mtum3mRXl2nmd1pracC2/WPmLVkXYp+VMY86QOR32LTchl6FJQ9lWZabhBWNBntj0BPeceg8ep6fd12itKfIX8eCqB7s9qupIUEoxNWsqc4fM5a3CtwCwtc1f1v+FFHcKl429DJfl6vR9awrn/BE/PqcPh+Xol74LIbpPQikxcGkoKPezdl/z6iNVDeEj1p2aQISvPbOGLcXmm64X1x4gxedkwbjsLj/EdEQDeyoaWh1jRyr9R+7YK/zhVn3MS084Yn0RQgghhOgppRSTsibxqYmf4i/r/xKvu7S+fD1fev1LXDXuKhYOX8jgxMF4HB4UCo0makepj9RzoP4A68rW8cGBD5iQMYHbpt/W4b4yvBncNuM2vrP0OwSiATSapzY/RWWwkpun3MzwlOGtakGFY2E2VW7i92t+z4qiFfHHUz2pfGX6V1oV+z6Yz+njzPwz46EUwGu7XyPVk8pNU24iJyGn1aithkgDq0pW8bs1v2NL5RYsZZkZAD0okN6fXJaLW6ffyoaKDfGwriHawH0f38eyomVcNe4qJmZOJMmVhEOZwCmmY4RiISoCFWyv2s7youVsrdrKr07/FTkJOV3u8+BRZjY2UTva5vGYjhG1o1jKip9joEd/FxzcpkZja7tNXbCY3f6+ero/IQYiCaWE6KZ9VQEKyv3x+6GozcrdVSzoxcgtBWQkuslKchOMNE6Ni2lsPVA/GgghhBBCHJ0cysFNU26iqL6I/+36XzyIKWko4XdrfsdfN/6VnIQcMr2ZeBwewnaY2lAtlcFKakI1hG3zBeHQpKGd7kcpxYK8Bdxy4i38dvVvCdthYjrG/3b9j3f3vcv49PGMSBmBz+WjLlzHzuqd7KjeQSAaiLfhc/r42syvMS1nWqehg1KKy8dczku7XqKwrhCAqI7y9y1/5629bzE5azKDEwcDmJCmejt7a/cSsSNYWFw17io+PPBh/LUDjVKKsWljuWv2Xfzgwx9QHaoGIGJHeHPvm7xb+C6ZvkxyEnJIcieBNqOiqkJVVAYraYg0oNGke9K7nNK4o3oHK4pWUBeuoz5ST324nvpIPf6IH3/Ez9bKrfFtNZoHVj7AU5ueIsGVQKIrkSRXEknuJJJcSaR6Ujl7xNmkuFPa3Vexv5h3Ct+hNlzbZl8NkYb4KLsmz2x7hmVFy0hwtt1XkjuJBXkLGJI0pFfnWogjRUIpIbrJYSkO/kzgdva+LNt3zpvAl88YQ0MkRn0wSm0wQnVDhIfe3sHGA7W9bl8IIYQQQhgJzgTunH0nGb4Mntn6TKsgyB/xU1BTQEFNQa/347AcfHrSp3E73Dy05iFqw+YzXV24jpUlKzstMJ7pzeRrM7/GBaMu6LCWVEuDEgfx3ZO/y10f3EVlsDL+eElDCSV7S9p9jaUsLhh5AbfNuI1if/GADaWgMeQbtoD75t/H/330f63en6iOmuNsaP84e2JF0Qr+76P/6/b2BbUFFNS2/7vic/qYnjO9w1BqR/UOfvbRz7q9UmKxv5hif3G7zykUuQm5EkqJo5YUOheim4ZlJDB1aFr8fnayhzMm5PRqyKxSigS3k5wULyMyE5kyNJVTR2dx7pRBDE7teKi2EEIIIYToOaUUSe4kbp9xO7854zfMGzqPRFdit17rttyMTh3NjJwZ3dreZbm4dsK1PLTwIeYNnYfX4e10+yRXEueMOIc/LvojF42+qNv1j5RSnDb0NB4840FOyj0Jl+XqeFsUOb4cvjL9K9x1yl0ku5IZkzamW/tpr63+YimLOYPn8OdFf+bzJ3yeIUlDuhXYWVhkeDM4behp3X6fhRD9S0ZKCdFNiW4HD147jVc3FtMQjnH6+GwmDW7/2w8hhBBCCDFwOS0nswfPZmbuTHbX7mZ16Wo2VWyiyF9EXbgOW9u4LBfJ7mRyE3IZnTaaKVlTGJ02miRXUre/lLSUxYnZJ/LgGQ+ytXIry4qWsbliM+WBciJ2BJ/TR25iLlMypzB78GxGpo7EoRw9/tJTKcW07Gn8/qzfs75sPcuLlrOjegdVwar4foYkDWF6znROHXIqgxIHmXpSaC4ZcwkjU0cCJhjrqEB6oiuRb8/6dnx0mctykeHN6HYfLWXxhalfoCJQEe/z2PSxPTrGnAQTqH164qdZX76eNaVr2F27m8pgJeFYGEtZ+Jw+MrwZ5KfkMzFjIpMyJ5GbkNtliDVn8Bx+Mvcn3e5PZ5yWs9P6VWPTx/LjuT/uk5UflVJMzJzY63aEOFIklBKim5RSDEnzcePckUe6K0IIIYQQopeUUrgcLsamj42PFmoqMq3RKKWwlIXVOLnkUEfHK6VwO9yckH0CU7KmoDGr+GmtsZQVL9Dd24LVSil8Th+zBs1i1qBZ3dqPQjEydWQ8lOqMx+Hh7BFnH3L/LGVx2tDTDvn10Nz3TF8mpw87nQV5C1oVB1colFKHdE5HpY1iVNqoXvWvu3ITcrl49MX9si8hBjoJpYQQQgghhBDHtabwwqEcOOjetLlD3Y9CdWvqWW/2ARz2/QwE/XE+hRCHl/zXK4QQQgghhBBCCCH6nYyUEn2qaV50JGbTEI4RiMSI2RpLKTwuiwSXE7fTwmocSdubYcpN+wpFbepDUUIRG6XA63KQ6HHgdhzaUOuezu3u7VDrI0VrsxByIByjPhQlErNxOyySvS68rtbn7ug8QiGEEEIIIYQQA5mEUqJPaK2pCUT4qKCSd7eVsfFALaV1QQLhxlDKUnidDlITXAxL9zFlaConj8hg0pAUUn2uHhSLVGgNMW2zcX8tL6w5wMe7KympDRKM2liAz+1gUKqXWSMyuGjqECYNScFhdT9Widqa37+9g6KaYKfbOSzFFxeMJj8jodttDwRaayIxzce7K3l+zX7W7K2m0h82oZTTIjvZw6wRGVw6fShTh6bisBQuhwyqFEIIIYQQQgjRtySUEr2itSYYsXl+9X4e/aCAXWV+Yh2ONIpQXBtka3Edb2wuxWkp5o3N4o+fmYnH1fXcfaVM4FQbjPDrN7bxz5WF+EOxNttVByIU1QRZvbeap1fs5bqT87lt4RiSPM5uhV8xW/PKxmI2F9V1up3TobhyZt5RFUpprSmpDfF/L2/h5Q1FhKJ2m23K68NsLqrj36v2cdVJw7j9rLGk+FwooPfrgwghhBBCCCGEEIaEUuKQaa0pqwvxwxc38urGEmJ2zyKLqK05YWgqbmf3RuFYSoGG7z23npfWFbUKSJqipoN7UB+K8pf3d1EbiHDPJZO7FX4BuB0WTksR05o+WKl1QNBaU1wT5Ct/X83KPVXtbtMyePKHY/ztw93srw5wzUnDcFiKaA/fYyGEEEIIIYQQoiMSSolDorWm0h/ma8+s5f0d5a2ec1qKvHQfEwenMCwjgUSPk3AkRlFtkJ2l9eyuaKA2ECHR4+T8qYN7tN8nlu9h6fYyNOB1WZw0PIM5ozMZlpGAy1KU1oVYvquCpdvLqQ9FG/sK//5kH3NGZ3LJtCFdjpZyOy0euGYa5fVhagIRqhvCVDWEKasL869VhVQ1RHrU54EiGLH50f82tQqkFDAmN4mzJ+UyLjcZl8OirC7EJ3urWLq9nEp/mDc2lVBWF5JRUkIIIYQQQggh+pSEUuKQRG3NL1/fxgcHBVJThqZy6+mjOXV0Fsk+Z5sC2eGoTVFtkI92VbK/OsDo7KRu15OK2Zp3t5UBMCIzgbsvnszc0Vm4HCrehtaaT5+Sz/KdlXzrX2s50FgXKmprHl+2m3MmD8Ln7ny0lKUUo7KTGJXd/FjTNMX3tpcdlaGU1polG4p4Y1NJ/DGHUnxqdj53LBpHeoILMIXNtdZ85pTh7Cit44f/3cSyXRWsKaw+Qj0XQgghhBBCCHGskurFose01nxUUMl/PtnXavTMokm5/PWGWZw7ZRCpCS4sZcKiljePy8GIzESuOimP288ai7MHBcibZCd7+M110zl9XDZup9Uq1FJK4bQs5o7J5DvnT2zV/ubiOnZX+A/pmI/WFfaa+MMxHvtgd6vpd2dNyuW7508gPcEVf3/AHKvDUozLTeaXV5/IuNykI9VtIYQQQgghhBDHMAmlRI/FbM3jy/YQjDQXyR6Xm8SPL5lCVpK7WwFOy6CqJxRw09yRnDA0tdPXKqU4Y3w2I7MT448FwzG2ldShj5UiUd2ktWZtYTVbimvjjyV6HHz5jNH4XI4Oz6NSisGpXj4/bxSHkB0KIYQQQgghhBCdklBK9Nj+6gArCiri9y0Fn583itwUz2EfUZSR5OaiEwd3az9JHieTB6fE72tM349HS7eXEYk1h3HT8tKYMCily/OolGL+uGyykjyHu4tCCCGEEEIIIY4zEkqJHtFas25fDTUt6irlpng5fXxOv0xxmzQ4hUEp3m5vn3PQtvXBaF93acCL2Zq1hTWtHps9KhOno3vvV2aim7E5MoVPCCGEEEIIIUTfklBK9NjGAzWtaklNGpxCRqK7X/Y9cXAKjh7MJXM7Wv+Kx+zja+oeQEM41mqEmFIwYXByt0NEh2UKvwshhBBCCCGEEH1JQinRIxrYW9nQ6rExOUn9VnNoSJqvf3Z0DKkPRakNNo9sc1kWucndH22mlCI3tfvbCyGEEEIIIYQQ3SGhlOgR29ZUt5i6B22nyB1OyR7nUb8SXn8LRGKEo81F6Z0ORZLX2aM2Unq4vRBCCCGEEEII0RUJpUSPaCDUIuAA8LqsfguKulsHSTSL2Rq7xYqDllI4ezi0zeWQfyqEEEIIIYQQQvQt+UtT9NjBecbxWKfpaKIUKJrfNI2mx2+ZvMVCCCGEEEIIIfqYhFKiRyylSPS0nspV0xBBa0ktBiqP04GrxQizWEwTjMR61EYw2rPthRBCCCGEEEKIrkgoJXrEUpB7UA2pPQcVPhcDS5LHic/dHCRGbE2lP9zt12vds+2FEEIIIYQQQojukFBK9Ni43KRW9zcdqCXQw5E3ov8kuh3kJHvi92O2pqDc3+3Rbe2tuCiEEEIIIYQQQvSWhFKiR5RSTBuWjtvZ/Kuzq7yezUV1MoVvgHI7LSYMSm712Mrdld0uExWMxNhaXNf3HRNCCCGEEEIIcVyTUEr02PjcZEZnJcbvByM2j324m0hMQqmB6tQxWbRcIHH5rkpKaoNdvk5rzbbienZX+A9j74QQQgghhBBCHI8klBI9luhxcMXMPFouwvfqhmL+8fHeHq3Ep7WO38Tho5RizqhMBrWoBVZSG+TvH3X9fkVtzRPLdxOM2Ie7m0IIIYQQQgghjjMSSokeU0px+Yw8Jg9JiT8Wjtn8bMkWHnhjG2V1oQ7DJq01ttbUBiOs3FPFBzsr+rPrx62cFA+XTh8av6+BR9/fzYtrDxC17TbvldaaUDTG3z7czYvrivq5t0IIIYQQQgghjgfOrjcRoq30BBffv2gStzz5CRWNK7MFIjEeemsH/11zgNPHZzM9P51BKV7cTotIzKbKH2ZPZQObDtSy4UAN+6oCXDdrGHNHZx7hozG01kRtTShiE4nZhGM2wUiMQCRGQzhGdUMYfyjaYntYvbeaSEyT6HHgdTnwOh14XBYuh4XbYeF1WaiW8+ZaiNmaQCRGNGYTjtoEo2Z/DeEY9aEoFfWhVttvKa5j+a4KEt1OfG4HXpeFx+nA5VC4HBY+lwPLan9fClg8ZwSvbyphR2k9APWhKN/9z3qW7argkhOHMCwjAadD4Q9F2Vpcx3Or9/PutjIiMU1+RgL7qhrowUA4IYQQQgghhBCiUxJKiUOilOLkERncd+VUvvfcekpqTYDStFLb48v28PiyPTgshaVMgBOzdbeLax8pTy3fw9+W7SEYiRGKmnAqErOJ2RrbhliLEUUxW/OTlzZhKYXDUjgtEw65nBZep0VOipc/fmYm2S1Wvmvpna2l/HTJZgKRWDwIi8Q0UdvGbjxfLT36fgF/+3A3llI4G4Mol0PhdTlI9Dj51dUnMnlIarv7UkqRm+Lhnosn85W/r24VJP7z40L+vWofiR4nloJQYzjWtPtJg1P4wUWT+OITq6gJRPrgLAshhBBCCCGEEBJKiV5QSrFwQg6DFs/i569uZdnO8jbFzmO2JtbR6wGXc2DNIC2rD1FQ3v2i3rYGu2mEFUCLo60PRYnaHddiqg1G2VnW/X1pTI0n0IRjrffltBQN4Y7OtKGUYs7oTB64Zho/eGFjq+LlUVu3CZyUgpOGZ/Czy09gSJqX3BSPhFJCCCGEEEIIIfqMhFKiV5RSTB6SwsOfncnynRU8v2Y/n+ytoqwuRDhqx0fbKMBSCrfTIj3BxbhByZwxPodzpgzqpHHITfEwIjOxcV+Q6OnZr2x6oiv+eoCMRHfn2ye4W23fG2kJLpwdTKcDSPI4GJmVSF/UeXc2jpjqilKKeWOzeOpzs3li+W5e2VBMUU2QcNRGY86x1+lgRGYCl8/M46qZeaT6XGgNJ43IIBw1nc1JaX/0lxBCCCGEEEII0V1Ky9Jnoo+Y4uZQG4xQXBOkpC5EXTBCzNa4HRYpPhdZSR6ykz2k+Jw4lOqw3lJTe6Go3Woam8dp4XR0b3SV1ppITBOJNY9Wapry1t5+29u+N5QCr8uB1cExRmM2oWjfrWrndTlwdBKCtdT0n31tIMKeygaKaoIEIzES3U6GpvvIz0ggwe2InyetNeGYTbRxJJzTMgFjZ++fEEIIIYQQQgjRGQmlhBBCCCGEEEIIIUS/G1gFfYQQQgghhBBCCCHEcUFqSgkhhBA9pTVoG3QMLJeZrztQ2DEIVEFH650qC7xpYHVdh04IIYQQQojDSUIpIYQQoie0hpp98PoPoKYQJlwAc74MDteR7plRuw8evxTC9e0/78uExS9AUm6/dksIIYQ41mmtqQnVEIgGSPem43F4pAZrL1UFq9hVsyteE3dQ4iCGJg2V83oMkVBKCCGE6KnVT8DG/5ifSzfD+PMge8KR7VMT24aGSgjW0O5oKds2NyGEEEL0Ga01Lxe8zG9W/4a6cB2TMifxk7k/ITdRvgTqjdWlq/n6O1/Hxnx2WTx5MXfMuOMI90r0JQmlhBBCiJ4KVDf/HAtDuOGIdaWN5MFw7ZPgr4BAJTRUQNE62PwiHU7pE0IIIUSvBGNB/rrxr+yv3w/A8qLlvLH3DT498dNHuGdHN40mpmPoxs8wsk7bsUdCKSGEEKKnxiyEdf80U+Ty50DmmCPdo2YuL4yYZ35u+uC2803Y8r/m+0IIIYToU5FYhNpQbavHygPlfboPrXU8nFEomcImjgkSSgkhhBA9oRSMOQtuesWMQsqdDJ7kI92r9smHVSGEEKJf+Jw+hqcM54D/AABOy8mkjEl9uo/6SD0///jn1IZquX7y9czMndmn7QtxJEgoJYQQQvSU5YCciUe6F0IIIYQYIJyWk6+f9HUeWf8IFcEKzhh2BvOHze/Tfeyo3sFLu14iYkc4Z+Q5fdq2EEeKhFJCCCGEEEIIIUQvKKUYlz6O/5v/f2itsZTVp9PrtNasKllFxI70WZtCDAQSSgkhhDg6aQ3aprl4twJldX/KmtagY833lWVuXW3XHuXo3VQ5rcGOQKgOwn7zmDsRPClgOQfeNDytAQ2RAARrTbF3h8v0152AeS+66HOr96/Fe9dU9yrSYFYQjEV63naHfaaxMH29KU6vbXN+3QnmfFsus01P2tfatBmsMefDcoA7CTxJvf+9EEIIcVRRSqFQcBj+6Y/pGB8Xf9z3DQtxhEkoJYQQ4ui14T+w6lHzc0oeXPSACQS6o/YA/O92E1AoC864E4bPbbtdxQ546esmNGpP0iC4+LcmhOgpraGuCDb8G7a9CpW7TH/AHEfmGJh4IUy+DBKyjnzAoTXYUdi/Etb+EwqXQ31ZcyiVmAV5s2DqNaYAfGeBWiwEL94O1XsgYxRc8CvTRskm+ORvsHsp1Jc2h1KJWZB3Msz4LAw9yYQ/Pelz8XrY9ALsXQY1+0z41xRKeZIgeQgMngqjFsDI07t+P7Vt3q91z5hC8tX7TJBmOcCTCrkTYfLlMP48814e6fdOCCHEUa0yWMm2qm1HuhtC9DkJpYQQQhydlILscVC01gQMDjfMXGyCpe6M0tnxOmx/HdCQMsQEI+0J15sgIxZu//m04V2PpGqPHTMhyZv3QNVumkd8NQrWQO1+KHgPVv4VzrkXRp3e/miu/qA1BKrg7Z/Cmqch4m+7TUMFlG01IdvUa2HhD8CX3v77oW04sBrKtkDFTmiohJ1vwOs/hIZ2VitqanvT8zD/m3DKLSas6qrPdUWmzxufaw78DhaohOq9JmRb+w9TxD53csftxsLwyePw7v1QX9xOe1VQvRu2vQbDT4Xzfm5qkEkwJYQQ/U43jpSN2BHCsTAajUM5cDvcOJT5gmOgr2KntWZr5VaqglX9tj9oe848Dg9W4+eQ3p6zppUEw7EwETuCQuF2uHE1jloe6O+J6DsSSgkhhDh6ZU+AoTNNcBMLm+Bh+Kl0OW4+FjHbNgVBYxZBUm7726YMhTO+B/4yE4wEqqCyAMq3Hnq/tQ2rn4BX7mwOd9xJkDMBUoeZMKWm0AQ2YT+UboJ/3QQX/QYmXnRkwo1gDbzwZdi6BNBmalp6PmSNM6sPBmugdIsJ0iIBWPUY+Evh0j+AN7XztgPVsPJRWP57Exx5UyF7ogkLdcyEVuXbzHscqjMhU9pwmHRJx+dCa6gqgH/dDAc+aX7cckJiNiTlgNNjpvHVl5j31Y7C0BlmhFpH7Ci8/yC8d39jUKkgKdv0NzELoiGo3GlG2MUiZsTXM9fDNU9C9ngJpoQQxw2tNa/teY2CmgIAHMrBpWMuJTshu1uvL6gp4LXdr6Ebr9XTsqdxypBT2t3Pq7tfZXftbgBmD57NtOxpAIRjYVaVruKtvW+xuXIzVcEqYnYMj9NDti+bqdlTOTP/TCZmTMShHN0OQnZW7+T1Pa93uo2lLC4efTGDEgd1q82Wx6PRBKIBKoOV7Kvbx47qHbyx5w1iLb4Ee3PPm+yt3dtpWxMzJjI/b363j0trTXWomuVFy3l///vsrN5JTbgG27bxOr0MShzE9JzpnDHsDMakjcHR3VHLB+2jIdrAh/s/5M3CN9lZvZO6cB0KRbo3nSlZUzh7+NmcmH0iTsuJ05LI4lgn77AQQoijl8MNU66AgqWANiOfGipM6NCZiu2wf1XrNjoKspJyYO5Xm+9r24wE+s/nD63PWkPhCnjjh42BlILRZ8CZ34fcSaY/ANEwlGwwI6kK3jOhyZJvQsZIyJ3Sv+GGHYOlv2gOpBKzTX8nXmQCJGWZ89JQYUYQLf2lmcq29WVY9ns4/dudj/CKheD9X5k2Jl4Mp38HMsc2joTSjW29Ai9/24yiigbhw9/C2EWmFlR7QnXwvzuaAynlMCPNTvkSDJ4O3mTzmB01oVjZZvP7M3xO83twMK3NMb3/q8Ypix44+fMw+4uQPNgEXmgTJO58C16900wVrNgOr3wHrn2q4/4KIcQxRqN5ueBl3tz7JgBuh5u5Q+d2O5TaWb2Th9Y8FA+lbph8Q/uhFJolBUt4u/BtAEobSpmWPY3CukLuX3k/H+z/oN3i4AU1BXxU/BFPb36aC0ddyJenf5k0T1q3Apwd1Tt4aM1DnW7jtJycPOjkHodSxf5i7l95Pzurd1IWKKMh0tAqjGry2p7XeG3Pa522dcXYK5if170VACOxCK/ufpW/rP8LBbUF2Npus82uml18eOBD/rbxb5w38jy+dOKXyPZl9yj02lSxiftX3s+a0jVtjmtf/T7Wl6/nP9v/w6Lhi7h9xu0kuZKwlNXuORDHhiM0B0AIIYToA0rBmLOaRznVFMLu95uLWrdHa9jykgktoHm0VWcfqJRqvlmO7tczak80BO/cZ0ImgGGz4fI/w5Dp4PQ2F1x3eU2/rngEhs0y29YXwzv/13F9q8NBayhaY0Y+ocHlgwsfgBnXQ0KGORdN5yUpB0673UytQ5mQaeWjULWn6/3YURMyXfIQ5EwCp7vxnFtmFNmUK8y0vab3qXSjGY3UUZ/XP2PCPDBtnPwFuObxxlFx2eZcO1zmeFIGw+gz4ZyfwoQLO/5dCNaY8x8JmOM75Utw1g8hLd+01dRfT7IJ1y74FTh95rW7l5rQq7PfTSGEEL22s3onBbUFfO2dr/FO4TvxQEqhsLBMIfIWGqINPLvtWX607Ec0RBu6tY+mqWwO5WjTXm9Vh6p5b9977KrZRV24rl/CmGA0yK9X/5q7P7ybnTU7WwVSTeetpfpIPc9ue5bb3rqNgpqC+HS/zmitWVO2htvfuZ1VJavaHFfL9yYUC/G/Xf/j6+9+HX/EL6OljnHy7gohhDi6JTcGCmufbhzF9J/GKW4dXOIiftj8YvP9SZf07+iVojWmRhWYETkLvgUJme0HIUqZKWELvg1/v86Mztn5FhRvMCFWv4yW0rD6yeYQb8xZMO7cjvdtOU1tr08eA3+5mcK3/VU4+Yud99edCPO/bQKdjs7FxAvMtLmGcogEoXw7DD6x7bYRvxmx1fShOu9kU8jeldh1+NjRHxdam3NfutncTxtmwreOPigrZUZmDZtlwjE7Cuufbfzd7EWoKYQQolMFNQXc/cHdbK0y0+zzk/M5fdjpTM6cTKonlUA0wNbKrby25zV21ewCzGirtwvf5oUdL3DdhOu6HPlzyuBTePy8x6kL11EbqqU6XE11sJqXCl5iZ/XOXvU/05fJZyd9lqgdbfX46tLVrC1bG78/P28+o1I7qIfZ6ISsE7rcX9SO8vC6h3ly05PxoMjn9DF70GzmDJnD0KShOCwH5YFyPin5hHf2vROvbbWxYiN3fXAXvznzN2R6Mzs8bxpNSUMJP/rwRxT7m2sxprhTODP/TGYPmk26N52GaAPbqrbx9t632Va1jbVla/nVql+1O2pLHDsklBJCCHF0UxaccKX5g9+OwJ4PoLrQTHM7mNZwYI0pmA1mlbSJF/ZfX7WGHW+Y6WdgahcNm911UDJsttm2dJOZyrb9NRNK9YdgLex6p6kzJlTp6hvL5EFm+p2/sWD5ng/NSKXOvk3OnQKDJnd+LhIyzai4hnJAmzpf7Snb1vweKwtm3dxx2NVtjVP3mr7ZHTHPjAzrrE2HG4ad0jxiq2idGW2VkNGLfgghhOhMVaiKqrIqLGVx2ZjLuHXarWT5sloFJgvzF3LN+Gu4d8W9vLH3DQBsbfOvbf/i4tEXk9TFSr5J7iQmZU5q9ZjWmp3VO3sdSuUk5PDVGV9t9ZjWmofWPNQqlLpg1AWcP/L8Xu1La83SfUtbBVLDkodx1yl3cfKgk1vV2dJac/Hoi9letZ27P7ybjRUbAVhfvp5H1j/CN2Z9Awftf+miteaxjY+xs6b53OQl5fGT037C9JzpKFR8P2fln8VnJn6GRzY8whMbn+j1+RQDn0zfE0IIcXRTCvJmQdZYc7+hspNpUho2Pm9qGAHkz4aM0f1Xn0nHzIpzTQadAO6Erl/nToJBU5vv7/u4eRTQ4VazF2qLzM9Ot1mlMBoyI5U6utmx1nW9qvaYot+dGXyiqdHUGeUAV4tt2mtTayhZ3xz8eVMh/5Tev8eRABSva76fM8nU/ersPERDJrhqEqg0v59CCCEOu4X5C/n2rG+3CaTArOyW6cvkm7O+yaCE5ppPe2r3xEdPHQ/8ET9/WvcngjFzzUx2J3PPqfcwZ/AcnJaz1XlTSmEpi3Hp4/jhqT8k3ZMef+7FnS+yu2Z3h/vZX7efJQVL4ve9Di93zr6TGTkzsJTVZj+pnlRunXYrZ484uw+PVgxUMlJKCCHE0a+phk/pJkDDpudg5vWmblBLDZVmlBE0jrC6qutRP30pGobaA83300fQ5UqBTTJGNP9cs88EHt0JtHqrZl9ziBeLwHNf6rgQeEu1+5t/jvjNa52dhE6pw7rRmU6m17VUubv556RcM8Kqt4I1zSO/AJY/BGue6sbrqpt/tiPNqy0KIYQ4bJLdyXzpxC/hdXo7nFKmlGJQ4iDmDp3Lv7f/G4CwHWZn9U6mZk9t9zXHEq01HxV/xObKzfHHzh95PjNyZ3Q6fVEpxbj0cZyZf2b8vNWEa3hr71uMSh3V5rVaa5buXxqf8gdwypBTOGXIKZ3ux225WTx5Me8UvtPtWl/i6CShlBBCiKOfUjDpIhMUhOrMFL3Sza2nuGltpvbV7DP3U4aamj/9uopdxKzM1sSb2v3Xttw20mDqS9EPoVSgunlUlrY7Li7eGW0DXRRB9ST13XsRaP7gize1eyFaVyINzaOvwISLLQPG7tCYUWRCCCEOq+k509sNSA6mUEzMnAjbmx8rbSg9zL0bGDSaN/a8EZ+257JcnDfyvG4Vblco5g6Zy3+2/ye+OuJHxR9x45QbcR5U09PWNsuKlrV67dnDz26zXZt9KMXo1NGMThvN+vL1PT08cRSRUEoIIcSxIWucmca38y0TIGx+EQZPaw46moqgN9UEGne2KSLen7SmVTjToxCmxbb9uYJby0KrygGZo3s+uixtmBmZ1pmunu+Jliv69GalxJbsWOspk2n5ZlplTzjcZrU/IYQQh9XM3Jk4urGohFKKNE8aChUPVwLRwOHu3oDQEGloFfZkeDMYmTqyyyAPzHnLS87D5XARjoUBKKwrpCHSQIonpfV+og3sqm6eEulz+picOblb+3E73EzImCCh1DFOQikhhBDHBssFU66EXW+b0GbLSzD3dvA2fjiq2Qe73zc/Ozww+Qq6PXWurzhcracUhuq7/9pwi21dPtNWf3C1GI3lTYHr/m5GmfWI6nzqXl9ztVhNMexvDKl6eb6cnhZhnIKzfgjjD6HAbH+eByGEOA4pVLdGSTWxDvpSRHc1svcYURmspDzQPC3d6/Syq3oXhY7Cbr2+yF/UalRVfaSehmjbUKo2XEt1qDp+P9WTSqav+9Pq81Pyu72tODpJKCWEEOLYoBSMOROSB5tpVRU7Yd9KGH2GeX7X29BQYX7OnQRDpvXv1D0wYVjyYCjfZu43TSXsjpbbJuX0zZS07kgebMIYO2qKfYcbBv5on5QhzT/7y0z4d3B9sZ7ypJipgKFazMp/5abN/v4dEkII0SmH5WhVhFu0rzJYGS9wDqbI++de+1yP2oi1GJkcs2NE7LYLkNSF6wg11abE1PvydLWwSSOlFBleWbH2WCer7wkhhDh2JOXCmLPMz3YENr8AaDP1assS4lPnJl/WegRQf7EcZpW5JiUbTMHyrsRCULyh+X7uCf1XoD1jJPgaP9xHQ1C8tn+nD/aUUiZ0bJq24S+Dsi2977MnGTLHNN/ft5Iu62QJIYTod5aycPfXFzdHsfpIPfZBK/nGdKxHt+4IRoOttvU5fd2aWtly++7UuRJHLwmlhBBCHEOUmcLX9GF059vQUGVWgtu/0jzmSzfTro7UCJcxC5v7V7bFrBjYWWCitSnaXta4Oo7lNCPC+ktiDuSd1NQZU5erO0HakZR7AiQ3LvEdi8Cap1vXmToUlhPGLmq+X/AeVO8d2AGdEEIchyTA6J6YHWv13YrLcpHpzTzkW4Y3o81USGicDtmynCaqR9UT2mtTHFtk+p4QQohjh1IwdCZkj4fi9SaMOvAJ+EuhodJsM/xUSB955PqXNwuGzIDC5abe0Ye/hUt/3/GUuGjIbNO0al/uZBh2Sv+FapYDZlwPO940K/7tXgpr/24e66qIuNamOLiy+jcETMqGCRfCRw+b+xufM4HSpEu6LqjeFDId3F+lYOLFsOwh83tVXwzv/hwu+AU4fZ0fX/w8qL4t6C6EEMew7o7EEYfG4/SYcKjxsndi9on8fP7PDzkEUkqR6m67qrDLcpn6Xo37idgRdA++0InJqrXHPAmlhBBCHFvciSZ8KF5v6iDteBPqigBtAoEpV/XdimyHwpUAC74Jz1xvgqbN/zWjeuZ9AxIyWqwWqCFQCUt/BZteMI85PXDa18xUsv6iFIw+04Q8G/9jRh699n1Tn2v6ZyAxu3XQom2IBqFmP+x539TPOusecPbnVAoFs78IW5dATaFZjfHF283IpqnXmlUXD+5z2A+Vu8y0vKlXNxfIbyk1D+beBq9+z/xurf2H+d95X4eMUQdNqdTmXPnLYP8q2PEGzP+WWYlQCCFEl+rCdcdN0fEjIdWdistyxes9BaIBUj2pfT71MdGViMtyxetN1UfqidiRbu+nLnJ0/B5orakKVRFtuWrxQRSKdG86zv4qwXCUkLMhhBDi2KIUTLjIjC4K1sCO1yFUZ55Ly4eR87o/aqd6rymYHq4zbQTrTKHrA580bxOoMiNmErNMMWxPMniSwJ0Mg6ea4tgH92/UGTD/m/D2T83oo+V/MKHFqDMgc7TZrnKnmX5Yvh3QJkib/SWYcEHH/a89YEKgUF2LWy2UbGweART2w/u/MgXMPcktbkmQM9kcx8EcHjjnXqg7AHuXm/Px1k9g5aOmRlbqMLMaYNhvRhBV7TaF2UP1pqB8f3+YVMqEROfdBy/cat6jYDW8fjeseBgGTTXhkMNtVjWs3Q+VBSZI8yTCxAvbD6WUghk3mPdk5V/NlMB1/4Rtr5r3OmM0uJNMDTB/GVTvgao9Zv+uBJj71f49D0IIMZD04FKgtabIX3T4+iLITsgm2Z1MKGBCqdKGUurCdT1aGa87Uj2pJLmTaIg2AFATqqE2XEtiy5VyO6C1psRf0qf9OVyidpTvvPcdNlVu6nCbRGcij5zzCHnJef3Ys4FPQikhhBDHnszRMGw2bH8NKnY0Pz7uXEjowYet1U/Ae79oDHQ6+DQdqoVlvzvoQWVCmk//C0YtaPsaywFzbjXbvHu/CUzKtzWvyncwdxKccgvM+1rnBc43PQ+v3mVG/nTU32gAPvpT2/5aDrjiL6YI/MGUMiHWlX+F1+6CzS+aMK12v7l1prer3h0qpWD8eXD5n+HVO5vDva767Emk02IXTg8s+rFZAXHZQyb4DFabGlMF73X8Ooe7ufi6EEIcBxQKl+WK37e1TTAa7OQVzWxts7Vy6+Hq2rGhl9/3pHpSGZ02mvJAOQBVwSq2Vm5lzpA5ZrpdH0lyJTE0aSilDaWAGQG3u2Y3gxIGdbkfjWZ71fY+68vhpNHUR+qpCdV0uE00FpVpqe2QUEoIIcSxx3LC1GvMiKamEUION0y5ome1jZze5pXnekpZnQdIDrcJmvLnwPI/mkCjocJMB2s6hoQMUwPr5M+bkK2r4d4OD/jSDq2/KGjxx0PbpxuDqUt/DydcBZ88bqalBarMSoe6cRvLaUaHZY4x0/4mXdJc2P3g/fnSmkNCZzeWh1aYtpte4+oi8FKWWY1x0Almqt2mF8wItLDfrMjYdFyWy7SbPd70t7NzqBS4E8x0y7Fnw6rHYNc7UFdsgjqtG2tHOcx2qcPMezjpEjP9TwghjiPp3uZraFRH2Vu3l+k507sMI0oDpWys2Hi4u3dUOXjKV9gO96495eT0vNNZUbQCMO/PCztf4OTBJ+NUfRcTuCwX03Oms7p0NWBqhb237z1mD57dZVH6qmDVUfN74LAc3DD5BgpqCqgKVVEdqqYmVMOOqh0UNxQf6e4NaBJKCSGEOPYoBZMuhhGntX4soZ2paZ05+Qsw7dOH3o+uAi1lmaLnl/3RFGOv2m2CKZQJXtKGm6LdytG9MO3Ea830vkN18FTDNv1VJqgbd64pHO4vg+rCxjAtYgp+J2SaGlkJmY2jgzrot9ML1zzVHMJ52pkudzDLZUZzxSKNr+lGbS2lTH/mftXUmaorMtMcg9UmQHL6ILFFny1X98615YDB0+DCByBQbaYr1pdAJGBGwPnSTZuJ2WbqXlNfhBDiOKGUYlTqqFaPvVv4LheOurDT0MPWNi/seIGKQMXh7uJRJcOb0er+rupdaK0PeVSTUoqzhp/F3zb9jWK/CU3e2vsWb+19i0XDF3W73ZZFyzt6zYK8BTy1+al4/arX9rzGtROuJT85v8PXaK15c++bR830PYdycPaIs4Hmc2Jj85tPfsOjGx49kl0b8CSUEkIIcWxyuE0o0BtN9ZYOp6ZRNcmDza033InmdrgpBcrZuz4r1X79qq5e05Pplwe/1uUztaYyRnW9fXfbRJkRbQkZXW4uhBDHmxOzT8Tn9BGIBgB4f//7vLn3TRYNX9RmlTetNTEd4409b/D4psePiuLW/UUpxei00a0Khr+x9w2unXAtgxMHH3IwlZuQy/WTrueXK39JTMcIxoLcu+JewnaYRcMX4bbc7bbdFLr4I362Vm1la+VWrh5/dbtho1KKyZmTmZEzg2VFywBTv+oXH/+Ce+beQ5onrc0+tNasLVvLn9b9CRv7kI7tSGo6HgeOQ17N8HgioZQQQgghhBBCiD43Om00J+WexNL9SwEIxoL8aNmP2Fa1jUXDF5GTkIOlLAKRALtrd7OkYAmv7n6VQDRAti+bymDlgKrBo7UmYkeI2lEidoRwLEw4FiYYC9IQbaAyWNlq2+1V2/E4PPicPjwOD26HG7fDjdNy4rJcOJSj24HSuPRxDE8Zzo5qUyuzsK6Qb733Lb449YuMzxiPx+HB1jahWAh/xE9VsIosXxYjUkd02KZSiivHXcmG8g28XPAyGk1lsJIffPADnt/+PGfmn8n4jPGkuFNQShGKhqgKVbG3di8bKzayoXwD++r2MT5jPFeOu7LD/bgdbr4w9QusL19PfaQegHf3vctX3voK10+6nilZU0h0JRKxI5Q0lPBO4Ts8u/VZKoIVZHozqQpVYeujL5wS3SOhlBBCCCGEEEKIPueyXPy/E/8fmyo2URE00/HqwnX8ad2feHzT4yS7krGURTAWxB/2E9VmSvegxEHcPeduvv/B9+OFuAeCQDTAt5d+mz21ewhGgyaUssNE7AgxO0a0aUo6pnbSvSvuxWk5cSgHLssVD6V8Th9nDjuTL0//crf3neRKYvHkxdyz7J74aKm1ZWu57a3bSPGk4Ha4sbVNOBYmFAsRjoW5dfqtfP6Ez3fartfh5bsnfxdb27y25zVsbROxI6woXsGK4hU4lTNez8rWNlEd7XFApJRiRu4MvnTil/j1J78mYkfQmNFQ33zvmyS7k/E5fER1lLpwXXya36CEQdw15y5++OEPB9TvgehbEkoJIYQQQgghhOhzSimmZE3hR6f+iJ+u+CkH/AfizwWjwXZX4xudNprvn/J9pmRNYXDi4AEVRsR0jJ3VOymsK+z29rFY+yO9xqWP69G+lVKcP/J8DtQf4LGNj8WnREZ1tNUIrVa6MQNSKUWqJ5UfnfojJmZO5MlNT1IWKIs/H9VRorFoh6/3ODwMTxne5TQ1S1l8asKnsJTFH9f+kdpwLWCCrppQDTW0XrVudOpovj9nYP4eiL4loZQQQgghhBBCiMNCKcX8vPmMShvFv7f9m3f3vUuRv4hQLIStbSwsPE4PQ5OGsmj4Ii4feznZvmwA5g6ZG29ncGLHNQxHpIzghKwTAOIjkbor1Z3K1Oyp8dE/ne3HoRyMTx9Pmiet2+13JD85v8evaZoGNz1nOs9sfYZ15euoCdUQtaNoNJaycFkukl3JDE4azOi00d1qVylFgiuBGyffyKLhi3il4BXe2/cee2r34I80j2Braj/FncKw5GHMyJ3BvKHzmJAxAYdydLkfl8PFpyd+muk50/nHln+wongFVcEqInYEhcLtcDMkcQiLhi/iyvFXkuPLAbr/e9CVplpY4ViYimAFxf5iqoJVhOwQLstFqjuV3MRccnw5eJ3eQ67Vdbg11V+rDFZS7C+mIlBBMBbEUhZJriQyfZlk+7JJ9aT2aIpoy/bBjGrcX7+fkoYSAtEAboebHF8Oecl5pHpSUag+OUdKtyyXL4QQQgghhBBC9LGmPzsbog2UNZSZMCAWwuVwkenNJCchB5/TF/8jV2uNre14oWsLC4fVNvg4eDsAp3J2+49lW9ut6lZ1tJ+mfcV0rE+KsFtYWMo6pD/qm465OlRNaUMpdeE6bG3jcXpIcaeQ5kkj2Z2My3IdcvsRO0JlsJKKQAX1kXo0Go/DtJ/uTSfZlRyf1ncooYdGUx2qpsRfQm24FktZpHvTGZQwiERXYqe/Bz09b03Hs61qG2/ufZMVRSvYW7cXf8RPzDbvp0JhKQuf00dech5n5Z/FZWMvI9uX3avg5def/Jq/rP8LAInORP550T8ZnjL8kNrSWhO2w7y//32e2/4cGys2tgoloTk4TPWkMip1FHOGzGFB3gJGpo7sVtF1rTW7a3fz7NZneXffu5Q0lBCOhePnyGW5yE7IZt7QeVwz4RpGp47udTAloZQQQogjT9vmhgJlmVXNtAYdg2ANhBvA4QRvKjR9+9mTC6DWYEdNW5GA2YcnGdxJjSvJdbOtpktmLAShetMWgMsL7mRwenret6Z2tQ2RBtOuHTEr8rkTwJUIDlf329UaYmFzrNEgWC7wppiV5+jBsQohhBBCHAPqwnV8/4Pv8+GBD+PTHrtjbNpYfjrvp4xPH3/IwUtfhVJamxDvvo/v47Xdr8XrinXHidkn8uez/9zlCMKoHeWFHS/wuzW/69Z0yUxvJrdMu4XLxl6Gy3J1uz8Hk+l7Qgghjrw9y+Cdn4HTCxc9CMmDYNc78PEjULQOwnUmXEkdChMugBk3QFJO1wGL1hCshg3/gU0vQMUOCNebwCchHYbMhOmfgeGnguXsuD2tTR8KP4Jtr8L+VVB7oEUo5TN9Hn4qnPgpyJ1kgq+uaA2hWtj2Gmx5EUo2QaCqRSiVCClDYch0GH8ejJzXcbtaQ90BWPMP2PYyVO9tDqWSsmH4XJhxPQw6oXt9E0IIIYQ4BnidXoB4IKVQpHhSGJI4hEGJg0hwJdAQaWBP7R721u2NF6zfXr2de5bdwx/O+gOpntQj1n8wgdEvV/6Sl3a9FH8s2ZXMiNQR5Cbk4nV6CUQDlDWUccB/gKpgVXwE4Lyh8/A6vJ22H7NjPLX5KX67+rfxQvMO5WBI0hBGpIwgxZ2CP+pnT80eCusLidpRKoIV3PfRfdSF61g8eXF85FxPSSglhBDiyGsoh93vm7CkdBOs/Qcs/aUZOXTwdkXrYMtLcOkfIWdi50FS8Xp46WsmRDp4pZhAJVTsNGHQzJvgzDvNqKT22qsvgWc+C/tXm8DoYMFqqCuCA6th7T/hvPtgyhWdh2Zaw76P4dU7Yf8nZlTYwQKVUFMIhcuhoQxGnAbtNalt2PEmvPJtc0wHayiH0s2w4d+w4Fsw6/PNo6+EEEIIIY5hTuXkmvHXsK5sHdNyprFo+CKmZk8l05uJ2+FGodBoGiINvLf/PX7x8S/ixd43VmzkvX3vceGoC49ojalNlZt4dfer8fun553ObTNuIz8l30zTbDyGqB2lJlTD9qrtLN2/lDWlazhnxDmdtq215oMDH/D7Nb+PB1K5CbncOu1Wzsg/g2R3MhYWGo0/4mdF0Qp+s/o3FNQUELbD/HHtHxmWPIxFwxcd0jmSUEoIIcTAoWOw9AE48An4MmDap8zIHssFZVtg43MmpClaC//9MnzqGUjMaqcdbUZF/etG87+WA/Jmw5hFkJpnRhDtXwVbl0BDBaz4A6Bh0T3thzW+dDPVT8cgZQgMmQGDp5mf0VC2FTa/CFUFJgB67XswdAZkjOrgODXsXQb/usmEWWCmEw6ZDrkngC/NBHIVO6FkA9QVw5Sr2h/hpLUJ9J77ojkWpwdGzIdRCyAx20zj2/Mh7HjdjMJ6/YdguWHWTTJiSgghhBDHPKUUJ+WexJPnP0luQm67NakUiiR3EueNOA+HcvDdpd8lYkewtc3S/Uu5YNQFqHa/GTz8tNasKV1DMGZWq0zzpPHNWd9kWPKwVsfRVCw+OyGbLF8Wc4bMIRANdFm0vS5Sx0NrHqIhar4MTvekc9/8+5iRM6NN+8nuZBbmL2Rk6ki+8tZXKKwrJBgL8rs1v2Nm7kwyfZk9Pj4JpYQQQgwsez+E3Mlw5aOQNY54HSStYcZnTZBTvN6MLlr1GMz7etsRSdEQvP6DxkDKBQu+CXO+DK6E5rZmLob9i+HZG03QtfKvMOYsGH1m2/Ycbpj/TZh6DYw63YQ9TbWvwLQ362b452eheJ0JkbYsgTm3tj9aqqEclnyzOZDKPxXO+UlzANdEawjVmNBr0AkdtFUBr3zX/K87Cc7/hRml5XA1H+usm01/XrjVTBd89z4YNR8yx0qNKSGEEEIc81wOF0OShnS5nVKKeUPnMTJ1JNuqtgGwp3YPETuCx+E53N3sUE2oJv5zgjOBNE9ap0FT03MJroRO29Va88H+D9hSuSX+2HUTr2N6zvQO21dKMSp1FF868Uv84IMfENMxdtfs5tXdr3LdhOt6PFpKviIVQggxsFhOOON7kDW+dfCjlAlRFt5tQiI0rPunGQnUktYm2Nrxhrk/9iyY+1VTn6llW8qCoSfBaXcACqIBWPlo+9PolIL8OSaUSh5kRl61vOAqBWnDTfDV9PiB1aaPB9Ma1v8LSjaa+zmT4Iq/mNFXDndz4XWlwLLMKK38U0z/22trw7+b2zrpJph6NTjdrY/VcppaXCdeZx7zl5opkkIIIYQQohWf08eo1ObR7v6IP15n6kjJTsiO/1weKGdlyUr6Ys06G5vX97yO3VjmItWdygUjL+hypT6lFAvyFpCXnAeARvPK7ld6VIC9iYRSQhxGWmuzdKyticRswlGbSMzGbny8O6/t6ibEMSc1zxQMb+9bFqXMc1njzP2q3WYUUSvaTPOLhU3wNO0z0NE3W0qZkVHeFHN/30rwd7DaSFer9CkFg6bw/9k77/g4qnN/P2e2F/Uuy7JkufeCMRjTqwFDCJBCElJIQtpNzyX1QpJfenJzk5BLkktCSAghAUILvYMxuPfeJMvqvWzfmfP740grrbWSVi64cB5/9uOd2ZlzzpRdzXznfb8v/UaSoY6Ban2DMaOw/VE1TmHAkv9QaYBHErFkRtW2IlWU1Nz3KcEsFYYNpl2pBCqA/S+riDKNRqPRaDQaTRI+x8DDQEtaJ/S+SwjBwqKF+B1+AKJWlO+++V3+sv0vtIZaj2psgWiAHW07EtNV2VWU+ErSWjfDmcGcgjmJ6X2d+2gONo95DDp9T6M5DkgpCcVM1lZ3sGJvK3ube+kMRolbEpfdIM/vYmK+jzMqcjlvcj5221B9OGpa/PSZXdR3Dl+29PKZxVw7r/SYmO5JKdlW380ru1rI9Tm4ak4pmW77CTX007xDyasCV+bwnzu8UDJHeS2ZUWWMPv7MAVEn1ucXBcqnqXCain4a7u+1Owvc2SriKtShUuoyikcfZ9IFgFTTNqeKboK+iKsUnQZaoHWPeu/Ng8rzjzyFLtACrSq0nIwSValvpCd5GSXKcyoah646lcrnGLkai0aj0Wg0Gs3phJQSiSRmxQjFQ4TjYWJWjKgZJWbFiJkx2sPtJ3qYSVRlVXH9lOv567a/YmHRHm7nF2t/wQM7H+DSCZdyReUVVGVX4TScY7p/awu3JW1rZVZl2lX0BIIp2VMS04FYgLreukT0VLpoUUqjOcZIKaluC/Jfj23lrf1txMzhlesF5W2cU5WHPUVgg2lJXtvTwp6m3mHXr8hPkc5zhLT2Rvns/eupaQsigJq2IF9fNu2Yta/RpI2/aHQD7uzygffdh5I/i3SpanmgzMIf/czIleYsS6WzgRJ0Ij2pl5NSVbnrqYfGrSpCq7sOwt0q9S8ehlCnEsVGord5oI/MUiVMHSk9jQNt9TTAAzeNLHDFwwPji4XUS6PRaDQajeY0R0qJhUVdTx2rGlaxrnkd1V3VtIfbCcVDCVPz/teJTtc7HEMYfHrupxEI/rnrnwTjQSSSQ72HuGfbPTyw6wFm5M3gysoruWD8BRR4CtISpzrDnUTNaGK60FuY9piEEElphaY0aQm2jG3D0KKURnPM6QnH+c+HNrGmuiMxz24T+J127DZB3FRRVNG4xeKJeTjtqW++7YbBxdOKGJ/jpSsUoyccozccp6kngmkd+/DRxq4wDV3qZlUCW+q6MKXEfhJHSh0eqqqjuk4THJ6RPxciOZLqcBEpFhoQXswY1K4aQ+cSrBSeUlKqiKyVv4a9LypT8b7c+6RxIYbOP5xI90Af7uyRBbPRCHcPREZFe6HmjfTX7RfZNBqNRqPRaE5jpJQ0Bhq5e+vdPFf9HJ2RzhGXFwjksCH2JwYhBF67ly8u+CLnjz+fe7fdy6qGVYTi6gFjKB5iXdM61jet5+4td3NN1TXcOPVGCj2FI94jhc1wwk8KlJ/WWO6pPHZP0v4KxANj3jYtSmk0xxApJc/vaGJdjRKkBHDx9EJuWVrJhDwfDptBzLToDEY50BpkWknGsG05bILbrpiKlGBKSdyUdIWivP//VnGgdexf9tHI8TnIcNlpiyulvDLfh3GSizybDnVx/6oaphVn8pFzKk5QkVbNMcdKQyhJEiRFis/6Pnf6VEU9I03hRxjgP+wJkZSw/xV49NMD1fIyipVJetEMyChVIpnTA70tqqqeOYJX0+DxHfV3bNC+8hdCxbkM2R/D4XCnNk/XaDQajUajOU2QUrKncw+3vXYbezv3Jua7bC7KM8qZlDOJMn8ZuZ5c/A4/bpsbt93NfdvvY1XjWB5sHn+EENiEjYWFC5mbP5cd7Tt4fN/jvHboNZoCTVhYSCQNgQZ+v/n3PFP9DF9e+GUuGH/BsMblQgh16dh3aTpWf6rDxTvjCGzLtSil0RxDJPDSzmb6A5kmFvj4yfVzyPUl5/aWZnuYUZo1Ylv9ywsBBgKHDSQObMbxkV5KszzcvnwmT2yupzTLzacuqDqpRR4pJU9vaeCfaw9x4dQCPrKkIu17cc1JTnT4lFVAiTqDK+4d7j/lcIPdDdGA8ou66pfgzT3y8QTb4ZmvK0FKGDD/Q3De1/rMyY1kYal5h/KUShFsNTBevzIdNy21HVZ8eHPy0XBlgLCpiKecSrjud+kLcBqNRqPRaDSnOYFYgB+89YOEICUQLB23lI/P/jjTcqfhtrsRiKR7NSklz1Y/e6KGPCpCCBw2B7PzZzMrfxa3zrmVNxve5Il9T7CheQORvoejNd01fGvFt/jh0h9ywfgLUkZA+ew+bMKWiJbqjfUipUwrWkpKSW+0N0mY8jv9Y94eLUppNMeQaNyielAU01kT84YIUicrhiFYPreEq+eWJLSdk3nc0bjF6uqTy4BQc4zoaVBCzbBpbRI6awYms8cnf+zOAl+BSrELdym/KN9R+DbVrhowEy+aDZd9Xwlhqb4f8fDokV7+QnD4wOyE7noItSsD8iMho0SJXP0G7ZHeoxPgNBqNRqPRaE4TpJSsalzFppZNiXlLxy3lJ+f9BL/DP+K9jpnKzuEkQwiBQPk6LZ+4nCsqrmBjy0bu3nw3qxpWYWHRG+vlzo13srBoIZkpCgnlunPx2D3EojEAGgINYxpDY6Ax8d4u7GPypOpn7LFVGo1mWGKmRU94wBSvNHsUb5yTDCEEhlBPCk5mQQqgoSvMvuZRImo0pyZt+5RQMxzRADRsVu9tLiicniwQObwqtQ4gGoTq1w9L9xsj7fsHvJfKzhhekJISWnaqioAj4StUFQYBAq1Qs/LIx+cvhPy+qic9jdCw6ei2VaM5XZBSecqFOtT/+nuh0Wg070jWNq7FlEpgsgkbH5j+gdEFKWnSHjm1Hn4LIXDanCwqWsR/X/DfXFZxWeKz/Z372dG+I+V6uZ5cin0DVaf3de5LRFqNhkSys31nYjrDmcE4/7gxj12LUhrNMURKsAZd+NqNk1/cORWRUrLpUGeSAKg5jehtgj0vpL6JlBKqV0B7nydA7kTIn3rYQgJm3wB2FyBhzR9VxbzRbkqlTL3M4NS6kSqxxAKw8e8wmjGm3Q3Tl6txShPe+LWK5jqS8dlcaluFUGLYm3eq9Mcj3VaN5nQhFoLHPwe/Oxee+IKKYtRoNBrNOwqJpCU0UA3OY/dQnlk+6v1ZR7iD6q7q4zy644MQAp/Dx03Tb8LRZ+kQl3Hqe+tTLu+2uTmj6IzEdE13DQe6DqTlLdUaamVL65bE9NTcqeR5xp6doNP3NEeMlBJTSlp7ohxo7eVQR4jucAwpweeyU5DhoizHQ2mWB7/bjiC9dDApJb2ROPtbAuxvDdAeiCKAggwXkwv9VOT7cNmNUduSUnKoI0RvJI4hBBPzfTjsBlJKInGL/a0B9jT10Nqr2s/1Oakq9FOV78PjtI3YvpQqc9a0JNG4RTBq0h2OUd8ZIhwbSN1p7omwo6E7ZRt+l52ynLFVNzhWmJbkQGuAmDl8mlFBhot8v+uo++o/njVtQWragrT2RojGLZx2gxyfk9IsN+NzveT6nCOKeFJKTEsSiJo0d4d5Zmtj4ta/NxJnR2P3sMbsLrtBRZ4P4zj5cWmOMdKCV38C+ZNVxJMQ6tUfifTid1XkAwLmvV/5Kg1GCJiwBKZdBVv/pdZ55FNw+Q+gYDoY9oH2kErM6a6HA69B6QIomZPcXv4UtY4VV1FNPQ0qba7/fJMSwp3wyo+VYDYaQsDc98HG+1VaYMNG+NetcOn3VNSXMfhPs1SVBDtrVJXBskVD25p1A2x6AOrWwb6X4MmvwoXfgKzxyvMqqa0QdNTAgVdhxrXKF0ujOR3prIHtj6lzfvujcM4XoWDK2Ns5/KJcP2jSaDSaUwaBwGk4E9OWtIiP9ICRPj+pmmdpDjYf7+EdN4QQOAwHYpDhrmOEas/LKpfxyN5HCMVDBONBHtz9IN9c/E3sYni5SErJk/ufTOwnA4NllctGXGc4tCilGTNSSuKWZNWBdu5fVcOaAx10BKPEreQLN0OAy26jOMvNooocvnTJFEpGSGeTUtIdjvPg2loeXHeI6tYAkfiAaCIAj9PGzNIsPnpOBZdML8JhG17EsCR8/9/beXV3C26HjX/cehaTCzNYua+V3768j82HOglFzYSwIQCXw2BqUQafPG8il80sxmFLHUwYtyQ/fnonm2o76QhG6Q7FCUbjROJW0n7488pq7nurJmUbF04t5H8/uOCEeHMHo3E+9dd11HYEh13mS5dO4VPnVx1xH1JK6jpD/GNNLc9sbaS2I0gkZiXFkAjAbhNkeRxMK87kg2dN4PKZRUOMBlfsbeXlXS3sbuzhYHuQtt4IwehAnve6mg7e/b8rhx3LpEI/D37qbLxO/ZN3SlA4A1r3wP3vhSmXw7gFKiKoZae6yeyuU8uNX6xMx1P9BticcOn3ofMgHFqrBKc/L1fpdwXTVNW5WBh6G6B1r0rRi/TAe+8bKkqNW6jG1LgZ2vbAPz4ECz4E2RMgHoHmbWpcjVvUst31A2McDn8xLPsJPPwJCLbC/pfh3quVKFY4XQltsZBqp3U3tB+AWe8eKkoBeHLgql/APz+sbsQ3P6DaKztTpQnaXSp6qqsO2vZCR7US/iZeqEUpzemL0z/wPfLkgHv4arcjIi1Ydw+EOuHsz6j0YI1Go9GcMpRnlifeh+IhNjRvoCKzIuU9pJSS1Y2ruXvz3UOqyp1I4lacTS2bqMqqIsulimWN9CA/LuM8W/0sUUtZSrhsLioyK1IuL4RgZv5MLhx/IU8deAqAJ/Y9wbyCeVw18SoMMTQYpH8/3bP1nsR+mpwzmYvKLzqigAt9h6YZE1JKukIxfvHcbh5cV5sUFXQ4loRQzORAa4BwzOSrlx2eYpPc7oHWAN/41xZWV7enztoBglGTNdXtbKrt5PqF4/j6sulkuu3Dnvwx0yISt4iaFvuaA2w82Mn/e3IHvZGhCrkEwjGLTYe6+PI/N/HFS4J88ryqlNXuLEvy5v42ttenjoLqx7RUdM9wYzuRSJS4Zlmpf3Lj5pH/EJuW5Jmtjfz46R3UdoRGHEPMlLT2RnljbytXzU5t9vzg2kM8vil1yCmoc22wgHk40RE+05yETF+uohPe/A1s+rt6JSGU+HPtb9TNZiqEgMxxcOO98Nx3YNeTKppp7wvqlQqnDxwphHN3FlzxQxXN1F0HdWvVqz8KSVrq/cQLYPmv4MXvwZYHR95GIdTyN94Dz34LmrYqU/b9L6tXynWGqdAnBJTMg/f9DZ75Bhx8U6VA7nxi+P79RSMYyWs0pwFZ4+C6P8Ch1VB5vhKCj4RQO7z+S/UUZdEtWpTSaDSaU4yzSs7ij1v+SNgMI5H8ftPvKfYVs6BwAU6biqIyLZOWUAtPHXiKv2z7Cx2RDvwOP72x9PxrVQaRiSUtTGkSM2PErBhRM0p3ZOB+0cKiMdCI2+7GaThxGA7shh2bsGEII6UABEqU+unqn9IT6+GskrM4q+QsJudMJtedi9vmRgiBJS3C8TAHew7yyN5HeHzv44n15xTMYVL2pGHHbxd2Pjvvs2xt3crBnoOEzTA/WPUDdnfs5tpJ11LqL8VhODClSUuwhedrnucv29V+AvA7/HxxwRfJco5cXX7Y/o9oLc07lp5InK8/vIVntw2kTtkNQWW+j+klmRRnubEJQVsgyv7WXva3BOgIRrl4eiH5GalTwaSU1HeG+fzfN7C1T+SxG4LZZVksnZTPuGwPlpTsbw3w2u5W9jb3EDUtHlitRLEfXDdr1AgYKeGBNQfZfKiL3kicwgwX500pYGZpJj6XnbbeCG/sbWPVgTZipkrvu/PlvSyYkMOZFblDfhxshuC9Z4ynuSfZoyIat3hgTW3C62hJVR7zy7NTjqmqwH9CoqQAvE47//uBBbT1RugKxegIxmjqDvPnldV0hWJH1bYlJY9uqOO/Ht9KIDIQzZTvdzKjNIuKPC9+l51g1KS2I8jepl7qu0Lk+VxcOK0g5Q/xZTOKGJ87IBZICc9ua2Rfi6p0OCHPy1WzS4bNqsjzu4aNetOchER74ZLvQvliWPdnZd4d6VEiStZ4JVrN/xB480ZOpekXpq77nUq72/ow1K2HYItK/zPsKpIie4KKupp86dAoqf52JiyFD/4LVv9BGacH25QY5fBBbgXMvA5m36hM0Kcvh0ALlMyFkb7lwoCKc+Hmx2DX00o4a9mlxCkrnjy+inNUHyNta9EseP8DsPd5FbnVtFVFd/RXMnRnKw+uiqUw6VLIqUjnaGg0pybCgKoL1etoaN6uRN6MomMzLo1Go9G8bQghmJE3g4vLL+bJA08CUB+o5wsvfYFJ2ZMo8ZcgELSGWqnurqYj3IFEMr9wPjdMuYHb37iduBzdw3Zjy0Z+u+G3BOIBQrEQYTNMxIwQNaOE4gMP6EPxEJ9/6fM4bU5cNhcumwu33Y3H7qHAU8B3zv4Oue7UVZRNaVLbU0ttTy0P7X4Ir8NLliuLDEcGTptTCWDRbtrD7UlG5QWeAr6w4Au4bMPbsgghGJ8xnu+d8z2+8fo3aAg0EIwHuXf7vTy05yEKPYV4HV4iZoTmYDM90Z5EhJTX7uVLC7/EknFLjtiWRotSmrSxLMnvX93Ps9sHBKnJRX6+culUzpmUh89lT7r9ipmSlp4Ia6rbmVGaOazfT8yU/OSZnQlByueyc9sVU7lhYRkeR3JkwOcujHH36wf4/Wv7iJmSxzfWM70kg0+cO3HUL8Hre1oBOH9KAXdcM5MJed6Ez5WUko8treSB1bX88KkdROIWgYjJ3946yBkTcrEd1rTNENx89oQhffSE4zy9tTEhSp0/pYBPnjdx2DGdKBN0myGYWpwBqHSGft+nRzfUHZUoJaVke303P3xqR0KQ8jptfGRJBTctLk+Ilv1YUvlB7WzoprknQmGme0ibQgiumlPCVXMGoqgkUN0aSIhSE/N9fPWyqdrq43QhHlGCTNXFKsUs0q1ScAw7uDNVKl+6B1sIlb428QKYeL5K2Yv2ghVTkUcOLzi9A1FIw7UrBBRMhat+rir6RXuUOmp3g8sPhmNg3enXwLSr+6ZHGacQ4M2FeTcpn6lYUFUXtEy1vQ7PwPhG22Yh1FhmvAumX9vXVq9qy+ZQ2+rwqJt1/WXRaEZHSqh+Q/1eaDQajeaUxGE4+MoZX6En2sOK+hUqosgMs7VtK1vbtiYtaxM2zi07l28t/hZ2w06uJzctb6m2UBurG1enlfIXjAcJxodaqGS5soateieEIMuVhUAg+/4FYgECscCw/RjCYEbeDP5z0X8yJ3/OqPedQggWFC7g1xf9mp+u/inrm9djSpNALMCB2IGhyyOYkDmBLy74IheUX4AhjjwAQItSmrSQUrK3pZe/rapJpNZNLc7g9x9cqMSdFCe50y4Yl+OhNHt4zxIpJWuq23l2WyOgfKg+e2EVH1g8IWXaXLbXyecvnkx7IMr9qw9iSskfVxzgilkllOeOHlI/pcjPT66fQ1GmK2nMQghcdhs3nVnOm/vaeKZvPOtqOugOxcjxOZPaGYuYdCpU3ztWY4xbkv99ZR9tgb78ZbvBf109gxvPGJ/yeNoEZHkcnFmZ+onAcOMbrhrEqbCvNWNACCXGeHKGT9MbS1sIJfA4jzD9pr8Nl1+9RlpuuFS70dZxZQw1bh8r/cbwo41Tc3yQfeb5PY3KFD8aUMfDnQW+QvDlKzETRhcH+834Qx3QWatSyYQN/IWQPV5F6o3ld6//tzPSoypSBlqUCGxzgidXpXV6sgeKAQzGjEOkS723OZVn03B9S6ki/qSpRFB31mGm+33EwqpqpbApwVkYA/uvq1b5s5kx9VnmOPAVpB4bqIjAcDcpq18KW98Y0thX/fvIiqv9vv/VvvkWBNvV/4dj2FWU5ODiB5GeATHLlZleuqwZUyI8KKHblaEFZI1GozlKhBDke/L5yXk/4akDT/HE/ieo7qomFA9hSQu7Ycfv8DMpexLLq5ZzcfnFeOweLGlxVeVV7OncQ4GnAJsx/LVdniePpeOWHpUPlc/hGzaayWk4+dG5P2JF3QpW1q9kX+c+2sPthONh4jKOlBJDGDhtTrJd2UzNmcrF5Rdz3vjzyHBkpH2PJIRgas5UfnPxb3i59mWe3P8ku9t30xPrIW7FsQkbPoePiqwKLi6/mCsqriDfk3/U92BalNKkzeOb6ukMqgssp93g61dMG1aQGszIVezg4XWHEn5AFXk+3r+oPKWA0Y/DJvjEeRN5Zmsj7cEoTd0RntrcwK3njxwtJYCPLKkcIkgNxm4TXDazKJGe2B6M0tIbGSJKaVJzoDXA63sGyq5ePrOY6xeWjXg8QYtJGo3mNEBKJfBsfxTW3wvNOyDSq4QZUMKF06/SJieeD/M/CLlVIws7nTXw1l0qvbO3caDqpMOt1p3/QRVlN5JANLi9tr0qJXbPc8ofLR7p80QTYDiVIFU4Hc64RVWvHNxmyw544CYlGE29SpnrD4cZhQc/rIoT+Arh5kdVuu3hbH8UXrhdVbP80CNKOKpeAa//QqXaxgJq3IZdpZ9Ougiu/pXa/sNpPwB/uxHiKXwMcypU+q3TN/I+igZVmm/DRnX8Omugu0F91tMI91yRWlwrWwQ3/hkGVxx68051HmDAFT9S1S5HOkZSws4nlS8clkpRvvBbI49Xo9FoNGkhhMDv9HPjlBu5dtK1dIQ76Ip0YUoTl81FtiubTFcmdjHgVWxg8MWFXxxoY4To93kF87jz4juPfpzD9CGEoNBbyHWTruNdk95FOB6mN9ZLIBYgYkawpJUQjLJcWXjt3mH9qUYdgxD4HD6uqryKKyquoCvSRUekg6gZxWE4yHZlk+XKUtX9jtE9nBalNGkRjVuJ9DeAmaWZnFWVd9QnYlc4xprq9sT0uZPzyfaO/DRRCMH4XA/zy7N5cacKp3xpVzMfW1qJ0z78eLI8Ds6dPLKSK4SgPNeLzRDELUksbtEbHj2PWKOil1YdaE+kLjptBjctLsc+iiCl0Wg0pwXxCDz3LSX6WHGgL3XU5lYplPGIinQKtSuftJK5SlhKhZRQ8wY8/h+qMiSoyBmHV4lIsZCqBvnM1+HAq8pg35s/vOhhmUpsef6/VPRWP8Loi06ylJjTE1Li18x3D23DjClhxoyqogEjISUEWtXyUoI1TLGJWFAtEwupyKo9z8NTX+trX0D/U2kzCoFmiEeHjzgSApAq+ioeUVFK/WW/Hb6BCKiRCLbBC3eoCKnEtvSJitJS25TqhiHUMbT9SZfAyl+rbdv4N5h2pYowGw5pwpZ/qgg2W1/KsUaj0WiOKUIIXDYXxb5iin0jF8AQQowoRB3pskdDfz9ehxfvcS68IYTALuzkefLI86R4sHQM0aKUJi3ag1Fq2wdyXxdX5uG2H71xdENnmJbegdzZeeXppejYhGDu+AFR6kBrgK5QjIJhzNQBSrI9w5qtD8ZpN/r8r1QAppnOhawGgC2HOhPvizJdTCtOP1xUo9FoTlmkhN3PwLp7lRBSOBPO/gwUz1HROWYEuuqgbp2qrhgNQOV5qUUkKVWE0SOfUilszgyY/wFloO8vUuJQ0xZ463dQv15F1zj9cM1vlAiWqr2d/4Z/f0l5jAlDmeLPuFaNz5WhIpJa9yghrLNWmf6/nb/dsbDaf6/+VIlOiz4BleeqdL1YSEVp7X1JCTvDeVbkVMLHX1T7NtqrIpwe+zT0ju4FksBXoCKe+tPuYmF46qsqqsxXAFf9d+qUWHf2gIAGfRUx56gIqgOvqYqYLbugePbwfXfUQM2b6n3RTCidr1P3NBqNRvOOQItSmrRoD0QJRAYihiYX+o+J2NDUHSbal7pnNwSlWe602hVCUJYzUI2tJxyjPRAdUZQq8DtxHkkFNq1JpYUpJXUdA2kTpdkefC79E6PRaN4h7H5WiRkOL1z7GyhdkCwqFExX0TNLvwjBDuXhlAozBi/9QAlSdg9c/d8w6/pkg/rC6UrU+vtNSpja9ohaZvJlQ4WMnkYV/RPtVd5KZ34SLrhNCSmDl626WH0W6VafvZ2YEXjx+5BVBtf9vq8KphgYX9VFcOat6v1w1wiGTfl1+fLVdOa4Ae+udHG4lRjWT6R3wIPO7lKfpetvZ3PB3PerdMRIj4pUK5o1vBC55zkVRQeq0uZxfgKu0Wg0Gs3Jgq6RrkmL3nCcuKXUGUNwzDyWeiJx+prFMMSYRIwMtyMRJBk3ZZJolgqP06YfOh5HLEsdz36yvY5RvaQ0Go3m9EAmm4B784aKD/0G9HY3ZJYML640boJ9L6j3Uy5XAoVxWPVFIcBfrKKxhKHS2zY9MNSEW0olWLX3Vc2pugAu/s5QQaq/TaOvsMCJ+GMpLVj2E5XWeHiFSCFUBFU6ZuEnC0KoiLPscjW9/fEB0elw+r3IQO3/w/28NBqNRqM5jdGilCYtrL4CQP3YjtG10uFV1MbS7OHV1kerdmCItyPT952LRGJZA8fA0BfUmrGQOQ5mvVu9Sued6NFoNGNEQP4U9TbcBSvvVP5EY03/lhL2vKBS1hAw4xpl8p2ySwHjFqrUPYD6DSoaajBWXKXF0WcWvuiTKgLnZPx9Ll0A5WefnGM7Urz5Kk0SoKNaVfI7/JyQEpq3Q8NmNV1xLuRMeFuHqdFoTk9iZoz9XfvZ2b6TnmjPsNWrNZoTjc6t0aSFy2FgGGCa6vqpN2oek3Z9LjuGUKKXZUlCsfTbDUbNxLWdzRC4HWMswa45phgi+RgE+o/PaXR/oTmOjFsI1//xRI9Cozly5rwHNt4PvU2w9m6VtjXvJuUFlT1epc6NWiHPUul4oKKCDDu07hp++VDnQPRQqF0JYu6sgc/DXariHqjordJ5J6/oM27ByEbgpyJCwOwbYc2fINqjotmmLx8a8bXjCWX6LmxqeaGvZzQazdERs2L8Yt0veHTvo8StONNzp/Oz8382qrm3RnMi0KKUJi1yvE5cdhsxM44EDrUHkVIeta9UUYYbh80gErcwLUlzT2T0lVARVg2dA/5FHqeNHO9pdjF7imEzRJKRfFN3mEjcxOvUPzOaNDhZb5Q1mnQQQnlGXXMnPPsNaNunzLmf/w688T9QsRTmvE95Ejn9w5/vZmygOp4ZhX99cuTvhpQq9QtUVFT8sL+hkW71AmXUPViwOtnwF53oERwfCqZBxRLlOXZwZZ/h+ayBzyPdsOsp9T6nQp0r+vdQo9EcJQ29DTy+93ECsQAAG1s28tqh13jP1Pec4JFpNEPR6XuatMj3O8n3D4g+62o6sI5BBGhptpvcPn8qCWyt60ortFQC2+q7B9rJ8mhR6gQjgKlFGYnpuo4QdYOEQ41Gozmt6fcQ+si/4aJvQe5E5Y0UbIPtj8E/PwT3XqM8nuKR1Kl9VlxVfEtMx5RQNdzLiisfKMOeOs0vHlbLADg8w6cCngwc7pt1umDYYd4H1PZFemDbvwaOvZRwaI0SMUF5SaVrpK7RaDQjEIgFiJjJDyq6+r0PjyFSSkzLxLRMnR6oOWJO4qsTzcmEz2VnfnkO1W1BANZUt3OgNUBVge+ooqWyvU4WlOfw5Bb1ZHjFnlY+d+EkvKMYnrf1RllX05GYXlyZi9uhNdYTiRCCxZW5OGyCmCnpjcR5eksjky46NpUak/oCxCATdUvqIokajeYkQAjIKIFzvwoLPwr7X4YtD0HNShURU78eHrkVzvgoXPJdJRQlrW8o8QLA4YNrfgMZhWn2bYOscUPn9edQW/GhRujHDQny2KT5n/IIAZXnQ95kaNmpBMqzPwfeXKDPiL6/auPM605PYU6j0bztFHgLyPfkUx+oB8BpOJmeN/2Y91PdXc3P1vwMS1p8aeGXmJo79Zj3oTn90XfxmrQQwDVzS3H0OZx3BGP85sU9hGNHp4obAq5fMC7R7vaGbp7f0TRim5aUPLz+EPVdKgrH47Rx9dzSIx6D5tgxpyw7KVrqvrdq2FbffVyenGS6Bzw5mntUqqBGo9GcFAgBvnyYdQO89z746FNwxseU0GRGYc0fYevDQ6OlbI4+sQIl6hRMUcbX6bwmLFHCxmBcGQPCV7C9z0D9bcCMQjT49vR1KuDOglnXq/ftB+DAa30Gnc2w7yU1f9wCKJp54sao0WhOK/LceXxj8Tc4q+Qs5hfO56uLvsri4sXHtA8pJWsa1/B63eu82fAmXdFjH4mleWegRSlNWgghOLsqj6WT8hPz/r25gTse305jVxgp5RDhQUpVja0zqKKaUokGQgiWTMrn/CkFAMQtyU+e3smqA+1Yh7UppSRuWTy7rZG7XtmXuJa/YmYxc8qyjnk0jmbs+Fw2Pn7uxITI2NwT4Yv/2MjKfW3ETCvlOSKlJBwz2dXYQ217+jcx04oHxK/9LQFW7mvTYcMajebkQgglNBXNgit/Bst+DIZDRS1tfXhoNJFhh8IZ6n08Ak3bx17BbzCebMjse2jT2wwdB468rcElb604I8anBtsg1DH85+80hFBRUJ4cdcy3PKj+r34dehoBoQTM083oXaPRnDCEEJxfdj53XXIXf7z8j7xv6vtwHF5k4SiRSFY3rj6mbWremej0PU3auOwG37hyOvtaAhxsD2JKyT/W1rJibysXTC1g3vhs8vwuhICeUIzajhDb6ruVTxSSxz+7FJd9aEUZl93gG8ums7e5l+q2IPVdYT7113VcO6+Ui6YVUZTlUrYLHSGe3dbIU1saCPZV/5tS5OfLl07BbpxeglTctAhETaJxi0jcJBwzCUVN2oMxgtF4YrlDHSHW1XTgcdrwOGy4HTacdgOX3eirbDh0v8RNi0DEJGqqtkN9bbf1RpOqHx5sD7C2uh2v047bYeDpa9s5QttCCJbNLmbVgTYeWFOLlLC3uZdP/GUtZ1bmck5VPuV5Xtx2g3Dcoqk7zJ6mXjYf6mRfS4A7rpnJ+FzvkHZT9XPOpHyyvQ46gzEicYtv/msLHz93ImdNzMXjsCVSCNsCEWxCcMmMopRj1mg0muOOECDsMO1qePUn0HVIiURmfKjP06RLYN2fB4Srme8CuytVq6Nj98CEpdC4BeIh2PwPKJ4zkCI4Fpx+JbCZEeiuV55WqcYlJdSuUtXmTnWEGKiEZ5nqdaTkVkLVReqYHnwTOg/CzidVSqW/SPmR6b9RGo3mGCKEwC6O3+1+T7SHra1bj1v7mncOWpTSpI0QgsmFfn79/vl8/eHN7GxUF5x1nSH+tuogf1t1kH5t6HAT9JIs94jtTizw8T/vm89XH9zE3uZeOkMx7n2zhvveOojDLkBC1LSS2p1eksEvbpxLWY7ntIuSWlPdzn8+tJlQTAlTcUsSNyWmlJiDdsK/N9Xz9JYGbIbAbgjsNiVI5fic/OnDixiX4xnS9oq9rXz70a2ER2n7wbWH+Nf6OtW2TeAwlCBVmOHiTx9dRGFG6mPqtBl888rpGELw4NpDRE2LYNTklV0tvLKrRflBCXXfMvQ5e/oRARPzfXz47ArufHlvonLjD5/agdNmYLcJTEsmXosn5nLx9KLEQ36NRqM5plgmRHvBlammU/1NkhJ6m5TZNYA3b6ggJYSqvlY6Xxlg738Z1v9F+VOlMgLvj6KKBpRglEokmvte2Hif6nfDfVB+thLHhDFMe1IJJYePzVcA/kJo74XmHdC4GcadkdyGlBBohVV/OLoIr5MFm3MgnTLUCR3V6rgdyTWHsMG8m2DH4yqVctfTULtGfTbpYsjQNgQajebUYn/nfpqDzSd6GJrTAC1KacaEEIK5ZVn8+aNncs8bB3h8Uz1N3eGEWHS4GCUAv9vOvPHZOO3DZ4v2t3vPRxZx50t7eXpbI92hmBJKYsmN5nqdXD23hE9fUEVxpvu0E6QAglGTQx2hUSUaiUp5jFsSVV/DTKwfM1Mb2gajJnVjbTs+0HbMtDDN4dcWQuB32bl9+UzOnpjHH1ccYHtDN5G4lWj38HsVh01QnuujLGf0KKl+DEPwqfOrsBmCe1dW0xaIAkq8jB72MNtu6ExljUZzHAl3wT8+oNL0Jl0CBdOUmGE4AAmxIDRuhVd+qJYVAqZekTpiyemHi/8L/nmzSoF77jvQtBXmvh9yKpRQYsVUO+37lYn6gdfhml+pKKjBCKHmnXELrPy1EqYe+yzUvAmz3g3Z5ao9M6qEkpadsP8VFdEz813Jbbkz1fz2/UqAe/IrcPmPoGSO2s54GJq2wWs/hcZNA+2+Hcg+IU32RTNZcQi1D0Q2SVNNI/sqFdqUSJRKmBuMYYfxZ6l9HA/BS9+HK34COeWA0VctMaTa9RWM3JYQqq3CmdCwETbeD72NSkycfaOOktKMmcGWBRYWSHUNJgY9gTuW18j9/aXq63hci/f3J/v+He/tOxEkbaOUx32fHkuklKxrXkfMip3ooWhOA4TUJiyaI0BKiQRaeiJsrO1ky6EuDnWGCETiCSGqONPNlKIMZo3LojzXi8MmRv2BlVJF7BxoDfDmvja213fTHohiCEFBhotZ47JYXJnL+Fwvhhj5B1tKyau7W6jvVMau43O9LJ2UP+oY2nojPL+jCctSfxwunl44bFTQ4UTjFk9vbSCgVBzmlecwoyQzrXUHU9cR4tXdLRxpTTmHzeCKWcVkuIfmjh9sD7JiT+sRt+2y21g2q3jUComgjkEoZrKzoYf1BzvY1xKgIxAlbkncDoM8n5OKfB+zSrOYUpxBpts+pj/CypNKbdMbe1vZ1tBNW28UKSU+lzoHJxb4mDs+m8mFx74KoEaj0QDKQ+l3S1Vam7ApAceTC06fEktCHRBo6RNpBEy5DK77g/J8SoW0YNuj8PR/qvVAiTzurD5RKq6io2JBtazNCbc8pyKsUhHpgWe/qYQQqy8F3OZS47Q5VSpetHdAYLny53DmJw4bk4T2fXDfDQPeVHaPqvjn8Krqgj0NEI8qwUtK2PYvlZr2qTfAXzB0XGv/BP/+knp/xY/hrE+nv88Hc2gtvPwDiPRCrG+/xEIqRVJa6pj4C8HuBqdXjdfph3M+r4S24ejf5r+8C7pq1Tx3NmSOU8JWLKj2W+X5cN3vlMg1ElLCW3epY9H/N7hoFnzsGWVKr9GMgrr+ljQHm9ncspntbdup762nO9qNKU2chpMsVxYl/hKqsqqYmjuVcf5xuGyuI7oGklISMSPs7tjNuqZ17OnYQ3u4HVOa+B1+yjLKmFswl/mF88l15x71dZaUkriMU9dTx5bWLexq30VDoIHeWC+WtHDZXGS7sin1lzIpexJTcqZQ4ivBaXMO23d3tJuNzRux+qqPZjgzmF84H2O072sfXZEuNjZvVMIYkOXKYm7B3BHXt6TF+qb19MZ6AZiUPYlx/nGJMVrSor63nlUNq9jaupWmYBMxK4bH7qHYV8zUnKnMLpjNhMwJOI3ht61/n21q2URnpHPE7TCEwYLCBfid/rS2O6mPPlHQlCaheIiWUAsHuw9y16a72N62HQCB4D/m/weTcyaP2JbP4WNB4QJshz2UMS2Tdc3rCMaCifbmFMwhx50z5vGalsn65vUEYoFEWzPzZ5LvyR9lTc2JQotSmmPCgNKv6P/pPJo/TsejTc2J4/DjCcf2mOrzRaPRnDBiQXjqNtj9tIo4OtzAHJQwklEMc98HZ39OmV6P9PskLWjYDCv+W0UvhbsZ8jDBcCixpepCuPh29T5lW1IZp299CFb9Hlp2KW+ow7E5IasMlv1UeRylaqd+Azz3bSUEHd6GO1tFdF1wG2x6AJ79ltrmW19VkUSHs/YeFXEFcMWPYPGtw++Pkdj1NPzjQ2qfpYsAlv8a5n9w5OWkhIMr1bY0bhkQ9RLtGKqy3rv/MLooBcpL6u5LVConwEXfhnO/qiOlNKMipaSut457t93LCwdfoC3UlhBKUiEQeOweKrMquWD8BVw/+XoKvCm+h8P0ZUqTtxre4k9b/8Tmls1EUv1moMSOUl8pN0y5gRun3EiGM2PM1179/a1pXMP9O+5nXfM6eqO9o26fz+GjKruKz83/HIuLF6fsd2vrVj78zIeJmSqiZ1b+LP58xZ9xpllYYEPzBm559hbifd/9eYXz+OPlf8RhDG8aHjEjfOipD7GzfScAn573aT4151OA8mG6d9u9PLznYdrD7cNuo9fu5fMLPs9N024acX/GrTi3Pn8raxrXjLgdLpuL+668j6m5U0dc7nCkVGbmrx16jb2de6ntqaUt1EbYDCeEvsGIUbwyJudM5r4r78NjT7YYMaXJd1Z8h3/v/3di3n/M/w8+PvvjYz6fDnYf5ANPfYCuiKoGmOXK4r4r72NC5oQxtaN5+9Dpe5pjQv+PxbG8pDoebWpOHMf7eOrzRaPRnDDsHlj+S+i5DVp3Q3s1BFsgFlYRNd5cyJsCxbP7IobE6CKEMKBkLlz/R+Vl1LBJ/R8NKO+ojGLImwT5U/p8jkYQRIQAhxvmfQBmXAvNO6F520Bkk8MDGSWQP1m15xnmybQQKhrrAw8qT6mGzSoaybCpVMDxZ0JulRrL7Bv6Uvv6IrxSMXWZ6g+UEfiRMn4xfPixsQcA500afRkhoHwJ3Pw41K9XaZihdpXa582H3AqVkpfuXx9/sdrW3ia1X6YvH+OgNe9EpJRsbN7Id1Z+h5rumvTWQRKMB9nWto19nfs4p/SctEWpsBnmD5v/wH077iMcD4+4rCUtDvUe4lfrf8Wb9W9y+5LbKfOXpS0kSCnpinbx2w2/5dG9jxI2R+4vsR6S3lgvu9p3DRE4UvXRL/4cSTxG0vpp/tAk0g6BpoASoVtDrdy+8nZW1K0YtZ2IGaEyK73fxcF9Hc0yw/HEvid4bN9jaY9lxM+H2f8GBtdUXcMz1c8kUgKfqX6G9097/5iiu6SUvHbotaTIsYVFCxnnH5d2G5q3Hy1KaTQajUaj0RwN/dX1ssrUq+oYtmtz9IlFI6dEpN2eKwPGL1KvI23D6VOG6eVnD7+cryB1dNRgMorV62jx5sKEc46+neEQQqU6TrxAvY6U/nTA5h1quvzsPhFPP07RjExjoHGIIOWxe6jIrGBC5gSyXEr47Y50Ux+op663jo5wB2Zf1Oas/FlMyZ2SVl9RM8qv1v+Kv+/8eyISRiAo9BYyJWcKRb4iDGHQFmpjT8ceDvUewpIWEsmqxlV8/bWv88sLf0mBpyAt247OSCfffuPbvH7o9SGCht/hp8BbQI4rB5thIxQL0RpupSPckYjcmpE3g2k5007qyPjmYDM90R6+/9b3eb3udQDswk6eJ48CbwEeu4eoGaUl1EJbqI2IGaHQW8i03NG3yxAGN027iTOLz6Qz0klnpJOuSBddkS52d+weNsJtLPSnFA5GIqntqSUUDyXmjc8Yj9c+sj9seWZ5ytRHIQRzC+cyPXc6m1s3A8pIfV3TOs4rOy/t4xs1ozxX81xi2iZsXDXxKmwihYej5qRBi1IajUaj0Wg0Gs3bwfZH+8zuDZj9nqFVDjWaw5BS8ujeR5MEqTn5c/jqoq8yPXe68lMaFKkXs2J0RjrZ3bGb1w+9zsr6lVw76Vqcxujpav19/WPXPxKCVJYri1tm3cLVE68m152bEBQkku5oNy/WvMidG++kNdQKwObWzfx6/a+5/ezbcdiGT3HrH+sv1/1yiCBVkVnBe6a+h6XjllLoLcRpc2JgYEqTQCxAXW8d65rW8dqh17h64tVpp+KdKFpCLdy99W5erX0Vu7BzzrhzeN+09zEjdwZ+px+bsGFJi2A8yMGeg7xR9wYRM0K2K3vUtg1hcHH5xVxcfnFinoVFKBbi5qdvZk/nnqMe/61zbuXjsz+eNM+UJp978XOsbVqbGMe3Fn+LhUULR2xLCDHsuei2uVletZwtrVuQKH+xx/c9ztJxS9MSlaSU7Oncw462HYl54/zjWFS06KQWLTValNJoNBqNRqPRaI4vUkJ3nfLaAhX5VnWhjpLSjEpcxnmr4a3EtNfu5ZuLv8mMvBkpb7SdNieF3kIKPAWcU3oOPdGeEY3AB3Oo9xB/2PyHhH+S3+Hn+0u+z/njzx8S3SIQZLuyeffkd1PkLeKrr301YSz9TPUzLK9azpnFZw7br5SS1+te58n9TyYEKYHgovKL+MaZ36DQWzhkXRs2nDYnOe4cZubN5P3T3q8q1p3k36O9nXvZ17kPh83BZ+Z9hpum3TTEfN6GjSxbFrNds5mVNwtLWqP6M/WTaj/ZjbEVDxqpbYfNgYNkgTFuxYe077A5cNvTKw41XF8Xjr+Qu7fcTVNQpTyualhFbU8tFVkVabXxQs0LSSmgF5VflIgk1Jy86DrpGo1mTKiKdyO/NBqNRqN5RyNl8ivYBs//l/IFEzY489bhvbs0mkHEzBgdkY7EdJYri7KM0T2b+sWaTFdmWkKBlJJH9jySEAMAbphyQ0pB6vB+zi49m8srLk/Mi5gRHtnzCBbDFx+ImBH+uv2vRK1oYt7cwrncfvbtKQWpVP06bc4RDcdPFuJWnJgV471T38vNM27GbXePuH1CCGyG7aQX244HBd4CLhx/YWK6K9rF8zXPp3V/0Rvr5eXalxPTHrsn6bzUnLycEpFSUkq6w3Fe3NGEzRBcPK0Iv/uUGLrmFENKycH2ICv2tlKW4+WcqjzsNq3dDkYCf3mzht1NPSk/v2FBGQsm6AttjUaj0byD2fE41KwEhxdCHXDwTVX1EGDSxTDnvTpKSpMWNsOG2zYgKnVHu2kINJDpzDymokVPtIfna55PTGc4M7hu0nUjClL9GMLg8orLeWzvYwkfq7VNa+kMd5LnyUu5zu6O3Wxt3ZqYdtlcfHbuZ8l2ZZ+WYkyJr4SbZ9yMXafsjohAsLxqOY/uezRhsp+O4Xl/MYCD3QcT82bmzWRyzuTT8nw63ThlvhV/eG0f//vKPgTwtcun8anzJ+oTTHPMicQt/vOhzaw60I7HaeMvHzuTRRW5J3pYJxVSwis7m3lld0vKzxeU52hRSqPRaDTvbJq2wqrfJc8TAsrPgat+ocziNZo0cBgOpuVOY0e78skJxAL8bM3P+M5Z36E8sxzBsUlf29u5l7reusR0VXYVZRllaa0rhKAysxK/009XpAuA9nA7h3oOpRSlpJSsblydZMI9PXc68wrnnbb3d+eMS7/64TsZIQTTcqcxr2BeIm01HcNzieTZ6meJS5V6KhAsq1yWlpea5sRzSohSEtjfElAR0EB1a+BEDwlQP6jNPRGkhMJMF8Zp+iN6MmNakqbuME67QZ4vvXz5kQjHTA51qCoSoahJfWdolDXeeRgCPnn+RC6cVkhHMEp7IMrqA+3sbEwdOaXRaDQazTuO4jkqIirYl3aVUQKTL4GZ14E7W0dJadJGILim6hqeqX4mUelsdeNqPvbsx1hetZzlVcupyKzAJo483UtKyY72HcSsWGJeVVYVdsOeMDwfDa/Di8/uS4hSMStGQ6CBucwd2h8yKUoK4MziM3HZXEc0/lOB+YXz0/aIeqfjMBxcW3UtqxtXY0mLuIzzxP4nRjQ8bw218mbDm4npPE8e544797QVOU83TglRSgBLJuXz2u4WHDaD86eeHCpzdzjOR+9Zg8tucP8nzsLj1KUm326q2wJ88O5VLKrI5X/eN++of+p9LjuLK3N5cksDpdkeZo/TxniHI4RgSVU+S6ryE/nd//38bi1KaTQajUbTz7SrYeqV0GcYjWFXFff0DZJmjAghmFc4jw/P+DB3b707YULeEmrhT1v/xIO7H2RR0SKunHgli4oWkePOSaw3Fqq7qpOmVzeu5vMvfT7t9U1p0h5pT5rXHe1OuWzMilHfW5+YFgim5E5Jf7CnGDZho9RXqgWSNBFCcM64cyjzl3GwR6XjvdXw1rCG51JK3qx/k5bgQBbHktIlFPmK3q4ha46SU0OUEoL3LRrPmRW5OGyCCXm+k+JLvbe5l70tvZTnepPKmGreHqSUrK/poLErTDAaPyZt2g3B9981i48uraTA76Io8/R9YnMsOBm+hxqNRqPRnHQIoQzNDf3AUnP02A07n5jzCQq8Bfzf5v+jMdiY+Kwn2sNLtS/xyqFXKPGVcNH4i1hetZzJOZPTjp6SSNrCbUnzantqqe2pPapx9wtohxM1o/REBx5m2oSNAk/BaXtdaRM2PHbPiR7GKUW2K5vLKi7j7i13A9AV6eK5muf4xOxPDDlP4jLOs9XPJu7H7YadKyuv1JFppxCnjIOzw2YwtTiDiQV+bMaJP8GklKw50E40nl5Iq+bYI4E397cdUzlQCIHPZWf2uCyKs0aujKHRaDQajUaj0bwdOG1ObpxyI/dccQ8fmfkRCr2FSZ9b0qKut46/7vgrH3v2Y3x7xbfZ1bErrfQ7iUykBr4dmJaZVHVPCJFWhcBTFSFEWobxmgGEEFxZeSV+x4C5+TPVzxCIDbXxqe2uZWPLxsT0xKyJzC2Yq+/jTiFOiUipY01/ypHVp2b0a1xjOXFNS/Lm/rbRF3ybxzVSu/2eXEKQ0I3TbTvRRl87R9JGyrEwEMk+1nZ6I3E2HuxMe523GynlwP7iyLbz8Pbg6M+Pw9s50mOp0Wg0Go1Go3n7EEJQllHGlxZ+iZum3cQLB1/gqQNPsbtjN1FzQOTpjfXy5IEneaP+DW6ZdQvvn/7+Mfs1zcmfQ1V21VGNd2L2xNQfCIZEsfRfn55snKzjeidQmVXJ4pLFvHjwRQAOdB4YYngupeTl2peTIu8unXApPocuJnEqcVKKUlJKnt/exMH2YMrPl07OZ1px5qjttPZGeGJTPRK4enYJBRkuukIxXt3dwpv72mjoUmUmCzJczC/P5qJphRRnpo6OsaQkGDVp641Q0xZkW30XG2s7AegMRrl3ZQ0O29D1SrI8LJtdPKIJupSSpu4Ir+1pYV1NB03dYZBQmOlm4YRszp9SSFGma1TBYFNtJ2uq28nyOHjX/HHYDUHMlKytaeflnc3sbw0QjVtkeRxMKcrg7Il5zJ+Qjd0YUO5NS/LUlgaausPMLM3irIm5xC3JxtpOXtrZzN7mXsIxE7/LzpSiDC6aVsjM0kzstuHVfyklMVNS0xZgXU0HW+u7aegKEYlZuB02irNczCnL5pxJ+ZSOEJ1kWpJAJE5zT4Tq1gBratqp7VDnSE17kD+uOJAySHN6SSZLqvJSthuOmTyyoY5AZGh4sd1mcO3cUnJ86VdtkFJiSsnuxl5e3d3CjoZuOoNRnHaDijwf50zO58yKXLzO4cOpOwJRHt9Uj2lJrphVTEmWm55wnNf2tLBybxv1XSEsCfl+J/PHZ3PRtCJKs0eO6pJSEoiY7GjsZl11B7ubemgLRLGkJMNtZ0Kuj0WVuSyqyMHvsmtxSqPRaDQajeYkxRAGJf4SPjj9g9ww+Qa2t2/nqf1P8XLty7SEBnx1OiOd/Gr9rwjGg9w651Zsw6STCgReuzdp3kXlF/GxWR87LuO3CztO28D1tSWtlBEwJwMxK4aFzow5EdiEjWsnXcsrta9gSpO4jPP4vseTDM/DZpgXal5IrON3+Lmk/BJ9L3OKcXKKUsA/1tby4o7mlJ//6N2z0xKlGrvC/PjpnUTjFsWZbsblePjOo1vZWteViBLp5+F1hxif6+XbV03nkhlFQ0Skvc29/MffN1DfGSIYMTEHqeatvVF+8szOlGNYXJnL5TOLMFIIVlJK4qbkofWH+O3Le6nrCA1JRXtwbS3jcjx8/qLJXLdgHI4RxJ+V+9r4yTM7Kc5yc/H0IqSU/OCpHTy5uYHIkDTDBmaUZPLgp87G7hpo05KSe96oZv3BDi6fWcS0kgx+9swuHtlQRyhmJrXw9NZG7n59P+9fXM6XL52CxzFUaJFSsvpAO//7yj7W13TQk0L8ARAcpCjLzRcunsx7zhifMkXztd0t3PHENlp7IoRiZtIx3NPUyw+e3JGy7Q8sLmdJ1dBytADBqMn/vLCbpu7IkM/cDoMlVXlpi1JSSlp7o/zPC7t5bGM9vSm29c8rq1k4IYdvXjmdOWVZKX8wW3oj/PjpnYRiJlleB9OLM/n2o1vYWNs55Lz91/o6fvfqfr555TSWzS5JKX7GTYv7Vh3kH6sPsq8lQNRM/Yf1/17fz+yyLL57zUxmj0s9No1Go9FoNBrNyYEQAo/Dw8KihcwvnM8ts2/h8X2P849d/6A11Aoov52/bP8LS8ctZXb+7JTXdwJBkTfZFLop2JTo41jjtDnJdmUnPKtMadIYaERKedJdf3ZFunS01AlCCMGiokVUZVexu2M3AKsaViUZnu9s38mezj2JdeYXzmdC1oQTMVzNUXBSilICuHpOKWXZHjqCMTpDMfY191LXeWS5zhJ4fnsTm2o72d8aoDDDxfSSTLK9DjqDMbbWddEWiHKwPcg3/rWF0mwPM0szh/woZrjsTCxQea1x02JXYw9xS+KyG0wpysBIIaRMKvSPGPlz16v7uPOlvURNC6/TxtTiDMqyPVhSVZbb09TLoY4Q33lsK93hGB89p3JUT61AJE5DV4hfv7iH57Y14XXamFDkJ9vrJBIzaewO09obZcGEbLwjVAzc3dTLdx/fxmMb6/E4bcwvz6Ys20Pckuxp7mV/Sy+BqMmfVhwg2+PgMxdOShmp1NIbYcXeVkxL4nPZGZ/jYXyOF5/LRmcoxo6Gbpq6IzR2hfneE9spzHBx0bTClPstx+sk26tEolA0zp6mXiSQ6bZTme9LWdVmfI53yLx+PA4bH1lSQW1HiM5AlM5QjC11XfSEx2ac3i9Iff6BDby5T6V1ZnscTC/JpDDTRTBqsruph9r2IKsOtPPJv67jf947j7Mm5o74x/flnc38/tV97G7qpcDvYlpJBrk+J12hGNvqumnpjVDXGeJbj26lJNvD/PHZQ9oTQrCptpMdjT0YQkVYlef6KMlyYzME9V0hdtR3E4iabDjYyVcf3MR9tyymMPP0ze3XaDQajUajOZ0whEGpv5Rb59zKheMv5LbXb2Nf5z4AArEATx14itn5s4ddf1LOpKTpvZ17ics4DuE45mO1G3bKM8rZ0rolMW9r21aWVy0/5n0djoWVdoEqKSV1vXW6oNUJxOfwcWXllQlRqivaxUu1L/HRzI8C8ELNC0RMFVxgYHDlxCuxi5NS4tCMwEl5xIQQvGteKe+aVwoo75u7XtnLz5/bfcRtPraxDiEEN51ZzmcvnERxlhtDgCklNW1BvvmvLaw60E5bIMq9K6v5yQ1zkgSWSYV+7v/EWYnp9kCUq3/zOq29UcpyPNz38cV4HEMFHiEGvH8GI6XkxZ3N/O8rSpCaWZrJ7ctnMrcsC6fdQKJSy17e2cztj2+jtTfKr17cw7zx2SyckDOikBGOmfz3c7t5fU8r180fxy3nVlKZ78NhM7CkpCsUY3NtF8VZI4sO1a0BqtsCTCvJ5LvXzGBuWXZibD3hOPe8cYA7X9pL3JLct+ogNywcP6RNIQTnTyng6jklzCzN4oKpBZTleHDbbQihjm1jV5gfPrWDJ7c0EIqZ3LuymvOmFAxJhzxvSgHnTMpPTG9v6OY9v3uTqGlxRkUud31gQcr9YozgK+hx2vjU+SpfXgJxU/LRP6/hjb2tI+6bw4lbkp89uyshSF0wtYBvLJvOxAIfdkMgJXSGYvxzbS2/fnEPTd1hvvXIFv56y+IRU++e2tIAwA0Ly/jCxZMpyXZjEwJLQm17kO88tpXX97TSGYxxzxsHmPve+RwelGcI+NBZEwjHTK6cXcIZE3LI87uw21Q2f8xU6Zn/+dAmqtuC7Gnq5emtjdx89oST7mmVRqPRaDQajWZ4hBBMyZnCZ+d9lq+9+jVMqTIddrXvwpRmyht2IQSz8mfhtXsJxpU1xp6OPTT0NlCeWX7sx4hgbuFcnjzwZGLeqoZV9ER7yHSNng0zFhyGI8lkPBgLErfiaXlsSSRbW7ce0/GcTgypbncctDshBJdVXMa92+6lI9IBwPM1z/P+ae8nbsVZUbcisWyxr5izS87W9y+nICdtGQAhROJlM8SInkzpYEm4aGoh3756OqXZKkJECIHdMJiY7+PbV03H51Ki0uoD7UMiZQwhcNqNxMthE4kvohAChy3584HljJRfjEDE5Lcv7yUcs8jzOfn5jXNZVJGDqy8FzhACr9POlbNL+MLFUzCEEoL+9MaBpNTBVMRMyUs7m7lpcTk/evdsZpRk4nXacdgMXHYbhRluLp5emDIabDASyPU6+cWNc1hUkZs0tiyPg1vPr2JRRS4Azd1httR1pWzH77Lzixvn8olzK5lSlIHXaccwBo5tababb145naJM9cdhR0MPHYHokHZsxtBjMHB8wJFi/zvtBnYj9THop/88MxLn2oi7d+h+kpINBzt5YlM9ANOKM/jpDXOYUuRPHH/DEOT6nHzi3Il88ryJCGB/a4B73jgw4u+3JWHppHzuuGYmZTmexLbYDMGEPC/fumo6mW51cbG2uoOu0ND9JoRgXnk2d960gKvnlFCS7cFpNzD6tttpN1hUkcMXL1HnmQRWHWjXz4Q0Go1Go9FoTkGEEEzKnpQkvITN8IiV+CZkTmB63vTEdGekkyf2PZFW9b4jGd/i4sVkODMS86q7q3nh4AvHPFUuw5mB2zbw0Lw93E5bKL1iVc3BZjY2bzym4zldEAjsxoDAKaUkbIaPS1+l/lKWli1NTO/t2Mv+zv3s7tidSAEFOH/8+eS4c47LGDTHl5NWlDrWOG0GH11akdL3SAjB5KIMKvKUS397IEpncOjN/bFCSsmG2g6213cDcOmMIqYWZ6TO8RaCS2cUkedTf1RWH2intWf0sZVme/j0BVUJISlVu+moyMtmFTOtJLV45bYbnDtZRS71pxumQgiBfRhxrv/zoiwXU4vUH6ZAND7m9LkTzeMbleeWQEUlFfhTG9PbDMH7zyxPRJQ9tbWBtt7hj6fdEHz0nEp8KYzRhRBMzPdTVahSSrtCsWHb6hfcRjoGCyYok3OA5p4w5uEGVhqNRqPRaDSatxUp5ZiFGiklDYGGpIp8Oa6chDl0KpyGkxun3Ji0zAO7HmB90/ox9d8/3tHWKc8sZ0npksS0JS1+t+l37GzfeUyFqWxXNgXegsR0T7SHFXUrRu3DlCYP73k4yTheM4AhDPLcA569Esmu9l3HxX/LwODaqmtxGsrCJWyGeavhLd6sf5OYFQPAZXNxRcUVQ6O3NKcE7xhRqijTxYxhxBUAh80gt8/QOmZJwrHjW2XhzX1txC2JAFUZjuQf8cGvHK+Doj4RozMYS1ScG4mzJuZSkDG20q+HYwg4d0rBsF9tIQRFg3yHeo/Ah6n/ZQhBhlvlrFtSEj+FBJFQzGRtjQon9bnsnDVMpb9+Cvwu5pZlA9DUHWFHQ/ewy+b7XcwexhAdlGiV3ydYxk05xIx+JA4/zzwOG067kWhLezpqNBqNRqPRnFh2deziD5v/wO6O3UTMyKiCj5SSllALf9zyR+Jy4Np8fuH8pDS2wxFCcFH5RUlCUWekk2+u+CYvHnyRqBkdtt/+MfVGe9nYspHfbPhNwih9OGzCxkdnfpQsZ1ZiXkOgga+++lVeO/TaqP1Z0qIj3MGb9W/SEe4Yth+P3cOCogUD6yK5d9u97OpILaCoquExHt/7OH/d/lftJzUCgyPrAP69/980BZuOuTAlhGBOwZyk/lY3rmZ14+rE9NScqUzPm65T905RTkpPqeNBcZYbn2vkzR1IERz7E4mxIKWqFtfP45vqWXWgfdjlLQlN3Soc0rRkytS2w5lclHFkOvGgzXbYDMbnekf8cg82d7dG+QNpSWjrjVDdFuRQR5D2QJRA1CQcU6+t9anT/052ukNxmnuUwV6uz0mBf2QxUAiYXOTnmW3qeO5t7uW8KQUply3McJHhHuG8FcmeWSOdtlJKonGLhq4w1W0BGrrCdIVihPqOQWcolrJioEaj0Wg0Go3mxNAZ7uSuTXdxz7Z7mJIzhTOKzmBW/izGZ4wny5WFw1APdcNmmJZgC+ub1vPo3kfZ17Uv0UaRt4grKq9gtJsDt83N1xZ9jdqeWqq7qwElFN32+m0sKFzABeMvYHL2ZLJcWQgEITNER7iD2p5adrbvZFvrNmp7a7EL+6im5UIIpudN59a5t/LLdb9MRLwc7DnIV179CvML53Ne2XlMzplMtisbQxiE4iHaQm0c6DrAtrZtbG/bTmekk78s+8uIaVvLJy7n3/v+nfDLqg/U84WXvsCHZnyIs0vPJsedg0DQG+tlb8de/r3/37xy6BWiZpQCTwFdkS6i1vHLojlSTGkSM2PErThxK07EjBAxI4TNMF2RLkLxgSJhlrQSkUxuuxuXzYXL5sJhc2AXdhyGA7thT1vUEUKwpHQJmc5MuqPqAfv+rv189dWvcsvsW5ieOx23zY2FRcSMEIgF6Ah3YAiDBYWpfYBHwm1zs7xqOZtbNiORbG7ZnPBLA7ii8oqkNE3NqcU7RpTKcDuO2pfqWGFKSVufsCSBF3Y0j2n9WBpRRH5X+j8qSQxaxWEzRqzOly6mJVlb085f36xh9YF22oNR4ubp89QhEI0T7otQ8rvsiWij4RBCJKLyAFp7I8OWwPW77diO8ryVUhKMmjy5uYEH19Wyq7GH3kicUygYTaPRaDQajeYdi0QSiAXY0LyBDc0bMDBw2px47B4cNiVKRcwIoVhoiHjic/j44oIvUuYvGzW1SQhBRWYFPz73x3xrxbcSwlbUjPJWw1u81fAWNmHDZtgQCCxpEbfiQ6KJ7Pb0bjENYfDeqe8lEAtw95a7E1XUImYk7f5GEyL6TdxvmHJDUuRTfaCen675KR67B59DWbiE42EC8UDCRyvXnct3l3yXn6/9Ofu79qe1TW8nLx18id9v+j2heIiIGSFqRolZMWJWDFOaxK2Bh80xK8btK2/HZtgSIpTD5sBlc+G2uanKruIHS3+A256+sFORWcG1Vddy3477Evt1U8smvvTyl8hwZuCyuZRwZsWImBFiZoyzS8/mzovuHDGVNBVCCC4cfyH/t/n/aAo20RsbCPDIceVwwfgLdJTUKcw7RpQyxKgPB942pIS4pX7shIDpxZl4Xel9MQXKfHzU5Y7BxqrKgUfXUNy0+OOKA/z6pT0EIiaGgKJMN1OKMijP9ZLrc+Jz2XA7bDywpjbhs3UqYVkyIfAYRnrnmW1QhNlIqYrKjPzIxyalpCMY4+v/2syL25sxpcRpM6gq8DO5yE9plocsjwOvy0YsLvnNS3sIRNNPAdRoNBqNRqPRHD+cNidumzsR5QNgYRE2wyMaSwsEEzIn8IUFX+DC8gvHFAEzI28Gv73kt9y54U5eqHkhqR9Tmpjm8NeKBgZFvqK0o1acNicfn/1xKrMq+d+N/8uBrgNJotNo/dkM24hpiaBSBT8979OE42Ee2ftIIipLIgnGg0n7tp8yfxnfOutbnF1yNhMyJ5yUolR7uJ1dHbvSXr5/X0YZGvUlkWM2tTeEwafmforWcCvPVT+XiFwypUlnpDPlOkeTjZTvyeei8ov4+86/J81fXLKYUl/pEberOfG8Y0Spk0eSUgKZx6FEKLsh+O61M5k3Pjvt9W1jLQ93gpBS8sa+Nv7nhT2EYiYZbjtfvHgyy+eVkudzJarcCSGwLMnre1pPSVHK7bDhtAnCMQjHLOKWZKQEPiklgUFpcv5R0kqPBinhzpf28Py2JiQwtTiDby6bxsIJuXhdtsS3QghBY1eY37+2X4tSGo1Go9FoNCcJswtmc9cld/F8zfOsb1pPfaCeYCxIXMaTRASBwGbYyHBkUJlVySUTLuGKiivI9+SPOYJECEGpr5TvLfke10++nsf3Pc7aprW0BFuImlEsrESfhjBw290UegqZkTeD88rO48ySM5NMsEfDbti5bMJlLCpaxAsHX+C5mufY07GHnmhPUmRUf38eu4dCbyGzC2ZzafmllGeUj7o9PruP2868jSXjlvDgrgfZ1raNnmgPlrSQSAQCh+GgyFfEheMv5P3T3s84/zhA+XHt7dwLqFTIUSPOEBR7iwnEVBEop82J0zZ6UMFY8Tv8lGeUHxPfqxJfyRGdJxnODL675LucXXI2D+95mH2d+wjGg4lzs/+YuWwuct25TMuddsQRTQLB8onLeWTPIwmh1CZsXFl55ajCpObk5h0kSp082AxBabYHUIbSzd0RHLbT74skJTy4tjZhvv3J8yby0aWVKaOvJBCNH19z+eNFpsdBttdJdzhOZzBKbyQ+qn9ZbcdAjvf4XM9xCzdt7Y3w5JYGJEr8+sm7ZzN3fHbK/uKWNaIvmEaj0Wg0Go3m7cVhOJhfOJ/5hfOJmBE6I520hlrpjHTSG+0lZsUSQk2uO5ciXxF57jwchuOori+FEDhsDhYWLWRB0QJ6o700BBpoCjbRE+1BInHb3InqdnnuPLwOL4L0Knyn6i/Xk8uNU27kusnX0R5qpzHYSGuolVAsBAI8Ng/Z7mzyPfnke/Lx2D1p9yeEwGlzctH4iziv7Dxagi3U9dbRHm4nZsZw290U+4opyygj05mZaFdKyQenf5D3TH0PoKKDRks9cxgOfnr+T5NEw7GkxaXLZRWXccH4C45JW4YwjsiTSQiBx+7hXZPexbLKZTQGGqkP1NMV6cK0TFx2F9kudczy3Hn4HL4jrpAnhMBtd2MzbND3DL08o5yFRQt16t4pjhaljoajOPcXlOfwyIY6JPDW/jaWzS4+aTyvjhVR02Jfi8r3ddkNLppWOOw2hmIm9Z2hlJ+lw4mUUvwuO9OKMzjYHqQzGGN3Uw+FGa5hfxzDMYsth5Spu9dpY1px5nEbW2N3mI6AClGuzPcxfYQKlA2dYYJRbXSu0Wg0Go1GczLRf+3mtrspthdT7Ct+W/sWCDJdmWS6MpmaO/W49+cQKmKpyFd03Nov9ZdS6h895atfnOv37kq3D4/dczTDTAuH4UgY3Z9o+gWjiqwKKrIqjksfUkpePPhiIgIN4OIJF5PhzDgu/WnePk6/8Jy3CZshcNjUH4hwzBxTlI8QgnOn5CfMrp/d1siB1sCoObajlYA9GUl4LQkxbDSYlJJ11e3UtA/N5x4Jh81IpDIGInGsE+TcbQi4cnYJhlD+UA+vr8McZixSKtP33U09AMwszaIy33fcxmZJEiG9DtvwT5JMS/LklgZip5EBvUaj0Wg0Go1Gozk9CMQCPFfzXGLaa/dy2YTLdJTUaYAWpY4Qj9NGUaYKcWzujrD+YOeYBKPyHC83LCxDAM09Eb71yBYOtAawDhOe+oWoUMxkW303B1oDwzd6LDiGmoTDZjCuL00xHDdZX9MxZB9JKdnfGuDHz+wcc/pers9JpkcF++1q7GF/GsLe8UAIwUXTCpnb5wv2zNYG/rWhjrhpDTmWB9uD/OSZXUTiFg6b4CNLKnCNUq3vaMj3OxOeVTVtQeo6Q0PGZFqSp7c08NC6Q8dtHBqNRqPRaDQajUZzJEgpWd+8ngNdBxLz5hbMpSq76gSOSnOsOOnS9ywpaemJ0BuOE4yZhKJxeiMmu/oiSwC21nXx8s5mfC47HqcNr8OGz2WnMNP1tqXAOW0GF00tZMPBTqKmxXce3cqt509k9rgsDCEIRk3aA1H8LhvnTSkYouAahuBT51exta6LlfvaeGt/Ozf93youmVHEvPHZZHnsROOS1t4Ie5p72Xyok73NvdxxzUwmFviP34Ydw91nCLhsZhGv7GrGkvDLF3YjgcWVuTjtBh3BGCv3tnLfWzU0dUeoKvCxryV90S3H6+SsiXk8trGejmCML/1jI584dyKV+T4kKnqqtTfChFwv88pzhqwfMy2ausMEoyahqEkwGqcnHKelR5WjNS3Jij2tNHaF8blseBzqfMvyOMjxJufpZ7jtfOvK6XzqvvW09ka4/bFtrNrfzuUziyjKdBOOmWyo7eSB1QepbgsiBFy/oIxLZhQeV3W/KNPNoopcntveRFsgytcf3sznLpxERb4PKeFQZ5AnNzfw6IY6vE47bodBa+/Qihz9WFJ5oPVG4ol9FojE2ds8UJZ186FO8nxOfC47XqcNzwn4fmo0Go1Go9FoNJrTg4gZ4f4d9xO3lNWITdh49+R3nzTpi5qj46QTpcIxk1v/uo7dTT3ELRXFIaVkcDbU31Yd5O+rDyKEwG4IbIZgQp6Pf956Fhnut+fEFELwvjPLeWV3C+tqOqjrDPFfj21TKVIITCmxLMmy2cWcO6UgpdaT43Xw3++Zx/f+vY3ntjXR2B3mvrdquO+tGoQAZHLgkhCqWt+pghCCq+eU8vLOZp7b1kRTd4RvPrIFr9OGzTCIxEwicQu33eCzF1YxrSSTz9y3Pu32DQGfuWASGw52crA9yLb6br70j404bIYqa2qBKSVfvGRySlFqf0uAD969it5IHLPvXLOQ9AcSxUzJ9/+9HSFU+qHNENhtgqtml/Dj6+ckHVMhBAsn5PCL98zlO49u5WB7kIfXH+KRDYewGwaWlMT7TmKnzeDdC8fxzWXTcR5ng3u7IfjiJVPY0dhNbXuIVQfaWVezBq/ThgRCUZO4JSnJcvOT6+fw1JYGHlhTO2x7gUicW+5dw4HWwLDfz7+82X8OD3w/Jxb4eeCTZx3XSoMajUaj0Wg0Go3m9MKSFo/ve5xVjasS82bmzWTpuKU6de804aS7QxQIMt12CvyuMa2X5bEPcfJ32g3Kc71E4xaFGa4Ro4AEUJTpYkKuF5fDwJFGSlW+38mdN83n96/u54UdTbT2RoibEoTEbTfI8jqZmO8ftlshBEWZLv77PfN4aWczD649xLb6LrpDMeKWRBhqG3K8TqYVZ3DJ9CIumlY44j6YkOsFARlHcfNfkuVmQq4Xv9s+qgjmd9mYkOcFCdneoaVOfU4bP7l+DtOKq3lsYx1N3REiMQtDSLwuG/PLs/nokkounl5Ia2+UGaWZROJmwq9rJIQQTCny8383n8Fdr+xl5b42ukIxTEtiCIHXZZDrcyZSCA/HZghyfA68zpEraByO12lPeUyFEJw3OZ/7blnMvW9W8+IOJcTFTAvDEOR5HMwszeSmxeVcNK1oWI8nh82gPM9LOGpSlOlitPC1ggx1vBx2A+dh560QguklGdx98yLufHkvb+5rpTsUJxg1sRuCfL+LJVV53Hp+FVOK/PSE47y5v42SLDepfuOFEGS6HWP/frpT7zONRqPRaDQajUbzzkY95LYSxvqgfHF7o708deApfr3h14koKZfNxcfnfByf4/j58mreXoQ8yZyz+/2TxupZbaB8ngbf5JuWagtUxIjLbgyrpkopCcethEG1x2FLmGiPNl4JdAVjNHWHCURNbIYgw20n1+skw23HZoxeqrTf26c9GKW1J0ooptrJdNvJ9TnJcDswBCO2E41bRE3ly+SyG8Mai482jnDMwpQSgdqnI6VcxUyLSJ8XlNM2VBRRbQJIukNxGrpCBKJx7DaDPJ+TggwXTpuRKLkajJpIwOuwYaQZFdYfqdMeiNLcEyYcM3HYDDI9DnK9Ko0s1bEcfH6MhXTOJQn0hOM0doXpjcRx2gzyM5zk+13YRzkfrL5xScAmBG7HyH1F4lYiCmu481ZKiSklrT1qH8VMC49DpdTleJ2JcytuWoTjFjYBbodtSL9SSkJRk7G5f6moNk+K9jQajUaj0Wg0Gs07Gyklf9n+F9Y2riXTlYlN2OiOdrOvcx+1PbWYUt2zCQQ3TrmRry/+uk7dO4046UQpjUaj0Wg0Go1Go9FoNO8MpJT8cNUPeWDXA8MuIxCcW3YuP1j6A7KcWfph92nESZe+p9FoNBqNRqPRaDQajUYDkOnMZHnVcj4151NakDoN0aKURqPRaDQajUaj0Wg0mhPGsspl+J1+GgON9MZUZe9sVzbTcqdxVslZVGRWYIjhbU00py46fU+j0Wg0Go1Go9FoNBrNCaVfmpB9Nej7Tc+1EHV6o0UpjUaj0Wg0Go1Go9FoNBrN245O39NoNBqNRqN5u+l/JmhG1UtKMGxgd4Gwqc+O9smwlICEWBikCXY3GPah7UoJ0oJYSE073GoMR9J//3ZZMbVdlgUC1a/Neey2LVW/0gIzAmZctW84wO4ExLHvT6PRaDQazTFBi1IajUaj0WhOX6QFWx+Gjho17SuAeTeBbZhS0t31sPkfYKny0wgD5twIWeNTL2/FYePfobdJTedPgenLhxdBpIRAM+x/Ffa/Aq27INih2nG4IaMUys6AKZdD8Vw1ztEElVgYNvwFwt3gzoIFHwKbS23Lm3eqfuIhtQ1z3guzrgeHZ2D/HHwTVv0emrapeTkVarkZ1yghazSkhHgE2vZC7VtQtw7a90OwXc0XBji94CuEwmlQcR5MOBvc2emJRdKC7Y9B2z41XTwbJl+m1pUWdB6EnU9B9evQWQPRgPrMlam2peJcmHIFZJVpcUqj0Wg0mpMMnb6n0Wg0Go3m9EVKeOILsP5eNZ1RAre+Dv6C1Mtu/gc88ilg0OXRtb+FeR9ILWgE2+B350J3nZo+5wtwyXdTRyNFA7D+L7D690pIkdbw43Z4oepiuOA2KJo1spgS6lBj6KpVQs+tr6moq39+COrWJy9r2OHMT8Cl31ORRFsfgie/CuHOw5ZzwOJb4ZLbVYRTKqRUYtyOx2HLQ9C0VW3jaAibEu/O+wrMeNfwAmE/lgkP3AS7n1HTEy+EDz4EZgzW3A0r74TexpE6hMwSdWwWfrQvYkuLUxqNRqPRnAwYJ3oAGo1Go9FoNMeV0nkD70MdAwJSKg6tIUmQAji0dvjlu+tVRBAAAkrmDl2mX7x55JPw3Leho3pkQQogFoSdT8B9N6goodGW7yfaqyKWXv7BUEEKVETWmj/B3heheTs8+82hghSo9LvV/wf7Xh5IyRuyXRa8cDs89Z9Quyo9QQpUKmHLDnjsc6qP/qi0dOmoVmLgC7fDC3eMIkgBSHWcnv02vPazsfen0Wg0Go3muKHT9zQajUaj0Zy+CAFFM1V0jBkdSDMbLFT1Y0agfsPQ+Y2b1WeHp7JJCa27IR5W0w4PFExPjsKRUglhj34a9r00aFyGSi0rPwtyq1TbwTZo2AR1ayHcpZbrbYTH/0O9n3Ht6BE+Vhw2/g12PwsFU2HacrXt2/4FLTsHtnPN3SrVr7cZ8ier5Zw+2PnvgX1gRmDDfTDpkgEvqKR9a6j1tjyk+gXVRk4FFM5Q/7uzlcDVUaPSBFv3KFEK1H579ccwfjGMW5B+9FJvE7z6E1h3r+rXsEH+VBh/purTsENPoxLKGjaqiCpQ41h5J5SdCZMv1dFSGo1Go9GcBGhRSqPRaDQazelNdgV4cvp8n6SKEJJyqCjR2wztB9T7zHEQ6YFIt4rMCbQqT6LDadpGIrLKXwiZpcmfS1MJKPteHpjnyoBzvwLzPwTeXBJG3FIqkaV5B7z0fdjzvGo70g3P3Ab5k6Bw5uhiytZ/QfEseN/fB8Y8693w13dB1yE1vf9V9X/JXHjvfQOeWXPeC/cuh46+/VC/HkKd4Msb2o8QMPECGHeGErBmvAsmXwI5lX2eVYO2C5TQtv5eeOXHKhKsf966P8O4+Wr5dIgFVbQXEvxFcNG3Vd+ujIFxSal8tLY/Bs98QwmDoOa99b9q3PZh0hI1Go1Go9G8bej0PY1Go9FoNKc3nhwVQdNP8/bU6XDNOwYilCrPU75HoNLbWvcMXV5aA+bgoCKO+oURUMJI7RrY8FcSwpXdBVf8BJZ8AXz5KtqoX2QSQvkrFc+Gd/8fTF020FZPI7z8QxXtNRoCOOszA8beQkDeJJh53cAyVgyw4NyvKkGqf7msMhVF1E+gDXoahu/L6YMb/ggf/rfybCqapeYdvl1CgCcbzv6s8rQaTM0KJQCOCamisN71OyXuuTMH+unv0+FVItsF31Tj6adunTJE12g0Go1Gc8LRopRGo9FoNJrTG5tDpfD1075fRcwMRkqVNtefWjZuoYo2AuVBVL9hqLdSLDhQEQ5UtbzB4oc0Yc3/JXstTb8G5rwHjBEuwYRQqXWXfldFX/Wz90XleTVajRpnhkqJOzyiqnxJ8vj8RVB+dvJy/emO/ZgRVS1wpLFmlYHLn146nGGHBTcrQamf3mYItIy+7uGc8TGoumDkfoUBs6+H7AkD8yI9SoDUaDQajUZzwtGilEaj0Wg0mtOfknkD73uaVATQYKQ5YGhu9IlYg9epWzc0uqq3uS8lECWMlMxNFki66wfS5ED5Ri26RQkzo9Ef3TR9+cC8eBi2PMgQI/bD8eWD77DqgkJA1rjkSnc5lSp66XD8hSRS6aQciB47VmSOg+zxA9NmdOx9eHJg/geSRbaRli2ZM2iGVJFSugC1RqPRaDQnHC1KaTQajUajOb0RAopmKMNvUBXqOqqTlwl1Qssu9d6TpdL9imcNrNO8Q603mPb9A1FQDp8yFu9Hyj4/pvaBeTmVUDR7DAbbAqZcmWwyXr0CIr3DrwLgzQOHe+h8p08Jbv1klaUWyBzeQWOUyhz+WGJzJEdKSWvAjDxdimYlRz+NiIDMw/zAjrXQptFoNBqN5ojQopRGo9FoNJrTn+wJSqwBZSbesis5UqZ9/0AKWdZ48OT2rZOr5vU0DJiEg1q3edtAul9GEWSUJPdZvyk5uqpoBji96Y9ZCCV0uTMH5nXXQ3fdyOu5MoevljdYEOvftlTLDTYdT+W/lQ5SpnhZ6nW0le+KZ6cXcdaP3ZU83V8tUKPRaDQazQlFV9/TaDQajUZz+uPJVpFK/abdzYMMyqVUnlH9JuIF05SIYWRDzkRlMh4LKVPzwhl9goqExsEm51NVJNJAowMV7PrJrSTtCnODx+3NG1Q9LqzEscLpw6/j8KQn+jjGIJCNRr/AF+1V42s/AF21SuiLdEMsrMYeD6t92bjl6PpLO0qqj6PUwDQajUZz8iJTpGOLo334oXnb0KKURqPRaDSa0x/DodLxDq5U0y27VAU6mxOQcGj1wLL9/kNGXyW8gyvVMnVrYfaN6rN4FFp3Ja+TZHJuQfAw3ypv/tjHbXMeVtHPgmDrKOs4Rv68HyNFNNVYkVJFHTVshM3/hAOvKTEqFjryCKt08GQdfbSVRqPRaE4L4jLOXRvvoranljOLz+SGKTec6CFpxoAWpTQajUaj0bwzKJk78L7zoKrC5s2DaHAgcsdw9FXRE0pwGbcAFWYjVTqeGQO7U3lFdfWl0QljqMm5lEq4GozdNXYhRRgDvlb9xMKjrTSG9o9C2JFSRZG9/P9g2yPJVQaT+jAGXoZNpd1FgwOpj0eCkabwptFoNJrTntZgKw/tfoiOSAceu0eLUqcYWpTSaDQajUZz+iOESr2zu5Rxd6hdCSrePOXR1C8wefMgf9LAOkWzVDpcLKh8p0Jtyjuq8+CAWbbTD/lTDu8QjMOsO60jiRySQyOODm/3RCCl2m8PfjQ5ygzUPiyZq6oX5k1S1fxcfrB7+oQ5G/zr49Cw6cj711FSGo1Go0Gl7m1v305XVBewOFXRopRGo9FoNJp3BtnlfSJUvfI2at+vhKrmHQNRPvmTlMl5Yp3xkFHcJ0h1QNt+8BdD2x6V/geQWaLmDUYIZTg+mEi3EnPGIqhYphLEBhoe2u6JwIrDC3ckC1J2Dyy6Rb2yxg8YkR++vWYMbIcZj2s0Go1Gc4SsbliNdTxTxjXHlZPgUZtGo9FoNBrN24A7C3InqvdSQtte9b5hE9BnkjpuYXJVN6dfGZ+DEqH60/xaBvlJFUwbWlVPGJA5Lnled/3YxxwLDpicg0p/O1wAOxE0bYWdTw1MCwMuuA0u/a4ylLc5lBiVUoBLEf2l0Wg0Gs0REDbDbGjecKKHoTkKtCil0Wg0Go3mnYFhV+l4/bTuVb5GTX1CkzBg3BnJQoowlFDVT8MmJai07RuYVzKXlD5ORTOTp1t3qQijsdBdnyxKuTIhq2xsbRxrpITqFRAb5CGVNwkWflTt49EiwcwYRHuO7xg1mhGQUg55nU79vZ2c6G073v0fz/bTbfNY930ijtnx7LO+t56DPQePWXuatx+dvqfRaDQajeadQ8k8EsblndUQ7h4QmJz+oUKSEFA6X/kgSRNadiqD9M6+C2Bhg+I5Q/sRAsrOAId3IP2ueQf0NqUvKkkJtatVJbt+8icrj6YTTfv+5OmSOeBOM62wtxl6mo79mDSaEZBS0hnpZHfHbvZ27qU52Ew4HsZpc1LoLWRKzhTyPSNXyCz0FpLhzBhxmf6+JJLWUCu72nexr2sfrcFWYlYMr8NLmb+M6XnTqcyqxG1zp1W6PmpGqeutS6QoGcKgzF+GI91qm4eNrz5QTzg+UDQh35NPlisrrXUBOiOd7OrYxZ6OPTQHm4maUTx2DyW+EqbmTmVS9iR8Dl9a23Y43ZFuWkItADgMB2UZZRh91U2llFhYNAWa2Na6jf1d++mIdCAQZLuyGZ85nsnZkynLKBtx3/ZEe2gONgNgN+yU+cuw9VUklVLSHm5nR/sO9nTsoTXUiilNfA4fpb5SpuVOY2L2xFGPnZSSjkgHHWH1YKH//JFS0hhs5NXaV6npriHTmckZxWcwt2AuDsORaNO0THa27+SN+jdoD7eT78nnjKIzmJk/E7uwj2nfSimJWlFqumvY2b6T2u5auqPd2ISNXE8uE7MmMi13GkXeIgxhpN12MBakMdCIRGITNsoyyrD3RRtLKemKdrGzbSe7OnbREmxJfAdKfaVMzZ1KVXYVXrt3zNsikYTjYdrD7Txf8zzBQWnuPdEe9nftH6EFRbrfZ83xR4tSGo1Go9Fo3hkIAUXT+8zOw8rovLNGiSSgPKcySoaulz9Fpf6F2qHrkBKkAuqGCZdfCUWpLqjzp6jIrH7fpUAr7HoaFn08PV+peBi2Ppw8b8oVQ6vxnQgOj/hy+kmr6p+UsO/FAZN4jeY4I6USh/6+8+88feBpGgONxOXQiEWbsOEYparj9875Hssql43a397Ovdy/435ePfQqbeG2lF43bpubKTlTeO+093LphEtHFThC8RBfeeUr1PbUAkpI+eWFv2Rx8eIxCz+dkU4+88JnqO+tT7T1Pxf+D4tLFo+6bY2BRh7Y9QDPVj9LY6ARM0UVTYfhoCKzgusmX8e1k64lw5ExpjE+f/B5frzqx4ASDv521d/IdmUnxLQ/bfkTLxx8gY5wB5LkiBuBwG13U5VVxQ/P/SGVWZUp+3j90OvcvvJ2ALJd2fz1yr9S5C2iK9LF33f+ncf2PTbs9rlsLqblTuPmGTdzYfmFIwpE/9z1T/645Y8AfPmML/O+qe9jbdNabl95e+JYAji3Orl64tV87Yyv4Xf6iZpR/rjlj9y7/V4Cg6JS3TY311Rdw5fP+DI+h2/UfdkvRr1S+woP7HyA7W3bCcaDQ5YzMMh2Z3NO6TncPONmpuROSQiBI7GheQNffuXLWNLCY/dw77J7qcisoDfWy0O7H+LhPQ9zqOdQyv3oNJxUZVfxwRkf5PKKy3EazhHPk9ZQK+ua1rG7Yzd7OvZwsPsgzaFmArFA0nnwcu3LrKhbMerY71hyB1dNvGrU5TTHHy1KaTQajUajeeeQNR58+UpcCnVA/caBSKaSOeBwD13HXwA5FUqUCndB42ZlWg6QWQa+YSKX7G5YeDPUrVNRVkhY9TuYukz5TY10kyYlbH8s2UjcVwgz33VyVJ7z5iVPd9WpbRQjXFr2V+xb9Xvg9Elf0py8SCnZ1bGL77zxHXa27xxxWVOamObQG+fBjGakHLNi/GvPv7hr4120hdtGXDZshtncupltb2zjhZoX+PqZX6fEVzLsTXmmM5OzSs9iz/Y9fQOGZw48w5nFZyLSEYT7kFKyrmkd1d3Vie2ZnDGZmXkzR1zPkhavHXqNn6352aipUjErxp7OPfxszc946eBLfPusbzMxa2LawpRpmYRNFcXVHm6nJ9pDljOLzS2b+c7K73Cg68Dw24ckFA/REmoZMQrGlAN9tIZbqe+tx5Qm317xbdY1rRsidg0mYkbY1LKJb6z4BjfPuJlPz/00zmEeFsSteKKfne07qe+t546VdyQJUqAi4R7Z8whF3iJunXsrD+1+iD9s+QPxwx4AhM0wD+1+iHxvPrfOuXVE4ahfkP352p/zfM3zxPqLc6TAwqI93M4T+59gRd0KPjvvs7x7yrtHFWr796MlLaKmisTyO/zc8eYdrDi0AovhvzNRK8qO9h3cvvJ2trRu4csLv4zH7hl2+X4hcaRj0z+m0b7L/ctpTg60KKXRaDQajeadgysTcquUKBUNwME3B0y3yxaRMtrH5lIpevXrwYxCzRsQj6jPCqelFrJAiUczroWN90PNSjWvbS/8+0uw/FcqKuvwmzTZZwK+/xV4/r+U/5JqDM74qBLHTgaKZqmx9/uC1K2D5p0q/THVjWe/IPXEF6B199s7Vs07kv4UqW++/k32dO5JzM9z53Fe2XnMzJ+J3+GnO9rNlpYtrKhbQUdkwL9NICj2FVPkK6LUV0pZRhkz8mYM21/cinPP1nv4/abfE7Wiifk2YSPPk0eeOw+H4aA31ktzsJneWC+gboxfrn2Z5mAzPzv/Z5T5y1KKN0IILq+4nH/u+icRU/3+DE7rShdLWjxT/UySwHbJhEtGjLqRUvJs9bN8/63v0zPID84u7OR6csl35+OwDWxb/zISydqmtXzlla/w3xf8N5VZlWOO6oqYEboiXQRjQW57/TbqeuvU/kDgsXvw2D0YwiBshgnGggmhYXb+bHJcOWn1EbfibGzZyJub3mRt09pE+9mubAq8BXjsHkLxEE3BJroj3QlRJGpGuXfbvYzzj+P6ydePum17O/fy5+1/pranlkJvIYXeQpoCTYlURYnkod0PcUbRGdy95W7iVpwCTwFFviJaQ600BhoBJSA9vPthrp98PYXe1A9F+gWp216/jTWNa5I+y3BkUOAtwO/0E7fitIXaaAu1JSIIOyId/HTtTwmZIT40/UOJtMbRsLDY3LKZx/c9zmuHXkvsx0xnJgXeAnwOH2EzTHOwmc5wZ2I/xq04D+56kBJfCR+Z+ZFhhTa7Ycfv8A8RpWJWLPGd6F/ObRvm73IfAjGq4KZ5+9CilEaj0Wg0mncOhh2KZ8OBV5WwtPcFNd/uUn5Tw91UlC2E9X8GJOx+bkDISnhUDYMzAy77ATzwfpUuCLDnOfjrdbD4Vqg8D7z5alzxMHRUq5S9jX9LTnGrWApnfVoZr59ohIAJSyCjVAlNoKLIHv+c2tbSeSpKDFSaX6BF7ec3f6sEKWFT0Wq92ldKc/yQSP689c9JgtTs/Nl875zvqagdBEIIpJS8d+p72dW+i2+98S32dKjlDWHwiTmf4F1V70p45Azbl5Q8feBp/rD5DwlBSiBYWLSQm2fczJyCOfidfgwMYlaMpmATz9c8z/077k9EVG1r28YdK+/glxf8kkxXan+2qTlTmZ47nY0tGwFoDjSzqmEVV1ZembbY0xhsTBIpfA4fl0y4ZNj1pZRsbt3Mj1b/KCE2GcLgzOIz+dCMDzEzb2bStrWEWni+5nn+uv2vtIfbAdjXtY8frPoB/3Ph/4zZwyduxdnbuZeHdj9EXW8dLpuLs0vPZlnlMqblTCPTlYkhDIKxIId6D7GucR2v1b3GeWXnpZV+1s/dW+6mN6qEwsqsSj4848MsKV1CjjsHm7BhSpPWUCtPH3iaP2/7M91RFS0bs2L8aeufuHD8heR58kbqgh1tyqNqedVyPj//8+S4c2gKNvHNFd9kY/NGQKWo/WDVD2gNtXJN1TV8bv7nyHPn0R5u57/e+C/ebHgTgJZgC5tbNnPJhEtS9hUxI/xkzU+SjnWBp4APTP8AF5dfTKG3EIfhwMIiEAuwtXUr92y9JxElFjWj3LXxLqqyqlg6bmna59ffd/49kR44zj+Om2fczHll55HnycMu7JjSpCPcwQsHX+CPW/6YOP9NaXLf9vu4fMLljMsYl7Lti8ovYkHRgiHz/7XnX/xh8x8S0xeXX8yXFnxp1IzydEVLzfFHi1IajUaj0WjeWSSq5UkI9qXY+IuGj0ISQglZdrcSjoKtar5hU/NHuljvN0pf/it47HMDXlQtO+HfXwZXBnhzwXCoanbBdtXHYEoXwDW/Bnf2kW/zsSajWIlqL3y3LzURqN8Af7seciZCZgkglFjVeVDtZ2kpUW3BzUrke+w/0Gl8muNFS1CJI/34HX6+ceY3qMqqSrrBFkIgEEzLncZti27jcy9+jrAZxpQm/9rzL66qvGpUM/GGQAN3brwzEa0hEFw76Vq+tuhrQ/yUHDYHlVmVfGL2J1hcvDgp+mdN4xr+tuNv3Do3dVqWy+bi8orLE6KUhYp6urzicuwjpc72IaVUEWHhgYiwuQVzqcxM7bsEEIwH+eW6XybWEQjeM+U9fHHhF4cYVDtsDiY4JnDLrFuYnT+br732tcR6a5vW8sS+J3j/tPePzdQayV0b76Ih0ECeO4+vn/l1Liq/KMkQHCDXnUtZRhmLixfz0VkfHZNZN5AQ3OYXzudHS39Eqb80edtQhuu3zL6FcRnj+K83/itxvOt66ljduJorKq4Ysc+YFaPYV8yXFn6JPHceQgjK/GV8eu6n+dyLnyNmxZBI9nftpyq7iq+c8RVyXDkIISjyFvGRWR9hTeMa4jKOhcX2tu1cXH7xkD77RdIXal5IzCvPKOen5/2UGXkzhizvsrk4d9y5zC2Yyx0r7+CFg2q9YDzIbzf+lnmF89IWE/sjAKfmTOWn5/10SHScAwcl/hI+OP2DVGRW8LXXvpbwzGoJtfDaodd437T3pdyPPocvZURfljPZoN9r9w45fpqTm5PgcZtGo9FoNBrN24QQUDh9IJKnn4JpI1ePy54wtOqdKwvyJqXX5+TL4T1/HSSIAUjlTdVRDW17oLs+WZCyOWHmdfDev0JO5cnhJdWPMODMT8CijylBrZ9YCJq3qciovc+rtL5AixKk7G446zNw+f+D8rOVIKfRHCd2tu9M8nWaUzCH6XnTh71RFUIwr3AeU3KnJObt6djDge7h/YtACQAP7X4oYRoOMCNvBl9Z+JURDb6FEMwpmMN/LvpPXDaXagvJP3f/MyFSpVrngvEXJEV4rG9az6GeQyOOsZ+YFePZ6mcT6U8CwbLKZcNGgkkpeaX2lUQUD8C8wnl8fsHn8TqGr5gmhEhEUvVjSYuHdj+UEC3GQn2gHo/dw+1LbleG2LbhDbGFEHgdXtyH/8anQa47l++c9Z0RBQ1DGFxafilnlZyVmGdhsbpxdcrlD+eskrMSglT/eGfmzRyShnfphEsTglT/cpOyJyVF0Q133Luj3fxl+18SqYwum4uvLfpaSkGqHyFUmt2XFn6JAk9BYv6O9h28UfdGoupiOvgdfr591rdHTNcUQrCkdAkXlV+UNH910+pRPaM0px9alNJoNBqNRvPOIqsM8qrAkzvwmrBEpZUNhztTRTwNXqdwukpDSwchoPws+OAjcNn3lSdTqpsmYaiIqKqL4YZ74LrfjW6KLgzwZA+MyzVMJTxhSx6/YxhDWcOhorf6l7O7Ui9n96h0vWt+o9IYU26PUOJTxblw4z1wyR3g8KltKp6j2vfmqvTFkXBlDIzHmzv2CoQOb3rbrjktkFImGXkDTMudhm2k7ziqGtjk7MmJ6YgZobqresR1uqPdPFv9bGLaEAY3z7iZLFfWqJEaQgiWjlvKGUVnJOa1hlqVcDSMCFDiK0mqktcd7ebVQ6+OKhpIqSJwtrVuS8wr9BaypHTJsOOMW3Ee2/tYQtwwhMEHpn8Av8M/qrm6EIIrKq4gyzUQxXKg+wA72naMuN5wLKtcxnnjzjuu0S9XVl5JVXbVqH3YDTvnjz8/aV5Nd01axtnT86YPmedz+CjxDVR+NYTBvIJ5Q8bhc/jIdA6IUp2RziHm+1JKVjeuZn/X/sS8+YXzRzzO/QghKMsoY+m4pYl5lrR4oeaFMQlFF4y/gNn5s0ftzxAGF46/MOlcqu2uJWpGR1hLczqi0/c0Go1Go9G8s3Bnw4cehcGViNxZowg/NpWCFwsNzLO7Ugsxw7YhwJcHZ38OFn5EmZ637FLeSmZMCS/Z5VAwVQlnhiO96ChXBnzwYbD6boiGE1yyxsEtg/ywhotUGrcAbn2dRGqdJ3v47bG7YO77YPpy5RfVshN6m5WXlMuvxKf8KZAzQRnG92+P3Q3v/UufYbwYWs0vqR8Dlv00OYrMM0YvkDNvhXkfGJh2+se2vuaUo7u/QmYfg8WRkRh80w8kvIOGo7+iWj+F3kIWlyxOWzxxGA4ur7iclfUrEzf+r9a+yodmfCgRQTUYQxgsq1zG8zXPJ0SQ52ue571T3ztqdNBLB19K+P0ALB23dEST9IZAA9vaBkSsfE8+C4sWpr1tRd4iyjPK2RLZAgwYii8qXjQmccllc/GuSe8ak0fUWHEYDuWtlUYlQyEEFZkVCa8pUOdb3IqP6D9mCCNlhUVDGGS7shPTLpsrSaQaPMbB1enCZhgLCxsDYqtERbcNFqsuGH9B2qbe/V5oj+x9JDFve/t2ArFAWil8hjC4bMJlaR0rIQTjM8bjtDkTqZC9sV6iVhQ3Y49005y6aFFKo9FoNBrNOwshwF8w+nKHr+PJGbsYMlxbrgwVeVU6/xi0ZyhPrNEw7MoLajTsrj5PqHT7F0qAGrdAvdJdZyQhasiyWpEjpQAAEqJJREFUuemPJ9X67syR0zM1px2HiwOReGSYJZMJm8mebk5j+Kg8KSVbW7cmqpYBTM6enCQwjIYQgtkFs3Hb3YTiSvQ+0H2AtlAbpf7SlMsvLFrI+IzxVHdXA7CrfRe7O3Yzp2DOsP0E40FePPhiYtphOFhWuWxYEUZKye6O3UnV9iZkTBjTttkNO8W+Yra0bknMO9A1cjpkKoq8RWlFMB0NOe6cMVUH9Nq9GMJIiFIxKzYkaulwbMI2xP8IlBDkHBT96bF78KcQzgUiqRKeaZlDbPnC8TDb27Ynpu2GfcS0vSF9CEGJryRJcOsId9AR7khLlMpwZDAld0ra/XnsnqQIRtMysayR96Pm9EOLUhqNRqPRaDQajea0oiyjDIFIRB8d6DqARI4YCWNKMyldzyZsKYWhwQxOkwJVuW2sET35nnyyXdkJUSoQDdAQaBi270xnJheWX8g9W+8BlJD2fM3zw6ZM9YtngwWhquwqZuXPGlE82Ne5LyltK2yGeWLfE2PatpZgS9J0R7gDS1qjplIOptRfitfuHVO/Y6XAU4DfkX4E5ZEIZDZhwzVMOvTg89JhOJJEqrHQFelK2ucGBuua1o2ahjqYw72qomaUnljPMEsnk+3OHpsoe9j3UftJvTPRopRGo9FoNBqNRqM5bRBCMCt/Fn6nPxHps7ZpLfW99YzzjxtWuNnXuW9Iutqk7OGLGVjSojXUmjTvcMPqdHDb3GQ4M2gINABKHDu83cO5fMLlPLDzgYSQ9UrtK3x89sdTpilKJM9WP0tsUMryZRMuG1XoaQw2Jk1vad2SFPV0JESt6JiFh0xn5nGvpJblyhqTUHYkGMJIK43OEMYRpyp2RjoJmQNp5lEryq/W/+qI2urHwiJmxkZfEMhwZqSdKqjR9KONzjUajUaj0Wg0Gs1pxfiM8Zw77tzEdEuohZ+v/Tlt4bYhpuBSSpqCTfx87c+TPKQur7icPM/waaYSmeTRBCqta6wCik3YcNsGPHQkkkAsMOzyQggm5UxiZt7MxLzanlo2Nm9MaXjeEe5gRd2KxHSGI4OLyi8adZy90bFXyhuVIwiEsRv2tLyejoaRKvodS9LpQ/T9OxKC8eAJTX9zGs7j6v2lOT3RkVIajUaj0Wg0Go3mtMImbHxizidY37Q+EfHz4sEXOdB1gMsqLmN67nR8Dh+BWIBtbdt45sAzHOw5mFh/eu50PjzzwyOKAxI5VGQ5Ql3jcLFitGp6TsPJssplrGtah0RiSpNnqp/h3LJzk8bcX42tKdiUmDe/aD4TMieM2L5EDvFI8tg9+By+dDcpJekazr/dHG/R6+3qx5JWUiSagUGOO+eoBDeH4UjfKP1tEPY0px9alNJoNBqNRqPRaDSnFUIIqrKquGPJHdyx8o6EMLW/az+/2/Q7BAJDGENu4gWC2fmz+d4536PAUzDiTbaBMaTiXTgeRko5pptzCytRfayf0SrpCSFYOm4pue5c2sJtALzV8BbNwWaKfQMFDUxp8mz1swmBycDgysorR01VE4gh1f+unng1n5v3ubS3KxV2w37c0+TeySQivvpO6Wx3Nndfdje57qMpFkFaJucazZGiRSmNRqPRaDQajUZz2iGEYEnpEu669C6+/+b3Wd+8PvFZf3RRPw7DwTj/OK6eeDXvmfoesl3ZowpLhjDIcyen97WF2sY8zqgZTUqVM4SRlohQ5Cvi7NKz+ff+fyf6Xlm/kusmXZcYe0OggXVN6xLrFPuKWVyyOC3RLNeTPIZQPHTUUTea40umMxOn4SRuqYqQUTOK0+Ycciw1mpMJLUppNBqNRqPRaDSa0xJTmqxpXMO+rn0A5LhyuHbStTgMB1EritvmptBbyKTsSVRlV43ZVLsyqzJpuqa7ZtQqf4fTEe6gM9KZmPbYPUnRTsPRH/X0zIFniMt4wtB8edVyHMKBlJK3Gt6iK9KVWOe8svPSjpqpyKxImq7tqSVmxY64Mpzm+JPjyiHLlZXwOgvFQzQEGijPLD/BI9NohkeLUhqNRqPRaDQajea0Q0rJE/ue4Bdrf0HEjJDnzuOn5/+UM4rOOGZmzLPzZ2MTtkTU1Z7OPfTGesl0ZqY9xt0duwnGBgzTi73FaVXxE0Iwr3AeE7ImsK9TiW5bWrZQ21PLxKyJmNLk5YMvJ9ITnYaTKyqvSEswE0IwLXcaLpsrkVpY011Dc7CZsoyytLZN8/bjd/qZmD0xqZLjhuYNnFl8po5w05y0aGt8jUaj0Wg0Go1Gc9rRGenk7i13J0SV66dcz6KiRcdMkBJCMD1velJUU31vPVtbto5qVN6PJS1eOvgSFgOm4ouKF+G1e9Na3+/wc0n5JYnpnlgPK+tWIqWkMdDIltYtic+m5ExhRt6MtMWJyqzKpGiprkgXr9S+kva2ad5+bMKWVHUS4IWaF+iNHYdKiicJhpH8fR6clqs5NdCilEaj0Wg0Go1GozntONh9MBExAoxace5IyHZlc+mESxPTMSvG/TvvH2JcngopJbs6dvHqoVcT81w2F8sql41pDJdMuCRJxHrl0CvErThrm9Ympe5dVnEZbtvIBuqD8dq9XDnxykRklURy/877qeut08LUSYoQggvHX0ihZyDSbk/nHh7d++iQaoqnCxmOZBP2pmCTFqZOMbQopdFoNBqNRqPRaE47Do8IenTvo+zv2k8kHsG0TCxpDXlJKccsuNw45cakdLs36t7g/p33J8ymUyGlpDXUyk/X/JTuaHdi/rnjzmVW/qy0o5mEEEzMmsicgjmJeTvbdlIfqOe1Q68lUveynFlcOP7CMaVwCSG4puqaJN+s2p5a7lh5B/WB+rT2k5QS0zKp663jUM+htPvWHDnFvmJunHpjQky0pMVdm+7i6QNPj3hODkZKSW+0l+1t29Ne50QxPmM8DsORmN7ZvlN5u2nh9JRBe0ppNBqNRqPRaDSa047xGeMp9ZdS010DwJrGNdz89M2UZZSR5cwaksZnCIMMZwZlGWXMKZjD3IK5ZDmzRhRyhBCMzxjPp+Z8ih+t/hExK0Zcxvnfjf9Lc7CZD0z/ACW+EmzCllgnYkbY3LKZX2/4NZtaNiXmF3oL+cy8zyTdYKeDw3CwrHIZqxpWIZF0R7tZUbeCzS2bE8ucUXzGEXlB5bnz+NLCL3Hba7clzLNXNa7i1udv5YPTP8jScUvJ9+SrMYsBESoQD9AUaGJb2zbeqHuDDc0b+OScT3LT9JvGPAbN2DCEwfunvZ/VjatZ07gGgJ5oD3esvINVDat49+R3U5VdhcfuUee2VMJVxIzQEelgf+d+1jSuYWXDSuzCzr3L/n97dxcbRbnHcfz3zGx3u9vtlr63lJYXOQ0EUTkK4QhF7I2hOcbEGKJXGuXGRIPRmGiiMcRIwAsxxsQYjclRjN4Y9ULFd1RI0UMPKloqraKVt9K6bWnL7nY7+5yLpnPcg0BbyiLr93M3s/PMzLOzvZhfn+f//EsB588bGywoWaCaohr9OvSrpPFpplu+2qJHVj6i+uL602qoedZTOpNWgVPwp+7XXwlPAQAAAEDemRWapY1/36jHWx9Xf6pfknRy9KTaf2s/Z1vXuJobm6s7L79TLfNbVOCeOSgyxuimhTfpl6FftL19uzzrKeWl9OqBV/Xeofe0uGyxGmINCrkhDaQG1Nnfqa6BrqwpfsXBYj284mEtnLVwygWpjTFaNXuVKsOVOpE4ISurNzrfUF+iT9J4SNEyvyUrGJvKuZvmNOm+q+/TtrZtSowlJI0XPd/85WbFQjHVFtWqrLBMrnE16o1qcHTQX1Hw932cGLWFCy8WjOmxfzymBz97UAfiByRJSS+pN7ve1LuH3lV1pFpVkSqFA2FlbEbD6WENpAYUT8Y1kh7xp/otnLXwYnZjUkpCJbpxwY167pvn/N/YnmN7dMeOO3RV5VWqi9bJMY4SYwkNpgYVT8U1mBrUoysfzRphiIuHUAoAAABAXrHWajQzqtJQqZZULNGuI7um1N6znn4a/EmbWjfp2MgxbVi64ayjKoJuUPdcdY8K3UK93P6yH97Ek3HtPrpbu4/uPmPbmqIaPbTioSlPr/u9ykilrq27Vm91vSVJ6uzv9D+bHZ2t5TXLp31u17ha37hesWBM29q2qedUj6TxkGkwNZhVt+psJrPqH2aGMUYNxQ16au1T2vrVVn1x5Au/zlLKS6l7qFvdQ93nPs8l8MyMMbpt8W3ad2KfWo+1+vv7En36qPujP2zjGndSdd+QG4RSAAAAAPKGtVZdA116+j9P68tjXyrlpWRkFAvFVF5YrsJA4Wkv2xmbUWIsoZOjJ3UydVJjdryOTjqT1kvfvaRlVcu0ombFWYOdwkCh7r7ybl1ZeaVe2P+Cvuv7TulM+ozHx4Ixra1fq7uW3qX5sfnTDo2k8fBg3fx1euend0675to5azUrNGva55Yk13HVMr9FS8qX6JX2V/Rx98eKJ+PnHP0UdIKqi9ZpTf0aXVd/3XndA6YWEhljVBet09Y1W/X+z+/rtY7X1DXQddbfpCQ5clQSKtEVlVfo5r/drJAbOt/bPvt9zkDwVRIs0eamzXp237Pa8fMOjaRHznq8Y5wZW4UT589YKoABAAAAyAPWWnXEO3T/zvt1eHi8sHZ1pFoblm5Q05wmlYZK5TruaS/C1lqN2TGNpEd0sP+gnv/meX3d+7X/+br567SlacukXmSttUp6Se3v26/Wo6062H9Q8WRcXsZTOBDW7OhsLa1YqpW1KzU3NleOcc4rkJqQGEvo0+5PlfSS/j4jo+U1y6dVT+qPWGtlZXV85Ljaetr0be+36h7q9oO8oBNUcbBYtUW1Wli6UEvKl+iyWZcpWhAdv59J9PPQ4CHtO7HP364vrtc11dfMyHc0oftkt/b27PW3a4tqtbJ25aSvMZAc0M7DO/1pbsXBYl1ff33WaDprrQ7ED6gj3iFJCjgBNdc3KxqMZp3LWqu9PXv9mkiRQETNDc0KusGs4zI2o88Pf654Mi5JKiss05o5ayb9mzw1dkrtv7Vrb89edfZ3qjfRq+RYUo5xFAlEVB4u17zYPC0uX6zFZYtVFamSa9yzfifHR46r9WirH05WhCu0um71pAOf4dFhffLrJ34x9XAgrOaG5mkFYdZaedZT10CXdh3Zpfbf2tV7qldJLynXuIoWRFURqdC82DwtKluk5TXLVVRQNOXrYOYRSgEAAADIC8mxpO795F7tObZH0nhY8Mz1z+jq6qsnHThMjLS6fcftGhodkiQ1FDfo9X++ruJg8Tlan36ujDLyMuNTpxzj+LWdZjJkuRgmXiMzNuNPDTMyWaNQLvU+5qOJYNGznv8MJ56ZkcmLZ3amPubL316+YfoeAAAAgLzQOdCZNcqmqa5Jy6qXTekldGJFvbponT/KZWh0SImxxJRDKWOMXLly3akXGf+zm/hOXePKVf71L18ZY/zwMF/9FfqYT3hKAAAAAC551lp19Wevand5xeVypvHK4xhHAfO//98zsgIALgxCKQAAAAB5YTg9nLU93SLNA6kBf5U5aXwaYCQQOa97AwCcjlAKAAAAQF4oCZZkbf8Q/+GcK8T9P896ervrbfUl+vx9i0oXKVJAKAUAM41QCgAAAMAlzxijxrJGhQNhf98Hv3ygtp628cLH51jfyVqr4dFhbW/frhf3v+iHWQVOgVoWtMzI0vUAgGysvgcAAAAgL4x6o3pg5wPaeXinv6+ssEy3NN6i5vpm1UZrFXbDcoyjjDJKe2mNpEd0dOSo9vXs04fdH6oj3qGMzfjtb5h3g55Y9YRCgelNBQQAnBmhFAAAAIC8YK3VjwM/auOnG9U91J31WcgNqSRUomhBVAEnIC/jKeklNZwe1kh6RGOZsazjjYxW163Wpms3qSJcQbFzALgACKUAAAAA5A1rrQ72H9ST/35SbT1t8qw3pfZGRtVF1VrfuF63LrpV0YIogRQAXCCEUgAAAADyirVWibGEdh3ZpR0/79D3fd8rnowrnUkrYzOysjIyMsbIMY4K3UKVh8vVWNqo1XWrtapularCVYRRAHCBEUoBAAAAyEvWWmVsRkOjQ+pN9Kov0edP1XOMo3AgrFgoprJQmUoLSxUpiPhhFQDgwiOUAgAAAAAAQM45F/sGAAAAAAAA8NdDKAUAAAAAAICcI5QCAAAAAABAzhFKAQAAAAAAIOcIpQAAAAAAAJBzhFIAAAAAAADIOUIpAAAAAAAA5ByhFAAAAAAAAHKOUAoAAAAAAAA5RygFAAAAAACAnCOUAgAAAAAAQM4RSgEAAAAAACDnCKUAAAAAAACQc4RSAAAAAAAAyDlCKQAAAAAAAOQcoRQAAAAAAAByjlAKAAAAAAAAOUcoBQAAAAAAgJwjlAIAAAAAAEDO/RfzNJGM5QQA9gAAAABJRU5ErkJggg==\n"
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 0 Axes>"
+ ]
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "HGl_7NJYyAlR"
+ },
+ "source": [
+ "### Visualization with pyLDAvis"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "#### Visualization All Data"
+ ],
+ "metadata": {
+ "id": "4uaqHEqn4QZm"
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "xGtJVDCWyEtL",
+ "outputId": "aff476ce-dde7-4a23-d65c-b6f9ebbba02d"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization\n",
+ "all_3Topics_Visualization = pyLDAvis.gensim.prepare(topic_model=ldamodel_allSpeeches_3,\n",
+ " corpus=doc_term_matrix_unsc_speeches,\n",
+ " dictionary=dictionary_unsc_speeches)\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(all_3Topics_Visualization)\n",
+ "\n",
+ "# Saving\n",
+ "pyLDAvis.save_html(all_3Topics_Visualization, 'all_3Topics_Visualization.html')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "q2R7I1ZD1nbK",
+ "outputId": "7ca73865-105e-432c-ccc0-ff946f9d70e9"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization of 5 Topics of all data\n",
+ "all_5Topics_Visualization = pyLDAvis.gensim.prepare(topic_model = ldamodel_allSpeeches_5,\n",
+ " corpus= doc_term_matrix_unsc_speeches,\n",
+ " dictionary= dictionary_unsc_speeches)\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(all_5Topics_Visualization)\n",
+ "# Saving visualization to HTML\n",
+ "pyLDAvis.save_html(all_5Topics_Visualization, 'all_5_Topics_Visualization.html')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "KUvRsaF11q_j",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "4275c5e6-2d67-492f-f7bf-cda99d3f809f"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization of 10 Topics of all data\n",
+ "all_10Topics_Visualization = pyLDAvis.gensim.prepare(topic_model= ldamodel_allSpeeches_10,\n",
+ " corpus= doc_term_matrix_unsc_speeches,\n",
+ " dictionary= dictionary_unsc_speeches)\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(all_10Topics_Visualization)\n",
+ "# Saving visualization to HTML\n",
+ "pyLDAvis.save_html(all_10Topics_Visualization, 'all_10_Topics_Visualization.html')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "CX4qHdkh2GX_"
+ },
+ "source": [
+ "#### SV Data visualization"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "97rYMsqh1yLW",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "0f00c299-5acb-4cf8-b9e1-266f06c2ec4a"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization of 3 Topics of SV data\n",
+ "sv_3Topics_Visualization = pyLDAvis.gensim.prepare(topic_model= ldamodel_SV_3,\n",
+ " corpus= doc_term_matrix_unsc_SV,\n",
+ " dictionary=dictionary_unsc_SV)\n",
+ "\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(sv_3Topics_Visualization)\n",
+ "# Saving visualization to HTML\n",
+ "\n",
+ "pyLDAvis.save_html(sv_3Topics_Visualization, 'SV_3Topics_Visualization.html')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "WS0HSBn412m5",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "b8cf43d4-3508-4a5e-d2ee-978e0fa41893"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization of 3 Topics of SV data\n",
+ "sv_5Topics_Visualization = pyLDAvis.gensim.prepare(topic_model=ldamodel_SV_5,\n",
+ " corpus=doc_term_matrix_unsc_SV,\n",
+ " dictionary= dictionary_unsc_SV)\n",
+ "\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(sv_5Topics_Visualization)\n",
+ "# Saving visualization to HTML\n",
+ "pyLDAvis.save_html(sv_5Topics_Visualization, 'SV_5Topics_Visualization.html')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "IPng91ZK13G8",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "08e23b65-960b-453e-92c5-e271890552fe"
+ },
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py:283: DeprecationWarning: `should_run_async` will not call `transform_cell` automatically in the future. Please pass the result to `transformed_cell` argument and any exception that happen during thetransform in `preprocessing_exc_tuple` in IPython 7.17 and above.\n",
+ " and should_run_async(code)\n",
+ "/usr/local/lib/python3.10/dist-packages/pandas/core/dtypes/cast.py:1641: DeprecationWarning: np.find_common_type is deprecated. Please use `np.result_type` or `np.promote_types`.\n",
+ "See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information. (Deprecated NumPy 1.25)\n",
+ " return np.find_common_type(types, [])\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Visualization of 3 Topics of SV data\n",
+ "sv_10Topics_Visualization = pyLDAvis.gensim.prepare(topic_model=ldamodel_SV_10,\n",
+ " corpus=doc_term_matrix_unsc_SV,\n",
+ " dictionary= dictionary_unsc_SV)\n",
+ "\n",
+ "pyLDAvis.enable_notebook()\n",
+ "pyLDAvis.display(sv_10Topics_Visualization)\n",
+ "# Saving visualization to HTML\n",
+ "pyLDAvis.save_html(sv_10Topics_Visualization, 'SV_10Topics_Visualization.html')"
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "provenance": [],
+ "collapsed_sections": [
+ "j4gu7UQrFH77",
+ "fjDCuOc4mkqO",
+ "hQSE3j4AoXHL",
+ "8mjfBFt9ocPW",
+ "UJk056i8oCsi",
+ "Z3n1jOFmv28N",
+ "66LXkYxhv7kk",
+ "3HsAczFSpYI0",
+ "i-1FI5ZvzYVW",
+ "fcIe3XMdzbX9"
+ ]
+ },
+ "kernelspec": {
+ "display_name": "Python 3",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file