6581 lines
880 KiB
Plaintext
6581 lines
880 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "rOcyai_EJqet"
|
|
},
|
|
"source": [
|
|
"# **FYP.24.s2.43p - SafeQR Project**\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "pbQh7ysA5nR1"
|
|
},
|
|
"source": [
|
|
"**About Dataset**\n",
|
|
"\n",
|
|
"The original dataset is downloaded from https://www.kaggle.com/datasets/sid321axn/malicious-urls-dataset which consists of a huge dataset of 651,191 URLs, out of which 428103 benign or safe URLs, 96457 defacement URLs, 94111 phishing URLs, and 32520 malware URLs. The dataset only made up of URL and target class. We further process that data that did the following checks:\n",
|
|
"\n",
|
|
"\n",
|
|
"* number of redirections\n",
|
|
"* show the redirect chain\n",
|
|
"* show hsts headers a website use\n",
|
|
"* check for SSL stripping\n",
|
|
"* check for host name embedding (deceptive url)\n",
|
|
"* whether javascript present in url\n",
|
|
"* whether have shortening service\n",
|
|
"* whether url uses have ip address\n",
|
|
"* check for tracking mechanism\n",
|
|
"* check of URL encoding\n",
|
|
"* check for executables"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 538
|
|
},
|
|
"id": "tCa8uewcrMq5",
|
|
"outputId": "bdbde122-5e2e-435b-9159-e866cfa859c8"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Mounted at /content/drive\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stderr",
|
|
"text": [
|
|
"<ipython-input-2-2f803395ba41>:18: DtypeWarning: Columns (11) have mixed types. Specify dtype option on import or set low_memory=False.\n",
|
|
" data = pd.read_csv(path)\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain \\\n",
|
|
"0 famouswhy people com \n",
|
|
"1 charlotteobserver events com \n",
|
|
"2 wikia icehockey com \n",
|
|
"3 vimeo NaN com \n",
|
|
"4 pensiiilfov www ro \n",
|
|
"\n",
|
|
" query fragment redirect \\\n",
|
|
"0 {} NaN 0 \n",
|
|
"1 {} NaN 0 \n",
|
|
"2 {} NaN 1 \n",
|
|
"3 {} NaN 0 \n",
|
|
"4 {view=article, id=77, Itemid=184, option=com_c... NaN 0 \n",
|
|
"\n",
|
|
" path \\\n",
|
|
"0 /marguerite_churchill/ \n",
|
|
"1 /statesville-nc/events/jazz%2Bconcerts \n",
|
|
"2 /wiki/Cory_Pecker \n",
|
|
"3 /9425680 \n",
|
|
"4 /index.php \n",
|
|
"\n",
|
|
" redirect_chain \\\n",
|
|
"0 {https://people.famouswhy.com/marguerite_churc... \n",
|
|
"1 {} \n",
|
|
"2 {https://icehockey.wikia.com/wiki/Cory_Pecker,... \n",
|
|
"3 {https://vimeo.com/9425680} \n",
|
|
"4 {http://www.pensiiilfov.ro/index.php?option=co... \n",
|
|
"\n",
|
|
" hsts_header ssl_stripping \\\n",
|
|
"0 {\"No HSTS Header detected\"} {false} \n",
|
|
"1 {} {} \n",
|
|
"2 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false} \n",
|
|
"3 {\"No HSTS Header detected\"} {false} \n",
|
|
"4 {\"Not an HTTPS connection\"} {false} \n",
|
|
"\n",
|
|
" hostname_embedding javascript_check shortening_service has_ip_address \\\n",
|
|
"0 0 NaN NaN NaN \n",
|
|
"1 0 NaN NaN NaN \n",
|
|
"2 0 NaN NaN NaN \n",
|
|
"3 0 NaN NaN NaN \n",
|
|
"4 0 NaN NaN NaN \n",
|
|
"\n",
|
|
" tracking_descriptions url_encoding has_executable qr_code_type_id \\\n",
|
|
"0 {} NaN NaN 9 \n",
|
|
"1 {} Yes NaN 9 \n",
|
|
"2 {} NaN NaN 9 \n",
|
|
"3 {} NaN NaN 9 \n",
|
|
"4 {} NaN NaN 1 \n",
|
|
"\n",
|
|
" contents \\\n",
|
|
"0 https://people.famouswhy.com/marguerite_church... \n",
|
|
"1 https://events.charlotteobserver.com/statesvil... \n",
|
|
"2 https://icehockey.wikia.com/wiki/Cory_Pecker \n",
|
|
"3 https://vimeo.com/9425680 \n",
|
|
"4 http://www.pensiiilfov.ro/index.php?option=com... \n",
|
|
"\n",
|
|
" qr_code_id created_at \\\n",
|
|
"0 403ffba7-f30e-438b-af75-4f4aaa999377 2024-08-10 09:54:43.798 +0800 \n",
|
|
"1 9e5c7974-82aa-40b7-94a0-4fa7d49c1d79 2024-08-10 09:54:59.363 +0800 \n",
|
|
"2 e8b37ba0-ffbb-4e1f-b77a-5617472ddfe9 2024-08-10 09:55:10.845 +0800 \n",
|
|
"3 8e9c40e1-2a77-4da0-ac25-8384827c2b68 2024-08-10 09:55:11.564 +0800 \n",
|
|
"4 65cec661-0c54-42d4-9f80-e0486e8a7cfc 2024-08-10 09:55:11.512 +0800 \n",
|
|
"\n",
|
|
" result_category \n",
|
|
"0 benign \n",
|
|
"1 benign \n",
|
|
"2 benign \n",
|
|
"3 benign \n",
|
|
"4 defacement "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-988fbcc4-eb62-4540-85c6-b4946a9bcc41\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>qr_code_type_id</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>qr_code_id</th>\n",
|
|
" <th>created_at</th>\n",
|
|
" <th>result_category</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>famouswhy</td>\n",
|
|
" <td>people</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/marguerite_churchill/</td>\n",
|
|
" <td>{https://people.famouswhy.com/marguerite_churc...</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>9</td>\n",
|
|
" <td>https://people.famouswhy.com/marguerite_church...</td>\n",
|
|
" <td>403ffba7-f30e-438b-af75-4f4aaa999377</td>\n",
|
|
" <td>2024-08-10 09:54:43.798 +0800</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>charlotteobserver</td>\n",
|
|
" <td>events</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/statesville-nc/events/jazz%2Bconcerts</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>9</td>\n",
|
|
" <td>https://events.charlotteobserver.com/statesvil...</td>\n",
|
|
" <td>9e5c7974-82aa-40b7-94a0-4fa7d49c1d79</td>\n",
|
|
" <td>2024-08-10 09:54:59.363 +0800</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>wikia</td>\n",
|
|
" <td>icehockey</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/wiki/Cory_Pecker</td>\n",
|
|
" <td>{https://icehockey.wikia.com/wiki/Cory_Pecker,...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>9</td>\n",
|
|
" <td>https://icehockey.wikia.com/wiki/Cory_Pecker</td>\n",
|
|
" <td>e8b37ba0-ffbb-4e1f-b77a-5617472ddfe9</td>\n",
|
|
" <td>2024-08-10 09:55:10.845 +0800</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>vimeo</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/9425680</td>\n",
|
|
" <td>{https://vimeo.com/9425680}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>9</td>\n",
|
|
" <td>https://vimeo.com/9425680</td>\n",
|
|
" <td>8e9c40e1-2a77-4da0-ac25-8384827c2b68</td>\n",
|
|
" <td>2024-08-10 09:55:11.564 +0800</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>pensiiilfov</td>\n",
|
|
" <td>www</td>\n",
|
|
" <td>ro</td>\n",
|
|
" <td>{view=article, id=77, Itemid=184, option=com_c...</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/index.php</td>\n",
|
|
" <td>{http://www.pensiiilfov.ro/index.php?option=co...</td>\n",
|
|
" <td>{\"Not an HTTPS connection\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>http://www.pensiiilfov.ro/index.php?option=com...</td>\n",
|
|
" <td>65cec661-0c54-42d4-9f80-e0486e8a7cfc</td>\n",
|
|
" <td>2024-08-10 09:55:11.512 +0800</td>\n",
|
|
" <td>defacement</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-988fbcc4-eb62-4540-85c6-b4946a9bcc41')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-988fbcc4-eb62-4540-85c6-b4946a9bcc41 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-988fbcc4-eb62-4540-85c6-b4946a9bcc41');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-7cacaae4-90c9-4e55-9123-42fc7900e4fa\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-7cacaae4-90c9-4e55-9123-42fc7900e4fa')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-7cacaae4-90c9-4e55-9123-42fc7900e4fa button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 2
|
|
}
|
|
],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"import numpy as np\n",
|
|
"import seaborn as sns\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"\n",
|
|
"from google.colab import drive\n",
|
|
"drive.mount('/content/drive')\n",
|
|
"\n",
|
|
"# Ensure that all rows are displayed\n",
|
|
"pd.set_option('display.max_rows', None)\n",
|
|
"\n",
|
|
"# Ensure that all columns are displayed\n",
|
|
"pd.set_option('display.max_columns', None)\n",
|
|
"\n",
|
|
"# Load the data\n",
|
|
"path = '/content/drive/MyDrive/Colab Notebooks/url_db_cleaned.csv'\n",
|
|
"\n",
|
|
"data = pd.read_csv(path)\n",
|
|
"\n",
|
|
"data.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "Zyyz8uvamchf"
|
|
},
|
|
"source": [
|
|
"**Data Cleaning**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 1000
|
|
},
|
|
"id": "EnPxbLfKOjcs",
|
|
"outputId": "91f754f4-6067-4f20-b5cf-6497b6604787"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain \\\n",
|
|
"0 famouswhy people com \n",
|
|
"1 charlotteobserver events com \n",
|
|
"2 wikia icehockey com \n",
|
|
"3 vimeo 0 com \n",
|
|
"4 pensiiilfov www ro \n",
|
|
"5 npr 0 org \n",
|
|
"6 rottentomatoes 0 com \n",
|
|
"7 majorleagueumpires 0 com \n",
|
|
"8 ebay 0 com \n",
|
|
"9 spokeo 0 com \n",
|
|
"10 sharetv 0 org \n",
|
|
"11 123people 0 com \n",
|
|
"12 123people 0 ca \n",
|
|
"13 zimtelegraph 0 com \n",
|
|
"14 manta 0 com \n",
|
|
"15 youtube 0 com \n",
|
|
"16 torcache 0 net \n",
|
|
"17 google 0 com \n",
|
|
"18 tvfanatic 0 com \n",
|
|
"19 filmreference 0 com \n",
|
|
"\n",
|
|
" query fragment redirect \\\n",
|
|
"0 0 0 0 \n",
|
|
"1 0 0 0 \n",
|
|
"2 0 0 1 \n",
|
|
"3 0 0 0 \n",
|
|
"4 {view=article, id=77, Itemid=184, option=com_c... 0 0 \n",
|
|
"5 0 0 0 \n",
|
|
"6 0 0 2 \n",
|
|
"7 0 0 0 \n",
|
|
"8 {_nkw=wil%2Bwheaton} 0 1 \n",
|
|
"9 0 0 2 \n",
|
|
"10 0 0 2 \n",
|
|
"11 0 0 0 \n",
|
|
"12 0 0 1 \n",
|
|
"13 {p=6151} 0 1 \n",
|
|
"14 0 0 2 \n",
|
|
"15 {v=TlqWAJFUols} 0 1 \n",
|
|
"16 {title=%5Bkickass.to%5Dunbroken.2014.1080p.brr... 0 0 \n",
|
|
"17 0 0 1 \n",
|
|
"18 0 0 2 \n",
|
|
"19 0 0 0 \n",
|
|
"\n",
|
|
" path \\\n",
|
|
"0 /marguerite_churchill/ \n",
|
|
"1 /statesville-nc/events/jazz%2Bconcerts \n",
|
|
"2 /wiki/Cory_Pecker \n",
|
|
"3 /9425680 \n",
|
|
"4 /index.php \n",
|
|
"5 /artists/134598784/seasick-steve \n",
|
|
"6 /celebrity/virna_lisi/ \n",
|
|
"7 / \n",
|
|
"8 /sch/i.html \n",
|
|
"9 /Susan%2BMeldrum \n",
|
|
"10 /person/noah_beery_jr \n",
|
|
"11 /s/jesse%2Baaron \n",
|
|
"12 /s/kevin%2Bbrown \n",
|
|
"13 / \n",
|
|
"14 /c/mtk113h/john-wornall-house-museum \n",
|
|
"15 /watch \n",
|
|
"16 /torrent/DEAC407A10AE056525A93EFA957BD252715DE... \n",
|
|
"17 / \n",
|
|
"18 /2009/05/merik-tadros-previews-ncis-showdown-s... \n",
|
|
"19 /film/46/Janis-Paige.html \n",
|
|
"\n",
|
|
" redirect_chain \\\n",
|
|
"0 {https://people.famouswhy.com/marguerite_churc... \n",
|
|
"1 0 \n",
|
|
"2 {https://icehockey.wikia.com/wiki/Cory_Pecker,... \n",
|
|
"3 {https://vimeo.com/9425680} \n",
|
|
"4 {http://www.pensiiilfov.ro/index.php?option=co... \n",
|
|
"5 0 \n",
|
|
"6 {https://rottentomatoes.com/celebrity/virna_li... \n",
|
|
"7 {https://majorleagueumpires.com/} \n",
|
|
"8 {https://ebay.com/sch/i.html?_nkw=wil+wheaton,... \n",
|
|
"9 {https://spokeo.com/Susan+Meldrum,https://www.... \n",
|
|
"10 {https://sharetv.org/person/noah_beery_jr,http... \n",
|
|
"11 {https://123people.com/s/jesse+aaron} \n",
|
|
"12 {https://123people.ca/s/kevin+brown,https://ww... \n",
|
|
"13 {https://zimtelegraph.com/?p=6151,https://www.... \n",
|
|
"14 {https://manta.com/c/mtk113h/john-wornall-hous... \n",
|
|
"15 {https://youtube.com/watch?v=TlqWAJFUols,https... \n",
|
|
"16 {http://torcache.net/torrent/DEAC407A10AE05652... \n",
|
|
"17 {https://google.com/,https://www.google.com/} \n",
|
|
"18 {https://tvfanatic.com/2009/05/merik-tadros-pr... \n",
|
|
"19 0 \n",
|
|
"\n",
|
|
" hsts_header ssl_stripping \\\n",
|
|
"0 {\"No HSTS Header detected\"} {false} \n",
|
|
"1 0 0 \n",
|
|
"2 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false} \n",
|
|
"3 {\"No HSTS Header detected\"} {false} \n",
|
|
"4 {\"Not an HTTPS connection\"} {false} \n",
|
|
"5 0 0 \n",
|
|
"6 {\"HSTS Header: max-age=31536000 ; includeSubDo... {false,false,false} \n",
|
|
"7 {\"No HSTS Header detected\"} {false} \n",
|
|
"8 {\"HSTS Header: max-age=31536000\",\"HSTS Header:... {false,false} \n",
|
|
"9 {\"No HSTS Header detected\",\"HSTS Header: max-a... {false,false,false} \n",
|
|
"10 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false,false} \n",
|
|
"11 {\"No HSTS Header detected\"} {false} \n",
|
|
"12 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false} \n",
|
|
"13 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false} \n",
|
|
"14 {\"No HSTS Header detected\",\"Not an HTTPS conne... {true,false,false} \n",
|
|
"15 {\"HSTS Header: max-age=31536000; includeSubDom... {false,false} \n",
|
|
"16 {\"Not an HTTPS connection\"} {false} \n",
|
|
"17 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false} \n",
|
|
"18 {\"No HSTS Header detected\",\"No HSTS Header det... {false,false,false} \n",
|
|
"19 0 0 \n",
|
|
"\n",
|
|
" hostname_embedding javascript_check shortening_service has_ip_address \\\n",
|
|
"0 0 0 0 0 \n",
|
|
"1 0 0 0 0 \n",
|
|
"2 0 0 0 0 \n",
|
|
"3 0 0 0 0 \n",
|
|
"4 0 0 0 0 \n",
|
|
"5 0 0 0 0 \n",
|
|
"6 0 0 0 0 \n",
|
|
"7 0 0 0 0 \n",
|
|
"8 0 0 0 0 \n",
|
|
"9 0 0 0 0 \n",
|
|
"10 0 0 0 0 \n",
|
|
"11 0 0 0 0 \n",
|
|
"12 0 0 0 0 \n",
|
|
"13 0 0 0 0 \n",
|
|
"14 0 0 0 0 \n",
|
|
"15 0 0 0 0 \n",
|
|
"16 0 0 0 0 \n",
|
|
"17 0 0 0 0 \n",
|
|
"18 0 0 0 0 \n",
|
|
"19 0 0 0 0 \n",
|
|
"\n",
|
|
" tracking_descriptions url_encoding has_executable tls \\\n",
|
|
"0 0 0 0 1 \n",
|
|
"1 0 Yes 0 1 \n",
|
|
"2 0 0 0 1 \n",
|
|
"3 0 0 0 1 \n",
|
|
"4 0 0 0 0 \n",
|
|
"5 0 0 0 1 \n",
|
|
"6 0 0 0 1 \n",
|
|
"7 0 0 0 1 \n",
|
|
"8 0 Yes 0 1 \n",
|
|
"9 0 Yes 0 1 \n",
|
|
"10 0 0 0 1 \n",
|
|
"11 0 Yes 0 1 \n",
|
|
"12 0 Yes 0 1 \n",
|
|
"13 0 0 0 1 \n",
|
|
"14 0 0 0 1 \n",
|
|
"15 0 0 0 1 \n",
|
|
"16 0 0 0 0 \n",
|
|
"17 0 0 0 1 \n",
|
|
"18 0 0 0 1 \n",
|
|
"19 0 0 0 1 \n",
|
|
"\n",
|
|
" contents target \n",
|
|
"0 https://people.famouswhy.com/marguerite_church... benign \n",
|
|
"1 https://events.charlotteobserver.com/statesvil... benign \n",
|
|
"2 https://icehockey.wikia.com/wiki/Cory_Pecker benign \n",
|
|
"3 https://vimeo.com/9425680 benign \n",
|
|
"4 http://www.pensiiilfov.ro/index.php?option=com... defacement \n",
|
|
"5 https://npr.org/artists/134598784/seasick-steve benign \n",
|
|
"6 https://rottentomatoes.com/celebrity/virna_lisi/ benign \n",
|
|
"7 https://majorleagueumpires.com/ benign \n",
|
|
"8 https://ebay.com/sch/i.html?_nkw=wil+wheaton benign \n",
|
|
"9 https://spokeo.com/Susan+Meldrum benign \n",
|
|
"10 https://sharetv.org/person/noah_beery_jr benign \n",
|
|
"11 https://123people.com/s/jesse+aaron benign \n",
|
|
"12 https://123people.ca/s/kevin+brown benign \n",
|
|
"13 https://zimtelegraph.com/?p=6151 benign \n",
|
|
"14 https://manta.com/c/mtk113h/john-wornall-house... benign \n",
|
|
"15 https://youtube.com/watch?v=TlqWAJFUols benign \n",
|
|
"16 http://torcache.net/torrent/DEAC407A10AE056525... benign \n",
|
|
"17 https://google.com/ benign \n",
|
|
"18 https://tvfanatic.com/2009/05/merik-tadros-pre... benign \n",
|
|
"19 https://filmreference.com/film/46/Janis-Paige.... benign "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-ed212002-5038-4f65-b660-01ff273628e4\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>famouswhy</td>\n",
|
|
" <td>people</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/marguerite_churchill/</td>\n",
|
|
" <td>{https://people.famouswhy.com/marguerite_churc...</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://people.famouswhy.com/marguerite_church...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>charlotteobserver</td>\n",
|
|
" <td>events</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/statesville-nc/events/jazz%2Bconcerts</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://events.charlotteobserver.com/statesvil...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>wikia</td>\n",
|
|
" <td>icehockey</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/wiki/Cory_Pecker</td>\n",
|
|
" <td>{https://icehockey.wikia.com/wiki/Cory_Pecker,...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://icehockey.wikia.com/wiki/Cory_Pecker</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>vimeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/9425680</td>\n",
|
|
" <td>{https://vimeo.com/9425680}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://vimeo.com/9425680</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>pensiiilfov</td>\n",
|
|
" <td>www</td>\n",
|
|
" <td>ro</td>\n",
|
|
" <td>{view=article, id=77, Itemid=184, option=com_c...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/index.php</td>\n",
|
|
" <td>{http://www.pensiiilfov.ro/index.php?option=co...</td>\n",
|
|
" <td>{\"Not an HTTPS connection\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://www.pensiiilfov.ro/index.php?option=com...</td>\n",
|
|
" <td>defacement</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>npr</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/artists/134598784/seasick-steve</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://npr.org/artists/134598784/seasick-steve</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>rottentomatoes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/celebrity/virna_lisi/</td>\n",
|
|
" <td>{https://rottentomatoes.com/celebrity/virna_li...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000 ; includeSubDo...</td>\n",
|
|
" <td>{false,false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://rottentomatoes.com/celebrity/virna_lisi/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>majorleagueumpires</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://majorleagueumpires.com/}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://majorleagueumpires.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>ebay</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{_nkw=wil%2Bwheaton}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/sch/i.html</td>\n",
|
|
" <td>{https://ebay.com/sch/i.html?_nkw=wil+wheaton,...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000\",\"HSTS Header:...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://ebay.com/sch/i.html?_nkw=wil+wheaton</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>spokeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/Susan%2BMeldrum</td>\n",
|
|
" <td>{https://spokeo.com/Susan+Meldrum,https://www....</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"HSTS Header: max-a...</td>\n",
|
|
" <td>{false,false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://spokeo.com/Susan+Meldrum</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>sharetv</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/person/noah_beery_jr</td>\n",
|
|
" <td>{https://sharetv.org/person/noah_beery_jr,http...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://sharetv.org/person/noah_beery_jr</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/s/jesse%2Baaron</td>\n",
|
|
" <td>{https://123people.com/s/jesse+aaron}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.com/s/jesse+aaron</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>ca</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/s/kevin%2Bbrown</td>\n",
|
|
" <td>{https://123people.ca/s/kevin+brown,https://ww...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>Yes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.ca/s/kevin+brown</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>zimtelegraph</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{p=6151}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://zimtelegraph.com/?p=6151,https://www....</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://zimtelegraph.com/?p=6151</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>manta</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/c/mtk113h/john-wornall-house-museum</td>\n",
|
|
" <td>{https://manta.com/c/mtk113h/john-wornall-hous...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"Not an HTTPS conne...</td>\n",
|
|
" <td>{true,false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://manta.com/c/mtk113h/john-wornall-house...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>youtube</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{v=TlqWAJFUols}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/watch</td>\n",
|
|
" <td>{https://youtube.com/watch?v=TlqWAJFUols,https...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000; includeSubDom...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://youtube.com/watch?v=TlqWAJFUols</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>torcache</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>net</td>\n",
|
|
" <td>{title=%5Bkickass.to%5Dunbroken.2014.1080p.brr...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/torrent/DEAC407A10AE056525A93EFA957BD252715DE...</td>\n",
|
|
" <td>{http://torcache.net/torrent/DEAC407A10AE05652...</td>\n",
|
|
" <td>{\"Not an HTTPS connection\"}</td>\n",
|
|
" <td>{false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://torcache.net/torrent/DEAC407A10AE056525...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>17</th>\n",
|
|
" <td>google</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://google.com/,https://www.google.com/}</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://google.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>18</th>\n",
|
|
" <td>tvfanatic</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/2009/05/merik-tadros-previews-ncis-showdown-s...</td>\n",
|
|
" <td>{https://tvfanatic.com/2009/05/merik-tadros-pr...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>{false,false,false}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://tvfanatic.com/2009/05/merik-tadros-pre...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>19</th>\n",
|
|
" <td>filmreference</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/film/46/Janis-Paige.html</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://filmreference.com/film/46/Janis-Paige....</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-ed212002-5038-4f65-b660-01ff273628e4')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-ed212002-5038-4f65-b660-01ff273628e4 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-ed212002-5038-4f65-b660-01ff273628e4');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-ed6f5197-54a8-4add-bf05-580db52d12c7\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ed6f5197-54a8-4add-bf05-580db52d12c7')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-ed6f5197-54a8-4add-bf05-580db52d12c7 button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 3
|
|
}
|
|
],
|
|
"source": [
|
|
"# Drop the 'qr_code_id' and 'created_at' columns\n",
|
|
"data = data.drop(columns=['qr_code_id', 'created_at'])\n",
|
|
"\n",
|
|
"# Replace all NaN and None values with 0\n",
|
|
"data = data.fillna(0)\n",
|
|
"\n",
|
|
"# Replace the string \"{}\" with 0\n",
|
|
"data = data.replace(\"{}\", 0)\n",
|
|
"\n",
|
|
"# Rename the 'qr_code_id' column to 'tls'\n",
|
|
"data = data.rename(columns={'qr_code_type_id': 'tls'})\n",
|
|
"\n",
|
|
"# Rename the 'qr_code_id' column to 'tls'\n",
|
|
"data = data.rename(columns={'result_category': 'target'})\n",
|
|
"\n",
|
|
"# Change the value in 'tls' column: 0 when value is 1, 1 when value is 9\n",
|
|
"data['tls'] = data['tls'].replace({1: 0, 9: 1})\n",
|
|
"\n",
|
|
"# Display the first few rows to verify\n",
|
|
"data.head(20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 1000
|
|
},
|
|
"id": "ywGN31K4VqYh",
|
|
"outputId": "efc2e527-f54f-4bda-8afc-d424fb910f0b"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain \\\n",
|
|
"0 famouswhy people com \n",
|
|
"1 charlotteobserver events com \n",
|
|
"2 wikia icehockey com \n",
|
|
"3 vimeo 0 com \n",
|
|
"4 pensiiilfov www ro \n",
|
|
"5 npr 0 org \n",
|
|
"6 rottentomatoes 0 com \n",
|
|
"7 majorleagueumpires 0 com \n",
|
|
"8 ebay 0 com \n",
|
|
"9 spokeo 0 com \n",
|
|
"10 sharetv 0 org \n",
|
|
"11 123people 0 com \n",
|
|
"12 123people 0 ca \n",
|
|
"13 zimtelegraph 0 com \n",
|
|
"14 manta 0 com \n",
|
|
"15 youtube 0 com \n",
|
|
"16 torcache 0 net \n",
|
|
"17 google 0 com \n",
|
|
"18 tvfanatic 0 com \n",
|
|
"19 filmreference 0 com \n",
|
|
"\n",
|
|
" query fragment redirect \\\n",
|
|
"0 0 0 0 \n",
|
|
"1 0 0 0 \n",
|
|
"2 0 0 1 \n",
|
|
"3 0 0 0 \n",
|
|
"4 {view=article, id=77, Itemid=184, option=com_c... 0 0 \n",
|
|
"5 0 0 0 \n",
|
|
"6 0 0 2 \n",
|
|
"7 0 0 0 \n",
|
|
"8 {_nkw=wil%2Bwheaton} 0 1 \n",
|
|
"9 0 0 2 \n",
|
|
"10 0 0 2 \n",
|
|
"11 0 0 0 \n",
|
|
"12 0 0 1 \n",
|
|
"13 {p=6151} 0 1 \n",
|
|
"14 0 0 2 \n",
|
|
"15 {v=TlqWAJFUols} 0 1 \n",
|
|
"16 {title=%5Bkickass.to%5Dunbroken.2014.1080p.brr... 0 0 \n",
|
|
"17 0 0 1 \n",
|
|
"18 0 0 2 \n",
|
|
"19 0 0 0 \n",
|
|
"\n",
|
|
" path \\\n",
|
|
"0 /marguerite_churchill/ \n",
|
|
"1 /statesville-nc/events/jazz%2Bconcerts \n",
|
|
"2 /wiki/Cory_Pecker \n",
|
|
"3 /9425680 \n",
|
|
"4 /index.php \n",
|
|
"5 /artists/134598784/seasick-steve \n",
|
|
"6 /celebrity/virna_lisi/ \n",
|
|
"7 / \n",
|
|
"8 /sch/i.html \n",
|
|
"9 /Susan%2BMeldrum \n",
|
|
"10 /person/noah_beery_jr \n",
|
|
"11 /s/jesse%2Baaron \n",
|
|
"12 /s/kevin%2Bbrown \n",
|
|
"13 / \n",
|
|
"14 /c/mtk113h/john-wornall-house-museum \n",
|
|
"15 /watch \n",
|
|
"16 /torrent/DEAC407A10AE056525A93EFA957BD252715DE... \n",
|
|
"17 / \n",
|
|
"18 /2009/05/merik-tadros-previews-ncis-showdown-s... \n",
|
|
"19 /film/46/Janis-Paige.html \n",
|
|
"\n",
|
|
" redirect_chain \\\n",
|
|
"0 {https://people.famouswhy.com/marguerite_churc... \n",
|
|
"1 0 \n",
|
|
"2 {https://icehockey.wikia.com/wiki/Cory_Pecker,... \n",
|
|
"3 {https://vimeo.com/9425680} \n",
|
|
"4 {http://www.pensiiilfov.ro/index.php?option=co... \n",
|
|
"5 0 \n",
|
|
"6 {https://rottentomatoes.com/celebrity/virna_li... \n",
|
|
"7 {https://majorleagueumpires.com/} \n",
|
|
"8 {https://ebay.com/sch/i.html?_nkw=wil+wheaton,... \n",
|
|
"9 {https://spokeo.com/Susan+Meldrum,https://www.... \n",
|
|
"10 {https://sharetv.org/person/noah_beery_jr,http... \n",
|
|
"11 {https://123people.com/s/jesse+aaron} \n",
|
|
"12 {https://123people.ca/s/kevin+brown,https://ww... \n",
|
|
"13 {https://zimtelegraph.com/?p=6151,https://www.... \n",
|
|
"14 {https://manta.com/c/mtk113h/john-wornall-hous... \n",
|
|
"15 {https://youtube.com/watch?v=TlqWAJFUols,https... \n",
|
|
"16 {http://torcache.net/torrent/DEAC407A10AE05652... \n",
|
|
"17 {https://google.com/,https://www.google.com/} \n",
|
|
"18 {https://tvfanatic.com/2009/05/merik-tadros-pr... \n",
|
|
"19 0 \n",
|
|
"\n",
|
|
" hsts_header ssl_stripping \\\n",
|
|
"0 {\"No HSTS Header detected\"} 0 \n",
|
|
"1 0 0 \n",
|
|
"2 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"3 {\"No HSTS Header detected\"} 0 \n",
|
|
"4 {\"Not an HTTPS connection\"} 0 \n",
|
|
"5 0 0 \n",
|
|
"6 {\"HSTS Header: max-age=31536000 ; includeSubDo... 0 \n",
|
|
"7 {\"No HSTS Header detected\"} 0 \n",
|
|
"8 {\"HSTS Header: max-age=31536000\",\"HSTS Header:... 0 \n",
|
|
"9 {\"No HSTS Header detected\",\"HSTS Header: max-a... 0 \n",
|
|
"10 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"11 {\"No HSTS Header detected\"} 0 \n",
|
|
"12 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"13 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"14 {\"No HSTS Header detected\",\"Not an HTTPS conne... 1 \n",
|
|
"15 {\"HSTS Header: max-age=31536000; includeSubDom... 0 \n",
|
|
"16 {\"Not an HTTPS connection\"} 0 \n",
|
|
"17 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"18 {\"No HSTS Header detected\",\"No HSTS Header det... 0 \n",
|
|
"19 0 0 \n",
|
|
"\n",
|
|
" hostname_embedding javascript_check shortening_service has_ip_address \\\n",
|
|
"0 0 0 0 0 \n",
|
|
"1 0 0 0 0 \n",
|
|
"2 0 0 0 0 \n",
|
|
"3 0 0 0 0 \n",
|
|
"4 0 0 0 0 \n",
|
|
"5 0 0 0 0 \n",
|
|
"6 0 0 0 0 \n",
|
|
"7 0 0 0 0 \n",
|
|
"8 0 0 0 0 \n",
|
|
"9 0 0 0 0 \n",
|
|
"10 0 0 0 0 \n",
|
|
"11 0 0 0 0 \n",
|
|
"12 0 0 0 0 \n",
|
|
"13 0 0 0 0 \n",
|
|
"14 0 0 0 0 \n",
|
|
"15 0 0 0 0 \n",
|
|
"16 0 0 0 0 \n",
|
|
"17 0 0 0 0 \n",
|
|
"18 0 0 0 0 \n",
|
|
"19 0 0 0 0 \n",
|
|
"\n",
|
|
" tracking_descriptions url_encoding has_executable tls \\\n",
|
|
"0 0 0 0 1 \n",
|
|
"1 0 1 0 1 \n",
|
|
"2 0 0 0 1 \n",
|
|
"3 0 0 0 1 \n",
|
|
"4 0 0 0 0 \n",
|
|
"5 0 0 0 1 \n",
|
|
"6 0 0 0 1 \n",
|
|
"7 0 0 0 1 \n",
|
|
"8 0 1 0 1 \n",
|
|
"9 0 1 0 1 \n",
|
|
"10 0 0 0 1 \n",
|
|
"11 0 1 0 1 \n",
|
|
"12 0 1 0 1 \n",
|
|
"13 0 0 0 1 \n",
|
|
"14 0 0 0 1 \n",
|
|
"15 0 0 0 1 \n",
|
|
"16 0 0 0 0 \n",
|
|
"17 0 0 0 1 \n",
|
|
"18 0 0 0 1 \n",
|
|
"19 0 0 0 1 \n",
|
|
"\n",
|
|
" contents target \n",
|
|
"0 https://people.famouswhy.com/marguerite_church... benign \n",
|
|
"1 https://events.charlotteobserver.com/statesvil... benign \n",
|
|
"2 https://icehockey.wikia.com/wiki/Cory_Pecker benign \n",
|
|
"3 https://vimeo.com/9425680 benign \n",
|
|
"4 http://www.pensiiilfov.ro/index.php?option=com... defacement \n",
|
|
"5 https://npr.org/artists/134598784/seasick-steve benign \n",
|
|
"6 https://rottentomatoes.com/celebrity/virna_lisi/ benign \n",
|
|
"7 https://majorleagueumpires.com/ benign \n",
|
|
"8 https://ebay.com/sch/i.html?_nkw=wil+wheaton benign \n",
|
|
"9 https://spokeo.com/Susan+Meldrum benign \n",
|
|
"10 https://sharetv.org/person/noah_beery_jr benign \n",
|
|
"11 https://123people.com/s/jesse+aaron benign \n",
|
|
"12 https://123people.ca/s/kevin+brown benign \n",
|
|
"13 https://zimtelegraph.com/?p=6151 benign \n",
|
|
"14 https://manta.com/c/mtk113h/john-wornall-house... benign \n",
|
|
"15 https://youtube.com/watch?v=TlqWAJFUols benign \n",
|
|
"16 http://torcache.net/torrent/DEAC407A10AE056525... benign \n",
|
|
"17 https://google.com/ benign \n",
|
|
"18 https://tvfanatic.com/2009/05/merik-tadros-pre... benign \n",
|
|
"19 https://filmreference.com/film/46/Janis-Paige.... benign "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-a11320e6-f5be-48f9-b984-8f51a6aaf569\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>famouswhy</td>\n",
|
|
" <td>people</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/marguerite_churchill/</td>\n",
|
|
" <td>{https://people.famouswhy.com/marguerite_churc...</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://people.famouswhy.com/marguerite_church...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>charlotteobserver</td>\n",
|
|
" <td>events</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/statesville-nc/events/jazz%2Bconcerts</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://events.charlotteobserver.com/statesvil...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>wikia</td>\n",
|
|
" <td>icehockey</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/wiki/Cory_Pecker</td>\n",
|
|
" <td>{https://icehockey.wikia.com/wiki/Cory_Pecker,...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://icehockey.wikia.com/wiki/Cory_Pecker</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>vimeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/9425680</td>\n",
|
|
" <td>{https://vimeo.com/9425680}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://vimeo.com/9425680</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>pensiiilfov</td>\n",
|
|
" <td>www</td>\n",
|
|
" <td>ro</td>\n",
|
|
" <td>{view=article, id=77, Itemid=184, option=com_c...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/index.php</td>\n",
|
|
" <td>{http://www.pensiiilfov.ro/index.php?option=co...</td>\n",
|
|
" <td>{\"Not an HTTPS connection\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://www.pensiiilfov.ro/index.php?option=com...</td>\n",
|
|
" <td>defacement</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>npr</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/artists/134598784/seasick-steve</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://npr.org/artists/134598784/seasick-steve</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>rottentomatoes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/celebrity/virna_lisi/</td>\n",
|
|
" <td>{https://rottentomatoes.com/celebrity/virna_li...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000 ; includeSubDo...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://rottentomatoes.com/celebrity/virna_lisi/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>majorleagueumpires</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://majorleagueumpires.com/}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://majorleagueumpires.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>ebay</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{_nkw=wil%2Bwheaton}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/sch/i.html</td>\n",
|
|
" <td>{https://ebay.com/sch/i.html?_nkw=wil+wheaton,...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000\",\"HSTS Header:...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://ebay.com/sch/i.html?_nkw=wil+wheaton</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>spokeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/Susan%2BMeldrum</td>\n",
|
|
" <td>{https://spokeo.com/Susan+Meldrum,https://www....</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"HSTS Header: max-a...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://spokeo.com/Susan+Meldrum</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>sharetv</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/person/noah_beery_jr</td>\n",
|
|
" <td>{https://sharetv.org/person/noah_beery_jr,http...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://sharetv.org/person/noah_beery_jr</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/s/jesse%2Baaron</td>\n",
|
|
" <td>{https://123people.com/s/jesse+aaron}</td>\n",
|
|
" <td>{\"No HSTS Header detected\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.com/s/jesse+aaron</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>ca</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/s/kevin%2Bbrown</td>\n",
|
|
" <td>{https://123people.ca/s/kevin+brown,https://ww...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.ca/s/kevin+brown</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>zimtelegraph</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{p=6151}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://zimtelegraph.com/?p=6151,https://www....</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://zimtelegraph.com/?p=6151</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>manta</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/c/mtk113h/john-wornall-house-museum</td>\n",
|
|
" <td>{https://manta.com/c/mtk113h/john-wornall-hous...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"Not an HTTPS conne...</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://manta.com/c/mtk113h/john-wornall-house...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>youtube</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{v=TlqWAJFUols}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/watch</td>\n",
|
|
" <td>{https://youtube.com/watch?v=TlqWAJFUols,https...</td>\n",
|
|
" <td>{\"HSTS Header: max-age=31536000; includeSubDom...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://youtube.com/watch?v=TlqWAJFUols</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>torcache</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>net</td>\n",
|
|
" <td>{title=%5Bkickass.to%5Dunbroken.2014.1080p.brr...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/torrent/DEAC407A10AE056525A93EFA957BD252715DE...</td>\n",
|
|
" <td>{http://torcache.net/torrent/DEAC407A10AE05652...</td>\n",
|
|
" <td>{\"Not an HTTPS connection\"}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://torcache.net/torrent/DEAC407A10AE056525...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>17</th>\n",
|
|
" <td>google</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://google.com/,https://www.google.com/}</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://google.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>18</th>\n",
|
|
" <td>tvfanatic</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/2009/05/merik-tadros-previews-ncis-showdown-s...</td>\n",
|
|
" <td>{https://tvfanatic.com/2009/05/merik-tadros-pr...</td>\n",
|
|
" <td>{\"No HSTS Header detected\",\"No HSTS Header det...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://tvfanatic.com/2009/05/merik-tadros-pre...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>19</th>\n",
|
|
" <td>filmreference</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/film/46/Janis-Paige.html</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://filmreference.com/film/46/Janis-Paige....</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-a11320e6-f5be-48f9-b984-8f51a6aaf569')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-a11320e6-f5be-48f9-b984-8f51a6aaf569 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-a11320e6-f5be-48f9-b984-8f51a6aaf569');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-f3b03455-8f25-4ae3-afac-d66b12cea3c4\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f3b03455-8f25-4ae3-afac-d66b12cea3c4')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-f3b03455-8f25-4ae3-afac-d66b12cea3c4 button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 4
|
|
}
|
|
],
|
|
"source": [
|
|
"# List of columns to modify to 1\n",
|
|
"columns_to_modify = ['hostname_embedding', 'javascript_check', 'shortening_service',\n",
|
|
" 'has_ip_address', 'url_encoding', 'has_executable',\n",
|
|
" 'tracking_descriptions']\n",
|
|
"\n",
|
|
"# Update the values: set to 1 if not already 0\n",
|
|
"for column in columns_to_modify:\n",
|
|
" data[column] = data[column].apply(lambda x: 1 if x != 0 else 0)\n",
|
|
"\n",
|
|
"# Convert 'ssl_stripping' column: set to 1 if the value is \"true\", else set to 0\n",
|
|
"data['ssl_stripping'] = data['ssl_stripping'].apply(lambda x: 1 if \"true\" in str(x).lower() else 0)\n",
|
|
"\n",
|
|
"\n",
|
|
"# Display the first few rows to verify changes\n",
|
|
"data.head(20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 696
|
|
},
|
|
"id": "25TtImKZ21tM",
|
|
"outputId": "79f1924b-b54c-4d24-ffd1-d3079dc51914"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain \\\n",
|
|
"0 famouswhy people com \n",
|
|
"1 charlotteobserver events com \n",
|
|
"2 wikia icehockey com \n",
|
|
"3 vimeo 0 com \n",
|
|
"4 pensiiilfov www ro \n",
|
|
"5 npr 0 org \n",
|
|
"6 rottentomatoes 0 com \n",
|
|
"7 majorleagueumpires 0 com \n",
|
|
"8 ebay 0 com \n",
|
|
"9 spokeo 0 com \n",
|
|
"10 sharetv 0 org \n",
|
|
"11 123people 0 com \n",
|
|
"12 123people 0 ca \n",
|
|
"13 zimtelegraph 0 com \n",
|
|
"14 manta 0 com \n",
|
|
"15 youtube 0 com \n",
|
|
"16 torcache 0 net \n",
|
|
"17 google 0 com \n",
|
|
"18 tvfanatic 0 com \n",
|
|
"19 filmreference 0 com \n",
|
|
"\n",
|
|
" query fragment redirect \\\n",
|
|
"0 0 0 0 \n",
|
|
"1 0 0 0 \n",
|
|
"2 0 0 1 \n",
|
|
"3 0 0 0 \n",
|
|
"4 {view=article, id=77, Itemid=184, option=com_c... 0 0 \n",
|
|
"5 0 0 0 \n",
|
|
"6 0 0 2 \n",
|
|
"7 0 0 0 \n",
|
|
"8 {_nkw=wil%2Bwheaton} 0 1 \n",
|
|
"9 0 0 2 \n",
|
|
"10 0 0 2 \n",
|
|
"11 0 0 0 \n",
|
|
"12 0 0 1 \n",
|
|
"13 {p=6151} 0 1 \n",
|
|
"14 0 0 2 \n",
|
|
"15 {v=TlqWAJFUols} 0 1 \n",
|
|
"16 {title=%5Bkickass.to%5Dunbroken.2014.1080p.brr... 0 0 \n",
|
|
"17 0 0 1 \n",
|
|
"18 0 0 2 \n",
|
|
"19 0 0 0 \n",
|
|
"\n",
|
|
" path \\\n",
|
|
"0 /marguerite_churchill/ \n",
|
|
"1 /statesville-nc/events/jazz%2Bconcerts \n",
|
|
"2 /wiki/Cory_Pecker \n",
|
|
"3 /9425680 \n",
|
|
"4 /index.php \n",
|
|
"5 /artists/134598784/seasick-steve \n",
|
|
"6 /celebrity/virna_lisi/ \n",
|
|
"7 / \n",
|
|
"8 /sch/i.html \n",
|
|
"9 /Susan%2BMeldrum \n",
|
|
"10 /person/noah_beery_jr \n",
|
|
"11 /s/jesse%2Baaron \n",
|
|
"12 /s/kevin%2Bbrown \n",
|
|
"13 / \n",
|
|
"14 /c/mtk113h/john-wornall-house-museum \n",
|
|
"15 /watch \n",
|
|
"16 /torrent/DEAC407A10AE056525A93EFA957BD252715DE... \n",
|
|
"17 / \n",
|
|
"18 /2009/05/merik-tadros-previews-ncis-showdown-s... \n",
|
|
"19 /film/46/Janis-Paige.html \n",
|
|
"\n",
|
|
" redirect_chain hsts_header \\\n",
|
|
"0 {https://people.famouswhy.com/marguerite_churc... 0 \n",
|
|
"1 0 0 \n",
|
|
"2 {https://icehockey.wikia.com/wiki/Cory_Pecker,... 0 \n",
|
|
"3 {https://vimeo.com/9425680} 0 \n",
|
|
"4 {http://www.pensiiilfov.ro/index.php?option=co... 0 \n",
|
|
"5 0 0 \n",
|
|
"6 {https://rottentomatoes.com/celebrity/virna_li... 1 \n",
|
|
"7 {https://majorleagueumpires.com/} 0 \n",
|
|
"8 {https://ebay.com/sch/i.html?_nkw=wil+wheaton,... 1 \n",
|
|
"9 {https://spokeo.com/Susan+Meldrum,https://www.... 0 \n",
|
|
"10 {https://sharetv.org/person/noah_beery_jr,http... 0 \n",
|
|
"11 {https://123people.com/s/jesse+aaron} 0 \n",
|
|
"12 {https://123people.ca/s/kevin+brown,https://ww... 0 \n",
|
|
"13 {https://zimtelegraph.com/?p=6151,https://www.... 0 \n",
|
|
"14 {https://manta.com/c/mtk113h/john-wornall-hous... 0 \n",
|
|
"15 {https://youtube.com/watch?v=TlqWAJFUols,https... 1 \n",
|
|
"16 {http://torcache.net/torrent/DEAC407A10AE05652... 0 \n",
|
|
"17 {https://google.com/,https://www.google.com/} 0 \n",
|
|
"18 {https://tvfanatic.com/2009/05/merik-tadros-pr... 0 \n",
|
|
"19 0 0 \n",
|
|
"\n",
|
|
" ssl_stripping hostname_embedding javascript_check shortening_service \\\n",
|
|
"0 0 0 0 0 \n",
|
|
"1 0 0 0 0 \n",
|
|
"2 0 0 0 0 \n",
|
|
"3 0 0 0 0 \n",
|
|
"4 0 0 0 0 \n",
|
|
"5 0 0 0 0 \n",
|
|
"6 0 0 0 0 \n",
|
|
"7 0 0 0 0 \n",
|
|
"8 0 0 0 0 \n",
|
|
"9 0 0 0 0 \n",
|
|
"10 0 0 0 0 \n",
|
|
"11 0 0 0 0 \n",
|
|
"12 0 0 0 0 \n",
|
|
"13 0 0 0 0 \n",
|
|
"14 1 0 0 0 \n",
|
|
"15 0 0 0 0 \n",
|
|
"16 0 0 0 0 \n",
|
|
"17 0 0 0 0 \n",
|
|
"18 0 0 0 0 \n",
|
|
"19 0 0 0 0 \n",
|
|
"\n",
|
|
" has_ip_address tracking_descriptions url_encoding has_executable tls \\\n",
|
|
"0 0 0 0 0 1 \n",
|
|
"1 0 0 1 0 1 \n",
|
|
"2 0 0 0 0 1 \n",
|
|
"3 0 0 0 0 1 \n",
|
|
"4 0 0 0 0 0 \n",
|
|
"5 0 0 0 0 1 \n",
|
|
"6 0 0 0 0 1 \n",
|
|
"7 0 0 0 0 1 \n",
|
|
"8 0 0 1 0 1 \n",
|
|
"9 0 0 1 0 1 \n",
|
|
"10 0 0 0 0 1 \n",
|
|
"11 0 0 1 0 1 \n",
|
|
"12 0 0 1 0 1 \n",
|
|
"13 0 0 0 0 1 \n",
|
|
"14 0 0 0 0 1 \n",
|
|
"15 0 0 0 0 1 \n",
|
|
"16 0 0 0 0 0 \n",
|
|
"17 0 0 0 0 1 \n",
|
|
"18 0 0 0 0 1 \n",
|
|
"19 0 0 0 0 1 \n",
|
|
"\n",
|
|
" contents target \n",
|
|
"0 https://people.famouswhy.com/marguerite_church... benign \n",
|
|
"1 https://events.charlotteobserver.com/statesvil... benign \n",
|
|
"2 https://icehockey.wikia.com/wiki/Cory_Pecker benign \n",
|
|
"3 https://vimeo.com/9425680 benign \n",
|
|
"4 http://www.pensiiilfov.ro/index.php?option=com... defacement \n",
|
|
"5 https://npr.org/artists/134598784/seasick-steve benign \n",
|
|
"6 https://rottentomatoes.com/celebrity/virna_lisi/ benign \n",
|
|
"7 https://majorleagueumpires.com/ benign \n",
|
|
"8 https://ebay.com/sch/i.html?_nkw=wil+wheaton benign \n",
|
|
"9 https://spokeo.com/Susan+Meldrum benign \n",
|
|
"10 https://sharetv.org/person/noah_beery_jr benign \n",
|
|
"11 https://123people.com/s/jesse+aaron benign \n",
|
|
"12 https://123people.ca/s/kevin+brown benign \n",
|
|
"13 https://zimtelegraph.com/?p=6151 benign \n",
|
|
"14 https://manta.com/c/mtk113h/john-wornall-house... benign \n",
|
|
"15 https://youtube.com/watch?v=TlqWAJFUols benign \n",
|
|
"16 http://torcache.net/torrent/DEAC407A10AE056525... benign \n",
|
|
"17 https://google.com/ benign \n",
|
|
"18 https://tvfanatic.com/2009/05/merik-tadros-pre... benign \n",
|
|
"19 https://filmreference.com/film/46/Janis-Paige.... benign "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-4b5286e0-2720-49c1-9855-ec5706f63403\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>famouswhy</td>\n",
|
|
" <td>people</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/marguerite_churchill/</td>\n",
|
|
" <td>{https://people.famouswhy.com/marguerite_churc...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://people.famouswhy.com/marguerite_church...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>charlotteobserver</td>\n",
|
|
" <td>events</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/statesville-nc/events/jazz%2Bconcerts</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://events.charlotteobserver.com/statesvil...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>wikia</td>\n",
|
|
" <td>icehockey</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/wiki/Cory_Pecker</td>\n",
|
|
" <td>{https://icehockey.wikia.com/wiki/Cory_Pecker,...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://icehockey.wikia.com/wiki/Cory_Pecker</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>vimeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/9425680</td>\n",
|
|
" <td>{https://vimeo.com/9425680}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://vimeo.com/9425680</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>pensiiilfov</td>\n",
|
|
" <td>www</td>\n",
|
|
" <td>ro</td>\n",
|
|
" <td>{view=article, id=77, Itemid=184, option=com_c...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/index.php</td>\n",
|
|
" <td>{http://www.pensiiilfov.ro/index.php?option=co...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://www.pensiiilfov.ro/index.php?option=com...</td>\n",
|
|
" <td>defacement</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>5</th>\n",
|
|
" <td>npr</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/artists/134598784/seasick-steve</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://npr.org/artists/134598784/seasick-steve</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>6</th>\n",
|
|
" <td>rottentomatoes</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/celebrity/virna_lisi/</td>\n",
|
|
" <td>{https://rottentomatoes.com/celebrity/virna_li...</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://rottentomatoes.com/celebrity/virna_lisi/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>7</th>\n",
|
|
" <td>majorleagueumpires</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://majorleagueumpires.com/}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://majorleagueumpires.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>8</th>\n",
|
|
" <td>ebay</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{_nkw=wil%2Bwheaton}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/sch/i.html</td>\n",
|
|
" <td>{https://ebay.com/sch/i.html?_nkw=wil+wheaton,...</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://ebay.com/sch/i.html?_nkw=wil+wheaton</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>9</th>\n",
|
|
" <td>spokeo</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/Susan%2BMeldrum</td>\n",
|
|
" <td>{https://spokeo.com/Susan+Meldrum,https://www....</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://spokeo.com/Susan+Meldrum</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>10</th>\n",
|
|
" <td>sharetv</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>org</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/person/noah_beery_jr</td>\n",
|
|
" <td>{https://sharetv.org/person/noah_beery_jr,http...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://sharetv.org/person/noah_beery_jr</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>11</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/s/jesse%2Baaron</td>\n",
|
|
" <td>{https://123people.com/s/jesse+aaron}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.com/s/jesse+aaron</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>12</th>\n",
|
|
" <td>123people</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>ca</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/s/kevin%2Bbrown</td>\n",
|
|
" <td>{https://123people.ca/s/kevin+brown,https://ww...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://123people.ca/s/kevin+brown</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>13</th>\n",
|
|
" <td>zimtelegraph</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{p=6151}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://zimtelegraph.com/?p=6151,https://www....</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://zimtelegraph.com/?p=6151</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>14</th>\n",
|
|
" <td>manta</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/c/mtk113h/john-wornall-house-museum</td>\n",
|
|
" <td>{https://manta.com/c/mtk113h/john-wornall-hous...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://manta.com/c/mtk113h/john-wornall-house...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>15</th>\n",
|
|
" <td>youtube</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>{v=TlqWAJFUols}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/watch</td>\n",
|
|
" <td>{https://youtube.com/watch?v=TlqWAJFUols,https...</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://youtube.com/watch?v=TlqWAJFUols</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>16</th>\n",
|
|
" <td>torcache</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>net</td>\n",
|
|
" <td>{title=%5Bkickass.to%5Dunbroken.2014.1080p.brr...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/torrent/DEAC407A10AE056525A93EFA957BD252715DE...</td>\n",
|
|
" <td>{http://torcache.net/torrent/DEAC407A10AE05652...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>http://torcache.net/torrent/DEAC407A10AE056525...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>17</th>\n",
|
|
" <td>google</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>/</td>\n",
|
|
" <td>{https://google.com/,https://www.google.com/}</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://google.com/</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>18</th>\n",
|
|
" <td>tvfanatic</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>/2009/05/merik-tadros-previews-ncis-showdown-s...</td>\n",
|
|
" <td>{https://tvfanatic.com/2009/05/merik-tadros-pr...</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://tvfanatic.com/2009/05/merik-tadros-pre...</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>19</th>\n",
|
|
" <td>filmreference</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>com</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>/film/46/Janis-Paige.html</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>https://filmreference.com/film/46/Janis-Paige....</td>\n",
|
|
" <td>benign</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-4b5286e0-2720-49c1-9855-ec5706f63403')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-4b5286e0-2720-49c1-9855-ec5706f63403 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-4b5286e0-2720-49c1-9855-ec5706f63403');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-0565dfc2-87bf-483c-b534-2c932b670d86\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0565dfc2-87bf-483c-b534-2c932b670d86')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-0565dfc2-87bf-483c-b534-2c932b670d86 button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 5
|
|
}
|
|
],
|
|
"source": [
|
|
"import re\n",
|
|
"\n",
|
|
"def process_hsts_header(value):\n",
|
|
" # If the value is already 0, return 0\n",
|
|
" if value == 0:\n",
|
|
" return 0\n",
|
|
"\n",
|
|
" # Check if the value starts with '{' and ends with '}', indicating it's an array-like format\n",
|
|
" if isinstance(value, str) and value.startswith(\"{\") and value.endswith(\"}\"):\n",
|
|
" # Remove the curly braces and split the string by commas\n",
|
|
" items = re.findall(r'\\\"(.*?)\\\"', value)\n",
|
|
"\n",
|
|
" # Check the first item in the parsed list\n",
|
|
" if items and 'no' in items[0].lower():\n",
|
|
" return 0\n",
|
|
" else:\n",
|
|
" return 1\n",
|
|
" else:\n",
|
|
" # If it's not in the expected format, return 0\n",
|
|
" return 0\n",
|
|
"\n",
|
|
"# Apply the function to the 'hsts_header' column\n",
|
|
"data['hsts_header'] = data['hsts_header'].apply(process_hsts_header)\n",
|
|
"\n",
|
|
"# Display the first few rows to verify the changes\n",
|
|
"data.head(20)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 226
|
|
},
|
|
"id": "-xm0OCUi7_Nt",
|
|
"outputId": "eaa62d42-3b59-4957-a880-bf557add58fd"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain query fragment redirect path \\\n",
|
|
"0 9 6 3 1 1 0 22 \n",
|
|
"1 17 6 3 1 1 0 38 \n",
|
|
"2 5 9 3 1 1 1 17 \n",
|
|
"3 5 1 3 1 1 0 8 \n",
|
|
"4 11 3 2 53 1 0 10 \n",
|
|
"\n",
|
|
" redirect_chain hsts_header ssl_stripping hostname_embedding \\\n",
|
|
"0 52 0 0 0 \n",
|
|
"1 1 0 0 0 \n",
|
|
"2 92 0 0 0 \n",
|
|
"3 27 0 0 0 \n",
|
|
"4 86 0 0 0 \n",
|
|
"\n",
|
|
" javascript_check shortening_service has_ip_address \\\n",
|
|
"0 0 0 0 \n",
|
|
"1 0 0 0 \n",
|
|
"2 0 0 0 \n",
|
|
"3 0 0 0 \n",
|
|
"4 0 0 0 \n",
|
|
"\n",
|
|
" tracking_descriptions url_encoding has_executable tls contents target \n",
|
|
"0 0 0 0 1 50 0 \n",
|
|
"1 0 1 0 1 72 0 \n",
|
|
"2 0 0 0 1 44 0 \n",
|
|
"3 0 0 0 1 25 0 \n",
|
|
"4 0 0 0 0 84 1 "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-11b744b8-7064-4c87-b911-8a9aac84255b\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>9</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>22</td>\n",
|
|
" <td>52</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>50</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>17</td>\n",
|
|
" <td>6</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>38</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>72</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>5</td>\n",
|
|
" <td>9</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>92</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>44</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>5</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>8</td>\n",
|
|
" <td>27</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>25</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>11</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>10</td>\n",
|
|
" <td>86</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>84</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-11b744b8-7064-4c87-b911-8a9aac84255b')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-11b744b8-7064-4c87-b911-8a9aac84255b 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-11b744b8-7064-4c87-b911-8a9aac84255b');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-b7fbd6c0-15cd-4d7d-a1cd-3e0d341aa5a9\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b7fbd6c0-15cd-4d7d-a1cd-3e0d341aa5a9')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-b7fbd6c0-15cd-4d7d-a1cd-3e0d341aa5a9 button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 6
|
|
}
|
|
],
|
|
"source": [
|
|
"# List of columns to convert to number of characters\n",
|
|
"columns_to_convert = ['domain', 'top_level_domain', 'subdomain', 'query',\n",
|
|
" 'fragment', 'path', 'redirect_chain', 'contents']\n",
|
|
"\n",
|
|
"# Apply len() function to each of the specified columns to get the number of characters\n",
|
|
"for column in columns_to_convert:\n",
|
|
" data[column] = data[column].apply(lambda x: len(str(x)) if pd.notnull(x) else 0)\n",
|
|
"\n",
|
|
"# Map the target class to numerical values\n",
|
|
"target_mapping = {\n",
|
|
" 'benign': 0,\n",
|
|
" 'defacement': 1,\n",
|
|
" 'malware': 2,\n",
|
|
" 'phishing': 3\n",
|
|
"}\n",
|
|
"\n",
|
|
"data['target'] = data['target'].replace(target_mapping)\n",
|
|
"\n",
|
|
"# Display the first few rows to verify the changes\n",
|
|
"data.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 1000
|
|
},
|
|
"id": "W2p4MfwlRjJx",
|
|
"outputId": "a5250b75-757c-476b-fc7f-5e83926e2d95"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 1200x1000 with 2 Axes>"
|
|
],
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABCAAAAPQCAYAAADn2QryAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd1gUx//A8fcdIggKHKg06R0bChY09h5jjRp7jb2X2LvG3muisaJGY0HsvRujMQo2wG4sWIA7EJAm9/sDOTi4g9NvUJLfvJ7nHmVvZu+zs7tze7MzsxKlUqlEEARBEARBEARBEAQhH0m/dACCIAiCIAiCIAiCIPz3iQYIQRAEQRAEQRAEQRDynWiAEARBEARBEARBEAQh34kGCEEQBEEQBEEQBEEQ8p1ogBAEQRAEQRAEQRAEId+JBghBEARBEARBEARBEPKdaIAQBEEQBEEQBEEQBCHfiQYIQRAEQRAEQRAEQRDynWiAEARBEARBEARBEAQh34kGCEEQBEH4D9u4cSMSiYTHjx//Y+t8/PgxEomEjRs3/mPrFARBEAThv080QAiCIAjCR3rw4AF9+/bF2dkZQ0NDTExMqF69OkuXLuXdu3dfOrx/zLZt21iyZMmXDkNN9+7dKVq0qNb3JRIJgwYNytcYVq1aJRpfBEEQBOETFPrSAQiCIAjCv8nBgwdp27YtBgYGdO3alTJlypCcnMyFCxf44YcfuH37NmvWrPnSYf4jtm3bxq1btxg2bJjacgcHB969e4e+vv6XCewLW7VqFcWLF6d79+5fOhRBEARB+FcRDRCCIAiCoKNHjx7Rvn17HBwcOHXqFNbW1qr3Bg4cyP379zl48OD//DlKpZLExESKFCmS473ExEQKFy6MVPrlOjFKJBIMDQ2/2OcLgiAIgvDvJIZgCIIgCIKO5s2bR1xcHOvWrVNrfMjg6urK0KFDVX+npqYyY8YMXFxcMDAwwNHRkfHjx5OUlKSWz9HRkW+++YajR4/i5+dHkSJF+Pnnnzlz5gwSiYTt27czceJEbG1tMTIyIjY2FoDLly/TuHFjTE1NMTIyolatWly8eDHP7QgKCqJp06bY2NhgYGCAi4sLM2bM4P3796o0tWvX5uDBgzx58gSJRIJEIsHR0RHQPgfEqVOnqFGjBsbGxpiZmdGiRQtCQ0PV0kydOhWJRML9+/fp3r07ZmZmmJqa0qNHDxISEvKM/VMkJSUxZcoUXF1dMTAwwM7OjtGjR+fYDxs2bKBu3bqULFkSAwMDvL29Wb16tVoaR0dHbt++zdmzZ1XlUrt2bSBzvo0LFy4wZMgQSpQogZmZGX379iU5ORmFQkHXrl2RyWTIZDJGjx6NUqlUW/+CBQuoVq0aFhYWFClSBF9fX3bt2pVjmzKGmmzduhUPDw8MDQ3x9fXl3Llz/2zhCYIgCMI/SPSAEARBEAQd7d+/H2dnZ6pVq6ZT+u+//55NmzbRpk0bRo4cyeXLl5k9ezahoaEEBgaqpQ0PD6dDhw707duX3r174+HhoXpvxowZFC5cmFGjRpGUlEThwoU5deoUTZo0wdfXlylTpiCVSlU/oM+fP0/lypW1xrVx40aKFi3KiBEjKFq0KKdOnWLy5MnExsYyf/58ACZMmEBMTAzPnj1j8eLFALnOvXDixAmaNGmCs7MzU6dO5d27dyxfvpzq1atz7do1VeNFhnbt2uHk5MTs2bO5du0av/zyCyVLlmTu3Lk6lW1kZKRO6dLS0mjevDkXLlygT58+eHl5cfPmTRYvXszdu3fZu3evKu3q1aspXbo0zZs3p1ChQuzfv58BAwaQlpbGwIEDAViyZAmDBw+maNGiTJgwAQBLS0u1zxw8eDBWVlZMmzaNP/74gzVr1mBmZsbvv/+Ovb09s2bN4tChQ8yfP58yZcrQtWtXVd6lS5fSvHlzOnXqRHJyMtu3b6dt27YcOHCApk2bqn3O2bNn2bFjB0OGDMHAwIBVq1bRuHFjrly5QpkyZXQqH0EQBEH4rJSCIAiCIOQpJiZGCShbtGihU/rg4GAloPz+++/Vlo8aNUoJKE+dOqVa5uDgoASUR44cUUt7+vRpJaB0dnZWJiQkqJanpaUp3dzclI0aNVKmpaWplickJCidnJyUDRo0UC3bsGGDElA+evRILV12ffv2VRoZGSkTExNVy5o2bap0cHDIkfbRo0dKQLlhwwbVMh8fH2XJkiWVUVFRqmUhISFKqVSq7Nq1q2rZlClTlICyZ8+eauts1aqV0sLCIsdnZdetWzclkOtr4MCBqvQBAQFKqVSqPH/+vNp6fvrpJyWgvHjxYq7l0qhRI6Wzs7PastKlSytr1aqVI21GWWffL/7+/kqJRKLs16+fallqaqqyVKlSOdaTPYbk5GRlmTJllHXr1lVbnrGtV69eVS178uSJ0tDQUNmqVascsQmCIAhCQSCGYAiCIAiCDjKGPRQrVkyn9IcOHQJgxIgRastHjhwJkGOuCCcnJxo1aqRxXd26dVObDyI4OJh79+7RsWNHoqKiiIyMJDIykvj4eOrVq8e5c+dIS0vTGlvWdb19+5bIyEhq1KhBQkICYWFhOm1fVhEREQQHB9O9e3fMzc1Vy8uVK0eDBg1UZZFVv3791P6uUaMGUVFRqnLOjaGhIcePH9f4ym7nzp14eXnh6empKqfIyEjq1q0LwOnTp1Vps5ZLTEwMkZGR1KpVi4cPHxITE5N3QXzQq1cvJBKJ6u8qVaqgVCrp1auXapmenh5+fn48fPhQLW/WGORyOTExMdSoUYNr167l+Bx/f398fX1Vf9vb29OiRQuOHj2qNpxGEARBEAoKMQRDEARBEHRgYmICpP9g18WTJ0+QSqW4urqqLbeyssLMzIwnT56oLXdyctK6ruzv3bt3D0hvmNAmJiYGmUym8b3bt28zceJETp06leMH/8f80M6QsS1Zh41k8PLy4ujRo8THx2NsbKxabm9vr5YuI1a5XK4qa2309PSoX7++TrHdu3eP0NBQSpQoofH9169fq/5/8eJFpkyZwqVLl3LMRxETE4OpqalOn5l92zLy2dnZ5Vgul8vVlh04cICZM2cSHBysNkdF1gaNDG5ubjmWubu7k5CQwJs3b7CystIpXkEQBEH4XEQDhCAIgiDowMTEBBsbG27duvVR+TT9cNRE0xMvtL2X0bth/vz5+Pj4aMyjbb4GhUJBrVq1MDExYfr06bi4uGBoaMi1a9cYM2ZMrj0n/kl6enoalyuzTcr4v0pLS6Ns2bIsWrRI4/sZjQIPHjygXr16eHp6smjRIuzs7ChcuDCHDh1i8eLFH1Uu2rZN0/Ks23v+/HmaN29OzZo1WbVqFdbW1ujr67Nhwwa2bdum8+cLgiAIQkElGiAEQRAEQUfffPMNa9as4dKlS/j7++ea1sHBgbS0NO7du4eXl5dq+atXr1AoFDg4OHxyHC4uLkB6o4iuPQEynDlzhqioKPbs2UPNmjVVyx89epQjra6NJxnbEh4enuO9sLAwihcvrtb74XNycXEhJCSEevXq5bo9+/fvJykpiX379qn1YMg6RCODruXysXbv3o2hoSFHjx7FwMBAtXzDhg0a02f0hMnq7t27GBkZae3xIQiCIAhfkpgDQhAEQRB0NHr0aIyNjfn+++959epVjvcfPHjA0qVLAfj666+B9KcmZJVxJz77Ew0+hq+vLy4uLixYsIC4uLgc779580Zr3oy78FnvvCcnJ7Nq1aocaY2NjXUakmFtbY2Pjw+bNm1CoVColt+6dYtjx46pyuJLaNeuHc+fP2ft2rU53nv37h3x8fGA5nKJiYnR+OPf2NhYbTv/KXp6ekgkErX5Gx4/fqz2pI6sLl26pDY3xNOnTwkKCqJhw4Zae2EIgiAIwpckekAIgiAIgo5cXFzYtm0b3333HV5eXnTt2pUyZcqQnJzM77//zs6dO+nevTsA5cuXp1u3bqxZs0Y17OHKlSts2rSJli1bUqdOnU+OQyqV8ssvv9CkSRNKly5Njx49sLW15fnz55w+fRoTExP279+vMW+1atWQyWR069aNIUOGIJFICAgI0Dj0wdfXlx07djBixAgqVapE0aJFadasmcb1zp8/nyZNmuDv70+vXr1Uj+E0NTVl6tSpn7yt/6suXbrw22+/0a9fP06fPk316tV5//49YWFh/Pbbbxw9ehQ/Pz8aNmxI4cKFadasGX379iUuLo61a9dSsmRJIiIi1Nbp6+vL6tWrmTlzJq6urpQsWVI1qeX/omnTpixatIjGjRvTsWNHXr9+zcqVK3F1deXGjRs50pcpU4ZGjRqpPYYTYNq0af9zLIIgCIKQH0QDhCAIgiB8hObNm3Pjxg3mz59PUFAQq1evxsDAgHLlyrFw4UJ69+6tSvvLL7/g7OzMxo0bCQwMxMrKinHjxjFlypT/OY7atWtz6dIlZsyYwYoVK4iLi8PKyooqVarQt29frfksLCw4cOAAI0eOZOLEichkMjp37ky9evVyPIVjwIABBAcHs2HDBhYvXoyDg4PWBoj69etz5MgRpkyZwuTJk9HX16dWrVrMnTs31wk285tUKmXv3r0sXryYzZs3ExgYiJGREc7OzgwdOhR3d3cgfQLNXbt2MXHiREaNGoWVlRX9+/enRIkS9OzZU22dkydP5smTJ8ybN4+3b99Sq1atf6QBom7duqxbt445c+YwbNgwnJycmDt3Lo8fP9bYAFGrVi38/f2ZNm0af//9N97e3mzcuJFy5cr9z7EIgiAIQn6QKP/p2Z4EQRAEQRCEfCWRSBg4cCArVqz40qEIgiAIgs7EHBCCIAiCIAiCIAiCIOQ70QAhCIIgCIIgCIIgCEK+Ew0QgiAIgiAIgiAIgiDkO9EAIQiCIAiC8C+jVCrF/A+CIAiCmnPnztGsWTNsbGyQSCRaH+Oc1ZkzZ6hYsSIGBga4urqycePGfI1RNEAIgiAIgiAIgiAIwr9cfHw85cuXZ+XKlTqlf/ToEU2bNqVOnToEBwczbNgwvv/+e44ePZpvMYqnYAiCIAiCIAiCIAhCAZSUlERSUpLaMgMDAwwMDHLNJ5FICAwMpGXLllrTjBkzhoMHD3Lr1i3Vsvbt26NQKDhy5Mj/FLc2hfJlrYLwGRzU9/jSIeRgcfPKlw4hB3vJky8dQg7JeoZfOoQc3ksLZnUY/77olw4hh/cFsPOckfTdlw4hh9jUYl86hBzMCsV86RD+NaSS9186hBzSlHpfOoQczBJffukQclAYWn3pEDRKUep/6RBykEgK3n1IpVLypUPIoaiy4NWdKXq5//j8Ulycnb90CJ+kIP6uyPDnhA5MmzZNbdmUKVOYOnXq/7zuS5cuUb9+fbVljRo1YtiwYf/zurUpmFfcgiAIgiAIgiAIgvD/3Lhx4xgxYoTasrx6P+jq5cuXWFpaqi2ztLQkNjaWd+/eUaRIkX/kc7ISDRCCIAiCIAiCIAiCUADpMtzi36Tg9aMVBEEQBEEQBEEQBCFfWVlZ8erVK7Vlr169wsTEJF96P4BogBAEQRAEQRAEQRCE/3f8/f05efKk2rLjx4/j7++fb58pGiAEQRAEQRAEQRAE4V8uLi6O4OBggoODgfTHbAYHB/P3338D6fNJdO3aVZW+X79+PHz4kNGjRxMWFsaqVav47bffGD58eL7FKOaAEARBEARBEARBEP7fkugXvKevfIqrV69Sp04d1d8Zk1d269aNjRs3EhERoWqMAHBycuLgwYMMHz6cpUuXUqpUKX755RcaNWqUbzGKBghBEARBEARBEARB+JerXbs2SqX2x+tu3LhRY57r16/nY1TqxBAMQRAEQRAEQRAEQRDynegBIQiCIAiCIAiCIPy/JS303xiC8W8gekAIgiAIgiAIgiAIgpDvRAOEIAiCIAiCIAiCIAj5TjRACIIgCIIgCIIgCIKQ70QDhCAIgiAIgiAIgiAI+U40QPzH1a5dm2HDhn3RGM6cOYNEIkGhUHzROARBEARBEARBEIQvRzwFQ8h31apVIyIiAlNT03z9HPOv/HAe2QvTimUwtCnJ1W8H8Grfydzz1KyM94KxFPV2I/FpBPdnr+bZ5kC1NA79O+I8ohcGViWIvRHG7WEziPnz5kfFplQqCdy2hjPH95IQH4ebZzm69R+DlY291jxht69xOHALj++HoZBHMmTcPHyr1lZLs3bpNC6cOqi2rGyFqoyauizPmAIPHmFH4D6i5QpcnBwY0qcnXu5uWtOfuXCJ9Vu38/L1G0rZWNGnW2eq+lVUvV+neVuN+fp270z71i3yjAdg34GD7Nq9h2i5HGcnJwb064unh7vW9OfOX2DTli28evUaWxsbevXoTuVKfqr3A7Zu48y5c7x5E4l+oUK4urrSo2sXPD09dIong1KpZEtAAEeOHCE+Ph5vb28GDhqEra1trvn279/P7l27kMvlODk7079/fzw8Mj87OTmZtWvXcu7sWVJSUqjo68vAgQORyWQ6xbRj6zpOHt1PfHwcnl5l6T1gJNa2drnmO3JgD/v2/IpCHo2Dkws9+w7DzcNb9f7LiOdsXreSsDs3SE1Jwce3Cj37DsNMZq5TTDu3/sKpo/uJj3+Lh1c5eg0YlWtMobeC2b97G48ehCGPjmLkhNlU8q/5P683a95tWzZx7Mgh4uPj8PIuTf+BQ7GxLZVrvoP7gwjc/RtyeTROTi706T8Idw9P1fsrly8m5Po1oqOjMDQsgqe3N9179KaUnfZzOntcu7et4fSxIBLi43D3KkeP/qNzrxNuXedg4BYePQhDER3JsPHz8KtaSy3N7m1r+eP8caIjX6FXSB8nV0/adu6Hq0cZnWLaumUzR48cVpXVgIFD8jzOD+zfx57dOz+UlTN9+w/E40NZvX0by9YtAVy/9hdv3rzG1NSUqv7V6NylO8bGxv/KmPI6r7M7f/48AZs38+rVK2xsbenZoweVKldW28ZPqV+yKojltPvwCX7de4hoRQwujnYM/74L3m4uGtM+/PsZ67bvIfzBY16+iWRIj460a9ZYLU3w7TC2BR0i/MFjouQKZo0ZSs0qvjqWUKaCWFZKpZJft2zgxNGDH+rzMvQdODzPeurQgUD27t6BQh6No5ML3/cbgruHl+r9iWOHcftmiFqehk2a0X/QCB1j2sjxIx9i8i5Dv4HD8o5p/14Cs8TUu/9gtZgmjBmeI6ZGTZrRf/BwHWP658sJICz0Nls3r+NeeChSqRQnZ1cmz5iHgYFBrusOOnCInXsCP1xLOTKwb+9cr1vOXrjIpi3bePnqNbY21nzfvStVsly3bN76K2fOX+DNm0gKFSqEm6sLPbp2xiuXdWpSEK9bCjqJvrgv/7mIkhbyXeHChbGyskIiyd/H2+gZGxF7I5xbQ6bplL6IYykq7fuZqDOXueDXgkfLN1H255kUb/CVKo112yZ4zR/HvZkruVC5FW9vhFHl4DoKl8j7x1hWh/Zs5vjBHXTvP5bJ89djYFiEBVOHkJycpDVPUmIido5udOn7Q67rLlvRn6UbD6le/UfNzDOeU+cvsnrdJrq1b8uaxXNxcXRg9JQfkStiNKa/FRrOjAVL+LpBXdYumcdXVSozadY8Hj35W5Vm96Y1aq/RQwYgkUioWa1qnvEAnDl3njVrf6FTxw6sXLYEZycnJkyarLXnzO07ocyeN5/GDRuyatlSqvlXZdrMH3n8+Ikqja2tDQP79ePnlStYOH8uVpYlGTdpMooYzdupza6dO9m3bx+DBg9m8ZIlGBoaMmniRJKTk7XmOXv2LGvXrKFjp04sX74cZycnJk2cqLY9a37+mSuXLzNu/HjmzptHdFQUM2fmvf8AgnZv4/D+3fQZOIrZC3/GwLAIMyePzPWYunjuJJt+WUHbDt2Zu/QXHJxc+XHySGIUcgASE98xc9IIJBIJU2YtZcb8VaSmpjBn+ljS0tLyjGnf7q0c2b+L7wf+wMyFazEwNGT25BG5xpSY+A4HZ1d69Bv5j643w55dOziwL5D+g4Yyf/EKDAwNmTJpbK777vzZ06xb+xPtO3Zh8fKfcHR2ZsqksSg+lBOAi6sbQ4b/wMqf1zNt5hxQwuSJY3j//n2eMQEc2BPAsQO/0bP/GKbNX4eBgSFzpwzNvU5Ieoe9kxvdcqkTrG3t6dZ3FLOXb2Py3DUUL2nN3ClDiI2Ra82TYfeu39i/by8DBw1h4eJlGBoaMnnSuFzL6tzZM/yy9mc6dOzM0uWrcHJ2ZvKk8aqyioqKIjoqip7f92bl6jUMGz6Kv65eZemShXnGUxBj0uW8zurOnTvMnTOHho0asXzFCvz9/ZkxYwaPHz9WpfmU+qWgl9PJC3+wYsM2erRryboF03F1tGfE9PnIFbEa0yclJWNjWYJ+XdphYab5ZsW7pKT09fTuqkOJaFfQygogcNd2Du7fQ9+Bw5m7aBUGhoZMnzQ615gunDvFhrWr+a5jNxYuW4OjkwvTJ41Wq6cAGjRqyvqA3apXt559dY7pwL499Bs0nHmLV2JoaMi0SWNyj+nsadavXU37jl1ZtPxnHJ1dmDZpTM6YGjdlw5Zdqle3Xn10jik/yiks9DYzJo/Bp4If8xavYv6S1XzdrCVSae7XrWfOXeDnX9bTuUN7Vi9dhLOTI+MmT0Ou7bolNIxZ8xbSuEF9Vi9bRPWqVZj64xweZbluKWVrw6B+fVizcimL583G0rIkYydN/U9ctwhCBtEA8R8SHx9P165dKVq0KNbW1ixcqP7FJ5fL6dq1KzKZDCMjI5o0acK9e/dU72/cuBEzMzMOHDiAh4cHRkZGtGnThoSEBDZt2oSjoyMymYwhQ4aoXWQHBATg5+dHsWLFsLKyomPHjrx+/Vr1fvYhGBmfc/ToUby8vChatCiNGzcmIiLif9r+N0fPcXfKEl4FndApvUOf9rx79IzQ0XOJC3vIk1Vbebn7KE5Du6vSOA3rwdN1v/Fs0x7iQh9wc8AU3ickYtf9W53jUiqVHN2/nWZte1KxSi3sHd3oM2wqiuhIrv1xVmu+8r7VaNO5P37+dXJdv76+Pmay4qqXcVGTPGPaGXSApg3r0aR+HRzt7RgxoA+GBoU5fOKUxvS79x+kckUf2rdugYNdKXp2bo+bszOBB4+o0pjLZGqvi5f/xKdsaWysLPOMB2BP4F4aN25Eowb1cbC3Z8igARgYGnD02HGN6ffu24efb0Xaftsae3s7unXpjKuLC0EHDqjS1K1dm4oVfLC2tsLRwYE+vb8nISGBR48e6xQTpO+/vXv30r59e/z9/XFycmLkqFFERUVx6fffteYLDAykcZMmNGzYEHsHBwYNHoyBgQHHjh0D0s/XY8eO0bt3b3x8fHBzc2P4iBGE3rlDWGhonjEdDPqNb7/rSqWqNXBwcmXQiAnIo6P489J5rfkO7N1BvUbNqNOgKXb2TvQZOIrCBoacOp7eiyb8zk1ev37JwOHjcXB0wcHRhYHDJ/Dwfhi3blzLM6bDQb/R6rtu+H2IaeCIScijI7maS0wV/Pz5rksfKlerpfH9T11vRt59e/fQrn0nqvpXx8nJmeEjxxAdFcUfly5qzRcUuJuGjb+mfsPG2Ns7MGDQMAwMDDhxLPN4b9zkG8qULYelpRUurm506tqDyDdveP36Va4xZcR1ZN92WrTrgW/VWtg7udFveHqd8FcedULbzv2o5F9ba5pqtRpRxqcyJa1sKWXvTKdeQ3mXEM/fj+/nGVPQ3kC+a9+Rqv7VcHJyZsTI0URHRXEpl7LaG7ibRo2b0KBhI+ztHRg4aCgGBgYcP3YUAEdHJ8ZPnEyVKv5YW9tQ3qcCXbv14Mrly3k21hTEmPI6r7MLCgrC18+PNm3aYG9vT9euXXFxcWH//v2qbfyU+qWgl9P2/Udo1qA2TevVxMnOlh/6dsfQwIADpzQf315uzgzs1oH6X1VFX19fYxr/iuXp07ENtar6aXxfFwWxrJRKJQeCdtH2uy5U8f8KRycXho4cR3R0JJcvXdCab1/gTho0bkq9Bk2ws3ek36ARGBgacvLYYbV0BoaGyMzNVS8jI916ZOzfu5t27TtTxb/6h5jGEh2Ve0xBgTtp2Phr6jVMj6n/oOEYGBjkjMnA4JNiyq9y2rB2JU2bt+bbdh2xd3DCtpQ91WvUQV+/cK4x7d4bRJNGDWncoB4O9nYMHdgfAwMDjh7X3Ps2cN9+KvlWpN23rXCws6N7l064ujgTdOCQKk3d2rWo6FMeaysrHB3s6fd9TxISEnj4L79uEYSsRAPEf8gPP/zA2bNnCQoK4tixY5w5c4Zr1zJ/NHTv3p2rV6+yb98+Ll26hFKp5OuvvyYlJUWVJiEhgWXLlrF9+3aOHDnCmTNnaNWqFYcOHeLQoUMEBATw888/s2vXLlWelJQUZsyYQUhICHv37uXx48d0794911gTEhJYsGABAQEBnDt3jr///ptRo0b942WSG7OqPkSeuqS27M3xC8iq+gAg0dfHtGJpIk9mqayVSiJP/Y5Z1Qo6f86bVy+IkUdRunxml1sj46I4u5fmfvjHDeXQJOzWNQZ1bcSY/m3YuHoOcbGKXNOnpKRw9/5DfH3KqZZJpVIqli/H7bC7GvPcCbuLb/lyassqVSyvNX20XMEfV6/xdYO6Om1DSkoK9+7fp6JPebWYKvj4cCcsXGOe0LAwKvj4qC3zrViB0LAwrZ9x6PARjI2NcXZy1CkugJcvXyKXy/GpkLnPjY2N8fDwyPWz7t+7h0+W+KRSKT4+Pqov6Xv37pGamqq2Xjs7O0qULKl1vRlev4pAIY+mrE/mhbixcVFcPbwID7utNaaH9+9Sziezy7JUKqWcjx93P+RJSUlBgkTtB0DhwoWRSKSE3b6RR0wvUMij1GIyMi6Kq4c3d8Nu5Zo3v9b76mUEcnk05X0yhwoZGxfF3cOL8NA7GvOkpKRw//5dfLLkkUqllPepSFiY5jyJie84efwIllZWFC9eIs9tyqgTymSrE1zcS3PvH6gTMqSmpHD66F6MjIvi4KR9eBXAq5cvkcuj1bY7/Tj31HphmV5W9/DxyTyG04/zCoSFab8YjY+Px8jICD09vX9VTLqc19mFhYbmrKd8fVXpP6V+ya7glVMqdx88xq9cabV1+5Xz5nZ47g1h+a2glVV6TBn1VGbdbGxcFLc86vMH9++q5UmvzyvmyHPu9Am6dmjBkAE9CNi4lqTExFzjyRpTuWwx5VV3PtDwHVPex5fwbHXnudMn6dK+JUP69yRgw8fF9E+Xk0Ih5254KKamZowdOYjunVozYcxQ7tzOvS5Ov5Z6QMXs11I+5bVet9wJC1dLD+BXsQKhWtKnpKRw6MgxjI2NcHFyyjWerAridcu/gbSQpMC+/mvEHBD/EXFxcaxbt44tW7ZQr149ADZt2kSpUunj4u7du8e+ffu4ePEi1apVA2Dr1q3Y2dmxd+9e2rZNH7+fkpLC6tWrcXFJH6fZpk0bAgICePXqFUWLFsXb25s6depw+vRpvvvuOwB69uypisPZ2Zlly5ZRqVIl4uLiKFq0qMZ4U1JS+Omnn1SfM2jQIKZPn651+5KSkkhKUu+anKJMQ1/y6W1oBpbFSXoVqf45ryLRNy2G1NAAfZkp0kKFSHodlS1NFMYezjp/Tow8Pb+pmfqwDRMzc9V7n6psBX98q9ahhKUNr18+Y1fAahZMH8bkueuQarnoiYl9S1paGrJs3VxlZqb8/fy5xjzRCoWG9GbI5QqN6Y+eOotREUNq+lfRaTtiY2NJS0vDzEx9DKHMzIynT59pzCOXK5CZmeUZ0x9XrjB77nySkpIwN5cxe+b0j5qPRC5P76aZfXyjmUymek/b9mjK8/TZM9V6CxUqlOMckZmZIY+OzjUmxYfjJnt5mZmZo1Bozvs2Noa0tPc5jkNTMxnPn6V3/3Tz9MbA0JAtG36iY9c+KFGydeNPpKW9R57HsaqQR39YX/b1m6NQfPpx/r+sN2P/mGXfD2ZmyOWayyk2Nib9WMyRR8bzp0/Vlh06EMTG9WtJTEzEtpQd03+cp/Xurfo2pcdtorFOyH3f6+L6nxdYMX8iyUmJmMmKM2b6coqZmOWaJ6M8zGTq6czMZCjyOM41ldWzbGWVISYmhu2/bqVxk6/z3I6CFpMu53XObZDnjCVL3fEp9UvOzyhY5RTz9i3v09IwN1PvjWduZsqT5/9bT8f/VUErK8hSx2lYv0JLffD2Qz1lmuM7QMbzp5lDI2vWqkeJkpaYWxTn8aMHBGxYw/NnTxk7Ufv1VtaYsm+zqZlMa935VkvdaWom41nWmGrXo2RJS2TmFjx5/JDN69fw/LnuMf3T5fTqZfoxuX3bJrr36oeTsytnTh5jyviRLF21Xuv8EpnXUmZqy2VmprnUBwrMNKSPzjZE5Y8rf/LjvIXp1y0yGXNnTMPUNO/erZmfU/CuWwQhK9EA8R/x4MEDkpOTqVIl8wefubm5auKY0NBQChUqpPa+hYVFemtollZ/IyMjVaMAgKWlJY6OjmqVjaWlpdoQi7/++oupU6cSEhKCXC5XjRX/+++/8fbOnNwuq+yfY21trbbO7GbPns20aepzO3SQmNNJr7jWPF/K72eOsHH1bNXfIyYtzrfPqlqzoer/do6u2Dm68UPfVoTe+kutx8XndvjEKerXqkHhwrl3X/wcfMqVY9XypcTGxnL4yDF+nDOXZYsW5rgIyHD61CmWL1+u+jv7cfclnD99jJ9XLlD9PW7K3Hz5HFNTGSPHTmftqoUc3r8LiURK9Vr1cHJxzzGHy4XTR1m7cr7q7zFT5mdf3Wd35vRJVi3PPN8mT/sxXz+vVp16+FTwJTo6mr17djJv9gzmLlia47i/eOYI61fNUf09avKifI3Lq6wvPy4JIC5WweljQayYO56pC9arNeKcPn2SlcuXqv6eMi3/x/AmJMQzbcpE7O3t6dipS473C2JMBZEoJ90VxLI6e/o4P63IrAMmTJ2dI80/pWGTZqr/Ozg6IzO3YMr4kUREPMfaOnMywrOnT7B6eWZME6flX0yNmnyj+r+jkzMymTmTx4/SENPnKSflh2vWRk2+oV6DJgA4u7hxI+QaJ48fpkv33vnyubkpX64sPy1bTExsLIePHmPm3PksWzgvR2NHhoJ43SIIuRENEIKa7HfvJBKJxmUZjQzx8fE0atSIRo0asXXrVkqUKMHff/9No0aNcp3oRtM6lUql1vTjxo1jxAj1WZtPmX/87NdZJb2KxMBSvQHDwLI4KTFvSUtMIjlSTlpqKgYlLbKlsSDppXrPiawqVK6Bi0dm19OUlPRyiFFEY2ae+XmximjsnT5uVuO8lLSypZiJGa8jnmltgDA1KYZUKs0x4aRcEYO5li83czMzDekVyGQ509+4HcrT5y+YPDrvGa0zmJiYIJVKc0xUlf4ZmmdWlsnMckz0pCkmQ0NDbG1ssLWxwcvTkx69+3Dk2HHat9P81I4qVavi4Zn5tIOMIUpyuRxz88wfcAq5HOcsjWiatif7nQaFXI75h+2RyWSkpqbm6CkkVyiQmavfGfer8hWuWZ5UkfohJoVCjizLMaVQROOopat9MRNTpFI9YrL1kIhRyDGTZR7j5StWZsUvO4iNUaCnp4dx0WJ837kFllY2avl8q3yFq5bjPGtMMYroPLv/5ybj6Ru6rLdyFX+1J1Woykkux9w8cxsVCgXOztr2nWn6sZh93ynkmJmrH4vGxkUxNi6KjW0pPDy96NiuFZd+v0Ct2upDjypWroGLe2ZZpaamxxWbbZtiFdHYO396WWUwNCyClY0d2Njh6lmWkX2/5ezxfTRv212VpkoVf9UM/pB5nCvkimxlJcdJa1mZaC2r7MdwQkICkydNoIiRERMmTaVQoZyXHwUxJk3rzu28zk4my3lnXSGXq+q1jH8/pn4p6OVkWqwYelIp0dkmnIxWxGidYDK/FMSyqlylOu5Z6nNV3ZmjnpLj5OyqMaZiH+qpGIWGeiqXJxZlPPnh5Qv1H/uVq1RTeypERkzZ684YHWLKXk4xGspJLSbPjJheZIvp85ST7MO6Stk5qqUpZWdP5Bvtc/pkXksp1JbLFTG5Xrdkn7A2/dpLPX0RQ0NsbayxtbHG29ODbr37c+TYCTq0a6NxvQXxuuXfSKL/3xvqUFCJOSD+I1xcXNDX1+fy5cuqZXK5nLt308foe3l5kZqaqvZ+VFQU4eHhWnsp6CIsLIyoqCjmzJlDjRo18PT0zLUnw6cyMDDAxMRE7fW/DL8AUPwRjEVd9Sc0FK9XDfkfwQAoU1KIuXab4nX9MxNIJFjU8Ufxx3Wt6y1iZIyltZ3qZWvnjKnMgjs3/lSleZcQx8O7t3H1KPs/bUN20ZGviHsbg6lMe88QfX193F2duRaSOb4xLS2NazduUtpTc4OIt6c7126oj4f8K/iGxvSHjp/E3dUZ14+YZ0FfXx83V1euB2fOM5CWlkZwcAjeWh6Z6eXpSXCI+qO8rl0PxivLl7AmyjSl2rwn2RkZGWFjY6N62dvbI5PJCAkOVqVJiI8nPDxc62fp6+vj6uamlid9e4Lx9Eq/2HJzc6NQoUIEZ0nz7Nkz3rx+nWO9RYyMsLYppXqVsnfETGbOreC/MmNKiOd+eCgenqXRRF9fH2dXd26GZOZJS0vjZshfuGvIY2JqhnHRYtwM+YvYGDl+Vb5Se7+IkTFWNqVUr1L2TpjJLDTEdAd3z7wfAalNSUsbndebvu9sVS87ewdkMnNCQq6r5b0bHoqHl+Z6T19fH1dXd0JCMufPSUtL40bwdTw9c6srlShRqho9skovKzvVy9bOCVOZBbdDMuuEhIQ4Hty9jds/XCdA+oRk2Y/57GVl/6GsgrOVVXh4mOqYzS69rNwICQlWLUtLSyMkOBhPz8w8CQnxTJo4jkKFCjFp8jStPaMKYkw51p3HeZ2dp5eX2jkOcP36dVV6Kyurj65fCn45FcLdxZG/bmSOy09LS+OvG3co7aH5h2J+KYhllV6f26pedvaOyGTm3MhS5yQkxHMvj/rcxdWdG8Hq9dTN4Gta8wA8epg+B4fMXP3Giq4x5VV3uri6q+VJrzuv4ZFL3fnowYMPMan/gP1c5VTS0gpzi+K8eK4+nObF82eUKKl9Eu30aykXroeoX7dcD7mh9brF29ND7ToHMq5bcn80uFKZ9q+7bhGE3IgeEP8RRYsWpVevXvzwww9YWFhQsmRJJkyYgFSa/iPdzc2NFi1a0Lt3b37++WeKFSvG2LFjsbW1pUWLFp/8ufb29hQuXJjly5fTr18/bt26xYwZM/6pzfooesZGGLvaq/42ciqFSXlPkqNjSHwagcfMERjaWhLSYwwAT9Zsx2FAJzxn/8DTjbspXqcq1m2b8GfzzEdUPVqygfLr56L46xYxf97AcUg3ChkX4emmPTrHJZFIaNSsPft+W4+ltR0lLG3Ys+0nzMyLU7Fq5sz/cycNoGLV2jRo2g6AxHcJvIrIHEf45tULnjy8S9FiJliUsCLxXQJ7t/+CX7U6mJpZ8PrlM3ZsWkFJ61KUrZj7oy/btviGOUtW4u7qgpe7K7v2HSQxMYnG9dKfuDFr8XJKmJvTu1snAL5t1pRh46fwW+B+qlaqyKlzFwm//4CRA9Uf5xWfkMDZi3/Qv+fHPyatdauWLFi0GHc3Vzzc3QkMCiIxMZGGDeoDMG/hIopbWNCzezcAWjZvzg9jx7FrTyCVK/lx9tx57t2/z7DBg9LLLzGRbTt+w79KZczNzYmNiWXfwYNERkVR46vqOsclkUho2bIl27dvx8bWFktLSwICArCwsMD/w3wqAOPGjqVatWo0a94cgFatWrFo4ULc3Nxw9/AgaO9ekpKSaNCgAZA+IVTDhg1Zu3YtxYoVw8jIiJ9Wr8bLy0vrhXDWmJq2aMfuHZuwsi1FSUtrdmz5BZm5BZX8a6jSTRs/lMr+NWnSLP2pLd+0/I6Vi2fh4uaJq7sXB4N2kpT4jjr1M8cpnz5+EFs7R0xMzbgbdosNa5bRtEU7bEvZ54gje0xNWrQjUBWTDb9tWYvMvDh+WWKaMX4Ilfxr0rhZ+p2cxHcJvMxynL9+9YLHD+9StKgJxUta6bxebTE1b9ma37ZvxcbGFktLK7YGbMTcwoKq/pnHwMRxP1C1WnW+adYSgBatvmXJonm4unng7u7BvqA9JCYlUq9BYwBeRrzg/LkzVKjoh6mpKZGRkezeuR2DwoXxrZT30CeJRELj5u3Z+9sGLG3sKGlpw66tP2NmXhzfLHXCrIkD8atam4bftFWVlaY6wbiYCcVLWJGY+I6g3zbgW7kGZubFeRur4PjBXcij3lDlq3p5xtSiZSt2bN+G7Yey2vKhrPyzlNX4caPxr1adZs3SvzdatvqWxYvmpx/n7p4EfSir+g0aAR9+lE0YR1JSEqN+GMO7hATeJSQAYGJqmusEfQUxprzO6wULFmBhYUGPHj0AaNGiBWNGj2bP7t1UqlyZs2fPcu/ePQYPGaLaRl3ql3/bvmvfrDE/Ll+Lp6sTXm7O/Lb/GO+SkmhatyYAM5b+TAkLGf06p3/fpaSk8vhZ+hxEKampvImWc+/RE4oYGlLKOv1HYMK7RJ6/zLwjHfH6DfcePaFYUWOsSug2HLMglpVEIuGbFm3YuT0AaxtbLK2s2RawHnPz4lTxz2z4nTx+BFX9a/B1s1YANG/VlmWL5uDi5o6buxcHgnaRmJhZT0VEPOf8mZP4+lWhmIkpjx89YP3aVXiXKYejk+a74FljatbyW3Zu34KNjS0lLa3ZFrABcwv1mCaNG0nVal/R9ENMLVq1ZemiObi6eeDm7sn+oN1qdWdExHPOnT6Fb6UqFDMx4cmjB6xbs4rSOsaUH+UkkUho2fo7tm/diKOTC07Orpw+eZTnz/7mh/FTc43p25YtmLd46YfrFjcCg/aTmJhIo/rp9e3chUsobmFBr+7pQ3FaNW/GyLET2LlnL1Uq+XHm3Hnu3n/AsEEDAHiXmMi2HTvxr1IZC3MZMbGx7DtwmMioaGr+y69bBCEr0QDxHzJ//nzi4uJo1qwZxYoVY+TIkcRkeW7whg0bGDp0KN988w3JycnUrFmTQ4cO6TRpmjYlSpRg48aNjB8/nmXLllGxYkUWLFhA8w+V2edk6lsG/5MBqr+9F4wH4OnmPdzoNQ4D6xIUsbNWvf/u8TP+bN4X74XjcBzclcRnL7nZdyKRxzMf5xSx8zCFS5jjPmUIBlYliA0J5co335P8+uMm1fu6dVeSEhPZuGoWCfFxuHmVZ9SUpRQubKBK8/rlc7UnWDy6H8qcif1Vf/+6fgkAX9VtSu+hU5BKpTx9fI8Lpw+SEP8WmXkJSvtU4dtOffN8dFTdGtWJiYll47YdRMsVuDg7MnfqBMw/DF94/SYSaZYx/2W8PJg4cijrt/7KLwHbsLWxZsb40Tg5qP8oPXXuIkqlkro1df+izFC7Zg1iYmLYvGUrcrkcZ2dnfpw+TdWV8c2bN2oxlfb2YuwPo9gUsIWNmzZjY2vDlIkTcHR0ANJnb3729BkzTp4kNiaWYiYmuLu5sXDeHBwdHD4qtjZt25KYmMjyZcuIi4ujdOnSTJ8xQ+0OV0REBDGxmV2Oa9WqRWxMDAFbtiCPjsbZxYXpM2aodc3s07cvEqmUH2fOJCUlBV9fXwYMHKhTTC2+7Uhi4jt+Xj6fhPg4PL3LMmH6ArVj6tXLF7yNzawDqtesR2yMgh1b1qGQR+Po7MqE6QvUuuw+f/6UrZvWEBcXS8mSVrRu14VvWn6nU0zNv+1EUuI71i6fR0J8HB7e5Rg7fWG2mJ6rxfTgXhgzxg9W/R3wS/o41pr1mjBg+ESd16tN6zbfkZiYyMrli4mPi8O7dBmmTp+jtu9eRrwgNktdWaNWHWJiY9gWsPHDsejC1OmzVftOv3Bh7ty+xb6gPcTHxWFmJqN0mbLMXbgsx8Sg2nzTugtJie9Yv3I2CfFxuHuXZ/TUnHXC2yx1wsP7ocyaMED199Z1S9LjrduUvsMmI5VKiXj2hKWnDvE2VkFRE1OcXb2YOOdnStnnPXHut23apR/ny5eoymr69FnZyipCraxq1qpNTGwMWwI2q87b6dN/VJXV/fv3CQ9Pnx29d6/uap+3bsNmLC2t/lUx5XVev3n9Wq2e8vb2ZvSYMWzetImNGzdia2vLpEmTcHR0VKXRpX7JS0Erp3pfVUUR+5Zfft1DtCIGVyd7Fk76AfMPQzBeRUYhlWaWU6RcTo+Rk1R//xp0mF+DDuNT2pMVM9K/y8MePGLI5Mx5AJZv2AZAkzpfMWFwn39tWQG0atOexMR3rF6+kPj4OLy8yzJpxtyc9VSWuvOrmnWJjYlh+5aNyOXRODm7MHn6XFV9rl9In5Dgv9gftJukxHcUL1ES/+o1aNtetzk80mNKZNXyRcTHxeFVuiyT86g7v6pVh5hYBb8GbEAuTx/WMiVLTIUK6XMj+C8OBO0mURVTTdp16PwRMf2z5QTQrGUbkpOTWb92JXFv3+Lo5MKUmQvUhoRoUrvmVyhiYti05Vfkcjkuzk7Mmj5FNRT09Zs3SLIc56W9PBn3wwg2Bmxlw+Yt2NrYMHXCWJw+XLfoSaU8ffac4yfnEhsbSzGTYni4ubF47iwcHXK/CZBdQbxuEYQMEmVuA+8FoQA7qJ97l7UvweLmlS8dQg72kidfOoQckvUMv3QIObyXFsz22Pj3mp8k8yW9L4Cj94yk7750CDnEphb70iHkYFYoJu9EAgBSyfsvHUIOacrcH+n4JZglvvzSIeSgMMz9B/+XkqL89Bs++UUiKXg/A5TKgjcWv6iy4NWdKXp5N8J/CS7Ouj8priA5UeqfHwL5T6n/7J97RHdBUPCuIgVBEARBEARBEARB+M8pmLf8BEEQBEEQBEEQBOEzkBYqeD1v/qtEDwhBEARBEARBEARBEPKdaIAQBEEQBEEQBEEQBCHfiSEYgiAIgiAIgiAIwv9bEn0xBONzET0gBEEQBEEQBEEQBEHId6IBQhAEQRAEQRAEQRCEfCeGYAiCIAiCIAiCIAj/b4mnYHw+ogeEIAiCIAiCIAiCIAj5TjRACIIgCIIgCIIgCIKQ70QDhCAIgiAIgiAIgiAI+U40QAiCIAiCIAiCIAiCkO9EA4QgCIIgCIIgCIIgCPlOPAVD+NeyuHnlS4eQQ1TZyl86hBwK3/79S4eQQ3Hl6y8dQg5pSr0vHYJGUknalw4hByNJ/JcOIYc0Ct7+M9J796VDyCGtgN53sDuz9kuHkENEne5fOoQciqVEf+kQcogytP3SIeSgL0n+0iFoJC2A9ZShMuFLh5DDe2nB+3lS/GnIlw4hB7l16S8dgiB8koJ3hguCIAiCIAiCIAjCZyLRE4/h/FwK5q0QQRAEQRAEQRAEQRD+U0QDhCAIgiAIgiAIgiAI+U4MwRAEQRAEQRAEQRD+35KKIRifjegBIQiCIAiCIAiCIAhCvhMNEIIgCIIgCIIgCIIg5DsxBEMQBEEQBEEQBEH4f0siFUMwPhfRA0IQBEEQBEEQBEEQhHwnGiAEQRAEQRAEQRAEQch3ogFCEARBEARBEARBEIR8JxogBEEQBEEQBEEQBEHId6IBQhAEQRAEQRAEQRCEfCcaIP4FHB0dWbJkyUfnk0gk7N279x+P52NNnToVHx+fLx2GIAiCIAiCIAhCDhI9aYF9/deIx3AK+W7UqFEMHjz4s32eUqkkcNsazhzfS0J8HG6e5ejWfwxWNvZa84TdvsbhwC08vh+GQh7JkHHz8K1aWy3N2qXTuHDqoNqyshWqMmrqslzjMf/KD+eRvTCtWAZDm5Jc/XYAr/adzD1Pzcp4LxhLUW83Ep9GcH/2ap5tDlRL49C/I84jemFgVYLYG2HcHjaDmD9v5rrerJRKJbu2/sKpY/uIj3+Lh1c5eg74AWsbO615Qm9d58CebTx8EI4iOpIR42dTyb+WWporv5/hxOFAHj0IJ+5tLLOXbsTR2V2nmIIOHGLnnkCi5QpcnBwZ2Lc3nh7a8569cJFNW7bx8tVrbG2s+b57V6pU8lO9v3nrr5w5f4E3byIpVKgQbq4u9OjaGa9c1qnJ/v372bV7N3K5HGcnJ/r374+Hh4fW9OfPn2dzQACvXr3C1saGHj17UrlSJdX7SqWSgC1bOHLkCPHx8Xh7ezNo4EBsbW11jkmpVLJ9y3pOHD1AQnwcHl5l6TNwBDa2pXLNd/hAIEG7t6OQR+Po5EKvfkNx8/AC4PWrCPr3bK8x38ixU6lWo06eMW3ZEsDRI4eJj4/Hy9ubgQMH57ldB/bvY/fuXcjlcpycnOnXf4Ba+R4+fIizZ05z//4D3r1LYMdvuyhatGiu68wa09Ytmzh25DDx8XF4eZdmwMAheZbTwf1B7Nm9E7k8GicnF/r2H4i7h6fq/RXLlxBy/RrR0VEYGhbBy9ubbj2+x85Oez2TPa7tWzZw/MP+8/Qqo/P+26vaf65832+I2v7r17ODxnyjxk6lWo3aeca0bcsmjh05pCqr/gOH6lRWgbt/U5VVn/6D1Mpq5fLFamXl6e1N9x69KaVDWe24do9NV8KIik/EvaQZY+pXpIy1RZ75joT+zbj9l6jtasvi1l+plkfFJ7L0bAiXHr0kLimFinYlGF2vIg7mxfJcZwalUsmWgAC183fgoEF5Huf79+9n964Px7mzc456JDk5mbVr13Lu7FlSUlKo6OvLwIEDkclkecYUePAo2/fuJ1oeg4ujPUP79MDL3VVr+tMX/2D91t94+foNtjZW9Ovakap+FVTvJ7xLZM3mbVy4fJWYt2+xLlmSb79pTIsmDXQooUzpx9RGjn84pjy9y+h4TO1l74djytHJhT79B6sdU1nXP33yOK799SfjJk6jarWvNKxNXV77Ibvz588TsHkzr169wsbWlp49elCpcmW1GD7leMi+HflRThPGjODWzRC1PI2afMOAwcPzjGnfgYPs2r2H6A/fewP69c31+/jc+Qts2rKFV69eY2tjQ68e3an84fs4NTWVjZu38OfVq0S8fImxsTEVfMrTq3s3LCzyPp8zFMR9t+P0ZTYd+52omDjcS1kypsPXlHHSvN/2nL/KgUsh3H/xGgAvexsGt6qnlj4hMYlle05wOjiMmPgEbIrL6FC3Cm1rVdK4Tk32HjzMjj37PlxLOTC4by+83N20pj9z4Xc2bNnOy9dvKGVjTe/unanqV1EtzZOnz1izcQs3bt3h/fv3ONiVYuq4UViWLKFzXIKQ4b/XpCIUOEWLFv2oL5j/1aE9mzl+cAfd+49l8vz1GBgWYcHUISQnJ2nNk5SYiJ2jG136/pDrustW9GfpxkOqV/9RM/OMR8/YiNgb4dwaMk2n+Is4lqLSvp+JOnOZC34teLR8E2V/nknxBpkXVtZtm+A1fxz3Zq7kQuVWvL0RRpWD6yhcwlynzwDYv3sLRw7spNeAH5ix4BcMDA2ZM3l4nuVk7+RKz34jc0nzDg/v8nToNkDnWADOnLvAz7+sp3OH9qxeughnJ0fGTZ6GXKHQmP52aBiz5i2kcYP6rF62iOpVqzD1xzk8evxElaaUrQ2D+vVhzcqlLJ43G0vLkoydNBVFTIzOcZ09e5Y1a9fSqWNHli9fjpOzMxMnTUKhJa47d+4wZ+5cGjVsyIrly/H392fGjBk8fvxYlWbnrl3s27ePwYMGsWTxYgwNDZk4aRLJyck6x7V3168c2r+HvgNHMnvRTxgaGjJj0qhc99/Fc6fYuHYl7Tp2Y/6ytTg4uTBj0ihiFHIALIqX5JeAPWqv7zr1wLBIESr4Vckzpl27drJ/XxADBw1h0eIlGBoaMmnShFy369zZs6xdu5aOHTuzbPkKnJydmTRpglr5JiUlUdHXj3bffadz+WTYvWsHB/btZcCgoSxYvBxDQ0MmTxqXa0znz57hl7U/06FjZ5YsX42TszOTJ41D8aGcAFxd3Rg6fBSrfl7HtJmzUSqVTJ44lvfv3+sUV+CuXzm4fzf9Bo5gzqLVGBgWYcakH3LdfxfOnWLD2lW069idBcvW4ujkwvRJP6jisiheknUBu9Ve7VX7r7LW9WbYs2sHB/YF0n/QUOYvXoGBoSFTJo3No6xOs27tT7Tv2IXFy3/C0dmZKZPGqpWVi6sbQ4b/wMqf1zNt5hxQwuSJY/Isq6Ohf7PwdDB9q5dmW7eGuJcwY8BvZ4mOT8w134uYeBafDqZCKfULY6VSyfDACzxTxLOk9Vf82q0h1iZG9PvtDO+SU/Msnwy7du5k3759DBo8mMVLPhznEyfmWk5nz55l7Zo1dOzUieXLl+Ps5MSkiRPVjvM1P//MlcuXGTd+PHPnzSM6KoqZM/P+jjl1/ndWrg+g23dtWLtoNi5ODoyaOhu5QnM9dys0nBkLlvF1/TqsXTyHGlX8mDB7AQ+fPFWlWbl+M1euhTBh+EA2r1hIm+ZNWLpmAxcvX9W5nAD27NrOwX2B9B80jPmLV2BoaMhUHY6p9Wt/4ruOXVm0/CecnF2YOmmM2jGVYd/e3UgkEp3j0WU/ZHXnzh3mzplDw0aNWL5ihcb6/FOOh+zys5waNm7Kxi07Va/uvfrkGc+Zc+dZs/YXOnXswMplS3B2cmLCpMlay+n2nVBmz5tP44YNWbVsKdX8qzJt5o88/vB9nJSUxP0HD+jY4TtWLlvC5AnjePbsOVOm5318ZyiI++7on7dYuPMofb+pzbaJfXG3s2LA0gCiY+M0pr8a/pjGlcuydmR3No35HitzE/ovCeC1PFaVZuHOo/x++z4/9mrNnmmD6FSvKnN/PcSZ4DCdYjp9/iKrf9lE1w5t+XnJPFycHBkzeWYu9UEYM+cvoUnDeqxZOp/qVSsx+cd5PHrytyrN84iXDB0zEftStiyaNZW1yxfSuX0bChcurFNMgpCdaID4THbt2kXZsmUpUqQIFhYW1K9fn/j4eGrXrs2wYcPU0rZs2ZLu3burLXv79i0dOnTA2NgYW1tbVq5cqfb+vXv3qFmzJoaGhnh7e3P8+PEcMdy8eZO6deuqYujTpw9xcZmVZPfu3WnZsiWzZs3C0tISMzMzpk+fTmpqKj/88APm5uaUKlWKDRs2qK13zJgxuLu7Y2RkhLOzM5MmTSIlJUX1fvYhGBmfs2DBAqytrbGwsGDgwIFqeT6VUqnk6P7tNGvbk4pVamHv6EafYVNRREdy7Y+zWvOV961Gm8798fPP/Q6vvr4+ZrLiqpdxUZM8Y3pz9Bx3pyzhVdAJnbbBoU973j16RujoucSFPeTJqq283H0Up6HdVWmchvXg6brfeLZpD3GhD7g5YArvExKx6/6tTp+hVCo5vO83WrXrjl/Vmjg4uTJg+GTk0ZFc/eOc1nw+fv5816Vvjl4PWdWo24RvO/SkrI/urfUAu/cG0aRRQxo3qIeDvR1DB/bHwMCAo8c19xYJ3LefSr4VafdtKxzs7OjepROuLs4EHTikSlO3di0q+pTH2soKRwd7+n3fk4SEBB4+eqxzXIGBgTRp3JiGDRviYG/P4EGDMDAw4NixYxrTBwUF4efrS5s2bbC3t6dr1664uLiwf/9+IL3s9+7dS/v27fH398fJyYlRI0cSFRXF75cu6RSTUqnkQNBO2nzXhcr+X+Ho5MLgkeORR0dx5dIFrfn2B/5G/cbfULfB19jZO9J30EgMDA05eSy9zPT09JCZW6i9rlw6T7Wv6lCkiFGeMQXtDeS79h0+bJczI0f+QHRUFJcu/a41X2DgHho3bkyDhg2xt3dg0KDBGBoYcOzYUVWali1b0a7dd3h65rwDmldM+/YG0q59J6r6V8PJyZnhI8cQHRXFH5cuas23N3A3jRo3oX7DxtjbOzBg0FAMDAw4niWmxk2aUqZsOSwtrXB1daNz1x5EvnnD69evdIrrQNAutf03ZOQ4oqMj89h/O2nQuCn1GjT5sP9GYGBoyKlc9t/lS+epruP+27d3z4eyqq5zWQUF7qZh46+zlNUwDAwMOHHsSJay+kZVVi6ubnTSsay2XA2ndTlnWpR1xqW4KRMa+WGoX4i9Nx9pzfM+LY3xBy7R76sylDIzVnvvb3kcN19EMaGhL6WtLXC0MGF8Qz+SUt9zOPSJljXmLKfs5+/IUaOIiori0u+5HeeBNG7ShIYNG2Lv4MCgwYPV6pH4+HiOHTtG79698fHxwc3NjeEjRhB65w5hoaG5xvRb0EG+aViXr+vXxtG+FCP7f4+hQWEOnTijMf2u/YepXLE8HVo3w9HOll6dvsPd2YnAg5nH9+2wuzSqW5MKZUtjbVmS5o3q4+LkQOi9BzqVU0ZZ7d+7h7btO1PFvzqOTi4MGzmG6KhI/sjlOA8K3JXlmHKkv4ZjCuDhg/sE7dnJ4GG53zjIKq/9kCOWoCB8/fw+qj7X5XjIKr/LycDAAJm5ueplZGSsZY2Z9gTupXHjRjRqUB8He3uGDBqAgaEBR4/lvLYE2LtvH36+FWn7bWvs7e3o1qUzri4uBB04AICxsTFzfpxBrRo1sCtVCi9PTwb278u9+/d5/fq1TuVUEPfdluO/0/orX1pUr4CLTUkmdPoGw8L67L14XWP6Wd+3oV3tynjYWeNkXYLJXVugVCq5HPZQlSbkwVO+8S+Pn4cTNsVlfFvTD/dSltx+/FynmHbu3c/XjerTpH5dHO3tGD6gDwYGBhw+fkpj+j37DlG5og/tW7fAwa4UPTt3wM3Fib0HDqvSrA/YRmXfivTt0QU3F2dsra2oXqUSMjNTnWL6t5DqSQrs679GNEB8BhEREXTo0IGePXsSGhrKmTNnaN26NUqlUud1zJ8/n/Lly3P9+nXGjh3L0KFDVY0MaWlptG7dmsKFC3P58mV++uknxowZo5Y/Pj6eRo0aIZPJ+PPPP9m5cycnTpxg0KBBaulOnTrFixcvOHfuHIsWLWLKlCl88803yGQyLl++TL9+/ejbty/Pnj1T5SlWrBgbN27kzp07LF26lLVr17J48eJct+f06dM8ePCA06dPs2nTJjZu3MjGjRt1Lg9t3rx6QYw8itLlM+/2GRkXxdm9NPfDdR+eoE3YrWsM6tqIMf3bsHH1HOJiFf/zOrMzq+pD5Cn1H6Jvjl9AVtUHAIm+PqYVSxN5MssXpFJJ5KnfMataAV28fvUChTyKMj6ZwxWMjIvi4u7NvbBb//M2fKyUlBTu3n9ARZ9yqmVSqZSKPuW5ExauMc+dsHC19AB+FSsQqiV9SkoKh44cw9jYCBcnJ53junf/vloDmlQqxcfHh9AwzXcjQsPC8Kmgvh98fX1V6V++fIlcLqdClnUaGxvj4eGR5w+NDK9eRqCQR1POxzfLOori5uFFeNhtrdvy4P5dtTxSqZRyPr7c1ZLnwb1wHj28T72GTfOMKWO7fHwytz19uzy1bldKSgr3799Ty5NevhUIC9OtLHLz6uVL5PLoHDG5e3gSFnonl5juUt4ns/tpekwVCQ/TnCcx8R0njh/F0sqK4sXz7o6asf/K59h/3lo/I33/hWvcf9ryZO6/r3WKSS6PVttuY+OiuHt4EZ5HWflkK6vyPhUJy6WsTh4/kmdZpbx/T+hLOVUcLTPXLZFQxcGSGy8iteZb8/sdzI0MaVXOOcd7yR96XBTW01NbZ2E9KcHPta8zK9VxXiH7ce6htU5ISUnh/r17GuuRjHPj3r17pKamqq3Xzs6OEiVLal1v+rpTufvgEb7ly6qt27d8WW6H39WY53b4PbX0AJUqlFdLX9rTnYtX/uJNVDRKpZJrN27z9HkElSqUy746rT71mHqg4fwrn+38S0pMZOG8H+k7YAgyc916/umyH7ILCw1Vq6shvT7PSP8px0N2+VlOAGdPn6Rz+1YM7t+LzRt+ISkx9x5EGd97FX3Kq627go+P1u/j0LCwnOVUsUKuZRAfn4BEIsFYh+F0BXHfpaSmEvp3BFW8MusaqVRKFS9nbjx8mkvOTInJKaS+f4+pcRHVsvIudpwNCee1PBalUsmfYY948iqKqt4ueceUksLd+w/xLa9+LeXrU5Y74dqupe7muJaqVMGH22Hp9UFaWhp/XL2Gna01oyfPoHXnngwYOZYLl67otI2CoImYA+IziIiIIDU1ldatW+Pg4ABA2bJl88ilrnr16owdOxYAd3d3Ll68yOLFi2nQoAEnTpwgLCyMo0ePYmNjA8CsWbNo0qSJKv+2bdtITExk8+bNGBunt36vWLGCZs2aMXfuXCwt0y/yzM3NWbZsGVKpFA8PD+bNm0dCQgLjx48HYNy4ccyZM4cLFy7Qvn36WPGJEyeqPsfR0ZFRo0axfft2Ro8erXV7ZDIZK1asQE9PD09PT5o2bcrJkyfp3bu3xvRJSUkkJal3TU5OTqJwYQO1ZTHyKABMzdQvSEzMzFXvfaqyFfzxrVqHEpY2vH75jF0Bq1kwfRiT565DmuWC9n9lYFmcpFfqF8NJryLRNy2G1NAAfZkp0kKFSHodlS1NFMYeOS+6NYmRRwM5y8nUzBzFh/c+p5jYt6SlpSEzM1NbLjMz5WmWxq6s5HIFZhrSR2frfvrHlT/5cd5CkpKSMJfJmDtjGqamefdcAYiNjU2PK9sYbJmZGc+ear7AkMvlGrbDDLlcrnof0LjOjPfykrGPzGTZ959M6/57GxtDWtp7zMxkOfI8f/q3xjwnjx2klJ0Dnt5l8owpc7vM1Jab5bJdGeVrpiHPUy3l+zHkqnJS32YzM1kuMcVo3OdmZrIc+/zggX1sXL+WxMREbEvZMePHuejr6+cZV8Y+Ms22/9Ljym3/pWFmljOPtv134tihj95/OcvKTGtMGWWlqXyfZyurQweC1Mpq+o/zci0reUIy75VKzI0M1ZZbGBvyODpWY57rz96w98ZDtndvpPF9R3MTrEyMWH7uBhMb+VFEX48tV+/y6u07IuNy/1GmikvL+Wsmy+2Y0lyPmMlkqvpNLpdTqFChHHObyMzMkEdrr5NjYmN5n5aW406kzMyUv59pvmMarVBoTB8tz+yiPbRPDxasXEubngPQ09NDKpEwamAfypf20hpLdtqPqbzPP015sp5/69auwtOrNFX8q+scjy77QdM25Igly77+lONB02dk5FFbxz9QTjVr16VESUvMzS14/Pghm9ev5fnzp4ybqH1IqKpeNsv5HfX0qfbvY83fewqN6ZOTk1m3YSO1a9XE2Cj33llZYypI+04el8D7tDTMTdTPWYtiRXkcoVuD5tLdxylhWkytEWNM+6+ZsWUfjcYspJBUikQqYVKX5vi6O+a5PtW1lCz7+W2WR31gli29qWr4qyImhnfvEvl11156dG5Pn+6dufJXMFNmz2fRj1MpX7a0TtsqCFmJBojPoHz58tSrV4+yZcvSqFEjGjZsSJs2bXSaWCqDv79/jr8znowRGhqKnZ2dqvFBU/rQ0FDKly+vanyA9EaNtLQ0wsPDVQ0QpUuXRirN7BhjaWlJmTKZF696enpYWFiodZnbsWMHy5Yt48GDB8TFxZGamoqJSe4/8EqXLo1elh/t1tbW3LypvYfC7NmzmTZN/Quz18AxeJepwMbVs1XLRkzKvefF/6JqzYaq/9s5umLn6MYPfVsReusvtR4XBdGFM0f5ZeU81d+jJy/4gtF8XuXLleWnZYuJiY3l8NFjzJw7n2UL5+X4wi3Izp0+zs8rFqr+Hj91Tr5/ZlJSEufPnqRt+64a3z99+hQrlmdOwDp12vR8jykvZ06fZOXyJaq/J0/TfXzxp6hdpx4VKlQkOjqawD07mTt7JvMWLMkxLvZstv034bPtvxNa99+Z0ydZtTyzvpw87cd8jadWnXr4VPAlOjqavXt2Mm/2DOYuWPqPjSGOT0ph4sHLTGpcCZmRgcY0+npSFraszrQjf1JrWSB6EglVHC2p7myttUfi6VOnWL58uerv7N9D/1V7DhzhTvg9Zk34AauSxQm5HcqSn9dT3FyGn4/mGyhnTp9gdZZjatK0WfkS2+U/fudGSDCLl/+cL+vPb5+rnCB9wskMjk7OmMssmDR+FBERL7C2tsklZ/5JTU3lx9lzASWDB37cXFH/JesPn+fon7dYO6o7BlkaY7efvszNh89YMrAj1hamXLv7hDnbDlLCtJhOvSD+aWlp6XVjtSqVaNuyGQCuzk7cDgtn35Fj/6kGCIn0vzfUoaASDRCfgZ6eHsePH+f333/n2LFjLF++nAkTJnD58mWkUmmOC59/Yi6ET5X9jpREItG4LC0tDYBLly7RqVMnpk2bRqNGjTA1NWX79u0sXLiQ3OS2Tk3GjRvHiBEj1JYFP07kfWoqLh6ZlV9KSvrEQTGKaMzMi6uWxyqisXf6uCcf5KWklS3FTMx4HfHsH22ASHoViYFlcbVlBpbFSYl5S1piEsmRctJSUzEoaZEtjQVJLzW3uvtW/gpXd83lJMtSTjGKaBydtc+UnF9MTYohlUpzTDgpV8RobaiTycxyTD4lV8Rgnu2uTRFDQ2xtrLG1scbb04Nuvftz5NgJOrRrk2dcJiYm6XFluxsiVyi0dvuVyWQatkOh2o6Mf+VyOeZZ1iFXKHBx1tyDpVKV6qonHUBmHaGQRyMzzzwOYhRyHJ01z3xfzMQUqVQvxwRlMQp5jp4UAJcuniE5KZFa9TTfTa5SpSoeWWZbzzim5HIF5lliUigUOGvZrozyVWS7S6ZQKJCZ695Am6FyFX+1GeAzy0meLSY5zs6aL+RMTEw17nOFQp4jJmNjY4yNjbGxLYWHpxcd2rXm0u8XqFW7bra4quOuYf/FyKNzxOWU6/6TolCo3w1XaN1/Z0lOSqK2lv2XvaxStZaVIs+yUmgoK7McZVUUY+OiqrLq2K6VxrLKIDMqjJ5EQnSCes+EqPhELIwNc6R/pojjRUw8w3afVy1L+/Dd6jf/NwK//xo7WVG8rczZ0b0Rb5OSSXmfhrmRIV0CjuNtpfl8rlK1Kh6eOY+p7OevQi7H2UVbOWmuRxRyOeZZ6oXU1FTi4uLUekHkVtcAmJqYoCeV5phgTq6IwTxbz6IM5mZmWtKn3zVNSkpm7ZbtzBw3Ev8PM+G7ODpw/+ETduw9oLUBonKVanhorKdynn9On3BMZZTDzZDrvIx4Qce2zdXSzJ01De/SZflx7iIt6857P2Qnk8lyxiKX51mf53Y8fK5y0sT9w7Ec8eK51gYIVb2s0PC9l8v3sebvPTO1Zampqfw4Zy6v3rxm3qwfder9kDWmL73v1NZf1Ag9qTTHhJNRb+OwMM19WMnmYxfZcOQCPw3vinspK9XyxOQUlgeeZFH/9tQol37N6l7KivBnLwk4/nueDRCqayl59vNbkUd9oMiWPkZ1k8bUpBh6eno42Ks/2cPBzpabd3QbZiQI2Yk5ID4TiURC9erVmTZtGtevX6dw4cIEBgZSokQJIiIiVOnev3/PrVs5x+D/8ccfOf728kr/AvPy8uLp06dq68me3svLi5CQEOLj41XLLl68qBpq8al+//13HBwcmDBhAn5+fri5ufHkiW6TeX0MAwMDTExM1F6FCxtQxMgYS2s71cvWzhlTmQV3bvypyvsuIY6Hd2/j6vFxw17yEh35iri3MZjKiued+CMo/gjGom5VtWXF61VD/kcwAMqUFGKu3aZ43Sy9XCQSLOr4o/hD88RHRYyMsbIppXqVsnfCTGbBrZDMGc0TEuJ5cPcObp55d9f+p+nr6+Pu6sL1kBuqZWlpaVwPuYG3p+bj09vTg+vBN9SWXbsejJeW9BmUyjSdG/n09fVxc3UlOCTzMWZpaWkEBwfjpWVCRC9PT4KDg9WWXb9+XZXeysoKmUymts74hATCw8Px9NLcvbmIkRHWNqVULzt7R8xk5twMuaZKk5AQz73wUDw8Nd+N0NfXx8XVnZvBf6lty43ga7hryHPq2CH8qlTH1NRM4/qMjIywsbFRveztHZDJZISEZG57QkI84eFhWrdLX18fV1c3grPkyShfT0/du3qrx2SreqXHZE5ISOZ5kZAQz93wMDy9vHOJyZ0bWfKkpaUREnwdD0/NedIpUaLUeGxp2383cuy/O1o/I33/eXAjODNP+v77S2Oek8cO4lelWh77L7Os7LSWVSgeeZRVSEj2mK7jqUNZpeZyHurr6eFlJePyk8yJKtOUSq48eUU5m5x1rqOFCTt7NGJ794aqVy1XWyrZl2R794ZYmRRRS1/MoDDmRoY8iX7LnZdyartqfuxezuPcPv04z3KOJ8THEx4errVO0NfXx9XNTS2P6jj/cG64ublRqFAhtbrj2bNnvHn9Wut609ddCHcXJ/66kXndkJaWxrUbtyit5ZGJpT3c1NIDXA2+oUqf+j6V1NT3OZ4uIdWTkqbUfqPAyMgIaxtb1SvjmMp+nOd1TLloOP9uZDn/vm3bgaUr17JkxRrVC6Bn7/4MGa59Qkpd9kN2nl5eGuvzjPQZ9fnHHA+fq5w0efQgfRJR81waKTK+97J+v6aXU4jW72MvT0+17zTI+D7O0sj5ofHh+YsXzPlxZp49ZbPHVBD2nVpMhQrhZW+tNoFkWloaV0IfUc5Z++PMNx65wNoDZ1k5tDOlHdXrndT370l9n/Pc05NIVD0Rco1JXx93V2eu3cjsUZyWlsa1kJt4a7nW9/Z051qIeg/kq8EhlPZ0V63Tw82Fp89eqKV5+jwCyxLiEZzCpxE9ID6Dy5cvc/LkSRo2bEjJkiW5fPkyb968wcvLC2NjY0aMGMHBgwdxcXFh0aJFGh8pdPHiRebNm0fLli05fvw4O3fu5ODBgwDUr18fd3d3unXrxvz584mNjWXChAlq+Tt16sSUKVPo1q0bU6dO5c2bNwwePJguXbqohl98Cjc3N/7++2+2b99OpUqVOHjwIIGBgZ+8vv+VRCKhUbP27PttPZbWdpSwtGHPtp8wMy9OxaqZT26YO2kAFavWpkHTdgAkvkvgVUTmOMI3r17w5OFdihYzwaKEFYnvEti7/Rf8qtXB1MyC1y+fsWPTCkpal6Jsxao54shKz9gIY9fM590bOZXCpLwnydExJD6NwGPmCAxtLQnpkT5x6JM123EY0AnP2T/wdONuitepinXbJvzZvK9qHY+WbKD8+rko/rpFzJ83cBzSjULGRXi6aY/O5dSkeTv27tiElY0dJS1t2LllDTLz4vhVralKN3PCYCr516LRN21U5fRSrZwiePzwLkWLmlC8ZHorftzbWCLfvEQend4bI+J5+vh0M5kFZjLtj2P9tmUL5i1eirubKx7ubgQG7ScxMZFG9esBMHfhEopbWNCrexcAWjVvxsixE9i5Zy9VKvlx5tx57t5/wLBB6V063yUmsm3HTvyrVMbCXEZMbCz7DhwmMiqaml/pPm64VatWLFy0CDc3Nzzc3dkbFERSUhINGjQAYMGCBVhYWNCjRw8AWrRowegxY9i9Zw+VK1Xi7Nmz3Lt3jyGDB6vKvmXLlmzfvh1bGxssLS0JCAjAwsKCatmGTmkjkUj4pkVbdm3fjLVNKUpaWfFrwHpk5hZU9s98XOvU8cOp7F+Dr5u1BqBZq3YsXzQbFzdP3Nw9ORC0i6TEd9Rt0ERt/REvnnHnVggTps7VuZwkEgktWrZi+/ZfsbGxwcrSioCAzZhbWODvX02Vbvy4sfhXq0azZs0/lG9rFi1agJubG+7uHgQFBZKYlEiDBplDnqKjo5HL5US8SL8Aevz4MUWKFKFkyZIUK1Ys15iat2zFju3bsLGxxdLSmi0BGzG3sKBqlrHjE8b9gH+16nzTrCUALVt9y+JF83B1c1eLqX6D9N4ELyMiOH/uDBUq+mJiakZU5Bt27dyOQeHC+FXKuzdU+v5rw67tAVjblMLSyppfA9Zhbl5cbf9NGT+CKv5fZdl/bVm+aDaubh64uXuxP2gXSYmJWvbfjY8a6pFeVq35bfvWD2VlxVYNZTVx3A9UzVJWLVp9y5JF83B188Dd3YN9QXtITEqkXoPGH8rqxYey8sPU1JTIyEh2fygr3zzKqrOfB5MPXcbbypwy1hZsuxrOu5RUWpRNn0R24sE/KFnUiCG1ymFQSA/XEmZq+YsZpve0y7r8eNhTZEYGWJkYce9NDPNPXqO2my3+TlboIuv5a2Nrq3b++lfLPM7HjR1LtWrVaNY84zhvxaKFC9OPcw8PgvbuVatHjI2NadiwIWvXrqVYsWIYGRnx0+rVeHl5af2BlaFdi6bMXroaT1dnPN1c2bX/EO8Sk2hSP/0778fFKylhYU6frh0AaNOsCUMmTGfH3gNU9avAqfO/E/7gIaMGpj+e0djICJ8yXvy0cSsGhQtjVbIEwbfucPT0OQb27KJTOWWUVbMPx5S1TSksLa3YFrABc4viVM1ynE8aN4qq1b6iqeqYasPSRXNxdXPHzd2T/UG71c6/jKc5ZFeiREksraxzjSmv/aCpPh8zejR7du+mUuXKqvp88JAhqm3U5Xj4EuUUEfGCc6dP4lupCsVMTHj86CHr16yidJlyODrlfie9dauWLFi0+MP3sTuBQUEkJibSsEF9AOYtXERxCwt6du8GQMvmzflh7Dh27QmkciU/zp47z7379xk2OH2i89TUVGbMmsP9Bw+YPmUyae/TiI5O751QrFhRnebOKYj7rnODakzeEIi3gy1lnGzZduIS75KTaVE9fWLLiev3UNKsGENap8e44ch5Vu87zaxebbCxMCMy5i0ARgaFMTI0oGgRQ3zdHVmy+xiGhQthbWHGX3cfc+CPEEa01dybLbu2LZsxZ/EKPFxd8HR3ZXfQQRITk2hcP/0pb7MXLaO4hQW9u3UCoHXzrxk+bgq/Be6jqp8vp85f4O79h4wc1E+1zu9at2DGvMWUK+NFhbJluHItmEtXrrJ41v+PIWnCP080QHwGJiYmnDt3jiVLlhAbG4uDgwMLFy6kSZMmpKSkEBISQteuXSlUqBDDhw+nTp2cj4IcOXIkV69eZdq0aZiYmLBo0SIaNUqvjKRSKYGBgfTq1YvKlSvj6OjIsmXLaNy4sSq/kZERR48eZejQoVSqVAkjIyO+/fZbFi3S3FVRV82bN2f48OEMGjSIpKQkmjZtyqRJk5g6der/tN7/xdetu5KUmMjGVbNIiI/Dzas8o6YsVZuw8vXL52pPsHh0P5Q5E/ur/v51/RIAvqrblN5DpyCVSnn6+B4XTh8kIf4tMvMSlPapwred+qKvn/sYZlPfMvifDFD97b0gfULPp5v3cKPXOAysS1DELvOi6d3jZ/zZvC/eC8fhOLgric9ecrPvRCKPZz6OK2LnYQqXMMd9yhAMrEoQGxLKlW++J/m17hNtNvu2M0mJifyyYi4J8XF4eJdj7LRFauX06uVz3mYpp4f3w5gxPvPJKQHr0ucAqFn3a/oPT5+M9K/L5/lpaeZ48mXzJgPwbYeetOn4vdZ4atf8CkVMDJu2/IpcLsfF2YlZ06eounC+fvNGbXxeaS9Pxv0wgo0BW9mweQu2NjZMnTAWJ8f0iV71pFKePnvO8ZNziY2NpZhJMTzc3Fg8dxaODvaaQtCoVq1axMTGsiUggGi5HBdnZ2ZMn67qvpkeV2ZnMm9vb8aMHs2mzZvZuHEjtra2TJo0CUdHR1Watm3akJiYyLLly4mLi6N06dLMmD79o8bDt2zTgcTEd/y0fAHx8XF4epdl0oz5avvvZcQL3sZmdsWsXrMuMTEKtm9Zj0IejZOzKxOnz8/Rhf/U8UNYFC9B+Yof9yjVNm3akpiYyPLly4iPi8O7dGlmTJ+ptl0RES+IjcmMqWatWsTExrAlIAC5XI6zszPTp89U6+p7+NBBtm3bqvp7zOhRAAwbPkKtoUKTb9t8R2JiIiuWL/kQUxmmTZ+tFtPLiAhiYzInNqxRqzYxsQq2Bmz6EJML06bPUsWkX1if27dvsi9oD3FxcZiZyShdpizzFi7NMXGbNq3adCApMVG1/7y8yzJpxrxs++85sVn231c16xIbo+DXLRtU+2/S9Hk59t/J44exKF4Cn4/cf60/lNXK5YtVZTV1+pxsZaW+/2rUqkNMbAzbAjaqymrq9NlZyqowd27fYl/QHuKzlNXchcvyLKtGXvbI3yWx+sItouIT8Shpxsq2tVRDMF7GJiDNdqcwL2/i37Hw9HWi4pMoXtSQb0o70qdabr01cmrT9sNxvmyZ6vydPmNGtuM8gpjYzGOqVq1axMbEELBlC/LoaJxdXJg+Y4bacd6nb18kUik/zpxJSkoKvr6+DBg4MM946taohiI2lvXbdhItV+Dq5MD8KWMx/9CF+nVkJNIsdWcZLw8mjRzMui07WBuwnVI2Vvw4bhTODpl3bSePGsqazb8yc9EKYuPisCpRgu87t6dF4wYfVVat27QnMTGRVcsXER8Xh1fpskzJcf7lPKZisxxTTs4uTJk+R+NQo4+V13548/q12jHl7e3N6DFj2PzhaV2a6nNdjoe85Ec5FSpUiJDga+kNE4mJFC9REv/qNWjXoXOe8dSuWYOYmBg2b9mqqpd/nD4ts5zevFErp9LeXoz9YRSbArawcdNmbGxtmDJxAo4fvo8jo6L44/JlAAYMHqL2WfNmz6J8ubx7qBbEfdeoUhnkb+NZve8UUbFxeJSyYuWQLlh8mJjyZXSMWkw7z14lJfU9P/y8Q209fb+pTb/m6df+c3q3YXngCcav201s/Duszc0Y2LIebWvpVp/XqVEdRUwsG7ZuRy5X4OLsyNxpE1RDMF6/iUQqybxmKePlyYRRQ1m/ZTvrNm/D1saa6RNG45TlOqmGfxWGD+jNtp2BrFizATtbG6aNG0XZj5iUVhCykig/5lmQglCA/BEWk3eizyyqbMGbjNL6tm7Ps/6cikt0e+7355Qq/Wcmw/unJSjzfmb752YoefelQ8ghjX/uSTT/lBRl3nf1PrdCktQvHYJGdmfWfukQcoio0/1Lh5CDcXLB+95T6Be8btj6kuQvHYJGKcqC9z1jqEz40iHk8F5a8O6PWj8teI+dlFsXzAkgbd3/2SHPn8tl/ypfOgStqly6/KVD+EcVvDNcEARBEARBEARBED4TqZ54CsbnIiahFARBEARBEARBEAQh34kGCEEQBEEQBEEQBEEQ8p0YgiEIgiAIgiAIgiD8vyURQzA+G9EDQhAEQRAEQRAEQRCEfCcaIARBEARBEARBEARByHdiCIYgCIIgCIIgCILw/5ZEKu7Lfy6ipAVBEARBEARBEARByHeiAUIQBEEQBEEQBEEQhHwnGiAEQRAEQRAEQRAEQch3ogFCEARBEARBEARBEIR8JxogBEEQBEEQBEEQBEHId+IpGIIgCIIgCIIgCML/WxKp5EuH8P+GaIAQ/rXsJU++dAg5FL79+5cOIYeI0tW+dAg5FcByMpXEfOkQNCqmLHhxFXqf/KVDyCFJz+hLh5BDifhHXzqEHOKMSnzpEDR6U6vTlw7hX0FJwbtAPh5m+6VDyOFrr4J37gGYpkR+6RByiCpk9aVDyME1dO+XDiGHBx4tvnQIOciTTb50CBoVvBpBKGjEEAxBEARBEARBEARBEPKd6AEhCIIgCIIgCIIg/L8l1St4Pcz+q0QPCEEQBEEQBEEQBEEQ8p1ogBAEQRAEQRAEQRAEId+JBghBEARBEARBEARBEPKdaIAQBEEQBEEQBEEQBCHfiQYIQRAEQRAEQRAEQRDynXgKhiAIgiAIgiAIgvD/lkQqnoLxuYgeEIIgCIIgCIIgCIIg5DvRACEIgiAIgiAIgiAIQr4TQzAEQRAEQRAEQRCE/7ckUnFf/nMRJS0IgiAIgiAIgiAIQr4TDRCCIAiCIAiCIAiCIOQ70QChA0dHR5YsWfJZP7N27doMGzbsk/N/iZg12bhxI2ZmZl86DEEQBEEQBEEQBI0kUkmBff3X/OvmgKhduzY+Pj4F4se1kLfvvvuOr7/++rN+ZuDBI+wI3Ee0XIGLkwND+vTEy91Na/ozFy6xfut2Xr5+QykbK/p060xVv4qq9+s0b6sxX9/unWnfuoVOMSmVSnZt/YVTx/YRH/8WD69y9BzwA9Y2dlrzhN66zoE923j4IBxFdCQjxs+mkn8ttTRXfj/DicOBPHoQTtzbWGYv3Yijs3ue8Zh/5YfzyF6YViyDoU1Jrn47gFf7Tuaep2ZlvBeMpai3G4lPI7g/ezXPNgeqpXHo3xHnEb0wsCpB7I0wbg+bQcyfN/OMJ6v8KKvU1FR+2/IzwVcv8frlC4oYF6VseT/ad+uPuUUJnWLaEhDAkSNHiI+Px9vbm4GDBmFra5trvv3797N71y7kcjlOzs70798fDw8P1fvJycmsXbuWc2fPkpKSQkVfXwYOHIhMJsszpn0HDrJzdyDRcjnOTk4M7NcHTw/t+/7c+Qts3LKVV69eY2tjw/c9ulG5kp/q/c1bt3Hm3HnevIlEv1Ah3Fxd6d61M16eHlrXmd3eg4fZsSfz3Bvct1ce597vbNiSce5Z07u7+rkH8OTpM9Zs3MKNW3d4//49DnalmDpuFJYl895vkL4Pdu3ejfxDOWXfB9mdP3+ezQEBvHr1ClsbG3r07EnlSpVU71+8eJGDhw5x//593r59y4rly3FxcdEplgy7jpxmy/5jRCticHUoxcieHSjt6qQx7cOnL1izI4iwR3/z8k0Uw7q1o33T+jnSvY6Ws3LLHi4F3yIpKZlSViWYOKA7Xi6OOscVdOAQv+3Z+2H/OTKo7/e5HlNnL1xk45ZfefnqNbY21vTu3pUqlXxV789bvIxjJ0+r5fGrWIE50yfrHFNBPM7zOq+zO3/+PAGbN/Pq1StsbG3p2aMHlSpXVr3/qfVLVoEHj7J9736i5QpcHR0Y0qcHXu6uWtOfuXiJdVt/U33v9e3aiap+FVTvJ7xLZM3mbVy4/Cexb99iXbIkrb9pQosmDXSOKWPbrhxZzu0/dpL0LhZrp4rUbjMFsxKOOuX/6+QaLh1cRPkaXanRajwAsdHP2Dwz5zkA0LjrElx9GucZU37U54cPHeLMmTPcv3+fd+/e8dvOnRQtWlSn7SyI+0+pVLJ9y3pOHD1AQnwcHl5l6TNwBDa2pXLNd/hAIEG7t6OQR+Po5EKvfkNx8/BSvS+PjmLz+tXcuP4X794lYFPKjm+/64J/9Vq5rDXd9gvBbDr9F5Fv43G3KcHYVnUo62ClMe2JG/dYd+IKTyNjSEl7j0NxGV1qV6SZn7cqzaRfj7Lvzztq+ap5OLC6b+s8Y8kqvaw2cPxDWXl6ldG5rPaqysqV7/sNUZXV61cR9OvZQWO+UWOnUq1G7TxjCvr1J86dCCQh/i2unuXp0nc8ljb2WvOE3/6Lo3s38/hBKDHySAaOXUjFKnXU0iS+S2B3wDKuXzlD3NsYipe0oX7TDtRu3CbXeAQhK9EDQshXRYoUoWTJkp/t806dv8jqdZvo1r4taxbPxcXRgdFTfkSuiNGY/lZoODMWLOHrBnVZu2QeX1WpzKRZ83j05G9Vmt2b1qi9Rg8ZgEQioWa1qjrHtX/3Fo4c2EmvAT8wY8EvGBgaMmfycJKTk7TmSUpMxN7JlZ79RuaS5h0e3uXp0G2AzrEA6BkbEXsjnFtDpumUvohjKSrt+5moM5e54NeCR8s3UfbnmRRv8JUqjXXbJnjNH8e9mSu5ULkVb2+EUeXgOgqXMP+o2PKjrJKTEnn04C6tvuvBrCUbGDFuFi+e/82CmWN0imnXzp3s27ePQYMHs3jJEgwNDZk0cSLJycla85w9e5a1a9bQsVMnli9fjrOTE5MmTkShUKjSrPn5Z65cvsy48eOZO28e0VFRzJw5M894zpw7z89r19G5Y3tWLVuMs5Mj4ydNQZ5l3VndvhPKrHkLaNywAauXLaGafxWmzpzFo8dPVGlK2doyqF9f1qxczqL5c7G0LMm4SVNQxGg+d7I7ff4iq3/ZRNcObfl5yTxcnBwZM3lmLudeGDPnL6FJw3qsWTqf6lUrMflH9XPvecRLho6ZiH0pWxbNmsra5Qvp3L4NhQsX1imms2fPsmbtWjp17Mjy5ctxcnZm4qRJavsgqzt37jBn7lwaNWzIiuXL8ff3Z8aMGTx+/FiVJjExkdKlS9OzRw+dYsju+O9/snTzTr5v8w2b5k7EzcGOYT8uJTomVmP6xKRkbC1LMLBjKyzMTDSmiY2Lp8+keRQqpMfi8UP4dfE0hnRtSzFjI53jOn3uAj/9soEuHb7jp6ULcXZyZOzk6dqPqdAwfpy3iMYN6vHTsoVUr1qFKT/OUTumACr5VuC3gPWq14TRI3SOqSAe57qc11nduXOHuXPm0LBRI5avWKHxmPqU+iWrU+d/Z9X6zXT/7lvWLpqDi5MDP0ydlev33vQFy2havw6/LJ7DV1UqMXH2fB5mOfdWrd/MlWvBTBg+iE0rFtGm+dcsXbOei5ev6hRThmunfiHkfAC1206l7bDf0C9chH0/f09qivb6PMOrv29y69IOLKzVG3eKmlnTY+p5tVflRoPRNzDC3qtGnuvNr/o8KSkJXz8/vmvfPs8Ysiqo+2/vrl85tH8PfQeOZPainzA0NGTGpFG5fhdfPHeKjWtX0q5jN+YvW4uDkwszJo0iRiFXpVm+aBYvnj9l7ORZLFq5garVarJozlQePribazxHroezIOgcfRtVZfuITnjYFKf/mj1EvU3QmN7UyJDv61dh89Dv2DWqCy0qezNl+zEuhj1WS1fd05GTU/uoXnO7fPxNs8Bdv3Jw/276DRzBnEWrMTAswoxJP+RaVhfOnWLD2lW069idBcvW4ujkwvRJP6D4UFYWxUuyLmC32qt9px4YFilCBb/KWteb4XDgJk4c/JUufcczYe4mDAyKsGj6QFJyiSk5MZFSju507jNWa5odGxZy6/rvfD9sJjOX76ZBs45sXTuX4Ctn84xJEDL8qxogunfvztmzZ1m6dCkSiQSJRMLjx485e/YslStXxsDAAGtra8aOHUtqaqoqX+3atRk0aBCDBg3C1NSU4sWLM2nSJJRK5SfFoVAo+P777ylRogQmJibUrVuXkJAQAO7evYtEIiEsLEwtz+LFi9Xukt26dYsmTZpQtGhRLC0t6dKlC5GRkZ8Uz+vXr2nWrBlFihTBycmJrVu35kjz999/06JFC4oWLYqJiQnt2rXj1atXqvenTp2Kj48P69evx97enqJFizJgwADev3/PvHnzsLKyomTJkvz4449q6120aBFly5bF2NgYOzs7BgwYQFxcnOr97EMwMj4nICAAR0dHTE1Nad++PW/fvv2kbc9uZ9ABmjasR5P6dXC0t2PEgD4YGhTm8IlTGtPv3n+QyhV9aN+6BQ52pejZuT1uzs4EHjyiSmMuk6m9Ll7+E5+ypbGxstQpJqVSyeF9v9GqXXf8qtbEwcmVAcMnI4+O5Oof57Tm8/Hz57sufXP0esiqRt0mfNuhJ2V9KmlNo8mbo+e4O2UJr4JO6JTeoU973j16RujoucSFPeTJqq283H0Up6HdVWmchvXg6brfeLZpD3GhD7g5YArvExKx6/6tznHlV1kZGRdlwoyl+Neoh00pB9w8y9Cj7wge3Q8j8vXLPGPau3cv7du3x9/fHycnJ0aOGkVUVBSXfv9da77AwEAaN2lCw4YNsXdwYNDgwRgYGHDs2DEA4uPjOXbsGL1798bHxwc3NzeGjxhB6J07hIWG5hrT7sAgmjRuSKMG9XGwt2fooAEYGBpw9Jjm/bl3334q+Vak3betsbe3o3uXzri6OLPvwEFVmrq1a1Gxgg/W1lY4OtjTt3cvEhISePToca6xZNi5dz9fN6pPk/p1cbS3Y/iAPhgYGHD4uOZzb8++Q9nOvQ64uTix98BhVZr1Aduo7FuRvj264ObijK21FdWrVEJmZqpTTIGBgTRp3JiGDRviYG/P4EGD1PZBdkFBQfj5+tKmTRvs7e3p2rUrLi4u7N+/X5WmXr16dOrYkQoVKmhcR15+PXCcFvW+4ps61XEqZcOY3p0wLFyYA6cvakzv7erI4C5taFC9Mvr6+hrTBAQdxdJCxqQB3Snt6oRNyeJUKV+aUla6N/7u3ruPrxs1oHGDejjY2zFsYD8MDAw4clxzz6g9+w5QybcC333bCgc7O3p06YirizNBBw6ppdPX11erP4vpeEcYCuZxntd5nV1QUBC+fn5aj6lPrV+y2hl0MMv3XilG9P8eQ4PCHDpxWmP63fsPfzj3muNgV4penb7DzdmJwINHVWluhYXTuG4tKpQtjbVlSZo1qo+rkwOh9+7rFFPGtoWc24xfg344l6lHcRsP6necS3zsax7eyv27JzkpnmNbR1G33QwMjNQb3qRSPYxNSqi9Ht46gWv5JhQ2MM4zpvyozwFatmpFu3bt8PT01KF0MhXE/adUKjkQtJM233Whsv9XODq5MHjkeOTRUVy5dEFrvv2Bv1G/8TfUbfA1dvaO9B00EgNDQ04ey6wXwkNv06RZa9w8vLCytqFN+64YGRfl4f3cGyACzl6jddUytKxcGhcrCya2qY+hfiH2XrmlMX0lVzvqlXPF2dICu+JmdKpZETfrElx/9EItXeFCehQ3MVa9TIwMdSqjDOlltUutrIaMHEd0dGQeZbWTBo2bUq9Bkw9lNQIDQ0NOfSgrPT09ZOYWaq/Ll85T/as6FCmSe+OyUqnkxIFtfNP2eypUqY2dozu9hk5HEf2Ga5fPaM1X1rc6rTsNpGLVulrT3A+7QbU6zfAs40fxkjbUavgtdo5uPLyneT8Igib/qgaIpUuX4u/vT+/evYmIiCAiIgJ9fX2+/vprKlWqREhICKtXr2bdunU57iJu2rSJQoUKceXKFZYuXcqiRYv45ZdfPimOtm3b8vr1aw4fPsxff/1FxYoVqVevHtHR0bi7u+Pn55ejEWDr1q107NgRSG/AqFu3LhUqVODq1ascOXKEV69e0a5du0+Kp3v37jx9+pTTp0+za9cuVq1axevXr1Xvp6Wl0aJFC6Kjozl79izHjx/n4cOHfPfdd2rrefDgAYcPH+bIkSP8+uuvrFu3jqZNm/Ls2TPOnj3L3LlzmThxIpcvX1blkUqlLFu2jNu3b7Np0yZOnTrF6NGjc433wYMH7N27lwMHDnDgwAHOnj3LnDlzPmnbs0pJSeHu/Yf4+pRTi69i+XLcDtP8xXYn7C6+5cupLatUsbzW9NFyBX9cvcbXDbRXztm9fvUChTyKMj6Z3YCNjIvi4u7NvbB/R4VtVtWHyFOX1Ja9OX4BWVUfACT6+phWLE3kySwXcEolkad+x6yq7j/UPmdZJSTEI5FIMCpaLNd0L1++RC6X45PlB6exsTEeHh6EZmtozJCSksL9e/fw8fFRLZNKpfj4+KgaF+7du0dqaqraeu3s7ChRsqTW9Was+979+1TItu4KPuW15rsTFkYFn/Jqy/wqVsw1/kOHj2JsbIyzk+ahAdnT373/UO1ckkql+PqU5U54uJaY7lLRJ9u5V8FHde6lpaXxx9Vr2NlaM3ryDFp37smAkWO5cOlKnvFkxHTv/n2N+0DbdoeGhantDwBfX99c98fHSElNJfzh31Qqm9kdWSqVUqmsFzfvPvzk9Z6/GoKXswPjF/1Ek+9H0nX0DPaeOK97XCkp3L3/gIpZjhGpVEpFn3LcCdO2/8LV0gNUqujDnWx1Z8jNW7Tp1I3ufQeyZOVPxMRq7umhKaaCeJzndV5nFxYaqrYNkH5MZaT/lPpFPaZUwh88xLd8WbWYfMuX5U74PY15boffxbd8GbVllSuU50545r4r4+nBxStXeRMVjVKp5PqNWzx9HkGlCuWyr06r2OhnJLx9g517NdUygyLFsLQvx8vHwbnmPbt7Oo5etdXyavP66S0in4fiXSXvxu78qs8/VUHdf69eRqCQR1POJ3NIlbFxUdw8vAgPu61lW1J4cP+uWh6pVEo5H1/uZsnj4VWa38+d5u3bWNLS0rhw9iQpycmULuujNZ6U1PeEPntFVffM4QNSqYSq7vbceByR5/YolUou3/2bx2+i8XVWH2pz9f4zak/+ieazNzJz10kU8e/yXF9WGWVVPkdZeRMedkdjnvSyCtdYVtryPLgXzqOH96nXMO8eGpGvnhMjj8S7fBXVMiPjYji7leFB+A1dN00jV89yBP95FnnUa5RKJWE3/+Tli78p7aN7r2BB+FfNAWFqakrhwoUxMjLCyip9zNeECROws7NjxYoVSCQSPD09efHiBWPGjGHy5MlIPzzT1c7OjsWLFyORSPDw8ODmzZssXryY3r17f1QMFy5c4MqVK7x+/RoDAwMAFixYwN69e9m1axd9+vShU6dOrFixghkzZgDpvSL++usvtmzZAsCKFSuoUKECs2bNUq13/fr12NnZcffuXdzd8x7Dn+Hu3bscPnyYK1euUOnDOOV169bh5ZV5gXvy5Elu3rzJo0ePsLNLH0e/efNmSpcuzZ9//qnKl5aWxvr16ylWrBje3t7UqVOH8PBwDh06hFQqxcPDg7lz53L69GmqVEmv1LJOlOno6MjMmTPp168fq1at0hpzWloaGzdupFix9B9+Xbp04eTJkzl6V2SVlJREUpJ6t7Gk5GQMsnTFjol9S1paWo67ozIzU/5+/lzjeqMVCg3pzZDLFRrTHz11FqMihtT0r6LxfU1i5NEAmJqpD0UwNTNH8eG9gs7AsjhJr9R76CS9ikTftBhSQwP0ZaZICxUi6XVUtjRRGHs46/w5n6uskpOT+HXjKqrVbICRUe53zOTy9O6Q2edlMJPJVO9lFxubfmGlKc/TZ89U6y1UqFCOMcIyMzPk0dq3VbXubJO7yszMePpU83EulytypDczMyM6W/x/XPmTWXPnk5SUhLm5jDkzp2Nqqrnbf1aqc0+W81z6+1lu5172bTBVda9XxMTw7l0iv+7aS4/O7enTvTNX/gpmyuz5LPpxKuXLls41Jm37QGZmxrOnTzXmkcvlGstV237+WIrYON6npWGebSiFzKwYj1/kfRGtzYvXb9hz/CwdmjagW6uvCX3wmMUbtqNfSI+mtfP+Aae97jTjqZb9p/WYytLVulLFCnxVrSpWlpZERLxk3eYtjJ8yg2UL5qCnp5drTAXxONflvM4ZkxyzXOqOT6lfsor5EJO5pu+9Zy805olWKDDXcO5FyzO7/A/p04OFK9fQtmd/9PT0kEokjBrYh/KlvdFVQuwbAIyKWagtNypWnIS32nt83r1+kDfP7tBu+C6dPufO5d3ILF2wdqqYZ9r8qs8/VUHdfxnft2ay7N/FMq3fxW9jY0hLe4+ZmSxHnudPM4eHjBw7lYVzp9G9fTP09PQwMDBk9MSZWNtony9BHv+O92lKLIqp3/m3KGbEo9faz5O375JoMG0tKanvkUoljP+2Lv4eDqr3q3k6Uq+sK7bmpjyNUrD80EUGrAkkYGh79KS63aPNKA/TbGVlZiZDnmtZpWFmljNP1rLK6sSxQ5Syc8DTu4zG97OKUaRfi5mYqq/fxMyCWMWn9bbO0LH3GDavmsmo7xujp1cIiURCtwGT8Cjtm3dmQfjgX9UAoUloaCj+/v5IJJkzhFavXp24uDiePXuGvX16a2nVqlXV0vj7+7Nw4ULev3+f54VQViEhIcTFxWFhof6F+u7dOx48eABA+/btGTVqFH/88QdVq1Zl69atVKxYUdUtLyQkhNOnT2ucnOjBgwcf1QARGhpKoUKF8PXNPPE9PT3Vhj2EhoZiZ2enanwA8Pb2xszMjNDQUFUDhKOjo6pRAMDS0jL9iytLJWxpaanWu+LEiRPMnj2bsLAwYmNjSU1NJTExkYSEBIyMNHcRy/451tbWauvUZPbs2Uybpj5fwYiB/Rg5uH+u+f5ph0+con6tGrmOQb9w5ii/rJyn+nv05AWfI7R/pS9RVqmpqSydmz4Eq+eAH3K8f/rUKZYvX676O/tx919WvlxZVi9fQmxsLIeOHGPmnLksW7Qgx4+6zyEtLX2IXLUqlWjbshkArs5O3A4LZ9+RY3k2QPx/kpamxMvFgf4dWwHg4WTPg79fEHj8nE4NEPmlTq3M8fjOjg44OTnQ9fv+hNy8naP3y+dUkI7zgmrPgSPcCb/HrAmjsSxZnJDboSz5eT0W5jL8tOy78L/2c2bnFNXf33z/00d/7lt5BOcDZ9Gi33oK6RvkmT41OZG71w5QqaHma4H/r/X5x+6/c6eP8/OKhaq/x0/933ulavNrwDoS4uKY8uMiTExMufLHBRbOmcrMectwcPy4CX3zYmxQmN9GdiYhOZnL956yMOgcpSxMqeSafj3cpELm/CJuNsVxtylO0x83cPX+M6q4a56s8Wy2spqQj2WVISkpifNnT9C2fVeN7/9x9hCbf8q8iTd0wrJ8i+Xkwe08uHuTweMXY1HCmrt3rrFlzRzMzEuo9bj4N5Lq/feeNlFQ/esbID63uLg4rK2tOXPmTI73Mn70W1lZUbduXbZt20bVqlXZtm0b/fv3V1tHs2bNmDt3bo51WFtb51foeco+vlgikWhclpaWBsDjx4/55ptv6N+/Pz/++CPm5uZcuHCBXr16kZycrLUBIrd1ajNu3DhGjFCfvCzqiXpXX1OTYkil0hwTN8kVMTnuFmQwNzPTkF6BTJYz/Y3boTx9/oLJo4fnGqtv5a9wdc/8cZSSkj6xVYwiGpl5cdXyGEU0js7anxBQkCS9isTAsrjaMgPL4qTEvCUtMYnkSDlpqakYlLTIlsaCpJfaW9s/d1mlNz5MJPL1Syb+uFxj74cqVavikWUMb0pKCpB+58zcPPNugkIux1nL0w9MTEzSj8Vsd9QUcjnmH+6iyWQyUlNTiYuLU2uMlCsUyMy1T9ypWne2Se/kCgXmGo7b9M8yy5FeoVCoYslQxNAQWxsbbG1s8PL0pHvvvhw5dpwO7TQ/CSaD6tyT5zyXtMWUfu5l34YY1Y9AU5Ni6Onp4WCvflfMwc6Wm3fy7pqubR/kVr4ymUxjueryVBJdmJkURU8qJVqhPgxBrniLhY7zWmhSXGaKYykbtWWOpaw4c/maTvm1152a60LI5Zgy015WNlZWmJqY8CIiIs8GiIJ4nOtyXueMSYZCQ3pZlnoAPq5+ycr0Q0zRmr73cjn3ojWce+YfejAlJSXzy5ZfmTFuFP4fnkrj4ujA/YeP2bH3gNYGCKfSdbC0z3zv/fv0+jzhbRTGJpnzkSS8jaS4rVeO/ABvnt3mXVwUOxZlPoVAmfaeFw+vcuPiVvrPu4FUmnnT6P6No6SmJOLp11Lj+j5Xff6pCsr+q1SlutqTKjLKSSGPRmae+b0eo5Dj6Kz56RzFTEyRSvVUkyhmzZPRk+JlxHMOHwhk8aqN2DukD3tydHblzq0bHDmwl76DNE8kLTMugp5UkmPCyai3CRQvpn0+BKlUgn0JMwA8bUvy6FU0607+qWqAyK6UhRky4yL8HanQ2gBRuUp13DWUVYw8GvMsZaVQyHHKtaykKBTqPSQUWcoqq0sXz5KclETteo00rq985VpMcc/sGZH6IabYmGjMzDOfGBWriMLOSfcn/mSXnJTInq0rGDhmIeX90huY7RzdefroLkeDNv/rGyCEz+dfNQcEQOHChXn//r3qby8vLy5duqQ2oeTFixcpVqwYpUplXrhmnbcA4I8//sDNze2jej8AVKxYkZcvX1KoUCFcXV3VXsWLZ/5g6tSpEzt27ODSpUs8fPiQ9llmRa5YsSK3b9/G0dExxzqMjXPvDp6dp6cnqamp/PXXX6pl4eHhajMze3l58fTpU55m6XZ8584dFAoF3t66d6fM7q+//iItLY2FCxdStWpV3N3defFCc5fB/5WBgQEmJiZqL4NsvRD09fVxd3XmWkjmYx/T0tK4duMmpT019yrx9nTn2g31x0T+FXxDY/pDx0/i7uqMq5NjrrEWMTLGyqaU6lXK3gkzmQW3QjJnn05IiOfB3Tu4eebdla4gUPwRjEVd9fF9xetVQ/5HMADKlBRirt2meF3/zAQSCRZ1/FH8cV3rej9nWWU0Prx88ZQJM5dSzETzDz4jIyNsbGxUL3t7e2QyGSHBwZkxxccTHh6Ol5bJxvT19XF1c1PLk5aWRnBwMJ4fhke5ublRqFAhgrOkefbsGW9ev9a63ox1u7m6Ehwckm3dN7Tm8/b05HqI+rjPa9eDc/0cAGWaUnVxlRvVuXcj27kXchNvLY8n9PZ0VztXAa4Gh6jOPX19fTzcXHiarRvy0+cRWJbI+xGcqnIKyV5O2rfby9NTbX8AXL9+Pc9y0pV+oUJ4ONvz563MBpS0tDT+vBVKWXfdhyplV87Dlb9fqE+m+vTFK6x0fAJN+v5z4VqWYyQtLY3rITfx1vJ4Sm9PD64Hqx9Tf10PwVtLXQvwJjKS2LdvMTfP+0dbQT3O8zqvs/P08tJ4TGWkt7Ky+uj6RT2mQni45Dz3/rpxC28PzY22pT3cuXZDfU6dq8E38f7weNPU96mkpr5HKlG/G6inJ8118u7ChkUxK+GgeplbumJUrATP7mXOH5ScGMerv29g5eijcR2l3KrS4Yd9tB8ZqHqVtCuDR8VmtB8ZqNb4AHDn8i6cStehSFHNx/rnqs8/VUHZf0WMjLC2KaV62dk7YiYz52ZIZiNmQkI898JD8fDU3PtMX18fF1d3bgZnXo+mpaVxI/ga7h/yJCUlAuSITaonzfVGlH4hPbxKWXL5XuZ1bFqa8v/Yu++wKI43gOPfAxEElabSpIMUNWIXTdRobEmMmkRjjN3YaywxFuy9Kxp7R6OJvZdorImaaNQkCooVVJByB1KOIvz+QA8OjmIShPx8P89zj3LMzr07Ozu7zM3McvF2CG85FfyLu7T0dFJSn+f6+3DVM1QJiZQvm/u9eG5ldT1HWd3Aw1P3PXZGWXlw/WrmNhlldVnnNieOHaRW3fqYmprpjqmUCVY2DpqXrb0LpubluHk9c82kxIQ47t7+E1ePvz/67PnzVJ6npqKn0P7zUU9PTzNqUYiC+M91QDg5OXHx4kXu379PZGQkAwYMICQkhMGDBxMYGMjevXuZOHEiw4cP15o68PDhQ4YPH05QUBDfffcd/v7+DB069JU//7333sPX15e2bdty7Ngx7t+/z88//8y4ceP47bfMP5o+/vhjnj17Rv/+/Xn33Xextc38dmrgwIFER0fz+eef8+uvv3Lnzh2OHj1Kjx49tDpXCsLDw4OWLVvSt29fLl68yOXLl/nyyy8pVaqUVsxVq1bliy++4MqVK1y6dImuXbvSqFEjatWqlUfueXNzcyMlJQV/f3/u3r3L5s2bWbHi1Ydc/pvat/mQA8dOcOTEKR6EhLJw+WrU6iRaNs14jvGMhf6s3pi5QOgnrT/g0pWrfL97Pw9DH7Fh6/cEBd+h3QfazxGPT0jg9PkLfNCs6SvHpFAoaPVRB/Zs38hvF8/y8P4dli+YgrlFOWrVa6hJN23cYI4eyJzzqk5M4P7dW9y/mzHSIyL8Cffv3tJ6akPcs1ju371FaMg9AJ48esj9u7dQKbXXYshO38SYstU8KVst44bL2LkiZat5YmSfcSH3mDacauszR+g8WLUNY2d7PGeOwsTDBcd+nbBp34p7izdo0txbtB77Xh2w69KW0p4uVFk2iRImpQjZuKvIyyo1NZVFs8ZyNziQQSMnkZaWhkoZhUoZpfmmIK+Y2rZty7Zt27hw4QL37t1j3vz5WFpa4ls/c3j7mG++Yf++fZqf27Vrx5EjR/jx+HEePnzIsqVLSUpKolmzjOewm5iY0Lx5c1avXs21a9e4ffs2CxcswMvLK9+b2k/ateHQ0WMc+/EEDx+GsGTZctRqNS1e1M858xeydsNGTfq2H7Xmt8tX2LFrNw9DQtm0ZSu3goP56MMPAEhUq1m3cRM3AwMJf/qUW7eDmb9oMZFRUTR8+22dMWTXvm1rDh79kaMvzr1F3744997LOPdmLliide59/NH7/HrlKt/v3sfDkEds2LqdW8F3afthK02azz5uw6lzP3Pg6HEePX7C7gOH+eXSb7R5X/e3QNm9PAbHf/yRhw8fsnTZMq1jMG/ePNavX69J36ZNGy5fvszOXbsICQkhICCA27dv07p1a02aZ8+ecefOHR48zJinGxoayp07d4jOY92OrD7/sBn7Tpzl4KmfuRf6hDlrtqBOSuaDxg0AmLx0Hd9uzTxnUlJTuXU/hFv3Q0hNTSUiWsWt+yGEhGVOW+v4wXv8efsuG3YdIiTsKUfPXWTPibN80uLdHJ+fm0/afsSho8c5duIkD0JCWPztStRqNS3fy6hTs+YvZs2GzZr0H3/0Ib9e+Z0fdu3lYUgoG7ds41bwHdp8mLFAWmJiIivXbeBGYBBh4U+5cvU6E6bOxNbGmlo1CrYwbXGs5/md17nVqV07d+qsUwVtX/LSvs0HHDh2kiMnT2dc91asQa1OotV7jQGYsXApqzZtzSzX1q24dOUa2/fs50HoI9Z/9wNBd+7Q7oOM88rE2JhqVbxZviGA3//4iyfhTzl84hRHfzrDO/UK/sQlhUJBtYZd+e34Cu79eZLIx0Ec3zoak7IVcKnynibdnuXduX42Y42skkalsbSppPUqUbIURsZmWNpod26pIh7w+O5veNfNe+RK9pgKoz0HiI6O5s6dO5ovYu7fv8+dO3fyfcpXcTx+CoWCD9u0Z8e2Tfx64TwP7t9hyfwZmFtYUsc381yZNPYrDu3PbK9at+vAj0cP8tOPRwh9eJ9VyxaQpE6kSbOMdt2uoiPWtnasWDqf20E3CXvyiH27tnP999+o45v3I1S7NKrBrgt/sO/Xv7gbHsW0HSdITE6hbZ2Mzo1xW4+w+EDmUyfW/niJX4IeEBql4m54FBtPXebgbzf5oGbGfU9CUjIL9p3h+v0nPIqO4eKthwxdtw/7cmbU93TUGUPuZfUpO7Zt5tKF8zy4f5cl82dgYVFOq6wmjh2eraza8+PRAy/K6gErly0kSa3WlNVLTx6HcuPP67zX/INXium9Dztx4Ic1XL10mtAHt1mzeAJmFuWpUbexJt3cCX05cWib5md1YgIP7wXx8F7G4sOR4Y94eC+IqIiMNYpKGZfGo3JNvt+4iMA/fyMi/BHnTu7j51MHqVGv4Neb4kqhpyi2r/83/7kpGCNHjqRbt254e3uTmJjIvXv3OHToEKNGjaJatWpYWFjQq1cvxo8fr7Vd165dSUxMpE6dOujr6zN06FD69Onzyp+vUCg4dOgQ48aNo0ePHkRERGBtbU3Dhg2xssp8LGOZMmVo3bo133//PevWrdPKw9bWlvPnzzN69GiaN29OUlISjo6OtGzZUqvTpKDWr1/Pl19+SaNGjbCysmLatGn4+flpxbx3714GDx5Mw4YN0dPTo2XLllrzIv+OatWqsWDBAmbPns2YMWNo2LAhM2fOpGtX3XPUXocm7zQgJiaWDVu3E61U4erixOxJ4zRDGZ9GRGr1vFfx8mD8iKGs2/IdazZvxc7Whqljv8bZUXvo3ckz50lPT6dJwwZ/K67Wn3QmSa1mzdLZJMTH4eH9Ft9MXkDJkplzXMPDHvEsVqX5+W5wIFPHDtL8vHltxpy+hk3ep/9XGfX78sWzrFicOe9vyZwJAHzyeU8+7fRlrvGY1qyC74nMPya8540FIGTTLq73GoOhTXlK2Wd+q5B4P5RfP+qL9/wxOA3uijo0jD/6jifyeObF/skPhylZ3oJKE4dgaF2e2Gs3ufThlyQ/zbsz5HWUlTIqgssXM2L9Zkg3rc/zm7EU76p5L172afv2qNVq/JcsIS4ujsqVKzNl6lSttUCePHmitcJ/o0aNiI2JYXNAAMroaFxcXZkydarWcP4+ffui0NNj+rRppKSkULNmTQYMHJhvGTVu+A4xMTFsCtiKUqnExcWF6VMmafJ+GhGhteZNZW8vxowawYbNW1i/cTO2drZMGj8WZ6eMmyx9PT1CQkI5fuIksTGxlClbFg93NxbMmYWTo+5hqNm9+04DVDGxrN+yDeXLc29y9nMvs32r4uXJuJFDWRewjbWbMs69KeO0z713fOvy1YDebP1hN0tXrcfezpbJY0ZStXLBvnVs1KgRMbGxBGzeTLRSiauLC1OnTNEupyxtrre3N6O//pqNmzaxYcMG7Ozs8PPzw8nJSZPmwoULLFi4UPPzrBdT6b7o1InOnTvnG1Oz+rVRxT5j9ff7iFLF4u5UkYVjh2D5YmHKsMhorWMXEa2i69dTNT9v2X+MLfuPUd27EssnjcyI282J2SMHsHzrLtbtPIBNhXIM6/YZLd8p+HDYdxu+ndF2BmxDqVTi6uLMzCkTNFMwnkZEoJflJqiylydjR33F+s1bWbcpADtbGyaP+0ZTp/T09Lh77wHHT/xEXHwClhbm1KzuQ4/OnSiZy+NEsyuO9Ty/8zri6VOta4y3tzdfjx7Npo0bc61TBWlf8tLknfqoYmNZv/V7opUq3JydmDNxjGbqYXhklFY9r+Llgd+IwawN2M6azduws7Vm2phRuGQpgwkjh7J601amL/AnNi4Oq/Ll+bJzRz5q2Sz7x+epRpMvSU1O5KcfJpCUGIuNc01a91mttb5DTORDEuNffaHXm5d2UtrUGgePV7suF1Z7fujQIbZmeQLa16My1hj6avhwrY6K7Irr8Wv76eeo1Yms8J9HfHwcnt5V8Zs6V+taHPbkMc9iM6ePNGjYhJgYFdsC1qFSRuPs4sb4KXM10wpKlCjBuElzCNiwkplTxqBOTMTa1o5Bw8dQs3beT1FoWd0DZVwi3x75hcjYBDzsyvNtn3ZYlskYrRCmfKZ17iUmpzBj50nCVc8wNCiBs5UF079oScsX6z7oKfS49SSSfb/d4FliEhXKlsbXw4GBrepTssSr/XnU7tPPSVKrNWXl5V0Vv6lzspXVI2KzlNXbDZsQG6Piu4D1mrLymzInxxSME8cPY1muPD41Xu1x663adSNZncjG5dNIiH+Gu5cPX/ktxSBLTBFhocRluZe6f+cGc/0y/zbavn4BAPXfbU2vIRnrp/QdMZOdAf6sXjiO+LhYLMvb0K7TQBq3+PSV4hOFa9myZcydO5ewsDCqVauGv78/derUyTX9okWLWL58OQ8fPqRcuXJ8+umnzJw5EyOjV3ssbUEp0vMaT/d/onHjxvj4+LBo0aKiDkX8ix7/w0cJFYYwhV3+iV6zJ5WLbhG63Nj8VbDn279OpiVi8k9UBEqk5T80/HUrkZZc1CHkkKSf93PRi4J53D9bIb8wxBnnP32lKKQpXm065OuQqlewjpLXyTi5YI8xfZ123KmWf6LX7H2ve0Udgk7F8fhFlbAu6hBycAvaU9Qh5HDHo01Rh5CDMjn/p/cUhbe9X206eXFxo92rj3J+Xbx3nyhw2u3bt9O1a1dWrFhB3bp1WbRoET/88ANBQUFUqFAhR/qtW7fSs2dP1q1bR/369bl16xbdu3enY8eOLFiw4N/cDY3/3BQMIYQQQgghhBDi36LQ0yu2r1exYMECevfuTY8ePfD29mbFihUYGxvnGJH/0s8//0yDBg3o1KkTTk5ONG/enM8//5xLly7pTP9veOM7IM6ePUvp0qVzfRW14h6fEEIIIYQQQojCkZSURGxsrNYrKSkpR7rk5GQuX77Me+9lrrOjp6fHe++9xy+//JIjPUD9+vW5fPmypsPh7t27HDp0iPfff79wdob/4BoQf4euR2a+VKtWrRwrVBcnxT0+IYQQQgghhBCFY+bMmUyePFnrvYkTJzJp0iSt9yIjI3n+/LnWuoQAVlZWBAbqfoR5p06diIyM5O233yY9PZ3U1FT69evH2LFj/9V9yOqN6IDIS6lSpXBz0/2c3uKguMcnhBBCCCGEEKJwjBkzhuHDh2u9Z2homEvqV3Pq1ClmzJjBt99+S926dQkODmbo0KFMnTpV66EG/6Y3vgNCCCGEEEIIIYQojgwNDQvU4VCuXDn09fUJDw/Xej88PBxra90Lzvr5+dGlSxe+/DLj6XlVq1YlPj6ePn36MG7cuL/1hMb8vPFrQAghhBBCCCGEEP9lJUuWpGbNmpw4kfnUjLS0NE6cOIGvr6/ObRISEnJ0MujrZzyZqrAelikjIIQQQgghhBBCvLEUeoqiDuFfMXz4cLp160atWrWoU6cOixYtIj4+nh49egDQtWtX7OzsmDlzJgCtW7dmwYIFVK9eXTMFw8/Pj9atW2s6Iv5t0gEhhBBCCCGEEEL8x3322WdEREQwYcIEwsLC8PHx4ciRI5qFKR8+fKg14mH8+PEoFArGjx/Po0ePKF++PK1bt2b69OmFFqN0QAghhBBCCCGEEP8HBg0axKBBg3T+LvvTIUuUKMHEiROZOHHia4jsxWe+tk8SQgghhBBCCCGKmf+XKRj/BbIIpRBCCCGEEEIIIQqddEAIIYQQQgghhBCi0MkUDCGEEEIIIYQQbyyZgvH6SAeE+M9K1jcq6hByKJf+tKhDyOmvn4s6ghyeVK5f1CHkYBp0uKhD0Cmd4ndBfJJesahDyMEx6XZRh5BDqIlnUYeQg4EipahD0KlUenxRh/CfEGdgXtQh5NDM81FRh5BDqZS4og5BJ6OkmKIOIQcDA8uiDiGHkza9ijqEHKov71bUIeRg0n9SUYeQi0pFHYAo5mQKhhBCCCGEEEIIIQqddEAIIYQQQgghhBCi0EkHhBBCCCGEEEIIIQqddEAIIYQQQgghhBCi0MkilEIIIYQQQggh3lgKPfle/nWRkhZCCCGEEEIIIUShkw4IIYQQQgghhBBCFDqZgiGEEEIIIYQQ4o2lp68o6hDeGDICQgghhBBCCCGEEIVOOiCEEEIIIYQQQghR6GQKhhBCCCGEEEKIN5ZCT6ZgvC4yAkIIIYQQQgghhBCFTjoghBBCCCGEEEIIUehkCob4v7PvwEF27NxFtFKJi7MzA/r1xdOjUq7pz5w9x8aAAMLDn2Jna0uvHt2pU7uW5vebt2zl1JkzREREYlCiBG5ubvTo2gVPT48Cx7T3wCF+2LWbaKUKV2cnBvbtnWdMp8+dZ2PAVsLCn2Jna8OX3btSN0tMm7Z8x6mz54iIiKREiRK4u7nSo2tnvPLIM7v09HR2bFnDyWP7iI9/hofXW/QcMAobW/tct7n55+8c2LWVu3eCUEVHMnzsTGr7NtL8PjU1le8DVnL1t194GvaYUialqVqtFh279cfCsnye8Vi8XQuXEb0wrVEFI9sK/PbJAML3nch7m4Z18J73DaW93VGHPCF45nJCN+3WSuPYvxMuw3thaF2e2OuB/DVsKjG//lGAEsq0f/9+du7YgVKpxNnFhf79++PhkfvxP3v2LJs3bSI8PBxbOzt69uhB7Tp1NL9PT08nYPNmjhw5Qnx8PN7e3gwcNAg7O7sCx/Rv1vPU1FQ2bArg199+40lYGCYmJlT3qUav7t2wtLQscEzp6ens3Lqan47tJT4+jkpeVenZ/2usbR1y3ebmn79zcHcA917Uqa/GzqZWvUZaaXZuXc0vZ38kOjIc/RIGOLt50KFzP9w8quQb085Dx/luzyGiVTG4Otnz1Zdd8a7kqjPt3YehrP1uJ0F37hMWEcmQnl/QoXXLf5RnbtLT09kesI4fj+4nIT4OD6+q9Bk4HBu73M8/gMMHdrFv5zZUymgcnV3p1W8o7h7emt8ro6PYvG4513//jcTEBGwr2vPJZ12o16BxgWLaGrCB40cOER8fh6d3FfoPHIqtXcU8tzu4fw97dn6PUhmNk7MrffoPppKHp878p0wYw5XLvzJm/GTq1X8735j2HTjIDzt3a+r5wH598q3nGwK2aOr5lz26abXnm7Zs5dSZs5r23N3Nje5dO+P1Cu15cWwP0tPT2RKwiaNHDhMfH4eXd2UGDBySbx4H9u9j184fUCqjcXZ2oW//gXi8OHbPnsWyJWAzv1+5TETEU0xNTannW5/OXbpjYmJS4LiKU53affAI23fve3EtdmRIn554VXLPNf2pc7+wbss2wp5GUNHWmj7dOlOvVg2tNA9CQlm1MYBrf97g+fM0HO0rMnnMCKzK533Ny2rHkZ8I2H+MaFUMbo4VGdHzcyq7OetMezfkMau27yXw3kPCIqIY1q0DHT94TyvN6u/3sXbHAa33HG2t2L5oaoFjyjh2Gzn24th5eVcu4LHby+4Xx87Z2ZU+/QdpHbtl/gu59vsVoqOjMDIqhae3N9179Kaife7XiawxHdmxjF9O7kAd/wwnj+q07+lHeRvHXLf5cc9qrv/6I08f38OgpBFOlXxo/flXVLDNKN/oiEdMHdJC57bdhs7Hp57u371k3KAZJo0/RL+MKSmPHxK7eyMpIXdyTa8wMqbM+x0wqlobPePSPFdGErtnM0mBVwEoP24xJSxy1p3488eI3bUhz1iyKo73CEK8JCMgxGuVnJxcqPmfOnOWVavX8EWnz1m2ZBEuzs6M85uASqXSmf6vGzeZOWcuLZs359sli6nvW4/J06Zz//4DTRo7O1sG9uvHymVLmT93NtZWFRjjNwFVTEwBYzrHyjXr6Px5R5YvXoCLsxNjJkxGmVtMNwOZMWc+LZu9x/IlC2hQry6Tps/iXpaYKtrZMqhfH1YtW8zCOTOxsqrAN36TChwTwP6dARw58AO9Boxi6rw1GBoZMWvCVyQnJ+W6TZJajYOzGz37jdD5++QkNffu3KLdZz2YsWg9w8fM4PGjh8ybNjrfePRNjIm9HsSfQyYXKP5SThWpvW8lUacucq5WG+75b6TqymmUa5Z5A2rTvhVec8dwe9oyztVpx7PrgdQ9uJaS5S0K9BkAp0+fZvWqVXT64gv8/f1xcXbGb/z4XOvUjRs3mD1rFs1btMB/6VJ8fX2ZOnUq9+/f16TZ8cMP7Nu3j0GDB7Nw0SKMjIzwGz++wOfHv13Pk5KSCL5zh06ff8ayJYuYMG4MoaGPmDhlWoHLCeDArs0cPfA9PfqPZsrcNRgalmLWxGF516mkRByc3ened2SuaaztHOjedwSz/LcwcfZKylewYdbEocTGKPOM58S5Cyxdv5Uen7Vj7fypuDk5MHzKHJQq3edJUlIytlYV6NelA5bmpv9KnrnZs2Mrh/bvpM/AEcxYsBJDIyOm+o3Ms6zOnznBxtXLaN+pO3OWrMHJ2Y1pfiOJUWWWg/+C6Tx+9JDRE2awYNkG6tZvyIJZk7h751a+Me3asY2D+3bTf9Aw5i5cipGREZP8vsmzXp49/RPrVq/gs05dWeC/AmcXVyb5jUalynls9u3ZiUJR8Dm2p86cZeXqtXTu1JFvlyzExdmJsX4Tc287b9xkxpx5tGzejOVLFlHfty6Tps3I1nbaMahfX1Yt82fB3NlYWVVgjN/EAredxbE9ANi543v279vDwEFDmL9wCUZGRkzwG5NnHmdOn2LN6pV83qkzi/2/xdnFhQl+YzXHLioqiuioKHp+2Ztly1cx7KuRXP7tNxYvml/guIpTnTp59jzL126kW8f2rFo4G1cnR76eOD3Xc/fPm0FMnbeI95s1YfWiObxdtw5+M+Zw78FDTZpHT8IY8o0f9nZ2LJw+mTVL5tHls08oaVCyQDEBHP/5VxZv+oEvP/2QjbPH4+5oz7Dpi4mOidWZXp2UjJ1VeQZ2aoelWdlc83Wxt+Xgqrma18opXxc4JoBdO7ZzYN9u+g8aytyFSzE0MmJiAY7d2tUr6NipCwv9V+Dk4sJEv2+0jp2rmztDvhrFspXrmDxtFqTDhPGjef78eb4xndy/jjNHttC+1wSGTd2KoWEpVszqS0oe7eadm7/xdvPPGTplK/3GruJ5agorZvYhSZ0AgJmlNZOXn9J6tfx0IIZGxnj5vJNnPEY+9Sj7UWfiju0icuE4Uh8/xKLPN+iVzuW46Otj0XcM+ublUW5cTMSsEcR8v5rnMdGaJFGLxhM+qb/mFbViBgDqaxfzLZ+Xius9ghAvSQfEGyw+Pp6uXbtSunRpbGxsmD9/Po0bN2bYsGEAKBQK9uzZo7WNmZkZGzZs0PwcEhJChw4dMDMzw8LCgjZt2mjdWHXv3p22bdsyffp0bG1t8fDwYMqUKVSpkvObSx8fH/z8/P7RPu3avYeWLVvQotl7ODo4MGTQAAyNDDl67LjO9Hv27aNWzRq0/+RjHBzs6dalM26uruw9kPnNQZPGjalR3QcbG2ucHB3p0/tLEhISuHfvvs48s9u5Zy+tWjSnZbOmODrYM3RgfwwNDTl6XPe3+7v37ad2zRp0+KQdjvb2dO/yBW6uLuw9cChLTI2o4VMNG2trnBwd6PdlTxISErhbwJjS09M5vO972nXoTq16DXF0dmPAVxNQRkfy24UzuW7nU8uXz7r01Rr1kJWxSWnGTV2M7ztNsa3oiLtnFXr0Hc694EAin4blGVPE0TPcmriI8L0/FmgfHPt0JPFeKDe/nk1c4F0efLuFsJ1HcR7aXZPGeVgPQtZ+T+jGXcTdvMMfAybyPEGNffdPCvQZALt376Zlq1Y0b94cB0dHBg0ejKGhIceOHdOZfu/evdSsVYtPP/0UBwcHunbtiqurK/v37wcyyn7Pnj107NgRX19fnJ2dGTFyJFFRUfzy888FiunfrucmJibMmj6VRu+8g33Finh5ejKwf19uBwfz9OnTAsWUnp7OkX3baduhB7XqNcTB2Z3+X01EFR3J5bzqVM36dOjcj9q+jXNN06BRC6r41KGCtR0VHVz4otcwEhPieXg/OM+Ytu07TOtmjfmgaUOc7e0Y1a8HRoaGHDihOx4vdxcGdv+c997xxaCEwb+Spy7p6ekc3PsDn3zWhTq+7+Dk7MrgEeNQRkdx6ZdzuW63f/f3vNfyQ5o0ex97Byf6DBqBoZERJ48d1KS5dfMvWrX+BHcPb6xsbPm0YzeMTUpzNzjvDoj09HT279lF+46dqevbACdnV4aNGE10VCQX8ohp7+4dNG/5Pu81b4mDgxP9Bw3D0NCQH48d0Up3904we3f9wOBhowpYSrBz915atWyuqedDNfVcdxuxR9N2ZtTz7l064+bqwr4DmeXTpHGjLO25A31793ql9rw4tgfp6ens3bObzzp2op5vfZydXRg+4muio6L45ZfzuW63Z/dOWrRsRbPmLXBwcGTgoKEYGhpy/NhRAJycnBk7fgJ16/piY2NLNZ/qdO3Wg0sXLxboj8XiVqd+2HuAD5o3pdV77+LkYM/wAX0wMizJ4R9P6ky/c/9B6tTwoePHbXC0r0jPzh1xd3Fh98HMONYGfEfdmtXp16ML7q7O2NlY06BubczNdHdg6vLdgeO0afo2H77bAOeKtozu/QVGJUty4Cfdx87bzYnBXT6lWYM6GBjobqcA9PX0sDQz1bzMypYpcEzp6ens27OLDh2/oJ5vA5ydXfhqxGiio6K4kEed2rt7Z5Zj58gAHceuZasPqVL1LaysrHF1c+eLrj2IjIjg6dPwfGM6fXgzzdv1oWqtJtg6etBpwAxilU/547fcR0v2HbOSOo3aYmPvhp2jJ536T0cZ+YTQezcA0NPTp6xZOa3XH7+ewKdeCwyNjPOMyaTh+yRc+InEX0+TGv6ImJ1rSU9JolSdXO6R6jRGz7g0yvULSLl/i+fKSJLvBpL6JLNTKy3+GWnPYjQvI+/qpEaGkXznZp6xZFUc7xGEyEo6IN5go0aN4vTp0+zdu5djx45x6tQprly5UuDtU1JSaNGiBWXKlOHs2bOcP3+e0qVL07JlS60e8hMnThAUFMTx48c5cOAAPXv25ObNm/z666+aNL///jvXr1+nR48ef3t/UlJSuB0cTA2fapr39PT0qO7jw43AIJ3b3AwMpLqPj9Z7NWtU52ZgYK6fcejwEUxMTHBxdipQTLeC71DD5y2tmGr4VMs1phuBQVrpAWrVqM7NXNKnpKRw6MgxTEyMcXXWPWQzu6fhj1Epo6jikzk02dikNK6VvLkd+GeB8iiohIR4FAoFxqULfvNTEGb1fIg8+YvWexHHz2FezwcAhYEBpjUqE3kiy018ejqRJ3/GrF71An1GSkoKwbdv45Oljujp6eHj40PgTd03A4E3b+asUzVratKHhYWhVCrxqZ4Zg4mJCR4eHrnWu+wxFXY9B4iPT0ChUGBSunS+MQFEvKhTlavV1ryXUacqczvo1aa85CU1JYWfju7B2KQ0js65D51OSUnl1p371KpWWfOenp4etd6qzF9BeXdcFHaeT8OeoFJG81aW88/EpDTuHl7cyuX8S0lJ4W7wLa1t9PT0qOpTk6DAvzTvVfKqzPkzJ3n2LJa0tDTOnT5BSnIylav65BlTeNgTlMpoqvlkDi83MSlNJQ8vgm7eyDWmO8G3tLbR09Ojmk8NggIzt0lSq5k/Zzp9BwzB3KJgo49e1vPq2c696j7Vcq23NwIDqZ7lvACoVaNGPu350Rftef5tZ3FsDwDCw8JQKqPx0Tp2Jnh4eOYaV0pKCsHBt/HxyfzcjH2pTmBg7n/oxMfHY2xsjL6+fgHiKj51KuNafJea2a/F1d7ir0DdnXM3Am9Rs5r2tbh2jWqa9GlpaVz47QoVbW0ZNXEa7br0ov/IMZy7cCnfeDRxpaYSdPchtat6acVVu6oXf9y6W+B8dAkJe8qHfUfx8aCxTFiyhrDIqAJv+3ePXXDwLa16+PLYBQbq3katTuTE8SNYWVtTrlzeU1ainobyTBVJpSq+mvdKGZfB0fUt7t++VuB9S0yIA8C4tO5OopC7f/HoQSB13/0474z09TGo6EzS7Sxtdno6Sbf+pKSj7muTYeWapDy4jenHPagwaTnlRs7GpGkbyG0Uj74+pWq+TcKl0/nu10vF9R7hv0Chp1dsX/9vZA2IN1RcXBxr164lICCApk2bArBx40YqVsx7bl9W27dvJy0tjTVr1miGQK5fvx4zMzNOnTpF8+bNgYwboTVr1lCyZOaQxBYtWrB+/Xpq166t2a5Ro0a4uLjo/KykpCSSkpKyvZeMoWFmnrGxGTfcZmbmWunMzcwICQnVma9SqcLczCxHeqVSpfXehUuXmDl7LklJSVhYmDNz2hRMTfP/hiMm9hlpaWk6PsOUkNDcYzLTkT462/DTC5d+Zfqc+RkxmZsze+pkTE1zH46pFZcyY7ifqZn2jZupmQUqZbSuTf6W5OQkvtvwLfUbNsPYuGBzhgvK0KocSeGRWu8lhUdiYFoGPSNDDMxN0StRgqSnUdnSRGHiobueZfeyTpmba9cpM3PzPI6fEjMd6ZVKpeb3gM48X/6uIDEVRj1/KTk5mbXrN9C4UUNMjPP+BugllTKjnHXXqYLf+Obmyq/nWDrXj+QkNWbm5fhmyhLKlDXLNX3Ms2c8T0vDItt5amFWlgePHv+tGP6tPJUvyiN7Pcnr/HsWG0Na2nNMsx13MzMLHoVkfns24pvJLJg9iR4dP0RfXx9DQyNGjZ+GjW3ebfvLupej7prlXi9jY2My6qKObUJDQjQ/r139LZ5elanr2yDPGLTzjs2l7TQjJORRLvuQs56bmZkRrczZds7I0p7PmjalQG1ncWwPMvKIfrGNmXYeZuaocj12sQU6dlnFxMSw7bsttGz1fgHjKj51KvNarH3umpuZ8vCR7voUrVLpSJ/ZbqpiYkhMVPPdzj307NyRvt2+4NKVq0yYOY8F0yfiU6Wyjly1qWLjMtqUbFMpzM3KcP/xkwLtmy6V3Z3xG9AdB1tropQxrN2xn34T5rJl/iRMShnlu33ux85MU9+yy+vYPcpWpw4d2MuGdatRq9XYVbRnyvQ5eY7mAHgWk3G9L22qveZAaVNLnqkidW2SQ1paGns2zcLZozo29ro7CS7+tAsrOxecK+X9RYWeSRkU+vqkPdOewpMWF0OJCrY6tylhWQF9N28Sr5wnes0cSpSzwvTjHij09Yk7titHeqMqtVAYGZP4a8E7IIrrPYIQWf3/damIArlz5w7JycnUrVtX856FhUWeC2lld+3aNYKDgylTpgylS5emdOnSWFhYoFaruXMncwGeqlWranU+APTu3ZvvvvsOtVpNcnIyW7dupWfPnrl+1syZMzE1NdV6LV+58hX2+J/xeestvvVfzMJ5c6hVoybTZ83OdS7d61LtraqsWLKQRXNnUbtmdabNnpvr3Ohzp47SvX1TzSs1NbXQ40tNTWXxbD/S09PpOaDgw65F0UpNTWX6zNlAOoMHDsg13flTR+jZ4V3N6/nzwq1T3lVrMmPRJibOXs1bNerhP3scMap/r7OsMJ356RidP2mheRVk+PrftW3zWuLj4pgwfSGzF63mw3YdWDBrEg/uay+KduqnH/ns4w80r8I6fhcv/Mz1a1f5su/AQsn/76j2VlWW+y9i0bzZ1KpRg2mzZufadhZHP/10gk8//kjzSi3E+vRSQkI8kyeOx8HBgU5fdNGZ5k2rU2lp6QDUr1uL9m0+xM3FmU6ftsO3dg32H9Y91P11qV+9Kk19a+HuWJF6PpVZMGYIz+ITOPHLbzrTn/rpBB0+/lDzKuz2vNG7TVnkv4IZsxdgZ1eROTOn5lhb4vK5A4zuXlvzev4v3LfsXD+NJyHBdB08V+fvk5PVXP75EHUb5zP64e9SKEiLiyXmhzWkht5DffUCcT/uxdi3qc7kxnXfJSnwGmmxqsKJ528o6D2CEHmRERAiVwqFgvT0dK33UlJSNP+Pi4ujZs2abNmyJce25bOs/qxrtezWrVtjaGjI7t27KVmyJCkpKXz66ae5xjJmzBiGDx+u9d6TLN/6AZQtWxY9Pb0cC1UpVaoc3y69ZG5uluPGMyO9mdZ7RkZG2NnaYmdri5enJz169+HIseN07NA+15gBTMuWQU9PT8dnxOQZU/bODaUqBotsvdmljIyws7XBztYGb08PuvXuz5FjP/J5h5zlWLPO27hVyvw2JiUl40Ifo4rG3KKc5v0YVTROLrkPay+ojM6H8UQ+DWP8dP9/ffQDZIx2MLQqp/WeoVU5UmKekaZOIjlSSVpqKoYVLLOlsSQprGDflrysU9m/rVMplVjkevxyfuuoUio1x/vlv0qlEossQ4dVSiUurvk/SaEw63lqairTZ80mPOIpc2ZMz/ObjRp13sE1S51KTc1oG3TVKcd/oU4ZGZXC2tYea1t73D2rMLzvp5w6vp827bvpTG9apgz6enpEZ1tcMFoVi2W2b3oK6u/mWbvu21pPqkh90Y6qlEod55+bzjzKlDVFT09fa8FJAJUqGjPzjHoU9uQRhw/sYuG3G7F3zJhS4OTixs0/r3PkwG76Dspc6LNO3fp4eGQO+07JEpOFhWWW/JU4u+iul2XLmmbUxez1XaXUDIv/49rvhD15TKf2H2mlmT1jMt6VqzJ99oJc8i6bS9upwiJbvX1JVz1XqVQ5ztVS2drz7r37cuTYcT7Ppz0vLu1B3bq+midVQNZjp3qFY1c232P3UkJCAhP8xlHK2JhxfpMoUUL3rWNxrlOZ12Ltczfj2mqmMxYLMzMd6TPbTdOyZdDX18fJXvvJNQ4VK/LHjYJNnzErWzqjTVFpLzipVD3D8hXWkchPGRNjHGytCA3TPV+/Tl1frSdVpOZ67FS4/I1jZ2ahfX6YmJTGxKQ0tnYV8fD0olOHdvzy8zkaNW6iSVO55ruMdMucApP64r4lLiYKU/PMe8y4mChsnfL/8mzn+uncuHKaQRM3YmZprTPNtYvHSElKpHbDj3T+Pqu0+GekP3+OXhnt46RX2pS0Zyqd2zyPVcHz55Dl3jr16SP0y5qDvn7G717QNy9HSfcqKDcszDeWrIrLPcJ/kUKv4Iski39GRkC8oVxdXTEwMODixcxVdZVKJbduZc6FLF++PE+eZA4BvH37NgkJCZqfa9Sowe3bt6lQoQJubm5ar/ymJ5QoUYJu3bqxfv161q9fT8eOHSlVqlSu6Q0NDSlbtqzWK+v0CwADAwPc3dz4/ep1zXtpaWlcvXoN71wesebl6cnVa9pzB6/8fhUvz5yP+8oqPS1dqzMmNwYGBlRyc+X3a9ox/X7teq4xeXt6aO1DZkx5X2DT09NyjamUsQnWthU1r4oOzpiZW/LntcxvQxIS4rlz6wbunvk/2jAvLzsfwh6HMG7aYsqU/fduorJSXbiKZZN6Wu+Va1of5YWrAKSnpBBz5S/KNcmcL4pCgeW7vqgu/F6gzzAwMMDN3Z1rV69q3suoU1fx9PLSuY2nlxdXs6SHjDVOXqa3trbG3NxcK8+E+HiCgoLyrXcvYyqMev7yxuLR48fMmj6NsmXzHpKeUafsNS87+4w69de1zLVdMurUX7h7VM13v15Venq65oZUFwODElRydeLy9cy5x2lpaVz+4y8qe+j+Iz8/fzfPUsbG2NhW1LwqOjhhZm7BH9cua9IkJMRzO+gmlXI5/wwMDHBxq8QfVzO3SUtL44+rV/DwzOgISkpSA+R4KoCevh7padqdycbGxtjY2mle9g6OmJtbcP1a5jpACQnx3Aq6iYeXN7oYGBjg6laJ69cyz6e0tDSuX/0dD8+MbT5p/zmLl61m0dJVmhdAz979GfJV7iOjXtbzq1cz621GPb+e63ni7emp1dbCv9+eF4f2wNjYGFtbO83L4cWxu5rlOCQkxBMUFJhrXAYGBri5uXPtmva+XLt6FU/PzG0SEuLxGz+GEiVK4Ddhco7RjNnjKq51KuNa7MKVa39o5Xvl+h9U9tT9aEJvz0pcua69fs3lq9c16Q0MDPB0dyUk2xSO0MePsaqg3TmeG4MSJfBwceDXPzM7LNLS0vj1z5tUrVSwqYIFkaBW8ygsItdOjex16uWxu5atTuV37NzcKnEty/F+eew8PXVvkyGddNI1nR4vGZUyoby1g+ZlXdGVMmbluPXnBU0adUIcD+5cx8m9WvZMM3NPT2fn+un88esJBoxfh2WF3KejXfxpF5VrvkvpsgVYq+b5c1JC72HonmWqjUKBoXtlkh/c1rlJyr1b6Jez0lrzQb+8Dc9jlFqdDwClajciLS6GpJsFu195qbjcIwiRF+mAeEOVLl2aXr16MWrUKE6ePMmff/5J9+7d0cuy0EmTJk1YunQpv//+O7/99hv9+vXTmqP3xRdfUK5cOdq0acPZs2e5d+8ep06dYsiQIYTmMh82qy+//JKTJ09y5MiRPKdfvIqP27Xl8NGjHP/xBA8fhuC/7FvUajXNm2U8I3vO/AWs27BRk77tRx/x2+Ur7Ni1m4chIWzespXbwcG0+fBDANRqNes2buJmYCDhT59y+3Yw8xctJjIqinfeLtjc00/atuHQ0eMcO3GSByEhLPl2BWq1mhbvZQy5mz1/EWs3bNakb/dRa3698js/7NrDw5BQNm35jlvBd2jzYca820S1mrUbN3MjMIjwp0+5FRzMvEX+REZF07CAMSkUClp91IE92zfy28WzPLx/h+ULpmBuUY5a9Rpq0k0bN5ijB3ZoflYnJnD/7i3u383oqIoIf8L9u7c0T7hITU1l0ayx3A0OZNDISaSlpaFSRqFSRuW4uchO38SYstU8KVst44Jn7FyRstU8MbK3AcBj2nCqrZ+tSf9g1TaMne3xnDkKEw8XHPt1wqZ9K+4t3qBJc2/Reux7dcCuS1tKe7pQZdkkSpiUImRjzrmWuWnXrh1Hjhzhx+PHefjwIcuWLiUpKYlmzZoBMG/ePNavX69J36ZNGy5fvsyunTsJCQkhICCA27dv07p1a03Zt23blm3btnHhwgXu3bvHvPnzsbS0xLd+/QLF9G/X89TUVKbOmMWt28GMHjmStOdpREcriY5WFugPs5f71fKjz9jz/QYuXzzDw/vBrFg4GTOLctTMUqdmjB/EsQM/aH7OWaceZ9SpiIw6pVYnsn3Tcm4H/knE0yfcCw5k1eJpKKMiqPu27mGrL3X8qBX7j5/i8Mmz3A95xLyVG0hUJ/FB04x4pi5ewYrN2zXpU1JSuX3vAbfvPSAlNZWIKCW37z0g9El4gfMsaFl90KY9O7dt4tcL53hw/w7+86djbmFJHd/Mx8hOGjuMw/t3an5u3a4DPx49wKkfDxP68D6rl80nSZ3Iu80y2ga7io5Y29qxcuk8bgfdIOzJI/bt2sb133/Tyje3mFq3/Zjvt23h4oWfuX/vLovmzcLCshz1smzrN2YkB/fv0fzcpt2nHDtykJM/HiXk4QNWLFuEOknNe81aAGBuYYGjk7PWC6B8+QpYWdvkGdMn7dpw6Ogxjr2o50uWLc9oO5tlHPc58xeyVquet85Sz0PZtGUrt4KD+ejDD4CMtjNre34rS3ve8O28y+el4tgeKBQK2rRtx/ZtW7l44Rfu37vHgnlzsLC0xDfLGgljx3zN/v17M8ur3SccPXKIEz8eI+ThQ75dtkTr2CUkxOM3bgxJajVDhw0nMSEBZXQ0yujoAk0jKm51qn2bDzlw7ARHTpziQUgoC5evRq1OomXTdwGYsdCf1RszR3R+0voDLl25yve79/Mw9BEbtn5PUPAd2n3QUpPms3Yf8dO5nzlw9EcePX7C7gOH+fnSZdq+3yLf8nnp8w+bse/EWQ6e+pl7oU+Ys2YL6qRkPmiccewmL13Ht1szr1kpqancuh/CrfshpKamEhGt4tb9EEKyjG5YsukHrtwI4vHTSK4H3WH03OXo6enR/O06BYpJoVDwUbZjt3DebCwsLamXpU6NHzOKA1rH7hOOaerUA5YvW4w6SU3TZhllFvbkMT9s30rw7VtEPA3n5o2/mD1jKoYlS1Kzdt6xKRQKGrXqwvE9q/jzt594/PAWW5aPpax5BarWyrwWfDutF2ePbtX8vHPdNH47d4DOg2ZjWMqEWFUksapIkpPVWvlHhD3kbuBl6r1b8KdkxZ85hHHddylV6x1KVLCl7Cc9UZQ0IvHFopGmn/enzPufZab/5Th6xiaUbdsV/XLWGHr5ULppGxLOZ3uKjkJBqdoNSfztLKSlFTiel4rjPYIQWckUjDfY3LlziYuLo3Xr1pQpU4YRI0YQk2Vo8fz58+nRowfvvPMOtra2LF68mMuXM799MzY25syZM4wePZqPP/6YZ8+eYWdnR9OmTQvUM+ru7k79+vWJjo7WWovin2jc8B1iYmLYFLAFpVKJi4sL06dM1gw7i4iIQC9Lz3Nlby++GTWSjZsD2LBxE7Z2tkwcPw4nJ0cgY+Xg0JBQpp44QWxMLGXKlqWSuzvz58zCydGxgDG9jSomho0B36FUKnF1cWbGlImaoW1PIyK0hn1V9vJkzKjhbNi8hfWbArCztWXSuG9wfhGTvp4eIaGPOH5iNrGxsZQpWwYPd3cWzp6Bk6NDgcuq9SedSVKrWbN0NgnxcXh4v8U3kxdQsqShJk142COeZZl7eDc4kKljB2l+3rx2CQANm7xP/6/Go4yK4PLFjMerfTNEe2i834yleFetQW5Ma1bB90RmR4z3vLEAhGzaxfVeYzC0KU8p+8yby8T7ofz6UV+854/BaXBX1KFh/NF3PJHHMx/v9uSHw5Qsb0GliUMwtC5P7LWbXPrwS5KfFnxRxEaNGhEbE8PmgACU0dG4uLoyZerUzDr19KlWnfL29ubr0aPZtHEjGzZswM7ODj8/P5ycnDRpPm3fHrVajf+SJcTFxVG5cmWmTJ2a57eLWf3b9TwyKooLL0ZDDRg8ROuz5sycQbW3CjaC4cOPu5CkVrN22SwS4uOo5P0WoyctylanQrPVqZtMH5c5lztg7WIA3mnyPv2GTUBPT4/Hofc5e/IQz2JVlC5rioubF36zVlDRIe9vCJu+XQ9V7DPWbNtJtDIGN2cH5k8YhcWLbwHDI6K0yilSqaTH8PGan7/be4jv9h7Cp7InS6eNK1CeBdX2004kqdWs9J9HfHwcnt5VGT91nnZZPXlMbGxmm9ygYVNiY1RsC1iHSpkxXWPclHmaKRglSpRg3KQ5BGxYyawpY1AnJmJta8eg4WOpUds3RwzZffxpR9RqNd/6LyA+Lg6vylWZOGWmVr0Me/KY2CzXiXcavUtsbAxbN29AqcwYWj9xyixNTP9EZj3fmqWeT9LU86cREVqjPSp7ezFm1IiMtnPjZmztbJk0fqx22xkSyvETJzXtuYe7GwvmzCpw21kc2wOATz7tkJGH/yLi4+LwrlyFKVNmZDt2T7SOXcNGjYmJjSFg8yZN+U6ZMl2zL8HBwQQFZXwz37tXd63PW7t+E1ZWuoexZ1Wc6lSTdxoQExPLhq3biVaqcHVxYvakcZopPU8jIrWOXRUvD8aPGMq6Ld+xZvNW7GxtmDr2a5yz1JV3fOvyVf8+bN2xG//V67C3s2XyNyOp6q175IkuzerXRhX7jNXf7yNKFYu7U0UWjh2C5YuFKcMio7XqeUS0iq5fT9X8vGX/MbbsP0Z170osn5QxzepptJIJi9cQ8ywes7Klqebpxprp32D+Co/i/PjTz1Cr1SzzX6ipU5OmzMr32MVkOXYuLq5MmjJTU6cMSpbkxl9/sm/vLuLj4jAzM6dylarMnr8kx6KJujRp3ZPkpES+XzOJxIRnOHvUoO83KzDI0m5GhocQ/yxz+sH5HzM6mZdN1X7K2uf9plGnUVvNz5dO7cLUwgqPtwrW8QegvnqBWJOylG7xKfplzUh59IDo1bNIi8uYUqNvZgnpmR0IaapoolfNpmybzpQfOYvnMUrizx4h/uQ+rXxLulehhEV5Ei6eKnAsWRXXe4TiTqZgvD6K9OyT/MUbrXHjxvj4+LBo0aJC/6z09HTc3d0ZMGBAjvUdCuJ+Ps+1Lwp66YW/GNirikyvUNQh5PCkcsEv8K+LZ9Dhog5BJ/20wl8w9FVFPs/7cWlFwfG57iGvRSmsZME6KV8nA0Xx/LaqVHp8UYeQQ6pe3qvyF4W09Pwff/m6Paf4xVQ2tXguUFtKXbAnm7xOT0v/e1M9/i13YvLv3Hrdqm/Rvd5QUUrqP6moQ9DJyU33tKbi7kGftkUdQq4cV+0p6hD+VTICQhSJiIgItm3bRlhYGD169Mh/AyGEEEIIIYQQ/2nSASGKRIUKFShXrhyrVq3KdVVeIYQQQgghhBD/P6QDQmg5derUa/kcmfkjhBBCCCGEEG8WeQqGEEIIIYQQQgghCp2MgBBCCCGEEEII8cZS6Mn38q+LlLQQQgghhBBCCCEKnXRACCGEEEIIIYQQotDJFAwhhBBCCCGEEG8shZ6iqEN4Y8gICCGEEEIIIYQQQhQ66YAQQgghhBBCCCFEoZMOCCGEEEIIIYQQQhQ66YAQQgghhBBCCCFEoZMOCCGEEEIIIYQQQhQ6eQqG+M96rlf8qm9aun5Rh5CDqSKmqEPIwTTocFGHkEOgR6uiDkEnz2JYVuZ6yqIOIYdYg3JFHUIOxsQXdQj/Gc/ldqRA9Ekt6hBy0FM8L+oQckg0KF3UIehUHOMqQUpRh5CDh1lIUYeQQ3L/iUUdQg7pCvke+d+k0JPyfF2kpIUQQgghhBBCCFHopANCCCGEEEIIIYQQhU7GPAohhBBCCCGEeHMpFEUdwRtDRkAIIYQQQgghhBCi0EkHhBBCCCGEEEIIIQqdTMEQQgghhBBCCPHGUujJFIzXRUZACCGEEEIIIYQQotBJB4QQQgghhBBCCCEKnXRACCGEEEIIIYQQotBJB4QQQgghhBBCCCEKnXRACCGEEEIIIYQQotDJUzCEEEIIIYQQQryxFHryvfzrIiUthBBCCCGEEEKIQicdEMVUeno6ffr0wcLCAoVCwdWrV4s6JCGEEEIIIYQQ4m+TKRjF1JEjR9iwYQOnTp3CxcWFcuXKFXVIhaJx48b4+PiwaNGify3P9PR0AjZv5siRI8THx+Pt7c3AQYOws7PLc7v9+/ezc8cOlEolzi4u9O/fHw8PD83vk5OTWb16NWdOnyYlJYUaNWsycOBAzM3N841p//797Ni5E6VSiYuzc468szt79iybNm8mPDwcO1tbevTsSZ3atbX2cXNAgNY+Dho4MN99zKq4llNeeWd39uxZNm/aRHh4OLZ2dvTs0YPader84318yeLtWriM6IVpjSoY2Vbgt08GEL7vRN7bNKyD97xvKO3tjjrkCcEzlxO6abdWGsf+nXAZ3gtD6/LEXg/kr2FTifn1jwLF9E/37U06fsU1pn+ST2Eev+IYk7SdRVNO58+f5+ChQwQHB/Ps2TOW+vvj6upagNIp+P7qiulNPfeKY1lJORXMvgMH+WHnbqJfnHsD+/XB06NSrunPnD3HhoAthIc/xc7Wli97dKNO7Vqa32/aspVTZ84SERGJQYkSuLu50b1rZ7w8c9/PHDHtP6DVHgzo3y/Pcjpz9iybNgdo2oOePXtotQfnzp/n0KHD3H7RHizzX/LK7cF/gUJPUdQhvDFkBEQxdefOHWxsbKhfvz7W1taUKKHdV5ScnFxEkRV/O374gX379jFo8GAWLlqEkZERfuPH51lmp0+fZvWqVXT64gv8/f1xcXbGb/x4VCqVJs2qlSu5dPEiY8aOZfacOURHRTFt2rR84zl9+jSrVq/mi06d8Pf3x9nFhfF+flp5Z3Xjxg1mzZ5Ni+bNWervj6+vL1OnTuX+/fuaND/s2MG+ffsYPGgQixYuxMjIiPF+fq9UL4pjOeWXd1Y3btxg9qxZNG/RAv+lS3WW09/Zx6z0TYyJvR7En0MmFyh9KaeK1N63kqhTFzlXqw33/DdSdeU0yjV7W5PGpn0rvOaO4fa0ZZyr045n1wOpe3AtJctbFOgz/sm+vWnHrzjG9E/yKczjVxxjkraz6MpJrVZTuXJlevboUdBieeX9zR7Tm3ruFdeyknLK36kzZ1m5ei2dO3Xk2yULcXF2YqzfRJS5xPTXjZvMmDOPls2bsXzJIur71mXStBncu/9Ak6ainR2D+vVl1TJ/FsydjZVVBcb4TUQVE1OgmE6fPsPq1avp3KkTS/2X4OLizLh824M5tGjenGX+S/D19WXK1GnZ2oMkKlf2/tvtgRDZSQdEMdS9e3cGDx7Mw4cPUSgUODk50bhxYwYNGsSwYcMoV64cLVq0AGDBggVUrVoVExMT7O3tGTBgAHFxcVr5rV69Gnt7e4yNjWnXrh0LFizAzMxM8/tJkybh4+PDunXrcHBwoHTp0gwYMIDnz58zZ84crK2tqVChAtOnT9fKV6VS8eWXX1K+fHnKli1LkyZNuHbtWo58N2/ejJOTE6ampnTs2JFnz55p9vP06dMsXrwYhUKBQqHQavD+jvT0dPbs2UPHjh3x9fXF2dmZESNHEhUVxS8//5zrdrt376Zlq1Y0b94cB0dHBg0ejKGhIceOHQMgPj6eY8eO0bt3b3x8fHB3d+er4cO5eeMGgTdv5hnT7t27adWyJc2bN8fRwYHBgwZp5Z3d3r17qVWzJp9++ikODg507doVV1dX9u/fn+s+jhwxgqioKH7+5Zf/dDnllbeucqpZq9YrlVNB9jGriKNnuDVxEeF7fyxQesc+HUm8F8rNr2cTF3iXB99uIWznUZyHdtekcR7Wg5C13xO6cRdxN+/wx4CJPE9QY9/9kwJ9xj/Ztzft+BXHmP5JPoV5/IpjTNJ2Fk05ATRt2pQvOnWievXqBSqXV91fXTG9qedecSwrKaeCldPO3Xtp1bI5LZq9h6ODA0MHDcDQyJCjx3TfM+zZt5/aNWvQ4ZOPcXCwp3uXzri5urDvwEFNmiaNG1Gjug82NtY4OTrQt3cvEhISuHfvfoFi2rV7Ny1btqR582ZZ2gMjjuZSTnv27qNWzZq0//QTHBwc6Na1C26uruzbf0CT5r2mTV60Bz4FikGI/EgHRDG0ePFipkyZQsWKFXny5Am//vorABs3bqRkyZKcP3+eFStWAKCnp8eSJUv466+/2LhxIydPnuTrr7/W5HX+/Hn69evH0KFDuXr1Ks2aNcvRkQAZIy4OHz7MkSNH+O6771i7di0ffPABoaGhnD59mtmzZzN+/HguXryo2aZ9+/Y8ffqUw4cPc/nyZWrUqEHTpk2Jjo7WynfPnj0cOHCAAwcOcPr0aWbNmqXZT19fX3r37s2TJ0948uQJ9vb2/6jswsLCUCqV+GS5aTIxMcHDw4ObgYE6t0lJSSH49m18fHw07+np6eHj46O5IN6+fZvU1FStfO3t7SlfoUKu+b7M+3ZwsM68c9vuZmCg1ucA1KxZU5P+5T5Wz5Lny33M7wL+UnEsp/zyzi7w5k2tMoCMcnqZ/u/s4z9lVs+HyJPaf8hEHD+Heb2MOBUGBpjWqEzkiSw3N+npRJ78GbN6Bb/Rl+OX//ErjjG9VNyOX3GMSdrOoiunf0rOvQz/1bbz7+bxppXTy3OveraYqvtUy3X7G4GBVPeppvVerRo18izTQ4ePYmJigouz8z+IKe/2IHvHQs2aucf0/0yhp1dsX/9vZA2IYsjU1JQyZcqgr6+PtbW15n13d3fmzJmjlXbYsGGa/zs5OTFt2jT69evHt99+C4C/vz+tWrVi5MiRAFSqVImff/6ZAwcOaOWTlpbGunXrKFOmDN7e3rz77rsEBQVx6NAh9PT08PDwYPbs2fz000/UrVuXc+fOcenSJZ4+fYqhoSEA8+bNY8+ePezYsYM+ffpo8t2wYQNlypQBoEuXLpw4cYLp06djampKyZIlMTY21tpPXZKSkkhKSsrx3svPfkmpVALkmEtoZm6u+V12sbGxpKWl6dwmJDRUk2+JEiUoXbq0VhpzMzOUWTpcCpq3uZkZoSEhOrdRKpWYZxmhovmcF/Hnto9Z0+Tnv1JOWfPWtQ9mecT/d/bxnzK0KkdSeKTWe0nhkRiYlkHPyBADc1P0SpQg6WlUtjRRmHi4FPhz5Pjlf/yKY0xZP+dV8ynM41ccY5K2M0tsr7mc/ik59zL9F9vOv5vHm1ZOmph0nEshIY9yiUmVI72ZmRnR2T7vwqVfmTF7LklJSVhYmDNr2hRMTcsWOCYz85yfEZJHe2CmI6bCuk8SAqQD4j+lZs2aOd778ccfmTlzJoGBgcTGxpKamoparSYhIQFjY2OCgoJo166d1jZ16tTJ0QHh5OSk6SQAsLKyQl9fH70svW5WVlY8ffoUgGvXrhEXF4elpaVWPomJidy5cyfXfG1sbDR5vIqZM2cyebL2PPzBQ4bwVtWq+Pv7a97LnkZk+OnkSSmn/zA5fv9txfH4FceYiiMpp/82OX4FI+VUvFR7qyrL/RcRGxvLoSPHmDZrNksWzMvReSHEf5V0QPyHmJiYaP18//59PvzwQ/r378/06dOxsLDg3Llz9OrVi+TkZIyNjQuct4GBgdbPCoVC53tpaWkAxMXFYWNjw6lTp3LklbUnNa88XsWYMWMYPny41nuhjx7x/PlzPDw9Ne+lpKQAGT26FhaZi/qplEpcclmxt2zZsujp6eXo7VUplVi86Bk3NzcnNTWVuLg4rZ57pUqFuUXuiwfmlnde25mbm+dYwEipUml66V/+m30flSoVri66v0WvW6/ef7Kcsuadnbm5OSod6fMrp7z28Z9KCo/E0Er7iTWGVuVIiXlGmjqJ5EglaampGFawzJbGkqQw7ZETWcnxe/XjV5xiKo7HrzjGVJC8pe0sWN7/pJz+KTn3/nttp5TTP7jG6DiXLLKNQMiMySxHepVKlWMfShkZYWdri52tLV6ennTv3Zcjx47zeYf2BYpJpcz5GeYWeZSTjpj+rfZACF3+/yaVvEEuX75MWloa8+fPp169elSqVInHjx9rpfHw8NCsIfFS9p//jho1ahAWFkaJEiVwc3PTer3KI0NLlizJ8+fP801naGhI2bJltV6GhoYYGxtja2ureTk4OGBubs61q1c12ybExxMUFIRXlotrVgYGBri5u2ttk5aWxtWrV/H08gIypr+UKFGCq1nShIaGEvH0aa75vszb3c2Nq1kW53yZd27beXl6an0OwO+//65Jb21tjbm5uVae8QkJBAUFaeLN7r9QTvnlnZ2nl5fOcnqZ/mU5vco+/lOqC1exbFJP671yTeujvJARQ3pKCjFX/qJcE9/MBAoFlu/6orrwe675yvEr2D4W15iK4/ErjjFlz1vazqIpp39Kzr0M/6W2U8qpYPuYPSZ3NzeuXs1+7l3PdXtvT09+v3Zd670rv+d+rr6Unpau6RQqUEzXrmaLKb/24JrWe1f+xfZACF1kBMR/mJubGykpKfj7+9O6dWutxSlfGjx4MA0bNmTBggW0bt2akydPcvjwYRSKf/as2/feew9fX1/atm3LnDlzNJ0fBw8epF27dtSqVSv/TMiYonHx4kXu379P6dKlsbCw0Jr28aoUCgVt27Zl27Zt2NrZYWVlxebNm7G0tMS3fn1NujHffEP9+vVp/dFHABlPB5k/H3d3dyp5eLB3zx6SkpJo1qwZkDH6pHnz5qxevZoyZcpgbGzMiuXL8fLyyvXi91K7du2Yv2AB7u7ueFSqxJ69e7XynjdvHpaWlvR48XijNm3a8PXo0ezctYs6tWtz+vRpbt++zZDBg3Pso52trdY+1vf1zTWO/0I55ZW3rnIa/fXX7Nq5k9p16mjKafCQIa+0j3nRNzHGxM1B87Oxc0XKVvMkOToGdcgTPKYNx8jOims9RgPwYNU2HAd8gefMUYRs2Em5d+th074Vv37UV5PHvUXrqbZuNqrLfxLz63WchnSjhEkpQjbuKlBMr7Jvb/rxK44xvUo+r/P4FceYpO0smnICePbsGU+fPiXqxbz80Bfz7M3NzbW+Lc4rJjn3/rttp5RTwcrpk3ZtmLtgEe7ubnhWqsSuvftQq9W0aNYUgDnzF2JpaUGv7t0AaPtRa0Z+M5Ydu3ZTp3ZtTp05w63gYIYOHghAolrNd9u/x7duHSwsLIiJiWX/wYNERkXR8O23c40jq4/btWNelvZg9969qJPUNH9RTnPnzcfS0pKePbpnxNTmI0aN/kbTHpw6fYbbt4MZmmd7kLHGRUHbAyGykw6I/7Bq1aqxYMECZs+ezZgxY2jYsCEzZ86ka9eumjQNGjRgxYoVTJ48mfHjx9OiRQu++uorli5d+o8+W6FQcOjQIcaNG0ePHj2IiIjA2tqahg0bYmVlVeB8Ro4cSbdu3fD29iYxMZF79+7h5OT0j2L7tH171Go1/kuWEBcXR+XKlZkydSolS5bUpHny5AkxsbGanxs1akRsTAybAwJQRkfj4urKlKlTtYag9enbF4WeHtOnTSMlJYWaNWsyYODAfONp1KgRMbGxBGzeTLRSiauLC1OnTNHk/TQiQmuFW29vb0Z//TUbN21iw4YN2NnZ4efnp1Uu7T/9FLVazRJ/f80+Tp0yRWsf/4vllFfeEU+fopel48zb25uvR49m08aNuZZTQfYxL6Y1q+B7YnPmZ84bC0DIpl1c7zUGQ5vylLK30fw+8X4ov37UF+/5Y3Aa3BV1aBh/9B1P5PFzmWX6w2FKlreg0sQhGFqXJ/baTS59+CXJ2RamzI8cv/wVx5heJZ/XefyKY0zSdhZdOV24cIEFCxdqfp41ezYAX3TqROfOnQsUk5x7/922U8qpYOXUuOE7xMTEsClgK0qlEhcXF6ZPmaR97mWJqbK3F2NGjWDD5i2s37gZWztbJo0fi7OTIwD6enqEhIRy/MRJYmNiKVO2LB7ubiyYMwsnRwddIegop4bExMaweXOAJqZpOdoD7XIa/fUoNm7azIYNG7G1s2OC33itcvrlwgUWLFyk+XlmlvagS+cvChTXf0HWchGFS5Genp5e1EGI16t3794EBgZy9uzZog7lH7lz925Rh5CDohieTun/cLTLmyLQo1VRh6CTZ9Dhog5BiEInbWfBSDkJUTRKpOU/BeJ1S1PoF3UIOjm7uhV1CH9L+OguRR1Crqxmb84/0X+IjIB4A8ybN49mzZphYmLC4cOH2bhxo+YxnUIIIYQQQgghxOsgHRBvgEuXLjFnzhyePXuGi4sLS5Ys4csvvyzqsIQQQgghhBCiyMkUjNdHOiDeAN9//31RhyCEEEIIIYQQ4g0nj+EUQgghhBBCCCFEoZMREEIIIYQQQggh3lx68r386yIlLYQQQgghhBBCiEInHRBCCCGEEEIIIYQodNIBIYQQQgghhBBCiEInHRBCCCGEEEIIIYQodNIBIYQQQgghhBBCiEInT8EQQgghhBBCCPHGUigURR3CG0NGQAghhBBCCCGEEKLQSQeEEEIIIYQQQgghCp1MwRD/WfHPSxd1CDnoKdKKOoQcyqTHFHUIOaRT/Ia5eQYdLuoQdAr0aFXUIeRQ5+qmog4hB+Of9xd1CDkk+n5Q1CHkUDr8dlGHoNM9p6ZFHUIOJUkq6hByeF4Mb9uS0gyLOoQcSuklFHUIOumnpRZ1CDkkKkyKOoQc9Ch+91KlnscVdQg5PMa+qEPQybmoA/ibFHryvfzrIiUthBBCCCGEEEKIQicdEEIIIYQQQgghhCh0xW8snxBCCCGEEEII8Zoo9Irf9OD/VzICQgghhBBCCCGEEIVOOiCEEEIIIYQQQghR6KQDQgghhBBCCCGEEIVOOiCEEEIIIYQQQghR6KQDQgghhBBCCCGEEIVOnoIhhBBCCCGEEOLNpSffy78uUtJCCCGEEEIIIYQodNIBIYQQQgghhBBCiEInUzCEEEIIIYQQQryxFHqKog7hjSEjIAQAjRs3ZtiwYZqfnZycWLRoUZHFI4QQQgghhBDi1SxbtgwnJyeMjIyoW7culy5dyjO9SqVi4MCB2NjYYGhoSKVKlTh06FChxScjIIROv/76KyYmJoX6GRs2bGDYsGGoVKp/Nd/09HS2b1nLiaP7iY+Pw9OrKr0HjMDGzj7P7Y4c2MW+Xd+hUkbj6OxKz77DcPfw1vw+7MkjNq1dRuCN66SmpOBTsy49+w7DzNyiQDFtC1jHj0cPkBAfh4dXVfoMHI6tXcU8tzt8YDd7d25DpYzGydmVXv2G4u7hBcDT8Cf079lR53YjvplE/XfezTPvfQcO8sPO3UQrlbg4OzOwXx88PSrlmv7M2XNsCNhCePhT7Gxt+bJHN+rUrqX5/aYtWzl15iwREZEYlCiBu5sb3bt2xsvTI884sse0Y+cuTUwD+vXNN6aNAQGamHr16K6JKTU1lQ2bAvj1t994EhaGiYkJ1X2q0at7NywtLQscE2Qcv4DNmzly5Ajx8fF4e3szcNAg7Ozs8txu//797NyxA6VSibOLC/3798fDI7M8kpOTWb16NWdOnyYlJYUaNWsycOBAzM3Nc83T4u1auIzohWmNKhjZVuC3TwYQvu9EnnFYNKyD97xvKO3tjjrkCcEzlxO6abdWGsf+nXAZ3gtD6/LEXg/kr2FTifn1jwKUTqadh3/kuz2HiFbF4Opkz1dfdsHb3VVn2rsPQ1m7bRdBd+4TFhHJkB6d6NC6pVaaq38FsnXvIYLu3CdKqWLG6KE0rFvzlWLa/nswm34NIipeTaXyZnzdtDpVbPI/Z48GPmTMgYs0drNlQdsGmvej4tUsOXOdX+6HE5eUQvWK5RjdtDoO5mUKHNPOwz+yde9holUxuDk58FWvzni7u+hMe/fhI9Zs20XQ3fuERUQxpMfnfPZhC600m3Yd4PSFyzx49ATDkgZU9XCjf5cOONrZFDimbad/Y+PxC0TGxlGpohXfdGhOVSfd9fvH3wNZe/Q8IRFKUp6n4VjBnC5N69G6blWtND+cvcLNkDBi4hPZPqYXnvbWBY7npfT0dL4L2MDxIwcz2nPvKvQbOCzftvPQ/j3s3rld03b27j+YSi/aToBxo7/irz+uaW3TolVr+g/+qkAxFZf2IGtMWwI2cfTIYeLj4/DyrsyAgUPyjenA/n3s2vkDSmU0zs4u9O0/EA8PTwCePYtlS8Bmfr9ymYiIp5iamlLPtz6du3Qv8P1Bcbz2Fcfj929e+wA2b9nKqTNnNNdjNzc3enTtgucrXI+L67m3NWAjx44c0tTz/gOH5hvTwf172b3z+xf13JU+/QdR6UU9B1jmv5Brv18hOjoKI6NSeHp7071HbyraO+Qb0+6DR9i+ex/RShWuzo4M6dMTr0ruuaY/de4X1m3ZRtjTCCraWtOnW2fq1aqhleZBSCirNgZw7c8bPH+ehqN9RSaPGYFV+fL5xvNSeno6O7eu5qdje4mPj6OSV1V69v8aa9vc9+nmn79zcHcA9+4EoYqO5Kuxs6lVr5FWmp1bV/PL2R+JjgxHv4QBzm4edOjcDzePKgWOTRSu7du3M3z4cFasWEHdunVZtGgRLVq0ICgoiAoVKuRIn5ycTLNmzahQoQI7duzAzs6OBw8eYGZmVmgxygiI/zPJycn/Sj7ly5fH2Ng419+npKT8K59TGPbu3Mrh/TvpM3AkM+evxNCoFNMmjCA5OSnXbc6fOcHGNUtp/3l3Zi9eg6OzG9MnjCBGpQRArU5kmt9wFAoFE2csZurcb0lNTWHWlG9IS0vLN6Y9O77j0P5d9B04gpkLVmBkZMRUv5H5xHSSDauX0aFTN+YuWY2jsytT/UZqYrIsV4E1m3dpvT77ogdGpUpRvVbdPOM5deYsK1evpXOnjny7ZCEuzk6M9ZuIMpfOoL9u3GTGnHm0bN6M5UsWUd+3LpOmzeDe/QeaNBXt7BjUry+rlvmzYO5srKwqMMZvIqqYmHzL52VMq1av4YtOn7NsySJcnJ0Z5zch1w6qv27cZOacubRs3pxvlyymvm89Jk+bzv0XMSUlJRF85w6dPv+MZUsWMWHcGEJDHzFxyrQCxZPVjh9+YN++fQwaPJiFixZhZGSE3/jxeZ5vp0+fZvWqVXT64gv8/f1xcXbGb/x4rf1ZtXIlly5eZMzYscyeM4foqCimTcs7Pn0TY2KvB/HnkMkFir2UU0Vq71tJ1KmLnKvVhnv+G6m6chrlmr2tSWPTvhVec8dwe9oyztVpx7PrgdQ9uJaS5fP/Q/2lE+cusHT9Vnp0aMvaeVNwc3Jg+JS5KFWxOtMnJSVja1Wefl06YGlmqjNNYlJSRj69uxY4jqyOBoaw4NQ1+vh6s7VLM9wrmDJwxxmi49V5bvc4Jp6Fp65TvWI5rffT09MZvuc8oTHxLGzbgK1dm2FT1oR+358hMTm1QDH9eP4i/hu20bNDW9bNnYyboz3Dp85DGZNLOSUnYWtVnv6d2+daTlf/CuTjlk1YNdOPRRNHkfr8OV9NmUeiOvf2Jasjv91g3s4f6fvBO2wb0wsPuwr0999G1LN4nelNTUrxZcsGbBrZnR3jetOmXjUmbt7P+Rt3NGkSk1Oo7mbPsLZ5/zGYn907tnFg3y76DfqKOQuXYWRkxGS/0Xmee+dO/8S61cvp2KkrC/xX4uTiymS/0ahetJ0vNWv5AesDdmhe3Xr1KVBMxak9eGnnju/Zv28PAwcNYf7CJRgZGTHBb0yeMZ05fYo1q1fyeafOLPb/FmcXFyb4jdWUU1RUFNFRUfT8sjfLlq9i2FcjufzbbyxeNL9AMUHxu/ZB8Tt+//a1D8DOzpaB/fqxctlS5s+djbVVBcb4TSjw9RiK57m3a8d2DuzbTf9BQ5m7cCmGRkZM9Psmz5jOnv6JtatX0LFTFxb6r8DJxYWJft9oxeTq5s6Qr0axbOU6Jk+bBekwYfxonj9/nmc8J8+eZ/najXTr2J5VC2fj6uTI1xOno1TpLuc/bwYxdd4i3m/WhNWL5vB23Tr4zZjDvQcPNWkePQljyDd+2NvZsXD6ZNYsmUeXzz6hpEHJApXRSwd2beboge/p0X80U+auwdCwFLMmDsvz3EtKSsTB2Z3ufUfmmsbazoHufUcwy38LE2evpHwFG2ZNHEpsjDLXbf4rFAq9YvtKSkoiNjZW65WUpPtYLliwgN69e9OjRw+8vb1ZsWIFxsbGrFu3Tmf6devWER0dzZ49e2jQoAFOTk40atSIatWqFVpZSwfEf1zjxo0ZNGgQw4YNo1y5crRo0YI///yTVq1aUbp0aaysrOjSpQuRkZGabeLj4+natSulS5fGxsaG+fNz3kxkn4KhUChYvnw5H330ESYmJkyfPh2AvXv3UqNGDYyMjHBxcWHy5MmkpmbeiKtUKvr27YuVlRVGRkZUqVKFAwcOcOrUKXr06EFMTAwKhQKFQsGkSZP+cXmkp6dzcO/3fPJZV2rXewdHZzcGDR+HMjqKX385m+t2B/Zsp2mL1rzb7APsHZzpM3AkJQ2NOHn8IABBN/7g6dMwBn41FkcnVxydXBn41TjuBgfy5/Ur+cZ0YO8PfPpZF+r4vo2TsyuDR4xFGR3FpV/O5brd/t3f817LD2nS7H3sHZzoO2gEhkZGnDiWMSRKX18fcwtLrdelX85S/+13KVUq984jgJ2799KqZXNaNHsPRwcHhg4agKGRIUeP/agz/Z59+6ldswYdPvkYBwd7unfpjJurC/sOHNSkadK4ETWq+2BjY42TowN9e/ciISGBe/fu5xnLS7t276FlyxaamIZoYjqeS0z7qFWzBu1fxNStS2fcXF3Ze+AAACYmJsyaPpVG77yDfcWKeHl6MrB/X24HB/P06dMCxQQZx2/Pnj107NgRX19fnJ2dGTFyJFFRUfzy88+5brd7925atmpF8+bNcXB0ZNDgwRgaGnLs2DEg4zw8duwYvXv3xsfHB3d3d74aPpybN24QePNmrvlGHD3DrYmLCN+r+1hl59inI4n3Qrn59WziAu/y4NsthO08ivPQ7po0zsN6ELL2e0I37iLu5h3+GDCR5wlq7Lt/UrBCArbtP0LrZo35oGlDnO3tGNW3O0aGhhw4eVpnei93FwZ2+5z33q6HgYGBzjS+NarRp9OnNKpXS+fv87Plt1u0q+pMm6rOuJQry7hmNTEy0Gfvn/dz3eZ5WjrjDl6kX4PKVDTV/pb3oTKOP55EM/a9GlS2scDJogxjm9UgKfU5RwIf5pKjtu37j9L6vUZ80OSdF+XUDUPDkhw4cUZnei83FwZ16/iinHQPWlzgN5IPmryDi4Md7k4OjBv0JeGRUQTdyX0/s9p88iIfN/ChrW81XG3KM/7z9zEqWYI9P1/Tmb52JUea+njiYlMO+/LmfNGkDu52Ffj9TogmTeu6Ven3/jvU9XQuUAy6pKens3/PTjp07Exd3wY4ObsydMQ3REdFcjGPtnPv7h9o3vJ9mjZvhb2DE/0HfYWhoSEnjh3WSmdoaIi5hYXmZWyc/7f6xa09eBnT3j27+axjJ+r51sfZ2YXhI74mOiqKX345n+t2e3bvpEXLVjRr3gIHB0cGDhqKoaEhx48dBcDJyZmx4ydQt64vNja2VPOpTtduPbh08WK+f5i9jKu4XfuK4/H7t699AE0aN85yPXakT+8vX+l6XFzPvX17dtGh4xfU822As7MLX40YTXRUFBfyqOd7d++kecv3ea95SxwcHBkwaBiGhob8eOyIJk3LVh9SpepbWFlZ4+rmzhddexAZEcHTp+F5xvTD3gN80Lwprd57FycHe4YP6IORYUkO/3hSZ/qd+w9Sp4YPHT9ug6N9RXp27oi7iwu7D2bGsjbgO+rWrE6/Hl1wd3XGzsaaBnVrY55LB3RuZXVk33baduhBrXoNcXB2p/9XE1FFR3L5gu5rDYBPzfp06NyP2r6Nc03ToFELqvjUoYK1HRUdXPii1zASE+J5eD+4wPGJVzdz5kxMTU21XjNnzsyRLjk5mcuXL/Pee+9p3tPT0+O9997jl19+0Zn3vn378PX1ZeDAgVhZWVGlShVmzJhRoHb+75IOiP8DGzdupGTJkpw/f55Zs2bRpEkTqlevzm+//caRI0cIDw+nQ4cOmvSjRo3i9OnT7N27l2PHjnHq1CmuXMn7j2iASZMm0a5dO/744w969uzJ2bNn6dq1K0OHDuXGjRusXLmSDRs2aDon0tLSaNWqFefPnycgIIAbN24wa9Ys9PX1qV+/PosWLaJs2bI8efKEJ0+eMHJk7j2uBfU0/AkqZTRVfTL/YDExKY2bhxdBgX/p3CYlJYW7wbd4yydzaLeenh5v+dTi1ottUlJSUKDQ+kOpZMmSKBR6BP51Pc+YwsMyYsqav4lJadzziemOzphqamLK7s7tIO7dDaZp8w/yjCclJYXbwcFU9/HRyru6TzVuBgbq3OZGYCDVfbR7QmvVqJFr+pSUFA4dPoqJiQkuzvn/AfIyphpZPiMjJh9uBAbp3OZmYKDWPgDUrFE915gA4uMTUCgUmJQunW9ML4WFhaFUKvGpXl3znomJCR4eHnnuf/Dt2/hkK2MfHx/Nzejt27dJTU3Vytfe3p7yFSrkuQ+vyqyeD5EntS86EcfPYV4vIzaFgQGmNSoTeSLLzXd6OpEnf8asXnUKIiUllVt37lPrrcqa9/T09Kj1ljd/BRXNTUnK8zRuhiup62iVGZNCQV0HK64/jsp1u1W/3MDC2JC2VXPW2+TnGaOdSpbQ18qzZAk9rj6KzJE+R0wpqQTduU/ttzKndmWUU2X+vHUnjy1fTXxCIgBly+R/U5+S+pybD59QzyNzf/X0FNTzdOb6vdB8t09PT+di4D3uh0dT0y3/4cqvIjzsCUodbWclDy+Cbt7QuU1ubWc1n5oEBWpvc+anE3Tp2JYh/Xuyef1qktR5j4yB4tkehIeFoVRG4+OTOYw7IybPXP/4TUlJITj4Nj4+mZ+XEVN1AgNz/4M5Pj4eY2Nj9PX1c02TGVfxuvZB8Tt+r+Pal3E9PvLieuyUayxZFcdz72VM1bTqef4xBQff0jo3MmKqQWCg7m3U6kROHD+ClbU15crlPuUhJSWFW8F3qenzllbeNaq9xV+Bt3RucyPwFjWrvaX1Xu0a1TTp09LSuPDbFSra2jJq4jTadelF/5FjOHch7/n72UWEP0aljKJytdqa94xNSuNaqTK3g15tamVeUlNS+OnoHoxNSuPonPu0E/HPjRkzhpiYGK3XmDFjcqSLjIzk+fPnWFlZab1vZWVFWFiYzrzv3r3Ljh07eP78OYcOHcLPz4/58+cXeATe3yFrQPwfcHd3Z86cOQBMmzaN6tWrM2PGDM3v161bh729Pbdu3cLW1pa1a9cSEBBA06ZNgYwOjIoV854/B9CpUyd69Oih+blnz5588803dOvWDQAXFxemTp3K119/zcSJE/nxxx+5dOkSN2/epFKlSpo0L5mamqJQKLC2zn9ecFJSUo6hRsnJSZQsaaj1nkqZ8YeFmZn2nEszMwtUqmideT+LjSEt7TmmZtrDzU3NzHkUmjGk0d3TG0MjIwLWr6BT1z6kk86WDStIS3uOUpn7HzMZMWV8bva1IkzNzDW/yy2m7PthambOoxDd37SeOHaQivaOeHrnPQ8vNjaWtLQ0zLPN7TI3MyMk5JHObZRKVY70ZmZmRCu1h9xduPQrM2bPJSkpCQsLc2ZNm4Kpadk848kaU/b9zYhJ9x9BumIyNzNDqVTpTJ+cnMza9Rto3KghJnlML8r5ORn7mH0er5m5ueZ32WnKWMc2IaGhmnxLlChB6WydIeZmZiijddeLv8PQqhxJ4dp/HCeFR2JgWgY9I0MMzE3RK1GCpKdR2dJEYeKhe12C7GKePeN5WhoWZtrH2sLMlAePnvyzHfibVIlJPE9Px8LESDsmEyPuRz/Tuc3voZHs/eMe33VtpvP3ThZlsC5jzNIzfzCueU1KGZRgy2+3CH+WSEQ+0zoAVJpy0v4my8K0LA//pXJKS0tj8fqtvOXpjotD/u26Mi6B52npWJbV7qywLGPCvfDc27ZniWqajV1CSspz9PQUjO3YEl+vgtWXgspsO3O2g8o82840nduEZmk7GzZuSoUKVphbWPLg/l02rVvFo0chfDN+Sp4xFcf2QKkpJzPt/M3MUeUTU/ZyMjMzJzQkROc2MTExbPtuCy1bvZ9nPC8Vt2sfFL/jV5jXvguXLjEzy/V45rQpmJoW7Fv04nzu5ayzZrnGFJtLTGZm5jzKVs8PHdjLhnWrUavV2FW0Z8r0ObmOzgOIiX324l5Ku0zNzUx5+Ej3vVS0SqUjfeaxU8XEkJio5rude+jZuSN9u33BpStXmTBzHgumT8SnSmUdueb08l44532theZ3/8SVX8+xdK4fyUlqzMzL8c2UJZQpa/aP8xW5MzQ0xNDQMP+Ef0NaWhoVKlRg1apV6OvrU7NmTR49esTcuXOZOHFioXymdED8H6hZM7O3+dq1a/z00085LoIAd+7cITExkeTkZOrWzZwnaWFhobWQUm5q1dIeBn3t2jXOnz+vGfEA8Pz5c9RqNQkJCVy9epWKFStqOh/+iZkzZzJ5svac936DRlKlajVWLpuneW/MxNn/+LN0MTU1Z8Q3U1j97XwO79+BQqFHg0ZNcXathEKh/dieMz8dZ+XSzGktYyfNKpSYskpKSuLs6RO07/j35sr/W6q9VZXl/ouIjY3l0JFjTJs1myUL5uW4WXrdUlNTmT5zNpDO4IED8kz708mT+Pv7a37OXu/E/6f45BT8Dl3Er3lNzI11X+QN9PWY16Y+U47+SuOle9FXKKjjWIEGztakp7/mgHMxf/Vm7j4MZfn0cYX6OSaGhnw/5ksSkpK5GHSf+Tt/pGI5c2pXcvzbeZ7+6UeW+y/Q/Dx+cs7hpf+WFq0+1PzfydkFc3MLJowdyZMnj7CxyVyMsDi2Bz/9dIJl/os1P0+cXHjfUr2UkBDP5InjcXBwoNMXXXSmKY7XvuJ4/F4Xn7fe4lv/xcTGxnL4yDGmz5rNkgXzdS4sVxzPvVM/neBb/4WanydMnk5havRuU3yq18yYC7/rB+bMnMrseYspWfLV1l74J9LSMi4k9evWon2bjHJyc3Hmr8Ag9h8+nmsHxPlTR1j7beb976gJBV+n5e/wrlqTGYs28Sw2hp+O7cV/9jgmz1ubo8NDvH7lypVDX1+f8HDt6UPh4eG5fuFrY2ODgYGB1sg2Ly8vwsLCSE5OLpRzQDog/g9kXY06Li6O1q1bM3t2zj/EbWxsCA7++8Ohs696HRcXx+TJk/n4449zpDUyMqJUqVJ/+7OyGzNmDMOHD9d671ZIDM9Tn+OW5UkVqS8Wx1SplJhbZC4gp1JF45TL8LAyZU3R09MnJtsIiRiVEjPzzKclVKtRh6VrthMbo0JfXx+T0mX4snMbrKxttbarXbeBZrVuyFywU6WMxtwiM78YlRInF7c8Y8q+cFNGTDkb+F/OnyI5SU2jpi1y/C67smXLoqenl2PBSaVKhUW2b9BeMjc3y5FepVJhke1bhVJGRtjZ2mJna4uXpyfde/flyLHjfN6hfYFiyr6/SpUq1xXEdcWUkV57H1JTU5k+azbhEU+ZM2N6vqMf6tarh4dn5urYL4+fUqnEwiKz7FVKJS6uup/woCnjbN+oqZRKTZmZm5uTmppKXFycVoehUqXC3OLfu4gnhUdiaKW9mKKhVTlSYp6Rpk4iOVJJWmoqhhUss6WxJCks/2kFAKZlyqCvp0d0tgUno1UxuS6cWNjMShmir1DkWHAyOl6NZbZREQChqngexyYwbHfmXOK0F70KtefvYFevltiblcbb2pxt3ZrzLCmF1OdpmBsb0jXgBF7W+a90b6YpJ+0FyqJjYnOMivg75q/ezM+Xr7Fs6hgqWBasDpmXNkZfT0FUrPaCk1HP4ilXNvcpHHp6ChwqZHyGp70198IiWXv053/UAVGnbn2t1fJTUjIWllMplVhkazud82w79XJ88x+jUuZ5XlXyzPjcsMePtf4IKo7tQd26vponVWSNSaVUaZWTSqXE2SXvmLKXk0pHOSUkJDDBbxyljI0Z5zeJEiV03zoWx2tfcTx+uvIujGufUbbrcY/efThy7DgddVyPi+O5V6eur9aTKjT3d9liUqlUuORaz3XHpFIpMbPQLl8Tk9KYmJTG1q4iHp5edOrQjl9+Pkejxk105m1atsyLeynt9lypisEily9dLMzMdKTPPHamZcugr6+Pk732U9scKlbkjxu5T+WpUecdXCtldk6kpmaUVYwqWuteOEYVjaPLP58qYWRUCmtbe6xt7XH3rMLwvp9y6vh+2rTv9o/zFv9MyZIlqVmzJidOnKBt27ZAxgiHEydOMGjQIJ3bNGjQgK1bt5KWloaeXsbqDLdu3cLGxqbQOuBkDYj/MzVq1OCvv/7CyckJNzc3rZeJiQmurq4YGBhw8eJFzTZKpZJbt3TPV8vvs4KCgnJ8jpubW8aczbfeIjQ0NNe8S5YsWeAFTgwNDSlbtqzWq2RJQ0oZG2NjW1HzqujghJm5BX9evazZNiEhnuCgm3h46u45NjAwwMWtEn9cy9wmLS2NP65dppKObcqammFSugx/XLtMbIySWnXf1vp99pjsX8T0x7XMdTYSEuK5nU9Mrm6V+OOqdkzXr17RGdPJY4eoVbcBpqZmugswW97ubm5cvZq5wFxaWhpXr17HK8uNWlbenp78fk17rYsrv1/NNf1L6WnpBXpiysuYfr+a+RkZMV3DO5fHhnl5enL1mvYiedljetn58OjxY2ZNn0bZsvlPBzE2NsbW1lbzcnBwwNzcnGtXr2rSJMTHExQUlOv+GxgY4OburrVNxv5cxdMr42bL3d2dEiVKcDVLmtDQUCKePs23XF+F6sJVLJvU03qvXNP6KC9kfG56SgoxV/6iXBPfzAQKBZbv+qK68HuBPsPAoASVXJ24fD1zjnZaWhqXr9+gsofum9XCZqCvh5eVOZceZi44mpaezqWHT3nLNudjWJ0syvB9t+Z817WZ5tXIzZZaDhX4rmszrMtod1yVMTTA3NiQh8pn3AiPprGbbY48c8RkUAIPVyd++yNz7vHLcqpSSfcNdEGkp6czf/Vmzly6zJJJX2NrVfBHtRmU0MfLwYaLQfezxJTOxaD7vOWc/xQOzTbp6aSkFuxJILnJaDvtNC97ByfMzS24nq3tvBV0Ew8vb515vGw7s27zsu308NS9DcC9OxlrcGT/Q6k4tgcZMdlpXg4OjpibW3D1Wub5mpAQT1BQoCZ/nTG5uXPtmnZM165exdMzc5uEhHj8xo+hRIkS+E2YnOfNaHG89hXH45c978K49umS1/W4+J57mfXc/kU9v5atnucXk5tbJa7liOl3PPOICdJJJ13T6ZFb3pXcXLhyLXNNhbS0NK5c/4PKnrpH/np7VuLKde01GC5fva5Jb2BggKe7KyHZpnCEPn6MVQXtLxKyKmVsoukQsLa1x87eGTNzS/669qsmTUJCPHdu/YW7R9Vc8/m70tPTSU35d57CV6T0FMX39QqGDx/O6tWr2bhxIzdv3qR///7Ex8drptF37dpVa/2I/v37Ex0dzdChQ7l16xYHDx5kxowZDBw48F8t3qxkBMT/mYEDB7J69Wo+//xzvv76aywsLAgODmbbtm2sWbOG0qVL06tXL0aNGoWlpSUVKlRg3Lhxmh6vVzFhwgQ+/PBDHBwc+PTTT9HT0+PatWv8+eefTJs2jUaNGtGwYUM++eQTFixYgJubG4GBgSgUClq2bImTkxNxcXGcOHGCatWqYWxsnOejPwtCoVDwQZsO7Ny+EWu7ilSwsmF7wBrMLSyp7fuOJt3ksUOp49uQVq0zVvn/sO1nLFs4A1d3T9wqeXFw7w8kqRN5973Mua4/HT+Inb0TZU3NuBX4J+tXLeGDNh2wq5j3wmsKhYIP27Rnx7ZN2NhWpIK1Nd9tXoe5hSV1fDM7LyaN/Yo6vu/wfuuMESWt23XAf8FMXN09ca/kyYG9O0hSJ9KkWSut/J88DuXGn9cYN6ng008+adeGuQsW4e7uhmelSuzauw+1Wk2LZhnrgsyZvxBLSwt6dc/ozW77UWtGfjOWHbt2U6d2bU6dOcOt4GCGDs5onBLVar7b/j2+detgYWFBTEws+w8eJDIqioZvv51rHFl93K4t8xYspJK7Gx6VKrF7717UajXNm733IqYFlLO0pKcmpo8Y9c2YFzHV4vSZs9wODmbY4Iwe3tTUVKbOmEXwnTtMmTiBtOdpREdnfAtSpkzpPOd2ZqVQKGjbti3btm3D1s4OKysrNm/ejKWlJb7162vSjfnmG+rXr0/rjz4CoF27diyYPx93d3cqeXiwd88ekpKSaNYsY30BExMTmjdvzurVqylTpgzGxsasWL4cLy+vXP9ogIzHcJpkWezP2LkiZat5khwdgzrkCR7ThmNkZ8W1HqMBeLBqG44DvsBz5ihCNuyk3Lv1sGnfil8/6qvJ496i9VRbNxvV5T+J+fU6TkO6UcKkFCEbdxWojAA6tm7JdP/VeLo54+Xuwvf7j5GYlMQHTRoCMHXxSspbmtOvc8aCuCkpqdwPzbjJSklNJSJaye17DyhlZERFm4zFkxIS1TwKyxxG+ORpBLfvPaBMaROsy+d+M/bSF7UqMfHwJbytzKlsY8HWy7dJTEnloypOAPgdukSF0qUY3LAqhiX0cSuvPQqhjGFGHcn6/vGgEMxLGWJd1pjgyBjmnrxKYzc7fJ3yX8sG4LPWLTLKydUZb3cXvj9wDHVSEh80yWifpi5ZRTkLc/p3bq8pp3uacnpORJSSW/ceYJylnOav3szxs78w65uhGJcyIurFfOLSxsYYGub/7UWXJnXx27SPyo42VHG0JeCnSyQmpdDWN2OxtHEb9lHBrAxDXzxSc+2R83g72mBf3pzklOec/SuYgxf/ZNznLTV5xsQn8iQ6hoiYOADuh2eMMCtXtjTlTAu2CKxCoaB120/4YVsAtrZ2VLCyYevm9VhYlqNulrbTb8wI6tV/mw9atwOgTbv2LF4wCzd3D9wrebJ/707USWqaNsuI78mTR5z56SQ1a9elTNmyPLh3h7WrvqVylbdwcs67I6i4tQcvY2rTth3bt23FztYOKytrAjZvwMLSEl/fBpp0Y8d8jW/9BrRu3QaAtu0+YeGCuRkxVfJk795dqJPUvNcsYzRBQkI8fuPGkJSUxMhRo0lMSCAxIQGAsqam+S5EWRyvfcXx+P3b1z61Ws3WLNfj2JhY9r24Hr/zdoNc48heTsXx3Puo7cd8v20Lti/q+ZYX9bxelno+fswo6tVvwIet276I6RMWLZiDm7sHlSp5sO9FPX8ZU9iTx5w9c4rqNWphampKZGQkO3/YhmHJktSsXSfPmNq3+ZBZi5ZRyc0Vr0pu7Nh3ELU6iZZNM9rKGQv9KW9hQe9uXwDwSesPGDZ2It/v3k+92jU4eeY8QcF3GDEw83r8WbuPmDJ3IW9V9qZ61cpcunKVny9dZtGMSQU4cpll1fKjz9jz/Qasbe0pb2XLji2rMLMoR816DTXpZowfRK16jWj+Ycb1Rp2YQNiTzLVHIsIfc//uLUqXKUu58tao1Yns/X4DNeq8g5mFJXGxMRw/uANlVAR1325a4PhE4frss8+IiIhgwoQJhIWF4ePjw5EjRzQLUz58+FDr7z57e3uOHj3KV199xVtvvYWdnR1Dhw5l9OjRhRajdED8n7G1teX8+fOMHj2a5s2bk5SUhKOjIy1bttRUtrlz52qmapQpU4YRI0YQ8wrPhn6pRYsWHDhwgClTpjB79uyMnltPT7788ktNmp07dzJy5Eg+//xz4uPjcXNzY9asjHmh9evXp1+/fnz22WdERUUxceLEf+VRnG0+6YRanchK/7kkxMfh6V2VcVPmaS1YGR72mGexmfvcoGFTYmNUbA9Yi0oZjZOLG+OmzNMa8vnoUQhbNq4iLi6WChWs+bhDFz5s+1mBYmr76eeo1Yms8J9H/IuY/KbO1Yop7En2mJoQE6NiW8A6VMponF3cGD9lbo5hqCePH8KyXHmq1ahNQTVu+A4xMTFsCtiKUqnExcWF6VMmaYZ8Po2I0FrborK3F2NGjWDD5i2s37gZWztbJo0fi7NTxnBrfT09QkJCOX7iJLExsZQpWxYPdzcWzJmFk2PBVsbPjGlLlpgma2KKiIhAL1tM34waycbNAWzYuAlbO1smjh+H04uYIqOiuPBipM+AwUO0PmvOzBlUe6vg3wJ82r49arUa/yVLiIuLo3LlykyZCVV0/gABAABJREFUOlXr28AnT54QE5s5BaFRo0bExsSwOSAAZXQ0Lq6uTJk6VWtYbZ++fVHo6TF92jRSUlKoWbMmA/LpcTatWQXfE5s1P3vPGwtAyKZdXO81BkOb8pSyt9H8PvF+KL9+1Bfv+WNwGtwVdWgYf/QdT+TxzEepPfnhMCXLW1Bp4hAMrcsTe+0mlz78kuSnBV+squnb9VDFPmPNd7uIVsXg5uzAfL9RmqkF4ZFR6GXpxY9UKukxwk/z83d7D/Pd3sP4VPZk6dSMfQq8c48hEzLnIvuv3wpAq3ffZtzg/J8b38LTHmVCEsvP/0VUghqP8mYs/fQdzRSMsNiEV/1igch4NQtOXSMqXk05k1J8WNmR3r55fZOm7b0GdVHFPGPNtt1Eq2Jwd3Zg/vgRWuWU9dyLVCrpMTJzEajv9h3hu31HqF7Zg6VTMr7B2H0045FvgyZoz7kfO7CXpmMjLy1reaOMi+fbA6eJjI3Ho6IV3w7qiGXZjI6CMGWM1rFLTE5hxrYjhKueYWhQAmcrS6Z3b0PLWpnlcOr6LSZsznws4Oh1uwHo9/479P8w8wY4P+0+7YhareZb/wXEx8XhVbkqE6bM0jr3wp48JjbLNeztRu8SE6viu83rUSozpiFMnDJb03aWKGHA9auXObB3J2p1IuXKV8C3QUM6fN65QDEVp/bgpU8+7ZARk/8i4uPi8K5chSlTZmQrpyda5dSwUWNiYmMI2LxJ0+ZOmTJdE1NwcDBBQRnDvnv36q71eWvXb8LKKv9Ot+J27YPid/z+7Wufnp4eoSGhTD1xQnM9ruTuzvw5s3ByLPgUqeJ47n386Weo1WqW+S/U1PNJ+cT0TqN3iYmNYevmDS/K15VJU2ZqytegZElu/PUn+/buIj4uDjMzcypXqcrs+UtyLA6aXZN3GhATE8uGrduJVqpwdXFi9qRxmumsTyMitY5dFS8Pxo8Yyrot37Fm81bsbG2YOvZrnLPcJ73jW5ev+vdh647d+K9eh72dLZO/GUlV77w7srL78OMuJKnVrF02i4T4OCp5v8XoSYuy3QuH8ixWpfn5bvBNpo/LrLMBazPWmnmnyfv0GzYBPT09Hofe5+zJQzyLVVG6rCkubl74zVpBRYd/dxFi8c8MGjQo1ykXp06dyvGer68vFy5cKOSoMinS04vL0llCvJrrt5/mn+g101OkFXUIOZTh1TuXCls6r/hX32vwXK949scGerTKP9FrVufqpqIOIQfjn/cXdQg5JPrm/1jA1610+O2iDkGne07F79uzkoqk/BO9Zmnp+T/+8nVLSi+cldn/iVJ6CUUdgk76af9smlJhSFTk/7je102PYngvlar7KSlF6TH2+ScqArU88l8TqThSzdb9B3txYDZ6aVGH8K+SNSCEEEIIIYQQQghR6KQDQgghhBBCCCGEEIWueI45FkIIIYQQQgghXgPFqy4KJf42GQEhhBBCCCGEEEKIQicdEEIIIYQQQgghhCh00gEhhBBCCCGEEEKIQicdEEIIIYQQQgghhCh00gEhhBBCCCGEEEKIQidPwRBCCCGEEEII8eZSyPfyr4uUtBBCCCGEEEIIIQqddEAIIYQQQgghhBCi0MkUDCGEEEIIIYQQbyyFnqKoQ3hjyAgIIYQQQgghhBBCFDoZASH+s54Xw/4zY0V8UYeQQ4nnyUUdQg5P0isWdQg5mOspizoEnepc3VTUIeRwyadrUYeQg++VtUUdQg5RpYpfPU9wMCvqEHQqqUgq6hD+E/RJLeoQdDAs6gBySE8vnt9kln/6Z1GHkEOYtU9Rh5BDRLJlUYeQg82h+UUdQg6p708u6hCE+FuK319wQgghhBBCCCGE+L8jHRBCCCGEEEIIIYQodNIBIYQQQgghhBBCiEIna0AIIYQQQgghhHhz6cn38q+LlLQQQgghhBBCCCEKnXRACCGEEEIIIYQQotDJFAwhhBBCCCGEEG8shaJ4Pr73/5GMgBBCCCGEEEIIIUShkw4IIYQQQgghhBBCFDqZgiGEEEIIIYQQ4s0lT8F4baSkhRBCCCGEEEIIUeikA0IIIYQQQgghhBCFTjoghBBCCCGEEEIIUeikA0K8Vo0bN2bYsGFFHYYQQgghhBBCiNdMFqEUheLUqVO8++67KJVKzMzMXutnp6en88OWNZw8up/4+Gd4eL1FrwEjsbGzz3Wbm39eZf/Ordy7E4gyOooR42ZS27fhP84367YBAZs5euQw8fHxeHl7M3DgYOzs7PLc7sD+fezcuQOlUomzswv9+g/Aw8ND8/vDhw9x+tRPBAffITExge3f76B06dL5xgOw5+Bhtu/aR7RShauzI4P79sKrknuu6U+d+5n1AdsIexpBRVsbenfvTL1aNbTSPAgJZdWGAK7/eYPnz5/jaF+RSWNGYlWhfIFigoyy2rl1NT8d20t8fByVvKrSs//XWNs65LrNzT9/5+DuAO7dCUIVHclXY2dTq14jrTQ7t67ml7M/Eh0Zjn4JA5zdPOjQuR9uHlXyjWn//v3s3PHiOLi40L9/f63jkN3Zs2fZvGkT4eHh2NrZ0bNHD2rXqaO1jwGbN3PkyBHi4+Px9vZm4KBB+dYHrf05/CPf7TlEtCoGVyd7vvqyC97urjrT3n0Yytptuwi6c5+wiEiG9OhEh9YttdJc/SuQrXsPEXTnPlFKFTNGD6Vh3ZoFjsfi7Vq4jOiFaY0qGNlW4LdPBhC+70Te2zSsg/e8byjt7Y465AnBM5cTumm3VhrH/p1wGd4LQ+vyxF4P5K9hU4n59Y8Cx7Xj8Em27DtCtCoGN0d7hvfqRGV3F51p74Y8YvW2PQTefUBYRBRDu3ek44fNtNLsOvoTu46e4klEJAAu9rb0/PQjfGtULXBMkFEHtgZs5NiRQ8THx+HlXZn+A4dia1cxz+0O7t/L7p3fo1RG4+zsSp/+g6jk4an5/TL/hVz7/QrR0VEYGZXC09ub7j16U9E+9/Pnpb0HDvHDrt0v2gQnBvbtjadHpVzTnz53no0BWwkLf4qdrQ1fdu9K3dq1dKZdtHQ5B48cpX/vnnzc5qN8Y3mpOJ57fzeP/PYlOTmZ1atXc+b0aVJSUqhRsyYDBw7E3Nw835j279/Pjp07USqVuDg7F6icNm3eTHh4OHa2tvTo2ZM6tWtrfn/+/HkOHjpEcHAwz549Y6m/P66uutuXvKSnp7MtYB0/Hj1AQnwcHl5V6TNweL71/PCB3ezduQ2VMhonZ1d69RuKu4cXAE/Dn9C/Z0ed2434ZhL133k335iK2/V4+4lf2HT4DFExcVRysObrLz6iiovue4tdpy9x4Pzv3HkUBoCXkx2DPmmRa/rpG3ez89QlRnz+AV80f7tA8UDxrOfp6ens3rqKU8f3kBAfh7vnW3TrPzrP+4PAv65weHcA94MDUSkjGTJmDjXrNdZKs3rxZM6dPKj1XtXq9Rg5aUm+MRlUexvDWk1QmJQhLeIxiT/tJC3soe603nUo1bKT9j6lpvBsySit9/QsrDB8pzUlKrqCnh5pUeEk7F9H+jNVvvFo8i2GZSXESzICQvzf2bdzC0f27+DLgaOYNn81hkZGzJwwnOTkpFy3UasTcXRxo0e/Ef9qvi/t2PED+/ftZeCgISxYuAgjIyP8/MaRnJyc6zZnTp9m9erVdOrUmSX+S3F2ccHPbxwqlUqTJikpiRo1a9Hhs8/yjSGrn86eZ/majXT9vD0rF83B1dmJ0ROmoVTF6Ez/581Aps1dRKvmTVm1eC4N6tVmwvQ53HuQeZF99CSMoaPH41DRjgUzJrHafz6dO35KyZIlXym2A7s2c/TA9/ToP5opc9dgaFiKWROH5VnOSUmJODi7073vyFzTWNs50L3vCGb5b2Hi7JWUr2DDrIlDiY1R5hnP6dOnWb1qFZ2++AJ/f39cnJ3xGz9e6zhkdePGDWbPmkXzFi3wX7oUX19fpk6dyv379zVpdvzwA/v27WPQ4MEsXPSiPowfn2d9yOrEuQssXb+VHh3asnbeFNycHBg+ZS5KVazO9ElJydhaladflw5YmpnqTJOYlJSRT++uBYohO30TY2KvB/HnkMkFSl/KqSK1960k6tRFztVqwz3/jVRdOY1yzTJvkG3at8Jr7hhuT1vGuTrteHY9kLoH11KyvEWBPuPH85dYsnE7vdp/xIY5E3F3sueraQuJjtFdTuoX5TTgi09yLafyluYM6PwJG+ZMYP1sP2pW8eLrOf7cDXlUoJhe2rVjOwf27ab/oKHMXbgUQyMjJvp9k2cdOHv6J9auXkHHTl1Y6L8CJxcXJvp9g0qVWYdd3dwZ8tUolq1cx+RpsyAdJowfzfPnz/OM59SZc6xcs47On3dk+eIFuDg7MWbCZJS51PO/bgYyY858WjZ7j+VLFtCgXl0mTZ/FvfsPcqQ99/MFbgYFYWlRsOP2UnE89/5uHgXZl1UrV3Lp4kXGjB3L7DlziI6KYtq0afnGc/r0aVatXs0XnTrh7++Ps4sL4/388iynWbNn06J5c5b6++ssJ7VaTeXKlenZo0dBi0WnPTu+49D+XfQdOIKZC1ZgZGTEVL+Rebbn58+cZMPqZXTo1I25S1bj6OzKVL+RxLyo55blKrBm8y6t12df9MCoVCmq16qbb0zF7Xp89OJ1Fmw7SJ82Tdk6aRDu9jYMnL+O6Ng4nekvB96lZb23WDW6NxvG98fKwowB89bxVJnz+n3y8l/8cSeE8mZlXykmKH71HODQrk0cP7id7v2/YcLcdRgalWLepCF53x+o1dg7udOl76hc0wBUreHL4g2HNK/+I/OPqUSl6hg1akvShSPEB8zjecQjTD7uh6JU7h1P6UmJPFvhp3nFrdG+ZipMLTH+bAhp0eHEf7+UuE1zSLpwFFJT840nq+JWVv8FCj1FsX39v5EOCKFT48aNGTRoEIMGDcLU1JRy5crh5+dHeno6AJs3b6ZWrVqUKVMGa2trOnXqxNOnTwG4f/8+776b8Q2Eubk5CoWC7t27a/JOS0vj66+/xsLCAmtrayZNmvSvxZ2ens7hvd/T7rNu1Kr3Do7Obgwc7ocyOpLffjmb63bVa/nyWZc+1KnfSOfv/26+L7fdu2c3n3X8HF9fX5ydXRgxYhTRUVH88svPuW63e/cuWrb8H3v3HRbF0Qdw/EsTBKUrvXdsCCqgMfbee4019hJb7L3EEjsao0Zj11jBFnuJGkts2AB7BxW4AwFByr1/AAcHd3AmFvJmPs9zj7I3O/e72d3ZvdmZ2YbUq18fe3sHBg8egp6uLkeOHJanadmyFe3bd8DT01NlPsrsCN5H4wZ1aVS3No72dgwf2BddXV1+P3pCafrdew9SxdeHjq1b4GBnS6+unXBzcSJ4/+/yNGs3bqGKny/9en6Dm4szNlaWVPOvjImKH3LKyGQyDu39jZbte1Ip4GvsndwYMHwK0thorlz4Q+V6Pn5Vad+1P5UDa6pMU61GA8r6VKG0pQ229s506T2Md0mJPH18v8CY9uzZQ8NGjahfvz72Dg4MHjIEXV1djhw5ojR9SEgIfpUq0bZtW+zt7enWrRsuLi7s27dP/h2Dg4Pp2LFj1v7gxMhRo4iJieH8n6r3h9y27TtEs3o1aVLna5zsbPi+Xw/0dHXZf+K00vRebs4M6t6Jul8FoKOjozRNoG8F+nZuS40A5XewC/Pm8B/cnbKYVyHH1Erv0Lcj7x49J2z0XBLCH/Lkp81E7TqM03c95GmchvXk2ZrtPF+/m4SwB9wcOIX0pGTserRR6zO27jtC87pf07T2VzjZWTO67zfo6hZj/4mzStN7uzoxpFt76n3lj46O8g6C1Sv5UNW3PHZWFthbW9K/c2uK6+ly6+5DtWKCzH1gb/Bu2nfsQkBgNZycnBk+cgyxMTFcOH9O5Xohe3ZRv2Fj6tZviL29AwMHD0NXV5djRw7J0zRs1JSy5cpjYWGJi6sbXbr1JPrNG16/flVgTLuCQ2jUoD4N69XBwd6O7wYNQFdXl8NHlfdi2bN3H5X9fGnfphUOdnb0+KYLri7OhOw/qJAuOjqG5StXM27UCLS1tdQuIyiax97fzaOw75KYmMiRI0fo06cPPj4+uLm5MXzECMLu3CE8LKzQcmrUsCH169fHwd6eIYMHF1pOlfz8VJYTQJ06dejSuTMVK1ZUq1yUkclk7A/ZQdsO31Al8CscnVwYMnI8ktgYLp1XfgwC7NuznboNm1K7XmPs7B3pN3gkunp6HD+SuW9paWlhYmqm8Lp0/gxVv6pF8eL6hcZU1M7Hm4+codXXlWlRvRLONhZM6NYSvWLFCDlzWWn6Wf060r52IB721jhZlWZyz9bIZDIu3XmgkO61JI55m/cyq18HtLU+7HK/KO7nMpmMw/u20axdL3z9a2Dv6EbfYVORxkZz9YLycx9ABb+qtO06gEqBBfeM0dHRwdjEXP4yKFF4o42uX01Sb50n9fYlMmJfkXxsB7K09+iULaAhTAaypLe5XooNTXrVmpD26A4pZ/aR8eYFsrgY0h7eRvZOeYOU0o8ogmUlCLmJBghBpfXr16Otrc2lS5dYsmQJCxcu5JdffgEgNTWVGTNmEBoaSnBwMI8fP5Y3MtjZ2bFr1y4AIiIiiIyMZMmSJQr5GhgYcPHiRebNm8f06dM5evToR4n59auXSCUxlPPJ+RGlb1ACVw9v7obf+iL5RkVFIZFI8PHJuZAzMDDAw8NT5Qk3NTWV+/fvKayjqamJj09FwsMLPkkXJjU1lbv3H+JXobxC3n4+5bgTEaF0nTvhd/H1Ka+wrHJFH26H3wUyG5UuXL6KnY0VoyfPoHXXXgwcOZaz5y99UGxvssq5TIWcrsD6BiVwcS/DvQj1u90XJi01lZOHg9E3KIGDk+phJ6mpqdy/dw8fHx/5sszt4KNy24WHhVExV3oAPz8/eXr5/lAx7/7gQVh4eKGxp6amcffBYyqVL6MQU6Xy3tyOKLgxpSgxDvAh+sR5hWVvjp7FJMAHAA0dHYx8yxB9PNfFrkxG9Ik/MQ4o/EdRamoaEQ+fULm8l3yZpqYmlct5cyviQQFrqi89PYOjZy+SnPyecu7qd09/FRWJRBJLBZ+cIUwGBiVw9/AiIuyO0nUy64S7+ORaR1NTkwo+voSHK18nOfkdx48ewsLSEnNz1cOgMuuEBwrHuKamJr4+FbgTrqpOiMhXJ1TyrUhYrvQZGRnMXbiYdq1b4uhQ+BCQvDEVtWPv7+ahzne5d+8eaWlpCvna2dlRqnTpAmNLTU3l3v37SvNWtV5YeLjC50BmOalbBup6FRWJVBJLeZ+coVwGBiVw8/AiIvy20nVSU1N5cP+uwjqampqU9/Hjrop1HtyL4NHD+9Sp36TQmIrc+TgtjbDHL/Ev46qQt7+3CzfuK+/Gn1dySipp6ekYGhSXL8vIyGDiqu10a/g1LjYWHxxXUdvPIfP6IE4SQ5kKOUOq9A1K4Oxehvsf4fog/NZVBndrwJgBbVm3Yg4J8dKCV9DUQtPClrQnd3MtlJH25C5aVo6q1ytWjBLfTqZEnykUb94bTTPLXG9qoO3sTYbkDfqt+1Oi/wwMOg1H2+XDhvgVubIShDzEHBCCSnZ2dixatAgNDQ08PDy4efMmixYtok+fPvTq1UueztnZmaVLl1K5cmUSEhIoUaIEplldbUuXLp1vDojy5cszZcoUANzc3Fi2bBnHjx+nXj3Fsda5paSkkJKi2G3s/fsUihXTVVgmlcQCYGSs2NXXyNgUqTTmwwrgI+UrkWR2GzUxMVZYbmxsLH8vr/j4eDIyMjBWss6zZ88+IPL84uLfkpGRgYmJYs8EE2Njnj5X3o08VirFJM92NDE2knfPlsbF8e5dMlt3BtOza0f69ujKpSvXmTL7RxbOmkqFcmXyZ6qEVJJZlkrLWfL3t1+2q3+dZdmPk3ifkoyxiTljpy+lpKGxyvTZ2yHv2FRjExOePX+udB2JRIKxkvTZ2zpnf1CdpiBxb9+SnpGBaZ4utabGRjx5EVno+kWFroU5Ka+iFZalvIpGx6gkmnq66JgYoamtTcrrmDxpYjDwUD6HQ27S7HIyyltOhv+4nO4/eU7fCT/w/n0qxfV0mTN6EE521mqvn72d8+0nxsZIsuqavOLj47LqhLzrmPAiT51wcH8I69auJjk5GRtbO6bPmqey5wvkqhOUHOOq93NpvrrdxNiI2FzDQX7buRtNLU1aNW+q8rNVKYrH3t/NQ53vIpFI0NbWzjdngImxMZJY5ftEQXmbGBvzXMW5QiKRKNnWqs9Hf1f2edPYJG99biJ/L6+38XFkZKRjbGySb50Xz5T/ID9+5AC2dg54ehc+n09ROx9L3yZl1lOGitvd1Kgkj6PeqJXH0h2/U8rYUKERY93BP9DW0qRTvap/K66itp8DxKm4PjA0NpW/93eVqxiIX0AtSllY8zrqOTs3rmD+9GFMnrsGTS3lPbc0ihugoamFLOmtwnJZ0lu0TJU3+mRIXpN8eBvp0S/R0NWjmF8tDDp+R8L6OcgS4tDQL4FGMT10q9Qh5dxB0s7sQ9vRk+LNe5K0Yznpz9VrPC9qZfWvoSHuy38uogFCUCkgIAANjZxxR4GBgSxYsID09HSuX7/O1KlTCQ0NRSKRkJGRAcDTp0/x9vYuMN/y5RXvmllZWcmHb6gye/Zspk1THCfXd/D3lC1XgdXLf5QvGzPlx7yrfnYnT55gWVDOZDxTp03/gtF8HhkZmUNzqvpXpl3LZgC4OjtxOzyCvYeOqGyAOHfqEGt+miv/+/vJCz5pnN7l/Phh8Qbexsdx8kgIQXMnMG3+mnwnaUEoiIO1Jet/nEJi0jtOXLjCjGVr+GnaGJWNEKdOHuenoEXyvydPm/VJ46tRqw4+Ff2IjY0lePcO5s2ewdz5Sz54PpZ/4u79++zZu5+flixUOI/825w8cYKgoCD533nPQ0KOP04eZeWynDp8/NQ5n/wzU1JSOHP6OO06Kp+75v/9fPzrgVMcvnSDVWP6oJvVyHjn8Qu2Hj3HlqlD1D72iuJ+/uepQ6xbMVv+94hJiwpI/c8EfF1f/n87R1fsHN34vl8rwm5dUehF8E+lRz4mPfKx/O93Lx9Rosc4ipWvSsqfv0PW9kp7cIv3VzOHSrx/8wItayeKla/GOxUNEP+PZSX8fxMNEMIHS05OpkGDBjRo0IDNmzdTqlQpnj59SoMGDdSayCvvnTgNDQ15A4Yq48aNY8SIEQrLwp69JT0tDVePnB+3qamZnx8njcXE1Fy+PE4aW2BX+8Jk38FRJ19//wA8cs1Knx2TRCLF1NRMvlwqleLsrPxOrqGhIZqamkglUoXlUqkUE9PCZ4ouiJFhSTQ1NZHkmbBKIpVimucOTzZTY+N8k9FJpHHyu2hGhiXR0tLCwV5xZnMHOxtu3lHdrdK3SnVc3HO2X1paKqCinJ3//vbLpqdXHEtrOyyt7XDzLMuIfm05dXQfLdp1V5o+ezvkveMjlUgwVTFjt4mJCVIl6bPvCmX/K5FI5D2FstM4qzHLvFHJkmhpahKbZ8LJWGmcyokTi6KUV9HoWpgrLNO1MCc17i0ZySm8j5aQkZaGbmmzPGnMSIlS7DmhjHF2OcXlLaf4f1xOOjra2Fll3uHydHEk7P4jfjt4jLH9lP8IquIfqPCkirTUzP1cKpEoqROU7wOGhkZZdUKefUsqwThPnWBgUAIDgxJY29ji4elF5/atOP/nWWrUrK00b3mdoOwYV7mfG+eb5FAijcM06871rdt3kMbF0aXnt/L3MzIyWLlmHbtD9rFp7Wql+eZ836Jx7PkHBODhmbs+T/3gPNT5LiYmJqSlpcl7EWaTSKWYFDB5p6q8C1rPxMREybaWqvUUgoJU9q8mf1IF5JSVVBKLSa79PE4qwdHZNd/6ACUNjdDU1FKYWDV7nbw9KQDOnzvF+5RkatRpoDS/on4+Ni6pn1lP5ZlwMjbuLWaGJQtcd8Pvf/DrgdP8/H1v3O2s5Muv3X1E7NtEGo/KadxPz8hg0baDbDlyjgPzx+TLqyju5xWrVMdFxfWdca7rg3hpLPZOqp/W83eUtrShpKExryOfq/xRLXuXiCwjHQ19xe2koV+SjETlEx3nk5FB+usXaBqXyskzPZ30mCjFZLGv0LJ2UplNUS8rQchL9DURVLp48aLC3xcuXMDNzY3w8HBiYmKYM2cO1atXx9PTM18Phuw7bYXNvK4uXV1dDA0NFV7FiulSXN8AS2tb+cvW3gljEzNuXb8iXzcpKZH7EXdw9yy8e6YqpS2s1c5XX18fa2tr+cve3gETExNCQ68rrBsREY6nlxfK6Ojo4OrqxvVc62RkZHD9+nU8PZWvoy4dHR3cXZ25eiNnHGBGRgZXQ2/ireKxbd6e7lwNVRw3ePl6KGU83eV5eri58Oz5S4U0z15EYlFK9djzzO1nJ3/Z2GVuv9uhf8nTJCUl8uDubdw8PmwMpDpkMhlpqaobzXR0dHB1cyP0+nX5Mvl2ULHtPL28uJ4rPcC1a9fk6S0tLTP3h1xpkhITiYiIwEuNyct0dLRxd3Hkyo2c8dAZGRlcuXGHMh7KL+qLIumF65jVDlBYZl6nKpIL1wGQpaYSd/U25rUDcxJoaGBWKxDphWuF5q+jo42HswOXb+aM0c7IyODyzTDKenz44wQLIpPJ5BfsymTWCTbyl529AyYmpoSG5nyPpKRE7kaE4eGlvAdZZp3gTmjoVfmyjIwMbly/hqdnQb3OZMiQyRs9VOXt7urCtdAbCnlfC72Bt6eqOsGDa9dvKCy7eu06Xlnp69aqycqgxfy8dJH8ZWZqSrvWLZk9fWoB8ebEVBSOvfz1uf0H56HOd3Fzc0NbW1sh/ufPn/Pm9esC6wUdHR3cXF25HhqaL29V63l5eiotJ3Xqn4IU19fHytpW/rKzd8TYxJSbufbZpKRE7kWE4eGpvFecjo4OLq7u3Mx1rs3cz6/irmSdE0cOUsm/GkZGxkrzK/LnY21tvBytFSaQzMjI4FLYA8q7qp43Zd3B0/yy7wTLRvbE20mx4b9J1Yr8Nn0oW6cNkb9KGRvSrdHXLB/ZS2l+RXE/L65vgIWVnfxlY+eMkYkZd27kXB+8S0rg4d3buH7k64PY6FckvI3DyMRcdaKMdDJePUfbPvfNEQ207d0VejkUSEMDTXOrnAaLjHTSXz1F06S0QjJNk1LI3qoeIlXky+rfQlOj6L7+z4geEIJKT58+ZcSIEfTr14+rV68SFBTEggULsLe3p1ixYgQFBdG/f39u3brFjBkzFNZ1cHBAQ0OD/fv307hxY4oXL67287D/CQ0NDRq1aM+e39ZjaWNLaQtrtm9ajYmpOZUCq8vTzRg/lMqBX9OwWVsAkt8lERWZM6749auXPH54lxIlDDEvbal2vqpiatGyFdu2bcXa2hpLC0s2btyAqZkZgYE54zPHjxtLYNWqNGvWHIBWrVqzcOF83NzccHf3ICRkD8kpydSrl9P9LTY2FolEQuTLzB/+jx8/pnjx4pQuXZqSJVXfPWnXshlzFi3Dw9UFT3dXdoUcIDk5hYZ1M2c+nr1wKeZmZvTp3gWA1s0bM3zcFLbv2UtAJT9OnDnL3fsPGTm4vzzPDq1bMGPeIsqX9aJiubJcunqd85cus+gH9btyamho0LB5B4K3r8PS2o5SFtbs3LwKY1Nz/AK+lqf7YeJgKgXUoH7TdkD+7fcme/uVNMS8lCXJye8I2b4O3yrVMTY1IyE+jqMHdiKJeYP/V3UKjKlVq1YsXLAgczt4eBASHExKSop8zpL58+djZmZGz6zH1bVo0YIxo0eze9cuKlepwunTp7l37x5Dhg6Vf8eWLVuybds2rG1ssLCwYOPGjZiZmRFYVb3xuh2bNWRW0Go8XZ3wcnNm+74jvEtJoUntzDKasWQlpcxM6N+1PZA5IePjrPk9UtPSeBMr4d6jJxTX08M2605+0rtkXkTlPCkh8vUb7j16QskSBliWKvzCQstAH4NcF8z6TrYYVvDkfWwcyc8i8Zg5Aj0bC0J7Zt59e7JqGw4Du+A5+3uerduFea0ArNo14q/m/eR5PFr8KxXWzkV65RZxf93AcWh3tA2K82z9brXKqVOz+sxYtgZPF0fKuDqx7cAxklNSaFqrGgDTlv6S+VjNLm3k5fQoqxEtLauc7j56SnE9XXmPh5827yKwYlkszc1IfJfMkbMXuXo7gsUTh6sVE2TuA81btmb7ts1YW9tgYWHJ5o3rMDUzIyCwmjzdxHHfE1C1Gk2btQSgRas2LF44D1c3D9zdPdgbspvklGTq1GsIQFTkS878cYqKvpUwMjIiOjqaXTu2oVusGH6VC74z1aZlC+YtWoK7myse7m7sCdmX2dutbubxMXfBYszNzOjd4xsAWjVvxsixE9ixOxj/ypU49ccZ7t5/wLDBAwHkDcW5aWtrYWpijJ2tjVrlVBSPPXXzGDd2LFWrVqVZ8+z6vODvYmBgQP369Vm9ejUlS5ZEX1+fn1eswMvLS+UP49zltGDhQtzc3PBwdyc4JKTQcho9Zgy7du+mSuXK8nIaOmSIPM+3b9/y+vVrYrLG5T/PGsNvYmKicEe8sLJq2qIdO7dtwMraltKWlmzduBYTUzOqBOY8bnfq+OFUCaxO42atAWjWqj1BC2fj4uaJm7sn+0N2kpL8jtr1GinkH/nyOXduhTJh6lzUVRTPx13qV2fKLzvwdrShjLMdW46c413Ke5p/lTkR56TV2yltbMiQdpnH+boDp1kRfJQf+nXE2tyE6LjMOQj0dYuhr6eLcQkDjEsYKHyGtpYmZkYlcLRSfUMgbzkVtf1cQ0ODBs06snf7WiysMq8Pdm/5GWNTc3wDcp5gNnfSQHwDalKvSeb5L/ldEq/yXB88ybo+MCtlSfK7JIK3/UKlqrUwMjbjddRzflu/jNJWtpTzDcgXR24pV05RvGFn0l89Iz3qKcV8a6ChU4zU25k38PQadkGWEEfK2f0AFAtoQHrkYzKk0WjoFke3Um00DU1IvZkzIfP7yyco3qQ76S8ekPbsPtqOnmg7lyFp+7JCt1tRLitByE00QAgqdevWjXfv3lGlShW0tLT47rvv6Nu3LxoaGqxbt47x48ezdOlSfH19mT9/Ps2zTkAANjY2TJs2jbFjx9KzZ0+6devGunXrPkvczdt0ISX5HauD5pGUmICHd3nGTl+gMGHlq6gXvI3PGYLw4F44M8bnXHxt/CVzLOTXdRoxcPhEtfNVpW3bdiQnJxMUtJTEhAS8y5RhxvSZCmOyIyNfEh+XE9PXNWoQFx/Hpo0bkUgkODs7M336TIVusr8fPMCWLZvlf48ZPQqAYcNHKFwY5VWrejWkcfH8unkbEokUF2dH5k6bIB+C8fpNNJq5JuMp6+XJhFHfsXbTNtZs2IKNtRXTJ4zGKdfM9tUD/Rk+sA9bduxh2apfsbOxZtq4UZQr82F3iJq2/oaU5GTWLJ9DUmIC7t7lGTN1cZ7t95y3uWZdfng/jFkTBsn/3rQm86kr1Ws3pv+wyWhqavLy+WPOnDjI23gpJQyNcHb1YtKcn7G1L3hCwxo1ahAfF8fGTZuQxMbi7OLC9Bkz5NvhzevXaOYaZ+vt7c3oMWPYsH4969atw8bGhkmTJuHo6ChP07Zd1v6wdCkJCQmUKVOG6TNmqD1Gv85XAUjj3/LL1t3ESuNwdbJnwaTvMc0aWvAqOgbNXC3m0RIJPUdOkv+9NeR3tob8jk8ZT5bNGA9A+INHDJ2cM4Y06NctADSq9RUThvQtNCYjv7IEHt+YUw7zM/N9tmE3N3qPQ9eqFMVzdRN+9/g5fzXvh/eCcTgO6Uby8yhu9ptI9NGcx/NF7vidYqVMcZ8yFF3LUsSHhnGp6be8f63eJFp1q1VBEv+WX7YFEyONx83RjkUThucqp9g85SSl+/c5DWZb9h5my97DVPT24KfpowGQxMUzPWgNMZI4SugXx8XBlsUTh1OlgnoTrWZr3bYDycnJLA9alFUnlGXq9DkK+0BUnjqheo1axMXHsWXjuqw6wYWp02fL90WdYsW4c/sWe0N2k5iQgLGxCWXKlmPugqX5JvXLq+bXXyGNi2P9pq1IJBJcnJ34YfoU+WR9r9+8UXgWeRkvT8Z9P4J1Gzfz64ZN2FhbM3XCWJwcHT6oHApSFI89dfOIjIwkLj6nG3Zh3wWgb79+aGhqMmvmTFJTU/Hz82PgoEEUpkaNGsTFx7Np40ZiJRJcnJ2ZMX26PO/MbZdTn3t7ezNm9GjWb9igspwuXLjAwkU548jnzM38kd+lc2e6du2qdlm1bNuJ5OR3/Bw0n8TEBDy9yzFpxo8K9XlU5EuF83G1r2sTFydl26a1SCWxODm7MnH6j/mGYJw4ehAz81JU8K3Mhyhq5+MG/uWRvE1gRfAxYuLe4mFvxbIRPTEzymy0iIqRKuznO05eIDUtne+Xb1bIp2+LOvRvWfeDyqIgRW0/B2jcuhspycms++kHkhITcPOqwKgpSxT2p9dRLxSeyvDofhhzJg6Q/7117WIAvqrdhD7fTUFTU5Nnj+9x9uQBkhLfYmJaijI+/rTp0g8dnYLrhbS710jWN0C3aiM09A3JePOCpN0r5Y/W1CxpQkbW4+sBNHSLU7xeBzT0DZGlJJH+6hmJW5eQEZvT+J92/ybJx3ZQrEpd9Gq1JiP2De/2/Ur6y0dqlVFRLStByE1DJst1ZAhClpo1a+Lj48PixYu/dCgqXbtX+Djwz62k5tvCE31mxdPVf3b05xIpsy080WdmovNxZ4D/WAzfqTcT+ud0yUf5XAdfUuDVNV86hHze6H+8H+MfS/GMolcfAKRqFd6QK4BGEbxkS5IZFJ7oM9PTePelQ1DK6lXhw8c+tyhLny8dQj5v3psVnugz8z445UuHkM+dxl9+slBlAjz/PfNR5Zbw87gvHYJKJfrPLjzRv4iYA0IQBEEQBEEQBEEQhE9ONEAIgiAIgiAIgiAIgvDJiTkgBKVOnTr1pUMQBEEQBEEQBEH45DQ0xH35z0WUtCAIgiAIgiAIgiAIn5xogBAEQRAEQRAEQRAE4ZMTQzAEQRAEQRAEQRCE/65cj5oWPi3RA0IQBEEQBEEQBEEQhE9ONEAIgiAIgiAIgiAIgvDJiSEYgiAIgiAIgiAIwn+Whqa4L/+5iJIWBEEQBEEQBEEQBOGTEw0QgiAIgiAIgiAIgiB8cqIBQhAEQRAEQRAEQRCET040QAiCIAiCIAiCIAiC8MmJSSiFfy19zXdfOoR8MtD60iHkk6Kl/6VDyMch5d6XDiGfeB3zLx2CUvp/7vvSIeQTeHXNlw4hn/O+vb90CPlUuL3rS4eQj3ZG6pcOQakUzaJXT2lqpH/pEPKRaRS959Rrk/alQ8hHk4wvHYJSUnO3Lx1CPhmyonfdYqST8KVDyCe9TqsvHUI+JbWTvnQIKhh96QCEIk40QAiCIAiCIAiCIAj/XUWwgff/lRiCIQiCIAiCIAiCIAjCJycaIARBEARBEARBEARB+OTEEAxBEARBEARBEAThv0tT3Jf/XERJC4IgCIIgCIIgCILwyYkGCEEQBEEQBEEQBEEQPjkxBEMQBEEQBEEQBEH47xJPwfhsRA8IQRAEQRAEQRAEQRA+OdEAIQiCIAiCIAiCIAjCJycaIARBEARBEARBEARB+OREA4QgCIIgCIIgCIIgCJ+caIAQBEEQBEEQBEEQBOGTEw0Qn0jNmjUZNmyY/G9HR0cWL178xeL5O06dOoWGhgZSqfQf5fNv/O6CIAiCIAiCIPw3aGhqFtnX/xvxGM7P5K+//sLAwOCTfsa6desYNmzYP24w+Ng+x3fPTSaTsWXTeo4cOkhiYgJe3mUYMOg7rG1sC1zvwL4Q9uzajkQSi5OTC30HDMbdw1P+/vKgRYReu0psbAx6esXx9PamR88+2NrZqxXT5k3rOXLod3lMAwcNVSum3bt2yGPqN2CQQkzLghYrxOTl7U33nt9ip0ZM+/btY+euXUgkEpydnBgwYAAeHh4q0585c4YNGzfy6tUrbKyt6dmrF1UqV5a/f+7cOQ4cPMj9+/d5+/Yty4KCcHFxKTSO3HYdPMrW4IPESuNwcbRj+Lfd8HZXnsfDp89Zs3UXEQ8eE/UmmqG9utC+WcN/lKcq+/btY9fOnUgkEpycndUqq40bNvDq1SusbWzo1bMnlatUkb8vk8nYtHEjhw4dIjExEW9vbwYNHoyNjY3aMf127T4b/oogJjEZ91LGjK5TkbJWpoWudzj8KeP2X6SmqzULW1aTL49JTGbpHzc4//gVCSmpVLQ1Z0yditiblFQ7pp2/n2Dz3kPESuNwdbBjRO/OlHFzVpr24bMXrN4WTPjDJ0S9ieG7Hh3p2LSeQprdh0+y+/ApIt9EA+BsZ02vts0J9C2nVjymX1XCeWRvjHzLomddmsttBvJq7/GC1/m6Ct7zx1LC243kZ5Hcn72C5xv2KKRxGNAZ5xG90bUsRfyNcG4Pm0HcXzfVigkg+MDvbN8dQqxEiouTI0P69cbT3U1l+tNn/+TXTVuJev0GW2sr+vToin8lP/n7cxcFceTEKYV1Kvv6MGfaJLVj2nPgMNuC9xEricPF0Z7v+vbEy91VZfqT5y6wdvN2ol6/wcbakv7dOhNQqaL8/aR3yazasIWzFy8T9/YtVqVL06ZpQ1o0qqcyT2Uy684NHM5TdxZ2rOzftzdX3elMvwGD8MiqO9++jWfzpo1cu3qFN29eY2RkREBgVbp+00Otc9XfPX4Lq0fev3/P6tWr+eP0aVJTU/H182PQoEGYmJgUGlNRrKOy89myaR1Hs87Hnt5l1TwfBxOcdT52dHKh74AhCue+3PlPnzyOq1f+YtzEaQRU/arAfIvieQ8y64Tfdu/NqhMcGNKvN14F1Amnzv7Jr5u2KdQJAZV8FdI8efacVes2cePWHdLT03Gws2XquFFYlC6lVkxF9djbumkdRw8dkO9P/QcNK3R/OrgvmD27fkOatT/1GTAEdw8v+fsTxgzn9s1QhXUaNGrGgCHDC41p56GTbNp3JOu8Z8vIXp0o4+qkNO3DZy9Z9VsI4Y+eEvUmhmHd29OxSd186V7HSli+aTfnr98iJeU9tpalmDiwB14ujoXGk00mk7Ft068cPbyfpMQEPL3K0nfQiELL6vf9ewjetS2rrFz5tv9Q3LLK6vWrSPr36qR0vVFjp1K1ek214xP+2/7/mlQ+svfv33+UfEqVKoW+vr7K91NTUz/K5xRFhX33j233zt/Yv3cPAwZ/x4+LlqGrp8eUSWML3JZnTp9kzeqf6dj5GxYF/YyjszNTJo1FKpXI07i4ujF0+PcsX7mWaTPngAwmTxxDenp6oTHt2vkb+/cGM3Dwd8xfFISenh6TJ40rJKZT/LJ6JZ06d2Vx0AqcnJ2ZPGmcQkyurm58N3wUP61cw7SZs5HJZEyeOLbQmE6fPs2q1avp0rkzQUFBODk7M3HSJJWNV3fu3GHO3Lk0qF+fZUFBBAYGMmPGDB4/fixPk5ycTJkyZejVs2eh5aHM8bMXWPbrFnp2aMWaBTNwdbRnxPR5SKRxStOnpLzH2qI0/b9pj5mJ0UfJU5nTp0+zetUqOnfpQlBQEM5OTkyaOLHAspo7Zw71GzQgaNkypWW1c8cO9u7dy+AhQ1i0eDF6enpMmjhR7frmcPgzFp4KpW+gN1u+qYdbaSMG7fyD2MTkAtd7GZfIolM3qGhrrrBcJpMxIvgcz+MSWdSyGlu61cPK0ID+2//g3fs0tWI6du4SS9f/Ru92zVk3bwpujnYMn7mI2Lh4pemTU95jbVGKgV3aYGasfPuVMjNhYNc2rJs3mV/nTsKvrBej5wXx8NkLtWLSMtAn/kYEt4ZOUyt9cUdbKu9dScypi5yt1IJHQespt3Im5vVyftRYtWuE14/juDdzOWertOLtjXD8D6yhWKnCG38ATp45x8+/rKNbp/b8vPhHXJwcGDN5hsp98nZYODN/XESj+nVYuWQ+1QKqMHnWPB49eaqQrrJvRXZs+EX+mvB94RfO2U6c+ZPlazfSvUNbVi+cjYuTA6OmzlYZ062wCGbMX0rjurVYvWgO1f0rMWH2fB4+eSZPs3ztBi5dDWXC8EFsWLaAts0bsWTVr5y7eFntuAB27dzOvr3BDBo8lAWLlqpVd/6Rq+5cEvRTVt05Xl53xsTEEBsTQ69v+7B8xSqGDR/FlcuXWbJ4gVox/Z3jV516ZNXKlVy6eJFx48czd948YmNimDlzZqHxFMU6Ktvunds4sHcPAwYP48dFy9DT02OqGufjtat/pkPnbiwM+hknZxemThqjcO7Ltjd4FxoaGmrFUhTPe5BZJ6z4ZT3dOrVj5eJ5uDg5MmbyzAKOv3Bm/riYRvXrsGrJj1QLqJyvTngRGcV3YyZib2vDwh+msjpoAV07tqVYsWJqx1UUj709O7exf+9u+g8ezrxFy9HT02PapDEFxnT29EnWrl5Bx87dWBi0EkdnF6Yp2Z/qNWzCr5t2yl/de/ctNJ6jf/7Fkg07+LZtU9bPnYibgx3DZi0p8LxnY1GKQZ1bYWZsqDRNfEIifSfNQ1tbi0Xjh7J10TSGdmtHSYMPu47es3MrB/btov+gEcxZuAJdveLMmPQ979+nqFzn7B8n+HX1T7Tv3IP5S1fj6OTC9Enfy8vKzLw0azbuUnh17NITveLFqVipisp8BSEv0QCRR82aNRk8eDDDhg3D3NycBg0acOvWLRo1akSJEiWwsLDgm2++ITo6Wr5OYmIi3bp1o0SJElhZWbFgQf6KNO8wBA0NDVasWEHz5s0xMDBg1qxZAISEhODr64uenh7Ozs5MmzaNtLScHwBSqZR+/fphYWGBnp4eZcuWZf/+/Zw6dYqePXsSFxeHhoYGGhoaTJ06tdDvm5KSwpgxY7Czs0NXVxdXV1fWrFmjkObKlStUqlQJfX19qlatSkREhPy9Bw8e0KJFCywsLChRogSVK1fm2LFjhX73X375hVatWqGvr4+bmxt79+4tNFZ1yGQy9gbvpn3HLgQEVsPJyZnhI8cQGxPDhfPnVK4XsmcX9Rs2pm79htjbOzBw8DB0dXU5duSQPE3DRk0pW648FhaWuLi60aVbT6LfvOH161dqxLQnK6aqascUvGcXDRo2yhXTd+jq6nL0yOFcMTWRx+Tq6kZXNWPas2cPjRo2pH79+jjY2zNk8GB0dXU5cuSI8vIJCaGSnx9t27bF3t6ebt264eLiwr59++Rp6tSpQ5fOnalYsaLSPAqzbe/vNKtXkyZ1vsbJzobv+/dET1eX/cf/UJrey82ZQT06Ubd6IDraOh8lT2X27NlDw0aNqF+/PvYODgweMqTQsvKrVEllWclkMoKDg+nYsSOBgYE4OTkxctQoYmJiOP/nn2rFtPnyXVqVc6JFOSeczQ2ZUM8PPR0tQm49VrlOeoaMCQcu0r9aGWyNFO80PZUkcDMylvF1fSljZYqjaUnG1/MlJS2dQ+FPVeSoaOu+IzSv+zVNa3+Fk501o/t+g65uMfafOKs0vberE0O6tafeV/7o6CjvjFe9kg9VfctjZ2WBvbUl/Tu3prieLrfuPlQrpjeH/+DulMW8CjlWeGLAoW9H3j16TtjouSSEP+TJT5uJ2nUYp+96yNM4DevJszXbeb5+NwlhD7g5cArpScnY9Wij1mfsDN5H4wZ1aVi3No72dgwb2A9dXV0OHVXeM2P33gNU9q1Ih9YtcbCzpWfXTri5OBG8/3eFdDo62piamMhfJUuUUCsegO0hB2havzaN69bE0d6WkQO+RU+3GAePnVL+Hfb9ThXfCnRq3QxHOxt6d+mAu7MTew7k1E23w+/SoPbXVCxXBiuL0jRvUBcXJwfC7j1QOy6ZTEZI8B46dOwsrztHjBxNbEwM59WoO+vVb4C9vQOD8tSdjo5OjJ84GX//QKysrKngU5Fu3Xty6eLFQhtv/+7xW1g9kpiYyJEjR+jTpw8+Pj64ubkxfMQIwu7cITwsrMCYimIdlZ3PvuDdtOvYFf/Aajg6uTBs5BhiY6K5cF55vQAQsmdnrvOxIwOUnI8BHj64T8juHQwZ9r1a8RTF8x7Ajqw6oVFWnTB8YF90dXX5/egJpel37z1IFV8fOrZugYOdLb2U1AlrN26hip8v/Xp+g5uLMzZWllTzr4yJisbevIrqsbcveBftc+1P340cS2xMNBcL3J92UL9hY+rUb4SdvSMDBg9HV1eX40cU61BdXV1MTE3lL339wntkbN1/lBZ1vqJprWo42Vozpk8X9IoVY/9J5WXk7erIkG/aUq9aFXR0lF+3bAw5jIWZCZMG9qCMqxPWpc3xr1AGW8vShcaTTSaTsT9kJ207fEOVwK9wdHJh6MhxxMZGc6mAstq3Zwf1GjahTr3Msuo3eAS6enqcOHIQAC0tLUxMzRReF8+fodpXtShe/PPdaPxkNDSL7uv/zP/fN/oI1q9fT7FixTh37hxz5syhdu3aVKxYkcuXL3Po0CFevXpF+/bt5em///57Tp8+TUhICEeOHOHUqVNcvXq10M+ZOnUqrVq14ubNm/Tq1YszZ87QrVs3vvvuO+7cucPKlStZt26dvHEiIyODRo0ace7cOTZt2pTZOj9nDlpaWlStWpXFixdjaGhIZGQkkZGRjBo1qtAYunXrxtatW1m6dClhYWGsXLmSEnkuXCdMmMCCBQu4fPky2tra9OrVS/5eQkICjRs35vjx41y7do2GDRvSrFkznj4t+EfLtGnTaN++PTdu3KBx48Z06dKF2NjYQuMtzKuoSCSSWCr45HRFNDAogbuHFxFhd5Suk5qayv37d/HJtY6mpiYVfHwJD1e+TnLyO44fPYSFpSXm5gV3Z3wVFYVEEouPT84FioGBAe4enoQXElOFPDH5+PgSUUBMx44eLjSm1NRU7t2/j4+PT568fQgLD1e6Tlh4OD55LrD8/PxUpv9Qqalp3H3wmEoVyijEVKl8GW5H3P9ieaampnL/3j2lZaXqR0F4WBgVc6WHzLLKTh8VFYVEIlEoTwMDAzw8PNQqz9T0DMJeSfB3sMiJSUMDf3sLbryMUbneqvN3MNXXpWW5/F1D36dnAFBMW0shz2Lamlx/EZ0vfb6YUtOIePiEyuVzurRqampSuZw3tyLU/8FZkPT0DI6evUhy8nvKfeAQGnUZB/gQfeK8wrI3R89iEuADgIaODka+ZYg+nutHmExG9Ik/MQ4o/AdIamoqd+8/wLdCefkyTU1NfH3KcyfirtJ17oTfxc+nvMKyShV9uBMeobAs9NZt2nTtSff+Q1j800ri4t8WGk9mTGncffAIvwo5w1o0NTXxq1CO2ypiuh1xTyE9QOWKFRTSl/F059ylK7yJiUUmk3H1xm2evYikcsXyebNTKafuzF2fG+Dh4any+MusO+8p1LeZx2xFwsNV/5BPTExEX18fLS0tlWng7x2/6tQj9+7dIy0tTSFfOzs7SpUuXWC9UBTrqGx/93z8QMm5r0Kec19KcjIL5s2i38ChmJgW3vuoKJ73suO6e/8hfnnqBD+fctyJiFC6zp3wu/jmqRMqV/Thdnjm8ZeRkcGFy1exs7Fi9OQZtO7ai4Ejx3L2/CW14yqKx172/lTeJ2f4mbr7U+51Mvcnv3zXUn+cPM43HVsydEAvNv66mpTkgnsUpqalEfHwKZXL5T3veXFTzUZyZc5cDsXL2YHxC3+m0bcj6TZ6BsHHznxQHq+iIpFKYqmQp6zcPLxVXkNmllVEvrIqr6Sssj24F8Gjh/epU7/xB8UnCGIOCCXc3NyYN28eADNnzqRixYr88MMP8vfXrl2LnZ0dd+/exdramjVr1rBp0ybq1KkDZDZg2NoWPMYKoHPnzvTM1W2vV69ejB07lu7duwPg7OzMjBkzGD16NFOmTOHYsWNcunSJsLAw3N3d5WmyGRkZoaGhgaWlpVrf8+7du2zfvp2jR49St27dfPllmzVrFjVq1ABg7NixNGnShOTkZPT09KhQoQIVKlSQp50xYwZ79uzJ7Lo5eLDKz+7RowedOmWOI/vhhx9YunQply5domHD/GP4IbOnRkqKYrex9ykpFNPVVVgmkWR2EzPOM2bW2NgYiUR5A0d8fBwZGRlK1jHhxbNnCssO7g9h3drVJCcnY2Nrx/RZ81S2YufEFKsiJhN5vKpiyjv219jYhOd5Yjqwf69CTDNmzS0wpvj4eKV5mxgb58s75ztIMDE2zpdeVfwfKu7tW9IzMjA1Urw7Y2psyJMXL79YnqrKytjEhGfPnytdRyKR5N/WJjnbOvtfZXmqU57Sdymky2SYGugpLDc10ONxrPIfndeeRxNy8xFbuykff+9oWhLLkvos++MmE+r7UVxHm82X7/Lq7TveFDKsA0AqL2vFLqWZZR1Z6PoFuf/kOX0n/MD796kU19NlzuhBONlZ/6M8VdG1MCfllWKDS8qraHSMSqKpp4uOiRGa2tqkvI7JkyYGAw/lc13kFhf/Nmt/MlZYbmJsxLPnyoeVxEql+e5amhgbE5ur23hlv4pUrxqApUVpXkZGsWbjFsZNnUnQjz8UelEfFx9PekaGks8w4ukHxWRErCSny/h3fXsyf/lq2vYaiJaWFpoaGowa1JcKZbzyZqdSTt1prLDc2NgEqcq6M15lfa6qfouLi2Pb1s00bFT4RfTfOX7VqUckEgna2tr5bgCYGBsjKaBxvijWUbk/J3s9hXzUOPcVtv3WrP4JT68y+AdWy5uFinyL3nkPctcJ+Y/xgo+/vHEZIcmqE6Rxcbx7l8zWncH07NqRvj26cunKdabM/pGFs6ZSoVyZ/JnmURSPPamKaykjYxOV13dvVexPRsYmPH+Wc6Ps65p1KF3aAhNTM548fsiGtat48eIZYydOVx1PfELmeS/PUAoT45I8fvn3z3svX79h99HTdGpSj+6tGhP24DGLft2GjrYWTWpWVSuP7LIyMlFsnDNWp6yM86/z4pnym4rHjhzE1s4BT++yasUlCNlEA4QSfn45rX+hoaGcPHky30UBZA4/ePfuHe/fv8ff31++3NTUtMBJjbJVqlRJ4e/Q0FDOnTsn7/EAkJ6eTnJyMklJSVy/fh1bW1t548M/df36dbS0tOSNC6qUL5/T0m5lZQXA69evsbe3JyEhgalTp3LgwAEiIyNJS0vj3bt3hfaAyJ2ngYEBhoaGvH79WmX62bNnM22a4jjuQUOGUa58BX4KWiRfNnnarLyrflQ1atXBp6IfsbGxBO/ewbzZM5g7f4nCuMpTJ4+zPGhxrpgKH8P7T9SsVYeKFX2JjY1lz+4dzJ09k3nzF3/QWE/h/1fi+1QmHbzIpPp+mOjrKk2jo6XJ/BZVmX74L2ouC0FLQ4MqDqWp5mSJTPaZA87DwdqS9T9OITHpHScuXGHGsjX8NG3MJ2uE+Deq/XXOHBXOjg44OznwTZ9BhN66rdDb4nPavf8QdyLu8cOE77EsbU7o7TAWr1yLuakJlXyUTyJ68uRxlgctkf895RPXnQBJSYlMmzIRe3t7Onf5Jn9MJ04QFBQk/zvveUjIcerkMVbkOh9PmvZDAan/vosX/uRG6HUWBa38JPn/22VkZFbaVf0r065lMwBcnZ24HR7B3kNHlDZAFMVj7/TJY6wIWij/e+K02Z8slgaNmsr/7+jkjImJKZPHjyIy8gVWVh828eo/lZEhw8vFgQGdWwHg4WTPg6cv2XP0D5UNEKdPHmXlspzh3xOmzvnkcaakpHDm9DHadez2yT/rs9FUbz4Z4Z8TDRBK5J6JNyEhgWbNmjF37tx86aysrLh//+91D8/7OdmfNW3aNFq3bp0vrZ6eHsWLF//bn6WMuvnlvpuePdlTRkZml+1Ro0Zx9OhR5s+fj6urK8WLF6dt27aFTlSV9w69hoaGPE9lxo0bx4gRIxSWPXn+mrT0dIWZsdOyJvOUSiSYmprJl0ulUpydlXfbNjQ0QlNTM1+rvlQqwdhUsdXcwKAEBgYlsLaxxcPTi87tW3H+z7PUqFlbnqaKf6BCTKkqY5IUGlPeOy1SqQSTfDEZYGBgII+pU/vW+WJSzNtQad4SqVRlV1YTExP53RWF9GrMzq4Oo5Il0dLUJDZOcdKtWGk8Znnu9HzOPFWVlVQiwVTFdzcxyX+HSCqRyMsq+1+JRIJprvKWSiQ4qzF7unFxXbQ0NPJNOBmbmIxZnl4RAM+libyMT2LYnpwxqRlZrQqVF+xkd++G2BmXwNvShG3d6/M2JZW09AxM9HXptuk4XpaFb2NjeVkrTryVWdbqjTlWRUdHGzurzOEmni6OhN1/xG8HjzG238e/6El5FY2uheIEnboW5qTGvSUjOYX30RIy0tLQLW2WJ40ZKVGFD1UxMiyZtT9JFZZLpHGY5rnTmM3U2DjfZHQSqRTTAvZha0tLjAwNefEyqtAGCCNDQ7Q0NZV8xofGFIdp1l3clJT3rN60jZnjRhKYNTO/i6MD9x8+4bfg/SobIPz9A+Wz5UPuulOar+50Ull3Gqqsz/PWb0lJSUyeNIHi+vpMmDQVbe38l0T+AQF4eOaP6UOOX3XqERMTE9LS0khISFC44VFQvaxu3nl9qjqqin9VPHI9WaCgc5/q7af6fJxdDjdDrxEV+ZLO7ZorpJn7wzS8y5Rj1tyF5FUUz3uQu05QcowXePzljStO3ivCyLAkWlpaONgr9sR1sLPh5h3lw0eK4rFXxb+qwpMqUlPfZ8WkuD/FSSU4OSt/Yk9JFftTnJKYcnP3zPzcqJcvVTZAGBuWyDzvSRXPexLp23903jM3McLRVrGB3dHWklMXVQ/truJfLU9ZZW6/OEmsku1XSFlJFXtISKUSjE3yl9X5c6d5n5JCzToNCv9SgpCHmAOiEL6+vty+fRtHR0dcXV0VXgYGBri4uKCjo8PFixfl60gkEu7eVT52trDPioiIyPc5rq6umeOwypfn+fPnKvMuVqyYWk9kyFauXDkyMjI4ffr0B8ea7dy5c/To0YNWrVpRrlw5LC0tFWaI/lh0dXUxNDRUeBXT1UVfXx9raxv5y87eARMTU0JDr8nXTUpK5G5EGB5e3krz1tHRwdXVndDQnMo9IyODG9ev4empfJ1MMmTI5I0e2fLGZK8ypnA8C4npRq51MjIyCL1+DQ81YiroqSo6Ojq4ubpyPTTnkVMZGRlcv34dL8/8jzkD8PL05Pr16wrLrl27pjL9h9LR0cbdxZErN3LGGWZkZHDl5m3KeKh+FOCnzlNHRwdXNzdCc3337LLy9FLeldzTy0tpWWWnt7S0xMTERCHPpMREIiIi1CpPHS1NvCxMuPQ0p8dQhkzGpaevKW9tli+9o2lJtnevz9Zu9eSvGq7WVLIvzdZu9bAsqThxVEldHUz0dXkqecudV7HUdC28p4GOjjYezg5cvpkzzjcjI4PLN8Mo6/Fx52uQyQrev/8J6YXrmNUOUFhmXqcqkgvXMz87NZW4q7cxrx2Yk0BDA7NagUgvXKMwOjo6uLu6cO1GziM7MzIyuBZ6A28P5T3bvD3duRp6Q2HZles38PZU3cvuTXQM8W/fYmZa+A+lzOPEiSs3binEdPXGLcqoiKmMh5tCeoDL12/I06elp5GWlp7v6QSaWppkyFQ3NKuqO6/nqTsjIsJVHn+ZdacboaHXFb5P6PXreHrmrJOUlMikiePQ1tZm0uRpKnuMZcZkLX/Z29t/8PGrTj3i5uaGtra2Qt3x/Plz3rx+XWC9UJTqKH19faysbeSv7PPxjVznVnXOxy5Kzn03cp372rTrxJLlq1m8bJX8BdCrzwCGDlc+IWVRPO9lx+Xu6szVPHXC1dCbeKvoSZtZJyg+9vfy9VDKeLrL8/Rwc+HZc8Whhs9eRGJRSvn8UEXx2Cueb39y/Af7U97ru6sFXks9epA5d1FBjRQ62tp4ONvz162cRp2MjAz+uhVGOffCh+SpUt7DlacvoxSWPXv5CssCnrSUWVa28pedvSPGSsrqXsQdld87s6w8uHE9b1ldUbrO8SMHqORfFSMj4w/8hoIgGiAKNWjQIGJjY+nUqRN//fUXDx484PDhw/Ts2ZP09HRKlChB7969+f777zlx4gS3bt2iR48eaGp+eNFOnjyZDRs2MG3aNG7fvk1YWBjbtm1j4sSJANSoUYOvv/6aNm3acPToUR49esTvv//OoUOZM0M7OjqSkJDA8ePHiY6OJikpqcDPc3R0pHv37vTq1Yvg4GAePXrEqVOn2L59u9oxu7m5sXv3bq5fv05oaCidO3cusCfDp6ahoUHzlq3Zvm0zFy/8yeNHD1k0fy6mZmYE5BorOnHc9+zfFyz/u0WrNhw5dJDjx47w7OkTVixfQnJKMnXqZc5JERX5kh2/beH+vbu8ef2KsDu3mfvDDHSLFcOvcsGPHsqMqRW/bduSFdMjFs6fly+mCXliatmqDYdzxfTT8qUkpyRTt16DrJgi2fHbVu7fu8vr168Ju3ObOVkxVSokplatWnHo0CGOHjvG06dPWbZ8OSkpKdSrlzlHwPz58/n1119zyqdFC65cucKu3bt59uwZmzZt4t69ezRr1kye5u3btzx48IAnWcNvnj9/zoMHD9SeXLRj80bsO3qK30+c4fGzF8xfuY53ySk0qfM1ADOW/MzPG3+Tp09NTePeoyfce/SE1LQ03sRIuPfoCc8jX6mdpzqyy+rY0aM8ffqU5cuWqVVWu3ftUlpWGhoatGzZkm3btnHhwgUePXrE/AULMDMzI7CqeuM7u1RyZ8+Nh+y79ZiHMfH8cPQq71LTaF7WEYBJBy8R9EfmBaquthaupYwUXiV1dTAopo1rKSN0tDLrqqMRz7j89DXPpQmcuv+CATv+oKarDYGO6s0p06lZffYe+4MDp87x+PlL5q3eRHJKCk1rZe7j05b+wk+bd8nTp6amcffRU+4+ekpaWhpvYiXcffSUZ7m230+bd3HtTgSRr6O5/+Q5P23exdXbETSoHpDv85XRMtDHsIInhhUyfzDoO9liWMETPbvMoWQeM0dQ4dec3m1PVm1D38kOz9nfY+DhjEP/zli1a8SjJevkaR4t/hW73u2x+aYlJTydKbt8KtoGxXm2frdaMbVt2YwDh49x+PhJnjx7zuKfVpGcnEKDupk9luYsXMov6zfJ07du3oS/rl5n+569PH32nPVbfuPu/Qe0bNoIgHfv3rFy7XruhN8l6tVrrobeYNLMOVhbWVLJ10etmNq3aMKBIyc4dOI0j5+9YOHPa3iXnEKjupnD82YtWs6qDVtzvkOzRly6Gspvwft58vwFv27dQcSDh7Rqklk3Gejr41PWi5/XbebazdtEvnrN78dPcfjkH1QPqKxWTJB5rLSQ153nFerOwFx15/hxo9m3L0T+t2Ld+TRf3ZmUlMikCeNISU7mu2EjeJeUhCQ2FklsbKGN+Ooev+PGjmVfrqc7FVaPGBgYUL9+fVavXk1oaCj37t1j0cKFeHl5qfzBp27eX6KOys6nWZ7z8eL5czA1MycgMGfY0KRxozigcD5uy5FDBzhx7DDPnj7h5+WLFbafiakpDo5OCi+AUqVKY2FpVWg5FaXzHkA7eZ1wKqtOWE1ycgoN69YCYPbCpaxev1mevnXzxrnqhBes2/Ibd+8/lNcJAB1at+DU2T/Zf/goL15Gsmf/75y/dJkWjdW7W11Uj71mLduwY9smLl04p7A/+SvsTyM5sG+P/O8WrdpxVMn+lH19Fxn5gt+2bOT+vbu8ehXFpQvnWLxgNmXKlsfRqeAG9E5N67H3+BkOnPqTR88jmffLZpJT3tOkZtZ5b9laftqSc25ITUvj7uNn3H38LOu8J+Xu42c8i8q5odCxSV1u3XvIut0HeRb1msNnLxJ8/AxtGtQqMJa8ZdW0RVt2btvIpQvnePL4IUsX/ICpqTlVcpXVlPEjOLgvJ75mrdpx7PB+Th47xPOnT1i5fBEpycnUrtdIIf/Il8+5c+sGdes3UTsmQchNDMEohLW1NefOnWPMmDHUr1+flJQUHBwcaNiwobyR4ccff5QP1ShZsiQjR44kLk+3b3U0aNCA/fv3M336dObOzZxI0NPTk2+//VaeZteuXYwaNYpOnTqRmJiIq6src+ZkjvWqWrUq/fv3p0OHDsTExDBlypRCH8W5YsUKxo8fz8CBA4mJicHe3p7x48erHfPChQvp1asXVatWxdzcnDFjxhAfr/z5x59L67YdSE5OZnnQIhITEvAuU5ap0+cotLJHRb4kPtc2ql6jFnHxcWzZuA6JJHNoxNTps+VdLXWKFePO7VvsDdlNYkICxsYmlClbjrkLlmJsXPhdxjZZMS0LWiyPadr02XliiiQ+Vxf26jVqEhcvZfPG9fKYpk3/IVdMOty+fZO9IbtJyBXTvAVLCo2pRo0axMXHs2njRmIlElycnZkxfbo879dv3qCRqxHN29ubMaNHs37DBtatW4eNjQ2TJk3C0dFRnubChQssXJQz/ndO1rClLp0707Vr10LLqM5XAUjj3/LLtl3ESuJwdbJnweTvMc3qyvjqTQyaue6oRksk9BwxUf731pCDbA05iE8ZT5bNnKBWnuqoUaMG8XFxbNy0CUlsLM4uLkyfMUNeVm9ev1aIy9vbm9FjxrBh/XqVZdW2XTuSk5MJWrqUhIQEypQpw/QZM9Set6OBpx2SpBRWnLtNTFIyHqWMWda2unwIRlR80gcPZYxOTGbhqVBiEpMxNyhO0zIO9AksqLeNorrVqiCJf8sv24KJkcbj5mjHognDc7ZfdCyamrm3n5Tu3+eMp9+y9zBb9h6morcHP00fDYAkLp7pQWuIkcRRQr84Lg62LJ44nCoVCp9EDcDIryyBxzfK//aen1m3Pduwmxu9x6FrVYridjk/WN49fs5fzfvhvWAcjkO6kfw8ipv9JhJ9NOexZZE7fqdYKVPcpwxF17IU8aFhXGr6Le9fq34CSW61qlcjLi6OdZu3IZFIcXF2Ys60ifLu1q/fRCv0HCjj5cmEUcNYu2krazdsxsbaiukTRuPkYA9kzlL+8PETjpw4RUJiEmamJlSqWIEeXTpRrJAJcrPVrl4VaXw8a7fsIFYixdXJgR+njJUP83gdHa2w7cp6eTBp5BDWbPqN1Ru3YWttyaxxo3B2sJOnmTzqO1Zt2MrMhcuIT0jAslQpvu3akRYNlU+Eqkqbtu0zj5Vcdef06T8oqTtz6vOva9QkLj6OTRs3ZNWdzkyfPkt+zN6/f5+IiMy7ln1691D4vDW/bsDCouBGN3WO38jISOJynQsLq0cA+vbrh4amJrNmziQ1NRU/Pz8GDhpUaBkVxToqW+u2HUlOTuanoIUkJiTgVaYcU/Kd+/Kfj+NznY+dnF2YMn2O0m7gH6Ionvcgs06QxsXzq7xOcGTutAkKdYJmrsfwlfXyZMKo71i7aRtrNmzJVycAVA/0Z/jAPmzZsYdlq37FzsaaaeNGUe4DJoEtisdeKyX70+RCru++qlGLuHgpWzf+mmt/mivfn7S1dbhx/Qr7Q3aRnPwO81KlCaz2Ne07Fb796lWtjDT+Lau3780679myaPxQzLImpoyKjlWoz9/ESuk2eob87837jrB53xEqeruzYmrmk+u8XR2ZO2ogK7bsZu2u/ViVNmdY9w40rO7Ph2jVthMpycn8HDSfxMQEvLzLMWnGPIoVy5kLKiryBfHxucrq69rEx0nZuulXpJJYnJxdmTR9Xr5j7/jR3zEzL4WPr/oNyoKQm4ZM9qWnGBOEvyfigfJZlb8kDYre4aTNp+mu/k+UTFHvx9rnFK9nXniiL8Dy+NovHUI+KQHKn1bzJZ337f2lQ8inwu1dhSf6zLQzil59APBW55/9uPwUNDXUH9L4X5YqK3oTHhcjpfBEX4BuesE9U7+EJC3DwhN9ZmlF8P6oZcLfn/PtU3lp8HEmpf/Yyriq7olUlL3b8ukmOv2nince96VD+KiK3hEuCIIgCIIgCIIgCJ+JhoaYmeBzESX9f+zMmTOUKFFC5UsQBEEQBEEQBEEQPhfRA+L/WKVKlfLN4CwIgiAIgiAIgiAIX4JogPg/Vrx4cVxd/94jDAVBEARBEARBEP4TPnT2buFvE0MwBEEQBEEQBEEQBEH45EQDhCAIgiAIgiAIgiAIn5xogBAEQRAEQRAEQRAE4ZMTDRCCIAiCIAiCIAiCIHxyogFCEARBEARBEARBEIRPTjwFQxAEQRAEQRAEQfjv0hD35T8XUdKCIAiCIAiCIAiCIHxyogFCEARBEARBEARBEIRPTgzBEARBEARBEARBEP67NDS+dAT/GaIBQvjXik8r+aVDyEdf692XDiGfUomPvnQI+Tw38PzSIeSjT+KXDkGpd4FNvnQI+cQUt/3SIeRT4fauLx1CPqFl2nzpEPJxDT/2pUNQSkbRu/DTJP1Lh5DPe5nulw4hnwxZ0etMm65RNC9vE7WMvnQI+WQUwc7Qjk9OfOkQ8gmzbfylQ8jnfVrR3M8FoTBFr9YRBEEQBEEQBEEQBOH/jmiAEARBEARBEARBEP67NDWL7usDLV++HEdHR/T09PD39+fSpUtqrbdt2zY0NDRo2bLlB3/mhxANEIIgCIIgCIIgCILwL/fbb78xYsQIpkyZwtWrV6lQoQINGjTg9evXBa73+PFjRo0aRfXq1T95jKIBQhAEQRAEQRAEQRD+5RYuXEifPn3o2bMn3t7e/Pzzz+jr67N27VqV66Snp9OlSxemTZuGs7PzJ49RNEAIgiAIgiAIgiAIQhGUkpJCfHy8wislJSVfuvfv33PlyhXq1q0rX6apqUndunU5f/68yvynT59O6dKl6d279yeJPy/RACEIgiAIgiAIgiAIRdDs2bMxMjJSeM2ePTtfuujoaNLT07GwsFBYbmFhQVRUlNK8z549y5o1a1i9evUniV0Z8fwWQRAEQRAEQRAEQSiCxo0bx4gRIxSW6er+88cyv337lm+++YbVq1djbm7+j/NTl2iAEARBEARBEARBEP67NIruwABdXV21GhzMzc3R0tLi1atXCstfvXqFpaVlvvQPHjzg8ePHNGvWTL4sIyMDAG1tbSIiInBxcfmH0edXdEtaEARBEARBEARBEIRCFStWDD8/P44fPy5flpGRwfHjxwkMDMyX3tPTk5s3b3L9+nX5q3nz5tSqVYvr169jZ2f3SeIUPSAEQRAEQRAEQRAE4V9uxIgRdO/enUqVKlGlShUWL15MYmIiPXv2BKBbt27Y2Ngwe/Zs9PT0KFu2rML6xsbGAPmWf0yiAUIQBEEQBEEQBEH479LU+NIRfBQdOnTgzZs3TJ48maioKHx8fDh06JB8YsqnT5+iqfllB0GIBghBEARBEARBEARB+D8wePBgBg8erPS9U6dOFbjuunXrPn5AeYg5IARBEARBEARBEARB+OREA8RHUrNmTYYNG/alw+DUqVNoaGgglUo/+2evW7dOPm5IEARBEARBEAThX0FDs+i+/s+IIRhFgKOjI8OGDSsSDRj/D2QyGbu2rOLkkRCSEhNw9ypPzwGjsbS2V7lO+K1rHNiziUcPwpHGRjNs/DwqBdRQSLNry2ounDlKbPQrtLR1cHL1pF3X/rh6FD5Ji0wmY9umXzl6eD9JiQl4epWl76ARWNvYFrje7/v3ELxrG1JJLI5OrnzbfyhuHl4AvH4VSf9enZSuN2rsVKpWr1lg3jsPnWTTviPESuNwdbBlZK9OlHF1Upr24bOXrPothPBHT4l6E8Ow7u3p2KRuvnSvYyUs37Sb89dvkZLyHlvLUkwc2AMvF8cCY8lNJpPx26a1HDu8j6TEBDy8ytF30AisbAqeiff3/bvZm1VWDk4u9O7/HW4e3vL3JbExbFy7ghvXLvPuXRLWtna06fANAdVqqhXTpo0bOXToEImJiXh7ezNo8GBsbGwKXG/fvn3s2rkTiUSCk7MzAwYMwMPDQ/7++/fvWb16NX+cPk1qaiq+fn4MGjQIExOTQmPa9fsxtoT8nrn9HO0Z3rsr3m7OStM+fPqCX7btJuLhY6LexDC0Zyc6NG2gkGbD7v2cvnCFJy8i0S2mQzkPVwZ80x4HG6tCY8kmk8nYsmk9Rw4dJDExAS/vMgwY9F2h+/mBfSHs2bUdiSQWJycX+g4YjLuHp/z95UGLCL12ldjYGPT0iuPp7U2Pnn2wtVN9TGcLPvA723eHECuR4uLkyJB+vfF0d1OZ/vTZP/l101aiXr/B1tqKPj264l/JT/7+3EVBHDlxSmGdyr4+zJk2qdBYAEy/qoTzyN4Y+ZZFz7o0l9sM5NXe4wWv83UVvOePpYS3G8nPIrk/ewXPN+xRSOMwoDPOI3qja1mK+Bvh3B42g7i/bqoVU7aiuP0yY1rH0ayYPL3LqhlTMMFZMTk6udB3wBCFmHLnP33yOK5e+YtxE6cRUPUrtWIqavWBTCZj66Z1HD10QF5O/QcNK7ScDu4LZs+u37LOMS70GTAE96xzDMCEMcO5fTNUYZ0GjZoxYMjwQmPKjutjn/uyRYTdZvOGX7gXEYampiZOzq5MmvFjoY+qk8lkbN60gcOHfpfv5wMHDS10++3ft5fdu3Zk7efO9BswCI+sfert23g2b9rItatXePPmNUZGRgQEVqXrNz0wMDBQq5w2b1rPkTwxqXPs5cTkQr8BgxT282VBixWOPS9vb7r3/Ba7f+mxt+3UZdYfPU9MfALuthaM6dCAco7Kt9vxa+GsOXSOp29iSUvPwL60Kd3q+tPUv7xCDCv2n2b32eu8fZeMj7Mt4zs3xqG0aaGx5P0uOzf/wokje0lMfIuHV3l6DfweK2vV1y1ht66xf/cWHj6IQBobzYjxs6kcqHjdeenPUxz7fQ+PHkSQ8Dae2UvW4ejsrnZMe7as4tTRYJISE3DzLE/3AWMKvha+fZXf92zi8f1wpJJoho6bh19AzXzpXj57xG/rlxFx+yrp6enY2DkxZOxczErlf8yjICjz/9ekIvyrpaam/uM89u/eyJH92+k1YAzTflyDrq4ec6d8x/v3KSrXSUl5h72TG937fa8yjZWNPd37jWJ20BYmz12FeWkr5k4ZSnycpNCY9uzcyoF9u+g/aARzFq5AV684MyZ9X2BMZ/84wa+rf6J95x7MX7oaRycXpk/6Hqk08/PMzEuzZuMuhVfHLj3RK16cipWqFBjP0T//YsmGHXzbtinr507EzcGOYbOWEBsXrzR9csp7bCxKMahzK8yMDZWmiU9IpO+keWhra7Fo/FC2LprG0G7tKGmgX2j55Ba8cwsH9+2i76CR/LBwJbp6esyYNKrAsjr3x3HWr15Ou849mLf0FxydXJk5aRRx0pxtE7RwFi9fPGXM5B9YuHwd/lW/ZuGcqTx8cLfQmHbu2MHevXsZPGQIixYvRk9Pj0kTJ/L+/XuV65w+fZrVq1bRuUsXgoKCcHZyYtLEiQq9k1atXMmlixcZN348c+fNIzYmhpkzZxYaz7FzFwlat41e7Vuy9sdpuDrYMWLGfCQqtl/K+xSsLUoxoGs7zIyNlKa5fjuc1g1rs2r2JBZP+Z609HSGT5/Pu2TV5Z7X7p2/sX/vHgYM/o4fFy1DV0+PKZPGFlhOZ06fZM3qn+nY+RsWBf2Mo7MzUyaNle/nAC6ubgwd/j3LV65l2sw5IIPJE8eQnp5eYDwnz5zj51/W0a1Te35e/CMuTg6MmTwDiTROafrbYeHM/HERjerXYeWS+VQLqMLkWfN49OSpQrrKvhXZseEX+WvC9+r9GAPQMtAn/kYEt4ZOUyt9cUdbKu9dScypi5yt1IJHQespt3Im5vVyLtat2jXC68dx3Ju5nLNVWvH2Rjj+B9ZQrNSHXUQXte2XGdM2Duzdw4DBw/hx0TL09PSYqkZMa1f/TIfO3VgY9DNOzi5MnTRGIaZse4N3oaHxYROPFbX6AGDPzm3s37ub/oOHM2/RcvT09Jg2aUyBMZ09fZK1q1fQsXM3FgatxNHZhWlKyqlewyb8ummn/NW9d1+1YsqM6+Of+yCz8WHG5NH4VKzE3EUrmLf4Zxo1a4WmGpPI7dq5nX17gxk0eCgLFi1FT0+PyZPGFVhWf5w+xS+rV9Kpc1eWBP2Ek7MzkyeNl8cUExNDbEwMvb7tw/IVqxg2fBRXLl9myeIFapXTrp2/sX9vMAMHf8f8RUFqxXQmV0yLg1ZkxTROoZxcXd34bvgoflq5hmkzZyOTyZg8cey/8tg7fPk2C3YdpV+T6mwd/y3uthYMXLqV2PhEpekNDfT4tlE1Nnzfkx0T+9AisAJTNuzjzzsP5GnWHTnPlpN/MaFzIzaO7klx3WIMXLqFlNQ0teMC2LdrE4f276D3wO+ZMf8XdPX0mDN5eMHXncnJ2Du50qv/yALSvMPDuwKdug/8oHgADu7ewNEDv9FjwFgm/7gWXb3izJ86tNCY7Bzd+KaAa+FXkc+ZOa4P1rYOjJv1MzOXbKF5+97o6BT74BiF/y7RAPERZWRkMHr0aExNTbG0tGTq1KlAZivk1KlTsbe3R1dXF2tra4YOHQpkDt148uQJw4cPR0NDQ14ZP3nyhGbNmmFiYoKBgQFlypTh4MGDasdy5coVKlWqhL6+PlWrViUiIkLh/ZCQEHx9fdHT08PZ2Zlp06aRlpZT4S5cuJBy5cphYGCAnZ0dAwcOJCEhQSGPdevWYW9vj76+Pq1atSImJiZfHIV9joaGBitWrKB58+YYGBgwa9Ystb+jMjKZjEN7t9GifU/8Ampg7+RG/+FTkcZGc+XCaZXrVfCrSruu/akcWFNlmqo1GlDWpwqlLW2wtXemS+/veJeUyNPH9wuNaX/ITtp2+IYqgV/h6OTC0JHjiI2N5tL5syrX27dnB/UaNqFOvUbY2TvSb/AIdPX0OHEkcz/Q0tLCxNRM4XXx/BmqfVWL4sUL/tG/df9RWtT5iqa1quFka82YPl3QK1aM/SfPKU3v7erIkG/aUq9aFXR0dJSm2RhyGAszEyYN7EEZVyesS5vjX6EMtpalC4wlN5lMxoGQHbTp8A1VAqvj6OTCkJETkMTGFFJW26nbsCm16zXGzt6RvoNHZpXVAXmau2G3adSsDW4e3lhYWdO2Y3f0DUrw8H7BDRAymYzg4GA6duxIYGAgTk5OjBw1ipiYGM7/+afK9fbs2UPDRo2oX78+9g4ODB4yBF1dXY4cOQJAYmIiR44coU+fPvj4+ODm5sbwESMIu3OH8LCwAmP6bd9hmtWtQZPa1XGys+H7ft3R1S3G/uN/KE3v5erM4O4dqftVADo6yju+LZw0iia1q+Nsb4Oboz0TBn/Lq+gYIh48LjCW3OW0N3g37Tt2ISCwGk5OzgwfOYbYmBgunFe+XwGE7NlF/YaNqVu/Ifb2DgwcPAxdXV2OHTkkT9OwUVPKliuPhYUlLq5udOnWk+g3b3j9+lWBMe0M3kfjBnVpWLc2jvZ2DBvYD11dXQ4dVd7jYPfeA1T2rUiH1i1xsLOlZ9dOuLk4Ebz/d4V0OjramJqYyF8lS5RQq4wA3hz+g7tTFvMq5Jha6R36duTdo+eEjZ5LQvhDnvy0mahdh3H6roc8jdOwnjxbs53n63eTEPaAmwOnkJ6UjF2PNmrHVRS3n0wmY1/wbtp17Ip/YDUcnVwYNnIMsTHRXCigPgjZszNXTI4MUBITwMMH9wnZvYMhw1RfbCuLqajVB5nltIv2ucrpu5FjiY2J5mKB5bSD+g0bU6d+5jlmwODh6OrqcvyI4v6uq6uLiamp/KWvX/gd/ey4PsW5D2Dt6mU0bt6a1u27YO/ghI2tPdWq1yr0R5BMJiMkeA8dOnYmILAqTk7OjBg5mtiYGM4XsJ8H79lFg4aNqFe/Afb2Dgwa/B26urocPXIYAEdHJ8ZPnIy/fyBWVtZU8KlIt+49uXTxYqE/9jOPvT1Zx15VtY+97Jhyjj3FmAAaNmoiP/ZcXd3o+i8+9jYev0jrahVpWdUHF6tSTOzUGL1iOgSfv640fWV3R2r7eOJsZY5dKVO61K6Cm40F1+4/k3/HzScu0afRV9Sq4IG7rQUzejTnTdxbTl6PUJqnMjKZjN/3bqdV+x5UCvgaBydXBg6fjCQ2mssXlJ+TAXwqBdLhm375ej3kVr12I9p06kU5n8pqx5Md0+F922jWrhe+/jWwd3Sj77DMa+GrhVwLt+06gEqBtVSm2bVpBRX8qtGhx1AcnD2wsLLF1/9rDI0/rMFb+G8TDRAf0fr16zEwMODixYvMmzeP6dOnc/ToUXbt2sWiRYtYuXIl9+7dIzg4mHLlygGwe/dubG1tmT59OpGRkURGRgIwaNAgUlJS+OOPP7h58yZz586lxAdc5E6YMIEFCxZw+fJltLW16dWrl/y9M2fO0K1bN7777jvu3LnDypUrWbduncKPf01NTZYuXcrt27dZv349J06cYPTo0fL3L168SO/evRk8eDDXr1+nVq1a+e7UqPM5AFOnTqVVq1bcvHlTIc6/482rl8RJYihbIacHgL5BCVzcy3Av4sO6IxckLTWVk4eD0TcogYOT6u7cAK+iIpFKYqngk9ON28CgBG4e3kSE31G6TmpqKg/uR1A+1zqampqU9/FTuc6DexE8enifOvUbFxhPaloaEQ+fUrlcTndWTU1NKpfz4ubdhwWuW5Azl0PxcnZg/MKfafTtSLqNnkHwsTMflMfrrLIq71NJviyzrLy4G35L6Tqpqak8vH9XYR1NTU3K+fgREX5bvszdqwzn/jjB27fxZGRkcPb0cVLfv6dMOZ8CY4qKikIikeBTsWKumAzw8PAgLDxcZUz3793Dxycnb01NTXx8fOQ/Ju7du0daWppCvnZ2dpQqXVplvpl5pxHx4DGVy+cML9HU1KRS+TLcuvtA5XofKjHpHQCGJdX7sfEqKhKJJJYKPr7yZQYGJXD38CIiTPV+fv/+XXxyraOpqUkFH1/CVeznycnvOH70EBaWlpibl1IZT2pqKnfvP8C3Qk53W01NTXx9ynMnQnmj053wu/j5lFdYVqmiD3fCFS9GQ2/dpk3XnnTvP4TFP60kLv6tyjj+KeMAH6JPnFdY9uboWUwCfADQ0NHByLcM0cdz/fiVyYg+8SfGARVRV1Hbfv8kpgf37yqskx1T7rozJTmZBfNm0W/gUExM1b9wLmr1AeSUU/k85xh1yinvOaaCknPMHyeP803Hlgwd0IuNv64mJTm5wHhyx/Upzn1SqYR7EWEYGZkwbuQgenZpxcQx3xF2+4YaMUUhkcQq7LOZ289TZUNP5n5+Dx+fnG2Tuf0qEh6uunEoMTERfX19tLS01IxJcZ9y9/AkvJBjL+9+7pNnP88tOfkdx44e/lcee6lp6YQ9jcTfM2eYqKamBv6ejtx4+KLQ9WUyGRfDH/H4VQy+bplDEF5ES4mOT1DIs2RxPco52RD66LlacQG8fvUSqSSGsrmuQTKvO725p+K65VPLvhYuk+da2Nm9DPf/wbVwRkYGoZfPYWltz49ThjC4WwOmjerJlQunPkLUwn+JmAPiIypfvjxTpkwBwM3NjWXLlnH8+HFKly6NpaUldevWRUdHB3t7e6pUyawUTE1N0dLSomTJklha5oydevr0KW3atJE3VDg7Kx/brcqsWbOoUSOzVXXs2LE0adKE5OTkzG6Z06YxduxYunfvLs97xowZjB49Wh5/7vkoHB0dmTlzJv379+enn34CYMmSJTRs2FDeKOHu7s6ff/7JoUM5rdzqfA5A586d6dmzZ4HfJyUlhZQUxW5j79+nUKyY4lhPqSSzF0bellhDY1PiJLEFfoY6rv11lmU/TuR9SjLGJuaMmR5ESUPjAteRZn2ukYliTMbGJkhUxPQ2Po6MjAyMjfOv8+LZU6XrHDtyEFs7Bzy9C56TQhqfQHpGBqZ5hlKYGJfk8cvIAtctyMvXb9h99DSdmtSje6vGhD14zKJft6GjrUWTmlXVykOStf2M84x5NjI2lZdjXplllY6RseI6xsamCmU1cuw0Fs6dSs+OTdHS0kJXV4/vJ87Eyrrg8awSSWbX0bzjsI1NTOTv5RUfn9nIoWydZ8+fy/PV1tbO17BoYmyMJFb1vip9+zZr+ykOpTA1MuTpi7+//XLLyMhgya9bKO/phrN9weWTLbss8m47Y2Njlft5fPZ+nm8dE148e6aw7OD+ENatXU1ycjI2tnZMnzVPZW8cgLj4t1nbwFhhuYmxEc+eK79gjZVKMclTribGxsTm6iZf2a8i1asGYGlRmpeRUazZuIVxU2cS9OMPhf7Q+Dt0LcxJeRWtsCzlVTQ6RiXR1NNFx8QITW1tUl7H5EkTg4GH+ueNorb9Co6poGNPdUzPc8W0ZvVPeHqVwT+wWoExqIqpqNQHkHOOyV9vqnGOUbLO81z15tc161C6tAUmpmY8efyQDWtX8eLFM8ZOnF5gTLnj+tjnvldRLwH4bcs6uvcegJOzK6eOH2bK+JEs/unXAucokMjLyjhf/tJCtl9h+1RucXFxbNu6mYaNCr4hoBjTh+/n+fYpJTEd2L9X4dibMWvuv+7YkyQkkZ4hw8xQsUHczLAEj1/l732b7e27ZOqPW0JqajqamhqM79SIQK/MejE6PiErD8U8TUsaEKNiWIcy2deWRnn22YKuWz61uKxrqbwxZV4Lqy6vwsTHxZKcnMT+Xetp06U/7bsP4ebV8wTNGcPYmSvwLOtbeCaCgGiA+KjKl1e8c2ZlZcXr168ZNGgQixcvxtnZmYYNG9K4cWOaNWuGtrbq4h86dCgDBgzgyJEj1K1blzZt2uTLX91YrKwyJ5F7/fo19vb2hIaGcu7cOYWeCOnp6SQnJ5OUlIS+vj7Hjh1j9uzZhIeHEx8fT1pamsL7YWFhtGrVSuEzAwMDFRog1PkcgEqVKlGY2bNnM22a4pjpbweNoUw5H9b+NEe+bNTkheoUz9/mVc6PWYs3khAv5eSREJbNHc/U+WsVKvnTJ4+yclnOuM8JU+coy+qjSklJ4czpY7Tr2O2Tf5YqGRkyvFwcGNA5c7/wcLLnwdOX7Dn6h8oGiD9OHmFVrrIaN3XuJ4tv28Y1JCYkMHnWIgwNjbh04QwL50xlxrwgHBxd5OlOnjhBUFCQ/O+8+91/wYLVG3n49DkrZk1QmebUyeP8FLRI/vfkaf9s+FRhatSqg09FP2JjYwnevYN5s2cwd/4SihX7vONOa3+dM/eCs6MDzk4OfNNnEKG3biv0tijqiuL2O3XyGCtyxTRp2g+fJJaLF/7kRuh1FgWtLDRtUawPTp88xoqgnHPdxGmzP9lnNWjUVP5/RydnTExMmTx+FJGRL7CyUpz873Od+2QZMgDqN2pGnXqNAHB2ceNm6FVOHD1I1x45c1ScPHmc5UFL5H9PmabenBr/RFJSItOmTMTe3p7OXb7J9/6pk8dZHrRY/vfkTxxTzVp1qFjRl9jYWPbs3sHc2TOZN39xkT/2PgYDXV1+G9+HpJT3XIp4zPydR7ExN6ayu+PfzvPsqcP8snye/O/Rk+d/hEj/mT9PHWLdipx6YMSkRQWk/vuyjz1f/69p2KIzAA7O7twLv8GJQ7v//Q0QHzgfkPD3iQaIjyhvi7KGhgYZGRnY2dkRERHBsWPHOHr0KAMHDuTHH3/k9OnTKluhv/32Wxo0aMCBAwc4cuQIs2fPZsGCBQwZMuSDY8meVyIjIwOAhIQEpk2bRuvWrfOtp6enx+PHj2natCkDBgxg1qxZmJqacvbsWXr37s379+/lDQeFKexzsqkzQ/S4ceMYMWKEwrKbT96RnpaGi3sZ+bK0tMxJLOOlsZiYmsuXx0tjsXcueKiEOvT0imNpbQfWdrh6lmNkvzacPrqX5u16yNNU8a+mMIt49sSacZJYTE3N5MulUglOzq5KP6ekoRGamppIpYqt51KpBGOT/F0Wz587zfuUFGrWaZDvvbyMDUugpalJrFRxwkKJ9K3KCQrVYW5ihKOttcIyR1tLTl28qnKdyv5fKTypIi2rrKQSicL2i5PG4lhgWWkpTDgJIJXGyssqKvIFv+/fzaKf1mPnkNnd0tHZlbBbNzi0fw/9Bo+Sr+cfEICHZ86M3dnbTyKRYJqru6hUIsHZJafhIjdDQ0M0NTXz3SmSSiSYZt0dMjExIS0tjYSEBIW7nhKptMBuqcYlS2ZtP8WJFGPj4vP1ivg7FqzeyJ9XQlk+YxylzVTHUcU/UGFm89zbTnE/l+LsrKqcsvbzvOUklWBsqngXzcCgBAYGJbC2scXD04vO7Vtx/s+z1KhZW2neRoYls7aBVGG5RBqHaZ67n9lMjY3zTVApkUoxLeDxwtaWlhgZGvLiZdQnaYBIeRWNroW5wjJdC3NS496SkZzC+2gJGWlp6JY2y5PGjJQoxZ4TuRXF7VfFvyoeSurO/DFJcPobMWUfVzdDrxEV+ZLO7ZorpJn7wzS8y5Rj1tycH/dFsT6o4l81zznmfU5+ucopTp1zTJ6Y4nKVkzLunpmfG/XyZb4GiM917jPJysvOzkEhjY2dA2/evFZY5u8fKH9SRe6YpBLpB+xThoXuU9mSkpKYPGkCxfX1mTBpqtIbTXmPvYL288KOvXz7lFSCSb5jzwADAwP5sdepfet/xbGXm0kJfbQ0NfL1TIiJT8DcUPXwZE1NDeyznmjhaWfJo8ho1h76k8rujvL1YuITKWVUUr5O7NtE3G0tVObpV+UrXHNdd2Yff3F5rjszr1v++XWnOipWqY6Lh/KYjPNeCzup9xQNZUoaGqOlpYW1neIT06ztHLl7J1TFWoKQn5gD4jMpXrw4zZo1Y+nSpZw6dYrz589z82bmOKxixYopnaTIzs6O/v37s3v3bkaOHMnq1as/Siy+vr5ERETg6uqa76WpqcmVK1fIyMhgwYIFBAQE4O7uzsuXLxXy8PLy4uLFiwrLLly48EGf8yF0dXUxNDRUeBUrpktxfQMsre3kLxs7J4xMzLgd+pd83aSkBB7cvY2bR7kPLKnCyWSyfE/uKK6vj5W1rfxlZ++IsYkpN0JzfognJSVyL+IOHp7eebMEMhuQXFw9uHE9Z52MjAxuXL+idJ3jRw5Qyb8qRkbGhcaso62Nh7M9f93KGVeckZHBX7fCKOf+YUN9civv4crTl1EKy569fIVlATPx5y0r26yyuhl6RZ4ms6zCcPdUPrRER0cHZ1d3bl7PWScjI4Ob16/i4Zl5Qk5JyRyznHfGbU0tTXmLfjZ9fX2sra3lL3t7e0xMTAi9fj0npsREIiIi8PLM/2ix7Jhc3dwU1snIyOD69et4emVe5Lm5uaGtrc31XGmeP3/Om9evVeabmbc2Hi6OXL6ZM6Y2IyODKzfuUNZd+YWhOmQyGQtWb+SPS1dYOnU01hYFjxHOLCcb+cvO3gETE1NCQ6/J0yQlJXI3IgwPL9X7uaurO6Gheffza3iqODayokWGTP6jWVXe7q4uXLuRM941IyODa6E38PZQfgHm7enO1VDFceRXrt/A29NDaXqAN9ExxL99i1mei/6PRXrhOma1AxSWmdepiuTCdQBkqanEXb2Nee3AnAQaGpjVCkR64RqqFMXtp6+vj5W1jfyVHVPeurOwmFxc3bmR63tkx5Rdd7Zp14kly1ezeNkq+QugV58BDB2uOCleUawPiucrJ8d/UE55t91VleclgEcPMueZUdZI8bnOfaUtLDE1M+fFC8WhBpEvnlGqtOIPx7z7uX3WPnU9z34eEREu3xbKYnJ1dSM09LpCTKHXr+PpmbNOUlIikyaOQ1tbm0mTp6nsnaUqpvzHXjiehRx7effz0Fz7uXKZx17e65aieOwp5K2thZe9FZciHuXKW8aliMeUdy748am5ZchkvM+aCN3G3BhzwxJcingsfz/hXQo3H72ggpPqYTyZ15228petvRPGJmbcCr0sT5OUlMiDu3dwU3Hd8rEV1zfAwspO/rKxc8bIxIw7N3Kuhd8lJfDw7m1c/8G1sLaODk6u3kS9UBwKHPXiKealxSM4BfWJHhCfwbp160hPT8ff3x99fX02bdpE8eLFcXDIbL13dHTkjz/+oGPHjujq6mJubs6wYcNo1KgR7u7uSCQSTp48iZeKk+OHmjx5Mk2bNsXe3p62bduiqalJaGgot27dYubMmbi6upKamkpQUBDNmjXj3Llz/Pzzzwp5DB06lGrVqjF//nxatGjB4cOHFYZfqPM5n4KGhgYNm3ckePuvWFjbUdrCmp2bV2Jsao5fQM5Mwz9MHESlgJrUb9oOgOR3SbyKzJl06M2rlzx5eBeDkoaYl7IkOfkdIdt/xa9KdYxNzXkbL+XogZ1IYt7g/1WdQmNq2qItO7dtxMraFgtLK7ZuXIOpqTlVAnO6c08ZPwL/wK9o3Cyzx0izVu0IWjgbVzcP3Ny92Beyk5TkZGpndTnNFvnyOXdu3fig7q6dmtZjxvJf8XJ2wNvVid8OHiM55T1NamaOyZy2bC2lTI0Z2DkzltS0NB49z5xfIC0tjTexUu4+fkZxPV3ssp5y0bFJXfpMmsO63QepU7USd+4/Ivj4Gcb2zd8FtaCyatKiHbu2bcDK2pbSllZs27gGE1MzhbKaOn4Y/oHVadSsTVZZtWfZwtm4uHng6u7FgZAdpCS/o1a9zPG3NrYOWFrbsHLZfLr1HkhJQyMunT/DjWuXGTel4HLT0NCgZcuWbNu2DWsbGywsLNi4cSNmZmYEVs0ZWjJu7FiqVq1Ks+aZd3ZatWrFwgULcHNzw93Dg5DgYFJSUqhXrx6QeVeqfv36rF69mpIlS6Kvr8/PK1bg5eWl8kI4W4dmDZgVtBpPFye83ZzZvv8IySkpNKldHYAZS1dhbmrCgK6Z+3dqahqPsuY9SE1L502MhLuPnqCvp4etVeYF+4LVGzl65jxzxn6HfnE9YrJ6DpTQ10dXt/BhDhoaGjRv2Zrt2zZjbW2DhYUlmzeuw9TMjIBcY30njvuegKrVaNqsJQAtWrVh8cJ5uLp54O7uwd6Q3SSnJFOnXkMAoiJfcuaPU1T0rYSRkRHR0dHs2rEN3WLF8Ktc8ONm27ZsxtxFQbi7uuDp7saukP0kJ6fQoG7mnb85C5dibmbKt927AtC6eROGj5vM9j17Cajky8kz57h7/wEjBvcH4N27d2zYup3qVQMxNTHmZVQUq37diLWVJZV8fQotI8h8DKeBa85z2PWdbDGs4Mn72DiSn0XiMXMEejYWhPYcA8CTVdtwGNgFz9nf82zdLsxrBWDVrhF/Ne8nz+PR4l+psHYu0iu3iPvrBo5Du6NtUJxn63erFRMUze2noaFBs6yYrKxtsbCwZMvGXzE1MycgV30wadwoAqp+RRN5TG1ZsnAurm7uuLl7si9kF8kpydStl9lDLPtpDnmVKlUaC0urQmMqavVBZjm1Yce2TVhb21DawkpeTv4K5TQyq5xaZZVTO5YsnJN1jskpp+xtFxn5gj9OnsCvsj8lDQ158ugBa1b9RJmy5XF0Kryx81Od+zQ0NGjRugO/bV6Ho5MLTs6unDx+mBfPn/L9+IKHyGhoaNCiZSt+27YFm6z9fFPWfh6Yaz8fP240gVWr0axZCwBatmrDooU/Zm4/d09Csvbz7H0qKSmRSRPGkZKSwqjvx/AuKYl3SUkAGBoZFTg/TOaxlxlT5rFnJY8p97E3Ydz3BOY69jJjmoermzvu7h6EhOxRiCkqMjLr2PPD0MiYmOg37Mw69ir9C4+9b+r4M2n9XrztrSjraMPmExd5l5JKi8AKAExcF0Jp45IMbZlZv685dA5vByvszE14n5bO2dv3OXDxJuM75exHXWpXYfXBs9iXMsXG3Jjl+05RyqgktXxUNzorK6tGzdsT/Nt6LLOuO3dsWoWJqTmVAr6Wp5s5YQiVA2vQoGlbIPO6M0rhujOSxw/vUqKEofzHfMLbeKLfRCGJzezNFpn1w9/YxAxjE8Veb3ljatCsI3u3r8XCyo5SFtbs3vIzxqbm+Oa6Fp47aSC+ATWp16S9PCZl18IlShpiViozpkatuvLT/Al4lKmIVzk/blw9z/W/zjJu1gq1y6zI+sCbo8LfJxogPgNjY2PmzJnDiBEjSE9Pp1y5cuzbtw8zs8zKY/r06fTr1w8XFxdSUlKQyWSkp6czaNAgnj9/jqGhIQ0bNmTRoo8zpqtBgwbs37+f6dOnM3du5mREnp6efPvttwBUqFCBhQsXMnfuXMaNG8fXX3/N7Nmz6dYtZ36BgIAAVq9ezZQpU5g8eTJ169Zl4sSJzJgxQ+3P+VSatv6GlOR3rF0+m6TEBNy9KzB66hKFCStfR73gbbxU/vfD+2H8MCHnOcub1ywGoHrtJvQbNhlNTU0inz9hyYmDvI2XUsLQCGdXLybOWYmtfeG9Blq17URKcjI/B80nMTEBL+9yTJoxTyGmqMgXxMfndP/+6uvaxMdJ2brpV6SSWJycXZk0fV6+IRjHj/6OmXkpfHzVf0xTvaqVkca/ZfX2vcRI43FztGXR+KGYZU1MGRUdq9Bb4E2slG6jc7bt5n1H2LzvCBW93VkxNXP4grerI3NHDWTFlt2s3bUfq9LmDOvegYbV/dWOC6Bl286kJCezMqusPL3LMXHGfIWyehX5UqGsqn1dh/g4Kds2rUUqyRyuMWH6fHlZaWtrM2HqPDatW8mc6eNIfvcOS2sbBo8Yj2/lwHwx5NW2XTuSk5MJWrqUhIQEypQpw/QZMxTucEVGRhIXnzOspUaNGsTHxbFx0yYksbE4u7gwfcYMhUnD+vbrh4amJrNmziQ1NRU/Pz8GDhpUaDx1q/kjjXvLL9v2ECuNw83JngUTR8qHYLyKjlHYftESCT1H5Uz8unXvIbbuPUTFMh4smz4OgD2HTwAweLJig8z4Qb3lDRuFad22A8nJySwPWkRiQgLeZcoydfochXKKinxJfFzOtqteoxZx8XFs2bgOiSSzy/HU6bPl5aRTrBh3bt9ib8huEhMSMDY2oUzZcsxdsBRj44J7HdSqXo24uDjWbd6GRCLFxdmJOdMmyodgvH4TrVBOZbw8mTBqGGs3bWXths3YWFsxfcJonBwyGww0NTV5+PgJR06cIiExCTNTEypVrECPLp0oVsikbtmM/MoSeHyj/G/v+eMBeLZhNzd6j0PXqhTF7XIuxN89fs5fzfvhvWAcjkO6kfw8ipv9JhJ9NOdReJE7fqdYKVPcpwxF17IU8aFhXGr6Le9ff9hkY0Vt+2XG1JHk5GR+ClpIYkICXmXKMWX67EJjis8Vk5OzC1Omz1E6fO3vKGr1AUArJeU0uZBt91WNWsTFS9m68ddc5TQ3V72pw43rV9gfsovk5HeYlypNYLWvad+pq9pl9anOfc1atiP1/Xt+Xb2chLdvcXRyYcrM+VhaFX43vE3b9pnbL2ixfD+fPv2HPGUVqVBWX9eoSVx8HJs2bsjaz52ZPn2WfPvdv3+fiIjMXoV9evdQ+Lw1v27AwqLgu8Ntso69ZblimpZvP48kPi5nn6peoyZx8VI2b1wvP/amTf8h17Gnw+3bN9kbspuEXMfevAVL/pXHXoNKZZAkJLFi/2mi4xPxsLXgpyGdMMsaShEZG6dQn79Lec8PW3/ntfQtujraOFqaM6tnCxpUyhmq0KN+IO/ev2fGlgO8TUqmoosdPw3phK6Kx1Wr0qxNV1KSk/ll2VySEhPw8C7P2GkLFa9b8l13hjNj/GD53xvXLAXg69qNGTB8IgBXLp7h5yU58/MsnTcZgDadetG2c8HX0o1bdyMlOZl1P/1AUmICbl4VGDUl/7VwQq6YHt0PY87EAfK/t65dDMBXtZvQ57vMa4hKgbXoMWAs+3euZ9PqBVjZ2DNk7BzcvX3UKClByKQhk8lkhScThKLnrwjplw4hH32td186hHysE5U/cvBLem6geojBl6Kvqf6s15+TUVLBz2v/EmKKq/dkjM/JID2u8ESfWWiZNl86hHxcw4996RCUklH0Jv/S0Xj/pUPI571Mt/BEn1mGrOjdNSxWBLcdFM39PKMIjsZ2eHLyS4eQT5ht4U80+dzeZxTN+8gBnv98PqovIXl/0e3Fodd0QOGJ/kWK5p4rCIIgCIIgCIIgCJ+DeArGZ1P0mj2FAvXv358SJUooffXv3/9LhycIgiAIgiAIgiAISokeEP8y06dPZ9SoUUrfMzQ0/MzRCIIgCIIgCIIgCIJ6RAPEv0zp0qUpXbr0lw5DEARBEARBEARBED6IGIIhCIIgCIIgCIIgCMInJxogBEEQBEEQBEEQBEH45MQQDEEQBEEQBEEQBOG/S0Pcl/9cREkLgiAIgiAIgiAIgvDJiQYIQRAEQRAEQRAEQRA+OTEEQxAEQRAEQRAEQfjv0hT35T8XUdKCIAiCIAiCIAiCIHxyogFCEARBEARBEARBEIRPTgzBEARBEARBEARBEP67NDS+dAT/GaIBQvjXMtaO+9Ih5JNRBDsVJeiX+tIh5KOjkfqlQ/jXKPHq3pcOIZ8ke+MvHUI+2hlFb59yDT/2pUPI575n3S8dglLu4Ue+dAj/CtqkfekQ8iuC1+yaGulfOgSlZLKiV1gayL50CPlIbCp86RDyMdSK/9Ih5JOuVVR/xhl96QCEIq7o/VoSBEEQBEEQBEEQBOH/jmiAEARBEARBEARBEAThkxMNEIIgCIIgCIIgCIIgfHKiAUIQBEEQBEEQBEEQhE+uqM5eIgiCIAiCIAiCIAifnoa4L/+5iJIWBEEQBEEQBEEQBOGTEw0QgiAIgiAIgiAIgiB8cmIIhiAIgiAIgiAIgvDfpaHxpSP4zxA9IARBEARBEARBEARB+OREA4QgCIIgCIIgCIIgCJ+cGIIhCIIgCIIgCIIg/Hdpivvyn4soaUEQBEEQBEEQBEEQPjnRAPEFTJ06FR8fn8/6madOnUJDQwOpVPpR8+3RowctW7b8qHkKgiAIgiAIgiAI/3/EEIx/salTpxIcHMz169cLTVu1alUiIyMxMjL6qDEsWbIEmUz2UfP8p2QyGZs3beDwod9JTEzAy7sMAwcNxcbGpsD19u/by+5dO5BIYnFycqbfgEF4eHgC8PZtPJs3beTa1Su8efMaIyMjAgKr0vWbHhgYGKgV05ZN6zly6KA8pgGDvsPaxrbA9Q7sC2HPru1ZMbnQd8Bg3LNiAlgetIjQa1eJjY1BT684nt7e9OjZB1s7+0JjCtl/kO27g4mVSHFxcmRwv2/x9HBXmf702XOs27SVqFevsbG2ok+PbvhX9pO/P2/RUo4cP6mwTiXfisyZPrnQWHLLLKt1HM0qK0/vsmqWVTDBWWXl6ORC3wFDFMoqd/7TJ4/j6pW/GDdxGgFVv1Irpk0bN3Lo0CESExPx9vZm0ODBhe5T+/btY9fOnUgkEpycnRkwYAAeHh7y99+/f8/q1av54/RpUlNT8fXzY9CgQZiYmBQa07bTl1l/9ALR8Qm421owtn19yjkqj+fYtXDWHD7HszcSUtMzcChtwjd1AmjmX04hzY4zVwl7FkVc4jt+G9cbTzvLQuPILWT/QXbs3iPfpwb161PoPrV+0xb5PvVtj274V66kNO3iZSs4cOgwA/r0onWL5mrHtOfAYbYF7yNWEoeLoz3f9e2Jl7uryvQnz11g7ebtRL1+g421Jf27dSagUkX5+0nvklm1YQtnL14m7u1brEqXpk3ThrRoVE/tmKBo1QmmX1XCeWRvjHzLomddmsttBvJq7/EC4zD9ugre88dSwtuN5GeR3J+9gucb9iikcRjQGecRvdG1LEX8jXBuD5tB3F831SidHEW1Pi9q9UFRLKeiGldh2yGvM2fOsHHDBl69eoW1jQ29evakcpUqCt/x7+wPuclkMjZt2phVTol4eXszaNAQtcpp166s7+LkTP8BAxW+y++/H+T0qZPcv/+Ad++S+G37TkqUKKF2TEVt2+05cIjf9uzNOsc4MLRvL7zc3VSmP3X2PGs3byPq9RtsrS3p270rAZV85e/Xat5O6Xr9enSlY+sWhcaTrahuv09xjsmd/7TJ47l65S/GT5xGQNVqasUlCCB6QPwnpKamUqxYMSwtLdH4yI+YMTIywtjY+KPm+U/t2rmdfXuDGTR4KAsWLUVPT4/Jk8bx/v17lev8cfoUv6xeSafOXVkS9BNOzs5MnjQeqVQCQExMDLExMfT6tg/LV6xi2PBRXLl8mSWLF6gV0+6dv7F/7x4GDP6OHxctQ1dPjymTxhYY05nTJ1mz+mc6dv6GRUE/4+jszJRJY+UxAbi4ujF0+PcsX7mWaTPngAwmTxxDenp6gfGc/OMsP//yK9906sDPSxbg7OTI2MnTkajoIXM7LJxZ8xbSsF4dfl66gGoB/kyZNYdHj58opKvsV5HtG9fKXxNGj1CrfHLbvXMbB/buYcDgYfy4aBl6enpMVaOs1q7+mQ6du7Ew6GecnF2YOmmMQlll2xu864OPg507drB3714GDxnCosWL0dPTY9LEiQXGdPr0aVavWkXnLl0ICgrC2cmJSRMnKvRCWrVyJZcuXmTc+PHMnTeP2JgYZs6cWWg8hy7fYf6uY/RrUp1t43rjYVOaAUHbiHmbqDS9kUFxvm1YjQ2jerBzQh9aBFRgysZ9nLvzQJ7m3ftUKrraMaxlLfULJpdTf5xl5S9r6dqpIyuWLMTZyZFxk6cVuE/9MG8BDevVZcXShVQL8Geqkn0K4OyfFwiLiMDM1PSDYjpx5k+Wr91I9w5tWb1wNi5ODoyaOhuJNE5p+lthEcyYv5TGdWuxetEcqvtXYsLs+Tx88kyeZvnaDVy6GsqE4YPYsGwBbZs3YsmqXzl38fIHxVaU6gQtA33ib0Rwa+g0tWIv7mhL5b0riTl1kbOVWvAoaD3lVs7EvF5OY55Vu0Z4/TiOezOXc7ZKK97eCMf/wBqKlfqwbVgU6/OiVh8U1XIqinGpsx1yu3PnDnPnzKF+gwYELVtGYGAgM2bM4PHjx/I0f2d/yGvnzh3s2xvCoMFDWbgoK49JEwopp9OsXr2azp27sjRoGU7OzkyaNEHhu6SkpODrV4n2HTqoHUu2orbtTpw5x4o16+nesR2rFs3FxdGB0VNmFVKfL6ZxvdqsXjyPr/yrMOmHeTx68jTnO65fpfAaPXQgGhoafF014IPKqihuv091jsn2d66lBCGbaID4h3bu3Em5cuUoXrw4ZmZm1K1bl8TERE6dOkWVKlUwMDDA2NiYatWq8eRJ/gvrwqjKZ926dUybNo3Q0FA0NDTQ0NBg3bp1AGhoaLBixQqaN2+OgYEBs2bNyjcEY926dRgbGxMcHIybmxt6eno0aNCAZ89yLrSzh4qsXLkSOzs79PX1ad++PXFxOZV93iEYNWvWZOjQoYwePRpTU1MsLS2ZOnWqwncKDw/nq6++Qk9PD29vb44dO4aGhgbBwcEfXD55yWQyQoL30KFjZwICq+Lk5MyIkaOJjYnh/PlzKtcL3rOLBg0bUa9+A+ztHRg0+Dt0dXU5euQwAI6OToyfOBl//0CsrKyp4FORbt17cunixUJ/7MtkMvYG76Z9xy4EBFbDycmZ4SPHEBsTw4UCYgrZs4v6DRtTt35D7O0dGDh4GLq6uhw7ckiepmGjppQtVx4LC0tcXN3o0q0n0W/e8Pr1qwJj2hW8l8YN6tGwXh0c7O0YNqg/urq6HDqq/K7n7r37qexXkQ5tWuFgZ0fPbzrj6uJMyP6DCul0dHQwNTGRv0qq2VKfTSaTsS94N+06dsU/sBqOTi4MGzmG2JhoLpw/q3K9kD07c5WVIwOUlBXAwwf3Cdm9gyHDvv+gmIKDg+nYsSOBgYE4OTkxctQoYmJiOP/nnyrX27NnDw0bNaJ+/frYOzgweMgQdHV1OXLkCACJiYkcOXKEPn364OPjg5ubG8NHjCDszh3Cw8IKjGnjiYu0ruZDy8AKuFiVYmKnxugV0yb4z1Cl6Su7O1DHxxNnK3PsSpnQpXYV3GxKc+1BzvHezL8c/RtXx9/TSe2yyW1XcAiNGtSX71PfDRqArq4uh1XsU3v27qOyny/ts/apHt90UbpPRUfHsHzlasaNGoG2ttYHxbQ95ABN69emcd2aONrbMnLAt+jpFuPgsVNK0+/c9ztVfCvQqXUzHO1s6N2lA+7OTuw5cFie5nb4XRrU/pqK5cpgZVGa5g3q4uLkQNi9B0rzVKao1QlvDv/B3SmLeRVyTK34Hfp25N2j54SNnktC+EOe/LSZqF2HcfquhzyN07CePFuznefrd5MQ9oCbA6eQnpSMXY82an0GFN36vKjVB0WxnIpqXIVth7xCQkLwq1SJtm3bYm9vT7du3XBxcWHfvn3y7/h39gfl5dQpKw9nRo78PqucCtqndtOwYUPq1a+Pvb0DgwcPQU9XlyNHcuqrli1b0b59Bzw989/BVi+morPtdoTsp0n9OjSqWwtHeztGDOyLnm4xfj92Qmn6XfsOUMXXh46tW+BgZ0uvrh1xc3Zmz4Gc+jL39YqpiQnnLv6FT7kyWFta/I2yKlrb71OdYyDzWip4906GDhv1QXEJQjbRAPEPREZG0qlTJ3r16kVYWBinTp2idevWyGQyWrZsSY0aNbhx4wbnz5+nb9++H9xSmJaWpjKfDh06MHLkSMqUKUNkZCSRkZF0yNVCOnXqVFq1asXNmzfp1auX0vyTkpKYNWsWGzZs4Ny5c0ilUjp27KiQ5v79+2zfvp19+/Zx6NAhrl27xsCBAwuMe/369RgYGHDx4kXmzZvH9OnTOXr0KADp6em0bNkSfX19Ll68yKpVq5gwYcIHlUtBXkVFIZHE4uOT08XOwMAADw9PlRdxqamp3L9/Dx+fnG7Wmpqa+PhUJDxc9YVfYmIi+vr6aGkV/KPoVVQkEkksFRRiKoG7hxcRYXcKiOmuwvfQ1NSkgo8v4eHK10lOfsfxo4ewsLTE3LyUynhSU1O5e/8Bvj4VFPL29SnPnfAIpevcCY9QSA9Q2deHO+F3FZaF3rxF2y7d6dFvEIuX/0xcfLzKOJT5u2X14P5dhXWyyyoiV1mlJCezYN4s+g0ciskH3EmPiopCIpHgUzFn/8jcpzwICw9XGdP9e/cU5nrJ3Kd85PvhvXv3SEtLU8jXzs6OUqVLq8wXIDUtnbCnkQR45DQUaGpqEODpxI1Hzwv9PjKZjIvhj3j8KhY/18KH6qgjZ58qnysmTXx9KhSyT5VXWFbJtyJhudJnZGQwd+Fi2rVuiaPDh8WamprG3QeP8KuQM8xEU1MTvwrluB1xV+k6tyPuKaQHqFyxgkL6Mp7unLt0hTcxschkMq7euM2zF5FUrlg+b3YqFbU64UMZB/gQfeK8wrI3R89iEuADgIaODka+ZYg+nuviWyYj+sSfGAdURF1FsT4vavUBFM1yKopxqbMd8goPC6Ninjm7/Pz85On/zv6QlzwPn7x5fPxyUldR3HZ37z/EL+85pkJ5bocrr8/vhN/Fr4JivVzZt4LK9LESKRcuX6Vxvdoq41CmaG6/T3eOybyW+oF+A4d80LXUv4FMQ6PIvv7fiDkg/oHIyEjS0tJo3bo1Dg4OAJQrV47Y2Fji4uJo2rQpLi4uAHh5eX1w/vHx8QXmU6JECbS1tbG0zD9Ou3PnzvTs2VP+98OHD/OlSU1NZdmyZfj7+wOZDQdeXl5cunSJKlnjG5OTk9mwYYN8HFtQUBBNmjRhwYIFSj8XoHz58kyZMgUANzc3li1bxvHjx6lXrx5Hjx7lwYMHnDp1Sr7+rFmzqFev4PHTKSkppKSkKCx7n5JCMV1dhWUSSSwAxibGCsuNjU2QSvJ3IYPMcs7IyMA4zzhbY2MTnufqEZJbXFwc27ZupmGjxgXGnRmTJCumvPkby+PNH1Ocyphe5Inp4P4Q1q1dTXJy8v/Yu++oqI42gMM/UARBkWJBUDrSomIXUzSfiiUxdmOJNRp7iRo79h5bxBIlsaFGY0OwG2OPvWCigGDFxAoLCAiC8P0BLCywsBoJa/I+5+xRdufOvndm7uzu3LlzsapUmemz5qOnp6c2npjY56SmpmJqoroeiKmJCREP/lSzD9GY5rjUxsTEhKhs0/Lq1KzBBw3qY1GhAg8fPuLHDRuZMGUGSxfM1ejLavr7qCsrU+VrOeVXVtnr70ffFbi4ulPP8/WuU8x835zXYZuY5hdTepvKa5uIBw+U+RYvXjzX9ZymJiYoovJuFwCKuARepaZhbqx6vax5aSPuPI5Uu93zF4k0nbCU5ORX6OrqMKFzczxd7dWmfx1ZbcpE5XlTkzLK/c1JoYjOdfmWqUkZlTa1dftOdIvp0vazT98gplhe5dnOy3BfTTuPio7OM32UImvW1/CverNguS8d+gyiWLFi6OroMHrwV1R317yP17Y+4XXpVyhL0uNnKs8lPX6GXpnS6Broo2daBt3ixUl6EpkjTSRGzpq3OW3uz7WlP0jfVvvKSRvj0qQecu+DIncs2er6TdpDXu+RnoeJah4mJgW2qdxla6Iyk/VNaVvdqf/eUob7f75Of26CQhGdZ/qDvx7HsKQBH3nWyzeWnLSz/grvM+YH35W4uLpT/zW/SwmRnQxA/A3Vq1encePGVK1alWbNmuHl5UWHDh0wMzOjV69eNGvWjKZNm9KkSRM6depExYoVXyv/v5NP7dp5L+SWXfHixalTp47ybxcXF0xMTAgODlYOQFhbW6ssouPp6UlqaiqhoaH5DkBkV7FiRZ48eQJAaGgolStXVtm2brbFnNSZM2cO06apXp88ZOhwqlarxnKf75TPTZmm2fWyf0dCQjzTpkzC2tqart2653r92NEjrPBZrPx78rRZhRpPw48b41GjFlFRUfjv3Mb8OTOYt+A7SpQoUajvm9PHDT9U/t/e1gY7Oxt69B1I0O/Xc53pznTs6C+szFZW3tNmF0ps587+xrWgqyz2WVVg2qO//oqPj4/y75zt7l1lpK/Pz+P7kpD0knOhd1m44xcqlTWlThWbog4tTzfDw9kVsIcV3y3SqutMd+45wI3QMGZP/AaL8mUJuh7MklVrKGtmSm2Pqnlu81/tE17X0aNHtK4/18b+QBvLSZvj0jZHj/7KMp+lyr+nTptehNGkk7qD/b/8SpOGHxbYT2pj/f1TnzGZ36WW+HxfKPmL/w4ZgPgbihUrxuHDh/ntt984dOgQPj4+TJw4kXPnzrF27VqGDRvGgQMH2Lp1K5MmTeLw4cPUr/96C9u8aT6arlBdGHKeadPR0SE1NfVv5Tl+/HhGjlRd0DDiwSNSXr1Srq4M6bM6AKIV0ZiZmSufj45WYGfvkGfexsbG6Orq5hrVj45W5JpelpCQwGTviZQ0NGSi91SKF899CNWt56myYnCKMiZFjpiisVcbUxm1MZmYqY5OGxmVwsioFJZWlXB2caVrp7ac+e0UDRvlPY2wjHFpdHV1cy3cpIiOzjWCn8nU1CTXYoLR0dGYmahfnd3SwoIyxsb89fCh2gGIuvUa4OycdeY4WW1Z5Vd/6ssqs/5+D7rCo4d/0bWj6t0T5s2ehpt7VWbNW6R8rl79+ji75G5TCoUCs2ztIVqhwN4h/zaV8+xHtEKBWcbZBVNTU1JSUoiLi1M566mIjs53WqNpKUOK6eoQGau64GTk83jKGqs/7nV1dbAun56vS2UL7jx6xo8Hf3srAxBZbSpa5XlFdIzaFfxNTU1yLfymiI5Rtqk/rt8gOiaGbr37Kl9PTU1l1Y/r2Lk7kI1rfAuIyZhiebbzGMzUtHMzExM16dPPoiUlvcR34xZmjh+FZ8ZK6g62NoTfvsdW/z1qByC0vU94XUmPn6FfoazKc/oVypIc85zUxCRePlOQmpKCfnnzHGnMSXqkOnMiu3r1PLWuP9fG/kAby0mb48qZd371kJOpae4z/tEKhbJfy/z3ddpDvXr1c5TTy4w8cpZTNPb2ec8YyiqnaNXYoqMxNVP/uayOtted+u8tMZipWQg97/487+85164HE/HnX0we83W+cYB21t8/9RlzLegqjx7+RZeOqncImTt7Gm7u7zE723epd5KOrEzwT5GS/pt0dHR4//33mTZtGleuXKFEiRLs2pV+K7IaNWowfvx4fvvtN9577z02b978Ru+hLp8SJUpotBCUOikpKVy8mLVye2hoKNHR0SqXedy/f5+//vpL+ffZs2fR1dXN95ZV+XF2diYiIoLHj7MWRLtw4UKB2+nr62NsbKzyKKGvj6GhIZaWVsqHtbUNpqZmXA26otw2ISGe0NAQXNRcBqOnp4ejoxNBQVeVz6WmphJ09SouLlnbJCTE4z1pPMWLF8d78jS1o+Q5Y6qcEVNQjphuhgbj7OqWT0xVCAq6rBLTtatXcHHJe5t0aaSRpvzwUZd3FUcHLgddU8n7StDvuLnkXa9uLs5cuXpN5blLV4Jwc1F/i8Wnz54R+/w5Zvl8mBoaGlLR0kr5yCyra9n2W5OycnCswrVs5ZtZVs4ZZdW+Yxe+W+7LkmWrlQ+APv0GMuxr1QUp0+vPUvmwtrbG1NSUoGy3u02Ijyc0NBRXNQtD6enp4ejkpLJNamoqV69eVbZDJycnihcvrnIb3QcPHvD0yRO1+QLoFS+Gq3VFzoXezZZ3GudC71LNLv/ba2WXmpZGckqKxunzk9mmruRqU9deq01dvnIV14z0TT5uxCqfJXy/dLHyYW5mRsd2bZgzfaoGMRWnioMdl679oRLT5Wt/4K7m1qDuzk4q6QEuXr2mTJ/yKoWUlFe5ZmToFtMlNU39IKu29wmvK/rsVcz/pzoIXrZxAxRnr6a/Y3IyMZevU/Z/nlkJdHQw/9iT6LNXUEd7+3Pt6g+0sZy0OS6VvAuoh5xcXF1z3er8ypUryvQWFhav3R5ytymb9Dyy7bOm5XQ1RzldzVFOmnoX6q6Koz2Xg7Ju45ven/+Ou5rvIW4uVbh8TfW2v5euXssz/b7DR6jiaI+jnW2BsbwL9VdYnzEdOnZm6fLVfLdslfIB8GUe36WEyI/MgPgbzp07x5EjR/Dy8qJ8+fKcO3eOp0+fUrJkScaPH89nn32GpaUloaGhhIWF0aNHj9fK/86dO6xevVptPra2tty5c4erV69SqVIlSpcujX6ONRHyo6enx9ChQ1m6dCnFixdnyJAh1K9fX+WSCAMDA3r27MmCBQuIjY1l2LBhdOrUSe3lFwVp2rQpDg4O9OzZk/nz5/P8+XMmTZoE8FamWevo6NC6TVu2btmMlaUVFSpYsNFvHWbm5nhmu15twvgxeDZ4n1at0kdx27Rtz+JF3+Lk5ESVKi7s3r2TxKREmjRtBmR8YE4cT1JSEqO/GcuLhAReJCQAYFymTL5rHOjo6PBZm3b8vGUTlhkxbcqIKfs1dJPGf0P9Bu/zaas2ALRu254li+bj6ORMlSrOBGTE1LhpcwAePfyLkyeOUaNmbcqUKcOzZ8/YsW0L+iVKUKtO/pe1tG/zGfMXL8XZyQHnKk7s3L2HxMREmjdpDMDchd9R1tyMvr3Sp0W2++xTRo6bxLadu6lXpxZHT5ziZvgtvh4yEIAXL16w4aetfNjAEzNTU/56+AjfteuxrGhB7ZqaLzqno6NDq4yyqmhZiQoVLNjstxYz87LU98y6xZ/3+NHUb/ABnyjLqgPfLZqHo1MVnKq4ELh7h0r9mZqZ5TmroFy58lSwyP+SJh0dHdq0acOWLVuwtLKiQoUK+Pn5YW5ujmeDBsp048eNo0GDBrT6LH2WRdu2bVm0cGF6m3J2Zre/P0lJScr1ToyMjPDy8sLX15fSpUtjaGjI9ytX4urqqvZLS6bu/6uH94YA3G0q8p6NJRuPnudFUjJtPNNnmkxcF0B5k9IMz7il5o8HTuNmU5HK5Ux5mfyKk9fD2XvuDyZ2aa7MMyb+BQ+jYngaEwfA3cfp14mWNS5F2TIF382kfZvWzF/8HVWcHHGu4sSu3YEkJibSLKNNzVu4hLLm5nyZ0abaftaKUeMmsm2nP/Xq1ObYiZPcDL/FiCHpi9xmDjRmV7x4McxMTahcKf97q2fq1PoT5ny3EhdHe1ycHNkeuI8XiUm0aNIQgFmLl1PO3IyvenQBoEOrFgybOJ2t/nuoX7sGv578jdBbtxk9+CsAjAwN8XjPle/XbUK/RAksypfj6h83OHj0BIP7aD6FWNv6hGJGhhhlW5DU0K4SxtVdeBkVQ2LEQ5xnjsTAqgJBvccCcG/1FmwGdcNlzjdErNtB2Y/rU7FjCy581l+Zx50la6m+Zh7Rl/4g5sI1bIf1pLhRSSLW73ytctLG/lzb+gNtLCdtjaugeliwYAHm5ubKNbRat27N2DFj2LljB3Xq1uX48eOEhYUxdNgw5T5q0h40KactW37C0tISiwoW+PltyCinrDwmjB+HZ4MGtGqV2abasWjRgoxycmb37l0kJiXStKmXcpuoqCgUCgUPM04k3b17l5IlS1K+fHlKly79TtVdx9afMnfJcqo4OuBaxZHtAXtJTEyieeP0z7nZi30oZ2ZGv57dAGjf6hNGTJjCz7sCqV+nJr+eOE1o+C1GDe6vkm98QgLHT59lYJ/X+46es6y0rf4K4zMmv+9SFgV8lxIiOxmA+BuMjY05ceIES5YsITY2FhsbGxYuXEi7du0YMGAA69evJzIykooVKzJ48GD69+9fcKbZGBoaEhISojaf9u3bs3PnTj7++GOio6NZu3YtvXr1eq38x44dS9euXfnzzz/58MMP+fHHH1XSODo60q5dO1q2bElUVBSffvopK1aseK39yK5YsWL4+/vTt29f6tSpg729Pd9++y2tWrXCwMDgjfPNrn2HTiQmJuLjs4T4uDjc3N9j+vTZKqPsjx4+JDbb7UQ/atiImNgYNvptQKFQYG9vz/Tps5TTK8PDwwkNTV/Rut+XvVTe78e1G6hQIf8BmXYdPicxMZHlPouVMU2dPjdHTH+pxPRhw4+JiY1hs9+6jJgcmDp9jjImvRIluHH9DwJ27yQ+Lg4TE1Pc36vKvIVLMcnn0giAjz/6gJiYWNZt3IJCocDB3o450ycrpyY+efoUXd2sASF3VxcmfPM1a/02s2bDRqwsKzJt4jjsbNOn7+vq6nL7zj0OHzlKXHwC5mam1KrhQe8vulLiNRe/a9ehM4mJiazwWUR8XByu7lWZMn1OgWUVm62s7OwdmDJ9Liamb2eF5g4dO6a3qaVLiYuLw93dnekzZqjE9PDhQ5W7fjRs2JDYmBj8Nm5EERWFvYMD02fMULkk4av+/dHR1WXWzJkkJydTq1YtBg0eXGA8zWu7oYiLZ8We4zyLjce5UgVWDOmMuXH6QMEjRYxK/b14mczsLQd4HP0cfb3i2FUwZ1av1jSvnXUm5Ni1m0z226P8e+ya9JlcA1p+yMBPPyowpkYffUB0TAzrN/6kbFOzp09RaVM6OdrU+G9Gss5vE2s3bMTK0pKp2drU2/C/DxsQHRvLms3biFJE42hnw7dTximn7D559kylnN5zdcZ71FB+3LgVX78tVLK0YNb40djbVFammTx6OKs3/MTMRcuIjYvDolw5+n7RmdbN819INydt6hPK1HoPzyN+yr/dFkwAIGLDTq59OR79iuUoWTnry+WLuw+48Fl/3BaOx3ZoDxIfPOL3/pN4djjrVrkPt+2nRDkzqkwZhr5FOWKDgjn/aV9ePlG/UGpetLE/17b+QFvLSRvjKqgenj55gm62kyFubm6MGTuWDevXs27dOqysrPD29sbW1laZRpP2UJAOHTLy8FmaUU7uzJg+M0eb+itHOTXMKCe/bOU0U6VN7d+3l82bNyn/Hjsm/baJI74eqfJDNy/aVnf/+/D99O8tm7cSpYjGwd6WeVMnKi+pe/L0mUrdvefqzKRRw1mz6Sd+8NuMlWVFZkwYg12OOyr9euI0aWlp/O+jN19UURvrrzA+Y/715BKMf4xOWlpaWlEHIf5569atY8SIEbmuwc5u6tSp+Pv755p++LadPn2aDz74gPDwcOXdPjQRduteIUb1ZlK18Komw9TnRR1CLvG6xgUn+ofp6bws6hDyZHXnVMGJ/mFPrOsUnOgfVuJVYlGHkEuMXtmCE/3Dwl2aFHUIeaoScqioQ8hFV+fNL3EsLKlpmt1R6L9OG+sOIC1NexbUzZSmhd9bjFJiCk70D0sorn7GQVF5paXnkZ0dKhecSAu9OPZTUYegVslGXYo6hLdKO1uu+FfbtWsXpUqVwsnJifDwcIYPH87777//WoMPQgghhBBCCCHeLTIAUcRy3vM7u/379/Phhx+qff1d9fz5c8aOHcv9+/cpW7YsTZo0YeHChUUdlhBCCCGEEEKIQiSXYBSx8PBwta9ZWVlRsmTJfzCad4tcgqEZuQRDM3IJhubkEgzNyCUYmpNLMDQjl2BoRhvrDuQSDE3JJRiakUsw3i65BOOfo50t9z/E0dGxqEMQQgghhBBCCCEKnQxACCGEEEIIIYT4z0rT0b4ZSv9W2jfvSgghhBBCCCGEEP86MgAhhBBCCCGEEEKIQieXYAghhBBCCCGE+O/SkfPy/xQpaSGEEEIIIYQQQhQ6GYAQQgghhBBCCCFEoZMBCCGEEEIIIYQQQhQ6GYAQQgghhBBCCCFEoZMBCCGEEEIIIYQQQhQ6uQuGEG9R5WO+RR1CLk8bdivqEHIpmRZf1CHk8kpLu8M7to2LOoRcSugkFXUIuSTpGhZ1CLmkoVPUIeRSJeRQUYeQp5suXkUdQi4uofuLOoRc9NK079hL0dEr6hByKZkcV9Qh5Cm+eJmiDiEXHVKLOoRckoprX39uHne/qEPIJap05aIO4d9FR/s+s/+tZAaEEEIIIYQQQgghCp0MQAghhBBCCCGEEKLQaeecYyGEEEIIIYQQ4p+gK+fl/ylS0kIIIYQQQgghhCh0MgAhhBBCCCGEEEKIQieXYAghhBBCCCGE+M9Kk7tg/GNkBoQQQgghhBBCCCEKnQxACCGEEEIIIYQQotDJAIQQQgghhBBCCCEKnQxACCGEEEIIIYQQotDJAIQQQgghhBBCCCEKndwFQwghhBBCCCHEf5eOnJf/p0hJCyGEEEIIIYQQotC91gBEo0aNGDFiRCGFIjQxdepUPDw83nq+d+/eRUdHh6tXr6pNc+zYMXR0dIiOjgZg3bp1mJiYvPVYhBBCCCGEEEL8+2jNJRjr1q1jxIgRyh+3Qvt9/vnntGzZsqjDyCUtLY1NGzdw8MB+4uPjcHVzZ9DgYVhZWeW73Z7AAHbu2IZCEYWdnT39Bw7G2dkFgOfPY9m00Y8rly/x9OkTypQpQ33PBnzRvRdGRkYFxrT1chjrz4cQGZ9IlfImjG1Sk/cqmhe43YHg+4wPPEMjRysWt/tA+XxkfCLfHQ/izJ1HxCUlU7NyOcY0romNWekC88wUsGcv23bsIkqhwN7OjsEDvsLFuYra9CdOnmLdxk08fvwEK0tL+vbuSd06tZWvb9i0mWMnTvL06TP0ihfHydGRXj2+wNXF+Z2OCSAwMJDtO3agyIhr4MCBODurz+PkyZNs8PPj8ePHWFla0rtPH+rWqaN8PS0tDb+NGzlw4ADx8fG4ubkxZPDgAttodmlpafy0cR2HD+wlPj4OF7f3GDB4BJZWlfLdbl+gP7t2bCVaEYWtnQP9Bg6lirOr8vWJY7/m+u9BKts0a9GKgUO/LjCmwMBAdmzfjkKhwM7eXqNy8tuwgcePH2NpZUWf3r2pU7euyj5u9PNTKafBQ4a8djlpW3+QGdfmjes4fGCfsv4GDh5eYP3tDfTHf8fPKDLq76uBQ6mSEVfO/KdPHs/lSxcYP2ka9Rt8kEduubfRlrIy+6A29qO+pEzN9zCwLM/F9oN4HHAk3zjMPqqL24JxlHJzIjHiIeFzVvJgwy6VNDYDu2I/8kv0LcoRey2E6yNmEHPh9wLLJrs3bZcFHR8vX77E19eXE8ePk5ycTM1atRg8eDCmpqYFxhSwZy/bd+xU9p2DBvQvsO9cv3Gjsu/8sncvlb7Tb9Nmjp04oew7HR0d6d2jOy6v2XempaWxcaNfRpuKx9XNjcGDh2rUpnbsyCgrO3sGDBykUlb79+/j+LGjhIff4sWLBLb+vJ1SpUoVGM+uvQfYuiuAKEU0DnY2DPuqD65VnNSmP3bqDGs2beHRk6dUsrTgq55fUL92TZU09yIesHr9RoL+uMGrV6nYVK7EtPGjqFCuXIHxZNKmYy97TNpUdwABgXtUPosHDRyQ72fMiZMn2eC3UflZ3KdPb+VncUpKCus3bODChYs8fPQIIyMjanh40Kd3L8zNC/5+lmn7gaNsDDxEVHQMjjaVGNWnC+6OdnmmvR3xF6u37ibkzn0ePY1kRM9OdP6kSa50T6IULN+4kzNX/yAp6SWVLMoxaVAvXB1sNY6rsPqp/fv2cezYMcLDw3nx4gU/b9umcf1puzS5BOMfIyUt3ljJkiUpX758UYeRy47tPxMY4M/gIcNYuHgpBgYGTPYez8uXL9Vuc+L4MX7wXUWXrl/wnc8K7Oztmew9gehoBQCRkZFERUbSp28/lq9czYivR3Pp4kW+W7KwwHgOBt9n4dGr9H/fnc09vahSzoRBPx8nKj4x3+3+ioln8dGr1Kik+iUmLS2Nr3ed4kF0PEvafcBPPb2oaGzIgJ+P8eJligYlBMdOnGSV74980bUzK5Yuxt7OlgneU1CoGQC8fiOY2fMX0NyrKSuXLqGBZz2mzpzNnbv3lGkqWVkxZEB/Vi/3YdG386hQoTzjvacQHRPzzsYEcPz4cVb7+tKta1d8fHyws7dnkre32sHSGzduMHfePJp5ebHMxwdPT09mzJjB3bt3lWm2bd9OQEAAQ4cMYcnixRgYGDDJ2zvfNprTru1b2BOwkwFDvmb+4uUYGBgwzXtsvnmcOn6UNb4r6dy1B4t8VmFr78A077HKdp6pafNPWLtxu/LR88uvCozn+PHj+K5eTddu3fDx8cHezg7vSZPyLad5c+fi1awZPsuW5VlO27dtIyAggCFDh7J4yRIMDAzwnjTptcpJ2/qDTDu3b2FvwC4GDhnBt4uXYWBgwFTvcfnGdfL4Udb4fs/nXXuwyOd77OwdmJpH/QEE+O9AR0dH43hAu8qqmJEhsddC+WPYNI1iL2lbiToBq4g8do5TtVtzx2c9VVfNpGzTrIGXih1b4PrteMJmLudU3bY8vxZCvb0/UqKcmUbvkelN2qUmx8fqVas4f+4c4ydMYN78+URFRjJz5swC4zl24iSrfX+gW9cuLF+6BHs7OyZ6T1Z77F2/Ecyc+d/S3MuLFUu/o4FnfabNnMXdbH2nlZUlgwcMYNXyZSz8dh4WFcoz3nvya/WdANu3byMwYDeDhwxj0eKMsvKeWECbOo6vry9du37BUp9l2Nnb4+09UWV/kpKSqFmrNp0+/1zjWH49eZqVP66nZ+eOrF48DwdbG8ZMmYUiOu99+iM4lBkLltCy6f/wXTKfD+rVxXv2fO7cu69M8+fDRwwb501lKysWz5rGD0sX0P3z9pTQK6FxXKBdx14mbao7gOPHT+Dr68sXXbuyzGcp9vZ2TCzws3g+zby8WO6zFE9PT6bPmKn8jElKSiI8/BZdu3Rhmc9SvCdN5MGDB0ydNl3jmA7/doHvNmyjb4dPWT9vEk42lRkx6zuiYmLzTJ+Y9BKrCuUY3LUt5ibGeaaJjYvnK+/5FC9ejMUThvHT4mkM69GR0kaGGscFhddPJSUlUat2bT7v3Pm14hEiu9cegEhNTWXMmDGYmZlhYWHB1KlTla/dv3+f1q1bU6pUKYyNjenUqROPHz9Wvh4UFMTHH39M6dKlMTY2platWly8eJFjx47Ru3dvYmJi0NHRQUdHR5mvra0ts2fPpk+fPpQuXRpra2tWr16tEtPYsWOpUqUKhoaG2Nvb4+3tTXJysvL1zMsW1qxZg7W1NaVKlWLQoEG8evWK+fPnY2FhQfny5Zk1a5ZKvtHR0fTt25dy5cphbGzM//73P4KCVM8M5mf37t3UrFkTAwMD7O3tmTZtGikpWT8QdXR0WLVqFZ9++imGhoa4urpy5swZwsPDadSoEUZGRjRo0IBbt27lynvVqlVUrlwZQ0NDOnXqREyOLwU//PADrq6uGBgY4OLiwooVK1ReP3/+PDVq1MDAwIDatWtz5cqVXO+xb98+qlSpQsmSJfn4449VfhhA7kswMsvZz88PW1tbypQpQ+fOnXn+/LkyzfPnz+nWrRtGRkZUrFiRxYsXv9VLe9LS0tjtv4vPO3elvmcD7OzsGTlqDFGRkZw5c1rtdv67dtCseQuaejXD2tqGwUOGo6+vz+FDBwGwtbVjwqTJ1KvnScWKllT3qEGPnr05f+4cr169yjemjRdDaVfNntZV7XEoW4aJzWpjoFcc/9/vqN3mVWoqE/acYcAH71HJRPVMxX1FHL//FclEr1q4VzTH1tyYCV61SUp5xf7ge2pyVLVj125aNPeiWdMm2FhbM3zIIPQN9Dl46Je8yycgkDq1atKpfTusrSvTq/sXODrYE7BnrzLN/xo1pGYNDypWtMDWxpr+/b4kISGBO3fuvrMxAezatYsWzZvj5eWFjbU1Q4cMQV9fn0OHDuWZfvfu3dSuVYsOHTpgbW1Njx49cHBwIDAwEEhvo/7+/nTu3BlPT0/s7OwYPWoUkZGR/HbmjEYxpaWlEei/g06dv6Ce5/vY2jkwfNQ4oiKfce7MKbXb7d61Da/mLWns1YLK1rYMHPI1+vr6HDm0XyWdvr4+pmZmyoehYcFny3bt2kXzFi3w8vLC2saGIUOHFlhOtWrXfq1yGjV6NJGRkZz57TeNy0nb+oPMuAL9d9IxW/2NGDWWqMhnnM23/rbj1bwlTbyaY21ty8AhI9DX1+eXQwdU0t2+Fc7undsYOuIbjcopMyZtKqunB09wc8oSHu/O+/jPyearzry484DgMfOIC7nNvRWbeLTjIHbDeynT2I3oTcSPP/Ng/U7igm/x+6ApvEpIpHKv9poVEm/eLgs6PuLj4zl06BD9+vXDw8MDJycnvh45kuAbNwgJDs43pp27/GnevJmy7xym7DsP55nePyCA2rVq0jGj7+zZ/QscHRzYvWePMs3/GjXK1nfa8FW/vq/dd2a1qS4ZZWXPqFHfZLSp/MpqJ82bN6eplxfW1jYMGTIUA319DmW0KYA2bdrSqdPnuLjknv2jzrbde/jEqzEtmnyMrXVlRg76CgP9Euz/5dc80+8I3Evdmh50btcam8qV6PNFZ5zs7dm1N+t4+3HjT9SrVYMBvbvj5GCHVUUL3q9XB1OTMhrHpW3HnmpM2lF3ADt37aJ58+Z4eTXN9llswEE1nzH+uwOoXasWHTu0x9ramp49uuPo4EBAYHo7NzIyYs7sWXz00YdUrlQJVxcXBg0aSFh4OE+ePNEopp/2HKZ14w/49OP3satkydh+3TAoUYI9R/OuNzdHW4Z270DT9+uip6eXZxq/3QepYG6K96BeuDvaYVm+LPWqu1PJQvMTfoXVTwG0aduWTp06vXb9CZHdaw9ArF+/HiMjI86dO8f8+fOZPn06hw8fJjU1ldatWxMVFcXx48c5fPgwt2/f5vNsI5zdunWjUqVKXLhwgUuXLjFu3Dj09PRo0KABS5YswdjYmIcPH/Lw4UNGjx6t3G7hwoXKH8mDBg1i4MCBhIaGKl8vXbo069at48aNG3z33Xf4+vqyePFilbhv3brF/v37OXDgAD/99BM//vgjn3zyCQ8ePOD48ePMmzePSZMmce7cOeU2HTt25MmTJ+zfv59Lly5Rs2ZNGjduTFRUVIHldPLkSXr06MHw4cO5ceMGq1atYt26dbkGOWbMmEGPHj24evUqLi4udO3alf79+zN+/HguXrxIWloaQ4YMUdkmPDycn3/+mcDAQA4cOKAsl0ybNm1i8uTJzJo1i+DgYGbPno23tzfr168HIC4ujk8//RQ3NzcuXbrE1KlTVcobICIignbt2tGqVSuuXr1K3759GTduXIH7fevWLfz9/dmzZw979uzh+PHjzJ07V/n6yJEjOX36NAEBARw+fJiTJ09y+fLlAvPV1ONHj1AoovDwyJoiaWRkhLOzi9ovccnJyYSHh+HhUUP5nK6uLh4eNQgJUf/FLz4+HkNDQ4oVK6Y2TfKrVwQ/UlDPtkJW3jo61LOpwLW/nqndbvVvNzAzNKBtNftcr73M+OJQItv76uroUKKYLlf/VJ+nMqbkZMLCw6mRbS0RXV1danhUJzgkJM9tboSEUMOjuspztWvWVJs+OTmZffsPYmRkhL1d3lMRtT2m7HF55IjLw8ND7fsEh4TgUaOGynO1atVSpn/06BEKhUJlX9PbqHOBPzQyPX70EIUiimoetbLlUYoqzq6EBt9Quy+3wm+qbKOrq0t1j1qEhqhuc+LoEbp3bsOwgX3wW+tLUmL+s3WSk5MJDwvLs5zU7VNIcLBKGUB6OWWmzyyn7GWZWU7qyj4nbesPsuJKr7/qKnFpVn/Zt0mvv5oq9ZeUmMjC+bPoP2gYpmaan9nX1rLSlEl9D579qjqA9/TwKUzrewCgo6dHmZruPDuS7ct3WhrPfv0Nk/qqx2t+3qRdanJ8hIWFkZKSopJv5cqVKVe+fL7tPbOPqpmtL0zvOz24ERKa5zbBISG5j72aNQroOw9k9J22amPJSVlWHjnL6u23qYIkJydzM/w2tTyqqeRbs3o1rofczHObGyE3qVW9mspzdWpWV6ZPTU3l7MXLVLK05JspM2nb/UsGjh7PqbPnXys2bTz2tKnuMvPO+ztC/p/FNWp4qDxXq5b67wiQXj46OjoYaXBJQXJKCqG371OnatYljLq6utSp6srvN28XuL06Jy8G4Wpvw4RF39Oi7yh6jJmB/y8nXyuPwuqn/vV0dLT38S/z2mtAVKtWjSlTpgDg5OTEsmXLOHIk/brM33//nTt37lC5cmUANmzYgLu7OxcuXKBOnTrcv3+fb775Rjlq5uSUdd1dmTJl0NHRwcLCItd7tmzZUvkDe+zYsSxevJijR48qr0maNGmSMq2trS2jR49my5YtjBkzRvl8amoqa9asoXTp0ri5ufHxxx8TGhrKvn370NXVxdnZmXnz5nH06FHq1avHqVOnOH/+PE+ePEFfXx+ABQsW4O/vz/bt2/nqq/ynJE+bNo1x48bRs2dPAOzt7ZkxYwZjxoxRlh9A79696dSpk3LfPD098fb2plmzZgAMHz6c3r17q+SdmJjIhg0blNdx+fj48Mknn7Bw4UIsLCyYMmUKCxcupF27dgDY2dkpB0F69uzJ5s2bSU1N5ccff8TAwAB3d3cePHjAwIEDle+xcuVKHBwcWLgwfaqes7Mzv//+O/Pmzct3v1NTU1m3bh2lS6evRdC9e3eOHDnCrFmzeP78OevXr2fz5s00btwYgLVr12JpaZlvnpA+5SspKUnluZdJSZTIqJtMCkX64JCJqYnK8yYmpkQrck9TBoiNjSU1NRWTHNfZmpiY8iAiIs9tYmJi2PLTJpq3yH8NDEXCS16lpWFmaKDyvLmRAXej8p6id+XBU/yv3WZLr2Z5vm5rZoyFsSE+J64xqVltSuoVY+PFmzx+/oJncfn/UISs/TXNsYCoqYkJERF/5r0fiuhc6U1MTIjKUaZnz19g9rxvSUpKwszMlLkzp1OmTN7TDLU9JpW4crQNUxMTtW1DoVDkuR+KjLgy/80rT4WaNppTtLKdq+ZRxsRUeQzk9Dw2Js92XsbElAcRWVOKP2rUmPLlK2BqZs69u7fZsGY1f/4ZwbhJ6qelqisnE1NTIh48yHMbhUKR+5gzNS2wnLKnKYi29QdZcSky4sr9Hur2LVZN/eWM60ffFbi4ulPP832NYsmKSTvLSlP6FcqS9Fh1ADbp8TP0ypRG10AfPdMy6BYvTtKTyBxpIjFyzj3Qq86btEtNjg+FQkHx4sVzXUttamKCIp+THso6MMndn0REqDv2cved6f1PtMpzZ8+fZ062vnPOzOmUKaP5mf2sslJ9L5N8+rqsNpV7mwg1bUoTMbHPMz5jVOM3NSnD/T/z/oyJio7OI31WOUXHxPDiRSI/7fCnzxed6d+zG+cvX2XynAUsmjUFj/fcNYpNG489baq7N81boVDkWig9v/hfvnzJmrVradSwIUaGBV/uEB0bx6vUVMxyXEphalKau389LHB7df568pSdh4/T5ZOm9GzbkuBbd1m8dgt6xYvxSaMGGuVRWP2UEG/LGw1AZFexYkWePHlCcHAwlStXVg4+ALi5uWFiYkJwcDB16tRh5MiR9O3bFz8/P5o0aULHjh1xcHB4rffMHKTIPj1q69atLF26lFu3bhEXF0dKSgrGxqodgq2trfJHMUCFChUoVqwYurq6Ks9l5hsUFERcXFyuhWhevHiR5yUROQUFBXH69GmVGQ+vXr0iMTGRhIQEDDM6t+z7VqFC+lnyqlWrqjyXmJhIbGyscp+sra1VFpHx9PQkNTWV0NBQSpcuza1bt/jyyy/p16+fMk1KSoryi0NwcDDVqlXDwMBAJY/sgoODqVevnspzOdPkJWc5Z7YPgNu3b5OcnEzdbIvMlSlTJt8FhDLNmTOHadNUrwUeMnQ4VatVY7nPd8rnpkwr+HrZvyshIZ5pUyZhbW1N127d32re8UnJTNp7Du/mdTA11M8zjV4xXRa2eZ9pBy7QcOkuiunoUM+2Au/bVyQtLe2txvO6qlerykqfJcTGxrLvwCFmzp3H0kULcn3Z/a/H9LqOH/2FlT6LlH9Pmjan0N6rWYtPlf+3tbPH1NSMyRNG8/Dhn1SsqPnij0Xh6NEjWtkfHDv6Cyt9smbleU+bXSixnDv7G9eCrrLYZ1WBabW1rLTN0V9/xcfHR/l3zs+hfzOPatVY4fMdsbGx7D9wiFlz57F00UK1d786evRXlvksVf79OtfSv4tSU9M/bxvUq03H1un9pqO9HddDQgncf1jtAIQ2Hnv/tbrLKSUlhVlz5pCWBkOGDC7SWFJT03B1sGFg17YAONtZc+v+X+w6fELtAMR/uZ8S76bXHoDIec2Sjo4OqampGm07depUunbtyt69e9m/fz9Tpkxhy5YttG3b9o3f88yZM3Tr1o1p06bRrFkzypQpw5YtW5Rn7vPLI7984+LiqFixIseOHcsVjya3noyLi2PatGnKWQjZZf/hnz2GzAXD8npO0zKOi4sDwNfXN9cAwtuc7qrO32kf+Rk/fjwjR45UeS7iwSNSXr1SrvgMKNf+iFZEY2aWNXgUHa3Azj7vwS5jY2N0dXVznWmIjlbkmsKckJDAZO+JlDQ0ZKL3VIoXz/8QMjUsQTEdHaISVGcmRMYnYm5kkCv9g+g4/oqJZ8SOrOl2qRmDCrW//ZldfVtS2bQUbhZmbO3VjOdJL0l+lYqZoQHd/Q7jZlHwlOvM/c25uKMiOhqzHGcXlPthapIrfXR0NGY5RspLGhhgZWmJlaUlri4u9OrXnwOHDtOlU8d3LiaVuHK0DUV0tNrp7aampnnuR+ZZhcx/FQoFZtnyUERH42Cf95nYuvUaqNypIjk5fRGpaIVCpZ3HRCuws3fMM4/SxmXybOcxebTz7Kq4pL/vo7/+UjsAoa6cohWKXPWRydQ099m9aIWiwHKKViiwVzNwXa+ep1b2B3XrNcBZpf4y41K8Rlx511/2uH4PusKjh3/RteNnKmnmzZ6Gm3tVZs3LGsTS1rJ6U0mPn6FfoazKc/oVypIc85zUxCRePlOQmpKCfnnzHGnMSXqk/tK1evXr4+ySu5xep11qcnyYmpqSkpJCXFycyiyI/Pqa7HnnXIg0e5+TU159Z3p6E5XnDHL0nb37fcWBQ4fprKbvrFevfo42ld5PKXK1qWjs1fR1WW1KNb7o6GhMzQq+G4g6ZYxLZ3zGqK6XpYiOwUzNdzozE5M80meVUxnj0hQrVgzbbCfeAKwrVeL3G+qn+WvjsafNdfemeZuamuZaoDI6j+MiJSWF2XPm8uTJU+bNma3R7AcAE+NSFNPVJSpadTarIvo55q+xBkhOZU3LYFtJdWawbSULjp1Tf7nyP9VPCfG2vLW7YLi6uhIREaEyFerGjRtER0fj5uamfK5KlSp8/fXXHDp0iHbt2rF27VoASpQoodHiXTn99ttv2NjYMHHiRGrXro2TkxP37mm2EF9+atasyaNHjyiecfup7I+yZctqtH1oaGiubR0dHVVmXbyJ+/fv89dffyn/Pnv2rPIykgoVKmBpacnt27dzva9dxnXvrq6uXLt2jcRs13WfPXtW5T1cXV05f171OsacaV6Xvb09enp6XLhwQflcTEwMN2/mff1ldvr6+hgbG6s8SujrY2hoiKWllfJhbW2DqakZV4OyFtVMSIgnNDQEF1fXPPPW09PD0dGJoKCryudSU1MJunoVF5esbRIS4vGeNJ7ixYvjPXkaJUoUvMq1XrFiuFqYcu5e1mKsqWlpnL/3mGqWuduRrbkx23o3Y0svL+WjoaMVdazLs6WXFxbGJVXSl9YvgZmhAfeinnPjkYJGjgWfodbT08PJ0ZGrV7MWVE1NTeXq1Wu4qllUyM3FhStB11Seu3zlqtr0mdJS01QWhH2XYlKJKyhnXOrfx9XFhatXr6o8d+XKFWV6CwsLTE1NVfKMT0ggNDRUbRstaWhIRUsr5aOytS2mpmZcC8r6QpKQEM/N0GCcXd3yzENPTw8Hxyoq26SmpnLt6mWcXfLeBuBOxoyv/H4E6enp4ejkRFC2/c4sJ3X75OLqmmc5ZabPLKfseSbExxMaGqq27LW1PzDMVX82f6P+svYlvf6uKOuvfccufLfclyXLVisfAH36DWTY16oLUmprWb2p6LNXMf9ffZXnyjZugOJsemxpycnEXL5O2f9lm8mno4P5x55En829CHOm9HKyVD6sra1fu11qcnw4OTlRvHhxlWPiwYMHPH3yJN8+LbOPunI1qy9MzzsINzW3zHR1cVHpf+Dt9J25y8omvayytQ9N29TVHG3qao429br09PSo4mjP5aCsW66mpqZy+drvuLvkfbtSN5cqXL6meovWS1evKdPr6enh4uRARI5LOB789RcVyqv/nqiNx542111m3umfxbnzzv+zOGc7v6KSPnPw4c+//mLO7Fm5Zk/nG1Px4jjbW3Phj6zBptTUVC78EUzVKppf1pVTNWdH7v/1SOW5iL8eY5HP3Xr+qX5KiLflrQ1ANGnShKpVq9KtWzcuX77M+fPn6dGjBw0bNqR27dq8ePGCIUOGcOzYMe7du8fp06e5cOECrhmN2tbWlri4OI4cOcKzZ89ISEjQ6H2dnJy4f/8+W7Zs4datWyxdupRdu3YVvKEG++Pp6UmbNm04dOgQd+/e5bfffmPixIlcvHixwO0nT57Mhg0bmDZtGtevXyc4OJgtW7aorFfxpgwMDOjZsydBQUGcPHmSYcOG0alTJ+X6GdOmTWPOnDksXbqUmzdv8vvvv7N27VoWLUo/+9W1a1d0dHTo168fN27cYN++fSxYsEDlPQYMGEBYWBjffPMNoaGhbN68mXXr1v2tuEuXLk3Pnj355ptvOHr0KNevX+fLL79EV1f3tW8Xp46Ojg6t27Rl65bNnDt7hrt37rBowXzMzM3xzHZN9ITxYwgM3K38u03b9hw8sI8jvxwi4v59VixfSmJSIk2apq/DkJAQj/fE8SQlJjJ8xEheJCSgiIpCERVV4MDZF7Wd2RV0m4A/7nA7MpbZhy7yIjmF1lXTB4Qm7T3L0uPpXx71ixfDsZyJyqO0gR6GJfRwLGeCXsYslsMhEVy8/4QH0XEcDfuTgT8fo5GTFZ52uddQyUv7tq3Zd/AQh345wv37ESxdvpLExESaNU1fm2P+wsX8uG59Vvl81oqLly6zfecu7kc8YMOmzdwMD+ezTz8B4EViImvWbyA4JITHT55wMyychUu+41lkJB998EGeMbwLMQG0bduWAwcOcPiXX7h//z7Lli8nKSmJpk2bAulrw2QOpAK0bt2aS5cusWPnTiIiIti4cSNhYWG0atUKSG+jbdq0YcuWLZw9e5Y7d+6wcMECzM3NaaDBZU6ZebRq055tWzZy/uxp7t65zZIFczEzL0s9z6x98x4/ir2BWf1h67YdOXxgL7/+cpCI+/f4fvkSEpMSady0OQAPH/7J1s1+hIfd5PHjR5w/e5olC+fg/l41bO3yv1wus5x+OXyY+/fvs3zZMo3KaeeOHRqX04KFCzE3N8ezgWbXwWpjf5AZV6s27fh5yybOnf1Npf7qq9TfaPYG+meVWdsOHMqj/jLjMjUzw8bWTuUBUK5ceSpYVHynyqqYkSHG1V0wrp7+ZdnQrhLG1V0wqJy+H84zR1J9bdaaRPdWb8HQrjIuc77ByNkemwFdqdixBXe+W6dMc2fJWip/2Qmr7m0o5WLPe8unUtyoJBHrd+ZbNjnLSZN2OX7cOAIDApR/F3R8GBkZ4eXlha+vL0FBQYSFhbF40SJcXV0L/PLfrm0b9h88yOGMvtNn+QoSExPxatoEgPkLF7FGpe/8LFvfGYHfps2EhYfT+tP0ywgSc/SdYdn6zg8/0Hxtkcw2tWXLT5zNaFMLFyzIaFNZZTVh/DgCA7OXVTsOHtjPL79klNVyHxKTEmna1EuZJioqilu3bvEw42TM3bt3uXXrlspdt3Lq2PpT9hw6woEjx7gX8YDFK31JTEyieeOPAZi92Aff9ZuU6du3+oTzl6/y865A7j/4k3WbfyY0/BZtP2muTPN52884euo39hz8hT//esiuPfv57fwl2rTMew2n/MpJW4697DFpS90BtGvblv0HDio/i32WLycxKRGvjGPo2wULWbN2XVb5tP6Mi9k+i/02biIsLJzPWqW385SUFGbOns3NsDDGfjOa1FeviIqKIioqSuOTFF0+bUrAkZPsPfYbdx48ZP4Pm0hMesknjdLrbdqyNazYnNW/JKekcPNuBDfvRpCSksLTqGhu3o0g4lHWZeWdP2nCH2G3WbdzHxGPnnDw1Dn8j5ykfbOPNYoJCq+fgqz6++s160+I7N7aHEgdHR12797N0KFD+eijj9DV1aV58+bKa5KKFStGZGQkPXr04PHjx5QtW5Z27dopr1Nq0KABAwYM4PPPPycyMpIpU6ao3OJTnc8++4yvv/6aIUOGkJSUxCeffIK3t7dG2xa0P/v27WPixIn07t2bp0+fYmFhwUcffaRcqyE/zZo1Y8+ePUyfPp158+alj5S7uNC3b9+/FReAo6Mj7dq1o2XLlkRFRfHpp5+q3Gazb9++GBoa8u233/LNN99gZGRE1apVlbe6LFWqFIGBgQwYMIAaNWrg5ubGvHnzaN8+61Zk1tbW7Nixg6+//hofHx/q1q2rvB3q37Fo0SIGDBjAp59+irGxMWPGjCEiIkLlspS/q32HTiQmJuLjs4T4uDjc3N9j+vTZKiP/jx4+JDbbrUs/atiImNgYNvptQKFQYG9vz/Tps5RT9cLDwwkNTR/l7vdlL5X3+3HtBipUUP/Dv5mrNYoXSaw89QeR8Yk4lzdheceGykswHsUmoPuaAzBP41+w8OgVIuOTKFvKgE/dbfmqgfqz2Dk1+uhDYmJi2LBxs3J/Z02fqtzfJ0+fqgwKubu5Mv6bUazz28Ta9X5YWlkyddIE7GxtACimq0tExAMOH/mV2JhYShsb4+zkyKL5c7G1sX5nYwJo2LAhMbGxbPTzI0qhwMHenhnTp6vGlW1Wk5ubG2PHjGH9hg2sW7cOKysrvL29sbW1Vabp2KEDiYmJLPXxIS4uDnd3d2ZMn/5aZ4bbduhMYmIiK3wWER8Xh6t7VSZPn5ujnf+l0s4/aPgxMbHR/OS3FoUifXrvlOnzMDFNP7NSvLge165eYs/uHSQmvqBsufJ4vv8Rnbp8oVE5xcbE4LdxI4qoKOwdHJg+Y4aynJ4+eaLSzt3c3Bgzdiwb1q9XW04dOnZMP5aXLlWW0/QZM16rnLStP8jULo/6mzJ9Tr7192HDj4mNjWGz37ps9TdXWX9/lzaVVZla7+F5xE/5t9uCCQBEbNjJtS/Ho1+xHCUrZw2qvLj7gAuf9cdt4Xhsh/Yg8cEjfu8/iWeHs25r+nDbfkqUM6PKlGHoW5QjNiiY85/25WWOhSkLokm7fPjwITGxWVOzCzo+AL7q3x8dXV1mzZxJcnIytWrVYtDggq9Hz+o7N2XrO6dlHXtPn6oce+5uroz7ZjTr/Taybv0GLK0smTJpIrYZfaeuri4PIh4w48gRZd9ZxcmJhfPnYmtj83pl1SGjrHyWZrQpd2ZMn5mjrP7K0aYaZrQpv2xtaqZKWe3ft5fNm7MGC8aOSb+T14ivR6r82M3ufx++T0xMLOs2byVKEY2DvS3zpk5UXub35OkzlXJ6z9WZSaOGs2bTT/zgtxkry4rMmDAGu2yfHx961uPrgV+xefsufHzXUNnKkmnjRlPV7fXOGGvTsZdJm+oOoGHDj4iJjcHPb6My75m5PotVP2PGjvmG9Rv8WLduPZZWVkz2nqT8jHkWGcnZs+l3vhs0ZKjKe82bO4fqOda8y0vTBnWIjn2O788BREbH4mRbicUThmGesTDlo2dRKt9bnkZF02PMDOXfmwIPsSnwEDXcqrByano5uDnaMm/0IFZu3smaHXuoWL4sI3p+TvMPVS+rLkhh9VP79u1j86as+hvzTfrsuq9HjlQZqHgXpem8tfPyogA6aUW9ap34T4uPj8fKyoqFCxfy5Zdfvta2Ybf+/qU2b5vVsR+LOoRcnjbsVtQhvBNe6bzda9LfliTe3uDc21JCJ6ngRP+w1LTCX+Pmdb1C+2Iqxutf6vhPuOmi/odHUXEJ3V/UIeRSLDWlqEPIJUVHr+BE/zDDFO08Gxtf/M3XBigsOvz9dbreNm3sp0zi8r5bSlGKKl254ERFQN16Vtru+fm9RR2CWqXrflLUIbxV2vmNW/xrXblyhZCQEOrWrUtMTAzTp6evtNy6desijkwIIYQQQgghRGGSuSZvyN3dnVKlSuX52JRtapLIbcGCBVSvXp0mTZoQHx/PyZMnNVrYUwghhBBCCCHeOh0d7X38y8gMiDe0b98+tYvUaLJGxH9VjRo1uHTpUlGHIYQQQgghhBDiHyYDEG/I5jUXYhJCCCGEEEIIIf7L5BIMIYQQQgghhBD/XTq62vt4TcuXL8fW1hYDAwPq1avH+fPn1ab19fXlww8/xNTUFFNTU5o0aZJv+rdBBiCEEEIIIYQQQoh33NatWxk5ciRTpkzh8uXLVK9enWbNmvHkyZM80x87dowuXbpw9OhRzpw5Q+XKlfHy8uLPPwvvzi8yACGEEEIIIYQQQmihpKQkYmNjVR5JSXnfEn3RokX069eP3r174+bmxvfff4+hoSFr1qzJM/2mTZsYNGgQHh4euLi48MMPP5CamsqRI0cKbX9kAEIIIYQQQgghhNBCc+bMoUyZMiqPOXPm5Er38uVLLl26RJMmTZTP6erq0qRJE86cOaPReyUkJJCcnIyZmdlbiz8nWYRSCCGEEEIIIYTQQuPHj2fkyJEqz+nr6+dK9+zZM169epXrjowVKlQgJCREo/caO3YslpaWKoMYb5sMQAghhBBCCCGEEFpIX18/zwGHt23u3Lls2bKFY8eOYWBgUGjvIwMQQgghhBBCCCH+s9J0dIo6hL+tbNmyFCtWjMePH6s8//jxYywsLPLddsGCBcydO5dffvmFatWqFWaYsgaEEEIIIYQQQgjxLitRogS1atVSWUAyc0FJT09PtdvNnz+fGTNmcODAAWrXrl3occoMCCGEEEIIIYQQ4h03cuRIevbsSe3atalbty5LliwhPj6e3r17A9CjRw+srKyUi1jOmzePyZMns3nzZmxtbXn06BEApUqVolSpUoUSowxAiHeWrs6rog4hl4cf9yrqEMS/TAnyvs2SUKWN/YEu2heTtnIJ3V/UIeQS4tyiqEPIRRvLSYe0og4hlxd6hfOl+e+SPkEzqVo4QTuqdOWiDkEIjXz++ec8ffqUyZMn8+jRIzw8PDhw4IByYcr79++jq5t1jK1cuZKXL1/SoUMHlXymTJnC1KlTCyVGnbS0NO375BBCA7du3y7qEIQQQvxLyQCEEEK8Pgd7+6IO4Y3EXj5c1CGoZVyzaVGH8FZp3xCjEEIIIYQQQggh/nVkAEIIIYQQQgghhBCFTtaAEEIIIYQQQgjxn5XGu38bzneFzIAQQgghhBBCCCFEoZMBCCGEEEIIIYQQQhQ6GYAQQgghhBBCCCFEoZMBCCGEEEIIIYQQQhQ6GYAQQgghhBBCCCFEoZO7YAghhBBCCCGE+M9K05Hz8v8UKWkhhBBCCCGEEEIUOhmAEEIIIYQQQgghRKH7Vw1A9OrVizZt2hR1GH9Lo0aNGDFiRJHGYGtry5IlSwr1PXR0dPD39y/U9xBCCCGEEEKIAunoau/jX+ZftQbEd999R1paWlGH8bfs3LkTPT2919pGR0eHXbt2vfODL29LYGAgO7ZvR6FQYGdvz8CBA3F2dlab/uTJk/ht2MDjx4+xtLKiT+/e1KlbV/l6WloaG/38OHDgAPHx8bi5uTF4yBCsrKw0julN8yhoX16+fImvry8njh8nOTmZmrVqMXjwYExNTQuMSRvLSRtj+jv5FGb9SUzvbkzaGpfEVHBMZh/Uxn7Ul5Sp+R4GluW52H4QjwOO5L/NR3VxWzCOUm5OJEY8JHzOSh5s2KWSxmZgV+xHfom+RTlir4VwfcQMYi78XkDpaL6/OUnfKTG9izFpYzvXxpj+Tj6F/dknBPzLZkCUKVMGExOTog7jjbx8+RIAMzMzSpcuXcTRvLuOHz+O7+rVdO3WDR8fH+zt7PCeNIno6Og809+4cYN5c+fi1awZPsuW4enpyYwZM7h7964yzfZt2wgICGDI0KEsXrIEAwMDvCdNUtaZJt4kD032ZfWqVZw/d47xEyYwb/58oiIjmTlzZoHxaGM5aWNMfyefwqw/iendjklb45KYCo6pmJEhsddC+WPYNI3iL2lbiToBq4g8do5TtVtzx2c9VVfNpGzTD5RpKnZsgeu34wmbuZxTddvy/FoI9fb+SIlyZhq9h/Sd73abkpjke8t/5dgTItO/agAi+yUYBw4c4IMPPsDExARzc3M+/fRTbt26pUzboEEDxo4dq7L906dP0dPT48SJEwD4+flRu3ZtSpcujYWFBV27duXJkyfK9AqFgm7dulGuXDlKliyJk5MTa9euVb7+4MEDunTpgpmZGUZGRtSuXZtz584BMHXqVDw8PPjhhx+ws7PDwMAAyH0Jhq2tLTNmzKBLly4YGRlhZWXF8uXLVV4HaNu2LTo6Osq/CxIYGEidOnUwMDCgbNmytG3bVuX1hIQE+vTpQ+nSpbG2tmb16tUqr0dERNCpUydMTEwwMzOjdevWKh0owJo1a3B3d0dfX5+KFSsyZMgQtfFMmTKFihUrcu3aNY3iV2fXrl00b9ECLy8vrG1sGDJ0KPr6+hw6dCjP9Lt376ZW7dp06NABa2trevTogYODA4GBgUD6CLK/vz+dO3fG09MTOzs7Ro0eTWRkJGd++02jmN40j4L2JT4+nkOHDtGvXz88PDxwcnLi65EjCb5xg5Dg4HeunLQxpr+TT2HWn8T07sakrXFJTJrF9PTgCW5OWcLj3b/kmy6TzVedeXHnAcFj5hEXcpt7KzbxaMdB7Ib3UqaxG9GbiB9/5sH6ncQF3+L3QVN4lZBI5V7tNXoP6Tvf7TYlMcn3lv/CsfcuSNPR0drHv82/agAiu/j4eEaOHMnFixc5cuQIurq6tG3bltTUVAC6devGli1bVC7Z2Lp1K5aWlnz44YcAJCcnM2PGDIKCgvD39+fu3bv06tVLmd7b25sbN26wf/9+goODWblyJWXLlgUgLi6Ohg0b8ueffxIQEEBQUBBjxoxRvj9AeHg4O3bsYOfOnVy9elXtvnz77bdUr16dK1euMG7cOIYPH87hw4cBuHDhAgBr167l4cOHyr/zs3fvXtq2bUvLli25cuUKR44coW626V8ACxcupHbt2ly5coVBgwYxcOBAQkNDleXSrFkzSpcuzcmTJzl9+jSlSpWiefPmypHVlStXMnjwYL766it+//13AgICcHR0zBVLWloaQ4cOZcOGDZw8eZJq1aoVGL86ycnJhIeF4eHhoXxOV1cXDw8PtR1jSHAwNbKlB6hVq5Yy/aNHj1AoFHjUqKF83cjICGdnZ4JDQjSK603y0GRfwsLCSElJUcm3cuXKlCtfPt/YtLGctDGmTNpWfxLTux2TtsYlMWlef6/DpL4Hz349o/Lc08OnMK2fHp+Onh5larrz7Ei2HwVpaTz79TdM6tegINJ3pnuX25TEJN9b/gvHnhDZ/avWgMiufXvVMwdr1qyhXLly3Lhxg/fee49OnToxYsQITp06pRxw2Lx5M126dEEnY6SpT58+yu3t7e1ZunQpderUIS4ujlKlSnH//n1q1KhB7dq1AVRmH2zevJmnT59y4cIFzMzSp1Hm/AH+8uVLNmzYQLly5fLdl/fff59x48YBUKVKFU6fPs3ixYtp2rSpclsTExMsLCw0KptZs2bRuXNnpk3LmkJavXp1lTQtW7Zk0KBBAIwdO5bFixdz9OhRnJ2d2bp1K6mpqfzwww/Kslq7di0mJiYcO3YMLy8vZs6cyahRoxg+fLgyzzp16qi8R0pKCl988QVXrlzh1KlT+V6XlpSURFJSUq7n9PX1lX/HxsaSmpqa6zo0E1NTIh48yDNfhUKBSR7pFQqF8nUgzzwzXyvIm+Shyb4oFAqKFy9OqVKlVNKYmpigiIpSG482lpM2xpT9fV43n8KsP4np3Y5JW+OSmDSvv9ehX6EsSY+fqTyX9PgZemVKo2ugj55pGXSLFyfpSWSONJEYOdsXmL/0nVne1TYlMcn3lv/CsSdEdv/aGRBhYWF06dIFe3t7jI2NlYMD9+/fB6BcuXJ4eXmxadMmAO7cucOZM2fo1q2bMo9Lly7RqlUrrK2tKV26NA0bNlTJY+DAgWzZsgUPDw/GjBnDb9mmNV29epUaNWooBx/yYmNjU+DgA4Cnp2euv4P/xlSnq1ev0rhx43zTZJ+JoKOjg4WFhfLyk6CgIMLDwyldujSlSpWiVKlSmJmZkZiYyK1bt3jy5Al//fVXge/x9ddfc+7cOU6cOFHgojhz5syhTJkyKo/vv/9ewz3+Zx399VfatW2rfLxKSSnqkMRr0Mb6k5je3ZhAO+OSmMTbpo31JzG9uzEJzUn9iXfNv3YGRKtWrbCxscHX1xdLS0tSU1N57733VBZf6datG8OGDcPHx4fNmzdTtWpVqlatCqRfwtGsWTOaNWvGpk2bKFeuHPfv36dZs2bKPFq0aMG9e/fYt28fhw8fpnHjxgwePJgFCxZQsmTJAmM0MjIqnJ0vgCax5bwTh46OjvLykbi4OGrVqqUcvMmuXLly6OpqNq7VtGlTfvrpJw4ePKgy8JOX8ePHM3LkSJXnHvz5p8rfxsbG6Orq5hrdjVYoMFOzOq+pqSnReaTPHAHO/FehUKgMJkUrFNg7OOSZZ7369XF2cVH+nZyc/Np5aLIvpqampKSkKGfkZFJER2Oaz8CXtpSTtsakjfUnMb27MWlrXBLT6/edbyLp8TP0K5RVeU6/QlmSY56TmpjEy2cKUlNS0C9vniONOUmPVGdO5EX6znevTUlM8r3lbcek7fUnRE7/yhkQkZGRhIaGMmnSJBo3boyrq2ueU45at25NYmIiBw4cYPPmzSo/gkNCQoiMjGTu3Ll8+OGHuLi4qCxAmalcuXL07NmTjRs3smTJEuVijdWqVePq1atEvYUpSWfPns31t6urq/JvPT09Xr16pXF+1apV48iR/G8blp+aNWsSFhZG+fLlcXR0VHmUKVOG0qVLY2trW+B7fPbZZ2zevJm+ffuyZcuWfNPq6+tjbGys8sh++QWkl4OjkxNB2dbTSE1N5erVq7hkK6/sXFxdc62/ceXKFWV6CwsLTE1NVfJMiI8nNDQU12ydfXaGhoZYWloqH9bW1q+dhyb74uTkRPHixVXif/DgAU+fPFGbr6Z551QY5aStMWlj/UlM725M2hqXxPT6feebiD57FfP/1Vd5rmzjBijOpr93WnIyMZevU/Z/2WY66uhg/rEn0WevFJi/9J3p3qU2JTHJ95a3HZO2158QOf0rZ0CYmppibm7O6tWrqVixIvfv31euoZCdkZERbdq0wdvbm+DgYLp06aJ8zdramhIlSuDj48OAAQP4448/mDFjhsr2kydPplatWri7u5OUlMSePXuUAwNdunRh9uzZtGnThjlz5lCxYkWuXLmCpaVlrksqCnL69Gnmz59PmzZtOHz4MNu2bWPv3r3K1zN/7L///vvo6+vnun4rpylTptC4cWMcHBzo3LkzKSkp7Nu3L9ddQdTp1q0b3377La1bt2b69OlUqlSJe/fusXPnTsaMGUOlSpWYOnUqAwYMoHz58rRo0YLnz59z+vRphg4dqpJX27Zt8fPzo3v37hQvXpwOHTq8Vtnk1LZtWxYtXIiTkxNVnJ3Z7e9PUlISTZs2BWDBggWYm5vTu3dvIH0QauyYMezcsYM6dety/PhxwsLCGDpsGJA+86NNmzZs2bIFSysrKlSogJ+fH+bm5ng2aKBRTJrmMX7cOBo0aECrzz7TaF+MjIzw8vLC19eX0qVLY2hoyPcrV+Lq6qr2w0+by0kbY3qdfP7J+pOY3t2YtDUuiUmzmIoZGWLkaK3829CuEsbVXXgZFUNixEOcZ47EwKoCQb3TP0/vrd6CzaBuuMz5hoh1Oyj7cX0qdmzBhc/6K/O4s2Qt1dfMI/rSH8RcuIbtsJ4UNypJxPqd+caSSfrOd7tNSUzyveW/cOy9C9J0/pXn5bXSv3IAQldXly1btjBs2DDee+89nJ2dWbp0KY0aNcqVtlu3brRs2ZKPPvoIa+usLxXlypVj3bp1TJgwgaVLl1KzZk0WLFjAZxkHKUCJEiUYP348d+/epWTJknz44YfKM/klSpTg0KFDjBo1ipYtW5KSkoKbm5vKLTQ1NWrUKC5evMi0adMwNjZm0aJFNGvWTPn6woULGTlyJL6+vlhZWeW6HWZOjRo1Ytu2bcyYMYO5c+dibGzMRx99pHE8hoaGnDhxgrFjx9KuXTueP3+OlZUVjRs3xtjYGICePXuSmJjI4sWLGT16NGXLllU7uNChQwdSU1Pp3r07urq6tGvXTuNYcmrYsCGxMTH4bdyIIioKewcHps+YoRyUefrkCbrZbmfj5ubGmLFj2bB+PevWrcPKygpvb2+VBUU7dOxIYmIiPkuXEhcXh7u7O9NnzKBEiRIax6VJHg8fPiQmNlbjfQH4qn9/dHR1mTVzJsnJydSqVYtBgwe/k+WkjTG9Tj7/ZP1JTO92TNoal8RUcExlar2H5xE/5d9uCyYAELFhJ9e+HI9+xXKUrFxR+fqLuw+48Fl/3BaOx3ZoDxIfPOL3/pN4dvhUVvzb9lOinBlVpgxD36IcsUHBnP+0Ly9zLEypjvSd73abkpjke8t/5dgTIpNOWvb7UL7junTpQrFixdi4cWNRh/LW2NraMmLECEaMGFHUoWidW7dvF3UIQggh/qVCnFsUdQi5uITuL+oQhBAiXw72Bd/BRxtFXTtZ1CGoZVbtw6IO4a36V8w1SUlJ4caNG5w5cwZ3d/eiDkcIIYQQQgghxLtCR0d7H/8y/4oBiD/++IPatWvj7u7OgAEDijqcIufu7q68PWbOR153rhBCCCGEEEIIIQrbv2INCA8PDxISEoo6jEJR0HoOedm3b5/yFjw5VahQ4W9GJIQQQgghhBBCvL5/xQCEUGVjY1PUIQghhBBCCCGEECr+FZdgCCGEEEIIIYQQQrvJAIQQQgghhBBCCCEKnVyCIYQQQgghhBDiPytNR87L/1OkpIUQQgghhBBCCFHoZABCCCGEEEIIIYQQhU4uwRBCCCGEEEII8Z+Vhk5Rh/CfITMghBBCCCGEEEIIUehkAEIIIYQQQgghhBCFTi7BEEIIIYQQQgjxnyV3wfjnyACEeGelphUr6hByKZ0cVdQh5KKN17TF6ZkWdQi5FCOlqEPI0yst7Ka1sazSdLSvnb9M0y/qEHIproV1B6CXllTUIeTiErq/qEPIJcS5RVGHkItjyC9FHUIuJdC+9gTwCu373pKmhZOhDVLjizqEXF7paN9ncbKO9n3GCKEJ7et1hBBCCCGEEEII8a8jAxBCCCGEEEIIIYQodDIAIYQQQgghhBBCiEInAxBCCCGEEEIIIYQodNq3oooQQgghhBBCCPFP0cLFrP+tZAaEEEIIIYQQQgghCp0MQAghhBBCCCGEEKLQySUYQgghhBBCCCH+s9LkvPw/RkpaCCGEEEIIIYQQhU4GIIQQQgghhBBCCFHo5BIMIYQQQgghhBD/WWlyF4x/jMyAEEIIIYQQQgghRKGTAQghhBBCCCGEEEIUundmAKJXr160adOmqMN4bba2tixZsqSowyh0jRo1YsSIEUUdhhBCCCGEEEIILSVrQJA+uBEdHY2/v/9bz/vChQsYGRm99Xy1zc6dO9HT0yvqMABIS0tj08YNHDywn/j4OFzd3Bk0eBhWVlb5brcnMICdO7ahUERhZ2dP/4GDcXZ2AeD581g2bfTjyuVLPH36hDJlylDfswFfdO+lUf3u2nuQLf6BRClicLC1ZvhXvXGt4qg2/dHTZ1mz6WcePXmKlaUFA3p0pX7tGsrXE14ksnrDZk6du0jM8+dULF+e9p82p3WLphqWUvaYonG0tWFYATEdO32GHzNiqmRpQf8e3dTEdIHYjJjafdritWIC7au/wMBAtu/YgUKhwN7OjoEDB+Ls7Kw2/cmTJ9ng58fjx4+xsrSkd58+1K1TR/n66dOn2btvH+Hh4Tx//pxlPj44ODi8Rgml07ZyAu0sq8DAQHZs345CocDO3l6jmPw2bODx48dYWlnRp3dv6tStq3w9LS2NjX5+HDhwgPj4eNzc3Bg8ZEiB5Z5TWloaP21cx+EDe4mPj8PF7T0GDB6BpVWlfLfbF+jPrh1biVZEYWvnQL+BQ6ni7Kp8feLYr7n+e5DKNs1atGLg0K81iknb2lTAnr1s37GTqIw2NWhAf1ycq6hNf+LkKdZv3Mjjx0+wsrTky969qFuntvJ1v02bOXbiBE+fPkOveHEcHR3p3aM7Li7q20RO2tamzD6ojf2oLylT8z0MLMtzsf0gHgccyX+bj+ritmAcpdycSIx4SPiclTzYsEsljc3ArtiP/BJ9i3LEXgvh+ogZxFz4XaOYsu/b5o3rOXRgn7JNDRw8vMB2vjdwN7t2/JzRphz4auAQqmS0qZz5T5s8gcuXLjBh0jTqN3g/33wDAveo9FGDBg7It+5OnDzJBr+Nyj6qT5/eKn3UqdOn2bdvP2EZfdRyn6Vv3J9v3OiXcezF4+rmxuDBQzU69nbsyGiLdvYMGDhIZX/279/H8WNHCQ+/xYsXCWz9eTulSpXSOCZt6w9279nHzzv9iVJE42Bny5D+ffPtD46fOs26jT/x6PETrCwr0q9XD+rVqaV8ff7ipRw6clRlm9o1azB3+uQCY8n0NvuolJQU1m3YyIWLF3n46BFGRkbU8KjOl716Ym5urnFMoJ31J0Smd2YGRGF49eoVqamphfoe5cqVw9DQsFDfozC9fPlSo3RmZmaULl26kKPRzI7tPxMY4M/gIcNYuHgpBgYGTPYen+++nDh+jB98V9Gl6xd857MCO3t7JntPIDpaAUBkZCRRkZH06duP5StXM+Lr0Vy6eJHvliwsMJ5fT/7G8jV+9Py8A76L5uBgZ8PoqXNQRMfkmf6P4FBmLFhKyyYf47t4Lh/Wq83EOQu4fS9CmWb5mg2cvxzExK8Hs2HZQjp81oLvVq/l9LmLGpXRryd/Y8WaDfT6vD2+i+biYGfDN1Nn5xvT9AVL+aTJx/yweC4f1KvDpDnfcvvefWWaFWs2cP7yVSZ+PYT1yxbR4bOWfLd6jcYxZdKm+jt+/DirfX3p1rUrPj4+2NnbM8nbm+jo6DzT37hxg7nz5tHMy4tlPj54enoyY8YM7t69q0yTmJiIu7s7fXr3fq1yyUmbygm0s6yOHz+O7+rVdO3WDR8fH+zt7PCeNCnfmObNnYtXs2b4LFuWZ0zbt20jICCAIUOHsnjJEgwMDPCeNEnjvjLTru1b2BOwkwFDvmb+4uUYGBgwzXtsvvmcOn6UNb4r6dy1B4t8VmFr78A077HK+svUtPknrN24Xfno+eVXGsWkbW3q2ImTrPb9gW5du7B86RLs7eyY6D1Zbf1dvxHMnPnf0tzLixVLv6OBZ32mzZzF3bv3lGmsrCwZPGAAq5YvY+G387CoUJ7x3pOJjsm778tJG9tUMSNDYq+F8sewaRqlL2lbiToBq4g8do5TtVtzx2c9VVfNpGzTD5RpKnZsgeu34wmbuZxTddvy/FoI9fb+SIlyZhq9R6ad27eyJ2AXA4cM59vFy9A3MGCK97h89+3k8aP86Ps9nbt2Z7HP99ja2zPFe1yudg4Q4L8DHQ0Xjjt+/AS+vr580bUry3yWYm9vx8QC+6j5NPPyYrnPUjw9PZk+Y2aOPioJd3e3v92fb9++jcCA3QweMoxFizPagPfEAo694/j6+tK16xcs9VmGnb093t4TVfYnKSmJmrVq0+nzz187Jm3rD46eOMX3P6yle5fP+f67hdjb2TJu8nQU6vqD4BBmzV9E86aN+X7pQt6vX48ps+ZyJ1t/AFCnVg1+9lujfEwcM1LjMnrbfVRSUhLht27RtcvnLF+6hMkTx/PgwZ9MmT5T45gyaVv9CZGd1g1AbN++napVq1KyZEnMzc1p0qQJ8fHxytcXLFhAxYoVMTc3Z/DgwSQnJytfUygU9OjRA1NTUwwNDWnRogVhYWHK19etW4eJiQkBAQG4ubmhr69Pnz59WL9+Pbt370ZHRwcdHR2OHTsGQEREBJ06dcLExAQzMzNat26t8sGTeVlIfjHlvARDR0eHH374gbZt22JoaIiTkxMBAQEqZRAQEICTkxMGBgZ8/PHHrF+/Hh0dHbUdWnb37t2jVatWmJqaYmRkhLu7O/v27VO+/scff9CiRQtKlSpFhQoV6N69O8+ePVO+3qhRI4YMGcKIESMoW7YszZo1o2vXrnye48MrOTmZsmXLsmHDBuV22S/BSEpKYuzYsVSuXBl9fX0cHR358ccfNY7jTaWlpbHbfxefd+5Kfc8G2NnZM3LUGKIiIzlz5rTa7fx37aBZ8xY09WqGtbUNg4cMR19fn8OHDgJga2vHhEmTqVfPk4oVLanuUYMePXtz/tw5Xr16lW9MP+/ey6de/6Nlk0bYWldi1MC+GOiXYN8vx/JMvz1wP3VrVqdLu1bYVrbiy26fU8Xejl17DyrTXA+5SbP/fUSNqu5UrFCez5o1wcHOhuCwWxqV07bde/nEqzEtmnyMrXUlRipjOppn+h2B+6lb04PO7T7DpnIlvuz2OU45YvojJJTm/2uojKlVsyY42tkQHBauUUygffW3a9cuWjRvjpeXFzbW1gwdMgR9fX0OHTqUZ/rdu3dTu1YtOnTogLW1NT169MDBwYHAwEBlmsaNG9Ota1dq1KiRZx6a0LZyAu0sq127dtG8RQu8vLywtrFhyNChBcZUq3ZttTGlpaXh7+9P586d8fT0xM7OjlGjRxMZGcmZ337TOK60tDQC/XfQqfMX1PN8H1s7B4aPGkdU5DPOnTmldrvdu7bh1bwljb1aUNnaloFDvkZfX58jh/arpNPX18fUzEz5MDQs+MyUNrapnbv8ad68Gc2aNsHG2pphQwahb6DPwUOH844lIIDatWrSsX07rK0r07P7Fzg6OLB7zx5lmv81akTNGh5UrGiBrY0NX/XrS0JCAnfu3C2wjEA729TTgye4OWUJj3f/olF6m6868+LOA4LHzCMu5Db3Vmzi0Y6D2A3vpUxjN6I3ET/+zIP1O4kLvsXvg6bwKiGRyr3aa/QemfsW4L+TTp27Ud/zfezs7Pl61FiiIiM5m0+b2r1rB17NW9LEqznW1jYMGjICfX19fjl0QCXd7Vvh+O/czrARozWKZ+euXTRv3hwvr6bZ+igDDqqpO//dAdSuVYuOHdpjbW1Nzx7dcXRwICAwqz01afy/jD7KQ6MY8pJ17HXJaAP2jBr1Tcaxp74N7Nq1k+bNm9PUywtraxuGDBmKgb4+hw5lfS63adOWTp0+x8Ul9+wRzWLSnv5gh38ALZs1pXnTxthYV2bE4AHo6+tz4HDes312BuyhTq0afN6+LTaVK9O7e1ccHezZvWefSjo9PT3MTE2Vj9IazhCBt99HGRkZMXfWDBp++CGVK1XC1cWFwQP7ExYezpMnTzSOSxvr712QpqOrtY9/G63ao4cPH9KlSxf69OlDcHAwx44do127dqSlpQFw9OhRbt26xdGjR1m/fj3r1q1j3bp1yu179erFxYsXCQgI4MyZM6SlpdGyZUuVAYGEhATmzZvHDz/8wPXr11m6dCmdOnWiefPmPHz4kIcPH9KgQQOSk5Np1qwZpUuX5uTJk5w+fZpSpUrRvHlzldHDgmLKy7Rp0+jUqRPXrl2jZcuWdOvWjaioKADu3LlDhw4daNOmDUFBQfTv35+JEydqXIaDBw8mKSmJEydO8PvvvzNv3jzldLvo6Gj+97//UaNGDS5evMiBAwd4/PgxnTp1Uslj/fr1lChRgtOnT/P999/TrVs3AgMDiYuLU6Y5ePAgCQkJtG3bNs84evTowU8//cTSpUsJDg5m1apVrx3Hm3j86BEKRRQeHjWVzxkZGeHs7EJIcHCe2yQnJxMeHoaHR9aPHF1dXTw8ahASkvc2APHx8RgaGlKsWDG1aZKTU7h56w61qldVybtW9apcD72Z5zbXQ8NU0gPUqVFdJb27SxVOn7/E08go0tLSuHztOhF/PqROjWpqY8keU+it23nGdCM0LM9trofepFb191Seq1ujOjeyxfSeizOnz19UxnTl2h8ax5RJm+ovOTmZsPBwPDw8cuTrQXBISJ7bBIeE4JHjx3KtWrXUpn9T2lROmXlrW1klJycTHhaWZ0zqyigkOJga2dJnxpSZ/tGjRygUCpW408vd+bXifvzoIQpFFNU8sqYCGxmVooqzK6HBN9Tuz63wmyrb6OrqUt2jFqEhqtucOHqE7p3bMGxgH/zW+pKUmKhBTNrZpmp6VFfJu4aHBzdCQvPcJjgkJHf91ayhtm6Sk5PZt/8ARkZG2NvZqo0le3ptbVOvw6S+B89+PaPy3NPDpzCtnx6njp4eZWq68+xIth+/aWk8+/U3TOprPhiY2c6rq7Spgtt5ePhNlXaY3s5rEpKtnSclJrJw/mz6DxqKqVnBszIy21ONHHVXo4A+KufAQq1aNd96vSjbgEfONvD2jz1NaWN/cDP8Vq7+oKZHNbX9wY2QUJX0AHVqenAjRPW7V9Dvf9ChW0969R/MkuXfExMbqzaOnDEVdh8FEB+fgI6ODkavMTCibfUnRE5atQbEw4cPSUlJoV27dtjY2ABQtWrWjyRTU1OWLVtGsWLFcHFx4ZNPPuHIkSP069ePsLAwAgICOH36NA0aNABg06ZNVK5cGX9/fzp27AikH2ArVqygevWsDqNkyZIkJSVhYWGhfG7jxo2kpqbyww8/KKf3rV27FhMTE44dO4aXl1eBManTq1cvunTpAsDs2bNZunQp58+fp3nz5qxatQpnZ2e+/fZbAJydnfnjjz+YNWuWRmV4//592rdvryw3e3t75WvLli2jRo0azJ49W/ncmjVrqFy5Mjdv3qRKlfRr1pycnJg/f74yjYODA0ZGRuzatYvu3bsDsHnzZj777LM8L7u4efMmP//8M4cPH6ZJkyZvHEd2SUlJJCUlqTz3MimJEvr6Ks8pFOkDOSamJirPm5iYEq3IPX0TIDY2ltTUVExMTXNt8yAiIs9tYmJi2PLTJpq3aJnn68p0sbG8Sk3F1KSMyvOmJmW4/+DPPLeJio7OM32UImuK8PCverNguS8d+gyiWLFi6OroMHrwV1R3d82ZXZ4xpaamYpZnTH+pjcnMxCTfmIZ91ZuFy1fTsc/AHDG5FRhTJm2qv8x8TXPka2piojZfhUKBaa5yMkGhJvY3pU3llD1vbSordTGZmJoS8eCB2phylY+pqTKmzH/zyvN14o5W1p9qPmVMTJV1m9Pz2Jg866+MiSkPIrIuhfqoUWPKl6+AqZk59+7eZsOa1fz5ZwTjJk3PNyZtbVMmJrnbVESEuvqLVtOmolWeO3v+PHPmfUtSUhJmZqbMmTmdMmVU+8P8YtLGNvU69CuUJemx6ozDpMfP0CtTGl0DffRMy6BbvDhJTyJzpInEyNkeTWXGn7t9mKht57Fq2rmJiSl/ZmtTP/iuxMXVnfqe+a/5kJVvZls1yRVLRD59lIlJ7vRvvz/PbAOav9eb7M/rxaRd/UFM7PP0Yy/X9xYTItR8l8qrPzAxMSEq26U8dWrW4IMG9bGoUIGHDx/x44aNTJgyg6UL5hb4g7ow+6hML1++5Me162jU8COMXuNybm2rPyFy0qoBiOrVq9O4cWOqVq1Ks2bN8PLyokOHDsoPZnd3d5UOoWLFivz+e/qCSMHBwRQvXpx69eopXzc3N08/i5BttK9EiRJUq1bwGdmgoCDCw8Nz/cBOTEzk1q2sae75xaRO9vc3MjLC2NhYObUqNDSUOtkWOAKom22xqoIMGzaMgQMHcujQIZo0aUL79u2V7xcUFMTRo0fzXIDo1q1byh/+tWrVUnmtePHidOrUiU2bNtG9e3fi4+PZvXs3W7ZsyTOGq1evUqxYMRo2bJjn65rGkd2cOXOYNk31+tYhQ4dTtVo1lvt8p3xuyrTXv07udSUkxDNtyiSsra3p2q17ob9fXnbuOcCN0DBmT/wGi/JlCboezJJVayhrZkptj6oFZ1CoMY2hQraYzM1Mqe2R9zF39OiR/2T9vS4pp3fb8aO/sNJnkfLvSdPmFNp7NWvxqfL/tnb2mJqaMXnCaB4+/JOKFbMWH/svtymPatVY4fMdsbGx7D9wiFlz57F00cJcPzbF6zl29AgrfBYr/548TbMTJ6/r3NnfuBZ0lSU+3xdK/oXt6NFfWeazVPn31Gn5Dw7+E/6r/cHHDT9U/t/e1gY7Oxt69B1I0O/Xqanme8s/JSUlhVlz5gFpDB08KN+0/9X6e9vS0Gw9GfH3adUARLFixTh8+DC//fYbhw4dwsfHh4kTJ3Lu3DmAXHdZ0NHRee1FJEuWLKnRgkVxcXHUqlWLTZs25XqtXLlyyv+/SUxvYz/U6du3L82aNWPv3r0cOnSIOXPmsHDhQoYOHUpcXBytWrVi3rx5ubarWLGi8v95rWTbrVs3GjZsyJMnTzh8+DAlS5akefPmecZQsmTJfGPUNI7sxo8fz8iRqgsDRTx4RMqrV8rVeQHl5TbRimjMzLJWDI6OVmBnn/fK1MbGxujq6uYaFY6OVuSa2pmQkMBk74mUNDRkovdUihfP/xAqY2xMMV3dXIs7KqJjMMsxMp3JzMRETfr0kf+kpJf4btzCzPGj8KydPr3OwdaG8Nv32Oq/p8ABiDIZ+xv1mjFF5ViDJGdMP2z8iRnjR+eI6W5GTHl/kBmOQVMAAQAASURBVNer56m19ZeZb84zUIroaLVTfk1NTXMtiKWIjs51dvN1aXM5Zc9bG8qqoJiiFQrM1LyHqWnus0PRCoUypsx/FQoFZtn2K1qhwD6fle/r1mugcqeK5OSXWbFkq7+YaAV29nnfiaa0cZk86y8mj/rLropL+vs++usvlQGId6VN5Vx4ML82YmpqoqZNmag8Z2BggJWlJVaWlri6uNC731ccOHSYzp06ahSTNrSpvyPp8TP0K5RVeU6/QlmSY56TmpjEy2cKUlNS0C9vniONOUmP1K/VVLeep8qdKlKUbUqRo01FY6+2TeXdzqOjFZiYpZfVtaCrPHr4F106tlZJM3f2NNzc32P2vEXklNVWo3PkG42pWT51F51H+r/dn9fPceyl9weKXMdetMrs0ezeZH/yj0m7+4MyxqXTj71c31tyH9+Z8uoPoqOjMTNRXz6WFhaUMTbmr4cPCxyAKMw+KiUlhVlz5/H46RPmz55V4OwHba8/IXLSqjUgIP3H+Pvvv8+0adO4cuUKJUqUYNeuXQVu5+rqSkpKinKwAtJXaw0NDcXNLf8p4CVKlMi1eErNmjUJCwujfPnyODo6qjw0mar5ppydnbl4UfWuARcuXHitPCpXrsyAAQPYuXMno0aNwtfXF0jfp+vXr2Nra5trnwq6fU6DBg2oXLkyW7duZdOmTXTs2FHtbTerVq1Kamoqx48fz/P1N4lDX18fY2NjlUcJfX0MDQ2xtLRSPqytbTA1NeNq0BXltgkJ8YSGhuDimvflCXp6ejg6OhEUdFX5XGpqKkFXr+LikrVNQkI83pPGU7x4cbwnT6NEiRL5lll63sWp4mDHpWt/qOR9+dofuKu5TZO7s5NKeoCLV68p06e8SiEl5VWugTTdYrqkphU8kKWnVxxnB3suX8uaqZOamsqla3/g5uykJqYqXM4V0++45YhJN0dMxYrpKtdwyYs215+enh5Ojo5cDcq6pWFqaipXr17FVc2CXq4uLly9elXluStXrqhNryltLqfMvLWlrLLH5OjkRFC298iMSV0Zubi65hlTZnoLCwtMTU1V8kyIjyc0NDTfuEsaGlLR0kr5qGxti6mpGdeCLmflkxDPzdBgnF3z/rzS09PDwbGKyjapqalcu3oZZxf1n3F3Mmbs5fwC+a60qStXr6nkffVqEG5qbpnp6uKi0gYBLl9R3wYzpaWmqawVlV9M2tKm/o7os1cx/199lefKNm6A4mx6DGnJycRcvk7Z/3lmJdDRwfxjT6LPXkGdnG2qckabCsrRpgpq546OVQjK1c6v4JLRzjt07MzS5av5btkq5QPgy34DGfb1N2rzTe+jrqrkW3AflbM9va3+3FL5SD/2TFWOI02Pvbz2J/ux93oxaXd/UMXRgctBqv3BlaDf1fYHbi7OKv0HwKUrQbi5qL9F5tNnz4h9/hwzDQZxCquPyhx8+POvv5g7aybGxsYFxqLt9SdETlo1AHHu3Dlmz57NxYsXuX//Pjt37uTp06e4qjlYsnNycqJ169b069ePU6dOERQUxBdffIGVlRWtW7fOd1tbW1uuXbtGaGgoz549Izk5mW7dulG2bFlat27NyZMnuXPnDseOHWPYsGE8UHOt59vQv39/QkJCGDt2rHIthcxFLTWZuTFixAgOHjzInTt3uHz5MkePHlWW3+DBg4mKiqJLly5cuHCBW7ducfDgQXr37q3R6rVdu3bl+++/5/Dhw3Tr1k1tOltbW3r27EmfPn3w9/dXlt3PP//8VuLIj46ODq3btGXrls2cO3uGu3fusGjBfMzMzfHMdq3ohPFjCAzcrfy7Tdv2HDywjyO/HCLi/n1WLF9KYlIiTZo2AzI63InjSUpMZPiIkbxISEARFYUiKqrAmDu1/oS9h37lwK/HuRvxJ4u+/5EXiUm0aJJ+icqsxctZveEnZfoOrVpw/nIQW/33cO/Bn6z9aRuht27T9pP0WIwMDfF4z5Xv123iyu/Xefj4CfuPHOPg0RN8WL9OnjHk1LH1J+zJiOlexAMWf/8DiYlJtGjSCIDZi5exesNmZfr2ypgCs8V0SyWm6u+5sXLdxjeOCbSv/tq2bcuBAwc4/Msv3L9/n2XLl5OUlETTpk2B9LvyrF27Vpm+devWXLp0iR07dxIREcHGjRsJCwujVatWyjTPnz/n1q1b3Lufft3+gwcPuHXrlnIh2nexnLS1rDJj+uXwYe7fv8/yZcs0imnnjh15xqSjo0ObNm3YsmULZ8+e5c6dOyxYuBBzc3M8M9Ye0oSOjg6t2rRn25aNnD97mrt3brNkwVzMzMtSzzPrVoje40exNzBrAL51244cPrCXX385SMT9e3y/fAmJSYk0bpo+G+3hwz/ZutmP8LCbPH78iPNnT7Nk4Rzc36uGrV3+Z9O1sU21a9uG/QcPcviXI9y/H4HP8hUkJibi1TR9baH5CxexZt36rFg++4yLly6zfecu7kdE4LdpM2Hh4bT+NP2ylMTERNas30BwSAiPnzwhLCychUu+41lkJB9+oNlaAtrYpooZGWJc3QXj6uk/YgztKmFc3QWDyukzCp1njqT62qwZh/dWb8HQrjIuc77ByNkemwFdqdixBXe+W6dMc2fJWip/2Qmr7m0o5WLPe8unUtyoJBHrd2oUU+a+fdamHT9v2cS5s79x985tFi+Yh5m5ucraDZPGf8OeQP+sMmvbnkPKNnWPlcu/U2nnpmZm2NjaqTwAypUrj4VF3rMoAdq1bcv+AweVfZTP8uUkJiXilVF33y5YyJq1WWXQpvVnXMzWR/lt3ERYWDiftcq6zCmzj7qv7KP+fOP+fMuWnzibcewtXLAg49jLagMTxo8jMDDrrmlt27bj4IH9/PJLRltc7kNiUiJNm3op00RFRXHr1i0e/pW+vtPdu3e5desWz58/1ygmbeoP2rf5jH0HD3PoyK/ci4jguxWrSExMpHmTxgDMXfgdP6zzU6Zv99mnXLh8hW07d3M/4gHrN23hZvgtWn+avl7BixcvWLVmHTdCQnn0+AmXr15j8ow5WFa0oHZNzRZbfdt9VEpKCjNmz+VmWDhjR48m9VUqUVEKoqIUGg2SZtLG+nsXFPWdLv5Ld8HQqjkzxsbGnDhxgiVLlhAbG4uNjQ0LFy6kRYsWbN26tcDt165dy/Dhw/n00095+fIlH330Efv27VN7pj5Tv379OHbsGLVr1yYuLo6jR4/SqFEjTpw4wdixY2nXrh3Pnz/HysqKxo0bazQa+abs7OzYvn07o0aN4rvvvsPT05OJEycycOBA9HMsuJiXV69eMXjwYB48eICxsTHNmzdn8eL0azItLS05ffo0Y8eOxcvLi6SkJGxsbGjevDm6ugU37m7dujFr1ixsbGx4//38v6ytXLmSCRMmMGjQICIjI7G2tmbChAlvJY6CtO/QicTERHx8lhAfF4eb+3tMnz5bZZT20cOHxGa77/tHDRsRExvDRr8NKBQK7O3tmT59lnIaXXh4OKGh6asU9/uyl8r7/bh2AxUqWKDO/z5sQHRsLGs2byNKEY2jnQ3fThmnXNTxybNn6OpmDS695+qM96ih/LhxK75+W6hkacGs8aOxt6msTDN59HBWb/iJmYuWERsXh0W5cvT9ojOtmzfVqIwyY1q7+eeMmGyZP2W8MqbHzyLRyVYX2WP6wW8LVpYWzBz/DfY21iox+W7YzKxFPsTGxVEhI6bPNIwpkzbVX8OGDYmJjWWjnx9RCgUO9vbMmD5dme+Tp09VysnNzY2xY8awfsMG1q1bh5WVFd7e3tja2irTnD17lkWLs66TnptxKVK3rl354osv3sly0tayatiwIbExMfht3IgiKgp7Bwemz5ihjOnpkycqs3bc3NwYM3YsGzLuaJRXTB06dkwv96VLiYuLw93dnekzZrz2WaC2HTqTmJjICp9FxMfF4epelcnT5+aov79U6u+Dhh8TExvNT35rUSjSp9JOmT4PE9P02Q3Fi+tx7eol9uzeQWLiC8qWK4/n+x/RqYtm7Urb2lSjjz4kJiaGDRs3KfOeNX1aVv09fapSf+5uroz7ZjTr/Taybv0GLK0smTJpIra26Yta6+rq8iDiATOOHCE2JpbSxsZUcXJi4fy52GYsfF0QbWxTZWq9h+eRrB9ebgvSP2sjNuzk2pfj0a9YjpKVs36Yv7j7gAuf9cdt4Xhsh/Yg8cEjfu8/iWeHs24B+3DbfkqUM6PKlGHoW5QjNiiY85/25WWOhSkL0q7D5yQmJrLcZ7GyTU0toJ1/2PBjYmJj2Oy3LqPeHZg6fc7fvvShYcOPiImNwc9vo7I9zczVR6nW3dgx37B+gx/r1q3H0sqKyd6TVOruzNmzLFq8RPn3nGx9VPcv1J+oyalDh4w24LM0o5zcmTF9pko5PcxRTh81bJhx7PllO/ZmqpTT/n172bw561LisWPSb1k64uuRKgMVedG2/uDjjz4gJiaWdRu3oFAocLC3Y870ycrLF548faryXcrd1YUJ33zNWr/NrNmwESvLikybOA67bP3B7Tv3OHzkKHHxCZibmVKrhge9v+hKiQJ+N2R6233Us8hIzmbM5B40dJjKe82fM5vq1TRf40vb6k+I7HTS8psfLbTCrFmz+P7779/Kysb/JmG37hV1CLmUTtb8rMc/RRsX1YnTezvX+b9NxUgp6hDy9Eq7xokB7SyrNA1miP3TXqYVPGj8TyuuhXUHoJeWVHCif9grXe079kKcWxR1CLk4hvxS1CHkUgLta08Ar9C+WxWmaddkaAAMUuOLOoRcXuloX3+QrKN9nzEATg6aDehqm79CrxWcqIhYOhftoqhvm/YdTYIVK1ZQp04dzM3NOX36NN9++y1Dhgwp6rCEEEIIIYQQQog3pn3DnoKwsDBat26Nm5sbM2bMYNSoUUydOhWAFi1aUKpUqTwfs2fPLtrAhRBCCCGEEEIINWQGhBZavHixct2GnH744QdevHiR52tm+dyKTQghhBBCCCGEKEoyAPGOsbKyKjiREEIIIYQQQgiNaONaUv9WcgmGEEIIIYQQQgghCp0MQAghhBBCCCGEEKLQySUYQgghhBBCCCH+s7TxtvX/VjIDQgghhBBCCCGEEIVOBiCEEEIIIYQQQghR6OQSDCGEEEIIIYQQ/1lpOnJe/p8iJS2EEEIIIYQQQohCJwMQQgghhBBCCCGEKHQyACGEEEIIIYQQQohCJ2tAiHeWSeKjog4hl0gDq6IOIZfDIdoXU1OXP4s6hFx0dV4VdQh5SkrVL+oQ8qB9MRUnpahDyCU1TQvH+LX0LmMpOnpFHUIuOqQVdQi5OIb8UtQh5BLu0qSoQ8jFJXR/UYeQp9S0YkUdQi4GqfFFHUIut1/aFnUIuZiWiCvqEHKxib1W1CGoYVPUAQgtp4XfjoQQQgghhBBCCPFvIzMghBBCCCGEEEL8Z6Vp6xTBfyGZASGEEEIIIYQQQohCJwMQQgghhBBCCCGEKHRyCYYQQgghhBBCiP+sNB05L/9PkZIWQgghhBBCCCFEoZMBCCGEEEIIIYQQQhQ6uQRDCCGEEEIIIcR/ltwF458jMyCEEEIIIYQQQghR6GQAQgghhBBCCCGEEIVOBiCEEEIIIYQQQghR6GQAQgghhBBCCCGEEIXuPzcA0ahRI0aMGPGPv++xY8fQ0dEhOjr6H3/v7GxtbVmyZEm+aXR0dPD39/9H4hFCCCGEEEII8d8gd8H4hzRo0ICHDx9SpkyZog7lX2/H/l/4yX8fUdExONhW5uu+3XFzcsgz7e37D/hxy05Cb93l0dNnDOvdlU6tmqukuXo9hM279xF66y6Rimhmjx3OR/VqvVZMaWlpbN64jsMH9hEfH4eL23sMHDwcS6tK+W63N9Af/x0/o1BEYWvnwFcDh1LF2SXP/KdPHs/lSxcYP2ka9Rt8oFFM5w/4cP3sNpJexFLRriaNOkzBpJytRvt06chqzuxdRPUPe/Bh2wkAxEY9YMPMJnmmb95jCY4ezfN8LWdc2lZWgYGB7Ni+HYVCgZ29PQMHDsTZ2Vlt+pMnT+K3YQOPHz/G0sqKPr17U6duXZUYNvr5ceDAAeLj43Fzc2PwkCFYWVkVGEv2PLZsXMMvB/eQEB+Hs2tVvho8ssBy2r9nF7t3bCE6o5y+HDAcJ2dXAJ48fsjAPp3z3G7UuKk0+PDjdzImbWtPmdtt2biWwxll5eL6nsZl5a8sK0f6DhimLKtMocHX2bThB8JCg9HV1cXO3hHvGd+ir69fYEybNm7g4IH9xMfH4ermzqDBwwpsl3sCA9i5YxsKRRR2dvb0HzgY54yyev48lk0b/bhy+RJPnz6hTJky1PdswBfde2FkZKRROW3c6JcRUzyubm4MHjxUo5h27Mg4Zu3sGTBwkMoxu3//Po4fO0p4+C1evEhg68/bKVWqVIHxKGN6g+O3oH7k5cuX+Pr6cuL4cZKTk6lZqxaDBw/G1NRUo5g2b1zPoYx27urmrmE7382ujHZuZ+fAVwOHqG3n0yZP4PKlC0yYNI36Dd7PN1+zD2pjP+pLytR8DwPL8lxsP4jHAUfy3+ajurgtGEcpNycSIx4SPmclDzbsUkljM7Ar9iO/RN+iHLHXQrg+YgYxF37PN9+89qUw6m//vn0cO3aM8PBwXrx4wc/btr1Wm9q0cT2Hchx7mtRf1rHnQP+Bg1Xqb5nPEoKuXCYqKhIDg5K4urnRs3dfKle2LjCm3Xv2sW3nLqIU0TjY2TK4fz9cnKuoTX/81GnWb9zMo8dPsLKsSN9ePahXp7by9Q2bfuLYyVM8ffqM4sWL4+ToQO8eX+CaT545paWlEbBlJScP7+JFwnMcXKrT7asJVLC0UbvN/h0/cvnsrzz68y4lSuhj71Kd9t2HY2Flq0yT/DKJbesWceHUQVJSXuLm4Um3ryZgbGKucVxbN/3IkYOB6Z8zrlXpN2gUFa0q57vdgT07Cdj5E9GKKGzsHOjTfwROzm7K1x89/JMNPy4n5MY1UpKT8ahVjz79R2BiapZvvtsOHWdj4C9ExsTiZG3F6F6dcHe0zTPtrYi/WL19LyG37/PwWRRfd29Pl5b/U0nzKjUV3+172X/qAlHRsZQ1LcOnDevTp21zdHT+PXeOSNP5z52XLzJS0v+QEiVKYGFh8a84UJOTk4s6BLWOnDrLsrWb6d2pDT8umI6jrTUjp3+LIjo2z/RJSS+xrFCOAd07YW6S9+DQi6Sk9Hz69XjjuHZu38LegF0MHDKCbxcvw8DAgKne43j58qXabU4eP8oa3+/5vGsPFvl8j529A1O9xxIdrciVNsB/x2u3rcu//kDQST8adZxKxxE/o1eiJAGr+pKSnFTgto/v/84fZ7ZiXlH1R3gpk4r0nnpS5VG32VD09A2xdv1Qo7i0rayOHz+O7+rVdO3WDR8fH+zt7PCeNEntbKYbN24wb+5cvJo1w2fZMjw9PZkxYwZ3795Vptm+bRsBAQEMGTqUxUuWYGBggPekSfnuY07+239iX+BO+g8exZxF32NgYMAM79G8fKm+/k6f+JV1vsvp1LUn3y71xcbOgRneo4nJKCfzsuX5wW+nyuPzbr0xKFmSGrXrvZMxaVt7yrRr+0/sDdzBgMEjmbtoJfoGJZnh/U2+ZXXqxK+s9V1Bp669WLDUF1s7B6Z7f6MSV2jwdWZMHoNHjdrMW7yS+Uu+p0WrtujqFhzjju0/Exjgz+Ahw1i4eCkGBgZM9h6fb1mdOH6MH3xX0aXrF3znswI7e3sme09QxhQZGUlUZCR9+vZj+crVjPh6NJcuXuS7JQs1Kqft27cRGLCbwUOGsWhxxrHiPbGAmI7j6+tL165fsNRnGXb29nh7T1Q5ZpOSkqhZqzadPv9cozhUYnqD41eTfmT1qlWcP3eO8RMmMG/+fKIiI5k5c6ZGMe3cvpU9AbsYOGQ43y5ehr6BAVM0aOc/+n5P567dWezzPbb29kzxHvdW2nkxI0Nir4Xyx7BpGqUvaVuJOgGriDx2jlO1W3PHZz1VV82kbNOsAb2KHVvg+u14wmYu51Tdtjy/FkK9vT9Solz+P8ZyKqz6S0pKolbt2nzeOe8B0/zs2L6VPQH+DBoynAWLfTQ69k5mO/aW+KzMOPbGq9Sfo6MTw78ezYpVPzJt5hzS0tKYPGkcr169yjeeYydOseqHNXzRpTMrv1uEvZ0t4ydPQ6Hmc+96cAiz5y+kedMmrFy6iPfr12PqrLncuXtPmaaSlSVDBnzF6uXfsXj+HCpUKM8476lEx8RoXE4Hd63j170/8cWACYyfuwF9/ZJ8N2Mwyfn0mzevX+bjFp8zfu4GRkxZyauUFJZMG0hS4gtlmp/XLiDo4gn6fzOf0TN+ICbqKSvnjdI4rt07NrM/cAdfDR7NnIWr0DcoyczJowr47DvC+h+W0bFLL+Z99wM2do7MmjxK+dmXmPiCmd4j0dHRYcrs75jx7QpSUpKZO30cqampavM9fOYSS/x20rd9SzbMHoeTTSWGzV1GVMzzPNMnvUzGqrw5g7u0xtzEOM80GwIOsePwSb7p1YmtC70Z0rU1foGH+fngMY3LSIjs/pMDEKmpqYwZMwYzMzMsLCyYOnWq8rVFixZRtWpVjIyMqFy5MoMGDSIuLk75+r1792jVqhWmpqYYGRnh7u7Ovn37CnzPnJdgrFu3DhMTE/z9/XFycsLAwIBmzZoRERGh0T7cunWL1q1bU6FCBUqVKkWdOnX45ZdfVNI8efKEVq1aUbJkSezs7Ni0aVOufMLCwvjoo48wMDDAzc2Nw4cPq7x+9+5ddHR02Lp1Kw0bNsTAwECZzw8//ICrqysGBga4uLiwYsUK5XYvX75kyJAhVKxYEQMDA2xsbJgzZw6QPlI8depUrK2t0dfXx9LSkmHDhmm03wXZEniAVk0b8Unjj7CrbMU3/XthoK/Pnl+P55ne1cmewT270OSD+ujp6eWZxrNmdb7q2oGG9Wvn+XpB0tLSCPTfScfOX1DP831s7RwYMWosUZHPOHvmlNrtdu/ajlfzljTxao61tS0Dh4xAX1+fXw4dUEl3+1Y4u3duY+iIb14rpqATG6jddAD27zWmrKUzTbrOIz72Cbf/+CXfbV8mxXNo02j+12kG+oaqH1a6usUwMi6n8rj9xy84Vm9BCX3NznZqW1nt2rWL5i1a4OXlhbWNDUOGDkVfX59Dhw7lHcvu3dSqXZsOHTpgbW1Njx49cHBwIDAwULmP/v7+dO7cGU9PT+zs7Bg1ejSRkZGc+e03jWJKS0tjz+5tdPi8O3U9P8DWzoGhoyagiIrkfD7lFLjrZ5o0/5T/NW1JZWtb+g8Zhb6BAUcOpfdhxYoVw9TMXOVx/sxJGnzwMSVLGr6TMWlbe8qMa8/u7SplNWzUeKKinhVQVtto2vwTGjdtkVFWI9E3MODXQ1mfQWt8l9Hys3a069QNaxs7rCpZ8/6HH6OnV6LAmHb77+Lzzl2p79kAOzt7Ro4aQ1RkJGfOnFa7nf+uHTRr3oKmXs2wtrZh8JDh6Ovrc/jQQQBsbe2YMGky9ep5UrGiJdU9atCjZ2/OnztX4I+grJi6ZBwr9owa9U1GTOqPlV27dtK8eXOaenlhbW3DkCFDMdDX51BGTABt2rSlU6fPcXHJfba/oJje5PgtqB+Jj4/n0KFD9OvXDw8PD5ycnPh65EiCb9wgJDi4wJgC/HfSqXM36nu+j52dPV+PGktUZCRn86m73bt2ZGvnNgzKp53779zOsBGjNS6npwdPcHPKEh7vzv/zJJPNV515cecBwWPmERdym3srNvFox0HshvdSprEb0ZuIH3/mwfqdxAXf4vdBU3iVkEjlXu01jquw6g+gTdu2dOrU6Y3aVID/roz6a6Bx/WUee1n1p3rsATRv8QnvVa1GhQoWODo68UWP3jx7+pQnTx7nG9MO/920aOZF86aNsbGuzPDBA9HX1+fg4bxnsewKCKROrZp0at8Wm8qV6dW9G44O9uzek9U3/a9RQ2p6VKeihQW2NtYM6NuHhIQEbt+5q3E5/bJnM5906IdH3Y+pZFuF3sNmEB31lCvnj6rdbvjk5TT432dYWjtQ2c6Z3kOnEfXsEfdu3QAgIf45p47406nXSFyq1sXGwY2eQ6ZxKzSI26HXNIpr7+6faf95D+rU/xAbO0eGjJyIIiqSC2dOqt1uj/9WGjdrxcdNP6GytR1fDR5NCX0Dfj28F4DQG7/z5MkjBn89ARtbB2xsHRj89URuh4fwx7XLavPdvPcIbf7XgFaNPLGvVJFxX3bGoEQJAo+dyTO9m4MNw7q1w6tBbUoUz3ti/LWbd/iodjU+qPkeluXMaVyvJvWquXI9/F6e6YUoyH9yAGL9+vUYGRlx7tw55s+fz/Tp05U/vHV1dVm6dCnXr19n/fr1/Prrr4wZM0a57eDBg0lKSuLEiRP8/vvvzJs3T+MpdjklJCQwa9YsNmzYwOnTp4mOjqazhiPncXFxtGzZkiNHjnDlyhWaN29Oq1atuH//vjJNr169iIiI4OjRo2zfvp0VK1bw5MkT5eupqam0a9eOEiVKcO7cOb7//nvGjh2b5/uNGzeO4cOHExwcTLNmzdi0aROTJ09m1qxZBAcHM3v2bLy9vVm/fj0AS5cuJSAggJ9//pnQ0FA2bdqEra0tADt27GDx4sWsWrWKsLAw/P39qVq16huVYXbJySncvHWX2tXclc/p6upSu5ob10PD/3b+b+rxo4coFFFU96ipfM7IqBRVnF0JDb6R5zbJycncCr+pso2uri7VPWoSGpK1TVJiIgvnz6L/oGGYmml+Fig26gEJz59SuUoD5XP6JUtTwboaj+5ezXfb4zumY+vaSGVbdZ5E/MGzP4Nxq6fZF0RtK6vk5GTCw8Lw8PBQydvDw0Ptj4KQ4GBqZEsPUKtWLWX6R48eoVAo8KhRI9s+GuHs7ExwSIhGcT1+9JBoRRTVPLIuBTIyKoWTsyuhIdfV7sut8Jsq2+jq6lLNoxY31WxzKyyUO7fDaez1yTsbkza1p+xxRSuiqJ6rrNxU3iN3XKF5llXmNtHRCsJCgylTxpTxowbTu1tbJo0dTvD1gr9EP370CIUiCg+VsjLC2dlFbVtPTk4mPDwMD4+stpx+fNQgJET9j+b4+HgMDQ0pVqxYvjEpjxWPnMfK249JU29y/GrSj4SFhZGSkqKSb+XKlSlXvnyB/cKbtvPw8Jsq9Z3ZzkNytfPZ9B809LXb+eswqe/Bs19VfyA9PXwK0/oeAOjo6VGmpjvPjmQbJEhL49mvv2FSvwaaKqz6+zuyjj3VmKo4uxBSQP3l7Kc8cvRT2SUmvuCXwwepYGFB2bLl1MaTnJzMzfBb1PSoppJ3TY/q3AgJzXObGyGhKukBatesQbCa9MnJyew7cAgjI0Mc7OzUxpLds8d/Ehv9DNfqWTPfDI1KY+f0nkYDBZleJKSfVDQqlT7r9f7tYF6lpOBavb4yTcVKdpiVteDWzYLzffI4vT+v+n/2zjssqqPtwzcIgqCwgEqT3rFhF01iYsUk9hJbYo+9V1TsXbGhsZDYUKOxYO/GEk3UWECjgr1jg10QEASX7w9gYdldWH1FNl/mvq5zKWdnZn9n5jlzZuc884xfzksqU9OSuBfw7Lur9tlXXfHsS0tLQw89pZdjxYsXR09PnygNfXpaejpR9x5Ro0LOJJi+vj41Knhz9dbdAq9FE5U8XbjwTzQPYjInrm4+eExk1B3q+PkWkPPfRQZ6Onv8f+M/GQOiUqVKTJo0CQAPDw+WLl3KsWPHaNSokVKASmdnZ6ZPn07fvn0Vb/cfPnxImzZtFD+YXV1dP1hHWloaS5cupVatzM503bp1+Pj4cP78eWrmWi+ujsqVK1O5cmXF39OmTSM8PDzTrXDgQG7evMmBAwc4f/48NWrUAOCXX37BxydnrfDRo0eJiori0KFD2NnZATBz5kyaNm2q8n1Dhw6ldevWir8nTZpEcHCw4pyLiwvXr19n5cqVdO3alYcPH+Lh4cFnn32Gnp4eTk456/MePnyIjY0NDRs2xNDQEEdHxwKvNzU1ldRUZVe21LdvMSqe81Yv/vVr3snlWOZxIbOUmPPgSUy+5RcmUmmmO50kzzpeicRC8VleEhLikcvlavM8zuUl80voT3j7lKeWf/7rcfOSnPASAJNSyusbTUqVJvn1K435bl7ex8vH12k/bJtW33P93HYsrN2wdalacGJ0r64SEhKQy+Uqa7AlFhY8evxY4zWoaLHI0Z/9r7oyNV1jXmTSuKw8yj8IzCUWis/y8johHrn8HRKJhUqeJ48eqs1z7PA+yjk44e1b4V+pSdfsKZvs+jDPU1eZuvKrKzkSiWqe7Lp6/uwpAFs2raVrz364uLpz4tghJo0bwaKf1uS7nlyqaD+JSvkyjXWVoFVd5SY+Pp7Nv24koOnXGrXkaMq+V/JqkuTTftmaVPNo62GonSbt719t+hGpVIqBgYHKCw0LiQRpnHqbyKtJtR0kGu0pPzt/kquefg5djrdPeWp/gJ2/D0bWpUl9rvzsSX3+CkPzUugbG2FoYY6+gQGpL2LzpInF1Ev7cVhhtd//Qs699/79lIomNffevr27Wbs6lJSUFOzLOTBtxhyNHp8A8QmvM8uWSJTOW0jM83nuyZCoSR+XZznP2fN/M2NuMKmpqVhaWDBn2hTMzdW7/eclQZZpH6XMlftAM4kVCdJYdVlUkMvlbFk9HzdvP+yd3AGIl8ZiYGCIiWmpDypXlpUm73NMIrFEJsv/2WcuUX1ePnmc6VXg4e2LkbExG9asoNMPP5JBBhvXrkAuf4dUgy5ZQmLmONhc+VoszUvx4OmzAq9FE12bNybpTQrtR0xDX18PuTyDfu2bEfBZ/mN3QdGxbNky5s2bx7Nnz6hcuTIhISH5/tbaunUrQUFB3L9/Hw8PD+bMmcPXXxf8nP5Q/pMeEJUqKc/S2traKjwDjh49SoMGDbC3t6dUqVJ8//33xMbGkpycDMDgwYOZPn06devWZdKkSVy5ov2sa14MDAwUkwMA3t7eSCQSbmgxo56YmMjIkSPx8fFBIpFQsmRJbty4ofCAuHHjBgYGBlSrljO7ml1+Njdu3MDBwUEx+QDg7++v9vuqV8+Z2U1KSuLOnTv07NmTkiVLKo7p06dz584dINP7IiIiAi8vLwYPHqzkptiuXTvevHmDq6srvXv3Jjw8nPT09Hyvd9asWZibmysdi0PXFVhPRcGJ40f5rvU3iuPdu/yv7UM5d/ZPrkRG0KvPgALTRl/cw8qxVRWH/AM0vZbG8Ef4TBp3mY+BYf7B7ADS36Zw89LefL0fdLGudJFTx4/QuU2A4iisespNamoqf5w8ptHTQBc16ao9nTx+hE5tAhRHYenKkGcA0LhpMxo0aoqrmwc9fhyIfTkHfj+ivFTw+PFjtG3dXHGkF7Ac4mOQnJzElEkTcHR0pFPn71U+P378d9q0bqk4PoVNFcTx33+ndatWiuNdAc+qT8GJ48do3/pbxVH4dt6/UMr/FOhq+7Vr3UxxpBeynX/5VQMWhyxn1pxg7O3tmTNr+nvFG/qYVK5UkRVLFrJo3mxqVKvC9DnzNMaVOHdyP4M61VEcH6Oefg2dxdOHt/lx+OwPLuOP44fp0rax4iho/PqhmJtbMGLsVC6eP8P37RrTtX1TkpIScXHz/OTx5I6evcTB038zbWA3wmaOZVK/79mw7xh7T579pDoE2rFlyxaGDx/OpEmTuHTpEpUrV6ZJkyZKXvC5+fPPP+nYsSM9e/bk8uXLtGzZkpYtW/LPP/8Umsb/pAdE3plfPT095HI59+/f59tvv6Vfv37MmDEDS0tLTp8+Tc+ePXn79i0mJib06tWLJk2asG/fPg4fPsysWbMIDg5m0KBBn/QaRo4cyZEjR5g/fz7u7u6UKFGCtm3bFtpDJXe08uyYGKGhoQrvjWyyXWqrVq3KvXv3OHDgAEePHqV9+/Y0bNiQbdu24eDgQHR0NEePHuXIkSP079+fefPmcfLkSY2z8oGBgQwfPlzpXMKdSKW/zUuVopi+PnF5Ak7GyeI1BpgsDGrWqoNXrqj02UE7ZVIplpY5HgcymRQXV/W7c5iZmaOvr6/y5lEmkyrcYK9GXuZZzFM6tWuulGbOzCn4lq/IjDkLFOdcyn+FtWPOxNu7d5l2kvw6FlOzsorzya9fUdpeOaJ+Ni8fX+NNYixbFuR4wmTI3/H07gWunNlIv7lX0NfPcam+feUQ6WkpeFdvqbY80M26Ui7bDH19fZW3UDKpFEsNkektLFTfGMukUsWbqux/pVIplrlcmmVSKa5u6q+xRq26Sjsd5NRTHBa56ileJsXZ1V1tGaXMzNHXL6YSYC5eJlUbUfuvMyd4m5pCvQZN/jWadNWeataqi6caXfHSODW68qsrfZU3arJcdZVd7w4OyhHh7R2cePlSeeBRq5a/YqeK3JpkUtl71JVZgXWVTXJyMhODxlPCxITxQZMxULPWuFat2nk0ZfZTUhVNMo3ehzmaZHk0ybCwLHg3CRVNtWvj5a1aT+9z/2rTj1hYWJCenk5iYqKSF4RUJlOpy5q1/JV2OkjXaOcyXD/AziVZ9XQlMoJnMU/p2K6FUprZM6fgW74CMzX0mx9C6vNXGFmXVjpnZF2atPjXyFNSeftKijw9HaOyVnnSWJH6TLPX3qdqv/chb/vl108V1H4qmmRSFTs3NTXF1NQUO/tyeHn70LF9a/768zT1vlTe6SAbc7NSmWXnmRiQyuI17shiYSFRCcwslcVjmccroISxMfZ2ttjb2eLr7UXX3v04ePgoHdu3VSmzcs16uHjmeLpl2/nr+DgkljlLSBJksTi4aN6VKptNobO5cuEPRk3/BYvS1jnXa2FFenoayUmvlbwgEmSxmFmo7oJRvdZnuOfaqUJx/8mkWFjm2LBMFoezi4daLdnPvvg8/Xnmsy/nOytXrcnSn7eQEC+jWLFimJYsRa8uLbC2sctbJAASs5KZ4+A8ASfj4l9rDDCpDUs2htO1RWMa18l8GenuaE/MyzjW7T7Mt/VqF5D730PG/4ONAiAznmHv3r3p3r07ACtWrGDfvn2sXr2asWPHqqRfvHgxAQEBjBqVGc9q2rRpHDlyhKVLl7JixYpC0fif9IDQxMWLF5HL5QQHB1O7dm08PT15+vSpSjoHBwf69u3Ljh07GDFiBKGhoR/0fenp6Vy4cEHxd3R0NDKZTGmZhCbOnDlDt27daNWqFRUrVsTGxkYpyr63tzfp6elcvHhRpfxsfHx8ePToETExOcsTzp4teDbT2toaOzs77t69i7u7u9Lhkmstn5mZGd999x2hoaFs2bKF7du3E5flSlqiRAmaNWvGkiVLOHHiBH/99RdXr2reSsvIyAgzMzOlI/fyCwBDQwM83Zy5eCVnzZ1cLufileuU91I/qC8MTExMsLWzVxwOjk5YWFhyJTInaFBychI3o2/g5aN+/ZyhoSFu7p5cibysOCeXy7kScRkv78w8bdp1ZPGyUBYtXaU4AHr07sfgYcpB8Yobl0RSxklxWFq7Y1KqDI9v5ay5fZuSyPOHV7Bx9lOrqZxHbTqO2k2HEeGKo6xDBbyqNqPDiHClyQeA6+e24VL+K0qU1LxuWBfrKm/Z7h4eREZEKJUdERGBt4b71NvHh4hc6QEuX76sSG9jY4OFhYVSmclJSURHR+OjIXhZCRMTbO3KKQ4HR2ckFpZczVNPt6Jv4OVdXm0Z2fV0NSKnT8isp0t4qsnz++H9VK9VF3Nzyb9Gk67ak6a6yqvrVvR1xXeo1+XFlYicPJm6LirylLW2wdKqNE+eKLtgxzx5RJmy1krnTExMsLOzVxyOWXUVkeu6k5OTiI6O0mjrhoaGuLt7EBkZoaQpMiICb++cPMnJSQRNCMTAwICgiVMonqfvVtZkpzgyNVkola+tpog8miLyaNIWVU2O733/atOPeHh4YGBgoNR3PH78mJcvXqiUm7ftsu08Mk/bFWTn7u6eREbmtafLeGfZU9t2HViybBWLl65UHAA9C+g3PwTZ2Qis6iv/kCndoA7SsxEAZKSlEX/pGqXr5/LS1NPD6it/ZGcvo4lP1X7vg6Z7T7X9ovAuoP3y9lORufop9WSQQUa+u5kZGhri6e7G5cgcD1+5XM7lyCv4eqv/oe/r7cXlCGWP4EuXI/DRkF6hJkOuUYtxCVPK2joqDlsHV8wkpblx5ZwizZvkRO7d+gdXr0pqy8j8jgw2hc4m4tzvDJ+yktLWytutOrr6UMzAQKncZ0/uE/fqGW6equXm7c/LZfXn/+R6jiUnJ3G7gGefq7snVyOVn31XIy+qffaZmUswLVmKq5EXSYiXUr2W+u2eDQ0M8HZx4O9/cmJvyOVyLlyLpqLHhy8ZT3mbpuJ1UUxfH3mW152g8ElNTSUhIUHpyLs0HTI3Abh48SINGzZUnNPX16dhw4b89Zf6QKR//fWXUnqAJk2aaEz/MfhPekBowt3dnbS0NEJCQmjWrBlnzpxRmfkZOnQoTZs2xdPTE6lUyvHjx7WaMFCHoaEhgwYNYsmSJRgYGDBw4EBq165dYDwEyBys7Nixg2bNmqGnp0dQUJDStjxeXl4EBATQp08fli9fjoGBAUOHDqVEiRKKNA0bNsTT05OuXbsyb948EhISGD9+vFbap0yZwuDBgzE3NycgIIDU1FQuXLiAVCpl+PDhLFiwAFtbW6pUqYK+vj5bt27FxsYGiUTC2rVreffuHbVq1cLExIQNGzZQokQJpTgRH0qHZgHMCAnF290FHw9XfttzmDepqXxT/wsApi1eSRkrC/p2aQ9kBq68//hJ5v/T03kZJ+XWvQeUMDamnG3mgD35TQpPnuVEjI558ZJb9x5QqqQpNmVKUxB6eno0a9ma3zZvxNauHNbWNmwKW4OlVWlq++c8RIICR1K7zmd806wlAC1atWXxgjm4e3ji4enNnl3bSUlNoWGjzLe/FpaWaoOClSlTFmsb2wI1Vf7iBy4cWYGktDOlLO05d3AJpmZlca2Q0wntXN4N1woNqfR5F4obl8TKVnm/boPiJTA2kaicl718wNO7F2jWa1WB9aPrddWqVSsWBAfj4eGBp5cXu3buJDU1lUaNGgEwf/58rKysFDPNLVq0YMzo0ezYvp0aNWty8uRJbt26xaCsnV709PRo2bIlmzdvxs7eHmtra8LCwrCyssK/TsGBPbPL+LZFO7ZtXo+tXTnK2tjwa9hqLCytqJmrniaPG0ZN/8/5ulmm10qzVu0JWTALNw9vPDy92btrG6kpb6jfSDnuS8zTx1z/J5Lxk+dopUeXNemaPeXUVVu2bQ7L1GVjy69hv2BpWVqpriaNG04t/89y1VU7QhbMwt3DCw9PH/bs2kZqSoqirvT09GjR+ju2bFyLs4sbLq7uHD92iCePHzJqXP7bIerp6dGiZSu2bN6EvZ091tY2bAhbi6WVFf651v+PCxyNf526NGuW+Va8Zas2LFwwL/P+8PRm164dSnWVnJxE0PhAUlNTGTlqDG+Sk3mTtaTRzNw830CU2Zo2b/4VOzs7bKxtCAtbn6Up514ZFzgW/zp1aNYs0yOlVavWLFgwP0uTF7t2hZOSmkKjRo0VeeLi4pBKpcRkvWS4f/8+JUqUoGzZspQqpbx+Oq8mbe7fwLFjqVOnDs2aZ2vKvx8xNTWlcePGhIaGUqpUKUxMTFixfDk+Pj4F/sjV09OjeZad22W13castssdu2FC4Chq16nLtwo7b8OiBXNx9/DC09OL3Vlt16BRAJC/ndsUYOfFTE0wdXdU/G3iUg6zyt68jYsn5VEMXtOHY2xvTWT3zMDXD1Ztxql/Z7xnjeLR2u2U/qo2tu2a8nfzPooy7i1aQ+XVc5Bd/If4v6/gPLgrBqYleLRuR75a8tZVYbQf5NjU0w+wqeZZ915m+9kq7r3c7Tc+cBT+udov896bi7uHp5KdZ997z2Ji+OPUCapUrYaZuYTYVy/ZtnUzRsWLU71G/uPMNi1bMHfhYjw93PHy9CB81x5SUlJo0rABAHOCF1Hayoqe3TKXUrVq3owRY8ezdcdOatWozolTf3Dz9h2GDsxcvvMmJYVNW7biX6smVpYWxCcksHvvAV7FxvHFZ9rFF9HT06Pht53Yv+1nyto6Utranl2//oTEsgxVan6lSLdgUh/8an1F/a8zg7pvWjWL838coH/gQoxLmBIvzfSYKWFSkuJGxpiYluKzBi3ZuiYY05LmlDAx5def5+DqVSnfiY3cur5p0Z7tW9ZhY1+Osta2bNnwMxaWVtTwz9l+fMq4IdT0/4KmzTKXpX7b8juWLZyJm4c37p4+7Nu1ldSUN3zVMGfd/fEj+7B3cMbMXMLNqH9Ys2oJ37Roj305RxUd2XT6pgFTlq/Hx9WR8u7ObD7wO29SUxWeCpN+WkdZCwkDOmb24Wnp6dx7HJP1/3e8lMq4ef8RJYyNcLDJ9JD9vGoF1u48hI2VJa4OtkTff8Sm/b/T7Ev1y7YFH59Zs2YxZYryc3zSpElKOzkCvHr1infv3mFtrfzSwdramigNgXafPXumNv2zZx8eN6QgxARELipXrsyCBQuYM2cOgYGBfPHFF8yaNYsffvhBkebdu3cMGDCAx48fY2ZmRkBAAAsXLvyg7zMxMWHMmDF06tSJJ0+e8Pnnn/PLL79olXfBggX06NGDOnXqULp0acaMGUNCgvLSgzVr1tCrVy/q1auHtbU106dPJygoSPG5vr4+4eHh9OzZk5o1a+Ls7MySJUsICAgo8Pt79eqFiYkJ8+bNY9SoUZiamlKxYkVFEM9SpUoxd+5cbt26RbFixahRowb79+9HX18fiUTC7NmzGT58OO/evaNixYrs2bMHKytVV7f3pcFntZElvObnX3cQJ4vH3cWR4KBRWGYtwXj+KhZ9/ZxZ3FdSKd1H5NTJr7sO8OuuA/iV92bptHEARN25x+CJsxRpQtZsAqDpV58xftCPWulq3bYDKSkp/BSygKTERHzKV2TS1FlKbwKfxTwlIdd+2J/X+4qEhHg2ha1FKs10g540dbZa1/QPoWr9XqS/fcPxrRNJfZOArUs1mv0YqhTfIf7VQ94kaRcYMTc3zm+npLkNjl7vH7hM1+qqXr16JMTHE7ZhA9K4OFzd3Jg6bZrCFfXlixfo53oz4Ovry+gxY1i/bh1r167F3t6eoKAgxS4wAG3btSMlJYWQJUtITEykfPnyTJ02TeObYXW0bNuRlJQ3rAiZT1JSIt6+FQmaNo/ixXPa71nMU14n5NRT3S/qEx8vY/OG1cikcbi4ujNh6jyVevr9yH6sSpehctUavA+6qEnX7CmbVm07kpqSoqgrH9+KBE2bm6eunpCQq64++6I+CfEyft2wRlFXQVPnKulq1rIdaW/fsiZ0GYmvX+Ps4sak6fOxsVV+66eONm3bZ9plyCKSEhPxLV+BqVNn5qmrGKW6+qLel8QnxLMhbD1SqRRXV1emTp2huD9u375NdHTmoKd3z25K3/fLmvVYW9vkq6lt26x7JWRJlqbyTJs6XUlTTJ72+6JevSxNYbk0TVdyHz+wfx+bNuVsTT1mdOYWk0OHDVeaqFCrSYv7NyYmhvhcz+SC+hGAH/v0QU9fnxnTp5OWlka1atXoP0C7OCOt235HSkoKy0IWKtpu8tTZBdp5fC47d3V1Y/LUWRrd7N8H82oV8D8Wpvjbd37m8/TR+h1c6RmIkW0ZSjjkTGK8uf+Yv5v3wTc4EOdBP5Dy+BlX+0zg1ZGcbWljth6geBlLPCcNxsimDAmRNzj/bS/evtAuAGE2hdV++/fvZ1Ou7c5HZ7kzDxs+XGmiQh1tstpvaa57b4pKPxVDQnyOps/rfUl8goyNYesU7Tdl6kyFJsPihly7dpXdu3aQmJiIRGJB+QoVmRu8WCVgYl6+/OIzZPHxrNvwK1KpFDdXF2ZOnaQICPvi5Uv0co2lyvt4EzhqOGvDNrJm/Qbs7eyYPH4sLs6ZL5aK6evz6PETjhybQ0JCAqXMSuHl4cHCOTNxdtL8YzovTVp1IzX1DRtWTCc56TXuPn4MCVqGYa5+8+WzRyQmyBR/nzy0FYDgoN5KZXUbOIU69TMnmNp3H4menj4r5o0kPe0t5f3q0OnHQK11tWjTiZSUN6wMmUdy1rNv/NT5Sv3582d5n30NSIiXsWXDL8ikcTi7ujN+6nyl/vzJk0dsXLeKxMQEypa1oXX77/m25Xf5amnkXw1pwmtWbdtLrOw1nk72LB47QLEE4/krqdKY5aU0ni6BOTExNuw9xoa9x6jq48GKiUMBGNmtPSt/28vcNZuRxidS2sKcVg0+o1cb1aD1gsJB3VJ0I6OC47HpKnoZGRnCf6YIWLt2LUOHDlVZMyfQnpfXzhWc6BMTa1zwIP9TcyRK9zQ18n5S1BJUMNQrmqBcBfFGblLUEv4VGOgVfXC5vLzLyH+byaKguI7auR7yghN9YvT0dG94lJ6hefeCouK2d8OCE31ivKMPFLUEtbzL0L33fsbypKKWoMK9t/+7R+zHxqJ4YlFLUMHp9YcHwi9MzKvqXp+gDXfufvhWpYWNm5a7LmbHLNy2bRstW7ZUnO/atSsymYxdu3ap5HF0dGT48OFKO0FOmjSJnTt3EhkZqZL+YyBiQAgEAoFAIBAIBAKBQPAvpnjx4lSrVo1jx44pzsnlco4dO6Zxp0N/f3+l9ABHjhzRmP5jICYgPhJ9+/ZV2pIy99G3b9/3Lq98+fIay9uYy8VPIBAIBAKBQCAQCAQfTkaGns4e78Pw4cMJDQ1l3bp13Lhxg379+pGUlKSIVfbDDz8QGJizxGjIkCEcPHiQ4OBgoqKimDx5MhcuXGDgwIEftX5zo3u+YP9Spk6dysiRI9V+ZmamuvVNt27d6Natm8by9u/frzEycN5AIQKBQCAQCAQCgUAg+G/z3Xff8fLlSyZOnMizZ8/w8/Pj4MGDit+PDx8+RF8/xwehTp06bNq0iQkTJjBu3Dg8PDzYuXMnFSpU0PQV/zMiBoTgX4uIAaEdIgaEdogYEP9uRAwI7RAxILRHxIDQDhEDQntEDAjtEDEgtEPEgPi43L5zr6glaMTdzaWoJXxUdK8nFAgEAoFAIBAIBAKB4BORISITfDJETQsEAoFAIBAIBAKBQCAodMQEhEAgEAgEAoFAIBAIBIJCR0xACAQCgUAgEAgEAoFAICh0xASEQCAQCAQCgUAgEAgEgkJHTEAIBAKBQCAQCAQCgUAgKHTELhgCgUAgEAgEAoFAIPjPkoFeUUv4zyA8IAQCgUAgEAgEAoFAIBAUOmICQiAQCAQCgUAgEAgEAkGho5eRkZFR1CIEgg/h1p0HRS1BBX29d0Ut4V9BibTEopagwhvDkkUt4V9DRobuuSnqIy9qCSq808FVjrraR4k+QTv0M3TPzuV6uvcuK8qraVFLUItv1L6ilqCCLrafPKNYUUtQwVieVNQSVEjRNy1qCWrxcHMqagkfRPSdR0UtQSNebg5FLeGjonu9jkAgEAgEAoFAIBAIBIL/d4gJCIFAIBAIBAKBQCAQCASFju75hwoEAoFAIBAIBAKBQPCJELtgfDqEB4RAIBAIBAKBQCAQCASCQkdMQAgEAoFAIBAIBAKBQCAodMQEhEAgEAgEAoFAIBAIBIJCR0xACAQCgUAgEAgEAoFAICh0xASEQCAQCAQCgUAgEAgEgkJH7IIhEAgEAoFAIBAIBIL/LGIXjE+H8IAQCAQCgUAgEAgEAoFAUOiICQiBQCAQCAQCgUAgEAgEhY5YgiEQCAQCgUAgEAgEgv8sGRliCcanQnhACAQCgUAgEAgEAoFAICh0/nUTECdOnEBPTw+ZTKb28/v376Onp0dERMQn1ZWXbt260bJlyyLV8OWXXzJ06ND/uZzJkyfj5+f3P5cjEAgEAoFAIBAIBIL/Lh9tCcaXX36Jn58fixYt+lhFfhAODg7ExMRQunTpItWhC+zYsQNDQ8P3yqOnp0d4eLjS5MnIkSMZNGjQR1ZXeGRkZLBxw3oOHTxAUlIiPr7l6T9gMPb29vnm27tnNzu2b0UqjcPFxZU+/Qbg5eUNwOvXCWzcEMblSxd5+fIF5ubm1PavQ5fvu2Fqalqgpj179rB92zakUikurq7069cPLy8vjen/+OMPwtav5/nz59jZ29Oje3dq1KypdI0bwsI4ePAgSUlJ+Pr6MmDgwAKvMTcfWkZB13Jg/35OnDjB7du3efPmDb9t3UrJkiW10hS+7yBbwncTJ5Xh5uLE4B974OPpoTH9idN/sXrjZp69eEk5Oxt+7NqF2tWrKqV58Ogxq9ZtIPKf67x7J8fJoRxTAkdgXaaMVpqg8Orq7du3hIaGcurkSdLS0qharRoDBgzAwsLi36tpQ1jWvZeEj68vAwYM0ure2749S5OLK3379Ve2qQP7OXniOLdv3+HNm2S2/LZNa5vas2cP27ZvRyqV4uriotW9tz4sjOfPn2NvZ0f3Hj2oWaOG4vMzZ86wb/9+bt++zevXr1kaEoKbm5tWWnIj+int0MU+QRfvvd179irZef9+ffNtu1N//MH6sA0KO+/Ro7uSnZ8+c4b9+w9wK8vOl4Us+WA715XnjOVn1XEd0RPzqhUwtivLhTb9eb77WP55vqiJ7/yxlPT1IOVRDLdnLefx+nClNE79OuE6vCdGNmVIuBLFtaHTiP/7agE1o4wutp8utV1uTbrWb+7au5/fduzM6qOcGdinF95enhrTnzx9hrUbfuXZ8xfY29nSu9sP1KpRTW3aRUuXs/fgYfr17kGbFs0K1JIbXawrXUfsgvHp+GQeEBkZGaSnpxf69xQrVgwbGxsMDP674S3evn0LgKWlJaVKlfqfyytZsiRWVlb/czmfiu3bfmPP7p0MGDiY4IVLMDY2ZmJQoKJe1HHq5Al+Dl1Jx05dWBzyEy6urkwMGodMJgUgNjaWuNhYevTqzbLlqxg6bCQXL1xg8aLgAvWcPHmS0FWr6NS5MyEhIbi6uBA0YYJGL57r168zZ/ZsGjdpQsjSpfj7+zNt2jTu37+vSLNt61Z2797NwEGDWLhoEcbGxgRNmJDvNeblQ8rQ5lpSU1OpVr0633XooLUWgN//OMPyX9bRtUM7Vi2cg5uzE6MnzUAqi1eb/p8b0Uybv4ivG9UndNFcPqtVk6CZc7n34KEizZOYZwweG4SDvT0LZ0zh5yXz+f67NhQ3LP5e2gqrrlatXMn5c+cIHDeOOXPnEhcby/Tp0/+9mrZtZc/uXQwYOJgFC7M0BY0v4N47SWhoKJ06dWFJyFJcXF0JChqvYlNVq1Wn/XffaaUj9/WuCg2lc6dOhISE4OLqyoSgoHzvvdlz5tCkcWOWhoSovfdSUlIoX748Pbp3fy8teRH9VMHoap+ga/feyZOnCA0NpUunTiwNWYKrqwvjC7TzuTRp3JhlIUvw9/dn6rTpeew8lfLlff9nO9el50wxUxMSrkTzz+ApWqUv4VyOGrtXEnviHKert+BeyDoqrpxO6UafKdLYtmuKz7xAbk1fxumarXh9JYpa+36heBlLrXXpavvpUttlo2v95vFTp1nx8xq+7/gdKxYH4+rizNiJU5FqaLtrN6KYMXcBAY0asGJJMHVr12LSjNncu/9AJe3pP89yI/omVpba21JudK2uBILcfJQJiG7dunHy5EkWL16Mnp4eenp6rF27Fj09PQ4cOEC1atUwMjLi9OnT3LlzhxYtWmBtbU3JkiWpUaMGR48eVSovNTWVMWPG4ODggJGREe7u7vzyyy9qvzs5OZmmTZtSt25dZDKZyhKM7CUbx44do3r16piYmFCnTh2io6OVypk+fTply5alVKlS9OrVi7Fjx2q97ODdu3cMHz4ciUSClZUVo0ePJiMjQymNXC5n1qxZuLi4UKJECSpXrsy2bdsUn0ulUjp37kyZMmUoUaIEHh4erFmzRvH548eP6dixI5aWlpiamlK9enXOnTsH5CyR+Pnnn3FxccHY2BhQXYLh7OzMtGnT6NixI6amptjb27Ns2TKlzwFatWqFnp6e4u+8SzDkcjlTp06lXLlyGBkZ4efnx8GDBxWfZ7fBjh07+OqrrzAxMaFy5cr89ddfijQPHjygWbNmWFhYYGpqSvny5dm/f79W9Z0fGRkZ7NoZzncdOlHbvw4uLq4MHzGauNhY/vrrjMZ8O8O30ySgKY0aN8HR0YkBA4dgZGTEkcOHsurGhXETJlKrlj+2tnZU9qvCD127c/7cOd69e5evpvDwcAKaNqVx48Y4OjkxcNAgjIyMOHz4sNr0u3btolr16rRt2xZHR0d++OEH3Nzc2LNnj+Iad+7cSYcOHfD398fFxYURI0cSGxvLX3/+qXU9fUgZ2lxLy1ataN++Pd7e3lppyWbrrr1807gBTRt+hbOjA8P7/4ixUXEOHP1dbfrte/ZRs6ofHVq3wMmhHD26dMDD1ZXwfTm2+MuGX6lVrQp9u3+Ph5sL9rY21K1VAwuJuda6CquukpKSOHz4ML1798bPzw8PDw+GDR/OjevXibpx41+pKfPe65ilyZURI0Zl3Xv5adpBQEAAjRo3xtHRiYEDB2FsZMThrHsPoGXLVrRv/91721R4eDhNAwJo3LgxTo6ODBo4sMB7r3q1ahrvPYAGDRrQuVMnqlSp8l5aciP6Ke36KV3sE3Tx3tsRHk5AQACNGzfKZefGHNLQdjt37aZ6tWq0a9sGR0dHuv7wPe5ubuzes1eRpmGD+ll27qdVvahD154zLw+d4uakRTzfdbTgxIDTjx14c+8xN0bPITHqLg9+2siz7YdwGdJNkcZlaHce/fIbj9ftIPHGHa72n8S75BQcurXRWpcutp+utV22Jl3rN7fv3M3XTRoR0KgBTo4ODB3QFyMjIw4eUe9Zs2P3XmpUq8J3bVrh5OBA9+874e7myq69yuPfV69iWbryZwJHDsPAoNh71RPoZl0JBLn5KBMQixcvxt/fn969exMTE0NMTAwODg4AjB07ltmzZ3Pjxg0qVapEYmIiX3/9NceOHePy5csEBATQrFkzHj7MeUPxww8/8Ouvv7JkyRJu3LjBypUr1bpnyWQyGjVqhFwu58iRI0gkEo0ax48fT3BwMBcuXMDAwIAePXooPtu4cSMzZsxgzpw5XLx4EUdHR5YvX6719QcHB7N27VpWr17N6dOniYuLIzxc2UVv1qxZrF+/nhUrVnDt2jWGDRtGly5dOHnyJABBQUFcv36dAwcOcOPGDZYvX65YRpKYmEi9evV48uQJu3fvJjIyktGjRyOXyxXl3759m+3bt7Njx45841/MmzePypUrc/nyZcaOHcuQIUM4cuQIAH///TcAa9asISYmRvF3XhYvXkxwcDDz58/nypUrNGnShObNm3Pr1i2ldOPHj2fkyJFERETg6elJx44dFV4wAwYMIDU1lVOnTnH16lXmzJmjtQtefjx/9gypNA4/vxyXW1NTU7y8vDUO4tLS0rh9+xZ+fjk/KPT19fHzq0JUlOaBX1JSEiYmJhQrpvnhkJaWxu1bt5QmcDLL9tOoJ+rGDarkmfyqVq2aIv2zZ8+QSqX45foBlHmNXtyIitKoJTcfUsaHXIu2pKWlcfP2Xar5VVIqu2rlSlyLuqk2z/Wom1SrXEnpXI2qlRXp5XI5Zy9copydHaMmTafV9z3pNzKQ02fPv5e2wqqrW7dukZ6erlSug4MDZcqWLbAddVqTX15NH//e04a0tDRu3b6t9no1XcuNqCila4fMe0/b+0pbRD9VcH3qap+ga/detp1XyVN2lQLsPO8P02rVqn50O9e158z7Iqntx6vf/1I69/LIaSxqZ2rTMzTEvGp5Xh3L9YM8I4NXv/+JpLZ2E5S62n662Ha62G/evH2Hqn6Vlcqu6leJ61HRavNcj4pWSg9Qo6of13P1aXK5nNkLFtG+dQucnRw1fn9+6FpdCQR5+SjrFMzNzSlevDgmJibY2NgAEJXVQU2dOpVGjRop0lpaWlK5cs7NN23aNMLDwzPdvAYO5ObNm/z2228cOXKEhg0bAuDq6qrync+ePeO7777Dw8ODTZs2Ubx4/u6TM2bMoF69ekDmpMg333xDSkoKxsbGhISE0LNnT7pnuapNnDiRw4cPk5iYqNX1L1q0iMDAQFq3bg3AihUrOHQo5+1damoqM2fO5OjRo/j7+yuu6fTp06xcuZJ69erx8OFDqlSpQvXq1YEcbwSATZs28fLlS/7++28ss1yx3N3dlTS8ffuW9evXU6aANax169Zl7NixAHh6enLmzBkWLlxIo0aNFHklEomiHdUxf/58xowZQ4cs97k5c+Zw/PhxFi1apORRMXLkSL755hsApkyZQvny5bl9+zbe3t48fPiQNm3aULFiRUV95EdqaiqpqanK15yaSnEjI6VzUmlc5jVYSJTOSyQWyKRStWUnJCQgl8uR5FlnK5FY8PjRI7V54uPj2fzrRgKafp2v7uyy867hlVhY8OjxY7V5pFKpqhYLC6RZ+rP/VVemVMM1qvuO9y3jQ65FW+ITXmeWnectpIXEnIdPnqjNEyeTqUkvQSqVASCLj+fNmxR+3b6THl060KdrZ85fimDirPksmDEJvwrltdJWWHUllUoxMDBQmXizkEiQxsX9izVJlMuXSArUpHq/Snik4d7TFk3XayGRaLyvpVIpFnkmsi3y0f+hiH6q4PrU1T5B1+69D7mHpFKpygub/O7TD0XXnjPvi5F1aVKfv1I6l/r8FYbmpdA3NsLQwhx9AwNSX8TmSROLqVf+Y5psdLX9dLHtdK3f1NxHSXj0WH0fJZXKVJ4xEomEOFmO/s3bwilWrBitmn+b7/fnh67VlUCQl0KPAZH9gzqbxMRERo4ciY+PDxKJhJIlS3Ljxg2FB0RERATFihVTTBZoolGjRri7u7Nly5YCJx8AKlXKeStia2sLwIsXLwCIjo6mZq7AWYDK35qIj48nJiaGWrVqKc4ZGBgoXfft27dJTk6mUaNGlCxZUnGsX7+eO3fuANCvXz82b96Mn58fo0eP5s9cLm4RERFUqVJFMfmgDicnpwInHwDFBEjuv2+8x8x0QkICT58+pW7dukrn69atq1JOfnU+ePBgpk+fTt26dZk0aRJXrlzJ93tnzZqFubm50rFixU8cP36Mtq2bK470T+AClpycxJRJE3B0dKRT5+8L/fs+Bsd//53WrVopjnefIB5LUSOXZy6DqlOrOu1afIu7qwud2rbCv0ZV9hw4ojGfLtaVTmo6/jttWrdUHO/eFb0mXUX0U7rBh/QJunjv6Sqirv696GLb/Rf7zZu37xC+ey+jhg5GT0/7gIj/xboS/Lsp9EiNeaOijhw5kiNHjjB//nzc3d0pUaIEbdu2VQRFKVGihFblfvPNN2zfvp3r168r3qLnR+7dILJv6txLGAqTbE+Kffv2qUSfNcp6g9+0aVMePHjA/v37OXLkCA0aNGDAgAHMnz9fqzrRxeiz+dV5r169aNKkCfv27ePw4cPMmjWL4OBgjbttBAYGMnz4cKVzjx4/I/3dO0V0Xsh0IQOQSWVYWuYEzpTJpLi4qo8AbWZmhr6+vsqssEwmxSLPpE9ycjITg8ZTwsSE8UGTCwx2ml123jcGMqkUSw2RzS0sVGeoZVKp4q1C9r9SqVRpUkomleKqIcp1rdq18fJWraf3KeNDrkVbzM1KZZadJ7icVBaPpYalVZYSiZr0MsUbeHOzUhQrVgznrOVg2TiWK8fV65pdVT9VXVlYWJCenk5iYqLSW0+pTKZidzqpqVbtPPfe2yxNee89mUYPp5x7T6asSSbDwvJ/sylN16vuWrKxsLBQCR6WaVP/m5ZatfxFP5UrjSYbzY2u9Am6eO+pK/t97iELCwuVAIeyj2HnOv6ceV9Sn7/CyFp5RzUj69Kkxb9GnpLK21dS5OnpGJW1ypPGitRnyp4TmtCV9tPFttP1flNzH5XT5+TFwkKi8oyRyWRYSjLr5+q168ji4+nUvbfic7lczspf1rJj1x42rl6ltlxdr6t/C2IXjE/HR/OAKF68uFYBSM6cOUO3bt1o1aoVFStWxMbGRilyb8WKFZHL5YrYCJqYPXs2Xbt2pUGDBly/fv1/0u7l5aUS70BT/IO8mJubY2trqwgICZCens7FixcVf/v6+mJkZMTDhw9xd3dXOhxyDYTKlClD165d2bBhA4sWLWLVqsyOplKlSkRERBBXgAu0Npw9e1blbx8fH8XfhoaG+bajmZkZdnZ2nDmjHMTmzJkz+Pr6vpcWBwcH+vbty44dOxgxYgShoaEa0xoZGWFmZqZ0FDcywsTEBDs7e8Xh6OiEhYUlEZGXFXmTk5OIjo7CO9d15sbQ0BB3dw8iIyMU5+RyOZEREXh75+RJTk4iaEIgBgYGBE2copXnjaGhIe4eHkTmisshl8uJiIjQqMfbx0cljsfly5cV6W1sbLCwsFAqMzkpiejoaHw0BHXKrCc7xeHo6PjeZXzItWiLoaEhnu6uXIrM2bpMLpdz6cpVynur387K19uTS1eUtzq7GHFFkd7Q0BBvDzce5XHXfvz0KdZlNW/T+6nqysPDAwMDA6W2fvz4MS9fvFAp99+hySlTU677SNt7LyLPvReR5977EAwNDfFwdyciMlKlbE115OPtrfbe05ReW0Q/laWtABvNq0kX+gRdvPfylp1p56pl52/nkUrnLn00O9fd58z7IjsbgVX92krnSjeog/RspraMtDTiL12jdP1cnqV6elh95Y/s7GW0QVfaTxfb7t/Qb3q6u3EpMseDVy6XcznyKr7e6rdQ9fX24nKEssfvxcuR+Gb1UQ2/qseqkIWsXLJAcVhZWtKudQtmT52kUYuu15VAkJePNgHh7OzMuXPnuH//Pq9evdLoXeDh4aEIlBgZGUmnTp2U0jo7O9O1a1d69OjBzp07uXfvHidOnOC3335TKWv+/Pl07tyZ+vXrK2JOfAiDBg3il19+Yd26ddy6dYvp06dz5coVrd2fhgwZwuzZs9m5cydRUVH0799faXa6VKlSjBw5kmHDhrFu3Tru3LnDpUuXCAkJYd26dUBm3Ildu3Zx+/Ztrl27xt69exUTAx07dsTGxoaWLVty5swZ7t69y/bt25V2ldCWM2fOMHfuXG7evMmyZcvYunUrQ4YMUXzu7OzMsWPHFAGI1DFq1CjmzJnDli1biI6OZuzYsURERCiVUxBDhw7l0KFD3Lt3j0uXLnH8+HGliZAPRU9PjxYtW7Fl8ybOnf2L+/fusWD+XCytrPD3z1k2Mi5wNHv27FL83bJVGw4d3M+xo4d59PAhPy1bQkpqCg0bNQGyOtzxgaSmpDBk6HDeJCcjjYtDGhdX4MRbq1atOHjwIEePHOHhw4csW7qU1NRURWyU+fPnK+140qJFCy5evMiO7dt59OgRGzZs4NatWzRr1kxxjS1btmTz5s2cPXuWe/fuMT84GCsrK/zr1NG6nrQpI3DsWPbs3q31tQDExcVx584dnj59CmTuinLnzh1ev36dr6Z2Lb5l7+FjHDx2ggePHrNweSgpKakENPgKgJkLQwhdt1GRvk2zbzh/KYLfwvfw8PET1m76jejbd2j1TYAizXetmnP89J/sPXSUJ09jCN97gD/PX6Tl1020qqfCrCtTU1MaN25MaGgokZGR3Lp1i4ULFuDj41PgYE1XNbVo2YrNm3/lbNa9Fzx/fta9l6NpXOBY9uzJrak1hw4e4OjRLE3LQkhJTaFRo8aKNNk2FfOeNpV9vUeOHuXhw4csXbZMq3tv+44dau89gNevX3Pnzh0eZC0bfPz4MXfu3HmvCWLRT2nXT+lin6CL917rVq04cPCQws5Dli0jJTWFxlllz5sfzOo1axXpW7ZozoVcdh62YSO3bt2mebOcNefZdv5QYedPPsjOdek5U8zUBLPK3phVzvwBbeJSDrPK3hg7ZC4R9Zo+nMpr5ijSP1i1GRMXB7xnjcLUyxWnvp2wbdeUe4tz6vLeojU49GyP/fctKentSoVlkzEwLcGjdTu0riddbD9da7tsTbrWb7Zp2Zz9h45w+NjvPHj0iMU/rSQlJYWAhg0AmB28mJ/XhinSt27+LX9fuszWHbt4+Ogx6zZu5ubtO7T4NjOGgrmZGS7OTkqHgUExLC0scChnr1bDv6WuBILcfDSfmZEjR9K1a1d8fX158+aN0kAlNwsWLKBHjx7UqVOH0qVLM2bMGBISEpTSLF++nHHjxtG/f39iY2NxdHRk3LhxastbuHAh7969o379+pw4ceKDZuI6d+7M3bt3GTlyJCkpKbRv355u3bpx/rx2kbFHjBhBTEwMXbt2RV9fnx49etCqVSvi43PcsqZNm0aZMmWYNWsWd+/eRSKRULVqVcV1FS9enMDAQO7fv0+JEiX4/PPP2bx5s+Kzw4cPM2LECL7++mvS09Px9fVVCvioLSNGjODChQtMmTIFMzMzFixYQJMmOQOv4OBghg8fTmhoKPb29kreKdkMHjyY+Ph4RowYwYsXL/D19WX37t14eHhorePdu3cMGDCAx48fY2ZmRkBAAAsXLnzv61FHm7btSUlJISRkEUmJifiWr8DUqTOVbONZTAwJudrni3pfEp8Qz4aw9UilUlxdXZk6dYbCpfH27dtER2dOcvXu2U3p+35Zsx5ra81BO+vVq0dCfDxhGzYgjYvD1c2NqdOmKcp++eIF+rkmu3x9fRk9Zgzr161j7dq12NvbExQUpBSYtG27dpnXuGQJiYmJlC9fnqnTpr2X/WtTRkxMDPG57s+CrgVg//79bNqY86Ng9KhRAAwbPlxpEJKX+p/XJT4+gbWbthAnleHm6sycyeOxzHJlfPHylVI9VfDxYsKIIaze+Cs/h23C3s6WaeNG45IravTn/rUY1u9HNm0LJyR0NQ72dkwZO5KKvu832VVYdfVjnz7o6eszY/p00tLSqFatGv0HDPj3amqbpSlkSda9V55pU6fn0fQ0z71XL+veC8t1701X0nRg/z42bcqxqTGjRwIwdNhwpYmKvNSrV4/4hAQ2hIURJ5Xi5urKtKlTFWW/ePkSPf2ceXhfX1/GjB7NuvXrNd57Z8+eZUGuvmr2nMwfLJ07daJLly5a1ROIfkobdLVP0LV7r169L4hPiCcsbIPCLqar2Lly240ZPYp168NYu3Yddvb2TAyaoNR2f509y4KFixR/z8pl59936VzkdfUhzxnzahXwP5bzY9B3fub469H6HVzpGYiRbRlKZE1GALy5/5i/m/fBNzgQ50E/kPL4GVf7TODVkdM52rceoHgZSzwnDcbIpgwJkTc4/20v3uYJTJkfutp+utR22ehav/nVF59l9lEbNiOVSnFzdWHW1ImKJRgvXr5EP1fblffxZtyoYawJ28Tq9Ruwt7NlyvixuDg75XvdH4Ku1dW/AbEE49Ohl5GRkVHUInSRRo0aYWNjQ1hYWMGJ/yU4OzszdOhQhg4dWtRSPgq37jwoagkq6OuJGWBtKJGm3Q4zn5I3hv/7NrD/FTIydO8hrc+nienzPrwr/DBL742u9lGiT9AO/Qzds3O5XqHHM39voryaFrUEtfhG7StqCSroYvvJM3RvS0djeVJRS1AhRV/34r8BeLh9/AmVT8HV28+LWoJGKrpbF7WEj4rujY6KgOTkZFasWEGTJk0oVqwYv/76K0ePHuXIEc2R8gUCgUAgEAgEAoFAIBBoj5iAIHOt1P79+5kxYwYpKSl4eXmxfft2GjZsCKCyL3duDhw4wOeff/6ppAoEAoFAIBAIBAKB4COii96d/18RExBkbv159OhRjZ/njfSdm7zbauoy6uI5CAQCgUAgEAgEAoFA8CkQExBa4O7uXtQSBAKBQCAQCAQCgUAg+Feje5FnBAKBQCAQCAQCgUAgEPy/Q0xACAQCgUAgEAgEAoFAICh0xASEQCAQCAQCgUAgEAgEgkJHxIAQCAQCgUAgEAgEAsF/FjliF4xPhfCAEAgEAoFAIBAIBAKBQFDoiAkIgUAgEAgEAoFAIBAIBIWOWIIhEAgEAoFAIBAIBIL/LBliCcYnQ3hACAQCgUAgEAgEAoFAICh0xASEQCAQCAQCgUAgEAgEgkJHLMEQ/GtJyzAsagkq6FOsqCWoYJ72qqglqGCcGl/UElR4Y1iyqCWopZg8vaglqFDmxT9FLUEFWWmPopagQlIx86KWoEJGhm66mCYZ6F5d6fOuqCWo8E4HnzHyDN3T5Bu1r6glqOW69zdFLUEFz6jDRS1BhXQd/Hli9vppUUtQ4bWZb1FL+H+Frj4f/z8iPCAEAoFAIBAIBAKBQCAQFDpiAkIgEAgEAoFAIBAIBAJBoSMmIAQCgUAgEAgEAoFAIBAUOmICQiAQCAQCgUAgEAgEAkGhIyYgBAKBQCAQCAQCgUAgEBQ6uhdmViAQCAQCgUAgEAgEgk9EBmIXjE+F8IAQCAQCgUAgEAgEAoFAUOiICQiBQCAQCAQCgUAgEAgEhY5YgiEQCAQCgUAgEAgEgv8sGRliCcanQnhACAQCgUAgEAgEAoFAICh0xASEQCAQCAQCgUAgEAgEgkJHLMEQCAQCgUAgEAgEAsF/FrELxqdDeEB8Ik6cOIGenh4ymayopfxP6OnpsXPnTgDu37+Pnp4eERERRapJIBAIBAKBQCAQCAS6j/CAEHwwDg4OxMTEULp06aKWokRGRga/bljD0UP7SEpKxNunAn0GDMPOvly++fbvDWfn9i3IpHE4u7jRq+9gPL18FJ9PGDuUa1cjlfI0btqMfgOHa6Vp04a1HDm4P1OTbwX6DRhSoKZ9e3ayc/tvSLM0/dhvEJ5e3orPx48Zzj95NDVp+i39Bw0rUFP4vkNs3rmHOKkMd2cnBv/YHR9Pd43pT5z5i182/sazFy8pZ2dDnx86U7t6FcXnyW9SWLV+E6fP/U3C69fYli1L62+b0qJpowK1ZLPt4HE27DlMnCwed6dyjOjRkfLuLmrT3n30lFVbdhF17yHPXsYytGt7OnzTUClN6G+7+WXbXqVzTnbWbFk0TWtNAHv27GH7tm1IpVJcXF3p168fXl5eGtP/8ccfhK1fz/Pnz7Gzt6dH9+7UqFlT8XlGRgYbwsI4ePAgSUlJ+Pr6MmDgQOzt7bXWtHvvPrZt30GcVIqriwv9+/bB28tTY/pTf5xm3YYNPH/+Ans7O3p270bNGtUVn4dt3MSJU6d4+fIVhgYGuLu70/2H7/H21nydedly7C/WHzhFbHwino42jO7cnAquDmrT7jh5nr1nLnPnyTMAfJztGdimicb0M9aFs/3EeUZ0/IbOjT/TWtPOfQfYsmM3cVIZbi5ODOrTEx9PD43pT5z+kzUbNmfZuS29u3WhdvWqSmkePHrMqrUbuPLPdd69e4eTQzkmB47EumwZrXVlZGSwccM6Dh88QFJSIj6+5ek/YLAWfcIudmzfilQah4uLG336DVDqE5aGLCLy8iXi4mIxNi6Bj68vXbv3wsHBUStNGzaEcejgAZKSkvDx9WXAgEEF2uXePbvZvj3r/nBxpW+//kr3x4ED+zl54ji3b9/hzZtktvy2jZIlSxaoJ1vTxg3rszTl1JM2mnLqyZU+/QbglVVPr18nsHFDGJcvXeTlyxeYm5tT278OXb7vhqmpqVaaPuT+Lagfefv2LaGhoZw6eZK0tDSqVqvGgAEDsLCw0E6TjrVdti5dsvPde/aybft2pNn9Zr+++fblp/74g/VhG3j+/Dn2dnb06NGdmjVqKD4/feYM+/cf4Nbt27x+/ZplIUtwc3PTsnbA8rPquI7oiXnVChjbleVCm/48330s/zxf1MR3/lhK+nqQ8iiG27OW83h9uFIap36dcB3eEyObMiRcieLa0GnE/31Va12gu/ferxvWcuTgPsVYqu+AoQWP7/bsJDzX+K53v0FK47vxY4apjO+aNG1GPy3GUlsPn2TDnqPExifg4WjPyG7tKe/urDbtnUdPWbVtH1F3HxLzKo5h37eh49f1ldK8k8sJ3baPA6f/Jk6WQGkLc76tV5serQLQ09P+DX1hjYUBom5cY+P6X7gVfQN9fX1cXN2ZOG0uRkZGWusT/LcRHhCfgLS0tKKWUCgUK1YMGxsbDAx0ax4rfNtm9u3ZQZ8Bw5iz4CeMjI2ZGjSat2/fasxz+tTvrAldzneduhK8ZBXOLm5MDRqNTCZVSteoyTesDtuuOLr26KOVph3bNrNvdzj9Bg5l3sKlGBsbMzlobL6a/jh5nNWhK/iu0w8sCFmBi6sbk4PGqGhqHPANazdsVRzdev5YoJ7f//iTn1avp9t3bQhdMBs3FydGTZ6JVBavNv0/N6KZOn8J3zT8ip8XzuazWjWYMGsedx88VKT5afV6zl+KYPywgaxbuoC2zb9m8arVnDl3Qas6OvLn3yxev5Vebb9l3ZwJeDg5MHTGYuLiE9SmT0l9i711GQZ0aoWVxExjua4OduxbNU9xrJw6Wis92Zw8eZLQVavo1LkzISEhuLq4EDRhgkZvpuvXrzNn9mwaN2lCyNKl+Pv7M23aNO7fv69Is23rVnbv3s3AQYNYuGgRxsbGBE2YkK895ObEqT9YFfoznTt1ZNmSRbi6uDA+aKJGTdeu32DW3HkENG7MT0sWU8e/NlOmz+D+/QeKNPb2dgzo25eVy5YSPG8ONtZlCQyaiCxevU3k5dC5KyzYvI8fWzRg0+SBeDjYMiB4NXEJiWrTX4y6S0DtSqwa05u1E/phbSmh//zVvJCqft/vF69x9c4jyuTTzuo4/scZlv+8jh86tmPlorm4uTgzZuL0fOw8iunzFtG0cQNWLZ5H3do1mDhjLvdy2fmTmGcMGTMBx3L2LJg5mdCQYLp0aEvx4sXfS9v2bVvYu3sn/QcOYf7CEIyNjZkYFFhAn3CCn0NX0rFTFxaFLMfF1ZWJQYFKfYK7uwdDho3kp5W/MGX6LDIyMpg4YSzv3r0rUNO2bVvZs3sXAwYOZsHCLLsMGp+vplMnTxIaGkqnTl1YErIUF1dXgoLGK9liamoqVatVp/1332lXObnYvu039uzeyYCBgwleuESrejqVq54Wh/yUVU/jFPUUGxtLXGwsPXr1ZtnyVQwdNpKLFy6weFGwVpo+5P7Vph9ZtXIl58+dI3DcOObMnUtcbCzTp0/XTpMOth3olp2fPHmK0NBQunTqxNKQJbi6ujA+KCjfvnz2nLk0adyYZSFL8Pf3Z+q06Up9eUpKKuXL+9Kje/f3rhuAYqYmJFyJ5p/BU7RKX8K5HDV2ryT2xDlOV2/BvZB1VFw5ndKNciZlbds1xWdeILemL+N0zVa8vhJFrX2/ULyM5Xtp08V7L3zbZvbu3kHfgcOYu3AZxsbGTAkak//47uRxVocup0OnH1gQshJnVzemqBlLNQr4hjUbtimOrlqMpY78dZFFYTvo1eZr1s8ci4dTOQbPXkpc/Gu16VPfpmFf1ooBHVtoHLes332Y7Uf+YFS39mwJDmJgpxaE7TnCb4dOFKgnN4U1Fo66cY1pE8fgV6U6cxf+xLxFy/m6WUv09cXyBYH2iAmID8DZ2ZlFixYpnfPz82Py5MlA5jKF5cuX07x5c0xNTZkxY8Z7f8fp06f5/PPPKVGiBA4ODgwePJikpCQlDTNnzqRHjx6UKlUKR0dHVq1apVTG48eP6dixI5aWlpiamlK9enXOnTun+Hz58uW4ublRvHhxvLy8CAsLU8p/69YtvvjiC4yNjfH19eXIkSNKn+ddgpG9zOTYsWNUr14dExMT6tSpQ3R0tFK+6dOnU7ZsWUqVKkWvXr0YO3Ysfn5+711H6sjIyGDvrm20++57avl/hrOLG0NGBBIX94pzf53WmG93+FYaBXxDg0ZNcXB0pu/A4RgZG3Ps8AGldEbGxlhYWioOExPtZuz37NxBuw5dqOVfF2cXN4aOGENc7CvO5qNpV/g2Ggd8TcPGATg6OtNv4FCMjIw4evigsiYjo/fWtHXXPr5p3ICmDb/C2bEcw/v1wtioOPuPHlebfvueA9Ss6keH1s1xcihHz87f4eHqQvi+Q4o0/0RFE1C/HlUqlsfWuizNmjTE3cWJG7duF6gH4Ne9R2jR4DO+/aouLuXsGNO7M8bFi7P3+Bm16X3dnRn0fVsa1a2JoaGhxnKL6etjJTFXHBKzUlrpySY8PJyApk1p3Lgxjk5ODBw0CCMjIw4fPqw2/a5du6hWvTpt27bF0dGRH374ATc3N/bs2QNk2sPOnTvp0KED/v7+uLi4MGLkSGJjY/nrzz+10rQjfCcBAU1o0qghTo6ODB7YHyNjIw4dPqI2/c7du6lerSrt2rTG0dGBrt93wd3NjV17c7xD6n/5JVWr+GFra4OzkxM/9u5FcnIy9+7d10rTxsN/0OqLGrT4vDqu9taM/6ElxsWLs+sP9RNQM/p0oH19f7wc7XCxLcvE7q3JyMjg/PU7SuleSOOZu3E3M/p8h0Gx93tkbd25h6+bNKRpw/o4OzowrP+PGBkZceDI72rT79i9P8vOW+DkUI4eXTri4ebCzr05/cDqsE3UrFaVPt2/x8PNFXtbG+rWqoGFxFxrXRkZGezeGU77Dp2p7V8HFxdXho0YQ1xsLGf/Um/vADvDt9MkoGlWn+BE/4FDMDIy4sjhnPswoOk3VKhYCWtrG9zdPejyQ3devXzJixfPC9S0a2c433XomGWXrowYMYq42Fj++kuzXYaH7yAgIIBGjRvj6OjEwIGDMDYy4nAuTS1btqJ9++/w9vbWWE7+mjop6mn4iNFZmgqup0aNm+Do6MSAPPXk7OzCuAkTqVXLH1tbOyr7VeGHrt05f+5cgRM1H3r/FtSPJCUlcfjwYXr37o2fnx8eHh4MGz6cG9evE3Xjhpb1pDttl61Ll+x8R3g4AQEBNG7cCCdHRwYNHIiRkTGHNPTlO3ftpnq1arRr2wZHR0e6/vA97m5u7N6T0282bFCfzp06UaWK33vXD8DLQ6e4OWkRz3cd1Sq9048deHPvMTdGzyEx6i4PftrIs+2HcBnSTZHGZWh3Hv3yG4/X7SDxxh2u9p/Eu+QUHLq10VqXrt57e3Zup32usdSQEWOJi81/fLcrfCuNA76mQePM8V2/gcMwMjJSHd99wFhq075jtKxfh2Zf+uNazpaxPTtgXLw4e078pTa9r5sTgzu3pnGd6hTX8PLuys17fFG9Ep9VrYBdGSsa1KpKrUo+XLv9QG16dRTmWHhN6DK+ad6aNu074ejkgn05R+p+/hWGhu83CS/4byMmIAqJyZMn06pVK65evUqPHj3eK++dO3cICAigTZs2XLlyhS1btnD69GkGDhyolC44OJjq1atz+fJl+vfvT79+/RQ/9hMTE6lXrx5Pnjxh9+7dREZGMnr0aORyOZA5GBoyZAgjRozgn3/+oU+fPnTv3p3jxzN/gMrlclq3bk3x4sU5d+4cK1asYMyYMVrpHz9+PMHBwVy4cAEDAwOl69+4cSMzZsxgzpw5XLx4EUdHR5YvX/5e9ZMfz5/FIJXGUdmvmuKcqWlJPLx8iI66pjZPWload27fVMqjr69PJb+qKnlOHT/KDx1bMLh/d8LWhpKakvIemnLcuE1NS+Lp5UP0jesFaMrJo6+vT2W/qkRHKec5efwYXTq0YlC/nqxf83OBmtLS0om+c5dqlSsqlV2tckWuR99Sm+da9E2qVa6gdK5mlcpcj76p+LuCtxdnzl/gZWwcGRkZXL7yD4+exFCjSqV89QCkpacTffchNSrmuPnp6+tTo6IPV2/eLTB/fjx69oJv+4yi9cBxTFzyM89exWqdNy0tjdu3bilNkOnr6+Pn56fxR0HUjRtUyTOhVq1aNUX6Z8+eIZVK8auSs3zF1NQULy8vbkRFaaXp1u3bVPWrrKSpip8f16Oi1ea5ERWlqqlqFY3fl5aWxv4DBzE1NcXVxblgTenp3Lj/lFrlc5bw6OvrU8vXjSu3H+aTM4eU1DTS373DzLSE4pxcLmfCqt/4IeAL3OyttSon9zXcvH2XapVz7E9fX59qfhW5Hq2+nq5H3aSqn7K91qjix7Womwo9Zy9cwsHeltETp9G6Sw/6jxjL6b/Ov5e258+eIZXG4eenbAOeXt5E5dMn3FbTJ/ip6ROySUl5w9Ejh7C2saF06fyXhyjs0i+vXXprtPVMTbeU8mRqqkJUVP4/mrUhp55y952FoykpKQkTExOKFSuWr6YPuX+16Udu3bpFenq6UrkODg6UKVu2wH5BF9sOdMvOs/vNKnnaoIqfn8b6vREVpTKxUK1aVa366cJCUtuPV78r/7h9eeQ0FrX9ANAzNMS8anleHcs18ZSRwavf/0RSuwraoov3XvZYqlKe8Z02Y6lKecZ3lf2qqdjTqePH+L5DSwb360HYmoLHd2np6UTde0SNCjmTc/r6+tSo4M3VWx8+bqnk6cKFf6J5EJM5mXbzwWMio+5Qx89X6zIKaywsk0m5GX0Dc3MJY0cMpFvn1owfM4Tr195veY9AoFu+8/+P6NSpE91zueTdvat9ZzRr1iw6d+7M0KFDAfDw8GDJkiXUq1eP5cuXY2xsDMDXX39N//79ARgzZgwLFy7k+PHjeHl5sWnTJl6+fMnff/+NpWWm2527e86Pg/nz59OtWzdF/uHDh3P27Fnmz5/PV199xdGjR4mKiuLQoUPY2dkBMHPmTJo2bVqg/hkzZlCvXj0Axo4dyzfffENKSgrGxsaEhITQs2dPRd1MnDiRw4cPk5io3k07m9TUVFJTU5XOvU1NpXie9WYyaRwA5nnWzEokForP8vI6IR65XI65RDXPk0c5P56+qNeAMmWtsbQqzf17dwhbs4onjx8xdsLUfLVLpZmuaxI1mrI/y0tCliZ1eR4/epSj6cv6mZosrbh//y7rV4fy5MkjAidodueMT0hALpdjmeeNrYXEnIePn6rNEyeTYSmRqKSPy+UuP/jH7gQvW0W7Hv0oVqwY+np6jBzwI5XLF/zQlCUk8k4uxzKPS6KFpBT3n8YUmF8T5T1cCOrfDUc7G2Kl8fyybQ99J85jY/BkTEsYF5g/Iauu8q7BllhY8OjxY7V5pFKpartZ5LR19r/qytRkD+o0SfLYq4VEwqNHmjTJsFBpPwlSqUzp3Nnz55k1Zx6pqalYWlowa/pUzM0LfrMve52c2X5mymvDLc1Lcf/ZywLzAyzZeoAyEjOlSYy1+09hUEyfjo3qaFVGbuITXme1XV47l/Dw8RO1eeJk6urJHGmWi7YsPp43b1L4ddtOunfpwI/dunD+YgSTZs1jwYzJVK5YXitt0qy+6EP6BBW7ydMnAOzbu5u1q0NJSUnBvpwD02bMyddLKFNTtl1K8pQvyUdTli2qyfMoj6YPIaee8pZvgaxATQXXUzbx8fFs/nUjAU2/1kLT+9+/2vQjUqkUAwMDlfgKFhIJ0jj1zy5VTRLl8ouw7TJ16Y6df8j1SqVSJBLV9Nr004WFkXVpUp+/UjqX+vwVhual0Dc2wtDCHH0DA1JfxOZJE4upl6vW36OL955Mgz2ZSywUevPyWsNYylxiwePc47svG1C2rDUWllY8uH+X9atX8eRJ/uM7xbjFXNmr0tK8FA+ePivwejTRtXljkt6k0H7ENPT19ZDLM+jXvhkBn9UsOHO2tkIaCz9/ljke27xpHd169sXF1Z0Txw4zadwIFv+0usD4ErpORoZYRvKpEBMQhUT16tULTqSByMhIrly5wsaNGxXnMjIykMvl3Lt3Dx+fzLfElSrlvKnT09PDxsaGFy9eABAREUGVKlUUkw95uXHjBj/+qLy+rW7duixevFjxuYODg2LyAcDf318r/bl12draAvDixQscHR2Jjo5WTHpkU7NmTX7/Xb1LdDazZs1iyhTlH9X9Bw2nQsVKrFi6QHFu/ORZWmn8EBo3bab4v5OzKxaWVkwaN4KYmCfY2uYEZTpx/CjLQxYq/g6aMrPQNDVp+q3i/84urlhaWBE0biQxMU+xtbXLJ+fHZ8feg1yPvsXM8aOxLluayGs3WLRyNVaWFlT3K9gLojCoUyXHy8PDqRzlPVxo2X8sx/66QPP62gcy/K/gV6kSP4UsJiEhgQMHDzNj9hyWLAhWGYR/bNbsO8Gh81dYNaY3Rlk/IK7ff8KvR86wafKg9wq8VZjI5RkA1KlVg3YtM/sDd1cXrkVFs/vgYY0TECeOH2NZyCLF3xOnaLeu/0P58qsGVKlSlbi4OMJ3bGXOrOnMnb9IKU7F8eO/szRkieLvyVPyn0j9FBw/foxlIYsVf08q5HoCSE5OYsqkCTg6OtKp8/eqmn7/nZCQEMXfeZ9DRYEuth3opp0LtEMX772Tx4+yPCRnfDdhSuGN7/KOpSwsLJk4bqTK+O5TcPTsJQ6e/ptpA7vhWs6Wmw8es2D9dkUwSnWcPH7kk4yFM7K8qJs0/ZYGjTJfSLq6eXAl8hLHjhzg+269C+V7Bf//EBMQH4C+vj4ZGRlK5/IGmtQmmq8mEhMT6dOnD4MHD1b5zNExJ8Jz3pl+PT09xRKLEiVKUFTk1pX9wyFb14cSGBjI8OHKu03cfRTLu3fv8PTKecOelpYZXCdeKsXS0kpxXiaT4uKqfoeHUmbm6OvrE58nIJFMJkVioTloU3ZU4GdPlR9QNWvVwStXxOBs25Cp1aQ+WrZZlqa8bxpkMikWGiaVADyz1unGPH2icQLC3MwMfX194vIE4pPK4rHM87YjG0uJhLg8gboy02e+XU5NfcvPG35lWuBI/LN2DHBzduL23fts2bm3wAkIiVlJiunrEydTDjgplb3G6j3W1hdEKVMTHO2sefzshVbpzbLqKu8bL5lUiqWGyPQWFqpviGRSqeKNXva/UqlUaYJQJpXiqkX09GxNeQNoSWUyjdHyLSwkirf4yuklSueMjY2xt7PD3s4OH29vuvf+kYOHj9Chfbt8NUlKmWS2X56Ak3Hxr7EqIObG+gOnWLPvJCtG9cTTwVZx/vLNe8S9TuLrkXMU597J5SzcvJ9Nh8+wb37+S8LMzUpltV1eO5fla+eq9RSv8IowNytFsWLFcHJUfsvj5GDP1eua3bJr1vJXiuCfX5/gWkCfoGKLMikWlsrtbmpqiqmpKXb25fDy9qFj+9b89edp6n2ZE229Vq3aisj0mZoy+06pVJZHkwxXV/VvThW2mMeTRiaTqWjShlq1/PNoyq6nvJry6zvNtO47k5OTmRg0nhImJowPmqw2oHKt2rXx8lbV9D73rzb9iIWFBenp6SQmJip5QUhlMhXduth2oJt2nlPu+1+vhYWFSoBKWT797Kcg9fkrjKyVdx4zsi5NWvxr5CmpvH0lRZ6ejlFZqzxprEh9puw5kRtdvPdq1qqjtPtCtp3ntad4LcZ3eTXFFziWyh7fPdU4AaEYt+QJOBkX/zrfwNgFsWRjOF1bNKZxncwXme6O9sS8jGPd7sMaJyBq1qr7ScbCFllllXNwVkpTzsGRVy/zjzMkEORGxID4AMqUKUNMTI5beEJCAvfu3fto5VetWpXr16/j7u6ucmg7s1+pUiUiIiKI0+C66ePjw5kzyoGEzpw5g6+vr+LzR48eKV3n2bNnP/CKcvDy8uLvv/9WOpf3b3UYGRlhZmamdBQ3MqKEiQm2dvaKw8HRGQsLS65EXlLkTU5O4lb0Dby81b+dNDQ0xM3dkysROXnkcjlXIy5pzANw725mcEULS+UHvYmKJie1mm5G38DLR/3yBIWmyMtKmq5EXMbLW/OShnt3MgP4afJ8ySzbAC83Vy5dyVmzJ5fLuXjlH3y91G9PWN7Lk0tX/lE6dyHiKr5Z2z6mv0snPf0d+nneVBcrpjpZp1aTgQFero78/U/Ojzi5XM7f/9ygoqf2bqMFkZySwpNnL7We1DA0NMTdw4PIrECr2boiIiLw9vFRm8fbx0cRmDWby5cvK9Lb2NhgYWGhVGZyUhLR0dH4aBHozdDQEA93dy5HXMmjKRJfDVtm+nh7ExGpvMXYpcsRBX5fhjxDq118DA0M8HG2UwogKZfLOX/jDpXcNW+Lt3b/SX7e8ztLR3TH10X5R/03daqwZepgfp0ySHGUkZjxQ9MvWDai4Lg6hoaGeLqr2vmlyKv4ath2z9fbk0uRymtZL0REUt7bU1Gml4cbj/IsVXr0JAbrMppjLJiYmGBnZ684HLP6hMhc93dmnxCFdz59gruaPiGygD4BMshAtR0zNdkpjkxNFkRGRihpio6O0mjrmZo8iMiVR3F/eKvPkx+a6ikiTz1poykyj6bIPJqSk5MImhCIgYEBQROnaHy2qtaT43vfv9r0Ix4eHhgYGCj1HY8fP+blixcq5epi2+Xo0i07z12uh7u72uvV1G4+3t5EROTtNy9r1U8XFrKzEVjVV/4RWrpBHaRnIwDISEsj/tI1StfP5bGqp4fVV/7Izl5GE7p472k7vtNuLKU8vrsScUmrsVR+kxSGBgZ4uzjw9z85MYXkcjkXrkVT0ePDxy0pb9NUvP6K6esrPPDU8anGwmWtbbC0Ks3TJ8pLap4+eUyZsu8Xp0kXkevw8f8N4QHxAdSvX5+1a9fSrFkzJBIJEydOLDB4zvswZswYateuzcCBA+nVqxempqZcv36dI0eOsHTpUq3K6NixIzNnzqRly5bMmjULW1tbLl++jJ2dHf7+/owaNYr27dtTpUoVGjZsyJ49e9ixYwdHj2ZGYm7YsCGenp507dqVefPmkZCQwPjx4//naxs0aBC9e/emevXq1KlThy1btnDlyhWNb2neFz09Pb5t0Zatm8OwtbPH2saWTWGrsbQsTS3/HJf7ieOGU9v/c75u1gqA5q3asWTBbNw8PPHw9GHvrm2kpKTQoFEAADExT/jjxDGqVa9FKTNz7t+7w+rQn/CtUAlnl/zfWuvp6dGsZWt+27wRW7tyWFvbsClsDZZWpamdS1NQ4Ehq1/mMb5q1BKBFq7YsXjAHdw9PPDy92bNrOympKTRs1CRL01NOHT9GtRq1KGVmxv17d1m96ifKa6GpXYtvmLX4J7zc3fDxcGPbnv2kpKTStOGXAMxcuJTSVpb8+EMnANo0a8qQ8VPYsnMPtatX5fc//iT6zh1GDMh0tzM1MaFyBV+Wr91A8eLFsSlbhoh/rnPo+CkG9PhBq7br+G0jpi1bg4+rE77uLmzZf5SU1Ld882VdAKYsXU0ZSwn9O7UGMgNA3XucOUGWnp7OyzgZN+8/ooSxEQ42ZQFYsn4rn1WvhE1pK15J4wn9bTf6+vo0fo+1lK1atWJBcDAeHh54enmxa+dOUlNTadSoEZAZT8XKykoR16RFixaMGT2aHdu3U6NmTU6ePMmtW7cYlOXRpKenR8uWLdm8eTN29vZYW1sTFhaGlZUV/nW0i3XQulVL5i9YiKeHO16enoTv2kVKSgqNGzUEYG7wAkpbWdGjW1cAWjZvzqixgWzbEU7NGtU5eeoPbt2+zdBBmYFtU1JS2LTlN/xr1cTS0pKE+AR279vHq9hYPv+srlaaOjf+nEk/b8XX2Z7yrg5sOnyGN6lvaf5ZZkCroNDfKCsxY1C7zHtq7b6TLN95hJl9OmBX2oJXWW+RTIyKY2JshKSkKZKSyp5kBsX0sTIvibNt/gEVs2nXshmzFy7Fy90Nb093tu/aR0pKKgENvwJg1oIllLayonfXzpn12vxrhgVO4rfw3dSuXo3f/zjNzdt3GTGwr6LM71q3YNrchVSq4EOVihU4fymCv85fYOFM7V3z9fT0aN6yFVs2b8LOzh5ra1s2hK3F0sqK2v459T0+cBT+derybVaf0LJVGxYumIu7hyeenl7s2hWu1Cc8i4nhj1MnqFK1GmbmEmJfvWTb1s0YFS9O9Rr527yenh4tWrZi8+ZfsbOzw8bahrCw9VhaWeHvn2OX4wLH4l+nDs2aNQegVavWLFgwP/P+yKWpUaPGijxxcXFIpVJinmZO3Ny/f58SJUoodkMqSNOWzZuwt7PH2tpGUU/+ueppXOBo/OvUpVmzFrnqaV6WJm927dqhVE/JyUkEjQ8kNTWVkaPG8CY5mTfJyQCYmZvn+zzX9v4NHDuWOnXq0Kx5dj3l34+YmprSuHFjQkNDKVWqFCYmJqxYvhwfHx+NP/h0ue2ydemSnbdu1Yr5Cxbg4eGR02+mptA4qw3mzQ/GysqKHt27Zepo0ZxRY8ayfccOataowYmTp7h16zZDBg1SlPn69WtevHhBbNbLnsdZ8WUsLCzyfRGQTTFTE0xzTdKauJTDrLI3b+PiSXkUg9f04RjbWxPZPdPj68GqzTj174z3rFE8Wrud0l/VxrZdU/5unrMl+L1Fa6i8eg6yi/8Q//cVnAd3xcC0BI/W7ShQTza6eu81a9mGrZs3YGdnT1lrW8VYqpbSWGpE1lgqc3zXolU7Fi+YjbuHl9JYKvf47tTx3xVjqQf37vCLlmOpTt80YMry9fi4OlLe3ZnNB37nTWqqwlNh0k/rKGshYUDHzPrJPW5JS3/HS6nquOXzqhVYu/MQNlaWuDrYEn3/EZv2/06zL7VbBp1dV4UxFtbT06Nl6+/YvHEtzi5uuLi6c/zYIZ48fsiocZO11icQiAmIDyAwMJB79+7x7bffYm5uzrRp0z6qB0SlSpU4efIk48eP5/PPPycjIwM3Nze+e499uIsXL87hw4cZMWIEX3/9Nenp6fj6+rJs2TIAWrZsyeLFi5k/fz5DhgzBxcWFNWvW8OWXXwKZy0zCw8Pp2bMnNWvWxNnZmSVLlhAQEPA/XVvnzp25e/cuI0eOJCUlhfbt29OtWzfOn3+/KPL50aptB1JS3rA8JJikpER8fCsSNG2O0iz7s5inJCTkuGZ/9kV9EuLj2bxhLVJpHC6ubkycOkfhdmZoYEhkxEX27NpOasobSpcpi3/dz2nXQXXdojpat+1ASkoKP4UsICkxEZ/yFZk0dZaqpvgcTZ/X+4qEhHg2ha1FKs10e5w0dbZCk4GBAZERlzIfpikpCk3tO3YpUE/9z+sgS0hgzabfiJPKcHdxZu6kQEWgyeevYtHTz3GQquDjRdCIQfyyYQs/h23G3s6G6YGjcHXKGThNHDmE0PWbmLEghITERKzLlKFXlw40D2ikVR01qlMDWcJrQn/bTawsAQ/nciwcN1jhyvjsVZzSW4GXcTJ+GD1N8ffGPYfZuOcwVXw9WT55JAAv4qRMXPwz8a+TkJiVpLK3Oz/PGIvFe2zFWa9ePRLi4wnbsAFpXByubm5MnTZN4Yb78sULJc8PX19fRo8Zw/p161i7di329vYEBQXh7OysSNO2XTtSUlIIWbKExMREypcvz9Rp07T2cPryi8+Jj49n/YaNSKVSXF1dmTF1So6mly+VNJX39WHsqJGsC9vA2nXrsbO3Y9KE8Tg7OwGZ9/vjR4+ZduwYCfEJlDIzw9PDg+C5s3F2ctJKU5NalZC+TmT5zqPExr/Gy9GWpcO7Y5UVoOtZrExJ09bjZ0lLf8eoZRuVyvmxRQP6tmyo1XcWxFef10UWn8CajZuRSmW4uTozZ8p4xRKMFy9foa+X2869GT9yCKs3bOaX9Zuwt7Nl6vjRuOSy88/9azGsf282bQ1n6ao1ONjbMSVwJBXLv99b4zZtvyMlJYWlIYtISkzEt3wFpqj0CTEkxOcsS/q83pfEJ8jYGLYuq93dmDJ1pqLdDYsbcu3aVXbv2kFiYiISiQXlK1RkbvBilaCl6mjbNssuQ5ZkaSrPtKnTlTTF5OmnvqhXj/iEeDaEhSlscerU6Upu6gf272PTppx2HjM68/4cOmy40o9d9fXUPktTTj1NnTpTTT3l1vRllqb1uTTNUGi6ffs20dGZ3la9e3ZT+r5f1qzH2tom/3rS4v6NiYkhPiGn7QrqRwB+7NMHPX19ZkyfTlpaGtWqVaP/gAH5alFo0sG2A92y83r1viA+IZ6wsA2K650+daqi3BcvX6Knr9yXjxk9inXrw1i7dh129vZMDJqg1Jf/dfYsCxYuUvw9a07mkrHOnTrxfZfOBdaPebUK+B/L2QLdd/44AB6t38GVnoEY2ZahRK6laW/uP+bv5n3wDQ7EedAPpDx+xtU+E3h1JGdrxZitByhexhLPSYMxsilDQuQNzn/bi7cvtN8BCnTz3mulZiw1cersfMdSn9X7ivgEGb+Grck1lpqTayxlyJWIi+zdtZ0UxfjuC63GUo38qyFNeM2qbXuJlb3G08mexWMHKMYtz19JlZ57L6XxdAmcrfh7w95jbNh7jKo+HqyYOBSAkd3as/K3vcxdsxlpfCKlLcxp1eAzerUpOAi8al193LEwQLOWbXn79i2rQ5eR+Po1zi5uTJo+/5PHyhD8u9HL0MY/WiAoRBo1aoSNjQ1hYWEFJ87F9dvqd2woSvT1dM9RyjxN87rPosI4Nb7gRJ+YuFIORS1BLcXk6UUtQYUyL/4pONEnRlZa/fKhoiSp2MeLX/Kx0OddUUtQS4YOrgjV19O9utLFKO1yPp4H6MfCkLdFLUEt172/KWoJKnhGHS5qCSqk6+D7Ubv4j7M97cfkiZn2W3N+SnzdP20Q9I/F2SjdG5tmU9tb98YT/wu6d4cL/l+TnJzMihUraNKkCcWKFePXX3/l6NGjHDlypKilCQQCgUAgEAgEAoGgENG9Vw7/AZo2bUrJkiXVHjNnFt6WjbqAnp4e+/fv54svvqBatWrs2bOH7du307Dhx3G5FggEAoFAIBAIBAKBbiI8IIqAn3/+mTdv3qj9TJugRf9mSpQooQh0KRAIBAKBQCAQCARFjS4ucfv/ipiAKALs7UWgFoFAIBAIBAKBQCAQ/LcQSzAEAoFAIBAIBAKBQCAQFDrCA0IgEAgEAoFAIBAIBP9ZMhBLMD4VwgNCIBAIBAKBQCAQCAQCQaEjJiAEAoFAIBAIBAKBQCAQFDpiCYZAIBAIBAKBQCAQCP6ziF0wPh3CA0IgEAgEAoFAIBAIBAJBoSMmIAQCgUAgEAgEAoFAIBAUOmICQiAQCAQCgUAgEAgEAkGhIyYgBAKBQCAQCAQCgUAgEBQ6Igil4F+Lnl5GUUtQwTgjuaglqBBrYFPUElQwNLQqagkqGJBW1BLU8kbPtKglqPDMxq+oJaggzyhW1BJUkOvgHL8eutdvAughL2oJ/woydNCmjOVJRS1BhbRiRkUtQS2eUYeLWoIKN70bF7UEFcrf2FPUElR4bu5Z1BJUKPvmQVFL0IBdUQsQ6DhiAkIgEAgEAoFAIBAIBP9ZMhC7YHwqdG8qXSAQCAQCgUAgEAgEAsH/O8QEhEAgEAgEAoFAIBAIBIJCRyzBEAgEAoFAIBAIBALBfxa5boZI+n+J8IAQCAQCgUAgEAgEAoFAUOiICQiBQCAQCAQCgUAgEAgEhY5YgiEQCAQCgUAgEAgEgv8sYheMT4fwgBAIBAKBQCAQCAQCgeA/RFxcHJ07d8bMzAyJRELPnj1JTEzMN/2gQYPw8vKiRIkSODo6MnjwYOLj49/re8UEhEAgEAgEAoFAIBAIBP8hOnfuzLVr1zhy5Ah79+7l1KlT/PjjjxrTP336lKdPnzJ//nz++ecf1q5dy8GDB+nZs+d7fa9eRkaGiPkp+Fdy486TopagQomMpKKWoEIiZkUtQQVDvbSilqCCgQ5qAnibYVTUElQorpda1BJUkGcUK2oJKrxD9zQV411RS1CLHvKilqCCnp7uDY900c6N5MlFLUGFtGK612+CbrbfTe/GRS1BhfI39hS1BBXe6hkXtQQVLN/o3jgYoHQF/6KW8EGcvKZ7fVk2td2LkZqqPPYyMjLCyOjD+7obN27g6+vL33//TfXq1QE4ePAgX3/9NY8fP8bOzk6rcrZu3UqXLl1ISkrCwEC76A7CA0IgEAgEAoFAIBAIBAIdZNasWZibmysds2bN+p/K/Ouvv5BIJIrJB4CGDRuir6/PuXPntC4nPj4eMzMzrScfQAShFAgEAoFAIBAIBAKBQCcJDAxk+PDhSuf+F+8HgGfPnlG2bFmlcwYGBlhaWvLs2TOtynj16hXTpk3Ld9mGOoQHhEAgEAgEAoFAIBAI/rNkZOjp7GFkZISZmZnSoWkCYuzYsejp6eV7REVF/c/1lZCQwDfffIOvry+TJ09+r7z/GQ+IL7/8Ej8/PxYtWlTUUv7fcP/+fVxcXLh8+TJ+fn5q05w4cYKvvvoKqVSKRCL5pPoEAoFAIBAIBAKB4L/CiBEj6NatW75pXF1dsbGx4cWLF0rn09PTiYuLw8bGJt/8r1+/JiAggFKlShEeHo6hoeF7afzPTEAINPP/bZIgIyODXzes5cjBfSQlJeLtW4G+A4ZiZ18u33z79+wkfPsWZNI4nF3c6N1vEJ5ePorPx48ZxrWrkUp5mjRtRr9BwwrUtHvvPrZt30GcVIqriwv9+/bB28tTY/pTf5xm3YYNPH/+Ans7O3p270bNGplrtNLT01m7fgN/X7hAzLNnmJqaUsWvMj27dcXKyqpALdlkZGSwecNqjh7aS3JSIl4+FflxwPAC6+nA3nB2bd+sqKeefYfgkauepHGxrF+9nCuXL/LmTTJ25Rxo8933+Netp7WuTRvWcfjgfpKSEvHxLU+/AUMK1LVvzy7Ct/+GVBqHi4sbP/YbiKeXt+LzZSELibx8ibi4WIyNS+Dt60u37r0p5+ColaYNYWEcPHiQpKQkfH19GTBwIPb29vnm27NnD9u3bUMqleLi6kq/fv3w8vJSfP727VtCQ0M5dfIkaWlpVK1WjQEDBmBhYaGVJl2zc12tp40b1nPo4AGFPfUfMLhATXv37GbH9q1Z9uRKn34D8Mqyp9evE9i4IYzLly7y8uULzM3Nqe1fhy7fd8PU1LRATdm6Nm1Yy5EsO/f2raClne9kZ5adO7u48WO/QUp2nrv8qRMDuXTxbwInTKF2nc+00qRrdZWRkcGGDWFZmpLw8fVlwIBBWmnavj3Lplxc6duvv5JNHTiwn5MnjnP79h3evElmy2/bKFmyZIF6FJqEnReoadfe/WzdEU6cVIabizMD+vTO97l38vQZ1m3YxLPnL7C3s6VXtx+oVSNnbfL6jb9y4o/TvHz5CgMDAzzc3ej+Qxd88ilTHYXVfgf27+fEiRPcvn2bN2/e8NvWre9lU7rUfpafVcd1RE/Mq1bA2K4sF9r05/nuY/nn+aImvvPHUtLXg5RHMdyetZzH68OV0jj164Tr8J4Y2ZQh4UoU14ZOI/7vq1rUUCYfcywFELZxEydOneLly1cYGhjg7u5O9x++x9vbS2OZ6shsv3UcztN+2oxbctrPjT79Bij150tDFimNW3x8fenavRcOBYxbth84yqZdB4iTxePu7Miwnl3w9XBVm/buwyf8vHkH0Xfv8+xlLIO7d+S7b5sopVm/Yy8nz17kwZMYjIobUtHLnX7ft8fJ3lbLGhJ8SsqUKUOZMmUKTOfv749MJuPixYtUq1YNgN9//x25XE6tWrU05ktISKBJkyYYGRmxe/dujI3fP0CrWIIh+H9H+LbN7N29g74DhzF34TKMjY2ZEjSGt2/fasxz+uRxVocup0OnH1gQshJnVzemBI1BJpMqpWsU8A1rNmxTHF17Frzm6cSpP1gV+jOdO3Vk2ZJFuLq4MD5oIjKZTG36a9dvMGvuPAIaN+anJYup41+bKdNncP/+AwBSU1O5fecOnTp+x7Ili5g4PpDHj58waep07SsJ2LntV/bv2UGfASOYtWAFxsbGTAsaydu3mnc4OHPqd9aGLqN9p67MWxKKk4sb04JGEp+rnkIWzOTpk0eMnTiTBcvWULvOFyyYPZm7d25qpWvHti3s3R1Ov4FDmLdwKUbGxkwKGptv+/1x8ji/hK6gQ6fvWRiyAmdXVyYFjVVqPzd3DwYPG8WylauZMn02ZMDECWN4967gXQG2bd3K7t27GThoEAsXLcLY2JigCRPy1XTy5ElCV62iU+fOhISE4OriQtCECUrtvmrlSs6fO0fguHHMmTuXuNhYpk/Xrh11zc5BN+tp+7bf2LN7JwMGDiZ44RKMjY2ZGBSYr6ZTJ0/wc+hKOnbqwuKQn3BxdWVi0DhFPcXGxhIXG0uPXr1ZtnwVQ4eN5OKFCyxeFKyVJoAd2zazb3c4/QYOZd7CpRgbGzNZCztfHbqC7zr9wIKQFbi4ujFZTfsB7N65HT09Pa31gG7W1bZtW9mzexcDBg5mwcIsmwoaX4Cmk4SGhtKpUxeWhCzFxdWVoKDxSjaVmppK1WrVaf/dd9pVTm5Nws4L1HPi1GlW/ryaLh07sHzxAlxdnAmcOAWppufejShmzg0moFFDli9ZQN3atZg8Yzb3sp57AOXs7RjY90dWLVvMwrmzsLYuy9igycjec//5wmq/1NRUqlWvzncdOryXHtC99itmakLClWj+GTxFK/0lnMtRY/dKYk+c43T1FtwLWUfFldMp3Shn4tO2XVN85gVya/oyTtdsxesrUdTa9wvFy1hq9R0feywFYG9vx4C+fVm5bCnB8+ZgY12WwKCJ721T27dtYe/unfQfOIT5C0O0ar8/crXfopDlWe0XqNSfu7t7MGTYSH5a+QtTps8iIyODiRPG5jtuOXrmHCFrN9OjfUtWz5uCu5MDw6fNRxqfoDZ96ttU7KzL0K9LO6wk5mrTRFyLonVAfVbNCmLRpFGkv3vHsKnzeZOiezti/S9kZOjuURj4+PgQEBBA7969OX/+PGfOnGHgwIF06NBBsQPGkydP8Pb25vz580Dm5EPjxo1JSkril19+ISEhgWfPnvHs2TOtxtPZ/KcmIORyOaNHj8bS0hIbGxul9SoLFiygYsWKmJqa4uDgQP/+/UlMTFR8/uDBA5o1a4aFhQWmpqaUL1+e/fv3a/W9//zzD02bNqVkyZJYW1vz/fff8+rVKyDT+6B48eL88ccfivRz586lbNmyPH/+HIBHjx7Rvn17JBIJlpaWtGjRgvv37yt9x+rVqylfvjxGRkbY2toycOBAIHOZhJ6eHhEREYq0MpkMPT09Tpw4wf379/nqq68AsLCwQE9PT+G2c/DgQT777DMkEglWVlZ8++233LlzR+X6oqKiqFOnDsbGxlSoUIGTJ0/mWx+nT5/m888/p0SJEjg4ODB48GCSkj7O9pUZGRns2bmd9h26UMu/Ls4ubgwZMZa42Fec++u0xny7wrfSOOBrGjRuioOjM/0GDsPIyIhjhw8opTMyMsLC0lJxmJgU/BZoR/hOAgKa0KRRQ5wcHRk8sD9GxkYcOnxEbfqdu3dTvVpV2rVpjaOjA12/74K7mxu79u4FwNTUlNkzplHv889xKFcOH29vBvTrw63bt1VcqfKrp727ttL2u++p6f8Zzi5uDBoxDmlcLOfzqac94b/RMOBb6jf6GgdHZ/oMHIGRsTHHDufcC9E3rtG0WWs8vHywsbWjbYcfMDEtyd3bBU9AZGRksHvnDtp36Ext/7q4uLgybMQY4mJjOfvXGY35doVvp3HA1zRsHICjoxP9Bw7FyMiIo4cPKtIENP2WChUrYW1tg5u7B51/6M6rly958eJ5gZp27txJhw4d8Pf3x8XFhREjRxIbG8tff/6pMV94eDgBTZvSuHFjHJ2cGDhoEEZGRhw+fBiApKQkDh8+TO/evfHz88PDw4Nhw4dz4/p1om7cKFCTrtm5rtbTrp3hfNehE7X96+Di4srwEaOJi43lr3zsaWf4dpoENKVR4yY4OjoxYOAQjIyMOHL4EADOzi6MmzCRWrX8sbW1o7JfFX7o2p3z585p9QDObL8dtMvVfkNHjCEu9hVn822/bbns3Jl+auwc4O6d2+zasZVBQ0cVqCW3Jl2rqxxNHbNsypURI0ZlacrPpnYQEBBAo8aNcXR0YuDAQRgbGXE4SxNAy5ataN/+O7y9Vb1HCtIk7Lzgttu+cxdNmzQmoFEDnBwdGDKgH0ZGRhw6ov4tevjuPdSoVpX2bVrh5OBAt+874+7myq69Oc+W+l/Wo6pfZWxtbHB2cqRvrx4kJydz9979fLXkravCaD+Alq1a0b59+w+yKV1rv5eHTnFz0iKe7zqq1TU4/diBN/cec2P0HBKj7vLgp408234IlyHdFGlchnbn0S+/8XjdDhJv3OFq/0m8S07BoVsbrb7jY4+lAOp/+SVVq/hha2uDs5MTP/buRXJyMvfe06Z27wzPGrfU0Xrckt1+OeMW5fYDCGj6jWLc4u7uQRctxi1b9hyiWcN6fFP/c1wc7BnVpytGRsXZe+yU2vQ+7q4M7NqBhp/VxtBQvWP8gqCRfFP/c1wd7fFwdmT8wF48fxVL9J372lWSQGfZuHEj3t7eNGjQgK+//prPPvuMVatWKT5PS0sjOjqa5OTMLUovXbrEuXPnuHr1Ku7u7tja2iqOR48eaf29/6kJiHXr1mFqasq5c+eYO3cuU6dO5ciRzI5LX1+fJUuWcO3aNdatW8fvv//O6NGjFXkHDBhAamoqp06d4urVq8yZM0cr1zqZTEb9+vWpUqUKFy5c4ODBgzx//pz27dsDmbEphg4dyvfff098fDyXL18mKCiIn3/+GWtra9LS0mjSpAmlSpXijz/+4MyZM5QsWZKAgADFzOry5csZMGAAP/74I1evXmX37t24u7trVScODg5s374dgOjoaGJiYli8eDGQOSAaPnw4Fy5c4NixY+jr69OqVSvkcuX92keNGsWIESO4fPky/v7+NGvWjNjYWLXfd+fOHQICAmjTpg1Xrlxhy5YtnD59WjFh8r/y/FkMUmkclfyqKc6ZmpbE08uH6BvX1eZJS0vjzu2bSnn09fWp7FeN6CjlPKeOH+P7Di0Z3K8HYWtCSU1JyVdPWloat27fpqpfZaWyq/j5cT0qWm2eG1FRVMkTU6Na1SrcyCdgTFJSMnp6ephq6e75/FkMMjX15OHlQ3TUNY3Xoq6eKvlV42auPF4+5fnz1HFev05ALpdz+uQx0t6+pXxFPzWlquqSSuOo7FdVSVdB7Xf79k38cuXJbL+qREWpz5OS8oZjRw5ibWND6dL5u6k9e/YMqVSKX5UquTSZ4uXlpbFN0tLSuH3rllJsFH19ffz8/BQ/Jm7dukV6erpSuQ4ODpQpWzbftgbds3PQ1Xp6hlQap2QbmZq8Nf6oy7SnW/j55XxfpqYqREVp/iGYlJSEiYkJxYoVy1dTpq4Ps/M7t28q5cm289ztl5qSQvDcGfTpPxgLS+3eLGZq0r26UtiUX16b+viatEXYecFtl5aWxs3bd6jqV0mp7Kp+lTU+965HRSulB6hetQo3NKRPS0tj/8HDmJqa4ObiolFLXgqr/f4XdK39PgRJbT9e/f6X0rmXR05jUdsPAD1DQ8yrlufVsVyTPBkZvPr9TyS1q1AQn2IslZaWxv4DBzE1NcXVxblATdnktJ+yTXl6eRNVwLglb3/ul6c/z01KyhuOHjmU77glLS2d6Dv3qVHJV6nc6pXK889N1ReIH0pS8hsAzEppt+RQoLtYWlqyadMmXr9+TXx8PKtXr1b6fevs7ExGRgZffvklkPm7NSMjQ+3h7Oys9ff+p2JAVKpUiUmTJgHg4eHB0qVLOXbsGI0aNWLo0KGKdM7OzkyfPp2+ffvy008/AfDw4UPatGlDxYoVgczgHdqwdOlSqlSpwsyZMxXnVq9ejYODAzdv3sTT05Pp06dz5MgRfvzxR/755x+6du1K8+bNAdiyZQtyuZyff/5Z4U67Zs0aJBIJJ06coHHjxkyfPp0RI0YwZMgQxXfUqFFDK33FihXDMmuQWrZsWaUYEG3aKM9Kr169mjJlynD9+nUqVKigOD9w4EBF2uXLl3Pw4EF++eUXpQmcbGbNmkXnzp0V9e3h4cGSJUuoV68ey5cv17iOKDU1ldRUZVevt6mpFM8TAVYmjQNAkmfNrLnEAmnWZ3l5nRCPXC5Xm+fxo4eKv7/4sgFly1pjYWnFg/t3Wb96FU+ePGLshKlqy4VMVyW5XI5Eoly2hUTCo0eP1eaRSmVY5InFYSGRIJXK1KZ/+/Ytv6xZy5f1vsDUxESjltzk1JPyDxRziYXis7xk1tM7lWsxl1jwJFc9jRg7meA5U+jWoRnFihXDyMiY0ROmY2uX/1pIAKlUmqVL+TskEonG9kvQ0H4SiQVP8szG7t+7i7WrQ0lJScG+nANTZ8wtMHBOtqa867AlFhaKz1Q1Zba7ujyPHj9WlGtgYKAykWkhkSCNU3+t2eianWdfD+hWPUkV9SRRLl9igawATers6bGG2f34+Hg2/7qRgKZf56snR5cmO8+vrjTbeW5dv4T+hLdPeWr519VKS44m3aurHJvKq0lSoE2pXofkvd7OFKxJ2Lkm4hNeZ16vynPMXHG9qtcgU4lBZSExJy7P8qKz5/9mxtxgUlNTsbSwYM60KZibm+WrR/l7Cqf9/hd0rf0+BCPr0qQ+f6V0LvX5KwzNS6FvbIShhTn6BgakvojNkyYWU6+Cx9OFOZY6e/48s+bMy7QpSwtmTZ+Kubn6pQjqv0f981ib/lzFptS03769u5XGLdNmzNE4bpG9fs07uRzLPEspLM3NePgkRutryg+5XM7iNZuo5O2Bq2PB47p/E3Leb9mi4MP5z01A5MbW1lbhsn706FFmzZpFVFQUCQkJpKenk5KSQnJyMiYmJgwePJh+/fpx+PBhGjZsSJs2bVTKU0dkZCTHjx9X6y1x584dPD09KV68OBs3bqRSpUo4OTmxcOFCpfy3b9+mVKlSSnlTUlK4c+cOL1684OnTpzRo0OBDqiRfbt26xcSJEzl37hyvXr1SeD48fPhQaQLC399f8X8DAwOqV6/ODQ2z9pGRkVy5coWNGzcqzmVkZCCXy7l37x4+Pj5q882aNYspU5TXIvYfNIyKlSqzPGSB4tyEKbPe/0K1pEnTbxX/d3ZxxcLCkonjRhIT8wRb2/wDRRUW6enpzJg1B8hg0ID+GtOdOn6ElUtz1n2Omzy70DT9GvYLyYmJTJqxADMzc86fPU3w7MlMn7sEJ2c3pbQnjh/jp5Ace584ZUah6QKo91UD/KpUIy4ujp07tjJ31jTmzF9M8eLFFWmO//47ISEhir/z2l1RcPL4UZ2zc12sp+PHj7EsZLHi70lT3i8uyoeQnJzElEkTcHR0pFPn79WmOXH8KMtz2XnQlJlq0/2vnDv7J1ciI1gYsrLAtLpYV8eP/87SkCWKvydPyX/S61Mg7DwTbez8U1C5UkVWLFlIfEICBw4dZvqceSwJnqvyQzMb0X6Z6Er76SJ+lSrxU8hiEhISOHDwMDNmz2HJgmCNQdlPHD/GspBFir8nFnL7fflVA6pUqUpcXBzhO7YyZ9Z05s5fpDRu+ZQEh4Zx9+Fjls8YXyTfL/j/wX9qAiLvjKGenh5yuZz79+/z7bff0q9fP2bMmIGlpSWnT5+mZ8+evH37FhMTE3r16kWTJk3Yt28fhw8fZtasWQQHBzNo0KB8vzMxMZFmzZoxZ84clc9sbXOix/6ZtfYwLi6OuLg4RYTixMREqlWrpvSDPZsyZcqgr5//KprszzNyRTBJS0vLN082zZo1w8nJidDQUOzs7JDL5VSoUCHfoDoFkZiYSJ8+fRg8eLDKZ46OmqP6BgYGMnz4cKVz9x6/4t27d0oR/NPSMrXJpFIsLXN2hIiXSXFxVb8spZSZOfr6+ipvGuJl0nxdmD29M7/32dOnGicgzMzMMsvO8xZHKpNpjGxuYSFRCdSVmV6idC49PZ0Zs+fw/OUL5s6cka/3Q41adZV2qsi2AZk0Dos89eScbz0VU7mWeJlU4UnxLOYJB/aGs/CntTg6ZbrFOru6c/2fKxzcu5M+A0co5a1Zy18p4nO6Qpdy+8lkMlxdlScvsjHT0H4ymRSJpXIdm5qWxNS0JHb25fDy9qFT+1b89edp6n1ZX5GmVu3aeOVaw5tdV1KpVOEtlK3R1U2Tpsx2z/v2QyaVYpnV7hYWFqSnp5OYmKg0QSmVyVTsrmatOjpn57pYT7Vq+SsiwOfWJJPK8tiTFBeN9mSm0Z7yfl9ycjITg8ZTwsSE8UGTMTBQ/0itWasOXmrvv7x2np8uzXaeretq5GWexTylU7vmSmnmzJyCb/mKzJiTM4mli3VVq1btPJoy7Vyqokmm0QsxR5MsjyYZFpbq+9z8EHauvZ1nY25WKvN6VZ5j8fk+9/IGE5TK4rHM88a7hLEx9na22NvZ4uvtRdfe/Th4+Cgd27dVW+6nar/3Qdfb70NIff4KI+vSSueMrEuTFv8aeUoqb19JkaenY1TWKk8aK1KfKXtOqKMwx1LGxsbY29lhb2eHj7c33Xv/yMHDR+jQvp3acvOOW/Lrzwsat6jYlEyq0k+ZmppiamqqGLd0bN9aZdySjaRUKYrp6xMnUw6iGRefoOIV8SEEh4bx58VIlk0LpKyV9kv8BIK8/KdiQGji4sWLyOVygoODqV27Np6enjx9+lQlnYODA3379mXHjh2MGDGC0NDQAsuuWrUq165dw9nZGXd3d6Uje5Lhzp07DBs2jNDQUGrVqkXXrl0V3gZVq1bl1q1blC1bViW/ubk5pUqVwtnZmWPH1Ad2yt6GJSYmx/Uqd0BKQDGLmjsoUWxsLNHR0UyYMIEGDRrg4+Oj0ZXs7Nmziv+np6dz8eJFjZ4MVatW5fr16yrX4u7unu9srpGREWZmZkpHcSMjSpiYYGtnrzgcHJ2xsLDkSuQlRd7k5CRuRt/Ay8dXbdmGhoa4uXsq5ZHL5VyJuISXt/o8APeyAnLm9+PN0NAQD3d3LkdcUSo7IiISXw3bPPl4exMRqbwN4qXLEfjkGkRlTz48efqU2TOmY2aWvwtqZj2VUxwOjs5ILCy5mqeebkXfwMu7vMZrcXP35GrERaVruRJxCc+sPKmpmbEC9PNE39cvpq8SOwTAxMQEOzt7xeHg6ISFhSWRkZeVdBXUfu7unkSqtN9lvPNpP8gggwzFpIeyJjvF4ejoiIWFBZG57pvkpCSio6OV2kRFk4eHUp7Mdo/AO+ve8PDwwMDAQOl+fPz4MS9fvFApVxftXBfrKa89OWbZU0Qee4qOjlKUr1aTuweRkcqaIiMi8PbOyZOcnETQhEAMDAwImjgl3/7LRKX9nP6H9su5lmw7z26/Nu06snhZKIuWrlIcAD1692PwMOWAlLpYV6o25ZRpU7nK11ZTRB5NEXk0aYuwc+3tPHfZnu5uXI5Ufu5djryi8bnn6+2l9JyE7Ode/tshZmTI832p8qna733Q9fb7EGRnI7CqX1vpXOkGdZCezdSXkZZG/KVrlK6f4zGLnh5WX/kjO3uZgiissZQ6MuQZWtiUavupjlui8C5g3JK3P4/M1Z9rUEcGmvUZGhrg5ebMhas5cSTkcjkXr1yngqf6yRBtyMjIIDg0jFPnL7Jk8mjsrAve4lEgyI//lAeEJtzd3UlLSyMkJIRmzZpx5swZVqxYoZRm6NChNG3aFE9PT6RSKcePH9f4Izs3AwYMIDQ0lI4dOyp24Lh9+zabN2/m559/BqBLly40adKE7t27ExAQQMWKFQkODmbUqFF07tyZefPm0aJFC6ZOnUq5cuV48OABO3bsYPTo0ZQrV47JkyfTt29fypYtS9OmTXn9+jVnzpxh0KBBlChRgtq1azN79mxcXFx48eIFEyZMUNLo5OSEnp4ee/fu5euvv6ZEiRJYWFhgZWXFqlWrsLW15eHDh4wdO1btNS5btgwPDw98fHxYuHAhUqmUHj16qE07ZswYateuzcCBA+nVqxempqZcv36dI0eOsHTpUm2aK1/09PRo1rINWzdvwM7OnrLWtmwKW4OlVWlq+edsBxUUOILadT7jm2atAGjRqh2LF8zG3cMLD09v9uzaTkpqCg0aBQAQE/OEU8d/p1qNWpQyM+PBvTv8suonyleohLNL/p1661Ytmb9gIZ4e7nh5ehK+axcpKSk0btQQgLnBCyhtZUWPbl0BaNm8OaPGBrJtRzg1a1Tn5Kk/uHX7NkMHZQbqTE9PZ9rM2dy+c4epkyYifycnLi5zcqhUqZIFxjTIrqdvW7Rj2+b12NqVo6yNDb+GrcbC0oqauepp8rhh1PT/nK+btQagWav2hCyYhZuHNx6e3uzdtY3UlDfUb9QUAPtyTtjY2bNiaTBde/anlJkZ5/86zZXLFwicVPCyDz09PZq3bM1vmzdiZ2ePtbUNG8PWYmllRe1ca9onBI6idp26fNusZVb7tWHRgrm4e3jh6enF7l07lNrvWcxT/jh1gipVq2Nubs6rV6/YvnUzRsWLU61GzQI1tWzZks2bN2Nnb4+1tTVhYWFYWVnhX6eOIl3g2LHUqVOHZlnxW1q1asWC4GA8PDzw9PJi186dpKam0qhRIyDzrUbjxo0JDQ2lVKlSmJiYsGL5cnx8fAoc1OqinetqPbVo2Yotmzdhn2VPG7LsyT+XPY0LHI1/nbo0a9YCgJat2rBwwbxMTZ7e7Mqyp4aNMvdGT05OImh8IKmpqYwcNYY3ycm8yYoQbWZuXmCAt8z2y7RzW7tyWFvbKNqvtlL7jcxqv5ZZ7deWxQvm4O7hqdR+2bqydy3JS5kyZbG2yX+/dl2sq2xNmzf/ip2dHTbWNoSFrc/SlGNT4wLH4l+nDs2aZdtUaxYsmJ+lyYtdu8JJSU2hUaPGijxxcXFIpVJisl423L9/nxIlSlC2bFmVJY95NQk7L7jt2rRswdyFi7Oeex6E79pDSkoKTRpmLhedE7yI0lZW9OyWuRygVfNmjBg7nq07dlKrRnVOnPqDm7fvMHRg5tLCNykpbNqyFf9aNbGytCA+IYHdew/wKjaOLz7TPt5JYbUf5NjU0w+wKV1rv2KmJpi653ilmriUw6yyN2/j4kl5FIPX9OEY21sT2X0MAA9Wbcapf2e8Z43i0drtlP6qNrbtmvJ38z6KMu4tWkPl1XOQXfyH+L+v4Dy4KwamJXi0bkcBrZbJxx5LpaSksGnLb/jXqomlpSUJ8Qns3rePV7GxfP6eNtU8q/0yxy22ivbLPW4ZHzgK/1zjlsz2m4u7h6dSP5Xdfs9iYrLGLdUwM5cQ++ol27LGLdXzGbd816wJM0JC8XZzwdfDld/2HiYlNZVv6v8fe/cdFdXxNnD8uyBdqRZ67zbsYu8libHG2GvsJUZN7L0be4+9YIuKith7ixqNYgfFjiJSdumdff8AFhZ2gRQDvzfzOWeP7u7M3WfvnTs7zJ2Z2xCAOas2UtbUhGG9Mkd4pKam8Srkfeb/09IJj5Ty7NUb9HV1sbaoAGSOfDh79QYLJ36Pvp4ukVkjzErr66OjUzxTQYT/baIDAqhatSrLli1j0aJFTJo0iUaNGrFgwQL69OmjSJOens6IESMICQnB0NCQNm3aKK3VoI6lpSXXr19nwoQJtGrViuTkZOzs7GjTpg0aGhrMmTOHN2/e4J91WyALCws2btxI9+7dadWqFVWrVuXKlStMmDCBTp06ERsbi5WVFc2bN1dc9e7bty9JSUksX76c8ePHU7ZsWbp0yRmOuHXrVgYOHEiNGjVwc3Nj8eLFtGqV0xCzsrJi1qxZTJw4kf79+9OnTx+2b9/Ovn37GD16NJUqVcLNzY1Vq1YpVkHNbeHChSxcuJCAgACcnZ3x8/OjbNmy+dJB5jocly9fZsqUKTRs2BC5XI6TkxPf/oV7savTsUs3kpKSWLd6GfFxcXhUrMz02QuVev4/hn4gJtd9nhs0bkp0jIy9u7YhlWYOe5wxe5FiakGpUlo8CPgD/6OHSEpKpGy58njXb0TX7r0KjadJo4ZER0ez02c3UqkUR0dH5s2epRg2GB4erjRioKKnBxN/HM+OXT5s37ETSytLZkydgr29HQARkZHcvHULgOGjlKeyLF4wn6pVKhdpP3Xo0p2kpEQ2rF5CfHwc7p6VmTbnZ7S1cxb2/Bj6gdiYnP1Uv1EzoqNl7PPZikwahYOjM1Nn/5xrP5ViyszF+Gz/hQWzJ5GUmIi5pRUjx06iRq26+WJQpVOXb0lKSmLt6uXEx8XhWbESMws5fg0bNyU6Jpo9u7Zn7WMnZs5eoNjHWtraPHn8CL+jvsTHxWFsbELFSpVZtHRVvkWtVOnyzTckJSWxetUq4uLiqFixIrPnzFGKKTQ0lOiYnPtsN27cmJjoaHb5+CCNisLRyYnZc+YoDRcdPGQIEg0N5s2dS2pqKjVq1GD4iBFF2k8lrZyX1P3UuUvXzJhWr1CUp9mz5+fZT6FK+6lR4yZEx0Tjs2un4pydPXueIqbg4GCCgjJXUh80sJ/S523ZtpMKFcwLjauTiuM3Y/aCQst5TK5ynnn8FuZbTPavKon7qkuXrDK1elVWTBWZM3tunjL1IU9MjbNi2pUrprlKZerkiePs2ZMztXHCT+MBGPPDWKWOCpUxiXJe6LFr0qgBsuhodvjsRSqV4uTowPzZMxTD3z+FhyPRyPW75+HOpB/Hsn3Xbrbt9MHK0pKZUybikPW7p6mhwbuQ95w9v4iYmBjKGJbBzcWF5YvmY2+nfvqmKp/r+J04cYI9uabL/vRj5qijH8aOVeqoUKWkHT+jGpXwPr9L8dxzyWQA3u305cHASehYlEPPJqdTM/F1CLe/HoLn0knYj+pDUshHHg6ZSsTZnNsKhx44iXY5U1xnjEbHvBwx95/y+1ffkfJJ9V3T8vqn21IaGhqEvAthzvnzxETHUMbQEFcXF5YuXoi9nV2RYsrWOavdsibX8ZuVrz4PJSY6p0w1bNyE6BgZu3ftULRbZs2en6vdosXjxw/xO+pLXK52y+KlKwtst7SoXwdZdCyb9x0mShaNi4MtS6eOU0zBCIuIVCxqDxAhldJ//AzF871+p9jrd4pqFd1YM3sSAIdPXwBg5HTlC0mTRwxUdGwIwp8hkedeHEAQ/oc8ffG+uEPIR08eX9wh5BNH0VcI/7doSYq2Dsm/qVQJjAkgRa5TeKJ/mbYkufBE/7IM+T97W7l/QjolLyZN0gtPVAwk5J+iVdwkkpLXPCqJ5VwnI6G4Q8gnVbPk1ZtQMo/fM/eCO9yKQ8Wnx4o7hHxSJKrv0lacTBNLXjsYoGwl78ITlUDnHpS8tk22FlVKZp32V4k1IARBEARBEARBEARB+OxEB8TfNHToUEqXLq3yMXTo0OIOTxAEQRAEQRAEQRBKBLEGxN80e/Zsxo8fr/K9wu5MIAiCIAiCIAiCIBQvsSjBv0d0QPxN5cuXp3z58sUdhiAIgiAIgiAIgiCUaGIKhiAIgiAIgiAIgiAIn50YASEIgiAIgiAIgiD8Z8mRFJ5I+EeIERCCIAiCIAiCIAiCIHx2ogNCEARBEARBEARBEITPTnRACIIgCIIgCIIgCILw2YkOCEEQBEEQBEEQBEEQPjvRASEIgiAIgiAIgiAIwmcn7oIhCIIgCIIgCIIg/GdlyIs7gv8OMQJCEARBEARBEARBEITPToyAEP5nyeUl73696Rol75RyfnqkuEPI54LFwOIOIR8343fFHYJKGmQUdwj5hKeYFXcI+RhpxRV3CPnYv7lQ3CHkI7WqWtwhqJRcSr+4Q8gnowReo9HNiC/uEPJ5mWJf3CHkY6kbXtwhqJRWApvdFZ8eK+4Q8nns0a64Q8gn/caT4g4hHwOd8sUdgkrNizsAocQreTWhIAiCIAiCIAiCIPxLSuKFzf+vSl73viAIgiAIgiAIgiAI/++IDghBEARBEARBEARBED47MQVDEARBEARBEARB+M+Si7tg/GvECAhBEARBEARBEARBED470QEhCIIgCIIgCIIgCMJnJzogBEEQBEEQBEEQBEH47EQHhCAIgiAIgiAIgiAIn53ogBAEQRAEQRAEQRAE4bMTd8EQBEEQBEEQBEEQ/rMykBR3CP8ZYgSEIAiCIAiCIAiCIAifneiAEARBEARBEARBEAThsxMdEMK/4tKlS0gkEmQyWXGHIgiCIAiCIAiCoCCXl9zH/zdiDQjhs2jSpAleXl6sWLHiX/9suVzOXp9tnDt9nPj4ONw9KjFkxA9YWlkXmO+E/2GOHNqPTBqFvYMT3w0djaubh1KawKeP2b1zC8+DnqKhoYGDozPT5yxGR0enwG0fO3aMQwcPIpVKcXB0ZNiwYbi5ualNf/XqVXbt3ElYWBiWVlYM6N+fWrVrK31Hn127OHXqFPHx8Xh6ejJi5EisrKyKsIcy7bsWwI6LfxARG4+rZTkmdmxKZTtzlWnPPXjOlnO/8y4imtSMdOzKmtC7SXXa1fRUpJm29zR+t58o5avnZsf6IZ2KHFP2dzt1cC03LhwkKT4We7dqfDNgGuUs7NTmOXdkEw9un+PTh1doaeti7+pFu+4/UN7SAYCo8PfMGd1aZd6+3y/Fq67q97KVxOMnl8vZ47ODM6dOEB8fh4dnRYaN+L7Qcn782FEOH/oVqTQKBwcnBg8biaubu+L9tauXc//eXaKiItHV1cPd05N+/QdhbWNbpJgO79nIpbNHSIiPw8W9Cn2HTcDcUn3ewMd3OXnYh9fBgcikEYyetJgadZsopdm0chbXLhxXeq1ytbqMn7mqSDHt9dnO2VNZ9YFnJYaOGFN4fXDsCIdz1QeDho1Sqg+mTPiBxw/vK+Vp3bYdw0b9UGhM+y7dYcfZG0TGxOFqXYEJ37amsr3qY3/+XiBbTl3nbXgUaekZ2JY3pU+LOnxVp4rSd1zvfxnfawHEJibh5WjN5B5fYFfetNBYcjt8/BT7D/sRJZXh5GDH6MED8HB1UZv+0rUbbN29j4+fwrG2NGdw317UrVld8X7Tr79RmW9Iv15069S+SDH5HfPn4KFDSKVSHB0cGD5saIHn3pWrV9m5y4ewsDCsLC0ZMKA/tWvVAiAtLY0dO3dy+/YdQj9+xMDAgGpeXgzo3w8zM7MixQMlsz446n+CX32PZB07e0YO+Q53N1e16S9fu852n718DPuElaUFg/r1oU6tGor3Fy9fxZnzF5Xy1KxejYWzpxc5puzv5rdvPVfPHiYxIRYn96r0HDyZCpbq6/OTh7Zw9+YFPr5/jba2Do7uVenc+3vMrewVaVJTkjmwfRm3r50mLS0FTy9veg6ejKFx4cdRLpez22cnp0+dVNSdw0eMLnR/+x/zw/fQgay605Ehw0bgllV3xsbGsNtnF/fu/kF4+CeMjIyo612PXr37YWBgUKSYSlo95ed/nIOHfInKPveGDimwTF25eo0dPj6EhX3CytKSgf37UbtWTcX7u3bv4dKVK4SHR6BVqhTOzs7079Mbd3f1505upg1q4jhuIEbVK6FrWZ47nYcT5ne+4DyNauO5ZCKlPV1IehdK8IL1hOw8rJTGblgPHMcORMe8HDEPAnk8Zg7Rtx8WKaZscrmcM4fWcOviARLjY7F3rUanAdMpZ26vNs+Foxt5eOcc4R9eUkpbF3sXL77oNk7RbgGICHuL/56feR10l7TUFNyqNqBD3ymUMSpbpJj896/j+jlfEhNicXTzovvgKZQvoC11yncLAbfOE/b+FVraOji6edGx1xgqZJ178bHR+P+6jqf3byCN+EhpQxOq1mpKu24j0DMoU+T9JQhiBITw/87hg/s4fsyXISN+YNGydejo6jJ72k+kpKSozXPtygW2bVrPtz36snTVRuwdnJg97SdkMqkiTeDTx8yZPgGvajVZvHwdP69YzxftOqChUfCiNZcvX2bTxo306NmT1atX4+jgwLSpU9WOBnny5AmLFi6kVevWrF6zBm9vb+bMmcPr168VaQ4eOICfnx8jR41i+YoV6OrqMm3q1AK/Y26n7gWx5OgVhrSuy76xPXGzLMuwjb5ExiaoTG+kr8t3Leqw8/tvOTi+N+1rezJj3xmuB75WSlff3Z7zMwcrHot6f1GkeHK7cGwrV07t5puB0xkzZw86OnpsWDiE1JRktXlePL1Dg1bd+X72HoZO3kh6WiobFgwmOSnz+xibmTNr/SWlR5suI9DR1cfDq2GB8ZTE4wfge3A//n6HGTbye35evgYdXV1mTJtY4DauXr7Ilk0b6NajN8tXb8De0ZEZ0yYqlXMnZxdG//Aja3/Zyqy5C0EO06dOID09vdCYTvju5Ozx/fQbNpHpP29FR1ePJTNHk1LAsUtOSsLG3oXeQ34scNuVq3uzcvsJxWPY+LmFxgOZ9YG/ny9DR/7A4uVr0dXVZda0CQXXB5cvsnXTerr16MOy1b9g7+jErGkTlPYTQMs2X7LN56Di0Xfg4ELjOX3nMUsPnWXIlw3ZO/k7XK0rMHzVXqJi4lWmNzTQ5bu29dn5Y38OTB1Ee++qzNh5jN+evFCk2X7mBnsu3mZKj7bs+qk/ejraDF+1h+TUtCLtI4ALV6+zfssO+nb7ho3LF+Fkb8dPM+YhlUWrTP/oaRBzlqzgi5bN2LRiMQ3q1Gba/MW8evNWkebQjo1Kj59GD0cikdCoXt0ixXT58hU2bdpErx49WLN6FY6ODkyZNq3Ac2/hosW0btWKtatX4e3tzew5cxXnXnJyMsHBL+jRvTtrVq9i2tQphISEMHPW7CLvp5JYH1y8co0Nm7fRu/u3bFi5FEcHeyZOn41UTUyPnwYyb/Ey2rRszoZVS6lftw4z5i3k1es3Sulq1ajGr7u2Kh5TfhpbpHhyO314OxeO76XX0MlMWrgTHR09Vs4ZUWB9/uzxXZq2/ZZJC3cyZsZ60tPSWDFrGMlJiYo0v25bwv07Vxjy42LGz9lMdFQ46xeNK1JMhw7+yjG/I4wYOZqly1ehq6vL9GmTCtzfVy5fYvOmX+jeoxcrV6/DwdGR6dMmK+qEyMhIoiIjGfDdINau38iYH8bzx507rFyxtEgxlbR66tKVq2zctJmePbqzdtUKHB0cmDJtutpy/vjJUxYs/pk2rVqxbtVK6nnXZdbcebzOVaasrCwZMXQov6xdw9KfF2FeoTyTpk1HFq26jslL00CfmAdBPBo9q0jp9eytqeX3C5GXbnGtZnterd5B5V/mUrZlA0Uai2/a4vHzJJ7PXcu12h2JfRBIneNb0C735zpvL/lv4dppHzr1n8Go2fvQ1tFj88LBBbdbAu9Qr0V3Rs7ay+CJm0lPT2PTwu9IyWq3pCQlsGnhICRIGDJ5GyNm7CY9LZVtS0aQkZFRaExnj2zj0om9dB88lR/n+6Cjo8fqOcMKjCn4yR0at/mWHxfsYvT0X0hPT2P1nKGKtlS09BPRUeF06jOWqcsO0WfEbJ4EXMdn/cw/tb8EQXRACP+4fv36cfnyZVauXIlEIkEikSg1tgDevHlDu3btMDExwcDAgIoVK3LixIm//dlyuRz/owf55tve1PFugL2DE9+Pm0RUVAS3blxTm8/v8AFatvmS5i3bYmNrz9CRY9HR1eX8mZOKNNs2reXLrzvRuWsPbO0csLK2pX7DpmhpaRcY0+HDh2nTti2tWrXC1s6OkaNGoaOjw5kzZ1SmP3r0KDVq1qRLly7Y2trSp08fnJycOHbsmOI7HjlyhG7duuHt7Y2DgwPjxo8nMjKSG7/9VqT9tOvyXTrVrUSH2hVxMjdjapcW6GqV4sjvj1Smr+VsQ/MqzjhWMMOmrDE9G1XHxaIc9159UEqnXUqTsoYGioehvm6R4skml8u5fHIXrToOpnLNZljaudFj+HxipJ94eEf9lY4hk36hduMOWNg4Y2XnTo9h85BGhBLyKnNEhoaGJobGZZUeD2+fx6tua3R09QuMqSQeP7lcjt8RX7p260ld7/o4ODjyw7gJREVGcvPGdbX5jh4+RKs2X9CiVRtsbe0YPnIMOjo6nDtzSpGmTduvqFS5ChUqmOPk7ELPPv2JCA/n06ewQmM6fWwf7b4ZQPU6jbG1d2HwmJnIoiK4e/Oy2nxVa9SjS69h1PRuWuD2tbS0MDYpq3gYlDYsMH12TMeOHKJrt17U8a6fVR9MJCqy4Prg6OEDtGrzBc1bZdYHw0b+gI6OjlJ9AKCjo4OJqanioa9f+JXOXedv0al+NTrU88LJohxTu3+BrrYWR24EqExfy9WeZl7uOFqUxaacKT2b1cbFqgL3gt8pvuPuC78zqG0DmlZ1w9W6AnP6fU14dCwXA4IKjSfbgaP+fNmqOW1bNMXe1oaxwwejq6PNyXMXVKY/dOw4tat70a1Te+xsrBnQqxsujo4cPp5TlkxNTJQe12/dxqtyRSzNKxQpJt/Dh2nTpg2tWrXEztaWUSNHoqOjy2k1596Ro37UrFGDb7p0xtbWlr59euPs5ITfMX8ADAwMWDB/Ho0aNcTG2hoPd3eGDx/G8+BgPn36VKSYSmJ9cOiIH1+0bkmbls2xs7VhzIih6OjocOqs6jrT18+fWjWq8W3njtjZ2NC/dw+cnRw56q/8G6ylpaV0/MqULl2keLLJ5XLO+e/hyy6D8KrdFGt7V/qPnoMsKpx7v19Um+/76Wup1+xrLG2dsHFwo/+oWURFfOTNi8z6PCE+lmvnj9C131jcK9fGzsmTviNn8SLoPi+DHhQa09Ejh/m2Ww/qetfDwcGRseN+IioykhsF1J1HDh+idZu2tGzVGltbO0aM/B4dHR3OnjkNgL29A5OnTqdOHW8sLCyp6lWNPn378/utW4V23pbEesr38BHatGlN65YtsLO1ZfTI4ejo6nD6zFnV+8fPj5o1qvNN507Y2trQt3cvnJ2cOOrvr0jTrEkTqlfzwsLCHHs7OwYP+o6EhARevXpdaDwA4aev8GzGCsKOnitServB3Uh8FcLTnxYRF/iSN+t28/HQaRy+76dI4zCmP++2/ErIDl/inr7g4fAZpCckYdOvc5E+AzKP39VTO2neYQiVajbH0taNbsMWEiP7xOM/1LdbBk3YSK3GHTG3dsHSzp1vh8xHFpnTbnn17B7S8Pd8O2Q+FrauWNi68u3QBYS8ekTwk5uFxnTh+G7adB5E1axzr++ouURLw7n/u+o6HWDk1PV4N22PpY0z1vZu9Bkxm6iIUN6+fAqApa0Lg39cRpWaTShnboNb5Tp83X0UD+9cJj296B3eJZVcLimxj/9vRAeE8I9buXIl3t7eDBo0iNDQUEJDQ7GxsVFKM2LECJKTk7ly5QoPHz5k0aJFlP6TjRtVwj6GIpVGUdUrZyipgUFpXNw8CAp8rDJPamoqL4KfKeXR0NCgild1RR6ZTMqzoKcYGRkzcdxI+vXsxJQJ3/PkccHD9FJTUwl+/hwvLy+lbXt5eRH49KnKPIFPn1ItV3qAGjVqKNJ//PgRqVSKV7Vqub6jAW5ubjwNDCwwHoDUtHSehoRR1zVnWLyGhoS6rrY8eB1aaH65XM6tZ295HR5FDUflIat3gkNoMn0DXy/YztyD55HFJ6rZimqRn0KIlUXgWslb8ZqefhnsnKrw+vn9AnIqS0yIA0C/tJHK99+9fMz7N4HUaVrw9JCSePwgdznPGe5uYFAaVzcPgp4+UZknNTWV4OBneOXKo6GhQVWv6gQGqs6TlJTI+bOnqGBuTtmy5QqMKTzsA9HSSCpWzRlarm9QGkfXigQH/bnhrKoEPrrLyD6tmTCsC9vXLyQuRlZonuz9VCVPfVDYfnoR/EwpT+Z+qkFQnv105eJ5enfrwOhhA9i1bRPJSUkFxpOals7Tt6HUcc8ZYquhIaGOuz0PXr4v9PvI5XJuBb7idVgk1V0yz9/3ETIiYuKUtllGT5fKDlbcfxVS6Dazv/Oz4JfU8MqZ1qGhoUH1qlV4HPhMZZ4ngc+oUbWK0mu1qldVmz5KKuPmnbt80bJZkWN6HhysdC5paGhQzctL7XnyNDCQatW8lF6rUaN6gedVfHw8EokEgyL8/pTE+iDz2L2guldVpZiqe1XhSaDqDqgngUFK6QFqVffiSZ5jd//hI7r07Eu/ISNYsXYD0TExhcaTW0TYe2JkEXhUraN4Td+gDA4ulQrtKMgtuz43yKrP3758SnpaGh5Vc0bSWFg7YFrWnBfPCt5u2MePSKVRSvVg5v52V3sMM+vO53h55RyjzONejcBA1Xkgs2zp6+ujqalZSEwlrJ7KOvfylqlqXl5qy9TTwMD85bx6NbVlODU1lRMnT2FgYICjg32B8fxVxnW9iLhwQ+m18LPXMKmbGadESwuj6hWJOJ+ro08uJ+LCbxjXrUZRRYVntltcKiq3W2ydqvDmeUCRt5OUEAvktFvS01KQSCSUynWRS0tLB4lEg9dBdwvcVuSnzHPPvUrOuadnUAZ7l8q8LOQcyS3n3FPf4Z+YEIeufmk0NcWsfqHoRGkR/nFGRkZoa2ujr6+PuXnmmgKBeX6E3r59S+fOnalcuTIAjo6OBW4zOTmZ5GTlYWMpyclo51l7QSaNyozBxETpdWNjE8V7ecXGRJORkYGRcf48799lDicO+5j5h/m+PTvoN3AoDo7OXDp/hhmTx7Fy3Va18zRjYmLIyMjAJG88Jia8C1H9x4FUKsVYRXqpVKp4H1C5zez3CiKNTyQ9Q45ZGeUr/2Zl9Hn1SX3+2MRkWs7aRGpaOhoaEiZ3boa3W85cwnru9jSv7IyVqRHvImWsPnGd4RsPs+v7bmhqFK2vMzY6AoDSRsrzeEsbmREriyjSNjIyMjiycyEObtWwsFE9f/3WRV8qWDni4FpwI6MkHr/c28j3OcbGSNWU85iscp4/jwnv371Teu2E/1G2b91EUlISVtY2zJ63GC0trQJjipZGAmBkrDx01dDYVPHeX1W5mjc16jalXAVLPn0M4eCu9SyZPYbpi7agUUDjPvucz/udjYxN1O6nWDX7ycjYhJB3OdMLGjVpTvnyFTAxNePN65fs3LqR9+/fMXGq+uH80riEzHPPUPkKpJlhaV6Hqd9HsYlJtJq0ktTUrHOve1u8PTLrzIiYuKxtKG/TtIwBkWqmdeQVHRObWc6NlTvsTIyNePtedcdIlEymIr0xUqlMZfrTFy6jr6dLI+86Kt/PK/vcMzYxVnrd2NiYd3nKazapVIqxcf706s6rlJQUtm7bRpPGjTHQL3gkVO6YSlJ9oP7YGfMuRPWxk0plmKjYT1G5hu7Xql6NBvXqYl6hAqGhH9my04fJM+awasnCQv+gzhaTVWeXMcpbJ5gRU8Q6ISMjg/1bl+Dk7oWVnTOQWdeUKqWFfp4550XZrlRRJxgrvZ7ZRlC9v3PKYv66M0RNWYyOjmbf3t20aVv4NMSSVk8pvm+eNpGJsTHv3qkr5/nLlKr64Obvv7Ng0c8kJydjamrCgrmzMTJSfaHg79KpUJbkMOV2Q3JYBFpGZdDQ1UHLxAiNUqVI/hSZJ00kBm4Ft0lzi1WUc+V1Gf5su8Vv10LsXatjntVusXWuiraOHsf3LaVt1zEgl3Ni/zIyMtKJkYUXuL1oaebn5l0TxdDITHFeFiWmg9sW4+TuhaWt6rZUXIyUkwc3Ur9F0UeMCAKIDgihmIwePZphw4Zx5swZWrRoQefOnalSpYra9AsWLGDWLOV5f8NHjaVS5SpsWLNM8dqUmQs+S7zyrPl2rdt+RfOWbQFwdHLhwf27nD97kt79Bn2Wzy1JDHS0+XVcLxJSUrj1/B1Lj17B2syIWs6Zo1vaVstZSMrFsiyulmX5ct427gSHUMdV9SKEf1zz59fNOcd10E/r/nach7bNJfRdMKNn7lT5fkpKEn/8doJWHYf87c/6t1y6eJ51q5crnk+fNe+zfl7jps3xqlaDqKgojvgeYPGCOSxashJt7ZwrMb9dOsX29Tnn29hpy1Vt6h9Rt1Erxf9t7J2xsXfhxyEdefroD6URF5cvnmP96pz6YOqsz1MfQGZdkM3ewRETE1OmTx5PaOh7LCyKvnhgURjo6LB/8iASklP4Peg1Sw6exaqsMbVc7f/Rz/mcTp67QIvGDZXKUHFKS0tj3oIFyOUwcuSI4g6nxGnaOGdtHEd7Oxwc7Ojz3TDuP3xMdS/Vv9W3Lp/A55ectVlGTil8kdjC7N20gA9vg/lp3ra/lP/ixfOsXb1S8XzGrKKtHfN3JCTEM2vGVGxtbenRs3e+9/+/1lNF4VWlCutWryQmJoaTp84wb+EiVi1bmq/jsCS7e/0Yh7bMVDwf8OOGv73Nw9vn8DHkOcOn+yheK21oSq/Ry/HdNpvrp32QSDTw8v4CK3tPJBLlizq/XznO3o1zFM+HTVrzt2Pav3k+H969YNzc7SrfT0yIY938kZhbO/JV16F/+/OE/xbRASEUi++++47WrVtz/Phxzpw5w4IFC1i6dCmjRo1SmX7SpEmMHau8ANbLd5Gkp6fj6pZzJ4bU1MwFm6KlUkxNc3p+ZTIpDo7OKrddxtAIDQ0NovMs3CSTSTE2ybxyY5K1LWsbe6U01ja2RISrnxtvaGiIhoZGvitZMqkU0zxXLrKZmOS/EiOTShVXyLL/lUqlmJqaKqVxdHJSG4ti+wZ6aGpI8i04GRmbQNky6q8CamhIsC1nDIC7VXlehUWx5fxtRQdEXtZmxpgY6PE2Qqa2A6JijaaMd85pzKZlHb+46EiMTHKG/MdFR2JpX/hK2Ye2zePJ3cuMnLEDYzPVd/S4f+sMqcmJ1Gr0daHbKynHr3Ydb6U7VaSlpubEoVTOZTg6qt6GYVY5zxebTIqxqfJ3MTAojYFBaSytrHFz96BH147c+O0ajZvkDJ+vVrshTm4VFc8V554sCmPTnCtBMbIobB3Ur5z+V5Q3t6KMoTGfQkOUOiBq16mntAJ8dkx591N0EeqDvPspWibFxNRUZR4AV/fMz/344YPahr1Jaf3Mcy/PyITImDjKGqqfAqChIcE2644W7jbmvAqNYOup36jlaq/IFxkTTzmjnCvCUbHxuFoXba0FI8MymeU8z4KTUlk0pmr+MDA1NlaRXoaJSf70Dx4/5d37D0z/qfCV97Nln3uyPFdQZTIZJqYFnHsyFenznKtpaWnMX7CQT5/CWbRgfpFGP+SOqbjrg9zUHzvVxyLzM43zLVApk8kwNVb9HQAszc0xMjTkQ2io2g6IqrUb4+BaSfE8u56KjY7C2DSnPo+RRWLjUHh9vmfTQh7cucqPc7dgUjanLBuZmJGWlkpCfKzSKIgYWSSGJspXfOvU8VbcqQIyh/4DyKQyFW0EdXWnodq6M2+dkJCQwPRpU9DT12fKtJmUKpW/mV3S6ynF983TJpKqOJeyqSpTqsqgrq4uVpaWWFla4uHuTv9Bgzl15izduqq+Y87fkRwWgU4F5VEJOhXKkhodS0ZSMikRUjLS0tApb5YnjRnJH9WPEvCs3gxbp1ztlrTM4xcbHYFh3naLnXu+/Hkd3j6Xp/cuM3zaznztFrcq9Zm0/DTxsVI0NDTRMzBk1vCGeJVvq5SuSq0m2LtUzhdTjEy5LRUTHYl1EdpS+zfP5+EfVxg7eysmZvl/R5IS41kzdzg6egYM+Wk5mqUKHiEpCHmJNSCEz0JbW7vQhZdsbGwYOnQovr6+jBs3jk2bNqlNq6Ojg6GhodJDW0cHPX19LCytFA8bW3tMTEx5cD9nflxCQjzPg57i5l5R5ba1tLRwcnblQUBOnoyMDB4G3FXkKV/BHFOzsnx4rzzc8sP7EMqVV9/I19LSwtnFhfsBAUrbDggIwN3DQ2Uedw8PAnKlB7h3754ivbm5OSYmJkrbTIiPJygoCA/3wn/stEpp4mFdgVvPc75LRoacW8/fUcXeotD8ijxyOalp6o9xmCwWWUIi5QzVL3ilq2dAOXNbxcPc2okyxmV59ihngaWkhDjevHiAvUtVtduRy+Uc2jaPh7fPM3zqVszKq7912a2LvlSs0ZTShoWvcl1Sjp++vj6WllaKh42tHSYmpty/fy9nGwnxPAt6ipuHp8ptaGlp4ezsyv37yuX8QcA93N1V58kkR45c8cdENj19AypY2CgeVjaOGJmY8eTBbUWaxIQ4Xj57jLNb5bwb/VuiIsKIi43GyES5cVnU+qCw/eTk7KqUJ3M/3cWtgP306kXmXSkKavxrldLEw9aC34Ne5dq2nN+DXlPFsehXIzPkclLSMhf8siprTFnD0vwe9FrxflxiMg9fvaeqQ8G38FPEpaWFq7Mjd+/nrNWRkZHB3QcPqeiuuvPI092Vuw+U1/b4I+CByvQnzp7H1dkR5z8x11tLSwsXZ2cC7gcoxRQQEKD2PPFwdycgQHmtmLv37imlz+58eP/hAwvmz8PQsPDFTHPHVBLqg7wxuTo7cfd+zrzujIwM7t1/iKea2xt6urtxL0B5Hvgf9+7jqeZYA4RHRBATG4upms4fyKzPy1vYKh4WNo4YGpfl6YNbijSJCXG8ev4IRzf1Ix7lcjl7Ni0k4NYFxs76hbIVlM8NW0cPNEuVUtrux/eviYr4iJOr8nbz1p22WXVnQJ66MygoUO0xzKw7XbifpyzeDwjA3T0nT0JCPNOmTqJUqVJMmz5L7WifEl9PZZ17uctIZjm/r7ZMebi7E3A/77mn/lzNJs+QKzqF/mmymwGYNVO+407Z5vWQ3gzI/OzUVKLvPqZss5y1G5BIMGvqjezmPdTR1TOgrLmd4lHBypkyxmUJfqzcbnn74gF2Ll5qtyOXyzm8fS6P7pxjyJStmBbQbjEoY4KegSHBj28SHxOFZ3XltXTynXvWThgalyXoofK59/r5QxxdCz739m+eT8DvFxgzcxNlK+SPKTEhjtVzhlKqlBbDJq5ES7vg29ALgipiBITwWdjb23Pr1i1ev35N6dKl890yaMyYMbRt2xZXV1ekUikXL17EQ82P/58hkUj4qn0XDuzbhYWlFRXMLdizayumpmWp451z66Xpk8dS17shX7TrCMDXHb9h1bKFOLm44uLqgf/RgyQlJdG8ZRvFdjt0+pZ9u7dj7+CEg6MzF8+f5n3IW36cPLPAmDp27MiypUtxcXHB1c2No0eOkJycTMuWLQFYsmQJZmZm9O/fH4D27dsz4aef8D10iFq1a3P58mWeP3/OqNGjc2Lp0IF9+/ZhaWVFhQoV2LVrF2ZmZnjXq1ek/dS7cXWm7T1NRZvyVLI1x+fyPRJTUulQO7PDZcqeU5Q3LM33X2Xusy3nfsfTpgI2ZY1ISUvn6tPXHL/zlCldMn8EE5JT2HD6Ji2quGBmqE9IRDTL/a9iU9aYeu7q7zmdl0QioXHb3pw9spFy5naYlrfi5IE1GJqUp3LN5op06+YOpHKt5jRs3QOAQ1vn8sdvJxg4bhU6egaKOY66+qXR1s65E0f4x7e8DPyDQT+tL3JMJfH4SSQSvu7QiV/37cbS0ooKFczZvWs7pmZm1PWur0g3ddKP1K1Xn6/adciMrWNnVixbjLOLG66ubvgd9SUpOaecfwz9wNUrl6hWvSZGRkZERERw6MA+dLS1qVGrtqpQlGJq3a4bfr9upYKFDeUqWOK7ZwPGpmWpXrexIt2iacOpXrcJLb/sCkBSYgJhoTnzisPDPvDm5TNKlzHErJw5SYkJHNm3mZr1mmJkbManjyHs37GG8hbWVK5e8O0cJRIJ7Tp05sA+HywtrShfwYI9u7ZhaqZcH0ybNI669RrwZVZ90L7jN6xcthBnFzdcXN05dvSQ0n4KDX3PlYsXqFGrDmUMDXnz6gVbNq6jYqUq2DsUfNW6d/M6TNvhh6etBZXsrdh94RaJyam0987sYJu6/SjljcswukPmubXl1HU87SywKWtCSlo61x4Hc/zWQyZ3b6v4jj2b1WbTiWvYljPFqqwxa49dopxRGZp6FX6lK9s37b9i4Yq1uDo74eHqzEG/4yQlJdOmeebdSeYvX005U1MG9e0JQOd2XzJm8gx+PXyMurWqc+HKdYKCXzBuhPLUpviEBC5fv8mwAX2KHEu2Th07smTZMlxcXHBzdeXw0aMkJSfRKuvc+3nJUszMzBjQvx8AHdp/zY8TJnLI15fatWpx6fIVnj8P5vuskXVpaWnMnT+f4OAXzJ45g4z0dKKiMufYlylTptB1TqBk1gedO3zN4uWrcHNxws3VBd+j/iQlJdGmRWaduXDpSsqamfJdv8zpAJ2+/oqxE6dywPcodWrV4OKVazwLfsEPI4cBkJiYyM69+2lYzxtTExM+hH5k07YdWFqYU7N60Rfnk0gktPiqBycObqa8hS1lK1hxdO86jE3LUa12zl1vls0YgledpjT7ohsAezYu4PerJxk+aTm6egaK+ex6+qXR1tFF36AMDZp34MC2pRiUNkJP34C9mxfh6FalwI6N7Jjad+jI/n17sMqqO32y6k7vXHXn5Ek/4V2vPu3atQegQ8fOLF/2c+Zxd3XnaFbd2aJlayCr82HKJJKTkxn/4wQSExJITMgcZWhoZFTguhklsZ7q1LEDS5Ytx9XFOefcS0qiVcsWACxeuoyyZmYM6Nc3c/98/TU/TpzEQd/D1K5Vk8tXrvI8OJgxo0YCkJSUxJ79v+JdpzampqbERMfgd/w4EZGRNGxQX20cuWka6GPgnDOaUt/BGsOq7qRERZP0LhS3uWPRtarA/f4TAHizcR92w3vivuBH3m0/RNmmdbH4pi23v86po16t2EbVrYuQ/fGI6NsPsB/dl1IGerzb4VukmCDz+DVs04fzR36hrLkdpuWsOX1wFYbG5alYI6fd8sv8/lSq2YL6rTLr0MPb53Dvt+P0G7sGHV0DxboOevpl0Mpqt9y+7Et5SycMDE148zwAv10LaNimD+UtHfIHkiemZl/25OShTZS3sMOsvBXH9q3FyKQcVWvndF6snDmIqnWa0aRtdwD2bZ7PnasnGTJhBTq6+c+97M6HlOQk+v00n8SEeBITMkf0lTE0KXBNpv8FGfLijuC/Q3RACJ/F+PHj6du3L56eniQmJrJtm/L8zfT0dEaMGEFISAiGhoa0adOG5cv/mTnkHbt0IykpkfWrlxIfH4eHZ2WmzVmkdDXiY+gHYmJyhqw2aNSMmOho9vlsRyqNwsHRiemzFymmYAC069Alc9GyTWuJi43F3sGJGXOXFDqPsnHjxsRER7PLxwdpVBSOTk7MnjNHMZQx/NMnNCQ5t9jx9PTkpwkT2LljB9u3b8fKyopp06Zhb2+vSNPlm29ISkpi9apVxMXFUbFiRWbPmVPk+dVtqrkhjUtk3akbRMQk4GZVjnWDO2JWJnO0wkdprFJMiSmpzD90gTBZLDpapXCoYMq8nm1ok7Xug4ZEg2ehEfjdeUJsYjLlDUvj7WbLiLb10FYxBLUgzdoNICU5kV83zyQxIRYHt+oMmbhBqZc9Iuwd8bE5w0Ovn9sPwNo5/ZW21X3oXGo37qB4/vslX4xMK+BWpWgNeyiZxw+gU5dvSUpKYu3q5cTHxeFZsRIzZy/MX85z3WO9YeOmRMdEs2fXdqRSKY6OTsycvUDxXbS0tXny+BF+R32Jj4vD2NiEipUqs2jpqnwLkqnyRac+JCclsX3dfBLi43DxqMr4GSvRznXsPn18r3QHi1fBT1k4dZji+d6tKwBo0OxLBn0/Aw0NDd69fs61i8dJiI/FxLQcFb3q0LnnkEJvgQvZ9UES61YvIz4uDo+KlZleyH5q0Lgp0TEy9u7ahlSaOTR7Rq76oFQpLR4E/IH/0UMkJSVStlx5vOs3omv3XoXG07pmRaRxCaz3v0xETDxu1hVYN6o7ZllTKUKjopHkPveSU5i/9ySfss49e/OyzOvfntY1c0Z09WvlTWJKCnP2HCc2IYlqTjasG9UdHa2in3vNGtYnOjqG7Xv2EyWV4eRoz6KZUzDNGkL9KTxCqZxX8nBj6rjv2bp7L5t37cHK0oI5k3/CwU55utWFK9eRy+U0a1S0PzJya9y4EdEx0eza5ZNVXh2ZO3u2orx+Cg9HoqF87k346Ud27NzF9u07sLSyYvq0qYpzLyIykps3M68IDh+pPN1v0cIFVC1gHaKcmEpefdC0UYPMY+ezD6lUipOjAwtmT1cMf/8UHo5Grv1U0cOdyT/+wLZde9i60wcrSwtmTZmIg31mZ7GGhgYvX73h7PmLxMUnYGZqQo1qXvTv1QPtInTS5Na6Yz+SkxPx2TCXhPhYnD28+H7aWqX6PPzjO6U64fLpAwAsnaa8tlK/kbOo1yxz6lzX/uORSDTY8PN40lJTqOhVjx6DJxUpps5dumbu79UrFHXn7Nnz89QJoUp1QqPGTYiOicZn105FWZw9e57iuAcHBxMUlLnY9qCB/ZQ+b8u2nVSooHpKYLaSVk81adSQ6OhodvrsVnzfebNn5ZTz8HClcl7R04OJP45nxy4ftu/YiaWVJTOmTsE+V5kKeRfCnPPniYmOoYyhIa4uLixdvBB7u6JdpDCqUQnv87sUzz2XTAbg3U5fHgychI5FOfRsckZxJr4O4fbXQ/BcOgn7UX1ICvnIwyFTiTibc2vT0AMn0S5niuuM0eiYlyPm/lN+/+o7Uj79uYWTm3w1kJTkRA5umUFSQiz2rtX5bsJGpXIemafdcuPcPgA2zO2rtK2ug+dRq3FmJ1N46GtO7F9OYlw0JuWsaNZ+CI3aKqdXp2WH/iQnJ7Lnl9kkxMfi5F6NkVPXKZ97YSFK597V078CsGLGQKVt9R4xG++m7Xn38imvn2eOfJsx8iulNHPWncCs/L+/rojwv0kil8tFf4/wP+lJ8IfiDiEfHY2Cb29VHKyeqr4/fXG6YDGw8ET/Mjdj1auZF7c0ecmbWylNLfqw9X+LkVZccYeQj/0b9fdbLy5SK/VTmYpTcqmircPwb8qQlLxZqtrpJe835mWKfXGHkI+lbsF3CSguaSXwup+evGh3y/k3PfZoV9wh5JN+Q/UtUYuTgc7nmb7ydzWvrFt4ohLoyO2Cp44Xpw61/rdHl+RV8mpCQRAEQRAEQRAEQfiXiEvy/56S170vCIIgCIIgCIIgCML/O6IDQhAEQRAEQRAEQRCEz050QAiCIAiCIAiCIAiC8NmJDghBEARBEARBEARBED470QEhCIIgCIIgCIIgCMJnJ+6CIQiCIAiCIAiCIPxnyZEUdwj/GWIEhCAIgiAIgiAIgiAIn53ogBAEQRAEQRAEQRAE4bMTUzAEQRAEQRAEQRCE/6wMeXFH8N8hRkAIgiAIgiAIgiAIgvDZiQ4IQRAEQRAEQRAEQRA+OzEFQxAEQRAEQRAEQfjPkospGP8a0QEh/M8qLY8u7hDyKfvufnGHkM8Lt/bFHUI+1db3Le4Q8kkZNqO4Q1BJLz2uuEPIx+LE0uIOIZ/05h2LO4R8nlp/Udwh5GOoGVPcIahkFve2uEPIJ6qMTXGHkE+6pOQ120y0S14dpZsRX9whqGQY+6G4Q8gnzMi1uEPIJ/3Gk+IOIR9Nb8/iDiGfck+uFncIaugWdwBCCSemYAiCIAiCIAiCIAiC8NmJDghBEARBEARBEARBED470QEhCIIgCIIgCIIgCMJnJzogBEEQBEEQBEEQBEH47EreakaCIAiCIAiCIAiC8C8Rd8H494gREIIgCIIgCIIgCIIgfHaiA0IQBEEQBEEQBEEQhM9OTMEQBEEQBEEQBEEQ/rMy5JLiDuE/Q4yAEARBEARBEARBEAThsxMdEIIgCIIgCIIgCIIgfHZiCoYgCIIgCIIgCILwnyXugvHvESMgBEEQBEEQBEEQBEH47EQHhCAIgiAIgiAIgiAIn53ogBAEQRAEQRAEQRAE4bMTa0AIANjb2zNmzBjGjBnzj2739evXODg4cO/ePby8vP7Rbatz1P8EB3wPEyWV4eRgz4ghg3B3c1Wb/vK16+zw2cPHsE9YWVrwXb8+1KlVU/H+zt17uXT1GuHhEZQqVQoXZyf69+mFRwHbzGv/xVvsOPMbkdFxuFpXYEL3L6jkYK0yre/VO/jfuE/wh08AeNhaMqpjc6X0CUnJrPI9x8WAQKLjE7Asa0L3ZnX4pnGtIsckl8vZ57ONs6f9SYiPw92jEoNHjMXSSnVc2U76H+bIoX3IpFHYOzjz3dDRuLh5APApLJShA7qrzDd+4kzqNWxS4Lb167fEoMlXaJYxIvXDW2IO7yD13Qu16SW6+pT5oiu6lWuhoV+adGkEMUd2kRwYAEC5KSspZVouX77462eI8d1eYCy5+fkf58Chw0RJpTg6ODBi6OACy9SVq9fY7rObsLBPWFla8l3/vtRWKlN7uHTlKuHhEWiVKoWLszP9+vTCw92tyDEdPn6K/Yf9ssq5HaMHD8DD1UVt+kvXbrB19z4+fgrH2tKcwX17UbdmdaU0b96FsHGHD/cfPSE9PQM7G2tmTRpHhXL596EqWlUboFOzGRKDMmSEfyDx4iEyPr5VndazNnpteii9Jk9LJXbVj0qvaZhWQKdhO0pZO4GGBhmRYSQc24o8VlakmA6euojPsTNEyaJxtrNm3IDuVHR2UJn25bsPbNx/lMBXb/kYHsmYvl3p9mWLfOk+RUlZ6+PLjYBHJCenYG1ejqnD++HhZF+kmCDz/Du4ezMXzvgRHx+Lm0cVBgz/EQtLG7V5nj66h7/vHl6+CEIWFcHYyQuo5d1YKc3vv13i3MnDvHoRRFxsDAtWbsfesWh1lVwux8dnF6dPnSQ+Ph4PT09GjBiFlZVVgfn8j/lx6NBBpFIpDg6ODB02HDe3nLJ88uQJLl+6SHDwCxITE9j/60FKly5dpJhK4vE7duwYhw5mfV9HR4YNG6b0ffO6evUqu3buJCwsDEsrKwb070+t2rUV78vlcnx27eLUqVPEx8fj6enJiJEjC93vufn5H+fgIV9FHTV86JBC66gdPj6KOmpg/36KOiotLY3tO324fecOoR8/YmBgQDWvqgzs1xczM7Mix5T93fbv3sL508eIj4/D3aMyg4aPw8JKfTkHOOXvi5/vXmTSKOwcnBgwZAwubp6K9z+GvmfnlrUEPnlAWmoqXjXqMGDIGIxNTAuN6aj/CX71PaJoI4wc8l2hbYTtPnsVbYRB/fpQp1YNlWlXrFmP/6kzDBs0gM7t2xUaS7YDZy7jc+wckdExuNhaMb5fVyo626tM++LdBzYePE7gy7eERkTxQ+/OdP+imVKa9IwMNh08zslrt4mSxVDWxIivGtdlQMc2SCRFu9WgXC5nt88Ozpw6SXx8HB6eFRk+YnShbYTjx47ie+gAUmkUDg5ODBk2Alc3d8X7a1av4P69u0RFRaKrq4eHpyd9+3+HjY1tkWI6c2gNty4eIDE+FnvXanQaMJ1y5vZq81w4upGHd84R/uElpbR1sXfx4otu4yhvmVOPRIS9xX/Pz7wOuktaagpuVRvQoe8UyhiVLTAe0wY1cRw3EKPqldC1LM+dzsMJ8ztfcJ5GtfFcMpHSni4kvQsleMF6QnYeVkpjN6wHjmMHomNejpgHgTweM4fo2w8L3T+5lcRzTxCyiREQwv8rl65c45fNW+nVvRvrVy7D0cGeSdNnIZXJVKZ//DSQ+YuX0qZlC9avWkb9unWYOW8hr16/UaSxtrJk5NDBbFy7kuWLF1ChQnkmTpuJLDq6SDGdvv2IpQdOM+SrJuyZOgRXG3OGr9xFVEycyvR3gl7TpnZlNo3rx44J32FuasiwFbv4JI1RpFl64DS/PQ5m3sBO+M4aSc/mdVm09wSXAgKLvK8OH9zL8WOHGDpiLAuXrUdHV485034kJSVZbZ5rVy6wbdM6uvbox5JVm7B3cGL2tB+RyaQAmJUtz5Zdh5Qe3Xr2R1dPj2o1a6vdLoCuV10Mv+5F3BlfIpZPIe3DW0wHT0SjtKHqDJqamA6ZhKZJOaQ7VhK+cBzRv24iPTpKkSRyxVTCZg5TPCI3zAcg6f6tIu+nS1eu8sumLfTq0Y11q5bj6GDP5Gkz1JepJ0+Zv3gJbVq1ZP2qFdTzrsPMufPzlCkrRg4dwsa1q1n28yIqVCjPpGkzilymLly9zvotO+jb7Rs2Ll+Ek70dP82Yh1SmOv+jp0HMWbKCL1o2Y9OKxTSoU5tp8xfz6k1O58D70I+MnjgNGysrls+bxeZVS+j9bWe0tbSLFFMp12roNu5A8s1TxPssIT38PQadhiLRU/+Hpjw5kdgN0xSPuM2zlN6XGJmh/+1oMqLCiP91DXE7F5N88zSkpRUpprO/3WblzgN81+UrdiyaioudDWPmrSQqOkZl+qTkFKwqlGNEj46YGasudzFx8QyetphSpTRZPnk0e5fPYnSfbyhjoF+kmLIdO+TDKf8DDBz+I3OWbEZHV5eF038o8PxLTkrC1sGZAUPHFZAmETfPqnTvO/xPxQNw8OABjvkdZcTI0SxbvgJdXV2mTZtCSkqK2jxXLl9m06ZN9OjRi1Wr1+Dg6Mi0aVOQ5To/kpOTqV6jJl2//fZPxVMSj9/ly5fZtHEjPXr2ZPXq1Tg6ODBt6lSl75vbkydPWLRwIa1at2b1mjV4e3szZ84cXr9+rUhz8MAB/Pz8GDlqFMtXZO33qVML3O+5XbpylY2bNtOzR3fWrlqBo4MDU6ZNVxvT4ydPWbD4Z9q0asW6VSup512XWXPn8TqrjkpOTib4xQt6dP+WtatWMH3KJEJC3jNj9twixZPb0UN7OHnsEINHjGfB0l/Q0dVj7vRxBZbz61fOs2PzGr7p3o9FKzdj5+DMvOnjiM76nUlKSmTutLFIJBJmzF/JnJ/XkZaWysLZE8nIyCgwnotXrrFh8zZ6d/+WDSuX4uhgz8TpswtsI8xbvIw2LZuzYdVS6tetw4w8bYRs1367ydOgZ5iZ/rk/xM7e+IMVu3z5rvMX7Jw/ERc7a0YvXENUdKzK9MkpqViVN2NE9/Zqy/lOvzMcOnuVH/t1Zf/SaYzs0Z5dx87y6+lLRY7r0MH9+PsdYfjI71myfDW6urpMnzapwHJ59fIlNm/6he49erFi9XocHB2ZPm2Soo0A4Ozswvc/jGfdL1uYNXcBcrmc6VMnkp6eXmhMl/y3cO20D536z2DU7H1o6+ixeeFgUgsoTy8C71CvRXdGztrL4ImbSU9PY9PC70hJSgAgJSmBTQsHIUHCkMnbGDFjN+lpqWxbMqLQ8qRpoE/MgyAejZ5VYLpsevbW1PL7hchLt7hWsz2vVu+g8i9zKduygSKNxTdt8fh5Es/nruVa7Y7EPgikzvEtaJf7c+WqpJ17gpCb6ID4H5GRkcHixYtxdnZGR0cHW1tb5s2bB8DDhw9p1qwZenp6mJmZMXjwYOLicv647devHx06dGDJkiVYWFhgZmbGiBEjSE1NBaBJkya8efOGH374AYlEotQ7fu3aNRo2bIienh42NjaMHj2a+Ph4xfv29vbMnz+fAQMGUKZMGWxtbdm4caPifQeHzB7matWqIZFIaNKkCQCXLl2idu3aGBgYYGxsTP369XnzJv8P+p916MhR2rZuRZuWzbGzteH7EcPQ0dHh9FnVPdKH/Y5Rq0Z1unbuiJ2NDf1698TZyZGj/icUaZo1aUx1r6pYmJtjb2fL0O8GkJCQwMtXr4sUk8/Z3+jUoAbt61fDybI8U3p+ha62Fkeu31OZfv53XejapDZuNhY4WJRjep/2yOVybgW+VKS5/+IdX3lXpaabA5ZlTejcqCau1hV4/Pp9kWKSy+X4Hz1Il297U9u7AfYOToweN4moqAh+v3FNbb5jhw/Qss2XNG/ZFhtbe4aMHIuOri4XzmTuL01NTUxMzZQet25cpX6DpujpFdzAN2j0BQk3L5J4+zJpYe+JPrQFeWoyerUbq0yvX7sJGvqlkW5bRurrZ6RLI0h5GUhaaM4f1RnxsWTERiseup7VSIv4SMqLp0XaTwCHDh+lbZtWtG7ZAjtbW74fORwdXR1OnzmnMv0RRZnqhK2tDf1698LZyRE//+OKNM2aNKZ6NS8sLDLL1JBBA0lISOBVEcvUgaP+fNmqOW1bNMXe1oaxwwejq6PNyXMXVH+HY8epXd2Lbp3aY2djzYBe3XBxdOTw8VOKNFt89lKnRjWG9u+Ni5MDVhbm1K9TCxNjoyLFpFOjCamPbpD6+HcyosJIOncAeVoKWpXqqM8kB3lCbK6Hcqecbv0vSXv1hOSrx8gIf488OpK0l4+RJ6ruvMtrr/9Z2jdvwFdN6+NgbcmEQT3R1dbG/+J1lek9ne0Z1bsLLevXRktLS2WaXUdPU8HMhGnD+1HR2QHL8mWpU7Ui1ublixQTZJ5/J/1+pWPXftSs2wg7B2eG/zAdaVQEd25eUZvPq6Y33/Yekm/UQ24Nm7Wlc/cBVPYq+mio7JiOHjnMt9264+3tjYODI+PG/UhUZCQ3bvymNt/hw760adOGlq1aYWtrx8iRo9DV0eHMmdOKNB06dKRr129xd3dXux1VSuLxO3z4MG3atqVVq1bY2tkxctQodHR0OHPmjMr0R48epUbNmnTp0gVbW1v69OmDk5MTx44dAzL3+5EjR+jWrVvWfndg3PjxREZGcuM39fs9N9/DR2jTprWijhqtqKPOqkx/xM+PmjWq801WHdW3dy+cnZw46u8PgIGBAQvnzaFxw4bYWFvj4e7OiGFDeB4czKdPn4oUU/Z3O370Vzp/24dadRti5+DMyLFTkEZFcvvGVbX5/I/sp3nrdjRt+SU2tg4MHjEebR1dLpzNrEODnjzk06ePjPhhMnb2TtjZOzHihym8DA7k0YO7BcZ06IgfX7RuqWgjjBkxFB0dHU6paSP4+vlTq0Y1vs1qI/Tv3SNfGwEgIiKSNb9sZtL4HyhVSrPI+whgz/HzdGhWj3ZNvHG0tmDiwG7oamtz7NINlek9newY3bMTrerVRLuU6oHMD569olHNKjSoXgnLcmY0r1OdOlU8eBxctHaWXC7H78hhunbrSV3vejg4OPLDuAlERUZy84bq8w/gyOFDtG7Tlhat2mBra8fwkd+jo6PD2Vz1QZu2X1KpchUqVDDH2dmFXn36ExEezqdPYYXGdPXUTpp3GEKlms2xtHWj27CFxMg+8fgP9aMOBk3YSK3GHTG3dsHSzp1vh8xHFhlKyKsnALx6dg9p+Hu+HTIfC1tXLGxd+XboAkJePSL4yc0CYwo/fYVnM1YQdlR1eyAvu8HdSHwVwtOfFhEX+JI363bz8dBpHL7vp0jjMKY/77b8SsgOX+KevuDh8BmkJyRh069zkT4DSua5979ALi+5j/9vRAfE/4hJkyaxcOFCpk2bxpMnT9izZw8VKlQgPj6e1q1bY2Jiwu3btzlw4ADnzp1j5MiRSvkvXrzIixcvuHjxIjt27GD79u1s374dAF9fX6ytrZk9ezahoaGEhoYC8OLFC9q0aUPnzp158OAB+/fv59q1a/m2vXTpUmrWrMm9e/cYPnw4w4YNIygoCIDff/8dgHPnzhEaGoqvry9paWl06NCBxo0b8+DBA27cuMHgwYOLPCxQndTUVJ4Fv6C6VxXFaxoaGlT3qsqTwCCVeZ4EBimlB6hZvRpP1aRPTU3lxKkzGBjo4+SgehiwUvq0NJ6+DaWOh6NSTHU8HHnw8l1RvhZJKamkpadjZKCneK2qkw2X7wfxSRqDXC7nduAr3oRFUtfTqUjbDPsYikwaRVWvnGGkBgalcXHzJCjwiervkprKi+AgquTKo6GhQRWvGmrzvHgexKuXwTRv9UXBAWlqomXtQPLzRzmvyeUkP3uEtp3qaQU6FWuQ+uY5Rp36U37mesqOX4RB8/agrhxpaqJXowEJv18uOJZcUlNTeR4cTLVc04c0NDSo5lWVp4GqR5s8CQykmldVpddqVq+uNn1qaionTp7GwMAAx6KUqdRUngW/pEbecl61Co8Dn6mJ6Rk1qiqX81rVqyrSZ2RkcPPOXawtLflxxlw69h7IsPGTuHbz90LjyQxAE40K1qS9yf35ctLePEPTwl59Pm1tSn83ndKDZqD39UA0zMxzvSmhlKMnGdJw9DsNpfTQORh0/4FSTpWLFFJqWhpBL99Sq7JHTpgaGtSq7MHDZy8LyFmwq3fu4+Fox+RlG2j73Tj6/DSHI+fUN+hU+RT2AZk0kkpeOdNy9A1K4+TqyfPARwXk/Hw+fvyIVCrFy6ua4jUDAwPc3NwJfKq6wy41NZXg4OdKeTQ0NPDyqkZgYNE7+VRuuwQev9TUVIKfP1eaTpj5fb3U7qPAp0+V6g+AGjVqKNIr9nu1vPvdTW2dkTem58HBVM9V52TWUV5qf/eeBgbmj6l6tQI/Lz4+AYlEgkERp85A5pQ8mTSKyrnKuYFBaZzdPAgKfKz2+7wMfqbid6Ymz7LypKamIkGi1Mmkra2NRKJB4OMHauPJaSMo76vqXlUKaSMo1+e1qnvxJFddm5GRwcJlK+jaqT32doVPI1CKKS2NwFfvqFUpp3NOQ0ODWpXcefj8r5fzKq4O3HkUxJvQzD/qn70J4X7gC+p5eRaSM1PYx49IpVH56gNXN3cCn6pvIwQHP6OqV87Uvszzo7raNkJSUiLnzp6mgrk5ZcsWPNUvKjyEWFkELhW9Fa/p6ZfB1qkKb54HFOl7ASQlZI4s0S+d2bmenpaCRCKhVK7RflpaOkgkGrwO+mf/qDau60XEBeWOpfCz1zCp6wWAREsLo+oViTifq/NRLifiwm8Y161GUZW0c08Q8hJrQPwPiI2NZeXKlaxZs4a+ffsC4OTkRIMGDdi0aRNJSUns3LkTAwMDANasWUO7du1YtGgRFSpUAMDExIQ1a9agqamJu7s7X375JefPn2fQoEGYmpqiqalJmTJlMDfP+QNgwYIF9OzZU7EuhIuLC6tWraJx48asX78eXV1dAL744guGD88c7jthwgSWL1/OxYsXcXNzo1zW3HEzMzPFtqOiooiOjuarr77CySnzD2YPj5xGpirJyckkJysPG0tOSUFHO+cHIzomloyMDEyMjZXSmRgb8S4kROV2pVIZxirSR+UaLghw8/fbzFu8lOTkZExNTFg0ZxZGRmqmBuTeflwC6RkZmBoqN9rMypTmdWhEofkBVh46SzmjMkqdGBO6fcEcHz9aT1hKKQ0NJBoSpvX+mhqu9kXapkyaOU3BKM+cPWNjE6TSKFVZiI2JJiMjA2Pj/Hnev1M9z//cmRNY29jh7lmpwHg0DMog0dQkI1Z5CkFGXDSlyluqzFPKrDyazp4k3r1O1ObFlCpbAaNO/ZFoahJ3xjdfet1KNZHo6pN4u+gdEDExMWrKlDHv3qkebSKVyvKlNzY2Jkqav0zNX/RzZpkyNWHh3NlFKlM55Vx5ZIKJsRFv36uOKUomU5HeGKlUBoAsOprExCT2HjrCgF7dGNK3J7/fDWD6giUsmzcDr0oVC4xJomeAREMTeYLykGF5QiyaphVU5smQfiLp9D7SIz4g0dFFu0ZTDLp9T9yOhcjjopHol0airYtO7eYkXz9B2tVjlLJ3R+/r/iQcWEt6iPq1QQBkMXGZ516eIcomxmV4/SG0wLwF+fApHN+zl+n+ZUv6dvyCpy9es3zbPrRKafJlk3pF2kZ09vmX51wyMjZVnJv/NmlW+TQxMVZ63djYWPFeXtnnh7GKPO/eFa2DVZ2SePwU9YGJidLrxiYmBfzGSDFWkT57n+bsd/VpihKTsbFy/sw6Sv3vnqo6Lbs+yCslJYUt27bTpHEjDPSLPtVIJo0EyBebsbEpMllBvzPpKs4NE96HZF69d3H3REdXF59tG+jRZzBy5OzevoGMjHSkWZ+pivq605h3IX+yPs/VRth38DCampp0/PortZ+tjqKcG5VRet3UqAxvPnz809vL1vfrVsQnJtF13Bw0NCRkZMgZ1rUdbRoUPBUyW3Y7IF/ZNVZfLmOy2gj5yrKxCSF56oPj/n5s35rZfrWytmHOvEVqRy1li5VltpnyrstQ2shM8V5hMjIy8Nu1EHvX6pjbZF7csHWuiraOHsf3LaVt1zEgl3Ni/zIyMtKJkYUXabtFpVOhLMlhyrEmh0WgZVQGDV0dtEyM0ChViuRPkXnSRGLg5khRlbRzTxDyEh0Q/wOePn1KcnIyzZs3V/le1apVFZ0PAPXr1ycjI4OgoCBFB0TFihXR1MwZFmhhYcHDhwUvaHP//n0ePHjA7t27Fa/J5XIyMjJ49eqVotOgSpWcK6sSiQRzc/MCh2mamprSr18/WrduTcuWLWnRogVdu3bFwsJCbZ4FCxYwa5byHLsxI4fzw+iRanL8s6pWqcyGVcuJjonh5OkzzF30M6uWLs7XMPmnbT15ldO3H7FpfD90cv0477t4i4cvQ1gxogcWZkbcffaGhXuOU86ojMpREJcvnuWXNUsVz6fMXPhZ44bMTqOrl8/xTbc+n+cDJBIy4mKIPrAZ5HLSQl6haWiKQdMvVXZA6NdpSnLgfTJiZJ8nnj+papXKrF+9gpiYGE6cOsPchYtYtWzJZy9TqmRkZI7vq1enJt+0z2xEOzs68DgwiGMnzxbaAfFXpIe+Jj30teJ54odXlO43Ce0q9Uj+7aRiJEvai0ek3M3sNEoJf4+mpQPaVeqTWEgHxOeSkSHHw8mOYT06AuDmYMuLtx84fPaK2j9gr106zea1ixXPf5q+5F+JtSAXL15gzepViuczZ80uxmj+PX/l+P2XpaWlMW/BIkDOqBEFryty9eIZflmbU7YnzVj0WWIyMjJh3MTZbFq3lJPHDiKRaFC/cXMcnFz/9kjKP+tZ8AsO+/mzfuXSf/2zC3Lu5l1OXbvNnJH9cLS24NmbEJbtPKRYjDKvSxfPs3b1CsXz6bP+/Hoff0aTps2pVq06UVFRHPY9wKIFc1m8ZAXauS4q3b1+jENbZiqeD/hxw9/+3MPb5/Ax5DnDp/soXittaEqv0cvx3Tab66d9kEg08PL+Ait7TySS/42B4v/Fc+9zyPh/ONWhpBIdEP8D9PT0Ck9UiLw9yxKJpNAFY+Li4hgyZAijR4/O956tbc4ww7+y7W3btjF69GhOnTrF/v37mTp1KmfPnqVu3fw/jJA5BWXs2LFKr4W9e6X03MiwDBoaGvkWk5LKovP1yGczMTHOt1CXVBaNaZ5eYz1dXawsLbCytMDT3Y2+g4Zx6sw5unftUuD3NCmtj6aGRr4FJyNj4zAzKngo684z19l26hobfuiDq3XOyJSklFRWHz7PsmHdaFglc+VuV2tzgkI+suvsbyo7IGrXqY+rW84ok+z1P6KlUZia5qxqLpNJcXB0VhlPGUMjNDQ08vWey2RSlasf37h+mZTkZJo0b13g94TMtRrk6elolFG+MqVR2ogMNXc7SI+RQXq60uS4tE/v0TQ0AU3NzPeyaJqURdulEtLtywuNJTdDQ0M1ZUqGaZ6rvtlMTIzzpZfJZJiaqCpTllhZWuLh7k6/QUM4deYs3bt+U2BMOeVcebRIZrlVHZOpsbGK9DLF1W4jwzJoampib6O8OrattTUPnxQ+DFyeGI88Ix2JvvJVPIl+GTLiVS8YmE9GBumf3qNhXC5nm+nppEcqXwXMiApD07LwqSrGhqUzzz2Z8udLZbGYFXFdC1XKmhhhb608Ksfe2pxLt9QP1a1RuwHOrjmdOKmpmYu4RcuiMDHNuZoXLYvC3lH9nUz+SXXq1MUt18r02TFJpbI8dYIMR0fVV96yzw9ZnivnMpkME1PVdW5RlaTjl01RH+S5AiyTSvOd39lMTEyQqUif/ZuU/a9UKsU01+KFMqkUR6fCp9QpjkGeUXuZ57f63z1VdVre0S9paWnMW7iIsPBPLJ4/r9DRDzXrNMA512r5aVm/MzKZVKmcy2RR2DuoLueZvzOaROf5nYmWSTE2ySmXVavXZs3m/cREy9DU1MSgdBm+69WeCuaqR8xBQXVn/u+eTW19ntVGePj4CbLoaHr0H6R4PyMjg18viau5AAC+0UlEQVS2bMf36DF2b91IQRTlPM+Ck1HRsWoXmCyKVbsP07d9K1rVyxyC72xrRWh4FDv8zqjsgKhdx1vpThXZbQSZVJqvjeDoqLpcGma1EfKdHzJpvvrAwMAAAwMDLK2scXP3oHvXTtz47RqNm+TczcOzejNsnXIucKWlZdZRsdERGJrkTNeIi47E0q7w9WUOb5/L03uXGT5tJ8ZK0/3ArUp9Ji0/TXysFA0NTfQMDJk1vCFe5dsWut0/IzksAp0KyiM4dCqUJTU6loykZFIipGSkpaFT3ixPGjOSP6of5VHSzz1ByOt/o2vvP87FxQU9PT3On8+/yI6Hhwf3799XWhjy+vXraGhoFHhbsLy0tbXzrUBcvXp1njx5grOzc75H7l7qwrYLqFzduFq1akyaNInffvuNSpUqsWfPHrXb0dHRwdDQUOmhkycGLS0tXJ2duHc/Zx5aRkYG9+4/wFPN7Q093d24F6A8b+3uvYBCb4col2cofqALolWqFB62FkoLSGZkZPD701dUcVR/K6Ttp66xyf8ya7/vRUV75VuxpaWnk5aenq+3WVMiUVzJzktPXx8LS2vFw8bWHmMTUx7cz2l0JyTE8zzoCW7uqueIamlp4eTsxoOAnDwZGRk8CPhDZZ7zZ45Ts049jIyM1X5PhfR0UkNeoeOS60q7RIKOS0VS3jxXmSX11TM0y1ZQWvNBs5wF6dFSpc4HAL1ajcmIiyb5qeqFP9XR0tLCxdmZgID7itcyMjIICHiAh5oF9Tzd3ZXKIGSXqYIbSPIMedHKlJYWrs6O3L2fM4IpIyODuw8eUtFd9a3kPN1duftAecTTHwEPFOm1tLRwd3HiXZ4pHCEfPlChfMG3IcsMIJ2MsBBK2eZu2EgoZeuqNMqhQBIJGmUtcjosMtJJD3uLhony4oAaJuWQxxY+NF2rVCncHG25/SinAyUjI4Pbj55S2bXoQ1nzquLmzNs8Q6PffQjDvIAVyvX0DTC3tFY8rG0dMDYx49H9O4o0CQnxvHj2BBf3gqcr/VP09fWxtLRUPGxt7TAxMeH+/QClmIKCAnFXM0VOS0sLZ2cXAnLlyTw/AnB3L3haXWFK0vFTxKSlhbOLC/cDApRiCggIULuP3D08CMiVHuDevXuK9Obm5pn7PVeahPh4goKCCq0zsmNycXZW+h3LjOm+2t89D3d3Au7fV3otbx2V3fnw/sMHFs6bi6Fh4X8M5/2dsc76nXkU8EfOd0uIJzjoKW7uqkdVaWlp4ejsysP7OXkyMjJ4eP8PXFXkMTQyxqB0GR7e/4OYaCk16zTIlyb3tl2dnbibr43w8E+1Ef64dx/PrLqzRdPGbFy9nF9WLVM8zExN+aZTexbOnqE2FkVMpUrh7mDD7Uc5a1BkZGRw53EQlV3+ejlPSknN30bQ0FDbRsisD6wUj8z6wJT793N+MxMS4nkWFIi7h/o2grOzKw9y5cnIyOB+wD217YpMcuTk//3T1TOgrLmd4lHBypkyxmUJfpyzMGRSQhxvXzzAzsVL/dblcg5vn8ujO+cYMmUrpuXV30bUoIwJegaGBD++SXxMFJ7Vm6lN+1fIbgZg1ky5A6hs83pIbwZkxpqaSvTdx5RtlrPOBRIJZk29kd1U334p6eeeIOQlOiD+B+jq6jJhwgR++ukndu7cyYsXL7h58yZbtmyhZ8+e6Orq0rdvXx49esTFixcZNWoUvXv3Vky/KAp7e3uuXLnC+/fviYjI7GWdMGECv/32GyNHjiQgIIDnz59z9OjRfItQFqR8+fLo6elx6tQpwsLCiI6O5tWrV0yaNIkbN27w5s0bzpw5w/PnzwtdB6IoOndoz4nTZzlz/gJv3r1j1boNJCUl0bpF5vSVRUtXsGX7LkX6jl+34/bdexzwPcLbdyHs3L2XZ8EvaP9V5qKJiUlJbNmxiyeBQYR9+sSz4GCWrFhNRGQUjRrUL1JMvVrW4/DVu/j9FsDL0HDm7/YnMSWF9vUzFxSautWXVb45q5VvO3WVdX4XmNG3A5ZmxkRExxIRHUtCUuYaGKX1dKnhas+KQ2e4E/SK9xFS/H67h//N+zStVrRV5iUSCV+178LBfbv4/eZ13rx+yaql8zE1LUtt75wfkRmTx3LiWM50hnYdv+HcaX8unjtFyNs3/LJ2OclJSTRrqXyVIPRDCE8ePaBFqy+LFA9A/JUT6Ndpil7NhpQqb4lh5wFItHVJzFo00qj7MMp8kXMbv/gbZ9HQN8CwQx80y5qj4+FF6ebtSbieZzV6iQS9Wo1IvHMV/sJtojp3bM+J02c4c+48b9++Y9Xa9ZllqmVmmVq8dDlbtu9QpO/wdTvu/HGXg76Hs8rUHp4FB/P1V5n7IjEpia07dvI0MDCzTD0PZumKlURERtKoQdF+wL9p/xX+Z85z6vwl3rwLYfn6TSQlJdOmeVMA5i9fzaYdOVOnOrf7kt/vBvDr4WO8DXnP9j2/EhT8go5ftlGk+bbj11y89hv+p8/x/kMoh/1P8tvvf9Dhi8JHsAAk/3EJrcreaHnWQsO0ArotvkGipU3q48xbnuq26YlOg5w50tp1W6Np54bEyAyN8tbote2NhqEJqQ9zFuhKuXMBLbdqaFWui8S4LFpeDSjlWJGUAPV3asmt+1ct8Tt/leOXfuNVSCiLN+8mKTmFL5tknruz1mxl3Z6c8p2alsaz1+949vodaWlphEfJePb6He8+5kwp6/ZlCx49f8l23xO8+/iJ09duceT8VTq3blqkmCDz/Gv7dVeO7N/BnVtXefv6BeuXzcbEtCw16zZSpJs7ZRSn/Q8qniclJvD65TNev8xcAC88LJTXL58R8SnnD+q42Bhev3xGSNYIsdD3b3n98pliTnBBMbXv0JF9+/Zy8+YNXr96xdIlSzA1M8PbO2dqwuRJEzl2zE/xvGPHTpw+dZJz587y9u1b1q5dTVJyEi1btlKkiYqK4sWLF4R++ADA69evefHiBbGxqm8zmK0kHr+OHTty6tQpzp3N+r5r1pCcnEzLli0BWLJkCdu2bVOkb9++PX/88Qe+hw7x7t07fHx8eP78Oe3atVPs9w4dOrBv3z5u3rzJq1evWLJ0KWZmZnjXK9qUkE4dO3Dy9GnOZtVRq9euIykpiVYtWwCweOkytirVUV/nqqPesWv3Hp4HB9P+q8zzMy0tjTnzF/LseTATxo8nIz2DqCgpUVHSInWSZpNIJHzZviuH9u/g9q1rvHn9gjXL5mJiakYt74aKdLMmf8/JY4cUz7/q8C3nT/tz6fxJQt69ZtO6pSQnJdK0Rc5ixhfPHudZ4GM+hr7nysXTLFs4nS/bd8XKuuBFIDt3+FqpjbBy3S8kJSXRJquNsHDpSjbnaiN0+vqrrDbCUd6+C2HH7n1KbQQjQ0Mc7O2UHqVKaWJqYoKNtZXKGPLq8WVzjl68jv/lm7x6/5FFW/eRmJysGKkwY90O1u49qkifu5ynpqUTLs1fzhtWr8T2I6e5dvcRH8IjuXg7gD0nLtCkVtV8n6+KRCLh6w4d2b9vD7du/sbrV69YtmQxpmZm1PXOaftMmfQj/seOKJ536NiZ06dOcP7cGd69fcO6tatISk6iRcvM35GPoaEc2L+X4OfP+PTpE0+fPGbh/DnoaGtTs1bB61NIJBIatunD+SO/8PiPC4S+fca+DRMxNC5PxRo5U5R/md+f62dyfv8Ob5/D3evH6DHiZ3R0DYiRhRMjCyc1JUmR5vZlX948v09E2Fv+uObHrlU/0LBNH8oXMtpO00Afw6ruGFbNbHvpO1hjWNUdXZvMKcVuc8dSdVvOdIg3G/eh72CD+4IfMXBzxG5oDyy+acurldsVaV6t2IbNwK5Y9e5AaXdHKq2dSSkDPd7tyD+1tKB9VdLOvf8FcrmkxD7+vxFTMP5HTJs2jVKlSjF9+nQ+fPiAhYUFQ4cORV9fn9OnT/P9999Tq1Yt9PX16dy5M8uWLftT2589ezZDhgzBycmJ5ORk5HI5VapU4fLly0yZMoWGDRsil8txcnLi2z9xL/dSpUqxatUqZs+ezfTp02nYsCH79+8nMDCQHTt2EBkZiYWFBSNGjGDIkCF/drfk06RRA2TR0ezw2YtUKsXJ0YH5s2cohld+Cg9HopFzIlf0cGfSj2PZvms323b6YGVpycwpE3GwtwMyrxi8C3nP2fOLiImJoYxhGdxcXFi+aH6RV7tuXasS0th41vtdIDImDjdrc9aO7o1Z1sKUH6Oi0ch1peLA5TukpqXz4y/7lbYz5KsmDP06s5G8cFAXVh8+x+Qth4iJT8TC1JgRHZrzTeOi33qvY5fuJCclsWH1EuLj4/DwrMy0OYvR1tZRpPkY+p6YmJzhqg0aNSMmWsZen23IpFE4ODozbfbifFMwzp89iVnZcnhVL3o8SQE3iTEwpHTrLmgaGpP6/g1RmxaSEZd5RVzT2AzkOR0IGbIoojYuwrB9L8qNX0h6tJT4q6eIv+CntF1tl0qUMi1Hwq1LRY4ltyaNGhIdHc1Onz1IpVIcHR2ZN3umYnjzp/BwpStNFT09mPTjuMwytWMXllaWzJw6WblMvQvh7PkLxETHUMbQEDcXZ5YtXljkMtWsYX2io2PYvmc/UVIZTo72LJo5RTEt5FN4hFKZquThxtRx37N1914279qDlaUFcyb/hEOuz2voXYcfhg1mz8HDrN60FRsrS2ZNHE9lz6J1DKY9u0eSvgE69doi0TckI/w9Cb6/KG6tqVHGhIxc02UkOnrotfwWib4h8uQE0sPeEb93JRlRObdiSwt+SNK5A2jXboFu005kRIWTeGwb6R9e5ft8VVrWq4UsJpZNv/oRKYvBxd6a5ZNHK4Y2f4yIUjp24VEy+vw0R/F897Ez7D52hmqerqyfOR7IvNXjovHDWb/Hl62H/LEoX5Yxfb+lTcMCbjeqQrvOvUhOSmLzmkUkxMfh5lmFibOWKZ1/YR/fE5trzZKXwYHMmZzTAbxrS+YaDo2afcGwH6YC8Metq2xYOU+RZtXi6QB07j6ALj2+KzCmLl2+ISkpidWrVxEfF4dnxYrMmT1XacRbaOgHYqJz6oRGjRsTHRONz65divNj9uy5SsP/T544zp49OX8QTPgpc1+O+WGsUkdFXiXx+DVu3JiY6Gh2+fggjYrC0cmJ2XPmKL5v+KdPSueep6cnP02YwM6su09ZWVkxbdo07O3tc/b7N1n7fdUq4uLiqFixIrPnzCnySMOcOmp3rjpqVk5M4eFKMVX09GDij+PZscuH7Tt2YmllyYypU7DPqqMiIiO5eSuz43D4KOUpmIsXzKdqlaLdiQagfeceJCUl8svqn0mIj8PdszJTZi/JU84/EJvrd6Z+o+bERMvY77MFmTQKe0dnpsxeovQ78/79O3bv2EhcXAzly5vTqWtvvupQeNukaaMGmXWnzz5FG2HB7OlKbQSNPG2EyT/+wLZde9i60wcrSwtm5Woj/BNaetdAGhPLxoP+RMpicbWzYuXEEYpyHhYhVTp+4dJoek3KWcfJx/88Pv7nqe7hwobpYwAY368rv/zqz+Jt+5BGx1HWxIiOzRvwXeeiTyno3OVbkpKSWLN6RVZ9UIlZsxcolcuPoaHEROdMk2rYuAnRMTJ279qRVRadmDV7vqIsamlr8fjxQ/yO+hIXF4exsQkVK1Vm8dKV+RZMVKXJVwNJSU7k4JYZJCXEYu9ane8mbEQrV3mKDHtHfK5RcjfO7QNgw9y+StvqOngetRpnrgUTHvqaE/uXkxgXjUk5K5q1H0KjtsrpVTGqUQnv8zkdVp5LJgPwbqcvDwZOQseiHHo2OeubJb4O4fbXQ/BcOgn7UX1ICvnIwyFTiTib06keeuAk2uVMcZ0xGh3zcsTcf8rvX31Hyqc/t8hjSTv3BCE3iVz+//HuosJ/wdvnf+82b59D2Q/3C0/0L3tl1bi4Q8jHdP244g4hn5RhhQ+XLQ5a6cmFJ/qXlT6+tbhDyCe9ecfiDiGfV3r/znSKP8NQs4hrcvzLzOJU30mnOEWVUT9NrrhoZqQVdwj5xMiNizuEfEwo2l0R/m2GsR+KO4R8woxUT90rToHSoo0e+TdpehftFqb/Jpsnf+4W0P+WKi7lC09UAu26UtwRqNe7UeFp/peIKRiCIAiCIAiCIAiCIHx2ogNCEARBEARBEARBEITPTnRACIIgCIIgCIIgCILw2YlFKAVBEARBEARBEIT/LLEq4r9HjIAQBEEQBEEQBEEQBOGzEx0QgiAIgiAIgiAIgiB8dmIKhiAIgiAIgiAIgvCflSGmYPxrxAgIQRAEQRAEQRAEQRA+O9EBIQiCIAiCIAiCIAjCZyc6IARBEARBEARBEIT/LLm85D4+l6ioKHr27ImhoSHGxsYMHDiQuLi4Iu4vOW3btkUikXDkyJE/9bmiA0IQBEEQBEEQBEEQ/kN69uzJ48ePOXv2LP7+/ly5coXBgwcXKe+KFSuQSCR/6XPFIpSCIAiCIAiCIAiC8B/x9OlTTp06xe3bt6lZsyYAq1ev5osvvmDJkiVYWlqqzRsQEMDSpUu5c+cOFhYWf/qzxQgIQRAEQRAEQRAEQSiBkpOTiYmJUXokJyf/rW3euHEDY2NjRecDQIsWLdDQ0ODWrVtq8yUkJNCjRw/Wrl2Lubn5X/psMQJC+J+VqqlT3CHkI7WoWNwh5CNNMSzuEPIxGDazuEPIRy4pmf2xH7Ap7hDySftiVnGHkE+ZUgnFHUI+KWkl7yc2XbPkxQQQVabklfOSKFVS8n737GIeFHcI+XwycinuEFSKNfQs7hDyKZ/4prhDyMdAp3xxh5BPuSdXizuEfN55NizuEFSqkhpU3CH8v7NgwQJmzVJue82YMYOZM2f+5W1+/PiR8uWVz7VSpUphamrKx48f1eb74YcfqFevHu3bt//Ln10yWyKCIAiCIAiCIAiC8B83adIkxo4dq/Sajo7qDumJEyeyaNGiArf39OnTvxSHn58fFy5c4N69e38pfzbRASEIgiAIgiAIgiD8Z33Ou038XTo6Omo7HPIaN24c/fr1KzCNo6Mj5ubmfPr0Sen1tLQ0oqKi1E6tuHDhAi9evMDY2Fjp9c6dO9OwYUMuXbpUpBhFB4QgCIIgCIIgCIIg/I8rV64c5cqVKzSdt7c3MpmMP/74gxo1agCZHQwZGRnUqVNHZZ6JEyfy3XffKb1WuXJlli9fTrt27Yoco+iAEARBEARBEARBEIT/CA8PD9q0acOgQYPYsGEDqampjBw5km7duinugPH+/XuaN2/Ozp07qV27Nubm5ipHR9ja2uLg4FDkzxYdEIIgCIIgCIIgCMJ/VkYJnoLxuezevZuRI0fSvHlzNDQ06Ny5M6tWrVK8n5qaSlBQEAkJ/+xC36IDQhAEQRAEQRAEQRD+Q0xNTdmzZ4/a9+3t7ZEXsjhGYe+rUjLvOycIgiAIgiAIgiAIwv8rYgSEIAiCIAiCIAiC8J9Vku+C8f+NGAEhCIIgCIIgCIIgCMJnJzogBEEQBEEQBEEQBEH47EQHhCAIgiAIgiAIgiAIn53ogBAEQRAEQRAEQRAE4bMTHRCCIAiCIAiCIAiCIHx24i4Y/zFNmjTBy8uLFStWFHcowOeJRy6X47NrF6dOnSI+Ph5PT09GjByJlZVVgfmOHTvGoYMHkUqlODg6MmzYMNzc3BTvp6SksGnTJq5cvkxqairVa9RgxIgRmJiYFBrTkeMn2e/rR5RUhpODHaOGDMTD1UVt+kvXfmObzz4+fgrH2tKCQf16UbdmdaU0b96FsHG7Dw8ePSE9PR07G2tmThpPhfLlCo0HMvfT0b0buHLuMAnxsTi7V6X3kMlUsLRVmyfo8R+cPrKT1y+eEi2NYMTEpVSv01QpTVJiAod2reLe75eIi42mbHlLWnzZnSZtuhQak5//cQ4e8iVKKsXRwYHhQ4fg7uaqNv2Vq9fY4eNDWNgnrCwtGdi/H7Vr1QQgLS2N7Tt9uH3nDqEfP2JgYEA1r6oM7NcXMzOzIu0jAL9j/hw8dAhpdkzDhiqVi/wxXWXnLh/CwsKwsrRkwID+1K5VS/H+tevXOXHiJM+Dg4mNjWXt6lU4OTkVOZ5scrmcQ3s2cfHMUeLj43D1qMyAYT9hXsDxe/roHscP+/DqRRCyqAh+mLyImnUbK6U5tGcTN66eIyoiDM1SWjg4u9G111Cc3SoVKabDezZy6ewREuLjcHGvQt9hEwqMKfDxXU4e9uF1cCAyaQSjJy2mRt0mSmk2rZzFtQvHlV6rXK0u42euKlJM+3y2cfa0Pwnxcbh7VGLwiLFYWlkXmO+k/2GOHNqHTBqFvYMz3w0djYubBwCfwkIZOqC7ynzjJ86kXsMmKt/LG9fn2FcAH969Yv+ONQQ9vkt6ejpWNg6MmrgIs3Lmhca0x2cHZ06dID4+Dg/Pigwb8X2h++r4saMcPvQrUmkUDg5ODB42Elc3d5XbnzV9Mnf/uM3kqbOoW69+gdvNzvM56vOTJ05w6dIlgoODSUxM5NcDByhdunSh8XzOmP7Ob4xcLme3z05OnzqpOHbDR4wuNCb/Y374HjqQdewcGTJsBG5Zxy42NobdPru4d/cPwsM/YWRkRF3vevTq3Q8DA4NCYzpw5jI+x84RGR2Di60V4/t1paKzvcq0L959YOPB4wS+fEtoRBQ/9O5M9y+aKaVJz8hg08HjnLx2myhZDGVNjPiqcV0GdGyDRCIpNJ5sJXFfyeVy9vps49zp48Rn1VNDRvxQ6Ll3wv8wRw7tz6qnnPhu6Ghcs+qpbIFPH7N75xaeBz1FQ0MDB0dnps9ZjI6OToHbPnTyHHuOniRKFo2zvS0/DOyFp4ujyrQv375n8z5fgl6+5mN4JKP7d+fbr1orpdnp68/lm3/w5n0oOtpaVHZzZljvrthZWRS6f7LJ5XL896/j+jlfEhNicXTzovvgKZS3sFOb55TvFgJunSfs/Su0tHVwdPOiY68xVLCyByA+Nhr/X9fx9P4NpBEfKW1oQtVaTWnXbQR6BmWKHNf+3Vs4f/pY1vGrzKDh47Cwsikw3yl/X/x89yKTRmHn4MSAIWNwcfNUvP8x9D07t6wl8MkD0lJT8apRhwFDxmBsYqp2m6YNauI4biBG1Suha1meO52HE+Z3vsA4TBvVxnPJREp7upD0LpTgBesJ2XlYKY3dsB44jh2Ijnk5Yh4E8njMHKJvPyzC3vnfkZFR3BH8d4gREMKflpKSUtwhFOjggQP4+fkxctQolq9Yga6uLtOmTi0w7suXL7Np40Z69OzJ6tWrcXRwYNrUqchkMkWajb/8wu+3bjFp8mQWLV5MVGQkc+fOLTSei1evs37zDvp0/4ZfVizGycGeCdPnIpVFq0z/6Gkgc39eQdtWzdm48mfq163F9HmLefXmrSLN+9CPfD9hKrbWViybP5NNq5fSq1sXtLW1i7yfTh7ewbnje+k9ZDJTFu1AR0ePZbNHkJqSrDZPSlIS1vau9Bo8UW2a/duW8ujeb3w3Zi5zVx+iZbse7N60iIDfLxcYz6UrV9m4aTM9e3Rn7aoVODo4MGXadKVjkNvjJ09ZsPhn2rRqxbpVK6nnXZdZc+fx+vUbAJKTkwl+8YIe3b9l7aoVTJ8yiZCQ98yYXfgxy3b58hU2bdpErx49WLN6FY6ODkyZNk1tTE+ePGHhosW0btWKtatX4e3tzew5c3n9+rUiTVJSMhUrejKgf/8ix6GKv+8uTvv/Sv9hE5j982Z0dPRYOGMMKQUcv+TkRGwdXOg3ZLzaNOZWtvQbMo6Fq3czY9EvlCtvwcIZ3xMTLS00phO+Ozl7fD/9hk1k+s9b0dHVY8nM0QXHlJSEjb0LvYf8WOC2K1f3ZuX2E4rHsPFFO46HD+7l+LFDDB0xloXL1qOjq8ecaT8WGNO1KxfYtmkdXXv0Y8mqTdg7ODF72o/IZJn7wKxsebbsOqT06NazP7p6elSrWbtIcX2ufRUWGsLcSYOwtLZj0rwNzF25h6+7DkRLq/C6wffgfvz9DjNs5Pf8vHwNOrq6zJg2scC68+rli2zZtIFuPXqzfPUG7B0dmTFtomJf5eZ35NCf+kMRPl99npycTI2aNfm2W7c/Fc/njOmv/sYAHDr4K8f8jjBi5GiWLl+Frq4u06dNKjCmK5cvsXnTL3Tv0YuVq9fh4OjI9GmTFccuMjKSqMhIBnw3iLXrNzLmh/H8cecOK1csLTSeszf+YMUuX77r/AU750/Exc6a0QvXEBUdqzJ9ckoqVuXNGNG9PWbGhirT7PQ7w6GzV/mxX1f2L53GyB7t2XXsLL+evlT4DsqlpO0rgMMH93H8mC9DRvzAomXr0NHVZfa0nwqMKbOeWs+3PfqydNXGrHrqJ6VzL/DpY+ZMn4BXtZosXr6On1es54t2HdDQKPg8PHf9Fqu372NA1w5s/XkWznY2jJ2zBGl0jMr0ySnJWFYox7Be32BmbKQyTcDjQDq1acbGBdNYMeNH0tLT+WH2EhKT1Nd5eZ09so1LJ/bSffBUfpzvg46OHqvnDCuw3RL85A6N23zLjwt2MXr6L6Snp7F6zlCSkxIAiJZ+IjoqnE59xjJ12SH6jJjNk4Dr+KyfWeS4jh7aw8ljhxg8YjwLlv6Cjq4ec6ePK7A+v37lPDs2r+Gb7v1YtHIzdg7OzJs+juis45eUlMjcaWORSCTMmL+SOT+vIy0tlYWzJ5JRwF/Kmgb6xDwI4tHoWUWKXc/emlp+vxB56RbXarbn1eodVP5lLmVbNlCksfimLR4/T+L53LVcq92R2AeB1Dm+Be1y6jtCBKEgogPiP6Rfv35cvnyZlStXIpFIkEgkvHjxgoEDB+Lg4ICenh5ubm6sXLkyX74OHTowb948LC0tFVdsfvvtN7y8vNDV1aVmzZocOXIEiURCQECAIu+jR49o27YtpUuXpkKFCvTu3ZuIiAi18eT+Q+2vkMvlHDlyhG7duuHt7Y2DgwPjxo8nMjKSG7/9pjbf4cOHadO2La1atcLWzo6Ro0aho6PDmTNnAIiPj+fMmTMMGjQILy8vXFxc+GHsWJ4+eULg06cFxnTgyDG+aN2Cti2aYW9rww/DB6Ojo8PJsxdUpvf1O0Ht6l5069QeOxtrBvTqjouTA0f8TyrSbN21h9o1qjOkf29cnByxsjCnfp1amKj54Ve1n8757+Grb76jWp0m2Ni7MvD72ciiwrl765LafJVr1KdTzxFUr9tMbZrgwAfUa9oO90o1KVveksatOmNj78LL548KjMn38BHatGlN65YtsLO1ZfTI4ejo6nD6zFmV6Y/4+VGzRnW+6dwJW1sb+vbuhbOTE0f9/QEwMDBg4bw5NG7YEBtrazzc3RkxbAjPg4P59OlT4TsJ8D18mDZt2tCqVUvsbG0ZNXIkOjq6nM4qF/liOupHzRo1+KZLZ2xtbenbpzfOTk74HfNXpGnRvBk9e/SgWjWvIsWgilwu55Tffjp07U/Nuo2wdXBh2A8zkEVF8MfNK2rzedWoR9deQ6nl3URtmvqNW1PJqzblza2wtnWk58AxJCbE8/Z1cKExnT62j3bfDKB6ncbY2rsweMxMZFER3L2pvvOpao16dOk1jJreTdWmAdDS0sLYpKziYVBa9R8peWPyP3qQLt/2prZ3A+wdnBg9bhJRURH8fuOa2nzHDh+gZZsvad6yLTa29gwZORYdXV0unDkBgKamJiamZkqPWzeuUr9BU/T09IsU1+faV4d81lO1Rn2+7TcaO0c3KlhYU71OIwyNC24oyuVy/I740rVbT+p618fBwZEfxk0gKjKSmzeuq8139PAhWrX5ghat2mBra8fwkWPQ0dHh3JlTSulevgjmiO9BRo9R3/mlKqbPUZ8DdOjYka5du+Lunn+kRnHE9Hd+Y+RyOUePHObbbj2o610PBwdHxo77iajISG4UcOyOHD5E6zZtadmqNba2dowY+T06OjqcPXMaAHt7ByZPnU6dOt5YWFhS1asaffr25/dbt0hPTy8wpj3Hz9OhWT3aNfHG0dqCiQO7oautzbFLN1Sm93SyY3TPTrSqVxPtUqoH5z549opGNavQoHolLMuZ0bxOdepU8eBx8JsCY8mtJO6r7Hrqm297Uyernvo+q566VUA95ZennhqaVU+dP5PTVti2aS1fft2Jzl17YGvngJW1LfUbNi20Q3L/sdO0a9GYL5s1xMHGih+H9EVHRxv/86p/XzycHRnZtxstGtRFS0v18Vs2bTxfNmuIo60VLva2TBn5HWERkQS9eF1gLNnkcjkXju+mTedBVK3dFGt7V/qOmku0NJz7v6tuTwGMnLoe76btsbRxxtrejT4jZhMVEcrbl5nnlaWtC4N/XEaVmk0oZ26DW+U6fN19FA/vXCY9Pa1IcR0/+iudv+1DrboNsXNwZuTYKUijIrl946rafP5H9tO8dTuatvwSG1sHBo8Yj7aOLhfOZo72C3rykE+fPjLih8nY2TthZ+/EiB+m8DI4kEcP7qrdbvjpKzybsYKwo+cKjR3AbnA3El+F8PSnRcQFvuTNut18PHQah+/7KdI4jOnPuy2/ErLDl7inL3g4fAbpCUnY9OtcpM8QhLxEB8R/yMqVK/H29mbQoEGEhoYSGhqKtbU11tbWHDhwgCdPnjB9+nQmT57Mr7/+qpT3/PnzBAUFcfbsWfz9/YmJiaFdu3ZUrlyZu3fvMmfOHCZMmKCURyaT0axZM6pVq8adO3c4deoUYWFhdO3aVW08NjYFD1crzMePH5FKpXhVq6Z4zcDAADc3N54GBqrMk5qaSvDz53h5eSle09DQwMvLS9Hwe/78OWlpaUrbtbGxoVz58mq3m73tZ8EvqVG1itK2a3hV5klQkMo8TwKfUd2ritJrtap58TjwGQAZGRncvHMXGysLfpo+h069BjB83ESu3fhdbRx5RYS9J1oagWfVOorX9A3K4OhSiRdBD4q8HVWc3asQcPsy0shPyOVyAh/e5uOHt1T0qqs2T2pqKs+Dg6nuVVXxmoaGBtW8vHgSqHo/PQ0MpFquYwZQo3q1Ao9HfHwCEokEgyIMtc6OqVqeclHNy0vtZzwNDMzXsVCjRvUCY/orwsM+IJNGUrFqztQOfYPSOLlW5HnQPzckMi01lYunj6BvUBo7B/VThrJjipZGUrFqzggAfYPSOLpWJPgfiCnw0V1G9mnNhGFd2L5+IXExskLzhH0MRSaNoqpXDcVrBgalcXHzJCjwico8qampvAgOokquPBoaGlTxqqE2z4vnQbx6GUzzVl8U6bt8rn2VkZHB/TvXMbe05ecZoxjZpzWzxvfnj5uXCs0b9jEUqTSKql45U70MDErj6uZB0FP1+yo4+BleufJoaGhQ1as6gbn2VXJSEksXz2fI8FGYmBb9itnnqs//jpL2GwMQ9vEjUmmU0nHIjMld7XfOPHbP8fLK+bzMmKoRGKh+P8XHx6Ovr4+mpqbaNKlpaQS+eketSjmdOxoaGtSq5M7D5y8L/C4FqeLqwJ1HQbwJDQPg2ZsQ7ge+oJ6XZyE5c5S0fZUZU/a5l7ee8iAo8LHamF4EP1PKk1lPVVfkkcmkPAt6ipGRMRPHjaRfz05MmfA9Tx4XXMekpqYR9OI1tark7FcNDQ1qVqnIo2cvCsz7Z8QnJAJgWKbwKSoAkZ/eEyOLwL1KTrtFz6AM9i6Vefms6O2WxIQ4gAI7sRMT4tDVL42mZuEz1T+FZf7OVPaqqXjNwKA0zoUcv5fBz1T8ztTkWVae1NRUJEjQ0tJSpNHW1kYi0SDw8d9rp+VmXNeLiAvKHYPhZ69hUtcLAImWFkbVKxJxPlcHq1xOxIXfMK5bjf9P5PKS+/j/RqwB8R9iZGSEtrY2+vr6mJvnzAWeNStnmJaDgwM3btzg119/VXQUQOYP9ObNmxVD/Dds2IBEImHTpk3o6uri6enJ+/fvGTRokCLPmjVrqFatGvPnz1e8tnXrVmxsbHj27Bmurq4q41ElOTmZ5OTkfK/lncMolWYOXcs7Z9bYxETxXl4xMTFkZGSozPMuJESx3VKlSuWbI2xibIw0Kkpt3NExsVnbVh6ZYGJszNuQ9yrzRMlkmBgb50lvhDRrqK4sOprExCT2HjxC/17dGNyvF7//EcCMBT+zbN5MqlauqDYeRVyySAAMjZT/GDA0NiNGFlFo/oL0GDSBnevmMv67NmhqlkIikdB3+DTcKtZQmyf7GBgbKx8DE2Nj3r0LUZlHKlW1n4yRSmUq06ekpLBl23aaNG6EgX7hV6kVMZkof4axsTHv3r1TE5MUY+P86dWVvb9KJs08fkZ5rmobGZsq3vs77t6+xpqfp5GSnISxSVkmzl5FGUPjAvNEq4nJ0NhU8d5fVbmaNzXqNqVcBUs+fQzh4K71LJk9humLtqBRQONeJs08N43yzJc1NjZBKlV93sbGRGeVxfx53r97qzLPuTMnsLaxw92z8HUy4PPtq5joKJKSEvA/tIPOPYfSte8oHt69weqFE5g4dz3ulaqrzZtdRo3z1oPGxmr3VUz2vsqXx4T3uc6RzZvW4+5Rkbreha/5oCqmf7o+/ztK2m9MZt6orO0ZK2/f2ARZITGpOnYhauq36Oho9u3dTZu2BXe0yWLiSM/IwNRIef68qVEZ3nz4WGDegvT9uhXxiUl0HTcHDQ0JGRlyhnVtR5sGRZv2BCVvX0Hueir/9mWF1FNGxqrOvcx6KuxjKAD79uyg38ChODg6c+n8GWZMHsfKdVvVri8hi43NPH55RlSaGhny9n1ood+nKDIyMli5bQ9V3F1wtC14nYts0dLMtomhsfIaToZGRW+3ZGRkcHDbYpzcvbC0Vd2pHhcj5eTBjdRvUbSr+9m/uXnbL8bGpshkBR2/dBW/4Sa8D8kc0ePi7omOri4+2zbQo89g5MjZvX0DGRnpSP+B3/lsOhXKkhymvP+SwyLQMiqDhq4OWiZGaJQqRfKnyDxpIjFwU70miCAURnRACKxdu5atW7fy9u1bEhMTSUlJUbpSA1C5cmWl9QWCgoKoUqUKurq6itdq11ZuBNy/f5+LFy+qXNjrxYsXuLqqX1wwrwULFih1lACMGj2aKpUrs3r1asVredP8f5SRkdkVWq9OLb7p0A4AZ0cHHgcG4XfqjMoOiJuXT7BzwzzF8++nFL543191/vg+Xjx7yKjJyzErZ8GzJ3fx2bgQY9NySiMu/k1paWnMW7AIkDNqxPBiieHvuH7pFFvWLVI8/3F60eYV/1WelWswf8VOYmOiuXjmKKsXTWHWki1KjaXfLp1i+/oFiudjpy3/bPHUbdRK8X8be2ds7F34cUhHnj76Q2kUweWLZ/llTc6+mTJz4WeLKVtycjJXL5/jm2591Kb5t/aVPKtuqF6nEW3a9wDAztGV54EPuHDKV6kD4tLF86xbnRPH9Fnz+Bxu3fyNB/cDWLF6Q6FpL164UOLq8xIZ08XzrF2dM1Vyxqyir2vzVyUkxDNrxlRsbW3p0bP3Z/88Vc7dvMupa7eZM7IfjtYWPHsTwrKdhxSLUapSEvfV5Ytn2bBmmeL5lJkL8qX5J8iz1glo3fYrmrdsC4CjkwsP7t/l/NmT9O43qKDsn9XSTbt4+TaE9fOmqE3z+5Xj7N04R/F82KQ1f/tz92+ez4d3Lxg3d7vK9xMT4lg3fyTm1o581XWoyjRXL57hl7VLFM8nzVikMt3fZWRkwriJs9m0biknjx1EItGgfuPmODi5/um1dAShpBEdEP9x+/btY/z48SxduhRvb2/KlCnDzz//zK1bt5TSFWUV57zi4uJo164dixblr5wtLIq+6jHApEmTGDt2rNJrIe/fk56ejluuObypqalA5tUk01xDfWVSKY5q7jRgaGiIhoZGvqtXMqkU06wrEiYmJqSlpREXF6fUoSKVyQocUmxkWCZr28oLTkplMkzzXIHJZmpsrBjtkJM+WnG138iwDJqamtjluWpgZ2PFwyeqh+pWrd2YGa45V2fTsvZTTHQUxqY5d82IkUVi46D+Dg+FSUlOwnf3GkZMWErVmg0BsLF35d2rZ5w+ulNtB0T2Mci7cJ1UJlO7AryJiar9JMMkz35NS0tj3sJFhIV/YvH8eUUa/aAUU54RFTKZDBNTdTGZ5FugUlbAdyiq6rUb4uSa07GUlpZ5/KJlUZiYllW8Hi2Lws6x4KkSRaGrq4e5pQ3mlja4uFdi7JAuXDp7jPbf9FWkqVa7IU5uOTGlpqYoYjDOFVOMLApbh6J3NhZFeXMryhga8yk0RKkDonad+korwGfXB9HSKExNc66ayWRSHBydVW67jKFRVllUvnIlk0lVrjx+4/plUpKTadK8db73sv1b+6qMoTGamppY2jgovW5pY8+zJ/eVXqtdx1vpThXZdYJMKs2zr2Q4OqqrO7P2Vd66UybFOOsceXA/gI+hH+j+TXulNAvnz8KzYiXmL8r5Q6xO3br/Sn3+Z/xbMf2Z35g6dbwVd1/IHZNMKlNRzguOSdWxy/t5CQkJTJ82BT19faZMm0kpNWs0ZDM2LI2mhka+BSejomPVLjBZFKt2H6Zv+1a0qpc51N3Z1orQ8Ch2+J1R2wFREvdVZj2VM71BUR/kO/cKr6eiZSrOvax6yiRrW9Y29kpprG1siQgPU7ldAOMyZTKPX56FsqOiY/KNivgrlm7axW9/3GftnEmUN1PffqpSqwn2LpUVz9PSMvdTjCwSI5Nc7ZboSKztC2+37N88n4d/XGHs7K2YmFXI935SYjxr5g5HR8+AIT8tR7OUloqtQM06DXDOdfwUdadMqvR7LJNFYa9m6mLm8dMkOs/vTLRMirFJThmoWr02azbvJyZahqamJgaly/Bdr/ZUMLcs9PsWVXJYBDoVyiq9plOhLKnRsWQkJZMSISUjLQ2d8mZ50piR/PHvjZgV/rvEGhD/Mdra2koLIl2/fp169eoxfPhwqlWrhrOzMy9eFD7Hz83NjYcPHypNi7h9+7ZSmurVq/P48WPs7e1xdnZWemR3aOSNRx0dHR0MDQ2VHjo6Oujr62Npaal42NraYmJiwv1cC2EmxMcTFBSEh5rFxrS0tHB2cVHKk5GRQUBAAO4emX/MuLi4UKpUKaUFNkNCQgj/9EntdrO37ersyN0HOXMuMzIyuHv/IZ5qbuXo6e7K3fvKczTvBNynorurYptuLk68C/mglObd+1AqlFN9C049PQMqWNgqHpY2jhiZlOXpg5x1IxIT4nj5/BFOblVUbqMo0tPTSE9LQ0OiXLVoaGgoRm6ooqWlhYuzM/cCcuY1Zh6D+3i6q95PHu7uBNxX/qPq7r0ApeOR3fnw/sMHFs6bi6Fh0Ru/2TEF3A/IE1OA2mPu4e5OQEDemO4VWEaKQk/fQNEhYG5pg5WNA8YmZjy+n3POJSTE8+LZY1zcKhewpb9GLpeTlqq8GruevgEVLGwUDysbR4xMzPi/9u48rqb8/wP46xYt2hRF0qqmRFGyjbFnbUTZhmxlGVvSYhtkhCwja76yK/u+L6U0lkKIyoR2JSEltGk7vz/6dXTdwiydc9L7+Xj0eOjcO9/7+nZvt3ve5/N5v2OjP2UqyM9FUtxfMPyPM2W/eYXcD++goir+oUm+QQNoNmvOfmnr6KGhqhqioz417MrPz0P801gYm1S9b7x+/fpoYWiM6Ief/puysjJEP7xf5X8TEnQBVh1/hIpKw2rzcvWzqle/PvQNTfEyXXyryMv0VDTWEN/mVv7eqcV+aevoQlVVDVFRD9j75OfnIe7pYxi3rP5nZWj4A6KiPv9ZPYDJ//+shg3/BZu2bMdG323sFwBMnDwNs1zFp3lw9X7+dwjxb8znz53O/z93Dz977p4+fVLt/+fy584IUZ+9v0U9fAgTk0//TX5+HhYvWoB69ephsefSb5q0VL9ePZjoa+Puo0/9e8rKynDvr6cwq2aM47coLCqWuPIr/ZW/LUL8WZW/T2mxX9o6elCt8n3qMYxNqt5SWf4+9YPE+1TMw0j2v9Fo0hRqjRrjRbr4NpEX6c+hriF5Av7pf7sejFvo4V7Mpz4uZWVluB8di9Y//P2R0RUYhoHPjn24HnEfm36fi2ZNvjwyXE5eARqaOuyXZvMWUG7YGE9jPl0gK8jPRUp8DAx+qP5zC8MwOLLTGw8jrmL27zvQuInklo+C/FxsXjYV9erVx7T5G1FfpvoRpZ//nWn+/39nHj28z94nPz8PCV95/gwMf0BM1Kf/pqysDDFR9/FDFf+NskpDKCgqISbqPt6/ewurjj9J3Oefyrn9EI16iRfwGvf+EW9vPwQAMMXFeBf5Fxr36vzpDiIRGvXsjJzbD0DIP0EFiDpGT08Pd+7cQUpKCt68eQMjIyPcu3cPgYGBiIuLw+LFiyUKCVUZPXo0ysrKMGXKFDx+/BiBgYFYu7Z8SVrFB4QZM2YgOzsbo0aNwt27d5GYmIjAwEA4OjqyRYfP83xptNC3EIlEGDJkCA4fPozbt28jOTkZa3180KhRI3T+8Uf2fgvmz8e5s2fZ7+3s7HD58mUEX7mC1NRUbPH1xcePH9GnTx8A5StA+vbtix07diAqKgrx8fFYv24dWrZs+dUPtcOHDMKFwGAEhvyJZ2nPseF/O1BY+BH9rcs72a9ctwk7/A+w97e3HYi7kQ9x9NRZpKalY+/BI4hLSMKQnwew9xlpPxh/3gzH+cArSH+RgVPnL+FWxD0MHlj9VdjPf07WP4/G+WM78TDiGp4/i8fOjZ5oqKYOy4492Pv94fkrQi4eZr8vLMhHavJTpCaXf7B88yodqclPkZVZvi9UvoEijFu1w1H/DXjy6B4yX6Xj5tWzCP/zAiw7fXnKgb3dEFwKDMSV4BCkpqZh85b/obCwEH37WAMA1visw+69/uz9h9ja4t79SBw/eQqpaWnYd+Ag4hMSMPjnnwGUFx+Wea9CXHwC5nl4oKy0DNnZb5Gd/Za9CvY19nZ2uHQ5EFeCg5GamorNW7ag8GMh+v7/6+KPtT7YvWfvp0yDbXHv/n2cOHkSaWlp2Lf/AOLjE2A76Gf2Ph8+fEBiYiJSU8tPEp8/T0diYiKyv7LPuzKRSIT+tiNx+uhe3L9zHakpCfBbvxQN1RqjXadu7P28F81E0Plj7PeFBflISYpDSlJ5Q9PMVy+QkhSHN5nl+7ILCwtwJGAr4p88QubrDCQnPMH2jcvxNisTHX/q/dVM/Qb9grNHdyPyznWkpSRg+4bf0VCtMSw7dWfvt3rxdFy58KnJbWFBPp4lxeFZpUzPkuKQVZGpIB+H92xCwtMYZL56gb+iIrDBew40NJvDzLL6xqYVmX4ePAzHD+9DxO0wPEtJwiYfb6ipNUaHzp8+wC35zQ0Xz51kvx9kNxzBgecRGnwZz1OfYduW9fhYWIhefQaI/e9nvHiO2EfRsO5r88UcXP2sAGCA3RjcuXkFfwadxquMNFy5cBQP795E7wHDvprJdog9jh4+gDu3w5GSnIT1a1dDrVEjsd4NixbMwflzp9nvB9sNRdDliwgJDkJa6jNs3bIRhR8L0btPfwCAqpoadPX0xb4AQF1dA02bfnklXE29nwNAdnY2EhMT8eJFeSE3JSUFiYmJ+PCh6jGRNZ3p3/yNEYlEGDzEDkcOH8Sd27eQkpyMdWvXQK1RI3Su9Nz9tmAuzp07w34/xG4oAtnnLhX/27IJhR8LYd2n/O9Ifn4eFi9cgI+FhXCZ7YaC/Hy8zc7G2+zsr144GG3TG2dCw3D+2m0kp7/E6t2HUfDxI7tSYcn//LHl0KcsxSUliEtJQ1xKGopLSpH5NgdxKWlIe/lpYlFXy9bYezoQNyMf4UVmFkLvPsTBi1fRo30bicevTT+rivepY5Xepzb6rISaWmN0rPQ+5fmbGy6eO8V+b2s3HFcCz+Nq8GWk/f/7VGHhp989kUiEIfYjceHsSYTfvIaMF+k4uG830p+nfrVh7shB/XAu+Bouht5EyvMXWLs9AIUfP8KmV/nKxmWbtmPr/k9/W4qLSxCX/Axxyc/Kn7+st4hLfobnGZ9WWvjs2Ieg6+H4ffZUNJCXQ9bbHGS9zcHHj9822l0kEqGXjQMundiB6Lt/Iv1ZPPw3L4KKqjradPg0mWvj75Px56VD7PeHd3oj4vpFOLqsgqycAt69fYN3b9+g6GMhgE/Fh4+FBRgz/XcU5Oex9yn7hgtkIpEINoNH4MQRf9y9cxPPUhLhu245VNUaoX3nruz9lv7mgkvnTrDf/zxkJEICz+PPkEt4npaCHf/zwcfCAvS0/vTchF65gLgnf+FlRjquhwZi3SpP2AweAa3mOtXmkVZoAOU2JlBuU164bKDfHMptTCCnXf5+a7zcDW32fFqZ/Gz7YTTQ14bJyjlQMDaA7tTR0Bw+AMkb97L3Sd6wB9oTR0Br7BAomhig9ZbfUU9BHmn+J0HIP0FbMOoYDw8PjB8/HqampigoKMCTJ0/w4MEDjBw5EiKRCKNGjcL06dNx6dKlL/7vKCsr49y5c5g2bRratm0LMzMzeHp6YvTo0WxfiGbNmiEsLAzz5s1D37598fHjR+jq6qJ///6QkpKqMk9ycjL09PT+1f/HYcOHo7CwEJs3bUJubi5atWoFr2XLxK5GZGRk4N37T/Osu3fvjvfv3mHf/v14m50NgxYt4LVsmdjS+Sm//gqRlBRWLF+O4uJitGvXDtNnzPhqnp5duyDn3XvsOXAYb9/moIWBHlYvXchuwXid+UZsxUDrliZY6OGC3fsPY1fAQWg104TXwrnQ1/30B6dr545wnT4ZB4+dgu/2PdDWaoalCzxg1urbr/ANsBuPosIC+G9djvy8DzBq2Raui33FKv+ZL5+LTRtISYzFH4unsN8f2VO+fPrHnoMw8f9nTv/qvhIn9m/GjvULkZf7Ho3UNWE3egZ69PvyCVCPbl3x7t07BOw/gLdv38LAwAArvJayz0FmZiakKl39amXaEvPneMB/337s9Q9AM61mWLJoIfT0dAEAb7KycPv/txJNd54l9lhrVnqjjfnXrzR3794N796/w759+9lMy7282EyvMzMhqjRP3dTUFPPmzoF/wD7s3euPZlpa8Fy8SOw1fev2baxbv4H9fuX/b1FyGD0aY8c4fDVThZ/tx+JjYSF2bVmF/Lxc/GBqjnm/b4BMpefv1cvn+FDp+UtKeIwVCz+9ZvfvKt8b3bXXQEyd7QkpKSm8eJ6CG1cv4sP7HCgqq8DAsCUWr/JDc52vX7kcaD8OHwsLsfd/3sjPy4VRyzbwWLJRLNPrl+lir6nkhMdYtWga+/2h3eU/m5962WCyyxJISUkhLSUeN0MvID/vA1TV1NGqbUcMdfj1q6PkAMBu2Ch8LCyE3+a1yMvLRUtTMyxetkYs08uMdLx//2m58U/deuH9uxwc2r8HOW+zoW9giMVeayS2YIRcuYRGjdXR1rI9/q6a+FkBgFXnnpgwbT7OH/fH/h0+0NTSgfP8VfjBtO1XM9kPG4nCwkJs2bweebm5MG3VGr97rRJ773yZ8QLv3336WXXt3hPv3r/DwX17//93pAV+91r5r7cdVaip9/OLFy/i4IFPhd+5c8pXY7i6uYkVKrjM9E//xgDA0GEjyjNt3sA+d15e3p89dxliz1237j3w7v077N8XwL6/eXmtYDMlJCTg6dPybX2TJ04Qe7xdewLQpEn1zaP7dG6Ht+8/YPvx88jK+YAfdLWwcf4MdgvGqzdvxd7PM9++w5gFn3q27D8fgv3nQ2DZ0gh+nrMBAB4TRmDb0fNYs+cw3r7LRWNVFdj1/gmThooXBmvbzwoA7Ib9gsLCAmzd7FPpfWq15O+exPvUOxzevxdv32ZD36AFPL1Wi71PDRoyDEVFRdi9YwtyP3yAnn4LLFm+FpqaWl/MY92lI3LefcDOw6eQnfMORvo68Fnkzm7BePUmS2w1ypu3b+HosYT9/tDZyzh09jIsWhnD12sBAOBUYPmozJme4r15fpsxkS1sfE2fIY74+LEAB7d5IT/vA1qYWGDmov+Jf255Jf655UZgeRF3w5KJYv9bY2d4oXPPwUhLeoyU+PJVp0tm/ix2n2X/u4hGGl/+WQHA4KGjUVhYgG2b/0B+Xi5MTM2w0GvtZ3+PX+BDpeevS7feeP8uB0f270LO22zoGRhioddasecvPT0NB/y3Izf3PTQ0msJ+xFj8PGTkF7OotGuNziH72O9N1/4GAEgLOInoiQsgq6kOee1Pxd+ClOe4a/srTH0WQM95HAqfv0TMr4vw5sqnEbAZxy5BRl0NPyyZBdmm6ngf9RgRP09C0ev/rhmmEHyP0yaESsQw9OMm/40DBw7A0dER7969g7y8fI0/XmLSPx/nVVPkSvL4jiAhuUR4XYqby1Q9AYRPjEiYC8KyShp9/U4cK2GE97NSqpfPdwQJH0q+rd8Il1Trv//6nXhQT/Rtq5LqujLmyyMd+aDxLp7vCBJeq/z7Xjg1oZipuq8AnzQKn/EdQUIUI7zxjupywnvvTDP9tsIN12yKqx6fLnRbL/OdoHrT+vOd4L9FKyDIPxYQEAADAwNoaWkhKioK8+bNw4gRIzgpPhBCCCGEEEIIqV2oAEH+sZcvX8LT0xMvX76EpqYmhg8fjhUramaUGyGEEEIIIYTUhC/0syX/MSpAkH9s7ty5mDt3Lt8xCCGEEEIIIYTUAsLbyEsIIYQQQgghhJDvDq2AIIQQQgghhBBSZwl7LoPo63epRWgFBCGEEEIIIYQQQmocFSAIIYQQQgghhBBS46gAQQghhBBCCCGEkBpHBQhCCCGEEEIIIYTUOCpAEEIIIYQQQgghpMbRFAxCCCGEEEIIIXWWoIdgfGdoBQQhhBBCCCGEEEJqHBUgCCGEEEIIIYQQUvMYQuqwwsJCZsmSJUxhYSHfUVhCzMQwwsxFmb4NZfp2QsxFmb4NZfp2QsxFmb4NZfp2QsxFmQhhGBHD0I4XUne9f/8eKioqePfuHZSVlfmOA0CYmQBh5qJM34YyfTsh5qJM34YyfTsh5qJM34YyfTsh5qJMhNAWDEIIIYQQQgghhHCAChCEEEIIIYQQQgipcVSAIIQQQgghhBBCSI2jAgSp02RlZbFkyRLIysryHYUlxEyAMHNRpm9Dmb6dEHNRpm9Dmb6dEHNRpm9Dmb6dEHNRJkIAakJJCCGEEEIIIYSQGkcrIAghhBBCCCGEEFLjqABBCCGEEEIIIYSQGkcFCEIIIYQQQgghhNQ4KkAQQgghhBBCCCGkxlEBghBCCCGEEEIIITWOChCEEEIIIf+BR48eVXvb6dOnuQtCCCGECBQVIAghtcqSJUvw7NkzvmOwUlNTUdU0Y4ZhkJqaykMiQghf+vXrh+TkZInjJ06cgIODAw+JxCUkJCAwMBAFBQUAUOV7FyHkv5WWlobnz5+z30dERGD27NnYvn07L3nocwvhGxUgSJ3z6tUrjB07Fs2aNUO9evUgLS0t9sWH0tJS7Nq1C6NHj4a1tTV69eol9sWHvLw8LF68GD/++CMMDQ1hYGAg9sWXM2fOoEWLFujduzcOHjyIjx8/8pYFAPT19ZGZmSlxPDs7G/r6+jwkKufl5YX8/HyJ4wUFBfDy8uIhEflWJSUl8PLyEvvAKgRnz56t8uvcuXO4cuVKlSfedc2kSZNgbW2Nly9fsseOHDmCcePGYe/evbzlysrKgrW1NX744QcMHDgQGRkZAICJEyfC3d2dt1yfKy0txcOHD/H27VteHv/y5cu4efMm+/2WLVvQtm1bjB49mrdMtUFRURGePn2KkpISXnMI9fkbPXo0QkNDAQAvX75Enz59EBERgYULF/Ly91ion1tI3SFiqPxN6pgBAwYgNTUVM2fOhKamJkQikdjtgwcP5jzTzJkzsXfvXtjY2FSZaf369ZxnGjVqFK5du4axY8dWmcnFxYXzTBUePHiAPXv24NChQygpKcEvv/wCJycntG/fnvMsUlJSePXqFdTV1cWOP3v2DKampsjLy+M8EwBIS0sjIyMDGhoaYsezsrKgoaGB0tJSXnIBQEhICEJCQvD69WuUlZWJ3bZ7925eMuXk5CAiIqLKTOPGjeM8j5KSEmJiYqCnp8f5Y1dHSkoKIpFI4spZxTGRSISffvoJp0+fhqqqKme53NzcqjwuEokgJycHQ0NDDB48GGpqapzkcXZ2RmhoKK5fv47Lly9j0qRJ2LdvH4YOHcrJ41dl3LhxeP36NXbu3ImWLVsiKioKBgYGCAwMhJubG/766y9ecs2ePRtmZmaYOHEiSktL0b17d4SHh6NBgwY4f/48evTowWkeMzMzrF69GgMHDkRMTAzat28PNzc3hIaGwsTEBHv27OE0TwULCwuJv8GA+Gt8woQJ6NmzJ6e58vPz4ezsDH9/fwBAXFwcDAwM4OzsDC0tLcyfP5/TPEJ9/lRVVXH79m0YGxtj06ZNOHLkCMLCwhAUFISpU6ciKSmJ0zxC/dxC6o56fAcghGs3b97EjRs30LZtW76jsA4fPoyjR49i4MCBfEdhXbp0CRcuXECXLl34jiLBwsICFhYW8PHxwblz57Bnzx506dIFJiYmmDhxIiZMmAAVFZUazVBx0iMSibB48WI0aNCAva20tBR37tzh9TVWcUL4uaioKM5OxKqydOlSeHl5wcrKqsrCFh/OnTsHBwcH5ObmQllZWSyTSCTipQDRq1cvXLt2TVAFiCtXrmDhwoVYsWIFOnToAKB8KfHixYuxaNEiqKio4Ndff4WHhwd27drFWa4HDx4gMjISpaWlMDY2BlB+IiQtLQ0TExP873//g7u7O27evAlTU9Maz7N582Y4ODigU6dOSE9Px6FDh3gpbFcWFBSEwMBANG/eXOy4kZERr1vajh8/jjFjxgAo/z1MTk7GkydPsG/fPixcuBBhYWGc5klOTmZfIydOnMDPP/8Mb29vREZG8vr3uX///ti6dSvMzMzY3727d+8iOjoaEyZMQGxsLKytrXHy5ElOX2sLFixAVFQU/vzzT/Tv3589bm1tjd9//53zAoRQn7/i4mLIysoCAIKDg2FrawsAMDExYVcjcUHon1tI3UEFCFLnaGtrC27fq4yMDAwNDfmOIUZVVZXXE9VvwTAMiouLUVRUBIZhoKqqCl9fXyxevBg7duzAyJEja+yxHzx4wGaIiYmBjIwMe5uMjAzatGkDDw+PGnv86qiqqkIkEkEkEuGHH34QO5kuLS1Fbm4upk6dynmuCn5+fti7dy/Gjh3LW4bPubu7w8nJCd7e3mIfyPg0YMAAzJ8/HzExMWjXrh0UFBTEbq/4AMslFxcXbN++HT/++CN7rHfv3pCTk8OUKVPw119/YcOGDXBycuI0V8Xqhj179kBZWRkA8O7dO0yaNAk//fQTJk+ejNGjR8PV1RWBgYH/+eOfPXtW4pi9vT1u3LiBUaNGQSQSsffh43kDyrfUVfXazs7OZk+M+PDmzRs0bdoUAHDx4kUMHz4cP/zwA5ycnLBx40bO88jIyLBb14KDg9nio5qaGt6/f895ngpv3ryBu7s7Fi9eLHZ8+fLlePbsGYKCgrBkyRIsW7aM0wLE6dOnceTIEXTq1Ensb02rVq2QmJjIWY4KQn3+WrVqBT8/P9jY2ODKlStYtmwZAODFixdo1KgRZzmE+rmF1EEMIXVMYGAg07dvXyY5OZnvKKy1a9cy06dPZ8rKyviOwtq3bx8zbNgwJi8vj+8oEu7du8fMmDGDUVNTYzQ1NZl58+Yx8fHx7O2bNm1iNDQ0OMkyYcIE5t27d5w81rfYu3cvs2fPHkYkEjEbN25k9u7dy34dPHiQCQ8P5zWfmpoak5CQwGuGzzVo0IBJTEzkO4YYkUhU7ZeUlBQvmeTk5JiYmBiJ49HR0YycnBzDMAyTkpLCyMvLc5qrWbNmzF9//SVx/NGjR0yzZs0YhmGY+/fvM40aNaqRx//ScyWE541hGGbAgAHMokWLGIZhGEVFRSYpKYkpLS1lhg8fzgwdOpS3XDo6OkxgYCBTUlLCaGtrM+fPn2cYpvy5a9iwIed5Bg0axPTr14/x8vJi6tevzzx//pxhmPLPDUZGRpznqaCsrCz2N65CfHw8o6yszDAMwzx+/JhRVFTkNJe8vDz73qmoqMj+++HDh2wuLgn1+QsNDWUaNmzISElJMY6OjuzxBQsWMHZ2dpznEdrnFlL30AoIUueMHDkS+fn5aNGiBRo0aID69euL3Z6dnc15pps3byI0NBSXLl1Cq1atJDKdPHmS80w+Pj5ITExEkyZNoKenJ5EpMjKS80xA+R7PJ0+eoG/fvti1axcGDRok0Tx01KhRnPWo4GtPaXXGjx8PoLzJVJcuXVCvnrDe5idNmoSDBw9KXMnjU79+/XDv3j1em6t+7vM+FELQrl07zJkzBwEBAeze4czMTMydO5ftvxIfHw9tbW1Oc7179w6vX7+W2F6RmZnJXvVs2LAhioqKauTxhfhcfW7NmjXo3bs37t27h6KiIsydOxd//fUXsrOzOd/mUJmjoyNGjBjBbseytrYGANy5cwcmJiac5/H19cX06dNx/PhxbN26FVpaWgDKtyRW3mLANTk5OYSHh0uslAwPD4ecnByA8tdhxb+5YmVlhQsXLsDZ2RkA2FUQO3fuROfOnTnNAgj3+evRowfevHmD9+/fi/XHmTJlisTqNi5UfG5JSEhAYmIiunXrBnl5+Wq3bhLyXxPWJ1NCOLBhwwa+I0ho2LAh7Ozs+I4hZsiQIXxHqNKIESPg5OTEfrCoSuPGjTk7KcjLy8OqVauqbarIdXOpyrlCQkLQr18/seOBgYEoKyvDgAEDOMtSuUlgWVkZtm/fjuDgYJibm0sUttatW8dZrgo2NjaYM2cOYmNjYWZmJpGJr2XzFQoLCzk/sajKrl27MHjwYDRv3pwtMqSlpcHAwABnzpwBAOTm5mLRokWc5ho8eDCcnJzg4+PDFkLu3r0LDw8P9n0sIiICP/zwA6e5hKR169aIi4uDr68vlJSUkJubC3t7e8yYMQOampq85fr999/RunVrpKWlYfjw4ex2EGlpac77BwCAjo4Ozp8/L3Gcj0bQlTk7O2Pq1Km4f/++2Gt8586d+O233wCUv7dzvX/f29sbAwYMQGxsLEpKSrBx40bExsYiPDwc165d4zQLINznr1evXjh58qREc141NTUMGTIEV69e5TRPdnY2hg8fjtDQUIhEIsTHx8PAwAATJ06EqqoqfHx8OM1D6h6agkEIqTWKi4thYmKC8+fPo2XLlnzHASDcaSHm5uZYtWqVROOty5cvY968eYiKiuIsy9/pzF4xqoxLUlLVT6QWiUS8TAwpLS2Ft7c3/Pz88OrVK7a7/OLFi6Gnp4eJEydyngkoLyAFBQUhLi4OAGBsbIw+ffp88WdY03Jzc+Hq6oqAgAB2DGC9evUwfvx4rF+/HgoKCnj48CEA1PgJ2qxZs2BoaIhZs2aJHff19UVCQoIgC+BCk5OTg4YNG/L2+GVlZUhISKiyoNytWzeeUgEHDhyAr68vnj59CqD8d8/Z2RmjR48GUD5iuWIqBpcSExOxatUqREVFITc3F5aWlpg3bx7MzMw4efy/09uhokcM16SkpPDy5UuJqVSvX7+GlpYWiouLOc0j1Kk4pO6gAgSpE96/f8/+4fnaHyu+/kCRb6OlpYXg4GDBFCAaNmwoyGkh8vLyePz4scQUhZSUFLRq1YrGbAmcl5cX/P394eXlhcmTJ+PRo0cwMDDAkSNHsGHDBty6dYvviIKTm5vLrjgyMDCAoqIi5xm0tLRw9uxZtGvXTux4ZGQkbG1t8fz5c84zAeVLrhUVFTF8+HCx48eOHUN+fj67dYtrq1evhp6eHtsweMSIEThx4gQ0NTVx8eJFmJubc5rn9u3bGD16NJ49e1bluFk+xxeTqlWMB/6Siq0FXD9/0dHRAMoLn1evXhVr7F1aWorLly9j27ZtSElJ4TRX06ZNERgYiDZt2kBJSYktQCQlJcHc3By5ubmc5iF1D23BIHWCqqoqMjIyoKGhgYYNG1b5x4rrP1CWlpYICQmBqqpqtTO+K3DVb0FNTQ1xcXFo3LgxO02hOnz0ygCAGTNmYPXq1di5c6cg+hsIdVqIiooKkpKSJAoQCQkJvOw5rVDR3V5JSUnseF5eHpydnbF7926ekglLQEAAtm/fjt69e4tNLWnTpg2ePHnCW66QkJBqtxvx/dwpKipyfsL6uaysrCpHACsrK+PNmzc8JCq3cuVKbNu2TeK4hoYGpkyZwlsBws/PDwcOHABQPub1ypUruHTpEo4ePQoPDw8EBQVxmmfq1KlsXwOhjAmurKioqMrfPR0dHc4yCG3FQeVVcykpKdDW1pboC1VWVobU1NQaz/K5tm3bslOpevXqJXG7vLw8Nm/ezHkuoU7FIXUH/5/eCeFA5cozH0u8qzJ48GD2jV4o/RbWr1/PnhgKdanw3bt3ERISgqCgIJiZmUmcTHPdsHPZsmXw9PSEv7+/YEY4AuWvr9mzZ+PUqVNo0aIFgPLig7u7O689Dfz9/bFq1SqJAkRBQQECAgI4O4ndtGkTpkyZAjk5OWzatOmL9/18OT0X0tPTqxzNW1ZWxvly3QpLly6Fl5cXrKysBHVyJqQ+LIaGhrh8+TJmzpwpdvzSpUu8NjlNTU2Fvr6+xHFdXV1eTswqvHz5ku0ncv78eYwYMQJ9+/aFnp4eOnbsyHme+Ph4HD9+XHBjsePj4+Hk5ITw8HCx43xc2a/uIk5lXObq3r07++9evXqxF5sqy8rKgrW1NeeFtuTkZDAMAwMDA0RERLDNe4HysZcaGhoSxRIudO3aFQEBAew4UJFIhLKyMqxZs+ZvbZkk5J+iAgSpEyr/gar8bz4tWbKkyn/zqfIfZ76uiH1Nw4YNMXToUL5jsIQ6LWTNmjXo378/TExM0Lx5cwDA8+fP0bVrV6xdu5bzPO/fvwfDMGAYBh8+fBDbp1xaWoqLFy9KfGisSevXr4eDgwPk5OS+2KBMJBLxUoAwNTXFjRs3oKurK3b8+PHjsLCw4DwPUH61eu/evRg7diwvj1+dSZMmfbEPC5fc3Nwwc+ZMZGZmslc8Q0JC4OPjw2tRV0NDA9HR0RIroqKiotCoUSN+QqF8BVlaWhq0tbVx+fJlLF++HED5CSwf2x06duyIhIQEwRUgJkyYgHr16uH8+fO8v8aFchGnKtVNccjNzeWlkW/F+7fQJuUIdSoOqTuoAEHqrPz8fKSmpkqMZuN7Ca8QFRYWSvyc+OqVIbSxl0JZvfI5FRUVhIeH48qVK4iKioK8vDzMzc15a6JWcdVMJBJVOY1AJBJh6dKlnOVJTk6u8t9C4enpifHjxyM9PR1lZWU4efIknj59ioCAgCq7vHOhqKgIP/74Iy+P/SWXLl0STB8WJycnfPz4EStWrGCvLurp6WHr1q0YN24cb7lGjRqFWbNmQUlJiX0PuHbtGlxcXPDLL7/wlsve3h6jR4+GkZERsrKy2Ok8Dx484KUI4OzsDHd3d7x8+bLKiTh8fT54+PAh7t+/z8to0s8J5SJOZRWTlkQiERYvXiy2GrG0tBR37tzhfELI5+Lj4xEaGlrlKi1PT09Oswh1Kg6pO6gJJalzMjMz4ejoiEuXLlV5O18d79evX4+jR49WWRTho99CXl4e5s2bh6NHjyIrK0vidj6bcZWUlODPP/9EYmIiRo8eDSUlJbx48QLKysq8NJ4TusLCQsjKyvJ61ezatWtgGAa9evXCiRMnxPpmyMjIQFdXF82aNeMtnxDduHEDXl5eYt3lPT090bdvX17yzJs3D4qKili8eDEvj18dfX19XLx4UTCNaStkZmZCXl5eEO9JRUVFGDt2LI4dO8b2zikrK8O4cePg5+cHGRkZXnIVFxdj48aNSEtLw4QJE9jVPRXbASdNmsRpnqqmuYhEIt6aGFZo37491q9fj59++omXx/+St2/fYteuXXj8+DGA8tVbjo6OnPZGqtg2cO3aNXTu3Fns9SwjIwM9PT14eHjAyMiIs0yV7dixA9OmTUPjxo3RtGlTsb/FIpGIt5WShPCFChCkznFwcMCzZ8+wYcMG9OjRA6dOncKrV6+wfPly+Pj4wMbGhvNMnp6e2LlzJ9zd3bFo0SIsXLgQKSkpOH36NDw9PXlZAj5jxgyEhoZi2bJlGDt2LLZs2YL09HRs27YNq1atgoODA+eZAODZs2fo378/UlNT8fHjR3Y8oYuLCz5+/Ag/Pz/OM+Xk5OD48eNITEzEnDlzoKamhsjISDRp0gRaWlqc5wHKTy5WrFghuDGOz549g7a2Nq9jG6vy/PlznD17tsoC4Lp163hKJSwuLi4ICAiAubk5zM3NJa4O8/Vz2r9/P86cOSOYPixCLpDGxcWxK6LMzMwktvjUdc+ePfvi7Xz9vK5evYpFixbB29u7ypUZfK1IvH79OgYNGgQVFRVYWVkBAO7fv4+cnBycO3eO8xV3jo6O2Lhxo+Cmmenq6mL69OmYN28e31EAfJrO8bmKMa46OjrUjJLUKCpAkDpHU1MTZ86cQYcOHaCsrIx79+7hhx9+wNmzZ7FmzRrcvHmT80wtWrTApk2bYGNjAyUlJTx8+JA9dvv2bRw8eJDzTDo6OggICECPHj2grKyMyMhIGBoaYt++fTh06BAuXrzIeSagfMuDkpISdu3ahUaNGrHjo/78809MnjwZ8fHxnOaJjo6GtbU1VFRUkJKSgqdPn8LAwACLFi1CamoqAgICOM1TQehjHIW0BSokJAS2trYwMDDAkydP0Lp1a6SkpIBhGFhaWuLq1aucZxKiLzUnE4lEvP2cLCwskJiYCIZheO/DIsQCqdDt27cP27ZtQ1JSEm7dugVdXV1s2LAB+vr6GDx4MN/xBKGiYPv5Kja+V2aYmZmhc+fO2Lp1K9tMsbS0FNOnT0d4eDhiYmJ4ySU0ysrKePjwIa+NaCurPLq04jSw8murfv36GDlyJLZt28ZL7wzy/aMeEKTOycvLY5vdqaqqIjMzEz/88APMzMx4WwZXsd8UKB8l9+7dOwDAzz//zNty5+zsbPaPpbKyMrsN5KeffsK0adN4yQSUL0sPDw+XWDKsp6eH9PR0zvO4ublhwoQJWLNmjdhkh4EDB2L06NGc56kg1DGOQtwCtWDBAnh4eGDp0qVQUlLCiRMnoKGhAQcHB/Tv35+zHF8bfVsZH9uyhNp8Tkh9WFxcXGBlZSXR3NHOzg6TJ0/mNIubmxuWLVsGBQUFdo98dfhavbJ161Z4enpi9uzZWLFiBfv737BhQ2zYsIGXAkRiYiI2bNggtqXAxcWFnSbEB6H+7iUkJOD48eNikxykpaXh5ubGW/FdiIYPH46goCCxv8V8OnXqFObNm4c5c+agQ4cOAICIiAj4+PhgyZIlKCkpwfz587Fo0SJemlaT7x8VIEidY2xsjKdPn0JPTw9t2rTBtm3boKenBz8/P96a7zRv3hwZGRnQ0dFBixYtEBQUBEtLS9y9e5e3ZXAGBgZITk6Gjo4OTExMcPToUXTo0AHnzp1Dw4YNeckElG8tqOok9fnz5xKjHblw9+5dbNu2TeK4lpYWXr58yXmeCkIc4wgAs2fPRk5ODu7cuVPlFig+PH78GIcOHQIA1KtXDwUFBVBUVISXlxcGDx7MWcGt8pSErKwsLF++HP369UPnzp0BALdu3UJgYKDgejDwTShThABhFUgfPHjA/q4/ePCg2vvx2Rtm8+bN2LFjB4YMGYJVq1axx62srODh4cF5nsDAQNja2qJt27ZsU9OwsDC0atUK586dQ58+fTjPBAiz8SMAWFpa4vHjxzA2NhY7/vjxY7Rp04anVMJjaGiIxYsX4/bt21VuoeF6m+2KFSuwceNG9OvXjz1mZmaG5s2bY/HixYiIiICCggLc3d2pAEFqBBUgSJ3j4uKCjIwMAOUfXPv3748DBw5ARkYGe/fu5SWTnZ0dQkJC0LFjRzg7O2PMmDHYtWsXUlNT4erqyksmR0dHREVFoXv37pg/fz4GDRoEX19fFBcX87onvm/fvtiwYQO2b98OoPzDc25uLpYsWYKBAwdynkdWVhbv37+XOB4XFyc285trQhzjCJTvZT5z5gysrKwgJSUFXV1d9OnTB8rKyli5ciUvPVgUFBTYrSCamppITExEq1atAABv3rzhLEfl0bdDhw6Fl5cXZs6cyR6bNWsWfH19ERwczNn7gr29Pfbu3QtlZWXY29t/8b4nT57kJJOQCalAWvmquVCvoCcnJ1f5fiQrK4u8vDzO88yfPx+urq5ixZCK4/PmzeO0ABEdHY3WrVtDSkqq2j37FbjculY5y6xZs+Di4oKEhAR06tQJAHD79m1s2bJF4mdYl23fvh2Kioq4du0arl27JnYbH6OeY2Jiquxnoqury26badu2LftZmZD/GvWAIHVefn4+njx5Ah0dHTRu3JjvOADKr3TeunULRkZGGDRoEN9xAJTvbb5//z4MDQ15HVX6/Plz9OvXDwzDID4+HlZWVoiPj0fjxo1x/fp1dnsNVyZNmoSsrCwcPXoUampqiI6OhrS0NIYMGYJu3bqJXdXm0pkzZzB+/HgsWLAAXl5eWLp0qdgYR76u5CkrKyM6Ohp6enrQ1dXFwYMH0aVLFyQnJ6NVq1bIz8/nPNOQIUNgY2ODyZMnw8PDA2fOnMGECRNw8uRJqKqqIjg4mPNMioqKePjwocQqloSEBLRt2xa5ubmc5HB0dMSmTZugpKQER0fHL96XyxG5ampqiIuLQ+PGjb+6dYXL7SojR46EiooKtm/fDiUlJURHR0NdXR2DBw+Gjo4Ob2OE9+/fD3t7e0E06azM1NQUK1euxODBg6GkpMT29Nm8eTP27NnD+bZIOTk5xMTESExLiIuLg7m5OQoLCznLIiUlhZcvX0JDQ4Pds1/VR3aue0B8KUtlfPamIF9mYWGBNm3aYPv27exqreLiYkyePBlRUVF48OABwsLCMGbMGEGOqSa1H62AIHVegwYNYGlpyXcMMZ07d2aXXQuFrq6uIDqmN2/eHFFRUTh8+DCio6ORm5uLiRMnwsHBAfLy8pzn8fHxwbBhw6ChoYGCggJ0794dL1++ROfOnbFixQrO81QYPHgwzp07By8vLygoKMDT0xOWlpa8LiMGhLkFat26dewJ/dKlS5Gbm4sjR47AyMiIt9U+jRo1wpkzZ+Du7i52/MyZM2K9BWpa5RNmvk6eq1IxphEAb0W+qvj4+KBfv34wNTVFYWEhRo8ezRZIK7b58MHV1RVTp06Fra0txowZg379+ont2+eLm5sbZsyYgcLCQjAMg4iICBw6dAgrV67Ezp07Oc+jrq6Ohw8fShQgHj58yHlxOzk5mV1FJ6STQCFlqW2KioqQnJyMFi1asONw+bBlyxbY2tqiefPm7AWlmJgYlJaW4vz58wCApKQkTJ8+nbeM5PtGKyBIncMwDI4fP47Q0FC8fv0aZWVlYrfztYz4xYsXuHnzZpWZ+BjDCZT3N6ju50SjCcXdvHmTLYhYWlrC2tqatywlJSXw9vaGk5MTmjdvzluOquzfvx8lJSWYMGEC7t+/j/79+yMrKwsyMjLw9/fHyJEj+Y4oCHv37sWkSZMwYMAAdOzYEQBw584dXL58GTt27MCECRN4y/b69Ws8ffoUQHlBiesTM6ErKSkRK5BaWlryViCtnOny5cs4dOgQzpw5gwYNGmD48OFwcHDAjz/+yFsuADhw4AB+//13JCYmAgCaNWuGpUuX8jIq2MvLC+vXr8f8+fPZn0tYWBhWr14NNzc36r9C/pH8/Hw4OzvD398fANjpOM7OztDS0sL8+fM5z/ThwwccOHAAcXFxAMrfyyvGBhNS06gAQeocFxcXbNu2DT179kSTJk0klu7ycZVv7969+PXXXyEjI4NGjRqJZRKJREhKSuI8k7e3NxYtWgRjY2OJnxOfI/e+1ll73LhxHCURNkVFRTx69Ah6enp8R6kWwzAoKCgQzBaooqKiKottOjo6vOS5c+cONm3axHbjb9myJWbNmsUWJLj2/v17zJgxA4cPH2aXVktLS2PkyJHYsmULVFRUOM3yrZSVlWswSe2Tn5+PU6dO4eDBgwgODkbz5s3Zk38ulZSU4ODBg+jXrx+aNGmC/Px85Obm8lrQYhgGGzZsgI+PD168eAGgvCAyZ84czJo1i9OGnWfPnv3m+9ra2tZgkq+LjY2tcqwy37mEwsXFBWFhYdiwYQP69++P6OhoGBgY4MyZM/j999+/2CT2v1ZcXAwTExOcP38eLVu25OxxCamMChCkzlFTU8P+/ft5aVhYHW1tbUydOhULFixg533zrUmTJli9ejWvV1qroqqqKvZ9cXEx8vPzISMjgwYNGvAynlCIK0UGDx4Me3t7scaGQrFr1y6sX78e8fHxAAAjIyPMnj0bkyZN4iVPXFwcJk6ciPDwcLHjDMPQPuZKRo4ciQcPHmDz5s1ikzlcXFzQtm1bHD58mLMslefYfw3Xz198fHy17weenp6cZqnOmzdvcPjwYfj5+eHx48e8vcYbNGiAx48fC2J73+c+fPgAALxdEf78s8DnfRcqv/75ev6SkpJgZ2eHmJgYsXwV2ei9s5yuri6OHDmCTp06ifU6SUhIgKWl5d8qqP4XtLS0EBwcTAUIwhvqAUHqHBUVFRgYGPAdQ0x+fj5++eUXwRQfgPIPPxVjyITk7du3Esfi4+Mxbdo0zJkzh/M8X1spwpcBAwZg/vz5iImJQbt27aCgoCB2O19Xpjw9PbFu3To4OzuLncS6uroiNTUVXl5enGdydHREvXr1cP78eWhqavL6vFWlsLBQ4soiH1f1z58/j8DAQPz000/ssX79+mHHjh3o378/p1kqT3VISUnB/PnzMWHCBLHXlL+/P1auXMlprh07dmDatGlo3LgxmjZtKvF+wGcBomLlw4EDBxASEgJtbW2MGjUKx48f5y1Thw4d8ODBA0EWIPheil65eBUcHIx58+bB29tb7DW+aNEieHt78xURLi4u0NfXR0hICPT19REREYGsrCwa3/iZzMzMKlf25OXl8fL3ZsaMGVi9ejV27tzJay8KUocxhNQxe/fuZX755RcmPz+f7yisOXPmMCtXruQ7hpjVq1czLi4ufMf4Znfv3mWMjY05f1wNDQ1mz549nD/u14hEomq/pKSkeMvVuHFj5uDBgxLHDx48yDRq1IiHRAzToEED5vHjx7w8dnXy8vKYGTNmMOrq6oyUlJTEFx+0tbWZ6OhoieNRUVGMlpYWD4nK9erVq8rX1IEDB5ju3btzmkVHR4dZtWoVp4/5LUaOHMkoKCgw6urqzIwZM5jw8HC+IzEMwzBHjhxhDAwMmM2bNzPh4eFMVFSU2BcXLCwsmOzsbIZhGKZt27aMhYVFtV98adWqFXPjxg2J49evX2dMTEx4SFSuUaNG7POkrKzMPHnyhGEYhgkJCWHatm3LWy6h6dq1K7Np0yaGYRhGUVGRSUpKYhiGYWbOnMn069eP8zxDhgxhlJSUGE1NTaZv376MnZ2d2BchNY3KXqTOGTFiBA4dOgQNDQ3o6emhfv36YrdzPfYLAFauXImff/4Zly9fhpmZmUQmPpbxe3h4wMbGBi1atICpqalEJr6adVanXr167J5dLgl1pcjnS7+Fori4GFZWVhLH27Vrh5KSEh4SlY8CfPPmDS+PXZ05c+YgNDQUW7duxdixY7Flyxakp6dj27ZtWLVqFS+ZFi1aBDc3N+zbtw9NmzYFALx8+RJz5szhtTnfrVu34OfnJ3HcysqK8209b9++xfDhwzl9zG8hLS2No0ePCmb6RYVffvkFgHij5Yql/Fxtfxo8eDBkZWXZfwttBRQAJCYmomHDhhLHVVRUkJKSwnmeCqWlpexKkcaNG+PFixcwNjaGrq4u26iWlK+UHDBgAGJjY1FSUoKNGzciNjYW4eHhuHbtGud5GjZsiKFDh3L+uIRUoB4QpM4ZMWIEQkNDMWzYsCqbUC5ZsoTzTMuXL4enp6egGj7OnDkTO3fuFFSzTkCyMRfDMMjIyICvry+0tbVx6dIlTvOsWbMGL168ENQoQCFzdnZG/fr1JYpqHh4eKCgowJYtWzjJUXnP7b1799ilzFUVAPnY7qCjo4OAgAD06NEDysrKiIyMhKGhIfbt24dDhw7h4sWLnGeysLBAQkICPn78yDbmTE1NhaysrMTYQi4LucbGxhg8eDDWrFkjdnzu3Lk4c+YMpydCEydORPv27TF16lTOHvNriouL0b9/f/j5+Uk8T3x79uzZF28X4tYMPnTr1g1ycnLYt28fmjRpAgB49eoVxo0bh8LCQl5OYgGga9eucHd3x5AhQzB69Gi8ffsWixYtwvbt23H//n08evSIl1xClJiYiFWrViEqKoqdjjNv3jyYmZnxHY0QzlEBgtQ5CgoKEvuY+aaqqor169cLquGjkpISDh8+DBsbG76jiKmqMZe6ujp69eoFHx8faGpqcpqnrKwMNjY2iIuL432lyKZNmzBlyhTIyclh06ZNX7wvX6NdnZ2dERAQAG1tbXTq1AlA+bSH1NRUjBs3TuznV5Mrfz5vYlhxxbUyLq/Cfk5RURGxsbHQ0dFB8+bNcfLkSXTo0AHJyckwMzNDbm4u55mWLl36zfflspB78eJFDB06FIaGhuyEkIiICMTHx+PEiRM13nC48u9aXl4e1q1bBxsbmyqLWXz93qmrqyM8PFxwBQihMTAwwN27d9GoUSOx4zk5ObC0tORlIhUAJCQkwM7ODnFxcdDW1gYApKWlwcjICKdPn4ahoSEvuQIDA5GXlwd7e3skJCTg559/RlxcHBo1aoTDhw+jd+/evOQihAgbFSBInWNiYoKjR4/C3Nyc7yispk2b4saNG4L6cKirq4vAwECYmJjwHUXQhLRSRF9fH/fu3UOjRo2gr69f7f34Gu0KAD179vym+9X0yp+/c8Wwe/fuNZajOubm5ti8eTO6d+8Oa2trtG3bFmvXrsWmTZuwZs0aPH/+nPNMQpaWloatW7fiyZMnAMpHlk6dOpU9WatJX/pdq4zP3ztXV1fIysrytn2nMiGPl5SSksLLly8lGga+evUK2traEs1gucQwDK5cuSL2Gre2thbclpHs7GyoqqoKLhefpKWlkZGRIfG6ysrKgoaGBi9F7uPHj+Po0aNVjk/lYysyqVuoAEHqnAsXLmDz5s3w8/ODnp4e33EAlPeAyMjI+OpVay7t2bMHly9fxp49e9CgQQO+47Dc3Ny++b5c9M4Q6koRUrutX78e0tLSmDVrFoKDgzFo0CAwDIPi4mKsW7cOLi4uvGW7d+8eHj9+DKC8f0a7du14y0K+TcXKIyMjoyqn4nDZZ0iI4yUriiJDhgyBv78/VFRUxDKEhITgypUr1NfgM05OTti4caPExJC8vDw4Oztj9+7dPCUTluoKWy9evECLFi1QUFDAaZ5NmzZh4cKFmDBhArZv3w5HR0ckJibi7t27mDFjBlasWMFpHlL3UAGC1DmqqqrIz89HSUkJGjRoILFENjs7m/NMdnZ2uHr1Kho1aoRWrVoJouGjhYUFEhMTwTCMYJp1AuVX0CMjI1FSUgJjY2MAQFxcHKSlpWFpacnej6veGbRSpPbbs2cPFBUVJZoHHjt2DPn5+Rg/fjxPyT559uwZ7t+/D0NDQ95Wbz1//hyjRo1CWFgY2xAvJycHP/74Iw4fPozmzZtzliU6Ovqb7yuk1W58+dLKI776DAFfHy/Zp08fTnJUFEU+L4YAQP369aGnpwcfHx/8/PPPnOSpyrVr17B27Vqx4t+cOXPQtWtX3jJVd2X/zZs3aNq0KW+NhYWi4qKSq6srli1bBkVFRfa20tJSXL9+HSkpKXjw4AGnuUxMTLBkyRKMGjUKSkpKiIqKgoGBATw9PZGdnQ1fX19O85C6h6ZgkDpHiM0CGzZsCHt7e75jiBkyZAjfEao0aNAgKCkpwd/fH6qqqgDKO887OjqyDbG49Pvvv2PJkiWCWCkitNUhtcXKlSuxbds2ieMaGhqYMmUK7wWIwsJC6Orq8t6Qb9KkSSguLsbjx4/Z4t/Tp0/h6OiISZMm4fLly5xladu2rdi0hAoVJ498XEUHgKFDh6JDhw6YN2+e2PE1a9bg7t27OHbsGGdZKgsNDeXlcb9m9uzZ8PPzE+vJ1K9fPzRo0ABTpkxhT7ZrWsXUIH19fdy9exeNGzfm5HG/1f79++Ho6Ah7e3u2j8jNmzfRu3dv7N27F6NHj+Y0z/v378EwDBiGwYcPHyAnJ8feVlpaiosXL0oUJeqi9evXAyh/X/Lz8xObQCMjIwM9Pb0qJ/jUtNTUVPz4448AAHl5eXz48AEAMHbsWHTq1IkKEKTG0QoIQkitoqWlhaCgILRq1Urs+KNHj9C3b1/OR3EKaaXI51c5q1sp0q5dO96ueAqRnJwcnjx5IrElKyUlBS1btuR8eSxQ/iHe29sbfn5+ePXqFeLi4mBgYIDFixdDT08PEydO5DyTvLw8wsPDYWFhIXb8/v376Nq1K/Lz8znLUnl6woMHD+Dh4YE5c+aIXUX38fHBmjVrOC2mqqur4+rVqxKd7WNiYmBtbY1Xr15xlqUqCQkJSExMRLdu3SAvL19l81UuycvL4+7du2jdurXY8ejoaHTs2JGX3z0hatmyJaZMmQJXV1ex4+vWrcOOHTs4K9RU+LyJ7+dEIhGWLl2KhQsXcphKuHr27ImTJ0+yF034ZmBggBMnTsDCwgJWVlaYPHkyfv31VwQFBeGXX37hZSUwqVtoBQSpk0pLS3H69Gn2j3arVq1ga2vL+3z0zMxMdo+psbEx1NXVec0DlJ9cVP45fX7ywbX3798jMzNT4nhmZiZbxeeSkFaKVL7KuW7dui+uFCGfaGhoIDo6WqIAERUVJdENnysrVqyAv78/1qxZg8mTJ7PHW7dujQ0bNvBSgNDW1kZxcbHE8dLSUjRr1ozTLJVXgwwfPhybNm0Sm3Zhbm4ObW1tLF68mNPf0dzcXMjIyEgcr1+/vtjoV65lZWWxI6hFIhHi4+NhYGCAiRMnQlVVFT4+Przkat++Pdzc3CTGS86ZMwcdOnTgJVNISAjWr1/P/t1r2bIlZs+eDWtra17yAEBSUhIGDRokcdzW1ha//fYb53lCQ0PBMAx69eqFEydOQE1Njb1NRkYGurq6nL8nCJnQViD16tULZ8+ehYWFBRwdHeHq6orjx4/j3r17gluNS75TDCF1THx8PGNkZMQ0aNCAsbCwYCwsLJgGDRowxsbGTEJCAi+ZcnNzGUdHR0ZaWpoRiUSMSCRi6tWrxzg5OTF5eXm8ZHr16hXTs2dPRiQSMaqqqoyqqiojEomYXr16Ma9fv+YlE8MwzNixYxk9PT3mxIkTTFpaGpOWlsYcP36c0dfXZ8aNG8dbLqFp1qwZ8+jRI4njMTExjKamJg+JhGvu3LmMrq4uc/XqVaakpIQpKSlhQkJCGF1dXcbd3Z2XTC1atGCCg4MZhmEYRUVFJjExkWEYhnn8+DHTsGFDXjKdPn2a6dChA3P37l322N27d5lOnToxp06d4iUTwzCMnJwcExsbK3E8NjaWkZOT4zRL+/btmaVLl0ocX7JkCWNpaclplsrGjh3L9OvXj0lLSxN7PV2+fJkxNTXlLVd8fDzTunVrRkZGhmnRogXTokULRkZGhmnVqhUTHx/PeZ4tW7Yw9erVY3755Rdm48aNzMaNG5lRo0Yx9evXZ3x9fTnPU6FFixaMn5+fxPGtW7cyhoaGPCQql5KSwpSVlfH2+LVFSUkJs3PnTmbUqFFM7969mZ49e4p9cS0pKYn5+PEj+/2hQ4cYZ2dnZtOmTUxcXBzneUjdQ1swSJ0zcOBAMAyDAwcOsFX7rKwsjBkzBlJSUrhw4QLnmX799VcEBwfD19cXXbp0AVC+v3PWrFno06cPtm7dynmmkSNHIikpCQEBAWjZsiUAIDY2FuPHj4ehoSEOHTrEeSYAyM/Ph4eHB3bv3s1eja1Xrx4mTpyIP/74Q6K7e12lpKSEc+fOoUePHmLHQ0NDYWtry8tqEaEqKirC2LFjcezYMdSrV74wsKysDOPGjYOfn1+VV7Rrmry8PJ48eQJdXV2xJmGxsbHo0KEDcnNzOc9UuYFvxc+p4t+f/95xuYTX0tISrVu3xs6dO9nnqqioCJMmTcKjR4843QZ17tw52NvbY/To0ejVqxeA8ivqhw4dwrFjx3hbMdW0aVMEBgaiTZs2Yq+npKQkmJub8/J6qsAIaLxk8+bNMX/+fMycOVPs+JYtW+Dt7Y309HTOMwHA1q1bMXv2bDg5ObF798PCwrB3715s3LgRv/76Ky+5rl+//sXbu3XrxlESYZs5cyb27t0LGxsbaGpqSry2K3pFcEWIY0FJ3UIFCFLnKCgo4Pbt2xJ7dKOiotClSxdePog1btwYx48fr/JkccSIEVVuOahpKioqCA4ORvv27cWOR0REoG/fvsjJyeE8U2V5eXlITEwEALRo0YK3wkN1885FIhHk5ORgaGiICRMmwNHRkdNc48aNw40bN+Dj48MuZb5z5w7bNd3f35/TPLVBfHw8Hj58CHl5eZiZmfHa9LFdu3ZwdXXFmDFjxE4Yvby8cOXKFdy4cYPzTH/nNcNl486IiAh2TGnFxIvo6GiIRCKcO3eO86X8Fy5cgLe3N/taMjc3x5IlS9C9e3dOc1SmpKSEyMhIGBkZib2e7t27h379+iErK4u3bEKiqKiIhw8fwtDQUOx4fHw8LCwseC3UnDp1Cj4+PmJbQ+bMmYPBgwfzlunzkaoAfw1ghaxx48YICAgQ2ybGp+rGgj579gympqbIy8vjKRmpK6gHBKlzZGVlq7z6W93eXS7k5+ez+18r09DQ4LSxW2VlZWUSDRWB8r3MFR3D+aSgoCCI8Xqenp5YsWIFBgwYwJ7oRERE4PLly5gxYwaSk5Mxbdo0lJSUiO3lr2l+fn7w8PDA6NGjq1wpQiQZGRnByMio2tuVlZXx8OFDGBgY1HgWT09PjB8/Hunp6SgrK8PJkyfx9OlTBAQE4Pz58zX++FXhexpIdTp06ICkpCQcOHCAvYo+cuRIjB49mpfCpI2NDWxsbL54n0OHDsHW1pazfF27dkVAQACWLVsGoPwksaysDGvWrPniiM6aUDGa8FtUTHzgiq2tLU6dOoU5c+aIHT9z5gyvIziB8nHddnZ2vGb43Nu3b8W+Ly4uxoMHD7B48WKsWLGCp1TCIyMjI1HU4kPFpCyRSARPT0+xyV2lpaW4c+cO2rZty1M6UpfQCghS54wbNw6RkZHYtWuX2JXhyZMno127dti7dy/nmXr37o1GjRohICCAHWdVUFCA8ePHIzs7G8HBwZxnGjx4MHJycnDo0CG2mVR6ejocHBygqqqKU6dOcZ5JiIYOHYo+ffpg6tSpYse3bduGoKAgnDhxAps3b8b27dsRExPDeT6hrBT5HlS+csyFGzduwMvLC1FRUcjNzYWlpSU8PT3Rt29fTh4fKG/6qqyszP77SyruR76Oy2IWUD4lqHfv3rC0tMTVq1dha2uLv/76C9nZ2QgLC0OLFi04yQGUj7qsLDMzE/n5+WjYsCEAICcnBw0aNICGhgaSkpI4ywUAy5cvx9q1a9GlSxd2osrt27cRFhYGd3d3sdc4l8WRu3fvoqysDB07dhQ7fufOHUhLS8PKyoqzLN/i2rVrcHNzw/379/mOIgg+Pj5ISkqCr68vr1NnKoqN165dQ+fOncUuulWMBfXw8PhiIZ6Q/wIVIEidk5OTg/Hjx+PcuXPsFf7i4mIMHjwYe/bsYT8EcenRo0fo168fPn78iDZt2gAo3xIiJyeHwMBAiZGTXEhLS2M/pGpra7PHWrdujbNnz6J58+acZxKi6pbsJiQkoG3btsjNzUViYiLMzc15WdYotLF7tRnXBQghqLxXuLrRexWvKT6XW+/btw/btm1DUlISbt26BV1dXaxfvx4GBga8LlGvDh+vpXfv3sHX11esoDVjxgxoampyluFzBw8exP/+9z/s2rWLHRf89OlTdiygg4MDp3k+L45URyQScVoc6dChA+bOnYthw4aJHT958iRWr16NO3fucJblWzx58gRWVla8blkREjs7O4SGhkJNTQ2tWrWSWF168uRJTvM4Ojpi48aNVDQmvKEtGKTOadiwIc6cOYOEhASxvZR8Lo9r3bo14uPjxZYQjxo1Cg4ODpCXl+clk7a2NiIjIxEcHCzRHIx8oqamhnPnzknMZz937hzb5DQvLw9KSkqc5hLq2D3y9xQVFeH169cS2550dHQ4efyrV6+yr2OhjZKrsHXrVnh6emL27NlYvnw5WwhRVVXFhg0bBFmA4IOKigoWLlzIdwwxixcvxvHjx9niA1A+gnr9+vUYNmwY5wWI5ORkTh/vW8XGxsLS0lLiuIWFBWJjY3lIVC46Olrse4ZhkJGRgVWrVtFS/koaNmwoqO0ze/bs4TsCqeOoAEHqhIp9b9Wp/MF63bp1NR2nSg0aNOC0R8C3EIlE6NOnD/r06cN3FMFavHgxpk2bhtDQUHZLz927d3Hx4kX4+fkBAK5cucJ5AzpXV1fUr18fqamp7BQToHxvvJubGxUgBC4+Ph5OTk4IDw8XO871aoOK121JSQmuXbsGJycnwa1+2rx5M3bs2IEhQ4Zg1apV7HErKyt4eHjwmEw4Ll++DEVFRfz0008Ayqc67NixA6amptiyZQtUVVV5yZWRkYGSkhKJ46WlpXj16hUPiYRJVlYWr169klgxk5GRwU6k4UPbtm0hEonw+WLqTp06Yffu3TylEh464SdEHBUgSJ3w4MEDse8jIyNRUlLCXnWJi4uDtLQ02rVrx1mms2fPfvN9bW1tazDJJ0JuDiZUkydPhqmpKXx9fdlllMbGxrh27Ro7Ls3d3Z3zXEFBQQgMDJQ4WTQyMsKzZ884z/M94HLryoQJE1CvXj2cP3++yrFtXKtXrx7++OMPjBs3jtccVUlOToaFhYXEcVlZWerm/v/mzJmD1atXAwBiYmLg5uYGd3d3hIaGws3NjbcTpN69e+PXX3/Fzp072Sv89+/fx7Rp0zhbbefm5oZly5ZBQUHhqxcr+LpA0bdvXyxYsABnzpyBiooKgPLtpL/99huvFwg+XzEiJSUFdXV1tpcVEZeZmYmnT58CKP+coK6uznMiQvhBBQhSJ3y+wkFJSQn+/v7sVZ+3b9/C0dERXbt25SzT5/Pgq7qKUHHSwdXVzs9nUX+pORgVID7p0qULunTpwncMMXl5eWIdritkZ2dDVlaWh0S1H5ctkx4+fIj79+/DxMSEs8f8ml69euHatWvQ09PjO4oYfX19PHz4UGJs6uXLl8VW/9RlycnJMDU1BQCcOHECgwYNgre3NyIjI3kdDbh7926MHz8eVlZW7L74kpIS9OvXDzt37uQkw4MHD9hJQZGRkdUW+/gsAq5duxbdunWDrq4uW2x7+PAhmjRpgn379vGWi89RxbVJXl4enJ2dERAQwG6nk5aWxrhx47B58+Yq/1YT8j2jAgSpc3x8fBAUFCS25FRVVRXLly9H3759ObtaXXlPd3BwMObNmwdvb2+28/atW7ewaNEieHt7c5IHEL+a8bXmYERSYWEhioqKxI7x1eRJSGP3hM7LywseHh4SHwILCgrwxx9/wNPTEwBw6dIlaGlpcZLJ1NQUb9684eSxvtWAAQMwf/58xMTEoF27dhITVbhaqfU5Nzc3zJgxA4WFhWAYBhERETh06BBWrlzJ2Uns36Wrq1vlmOOaIiMjw450Dg4OZleyqKmpfXW6SU1SV1fHxYsXERcXx/YaMjExwQ8//MBZhsoXKP7880/OHvfv0NLSQnR0NA4cOICoqCjIy8vD0dERo0aN4vR19LlZs2bB0NBQ4oKEr68vEhISsGHDBn6CCYybmxuuXbuGc+fOsRcrbt68iVmzZsHd3R1bt27lOSEhHGMIqWMUFRWZ0NBQieNXr15lFBUVuQ/EMEyrVq2YGzduSBy/fv06Y2JiwkMihjEwMGAiIyMljt+7d4/R09PjIZEw5eXlMTNmzGDU1dUZKSkpiS++PHr0iNHQ0GD69+/PyMjIMMOGDWNatmzJNGnShElISOAtlxBJSUkxr169kjj+5s0bTp/Dd+/esV8hISFM586dmdDQUObNmzdit717946zTJWJRKJqv/h8rTMMw+zfv58xNDRk82hpaTE7d+7kPIe+vj7z5s0bieNv375l9PX1Oc9TYdCgQUy/fv0YLy8vpn79+szz588ZhmGYwMBAxsjIiLdcQlJUVMRIS0szMTExfEepNZo1a8bcu3dP4vj9+/cZLS0tHhIJU6NGjar93Nm4cWPuAxHCM1oBQeocOzs7ODo6wsfHh20aeOfOHcyZMwf29va8ZEpMTKxy/KeKigpSUlI4zwNQc7BvNWfOHISGhmLr1q0YO3YstmzZgvT0dGzbtk2sIR6XiouLMWvWLJw7dw5XrlyBkpIScnNzYW9vz/vYPSFiqhlNGhUVxU6A4ELDhg3FcjAMg969e4vdh+Fx5OXnkziExMHBAQ4ODsjPz0dubi40NDR4yZGSklLlc/Px40ekp6fzkKicr68vpk+fjuPHj2Pr1q3sSp5Lly6hf//+vOUCgOfPn+Ps2bNITU2VWEHGZc+F+vXrQ0dHh9dxsl8SHx+P0NDQKqfiVKzS4lpWVhbbk6IyZWVlwa3g4lN+fj6aNGkicVxDQ4NdmURIXSJiGA43tRIiAPn5+fDw8MDu3bvZfZ/16tXDxIkT8ccff0gsK+ZCt27dICcnh3379rF/pF69eoVx48ahsLAQ165d4zzToEGDkJ6eLtEcbMqUKdDS0vpbTTS/Zzo6OggICECPHj2grKyMyMhIGBoaYt++fTh06BAuXrzISy51dXWEh4fDyMiIl8evDVRVVSESifDu3TsoKyuLnfyXlpYiNzcXU6dOxZYtWzjJ83d+z7meqgIAAQEBGDlypEQPkaKiIhw+fJj3BpWvX79mG7yZmJhw2uCt4v1wyJAh8Pf3FzspKy0tRUhICK5cucLmE6pVq1Zh6tSpVRbEa0JISAhsbW1hYGCAJ0+eoHXr1khJSQHDMLC0tMTVq1c5yVFh165dOHnyJPbt28dp8fFrduzYgWnTpqFx48Zo2rSp2HuVSCRCZGQkL7lat26NqVOnYubMmWLHN2/ejK1bt/I6IlRIevfujUaNGiEgIIBt0FlQUIDx48cjOzsbwcHBPCckhFtUgCB1Vl5eHhITEwEALVq04KXwUCEhIQF2dnaIi4uDtrY2ACAtLQ1GRkY4ffo0DA0NOc+UmZmJ8ePH4/LlyxLNwfbu3cvbFUahUVRURGxsLHR0dNC8eXOcPHkSHTp0QHJyMszMzJCbm8tLLldXV8jKyvK2CqM28Pf3B8MwcHJywoYNG8ROGmVkZKCnp8f2ZBGq6dOnw8vLC40bN67xx5KWlkZGRobE735WVhY0NDR4u3L84cMHTJ8+HYcOHRJr8DZy5Ehs2bKlyiu0/zUpKSkAVTcTrl+/PvT09ODj44Off/65xrP8G8rKynj48KHEuMea0qFDBwwYMABLly6FkpISoqKioKGhAQcHB/Tv3x/Tpk3jJEcFCwsLJCQkoLi4GLq6uhKfC/g60dfV1cX06dMxb948Xh6/Ort378bMmTMxZ84c9OrVC0B5UcnHxwcbNmwQ3GhxvsTExKB///74+PEj2rRpA6B8hZ2srCyCgoLQqlUrnhMSwi3agkHqLAUFBZibm/MdAwBgaGiI6OhoXLlyhW3E1bJlS1hbW/PWebuiOVh8fDweP34MgPvmYLWBgYEBkpOToaOjAxMTExw9ehQdOnTAuXPnOLuKWJWSkhLs3r0bwcHBVTYM5GucnJCMHz8eQPkUhS5duqBevdr3J3H//v3w8PDgpABR3VaV58+fc3KSX51JkybhwYMHuHDhglgTXxcXF/z66684fPhwjWeoKHzo6+vj7t27nDwfNYHra1KPHz/GoUOHAJSvRCwoKICioiK8vLwwePBgzgsQn0+nEoq3b99i+PDhfMeQ4OTkhI8fP2LFihVsw2M9PT1s3bqV9xVRQmJmZob4+HgcOHCA/Yw3atQoODg4QF5enud0hHCPVkAQQv4Vrq+YCc369eshLS2NWbNmITg4GIMGDQLDMCguLsa6devg4uLCS64vTboQiUScL20WsosXL0JaWhr9+vUTOx4YGIiysjIMGDCAp2RfV3HVuCZ//ywsLCASiRAVFYVWrVqJFWpKS0uRnJyM/v374+jRozWW4UsUFBQQGBiIn376Sez4jRs30L9/f+Tl5fGSqzbi4vVUWdOmTREaGoqWLVvC1NQUq1atgq2tLaKiotClSxfeVpAJzcSJE9G+fXtMnTqV7yjVyszMhLy8PBQVFfmOIjgrV65EkyZN4OTkJHZ89+7dyMzMFNzKFkJqWu273EPIdyokJATr169nVxu0bNkSs2fPhrW1Nc/Jvqyu1zBdXV3Zf1tbW+PJkye4f/8+DA0NeV1hU3m0HPmy+fPnV7lVhWEYzJ8/X9AFCC5UXBV++PAh+vXrJ3aCUbFVZejQoTylAxo1alTlCgwVFRWxcctcqa3v5Xzo1KkTbt68iZYtW2LgwIFwd3dHTEwMTp48iU6dOnGe5+7duygrK0PHjh3Fjt+5cwfS0tKwsrLiPBNQvkpy8eLFuH37NszMzCRGb34+BpNLJSUl+PPPP5GYmIjRo0cDAF68eAFlZWUqRvy/bdu24eDBgxLHW7VqhV9++YUKEKTOoRUQhAjA//73P7i4uGDYsGHsEuLbt2/j+PHjWL9+PWbMmMFzwupxfcVMSIqLi9G/f3/4+flRs8daTF5eHo8fP4aenp7Y8ZSUFLRq1UrQV9C5/P3z9/fHL7/8ItGEkm/bt2/HsWPHsG/fPjRt2hQA8PLlS4wfPx729vb49ddfOctSm9/LAe7fz5OSkpCbmwtzc3Pk5eXB3d2dbZ67bt066OrqcpKjQocOHTB37lwMGzZM7PjJkyexevVq3Llzh9M8FfT19au9TSQSISkpicM0nzx79gz9+/dHamoqPn78iLi4OBgYGMDFxQUfP36En58fL7mERk5ODo8fP5Z4HpOSkmBqaorCwkKekhHCD1oBQYgAeHt7Y/369WKdpGfNmoUuXbrA29tb8B9a66r69esjOjqa7xjkX1JRUUFSUpJEASIhIYHX5rRC06tXL2RmZqJ58+YAgIiICBw8eBCmpqaYMmUKp1kqtoVUiI+Ph46ODnR0dAAAqampkJWVRWZmJqcFCHov/3sqFzoUFBSqPWE9dOgQbG1ta/z3MTY2lp36VJmFhQWvEx2Sk5N5e+wvcXFxgZWVFaKiotCoUSP2uJ2dHTWgrERbWxthYWESBYiwsDA0a9aMp1SE8IcKEIQIQE5OTpWz2Pv27UtL8wRuzJgx2LVrF02bqMUGDx6M2bNn49SpU2jRogWA8uKDu7s7bG1teU4nHKNHj8aUKVMwduxYvHz5EtbW1mjdujUOHDiAly9fwtPTk7MsQm0WWNvfy7t27SrIpni//vorOnbsWOMrM2RlZfHq1SuJx8nIyBBEk9qioiIkJyejRYsWgshz48YNhIeHQ0ZGRuy4np4e0tPTeUolPJMnT8bs2bNRXFwsNi1k7ty5cHd35zkdIdzj/92LEAJbW1ucOnUKc+bMETt+5swZwY9t42tKh1DQtInab82aNejfvz9MTEzYq/vPnz9H165dsXbtWp7TfdmYMWOgrKzMyWM9evQIHTp0AAAcPXoUZmZmCAsLQ1BQEKZOncppAWLJkiWcPdbfIdT38vfv31d5XCQSQVZWlj2BvHjxIpexvhlXu4X79u2LBQsW4MyZM2xfkZycHPz222/o06cPJxmqkp+fD2dnZ/j7+wMAu9XB2dkZWlpamD9/Pi+5ysrKqhy/+/z5cygpKfGQSJjmzJmDrKwsTJ8+HUVFRQDKt2XMmzcPCxYs4DkdIdyjHhCE8GTTpk3sv9+/f4+1a9eiS5cuYvuGw8LC4O7ujkWLFvEV86vqYg+I6OhotG7dGlJSUjRt4jvBMAyuXLmCqKgoyMvLw9zcHN26deMtz+XLl6GoqMhOdtiyZQt27NgBU1NTbNmyhZfmioqKinj06BH09PRga2uLLl26YN68eUhNTYWxsTEKCgo4z/S53NxcdiRmBa4KNACwfPnyL76XV87CZeNAKSmpLxaLmzdvjgkTJmDJkiWQkpLiLNe34urvTHp6Orp164asrCxYWFgAKG++2qRJE1y5cgXa2to1+vjVcXFxQVhYGDZs2ID+/fsjOjoaBgYGOHPmDH7//Xc8ePCAl1wjR46EiooKtm/fDiUlJURHR0NdXR2DBw+Gjo4O9uzZw0suocrNzcXjx48hLy8PIyMjwfXTIYQrVIAghCdfaipVGZ8Npr7FzZs30b59+zr1h1RaWhoZGRnQ0NCAgYEB7t69K7b/ldRehYWFkJWV5X1lj5mZGVavXo2BAwciJiYG7du3h5ubG0JDQ2FiYsLLB/uOHTuiZ8+esLGxQd++fXH79m20adMGt2/fxrBhw/D8+XPOMwHl++NnzpyJP//8U6yZG8MwEIlEVV6hrSlCfV8PCAjAwoULMWHCBHYVS0REBPz9/bFo0SJkZmZi7dq1mDNnDn777TfOcn0rLgvdeXl5OHDggFgxctSoURKTJ7ikq6uLI0eOoFOnTmI/i4SEBFhaWla7wqWmPX/+HP369QPDMIiPj4eVlRXi4+PRuHFjXL9+HRoaGrzkIoQIG23BIIQnQmwq5ebm9s33rdhaUHGFti5p2LAhkpOToaGhgZSUFIkrrqR2KSsrw4oVK+Dn54dXr16xy5sXL14MPT09TJw4kfNMycnJMDU1BQCcOHECP//8M7y9vREZGYmBAwdyngcAVq9eDTs7O/zxxx8YP3482rRpAwA4e/Yse1LLhzFjxoBhGOzevRtNmjThtXgkxPd1oHyCiY+PD0aMGMEeGzRoEMzMzLBt2zaEhIRAR0cHK1asEGQBgksKCgqcN1X9mszMzCpP5vPy8nh9vTdv3hxRUVE4cuQIoqKikJubi4kTJ8LBwUGQvUQIIcJABQhCCOtbl3HyfXWYb0OHDkX37t2hqakJkUgEKysrSEtLV3lfIa9eIeWWL18Of39/rFmzRqxze+vWrbFhwwZeChAyMjLIz88HAAQHB2PcuHEAADU1Nd6udvbo0QNv3rzB+/fvxbaATJkyBQ0aNGC/DwsLg5WVFWeroqKionD//n0YGxtz8ni1UXh4eJUTJiwsLHDr1i0A5cXk1NRUrqMJir+/Pxo3bgwbGxsAwNy5c7F9+3aYmpri0KFDnI8FrWBlZYULFy7A2dkZwKe/wTt37mS3+vAhMzMT6urqcHBwgIODg9htMTExMDMz4ykZIUTIqABBiAA4OTl98fbdu3dzkiM0NJSTx6nttm/fDnt7eyQkJGDWrFmYPHkyNdyqxQICArB9+3b07t0bU6dOZY+3adMGT5484SXTTz/9BDc3N3Tp0gURERE4cuQIgPLmcxWNMvkgLS0t0X/i8/GlAwYMwMOHDznrC9O+fXukpaXxVoBwc3PDsmXLoKCg8NVVZHw1pdXW1q5yWs+uXbvYvgZZWVm89Bb5Frq6upxsgfD29sbWrVsBALdu3YKvry82bNiA8+fPw9XVFSdPnqzxDNXlGjBgAGJjY1FSUoKNGzciNjYW4eHhuHbtGi+ZgPKtYrt27WILNhXWrl2LxYsXC6IvDCFEeKgAQYgAvH37Vuz74uJiPHr0CDk5OezIJr4kJCQgMTER3bp1g7y8PLuvuq6rGLV3//59uLi4UAGiFktPT4ehoaHE8bKyMhQXF/OQCPD19cX06dNx/PhxbN26FVpaWgCAS5cuVTnmUUi4bi21c+dOTJ06Fenp6WjdurXEiaq5uXmNPv6DBw/Y10lkZGS17498vm+uXbsWw4cPx6VLl9C+fXsAwL179/DkyRMcP34cAHD37l2MHDmSl3z37t3D48ePAQAtW7aElZWV2O2PHj3iJEdaWhr7XnD69GkMGzYMU6ZMQZcuXdCjRw9OMlTlp59+wsOHD7Fq1SqYmZkhKCgIlpaWuHXrFq+rDNzc3DB06FA4Ojpi3bp1yM7Oxrhx4xATE4ODBw/ylosQImzUhJIQgSorK8O0adPQokULzJ07l/PHz8rKwogRIxAaGgqRSIT4+HgYGBjAyckJqqqq8PHx4TwTITWhXbt2cHV1xZgxY8QavHl5eeHKlSu4ceMG3xFrFa4n49y+fRujR49GSkoKe0wkEvHShFLIkpOTsW3bNsTFxQEAjI2N8euvv0qsYOHS8+fPMWrUKISFhaFhw4YAysde/vjjjzh8+DDnq300NDQQGBgICwsLWFhYwM3NDWPHjkViYiLatGmD3NxcTvP8XatWrcLUqVPZnyUXHjx4gLFjx+Ljx4/Izs5Gx44dsXv3bjRt2pSzDISQ2oVWQBAiUFJSUnBzc0OPHj14KUC4urqifv36SE1NRcuWLdnjI0eOhJubGxUgyHfD09MT48ePR3p6OsrKynDy5Ek8ffoUAQEBOH/+PC+ZKk9aqSwrKwsaGhp0Ul2Jk5MTLCwscOjQIV6bUBYXF0NeXh4PHz5E69atecnwJfr6+hJbMPg2adIkFBcX4/Hjx+wWmqdPn8LR0RGTJk3C5cuXOc3Tp08fTJo0CRYWFoiLi2Mbvv7111+8Fmq+lbe3N0aMGMFpAcLQ0BCtW7fGiRMnAJR/RqDiAyHkS6gAQYiAJSYmoqSkhJfHDgoKQmBgoMQVKCMjIzx79oyXTITUhMGDB+PcuXPw8vKCgoICPD09YWlpiXPnzqFPnz68ZKpuceLHjx8hIyPDcRphe/bsGc6ePVvlNhou1a9fHzo6OoItDuXk5CAiIgKvX7+WmNxT0eSUa9euXUN4eLhY/w5jY2Ns3rwZXbt25TzPli1bsGjRIqSlpeHEiRPseOX79+9j1KhRnOf5u7he1BwWFoYxY8ZATU0N0dHRCAsLg7OzMy5evAg/Pz/B9hQhhPCLChCECMDnjcsYhkFGRgYuXLiA8ePH85IpLy9PrLN9hezsbM662xNS00pKSuDt7Q0nJydcuXKF7zjYtGkTgPItBDt37oSioiJ7W2lpKa5fvw4TExO+4n0Trlcg9OrVC1FRUbwXIABg4cKF+O2337Bv3z6oqanxHYd17tw5ODg4IDc3F8rKymLPkUgk4q0Aoa2tXWWfldLSUjRr1ozzPA0bNoSvr6/E8aVLl3KepTbo1asXXF1dsWzZMtSvXx8tW7ZEz549MWbMGJiZmeH58+d8RySECBAVIAgRgM/HX0pJSUFdXR0+Pj5fnZBRU7p27YqAgAAsW7YMQPmH1LKyMqxZswY9e/bkJRMh/7V69ephzZo1vJ2AfW79+vUAyouQfn5+YuNdZWRkoKenV+U4RSHh+irsoEGD4Orqyo79+7wJpa2tLWdZfH19kZCQgGbNmkFXVxcKCgpit0dGRnKWpTJ3d3c4OTnB29u7ysIyX/744w84Oztjy5YtbOPJe/fuwcXFBWvXruUl040bN7Bt2zYkJSXh2LFj0NLSwr59+6Cvr4+ffvqJl0xCFRQUhO7du4sda9GiBcLCwrBixQqeUhFChI6aUBIiAPn5+WAYhv2wmpKSgtOnT6Nly5bo168fL5kePXqE3r17w9LSElevXoWtrS3++usvZGdnIywsDC1atOAlFyH/tcGDB8Pe3p631UZV6dmzJ06ePElLmL+BlJRUtbdx3YTya1fKlyxZwlEScQoKCoiJieGsMei3UlVVRX5+PkpKSlCvXvk1sYp/f168yc7OrvE8J06cwNixY+Hg4IB9+/YhNjYWBgYG8PX1xcWLF3Hx4sUaz/BvcN0AtgJNyyKE/B1UgCBEAPr27Qt7e3tMnToVOTk5MDExQf369fHmzRusW7cO06ZN4yXXu3fv4Ovri6ioKOTm5sLS0hIzZsyApqYmL3kIqQl+fn5YunQpHBwc0K5dO4kTHy6voFentLQUMTEx0NXV5bQoYWFh8c0nEnxd3SdfZ29vj19++QUjRozgO4oYf3//b74vFwVCCwsLuLq6Yty4cWIn8w8ePMCAAQPw8uXLGs/wb3BdgPjStCw1NTXeVrEQQoSNtmAQIgCRkZHs0uvjx4+jSZMmePDgAU6cOAFPT0/eChAqKipYuHAhL49NCFemT58OAFi3bp3EbXyNcZw9ezbMzMwwceJElJaWolu3brh16xYaNGiA8+fPo0ePHpzkGDJkCCeP818pLCyEnJwcb49/9+5dlJWVoWPHjmLH79y5A2lpaXabAddsbGwwZ84cxMbG8r5NpTIhrToCyidwdOvWTeK4iooKcnJyuA/0N3Xt2hXy8vKcPd7XpmVRAYIQUhUqQBAiAPn5+VBSUgJQvqfS3t4eUlJS6NSpE28TJwwNDTFmzBg4ODjAyMiIlwyEcOHziQBCcOzYMYwZMwZAeQPBlJQUPHnyBPv27cPChQsRFhbGSQ6+tgz8HaWlpfD29oafnx9evXqFuLg4GBgYYPHixdDT08PEiRM5yzJjxgzMnTtXogCRnp6O1atX486dO5xlqWzy5MkAAC8vL4nbuC6yvX//HsrKyuy/v6Tiflxp2rQpEhISJEZu3rx5k/NtDV/72VRW8XPieosITcsihPwT1W+cJIRwxtDQEKdPn0ZaWhoCAwPRt29fAMDr1685/wBWYcaMGbhw4QKMjY3Rvn17bNy4UfDLTwn5XmRlZaFp06YAyk8qhg8fjh9++AFOTk6IiYnhJVNaWppYV/uIiAjMnj0b27dv5yVPhRUrVmDv3r1Ys2aN2IjS1q1bY+fOnZxmiY2NhaWlpcRxCwsLxMbGcpqlsrKysmq/uF7ho6qqitevXwMonzqhqqoq8VVxnGuTJ0+Gi4sL7ty5A5FIhBcvXuDAgQPw8PDgfCVidT8bIfycKtC0LELIP0ErIAgRAE9PT4wePRqurq7o3bs3OnfuDKD86oKFhQUvmVxdXeHq6oq4uDgcOHAAW7ZsgYeHBztiSyhTAwj5JzZt2oQpU6ZATk6OHX1ZnVmzZnGU6pMmTZogNjYWmpqauHz5MrZu3QqgfLVU5ckYXBo9ejSmTJmCsWPH4uXLl7C2tkbr1q1x4MABvHz5Ep6enrzkCggIwPbt29G7d29MnTqVPd6mTRs8efKE0yyysrJ49eqVxNXyjIwMtsliXXf16lV2RGloaCjPacTNnz8fZWVl6N27N/Lz89GtWzfIysrCw8MDzs7OnGYR2s+mKjQtixDyT1ATSkIE4uXLl8jIyECbNm3Yru4RERFQVlaGiYkJz+nK3b59G9OmTUN0dDQv++IJ+a/o6+vj3r17aNSoEfT19au9n0gkQlJSEofJyv3+++/YsGEDNDU1kZ+fj7i4OMjKymL37t3YsWMHbt26xXkmVVVV3L59G8bGxti0aROOHDmCsLAwBAUFYerUqbz8nABAXl4eT548ga6urlgTvtjYWHTo0AG5ubmcZRk1ahQyMjJw5swZqKioAABycnIwZMgQaGho4OjRo5xlEXqR7e+YPn06vLy80LhxY04er6ioCAkJCcjNzYWpqSkUFRU5edyqlJSUwNvbG05OThJbHfhG07IIIf8EFSAIIV8VERGBgwcP4siRI3j//j0GDRqEw4cP8x2LkO/aiRMnkJqaihEjRkBLSwtA+dQAVVVVXpoGKioq4tGjR9DT04OtrS26dOmCefPmITU1FcbGxigoKOA8EwC0a9cOrq6uGDNmjFgBwsvLC1euXMGNGzc4y5Keno5u3bohKyuLXb328OFDNGnSBFeuXIG2tjZnWYReZPs7lJWV8fDhQ8GNEeWKkpISYmJiJHpTCAFNyyKE/F20HpAQUqWKrReHDh1CcnIyevXqhdWrV8Pe3p7Xq0GE1BUNGzbE/fv3sWTJEolGmXwUIFq1agU/Pz/Y2NjgypUr7LLrFy9eoFGjRpznqeDp6Ynx48cjPT0dZWVlOHnyJJ4+fYqAgACcP3+e0yxaWlqIjo7GgQMHEBUVBXl5eTg6OmLUqFESkydqWnJycpX/ro1q8lqZvb39N9/35MmTNZbjS3r16oVr164JsgDxLdOyuF7BQggRNipAEEKqZGJigvbt22PGjBn45Zdf0KRJE74jEfKfcXNz++b7VjWes6YtXboUXl5esLKygqamJkQiEecZPrd69WrY2dnhjz/+wPjx49GmTRsAwNmzZ9GhQwfecg0ePBjnzp2Dl5cXFBQU4OnpCUtLS5w7dw59+vThPI+CggKmTJnC+eOSf6ZiqwxQXug4deoUVFRU2JGp9+/fR05Ozt8qVPzXBgwYgPnz5yMmJgbt2rWDgoKC2O18jVH9Vvv374eHhwcVIAghAGgLBiGkGvHx8TR+k3y3Pm+QFhkZiZKSEhgbGwMoXwEkLS2Ndu3a4erVq5zn09TUxJo1azB27FjOH7s6BQUFKCsrQ1FREVRVVfHs2TOcOnUK8vLysLe3h7q6Ot8Rv+jQoUOwtbWVOHn7L/n7+6Nx48awsbEBAMydOxfbt2+HqakpDh06BF1d3Rp77C8pLS3F3r17ERISgtevX0usqOHjNf53VN5aU5PmzZuH7Oxs+Pn5sc1eS0tLMX36dCgrK+OPP/6o0cevTkVfqKpwPUb1n+Dq+SOE1A5UgCCEVCsnJwfHjx9HYmIi5syZAzU1NURGRqJJkybsnnRCart169bhzz//ZPsrAMDbt2/h6OiIrl27wt3dnfNMjRo1QkREhKCauPXt2xf29vaYOnUqcnJyYGxsDBkZGbx58wbr1q3jfEzh38VFHwFjY2Ns3boVvXr1wq1bt9C7d29s2LAB58+fR7169Xhbwj9z5kzs3bsXNjY2Va6oWb9+PS+5vhVXJ7Dq6uq4efMmW4is8PTpU/z444/Iysqq0cf/XlEBghBSGW3BIIRUKTo6Gr1790bDhg2RkpKCyZMnQ01NDSdPnkRqaioCAgL4jkjIf8LHxwdBQUFs8QEon/iwfPly9O3bl5cCxKRJk3Dw4EEsXryY88euTmRkJHuievz4cTRt2hQPHjzAiRMn4OnpKfgCBBfXW9LS0mBoaAgAOH36NIYNG4YpU6agS5cu6NGjR40/fnUOHz6Mo0ePYuDAgbxlqA1KSkrw5MkTiQLEkydPJFaNcMnLy6va20QikaDeJwgh5GuoAEEIqZKrqyscHR2xZs0aKCkpsccHDhyI0aNH85iMkP/W+/fvkZmZKXE8MzMTHz584CxH5b4UZWVl2L59O4KDg2Fubi7RwJCPvhT5+fnse0FQUBDs7e0hJSWFTp064dmzZ5znESJFRUVkZWVBR0cHQUFB7HMqJyfH25QQAJCRkWELI7XRmDFjoKysXOOP4+joiIkTJyIxMZHta3Lnzh2sWrUKjo6ONf741Tl16pTY98XFxUhOTka9evXQokULKkAQQmoVKkAQQqp07949bN++XeK4lpYWXr58yUMiQmqGnZ0dHB0d4ePjI3bSMWfOHE4bzz148EDs+7Zt2wIAHj16JHacr4aUhoaGOH36NOzs7BAYGAhXV1cAwOvXrzk5OawN+vTpg0mTJsHCwgJxcXHsioO//vqL1wkG7u7u2LhxI3x9fQXR0LTC5cuXoaioiJ9++gkAsGXLFuzYsQOmpqbYsmULuypp69atnORZu3YtmjZtCh8fH2RkZAAo78cyZ84cXlZCVfj8vQEoL5xOmDABdnZ2PCQihJB/jnpAEEKqpKGhgcDAQFhYWIjt37xy5QqcnJyQlpbGd0RC/hP5+fnw8PDA7t27UVxcDACoV68eJk6ciD/++KNGmxbWJsePH8fo0aNRWlqK3r17IygoCACwcuVKXL9+HZcuXeI54ZdxsQ89JycHixYtQlpaGqZNm4b+/fsDAJYsWQIZGZmvjiusKXZ2dggNDYWamhpatWolsaKGr94UZmZmWL16NQYOHIiYmBi0b98ebm5uCA0NhYmJCfbs2cNLLqD8BB9AlcW1sLAwWFlZQVZWlutYYmJiYjBo0CCkpKTwmuNrpk2bhmXLltEUDEIIACpAEEKqMWnSJGRlZeHo0aNQU1NDdHQ0pKWlMWTIEHTr1g0bNmzgOyIh/6m8vDwkJiYCAFq0aEGFhyq8fPkSGRkZaNOmDduZPyIiAsrKyjAxMeE53ZfV5UZ4X9s+wNeJvqKiIh49egQ9PT38/vvvePToEY4fP47IyEgMHDhQsKvtuGho+i1u3ryJQYMG4e3bt7w8/reuYCGEkMpoCwYhpEo+Pj4YNmwYNDQ0UFBQgO7du+Ply5fo3LkzVqxYwXc8Qv5zGRkZyMjIQLdu3SAvLw+GYQS1XF0ImjZtiqZNm4odq9i2InS6uroSV/5rSn5+PlJTU1FUVCR23NzcnJPH/xyfKwm+REZGBvn5+QCA4OBgjBs3DgCgpqbGrkAQIq6v3W3atEni8TMyMrBv3z4MGDCA0yyVzZkzB6tXrwZQvhrD3d2dXcHi5uYm2NcdIYRftAKCEPJFN2/eRHR0NHJzc2FpaQlra2u+IxHyn8rKysKIESMQGhoKkUiE+Ph4GBgYwMnJCaqqqvDx8eE7IvkKoYwMzszMxIQJE3D58uUqby8tLeUsy+dKSkrw559/IjExEaNHj4aSkhJevHgBZWVlKCoq8pLJ1tYWRUVF6NKlC5YtW4bk5GRoaWkhKCgIM2fORFxcHC+5vobr1TT6+vpi30tJSUFdXR29evXCggULxBpFc6m2rmAhhPCLVkAQQr7op59+YpdXEvI9cnV1Rf369ZGamoqWLVuyx0eOHAk3NzcqQAhcdHQ0rK2toaKiwvvI4NmzZ+Pdu3e4c+cOevTogVOnTuHVq1dYvnw5r6+jZ8+eoX///khNTcXHjx/Rp08fKCkpYfXq1fj48SP8/Px4yeXr64vp06fj+PHj2Lp1K1ssunTpEts/gwDJycl8R6hSbV3BQgjhFxUgCCGsz5d5fsmsWbNqMAkh3AkKCkJgYCCaN28udtzIyIjGS9YCbm5umDBhgiBGBl+9ehVnzpyBlZUVpKSkoKuriz59+kBZWRkrV66EjY0Np3kquLi4wMrKClFRUWjUqBF73M7ODpMnT+YlEwDo6Ojg/PnzEsfXr1/PQxryd/30009wc3NDly5dEBERgSNHjgAA4uLiJN5PCSGkAhUgCCGsb/3QJxKJqABBvht5eXlo0KCBxPHs7Gzeu9yTr7t79y62bdsmcZyPkcF5eXnQ0NAAAKiqqiIzMxM//PADzMzMEBkZyWmWym7cuIHw8HDIyMiIHdfT00N6ejpPqcQVFhZK9MwQ6nhX6g1TjlawEEL+CSpAEEJYQl3mSUhN6tq1KwICArBs2TIA5ScXZWVlWLNmDXr27MlzOvI1srKyVS73jouLg7q6OqdZjI2N8fTpU+jp6aFNmzbYtm0b9PT04OfnB01NTU6zVFZWVlZl/4nnz5/z1j8AKC/YzJs3D0ePHkVWVpbE7Xz2zPgSap9WjlawEEL+CSm+AxBCajdlZWUkJSXxHYOQf+yPP/7A9u3bMWDAABQVFWHu3Llo3bo1rl+/znZ4J8Jla2sLLy8vFBcXAygvIKWmpmLevHkYOnQop1lcXFyQkZEBAFiyZAkuXboEHR0dbNq0Cd7e3pxmqaxv375io5NFIhFyc3OxZMkSDBw4kLdcc+fOxdWrV7F161bIyspi586dWLp0KZo1a8Zp746/68OHD7yP4BSawsJCvH//XuyLEEKqQlMwCCH/CtfdwAn5LxUXF6N///5YuXIlrly5gqioKHbiy4wZM3i9ak2+zbt37zBs2DDcu3cPHz58QLNmzdiRwRcvXoSCggJv2fLz8/HkyRPo6OigcePGvOV4/vw5+vXrB4ZhEB8fDysrK8THx6Nx48a4fv06u22Eazo6OggICECPHj2grKyMyMhIGBoaYt++fTh06BAuXrzIaR4LC4sqt1eIRCLIycnB0NAQEyZMoJVR/6+2rmAhhPCLChCEkH+FChCktlNXV0d4eDiMjIz4jkL+BSGMDL5586ZgpwaVlJTgyJEjYkU2BwcHyMvL85ZJUVERsbGx0NHRQfPmzXHy5El06NABycnJMDMzQ25uLqd5FixYgK1bt8LMzAwdOnQAUN5jJDo6GhMmTEBsbCxCQkJw8uRJDB48mNNsQjRjxgyEhoZi2bJlGDt2LLZs2YL09HRs27YNq1atgoODA98RCSECRAUIQsi/QgUIUtu5urpCVlYWq1at4jsKqeVkZGSgpaWFUaNGYcyYMTA1NeU7EgDg+vXr+PHHH1Gvnnjrr5KSEoSHh6Nbt2685DI3N8fmzZvRvXt3WFtbo23btli7di02bdqENWvW4Pnz55zmmTx5MnR0dLB48WKx48uXL8ezZ8+wY8cOLFmyBBcuXMC9e/c4zSZEQlvBQgipHagAQQj5V6gAQWo7Z2dnBAQEwMjICO3atZNYsr9u3TqekpFvdffuXYSGhuL169coKysTu43L5+/Nmzc4fPgwDh06hFu3bsHc3BwODg4YNWoUr2MJpaWlkZGRIbHVIisrCxoaGrwtlV+/fj2kpaUxa9YsBAcHY9CgQWAYBsXFxVi3bh1cXFw4zaOiooL79+/D0NBQ7HhCQgLatWuHd+/e4cmTJ2jfvj0+fPjAaTYhEtoKFkJI7UBTMAgh/wqNIyO13aNHj2BpaQmgfHJCZfT6Fj5vb28sWrQIxsbGaNKkidhzxvXz17hxY8ycORMzZ85EcnIyDh48CH9/fyxYsADdunXD1atXOc1TgWGYKn8WWVlZvPbIcHV1Zf9tbW2NJ0+esAUAc3NzzvPIyckhPDxcogARHh4OOTk5AOUTRSr+XdcZGBggOTkZOjo6MDExwdGjR9GhQwecO3cODRs25DseIUSgqABBCPlXaBEVqe1CQ0P5jkD+hY0bN2L37t2YMGEC31HE6OvrY/78+WjTpg0WL16Ma9eucZ7B3t4eQHkhZsKECZCVlWVvKy0tRXR0NH788UfOc1UWEhKCkJCQKlev7N69m9Mszs7OmDp1Ku7fv4/27dsDKF9ds3PnTvz2228AgMDAQLRt25bTXELl6OiIqKgodO/eHfPnz8egQYPg6+vLrmAhhJCq0BYMQshXVbxNVHUF7ebNm2jfvr3YB1tCCOGKpqYmrl+/LqgmomFhYThw4ACOHz+OwsJCDB48GA4ODujfvz+nORwdHQEA/v7+GDFihFjDSRkZGejp6WHy5Mm8TehYunQpvLy8YGVlBU1NTYm/MadOneI804EDB+Dr64unT58CAIyNjeHs7IzRo0cDAAoKCtipGETcs2fPeF3BQgipHagAQQip1q5du7B+/XrEx8cDAIyMjDB79mxMmjSJ52SEEFJuzZo1ePHiBTZs2MB3FCxYsACHDx/Gixcv0KdPHzg4OGDw4MFo0KABb5kYhoGTkxM2b94MRUVF3nJURVNTE2vWrMHYsWP5jkL+ISGtYCGE1A5UgCCEVMnT0xPr1q2Ds7MzOnfuDAC4desWfH194erqCi8vL54TEkJI+Z58GxsbxMXFwdTUFPXr1xe7/eTJk5xl6dKlCxwcHDBixAjeVhV8rqJnwV9//SWoVSIA0KhRI0RERKBFixZ8RxFTVFRU5Qm1jo4OT4mESYgrWAghwkcFCEJIldTV1bFp0yaMGjVK7PihQ4fg7OyMN2/e8JSMEEI+mTlzJnbu3ImePXtKNKEEgD179vCUTDhatWqFXbt2oVOnTnxHETNv3jwoKipKjL3kS3x8PJycnBAeHi52vKKJJ1/TQoSKVrAQQv4JakJJCKlScXExrKysJI63a9cOJSUlPCQihBBJ/v7+OHHiBGxsbPiOwoqNjUVqaiqKiorEjtva2vKSZ9WqVZgzZw62bt2K1q1b85KhgpubG/vvsrIybN++HcHBwTA3N5dYvcJ1I8MJEyagXr16OH/+fJVX9Im4oqIi3puYEkJqH1oBQQipkrOzM+rXry/xAdDDwwMFBQXYsmULT8kIIeQTXV1dBAYGwsTEhO8oSEpKgp2dHWJiYiASiSQa+PJ1BV1VVRX5+fkoKSmBjIyMWDNKAMjOzuYsS8+ePb/pfiKRiPOxpQoKCrh//74gXku1gdBWsBBCagdaAUEIqdauXbsQFBTELtu9c+cOUlNTMW7cOLGrWDRuixDCl99//x1LlizBnj17eG32CAAuLi7Q19dHSEgI9PX1ERERgaysLLi7u2Pt2rW85RJCg84KQh57a2pqStsLv0LIK1gIIbUDrYAghFRJyFepCCGkgoWFBRITE8EwDPT09CROgiIjIznL0rhxY1y9ehXm5uZQUVFBREQEjI2NcfXqVbi7u+PBgwecZSF/39WrV7Fo0SJ4e3vDzMxM4rWkrKzMUzLhoM8GhJB/i1ZAEEKqJOSrVIQQUmHIkCF8R2CVlpZCSUkJQHkx4sWLFzA2Noauri6ePn3Ke7bTp0/j8ePHAMobU9ra2kJaWprXXEJibW0NAOjdu7fYcWpC+Ql9NiCE/FtUgCCEfNXz588BAM2bN+c5CSGEiFuyZAnfEVitW7dGVFQU9PX10bFjR6xZswYyMjLYvn07DAwMeMuVkJCAgQMHIj09HcbGxgCAlStXQltbGxcuXBDcGEy+0Mk1IYTUPNqCQQipUllZGZYvXw4fHx/k5uYCAJSUlODu7o6FCxdCSkqK54SEECIsgYGByMvLg729PeLj4zFo0CDExcWhUaNGOHz4sMSVda4MHDgQDMPgwIEDUFNTAwBkZWVhzJgxkJKSwoULF3jJRQghpO6hAgQhpEoLFizArl27sHTpUnTp0gUAcPPmTfz++++YPHkyVqxYwXNCQggp31qwfv16HD16tMrRl1xOeKhKdnY2VFVVeR3pqKCggNu3b8PMzEzseFRUFLp06cIWmeui6OhotG7dGlJSUoiOjv7ifc3NzTlKRQgh3y/agkEIqZK/vz927twpNrfe3NwcWlpamD59OhUgCCGCsHTpUuzcuRPu7u5YtGgRFi5ciJSUFJw+fRqenp41/vj29vbYu3cvlJWVYW9v/8X7KioqolWrVpg6dSpUVFRqPFsFWVlZfPjwQeJ4bm4uZGRkOMshRG3btsXLly+hoaGBtm3bio1PrYx6QBBCyH+DChCEkCplZ2dXOQvdxMSE9yuKhBBS4cCBA9ixYwdsbGzw+++/Y9SoUWjRogXMzc1x+/ZtzJo1q0YfX0VFhV3d8LWiwsePH+Hn54ewsDCcPXu2RnNV9vPPP2PKlCnYtWsXOnToAKB8rPLUqVPFisx1UXJyMtTV1dl/E0IIqVm0BYMQUqWOHTuiY8eO2LRpk9hxZ2dn3L17F7dv3+YpGSGEfKKgoIDHjx9DR0cHmpqauHDhAiwtLZGUlAQLCwu8e/eO74hiYmNj0b59e+Tl5XH2mDk5ORg/fjzOnTvHjpYsKSmBra0t9u7dy+lqDCF7//59taM2ExISYGhoyHEiQgj5/tAKCEJIldasWQMbGxsEBwejc+fOAIBbt24hLS0NFy9e5DkdIYSUa968OTIyMqCjo4MWLVogKCgIlpaWuHv3LmRlZfmOJ8HY2Bjh4eGcPmbDhg1x5swZxMfH48mTJwCAli1b0gn1Z2xsbHDlyhXIycmJHX/69Cl69+7NToQihBDyz1Ebe0JIlfT19REXFwc7Ozvk5OQgJycH9vb2ePr0KXR1dfmORwghAAA7OzuEhIQAKF+htXjxYhgZGWHcuHFwcnLiOZ0kaWlptGnThpfHNjIywqBBgzBo0CAqPlRBUVER9vb2KCkpYY89fvwYPXr0wNChQ3lMRggh3w/agkEIqZK0tDQyMjKgoaEhdjwrKwsaGhrUjIsQIki3bt3CrVu32JNtUj4pZO/evQgJCcHr169RVlYmdvvVq1d5SiYsBQUFsLa2RvPmzXH48GH89ddf6N27NxwcHLBu3Tq+4xFCyHeBChCEkCpJSUmxncEre/bsGUxNTTndv0wIIeSfmzlzJvbu3QsbGxtoampKjARdv349T8mEJycnBz169ICRkRGuX7+OcePG4Y8//uA7FiGEfDeoAEEIEePm5gYA2LhxIyZPnowGDRqwt5WWluLOnTuQlpZGWFgYXxEJIURMfHw8QkNDq7y6z8UoTqFr3LgxAgICMHDgQL6jCM779+8ljmVkZKBPnz74+eefsWrVKvZ4dQ0qCSGEfDsqQBBCxPTs2RMAcO3aNXTu3FlsRryMjAz09PTg4eEBIyMjviISQghrx44dmDZtGho3boymTZuKXd0XiUSIjIzkMZ0wNGvWDH/++Sd++OEHvqMIjpSUlMSKEACo+HgsEonAMAxEIhFtPSSEkP8AFSAIIVVydHTExo0b6YoPIUTQdHV1MX36dMybN4/vKILl4+ODpKQk+Pr6VnmyXZddu3btm+/bvXv3GkxCCCF1AxUgCCGEEFJrKSsr4+HDhzAwMOA7iqDY29uLfX/16lWoqamhVatWqF+/vthtJ0+e5DIaIYSQOqwe3wEIIYQQQv6p4cOHIygoCFOnTuU7iqCoqKiIfW9nZ8dTktpjz549UFRUxPDhw8WOHzt2DPn5+Rg/fjxPyQgh5PtBKyAIIYQQUmutXLkS69atg42NDczMzCSu7s+aNYunZMJRUFCAsrIyKCgoAABSUlJw+vRptGzZEv369eM5nXD88MMP2LZtG9sLqcK1a9cwZcoUPH36lKdkhBDy/aACBCGEEEJqLX19/WpvE4lESEpK4jCNMPXt2xf29vaYOnUqcnJyYGJigvr16+PNmzdYt24dpk2bxndEQZCTk8OTJ0+gp6cndjwlJQUtW7ZEQUEBP8EIIeQ7QlswCCGEEFJrJScn8x1B8CIjI7F+/XoAwPHjx9GkSRM8ePAAJ06cgKenJxUg/p+Ghgaio6MlChBRUVFo1KgRP6EIIeQ7I8V3AEIIIYSQf8rLywv5+fkSxwsKCuDl5cVDIuHJz8+HkpISACAoKAj29vaQkpJCp06d8OzZM57TCceoUaMwa9YshIaGorS0FKWlpbh69SpcXFzwyy+/8B2PEEK+C7QFgxBCCCG1lrS0NDIyMqChoSF2PCsrCxoaGigtLeUpmXCYm5tj0qRJsLOzQ+vWrXH58mV07twZ9+/fh42NDV6+fMl3REEoKirC2LFjcezYMdSrV75IuKysDOPGjYOfnx9kZGR4TkgIIbUfFSAIIYQQUmtJSUnh1atXUFdXFzt+9epVjBw5EpmZmTwlE47jx49j9OjRKC0tRe/evREUFASgvIHn9evXcenSJZ4TCktcXByioqIgLy8PMzMz6Orq8h2JEEK+G1SAIIQQQkito6qqCpFIhHfv3kFZWRkikYi9rbS0FLm5uZg6dSq2bNnCY0rhePnyJTIyMtCmTRtISZXvwI2IiICysjJMTEx4TkcIIaSuoAIEIYQQQmodf39/MAwDJycnbNiwASoqKuxtMjIy0NPTQ+fOnXlMSGqj58+f4+zZs0hNTUVRUZHYbevWreMpFSGEfD9oCgYhhBBCap3x48cDKB/D2aVLF3bPPiH/VEhICGxtbWFgYIAnT56gdevWSElJAcMwsLS05DseIYR8F2gKBiGEEEJqLSUlJTx+/Jj9/syZMxgyZAh+++03iSvYhHzJggUL4OHhgZiYGMjJyeHEiRNIS0tD9+7dMXz4cL7jEULId4EKEIQQQgiptX799VfExcUBAJKSkjBy5Eg0aNAAx44dw9y5c3lOR2qTx48fY9y4cQCAevXqoaCgAIqKivDy8sLq1at5TkcIId8HKkAQQgghpNaKi4tD27ZtAQDHjh1D9+7dcfDgQezduxcnTpzgNxypVRQUFNhVM5qamkhMTGRve/PmDV+xCCHku0IbJgkhhBBSazEMg7KyMgBAcHAwfv75ZwCAtrY2nTSSv6VTp064efMmWrZsiYEDB8Ld3R0xMTE4efIkOnXqxHc8Qgj5LlABghBCCCG1lpWVFZYvXw5ra2tcu3YNW7duBQAkJyejSZMmPKcjtcm6deuQm5sLAFi6dClyc3Nx5MgRGBkZ0QQMQgj5j9AYTkIIIYTUWtHR0XBwcEBqairc3NywZMkSAICzszOysrJw8OBBnhOS2qC0tBRhYWEwNzdHw4YN+Y5DCCHfLSpAEEIIIeS7U1hYCGlpadSvX5/vKKSWkJOTw+PHj6Gvr893FEII+W7RFgxCCCGE1Hr3799nx3GamprC0tKS50SktmndujWSkpKoAEEIITWIVkAQQgghpNZ6/fo1Ro4ciWvXrrFL53NyctCzZ08cPnwY6urq/AYktcbly5exYMECLFu2DO3atYOCgoLY7crKyjwlI4SQ7wcVIAghhBBSa40cORJJSUkICAhAy5YtAQCxsbEYP348DA0NcejQIZ4TktpCSurTdHqRSMT+m2EYiEQilJaW8hGLEEK+K1SAIIQQQkitpaKiguDgYLRv317seEREBPr27YucnBx+gpFax9/fH9ra2pCWlhY7XlZWhtTUVIwfP56nZIQQ8v2gHhCEEEIIqbXKysqqbDRZv359lJWV8ZCI1FZOTk7IyMiAhoaG2PGsrCxYW1tTAYIQQv4DUl+/CyGEEEKIMPXq1QsuLi548eIFeyw9PR2urq7o3bs3j8lIbVOx1eJzubm5kJOT4yERIYR8f2gFBCGEEEJqLV9fX9ja2kJPTw/a2toAgNTUVJiZmWH//v08pyO1gZubG4Dyvg+LFy9GgwYN2NtKS0tx584dtG3blqd0hBDyfaECBCGEEEJqLW1tbURGRiIkJIQdw9myZUtYW1vznIzUFg8ePABQvgIiJiYGMjIy7G0yMjJo06YNPDw8+IpHCCHfFWpCSQghhJBaLSQkBCEhIXj9+rVE34fdu3fzlIrUNo6Ojti4cSON2ySEkBpEBQhCCCGE1FpLly6Fl5cXrKysoKmpKbGH/9SpUzwlI4QQQsjnqABBCCGEkFpLU1MTa9aswdixY/mOQgghhJCvoCkYhBBCCKm1ioqK8OOPP/IdgxBCCCHfgAoQhBBCCKm1Jk2ahIMHD/IdgxBCCCHfgLZgEEIIIaRWqRibCABlZWXw9/eHubk5zM3NUb9+fbH7rlu3jut4hBBCCKkGFSAIIYQQUqv07Nnzm+4nEolw9erVGk5DCCGEkG9FBQhCCCGEEEIIIYTUOOoBQQghhBBCCCGEkBpHBQhCCCGEEEIIIYTUOCpAEEIIIYQQQgghpMZRAYIQQgghhBBCCCE1jgoQhBBCCCGEEEIIqXFUgCCEEEIIIYQQQkiNowIEIYQQQgghhBBCatz/AZURW9sKtK6oAAAAAElFTkSuQmCC\n"
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
"<pandas.io.formats.style.Styler at 0x78a4244f7dc0>"
|
|
],
|
|
"text/html": [
|
|
"<style type=\"text/css\">\n",
|
|
"#T_4ccaf_row0_col0, #T_4ccaf_row1_col1, #T_4ccaf_row2_col2, #T_4ccaf_row3_col3, #T_4ccaf_row4_col4, #T_4ccaf_row5_col5, #T_4ccaf_row6_col6, #T_4ccaf_row7_col7, #T_4ccaf_row8_col8, #T_4ccaf_row9_col9, #T_4ccaf_row10_col10, #T_4ccaf_row11_col11, #T_4ccaf_row12_col12, #T_4ccaf_row13_col13, #T_4ccaf_row14_col14, #T_4ccaf_row15_col15, #T_4ccaf_row16_col16, #T_4ccaf_row17_col17, #T_4ccaf_row18_col18, #T_4ccaf_row19_col19 {\n",
|
|
" background-color: #b40426;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col1, #T_4ccaf_row0_col4, #T_4ccaf_row0_col11, #T_4ccaf_row0_col14, #T_4ccaf_row0_col15, #T_4ccaf_row1_col0, #T_4ccaf_row1_col11, #T_4ccaf_row2_col4, #T_4ccaf_row2_col11, #T_4ccaf_row2_col13, #T_4ccaf_row2_col16, #T_4ccaf_row3_col9, #T_4ccaf_row4_col11, #T_4ccaf_row5_col4, #T_4ccaf_row5_col10, #T_4ccaf_row5_col11, #T_4ccaf_row6_col11, #T_4ccaf_row7_col11, #T_4ccaf_row8_col4, #T_4ccaf_row8_col9, #T_4ccaf_row8_col11, #T_4ccaf_row8_col12, #T_4ccaf_row8_col14, #T_4ccaf_row9_col4, #T_4ccaf_row9_col11, #T_4ccaf_row10_col11, #T_4ccaf_row11_col4, #T_4ccaf_row13_col2, #T_4ccaf_row13_col11, #T_4ccaf_row14_col4, #T_4ccaf_row14_col11, #T_4ccaf_row15_col11, #T_4ccaf_row16_col4, #T_4ccaf_row16_col11, #T_4ccaf_row17_col3, #T_4ccaf_row17_col6, #T_4ccaf_row17_col11, #T_4ccaf_row17_col14, #T_4ccaf_row17_col18, #T_4ccaf_row17_col19, #T_4ccaf_row18_col11, #T_4ccaf_row18_col17, #T_4ccaf_row19_col5, #T_4ccaf_row19_col6, #T_4ccaf_row19_col7, #T_4ccaf_row19_col8, #T_4ccaf_row19_col9, #T_4ccaf_row19_col11, #T_4ccaf_row19_col14, #T_4ccaf_row19_col15 {\n",
|
|
" background-color: #3b4cc0;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col2, #T_4ccaf_row18_col1 {\n",
|
|
" background-color: #b6cefa;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col3, #T_4ccaf_row1_col17, #T_4ccaf_row1_col19, #T_4ccaf_row4_col17, #T_4ccaf_row11_col17, #T_4ccaf_row11_col18 {\n",
|
|
" background-color: #85a8fc;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col5, #T_4ccaf_row0_col7, #T_4ccaf_row0_col10, #T_4ccaf_row0_col12, #T_4ccaf_row2_col19, #T_4ccaf_row3_col12, #T_4ccaf_row5_col12, #T_4ccaf_row9_col12, #T_4ccaf_row13_col15, #T_4ccaf_row16_col12, #T_4ccaf_row19_col12 {\n",
|
|
" background-color: #4358cb;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col6, #T_4ccaf_row3_col16, #T_4ccaf_row6_col0, #T_4ccaf_row16_col7, #T_4ccaf_row19_col10 {\n",
|
|
" background-color: #465ecf;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col8, #T_4ccaf_row0_col16, #T_4ccaf_row1_col14, #T_4ccaf_row3_col6, #T_4ccaf_row3_col17, #T_4ccaf_row4_col14, #T_4ccaf_row7_col10, #T_4ccaf_row9_col14, #T_4ccaf_row10_col9, #T_4ccaf_row11_col14, #T_4ccaf_row12_col9, #T_4ccaf_row16_col9 {\n",
|
|
" background-color: #4055c8;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col9, #T_4ccaf_row2_col14, #T_4ccaf_row8_col0, #T_4ccaf_row12_col4, #T_4ccaf_row13_col9, #T_4ccaf_row13_col12, #T_4ccaf_row13_col14, #T_4ccaf_row17_col7 {\n",
|
|
" background-color: #3e51c5;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col13 {\n",
|
|
" background-color: #bfd3f6;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col17, #T_4ccaf_row2_col6, #T_4ccaf_row7_col8, #T_4ccaf_row9_col3, #T_4ccaf_row16_col3, #T_4ccaf_row19_col1, #T_4ccaf_row19_col16 {\n",
|
|
" background-color: #7597f6;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col18, #T_4ccaf_row4_col18 {\n",
|
|
" background-color: #8db0fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row0_col19, #T_4ccaf_row2_col18, #T_4ccaf_row10_col19 {\n",
|
|
" background-color: #7295f4;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col2, #T_4ccaf_row16_col17 {\n",
|
|
" background-color: #8caffe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col3, #T_4ccaf_row10_col3 {\n",
|
|
" background-color: #88abfd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col4, #T_4ccaf_row1_col9, #T_4ccaf_row3_col4, #T_4ccaf_row3_col11, #T_4ccaf_row6_col4, #T_4ccaf_row7_col4, #T_4ccaf_row8_col10, #T_4ccaf_row10_col4, #T_4ccaf_row12_col11, #T_4ccaf_row13_col4, #T_4ccaf_row15_col4, #T_4ccaf_row17_col4, #T_4ccaf_row17_col15 {\n",
|
|
" background-color: #3c4ec2;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col5, #T_4ccaf_row9_col15, #T_4ccaf_row11_col10, #T_4ccaf_row12_col15, #T_4ccaf_row18_col16 {\n",
|
|
" background-color: #485fd1;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col6, #T_4ccaf_row1_col12, #T_4ccaf_row2_col15, #T_4ccaf_row6_col1, #T_4ccaf_row7_col19 {\n",
|
|
" background-color: #6180e9;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col7, #T_4ccaf_row10_col7, #T_4ccaf_row11_col9, #T_4ccaf_row14_col9, #T_4ccaf_row15_col12, #T_4ccaf_row16_col10, #T_4ccaf_row18_col8 {\n",
|
|
" background-color: #455cce;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col8, #T_4ccaf_row2_col10, #T_4ccaf_row3_col10, #T_4ccaf_row5_col15, #T_4ccaf_row5_col19 {\n",
|
|
" background-color: #516ddb;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col10 {\n",
|
|
" background-color: #e0dbd8;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col13, #T_4ccaf_row7_col3 {\n",
|
|
" background-color: #9bbcff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col15, #T_4ccaf_row6_col14 {\n",
|
|
" background-color: #3d50c3;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col16, #T_4ccaf_row13_col1, #T_4ccaf_row17_col12 {\n",
|
|
" background-color: #5673e0;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row1_col18, #T_4ccaf_row19_col13 {\n",
|
|
" background-color: #ccd9ed;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col0, #T_4ccaf_row3_col15, #T_4ccaf_row3_col19 {\n",
|
|
" background-color: #799cf8;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col1, #T_4ccaf_row4_col9, #T_4ccaf_row8_col16, #T_4ccaf_row9_col10, #T_4ccaf_row10_col15, #T_4ccaf_row12_col14, #T_4ccaf_row13_col10, #T_4ccaf_row15_col14, #T_4ccaf_row16_col15, #T_4ccaf_row18_col4 {\n",
|
|
" background-color: #445acc;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col3, #T_4ccaf_row2_col12, #T_4ccaf_row14_col6, #T_4ccaf_row14_col8 {\n",
|
|
" background-color: #5f7fe8;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col5, #T_4ccaf_row8_col18, #T_4ccaf_row9_col7, #T_4ccaf_row12_col6 {\n",
|
|
" background-color: #6687ed;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col7, #T_4ccaf_row3_col8, #T_4ccaf_row4_col16, #T_4ccaf_row6_col16, #T_4ccaf_row8_col1, #T_4ccaf_row10_col5, #T_4ccaf_row10_col12, #T_4ccaf_row13_col6, #T_4ccaf_row14_col7, #T_4ccaf_row14_col15, #T_4ccaf_row16_col5, #T_4ccaf_row18_col12 {\n",
|
|
" background-color: #4f69d9;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col8, #T_4ccaf_row5_col13, #T_4ccaf_row6_col13, #T_4ccaf_row16_col2 {\n",
|
|
" background-color: #94b6ff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col9, #T_4ccaf_row17_col0, #T_4ccaf_row17_col5 {\n",
|
|
" background-color: #536edd;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row2_col17 {\n",
|
|
" background-color: #dcdddd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col0, #T_4ccaf_row9_col19, #T_4ccaf_row16_col1 {\n",
|
|
" background-color: #6a8bef;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col1, #T_4ccaf_row3_col7 {\n",
|
|
" background-color: #6c8ff1;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col2, #T_4ccaf_row5_col8, #T_4ccaf_row7_col6, #T_4ccaf_row12_col18 {\n",
|
|
" background-color: #8badfd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col5, #T_4ccaf_row4_col6, #T_4ccaf_row4_col8, #T_4ccaf_row11_col0, #T_4ccaf_row11_col1, #T_4ccaf_row11_col6, #T_4ccaf_row14_col1, #T_4ccaf_row15_col19, #T_4ccaf_row17_col1 {\n",
|
|
" background-color: #6384eb;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col13, #T_4ccaf_row7_col13 {\n",
|
|
" background-color: #9dbdff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col14, #T_4ccaf_row10_col14, #T_4ccaf_row13_col8, #T_4ccaf_row15_col0, #T_4ccaf_row16_col0 {\n",
|
|
" background-color: #5470de;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row3_col18 {\n",
|
|
" background-color: #f49a7b;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col0, #T_4ccaf_row16_col6, #T_4ccaf_row19_col0 {\n",
|
|
" background-color: #6282ea;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col1, #T_4ccaf_row10_col6, #T_4ccaf_row11_col8, #T_4ccaf_row15_col5 {\n",
|
|
" background-color: #6485ec;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col2, #T_4ccaf_row4_col13, #T_4ccaf_row11_col2, #T_4ccaf_row11_col13, #T_4ccaf_row13_col19 {\n",
|
|
" background-color: #a6c4fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col3, #T_4ccaf_row6_col5, #T_4ccaf_row18_col7 {\n",
|
|
" background-color: #7ea1fa;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col5, #T_4ccaf_row6_col8, #T_4ccaf_row7_col1, #T_4ccaf_row7_col15, #T_4ccaf_row9_col8, #T_4ccaf_row14_col5, #T_4ccaf_row14_col10, #T_4ccaf_row18_col19 {\n",
|
|
" background-color: #5b7ae5;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col7, #T_4ccaf_row5_col1, #T_4ccaf_row10_col16, #T_4ccaf_row12_col7, #T_4ccaf_row14_col16 {\n",
|
|
" background-color: #4e68d8;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col10, #T_4ccaf_row5_col0, #T_4ccaf_row6_col10, #T_4ccaf_row7_col12, #T_4ccaf_row7_col16, #T_4ccaf_row8_col19, #T_4ccaf_row11_col12, #T_4ccaf_row13_col5 {\n",
|
|
" background-color: #4961d2;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col12, #T_4ccaf_row4_col15, #T_4ccaf_row6_col12, #T_4ccaf_row6_col19, #T_4ccaf_row9_col16, #T_4ccaf_row14_col12, #T_4ccaf_row19_col17 {\n",
|
|
" background-color: #4b64d5;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row4_col19, #T_4ccaf_row7_col17 {\n",
|
|
" background-color: #779af7;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col2, #T_4ccaf_row10_col2, #T_4ccaf_row15_col6 {\n",
|
|
" background-color: #adc9fd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col3, #T_4ccaf_row5_col6, #T_4ccaf_row13_col0, #T_4ccaf_row18_col15, #T_4ccaf_row19_col3 {\n",
|
|
" background-color: #84a7fc;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col7 {\n",
|
|
" background-color: #e3d9d3;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col9 {\n",
|
|
" background-color: #abc8fd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col14, #T_4ccaf_row16_col14, #T_4ccaf_row19_col4 {\n",
|
|
" background-color: #3f53c6;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col16, #T_4ccaf_row7_col14, #T_4ccaf_row8_col15, #T_4ccaf_row13_col7, #T_4ccaf_row15_col9, #T_4ccaf_row15_col10, #T_4ccaf_row18_col9 {\n",
|
|
" background-color: #4257c9;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col17, #T_4ccaf_row12_col1 {\n",
|
|
" background-color: #7b9ff9;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row5_col18, #T_4ccaf_row18_col2 {\n",
|
|
" background-color: #96b7ff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col2 {\n",
|
|
" background-color: #b3cdfb;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col3, #T_4ccaf_row7_col9, #T_4ccaf_row8_col7, #T_4ccaf_row9_col0, #T_4ccaf_row11_col5, #T_4ccaf_row14_col0, #T_4ccaf_row15_col8 {\n",
|
|
" background-color: #5d7ce6;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col7, #T_4ccaf_row15_col17, #T_4ccaf_row17_col13 {\n",
|
|
" background-color: #7699f6;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col9, #T_4ccaf_row11_col16, #T_4ccaf_row12_col10, #T_4ccaf_row13_col17 {\n",
|
|
" background-color: #506bda;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col15 {\n",
|
|
" background-color: #9abbff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col17, #T_4ccaf_row10_col0, #T_4ccaf_row12_col0, #T_4ccaf_row15_col7 {\n",
|
|
" background-color: #5e7de7;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row6_col18 {\n",
|
|
" background-color: #f7b99e;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row7_col0, #T_4ccaf_row9_col1 {\n",
|
|
" background-color: #5a78e4;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row7_col2, #T_4ccaf_row15_col3 {\n",
|
|
" background-color: #a7c5fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row7_col5 {\n",
|
|
" background-color: #e9d5cb;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row7_col18, #T_4ccaf_row10_col18 {\n",
|
|
" background-color: #afcafc;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col2 {\n",
|
|
" background-color: #c9d7f0;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col3 {\n",
|
|
" background-color: #688aef;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col5 {\n",
|
|
" background-color: #82a6fb;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col6, #T_4ccaf_row10_col8, #T_4ccaf_row13_col16, #T_4ccaf_row16_col8, #T_4ccaf_row17_col9 {\n",
|
|
" background-color: #5977e3;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col13, #T_4ccaf_row9_col17, #T_4ccaf_row16_col19 {\n",
|
|
" background-color: #97b8ff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row8_col17 {\n",
|
|
" background-color: #d2dbe8;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row9_col2 {\n",
|
|
" background-color: #b1cbfc;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row9_col5 {\n",
|
|
" background-color: #bcd2f7;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row9_col6, #T_4ccaf_row12_col19, #T_4ccaf_row14_col19, #T_4ccaf_row18_col0, #T_4ccaf_row19_col18 {\n",
|
|
" background-color: #6e90f2;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row9_col13 {\n",
|
|
" background-color: #a1c0ff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row9_col18 {\n",
|
|
" background-color: #81a4fb;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row10_col1 {\n",
|
|
" background-color: #ead4c8;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row10_col13 {\n",
|
|
" background-color: #a3c2fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row10_col17 {\n",
|
|
" background-color: #89acfd;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row11_col3, #T_4ccaf_row14_col17 {\n",
|
|
" background-color: #80a3fa;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row11_col7, #T_4ccaf_row17_col10, #T_4ccaf_row18_col14 {\n",
|
|
" background-color: #4c66d6;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row11_col15, #T_4ccaf_row12_col16, #T_4ccaf_row15_col16 {\n",
|
|
" background-color: #4a63d3;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row11_col19, #T_4ccaf_row13_col3 {\n",
|
|
" background-color: #7396f5;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row12_col2, #T_4ccaf_row15_col2 {\n",
|
|
" background-color: #b7cff9;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row12_col3, #T_4ccaf_row18_col10, #T_4ccaf_row19_col2 {\n",
|
|
" background-color: #7a9df8;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row12_col5, #T_4ccaf_row12_col8, #T_4ccaf_row17_col16 {\n",
|
|
" background-color: #5875e1;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row12_col13 {\n",
|
|
" background-color: #9ebeff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row12_col17 {\n",
|
|
" background-color: #92b4fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row13_col18 {\n",
|
|
" background-color: #6b8df0;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row14_col2, #T_4ccaf_row14_col13 {\n",
|
|
" background-color: #a5c3fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row14_col3, #T_4ccaf_row18_col13 {\n",
|
|
" background-color: #90b2fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row14_col18 {\n",
|
|
" background-color: #8fb1fe;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row15_col1 {\n",
|
|
" background-color: #5572df;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row15_col13 {\n",
|
|
" background-color: #9fbfff;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row15_col18 {\n",
|
|
" background-color: #b5cdfa;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row16_col13 {\n",
|
|
" background-color: #aec9fc;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row16_col18 {\n",
|
|
" background-color: #7da0f9;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row17_col2 {\n",
|
|
" background-color: #ebd3c6;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row17_col8 {\n",
|
|
" background-color: #bed2f6;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row18_col3 {\n",
|
|
" background-color: #f59d7e;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row18_col5 {\n",
|
|
" background-color: #6f92f3;\n",
|
|
" color: #f1f1f1;\n",
|
|
"}\n",
|
|
"#T_4ccaf_row18_col6 {\n",
|
|
" background-color: #f4c6af;\n",
|
|
" color: #000000;\n",
|
|
"}\n",
|
|
"</style>\n",
|
|
"<table id=\"T_4ccaf\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr>\n",
|
|
" <th class=\"blank level0\" > </th>\n",
|
|
" <th id=\"T_4ccaf_level0_col0\" class=\"col_heading level0 col0\" >domain</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col1\" class=\"col_heading level0 col1\" >subdomain</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col2\" class=\"col_heading level0 col2\" >top_level_domain</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col3\" class=\"col_heading level0 col3\" >query</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col4\" class=\"col_heading level0 col4\" >fragment</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col5\" class=\"col_heading level0 col5\" >redirect</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col6\" class=\"col_heading level0 col6\" >path</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col7\" class=\"col_heading level0 col7\" >redirect_chain</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col8\" class=\"col_heading level0 col8\" >hsts_header</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col9\" class=\"col_heading level0 col9\" >ssl_stripping</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col10\" class=\"col_heading level0 col10\" >hostname_embedding</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col11\" class=\"col_heading level0 col11\" >javascript_check</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col12\" class=\"col_heading level0 col12\" >shortening_service</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col13\" class=\"col_heading level0 col13\" >has_ip_address</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col14\" class=\"col_heading level0 col14\" >tracking_descriptions</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col15\" class=\"col_heading level0 col15\" >url_encoding</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col16\" class=\"col_heading level0 col16\" >has_executable</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col17\" class=\"col_heading level0 col17\" >tls</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col18\" class=\"col_heading level0 col18\" >contents</th>\n",
|
|
" <th id=\"T_4ccaf_level0_col19\" class=\"col_heading level0 col19\" >target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row0\" class=\"row_heading level0 row0\" >domain</th>\n",
|
|
" <td id=\"T_4ccaf_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col1\" class=\"data row0 col1\" >-0.149618</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col2\" class=\"data row0 col2\" >0.070517</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col3\" class=\"data row0 col3\" >0.025251</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col4\" class=\"data row0 col4\" >-0.001999</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col5\" class=\"data row0 col5\" >-0.091271</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col6\" class=\"data row0 col6\" >-0.103002</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col7\" class=\"data row0 col7\" >-0.032532</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col8\" class=\"data row0 col8\" >-0.132035</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col9\" class=\"data row0 col9\" >-0.020964</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col10\" class=\"data row0 col10\" >-0.016897</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col11\" class=\"data row0 col11\" >0.000905</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col12\" class=\"data row0 col12\" >-0.016502</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col13\" class=\"data row0 col13\" >0.109330</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col14\" class=\"data row0 col14\" >-0.020126</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col15\" class=\"data row0 col15\" >-0.054941</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col16\" class=\"data row0 col16\" >-0.051782</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col17\" class=\"data row0 col17\" >-0.057589</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col18\" class=\"data row0 col18\" >0.034923</td>\n",
|
|
" <td id=\"T_4ccaf_row0_col19\" class=\"data row0 col19\" >-0.004340</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row1\" class=\"row_heading level0 row1\" >subdomain</th>\n",
|
|
" <td id=\"T_4ccaf_row1_col0\" class=\"data row1 col0\" >-0.149618</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col2\" class=\"data row1 col2\" >-0.109429</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col3\" class=\"data row1 col3\" >0.033378</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col4\" class=\"data row1 col4\" >0.004213</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col5\" class=\"data row1 col5\" >-0.074009</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col6\" class=\"data row1 col6\" >-0.008929</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col7\" class=\"data row1 col7\" >-0.025925</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col8\" class=\"data row1 col8\" >-0.069056</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col9\" class=\"data row1 col9\" >-0.031019</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col10\" class=\"data row1 col10\" >0.489992</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col11\" class=\"data row1 col11\" >-0.000740</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col12\" class=\"data row1 col12\" >0.080844</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col13\" class=\"data row1 col13\" >-0.042574</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col14\" class=\"data row1 col14\" >0.002598</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col15\" class=\"data row1 col15\" >-0.046689</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col16\" class=\"data row1 col16\" >0.023112</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col17\" class=\"data row1 col17\" >0.001871</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col18\" class=\"data row1 col18\" >0.276423</td>\n",
|
|
" <td id=\"T_4ccaf_row1_col19\" class=\"data row1 col19\" >0.058300</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row2\" class=\"row_heading level0 row2\" >top_level_domain</th>\n",
|
|
" <td id=\"T_4ccaf_row2_col0\" class=\"data row2 col0\" >0.070517</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col1\" class=\"data row2 col1\" >-0.109429</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col3\" class=\"data row2 col3\" >-0.116257</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col4\" class=\"data row2 col4\" >-0.001123</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col5\" class=\"data row2 col5\" >0.029653</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col6\" class=\"data row2 col6\" >0.060649</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col7\" class=\"data row2 col7\" >0.007279</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col8\" class=\"data row2 col8\" >0.156154</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col9\" class=\"data row2 col9\" >0.045547</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col10\" class=\"data row2 col10\" >0.029927</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col11\" class=\"data row2 col11\" >0.001463</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col12\" class=\"data row2 col12\" >0.075501</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col13\" class=\"data row2 col13\" >-0.474097</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col14\" class=\"data row2 col14\" >-0.007049</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col15\" class=\"data row2 col15\" >0.075147</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col16\" class=\"data row2 col16\" >-0.076408</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col17\" class=\"data row2 col17\" >0.350973</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col18\" class=\"data row2 col18\" >-0.069449</td>\n",
|
|
" <td id=\"T_4ccaf_row2_col19\" class=\"data row2 col19\" >-0.183335</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row3\" class=\"row_heading level0 row3\" >query</th>\n",
|
|
" <td id=\"T_4ccaf_row3_col0\" class=\"data row3 col0\" >0.025251</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col1\" class=\"data row3 col1\" >0.033378</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col2\" class=\"data row3 col2\" >-0.116257</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col4\" class=\"data row3 col4\" >0.000368</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col5\" class=\"data row3 col5\" >0.019897</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col6\" class=\"data row3 col6\" >-0.125852</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col7\" class=\"data row3 col7\" >0.102771</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col8\" class=\"data row3 col8\" >-0.079392</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col9\" class=\"data row3 col9\" >-0.037063</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col10\" class=\"data row3 col10\" >0.031424</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col11\" class=\"data row3 col11\" >0.003336</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col12\" class=\"data row3 col12\" >-0.016585</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col13\" class=\"data row3 col13\" >-0.042096</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col14\" class=\"data row3 col14\" >0.063684</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col15\" class=\"data row3 col15\" >0.148184</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col16\" class=\"data row3 col16\" >-0.033489</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col17\" class=\"data row3 col17\" >-0.265888</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col18\" class=\"data row3 col18\" >0.673632</td>\n",
|
|
" <td id=\"T_4ccaf_row3_col19\" class=\"data row3 col19\" >0.018143</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row4\" class=\"row_heading level0 row4\" >fragment</th>\n",
|
|
" <td id=\"T_4ccaf_row4_col0\" class=\"data row4 col0\" >-0.001999</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col1\" class=\"data row4 col1\" >0.004213</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col2\" class=\"data row4 col2\" >-0.001123</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col3\" class=\"data row4 col3\" >0.000368</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col4\" class=\"data row4 col4\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col5\" class=\"data row4 col5\" >-0.002871</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col6\" class=\"data row4 col6\" >0.002008</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col7\" class=\"data row4 col7\" >0.002674</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col8\" class=\"data row4 col8\" >-0.003584</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col9\" class=\"data row4 col9\" >-0.001408</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col10\" class=\"data row4 col10\" >0.004069</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col11\" class=\"data row4 col11\" >-0.000034</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col12\" class=\"data row4 col12\" >0.009304</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col13\" class=\"data row4 col13\" >0.001973</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col14\" class=\"data row4 col14\" >-0.000554</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col15\" class=\"data row4 col15\" >0.001837</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col16\" class=\"data row4 col16\" >-0.001020</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col17\" class=\"data row4 col17\" >0.000983</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col18\" class=\"data row4 col18\" >0.030370</td>\n",
|
|
" <td id=\"T_4ccaf_row4_col19\" class=\"data row4 col19\" >0.014667</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row5\" class=\"row_heading level0 row5\" >redirect</th>\n",
|
|
" <td id=\"T_4ccaf_row5_col0\" class=\"data row5 col0\" >-0.091271</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col1\" class=\"data row5 col1\" >-0.074009</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col2\" class=\"data row5 col2\" >0.029653</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col3\" class=\"data row5 col3\" >0.019897</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col4\" class=\"data row5 col4\" >-0.002871</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col5\" class=\"data row5 col5\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col6\" class=\"data row5 col6\" >0.110208</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col7\" class=\"data row5 col7\" >0.493915</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col8\" class=\"data row5 col8\" >0.124105</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col9\" class=\"data row5 col9\" >0.312038</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col10\" class=\"data row5 col10\" >-0.048606</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col11\" class=\"data row5 col11\" >-0.001758</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col12\" class=\"data row5 col12\" >-0.019225</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col13\" class=\"data row5 col13\" >-0.072290</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col14\" class=\"data row5 col14\" >-0.003036</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col15\" class=\"data row5 col15\" >0.025532</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col16\" class=\"data row5 col16\" >-0.050106</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col17\" class=\"data row5 col17\" >-0.034452</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col18\" class=\"data row5 col18\" >0.062467</td>\n",
|
|
" <td id=\"T_4ccaf_row5_col19\" class=\"data row5 col19\" >-0.125495</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row6\" class=\"row_heading level0 row6\" >path</th>\n",
|
|
" <td id=\"T_4ccaf_row6_col0\" class=\"data row6 col0\" >-0.103002</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col1\" class=\"data row6 col1\" >-0.008929</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col2\" class=\"data row6 col2\" >0.060649</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col3\" class=\"data row6 col3\" >-0.125852</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col4\" class=\"data row6 col4\" >0.002008</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col5\" class=\"data row6 col5\" >0.110208</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col6\" class=\"data row6 col6\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col7\" class=\"data row6 col7\" >0.132329</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col8\" class=\"data row6 col8\" >-0.034376</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col9\" class=\"data row6 col9\" >0.035940</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col10\" class=\"data row6 col10\" >0.003492</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col11\" class=\"data row6 col11\" >-0.001263</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col12\" class=\"data row6 col12\" >0.009201</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col13\" class=\"data row6 col13\" >-0.071098</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col14\" class=\"data row6 col14\" >-0.010602</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col15\" class=\"data row6 col15\" >0.244904</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col16\" class=\"data row6 col16\" >-0.002244</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col17\" class=\"data row6 col17\" >-0.146011</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col18\" class=\"data row6 col18\" >0.561191</td>\n",
|
|
" <td id=\"T_4ccaf_row6_col19\" class=\"data row6 col19\" >-0.149450</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row7\" class=\"row_heading level0 row7\" >redirect_chain</th>\n",
|
|
" <td id=\"T_4ccaf_row7_col0\" class=\"data row7 col0\" >-0.032532</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col1\" class=\"data row7 col1\" >-0.025925</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col2\" class=\"data row7 col2\" >0.007279</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col3\" class=\"data row7 col3\" >0.102771</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col4\" class=\"data row7 col4\" >0.002674</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col5\" class=\"data row7 col5\" >0.493915</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col6\" class=\"data row7 col6\" >0.132329</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col7\" class=\"data row7 col7\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col8\" class=\"data row7 col8\" >0.052521</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col9\" class=\"data row7 col9\" >0.079979</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col10\" class=\"data row7 col10\" >-0.024769</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col11\" class=\"data row7 col11\" >-0.000991</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col12\" class=\"data row7 col12\" >0.002580</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col13\" class=\"data row7 col13\" >-0.038346</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col14\" class=\"data row7 col14\" >0.005351</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col15\" class=\"data row7 col15\" >0.057792</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col16\" class=\"data row7 col16\" >-0.023774</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col17\" class=\"data row7 col17\" >-0.050487</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col18\" class=\"data row7 col18\" >0.157086</td>\n",
|
|
" <td id=\"T_4ccaf_row7_col19\" class=\"data row7 col19\" >-0.065771</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row8\" class=\"row_heading level0 row8\" >hsts_header</th>\n",
|
|
" <td id=\"T_4ccaf_row8_col0\" class=\"data row8 col0\" >-0.132035</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col1\" class=\"data row8 col1\" >-0.069056</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col2\" class=\"data row8 col2\" >0.156154</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col3\" class=\"data row8 col3\" >-0.079392</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col4\" class=\"data row8 col4\" >-0.003584</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col5\" class=\"data row8 col5\" >0.124105</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col6\" class=\"data row8 col6\" >-0.034376</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col7\" class=\"data row8 col7\" >0.052521</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col8\" class=\"data row8 col8\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col9\" class=\"data row8 col9\" >-0.033615</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col10\" class=\"data row8 col10\" >-0.041312</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col11\" class=\"data row8 col11\" >-0.001456</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col12\" class=\"data row8 col12\" >-0.048528</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col13\" class=\"data row8 col13\" >-0.061468</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col14\" class=\"data row8 col14\" >-0.020496</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col15\" class=\"data row8 col15\" >-0.028736</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col16\" class=\"data row8 col16\" >-0.042739</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col17\" class=\"data row8 col17\" >0.298860</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col18\" class=\"data row8 col18\" >-0.113300</td>\n",
|
|
" <td id=\"T_4ccaf_row8_col19\" class=\"data row8 col19\" >-0.157230</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row9\" class=\"row_heading level0 row9\" >ssl_stripping</th>\n",
|
|
" <td id=\"T_4ccaf_row9_col0\" class=\"data row9 col0\" >-0.020964</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col1\" class=\"data row9 col1\" >-0.031019</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col2\" class=\"data row9 col2\" >0.045547</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col3\" class=\"data row9 col3\" >-0.037063</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col4\" class=\"data row9 col4\" >-0.001408</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col5\" class=\"data row9 col5\" >0.312038</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col6\" class=\"data row9 col6\" >0.035940</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col7\" class=\"data row9 col7\" >0.079979</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col8\" class=\"data row9 col8\" >-0.033615</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col9\" class=\"data row9 col9\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col10\" class=\"data row9 col10\" >-0.015376</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col11\" class=\"data row9 col11\" >-0.000543</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col12\" class=\"data row9 col12\" >-0.016078</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col13\" class=\"data row9 col13\" >-0.023061</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col14\" class=\"data row9 col14\" >0.000566</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col15\" class=\"data row9 col15\" >-0.009352</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col16\" class=\"data row9 col16\" >-0.016072</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col17\" class=\"data row9 col17\" >0.065977</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col18\" class=\"data row9 col18\" >-0.012553</td>\n",
|
|
" <td id=\"T_4ccaf_row9_col19\" class=\"data row9 col19\" >-0.035747</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row10\" class=\"row_heading level0 row10\" >hostname_embedding</th>\n",
|
|
" <td id=\"T_4ccaf_row10_col0\" class=\"data row10 col0\" >-0.016897</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col1\" class=\"data row10 col1\" >0.489992</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col2\" class=\"data row10 col2\" >0.029927</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col3\" class=\"data row10 col3\" >0.031424</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col4\" class=\"data row10 col4\" >0.004069</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col5\" class=\"data row10 col5\" >-0.048606</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col6\" class=\"data row10 col6\" >0.003492</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col7\" class=\"data row10 col7\" >-0.024769</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col8\" class=\"data row10 col8\" >-0.041312</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col9\" class=\"data row10 col9\" >-0.015376</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col10\" class=\"data row10 col10\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col11\" class=\"data row10 col11\" >-0.000308</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col12\" class=\"data row10 col12\" >0.025159</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col13\" class=\"data row10 col13\" >-0.011978</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col14\" class=\"data row10 col14\" >0.064650</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col15\" class=\"data row10 col15\" >-0.021480</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col16\" class=\"data row10 col16\" >-0.007927</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col17\" class=\"data row10 col17\" >0.015209</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col18\" class=\"data row10 col18\" >0.157565</td>\n",
|
|
" <td id=\"T_4ccaf_row10_col19\" class=\"data row10 col19\" >-0.006299</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row11\" class=\"row_heading level0 row11\" >javascript_check</th>\n",
|
|
" <td id=\"T_4ccaf_row11_col0\" class=\"data row11 col0\" >0.000905</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col1\" class=\"data row11 col1\" >-0.000740</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col2\" class=\"data row11 col2\" >0.001463</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col3\" class=\"data row11 col3\" >0.003336</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col4\" class=\"data row11 col4\" >-0.000034</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col5\" class=\"data row11 col5\" >-0.001758</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col6\" class=\"data row11 col6\" >-0.001263</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col7\" class=\"data row11 col7\" >-0.000991</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col8\" class=\"data row11 col8\" >-0.001456</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col9\" class=\"data row11 col9\" >-0.000543</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col10\" class=\"data row11 col10\" >-0.000308</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col11\" class=\"data row11 col11\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col12\" class=\"data row11 col12\" >0.003082</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col13\" class=\"data row11 col13\" >-0.000462</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col14\" class=\"data row11 col14\" >-0.000174</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col15\" class=\"data row11 col15\" >-0.000794</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col16\" class=\"data row11 col16\" >-0.000320</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col17\" class=\"data row11 col17\" >0.001206</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col18\" class=\"data row11 col18\" >0.001699</td>\n",
|
|
" <td id=\"T_4ccaf_row11_col19\" class=\"data row11 col19\" >-0.002031</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row12\" class=\"row_heading level0 row12\" >shortening_service</th>\n",
|
|
" <td id=\"T_4ccaf_row12_col0\" class=\"data row12 col0\" >-0.016502</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col1\" class=\"data row12 col1\" >0.080844</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col2\" class=\"data row12 col2\" >0.075501</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col3\" class=\"data row12 col3\" >-0.016585</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col4\" class=\"data row12 col4\" >0.009304</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col5\" class=\"data row12 col5\" >-0.019225</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col6\" class=\"data row12 col6\" >0.009201</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col7\" class=\"data row12 col7\" >0.002580</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col8\" class=\"data row12 col8\" >-0.048528</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col9\" class=\"data row12 col9\" >-0.016078</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col10\" class=\"data row12 col10\" >0.025159</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col11\" class=\"data row12 col11\" >0.003082</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col12\" class=\"data row12 col12\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col13\" class=\"data row12 col13\" >-0.035354</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col14\" class=\"data row12 col14\" >0.012540</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col15\" class=\"data row12 col15\" >-0.009572</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col16\" class=\"data row12 col16\" >-0.018367</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col17\" class=\"data row12 col17\" >0.046652</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col18\" class=\"data row12 col18\" >0.021110</td>\n",
|
|
" <td id=\"T_4ccaf_row12_col19\" class=\"data row12 col19\" >-0.018505</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row13\" class=\"row_heading level0 row13\" >has_ip_address</th>\n",
|
|
" <td id=\"T_4ccaf_row13_col0\" class=\"data row13 col0\" >0.109330</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col1\" class=\"data row13 col1\" >-0.042574</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col2\" class=\"data row13 col2\" >-0.474097</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col3\" class=\"data row13 col3\" >-0.042096</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col4\" class=\"data row13 col4\" >0.001973</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col5\" class=\"data row13 col5\" >-0.072290</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col6\" class=\"data row13 col6\" >-0.071098</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col7\" class=\"data row13 col7\" >-0.038346</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col8\" class=\"data row13 col8\" >-0.061468</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col9\" class=\"data row13 col9\" >-0.023061</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col10\" class=\"data row13 col10\" >-0.011978</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col11\" class=\"data row13 col11\" >-0.000462</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col12\" class=\"data row13 col12\" >-0.035354</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col13\" class=\"data row13 col13\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col14\" class=\"data row13 col14\" >-0.006584</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col15\" class=\"data row13 col15\" >-0.027852</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col16\" class=\"data row13 col16\" >0.032882</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col17\" class=\"data row13 col17\" >-0.202050</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col18\" class=\"data row13 col18\" >-0.093624</td>\n",
|
|
" <td id=\"T_4ccaf_row13_col19\" class=\"data row13 col19\" >0.175486</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row14\" class=\"row_heading level0 row14\" >tracking_descriptions</th>\n",
|
|
" <td id=\"T_4ccaf_row14_col0\" class=\"data row14 col0\" >-0.020126</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col1\" class=\"data row14 col1\" >0.002598</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col2\" class=\"data row14 col2\" >-0.007049</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col3\" class=\"data row14 col3\" >0.063684</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col4\" class=\"data row14 col4\" >-0.000554</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col5\" class=\"data row14 col5\" >-0.003036</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col6\" class=\"data row14 col6\" >-0.010602</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col7\" class=\"data row14 col7\" >0.005351</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col8\" class=\"data row14 col8\" >-0.020496</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col9\" class=\"data row14 col9\" >0.000566</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col10\" class=\"data row14 col10\" >0.064650</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col11\" class=\"data row14 col11\" >-0.000174</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col12\" class=\"data row14 col12\" >0.012540</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col13\" class=\"data row14 col13\" >-0.006584</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col14\" class=\"data row14 col14\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col15\" class=\"data row14 col15\" >0.014311</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col16\" class=\"data row14 col16\" >-0.005150</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col17\" class=\"data row14 col17\" >-0.019448</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col18\" class=\"data row14 col18\" >0.039709</td>\n",
|
|
" <td id=\"T_4ccaf_row14_col19\" class=\"data row14 col19\" >-0.021144</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row15\" class=\"row_heading level0 row15\" >url_encoding</th>\n",
|
|
" <td id=\"T_4ccaf_row15_col0\" class=\"data row15 col0\" >-0.054941</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col1\" class=\"data row15 col1\" >-0.046689</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col2\" class=\"data row15 col2\" >0.075147</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col3\" class=\"data row15 col3\" >0.148184</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col4\" class=\"data row15 col4\" >0.001837</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col5\" class=\"data row15 col5\" >0.025532</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col6\" class=\"data row15 col6\" >0.244904</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col7\" class=\"data row15 col7\" >0.057792</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col8\" class=\"data row15 col8\" >-0.028736</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col9\" class=\"data row15 col9\" >-0.009352</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col10\" class=\"data row15 col10\" >-0.021480</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col11\" class=\"data row15 col11\" >-0.000794</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col12\" class=\"data row15 col12\" >-0.009572</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col13\" class=\"data row15 col13\" >-0.027852</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col14\" class=\"data row15 col14\" >0.014311</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col15\" class=\"data row15 col15\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col16\" class=\"data row15 col16\" >-0.020636</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col17\" class=\"data row15 col17\" >-0.052264</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col18\" class=\"data row15 col18\" >0.181566</td>\n",
|
|
" <td id=\"T_4ccaf_row15_col19\" class=\"data row15 col19\" >-0.056759</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row16\" class=\"row_heading level0 row16\" >has_executable</th>\n",
|
|
" <td id=\"T_4ccaf_row16_col0\" class=\"data row16 col0\" >-0.051782</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col1\" class=\"data row16 col1\" >0.023112</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col2\" class=\"data row16 col2\" >-0.076408</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col3\" class=\"data row16 col3\" >-0.033489</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col4\" class=\"data row16 col4\" >-0.001020</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col5\" class=\"data row16 col5\" >-0.050106</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col6\" class=\"data row16 col6\" >-0.002244</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col7\" class=\"data row16 col7\" >-0.023774</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col8\" class=\"data row16 col8\" >-0.042739</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col9\" class=\"data row16 col9\" >-0.016072</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col10\" class=\"data row16 col10\" >-0.007927</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col11\" class=\"data row16 col11\" >-0.000320</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col12\" class=\"data row16 col12\" >-0.018367</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col13\" class=\"data row16 col13\" >0.032882</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col14\" class=\"data row16 col14\" >-0.005150</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col15\" class=\"data row16 col15\" >-0.020636</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col16\" class=\"data row16 col16\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col17\" class=\"data row16 col17\" >0.025109</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col18\" class=\"data row16 col18\" >-0.026814</td>\n",
|
|
" <td id=\"T_4ccaf_row16_col19\" class=\"data row16 col19\" >0.121012</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row17\" class=\"row_heading level0 row17\" >tls</th>\n",
|
|
" <td id=\"T_4ccaf_row17_col0\" class=\"data row17 col0\" >-0.057589</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col1\" class=\"data row17 col1\" >0.001871</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col2\" class=\"data row17 col2\" >0.350973</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col3\" class=\"data row17 col3\" >-0.265888</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col4\" class=\"data row17 col4\" >0.000983</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col5\" class=\"data row17 col5\" >-0.034452</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col6\" class=\"data row17 col6\" >-0.146011</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col7\" class=\"data row17 col7\" >-0.050487</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col8\" class=\"data row17 col8\" >0.298860</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col9\" class=\"data row17 col9\" >0.065977</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col10\" class=\"data row17 col10\" >0.015209</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col11\" class=\"data row17 col11\" >0.001206</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col12\" class=\"data row17 col12\" >0.046652</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col13\" class=\"data row17 col13\" >-0.202050</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col14\" class=\"data row17 col14\" >-0.019448</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col15\" class=\"data row17 col15\" >-0.052264</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col16\" class=\"data row17 col16\" >0.025109</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col17\" class=\"data row17 col17\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col18\" class=\"data row17 col18\" >-0.293321</td>\n",
|
|
" <td id=\"T_4ccaf_row17_col19\" class=\"data row17 col19\" >-0.217785</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row18\" class=\"row_heading level0 row18\" >contents</th>\n",
|
|
" <td id=\"T_4ccaf_row18_col0\" class=\"data row18 col0\" >0.034923</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col1\" class=\"data row18 col1\" >0.276423</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col2\" class=\"data row18 col2\" >-0.069449</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col3\" class=\"data row18 col3\" >0.673632</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col4\" class=\"data row18 col4\" >0.030370</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col5\" class=\"data row18 col5\" >0.062467</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col6\" class=\"data row18 col6\" >0.561191</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col7\" class=\"data row18 col7\" >0.157086</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col8\" class=\"data row18 col8\" >-0.113300</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col9\" class=\"data row18 col9\" >-0.012553</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col10\" class=\"data row18 col10\" >0.157565</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col11\" class=\"data row18 col11\" >0.001699</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col12\" class=\"data row18 col12\" >0.021110</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col13\" class=\"data row18 col13\" >-0.093624</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col14\" class=\"data row18 col14\" >0.039709</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col15\" class=\"data row18 col15\" >0.181566</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col16\" class=\"data row18 col16\" >-0.026814</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col17\" class=\"data row18 col17\" >-0.293321</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col18\" class=\"data row18 col18\" >1.000000</td>\n",
|
|
" <td id=\"T_4ccaf_row18_col19\" class=\"data row18 col19\" >-0.086009</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th id=\"T_4ccaf_level0_row19\" class=\"row_heading level0 row19\" >target</th>\n",
|
|
" <td id=\"T_4ccaf_row19_col0\" class=\"data row19 col0\" >-0.004340</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col1\" class=\"data row19 col1\" >0.058300</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col2\" class=\"data row19 col2\" >-0.183335</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col3\" class=\"data row19 col3\" >0.018143</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col4\" class=\"data row19 col4\" >0.014667</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col5\" class=\"data row19 col5\" >-0.125495</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col6\" class=\"data row19 col6\" >-0.149450</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col7\" class=\"data row19 col7\" >-0.065771</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col8\" class=\"data row19 col8\" >-0.157230</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col9\" class=\"data row19 col9\" >-0.035747</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col10\" class=\"data row19 col10\" >-0.006299</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col11\" class=\"data row19 col11\" >-0.002031</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col12\" class=\"data row19 col12\" >-0.018505</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col13\" class=\"data row19 col13\" >0.175486</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col14\" class=\"data row19 col14\" >-0.021144</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col15\" class=\"data row19 col15\" >-0.056759</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col16\" class=\"data row19 col16\" >0.121012</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col17\" class=\"data row19 col17\" >-0.217785</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col18\" class=\"data row19 col18\" >-0.086009</td>\n",
|
|
" <td id=\"T_4ccaf_row19_col19\" class=\"data row19 col19\" >1.000000</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 7
|
|
}
|
|
],
|
|
"source": [
|
|
"# Copy the data to avoid modifying the original DataFrame\n",
|
|
"data_encoded = data.copy()\n",
|
|
"\n",
|
|
"# Encode categorical variables with integer encoding\n",
|
|
"for column in data_encoded.select_dtypes(include=['object', 'category']).columns:\n",
|
|
" data_encoded[column] = data_encoded[column].astype('category').cat.codes\n",
|
|
"\n",
|
|
"# Calculate the correlation matrix\n",
|
|
"correlation_matrix = data_encoded.corr(method='pearson')\n",
|
|
"\n",
|
|
"# Sort correlations in descending order\n",
|
|
"sorted_correlations = correlation_matrix.unstack().sort_values(ascending=False, key=abs)\n",
|
|
"\n",
|
|
"# Remove duplicate correlations and self-correlations\n",
|
|
"sorted_correlations = sorted_correlations[(sorted_correlations < 1) &\n",
|
|
" (sorted_correlations > -1)].drop_duplicates()\n",
|
|
"\n",
|
|
"# Create a heatmap of the correlation matrix\n",
|
|
"plt.figure(figsize=(12, 10))\n",
|
|
"sns.heatmap(correlation_matrix, cmap='coolwarm', center=0, annot=True, fmt=\".2f\")\n",
|
|
"plt.title('Correlation Heatmap')\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"# Display sorted correlations with background gradient (optional)\n",
|
|
"styled_correlations = correlation_matrix.style.background_gradient(cmap='coolwarm')\n",
|
|
"styled_correlations\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "4hsixXH5Ufxx",
|
|
"outputId": "35da13dc-c365-48b4-e84a-451567f3d83f"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Correlations with the target class in descending order:\n",
|
|
"tls -0.217785\n",
|
|
"top_level_domain -0.183335\n",
|
|
"has_ip_address 0.175486\n",
|
|
"hsts_header -0.157230\n",
|
|
"path -0.149450\n",
|
|
"redirect -0.125495\n",
|
|
"has_executable 0.121012\n",
|
|
"contents -0.086009\n",
|
|
"redirect_chain -0.065771\n",
|
|
"subdomain 0.058300\n",
|
|
"url_encoding -0.056759\n",
|
|
"ssl_stripping -0.035747\n",
|
|
"tracking_descriptions -0.021144\n",
|
|
"shortening_service -0.018505\n",
|
|
"query 0.018143\n",
|
|
"fragment 0.014667\n",
|
|
"hostname_embedding -0.006299\n",
|
|
"domain -0.004340\n",
|
|
"javascript_check -0.002031\n",
|
|
"Name: target, dtype: float64\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Copy the data to avoid modifying the original DataFrame\n",
|
|
"data_encoded = data.copy()\n",
|
|
"\n",
|
|
"# Encode categorical variables with integer encoding\n",
|
|
"for column in data_encoded.select_dtypes(include=['object', 'category']).columns:\n",
|
|
" data_encoded[column] = data_encoded[column].astype('category').cat.codes\n",
|
|
"\n",
|
|
"# Calculate the correlation matrix\n",
|
|
"correlation_matrix = data_encoded.corr(method='pearson')\n",
|
|
"\n",
|
|
"# Extract correlations with the target class\n",
|
|
"target_correlations = correlation_matrix['target'].drop('target').sort_values(ascending=False, key=abs)\n",
|
|
"\n",
|
|
"# Display correlations with the target class\n",
|
|
"print(\"Correlations with the target class in descending order:\")\n",
|
|
"print(target_correlations)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "MZyGGJbuYQoS"
|
|
},
|
|
"source": [
|
|
"**Use stratified sampling to select 80% data for training and 20% for testing.**\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 260
|
|
},
|
|
"id": "z92Vk5Tqtyvc",
|
|
"outputId": "aa0b6629-f7a7-493a-e285-19ebf32db105"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Training set size: 485667\n",
|
|
"Testing set size: 161889\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain query fragment redirect path \\\n",
|
|
"270120 15 1 3 1 1 0 16 \n",
|
|
"158380 10 3 2 1 1 1 20 \n",
|
|
"410696 12 1 3 1 1 3 29 \n",
|
|
"206227 4 5 3 1 1 1 13 \n",
|
|
"76878 5 1 3 1 1 2 17 \n",
|
|
"\n",
|
|
" redirect_chain hsts_header ssl_stripping hostname_embedding \\\n",
|
|
"270120 1 0 0 0 \n",
|
|
"158380 92 0 0 0 \n",
|
|
"410696 356 0 0 0 \n",
|
|
"206227 83 0 0 0 \n",
|
|
"76878 113 0 1 0 \n",
|
|
"\n",
|
|
" javascript_check shortening_service has_ip_address \\\n",
|
|
"270120 0 0 0 \n",
|
|
"158380 0 0 0 \n",
|
|
"410696 0 0 0 \n",
|
|
"206227 0 0 0 \n",
|
|
"76878 0 0 0 \n",
|
|
"\n",
|
|
" tracking_descriptions url_encoding has_executable tls contents \\\n",
|
|
"270120 0 0 0 1 43 \n",
|
|
"158380 0 0 0 0 44 \n",
|
|
"410696 0 0 0 1 53 \n",
|
|
"206227 0 0 0 1 35 \n",
|
|
"76878 0 0 0 1 34 \n",
|
|
"\n",
|
|
" target \n",
|
|
"270120 0 \n",
|
|
"158380 1 \n",
|
|
"410696 0 \n",
|
|
"206227 3 \n",
|
|
"76878 0 "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-55557050-3149-416f-a934-6ad75c53831f\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>270120</th>\n",
|
|
" <td>15</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>16</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>43</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>158380</th>\n",
|
|
" <td>10</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>20</td>\n",
|
|
" <td>92</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>44</td>\n",
|
|
" <td>1</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>410696</th>\n",
|
|
" <td>12</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>29</td>\n",
|
|
" <td>356</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>206227</th>\n",
|
|
" <td>4</td>\n",
|
|
" <td>5</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>13</td>\n",
|
|
" <td>83</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>35</td>\n",
|
|
" <td>3</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>76878</th>\n",
|
|
" <td>5</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>2</td>\n",
|
|
" <td>17</td>\n",
|
|
" <td>113</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>34</td>\n",
|
|
" <td>0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-55557050-3149-416f-a934-6ad75c53831f')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-55557050-3149-416f-a934-6ad75c53831f 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-55557050-3149-416f-a934-6ad75c53831f');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-88afaa5c-7dd0-4356-bf50-b06922d71fe6\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-88afaa5c-7dd0-4356-bf50-b06922d71fe6')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-88afaa5c-7dd0-4356-bf50-b06922d71fe6 button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"variable_name": "train_data"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 9
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn.model_selection import StratifiedShuffleSplit\n",
|
|
"\n",
|
|
"# Define the stratified shuffle split\n",
|
|
"stratified_split = StratifiedShuffleSplit(n_splits=1, test_size=0.25, random_state=42)\n",
|
|
"\n",
|
|
"# Separate the features and target\n",
|
|
"X = data.drop(columns=['target'])\n",
|
|
"y = data['target']\n",
|
|
"\n",
|
|
"# Perform the split\n",
|
|
"for train_index, test_index in stratified_split.split(X, y):\n",
|
|
" X_train, X_test = X.iloc[train_index], X.iloc[test_index]\n",
|
|
" y_train, y_test = y.iloc[train_index], y.iloc[test_index]\n",
|
|
"\n",
|
|
"# Combine X and y for training and testing sets\n",
|
|
"train_data = X_train.copy()\n",
|
|
"train_data['target'] = y_train\n",
|
|
"\n",
|
|
"test_data = X_test.copy()\n",
|
|
"test_data['target'] = y_test\n",
|
|
"\n",
|
|
"# Display the number of samples in each set to verify\n",
|
|
"print(f\"Training set size: {len(train_data)}\")\n",
|
|
"print(f\"Testing set size: {len(test_data)}\")\n",
|
|
"\n",
|
|
"# Display the first few rows of the training set\n",
|
|
"train_data.head()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "QepghCeJ96ef",
|
|
"outputId": "beeb7f27-764a-48e5-df6b-a7df3e4da707"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"<class 'pandas.core.frame.DataFrame'>\n",
|
|
"Index: 485667 entries, 270120 to 216243\n",
|
|
"Data columns (total 20 columns):\n",
|
|
" # Column Non-Null Count Dtype\n",
|
|
"--- ------ -------------- -----\n",
|
|
" 0 domain 485667 non-null int64\n",
|
|
" 1 subdomain 485667 non-null int64\n",
|
|
" 2 top_level_domain 485667 non-null int64\n",
|
|
" 3 query 485667 non-null int64\n",
|
|
" 4 fragment 485667 non-null int64\n",
|
|
" 5 redirect 485667 non-null int64\n",
|
|
" 6 path 485667 non-null int64\n",
|
|
" 7 redirect_chain 485667 non-null int64\n",
|
|
" 8 hsts_header 485667 non-null int64\n",
|
|
" 9 ssl_stripping 485667 non-null int64\n",
|
|
" 10 hostname_embedding 485667 non-null int64\n",
|
|
" 11 javascript_check 485667 non-null int64\n",
|
|
" 12 shortening_service 485667 non-null int64\n",
|
|
" 13 has_ip_address 485667 non-null int64\n",
|
|
" 14 tracking_descriptions 485667 non-null int64\n",
|
|
" 15 url_encoding 485667 non-null int64\n",
|
|
" 16 has_executable 485667 non-null int64\n",
|
|
" 17 tls 485667 non-null int64\n",
|
|
" 18 contents 485667 non-null int64\n",
|
|
" 19 target 485667 non-null int64\n",
|
|
"dtypes: int64(20)\n",
|
|
"memory usage: 77.8 MB\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"train_data.info()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "o4WAXeK7-GsN",
|
|
"outputId": "d809b63a-6620-44ec-adca-e7cffe7ab348"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"<class 'pandas.core.frame.DataFrame'>\n",
|
|
"Index: 161889 entries, 262506 to 281817\n",
|
|
"Data columns (total 20 columns):\n",
|
|
" # Column Non-Null Count Dtype\n",
|
|
"--- ------ -------------- -----\n",
|
|
" 0 domain 161889 non-null int64\n",
|
|
" 1 subdomain 161889 non-null int64\n",
|
|
" 2 top_level_domain 161889 non-null int64\n",
|
|
" 3 query 161889 non-null int64\n",
|
|
" 4 fragment 161889 non-null int64\n",
|
|
" 5 redirect 161889 non-null int64\n",
|
|
" 6 path 161889 non-null int64\n",
|
|
" 7 redirect_chain 161889 non-null int64\n",
|
|
" 8 hsts_header 161889 non-null int64\n",
|
|
" 9 ssl_stripping 161889 non-null int64\n",
|
|
" 10 hostname_embedding 161889 non-null int64\n",
|
|
" 11 javascript_check 161889 non-null int64\n",
|
|
" 12 shortening_service 161889 non-null int64\n",
|
|
" 13 has_ip_address 161889 non-null int64\n",
|
|
" 14 tracking_descriptions 161889 non-null int64\n",
|
|
" 15 url_encoding 161889 non-null int64\n",
|
|
" 16 has_executable 161889 non-null int64\n",
|
|
" 17 tls 161889 non-null int64\n",
|
|
" 18 contents 161889 non-null int64\n",
|
|
" 19 target 161889 non-null int64\n",
|
|
"dtypes: int64(20)\n",
|
|
"memory usage: 25.9 MB\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"test_data.info()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 320
|
|
},
|
|
"id": "4SsfPK9T-KMP",
|
|
"outputId": "97e6f5eb-dde0-41ee-fe77-e135b243bdf9"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
" domain subdomain top_level_domain query \\\n",
|
|
"count 485667.000000 485667.000000 485667.000000 485667.000000 \n",
|
|
"mean 9.348127 4.363529 2.772908 12.765531 \n",
|
|
"std 4.975088 10.547273 0.509683 34.268056 \n",
|
|
"min 1.000000 1.000000 1.000000 1.000000 \n",
|
|
"25% 6.000000 1.000000 3.000000 1.000000 \n",
|
|
"50% 9.000000 1.000000 3.000000 1.000000 \n",
|
|
"75% 12.000000 3.000000 3.000000 1.000000 \n",
|
|
"max 63.000000 242.000000 13.000000 2441.000000 \n",
|
|
"\n",
|
|
" fragment redirect path redirect_chain \\\n",
|
|
"count 485667.000000 485667.000000 485667.000000 485667.000000 \n",
|
|
"mean 1.012014 0.538027 29.757869 84.199075 \n",
|
|
"std 1.179588 1.011421 31.774638 280.354627 \n",
|
|
"min 1.000000 0.000000 1.000000 1.000000 \n",
|
|
"25% 1.000000 0.000000 10.000000 1.000000 \n",
|
|
"50% 1.000000 0.000000 21.000000 52.000000 \n",
|
|
"75% 1.000000 1.000000 40.000000 113.000000 \n",
|
|
"max 494.000000 20.000000 2156.000000 32498.000000 \n",
|
|
"\n",
|
|
" hsts_header ssl_stripping hostname_embedding javascript_check \\\n",
|
|
"count 485667.000000 485667.000000 485667.000000 485667.000000 \n",
|
|
"mean 0.164016 0.026444 0.008646 0.000006 \n",
|
|
"std 0.370290 0.160452 0.092580 0.002485 \n",
|
|
"min 0.000000 0.000000 0.000000 0.000000 \n",
|
|
"25% 0.000000 0.000000 0.000000 0.000000 \n",
|
|
"50% 0.000000 0.000000 0.000000 0.000000 \n",
|
|
"75% 0.000000 0.000000 0.000000 0.000000 \n",
|
|
"max 1.000000 1.000000 1.000000 1.000000 \n",
|
|
"\n",
|
|
" shortening_service has_ip_address tracking_descriptions \\\n",
|
|
"count 485667.000000 485667.000000 485667.000000 \n",
|
|
"mean 0.061052 0.019419 0.002753 \n",
|
|
"std 0.239426 0.137991 0.052396 \n",
|
|
"min 0.000000 0.000000 0.000000 \n",
|
|
"25% 0.000000 0.000000 0.000000 \n",
|
|
"50% 0.000000 0.000000 0.000000 \n",
|
|
"75% 0.000000 0.000000 0.000000 \n",
|
|
"max 1.000000 1.000000 1.000000 \n",
|
|
"\n",
|
|
" url_encoding has_executable tls contents \\\n",
|
|
"count 485667.000000 485667.000000 485667.000000 485667.000000 \n",
|
|
"mean 0.055046 0.009496 0.687399 64.732677 \n",
|
|
"std 0.228070 0.096985 0.463554 40.343858 \n",
|
|
"min 0.000000 0.000000 0.000000 10.000000 \n",
|
|
"25% 0.000000 0.000000 0.000000 39.000000 \n",
|
|
"50% 0.000000 0.000000 1.000000 53.000000 \n",
|
|
"75% 0.000000 0.000000 1.000000 81.000000 \n",
|
|
"max 1.000000 1.000000 1.000000 2183.000000 \n",
|
|
"\n",
|
|
" target \n",
|
|
"count 485667.000000 \n",
|
|
"mean 0.663722 \n",
|
|
"std 1.074267 \n",
|
|
"min 0.000000 \n",
|
|
"25% 0.000000 \n",
|
|
"50% 0.000000 \n",
|
|
"75% 1.000000 \n",
|
|
"max 3.000000 "
|
|
],
|
|
"text/html": [
|
|
"\n",
|
|
" <div id=\"df-957200e9-9b6c-45a2-a029-865e8de5ea11\" class=\"colab-df-container\">\n",
|
|
" <div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>domain</th>\n",
|
|
" <th>subdomain</th>\n",
|
|
" <th>top_level_domain</th>\n",
|
|
" <th>query</th>\n",
|
|
" <th>fragment</th>\n",
|
|
" <th>redirect</th>\n",
|
|
" <th>path</th>\n",
|
|
" <th>redirect_chain</th>\n",
|
|
" <th>hsts_header</th>\n",
|
|
" <th>ssl_stripping</th>\n",
|
|
" <th>hostname_embedding</th>\n",
|
|
" <th>javascript_check</th>\n",
|
|
" <th>shortening_service</th>\n",
|
|
" <th>has_ip_address</th>\n",
|
|
" <th>tracking_descriptions</th>\n",
|
|
" <th>url_encoding</th>\n",
|
|
" <th>has_executable</th>\n",
|
|
" <th>tls</th>\n",
|
|
" <th>contents</th>\n",
|
|
" <th>target</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>count</th>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" <td>485667.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>mean</th>\n",
|
|
" <td>9.348127</td>\n",
|
|
" <td>4.363529</td>\n",
|
|
" <td>2.772908</td>\n",
|
|
" <td>12.765531</td>\n",
|
|
" <td>1.012014</td>\n",
|
|
" <td>0.538027</td>\n",
|
|
" <td>29.757869</td>\n",
|
|
" <td>84.199075</td>\n",
|
|
" <td>0.164016</td>\n",
|
|
" <td>0.026444</td>\n",
|
|
" <td>0.008646</td>\n",
|
|
" <td>0.000006</td>\n",
|
|
" <td>0.061052</td>\n",
|
|
" <td>0.019419</td>\n",
|
|
" <td>0.002753</td>\n",
|
|
" <td>0.055046</td>\n",
|
|
" <td>0.009496</td>\n",
|
|
" <td>0.687399</td>\n",
|
|
" <td>64.732677</td>\n",
|
|
" <td>0.663722</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>std</th>\n",
|
|
" <td>4.975088</td>\n",
|
|
" <td>10.547273</td>\n",
|
|
" <td>0.509683</td>\n",
|
|
" <td>34.268056</td>\n",
|
|
" <td>1.179588</td>\n",
|
|
" <td>1.011421</td>\n",
|
|
" <td>31.774638</td>\n",
|
|
" <td>280.354627</td>\n",
|
|
" <td>0.370290</td>\n",
|
|
" <td>0.160452</td>\n",
|
|
" <td>0.092580</td>\n",
|
|
" <td>0.002485</td>\n",
|
|
" <td>0.239426</td>\n",
|
|
" <td>0.137991</td>\n",
|
|
" <td>0.052396</td>\n",
|
|
" <td>0.228070</td>\n",
|
|
" <td>0.096985</td>\n",
|
|
" <td>0.463554</td>\n",
|
|
" <td>40.343858</td>\n",
|
|
" <td>1.074267</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>min</th>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>10.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>25%</th>\n",
|
|
" <td>6.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>3.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>10.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>39.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>50%</th>\n",
|
|
" <td>9.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>3.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>21.000000</td>\n",
|
|
" <td>52.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>53.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>75%</th>\n",
|
|
" <td>12.000000</td>\n",
|
|
" <td>3.000000</td>\n",
|
|
" <td>3.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>40.000000</td>\n",
|
|
" <td>113.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>81.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>max</th>\n",
|
|
" <td>63.000000</td>\n",
|
|
" <td>242.000000</td>\n",
|
|
" <td>13.000000</td>\n",
|
|
" <td>2441.000000</td>\n",
|
|
" <td>494.000000</td>\n",
|
|
" <td>20.000000</td>\n",
|
|
" <td>2156.000000</td>\n",
|
|
" <td>32498.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>1.000000</td>\n",
|
|
" <td>2183.000000</td>\n",
|
|
" <td>3.000000</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</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-957200e9-9b6c-45a2-a029-865e8de5ea11')\"\n",
|
|
" title=\"Convert this dataframe to an interactive table.\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
|
|
" <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
|
|
" </svg>\n",
|
|
" </button>\n",
|
|
"\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",
|
|
" fill: #174EA6;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-buttons div {\n",
|
|
" margin-bottom: 4px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert {\n",
|
|
" background-color: #3B4455;\n",
|
|
" fill: #D2E3FC;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-convert:hover {\n",
|
|
" background-color: #434B5C;\n",
|
|
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
|
|
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
|
|
" fill: #FFFFFF;\n",
|
|
" }\n",
|
|
" </style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" const buttonEl =\n",
|
|
" document.querySelector('#df-957200e9-9b6c-45a2-a029-865e8de5ea11 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-957200e9-9b6c-45a2-a029-865e8de5ea11');\n",
|
|
" const dataTable =\n",
|
|
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
|
|
" [key], {});\n",
|
|
" if (!dataTable) return;\n",
|
|
"\n",
|
|
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
|
|
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
|
|
" + ' to learn more about interactive tables.';\n",
|
|
" element.innerHTML = '';\n",
|
|
" dataTable['output_type'] = 'display_data';\n",
|
|
" await google.colab.output.renderOutput(dataTable, element);\n",
|
|
" const docLink = document.createElement('div');\n",
|
|
" docLink.innerHTML = docLinkHtml;\n",
|
|
" element.appendChild(docLink);\n",
|
|
" }\n",
|
|
" </script>\n",
|
|
" </div>\n",
|
|
"\n",
|
|
"\n",
|
|
"<div id=\"df-1dd524fd-2d6b-4204-9bd0-063069b6ea8e\">\n",
|
|
" <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1dd524fd-2d6b-4204-9bd0-063069b6ea8e')\"\n",
|
|
" title=\"Suggest charts\"\n",
|
|
" style=\"display:none;\">\n",
|
|
"\n",
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
|
|
" width=\"24px\">\n",
|
|
" <g>\n",
|
|
" <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
|
|
" </g>\n",
|
|
"</svg>\n",
|
|
" </button>\n",
|
|
"\n",
|
|
"<style>\n",
|
|
" .colab-df-quickchart {\n",
|
|
" --bg-color: #E8F0FE;\n",
|
|
" --fill-color: #1967D2;\n",
|
|
" --hover-bg-color: #E2EBFA;\n",
|
|
" --hover-fill-color: #174EA6;\n",
|
|
" --disabled-fill-color: #AAA;\n",
|
|
" --disabled-bg-color: #DDD;\n",
|
|
" }\n",
|
|
"\n",
|
|
" [theme=dark] .colab-df-quickchart {\n",
|
|
" --bg-color: #3B4455;\n",
|
|
" --fill-color: #D2E3FC;\n",
|
|
" --hover-bg-color: #434B5C;\n",
|
|
" --hover-fill-color: #FFFFFF;\n",
|
|
" --disabled-bg-color: #3B4455;\n",
|
|
" --disabled-fill-color: #666;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart {\n",
|
|
" background-color: var(--bg-color);\n",
|
|
" border: none;\n",
|
|
" border-radius: 50%;\n",
|
|
" cursor: pointer;\n",
|
|
" display: none;\n",
|
|
" fill: var(--fill-color);\n",
|
|
" height: 32px;\n",
|
|
" padding: 0;\n",
|
|
" width: 32px;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart:hover {\n",
|
|
" background-color: var(--hover-bg-color);\n",
|
|
" box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
|
|
" fill: var(--button-hover-fill-color);\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-quickchart-complete:disabled,\n",
|
|
" .colab-df-quickchart-complete:disabled:hover {\n",
|
|
" background-color: var(--disabled-bg-color);\n",
|
|
" fill: var(--disabled-fill-color);\n",
|
|
" box-shadow: none;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .colab-df-spinner {\n",
|
|
" border: 2px solid var(--fill-color);\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" animation:\n",
|
|
" spin 1s steps(1) infinite;\n",
|
|
" }\n",
|
|
"\n",
|
|
" @keyframes spin {\n",
|
|
" 0% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 20% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 30% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-left-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 40% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-top-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 60% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 80% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-right-color: var(--fill-color);\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" 90% {\n",
|
|
" border-color: transparent;\n",
|
|
" border-bottom-color: var(--fill-color);\n",
|
|
" }\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"\n",
|
|
" <script>\n",
|
|
" async function quickchart(key) {\n",
|
|
" const quickchartButtonEl =\n",
|
|
" document.querySelector('#' + key + ' button');\n",
|
|
" quickchartButtonEl.disabled = true; // To prevent multiple clicks.\n",
|
|
" quickchartButtonEl.classList.add('colab-df-spinner');\n",
|
|
" try {\n",
|
|
" const charts = await google.colab.kernel.invokeFunction(\n",
|
|
" 'suggestCharts', [key], {});\n",
|
|
" } catch (error) {\n",
|
|
" console.error('Error during call to suggestCharts:', error);\n",
|
|
" }\n",
|
|
" quickchartButtonEl.classList.remove('colab-df-spinner');\n",
|
|
" quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
|
|
" }\n",
|
|
" (() => {\n",
|
|
" let quickchartButtonEl =\n",
|
|
" document.querySelector('#df-1dd524fd-2d6b-4204-9bd0-063069b6ea8e button');\n",
|
|
" quickchartButtonEl.style.display =\n",
|
|
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
|
|
" })();\n",
|
|
" </script>\n",
|
|
"</div>\n",
|
|
"\n",
|
|
" </div>\n",
|
|
" </div>\n"
|
|
],
|
|
"application/vnd.google.colaboratory.intrinsic+json": {
|
|
"type": "dataframe",
|
|
"summary": "{\n \"name\": \"train_data\",\n \"rows\": 8,\n \"fields\": [\n {\n \"column\": \"domain\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171703.8960710791,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 9.348127420640068,\n 9.0,\n 485667.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"subdomain\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171695.95586336797,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 485667.0,\n 4.363528920021332,\n 242.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"top_level_domain\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171707.88712214323,\n \"min\": 0.5096831547034654,\n \"max\": 485667.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 485667.0,\n 2.772908186061643,\n 13.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"query\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171585.45952890522,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 12.765530703136099,\n 2441.0,\n 34.26805601168982\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"fragment\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171684.03772113574,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 1.0120144049317743,\n 494.0,\n 1.17958773631168\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"redirect\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171708.0757673105,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 485667.0,\n 0.538027084401452,\n 20.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"path\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171595.2005905886,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 29.757869074901116,\n 21.0,\n 485667.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"redirect_chain\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 170418.7664479191,\n \"min\": 1.0,\n \"max\": 485667.0,\n \"num_unique_values\": 7,\n \"samples\": [\n 485667.0,\n 84.19907467462274,\n 113.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"hsts_header\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.1370554599,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.1640156732905468,\n 1.0,\n 0.3702901761163625\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"ssl_stripping\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.15460230908,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.02644404499379204,\n 1.0,\n 0.16045189462060128\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"hostname_embedding\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.1589292924,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.008645841698118257,\n 1.0,\n 0.0925802828228983\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"javascript_check\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.16391615057,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 6.177071944356936e-06,\n 1.0,\n 0.00248536647334473\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"shortening_service\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.14886553315,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.0610521200740425,\n 1.0,\n 0.23942614047301342\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"has_ip_address\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.1560915753,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.019418655169076753,\n 1.0,\n 0.13799134106034808\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"tracking_descriptions\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.16125654572,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.002752915063201741,\n 1.0,\n 0.05239601296455595\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"url_encoding\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.1497424545,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.055045947120146106,\n 1.0,\n 0.22807016009986783\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"has_executable\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.15866387766,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.009496218602458063,\n 1.0,\n 0.09698484315610917\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"tls\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171709.00489500113,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.68739897913591,\n 1.0,\n 0.4635537348206182\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"contents\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171586.03400817013,\n \"min\": 10.0,\n \"max\": 485667.0,\n \"num_unique_values\": 8,\n \"samples\": [\n 64.73267691648805,\n 53.0,\n 485667.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"target\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 171708.9247399166,\n \"min\": 0.0,\n \"max\": 485667.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 485667.0,\n 0.6637222623731899,\n 3.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
|
|
}
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 12
|
|
}
|
|
],
|
|
"source": [
|
|
"train_data.describe(include='all')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "IEicRI-f-WDl",
|
|
"outputId": "2b542830-582c-4850-d3b0-083676674daf"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Training set size: 485667\n",
|
|
"target\n",
|
|
"0 322156\n",
|
|
"1 71879\n",
|
|
"3 67205\n",
|
|
"2 24427\n",
|
|
"Name: count, dtype: int64\n",
|
|
"Testing set size: 161889\n",
|
|
"target\n",
|
|
"0 107386\n",
|
|
"1 23959\n",
|
|
"3 22401\n",
|
|
"2 8143\n",
|
|
"Name: count, dtype: int64\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Verify the split\n",
|
|
"print(\"Training set size:\", len(train_data))\n",
|
|
"print(train_data['target'].value_counts())\n",
|
|
"\n",
|
|
"print(\"Testing set size:\", len(test_data))\n",
|
|
"print(test_data['target'].value_counts())"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "ILJ3kNRUTiFZ"
|
|
},
|
|
"source": [
|
|
"**Define Function to print Model Evaluation**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "l2RpSFMEQ6c4"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import seaborn as sns\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"from sklearn.metrics import confusion_matrix, classification_report, accuracy_score\n",
|
|
"\n",
|
|
"def evaluate_model(y_test, y_pred):\n",
|
|
" target_mapping = {0: \"Benign\", 1: \"Defacement\", 2: \"Malware\", 3: \"Phishing\"}\n",
|
|
"\n",
|
|
" accuracy = accuracy_score(y_test, y_pred)\n",
|
|
" print(\"Accuracy on test set:\", accuracy)\n",
|
|
"\n",
|
|
" # Generate confusion matrix\n",
|
|
" cm = confusion_matrix(y_test, y_pred, labels=list(target_mapping.keys()))\n",
|
|
"\n",
|
|
" # Plot confusion matrix\n",
|
|
" sns.heatmap(cm, annot=True, fmt='d', cmap='Blues',\n",
|
|
" xticklabels=list(target_mapping.values()),\n",
|
|
" yticklabels=list(target_mapping.values()))\n",
|
|
" plt.ylabel('Actual')\n",
|
|
" plt.xlabel('Predicted')\n",
|
|
" plt.title('Confusion Matrix')\n",
|
|
" plt.show()\n",
|
|
"\n",
|
|
" # Generate and print classification report\n",
|
|
" print(\"Classification Report:\")\n",
|
|
" print(classification_report(y_test, y_pred, target_names=list(target_mapping.values())))\n",
|
|
"\n",
|
|
"# Example usage:\n",
|
|
"# evaluate_model(y_test, y_pred)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "47oJwkwQXZdo"
|
|
},
|
|
"source": [
|
|
"**Random Forest Classifier**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 767
|
|
},
|
|
"id": "4fLZ9-NXZNG-",
|
|
"outputId": "5b079cb7-1f52-4c40-b049-f46420185d06"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Fitting 5 folds for each of 1 candidates, totalling 5 fits\n",
|
|
"Best parameters found: {'rf__max_depth': 15, 'rf__n_estimators': 100}\n",
|
|
"Accuracy on test set: 0.903415303078035\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Benign 0.92 0.97 0.94 107386\n",
|
|
" Defacement 0.86 0.95 0.90 23959\n",
|
|
" Malware 0.97 0.87 0.92 8143\n",
|
|
" Phishing 0.83 0.56 0.67 22401\n",
|
|
"\n",
|
|
" accuracy 0.90 161889\n",
|
|
" macro avg 0.90 0.84 0.86 161889\n",
|
|
"weighted avg 0.90 0.90 0.90 161889\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from math import e\n",
|
|
"from sklearn.ensemble import RandomForestClassifier\n",
|
|
"from sklearn.preprocessing import MinMaxScaler\n",
|
|
"from sklearn.model_selection import GridSearchCV\n",
|
|
"from sklearn.metrics import classification_report, accuracy_score\n",
|
|
"from sklearn.pipeline import Pipeline\n",
|
|
"\n",
|
|
"# Step 1: Create a pipeline with MinMaxScaler and RandomForestClassifier\n",
|
|
"pipeline = Pipeline([\n",
|
|
" ('scaler', MinMaxScaler()), # Scaling with MinMaxScaler\n",
|
|
" ('rf', RandomForestClassifier(random_state=42)) # Random Forest classifier\n",
|
|
"])\n",
|
|
"\n",
|
|
"# Step 2: Define the parameter grid for GridSearchCV\n",
|
|
"param_grid = {\n",
|
|
" 'rf__n_estimators': [100],\n",
|
|
" 'rf__max_depth': [15]\n",
|
|
"}\n",
|
|
"\n",
|
|
"# Step 3: Initialize GridSearchCV with the pipeline and parameter grid\n",
|
|
"grid_search = GridSearchCV(pipeline, param_grid, cv=5, n_jobs=-1, verbose=2, scoring='accuracy')\n",
|
|
"\n",
|
|
"# Step 4: Fit GridSearchCV to the training data\n",
|
|
"grid_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"# Step 5: Print the best parameters found by GridSearchCV\n",
|
|
"print(\"Best parameters found: \", grid_search.best_params_)\n",
|
|
"\n",
|
|
"# Step 6: Evaluate the model with the best parameters on the test set\n",
|
|
"best_model = grid_search.best_estimator_\n",
|
|
"y_pred = best_model.predict(X_test)\n",
|
|
"\n",
|
|
"# Evaluate Model\n",
|
|
"evaluate_model(y_test, y_pred)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "jArbqusVGGgq"
|
|
},
|
|
"source": [
|
|
"# **Save Model for Deployment**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "bmmgi2vVGG4a",
|
|
"outputId": "17a956c2-3dc0-4ba4-9a53-146b073f9a51"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"['/content/drive/MyDrive/random_forest_model.pkl']"
|
|
]
|
|
},
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"import joblib\n",
|
|
"\n",
|
|
"# Save the model\n",
|
|
"joblib.dump(best_model, '/content/drive/MyDrive/random_forest_model.pkl')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "F8Vd5n64jbFY"
|
|
},
|
|
"source": [
|
|
"**Multinomial Naive Bayes**"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 767
|
|
},
|
|
"id": "EahjckuTm0Bt",
|
|
"outputId": "e5e4ba16-e6a7-449b-b524-b3b3c0b07f7d"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Fitting 5 folds for each of 3 candidates, totalling 15 fits\n",
|
|
"Best parameters found: {'nb__alpha': 0.1}\n",
|
|
"Accuracy on test set: 0.6897503845227285\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Benign 0.68 1.00 0.81 107386\n",
|
|
" Defacement 0.42 0.00 0.00 23959\n",
|
|
" Malware 0.97 0.53 0.69 8143\n",
|
|
" Phishing 0.00 0.00 0.00 22401\n",
|
|
"\n",
|
|
" accuracy 0.69 161889\n",
|
|
" macro avg 0.52 0.38 0.37 161889\n",
|
|
"weighted avg 0.56 0.69 0.57 161889\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn.naive_bayes import MultinomialNB\n",
|
|
"\n",
|
|
"# Step 1: Create a pipeline with MinMaxScaler and MultinomialNB\n",
|
|
"pipeline = Pipeline([\n",
|
|
" ('scaler', MinMaxScaler()), # Scaling with MinMaxScaler\n",
|
|
" ('nb', MultinomialNB()) # Naive Bayes classifier\n",
|
|
"])\n",
|
|
"\n",
|
|
"# Step 2: Define the parameter grid for GridSearchCV\n",
|
|
"# Naive Bayes doesn't have as many parameters as RandomForest, so the grid is smaller\n",
|
|
"param_grid = {\n",
|
|
" 'nb__alpha': [0.1, 1.0, 10.0] # Smoothing parameter\n",
|
|
"}\n",
|
|
"\n",
|
|
"# Step 3: Initialize GridSearchCV with the pipeline and parameter grid\n",
|
|
"grid_search = GridSearchCV(pipeline, param_grid, cv=5, n_jobs=-1, verbose=2, scoring='accuracy')\n",
|
|
"\n",
|
|
"# Step 4: Fit GridSearchCV to the training data\n",
|
|
"grid_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"# Step 5: Print the best parameters found by GridSearchCV\n",
|
|
"print(\"Best parameters found: \", grid_search.best_params_)\n",
|
|
"\n",
|
|
"# Step 6: Evaluate the model with the best parameters on the test set\n",
|
|
"best_model = grid_search.best_estimator_\n",
|
|
"y_pred = best_model.predict(X_test)\n",
|
|
"\n",
|
|
"# Evaluate Model\n",
|
|
"evaluate_model(y_test, y_pred)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "XcyJia5sjcL-"
|
|
},
|
|
"source": [
|
|
"**XGBoost (eXtreme Gradient Boosting)**\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 698
|
|
},
|
|
"id": "2iu2e4A1oVkL",
|
|
"outputId": "3f6beba6-3b4b-455d-efc3-8111c1935c93"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Accuracy on test set: 0.9136815966495562\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
],
|
|
"image/png": "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\n"
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Benign 0.93 0.96 0.95 107386\n",
|
|
" Defacement 0.87 0.95 0.91 23959\n",
|
|
" Malware 0.95 0.89 0.92 8143\n",
|
|
" Phishing 0.83 0.65 0.73 22401\n",
|
|
"\n",
|
|
" accuracy 0.91 161889\n",
|
|
" macro avg 0.90 0.86 0.88 161889\n",
|
|
"weighted avg 0.91 0.91 0.91 161889\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from xgboost import XGBClassifier\n",
|
|
"from sklearn.metrics import classification_report, accuracy_score\n",
|
|
"\n",
|
|
"# Initialize the model\n",
|
|
"model = XGBClassifier(objective='multi:softmax', num_class=4, random_state=42)\n",
|
|
"\n",
|
|
"# Fit the model to the training data\n",
|
|
"model.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"# Predict on the test set\n",
|
|
"y_pred = model.predict(X_test)\n",
|
|
"\n",
|
|
"# Evaluate the model\n",
|
|
"evaluate_model(y_test, y_pred)\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 787
|
|
},
|
|
"id": "1fvK493sRSBd",
|
|
"outputId": "fab548c9-f53c-4cca-d1bd-31d61c41fec1"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"metadata": {
|
|
"tags": null
|
|
},
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Fitting 5 folds for each of 8 candidates, totalling 40 fits\n"
|
|
]
|
|
},
|
|
{
|
|
"metadata": {
|
|
"tags": null
|
|
},
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/usr/local/lib/python3.10/dist-packages/joblib/externals/loky/process_executor.py:752: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n",
|
|
" warnings.warn(\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Best parameters found: {'n_estimators': 200, 'max_depth': 10, 'learning_rate': 0.2}\n",
|
|
"Accuracy on test set: 0.9327749260295635\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
],
|
|
"image/png": "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\n"
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Benign 0.95 0.97 0.96 107386\n",
|
|
" Defacement 0.90 0.96 0.93 23959\n",
|
|
" Malware 0.96 0.92 0.94 8143\n",
|
|
" Phishing 0.85 0.73 0.79 22401\n",
|
|
"\n",
|
|
" accuracy 0.93 161889\n",
|
|
" macro avg 0.92 0.90 0.91 161889\n",
|
|
"weighted avg 0.93 0.93 0.93 161889\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn.model_selection import RandomizedSearchCV\n",
|
|
"\n",
|
|
"param_distributions = {\n",
|
|
" 'n_estimators': [100, 200],\n",
|
|
" 'max_depth': [6, 10],\n",
|
|
" 'learning_rate': [0.1, 0.2]\n",
|
|
"}\n",
|
|
"\n",
|
|
"randomized_search = RandomizedSearchCV(\n",
|
|
" model, param_distributions, n_iter=8, scoring='accuracy', cv=5, verbose=1, random_state=42, n_jobs=-1\n",
|
|
")\n",
|
|
"\n",
|
|
"randomized_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"# Best parameters found\n",
|
|
"print(\"Best parameters found: \", randomized_search.best_params_)\n",
|
|
"\n",
|
|
"# Evaluate the best model\n",
|
|
"best_model = randomized_search.best_estimator_\n",
|
|
"y_pred = best_model.predict(X_test)\n",
|
|
"evaluate_model(y_test, y_pred)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "4qD9Y15UI8Q6",
|
|
"outputId": "9e61cae9-dfe9-40e2-b3f3-92e8d480b69f"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "execute_result",
|
|
"data": {
|
|
"text/plain": [
|
|
"['/content/drive/MyDrive/randomized_search_xgb_model-2.pkl']"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"execution_count": 37
|
|
}
|
|
],
|
|
"source": [
|
|
"import joblib\n",
|
|
"# Save the model\n",
|
|
"joblib.dump(best_model, '/content/drive/MyDrive/randomized_search_xgb_model-2.pkl')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"source": [
|
|
"**Multilayer Perceptron Classifier**"
|
|
],
|
|
"metadata": {
|
|
"id": "0uDd7pKyjYdN"
|
|
}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "nCY14uaioahd",
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/",
|
|
"height": 787
|
|
},
|
|
"outputId": "ffd251df-223f-4e81-ba2d-6e921ed2871e"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Fitting 3 folds for each of 2 candidates, totalling 6 fits\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stderr",
|
|
"text": [
|
|
"/usr/local/lib/python3.10/dist-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n",
|
|
" warnings.warn(\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Best parameters found: {'mlp__activation': 'relu', 'mlp__alpha': 0.0001, 'mlp__hidden_layer_sizes': (100,), 'mlp__learning_rate': 'constant', 'mlp__solver': 'adam'}\n",
|
|
"Accuracy on test set: 0.8830186115177684\n"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "display_data",
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 2 Axes>"
|
|
],
|
|
"image/png": "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\n"
|
|
},
|
|
"metadata": {}
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"name": "stdout",
|
|
"text": [
|
|
"Classification Report:\n",
|
|
" precision recall f1-score support\n",
|
|
"\n",
|
|
" Benign 0.90 0.96 0.93 107386\n",
|
|
" Defacement 0.82 0.93 0.87 23959\n",
|
|
" Malware 0.92 0.79 0.85 8143\n",
|
|
" Phishing 0.82 0.49 0.61 22401\n",
|
|
"\n",
|
|
" accuracy 0.88 161889\n",
|
|
" macro avg 0.87 0.79 0.82 161889\n",
|
|
"weighted avg 0.88 0.88 0.87 161889\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn.neural_network import MLPClassifier\n",
|
|
"from sklearn.preprocessing import MinMaxScaler\n",
|
|
"from sklearn.model_selection import GridSearchCV\n",
|
|
"from sklearn.metrics import classification_report, accuracy_score\n",
|
|
"from sklearn.pipeline import Pipeline\n",
|
|
"\n",
|
|
"pipeline = Pipeline([\n",
|
|
" ('scaler', MinMaxScaler()),\n",
|
|
" ('mlp', MLPClassifier(random_state=42, max_iter=300))\n",
|
|
"])\n",
|
|
"\n",
|
|
"param_grid = {\n",
|
|
" 'mlp__hidden_layer_sizes': [(50,), (100,)],\n",
|
|
" 'mlp__activation': ['relu'],\n",
|
|
" 'mlp__solver': ['adam'],\n",
|
|
" 'mlp__alpha': [0.0001],\n",
|
|
" 'mlp__learning_rate': ['constant']\n",
|
|
"}\n",
|
|
"\n",
|
|
"grid_search = GridSearchCV(pipeline, param_grid, cv=3, n_jobs=-1, verbose=2, scoring='accuracy')\n",
|
|
"\n",
|
|
"grid_search.fit(X_train, y_train)\n",
|
|
"\n",
|
|
"print(\"Best parameters found: \", grid_search.best_params_)\n",
|
|
"\n",
|
|
"best_model = grid_search.best_estimator_\n",
|
|
"y_pred = best_model.predict(X_test)\n",
|
|
"\n",
|
|
"evaluate_model(y_test, y_pred)\n"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"colab": {
|
|
"provenance": []
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"name": "python"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
} |