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Code for the offshore data blog post at welivein.space. Title: "Taking a closer look at all the offshore leaks" URL: https://welivein.space/data-science/python/2018/07/16/offshore_leaks.html
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Offshore_Leaks_Code.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"\"\"\"\n",
"Code for the offshore data blog post at welivein.space.\n",
"\n",
"Title: \"TAKING A CLOSER LOOK AT ALL THE OFFSHORE LEAKS\"\n",
"URL: https://welivein.space/data-science/python/2018/07/16/offshore_leaks.html\n",
"\"\"\"\n",
"import os\n",
"import glob\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import wikipedia\n",
"from tqdm import tqdm\n",
"from pprint import pprint\n",
"import seaborn as sns\n",
"pd.set_option(\"display.max_columns\", 24)\n",
"sns.set_style(\"whitegrid\")\n",
"sns.set_context(\"paper\")\n",
"sns.despine(offset=10, trim=True)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"\"\"\"\n",
"Functions that we need later\n",
"\"\"\"\n",
"def unique_vals(seq, idfun=None):\n",
" \"\"\"Find unique entries in a sequence and preserve the order.\"\"\"\n",
" seen = set()\n",
" return [x for x in seq if x not in seen and not seen.add(x)]\n",
"\n",
"\n",
"# Second: Compare two lists of strings in a fast manner\n",
"def compare(A, B):\n",
" \"\"\"Compare two lists of strings in a fast manner.\"\"\"\n",
" return list(set(A).intersection(B))\n",
"\n",
"\n",
"# define a function that prints all connection to a single name\n",
"def name_lookup_offshore(name, df):\n",
" \"\"\"\n",
" Look up names within the offshore data.\n",
"\n",
" Input:\n",
" name: (str) the name to look out for\n",
" df: (pandas dataframe) the dataframe that holds the offshore data\n",
" \"\"\"\n",
" vals = pd.unique(df.node_id[df.name == str(name).lower()].values)\n",
" print(\"#######################################\")\n",
" print(\"######### offshore database lookup:\")\n",
" print(\"#######################################\")\n",
" for ident_id in vals:\n",
" old_id = 0\n",
" for item in df[df.START_ID == ident_id].itertuples():\n",
" try:\n",
" relation_title = item.TYPE\n",
" id_ = int(item.END_ID)\n",
" if id_ == old_id:\n",
" raise IndexError()\n",
" else:\n",
" old_id = int(item.END_ID)\n",
" except IndexError:\n",
" id_ = False\n",
"\n",
" if relation_title == \"registered_address\" and id_:\n",
" # we\"re dealing with a private address here, so END_ID points\n",
" # to the address file where the address is saved in the\n",
" # address field.\n",
" try:\n",
" private_address = df.address.where(\n",
" df.node_id == item.END_ID).dropna().values[0]\n",
" except IndexError:\n",
" private_address = \"No address in the system\"\n",
"\n",
" print(\"{}; {}: {}, with id:{}\".format(name, relation_title,\n",
" private_address, id_))\n",
"\n",
" print(\"Find the interactive graph for this node at: \"\n",
" \"https://offshoreleaks.icij.org/nodes/{}\".format(id_))\n",
" print(\"------------------------\")\n",
"\n",
" elif relation_title == \"officer_of\" and id_:\n",
" try:\n",
" cmp_name = df.name.where(\n",
" df.node_id == id_).dropna().values[0]\n",
" except IndexError:\n",
" cmp_name = \"No name in the system\"\n",
" try:\n",
" cmp_jur = df.jurisdiction_description.where(\n",
" df.node_id == id_).dropna().values[0]\n",
" except IndexError:\n",
" cmp_name = \"No jurisdiction_description in the system\"\n",
" try:\n",
" comp_id = df.END_ID.where(\n",
" df.START_ID == id_).dropna().values[0]\n",
" cmp_address = df.address.where(\n",
" df.node_id == comp_id).dropna().values[0]\n",
" except IndexError:\n",
" cmp_address = \"No address in the system\"\n",
"\n",
" print(\n",
" \"{}; {}: {}, registered at: {}, jurisdiction: {}\".format(\n",
" name, relation_title, cmp_name, cmp_address, cmp_jur) +\n",
" \"with unique leak id:{}\".format(id_))\n",
" print(\"Find the interactive graph for this node at: \"\n",
" \"https://offshoreleaks.icij.org/nodes/{}\".format(id_))\n",
" print(\"------------------------\")\n",
"\n",
"\n",
"def name_lookup_psc(name, psc_names, psc_idxs, psc_df):\n",
" \"\"\"\n",
" Look up names within the psc data.\n",
"\n",
" Input:\n",
" name: (str) the name to look out for\n",
" psc_names: (str or list of str) the full list\n",
" of all names of the psc data\n",
" psc_idxs: (number or list of numbers) the full list\n",
" of all indexes of the psc data\n",
" psc_df: (pandas dataframe) the dataframe that\n",
" holds the psc data\n",
" \"\"\"\n",
" if psc_df is not None:\n",
" print(\"#######################################\")\n",
" print(\"######### psc database lookup:\")\n",
" print(\"#######################################\")\n",
" indexes = [i for i, x in enumerate(psc_names) if x == name]\n",
" if len(indexes) > 1:\n",
" print(\"Found multiple companies\")\n",
" for idx in indexes:\n",
" cmp_number = psc_df.company_number[psc_idxs[idx]]\n",
" print(\"------------------------\")\n",
" print(\"company number: {}\".format(cmp_number))\n",
" print(\"Find more information about this company at:\")\n",
" try:\n",
" print(\n",
" \"https://beta.companieshouse.gov.uk/company/{:08d}\".format(\n",
" int(cmp_number)))\n",
" except ValueError:\n",
" print(\"https://beta.companieshouse.gov.uk/company/{}\".format(\n",
" cmp_number))\n",
" print(\"------------------------\")\n",
" dict_ = psc_df.data[psc_idxs[idx]]\n",
" pprint(dict_)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['END_ID', 'START_ID', 'TYPE', 'address', 'closed_date', 'company_type',\n",
" 'countries', 'country_codes', 'end_date', 'ibcRUC', 'inactivation_date',\n",
" 'incorporation_date', 'jurisdiction', 'jurisdiction_description',\n",
" 'labels(n)', 'link', 'name', 'node_id', 'note', 'service_provider',\n",
" 'sourceID', 'start_date', 'status', 'struck_off_date', 'type',\n",
" 'valid_until'],\n",
" dtype='object')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# load the data\n",
"data_folder = \"/path/to/offshore_leak_data\"\n",
"files = glob.glob(os.path.join(data_folder, \"**\", \"*.csv\"), recursive=True)\n",
"data_frame = pd.concat(\n",
" [pd.read_csv(f, low_memory=False) for f in files], sort=True)\n",
"data_frame.name = data_frame.name.str.lower() # convert all name to lowercase\n",
"\n",
"# lets see what columns are available\n",
"data_frame.keys()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"#######################################\n",
"##### company_type #######\n",
"#######################################\n",
"Standard International Company 40072\n",
"Standard Company under IBC Act 26214\n",
"Business Company Limited by Shares 25130\n",
"Regular (Local) Company 17599\n",
"Client Sundry Account 8692\n",
"International Trust 999\n",
"Cook Islands Asset Protection Trust 547\n",
"Domestic Company 462\n",
"Cook Islands Asset Protection Trust - 3520A 445\n",
"International Company 390\n",
"Name: company_type, dtype: int64\n",
"#######################################\n",
"##### countries #######\n",
"#######################################\n",
"Malta 129661\n",
"Hong Kong 100243\n",
"China 72621\n",
"British Virgin Islands 61768\n",
"Barbados 57986\n",
"United States 55010\n",
"Not identified 51410\n",
"Switzerland 50913\n",
"Taiwan 39578\n",
"United Kingdom 36062\n",
"Name: countries, dtype: int64\n",
"#######################################\n",
"##### jurisdiction_description #######\n",
"#######################################\n",
"Bahamas 209686\n",
"British Virgin Islands 153872\n",
"Malta 83934\n",
"Saint Kitts and Nevis 70602\n",
"Undetermined 53571\n",
"Aruba 49050\n",
"Panama 48406\n",
"Barbados 40845\n",
"Seychelles 15964\n",
"Samoa 15013\n",
"Name: jurisdiction_description, dtype: int64\n",
"#######################################\n",
"##### name #######\n",
"#######################################\n",
"the bearer 71850\n",
"el portador 9351\n",
"bearer 1 2667\n",
"bearer 1367\n",
"carmichael trevor a. 1239\n",
"clementi limited 1113\n",
"tanah merah limited 1048\n",
"bukit merah limited 964\n",
"cst administration (baham 835\n",
"the corporate secretary limited 702\n",
"Name: name, dtype: int64\n",
"#######################################\n",
"##### service_provider #######\n",
"#######################################\n",
"Mossack Fonseca 213634\n",
"Portcullis Trustnet 61123\n",
"Commonwealth Trust Limited 44393\n",
"Appleby 24936\n",
"Name: service_provider, dtype: int64\n",
"#######################################\n",
"##### sourceID #######\n",
"#######################################\n",
"Panama Papers 1233702\n",
"Paradise Papers - Malta corporate registry 1090703\n",
"Offshore Leaks 841225\n",
"Paradise Papers - Appleby 554233\n",
"Bahamas Leaks 451432\n",
"Paradise Papers - Aruba corporate registry 228911\n",
"Paradise Papers - Barbados corporate registry 190554\n",
"Paradise Papers - Nevis corporate registry 70986\n",
"Paradise Papers - Bahamas corporate registry 38351\n",
"Paradise Papers - Samoa corporate registry 24456\n",
"Name: sourceID, dtype: int64\n"
]
}
],
"source": [
"# we\"ll pick the most interesting categories\n",
"cats = (\"company_type\", \"countries\", \"jurisdiction_description\", \"name\",\n",
" \"service_provider\", \"sourceID\")\n",
"\n",
"# print for every columns the top-10 histogramm entries\n",
"for key in cats:\n",
" try:\n",
" __data = data_frame.dropna(how=\"any\", subset=[key])\n",
" print(\"#######################################\")\n",
" print(\"##### {} #######\".format(key))\n",
" print(\"#######################################\")\n",
" print(__data[key].value_counts()[:10])\n",
" except (ValueError, KeyError):\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Plotting company_type\n",
"Plotting countries\n",
"Plotting jurisdiction_description\n",
"Plotting name\n",
"Plotting service_provider\n",
"Plotting sourceID\n",
"Printing to screen\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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k1Kpam2R1a+3G1tr2JNcledg++m4cb29McuV4+8o57QAAAADcjYUu0botyd8naUnul2GGzjuTbBsf35pk/fizbc7zZtvXJbkhSVprO6rqyPHxI1prO+b0feh8C9qyZcu8+h2zbv18N8m9NDM9M+9xmK91xx63qNvjLjPT04s+XgAAAEzGQgOe0zIENQ9PckKSP0pyfYbZPN9OckySW8efo+c8b7Z962z7OMvn9vHxO6pqbWvtzjl952XDhg3z6nfTLbfMd5PcS1NrpuY9DvN189Zt++/EgkytWbPo4wUAAMDi2bx587z7LnSJ1mFJbm2t7U7y3SRHZjjJ8pnj42ck2TQGNbuq6sRxls4jMgRBXxv7zPa9ery9aa/2TQusDwAAAOCQsdAZPP85yb+sqk1J1mY4yfIfJLl4bPtmkqvGvucm+VyGUOiC1tpMkmur6htVdXWS7UnOHvt+IMllVXVOhqtoXbvA+gAAAAAOGQsKeFpru3JXKDPXz+6j7zVJnryP9vMzXF59bttNSZ69kJoAAAAADlULXaIFAAAAwDIh4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6NzXpAoCV5bu335GdMzOTLmPFOXxqKvc/8ohJlwEAACxTAh5gUe2cmcnL3vnBSZex4nzqvW+ddAkAAMAyZokWAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQualJFwDA5Ny2487snNk16TJWpMOnVueo+66ddBkAABwiBDwAh7CdM7vyig9fOukyVqRL3vLySZcAAMAhxBItAAAAgM4JeAAAAAA6d0BLtKrq8Ul+Lcl9klyR5PeTXJrkqCRfbq2dP/Z7XpLzkuxJ8pbW2jVVdViSjyV5ZJJvJXlla+2OqnpYkk8mWZPkktbaxw+kRgAAAICVbsEzeKrqPkkuSPKC1trTWmsfSPL2JBe11jYmObmqTqqqqSTvTnJakrOSXDhu4owkO1trpyb5iyT/amx/f5Jzkjw1yauqav1CawQAAAA4FBzIDJ4nJbkjyWeranWSc5NsTPLO8fErx/u7krTW2vYk26tqdVWtTXJqhlk/GX+/K8lHkzy8tbY5Sarqq0ken+SL+ytmy5Yt8yr6mHXyoqUyMz0z73GYr3XHHreo2+MuM9PTiz5eSbLu+BMWfZsszesrSdaf8IBF3yaDpRozAADYlwMJeE5M8hNJHpvkR5L8XpIjWms7xse3JnloknVJts153rYk6/dq3zq2JcmqOX3ntt+jDRs2zKvom265ZV79uPem1kzNexzm6+at2/bfiQWZWrNm0ccrSW7+zncXfZsszesrSW657fZF3yaDpRozAAAOHZs3b5533wM5yfLWJP+1tXZ7a21LkqOT3DHOzkmSY5LcOvY7es7z9tU+25Yku/fRFwAAAIC7cSABzzVJalxydWKSHUk2ZTi3Tsbfm5JcN/Y7cuw301q7M8nXkpy5V98kua6qHjsu+3pahvPzAAAAAHA3FrxEq7W2tao+keSr43bOTdKSXFZV52S4ita1SVJVFyT5UsaraI2buCrJ86pqU8araI3t5+Wuq2hd3FozgwcAAADgHhzQZdJba7+f4dLocz17H/0uT3L5Xm27k7x2H32vzzBzBwAAAIB5OJAlWgAAAAAsAwc0gwcAOLhuu3NnpnftmnQZK86a1atz1NrDJ10GAMCCCXgAoCPTu3bl1Zf88aTLWHEuesWzJl0CAMABsUQLAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzU5MuAABgpdr+vZ2Z3rV70mWsSGtWH5b73efwSZcBAMuGgAcAYIlM79qdN33+6kmXsSL99os2TroEAFhWLNECAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgc1OTLgAAAJaD23fuzMyu3ZMuY0WaWn1Yjjz88EmXAbCiCXgAACDJzK7dOf+LmyZdxor0nmefOukSAFY8AQ8AANClHTt3Zma3WVeLbeqww3JfM66gOwIeAACgSzO7d+fCPzHrarGd8zQzrqBHTrIMAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA56YO5MlVtTHJpiTHJ1mV5NIkRyX5cmvt/LHP85Kcl2RPkre01q6pqsOSfCzJI5N8K8krW2t3VNXDknwyyZokl7TWPn4g9QEAAAAcCg50Bs9bknx9vP32JBe11jYmObmqTqqqqSTvTnJakrOSXDj2PSPJztbaqUn+Ism/Gtvfn+ScJE9N8qqqWn+A9QEAAACseAsOeKrquUmuTnL72LQxyZXj7SvH+w9P0lpr21trNyZZXVVrk5ya5Iqx7xXj/SR5eGttc2ttJslXkzx+ofUBAAAAHCoWtERrXGL1uiQvSvL8sfmI1tqO8fbWJA9Nsi7JtjlP3ZZk/V7tW8e2ZFjmlX2079eWLVvm1e+YdSYFLZWZ6Zl5j8N8rTv2uEXdHneZmZ5e9PFKknXHn7Do22RpXl9Jsv6EByz6Nhks1Zgd+4AHLfo2SWZmlma8jnvggxd9mwyWYsyOf5DxWirTS/QaO+HBxmwpLNV4AUtroefgeVmSy1trd1bVbNsdVbW2tXZnkmOS3JohpDl6zvP21T7bliS79+r71/MtaMOGDfPqd9Mtt8x3k9xLU2um5j0O83Xz1m3778SCTK1Zs+jjlSQ3f+e7i75Nlub1lSS33Hb7/juxIEs1ZrfevmP/nbjXpqaWZry23nHnom+TwVKM2Xd2GK+lsmaJXmO33WnMlsJSjded0zszs3v3/jtyr00ddljWrjl80mWwBDZv3jzvvgsNeH4iySlV9YIkj07ymQwnWz4jyefH3+cluS5JVdWRSe6fZGYMhb6W5Mwkfzz23TRu97qqemySbyR5WpIPLLA+AAAAlpGZ3btz8devnnQZK9IrH7dx0iWwDCwo4GmtvX32dlV9NclLMiyvuqyqzslwFa1rx8cvSPKljFfRGp92VZLnVdWmjFfRGtvPy11X0bq4tTY7swcAAACAu3FAl0lPktba0+fcffY+Hr88yeV7te1O8tp99L0+w8wdAAAAAObpQC+TDgAAAMCECXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzU5MuAAAAAFhevjcznV17dk+6jBVp9arDcp+pNYu+XQEPAAAA8H127dmdL3zzTyddxor0/Ec+ZUm2a4kWAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANA5AQ8AAABA5wQ8AAAAAJ0T8AAAAAB0TsADAAAA0DkBDwAAAEDnBDwAAAAAnRPwAAAAAHROwAMAAADQOQEPAAAAQOcEPAAAAACdE/AAAAAAdE7AAwAAANC5qYU+sao2JPlEkt1JdiX5+STfTnJxkhOTfDPJ61pru6vqCUk+nGRVkve11i4ft/GeJM9IcluSl7fWbqqq45NcmuSoJF9urZ2/0BoBAAAADgUHMoPn5iTPaa09NclvJvmVJK9Kck1r7dQk00lOH/temOSsJKcluaCqpqrqpCQnt9Y2JvlkkreNfd+e5KKx/eSxHwAAAAB3Y8EBT2vtptbatvHuTIZZPKcmuWJsuyLJqVW1Nsnq1tqNrbXtSa5L8rB99N043t6Y5Mrx9pVz2gEAAADYhwUv0ZpVVUckeU+GJVq/lWQ29NmaZP34s23OU2bb1yW5IUlaazuq6sjx8SNaazvm9H3ofOrYsmXLvOo9Zt36efXj3puZnpn3OMzXumOPW9TtcZeZ6elFH68kWXf8CYu+TZbm9ZUk6094wKJvk8FSjdmxD3jQom+TZGZmacbruAc+eNG3yWApxuz4BxmvpTK9RK+xEx5szJbCUo3XiT9ivJbKzMxMttywuGP2wIf8yKJuj7vMTM9ky/U3LPp2DyjgqaqpJJ9O8oHW2paq2prk6Azn4jkmya3jz9FznjbbPts34yyf28fH76iqta21O+f03a8NGzbMq+abbrllXv2496bWTM17HObr5q3b9t+JBZlas2bRxytJbv7Odxd9myzN6ytJbrnt9v13YkGWasxuvX3H/jtxr01NLc14bb3jzkXfJoOlGLPv7DBeS2XNEr3GbrvTmC2FpRqv7d8zXktlKd4T75j+3qJuj7vcm/3EzZs3z3u7C16iVVWrMpw756rW2n8am7+W5Mzx9hlJNo1Bza6qOnGcpfOIJNePfc+Y0/fq8famvdo3LbRGAAAAgEPBgczgeVaSf5HkIVX1kiR/neFEyxdX1aYMV9G6aux7bpLPZQiULmitzSS5tqq+UVVXJ9me5Oyx7weSXFZV52S4ita1B1AjAAAAwIq34ICntfbFJEfs46Gf3Uffa5I8eR/t5yc5f6+2m5I8e6F1AQAAABxqDuQy6QAAAAAsAwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6J+ABAAAA6JyABwAAAKBzAh4AAACAzgl4AAAAADon4AEAAADonIAXECeMAAAgAElEQVQHAAAAoHMCHgAAAIDOCXgAAAAAOifgAQAAAOicgAcAAACgcwIeAAAAgM4JeAAAAAA6NzXpAvalql6b5BVJppP8fGvt+gmXBAAAALBsLbsZPFW1Psmrkpya5Nwk75tsRQAAAADL26o9e/ZMuobvU1WnJ3laa+2Xx/vfaK095p6es3nz5uX1RwAAAAAsglNOOWXVfPotxyVa65Jsm3N/v3/IfP9YAAAAgJVo2S3RSrI1ydFz7u+eVCEAAAAAPViOM3iuSXJ+Va1O8pgk1024HgAAAIBlbdkFPK21W6vqkiSbMl5Fa8IlAQAAACxry+4kywAAAADcO8vxHDwAAAAA3AsCHgAAAIDOCXgAAAAAOifggQWoqlWTrgEAWPmqal1VPaqq7LcDcI98UMC9MLtz1VpzdnJYIr7E9KWqVgm9++C11a3nJPnXSX540oWwf1X1rKr6tfG219wyV1WrJ10DLCZvOhPmTaUfVbWqtbZ7vP2TVfXaSdfEPdv79eVL6PJXVatnX2csf1V1WGttT2ttT1UdNds26brYtzmfYT9XVY+ZdD3cszkHlS5LsibJk6pqarJVcXfmvPd9LclZVfVjrbXd9j2Wp9lxaa3tGu/fd7IVsT/7ei15ff0gl0mfkDEs8B+/M1VVSd6SZG2So5P8ZmvtzydbFftTVWcl+VJrbduka+EHjcHAUa21G8f7D0rya0k+2Fq7dqLFsV/jF853JHlMkpe01nZOuCTmGEO42WDngUkuTDKT5F2ttesnWhz7VVWPSnJ+kvskOT7J2a21GyZbFfekqu6T5KIk32utvXrS9XDPqupnkrwvyZ8kubq19vkJl8Re5oRxe8b7T03yQ621z060sGXKUbaDbHZGwZz/Qc+sqq9U1blVtXGy1THX3RyFfn2SG5K8PclXk7zYLKzlY+8Uv6qeVlVfSfLSJG8dP8RZRqrq/hleT8+qqvtW1U8n+XySK5N8c6LF8QP2fl8cX3P/LsnRrbUXJnHgYpmYM/tjd1WtHZuPzRAU/NLQpZ40O/OKydvHrNPVSV6Y5I9bay9Icm2S51bV4ZOojx80+zqrqtXjctX/M8Nn2H9N8lNVddrcfkzW3NdYVR1RVa9P8pokr8owbmdX1YmTqo8fNM7snp0pfN+qenOS85L8YlWdN+n6liNvNgdRVZ2c5GHj7bVV9fQkv5jkrUlWJXl5VVlfvUzMOeJ5elX95Ng8leQPWmv/lGRTkhOTnDGhEhmNO1WHzQlOZz/A1yd5XZI3JHlqktOr6kcnUyV7G8fsu0n+NMlDkjw0ye4kX09yY5Jfr6oXVNXxEyyT0V7LVE8aZxYcluRvk1xfVe9P8tGqevZs/8lVe2jba6zelOTyqnpphtfZf0zy/gyvt59PUhMrlCTfd/BvdqnI66vqKRn2DR+Q5Jix64UZvoyeMok6ucvcAHX8vWvcB3l4kn/TWvtYhpmovzy3H5PVWttVVUeN37d2ZPgMm05yQ2vt6iR/nuF8VywT45itqarfSPJbSR7XWjs9w8Hbf26//gcJeA6CqnpFVT0zwxvJW6vqI0k+mOFLzFlJHj/+PjrJyyZW6CFuH7M/Hl9VH0/y2iQfr6qHZ5i984rx6NnxGaa5P3WchcBBVlVTVXXkmOzvHoPTdyd5V1Wtba39QZIfS/KZJH+Q5Igkz51kzdxlHLNTkrwoyROTPCPJzUm+mOTkDLN4XprEuvgJqqpfr6pTx6Nn96+qizJ80XxHhvH5z0lahh2vP0nyc4mT0R9s49HoM5PvmyX8S0n+WZJXJ3lCkqe21j7TWnttki8lOSnJ/SZU8iGvqh5bVa/JcDAiVfVjVfXZDOHb45NclmF/8UVVdUyG98I7kpwoQJ2sOQHqxqr6TFW9Zpwp93cZxzPJVUkeWFWvm1Sdh7p97Nu/IcnVGT6vnpPk0xk+v04bu/zfQ7d60MGsk7vsY6bwIzPMiPt2kg8neU5VPbK1dnOGfY53HPwqlzcBz8Fxe4aQ4H8n+ckkP55h7fv2JD+V5NFJnpLk/03yuHGNPAdRVU3N/TIyBjYfSvJP47ToTyR5d5KPZEj6P5dhTP9Lkl1JZuxsHVzjzu5LkjxwvP+zSf5tklvHtgvHrg/LcLT6LzN8kflHYzUZ+1h+cL8kFyT5bJLfS/KoJOtaa5cnuSTDrKvjDnKZjKpqzXjzmxnOAZIM4/G91trPZNhB/tEMYfdXkpyZ5BcyvC9ykLXW7shwYtd3jz/PHB+6OsMyyB9K8onx6PXZSX4nydtaa1+dTMWHrqq63xjkvCDJFzLsJybJ/ZNsSfLeDDNBjmit/d3Y52MZPtfe0Fr7vAD14Jv9DKuqw6rqmKr6YJJnJvlPSV6cYWbVjUkeOwYJb8vw+fa3Eyr5kFU/eM6WtVX1hCTHtNYek+F98UNJdib5RpLHV9WjxvNbnd1a+4cJlX5Iq+8/Z9zDk6S19s0kP5Lkf7bWZt8f3zk+5YNJvlNVR0yi3uXKSZaXwN7TNsed5AszrJ3+0wzBwEdaa9dX1QuT/HSSn0jyZ0k+2lr7x4kUfoip4cSg61prN825/8Yk/yPDFRCeneRV4xeZVNWfJPl4a+1TVfWg1to/VNUbk/xMkrNaa9+byB9yiNnrzX9NknUZjmj+YpLXtNZqHMs/THJOhlD1+UmOTPLm1tr/mEzlh67a66Ty407WXyc5IcmlrbWnj+3vTbI6wxKSZ2Q4CnqBLzKTVVU/nmFM3pXkpiTnttbOGh/7tQw7yjdkeJ39h9mTZbP0xnMT7Jpz/w0ZvrS8qbX2iaq6IMNR6t9qrV1Ww9Ufb81wItFvTaToQ9g4+/fIDFfEOifDQaMHJ3lTko9nWJL11gzLss5J8hcZliNcXVXHuFDA5M3ug4z7GX+X5LzW2r+vqldkmDH8qQznufrXSf6qtfbRCZZLhsvWZ9g/PGsMAn4jw8GKH8twPs0PZ/j8+qLvYAfXGMTdL8kLW2uXjm3HZTj499gMM3T+MMPsxXfO2V+8LsnrWmtfmkDZy54ZPIuoqn5oXBaye3zz/+ExDZ5OcnGGo5vXJ/n/Mkwve1iSwzOcoPKDrbVf8cZyUH0hycYkqap/luEI9I9mmBb9jiSbk/xVVc1eAeE9GaZNJ8mtVfW7GWZfnS3cWXpVdXxVHbHXOvb7Zji/zstbax9KcntVndZam0lyRZJfzzD99rWttecKdyZjzhG0J1fVH2WYDXdhkm9lmFH1S2PXWzMsGVmb5GOttXeNy4KcyPwgmT3qOR6hXl9V/zHDQYmrkvxya+3PkqyvqpdW1UkZdsDWttb+e2vtg8Kdg2vOOVteWFXrMyxFvSjJ7PKCj2eY2n5sVf0/GZZrXS7cOfhquATzC5L8cIaDEk/L8OXy2AxBzlOT3Jbkr5L8cYbz7vxRhkujHybcOfiq6uTxdTV7/+wkX6vhxLzrM4Q4r0yS1tolGV5fT2mt/W2SXxDuHDzjkv37zbm/qoYL2Lwyw+ts2/iZ9ZAkx7XW/o8My7GenmRHa+2TvoMdfOP+4UySN1XVk8fm5yVZ3Vp7coal+r+a4cD7TVX1trHPmXPDnb2XdR3qzOBZJDVcru3fJ/nt1tqHxiPRp2VYL/h7rbUrq+pXMyzn+bcZpks/OcklrbXLJlX3oaaqKsNl9TaNXzT/RWttRw0nUX5+a+3dY3L86iR/n+Go9G8mOWNcUjd3W0e31r5zsP+GQ8345f7MJP8yyV+01v5NVb0jydYM4ehjMpxX599lCOje3VqbDe5e5HKXk7GPmQXPyjBD7hOttS9U1buSbM9wfqTZI9d3JHlPa+1v5jzv+2b/sDT2mhm3ejyp4QMyLON58Ri0XZphFuoXM5x75/QM4/kfJlb4IWb8srltzlg9LskHknwnyX/PcKTz6xkOUDwzw0nL12eYMbKjuSz6QVdV6zKM2Z4xQD0hw+fWE5I8qrX2knFmz0czvB+2DEt9npjk4tbaf5tQ6Ye0MSy4ZPy5IsN+4RMzLE19SZKp1tpbq+oLSf6wtXZRVT02yc2ttf81qboPReP74un5/9u787BN57qP429LTCQie0We8lHK8qAspYgiSzQhRpYolVTGEkp6ZGxlq6SQ9VGyDA1CStakEFL5UCiS7GvMIM8f39+Vq9vwTDHXed8zn9dxzGGu5b6Pc1zHdZ7n7/v7LnCF7VtUQ22upb5TK1Kb7PdTm+zXAFdS7RbOoCoqHu/iuONZqv6ZiwBbU43kJwIntoSJr1Fl/HNQ9yN79GXS5R5xMhLgeZFUvVueUnXwPp2qoz4e+Lvt70saR5VgbU7VeZ4A7ETVe45qNfMxIKo+LZsCOwM72P5ce34DKoiwXTthfIm6UFwgaSnb1/dOIv0LoZi6JG1GZQ9cRQXcVqcWMrdRpVmz29667aa9vAV/zqYu2EnbHDBJL2sZi73Hc/Jsf7EZqcy439g+UtVr7EhgD9vXSVrB9q86OfD4J0k7UhkGxwFPUIuaCbavlPQB6jNbrpWo5lw4IJJeYftRVUPe37c/S1OLlIepc+KZVJBnR2Aj6r7jbuCLrY9LdKCVxf2W+szeRmXsvM32ZyQdCPze9rGtZP+DwNhe6XgM3pBg96ZUmfc3gAepTdrPUxu4fwGOBf4G7Gt7rW6OePrVv7hvJftzUC0vVqKGahwOfIrKvp8POL3df7wReML27d0c+fRtyOe2EPAt4M9Umdxu1AbuGlSG1SSqj+bWyRCeckln+g+11PWrgc9Jmsf2bdQN8UXAe1pw51hqp+ZBYAvgPmqn7YFWxpXgzuBNAG6m0p8n9Z60fSY1An3Xln31XmpxQy+boHcyyoJmMCQtQqVpfsb2TsDXqc9tMdt72v40sKSktwI/BhZpf/9ggjuDJ2ke4GRJi7XHm1Lnw9WphecD1NSeeSS9qaVCnwG8GaAX3Ek51uC0HhK9vy+gmhq4EHWOPIgqgbyfaty7DXXT/G3gCfWN4Y6pp5UdjAP2kzQrcCN10zue6ltwJVXKM4HKMpiB6jVxPLWJMSbBncEbch7rfWanUz3GfgU82TK/TwDeJWkJ19THYxLc6VZfcGdb6js2J3Udewx4P9Vf551UNshoqs9OgjsDJOnlGjIchWpQ/mmqzPsAYHkqa9hUi4V7qMA3tm9OcGfweufFtlk+qj1eDrjb9meAj7Y/V1LnyY9R9yLH2b6zv4S8k3/ACJIMnhdB0ilUD5aTqBKDcVQTyoOpG+RHbB8oaV9gQaox5f1dHe/05vnS9lRjmS8AbqB21P5I3SzPTkX8NwAOtv23AR5uDKEaK7qE7c/2lYzMTTV7Pdj2+e0GbBvbK0latAVaY4CG7MTsDsxpezdVw8mzqO/UDdSkg29RPZP+bvvg5/udMfVImp3qGXGC7UckzU9tPsxENZz8GzWdYgx1TRtP9dnZmCo3vqSL454eqfr0HUPd7B5o+x5Vv7hDgWts79Xe93Hqc7uH+n6dA5ycANzgDb3vUPXdmZ9q4nqD7T1boG4tKmiwM7AHcKXt87o45uldWyw+03cdW5DKgluklc8tR2WBHEK1VliemnD2I6pENb2RBqQFBL4IzGD7y22TYmcqQ+58quzxfdSG+8uo3i0bUA2Vn+7PMI7uSBpNVbecRWWZ7gVs2lpmXEy1Y9illbc+lGvZvy8RsBfnS9RJRVQEcjkq/fZgKs1sDUlXUvW4Wye4MzgtxbZ3sZ67/zXbV1OLzeupG+VXUOm361M3WZ+3/bdEiDv3O6pp8hwtuDNL+w6dSZUeYPtoKqOABHcGr38HrS1ajgPeKGnFlkGwAXVT/HFqytm8VLbVWUN+T8bWD85c1LjRrSR9nvosTgAWbb0+9qPG+o6mgjzz2J5ge/MEdwbulVR53C4tuLOoq1H8lsDKLcsR6l5ubap5+T62v5cb4m70nQ+XkvQTaqLZYtQ1a0VJr3MNZbiJKq1bjfrMEtzpSMuof0bSEpKWpBq+TgTuba9fTZWPrE5tDp4KfMHVVD7BnQGR9GFqs2hO4LDWZ6e3ObsKNSnwUipgsA7VQ3NXamLWjNTnGgM0dB0l6TWSLqc+rzmpgOnLqH5Je7Rg6t+oDMeZaMGdZHb/+5LB8yK0RcknqN3NfahMnsOoE84R1OSKM5xGvJ1o/T8+TNXjHm372r4+OotQn9HOtn8naT7bd/f9bHpLdKzVSG8JXGz7gr7nP0n1KRhn+6KODm+61S7YS9m+tj2elbqBupOqd98QWNv2FpJOpoKns1I7NLvb/nk3Rz796gXQ+haf76TSoB+1vYOkHaidz22o69bRVAnC1dTggOx6DkALmD7V93gtKsh2B5Vd9UaqH9nh1GbS26msnVuBU3Kv0Q31NZRvC5EtqMk8p1CLyg2p4NuHqPKRB6nF5/iUY3Wj/7umanB9GDWk4WaqkfwkYAngctuXtGy6z1FDAO6e/G+NqUE11vx7VIncf1HBtZ+qhqM8SgXjxgHrUkG4x6m12cm2r+zmqGPIebHXr3Y5aqDNl3otFahg9wVU7503AAe4pnXGi5AAz4skaQHqZusLVLPDx1ud4GzpsTM4QwMykt5D7ZydDSwOXEqVF0zqe892wP22T9Wz3dgT2Bkm2qK0d6N8GrWI2YtqsryPM6WiE6pGu++gSkduo6YH/hw43PYT7WbsEGoazKzURfta6qbs0cn+0hgI1YjYXanPa16qBHJMe+1qqj/BYtTu2njXqN8YANV42NWBI2zf1/f8stRCcw7gRCrTdH3bYyRtTg1rOLqLY47nlKgua/vXknamMrt3pxagWwDz2/5K6032CttHdXfU06/J3CvOTjW93sz2/pK+QZXUfZXavF2QGtrw4POV/cfUpzaEQdIKVLD0w7Yfbte0/YGx1IbuWrZXlvT69B4bPFWj61l793qtRHV/4Bmq5+JD1Pfp3e31r1L3iV8bek+f9diLkwDPS6DdZG1se/2uj2V6M5md6V6U+KNUD6RTVeOZVwfO6S8xyMV6ZJC0HrXgXIYamZiRzB1STQzckPp+Hd3SbQ+kMj7+SgV9/krtqK0JzGb74fazuWAPiJ47pn4lKlD6SdsT2o3xp4GzbZ8t6XRg11YCFAPSt7kwK3AUNZXnkv7Pbsj7t6TK5g7ONawbkgSsbvuI9nhdqm/Vb4FfU5lva1MbSxdQjeQ/S5WQ/LaTg46hwbh3UyXFR1PDAL5JNcO+gwogPAmsQE0UPCcbtsOHahjATa6pqe+gPq+jqM/rdtuHdnqA06kWLP0EtTl0q6Tlqf5il1KbfIdSgxqOpErtHgfeRZWqntTL1M994ktj5v//LTEFxgOThjZqi6mv72K9GNU1/zpJx1O7nctQtdIXUKU+75B0fa9muu9nc5M8jNk+Czhr6II1umH7Nkm/o75Pi1O700tTJapLAwtTOzWfaSnwD7dAbKYuTWXt//Mo24+3vlUzUee+CbavkHQ9VYYAcDu1GP2aakLWLxLcGby+78SCVC+CTalAQX/J8NzAm4CdqF4SX2o/m+vWgLXv1CuBZSUtb/sqatGyFnXuO5s6J95KbUz8ieont3t/ZlYMjqRVqIDAPaqm8r3WChcAd9q+TNJjVIDnQCr7+ylgj2SdDh9994AHAEdKGt8+uyuBVanyubu6Pcrpk6QTqfu+Q4H5Jb2OyhJ+HXCq7TsknUlNM9uS2iRcmRrecBC1ZgMyqfilkgyeGHH6o7ttQbMxlZp5MnWS2IBqcn05VVe9FFXXeS9wiO2bujjuiJFkcoHPvgy5uanv3MuBb9t+TNL21IV7H9sTOjjk6ZqkMcBm1OjenalxvmOpheZfgJ9SzQuPA97eskYWp3qC/KSXZRVT32Syq95HZbwdQH12R1A7mk+212enevE8avt7HRxy9JG0MPBJ4CnXJJ8rqO/ZrFQp+PmtfH9r4Ae2b+nwcKdL7d5wXSqIvSywCZU1MDt1vrtYNfXxBttntd4g7wbeC5xu+8hujjxeSF/G497A62xvlYyPbqgmXC1ITSM+z/b72vNHUVmME6jm8jPYPqC99idgtO2rJM1FBXxETZm+oYN/xjQrU4JixOkL7ry6LUAXAOay/YO+XgTrUr0K5qYCO2OoaHKahUZMgb4Mtw9I+lh77qn23/upC/goYM3WgPItwLoJ7gyWpLlamdyGwA7AfFSmx11UwO0AYMX295uBXwFfbz9+s+3xCe4MVl/jyVHtqeWA79o+lSr12YDa+ey9/zHbRya4M3iS3qVq7N97vA0VJJ0dWFLSitTk1FVtjwZeLukyqs/OfgnudGYU8Efbd1BBnhWAlWzv2YI7s1ITBc+RtC0wo+2DqGtYgjvDV2/TaRzV5y8ZHx1o165NqWmbS1EbSz3fooKq8wIXAgu3vqhQPZKuagHYRYHrbb8vwZ2XXgI8Meypxo2u0Pd4tdYv4ghJvTr3KyRt0t6yN7WAedD24cAPqVKth4EHlZHMEc8haRZJY3rfNUlLSvos1Xj3Q5K2azfFPddSwdO5gVttf9L23RoyFjOmuoepiTw/bovJ46iMxd9SgYNDgeOpCSTbU02Wz4GU+AyKhox4lfTeVlawp6StqM9jfQDbPwZeC2zcGlRGt64AjusLxr2FylLcETiTymQ8DThc0reo8+VHbP9hsr8tBsL248CfWvBmbSrjalLf9WkmqjfjhVS2493t57IJOIy5puDOYHui7XO7Pp7ple0ngGuoPjrj6Isn2P41FfBZE7gfuA54VXv5xvaeZ2xf6wwImGrSgydGgrcCW1GZAjMCn6KadE2iajjvAn5GLUIvtv1LSevZnqQaf7k4cIztH3Zz+BEjwtPUQvOR9nhXYG7b67VSnl2BX1AXa2xPlPT9/uyPpEoPXktX3x/YT9LrqUDBdcAXqdH1J1LBnRmoBpSPArkxHhDVFKzHgJtUE0bmpEp3PkTd9F5E7YA+oJrgMxv1+Z3dFqnRoXYfsTaVFbcG8Gpq0QIVRN0E2ML2fpJemWy4bgxpoDwjNX75XuAB4F22j5K0EbCNpFOp7IO7gINsX9TRYcd/IBsTg6carrE8cK7tx9rTV1Nj698CzCJpL8DUhvrp1CS6HwP/a3si5LMbpPTgiWFJ0mjbp/cu2pKOpEb7nkX1/NiovW9bKlD5I6qx4Y9sX9PZgUeMIEMDMm0B+nnqxvhs6uK8ku2HWr+COYCv2n5gyO9Jo/KOSfofqgfPW13j6r9JNXhdguoNMtb23S/0O+Kl0zJKf0t9Z7YEJlK7nAdTfXb+Tn02x9s+TdJs1I7nPLaP6eaop2+SRA3KuKnXb6zvtcuBz1EbRqtQWXFrUD0oxtu+sItjnp61QM58tu9qf38G2Nr2MZIOB74PXAV8geq/cxFVsroQ1Y8xge6IKSDpzdS0sn1bhk7v+ddS17enqODOFlRW9/eBC/t7nuY+cbCSSh/DTmsoubWkjfpOBn8CNmpTKF4uabP2/ILA/Lb/DOyX4E7ElOvrZ7WqpMOoKT4/ozIK/k5dpMe1t59AjT9/zrjYXLSHhW8BvwQWaM0PF6eaKm9ve/MEdwbuytZX4EZq51PUyNhHqf4gsr0e8EhrSvkq2z9McKdTswB7SfoosF4rW+2V1+1LlWadBJwH7EhN09o5wZ3Bk7Q5lXH67vbUM1Qmwd6S1qeyCz7RSknOA9ajhgJ8FvhggjsRU87274D7gHUk9U+8up0Kns4GXGt7Q2CM7W97yECb3CcOVjJ4YliStAZVlnU48GmqvOBJajfmXKpcZFGqnGT33okkEeKIFzZkCt3cVGDgHqqx66HU5LlPUIvQw6j+LmvavrGbI44p1RY93wSupNKiT+z4kKYrk8mI25VaeJ5L9QA5yPYtklYD3kY1opwB2Cvfr8Fr/fhm6DsfLkZlLj4NrGz7kSHvPxe41Pa+kka14EEMUPvMxlF9xva1fa1qguMbgG8Ah1CbFI9R/ZC2AR6kxthfZvuvnRx4xAgxmevYf1NrsSuoflU7Auf3nTcXpqZlXWf7PLUpkVmPdSsZPDFc/YxKaT+Dmi6yGdV7Z2Nq2sHHgR1tj+6PEudkEvFcrRcV8M+eLbNJWh5YFZhoewdq8tyGVI+JC4BlqPrq1Wzf2GtOniblw9ppwG7A+gnuDE7vO9G+WwtLemd76WLgHcAfgduAD0h6EzCLa2zsONubJLjTjdbo8x+SFmqLmPuAfYB/2Xnua8z7SWqRQ4I73Wj3eE8AJ7fgzhzAZdSGxOJUhuldwENUKd28th+xfWqCOxEv7Hn6KK4MnGh7LNVXZ31gnt6Ltv8CHGH7vPb46fbfrMc6lAyeGLYkvZVKi96412xS0qeBv9g+o+99M/VOKBHxXJK+A+xh+z5Ja1LZcecB11O7oVu2184EbrE9tk3TutaZKhIxWa0UBNsTWhC1t7s5C9XrYwIVcPsHlV3weZ69WT6+k4OezkkaDYyyfVIrv9qd6qXzALWxdAYV6J7X9p6SFrV9W2cHHP+iBdvGANtSU3w2As4HFgO+TGUwHm37MEljWkldREwhSXMB+1M95C6isuPG2P5Qe/164Ahq833SkJ9N1s4wkQBPDGuSxgJLtIydiPg3SDoO+Jnt4yW9DridWnT+3vaurbHrbsDs1LSlsVTpyHq2b+7osCOGPUmzAh+gRjBvB3wbmNP2aEkrU5OyDqTGyJ5ATWG6jgouPKePVQyGpLWosu8P2360Bb93oaabjabKvn8EHEv1lTgImJBFy/AhaWZquuobqbKrOyXdBLyHyjD4dcuQi4gX0O4Ln+xlt0maj7qWTaD6x/0AeDt1PjyZypDbBjjS9vhODjqmSMakx3B3MjBW0hz99fCJEkdMkZ8A87a/n0ctbA4CNpE0n+27JR0E7EUFenaiyhCWAxLgiegjaR6q18DhtidKupjqo7MulaHzvwC2fy7p/VQq+xFUoOeBlvqe4M4AtT5j5wEnAce1HhGrAtu36ZxLuEabPyzpESpI91dJuwBPt+aiMYy06Wa/bn+QtAgVPH0S2Lx/+gbFw5oAAAchSURBVFlEPJek5aihGYsBy0j6K7AwtRlxC3Andb94dptStyvVImNR4GOtuXIMYwnwxLBm+05qpOzQ5xPciWh6Ac/WZPcP1ASfZ6hd6Tnb23ahyrTWkLQBsLqkH7pGoO9K9WTbEliHyuaJiH81G3VDPJra2byXasq7HfBx4FJJu9veDziVyuIZ1etNEINn+35JdwBfBBaRdArwHeDr7b83SPpK+/tKwJ/bz/2mo0OOKdDK615DbUy8kWoqf1e3RxUxYryK6jX2e+BoqkR1J+AV1PfqK8Am1JTHHajv1569H+7rO5e12DCVEq0YEZ6n8VdE9JG0G7AQcLvtr0p6M5UFt0LLODiFKj+4iroxHtsbny3pw8ASwDds39fNvyBi+Go3te+lRi7v03Y2X0UFd/4EXEhlEiybxebwIWkJqp/fpVTj+FupEeePUlMEP0Z9rpfbHtfVcca/R9JrqelYJ9ie2PXxRAxnQ/uVtn5kz1DJHqtQ94QTqSzVN1PZpmtSPa2O7/u5rMdGgEzRihEhJ5OI59eb8mJ7f6oEazNJG1K7MuOB5dtbv8izU2J26gV3mtNsfznBnYjJa7uVvwDuoNLVsf0A1bdlVPs+jQUmZtrcsGIquDM38AVq93oVYAdgSduHAqMT3BlZbN9u+6gEdyKeX8t2++d0K0kLtJdmpnqRnQJMAj7Y1lq/BA6lshnXGjoQIOuxkSEZPBERI8zz7aD0dmgkvYcK6ryNCvLsb/sP7T1L276u/T29rCL+Ta1/wc5U3x1TDSjPsH1spwcWz6stag4H9rV9dctYXAfYOw3lI2Ja0zIXZ7D9+/Z4SWq64yzURoSpDcErqKzuHXm2cfn/9P2eZOyMQAnwRESMIJJWB15he0J7/NZev4j+C7Gkl1ELmq2BPVt2T0S8BFqG3AeB1wPfsZ2+VcOcpDHAZrbX6fpYIiKmFkmjgI8CS9veTtK+wHzAYcCKwFJUNvcC1BCAMcBMwGtsX933e7IJOEIlwBMRMQL0gjeStqMmY90MbAs8DfyUWmQ+3Feu9Y829WcN4Ke27+3q2COmRW1C08OZ2jMySJqN6p90KqTUICKmHa0seDXbF7bHr6cydU6geo/tbHv59r5DgZ8DPwQ+A/zC9iV9vytZOyNcAjwREcNcf3M8SXNRqbSLUNMPDGwP3GH76Bf4HdmJiYiIiJjGSBKwO3C87Z9JmhVYG1i7ZfGcRzVMPk3SOtSUrJ2Be3JvOO1Jk+WIiGFI0ihJC0E1x5M0l6QjqTHNPwGeBGa0fQ+VwbN8q7me3O9KcCciIiJi2vRH4Hzg/ZJmbs3HrwDul7Qm1WB+bwDb5wC7274794bTpgR4IiKGmdY/Z2Ng9vZ4WeDHwFW2r7F9KTUJ6w1tTPN1VMnWQpP7fbmAR0REREybWqnwJcBTwIfa0/cAtwGLtt46F0tasm36/aWbI41BSIlWRMQwIWl+YCbbd7bRlvO1P09TZVnHUCm3V1AN8Val+uucK+lltp/s6NAjIiIioiOtv877qADPLrYfaJnfv7J9VLdHF4OUAE9ERMdaFs5TwBuAHYDdgOWAVYD7gIuBuYGlgcvbe74CvBm4xvZtgz/qiIiIiBguJM1M9eJZGng18Bvgy7bva6+nZH86kABPRESH2iSeDYCzbN8j6UbglcBawDNUqdbPW5bOLMDHgM2AbWzf2NVxR0RERMTwI2kpYAbb17XHCexMRxLgiYjoQBtn/kzvgitpEeBNwBLAVraXac9vBcwPXNReWwr4ku3HOjjsiIiIiBghMvZ8+pMAT0REhyStAKxEjT3/ne3vSjoMeNj2nm0X5iPA2cAvbT/efu6fo9MjIiIiIiIS4ImIGICWobMtcIvtYyWNArYHVgM+BfwXsCbwPeAuahT61VTmzmW2b+37XUm1jYiIiIiIf5EAT0TEVCbpQOC/gXOofjvfAU4DDgbmtP2RNv1gLNVs+ZvAO4DX2D6pm6OOiIiIiIiRZMauDyAiYlomaTbg3cCptg8BxgGr254EfBf4u6S3t4ycy4BFAdm+uBfcacGfiIiIiIiI55UMnoiIqUzSe4AtgKOpAM9DVDbPJcAywNtsf66999W27+3qWCMiIiIiYmRKBk9ExNR3EfA08H1gb2Bz4J3AG4DrgYckLQyQ4E5ERERERPwnZu76ACIipnW2n5Z0CDCv7Z/AP8uu5rR9A3BDpwcYEREREREjXjJ4IiIGwPZvgAslXSZpPPAg8KPe6+mzExERERERL0Z68EREDIikBYHDgUNsX9qey8jziIiIiIh40RLgiYjoiKQZbf+j6+OIiIiIiIiRLyVaEREDJmlGgAR3IiIiIiLipZIMnoiIiIiIiIiIES4ZPBERERERERERI1wCPBERERERERERI1wCPBERERERERERI1wCPBERERERERERI1wCPBERERERERERI9z/AUz2w34Ir0eKAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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fnuS0+eeOVdutlJ+a5M+TpLvvqaoT58dP6O57VtV9+Fx3dRt3zG3cvJaO3nDDDWt6Qqecetqa6rF/lncsr3kfrNWppz/woLbHfZZ37Dj4++uMBx3U9pgcitcWAAAwrvUGPE/PFLI8MsmDkvxakpsyjeb5RJJTktw2/5y8aruV8ttXyufROHfNj99dVcd39717q7tHG2ty1llnraneLbfeutYm2Q9LW5bWvA/W6pO337HvSqzL0pYtB39/ferTB7U9JofitQUAABxZtm3btua6652idUyS27p7V5JPJzkx0yLLz54fvyDJ1jmo2VlVZ86jdB6VKQj68Fxnpe618+2te5RvzTStq6rqxKo6M8ny3C4AAAAAWf8Int9I8m1VtTXJ8ZkWWX5vkivnso8lef9c9xVJ3pMpFLq8u5eTXF9VH62qa5PcmeQ75rpvSPKuqro001W0rk+Sqro8yQcyX0VrnX0GAAAA2JDWFfB0987cF8qs9ty91L0uydftpfyyTJdXX112S5Jn7qXuVUmuWk9fAQAAADa69U7RAgAAAOAIIeABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABjc0oFsXFVfm+RHkxyX5Ookb0/yziQnJflgd18217swyauT7E7y8u6+rqqOSfLmJI9J8vEkF3f33VX1iCRvS7IlyTu6++fmNl6S5AVJdiR5UXffdCB9BwAAANgo1j2Cp6qOS3J5kn/Y3U/p7jckeVWSt3b3eUnOqaqzq2opyQ8neXqSi5JcMTdxQZLt3X1+kt9L8sK5/MeTXJrkyUkuqarTquq0JJckOT/JK5K8br39BgAAANhoDmQEzxOT3J3k3VW1OVPwcl6S18yPXzPf35mku/vOJHdW1eaqOj5TWHP1XPfqJD+U5N8meWR3b0uSqvpQkq9NsinJb3b3ziS/X1WPWmsnb7jhhjXVO+XU09baJPthecfymvfBWp16+gMPanvcZ3nHjoO/v8540EFtj8mheG0BAADjOpCA58wkj03yuCRfluTfJTmhu++ZH789ycOTnJrkjlXb3ZHktD3Kb5/LkinMyV7KV7exus4XddZZZ62p3i233rrWJtkPS1uW1rwP1uqTt9+x70qsy9KWLQd/f33q0we1PSaH4rUFAAAcWbZt27bmugeyyPLtSf5bd9/V3TckOTnJ3fPonCQ5Jcltc72TV223t/KVsiTZtY+6e9YBAAAAOKodSMBzXZKap1ydmeSeJFszra2T+d+tSW6c650411vu7nuTfDjJs/eomyQ3VtXj5mlfT8m0Ps91SZ46/67HzW0CAAAAkAOYotXdt1fVzyf50NzOK5J0kndV1aWZrqJ1fZJU1eVJPpD5KlpzE+9PcmFVbc18Fa25/NW57ypaV3b3bXMb78gUAu1I8qL19hsAAABgozmgy6R399szXRp9tWfupd5VSa7ao2xXkpfspe5NmUbu7Fn+liRvOZD+AgAAAGxEBzJFCwAAAIAjgIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGNzSojsAwJHjM/fcm+3LOxfdjQ3n2KXNOel+xy+6GwAAbGACHgA+Z/vyzrzgje9cdDc2nHe8/PmL7gIAABucKVoAAAAAgxPwAAAAAAxOwAMAAAAwOAEPAAAAwOAEPAAAAACDE/AAAAAADE7AAwAAADA4AQ8AAADA4AQ8AAAAAIMT8AAAAAAMTsADAAAAMDgBDwAAAMDgBDwAAAAAgxPwAAAAAAxOwAMAAAAwOAEPAAAAwOAEPAAAAACDE/AAAAAADE7AAwAAADA4AQ8AAADA4AQ8AAAAAIMT8AAAAAAMTsADAAAAMDgBDwAAAMDgBDwAAAAAgxPwAAAAAAxOwAMAAAAwOAEPAAAAwOAEPAAAAACDE/AAAAAADE7AAwAAADA4AQ8AAADA4JYW3QEAYH0+c+/27Ni5c9Hd2HC2bN6ck44/dtHdAADYLwIeABjUjp078+J3/JdFd2PDeesLnrHoLgAA7DdTtAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEtHcjGVXVekq1JzkiyKck7k5yU5IPdfdlc58Ikr06yO8nLu/u6qjomyZuTPCbJx5Nc3N13V9UjkrwtyZYk7+jun5vbeEmSFyTZkeRF3X3TgfQbAAAAYCM50BE8L0/y+/PtVyV5a3efl+Scqjq7qpaS/HCSpye5KMkVc90Lkmzv7vOT/F6SF87lP57k0iRPTnJJVZ1WVacluSTJ+UlekeR1B9hnAAAAgA1l3QFPVT0nybVJ7pqLzktyzXz7mvn+I5N0d9/Z3Tcn2VxVx2cKa66e614930+SR3b3tu5eTvKhJF+b5PFJfrO7d3b37yd51Hr7DAAAALARrWuK1jzF6qVJvjnJN87FJ3T3PfPt25M8PMmpSe5YtekdSU7bo/z2uSyZpnllL+Wr21hdZ59uuOGGNdU75dTT9l2J/ba8Y3nN+2CtTj39gQe1Pe6zvGPHwd9fZzzooLbH5FC8tpLktAc95KC3yaHbX6c/5GEHvU2S5eVDs78AAA6l9a7B87wkV3X3vVW1UnZ3VR3f3fcmOSXJbZlCmpNXbbe38pWyJNm1R92PZAp0HruqfHWdfTrrrLPWVO+WW2/dn2ZZo6UtS2veB2v1ydvv2Hcl1mVpy5aDv78+9emD2h6TQ/HaSpJbP3PXviux3w7V/rrtrnv2XYn9trR0aPYXAMD+2rZt25rrrneK1mOTXFRVv57kK5P8h0yLLV8wP37BfP/GJFVVJ1bVmUmW5wDow0mevUfdJLmxqh5XVZuTPCXT+jzXJXlqVW2uqsfNbQIAAAAwW9cInu5+1crtqvpQkm/JNNLmXVV1aaaraF0/P355kg9kvorWvNn7k1xYVVszX0VrLn917ruK1pXdfdvcxjsyhUA7krxoPX0GAAAA2KgO6DLpSdLdT11195l7efyqJFftUbYryUv2UvemTCN39ix/S5K3HGhfAQAAADaiA71MOgAAAAALJuABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGNzSojsAAHA0uPOz27Nj565Fd2PD2bL5mNz/uGMX3Q0AWDgBDwDAYbBj5658z69eu+hubDj/5pvPW3QXAOCIYIoWAAAAwOAEPAAAAACDE/AAAAAADE7AAwAAADA4AQ8AAADA4NZ9Fa2qOivJzyfZlWRnkhcl+USSK5OcmeRjSV7a3buq6vFJ3phkU5LXdfdVcxuvTfK0JJ9J8vzuvqWqzkjyziQnJflgd182170wyauT7E7y8u6+br19BwAAANhIDmQEzyeTfEN3PznJ65P8QJJLklzX3ecn2ZHkWXPdK5JclOTpSS6vqqWqOjvJOd19XpK3JXnlXPdVSd46l59TVWdX1VKSH563v2huDwAAAIAcQMDT3bd09x3z3eVMo3jOT3L1XHZ1kvOr6vgkm7v75u6+M8mNSR6xl7rnzbfPS3LNfPua+f4jp1/Zd3b3zUk2z+0CAAAAHPXWPUVrRVWdkOS1maZovSnJSuhze5LT5p87Vm2yUn5qkj9Pku6+p6pOnB8/obvvWVX34XPd1W3cMbdx8776d8MNN6zpeZxy6mlrqsf+Wd6xvOZ9sFannv7Ag9oe91nesePg768zHnRQ22NyKF5bSXLagx5y0Nvk0O2v0x/ysIPeJsny8qHZXw986Jce9DY5dPsLAEZzQAHPPHXql5O8obtvqKrbk5ycaS2eU5LcNv+cvGqzlfKVuplH49w1P353VR3f3ffure4ebezTWWedtabncsutt66pHvtnacvSmvfBWn3y9jv2XYl1Wdqy5eDvr099+qC2x+RQvLaS5NbP3LXvSuy3Q7W/brvrnn1XYr8tLR2a/XX73fce9DY5dPsLAI4E27ZtW3PddU/RqqpNmdbOeX93/6e5+MNJnj3fviDJ1jmo2VlVZ86jdB6V5Ka57gWr6l473966R/nWTNO6qqpOrKozkyzP7QIAAAAc9Q5kBM8zkvzjJF9eVd+S5COZFlq+sqq2ZrqK1vvnuq9I8p5MgdLl3b2c5Pqq+mhVXZvkziTfMdd9Q5J3VdWlma6idX2SVNXlST6Q+SpaB9BvAAD4gu7avj3LO3ctuhsb0tLmY3LisccuuhsAG9K6A57u/vUkJ+zloefupe51Sb5uL+WXJblsj7JbkjxzL3WvSnLVevsLAABrsbxzVy779a2L7saG9Npnnr/oLgBsWAdymXQAAAAAjgACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHACHgAAAIDBCXgAAAAABifgAQAAABicgAcAAABgcAIeAAAAgMEJeAAAAAAGJ+ABAAAAGJyABwAAAGBwAh4AAACAwQl4AAAAAAYn4AEAAAAYnIAHAAAAYHBLi+4AAADAet2zfXuWd+1adDc2nKVjjsn9jj120d0A9oOABwAAGNbyrl254re2LrobG86lTzl/0V0A9pMpWgAAAACDE/AAAAAADE7AAwAAADA4AQ8AAADA4AQ8AAAAAIMT8AAAAAAMTsADAAAAMDgBDwAAAMDgBDwAAAAAg1tadAcAAAA4Oty7Y3uWd+1adDc2nKVjjsnxW45ddDdYMAEPAAAAh8Xyrl258vevXXQ3NpyLv+a8RXeBI4ApWgAAAACDE/AAAAAADM4ULQAAAODzfHZ5R3butmbSwbZ50zE5bmnLQW9XwAMAAAB8np27d+V9H/vtRXdjw/nGxzzpkLRrihYAAADA4AQ8AAAAAIMT8AAAAAAMTsADAAAAMLihFlmuqpckeUGSHUle1N03LbhLAAAAAAs3zAieqjotySVJzk/yiiSvW2yPAAAAAI4Mm3bv3r3oPqxJVT0ryVO6+/vn+x/t7q/6Ytts27aqel/YAAAgAElEQVRtjCcHAAAAsBfnnnvuprXUG2mK1qlJ7lh1f59PcK1/BAAAAICRDTNFK8ntSU5edX/XojoCAAAAcCQZaQTPdUkuq6rNSb4qyY0L7g8AAADAEWGYgKe7b6uqdyTZmvkqWgvuEgAAAMARYZhFlgEAAADYu5HW4AEAAABgLwQ8AAAAAIMT8AAAAAAMTsADAADAUauqfC9mQ/Af+QhUVZu8ycDB53U1pqratOg+sDZVtXnRfWDtvLYAJt29a+W290ZG5ipaR7CqeniSr0vy3u6+a9H94fNV1TErHwhVdWySxyX5aHffs9ie8cVU1VOTPDTJL3f3zgV3hzWqqi/v7r9adD/44qpqS5K/193/Y9F9Yd+q6suSbO/uTyy6L6xNVX1pd//1ovvB53NcOJaq2tTdu1fd/6kk7+rujyywW3wBq19f8/2vTfJn3X3rArt1xHE2+wixemTBPILnnyd5d5LbhTtHnpX9tfpNJsl5SV7lQ/zIVVVbquonkrwiyV8Jd45cK2fPquqY+T3xaUm+1SisI8ueI3aq6vlJtiZ5jH115PkC++QVSb5zftxZ6yPMyj5b9Z54VpKXVdXJC+0Yf4vjwrGsvJ5Wwp2qesD80CeTnL2ofrF3q/bX6nDn7yb5kSSfXVS/jlQOvo4Qq9L+b0hycZKvTfJ/Jbmlqp5aVY9cYPdYZU77V/bXV1fVFUnS3R9MsquqzlloB0mSVNWFVXXJfHtzVT0rye4kj01yeZLNVfXcqnrUArvJHubRH+nu3VX1wCSnzQdgD0lyUnfv8iV08arq7CRZCUmr6uT5c+pbMn12/VaSE4U8R4Y9D46r6h9U1Uvmh9+e5IFVdezqM9ks1kp4Or/nbU7yd+eH7p/kS7v7UwvrHH+L48KxrB61U1XPnk+q/z/zw5/NFPKY1n+E2GN/fWlVXVFVD+7uv0hyY5JnL7aHRx7/cRdkz3V2qupLqupnkzwryX9I8okk/zzJP870of5jC+koSe770pl87ovng6vqTUmekORhVfXKqnp6kv+SxIirI8Onklw0Hxg/LcnTuns5yb9LclGSc5P8nSRPX1gP+Zyq+qYk6e4dq4ovSnJFVT0jyX9M8tVV9UBfQo8IP19VL06Sqnpukn+Z5P9PclKS70ryM0leleSfLayHpKqWkr91lvrvV9Vbk5yZ5Pnz59Yjpiq93ReaxVs1EmQlPP36JFdmei/8x93935PsrqonLq6XOC4cS1WdVFUPSz63v86qqlck+dYk/znJ362q70hyXJLnzPV2fcEGOaRWfxbN++v4qrosyfOSHJ/k++Zjw+uSfHzexsm/mQ/yBVhJIuezMg+c/xM/INOaIDd2991JfqC7/1WmoWdfleR3HXgtRlWdmOTb59ubquoJmYa0n9rdb0nygiR/kOR7MoVyXzbXtb8Ooz1D0+7+rSR/lOQHkjwqya/N5b/a3a9O8otJzk9yvwV0l1Wq6vgk31ZV31ZVT66qX6uqH0nyjiSvzzSq8eWZPsiN4FmQeSTcypSslyd50bwvHpXkP84jCr4pyS8k+bZMB8p/s5DOknlE1bfNt8+oqm9NcmmS3+7ud2U6Y/2lmQK5f1JVJ/pCszjzF5jHZP5Mqqr7VdUvJHlupv32qiTnVtVPJ/mTJHcurLNHOceFQ3poku+pqgdV1eOSXJbkiUm+q7v/Z6bX10lJvjLJA6rqhMV19eg2v06eW1VnzPcfl+RlSZ7U3a/v7pcleV+Sb07ygzGl7vN4o1mAVWfSfjDJr2Y6UH5skrckeWRVnd7dO6vqKZnW4fl4d1/hwOvwqnntj3kNpEdV1QeS/HKShyf5n0nuqqoHdPc93f2BJD+V5E+TPDWR/B9uq0LT02paryWZRut8daaQ535V9egkmQ+i/2OSX+zun1xMj1k1BeHeTK+fi+efS5OcnuT7u/v6TAdiX57ku5OcMZ/NEfIcRvN74c75s+m47v7dTF8y35zklCQfSZJ5ocNzM521PjnJhxbU5aPWqtfVjZm+0PxypuOMJPn0/JPu/p3u/oUk18xlZy2gu9znuEwX1nheVb05SSU5Ick93X1Ld3eS1yS5J9OXnXMSZ60PJ8eFY9kjUPuzJH8/yfWZPrNeO/97cpJ0983d/bOZPrsePZ9s5zBaOVE7v042J7mqqn4lyZMyjdK5paoekSTd/eFMJwC3JvnaqjrB6O77CHgOg/k/7KY9ys7PlBT/35nWlnh2kluS/HWSF87VfjfJt3T36+dt7K/DpKqWunvX/EXyjExfUs5K8ivd/YtJrs30Yf7UlW26+0OZArm/mNuwvw6xPf/GVfW9mUbqvKyqXpbkjiS/nml49EMyDel8d5LtSZ7c3b90mLtM/tYX0J3zsOnTu/t3Mh14ndDdf5rpi8xTq6rmL6qXJvm5JE+et/VBfhjN74VfU1XvS/Kv5jPWL880Cu7ZSf5NVf1UVb0o06idH+zu7+zuTy+w20eVlWONVVN7Hpjps+up3f0D8/vdx5I8uKq+dNWmP5nkf2Wa1sphtGpEXOYRcKdk2h+75qv4vC5TkPB35jo7Mk2HfE2mE4PeCw8Tx4XjqM9fc+zxma5m9tuZRlZt7e4bMn3Peske21yZ5G9qWsCXw2R+fX3uRG2SP05yYpKbuvunMwU5f5hp4fIkSXf/eZK3JfnT7r7b6+s+/hCH2KrpWLur6rE12ZTpg/neTB/kX5Lpw/pjSf57kk1Vdb8kO7r79lVnDCT/h8h8YHxyVX1LknT3clU9tKa1Cn4g0xvLj2VayyXd/YeZDoifuMeB8pMzTalzpuYQq8+/VOKDk3y2u78uyX9K8k8zfRC8L8m2JJ/o7hcleXF33+Sg+PCrqm+fP8RXvoC+NNPZsu+ew7k3ZRoa/Zh5JMhfZ3p/TE9XITkhyU2L6f3RpT7/6liPy/Rl86cyTX38F5kOvl6f5A+7+6VJ3pnkU939se6+7jB3+ahVVV9ZVY9fdazxtKr6pUwnkF6ZaYr3JXP1qzOt6/eEVdNaT8n0RfXvLeQJHIXmkaarw7iLalpf4spMI09/c54y99EkH8wU6iT5XMjzgCR/dfh7fvRwXDiemq6U+txMI+FSVQ+bRzC+MslfdvcPJvmNJD86b/KzSS6Yjzl2z/v8H2Y6CXjbAp7CUWPl86emdY9WXl/HVtXrk7wx0wmH752q1gnd/TdJOsmja7o0+opzkzypqrZ4fd1n0+7dvuMcalV1/0z/SZ+T5M8zDRN8V5L/L8n3J3lPpg+L25O8s7vvWFBXj2o1rQNyfnf/xhzC/VyS67v7Tavq/FqSt2YaSn1Cko929x+sevwp89ovHAZV9VWZ1pj4k0xTrnYm+aFMw6U/mWmI588kOTXTF88/WVBXSVJV/yHT5elfOZ8de3WmdUC+McmLMp1JuyjJJZmuwnRskpd292dqutrZ85P8THd/YiFP4ChU0+LX/zVTePrZ+f73ZVpQ+SPdfXlVXZfked39Z4vs69Fqfh+8p7v/dJ5++pOZ3gc/2tPCyWcn+aUkF2ZaX+LMJB/o7pvm7U9Nck5PV/zhEKuqpyY5I9Ox3+ZM0/NPTPJj3f3HNV1x6VsyTf25LcmmTO+NP97dn57Pbr8syX/pacFlDhHHhWOZA+uTM4UDWzIdHz65uy+eZ07cmOm44k1J7s70GvyLOZxbaeO47nbZ7cOkqr65u391vv39SR6c6bhw9zzK+2cyjYD7WKa1rP44ye939/Z5m69L8sfd/ZmFPIEjlIDnINvLqILjMh0MP6u7nzSX/bdMq4B/U5KlJN+Q6QD6x1adzfncJeE4dFYNyVxZF+lBSX60u/9pVf37TNN9npNpfYI/yjTa4OWZPhh+dOUNZc/9zsE1f2jvXv2amL/U/HSmMzHfkeSGJO/NFA68JlNg8IQkPzJP+WEBqmrzHlNGfiPTwnhnZLp6xf2SnJZpnZ2/yDSa4HuTXDWv88IC1HSFntdmGkX1p0n+MskHkvzrTGshPSvTl9B/kWmduHsX09Oj016ONZ6e5DFJ3p9pVNW/zxTo3JNp5NUzMk2le093v/Pw95iV98L5uGNTpv31N5lO9H0o07T9hyb5lUzHhU/KtA7Pxd39PxbS6aOQ48Kx7OW9cCnT59KmTBdquCLTjImbM1196W2Zjj+emORNq4IC37sOg728vo5N8pbuvqSqfiJTkPPETK+nYzKNvro803Hij3X3X83beX19EQKeQ6Sq/kGmtSSumtPFH8q0YOgfVtWlSU7u7h+ap2KdvHJG2hvM4bP6b11VX57kcd393qr675nS49/JdLbzY0m+JtPaSJckOX6eLsJhUNPCyN+e5M3d/b9WlV+c6cP6v2Ua1v6GTAdeP5lpYeXfTHK5MzGLsfrDdw66v6S7/7qq/kWm4er/LNPirr+d5F8leXGmKSI/3t3/e2/tcPDNoze+Psn7u/uulffFedj0TZmCnV/KtK8+kuSZma5Y8ReZDo4/tpieH732+Oz66ty3ds41mYarPyjJw7v7v87D3T88P3bcShDnWOPw2csX0Idl2kevzHSC4ksyfaH5aKapJZ/u7tfNI69uXPkM81546DkuHFdN68J9W6bpjI/ONOL3385r7aSqnpTpRNILVo8C9l54+Ozx+jo1ydd397vnKcW/291vqqqvyHRi4pZMI/MvSrLsJNL+EfAcoHk49IszDft7e6bhmVdkGiJ4b5Lfy7QuwbdmWg/k+zMNDbyyu9+7qp3PG6HAoTcPdX51pjUJVpLiM5K8sbufUFUPyLS467OSvHr1EHYHW4dHTWuB/HymtSOumtcfWPmwfn+my51/X5JHZNp3H05y4ryGCwtWVRdkGlH1Z0mu6+6frqqtmc6wnZJpPbJnZVo870e7+855Owddh8H8OrowyYe7++pV5VdmGl11QqZw9Zp5Wt39knxVW6B8oWpaNPSFSb4i01SdH61pDZeHdfd3VtW5SV6aaTrWi1adRPo/7Z13tF1V9YU/CIFAqFKlC8hEmvSOUkQERHpRulSlSyf03kNL6FEIvRelI738QieCTIqAKL0FQm+/P9a+5HB5iYi5576bt74xMnj3vnPO2OTknL322nPNlfNWmyiquJWJJM4KxMbfy4622pSFzSFEG/tjKud9pYJMWk/Ghd2fpkTBJISaezihVBxMqE83J7pv7k+oGOcDjrF9Y1fXSepD0t5EonQSYlP2YULFuErZCNwW2AQ4zfZZlfPy+fqWZILnO1CR1+5LuOVfAPyM+Mf5DPC+7bslHUfIODciuvkcStToXmj73PpH3rPp6sUgqR9hVngCUeP+Udk5+yNxL08hssdn5kulfhr3TNLywDrE5PyMwqj3M4XZ4T8Jafu8wNGO1qRJzTTeixXVzvjAgURgfBQhZ9+TKNEaRtyrRcqx0zXUWTmB10tRV61D1Lb/yfZL5ftlCP+qVYnd0L2I5+/qNg21x9K8wFf4+l1A3J/xiNKrPxEbSg8RgfGMwPi2L6p9wEl17mr892BC8XE2UX51O3ANoV48mZjDNiM6Ml3brnH3NDIu7CxGcr+WAba1vY6ihfY5hA3G2ISaZzDwotMjrnZGYq+wBlHevQMxV01CvAe3JPyu1pa0PbFWfr0Nwx4jyC5a3wGXNm7AosBg26cTnUUWJl7+QyVdQUg4ryGyyB8SSoOnG8kdZTu3WqksPJeWtHD5ehbg/LKouQmYuyLjnML2W7ZPLwFar66vnIwuuvg7/hLA9i1EkvQXCjf9z8rvjybu299sr5jJnfagEd0Cv5A0g6T5i1zdxDzzVkngXA/8yGE4+ZikWUvA9m+NaPGcAXOLaPwdV78r5R8PAV8QGxWN728jOoysRmxSbJnJnfbgER5WS0qaijDkncT2DeWevA6sXY47Fpjb9tWN5E7OXfVT3oXjABOWrz4CjrR9IbFjvQbwMeEdtxxhErppI7mT8WE9ZFzYGVR8Wxr3a0tJhxULjKeACcpG0TOEWngvRwvtU4jSn2fLeXm/asT2F6Xk+8flGetF+IpdZ/s1wjdzOmBNh3H5uyXGP8n26ypdpNv5/9CppILnO6ARRnlLE7uaq5bP1xDZ4nEIw7W9yp/3CIng9MB2wLW2b2rP6HsWTT4gExEdEMYj1ATXEy+WRWyvX+rdG+3qj22UiiT1U3wlnnV0T2p4gvyIkEUfR3i4/J7wALmsnWNNgjIJb0EktJ8kSns2IjrE3EZM5McAtn1sm4bZY2l6F04JfOpKx8ayqzYnUQ45FrG7dneqCepH3zShXIBItt1LlGRtQLSRbZQ8bke0Yh7g7NbTFpqVBZK2IUofHyZijdWAO21fJWly4r34oO0jJI1fEuKpYKyBjAs7h2ZlcPnuZGJDYhCxyXcBkfSeg0jo7ExYYqxn+5HaB93DaXq+ehEGycsC/0esh+8D9rO9hKS+xLvwDeL5+lflOlk+9z+QOwTfkmoGsbGbZvtOojzkUEkDiH+4LzjaIw4DTgf+bHvPskv6AuEAnsmdmig7LH0lLUKU8Nj2WsAnhAHbmUTG+BziJXMHMEPj/Mz2t57qTqWkOYs/y87A/pJmbrzgHUZ5JryuViUkuZncaQOSFpd0oaKTWaNrxcZEd6UVbW9K7FwvRzxjaxPJnWFEUNa4Ts5BNdHYbZZ0KBEQTwVfuwf3E0rTC4kOTC9mcqd+Kmq4LyX9sPhL/IToBrgzYUS+FuEpsbKk6whj5TcJbxdy17NeqspDSVNImhWYnyh97EuodZ4FlpR0OJGs+3scrpltf9isUEhaR8aFnUNFGTyFpKMkzUw8S5cQz9X7ROLgLEZsph9KlEIu0J5R92wq78KlgNkJT8yliCTpRkRjlDslnUJsWtwLTE4kWRvxJJnc+d/I4Po/0Ah+m/+hSepdfjyICKpetv0b241uFrvaXtn2deX4XrY/s/1GXWNPvmodezohCXwb2EDS3cCDwLrAhLa3AvYuL6AXiN2bPjAimZeMfqoBraTJy8S9JLCH7U2IHc+VJPWpLFZOBba3vYHtoW0ZeAIR7C4PbC3pp8Ru2h1ES+1lyzFHApvZvpsoXX3Q9m623668V3Mx0yJGssjfAZjW9s+AYdWFadk5e5DotrSui/FrUi8lsdNH0m8ID5CZiedrP0nXAtsSHhP/ILx3drG9GfBW5RpfZHBcH+WefU/SUUSCYFUiWbAtEXucZfsU4HjgNWIBemk55oXGNdox9p5IxoWdhaRfEk02hhCts0UouV+wvTrRYGMW23syoqHN+sAD7Rlxz0bSQpL6EybkLwFLSxoCTAssBkxkew9gb2L9fCtR4TIhgEdYMCT/A5ng+Q9UMpFbSDpd0nrl+09L0uYlwmdnunJcr/L7j5o+54TQQrrarVR0Qtie2IkeTKg/biKyyNcRGf8DS7Z4mKR9iNbN22cirnV0UX6wJrHbMj7hAbKnpKsI07VTifaIDRXPcNv3t2XgSZXriefnZmKXbHfbzxELzy0lzU6Y6D1cjr8KWK4oErIEoQYqte+LS1qlfP0gMLmidfaBwEGKTpAN7rB9jO23ax9wD2UkSpvlieD3aNuPAkMJD7KTCd+Wq4A1ynP0iaRLCaPK4+oZdVJF0gzAPsDMto8jDK/XBcaxvRKh3DkAeIVI8iwJDAD+nomd1pFxYWcxCkXvk0SccUfxbbmbuGe9izXGTymJUqIscnbg57Yfa/GQk67ZhuiQelQRPVxAeJCdSNiYnFnKVD8gDOfPAA4qc10ymkgPni7QCI+dsQnJ2PHAZ8Q/wqOITiPnS+pdEj29gSOAA2y/176R90zURQtRjehcsT6RIT7U9quK7iObEt0sLnFpC1wCgSnL5JG0gObETvluDeJ+XG77bIWR4VWEvL3RfekE29fUP+JkZEiag/AeO1rS7sCuRAeYN4HVgUWI+zigsRsjaXmHWXbSIirvvbGI0pATiM2HR4DPCeXAROXnyQjT0F3yvVc/I/GWqHoXnA3cY/s0RUe6BQjFznTEfPZUOW4yoHfew9ajpo4wGuEPNz6wIbE73c/2K5J2I3akFyOSCIc07pGkdQg/nlfa8j/SA8i4sLNoevd9de80omPq0cDEtreW1IdIIKwH3GX7wcp1vnHfk9HPSJ6vxr1aDNiKiN+fKs/cFkQp8aNVdbCkKTJx2hoywVNBIzGhlDQL0aViN2JnbWxgedsfNJI87Rt1Al+VzG0OPE445n9avu9FZI1vI/yQPmx+MeWEUC+l7v3nhHz2HqJ19rPARbaHS9qZSO4sQCRN72vbYJORIul2IolwNXEfZyFk0QcQu9d7235X0ri2P2nbQHsA6sKMUOHd8gvbF0naH1gBONv2GeUZW40w/D+qDUNOCpJ+QCQB/mr71cr3CxMqq41sv1m+m9DF5DWVcPVSfcYkzeqmlsuS5iJ2o5/3iO5lfYHpbbt8zlijRjIu7CyKquNoovz0fts3VDbSxyG6Pf6ulH1Xz/tGsjypB0m/JkpNr6nGeZIOJDb8znFp5jCyJF7SGjLBQ5fdD9YgWo3eBFxm+8ZSW/2io2PFHcBttvcb1XWS1iBpOqLtcsOYcE5CEv1nYnf6aaJ9/Qfl+JUJs8M9qjsxeb9aT/PCU+HXcgxhMrkZkeGfGJgJuMX2kHLcBI37l7SfriZmSRsDs1Xfg5IE/JtQ9PzT9qCur5iMDrood1wd2AQ41/ZlZWd6EPFO/BewDGFCOSvwcCkxTmpC0vT+epeQzYlugFcRXjvH2H6i8vtBwNO2D2+6Ts5dNdDFon8SIoE9P3HPXrF9QeX36xLqxdNsP135PhegLSbjws5C0rSEF0sj+TkhUbZ4PdH2/EZgzqKwasQcmxEKuj9VrpOdlmqglDaOY/u18nxNBlxMlA9/SHSgO9v2y+X42YlGAHs37nH5Pu9XTWSCp4Kk1YCliQXK+eXnecvPKxGSzneIFm9X2369TUPtsZQXy2qEIdefieTAD4DhhJP+LcCVwEmutLOUNG0uZupD0qLA25UygoZ0c6/y/amSlidk0TsCuxMqnnNd2sUm3YuGEqdSlrAVEWyd0bi/5bixgCny/dhammTsMxHy5yUI36MNiNa+bxA72DcQc9gXxOLz320ZdA9G0lSEP8QDxH14CdiJSLgtQfhXbU6oCsYqC5qJgS+crZlrp6g/NrV9Rvk8AdEV8MdESX5/okxkm0rSYCZgBtt3tWfUPZOMCzuPEiMuCvQCpmCE5+LFROLtXcLb74NMurWfoij9FeEDNwthWzJfif8uJ9Q6+5SEXCNGnMn2C6O4bNJCeqTJsqSxVDFfk/QDSf2IlnsTMqK13l3EP9qfE21j/w780fZZtl9XtvitDY0wq/4SeJ5QCFxFBMmzECa9g4j22icAM1fvse2X1LWZZTKaKTLbXwPzSfqZpHuAwxUttW8lJgkcfiyTE+bKZwKXZnKnPXT1Lmt6R24JXC5pysruy4vAuPD1rgeOtqaZ3GkxJQEwkaTtiPlpN+AB2+cRu6DLA1MTXXtOBP5me79M7tRHiTUaz9YwYEbgcmCv4juwKLEDugaxofQ0MEFFNfJeKVvNWKMmGvFhKeeZWNJ9ks4FVgTmIHwZLyVaMm9PLFABsP1CJnfqI+PCzkJfby//DLAl0XXuXsJw9xNC9bEHUZ66m6Spm5M7ec/qoel+PU2UoD4AfEqo4g6SdBOhjNsSmK5sBDaaomRyp430uKChZIK/LNnFxktiLaKrwb7ALoQb+8IOAzwTSZ9PS3B8T7lOym1roFKC8JXhGhFQ3UzU6L5huz/hkXQOsWtzC/DjZhlgygJbi0a0vn6TUAwsTniy7E14tGxNlIm8LGmApIuJ1r7DbT/j7NzTNirlV8uUspFq2c8cwPeAP1QTN7avsz2gHePtiTQv8svn64C5bC8NXER0oYMoTViU2BkdSMxnF9Y32qQSa3xRgt6PgfcJw+vzy2EHAxMQJeG/Ld/P0LhGJVDOWKMGiiruy0qs8DihCnnQ9hWEN8gKROLgGOL+bVjUPklNZFzYmVQ2JeYrceI+hOLq+XIfziYUV1sDVxBl3q92cZ28ZzVQeb76An0Idemjth+w/Veim9ntwNsl0bMqoexJugE9tkRL0h7AtMBfiH+0pxHlIbdIWptYnJ5OlI187qauCe0Zdc+hC++WDYkuFSYy++8AfySMea+VtDSxW70M0a0iu1PUQJGtL010BPmg1FFvSCwwdyKC450JM97NiV2a04BfEGU857Rj3Mk3SnzGJaS30xJdYB6tHFc1F/2GVDrfifUiaUXgI9u3l/fiNraXKoucK4CzbF8paQngSdtvtXXAPYzmZ0TSYcQC8zZHR6xliU2lnR3moWsBPwKwfUhbBt3DaXrHTUhs9N1OmLr+hGiRvWL5/W7Al0RHs/MbJVxJ68m4sLPo4n5tRqjebiO6k21UFKhfEq20JyWScssAN6eiu14qidPGu3Bpwj7hDaLl+d8lHQq84+igOjuhalyJKP1+pE1DT7pgjE/wqGJuV37+HmHk9TyxW3YWsXM2I1FffSghE/wl4a7f6FiRi5iaaAq2ZiAMDVckFFYnEy+bPYnAaw+idO4yV1owZ81u61GY5A0CziOepV8SSZ1bbR9USrJ+Q/hV3S1pceJZO8j2i+0adzKCsvO8FVHvvgBwCJHcHge4sVr/nu/A+qjUsFfNracBTiJ20h4FPrZ9sKRrCYn0BZI2AhaxvX37Rt9zaZq7RLTxhZi3HicWow8TxspzAc8RXi5vVM7L7iI10fx3rWjvO4BQFUwIPGt7YHnGLiESCV8Qz98XRZWV8WENZFzYuUiav/y4GlEq9wPiedqfUHv/nkgS3Gl7t8p5+S6siabn63uE/+y6xLO1CvBTYpN2cuB4Qo1/C5Hk/koAAamw6i6M0QmepuB4RqLjwSeKtufvEfLAxYFXba9a6qzPs31d+0bdc2l6wfQldtH6EsmDZ4AdiElgUqLzwXUKo9e3bV9SuU5O4i2kKAN+R9S7X0Ioch4DlmOW3MIAACAASURBVCXMDQcQ9+k2YoEzHuER8gowoUvLxKReulAWzE0kDC4kDCg3BSYhFjELAu/a3qcNQ+3RSOoDfN/2c+Vzo4PIjESJwTWSTiICsP2IXetrbM/YvlEnDSTNSrwb7yF8/D4hFqGLESVaPyXmsN0J37EhlXMzUdAGJC0CrEl4wQ0j4o6LgJeJZ2w4YQL7BnBwo2wkY43Wk3FhZ9G07pqSMEz+BbGR9DaxCbgwoZDbjlCAvwPI9tC2DLoH04XKahsitriQ8NtZm+h4OyVwiu0BklYBZq6W6Ofz1f0Yoz14yq5zb0k7ElniQyUtbfsfRBeEO4hsvxTtZXesJneURl61UPFu+WoHk5i0V7a9RykXWZBo0fcTwpDtV5L62D69OomX6+RLprVsDAwtQe4LhIpnUmAI0Jvw3JkJ2IZ4xr4gPKw+y+ROe6h6hhVZLcSiZWbCfPdV20fa3ptIzH2f2KVO6md1YnGJpE2BCyX9xPY/gSGSrid2z64iEq2PE2aUvZt9epLWoq+bUCJpLqKN9vu2B5ck3ZZEImc+4rlax+ERsns1uQO581kHjXvWiO8kHU8k5C63/QzwQ8K3ahfCWHRTYnNiK9vbueIJkrFG68i4sLOoqDeqf88/JwzkT6iUx80N9COUjP8gWqF/0kju5BxWDxphJl9N7vwG2BY4wPYdRHnjwraXJd6Jqyg6z/2lkdwZyX1PugFjlIKnix3qWYmds38CxxE7NNMBg4ls8oyEJ8hdwCWNes/cRWsPkpYjOh9cBMxDTAJ7235U0iZEoPUJMTGcYPvldo21J1ECq+kJpdtHktYh7s2bwNFEIHy87b9I6u3wldiW6Jb1q4aMPWkvijbNBwCzA9cCTxCKq5Vsb1aO+Q3hD3KR7YvbNNQeRwmSxvYIT6SrCQPyp4jnbCWiS9b4RALoZuI+vQWcbHtYO8adBJLWIJJuzxKxxRTE3PWJpIuIbnPjEKbYp1aSrbnr2QZKaeo0tl8snjqb2J67/O63hPE1hFH5YNs3Vs7Ne1YjGRd2FpJ+DyxEGJMPkHQyoda5uhyyA7AFof4+zPYH7RlpAiBpHsKe5HxCpbMfsR6+rJTWnUlYmgwD+ldVVrlW7t6MUQmeBpIWAJ6z/XZ5ufzb9uGlJn5VQg74F+JFM9j2E+W8/MdaE00yzl5EWc/0ROvlV4EHiRp42T6gHLcM8Im/3sks71cLUZgYbk4sNOck1DtbE51ELnQYrS1GtGFenFDyHEskTvs5O2O1ha4WIYpW5+MDp5Q/nxEJ8GMJQ8NzFG3QX6+ck89Yi2l6F05q+50SWF0G/LQsQg8kEgh/Jzo+rgnsW114Jq2ni02k6YmFypPAVIS5/KfArMDjtq+XNAWwMuEv0Si7y+eqJjTCz6rx3/WIXernCBPywyX9lUgOXCVpYWB5Qt24u+132zf6nkXGhZ2FKv585at1y59+hE/LYODfRJnWsaV6AknT2/5X9Rr1j77n0cX8tTNxb4YQ8eADxPp4eSL59rakRYFJMtboPDo6wSNpZmJn8wHb90uajsg+zkVk8+8hJoTdCQf95yWtT3SKGeA0yKudpgm8MSmMBxxpe0dFN58NiBrrewnztYuaXy45KbQeST8kShkPsD1U0t5ECdZtRMB1LPA7269IuoBIpO4qaSrbr7Vt4D2cJs+C5QgvnQck9SPu30JEK9L+wOdEwmAe2/3VhblvMvop774+FdXoOMBehI/VabYvUvjsfGB7D0mzEW2ZjyDaAKfxZM2MJGm6HLCE7UMkLUW0qb8OmI9QCB/rShezUn7wZcYb9dDFgmZCYqf6YGLT4iAiRnwcOLui4qnGKfkubDEZF3YW+qbPzse23y0xIrYPkzQHobpagPD6u4u4Zw2Vahry1kQX78FGnHcooSh9UdE9ejbCzuTXhEjilFFdJ+nedGyCR9KRxELlTkKVsyfwETCT7XMlHU4Yey1OtGkel+gQM15VEpj/YOuhixfM1sTC8h7CpHcIsLbtFyStC/zQ9qGSFiT8Xj5py8B7MJJ2IO7D9uXzOIQx+UvAOcSCdFzbe5Xyn4VsX9u2ASdfUYKr3xHS9r5E54pJCT+Qgwh/nYOI5+8825+1aag9DkkbEN3lniY2Hz4l3oH/AP5K3LdbiZbndwDr2n5a0vLAPc7WsbXSlDAdHzicMNu9mWjve7ztxcvvLyTKwd8Avmf7ga6uk7SWpnv2faIE4W7iWdueKGv8V0nKrWS7n6RTgeNsP1W5TsaHLSTjws6ii/u1GVEJcTexqf4w4b24i+33ysbfNsRmxqtdXTNpHc1zjqSViPK4e4h56nJgkKNxwzxE7LEdIZJ4yfabbRh2MproyASPpAmIAPg024MkrQXsZXuhouoZQLxw5iQ8CvYnnMAHVbPHGWy1nuYsvaTJgCOJZNwpwOnEbtqMxO7nFcROzd22j6xeJ+9XvUhalmhDeqjt98p3KwHb2V6lqAqOA7Z21r23DX2z1e84RAeEz22vV4LhHYiE3HqE786SwDm2z62cl89YC5E0KVEa/DKR2DmUKBE5sJTx9CbejdMRSdS9Cbn7ZM5uZrXTxWLmx8Q9eYxQwB1PdMY6E3iEuGcbAnvafqj+EScjWYCuArxLlPacTLwD7yF2qvcmvOWO7OJySYvIuLDzaEqaLkSoPCYg1leTE16M1xMNNpYg5rH/I5I9nzVfI2ktTSqrPkTMMQcRs29LlHvfQTx3xxPefh8QzYY+Kefl/epgOjLBAyDpZ0RXg3XL54sIb5ClCH+QfkQ2ckFgI9uftmusCZQFzKHAn4kM8aW2zyj1nQNtL1hqqVcFbrd99civltRBKdHaBLjV9i3lu4mI4Ou3tj+UNIHTJK9bUBYzb9q+WtKKhEJnedvDy07axbavkDQ58E4mu+ullOecTXixnF7u0TrA9uVZOoBo+3szEXQ9ZvvYtg04Ab7y9NuE8NlZl9IFS9L+RNLgMMITaUmiJOvxtg02Ab5agE5FxBtz235C0i6EUejThPp7NYqS0cV3LN+F9ZJxYWdRNvV2BEx0m/uM8IL7QOHx94Ht8yQtCQx3dDpL2kQpbexHWCosAGD795ImBu4jukj/gNjIfcv2wHaNNRn9dHKCpxcRBA8jgqzJie4VsxHZyMmJnbRbK+fk5F0DXSgK1iZKQ85zGLmuR3hN/N5h0HYBsFOzhDPl0e2l7LJtDCwDXEx0iDmEkEYf3Mah9WgkrUzclysJJWMfwszwQaJ7z83EjufBxA7bSYQJ9p6276vUX3/tOU1aj6KN9uGE58eqxALzbUJxtSQwP/A9Qm16YbvG2VNpPBOVZ+RYwmz3YMJ8cnPgedtnSfoJ4b9zRNM1Ms6oiS6UIDMTSbgFbK8v6XpgiO39JM1AqEPWsv2xpBlsv9i4Tt6z1pJxYWfRxf2aivBd/NT2b8sGYD8i1rgLGAScVU3CledzrLxfracL9eL8hM/i5YTKdH5gM2IT4u+SBgEn2n5kVNdJOpex2z2A70p58ZxNqHS+sL2F7S9K/fRmthdtJHdKMijNvGqiogyYt3z1MDA3IQeEkG32BS6R9BfCZf9rnXvKdfIl00Zsf2n7bOAqws/qVODqTO60B0mTSjqd8JC4migP2ZiQQm8K7Ap8nygTEbGYmY+QTu9u+z4Y8R7M5E79FHXHw0TJ8EK2NyDm4UmI5+svhDoukzttoCR3egEzlK9eJBQgjwAvEKVYa0o6hgieXT2/BMcZZ9RA4++6JOIasexaxK70UeXz1sDvFGbYmxHJ1AkAKsmdvGc1kHFhZ1G5XxuWTaWPiRKsSYpy+2niHm5MbLYPIeav6jW+zPtVD5VyrLnKV48A0wD/Kir7Z4hOnAMlDSZijmcb5+fzNebRsQqeBpJ2Baa2vVsXGefcoa6BLnbR5iSUHuMTL5SjCAn7jLa3LR4hSxOL0sG2b27HuJP/jnye2ksprToLONr23UVBsCbhK/ElYUrZn/CceAsYWH6e29GJJLtWdAMkTU3UwfcjVCGXEX5IZ7d1YD2QLnY91yYSqC8Q/kiHSbqJ8Pu7VNKMhBfI1MCBtt9uy8B7MM1qG0n7EJ1RhwDnESXEgwlD8o8kHUH4SxwMXOI05q2FjAs7i6rapvw8FaEsfZbYhPgbkdBZAHjb4X86BZHcuaqh3EkFSH00+exMQbzjfgw8RCTjPgb2sP2zcsy8hOn1Y7ZPbc+ok7roWAVPhfOBsSVN0rz4zMVo62naRRu/fL0m0cp3JeBGojzkKOAnkhZ2GK49TphVLtW4ThuGn/wX5PPUPsqi5k1CDr16CcDuJ0woXyfktzcCXxBlWk8SZr5XAzNJmqPxnLblfyD5ilJycB2xw3YR8KdM7tRPU3Dcu/gVbAjsQZhQTiFpc0IBdxCA7X8CDwDvAz8q547VxeWT0YyksZrVNopOj7MRie1tiHjiWkJxOmU5bC9CuTPU9ieSetc78p5HxoWdRSNpWpI7sxIt6qcA7rC9BVFWPBZhfTEUWF7SdLbfIBRYv5Q0TblOJndaTFVtU5l/fgL0tr0E0WjoYOA2YLikbcoxzxENiH5cEqrJGEzHvzxtv2R7F9vD2j2WnkglQN4HOFzStIR64LXysr+E6GDRl3jp/LCc9xrx8hlSvU6SJF8tZrpaOA4GJgL2Ay4FnirvvscIL7LNgX62zy0B26vAhrafrGvsybfiUmBP4Fe2B7d7MD2REhxPrWiPvS5hNmlC0v4ecAkwm+3HgNuKAgFid9TEPJeKuJqoLEB/KKmh+JgLuLaUi/QDDi4xxwzAHJJ6l/vzR6KTIM6GGy0n48LOoiTixpN0IDE3zUqo4pYqv3+aUPS8TyR0jrX97/K7s4Fzbb+S78J6qKjifgsMkvQjwvD6H5Imtv134E6iRP9IQnFKmdeGED6NHb/+T0ZNx5doNUhZYHsou2F7ET4gB9h+WdKvgdkJ47UJgN8C62ZglST/mWoJgqSJPKJF/dhlgbMk0d73MtuDKuf1bjxjWY6VJKNG0g+AE4hd6mOKgudYQhl3LdFWdpjtQ9s4zKSCpO2Jjmb9Hd161iQ6BW5bfn8+UUI3ne1/tXGoPZqMCzsPSSsQ5XG/tf1x+e5KwhvpXcI37gjbN1TOyXVXm5C0EVF6eoDtoYpuc8sS6u2/A0cA29h+vm2DTNrKGJPBy5dMeyiT8w+JMoOXy9dXEVnibQgDtmNtf9pYdKakPUm+STUpI2kcSUcDp0naRlLfxjvO9t1EPXwfSX0r5zWSO1/J49v0v5Ik3YZRzDe9gHdtHwNQvFnOBSYjSiH7Amd8i+sko5muSnNKqc9cRELnvPL1zUBvSYMlPUaUYX3ZSO5kzNF6urpXGRd2TxpljiP59SzAXxvJncI2RKwxF9Hd7IbqCbnuaj2jeC5mBW62PRTA9m3ALcBPgcOIZ+/5ynXGmPV+8u0YYxQ8SesYmbluefGMTXQy6227v6S+wM+Ba4CJbb9V72iTpLMoE+/XEjKStgYmJTor3Up0xDoH+KQkgOYGFgHOTm+kJOmaUe0wS1oAWA24zvZ9pQRrAtsPSJq+miTIZGk9VI1eq99VFI23E+qdK8vnaYFXgSWAV0opSVIDksYpvjlImgAY2/bwjAu7Pwqz+KmBhzyiW9Yvgd8QfmMfAgcCJ9l+sHJeKoNrYmRzV+N9qGgIMCehqvpE0mrAvcB7tj+se7xJ9yMTPMlIaQ5sJW1HdEC4wvYzle/nI+rbPyMWnX8ETqwEZSnjTJImFK1GP6h8XhRY0PZASX8izFxnIxQFuxRDwyRJ/gskTQLsDNxOmLwOL99PQCxolgY+AhYinrPbKufm3NUGJM1ElPgcYvtflfLUFYjSgy2JBMJHwN7VMlaakuXJ6EXSesCllcTALoRXy1G2760cl3FhN6D571nSH4gyxn62r29KoG4HzAQsClxp+7iRXSeph1KGuhgwqOqlKOmHRLnqzOXPEGBf2++X32fX2x5OJniSb1AC4qltP1U+T0EYTj4I/AOYm5ion2w6ZzHAWfOZJCOn7ILND6xq+8BiFno4sCCwn+27JG1ItPtdjjB1PQC4vVkineqCJBlBc1AraUViR/pawpz8aSJQ/qqckZjP5gUudrbQrp0uFqBrEwbkRxP35Mum4zckdq6H2T6y1sH2YCpJtrWAa4pqYB2iO9a2RKeycaslPhkXto+RKINFlKEuQvghAbxeVVRJ6kPcx3frHG/ytWdsbKAPEQN+BtxHlMldafuWyvG9iO5Z79h+uB1jTrovmeBJvkLSVMA8hKna7sA9RD3n8cAkwIvAaUS3kRtsH1LOaw7QchctSbqgqHQWBQbY/lzSrLaflXQWsA+x0JyAKMs6GHgTWBG4yvYR7Rp3knRnivH4x7YfKJ8ns/12Kbt6lWjvex6xQTHQ9u1dJUdz17NemtQD3y9mvBsR5SP3EMqQB2z/VV9va189L5UFNSPpKKL71c+J2HBKYFyi69yq5ZhmBXjGhW2gxBybAmfYfkjSsUTL8wmBZ4EPbJ9UOb5RApT3qw0Ur7EvbH8saR6HgfLBwC+IFuf72x7W1VyV78KkSiZ4kq+QtBhwFPEiOR34GdF2dICkyYgWzYOAT4gOCCdW5exJknRNZWdmKWAFwhz0HeDPtmeStBPhufM60Y50Yts7S5qNqKl+tVwnFTtJ0oSkzYHNgFWBE4HxgD8BNxGlV/sAhxKdYD4FDrf9TtM18tmqgZJ0m972jeXzYkQJ3bjAmYR/y3iE6eujwG6E2vHDpuukH0iL6WLzbktgKLA4MKftLSXNAkxm+0FJ1wF/cLRpTmqmuugvz8cBxPvvL4Qp7//Zvrj8vg/xjrzC9kVtGXDyNUoc+AuiC9bFtu+VdBqhPL0D2Am4xfZZbRxm0iGkq3YPR193Vv8/YuG5O3AMoSK4qfxuUuAxojPCmkRHhHtJkuQ/UgmSPyR2PJd1dD+4QdLuto8nTA0vJ+qpnyjB9TO2X5U0di5Ak6RrSsD7InAlodQZCKxFyNfnBf4MLAxMQahP3+niGvls1cPkhPqjwXbARURJ1nxEsuBSQi28MNGiecLmizg7BbaMSvKsoZgap/zqE+BHtvsDc0tawfY/gNkk3QrcDzzVjjH3ZCr3q5HcmbI8G5fbXoWIO5YDVpY0V1H13Ac8ksmd+lEX3cwkLUhUTGwJPA6sVDzHniPW6r8lnq+rax5u0qGkgqcHo693QWhI2mcCTiIMDJcCfmx7b0nzEzLc9Yn2lo+3beBJ0gF0sfu5J7E7cydR/34m8DBwI7AyscO2B1GOlTs0SdIFXZR+LAp8Dgwn/KomcbRf3r18dzuR7JkK2KNhQpm0D0lXEfdlAHCh7TXK978BpiUSPjsSbewPattAexhq6mJWPD72AZ4HLiXiv762Tyzmr3vZXljR9fH2qi9j0nqaVWySfkKUdr9DtDX/t6RdiU2jgcD2RMnqsUTHwFQG10xTeelswMREK/q1gVlsHyJpSkKtcz3wJZHcubChekySb0MmeHoYkr4PzNswa5U0PXAkkSG+0PZVkrYijCd3JnbVpiNeMr9vmLGlPDpJumZkddCSjiD8P/4paRNAwP7AvsA0wDZEcP35qK6TJD2RLhYzvYl5aUtgWtv7ShoIfGJ7J0kbE13pdkzPlvZQ8fNo/HcVYF2iFHVFwo/sdOAeR/fAHYAZbe8qqY/tj8p10huphUga3/aHlfs0PTEfDSLmqbkJ5dVgQt39y+IhN4hoDPCvcp2MC2ui6Z02N+GfORdwPrAa0Bc4Gfg1UfI4FfA+cK5tl/PSZ6cmutjwWxs4hFBSvUqstW4GVrD9uqQrgBOabTAyGZd8WzLB04OQNDEh75sWWJaQbR5CKAheA04l2u49R2T7zwOuAxazfU/lOhkgJ0kTXSgLViMWM38BLiDKr862faWkeYkJ/SLbgyRNa/ulcl4+X0lSoWkxMwWxaHnV9sWSBKxB7ILeRcxlgwnF6VG276pcJ5+tmhiJCeiFhLfE5ZKOJhJ0xxL+SNOUw/a2/Vg5PhMGLUbSrMQ9WK8Yu65G+B5dSiQJ3rd9vKQ/EbHhMsD6DfVHUi9NZuMTAr8BVgGGATPZ/qmkyYln6gKirG5NopPZmW0adlIoG+gLE13n9iqJ0iHE2msxopvqkkRZ8SEuXely7kr+W9KDpwcgaZoSbL1LJHPeBXYsapx+RKeevYl2fJuX/54H/MD2F43kTqNmNF8ySfJ1yuTbWID2LV0P1iZ20FYhnquDgZ0lrQ78nqizvgvA9kv5fCVJ1zRUIJK2A3YlOs0tJ2nmshv9NlH++BmwBdF56VfV5E65Tj5bNVEWLpNK2kDSj8rXTwEflJ+PBVYnFDtbEOVzv2wkd8o1Ul3QIhQtzLH9LPBPotU5wPcI9c79xP1plDTuRCR4XiFixsZ1ch1RAyOJD9YEDgI2sb0x8ImkpW2/Sdy/NYGhtndrJHfyftVDma/GqnyeRtIZhNLqz4SCcc3y66OAs2z/kZjf1rC9byO5Azl3Jf89+aCP4Ug6nZAA/rp89SSR2Z+jGOS9XX63LtGFZHFgDuBa2ydXr5UvmCTpGkeHrN6S9iE6+VxELDQXA6YHdgD+RRiKLkwEXX+w/VT1GvWPPEm6H5IWl3ShpB+Xz+MAGwFbA4faPpLwmVi5nDIWsTBdwPY5tk8p52WMUxPFr6X6eS3gr4TJdf+iFHkdmF/SPMASRJJ7boCGr1/zdZLRT1loPiJpi/LVacAyxfvjB4TyY2NCGXddMYB9rzxbv254N0LOW3VRUe38QtKJkuawfQ7wBJHchiip27ccfxbRBXd4Oe9rxtlJ6yj+pl+WjYmGQXxfwgvpIdtXAXsBq5djLwX+ruhI97Ht55sTREny35IlWmM4xYDycGAiwqjrl8Ru5xPAzrbXkHQv8CzRKWuA7esq52e9Z5I00UU99ayEGeVwYKeye70TMI3tPSWdT9S6bzCq6yRJApLWJQx4LyGSpXcCjQYAp9u+uvhOrAf8HDBwkO1nKtfIuasGJM0FfGD7ucp34xI71HcSXQPvI0zlzwd+DGwFPAP0s/167YPu4ZS48ASgD3Ai0YZ5FsLo/xjCC2QHYHkiebBXljrWj6RxbX9SFvq9iXs1KXAboQQ5pxx6nO0lyzn9ifLvl6v+V/WPvmdRNhOWsf3XyufDgDkJQ/n+RMJ0GcK36m1J5xAJn+PbM+pkTCYTPGM4ZTfst0Sd7olE2UgfYFOifORG4BqiPd+fcyJIkm+PpAWA58pkfTIhXz+6eBlsBaxE7Fo/BlzfWIBm0JUkI6f4xe0NDCESO+PZPkLSOoQC7iDbw4vR8py2H23jcHsskiYlOm72Av4IHEdsHl1l+xFJvyYWNYOJBPj+tq+X9H3bL5drpM9OzZTF51ZEp9RTiEYbJxD3ciMiRlySaLBxRN6beijPwljAFrZPL9+NC/Sx/a6k+W0/LGkPIrk9hCj3vgQYUpSNSc1IWo+4D3cRz9IXhFp7LMLP9B7gAOABYi3W8LWaCXi72Gdk4jQZrWSCpwdQOiIcT7x4fkyUYO0NLAD83JU2pF0ZIyZJT0fSzESy5gHb90uaDtiP6FrxMDGBPwjsDhxm+x+S+hBmlY/YvqZcJxM7SfIfkDQHsKrtoxXtznclSoiHA0sDrzUWQJVzMjiuiWqcUJLc6xGKgkFEcmBrYqf6NOBcQnWwBZEsSCVIN6DEhQOIbqlTE0qdPYELbG/adGzGhTUi6THCW+dV4AhCYb9j2Ug6lvDRvIqIN64HrgA+t/1BOT+fq5qQ9HNgR+APxQ+u8f2UxLtwf6IM9R1CFTcTMB9wYsVAOePCZLSTCZ4xkK5e7pI2BRayvZ2kKVMWnSTfDklHAgsR5QarEkHwR0THinMlHU4Ex4sTwfI4RHvLd5uuk5N4knxLJN1O+BZcTSRQf0Dsfv4eeMn2sDYOLwEkrUGoQO4nSlMXK99fSSR23iUUxG8Cu9t+f2TXSlrLKOLCxW1vXT7vAtxm+0E1tbhvw5B7DA3lTsVnZ0miq+1FhDJuD+B54EJCff8ZkSh4kWh73mhTn4mdmqg8H0sDGwB/ACYmYsGHbD8maTfgQdt/lfR/xEb71fkeTOogEzxjKI3a3crniYjOWINsX9l0bE4KSdIFkiYAbgVOc7QzX4vwI1ioqHoGAHcTddZvEbs1axPPWWOHOwPkJBkF+nrr317Fw2pjYDbb+1WOm9P2E+XnfK5qoroALeU9ExJlV48RiZz3iMT3A7bPkbQ9UYYwSNL4tj8s18lYo42MIi482/Zl7RtZz6Xp3TcN8KHtYZJOA8a2vaWkOQn1xyBgXCKhcJPty9s28AQASbMB2wNTAD8iyuaWJfxOdwSmAqYBzrd9auW8nL+SlpIdJjqQrjqD6Ovt+LYELi8SQQBsvwfsAvyl+dwMuJKka4rkuR+lS0UJgp8t3hNzE0ahJwKPEhP5cNtnVOXsOYknyagpiYNxy8fGfNSH2KFudNGikdwpP+dzVQNlAfpluUfTABMWdeJwwkTehFLnZmB3SQOJBegQANsflo4wmdxpIf9jXHh1V+ckraE8D4Kv3n1jS9qfiM/3krQKYaOwWPGregL4N1EmPsT27xrJnbxf7aX4Ku5CdCde2fY2hK/VukSJ/iBgg0ZyJz3HkrpIBU8HI2kZYFZHO8TGd3MAqwFXuNKCuem8zBwnybekGJUfCQwjdq4nJwwqZyMkt5MDe9q+tXJOPmNJUhhJechXz0hZfK4GbNYoH5a0EjCL7QG1D7iHUxYhszc8JUryYF/gV8BNRLnqveW/y9l+tXi6bEKYzp/fnpEnGRd2b4pR/E6EJ8u1tgdI+hnhLXY4kdiZm/Cs2gj4me1VJY0P9PKItueZMG0TTaqrrz03RW11AGE0f171HKKTaj5jSS1kgqdDaDI1HJfogDUt0Wb00cpx1aA5J4AkGQ1Imge4gZCy71X5fmrbr1Y+pxllkoyE77r4TOrjOyxAl7O9WlnAPfMINwAAEnxJREFUjG37s3KdfBe2mIwLOwtJhxIeOgsAnxMJ0kVsvydpcsJQeVLCs+p12/tKOpPw9nu/qH0yEdcN6KLccRrCb2wVokT/rJGenCQ1kCVaHULxJOgtaVuiY8X7xG7ZDJJWL14hEG35GhN6TuJJMhqwPZRoATwOfKXqoZHcqXzOBU2SMOKZKD+PK+l0ohvWA02H2vaRtp/6T2UmSWspC9DjgTWJ+GI7SRPZvpkoRT2J8Jl4DdjZ9gnA65ImJHanP6uUIOS7sMVkXNhxXAXcY/tV228QZVc/Le+9mYFXiKTpS8CUkiaxvYXt9xr3LZM7ree7lDsSHow3EAnvs5rPSZK6SQVPN6V5l0XS3ERwdSFwJbELMAlgYEHgXdv7tGGoSdIjkDQtUWt9kLODT5L8RyT1JsoZ3yV2rQ8hus2NA9xo+4PGXJc70+1H0iLAbrbXKZ9vJhI+1wLzA6sTXhO7E0qRPfJdWB8ZF3Y+kvYmDHg/BoYSLepvAT4AlgSWIbpwVg15U3XVBv6HcsdULyZtJxU83ZDqLouk2cvXw4kM/99K9v9I23sDtwHfJ0xekyRpEbZfsr1LLmiS5Js073qWxeeNREvfG4nd6V0Iz6rliFIfcme6+2B7CPCwpHsk3Qo8QSgKtiCUO1MADwOv2d6m8S7sasc7Gb1kXDjGcA4wPnCi7R2Idug/IrqZHUQoQBqGvGNDNkKpg9GlOC0HZHInaTup4OmmSJqKMOqandg9ewKYGFjJ9mblmN8AawEX2b64TUNNkh5F7qYlyddp8viYvQS/MwO3Ahvavrty7EzAMcDFti9py4CTkVLMkq8hlIpXSFqWMFf+A9HuF9svl2PzXVgjGRd2HiMxmN+QUMQNBA4EPgS2t/1R4xzSkLd2UnGajEnkrks3YCRZ4NWAJ4m2iHMS0uhbgV6SNi7H3GR7rcYknvWeSdJ6ckGTJF/H9peSplK0yB4o6Q/AHMAehPoD+GrxeRxwSSZ3ugfN8YftfwHHAktJmhXYnOgeOJ7tl22/rGjrnH4uLSTjwjGDkgwYt+nrq4jEwXXA9ba3bCR3Gudk8qC1pOI0GdPJBE+baZLdLidpofKrqYDvAVcALxBSweGEvHPycswb5byGjDNfOEmSJElLycXnmEMuQLsfGRd2Dt/FkNf2e0THpXltn1uO69V8naQ1ZLlj0hPIEq1uQDHt+h0wC9AXOIFolbglUZP7aPnvPcB5jTakSZIkSVInTeVYyxFGrg9I6gf0BhYC/g/oT7QCXhKYx3b/xrlZ2lMfIykRqd7DLYnk3Ga2X68cMwfwfKVsJI1DayTjws4iDXk7iyx3TMZ0MsFTM80vc0njEB0QPre9nqQFgR2AvYi2lxMTAfI5jUx/OS/rP5MkSZLaycVn55EL0O5LxoWdRfV+FfXbyURXuX62H60cV02kZlK7TYwkyb0lYXZ9SvnzGbAvUZ56s+1zJE3ZlPTO5yvpGLJEq2Yqk8Jmkn5VAt8zgJklTWj7QWBcYFHb/YmJY6WKjHOscp18ySRJkiQtpbl0oCw+DwGmsb0qsBuwJnATcBlR2jMYuNP22Y3kTpZj1Ud2hOksMi7sLGx/Lqm3pG2JhNv7wCbADJJWlzRBOXQs+HpJUFIvWe6Y9FRSwdNiJK0MbAxcSfgR9CGC3weJlqM3Ey+Yg4EJgJOAE4E9bd9XkbTnLlqSJEnSFiRtBrxp+2pJKxIKneVtD5d0AdEV6wpJkwPvVBatuevZBrIjTPcl48LOolkBUgx5TyJUVlcCmwKTAAYWJMpW92nDUJMuSMVp0hPJBE+LkDQpcBQwAzFxLwL8G7ibcGd/AbgB+JJwZ3+vHPcEMMD2kDYMO0mSJOnB5OKz88gFaGeQcWHn0VRmNXtRu81MvBs3tH135diZgGOIZHd2CWwDWe6YJEGWaLWOXoQE8BDb5wOXA9MBrxGyzRsIE8qniRr4d4HTiZ3PIZLGSkl7kiRJUgeSJi2lPNsDVwOLEYme6YgEwa5EN5ENARG+BfMRrWR3t30fjJCxZ3KnHrIjTEeRcWGHUZLVU0kaCAyU9AdgDmAPYIvGccWQ9zjgkkzutI8sd0ySIBM8LaAEXG8Su5yrlxfG/cCMwOvA/MCNwBfEjuiTwMtEUD2TpDlsf5kvmCRJkqQmcvHZgeQCtDPIuLAzGIkX1WrE/VgJmBNYnVDw9JK0cTnmJttrNbot5buwHiStLOlCSetLmlrSTJLuAOYF1pG0CXAvcB/QX9K8RJL75XKJt4qnUi/IxE4y5pAJntHAKALbwcBEwH7ApcBTtocBjwETApsTrvvnlon7VULy+WRdY0+SJEl6Nrn47BxyAdoZZFzYeaQhb+eQitMkGTXpwfM/0lSfO5Ht98rPDfPCJYla6stsD6qc19v2p41rQE4ISZIkSetpnnMqvjljAwOJ5M0iwFDbe5bSnw2J5MFetp+uXGtC28Nr/5/ogTTFG8sRXjoPSOoH9AYWAv6PUFp9TnhLzGO7f/UeZ0ef1pJxYeeShrydQTHzPws42vbdkn5CdHM8mfCwOo14D64CvEXMa6sAc9veMZ+vZEwnEzzfkaYJfBzgcCJzfAcw2Pb7lWOPJLL+ZwMfVF8oGWwlSZIkdZGLz84mF6Ddl4wLO4s05O1MKsnqTYC5gd2JZgDnAZsBKxDvx6Hl89Xld1MRiZ89UxGXjOlkgue/pOxwftk0GW9NBFinErLoUwjp5iflJTQ3sRt6dsoAkyRJkrrJxWfnkQvQziDjws5G0mbAm7avlrQikSBd3vZwSRcQXbGuKKqRdypGvvlc1UAqTpPkvycTPN8SSRPY/qDyeVFgQdsDJf0JeACYDZgM2MX2G+0ZaZIkSZIEufjsfHIB2j3JuLCzkLQy4dNyJfHe60N4Ij1IeIvdTPjsHAxMAJwEnEgoPu6rJBZ65XuxHlJxmiTfjUzw/AfKi2F+YFXbB1Z2PhcE9rN9l6QNiW4iywEPAQcAt9u+ofla+YJJkiRJWk0uPjuPXIB2BhkXdhaSJgWOAmYgnqdFgH8DdwOvEGrFGwjvlr2B98pxTwADbA9pw7B7NKk4TZL/jeyiNQpKQLw98GiZxGct9ezfAzYA+kpaA/gzYfb1C+B2wvjwhubr5SSeJEmStJLSvWcBYLfyeRxJRxMB8mPlsJuJBc+FhHfLH4oy5BvXqmfUPZvsCNM5ZFzYkfQi/FcOsX0+cDnxbL0GjEUkd/oDTxMd6d4lknPv2B6ikXdES0YzksbuIum5OdGl7HfAVsBvJI1XuSeDgY+Aj5qfp0zuJD2VTPB0gUa0Ie1NtEBcQtI8wF/L90OBrYndz/mA/W1vD5wLrG77iHKdnBCSJEmSWsjFZ8eSC9BuTsaFnUlJFrxJKN9WL3//9wMzAq8TSqwbgS8IldyThKfL1cBMkuZwtKvPd2ELkTQBREKmqBAXlfT78uvFgfeBA4nn7ArbH1cS2n+zPSgT20kygkzwdEEl4/shMAmwrO2hwA2Sdrd9PPGiuRyYGXiiyACfsf3qSDLQSZIkSTLaycVn55IL0M4g48LOYBTJzsHARMB+wKXAU7aHEarGCQmVSD/b55bn6VVgw+y21FpScZokrSE9eArNdZqS9iR2N+8EZgfOBB4mAq2VgVmBPYCrbJ9V/4iTJEmSZASlq9JGwFu2DyplP8/YPqoEv9MARwB3AWc15ryujJiT1pAdYTqHjAs7izTk7SyK4nRRwufo86I4fVbSWcA+wLyE19ithO/Ym8CKxPN1RLvGnSSdQI9P8IzMgEvSEcBA2/+UtAlR974/sC8RJG8DjFXpVpFGXkmSJEkt5OKz88gFaGeQcWFnkYa8nUXlfbcUsAKh0HkH+LPtmSTtRHR5fJ0oXZ3Y9s6SZgPeK+qqNChPklHQYxM8zS8GSasB6wJ/AS4gZLZn275S0rzA0cBFtgdJmtb2S+W8nBCSJEmSWsjFZ+eRC9DOIOPCzqIr5aGkrYnkwKmE8uMU4Bzgk6KUm5tQyJ2dni3tJRWnSdI6emSCpzr5SuoL7EnUTA8EtiMmhYcIU8P+xK7oB8Cptp9qvkaSJEmStJJcfHYeuQDtHDIu7BwkTWD7g8rnRYEFbQ+U9CfgAcJvbDJgF9tvtGekSYNUnCZJvfTIBA+E5Jl4eTwD/I3oTvF7YHViUvgZMDWwPvCS7QFtGmqSJEnSg8nFZ2eRC9DOJOPC7k1RdcwPrOroEthQwy0I7Gf7LkkbEh3mliPeiQcAt7upS2CW99RDKk6TpD30iARPF5njWQkDr+HATsXcaydgmmJqeD6x67bBqK6TJEmSJHWQi8/uTy5AO4eMCzuLNOTtLFJxmiTtpUe0Sa/sfC4gaTLbzwLvA68C45TDPohDdDpwD5FJppw3VvU6SZIkSdIqNKLteePzrERSYGrgEtt/A34HTG37p0TCp7/tobb7NZI7zddJWkdZgG4PPFqSO7Pa/gz4HrAB0FfSGsCfgbMIldXtwLvNyR1IE+VWk3FhZ1B5h/UGJgeWkDQP8Nfy/VBga0IRNx+wv+3tgXOB1RvJHWUL7dooSZmG51hfSQcDawMnA6sQLekPBnaWtDqxUfE44bWD7Zca9z2fryT5boyRCh5JMwMrAQ/Yvl/SdMB+wFxEjec9wIPA7sBhtv8hqQ+wG/CI7WvKdXIHLUmSJGkLkhYAnrP9tqSTgVeAo21/LGkrYp57HXgMuN72M+W8nLtqIjvCdAYZF3Y2acjbWaTiNEnayxiX4CkdKBYijLtWJbwKPgJmsn2upMOJnbPFgZ2JnZoTbL/bdJ2cxJMkSZKWk4vPzicXoN2XjAs7izTk7Syy3DFJuh9jlHxb0gTAMsB5tg8ADgMOt30ncJekvwDvEVLAo4guFq8QstzGNRqy25zEkyRJkpZSFp9nEbuZp0paAZgFuNP2UkSQvDvwT+BZYANJE9v+yPbBmdypny5K6PYEjiXii7nKPdwbWF/SNMASwGnAHbbPqC5ibH+R9611ZFzYOYyiLGdSYGPb+wLXAssCw4hyx4OAe4E1GsmdLE2tlyx3TJLuxxj1EixdK/oRmX5sXwY8K2lSYG5CKngi8CghlR5egq3PK9fICTxJkiRpObn47CxyAdp5ZFzY/Wle4EtaTdJ5kn5TfidggXL4w4Rp+Ua29wMOKEnSz9O3pR4kzSzpd5IWLp+nk3Qa8RwdJOnX5eeZgenKaecQpvLX2D7Z9jM5dyVJ6xgTS7R6AUcSwdWEhCnbVoQB2/Hl8562b62ckzufSZIkSe1I+hmwle11y+eLCNPQhqdLP8JQubGo+bRdY+2pZEeYzibjwu5L9ZmQ1Jcon5sZGAhsR3TFegjoX/78glCDnGr7qeZrJK0lyx2TpDMY4xI8AMVh/wYi4Nqr8v3UDUPD8rlXdZcmSZIkSeokF5/dm1yAjhlkXNh9SUPezqAoTm8FTivJ67WAvWwvVHzkBgB3A3MCbxFlWGsDgxrPVM5dSVIPY2SCB0DSrkQL2d2aJ+ycwJMkSZLuQi4+uze5AB0zyLiw/aQhb2eTitMk6QzG5Drw84GxJU3SPGnnJJ4kSZJ0F2wPBY6jGFIWVQ8e0UK78TnnrhbThYHyrMDpRALnEtt/IxYwU9v+KZHw6W97qO1+jeRO+ux0SzIubDNpyNvx3Ar8U9K+pVzrPeBd4Cngh8AtRDfI9RvJncY9S5KkPsZYBU+SJEmSdAqSpgV2AQ6yPazd4+npSFoAeM7225JOJsytj7b9saStiLb2rwOPAdfbfqaclyUISVIopTsrEYv++yVNB+wHzEUYJt8DPEh0CjzM9j8k9QF2Ax7JLoHdj1ScJkn3Z4xP8KSMM0mSJEmSrsgFaM8j48J6SEPeMZcsd0yS7s0Yn+BJkiRJkk4hF5/1kQvQJGkNacg7ZpOK0yTp3mSCJ0mSJEmSHkUuQJOktaQhb5IkSXvIBE+SJEmSJD2OXIAmSeso5vBHAsOACYHJga2A2YDjy+c9bd9aOSeTph1EKk6TpHuSCZ4kSZIkSXocuQBNktaShrxJkiT1kwmeJEmSJEl6JLkATZLWkoa8SZIk9TJ2uweQJEmSJEnSDmwPBY4jDJQbqh4ayZ3K51yEJsl343xgbEmTND9H+VwlSZKMflLBkyRJkiRJjyU7wiRJkiRJMqaQCZ4kSZIkSZIkSVpGGvImSZLUQ5ZoJUmSJEnS45GUMVGStIhM7iRJktRDKniSJEmSJEmSJEmSJEk6nNytSpIkSZIkSZIkSZIk6XAywZMkSZIkSZIkSZIkSdLhZIInSZIkSZIkSZIkSZKkw8kET5IkSZIkSZIkSZIkSYeTCZ4kSZIkSZIkSZIkSZIO5/8BrxpNIe+CSfUAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# do the same but with real histogram plots\n",
"plt.close()\n",
"plt.rcParams.update({\n",
" \"figure.max_open_warning\": 0\n",
"}) # we are creating a lot of plots\n",
"for nr, key in enumerate(cats):\n",
" if \"node\" not in key:\n",
" fig, ax = plt.subplots(1, 1, figsize=(16, 8))\n",
" __data = (data_frame.dropna(how=\"any\", subset=[key]))\n",
" try:\n",
" __data = __data[key].value_counts()[:10]\n",
" print(\"Plotting {}\".format(key))\n",
" sns.barplot(\n",
" x=__data.index, y=__data.values, ax=ax, palette=\"GnBu_d\")\n",
" ax.title.set_text(key)\n",
" plt.xticks(rotation=45)\n",
" fig.autofmt_xdate()\n",
" plt.tight_layout()\n",
" plt.savefig(str(nr) + \"_\" + key + \".png\")\n",
" except (ValueError, KeyError):\n",
" pass\n",
"print(\"Printing to screen\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"# read in the psc data\n",
"# Attention: The way python is handling memory allocations you need\n",
"# temporarily more than 40 GB ram. When everything is loaded\n",
"# you still need 26 GB.\n",
"data_folder = \"/path/to/psc/data\"\n",
"psc_folder = \"People_with_significant_control_UK\"\n",
"psc_file = glob.glob(os.path.join(data_folder, psc_folder, \"*.json\"))\n",
"psc_ = pd.read_json(psc_file[0], lines=True)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 5446238/5446238 [02:37<00:00, 34581.92it/s]\n"
]
}
],
"source": [
"# get all the unique names from the psc data\n",
"name_list_full = []\n",
"idx_list = []\n",
"last_name_list = []\n",
"for idx in tqdm(range(len(psc_.data))):\n",
" try:\n",
" cur_name = psc_.data[idx][\"name\"]\n",
" name_list_full.append(str.lower(cur_name[cur_name.find(\" \") + 1:]))\n",
" idx_list.append(idx)\n",
" last_name_list.append(str.lower(cur_name[-cur_name[::-1].find(\" \"):]))\n",
" except KeyError:\n",
" pass\n",
"\n",
"name_list = unique_vals(\n",
" name_list_full\n",
") # this is faster than check within the for loop for existence\n",
"last_name_list = unique_vals(last_name_list)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 1455642/1455642 [00:01<00:00, 1104540.30it/s]\n"
]
}
],
"source": [
"# do the same for the offshore data\n",
"offshore_name_list = []\n",
"offshore_last_name_list = []\n",
"for offshore_name in tqdm(data_frame.name.str.lower().unique()):\n",
" try:\n",
" cur_name = str(offshore_name)\n",
" offshore_name_list.append(str(cur_name))\n",
" offshore_last_name_list.append(\n",
" str(cur_name[-cur_name[::-1].find(\" \"):]))\n",
" except KeyError:\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"For the full name we found 15714 entries in the offshore leaks\n",
"For only the last name we found 41900 entries in the offshore leaks\n"
]
}
],
"source": [
"mutual_last_names = compare(last_name_list, offshore_last_name_list)\n",
"mutual_full_names = compare(name_list, offshore_name_list)\n",
"print(\"For the full name we found {} entries in the offshore leaks\".format(\n",
" len(mutual_full_names)))\n",
"print(\n",
" \"For only the last name we found {} entries in the offshore leaks\".format(\n",
" len(mutual_last_names)))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"keith woods\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"keith woods; officer_of: dramoor holdings limited, registered at: No address in the system, jurisdiction: British Virgin Islandswith unique leak id:10136114\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/10136114\n",
"------------------------\n",
"keith woods; registered_address: Heritage House Ramsey Road Peel IM5 1RH, with id:14044495\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/14044495\n",
"------------------------\n",
"#######################################\n",
"######### psc database lookup:\n",
"#######################################\n",
"Found multiple companies\n",
"------------------------\n",
"company number: 10382384\n",
"Find more information about this company at:\n",
"https://beta.companieshouse.gov.uk/company/10382384\n",
"------------------------\n",
"{'address': {'address_line_1': 'Trinity Close',\n",
" 'country': 'United Kingdom',\n",
" 'locality': 'Woodbridge',\n",
" 'postal_code': 'IP12 4TN',\n",
" 'premises': '4'},\n",
" 'country_of_residence': 'United Kingdom',\n",
" 'date_of_birth': {'month': 9, 'year': 1969},\n",
" 'etag': 'f0c56f725f73642c13ee3ccd7ec77cba95128635',\n",
" 'kind': 'individual-person-with-significant-control',\n",
" 'links': {'self': '/company/10382384/persons-with-significant-control/individual/T6HwS9n4bcB-6VnPRQC7wGN94EM'},\n",
" 'name': 'Mr Keith Woods',\n",
" 'name_elements': {'forename': 'Keith', 'surname': 'Woods', 'title': 'Mr'},\n",
" 'nationality': 'British',\n",
" 'natures_of_control': ['ownership-of-shares-75-to-100-percent',\n",
" 'voting-rights-75-to-100-percent',\n",
" 'right-to-appoint-and-remove-directors'],\n",
" 'notified_on': '2016-09-19'}\n",
"------------------------\n",
"company number: 07520564\n",
"Find more information about this company at:\n",
"https://beta.companieshouse.gov.uk/company/07520564\n",
"------------------------\n",
"{'address': {'country': 'England',\n",
" 'locality': 'Swindon',\n",
" 'postal_code': 'SN5 5ED',\n",
" 'premises': '10 Bashkir Close',\n",
" 'region': 'Wiltshire'},\n",
" 'country_of_residence': 'England',\n",
" 'date_of_birth': {'month': 7, 'year': 1954},\n",
" 'etag': '46d7bd4a67af55100e05ed405fef722b5ff430d6',\n",
" 'kind': 'individual-person-with-significant-control',\n",
" 'links': {'self': '/company/07520564/persons-with-significant-control/individual/bu5NhqN6asydrC3NCNMyUVOj4XU'},\n",
" 'name': 'Mr Keith Woods',\n",
" 'name_elements': {'forename': 'Keith', 'surname': 'Woods', 'title': 'Mr'},\n",
" 'nationality': 'British',\n",
" 'natures_of_control': ['ownership-of-shares-25-to-50-percent',\n",
" 'voting-rights-25-to-50-percent'],\n",
" 'notified_on': '2016-04-06'}\n",
"------------------------\n",
"company number: 06217082\n",
"Find more information about this company at:\n",
"https://beta.companieshouse.gov.uk/company/06217082\n",
"------------------------\n",
"{'address': {'address_line_1': 'Kenwood Avenue',\n",
" 'country': 'United Kingdom',\n",
" 'locality': 'Leigh',\n",
" 'postal_code': 'WN7 2LP',\n",
" 'premises': '64',\n",
" 'region': 'Lancashire'},\n",
" 'country_of_residence': 'England',\n",
" 'date_of_birth': {'month': 4, 'year': 1956},\n",
" 'etag': '7d415e9525503d9e2ce1213c998fcc622ba2266a',\n",
" 'kind': 'individual-person-with-significant-control',\n",
" 'links': {'self': '/company/06217082/persons-with-significant-control/individual/s0mDEB78ELtsN0u4SU5HP_3hb_w'},\n",
" 'name': 'Mr Keith Woods',\n",
" 'name_elements': {'forename': 'Keith', 'surname': 'Woods', 'title': 'Mr'},\n",
" 'nationality': 'British',\n",
" 'natures_of_control': ['ownership-of-shares-75-to-100-percent',\n",
" 'voting-rights-75-to-100-percent',\n",
" 'right-to-appoint-and-remove-directors'],\n",
" 'notified_on': '2016-04-06'}\n"
]
}
],
"source": [
"# look for a name\n",
"lookup_name = mutual_full_names[100]\n",
"print(lookup_name)\n",
"name_lookup_offshore(lookup_name, data_frame)\n",
"name_lookup_psc(lookup_name, name_list_full, idx_list, psc_)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"List of Bavarian Christian Social Union politicians\n",
"List of German Christian Democratic Union politicians\n",
"List of German Communist Party politicians\n",
"List of German Free Democratic Party politicians\n",
"List of German Green Party politicians\n",
"List of German Left Party politicians\n",
"List of National Democratic Party of Germany politicians\n",
"List of Social Democratic Party of Germany politicians\n",
"We found 5 german politicians in the offshore leaks\n",
"josef bauer\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"josef bauer; registered_address: 2384, LIESINGTALSTRASSE 58, BREITENFURT, with id:58022447\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58022447\n",
"------------------------\n",
"josef bauer; officer_of: sky gourmet malta ltd, registered at: JAMES CONFECTIONERY VELLERAN STREET, FGURAFGR1900, MALTA, jurisdiction: Maltawith unique leak id:55033415\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55033415\n",
"------------------------\n",
"josef bauer; officer_of: sky gourmet malta inflight services ltd, registered at: JAMES CONFECTIONERY VELLERAN STREET, FGURAFGR1900, MALTA, jurisdiction: Maltawith unique leak id:55034593\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55034593\n",
"------------------------\n",
"josef bauer; officer_of: sky gourmet malta ltd, registered at: JAMES CONFECTIONERY VELLERAN STREET, FGURAFGR1900, MALTA, jurisdiction: Maltawith unique leak id:55033415\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55033415\n",
"------------------------\n",
"josef bauer; officer_of: sky gourmet malta inflight services ltd, registered at: JAMES CONFECTIONERY VELLERAN STREET, FGURAFGR1900, MALTA, jurisdiction: Maltawith unique leak id:55034593\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55034593\n",
"------------------------\n",
"philipp meyer\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"philipp meyer; registered_address: 'ETUDE MEYER & DORSAZ' 78, RUE DU RHONE GENEVA 1204, with id:58123536\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58123536\n",
"------------------------\n",
"philipp meyer; officer_of: societe africaine de developpment (sad) ltd, registered at: LEVEL 7, THE MALL OFFICE COMPLEX THE MALL STREET, FLORIANAVLT 16, MALTA, jurisdiction: Maltawith unique leak id:55029235\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55029235\n",
"------------------------\n",
"peter simon\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"peter simon; registered_address: 87 LANCASTER ROAD, W 11 1QQ LONDON, with id:58045346\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58045346\n",
"------------------------\n",
"peter simon; officer_of: brands exploitation limited, registered at: 57 HIGH STR, SLIEMA, MALTA, jurisdiction: Maltawith unique leak id:55006045\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55006045\n",
"------------------------\n",
"erich fuchs\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"erich fuchs; officer_of: smartis inc., registered at: Portcullis TrustNet Chambers P.O. Box 3444 Road Town, Tortola British Virgin Islands (w.e.f 9 December 2005), jurisdiction: British Virgin Islandswith unique leak id:135486\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/135486\n",
"------------------------\n",
"eduard oswald\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"eduard oswald; registered_address: 4 DURHAM PLACE LONDON SW3 4ET, with id:58033652\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58033652\n",
"------------------------\n",
"eduard oswald; registered_address: 4 DRUHAM PLACE LONDON SW3 4ET, with id:58128487\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58128487\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator leasing limited, registered at: 6, ROSA MARINA BLDG, 216 MARINA SEAFRONT, PIETA'PTA 9041, MALTA, jurisdiction: Maltawith unique leak id:55036078\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55036078\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator leasing limited, registered at: 6, ROSA MARINA BUILDING, 216 MARINA SEAFRONT, PIETA'PTA9041, MALTA, jurisdiction: Maltawith unique leak id:55024837\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55024837\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator leasing limited, registered at: 6, ROSA MARINA BLDG, 216 MARINA SEAFRONT, PIETA'PTA 9041, MALTA, jurisdiction: Maltawith unique leak id:55036078\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55036078\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator leasing limited, registered at: 6, ROSA MARINA BUILDING, 216 MARINA SEAFRONT, PIETA'PTA9041, MALTA, jurisdiction: Maltawith unique leak id:55024837\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55024837\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator aircraft management limited, registered at: 6, ROSA MARINA BUILDING, 216 MARINA SEAFRONT, PIETA'PTA9041, MALTA, jurisdiction: Maltawith unique leak id:55072072\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55072072\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator leasing limited, registered at: 6, ROSA MARINA BUILDING, 216 MARINA SEAFRONT, PIETA'PTA9041, MALTA, jurisdiction: Maltawith unique leak id:55024837\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55024837\n",
"------------------------\n",
"eduard oswald; officer_of: gladiator aircraft management limited, registered at: 6, ROSA MARINA BUILDING, 216 MARINA SEAFRONT, PIETA'PTA9041, MALTA, jurisdiction: Maltawith unique leak id:55072072\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55072072\n",
"------------------------\n"
]
}
],
"source": [
"german_politicians = []\n",
"wiki_data = wikipedia.page(\"List of German politicians\")\n",
"# This wikipedia page contains also partys that doesn\"t exist anymore\n",
"# So we need to manually define the indexes of the list\n",
"# for still active parties\n",
"idx_to_keep = (0, 3, 4, 6, 7, 8, 12, 14)\n",
"for idx, poli_list in enumerate(wiki_data.links):\n",
" if idx in idx_to_keep:\n",
" print(poli_list)\n",
" german_politicians.append(wikipedia.page(poli_list).links)\n",
"# Since we appended full lists we now have one large lists of several sublists\n",
"# therefore we need to flatten our list:\n",
"german_politicians_ori = [\n",
" item for sublist in german_politicians for item in sublist\n",
"]\n",
"# we need to clean out list from name appendixe like\n",
"# \"Surname LastName (politician\" we also need to get rid of\n",
"# non-name entries like \"List of ....\"\n",
"german_politicians = []\n",
"german_politicians_ori = unique_vals(german_politicians_ori)\n",
"for item in german_politicians_ori:\n",
" if \"List\" not in item and \"Members\" not in item:\n",
" if \"(\" in item:\n",
" german_politicians.append(item[:item.find(\"(\") - 1].lower())\n",
" else:\n",
" german_politicians.append(item.lower())\n",
"\n",
"politicians_full_names = compare(german_politicians, offshore_name_list)\n",
"print(\"We found {} german politicians in the offshore leaks\".format(\n",
" len(politicians_full_names)))\n",
"if politicians_full_names:\n",
" for lookup_name in politicians_full_names:\n",
" print(lookup_name)\n",
" name_lookup_offshore(lookup_name, data_frame)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"We found 4 american politicians in the offshore leaks\n",
"david scott\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"david scott; registered_address: Homat Ruby #301 Minami Aoyama 1-26-6 Minato-ku, Tokyo 107 Japan, with id:237672\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/237672\n",
"------------------------\n",
"david scott; registered_address: 33, KENILWORTH ROAD, BRIDGE OF ALLAN, STIRLING FK94RP, with id:58027627\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58027627\n",
"------------------------\n",
"david scott; officer_of: gozo aquaculture limited, registered at: 52, OLD THEATRE STREET, VALLETTAVLT 05, MALTA, jurisdiction: Maltawith unique leak id:55010764\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55010764\n",
"------------------------\n",
"christopher murphy\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"christopher murphy; registered_address: DEEP DARGLE, ENNISKERRY, CO. WICKLOW, with id:58060616\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58060616\n",
"------------------------\n",
"christopher murphy; officer_of: bwg trading limited, registered at: LEVEL 2, WEST MERCURY TOWER, THE EXCHANGE FINANCIAL AND BUSINESS CENTRE, ELIA ZAMMIT STREET, ST. JULIANSSTJ3155, MALTA, jurisdiction: Maltawith unique leak id:55041146\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55041146\n",
"------------------------\n",
"christopher murphy; registered_address: DEEP DARGLE, ENNISKERRY, CO. WICKLOW, with id:58060616\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/58060616\n",
"------------------------\n",
"christopher murphy; officer_of: cmhg co limited, registered at: LEVEL 2, WEST MERCURY TOWER, THE EXCHANGE FINANCIAL AND BUSINESS CENTRE, ELIA ZAMMIT STREET, ST. JULIANSSTJ3155, MALTA, jurisdiction: Maltawith unique leak id:55044774\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/55044774\n",
"------------------------\n",
"john curtis\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n",
"john curtis; registered_address: 6 Tower Drive, Dover, MA 02030., with id:235755\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/235755\n",
"------------------------\n",
"john curtis; officer_of: aquaventure water corporation, registered at: International Business Company Formation Inc. 101 Main Street Suite One Tappan, New York 10983 USA, jurisdiction: Undeterminedwith unique leak id:226236\n",
"Find the interactive graph for this node at: https://offshoreleaks.icij.org/nodes/226236\n",
"------------------------\n",
"john kennedy\n",
"#######################################\n",
"######### offshore database lookup:\n",
"#######################################\n"
]
}
],
"source": [
"american_congress = pd.read_json(\"us-legislators-current.json\")\n",
"delegates = [\n",
" american_congress.name[idx][\"official_full\"].lower()\n",
" for idx in range(american_congress.shape[0])\n",
"]\n",
"\n",
"delegates_full_names = compare(delegates, offshore_name_list)\n",
"print(\"We found {} american politicians in the offshore leaks\".format(\n",
" len(delegates_full_names)))\n",
"\n",
"if delegates_full_names:\n",
" for lookup_name in delegates_full_names:\n",
" print(lookup_name)\n",
" name_lookup_offshore(lookup_name, data_frame)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"You are not in it\n"
]
}
],
"source": [
"# You want to look for your own name ? Go ahead:\n",
"my_name = \"Julian Zimmermann\"\n",
"me_in_the_leaks = compare([my_name.lower()], offshore_name_list)\n",
"if me_in_the_leaks:\n",
" print(\"We found you\")\n",
" lookup_name = me_in_the_leaks[0]\n",
" name_lookup_offshore(lookup_name, data_frame)\n",
"else:\n",
" print(\"You are not in it\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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