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Arshad221b/Email_analysis.ipynb

Created December 4, 2023 03:26
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Email_analysis.ipynb
{
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"metadata": {
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"provenance": []
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"display_name": "Python 3"
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"cells": [
{
"cell_type": "code",
"source": [
"! pip install nltk"
],
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"colab": {
"base_uri": "https://localhost:8080/"
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"id": "HETk4D_d_teH",
"outputId": "4834d68d-b796-4c64-bf46-877baad4e0af"
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"text": [
"Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (3.8.1)\n",
"Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk) (8.1.7)\n",
"Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk) (1.3.2)\n",
"Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.10/dist-packages (from nltk) (2023.6.3)\n",
"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from nltk) (4.66.1)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import nltk\n",
"nltk.download('stopwords')\n",
"nltk.download('punkt')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
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"outputId": "ebdd073e-0d5f-4ad9-ea08-39d71f0c6a5c"
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"execution_count": 312,
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{
"output_type": "stream",
"name": "stderr",
"text": [
"[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
"[nltk_data] Package stopwords is already up-to-date!\n",
"[nltk_data] Downloading package punkt to /root/nltk_data...\n",
"[nltk_data] Unzipping tokenizers/punkt.zip.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"True"
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},
"metadata": {},
"execution_count": 312
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},
{
"cell_type": "code",
"source": [
"import re\n",
"import pandas as pd\n",
"import numpy as np\n",
"import pickle\n",
"import json\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import string\n",
"from sklearn.svm import SVC\n",
"from sklearn.metrics import accuracy_score\n",
"from sklearn.metrics import confusion_matrix, classification_report\n",
"from sklearn.model_selection import train_test_split\n",
"from gensim.models import Word2Vec\n",
"from nltk.tokenize import word_tokenize\n",
"from nltk.corpus import stopwords\n",
"from collections import Counter"
],
"metadata": {
"id": "ijChk-Yhbrew"
},
"execution_count": 410,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Data Gathering"
],
"metadata": {
"id": "2tvO0LYUu0aW"
}
},
{
"cell_type": "markdown",
"source": [
"**Following are the observations regarding the data provided:**\n",
"* The dataset comprises 52 rows and 17 columns.\n",
"* Each cell may contain a list of dictionaries, serving as samples.\n",
"* Column names, as interpreted, correspond to different departments or mail chains.\n",
"* It's worth noting that one sample contains a string object that requires cleaning.\n",
"* Data cleaning must be done in order to convert the data into a clean dataframe.\n",
"\n",
"**Steps followed:**\n",
"* Utilised pandas transformations to process and refine the raw dataset.\n",
"* In clean dataframe, columns are features\n",
"* Created new column named `type1` which contains the mail-chain/dept-name\n",
"* The `type1` column serves to store information related to the mail chain or department name associated with each entry in the dataframe.\n",
"\n"
],
"metadata": {
"id": "vnzTvRhEqudS"
}
},
{
"cell_type": "code",
"source": [
"with open('/content/email_campaigns.pkl', 'rb') as f:\n",
" data = pickle.load(f)"
],
"metadata": {
"id": "mGCVy173cPCf"
},
"execution_count": 430,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df = pd.DataFrame(data)"
],
"metadata": {
"id": "4lMM_P10dsqu"
},
"execution_count": 431,
"outputs": []
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{
"cell_type": "code",
"source": [
"df.shape"
],
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"outputId": "537b8817-b587-4c12-b2a8-c21381f10a27"
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"execution_count": 432,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(52, 17)"
]
},
"metadata": {},
"execution_count": 432
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]
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"cell_type": "code",
"source": [
"df.head()"
],
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"height": 598
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"outputId": "2ef29616-b96e-4642-ca35-734db16aaab8"
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{
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"text/plain": [
" example1 marketingAnalytics0 \\\n",
"0 [{'subject': '🚀 Propel Your Marketing ROI with... NaN \n",
"1 [{'subject': '🚀 Boost Your Brand's Visibility ... NaN \n",
"2 [{'subject': '🚀Boost Your ROI with Precision M... NaN \n",
"3 [{'subject': '💡 Elevate Your Marketing with Ac... NaN \n",
"4 [{'subject': '🚀 Propel Your Marketing with Dat... NaN \n",
"\n",
" HRConsultingSeries marketingAnalyticsSeries MarketingAnalyticsSeries \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
" series_legal IT_Solutions_Series Marketing_Analytics_Series \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
" series_marketing_analytics series1 HR_Consulting_Series \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
" financial_advisory_series series_IT_Solutions Series1_HR_Consulting \\\n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
" Series_IT_Solutions email_series_marketing_analytics legal_services0 \n",
"0 NaN NaN NaN \n",
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"2 NaN NaN NaN \n",
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"4 NaN NaN NaN "
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" <div>\n",
"<style scoped>\n",
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"</style>\n",
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" <th>Series1_HR_Consulting</th>\n",
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"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
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" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2c4bbb96-d8ef-4a3a-bb5d-51f9752d95da')\"\n",
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" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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"\n",
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" const element = document.querySelector('#df-2c4bbb96-d8ef-4a3a-bb5d-51f9752d95da');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
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" element.appendChild(docLink);\n",
" }\n",
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" try {\n",
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" }\n",
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" }\n",
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" quickchartButtonEl.style.display =\n",
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" })();\n",
" </script>\n",
"</div>\n",
"\n",
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" </div>\n"
]
},
"metadata": {},
"execution_count": 358
}
]
},
{
"cell_type": "markdown",
"source": [
"### Creating 'type1'"
],
"metadata": {
"id": "_pxUrXVujbiM"
}
},
{
"cell_type": "code",
"source": [
"# type1s = []\n",
"# columns =\n",
"\n",
"cell_values = []\n",
"def sort_data(cell_value, col_name):\n",
"\n",
" if cell_value != np.nan :\n",
" try:\n",
" temp_list = []\n",
" for d in cell_value:\n",
" if type(d) == dict:\n",
" temp_list.append(d)\n",
" d['type1'] = col_name\n",
"\n",
" cell_values.extend(temp_list)\n",
" except:\n",
" pass\n",
" return None\n"
],
"metadata": {
"id": "GjV3z_T_lvOd"
},
"execution_count": 359,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_sorted = df.apply(lambda x: x.map(lambda cell_value: sort_data(cell_value, x.name)))"
],
"metadata": {
"id": "BCqgc4IVmXAl"
},
"execution_count": 360,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_sorted = pd.DataFrame(cell_values)"
],
"metadata": {
"id": "cT89BM8Fp-9R"
},
"execution_count": 361,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_sorted.shape"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "63JcK34xtnbh",
"outputId": "6cc92d7d-159d-49e8-daba-122665d3016a"
},
"execution_count": 362,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(154, 7)"
]
},
"metadata": {},
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"df_sorted.head(10)"
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" meeting link clicked responded type1 meeting_link_clicked \n",
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},
"metadata": {},
"execution_count": 363
}
]
},
{
"cell_type": "markdown",
"source": [
"## Data Analysis"
],
"metadata": {
"id": "stYVOs1hypvu"
}
},
{
"cell_type": "markdown",
"source": [
"* **Data Analysis with Bar Graphs**: Employed bar graphs to gain\n",
"insights into the distributions of categorical columns, revealing valuable patterns in the data. Data is skewed.\n",
"* **Missing Values Identification**: Identified and acknowledged the presence of `NaN` values in certain columns, laying the groundwork for subsequent data cleaning.\n",
"* **Column Name Ambiguity Resolution**: Detected similarity issues between two columns, `meeting link clicked` and `meeting_link_clicked` and merged them into a `merged_meeting_link` column. This merger eliminated NaN values across the entire dataset.\n",
"* **Handling Categorical Columns**: Employed dictionary methods to transform categorical columns into numerical representations, facilitating a more streamlined analysis.\n",
"* **Correlation Matrix Visualization**: Visualised the correlation matrix to explore potential relationships between categorical columns. Notably, observed a meaningful correlation between the `opened` column and the newly created `merged_meeting_link` column."
],
"metadata": {
"id": "GMOt1UChxn_y"
}
},
{
"cell_type": "markdown",
"source": [
"### Plotting"
],
"metadata": {
"id": "ZByolqrq5dA7"
}
},
{
"cell_type": "code",
"source": [
"\n",
"def plot_bar_graph(col):\n",
" category_counts = df_sorted[col].value_counts(dropna = False)\n",
" category_counts.plot(kind='bar', color='skyblue', edgecolor='black')\n",
"\n",
" plt.xlabel('Categories')\n",
" plt.ylabel('Count')\n",
" plt.title(col)\n",
"\n",
" plt.show()"
],
"metadata": {
"id": "9HwqBKGJytmB"
},
"execution_count": 364,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plot_bar_graph('opened')\n",
"plot_bar_graph('meeting link clicked')\n",
"plot_bar_graph('responded')\n",
"plot_bar_graph('type1')\n",
"plot_bar_graph('meeting_link_clicked')"
],
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "AA7UiWtnytbQ",
"outputId": "af8f5334-b03d-40b9-db0a-6636e85ddfd3"
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"execution_count": 365,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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wYerZs+d1fxILAADYzdGy88033+jBBx90r48ePVqS1LdvX82fP19jx47VuXPnlJCQoNOnT6tNmzZasWKFgoKC3I9ZuHChhg0bpg4dOsjPz0/dunXTzJkzb/lrAQAAvsln7rPjJO6zAwBAyVPi77MDAADgDZQdAABgNcoOAACwmqMTlHFjDh8+rKysLKdjWKFq1aqqWbOm0zEAALcAZaeEOHz4sBrFxOjC+fNOR7FCcLly2rVzJ4UHAEoByk4JkZWVpQvnz6v75FmqHl3f6Tgl2omMvfrgxSHKysqi7ABAKUDZKWGqR9fXbTF3OR0DAIASgwnKAADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABW8+myU1BQoKSkJEVHRys4OFh169bVn/70Jxlj3PsYYzR+/HhFRkYqODhYcXFx2rt3r4OpAQCAL/HpsvPqq69q1qxZ+stf/qKdO3fq1Vdf1bRp0/TGG2+495k2bZpmzpyp2bNna+PGjQoJCVF8fLxyc3MdTA4AAHxFGacDXMtXX32lJ554Qp06dZIk1a5dW3//+9+1adMmSb+c1UlJSdGLL76oJ554QpK0YMEChYeHa+nSperZs6dj2QEAgG/w6TM7rVq1Unp6uvbs2SNJ2r59u9avX69HHnlEkpSRkaHMzEzFxcW5HxMWFqYWLVpow4YNjmQGAAC+xafP7IwbN045OTlq1KiR/P39VVBQoClTpqhXr16SpMzMTElSeHi4x+PCw8Pd264kLy9PeXl57vWcnJybkB4AAPgCnz6z88EHH2jhwoVKS0vT1q1b9c477+j111/XO++8U6zjTp06VWFhYe4lKirKS4kBAICv8emy8/zzz2vcuHHq2bOnmjRpoj59+mjUqFGaOnWqJCkiIkKSdPz4cY/HHT9+3L3tShITE5Wdne1ejhw5cvNeBAAAcJRPl53z58/Lz88zor+/vwoLCyVJ0dHRioiIUHp6unt7Tk6ONm7cqJYtW171uIGBgQoNDfVYAACAnXx6zs5jjz2mKVOmqGbNmrrjjjv0r3/9S8nJyfrDH/4gSXK5XBo5cqQmT56s+vXrKzo6WklJSapRo4a6dOnibHgAAOATfLrsvPHGG0pKStIzzzyjEydOqEaNGho0aJDGjx/v3mfs2LE6d+6cEhISdPr0abVp00YrVqxQUFCQg8kBAICv8OmyU6FCBaWkpCglJeWq+7hcLk2aNEmTJk26dcEAAECJ4dNzdgAAAIqLsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAaj5fdo4eParevXurSpUqCg4OVpMmTfTNN9+4txtjNH78eEVGRio4OFhxcXHau3evg4kBAIAv8emy89NPP6l169YKCAjQZ599pu+//17Tp09XpUqV3PtMmzZNM2fO1OzZs7Vx40aFhIQoPj5eubm5DiYHAAC+oozTAa7l1VdfVVRUlObNm+cei46Odv/ZGKOUlBS9+OKLeuKJJyRJCxYsUHh4uJYuXaqePXve8swAAMC3+PSZnY8++kixsbF66qmnVL16dd1zzz16++233dszMjKUmZmpuLg491hYWJhatGihDRs2XPW4eXl5ysnJ8VgAAICdfLrsHDhwQLNmzVL9+vX1+eefa8iQIXr22Wf1zjvvSJIyMzMlSeHh4R6PCw8Pd2+7kqlTpyosLMy9REVF3bwXAQAAHOXTZaewsFD33nuvXn75Zd1zzz1KSEjQwIEDNXv27GIdNzExUdnZ2e7lyJEjXkoMAAB8jU+XncjISDVu3NhjLCYmRocPH5YkRURESJKOHz/usc/x48fd264kMDBQoaGhHgsAALCTT5ed1q1ba/fu3R5je/bsUa1atST9Mlk5IiJC6enp7u05OTnauHGjWrZseUuzAgAA3+TTn8YaNWqUWrVqpZdfflndu3fXpk2bNGfOHM2ZM0eS5HK5NHLkSE2ePFn169dXdHS0kpKSVKNGDXXp0sXZ8AAAwCf4dNlp1qyZlixZosTERE2aNEnR0dFKSUlRr1693PuMHTtW586dU0JCgk6fPq02bdpoxYoVCgoKcjA5AADwFT5ddiSpc+fO6ty581W3u1wuTZo0SZMmTbqFqQAAQEnh03N2AAAAiouyAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwWpHKTp06dfTjjz9eNn769GnVqVOn2KEAAAC8pUhl5+DBgyooKLhsPC8vT0ePHi12KAAAAG+5oa+L+Oijj9x//vzzzxUWFuZeLygoUHp6umrXru21cAAAAMV1Q2Xn0jeJu1wu9e3b12NbQECAateurenTp3stHAAAQHHdUNkpLCyUJEVHR2vz5s2qWrXqTQkFAADgLUX61vOMjAxv5wAAALgpilR2JCk9PV3p6ek6ceKE+4zPJXPnzi12MAAAAG8oUtl56aWXNGnSJMXGxioyMlIul8vbuQAAALyiSGVn9uzZmj9/vvr06ePtPAAAAF5VpPvsXLx4Ua1atfJ2FgAAAK8rUtl5+umnlZaW5u0sAAAAXleky1i5ubmaM2eOVq5cqTvvvFMBAQEe25OTk70SDgAAoLiKVHa+/fZb3X333ZKkHTt2eGxjsjIAAPAlRSo7q1ev9nYOAACAm6JIc3YAAABKiiKd2XnwwQeveblq1apVRQ4EAADgTUUqO5fm61ySn5+vbdu2aceOHZd9QSgAAICTilR2ZsyYccXxiRMn6uzZs8UKBAAA4E1enbPTu3dvvhcLAAD4FK+WnQ0bNigoKMibhwQAACiWIl3G6tq1q8e6MUY//PCDvvnmGyUlJXklGAAAgDcUqeyEhYV5rPv5+alhw4aaNGmSOnbs6JVgAAAA3lCksjNv3jxv5wAAALgpilR2LtmyZYt27twpSbrjjjt0zz33eCUUAACAtxSp7Jw4cUI9e/bUmjVrVLFiRUnS6dOn9eCDD+q9995TtWrVvJkRAACgyIr0aazhw4frzJkz+ve//61Tp07p1KlT2rFjh3JycvTss896OyMAAECRFenMzooVK7Ry5UrFxMS4xxo3bqzU1FQmKAMAAJ9SpDM7hYWFCggIuGw8ICBAhYWFxQ4FAADgLUUqO+3bt9eIESN07Ngx99jRo0c1atQodejQwWvhAAAAiqtIZecvf/mLcnJyVLt2bdWtW1d169ZVdHS0cnJy9MYbb3g7IwAAQJEVac5OVFSUtm7dqpUrV2rXrl2SpJiYGMXFxXk1HAAAQHHd0JmdVatWqXHjxsrJyZHL5dJDDz2k4cOHa/jw4WrWrJnuuOMOrVu37mZlBQAAuGE3VHZSUlI0cOBAhYaGXrYtLCxMgwYNUnJystfCAQAAFNcNlZ3t27fr4Ycfvur2jh07asuWLcUOBQAA4C03VHaOHz9+xY+cX1KmTBmdPHmy2KEAAAC85YbKzm233aYdO3Zcdfu3336ryMjIYocCAADwlhsqO48++qiSkpKUm5t72bYLFy5owoQJ6ty5s9fCAQAAFNcNffT8xRdf1OLFi9WgQQMNGzZMDRs2lCTt2rVLqampKigo0AsvvHBTggIAABTFDZWd8PBwffXVVxoyZIgSExNljJEkuVwuxcfHKzU1VeHh4TclKAAAQFHc8E0Fa9WqpU8//VQ//fST9u3bJ2OM6tevr0qVKt2MfAAAAMVSpDsoS1KlSpXUrFkzb2YBAADwuiJ9NxYAAEBJQdkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNWK/EWgTnjllVeUmJioESNGKCUlRZKUm5ur5557Tu+9957y8vIUHx+vN998U+Hh4c6GBUqBw4cPKysry+kYVqhatapq1qzpdAzASiWm7GzevFlvvfWW7rzzTo/xUaNGafny5frwww8VFhamYcOGqWvXrvryyy8dSgqUDocPH1ajmBhdOH/e6ShWCC5XTrt27qTwADdBiSg7Z8+eVa9evfT2229r8uTJ7vHs7Gz97W9/U1pamtq3by9JmjdvnmJiYvT111/rvvvucyoyYL2srCxdOH9e3SfPUvXo+k7HKdFOZOzVBy8OUVZWFmUHuAlKRNkZOnSoOnXqpLi4OI+ys2XLFuXn5ysuLs491qhRI9WsWVMbNmyg7AC3QPXo+rot5i6nYwDAVfl82Xnvvfe0detWbd68+bJtmZmZKlu2rCpWrOgxHh4erszMzKseMy8vT3l5ee71nJwcr+UFAAC+xac/jXXkyBGNGDFCCxcuVFBQkNeOO3XqVIWFhbmXqKgorx0bAAD4Fp8uO1u2bNGJEyd07733qkyZMipTpozWrl2rmTNnqkyZMgoPD9fFixd1+vRpj8cdP35cERERVz1uYmKisrOz3cuRI0du8isBAABO8enLWB06dNB3333nMda/f381atRIf/zjHxUVFaWAgAClp6erW7dukqTdu3fr8OHDatmy5VWPGxgYqMDAwJuaHQAA+AafLjsVKlTQ7373O4+xkJAQValSxT0+YMAAjR49WpUrV1ZoaKiGDx+uli1bMjkZAABI8vGycz1mzJghPz8/devWzeOmggAAAFIJLDtr1qzxWA8KClJqaqpSU1OdCQQAAHyaT09QBgAAKC7KDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACr+XTZmTp1qpo1a6YKFSqoevXq6tKli3bv3u2xT25uroYOHaoqVaqofPny6tatm44fP+5QYgAA4Gt8uuysXbtWQ4cO1ddff61//vOfys/PV8eOHXXu3Dn3PqNGjdLHH3+sDz/8UGvXrtWxY8fUtWtXB1MDAABfUsbpANeyYsUKj/X58+erevXq2rJli9q2bavs7Gz97W9/U1pamtq3by9JmjdvnmJiYvT111/rvvvucyI2AADwIT59ZufXsrOzJUmVK1eWJG3ZskX5+fmKi4tz79OoUSPVrFlTGzZsuOpx8vLylJOT47EAAAA7lZiyU1hYqJEjR6p169b63e9+J0nKzMxU2bJlVbFiRY99w8PDlZmZedVjTZ06VWFhYe4lKirqZkYHAAAOKjFlZ+jQodqxY4fee++9Yh8rMTFR2dnZ7uXIkSNeSAgAAHyRT8/ZuWTYsGH65JNP9MUXX+j22293j0dEROjixYs6ffq0x9md48ePKyIi4qrHCwwMVGBg4M2MDAAAfIRPn9kxxmjYsGFasmSJVq1apejoaI/tTZs2VUBAgNLT091ju3fv1uHDh9WyZctbHRcAAPggnz6zM3ToUKWlpWnZsmWqUKGCex5OWFiYgoODFRYWpgEDBmj06NGqXLmyQkNDNXz4cLVs2ZJPYgEAAEk+XnZmzZolSWrXrp3H+Lx589SvXz9J0owZM+Tn56du3bopLy9P8fHxevPNN29xUgAA4Kt8uuwYY35zn6CgIKWmpio1NfUWJAIAACWNT8/ZAQAAKC7KDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Xz6PjsAANyow4cPKysry+kYJV7VqlVVs2ZNp2N4BWUHAGCNw4cPq1FMjC6cP+90lBIvuFw57dq504rCQ9kBAFgjKytLF86fV/fJs1Q9ur7TcUqsExl79cGLQ5SVlUXZAQDAF1WPrq/bYu5yOgZ8BBOUAQCA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACrUXYAAIDVKDsAAMBqlB0AAGA1yg4AALAaZQcAAFiNsgMAAKxG2QEAAFaj7AAAAKtRdgAAgNUoOwAAwGqUHQAAYDXKDgAAsBplBwAAWI2yAwAArEbZAQAAVqPsAAAAq1F2AACA1Sg7AADAataUndTUVNWuXVtBQUFq0aKFNm3a5HQkAADgA6woO++//75Gjx6tCRMmaOvWrbrrrrsUHx+vEydOOB0NAAA4zIqyk5ycrIEDB6p///5q3LixZs+erXLlymnu3LlORwMAAA4r8WXn4sWL2rJli+Li4txjfn5+iouL04YNGxxMBgAAfEEZpwMUV1ZWlgoKChQeHu4xHh4erl27dl3xMXl5ecrLy3OvZ2dnS5JycnJuXtBiOnv2rCTp6M5vdfH8OYfTlGwnD+2X9Mt76ss/c1/H76T38DvpPfxeekdJ+Z28lM0Yc+0dTQl39OhRI8l89dVXHuPPP/+8ad68+RUfM2HCBCOJhYWFhYWFxYLlyJEj1+wKJf7MTtWqVeXv76/jx497jB8/flwRERFXfExiYqJGjx7tXi8sLNSpU6dUpUoVuVyum5rXZjk5OYqKitKRI0cUGhrqdBxAEr+X8D38TnqPMUZnzpxRjRo1rrlfiS87ZcuWVdOmTZWenq4uXbpI+qW8pKena9iwYVd8TGBgoAIDAz3GKlaseJOTlh6hoaH8Bwyfw+8lfA2/k94RFhb2m/uU+LIjSaNHj1bfvn0VGxur5s2bKyUlRefOnVP//v2djgYAABxmRdnp0aOHTp48qfHjxyszM1N33323VqxYcdmkZQAAUPpYUXYkadiwYVe9bIVbIzAwUBMmTLjsEiHgJH4v4Wv4nbz1XMb81ue1AAAASq4Sf1NBAACAa6HsAAAAq1F2AACA1Sg7AADAapQdANZZt26devfurZYtW+ro0aOSpHfffVfr1693OBkAJ1B2AFhl0aJFio+PV3BwsP71r3+5v/Q3OztbL7/8ssPpADiBsgOvuXjxonbv3q2ff/7Z6SgoxSZPnqzZs2fr7bffVkBAgHu8devW2rp1q4PJADiFsoNiO3/+vAYMGKBy5crpjjvu0OHDhyVJw4cP1yuvvOJwOpQ2u3fvVtu2bS8bDwsL0+nTp299IEC/fDl1nz59VKNGDZUpU0b+/v4eC24ua+6gDOckJiZq+/btWrNmjR5++GH3eFxcnCZOnKhx48Y5mA6lTUREhPbt26fatWt7jK9fv1516tRxJhRKvX79+unw4cNKSkpSZGSkXC6X05FKFcoOim3p0qV6//33dd9993n8B3zHHXdo//79DiZDaTRw4ECNGDFCc+fOlcvl0rFjx7RhwwaNGTNGSUlJTsdDKbV+/XqtW7dOd999t9NRSiXKDort5MmTql69+mXj586d418vuOXGjRunwsJCdejQQefPn1fbtm0VGBioMWPGaPjw4U7HQykVFRUlvp3JOczZQbHFxsZq+fLl7vVLBeevf/2rWrZs6VQslFIul0svvPCCTp06pR07dujrr7/WyZMn9ac//cnpaCjFUlJSNG7cOB08eNDpKKUSXwSKYlu/fr0eeeQR9e7dW/Pnz9egQYP0/fff66uvvtLatWvVtGlTpyMCgKMqVaqk8+fP6+eff1a5cuU8PikoSadOnXIoWenAZSwUW5s2bbRt2za98soratKkif7xj3/o3nvv1YYNG9SkSROn46GUefDBB695+XTVqlW3MA3wi5SUFKcjlGqc2QFglVGjRnms5+fna9u2bdqxY4f69u2rP//5zw4lA+AUzuyg2LZu3aqAgAD3WZxly5Zp3rx5aty4sSZOnKiyZcs6nBClyYwZM644PnHiRJ09e/YWpwEul5ubq4sXL3qMhYaGOpSmdGCCMopt0KBB2rNnjyTpwIED6tGjh8qVK6cPP/xQY8eOdTgd8IvevXtr7ty5TsdAKXXu3DkNGzZM1atXV0hIiCpVquSx4Oai7KDY9uzZ4753xIcffqgHHnhAaWlpmj9/vhYtWuRsOOD/27Bhg4KCgpyOgVJq7NixWrVqlWbNmqXAwED99a9/1UsvvaQaNWpowYIFTsezHpexUGzGGBUWFkqSVq5cqc6dO0v65b4SWVlZTkZDKdS1a1ePdWOMfvjhB33zzTfcVBCO+fjjj7VgwQK1a9dO/fv31/3336969eqpVq1aWrhwoXr16uV0RKtRdlBssbGxmjx5suLi4rR27VrNmjVLkpSRkaHw8HCH06G0CQsL81j38/NTw4YNNWnSJHXs2NGhVCjtTp065f66ktDQUPdHzdu0aaMhQ4Y4Ga1UoOyg2FJSUtSrVy8tXbpUL7zwgurVqydJ+p//+R+1atXK4XQoTQoKCtS/f381adKEeRDwKXXq1FFGRoZq1qypRo0a6YMPPlDz5s318ccfq2LFik7Hsx4fPcdNk5ubK39//8tungXcTEFBQdq5c6eio6OdjgK4zZgxQ/7+/nr22We1cuVKPfbYYzLGKD8/X8nJyRoxYoTTEa1G2QFgldjYWL366qvq0KGD01GAqzp06JC2bNmievXq6c4773Q6jvUoOyiSSpUqXfeXfHIbdNxKK1asUGJiov70pz+padOmCgkJ8djO/UzglPT0dKWnp+vEiRPuD3Vcwm0Rbi7m7KBIuPU5fM2kSZP03HPP6dFHH5UkPf744x6F3Bgjl8ulgoICpyKiFHvppZc0adIkxcbGKjIy8rr/sQjv4MwOACv4+/vrhx9+0M6dO6+53wMPPHCLEgH/KzIyUtOmTVOfPn2cjlIqcWYHXsVt0OGUS/9uo8zAF128eJFPpzqIOyij2LgNOnwFlwbgq55++mmlpaU5HaPU4swOim3s2LFavXq1Zs2apT59+ig1NVVHjx7VW2+9pVdeecXpeChFGjRo8JuFhwnzcEJubq7mzJmjlStX6s4777zslhzJyckOJSsdmLODYqtZs6b7NuihoaHaunWr6tWrp3fffVd///vf9emnnzodEaWAn5+fUlJSLruD8q/17dv3FiUC/teDDz541W0ul0urVq26hWlKH8oOiq18+fL6/vvvVbNmTd1+++1avHixmjdvroyMDDVp0kRnz551OiJKAT8/P2VmZqp69epORwHgY5izg2K7dBt0Se7boEviNui4pZivA+BqKDsosgMHDqiwsFD9+/fX9u3bJUnjxo1TamqqgoKCNGrUKD3//PMOp0RpwUlqAFfDZSwU2aX7mly6bNCjRw/NnDlTubm53AYdAOAzKDsosl/PkahQoYK2b9+uOnXqOJwMAID/xWUsAABgNcoOiszlcl02KZRJogAAX8NNBVFkxhj169dPgYGBkn65adbgwYMv+5bpxYsXOxEPAABJlB0Uw69vzta7d2+HkgAAcHVMUAYAAFZjzg4AALAaZQcAAFiNsgMAAKxG2QGA67RmzRq5XC6dPn3a6SgAbgBlB8BNkZmZqeHDh6tOnToKDAxUVFSUHnvsMaWnp1/X4+fPn+9zXyTbqlUr/fDDDwoLC3M6CoAbwEfPAXjdwYMH1bp1a1WsWFGvvfaamjRpovz8fH3++ecaOnSodu3a5XTEG5afn6+yZcsqIiLC6SgAbhBndgB43TPPPCOXy6VNmzapW7duatCgge644w6NHj1aX3/9tSQpOTlZTZo0UUhIiKKiovTMM8/o7Nmzkn65XNS/f39lZ2e779Q9ceJESVJeXp7GjBmj2267TSEhIWrRooXWrFnj8fxvv/22oqKiVK5cOT355JNKTk6+7CzRrFmzVLduXZUtW1YNGzbUu+++67Hd5XJp1qxZevzxxxUSEqIpU6Zc8TLW+vXrdf/99ys4OFhRUVF69tlnde7cOff2N998U/Xr11dQUJDCw8P1X//1X955kwFcPwMAXvTjjz8al8tlXn755WvuN2PGDLNq1SqTkZFh0tPTTcOGDc2QIUOMMcbk5eWZlJQUExoaan744Qfzww8/mDNnzhhjjHn66adNq1atzBdffGH27dtnXnvtNRMYGGj27NljjDFm/fr1xs/Pz7z22mtm9+7dJjU11VSuXNmEhYW5n3vx4sUmICDApKammt27d5vp06cbf39/s2rVKvc+kkz16tXN3Llzzf79+82hQ4fM6tWrjSTz008/GWOM2bdvnwkJCTEzZswwe/bsMV9++aW55557TL9+/YwxxmzevNn4+/ubtLQ0c/DgQbN161bz5z//2VtvNYDrRNkB4FUbN240kszixYtv6HEffvihqVKlint93rx5HgXFGGMOHTpk/P39zdGjRz3GO3ToYBITE40xxvTo0cN06tTJY3uvXr08jtWqVSszcOBAj32eeuop8+ijj7rXJZmRI0d67PPrsjNgwACTkJDgsc+6deuMn5+fuXDhglm0aJEJDQ01OTk5v/0GALhpuIwFwKvMdd6UfeXKlerQoYNuu+02VahQQX369NGPP/6o8+fPX/Ux3333nQoKCtSgQQOVL1/evaxdu1b79++XJO3evVvNmzf3eNyv13fu3KnWrVt7jLVu3Vo7d+70GIuNjb3ma9i+fbvmz5/vkSU+Pl6FhYXKyMjQQw89pFq1aqlOnTrq06ePFi5ceM3XB+DmYIIyAK+qX7++XC7XNSchHzx4UJ07d9aQIUM0ZcoUVa5cWevXr9eAAQN08eJFlStX7oqPO3v2rPz9/bVlyxb5+/t7bCtfvrxXX4eky77U9kp5Bg0apGefffaybTVr1lTZsmW1detWrVmzRv/4xz80fvx4TZw4UZs3b/a5T5oBNuPMDgCvqly5suLj45WamuoxUfeS06dPa8uWLSosLNT06dN13333qUGDBjp27JjHfmXLllVBQYHH2D333KOCggKdOHFC9erV81gufUqqYcOG2rx5s8fjfr0eExOjL7/80mPsyy+/VOPGjW/otd577736/vvvL8tSr149lS1bVpJUpkwZxcXFadq0afr222918OBBrVq16oaeB0DxUHYAeF1qaqoKCgrUvHlzLVq0SHv37tXOnTs1c+ZMtWzZUvXq1VN+fr7eeOMNHThwQO+++65mz57tcYzatWvr7NmzSk9PV1ZWls6fP68GDRqoV69e+v3vf6/FixcrIyNDmzZt0tSpU7V8+XJJ0vDhw/Xpp58qOTlZe/fu1VtvvaXPPvtMLpfLfeznn39e8+fP16xZs7R3714lJydr8eLFGjNmzA29zj/+8Y/66quvNGzYMG3btk179+7VsmXLNGzYMEnSJ598opkzZ2rbtm06dOiQFixYoMLCQjVs2LCY7zCAG+L0pCEAdjp27JgZOnSoqVWrlilbtqy57bbbzOOPP25Wr15tjDEmOTnZREZGmuDgYBMfH28WLFjgMfnXGGMGDx5sqlSpYiSZCRMmGGOMuXjxohk/frypXbu2CQgIMJGRkebJJ5803377rftxc+bMMbfddpsJDg42Xbp0MZMnTzYREREe+d58801Tp04dExAQYBo0aGAWLFjgsV2SWbJkicfYrycoG2PMpk2bzEMPPWTKly9vQkJCzJ133mmmTJlijPllsvIDDzxgKlWqZIKDg82dd95p3n///eK9sQBumMuY65xNCAAl1MCBA7Vr1y6tW7fO6SgAHMAEZQDWef311/XQQw8pJCREn332md555x29+eabTscC4BDO7ACwTvfu3bVmzRqdOXNGderU0fDhwzV48GCnYwFwCGUHAABYjU9jAQAAq1F2AACA1Sg7AADAapQdAABgNcoOAACwGmUHAABYjbIDAACsRtkBAABWo+wAAACr/T+gtb0+nxh2FgAAAABJRU5ErkJggg==\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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Nvw8iIiLSh66JzI0bNzBr1izkz58f27dvR/fu3dGrVy8sWrQIABAeHg4AcHNzM/o6Nzc35blXDR06FE+ePFG2sLAwbb8JIiIi0o2ut5YSExNRpkwZjBs3DgBQsmRJnD9/HrNnz0a7du3e65i2trawtbVVs5lERESUTunaI5M9e3b4+PgY7StUqBBCQ0MBAO7u7gCAiIgIo9dEREQozxEREdGnS9dEpmLFirhy5YrRvqtXryJ37twAkgb+uru7IyAgQHk+KioKx44dg6+vr0nbSkREROmPrreW+vbtiwoVKmDcuHFo3rw5jh8/jrlz52Lu3LkAAIPBgD59+mDMmDHInz8/vL29MXz4cOTIkQONGjXSs+lERESUDuiayJQtWxbr1q3D0KFDMXr0aHh7e2PatGlo1aqV8ppBgwYhJiYGXbt2RWRkJCpVqoRt27bBzs5Ox5YTERFReqBrIgMAX331Fb766qvXPm8wGDB69GiMHj3ahK0iIiIic6D7EgVERERE74uJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2dI1kfnpp59gMBiMtoIFCyrPP3/+HD169ECWLFmQMWNGNG3aFBERETq2mIiIiNIT3XtkChcujHv37inbwYMHlef69u2LjRs3YtWqVdi3bx/u3r2LJk2a6NhaIiIiSk+sdG+AlRXc3d1T7X/y5Anmz5+PpUuXonr16gCABQsWoFChQjh69CjKly9v6qYSERFROqN7j8y1a9eQI0cO5MmTB61atUJoaCgA4NSpU3j58iX8/PyU1xYsWBCenp44cuTIa48XFxeHqKgoo42IiIg+TromMp9//jkWLlyIbdu2YdasWQgJCcEXX3yBp0+fIjw8HDY2NnBxcTH6Gjc3N4SHh7/2mOPHj4ezs7OyeXh4aPxdEBERkV50vbVUt25d5f/FihXD559/jty5c2PlypWwt7d/r2MOHToU/fr1Ux5HRUUxmSEiIvpI6X5rKSUXFxd89tlnuH79Otzd3fHixQtERkYavSYiIiLNMTXJbG1t4eTkZLQRERHRxyldJTLR0dEIDg5G9uzZUbp0aVhbWyMgIEB5/sqVKwgNDYWvr6+OrSQiIqL0QtdbSwMGDED9+vWRO3du3L17FyNHjoSlpSW+/fZbODs7o1OnTujXrx8yZ84MJycn9OzZE76+vpyxRERERAB0TmRu376Nb7/9Fo8ePUK2bNlQqVIlHD16FNmyZQMATJ06FRYWFmjatCni4uJQu3Zt/P7773o2mYiIiNIRXROZ5cuXv/F5Ozs7+Pv7w9/f30QtIiIiInOSrsbIEBEREb0LJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGbrvRKZPHny4NGjR6n2R0ZGIk+ePB/cKCIiIqK38V6JzM2bN5GQkJBqf1xcHO7cufPBjSIiIiJ6G++0RMGGDRuU/2/fvh3Ozs7K44SEBAQEBMDLy0u1xhERERG9yTslMo0aNQIAGAwGtGvXzug5a2treHl5YfLkyao1joiIiOhN3imRSUxMBAB4e3vjxIkTyJo1qyaNIiIiInob77X6dUhIiNrtICIiInpn75XIAEBAQAACAgJw//59pacm2Z9//vnBDSMiIiL6L++VyIwaNQqjR49GmTJlkD17dhgMBrXbRURERPSf3iuRmT17NhYuXIg2bdqo3R4iIiKit/ZedWRevHiBChUqqN0WIiIionfyXolM586dsXTpUrXbQkRERPRO3uvW0vPnzzF37lzs2rULxYoVg7W1tdHzU6ZMUaVxRERERG/yXonM2bNnUaJECQDA+fPnjZ7jwF8iIiIylfdKZPbs2aN2O4iIiIje2XuNkSEiIiJKD96rR6ZatWpvvIW0e/fu924QERER0dt6r0QmeXxMspcvXyIoKAjnz59PtZgkERERkVbeK5GZOnVqmvt/+uknREdHf1CDiIiIiN6WqmNkWrduzXWWiIiIyGRUTWSOHDkCOzs7NQ9JRERE9FrvdWupSZMmRo9FBPfu3cPJkycxfPhwVRpGRERE9F/eK5FxdnY2emxhYYECBQpg9OjRqFWrlioNIyIiIvov75XILFiwQO12EBEREb2z90pkkp06dQqXLl0CABQuXBglS5ZUpVFEREREb+O9Epn79++jRYsW2Lt3L1xcXAAAkZGRqFatGpYvX45s2bKp2UYiIiKiNL3XrKWePXvi6dOnuHDhAh4/fozHjx/j/PnziIqKQq9evd6rIRMmTIDBYECfPn2Ufc+fP0ePHj2QJUsWZMyYEU2bNkVERMR7HZ+IiIg+Pu+VyGzbtg2///47ChUqpOzz8fGBv78/tm7d+s7HO3HiBObMmYNixYoZ7e/bty82btyIVatWYd++fbh7926qGVNERET06XqvRCYxMRHW1tap9ltbWyMxMfGdjhUdHY1WrVrhjz/+QKZMmZT9T548wfz58zFlyhRUr14dpUuXxoIFC3D48GEcPXr0tceLi4tDVFSU0UZEREQfp/dKZKpXr47evXvj7t27yr47d+6gb9++qFGjxjsdq0ePHqhXrx78/PyM9p86dQovX7402l+wYEF4enriyJEjrz3e+PHj4ezsrGweHh7v1B4iIiIyH++VyMycORNRUVHw8vJC3rx5kTdvXnh7eyMqKgq//fbbWx9n+fLlCAwMxPjx41M9Fx4eDhsbG2UwcTI3NzeEh4e/9phDhw7FkydPlC0sLOyt20NERETm5b1mLXl4eCAwMBC7du3C5cuXAQCFChVK1avyJmFhYejduzd27typ6rIGtra2sLW1Ve14RERElH69U4/M7t274ePjg6ioKBgMBtSsWRM9e/ZEz549UbZsWRQuXBgHDhx4q2OdOnUK9+/fR6lSpWBlZQUrKyvs27cPM2bMgJWVFdzc3PDixQtERkYafV1ERATc3d3fpdlERET0kXqnRGbatGno0qULnJycUj3n7OyM7777DlOmTHmrY9WoUQPnzp1DUFCQspUpUwatWrVS/m9tbY2AgADla65cuYLQ0FD4+vq+S7OJiIjoI/VOt5bOnDmDX3755bXP16pVC7/++utbHcvR0RFFihQx2ufg4IAsWbIo+zt16oR+/fohc+bMcHJyQs+ePeHr64vy5cu/S7OJiIjoI/VOiUxERESa066Vg1lZ4cGDBx/cqGRTp06FhYUFmjZtiri4ONSuXRu///67ascnIiIi8/ZOiUzOnDlx/vx55MuXL83nz549i+zZs793Y/bu3Wv02M7ODv7+/vD393/vYxIREdHH653GyHz55ZcYPnw4nj9/nuq5Z8+eYeTIkfjqq69UaxwRERHRm7xTj8ywYcOwdu1afPbZZ/jhhx9QoEABAMDly5fh7++PhIQE/Pjjj5o0lIiIiOhV75TIuLm54fDhw+jevTuGDh0KEQEAGAwG1K5dG/7+/nBzc9OkoURERESveueCeLlz58aWLVvw77//4vr16xAR5M+f32idJCIiIiJTeK/KvgCQKVMmlC1bVs22EBEREb2T91priYiIiCg9YCJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktXROZWbNmoVixYnBycoKTkxN8fX2xdetW5fnnz5+jR48eyJIlCzJmzIimTZsiIiJCxxYTERFReqJrIpMrVy5MmDABp06dwsmTJ1G9enU0bNgQFy5cAAD07dsXGzduxKpVq7Bv3z7cvXsXTZo00bPJRERElI5Y6Rm8fv36Ro/Hjh2LWbNm4ejRo8iVKxfmz5+PpUuXonr16gCABQsWoFChQjh69CjKly+vR5OJiIgoHUk3Y2QSEhKwfPlyxMTEwNfXF6dOncLLly/h5+envKZgwYLw9PTEkSNHXnucuLg4REVFGW1ERET0cdI9kTl37hwyZswIW1tbdOvWDevWrYOPjw/Cw8NhY2MDFxcXo9e7ubkhPDz8tccbP348nJ2dlc3Dw0Pj74CIiIj0onsiU6BAAQQFBeHYsWPo3r072rVrh4sXL7738YYOHYonT54oW1hYmIqtJSIiovRE1zEyAGBjY4N8+fIBAEqXLo0TJ05g+vTp+Oabb/DixQtERkYa9cpERETA3d39tceztbWFra2t1s0mIiKidED3HplXJSYmIi4uDqVLl4a1tTUCAgKU565cuYLQ0FD4+vrq2EIiIiJKL3TtkRk6dCjq1q0LT09PPH36FEuXLsXevXuxfft2ODs7o1OnTujXrx8yZ84MJycn9OzZE76+vpyxRERERAB0TmTu37+Ptm3b4t69e3B2dkaxYsWwfft21KxZEwAwdepUWFhYoGnTpoiLi0Pt2rXx+++/69lkIiIiSkd0TWTmz5//xuft7Ozg7+8Pf39/E7WIiIiIzEm6GyNDRERE9LaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLaYyBAREZHZYiJDREREZouJDBEREZktJjJERERktpjIEBERkdliIkNERERmi4kMERERmS0mMkRERGS2dE1kxo8fj7Jly8LR0RGurq5o1KgRrly5YvSa58+fo0ePHsiSJQsyZsyIpk2bIiIiQqcWExERUXqiayKzb98+9OjRA0ePHsXOnTvx8uVL1KpVCzExMcpr+vbti40bN2LVqlXYt28f7t69iyZNmujYaiIiIkovrPQMvm3bNqPHCxcuhKurK06dOoXKlSvjyZMnmD9/PpYuXYrq1asDABYsWIBChQrh6NGjKF++fKpjxsXFIS4uTnkcFRWl7TdBREREuklXY2SePHkCAMicOTMA4NSpU3j58iX8/PyU1xQsWBCenp44cuRImscYP348nJ2dlc3Dw0P7hhMREZEu0k0ik5iYiD59+qBixYooUqQIACA8PBw2NjZwcXExeq2bmxvCw8PTPM7QoUPx5MkTZQsLC9O66URERKQTXW8tpdSjRw+cP38eBw8e/KDj2NrawtbWVqVWERERUXqWLnpkfvjhB2zatAl79uxBrly5lP3u7u548eIFIiMjjV4fEREBd3d3E7eSiIiI0htdExkRwQ8//IB169Zh9+7d8Pb2Nnq+dOnSsLa2RkBAgLLvypUrCA0Nha+vr6mbS0REROmMrreWevTogaVLl+Kff/6Bo6OjMu7F2dkZ9vb2cHZ2RqdOndCvXz9kzpwZTk5O6NmzJ3x9fdOcsURERESfFl0TmVmzZgEAqlatarR/wYIFaN++PQBg6tSpsLCwQNOmTREXF4fatWvj999/N3FLiYiIKD3SNZERkf98jZ2dHfz9/eHv72+CFhEREZE5SReDfYmIiIjeBxMZIiIiMltMZIiIiMhsMZEhIiIis8VEhoiIiMwWExkiIiIyW0xkiIiIyGwxkSEiIiKzxUSGiIiIzBYTGSIiIjJbTGSIiIjIbDGRISIiIrPFRIaIiIjMFhMZIiIiMltMZIiIiMhsMZEhIiIis8VEhoiIiMwWExkiIiIyW0xkiIiIyGwxkSEiIiKzxUSGiIiIzBYTGSIiIjJbTGSIiIjIbDGRISIiIrPFRIaIiIjMFhMZIiIiMltMZIiIiMhsMZEhIiIis8VEhoiIiMwWExkiIiIyW0xkiIiIyGwxkSEiIiKzpWsis3//ftSvXx85cuSAwWDA+vXrjZ4XEYwYMQLZs2eHvb09/Pz8cO3aNX0aS0REROmOrolMTEwMihcvDn9//zSfnzhxImbMmIHZs2fj2LFjcHBwQO3atfH8+XMTt5SIiIjSIys9g9etWxd169ZN8zkRwbRp0zBs2DA0bNgQALB48WK4ublh/fr1aNGihSmbSkREROmQronMm4SEhCA8PBx+fn7KPmdnZ3z++ec4cuTIaxOZuLg4xMXFKY+joqI0b+u7Cg0NxcOHD9/ra7NmzQpPT0+VW0RERGSe0m0iEx4eDgBwc3Mz2u/m5qY8l5bx48dj1KhRmrbtQ4SGhqJgoUJ4Fhv7Xl9vnyEDLl+6xGSGiIgI6TiReV9Dhw5Fv379lMdRUVHw8PDQsUXGHj58iGexsWg+ZhZcvfO/09feD7mGlcO64+HDh0xkiIiIkI4TGXd3dwBAREQEsmfPruyPiIhAiRIlXvt1tra2sLW11bp5H8zVOz9yFiqudzOIiIjMWrqtI+Pt7Q13d3cEBAQo+6KionDs2DH4+vrq2DIiIiJKL3TtkYmOjsb169eVxyEhIQgKCkLmzJnh6emJPn36YMyYMcifPz+8vb0xfPhw5MiRA40aNdKv0URERJRu6JrInDx5EtWqVVMeJ49tadeuHRYuXIhBgwYhJiYGXbt2RWRkJCpVqoRt27bBzs5OryYTERFROqJrIlO1alWIyGufNxgMGD16NEaPHm3CVhEREZG5SLeDfUl971u/hrVriIgovWIi84n4kPo1rF1DRETpFROZT8T71q9h7RoiIkrPmMh8Yli/hoiIPibpto4MERER0X9hjwxpSo8BxhzUTET06WAiQ5rRY4AxBzUTEX1amMiQZvQYYMxBzUREnxYmMqQ5PQYYc1AzEdGngYkMkQred1wOwLE5REQfgokM0Qf6kHE5AMfmEBF9CCYyRB/ofcflABybQ0T0oZjIEKmE43KIiEyPiQyRmeK4HCIiJjJEZonjcoiIkjCRITJDHJdDRJSEiQyRGeO4HCL61HHRSCIiIjJb7JEhorem1wBjLj5KRK/DRIaI3opeA4y5+CgRvQkTGSJ6K3oNMObio0T0JkxkiOid6DXAmIuPElFamMgQEaUTeoxBYkztYpJpMJEhIkoH9BiDxJjaxSTTYSJDRJQO6DEGiTG1i0mmw0SGiCgd+VTGAn0qMUl7LIhHREREZos9MkRERBr5VIo56jmYmokMERGRBj6VYo56D6ZmIkNERKSBT6WYo96DqZnIEBERaehTGdis12BqDvYlIiIis2UWiYy/vz+8vLxgZ2eHzz//HMePH9e7SURERJQOpPtEZsWKFejXrx9GjhyJwMBAFC9eHLVr18b9+/f1bhoRERHpLN0nMlOmTEGXLl3QoUMH+Pj4YPbs2ciQIQP+/PNPvZtGREREOkvXg31fvHiBU6dOYejQoco+CwsL+Pn54ciRI2l+TVxcHOLi4pTHT548AQBERUWlem10dDQA4M6ls3gRG/NObXtwK1g5RlrHfh09Yn5IXMbULuaHxP1UYn5I3E8l5ofEZUztYn5I3E8l5n/FTX4sIm8+iKRjd+7cEQBy+PBho/0DBw6UcuXKpfk1I0eOFADcuHHjxo0bt49gCwsLe2OukK57ZN7H0KFD0a9fP+VxYmIiHj9+jCxZssBgMLz1caKiouDh4YGwsDA4OTlp0dR0E5cxP66YesVlTMY017iMmT5jigiePn2KHDlyvPF16TqRyZo1KywtLREREWG0PyIiAu7u7ml+ja2tLWxtbY32ubi4vHcbnJycTPpHrGdcxvy4YuoVlzEZ01zjMmb6i+ns7Pyfr0nXg31tbGxQunRpBAQEKPsSExMREBAAX19fHVtGRERE6UG67pEBgH79+qFdu3YoU6YMypUrh2nTpiEmJgYdOnTQu2lERESks3SfyHzzzTd48OABRowYgfDwcJQoUQLbtm2Dm5ubpnFtbW0xcuTIVLeptKZHXMb8uGLqFZcxGdNc4zKmecc0iPzXvCYiIiKi9Cldj5EhIiIiehMmMkRERGS2mMgQERGR2WIiQ0RERGaLiQwRERGZLSYyREREZLbSfR2Z9CAiIgJz5szBiBEjPuqYpI5nz55BRJAhQwYAwK1bt7Bu3Tr4+PigVq1aH03MV0VFRWH37t0oUKAAChUqZJKYprJt2zZkzJgRlSpVAgD4+/vjjz/+gI+PD/z9/ZEpUyadW2jeFi1ahKxZs6JevXoAgEGDBmHu3Lnw8fHBsmXLkDt3bp1bSP9lw4YNb/3aBg0aqBtcjVWqP3ZBQUFiYWHxUcVcuHChbNq0SXk8cOBAcXZ2Fl9fX7l586YmMbdu3SoHDhxQHs+cOVOKFy8u3377rTx+/FiTmCIioaGhRqunHjt2THr37i1z5szRJF7NmjVl1qxZIiLy77//ipubm+TKlUvs7Ozk999//2hiNmvWTH777TcREYmNjZX8+fOLtbW1WFlZyerVqzWJKSJSokQJKVmyZKqtVKlSUqFCBWnbtq3s3r1b1ZhFihSRzZs3i4jI2bNnxdbWVoYOHSrly5eX9u3bqxpLb7GxsRITE6M8vnnzpkydOlW2b9+uWczPPvtMAgICRETk8OHDkiFDBpkzZ47Ur19fGjdurEnMly9fSlBQkGzbtk22bdsmQUFB8uLFC01iJdPjvCtimvfUYDC81abF5xoTGRE5c+bMG7cVK1ao/sPXI2ZKepw49PowqFSpkixevFhERO7duydOTk7i6+srWbNmlVGjRqkeL0uWLHL+/HkREfnjjz+kWLFikpCQICtXrpSCBQuqHk+vmG5ubhIUFCQiIn///bfky5dPYmJi5Pfff5cSJUpoElNEZMiQIeLs7CyVKlWSfv36Sb9+/eSLL74QZ2dn6d27t9SsWVMsLCxk/fr1qsV0cHCQkJAQEREZOXKkNG3aVERETp06JW5ubqrFSenChQvSvXt3KVGihLi7u4u7u7uUKFFCunfvLhcuXNAkpog+SbG9vb3cunVLREQGDRokbdq0ERGR8+fPS9asWVWNlZCQID/++KO4uLik+pB1cXGRYcOGSUJCgqoxk+lx3hXR5z01JSYyIkqW+LrsUYssUo+YKZnyxJFMjw8DEREXFxe5fPmyiIhMnz5dKlSoICIi27dvF29vb9XjpfzZNmvWTH766ScRSeoZsre3Vz2eXjHt7OwkNDRURETatGkjgwcPFhGRW7duiYODgyYxRUQ6d+4so0ePTrX/559/ls6dO4uIyIgRI6R06dKqxcyUKZOSPFSsWFHpzQsJCdHk57tlyxaxsbGR8uXLy8iRI+X333+X33//XUaOHCkVKlQQW1tb2bZtm+pxRfRJirNlyyaBgYEiktTjlnzhcf36ddV/lwYOHCjZsmWT2bNnS0hIiMTGxkpsbKyEhITInDlzxNXVVQYNGqRqzGR6nHdF9HlPTYmJjCS9yfPnz5ebN2+muW3evFn1pEKPmCmZ8sSRzNQfBslSJlD169eXCRMmiEjSB66dnZ3q8YoWLSrTp0+X0NBQcXJyksOHD4uIyMmTJzVL2PSImT9/flmxYoVER0dLtmzZlCvNoKAgyZIliyYxRUScnJzk2rVrqfZfu3ZNnJycRETk0qVLkjFjRtVi1q9fX2rXri2jR48Wa2truX37togkJcP58+dXLU6yYsWKyfDhw1/7/MiRI6Vo0aKqxxXRJylu2bKllCpVSjp16iQZMmSQhw8fiojIP//8I4ULF1Y1lpub2xuTwG3btomrq6uqMZPpcd4V0ec9jY6Ols2bN8usWbNk+vTpRpvamMiISK1ateTnn39+7fNBQUFiMBjMPmZKpjxxJDP1h0GycuXKyeDBg2X//v1iZ2en3A45cuSI5MyZU/V4q1atEmtra7GwsJCaNWsq+8eNGyd16tRRPd6rMf38/EwS09/fX6ysrMTFxUWKFy+udMfPmDFDqlatqklMERFXV1dZtGhRqv2LFi1SPoAuXLig6hXurVu3pF69elKsWDGZN2+esr9Pnz7Ss2dP1eIks7OzU3oR03L58mVNknARfZLif//9V3r06CENGjSQrVu3KvtHjBghY8aMUTVWhgwZ5OzZs699/syZM5olFXqcd0VM/54GBgaKu7u7ODk5iaWlpWTLlk0MBoM4ODho0gvOREZE1q5dK0uWLHnt848fP5aFCxeafcyUTHniSGbqD4Nke/bsERcXF7GwsJAOHToo+4cOHarZfel79+5JYGCg0b32Y8eOyaVLlzSJp1fMEydOyNq1a+Xp06fKvk2bNsnBgwc1i/nzzz+Lvb299OrVS5YsWSJLliyRXr16SYYMGZTf3SlTphgldOamYMGCMnny5Nc+P3nyZClQoIAmsfVIik3pyy+/lFq1asmDBw9SPffgwQOpU6eO1KtXT5PYepx3RUz/nlapUkW6dOkiCQkJkjFjRgkODpbQ0FCpXLmyrFmzRvV4XP2aPgkJCQmIiooymiZ78+ZNZMiQAa6urqrGevLkCRISEpA5c2aj/Y8fP4aVlRWcnJxUjZfS9evXERwcjMqVK8Pe3h4iAoPBoFk8vfz999+YOXMmrly5AgAoUKAAevbsiZYtWwJImo5uMBhgZ2enSrwtW7bA0tIStWvXNtq/Y8cOJCQkoG7duqrESbZq1Sq0bNkSdevWhZ+fH9zc3AAklWUICAjAtm3bsHTpUjRt2lTVuMnCw8Nx7949FC9eHBYWSeXGjh8/DicnJxQsWFCTmJGRkTh+/Dju37+PxMREZb/BYECbNm1UixMWFoYvv/wSly9fRtGiRY1+tufOnYOPjw82bdoEDw8P1WKmB6Z8T11cXHDs2DEUKFAALi4uOHLkCAoVKoRjx46hXbt2uHz5sqrx2COThri4OLl8+bK8fPnS5LHj4+Pl9OnTmk5HTrZ//35p1aqV+Pr6Krd5Fi9ebDRFWm3Xr1+XH3/8UVq0aCEREREikjSwMXkgmlZevnwpO3fulNmzZ0tUVJSIiNy5c8eoJ0EtderUEX9//1T7Z82aJXXr1lU9nojIw4cPpXr16sog8eDgYBER6dChg/Tr10+TmPHx8TJv3jz59ttvpUaNGlKtWjWj7WNStGhRZcZdSlu3bpVixYppEvPQoUPyzTffiKenp9jY2IiNjY14enrKN998o9wa0NK1a9dk27ZtEhsbKyIiiYmJmsXasGGDODo6isFgEGdnZ3FxcVG2TJkyqR4vISFBtmzZIiNGjJCuXbtK165dZcSIEbJ161bNZiwl0+O8m8xU72nWrFnl6tWrIpI0li55TNKlS5ckQ4YMqsdjIpNCTEyMdOzYUSwtLcXS0lL5MPjhhx9k/PjxmsTs3bu3cpslPj5eKlasqNxL3LNnjyYxRURWr14t9vb20rlzZ7G1tVW+199++02zD9u9e/eKvb29+Pn5iY2NjRJz/PjxygwmLdy8eVMKFiwoGTJkMHpfe/XqJd99953q8TJlyiQXL15Mtf/SpUuSOXNm1eOJJM0aql27toSFhSlduSJJAxd9fHw0idmjRw9xcHCQ5s2bS+/evaVPnz5Gm9bi4uIkLCxMbt26ZbRpwc7OThkwnlJISIgmJ2Y96ZEU58+fX3r37m1U6+RjpMd5V8T072nNmjXl77//FpGkWYblypWTv/76S2rXri3lypVTPR4TmRR69eolpUuXlgMHDoiDg4PyZq9fv16zuhg5c+aUEydOiIjIunXrJEeOHHLlyhUZNmyYMk1YCyVKlFAGTKb84AsMDNRsQF/58uWV+/4pYx47dkyTQbfJGjZsKK1bt5a4uDijuHv27JF8+fKpHu91gwnPnj2r2QyBlDVdUn6PwcHBmg1czJIlS5q9FFq7evWqVKpUSSwsLIw2LUsWuLm5KbOyUtq5c6dky5ZNk5gi+hSn0yMpzpAhgxLHVPQo0KnHeVfE9O/piRMnlKKUERERUrt2bXF0dJRSpUop5yk1MZFJwdPTU44cOSIixr9k165dE0dHR01i2traKlVnu3TpIr179xYRkRs3bmgWUyRpOl7yFearH3y2traaxHRwcJAbN26kihkSEqJZTBGRzJkzKzNAXo2rRWJRtWpV+eGHH1Lt//7776VSpUqqxxNJ+r6Su3JTfo8nTpzQrBcoe/bscuXKFU2O/SYVKlSQypUry5YtW+T06dMSFBRktGmha9euUrRoUbl+/bqy79q1a1KsWDHp1KmTJjFFUhcyc3V11byQmR5JcePGjWXFihWaHPt1Xi3QaWNjo3mBTj3OuyL6vKemxLWWUnjw4EGaAz9jYmI0GzDp5uaGixcvInv27Ni2bRtmzZoFAIiNjYWlpaUmMQHA3d0d169fh5eXl9H+gwcPIk+ePJrEdHFxwb179+Dt7W20//Tp08iZM6cmMQEgMTERCQkJqfbfvn0bjo6OqscbM2YM/Pz8cObMGdSoUQMAEBAQgBMnTmDHjh2qxwOAL774AosXL8bPP/8MIGmAZGJiIiZOnIhq1appErN///6YPn06Zs6cadIBxUFBQTh16pRmg07TMnHiRNSpUwcFCxZErly5ACT9/nzxxRf49ddfNYsbGBiIqVOnAgBWr14Nd3d3nD59GmvWrMGIESPQvXt31WPGxMQoa3al9PjxY9ja2qoeDwDq1auHgQMH4uLFiyhatCisra2Nnld9bR4AISEh8PHxAQCsWbMG9evXx7hx4xAYGIgvv/xS9XiAPuddQJ/31JSYyKRQpkwZbN68GT179gQA5eQ8b948+Pr6ahKzQ4cOaN68ObJnzw6DwQA/Pz8AwLFjxzQ9UXfp0gW9e/fGn3/+CYPBgLt37+LIkSMYMGAAhg8frknMFi1aYPDgwVi1apXyQXvo0CEMGDAAbdu21SQmANSqVQvTpk3D3LlzASS9r9HR0Rg5cqQmJ6yKFSviyJEjmDRpElauXAl7e3sUK1YM8+fPR/78+VWPByR90NaoUQMnT57EixcvMGjQIFy4cAGPHz/GoUOHNIl58OBB7NmzB1u3bkXhwoVTffisXbtWk7g+Pj54+PChJsd+HWdnZxw+fBg7d+7EmTNnlPe0cuXKmsaNjY1Vku0dO3agSZMmsLCwQPny5XHr1i1NYuqRFHfp0gUAMHr06FTPGQyGNC9EPpSNjQ1iY2MBALt27VLOQZkzZ0ZUVJTq8QB9zruA6d/TkiVLpnlxkzyTMF++fGjfvr16sfXuEkpPDhw4IBkzZpRu3bqJnZ2dsm6Lg4ODnDx5UrO4q1atkilTphgtbLhw4UJV14p5VWJioowZM0YcHByUpRHs7Oxk2LBhmsWMi4uTzp07i5WVlRgMBqWuQevWrSU+Pl6zuGFhYeLj4yOFChUSKysrKV++vGTJkkUKFCigzJz6GERGRsqYMWOkWbNmUrduXfnxxx/l7t27msVr3779GzetBAQEiK+vr+zZs0cePnwoT548Mdo+JnoUpzt37py4urpKnTp1xMbGRr7++mspVKiQuLm5Gd1aM3d6FOjU47wrYvr31NTrobGOzCuCg4MxYcIEnDlzBtHR0ShVqhQGDx6MokWLah77+fPnqtW9eFsvXrzA9evXER0dDR8fH2TMmFHzmKGhoTh//jyio6NRsmRJzXopUoqPj8fy5ctx9uxZ5X1t1aoV7O3tVTl+VFSUUh/mv67mtKwj8ylIroHx6hWf/P+aOWpdvc+YMQNdu3aFnZ0dZsyY8cbX9urVS5WYr1q9ejVatmyJhIQE1KhRQ7k1OX78eOzfvx9bt27VJO6TJ08wc+ZMo/Ngjx49kD17dk3i6SE0NBTff/89wsLC0KtXL3Tq1AkA0LdvXyQkJPzne/4h9DjvmvI97dKlCzw9PVP1Mo0ZMwa3bt3CH3/8gZEjR2Lz5s04efLkB8djIqOzhIQEjBs3DrNnz0ZERASuXr2KPHnyYPjw4fDy8lL+uCh9s7S0xL179+Dq6goLC4s0u1XV/qA9e/YsihQpAgsLC5w9e/aNry1WrJgqMdPy4MEDo8J02bJl0ywWAOzbt++Nz1epUkWVON7e3jh58iSyZMmSalxXSgaDATdu3FAlZlr0KE6nh3379uHXX3/FpUuXACTdQhw4cCC++OILnVtG78rZ2RmnTp1Cvnz5jPZfv34dpUuXxpMnT3D58mWULVsWT58+/eB4n/wYmXe5F6rFlfTYsWOxaNEiTJw4UblPDABFihTBtGnTVE1kmjRpgoULF8LJyQlNmjR542vVGt/Qr18//Pzzz3BwcEC/fv3e+NopU6aoEhMANmzYgLp168La2hobNmx442vVGEi4e/dupZLvnj17Pvh4b6NEiRIIDw+Hq6srSpQoAYPBgLSuS7QaYxATE4OePXti8eLFSiVWS0tLtG3bFr/99luagwvVoFai8l9CQkLS/L8pPXnyBDY2NihZsqTR/nz58sHKSr3Tt95J8V9//YUOHTqgSZMmSu/WoUOHUKNGDSxcuFCp2Ky24OBgLFiwAMHBwZg+fTpcXV2xdetWeHp6onDhwqrE0OO8C+j7ntrZ2eHw4cOpEpnDhw8rdx0SExNVuwPxyScyLi4u/znjQu0r6ZQWL16MuXPnokaNGujWrZuyv3jx4qqXcXZ2dla+V2dnZ1WP/TqnT5/Gy5cvASTNwHjdz1rtWS+NGjVSPuQbNWr02tep9b6m/HD19vaGh4dHmrc+wsLCPjhWspCQEKX3Q48P2n79+mHfvn3YuHEjKlasCCBpAHCvXr3Qv39/ZQaeGvT+oB09ejQGDBiQKjl79uwZJk2ahBEjRqgeE0gaIF+/fn18//33RvtXrlyJDRs2YMuWLarE0TspHjt2LCZOnIi+ffsq+3r16oUpU6bg559/1iSR2bdvH+rWrYuKFSti//79GDt2LFxdXXHmzBnMnz8fq1evViWOHuddQN/3tGfPnujWrRtOnTqFsmXLAgBOnDiBefPm4X//+x8AYPv27ShRooQq8T75W0v/1U2dkhZXgvb29rh8+TJy584NR0dHnDlzBnny5MHFixdRrlw5REdHqx4z+QM1W7Zsqo0Rof+T8jZTSo8ePYKrq6vqJ42XL1/iu+++w/Dhw994C0RtWbNmxerVq1G1alWj/Xv27EHz5s3x4MED1WJZWFgoJ+XkW3em/KA19XuaLHPmzDh06BAKFSpktP/y5cuoWLEiHj16pEqcW7duwdPTEwaD4T9nQ+XOnVuVmCnZ2triwoULad6KKFKkCJ4/f656TF9fXzRr1gz9+vUzOvceP34cTZo0we3bt1WNZ+rzrt7vqSnXQ/vke2RM1U39Oj4+Pjhw4ECqX6TVq1en6k5Wi4ggX758uHDhgkkG2gJJH7b29vYICgpCkSJFTBIzOW6dOnUwe/Zsk32v8pqFGqOjozUZzG1tbY01a9ZoOn0zLbGxscqCeym5uroq01rVonfv0+ve0zNnzqRaHFRNcXFxiI+PT7X/5cuXePbsmWpxks8/L1++xKhRo0yeFHt4eCAgICBVIrNr1y7NFm88d+4cli5dmmq/q6urJtP7TX3e1fs9bdWqFVq1avXa59VM5j75ROZV//77L+bPn2804KxDhw6anaxGjBiBdu3a4c6dO0hMTMTatWtx5coVLF68GJs2bdIkpoWFBfLnz49Hjx6Z7MPd2toanp6eml25vinuf92KUEvyGCCDwYDhw4cb3YZISEjAsWPHVOtKfVWjRo2wfv16o655rfn6+mLkyJFYvHixkqA9e/YMo0aNUr3uUspE/9atW6hQoUKqMSLx8fE4fPiwqleXmTJlgsFggMFgwGeffWaUzCQkJCA6OtrolrDaypUrh7lz5+K3334z2j979myULl1a9Xh6JcX9+/dHr169EBQUhAoVKgBIGiOzcOFCTJ8+XZOYpi7Qqcd5F9DvPY2MjMTq1atx48YNDBgwAJkzZ0ZgYCDc3NxU//l+8reWUtq/fz/q168PZ2dnlClTBgBw6tQpREZGYuPGjZoVvzpw4ABGjx5tNC1uxIgRqFWrlibxAGDjxo2YOHEiZs2aZbIekvnz52Pt2rVYsmSJplexr+rbty9sbW0xYcIETeMkF3fat28ffH19YWNjozxnY2MDLy8vDBgwQJOT2JgxYzB58mTUqFEDpUuXhoODg9HzWkwPPn/+PGrXro24uDgUL14cQFIPhZ2dHbZv367aYMlXmfI2z6JFiyAi6NixI6ZNm2Y0xiH5PdWqWCaQ9GHu5+eHsmXLplklWosZPe3atUOJEiVMmhQDwLp16zB58mTlIrJQoUIYOHAgGjZsqEm8AQMG4NixY1i1ahU+++wzBAYGIiIiAm3btkXbtm0xcuRI1WPqcd4FTP+enj17Fn5+fnB2dsbNmzdx5coV5MmTB8OGDUNoaCgWL16sajwmMikULVoUvr6+mDVrlrI8QEJCAr7//nscPnwY586d07mF6smUKRNiY2MRHx8PGxubVN18jx8/Vj1myZIlcf36dbx8+RK5c+dO9WEbGBioekwAysya/Pnzp/khr+ZsKSCpWvP06dNNWi9Gr+nBsbGx+Pvvv5WB6YUKFVK1Pk9aLCwsEBERkWqa99WrV1GmTBlNqrLu27cPFStWVHWm0NsKCgrCpEmTEBQUpFQUHjp0qGZX9XokxXp48eIFevTogYULFyIhIQFWVlZISEhAy5YtsXDhQk2WiNHjvAuY/j318/NDqVKlMHHiRKPxR4cPH0bLli1x8+ZNVeMxkUkheQxHgQIFjPZfuXIFJUqUUPWetN4WLVr0xufbtWunesxRo0a98XktroAAvLEMtsFgwO7du1WNt2DBArRo0YIDqVWWPHX1n3/+QZ06dYzWiElISMDZs2dRoEABbNu2TfXYVapUQadOndCsWbOP/n3Vs2aOHsLCwnDu3DmTFOjU47wLmP49dXZ2RmBgIPLmzWuUyNy6dQsFChRQffA2x8ikUKpUKVy6dClVInPp0iWl61wNmTNnxtWrV5E1a1blHvzraJWha/UH8yZaJSr/xVR1XZINGTIEvXv3RrNmzdCpUyflnr8pvHjxAiEhIcibN68mvQemrs+TUvJtHRGBo6OjUUJhY2OD8uXLG9ViUlPJkiUxYMAA9OzZE82bN0enTp1Qvnx5TWLpXSXaVIOp08N5EEgaaKzVgOJX6XHeBUw/QN7W1jbN392rV69qUjCTPTIprFixAoMGDULPnj2Vk9TRo0fh7++PCRMmGE2B/JBaFYsWLUKLFi1ga2urW4YOmKYY1KuSB4AFBwdj4MCBmg4Ae9X169cRHByMypUrw97e/rUzUT5UfHw8Nm7ciIULF2Lr1q3IkycPOnTogHbt2sHd3V31eEDSLZ6ePXsqv0/JFaJ79uyJnDlzYsiQIarEeXUa9OtoNQ0aSOrZGzBgQKruca3Fx8djw4YNWLRoEbZu3Yp8+fKhY8eOaNOmTZqzt96XHlWi06J1UpzyPLhw4cI3/i1qcR5s2rQpypUrh8GDBxvtnzhxIk6cOIFVq1apHhPQ57ybTOv3NFnnzp3x6NEjrFy5EpkzZ8bZs2dhaWmJRo0aoXLlypg2bZq6AVVZsekjkbyI1+s2CwsL5V81vHz5UhYtWiTh4eGqHO9d7N27V+zt7cXPz09sbGwkODhYRETGjx8vTZs21STmmTNnJFu2bJIvXz6xsrJSYv7444/Spk0bTWKKiDx8+FCqV6+uvHfJcTt06CD9+vXTLK6ISHh4uPz6669StGhRsba2lvr168v69eslISFB1Ti9evWS0qVLy4EDB8TBwUH5HtevXy8lSpRQNRaJREREyM8//yx2dnZibW0tDRs2lICAAFWOvXfvXnn58qXy/zdtWoiJiZGOHTuKpaWlWFpaKr9LP/zwg4wfP16TmHrImjWrnD17NtX+s2fPiqurqyYx9Tjvipj+PY2MjBQ/Pz9xcXERS0tL8fDwEGtra6lcubJER0erHo+JTAo3b958600t9vb2qh7vbZUvX14mT54sIiIZM2ZUfrGPHTsmOXPm1CRmjRo1ZODAgaliHjp0SHLnzq1JTBGRNm3aSO3atSUsLMwo7rZt28THx0ezuMmOHj0qXbt2FVtbW/Hy8hJnZ2fx8vKSPXv2qBbD09NTjhw5IiLGP9tr166Jo6OjanFSWrRokTx//jzV/ri4OFm0aJGqsUqUKCElS5Z8q01rx44dk27duomLi4t4enrKiBEjpFOnTmJvby/9+/dXNdatW7ckMTEx1f7ExES5deuWqrGS6ZEUW1hYpLkS/cOHD1W7cHyVnZ2dXL58OdX+S5cuiZ2dnSYx9Tjviuh3oXPgwAHx9/eXX375RXbu3KlZHI6RSUGL6ob/pVy5cjh9+rTJY5u6GBSQVKJ6zpw5qfbnzJkT4eHhmsQEgB07dmD79u3IlSuX0f78+fP/Z8XL9xUREYElS5ZgwYIFuHHjBho1aoRNmzbBz88PMTExGD16NNq1a6da/AcPHqSajgwkrYekxe0zIGl2Vp06dVLFffr0KTp06IC2bduqFutNy0yYwv3795X389q1a6hfvz6WLVuG2rVrKz/f9u3bo06dOvj1119Vi+vt7Z3mVPPHjx/D29tbk1tL69evx4oVK1C+fHmj353ChQsjODhY9XgA0qzSDCQVBExZxkBNRYsWxYoVK1ItL7F8+XL4+PhoElOP8y6gz3sKAJUqVUKlSpU0O34yJjKvuHv3Lg4ePIj79+8rC+El02La4ffff4/+/fvj9u3baU6L02rVYlMXgwJMPwAsWUxMTJoLGD5+/Nho5ota6tevj+3bt+Ozzz5Dly5d0LZtW6O6OQ4ODujfvz8mTZqkWswyZcpg8+bN6NmzJ4D/W7tq3rx5mtU5kdeMMbp9+7bqa8roNVA8Wa5cuZA3b1507NgR7du3T/P3tVixYsq6Mmp53c9YqyrRgGmT4hkzZgBI+n2dN28eMmbMqDyXkJCA/fv3a7bC9/Dhw9GkSRMEBwejevXqAJJq9Cxbtkyz8TF6nHcB07ynye/l21D7s5SJTAoLFy7Ed999BxsbG2TJksXoDTYYDJokMi1atABg/MYmryOj5WC+Fi1aYPDgwVi1ahUMBgMSExNx6NAhDBgwQNUr6ZQaNGiA0aNHY+XKlQCSvs/Q0FAMHjwYTZs21SQmAHzxxRdYvHgxfv75ZyVuYmIiJk6c+Map2e/L1dVVKYr3OtmyZVN1JsG4ceNQt25dXLx4EfHx8Zg+fTouXryIw4cPv9N6Ym+jZMmSSrXbGjVqGA0aTEhIQEhICOrUqaNqTL0FBAT8Z/E5Jycn1WbI6Vkl2pRJ8dSpUwEkJWyzZ882qt2SXHBw9uzZqsZMVr9+faxfvx7jxo3D6tWrlRo9u3bt0mzpGj3Ou4Bp3tPk9/K/aPFZyllLKXh4eKBbt24YOnToG2dkqEmPxbwAfYpBPXnyBF9//TVOnjyJp0+fIkeOHAgPD4evry+2bNmi2SyU8+fPo0aNGihVqhR2796NBg0a4MKFC3j8+DEOHTqEvHnzahLX1IKDgzFhwgSjCtGDBw9G0aJFVY2TXA9o1KhR6N+/v9FVdPKHT9OmTTW7JfC6mTzJTL0Mhhb0rBJ98OBB1K1bF61bt1Yu7lImxVosjVCtWjWsXbsWmTJlUv3Y6Yke511An/fUlJjIpJAlSxYcP378o/lgexumLAaV7NChQ0Yftn5+fprHfPLkCWbOnGkUt0ePHsiePbsqx9ezW1UvixYtwjfffKPZLY7X+eeff4wev3z5EqdPn8aiRYswatQodOrUSZU4yT1Pb0OrqtR6VIkGTJcUf6r0OO+mx/fUyckJQUFByJMnzwcdh4lMCoMGDULmzJlVq7nxtpYsWYLZs2cjJCQER44cQe7cuTFt2jR4e3trts7Iq+Lj4/H8+XOjq2t6e2+7qqxWlVEDAwNhbW2tnJT++ecfLFiwAD4+Pvjpp5806x1JT5YuXYoVK1akSnTe139Vok5JqzE8n0qV6I4dO77x+T///FOVOOmlCF+yT/28m7Lq74dgIpNCQkICvvrqKzx79gxFixaFtbW10fNqr8kDALNmzcKIESPQp08fjB07FufPn0eePHmwcOFCLFq0SPWqtBs3bsSjR4/Qvn17Zd/YsWPx888/Iz4+HtWrV8eKFStU7eI9cuQIHj16hK+++krZt3jxYowcORIxMTFo1KgRfvvtN9UH3j58+BAxMTFGt+cuXLiAX3/9VYnbsmVLVWPqpWzZshgyZAiaNm2KGzduwMfHB02aNMGJEydQr1499QtQIf3d4rlx4waKFSuG6Ohok8bVkpubG549e2aSKtHx8fFISEgw+juMiIjA7NmzERMTgwYNGmg2A6Vx48ZGj1++fInz588jMjIS1atXx9q1a1WJo1cRPj3Ou4C+7+nbUCuRYR2ZFH7++WcxGAxSsGBBqVKlilStWlXZqlWrpknMQoUKybp160TEuK7AuXPnJEuWLKrHq1q1qsycOVN5fOjQIbGwsJAxY8bImjVrpGDBgtK3b19VY9apU0cmTJigPD579qxYWVlJ586dZfLkyeLu7i4jR45UNaaISIsWLYwK3kVEREimTJmkcOHC0qBBA7G2tpbFixerHlcPTk5Ocv36dRERmTBhgtSqVUtERA4ePCi5cuXSJOa6detk/fr1yrZq1Sr53//+Jzlz5pR58+ZpEvN1YmNjpXfv3vLZZ5+ZNK7WXr58KWvXrlV+XwsUKCATJkyQe/fuqR6rffv20rVrV+VxVFSUeHh4SLZs2aRYsWJiZWUlmzdvVj3u6yQkJEjXrl3ll19+MVlMrehx3hVJf+/pq1J+5n0IJjIpuLi4yIIFC0wa087OTimIl/JNvXr1qiZFmbJlyyaBgYHK4759+0rt2rWVx5s3b5Z8+fKpGtPd3V1OnDihPP7f//4nFStWVB6vXLlSChUqpGpMEREvLy+j6qeTJk2SvHnzKlVTJ02aJJ9//rnqcUVEwsLCxN/fXwYPHix9+/Y12rTg6OgoV69eFRERPz8/mTZtmogkFVTTqrjX6/z999/SoEEDzY7v4uIimTJlUrbk6qGOjo7yzz//aBIzPj5eJk2aJGXLlhU3Nzej+JkyZdIk5qu0rhKdP39+2b59u/J45syZkiNHDomMjBQRkUGDBknVqlVVifW2Ll++LO7u7pocu0aNGrJgwQJ58uSJJsdPSY/zrkj6fE9TUiuR4fTrFGxtbVGxYkWTxvT29kZQUFCq2Unbtm0zWttJLU+fPkWWLFmUxwcPHkSzZs2Ux4ULF8bdu3dVjfnvv/8arUWzb98+1K1bV3lctmxZhIWFqRoTAMLDw+Hl5aU83r17N5o0aaJMF27QoAHGjx+vetyAgAA0aNAAefLkweXLl1GkSBHcvHkTIoJSpUqpHg9Iml45ZswY+Pn5Yd++fZg1axaApMXi1FwH6G2UL18eXbt21ez4U6dONbolYGFhgWzZsuHzzz/XbNbLqFGjMG/ePPTv3x/Dhg3Djz/+iJs3b2L9+vWpCqppxc3NDZUqVcLVq1dx9epVnDt3Du3atUOmTJmwYMECVK1a9YOOf+fOHaNBpwEBAWjatKlSE6hdu3ZYsGDBB8V4V8HBwYiPj9fk2IULF8bQoUPx/fffo169emjdujW+/PLLVEMK1KDHeRdIn+9pSqrVJfrwnOrjMW7cOOnZs6dJY/7xxx+SM2dOWb58uTg4OMiyZctkzJgxyv/VljdvXtm2bZuIiDx9+lRsbGzk4MGDyvOnTp2SrFmzqhrT09NT9u3bJyJJ5evt7e1l165dyvNnz57V5KrW1dVVgoKClMdZsmSR1atXK4+vXr0qDg4OqsctW7asjBgxQkT+74rj6dOn0qBBA/n9999VjyeStI5VkSJFxMnJSX766Sdl/w8//CDffvutJjHT8rHe4smTJ49s2rRJRJLe0+TbeNOnT9f85xseHi6TJk0SHx8fsbOzkxYtWijl3qOjo2XQoEHi6en5wXEyZ84sFy5cUB5nz55d/vrrL+VxcHCw2Nvbf3CctLzaa9mnTx/55ptvJGPGjNKjRw9NYook3b7avn27tGvXTpycnCRTpkzSpUsX1dex0uO8K6Lve/o2eGtJA40aNRInJyfx9vaWr776Sho3bmy0aeWvv/6SfPnyKYtT5sqVS7MxBkOGDJGCBQvK4sWLpUWLFuLp6Snx8fHK83PmzDG67aOGbt26ia+vr+zfv1/69esnWbJkkbi4OOX5v/76S8qUKaNqTBGRBg0aSMeOHSUhIUFWrVolNjY28vjxY+X5TZs2ScGCBVWPm/KDzsXFRc6fPy8iIkFBQZquKZWWZ8+eyYsXL5THS5cuVW3RNj1u8YiIbN26VQ4cOKA8njlzphQvXly+/fZbo/dXTRkyZFDWNnJ3d5dTp06JSNIHgZOTkyYxRUS++uorsba2lsKFC8vUqVPl0aNHqV4TEREhBoPhg2NVr15dhgwZIiIi+/fvFwsLC7l7967y/I4dOyRv3rwfHCctKccjVq1aVapXry7ffPONzJkzR7kVrLVnz57JypUrpXjx4qqv76THeVdE3/c0pfj4eDl9+nSqv88DBw6kuV7bu2Iik0L79u3fuGkhNjZWYmJiRCRphdJjx47JlClTlOxdi3ht2rQRFxcXKViwoOzfv9/o+apVqxoNzFXDgwcP5IsvvhCDwSCOjo6ydu1ao+erV68u//vf/1SNKZLUS5E1a1axsbERCwsLGTZsmNHzrVu3lu+++071uG5ubnLx4kURSRrMnfyhHhQUpEkP0LtwdHRU5QpIRGTBggWycOFCZVu8eLFs3bpVs2QiWZEiRZQBimfPnhUbGxsZOnSolC9fXrO/088++0yOHj0qIiIVK1ZUVgxevny5ZMuWTZOYIiIdO3aUw4cPv/E1iYmJqiw8m7wyc548ecTe3l46duxo9Hz37t2lbdu2HxwnPbp3755MnTpVSpcuLQaDQfWxc3qcd0X0e0979+6tXIzHx8dLxYoVxWAwiIODg6qL5SZjIqOzmjVryqxZs0RE5N9//xU3NzfJlSuX2NnZaXYbQi+RkZFGVyHJHj16ZNRDo6YHDx7I+vXrlQ+hlDZt2iQ3btxQPWbDhg1l7ty5IiLSv39/yZcvn4wZM0ZKlSolNWrUUD3eu1CrK1dPDg4OEhISIiIiI0eOlKZNm4pIUve8m5ubJjEHDx4sY8eOFZGk5MXKykry5csnNjY2MnjwYE1i6uHixYsybdo0Wb58eapBxHPmzJHTp0/r0zANPHnyRP7880/x8/MTKysr+eyzz2TUqFFKb6qeDh48qEpPhYg+72nOnDmVCR7r1q2THDlyyJUrV2TYsGFSoUIF1eOxjozOsmbNin379qFw4cKYN28efvvtN5w+fRpr1qzBiBEjcOnSJU3iPnv2DCKirOFy69YtrFu3Dj4+PqhVq5YmMdO7okWLYsuWLfDw8Pig49y4cQPR0dEoVqwYYmJi0L9/fxw+fBj58+fHlClTdFllPdmH1m04e/bsW79WqwVPM2fOjIMHD8LHxweVKlVC27Zt0bVrV9y8eRM+Pj6IjY3VJG5KR44cwZEjR5A/f37Ur19f1WN/KlWi9a6cbG9vj0yZMuGbb75Bq1atUKZMGdVjvC+1Kt6+q3r16mHevHkfXPHczs4O169fR65cudC1a1dkyJAB06ZNQ0hICIoXL57m4sEfgrOWXrF69WqsXLkSoaGhePHihdFzWvwxxcbGwtHREQCwY8cONGnSBBYWFihfvvx/rsP0IRo2bIgmTZqgW7duiIyMxOeffw5ra2s8fPgQU6ZMQffu3VWP2bhx4zRPXAaDAXZ2dsiXLx9atmyJAgUKqB77bdy8eRMvX7784OOkPPk4ODhotuidHkqUKKEsavomWi54WqlSJfTr1w8VK1bE8ePHsWLFCgBJq6jnypVLk5iv8vX11WxVcT0X3wOSisZlzZoV9erVA5BU8Xzu3Lnw8fHBsmXLVEvEGzVqpMpx3oeIYMaMGWjVqpXRgpzphV79C/v378ezZ88++Dhubm64ePEismfPjm3btimzKGNjYzVZT4qJTAozZszAjz/+iPbt2+Off/5Bhw4dEBwcjBMnTqBHjx6axMyXLx/Wr1+Pxo0bY/v27ejbty8A4P79+5qurxIYGKicMFevXg03NzejniAtEhlnZ2esX78eLi4uyiJlgYGBiIyMRK1atbBixQr88ssvCAgIMPk0eC28ePEC9+/fR2JiotF+T09PnVr04dRcsft9zZw5E99//z1Wr16NWbNmIWfOnACArVu3arrq9rVr17Bnz54031M1p2Dr/TMeN26c8sFz5MgR+Pv7Y+rUqdi0aRP69u2rWpVdrZZ1eBsigh49eqBq1aomWefoU9OhQwc0b94c2bNnh8FgUNbTO3bsGAoWLKh+QNVvVpmxAgUKyNKlS0XEeCzB8OHDNZsCuGrVKrG2thYLCwupWbOmsn/cuHFSp04dTWKKiNjb2yuzMJo1a6ZM2Q0NDdVsOt7gwYOle/fuRvdpExIS5IcffpChQ4dKYmKidO3aVZPR+29DrfEjV65ckUqVKomFhYXRZjAYVJ8N8a4+hjEyepg7d65YWlqKm5ubFC9eXEqUKKFsJUuW1Lt5qkp5bhg0aJC0adNGRETOnz+vyRThlE6ePClLliyRJUuWGBWQ04KPj48cOXJE0xjvS6+/UzXjrlq1SqZMmSJhYWHKvoULF8r69etVOX5K7JFJITQ0VFnLxN7eHk+fPgUAtGnTBuXLl8fMmTNVj/n111+jUqVKuHfvHooXL67sr1GjRqr1R9SkR0/Q/PnzcejQIVhYWCj7LCws0LNnT1SoUAHjxo3DDz/8gC+++EKT+KbSoUMHWFlZYdOmTcoVSXqRO3duVQt+BQcHY9q0acpYLh8fH/Tu3VvzFeQTExNx/fr1NHtHKleurHq8MWPGYOzYsRg8eLDqx/4vt2/fxoYNG9K83a3F+m8ZM2bEo0eP4OnpiR07dqBfv34AksY9qHHbIS33799HixYtsHfvXri4uAAAIiMjUa1aNSxfvhzZsmVTPeaECRMwcOBAzJo1C0WKFFH9+J+6r7/+GgDw/PlzZZ+a61cZUT01MmPe3t7KVUDp0qVl9uzZIiKyfft2k5UhNxU9eoJcXFzSrC/yzz//iIuLi4gkFalL/r+pqXU1kiFDBrl06ZIKLXp7bdu2VYoOmsq2bdvExsZGypUrpxQyK1eunNja2sqOHTs0i3vkyBHx9vZWerlSblr1eKk5bf1d7Nq1SzJkyCBFihQRKysrKVGihLi4uIizs7Nm67+1bNlSSpUqJZ06dZIMGTLIw4cPRSTp77Rw4cKaxGzevLmUKVNGKVsgInLhwgUpU6aMtGjRQpOYLi4uSmkGOzs7XZadeB29ft/UOgfGx8fL6NGjJUeOHGJpaakcc9iwYZrUSGOPTArVq1fHhg0bULJkSXTo0AF9+/bF6tWrcfLkSTRp0kTv5qlKj56gNm3aoFOnTvjf//6HsmXLAgBOnDiBcePGoW3btgCgzOAyZz4+Pnj48KFJYz558gR+fn7InTs3OnTogHbt2iljR7QyZMgQ9O3bFxMmTEi1f/DgwahZs6Ymcbt164YyZcpg8+bNJuvxatasGXbs2IFu3bppHiuloUOHYsCAARg1ahQcHR2xZs0auLq6olWrVpqNB/L398ewYcMQFhaGNWvWKKX1T506hW+//VaTmNu2bcOuXbuMlmXx8fGBv7+/ZrMotVgRXi1i5pOJx44di0WLFmHixIno0qWLsr9IkSKYNm0aOnXqpG5A1VMjM5aQkGBURXLZsmXSs2dPmTFjhmZ1TvQSGRmZZpXQR48eabaIWnx8vIwZM0bc3d2VK2h3d3cZO3asUl/m1q1bRvdUTenvv/9WpeptQECA+Pr6yp49e+Thw4fy5MkTo00r9+/fl8mTJyur2tapU0dWrVplVNlXTba2tspClSlduXJFbG1tNYkpktTjde3aNc2On5Zx48ZJ1qxZpV27dvLrr7/K9OnTjTatpKcq0VrKmDFjmvVMAgMDxdHR0fQN0kjKAqgiIjdv3pSpU6caLeyop3Hjxsm///77wcfJmzevsgxNyl6eS5cuadLjzkTmE1WnTh3x9/dPtX/WrFlSt25dzeNr/aGe0qsfOsnbjBkzZO7cubJ79+40C/W9r5S3OfQa7Hvq1Cn54YcfxM7OTrJmzSp9+vRJM+n4ELly5ZKVK1em2r9ixQrx8PBQNVZK1apVk61bt2p2/LR4eXm9dvP29tYsrh5Vov/8888039eVK1fKwoULNYnZoEEDqVy5sty5c0fZd/v2balSpYo0atRIk5giItevX5cff/xRWrRoIRERESIismXLFiVhVJteBVAXLlyorBUmIjJw4EBxdnYWX19fVapCv8rOzk45bspE5sKFC5r83jKRSWHkyJGpKh+KJPVeaHWfVi+ZMmUyuh+d7NKlS5I5c2YdWqQdLy8vcXBwEIPBIJkzZ5bMmTMr5bLd3NzEYDBI3rx5JTQ0VJV4e/fufeOmtbt378qECROkQIEC4uDgIG3btpUaNWqIlZWVTJkyRbU4o0aNEhcXF5kwYYLs379f9u/fL+PHjxcXFxcZPXq0anFetXbtWvHx8ZEFCxbIyZMn5cyZM0bbx0SPKtH58+eX3bt3p9q/d+9ezRYDDQ0NlRIlSoi1tbXkyZNH8uTJI9bW1lKyZEnNemiTy/f7+fmJjY2N8mE7fvx4pVq02rJkyaIkSX/88YcUK1ZMEhISZOXKlZqs+5bss88+k4CAABEROXz4sGTIkEHmzJkj9evX12QdwVKlSsmSJUtExDiRGTVqlFSqVEn1eExkUsiVK5f4+voaDXbas2ePeHh4SNmyZXVsmfoyZMggZ8+eTbX/7Nmzmk2/Dg8Pl9atW0v27NnF0tIyVY+FVpYuXSpVq1Y1Kj1+7do1qV69uixfvlzCwsKkYsWKmp28TOHFixeyevVqqVevnlhbW0vp0qVl1qxZRr1ea9euVbVbNzExUaZMmSI5c+ZUeqFy5swp06ZNk8TERNXivOrVAb7JPV3pYXq72oKDg5XkLDo6Wr777jspWrSoNGnSRJMraZGkW4bJS0CkFBISInZ2dprEFEn6fdqxY4fMmDFDZsyYoazwrZXy5cvL5MmTRcT4w/bYsWOSM2dOTWLqUfbi1bimmFK/fv16cXZ2lgkTJkiGDBlk0qRJ0rlzZ7GxsdFkIgAH+6Zw9uxZfPfddyhRogQmT56Mq1evYvr06Rg4cCBGjRqld/NUVa5cOcydOxe//fab0f7Zs2crxerU1r59e4SGhmL48OEmnZY8bNgwrFmzxmhKcL58+fDrr7+iadOmuHHjBiZOnIimTZuqGjc2NjbNKbNalO7Pnj07EhMT8e233+L48eMoUaJEqtdUq1ZNmdqqBoPBgL59+6Jv375KqYLkKtVa0qtgnKmnQQP6VIl2dXXF2bNn4eXlZbT/zJkzysBfLRgMBtSsWVOzQeKvOnfuHJYuXZpqv6urq2aD9fUqgGrqKfUNGzbExo0bMXr0aDg4OGDEiBEoVaoUNm7cqM37q3pq9BEYOnSoGAwGsba2VgYsfWwOHjwodnZ28sUXX8hPP/0kP/30k3zxxRdiZ2eXamVWtbxuQJ/W7O3tlQXMUjp+/LhyFRQSEqLavdv79+9LvXr1UvU4adnztHjxYnn27Jkmx35be/fulS1btmi++rUe9JgGnVJcXJyEhYXJrVu3jDYtDBo0SHLnzq2MHYuPj5eAgADJnTu39O/fX9VYhw8flo0bNxrtW7RokXh5eUm2bNmkS5cuqi2e+KqcOXPKoUOHRMS4R2bt2rWSJ08eTWLqVQBVjyn1psRE5hUzZsyQDBkySMuWLaVAgQLi4+MjQUFBejdLE6dPn5aWLVuKj4+PlC5dWjp06KD6gNCUChUqpHm1zrR8+eWXUqpUKaPYgYGBUrp0aalXr56IiGzYsEGKFCmiSryWLVtKxYoV5cSJE+Lg4CA7duyQJUuWSIECBYwG3KnlxYsXYmlpKefOnVP92GmZMGGCDBs2THmcmJgotWvXVm7zuLm5aTZYMtn169flhx9+kBo1akiNGjWkZ8+emq5aXLZsWRkxYoSI/N+H3tOnT6VBgwaaDtLUo0p0XFycNG/eXLmYs7a2FktLS+nQoYPqszfr1KkjEyZMUB6fPXtWrKyspHPnzjJ58mRxd3eXkSNHqhozWf/+/aVSpUpy7949cXR0lGvXrsnBgwclT548yi0fLdy7d08CAwONxmMeO3ZM09pT//77r/To0UMaNGhgNFB+xIgRMmbMGM3imgoTmRRq164tmTNnllWrVolI0lS5bt26iZ2dnfzyyy86t878bd++XWrVqpXm/Xct3bt3T/z8/MRgMIiNjY1SBKtmzZoSHh4uIiK7d+9WbQqku7u7HDt2TESSCltduXJFRJKufrRafsHb29tkCXfJkiVl+fLlyuOVK1eKvb29HDx4UB49eiT16tWTZs2aaRZfj0J8ek2DrlChglSuXFm2bNkip0+flqCgIKNNS1euXJGVK1fKxo0bNRuP4+7ubtRb+r///c/ob2TlypVSqFAhTWLHxcVJ586dxcrKSknaLCwspHXr1qrOYvxUZMqUSR48eCAiSX8jrxYY1LLYoEHEzCvvqKhmzZpYtGgRcuTIYbR/8+bN6Ny5M+7du6dTy9QRFRWl3If9r2XUtbhfmylTJsTGxiI+Ph4ZMmRIVSr/8ePHqsdM6fLly7h69SoAoECBApqtsu3k5KSMMcidOzeWLl2KihUrIiQkBIULF0ZsbKzqMefPn4+1a9diyZIlyJw5s+rHTylTpkw4fPiwUrysQ4cOSEhIwOLFiwEAR48eRbNmzRAWFqZJ/JIlS6J27dppFuLbsWOHJqvUu7u7Y8+ePShUqBB8fHwwYcIENGjQAGfOnEHFihURHR2tekwgaVzMqVOntFloLx2ws7PDtWvX4OHhASBpZfO6devixx9/BJC0In3RokWVMVhaCAsLw7lz5xAdHY2SJUtquohkTEwMJkyYgICAgDSX17hx44YmcRcsWICMGTOiWbNmRvtXrVqF2NhYVZYOWLRoEVq0aAFbW1ssWrToja9Ve6kCDvZNYefOnThw4AAGDRqE4OBgrF69Gjlz5sTjx4+xcuVKvZv3wTJlyoR79+7B1dUVLi4uaQ62FREYDAYkJCSoHl/vSpoFCxY0yQdCgQIFcOXKFXh5eaF48eKYM2cOvLy8MHv2bGTPnl2TmDNnzsT169eRI0cO5M6dGw4ODkbPq/nhHh8fD1tbW+XxkSNH0KdPH+Vxjhw5NK1sfOnSpTT/Hjt27KjZ71j58uVx8OBBFCpUCF9++SX69++Pc+fOYe3atShfvrwmMQHTVYnu168ffv75Zzg4OCgDQV9HzYHNbm5uCAkJgYeHB168eIHAwECjiRVPnz5VdW2wtHh4eMDDwwMJCQk4d+4c/v33X2TKlEmTWJ07d8a+ffvQpk0bk054GD9+PObMmZNqv6urK7p27apKYpF8jPj4eBgMBtSuXRtubm4ffNy3wUQmhTVr1qBNmzZo1aoVTp8+jbi4OABJ5d/Hjx9v9osZ7t69W7la37Nnj8nja7Zg2H9ISEjAwoULX3sVtHv3blXj9e7dW+m9GzlyJOrUqYO///4bNjY2WLhwoaqxkjVq1EiT46Ylb9682L9/P/LkyYPQ0FBcvXrVaKHG27dvazq7JVu2bAgKCkp15RwUFARXV1dNYk6ZMkXpdRk1ahSio6OxYsUK5M+fX7MZSwDwyy+/YNCgQRg3bhyKFi2a6kNdrZ7T06dP4+XLl8r/TeXLL7/EkCFD8Msvv2D9+vXIkCGD0Xn27Nmzmi1A2qdPHxQtWhSdOnVCQkICqlSpgsOHDyNDhgzYtGkTqlatqnrMrVu3YvPmzahYsaLqx36T0NBQeHt7p9qfO3duhIaGqhrLysoK3bp1UxaSNQnVb1aZsRIlSsiiRYtExHgUe2BgoLi5uenZNNXdunUrzVofiYmJqs6GSFnH5NVS/aYq3d+jRw9xcHCQ5s2bS+/evaVPnz5Gm9ZiYmLk1KlTyv1jczd37lxxcHCQjh07io+Pj1SoUMHo+Z9//lm++uorzeLrVYjvbSxdulSVZS6SpYcq0Vp68OCBfPHFF2IwGMTR0VHWrl1r9Hz16tXlf//7nyaxc+bMqYzPWbdunWTPnl2uXLkiw4YNS/U7rRYvL680C5FqzcPDI80Fe9evX69JzZwqVarIunXrVD/u6zCRScHe3l4ZiJoykQkODtZ07Rg9WFhYKCW5U3r48KGqJ8iUcdI6IZvipJwlSxbZvHmzZsd/X1qscHvy5ElZsmSJLFmyRNMZYvPnz5dGjRpJt27d5N69e0bPde/ePdUHkpr0KsT3NtR+T/WoEt2hQweJiopKtT86Olo6dOigSczIyMg0B9g+evTIaKZUWFhYmtXX34etra1SNbhLly7Su3dvERG5ceOGZus7LVmyRL7++muj9ZZMwZRT6kWSlinJkyeP/Pbbb3L48GHNq28zkUnB29tbqSaZMpFZtGiRZiPn9WIwGOT+/fup9t+8eVMyZMigWpy9e/cqC3HqVbo/+UorvUn5O/ahIiIipFq1amIwGJSZAQaDQapXr57m+2xK48ePV2UhurRERUWl+aGrFzXf0/+i1XT7113kPHjwQCwtLTWJ+bbUTBQ9PT1l+/btEh8fLx4eHkpphPPnz2uysKFIUq+/o6OjZMyYUYoUKSIlS5Y02rRiyin1Iqavvs0xMil06dIFvXv3xp9//gmDwYC7d+/iyJEjGDBgAIYPH65381SRPJDPYDBg+PDhyJAhg/JcQkICjh07lmZV2PdVpUoV5f/e3t7w8PBINcBNRDSb4QIA/fv3x/Tp0zFz5kyTDa4ztZ49e+Lp06e4cOGCMpvo4sWLaNeuHXr16oVly5bp1rZx48ahefPmH1xV+NmzZ9i5cyeqVaumVBBO/jcqKgp79+5F7dq1jQYif2yePn2KZcuWYd68eTh16pSqg/KjoqIgSRe3ePr0Kezs7JTnEhISsGXLFs3GIL0tUXGSbYcOHdC8eXNl0K2fnx8A4NixY5pNCjDlWLaUbGxssGLFCvz88884c+YM7O3tUbRoUeTOnVuTeKauvs1EJoUhQ4YgMTERNWrUQGxsLCpXrgxbW1sMGDAAPXv21Lt5qkgeyCciOHfuHGxsbJTnbGxsULx4cQwYMECT2N7e3sqsqZQeP34Mb29vTWZKAcDBgwexZ88ebN26FYULF041YHLt2rWaxDWlbdu2YdeuXUoSAyTNePH390etWrV0bJl6Hz5z587Fhg0b0KBBg1TPOTk5YcaMGQgLC0OPHj1UiZee7N+/H/Pnz8eaNWuQI0cONGnSBP7+/qrGSJ7JaDAY8Nlnn6V63mAwfFRLtfz0008oUqQIwsLC0KxZMyUBtrS0xJAhQzSJOXLkSE2O+7Y+++yzNN9btWmVIL0OE5kUDAYDfvzxRwwcOBDXr19HdHQ0fHx8kDFjRr2bpprk2UodOnTA9OnTNV3f41Xy/6d2vyo6Otro6k9tLi4uaNy4sWbHTw8SExPTnKZqbW2dapaWufr777/f2DPap08fjB49+qNJZMLDw7Fw4ULMnz8fUVFRaN68OeLi4rB+/Xr4+PioHm/Pnj0QEVSvXh1r1qwxqkdkY2OD3Llzp6qxZe6+/vrrVPtenV1ZtGhRbNmyRal1o4ZTp04ps3oKFy6MkiVLqnbsZHpNqU+2ZMkSzJ49GyEhIThy5Ahy586NadOmwdvbGw0bNlQ1FhOZNNjY2GhyokhPKleurHl9hmSmvp31qgULFmh27A+h5m2u6tWro3fv3li2bJnyYXPnzh307dsXNWrUUC2Onq5du4bixYu/9vlixYrh2rVrJmyRdurXr4/9+/ejXr16mDZtGurUqQNLS0tNF41Mvg0cHBwMLy+vj/Y27Lu6efOmMjX9Q92/fx8tWrTA3r17lVutkZGRqFatGpYvX45s2bKpEgfQb0o9AMyaNQsjRoxAnz59MHbsWKW33cXFBdOmTVM9keFg30+Uq6urODo6SseOHZWF07RStWpVqVq1qhgMBqlQoYLyuGrVqlKrVi3p2rWrpms8pVdqDgwNDQ2VEiVKiLW1teTJk0fy5Mkj1tbWUrJkSWVmhl7U+j4zZswoJ0+efO3zJ0+elIwZM35wnA9RuHBhCQ0N/eDjWFpaSt++fVP9XVhZWcmFCxc++Phv4uXlJaNGjdJsUcoPocVMv/+i5t9p8+bNpUyZMkZTsC9cuCBlypSRFi1aqBIjPShUqJAy/Trlz+/cuXOSJUsW1eOxR+YTdefOHWzcuBELFy5E1apVkSdPHnTo0AHt2rWDu7u7qrH0uJ1VqlQpBAQEIFOmTChZsuQbry61KGn/NrZu3YqcOXOqciwPDw8EBgZi165duHz5MgCgUKFCygDGj0HhwoWxa9culC5dOs3nd+zYgcKFC5u4VcbOnz+vynEOHjyI+fPno3Tp0ihUqBDatGmDFi1aqHLs/9K7d28sXLgQo0ePRrVq1dCpUyc0btw4XQyiFjNfUUevsWwdO3bE9OnTlcHxyWJiYtCzZ0/8+eefqsYLCQlJ83aZra0tYmJiVI0FAFxriRAREYG//voLixYtwuXLl1GnTh106tQJ9evXh4WFhd7Ney+jRo3CwIEDkSFDBvz0009vTGTUHoD3uvvRBoMBdnZ2yJcvHxo2bKj5mkiRkZEfPFMoLYsXL8Y333zz1h9sX375JebPn//ByzPMnTsX/fr1w/Lly/HVV18ZPbdx40Z8++23mDJlCrp27fpBcdKSKVOmNH+HUr6n7du3R4cOHVSNGxMTgxUrVuDPP//E8ePHkZCQgClTpqBjx46pPpTUFhgYiIULF2LZsmVISEhAy5Yt0bFjR5QqVUq1GJaWlmlOAHidsLAw5MiRA5aWlqq14b84OjrizJkzyJMnjyrHOnDgQKpb6adPn0aVKlX+cw289/W6n/PDhw/h7u6O+Ph4VeP5+Phg/PjxaNiwodHP77fffsOCBQvUv3hUvY+HzNLRo0ela9euYmtrK15eXuLs7CxeXl6yZ8+eDzpu48aN33r7WFStWlWcnJzEwcFBSpUqJaVKlZKMGTOKs7OzfP7558rKsGreIpgwYYLRitTNmjUTCwsLyZEjh+qrJL+uzogptGrVSgwGgxQqVEgaNWokjRo1koIFC4qFhYWmXfNTpkyRLFmySOvWrWXGjBkyY8YMad26tWTNmlXGjh0rnTt3FltbW5k7d65mbbh8+bIMHDhQ3N3dxc7OTurXr69ZrJRevHgh06ZNE1tbW7GwsJDixYvL/PnzVSk+aDAYdPtdeltq3lpq0KCBVK5cWe7cuaPsu337tlSpUkUaNWqkSoyUnjx5IpGRkWIwGOT69etGldQfP34sixYtkuzZs6se948//pCcOXPK8uXLxcHBQZYtWyZjxoxR/q82JjKfsPDwcJk0aZL4+PiInZ2dtGjRQikIGB0dLYMGDRJPT88PitG+ffu33rTi7e0tDx8+TLX/33//FW9vb9XjTZ06VZo0aWK07EJkZKR8/fXXMm3aNImJiZGGDRtKrVq1VIvp5eWljHXasWOHuLi4yPbt26VTp05Ss2ZN1eKI6P/hs2LFCmnYsKH4+PhIoUKFpGHDhrJixQpNYzZp0kRmzZqVav/s2bOlSZMmIiIyY8YMKVKkiKbtEBGJj4+XdevWaZ7IvHjxQlasWCF16tQRS0tLqVixovz5558yevRocXNzk2+//faDY+j9u/Q2zHks2+uqqSdvlpaWMmbMGNXjioj89ddfki9fPqUgXq5cuWTevHmaxOKtpU9U/fr1sX37dnz22Wfo3Lkz2rZtm+pWx/379+Hu7m7203ctLCwQHh6eqls1IiJCWXVXTTlz5sTOnTtTzXy7cOECatWqhTt37iAwMBC1atVSbWVje3t7XL16FR4eHujduzeeP3+OOXPm4OrVq/j888/x77//qhIHSPp5RkREqDrDQgsTJkxAt27dVLm9ljFjRgQFBSFfvnxG+69fv44SJUogOjoawcHBKFasmCZjAEwpMDAQCxYswLJly2BhYYG2bduic+fORkXizp8/j7Jly+LZs2cfFMvCwgJjxoz5zxIXvXr1+qA4H2Lp0qVo2LBhqhXl35eImGws2759+3SZUv/s2TOICDJkyIDY2FicP38ehw4dgo+PD2rXrq16PA72/US5urpi37598PX1fe1rsmXLZvIKjWrasGGD8v/t27fD2dlZeZyQkICAgIA0V4T9UE+ePMH9+/dTJTIPHjxQ7oG7uLiomkBlypQJYWFh8PDwwLZt2zBmzBgASSdNLQoN1qhRA1ZWbz596DWIOplaFYUBIHPmzNi4cSP69u1rtH/jxo3Kh0NMTIzq41YaN278n2NzWrZsiQIFCqgWs2zZsqhZsyZmzZqFRo0apVmmwdvbW7XBx7Nnz37jmBeDwaBaIjNjxoy3fm1yzJYtW6oSO5nBYEDNmjVRs2ZNVY+bFr2m1Dds2BBNmjRBt27d8OLFCzRo0ADW1tZ4+PAhpkyZgu7du6saj4nMJ2r+/Pn/+RqDwaBqhUZvb+83/iHduHFDtVjA/5UDNxgMqYpcWVtbw8vLC5MnT1Y1JpD0R9yxY0dMnjwZZcuWBQCcOHECAwYMUNp0/PhxVStsNmnSBC1btkT+/Pnx6NEj1K1bF0DSIMJXexHUULt27XRfKFLNzubhw4eje/fu2LNnD8qVKwcg6T3dsmWLUttl586dRktyqMHZ2Rnr16+Hi4uLMlsrMDAQkZGRqFWrFlasWIFffvkFAQEBqFixoioxb9y48Z9/9w4ODqrVZzp58qTJlj6YOnXqW71O7eSpa9eusLOz+89ESquep+rVq6NDhw5o3749PD09NYmRUmBgoPKzXr16Ndzc3HD69GmsWbMGI0aMUD2R4a2lT8j7XI2oafr06UaPX758idOnT2Pbtm0YOHCgZmXBvb29ceLECWTNmlWT478qOjoaffv2xeLFi5XZAFZWVmjXrh2mTp0KBwcHBAUFAYBqhQBfvnyJ6dOnIywsDO3bt1emPk6dOhWOjo7o3LmzKnGA19+qS2/UnG0CAIcOHcLMmTNx5coVAECBAgXQs2dPVKhQQZXjp2XIkCGIiorCzJkzlRmEiYmJ6N27NxwdHTF27Fh069YNFy5cwMGDBzVrh1beddaSOfL29sbJkyeRJUuWN/YAGwwG1S/mkk2bNg0LFy7E+fPnTTKlPkOGDLh8+TI8PT3RvHlzFC5cGCNHjkRYWBgKFCiA2NhYVeMxkfmEvO1tFC3/oNLi7++PkydPptsKvO8rOjpa+TnmyZMn3fdgvC1z+fBRO5HRQ7Zs2XDo0KFUvXdXr15FhQoV8PDhQ5w7dw5ffPEFIiMj3zvO66aXp+Xx48fvHedV5pIUfyxMMaUeSKqy3blzZzRu3BhFihTBtm3b4Ovri1OnTqFevXoIDw9XNR5vLX1C0ut4l7p162Lo0KGqJjJ69z4BSQNEixUrpsmxgaQxQHXr1oW1tbXReKC0pLXQ4vv6VK99EhMTcf36ddy/fz/VAPjKlStrEjM+Ph6XL19OlchcvnxZGftkZ2f3wWMfpk2b9kFf/75Gjhypa4J/+/ZtbNiwAaGhoanGrGmx/tDo0aMxYMAAo2VagKTBsZMmTcKIESNUj5lSqVKlUKpUKUyePBm///47Bg8ejFmzZqFo0aLo1asXOnTooMo4mhEjRqBly5bKEinJYzF37NihybpS7JEh3U2cOBG///47bt68qdox9ex9iomJwYQJExAQEJDmh55a8VJezb6pcKHBYFB1wO+tW7fg6emZ7tfiUbNH5ujRo2jZsiVu3bqVKpFT++ebUq9evbBs2TL873//MxpvNW7cOLRs2RLTp0/HvHnzsHDhQrO8tXT27Nm3ep0WFwQBAQFo0KAB8uTJg8uXL6NIkSK4efMmRASlSpXC7t27VY/5ut7MR48ewdXVVbPfo2QvX77EunXrsGDBAuzcuRPly5dHp06dcPv2bfj7+6N69epYunSpKrHCw8Nx7949FC9eXDk/HT9+HE5OTkYz4NTAHplPmKmvRl5dKkBEEB4ejgcPHuD3339XNZaevU+dO3fGvn370KZNG2TPnl2zD/yUCZIpp8i/OtbpdbT4HXoXX3zxBezt7VU5Vrdu3VCmTBls3rxZ0/f0VVOnToWbmxsmTpyIiIgIAICbmxv69u2LwYMHAwBq1aqFOnXqaBL/+fPnqc4Nai4xUqJECRgMhjR7+ZL3a5UoDh06FAMGDMCoUaPg6OiINWvWwNXVFa1atdLs55n8/bzqzJkzmlb6TmtK/dSpU40SisaNGyvJshrc3d1TLXeTPFBebeyR+UTpcTUyatQoo8cWFhbIli0bqlatqnqGricXFxds3rxZtVkkbyN56rUpVKtW7T9fYzAYNPkdepPAwECMGDECmzZtUv3YDg4OOHPmjCYzwN5W8tR9rdcqi4mJweDBg7Fy5Uo8evQo1fNq9+69DTVnTyZzdHREUFAQ8ubNi0yZMuHgwYMoXLgwzpw5g4YNG6raQ5w8BunJkydwcnIySmYSEhIQHR2Nbt26wd/fX7WYKVlaWqJmzZro1KnTa6fUx8TE4IcffjDLsYrskflE6XE1ovaaRm+rY8eOb3xe7QXTMmXKpPk6Sq/y8vJCpUqV0Lp1a3z99dfIlCmTZrGSFwHVw/bt27Fz507Y2Nigc+fOSiI+ZMgQbNy4UZNiWwDw+eef4/r167omMqZYbBUABg0ahD179mDWrFlo06YN/P39cefOHcyZMwcTJkxQNda7Jijff/89Ro8ercoMRAcHB6W3KXv27AgODlYWHVWrUGWyadOmQUTQsWNHjBo1yqimlY2NDby8vN5Y0+tDmXpKvclpUi+Y0r2MGTPK9evXRUTExcVFzp8/LyIiQUFBkjt3bk1injp1Ss6ePas8Xr9+vTRs2FCGDh0qcXFxmsQUEWVNnuStXr16kjt3bnF2dtZkjaclS5bI119/LTExMaof+3UCAwNlwIABkitXLrG1tZWGDRvKqlWr5Pnz5yZrw+s4OjqqUuJ93rx5YjAYJEuWLGJhYSHZsmWTJUuWiIuLi3z33Xdy8eJFFVqbtrVr14qPj48sWLBATp48KWfOnDHatBIeHi6tW7eW7Nmzi6WlZaoS81rw8PBQ1lhzdHSUa9euiYjI4sWLpW7duprEfFtq/S6JiDRs2FBZG6t///6SL18+GTNmjJQqVUpq1KihSoxX7d27V168eKHJsT9l7JH5RJnyaiTZd999hyFDhqBo0aK4ceMGvvnmGzRp0gSrVq1CbGysZjMn1q1bl2pfYmIiunfvjrx586oeb/LkyQgODoabmxu8vLxSdeNqUfG2ZMmSKFmyJCZOnIi9e/di6dKl6Nq1KxITE9GkSRPVe53ehah093r69On45ZdfMHDgQKxZswbNmjXD77//jnPnziFXrlyqxHidpk2bAjDu3dN6DAcAtG/fHqGhoRg+fLjJxuY8fvxYGSDt5OSkTLeuVKmS6oXM3pVav0tA0hiu6OhoAEm3vaOjo7FixQrkz59fs/Fd3t7euHfv3mufV7NYnV5T6vXAROYTVb58eRw8eBCFChXCl19+if79++PcuXNYu3Ytypcvr0nMq1evKgXgVq1ahSpVqmDp0qU4dOgQWrRoYdIpoBYWFujXrx+qVq2KQYMGqXrs5Oq9ejAYDKhWrRqqVauG7t27o1OnTli0aJGuiYxagoOD0axZMwBJlYytrKwwadIkzZMYQL/B4wcPHsSBAwdUK5z4NvLkyYOQkBB4enqiYMGCWLlyJcqVK4eNGzeqstxDepFyNpuDg4NSoVlL/7VMgJoJsV5T6vXAROYTpcfViIgos2t27dqFr776CgDg4eGhWS/QmwQHByuVd9Wk11ggIGkm2tKlS7F06VKcP38evr6+mg0gNLVnz54p9TcMBgNsbW2RPXt2k8TWYrDp2/Dw8DB53Z4OHTrgzJkzqFKlCoYMGYL69etj5syZePnype4z0czd6dOnjR4nVzefMmUKxo4dq2qsV5dl+ZgxkflE6XE1UqZMGYwZMwZ+fn7Yt28fZs2aBSDpatfNzU2zuP369TN6LCK4d+8eNm/e/NH8sc+ZM0fp3SpYsCBatWqFf/75R7cPYK3MmzdPKaAWHx+PhQsXphr4qVaBQ70KDqY0bdo0DBkyBHPmzIGXl5cmMV6VcmFMPz8/XL58GadOnUK+fPk0LfBoaq+79ZJyQc727dujQ4cOqsUsXrx4qn1lypRBjhw5MGnSJDRp0kS1WK+j9ZR6PXD69SfuxYsXaRZt02JhsbNnz6JVq1YIDQ1Fv379lJ6Lnj174tGjR6oVYnrVq9OFk6d9V69eHR07dvzPVZzfRubMmXH16lVkzZr1P+9Na3E/2sPDA99++y1atWqV5slST05OTggKCvrgwnRvs3qvmgUO9So4mFKmTJkQGxuL+Ph4ZMiQIdV4K3Mf2/Cu1CxyOHXqVIwdOxZ169ZV6pscP34c27ZtQ9++fRESEoIlS5bgt99+Q5cuXT443ptcv34dxYsXR0xMjCbHN+WUej2wR+YTdfXqVXTq1AmHDx822q/l4MVixYrh3LlzqfZPmjQJlpaWqsdLZorpwsmLMyb/39RVb0NDQ9NtpV21rpXUrOvxNvQqOJiSXuMcAgICXluZWs/xVq1bt1at9+DgwYMYM2YMunXrZrR/zpw52LFjB9asWYNixYphxowZqiUyybWAkiX3Dv/000/Inz+/KjHSYsop9Xpgj8wnqmLFirCyssKQIUPSnA2h5VW9KXuBgKSxFSKijK+4desW1q1bBx8fH9SqVUuTmKbwtuXdAW1KvL8qISEB586dQ+7cuY3q2Bw8eBBly5bVbKVdU1i8eDG++eabVN/DixcvsHz5crRt21anlqlv1KhRGD16NMqUKZPmuSGtWYAfatu2bciYMSMqVaoEIGkh2T/++AM+Pj7w9/fXpC5SxowZERQUlKo20PXr11GiRAlER0cjODgYxYoVU62nxMLCItXPU0Tg4eGB5cuXa1ZLxtPTE4sXL0bVqlXh5OSEwMBA5MuXD0uWLMGyZcuwZcsWTeKaChOZT5SDgwNOnTpl0oq6evQCAUkl3Js0aYJu3bohMjISBQoUgI2NDR4+fIgpU6aoPqXUVOupJJ8Uk/+ETTUbIlmfPn1QtGhRdOrUCQkJCahSpQoOHz6MDBkyYNOmTahataqq8d52IVAtFgE15Ro5UVFRSq/Dq1fwr9JibEP27NkxceJEtGnTRvVjv07RokXxyy+/4Msvv8S5c+dQtmxZ9OvXD3v27EHBggU1KdTm6emJvn37Go0JApJ6VKdOnYrQ0FCcPXsWtWrVUm215n379hk9Tr7NnS9fPlVucb9OxowZcfHiRXh6eiJXrlxYu3YtypUrh5CQEBQtWlSZ+GGueGvpE+Xj42PymUIdOnSAlZUVNm3aZNL1agIDAzF16lQAwOrVq+Hu7o7Tp09jzZo1GDFihOqJzOuuDeLi4mBjY6NanJRTgk+fPo0BAwZg4MCBylXdkSNHMHnyZEycOFG1mCmtXr0arVu3BgBs3LgRISEhuHz5MpYsWYIff/wRhw4dUjVe8nuYLCwsDNmzZzf6ADAYDJokMvKaNXJu375tVKVVDZkyZVKSJhcXlzTjapn8v3jxAhUqVFD9uG8SEhICHx8fAMCaNWvw1VdfYdy4cQgMDMSXX36pSczhw4eje/fu2LNnjzJG5sSJE9iyZYsy+WHnzp2oUqWKajHVPNa7+Nin1DOR+UT98ssvGDRoEMaNG4eiRYumGkSoxZVeUFCQyXuBACA2NlYZv7Jjxw40adIEFhYWKF++/Fuv9fI2knsMDAaD0ewaIKlHZP/+/ap+7ylnJDVr1gwzZswwOukXK1YMHh4eGD58uCa1bR4+fKgsCrdlyxY0a9YMn332GTp27PjWC0u+i1druTg6OmLfvn2qDPx8neSFTg0GA2rUqGGUNCUkJCAkJET1JT12796tLHGhx3IQnTt3xtKlSzF8+HCTxbSxsUFsbCyApNIMybfqMmfO/J+9Uu+rS5cu8PHxwcyZM7F27VoAQIECBbBv3z4lkevfv/8Hx/mvGW8paTX77WOfUs9E5hPl5+cHAKhRo4bRfi2v9PToBQKAfPnyYf369WjcuDG2b9+udCXfv39f1YQtucdARDB79myjAczJ66loNc393Llz8Pb2TrXf29sbFy9e1CSmm5sbLl68iOzZs2Pbtm3KdPrY2FhNB2+bUnICGBQUhNq1axslp8nvaXLVX7WkvGr39vaGh4dHmuMqwsLCVI2b7Pnz55g7dy527dqFYsWKpbrI0eKDr1KlSujXrx8qVqyI48ePY8WKFQCSbkdrWfCwYsWKmi/u+rYXEVreXv/Yp9QzkflE6XGlp0cvEACMGDECLVu2RN++fVGjRg3l1suOHTtQsmRJ1eIk9xhUq1YNa9eu1XThxlcVKlQI48ePx7x585TbVy9evMD48eNRqFAhTWJ26NABzZs3V24TJifHx44d+2hWM08uEeDl5YVvvvkGdnZ2Jo2fXNL+1bE5jx8/hre3tyYffGfPnlUqCZ8/f17146dl5syZ+P7777F69WrMmjULOXPmBABs3bpVs0VsgaSimAsWLMCNGzcwbdo0uLq6YuvWrfD09FSWbPlQes14e5PcuXN/VDWmONiXUjl//jyKFCmi+nGTa3GkdXWp5dUIAISHh+PevXsoXry40o7jx4/DyclJsw/dFy9eICQkBHnz5tV0IB+Q9L3Ur18fIqJcYZ09exYGgwEbN25UxgCobfXq1QgLC0OzZs2UK+dFixbBxcUFDRs21CRmMjVriryNyMhIrF69GsHBwRg4cCAyZ86MwMBAuLm5KR+8arOwsEBERASyZctmtP/WrVvw8fHRrO7Ip2Dfvn2oW7cuKlasiP379+PSpUvIkycPJkyYgJMnT2L16tV6N1FV6XVKvRqYyBAA4OnTp1i2bBnmzZuHU6dOaZJUvDpi/1V6DYRT27Nnz/DDDz9g0aJFAJK6x/PkyYOePXsiZ86cGDJkiCZxY2Ji8Pfff+Py5csAknppWrZsCQcHB03ipfT8+XPNeyteHSuRK1cuHDx4MFXFWy169s6ePQs/Pz84Ozvj5s2buHLlCvLkyYNhw4YhNDQUixcvVjVecjXq6dOno0uXLkrpACBpbM6xY8dgaWmp+oDq1xERbNu2DfPnz9fsAz65dyQ4OBjTp0/XpHckJV9fXzRr1gz9+vUzSoqPHz+OJk2a4Pbt26rHBJLOg7/++isuXboEIOmW+8CBA/HFF19oEg/QZ0q9SWm/wDalZ/v27ZO2bduKg4OD5M+fXwYPHizHjx/Xu1mqio6OlmHDhomvr6/kzZtXvL29jTa19erVS0qXLi0HDhwQBwcHCQ4OFhGR9evXS4kSJVSPp5f4+HgZPXq05MiRQywtLZXvc9iwYTJv3jzV4xkMBrGwsFC21z3WQvXq1WXgwIEiIpIxY0blez106JDkzp1b9XhVq1aVqlWrisFgkAoVKiiPq1atKrVq1ZKuXbvK1atXVY/7qhs3bsiwYcMkV65cYmtrK/Xq1dMkzt69e8Xe3l78/PzExsZG+fmOHz9emjZtqklMBwcHuXHjhogYv6chISFia2urScwlS5aIlZWVNG/eXKZPny7Tp0+X5s2bi7W1tfz999+axBQRcXd3l8WLF2t2fL1xjMwnKDw8HAsXLsT8+fMRFRWF5s2bIy4uDuvXr1emQGolMjIS8+fPV65GChcujI4dO6o+hTWlzp07Y9++fWjTpo1Jpn2vX78eK1asQPny5Y1iFS5cGMHBwZrGvnjxIkJDQ1OtpaLFbIixY8di0aJFmDhxolHl0yJFimDatGno1KmTqvH0GNeV7OTJk5g7d26q/Tlz5lStxkhKyd9rhw4dMH36dJOuhRMXF4fVq1dj/vz5OHjwIBISEvDrr7+iU6dOmrVjyJAhGDNmjNI7kqx69eqYOXOmJjFdXFxw7969VIPkT58+rdmtwrFjx2LixIlGg2979eqFKVOm4Oeff0bLli01iavHlHqT0juTItP66quvxMnJSb799lvZtGmTxMfHi4iIlZWVXLhwQdPYJ06ckMyZM0vOnDmlcePG0rhxY8mVK5dkyZJFTp06pVlcZ2dnOXjwoGbHf5W9vb1ydZfySi8oKEicnJw0iRkcHCzFihVTeiUMBoNRj4UW8ubNK7t27RIR4+/z0qVL4uLioknMdzF+/Hj5999/VTlWtmzZJDAwUESMv9cdO3ZIrly5VInxJteuXZNt27ZJbGysiIgkJiaqHuPkyZPSvXt3cXFxkTJlysj06dMlPDzcJOcGPXpH+vfvL5UqVZJ79+6Jo6OjXLt2TQ4ePCh58uSRn376SZOYNjY2cu3atVT7r127ptn3KSIyaNAgGT16tGbH19vrV0Kjj9LWrVvRqVMnjBo1CvXq1TPpNNm+ffuiQYMGuHnzJtauXYu1a9ciJCQEX331Ffr06aNZ3EyZMil1OUyhTJky2Lx5s/I4uVdm3rx5mpUg7927N7y9vXH//n1kyJABFy5cwP79+1GmTBns3btXk5h37txJVd4dSJql8fLlS01ivotx48aptqhigwYNMHr0aOX7MhgMCA0NxeDBg1Wffp3S48ePUaNGDXz22Wf48ssvce/ePQBAp06dVKlxktLnn38OW1tbHD16FCdOnECvXr00XZU+peTekVdp2Tsybtw4FCxYEB4eHoiOjoaPjw+++OILVKhQAcOGDdMkpoeHBwICAlLt37VrFzw8PDSJCSSNYZsyZQqqVKmCnj17ol+/fkab2dM7kyLTOnLkiHTu3FkcHR2lXLly8ttvv8mDBw9MctVlZ2cnly5dSrX/woULYm9vr1ncJUuWyNdffy0xMTGaxUjpwIEDkjFjRunWrZvY2dlJ7969pWbNmuLg4CAnT57UJGaWLFnkzJkzIiLi5OQkly9fFhGRgIAAzcbllCpVSpYsWSIixlfRo0aNkkqVKmkS812kbNOHioyMFD8/P3FxcRFLS0vx8PAQa2trqVy5skRHR6sSIy1t2rSR2rVrS1hYmNH3s23bNvHx8VE1Vq1atcTR0VFatmwpW7duVXp9THFu0KN3JFloaKhs3rxZVqxYofm4o99//11sbGykW7dusnjxYlm8eLF89913YmtrK7Nnz9YsbsoxVmlt5o5jZD4x5cuXR/ny5TFt2jSsWLECf/75J/r164fExETs3LkTHh4eRveo1eTk5ITQ0NBU053DwsI0iwkAkydPRnBwMNzc3ODl5ZWqfk1gYKCq8SpVqoSgoCBMmDABRYsWxY4dO1CqVCkcOXIERYsWVTVWsoSEBOVnmDVrVty9excFChRA7ty5ceXKFU1ijhgxAu3atcOdO3eQmJiItWvX4sqVK1i8eDE2bdqkSUy9ODs7Y+fOnTh06BDOnDmD6OholCpVCn5+fqqt7p2WHTt2YPv27amKwuXPn1/VqtQAsH37doSFhWHBggXo3r07nj17hm+++QbAm9fxUsO4cePQo0cPeHh4ICEhAT4+PkhISEDLli1V7R35r96Ho0ePKv/XovBf9+7d4e7ujsmTJ2PlypUAkmYXrlixQtNyBf+vvXuPizl9/wf+mkmlAyW1JWqUcmhLItayOYWwtGqx2I0l1jGUU2sV6xBarEMO60xL2MIu21aoUNiiKIkOUnaJj8JKDjXdvz/6Nd9GJfR+z1sz1/Px6PHQ+z3mulOme+77uq9LyPwyRaDj1wQ3b97Ezp07ERwcjMePH6Nfv37vVFb7bc2YMQNHjx7F6tWrZYln8fHxmDt3Lr788kusW7eO85hA+dHDN6koesaVN9XhOXbsGC/tApycnDB79mwMHToUo0ePxqNHj7Bw4UJs27YNly9f5q2w2blz57BkyRK5X+7+/v4fRFdxLuvM/PTTT5g7d26V61KpFN988w1CQkLqHKM6jRo1QlJSEqytreW+nkuXLsHFxQUFBQW8xAXK+wzt3r0bR48ehZmZGYYNG4Zhw4ahY8eOvMXMy8vDtWvXUFRUBAcHB1hbW3P6/L17936rx4lEIkRHR3Ma+0PDFHCkXmGEXRAiH5LS0lJ29OhRNmTIEF6e/+XLl2zGjBlMQ0NDloSqqanJZs2axV68eMFLTCGYmprKEhcrCw0NZdra2rzEjIiIYGFhYYyx8sTBNm3aMJFIxAwNDdnp06d5ifmh43JrycjIqMqR8tLSUjZs2DDWtm1bTmJUZ+DAgWzhwoWMsfKv59atW0wqlbLhw4fzdiz5dYWFhWzDhg2sQ4cOvCWOq6Lnz5+zPXv2sM2bNyvkKH0FRR2pVyRakSEKV1xcLDuG3KpVK7liX3y6fPmy3LFvLtsTVLZo0SL8+uuviI+PlzVVPHToEMaPH489e/Zg+PDhvMR9XWFhIZo0aSK3LfDPP//A1NRUVt1YmXG5IpOYmIj+/ftj+/btGDZsGEpLSzFixAjcuHED0dHRsu8z165duwZnZ2d07NgR0dHRcHV1RVpaGgoLCxEfH49WrVrxErcmSUlJnK3I+Pj4YOnSpdDR0al1y6e+Nzb08fFBSUkJNm7cCKD8OHSXLl1w/fp1aGtro7S0FCdPnuTtMIAQR+oViXJkVJSbm1u1+94ikQgNGzaElZUVRo8ejTZt2tQ5llQqRVpaGqytraGlpQVtbW1Zrsjz58+RkpICW1tb3n65PnjwACNHjkRsbKysZf3jx4/Ru3dvHDx4sEr597r68ccfUVhYiL59++Ls2bOIiIjAhAkTEBwczOsJl9dVd1LLxsYGV65cee9f7gYGBsjIyIChoWGVSdLruDox9L6cnJygpaXFyXN17twZYWFhGDp0KDQ0NLBz505kZWUhJiaG15M9tra2yMjIQFBQEBo1aoSioiK4u7tj2rRpaNasGS8xU1JSqr0uEonQqFEjvHz5EpqamnWOk5ycLDsFlpSUVOPPEt/5OYoQFRWFgIAA2ef79+9HXl4eMjMzYW5ujvHjx2PZsmVypx25cPnyZezcuRMhISGwsrKCh4cHQkJC0KJFC7i4uCjFJAYAbS2pqrFjxzI9PT0mkUiYu7s7c3d3Zy1btmT6+vpsxIgRrE2bNkxTU5OT+iu7d+9mnTp1ktWsqaykpIR16tRJdvqFDyNGjGCOjo7s+vXrsmtpaWnM0dGRjRw5kre4o0ePZtbW1kxbW5sdO3aMtzjvoq7bLXv27JFtA+7Zs+eNH4pWUlLCcnNzeY1x9OhR1qBBA2ZnZ8f+97//8RqLMcaio6NrvBcUFMRLzNcrJr/+oampycaMGcOeP3/OS3xlVHESq8LIkSPZxIkTZZ8nJyezZs2acR5XTU2NzZo1S3aKsYIiTqIpEm0tqShfX1/8999/CAoKkq2ElJWVYebMmWjUqBGWL1+OyZMnIy0tDXFxcXWK5eTkhGnTpmHkyJHV3j98+DCCgoJw9uzZOsWpiZ6eHk6dOoXOnTvLXU9ISED//v3x+PHjOseoLjm6pKQE3t7e6N+/v1xlXT6q7L4trrZbSktLceDAAbi4uCis1khtrl69io4dO3LWJ8zd3b3a6xcvXoSVlRUMDQ1l144cOcJJzNc1adIEp06dQqdOneSur1+/Hn5+flX6T3Hh999/x/z58zF37lxZs9GEhASsWbMGixYtQmlpKXx9ffHVV19h9erVdY5XUlICLS0tXLlyhZdmtR8CfX19JCYmypKXLSws4Ofnh/HjxwMAbt++jXbt2uH58+ecxnVxccGFCxcwZMgQeHh4wMXFBSKRCOrq6rh69SrvldwVhbaWVNTOnTsRHx8vt50jFovh5eWFbt26ISAgANOnT+ekkdnNmzfRtWvXGu937txZlrvCh7KysipHrgFAXV29ShfY9/Wmk0i7du2SdZflu8u3ojRo0ACTJ0/m9fsmtJraZri4uChsDD/99BMGDhyIs2fPysoWrFmzBkuWLOF8G6LC8uXLsX79ermv087ODi1atICfnx8SEhKgo6OD2bNnczKRUVdXh7m5uVL8v6hJu3btcPz4cfj4+CAtLQ15eXlyJ6hyc3N5eUMg5JF6RaKJjIoqLS3FjRs30Lp1a7nrN27ckL2gNGzYkJMf9mfPnr3xnePTp09RXFxc5zg16dOnD2bOnImQkBCYmpoCKK9K6+3tDWdnZ05icDUhqk+6dOmC5ORkSCQShcSrLcmU63ezu3fvBlB+TPXOnTswMjLiLOfmbU2YMEGWbxUXF4dDhw4hICAA4eHh6N69Oy8xU1NTq/2eSiQSpKamAgA6dOhQbSXe9/XDDz9gwYIFCA4OVmgVbkWZN28eRo4ciT///BNpaWkYNGiQXI+n8PBw2eoX18zMzODv7w9/f3/ZkfoGDRrgiy++UMiRekWgiYyK8vDwgKenJxYsWCDbcklMTERAQADGjBkDoLzd/Mcff1znWNbW1jh//jzat29f7f24uDjO60VUFhQUBFdXV7Rs2VJWBvzOnTuwtbXFr7/+ymmskpISDBgwAFu3buX1a3pfXL4Lmzp1KmbPno1//vkHnTp1go6Ojtz9mr7f7+v69esYOXJklSZ/Fe7du4eMjAxOYwLlExkrKytZwrqizZs3DwUFBXB0dIRUKkVkZOQbVzjrqm3btli5ciW2bdsGDQ0NAOU/1ytXrpStCv3777+criAEBQUhKysLpqamkEgkVX6WuC5aqWhubm4IDw/HiRMn0L9/f3h5ecnd19bWxtSpU3kfR79+/dCvXz88evQIv/76K3bt2oVVq1bV+9UwypFRUVKpFCtXrkRQUBDu378PADA2NoaXlxfmz58PNTU15OXlQSwWV6kq+q4CAwMRGBiI6OjoKr/crl69CmdnZ8ybNw/z5s2rU5w3YYzh1KlTuHHjBoDypd6+ffvyEsvIyAjnz5//ICcyXB5Jru6UmUgkAmOMly00R0dHeHp6YsqUKdXev3LlCjp16sTLi/LHH3+MnTt38jqBqLBhw4Zqr69evRo9evSQe+c+Y8YMzuOfP38erq6uEIvFsv+vqampkEqlOHHiBLp27Yrg4GDk5+dXWyTwfSi6aOWHburUqViyZIlcHhZfKh+pV2RcLtFEhsi2ffg6ildSUoL+/fsjLi4Offv2lb2ru3HjBk6dOoXu3bvj5MmT1eax1Efe3t7Q1NTEypUrhR5KFXfu3IGpqSknzUJrK5HP9ZbTzJkzIRKJaqwAnZ2djQkTJvBSjv348eMIDAzEli1beE9IrWnF6XUikQi3bt3iZQxPnz7F/v37ZStcbdq0wejRo3ltJUL+T+PGjetUJqG+xa0rmsgQhSgpKcHPP/+MAwcOIDMzE4wxtG7dGqNHj8asWbNkS9hcio6OxvTp03Hx4sUqk7QnT56gW7du2Lp1KycJzZV5eXlh3759sLa2rnbLhaviXjWdqqkOX6dqVEWTJk1QXFyM0tJSaGhoVMmVEbpmjjJ4/PgxQkNDkZ2djblz58LAwABJSUkwNjbmrQP2h4rLldP6ELeuKEdGRd2/fx9z5szB6dOn8eDBgyqN77henldXV3/j9lFoaCiGDRvGacx169Zh4sSJ1a406enpYdKkSVi7di3nE5lr167Jlmpfz9ngMkelplM1ihQcHIytW7ciJycHFy5cgEQiwbp162BhYcFrEzxF46sP2JuUlJSgbdu2OHHiBNq1a6fQ2JmZmYiJicGDBw+qJLL7+/tzHi8lJQV9+/aFnp4ebt++jYkTJ8LAwABHjhxBXl4e9u3bx3lMokSEKF5DhDdgwABmY2PDNm/ezI4ePcqOHTsm98G1kpISlpqaym7evCl3/dixY6x9+/ZMQ0OD85jm5uZyRfBel56ezszMzDiPqyo2b97MDA0N2bJly5iWlpas0N7u3btZr169eIv7119/sXPnzsk+DwoKYvb29mzUqFGssLCQt7hCMDU1fePPMB+2bdvG1NTUmLGxMbO3t2cdOnSQfTg4OPAS09nZmc2dO5cxJl+0MT4+nkkkEl5ifsi47BNWH+LWFU1kVJSuri5LTk5WSKzU1FQmkUhklUHd3NxYfn4+69GjBzMwMGDz589nd+7c4TyupqamXDXN12VmZrKGDRtyHldVtGvXjh09epQxJv8CmJqaypo2bcpbXFtbW/bnn38yxhhLSUlhmpqa7Pvvv2ddu3Zl3377LW9xKzx//pw9efJE7oMvy5cvZ2PHjmUlJSW8xXidubk5W7lypcLiMcZY48aNWVZWFmNM/mfp9u3bTFNTU6Fj+RDQRObd0NaSijIzM6uyncSX+fPnw8rKCkFBQQgJCUFISAjS09Ph6emJiIgI3mpzNG/eHNeuXYOVlVW191NSUnjrV3Pp0iUcPnwYeXl5ePXqldw9vvJVQkNDa4zJx/HVnJycahtvampq4tmzZ5zHqxy3oiJpWFgYBg8ejICAACQlJWHQoEG8xHz27Bnmz5+Pw4cPo6CgoMp9vo6vJiYm4vTp04iKioKdnV2VfCs+fpYePXqksMamFTQ1NautNZWRkcF5LzSifJS/BS6p1rp16+Dr64vbt2/zHisxMRGrV6/G4MGDsXnzZgDAggULMGfOHF4LjA0aNAh+fn548eJFlXvPnz/HokWLMHjwYM7jHjx4EN26dUN6ejqOHj2KkpISpKWlITo6mre8lg0bNmDcuHEwNjZGcnIyunTpgqZNm+LWrVsYOHAgLzEtLCxw5cqVKtcjIiJ4zenQ0NCQFVA8deoU+vfvD6C8oSUfJfuB8lou0dHR2LJlCzQ1NbFjxw78+OOPMDU15TV/Q19fH19++SVcXFxgamoKPT09uQ8+DB8+HFFRUbw8d01cXV2xZMkSWRNJkUiEvLw8zJ8/X6GNVvmyZMmSdyr6+c033wjS0FGouHVFp5ZUVOVTGNra2lWOPnN5CkMsFiM/Px8fffQRgPLM+KSkJN7rrNy/fx8dO3aEmpoapk+fLuvkfePGDWzatAlSqVR2KoJL7du3x6RJkzBt2jTZKQALCwtMmjQJzZo1q7Vmxvto27YtFi1ahFGjRsmdPPD390dhYSGCgoI4j7ljxw4sXrwYa9asgaenJ3bs2IHs7GysWLECO3bsqLG3Vl25urri1atX6N69O5YuXYqcnBw0b94cUVFRmD59Oi9F8czNzbFv3z706tULjRs3RlJSEqysrBAcHIyQkBCEh4dzHlMoK1aswNq1a/H555/Dzs6uymsDH7Vrnjx5gmHDhuHSpUt4+vQpTE1Nce/ePXz66af466+/qqxE1Tdqamq4d++e7DVQ0d7U0bxhw4YwNzfnpKO5UGgio6L27t37xvtjx47lLJaamppsiZgxBjMzM8TFxaFly5Zyj+PjnUBubi6mTJmCyMhI2VaaSCSCi4sLNm3a9NY1O96Fjo4O0tLS0LJlSzRt2hSxsbGws7NDeno6+vTpw2lp9wra2tpIT0+HRCLBRx99hJMnT8Le3h6ZmZno2rVrtdshXNi/fz8WL16M7OxsAOXbeYsXL4anpycv8QAgLy8PU6dOxZ07dzBjxgxZLG9vb0il0hoLytWFrq4url+/DnNzc7Ro0QJHjhxBly5dkJOTAzs7OxQVFXEeUyhv+j/BZ+0aoLzKd0pKCoqKitCpUyfOWogI7fU3c0LEf9OJSXV1dXz11Vf45Zdf0LBhQwWOjBuUI6OiuJyo1Ib9/5oxlT+vnFvBeKoEC5QXZQsPD8ejR4+QlZUFxhisra3RpEmTKo/9559/YGpqWm3F2nfRpEkTPH36FMD/5enY2dnh8ePHvPWUMjExQWFhISQSCczNzXHx4kXY29sjJyeHt1yo58+fw83NDV9//TWKi4tx7do1xMfH17kSdG3Mzc1x4sSJKtd//vln3mJaWloiJycH5ubmaNu2LQ4fPowuXbrg+PHj0NfX5y0uIEzuk6JcuHABBQUFsi3ezz77DNnZ2QgMDERxcTGGDh2KjRs31uvVggpCNmk8evToW3U0X7hwISeNQBVOmBxjIoTKpyteP3XB5ymM2NjYt/oQWqNGjTjJ2B81ahRbs2YNY4yxJUuWMCMjIzZhwgQmkUiYm5tbnZ+/Op6enmzx4sWMsfLjyFpaWqxv375MX1+fjR8/npeY/fr1Y1u2bGGMMfbo0SNmbGzMWrRowRo2bMg2b97MS8wKWVlZ7IcffmAjR45k9+/fZ4wxFh4ezq5du8ZLvLVr17L169czxhg7efIka9iwIdPU1GRisZitW7eOl5iMMbZ+/Xqmq6vLpk+fzjQ0NNikSZNY3759mZ6eHluwYAFvcRVlwIABciekUlJSmLq6OpswYQJbs2YNMzExYYsWLRJugBwRiURMX1+fNWnS5I0ffOncuTOLiIiocj0iIoJ17tyZMcbY0aNHmaWlJW9j4BNtLamQyvu0NS01Mh5WR942AVPoJDOuqloWFhbixYsXMDU1RVlZGQIDA2W9lxYuXFjtalBdlZWVoaysDA0alC+yHjx4UBZz0qRJvFRONjQ0lDUW3bFjBzZu3Ijk5GSEhYXB398f6enpnMcEypuZDhw4EN27d8fZs2eRnp4OS0tLrFy5EpcuXUJoaCgvcSvLzc3F5cuXYWVlxXlzzMoUlfvk4+ODpUuXQkdHBz4+Pm98LFeVqQGgWbNmOH78OBwdHQGUd8E+c+YM4uLiAAC//fYbFi1ahOvXr3MWUwhisRjr1q2rNUGbr5VyLS0tJCcny9rDVLhx4wYcHBzw/Plz3L59GzY2NrytGvOJtpZUSHR0NAwMDACAl340NdHX13+rZdX63oG1QsW/MVD+Aubr68t7TLFYLLclNnLkSN6SbSsUFxfLeu9ERUXB3d0dYrEYXbt2rbUPU134+vpi2bJl8PHxkev906dPH16SmqsjkUg47yVVnby8PHTr1g1A+S+jii1LDw8PdO3albOvNzk5WXZiKDk5mZPnfBuPHj2SS7avmKRW6Ny5M+7cuaOw8fBp5MiRguXICNHRXJFoIqNCevbsKfuzhYUFzMzMqkwwGGOcv3BUnjQxxjBo0CDs2LFD6funPHjwoNoS71y9g09JSYGtrS3EYnGNpxK4jlmZlZUVjh07Bjc3N0RGRsLb2xtA+dfN5+paamoqDhw4UOX6Rx99hIcPH/IWNzExscay/VyuUlSmqNynyv9HFfkmx9jYGDk5OTAzM8OrV6+QlJQkd6rv6dOnStNMVkibNm2Cq6srWrRoUW1HcwC4desWpk6dKuQw3xtNZFSUhYVFtccBCwsLYWFhwenqSOUJFFC+xdW1a9d615jsbV2+fBljx45Fenp6lV82XG7bdejQQXYSokOHDhCJRNX+cuMrkdrf3x+jR4+Gt7c3nJ2d8emnnwIoX52prlAeV/T19XHv3r0qp2uSk5N5mxwHBARg4cKFaNOmDYyNjeXeAPCZxNmnTx/88ccfcHBwwLhx4+Dt7Y3Q0FBcunTpnZqGvovx48dj/fr1VTpdP3v2DF5eXti1axdnsQYNGgRfX1+sWrUKx44dg7a2tlzvs5SUFLRq1YqzeEISMtm3W7duyMnJketoPnz4cLmO5h4eHoKNr64oR0ZFicVi3L9/v0rVzNzcXNjY2PBamfVD7bDKVQt7e3t7tGrVCvPnz6/ySw8AZ1sSubm5MDc3h0gkqnUrh69tkPz8fNy7dw/29vayra2EhAQ0bty4yn48V+bMmYO///4bv/32G1q3bo2kpCTcv38fY8aMwZgxY7Bo0SLOYxobG2PVqlX49ttvOX/uN3k99+nQoUOIj4+HtbU1Jk+ezMtqRU01Tx4+fAgTExOUlpZyFuvhw4dwd3dHXFwcdHV1sXfvXri5ucnuOzs7o2vXrli+fDlnMYXg5ub2VhMZ6lL/fmhFRsVUJPKJRCL4+flBW1tbdk8qleLvv/9Ghw4dBBqdsLia09+6dQthYWE1tkbgSuXJiSLyNapjYmICExMTuWsVxzv5EhAQgGnTpsHMzAxSqRQ2NjaQSqUYPXo0Fi5cyEtMsViM7t278/LctcWt2HJ58OABtLS00LdvXwDlFZSHDBnCWaz//vsPrLz/Hp4+fSpXT0QqlSI8PJzzHA9DQ0OcPXsWT548ga6uLtTU1OTu//bbb9DV1eU0phD4PqL/NhTd0VyRaEVGxfTu3RtAeVLdp59+KneaRUNDAy1btsScOXN4rbrbqFEjpKSk8FKM7l2FhoZi2LBhAIA7d+7A1NS0yovpuxo6dCg8PDwUWlp9xYoVMDY2xvjx4+Wu79q1C//73/8wf/58hY1FUfLy8nDt2jUUFRXBwcGB15/ZwMBA3L17F+vWreMtRnUiIiLg4eFRbUFDrrcMayuaJhKJ8OOPP+KHH37gLCZRjO3bt2PKlCkwNDSEiYlJla1RPuoRKRJNZFTUuHHjsH79eoUceX59L//48ePo06ePQhrglZaW4saNG9DQ0JAryvf777/D398fN27cwMuXLzmN+fDhQ4wdOxZdunSBra1tleV/V1dXTuMBQMuWLXHgwAHZCZcKf//9N0aOHKnQImfKqKysDJ9//jkyMjJgY2NT5XvK15aAtbU1+vfvD39/f95PlJw5cwaMMfTp0wdhYWFyp+80NDQgkUhgamrK6xgIPyQSCaZOnaqUb2gA2lpSWbt37wYAZGVlITs7Gz169ICWlpasjgyXXq+d8M0333D6/DW5du0aBg8eLDuF9cUXX2DLli0YMWIErl27hokTJ+LPP//kPO6FCxcQHx+Pv/76q8o9vhJv8/Pzq+3kbWRkxEtLBEUTqs5JhRkzZiAmJga9e/dG06ZNFZa4ef/+ffj4+CjkWGxFUn5FBWMhk1MJt4ToaK5INJFRUYWFhRg+fDhiYmIgEomQmZkJS0tLeHp6okmTJlizZg1nsSomTYo2f/58WFlZISgoCCEhIQgJCUF6ejo8PT0RERHBW+dtLy8vfPPNN/Dz81NYXQYzMzPEx8dX2a6Lj49XinfRleucJCUl1fhLlq9fvnv37kVYWBg+//xzXp6/JsOGDUNsbKxCT+5IJBKcO3cOv/zyC27duoXffvsNzZs3R3BwMCwsLPDZZ58pbCyEGxUdzSdPniz0UHhBExkVNWvWLKirqyMvLw/t2rWTXf/qq6/g4+PD6URGKImJiYiKikKHDh3g5OSEkJAQLFiwgPdjhgUFBfD29lZocamJEydi1qxZKCkpQZ8+fQAAp0+fxrx58zB79myFjYMvlWubxMbGKjy+gYGBIMeAg4KCMHz4cJw7d05hnajDwsLg4eGBr7/+GklJSbKt1ydPniAgIECpOn2rCisrK/j5+eHixYsK+zlSJMqRUVEmJiaIjIyEvb293HHoW7duoX379krRzff1jrONGjVCUlISr0mhQHmZcScnJ0yYMIHXOJUxxuDr64sNGzbIGgs2bNgQ8+fPr/cnEiorKSmBlpYWrly5AltbW4XF3b17NyIiIrB79265k35827lzJyZPnoyGDRtW2dLiqxO1g4MDvL29MWbMGLnXhuTkZAwcOBD5+fmcxyT8ErKjuSLQioyKevbsWbUvyIWFhUrRaRYo/w9acYy0Ivfn+fPnVXo/cZ3w3Lp1a3z//feIi4tT2LsfkUiEVatWwc/PD+np6dDS0oK1tbXSfC8rqKurw9zcXOHtLDZs2IDs7GwYGxujZcuWVb6nfJ36+OGHH/Djjz/C19e3zl3Z39bNmzfRo0ePKtf19PTw+PFjhYyBcEvZk/1pIqOinJycsG/fPixduhRA+S/CigaHFUe06zvGmNxJJcaYXMVZPhpkAsCOHTugq6uLM2fO4MyZM3L3RCIRr8u4urq66Ny5M2/P/yH44YcfsGDBAgQHB8udrOHT0KFDFRLnda9evcJXX32lsEkMUL5am5WVhZYtW8pdj4uL++CKWBIC0NaSyrp27RqcnZ3RsWNHREdHw9XVFWlpaSgsLER8fLxSlAV/fRJRk9dbKNRHz549w8qVK3H69OlqC17V96XjyhwcHJCVlYWSkhJIJJIqx/iFrIkREhICV1fXKmN6X97e3jAyMsKCBQs4eb63sWLFCvz666/YtWsX+vXrh/DwcOTm5sLb2xt+fn7w8vJS2FjI+xP6pJ8i0YqMirK1tUVGRgaCgoLQqFEjFBUVwd3dHdOmTav2GG99xGe/Hy5w1RIBACZMmIAzZ87Aw8MDzZo1U+qjs0KtjryNSZMm4ZNPPuFs5UIqlSIwMBCRkZFo3759lS0tPn4B+fr6oqysDM7OziguLkaPHj2gqamJOXPm0CSmHhGqo7kQaEVGRVXUxKjOpk2bMG3aNAWPiHu1VSqtoOh8iwpc9pzS19fHn3/+KUgZffJ/uO4j9qZtXpFIhOjoaE7iVFZSUgJ1dXW8evUKWVlZKCoqgo2NDXR1dfHw4UMYGhpyHpOQuqAVGRXl7u6OU6dOoVOnTnLX169fDz8/P6WYyFQ+sssYw6BBg7Bjxw7eOiQLqUmTJgrLF/kQPH78GKGhocjOzsbcuXNhYGCApKQkGBsbK9X3t/LPsKKMHDkSoaGh0NDQgI2Njez6/fv34ezsjGvXril8TKRuFNnRXBCMqKTt27czIyMjlp6eLru2evVq1rhxY3b27FkBR8YfXV1dlp2dLfQwZLgcT3BwMBs2bBh79uwZJ8/3Ibt69SozMjJiVlZWrEGDBrJ/wx9++IF5eHgIOrYP7WfsfTg6OrLx48fLXbt79y5r27Yt+/LLLwUaFakLsVjM7t+/X+X6//73P6ampibAiLhFKzIqasKECSgsLETfvn0RFxeHQ4cOyYpd0fZE/bNmzRpBjgcLwcfHB99++y0CAwPl3mEOGjQIo0ePFnBkyiE8PBw9evSAj48P1q5di7t376J3796wt7fHwYMHhR4eeQdCdDQXAk1kVNi8efNQUFAAR0dHSKVSREZGomvXrkIPS2VwmZD7ISfAci0xMRG//PJLlevNmzenYm0cMDIyQlRUlKwVwYkTJ9CxY0fs379focfASd3p6+tDJBJBJBLJlaKoUNHRvL6jiYwK2bBhQ5VrzZs3h7a2Nnr06IGEhAQkJCQAqP8lq2vyIZ3mYRzm2S9atIiz5/rQaWpqVilqCAAZGRkwMjISYET/RyKRVFkNq4/MzMxw8uRJODk5oV+/fggODv6g/u+QtxMTE6MSHc3p1JIKeVOZ6sqUoWQ1UJ7QXNnx48fRp0+fKjU+jhw5wus4pFIpUlNTIZFI0KRJE9n1uLg4dO7cWemq7/JtwoQJKCgowOHDh2FgYICUlBSoqalh6NCh6NGjB9atW8d5zDt37kAkEqFFixYAgISEBBw4cAA2Njb47rvvOI+naE2aNKl2olJcXAxNTU2oqanJrhUWFipyaIQDubm5St3RnCYyRGmNGzfurR7HdXfuWbNmwc7ODp6enpBKpejZsyfOnz8PbW1tnDhxAr169eI0HlA+Wfr5559x+PBh5OXlyfotVVCmXz5PnjzBsGHDcOnSJTx9+hSmpqa4d+8ePv30U/z111+cFaOrzMnJCd999x08PDyQn5+PNm3a4OOPP0ZmZia8vLzqfT+rvXv3vvVjx44dy+NICF+UuqO5cHnGRCivXr1ilpaW7Pr160IPRSk1b96cJSYmMsYYO3r0KDM1NWU3b95kCxcuZN26deMlpp+fH2vWrBlbvXo1a9iwIVu6dCnz9PRkTZs2ZevXr+clptDOnTvHNm3axFatWsVOnTrFayx9fX1248YNxhhj69evl30fIyMjmYWFBa+xFamkpITt3buX5efnCz0UwqHQ0FCmpaXFJkyYwDQ1NWUn6zZu3MgGDhwo8OjqjjK3VJC6ujpevHgh9DCU1sOHD2FiYgKg/ATI8OHD0bp1a4wfPx6pqam8xNy/fz+2b9+O2bNno0GDBhg1ahR27NgBf39/XLx4kZeYinbhwgWcOHFC9vlnn30GHR0dbN68GaNGjcJ3332Hly9f8hK7pKREtgV46tQpuLq6AgDatm2Le/fu8RJTCA0aNMDkyZPp9UHJLFu2DFu3bsX27dvlcri6d++uFCcaaSKjoqZNm4ZVq1ahtLRU6KEoHWNjY1y/fh1SqRQRERHo168fgPJ8g8q5BlzKz8+HnZ0dgPLGkU+ePAEADB48GH/++ScvMRVtyZIlSEtLk32empqKiRMnol+/fvD19cXx48exYsUKXmJ//PHH2Lp1K86dO4eTJ09iwIABAIC7d++iadOmvMQUSpcuXZS+pL2qUfaO5nRqSUUlJibi9OnTiIqKgp2dncITYJXZuHHjMGLECFnPo759+wIA/v77b7Rt25aXmC1atMC9e/dgbm6OVq1aISoqCh07dkRiYqLSJBNfuXJF1q0dAA4ePIguXbpg+/btAMpP2ixatAiLFy/mPPaqVavg5uaGn376CWPHjoW9vT0A4I8//kCXLl04jyekqVOnYvbs2fjnn3/QqVOnKq8N7du3F2hk5H0pe0dzmsioKH19fXz55ZdCD0MpLV68GLa2trhz5w6GDx8um0ioqanB19eXl5hubm44ffo0PvnkE3h5eeGbb77Bzp07kZeXB29vb15iKtqjR49gbGws+/zMmTMYOHCg7PPOnTvjzp07vMTu1asXHj58iP/++0/u5Nl3330HbW1tXmIKZeTIkQDkSzCIRCIwxiASiQTrTUbe38SJEzFz5kzs2rULIpEId+/exYULFzBnzhz4+fkJPbw6o1NLhPDoxYsXctU0FeXChQu4cOECrK2tMWTIEIXH54NEIkFwcDB69OiBV69eQV9fH8ePH4ezszOA8q2mnj178nZCq7S0FLGxscjOzsbo0aPRqFEj3L17F40bN4auri4vMYWQm5v7xvsSiURBIyFcYYwhICAAK1asQHFxMQDIOppXXuWsr2giQwjHpFIpAgICsHXrVty/fx8ZGRmwtLSEn58fWrZsCU9PT6GHWC9NmTIFV69exapVq3Ds2DHs3bsXd+/ehYaGBoDyhOd169YhMTGR89i5ubkYMGAA8vLy8PLlS9n3dObMmXj58iW2bt3KeUxCuKLsHc1pa0mFhYaG1lh3RBky2YWyfPly7N27F4GBgZg4caLsuq2tLdatW8fbRCYzMxMxMTF48OABysrK5O7V9zonALB06VK4u7ujZ8+e0NXVxd69e2WTGADYtWsX+vfvz0vsmTNnwtHREVevXpVL7nVzc5P7HiuT69evV/vaUHFii9QfSt/RXMiz30Q469evZ7q6umz69OlMQ0ODTZo0ifXt25fp6emxBQsWCD28eq1Vq1ayuiaVuyGnp6czfX19XmJu27aNqampMWNjY2Zvb886dOgg+3BwcOAlplAeP37MSktLq1wvKChgL1++5CWmgYGBrI5M5e9pTk4O09LS4iWmULKzs1n79u2ZSCRiYrGYiUQi2Z/FYrHQwyPvQdk7mtPxaxW1efNmbNu2DRs3boSGhgbmzZuHkydPYsaMGbKju+T9/Pvvv7CysqpyvaysDCUlJbzEXLZsGZYvX478/HxcuXIFycnJsg9lW13T09Or9hi7gYGB3AoNl8rKyqpNcv3nn3/kOnArg5kzZ8LCwgIPHjyAtrY20tLScPbsWTg6OiI2Nlbo4ZH3EB4ejvPnz8PHxwdAedmAXr16wc7ODocPHxZ4dHVHExkVlZeXh27dugEAtLS08PTpUwCAh4cHQkJChBxavWdjY4Nz585VuR4aGgoHBwdeYj569AjDhw/n5bkJ0L9/f7keTiKRCEVFRVi0aBEGDRok3MB4cOHCBSxZsgSGhoYQi8UQi8X47LPPsGLFCqVtJqvsKjqah4WFwcfHB7169YKDgwNCQkKUoqM55cioKBMTExQWFkIikcDc3BwXL16Evb09cnJyOO3KrIr8/f0xduxY/PvvvygrK8ORI0dw8+ZN7Nu3T64yLZeGDx+OqKgoTJ48mZfnV3Vr1qyBi4sLbGxs8OLFC4wePRqZmZkwNDRUuom/VCqVrTIZGhri7t27aNOmDSQSCW7evCnw6Mj7UuaO5jSRUVF9+vTBH3/8AQcHB4wbNw7e3t4IDQ3FpUuXqnSNJu/miy++wPHjx7FkyRLo6OjA398fHTt2xPHjx2VVfrlmZWUFPz8/XLx4EXZ2dnJlyAHQO+k6atGiBa5evYqDBw8iJSUFRUVF8PT0xNdffw0tLS2hh8cpW1tbXL16FRYWFvjkk08QGBgIDQ0NbNu2TSmKp6mKN3U0P378uFzSen1vKkvHr1VUWVkZysrK0KBB+Vz20KFDiI+Ph7W1NSZPnlzlFyH5sFlYWNR4TyQS4datWwocDanPIiMj8ezZM7i7uyMzMxNDhgxBRkYGmjZtioMHD8rq9pAPmyp1NKeJjAp78eIFUlJSqhzXFYlESlNEjZD39ccff2DgwIFQV1fHH3/88cbHKvuR5MLCwhrf4ZMPW2lpKQ4cOAAXFxe5ytjKhCYyKioiIgIeHh4oKCioco/KkL87AwMDZGRkwNDQsNYX/Pq+jKsqxGIx8vPz8dFHH70xIVJZ/r+MHz/+rR63a9cunkdCuKatrY309HSlrcpMOTIqysvLCyNGjIC/v7/SztIV6eeff5YlSFY+3cInHx8fLF26FDo6OrJjlTVZu3atQsakTCqvUr5eYFAZ7dmzBxKJBA4ODpTwr2QqOpor60SGVmRUVOPGjZGcnIxWrVoJPRSloshl3MqrQL17967xcSKRCNHR0byORZmVlJRgwIAB2Lp1K6ytrYUeDm+mTZuGkJAQSCQSjBs3Dt988w0MDAyEHhbhwOHDh/H999/D29tbKTua00RGRY0fPx7du3envj88UNQybuWtD0tLSyQmJsqdRCDcMTIywvnz55V6IgMAL1++xJEjR7Br1y6cP38en3/+OTw9PdG/f3/Kj6nHqtsaVaaO5jSRUVHFxcUYPnw4jIyM6Lgux3r16oVZs2Zh6NChvMZp2rQpwsPD8cknn0AsFuP+/fswMjLiNaaq8vb2hqamJlauXCn0UBQmNzcXe/bswb59+1BaWoq0tDSl6vKtSpS9oznlyKiokJAQREVFoWHDhoiNjZV7tyUSiWgiUwdTp07F7Nmz8c8///C6jPvll1+iZ8+eaNasGUQiERwdHast3Q+Ajl/XUWlpKXbt2oVTp05V+z1VxhwksVgse9de39+xq7r6PlGpDa3IqCgTExPMmDEDvr6+SlGi+kOiyGXciIgIZGVlYcaMGViyZEmNfX9mzpzJWUxVpCo5SJW3luLi4jB48GCMGzcOAwYMoNcJJaCsHc1pIqOiDAwMkJiYSMm+PBBiGXfcuHHYsGGD0jUwJIozdepUHDx4EGZmZhg/fjy+/vprGBoaCj0swoFbt27Bzc0NqampsjdVAGQr8fV9xY0mMirK29sbRkZGWLBggdBDIaTeyMrKQnZ2Nnr06AEtLS3ZKpsyEIvFMDc3h4ODwxu/piNHjihwVIQLQ4YMgZqaGnbs2AELCwskJCSgoKAAs2fPxurVq+Hk5CT0EOuEcmRUlFQqRWBgICIjI9G+ffsqyb7KuOevSMHBwdi6dStycnJw4cIFSCQSrFu3DhYWFvjiiy+EHh55RwUFBRgxYgRiYmIgEomQmZkJS0tLeHp6okmTJlizZo3QQ6yzMWPGKM2kjMi7cOECoqOja+xonpycLPQQ64QmMioqNTUVDg4OAIBr167J3aMXs7rZsmUL/P39MWvWLCxfvly2bKuvr49169bRRKYe8vb2hrq6OvLy8tCuXTvZ9a+++go+Pj5KMZHZs2eP0EMgPFH2juY0kVFRMTExQg9BaW3cuBHbt2/H0KFD5Y7rOjo6Ys6cOQKOjLyvqKgoREZGokWLFnLXra2ta82JIkRoyt7RnCYyhHAsJydHttpVmaamJp49eybAiEhdPXv2DNra2lWuFxYWQlNTU4AREfL2Fi5cKHvt+fHHHzFkyBA4OTnJOprXd3SejhCOWVhY4MqVK1WuR0REyG1LkPrDyckJ+/btk30uEolQVlaGwMDANx7NJuRD4OLiAnd3dwDlq4g3btzAw4cP8eDBAzg7Ows8urqjFRlCOObj44Np06bhxYsXYIwhISEBISEhWLFiBXbs2CH08Mh7CAwMhLOzMy5duoRXr15h3rx5SEtLQ2FhIeLj44UeHiHVUpWO5nT8mhAe7N+/H4sXL0Z2djYAoHnz5li8eDH1tqrHnjx5gqCgIFy9ehVFRUXo2LEjpk2bhmbNmgk9NEKqJRaL36qj+dGjRxU4Ku7RRIYQjj1//hyMMWhra6O4uBjXrl1DfHw8bGxs4OLiIvTwCCEqQlU6mlOODCEc++KLL2T5FK9evYKrqyvWrl2LoUOHYsuWLQKPjryPiIgIxMXFyT7ftGkTOnTogNGjR+PRo0cCjoyQmm3atAn37t3DvHnzcPz4cZiZmWHEiBGIjIx84wpNfUMTGUI4lpSUJKuUGRoaCmNjY+Tm5mLfvn3YsGGDwKMj72Pu3Ln477//AJTXYPLx8cGgQYOQk5MDHx8fgUdHSM00NTUxatQonDx5EtevX8fHH3+MqVOnomXLligqKhJ6eJygZF9COFZcXCwrPhUVFQV3d3eIxWJ07dqVao7UUzk5ObCxsQEAhIWFYciQIQgICEBSUhIGDRok8OgIeTvK2tGcVmQI4ZiVlRWOHTuGO3fuIDIyEv379wcAPHjwAI0bNxZ4dOR9aGhooLi4GABw6tQp2ffUwMBAtlJDyIfo5cuXCAkJQb9+/dC6dWukpqYiKCgIeXl50NXVFXp4nKAVGUI45u/vj9GjR8Pb2xvOzs749NNPAZSvzlRXKI98+D777DP4+Pige/fuSEhIwKFDhwAAGRkZVar9EvKheL2jeUhIiFJ2NKdTS4TwID8/H/fu3YO9vT3E4vKFz4SEBDRu3Bht27YVeHTkXeXl5WHq1Km4c+cOZsyYITtG7+3tDalUSrlP5IOkKh3NaSJDCCEcWblyJSZPngx9fX2hh0IIvv3227dqArx7924FjIY/NJEhhBCONG7cGFeuXFGKRnyE1BeU7EsIIRyh94WEKB5NZAghhBBSb9FEhhBCCCH1Fk1kCCGEEFJv0USGEEIIIfUWTWQIIYQjTk5O0NLSEnoYhKgUOn5NCCHVeJfWA9R6ghDh0ESGEEKqUdFg700YYxCJRErVgI+Q+oZ6LRFCSDViYmKEHgIh5C3QigwhhBBC6i1akSGEkGqkpKTA1tYWYrEYKSkpb3xs+/btFTQqQsjraEWGEEKqIRaLkZ+fj48++kiWL1PdyyXlyBAiLFqRIYSQauTk5MDIyEj2Z0LIh4lWZAghhBBSb9GKDCGEvKXr168jLy8Pr169krvu6uoq0IgIITSRIYSQWty6dQtubm5ITU2Vy5WpqDNDOTKECIdaFBBCSC1mzpwJCwsLPHjwANra2khLS8PZs2fh6OiI2NhYoYdHiEqjHBlCCKmFoaEhoqOj0b59e+jp6SEhIQFt2rRBdHQ0Zs+ejeTkZKGHSIjKohUZQgiphVQqRaNGjQCUT2ru3r0LAJBIJLh586aQQyNE5VGODCGE1MLW1hZXr16FhYUFPvnkEwQGBkJDQwPbtm2DpaWl0MMjRKXR1hIhhNQiMjISz549g7u7O7KysjB48GBkZGSgadOmOHToEPr06SP0EAlRWTSRIYSQ91BYWIgmTZrU2iGbEMIvmsgQQgghpN6iHBlCCKnFixcvsHHjRsTExODBgwcoKyuTu5+UlCTQyAghNJEhhJBaeHp6IioqCsOGDUOXLl1oO4mQDwhtLRFCSC309PQQHh6O7t27Cz0UQshrqI4MIYTUonnz5rI6MoSQDwtNZAghpBZr1qzB/PnzkZubK/RQCCGvoRwZQgiphaOjI168eAFLS0toa2tDXV1d7n5hYaFAIyOE0ESGEEJqMWrUKPz7778ICAiAsbExJfsS8gGhZF9CCKmFtrY2Lly4AHt7e6GHQgh5DeXIEEJILdq2bYvnz58LPQxCSDVoIkMIIbVYuXIlZs+ejdjYWBQUFOC///6T+yCECIe2lgghpBZi8f+956ucH8MYg0gkglQqFWJYhBBQsi8hhNQqJiZG6CEQQmpAW0uEEFKLnj17QiwWY/v27fD19YWVlRV69uyJvLw8qKmpCT08QlQaTWQIIaQWYWFhcHFxgZaWFpKTk/Hy5UsAwJMnTxAQECDw6AhRbTSRIYSQWixbtgxbt27F9u3b5Yrhde/enTpfEyIwmsgQQkgtbt68iR49elS5rqenh8ePHyt+QIQQGZrIEEJILUxMTJCVlVXlelxcHCwtLQUYESGkAk1kCCGkFhMnTsTMmTPx999/QyQS4e7du9i/fz/mzJmDKVOmCD08QlQaHb8mhJBa+Pr6oqysDM7OziguLkaPHj2gqamJOXPmwMvLS+jhEaLSqCAeIYS8pVevXiErKwtFRUWwsbGBrq6u0EMiROXRRIYQQggh9RblyBBCCCGk3qKJDCGEEELqLZrIEEIIIaTeookMIYQQQuotmsgQQgiA2NhYiEQiqtRLSD1DExlCyDvLz8+Hl5cXLC0toampCTMzMwwZMgSnT59+q7+/Z88e6Ovr8zvId9StWzfcu3cPenp6Qg+FEPIOqCAeIeSd3L59G927d4e+vj5++ukn2NnZoaSkBJGRkZg2bRpu3Lgh9BDfWUlJCTQ0NGBiYiL0UAgh74hWZAgh72Tq1KkQiURISEjAl19+idatW+Pjjz+Gj48PLl68CABYu3Yt7OzsoKOjAzMzM0ydOhVFRUUAyrdwxo0bhydPnkAkEkEkEmHx4sUAgJcvX2LOnDlo3rw5dHR08MknnyA2NlYu/vbt22FmZgZtbW24ublh7dq1VVZ3tmzZglatWkFDQwNt2rRBcHCw3H2RSIQtW7bA1dUVOjo6WL58ebVbS3FxcXBycoKWlhbMzMwwY8YMPHv2THZ/8+bNsLa2RsOGDWFsbIxhw4Zx849MCHl7jBBC3lJBQQETiUQsICDgjY/7+eefWXR0NMvJyWGnT59mbdq0YVOmTGGMMfby5Uu2bt061rhxY3bv3j1279499vTpU8YYYxMmTGDdunVjZ8+eZVlZWeynn35impqaLCMjgzHGWFxcHBOLxeynn35iN2/eZJs2bWIGBgZMT09PFvvIkSNMXV2dbdq0id28eZOtWbOGqampsejoaNljALCPPvqI7dq1i2VnZ7Pc3FwWExPDALBHjx4xxhjLyspiOjo67Oeff2YZGRksPj6eOTg4sG+//ZYxxlhiYiJTU1NjBw4cYLdv32ZJSUls/fr1XP1TE0LeEk1kCCFv7e+//2YA2JEjR97p7/3222+sadOmss93794tN/lgjLHc3FympqbG/v33X7nrzs7O7Pvvv2eMMfbVV1+xzz//XO7+119/Lfdc3bp1YxMnTpR7zPDhw9mgQYNknwNgs2bNknvM6xMZT09P9t1338k95ty5c0wsFrPnz5+zsLAw1rhxY/bff//V/g9ACOENbS0RQt4ae8uOJqdOnYKzszOaN2+ORo0awcPDAwUFBSguLq7x76SmpkIqlaJ169bQ1dWVfZw5cwbZ2dkAgJs3b6JLly5yf+/1z9PT09G9e3e5a927d0d6errcNUdHxzd+DVevXsWePXvkxuLi4oKysjLk5OSgX79+kEgksLS0hIeHB/bv3//Gr48Qwg9K9iWEvDVra2uIRKI3JvTevn0bgwcPxpQpU7B8+XIYGBggLi4Onp6eePXqFbS1tav9e0VFRVBTU8Ply5ehpqYmd4+P5ow6OjpvvF9UVIRJkyZhxowZVe6Zm5tDQ0MDSUlJiI2NRVRUFPz9/bF48WIkJiZ+cCeyCFFmtCJDCHlrBgYGcHFxwaZNm+SSXis8fvwYly9fRllZGdasWYOuXbuidevWuHv3rtzjNDQ0IJVK5a45ODhAKpXiwYMHsLKykvuoOE3Upk0bJCYmyv291z9v164d4uPj5a7Fx8fDxsbmnb7Wjh074vr161XGYmVlBQ0NDQBAgwYN0LdvXwQGBiIlJQW3b99GdHT0O8UhhNQNTWQIIe9k06ZNkEql6NKlC8LCwpCZmYn09HRs2LABn376KaysrFBSUoKNGzfi1q1bCA4OxtatW+Weo2XLligqKsLp06fx8OFDFBcXo3Xr1vj6668xZswYHDlyBDk5OUhISMCKFSvw559/AgC8vLwQHh6OtWvXIjMzE7/88gv++usviEQi2XPPnTsXe/bswZYtW5CZmYm1a9fiyJEjmDNnzjt9nfPnz8f58+cxffp0XLlyBZmZmfj9998xffp0AMCJEyewYcMGXLlyBbm5udi3bx/KysrQpk2bOv4LE0LeidBJOoSQ+ufu3bts2rRpTCKRMA0NDda8eXPm6urKYmJiGGOMrV27ljVr1oxpaWkxFxcXtm/fPrlEWsYYmzx5MmvatCkDwBYtWsQYY+zVq1fM39+ftWzZkqmrq7NmzZoxNzc3lpKSIvt727ZtY82bN2daWlps6NChbNmyZczExERufJs3b2aWlpZMXV2dtW7dmu3bt0/uPgB29OhRuWuvJ/syxlhCQgLr168f09XVZTo6Oqx9+/Zs+fLljLHyxN+ePXuyJk2aMC0tLda+fXt26NChuv3DEkLemYixt8zeI4SQD9DEiRNx48YNnDt3TuihEEIEQMm+hJB6ZfXq1ejXrx90dHTw119/Ye/evdi8ebPQwyKECIRWZAgh9cqIESMQGxuLp0+fwtLSEl5eXpg8ebLQwyKECIQmMoQQQgipt+jUEiGEEELqLZrIEEIIIaTeookMIYQQQuotmsgQQgghpN6iiQwhhBBC6i2ayBBCCCGk3qKJDCGEEELqLZrIEEIIIaTe+n/N8XeNS/vYTgAAAABJRU5ErkJggg==\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"### Handling NaN values"
],
"metadata": {
"id": "3wZIz82B4Me3"
}
},
{
"cell_type": "markdown",
"source": [
"#### Percentage of nan values"
],
"metadata": {
"id": "UcjuQaC9w5th"
}
},
{
"cell_type": "code",
"source": [
"df_sorted.isnull().sum() / df_sorted.shape[0] * 100"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mw4oEvxVwNOi",
"outputId": "b9bab565-a985-4bcb-c717-d2aa28f5593e"
},
"execution_count": 366,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"subject 0.00000\n",
"body 0.00000\n",
"opened 0.00000\n",
"meeting link clicked 10.38961\n",
"responded 0.00000\n",
"type1 0.00000\n",
"meeting_link_clicked 89.61039\n",
"dtype: float64"
]
},
"metadata": {},
"execution_count": 366
}
]
},
{
"cell_type": "markdown",
"source": [
"#### Check if meeting link clicked and meeting_link_clicked are complementory"
],
"metadata": {
"id": "sxuRTWmS0M29"
}
},
{
"cell_type": "code",
"source": [
"df_sorted[(df_sorted['meeting link clicked'] == None) | (df_sorted['meeting_link_clicked'] == None)].value_counts()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "XnptJTvss8Ud",
"outputId": "ff09afd2-e260-42fa-cf74-62b708bccf0b"
},
"execution_count": 367,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Series([], dtype: int64)"
]
},
"metadata": {},
"execution_count": 367
}
]
},
{
"cell_type": "markdown",
"source": [
"There are no rows where both columns are None, merging them together"
],
"metadata": {
"id": "-8E8yJUL0ye8"
}
},
{
"cell_type": "code",
"source": [
"df_sorted['merged_meeting_link'] = df_sorted['meeting link clicked'].fillna(False) | df_sorted['meeting_link_clicked'].fillna(False)"
],
"metadata": {
"id": "CIXgd9jA1Il6"
},
"execution_count": 368,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df_sorted.head(10)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 597
},
"id": "JR1xs9iI2TkF",
"outputId": "c21b8cfa-017c-4f05-df4d-094495c60a3e"
},
"execution_count": 369,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" subject \\\n",
"0 🚀 Propel Your Marketing ROI with Advanced Anal... \n",
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},
"metadata": {},
"execution_count": 369
}
]
},
{
"cell_type": "code",
"source": [
"df = df_sorted.drop(['meeting link clicked', 'meeting_link_clicked'], axis=1)"
],
"metadata": {
"id": "mcq-7SE32gEs"
},
"execution_count": 370,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.isnull().sum() / df.shape[0] * 100"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "vqX7PZno2zmY",
"outputId": "2eb39890-3c59-4dd6-b4d2-4840b9d60736"
},
"execution_count": 371,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"subject 0.0\n",
"body 0.0\n",
"opened 0.0\n",
"responded 0.0\n",
"type1 0.0\n",
"merged_meeting_link 0.0\n",
"dtype: float64"
]
},
"metadata": {},
"execution_count": 371
}
]
},
{
"cell_type": "markdown",
"source": [
"### Categorical Column handling"
],
"metadata": {
"id": "p5jyf4ozu7VT"
}
},
{
"cell_type": "markdown",
"source": [
"#### Categorical values"
],
"metadata": {
"id": "_7Ll3OdhxCzQ"
}
},
{
"cell_type": "code",
"source": [
"cat_cols = ['type1','opened', 'responded', 'merged_meeting_link']"
],
"metadata": {
"id": "xs7nQNZS4TOp"
},
"execution_count": 372,
"outputs": []
},
{
"cell_type": "code",
"source": [
"for col in cat_cols:\n",
" print(col, df[col].unique())"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "XRxVaGzpxGT9",
"outputId": "97c1ed13-692b-4143-b242-832e30347c6c"
},
"execution_count": 373,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"type1 ['example1' 'marketingAnalytics0' 'HRConsultingSeries'\n",
" 'marketingAnalyticsSeries' 'MarketingAnalyticsSeries' 'series_legal'\n",
" 'IT_Solutions_Series' 'Marketing_Analytics_Series'\n",
" 'series_marketing_analytics' 'series1' 'HR_Consulting_Series'\n",
" 'financial_advisory_series' 'series_IT_Solutions' 'Series1_HR_Consulting'\n",
" 'Series_IT_Solutions' 'email_series_marketing_analytics'\n",
" 'legal_services0']\n",
"opened [False True]\n",
"responded [False True]\n",
"merged_meeting_link [False True]\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"#### Handling boolean columns"
],
"metadata": {
"id": "XsBkZJQKxcyV"
}
},
{
"cell_type": "code",
"source": [
"bool_cols_dict = {\n",
" True : 1,\n",
" False : 0\n",
"}"
],
"metadata": {
"id": "030FSnO6vrl4"
},
"execution_count": 374,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df[cat_cols[1:]] = df[cat_cols[1:]].replace(bool_cols_dict)"
],
"metadata": {
"id": "E3mpnQm2v7AL"
},
"execution_count": 375,
"outputs": []
},
{
"cell_type": "code",
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"df"
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"height": 589
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"id": "1l9O5hYawBAO",
"outputId": "457b5547-0693-4b04-e12c-af2cca0d986e"
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" <td>Greetings [Recipient's Name],\\n\\nWe haven't co...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>example1</td>\n",
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" <th>152</th>\n",
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" <td>legal_services0</td>\n",
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" <td>Dear [Recipient's Name],\\n\\nIt’s clear that yo...</td>\n",
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" <td>0</td>\n",
" <td>legal_services0</td>\n",
" <td>1</td>\n",
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},
"metadata": {},
"execution_count": 376
}
]
},
{
"cell_type": "markdown",
"source": [
"#### Handling 'type1'"
],
"metadata": {
"id": "G9EasVJ5xgo4"
}
},
{
"cell_type": "code",
"source": [
"type1_dict = dict()\n",
"\n",
"keys = df['type1'].unique()\n",
"for i, key in enumerate(keys):\n",
" type1_dict[key] = i"
],
"metadata": {
"id": "HSdzzAOBwGii"
},
"execution_count": 377,
"outputs": []
},
{
"cell_type": "code",
"source": [
"type1_dict"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZxBU0pleyBSR",
"outputId": "ec5bbfdc-d85d-49e7-9ad2-cdc24ab0a3fc"
},
"execution_count": 378,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'example1': 0,\n",
" 'marketingAnalytics0': 1,\n",
" 'HRConsultingSeries': 2,\n",
" 'marketingAnalyticsSeries': 3,\n",
" 'MarketingAnalyticsSeries': 4,\n",
" 'series_legal': 5,\n",
" 'IT_Solutions_Series': 6,\n",
" 'Marketing_Analytics_Series': 7,\n",
" 'series_marketing_analytics': 8,\n",
" 'series1': 9,\n",
" 'HR_Consulting_Series': 10,\n",
" 'financial_advisory_series': 11,\n",
" 'series_IT_Solutions': 12,\n",
" 'Series1_HR_Consulting': 13,\n",
" 'Series_IT_Solutions': 14,\n",
" 'email_series_marketing_analytics': 15,\n",
" 'legal_services0': 16}"
]
},
"metadata": {},
"execution_count": 378
}
]
},
{
"cell_type": "code",
"source": [
"df[cat_cols[0]] = df[cat_cols[0]].replace(type1_dict)"
],
"metadata": {
"id": "_VckDpIayCpb"
},
"execution_count": 379,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.head(10)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 359
},
"id": "maQX4QjuyJhO",
"outputId": "21147d14-0594-42c4-c9f2-eff8342d8e72"
},
"execution_count": 380,
"outputs": [
{
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" <td>Greetings [Recipient's Name],\\n\\nYour success ...</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>🚀Boost Your ROI with Precision Marketing Analy...</td>\n",
" <td>Hi [Recipient's Name],\\n\\nDo you want to see a...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Your Marketing Strategy Deserves the Best Anal...</td>\n",
" <td>Hello [Recipient's Name],\\n\\nImprove your mark...</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
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"</table>\n",
"</div>\n",
" <div class=\"colab-df-buttons\">\n",
"\n",
" <div class=\"colab-df-container\">\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-84234568-8987-459e-ab0e-ec998fe06ac9')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
"\n",
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" </svg>\n",
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"\n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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" [theme=dark] .colab-df-convert {\n",
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" fill: #D2E3FC;\n",
" }\n",
"\n",
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" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
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"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-84234568-8987-459e-ab0e-ec998fe06ac9 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-84234568-8987-459e-ab0e-ec998fe06ac9');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
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"\n",
"\n",
"<div id=\"df-379c8b62-1868-4640-81fe-b6b44dff32bb\">\n",
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" title=\"Suggest charts\"\n",
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"\n",
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
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" </g>\n",
"</svg>\n",
" </button>\n",
"\n",
"<style>\n",
" .colab-df-quickchart {\n",
" --bg-color: #E8F0FE;\n",
" --fill-color: #1967D2;\n",
" --hover-bg-color: #E2EBFA;\n",
" --hover-fill-color: #174EA6;\n",
" --disabled-fill-color: #AAA;\n",
" --disabled-bg-color: #DDD;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-quickchart {\n",
" --bg-color: #3B4455;\n",
" --fill-color: #D2E3FC;\n",
" --hover-bg-color: #434B5C;\n",
" --hover-fill-color: #FFFFFF;\n",
" --disabled-bg-color: #3B4455;\n",
" --disabled-fill-color: #666;\n",
" }\n",
"\n",
" .colab-df-quickchart {\n",
" background-color: var(--bg-color);\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: var(--fill-color);\n",
" height: 32px;\n",
" padding: 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-quickchart:hover {\n",
" background-color: var(--hover-bg-color);\n",
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: var(--button-hover-fill-color);\n",
" }\n",
"\n",
" .colab-df-quickchart-complete:disabled,\n",
" .colab-df-quickchart-complete:disabled:hover {\n",
" background-color: var(--disabled-bg-color);\n",
" fill: var(--disabled-fill-color);\n",
" box-shadow: none;\n",
" }\n",
"\n",
" .colab-df-spinner {\n",
" border: 2px solid var(--fill-color);\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" animation:\n",
" spin 1s steps(1) infinite;\n",
" }\n",
"\n",
" @keyframes spin {\n",
" 0% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" border-left-color: var(--fill-color);\n",
" }\n",
" 20% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 30% {\n",
" border-color: transparent;\n",
" border-left-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 40% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-top-color: var(--fill-color);\n",
" }\n",
" 60% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" }\n",
" 80% {\n",
" border-color: transparent;\n",
" border-right-color: var(--fill-color);\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" 90% {\n",
" border-color: transparent;\n",
" border-bottom-color: var(--fill-color);\n",
" }\n",
" }\n",
"</style>\n",
"\n",
" <script>\n",
" async function quickchart(key) {\n",
" const quickchartButtonEl =\n",
" document.querySelector('#' + key + ' button');\n",
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
" try {\n",
" const charts = await google.colab.kernel.invokeFunction(\n",
" 'suggestCharts', [key], {});\n",
" } catch (error) {\n",
" console.error('Error during call to suggestCharts:', error);\n",
" }\n",
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
" }\n",
" (() => {\n",
" let quickchartButtonEl =\n",
" document.querySelector('#df-379c8b62-1868-4640-81fe-b6b44dff32bb button');\n",
" quickchartButtonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
" })();\n",
" </script>\n",
"</div>\n",
"\n",
" </div>\n",
" </div>\n"
]
},
"metadata": {},
"execution_count": 380
}
]
},
{
"cell_type": "markdown",
"source": [
"### Checking the correlation between the categorical columns"
],
"metadata": {
"id": "1fTUO_015Ico"
}
},
{
"cell_type": "code",
"source": [
"correlation_matrix = df[cat_cols].corr()\n",
"\n",
"plt.figure(figsize=(8, 6))\n",
"sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', linewidths=1)\n",
"plt.title('Correlation Matrix Heatmap')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 545
},
"id": "-J0aH0fyyQsQ",
"outputId": "59181978-445e-466d-93b9-c79d0bbc109c"
},
"execution_count": 381,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 800x600 with 2 Axes>"
],
"image/png": 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8EBYWhoMHDxY5Ji8nJwft27dH3759ERUVhSVLlqBVq1bo3r37K8dCRHpUZtfFEpXA9evXxfDhw4Wnp6cwMzMTNjY2omXLluKHH37QmOIhNzdXTJ06VVStWlWYmpqKKlWqiAkTJmjUESJ/ipEuXboUOs7TKUa2bt2qNY7z58+L3r17CycnJyGXy4WHh4fo27evOHTokLqOtilG/v33X9G8eXNhYWEhKlWqJMaNG6eeCuLIkSPqehkZGWLAgAHC3t5eAFBPN6JtihEhhDh48KBo2bKlsLCwELa2tqJbt27i6tWrGnWeTjHy6NEjjXJtcWrz7BQjRSlqipEvvvhCuLm5CQsLC9GyZUsRFhamdWqQnTt3Ch8fH2FiYqJxnm3atBF16tTResxn95Oeni48PDxEo0aNRG5urka9zz//XEilUhEWFvbCcwAgPvnkE63rnr5Wz04xIoQQt27dEoMGDRKurq7C1NRUuLu7i65du4pt27aVyutQ1Of4+XNJSUkRQUFBwtnZWVhbW4tOnTqJyMhI4eHhIQIDAwud599//y0++ugj4eDgIKytrcXAgQM1prIhoteDRIgSjGomIqL/rHXr1iEoKAhnzpyBn59fWYdDRC/BMXFERERERohJHBEREZERYhJHREREZISYxBEREQBg8ODBEEJwPBxRCR07dgzdunVDpUqVIJFI8Pvvv790m6NHj6JRo0aQy+Xw9vbGunXrSnxcJnFEREREryAzMxO+vr5YvHhxsepHR0ejS5cuaNeuHSIiIjB27FgMGzYM+/btK9FxeXUqERERkZ5IJBL89ttv6NmzZ5F1xo8fjz179mjcVrJ///5ITU3F3r17i30stsQRERERPUehUCA9PV1j0dfdX8LCwgrdsq9Tp04ICwsr0X54xwYiIiIySntMaxps32e+eR9Tp07VKAsJCdHLHXHi4uLg4uKiUebi4oL09HQ8efIEFhYWxdoPkzgiIiKi50yYMAHBwcEaZXK5vIyi0e61S+IMmVXT66FLbpT68fBvk8owEioNK78uuD9nn8+jyzASKg1bFxTc63XQpNgyjIRKw4bpbmV6fImpxGD7lsvlBkvaXF1dER8fr1EWHx8PW1vbYrfCARwTR0RERFSq/P39cejQIY2yAwcOwN/fv0T7ee1a4oiIiIiKQ2piuJa4ksjIyMDNmzfVz6OjoxEREQFHR0e88cYbmDBhAh48eIANGzYAAD7++GP8+OOPGDduHIYMGYLDhw/j119/xZ49e0p0XLbEEREREb2Cs2fPomHDhmjYsCEAIDg4GA0bNsTkyZMBALGxsbh37566ftWqVbFnzx4cOHAAvr6+mDdvHlatWoVOnTqV6LhsiSMiIiKjJDF9Pdqi2rZtixdNu6vtbgxt27bF+fPnX+m4TOKIiIjIKL0u3all5fVIYYmIiIioRNgSR0REREbJkFOMGAO2xBEREREZIbbEERERkVHimDgiIiIiMjpsiSMiIiKjxDFxRERERGR02BJHRERERqm8j4ljEkdERERGSSIr30kcu1OJiIiIjBBb4oiIiMgoSdkSR0RERETGhi1xREREZJQkUrbEEREREZGRYUscERERGSWJrHy3RZXvsyciIiIyUmyJIyIiIqNU3q9OZRJHRERERokXNhARERGR0WFLHBERERml8t6dypY4IiIiIiPEljgiIiIyShK2xBERERGRsWFLHBERERklibR8t0WV77MnIiIiMlJsiSMiIiKjVN7niWMSR0REREaJU4wQERERkdFhSxwREREZpfLencqWOCIiIiIjxJY4IiIiMkqcYoSIiIiIjA5b4oiIiMgocUycHt26dQtvvfWWPndJRERERFrotSUuIyMDf//9tz53SURERKRVeZ8nrkRJ3Pfff//C9Q8ePHilYIiIiIiKq7x3p5YoiRs7dizc3NxgZmamdX1OTo5egiIiIiKiFytREufh4YFZs2ahb9++WtdHRESgcePGegmMiIiI6EU4xUgJNG7cGOfOnStyvUQigRDilYMiIiIiohcrUUvctGnTkJWVVeR6Hx8fREdHv3JQRERERC/DMXEl4OPj88L1pqam8PDweKWAiIiIiOjldO5MzsvLw8GDB7F8+XI8fvwYAPDw4UNkZGToLTgiIiKiokikEoMtxkCneeLu3r2Ld955B/fu3YNCoUDHjh1hY2ODWbNmQaFQYNmyZfqOk4iIiIieoVNL3GeffQY/Pz+kpKTAwsJCXd6rVy8cOnRIb8ERERERFYUtcTr4559/cOLEiULzxXl6epbbCX8dW/nB64uhsGtUF+aVKuLsu6MQv+vFCa3jm03hM/f/YO1THdkxsbgZuhT3N/ymUcdj5AB4BQ+F3LUC0i9G4srY6Ug7c8mQp0LF1LaxHJ2aWcDOWoqY+Dxs3p+FO7F5RdZvXMsMPdpYwtlOivhkJbYfycLlW7kadVydZHi3nSVqvGECmVSC2EQllu54jOR0laFPh16iU0sbdH/LDvY2Mtx9mIM1O5Jw817Rc2M297VE/wAHVHA0QdyjPPz8RzLOX3uiUaffO/Zo728DK3MpIu8osHJrIuISi/4MUelp39QSnVtZwc5ahpi4XPy0Jx23H+QWWb9JHXO8294GzvYyxCfnYcu+x7h4Q6Fe36udNZrVs4CTnRR5SuDOw1xsPfgYt+8XvU96OU4xogOVSgWlUlmo/P79+7CxsXnloIyRzMoS6RejcHnM1GLVt/CsjCa7liPp6Ckc9+uB6B/Wo97yGXDu2Epdx61PAGrPmYAbMxbjeNNeeHwxEs32rIZZBUdDnQYVk19tM/Rtb4Xdx59g+po03E9QYmx/G9hYav/fWzV3EwzvaY3jEdmYtjoNEddz8Ml7NqhUQaauU8FeivEf2iIuSYm5G9MxdVUq/vg3C7l5nLanrLVoYIXAnk7Yui8V4+c9xN2HOfhmhCtsrbX/hNbwlGPshxVx+FQGxs19iNOXMzFuiAuquJqq6/R4yw4Bb9pixdYkTFj4EAqFChM/doWpiXG0APyXNatrjgEBtvj9SAYmL03Evbg8fBXoCBsr7e+3dxVTjOpjj2PnsjB5aSLCr2Vj7AAHuFcsaCeJS8rDT3+k4esfEzFjVRIepSgxLtARNpblOwmhV6PTp+ftt9/GwoUL1c8lEgkyMjIQEhKCzp076ys2o/Jo3zFcD1mI+J0Hi1Xf46P+eBJ9H9fGzUJG5G3cXbIRcdv3oepng9V1qo4NQszqX3F//Q5kXLuFS6NCoMzKRpXB7xroLKi4OjY1xz8RCpy4qEBsohI//5WJnDygpa9ca/32Tcxx5VYu9p/KRlySEjuPPcG9uDy81dhcXadnW0tcupWL7UeyEBOvxKNUFS7cyMXjLCZxZa1rW1scCnuMo6czcD8+Fyu2JiEnR+CtZtr/09rlTVtERD7BriNpeJCQiy1/peL2fQXeaW1bUKeNLbbvT8XZy1m4F5uLHzc9goOtDE3qWZbWaVER3mlhhaNns/DP+Sd4+CgP63anQZEr0KaRhdb6nfytcOmmAn/+m4mHj/Kw/VAG7sTmomOzgvcy7GI2rtzOwaMUJR4k5GHT3nRYmktRxVWvtzAvd6QyicEWY6BTEjdv3jz8+++/8PHxQXZ2NgYMGKDuSp01a5a+Y/xPsm/eAImHwzTKHh04DofmDQAAElNT2DWqg8RDJwoqCIHEwydg37xhKUZKz5NJAQ83E1y7U9CVJgBci85BNXdTrdt4uZvg6h3NbpMrt3Ph5Z7/Ay4BUL+aGeKT81v05n3mgAmBtmhQQ/v+qPSYyACvynJcvF7QFSoEcPHGE9Tw0J601/A016gPABeiCupXdDKBg60JLl3PVq/Pyha4eVeBmp7a90mlQyYDPCuZ4srtgq5QIYCrtxTwrqL9lpPeVcxw5ZZCo+zSTQW839BeXyYD2vlZIvOJCvfi2J1KutPpvwCVK1fGhQsX8Msvv+DixYvIyMjA0KFDMXDgQI0LHahochdnKOITNcoU8YkwtbOB1FwOUwc7SE1MoEhIeq5OEqxqepVmqPQca0sJZFIJ0jM1W8jSMwVcnbT/783OWorHmarn6qtg97/uOBsrCczlEgT4W+D3v7Ow/XAW6lQzxch3bTBvYzqu3+M4qbJiYyWDTCZB2mPNISRpj5Vwr6g9yba3kRWqn/pYCXtbE/V6AEjNeK5OhlK9jsqGjaUUMpkE6Rma39e0DBXcnLX/ybSzliLtufrpGQXf76ca1JBjVF97mJlKkJqhwuz1ychgS/srMZYLEAxF53ZcExMTfPDBBzptq1AooFBo/q9FLpdDLuf/QKl8kvzvdyjiRg4OnslvnYlJUKKauynaNDTH9Xucf5HI2F2NzsHEJYmwsZSirZ8lRvezx5TlSYX+g0dUXDqPqIyKisLo0aPRvn17tG/fHqNHj0ZkZGSxtg0NDYWdnZ3GEhoaqmsoRkkRnwi5i7NGmdzFGblpj6HKViAnMQWqvDzIKzo9V8cJijjNFjwqXRlZAkqVgK2V5v8Aba0Kt849lZahKjQo2taq4H/vGVkCeUqB2ETNlpm4JCUcbTnwuSw9zlRCqRSwe66FzM5GhtT0whd4Afmtbs/Xt7eRITU9T70eAOytn6tjLVOvo7LxOEsFpVIUumhFW2vbU2laWt1stdTPyRVISFbi1v1crP49DUoV0KYxe69ehUQqNdhiDHSKcvv27ahbty7OnTsHX19f+Pr6Ijw8HPXq1cP27dtfuv2ECROQlpamsUyYMEGXUIxW6skIOL3VXKPMuX0LpJyMAACI3FykhV+B81v+BRUkEji180fqyfOlGCk9T6kC7sbmobZnQVeaBEBtT1PcKmIKgtsPNOsDQO2qprj9IE+9zzuxeXBx1Pyj7uIoQxKnFylTeUrg9n0F6tUouAhFIgHqVbfA9bsKrdtcv5ONejU0/zjXr1FQPyEpDynpeaj7zD4t5BJ4e8gRdUf7Pql0KP83/Ucdr4KeIYkE8PGS42aM9illbsbkwMdLsyepbjX5C6egebpfUyMZQE+vJ52SuHHjxmHChAkICwvD/PnzMX/+fJw4cQJff/01xo0b99Lt5XI5bG1tNRZj70qVWVnC1rcWbH1rAQAsq1aGrW8tmFdxAwDUnBEM37UFF33cXfELLKtWQa3Qr2BV0wseHw+AW58ARC9ap64TvXAtqgztC/cPe8K6lhfqLp4CEysLxKzfUarnRoUdOJ2N1g3M4V9PDlcnGQYGWMHMVIJ/L+b/AR7SzRq92hZcmXboTDbqeJmiY1NzuDpJ0a21BTzdTHD4XMHA9v0ns9HExwytG8hRwUGKdo3NUb+6KY4+U4fKxh9H09G+uQ3aNLGGe0VTDH/PCXIzCY6cyr/l4OgBzhjQxUFdf8+xdDSoZYGubW1RqaIp+nSyR7Uqcuz9J72gzt/peLejPfzqWOINN1OMHlgBKelKnLmUVernR5r2nshEm8aWaNXAApUqmCCwmy3kZhIcC8+/WOWjd+3Qp2PBlcn7wjJRr7oc77SwgpuzDL3aWaNqJVMcOJX/XpqZSvBeBxtUq2wKJzsZPCuZYFhPOzjYyHD6Cr/fr4KT/eogNjYWgwYNKlT+wQcfYM6cOa8clDGya1wX/od+Uj/3mfs1ACBmww5cHDoBcrcKsPhfQgcAT+7cx5nuI+AzbwI8Px2E7PtxuDRiIhIPHFfXid36F8wqOKJGyJj8yX4vXMPprsOQ89zFDlT6zl7LgY1lFnq8aQFbq/zJfhdteYzH/+tOdbSVQoiCrtVbD/KwamcGeraxRK+2lkhIUWLxtsd4+Kig6+z89Rz8/FcmAlpYoH9HK8QnK7F0+2PcvM+LGsraiYhM2FpL0e8dB9jbynDngQIzl8eru8ucHUzwzNuN63cUWPRTAt7v7IABXRwR+ygXs9fEI+aZKxF3Hk6DuZkEI/o6wdJCishoBWYuj+O8gK+BU5ezYWOVjt7trWFnLcO92FzM2ZCM9P+NXXOyk0E800B+MyYXS7em4r0ONujT0QbxSXlYuCkFDxLyv7tCCFSqYIJWDR1gYylFRpYK0Q9yMXN1kroO6cZYki1DkYhn/9IUU+fOndGnTx8EBQVplK9duxa//PIL9u3bp3NAe0xr6rwtGYcuuVHqx8O/ZUL6X7fy64JxnX0+jy7DSKg0bF1QVf140KTYMoyESsOG6W4vr2RAdz/qabB9e6z43WD71hedWuK6d++O8ePH49y5c2jePH9c18mTJ7F161ZMnToVu3bt0qhLREREpG/GcgGCoeiUxI0aNQoAsGTJEixZskTrOiD/Tg7abs9FRERERK9GpyROpeLVckRERFS2yvuYOJ3aIW/fvq3vOIiIiIioBHRK4ry9vdGuXTv8/PPPyM7m5dFERERU+jjZrw7Cw8NRv359BAcHw9XVFSNGjMDp06f1HRsRERERFUGnJK5BgwZYtGgRHj58iDVr1iA2NhatWrVC3bp1MX/+fDx69EjfcRIRERFpkkgMtxiBV2ovNDExQe/evbF161bMmjULN2/exJdffokqVapg0KBBiI3lHEFEREREhvBKSdzZs2cxatQouLm5Yf78+fjyyy9x69YtHDhwAA8fPkSPHj30FScRERGRBt52Swfz58/H2rVrERUVhc6dO2PDhg3o3LkzpP8bCFi1alWsW7cOnp6e+oyViIiISM1YLkAwFJ2SuPHjx2PatGkYPHgw3Nw0b7lx7949vPHGG6hYsSJWr16tlyCJiIiISJNOSZxSqcTQoUNRsWJFjfKkpCRUrVoVSqUSZmZmCAwM1EuQRERERM8zlm5PQ9G5HVKi5cqNjIwMmJubv1JARERERPRyJWqJCw4OBpCfwE2aNAmWlpbqdUqlEqdOnUKDBg30GiARERGRNhwTVwLnz58HAAghcOnSJZiZmanXmZmZwdfXF19++aV+IyQiIiKiQkqUxB05cgQAEBQUhEWLFsHW1tYgQRERERG9THkfE6fThQ1r167VdxxEREREVAI6JXFEREREZa28t8SV7xGBREREZLykUsMtOli8eDE8PT1hbm6OZs2a4fTp0y+sv3DhQtSsWRMWFhaoUqUKPv/8c2RnZxf/9HWKkoiIiIjUtmzZguDgYISEhCA8PBy+vr7o1KkTEhIStNbftGkT/u///g8hISG4du0aVq9ejS1btuDrr78u9jGZxBEREZFRkkgkBltKav78+Rg+fDiCgoLg4+ODZcuWwdLSEmvWrNFa/8SJE2jZsiUGDBgAT09PvP3223j//fdf2nr3LCZxRERERM9RKBRIT0/XWBQKhda6OTk5OHfuHDp06KAuk0ql6NChA8LCwrRu06JFC5w7d06dtN2+fRt//vknOnfuXOwYmcQRERGRUZJIpQZbQkNDYWdnp7GEhoZqjSMxMRFKpRIuLi4a5S4uLoiLi9O6zYABAzBt2jS0atUKpqamqFatGtq2bcvuVCIiIqJXMWHCBKSlpWksEyZM0Nv+jx49im+//RZLlixBeHg4duzYgT179mD69OnF3genGCEiIiKjZMgpRuRyOeRyebHqOjs7QyaTIT4+XqM8Pj4erq6uWreZNGkSPvzwQwwbNgwAUK9ePWRmZuKjjz7CN998A2kxrpBlSxwRERHRKzAzM0Pjxo1x6NAhdZlKpcKhQ4fg7++vdZusrKxCiZpMJgOQf3vT4mBLHBERERknHedzM4Tg4GAEBgbCz88PTZs2xcKFC5GZmYmgoCAAwKBBg+Du7q4eV9etWzfMnz8fDRs2RLNmzXDz5k1MmjQJ3bp1UydzL8MkjoiIiIzS63THhn79+uHRo0eYPHky4uLi0KBBA+zdu1d9scO9e/c0Wt4mTpwIiUSCiRMn4sGDB6hQoQK6deuGmTNnFvuYTOKIiIiI9GD06NEYPXq01nVHjx7VeG5iYoKQkBCEhITofDwmcURERGSUJJLXpzu1LJTvsyciIiIyUmyJIyIiIuP0Go2JKwtsiSMiIiIyQmyJIyIiIqMkeY2mGCkL5fvsiYiIiIwUW+KIiIjIKL1O88SVBSZxREREZJw4xQgRERERGRu2xBEREZFRKu/dqWyJIyIiIjJCbIkjIiIi48QpRoiIiIjI2LAljoiIiIySRMIxcURERERkZNgSR0RERMapnI+JYxJHRERERolTjBARERGR0WFLHBERERkn3naLiIiIiIwNW+KIiIjIOHFMHBEREREZG7bEERERkVGSlPMxcRIhhCjrIIiIiIhKKnP5Nwbbt9WImQbbt76wJY6IiIiMUzkfE8ckjoiIiIyShHdseL0M/zaprEMgA1v5tZP68R7TmmUYCZWGLrlR6schG3LLMBIqDVMHmaofn41KKcNIqDT41XQo6xDKtdcuiSMiIiIqFkn57k4t3+2QREREREaKLXFERERknMr5mLjyffZERERERootcURERGScOCaOiIiIiIwNW+KIiIjIKHGeOCIiIiJjVM7vnVq+z56IiIjISLEljoiIiIxTOb93KlviiIiIiIwQW+KIiIjIKEk4Jo6IiIiIjA1b4oiIiMg4cUwcERERERkbtsQRERGRcSrnY+KYxBEREZFx4r1TiYiIiMjYsCWOiIiIjFM5v3dq+T57IiIiIiPFljgiIiIyTuX8wobyffZERERERootcURERGScONkvERERERkbtsQRERGRceKYOCIiIiIyNmyJIyIiIuNUzu/YwCSOiIiIjBMn+yUiIiIiY8OWOCIiIjJO5bw7lS1xREREREaILXFERERknMr5FCPFTuJ69+5d7J3u2LFDp2CIiIiIqHiKncTZ2dmpHwsh8Ntvv8HOzg5+fn4AgHPnziE1NbVEyR4RERGRzsr51anFTuLWrl2rfjx+/Hj07dsXy5Ytg0wmAwAolUqMGjUKtra2+o+SiIiIiDTolMKuWbMGX375pTqBAwCZTIbg4GCsWbNGb8ERERERFUkiMdxiBHRK4vLy8hAZGVmoPDIyEiqV6pWDIiIiInopidRwixHQ6erUoKAgDB06FLdu3ULTpk0BAKdOncJ3332HoKAgvQZIRERERIXplMTNnTsXrq6umDdvHmJjYwEAbm5u+Oqrr/DFF1/oNUAiIiIirYyk29NQdEripFIpxo0bh3HjxiE9PR0AeEEDERERUSnSudM3Ly8PBw8exObNmyH5Xyb88OFDZGRk6C04IiIioiJJpYZbjIBOLXF3797FO++8g3v37kGhUKBjx46wsbHBrFmzoFAosGzZMn3HSURERETP0CnV/Oyzz+Dn54eUlBRYWFioy3v16oVDhw7pLTgiIiKiogiJxGCLMdCpJe6ff/7BiRMnYGZmplHu6emJBw8e6CUwIiIiIiqaTkmcSqWCUqksVH7//n3Y2Ni8clBEREREL2Uk87kZik5n//bbb2PhwoXq5xKJBBkZGQgJCUHnzp31FRsRERFR0TjZb8nNmzcPnTp1go+PD7KzszFgwADcuHEDzs7O2Lx5s75jJCIiIqLn6JRqVq5cGRcuXMDXX3+Nzz//HA0bNsR3332H8+fPo2LFivqOkYiIiKiQ1+3ChsWLF8PT0xPm5uZo1qwZTp8+/cL6qamp+OSTT+Dm5ga5XI4aNWrgzz//LPbxdGqJAwATExN88MEHum5ORERE9J+xZcsWBAcHY9myZWjWrBkWLlyITp06ISoqSmsDV05ODjp27IiKFSti27ZtcHd3x927d2Fvb1/sY+qcxN24cQNHjhxBQkJCoZveT548WdfdGrW2jeXo1MwCdtZSxMTnYfP+LNyJzSuyfuNaZujRxhLOdlLEJyux/UgWLt/K1ajj6iTDu+0sUeMNE8ikEsQmKrF0x2Mkp6uK2CuVBsdWfvD6YijsGtWFeaWKOPvuKMTvevH0Oo5vNoXP3P+DtU91ZMfE4mboUtzf8JtGHY+RA+AVPBRy1wpIvxiJK2OnI+3MJUOeChVT05pStKgjhbUFEJ8s8OdpFR4kCa11K9gBbzWQwc1JAgdrCf46o8TJa0V/Z1vVlaJjIxnCriqx9yy/26+D/Xu2Yc9vPyMtJRlvVPVG4EdfoFqNOlrrnjlxBDu3rUd87H0o8/LgUqkKOvccgNbtAtR10lKSsHn9YlyKOI2sjMeoVachAkcEw7XSG6V1Sv9Nr9HYtfnz52P48OHqe8gvW7YMe/bswZo1a/B///d/heqvWbMGycnJOHHiBExNTQHkz/JREjqd/cqVK1G7dm1MnjwZ27Ztw2+//aZefv/9d112afT8apuhb3sr7D7+BNPXpOF+ghJj+9vAxlJ7k2w1dxMM72mN4xHZmLY6DRHXc/DJezaoVEGmrlPBXorxH9oiLkmJuRvTMXVVKv74Nwu5edr/cFDpkVlZIv1iFC6PmVqs+haeldFk13IkHT2F4349EP3DetRbPgPOHVup67j1CUDtORNwY8ZiHG/aC48vRqLZntUwq+BoqNOgYqrjKUEnPymOXlBi+R95iEsBPuwgg5W59vqmJhKkZAgcDFficdaLv6+VnCTwqy5FXDK/16+LsH8OYOPqRejdfxhmLFiPNzyr47uQsUhLTdZa38rGFj36DMaU2SsR+v3PaNO+K1YsmoGL4ScBAEIIzP92PBLiHiL4m9mYuXADnCu64ttJY5Cd/aQ0T41KQKFQID09XWNRKBRa6+bk5ODcuXPo0KGDukwqlaJDhw4ICwvTus2uXbvg7++PTz75BC4uLqhbty6+/fZbrbN/FEWnJG7GjBmYOXMm4uLiEBERgfPnz6uX8PBwXXZp9Do2Ncc/EQqcuKhAbKISP/+ViZw8oKWvXGv99k3MceVWLvafykZckhI7jz3Bvbg8vNW44K9Cz7aWuHQrF9uPZCEmXolHqSpcuJH70j8KZHiP9h3D9ZCFiN95sFj1PT7qjyfR93Ft3CxkRN7G3SUbEbd9H6p+Nlhdp+rYIMSs/hX31+9AxrVbuDQqBMqsbFQZ/K6BzoKKq0VtKc7dUCHilsCjNOCPk0rkKoGG3tp/Qh8mCew/p8LlOwJ5L2hYMzMB3m0tw66TSjzJ4ff6dfHXzs1o93YPtOnQFZXfqIoho8ZDLjfH3wf/0Frfp15jNPFvC/cqVeHiVhnvdO+HNzyrIerqBQBA3MMY3Iy6jCGjxqFadR9UquyBoJHjkJujQNix/aV5av89EonBltDQUNjZ2WksoaGhWsNITEyEUqmEi4uLRrmLiwvi4uK0bnP79m1s27YNSqUSf/75JyZNmoR58+ZhxowZxT59nZK4lJQU9OnTR5dN/5NkUsDDzQTX7uSoywSAa9E5qOZuqnUbL3cTXL2j2XV65XYuvNzze7glAOpXM0N8cn6L3rzPHDAh0BYNamjfH73e7Js3QOJhzf+NPTpwHA7NGwAAJKamsGtUB4mHThRUEAKJh0/AvnnDUoyUnieTAm5OEtyOLUiyBIDbsQJVKrzarO5dmslw475KY99UtvJycxF9Mwp1GzRRl0mlUtT1bYIbkS8f2iCEwOULZxD74B5q1WkAAMjNzf/bYGpaMEG+VCqFiampOtGj18+ECROQlpamsUyYMEFv+1epVKhYsSJWrFiBxo0bo1+/fvjmm29KdOtSncbE9enTB/v378fHH3+sy+ZQKBSFmiTlcjnkcu2tVq87a0sJZFIJ0jM1f4jTMwVcnbT/yNtZS/E4U/VcfRXsrPPzahsrCczlEgT4W+D3v7Ow/XAW6lQzxch3bTBvYzqu3yt6rB29fuQuzlDEJ2qUKeITYWpnA6m5HKYOdpCamECRkPRcnSRY1fQqzVDpOZZyQCaVIOO5Xq+MJwLOtroncXU9JXBzlGDFnuJ3nZDhPU5PhUqlhJ295jAGW3sHPHxwp8jtsjIzMDqoG/JycyCVyjD4469Qr2EzAEClyp5wquCKLRuWYugn4yGXW+CvXZuRnJiA1JSkIvdJxWDAG9WXJC9xdnaGTCZDfHy8Rnl8fDxcXV21buPm5gZTU1PIZAXDqGrXro24uDjk5OQUuiuWNjolcd7e3pg0aRJOnjyJevXqqQfkPTVmzJgXbh8aGoqpUzXHEoWEhGDKlCm6hPOf9PTq5ogbOTh4JhsAEJOgRDV3U7RpaI7r9zLKMDoiehW2lkBAExk2HMh7YXcrGQ9zC0t8u3ADsrOf4MqFM9i4ZhEqulaCT73GMDExwecTvsOKH2biowFvQyqVoa5vE/g29ocQbIV9Fa/LPU7NzMzQuHFjHDp0CD179gSQ39J26NAhjB49Wus2LVu2xKZNm6BSqSD9XzJ6/fp1uLm5FSuBA3RM4lasWAFra2v8/fff+PvvvzXWSSSSlyZxEyZMQHBwsEaZsbbCAUBGloBSJWBrpflhsrUq3Dr3VFqGCjZW0ufqS5GWoVLvM08pEJuo+b/0uCQlvCvrfFExlRFFfCLkLs4aZXIXZ+SmPYYqW4GcxBSo8vIgr+j0XB0nKOI0W/CodGUpAKVKwNpCs9zaQoKMbN32WclJAmsLCUZ0Lfguy6QSeLgINK0lxfSNeeDf9rJhY2sPqVRW6CKG9NQU2Nk7FbFVfveoa6UqAABPrxp4eP8Odm3bAJ96jQEAVb1rIXTRT8jKzEBeXi5s7Rww+cshqOpd23AnQ6UqODgYgYGB8PPzQ9OmTbFw4UJkZmaqr1YdNGgQ3N3d1ePqRo4ciR9//BGfffYZPv30U9y4cQPffvvtS3OoZ+mUDURHR+uymZoxd51qo1QBd2PzUNvTFBHX88e5SQDU9jTF4XPaf+VvP8ivf+hMwfraVU1x+0Geep93YvPg4ijT2M7FUYYkTi9idFJPRqBCwJsaZc7tWyDlZAQAQOTmIi38Cpzf8i+YqkQigVM7f9xd8nMpR0vPUqqA2CQBLzcJImPyMysJgKquEpyO0u27eDtWYPEuzTGxPVvIkJgGHL+iZAJXhkxMTVHVuyauXDgDv+ZtAOS3qFy+eAZvdyn+WHChEsjLzSlUbmllDQCIe3gPt29G4r2BI/QTeHn1Gk0x0q9fPzx69AiTJ09GXFwcGjRogL1796ovdrh37566xQ0AqlSpgn379uHzzz9H/fr14e7ujs8++wzjx48v9jFfqUknJycH0dHRqFatGkxMynfr0IHT2RjSzRp3YpWIfpiHDk3NYWYqwb8X88f+DelmjZTHKvx2NAsAcOhMNr78wBYdm5rj0q0cNPGRw9PNBD/9lane5/6T2fiolzVuxMgReTcXdb3MUL+6Keb+nF4m50gFZFaWsPIumN/Jsmpl2PrWQk5yGrJjYlFzRjDM3V1wISj/y3h3xS/wGDUQtUK/Qsy67XBu1xxufQJwpnvBD3j0wrXwXTMLqecuI+3MRXiOCYSJlQVi1u8o9fMjTSeuqdCrpQwPEgUeJAn415bCzAQ4fzM/ievVUobHWQIHz+c/l0nz54p7+tjWEnB1AHLygOTH+f8mpGoeIycPyFKIQuVU+gJ6vI/lC6ejqndtVKvhg727tkCRnY027bsAAJYumAoHxwroHzgKALBz63p4edeCi1tl5ObmIOLsCRw/+heCRo5T7/PU8UOwsbOHcwVX3LtzCz+tmg+/Zm+i/v/GzdF/w+jRo4vsPj169GihMn9/f5w8eVLn4+mUeWVlZeHTTz/F+vXrAeT34Xp5eeHTTz+Fu7u71knt/uvOXsuBjWUWerxpAVur/Ml+F215jMf/6051tJVqjH249SAPq3ZmoGcbS/Rqa4mEFCUWb3uMh48Kuk/PX8/Bz39lIqCFBfp3tEJ8shJLtz/Gzfu8qKGs2TWuC/9DP6mf+8z9GgAQs2EHLg6dALlbBVhUcVOvf3LnPs50HwGfeRPg+ekgZN+Pw6URE5F44Li6TuzWv2BWwRE1QsbkT/Z74RpOdx2GnAQOfC5rV+4IWMlVeKuBDNYWQFyywE+HlMj8X0O6nRUgRMFwChsLYGS3grHCLevI0LKODNFxKqzbzwsZXnf+rTvicVoqtm1aibSUJHh4Vcf4KQtg55DfnZr0KA6SZ8ZiKRRPsHbZHCQnPYKZmRyVKntgZPAU+LfuqK6TkpKIn9csQlpqMuwdnNG6XQB69RtS2qf2nyNeo5a4siAROoyq/Oyzz/Dvv/9i4cKFeOedd3Dx4kV4eXlh586dmDJlCs6fP69zQMO/5R+s/7qVXxeMK9ljWrMMI6HS0CU3Sv04ZEPuC2rSf8HUQQXJ69molDKMhEqDX02HMj1+xsldBtu3dfPuBtu3vujUEvf7779jy5YtaN68ucb/RurUqYNbt27pLTgiIiKiIr0mV6eWFZ3aIR89eqT1Zq6ZmZkaSR0RERERGYZOSZyfnx/27Nmjfv40cVu1ahX8/f31ExkRERHRCwiJ1GCLMdCpO/Xbb79FQEAArl69iry8PCxatAhXr17FiRMnCs0bR0RERGQQ5bz3T6dUs1WrVoiIiEBeXh7q1auH/fv3o2LFiggLC0Pjxo31HSMRERERPUfnyd2qVauGlStX6jMWIiIiouIzkm5PQ9E5iVMqlfjtt99w7do1AICPjw969OhR7if9JSIiIioNOmVcV65cQffu3REXF4eaNfPn+Zo1axYqVKiA3bt3o27dunoNkoiIiOh5gmPiSm7YsGGoU6cO7t+/j/DwcISHhyMmJgb169fHRx99pO8YiYiIiOg5OrXERURE4OzZs3BwKJip2cHBATNnzkSTJk30FhwRERFRkcr5mDidzr5GjRqIj48vVJ6QkABvb+9XDoqIiIiIXkynJC40NBRjxozBtm3bcP/+fdy/fx/btm3D2LFjMWvWLKSnp6sXIiIiIkMQkBhsMQY6dad27doVANC3b1/13RqEEACAbt26qZ9LJBIolUp9xElERESkwVjurGAoOiVxR44c0XccRERERFQCOiVxbdq0QWpqKlavXq0xT9zQoUNhZ2en1wCJiIiItCrnLXE6nf3Zs2fh7e2NBQsWIDk5GcnJyViwYAGqVauG8PBwfcdIRERERM/RqSXu888/R7du3bBy5Ur1HRry8vIwbNgwjB07FseOHdNrkERERETPK++T/eqUxJ09e1YjgQMAExMTjBs3Dn5+fnoLjoiIiIi006k71dbWFvfu3StUHhMTAxsbm1cOioiIiOhlhERqsMUY6BRlv379MHToUGzZsgUxMTGIiYnBL7/8gmHDhuH999/Xd4xERERE9BydulPnzp0LiUSCQYMGIS8vDwBgamqKkSNH4rvvvtNrgERERERacUxcyZmZmWHRokUIDQ3FrVu3AADVqlWDpaWlXoMjIiIiKoqxdHsaik5J3FOWlpaoV6+evmIhIiIiomJ6pSSOiIiIqKwYyz1ODaV8t0MSERERGSm2xBEREZFRKu9j4sr32RMREREZKbbEERERkXEq51OMsCWOiIiIyAixJY6IiIiMkijnbVFM4oiIiMgoCXanEhEREZGxYUscERERGSVOMUJERERERoctcURERGSUeNstIiIiIjI6bIkjIiIio8QxcURERERkdNgSR0REREaJ88QRERERkdFhSxwREREZpfJ+dSqTOCIiIjJKvLCBiIiIiIwOW+KIiIjIKJX37lS2xBEREREZIbbEERERkVHimDgiIiIiMjpsiSMiIiKjxDFxRERERGR02BJHRERERqm8j4ljEkdERERGqbx3p0qEEKKsgyAiIiIqqdu3bhls317Vqhls3/rCljgiIiIySkJSvlviyndnMhEREZGReu1a4vp8Hl3WIZCBbV1QVf04ZENuGUZCpWHqIFP14z2mNcswEioNXXKj1I9bdfu7DCOh0nB8d5syPb4QbIkjIiIiIiPz2rXEERERERWHKOdtUeX77ImIiIiMFFviiIiIyCiV93nimMQRERGRUSrvSRy7U4mIiIiMEFviiIiIyCixJY6IiIiIjA5b4oiIiMgosSWOiIiIiIwOW+KIiIjIKPG2W0RERERkdNgSR0REREapvI+JYxJHRERERqm8J3HsTiUiIiIyQmyJIyIiIqPEljgiIiIiemWLFy+Gp6cnzM3N0axZM5w+fbpY2/3yyy+QSCTo2bNniY7HJI6IiIiMkhASgy0ltWXLFgQHByMkJATh4eHw9fVFp06dkJCQ8MLt7ty5gy+//BKtW7cu8TGZxBERERG9ovnz52P48OEICgqCj48Pli1bBktLS6xZs6bIbZRKJQYOHIipU6fCy8urxMdkEkdERERGSQWJwZaSyMnJwblz59ChQwd1mVQqRYcOHRAWFlbkdtOmTUPFihUxdOhQnc6fFzYQERERPUehUEChUGiUyeVyyOXyQnUTExOhVCrh4uKiUe7i4oLIyEit+z9+/DhWr16NiIgInWNkSxwREREZJQGJwZbQ0FDY2dlpLKGhoXqJ+/Hjx/jwww+xcuVKODs767yfYrfEXbx4sdg7rV+/vk7BEBERERWXIe+dOmHCBAQHB2uUaWuFAwBnZ2fIZDLEx8drlMfHx8PV1bVQ/Vu3buHOnTvo1q2bukylUgEATExMEBUVhWrVqr00xmIncQ0aNIBEIoEQAhLJi180pVJZ3N0SERERvXaK6jrVxszMDI0bN8ahQ4fU04SoVCocOnQIo0ePLlS/Vq1auHTpkkbZxIkT8fjxYyxatAhVqlQp1nGLncRFR0erH58/fx5ffvklvvrqK/j7+wMAwsLCMG/ePMyePbu4uyQiIiLS2es02W9wcDACAwPh5+eHpk2bYuHChcjMzERQUBAAYNCgQXB3d0doaCjMzc1Rt25dje3t7e0BoFD5ixQ7ifPw8FA/7tOnD77//nt07txZXVa/fn1UqVIFkyZNKvFkdURERETGrF+/fnj06BEmT56MuLg4NGjQAHv37lVf7HDv3j1Ipfq9FEGnq1MvXbqEqlWrFiqvWrUqrl69+spBEREREb2MIcfE6WL06NFau08B4OjRoy/cdt26dSU+nk4pYe3atREaGoqcnBx1WU5ODkJDQ1G7dm1ddklEREREJaBTS9yyZcvQrVs3VK5cWX0l6sWLFyGRSLB79269BkhERESkzes0Jq4s6JTENW3aFLdv38bGjRvVk9j169cPAwYMgJWVlV4DJCIiIqLCdL5jg5WVFT766CN9xkJERERUbK/bmLjSpvNlEj/99BNatWqFSpUq4e7duwCABQsWYOfOnXoLjoiIiKgoKgMuxkCnJG7p0qUIDg5GQEAAUlJS1JP7Ojg4YOHChfqMj4iIiIi00CmJ++GHH7By5Up88803MDEp6JH18/MrNAMxERERkSEIITHYYgx0SuKio6PRsGHDQuVyuRyZmZmvHBQRERERvZhOSVzVqlURERFRqHzv3r2cJ46IiIhKhYDEYIsx0Onq1ODgYHzyySfIzs6GEAKnT5/G5s2bERoailWrVuk7RiIiIiJ6jk5J3LBhw2BhYYGJEyciKysLAwYMQKVKlbBo0SL0799f3zESERERFWIsY9cMRed54gYOHIiBAwciKysLGRkZqFixoj7jIiIiIqIX0DmJe8rS0hKWlpb6iIWIiIio2Ixl7JqhFDuJa9iwISSS4r1Y4eHhOgdEREREVBwqUdYRlK1iJ3E9e/ZUP87OzsaSJUvg4+MDf39/AMDJkydx5coVjBo1Su9BEhEREZGmYidxISEh6sfDhg3DmDFjMH369EJ1YmJi9BcdERERURHKe3eqTvPEbd26FYMGDSpU/sEHH2D79u2vHBQRERERvZhOSZyFhQX+/fffQuX//vsvzM3NXzkoIiIiopcp77fd0unq1LFjx2LkyJEIDw9H06ZNAQCnTp3CmjVrMGnSJL0GSERERESF6ZTE/d///R+8vLywaNEi/PzzzwCA2rVrY+3atejbt69eAyQiIiLSRvDqVN307duXCRsRERFRGXmlyX5zcnKQkJAAlUqlUf7GG2+8UlBEREREL6Mq51en6pTE3bhxA0OGDMGJEyc0yoUQkEgkUCqVegnO2HRqaYPub9nB3kaGuw9zsGZHEm7eyymyfnNfS/QPcEAFRxPEPcrDz38k4/y1Jxp1+r1jj/b+NrAylyLyjgIrtyYiLjHP0KdCxdC0phQt6khhbQHEJwv8eVqFB0na2/Yr2AFvNZDBzUkCB2sJ/jqjxMlrKq11AaBVXSk6NpIh7KoSe88WXY9Kh2MrP3h9MRR2jerCvFJFnH13FOJ3HXrxNm82hc/c/4O1T3Vkx8TiZuhS3N/wm0Ydj5ED4BU8FHLXCki/GIkrY6cj7cwlQ54KldDQgZ7o9rYrbKxMcOlaOuYuuYH7sU9euE3vzpXwfu8qcHQww63oDCxYfhPXbjxWr6/kao7RQ6qhno8tzEylOBWejAXLbyIlNdfQp/OfYywXIBiKTlenDh48GFKpFH/88QfOnTuH8PBwhIeH4/z58+X2bg0tGlghsKcTtu5Lxfh5D3H3YQ6+GeEKW2vtL3ENTznGflgRh09lYNzchzh9ORPjhrigiqupuk6Pt+wQ8KYtVmxNwoSFD6FQqDDxY1eYmpTvD+3roI6nBJ38pDh6QYnlf+QhLgX4sIMMVkVcnG1qIkFKhsDBcCUeZ714EEclJwn8qksRl1zOB3u8RmRWlki/GIXLY6YWq76FZ2U02bUcSUdP4bhfD0T/sB71ls+Ac8dW6jpufQJQe84E3JixGMeb9sLji5Fotmc1zCo4Guo0qIQGvlsF73V1x9wlN/DRl+fxJFuJ+dPqwcy06N/gt1pVwOhh1bB28x0MHXsON6MzMH9aPdjb5f+2m8ulWDCtPoQQ+Oybixg5LgImJlLMmlQXxbwpEpGaTklcREQEli9fjoCAADRo0AC+vr4aS3nUta0tDoU9xtHTGbgfn4sVW5OQkyPwVjMbrfW7vGmLiMgn2HUkDQ8ScrHlr1Tcvq/AO61tC+q0scX2/ak4ezkL92Jz8eOmR3CwlaFJPd6rtqy1qC3FuRsqRNwSeJQG/HFSiVwl0NBb+1fqYZLA/nMqXL4jkPeChjUzE+Dd1jLsOqnEkxwmca+LR/uO4XrIQsTvPFis+h4f9ceT6Pu4Nm4WMiJv4+6SjYjbvg9VPxusrlN1bBBiVv+K++t3IOPaLVwaFQJlVjaqDH7XQGdBJdWnuzs2/HoXx08l4dadTMxYEAknRzlaN3cucpv+PStj975Y/HkoHndisjBnyQ1kK1To2tEVAFDPxw6uFc0xc2EUbt/NxO27mZi5IBK1vG3QuL59KZ3Zf4cQhluMgU5JnI+PDxITE/Udi9EykQFeleW4eL2giV0I4OKNJ6jhIde6TQ1Pc436AHAhqqB+RScTONia4NL1bPX6rGyBm3cVqOmpfZ9UOmRSwM1JgtuxBd9yAeB2rECVCq/2X+kuzWS4cV+lsW8yPvbNGyDxcJhG2aMDx+HQvAEAQGJqCrtGdZB46JkhKUIg8fAJ2DdvWIqRUlEquZjD2VGOMxEp6rLMLCWuXk9H3Vq2WrcxMZGghrcNzl4o2EYI4GxECurUzN/GzEQKASA3t+B/czk5KqgEUN/HzjAnQ/9ZOiVxs2bNwrhx43D06FEkJSUhPT1dYylvbKxkkMkkSHusORYw7bES9rYyrdvY28gK1U99rIS9rYl6PQCkZjxXJ0OpXkdlw1IOyKQSZDw3LCbjiYD1K8x1XddTAjdHCQ6GcwycsZO7OEMRr/kfXUV8IkztbCA1l8PM2QFSExMoEpKeq5MEuWvRrTxUehwdzACg0Di1lNQc9brn2dmawkQmQXKK5jbJqblw+t82V6LSkZ2txMjBXpDLpTCXS/HJkGowkUng5Kh9v1Q0AYnBFmOg04UNHTp0AAC0b99eo7y4FzYoFAooFAqNMrlcDrmcLUxUPtlaAgFNZNhwIO+F3a1EZBgd21TEV5/UUD8fN80wF5ikpudi0qyr+HJkdbzXzR0qARw8loCom4+h4nefSkinJO7IkSOvdNDQ0FBMnao5QDgkJARTpkx5pf2WlceZSiiVAnbPtZDZ2ciQmq49oU19rCxU395GhtT0PPV6ALC31tyHvbUMdx4WfcUrGV6WAlCqBKwtNMutLSTIyNa+zctUcpLA2kKCEV0LvpIyqQQeLgJNa0kxfWOe0YzRoPxWN7mLZoua3MUZuWmPocpWICcxBaq8PMgrOj1XxwmKOA5VKQvHTyfh6vWz6udmpvkdVQ72pkhKKfjNdbA3w83bGVr3kZaeizylgKODqUa543P7OHM+Bf0+Og07WxMolQIZmUrs3OCPh3EJ+jylckFVzn8XdUri2rRp80oHnTBhAoKDgzXKjLkVLk8J3L6vQL0a5jhzOQsAIJEA9apbYO9x7d3L1+9ko14NC/x5rGB9/RoWuH43v4UyISkPKel5qFvDXJ20Wcgl8PaQY9+Jx1r3SaVDqQJikwS83CSIjMn/BZEAqOoqweko3f4rfTtWYPEuzS6Yni1kSEwDjl9RMoEzMqknI1Ah4E2NMuf2LZByMgIAIHJzkRZ+Bc5v+RdMVSKRwKmdP+4u+bmUoyUAePJEiQdPNP/TnZisgJ+vA25GZwIALC1k8Klhi9//fKh1H3l5AtdvPkbj+g7452R+V7lEAjT2dcCOPQ8K1U/733/aG9W3h4OdKY6fTipUh+hFdJ7sNzU1FatXr8a1a9cAAHXq1MGQIUNgZ/fygZn/xa7TP46m45MBzrgVk4ObdxXo0sYWcjMJjpzKT7hGD3BGcpoSm/bkD3jdcywdU0e7oWtbW4RffYKWDa1QrYocy38t+F/4nr/T8W5He8Q9ykNCci76BTggJV2JM5eyyuQcqcCJayr0ainDg0SBB0kC/rWlMDMBzt/MT+J6tZThcZbAwfP5z2XS/Lninj62tQRcHYCcPCD5cf6/Camax8jJA7IUolA5lT6ZlSWsvAsmMbesWhm2vrWQk5yG7JhY1JwRDHN3F1wIGg8AuLviF3iMGohaoV8hZt12OLdrDrc+ATjTfYR6H9EL18J3zSyknruMtDMX4TkmECZWFohZv6PUz4+027rrAQL7vYGYh08QG5+NYR94IilZgX9OFvxOL5xRH8fCErFjT35i98vv9/HN57UQefMxrl1/jL493GFhLsWeg3HqbTq3d8Hd+1lISctF3Vq2+Gy4N37deR8xD148/xwVVt7nidMpiTt79iw6deoECwsLNG3aFAAwf/58zJw5E/v370ejRo30GqQxOBGRCVtrKfq94wB7WxnuPFBg5vJ4pGXk/xF3djDRaE25fkeBRT8l4P3ODhjQxRGxj3Ixe008YuIKWmN2Hk6DuZkEI/o6wdJCishoBWYuj0NuHptlytqVOwJWchXeaiCDtQUQlyzw0yElMv/XnWpnpfnjYmMBjOxW0MXSso4MLevIEB2nwrr95XNybGNi17gu/A/9pH7uM/drAEDMhh24OHQC5G4VYFHFTb3+yZ37ONN9BHzmTYDnp4OQfT8Ol0ZMROKB4+o6sVv/glkFR9QIGZM/2e+FazjddRhyEtga87rYuD0G5uYyjBtdA9ZWJrh0NQ1fhFxCTm7Bb7C7qwXsbQu+24ePP4K9nSmGDfSEo0N+1+sXIZc0LpB4o7IlRgR6wdbaBHEJ2djw6z1s2Xm/VM/tv6K891JIhCj5S9C6dWt4e3tj5cqVMDHJzwPz8vIwbNgw3L59G8eOHdM5oD6fR+u8LRmHrQuqqh+HbOAM5f91UwcV/IHbY1qzDCOh0tAlN0r9uFW3v8swEioNx3e/2vCqV/VnuOH+hnRuZPrySmVM55a4ZxM4ADAxMcG4cePg5+ent+CIiIiIilLe752q0zxxtra2uHfvXqHymJgY2Nhov0MBEREREemPTklcv379MHToUGzZsgUxMTGIiYnBL7/8gmHDhuH999/Xd4xEREREhZT3227p1J06d+5cSCQSDBo0CHl5+ZdIm5qaYuTIkfjuu+/0GiARERERFaZTEmdmZoZFixYhNDQUt27dAgBUq1YNlpa8MTsRERGVDk4x8gosLS1hb2+vfkxEREREpUOnMXF5eXmYNGkS7Ozs4OnpCU9PT9jZ2WHixInIzeWUEURERGR4KmG4xRjo1BL36aefYseOHZg9ezb8/f0BAGFhYZgyZQqSkpKwdOlSvQZJRERERJp0SuI2bdqEX375BQEBAeqy+vXro0qVKnj//feZxBEREZHBGctVpIaiUxInl8vh6elZqLxq1aowMzN71ZiIiIiIXkpwst+SGz16NKZPnw6FQqEuUygUmDlzJkaPHq234IiIiIhIO51a4s6fP49Dhw6hcuXK8PX1BQBcuHABOTk5aN++PXr37q2uu2PHDv1ESkRERPQMY7kAwVB0SuLs7e3x7rvvapRVqVJFLwERERER0cvplMStXbtW33EQERERlUh5v7BBpzFxT548QVZWlvr53bt3sXDhQuzfv19vgRERERFR0XRK4nr06IENGzYAAFJTU9G0aVPMmzcPPXr04PQiREREVCoMceP7p4sx0CmJCw8PR+vWrQEA27Ztg6urK+7evYsNGzbg+++/12uARERERFSYTmPisrKyYGNjAwDYv38/evfuDalUiubNm+Pu3bt6DZCIiIhIG5XgPHEl5u3tjd9//x0xMTHYt28f3n77bQBAQkICbG1t9RogERERkTbsTtXB5MmT8eWXX8LT0xNNmzZV3z91//79aNiwoV4DJCIiIqLCdOpOfe+999CqVSvExsaqJ/sFgPbt26NXr156C46IiIioKMbSYmYoOrXEAYCrqytsbGxw4MABPHnyBADQpEkT1KpVS2/BEREREZF2OiVxSUlJaN++PWrUqIHOnTsjNjYWADB06FB88cUXeg2QiIiISBuVMNxiDHRK4j7//HOYmpri3r17sLS0VJf369cPe/fu1VtwRERERKSdTmPi9u/fj3379qFy5coa5dWrV+cUI0RERFQqBKcYKbnMzEyNFrinkpOTIZfLXzkoIiIiInoxnZK41q1bq2+7BQASiQQqlQqzZ89Gu3bt9BYcERERUVHK+zxxOnWnzpkzB2+99RbOnj2LnJwcjBs3DleuXEFycjL+/fdffcdIREREVIixXIBgKCVO4nJzczFmzBjs3r0bBw4cgI2NDTIyMtC7d2988skncHNzM0ScRERERPSMEidxpqamuHjxIhwcHPDNN98YIiYiIiKilzKWbk9D0WlM3AcffIDVq1frOxYiIiIiKiadxsTl5eVhzZo1OHjwIBo3bgwrKyuN9fPnz9dLcERERERFKe8tcTolcZcvX0ajRo0AANevX9dYJ5GU7zlbiIiIiEqDTknckSNH9B0HERERUYmU96tTdRoTR0RERERlS6eWOCIiIqKyxjFxREREREZIpSrrCMoWu1OJiIiIjBBb4oiIiMgolffuVJ1a4i5fvlzkut9//13XWIiIiIiomHRK4jp16oTo6OhC5du3b8fAgQNfOSgiIiKilxHCcIsx0CmJGzZsGDp06IC4uDh12ZYtWzBo0CCsW7dOX7ERERERGY3FixfD09MT5ubmaNasGU6fPl1k3ZUrV6J169ZwcHCAg4MDOnTo8ML62uiUxE2dOhWdO3dGhw4dkJycjE2bNiEoKAgbNmxAnz59dNklERERUYmohOGWktqyZQuCg4MREhKC8PBw+Pr6olOnTkhISNBa/+jRo3j//fdx5MgRhIWFoUqVKnj77bfx4MGDYh9T56tTf/jhB/j6+qJ58+YYPnw4Nm/ejHfffVfX3REREREZrfnz52P48OEICgqCj48Pli1bBktLS6xZs0Zr/Y0bN2LUqFFo0KABatWqhVWrVkGlUuHQoUPFPmaxr07dtWtXobLevXvjn3/+wfvvvw+JRKKu071792IHQERERKQLYdDBa8W/F3xOTg7OnTuHCRMmqMukUik6dOiAsLCwYu0jKysLubm5cHR0LPZxi53E9ezZs8h1a9asUWeaEokESqWy2AEQERER6cKQOZxCoYBCodAok8vlkMvlheomJiZCqVTCxcVFo9zFxQWRkZHFOt748eNRqVIldOjQodgxFrs7VaVSFWthAkdERETGLjQ0FHZ2dhpLaGioQY713Xff4ZdffsFvv/0Gc3PzYm/HyX6JiIjIKBnytlsTJkxAcHCwRpm2VjgAcHZ2hkwmQ3x8vEZ5fHw8XF1dX3icuXPn4rvvvsPBgwdRv379EsWocxJ36NAhHDp0CAkJCVA99yoWNYiPiIiIyBgU1XWqjZmZGRo3boxDhw6ph589vUhh9OjRRW43e/ZszJw5E/v27YOfn1+JY9QpiZs6dSqmTZsGPz8/uLm5QSIp/uA/IiIiIn14nSblDQ4ORmBgIPz8/NC0aVMsXLgQmZmZCAoKAgAMGjQI7u7u6i7ZWbNmYfLkydi0aRM8PT3Vc+9aW1vD2tq6WMfUKYlbtmwZ1q1bhw8//FCXzYmIiIj+U/r164dHjx5h8uTJiIuLQ4MGDbB37171xQ737t2DVFpwKcLSpUuRk5OD9957T2M/ISEhmDJlSrGOqVMSl5OTgxYtWuiyKREREZFe6DIpryGNHj26yO7To0ePajy/c+fOKx9PInSYZGX8+PGwtrbGpEmTXjkAIiIiIl3M32m4LC64x+s/VEynlrjs7GysWLFCfSWFqampxvr58+frJTgiIiKiorxOY+LKgk5J3MWLF9GgQQMAwOXLlzXW8SIHIiIiKg3CoP2pr38+o1MSd+TIEX3HoTZoUqzB9k2vhw3T3dSPz0allGEkVBr8ajqoH7fq9ncZRkKl4fjuNurHe0xrlmEkVBq65EaVdQjlGif7JSIiIqP0ul3YUNqKncT17t0b69atg62tLXr37v3Cujt27HjlwIiIiIioaMVO4uzs7NTj3ezs7AwWEBEREVFx8MKGYlq7dq3Wx0RERERU+jgmjoiIiIySqpwPiit2EtewYcNiTx8SHh6uc0BERERE9HLFTuJ69uxpwDCIiIiISoZj4oopJCSkxDvfvHkzunfvDisrqxJvS0RERPQi5T2Jkxpy5yNGjEB8fLwhD0FERERULhn0wgZR3lNkIiIiMhhVOc8zDNoSR0RERESGwSlGiIiIyCgJVVlHULbYEkdERERkhNgSR0REREapvI+9N2hLnIeHB0xNTQ15CCIiIqJyyaAtcZcvXzbk7omIiKgcU5XzMXE6JXEODg5ab8ElkUhgbm4Ob29vDB48GEFBQa8cIBEREZE25b07VackbvLkyZg5cyYCAgLQtGlTAMDp06exd+9efPLJJ4iOjsbIkSORl5eH4cOH6zVgIiIiItIxiTt+/DhmzJiBjz/+WKN8+fLl2L9/P7Zv34769evj+++/ZxJHREREBqEq3w1xul3YsG/fPnTo0KFQefv27bFv3z4AQOfOnXH79u1Xi46IiIiItNIpiXN0dMTu3bsLle/evRuOjo4AgMzMTNjY2LxadERERERFECphsMUY6NSdOmnSJIwcORJHjhxRj4k7c+YM/vzzTyxbtgwAcODAAbRp00Z/kRIRERGRmk5J3PDhw+Hj44Mff/wRO3bsAADUrFkTf//9N1q0aAEA+OKLL/QXJREREdFzyvnFqbrPE9eyZUu0bNlSn7EQERERUTHpnMSpVCrcvHkTCQkJUD03296bb775yoERERERvYjKSMauGYpOSdzJkycxYMAA3L17t9BEexKJBEqlUi/BEREREZF2OiVxH3/8Mfz8/LBnzx64ublpvXsDERERkSHxjg06uHHjBrZt2wZvb299x0NERERULKKc3ztVp3nimjVrhps3b+o7FiIiIiIqJp1a4j799FN88cUXiIuLQ7169WBqaqqxvn79+noJjoiIiKgoKnanlty7774LABgyZIi6TCKRQAjBCxuIiIiISoFOSVx0dLS+4yAiIiIqEV7YoAMPDw99x0FEREREJVDsJG7Xrl0ICAiAqakpdu3a9cK63bt3f+XAiIiIiF6Ek/0WU8+ePREXF4eKFSuiZ8+eRdbjmDgiIiIiwyt2EvfsrbWev80WERERUWkr50PidJsnbsOGDVAoFIXKc3JysGHDhlcOioiIiOhlhEoYbDEGOiVxQUFBSEtLK1T++PFjBAUFvXJQRERERPRiOl2d+nQ+uOfdv38fdnZ2rxwUERER0ctwst8SaNiwISQSCSQSCdq3bw8Tk4LNlUoloqOj8c477+g9SCIiIiLSVKIk7ulVqREREejUqROsra3V68zMzODp6am+mwMRERGRIRnL2DVDKVESFxISAgDw9PREv379YG5ubpCgiIiIiOjFdLqwITAwENnZ2Vi1ahUmTJiA5ORkAEB4eDgePHig1wCJiIiItCnvV6fqdGHDxYsX0aFDB9jZ2eHOnTsYPnw4HB0dsWPHDty7d4/TjBAREREZmE4tcZ9//jkGDx6MGzduaHSpdu7cGceOHdNbcERERERFUQnDLcZAp5a4s2fPYsWKFYXK3d3dERcX98pBEREREb2MsXR7GopOLXFyuRzp6emFyq9fv44KFSq8clBERERE9GI6JXHdu3fHtGnTkJubCyD/pvf37t3D+PHjOcUIERERlQohhMEWY6BTEjdv3jxkZGSgYsWKePLkCdq0aQNvb2/Y2Nhg5syZ+o6RiIiIiJ6j05g4Ozs7HDhwAMePH8fFixeRkZGBRo0aoUOHDvqOz6i0b2qJzq2sYGctQ0xcLn7ak47bD3KLrN+kjjnebW8DZ3sZ4pPzsGXfY1y8oVCv79XOGs3qWcDJToo8JXDnYS62HnyM2/eL3ieVnv17tmHPbz8jLSUZb1T1RuBHX6BajTpa6545cQQ7t61HfOx9KPPy4FKpCjr3HIDW7QLUddJSkrB5/WJcijiNrIzHqFWnIQJHBMO10huldUpUDEMHeqLb266wsTLBpWvpmLvkBu7HPnnhNr07V8L7vavA0cEMt6IzsGD5TVy78Vi9vpKrOUYPqYZ6PrYwM5XiVHgyFiy/iZRUftfLgmMrP3h9MRR2jerCvFJFnH13FOJ3HXrxNm82hc/c/4O1T3Vkx8TiZuhS3N/wm0Ydj5ED4BU8FHLXCki/GIkrY6cj7cwlQ57Kf56KY+J016pVKwwZMgRfffVVuU/gmtU1x4AAW/x+JAOTlybiXlwevgp0hI2V9pfYu4opRvWxx7FzWZi8NBHh17IxdoAD3CsW5NVxSXn46Y80fP1jImasSsKjFCXGBTrCxvKV3jbSg7B/DmDj6kXo3X8YZixYjzc8q+O7kLFIS03WWt/KxhY9+gzGlNkrEfr9z2jTvitWLJqBi+EnAeR3Ccz/djwS4h4i+JvZmLlwA5wruuLbSWOQnf3iBIFKz8B3q+C9ru6Yu+QGPvryPJ5kKzF/Wj2YmRa+l/RTb7WqgNHDqmHt5jsYOvYcbkZnYP60erC3MwUAmMulWDCtPoQQ+Oybixg5LgImJlLMmlQXWm5RTaVAZmWJ9ItRuDxmarHqW3hWRpNdy5F09BSO+/VA9A/rUW/5DDh3bKWu49YnALXnTMCNGYtxvGkvPL4YiWZ7VsOsgqOhToPKAZ2yAZVKhenTp8Pd3R3W1taIjo4GAEyaNAmrV6/Wa4DG4p0WVjh6Ngv/nH+Ch4/ysG53GhS5Am0aWWit38nfCpduKvDnv5l4+CgP2w9l4E5sLjo2s1TXCbuYjSu3c/AoRYkHCXnYtDcdluZSVHHVqQGV9OivnZvR7u0eaNOhKyq/URVDRo2HXG6Ovw/+obW+T73GaOLfFu5VqsLFrTLe6d4Pb3hWQ9TVCwCAuIcxuBl1GUNGjUO16j6oVNkDQSPHITdHgbBj+0vz1OgF+nR3x4Zf7+L4qSTcupOJGQsi4eQoR+vmzkVu079nZezeF4s/D8XjTkwW5iy5gWyFCl07ugIA6vnYwbWiOWYujMLtu5m4fTcTMxdEopa3DRrXty+lM6NnPdp3DNdDFiJ+58Fi1ff4qD+eRN/HtXGzkBF5G3eXbETc9n2o+tlgdZ2qY4MQs/pX3F+/AxnXbuHSqBAos7JRZTDHkb8KjonTwYwZM7Bu3TrMnj0bZmZm6vK6deti1apVegvOWMhkgGclU1y5XdAVKgRw9ZYC3lXMtG7jXcUMV24pNMou3VTA+w3t9WUyoJ2fJTKfqHAvjl0sZSkvNxfRN6NQt0ETdZlUKkVd3ya4EfnyrhEhBC5fOIPYB/dQq04DAEBubg4AwNS04P2XSqUwMTVVJ3pUtiq5mMPZUY4zESnqsswsJa5eT0fdWrZatzExkaCGtw3OXijYRgjgbEQK6tTM38bMRAoBIDdXpa6Tk6OCSgD1fewMczKkV/bNGyDxcJhG2aMDx+HQvAEAQGJqCrtGdZB46ERBBSGQePgE7Js3LMVI6b9GpyadDRs2YMWKFWjfvj0+/vhjdbmvry8iIyNfur1CoYBCoZnAyOVyyOVyXcIpczaWUshkEqRnqDTK0zJUcHPW/hLbWUuR9lz99AwV7Kw18+oGNeQY1dceZqYSpGaoMHt9MjKyjON/CP9Vj9NToVIpYWev2Q1ia++Ahw/uFLldVmYGRgd1Q15uDqRSGQZ//BXqNWwGAKhU2RNOFVyxZcNSDP1kPORyC/y1azOSExOQmpJkyNOhYnJ0yE+wnx+nlpKao173PDtbU5jIJEhO0dwmOTUXHpXzW92vRKUjO1uJkYO9sPynaEgAfBzoBROZBE6O2vdLrxe5izMU8YkaZYr4RJja2UBqLoepgx2kJiZQJCQ9VycJVjW9SjPU/xzOE6eDBw8ewNvbu1C5SqVSTzvyIqGhobCzs9NYQkNDdQnlP+9qdA4mLknE9JVJuHRDgdH97IscZ0evN3MLS3y7cAOmzVuLPh+MwMY1i3D10jkAgImJCT6f8B1iH97DRwPeRlCftrh6MRy+jf0h4cCoMtGxTUXs/7WVejExMcz7kJqei0mzrqJlUycc+LUV9m5pBWtrE0TdfAyV6uXbE5VnvHeqDnx8fPDPP//Aw8NDo3zbtm1o2PDlTcMTJkxAcHCwRpmxtsIBwOMsFZRKAdvnWtG0tbY9laal1c1WS/2cXIGEZCUSkpW4dT8Ns8dWQJvGFvjjWKZ+T4KKzcbWHlKprNBFDOmpKbCzdypyO6lUCtdKVQAAnl418PD+HezatgE+9RoDAKp610Loop+QlZmBvLxc2No5YPKXQ1DVu7bhToaKdPx0Eq5eP6t+bmaa/311sDdFUkqOutzB3gw3b2do3Udaei7ylAKODqYa5Y7P7ePM+RT0++g07GxNoFQKZGQqsXODPx7GJejzlMhAFPGJkLtojouUuzgjN+0xVNkK5CSmQJWXB3lFp+fqOEERp9mCR1QSOjXpTJ48GaNHj8asWbOgUqmwY8cODB8+HDNnzsTkyZNfur1cLoetra3GYsxJnPJ/03/U8So4B4kE8PGS42ZMjtZtbsbkwMdL85zrVpPj5j3t9Z/dr6mMLTNlycTUFFW9a+LKhTPqMpVKhcsXz6B6rXrF3o9QCeTlFn6/La2sYWvngLiH93D7ZiQaN3tTL3FTyTx5osSD2Gz1En0vC4nJCvj5OqjrWFrI4FPDFpcjC9/BBgDy8gSu33yMxvULtpFIgMa+DrgSVXibtPQ8ZGQq0ai+PRzsTHH8NLvSjUHqyQg4vdVco8y5fQuknIwAAIjcXKSFX4HzW/4FFSQSOLXzR+rJ86UY6X+PSgiDLcZApySuR48e2L17Nw4ePAgrKytMnjwZ165dw+7du9GxY0d9x2gU9p7IRJvGlmjVwAKVKpggsJst5GYSHAvPnx7io3ft0Kejjbr+vrBM1KsuxzstrODmLEOvdtaoWskUB05lAQDMTCV4r4MNqlU2hZOdDJ6VTDCspx0cbGQ4fSW7TM6RCgT0eB9H9u/CsUN78CAmGmuXzoYiOxtt2ncBACxdMBW/rF+irr9z63pcOn8KCXEP8CAmGnt+24jjR/9Cy7bvqOucOn4IVy+dQ0LcA5w9eQyhk8fAr9mbqP+/cXNU9rbueoDAfm+gZVMneHlYYWJwLSQlK/DPyYLWlIUz6qN3l0rq57/8fh/dOrnhnbdc4FHZEl+Oqg4Lcyn2HCy4z3Tn9i6oU9MGlVzN8Xbbipg+3ge/7ryPmAecXqYsyKwsYetbC7a+tQAAllUrw9a3FsyruAEAas4Ihu/aWer6d1f8AsuqVVAr9CtY1fSCx8cD4NYnANGL1qnrRC9ciypD+8L9w56wruWFuounwMTKAjHrd5TqudF/i85zVbRu3RoHDhzQZyxG7dTlbNhYpaN3e2vYWctwLzYXczYkIz0zv3vUyU4G8UxP6c2YXCzdmor3OtigT0cbxCflYeGmFDxIyAOQfwVjpQomaNXQATaWUmRkqRD9IBczVyep61DZ8W/dEY/TUrFt00qkpSTBw6s6xk9ZADuH/O6SpEdxGmPZFIonWLtsDpKTHsHMTI5KlT0wMngK/FsX/KcnJSURP69ZhLTUZNg7OKN1uwD06jektE+NXmDj9hiYm8swbnQNWFuZ4NLVNHwRcgk5uQX/a3d3tYC9bUH36eHjj2BvZ4phAz3h6JDf9fpFyCWNCyTeqGyJEYFesLU2QVxCNjb8eg9bdt4v1XOjAnaN68L/0E/q5z5zvwYAxGzYgYtDJ0DuVgEW/0voAODJnfs4030EfOZNgOeng5B9Pw6XRkxE4oHj6jqxW/+CWQVH1AgZkz/Z74VrON11GHIS2Nr6Koxl7JqhSMQrToaSkZEB1XOjb21ttV9uXxyDJsW+SjhkBDZML/jxOxuV8oKa9F/gV7OgK7FVt7/LMBIqDcd3t1E/3mNaswwjodLQJTeqTI8fODnu5ZV0tH6aq8H2rS86tcRFR0dj9OjROHr0KLKzC7r2hBCQSCRQKpV6C5CIiIhIG2OZlNdQdEriPvjgAwghsGbNGri4uHAKBCIiIqJSplMSd+HCBZw7dw41a7KpnIiIiMqGqpyPidPp6tQmTZogJiZG37EQERERFRsn+9XBqlWr8PHHH+PBgweoW7cuTE01J7KsX7++XoIjIiIiIu10SuIePXqEW7duISgoSF0mkUh4YQMRERGVGl7YoIMhQ4agYcOG2Lx5My9sICIiIioDOiVxd+/exa5du+Dt7a3veIiIiIiKRai035+8vNDpwoa33noLFy5c0HcsRERERFRMOrXEdevWDZ9//jkuXbqEevXqFbqwoXv37noJjoiIiKgo5X2KEZ2SuI8//hgAMG3atELreGEDERERlUeLFy/GnDlzEBcXB19fX/zwww9o2rRpkfW3bt2KSZMm4c6dO6hevTpmzZqFzp07F/t4OnWnqlSqIhcmcERERFQahBAGW0pqy5YtCA4ORkhICMLDw+Hr64tOnTohISFBa/0TJ07g/fffx9ChQ3H+/Hn07NkTPXv2xOXLl4t9TJ2SuOKqV68eJwUmIiIig3idJvudP38+hg8fjqCgIPj4+GDZsmWwtLTEmjVrtNZftGgR3nnnHXz11VeoXbs2pk+fjkaNGuHHH38s9jENmsTduXMHubm5hjwEERERkd4pFAqkp6drLAqFQmvdnJwcnDt3Dh06dFCXSaVSdOjQAWFhYVq3CQsL06gPAJ06dSqyvjYGTeKIiIiIDMWQLXGhoaGws7PTWEJDQ7XGkZiYCKVSCRcXF41yFxcXxMXFad0mLi6uRPW10enCBiIiIqL/sgkTJiA4OFijTC6Xl1E02jGJIyIiIqOkEoab7Fculxc7aXN2doZMJkN8fLxGeXx8PFxdXbVu4+rqWqL62rA7lYiIiOgVmJmZoXHjxjh06JC6TKVS4dChQ/D399e6jb+/v0Z9ADhw4ECR9bVhSxwREREZJV2uIjWU4OBgBAYGws/PD02bNsXChQuRmZmJoKAgAMCgQYPg7u6uHlf32WefoU2bNpg3bx66dOmCX375BWfPnsWKFSuKfUyDJnHLly8vNGiPiIiI6L+mX79+ePToESZPnoy4uDg0aNAAe/fuVedB9+7dg1Ra0AHaokULbNq0CRMnTsTXX3+N6tWr4/fff0fdunWLfcxiJ3Hff/99sXc6ZswYAMCAAQOKvQ0RERFRSbxOLXEAMHr0aIwePVrruqNHjxYq69OnD/r06aPz8YqdxC1YsEDj+aNHj5CVlQV7e3sAQGpqKiwtLVGxYkV1EkdERERkKLrcWeG/pNgXNkRHR6uXmTNnokGDBrh27RqSk5ORnJyMa9euoVGjRpg+fboh4yUiIiIi6DgmbtKkSdi2bRtq1qypLqtZsyYWLFiA9957DwMHDtRbgERERETaqFSGm2LEGOg0xUhsbCzy8vIKlSuVykJznhARERGR/umUxLVv3x4jRoxAeHi4uuzcuXMYOXJkofuAERERERmCIW+7ZQx0SuLWrFkDV1dX+Pn5qWc0btq0KVxcXLBq1Sp9x0hEREREz9FpTFyFChXw559/4vr164iMjAQA1KpVCzVq1NBrcERERERFEQa87ZYxeKXJfj09PSGEQLVq1WBiwps/EBEREZUWnbpTs7KyMHToUFhaWqJOnTq4d+8eAODTTz/Fd999p9cAiYiIiLThmDgdTJgwARcuXMDRo0dhbm6uLu/QoQO2bNmit+CIiIiIilLekzid+kB///13bNmyBc2bN4dEIlGX16lTB7du3dJbcERERESknU5J3KNHj1CxYsVC5ZmZmRpJHREREZGhqMr5hQ06daf6+flhz5496udPE7dVq1bB399fP5ERERERUZF0aon79ttvERAQgKtXryIvLw+LFi3C1atXceLECfz999/6jpGIiIioEGMZu2YoOrXEtWrVChEREcjLy0O9evWwf/9+VKxYEWFhYWjcuLG+YyQiIiKi5+g8uVu1atWwcuVKfcZCREREVGxCVb7HxOmUxKWnp2stl0gkkMvlMDMze6WgiIiIiOjFdEri7O3tX3gVauXKlTF48GCEhIRAKtWpx5aIiIjohcr7mDidkrh169bhm2++weDBg9G0aVMAwOnTp7F+/XpMnDgRjx49wty5cyGXy/H111/rNWAiIiIi0jGJW79+PebNm4e+ffuqy7p164Z69eph+fLlOHToEN544w3MnDmTSRwREREZhOA8cSV34sQJNGzYsFB5w4YNERYWBiD/Ctan91QlIiIi0jeVShhsMQY6JXFVqlTB6tWrC5WvXr0aVapUAQAkJSXBwcHh1aIjIiIiIq106k6dO3cu+vTpg7/++gtNmjQBAJw9exaRkZHYtm0bAODMmTPo16+f/iIlIiIieganGNFB9+7dERUVheXLlyMqKgoAEBAQgN9//x2enp4AgJEjR+otSCIiIiLSVOIkLjc3F++88w6WLVuG0NBQQ8RERERE9FLlfYqREo+JMzU1xcWLFw0RCxEREREVk04XNnzwwQdaL2wgIiIiKi1CqAy2GAOdxsTl5eVhzZo1OHjwIBo3bgwrKyuN9fPnz9dLcERERESknU5J3OXLl9GoUSMAwPXr1zXWveh2XERERET6Ut7HxOmUxB05ckTfcRARERGVSHmfYkQihNA5jb158yZu3bqFN998ExYWFhBCsCWOiIiISkWrbn8bbN/Hd7cx2L71RackLikpCX379sWRI0cgkUhw48YNeHl5YciQIXBwcMC8efMMEet/jkKhQGhoKCZMmAC5XF7W4ZCB8f0uX/h+ly98v6ks6JTEDRo0CAkJCVi1ahVq166NCxcuwMvLC/v27UNwcDCuXLliiFj/c9LT02FnZ4e0tDTY2tqWdThkYHy/yxe+3+UL328qCzqNidu/fz/27duHypUra5RXr14dd+/e1UtgRERERFQ0neaJy8zMhKWlZaHy5ORkNiMTERERlQKdkrjWrVtjw4YN6ucSiQQqlQqzZ89Gu3bt9BYcEREREWmnU3fq7Nmz0b59e5w9exY5OTkYN24crly5guTkZPz777/6jvE/Sy6XIyQkhK2X5QTf7/KF73f5wvebyoLOU4ykpqZi8eLFuHDhAjIyMtCoUSN88skncHNz03eMRERERPQcnZO47OxsXLx4EQkJCVA9N9le9+7d9RIcEREREWmnU3fq3r178eGHHyI5ORnP54ASiQRKpVIvwRERERGRdjpd2PDpp5+ib9++ePjwIVQqlcbCBI6IiIjI8HRK4uLj4xEcHAwXFxd9x0NEOho8eDB69uxZ1mGQnkyZMgUNGjR4pX3cuXMHEokEEREReonJmHl6emLhwoVlHYZOJBIJfv/991I73vOfPV1+W0o75vJKpyTuvffew9GjR/UcivFo27Ytxo4dW+rHvXLlCt599114enpCIpEY7Q8SEREVVlTiHhsbi4CAgNIP6H8WLVqEdevWldnxqWg6jYn78ccf0adPH/zzzz+oV68eTE1NNdaPGTNGL8GRpqysLHh5eaFPnz74/PPPyzocotdeTk4OzMzMyjoMKga+V0VzdXUt0+Pb2dmV6fGpaDq1xG3evBn79+/H9u3b8cMPP2DBggXq5b/eOjR48GD8/fffWLRoESQSCSQSCUxMTDB37lyNehEREZBIJLh58yaA/KblpUuXIiAgABYWFvDy8sK2bds0tomJiUHfvn1hb28PR0dH9OjRA3fu3FGvb9KkCebMmYP+/ftzLiIDUSgUGDNmDCpWrAhzc3O0atUKZ86cAQAcPXoUEokEe/bsQf369WFubo7mzZvj8uXLGvs4fvw4WrduDQsLC1SpUgVjxoxBZmamer2npye+/fZbDBkyBDY2NnjjjTewYsUKjX287LOgVCoRHBwMe3t7ODk5Ydy4cYUuMiqP2rZti9GjR2Ps2LFwdnZGp06dcPnyZQQEBMDa2houLi748MMPkZiYqN5m27ZtqFevHiwsLODk5IQOHTqo36+n3UhTp05FhQoVYGtri48//hg5OTnq7V/0mQEKPjeHDh2Cn58fLC0t0aJFC0RFRWnE/t1338HFxQU2NjYYOnQosrOzC53f0/tVm5ubo1atWliyZInG+tOnT6Nhw4YwNzeHn58fzp8/r7fX9dNPP8XYsWPh4OAAFxcXrFy5EpmZmQgKCoKNjQ28vb3x119/qbd52euu7b0CgF27dqF69eowNzdHu3btsH79ekgkEqSmpqq3fdl3LCEhAd26dYOFhQWqVq2KjRs3luh8JRIJli9fjq5du8LS0hK1a9dGWFgYbt68ibZt28LKygotWrTArVu3NLbbuXMnGjVqBHNzc3h5eWHq1KnIy8tTr09NTcWwYcPUn6W33noLFy5cAACsW7cOU6dOxYULF9R/W562fj3bNfm0i3zHjh1o164dLC0t4evri7CwMI1YVq5ciSpVqsDS0hK9evXC/PnzYW9vX6LX4annu1Pbtm2LMWPGYNy4cXB0dISrqyumTJnywn2EhITAzc0NFy9e1CkGKoLQgYuLi5g5c6ZQKpW6bG7UUlNThb+/vxg+fLiIjY0VsbGxYsaMGcLHx0ej3pgxY8Sbb76pfg5AODk5iZUrV4qoqCgxceJEIZPJxNWrV4UQQuTk5IjatWuLIUOGiIsXL4qrV6+KAQMGiJo1awqFQlEoDg8PD7FgwQKDnmt5NGbMGFGpUiXx559/iitXrojAwEDh4OAgkpKSxJEjRwQAUbt2bbF//35x8eJF0bVrV+Hp6SlycnKEEELcvHlTWFlZiQULFojr16+Lf//9VzRs2FAMHjxYfQwPDw/h6OgoFi9eLG7cuCFCQ0OFVCoVkZGRQojifRZmzZolHBwcxPbt28XVq1fF0KFDhY2NjejRo0epv2avkzZt2ghra2vx1VdficjISHHy5ElRoUIFMWHCBHHt2jURHh4uOnbsKNq1ayeEEOLhw4fCxMREzJ8/X0RHR4uLFy+KxYsXi8ePHwshhAgMDBTW1taiX79+4vLly+KPP/4QFSpUEF9//bX6mC/6zAgh1J+bZs2aiaNHj4orV66I1q1bixYtWqj3sWXLFiGXy8WqVatEZGSk+Oabb4SNjY3w9fVV1/n555+Fm5ub2L59u7h9+7bYvn27cHR0FOvWrRNCCPH48WNRoUIFMWDAAHH58mWxe/du4eXlJQCI8+fPv/LramNjI6ZPny6uX78upk+fLmQymQgICBArVqwQ169fFyNHjhROTk4iMzNTpKSkvPB11/ZeRUZGitu3bwtTU1Px5ZdfisjISLF582bh7u4uAIiUlBQhRPG+YwEBAcLX11eEhYWJs2fPihYtWggLC4ti/2YCEO7u7mLLli0iKipK9OzZU3h6eoq33npL7N27V1y9elU0b95cvPPOO+ptjh07JmxtbcW6devErVu3xP79+4Wnp6eYMmWKuk6HDh1Et27dxJkzZ8T169fFF198IZycnERSUpLIysoSX3zxhahTp476b0tWVpY6nt9++00IIUR0dLQAIGrVqiX++OMPERUVJd577z3h4eEhcnNzhRBCHD9+XEilUjFnzhwRFRUlFi9eLBwdHYWdnV2xzj8kJETjsxcYGKjx29KmTRtha2srpkyZIq5fvy7Wr18vJBKJ2L9/v8Zr+NtvvwmVSiVGjx4tPD09xY0bN4p1fCo+nZI4BwcHcfPmTX3HYjTatGkjPvvsM/XzBw8eCJlMJk6dOiWEyP8j7OzsrP5xFSL/A/3xxx9r7KdZs2Zi5MiRQgghfvrpJ1GzZk2hUqnU6xUKhbCwsBD79u0rFAOTOP3LyMgQpqamYuPGjeqynJwcUalSJTF79mz1H+NffvlFvT4pKUlYWFiILVu2CCGEGDp0qPjoo4809vvPP/8IqVQqnjx5IoTIf+8++OAD9XqVSiUqVqwoli5dKoQo3mfBzc1NzJ49W70+NzdXVK5cmUlcmzaiYcOG6ufTp08Xb7/9tkadmJgYAUBERUWJc+fOCQDizp07WvcXGBgoHB0dRWZmprps6dKlwtraWiiVypd+ZoQoSOIOHjyorrNnzx4BQP2Z8Pf3F6NGjdI4drNmzTT+kFarVk1s2rRJo8706dOFv7+/EEKI5cuXCycnJ/U+n8aqrySuVatW6ud5eXnCyspKfPjhh+qy2NhYAUCEhYW99HV/us9n3yshhBg/fryoW7euRtk333yjkcS97DsWFRUlAIjTp0+r11+7dk0AKFESN3HiRPXzsLAwAUCsXr1aXbZ582Zhbm6uft6+fXvx7bffauznp59+Em5ubuoYbW1tRXZ2tkadatWqieXLlwshCidPz8bzfBK3atUq9forV64IAOLatWtCCCH69esnunTporGPgQMH6jWJe/bzIIQQTZo0EePHj9eIeevWrWLAgAGidu3a4v79+8U6NpWMTt2pgYGB2LJli04tf/9FlSpVQpcuXbBmzRoAwO7du6FQKNCnTx+Nev7+/oWeX7t2DQBw4cIF3Lx5EzY2NrC2toa1tTUcHR2RnZ1dqMmeDOPWrVvIzc1Fy5Yt1WWmpqZo2rSp+n0CNN9HR0dH1KxZU+N9XLdunfo9tLa2RqdOnaBSqRAdHa3ern79+urHEokErq6uSEhIUO/jRZ+FtLQ0xMbGolmzZup9mJiYwM/PT/8vihFq3Lix+vGFCxdw5MgRjfejVq1aAPLfb19fX7Rv3x716tVDnz59sHLlSqSkpGjsz9fXF5aWlurn/v7+yMjIQExMTLE/M4Dme/70zjZP3/Nr165pvJ9Pj/NUZmYmbt26haFDh2qcy4wZM9S/D9euXVN382vbx6t6Nn6ZTAYnJyfUq1dPXfZ0toKEhISXvu5PPfteAUBUVBSaNGmiUda0aVON5y/7jl27dg0mJiYa+65Vq1aJuxKfPd+n5/b8+WZnZyM9PV0d17Rp0zTiGj58OGJjY5GVlaW+u5GTk5NGnejoaJ1+41/0eYqKiir0uj3//FU9e/ynMTw9/lOff/45Tp06hWPHjsHd3V2vx6d8Ol3YoFQqMXv2bOzbtw/169cvdGHD/Pnz9RKcMRk2bBg+/PBDLFiwAGvXrkW/fv00fvhfJiMjA40bN9Y6dqNChQr6DJUMKCMjAyNGjNB6cc8bb7yhfvz8d0YikajvfMLPwquxsrJSP87IyEC3bt0wa9asQvXc3Nwgk8lw4MABnDhxAvv378cPP/yAb775BqdOnULVqlX1Gtez77lEIgGAQne7KUpGRgaA/HFOzyd7MplMTxG+mLbPbFHn9LLX/aln36vietl37Pr16yXepzbazu1F72FGRgamTp2K3r17F9qXubk5MjIy4ObmpnVmB13Gqr3K50kfXvQb9lTHjh2xefNm7Nu3DwMHDiy12MoTnZK4S5cuoWHDhgBQaFD30w/Tf5mZmVmhSY07d+4MKysrLF26FHv37sWxY8cKbXfy5EkMGjRI4/nT17FRo0bYsmULKlasCFtbW8OeAGlVrVo1mJmZ4d9//4WHhwcAIDc3F2fOnNGYUubkyZPqhCwlJQXXr19H7dq1AeS/j1evXoW3t7fOcRTns+Dm5oZTp07hzTffBADk5eXh3LlzaNSokc7H/S9q1KgRtm/fDk9PT5iYaP+5k0gkaNmyJVq2bInJkyfDw8MDv/32G4KDgwHkt7A8efIEFhYWAPLff2tra1SpUgXOzs7F+sy8TO3atXHq1KlCvw9Pubi4oFKlSrh9+3aRfwxr166Nn376CdnZ2erWuGf3UZqK87prU7NmTfz5558aZc9eJPJ03y/6jtWqVUv9fXjaqhcVFaVxYYQhNGrUCFFRUUXG1ahRI8TFxcHExASenp5a62j726KLmjVrFnrdnn9eGrp3745u3bphwIABkMlk6N+/f6nH8F+nU3fqkSNHilwOHz6s7xhfO56enjh16hTu3LmDxMREqFQqyGQyDB48GBMmTED16tW1dmNs3boVa9aswfXr1xESEoLTp09j9OjRAICBAwfC2dkZPXr0wD///IPo6GgcPXoUY8aMwf379wHkX4IfERGBiIgI5OTk4MGDB4iIiFBfAUuvxsrKCiNHjsRXX32FvXv34urVqxg+fDiysrIwdOhQdb1p06bh0KFDuHz5MgYPHgxnZ2f1lVvjx4/HiRMnMHr0aERERODGjRvYuXOn+n0ujuJ8Fj777DN89913+P333xEZGYlRo0YZ/I+UMfrkk0+QnJyM999/H2fOnMGtW7ewb98+BAUFQalU4tSpU/j2229x9uxZ3Lt3Dzt27MCjR4/USTmQ/70bOnQorl69ij///BMhISEYPXo0pFJpsT8zL/PZZ59hzZo1WLt2rfr34cqVKxp1pk6ditDQUHz//fe4fv06Ll26hLVr16p7PgYMGACJRILhw4erY33+qvnS8rLXvSgjRoxAZGQkxo8fj+vXr+PXX3/VuEITePl3rGbNmnjnnXcwYsQInDp1CufOncOwYcPUSbihTJ48GRs2bMDUqVNx5coVXLt2Db/88gsmTpwIAOjQoQP8/f3Rs2dP7N+/H3fu3MGJEyfwzTff4OzZswDy/7ZER0cjIiICiYmJUCgUOsXy6aef4s8//8T8+fNx48YNLF++HH/99VeZNLL06tULP/30E4KCggrNyEB6UNaD8oxRVFSUaN68ubCwsBAARHR0tBBCiFu3bgkAGgPOnwIgFi9eLDp27Cjkcrnw9PRUD4Z/KjY2VgwaNEg4OzsLuVwuvLy8xPDhw0VaWpoQomBA6/NLmzZtDH3K5caTJ0/Ep59+qn4PWrZsqR4g/XSA+u7du0WdOnWEmZmZaNq0qbhw4YLGPk6fPi06duworK2thZWVlahfv76YOXOmer22i1J8fX1FSEiI+vnLPgu5ubnis88+E7a2tsLe3l4EBweLQYMG8cKG5y46EkKI69evi169egl7e3thYWEhatWqJcaOHStUKpW4evWq6NSpk6hQoYKQy+WiRo0a4ocfflBv+3RA9+TJk4WTk5OwtrYWw4cP1xic/qLPjBAFn5unA/OFEOL8+fMavx1CCDFz5kzh7OwsrK2tRWBgoBg3blyhQe4bN24UDRo0EGZmZsLBwUG8+eabYseOHer1YWFhwtfXV5iZmYkGDRqI7du36+3ChudfV22fYzwzAP9Fr3tR+xRCiJ07dwpvb28hl8tF27Zt1RdnPHvBxsu+Y7GxsaJLly5CLpeLN954Q2zYsKFEF4M9ex5CFPz2Pvs6antf9+7dq74S1tbWVjRt2lSsWLFCvT49PV18+umnolKlSsLU1FRUqVJFDBw4UNy7d08IIUR2drZ49913hb29vQAg1q5dWygebbGkpKQIAOLIkSPqshUrVgh3d3dhYWEhevbsKWbMmCFcXV2Ldf7FubDh+feuR48eIjAwUP38+ddwy5YtwtzcXGzfvr1YMVDxSITg5FL68s8//6B9+/aIiYkpdEsyiUSC3377jbdFMmJHjx5Fu3btkJKSovN8S2RcBg8ejNTUVN4+qAzNnDkTy5YtQ0xMTFmHYtSGDx+OyMhI/PPPP2UdCumRTmPiSJNCocCjR48wZcoU9OnTh/eUJSLS0ZIlS9CkSRM4OTnh33//xZw5c0o0HIHyzZ07Fx07doSVlRX++usvrF+/vtDk0GT8dBoTR5o2b94MDw8PpKamYvbs2WUdDhGR0bpx4wZ69OgBHx8fTJ8+HV988cVL7wZQEhs3btSY4uPZpU6dOno7Tlk7ffo0OnbsiHr16mHZsmX4/vvvMWzYMABAnTp1inwNSnp3Cypb7E4lIqJy4/Hjx4iPj9e6ztTUVH2V8X/Z3bt3kZubq3Xd01u/kXFgEkdERERkhNidSkRERGSEmMQRERERGSEmcURERERGiEkcERERkRFiEkdERET/324dkAAAAAAI+v+6HYGukCGJAwAYkjgAgCGJAwAYCqhW6Hh1JGWEAAAAAElFTkSuQmCC\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"## Train Test data split"
],
"metadata": {
"id": "8q_jSc9Z7LcY"
}
},
{
"cell_type": "code",
"source": [
"df_shuffled = df.sample(frac=1, random_state=42)\n",
"\n",
"split_index = int(0.8 * len(df_shuffled)) # 80% training, 20% testing\n",
"\n",
"train_data = df_shuffled[:split_index]\n",
"test_data = df_shuffled[split_index:]"
],
"metadata": {
"id": "OkQLv17J8l-S"
},
"execution_count": 382,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Data Cleaning"
],
"metadata": {
"id": "Ya79mhf77qBs"
}
},
{
"cell_type": "markdown",
"source": [
"* Cleaning Required for `body` and `subject` Columns: Textual data in the `body` and `subject` columns needs preprocessing before model input.\n",
"* Removed tokens which are unnecessary.e.g `\\[Your Name\\]`\n",
"* Stopword removal\n"
],
"metadata": {
"id": "c4KoVcAPyPxJ"
}
},
{
"cell_type": "code",
"source": [
"df.iloc[0]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "pyaGkM5a7uNl",
"outputId": "c58c33c7-4815-4f45-9efe-29876d87e09c"
},
"execution_count": 383,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"subject 🚀 Propel Your Marketing ROI with Advanced Anal...\n",
"body Hey [Recipient's Name],\\n\\nReady to see your m...\n",
"opened 0\n",
"responded 0\n",
"type1 0\n",
"merged_meeting_link 0\n",
"Name: 0, dtype: object"
]
},
"metadata": {},
"execution_count": 383
}
]
},
{
"cell_type": "code",
"source": [
"df.iloc[0]['subject']"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"id": "OByVXsTh73GF",
"outputId": "557e3642-eeb7-4238-ec1c-d6a9a97e6c63"
},
"execution_count": 384,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'🚀 Propel Your Marketing ROI with Advanced Analytics!'"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
}
},
"metadata": {},
"execution_count": 384
}
]
},
{
"cell_type": "code",
"source": [
"df.iloc[0]['body']"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 69
},
"id": "AXszmSH08Sf3",
"outputId": "edf19d73-2b2d-4543-bdaa-49b7e60f6e9c"
},
"execution_count": 385,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"\"Hey [Recipient's Name],\\n\\nReady to see your marketing performance soar? With our cutting-edge Marketing Analytics services, your business can harness the power of data to drive decision-making and skyrocket ROI!\\n\\nQuick question - are you leveraging your data to its full potential? Let's talk strategy! 👉 [meeting link]\\n\\nBest,\\n[Your Name]\""
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
}
},
"metadata": {},
"execution_count": 385
}
]
},
{
"cell_type": "code",
"source": [
"def clean_text(text):\n",
" # Remove [Your Name] and [Recipient's Name]\n",
" text = re.sub(r'\\[Your Name\\]', '', text)\n",
" text = re.sub(r'\\[Recipient\\'s Name\\]', '', text)\n",
"\n",
" # Remove newline characters\n",
" text = text.replace('\\n', '')\n",
"\n",
" # Convert to lowercase\n",
" text = text.lower()\n",
"\n",
" # Remove punctuation\n",
" text = text.translate(str.maketrans('', '', string.punctuation))\n",
"\n",
" # Tokenize the text and remove stop words\n",
" stop_words = set(stopwords.words('english'))\n",
" tokens = word_tokenize(text)\n",
" tokens = [word for word in tokens if word.isalnum() and word not in stop_words]\n",
"\n",
" # Join the tokens back into a string\n",
" text = ' '.join(tokens)\n",
"\n",
" # Additional cleaning if needed\n",
"\n",
" return text"
],
"metadata": {
"id": "WVtVqjbk9Q30"
},
"execution_count": 386,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df['subject'] = df['subject'].apply(clean_text)\n",
"df['body'] = df['body'].apply(clean_text)"
],
"metadata": {
"id": "0mm2SN16BRue"
},
"execution_count": 387,
"outputs": []
},
{
"cell_type": "code",
"source": [
"df.head(10)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 359
},
"id": "Hz52JPZCCH8S",
"outputId": "082fb3ba-a8a9-4307-a503-c4023480d75d"
},
"execution_count": 388,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" subject \\\n",
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"1 data superpower unlock insights us \n",
"2 turn marketing data decisions lets explore \n",
"3 marketing success click away lets chat analytics \n",
"4 boost brands visibility proven marketing analy... \n",
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"6 last call blueprint marketing success awaits \n",
"7 confident data \n",
"8 roi precision marketing analytics \n",
"9 marketing strategy deserves best analytics \n",
"\n",
" body opened responded \\\n",
"0 hey ready see marketing performance soar cutti... 0 0 \n",
"1 hi im reaching believe last message mightve sl... 1 0 \n",
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"6 hello hope message finds well noticed opened l... 0 0 \n",
"7 greetings success business last month analyses... 1 0 \n",
"8 hi want see better return marketing efforts cu... 0 0 \n",
"9 hello improve marketing effectiveness datadriv... 1 0 \n",
"\n",
" type1 merged_meeting_link \n",
"0 0 0 \n",
"1 0 0 \n",
"2 0 0 \n",
"3 0 1 \n",
"4 0 0 \n",
"5 0 0 \n",
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"8 0 0 \n",
"9 0 0 "
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"</div>\n",
"\n",
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]
},
"metadata": {},
"execution_count": 388
}
]
},
{
"cell_type": "markdown",
"source": [
"## EDA"
],
"metadata": {
"id": "DNbMZk9dB_ey"
}
},
{
"cell_type": "markdown",
"source": [
"* The objective is to understand the impact of specific words on customer behaviour, particularly in terms of opening emails or clicking on links. To achieve this, I plotted word counts against both opened and non-opened emails.\n",
"* Recognizing that a **mere word count might not provide nuanced insights, I opted for a more comprehensive approach by considering the percentage of word occurrences** relative to opened and non-opened mails.\n",
"* This **in-depth analysis covers both the `subject` and `body` fields** since user decisions to open emails are often influenced by the `subject` while link clicks depend on the content within the `body.`\n",
"* Key findings indicate the significance of certain words, such as `analytics`. **Only 23% of opened mails contained `analytics` in their subject, in contrast to approximately 40% in non-opened mails.**\n",
"* A similar pattern is observed for emails with clicked meeting links – **only 15% featured `analytics` in their body, while around 32% of non-opened mails contained this keyword**.\n"
],
"metadata": {
"id": "TsaiziVMyeTa"
}
},
{
"cell_type": "code",
"source": [
"\n",
"def plot_comparison_graph(col1, col2):\n",
" true_sentences = df[df[col1] ==1][col2]\n",
" false_sentences = df[df[col1] == 0][col2]\n",
"\n",
" tokenized_words_true = [word_tokenize(sentence) for sentence in true_sentences]\n",
" all_words_true = [word for sublist in tokenized_words_true for word in sublist]\n",
" word_counts_true = Counter(all_words_true)\n",
" top_words_true = word_counts_true.most_common(20)\n",
"\n",
" tokenized_words_false = [word_tokenize(sentence) for sentence in false_sentences]\n",
" all_words_false = [word for sublist in tokenized_words_false for word in sublist]\n",
" word_counts_false = Counter(all_words_false)\n",
" top_words_false = word_counts_false.most_common(20)\n",
"\n",
" words_true, counts_true = zip(*top_words_true)\n",
" words_false, counts_false = zip(*top_words_false)\n",
"\n",
" counts_true = tuple(element / len(df[df[col1] ==1]) * 100 for element in counts_true)\n",
" counts_false = tuple(element / len(df[df[col1] ==0]) * 100 for element in counts_false)\n",
"\n",
" fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(16, 6))\n",
"\n",
" axes[0].bar(words_true, counts_true, color='green')\n",
" axes[0].set_xlabel('Words')\n",
" axes[0].set_ylabel('% Word Count')\n",
" axes[0].set_title(f'top words for {col2.upper()} (for True {col1.upper()})')\n",
" axes[0].set_xticklabels(words_true, rotation=45, ha='right')\n",
"\n",
" axes[1].bar(words_false, counts_false, color='orange')\n",
" axes[1].set_xlabel('Words')\n",
" axes[1].set_ylabel('% Word Count')\n",
" axes[1].set_title(f'top words for {col2.upper()} (for False {col1.upper()})')\n",
"\n",
" plt.xticks(rotation=45, ha='right')\n",
" plt.tight_layout()\n",
" plt.show()"
],
"metadata": {
"id": "MyTI9TgSC0XL"
},
"execution_count": 389,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plot_comparison_graph('opened', 'subject')\n",
"plot_comparison_graph('opened', 'body')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 907
},
"id": "PDA2f-pOF0Ws",
"outputId": "b1195a0f-a45f-4619-c2e1-2bb4ede3ed87"
},
"execution_count": 390,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-389-6e5e57b33386>:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
" axes[0].set_xticklabels(words_true, rotation=45, ha='right')\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1600x600 with 2 Axes>"
],
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\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1600x600 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"plot_comparison_graph('merged_meeting_link', 'subject')\n",
"plot_comparison_graph('merged_meeting_link', 'body')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 907
},
"id": "tzdRSFI6LT8R",
"outputId": "43210014-348e-42cd-8e8f-5dbf1ed94702"
},
"execution_count": 391,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-389-6e5e57b33386>:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
" axes[0].set_xticklabels(words_true, rotation=45, ha='right')\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1600x600 with 2 Axes>"
],
"image/png": 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wjDFm//79pmLFiqZatWp258S9Vhk/2Nbzr126dMn8+eefJj093fTu3dvcf//9th2/devWxmKxmPbt29tOzZQXMn7RTp8+3bz66qvm9OnT5uLFi6ZLly6mQYMGZvLkybajqL788kvTpEmTPB/UZfySPnXqlElJSTG7du0yPXv2NM2bNzcVK1Y07777ri0J+Oqrr4wx+fPlZI1l5cqV5oUXXjC7d+82xlw+wrZVq1amcuXKZvv27bb1Fy1alKf/MH744QdbQjVx4kTz+eefm+3bt5tGjRqZG2+80ZQpU8Y8+OCDZt68eebAgQMmICDA7tyr+enTTz81/fv3N2XLljUdO3Y0r776qmnWrFm+Tpu3vh+JiYm2fX/8+PGmT58+ply5cuaRRx6x7cfnz583/fv3NxMmTMizU8189dVXdkcRfv7556Zp06amWrVqZtSoUeb48eNm48aNplChQubhhx/O1/PmX/lDhfWcs9YfKVq1amVGjhxpnn76afP444+b4cOHmzfffDNfYlm+fLnx9fU1t956q6levboJCwuzO9+oMZeTkurVq5tGjRrl20B73bp15rXXXjMnTpwwhw4dMs8//7y54YYbzMMPP2x+/PFHk56ebg4dOmQaNmxo/vrrrzzr1/p8Mj6vnTt3mrNnz9rOOfvjjz+a7t2724osDRo0MDfddFOefodntGjRIlO2bFlTsWJFU7VqVfPKK6/Ylr355psmOjraNG7c2AwcONBYLJY8/wEj42sxceJE06pVK1OlShUzePBg25F91kQsKirKPPnkk3leJLd+X3z11Vfm3nvvNTVr1jRPPfWUWbZsmTHm8tT1W265xTRo0MDs3r3bjBw50tSoUcPEx8fnSxwZrV692tx4443G39/f3H333bYfJz744ANz8803m8TExDyNIWMc+/fvNwcOHDCXLl0yDz30kImKijK+vr6me/fu5t133zVHjx41Dz74oOnb9//YO+9ArPr//5+LjBJRCJG9Cdl7RkpS7ibR0KahFO20i/bUutulkupuamhPJO2FlKKiYWQ+f3/4Xe/7Oq7u7+fzuTuX60rn8U8551zXeV/nvMfr9X6tMEbvz2tknj17NhISElBZWQkjIyNoamqiTZs2GD16NA4dOoQPHz5ATk5O4Ckf6+vr4eHhgeDgYNrxz58/IzQ0FBwOB4MHDxZoG1h+H5pavwBEQ7YXFT0HEL5c/fLlS7Ixn5ycjB49eqC2thYXLlyAtbU1lJSUiLctl3HjxmHAgAGMr5HCliNFUXbiZcSIEVBWVsbGjRvJBjKXUaNGwcHBQWCbc0ePHoWkpCRiY2Mxbtw4dOvWDVJSUjhy5AiAv9NS2djYMB5hyZUVXr16hby8PBJFmpeXh4kTJyIxMRHv3r0jere/vz9WrlxJ+yyT7UhNTYWOjg4WLlxIxu7169fh6uqKnj174uTJkwCAGTNmID4+nrH7i6rOJyyZ+kc8fvwYurq6fH2wpKQEmpqakJKSokVOMI2wZDjerB27d+9GaWkpSkpKYGBgAFNTU9y7d482FiorK6Gjo8NoW3j7RGVlJcmKUFtbi5CQEDg5OWHFihVEvzt+/LjAU0Fxf/OtW7dgbW2NrVu3ok2bNjTD56VLlxAaGkrbP2OaxMREhISEwNjYGMuXL8fjx49RU1ODVatWoVOnTrTMHoI0/k2YMAEcDgeenp58qafWr1+PFi1aYNq0aQJ3ShZFWMOGAPhRZy4qKoK9vT2ioqJQUVFBKzbbt29fuLi4wMfHh5HicqWlpVBWVsaiRYtw7NgxiImJ4dixY+R8VVUVXF1daaFjEydOxI0bNwSWpiEmJgYqKipYtWoVzQOBd6OluroaXbt2xR9//CEwr7Ldu3ejd+/etFy7T58+RXx8PGxsbODu7g4OhwM3NzeBeFJyv/PQoUOQkZHBvHnzaJPwt2/f4ObmBk1NTRw6dAiTJk2CgoICzWvhZ3j58iUsLCwQHByMyMhIiImJkRyz169fx9KlS3Hs2DHyXj5+/Ah7e3ucP3+ekfs35uTJk9i7dy9u375NDAVfvnxBXl4eQkJC0LdvX3A4HHA4HIEUgOW+j+PHjyM0NJRsTiYnJ0NTUxO2trbk2VdXV2PatGnQ1NRkbJy8f/8e2traGDJkCF68eIHHjx9DXl4e8+bNw/jx42FpaYmePXsiPz8fN27cgLi4OEaPHi0QLx7us7h9+zaOHj2K79+/o6qqCrNnz4a4uDiUlZUxceJEhIaG4o8//kDv3r3Rv39/gXjflZSUYPTo0di6dSuqqqrw+vVruLu7Q1dXl09oefHihcBSuHELhc+ZM4dEUtXX1/MJcLGxsTA1NWU8P3JeXh68vb0BNPRRrtHz2bNn6NGjB2RlZRESEoLTp08DALKzs2FmZoaCggLG2sDtF58+fYKRkRG2b9+OCxcuYNGiRZCQkMCMGTPItfv27cPo0aMREBAgUK/46dOno127dtizZw+2b98ODw8PWFhYkBo4379/x7x586Crq8toiDT3WRw9ehStWrXCzJkzsWvXLnh4eEBPTw/3799HXV0drl69Cjs7O7Rv3x7a2tqMF7bjLYA6ffp0bNy4kfTPr1+/8nmeRkVFITAwkHEPHm47jhw5QjzDa2tr8fnzZ1y4cAEpKSm0dXTgwIGMFoD88OEDVFVV4eLigqioKMjIyJD5qKioCGvXrkVaWhr53XV1dXBxcWkSQ/2KFSvg7OzMl/JyxYoVsLCwgLm5eZNF4LE0H4StXzRGWLK9KOk5oiBXd+3aFe3atUN8fDzExcVpab9Gjx5Navi9f/8e7969w9SpU6GoqIiHDx8y1gZAdORIUZKd3rx5g7dv39Ke9YABA2BsbIzt27cT718ugopArq6uhr+/P2JjY8mxiooKTJgwAVJSUuQdPHr0CH/88QdJLcok3EL22traMDc3J2mveOeFmpoaklpPUHsSR48ehbS0NDZs2MCXpvP69evw9vaGpaUlPD09ISUlhVu3bjFyX1HS+XgRlkwN0N89d3378uUL3N3d0a1bN1p0+KdPnxAcHIzExESB1yxqahnuzp070NLSQmpqKiZPngw5OTnSNz98+AANDQ24uLjw6cBVVVWMOeE2NnT5+vpCVVUVw4YNw9WrVwGANl9VV1ejW7du6NWrl8Cijxs7kXIdFBITE8mxyspKdOvWDUFBQQIzKMTGxqJ9+/ZISEjA+vXrIS8vjz/++ANlZWX48uULVq1aBUtLS/Tt21cg929MfHw8xMTEfpjic9myZXB2dv4tI8JZwwbD8A6o58+fo7CwkCjV3FoKCxcuJMV2Kisr0bdvX2zduhXm5uZ8oWb/hu/fv2PXrl2QlJSElJQUn+BQWVkJY2NjBAUF4ezZs5g8eTKUlZUFFkZ26NAhqKqqIiMjgxzjfU5lZWXYunUr/P39YW5uTtK+MDE58X7HjRs3MGDAACgqKmLQoEF8uXYfP36MtLQ0dOnSBerq6jh69CgA5lNF3L59G+3bt+ebjLheGfX19fDz84O+vj6MjIxoz+1nqampwYEDB6CkpIRWrVrh5s2bP7yuqqoKhYWF6NGjB+zt7QUSuRIdHQ0VFRUoKirC0tIS0dHRNOtyTU0NPnz4gPXr18PU1BRxcXEAmLeCHzlyBNLS0liwYAGtkOCqVaugo6MDd3d39O3bF7169UK7du34ogZ+loyMDNjY2CAyMhLz5s2jpWr566+/4OHhgR49eiA/Px83b94Eh8PBhAkTGH0nvAa3du3aYc6cOUSY/Pz5M5YuXQoxMTG+8HSm3gXvGLt37x6UlZVhY2ODc+fOkeOfP3+Gm5sbdHV1GVfGf8S1a9egoKCApKQk2nHeoszp6ekYMWIE2rZtK5DCpJcvX4aJiQmMjY0hLi6Offv20c43VvomTZoEJycnxou5nTt3DrGxsYiMjCRj9Nu3b1i7di3ExcVpxg0AjHo9lpaW0v4+ceIETExMiKKZlpYGaWlp2NjYwNTUlHjwV1ZWYtu2bT89Tk6cOEEzahUXF8Pd3Z0odxUVFVBSUvphmPjly5cFppAeP34cUlJScHNzg5qaGjw8PPj6R1ZWFiZPngx5efl/THH4sxw7dgwyMjLE2/JHFBUVYcqUKWjbti3jY/fFixeQkZGBjIwMmZsbK0KVlZV4+/Ytunfvjs6dOwtk7nz9+jUePnyI169fo76+Hk+fPkWnTp0wZMgQWq7sSZMmYcaMGXyeuiws/wlR0C94EaZsL0p6jqjI1UZGRhAXFyf14Xjp06cPDA0NIScnBycnJ+jo6DAuywpbjuRF2LITb1SAra0tjIyMoK+vTxuDXOPGzp07aXKlIEhNTcWyZctgbGxMore4aW/KysrQpUsXREREENmNyfpg3GdRWFiIDh06ICkpCQcOHMC4ceMgJiaGnTt3kmuTk5PRs2dPqKurM94/uZSUlMDLywvLli0D0DBXFBcXY/PmzaTO4/3795GQkIBx48bRNtaZQNg6n7Blal54M1hER0fD19cXmzdvRnFxMfLz86Gmpobu3btj586dyMnJQUxMDOzs7Bg1/omKDPfgwQNERkZCUVER8vLyxLDI9cgvLi6Guro6XF1dfxiVwOR7mTFjBtq3b49t27bh2rVr6NChA1xcXEi6Za7+161bN8bXdl4SEhLQrVs3jBs3jkSVFRYWwtbWFvr6+li9ejUSEhLg4+MDU1NTIvsz3Y7bt2/DwMCAGLnu3LkDcXFx2txVVlaGBQsWICwsTCBrWnZ2Nq5cuYKcnBzSZydPngwJCQns2rWL73redJ2/E6xhQ0BMnz4dGhoaMDQ0hK+vL5mEN27cCHFxcQQEBJCQLlNTUwDA2LFj4e7uzsjkdPfuXeLpvnTpUnKcO+izs7OhrKwMHR0daGtrMyZA/Ch0dfny5fDz80NtbS25P2+NicLCQkyePBkDBw4k55lK88Nl4sSJMDAwQGRkJIKDgyEjI4NBgwb9cDOyoqIC7u7uGDJkCKNt4LJ7927Y2dkBaFDODhw4AH9/f1haWmLSpEnkuidPnjAats+daM+fP4+OHTvCxMQE/fr1I4sz95l///4dO3bsgKenJ+zs7MiCxeSimZWVBQ8PD2RkZCA/Px/x8fGws7PDiBEjfrhArly5EoqKinwC2c9SUFCATp06/WMY/JEjRzBnzhwEBQVh3rx5Aqu9kpGRATs7O2hqamLq1Km0c8ePH4e7uzuCgoKQm5uLO3fuMC5oAw0b+W3atMGmTZv4Nqa/fv2KmTNnQlJSklbAjKkFk/s9XA/GHj16gMPhYOPGjbR+9/nzZ3h5eUFBQYHRtE8/YuHChfDz8wPQ8PtPnDiBAQMGwNHREcePH0d1dTXi4+PRo0cPgUYnLF68GBwOB7q6uuRYY6Xz2rVriIqKgoKCAuPFUauqqjB9+nSIi4vD2tqado4r3EpLS9PmLqbo2bMnLbQXaFA4o6OjATQoZIqKikhKSsKVK1egrq4OU1NTmucu8O/nLl7vOu6YKysrg7W1NZ48eYJXr16hQ4cOGD58OPnM6dOn8fz58391v/+WgoICxMTEYNOmTQAajPZhYWGwtrYmGzhZWVkYPXo0LCwsGOsTjQt5fvr0CQ4ODqRQOHeDYN++fSRH9YkTJ9C3b1/o6+sLxPiXnZ2Ndu3aQUVFBV5eXnzrVU1NDXbt2gV7e3s4Ozszup5x562UlBTo6+vD2NiY9JfXr1/j0qVLsLKygr29PXx9fdG7d2/IysoKfO5iad4IQ78QRdleWHoOL6IgV1dWVqKqqgp6enrQ0dGBnp4eLl26xPfdN27cwO7duwVqcBemHNkYYctOZ86cQcuWLbFhwwY8f/6c5D/nlU9CQkLQvn177N27V2DP4e7du2jbti0xGgQEBBCva+49Q0NDSZF5QXD+/HmsXLkSMTEx5NjHjx8RGxsLDodD6ijm5OQgLi6O5mTGNCUlJdDT08P69etRVVWFqVOnwtnZGW3btkXLli1x6NAhcq2g3omwdD5hy9Q/IiUlBbKyshg5ciSmTZsGNTU1dO3aFdXV1Xj8+DF8fX2hq6sLdXV1dOzYkVFnT1GQ4Xj3OlatWgUOhwMtLS1azSzuXFpcXAxNTU0YGBgwlsmjcbqiZ8+eoVOnTkhLSwPQsG5ISUlh69atABqeWWVlJcaPH4/Q0FCB7dslJiZCSUkJY8aMgZOTE6ysrLB27VoADbpHv379YGdnBw8PD4wcOVJg7QCAmzdvwtbWFkCDE0nr1q2xfv16AA16MPdZlZeX02QgpoiNjUWnTp2InhMQEEC+Py4uDpKSktizZw/f5343owbAGjYYg7cD//XXX1BRUUFqaipWrVoFNzc3qKurE+XjzJkziIqKQlBQEMaMGUMmlZ49e2LUqFE/1RG57aipqcHVq1exY8cOiIuL0/JDcgd9RUUFcnNzGfNg2rVrFywtLfkG87hx40ixH4C+4XDt2jV8/PgRZWVl5Hcz7cWUnp4OJSUlmhfV9u3bYWZmhpCQEJrlm/sukpOTYW5uzmhqGe7vO3DgAIyNjTFlyhRSqCwkJATLli2DjIwMzUudCRq/j9LSUrx58wa7d++Gra0tgoOD+byFDh8+jKSkJIEsFPv27UNgYCCGDh1Knkl5eTmWLVsGW1tbjBw5kigf3PdRVFQEMzMz4k3DFLm5udDU1KRt2P0oLLYpFofs7Gxoa2vD2dmZzxvjxIkTsLCwQP/+/RlftLm/be7cuQgICKCd4x2LNTU1iI6ORtu2bQWSq//y5cs0pc/Pzw+qqqo4f/487TeXlpaie/fuAt88TkpKgo6ODlauXInu3bsjICAAAQEBGD58OMTFxVFcXIzi4mLGoyO4cPve4cOHMWfOHNjZ2cHGxoaMVe4YefLkCSnuJ6iinK9evcLcuXPB4XCIMMelrKwMy5YtQ7t27fDhwwdGx8qrV6/IHMAb/vz582dUVVXBz88Pc+bMIcc9PT2hp6dH6jgw0ZaMjAzY2toiIiICOTk5qKyshImJCTZu3Ag9PT1ERESQcZKbm4v+/fuT3MyCICsrC76+vrCzs6Nt1GVmZiI8PBzW1tZkEzI7OxuFhYWM3Pf8+fOQlZWlveMvX77Aw8MDq1evRn5+PuLi4uDh4YG2bdsSb6rKykrs2rWLeHr9LD9SFkpKSvDw4UNoamrC3d2dNl/U1tbi7t272LdvH032YIqLFy9CVlaWbNStWLEC4uLipN5BZmYmNm/ejF69emHs2LECL1zO0vwQtn4harK9MPWcxm3gImy5Gvg7mtTBwQE6Ojp8xg1BbPhwERU5EhAd2WncuHEk0jwvLw86OjpkU5m3/wwdOlRgKZeeP3+OWbNmkc3zjRs3wt7eHvHx8bTc7IMHD8aQIUNQXV3NuL5TUVGBYcOGgcPhoEuXLrRzXOOGhIQE2TgVdOFdoCGFXps2bSAvL4+ePXuSXP0BAQH4448/BH5/QDg6nyjI1Ly8fv0a5ubm2LhxI/n+1q1bY8qUKaQflJeX4/Xr17hz5w7jteoA0ZHhLly4gGPHjiE9PR1RUVEwNDQkBj/g73FRXFyM4OBgRsZJaGgoqSnL5fnz57CwsADAX6C7rKwMhw4dQkVFBWpqagS2bwc0RI1w02c+e/YM0dHRMDAwoBnFP336RDNWM73Gcb/v/PnzUFdX/2Ftj7Nnz6J37940x1cmx0lCQgIUFRVJHa9JkybxpWePi4sDh8MRSLrRXw3WsMEwO3bswMaNG8kkDTR4IDg7O6NDhw5kUub1ZCkqKkJcXBzatWv3r9M08IZf8wpM5eXlWL9+PcTFxbFgwQJyfPPmzUhNTf1X9/q/4E5uvBvQZ8+ehZ6eHlauXEmb/D58+ABvb2+Be0dcunQJKioqfILr5s2bISYmhrCwMD5PncGDB8PS0vKnQw1/9Hs+f/6M6Oho+Pj4YOzYsbhz5w4AID8/H7a2tox6lfFO8ufOncP58+eJ1yw3rNTW1hZ9+/YlKQ0mTpxIak0AzC5YFRUVGDFiBDp06AAHBwfaufLyciQkJMDBwQH9+vWjtT0uLg4tWrRgtIhafX09bt26BUlJSdJfeRfIe/fuEc/8piI7OxuWlpYYMWIEn6B75swZxjYHeeH20ZEjR6Jr164A+JX2jIwMfP/+HTU1NQJJ5fD06VNs3LiRL3erl5cX1NXV+YwbgjI08c7Lubm5GDFiBLS0tDBs2DCkp6cDaHhH1tbWAsk/DPz922pqamieNFeuXIGFhQVsbGxotRIuX76MjIwMlJSUMHr/srIy2vxXUlKC2NhYyMjI0NY3oGHsMnV/LrzzzqpVq2Bra0sLP3/37h00NDSI8vHhwwf069cPhw4dYrx/ZGZmonPnzhg2bBgKCwuxdu1acDgcdOvWjXbdtGnTYGZmJtDcv2fOnIG7uztat25N8+gCGoweQ4cOhba2NuPre2VlJXn+3HmIWyjY2toaUlJSCA4ORlJSEvLy8tCnTx+MGjWK0TbwzkunTp3C7t27aSm2bt++DU1NTXh5eZFaAyNHjqRF5DG1nnG/Z/LkyRg6dCiAhlzqOjo6tN/Nu3nUFBs2LM0XYekXgGjI9qKi54iCXM19FgUFBXj27BmfbOzg4AA9PT2kp6ejvr4e8+fPJ3nQBVk/UJhypLBlJ16+f/8OOzs7rFq1Cl++fEGHDh0wYsQI0sYNGzbg+PHjjN+Xly9fvsDGxgZKSkqYMGECgIZnM3nyZNja2sLLywsLFy5EeHg4WrduLdCiuzk5ORgzZgzExMT4Nt8+ffqEyMhIyMvL48uXLwIpFP7ixQtcu3YNDx8+JAaukydPYt++ffj+/TsZj+Hh4YiJiRFo4V9emlLnEyWZmsvr16/RuXNnlJeX49mzZ3wR0Ddv3hRY2k5RkuFu3rwJIyMjUvMnMzMTI0eOhKGhIfbu3UuuW7lyJW2++tn2TJw4kS96MDc3F6qqqoiNjYW8vDzNme3OnTvo0qULrY4f033j1KlTuHjxInx9fUkaNKBhDEdHR8PIyAirVq3i+xzT7di2bRuMjY3J33/88Qc4HA4tddz3798REBCA4OBggcwZ5eXlJJ0o0ODYIisri82bN5PzXDZs2CBQ54VfBdaw8RM4OzvTPDNzc3NhaGgIDofDt0GXk5MDV1dXdOzYkSaAFhUVISYmBjo6Ov86TQN3MJ85cwZBQUHw9fVFSEgI6eDV1dVYv349WrRogbCwMIwaNQrS0tKMhdLV19fTJtcbN26Aw+GQzYSSkhKEhobCzc0Ns2bNQnFxMe7cuYOAgADY2toyOhB5c8px/3/p0iUoKiqSUDHuJF5TUwN9fX2YmZkhMjKS5gng7+/PVzDq37bl6tWrmDNnDmJiYkh/qa2t5fPmmjVrFoyMjBjxsP3jjz9oYWlc7xQtLS20bNmSCC5VVVXYvn07bG1tYWJiAh8fH6iqqgp0cuR66GhoaPDl5i8vL8fs2bMRERFBWyQOHTr0UwV4eftD48XH19cXlpaWfJ4gUVFRGDFiBE2oaQq4m6gRERFNUkuCy8KFCyEnJ0dSFPBucE+ePJkUkWOaFy9ewNzcHO3atSOpdXifuZeXF7S1tXH69GmBbgyeOnUKYWFhcHJywoQJE0i4c+NcrnFxcbCwsOArIM4E3Gd+4sQJ9OvXD8bGxpg0aRLZELl06RJsbGxgZWWFZ8+eIS4uDkZGRox5MXHvzw2FNzMzg7OzMw4fPozy8nJ8/foVcXFxNMFK0Hz//h05OTlo3749/P39yYbI58+f0atXL3h5eWHjxo3w8fGBq6srGd9MC5mZmZmwtLREREQEzp07h8mTJ0NcXBxLly7F0qVLMXr0aMjKygok3VJj0tPT4ePjAycnJ7Kucbl9+zZGjx7NWJh6Y169egUOh4MlS5YAaBirhw4dQnJyMs3bc8CAAYiKikJdXR3jCseUKVPQunVr6Ovrk7oC3H5x+/Zt6OjooGPHjrC3t4eOjo5AZAzu/caMGYO1a9fi8+fPUFNTo21eHTlyBIcOHWpS4zhL80AU9AtRlO2FpecAoiNX89ZvMDAwgL6+PuTl5bFy5UpaIWQXFxeoqanBzc0NcnJyxIlKkAhLjhS27MTl5s2bJJp48eLF6NevH1RVVWnRUpWVlRgyZAjmzJkjkAgJXjIzM6Gvrw9LS0si09bW1mLHjh0YOHAg7OzsEBwczGjECvf3VFVV0WT5169fY9CgQWjTpg2fcaOkpITxoum8NV+0tLRI0XJra2u+eaGgoAAzZsyAgoJCk+pdQNPrfMKUqRv39aysLHTs2BGXL1+Grq4uhg8fTu5z79499O/fn/EUcaIgw/3oWfbq1QtmZmbk7+zsbIwePRra2tqYOXMmunXrBj09PUb04Mb337hxI7Zs2UKMSDNmzIC0tDRGjx5NruFu4nfv3l1ghr9JkyZBRkYGHTp0gJSUFGbNmkU7//LlS8TExEBeXp7mOMEk3Hd/9+5d2NraEnnn8uXL8Pb2hq6uLnbv3o1Vq1bBz88PpqamAqsxAgCurq5ISUnBX3/9RYueqampwfr160ntES6/u3GDNWz8SyoqKrB69WqaZ1RVVRVOnz4Ne3t7GBsb822IPnz4EIaGhnx5LN+8efOv851yJ7gjR45ATk4O48ePx8aNG6GjowNPT088e/YMQMNgS0lJgZ2dHfz9/RndfOHdoOcuygsXLoSkpCSZEN6/f4/o6GgYGhpCQkICJiYmcHFxYTTPbOOihV+/fiV/c/OY8oaKvXv3DmFhYZg/fz7k5eUZTQHFbUtKSgoUFRXh5+eHvn37gsPh8FlVjx8/jsjISLRt25aRaI2KigoMHToUEhISOHLkCPLz82FiYoI7d+7g3r17WLhwIcTExLB8+XIADf323LlzmDBhAsaOHUvaxuQm8ufPn1FdXU3Gy4cPHxAdHQ0HBwda2CvQsHgyHd7I/b6LFy9i4sSJmDdvHjGUpKenw9nZGaampkhPT8exY8dIwV1Bpfb5T2RmZsLOzg79+/dnPB8791m8f/8eBQUFRLirra2Fra0tDAwM8Pr1a9TV1aG6uhrTpk2Durq6wCIU3rx5g7i4OCgrKyM8PJwc550/ra2tYWpqSvNOYJLU1FRIS0tj7ty5WL58OXr27AlpaWnaJsGVK1cwZswYKCgoCGTzmvtejh49ilatWmHmzJnYtWsXPDw8oKenh/v376Ourg5Xr16FnZ0d2rdvD21t7Z8y+PHCnbNOnToFSUlJTJ8+HZs3b0bPnj1hZGSERYsWoaKiAh8+fMDMmTPB4XCwfft2Ru7Ny/nz50kkQlRUFGbPng0AePz4MdTV1eHr60uMSqmpqaR93bp1E6hwCTSMS2tra4wcORJnz57FmjVrYGpqCnt7ewwYMIDxEHVun3jy5Alu3LhBatAADXNZ9+7d4e3tzbd2MVm8vTE1NTWYM2cOJCUlkZiYyHeeG9mjoKDAWF5oXmX47t27cHBwwPXr11FeXo61a9eidevWmDFjBtkYKSoqQmxsLObNmyeQ9WzPnj1QV1fHhw8fMHXqVGhoaEBdXR3jxo2jbbSGhoZi6tSprGGD5X9CVPQLUZHtRUHPETW5+uTJk2jTpg1WrFiBL1++YObMmZCXl0dcXBwtTefSpUuxcOHCZi1HClt24vLx40d4eHgQnebw4cNkI53bR6uqqjBt2jR07NhR4OlUuWRnZ6NTp06IiIigRTgCDf1aEIXCT5w4gR49esDW1hb9+vVDeno6amtr8fbtWwwePBgKCgp8ThmC4Nq1a5CRkcGGDRvw7NkznDhxAt27d4eCggKp43H+/HmEhIT8lIPpzyJInU9UZGpu37h27RqSkpLI8dDQUHA4HPTr1492fVxcHOzs7BjN1MBFVGS4CxcukH2GL1++wMTEBOPHjyfnnzx5glmzZsHKygpBQUGMvY/Gjp6enp4wMjLC3r17UV1djVevXiE0NBTy8vKIjY3F1KlTSYFuQelZr1+/ho2NDbKysnDr1i3MnDkTLVu2pNXPAhoyPKxZs0Zgjo7csVBWVoaJEyeia9euZH27cuUKhg4dCnV1dXh4eGDo0KE0Z2mmOHz4MO7du4eamhqEhITA3d0dCgoKtOiZgoIC+Pv7N5mT4a8Ca9hggHnz5pGOVV1djfPnz6NTp06ws7Ojhb0CDd6OPzsYd+7cScvv9uDBA5iamhJFo7CwEBoaGmjVqhVMTU1pwlN5eTlfpMDPcO7cOQwcOBC1tbWIiopCp06dSM75xYsXQ0xMjLSrsrISX79+xZkzZ4igCTAzGfBOsEuXLoWXlxesrKwQGBiIV69eoaioiAgzCQkJSEpKgo+PD3x8fAAAxsbGJFT333LixAma0Hjjxg2oqqqSBfzt27eQkpKCmJgYFi5ciNraWlRVVWHOnDno27cvo2HAX758waRJkyAuLo7p06dj8uTJ5Fx9fT2WL1/+Q88/LkxO0EuXLiXF0WNjY4nQVlRUhIkTJ8LBwYGWG5m3nUxy+vRpiIuLIygoCO3atYO7uzu2bdsGoCFEPigoCPLy8jAwMIC9vb3QBFwut2/fhru7O2M58gHQvFCsra2hoqICBwcHEnb76NEjuLq6onXr1nBwcICrqyuUlJQYTY/2o/daWFiIOXPmQE1NjRbFw7uxI4g0XEBDGLyHhwdWrlwJoKFfqqqqYuzYseSa4uJiTJ48Gd26dWPU2MU7Z9TX16O4uBju7u5kXFZUVEBJSQkTJ06kfa6yspKRAqCN15Ly8nIEBgby3W/q1KkwMDAguVjz8vIwf/58mqGYCT58+IDAwEC4uLigV69ekJaWps2pjx49grq6Ory9vUl+bq6xhTcNhSDJyMiAjY0NIiIiUFhYSPPCZBLu9x48eBAaGhro2LEjVFRUYGlpSfrg+fPn0b17d/j5+Qmsrge3HY8ePcKVK1dImq2EhARwOBwyboCG2lTdu3eHnp6eQAr1Ll26FGPHjsWYMWNox9evXw9ZWVnMnDnzh/MlE32C1/M4JCSEGHW+fv0KX19fyMvLE2+36upqxMXFoUOHDgItgsrS/Glq/YKLsGV7UdJzuIiKXM1dJ7kpMQoKCqCnpwdbW1vIyspi0qRJtOfBtCwtCnKksGWnf2L06NEwNzcnf69fvx66urpwcXFBUFAQevbsCUVFRYGsj/8XvFEBgkw5BTQ460lISGD8+PFYuHAhbGxs0LlzZyQlJaGurg55eXkYPnw4X554QbB69Wr4+/vTjuXn56Nbt25wcXFBZWUlXr58iUOHDiE3N1egbflPCELnEzWZ+tChQ1BUVMS4ceNIJMa1a9fg6+sLIyMjXLhwASkpKYiOjoasrCyfIe5nEDUZ7uTJk+BwOHBzcyNFsdeuXYvu3buT1MdcuKlVgZ9/H7zrAe88GBwcDFNTU+zduxf19fUoKChAYmIiLC0t0atXL0RHRwusPtTChQvRq1cvREREkO8uKirCggULICcnh2XLlv3wc0wbN5YtW4bWrVvjyJEj+Pr1Kz58+IAOHTogOjqadl3j+rtMRmPm5eVBXl6epJ/KysqCvLw87OzsUFxcjJqaGnz48AH+/v5wdnZmU9w2gjVs/CT19fWIiooCh8MhIcrV1dU4d+4crKys4ODg8MMNj3/bEcvKyuDj4wNHR0fiLZuVlUUKlHHzA44cORIvX76EhoYGvL29GfOcbMyqVavg6OiITp06oW3btnweKFwFiDtpN4Zpi+/06dPRvn17bNy4Ebdu3UKbNm3g6emJ4uJiVFdXY+LEibC2toaJiQm6detG3o2dnR1fUdz/hffv30NbWxtDhgwhQuPWrVsxffp0AA2W6I4dO2Ls2LFE+eEWQKqqqqJFl/wMvP3qy5cvmDx5MjgcDrp37067jquESUhI0HISMw03t3NSUhKWLFkCR0dHuLm5kY25oqIiTJo0CTo6OmQSFwQFBQXEy4/7d0hICJycnGjW7kePHqGoqEggOXf/DYJIg5WWlgZpaWmsWLEChw4dQkJCAtTU1BAYGEiu2bBhA+Lj47F8+XJGixpyBapbt25hy5YtWLp0KfEELSkpwZw5c2BkZEQLPxWk9znQMHZ1dHTw8OFDvHnzBurq6rQcr4cPH0ZJSQk+fPiA0tJSRu/LnTO483NZWRmsra3x5MkTvHr1ii/f7OnTpxnz8vvRWgIA7u7upNAk77P38/MjhmBAcLlmHzx4QFIM8W4Qce/36NEjaGhowNfXly91QVPlRc7MzCSeiNz5XhDpJG7cuAFZWVls27YNDx8+xIMHD+Di4oKOHTuScXP27Fm4uroiKChIYBFNR44cQevWraGrqwspKSls3rwZRUVFZC3j5rv9/v07Nm3aJLA0WNyieXZ2dvj06RPt3IYNGyAvL4/x48fzKR1McfnyZTg6OsLf35944NbX1+P8+fMwNTWFqqoqvL294efnB2Vl5SbfvGJpXjS1fsGLMGV7UdNzREGu5t3Uqqurw+7du/H69Wt8+PABJiYmiIiIANCQpk9BQQHjx48X6EatMOVIYcpO/xRNzt3Y+vz5M3R1dTF37lxy7sSJE1i0aBH++OMPLF68WGjGbkFEBfCuw/X19fj69Ss8PT1pMnxNTQ3Cw8NhZWWFmzdvAmiIAIuMjGTcOaYx8+bNg6qqKvGq5r6/AwcOQEdHh0QQNZXs+J8QhM4nKjL17du3IS8vT1IO83Lx4kX069cPbdq0gZmZGby9vRk1anARpgzHfZbcPnj//n24ubmhT58+6NixIwYPHozk5GSYm5tjypQp5HO8c83Pvg/ez+/evRvBwcG0yLWgoCCYmJhg7969RP9r7EDBtO5XV1eHlStXomXLlrC2tqbpUsXFxVi0aBHatm2LmTNnMnrfHxEZGQkOhwNnZ2dMnDgRJ0+exPXr19GhQwccO3aMXMf7DASh+02bNg26urpkfkpLS4OMjAxsbW1hZmYGFxcXWFlZMRoZ21xgDRv/I/fu3SMT/5w5c5CVlYWysjLMmDEDYmJi2LVrF4C/lQ8bGxvo6OjQCpn9LIWFhejTpw/c3d2J0P/y5UvU1dVh4MCB6N+/P6qqqlBdXY0uXbqAw+HA0dGR0VA63smxX79+4HA4CAwMJBv0vOcXL14MSUlJvnAypnnx4gUsLCxI8aVz585BVlaW5KPjUlxcTCtGNWPGDHTo0OGnBe+MjAzY2toiIiICL168wKdPn3D79m2Ul5fDy8sLw4YNQ11dHQoKCqCoqAgOh/OPVuifhdvfSkpKEBcXB3FxcSQnJwOgT8Jz586Fi4uLQCbmlJQUGBsbk7y+p0+fhpSUFMzMzGBvb082BN+9e4fVq1cLbGK+c+cOevToAWtra1rdlNevXyM0NBROTk4/ZdQSZbhKB2+O1AkTJmDYsGHkmtraWqSnp0NNTY0WAsskvO/24MGDaNOmDaytrWFoaAhpaWkkJCSgrKwMHz9+xJw5c2Bubo5JkyYJpC1cuM/ky5cv6NatG3bu3AktLS2MGDGCtDc/Px9DhgwhkQpMwztn5OTkoLKyEiYmJti4cSP09PQQERFBK+jWv39/Rj3zuWuJh4cHiSwLDQ2FnZ0duYY7lyxatAiurq4Ci4jgzkFPnz5Ft27d4O3tDS8vL1oeVe69Hz9+TDwChQXT3nWXLl3i8zJOSkqCi4sLn3HP0dERtra25O/09HSBFCyvq6vDp0+f4OzsjE2bNuH58+eYP38+OBwOFi9ejHfv3mH58uWQkpLC/PnzGb/3j1i4cCExpjR+XsuWLUOXLl0EVhw3JSUFhoaGkJOTo+Vmr6+vR0lJCRYsWIApU6Zg1apVtDR2LCz/DaKgX4iKbC8Kek5jhC1XX7t2jRZZCjREsXl7e5P0GQkJCdDU1ESnTp0Yq1kgKnIkL8KSnRpHcnOdtLjvuqKiAjExMQgICCAe8KIEk3LLsmXLEBMTQxtz1dXVsLW1JTW4uGOmrq4O5ubmGDJkCO1aQZOeng5zc3Ns2rSJ5viRlZUFLS0tgWyeiwqiIlNz27Fu3Tr4+fmhpqaGHGvcB54+fYpv374x5uzZuB2iIMPxRv3Hx8eja9eu+Pz5MwYPHoxx48ahc+fO4HA4fLUTfhbetfvGjRsYMGAAFBUVMWjQIJoBJygoCGZmZtizZw+fjC2oekBfv37Ftm3b0KJFC5IqjUtxcTHi4uIEJtsDdCe+Pn36IDAwEMuXL4e1tTX8/f0RFBSEsLAwkpJKUHDHw7179+Do6IidO3eScy9evMD69esxb9487Nu3j6xvv3tNjcawho3/gZycHJiYmGDWrFkYNWoUOBwO8Rb59u0b4uLi+JSPv/76C4MHD2Zk07a+vp50+ocPH8Lf3x9OTk7Yu3cvucbBwYG2STt27FhcuXJFYPnxr127hqVLl2LmzJlwd3dHWFgYEZh4B9vMmTMZF/Qbb3xkZGRAR0cHQEMobOvWrYmH/pcvX/giAp48eYJhw4ahffv2jFnlMzMzYWVlhWHDhhHvoNzcXFhYWJCQ2+LiYgwbNgzr169nzMOM91msXr2apuh8+fIFEyZMgLi4OFJSUgDQFyfegutMcunSJZLe6/jx42jXrh02btyI1NRUKCoqwsXFBXfv3qV9RhDGjZycHLi4uKBly5bEs5jLmzdvMHjwYJiZmZHCj82FAwcOQExMjHhmcd9vYGAgvL29adfW1tZi7ty58PDwIOkmeD/zb5k3bx5NOHz48CFUVFSwfft2omQsWLAA7dq1I55Eb968wZQpU2Bvby8wz+tz584hMTGRzFWDBw8Gh8NBnz59aNdNnToVZmZmKCgoEEg7gL9TBAwbNgyFhYVYu3YtOBwOunXrRrtu2rRpMDMzY2QD+0driaOjIw4fPoxHjx5BU1OTL9/t4MGDERgYyOgmGvDPG9h37txBcHAw3Nzc+IrEVVdXIy8vT+heKkx419XV1eHMmTOQk5Pj6+8zZ86EhoYG3/1u3LiBDh06CKwYLG96rYqKCkybNo0WxbZy5UqacWPBggVo27YtPn36xMg6wtsnbt++jfT0dFrKCu6m4rp16/5R8RKEAvTt2zccPXoUHTp0gJeXFznOKhYsP4uw9YvGCEu2FyU9R9Tk6pEjRxIdh8uUKVPg6+tLjA9TpkxBcnIyY1HHoiBH/hNNLTvt378f1tbW+Pz5M+rr6/H+/Xu0b98epqamWLx4Mel/Dx8+RMuWLfHnn3/+1P0EBVNRAevWrSMRF1yv7urqajg5OdHkR67MOGnSJPj7+wvM8QBo2Py7f/8+rVB6eHg47O3tsX79enz79g2VlZWYOnUqTExMBKZjCBNRlalnz54NU1NT0v94+8H169cFdl9ehC3DnT9/Hm3atMGECROIDuzk5ERS5p06dQpjxowBh8PB4MGDBdKGiRMnwsDAAJGRkQgODoaMjAwGDRpE0yeCg4OhrKyMM2fOCKQNAFBaWkrLglBRUYENGzZAXFycLz15aWmpwGT7pUuXIiYmhqT/OnDgAEaMGIFbt24hNzcXnp6exBmZyVq8vBw5coQvwrJfv36wsbH5Pz8nbB1YFGENG/8jCxYsgLKyMlq2bEkKeXIXEa7yIS4uTsLGeTvdz3ZA3hDKvn37wtHREa1atYKenh4RoFxcXODm5obLly9jwoQJUFNTw5s3b37qvv/EwYMHaUUCV65cCWdnZ5oCBICEuTE5KfFa2i9cuACgweJrZ2eHCRMmQFZWlhbumJ2dDScnJ1y7do0c+/TpE06cOMFoiDTwt3EjIiICDx8+RF5eHjgcDnbu3IlPnz5hxowZsLa2pkWN/Ay8QszFixexaNEicDgchIeHk0WDq4RJSEggNTWV7zsEpXgUFxejvLwc7u7uxKO3pqYG1tbW6NChA/H4EtT9uTx9+hS+vr5wc3MjRdS45OfnY+TIkULPr8o0+fn58PPzg6qqKi3sPCkpCXZ2dnw5PLdv3w5dXV2iuP8s8+bNg4SEBEmZAzSEAevp6RHPSy7x8fFo1aoVMYK8f/9eYArHoUOHICcnh4kTJ9IMiwEBAejQoQOWL1+O1atXY9SoUZCVlSV5YAVJZmYmLC0tERERgXPnzmHy5MkQFxfH0qVLsXTpUowePRqysrKM1X35v9aSzZs34/Dhw9DU1CTz2MCBAyEjI8NofRHedgANOdWXLFmCDRs2kL5x5coVBAcHw8vLCwcOHADQkBKLN9KtuQh23DUtLy+PeKs9evQIHTp04IuGuH37NrS0tASaKzs1NRV+fn4wMTGBkZERn2fjypUrISkpidmzZ+P9+/d8qaH+Lbx9IjY2FqamptDS0oKdnR3c3d3JuZkzZ0JCQgIbNmzgW0uZWE+43/H27Vvk5+fTZJpjx45BU1OTloqG1+An6PWMpXkiTP2CF2HK9qKi54iSXM39npKSEujr62PRokXk3Pr16yEnJ4fw8HD07t0bMjIyjBYfFrYc+Z9oStnpwYMHxDjCXa+LiooQFRUFb29vKCgoYPXq1Xj27BmWL18OT09PgenfosTVq1dpaaXOnz8PKSkpvtQx/fr1w6BBgxhP+8QdH4cOHYKGhgb09PQgJiaG3r174+7du6ipqcGQIUNgbm4OOTk5uLq6ol27ds0yVaQoy9RJSUlo3749rl69SlszuO9n9+7djN5PFGS4xt+Tn5+PgwcPQkVFBZ6enti6dStu3bqFQYMG0YwI+/fvF4ixJT09HUpKSiQlHNAwZ5uZmSEkJIQ2T8bGxgqsLyxZsgROTk6kFi7XyFNdXY3169ejRYsWP4wCF4RsvWHDBri5ucHBwQGJiYn4+PEjunfvTtJJVldXY8uWLbRsDkySkZEBa2trtGrVCsuWLSNOXAUFBTA2NiZp61n+O1jDxn8JtzMfOXIEHTp0gKGhIWbPns1XgOzbt2+YPn06OBwOSYnEJDdv3kSrVq2wdetWPHnyBM+fP4eHhwfs7OyQnJyMrKwsmJmZQUNDA7q6ugJduF++fAlpaWlSzA8A1qxZAzc3N/Tt2xd3795Fly5d4OnpSc4zMSmdO3cOgYGByM7Oxvjx4yEpKYm3b9+irKwMo0ePRps2bUgRO6DBOyUgIAA9evRo0hzsXE+i/Px8LFmyBBwOBwYGBlBQUBDIe5kyZQo0NTUxY8YM9O7dG7KysggMDCRK2NevXxEdHQ0Oh4NLly4xfn+gwZDRWJB/9uwZVFVVSX7Ct2/fol+/fjh8+LDABNzCwkI8evQIpaWlJMQwJycHXbp0QZcuXfiMG81lc7Qxb968Qbdu3aCkpESU0nv37sHGxgYhISHEKAg0eHF4eHgwEgL86dMndO7cmUTI3L17Fx8/fsS5c+cgLS1N+givl5empqZA66wADQZOFRWVH96ntrYWw4YNg7OzMzp16oR+/foxvpH/f5GZmQlra2uMHDkSZ8+exZo1a2Bqagp7e3sMGDAAOTk5jN7vR2uJu7s73N3dsXXrVjx//hyjRo1Cr169EB4ezvgmOu9aMGnSJLRr1w5WVlbQ1taGo6MjGZNXrlzBwIEDoaGhAWNjY+jp6TVJCoOmgqu81NfX49WrV+BwOFi6dCnKyspQVlaG2NhYODg4EA+mz58/Y9asWTAyMmIs1Uhj7ty5Azk5OYwaNQqDBw8mKQry8vJo1y1atAgKCgqMbGI1XguWL1+Odu3a4ebNm6itrSUpsNLS0sg1M2bMAIfDIR7TTMHtmykpKTAwMICuri5kZGQwefJkYgw9duwYdHR0aDnlWVj+DaKiX3ARlmzPRZT0HGHJ1Y2fZ21tLb5//47o6GjaRhDQMA9zC1MLQmYRlhz539LUshO3ZsGOHTvIsbdv32LBggWwsrKCpaUlTExMoKamJvDi2MKE20eXLVsGPT09TJw4kdTXWrduHaSkpBAUFISpU6ciIiICMjIyjL8LLteuXYOsrCySkpLw8OFDXL9+HTY2NvD19UVWVhZqa2uRkZGBtWvXYvfu3c0yVaSoyNTcdjx8+BAZGRm0+dnJyQl6enpIT09HaWkpvn37hmnTpkFdXZ3RdyIKMhyvTPvx40dUVlaS/Yj3799j9OjRcHNzg5GREXr06EFqG/LCtHHj0qVLUFFR4VsnNm/eDDExMYSFhdFqbgDM749MmzYNKioqWLduHc6ePYv27dvDy8uL1Dyprq7Gxo0bweFwaPUfBcnTp0+xZs0ayMjIYPDgwZg+fTokJCSIsYl3bAnC4PTt2zckJCTA1dUV2traGD16NK5du4bw8HCMHj2adZb6H2ANG/+Bxsr2hw8fUFJSgvnz58PCwgKxsbF8uSq54VSC6PybNm2CiYkJrZjPmzdv4OLiAn19fRw8eBDfv39Hbm4uox4zjYsecRfBGTNmoEePHrQIiqSkJLi6ukJNTQ3Ozs6Mpy5JS0uDnZ0dDA0N0bZtW1rxsZycHPj4+MDGxgaRkZGYN28ePDw8YGZmRtrclMYNKysrDB8+HM+fP0dGRgaOHDnCtzn0b2jct27cuAEFBQWiYNTV1eHy5ctQVFREUFAQCUv//PkzVq1aJZC+OX36dJiZmaFNmzYICgrCzp07UV9fj2/fvsHNzQ1BQUE4cuQIfH190aVLF1q+Xibg9s0jR47AzMwMKioqsLOzw6xZs0heRK5xw9/fn3g9NncKCgqIUsqNnkhPT4ednR0sLS1ha2uLwMBAyMnJMRYRUFlZib59+6Jv375ITExE+/btcffuXdTX18PZ2Rnu7u4khQw3t6mpqSlfeDTTHD9+HDY2Nvjw4QMZA43737dv31BWVibwouU/IiMjAzY2NoiIiEBhYSEtJRDT/GgtKSgogIuLC3R1dWmbxYIM0/706RP69u2L+/fv4+vXr7h06RJMTExgbm5OBOoHDx4gNTUVK1asIG35ldP/cPscr8LA9QSdNWsWpKSkSGq2wsJCTJ8+HWpqalBSUkLnzp2hrKxMUi0wzYsXLzBr1iw+r2B1dXXExsbyrV9MpDxpbKDhpo/g1n1JTU2FnJwc+Zt302zTpk2M9QXeuSA9PR0tW7bE6tWrcfXqVWzduhUGBgYIDQ3F06dPUVdXh6NHj6Jt27bo27cvI/dn+b0QBf1ClGR7LsLSc0RNrr5+/TrxWuW+p7t370JKSoqkJONtuyAN/sKQI/8XBC078aY6unz5MkJDQ2Fubk5LkQY0bOYePnwYenp6kJKSYqRguajB6wnPZdWqVbC0tERUVBRJ3Xr58mX4+fmhS5cu6N27t0AdhZYuXQpXV1da+x4+fAhLS0v0799fYPcVRURBpj548CCUlJSgrq4ObW1tUky+trYWnp6e0NDQQMeOHeHi4sJoOnBRkeF4N6Lnz58PDw8PGBgYoE+fPjh79iyABl3z2rVr6N+/PzgcDjgcDqOGUN6oGO7/L126BEVFReIgxF0zampqoK+vDzMzM0RGRtLWfSY5c+YMzM3NcfnyZQDAyZMnISsrS1L6cefLqqoqpKSkCEzP27FjB2bPno3hw4fj1q1bxFEgLy8P3t7e6N27N1q0aIEuXbrg3bt3AmlDVlYWrly5QtvDfPr0KY4fPw4DAwMEBARATU0NHA6HVh+W5f+GNWz8HzSeIE+fPk28zoGGVCuWlpaYMWMG6fhDhgyheSQwPSh37twJQ0NDslHLnZTu37+P1q1bw9TUlNFwvsZeN43T9XAXBd6wNqBBCcnIyCDPkOnnEBkZCTExMfj4+PDlGc/OziaKYVBQEKKiooS2GZaZmQk7Ozv069ePMW+Erl278nmGpaWlQU1NjWwQcRexkydPQlxcHEOHDiWF7ATxTtatW4f27dtj69atSE5Ohq+vL5ydnUl46+7du+Hm5gYtLS14e3sLzMjEXSQTExNRVFSEiRMnQk1NDcOHDycL9YMHD2BnZ4devXo1qVdZU/Ejy35BQQH8/f2hqKhIlNKcnBwcOHAAQ4YMQXx8PKPpC4AGAcbExARiYmKYN28egAah9vjx43BwcICLiwuePn2K7OxszJ49GyoqKowY/f4vVq5cCTk5OfI378ZyZmYmY4Wgf4bMzEzY2tqiX79+JEpCEN4a/81awk39IShvkQ0bNkBPTw/+/v4klVF9fT1u3rwJExMTWFhY/NBbqDlEWOXl5SEkJARAw8a9gYEB6f/z5s0Dh8Mhxo2Kigrk5+dj5cqVOHjwIPGKZJovX77AxsYGioqKmDZtGu3c2rVr0aFDB0yfPp12/5/tG1FRUQgICKB9V11dHRwdHbFlyxacPn0arVu3Jjn1a2trkZCQ8MONvX8L74YLt29NmjSJz5PvxIkT0NHRwfTp0wEA5eXlOHHiRLPcvGIRLMLWL0RVtgeaXs8BREuurqurQ3l5OeLi4iAvLw87OzssWbKEbBjPnDkT3t7eAqudCIiOHPm/IGjZ6dChQ5CVlcWTJ0+QmZmJiIgIGBkZkZQ+vHz79k1gG2LChPs8jx8/DltbW+zbt4+cW7lyJTFucPVd7noqaEeh2bNnw9ramrSRa3Q9d+4cJCQkhNovmxJhytTcvlFaWgozMzP8+eefuHz5MhITEyElJYVJkyaRaw8fPox169Zh586djKSBFlUZbubMmWjXrh22bt2KOXPmoH///pCSksLRo0dp161btw4hISECcdIpKyujrfchISFo3749bUP93bt3CAsLw/z58yEvLy+wWhI3btwg+0KnT58mtVfz8vKgpKQEb29vvtqzTMsYkyZNgqKiInr06AFLS0u0b98es2fPJv3w27dv2LNnD9mnEIT+O3XqVBgYGEBOTg6mpqbw9/ennS8tLcWePXvQt29fGBgY/NKOfE0Na9j4L5g6dSp0dXXRuXNnqKiooEuXLmQAzJ07F9bW1vD19YW7uzuUlJQE2gGfP38OaWlpvtyVd+/ehZubGwYMGMCYsDt58mSMHz+e5LpPTk6GrKwsJk6cSKytABAaGgpPT89/3CRmchOK+107duzAn3/+CRcXF/Tu3Zsvz+uP7iuszbDbt2/D3d2dsU3T6OhoIrRxF6+8vDy0bNkS27Zto137+vVraGlpQVxcXGBepZcvX8bixYtphfI+fvyIqKgo2NjYkLDGkpIS5OXlCUwhLioqgo+PDxYvXgygwWulY8eOsLe3h5mZGUaMGEEU5UePHglUKRQW3AX4zp072LdvH/766y9yrrCwEF27dqUppYJsw/Xr10n6tWHDhhFFs6qqCidPnoS7uzukpaWhr68PPT09gXmgP3nyhNQHePjwIQwMDDB//nyiaNXW1qKurg6DBw/G+vXrRSLkk+k540f8X2uJu7s7BgwYwEih8n+itrYW+/fvR6dOnaCurk47V19fj1u3bsHc3Byqqqoi8U6YZt++fbC0tISjoyMtbz4XrnFj5cqVTZ7WQ19fH87OznxpIzZs2ABpaWnMnTuXsfk7JyeHbFxyf2dtbS2mTJkCb29vyMnJYcOGDeT6d+/eoVu3bli7di0j9z948CAsLCz4Qt5HjRpF8i/X1NSQdWvNmjVQUFBolkVHWZoeYegXoijb89KUeg4XUZCrf7TOff36FaNHj4a7uzvatWuHTZs2IT4+Hi4uLgJLKSsKcuS/hWnZifssysvLERsbi4SEBHIuOzv7h8aN5pQqkwvvRmlKSgpatWqFxMREPk/7FStWwMLCAhMnTqRtnDJZs4A773z8+JHU17p9+zY4HA55D7x6iKGhocCdpkQBUZCpz507h+joaIwZM4ZE3JWXlyMpKQkSEhKIjo5m/J6iJMPxPtfCwkJ07twZycnJ5Nj79+8xYcIEtGnT5h913p9d43nH6tKlS+Hl5UVqWbx69QpFRUXo3r07FBQUkJCQgKSkJPj4+MDHxwcAYGxsjAkTJvxUGxqzd+9ebNy4EUDDuC0rK4OnpydZ40tKSmBrawsOh4OBAwcyem9eTp8+DTU1NVpU4bx589CpUycsW7aMFuFXVlbGeGYRoMEA3LZtW6SnpyMrKwv79++HsbEx7Ozsfng9t0+xxo3/Dtaw8R9Ys2YNlJSUcPfuXQAged94c4pu3LgR48ePx7Bhw0jHE+Qm+q5duyAhIYFp06YhNzcXpaWlmDlzJsLDw/HlyxfG7jN27FhYW1tj1qxZ+PLlC/Lz87F3714Sduzt7Y2bN29i3bp16NGjB9k8ZNoLn/f7Gn/3qVOn4OjoiN69e9MUsoMHD9KuE/bGGBPh0I1/+7Jly3Dw4EFUVFSgvr4eUVFRsLOzo/320tJSDBs2DH/99RdatWpFUnkwxdOnT0kI5ZIlSwD8/ay/ffsGPT09TJ48+T/+Fiaoq6vD7t278ejRIxQXF8PQ0JDUWgkPD4e8vDz69esnsBBLUeHIkSOQlJSEhYUFOBwOBg0ahKdPnwJo2BTs2rUr1NTUBFJ4mFcJLCkpQXp6Ovbu3QtHR0eEhYXxedFdu3YNOTk5AvNsO3z4MCm2ya3DM2LECLi6umLWrFkkncWMGTOgrKxMU8SEjSDSTzWmqdYS4MdjvqKiAseOHYOKigr8/Pxo5+rr63HlyhWEhIQ0iwiNHzF58mRwOBziaQjQPRvnzZsHKSkpLF68mK9AtiDJzs6GpaUlRowYwTdPbNmyheTCZZJdu3ahbdu2xJh2/fp1qKiowNbWlnhbFhYWolu3brR80T9Lbm4uAgIC4OXlRTPOr1u3DpKSkmTzjivbHT9+HKampowVS2f5fRGWfiEqsv3/RVOtTaIiV/NuxM6fPx/Tp0+necMXFRUhPj4eDg4OcHNzA4fDQVBQ0E/f958Qphz5s/ys7HT16lVav7h58yaUlZVhb29PG5vA38YNc3Nz7Ny586fuK4pwxz6XgoICmJqakvo7dXV1qK2txblz54jssnbtWmhpaWHq1KmMbcadOHEC9+7dI38fPnwY9vb2pEbCtm3bsHLlSrRs2RJ79+5FVVUVqqqqMG3aNBgbGzdLRwRRk6mrqqowd+5cMm/wwjVutGrVCmPGjGH0vqIiw/G+j6KiInz69AnS0tJ8NT3z8vLg4uKC5cuXAxDcfuH06dPRvn17bNy4Ebdu3UKbNm3g6emJ4uJiVFdXY+LEibC2toaJiQm6detG5k07OzsSIc0EDx48gJWVFTp37kzWtJKSEmhraxOj+bdv3xAWFobHjx8LVM44ePAgDAwM8O7dO9pzj4uLg4qKConA5IXp9gwcOJBEDHG///bt2zA0NMS4cePIcd59S2HvYf5KsIaN/8CoUaPIhu2BAwcgLy9PvAf/aaNB0Fa1+vp67N27F61bt4a2tjZ0dXXRtm1bxjyeeQfQtGnTYGVlhVmzZhHB4P3790hPT4e/vz8cHBxgb28PDoeDiRMnMnJ/XngnlK1bt2L8+PEYO3YsTp06RSalU6dOwdnZGT169EBSUhK6d+8OdXX1ZjcR8OZLBABvb2/Iysri+PHjABpCMUNDQ2FgYIDY2Fjs2LEDXl5ecHFxwefPn2FtbU2bTJni5MmTUFBQQM+ePVFSUkJ77kOHDkX//v0Zfxf/9H3cPIlLly5F9+7dieCyatUqGBsbIzg4mK8gZ3OA+zyKi4vRpUsXbNu2Dd++fcP169ehpKSEP/74g4R3vnv3Do6OjtDX1xdIwbhTp05h8ODBtBQWW7ZsgZOTE8LCwmhefoIco2lpaWjVqhXWrVtHqwNQUlKC6OhomJiYQEpKCubm5ujYsaNAC5CKKoJeS7jwzuPnz5/H3r17cfLkSWLQOn78OHR0dIh3FW/7uDQX4wbvb1q1ahXGjh0LFxcXBAYGkg073o2ZGTNmQEFBgZFaFv8LmZmZ6Ny5MyIiIprEM/fKlStwc3OjeVempaVBWVkZnTt3hr6+PpycnGBjY0PmrZ/pEzt27MCLFy8ANOQKDwoKgpubG807u0ePHlBVVaWlOZg0aRKsra1/qACxsPwvNLV+IUqy/X/T1qZYm0RJrj58+DDatWuHnj17YujQoeBwOJg8eTLtnd+/fx8HDx6Eg4MD47UsREGOFDb37t0Dh8PBnDlziNzy8uVL+Pr6gsPhkH7B+5vv37+P/v37w87ODl+/fm02uuf69esRGBhIW+vu378PDQ0NvHjxAlVVVVi6dClcXFwgLi4OMzMzsnavW7eOsZSZ79+/h7a2NoYMGYKXL1/i4cOHkJWVxfz587Fo0SKMGTMGLVu2RFRUFFavXg0OhwNjY2N07twZioqKzVK2FyWZmvc7X79+jUWLFoHD4SAxMZF2XXl5OVavXg0lJSUUFRX99DgRVRkuNjYWoaGh+PDhA/z9/TFmzBg+I4qHhwfjBh5eXrx4AQsLC5w+fRpAQySNrKwsLfoZaJjreWWNGTNmoEOHDuS5/iyTJ09GcHAwnJyc0LZtWxgaGuLPP/9EXV0dOnfuDFdXV+zevRuenp6wt7f/Yf1BJuD2tZ07d0JJSYnU5uJGFX3+/BkKCgpkfhcE586dQ3V1NXx9fdGjRw++8zExMfDy8mpW66kwYA0bPPBOsuXl5aivr4eNjQ1WrVqF69evo3Xr1mRS4KZK4PWoaWpyc3Nx9OhR7N+/n5Echbw0tmRaWVlhxowZfN7u586dw6pVq9CxY0fo6+sLLJ3MlClToKSkhDFjxsDLywsODg6Ij48nAn9aWhp69uwJCwsLWg2H5iJg8goxb968If/v27cv5OXlSW7mp0+fYsmSJVBXVycpDLjPws3NjeQ2/NnnwjUgcElNTYWUlBRGjx6Nt2/for6+HpWVlbCyskJkZORP3etHcNufnZ2N8+fP4/r167Tz0dHRsLOzIwWqJ02ahCVLljRrL9vTp09j2LBh6Nu3Ly0C4s6dO1BWVkZwcDDxfH7//r1A0gwdOnQILVu2xKJFi/gKBW7atAmOjo58ecKZpr6+HjU1NQgLC+Pre9xUE5WVlSgqKsKePXtw6dIl2pj6HRHkWsLLlClToKGhARcXFxgaGsLDwwNpaWmoq6tDamoq9PX1fyjwNTdOnz5N8+Lavn07HBwcEBgYSFMyuAYFYc1b3BpR/fv3ZzRH9T95QN25cwceHh7Q1dUl/fD+/ftITk7GokWLkJqaSmSTn9ngvXHjBvz8/Gh9PT8/Hz179oSbmxvx+svNzUXPnj0hKSkJFxcXuLu7o02bNkIpjsvyayMq+oWoyfb/CUGuTcKWq3nv/+zZM3Ts2JGk2Hvz5g1atWpFUoI0/m5BebWKghwpbJKSkiApKYn4+Hjy3F++fAkfHx+oqamRfsi7Bj148EAkarQxyePHj8kGJ7cv1NbWwsHBAXp6etDS0kLPnj2xYMECfPz4EW3btsXs2bMF0hZucfixY8di+vTptEwAnz9/xvr169GqVSvs3bsX9+7dw5o1a7B582bGaluKKsKUqbljo/FG7Nu3bzFnzhy0bt0aK1eupJ2rqKhAaWnpT99blGQ43rn5/PnzMDc3J7VfFyxYAHNzc6xevZo4LpWXl8PZ2RkLFixgrA2N14OMjAzo6OgAaDBytW7dmqSC+vLlC7Zu3Uq7/smTJxg2bBijhdy3b98OeXl5ZGRkoKSkBO/evYOvry9sbW1x4MABZGVlwc7ODp06dUKXLl0EVnuVl7q6OhgbG8Pd3Z12/Pnz59DX18e1a9cEct+ZM2eS4uirVq2Cvb09MTpx2bBhA2xtbRnPlvC7wRo2fsCMGTPIZLxu3TpYWVlBUlKSNhGUlpbCz88P8+fPF1YzBcI/CeZTp05F586dMXPmzB+GdN67dw96enrYtGkT421KSkqCtrY2Cdc/dOgQ8Q6Ji4sjwuX79+9RWFgo0KKGwoB3kl+8eDGGDh1K28j/448/aEoY0LBwci3RQIMluEOHDowIeYsXL0bv3r3Ru3dvZGRkkPukpKQQD/g+ffqgZ8+e6NSpE9lM/lkWLlyIadOmkeeRkpICGRkZGBgYgMPhIC4ujnhgbNy4Eba2tggODsagQYMgIyMjkPQpwoa32O6lS5fA4XAgLS1NBBPeXMnq6uro0qULSSfANPfv34e6ujqfwMS7Ibp582aYmJhg1KhRjPWLf8LT05NsCjQWlJjyRmH579myZQtUVVXJ3LV48WK0bNmShCJXVVXh2LFjaN269Q/T1zUXampqEB0dDQ6Hg7179wJoSD+1fft2ODo6IiAgAG/fvsXs2bNhamra5JEajWE6ZznvWDxx4gQOHDiA48ePE6UmKysL7u7u0NXVJXn0G8slTHhzcT22srKyyNrAVYy5XmRctm/fjpkzZ2LBggXNch1haTqEpV+IomwvTIQpV+/fv5+vHTdv3oSzszOAhs24Dh06kFSqAPicQZh02hIlOVKY1NfXk/fx559/QkxMDImJiWS9efXqFdzd3dGxY0di0GkuemZjeMfH7du34e3tTQytz549w5w5c7B8+XK8e/eOPIOgoCBGU9g0JiMjA3Z2dtDU1MTYsWNp50pLSzFkyBD0799fYPcXNYQpU3PnhHPnziE0NBR9+/alRfa9ffsWc+fOhaysLFavXs3ovbmImgy3Y8cOREVF8TnUjRs3DmZmZnBzc8PYsWPh7OwMU1NTxuYOXqcEbqq8r1+/ws7ODhMmTICsrCxt/c7OzoaTkxNtE//Tp084ceIEo7rx9OnT4eLigrq6OjKfvHnzBnZ2dtDX10dycjJqampQUlLCiMPSj9i8eTNGjx6NOXPmkFon169fh6amJmxsbHDq1CmcOHEC3bt3h62trUAyA9y/fx8BAQGkJtarV6/g6OiInj174vDhw6irq8PHjx/RpUsXgWQ4+d347Q0bmzZtogmMtbW18PHxwdmzZwE0WIXd3d1hb29PJoH8/Hx069YN9vb2zUqo4RVkSktLUVJSQjv2IwWIW3gXaBDy3d3dfzq/Ke89q6ursWbNGsTHxwNo2MyWl5dHQkICRowYAWVlZcyePZvvPTRlLuCmIiYmBoqKijh8+DCfl1SvXr1IGB2v4nXr1i2MHTsWampqjFjhuUWPYmNjYWpqCl1dXfz555+kuOTx48fRpk0bmJub4+LFi2SRYCK0jhtivGDBAhQVFcHGxgbbt2/HixcvcODAAUhISGDkyJH4/v07qqurER8fj169esHf358veqA5cfnyZQwfPhxfvnzB3bt3IS4ujsGDBxMPK+4ieePGDRgYGKCgoEAg7Thz5gyMjY1RXV2N6upqbNmyBZ6enlBRUUFwcDC5bufOnQKLCuD1du/atSt8fX3J39zn8P79e8yZM4ekVGARLNznHhkZSfKHHjp0iFYUuqysDMXFxaitrcXly5ebTdopXniF1eLiYsTGxoLD4ZCi4VVVVdizZw+sra3Rvn17aGho4NatW8JqLg1B1HuZPHky5OTkYGxsDDExMXTt2pV4MGVmZsLT0xOGhoYC9dIuKCiAs7MzAgMD8fz5cwB0xZg3XzMLy/+KqOgXoiLbiyJNLVcXFBRASkqKJpsADZstJiYmuHjxIrS0tDBixAiyDt6+fRvBwcECdcgQFTlSmHD7++nTp7F27VqoqKiAw+Fg4cKF5Jrc3Fy4u7tDR0dHoNGtokROTg6cnJzg5+eH1NRUvvNlZWWYNWsWlJSUyDoqKLKzs6GlpQUjIyM+r/tp06bBwsKi2adyERWZOiUlBXJychg9ejRmzJgBPT09+Pn5kVorb9++xbx588DhcPhSIP0MoiLDNd6A7tWrFzgcDlxcXGi18gBgz549GDduHHr27ImJEycyVi/r3LlzCAwMRHZ2NsaPHw9JSUlST3L06NFo06YNzUBeWVmJgIAA9OjRQ2D7ZNznEh8fDxsbGyI3cMflhQsX0KpVK3h4eNBqVzHdnunTp0NWVhZBQUFwdHREu3btEBMTAwB49OgR3N3doaGhAWNjY1oUJpNjZd26dXBzc4OzszOKiorI8QcPHsDb2xtGRkZQUVGBlZUVOnXq1OyyzQiD39qwcf36dYiLi2PMmDGkaGxtbS1MTExoi/fx48fh7e0NFRUV6Ovrw8rKCg4ODgIZBMKCd0KZP38+fHx80L59e8TGxuL8+fPk3NSpU2FtbY3Zs2eTQcodgP369UNgYCBjnthr167FxYsX8eHDBxQWFiI/Px9mZmZISEgA0OAJrqSkBA0NDRK+3Vw5cuQIOnbsSBPkuLlvuQQHB4PD4eDq1avkWHl5Ofbv389YrtM5c+YgJSWF/D1w4EAYGRmRXLwAcOzYMUhISGD8+PGor69nZHxw+9jmzZshJiaGqVOnYujQocSgAjTUdpCUlMTw4cNpGwLNURnnZdu2bVBVVcWYMWNQVlaGK1euQFxcHCNGjOBTShsLW0xy48YNmJiYoE+fPrCyskJgYCDGjh2L1NRU2gauoLh16xb69u2L27dvA2goTN6yZUuMHz+edt3UqVPRqVMnmpDBIji4UVRDhw7F1q1bcfXqVVpYdG1tLZKSkrB9+3ba55rDugr8Pfa46aS4f3/48IEUD+dGbtTU1CAvLw+nT58m0QrNBV5B/fnz5zA2NsatW7fw9etXPH78GK6urujSpQuuXLkCoMGDuVOnTujXr59A27V27Vp4enqif//+fIqxl5cXowo5y++DqOgXoijbiwrCkqsvXbqEjh07wt/fnxzLz8+Hj48P5OTkMHDgQNr1MTEx8PHxIR7KgkBU5Ehh89dff0FaWhrLli3D8uXLERkZCTExMeJcBzQYNywsLGBmZtasnBu5cN9zVlYWibh+9OgRunTpgi5dutA2I0+ePIl+/fpBXV29yWpZ3L9/H+bm5hg8eDCtoPiIESPg4+NDUhA3V0RBpr5//z4MDQ1JhE5eXh7U1NQgJiYGW1tbYgguKCjAkiVLyBooCIQhw/HKs3v27MHOnTsBAGPHjoWioiI2btz4w37I+w6YmDvS0tJgZ2cHQ0NDtG3blvacc3Jy4OPjAxsbG0RGRmLevHnw8PCAmZlZk6R9un//PsTFxTFnzhza8dOnTyM4OBheXl7w8fERiFxx+/ZtBAYG4vLlywAaamv++eefkJaWxrRp08h1L168wJs3bwSW6eX8+fPo2LEjpKWlceLECdq5d+/e4datW1i+fDn2798vsKiV343f2rABAAcPHkTHjh0xatQoMiGYmpri9OnTqKurI5PX8+fPcebMGaxbtw4nTpxoth1w+vTpUFRUxI4dO/Dnn3/Czs4O7u7utHDsuLg4qKurIykpCUDDxFhSUgJVVVWyqfhv4J1g161bBxkZGeTk5JBnffr0aejr6xMvmevXryM4OBjr169vlhEavGzduhWWlpYAGnIhLly4EHp6emjbti369OlDrps+fTp5XkxafE+ePIkDBw4gPDwcFy9epJ0LCQmBkZERtm/fTnIDpqamQkZGBsOGDfvpRau+vp5W4HHPnj0QFxdH+/btSV5kXk8rGRkZDBw4kKRw+R0s3zt27IC+vj5GjhyJ8vJyXL58GeLi4qTmCRemngX3ez5+/EjCYGtqarB582YMHDgQU6dOJfUBysvL4eLigrS0NEbu/U/s3r0blpaWCA0NJcrO5s2bISMjA3d3dxIuLS8v3yyLCYoKp06dIhswM2fOJMVxExMTweFwICEhQUvF8eXLF3h7ewssN7Mw2L9/P4qLi8nf9+/fh5ycHF9O1Q8fPiAqKgocDgdHjx5t6mY2CY034xYsWICwsDCEh4fzyVjm5uYICQkh1z569KhJ1vaNGzfC1dWVphi/fv0anp6e6N69O1sonOVfIUr6hTBle1FFWHJ1fX09rly5AlVVVXTt2pUc37RpE9q3b4/IyEjcuHEDWVlZiI6Ohry8fJNEHTe1HClq1NbWIjg4GEOGDCHH6uvrsW7dOoiJiWHRokWkH+Tn55NC2c0J7rs9fPgw1NTUEBMTQ6K4Hj58SIwbhw4dAtCwgbho0aImT9GYmZkJMzMz6OjoYPDgwRg5ciTatWvXLOtfiaJMffr0aZLq9/Xr19DR0cHw4cNx6dIlyMvLw9/fn9TibAonpaaU4Xhl0gcPHsDKygoWFhZkLQ0PD4ehoSF27txJDDyClGO5xlcfHx9S24NLdnY25s+fDwsLCwQFBSEqKorIFU2xf7l9+3ZISEggJiYGd+/excuXL9G9e3csWLAAjx49AofDYXxvYMeOHfDx8YGtrS0tvWZlZSXWrFkDAwMDvjSLALPv6Pnz5yQC9OXLl9DR0UFAQADf+2lMc3HoEya/rWGDN1Tx9OnTUFVVxfDhw3Hnzh34+PggOzsb9fX1qK6uJh2tcUGX5tYBT548CSMjI9y8eRNAQ2iyhIQEOnfuDGdnZ5w6dYpcu2HDBj5BnykvnmvXrmHZsmXYtWsXgL8nm7S0NBgaGmLt2rXIz89HQEAARo0aRe7fXN7HjybX48ePw8TEBF5eXtDW1kZYWBgSExNx/PhxiIuL8xkbmFywoqOj0aZNG6irq4PD4WDEiBF8QkJYWBgUFBRIbk8AOHDgANq3b89XlPJ/hft+09LSMHHiRDx48AAHDhyAmJgYZs+eTZ4X97pjx45BWVmZVviwufHy5Uuaogk0CBAGBgYYPnw4qqqqcOXKFXA4HEyYMEFgYci2trbQ0NDAmDFjiCGjMbNmzYKmpmaTeKDv27cPzs7O6N+/P2nP/fv3MWjQIPTr1w9jx45lU1AJkOLiYtjZ2UFXVxejRo2ClJQUMTJ9//4dw4YNQ+vWrXH//n18+PABubm58PPzg42NTbNxEvjw4QOkpKRoHrbPnj1D3759oaysjHPnzgH4e766e/cuJCUlweFwaJ6QzYE+ffogPDyc/F1TU4MZM2aAw+HA0tKSyAzcd5+amoqWLVvypVxhMuovMzMTW7duxd69e0ndLuDHinFBQUGzTLnCIlhETb8QFdlemIiCXN3YIHDlyhVoamrC29ubHFu6dClcXFwgKSkJS0tLWFlZCWyzVhTkSFGiuroaLi4upH4DN+K8rq4OQ4cOhYSEBObOnSvkVgqe8+fPo1WrVti6dSuf/vbo0SP4+vrCz8+P5KwXVr+4f/8+9PT0oKGhgUWLFjVLQ5OoydS8BlbuvNS7d28MHDgQdXV1qKiogKOjIzgcDjw8PBi9t6jJcJMnT0ZwcDCcnJzQtm1b6Ojo4PDhwwCAQYMGwdjYGLt37yYGHqbhjjuus4KLiwt69+6N9PT0f7z2n/4WJIcOHYKysjLU1dXRoUMHWFlZobKyEnl5edDX10d2djaj99u/fz9MTEwgJSVFk22Ahr4jLy9P9DBBMHXqVBgZGaFdu3ZwdXXFkSNH8OrVK+jo6KBPnz60PttcnQSEyW9r2OAyY8YMPHv2DEePHoWGhgb69+8PKSkpKCgowNraGtbW1jAwMICenh6mTp0q7OYKlJycHMybNw9AQ1HPtm3bYtu2bbh27RratWsHJycnmlcAQJ8c/+0A5f2Ox48fg8PhgMPh8KWX+vjxI0JDQ6GlpQVVVVXY2Ng0u3x0vMrXq1evSKj79+/fsWfPHowcORJ79uwhkQpPnz6Fra0tHjx4IJD2ZGZmolu3brh+/TqKiooQGRkJKysrLFy4kE8Rnzt3Lp8gxVvz4Gc4fPgwWrZsiXnz5hGLd1JSEsTExDB//nw+40ZzDkXmelBOmzaNr6Dvli1biIfdt2/fcOPGDYFs5N+9exft27fH7NmzkZiYSLwRuLnDAeDo0aMYPnw4lJSUBBYh8fjxY750EHv27IGLiwv69evH5+XY3CO7RIEHDx5ASUkJ0tLSZGOIO0/fu3cPvXr1grS0NLS1tdG5c2c4OTk1q7SOQMNa2rFjR/j5+ZHIsRcvXiA8PBwKCgo0D6WCggKEhoZi3rx5zc7o9ubNGxKxx52Tv379isTERIiJiWHFihW060+ePAlDQ0O+zbafhdcLVUlJCc7OzjA3N4erqytxoAAaFGNPT09069btfy4IzMLSGFHRL4Ql24sKoiBX89ao2LBhAxYuXIjz58/j0qVLMDQ0pBk3CgsLkZGRgdzcXJLCkGlEQY4URebPnw9NTU3ye7nvbd68edDS0kK7du1oXsDNkejoaOKQwB07jfV0e3t7BAUFMabj/Vvu3r2LLl260CJkmxuiIlOXlpZCWloaixcvJsdKSkpgbW1NIniqq6sxfPhwnDx5ktEaNKImw23fvh3y8vLIyMhASUkJ3r17B19fX9jY2JBUk1x5v3Gk9s/Au5Y11mdPnToFR0dH9O7dm6RgAsDnMCWM9fzNmze4ceMGLl++TNodGxsLIyMjgTihnjp1Cp06dUKPHj1oz6KoqAh6enoCi5Dft28fVFRUkJqaij///BOTJ0+GmJgYduzYgZcvX0JXVxcDBgzAjRs3BHJ/lt/QsME7oPft2wc5OTli3Tx48CDat28PJycnzJo1C2fPnsWpU6ewY8cOHDhwoNl4lAI/3uCrrq5GaWkpysvL0aVLF6IIAYCrqyv09fVJ6CFT8ArtXG+y1NRUyMrKIiQkhNRQ4M1Tfvv2bZw+fbrZpgMDGiy+JiYmkJGRwciRI/k2aGtra1FSUoIePXrA3d1dIBu2+/btg7e3N/r27UsTjsaPHw9ra2ssWLCAz7gBMP8+nj59Cm1tbZLLk5dNmzZBTEwMCxcu/K02rbkFJufOncu3CWhtbQ1ZWVlMmjRJIALM8+fPkZCQQPNcu3//Puzs7GjGjW3btmHUqFECU4gLCgpgZmaGESNG8AnQO3bsgIKCAgYMGEBLofGrb9CIMtxn++jRI5ibm6NTp04wMzP7odB66tQpHDp0COfOnRNYblNh8+DBA6ipqcHX15cYN54/f47BgwdDTk4OR44cwevXrzFr1iz4+PjQ6gU1N9asWQMTExOygVZeXo758+eDw+FgwYIFyMjIwMuXL9G1a1e4uLgIZC5PT0+HsrIyWUfOnj0LWVlZaGlpkdzUALBixQp069aNbHKysPy3iIJ+ISqyvSgibLn60KFDaNOmDfr37w9HR0fY29sjIiICly9fhpqaGvz8/Bi9339CmHKksOH+purqatrYu3PnDnx9fdGzZ0+a7BodHY3t27c363UaaBgDrq6uCA0NJcd43z93DX/8+LHI1AFrrnUURVGmnjp1KoKDg4kh6fv37zAyMiLFuydNmgR9fX0+YykTiJIMN336dCKrcp/3mzdvYG9vDy0tLWLcmDdvHmPF7HnXo61bt2L8+PEYO3YsTp06RfZoTp06BWdnZ/To0QNJSUno3r071NXVRWoOf/DgAQYNGsRo6rjU1FTs27ePFq1y+PBh2NrawsHBAWvXrsXBgwcREBAAExMTgTjRXbx4EREREVi+fDk59vXrV6xatQrS0tK4du0aMjMz0apVK8yaNYvx+7M08NsZNricPn0a48aNw+bNm2nHU1JSoK6ujqioqB8WhmsOmy+8k+PTp0/5vJI+fvwIXV1dUnDp06dPGDhwIPbt28eooH/hwgX4+/vj7du3GD9+PDQ0NEjqjoMHD6JFixaYMmUKeeY/mpibi4cv7+/Yt28fNDU1kZycjKSkJOjr6yMoKAgXLlwAAFRVVWHLli3w8fFB586dBVIEqq6uDnFxcdDR0YGhoSHfc54wYQLs7OwwdepUgUdHpKWlwcDAgBZmzPtbd+/eDQ6Hg2XLlgm0HaLGlStXoK6ujvj4eNqG4ahRo7Bw4ULGvVXq6+vx6dMnaGhoQFpaGqNGjaKdz87Ohq2tLQIDA0lfFZTCkZ2djS9fvmD58uWwtbXF+PHj+eZrFxcXKCsrIyIiolmk0hBVfjTvfP78GVlZWXBycoKxsTFfOoPGodnNZR5vzIMHD6Cqqkozbrx69Qrjxo0Dh8OBgYEB2rZt2+zyQjfuEy9evICmpiZcXV3JXFVRUYEFCxZAXFwcEhISGD9+PHx9fUmEx79dz370ucrKSsTGxpIUI/n5+dDW1kafPn0waNAgqKur07z+SktL/9W9WVgA4ekXoiLbiwqiJFc/evQIHTt2JBtwjx49QsuWLTFjxgwADfKcrq4uHBwcGLnff0tTy5GiAFeXPHPmDP744w94enpi7NixJMXu4cOH4evrC1VVVYSGhqJbt26QlZX9x3SrzY24uDg4OTnh6dOn5Fh9fT3y8vIwduxYkuaHRTCIgkz9Txvhp0+fRtu2bWlp+k6ePAkNDQ1oaGhAU1PzpyP0RVmG4z6X+Ph42NjYEB2Xu15cuHABrVq1gqurKy01N5M6zpQpU6CkpIQxY8bAy8sLDg4OiI+PJ/JDWloaevbsCQsLC3h7e4tUZpOamhpkZmZi0qRJjEVExsTEQFFREaqqqrC0tERUVBQ5l5qaCjMzM4iJiaFHjx6YMWMGeRdMvpN3795BV1cXsrKymD9/Pu1cSUkJAgMDSd/NyspqtjqvKPBbGjZu3LgBCwsLKCgoYMeOHQDoOXGTk5OhqamJ/v37MxpKJ2rExsZCTU2NeJE9ffoU9fX1KC4uRteuXREcHIzVq1fDz88Pzs7OZLFhStDfu3cvPD09yeYOV4Dmfv/+/fvRokULTJ06tVkYlH7EokWLaIpDeno6pkyZgi1btpBjt27dgrW1NYKCgpCeno76+nps3boVs2fPFmgRqOrqaiQkJEBXVxcjR47kq6sxePBgDB06VOCL5ZEjR6ChoUEMG7xFNy9evIjHjx8jOTn5twmV5+XKlSvQ0tJCZGQk9u7di+nTp8PExOSHkTRMkZ6eDj09PTg6OvIVwrp//z709fXRp08fUjSNaY4cOQJlZWXEx8cDaCigZ2VlhfHjx5P5urKyEsOHD8eCBQvYHPkChHctuHTpEk6cOEHzGLtz5w6cnJxoXmZhYWFYs2YNANEQtJmC97fw/j8nJwcqKio04wbQMK+fO3eu2fVP3j5x7tw54hWdm5sLPT09ODk50TbQVqxYgRYtWmD16tXkcz/r4fb69WsSfr93716MGzcOr1+/xtWrV1FWVgY7OzsMHToUQEO/bdWqFWRlZUnRZBaWf4so6BfClu2FjSjK1WfOnIGVlRWABuO2pqYmhg8fTs7fuXMH58+fh6mpKSk62lQIQ44UNqmpqZCTk8Po0aOxefNmKCkpISgoiBgvHjx4gISEBPTs2RPDhg1DTk6OkFvMPFw5pbi4GHl5eWRz/OLFi9DU1MTUqVPx5MkTAA1jYfbs2dDT02t2MosoIWyZmldGBRoMCI2jucLDw2Fvb0+u5Tq93bp166dranIRdRnu/v37EBcXx5w5c2jHT58+jeDgYHh5ecHHx4dxp7qkpCRoa2uTOg2HDh2CuLg4zMzMEBcXR9as9+/fo7CwUGQj4pmIYqmvr0dhYSF8fHyQk5ODvLw8LF26FJaWlhgyZAi57sSJE7CxscGIESNICihByDrZ2dnQ1dVF586d+Yx7w4YN44vIZI0bguG3NGwADaFq2tracHFxIRMx78DftWsXgoKCmo2gD9AHckpKCrS1tZGamoqTJ0/C0dERurq6ZKMyNTUVXbt2hampKbp27cqo9xLvYB45ciQ4HA48PT2JIlJfX08W5wMHDhDv8OY2CTx9+hT9+vUjv+v169do1aoVOBwOLVUAQFfCePMFAsxOjg8ePMDTp0+JkaCmpgaLFi2Cvb09xo4dyxeG3bi2hSB49eoVWrZsiWnTpvGdmzBhAmbOnNns+sb/wp07d+Dq6goNDQ2YmJggIyODse/+p/fKTWEQGhrKt4A/ePDgh96oTPDXX3+hZcuW2Lx5M035X7duHezs7NCvXz9s376dpJzgRoCxCJbJkydDVVUV+vr6EBMTQ2BgIM6fPw/g7/4pKysLJycnaGpqipyQ/bNwx0laWhqio6PRo0cP/PnnnyQSg9e40Zz7JO98MWXKFJibm2P58uXEKP4j40ZZWRlJS8WEUlpdXY3+/fvDyckJEydO5Pve9PR0WFlZkQLl9+7dQ9euXTFr1qxm6Z3M0vQ0tX4hKrK9KCCKcjXQkDalW7duyM3Nhbq6OkaMGEHucfXqVUybNg15eXkCcwj5TwhSjhQ1Hj58CCMjI6xbtw5AQy1AVVVVSEpKws7ODg8ePCBrWW1tbbNywODC/U1HjhyBpaUldHR0YGVlhalTp6KiogLbtm2Dubk5rK2t0a1bN3Tr1g1t2rQRWL08FjrCkKm3bdsGVVVVPHv2DADw8uVLKCsro0uXLti0aRO5x/Xr19G5c2dSK45pef5XkeG2b98OCQkJxMTE4O7du3j58iW6d++OBQsW4NGjR+BwOLR6ev8G3nW5uroaa9asIU59KSkpkJeXR0JCAkaMGAFlZWWaYf5H39Gc+PjxIx4/fozu3bsTHePr169YvXo1LCwsiOELaHAosbOzQ0hICN9azyTZ2dmwsLBAWFgY0f++fv0KJycnmiMDi+Bo9oaN/2tAr1q1Cra2thg2bBjJF/ijCbq5TQr79u3DunXr+DwkXV1doaWlRQTar1+/4tOnT0QAYmLx4n2WBw4cwOzZs7Flyxb4+voiMDAQ2dnZAOhKxY4dO+Dm5tashcvjx4/j48ePuHPnDjp27AhfX1++9CS3b9+Gurq6wIpMxsXFQV9fH2pqalBWVsb06dNRU1ODmpoaLFiwAI6OjoiKiuKL3GiK8bF161YiQOTk5ODRo0eYMmUK5OXl8fjxY4HfX9T5+vUrXr9+zWgBPd5il0lJSViwYAGePXtGQm/T0tKgpaWFkJAQ3Lt3j7H7/hOVlZXo06cPMXCVl5fj6dOnSEhIwLlz5zB79mz07t0bHTp0gIWFRbNWzEWJLVu2QFlZGbdu3cLHjx9x7949ODo6wt/fH7du3QIA5OXlITExkRYu3dyMkSkpKZCWlkZYWBi6dOmCTp06wc3NDefOnQPwd0FxR0fHZm3cAIAlS5ZAUVGReNfxkpubC319fbi6uhLPz4qKCixatAgcDgfbt2//6fuXlpbC3t4eHA4Ho0ePpp07f/482rRpQ4oHxsXFYcCAAWz6KZb/GVHTL4Qp24sSoiRXc8nNzSUGlnHjxtHORUVFwdfXV+hzkCDkSGHC7Qf19fW0cZaZmYm5c+eirq4Ob968gba2NvEIV1RURM+ePYns0hzhPou0tDTIyMhg+fLlKC0tRUxMDKSkpEgh6LS0NKxYsQK9evXCrFmzWF2riRCWTF1UVARLS0tYWFgQo0FKSgrmzp0LaWlpdO/eHQkJCairq4Ovry+Cg4N/7of+H/wqMtyhQ4egrKwMdXV1dOjQAVZWVqisrEReXh709fXJntbPsnbtWly8eBEfPnxAYWEh8vPzYWZmhoSEBAANNW+UlJSgoaGBtWvXMnJPUWbGjBkkdaOZmRnt3NevX7FmzRp07twZQUFB5Pjx48ehr6+PiIgIgdblyczMhImJCVRUVBAQEIDevXvDysqKpNltjnuZokSzNmzwCjKpqalYvHgx/vzzTxLCBQAJCQlwcnJCREQEEeaa24YLL1+/foWqqio4HA6mTJkCgF5Ezc3NDbq6urh+/Tpt8DGhfPF+39SpU6Gnp0cm4D179sDLywuBgYG0gn5nz579xxQfzYV3796hY8eOCA8Px6dPn3D9+nVoaGhg8ODBfMUNHz16JJD+uWzZMrRr1w4XLlzAxYsXsW3bNkhKSmLYsGEAGvrGggULoKuri8TERMbv/5+oq6tDcnIyFBQUoK6uDj09PRgaGrLeQwKCO84OHz4MeXl5+Pv7Q0dHB05OTli7di3ZrExLS4O+vj7fuBUEFRUVsLGxQVRUFD59+oTIyEi4u7tDVVUV6urqWLp0KUpLS/H69etmv3EsSowbN44oONx1gusRGRER8cPPNLc19t27d7CyssKqVavIsXPnzmHgwIHw8PAguWSzs7NhbGwsMkU3maa+vh6lpaXw9fUlBR65cwmvDJGbm4vWrVtj5MiR5Fh5eTkSExMZSSlYXV0NLy8vWFpaokuXLti9ezc59+zZM/Tv3x8qKiqwsrKCrKxskxhmWZoXoqZfCFO2F0VEQa5uTGpqKmRkZDB16lQ8e/YMOTk5mDx5MuTl5ZtlqiNRgFcWTEtLw9GjR1FbW4uHDx+ivr4eAwcORGhoKImU8fLyAofDga+vb7OqzbZz504SoQI01JQZNmwYJk6cCKBhU1tLSwtjxozhM3g2R71blBGGTM29T2lpKRwcHGBiYkKMGwDw5MkTREZGwszMDNbW1hg+fDg4HA5Onjz5U/f9J34lGe7Nmze4ceMGLl++TJ5jbGwsjIyMfljo/b+Bd11et24dZGRkkJOTQ97z6dOnoa+vT9JZXr9+HcHBwVi/fn2zXdO57NmzB+3bt8eGDRsQGRmJtm3bIjAwkHbNt2/fsGjRIoSHh9McN06ePCmwjBK85OTkQFtbG66urqSmGcBMCi6W/5tma9honBJBXV0d7u7ucHV1hZOTE44dO0bOJyQkwNXVFcHBwUL3mGGaH01wr1+/JgsXd4DzCjJGRkbo06ePwNoUHx8PRUVF3Lp1i/a8uSHyfn5+OHr0KPz8/GBlZfVbCFUZGRmwtrbG0KFDUVJSgqtXrxIl7EcKD5NKWF1dHYKCgjB9+nTa8QsXLoDD4ZDcnVVVVdixY4dQNyXfvn2L69ev48aNG4zl8mT5MZcvX4aKigq2bt0KoMFDqEWLFrCwsEBCQgLJx3vy5ElYWFjw5WEVBDt27EDLli0hJyeHXr16kRzm48aNg5eXV7PzPBU1Gq8n9fX1GDJkCLp27UrOcwW3vXv3ok2bNnj79m2zM2Q0Jj8/H2pqasTTkUtaWhqMjY1x+PBhcozrtdNc+fr1K/T09LBy5Uq+c5WVlaTw6Lt37wTaL75//453796he/fu8PT0pCnGT58+xdatW7Fo0SKSdoGF5b9FFPQLUZTtRQ1hytU/ora2Ftu3b4ecnBzU1dVhbGwMCwsL1kFHQJSWlkJZWRmLFi3CsWPHICYmRhubVVVVcHV1xYoVK8ixiRMn4saNG7RN3V+dsrIy+Pj4wNHRkRYR2adPHxw4cADFxcVQU1PDiBEjyLnU1FScPXu22W+SChtRkam57Xjw4AGOHDkCDocDV1dXmnz0/ft3fP78GePGjUPnzp2hoKBAal8Kgl9Rhnvw4AEGDRqEdu3a8UUH/huuXbuGZcuWkcLovNFWhoaGWLt2LfLz8xEQEIBRo0bRUug1Rw4dOoTt27dj586dABocHg8ePAgtLS307t2bdm1FRYVQo1KzsrJgb2+P4cOHE72HRfA0W8MGl9WrV0NTUxPXr18HACxfvhySkpIwMDBAcnIyuW7OnDkYOXJks1rEeX9LWloajhw5QkL3CgoKYGZmBltbW5KrnndCFNSk+OnTJ/j4+JAF6s2bN7hw4QIiIiKwf/9+JCQkoHfv3tDU1ISnpydZ0H8H40ZmZiYsLS1pSpiWlhZ69uwpsLyRHz58AACYmJggJiYGQMOz5j73CRMmwMvLi6+2RnNdNH9neMdYTU0N1q9fT1ImvHz5Ejo6Ohg8eDD69esHVVVVrFq1Ct++fQMAYuRoCh4+fIizZ88C+HuOGzt2LMLCwpqVh52owbuevHjxAm/fvkVdXR0uXboEDofDt6mfnJyMzp0786Wuaw5wx0pWVhZev36NT58+wcrKikQg8j4re3t7WiG75sSP5KWPHz/C0tKS5JPlvSY7OxsTJkygFR8V9FrCzXvs7e1NDKGzZs3ChAkTBHpfluaPsPQLUZTtRRVhyNX/iYKCAly5cgVZWVlEBmdhnu/fv2PXrl2QlJSElJQUDhw4AODv8VBZWQljY2MEBQXh7NmzmDx5MpSVlZtNKi5eCgsL0adPH3h4eJB6BREREbC3t4e2tjbGjBlDNv/KysrQv39/LF68+LebL5oSUZOpU1JSICcnh5iYGPTo0QMaGhowNzf/oeHgyZMnTeZc+KvIcDU1NcjMzMSkSZNIlPb/Cu94e/z4MTgcDjgcDl96qY8fPyI0NBRaWlpQVVWFjY1Ns98vKygoQOvWrcHhcGiOU1zjhra2Nv744w++zwnzeWRmZsLOzg79+/dnU/k1Ec3asPH161eEhYURj/Njx46hTZs2iIuLQ2BgIHR0dHD8+HFy/Y9SJvyq8A7k2NhYkvtPWloa4eHhKCgowOvXr2Fqago7OzvaRgMXQQg0JSUlUFNTw/Tp03Hp0iX069cPdnZ2sLGxgYqKCjZs2IDS0lI8e/aMvIffyQubq4QNGzYMpaWluHDhAnr16iWQPpmYmIjRo0fjzZs3WLBgAbS1tUmBSW7/mTFjBnx8fBi/N4vowX3n6enpuHfvHp4/f47Hjx+jvLwcbm5upBBXSUkJFBUVoa+vj1WrVqG+vl5ogsPjx48xbdo0tGnThk3lIEAapxE0MjJCu3bt4ObmhjVr1iAhIQHS0tL4888/UVhYiKKiIvj7+8Pf37/ZCdm8RTfV1NQwY8YMAMCoUaOgpKRENjm513bv3h3z588XSlsFSWOl/NWrV0TRPXLkCMTFxbF06VLyvL59+wZ/f38EBQU1eZ949eoVevXqBTMzM9jY2EBOTg43btxo0jawNC+EpV+IqmwvyjSlXM0iWty9e5dsDi5dupQc5+qV2dnZUFZWho6ODrS1tZtd9Ayvo9rDhw/h7+8PR0dHHD58GK9evYKNjQ06dOhA+8y0adOgqanJehkLEFGTqYuLi6Gnp4cFCxYAaFgjnj59CisrK5pxQ1jy/K8kw/3bdEOfPn0i/7958yaAhsgpWVlZhISEEAdT7jv49OkTbt++jdOnT5M1vbnvl126dAnW1tZwdnamyTGVlZU4fPgwpKWlSR1OUeH27dtwd3dHYWGhsJvyW9CsDBs/ElKfPXuGly9f4uHDh9DW1iY5sLdv344WLVpAXl4eZ86cIdc3t02YJUuWQFVVlRScWrNmDTgcDnr37o2CggIUFBSgU6dO0NLSQlFRUZO0acuWLVBQUICcnBymTJmCtLQ0AEBISAjCw8Np1/6OikdmZiasra3Ru3dv4hEPMPsspkyZAiUlJezduxf5+fnIyMhAjx490LVrV2LcKCsrg6+vLwYPHszYfVlEm4sXL4LD4eD48eNEOMvIyICJiQnJHf7gwQP4+/sjIiJCoGHI/4m7d+9iwIABMDY2ZnPkCxDeeWffvn1QUVFBamoq/vzzT0yZMgXS0tIYN24cNmzYAElJSWhoaMDAwACdO3cmfai5zeN//fUXWrZsic2bN9M2Dvv06QNlZWUsXrwYW7duRXR0NOTk5Jqdpw6vnDR79myYm5vDyMgIqqqq2Lx5Mz5+/Ij169eDw+HA29sbXbp0gbOzM8zNzYXmVfbmzRts3boVc+fOxZMnT5r03iy/PqKmX4iibC/KNIVczSI68DrGXb16FTt27IC4uDji4+PJNdxNwIqKCuTm5jbLSA3unHPgwAH07dsXjo6OaNWqFfT09JCUlIT9+/dDXV0dlpaW6NOnD3r37o22bds2OwOPKCGKMnVhYSG0tLTIesXtN48fP4aqqip8fHyELsc2ZxnuwoUL8Pf3x9u3bzF+/HhoaGiQ+kAHDx5EixYtMGXKlP+z7k1zdVjYvn07pkyZggkTJiA5ORmXLl2CoaEhSdfGpaKiAhcvXhTJ5yDIYuUsdJqNYYN3kj916hT279+Phw8fkmNJSUlwdXUlRW9TU1PRq1cvrF27ViQHARO8ffsW4eHh2L9/P4CGQsAKCgqYOXMm2rRpg969eyM3Nxe5ubkIDQ1t0ueQn59PC2+sq6uDt7c3X52H35Vbt24hPDxcIErXuXPnoK2tjatXr9KOHz16FIGBgZCRkYGNjQ3Mzc1hZmbW7MMbWRp49eoVUlJSsHjxYgB/v+/Lly9DR0cH+/btQ3l5OebMmYP+/fvTNgeEQUVFBS5fvkzSbbAIlosXLyIiIgLLly8nx758+YK1a9eidevW+Ouvv/D06VMcPXoUJ06caLYeRJWVlejTpw/xCiovL8ezZ8+QkJCA06dPo2fPnvD09ISenh7c3d0ZybMrqsTHx0NJSQlnzpxBWVkZevXqBQUFBTx9+hRAwzoWExODMWPGYNGiRaQvNLc+wdK8ETX9QpRle1FGkHI1i2jAm2aK9z2Xl5dj/fr1EBcXJ17pALB582akpqY2eTubkps3b6JVq1bYunUrnjx5gufPn8Pd3R3u7u5ISkrCs2fPMGHCBISHh2POnDkiVbOgOSNqMrW+vj7GjBlDO1ZZWQlPT09wOBw4OTmxxY8FxN69e+Hp6QkDAwO0bduWpEnkzmH79+9HixYtMHXq1N9Kfo6JiUH79u0xceJE/PHHHzAwMMC4ceNw+fJlqKqqolu3bj/8HCvz/L40G8MGl9jYWMjIyEBfXx8tWrTAmjVrUF1dje3bt0NVVRWXL19GVVUVevTogbi4uGZdaKeyshIpKSkoLS3FnTt3oKWlRTzKEhMTweFw4OnpSfPmaurn8O3bN1y5cgUBAQEwNzf/rSbs/4SgUqNt27YNpqampJAl7/e/fPkSp06dQnx8PDZs2MBuRDVDftSf8vLyICkpCWlpab60Od++fUPXrl2ho6MDfX19tGvXDhkZGU3VXBYR4N27d9DV1YWsrCxf//j06RN69uyJyMhIvs81x3W1oqICNjY2iIqKwqdPnxAZGQk3NzeoqqpCU1MTiYmJKCkpQXFxMb58+SLs5jIK79xRV1eHgIAAUi/ryJEjUFBQwLp16wD8HY7fuA80xz7B8nsgKvrFryDbiyrNKeUwCx3uuz1z5gyCgoLg6+uLkJAQor9UV1dj/fr1aNGiBcLCwjBq1ChIS0sL3RNd0GzatAkmJiaoqKggxwoKCuDs7Aw9PT2kpKQIsXW/J8KUqbnj5MmTJ7hz5w4uXrwIoKFmlJWVFRITE2nXjx07FhcuXBBqhH5zhfd9jhw5kqzdXMMGb6rnAwcOQFpaGqNGjfot1vNTp05BW1ubRKUmJydDSkoKe/fuBQBcuXIFOjo6sLGxEWYzWUQMMeoXBwD5Ny8vj7p69SqVlpZG3bx5k1q8eDE1btw4avny5ZSmpibl4OBABQUFUaamptTLly+p+Ph4isPhUAAocXFxIf8S5pGWlqYCAgIoeXl56ty5c5SpqSkVHh5OURRFSUpKUiEhIZSUlBSlqKhIPtOUzwEAdffuXWrJkiVUTU0NlZGRQbVo0YKqq6trsjaIMty+KSbGzDDljpXKykraM+ZwOOTvjIwMSl9fn5o5cyY1atQo8j5atGjBSBtYhI+YmBhVUFBAHTp0iKIoitq/fz81bdo0avXq1ZSsrCz15MkTcm1tbS3VunVrav/+/VR8fDwVGxtL3bp1i+rcubOwms8iBFRUVKiUlBRKWVmZSklJobKyssi5tm3bUoqKitSLFy/4Ptcc19WWLVtSUVFR1JYtWyhtbW3q7du31LBhw6jCwkIqMDCQOnHiBCUrK0spKSlRcnJywm4uo3DXotmzZ1PLli2jsrKyKFtbWyo9PZ0aNGgQtXDhQmrMmDFUZWUlNXfuXOrNmzd8faA59gmW5omo6heiLtuLMkzL1SyiQV1dHcXhcKjU1FSqT58+lKamJtW7d2/qxo0blK+vL/X8+XNKQkKCGjlyJJWcnEw9efKEys/Pp27cuEEZGRkJu/kCpWXLllRdXR1VVlZGURRF1dTUUOrq6tSGDRuo9+/fUzNnzqR27NhBUdTfcx6LYBGWTA2AjJOuXbtSYWFhVLdu3ajIyEjKwsKCcnV1pXbu3EkNHTqU2r9/PzV69Ghq//79lJ6eHqWpqflT92ahU19fT95ncnIypaKiQm3evJmSkJCgJk6cSN2/f5/icDhUfX09RVEU1bdvX2rTpk3Uo0ePfov1q7CwkNLQ0KDs7OyoQ4cOUcOGDaNWrlxJDRgwgPr+/TtVV1dHJSUlUerq6uQZsbD80hEbvB43nz59wrNnzxAbG0uzZK5cuRJiYmJYvXo1Ll68iCNHjtA80Zu71ZNr6R0yZAhcXFzw5csXVFZWIiAggISxA8LzXvr+/TsyMzN/y0LhwuLRo0cQFxfH7Nmzace/ffuGwMBArF27VjgNY2kSqqur0b9/fzg5OWHixIngcDjYvn076uvrsW3bNkhISNBSwrGhxyxcsrOzYWFhgbCwMJJi6evXr3BycsLw4cOF27gm5uHDhzh79iyAv9fPsWPHIiwsDN+/fxdm0xiHVz7Yv38/NDQ08ODBA4SGhsLPz4+kueDy9u1buLq6YteuXcJoLgvLTyPq+oWoy/YsLIJm586dJEIQaKj/ZmpqijVr1gBoqBugoaGBVq1awdTUlFYMu7y8nKSOa+48f/4c0tLSmDlzJu343bt34e7ujgEDBrApXYWEMGTqM2fOQF5eHps2bUJVVRVOnjwJDoeDkSNH4uLFi0hKSoKlpSVMTExgZWXVrNOpCovGxeP19PTI3suePXvg5eWFwMBA3L9/n1x39uxZ2ueae3rwHTt2ICQkBCdPnkTr1q2xYcMGci4lJQVxcXG0qFRW1mEBmkkqqmnTpsHW1hZt2rRBp06d+IoKrVixApKSknz1G5q7UYOXGzduQEJCAmZmZtDX1xfJtE/spNR0bNq0CRISEhg3bhzOnj2L9PR0+Pr6olOnTiLXL1iYp7S0FPb29uBwOBg9ejQ5XlFRgS1btqBFixaYMWMGOd7cBSiW/57MzEyYmJhARUUFAQEB6N27N6ysrFBVVQXg9+wrjx8/xrRp09CmTRvk5OQIuzkCIz09HaNGjcLKlSsBAGvXroWWlhZ69OhBrvn69Sv8/f3h4eHxW8lYLM0TUdcvfgXZnoWFacrKyuDj4wNHR0ds374dAJCVlYW4uDgADYWGdXR0MHLkSLx8+RIaGhrw9vbGo0ePhNhq4bFr1y5ISEhg2rRpyM3NRWlpKWbOnInw8PBmlzLzV6MpZeovX75gxIgRmDt3LoCG2oq6uroIDg6GnJwc+vfvj1evXgFokOWEXUuxuRMfHw9FRUXcunWLpAcHGup0de3aFX5+fjh69Cj8/PxgZWX1W+lXjx8/hqSkJHG+5FJRUQE/Pz8MHTr0t3oeLP8dHODXizusr68nYVj79++noqOjqbi4OOrVq1dUUlISNWbMGCoyMpIWNrdgwQLq5MmT1NWrVykOhyOspguVzMxMKiUlhZKTk6Oio6OpFi1aULW1tWyaod8QANSxY8eocePGUXV1dZS8vDzVoUMH6q+//qIkJCSouro6NnVBM6ampobq2rUrVVJSQikpKVHh4eFUSEgIRVENqcr27t1LRUVFUaNGjaKWL18u5NayiBoPHjygAgMDKXV1dWrgwIHUqFGjKIpq6FcSEhJCbl3TkpGRQSUmJlL37t2j9u3bR1lYWAi7SQLh/fv3lIuLC1VcXExNmzaNio2Nperq6qiYmBjqwoULFIfDofT19anXr19T379/p+7cucOuJSy/HL+ifsHK9iy/I+/evaPGjx9PFRcXU4MHD6YGDx5MvXr1itLS0qIGDRpE1dfXUzt27KA4HA7VvXt36ty5c5SDgwN16dKl305OAUDt37+fGjFiBKWkpESJiYlRpaWlVFpaGptaVgRoKpm6urqaOnr0KNW5c2dKQUGB8vHxoTp37kxt2bKF2rdvHxUSEkL5+vpS69evp3R0dBi7Lws/JSUlVL9+/ajBgwdTISEh1Nu3b6lnz55Re/fupXx8fKg3b95Q169fpzIyMigdHR3qzJkzlISEBEkn9jtw6NAhKiwsjIqKiqL8/f0pANSiRYuooqIikr7+d3oeLP+ZX9KwweXSpUtUcnIyZW9vT4WFhVEURVHr16+nFi1aRIWEhFCjR4+mKR/czs8OggZYxYfl48eP1JcvX6j6+npKV1eXEhMTY/vFb0JVVRVVWlpKRUREUBUVFdTQoUOp0NBQcn7FihXUkiVLqJycHEpJSUmILWURRe7du0eNGjWK6tSpEzVlyhRKT09P2E0SCpWVldTdpwOnFAAADQBJREFUu3cpLS0tSkNDQ9jNESj379+ngoODKWVlZWr16tWUtbU1VVdXR504cYK6dOkSVVNTQ2lra1NRUVHs5irLL82vrF+w446lOQOAqq2tpSQkJKhHjx5RkydPpr58+UJFRkZSAwYMoCiKohwdHamwsDBq9OjRFEVRVGRkJNW/f3+qY8eOVMeOHYXZfKGSl5dH3b9/n6qsrKTs7e0pLS0tYTeJ5f/TVDL19+/fKWlpaWr37t3U+vXrqeTkZEpdXZ3av38/tWnTJio3N5e6fPnybz1OmoLS0lLKzMyMGjJkCDEm5ebmUvX19dSbN2+o2bNnU/3796c+fPjw2+7P1NXVUcnJyVRMTAxFUQ21adTU1KjDhw+zjlMsP+SXNWxwvQeLioqo+fPnU+PHjyfn1q1bRy1evJgKCwujhg0bRrM6i4LSwcIiqvB6K7L8Hrx69YoaN24c9f37dyo8PJwaNGgQNXv2bCo/P59avnw51bZtW2E3kUVEycrKokaNGkXp6OhQs2fPbvZFOFkajBvh4eGUjY0NFRUVRXXq1OmH17EKB8uvCqtfsLCILtxxlpycTB0+fJgqKCigsrOzKTU1NWrGjBlUeHg45erqSomJiVHz58+nUlJSqOTkZOr27dtUhw4dhN18FpZ/pCll6nnz5lHJycnU5cuXKQUFBSouLo7q0KEDNXLkyN8uoklYbN26lYqJiaHq6uqoUaNGUV26dKF8fHyo0NBQqkWLFtSff/5Jrv2d92c+fPhAff78mZKSkqI0NDQoDofz2xl5WP47flnDBkU1KNh9+vShNDU1qcTERMrc3Jyc27BhAxUVFUWtXbuWhPSxsLCwsPCTm5tLTZo0iXr+/DklLS1NPX/+nDpz5gxlb28v7KaxiDh37tyhYmJiqH379lGqqqrCbg5LE5CVlUVFRERQ1tbW1Pjx4ylTU1NhN4mFhVFY/YKFRXS5desW5eXlRa1Zs4ZydnamxMXFqeHDh1MVFRXU5MmTKX19fWrQoEHUly9fKElJSergwYOUlZWVsJvNwvIfaSqZOisri3J0dKRsbGwoaWlp6s6dO9SVK1f+0VmFRTC8fv2aqqqqovT19SmKajBg+Pr6Ug4ODtT8+fOF3DrR5Hc28rD83/zShg2Koqjs7GxqyJAhlI2NDZ+CnZKSQvXs2ZP1GmRhYWH5D7x9+5Y6c+YM9ebNG6pfv36UoaGhsJvE8ovADW1n+X3IysqiRo4cSWlqalJLly6ltLW1hd0kFhZGYfULFhbRJCkpiVq1ahV19+5dqmXLlhRFNciw/fv3p4qKiqiFCxdSPXr0oN69e0fJyspS7dq1E3KLWVj+e5pKpr5x4wa1fv16qk2bNtTo0aNZJxUhUlZWRt27d49asmQJlZ+fT2VmZrIRCSws/yO/vGGDoujegxMmTKBMTExo59mUCCwsLCwsLCwszHH79m1q48aN1JYtW1jvKZZmCatfsLCIHrt27aIWLFhAXblyhVJSUiJFlnNycignJydKU1OTiouLo0JCQoTdVBYWkaa+vp7icDhsGkUhAoC6dOkSlZiYSNXU1FDHjx9na0iwsPwLmoVhg6JY70EWFhYWFhYWlqaEm++cDQ1naa6w+gULi2jx4sULytzcnIqJiaHi4+PJ8YyMDCo6Oprq0KEDtXjxYrYAMgsLyy9BVVUV9ejRI8rCwuK3LBTOwsIEzUYLtbKyotauXUvJyspSmpqawm4OCwsLCwsLC0uzhsPhUABYowZLs4XVL1hYRAs9PT1q8+bN1OLFi6np06dTeXl51OfPn6mjR49S2tra1MaNG1mjBgsLyy+DlJQUZWVlRYmJiVH19fWsUYOF5V/QbCI2uLDegywsLCwsLCwsLCwsTMHqFywsogMAav/+/dSIESMoJSUlSkxMjCotLaXS0tKozp07C7t5LCwsLCwsLE1IszNsUNTfygcLCwsLCwsLCwsLC8vPwuoXLCyiRV5eHnX//n2qsrKSsre3p7S0tITdJBYWFhYWFpYmplkaNlhYWFhYWFhYWFhYWFhYWFhYWFhYWFhYmidsLDULCwsLCwsLCwsLCwsLCwsLCwsLCwsLyy8Da9hgYWFhYWFhYWFhYWFhYWFhYWFhYWFhYfllYA0bLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCy/DKxhg4WFhYWFhYWFhYWFhYWFhYWFhYWFhYXll4E1bLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCw/DKwhg0WFhYWll8WDw8PasKECcJuBgsLCwsLCwsLCwsLCwsLCwtLE8IaNlhYWFhY/jUbN26kZGVlqdraWnKsrKyMkpCQoDw8PGjXpqenUxwOh3r58mUTt5KFhYWFhYWFhYWFhYWFhYWFpTnBGjZYWFhYWP41np6eVFlZGXX37l1y7MqVK5SKigp169Yt6vv37+T4xYsXqY4dO1K6urr/0z0A0AwnLCwsLCwsLCwsLCwsLCwsLCy/N6xhg4WFhYXlX2NoaEipqqpS6enp5Fh6ejrVs2dPSltbm7p58ybtuKenJ1VVVUWNGzeOUlZWpqSlpSkXFxfqzp07tOs4HA516tQpytrampKSkqKuXr1KlZeXU2FhYVTr1q0pVVVVKjExka8969evp/T19SlpaWmqffv21B9//CHQ38/CwsLCwsLCwsLC0rxg092ysLCw/Bqwhg0WFhYWlp/C09OTunjxIvn74sWLlIeHB+Xu7k6OV1ZWUrdu3aI8PT2pKVOmUIcPH6Z27NhBZWZmUnp6epSfnx9VUlJC+97Y2Fhq8eLF1OPHj6lOnTpRMTEx1KVLl6ijR49SZ8+epdLT06nMzExy/d27d6lx48ZR8fHx1NOnT6nTp09Tbm5uTfMQWFhYWFhYWFhYWFgYgU13y8LCwsLy38AaNlhYWFhYfgpPT0/q2rVrVG1tLfXt2zcqKyuLcnd3p9zc3Egkx40bN6iqqirKw8OD2rBhA7Vs2TLK39+fMjExoTZv3ky1bNmS2rp1K+174+PjqS5dulC6urqUpKQktXXrViohIYHy9vamzM3NqR07dtCUndevX1MyMjJUQEAApampSVlZWVHjxo1rykfBwsLCwsLCwsLCwvKTsOluWVhYWFj+G1jDBgsLCwvLT+Hh4UGVl5dTd+7coa5cuUIZGBhQSkpKlLu7O1E80tPTKR0dHerLly9UTU0N5ezs/P/au3/XptY4DODPlXaxFtIIilIVf6Ho4FJ0azii0EVEQQehggQH0UHQTELpKHUR/4FOpbg4iaKDyaKgBQcXQVAc3Y7SWqWF9g5ycy33qrdobw18PlPy5s035836cJ7T/n53d3cOHjyYly9fLpk7MDDQfv369evMzc3l0KFD7bVqtZo9e/a03x89ejTbtm3Ljh07Mjw8nImJiczOzq7gyQEAgF9N3S0A/4VgA4CfsmvXrvT396fZbKbZbKZWqyVJNm/enC1btuTJkydpNps5fPjwsub29PQsa39vb2+eP3+eycnJbNq0KSMjIzlw4EDev3+/rDkAAMDqUncLwI8INgD4aUVRpNVqpdVqLem9HRwczP379/Ps2bMURdGulXr8+HF7z/z8fKamprJv375vzt+5c2e6u7vz9OnT9lpZlnn16tWSfV1dXTly5EjGxsby4sWLvH37No8ePfp1BwUAAFaculsAfqRrtS8AgM5XFEUuXryY+fn59h0bSVKr1XLp0qXMzc2lKIr09PTkwoULaTQaqVar2bp1a8bGxjI7O5t6vf7N+evWrUu9Xk+j0cj69euzYcOGXLt2LWvW/J3P3717N2/evMng4GD6+vpy7969LCwsLKmrAgAAfn9f192WZbmk7vbcuXOrUnc7NDSUoaGhnDhxImvXrl3B0wPwXwg2APhpRVHk06dP2bt3bzZu3Nher9VqmZ6ebvfkJsn169ezsLCQ4eHhTE9PZ2BgIA8ePEhfX993f+PGjRuZmZnJsWPH0tvbmytXruTDhw/tzyuVSu7cuZPR0dF8/vw5u3fvzuTkZPbv378yhwYAAFbE13W3ZVmuet1tq9XKw4cPMzIyktHR0UxNTaVSqSxrFgC/1h+Li4uLq30RAAAAAPCXs2fP5t27dynLMo1GI6dPn06S1Ov1VKvV3Lp1K+Pj4zl+/Hiq1WrGx8dz5syZJF/qbrdv357Lly/n6tWr7YeMl2XZDiRmZmZSrVYzMTGRU6dOJflSd9vf35/z58/n5s2b/7imjx8/plKp5Pbt2zl58uT/8j8A8O/csQEAAADAb0XdLQDfI9gAAAAA4Lei7haA71FFBQAAAAAAdIw1P94CAAAAAADwexBsAAAAAAAAHUOwAQAAAAAAdAzBBgAAAAAA0DEEGwAAAAAAQMcQbAAAAAAAAB1DsAEAAAAAAHQMwQYAAAAAANAxBBsAAAAAAEDHEGwAAAAAAAAdQ7ABAAAAAAB0DMEGAAAAAADQMf4E4j+XmPa8IZMAAAAASUVORK5CYII=\n"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1600x600 with 2 Axes>"
],
"image/png": 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eAKdOndKvv/6qgIAAr2Rg8+bNyp07t8qWLStJ+vXXX3Xvvffq559/Vv/+/TV48GAdOnRI9evX9xqH1a1Hjx767bffNGTIEL3yyiuSpBkzZuiZZ55Rvnz5NG7cONWuXVutWrWKcxJ5+vTp6t27t8qVK6cJEyZo+PDhqly5crzbcatbt65nuJjGjRt79q105YZ0tWrV0pdffqkePXpo1KhRunDhglq1aqWlS5fGWdfIkSP1+eefq1+/fnrjjTfibbTFduHCBZ08eVInT57UkSNHNH/+fM2aNUsdO3b0JCCrV69WdHR0vEMOuXXu3FmXL1/WmjVrEt2eW9asWfXQQw/pr7/+0m+//SZJnu7gAwYM0B9//KEXXnhBtWrV0jPPPHPN9W3dulUul8tr+J603K/XEt8xlhyjRo1S586dVapUKY0fP159+vTR+vXrVbdu3SSPT12sWDHVrFlTCxYs8ExbvXq1IiIi4v3eusU+ZmI/Ll68eM1tuk9Y5MiRwzPNPeTRY489lqS4Yzt37ly8sVy+fDlJr0+XLp06dOigc+fOxXt/kWupW7euChUq5JVofPLJJ8qaNWuiQxskNe7o6Oh4lzt79myyY01McHCwXnzxRa1cudIzxmt8tmzZovDwcHXo0CHeIQDSSvHixZOcKLktXrxYnTp1Ut26dbVy5coEh3KoWrWqwsPD9euvv6ZkyABwyyKnIKcgp7i+/ep+uAt8EydOVJUqVTRixAi98cYbnuP/WvcMGTZsmIYPH64GDRrovffe02uvvaYiRYp4tQF//fVX3XPPPdqzZ49eeeUVvf3228qSJYtat24d7/tKSMeOHbVy5UqdOXNG0pWi5aJFi6558U987d+kFIDiyzX27dunffv2qXXr1gneKy4hKdEWf/zxxyVJX331VbK27dahQwctXLjQc4HNyZMn9dVXXyW6D5MTd0RERJzl/v333+uKNTGvvfaaLl++fM2LkFatWqWSJUvq7rvvTvEYbsSwYcMUFhamKVOmJGn5sLAwNWzYUKGhofryyy9VvXr1eJcrV66cMmXKpG+//TYlw8WtJs36iAAOklBX8Z9++skk2dNPP+01vV+/fibJNmzY4JlWtGhRk+Q1zExERITlz5/fqlSpkuj2Fy1aZJLst99+MzOzFStWWGBgoLVq1coeffRRz3J33nmnPfTQQ57nrVu3towZM9rBgwc9044fP27ZsmWzunXreqa5uw/WqVPHLl++7Jl+8eJFy5Mnj1WuXNmru+q0adNMkldX8QcffDDZQ8a4KZ4uxn369DFJtnnzZs+006dPW/Hixa1YsWKeLsvurpu33357kru2Sor30bp1a7tw4UKcGH788ccE1/XDDz+YJOvbt69nWkJdxd3eeecdk2TLly/3TDt8+LBlyZLFcubMaRkyZLBffvklSe/lscces1y5ciX4Pn25X93i656b0DFmdqW7ddGiReOsx92F1e3w4cOWLl06GzVqlNdyv/zyi6VPnz7O9KvF7ib73nvvWbZs2Tzv7ZFHHrEGDRqYWcLdbxN6LFiwwOu9ZMmSxf755x/7559/7MCBA/bWW2+Zy+WyChUqeA0H8NBDD5kkCw8P99rW+fPnPa//559/7L///vPMc3chTuixbds2z7LX6oK9dOlSk2QTJ05MdL/FFrtbcb9+/axkyZKeedWrV7cnnnjCs7/iG34qqXEntNwzzzwTb1zXO/zUokWLLDw83HLkyGGtWrXyzL96CICJEyeapDjDCFy+fNnrs/rnn3/iHZoqITc6/NTOnTvt4MGDlj59euvdu7dnfkJd4AsUKGDp06e3+vXr29mzZxONbevWrSbJPvnkkyS/HwBA4sgpyCkSQk7hvb34Hu7c4ur1XLx40SpUqGANGzb0mn718FOVKlVKdH+amd13331WsWJFr88vJibGatWqZaVKlUpS7D179rRTp05ZxowZbc6cOWZm9vnnn5vL5bLDhw/H2/7r0qVLgu+7adOmnuXc+/Ojjz6yf/75x44fP25r1qyxkiVLmsvlsh07dniWXb58uUmyCRMmeMUYExMTp/0ae1jepLbFkzKMU0hIyDV/l2KL3W7fvXu31zE2efJky5o1q509ezbe4bqSG3d8j8DAwHjjut7hp9zH2xNPPGFBQUGeYaWubt9HRER4fjuu9t9//3l9VtcznNf1Dj/l/t43aNDA8uXL59l2YsNPFS1a1IKDg73yu4SULl3amjdvnuT3A1yNnhrADfjiiy8kSX379vWa7r6Z29VXixQoUEAPPfSQ53lwcLA6d+6sH3/8UaGhoQlux92d9JtvvpF05eqp6tWrq3Hjxp6rqsLDw7V7927PstHR0frqq6/UunVr3X777Z515c+fXx07dtSWLVviXPXRrVs3r6uQv//+e504cULPPvus19U0Xbt2jXOzrezZs+vYsWPauXNngu8jOb744gvVqFHD62bOWbNmVffu3XX48GHPFUluXbp0SdbN4x588EGtXbtWa9eu1fLlyzVw4ECtWbNGHTt29FwNcvr0aUlStmzZElyPe15yulC7r5Rxr1+SihYtqqFDh+rUqVPq27dvkrsl//vvv15X5FxLau/Xa7n6GEuOJUuWKCYmRu3atfO6oiZfvnwqVaqUvv766ySvq127djp//rxWrVql06dPa9WqVde8cir2MRP7cfXNFM+ePavcuXMrd+7cKlmypPr166fatWtr+fLlXl323cfM1VdOTZ061fP63Llzx7mhuSR179493ljKlSuX5H0Q33GYHO6bmO/cudPz77X2YVLjLlasWLzL9enT57piTUxISIj69OmjFStW6Mcff4x3mYQ+q19++cXrs8qdO3eqXOGVmNtvv12PP/64pk2bpr///jvRZU+dOqXLly+rUKFC1/xeu39XTp48mWKxAgDiR07xP+QU5BRS/O3upk2bSvK+Yfh///2niIgI3XvvvYn2upWuHFu//vqr9u/fH+/8U6dOacOGDWrXrp1Onz7tdfV+06ZNtX//fv31119Jij9Hjhxq1qyZp2f4/PnzVatWrURv8BwUFBRv+ze+K/yffPJJ5c6dWwUKFFCzZs0UERGhOXPmeF0Vn1D7NSIiIk779aeffvJaJqXa4lmzZr3uXKN8+fK68847vfbhgw8+mOgNq5MT9+TJk+Mst3r16uuK9VoGDRqUaG+NhD4rSapfv77XZzV58uRUiTExw4YNU2hoqKZOnXrNZcPCwpQ1a9ZrDnknXfmekGvgRqRP6wAAJzty5IgCAgJUsmRJr+n58uVT9uzZdeTIEa/pJUuWjDMWe+nSpSVd6TKaL1++eLeTN29elSpVSps3b9YzzzyjzZs3q0GDBqpbt6569eqlP/74Q3v27FFMTIwnAfnnn3907tw53XHHHXHWV7ZsWcXExOjo0aMqX768Z3rx4sXjvD9JKlWqlNf0DBkyeCU1kjRgwACtW7dONWrUUMmSJdWkSRN17NhRtWvXjvc9XcuRI0fi7Xrp7gZ/5MgRr0b61bFfS6FChbzGjG3VqpVy5cqlfv36adWqVWrZsqUnuUisIZaUJOVq7m7IV7/G3QiNb8zJxLgTpqRI7f16LTeyvv3798vM4hyPbhkyZEjyunLnzq1GjRpp/vz5OnfunKKjo/Xwww8n+pqrj5mEBAUFeYaWOnbsmMaNG6cTJ07ESeTcn/+ZM2e8Evq2bdt6PoOXXnpJ0dHRcbZRqlSpJMWSmISOw6SqUqWKypQpo/nz5yt79uzKly+fGjZsmOhrkhp3lixZbvj9JccLL7ygd955R8OGDdPy5cvjzI/9WcVWsmRJz1Afs2fP9gzJ4GuDBg3SnDlzNGbMGE2cODHB5e677z4VKVJEU6ZMUc6cORNd1v27Et/9QwAAKYuc4n/IKcgppMTb3atWrdLrr7+un376yeueM9dqs4wYMUIPPvigSpcurQoVKqhZs2Z6/PHHdeedd0qSDhw4IDPT4MGDNXjw4HjXceLECRUsWDBJ76Fjx456/PHH9eeff2rZsmUaN25cosunS5cuye3fIUOG6N5779WZM2e0dOlSLVy4UAEB3tcsJ9R+zZo1q6f9+tVXX+nNN9+Ms/6UaoufOXNGefLkue7Xd+zYUW+//bZefPFFbd26Va+++mqiyycn7ho1aiT7O3K9Yl+EFN8QzAl9VpL0wQcf6PTp0woLC7uuYYtTQt26ddWgQQONGzdOzz77bKLLzp07V4899pgaN26sLVu2JPr5mxm5Bm4IPTWAFOCLH+I6depo8+bNOn/+vHbt2qV7771XFSpUUPbs2bV582Zt3rxZWbNm9RoHNblu5Ir8smXLau/evVq4cKHq1KmjxYsXq06dOho6dOh1rzM5UqI3wX333Sfpf1evuRvlsW+ceDX3vORcIb97925JipO4Xo9cuXLpv//+u+H1JCQle2kktL6Evj9Xn8yPiYmRy+XSmjVr4r0C54MPPkhWLB07dtTq1as1depUNW/eXNmzZ0/W6xPiTkgaNWqkrl27av369QoNDY0znnGZMmUk/e94cCtcuLDn9cm5Yi65UuI47Nixoz755BPNnz9fjz76aJxkyimu1Vsjoc8qa9asns/q6pMyvnT77bfrscceS1Jvjffee0/t27fXpEmTEr0xpPt35bbbbkvJUAEAiSCnIKcgp0jc5s2b1apVKwUFBen999/XF198obVr13r1jElI3bp1dfDgQX300UeqUKGCPvzwQ911112eG6vHxMRIkvr16xdvrrF27dpk7etWrVopMDBQXbp0UVRUlNq1a3f9b/wqFStWVKNGjdS6dWvNmjVLrVq1Urdu3bzuUZNQ+zV9+vSe9mtyjrfkOnbsmCIiIm7o+OzQoYNOnjypbt26KVeuXGrSpEkKRuhb7ntrjB07Ns68kJAQ5c+fP85nJUl33323GjVqdN2F3ZQydOhQhYaGXjPnrlevnj799FMdOnRITZs2VURERILL/vfff+QauCHOPPsA+FhCCUbRokUVExMTpwtrWFi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+a6dPn/Z5PKtWrTKXy2U9evSwv//+2+fbf+WVV+y2226zjz76yN555x2rXLmy1ahRw/OdSU2x/za+8sorVqxYMRs1apSdOXPGJ383r45j5cqV1qBBA6tSpYpVrlzZp8fnX3/9ZXfddZe5XC7r3bu3Z3rsdgaQ2tI6x/CndrVZ2uUXsaVlu9rf8j2ztP+b6ZYW7Wozs0WLFlnt2rWtZs2aFhgYaPPnz/fp9mNLq/ZkWrcdRo4caVWrVrVvvvnGM23btm1Wvnx5u3DhQqpv/2rfffed3Xbbbfbhhx96Tf/3339Tfdv+kGu5uT/7xYsXW968ee2ZZ57x5GCx56fm9qOioszM7Ndff7WsWbNa586dvWJIC88++6zVrFnT89xXfz/95dzUyy+/bMWKFbOmTZtau3btzOVy2RdffOGTbftDfuFP58b8BUUNP9K/f39r3LixNWjQwIKDg61AgQK2devWVN/ugQMHzOVyWadOnbym16tXz6ZMmZLq249Pnz59rE+fPmZmtm/fPps5c6ZVqVLF2rRpYzNnzkz17Q8cONDy5MljkydPtvfee8+qV69uVatWtffee8+zTGr9AYmOjrZz585Z27ZtbejQoWZ25URqoUKFrFevXl7LpbZff/3VypQpY5MnTzYzs9OnT1v+/PktY8aMVrNmTfvpp59SPQazK42ZTJkyWevWra1mzZpWsGBB69Chg08Lf4cOHbISJUp4joHo6Gi7dOmSff/99z5NgC5dumRmZj/88INVr17dPv30UzMzu3z5sk+2v3DhQnO5XJY3b16fJ36XL1+2BQsWWK1atax58+Zp2tjetm2bFS9e3Hbv3m1maVfY2Lhxo5UoUcJ27NhhZmYXLlyw0NBQW7FihZ07d87MUr+xO2bMGHO5XFaiRAnPNPdxmppiv69Vq1ZZ+vTpbdy4cfbGG29Y586dLV26dDZx4sRULWzExMR4vnsnT560yMhIM7vyuaRLl866d+/u05M0P/30k1WoUMG+/fZbMzNbt26dBQUFef5u+uqE+siRIy1Xrly2Y8eONDkhYHblmAgKCrJ33nnHNm/ebL179zaXy+X5rqSmy5cvW2RkpNWpU8cqVKhg999/v3322Wee+RQ24GtplWO4pWW7Ora0zi/Ssl3tD/mev/3NNEv7drWZ2aBBg8zlclnVqlXt8OHDZua7E5Vu/tCeTKu2w5IlS+z++++3Zs2a2caNG83MbPv27XbPPfd4vWdf/e2eMmWK1a5d28zMzp49a4sXL7bWrVtb+fLlPb8dqcWfci2zKydus2TJYjNmzPDZNt1iF1Vef/11q1SpkrlcLmvTpo1PLm5M6HgLDQ21QoUK2cSJE1M9Bncc/nJuauHChZY/f3777rvvzMxs7ty5Pr/QMi3zCzd/ODfmTyhq+Inp06dbtmzZbMeOHfb333/bb7/9Zs2bN7e8efOmetIRHR1tK1eutFy5clnnzp0902vXrm0ff/yxmV35A5eaJ/Hd3A3LJ554wvLnz28TJkywe+65x1q0aGEvvPCCNWvWzBo0aOBpBKeGAwcOWOnSpW3x4sWeafv27bPOnTtb+fLlva6aSM3GXZMmTWzDhg127NgxK1CggHXv3t0zb+XKlZ4f85Tgfh8xMTFen8cPP/xgw4cPt+joaDt27JgVL17cevfubX/++afddttt1rp1a9u5c2eKxRGbO44jR45YmTJlbOrUqZ55n376qTVr1sw6derksyuJfv/9d6tatart2rXLTp48aW+++abVq1fPsmfPbvXr1/c0glPLvHnz7Pvvv/ea1r59e6tSpUqqbtfsf8dHdHS0HTlyxGbNmmWNGze2YsWKeV3tGFtKN2xixzBv3rxEG9tXX9mUGv777z+rVKmSlS1b1n777Tcz8y5sDB48ONVjMDNbv369FSxY0M6cOWO//fabDRw40EqUKGHZsmWz6tWre64wSg3uz3jx4sU2bNgwq1GjhlWrVs3TgyW1rnw9fvy4VwwXL160Zs2a2TPPPOO13ODBgy19+vT27rvvWnh4eIrG8Pnnn3udfFqyZInVrl3bSpYsaYMGDbKTJ0/atm3bfH6SZteuXVaqVCkzu/K5ZM2a1XOy6uzZs/bpp5+meI+NKVOm2P/93/95np84ccIaN27suWrpzz//tHXr1lmHDh1swoQJXp9farl06ZK1b9/ehg8fbmZX/o6UKFHC6++oWeqfoPnvv//s4MGD1rhxY2vcuLEtWrTIaz7FDfhCWuYYZmnXrk7L/MJf29Vple/549/MtGxXm3kf61OmTLGXX37ZmjRpYq1bt7ZffvnFzHz7N8LX7Ul/azusXr3amjdvbk2aNLFvv/3W1q9fb3fddZdPe3G5LVq0yIoVK2aDBg2y++67z1q2bGnt2rWzoUOHmsvlSrXipz/kWlf//rz66qv25JNPmtmVNtWGDRvsySeftI4dO3ou4ElN69ats8DAQJsyZYqtXLnS5s6da9myZbOWLVv6bNSGTz75xPbt22fnz583M7Pz589bz549rV27dhYdHe2zAqgvz025Xf0bOGrUKOvWrZuZ/S/PcRfZIiIiUv2Cy7TML/zt3Jg/oajhJ1577TVr1aqV17Tw8HBr2LChFS1aNFV+JGKLiYmxVatWWUhIiHXo0MHMzGrWrGlLliyJs6z7BzUlxP6hmjBhgr311lt2+vRpu3jxoj344INWpUoVGzdunOeP94oVK+yee+5J1e6X//zzjxUpUiTOH+tDhw5ZoUKFrGTJkql6RdPly5ft4sWLVr9+fXviiSesZMmS1r17d09CdvLkSWvXrp1Nnz49RX8wY5/oWrt2rS1fvtwuX75sv/76q8XExFjHjh3tscce81yt07BhQ3O5XNakSZMUu5pm1qxZNmnSJK9pBw8etIIFC9ratWu9pn/yySeWL18+27RpU4ps+1qOHj1quXLlsiZNmljevHmtdevWNnr0aPvyyy+tbNmyqXpM7N692+rVq2cBAQHWq1cvz9WEv//+u9199902d+7cVNu2+xhbu3atvfrqq7Zv3z4zu9JwaNCggRUrVszTW8HsSkP8xIkTqRaP2ZXvyNy5c+NtbD/11FNWtmxZn1yx8d9//1mtWrWsZMmSXoWNmTNnmsvlspEjR6bo9rZs2eJJKkeNGmVLliyx3bt3W/Xq1e2OO+6w3Llz29NPP20zZ860I0eOWFBQkOeKw5TkPiYuXbrkleRu3rzZKlWqZNWqVfP8TpiZffvtt3bq1KkU2faUKVOsUaNGXleiREVFWd26dW3gwIFm5l1MadeuneXJk8fefvvtFOuxERoaasWLF7cnnnjCDhw4YHv27LHs2bPbyJEj7YUXXrDKlSvbgw8+aEeOHPGcpHnuuefsr7/+SpHtx2f48OG2cuVK27Jli1WrVs1mzJhhISEhXlf0bdq0yR577DGv7+uNWrt2rRUqVMieeeYZ27Nnj5ldKZ7ccccd9vTTT9s333xjbdq0sRo1alizZs0sICDARo0alWLbjy3238Nz585Z6dKl7YsvvrDw8HArWLCgde/e3bPM1KlTPd/ZlN7+8ePH7ZdffrGIiAhPe+n//u//rHHjxtasWTPPd/K1117zXDEOpKa0zjHSol3tD/mFP7Srr5YW+Z4//s1My3a12f/+Xqxfv95mz57teT5v3jxr0KCBtW7d2utv9U8//eTVrrpRad2e9Je2w9UnTFevXm1Nmza1li1bWq9evaxy5co2ZMgQGz16tI0bN87GjRtn/fv3T9FisPuzP3PmjF24cMGio6Pt1KlTNmDAAKtcubI999xznu398ccfVqNGjRRvv8THl7mW+3OI/Xn8/vvvdvbsWRs6dKjlyJHDvv32W2vTpo01adLEHnjgAatSpYpVrFgx1Xv09OvXz5o0aeI17ccff7Rs2bJZ27ZtU30oqtDQUMuRI4dVq1bNmjVrZj/88INdvnzZdu/ebRkyZIhzfiQ1pNW5qdjrWrZsmR0/ftzGjh1rTz/9tH322WdeF26ZXem1MWDAgBTvoZ+W+YU/nxvzJxQ1/MRLL71kRYoU8Tx3/0gsWLDAXC6X3X777Z4vSGpdtXH58mVbtWqVZcmSxTp06GDVq1e3UqVK2cMPP2yNGze25s2bW+vWre2pp55K8S65L7/8suXLl88mTpzo1YiNfXWt+2rchx9+OMV+MOPbl2FhYXb33Xdbr1697Ny5cxYTE+PZXrt27axOnTrWqFEj+/LLL1MkBve6T5065RnSyOxKQzdnzpxWuXJlr+Vfe+01K1mypP3xxx8psn2zKydn8+TJY6NHj7YVK1ZYQECA17i7UVFRdu+999o777zjmfbiiy/atm3bUuQqhejoaPvnn3+sTZs2Vr16da/Ed/fu3VakSBFbunSpJxa3ihUrWt++fW94+1dzfyaHDh2yPXv2eL57Bw8etNdee83eeustCw0N9SzfqFEjn3QB/eyzz6xr166WJ08ea968ub311ltWp04d69+/f6psz70fPvvsM8uSJYuNHDnSK8k6ffq01a1b14oWLWqfffaZvfTSS5YjR44UPTZjfz/Onj1r//33n5ld+Y2cM2dOnMb2zz//bD169EjRKzXcMfz111929OhRrysIw8PD4y1szJ07N0UbNQcPHrRKlSpZ27Zt7fnnn7eAgABPQ3rr1q02btw4W7Fihec38+TJk3b33Xfb+vXrUywGs//ti88//9weffRRK1u2rL300ku2atUqM7ty4rxatWpWpUoV27dvn7322mtWunRpr+/Ljdi6dasVK1bM2rVr53Ui7rnnnrPbb7/dIiIizOx/hY1XXnnFcuXKZblz506xworZlR4R1apVs+eff95GjhzpVcBatWqV1a9f31q2bGlHjhyx7du3m8vlsj59+qTKcBafffaZZcyY0TMee5MmTczlctnbb7/tWeb8+fN2//33W+vWrVO8DfHhhx/aXXfdZc8884zn6tI5c+ZYsWLFLEuWLDZgwABbt26dmZm98MIL1qFDh1Rrx3z11VeeglePHj3sueees4IFC9qzzz7r+dsaGRlpHTp0sEmTJqVYHO7vxdKlS61ChQqWL18+q1Gjhg0ZMsRT5P3ll1+sRYsWVrFiRatZs6ZlzZr1lu0mDt/yZY7hD+3q2NIqv0jrdnVi0iLf86e/mbH5ul1t5t22zpUrl3Xv3t1zYt/syom5Bg0a2IMPPmhbtmyx4cOHW968eVOs4OYv7cm0bjvEXteXX35px44dM7Mr9w24//77rUiRIpY1a1Z76qmn7J577rHatWtbkyZN7P7770+x49J9LKxatcratGljFStWtK5du3ra1Ff3HBs0aJCVLVs2xdrUV8eRlrnW4cOH7b777jOzK1f9uy+a27dvn7Vs2dKyZctmnTp18ty/4eeff7YKFSrY0aNHUyyG2Nz7pFu3btawYUPPdHcR5YMPPjCXy2UtW7ZM0XsZxHeMnzlzxhYvXmxt2rSx3Llz20MPPWSzZ8+2p556yjp27OjpIZ9S/OHcVOz9MHz4cCtevLj99ttvtnDhQitZsqRlyZLF62R/RESENW/e3Pr165diMcTm6/zC386N+TuKGj6W0AH+f//3f1a6dGl76aWXvJbZsGGD9erVy5o3b25ly5ZN0a6f7h+s2F2No6OjbdWqVVasWDHLkCGDvfXWWzZmzBgbMGCAvfrqqzZ48OAUvcrT7EqjLn/+/LZr1y7PtNj74MyZMzZjxgxr3ry5VaxY0XOyKiUTr/3799vx48c9V8G47xvwxhtveE6SnT9/3tq1a2czZsywihUr2osvvnhD249t2bJlVrNmTatWrZqNHTvW9u/fb2Zmb7/9tgUEBNgjjzxizz33nD3++OOWPXt2++GHH1Js22ZX/kDPmTPHMmbMaIGBgfbJJ5+Y2f+OkfPnz1vZsmWtdevW9tVXX1m/fv0sT548KXZFvvtqsF9++cWefPJJq1mzpk2fPt0zv127dlawYEHPOLNmV5LQevXqxale3yj3e16yZImVLFnSKlWqZDly5LCn/l979xnXRNr1AXgiYkdERaQXQbqIVBVBFBQLYkNYXbGAYhdRBAR7d+29rmtFcQWxYcdeUFDXjr2u2BAVUEr+7wd+uTcDuM+7MiERzvXleTaJZJLM3HPO3U5gIG+ZNFB47URGRkJDQ0MmSejBgwexfft2JCcnsxtmZmYmnjx5gj59+rDiWCKRCElJSYK/PwAkJydDQ0Oj2F7Tko59sViM9u3bw8TEBGZmZrzruLSkg/127drBysoKvr6+2LdvHwB+sO3t7c3OR1m0kwkJCbC0tISZmRnU1NSwfv161kkuGdgwNzdniZnQ8vLysHPnTqirq6NGjRrf7Qz99u0bXr16BW9vbzg5OQnaISD9XdSoUQMTJ07Eli1b0Lp1axgbG+Ovv/5CQUEBzp49C0dHR2hoaMDQ0FCwPUYlbfaVK1dgbGyMHj16sNlrt2/fhpOTE9q3b89LAseOHYsjR47IpEh2SkoKHB0doa+vj/DwcN5z+/btg5ubG7p27YrHjx/j8uXLMplZt2PHDqxfv543U+nZs2dwdnaGiYkJli5divnz58PDwwOWlpasHRGiY0D6Olu8eDEcHR0xePBg1k6/f/+erewCCs8fd3f3Yt/Vj7p37x47hoKCAmRkZMDCwgJHjhwBACxZsgTq6upwdXVlCbpYLGZbagiZfAGF7bWKigoWLFiA9PR0jBkzBlpaWhg0aBDrgEhLS8OqVaswYcIEXicWIUKQd46hSHE1IL/8ApB/XC1NUfI9RbhnKkJcDQCnT5+GiorKd+u47N27Fx4eHtDS0oKhoaGgq6nkHU/KO3aQ/E0JSWHyDRs2sPbq0KFD8Pb2hqenZ7HcT0Ko72Pv3r2oVq0aZs+ejS1btqBfv34QiURsogpQ2Jk8ZMgQ1K1bl/e4EBQh1wIKrwkLCwuYm5tDSUkJMTExvOeL5tljx45FixYt2P1EVhISElClShXe9olA4aQAFxcX6OrqCrbdj/S959ChQ4iJicG2bdt4gxZ79+7F1KlTUbt2bVSvXh3q6up4+vRpsX9fWvLum5J4/PgxAgICkJiYyB4bPHgwqxd48+ZNXLt2De3bt0ezZs1Yu16aCQqKkF8oUt/Yz4AGNcqQ9MUVExODqVOn4s8//8SHDx+Qn5+PWbNmwcnJCcHBwXj79i3S0tLQqVMnjBw5EufOnUP9+vVx4sQJQY/l0KFDGDp0KPz9/ZGcnMwC+oMHD6J+/foYOnSoIO8nUdLy5oULF6J9+/bIz88v1hAVFBTg1atXGDduHHr37s2eF7IIbVRUFHR1dWFqaop27dohPT0dQOHyMSUlJXTu3Bl9+vRBixYtYGlpCQAYPnw43NzcBAlorl27hnr16mHGjBkICAhA8+bN4evry24eR44cQceOHeHj44PRo0fLrCPkypUrLJCfN28ee1zyXV+/fh0NGjSAkZERDA0NBbt5bdq0CS1atMDbt28B8PfrlHTUZWdnw83NDQ0bNsTmzZuxe/duREREQE1NjRf4CuXkyZNQUVHBypUrARTuRy0SibBlyxZ2bm7cuBE+Pj7Q1taWyY08NDQUDRs2RP369dG0aVOEhobyAsi8vDy8ffsWK1euhKWlJdt6R+gZ0Fu3boWjoyOAwiR9586d6NChA5o2bYqxY8ey1929e1cm28JJOtBnzZqFzZs3o3///qhTpw4rupuXl4dt27bBwsICvr6+Mtlb9MCBA1BRUcGiRYvw7NkzREdHo0aNGpg9ezb7zB8/foSFhQWaNWsmeKAv+U2PHz8OPT09WFhYwM/Pjy2vlVyjX79+xaZNm+Du7g5HR0fWnpemnTpw4ACrmyIWi/HmzRu4ubmx2aXZ2dlQV1cv1hmVk5OD06dPC7p9hPTveuHCBRgbG6N79+5sT+yEhAQ4OTlBT08PQ4YMgY+PD6pVqybTzuPr16/D0NAQLVu2LNYBdODAAdjY2MDf318mhdNfvnyJunXrQiQSscJ9Eunp6ejduzccHR3RunVrBAcHC3r/lP4t5s2bh1GjRkFLSwtKSkoIDAzErVu32POfP3/GqVOn0LFjRzRp0kSQ94+Pj4dIJMKff/7JzvPs7Gw0atQIp0+fZq8LCQmBiYkJunbtijFjxsDf3x9qamqCdwqkp6fDw8MDc+bMAVDYKaOnpwcnJydYWVlh8ODB7B5X1sVfScWgSDmGPOJqRcwv5BVXS5NXvvc98rxnKkpcDQDz58+Hv78/gMJVPYmJifD390fXrl2RkJAAoHDm+uXLlwWdiS7PeBKQf+xQ1Lx589CgQQOcP3++WO21/fv3o0OHDujQoQOvQ1V6pVlpffr0CZ06dWIra9++fQttbW2MGDGCvebz58+YPHkyevToIbOJU4qQawHAnDlzIBKJ0KhRI/ZY0Zom586dw8iRI6GmpiZobRHJ57l9+zYOHjyIxMRElsMEBwfDxMSEfR8FBQWIiIjAggULZLL91fjx46Gjo4O2bdtCW1sb7u7uxe5xT58+xaJFi2Bubs6rkSQERemb2rhxI6pWrQpTU9NikyZ79+6NJk2aQElJCc7OznB3dxeknVKE/EIR+8YUHQ1qlBHphn/ChAmoVasWXFxcUKlSJQQEBOD27dv4+vUrlixZAnNzc1SpUgUGBgawsbEBUDi7z9DQUNDicUeOHEHVqlXh6+uLZs2aoWbNmli1ahWb5bpv3z6oqamhc+fOJX6O/2rLli1o2rRpseBw1KhRrLAp8E9DlJeXh3PnzuHdu3f48uULb6ZRaUi///79+9GwYUPs2bMHS5YsgaurK3R0dFgCdvjwYYwcORJdu3bFsGHDWPDr4+ODIUOG/PD3If3vzpw5w9tXe+vWrWjdujW6d+/OgjshZ9cWJfmbeXl5OHv2LDZt2gQlJSVMmzaNvUby/tnZ2Xj8+LGgM8l+//13ODo6onPnziUWIpMUf/r27RsCAgJgamoKIyMjODg4CJ4ASs6t8PBwFiA8fvyY7R0pkZeXh7S0NIwZM0Yme2levXoVrVu3RkpKCp4+fYpp06axmUwlzSRcvHgx6tevz2YLCEFyju7cuRPm5uYYP348WrVqBW9vb/Tp0we//fYbatasyZaGy8L9+/dhb2/PBpfS09Oho6MDc3Nz1KpVi+3vK5l1JoviYOnp6ejcuTPrrHz69CmMjY3h6OgIkUiEadOmsetB6AJlRa/3jIwMvHjxAlu3boWDgwN69OhRbMnx7t27sXbtWkE6aKT3wZbMmPzy5Qvs7Oxw9+5dPHr0CNra2qxgG1DYcSIJemXh7t277PuWDGx069aNJTYPHz5EaGgounbtCn9//+/OsBPS9evX0bRpUwwePLhYJ83hw4d5s2iEdv78edja2sLOzo51SkifN5mZmbyEUOhOgblz56J27dpITEzEpUuXMH36dNZeStrGw4cPw8/PD15eXoJ1jACFs5Tq1auHuLg45OTkIDs7G+bm5khLS+PdY5cvX46BAwfC3d0dISEhMpn9W1BQwLace/PmDUxNTTFkyBAAQL9+/VCnTh34+fnJvN4QqZjknWPIO65WlPxCQt5xdVFlne/9L/K4ZypSXA0UbqeirKyMY8eOoWPHjvDy8kL37t3h7u4Oc3NzwScJyTueLEoesUPRCUdfv36Fl5cXb8AR4H/OI0eOwMHBQfBVZBKZmZkwNTXFmTNn8PLly2IxdWxsLJ4+fYrPnz/LbEWCIuRakvNz9+7dmDJlChwdHWFvb8/OScnvf/fuXUydOhXOzs6CxvfSW8IZGBjA2toaLi4u0NTUxI0bN/DgwQOMGDECysrKcHR0hKOjI1RUVGRSsH39+vXQ1NRkE7YkkwGkt2eUHG9ubi7WrFmDFi1alHpFuiL1TUnz9PSESCTCxo0bi7VBaWlpSEpKwt27d3n33dKSd36hSH1jPwsa1CgD0hf7tWvX0KlTJ1y4cAEAcOzYMVhaWsLPz4+Nvufn52Pv3r24cOEC+7fjxo2Dra1tqfdQlN4jLzIykrdlRVhYGOrWrYvly5ezQHf37t3Q09MTbLatJBiRNNRAYcBgbGyMxYsX84KVt2/fom3btmxUXPr4hbBp0yasXr0aq1evZo/duHEDLVu2hLa2NvuupUfg09PTERkZiXr16vFmk/wXks9w5swZLFu2DJGRkcWCJcnNw9fXlzfiK4viSzk5ObxzNCsrCytXroSSkhKvKNu6deuwZ88ewd5fIj8/HzExMSUWIuvXrx+cnZ2xZs0a9vpHjx7h77//FnR/fMl3IfnN+/Xrh8WLFyMvLw9aWloIDg5mr9mxYwfbw1AWe/3GxMSgS5cuGDhwIHvPrKws/Pbbb3BwcEBwcDAL7iQBenp6OqysrHjX1Y8o6fz6+PEjQkND4eHhgeHDh7NOj6dPn8rk5ik5hm/fvuH9+/cYOXIk3r17h+fPn6Nx48Ys4WnVqhVq1aqFbdu2Cfr+Rb179w6rV6/G33//jfT0dFhYWCAwMBBA4SyN2rVrIzo6WtDzEeAHZceOHcPx48dZW5CTk4Pff/8dDg4O6NWrF1suP2bMGLYPLyDM+ZmSkgIHBwcEBQXhxo0byMnJgYWFBVavXg1jY2MEBQWx93n8+DH8/f1x8ODBUr9vSR48eAB7e3sMHz6czV6RHtiQPv/FYrHMA21pqampaNasGYKCgn743vD/NXv2bCxbtox9vosXL0JfXx/u7u68RKcoIe4f0sUc8/Ly4OnpWWzv8eXLl7Mio0+ePIFYLMa1a9cESTi2bdvGSyJ/+eUXqKqqYteuXXj06BGsrKzYvtiy8r3vMSsrC0DhzM9OnTqxTilJR3KPHj1kWviWVEyKlGPIK64GFCO/UJS4WvpY5JXv/S9lec+UZ1wN/PNbSN/78vLy0K1bN2hoaKBv375sldT9+/dhZmYm6ExbRYgn5R07tG7dulih8Tdv3kBdXZ1tASZ9zebk5LBrQbqtLK2iMVpOTg66deuGJUuWwNDQEIMGDWLv9erVKwwYMIBtXSckRcm1pK8N6UGnM2fOwMbGBvb29uycBAq3qEpJSRE85wIKf2dVVVXW53Dq1Ck2eQ0oHIA6duwYwsPDMXPmTJmtThg3bhxGjhwJoLDPQVVVlQ04ZWdnswkCku/uwYMHqFevXqnycUXom/q3a6xly5bQ1dXF6dOn//V1pblOFSG/kFCEvrGfDQ1qyJB0QTig8GbdtWtXdOnShddAHzlyBJaWlvD392f7g0tcvnwZI0aMgKqq6g8vZ9q2bRsLGMViMa5evQpVVVVYWVkV2x8wLCwMampqWLlyJZsRUNriQ2KxmBcMXbhwASKRCMuWLQNQGHD/+uuvcHV1ZUU1L1++jM6dO8PBwUGQEdeWLVvyOtoeP34MU1NTiEQiXpE+oDABa9WqFfT09HgFgdPT0xEWFgYjI6NSLy2Lj49HtWrVYG5uDlVVVairqxcL6rdv3w5bW1v07dtX8O1sJDegw4cPo2vXrmjXrh369OnDvuvc3FysXLkSlStXRkBAAIYMGSKTbVyktwHYtm3bdxvv5s2b8xpvWdi+fTuUlJTw+fNnzJs3DxoaGmjYsCFGjx7N27bg119/RUhIiOC/CVAYrAwePBja2tpwdnbmPZeVlYX58+fD2dkZfn5+vOsiMjISlStX5p2v/5Xktzh79iymTJmCsLAwds3k5+cXawcmTZoEMzMzvHr16off83vHcPToUYSEhODRo0cs4Q4JCUGPHj3YbPTBgwdDXV0denp6+Pjxo0xnFUo6YmbNmgUPDw/WWTlz5kwYGBhATU1NsFmWPXv25CUPYWFhUFVVhYGBAapXr84KhX379g0bN26Eg4MDLCws4OHhAU1NTZksz5d0PgQGBuLVq1dYvnw5RCIROnbsyHvdhAkTYGVlJdjesiUJDw9Hy5YtERoayr7zixcvwsTEBL6+vjh16pTM3vt/SU1NhaOjI/z9/WW65VVoaChEIhE2bNjAG9jQ09ND27Zt2bUg9DUh/fcuX76MrKws+Pj4YPjw4QD4HQ6BgYGoW7cuevXqxZt1W5qE4+HDhzAzMys2i/eXX36Buro61q5dCwMDA/j6+mLy5MmYO3cuJkyYgLFjx2Lr1q2CbRkh+RvXr1/H8ePHi8VtoaGhcHR0ZG3m2LFjMXfuXJlsz0cqLnnnGIoQVytCfiF9LIB842p553v/VVncM+UZVwP/nBdHjhyBv78/vLy80K9fP9ZhXrSTLDw8HPb29oLcLxQlnpR37AAU5jaSwVTpNqNz587w9vZm37fkufPnzyM8PJy3JVVpj0G6jYiKimL77kdHR7OYWvrYIiMjYWZmxuolCEVRci3J3zpw4AD8/Pxgbm6OsWPHssG0U6dOwd7eHra2tkhLS2Pfh9BF0iXWrVuHvn37AiicuKerq8vOUQAy6TAu+n0WFBSgV69eWLhwIVJSUlCrVi02IF1QUIAlS5bgjz/+4P27VatWQU1NrdQd7vLsm5K+tg4cOIAVK1YgPj6et3rU0dERRkZGOHPmjOCT1hQlvwAUq2/sZ0KDGjISFRWF/v37807wtWvXonbt2tDV1S22XO3o0aOwsbGBl5cXbymuZJn2jxZr+95F2qdPH4hEIsyZM6dYoxQREQGRSIR169YJcoFKB8mSxnHWrFmoUqUKSzxev36N0NBQmJqaQllZGRYWFnBxcRFkuWl2djaWLl3Kmxn27ds3HDp0CE5OTjA3N2fFeKSP09TUFF27duU9/uLFix+axST9PWZkZGDy5MmsQyohIQEeHh5o3rx5sd85NjZW8GXYku8yPj4etWvXxujRo7F69WoYGRnB3d2dzQ4qKChAXFwcHB0d0aFDB8H3IC/puLZv3w5nZ+dijXdgYCDMzc2xadMmQd9T8ru8ffsWgYGBLBF//vw5fHx8oKGhwZbZ5uTkIDIyElpaWjLZckri3bt3iIiIgK6uLqKjo3nPZWVlYfLkyQgKCuLd0P/8889SFWOW/K24uDjUr18f7du3Z8USV61axUs49u3bhxEjRqBu3boyWeK4e/duVK9eHdOmTWPBTG5uLlq3bo3Ro0ez1w0fPhzr1q0TtKOwaGelpJaExKBBg9ClSxfWLo0dOxaHDx8WbEl4dnY2Bg4cCGVlZcTHx+Pp06ewsLDA5cuXce3aNcyaNQuVKlXCwoULARS2Y8eOHUNISAiGDx/OfidZrCBKTU1F06ZNERQUhGPHjmHcuHFQUlLCvHnzMG/ePAwdOhQqKiqCthPf65yfPHkyHB0dERoaylZsJCcno169eggICCjWnpel5ORkuLm5CTrYV5LJkyejcuXKWLduHW9gw9DQEE2aNBF8QEO6vQkJCYGxsTHevXuH8PBwqKurs3ZS8r4TJ05Es2bNMGzYMEGSj/379/MGDq9du8bbX9fPzw8ikQg2NjZo3749fv31V/j7+8PT0xOdO3cu9TYFs2bNwoQJE3htZc2aNdG4cWOIRCJERkayzo/Vq1ez7Tz69u2LmjVrVsj9bYnsyDvHUIS4GpB/fiGhCHG1IuR7P6Is7pnyiKul7dmzBzVr1kRoaCi2bdsGAwMDNGnShPdbHT16FKNGjRJsT3ZFiSflHTsUNXv2bPTp04cN/C5btgy2traIiopiqy2/fPmCzp07o3379oIfw+7du6GiooJx48bxOoyHDBmCWrVqISoqCpMmTUJQUBBq164ts9xbnrkW8M/vLanlMXHiRGzZsgWtW7eGsbEx/vrrLxQUFODs2bNwdHSEhoYGDA0NBbsmSzJt2jR069YNjx49gq6uLgYPHsyOc9++fYiOjmbniBCkr62HDx+yFRg7d+5EtWrVIBKJsH37dvaaz58/w9PTE1FRUewxsViMBQsW/FCMq0h9UxLjxo2DhoYGmjVrxmr+rFixgj3v7OwMExMTHDt2TLB7lrzzi38jj76xnxUNasjI+/fvWUCQmprK26uvYcOGGDp0aLGO0X379qFv377FbqA/2kHzvy7Svn37olatWoiLiysW6E6aNAl37979ofeVduzYMfTu3Rv5+fkYOXIkmjRpwjoA58yZg0qVKrHEIycnB58+fcLhw4fZzQwQdg/P6dOnY926dQAKb97Hjx9HkyZN4OjoyJvZBhQu5SptMFd0G5aUlBRoaGjAyckJFy9eZI8nJiaiQ4cOcHJyksky7M2bN/NuCjdv3oSlpSX77l+9egVdXV3UqFEDlpaWvD3xs7KyBJ+9JV2M68KFCzh06BB7bteuXWjevDmv8b5+/TqGDRsmk308L1++jFatWqFVq1a8a3Lfvn1o3bo16tSpA09PT7Rp0wYNGzaUSUf+x48fkZubyzoI3r59i9DQUDg7O2PKlCm81379+lWQ/Z+lC0ADhTMcNTU12T6NL1++RNWqVVGpUiXMmjUL+fn5+PbtG6ZMmYJevXr98EDrv7l37x4MDQ3ZMltpktmcK1euxMiRI6GpqclmOQlp9+7dqFevHtTV1dG0aVOEhYWx5xYvXozKlStj2LBh8PX1hYqKiuD782dmZmLs2LFQUlJCVFQUxo0bx54Ti8VYuHBhiTNhJWSxUkMiNTUVdnZ2CA4OxpEjR7Bs2TJYWlrCyckJv/zyi0wKGF64cAG//fZbsfZ58uTJsLKywvjx41k7ceXKFTx48EDwY/ivZDGoUtK5Hh0dzQY2JL/76dOn0a1bN5kMbAGFM9UCAgJ4tXRcXV3RuHFj3Lx5Ex8+fGDbakhmLwGlm+H4+vVr6OvrY8CAAbh+/Tq+ffsGLS0t9OrVi5fwBwYGQkVFpdiMZCEsXboUIpEIM2fORHp6Ouzt7bFx40Y8ePAAO3fuhLKyMoKDg/H161fk5uay5LhDhw5lUteFVCyKkGNIlHVcLSHv/EKR4mpFyPdKQxb3THnE1SV5//49nJycWN2G9+/fQ09Pj1eY/fXr15g8eTJcXV0FjaMUKZ6UR+xQ0r+Pi4uDkpIS7/uPioqCnZ0dGjdujC5dusDW1hbW1tZs4FOoztM7d+5AV1eX5VlFTZ48GR06dICjoyOCgoJkkmcB8su1pPNOsViMN2/ewM3NjZ1/2dnZUFdXL7btUU5ODk6fPi3o1niS3/TJkydsNda+ffvQokULNGzYkG0zLJmBP2LECAQGBgrSbq9cuZIXu0ZERMDS0hL16tVDWFgY9u7di7CwMGhpaeH48ePIzs7GgwcP4OXlBTs7u1LXslCUvimA38bExsZCXV0dZ8+ehVgsxl9//YXx48dDW1ubrSoDAGNjY/j6+gry/oqQX0goUt/Yz4gGNWRAei/ruLg4mJubY9WqVexk3bx5M7S1tTFixIjvzt4rKCgo1U30/3uR+vv7Q1VVtcRAVwhLlixB8+bN0aRJE9StW7dYAVlJ4rF8+fIS/72QMyTEYjFGjhwJkUjEluPm5ubi2LFjsLW1hbOzc4mB9Y8GuBcuXECdOnXw999/s98yOTkZ3t7eqFKlCs6cOcN7/aFDh+Dt7Q1TU1NBl2F/+fKFjbZL9g29evUqIiMjARTOkjMyMkJwcDAePnwIXV1dtG3bVibFVIF/Gu3du3dDR0cHzs7OUFNTQ6dOndiNVrLcztvbmyVqsjg/gcLr0c7ODrVr18bz5895zz179gxLlixBaGgoli9fjocPHwr+/vPmzUOHDh3QtGlTREREsN8+PT0dY8aMgbOzM6+4pERp2wdJAWhJ0LxhwwY2++PZs2fQ09PD8OHDWdKzdOlSAIW/g2SZstCOHj2Kxo0b82aASD5namoqhg4dCkNDQ9jZ2cmklsenT5/g6emJLVu24Pbt25g+fTpsbW0xYMAA9rrp06fD1dUVnTt3LraSozSk25nMzEyMGzcOIpEInTp1KnacCxcuhLKycrH9gctCSkoK7O3tERQUhFevXvH2EBeaWCxGYGAgLCwssGjRomIdZL169ULDhg0xZMgQtmKjPNq/fz9EIlGJtUrCwsJQo0YNbN68uVgdDaE7Z1avXg01NTU4Ojry2sJnz57Bw8MDdevWhaWlJczNzWFiYiJoEcGUlBSW6GdkZCApKQlGRkbo378/ry3o1asX6tevj+3btwt2TkrO8XXr1qFSpUoIDw/HwIEDee1gYmIiqlSpgkGDBvGSNHmuGiLlkyLkGBJlHVdLk2d+oUhxtaLke4pEHnH197x+/RqWlpZ4//49Xr16BS0tLQwePJg9f+DAAQCFgzBCzYZXtHhSnrGDxJ07d9gs+4MHD6JatWq8gtzHjx/HxIkTMWzYMMyZM6fUxdFLus5OnToFa2trvHjxgv1GRT/jt2/fkJubK9MJSvLItaTzTkk7+OXLF9jZ2eHu3bt49OhRsSLphw4dKtauC0HyWePj42FhYYH169fj06dPyM/Ph4+PD6pVq4a9e/ciKysL79+/R0REBBo0aCBI+/3o0SPo6Ohg0KBBuH//PhISEqCtrY34+HhMnToVzZs3h5+fH+bOnYtRo0ahcuXK0NPTg42NjSArDBWlb0qyQgz45xqbOnUq2rZty3vdkydPEBwcDC8vL16eJ2R+I8/8QkLR+sZ+RjSoIUMPHjzAx48f0a1bN7i5uWHNmjW8pENHRwejR4+WWefx//ci9ff3R/369RETE1NicdEfIX2Tlizb6tKlC+sEkH5+zpw5qFKlCpvFIpRr166xpXxTpkzB1atX8eXLF0RHR6NSpUrYsmULgH8SMHt7exgZGQnWQEiKbwHgzZhLSUlBu3btoKGhUWx21N69e+Hr6yv4qOurV6/g6+sLNzc3loA9fPgQBQUF6N27N/z9/Vkg5enpCZFIhObNmwt2PhR17tw5qKmpsdl9J06cgEgkYrNGCgoKsHPnTpibm8PX11ewBLwkeXl52LVrFxo1agQXFxc2Al4WJMUx165di7lz56J58+ZwdXVlM3vT09MxduxYGBkZYcOGDYK+t3QB6AcPHuD9+/dITk5GVlYW2rRpg8DAQBQUFOD58+eoX78+RCIRfvvtN0GPoaj4+Hjo6uqyQFv6dz979iwuXLiAL1++ICMjQ7D3lPz97OxsfPr0Cd26dWODW58/f8bSpUthY2PDG9j49OmTzAIJyd+VFPdUUlJCbGws71iBwuDPxcVFLltGpKamwsHBAX5+fmxQTFbHkZOTg+DgYDg4OGD+/Pm8pd9LliyBsbExfHx8ZLbHriIQi8UICAiAmpoaEhMT2WNA4X1Oskw9ISFBpsdx+fJltGzZEjVr1uTt2y6xdetWLFu2DAsXLpTJVmiSLdAGDhyIDx8+4OzZs9DV1S0W03Tq1An6+vpsT+jSkN4nVywWY9u2bVBSUoKGhgbbv1gSzxw6dAg1a9ZE79692d7L8trShZR/8sgx5B1XA4qRXwCKFVfLM99TNPKMq0uSm5sLW1tbzJs3D4aGhryi5M+fP4ebm1uJExaEoCjxpLxjh927d6NWrVrYuXMnmxxz4MABNrDxvcGTHz2GGzduoG7dusVqHGzfvh3Kysosh5H++1euXJHJ6vOSyCPXAvh5540bN5CTkwMLCwusXr0axsbGCAoKYt/J48eP4e/vL7NrIzExEdWrV8eSJUt4dQDz8vLQokULWFhYQF1dHe7u7tDT0xN0It3Vq1dhZ2eHkJAQhIaG8lYhSLZ98vX1xZEjR3Dz5k3ExsYiKSlJkBWGitA3dfbsWVSuXBm//PIL7/Fly5bBwsKi2Iqc2NhY1KhRo9jE0p89vyhKkfrGfkY0qCGg2NhYzJ49G0DhvpFt2rQBUBhA9ezZEy4uLrykY8uWLVBSUvrusk8h/H8v0o4dO8rkIj137hzmzZuHiRMnws3NDQEBAWzfVOlGeeLEiYIGVDdu3ICFhQUmTZqEIUOGQCQSscTu8+fPiIyMLJaA7d+/H/379y9VI1lSYPT48WNUrlwZoaGh7LGUlBR07NgRurq6xW4eQi5JF4vFLHi+desWOnTogBYtWvD2aHR2duYtQR0+fDjOnDkjeGEyaYsWLWL7KqelpcHY2Jg3OyMrKwsFBQXYtWuXoAM8/7a0b/fu3XB2dkanTp1Yh5R00if0jUMyw1Kyl+mhQ4dQtWpVWFlZwcnJiXUW//3331i6dKnM6iTY2toiMDCQzYZ5/PgxbGxskJSUBAB48+YNAgMDsXLlSpkNwEo8evQI1atXx4QJE4o9FxISgujoaJnssZuQkAAnJyd06dKl2F7gnz59wtKlS2FnZ4eePXsK/t7Sn2fp0qVo27YtG1jLzMxESEgIlJSUEBcXB4B/HsqqIPT/hyz2wZZ8jtevX+P9+/esDfr69SsGDx4MBwcH/Pbbb6yNjIyMxPLlywUr0q7oAgICoKKiwgY2gMJ2PSoqircFlRBKus7y8vJw9epVWFtbw9bWlg0wfa9zTJa1XQYOHIiMjAxeTCM9K7m0BRMlpAtqjhkzBjdv3sTOnTtRqVIlTJ48mX1Pktft3bsXDRo0KHVxWUKKkneOIa+4+nvklV8oalwt73xPEcgzrv63QrHjxo1DnTp10K5dO97jkZGRaNq0abFV4j9KEeJJRY0dfHx8YGRkhF27dvEGNqpXr45hw4YJvs2yZCu827dvsy3QHj9+DGtra4wZM6ZYYfIBAwZgxowZMslxipJXrgUUtlPNmjVDYGAgXr16heXLl7Mi6dImTJgAKysr3oDDj5Ku/SQWi5GTkwNvb2+MHTu2xNfl5+fj2LFjWLJkCQ4ePCjIMRQlWfWupqZW7B69d+9etGnTBl27dsWFCxd4z/3ItaFofVNZWVnYsWMH9PX14e/vzx5PTEyErq4uFi9ezCvKnpKSAhsbG5nWMwXKPr8oSl59Y+UFDWoIJD8/H4sWLYJIJEKbNm2goqLCK9QnnXSsXbuWBQ2JiYky2/taQl4X6a5du3hL5RYvXoyWLVvyEg8ArOiT0B10M2fORIMGDVC9enUcP34cwD8NuyQBU1JSYkvmpX+H0vwmz549YzNhYmJi0KdPHyxdurRYAHHlyhV07NgRRkZGMturUPJd7ty5E7169ULz5s1Ro0YNGBsb448//gAAuLi4wNXVFadPn0ZISAi0tLRk1mBLhIWFISQkBACgra3NK8YVGxv73f1GS+O/LO3r0qWLzFdsnDp1in0H+/btQ7169bB69Wrs2bMH9evXh4uLC65cucL7N7Ic2AgKCsKtW7fw5MkTiEQibN68Ge/fv0d0dDTs7OzKLAHesGEDlJWVERYWhhs3buD27dsYP3486tSpI+jSV+llt9WrV0dISAj8/f1Rp04deHt78177+fNnzJ07F61atRK0E1860ExKSsLs2bMhEonQr18/NkNKkogqKytjz5493/0c8iDk8lvp5eC2trYwNjZGo0aNMH36dACFs4uGDRsGR0dH2NjYoGfPnqhRo4ZMlqYrgs2bNyMiIgITJ05EfHw8ezwgIADVq1fH4sWLkZiYiC5duvD2lhViYEP6vLx79y7u37/PZk4VFBTg2rVrMDMzg4ODA+sckHUcI62kzjsjIyP06NGDt1+zUCQFNadPn846y9auXYtKlSrxOiEk7yl05wghipJjyCuuLkqe+YWixtWA/Dtl5E0ecXXRWcWHDx9GaGgo/Pz8sHfvXrx58wYvXryAp6cnnJycMH36dGzevBnBwcFQVVXlXceloQjxpCLEDv/2GXr06AF9fX3ewMbBgwcFXYkuXQvk9evXUFJSwuDBg5GXlwexWIzIyEg4Oztj+PDhePnyJW7fvo0JEyZAXV1d5hPHpJVVrlUSSTsVFBSEY8eOYdy4cVBSUsK8efMwb948DB06FCoqKoIUSR89ejSWLl3KOy9ycnJgZWXFBp6lz0GxWFxmOzb89ddfMDIygqenZ7HaawcOHICVlRUiIiLYcZWGIvVNAYW7I8TExEBXVxd+fn7s8cjISKipqWHq1Kk4efIk7t+/j3bt2sHV1bVMBvzKOr+QJo++sfKEBjUE5uTkBJFIxEY+CwoKWCdDeno6W6osvZccIPsOAXlcpA8fPkS1atVY0TygcGmZq6srevXqhStXrsDT0xPu7u7seSGOQfJdxsfHQ1tbG6amppg8eXKxwPPz58+IioqCSCTizdgvjdzcXPj7+6NFixYYM2YMRCIRW5a+fv16VK5cmXfzSE1NhYuLC6ysrJCbmyuThvLixYuoUaMGNmzYwILM1q1bw9HREbGxsbh69SqsrKygq6uLRo0aCbrEUiwWs9/j/fv3vP1Ma9WqBRUVFYSEhPBuVEFBQejfvz9vmxmh/Jelfb169ZL5DfTNmzfIysqCm5sbZsyYAaCwU9LOzg7a2tq8QmWyJD1z5unTp5g7dy5EIhEaN24MNTU1mRRH/56CggLExsZCTU0NOjo6MDY2hqmpqUyO4dq1azh8+DDmzJkDoLAzcteuXTAwMED37t15r/38+TNv5oiQxo8fD319fURHR6N79+5QUVFBly5dWCL66dMnhIaGQiQS4dSpUzI5BkVw9OhRVK1aFUuWLMG2bdtYYfaBAwcCKBzY2LJlC4YMGYKBAwfKrIiivI0bNw716tVDr169YGVlBTMzM/Tv3589HxYWBg0NDTRq1AgtWrQQdBsR6bZmypQpMDMzg7GxMRo2bMi7T167dg3m5uZwdnaWSVv9vxTtvEtKSoKVlZWghSSBfy+ouWbNGlSqVAmzZs0qk2SLEHnlGPKMq0sir/xCQp5x9f8iz04ZRVCWcXVsbCwqV67MZlPv378fVatWRdeuXeHi4gIdHR306tUL9+/fx8OHD9m2V/b29ujSpUuxjkwhyCueVLTYYcWKFbwteyS6desGDQ0N7Nq1i73/+fPnBa9hIckXduzYgZo1a2LEiBEACtvsmTNnwsHBASKRCBYWFjA2Ni7TNkJyHGWVa5UkNTUVdnZ2CA4OxpEjR7Bs2TJYWlrCyckJv/zyC27cuCHI+yxatIh9Jun7YLNmzfDrr7+y/5Y8l5aWhpUrV5ZZnb5r167B1tYWgwYNKpbTnDt3TpD+QUXpmyr6d758+YKYmBjo6OjwJmdNnToV9vb2qFatGqytreHk5MTynLIe2JBFfqFofWPlBQ1qCCwsLIwFC5KOMuCffS3T09Ph6enJG30rK7K8SIvOVJQ0PtHR0fD29ubtd7527Vq0atUKWlpaaNmypWB77RZt6N6+fYsPHz5gxowZsLGxQURERLFZ1tnZ2Vi1apWgwUxGRgZLPIcOHcoez8nJKfHmce3aNZksbZRYs2YNLCwseEV2X7x4ARcXF5iYmGDXrl34+vUrHj9+LNjshAMHDvBmH8XFxaFly5YwMTHBpEmTcPz4cVZ46/DhwwAKA8AJEyagQYMGMpslIu+lfZIZW9LS0tKgqamJvXv3Aiic9eXn54fdu3eXaUeZZMWGpHhZSkoK4uPjeYXkytLLly9x/vx5XLhwQSb1EjIyMqCpqQmRSMRbgpydnc0GNqSDLKEUbWsuXLgANTU1nDhxAkBhO3b69GnUr18fXbt2ZYnRx48fsWTJEpkWD5QXyX1j6NCh6N27N++5pKQkVKpUCXPnzuU9Xh6/B6BwYEdbWxtnz54FUNgBsX79epiZmfHuJ2lpaWz/dkD472Py5MnQ0NDAgQMH8OLFC3h7e0NFRQWbNm1ir7l+/TrU1NRYJ1FZS01Nhb29PXr16oWPHz8WKyQvhJIKakq3y1u3bi2TekOEAGWfYyhCXK0I+UVR8oir/4uyGvRVBPKMq3NyctCxY0doa2vj0qVLGD16NG+gLTY2Fp6envD392fbDeXk5ODbt2+8LXF+lCLGk/KKHYq2d02bNoWOjg7OnTtX7Ddv2rQpbGxssGnTJt7vINT3cfPmTdSrV49t4RMfH48qVapg+PDh7DWZmZk4fPgwUlNT5bpdpaxzrX8j2YIpKCgIr169Yr+h0EWYgcJ+iXnz5rFrYNWqVTA3Ny+WW4SFhcHBwYFdr2VBMrFw0KBBJa6OEGJgQ959U0WvQclnysnJwY4dO6Ctrc3b4vnhw4e4fPkyLl26JLM859/IIr9Q1L6x8oIGNUpB+gIteqHNnz8fIpGoWGN5//595OTkFAvSy4rQF6mkMJ9E0Y7ghIQE1K1bFxcvXuQ9/uLFC6SkpAjWUEn/FidPnsShQ4dYMAsA06dPR9OmTREdHc2ChwEDBvBmAgjVWObm5qJNmzZo2rQpPD09sXXrVvZcdnY21q9fj+rVq2P06NGCvN//snnzZpiamrJ95yUJ4V9//YVatWrB0tKSd4yl9fr1axgaGmLAgAF48OAB7ty5gzp16mD69OkYPXo07Ozs4Ofnh3nz5mHYsGFQVlaGjY0NnJycBC/GVZQ8l/ZFRUXBysoKqqqq6Nq1KzZv3gyxWIzPnz/D1dUVXbt2RXx8PNq1awdPT092Tpf1wIajoyP8/PyKFeQqD4q2t0lJSXBwcICDgwPv+s/JycHu3btRu3Zt9O3bV7D39/LyKjYz7ujRo9DS0mLFVyXHePDgQSgpKWHgwIH4+PEjAMglsJOlotv1eHl5scJxYrGYdUjNnDkTTZo0wdu3b1kgXF5nmkoG1KS3e8vMzMT8+fNhb2+PBw8eFPs3QrcRKSkpcHNzY0F1QkIC1NTU4OHhgcqVK2Pz5s3stffv3y/TraeKSk5Ohqurq6Dbwkn7t4KaSUlJuHPnDmJjY8t02whSMcg7x5B3XK0o+UVJyjqu/hFlMegrb/KMqyXX1tevX9G5c2c0aNAANjY2vO0igcJtyjQ1Ndl2bUJRxHhSXrGDdDu3bds2Vt+mTZs2MDAwwNmzZ3mxo5+fH+rUqSOTOnlAYYds8+bNsXr1avbYnj17UKVKFYwYMULQ1bU/u9TUVDg4OMDPz4+tVBDqviX9PUu2b5QUo09PT0dISAjMzc3RvXt3TJkyBb1790bt2rUF2xLuv5B8Dz179pRJwXh59k1J/54LFixA37594enpiR07drC2SjKw0atXrxL/hjxWQwuZXyhy31h5QYMaP0j64lq8eDH69+8PNzc3LF68mBWCk2ydMW3aNLx69Qre3t68G6i8tisQ6iIdN24cRo8ezZboxcbGQkVFBWPGjMHp06fZ63799Ve4u7sXS1AkhOwQCQ8PR6NGjdCsWTM0bNgQnp6eLBGaOnUq7Ozs0K5dO7i5uUFdXV1mnYNfv37F33//jU6dOsHd3Z0VTpRYuHAhNDQ0yqTA7f3791GtWjVMnDiR9/iVK1fg6uqKX375RfDihZLZFyNGjMD06dPZvvhAYQEsT09P9OrVCwkJCTh79ixmz56N7du3C3Ycira0b8WKFdDQ0MCGDRsQGxuLdu3aoWXLlmx279atW+Hq6goDAwO0bdu2TJdZFiWLAtCKQBJUXbhwAatWrcKsWbNw9OhRnDp1CmZmZmjfvj3v9dnZ2UhISBC0ZkNoaCjrqJf8tk+ePEH16tXx+++/81777NkzGBgYQElJ6btB3s9MugBzaGgonj59ilWrVqFhw4asboHkNStXroSNjU257JSRWL9+PZYuXYrjx4/DyMgI58+f5z1/69YtKCkp4ciRI4K/d9EEMi0tDUuWLIFYLMaJEyfQsGFDNvu0bdu2qFOnDi9ZB8q2pkZRspjVJ/G/CmpOnDhRrp+dlE+KlGPII65WxPxCmjzi6h8h60FfeZJ3XC1938zLy0Pfvn0hEomwZMmSYu9ja2uLYcOGCfK+EooQTypC7CD9Pd+4cQO2trawsbHBgQMHAACtW7eGgYEBTp8+zfK7AQMG4Pbt2zLNsQYPHgwrKyveY3v27EHNmjURGBgos1VkPyOh887nz5+zlRZ79+5lg2kLFizgTQb48OEDYmJi0KZNG9Zuy3Nb20uXLmHAgAEyOy/l0Tcl/VmioqJQt25dDBo0CN27d4eamhoGDRrEViDs3LkTBgYG8PT0FOz9S0vI/ELefWPlHQ1qlFJ4eDjq16+PpUuXIjIyEmZmZvDy8kJ2djZycnKwZs0aiEQimJubw9raWmFG54W4SIcPHw47OztMmjQJmZmZePr0KbZv346mTZvCwcEBbdu2xcWLF7FixQp4e3uzvVxl1VgvW7YM6urqrAjc6tWrIRKJ2DJcyWOjR49GYGAgS7xk2SHx8OFDdOrUCW3btmU31UmTJqFfv35lurRxy5YtUFZWxoQJE/D48WNkZGRg4sSJ6NevHzIzM2XynikpKXB0dIS+vj7Cw8N5zyUkJMDd3R3du3dHSkqKYO+piEv7Tp8+jTlz5rACkgDw7t07jBw5Evb29qyQ5YcPH/DkyROFmI0vy05Cefrzzz+hqqoKf39/NG/eHE5OTggKCsLp06ehpaWFDh06yOR9i7Z5v/32GytUKBaLMXLkSDg6OmLXrl3sNRkZGQgMDMT+/ftRo0aNclkgTFKAedq0abhy5Qpu3rwJb29vdOzYkVfMc+zYsWjduvV3O65+dl+/fkXHjh3RvXt3fPjwgdXQkJ6t9ezZM9jY2ODMmTMyOw7ptlOyZUrfvn0xZMgQdp/s168fzM3N4eLiUm5XyxQlz4KapGKTd44hr7ha0fKLksgjrv4R5TGek2dcLX3fS0xMxKxZswAUbl/bs2dP1KtXj7eCoqCgAK6urpg6dWqp31vy96QpQjypCLHDuHHj0K1bNzg4OKBOnTowNDRkxdA9PT1haGiIdu3aoXnz5jA3N2fHVdo2Q3rLJOnPlZmZCUNDQ8ycOZP3+p07d0JDQ6PMt3pSdEK1U5mZmfDy8oKHhwd+//13iEQi7Nixgz3/22+/sYEN6YElsVisEKvgpQvNy4o8+qb+/vtvjBw5kjcpISYmBjY2Nhg5ciRyc3Px+fNnbNy4Ed26dSu3derk0TdWUdCgRilcvHgRZmZmrEDYoUOHUK1aNVZ8R+LOnTtITExkN1BFaDRLQ/qmPWHCBNja2mLSpElsRtXr169x8uRJdOjQAc7OzmwPvzFjxsj0uIYMGcJG33fu3Ik6depg1apVAMDbykNaWfwWjx49Qrdu3WBlZQV7e3uoqqoWWy4va2KxGNu3b0etWrVgaGiIRo0aoW7dujJvNK9fvw5DQ0O0bNmy2OyHAwcOoGnTpujTpw+ysrJKHeQq4tK+e/fuQSQS8WaGSD7n58+fYWxsjHHjxhX7d+X1Zi5Pt2/fhp6eHpsldvv2bVSvXh3R0dEAgDNnzqBRo0Zo3ry54O8t+c0l/9u2bVuoqKhg3759AAq3rPj111/RuHFjREREYNOmTWjTpg1cXFzw8eNH2NnZISoqSvDjkqfvFWDes2cPvL29Ua9ePXTs2BHt27dH7dq1cfXqVfkcqIxJzokrV66gVq1aSE5OxsWLF6GmpgY/Pz+sXr0ap06dQrt27WBnZyfoILx0OxMXFwcHBwde/PLp0yfY2tpiypQpAArvl926dcOFCxeKndPlmbwLapKKSRFyjLKOqxU1v/jescojrq7o5BVXS2+9lpubi4KCArRr1w6LFy9mj3/9+hU+Pj5QU1PDzJkzsXXrVoSHh0NFRUWwLQoVIZ5UtNhh06ZNUFNTQ0pKCt69e4eXL1/C09MTdnZ27HebM2cOgoODMWzYMNZGleacEIvF7DMcO3YMTk5OmD9/PlttUFBQgHHjxsHHx4dtsSp5v++1naT08vPzER8fj8aNG0NZWRkrVqwAAF7tFMnAxoIFC8p0gun/V1nE1WXZN7V9+3aIRCLo6emxeEZiy5YtqFatGhsYlf6dymtfSFn2jVUkNKhRCseOHYOFhQWAwhnAKioqLNj/8uULEhISis0sLS/bFEh/jsjISNja2iI6OrrYzINjx45hyZIl0NPTg4mJiWDBvvRFLrno7e3tsWTJEpw/fx61atViv0V+fj7Gjx+PmJgYQd77R7x48QIbNmzA1KlTWeEweXj8+DESEhKwY8cOmRTCLsn169fRtGlTDB48uFjjffjwYUELUSvi0r6DBw9CTU0NPj4++PDhA+/cHThwIPz9/emmVQYOHz4MW1tbAIXBnL6+Pq9I/OXLl3H8+HFYWlrKrDiadDHLXr16oU6dOizhunfvHubOnQsdHR22nYdk1q2rqyvbUqG8nCtFCzBLf0937tzB1q1bERAQgAkTJlSI2fCZmZnw9fXFiBEjAAAnTpxgBUitra3h4eHBzgch4gjp73v37t0YM2YMateuDWtra7YfNVC4xVL16tUxatQo2Nvbw8bGRrAZjj8beRbUJBVPWecYihJXyzu/+K/kEVdXdGUdVz948AAikQh9+vThPe7m5sauCekaG35+fhCJRGjRogUiIyPx119/CXIcihBPKmLsMGnSJLRs2ZJX8+rFixdsRrT0qhWhB3+PHDmCpUuXokePHvDw8GAr6+7fv4/nz5+jWrVqvO+FyI7kt09LS4OOjg4MDAzg4+PDVg9Jd5hLtqJaunRpucmr/itZ9U0Vvb5fvHiBPn36QCQSISEhAQC/3omhoSEbfKooyrJvrKKgQY3/J+kGT3JDPHbsGFq1aoUdO3agdu3avBmnR48eRWBgYIlFPX9m32v4w8PD0axZM0ycOJHNqJJ27do1GBsbY82aNYIeT3R0NJsls2LFCtja2qJKlSrYsGEDe01GRgbat2+PGTNmCPre5P8vNTUVzZo1Q1BQEG7duiXT91KEpX1F63Ls2bMHVatWxdChQ/Hy5UuIxWLk5OTA1taWdWIS2Tpy5Ag6duyIx48fQ0dHB4MHD2Zt+dmzZzFhwgQ8efJE0LoN0oHdnDlzMHDgQF6thJ49e/ISUaDw3JE+hrCwMGhra5e7wu0lFWCW/B5JSUnlvnNo4cKFmD9/Pp4/f84eW7t2LWrUqIF79+4BKBzoSE9Px6NHj9i9V+jVhREREahfvz6WLFmCRYsWwczMDM7OzmzWZV5eHsaPH48OHTqgf//+gg6sEEIKKVKOIa+4WtHyC6JY5BlXFxQUYN++fahXrx4CAgLY4y1btmRbYOXl5bGYLzs7G126dIGpqSmvI7W0xyChCPGkIsQOkjZj9uzZsLe3Z59V8l7Hjh1D9erV4ebmxttyS6g46vLlyxCJRNi3bx8KCgrw6tUrzJo1C7a2trCwsMDMmTPh5+eH5s2bl8u6Norq/fv3uHXrFv788080b94cHTt2LHFgY82aNTLvk6jI1qxZw7bMffLkCXx8fFCvXj3eyvu3b9/CwMCgWH2PiqAs+8YqAhrU+H8oOuIouRmKxWJYW1tDJBLxRhhzcnLQsWNH+Pr6lqvRX+nvISMjAx8+fOA9VlLikZ+fz14TFhYGNze3H943cc2aNbhx4wb77/z8fHh4eLDCqRcuXICbmxucnJxw7tw5AMDTp0/RsWNHODk5/fTbfv3sUlNT4ejoCH9/f5nPvJbn0r45c+age/fubOBEEmTHxcWhatWqsLa2hq+vL3x8fNCkSRMqFldGHj9+jBo1akAkEmHUqFG850aOHIl27dohIyNDJu8dFhaG+vXrY/fu3cVWgXTr1g1qamrYt28fL/m8dOkShg8fDi0trXK5zc2/FWAePXo0Jk2aVG6vjezsbISHh0NVVRVt2rTBwIED8f79e+Tk5KBPnz4YMmRIiZ9d6NmNaWlpMDAwQHx8PHvs6dOn8PLyQpMmTXizsKW3S6B7KSHCkWeOoShxtbzzC6LYFCGuFovF2L9/P1RVVfHLL78AAJo3b464uLhir83NzUVeXp6gq34lFCGeVLTY4ebNm6hcuTLb7kriwIED6Nq1K7p3745WrVoV27qvNK5fv45du3aVuJXXrVu3sHnzZhgZGUEkEkFXV1chtzkqLyT3wadPn+LJkydssL+goAA7duyAs7MzOnfuzH6DRYsWYevWrXI73vJOLBYjIyMDKioq2LlzJ3v8+fPn6NSpE9TU1DB58mSsXLkSnTp1grW1dYXNK8qyb6y8o0GN/0E6qF6+fDl69+6Ntm3bstlJN2/eROPGjeHi4oLNmzfj999/h4eHB6ysrHiJyc9O+nuYMWMGPDw8oKGhgYiICBw/fpw9Fx4eDjs7O0yePBnp6ekA/vn8fn5+6NKlyw8Fm+fPn4eSkhKGDRvGlsjl5+fDwsKCFQIDgH379qFt27Zo2LAhTExMYGtrC2dnZ5pdqiCSk5Ph5uZWJjNW5LG0b/Hixahbty4iIiJgaWmJRo0a4Y8//mBbROzbtw+qqqqwtrZGUlISOx+FLu5JSrZnzx7UrFkT4eHhSEtLw40bNzBu3DjUqVOH17EjpPj4eOjp6fFmpnz+/Jk3w65Hjx4QiUQ4e/YseywrKws7duzgFYsubyp6Aebnz59j7dq1aNasGczMzBAQEIBOnTqhU6dOrCNAlvHDq1evYGBgwIooStqjV69eoUGDBrC3t8emTZt4/6Y8xDOEKAp55hiKElfLO78gik2R4ur8/Hzs378fNWvWxC+//AIHBweYmJigZ8+e8PT0RIcOHeDj44OBAwfKZHtGRYknFTF22LhxI5SVlTFu3DgkJyfjwYMH6NSpEyZOnIhXr16hV69esLa2FqQz+8uXL9DU1IRIJOKt3CnaFn769AkbN24sd7t2KBLJebV79240btwYhoaGUFVVxdChQ9nW0jt27ICLiwssLCwQHBwMkUgks5yvopK0d9LXubu7O5YtW8Z73fPnz+Hr6wuRSIS+ffti/fr1bDJCRR3YKMu+sfKMBjX+n8LDw6GlpYXo6GisX78eIpEIw4YNQ2ZmJu7evQt3d3dYWlqiRYsWCAgIKLed6FFRUahfvz42bdqEP/74A46OjnBzc+Mtd42MjISOjg5b6llQUIAPHz5AU1MTycnJP/zeu3btgp6eHoYMGcISMEtLSxw6dIi3j+b9+/dx+PBhrFixAgcOHCg3BdrLi7KcSVfWS/umTJnCm7XVu3dvmJmZ4ffff2edlHv37oWysjJGjx4NsVhc7toIRZafn4+NGzeidu3a0NHRgbm5OWxsbGS6EmLDhg1o2rQpAODu3buYNWsWjI2NUbduXfj6+rLXRUVFsXOhonQcUwHmf6xduxajR49mBVCF3i6xpA6W169fw9TUFKNHj2avkZyDHTp0gJWVFdq3b49Lly4JeiyEED555RiKFFfLM78gikuecbXk/M/Pz2f/v6CgAPv374eBgQGUlZUxf/58zJkzB+Hh4ZgwYQImTpxYbCKVUOQRT/5MscOff/6JBg0aQEdHBzo6OrC1tWU55/PnzxEQECDYhLYbN27A2toaVlZWJW6XSrld2Tl58iSqV6+OVatWISkpCXFxcahfvz66deuGFy9eoKCgAIcPH8bgwYPRpUsXGtCQIenaHP3790ePHj2KtUGPHj1Cz5490aBBAzaBTaht+n5WtMq09GhQ4//h4sWLMDY2ZvvCnTlzBsrKyrz9ZQEgPT29XG/RcPDgQZiZmeHixYsAgNOnT0NZWRnNmjVDy5YtkZiYyF67atWqYgHVjzZY0rNtDh06BE1NTQwaNAiXL1+Gh4cHrl+/DrFYjNzcXPaemZmZvL9BwUXFVRZL+w4ePIidO3eiX79+SEpK4j3Xp08fmJmZYePGjey8lKwYCAwMpJmFcvD8+XOcOXMGV69eLXGP7h9VUvK3b98+WFhYoE2bNjA0NERAQAAWLFiAffv2QUlJqdj5Ut7uG/8fFbkAc9FgPzk5Gf369UPHjh2L3cd+lPR5+eDBAzx69Ih9zwkJCVBSUsK8efPYa/Ly8tCnTx/s3r0b+vr6GDNmjCDHQQgpTh45hqLF1fLKL4jikndcLTm3Dh06hKFDh8Lf3x/Jycns2jl48CDq16+PoUOHlvq9SqII8eTPGDu8fPkSycnJvFU7kg7DH22zJOdCdnY28vPzWXtz48YNaGpqon379qxmAyl7EyZMQMeOHXmPXb16FXXr1kVISAjvcbpXyM7q1atRr149mJiYwNnZGW3btoW7uzuOHDmCN2/e4MuXL+y1b968QceOHaGlpUWDTEQQNKjx/3Do0CE4OzsDKJwFUKtWLaxevRpA4d6vJ06cKPZvyuNM2xs3bmD69OkACveprFu3Ln7//XecO3cO9erVQ4sWLdhSVAnpAKK030l0dDTS0tKQkJAAXV1d+Pv7o2rVqlBTU4OdnR3s7OzQuHFjGBsbFysQTSo2WS7tCw0NhaqqKnR0dCASiTB48GB8/PiR95qAgACoqalh//797LGdO3dCQ0OjwnXillfSyd+jR4/YMv+vX79i27ZtCA4OxrZt2/DixQsAwL179+Dg4CCzGX3k53Xx4kVUrVoVp06dKvXfkr7vTp48GdbW1jAzM4OmpibWrVuHjx8/YtWqVRCJRPDx8UFgYCBbpg8AgwcPRrt27Up9HISQkskzx1CUuFre+QVRLIoSVx85cgRVq1aFr68vmjVrhpo1a2LVqlW8ra/U1NTQuXNn9m+EOBcVIZ4sL7FDaQdfJd/DgQMH8Msvv8De3h7Dhg1j592NGzegpaUFLy8vGtiQA7FYjAEDBrBzraCggA1qbtmyBQ0aNMCzZ89K3B6JlE7RgdeHDx/i9u3b2Lp1KyZOnAgvLy+IRCI4Ozujdu3aMDc3R+vWrbFt2zYAhRMMXVxcYGJiQttwk1KjQY0iSpoZcf78eVhbW2PhwoWoXbs2Vq1axZ47cuQI2rRpg4cPH5blYcpcSd9Dbm4uMjIykJWVBU9PT5aAAECrVq1gYmJSbES8NKRvPDExMahduzZOnjwJoHDJvIaGBlq0aIFJkybhyJEjSExMxKZNm7Bz584KOduZ/DtZLO1LTU1Fx44dcf78eaSnp2PEiBGwtbXFrFmzis1qnDp1arHzUnrWJSkfwsPDYWFhgZo1ayI4OBh//fUX7/n8/Hx8+PAB3t7ecHNzk8m+y+TnJbnvOTs7F9uTujSmTZsGdXV1HD58GF++fGEFRe/duwegcGZ079694ePjg6CgIJZgdOrUCcOHDxfsOAipyOSdYyhCXK0I+QVRXPKOqyXXyIcPHxAZGcm7HsPCwlC3bl0sX76cDWzs3r0benp6ePnyZanetySKEE9S7FC4KqVatWqYMWMGVq1aBT8/P1SqVAm3b98GUFj7SE9PD82bN6eC4DImuT7fv3+PrKwsAEBcXByqVq2Ko0ePAvjnHhMfHw9zc3P6TWRAuq3ZuHEjwsLCMGrUKN6qyjNnzkBNTQ1XrlxBYmIiNm7ciJCQEN4AxsuXL/Hs2bMyPXZSPtGghhTpCzQxMRE7duzAzZs3kZGRge7du6N69eqIjIxkr8nJyYG3tzf8/PzKVceU9Ge5d+9esZkf7969Q6NGjVig9/79e/Tu3RsxMTEy+R4OHTqEUaNGYd26dbzH4+LioKOjg5EjR5ZY/IwGNogsxcTEoG3btujVqxdvJtDo0aNhZ2eHmTNnlrh9DJ2X5Yv0bx8TEwN9fX3ExsZi7dq1MDExQdeuXdlM22/fvmH9+vXw8PBAs2bNWGBXnu4fpPTWrFkDkUhUquKS0udUQUEBOnfuzApkxsfHQ01NDStWrADwz1Y00svyMzIyEB4eDnV1dZa4E0J+nCLlGPKKqxUtvyCKRV5x9bZt21jdPbFYjKtXr0JVVRVWVlbYvXs377VhYWFQU1PDypUr2bFIb6tSGooQT1LswJeRkQEPDw8sWrQIQOG2OVpaWsUGbK5duwZzc3NWnJrITnx8PFq2bAkTExNMmjQJiYmJGD16NMzMzHDkyBH2uoiICNjZ2eHDhw9yPNryLSwsDBoaGhgzZgx8fX1hZGSEUaNGQSwWs9o7V65cKfbvqC+ECI0GNUoQERGBmjVrwsTEBMrKyvj999+xceNGODo6wsvLCxs2bMAff/yBdu3awdraml2Y5S3gjoiIgJaWFpu5de/ePYjFYrx58wZeXl7o0aMHli5divbt26Nly5bs8wv5PVy4cAE2NjZQU1Njs1alR3hjY2Ohr68Pf3//Egt1ESILBQUFiIyMhJGREUxNTYstbw4JCYGjoyPCw8MFS3aIYpk9ezZv9uzJkycxfvx4rF+/nj126dIl2NnZoWvXrjh58iTEYjE2bNiAyZMns/sGBXakqAcPHrAOltKaNGkS5syZA21tbdy7dw9JSUmoVasW6zTMzs5GVFQUb6bUkydPEBUVBQMDA1y9elWQ4yCEFJJ3jqEIcbUi5BdEscgrrn748CHMzMyKFZDu06cPRCIR5syZU6xGR0REBEQiEdatWyfIdjaKGE9S7FDozZs3MDY2RkpKCl6+fAltbW0MGjSIPf/nn38iLS0NAKhGYhlISUmBqqoqpk2bxgY7/f39sXDhQowZMwbKyspwcnKCi4sL6tSpg9TUVHkfcrmVmJgIQ0NDXLp0CUBh7FCtWjU2CAoANjY2mDVrFvtv2v6LyAoNauCfC0wsFuPx48dwcXHB+fPn8f79e8ybNw+VK1fGihUrsG7dOgQFBaFOnTpo3bo1+vTpwxKB8lCIWjpZiIuLg6GhIfbs2YODBw+iefPmaNSoES5fvgygsCCbl5cXLC0t4eXlJdMZx4sWLYKhoSFcXFzYPqnSgduWLVvQtWtXSnZImcrNzcX8+fPRqFEjBAcHF9vvt3///hg4cCDdwMuhe/fuwc/Pj7X7z549Q40aNSASiXjbZgD8RPT06dO858rDfYMoFun74I4dO6Crq4ubN2/i119/Rfv27VGjRg1eAeKXL1+iVatW2LJlC3ssNzcXaWlpMtlOg5CKRhFzjLKOqxU1vyCKpazj6v379+PNmzfsv69du4aUlBT233379kWtWrUQFxdXrMN60qRJuHv3bqmPQVHiSYodCknOratXr+LZs2f49u0bvL29sW7dOhgYGGDQoEHsu37+/DkGDBiAPXv2UK5XBh48eIDp06djxowZ7LG9e/fCw8MDvr6+SEhIwMmTJxEeHo65c+eywSYiGxs2bICrqyuAwu0rVVRU2KBnZmYmzpw5Azc3N0yePFmOR0kqigo/qCF9E3///j3S0tIQERHBCw4WLlyIypUrY9GiRfj8+TM+fPjAe768zbSNiYnBihUrsHTpUvZYbm4uWrVqBQMDAxbwffr0Ce/fv2c3ciGXpRe1ZMkSODg4IDAwkAWgJb0fJT1Elm7evIl79+6xJdV5eXmYPXs2nJycMHz4cLbHrgQVJiu/JL/pvn378O7dO1y+fBl6enpo165dsRlqycnJ0NHRkWmhVUKknTx5EkOGDMHixYsBAMuXL4eBgQG8vb3Zaz59+oQOHTqgdevWNMBGiAzIO8dQtLhaXvkFUVzyiqtfv34NfX19DBgwANevX8e3b9+gpaWFXr168WI4f39/qKqqljiwIRRFiicrcuwg+R3i4+OhpaWF6OhoFBQUYPjw4RCJROjWrRuvPYyIiICFhQXVBCgDmZmZsLe3R4MGDRAREcF7bu/evXB3d0f37t3LzQqhn8GmTZvQp08fHDx4kLeKCyicvDBv3jzs27eP7t+kTFT4QQ2JCRMmwMHBAaqqqmjSpEmx2ReLFi1C5cqVERERwStCVt46Kz99+gRNTU2IRCKMHz8ewD+fMTc3F66urmjUqBHOnz/P++xC7uG5Z88ezJkzB3/88QdvH7758+ejRYsWCAoKYglYeQqmiGKLjIyEiYkJtLS00KBBA0RFRSEvLw95eXmYOXMmmjdvjpEjRxabWUYDbeXX33//DT09PfTr1w/v37/H+fPnoauri/79+xcr6Hj79m1qr0iZ+Pvvv9GoUSOoqKhg9uzZAArvlWPGjIGNjQ2aNm0KX19fODk5wcbGplytOCVEEckjx1C0uFpe+QVRXPKOq1NSUuDo6IigoCBkZGQgKSkJRkZG6N+/P2/bGn9/f9SvXx8xMTG8rdqEpAjxJMUOhat3qlevjnXr1uH58+fs8X79+kFdXR2zZs3CnDlzMHjwYKioqODatWtyPNqKJTU1FY0bN0bLli2L1WM6cOAAmjZtij59+iArK6vc9c8pojt37qBKlSoQiUTYuHEjezw7Oxvt2rVD//792WPlqY0giqnCDmpIB0QxMTHQ1NTE0qVLERISgho1amDcuHHF9tecOXMmWrRoUa4aypICw2fPnsHZ2RkWFhasUKD0bCkzMzP4+voKdgzS3+f48eOho6MDNzc3tGrVCi1atMDevXvZ8/Pnz0erVq3Qo0cPZGRkCHYMhPyb3377DfXq1cOJEyeQlJSE33//HVWqVEFgYCCAwoR85syZaNSoERYsWCDnoyVlKSUlBXZ2dhg4cCA+fPiAs2fPskT0xo0bxV5PgR0pC9evX4exsTFatGjBOjHz8/ORkJCA0NBQjBw5EgsXLqTaLoTIgLxzDEWIqxUhvyCKS1Hi6tTUVDRt2rTEGE56YKNjx47Q19fnDToKTRHiyYocO+Tk5MDX1xcTJkwAAGRlZeHevXv47bffkJCQAB8fH3h5ecHW1hZ9+/Yt8TchsnX9+nU0bdoUgwcPLjawcfjw4WL3VSJbu3btQvXq1TF+/HgkJSXhxIkT8PT0RJMmTcpV20AUX4Ud1JA4efIkhg0bxorlAcCKFSvY0s6ijaP03rg/O+mE4+jRo4iPj0dCQgKAwn0irays4ODgwJZVSj5zfn6+TAKppUuXQl9fH+fPnwdQuCS/SpUqaNy4MWJjY9nrpkyZguDgYJq9RcpEQUEBunbtiqioKN7jJ06cgEgkwrJlywAUFojbtGkTdVpXQCUlxQYGBvDx8eEVfySkLEmSv6CgIFy/fv27r6M2ixDZkHeOIa+4WtHyC6JYFC2ulo7hMjIyeIMJ0tvZvHjxQqbHUfRY5BVPVtTYITs7G/b29hg5ciTev3+PESNGwNXVFVpaWtDX18eCBQvw+fNnZGVlUVFwOUpNTUWzZs0QFBSEW7duyftwKrT8/Hxs374d2tra0NbWhp2dHby9vcvlKi6i2Cr0oIZkmWWtWrXY3pESy5cvh46ODiZMmFAsiCgPAxrSnyEiIgLa2tqwtbVFtWrV0K9fPzx//hzPnj2DpaUlHB0deUswJYRsqD59+oSAgAAWyO7duxeqqqqIjIxEly5dYGRkhH379hU7fhrYILL09u1bAICFhQXCwsIAFJ57kpt1SEgI2rRpU2zPX7qJVzySRDQwMBAZGRk4ceJEsf13CSlrkuRv0KBBxWa1EUJkR945hrziakXLL4hiUdS4uqTBBCMjI/To0YN17JdV/q8I8WRFjR02bdqE6tWro3bt2ujWrRsbkB41ahTc3d1p9rmCSE1NhaOjI/z9/XHnzh15H06F9+bNG6SlpeHp06dUC4vIRYUe1AAKZyM0btwYnp6exfasXLlyJZSUlHiFb8qbuXPnQlNTE5cuXQIALFu2DCKRCN27d8fz58/x/PlzNGnSBAYGBkhPTxfsfUsKzNLS0vDw4UPcunULhoaGWLJkCQBg48aNqFy5MurUqYPDhw+z15eHwSWiuBYsWIChQ4fixYsXmDlzJgwNDXH58mUA/5x70dHR8PDwkOdhEgWSmpoKOzs7dO/enbdFAQ1sEHlKTU2Fg4MDevbsybZ8IYTIXlnmGIoWV8srvyCKS9Hj6qIrNpKSkmBlZYWXL1/K5VjkHU9W1Njh1q1bOHLkCIB/vu/hw4cjICAAX79+leehESnJyclwc3PDq1ev5H0opAjKe0lZq8RVcE2aNOFiY2O5d+/eccuWLeNu3brFnhs6dCgXGxvLDRo0SI5HKDuvXr3ibt++zS1atIhzdHTk4uLiuEmTJnHR0dHc8ePHudGjR3P5+flcQkIC5+LiwtWrV0+Q9xWLxVylSoWn3qFDh7idO3dyt2/f5kxMTDgjIyPu3LlznI6ODhcYGMhxHMepqalx3t7e3IwZM7i2bduyvyMSiQQ5HkKKCg8P5+bMmcO1atWKKygo4Ly8vDgrKytu4sSJ3JUrVziRSMRlZWVxycnJnI6OjrwPlygIW1tbbuXKlZyKigpXo0YN9rikvSNEHmxtbbnly5dzKioqnL6+vrwPh5AKo6xyDEWLq+WVXxDF9TPE1ba2ttzvv//O/fXXX1xwcDBna2vLJScnc1paWnI5FnnHkxU1drCwsOA8PT05juO4tLQ0Lioqitu6dSsXFhbGVa1aVc5HRyQcHBy4Q4cOcZqamvI+FFIE5b2kzMl7VEVRSC+zLGl/vvK4FDonJwdxcXHIyMjA5cuXYWBgwGZxLViwACKRCO7u7rwZVEJ+DxEREahZsyZMTExQuXJlLFu2DLm5udi4cSM0NTVx+vRpfPv2Dd7e3oiMjOTtuUuIrBw7dgyGhoY4e/Ys7/GEhAR06dIFNWvWhL29PaytrWFlZcWWzNPKISJB2+MRRUTnJSHyUVY5hqLE1fLOL4hi+dni6uTkZLi6uirEDHBFuG8rwjHIw5UrV/DLL7/A3Nwc165dk/fhEEII+Y7K8h5UURS2trbc+vXrueDgYG7y5MncvHnzOENDQ/a8kpKSHI9ONqpVq8Z17tyZU1ZW5o4dO8ZZWlpy/fr14ziO46pUqcL16dOHe/fuHVe/fn32b0rzPQDgRCIRB4B7+vQpd/bsWe7o0aOcqakpt3HjRm7UqFFcVlYW5+joyDk7O3Ndu3bl6taty1WpUoWLi4tj/7Y8/hZEcTx79oyrUaMGZ2lpyXHcPzMgu3TpwllZWXFpaWnc5cuXOXV1dS4oKIirXLkyl5+fz1WuTM0pKSRpq2imClEkdF4SIh+yyjEUNa4u6/yCKLafLa52cHDgDh8+zFWrVk0u7y9NEe7binAM8mBhYcENHTqUMzAw4HR1deV9OIQQQr6DeuGkSJZZrl69usIss5QEjGlpaVxmZiYnEom4r1+/cocPH+Z+/fVXzs/Pj+M4/tL2HyH97zMyMri8vDzOxcWFc3R05JSUlLixY8dylStX5kJDQ7nFixdzo0aN4gICArjXr1+zALegoICSHiIzks6BnJwcrqCggD0uEonYuZeSksI1a9aM8/LyYs8XFBTQgAYphrbHI4qIzktC5EPoHEPR4+qyyi+I4vqZ42pFGNCQUIT7tiIcQ1mrXr0616pVK3kfBiGEkP9BBADyPghFIwnCKlKgffHiRc7V1ZUzNTXlvn37xlWrVo1LTU0VPKiMiorijh49yqWlpXH6+vpcbGwsZ2pqyp5fvHgxFx4ezoWFhXEzZsxgj9OABikrd+7c4aytrbno6GhuypQp7PEvX75wffr04dq1a8cNHz5cfgdICCGEkJ+S0DmGosfVZZVfEMVFcTUhhBBCZIUiyhJUxGWWzs7O3MWLF7m4uDiudu3aXGhoqCDLf6WTth07dnAbN27kIiMjuUePHnFr167l1q9fz40YMYLNWgsJCeGysrK4gwcPssSP42hZOik75ubm3MqVK7kRI0ZwGRkZXOfOnbkqVapws2bN4l6/fs0FBwfL+xAJIYQQ8hMqbY7xs8XVssovyM+D4mpCCCGEyAqt1CDfJWTCcerUKS42NpZzcnLiAgICOI7juJUrV3KzZ8/m+vTpww0dOpS3HF96n+CKuOSVyBcAbu/evdyoUaO4goICrk6dOpy2tja3f/9+TllZmVYOEUIIIURufua4mgY0Kh6KqwkhhBAiCxRRku8SKuF4/fo1FxgYyKWnp3ONGzdmjw8bNowDwM2ZM4dTUlLiAgMDOSMjI47jOIVJvEjFJBKJOB8fH65ly5ZcZmYmJxaLuUaNGnGVKlWiZJwQQgghcvOzx9UUQ1U8FFcTQgghRBZopQYpE3/99Rfn6+vL6evrcwsWLOCsra3Zc6tWreJGjhzJLV++nBsyZIgcj5KQf1eR6uwQQgghRDFRXE3KA4qrCSGEEFIaNKhBysz169e5AQMGcPb29tzo0aM5S0tL9lxcXBzn4+NDS48JIYQQQgj5HyiuJoQQQgghFRkNapAydfXqVS4oKIizs7PjQkJCOAsLC97ztKcqIYQQQggh/xvF1YQQQgghpKKiQQ1S5q5evcoFBwdz+vr63Lx58zhDQ0N5HxIhhBBCCCE/HYqrCSGEEEJIRUSbWJIyZ2tryy1fvpxTUVHh9PX15X04hBBCCCGE/JQoriaEEEIIIRURrdQgcgOAE4lEVCSOEEIIIYSQUqC4mhBCCCGEVCQ0qEHkSpKAEUIIIYQQQn4cxdWEEEIIIaSioEENQgghhBBCCCGEEEIIIYT8FGhtMiGEEEIIIYQQQgghhBBCfgo0qEEIIYQQQgghhBBCCCGEkJ8CDWoQQgghhBBCCCGEEEIIIeSnQIMahBBCCCGEEEIIIYQQQgj5KdCgBiGEEEIIIYQQQgghhBBCfgo0qEEIIaRcad26NRcSEiLvwyCEEEIIIYSUA5RfEEKI4qFBDUIIIYJavXo1p6KiwuXn57PHvnz5wikrK3OtW7fmvfbkyZOcSCTiHj58WMZHSQghhBBCCPkZUH5BCCGkKBrUIIQQIih3d3fuy5cv3JUrV9hjZ86c4Ro2bMhdunSJ+/r1K3s8KSmJ09PT4xo1avSf3gMAL6khhBBCCCGElE+UXxBCCCmKBjUIIYQIytTUlNPU1OROnjzJHjt58iTn4+PDGRoachcvXuQ97u7uzn379o0bNWoU16BBA65atWqci4sLd/nyZd7rRCIRl5iYyNnZ2XFVq1blzp49y2VlZXEBAQFcrVq1OE1NTW7BggXFjmflypWciYkJV61aNU5DQ4Pr2bOnTD8/IYQQQgghRDiUXxBCCCmKBjUIIYQIzt3dnUtKSmL/nZSUxLVu3Zpzc3Njj+fk5HCXLl3i3N3dufHjx3O7d+/mNm3axKWmpnLGxsZc+/btuQ8fPvD+bkREBDdnzhzuzp07XJMmTbiwsDDu1KlTXEJCAnfkyBHu5MmTXGpqKnv9lStXuFGjRnHTpk3j7t27xx06dIhzdXUtmy+BEEIIIYQQIgjKLwghhEirLO8DIIQQUv64u7tzISEhXH5+PpeTk8NdvXqVc3Nz4/Ly8rjVq1dzHMdxFy5c4L59+8a1bt2aGzRoEPfHH39wHTp04DiO49atW8cdPXqU27BhAxcWFsb+7rRp0zhPT0+O4wr30d2wYQO3detWrm3bthzHcdymTZs4HR0d9vpnz55xNWvW5Dp37sypqKhw+vr6nK2tbVl9DYQQQgghhBABUH5BCCFEGq3UIIQQIrjWrVtzWVlZ3OXLl7kzZ85wjRs35tTV1Tk3Nze27+3Jkyc5IyMjLjMzk8vLy+NatmzJ/r2ysjLn6OjI3blzh/d37e3t2f9/+PAhl5ubyzk5ObHH6taty5mamrL/9vT05PT19TkjIyOub9++3LZt27js7GwZfnJCCCGEEEKI0Ci/IIQQIo0GNQghhAjO2NiY09HR4ZKSkrikpCTOzc2N4ziO09LS4nR1dbnz589zSUlJXJs2bf7T361Zs+Z/er2KigqXmprKxcTEcJqamtykSZM4Gxsb7uPHj//p7xBCCCGEEELkh/ILQggh0mhQgxBCiEy4u7tzJ0+e5E6ePMm1bt2aPe7q6solJiZyycnJnLu7O9eoUSOuSpUq3Llz59hr8vLyuMuXL3MWFhbf/fuNGjXilJWVuUuXLrHHMjIyuLS0NN7rKleuzHl4eHDz5s3j/vrrL+7JkyfciRMnhPughBBCCCGEEJmj/IIQQogE1dQghBAiE+7u7tzw4cO5vLw8NpOK4zjOzc2NGzFiBJebm8u5u7tzNWvW5IYOHcqFhYVxdevW5fT09Lh58+Zx2dnZXGBg4Hf/fq1atbjAwEAuLCyMq1evHtegQQMuKiqKq1Tpn/H6/fv3c48ePeJcXV05NTU17uDBg5xYLOYtISeEEEIIIYQoPsovCCGESNCgBiGEEJlwd3fncnJyODMzM05DQ4M97ubmxn3+/JkzNTXlNDU1OY7juDlz5nBisZjr27cv9/nzZ87e3p47fPgwp6am9q/v8dtvv3FfvnzhvL29ORUVFW7s2LFcZmYme75OnTpcXFwcN2XKFO7r16+ciYkJFxMTw1laWsrmQxNCCCGEEEJkgvILQgghEiIAkPdBEEIIIYQQQgghhBBCCCGE/C9UU4MQQgghhBBCCCGEEEIIIT8FGtQghBBCCCGEEEIIIYQQQshPgQY1CCGEEEIIIYQQQgghhBDyU6BBDUIIIYQQQgghhBBCCCGE/BRoUIMQQgghhBBCCCGEEEIIIT8FGtQghBBCCCGEEEIIIYQQQshPgQY1CCGEEEIIIYQQQgghhBDyU6BBDUIIIYQQQgghhBBCCCGE/BRoUIMQQgghhBBCCCGEEEIIIT8FGtQghBBCCCGEEEIIIYQQQshPgQY1CCGEEEIIIYQQQgghhBDyU6BBDUIIIYQQQgghhBBCCCGE/BT+D0BlxvdZEvrIAAAAAElFTkSuQmCC\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"## Model Building"
],
"metadata": {
"id": "ARa_iXdV7I5l"
}
},
{
"cell_type": "markdown",
"source": [
"* In preparation for any machine learning model, it's imperative to tokenize textual data. To accomplish this, I employed the `Word2Vec` tokenizer, generating distinct embeddings for both the `subject` and `body`.\n",
"* To meet the requirement for probability output, I opted for a probabilistic model designed for classification tasks. In this context, Logistic Regression and SVM classification emerged as optimal choices, with tree-based models serving as viable alternatives.\n",
"* Given the constraints of limited data and time considerations, I selected SVM with a linear kernel for classification. This choice aligns with the need for a balance between model performance and computational efficiency."
],
"metadata": {
"id": "UTlgsh51zAJA"
}
},
{
"cell_type": "markdown",
"source": [
"### Tokenisation"
],
"metadata": {
"id": "jafUvlW6ggGj"
}
},
{
"cell_type": "code",
"source": [
"tokenized_text1 = df['body'].apply(lambda x: x.split())\n",
"tokenized_text2 = df['subject'].apply(lambda x: x.split())\n",
"\n",
"\n",
"word2vec_model_text1 = Word2Vec(sentences=tokenized_text1, vector_size=50, window=5, min_count=1)\n",
"word2vec_model_text2 = Word2Vec(sentences=tokenized_text2, vector_size=25, window=5, min_count=1)"
],
"metadata": {
"id": "m4MKbsIFgMzp"
},
"execution_count": 424,
"outputs": []
},
{
"cell_type": "code",
"source": [
"word_embeddings_text1 = tokenized_text1.apply(lambda x: average_word_vector(x, word2vec_model_text1, 50))\n",
"word_embeddings_text2 = tokenized_text2.apply(lambda x: average_word_vector(x, word2vec_model_text2, 25))\n",
"\n",
"word_embeddings_df_text1 = pd.DataFrame(word_embeddings_text1.tolist(), columns=[f'feature_text1_{i}' for i in range(50)])\n",
"word_embeddings_df_text2 = pd.DataFrame(word_embeddings_text2.tolist(), columns=[f'feature_text2_{i}' for i in range(25)])"
],
"metadata": {
"id": "mDZSOpqugPzb"
},
"execution_count": 425,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def average_word_vector(tokens, model, num_features= 25):\n",
" if len(tokens) == 0:\n",
" return np.zeros(num_features)\n",
" else:\n",
" return np.mean(model.wv[tokens], axis=0)"
],
"metadata": {
"id": "vbescq5igTEP"
},
"execution_count": 426,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### Model training"
],
"metadata": {
"id": "_Cz_Hdt_gltS"
}
},
{
"cell_type": "code",
"source": [
"df_concatenated = pd.concat([df, word_embeddings_df_text1, word_embeddings_df_text2], axis=1)\n",
"\n",
"X_train, X_test, y_train, y_test = train_test_split(\n",
" df_concatenated.drop(['body', 'subject', 'opened'], axis=1), df_concatenated['opened'], test_size=0.2, random_state=42\n",
")\n",
"\n",
"svm_model = SVC(kernel='linear')\n",
"svm_model.fit(X_train, y_train)\n",
"\n",
"predictions = svm_model.decision_function(X_test)"
],
"metadata": {
"id": "AHzUKtBEgWge"
},
"execution_count": 427,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### Evaluation"
],
"metadata": {
"id": "pHfZvKI3goub"
}
},
{
"cell_type": "markdown",
"source": [
"* For skewed data, it is better to used confusion matrix over mere accuracy. To find out recall and precision.\n",
"* After creating the validation data, I got **precision of 90%** for opened mails. Which is pretty good considering the model size and data.\n"
],
"metadata": {
"id": "IDZKQfUCznLu"
}
},
{
"cell_type": "code",
"source": [
"threshold = 0.1\n",
"\n",
"binary_predictions = (predictions > threshold).astype(int)\n",
"\n",
"classification_rep = classification_report(y_test, binary_predictions)\n",
"print(\"Classification Report:\")\n",
"print(classification_rep)\n",
"\n",
"cm = confusion_matrix(y_test, binary_predictions)\n",
"\n",
"plt.figure(figsize=(6, 6))\n",
"sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', cbar=False,\n",
" xticklabels=['Predicted 0', 'Predicted 1'],\n",
" yticklabels=['Actual 0', 'Actual 1'])\n",
"plt.xlabel('Predicted Label')\n",
"plt.ylabel('True Label')\n",
"plt.title('Confusion Matrix')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 856
},
"id": "M05ntrMrCAe7",
"outputId": "3a2b216a-8fe6-4bda-b89b-c7aecf85d742"
},
"execution_count": 428,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.10/dist-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/usr/local/lib/python3.10/dist-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n",
"/usr/local/lib/python3.10/dist-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
" _warn_prf(average, modifier, msg_start, len(result))\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Classification Report:\n",
" precision recall f1-score support\n",
"\n",
" 0 0.00 0.00 0.00 3\n",
" 1 0.90 1.00 0.95 28\n",
"\n",
" accuracy 0.90 31\n",
" macro avg 0.45 0.50 0.47 31\n",
"weighted avg 0.82 0.90 0.86 31\n",
"\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"with open('svm_model.pkl', 'wb') as model_file:\n",
" pickle.dump(svm_model, model_file)"
],
"metadata": {
"id": "2gZUUQA4NOPV"
},
"execution_count": 423,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"#### load model"
],
"metadata": {
"id": "-a1iChFYhTKU"
}
},
{
"cell_type": "code",
"source": [
"with open('svm_model.pkl', 'rb') as model_file:\n",
" loaded_svm_model = pickle.load(model_file)"
],
"metadata": {
"id": "bvr7XIfFhUaO"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Improvements/Feedback\n",
"* To gain a deeper understanding of the scenario, acquiring additional data would be beneficial. Exploring alternative models, including tree-based models, logistic regression, or even employing ensemble models, could provide valuable insights.\n",
"* For enhanced analysis, consider conducting sentence-level counts and capturing bigram/trigram word counts as distinct features. This approach can contribute to a more comprehensive representation of the textual data.\n",
"* In the realm of deep learning, leveraging advanced models like RoBERTa or other BERT-based models could significantly improve text classification accuracy. However, it's essential to note that implementing these deep learning models effectively requires a substantial amount of data to achieve optimal performance."
],
"metadata": {
"id": "YxUB3YaX1Ik0"
}
}
]
}
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