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FMassin/How to do seismograms with obspy.ipynb

Last active October 18, 2017 01:04
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How to do seismograms with obspy.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Preambule\n",
"This makes all figures interactive and include them inside the notebook interface."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib notebook"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Dependencies"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# alway useful\n",
"import os\n",
"# for system commands e.g. files listing\n",
"import glob\n",
"# for plots\n",
"import matplotlib\n",
"import matplotlib.patheffects\n",
"# for direct call to matplotlib's dates handlers\n",
"from matplotlib.dates import AutoDateLocator, date2num\n",
"# for numeric operation\n",
"import numpy\n",
"# for seismology\n",
"import obspy\n",
"# for direct call to obspy's arrival time model\n",
"from obspy.taup import TauPyModel\n",
"# for direct call to obspy's massive downloader\n",
"from obspy.clients.fdsn.mass_downloader import CircularDomain, Restrictions, MassDownloader\n",
"# for outputs\n",
"if not os.path.exists('material'):\n",
" os.makedirs('material')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Events\n",
"This is a list of dictonnaries (one per event) that will be used to control event's data request and adjust ploting style."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Linthal aftershock, Swiss\n",
" Linthal mainshock, Swiss\n",
" Norcia mainshock, Italy\n"
]
}
],
"source": [
"# This is a list: a = [1,2,3,'a','b','c']\n",
"## this is how to use it: b = a[0]+...\n",
"# This is a dictionnary: a = {'a':1, 2:'b','c':3}\n",
"## this is how to use it: b = a['a']+...\n",
"# This a list of dictionnaries:\n",
"events=[{'name':' Linthal aftershock, Swiss',\n",
" 'ot':'2017-03-06T20:55:45',\n",
" 'lat':46.91,'lon':8.92,'dep':8,\n",
" 'prov':['ETH'],\n",
" 'm':'M1.8',\n",
" 'tc':-0.12},\n",
" {'name':' Linthal mainshock, Swiss',\n",
" 'ot':'2017-03-06T20:12:07',\n",
" 'lat':46.91,'lon':8.92,'dep':8,\n",
" 'prov':['ETH'],\n",
" 'm':'M4.5',\n",
" 'tc':-0.05},\n",
" {'name':' Norcia mainshock, Italy',\n",
" 'ot':'2016-10-30T06:40:19',\n",
" 'lat':42.8547,'lon':13.0884,'dep':10,\n",
" 'prov':['INGV'],\n",
" 'm':'M6.6',\n",
" 'tc':-1.2}]\n",
"## this is how to use it: \n",
"for e in events:\n",
" print(e['name'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Bulk download \n",
"... of all data available next by events. "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2017-06-22 10:15:58,772] - obspy.clients.fdsn.mass_downloader - INFO: Initializing FDSN client(s) for BGR, EMSC, ETH, GEONET, GFZ, INGV, IPGP, ISC, KOERI, LMU, NCEDC, NIEP, NOA, RESIF, SCEDC, USGS, USP, ORFEUS, IRIS.\n",
"[2017-06-22 10:15:59,070] - obspy.clients.fdsn.mass_downloader - INFO: Cannot use client 'EMSC' as it does not have 'dataselect' and/or 'station' services.\n",
"[2017-06-22 10:15:59,531] - obspy.clients.fdsn.mass_downloader - INFO: Cannot use client 'ISC' as it does not have 'dataselect' and/or 'station' services.\n",
"[2017-06-22 10:16:00,000] - obspy.clients.fdsn.mass_downloader - INFO: Cannot use client 'USGS' as it does not have 'dataselect' and/or 'station' services.\n",
"[2017-06-22 10:16:03,925] - obspy.clients.fdsn.mass_downloader - INFO: Cannot use client 'IRIS' as it does not have 'dataselect' and/or 'station' services.\n",
"[2017-06-22 10:16:09,583] - obspy.clients.fdsn.mass_downloader - INFO: Cannot use client 'USP' as it does not have 'dataselect' and/or 'station' services.\n",
"[2017-06-22 10:16:09,586] - obspy.clients.fdsn.mass_downloader - INFO: Successfully initialized 14 client(s): BGR, ETH, GEONET, GFZ, INGV, IPGP, KOERI, LMU, NCEDC, NIEP, NOA, RESIF, SCEDC, ORFEUS.\n",
"[2017-06-22 10:16:09,592] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:16:09,596] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:09,652] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available for request.\n",
"[2017-06-22 10:16:09,655] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available.\n",
"[2017-06-22 10:16:09,661] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:16:09,668] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:09,706] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - No data available for request.\n",
"[2017-06-22 10:16:09,711] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - No data available.\n",
"[2017-06-22 10:16:09,716] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:16:09,722] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:10,385] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available for request.\n",
"[2017-06-22 10:16:10,396] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available.\n",
"[2017-06-22 10:16:10,410] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:16:10,413] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:10,552] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available for request.\n",
"[2017-06-22 10:16:10,556] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available.\n",
"[2017-06-22 10:16:10,559] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:16:10,563] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:10,849] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Successfully requested availability (0.28 seconds)\n",
"[2017-06-22 10:16:10,887] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Found 27 stations (27 channels).\n",
"[2017-06-22 10:16:10,893] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Will attempt to download data from 27 stations.\n",
"[2017-06-22 10:16:10,900] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Status for 15 time intervals/channels before downloading: EXISTS\n",
"[2017-06-22 10:16:10,905] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Status for 12 time intervals/channels before downloading: NEEDS_DOWNLOADING\n",
"[2017-06-22 10:16:11,029] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Successfully downloaded 1 channels (of 12)\n",
"[2017-06-22 10:16:11,032] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Launching basic QC checks...\n",
"[2017-06-22 10:16:11,056] - obspy.clients.fdsn.mass_downloader - INFO: File 'waveforms/IV.FEMA..HNZ__20161030T064009Z__20161030T064119Z.mseed' has only 15.88 seconds of data. 66.50 are required. File will be deleted.\n",
"[2017-06-22 10:16:11,061] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Downloaded 0.0 MB [40.60 KB/sec] of data, 0.0 MB of which were discarded afterwards.\n",
"[2017-06-22 10:16:11,064] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Status for 11 time intervals/channels after downloading: DOWNLOAD_FAILED\n",
"[2017-06-22 10:16:11,067] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Status for 1 time intervals/channels after downloading: DOWNLOAD_REJECTED\n",
"[2017-06-22 10:16:11,073] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Status for 15 time intervals/channels after downloading: EXISTS\n",
"[2017-06-22 10:16:11,103] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - No station information to download.\n",
"[2017-06-22 10:16:11,109] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:11,113] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:11,151] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available for request.\n",
"[2017-06-22 10:16:11,154] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available.\n",
"[2017-06-22 10:16:11,158] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:11,161] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:11,307] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available for request.\n",
"[2017-06-22 10:16:11,310] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available.\n",
"[2017-06-22 10:16:11,316] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:11,323] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:11,385] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available for request.\n",
"[2017-06-22 10:16:11,388] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available.\n",
"[2017-06-22 10:16:11,392] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:11,398] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:31,104] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available for request.\n",
"[2017-06-22 10:16:31,107] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available.\n",
"[2017-06-22 10:16:31,111] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:31,114] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:31,248] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available for request.\n",
"[2017-06-22 10:16:31,252] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available.\n",
"[2017-06-22 10:16:31,255] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:31,260] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Requesting unreliable availability.\n",
"[2017-06-22 10:16:31,413] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available for request.\n",
"[2017-06-22 10:16:31,416] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available.\n",
"[2017-06-22 10:16:31,419] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:31,422] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Requesting unreliable availability.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2017-06-22 10:16:36,274] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available for request.\n",
"[2017-06-22 10:16:36,276] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available.\n",
"[2017-06-22 10:16:36,279] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:16:36,282] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:14,233] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available for request.\n",
"[2017-06-22 10:17:14,236] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available.\n",
"[2017-06-22 10:17:14,239] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 15\n",
"[2017-06-22 10:17:14,243] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:14,317] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available for request.\n",
"[2017-06-22 10:17:14,321] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available.\n",
"[2017-06-22 10:17:14,326] - obspy.clients.fdsn.mass_downloader - INFO: ============================== Final report\n",
"[2017-06-22 10:17:14,329] - obspy.clients.fdsn.mass_downloader - INFO: 15 MiniSEED files [0.4 MB] already existed.\n",
"[2017-06-22 10:17:14,332] - obspy.clients.fdsn.mass_downloader - INFO: 15 StationXML files [0.2 MB] already existed.\n",
"[2017-06-22 10:17:14,335] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,338] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,341] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,344] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,347] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,350] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,353] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,356] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,361] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,363] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,367] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,371] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,374] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,378] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,380] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,383] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,387] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,391] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,396] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,401] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,404] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,407] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,410] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,413] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,415] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,418] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,421] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:17:14,424] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:17:14,428] - obspy.clients.fdsn.mass_downloader - INFO: Downloaded 0.0 MB in total.\n",
"[2017-06-22 10:17:14,432] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:17:14,439] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:14,489] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available for request.\n",
"[2017-06-22 10:17:14,492] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available.\n",
"[2017-06-22 10:17:14,495] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:17:14,498] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:14,566] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Successfully requested availability (0.06 seconds)\n",
"[2017-06-22 10:17:14,576] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Found 5 stations (5 channels).\n",
"[2017-06-22 10:17:14,580] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Will attempt to download data from 5 stations.\n",
"[2017-06-22 10:17:14,587] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Status for 5 time intervals/channels before downloading: NEEDS_DOWNLOADING\n",
"[2017-06-22 10:17:14,811] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Successfully downloaded 5 channels (of 5)\n",
"[2017-06-22 10:17:14,816] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Launching basic QC checks...\n",
"[2017-06-22 10:17:14,938] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Downloaded 0.1 MB [543.12 KB/sec] of data, 0.0 MB of which were discarded afterwards.\n",
"[2017-06-22 10:17:14,942] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Status for 5 time intervals/channels after downloading: DOWNLOADED\n",
"[2017-06-22 10:17:14,969] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - No station information to download.\n",
"[2017-06-22 10:17:14,976] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:14,981] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:15,641] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available for request.\n",
"[2017-06-22 10:17:15,646] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available.\n",
"[2017-06-22 10:17:15,648] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:15,650] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:15,769] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available for request.\n",
"[2017-06-22 10:17:15,772] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available.\n",
"[2017-06-22 10:17:15,774] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:15,776] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:15,911] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - No data available for request.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2017-06-22 10:17:15,913] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - No data available.\n",
"[2017-06-22 10:17:15,916] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:15,918] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:15,953] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available for request.\n",
"[2017-06-22 10:17:15,955] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available.\n",
"[2017-06-22 10:17:15,959] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:15,962] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:16,105] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available for request.\n",
"[2017-06-22 10:17:16,107] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available.\n",
"[2017-06-22 10:17:16,111] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:16,115] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:16,174] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available for request.\n",
"[2017-06-22 10:17:16,177] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available.\n",
"[2017-06-22 10:17:16,181] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:16,184] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:35,251] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available for request.\n",
"[2017-06-22 10:17:35,254] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available.\n",
"[2017-06-22 10:17:35,260] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:35,271] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:35,395] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available for request.\n",
"[2017-06-22 10:17:35,408] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available.\n",
"[2017-06-22 10:17:35,412] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:35,418] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:35,568] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available for request.\n",
"[2017-06-22 10:17:35,576] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available.\n",
"[2017-06-22 10:17:35,580] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:35,583] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Requesting unreliable availability.\n",
"[2017-06-22 10:17:40,381] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available for request.\n",
"[2017-06-22 10:17:40,384] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available.\n",
"[2017-06-22 10:17:40,387] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:17:40,389] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:18,946] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available for request.\n",
"[2017-06-22 10:18:18,949] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available.\n",
"[2017-06-22 10:18:18,951] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:18,953] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:19,036] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available for request.\n",
"[2017-06-22 10:18:19,038] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available.\n",
"[2017-06-22 10:18:19,040] - obspy.clients.fdsn.mass_downloader - INFO: ============================== Final report\n",
"[2017-06-22 10:18:19,044] - obspy.clients.fdsn.mass_downloader - INFO: 0 MiniSEED files [0.0 MB] already existed.\n",
"[2017-06-22 10:18:19,047] - obspy.clients.fdsn.mass_downloader - INFO: 5 StationXML files [0.1 MB] already existed.\n",
"[2017-06-22 10:18:19,050] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,052] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,055] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,058] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,061] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,064] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,067] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,070] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,075] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,079] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,085] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,088] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,091] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,093] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,095] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,099] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,102] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,105] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,109] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,110] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,114] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 5 MiniSEED files [0.1 MB].\n",
"[2017-06-22 10:18:19,116] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,121] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,127] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,131] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,134] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,137] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:18:19,140] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:18:19,142] - obspy.clients.fdsn.mass_downloader - INFO: Downloaded 0.1 MB in total.\n",
"[2017-06-22 10:18:19,146] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:18:19,153] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:19,205] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available for request.\n",
"[2017-06-22 10:18:19,207] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - No data available.\n",
"[2017-06-22 10:18:19,210] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 0\n",
"[2017-06-22 10:18:19,213] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:19,267] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Successfully requested availability (0.05 seconds)\n",
"[2017-06-22 10:18:19,273] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Found 5 stations (5 channels).\n",
"[2017-06-22 10:18:19,278] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Will attempt to download data from 5 stations.\n",
"[2017-06-22 10:18:19,281] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Status for 5 time intervals/channels before downloading: NEEDS_DOWNLOADING\n",
"[2017-06-22 10:18:19,468] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Successfully downloaded 5 channels (of 5)\n",
"[2017-06-22 10:18:19,472] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Launching basic QC checks...\n",
"[2017-06-22 10:18:19,514] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Downloaded 0.1 MB [457.64 KB/sec] of data, 0.0 MB of which were discarded afterwards.\n",
"[2017-06-22 10:18:19,516] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Status for 5 time intervals/channels after downloading: DOWNLOADED\n",
"[2017-06-22 10:18:19,528] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - No station information to download.\n",
"[2017-06-22 10:18:19,532] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:19,536] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,195] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available for request.\n",
"[2017-06-22 10:18:20,199] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - No data available.\n",
"[2017-06-22 10:18:20,201] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,204] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,345] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available for request.\n",
"[2017-06-22 10:18:20,348] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - No data available.\n",
"[2017-06-22 10:18:20,351] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,353] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,412] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - No data available for request.\n",
"[2017-06-22 10:18:20,417] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - No data available.\n",
"[2017-06-22 10:18:20,420] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,424] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,461] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available for request.\n",
"[2017-06-22 10:18:20,464] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - No data available.\n",
"[2017-06-22 10:18:20,467] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,471] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,616] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available for request.\n",
"[2017-06-22 10:18:20,620] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - No data available.\n",
"[2017-06-22 10:18:20,626] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,630] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:20,687] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available for request.\n",
"[2017-06-22 10:18:20,691] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - No data available.\n",
"[2017-06-22 10:18:20,694] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:20,697] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:40,552] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available for request.\n",
"[2017-06-22 10:18:40,556] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - No data available.\n",
"[2017-06-22 10:18:40,559] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:40,562] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:40,674] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available for request.\n",
"[2017-06-22 10:18:40,677] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - No data available.\n",
"[2017-06-22 10:18:40,679] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:40,682] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:40,837] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available for request.\n",
"[2017-06-22 10:18:40,841] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - No data available.\n",
"[2017-06-22 10:18:40,844] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:40,847] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Requesting unreliable availability.\n",
"[2017-06-22 10:18:45,698] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available for request.\n",
"[2017-06-22 10:18:45,700] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - No data available.\n",
"[2017-06-22 10:18:45,703] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:18:45,704] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Requesting unreliable availability.\n",
"[2017-06-22 10:19:24,987] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available for request.\n",
"[2017-06-22 10:19:24,990] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - No data available.\n",
"[2017-06-22 10:19:24,992] - obspy.clients.fdsn.mass_downloader - INFO: Total acquired or preexisting stations: 5\n",
"[2017-06-22 10:19:24,995] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Requesting unreliable availability.\n",
"[2017-06-22 10:19:25,067] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available for request.\n",
"[2017-06-22 10:19:25,070] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - No data available.\n",
"[2017-06-22 10:19:25,073] - obspy.clients.fdsn.mass_downloader - INFO: ============================== Final report\n",
"[2017-06-22 10:19:25,077] - obspy.clients.fdsn.mass_downloader - INFO: 0 MiniSEED files [0.0 MB] already existed.\n",
"[2017-06-22 10:19:25,080] - obspy.clients.fdsn.mass_downloader - INFO: 5 StationXML files [0.1 MB] already existed.\n",
"[2017-06-22 10:19:25,082] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,086] - obspy.clients.fdsn.mass_downloader - INFO: Client 'KOERI' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,089] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,092] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GEONET' - Acquired 0 StationXML files [0.0 MB].\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[2017-06-22 10:19:25,098] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,107] - obspy.clients.fdsn.mass_downloader - INFO: Client 'INGV' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,111] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,114] - obspy.clients.fdsn.mass_downloader - INFO: Client 'LMU' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,117] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,120] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,122] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,126] - obspy.clients.fdsn.mass_downloader - INFO: Client 'RESIF' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,128] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,132] - obspy.clients.fdsn.mass_downloader - INFO: Client 'IPGP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,135] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,139] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NOA' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,142] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,144] - obspy.clients.fdsn.mass_downloader - INFO: Client 'NIEP' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,148] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,151] - obspy.clients.fdsn.mass_downloader - INFO: Client 'BGR' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,155] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 5 MiniSEED files [0.1 MB].\n",
"[2017-06-22 10:19:25,157] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ETH' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,160] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,163] - obspy.clients.fdsn.mass_downloader - INFO: Client 'SCEDC' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,167] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,170] - obspy.clients.fdsn.mass_downloader - INFO: Client 'ORFEUS' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,172] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 MiniSEED files [0.0 MB].\n",
"[2017-06-22 10:19:25,175] - obspy.clients.fdsn.mass_downloader - INFO: Client 'GFZ' - Acquired 0 StationXML files [0.0 MB].\n",
"[2017-06-22 10:19:25,178] - obspy.clients.fdsn.mass_downloader - INFO: Downloaded 0.1 MB in total.\n"
]
}
],
"source": [
"# No specified providers will result in all known ones being queried.\n",
"mdl = MassDownloader() # [e['prov']])\n",
"for e in events:\n",
" origin_time = obspy.UTCDateTime(e['ot'])\n",
"\n",
" # Circular domain around the epicenter. This will download all data between\n",
" # 70 and 90 degrees distance from the epicenter. This module also offers\n",
" # rectangular and global domains. More complex domains can be defined by\n",
" # inheriting from the Domain class.\n",
" domain = CircularDomain(latitude=e['lat'], longitude=e['lon'],\n",
" minradius=.05, maxradius=.3)\n",
" restrictions = Restrictions(\n",
" \n",
" # Get data from 10 secondes before the event to one minute after the\n",
" # event. This defines the temporal bounds of the waveform data.\n",
" starttime=origin_time - 10 ,\n",
" endtime=origin_time + 60,\n",
" \n",
" # You might not want to deal with gaps in the data. If this setting is\n",
" # True, any trace with a gap/overlap will be discarded.\n",
" #reject_channels_with_gaps=True,\n",
" \n",
" # And you might only want waveforms that have data for at least 95 % of\n",
" # the requested time span. Any trace that is shorter than 95 % of the\n",
" # desired total duration will be discarded.\n",
" minimum_length=0.95,\n",
" \n",
" # No two stations should be closer than 10 km to each other. This is\n",
" # useful to for example filter out stations that are part of different\n",
" # networks but at the same physical station. Settings this option to\n",
" # zero or None will disable that filtering.\n",
" #minimum_interstation_distance_in_m=9999,\n",
" \n",
" # Only HH or BH channels. If a station has HH channels, those will be\n",
" # downloaded, otherwise the BH. Nothing will be downloaded if it has\n",
" # neither. You can add more/less patterns if you like.\n",
" channel_priorities=[\"HGZ\",\"HNZ\"],#,\"HHZ\"],\n",
" \n",
" # Location codes are arbitrary and there is no rule as to which\n",
" # location is best. Same logic as for the previous setting.\n",
" #location_priorities=[\"\", \"00\", \"10\"],\n",
" )\n",
"\n",
" # Specify providers (list of strings) will result in specific short queries, but will need to be adapted manual to each event.\n",
" # mdl = MassDownloader(e['prov'])\n",
" \n",
" # The data will be downloaded to the ``./waveforms/`` and ``./stations/``\n",
" # folders with automatically chosen file names.\n",
" mdl.download(domain, restrictions, mseed_storage=\"waveforms\",\n",
" stationxml_storage=\"stations\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Processing\n",
"Just so the plots are nice."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3 Trace(s) in Stream:\n",
"M1.8. 8km. Linthal aftershock, Swiss. CH.SLTM2.HGZ | 1970-01-01T00:00:00.000000Z - 1970-01-01T00:00:10.000000Z | 250.0 Hz, 2501 samples\n",
"M4.5. 8km. Linthal mainshock, Swiss. CH.SLTM2.HGZ | 1970-01-01T00:00:00.000000Z - 1970-01-01T00:00:10.000000Z | 250.0 Hz, 2501 samples\n",
"M6.6. 10km. Norcia mainshock, Italy. IV.T1212.HNZ | 1970-01-01T00:00:00.000000Z - 1970-01-01T00:00:10.000000Z | 125.0 Hz, 1251 samples\n"
]
}
],
"source": [
"# prepare object for arrival time calculation\n",
"model='iasp91'\n",
"model = TauPyModel(model=model)\n",
"\n",
"# prepare empty data stream objects\n",
"stream = obspy.core.stream.Stream() # for wide scale plot\n",
"zoomedstream = obspy.core.stream.Stream() # for zoomed plot\n",
"others = obspy.core.stream.Stream() # for the data I have but not in main plot\n",
"\n",
"# go over each event\n",
"for i,e in enumerate(events):\n",
" # go over each file\n",
" for f in glob.glob('waveforms/*'+e['ot'][:15].replace(':','').replace('-','')+'*mseed'):\n",
" \n",
" # read the file\n",
" tmp=obspy.read(f)\n",
" \n",
" if len(tmp[-1].data)>1: # if not empty\n",
" tmp.detrend() # take out the trend\n",
" \n",
" # read inventory\n",
" inv = obspy.read_inventory('stations/'+tmp[-1].stats.network+'.'+tmp[-1].stats.station+'.xml') \n",
" # remove response\n",
" tmp.remove_response(inventory=inv,output='ACC')\n",
" \n",
" # remove everything over Nyquist\n",
" tmp.filter(\"lowpass\", freq=tmp[-1].stats.sampling_rate/2.1)\n",
" \n",
" # arrival times from velocity model\n",
" d=numpy.sqrt((inv.networks[0].stations[0].longitude-e['lon'])**2.+(inv.networks[0].stations[0].latitude-e['lat'])**2.)\n",
" arrivals = model.get_travel_times(e['dep'], \n",
" distance_in_degree=d, \n",
" phase_list=['p'], \n",
" receiver_depth_in_km=0.0) \n",
" \n",
" # slice the data around arrival with a correction for visual allignement \n",
" tmp=tmp.slice(obspy.UTCDateTime(e['ot'])+arrivals[0].time-2.+e['tc'], \n",
" obspy.UTCDateTime(e['ot'])+arrivals[0].time+8.+e['tc'])\n",
"\n",
" # tweak the metadata so the legend is OK\n",
" for t in tmp:\n",
" t.stats.channel = ' '+t.stats.network+'.'+t.stats.station+'.'+t.stats.channel\n",
" t.stats.network = e['m']\n",
" t.stats.station = ' '+str(int(numpy.sqrt(e['dep']**2+d*90)))+'km'\n",
" t.stats.location = e['name']\n",
" \n",
" # only get the stations I want\n",
" if 'SLTM2' in f or 'T1212' in f and len(tmp[-1].data)>1: #T1216\n",
" stream+=tmp \n",
" zoomedstream += tmp.slice(obspy.UTCDateTime(e['ot'])+arrivals[0].time-.2+e['tc'],\n",
" obspy.UTCDateTime(e['ot'])+arrivals[0].time+.8+e['tc'])\n",
" zoomedstream[-1].interpolate(sampling_rate=1000)\n",
" \n",
" stream[-1].stats.starttime=0.#arrivals[0].time-.2+e['tc']\n",
" zoomedstream[-1].stats.starttime=0.#arrivals[0].time-.2+e['tc']\n",
" elif len(tmp[-1].data)>1:\n",
" # the other stations are kept separately\n",
" others+=tmp\n",
" others[-1].stats.starttime=0.#arrivals[0].time-.2+e['tc']\n",
"# Show what's in\n",
"print(stream)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Finally Plotting\n",
"Obspy plot look like this:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
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" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
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" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
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" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
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"\n",
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"\n",
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" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
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"\n",
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" nav_element.attr('style', 'width: 100%');\n",
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"\n",
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" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
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" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"\n",
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" nav_element.append(status_bar);\n",
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"\n",
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" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
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"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
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" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
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"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
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" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
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" case 2:\n",
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" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
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\" width=\"800\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# options for the plot method\n",
"specs={'method':'full',\n",
" 'transparent':True,\n",
" 'color':'gray',\n",
" 'tick_rotation':10,\n",
" 'equal_scale':False,\n",
" 'type':'normal',\n",
" 'automerge':False,\n",
" 'grid_color':'gray',\n",
" 'grid_linestyle':':',\n",
" 'grid_linewidth':.5,\n",
" 'tick_format':'%S',\n",
" 'handle':True}\n",
"# do a default obspy stream plot\n",
"fig=stream.plot(**specs)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"That's not nice enough, this a function that wrapps obspy's plot and customizes:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": true,
"scrolled": false
},
"outputs": [],
"source": [
"def custom_plot(stream,\n",
" zoomarea=None,\n",
" figsize=[6,max([6,len(stream)*1])] ):\n",
" \n",
" # make a figure so the plot is interactive\n",
" fig = matplotlib.pyplot.figure(figsize=figsize)\n",
"\n",
" # make a big axe so we have one ylabel for all subplots\n",
" biga = fig.add_subplot(111, frameon=False)\n",
" # turn every element off the big axe so we don't see it\n",
" biga.tick_params(labelcolor='none', top='off', bottom='off', left='off', right='off')\n",
" # add common labels\n",
" biga.set_ylabel('Acceleration (m/s/s)')\n",
" fig.axes[0].set_title('10s view')\n",
"\n",
" # default obspy stream plot\n",
" stream.plot(fig=fig,**specs)\n",
" for a in reversed(fig.axes):\n",
" # adjust Y range\n",
" a.autoscale(enable=True, axis='y', tight=True) \n",
" if zoomarea:\n",
" # add rectangle for next zoomed plot\n",
" a.fill([date2num(obspy.UTCDateTime(min(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(min(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(max(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(max(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(min(zoomarea)).datetime)],\n",
" [min(a.get_ylim())*.99,\n",
" max(a.get_ylim())*.99,\n",
" max(a.get_ylim())*.99,\n",
" min(a.get_ylim())*.99,\n",
" min(a.get_ylim())*.99],\n",
" facecolor='.9',zorder=-9)\n",
" # add grid\n",
" a.grid(linestyle='dotted')\n",
"\n",
" # add a xlabel on the bottom subplot\n",
" fig.axes[-1].set_xlabel('Time (seconds)')\n",
" # tweak the X-tick's labels to show seconds with 1 decimal\n",
" fig.axes[-1].set_xticklabels(numpy.round((fig.axes[-1].get_xticks()-min(fig.axes[-1].get_xticks()))/(numpy.diff(fig.axes[-1].get_xticks())[0]/2.),decimals=1))\n",
" \n",
" return fig"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now I can use my custom_plot function as much as I want:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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]
},
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},
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\" width=\"600\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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gTUTz+BnXvWqV83lhwObo2U6nMjMYx7zmJnNNtts5g//8A9n/uzP/qzhAVqUAWy/TF900UUz8TmDmbj7nIk3VWYiMJkrH4HGzPvf//7Oul00u/LllwZyGv1dffXVTTvml7xnOXKacgC6C0fapMl797vfPXP/+99/o3a6+Crzp5Fbfmk4AoRGhzGRNu3GR+5mYu/dHA+0k3nvSlMOKPnK+egsJomxZXL5Sekrr7xyJt5SatrNMrWloWU+6S9+8Ysze++990x8aLfBe97znjMXXHDBRrLaPvUicJ3j23yOi5VmTMYeoZntt9++GXuxYbgZI4xZ+LHvZJkYcxHgNzyRrz1Ix8Q+8+d//uczt7rVrZpxu91228287nWvmyvTZpvYKjATb9k1iJ5/93d/d+78mGOOmXn5y1+OP5p53/veN0cHfUTA3uTbtw8//PCZO9/5zs14he/Xv/71TXl558Q0Y/nBD37wnK7Jj4mhoRcrTXPtxMTd2A8fdPOb33zmrne9a+N/aP+b3/zmHJ/yzxFeDzzwwI1sRl9n3GUfSHucA6ThYVw6JsO5MqTtE6Y5L9PQM580bVDGNO2OS8OfZTLvXemllAlfcumllzbyrBaZshw5rQ3sp6XNprXTZz7zmZkDDjig6ZPQHrLv/fjHP27GQIyDHHPE6eLDkCtY3AYRBG2d2N4l0uyZysBbg2yE3zVl5nJfabl2deRtWMZJlWaT3Mrf7rrZTQ4f1WCJSGyWiHyFlqNp7gp9gy2nt9pqq9EJJxDzxaavKHPiiSeOWGL3nCNlonOMInBqykiHlQtpmaYcd8fclbESER1r9K53vaspRxnpSsP65D/1qU9t9ohx1/ehD31o9MIXvrC5a7PsuLqZTp+0/EIzp3Mb5kMv896VLvnMtOabph4wrUysKN32trdt3qhSDuiYnkamcCZj24cu0IfHvmU2UPwNv5zLe04rh3Qf9ahHjfbbb79RBCzNKsFrXvOaOR1Qz3LLlX72s5894oWTI444olndiJuK5tMC3NWW/UpeOcpvWeYf/uEfmjHCqgerxSeffPLo9re//Vz5JhE/0uKcu3ZWh8C99tqrGZ+eP+EJT2iqRAA4Ovroo5s0dVmh+cQnPtH4BvmJCWn0tre9bRQOvlmlYZwfe+yxnXaSB47KQQOmWSF55CMf2diPvT7YMIKkZqUngpamP8unR67Hjdzo6U9/eiMj9GyHdPaBbNLWH5K23a40q6iWIa3cpjkv07ZPPkD9nKYt89vS8Gd+5r0rTdkq08q3E/0XYPUem9mvutL0GcvYx6hvuux7XFsOGDLAIgAiEjkgkM8wPCLwjoEbopNIJDgq0q8I5DHfHoFshN/grTYcHxPndwm8WeDLA98XCNwmcJ/AGwSyOvUXgQR0G9aPI9EHHHB9yj7xiU8cfeADH5grymO4Jz3pSXPnJJi0eMzU5+93WAqlPN+h2XzzzZuA6StfIaacDNSFHzrW7rvvPrrDHe7QbKosa15++eWNs82B4aGHHjpat25dw+M73/nOxinvtNNOo1hJG732ta8tSUx9vn79+lHcJTf1jjzyyNHee+89et7zntd8lZd2mCiBP/3TPx3FCtgo7tabL7ejWx1zrOZdpzx1YsWh+asDvr4fKy5zjwW4Ng5OOumk0a677trsN2FCPO6445ritAkfZ599dsPDwQcfPHrOc54zd84jMIBX2vfff/9mgiIYY+IXmHhf+cpXjmIFobEljuEFL3hB8y0v+gFvE/HIQ/jYxz7WfB+Hb30x6QtMzMi95ZZbjrbddtsRAY/OhjLwBu/Izmv1TNYlxArq6E53utPoX//1X8tLG50zIdOHnvnMZzZOjC8nP/CBDxzd8Y4M0w03CnwHDuBNM94wY6xgH/pdrMg01+hH55xzTpNGx+xdZE8P+bEKPDa/udjxQ9DA32XEKtHo3ve+d+Ms6Z98PuXhD394R63x2XzTjhsfggzkILjifKGA/S+77LI5nX/0ox9tdJnfyqP/019x+vQf/gbkvPPOm3fT6AGa9DNu6pAH29Gf23xarGiNCFhjZXvupnDejdeKEzWADXbZZZdWW0ysvMYLxIpVowFuSoaGtrExdBtd9IYMsGjjeYG3CmQWOCjw8YHXBhKR5JWsV83mfz+Oxwc+P5BPLwCXBr4w8MTAawK/F7hh5o6br0gTmDGTsAr22EACOdK9QWP2qUCgwEoTkxMTJs/3mZTmCzg8Jlv2IbDP4OMf/3jz9mIfevGoo9lnxYoJd/QEKvFoc6OqOH3ehGTSZaVCYKWMQO4jH/nI6C//8i9H//RP/9RMkjh8Ahic8ZBAe3zQkO/C/NEf/dHor/7qrxry3MUTSLhKQLAay8vNSt597nOf65SnEv9N9fnPf74JLnjTk5W8PsCkz0of+63e8pa3jJ72tKeNfvCDHzQB8jve8Y4RkyR3+kxY+RwdAuzRikdLzWoj+0de+tKXbhTcEQgQUECfPRfsGYnHdw2fBLEEMALX4/FBE8S9+tWvntM3wS3tsX+EoIUAPh49NdWYOOEbm7FqCY/svcnwpje9qQlKoE8QMQ4I7m53u9s18tMHy2ANe2E3AF5YqeWIfThyvQQCVYIi+vP5558/F6x15Zf18/lZsa+LvsHNw1Bw97vfffSGN7xhxD4/9+gMQZubnMc+9rGjf/mXf2nIYasnP/nJY0mjW4P3sQVbLrL6xk0KYxp7sFeRYxcwUT3+8Y9vAjJuZiosvgaYV1gpnWZ+WXyuNo0WmNOAxQiwltMeQwdYPwodcat5w8DbB54RCLAEtGFZoDkdsXuZoOvGgdsEHh2Y4cg42SqQFa71gTzqA64MvGfgTQM3C8Tjfypw0YDolzteHCmTKemFRMSxJ6N5VMGdOZM3E8AjHkGMOBke9rCHNZMvEzd/LcPE4eNKasf+mhFlmEzKO/6/+Zu/aVYkYq9TsxpCYPMHf/AHTfDCXTCT/5BAUMSqB7piFehLX/rSWPKsgnSVJ0BjtY/lYoMcAqNJwAZ46DIZog9WswjU+gCB2Nlnn92sNsUenEZPyPHhD394rjob+2NPTxNIEfgQZLAK4woj/60osPrAOXe4Wd/0qb/7u79rVhIJLvg+EYEbwEog9agjTYJGgRVD+iWPjmI/jtmdR1Y8DMSe//znNwHZPvvs0wSdVCKAYpMxK2gEfc961rOaoJFVL1ba2v6EldUZAhfswSocq5VAV35zseOHgA8ak4A+ziqhGHubOqu87GUva24oeFSG3m8TX9lm1W0IYAwRWHHjxdgbd+PFCyDoaFwQhh2ViSMBscBqKgGV+sGWrIhRjlUzN4Rb/sUvfnHTL1kRrbB0Gvi93+PhTYVpNbCYAda0vAxZfugAa0jeFo3WtAESjpT9FjhT0guBP/7jPx7d5S53aZwtkziPZHgMNAlwsEyGb3zjG5vn1NzNEmz46I36rHwwGbPKU0Je3cAJlOd9ApaS5rhzvrcjMAGMo89kwcTBESjL82iKO38mE8ox0ZSrL7aVj6y68KiJQJK6roLlMl1pVgcJKgjsqAuyKoXNBP52RODjtDxmJCgh6P3rv/7ruTdOKdOlj+9973vNqo10YjP0iDyAfWIEBG1AEPTP//zPTUBGsN4XCOJYCfv2t7/dBEZ8eJIVTcAVLIJhAiWCcVal0COri23ACiErbOjioQ996NwqUVd+Gw3zCBKzfs0vj6z6sqInEoR2AUH5X/zFX4xiI//cI19Wdvr0ny6a5jOOWb1kBXjcjRfjkhVl9n/lVU3peKQPKRPH/IhZG6MfxgljmMeSlONGLT9WZmsAvopAHfkrLI0GmFe4CZl2flka7lZ2KwZYHHNfHoLr5bTHmgywNGZf47HPhgCHx10L/VIvjxiZhHG0TLqPe9zjmhWISbzwCI99WzyWoMNwN84qFn/tI+DoCQp4lLiSwUBKHgmYWMZte+TB6gkBAKs5BKOsFLCa01ZWeh55xPcnf/InzaTNRIQdu+qVPLHHhRUnbO6kxwoVwYlQ1uExKPyx74evZDPJTQImR4I5gTR5wDbbbDNC/jZAB6eeemqjG19tbys3Lo/9SOtj7xyPwAGCc+RlVY1gi0d1yEMf6wqwWIElcCBQYx/Yc5/73IZWV35zseOHgA75aXMxgNU/bkp4vPateN1/CGDVlUC3a2WKFc+XvOQlTX8guJ0v3OxmN2s+AcBLNvRhPkvS1pfRHxvaeWxL/6mwdBpgXmHsTzu/LB2HK7el/BjPz9QMxe1y2mNNBljlxNjHkDjK/Hgo18GABDZ0kpzOZUwzyeP84lXU5i6aO30eXU0CJkMmBu5Ocazsp2JPR65L0IYDZqWGRyOLBQwA5BXbHP24tlk9KwOHLpuw8kUwwR08b1+ygte3PQIiVkV4XHX88cePvvCFL3SyBU+sGDkYCbDYoPyKV7yi0Tv5rBZ2vZCAznWuTOS02efOidUU9mER2PBmKf8R55tqBD88BqZNZKZ9ZBLoS7yVRpCeH32iSx5vlkAb7P9C99DjQ5MEU/4nHXpmxe/tb397E2Cx+kG/o422/Vfsl2Bll/1ByEtAisxd+SU/5Tl3/wQHBC3sDUTnrBBhc7+hVNaZdM4eNlbg6KvwxUoSwYofFab+Qvozj1r5F4i2Gy/2GbrnkhdSFgq8HMHLKiA6x4Y8yiUNoC90xx5FXrqpsLQaYNzhp7p82dJys2m1pt+F66H3YS2nPdZkgNVn4iu7J49M3F9SXmMvDEv2bODm7SvSvLkDEATlvTjsBWEjJBM6TnfdunXNXXVb2YbA7A+TAhMd+3V4o4x9KHymodz3QVs8QmGfCZPztMCqy6SNuOw7Qkbx3HPPnaoZ7uh5rMNjNyZoBgCTe9tAYFWFSYrHMWzo56683Ojd1fghhxzSbGDH6bGixJ6sLuBlBmzBI0FWBwF04eccsBcraQR5bUAgQHCATEzeBCrs2ZoEvIlIeYILAjqCK1bdAOrzhiF79LA5b5ARmGfYc889m4CdCZVADH7pAznwtjx6YyWUOgSBBAW0zQsPAoEUAQdBF/ZAZ9w4dG08581KHmuiYz5TQAADdOVP6l88hiVAAOnz7Fkk8DQIlM9xR+R3sz43HazosloMstrGTUjey7aQ/szjZ/pOGxA4s/q51157NTaBLwIyAJ1yPs1bhby8Au/cLPBmKX2SIJx2WDFkJZO9WOgQ2hltt43PmjeMBphX6EvzmV+G4WDTpUKA5ePzoQOs5bTH9TZdk8yLczbH/5T9FzjGDDxuYwJlNaDC0mqAO3EeefAItC3I4jqfIODZPGn2OLWVW1quV2Zr7LvhMXT+FMR8OZ1kl/nSrfUWpoEh7MI+TVa7uCmoMIwGCBJ4u5ubgbr3bTqdcuPFNhyQN5B5gjAUQHP2JSA++7RhuXco4hPorMkVLFZLKqwsDfCIqQtYteGOnxUzgAlmUwceWbG6MTQwaQ4RXMnXOLtYph6XXgPVLkuv80ktMq8QGNT5ZZKmrnud4NRvyA29B2s57bEmI40uhQ/99sJ1u1HNadMAq1F8CqFrVYpgBJtRBlgNARbL4DxuXMmyTLJLmy3Xah4TBN+140ZgsWEIu1RfN7yV8FE8Lu+aX4ZvcfVQzAHW0I8Il9MeazLAwpglsN9j0pewyzr1fBgNEGSwebsr2GAy4Dm6AVhXuWG4WRoqyCAuTYvTtwJ/4+wyPcXVWwOfgr7afMvQUi/ULrwsg13ZL1hhOA1ge/bBLUUfGI7rlUEJnbmCNXSAtZz2WJMBVltEywZjXnvneW2FpdeAq1NtLTOhEFwZYLWV2VTzlmLFYyG6GWeXhdBdbXXpo4DHxZZvIXbhZRluWvB5FYbTAPMK/5TQNr8M18rqpEQQRJ/Gx6+mR4Rr8it0bQOAt3F4A4fvTLHhvb5uu3IGMhvgGXi8BUeat6OW882QITTD40Hu1NjYXzfEDqHR5aXhI1/2CfZ9y3WpOWYS46v7/GsD3+3K/wKx1Lxsiu3xeRNW/bpW/phXhtycvSnqaL48c6OJHyTIGnoFq22+ny+f09ZbkwFW25IhHwHk+1R8HZnvGfmnt9MqtJafXgPc9fNmJ296tK1S8Zo+g483P/kCObbyld7pW1sZNfgiN98vYpLLnwxYGdxt4GKSXVYSr8vNC98Y4/9K+cwHN2eLCfO1CzclfHGfDxK3/dvDYvK8GmjzDUI+rdP1347MKzwi5DMo9aZpOoujO3TGzcnQAVbbfD8dd/MvvSYDrK6Ili9o862hCkurAR5X8Lcg/Pdam234ejpBFd/64TtLfCdqXXyzalMGvmXEF9T5tlH5h90rRa5JdlkpfK4EPvja/dnxcVe+I9b1XayF8snqLeODu/xx42Wh7dT67Rrww8rtV0eNbfzf0K4yNb9dA4sZYLXNKe1cDJ9b92ANr9NKcUoNMAD4aGLXQOCZPJOKd4XLeUcypWidxd17Ne4/GjsrL9GFSXZZIjY2iWa86+76EO0QQvCRUT4iXO0yhDano8GqIQHWuP1B1S7T6TSXNsDCz4/Tca7TN901r/Stv5ByazLAKr+GvRAF1roL1wD24EvrXXZZjQGWQeJKDrAm2WXhll89FJwUmIQXCwjeeLRc7bJYGu6mawA9zr7VLt36m3QFf8gj7MV4RNg1r0ziaYjrazLA2tQ3SA9h+JVEA3vwty1tdvHOkT1XdQVraa02zi5Ly8nKb80AazFXsJiEeMuZfYpd42Xla2rT5NDASju3SVHHS5tWJuexFQE/v1h7sNrmlclcDVNi6ABr82Dr5MBfBl4e+IDANuCT3EcF8s+1Vwc+MTDD+ji5JpDP2h8ReP1A4A8DPxj4/cCfBJ4ROPW/qC7nkmHwW6HQAPZgA3ubXZhUGHwsHfv1ald/CjKb1KkyrOQVrHF22aSUvQTMOvEudoDFo2W+YdU1XpZA1DXZhPY10GpTQh0vbVqZnKcvXKwAq21emczVMCWGDrAODbZ+EEig9eLAYwM3/tO/yAh4deAtAvnDIf78722BOwQCuwa+OfDRgdvM4ivjCNw48PzAOwdS/7TAEwKnguVcMpyK0TVSGHvwJ7xtdtGhEWAxULh7d0BuyurZFPZgaRf+X80/T96Udb6YvDsBL3aAhQw//OEPO8fLYsq4lmnrhzy26cLx0ubH2spz48jqzVoHfeFiBVh97bEYdhgywCL4eVTgAYH/EXhi4KWB+wWW8JTIODCQFSoCJoKk/QMBjscHXhj400DKPTUQuDLwnwN/GMh/UhwcuF3gzQN7g4+aeleoBRdVA9iDt6/a7OLERYAFUGY1BFjIwNI1b4YN4WShd/TRRw/6/4ba5Zvf/ObovPPOG4TPRe1Iy0jcfroUARb/Ydk1XpZRBau6aQMr7dwmrOOlzY+1lb/44oubt6Lbrq2lPP05eluMTe597bEYOh8ywNo+GPxF4HcSowRYO6dzkpsFbhl4CSezkMvtFHnltW0jjwCuhPtGxr8G/ri8MHvOrHzThDch3wmNyNnoOacxuPmkLd+VJkK2DGnuTADTnJdprptPmvqUMW2nI78tDX/mZ9670pRdqTLB101vetNGB6VMOjQfDzJY3HC6kmXKcuS0NlBm7M33sMyfr0x8R+yKK65o/g8PmmV/o6/l/pbTXX2PMvx9BTYgcLjmmmsg3fDaJZNycDQ9X5loSzlyWt45muZ6TnfJtFjjCR2hKyZidcOR9uQ9p+HV/CxHTnM9yyRdbM3HdtXvYskkv1mOnMY2ltlU7CS/WY6c7pKJvxcCKIuN2+zENfxYtlmXbci/8sorR3w/jZss6gJ53HSlKavtSc9XJm0mv20yUQagjZyW3y754M8yXXKYbzk/Js1YGlKmRoBl+hkywCIAYkUqA+dlYOT5z1PBXK6kI03rWY1HhO8MfIkZLceXRh6rYGIzQ1xyySVNUb5qDALkMUEB3Fl861vfatI8HuFDlwBfeucPXQE+KMe3aIAzzzxzbuXg9NNPb/ZIkH/KKafMOVzSdCQGJ2mAvRSUB7grhQ4AXegDtEe7AHzADwB/8AnA96Ys0wUXXDDiI37f+MY3riOTAZY2wAn4n5Gbsp0IWLyz+uIXv7jgvvfTn9LF4w7nF9zjDNP3CKh4dOuqjH1yNfQ9Pib84Q9/eLDxhI78wjcfwwWG9hFORHzQ9GMf+9iIb28Ba8FHLLff+8IXvtDomh/GRJcvx4/hv/v48quuuqqhedlll13H73FhrcxP9mv8Om8RMkfq74eYc5lnlwuuN2DDuwWtTwb+QaJ5SKR/HfjXKW+zSPOHfzcLNHh6UaTvGfjYwBMCoXNwIHDzQCIZVp82zB4b0kQjnwh8WWAXsIIFCtC4hjtANol6F8CjmpzG4ETT5JNm7w/YlSaypyxlSDNxUt80jVPXCZU0KzIEC6aJ2OGBfNIg5bvSlKU+ZTLvXWnaWakywbN6QFdZJr6oz3+nvehFL2ru2g8++ODRjjvu2HxNeSXLpP267HTQQQeNbnvb246+9KUvjZ7whCeMtttuu7n+Nh87MQEQuO+3336jO9/5zoP0PXjnzv3d7373iACOj70+7WlPa/rbpt73jjvuuOaNvGc/+9lz/W0hMr3+9a8f7bDDDqOvfOUrzceK+aI7/VPfMYSPeM1rXtP8gwE+4lnPelYzGbX5Cz5gy+S9zz77DOIj4J0AZ4899mh8yJAyMU7oZ21yOIayD+waT+QDi+XL/ZAsbTznOc9pvttHWr9F30FP8EGQAM/jZCKIeMMb3gCJ5u/Z6DvZ75VyZPk2Zb+X5TBNYHXYYYeNnv70pzc3zyeddNLoFa94xZw/tL9NO564CeFfMnbbbTf/XSHHHI3uF/vntwdsgOUfVpm2DtzwLGE02iXS7wvM8JM4YSP8roHnzl6g3GWz6a/EkWsC164ONLjiDcSTAr8QOC64istNcEeAtxHQeQGPZZqOLvRJM5CEadJMpJa3E0GnT7qL9678PnLkMvIFP9Ok5yMTdQB4z2nycEQA//EGwIsDM/PbJz2NHLbFcT4yYUOgyx7I4IoHQYzl+siRyyiTK1g4IcD8rnRfmfg8BquIN7vZzZpHhKTdDwdt+R6Xzvz2SU/ifaEyYRsey+ZVxD5y5DJZDvjJ9nTVNZdZqExM2EziW2yxRRM80ab0S3/x3e9+t/mXgEc+8pHXGU/Uy3LktPQybdKsrp9xxhlN29wICAuVCTol746brvzMb590l0xd+V0yETwJ2Fo/ZXnHE0d4l7cuOViFFBi78mM9rnWlLUuZPml5pPw0aWWiXpccXfldvLfl68/xK/oW8ijbJd8kORgv3Ozw35C77747IiwLbJgFhmmaAIjVpwMCmQ0fEXjHQPJKOCoyXhHIitIegfsFHh0IcHxM4F0CiThfHmiQRiRzfOD3Ap8XOC9wEppX5VppcA1gDx+hlsSZrBhMDkwG3GqwHzJwp0vg6GO9UvZpzgkYgCF1Ay0eh2CDnXbaqbkr9/HXNLytxLLoi8CWoGWhYEBlwOwj1YXSzfW1KwEWwFfdzcvlSBMMgOztGQK8yVHOIWhuajTQgf9/2qUH7NHlx0p5eaxLcML/rxLArmWwH+Pb8YlAl4776gn9QgPfKv2+dYcsN2SABV8EPbcK/HHgQYGPD+Rx4JMCXaGK5OhVgeR/P5CA6fmBlwcClwa+MPDEwGsCCaYODATuFfiwQAIyZhSCOnDbwN6Qo+LelWrBRdMA9nj4wx++0d2KjTFIvKshj7Le8VhmUzwiA7KwWXmIAKtcwRpCJ/D3wAc+sAlC+J9OAgjeKNzUAYdrcGXwsBCZnAyWMsDiT4exTxs4obCBeghQRx6HoLmp0cDGrOICXXrAHl1+rJSXAIC/B+P/V4eyU9nGcpzzAhKyTQP2V26iDbB8kWkaOrksj8gBbjK6xklTYJF/hg6wWPd8eOANA28feEYg8IHA/Dbhr+KcoOvGgdsEHh2Y4cg42SqQFa71gT7mY1cnz5OgT13x6khX2IQ14CArRWgLsPJyfVl+Uzhn1cQl8KEDrKGDTwIRgCD31re+9YjHT5s6uNqHHMq3EJkMsG50oxs1K61dE/BC2nB80F94W9EXbNpoOj6GmriVx2Nbm6s9D9knBVjoQDtN0gd/eXTLW96yuWlZTStYvGzFnk374CQ9ZJ0RCHkzPVSAxfjmceFywdAB1nLJMVW7fQfBVERr4XlrAHvwNmWbXdoCrLZy8258GSoaBOFQ2IS50BUsHIhBw5C6gZZvQ/F4hMm9T0ACP0M9nloM86graPeRZxIPBlhMDjzyXcxHhPQZXtBhf0mXrZ3chg6wlHOSPlbjdQIsAlu2K3TpAXt0+bGsE8qxsZsAa7PNNmseEQ7xqDq3sVxp9IR/y3vMJvFiP6Zvu4LVpeNJtLiO/7n66qtHW2+9dbP6nsd7n/pDllmTAVbeIDekMiut+WkAe/D2W5tdGGje1UCdQeiAnF9ry1/LAIslcVY9FhpgUV8HPaRusMe9733vRmEGD30CEt5iO/TQQ+d4Wn6Nb8xBdrh95Nm49nXPnAzU0WIHWAS67N1pGy9wt1gB1lpewdIPYeMuPYzzY7nXEHwQBGy55ZbNChZjdqE+INNfzrR9jxW6vqA/xLfr67t03IcmjyhZAdt55w0PzeSpT92hy6zJAMvJaGhlVnrz0wD2YNJrs4uOTcqrIcAyCEIW7ooXutrj/isCNmmrr4UcsQd/LgywggWv2IPJYRwwWRBkLHSZf1wbC7lGX/NOeYgASzmXKsCi3zABtY0X9OKEUlewFtJLNq6LvrGvb9VufHXD2Tg/lssTAPCGHi8ssIIFDGWr3M5ypPU/0+zDsg6b/n3Mnm+CppWD7/QR7G6//fZN1eX8DtaaDLA06LSGq+UXRwPYg/+6a7MLjs23d2h9NQRY3rERECGP5/PVrgEWzrpNh/OlCy2+0wUYPJCetEIjD0MEL7Q3NOC82U9DvxqCR4JOJkxsuRSPCOk3TMjqudSPAZbBcXl92nNXEzxOW381lNcPMQ669IA9uvxY1gF7rtgaQJDvixGrZR+WfY//y+wL6I2xwxgCGZsLCTh5PMg3+/iqPrCcq4NrMsDqWlrv2yFquWE1gD34KGKbXZi8XG2g1dUWYDFZLjTAckWGR0cLpZUtiz34PANODxuwggVMCkrkYVK53NZSprmjxYkjzxA8usqKnhYrwFKn9H9sga3bxgt6ZJJjcmFiccJbiH4NKDwuhNamWJcVW/RIQD5uBWucH8tyQ0ufxpFVm4UEFJn2cqftbzwi7FphLXk0wDKfG0VvGs2b5og/hAb2QL/L2W/XZIA16RHHNMasZReuAezB3XabXZi8VtsKlisPTJYEWDiiUnYcFX8d1AdwRgQM0JJ2n3qTysATjp+7doMH6qyGFSxWEIYOsNDNYgVY2pU+AzIuyj5D+wB9h08AAENM3E5QtLmY0HdCXkwe2mgrN+MA9Lwsiz26/FguyyPlHByzirVaVrDopzzqow/2XUGlDr5LwJctRB/YBzsBQ+xxla/5HNdkgOXd4HwUVusMrwHswX/DtdklDxZaZnJxslkIJ+6bWQiN+dZVTpyKjqWcLPmLoA984AO97r4MsIbSjXLB51XxPRmdVd8VLO0zxOqQvAx55A6XFR7kmRQs9mk399GlCLCYwNCt/ajkcbECLAOtsr0hzk877bTRRz7ykSFIDU5DubnRYyx4XjaEPbr8WC7L+HAFi3xWW4YIhHMby5Wm7/F2JNB3ozt6w3cJBJwL0Qe+XZ/FSu9C97jK13yOazLAyncP81FarTOsBrDHQx7ykI3u6miBO9o8eZE3RBDBgON/wM4991xILjkYgCCLjqWcLHXiHscx6Z6iIXST28EufGDUFUSCB2BS4KR8k8rltpYqjZ55dGaANQSPuY8aYE2zGsMfBE/6Qr46xcZMHhzb/BjtMskxaVNmIROVNqEPEtT16YvWmfbIasdK/caacqP3SY8I2/xYqYu2Fawh7FS2sxzn9D1WoFgh7htg0bfpqwIBFjpX7+b3PTIeDWAJsIa4ierbdlluTQZY5WpBqZR6vrQawB58F6a0i6tM3o3AFZOKk818uWRSpS3+X+2CCy6Yigx1Fvo1c4OpvIJlnswoex8nwwoWAQNOaqG6sX2O6Aja6p9JlglmksOShyGCl8zPEGnfKEJfBEND8FgGWAQ52m8Sz+j4i1/8YvPdnnFl1al9BvrleKG+/YgJhiCr72OacW3TB9EXck4TOI6jWV5DHvraYtEv25vmHLmBSStY2KPNj5VtEYTk4HiIb+GVbSzXubLxCYr5Blj0W4D+MC3Q/0F9Vn1EOK0GByjf5pgGIFtJzFMD2INvJ5V20bE5WCBPEMEgXgg4WfHHtaeeeuroe9/j35gmw5VXXtmsevXdG9VF0faRxUeETozWUUZ1YH55pBxBwmLtwfrxj38856xou09QoixDBC+lvAs9Z7UPGHIFi+DAPuoq36QgVDl8w8k+YX555DoBLkif4bwcL9Sx3zCBM1EtZC8L9Ah4CLB8221Sf6TOfAAd0m8MgOdDY7HqeJNDgAV6XrbX5cfKctgoB1jYk7orMbgsefcce7XZStmmDbD0g9C3r81nVc/+6QoWAdZy+qE1uYKVlyPtMPW4fBrAHnvvvfdGy8RwoyNz8iKPsjiitsmF633AAOB+97tfU7zPXT5tsnoFOIk1J/P4sX2cio7FPMnhwAB1YH559C6PAAvdlHTK8tOcQ48ldoMG6vbZt2SwsJyOrUvOMsAiEFpIX6IdnLp9VF313fcxTYCFPQDb4sWDEuybBlh9+nZJI59DD/046TmB5TJDpO3v85lUh2h/HA3HIHoHGWP28VwP+7T5sVyGtEGI+fqAhfZD6S3F8Zxzzmn2iJZtIRt64D8W+77Fij7t29AjKOJ8PjcH9iPHSN2DVVpoCc43pY68BOpY9iawB/svSrvozLlrFByIbQ7OMpOO1mUyZEWgz2rDZZdd1vyJKbxYf1I7Xdetjyw61zIwcqJUB120nED5+xToSbur/DT52IO7VO8GqYvOJulLHpYiwOIvY9RBH9kIsJAHB+ym/UnyTKKbAywmFuwwaU+VNF0F0N7ml0d0at+3zziZ5LLSIcBCPoODXGaatPUJ4AHPp6HRp6yyzGdS7UN/IWWwL7oH9UVt47LLj5VtY6O8goUPAkr/V9ZbSef8F2bb+KafIpt66tNfct9GRm4cCOjn0xe0iz6LYG05VwbX5ArWptSRV9KgWixesAf7mkq7OFi8G6F9Jxkn8fnwZDDDRIUj6OMEuGPjy8C8IbOQtuE3t+9kWdJ0wpnEG8EFOmEfB8eSznz0Yx3sgRPVWZHPpN3mWK3DUR4mlct15ps+6aSTRuedd17v6gRYPB7EiRtgLZRP+qk6YnJZt25d709szGcFyz5jH8nC5wBriP5g/3MFy/Pc5hBp+V6pK1j6II9teujyY6V+sFsOsLSnfqEsvxLPCX66+h+yuZLb5+YFf6FfV9b5BljypJ1YwVpOWJMBVmnM5TRAbXtD0LTnnnteZ5AtVoBlAEA/IMDq4wSYmPk6MM7DyWC+ttOR0n6Xc7UNddDVFgEWe20IGKCnbF3lp8l3nBiIUHclrWBxZ8pEN83fchDQEIwCyjVEgKVDhy57+1jBmmQ7yrqCNclueRKyrbY7c/sN/ZS+ZV+jrfmAgYQBVh+Z5tOOE+N8Vi3m0940ddCBKzIe2/TAeGnzY2Vb2MiAnGtdPqCst5LOsZN9LfNFHn1PPdl/cpkyTR/V13iNFdP59AXton5ZwVpOWJMBVrlSspwGqG1vWBpnQirtUg4WdOVAbBvcfXXppINjI2Do4wSc4Gh/0mQ4iQ/rExR1OVcnnEm8ccfP40FgCN4y7+gJG+isuNZ3BQu5CFxLm2b6ppHx/e9//9Tfq4E3ggz+lqNPO7SXJ7chAizaxVYGPbTBSif5/CfaJFiKFay2QGwSX163/y3mI0L6mWNyPpOqvC7WkX6mfccFDti8zY+VfBmEmD/pESHlWaXt28elu1hH9OHY1m60RT9TtnF6KvnCH+oHveYLGtP2Xf2m9qorWGp0CY8rpaMuocgruins0bYHC+fO5K4DQggDLIOU+QhmXWjhCJxEumgxyKlD+aFWsKDVJ8DCmY0DV7AoA01lG1en7zX1kgMsV7DGOT54YJWIMtIY1+aPfvSjEW9o9n2tW1quPNIeNPoADhgbAtgeGyxkBat06NAl4AX7vG06zQqWk5DjwbZpU2CCA+gLll+Iv9N+TFTQ89z2hjjKMzpbiY8IGYMGDE7cbeNSP8ZHgnkrug30JfZByminHKzkugRtp59+eu+3nXPdxUjnIFjb0Y78I9sQjwjR8bT9TbvoszhmXS+GPsbRHHoFa/No7OTAXwZeHviAwDbgi4VHBf488OrAJwZmWB8n1wTyTvURgdcPFA6IxGWB/xe4PnBqwPlUWDkawB73ute95oInOWOw6NDM03YLCSR0BDg2Awbptx1xnDhGBirtL6Rt6FNfp+pRnmxfx6XDMD8f4Qtn5woWtMgDhwDlzMvsrPpAfxxf1GOfE9AneDFQ6lM2y2U98vp+agO96nAJVLD/tO1mHtRD2U95TEiANS4QhU7fFSz6h33fyb6Ntv3Gvkob2pH0tMAER7+CHjIq77R0xpU3UOTvfXgUX46FcXWX4ho6UOfauW3i14/xB+mf+tSnWlnL9rFAlw/wujqf5lG4dRfj2BVgKRt6ENv0VPKU/aHXfCSd2/LauCN9ibbVKWWz/xpXdzGuDR1gHRpM/iBw88AXBx4buOH5RSQSvDrStwjcKvBxgW8L3CEQ2DXwzYGPDtxmFl8ZR4E/aHth4DlmTHtcaQN4Wv5XW3nswWRU2gXHokNTZifHhUwa1GXlggkWxznJCdiWTkNHIk/THpETWoCOoJTdSWccb3yigWDHAEuaJa1p+bO8gYc6J7/PnSn68pGSNKTZdjRQ6vtpA2moG+5S+04+2C7L0+eRp+21HbVT2U8JsLAPb1uNA1ewJvUpdKp9XcFy4s30pYOMXX0rl5+URscGF33GyiR6bdfVof+f6KdH2souRx460L7oFN3a9zI/jDv8GHbh+3HaIpcxL/dB7dl1Y6R++vbx3N5ipHPQI2+0U8rWt79kfyi/8w2w0L2rV9JyK4DnS3kcMsBiu/6jAg8I/I/AEwMvDdwvsISnRMaBgaxQnR94QuD+gQDH4wMvDORTrpR7aqBwVCROC6SNeUHbnd+8CNVKg2gAe/BooLQLg1fHZkNOMgY95k9zzAO6jxPQcdA2jnEhbcMn9Z38PJZBkY6rbRJVVj9PUAZYC+VP+k4i2WHprMYFTrTvRvJx5cp2+pS1DkcDs3Xx1t58VrCggTzS4Xxa0D5lP+0TLNDfCSoJ9ifZjOv2ffuM/TLzTB7XmbQtP4l2rl+mlyPAWmmPCbFxti9p7Z71pR/DBqT5qnsJ2iyPKe1Z+gDr6gumfYRu/aGPOcBSHtowbfCIb+0ztnLfllfGJX3YGxDzJx3b5gx91qS6i3F9yABr+2DwF4HfSYwSYO2czkluFrhl4CWczEIut1Pklde2jbz5vG/JX2rzrEJsXh/CoQF0aDt1TmNw80l7Z9GVpmNZhrSBgmnOyzTtm0+a+pQxTVvj0vBnmcx7V5qyK1Um5Lzb3e620UQDrzgxHFGWSdshz3xloh5ODf3rBEhrj5yGN+3ChEU9z7EZtICuNLxbRjk4Qscj9aWpTJ4b5JBvHzNNgIUTMpjJuqF+liOnaU9ZSXf1PR07S+zK5wqWj7aUCTqm4c9leYImZaKMvOe0TtgVLHhXVuWgvGl5hzYyb7PNNs1Gd9qnDNAlE9cNPCjjI0LqwhugHOPSyqR9nFSUzwnZ67RbygT/5LHaR71SPtpXVq7b9+iz8sYRGlwHsJm82B+UhyPgeZmGhmVIQxf+kYW0Y4U00CaT+bm/5TTXlYk0tLT/zW9+88aeTODkK1NOw5/5XXLk/DaZaFf5ynSbTOgAnSoH+iAvy+E1/Bg0AAKizHuWFVsqR1M4fuSbI+C5wRwvc5A3hEzQL/ubMsh/lg/ezcc++hx4Uw75RFfwSX9BT8qRZcpp6uPHKAdwTtvs++ORMW2bbxpecpryAH2JOUPeOe67777NteX4GTLAIgBiRSoD52Vg5Dn7r4RcrqQjTetZp8/xpVGIVTDxGipdeinx3Gj01a9+tUHSl1xyyeiKK64gObr44ovn3gD63Oc+N/rOdzbEjJ/97GfnHkV8+tOfnlv+P/PMM+deKWUzolH3Kaec0nQwOgxpjnQ40gDlKA/QaaED8FgB+gDLwrQLwAf8ALyhBJ8AfMM/sKnK9LWvfa3Z6JxlYpmdwZJlohyALudrJwc8+meCxTEYCLTZyUcWTMzaEB7maydowANy4WgBV2CUiYmS9gw62voeARb6wQkB/KcdAP2h+h70cJj2Pe8G4R0o+x4f/kQ27t7hDb0qE+XbxpMTrCsXfccTusGJswkYma+66qqJ4wlbX3NN4wYamQgUoTPf8STv9FVAOxnkuMrYJpN+ggCLCaOt7+kjkI/JAjpMRoB+LPsI+qSTjSso1C3tpP0m+T38FUgbBBYEDT72bJMJvqbtexdeyMOKDfv16DP0gyyTfY8y87UTddv6HvmTfDljke/0oQd0SZ+mH7X5cvyTfUJdZV/+hS98gSabj+Pqy5EVIGBos5M3OlzHppPGE7QmyUSZae2EvQHsr98i6HN+8s+66fvYSR21yQQd+x46hQ51AO1EgMXLL+qnj0zQoH1oOp4MDBvim/DPbsH7tQX/h8T5m4o8VrAIN1lVEl4UiQ/NnpwQxxd4IY43D6R8GWCdGnnrA8dBuYK1VRSeiTeOwgfNzIQRGizTYZC5fNIxYTTlu9IxAObKkI6B0JQ3zXmZpoD5pGmDMqZpa1wa3i3TJUfOpyznQJccOR9elFveqWta3jma5npO95UpHNXMRRddNBMDciOZ3vOe98wcf/zxG9mJMgcccMBMBBNNWWQKRzZz7LHHTvzNCPsAAEAASURBVJRPmeIvb2be/OY3N7zGF9obejHJzvFeyhTBT1MmJuaZ888/f+Y1r3kNojb60QbI2paGP/O1x8c+9rGZd7zjHQ2/tIU8Mck0NCkLn+QdeuihM6973evm8rUHZUgfc8wxM/F5gzk7xSTQ1AsnPIid4tXwmVe/+tUN/1m+Aw88cCacasOXMnFCGlvCO/Y8+OCDZ0477bQ5O1FG3nMaG1MHewPayTQ6ymn7GLQPOeSQmQhC5tqkLgC/OU271EMebGiZj3/84w2NNjtRppSPcwB6pGMyaPpDztdOr33ta2fQIdAmU0w8Dd8nnHDCzBvf+Mbr2Ix6ynr44YfPfPSjH23K0Db6ynKQB6CTt7zlLU366quvbsrFBNUpR5ZPmahMGjne+973NmOLNO0fdthhc/2tTSbqkg/f8p7TXDefNHRjU3jDJ2OQPnDcccc1+cpEGdPwm9PqPcuR05S1DGloAV3pUibKo+v4U/g5md797nc3finLQToCq6bfY0vqUC7zTjr2aDXXGKPKQZry3/rWt1rtdPLJJzc2pe9GgNbUW4hM8AogawRLMxEwXsdmXM/ywTvlgTe84Q0zEbw0PMcN1ZwcyhY3FY0cH/rQh2aOOOKIVpmgo53wJ+eee25zTr62Ofroozfyb+ZTprSTMlHnqKOOmuOd/Lj5IX4oY45xccNg14ZcwWL5hyBo68TdLpHmjb8MP4kTNsLvmjJzua+0XLs68nj8OC38Oipwey/+HALcJQFE4UbiOe2jIMqQ9o6xK03EbBnSLs2b5rxMQ9t80tSnjGnaGpeGX8tk3rvSlOUa0CVHzoeXpZKJO+PddtutsUuWKQZUo5Msk3qMwdnIwbWYSEasnHBHOU4+ZbIu+veRF3W1B0fT0Avn0tClPn0nBm2D6Ed+u9LwZxnlgB55nNMOdcNnNG2Qb3ssw4cjadoiX3uYZnWE/Vfm50dH6kk5SpnMp1HqU9409AH0hG1sz3xWsdS1MlGetHKgJx4TcjdPPa4B0spp7/hZGQC0k2l4zWl5px72406Xx0vc6WY5cpp2sRv8qSfkJo2O4U/5SpnkPecrkzxYJsuH7ujD8q6d4AsZXMFiQy+6Nl/5qGfaPkMZ2pBXykDXc+jo3zySl3nvSkOjlAM7o+OsqyxHTsMrUMpBvnJwPaepb3/HFvRnVrDIV6achj/zu+TI+W0ywQP58u7KKfnwbj5p7UefVw7tmuUgDf/4MerQ91nBIl9+oUsfBChrPu0A6CHzbpr+SR/nb5jo431kyvKVMsETwOptBMyjCJyvYzOuZ/ngHTqsStHnt9hiC4o0/VY5tKP80W8oqxyUL9PQpR59lWuAvCMzPkF7mE+ZLpnQPfaR96x/6i01DBlgEQCx+nRAIJ9heETgHQPJK+GoyHhFIHui9ghkI/zRgQDHxwTeJfBmgS8PfF+gQG9kEwK857TXJx7tCBML1gJLogHswXdjSrswWJwkZMQBw6QhMOgBJyzzu460o1PA0QEGDG11bIs61jOvrfykvNw+ZXEsWXadup86wMGWQKDAxOAGd64PwVtuB+eoA8z5Os6cZ1q9wAuTkkGT19uO6p5HddMA9bTflltu2bqpONNTj05oXKN/mZ/L9k1nHso60LZvltc4Z4JDR8ig3trKkcd17UtfYRy08U3fUT7LT6Ld1Sb5WT741Fbj6kx7DZ4ZA/Q1A6xpacy3PPaJ1eTm0VwbDXWc/RD6dYzmOtiFx7Zc418fOObgjbLW00bkGUAYfJGXAR4JGvibLoK2IYC2PvKRjzR+h+92+Yh7Em03uBPsAcqT08rWp79402NfbYjO/nCD2denWw9dZVuRn32r5ZbqOGSABc/PC7xVIBsSDgp8fOC1gU8KzCtZr5rN5+Hz8YHPD7w8ELg08IWBJwZeE/i9wAMDhcMj8avABwUeNpveM44VVpkGcG7lYEFEBmMe2E5ifQcjE453SwQLwLiJw7ZoV+dhXlN5yp/cPlXLAEunzh0c0MYbskInB1jKtJAJtWlw9ge9Km/OHxc42Ta6Qrd9AiwCOSYQjl2TTG7fNOW1H2/tMfm4gmaZfNRmuU+RRt/j6mUaZTrzUF6TdpnvOTbExuiKSWAcD+iVcgK2VtfmcSRPm9kfFjLBLEWAlcc5/RmdgksB9E/6XFdw71jMfQb92pdKHg0Ytt56w4OcMiCSnjai/iQ7qR9uIqA3zRgp+fM8Hsk1exH333//JsiPR6BeGns0wOJL6/RH5aGSOlE2xmab78oN2Idz3/Y6YwO7TCOvupLGch+HDrD4nPLDA28YePvAMwKBDwTmtwkZPQRdzCDbBLp6FckGjozfrQJZ4VofuGGJIhIB6wNZ48x4dpz3Bjt07wq14KJqAHvssssuc47GxroGC4PRgUlZB3HfAIsJxwHtCsg4h25b1LGeefI6zZH2cx8knSdBnVZ+U6ek74RgEMb1IXjL7cAHj68yr1zHcXbpSzngZVwgltuBlnfEXXRzedOUNcBi8iEgdMO/ZfKxnAC4RmBHYDNfe+YAJLdFmknZNstrnLOChY372A3+LIc9kFtdZ9q05wRn+fnKhl6yfOgKWm3tZh6mTedx7g2DLwdMS2va8voOb9LK+o7FHGCh1za7Yhf+JgkgAGFslgEW9VixymPKdJde1Y9/NN93tamUJZ9//vOfH+2+++6j2972tqO73vWuzQsy6iKXK9O88AO/yFb2b2RjZVV58K3w3iUXtL1mndwebdAH+9ykWQ870k8ztNHO1xczPXSAtZi8DkZbow5GsBJakAawB2/GZLswsHQsJXEcXJ40dI7TBFgOOgfjOOdiW7Tr5NXmYEs+u86h5+RHGXjJskvbR4RtvFlGfqAjTfklbyFAu2DmDXpM7l1Oz7bhpU+AhZ0JlNhDBXTRbS4WPznAck8IbyN1QZvOnDidSLvqduVnHsoy9C37ZnmNcwIsJpE+dst9BntwrjyZNnn2Cft4ab9cflwanWAfb0I8tvXHcXQmXcvjfLkCrC6ZtJ9+AlnKwEL50DN+zDKuOHmdY7aP+X0eEdKmH98sbyJo96yzzuo9digPDQI2gE9LkBcvpshS55EVLN56JZCin+U+SJ+070HAm58u3VIm+wvOMzA2AMZJX6AvZVtRD9mWC9ZkgLVcyq7tdmvAwWgJBgVLw06A5nNkQnJgcq4T7DsQqeukhqNg4mCi7ALboo71zOuqMy4f2Zz8KFcGWE7241awdGzZoQ3BW+abNtr0j77UeS5PWr3ACwEWznXcEr+TuAGWK3Ml3bZzbOakTzBKeqkDLOSTh5JHdKcty2uc+4hQG6q7trJc075cJ20fyOXJk57lx9HNdcu0E6PyeeyyfVmf87PPPnvifzKiI3lmcmSD+BCrNG38lHnK2CWT9svjAF7bdA9tdU4Z+mTpk7J95EVf0BUIwAN6MeAoA6zLL7+8+SwDn5LoA96I+m8L0L397W8/gs4kQE/2g1IPpWyWU8dttO2b6i2X0f+VOsxlcnrcTXkut5TpNRlg2aGXUtG1rW4NYI8dd9xxo6CjzbFJgcHowCRP56jjsFzXsQxwCO4mOQHuMkEngi4H29Vmzof33AdJZ+eq7DqYNt6UPzsm017Lbc4nDR0Cn8wrdHD28ljStW14cVIapysDWwOsvitYtAMamBMos4o1LsCSZ20I7/LotVKeSefjVrAmBVhMHHkFq0tPTBzIqn2xB30j9xn5hIblPLaVs/y4o/3OidKVAfPH1fUa3zTye13mlUd41g5cYxWr3Bxe1hnqXFn0ISVd+0XmrwwsrINd3HtFebC0Kee5/1HXFawuO8EDtLAnNy2ln+NxH1DmN5ktP37XzwCLIre5zW2aPVklv2X13A+RQ/1QrpTNfqOOS1qcQw+wrzYnsz9+rLhvgEX7jBX7qbRK/2X+UhzXZIClUZdCwbWNyRrAHnxsMNvFgZsdm5QYjLmsA7ivg6FuHtA4Aid628hHBq7lPeb2c9k+aRypdCiPA8jOVSeHM8X5tjl/y2RnPclR9+Etl8EG7IUpZcWBtfFEXcsik7xpy0zbtHpnzwpBUt8VLOsZYEGPje7jAix1lvuU6XE8ymvbkb7nRFJeh3YXXVb10BW6tC+ou5KOK4C5HIGo8uTy5Kl39Emf6KKb67WlDXbph4ByOt7a6uQ8eMFO8d3BnH2dNDrSDlwkwNoUV7DQs8EkNgBLG5WyIq920s7kZWCsqR8C6+zn0FN8P6spXq5sZRo5bbkcYK1bt65ZaeaTN+Mg+y54yvLlvgcNx6ZjtY2ufq8tCKK/QyPL20bDPMeaujJ/vv3f+gs5rskAiw5dYeVoAHs4wcpV12DhOo4rDxon+74DkUGdBzSDWBq2n4+05aTlMTuWXLZPGnq5fdI6GuojOzohnwm4bUJTfidd6lGHc6+RtxCADpNrOV5wYFzLPNuObcOHjm6crnS+2IC2nNSl13XM9SzDChYTTld75mtD6snjOPtLvzwiP7ZyIimvQ7uLbtaTNjSvpGO+5bAHwY75uTwyZvnKvpXLTkprCwMs5VT3k+o7HvPX5dvqwLN24DoB1kra5I4+8xjgHJ5ZLcmgXchDHsrpxyxX2sf8LjthYwIvV2XKAIsvw2MX/i5KfUuz68gKFv0n63zzzTdvHs1eddVVTTXGUZsN4Md+qB5sB9m8Rl6fgFwfkutJjyMrvH1XsBxr6ko62XbmLdVxTQZYdOYKK0cD2GO77bbbKOjQMWUnIMcMxjy5MLDYAMpALJ2edfKRurkP4AjGTRrZqegIcvuZdp80TkU6lC+dK7Ijtw5bx5Fp48xYnchycL3UTa4zbRoZcbxlGzqwNr7UC3zggAFt2da+emeS4JFA3xUsg04nfWgTYGH/rhUTdAZk3du/xvHYVGr5kQcnkrIItLvoqid0pJ7MK+mYL9/Yg9UH83P5cgJfSH8gwKKPaW+O9EltltttS7tSAk8+lmorh47UAdcJsGhjXDvsNzryyCN7jfe2Ns2zD3s03yP59hHz5LXUP3bxbVjqgPY561LH+uZxRM8GGznf/iMPOcCCFn+Pdec737nR2TQBVl69oj3sui5WsQiwoBv/EDH6xCc+kVlp0lyzHyJHlq+UDZ4n9RfqAKWPaTLjB3mnDbDUlTS6aHt9MY9rMsDSqIup2Eq7vwawx2fj/xazXRy45WCBap40mFCZ6HBspPtM0GWAwwTpZNnGNXxlp0IZ+WsrPymP9vOgJ52dK7SVm0mtjTfKyFNuL+sm588njdx8OTrbBTpOuG2TkmXhQxnG6YpJFCcMTVZKxk2qWQbL5QCLR4RA12NC+GBSoD1BHp3IzO9zbOMh14N2F111gp60o3mZBumsU89ZXWgrr4zSoG9Z37y+RwKsvIKJ3qZZZTTAoj3/v7CtbXSkHbjufry2FRTr83+S/Adl29iwTD4ySb/1rW+9TqBn/ba+TP2SN/IMkEr9o2f/45EyIHn5pg961oeWgJ3aHhHaf9QPG+fVK/2cPrjzzjs3gYj50uw6Uq4MsCi7LgIs/k/wnHPOafTUphPksb8iR9ZB2ffoL5N8q34v+8PM9zQrWOpK/ySd+fZ/6y/kuCYDLO4WKqwcDWCPrbbaqrmLkysHi47FfI4McAeNDkyn3Ocujjp5QE+zgmU928989U1TVydFHWjqaDjPThjeuhxdm6POuoHWQgCHyaPbcrzowLRRbkO9IJP8ZSecy5JmgiBIwhlPs4JlcIN+BPoK/PKHuG1QTgCUgU+wTZY2GjnPyTnzkK+jJ/TRNnGqJ3RkXzAv0yBtvuWwBxOt+ZZnIidPvZNPndy3yEMP/uE1511ggJWvTxNgMRbRAfx0rSpCG93ncY4NgXEBljdSXZvh0QP7oQxu6BM89vJP1ZsG4kcbejTfI7zZ381Tv2W/xi4EBPQn0m3l2vogdKlT2ol8x748sKKD7PQpg1ZWmV3ZUl7qdgGrifSfEtjoTv1PfepTzaVSPjLRK7wCyJfHTZtsjI0u3UJDmaVJXoZpAix1lfsStEr/lekvdnpNRhrLqfDFNuimSB973PrWt95oIDhwy8GCfDmIcPDiZIA+ARaD2smKOkzw0uG8BByH5QkESLc5n7Je1zntZ4dSOtc84eBYdRyZXuYp52fd5Pxp0zha2mBVqBwvOvs2vnTA6MkJRlu28UCgZIAyzeRNPfpG1iP0CdK6bAkf8pR5gc44HnPZnDbIy6to+bp9t422/Qd72bfQXRuYr6zYgyDEfOtIM8tInbIc/9sZf0Q8cawgHzbJMI2NWClhImd1eVKAlXmmP9DOuADL/WF+WTzzSPqSSy4ZffjDH55rV79QlrevtPVl6GA77cg5IK/qe0PuhomcgMDyHrP9qWN963HEpgYbOd+60iKQYmyyIkeAhX65xpGgS71kGmWaAKttBYtHs9CHv5122qnVx9GX7K+0m3XQJhtjw3FS8sG5Mtu3yzLoU9uV18pzdaV/8nrpv8xfiuOaDLBKh7MUiq5tdGsAe3z605/eaCJwsDiYc23ytKGO0RWsPs/rqZsHtHdZXXd/OIHsFEnbfuarb7psH150NNDAUelQ5a2kDY3Mk9fbJlSvTXOUnyuvvPI6surA1H2mC1/aTBmyE85lSeN8DVCYVF2ZKMuV57levkab9p2cT7ptAiAfebrqcL0LnJwNEMtyyt9G2/6DDbWjeSUd89Ur56zEmG959Sw98qmjLS2njvkPunEwxAoWEz83P662tLWX+7vXGc/jAixlKAMm61922YZ/ZnPvl4/PyvLYEH3BQ9tKI7bTjtJWv+rbfOzB3jCve8zlSJtvPY6M2672uS4PBEAAQQc6dc+X+crZFGr5Ycwic1uAxU3RnnvuOXr4wx/e7GnNfEsKGe2HyJHL5GuWZ2y0+Qmv2zelab5HAizaaBtDlvFoO6V+y3Fi+aU4rskAazkj2qUw6qbWBva43e1ut9FKiY6NQV8Cg9FB46Bikmb1os/dDoM6D2jqElxJq2yvdBzUzY6lLD/unHbK9tsCLJ0Ek78TeaZL+1kGr2XdmDefo/rla8/leBkXYGXZ5G+cc0S2HGAxqedAl+v5XFmGDLDGBWW213aEB2ynrcoyTopt8tt/0JH6Na+koy3UJ+UJWsy3vPUzP239wf50xRVXWLX1iC20jQXKFazSXpbjyGTPxO8KVpsdCSqQQ11Zf9KnGgyw2h4Rcq38dIF+oS3AMthoG//6IfniqH7Vt9ewC/IqS1u5NnrUL32ANOXJMUfACqDbHGDlfOu2HQ3AlLksw9/msGke3kv5KIut7IeUyX2b8sosXQIsxkkX2IeRvw0MHLVfWxnz4AU9lXOG48tyS3msAdZSaru21aoBBkDbHiwdVVkpTxpOFgwsBmOfgcigzgPaFQhple3hOHQqXMOJ6BjKspPOvUvN7ZfONTth5NLJZtq0XzozrsOnd4W5/LRpnStv5pUOyna7+FJXPiaUVhsPOVAiQEY/0kUPBx10ULMqUNbFVuXkTxn6THb6uR58tPUp8mwzl5+Uhgf6TunQrWdbbbTtP+iS+rlPW9+jZdUr9iAAKfXqufahftm3yLOfs9piHfJLmLSCBV9vectb5jZ2l/UNsAgGadOgKJezfXXlNT7YySqdvJrvUVplwMR1N5pjG1ew9AtleegbbLTZKY9F21a/8m4+dkEOZfGY+yN1rG89jtRtG7fWlRYBLmWRixU+V7AYO/Qj5cy0c1p9GJDlazkNj6V8XMfm9sOyTJts2KDLhtBTZmRqA1awgD5PJrCfesq0umjnMouVbpdqsVpbIXR1WCuEnTXPBvY488wzNwpa2hybimKAO/h1igzkPgEWd9HZSUCTukCXIyjL5/abilP82Pd0UlQtJ0Fk1wl3Oag2ZwYt6NoG5/MF9fvlL3/5OvRw5OMCvywbDk9abbwQYKl/Jg+AiR1gEqVu+Ye5XMuBGecC7TkpmeexS2eTeLR+eeziwXLoCGjjR52oK+zdZTfzLct526Nbadp3aJs6TmKcA/RzJi7ouNKz4crGv5MCLCZzZGvbX0WgzKTIRG4Q0FZO3WSe4YLPtjBWkbMEaMMbdisDJsrSZ/kTY9p1xcbAgxUvV9I44j/GBVhtk7a8qm/5Q5/f+c53NgpAuJbLkba+9TjiA7z5yvnoh2sgwNjDz9EO5dUtQQQ2Vd5MI6cJsKSR88s0PGa+vY6M9kP0T9+S7zbZuAlinHQB9ZENntrAAEv7tZUxD1055szjCM/LBWsywFrOiHa5DL2S28Ueu+yyy0YrJQwWBnAbGHTgIA2KKMtgnHSnozPQSUDflZAuR5CdCuVxPvMdtE52OkzokTafcxyVsuMw0IV8cx0oedqQO1yApXxMdG3jpW+Aha7gvwtykMJdOODqhMe2SZR6BmaZNnrraq9tAqDuuDqZdpmm77XxYDlt2MaP+nWypT+aZ32P5ttnsQcflqTPGCxQ1glRmuTRt6zPOQDfrBizUb5rHxa0QIPeDTVHzbnXnMw9WoYj4xDeCLBYbYPncQGWupIG37UjePjGN75h1tzRABwZ6BtZB0zEfL6BTxfQtrxxZCUN3q3vzdm4AAvblZO2+oVWBmSkDytLWznqmF/WzT7Aa20BHgGWgbEBFuWRd1IgQoBF/ex/bCsf4RF+xvkd5VAPHO2j0tJXe14eaWMcL+ge/8wboJOgTVfUafNfk2gNdb0GWENpstKZtwYYAOXbajg2HVVJGEfCwGcCdlBBo88Klk4sD2onyb4B1rjJsOT1qvhwn3+fwTUnu+yI4EW+KIPsOi95KyfpLkfdxhuPgk477bTm44Hw0wd0mqVdrDtNgCUt6+Yjk70BbhlgORF2BVjWy/ToM6WuvN6lM+o42Vq2zzEHh23l7b9t/KgT+yF2M6+kZd+wz9DXCVoA+xNp69t3yGvrD+qcP/hlH1YOUKgDOBbaAiyvG7y0TermMVblt23TurpRV03jsz8E9wRYJX8G3gRYyO851Qw8dthhhybgIKDAVxDwbbvttg1l+xN6ACYFWCVv6ld9N0TiBzld3SXPesqIHeHFfOtxpB+UwQz51C0DPPwc9oGOKzyU7eP/sBk2mQRtMmIHZLAflmXQh3nSN8Aqbeh17OcYMC8f0SfbFLo+vZLLtumK69hluWDolnlX/uTAXwby19wPCGyD34vMowJ/Hnh14BMDM6yPk2sCfxZ4RGBeyrhdnJ8byHOEiwLvFDgVlANjqsq18OAawB4EANkuDJY2R0TjOgicJxOjDggHgyNtc1Qy7YSkkyCfiZpB3rX6RZ1cHieSeZV22/Giiy4affzjH5/jyckyOxXS5kMjy64OyMtQ8uQ1+My0cGzHHHNM89iEj4by5ec+oHznn39+q6x9Ayz4L3m3fWSgHQMlj06YBlhtG5mZHA0+pcdxXHvwUU4Ak+qwD+ikk07KTcylu3iwgG21ya/9fDSC3chrA/PtM+iMx2CAdspp2yWv7FvkwTf2I+BgwjXQ4Jqg7rsCLK4bYHm0LkfzGJMAdNraUTf286bw7A8BFoFaObnaPwiwAAMm0pTFP9AegRN8UJ5xwKofYHn5McDyvCk0+wN/JW/YDHtl3VOcc1bptJN2sJxH83M7bXbiujeQuaw6ZfXK/sN15FbvuXxO4zOVN+eXaXmUZ67rV/SFuQw+FzRPeo5R7Wy+R2iqL/PKIwFW18eDc9k2XXE9y5DLL0V66ADr0GD6B4EEWi8OPDZww61WJBK8OtK3CGSEPC7wbYE7BAK7Br458NGBjAjwlYHCMZE4IxC6hwd+JPC3A3vDJINKiM6oIzNvyCOD/rzzzhu7/NkV+Q/Jx3xoEYy85z3vGU36c1D4P/HEE0e+Nt3WFva4293uttFAY1CUjs26OgicCU7RQYyDob2uQIn6OoncB3BSOK0u5wQvOhVotE2Gl19+eet+EfjjbpMvJAO2n+nBi/mUybLLZ75umUyDPIDyTsicUw984AMf2LwdxJ6WPn1KGrvttttGdoEm0BXI0FbmC4fb5eBcJTGw4k6TidEJ1EneVYgNLY8a/nNgbX7mq01G+CgngFwn0zH9ta99bcT/vZX65zr82/csn4/0K/QEryWUvMCXOi/Lko9dnUxJs0ID5DrqOcvY1lfhG53Lext/6n4hARZ8Wp+Ari2Akee2sc638ZClfNvR/mGAlQNwAiwmZAB/gH6cnFmNhQ/Lyw9jH92WenDstPEGX/LeNBY/yAt9EKA/k2c5j9k+TcHZsm03htQp288BlvU5ku/KYc7PaXwcepkE8ijPlLevOb7li+DJctaTvmWta77H0l+Yn4/YjdVP28jXcho+1H3OxwbLBUMGWGz3f1TgAYGsLp0YeGngfoElPCUyDgxkher8wBMC9w8EOB4feGHgTwMp99RAAK+yU+DrAlnffXsgMtw3sDf0WTLEmEcfffTo+OOPH3EXLzAI6Cx5MDBgP/ShD83dGVm2PDKg+fidky0f/Dv99NNHxx577Fzn5dVbBzqO5LDDDhudcMIJEydF6rRNAvAAr0wUF1xwwUQ6Jc9t50xe8MRGS1aenMzaVo8IrC6++OLmO1eWK2liD/dpeK3tztFrTA4MGpwFcjuodBzjnIwD3YEvTep21aNOdhyky8HO14/POussyc0ddeJOErafBz1pbYeOkN32LOd1CZc8mV9OqNACcIZ8qRkZfVTD3bZBjvU9Kh/7VtrGCzq3n1qHI3xl3dKutHI50rZtgEUejzycQJ3kkT3bhnP6tHannqDTb2uTPPVqeY7UUU85n7S6kpd8Hdtm3vM101204SXrqbSb9TmWOnW8eM2y9q1MN/cty8E3wZX6s496naPyGiB5zXOue0OCHUt9c83Ahbpd/UW9t9kFOeiz5T4s+gfloY/+XZGiHQIs+izgjZhfrac8e7ssr9zQaONP3uxTDdHZH9ovZcYu9M1cnnLSsXybrG12oqns32xfP5f3X3GNfGSyHcvnI3bzUXzOL9PymGmV/SuXsZx50rMvWtd8j+hLH2deeSRgxi+27eHLZdFV1r3X2vyX1xb7ONXKzwRmto/rvwj8TipHgLVzOifJ/yBsGXgJJ7NAuXvOpgmgPjmb5sA1Hp4TwHHt64H5ltA2rju7xbiOshtuJyIR0KxXe0dz9tlnN0Zjcud7P7vuumvT+egMp556auNc2XxNEEHHZbXGZ/x00qc97WnN/2bxp5i8Gkzg9OQnP7kJFrgjotPZwUh/9KMfHbHScdVVV42e8YxnNH+meatb3aq5w+ItOmh+8pOfbBzHQx7ykOY/oXAGvEXFhtT73Oc+zcQC7TPOOKOhg1A4HCYgnMeTnvSkpixfMia4oXPRMXUqBIMPeMADGgcKvzgj2oV/HiHd8573bGTCKRDsUZcNhrRPWZwRwQJO7x73uEcTfCITg+SDH/xgc2e93377NQ4LnRFAUhfHh6NjmZ7JEUQ3HBkYyA9f5IHkqTsGIZCdEM4EmWgD54jN3I+AjH6/iXx0AGIDHQEDFtRO0GOlJNuMujgMjpQD4Bda5GU54AWeqQ+fymcQgc7ud7/7zTlb6OlcoKeM0IAvHIW80y75uW3agTfbUz7app5y6NzRJY+EKMcqFhMlX/Pmuzd777130z70lIn6AH2bDw9mmeCVsvQ5+dY21KOPmE85nDrn8gYPoBM0vCgrfRG68EE9Jz70Szn7BryhI3RFXdohTRsA/QIdlzJRn/IclRU66Ml8eYeWm2vhxeBCObAtsso7MpVpaZd24hzeOMILCA/IAEBHmRwL8Ctv3CwB1FcOaVEGehzlyXrqC77QLWAfpU10hnzYgCM8ZJm8jj4YL4xtxhuBKCsNXIcP6jOm5Im2nCDlAdrIBsCPcmTbMLniy+BBmaBNP0Emgij6BmlsDk/4Kc5pH8DvoAd4MMCCnnIjp/0MfjmnvIE+15QDetSFd+xFvnaCHjeZ1DUfuZQR/gDKZ1nhFb1xBAF4IE1d2s/59kMCrGwb8xlX6AU+5AV6tAE9eAJKmdAvoHyk1RH8moZmLoNcnANcA+AXO0tTP5TlIE09eONo3yIt76QNJHlcv+WWW24kk/LRDm1wzGPI/IapZfgZegWLFakMnG/4kMVvcj3/+W+ympUs8zlmOqbJL69Boq0N8oGXBrIKJl5D5hFHHDE65JBDmgAEo+IcCATe/OY3j4466qjRO97xjhF7ZwhyMOi6deua/2fC2RKAPOpRj2o6BKtRGJ3gZI899mgM64oTXyY/Mv7tHUdIAMLjNI4PetCDmo76zne+sxmMBHf3v//9m0eFBE08KiNQOO644xrH9bCHPaxpn9URVo0I9lhZgy4dk+/FgHwcjs5GO+973/uax3I4G5wEd4H3ute9GtrUe/vb3z46+OCDmzbe9ra3jd74xjeOTj755NGXvvSlRnb44Ps2hx9+eBMU8hiTx3xMyPxhKjzc5S53aeRg0kZ3BFc4WFbK3vWudzUTEzRxOASdDH72IgEEcp+NP3cGWAVjheu+971v4whJA/CN4wTQLwjgbAlWcCC8LUQZ7sY/97nPNQEhOqEMbQDYgUARIIhjMgA+//nPN5MA6VNOOaXhD8dEmkGN0yANcO5dNO0R8OKcoAt9nBbOBydE0IpM8AMgB5MBdeDLt7auiiBbmQj4oQfwOArACULDSQm9ZJloE+eBTOoJO8AD/MI7MugU0QvXCAi4SUD/0KCPUB86gDJBA+Cun3ayTNRHV9THFsgFIA/5lNdOTCbo3BsTZIIWgA0Yf0x62gldoUN4YhJ3MoCGMpEP0N+znZh46cMAY7WUCR2jj9z34IcJDOfMmAeUCUdt36FNZaIMdoKefU+ZoJ3tBI/QLu0EH+hGmbAPvqTse8gEP+hUO5HefnvuZzf0TccT/EDHvofO0QMTmTKhL4B+5SNCbUMfM01/Ry/YJ8v0mc98pqmHPtCNq0XIB68AMsErfow0MsGzY49y9FWA/ufEat8jX5mwPzxnmbjRpZ8gE3Vpi75HfwI45xrtcx3b0I8vvPDCRj9cRyZu+rDBueee2+TTn7Odzo4bcAAetJNjC3nKvoePpj36jX2Pc3Xq50agV44n9MD41E60i0zkUz73PfwF8xI3q3k86aPQr+MJOsoE7/BGO0ApU+576AXA9wPoDD0B+DTowxcAb/ov+AeQmf5EfwR4WgMgEwhQj/5Jmdz3skzYiX7Bl/0p43hUJujQl5AZ++FXsYt24gguFwy5gsXqVflwl3PyM3jOapLBUy5X0pEm+eU16Oa6nGf4hzg5KGXQ5jV77bVX4yS4e8eJYGA6MgZkEOA07njHOzZBBM7p7ne/e2NABikOEyRgINABCZIInFjRYeULGnR2HCvBiHDve9+7CdCIyNl4TNADL7bPnoI73elOTYdgMzLn3MHd4Q53aFa24A+aOMb9999/tC4CPwa6dwV0/Pe+973NBLXvvvs2MtA29OlkDHYmMzow7bJiB690zh133LGRixU0OjUbTAn2XPVgUOIgGWgMUhw8RyZD2mTAr1+/vhk8BIIEYgDBI/ohAGQCgw9Wl9wngZNATuTAaSKTQOAIIL+AXQAGKfwgOwOdABe7cNfKYKQNgL9+IB9gpUYnhy2wJ8AKDRMmeiCghReQfGSkDVYyAfRHwEqghB2h72MkrhP0ESy6PwTHQ7/AOUGHfSWkeYOLu38AHeiAsAMBLg4OmXBAAK+dZ5kIlClDwI99gQc/+MGNQ0TH8I4MOlP6DKgdDAiQGZnQDaBM6AO6yEe/0U6UQX4cGW9HOtGTj53oO7SrnVgtwz7UAbQTafoFgbLtOK4oD09M4vQHnDX9TpkYqwBjEJnIB7AnYwrbMK6zTNiE4AD5GGOAMnFTAGhjZeLmQOdMQKRMlGUPFGOdgDV/YoT27W/ojv7AmOVmLduJmw37GEdsiT5Im087yMQYxJ9oJ+3BdfhDDsYT8iE3OgbQOe0zKSmTQQ7nlAX8myn220EboG/iT4BSJvRLv6FvOxbot3k8cZPK+GX8Iw9jW/kpR18FyJMP+x75+gj6ITJmmej76BgZkI8bV/oeZeGfMUGbpF2Z5uYPGgRhlKfMOeec0/Qf7HRV9Gcm6H322WeOT+YHngLQH+178Eb6/e9/f+MbKA8gE3MA9OnT9jH6h77OFTVsbd+jLjpkzsE22ol8ZMKmtJ/7HvMRPgXd5fHECjk6YGwjk/2QcUBZb0zgDyhlyn3PGzP8BUDfQx/cwNBf8EfOO8wVBljyiUzrYux6g8h3yYDSl6N36ua+l2Wy72E/eKKPAMpEmr4E74wz5jR8AqB82GC5YMgAi9CVFSZmxWalKI7MSu8LzMASAhvhdw3cEBJvKHfZbCFCXa4J0Lg6kOCKa9y64Rk2rC1vqJuDqLg0B5Sx3Fwmqy86FTPpdHvttZenc0cMBzgZeoGBsPvuuzdBg4akzBOf+ESLNEcmOJwRUbVL6EyuL3jBC+aWcSkIDYE26cwCA+WhD31oM4C5s4NXnRlldFwM4Gc+85lNRyz5VQ46LCgwcDIQmD3iEY+YG5z5GkEUmIFBhMw4UxwlA5KJgkGDY/GxHbpi8sU54iDkB9kYqARl6ADnAzBYdLzKR75pZMW5QocBJT3yXaanvPmkoZ0DDicT8tEpjhzEoVlexyEv8Mt18kmDTlrohrtr86WHU0A/fC4BRwJAT1ngEb7y3SVtkK8+qANdgHzaL69TljzatZ78Qw95cYbeiRIkcBcvv9A2LQ1WIbWL7cM3TosJSRmoSxpbwoP56spzrgkETfQVwHz6CxMBbXFEb/RRypYyoUNkMp+0j0nkH9rQcjJQr+ZzjTzAviGvOXCGF/MpC30g9z3OlcM0PNKX5ZF80vJnPkd4zH2SspzDF3ThFcSmZ599Npc36ofkQ0ce4Fe68o4fAtCTNOEPsB5pyqnLnE+afCdO+jY6IBiTd+ozJvCxyoce6C/0ccqZjx7Uv/JR3zTXsl6Qg4kWX0qa/kPATRlXOmhLYFxzHX8J7/hFyiIf/Gg/jpzLF/XtD/CQ80mD6puyyORYU+/kyz9p2gWoq3ycUx7kOkeBtH4w55f2sDxjksCHG1m2k2gPedfOyAqY35a2f6sD+BWQCR7Mg29ll7b8yit2B8w3DX3yLEd+W5q5hLmjlInyyAEdeEYHZRlloexSw2+0tvCWCYBOCDwgkJDxEYEsN5BXwlGR8YpAlhC43dov8OhAgONjAu8SSKj98sD3BQKXB7K++LeBjKJnBWK5zwT2hmzA3pVaCnJX+oQnPGGjqLwsRidkkNNBNDxlGOh20LJO1zkdkQknB1dlWTp4GVyVZSadT8sXAaPOGNrccfPfggZX5OFs+Yd2Vmd4JJm/DYU9vAuhLIOFActA7gICKQPX7FDJ5zFVF+jk8kCnrDot6zo4c59hQJtPXSZ/6CEfd486JRw2gE3Qx1Vxt2a93L5peNMJKrvtWg96lMNhZQdJPkD5XFbHJz36D2VYcVgXwTE61PltoLDhl3qUy3bJ1w0cyrq0Lc+Uh0d5yPVJE8AYYHmNlQ6CGXTIkX5FfzaIpZx6VSbrcjRPPXpNHtp01lXH1UNkhZcM3uFPujuGdskLdNSvNEu7mc+x1Cll955dccy2pp1SvpKuAZYTEbKpz9ymus95prGJK8GMt3LM8QiLfuGKK/UYA06C0uEIz+o/55v2mvYjn2COfgK44sPKETcLBF4Z8L2A41vfSN9DFwYEbXrQblwroa1fOxakSR3KSUcZShtRDh+g3+BcwDbqwLxxR27M8UfczJWgnfvQk0d5hpZ9zfHNPAHflLGc9WzbstY13yO+TP9nXtuR+ZMxx81zGyhbm63koa3eYucNGWDB6/MCbxXIcw1WlR4feG3gkwJdoYrk6FWB5H8/8PjA5wcSPAGXBr4w8MTAawK/F3hgoLB/JB4cyAad5wb+UeCG28lILCXQUVkFyIHTUra/qbX12Mc+dvTc5z63cYLud1GGPAgcrOMcAU4dh4SzzQ6tdPbS9+hAz+1xjXpAV4CVHQd15ZE6ODRWWQhYyGeVEXAShj+CThy613L7OhicjXRtL19riMZPlwxchy560dnr3KXHdVYceRTKpAMtJ13pc4QP6mQ+83UcGW3Ir9egl+tAQx4sw5G6XQEW13Gk6I/J3BUs8gHptTlT+4xlNtT4TR31YD7HrjoEWLRN3+gKsHLfyzRNQ1vnbx5H9JR5QWfaNZcjTb/IOiXPdnMd7FgGfPSfskyujw7b+BsXYNGGdkc35ZijjzP55mBHW5VtYSf1D18leC3bMwdY2IfHcayOE9jlNqHluPbIihu8XBU3O2WAVY4D25SHzBu2Uwfmt5XP5bye7W5d7ISdS6BOW/tlOc/dVsKjwhLUvbYor+dz+GFeyzLaj/RJlEcWeLRcKZtl22SjPvmW4bwLtCs2bgN1O42u2ugMnTd0gPWjYJBnXTcMvH3gGYHABwLz24S/inOCrhsHbhN4dGCGI+Nkq0BWuNYHblgKiETANwLvHcgqGc9bvhg4FdhRpqpUCy9YAwxYBgp3ndwBGwRgDzfD0kifwaLDpHx2GDp7aXM9gwO9HNRuiC0DLB1HnuBwIvBsGzyCwNHzRijl/DaYDpvJkJUjJh3/Wy23L214K2W3nHwjizyVzoxr0rKPWzY7HvZDoCd1yCpWCdSHVrZLLqPOddpeo548k0e78KCuLEcARX7bChZl3MxqgIVdlKnUkTQ5KqdlvNamB69Zp5TFAJCAwmDZOt5Ju5JifnmEdskLZeBHW3FOWvk4z6AtzOOctzsB5SINjwZenAPQpe+of/ok49C+gx1Luak3LsDCJgA0qO+YazLjhwCLcZ7lk6+yLfiXF+vno7ZRhxypk/XO/jr4RTZWOjLYx13BYgzS/1nhobx8tekBXl2lyTRJw3PWPXn2EeoI8G85juik7YacOnmMU59z0LEmzXFHaLMFhn1mpS9Th33o2UfknTbtn9mu6sFrpS0t6/WSd+TL/qK87jkrj9BmlbIN7FdtsnW13UZn6Lzf9IShKa9gehp9BbO4qlljrxLOzc3K2MN9bAiuI9C5tilDx8m1PKjId2WrrZ6DrewDODiccOmU2spbV4fIChaPIv4/e28CbUtR3f931j+J65eIKIIo42MGZRZQBpGAQgQTFFQiihKNQwxJnH6JJiZBcRZBQxAFjYgPcWISRMAHMqvMPmYewwMeyKAoDvxF/2vdf33qvu9h37rVfXruPvf0XqtOV1fXsIeqXbt31alGUfAGqXN3oBFAiaMcMMD4pxhglbAUDPWJdikqtSU8KCulpzykCcL85KUttaF8XDXpxAwsylG/lYstK55LsekZeAoH0qiDyV28Uj6MFyDNwNIeHyZzLeuov9AmbVgeql7oJIiPSs/imWgJy+DBYmkbHEIPFgYW6TG+qk2uaQZWyCfoEY62PPFYXjZXQ7/tF9ZgUB3CT8tPGAFaHiQPfTOUIfLKY2Ax1piIudpxg4FllwdpRzzWmCANgOdZ41x9XLzBewVYA4v+oU3l8nT4TO4nXCIkneV6xijjNsvAEm4xgwi8hJPaEo+tFxG5ql+RX/SojK7ISeWVpnJZ/FFee2WjOTIMlwkl57z1hTSqr9nxTV3QJV7YZ+Cke5W1eBJHLyhP+MzeIwOM5zIerDz127bqjE+lgVUnA4e6inNAG+W1j4Ma7ADUYM1SBHZyk5KkHhleVuGTLlA7mniUzpWyobGh/HaQSkkKT/YHyQjgqrY1mQg/lgkB6rJKW7hYA0u022e+sPuJ4aRnwlN5UNLCV3l01R65kGaeU566VI/K6KoJU0pb6aHCFB3ilfLJwBLflK6J0xpYeAcB7cPSxKcy4ZU2Q7zUfowXwlETGvUxQdEeBmDMwIJnMlDD9u09fLL16hn4WFyyeC1ZqCxX0ihv5SPjyeYL+0NohIFfjFfIEbpjoHSNNa4YPpQBH7wMaQZW2BZGjuqJtRXKJmZgUY49aYSwP/FSg/fYerYwsJAvBrv6cYwPWf0M3qtPCW/J2coV/JWPq+hRGV0Z5/DPgupLK2Pz2ji0YOSJV3oG79E7Fj89i11DGtXX1KcoQx7whDbSrV7jufKqLGkWSJeOs+mxOMZzmoGlfiV5xsp3kTaVBlaasLsQwDS2ycSEkuZNF0AenGUiueRRLAxkKWY7qJQmIyfkr5RYzPtB2bCccJKioD7FecaERZARgNGi5SPSwVMKkiMagFCh6B7cUBQoLeFHeeLCm/JS2DFFKdyUP0upkxc5hDSrDZ5buZAuEM8lK9KZtGhXOJAmHG0+0jGw4LfNSzq8oowMLAwueSGEJ3WJp5QJgWdhe1k8i+FIW8gXDxaTVcyDlcfAEi7wxgJ1W9rBQX3N5iNOuvqI7pELaaKL9NB4Ik3l1B/CPMiRNAuiVYaUfUZc6RprumJ0Ijc8MaGBpZcM2xY8oR/A4zSQnCVPGQ0yxFUOWbBUGE7wpL/ZHeosnMnPWNXf/YUXfIDP4hP5svoZ8rK8J79o09glzeZjbIsenlkIxzjPqhgN0Cs5qh3RE/JIz8OrxZ1n8Ef6SHnVb5GjXtj0jCt0Ucby1T4nXX3UpsfiGMn0r1hd4lWMv2njKtZG3WlTaWDRKQbojgMMOLxY8mAhD05/l1ykTGODxWItxa7JnmcoXga1JmObnziDjYktpmRQxmE5DU7hRh2Ko2C1bBUaWEwemszUlvVgUY9ACgbFgaKw9JCH58KDe8XtBE06oLqUB14K39kcc3+hOc2DBf+tXGxJyUaKjWdq0+KltsPJSN4hW6fiyBBFCt+YAJEnPNEelxiPVJYruKkPKV33wkfpXKkfnJWHNP2DMG2JEJ7FJhTKWgAXDI5wUoAfFhfah3+hIUZd0C1DgHvKSS7iufqbXZ4ir2ShfOqTPAPgq5UhaZqYrVFCukDpGn+6MnZ4aUJu1mNEOfVp2xY8hA9lDCzhIJyKXvFiAeKrrhY/+oP6eVg/Mgj7tJb4rPFHPvUrjEP7zNbJuFV5patcGg7KF7vGDKxx4yasJ6SRPkR/kj4jv8YaZ6NxBEwM1Ldjz4oaWPBIY9PWJ16pn9ln0NEVTKWBFVNiXQlgWtu1BhbyQDlLLhos4xSLFLuUI7xk8JMeGkric9aAphwGk/CgjJSoJirSFEfhsMQBWAOLdJRZOJmBJxOPjCBf0P3oXgaWpYc8PLcTtHCKKQ6LG2XJm8VHDCx53MgvoBx1WbnoGVcpMjshaRIXDuRT29THhMq5WpThjTfcf0V+gElIy11S5hgOMrDG0SSlP1vb7C9lAOEzm/rkL/So35GKEsfwQq5MVjwTfTyHFng3DtSerZsy4q/Ki2dWzjyjL9LH1L+UhlyQv3CCp+QN+05Yb9gnodvKkPrLGlj8MQEDC+9Q2DfhJWm2LU2UWQaW6hH/wI2+QH1VIDSwYv2ZNpUetgVe6lN6JhzFc9KRv/IxztKM8nCMU1a8Uh8iLS/UZWCpf9EucUsbafBBX17gH/UxgDZbj82TpY9tPuLaXxdbJoRXtEMIwerz8FnT99V6adPYNVR/mrAbam6oNsIBlhCYJFCYyIMTiyUXKapxikUGVqgEswws2giVhNCjHMpQio104WTLSOmTl8mPZ3ozlQJFmYaTGfVxwnHoZZBSQNlQJqSH+u3EK4VtcaJuQGnCm7zCdzbH3N+Y144clKMuKxdbkmfgnZdXyJQT2TmviH8mjjOwaMt6KeAZvAFoM6tvwD/xyBdwP9xjrKVNzNSnfkcZ5IdMyS88ZOChsHlexMCyfKJ+5GPlEsqNPABtgrs1sCiLXOC/6BRv0vqW+kPYJ+FViJsMrLCuWYzcX7/dMjhn32nJmzrY53T22Wf78+3C5UGVI5/wJA0DC5lY2pRXV2gM6QyNSOUtcmUccgI/eAPgBlhe0B/S+hmyCz2T0EZ/sWOVfPBefUZ6wjdmfsJyPJJs03AwxedF0wysInWBu3CgAehQP1WD5EGPU+8id0xNDChjeWLzUCfyzQP0R3R0zMBCVpJhWJf6fpjexv1UGlh0igG65YDd6I48+FeU5MJgYVCmTYbCnDcaFFY46LMMLAZ6mF/1UQ5AYQg0OG0ZxXmGgcUeIXlaxhlYfDqEzxxZkIIBt5ii4LnwoJzi4pety+JGetYkwXOMBLwxIdAGStPKJcyDQrMTkvASDuSXQkdRqx2+QUa5LA8WZe1khHKVgTOOJtokjwXah1+Sk31GnDKWFmuIyMCS4cGVyVWyDuuy91L6Fh8mW3hl+SRZ2gmNekIPKWnklVzEc/EmND7UhvJZuqiL/KTZt3zoow3hRD4L9EfOUtN3CHl26KGH+i9NwF99FsWWIU5blscY2WxKV/8P8+veyjPEX3mKXuHLgQceONrfJzlRvwBc1X+Vpqt4Y+XF+IVGPSOv4uRjiTCtz8AD+pSVg4yScfwRTvYaM7Dog6LT5k2Lg7uljz4U4iL6WB5UXwvrI139L3yWpY/DvNyzAhA7qiGPrGL1NZ32x0030Mf66cgDdMsBJlcGJ/uwePPRMghGFYpAAzcLS747FXNLYyjhto5BTEkonwysiy66yHsoXvKSl4wUg1Uswg3lI7xVhxRomgcLhR0qbdUNbrEJhOdStrQjpSc81DZXKTkpNPLG8qkMNIMrY8IatJSjXSZBPAz2mcqGBpZwFA7kU9vIFAOL5SOOsuCbZuMMLBk21BMaWFneI/grw4SyAPSEfJ99MvvLM/GVFOQgD47wkIEFv4AsHHwG96M2rYEl2Yg35BXP9EzlRYf18iAr0u3EJcNAOKu8+pZkE/YvZEh9dqKDTtGsesZdaYfv+xGskWDL0ZbwJB0PVlofsOXgk/jHRBoakTZv2bgMD2sA0qbkF9ardPqM8CE/MrFjSfmgGyPYvjTYOiUnyiquvqC+YfOPiyM//SFAecFPdCot6wrf1efJZ/uIyqkPx/Sw8th+qjRdqVP0Ki3ryku1/QqI8mbRBk+7gqn0YEnZdMX0od3ZjcW8jeDuRR586V5yyVJslne8LccUBkYDXqiYoqeNNIXFhEl9fOOQvSQcCoqSI7/1fKg8z8DfThIoVJ6nGVgWf8WlYMAt9iZGfeINZWgXgydm9FjcyDuOl9AMn0JlLAPLyoX6LECrnZBiE4IUMPVhYCEbztZ65StfOdpTYeskrknIGgtMYvLSxHhk67ATstJpX7gozV6hBV4JrCEiY0OTjTxxRQyscXwK5SY8MKTATZM46fQF5EIZ8Vy8sfnIa+tFzpYunmv8WMOnjIFFXQI7VpTGFdwsjzHes/ZfqayVDXgKZz2v4yq+WTlljR31JfqVgLLc27GqfDKU9QKmMrpqLFtjQPVIPyhvnit9FvzVPygzbtyE9dJ3LH3Upf6kvNCHvPXJIqXbK/hbPOwzaCxCH3MGul39XXVlyUp8VN42r1NpYKnTt8nooa35HMAw4d9kyIPvOkouWYNlfi3zU5jEGVR2qU+5GOhpA5r0d73rXcl73vMe/y9HlCIKJqZUqI9NveDPfg4BygYlWsXAkrJXneBllUQMJ+UVrlKMXMVX5bFXGQkyGvQMPoGHlYue6cpEh6wEUqKWv8ThCflog/aYMDkMMW0iloGlK/WHHizqSAM7ISsP7WfxgTJ2ckWBy8CDTnCVUhev0iZLtclVbUoepCmuZ6RJbuIhaQB9EO+V5RXlJBfVJQMp1neoh/5DXiZwm0fGSki7jErK1gW0JTzBI2sfnm0T2Vg6Lf42X5U4/Iev9kUjSw9JdsKLtpEdOk3PSFMcPQHYPu0TVv5ozNhxThzDy8relsmKqx29FJAXGUveWWX1DNxD+tRPlYdVBJarNVaUbq+UsXTZZ6SLdpueFsfAAsJlwizaJIO0OptMn0oDy74lNMncoe5sDrB3iQkEeTBgJJcsxZZd4+zTRW7JkUF7003285ezzxjQoZKwdaKAUGpMauCG0gzz656/JqP8aM8CRgQGFhNynslACgbcYm86/Z/8AABAAElEQVToPLcKCpzSlAaTEfhrIhtnWKQZWChW2rVysTQSh1d2YpZxIP6QB/5ogsQwyWOUaHKwkzx8lIEzrn/QHnksQE8az8gHLbYM/JPsoAFcNFlBB/eSm20njKtN8Ybnils+KZ+d0MjLv1rt8iBpGi9MajII1G/kCSEfoDZoU33CToai0cqxqgdrtuX5v7a/QBd0FPVgZU2k81sslkLfFD8pKZ7GaonJi/6Dl1B6jHL0RUAGVlr/V18Kx7nSfSUFfjR21GcpOm7chNVDo+2P9CH1J+VlyY5P82QBZdTnbT54Bb1FaKS/0MfDje5ZtFl52PbbiA8GVhtcHtqIcoCJg8mKQXzjjTeOFFNVBc8Ewp4A9vkwiC3kHdDWwJIyVT0McMJ9993nP39jJyzyoESreLCYiCyECgp+hYpO+TEGwEfGCHml5JXHXjFmoMV6+6zis3Kx5YjbCZN7KdEQN/iHAkTWeBfHQczAgiYmV5Ql1yyaQmOJ9uBDKEeLh3BUWmgcWwML2cowVf60q3gh3pAPXACLTywfeTDyddAq9wA8QC7gILmF+M7mnHsEiAwsGVXkUV8LDaywT6u+KlfaEg55jmhQW1Y2lLf4K08dV/qdDCz6K3JKM4gkO8mS9ikDfnZCVz7kCKhv+xvzwxgEbFl0lfqFyZorGjOwihqn4G7pixlYeZDBgLKGo8qI1iI0Upf0q+rhmqUT1I7N31Z8Kg2sIgJtSxDT2I7ezFFqfOZCcmECS1Nsefm07bbbeu+LDjNVubxKAtyYvBi4wkt1cJXitMuDeo4S5Y2VgZ1notIbHMqMEE4goYIij9pXm/ZqDSyUflZeDDJ4jfEjkFJlQrRy0XNdMXLsxCwjIuQX+fBYoGTzGCbwnnw694b2xEeMb+qRYSBc7JX2oNsa19A0zijT5E9d4URO+/IGwKu8/VPGuHhK3TE+iWd6Rj7wZ2LWOCENIC9y4R944EQZ8BWPZnPN/tp6ZXTb/iU+WtqrvuDY9m2cdtVfMLDo13kMbuQm/oVysfVXjduJW+Mhrb9qTAkv2qbPceyDeE6a8qEPoF9jnWcWlG4NEeSqdJs3Tzw0sOhL8F7yzlMHuFv6wMfSlqcO8lDG9muVU1pRGq1+U11ZtJXBWfVWvU6lgdWlRVtVYAupvCYOlA//+pNcMLDS3vTy0s9BgijM66+/fk4RFFieAc3khVJin0hsgCot9pd02tWSgJ3M5iBibjBymIg1AYZKEHxDxSvFbaoZRa0CQkFmGRYUwkOCASSQ4oNGKxc915V29MZPmi2nPFzBFT4CaROWf7jyB/rf/e53+31wSpfxIDyzaNIzOzmApyYd1Wmv9DcZUNBBUJvko6zkU8SDRVn4KN5wL7ysDNWfbD7aY9LWOKEswDhBLjLyeBFIMzxUL/1HRpTtk+prMnzo800ZWLSldvQPQnluZimL/yJP+AAN8E44x3OXT6UPIFtAV/E4rFWykyx5jryQn/QYaeqL6IO0usgnnWTHOXGlk6cI0C5l1aepC7yET566oBH66BMAtKk/5SmvPGH/V7poLUqjHYuqi/6RRpuVh/K3dR0MrLY4PbQzjwN6e0X58OV3BgKDmckwSxnNqyiSgOJmIzV/6dVAJlteJaFJjY3sMaWC8iF93XXXndc6uEsp2clsXkaTgJKRsRJOILRThAYZWPCTcpoMTHNzouxr0JINDzRpgJPkMqfAyhuOW2Byl9Ej4yDkF+2r/jwGVqwtGTtqK02ZUlbPULqCcV4nJlfopkzMEEGpa7IaV5fa1FUTle5jfJKM9Iy8WlZSX1R55IpcxEt4wuQuHikfVxnv1BujCxkjLxk+XKk/yxi19ReJ06/hMX2S/pBn/xX1wxvkIhzzjqkiuJGXcasxWMaDhQzoI/BPILmO6zMyNG1Z+BSOJdU77orckaHoEe9C3ZJVD7ijx6R76ENl8KGM7ddqU/UWNbDo5xqLqgv60mizPFX+tq5TaWCV6SRtCWSa2kEOTBIon913332k6BmMVQ0s+Mhfh1F68p6QxqDOM6C17wUDItZfSOMk69gzi3veyQCcwBUIy/DMKigmKSluXyD4kYElQykrL0X555PlkdpCYUkuQRP+Vid5c0I7oHKaLHyi+8HgkaK3vNHzPFfxRAZWmjKlrtDAYpLAI5HVtjym4Ck5WINFBhZ10V9l3OTBnT4i3pA/Jhf1ST0jX5qBRX3IBS8rkOXB4rn6D3TRF8I+C281AWviasLAkgxpi6V7/SMMHLMAebZhYNEHkL/6C7xSXwrxo4/DVysv6GLvp+Wv8lFefSysi3vJX0YHafQZpXNfFNRnKaeXjaxxE9YvvSEay+IDDZYutaO0ojRKv6ke5AV9abRZeahMW9e6DKwdHcI/ceFxFy52YX0X0oCvbF7uAnmvdWEbFwTg8xkX2BH4kAvvckHAoajfduE+F/BZLnKhFHRp0ZZCeAEX4u2ciYSzp5CLJuIsZZSXHVLoUi6Uy6skGPTysEnR2HZ32WWXZLfddrNJo7idyIXD6GFKhPZEe6goQgUFDVlKQ294ojttkhAqGFhMvppcpVBpQ3JRXntFgXMi//Lly32y8OLt2YL4h0yLKlPVI2NHBlYWTXom+vHcoMyzjCLJDBnEPD3iKXyin2bVJZx1hX54I1BcfCEdnsEbPSMNWskj2kkDaB+5kB8ZyIOV1teQI/STT316tqbZX/qbaFYfaMLAUr/mn6m0s9Zaa1k0UuPIkz4pHNPoTK0g5wP6ALxFxvI4hX3ZVoVsNFbgL3EMeeqwIDln6TSNCxkdlCeeNc5tG7E47UELIANaYyOWP0wT3pbGMvhQxvZrtSNai9ZpDUfqom6MrDTaQnmo/TaudRhY/OXpNBeOcWE1Fy5zYbELaXCKe7DEBfKe4MLpLuhE+be7+B4ubOoCs9d7XdjLBQF1v8aFJ5RQ5tolw8vgu5DL6KgG7fUZt/ehCC+k0KVcKMtgzDugtTQTy7/ddtsli4LjGYSbJmvu804GKFhNbsJb9fFMyog0FJ6Un/LYKxMyilWKMSsv5bRUIy+WyvH2LbnY+m0cHuDBQsGxnBoaA+SV4itilNg2iEMDfChjYDFZAlYuPsH8aPLDwNKkZGnBCMVgO/fcc32prLpMtT5K/xFPSVA87FfQaCcibXAPJ3n0l+SCwSQPlsXX4gDfqJd8aQaWxoj6YBMGlsaCPJ5p3yy0uBOn/8B7GVjh+Ajzl72XTNFBhHH9FXlJluozMQNL/V/1x/CT19fOTYx5ZFcWkKFe2iTfIryT3hCNRXSnxVn9z6YRV18vSqP0m+obR5vlqcq0da3DwNrDIYvB80UX+JDTR1zgYIwNXAhhM5fwXBc+6gJ5j3MBHF7kAnCIC0e68LALy1zAAHuDCwCvgHi3fshNFQgVW5W6hrLVOIARw6SJRwi5yMDShFeldikTeTKoq4jSyjKwsvAS7iiOvH2NvJrchLfaCBUUCi+rXikg0S0Fr/rCK8YDoH1SUnxMiJJLWEb3GFhM3BxZwR8KdthhBz0aXaWoY5P7KNOYCEYG+MjACnlki4te0a8+lTVhyjghryZyGQTUzdIP35HUZzqy6rK4EA8NJ+SHTEPDCbyFK+VkYBG3gOwlFxlYTPAW3zA//R7eaenbPoeXmqTUB5swsCQzDCyMjbw8FP9kxKTRaWkqE9e4xSiRByurHvCS8aE+w4tXODbV/1V/rE76A2BfpIroqlid9GnJU/KVDGL5wzThLRrLGljww9KldpQm2pU+7krfBCfpKY1zjfuwfCiP8HmT93UYWBhMSw2SLP3d6cLzTJqi5L3dBeuBusHdK29Yl32mOopc8a5x8I7CKhSWQBCwhGzjCE7pxGUBp8URtvIQ520eUJz7MM5zpROnPHkUV+chPRYHP6Vb3NPi5O0jTSh8JmgO7UQuxBlwDG7hW5YmDTgpZvgLHxhwkgf8Vlzy4ErQBKD8ks04OfE2inJjIrDyS6ODdMqg2Jl09TYLrpSnfcWFr5QGuJBH6eBN21zluaFO0STcuVecupjw8GBRlyYL6kQu4BfSAT4Af0un/tNOO83jqUMHLa1SoLRh6UiLx2iiLfgpAyuLJsldkwt9CqB9S4eNww+98VMOnOGL6KC9XXfdNTnggAOS5z73uT4vz4A0OpROPfRt2gOY7OzkJdlsuumm3oCjHDL4qftcE/usJCfKE6fdZcuW+XowsPAcUgdytzSRj7qghXLwgfyiCVyIy8AiL32Qe+oTvqKD/DaeJifSRZONq1/jfZP3SjRRt8XdxsUr9Wf1p5AO7gGbDr5Kt7jH4vQPgHYwdOkP0AFYOhQHLxku0jEsf/KcAECHxir10a7SFQc/247wpY4YrZRTnhgd1E867dGXqUdjWuOGPKTH5CTchTf3kgdpilNHWhz8RB9yV5x04a55GBp5rnTi1AvE4vRzQN45Xem3MZrUti/U8k8dBha9claDPYk897O99ck0YuPyhs/T6plba/rd+90j/n+usIKsN998M5fklltu8YH40qVLvdIift111/llD+JXXnmlfzsnfsUVV3ilR/ySSy7xio34hRdeONqQev75548mtnPOOcd3bARMnCsdnTjAQCY/wNsq9QAoTOoHULK0C+AlAB+At0DwBFC24A9MGk0MMgY5dC5fvtx//483vTvuuKMyTSgDFIqOTIC/DEAGdB453XvvvZ6nDPaickKpYBDklZMUEjjDB0B9D3xRlPAIYKKU0oj1PSkgeaQuu+yysX0PPpGfvqe+hMGFHJBPWt8jHSMZw4cjK7T8Y8eTlh6Z3EUTdBQdT4wd+ABvzzvvvFSaZGBx0CzAqc/wkAkxazxRL8oaA0B9JxxP1PHqV7/aH2IrWsfRRF1s6maMA7fddtto4rQ6gkmd9uHdySef7PUDnrOw7yEP6kOu8F79m/4WkxPtP/LII74+8oc0wVcMBfTJAw884CfmcTRBR6zvkW5psnrvoosu4rGfPDUp5tF7Mqrp99Ci/lm33qPf0AfEK/qKjLoYTeDC90oB9XEMrZAmGV/wOU2XIxMA+Yk+6Ka/A3Y85Z2f0FuUv+CCC0Z9Dxlk0WTnJxlA6Exooo9Ac9H5SWWhw/Y95AdQZ16aaBvDEdBp7pdfzpbuxC8lx+Qk/vtMPfxh3xNmfCx82KWzEZ09WBbwPL3cJqyMv9Jdrw3Sz3L3h61MwxDa2jw/0MWvNveKsry4SDcZ19CDtbbLO+MGg9NRMzNukvIhjLsONUon7iY/nz8t7jriKA9x17F9fsW5D+NkUDpx2iCP4rSVFQd35Umjw6aTl3sgjQ6bDi6iW7hTVnHhzlVxntt4HprcIJk5/PDDZ+6++26P3xlnnDFz/PHH+7jwtXTYeB6aPvGJT8xcfPHFoOZx//jHPz5z6aWXjuhQuqVDcee98bi5yXyObPLI6cQTT5w54YQTPB3gCVjcwzg0w4ejjz7a5yO/5OGU4synPvWpkTyOOuqomSVLlpDF4xXKyU2Svi6nWP3VTcBeLlY2Nk55+P6FL3zBt3HNNdf4ck6hjvoYeSwdNv79739/5mMf+9iMU9wj3C194A9t1CuawD0tntb3Fi9e7OtBhmE/pD5L0xFHHDHjJjOSZ773ve/NHHPMMT5u6bBx8EVm3/72t2eckh7lt3TYOLhzD6TRofRvfvObM1/5yldG8qM/ffazn/VlQzrUbz796U97XCxN4Bv2PWdEep7A3xUrVvg2aBcAP+L0Q9onj5vUfLpw5wq9xx57rM9LPyC/cKeetHianEKaoEF0IBfwcJ+xomqPb0iT0kWHO5LClzn11FNn4IvSwd3SEYuTV+lpdNj0z3zmM76/gOPVV1/t8QafGE2nnHLKzFe/+lUezzgDyOPImAnldNJJJ/lnzDvCPex7zggZ8UX4IrNvfOMbvn7SlJ6XJrec7et0humMM8ZnPvrRj47ooNIYTZITzykHH2699Vbf9gc/+MEZ95HxOX3M0mHj4CpaGYcf/vCHqdLXIzrci4avH9rz0kQbzsjy5egXgHOYjOiM0UT9zPsusJLVKvxxjtZ2G5NnH/f8HSYP/ruNXJj/ITjnPHLpm7iA4aNlwi1d/CgXAJ5v5cKsOyZJeBarxyXnAtpQO/MK8FYrsHEsakGeuFzYlCkSx2ug/Lw5EYA8cYtvnngeOmwe4QU+ReJFadJfzXmz4Uwp3rhw1ddFk9zGosMN0JE3gzQgjb411lhj9Fx58siGPOutt573VuahgzzKhxdCccmDK3irfzgFNcJZeFk65MHijR/AI4hcAOUP5bT66qt7zy7pTsn6vLSHB4vjLsBJ7Qs/MhF/8Ytf7PdeaYlF6b4S94MMAJZcRRP3aXHhSB4b1x4WPA02XXFLE3ngGYBnSMu90CA6bBw6wJ+84CUehrT6Ct1PGu6xdNKs/Igrn3CnXuI77rhj8q1vfcvLC75amoQv5Xn7Ry54BQX0HeUhTbhzlZcLD5bSlYdy8k7gwYB24UeetHiIO3mBrHT6AmNc58dZfNPi4AfgeSEufEI6fCb3Y9OVl2d54vQBeUbgFfwHYjTRH/FyAfAN/DmfjKVe5SdNHlXb/y2t4Ksx4uyFEf7IWfWUoUnjxRkv3nNPG6oPnMfFhTflAXCDhxb3tLjFl3agxdKm+riSN49slEceLHgOoA+BNL0gfeYztfxTxxLhRQ5njKo3uYAm/XcXrnHhbhdCuM0l4At9nwvkfasLWJaXugAsdoF/DjKzbezCW1w4yQUBZWZH22x5xfV8uE4YBxh8KDUtA7B0IMVQBykoFSYPAYNRA1VpaVcmLxRs3vy2HjZEv+xlL7NJmXEpJClam5lnKCiBNbCUZq8yDmRg5cGffxK6tz+/RIVCRS7Qnse9Tl79IcDiobgUtYwcpRe9aqKN8SisizahB7AGVpjP3qO46X/QLB7a52Xj8F+TFHVkyY8lQfrdNttsk2D0poHkghEgSMOZ9jW+rEGmcnaMYPxoAtPzOq+0xXgv0hfoXwD9OY/sq+ALbvq81jgcyUvfApAH/VOTvsWBvgjeWeMQQwWwxgBjXnrB1pc3LjkiU3RgUd6J7/RdGTFZNKThRRmMK0sbeaXTitIIn61u0jiXnknDo4v0OgwsZi+W/t7pApsMdnfh9S4IPu8iBMHBLrK3C+T9excOcGHWBJ39V+HF7p7F2StcwLN1gQsCDDQO9sDQunVl3F2KQVGBFqt9yF2UA0wSTA7IBYVVp4FlJ1oGuN7C8uCI0nvpS1+abL755nmyV8qjPikjwlbGMyk48EfhZSk6aAZ3JlUZSra+WNz+k1AGAO3yryjhFiuXJ02KPTa55ymvPDIg8ihSK3f6FJPhOCAPBhaTZEwO48qnPUdWkh95iKfJD16/7W1vS/bbb7+06rw8JBdrBKThTJ30G55LFrZy0piAydO0gQUOec+/Eo6StzxYSm/iiu6RkTSuz6i/wDf1GcnF4sYYHFeXxpiMDsrTT5Ru68sblx6lTyNf8TFveXQI7Vc1sESDpQ0cdK/nefHCuKIf0VcB0UZ6DIrWH6ujbNqTa2Fla5gtd5W7bJ1SxduD9Dvc/a5Bmm5Zm8BQI8RgUSyxaJoEW7TckL8ZDuA9cXuwvELJOxnmxUSTB/kl9yIDbuedd87bVKV8wik2AfIMJS4DkbjeLmONomgwRoq88cvAYrOuDDj4xdLtFltsUUnR45U55JBDKntGZEDkmSjgoxQwE/O4CQ4+MiFRhmA/NB3jcZE0ZGUNLPibJT95HtLasHLBUANv6pQXJCwnYy7NwBVf8QRA+7j2w/qL3O+1116F65e8oVG4FmmzSF71E3g5jg/wnTGJcSUD68Ybb5w3Xl7wghf4tCw8JDvpKPISl+yyyqY90wsJBhayjemWtLJKp5/Cd/XfMvioDHVIltQvWvVcbea5Iht5ccfRpnby1Ft3njo8WHXjNNQ3ZRxYtGiR97bwbxMGg5RcHWywBlYVJVEHLll1ZBlYUkDwBmUHZE3QPEe5Qu+4fOQFaANPIv8kLFJutnT2L3XHPoqdXWr+U00YeSYKvCT8IwvlS7Cenvk1z6bojZ/9SmorLW+RdOiX3CgHfyXTIvWk5cVwysJXfcsuJ9q6dNAsxjST1jjDwpYtGucj7DqiIW9ZOynnkX3eemP51AfQQWkeEZWTnuKlUAaWntkrezmhOwtoCyPLLqMx3iW7rLJpzygLr/nXapklQuqVgSUjpUy/VRnpX+Gr+3F8Vn57pb/LwJIHyz7vS3wqDawqnbYvgltIeGjyRcEDUnJ10IhyZgACUhJ9lL9wik0gegb+UkpSWmk80oRrJ6e0vErn480oYwwSFCvtbrnllpWUvOqu41qEJox2DHb3zzrftCbDLDzU7+BxnZ4SeCm50T7GVl7DN4ZvKBcMpyx81VfSPFh87ggvpfs3qPeUNmlgxegZlwa98vBk0TmunjzP1U90zSqjPDKw6J9Vxgs0SkfRLn1GYz8Lj6xnnEvHWXYcb1BEF6hOGVjqv+pLep7nqjKqQ2WglWdlDCz6qDzU4zxYVXkofMtcp9LAsp24DNOGMvVyAEXF5KZTsqW46mgFg4UBCGiAa8DXUX9ddUgJjDOw5AkZN0HLGBmXz+K/0047eUXMP9TgEeOE82n6Ml5EU56JAgMLYMkGyNOnZGCRv86JHF5KbtRNP6zSB0O5sCFeB7xSfwjqW2keLPK/5CUv8V4Y4n0zsMBJMo+ND57XBeoDRTye+mMEuFUZL8jJjjXiVfoJPNlqq6380iAvG+JhEV7VYWCp/1nawIF7PSuCE3nRBfJgod+zaAvbLdpWlfxTaWBVYdhQthkO8BbNAX9AnskwLxYovUnyYMUmdilZJua8RmIRY0S85GgJltbYuyXDTPUoT5dX4ZKlTIUfeelTOlS4yIRJHWpL9VW5Ij+UPHvnAIwtybRsvRY//oTB8Q5poEkszYNFOfbgqY4+G1ix8ZFGd5l06R5ds+qgHzJO5MECNyuXrLKxZ8jJLhEy1iW7WP48aeC49daz26PLGKd1GFjq69JdwruqgSUPVtnlT+HR5HUqDayqnbZJgUxj3ciDf98AxMsogjS+oWBkYGmAa8CnlekiXX0yRrueoZDkCZEBlIarFP24fLY8rvoXvvCFPgke0S6Tt9q3ebuIa3LNY2CBH14sZA8tMb6GNGjCJF1thXnK3EsG6n/IUGll6isqF/X3LA8WeOyxxx7J3nvvnXk8RBl86ygjftUplxheMqx0jeVRGuMFj5cMLAzTKuMlXCKsYoAIR676PmieMWDLEYfv9Fv1XfWlMF/WvcqoDuWtQh+8zuvB6lJ/TaWBFQpaAh+u3XAAeeggRBRWmTX5NMxRKriQ8R7ojaePb+hSAjElqGcoJC13asJJo1sGVl5jRPXwnT08HeCBXNzJzSPlqjxdXUVTjEcxnDCwACbLvH1KS0Rqy1dQ8SecYOCr0spUXVQuaivLgwUeGC/8azYvr8rgXraM+nHTBhbtcAiqDkIdhy99SwYWZauMF8Y5YxxAXxGX7MbhkfWcf8Tuu+++/huaWfliz9AzvBDQ54Ay+KiMaFM71CndprS8V8YnBhZ84iVK/SNWXrjHnjWdVtcxDU3jWWv9fVQgtRI4YZUhD5ZzUAQajHWRoMkYwwRFCGgSrauNOuqRoolNIOIJikIGluhKa1sGwjhDLCwPHq997Wv9myty4aT9vowX3vA5wJUTzPPA+uuv73HPszyo+ugb7FeJyUF5il4lAyYq5FLVg1VULupb4wysonS1mV8T6Lh+XwdOb3rTm3JXg4Glb37SZ5Bv2fGCnLREqKtklxuhlIxa/k15nJoMvxkPMlLK4KMyqkONVTEgeUnGuMLI4hgW6TvVba9l5WHrKBufSgNLAi/LtKFcvRxAHhtvvLEfLDIg6mpBipl62YyKsaK0utqoox71ydgEomcoJC13xvJZPKRwNLnbZ+PiGLsC5NIn2H13zjHOB0x4/DNy3NKYrU3Gt/hnn5WNWwOZOpholFamTo2XvGXZV8fSVZU287bVVD6N2ToN3zpwpb8sX77cV0Vc/4guU7ddIpQx0rXM1lxzzcR9i3D0YlcGH5URTeIN+ky6TWl5rxqf4IZe5/NEaVC2jbT6iqRPpYEVCroIw4a89XMAeVx55ZUJ/2LTYKyrFRkiGCYMRJRgl280aXRJCQhfm0/PZGCB/zjDSQpoXD7bThhvUi5hW03dv+pVryqkxOkfTHRV+BbSoj4NP3nrrurBKioXjOS+Gcohj8bdSx59M7DwYHEGFgCO7sPGpfUY45wxDuiqse8TO/hZZ511fH/96cpvLqovF0FFZei3FqoYWNrm8eMf/9h/pgs80yBsNy1fE+lTuQcLBTpAfziAPPA0NCEXGSzWwOoP5U9iIkUam0CkoGRg8TY/zkiUAtKb/5Mt5Y81KZf8WFTLifeKSTAvkBfjdBx/89ZHPhkHdi+L0orUo7wLQS6iJe9V/VjjOW+5pvNhkAsYc1X0GDpAS4N9MbA4qJSxcM899/gXlTLjwuov8YprFQNLL5APP/ywP4oiC68m5hVLR1Z8Kj1YXTI8SxjT+gx5sF+mCZBCnhQDSxOJ5YWML97EoEM02TxhXAqo6kTelFxCfPtyzz+uFq3cHF8XTppgJD/qjRnSedtrcrzkxaHtfPRjJtHY+GgbF9ueNd4xsHQqvs2TN45cZWDJ66K+k7eOuvPBb/bGPvTQQ7n0Tqx9zbeiSXkwsMrSpxdI6tIxFKo3vKr9ML2N+6l05YSCboPRQxvpHEAel1xyyWgjZXrO4k+kkLUHy75xFq+tuRLsk+GbfTKmbEtKkweriIEl+m19eeNNyiUvDm3nYyN4lX00MXxl5OLB0nJSFQNrGuVCP6bfZ3kqYrxvOs0aWIzTKnqM8vJc6aqx3zQdWfXjlQPKGkPIjLLhvAuNZemjPsYVHrbVV189C/157WZmrvnh4MGqmaFDdcU5wBsG3+pq4k1Dxog8WHV7J4pTGy/BIZ+EGEixoZAwFEVTLK/SmJBe9KIXjf0GmvLHrk3KJdbeQk2T/Jhg6jCwplEufd1Dphc2xiRyrqLHYgaW+k6XYwMD69prry1tYIE7tIUGFvdlDSzqhNd84mkcNDGvjGtTzwcDS5wYrp1xgAGgt6S6kUBBUT8GFsc02DfOuttqqj4pIRRS3iVC3hr33HPPSig1KZdKiE1YYU2SdRpYTY2XvrKWF6M+vhxJn+CRrDpeKB8uEWrsdykXbSBXPy6DC2XllVN57uXdVVqR60EHHZQrO3ztCrpruSuKXbuhJd0hKkPTK+Vx4YUXNiYX3i4xrpC73jgnifFSECikvAZWHfTBryblUgeOk1CHJpE6lwgHufRD8niKkS97HquOF4wpGSG69sHAYgkOOqvggoEVzrvQWKXOvD0gbDdvuTry1Wlg8TGsn7jwuAsXu5C1a3kj9/zylXmvdddtXBCA02dc+KULD7nwLhcEfMfjAhd+4QLPvuzC01woBJqwChUaMjfGAeTBV+ibkgsG1qOPPurxn0QDC2+UlC9LhCi7NqBpubRBQx/agI8EFD1LhMizigwHufRBqk/igBdLHqwqekxjnJplFFTxGj2JYbUY/Y09olVwgTbRJGzaMrDAvyuoq+WnOAJOc+EYF1Zz4TIXFruQBqe4B0tcIO8JLpzugpYr3+7ie7jAyWG7ufBeF/ZyAXi6C8e6sK4LG7uwigtHulAIumR4IUSnJDPy4J8qTcll0g0suoEUVJserKblMiXd25PJ5CQPFv0RI6ssDHIpy7lmylkDq4oeQ65aIuyTBwuu7bLLLqOPgZfhIv1fNKn8YGCJE+Ove7gsT7jwRRc4de0jLjzfhQ1cCGEzl/BcFz7qAnmPcwFD70UuAIe4gNH0sAvLXMAAe4MLwLkuYMjxzZNfu3C8Czu7UAhQdAP0hwPI47zzzvMTUBNY4S2QB0t7Jppop8k6paDaNLCalkuT/Opb3SwjyYNV5R+E0DXIpV/SZa/jbrvtVlku1oMlY4S0PgCfp9p2221Lo4L+Cj1Y3JPeNHQ539flwcJgWmoYxTLhnS48z6QpSt7bXcAgE9zgIsob1mWfKb+ufDfjJt1ErnjWWEJUwOM1AjqxOrKNI3ilE9dbRVocASoPcU5rBhTX6c1cFee5jVNeHYE4bQFpcfBTHot7Wpy8faUJPuhbWU3QhMcAwwSvAXFAsrFxyYOr4jy38a7kxNstvIEOJmvwEO42Dq5Kt3TYOM/z0AS/tt9+e+89s/1wIfU9299sXGOlrvHEREmfY4mQPlhFTtTFeV2qw8rGxgc5zS61SZbIV2MlLY6MlCevjljkNuCzhEY59BjjhrKAlUdaXHJijKu/qS/K06l06uRZ0zTRTh4dMY4m6gFXGY+WDuLQDDRJk9rwDbX8U5eBxVHJvwpw5z52hPK4vOHztHrwXL3DhQ8F7drb97ubx0xYwcObb76ZS3LLLbf4QHzp0qXJsmU4zJLkuuuuS+6++24f5xMu9913n4/zGQR9MoDzTn72s5/5dDac8kFM4Pzzz/cfnyR+zjnneIVK5yHOFQVLHOAjleQHKE89APVSP0B7tAuAB/gA4AeeAHiDPzCJNF199dXJaqut5k8LboImTUS8Lf3qV7PddNLkRN+hj2BgcapyG32PwwXpTyiohdr32hpP7J3jjxbI7/HHH6+kIzQRX3bZZX7MT4OOaEtOVXT5kiVLvB5Dx5TR5Rgh9A10uQwozUmTPj/xUWZ0mJ2fSHvsMabnZudcxl7fgZHMq3EsfNilsxGdpTsLeJ5ebhNWxl/prtcG6We5+8NWpsHxrc3zA138anNPFG/Xgy7sx00GhB6stV3eGTdxuDl3ZsYJ3Icw7t4+RunEXWf3+dPiToCjPMSdVe/zK859GCeD0onTBnkUp62sOLgrTxodNp283ANpdNh0cBHdwp2yigt3rorz3Mbz0uSUyszZZ5894wZcIzSdccYZM4cffvjMscce2xpNVjY2LhlY2dg4eZXHyuOYY46Z+c53vuPpuP766+fQ0ZSc3MvAzFlnneVlThuWDhsXvpYOG0+jydJn4232PUuHjddN03HHHed5uXjx4pmvfe1rlXQE/EEujBvAysbGoaFJmhainKrQ5L516vUY44Z6smQTk5N78fY6Crm5l04/1mPyI039kzh1AWnxKjRZOmxceFk6bDzse/T7U045xeMt3I888siZH/zgByPclZ5Gh00vQtMjjzwiu4WVrFbhj3O2xmbzLNjHPcSbJPg/LsI/BWPLd7iPNnEB40fLhFu6+FEuADzfyoVZl0yS8MzWQ73nufBuF77rQhZQv9oY5dMyEW8MAhu368J54vobNnUVieP+VX7eSuXKzBO3+OaJ56HD5hFebdDEnhQOxUQuconXSZP2vLD/SjwuQl9f5MQbH8BfwsvQYWWZhyb2ru2+++5+nwT51WYe2dg8tl/liReRTVGa0saWxTdPPA8dNg80uQnIe7D527v6+ThaY3JyM5KXi/p1lzTBf2AcHTZPjCaep9Fh0/PIxuaxMsgTL0JHSBPjEj3GuJF8Le5pceHLlT6iK/mFs/LQptLyxqvQpLJpuKelW3yJU48zijxt4A04g2rUb5qkSTTMttrub11LhBc5tDGq3uQChtO/u3CNC7PrbC5i4DYXv8WF97lA3re6gIV5qQvAYhf45+AaLmzswltcOMkFYB0XlrjABvmvuVAK1PlLFR4K1c4B5MEnSpqSi/4SP4lHNIjZKCmWDwC9IOhZU9em5dIU3n2sFyXPhMIWARlGZfEc5FKWc82WqyoXxrhbAfBIYmhZo6NZzJuvHVqgyYKMSZvWRLypeSUPrnUZWHiJWPp7pwtsRmLz+etdEHzeRQiCg11kbxfI+/cuHODC/+cCwL8KOUeLDVFXuIBn6wIXgDe7sMiFT7rAPwkJ1rvlbseDczWOzzTkaI0DyOPMM88cbQytu2EZJJNuYLklCM8a0VM3n8L6mpZL2N5CvmeCgZ91GFiDXPrZU6rKBW+QjBCMcesF6ifF+bGCFmiy0JaBhVy6grxLhHnwu8plsnunbBnOtrJwh7vZ1SaYOCY8hhohhA+6BEIlWEhvBpUY0ZPCyGPvvfdu7I1NBskkG1jwqG0PVtNy6Un3awUNeMkSSR0G1iCXVkRWuJGqcsEIkYHFlfoWCkCLNbBY5sZb14YR2SUf6/JgLZR+MNDREQeaHAQLwcBCEWkPluhpQ1RNyqUN/PvSBkuEGFdMMlWXCKFpkEtfJDsXjypyYYzbJcI2jI+52Dd3By3WwJIhuZBojHFvKg0sK+gYU4a0djmAPHSMRRMtaw/WpB4yCk9QRLz1AaLH3zT407RcGkS9d1Uz8XJMA1DVwBrk0jvxeoSqymUhLxHS/2VUwSzFqxikeXsBcukKptLAakOoXQl0EttFHvvuu29jb+Xy+Ez6EiGyxdBqq/82LZdJ7KtlcYaXdRlYg1zKSqHZclXlwtiW4cGV+hYKQIs1dERnGx6sLvk4lQbWQum0C4kOO/jqpmudddbxe7ye85zn1F11a/VJEclYbKvhJuXSFg19aAclr0mlqgcLega59EGq83GoIhfGOEuEeKqpR2N+fiuTlwItljeKLyQaY1KZSgNLwo0xZEhrnwPIg5PVm5ILg3jnnXcenePUPoXVW5QiatPAalou1bkyOTXYs3iqGliDXPop96py0RjHEMfQ6tLzUjeH7QsGdetlQzTX3Z6tr6l5xbaRFl84Psg0CiPpVtlFHg9JLXMAeey///4ttzpZzUkRtbX/Cu4Mcqmvj9jJsqqRPMilPrnUWVNVuXBQKcCfWTAKNObrxLGruuj/1tBp08BCLl3BVHqwtFm4K6YP7c7lAPLg+12DXObyxd5J2VadnG2d4+KDXMZxKP9zq+SrynCQS36+t5mzqlz+7M/+zKOLgYUBojHfJg1NtYWBhVfO/kuStuyLR1NtdzmvTKWBZS3ppoQ61JufA8jj0ksvnfOGk7/0dOSUIqo6ORfh1iCXItzKziv5sTxY9WTpQS7ZvO7qaVW5yMDivDvqUp/pip4625WxKM8V9AFKr7OtsC61Faa3cT8sEbbB5aGNTA7wdr/ffuO+251ZxYJ/KEXUpoE1yKW+bqXJsur+KzAa5FKfXOqsqapctESIgYUh0uZYr5MPsbrU/zF24NMvfvELn41PpDUNtNcVTKUHS27Krpg+tDuXA8jj0UcfHbmP5z4d7uCADKw292ANcqmv70nJ12FgDXKpTy511lRVLvJuysCSUVInjl3VpX6vz3098MADyaqrrprIa9ckXsilK5hKA0tuyq6YPrQ7lwPI46qrrhr9s2Tu0+EODkjZtvlWO8ilvr4n+WmiqVLzIJcq3GuubFW5cNAo/UOb3LlfKLDWWmt5Uu677z5//elPf5oorWkakUtXsHAkWICDepssUGTI2iAHkMc+++zjXccNNjPRVcuD1aaBNcilvi4jnVOHgTXIpT651FlTHXLBo7NQPVhrrrlmgoHFpnMMrLbOJdTYq1PWeeuaSgOrS5dhXsFMUz7k8fDDDw9LhBlC78LAGuSSIZCCj+r0YA1yKcj8lrLXIRcMLHmwNOZbQr/xZtZdd93k3nvv9dtBnnjiidY8WMilKxgMrK44P7Q74gAD4MYbbxwMrBFH5kc0QbfpwRrkMl8OZVPqlN8gl7JSaLZcHXJZqB4sOL/eeuslP//5z5M77rjDC6ItDxZy6Qqm8l+EUnZdMX1ody4HkMeee+45N3G4m8MBvc22aWANcpkjgko3WqaoY4lwkEslUTRWuA658E/Cn/3sZwvuHCyYjgcLYL/t05/+9FY2uNMecukKBg9WV5wf2h1xgDeM+++/f/BgjTgyPyIDq+1/EQ5ymS+LMilS8nUYWMN4KSOB5svUIRcMLJ2DpTHfPObttMC/BjmWAS9WW94rKOvSg1WngbWjo+UnLjzuwsUurO9CGmzkHlzuAnmvdWEbFwTg9BkXfunCQy68ywXBhi5ylQscovGoC2e4UPgLvl0y3OE7QMAB5HHnnXd2OhAClHp3qwm6TQ/WIJf6ukGdHqxBLvXJpc6a6pDLQl4i5IBdebEGA6tYz3uKy36aC8e4sJoLl7mw2IU0OMU9WOICeU9w4XQX5Md7u4vv4cKmLuzmwntd2MsF4BEXXuMC5Z7twq0u/LcLhUCTVaFCQ+bGOIA8dt99905duY0RV1PFeptt08Aa5FKT8Fw1eK423HDDZO21165c6SCXyixspII65IKB9bvf/S75wx/+MDr7rhFkO6pUBlZbRzRAJnLpCuryYO3hCHjChS+68DsXPuLC813YwIUQNnMJz3Xhoy6Q9zgXwONFLgCHuHCkCw+7sMwFDLA3uAD82oW7XZjhxgG71/CGFQLeNAboDweQxz333DN4sDJE8uxnPzvZaqutktVW492iHRjkUh+fMZAPOeSQZI011qhc6SCXyixspII65IKBBXCUgV6qGkG2o0o333zzZJNNNknWWWed1jBALl1BXQYWBtNSQwRLf3e68DyTpih5b3cBg0xwg4sob1iXfab8LB/+vy7g3TpKiZErnrWnmbAKeXg7ADiATIeQ2TjH+SuduASUFqc+5SGuj0sqzn0Yp32lE6c8eRSnraw4+CmPxT0tTt6+0vT73//e78GC/oVCk6XDxiWDonLCc/WKV7zCv41Rn+1vNl5n36OdFStW+LZow9Jh42VpsnTYOP2gKZosHTYODZNCE3gjF8bNtOgIKxsb71Pf4+gB9iyCX1ldbj3UHDQao4/6lU5cYyUt3qfx9NSnPjU56KCD/GeAoMHSYeN10qR6/WBp+acuA+upDu9fBbhzT3oI4/KGz2P1PN1V+gwX/tUFjLU0eL978JgJK8h4662sLCbJLbfc4gPxpUuXJsuW4TBLkuuuuy65+24cZUly5ZVX+sPRiF9xxRX+gDTil1xyif+3B/ELL7ww+eUvsfmS5Pzzz09+/WscbUlyzjnneHcvHZ84V9y/xAHykR+gPPUA/IuE+gEOZKNdgEPawAcAP/AEwBv8gUmk6dprr0122WUXT99CoWkhyOmRRx7xChAX+0Lte5MoJ+SBF0B6YRp0xCTICf2NHvvNb35TWpdzHqDgwQcfHOanGuZc5t2u4I9yNnyZy7drSl6WA3/uAkt8B5g8eJ4wcM42aURf6cJ/uLA9NyvhLHc9z4X/cQGDiLpmLYYkOdDFqWcHF0J4pku40YW1XYj5AfFgEQR4sFYwcay++uoj6xlXrKxc4giEDXmK8yZBID0W5w2BvDwjjgKkvOI0TlmtBRNn0yveBsWx2MGBdOIE8qfFyUt58ljc0+K001ea4BMTOOekwMOFQJPkN8lyQi4Y8htttJHvOwuBpoUwnhgjd911lx8veDwWAk0LQe/hwcKzuP76s//vKkPTr371q+Too4/289WrX/3qZLPNNvNzi9XrfdblfdQRfFj6mc/EVEhWdeFXnrkt/eQ1sMahs4/LgHG0ycqM/8ddMbpY9pt1Ba184C6buXC1C6u78IQLAHne5MIPXPihC9R1sgvAf7mwoQtv5CaANd39gy7kZRzLhY/xN9E297IEOA+3AQdQGHiutttuu5ERGmQZbjvgwCCXDpieo8lBLjmY1EGWOuSCgXLEEUd47A8++GDvqeyAlAXV5KOPPtqZgVXXEuFFTiIYVRhJeIz+3YVrXMBwCuE2l3CLC+9zgbxvdWHGhUtdABa78F4X2A26sQtvceEkF4A9XMDz9f+4wBLhp12gnUJWqTxJrtwAPeAA8thxxx0H46oHsrAoDHKx3OhPfJBLf2RhMalDLngndVYaqyIDVOcAcukK6jKw8ESx9PdOF9iMtLsLr3dB8HkXIQgOdpG9XSDv37twgAtaKD3OxTlHiw1RbD5iE/sFLgCruIBni2VEDDUMNJYQC4HcrYUKDZkb4wDyYF/cIJfGWFyq4kEupdjWeKFBLo2zuFQDdcmFw0aBLg2DUgzoaaEu55U6TburHH+3TuExZ1tZuMPdpO3pYi8VhhohhLNcAmGABcYBPnA6QP84MMilfzIBo0EuC1cuHNXAvqHBg9VPGRfBqk4Dq0i7neYdOm6n7J/XOPJg/9UA/eLAIJd+yUPYDHIRJ/p1rUsuOgtr8GDVI1/k0hXUtUTYFf6l2u3SZVgK4QVeCHnceOONwxJhz+Q8yKVnAlmJziCXhS0XLRF2aRj0k8PlsOpyvp9KA6ucmIZSAwcGDgwcGDgwcKBZDsiDNRhYzfK5jdqHJcI2uDy0kckBFMmWW26ZmWd42D4HBrm0z/M8LQ5yycOl9vPUJRd5sIYlwnpkiFy6gqk0sPju3TOewSkPA/SBA7hwOYF+iy22GDZ29kEgK3EY5NIjYRhUBrkYZvQoWpdc+MLHY489lnCSO9cBqnGAPwx0BXUdNNoV/kXbfYEr8KOihYb8AwcGDgwcGDgwcGDgwERz4IUO+x+3ScG0ebBWwFw+y/K0p3Go+wADBwYODBwYONBXDpx99tnJHXfckbzznbFTe/qK9YBXnzjA54fWXXddUPLzf5u4TZuB5XnLF70HA6vNbpbdFp+HwOhlEHCS8QD94MAgl37IIcRi2uTCN1RXWWUV/z3MkBd9up82ufSJ91m4IJeuYCpnsy4Z3pWg+9wu8rj//vv9R2v7jOe04TbIpZ8Snya5PP74414v8J2/vsM0yaXvsrD4IZeuYCo9WFn/zpiZmUkeeuihhIE9QHscePazn53ce++97TU4tJSLA4NccrGp9UxV5MIxAGuuuWbvPUIwVXr4d7/7XfInf/InrfO5SIPMK7vsskuRIkPeFjiQNd833fy0GVh8MzH1QMtzzjknOeGEE/xyVdOMH+qfy4E//OEPvVegczGejrtBLv2Uc1W5rLPOOslb3vKWZL/99usngSuxkoH1xBNP+GXCPiPLvwjvvvvuZIMNNhj+Dd0jQSGXleDnf920cZ02A+v3MBUvVQgXX3xx8p//+Z/JX/zFX/gNlcMxDiGHmrtHHryh8hV59lsM0A8ODHLphxxCLKrK5Ze//GXC5vH/+q//SvBmofP6CEyMGFYA+qHvgFw4EmDRokV9R3Wq8EMuK8HP/7pp4zptBpbnacxl+K1vfSvZZpttkk9+8pPDJN9Gzxva6C0HfvOb3/gx8Od//ue9xXFArBoHXvSiFyVvfetbk29/+9u9NbDsB61laFWjutnSzCs77rhjs40MtRfmQGy+L1xJyQJTucnduAxHbLvpppuS3XbbbTCuRhxpL8IbBsrUvGm01/jQ0jwOIAuMrEEu81jTi4Q65IKnGH13ww039IKmGBJaHuTZJHiwmFduvfXW1C0oMRqHtOY5EJvvm291toWpNLBizOUNaZLf2PfYY49k8eLFMdJaSXv729/uvX9lGjvxxBOTfffdt0zRpA262Xz/9Kc/vRR+KnT44Ycnf/d3f6fbWq6HHnpo8uEPf7iWumwl/OsGpcQ+nzSj9+STT07+6q/+yhbrRfz3v//9VExwaXIpIgQ+yQK/+gqT5sGCjxbnvvJ1wKs9DkylgZX320SspWN0/fa3vx1JhLcqzmSJrbP/8Ic/9Oc4ZU16TIpPecpTEs7iIjzvec8b1T0ucv311ye77rqrP8Nrww03TL74xS+OK1L7c958V6xYMa/ez3/+88m//Mu/zEuPJcC7yy67bPSIOpFJX/dfrbfeegn7VhYKMDkfccQRyfrrr+/7IFd7kKP+1sxLB3t0YnJ53etel5x11lmNsWTp0qXegMOwfeYzn+m9LWeeeaZvD4P8JS95yby2wfPmm29O+NRICJdccknywhe+MFl11VV9fXvuuaffkEy+mPF70UUXjcYoPOB8No1ZthJwbADtbbzxxnOauuuuu3y68ONzJ695zWsS/vXHvs699947ue222+aUsTdsPv/Rj+Z+bOIDH/hAwguMgEkcnNlMjX7i+oY3vGFUL4a8cNUVnfOnf/qnqsJfY3Kdk6Hjm0nzYKHDtttuu2GDe8f9Jmw+73wflqvjfioNrCIuw7XXXjs544wzRrxGyT/nOc8Z3SvCpPSud70r1xr8f/zHf/glGJZhWJrMC4ccckiyzz77+MmevRO0xzf8Jh2Y8OFfHW/lk86LNvD/yle+krDnkD920AcvvfTS5PnPf75vGhlIDizLMJnrvg3caINlFpavMGSWLVuW/OxnP0s+9alPJfzLdxwwtmUgKi/fc9t///39CwCbkPkW6T/+4z9mToR4RuEN4fzzz094odH9T37yE1XtDa8f//jJr2/g2dtkk01GzykDLRiMjzzyiN/v9MpXvnL0vGgE2l7+8pd7maGXOKUafPbaa6/kggsu8NXx4iVcuf785z9Pnvvc5ybve9/7ijbXaX4MLIxAXmgnYQ8Wfe/GG2+cCg9qpx2jYONF5vuCVY/NPpUG1liumAyvfe1rE5SmgGU43t5DOP7445MXvOAF/oPF4bO67pcvX56AD2/T22+/vW+LySgE3pCZEPTGj5I69thjk0XOc4RH4Atf+EJyxRVXeKXLWzXejKpgl6vwMOAheMc73uG9bSj3a6+91jfB2zVLbrzJ83Yt3jJxxPJT6KMf/aj3tnD6/s477+wnqzz4Mknyz1CMB9p685vfnPz0pz/1uFHXgQceOFLcTLx/+Zd/may++urJGmus4TcAS6nDd7tREj5++tOf9vyHn4cddtgIHbwPvMVSP8b50UcfPXqGsfLqV7/aTxj0Ff7SLcDIoRz1vfjFL55jOJOPv9PjycG4/+///m8VG105u22rrbZKPve5z43S0iJXXXWVX5KFDgAPHcY7QN/4h3/4h4TlIyY4+KH+Qb+CJsB6kaCLfklfWm211RI2UANp6f5hxs8HP/hBLyM8wciC/ovcwW0cYAyGCvX222/3XuMDDjhg5InCyIHuqhDqh6997WvJwQcfPKoWD9c//dM/Jc961rN8H/rnf/5nL9uyH/HFyLzyyiuTr3/9694A5e2cvvbGN77Rj59RwybCixh5+NfgJAH9j38WEyZhD9Yk8XbAtR0OTKWBVcRliKHAWwlvn7xJ8yYq979E9Oijjyaf+cxnvNteaVlXJl0mSw6lw4uQF3jrxsBjeQIli6HCsocFPGJ4uf7nf/7Hv7XrGRM4yyenn366Xw7CQGCZjmVNDJg777xTWWu50h4TLYYLExtKHuDtmokNrwBv1xirTKCXX355svvuu8/LT5nNN988ufrqq/2b+Etf+lK/HEJ6Hjj11FO9B5LvmX33u99N/vqv/zo55phj/MnxTLxMiAAGHoYFJ8ojY9o77rjjUpvAewCN9I1vfvObyQ9+8AOfl6W29773vd6zwDOMPAG8x4iEJ5ttttmov+BhAC88m/QzPBTcI2cCxhX/TgI3jByWiS2Qzl/tmbypfxxg3H3pS1/yxh/LztbjQ914ZDCw2ACNYaDlXK4ynmwbeMRYRn/ggQeShx9+2Pcnnqel27Kx+IUXXpi84hWviD3KlWbpocCmm27q9xph3H//+9/3sslVUY5MLP+ddtppXk70GQzkcNnQVsNSJUYqS5VlgH6GscmyLuNmHND/8VbSz4vovXH1tvEcA4vlWQwsvey00W7ZNuDvlltuOXF8LkvvpJTrst9PpYEVvuFmdRSEg6fjG9/4hn9rJB4K7N/+7d9yn53FJMhkjyeFCZ2JlCWLPPCyl70sOemkk7zCwTj7xCc+MWe5ksmSPHjTwk3j7I/SmTe8zWLY4G3AeNl6661r/zcR9fJ2D694o7fLKiGteB2YBP/mb/4mmh8DDU8GJznDawwgjLM8gNeKbxyyBwbPEJMT+95YdoBHwguDl03b7FXBS/S2t71tZFjE2sGQwrvDnhmMKNUDjsgXoxuPDl4pAcs4GEJ4w6BVZfBKIAPopPx73vMe7z3C04Sxw54iPHFMNMhOy3nUS9+hpY+I6wAAQABJREFUzn/913/NvYme/TpHHnmk93DCD+j93//9X4+mjBG+DXnNNdckr3/96/0yNmMGg5LlrhDAGSOR/UfQJiMsLT0sH95TF/LKAl5MMGZsUH5wtcuaGDMYNkzSeOroS9AV26ulOvJe6TfIeMmSJf7lJ+bdVl0Yn+ylYtxmAS8Rli5kJRBvMD6gEY8peekX4ZjH88lhohi68jyqnkm44gFFZzEmJ8HAot9dd9118zyok8DrhYxjkfm+bj5MpYFVlIkoTd4AWc4KFSgDCm8SiiwPoIyZeNlwSl1McHhzxgETNp4M9qKgbFhye//73z9aeqM8xhdvUCjoEPBECPBOhPd5DRbVMe7KpzgEKMlx9Wfl53R9jCImSiZeJhYmmjwQ0hneCy8mWwwPDCYmq3e/+92ZbaThi4cOLyJeDIwRPISCtDJ4fuxyFUvAGIWk84cCvBVpH8FmGRj+YrAVAZaU2MiNNw3jjf4L3nh/dtppJ+9RpF8TZ+mRfi6vZNgORgvGI8tu4Pqxj33MZ0lLD8uH9xgtbA7PAoxl/nhgg81vDSzSGRdf/epXfb0sjxM+8pGP2CKl44xj6sZbdNBBB0XrYUmQJWj6WKhDwgJ42SxdeEQFvBTBG3mv8GCTl6Vh+49A/gFKn+AFIzS8VFffr9aDNSlLhOjWAQYOiANTaWCFHigxI+26ww47eI8Ek1F4kBxv0iw18YbI5I+nizfUv/3bv02rbk46E2c4GczJsPKGJTz+MfSqV73Ke3nweIRLjCz1oYhYSuwzaHIQjtzDhzCd5+x/wlvEWzgTCZ6/vDxT/XmuRx11lF+ewwvIxmHu88glrJulP5YM8VYwweHFGwdrrbXWnO8w0i4eJNIxtPBSpeGCrDEemNhZTiwKeMXwpGL084cJGVh4fFgiVD+DJoxajK0QeFn40Ic+5MfBeeedl3z2s5/1xltaelg+vGdZXvsHw2d577PeWvEA4i1kCbcOwAvNPyrhFd6xEDAUWPZlvMKnKoC3FK8VLwax8aK62dDOc3TCpAJ8w2CZFA8W8wqe+6Lzy6TKJw/ejMOuvzHbpTym0sAqMxGxz4IQAqchsyTExExA2TJh2c3NtgxvuexXAQeMMbwC4Z4um19xlm5QOEw8TLbsp6KsnfCYLL/zne/4/UMspTUFeNAw5BTSJv+09vEiYTgJKM9AjNXDRIJBxcTFWzkbdWP5VFfZKx4sPEF4yTBo8mwWj7WFlxNDhKUyliHzDG6WdVkuRLb0C/oOEwuGPR4k6mGjOfzG+GPpTsAkeqL7UwE8OdQdASLeHO7+xs9kHAOM1XPPPdf3Q/jOvj7qxbuKgYVXhH+p4oXDSAIHjuHAQEAWIbAvSN4vvH/QDt1p6WH58B6PGv+IQ9bse4QmvGn2qIKwjO5ldNh9WPwRBJ7iEQR4IcIggi4BfFB/5kpfywv0G/aN8UeSEPAqybPH3r+qgKHGH1zYo0afAW/0CbpHwF7DL3/5y35LA8u0kwryYGFgIZO+A2OXZf0y80vfaSuLHy9t9MUu5delPOZry7KcnKByUsJFUOafcIQQUK54rhSYGPnHGvsiACZce9YVih7PBMsgeEnYLM0//gAMJsrGgIkfLwKTDpMYkzLLWKFxRvnvfe97/ltj4/Z6xNoJ8Y3lYeKFTgU2qBcB9gvxhg2PtMk8TSZ4Z9gPhXdg0aJF/swfJv26gb1xeMfw5LDPruxf6dlPhRcLo4h/+7FsOw7Yy0U/QLb0CzbDc8/kiLHCd+NY0mKvFHXbZUfqJg99g6UjjHuApcVwM7x/4H7AjX/q4XVlyYk+SfmNNtrIG1gcjwBQHl7T7zE4YvuvyAffmPDpl3h4kRf7sNLSKcOYoK/FYIsttvD73zAkwQn+0NfzfJhYBsXHP/5xP0aoH3rhH54rvMCMGeqyxxZgpKo/c2V8FQGMYfpnCIxptgAgU/BgfBJk7GE4FzmwFQMXAwo+8zIHzxkjyF4GHOMeg5l0taer2g3x7OO9DKxJ2eSODkN/pOmyPvK4aZzoh4A9S7LpNsP6u5THH4XILPD7pzn63HaIx7xisrTyds5SFP8KGmDgwKRzAGOCiR2DrQiwDI5XBKMGYKMxaXgdMeT6DPwDEwMLnGXM9BnfrnHj34X8mzg82LRrvGifPsgxHRiRGPcsPXPgapeTZR/4Mmk4sJ+Qlxv2ArK/tQvAyMNB4YCfWYuvJUSm0oPVpcuwJblOVDMsAbEUqOWtiUK+p8ji/SlqXEEKS2taBkQeGitduvjzsli4g79dIsxbflLyTcN4wUgGWCFgiRB5qi/2VU7ghzHRdzzb5J88V3gju4Iu5YGB9ZaWCGf353dd+K0LfCtiLxdi8CqXyLciWHQ/0QULL3Q3HFf8CxcecuHLLuCVKgSaQAoVGjI3ygEt7TTayFD5WA7ISFFGlggJKMg+Gy0YHXg92PtFIL6QoY7x0ucXGk3IGFgsEQJ9P6qBeYVl92F+eXLk6V/aMpiffNJerEt5YGBd2BKp7ADlv9cYWv/XhW+6sJoLITzqEjj45XPhA3fPxibqWdcFPgK2igtPHhLjbvJAjOG8JcnazlPHkKc+DuD2h/+D+78+npatyRpYkgv7fDBYOCqkr0aW8GJsE3Rflg99Lie5VB0vTHpN7Gesg3cysNgPh24A+u5Fpd9lHalSB18mrQ7NqZJnF/jH5vu28MDAqvcI7zjm7NzmaObDXcBX+B0XbnBhfxdCwOD7tgsPhw/c/bku8Fe+37jwaxeOd2FnFwpBzGXIpltOqu7zW10hIicoMzznX3wD77sVGvy3BpbkgreE5Ub2wpT9xEvTlMljNQ0eLMmlynihLPrO/gu5aRkVqV8ej0nyYDGvcLxJbH4pQvtCytsHD1aX8mhr1+omrtNgFN1nOg8G1vPMfZno7q7QTRkFefWZff2ZzYTHazSRW6XMuTicdk7gH0b6N4iUGG+LaXEmJZ4TYnG1qTdO6sGq5poWp0xWm2m41JUeo8PSVydN4IwsmBxpoym626SpLfnVSRM4cywCG8TxHCAXjCotR2EEc88/D5ukrwxNMv7AjaUkJmjiGmd58SUf7VOuzn5YhibhjhxsHLyYNBgvSs9LH2XxRPJPRA6P5d+WGnvUyXPqJU7dhLQ4PBcOxPkTBOUVByfK6s8RxOlL0KM4fKF90okTyI/ng7pYHpSxhQeLvJQnD3EAHNLitNMWTeDAv14BeBDSZOmz8T7TNE5Olg4bhybu5cHStQs5If+uoC0DCw9WuHuf+2J/cZrLJTxXfHht/rc7nsz3fhed94VTzpDib+Sc0QHwd2YMKk6z5nwgDm9EsTBAUNYMYAY0A5w07m0cBYAbmzI2jluUiQog3cZ5M6MDUj/pNk4nZICiXGyczs49bfGcMoqjdHD36zRnxelcomOgaZAT/TCt79GX+McNfYc8Yd+jz9Pn1F/71PcYn4w3cFcc/MDV0mHjsfHEWIVOymkMkab4QhlP/CuUozrwTC5btswfkInBhR7kGBbOHWM/EUtebNzGcOAeDw36kvKc/cVxERiy/GMVncpyMkeV8DF35ECck+ThNXn2339/763m+ApeZDk8mLOj+H4qxj2Hv3LQLB8vpzw6S19tQFfy+R8d+Aze9GfOb7O6nE9pIT8O/eyCJgzYGE0cW8KB0XxzlYOE+YYo/16fBJrS5JRFEzJkXgLIB3QhJ82JHoGWf9oy7fgg2wUuzL76zhJ5jLs84cJ7Z2/n/b7PpWzuwqHznsx6vqjvzS58N/JcSTEP1gpO2ebgSpQtYN+AGNCcFYOyJh3FQBohLY6xQ17yEEcxoIgVpw3Kkq44Rk+eNzkmNAJlbRzc+/omB63QB77gqXiMDtLgE/9642gB+AitMdlYOUk28FnxQU7V+h4Tw9e//nV/VAlnbqGYmCj4ODS85fNMTLycc9W3vkf/YXLmE0CcAcaBu8Q5a82Om7S4xhPfFOSD2hgCi9y5Vmn9kD7eVd+jXb5RydlbGJHjaArHE2X4bFOY3iVNoY7gRZcDnA877DCvO/msEUc2cB5e3/qedDmGOWfUcV4cMgppKiqnPva9IjQxz/JdXIxuDPdDDz20k/GEXlt57EzrxzS05cFa5gwLvFgchLECI8PBli6c5GPFfvDBnufCu13IMq6oFQOOMAfoJAATs8DGeVMboD0OoHh4k2YQMJEP0A0HmNDwRuCh4NwY5MK95MJ+Ct5AORjXjpdusJ3bKkbRBhts4A9iRaGzv4jDfznUtwjw6Sto5gVLBwAXKd9GXuSC4Si5VGnTyhGDS5AnLj1KmSJxGR+U00tRGGevnw5rBhfqx4Cx+OaJ56HD5ilCBzgrPzRhuDJ2qE96LI0+m56HDpvH4psnLhwtvnnieeRk6bBx8MW7CODtZHsBYOmw8Tx02DxFaLLteCRa/GlrNmP/1ZkuHO4Ca2Yvd2FrF0gLAauH/+Uy2m2cfBhoS1zgA1tfc6EU0BEG6A8HkAeDcJBLtzLBqABYHgRCuejv8kx0fQOMP/aOAZxaDmiDrb/J8YNnhOUolgP5vA6GTB8hlEsfcayKE8uF9hw3+h5LhH2GSZQLS7gsqTYB2nfFi4B0SxPtjKuzy3mlTUuD/VK8Tv7chaNc4LPzHMnwOhfsRvVD3D2m7xEuvH5l/APuCrzZhUUufNIFjDaCLetuxwNLUgP0hwPIg5OaB7l0KxOUIG+GejsM5cK+FkBvpt1iO7d19o7JwOJzOEBRAwv6mcRZemNy6PojtXMpfPIulMuTTxZGjKUxs6zjicI71EfD3nJ80uTCCwR71Jrq54w/dAmeyCI646677qr15abLeaVNA+sR1xn3dYHX401dwBMFnOyC/Tfhie6evWE2HO7ugQ+6QDqvqAq2rEseD126DMdjN305kAebZQe5dCt7DAx5r8AklEufPVjgLsOKN1biRQ0sJnWAowtYIuUD1n2EUC59xLEKTmyoZvLH8yGYBA/WpMkFby377rTXS7yu68pLCt5kXsxoJ4+hw5j96le/6vff1YVHl/NKmwZWXfyqXE+XLsPKyC/ACpAH+14GuXQr3NDACuUiD1bfPAks7YG78IOLKPaiBpb+rcbSFB+cZr9ZH5cJQ7l022vqb53lQcAuEeLByloiZAK/55576kemQI2TJhf9sy+P4VOADaOsGFi86OiljTE6DrSsWHTsZtXb5bwylQZWUx0qS8jDs3QOIA/O5Rnkks6jNp6EBlYoF3mwirj728Bbb+HWwCrj8cCDxTIjyxrbbLONXya8/fbb2yChUBuhXAoVnoDMGFjsg9OSLygjzyzDHjmdeOKJo83UXZA5aXKRgcX4aQIwkuTBov48BpZknCdvXpy7nFem0sCy/0bIK6QhX3McQB6coTPIpTke56k5NLBCuWB48DYoJZinzjbySBnrTZk2wbWoYsWDJa+J/oHIHpUYcIQFm4PxnrUNoVzabr/p9jCwWB7kX2wCDK4sD5Y8H5y91BVMmlwefJAv180eIdQEz0IPVp4XM+WRPOvAq8t5BQPr3+ogYpLqsAN3kvBeqLgiD/5aP8ilWwlLIQqLUC7c40mQElS+rq/Cx3qwUKpFDSw8WCxVC7bffnt/CCcb6EPg3K3TTz/dH3oZPmv6PpRL0+21Xb81dNX2OA+W+kCXBtYkyYUXgzY8WEWXCPXyJnlK/lWuyKUrwMA6oavGu2q3qOLtCs9paRd5nHnmmYUnxGnhT1t04tLXRnHajMkFI0ZKsC28xrUjZWwNLDxYRZY+dESDNbB0ptH1118/D4UbbuBLX+5v0Cs3xs/L0GBCTC4NNtd61fJg2YbH7cFSn+zSwJokuXAaPh5BXmyLjBMrk6w444kXNpYI8T7i+dY4zSqnPPJKZ+XN+wy5dAUYWPy7b6qgS5fhVDE6J7HIQ5/WyFlkyFYzB/gnEZOUNbBichnnSagZrVzVSSnbJcKiHiyMSxSxlghpmEmdj8CzTGiXAjEA9PbPRNU2xOTSNg5NtcfEijztPwhpa5zBrD7QpYE1SXJR/1133XUbMbDQJfxBBH2CB4mXnzxGkwzlhbRE2NRYGeodOJCbAyinAbrjgBQab5wWQrn00cBCcaPEMYgERfdgyRNlDSzqwsDi2AD9w5A0PslDW7z9d2FggUMoF9IWAmC8AqEcxslTEzPlmzp2IA9/J0UuGFj036Y8WPoXoPQJLz8ygrP4qDx5jLGsevrybCo3uTfhEu2LQCcRD+TBicKDXLqTnhSi9WDF5MKbqJRgd9jObRl8wMvutRg3Ic+twZ1+7Da4A3wzzcJ6663n612+fLlPxpPF8iDHOPA90y4MrJhcLM6THJccYgYWHpE04wkDS593kpHWNh8mSS5scOd7oxiETejdUJ/k1RsylOs0sJqgL2/fmkoDa1LeMvIKcdLzIY999913wb6VT4J8Yh6smFz66MGSgWX5PG5JyeYljqHEBB3qBvaP8G1SnbHEh+DxdnEYKcaYPF9hfU3ex+TSZHtt1o1xxMnfoRx0nzZZ0gfWX399j2pXy4STJBf9kQCc03haRe6hPsGDlcdokoHFv3Trwkt9pwo9ZctOpYFVlllDueY4UNdgag7DhV2zFKL1YEFxKJdJMbBQqkU2t0J/SLskzsR99913+31Y1157rV9WWbRokTewMMzs/iyVafoayqXu9rqgCRoeeeQR7xkM6cFgBtJkioGFgYxx1pWBBX5Ny4U26gD4yMtDUwYWhhIb22kDyLsHCzlqHOYxyOrgRZN1TKWBNSmDoEnB96lu5HH++edPjHLqE+/qwgWXPsaT/axETC55Xf114ZWnnjQPVtpkHKuTCQHaYoAxhQF2//33++VBjm9g8uAfh7Qh4zRWtom0mFzqbIf9OZ/4xCeS2PEUdbYTqwvjaM0115z3aJyBJflRtisDq2m5zGNKhQRwhadNGVj8QxHjSsv2efdgIUctD9dlYEFrVzCVBpYGa1dMH9qdywHksf/++/sBP/fJcNcWBzAStCFVbcbkghGG8uzTJ2RQxPYfhOAP7uzXyYtnzEgTH9iHhUHF1wZQ1tttt51/pP1abS8TxuQiXOu4Xn311V7GbdOFDDDqnvWsZ80jA5qBmNGMnFlSom9StisDq2m5zGNKhQT4CL4YWPCvbo8lOsL+6aSIB0tHpdRlYKnvVGBX6aJTaWDV3ZlKc38o6DmAPFCsg1y66xCxJbKYXJjEABRoX4CJWXgJJynVvG+vKPM0DxZv4muttVbCxuDNNtvMLxHSjgystje6x+QiuqteMVT4lySgjcpV68xb/uGHH/ZZi3qw8HoAyI+y4E2faBualEudtOjFQwYWdecdJ3nxCA0sXoDGvZjBvyY8WNTbFUylgVV3Z+pKeAulXeRx6aWX1j7IFwp/2qCDSUl7H9ReTC4yQrqYwIRXeAWX0IPFmzkQ83iE5bmnDtEWe84yIbDDDjv4Kz8YXnj92vb0xOQyQqpi5Oabb/beIJZ22l76xPOEp1BLRJYUGcwxecrAwsiWF7Zt3MG1SblYXlSNgyfAGNE4UVrVulUeQ916sDQ+s7xS4IDxx9ERbFXIyqt28lzrpi1Pm8qDFlrbhfuVMA1XDdZpoHUSaEQe++233ySgumBxZEKKHe4YykWeIk1qXTOEt9OYcaQxHpuQYzjH6rD5tt12Wz+BbrjhhjZ5tNF9TmLDN02OFw5VhUb+zde2kYKBxdEXdh+gWJllCCA7AANZe36UpvJtXJuUS534a0yAr/hVtxES82BBA3KRERzSJJkhRwyyugws6YKwvTbu8WC9to2G+tRG3n0ZfcJ5IeOCPPACDHLpTsp4sELFF5OLvDx9MbB4UwZP4SUOSqnmmTiYcMint2zVYa94VfbZZ5/RhKRn7Bdpe4kwJhfhU+V61113Jffee2+CMYk3s20DiyXC2PIgNEmeMg4sneqLGP+SYV2Ts21nXLwpuYxrt+hz8RCeZhmuReu1+dMMrKw+FcoxK69ta1wcuXQFGFhHdtV4V+3ihhygPxxAHldddVXqIYL9wXRhYoICYkIKlwhjcpEHS2+bXXNEeKQZWJpMsvBMqyOrjJ5xLEDbS4QxuQifMle8gD/+8Y+Tk08+OWEplENU2zawwAEDK7bBHZqyDCwrP/UDpZXhR9kydculLB7jyumlo4qBxbElbOtIAwwsHdFAnjyGr2SGDOl/uk9rI286cukKpnIPlgZrV0wf2p3LAeSBd2CQy1y+tHWnt/3QgxWTi/ZV6G2zLRzT2hHuUuDKpzfzpg0sPFjgwITSFsTkUqXtO+64Izn33HOTnXbaKTnkkEO8V4O+UJcHIQ9ufI4Ib2SaBytLnvRF9m7BF5YXmdjrmpzz4K48dctF9dZ91ZiAp+KrjK68bd1yyy3eKE/LH3qweDFjOVLjNVZOOkWeyKy8sfJpacilK2jTwFrDEfldF37rwm0u7OVCDDiMZrELv3bhXhfCJcxNXdr5K58/5K6HuVAIunQZFkJ0SjIjD95eB7l0I3BNpKEHKyYXlCQKsIsJLMYd4SHPhfJIqWoyUXrsmlZHLG+YhgcLeOyxx8JHjd3H5FKlsdtvv93vJeMlB0MFwGBVv6hSd96yOlohzcCi32EMxOSJ/JC/9hMRl0zztl9HvrrlUgdOsTrEQ8ZIWQMLA4r+keYdCg0sZEOfyjKaJDPkR6ir/3U5r7RpYB3rhP2gCxha/9eFb7qwmgshfNAlrO4Cm+9f48LnXNjMBYD/iJ/jwldceKYLm7iwxIVC0CXDCyE6JZmRB38NH+TSjcD1d/zQg5UmF5Sf3ja7wfjJVq1SfjL1ySWlPG/maXXY+tLiMkqzJo60smE6y3QyNMJn9j5NLjZPkTh7r8LN+20vEUI3/Srsg5YODAIZBzadvqila9KpRzK1+ZqO1y2XpvAVD6sYWBr/0h0hrqGBxfNxBhZ1ghNeyHF5w/ay7rucV9oysJ7qGPAKFw534XEXvuPCDS7s70IIh7iED7vwKxd+5MKZLhzsAvC3LvzQhZNd+L0L5LnVhUIgq71QoSFzYxxAHnvuuefobaqxhoaKoxzQm6KMBWVKkwuTmRSs8nZ1ZSLF62L3e4ALihrQZOJvUn40GdtJOiXrvGTxTDyclyFnwk033eSX6biOgzS5jCsXe87SHHvINtpoozmPMXRYssvDvzkFS97wbTz+QSgvVKwaZBozmJEfRpWgKwOrTrmIliau4iH4EgCl5W0PAwr49a9ZaJoL7KcLj2kgxzijCTlqDDKueGmhrqogGqvWU6Z8WwYWnqbfuHCfQRID63nmniifsn+2C0u5WQk2304u7VEXMLI4le4MF/B0pcFT3IOnmbAKGaU0cG/KxWnjdDalE5cFnBanPuUhrk6hOPdhHDyUTpzy5FFcHZ70WBz8lG5xT4uTt680MRj5DAn0LxSaLB02Lhn0SU4oSQwUJjDb38Cbf5WRZtNRgvLYpNFh06lHdBOnLiAtTj9QHo0b8iuuccMVPJhQmZiVTl4tdaku2gIsHYpLsatNi3taXDSxJ4229CZfhib4zynxAGPB0mHj4Cd6VqxY4fNSRnSEcXAX3Wl0LFu2zPNugw028HnJB2iiw3AsQxN4C3cbp26lExdNTNi0KXxjNNE/4Y/yiCaMfeRgcVf/JK/S0+iw6eIvuKm/2bhwj9EEDegx6qMsEKMjTAc/ygCiKStO3io0wUOBjsSAhzGaLB02rpcSlsaFu2hV/TJsRBMGFv1JuCsdXKhDhjJx+gL1kZ+r8igOLjYO7gDplg7ias9naPmnLQMLDxbeJgvck25B99Ystvkwpt7owj+5sJ4L97pwkgtp8H73gM0RCivIqLdENuoRgKVLlyYoG4CzYPiXBHDllVcm9903axdeccUVCd/pAi655BJ/VgzxCy+8MOFNEOCberLqzznnHP+mT4chzpWOTBwgH/kBylMPwBk01A/QHu0C4AE+APiBJwDe4A9MIk38g/DOO+9cUDRNkpzwYMhzEPY9+hWKzPY9FBYf5QW67nuMIcYVYMcTXwaAJhRuSFM4nlDsTAZlxhNtMPFLL5TREWeffbbHFSOXyWmcjkAet9122+hfXFV0xPXXX++/qciEZvWe9B8TXBmaoKGI3oNu6MrSe/AZT1coJ9qivHQ5xpX0saWpaV2+ZMkSr8c4tqPPulwvA9///vdHxsc111xTaH7SnkMMynA8ybuleVM6AgMLXSM5hXMuOoV+iJzod8Dll18+Gltl51wZ277CBfqznaMLz5OFY9zNkTbBxfFgYYridRK8x0W+vfLmTHf9sh646zNdwLx90j9sHrpo6MHCQJtxQnaG7cyMUwA+hHGnlEfpxN2E4vOnxd3gHuUh7hSFz68492GcDEonThvkUZy2suLgrjxpdNh08nIPpNFh08FFdAt3yiou3LkqznMbH2ia7WN9l9Npp50288UvfhHxeZkLX+QXi5955pkzX/jCF3x+28fS4tTRVN+zuId972Mf+9iMU9BjaYKe448/fkRrGh023dL0uc99buass87y/CBd48bG08aTm4xmPvShD3k8v/SlL82ceuqpc8ZQSBP1AGmysengCw6AxV1x8rqPOs84w8DnsTShIw8//PAZZ8il6os0msroiBNOOGHmjDPOGOFr6VAc/iDvkKbjjjtuxhmpoz7mDIeZo48+eh5NVh5pcXCnLmc4jHQdFZWhiXLCPSs+Tk6UlcyIWzml0WHTQzn96Ec/mjniiCM8TdSLnN1Lru93tr/ZOHRQD0D84x//uC/nHAQjeYhW94cl/8zt7fP5hfsFF1wwc9RRR43kpHQyge/ixYtnTjnlFB9/4IEHfB3Lly8vNJ5icnLGNjZFaFfMtRQauptdgG2oclMtriG8U+u44L1I7rqlC6H36RcujY3wW7lwuQsA+bQxgY9kPYfElQDTgD+avcz7ZaF4drHYPNLbutyjPLJxuTZJzxPnzUpQJK63X8qyzKBljTxxi2+eeB46bJ4idIC/8pehifL33HNPsu66647kMOk0SZZ56LB5rAzyxMV3K4M8cSsn3ha1udj2PerhDRW52HSW5PAaABb3tHgeOmyeIjThfdI+KEsT+FKPU9xzcLd0KA4t0CQc0uiw6coLD+Cdlkxsuo2n0eQmGe+54d+IeLC4t3TYuPB1E5/3KCIXQOlh3OIbi7tJzOO98cYb+3osvnyuBKBv2HQbT6NpXHqMJuQE/ao/RhPP3CQ+yiOatLSkezwl4+ShdqDRxmmXj13TJw488EAee8hDE+1Ljyl/jA4qtOnCm/Q8cYtvnrhwoX7i9DGuSgcXZ+OMvNhKj8mJOkiXlwpvmHAQTc7IIZvfc8VVNEkuuteVPNRBnRx7Qlz6iDTqVR4fcT/CkftxcWjrCmYxb7519l/hfTrcBbxNL3dhaxdIC2GxS/iAC+yXYs8VG+G/5gLAs792YVsXsGr+wwXW1dg4nxtQUAP0hwPIg4l8kEs3MmESlZFiMUiTizWwbP4u4ppcY22jeJm4xwF1oPzLArzTkkbROlSOCUVLhOPqSJPLuHLhcwwsJq911uG9dy4w+SFn4Tf3af13yMlOlLEW0uQpA1llkCWTPMZYUdCLA0uwMhTy1lGXXPK2VzZfyGsMGoyuvABfZJBpO4wtK+NLZ+bpGXKh7bQxyThkiRDQeKxjea/LeaUtAwuevcOFtVz4uQtHuXCQC4+68DoX5KFy0eQ/XSCdzU6nunCYC7e5ALBh6h9cYHM7m0DYPP9GFwqBLO5ChYbMjXEAeeyyyy6jN6HGGhoqjnIgzcBKkwtKkImoyzdDEYICxhCIQdqEHOalDin28FmeeyaDsoaI9sNgYOXFN00ueXC1edjP9IxnPGPkYbDPiFcxHMO6xt2Hk34sf4w/GFFM+FZ+6g/yYsXqSktTGfDRnty0vGF6XXIJ6637HtrAVUA8zehRHnuVEcrno4oaWNSTZjRZQxkDHwMtLa/FZ1zc0joub93P2zSwMIj2dYFXRQ4LXeICcLILz/Ox2R++3InR9VQX8IHLe+WiHr7hfhe58HQX8ITd70IhKPNmU6iBIXMhDiAPTpMe5FKIbbVkxkhCicU8WGlyYTKjXNE3/FoQNpWAAwaKlhPMIx/NO3EwqWpSDuvIc1/FECljYKXJJQ+uNg8GFpNkGlShK63OtHT6EgZUFsQMLE32Vn6Ky1jKqjN8pvro4/ozVJgn7b4uuaTVX1e6lghVH+OkiAdLHiqO1cgysPDIWhjnlUJe1lAmfx0GVpfzSpsGluV1p/E+vHl3yoCeNY48+OfNIJf2BcPEhgKS8rMYpMmlygRm668axzgBf/ZtxIAJOc/EgWKP0R+rM5aGIUIdZZYioAE8mYxiBkSsvTS5xPJmpWFgpfGOcm0ZWNCTx4MVM5itQSRaq/RPGWV88JoT7mVMqO6sa11yyWqjjmchr4saWOL56quv7vkTvmjBM+q0e6zAW2MsZjSBE3pIslP+sp5hyyfk0hVMpYGF8AfoDweQx4477jjHbd0f7BY2JlJgTKYhpMlFb5lStGG5tu75yzeQ5oXJY7Cg2DHCrGIvir94F5s4xtVlPXB58KW+NLmMa8s+ZzLjpSaNd+Rty8DCMGUSDD0eFl/i8Cc0mGUQWflpItezsJ6se5XZYYcd/ISPkZUX6pBL3raq5IOH8FIA3iFf9Sx21bjHgwWEXiwMrHD/FfkkF+kc0gSqU7qFdPJLHspX5gp9XQEG1tpdNd5Vu126DLuiuc/tIo9bb711WCI0QmKy5jyYpt++pOyk/AwKXh4xuWgyk1K0ZdqM44EB2EcUg9iEHOaTAhdN4fM89zKwxMs8ZZSHMlriBN/QG6B89lrHeOGcKPrWOANLS5i2/brjotlO+rE2eI5BbEF90E7MipcxeOkPeF7gC3LFCM0Ldcglb1tV8sFDa3QUNbDk1StqYGFA01ZMLpKjHYfwP5a3KO1dzvcYWAcURXjIP3Cgbg5ooqu73kmtjwMgv/e97/mPYDdJgxSYjISwrZhcNIHFnoXlm7zHwFp11VXnTBa2PZR5OCHb58RFg1XsYZ5x9zJOxctx+e3zMh4syoM3B1u6M7xsdbnjMk7HGVjQ1LSRLxmVMbBi8sNAYjLXs9xMcRmZ6NUXqEPGX946yrSZt+668sFvy2viRYwQeMS/T7W8HHqw4FmaN5KxEhsnMrCkW6AVOZR5aamLT3XUg4F1TB0VTVId4drwJOG+EHFFHtttt928NfuFSGtemnSSNh/ibRKkwGQk2LbS5CIlKKVoy7QZZ4kwy0CIeTxC/DQhalINn+e5l3EqXuYpozwYWCrPpMRSzTiDRnJ58MEHR1+ZUH15rxhY8GeVVTgNJw7gBS7iUTxX9dQqBpYme2swgBH9uQzelFFfKGpgSS4XX3xx4g5Erc6YhmoIDayiHix4zhIg/OHKVxMspC0RkqeIgZWW17aVJ45cuoKp3INVxFrvSjDT1C7yuPHGGwu9RS1k/sAPDiwEmjaweJtkQtFhfpavaXIhL8q1zARm668ax8DSW3SsrrYMLHiBEi9jYFHGLhFChwyOGE2kSS4YZ3yyZJxBFqsHAwvecWhkGgivMnSl1RlLF72hkRTmlSFg6WWyx+AP6aBP2/5JmZ/85CeJOyk8+dSnPuU/uRPWzz31WQNLuMXyhmmSCy9HN9xww+gTL2G+8H758uXJ6aefHiY3do8RDy8F4qvux10xoPSShYEeerDqMrAw8JFHmT+PWBqQS1cwlQZWV8we2h04EHIAxR8uQ3AAJIp9iy228IZWkQ2oYf3j7pk8Y96rceWYhFB+XQF8G+fByjNxaBLWhFGGHiZ3JgNriGhCz1LuTByUkQdLBkbeSR0Di74RW3IZRwcGVpb3j/LqF5aucfWWeS56MVSzQPyx48FO9rZsaGC5z7ck7lM83tsCv/g+ZQzoD+oL4BOOzViZME3fQbzsssvCR/Pu6QN86Jvv8pWR47wKcyTAb/GS7HnGia1WRi1pdRpYvKRYw0/9ry2+WBrrik+lgdWly7AuwS2kepDHlltuOZVLhGxk/+QnP5n88Ic/HHkieAPG9b7rrrt6Q2vFihWNiRvlpQk+bCRLLkxCMk7Ccm3csyzBRFuHBwtaYh68InSEBtZDDz3kJ3Qt9cbqgn8YYvIUadKTwRErQxpy2XzzzUcGrj68m5Y/lp7HwJKh0bQhLSNG9MfwJU3PLX/ALfaPtdDAkpGoz9+k0YRMrAdLuKXhZNORy2abbebPZltvvfWSm2++OdWQUzm8ajL2kEkMMML4swl9pQ6Af9aQIW55Oq4N66GKGVjwLM1YTlv2k9FmPZF1GVjIpSuYSgMr662yK0FMc7vIg6/eT6Nc+Bs4E8T/z96bgN1SVGfbnfx+cQgSAzKIIAcZREEG8YCiDIKCDIoCTihqME7oZ4zGOCYeRY1GHEEUnEAZBBEEGQTCjIwCcgABGQUUFEWjgInJ9e9v3fWeZ7PeOtW9u/fQ3fvdva6rdteurq5aQ3XV06uqq+2jqdm3v/3tsK8Mg/Laa6+drbHGGqGzn+Q0IQOPOrK4DRbZhUGIjrYp0mBU5IVhQB40cPgBdRRZAFj+SVuDJl6mPNK5qgALu1x22WX9YqsCLAZApnWKdEfhAhqTBtKykQBUX7AoovPKz2kNzFHWwLvnW7YBEAAo8gCWL6+qBwu78KAEbbfddsG7c/HFF8es9f8jx3nnnZdtsMEGIU1tpp9hWYT7/9hjj+0Dsfh81f/UK11yLQDEewUHled1lAJYHoDFZQ0CWD6/+iXZzp+rEm9yXJlJgFXFOF3eejSgzrye2tpRCzf+XXfdFT4T9NrXvjZjapA1IqSts846YV3Jk5/85Imuw6LzUkeW0kqeXZr2YDE9yNMuH0nOozIAC/nzZMwrN5Uee7AEAAWiUtfonACWnvqreE0oV1NSqTpSaegOGgSw6lprJ8DkB/0U3zqv/OTxg72/Bpv6gRmwJXlou3kPBx5wU19VWwiosAknwOmee/jiW5qYFgTo7rTTTuFtWLWZOLfWOMlu8fmq/+FRuuRaAKf4LlMWupN3k7d48Sb7dVJlAFbsjUvZUf2St2MZ/tqUZyYBVpMuwzYZvy28YA+mPGbNLnzgmsECMEV49atfHUAWwIv/EAAL4JU3IIxqQ78GKC6ryC50sHSKTRGDUdF39OCLgYOO33f+Mb8MqHlTpHHeov/xk7kGS4Go1LU6p/o16HkAkboOuwgcASSqerDEW9H0quql/EnbWfJKftUdH3Ve+TnvB3ufH75jDxZpgHI8ximZGPQ9wCrrwcL7fMEFF4T+C1tiHzw7g3QH+Fp11VWDLQFksouXg7jaSVUgHZej/+hPuiStKsBCd5qW5QGH+0sgkPIGASz0HOuf/wJtlAHxH3uNCrCaHFdmEmBVQetzpu5+J6kB7HHFFVdUeoqaJD+psu+7777lOoVUvippTAXSiay++urhsrXWWiuArC233DJ0vCSuttpqYe3FuJ5ePX90dEUAq8gu8O0HMF9uHXH0MQggaBDxA3LM26Q8WJru0dqfuF7+M3AyUIlPHYv45Trswlu3DD5PeMITKgMseGLQAQAMohioDMo/zHnkZZBHniKSfnz/7Qd7fy2Al3KVl7YqjwhtNx7guZa8PNxIL2UBFmutsAfXs1YK0IEsefWIT9oIwAoCMKvN6LyOAi9VNj3VtfER+QBE6Fs0DMBCNggPFiSQT/noQQAsnHQ/8tZKJp1KASx0GD+4KH+Vo9pAlWvGlXcmAdagG3lcyu3KKacB7IE3oq12ofM47LDDsqOOOmqs68TusNezWWvlF1jzf5dddunrQruUj6Nzja3B9Acdogae+HyRXQY9ncdljfs/T/vjAlh58lfhGc8FgwT6BLjKGyHvQ6osgI4GHM4LQAwCWNiFNkOdDOYa3FJ1pNIAGwyQZe63QSAhVX7VNNqhZC+6VqDA6yc1MFOGQJIeAjgqLU8m5RV4KAOwqB/98wCGHAzmmrZWPbSHFMUAi4eGlLdVIH0cHiyBDa/vqgDLe6gkq3jTlGoewBKgjMEkekxdMw6AVaadp+wzjrSZBFhNugzHYbSFVgb2WG+99Vo7RXjuueeGAQCX/g9/+MOwRuqII44Ii9KvvPLKyus0sB8dHWutFi1aVGhOBgU6nkkALLneNUUVM1Jkl0GDR1zWOP8DYtCHpsnyytYgokEllW9cHiyBNMoDVDHQMPgUASzODQOwsAuDP9fiQdDglpIvlZYHSlJ5aX8CHqnz40gDMMlWReUpTxmAJXsInGAXpdF2U1PuklNATAArDyDBK2+LiojDmx6KVE5eXfAmwMERcJW6z+XtSZ1T3WWP0p10yXXEi+4RXzY80rY9CEWvaoOSFd2liLzoBUDqKa9Nkl/9lM9fJd7keD+TAKtsY6pixC7v8BrAHrxt00a7sFs2r1I/73nPy174whdmP/7xj7NvfOMbwVtBx8seNqeddlpl4QFXAAWttcorQF6kcXSucR0afDTwxOeL7EInCf9N2Axd0NHrW2gx3/qf8njoHEfsx6CaJ7/POyiuJ3kGDnmv8EZKx6nrOefBLQMB9pYXIHUNaej8zjvv7HuwkGHQNb4sBjMN/j49FWcgFfBInR9HGoN+3oDsyxcoEEhADwQN9j4va6AgAVxkkMw8sKCDmJSmfOJJ9cX5+Q+o0uJ5bIJnRtNm4kvl+uvlwfEAi/NqOz4vMtCWafdFYM9fkxeXLNIl+ap4sASgJBvX0/ZjgJXyRpGX9s19K/lJg9CRL3MuNX/nd50vc2yijxJfD0/EKmUGjn5KZgbEbb2I2OOJT3zivKmytjDN997wlDzjGc8I/DGQMSBvuummobPgsxiAw913333euoZB/N98882hHBa5DiKeiCcJsPwg73kpsos6QwYu31n76ycVV+eswSmvHvGlQSXOR6fOgDUOgMWgwcDKGhzWzTGQrLnmmgGc08EL7HkeGDi9DFwDz3n86lrsAt+ACA3mTFMNApy6Pm8w03l/BGykAILPM2oceWWrorKUR/pJDfa6Xp5BeX+8p5K2m5JJQFJtWwCLe15xla8jAAu904ZuvfXW8NAhD5bKoVwBcF2nNiwvLLZEPtK1bQN5sTPthC1bAHDIkXe/quyio8CGb4/EqYeHlkFjo/TmARSyaZpaNvHnY35o87y4I6LuvDaJXgXelL/qcZBMVcurkn8mPVhNKryKcWYlL/aI1yK1QXY6NjrN5z73uWH6kgFw6623zjbbbLMwgMIjbz/SAbOeqiwxQPAx50022aRfTtG1dGCTAFhyvecBjCK7aPBQh1vE/7jPMQjRgWsQzSs/HpDjfBpQ8+SP8xf9p23QFgBY8McgK/CT58WifcUyMJALQOTVh13IoylC8mmAy7vGp+cNZj6P4gAs6Ulp4z4ii2xVVDZyS3byqe2pLfpr8QbCOzqGkEF2Jr+u9ddIztiDVeQdZId4ADUACK80pLWB4itVF22E+1py034AW7EHi7rRDy/AQKP2A2pbqpcyBbZ0jrQ8EoCSbOSjnQsE6fwggIX8ADoI0EfclxlO2A82y7t/lGfQkTbTFDVXc1MSW71C8Q2y0FXtNIA9eM25bXYBXEHrr7++43Z+FA8UgykDa1m6/vrrQ4e/ePHiUpdQPgOoOqRSF5XIRMdFp5a3RqHILhqENCiVqG5sWeiceQpmUCoiDSJ57WoQwCwqO3WOTxvhMcG+DJYCT6kBAltSvwZ9lQfPgwY6zrP3ENeuuOKKQQ9VABY2Sw1m4sEfyQdAwMswDuIbm4AST8gjW/n0VJx8sqeAS54seIWwB7omr9psnkzoBYCrAVleqzyAhU7wYAGw8FaKND0pvsSnznNUG/ZptOkYYAkg1gGwpFfPUxyXLB5AyYOFPsoALDx+1KU2qzKlL18nbVz3qU+vEi8jV5XyquSdSYClG6iKorq8k9MA9lh33XX7HdvkaqpWMgCL1+CLXPIM8nwe46abbio9CLElBYv69aQ7iCsAFoNE/NV6db6Drs87nxrgfd4iu6gzVOfor5t0nHVOZabDBj2Zq+PWwDsq3wyCtBUGdQ+wUnbSQJQCWHkDuvjjPIMZAzk2AmTJg6A8RUdsJvsV5eMcuvED56D8g86ffvrp4WHK56sKsARA1fbyZAHgons9BEjX5Od+igdeyvNtYRDAwpsELwAsljhAAA9fD2nik7goBbBoM6R7UtvhHLyN6sGSzB7Q6j7ROV9/HJcsXucALNZjwqvatXQXX89/3bta6J4qU9ehS/iSzZVe5djkeF8nwFrFlHKqhQct3GRhRwspYnOWIy380cKdFl5lwdPr7Q8fZ/uDhW9aSL+uYCfyqEmF5/E0y+nYo21rsBhUAFgAv0HE1BCdCxuHDiLysP7gmc985qCs/fMALMh3roC0z3zmMxmf2hmWABhF4LHILhqI1DkOy0PV67ALgxADziDSIJLXOQtgaUAcVN6g8+gLsA3Bn8rVIOmv16AvPeocPOfxqzziG2AFMUUjb4DyFB2xWVxvXn7lE795+cqmAz59O+Y6AGPRgOzL9vpR2/PeFJ8XAIruxbtkETjQ9bqGfMpDmnjKA7x4ryAAFnVhDx6aNL5wpIy4HgADOvDr7yiHa/F2+vrUdgCL9ANVgDRlxqS2JVDFecXLACwBKOmQ6wFYELzx3VTafpF3GT1hR4FJ6ceXGQq0H/VPKS+w8uhIOSkZZA/lq/NYJ8D6kgl2rwWA1nssHGdhJQsxfcQS2H2NR4KXWzjEwlyvlWVPt/jnLLzUApPShH+xUIlSRqhUQJd5rBrAHuecc07y5hhrRRUKY0sGBjI8TYMIzwWD6aBpQp7y2PWZjrJo2jGuT2t5NDDdcsstGZ4AOim2kAB0DEN0WgIBqeuL7MK0IvVr8EpdP4k0BmgGID0FF9UBf5AGlTgv9mVwzpsijfOX+c80IcTgSbnoV4Okv1568wM65+F5UP8kMKUBifYRezd9XT6O54ZBUtf6c6m48mkQTOUpm0b7R+dqx7oO+2iQV1reEf3InuIpD2ABSmgvAqRq63kyUZ63RxmARZkCAdgem3v7UZ5sLZmQn3s2BliaWvTtBf7RDTLSb8S6U5llj9Kd7g2uk+4933nloSPy+3tG/RPTm3jydQ/klQH44v4t68GiHNkwr0zS2TqHl45iKiNXfM24/tf1FuEKxvBLLOAOeMjCyRautbCHBbxQnva1Py+zgIfqUgsnWdjHwoeXHb9nxyssQB+zcISFSiAr5R6msBSlkHgqjWvz0jnHDRUH5eeooHJ0TtfSSEijYcfn4gG26L8/p7iOqosjlJfOOTofeCEPAx488aSg4HkkfxFxzcYbb9x/8ivKy0CCF0ieIDbngw86DDo6OimOPA3ypp86j6IyU+cAMcjo11ak8pEG/wAm3gx8/vOfn5ct441EnvBe97rXlZJVBSEDT310rjwlfve73w31PetZz8q+9a1vBS+WPCe6pswRgKVd5FP5B9mFgUqDXOr6SaTpqTcenFJ16X7J62Bjj0WqjKppeDxf9apXhZc2uFbTVHE5GnT9gE4e2pz3YMTX8V9P8/JgYYd4XVPqOtJSHoi8vKSLP/FblHfQOQEHyqLdCOgw6AvMDCqDe0EgQUAxr6+R7sW7ZFG9cdsln87Bh3jKs4cWuKt+vilI++S+EVFeXI+ARdyG4RdCT1o+QJx06sBTVMZLrrpTR+luFIDldUQdgD90y3Y26PBpT3taqup5aciue1n6icvlAoHiQQCL82ypE+uUMrw9+F8n1QWwWCXM6xxzr1nMSQjA2mgu2v9lLoTvhiztp8wBsWcv+4/lzo7OPcn+0zLnXhdxJy36yGVBqWFzFKZWUsZUpjYdubE80IE3GgxpcXrdfMMHYHUQqQNKHbnRuTm5kbAJR57USOMcMgIsuBmZWuOJDqLT4c2djTaaa0J0tgw8AC4W0vKUf9lll2W77bZbeAMHXulcAGOK01nDE+kCYgzGxAFYixYt6oNI0uEHeXkSV5z/5GdgpYMBAMKb0smLDJR36aWXhg+7PulJTwplIAf8kEdxD6SJwyuBzhU9XHTRRaG+l7zkJUFHlHXeeeeFV7vFe55M1CE54AleAYZ5MpFfUx7kiWXCXnRs8B/LUUYmL5+PF9mJwYm60LHav5dJcS8TAyTp2MnLQXvRoCs7kcfznhenPPQML8RlJ/Lj9eQc6YB96oll0oBBfV4O/jNIkV/tn3LU3iifa/lPXoi4gJOXj7yU7WUS2BB48PKlZJJ+xK+XNZaJeoranp/ewo54fuEX+0g+/lOOl8PHOSfAA0/yXnk5FOdhC361cFx16BrpQjLxn2uoD3tyxL7Uh6zUDZGfODLw9jOEnqmXl164TvajLtUjOejL0Ku3AdfLgyUPJeXR39HWiWsqGFtTf9z2JAe8+7i3E9dynbcT/yHywQfXoisfh3d4kM6lA8lE/3SHvUnNkYc28nI9fBKHqEdxgBDeLsoBYIkn8nnepSPq9eleJuJ6gxN9Ua/KoX5kbYrmNDv52gFYu1n4vKvquRZn8vYUl8b04T9a+KBL29jim1k40sIbLeC9+okF6H8t4L06yEIKYHHuhxbevyy8y47Z/vvvn2277bahQbP2Z6uttgoNnpuF78BxU/CRXdbJYHi8A+yDBIHOeU0fI/KaPQEDc/7pT3966Oh4O4yBnxvr2c9+dnh9m0a03XbbhQGNG3bHHXfMFtkAToNjE0s8JTSEbbbZJiyspoGzJQCuVDpp+KVREqd8QAgB3rnxuLHhXcCDODcxAzD5kQkQgEw0OtYNbbHFFqFOvEfEkWnzzTcPsiATZfOfm/I5z3lOkJvBYvvttw8DOk9X8ItLGPmQifq4EUhHt8iEHKxToF7KZI4efuAFQIUOuJ766Xx4SrvhhhvCDcgaI9LIg04pB1732muvcA2L0JGPPNgGXaJf+Gaa78ILLww6gRftaYVe2JGdjgA+TjnllH5Hyaah8AmQgTfK4aZlKo79aQA5P/rRj8IgSgfLWig2C0UXS5cuDXZAd0wXMoDcdtttGd8c5M0yOj5sDs98vwyesZuAGfZlZ3h0AbABkKETOq3LL7885Kcj4XraKm0Br9kd1rHRXi+55JJcmbA9ekFubA/vF9v+XdiAtpaSibrQH2Vjk1gmdKHBYxiZ0DF144kBJNJ2kanITrQ/5MB7EMuUshODK+UCzrETR+yE/pAfXXOvyE60E9oc8o5DJvTD4ICtafdqe9gV/cIzbQKi7XG/kAaf2CklE/cj639oZ9gGu1AW9xx7JcV28jIBiq+66qrQ7rhXB7U9eGbahSN1lbWTgAcyyU5syiuQBbin76QN0W4pm/tN95O3k5eJjX5pA7RbriNOH5u6n2hLbIeCTsnHYI3e6Tdpe/St8CmZyItu4UV2ov2gP7UZ2Yk8LGugPPoj2Yl7nf4Y3gDaXIft6fckE22X/ozg+wjsAV/0E/RlyEQ/SHn0qdTBvc6YBLCJ+4gy99MZZ5wR2jxbz6jfox2hd+pEZ+ojJJP6PZY3XHvttUE/tD9/P8EfctI/02cOup8Ak7Q9bMH9gWcfPccyoUfdi5SZ10fQjtAv9sMeshNtj4fuz32OlUXZJy38N5GFRpubQPdHQgGKDozS8GABP+dWb86dfLcdjp+LhunCdyyLc1jZAvnxYKUIDxZlKbCuq2cNwe6LXs8aRQhx3BpcP5243Qghf17cOvx+HuLW+EN+xfkfx8mgdOLUQR7FqasoDu/KkyeHTycv/6E8OXw6vEhu8c61iot3jopz3sfLymQ3Rc86slC2l4l0ySDe9Z+6BslE/UcddVTvE5/4RM/AVih/kEw2APQ++9nP9my39p4NvlRTWqavfvWrveOOOy7ozcuBzj75yU/2zj333L4NvBw+nicT1y5ZsiTIYh1f3zbWOYV0A2Z928DzIDvZQBCuM7d6btuDFxsMwnn05mUifvTRRwf9poeySiAAAEAASURBVGxTRibKkD18HN6VLjkk0+GHH9479thjl5OP86m294UvfKFng0qfdy8HNj7++OO5NNjFyzcumWyw6h100EHLtT3seeCBBy4nh4GQ3pe//OWQDl8pmb73ve/1Dj300B73B2SDUO9jH/tYiHv5kCGWyV7cCHY3gB3yl7HTpz71qZ5toxJsctZZZ/Vof1CRneBbvCsOnx/5yEdCG6Y8CH7hnXOe97z4d77znZ5Ni4drsR02hLwcitOncM9wX37+858PuqBc+PnoRz/aMw93uFZtDzkNTM5rezYw984+++zl7GReplC2PTiFMiiT/oI6KQ/dQCeccELva1/7WohLpoMPPriHnb1tFKc+AzIhP3IccsghPQNCQT7JY8Cr34+Idy7Ii3s7IQvtDtK9ZWA3yGJgrm8zzst+xOlnvvjFL/a+8pWvhHYnfiUT7RxdGwAk+8D7SbKYFyvIS9nIC8VyoC8D6vPSvUzEaQfU/+lPfzrwLd45GsACI8S4wpImTw9PFk+2rputeEDQw5uFZNnG9v/6qNrf2X8WwrOYXeTz/dQS43N3WlrKe8X1oFXWcin8kUSemiGeBAhxHA+G0onzRAHlxSlPeYjzxAQpzv84znmlE+d68ihOXUVx+FOePDl8OnnbKhNPljy5IL+XiXTJIN71H90Mkgmd7r333uHp+5hjjglPN0V2okye3uwGDx4yvFtQWTvxxHqbPWVBXg6eoPCULDJPRUqOMjLhQYB4cucpTnLwpM0TLnWojZFPcfHOUXHO48GiDLxmHFNtDxl4yuc8wctEnLp5YhxWJsqgXMjH4UXpkoM8xHlKhmele5l8nOvJQ7COu8+7lwPvEk/sEDJ4+cYlE0/qeDfhw8tEe0B/sRz8twEjpMNXSiZ0gF00fUI7RUYbTJJ2knzIJI8jbcinE0d+ye3tgdcLfvFa4OlUG49lglcolol0Ap4K6uVe1zQY6fCusmQDbycfR2byQ+gJHULwLd4Vl4y0dfJJJupEJtouRDq6Q0bag7cT9ckekgNe5YmjLUKcww7IRnnkgXSPEKdcww9hyhLvuWSFX8VpL3jbINKJIwdxvD3wY+CkLyvXid+8uHRLmQaI+ryRDt/ilXP+v4/jyYaXl73sZYEH8SvbrGPeYbx6eOEgLxNxgtK9LHjzdC8oTywHHm7uIZ/uZYIHvFfonjYGiXeOKjecqPmnLoAFADrJwhIL3BG7W9jEAmkxMRX4IQusl9rSAgvhj7YAcdzLwhYW/sYCU4nfslCJGEA7ao8GsAfTB5OwCx0Si47pQO2JNxzzJGe6jekVPnujBcR5eVPprGeis8Dd7Yk1YXQCuMCHJaYSCEyHxETHi4u8CjHo0CEVdT6D7MKAogG7St3D5mUAoKNlyrQs0RFrQI6voTNmWmqSxODIQB63bfQmcODrh984rz/PdUx9M8WmfLRxSP99/jhO+4T08BCfT/2HT65jETEkcJTKW5SG7QAQtFcBFNlGg3zR9ZxjkNU18ARQyiP0gpwApNjOpAtgcf3VV18dilm0bLpWZVIG18ek+w1ZROg/7scETpWH+w6QxVRaigTIOUefBaghDQIsAKwpY1hCd7GuBZak11TZABj6N/qMFDGNuO+++wYeU+fjNGQBZNKmBtkR+WnveUQZ8M6UOrqN+6Qy90Ve2aOm1wWw4HN/C2tY+K2Fz1p4hYX7Lbzagvdk/euy9Hvs+D0Lb7dwkwXoWgvvsnCyBUaxX1r4mIVKpAZV6aIu88Q0gD1YPzIpu3CD4sliLQfre1LE4G3TH2FdwaDXjFPXk8aaHQYjFrR7ol4W5Mcdm88zKA6o2G+//cLTbJx3WIDF+q8iGmQXOnu8KX6gKipv1HMCB/FgWVRuHmChI64DYMlDJq+EeB0WYN1ua3wg1jvqfhHAKmMHDWYMcGWJNg2/2vdJ4Kjs9congEVbFkAReJEMypt39PZElkFAUV6sGMx64MO9j2eONZ7yFKt++EoN0PBP2f6eTt0v1OMHfHSI7vPuPcpk7ROkNiMZSOO6UQAWsnieKVMPWUUAi/s8D1xRxjBUBWBJJ6l66F/RPeutIHmxlFf3if7XeawTYAG7d7XAI+MGFjTSHWXxjSyI/mQRQBc+7LUs4LXydLj9wRUArH+9hTk/r0XKUpXOpWyZXb7hNYA98BhN0i4sZn3BC14QFp+yyDcmFpfTifCq9bB84KXiKY+FqQzgEEc6ALnO43rH8Z+OjylC1VmmTFzzAKQiGmQXpgSo8w5beFsHCWAVeS1iPvyA7M8BRuC9Cljz15eNa3AEXHjKA1h5A7quBWBhb70UQ7rAicCK8qaO1FtFf5QhMCKANawHi0ESfciDhYdG4CUe9FO8k+btKbCYl5d0eX+KABYL0ZGJh7yY0G1KrwAs773iutT9Qr0AF4EXvC3YL09e9KO2oqPaEHXIg1XlXuc6EXzEgAO+SROPyqsjegbsaTpU6aMeAVhMd+KdKgLKjA20nTyZmTHgAVazDgKm4m/Y/lzXj3KsE2CNwudYr9VNPdZCu8KG1gD2OOmkk/qd7dAFDbiQfaNYw/SDH/wgu+666/q56SzPO++88JYkN/0oxJukADWmcSCe9ukcAHiTIjp6AIN/Ui6qiw6Ip7y8p2hdO8guDBR4I/TNRl03qaPkiwfLovr8gOzz6Sm3Sln++rLxYTxYAA+8Kili/dMim8by94sGpxQQiMsoA0ria9ARugcc8BAxrAeL+wDAQ3tFRj/NmQc4Yl68PcvIInASA2mBRgZt3r5jeil1P1QBWKn7RWAWXiEebPKmBzmPfmib2F/TYgKJnIdHgJA8gKQVEeDDtwt4TOm6CGABgqDYu1dUb5lz6mvpL6Wn1HXIr+nS1HneoOWBI+9eQ+amaCYBVozgm1J+V++cBrAHnqNJ24UnmV133TW8Hn7iiSeGrRfoPNisk0GkaJPQsrbCq0OnzlMxxPoriPVTkyKADlS206WTh1IDSjix7KeMXZBXi579tZOITwJgxQPvuPnWwKEBVuUjSwrcafBLDQp4WfBUMhXi75cqHiz4SNUrvlJHZGAQ5FrAHXzkeRNS15OmAZJ7Q54f2qvklNx51ysdLwUPCHh3AA7Sr87HRwGsWGatweJeQKds9ZIi+PIARXngPV4LmLpfxB+6Q2eA1CKAJX6REY8h1yuNuuV11j0sflJHwNXXv/718NUHnR8GYGF7aNwAC1kA7JD0FP5EPwKYAPSYAKGkA7Aogz4+9mBNelyJefL/ZxJgeQV08XZooK6bgBtwjz32CHtzse7CXgEOHd9rX/va/hPQKBqhw2BfMfaLoWNm8SwdatzBj1JHfK0fsOJzqf90zqy7EDBL5VHaILsAsACpw04bqZ4yx2EAFvxrEPd1qKxJAyzqJ3iAxUA7DMASkAXkeLtUBVhFg5nXkeK0XU0fsScg8XgQU968o6a7GCwFTIYBWFpnwx5R0CBZNDjHduY6bML0Pfds3gNQyoNFe0Ie3XdeZm8Xzx91AQQ4lgFY5AWM4eXxU1zIA++D1mEBaNmDDIDIflOa3h0GYHF/U688pV7eUeLoSoCxyI6a+pNHz9fJHlkQLxChJ7xY8k77fE3FZxJgqbNoSuldvfM1gD3oDOqyCx0qi4TZcJZpw9fZp2vY6mBcxCd6uMlt/5vw+vAuu+wyrqKT5dA5MQjyJF6G6Jy1PUNR/jJ24fVsSIN/UXmjngOU0CmX9XZQHwNkCmCpE54k8JW8Gsz1X+u/UnUXgSXWuvEiBfL7+0XXVFnkLl7KHMUncmgtYdVpQnkfGKgB99xvACx5hyTDIH64HtChKf6igZmy5P2RDCpfNmF6ifLy2hR8iUddC99QDLBS94v4A1gJ5BQBLOSDAHAsM9A0Wki0H0CE1mEpLXXkwY7r99lnnwBobf+rkA0eYxDICdLy+l8A1ri9V+JZ8klPSvdHQBNyqw35cwAsdCYQBpCOwX+eXL6cScVnEmClGtikFNyVO1gD2IOpu7rtggdn5513Xq6jHMxxcQ46UKbfcK3z9uIk11+JE2RRx6+01JEnW56MB00Pcm0Zu9ChscCUHbaZjrBNHVPVjiUNgFXUEacqYeDMA1gMnnW0OQ3m4k/es3jQ57wG+hTPAGMGpNguuiYGAqrPH4fRoXRO3fI+VQVY8mAJ8ABOGLglp2TwvObFeZEEYAQN8qoIsOR5sCgnz3tF+UUAK/YAx3bhetkYgMV9B79FD3PwCZjA1ugYQB0TAKtoipB7nF3medBbZN5OHibZggZQir5Tuob3PCDSNMDigZh2I4DFERkhAJbf/iblwarjHo9tpP8zCbAkfHdsjwbybu72cFieEzpIvhXItOMwH2EuX9PDORmwBgEsPrfDJyPolOR5eriEdKyMXRjw2CeHJ0eOZQb6dG3FqYADDVjFOR8+y2CiQfzh1LlXueNB158fZ3xcAAuQoid1bxfaWwoIpGRgoBdgSp1PpUnnPDhwLSCh6pQwgyJ8aiEyoJx2KNukBv0UL6TR3kSDZMHjxno1eUr8degQECOvnM75o/Tq15xxnzFoCyz6/N4upCMXctN2eQMUMMf/PAJMoCO9OBLzzXV6eBPIiMtC13ho9Z1WPoHD1jP2BYDw0JcCHHn3CXJPEmAJQKqNxbLoP+2eKUIW/9vu9mH9LPLT38QAK/ZgqYwmjjMJsOKboAnFd3U+rAHswXeuFpJd6DgW2dNjXQTAKpoiRLfsUs9i0De96U3he2GDeCtrF15vf9e73hVAJWVW9W4M4kPnAQeDOmLl1TFv4GAAqlqWyqx6HAfAYjABYOGRSdlFQKCINwbLYXQoPWmwx4tV1cYM+gAHAAREO2TApM0COLQXUxH/OseAKmClo87FR8plc17Vq/P+ukEeLHTv3+oEYKGDGCil7EIe9Acg5YUXNuQcRNhYezultkbAgwU/fD/Q86VytVZJnjJ4YAd2NlAGXMkLqfwc4zaqc/CNXCk+lGeUI+AWL78HSany0AltiIX7tGE85nqY89fy0BQDLPhvimYSYFV5WmrKMLNUL/Zg4Xlnl+GtznQFHZA8AnFJDGQMsKw501NjnCf+X9YuDGJ0gFqTMsiTFtdT9v+wHiw6WO+BoD68bH6QLcvDMPniwQs5IAEXX6bugdiODBrIgJ5TdikDsCgTsFBVbtoW3hAtMGeArurBEjiUrAAsCK8O8sRgRflSR8ASn6WCqsqi8nQdsqDTPEKvkPfKAi7V1v11KbtwnrpYlI/uvffNX+vjeMbIi8cwBobkY8kBL9LwwGTfuQzA218v28jbyTn0y0eQ3/ve9/Y/huyvgUeAS0x4r6BJrcGCL9rWIPsLYLHWE5uw3pB1iBDeUBEgPgZYuqeUp87jTAKsuLOtU+FdXctrAHvw1NXZZXndlE1Rh5/nWdBbR3prp0y5Ve3CwADYyuOhTJ1FeYYFWJQZAxYGTA2eRXWO41w8eCEHA2eqfqX5AR0eAM8QOk7ZhWm7+JpwgfvRACpw4U4VRhmg8DIIiOAZqWpj+Nf1VEYcAMA04TAD4Oabbx7ASgqAFAqz7KR0UDQ9SNaUPbiX4vVX5E3ZhXTq4qGDqb2U94g8njT1KI+hP0ece2yvvfYKnmh5xnwe0mgPktGf49oUmCG/2ofPzzpSrinDt79u3HFNEQLIAdeAMhbx05/BuwiAxf0FQBU1Oa7MJMBq0mUoo3fHhzWAPfiYaGeXh3VSNaYnTO1ZE19POu7zKuuOqtqFjpuOeJIerNSgEcvq/2vwTgEsnfP5JxGHZz94CSimBjqtj4n51SJxgEnKLgCBQQCLeqGU56yK3NgYgFVl4AJgCTioLrxYDITD2IHtQXhDblhSOyqaHqTsGGDhCaZ9p9YwpuxCGaqrzPQg+aWnPIBFHghPNGXH9xsAS9ODczkH/1JO6i1UPFiAyWGB7OCay+Wg3XMPMUWI7vVNVj89SEn0b7RLtXXSmhxXZhJgDXNDY6iOJqMB7LHbbrsN1dFOhqPpK5UnNzpmnupSBMCquo5iGLvgSavq3Ujxm0qjg60KDnSvx4ClaQ9WnhwMZICsmF8ACoAMO6fsUgZgCeRpwE/puEwagzf8+UGs6DoGPEBA7AXRNKFATFEZ4z6HR4RPZzHVVkTiTeCV74xio0WJ9ZUpu1C29F0WYMnTV2Yqn/stBljMBvjpwSL5dA4e1T6UxpF2VxWs+evHFZdOaEuAa6YFt99+++WmO7k/IG3DQlx9APG6aSYBlncf1q3wrr7lNYA9eDLs7LK8bsqmMPjS6bDwM0VMa1QFWMPYRd6NFA+jpOmpNA+Y5JWtzjUGLPzX4Jl37bjSNXghAzQIKMJzzK88QAzuKbvUCbAElMoCaYAY3hF5WaVXASzZSOl1HLlftt566z74yatTbcQDLKYV/bSUrk3ZhXO0WULsbdF18RG9cC8X7Zela1IAaxgPlqYI1UZVPnaTDpTWxFGAkban5RDbbbddeFnC8yOA5ddhNTmuzCTASr154Y3UxevVQNEbMfVyMt21CWDFnSQdDB6sKuuv0MQwdqED5Ik65mFUzTLAIUdVgKXBIQYsdXuwkF9TMACOIjmKABblpOyCnCqfPCmSx6mo7tR1cZo8GgzkZUgLpeN1S0yBARibAFhl+CaP2g/thammO2yzVy2wj8tI2YU8TGe9/OUvLz3NhufqjW98Y/BkxnXE/8cFsORlE5BUPfxPgUmdr+soDxbTg6mpdfGRAljYpSmaSYDV5hu6qYbQZL3Ygw0/O7uMZgUAFoNo7FngP51MVYA1jF3o8OmUNZiPJtHDV6u8quBAbSo1cGjwfLiWycQ0eGkKBlmK5IDnmF//Fl7KLsgSXxNLw+aUrFFh0fIoJHkGATrVgXcaigEWcgCy6rKD+KlyFG/olq0TAOp5ACtlF+rCc5eaUqzCR15e7jeArkAEfNK+5PHJuy5Ol03VRnW+LR4sQN7Tn/70gdvLkA/Q7j1Y2KUpmkmA1aTLsClDt7le7EHn39llNCsBsKB4mlAL34eZIqxqF7nv43Uho0k2N61GGUXAJFWHOteUB0vnUteNMy0evBgAlZaqJwWWmCLUU3zqfkld48vmGr6Pqc0n/bmqcQAag1is07xyAFisDxRY8fn4jNS2227rk1oV10sHABfWX2GDvK8gpOwyaWG43/AWy5sY74FVtn61xxhgIXcbPFjIseeeexbuuk8erVP0a7AuuugiTjVCHcBqRO1dpV4DdEx8xoFjR8NrAPc40zcxwGL9FYNb1afaYexSdX1OWWlH9WB5MMDTPiE14Jflp0q+ePAa5MGCL88vdcUAK75fuIbBMI/YGRwv2GabbZaXpVL6oPp8YQCs2Hul86w3Krs2SdfUeWTARla+7XfVVVcF71XeFNUw98uossQPNAJamsYtW37cRnVdWzxY4qfMES+t3rolvz4MXubaced5xLgLnIby9FQyDbzOAo/YY4cddpgFUScuo9Zh+Yr0BmHewODz+vgwdsHDxBPvuD1Y4wRYAi8MnHWQH7zwNpQBWB4sMXAz5aHX91N2Qef+mliua665JkwRl3kzLb429b8qwMrz+qTKblsaDyaARL7tV+RtS9ll0rLAG/e17jcBrKoPU76Nimfaaps8WOJr0JGXA9hfDeK+0RrAQddN4nznwZqEVrsyK2mAAYQbgmNHo2mAAZStGvwicwGsqiUPaxeequN1YFXrjvMDShhIqk5XaGNFgSrKFRBpAmAxBYP3TItxYzn5H4MXBgns6acI4/uFa+SZi8tEdzfeeGPwXlUF2XFZ+k99XqdKj4/wrb2U4nPT8v8Nb3hD9u53vztjOrPIbsPeL6PogfaNt8oDLIB41XV2KYCFfbFfXffJKHrw17KNAx/W5r5h3VyTVBfAWmxCXmPhIQvnW1jbQh6tayd+ZIG8V1nY1IKnXe3PtRYetHCrha0tVKJuIK+krolnxh5MYXR2GV3VTLfg1tdTG3HWUVVdfwUnw9qFacJJACwGgaoAgfystfJgoG6AxWAHD4ArDYSa2klZnLzikfNMD0IeYMX3iwZBf124yH5uuOGGYEsWCY+LYh7zygXc0QbjLRry8rcxnXaHd2oQDXu/DCp30Hn/QMMarKrTg5SPfLRTbCVSW6r6UKPrmzoCsCB2fQdgDaOPcfFeB8BiH/sTLBxkYSULrDg70kIeHWMn/sMCeb9q4UQLat2ArYMtvNECH5DazsIdFipRmZulUoFd5pE0gD1wvXd2GUmN4WKmCFmAfPHFF4enzzPOOCMcB22omKp5WLtoq4ZUmcOmDZpWKyq3aYAFbwzSZQEWYEmDG9fGACtllyKApU+7CKBR5qhEfR605pWX9wZhXv5pTk/ZpQ55AFgC7kwRDgso1EbFs8DWtAEs2jlvTPPdQj6wPWi3fsk7iWMdAGt7YxxY/DULfE3y4xa2sLCOhZieYglPs/AJC+T9sgV43MYC9AELXH+pBeaT7raQ3lnRTuRR5ynJ00wz6diDG6Gzy+j6p5N80YteFBblfve73w1HtsAo8pjk1TqsXaiLjt5PU+bVUTZ9IQEsBizslEcpgIUnTtNTKbsIYGlQ9GXjTdTLBz59lHjMY15Z8qTmLXLPu24a01N2qUOOGGBVXX8lHmOAJZCvtqV803DEi3XzzTeHqcImX6KoA2ABmJY6ozD1x9TeRi5NUfL+zMLDfsq56UDl3dLOrWLhFgt3Wfi8BTxkecS5FV0In03Xk5dfs+DjbCjHf4i4Bv68OOUpD3ENLIrzP45TttKJcz15FKeuojj8KY/nPS9O3rbKxI3MmhLkXygyeTl8XDaYpJ14U2ybbbYJU0Ps2cPUEG3Ntzcfz2t78M23vzhP8HL4eCwTT9CkacEteZWHOGVBeXHagfLovsH7AzDxcvg45eXJhAdLwINyAWsQHgcvh4+LX46pOHmVnieHT4d3ZIjBjuQT7xw9eOE/emRdjfIgA3bRAMh/rblBTi8HceqUTZB7HDJJp7GdKN/LxPo/ePdeRMlBXq4nv+LinfRUHN6VnieHTycv/yHi4jcvDi/KIzm4VnHxzlFxzhNH9/RjlF2nTIBn2hbtRFOEXr6yMqmNinfKhEifNjuxISlvEmKXhQ6wVjAb/SFY6uEf/pMe06C8T7QL9raAR2tzC6zt+mcLefR+O8F2wwp4vMKCT46sTSBAS5cuDYiXOK/kMn8LXX755dldd4HlsjDtom+9XXDBBWF3bNLPOeec/pqTM888s+/SP+2000LDp7ET50ijJQ7h+ic/RCdIORCdEuVD1Md0DwQf8APBH3xCIHX4h6ZRJl5/5rMVyLdQZGraTnS0L37xi7Pdd989O/3004dqe0wtMTgBRKq0PXlL2EoAGsf9BChiuon7p+r9hPdH9zD3k/hibVpddqKz537nPmcg1rRfqo+AXw1u5GOBOtMe6iOwx/rrr9/vF5CJPa4ggFcsE9NH6GycfQQgkPYBT1Bev4eu8bDMQr9H/00/hq3r7Mv18HDwwQcHO7NMYJjxCSDF/lEan/SAhK3V9rD1NIxPAlVs2TDOqXHkr5susgr5yFYqfMzS/9ECa7A80Rvs7hOWxV9qRxa2e/qB/Xn7sgSA0uvcyb0sfon7H0djDxYArWcdgwHbXs86nRDiuCH4fjpxG2RC/ry4PUn28xA3tB/yK87/OE4GpROnDvIoTl1FcXhXnjw5fDp5+Q/lyeHT4UVyi3euVVy8c1Sc8z5eVibrfHsGEnvWUSwYmbxtfFw28LbxcfIqj7dHXnySdqLsm266KfCDLb0cPi5+JYeBod6SJUt6tjUATSJcpzx5cvj0lExf/vKXez/4wQ9C+1IbK9v2vvnNb/ZsujTwghxXXHFF4A+evBw+Ln4lExf7OHmVx/OeF6d++PjiF7/YM8Ab5KDM1P1kDxyBP3hFxm9/+9u9Y445pt9HUO/PfvazHvcNRD4bDMM1119//TyZDKD1bSF+vRw+XkWmU089tXfIIYcM7CMOPfTQ3ve///15/YLsJ97RgeLwUBSHX+XxvOfFq8hEvam2p3Tf3nyc8/yn3dOPUUadMlEv98eJJ57Ysz3wYCfoiHYBlZXpuOOO6x1xxBF93rl/uY/plymrTpnEO/ZLxcvIdPjhh/eOP/74nk1TC5swm1UrPWIMtT13QBk72/n9XZ5HW5w3Ba93aYr+1CLrWwAYaZpwY4t/1gLEIzHKKkuUoXL617AIGJJbPY7zhCgqE8f9LaoS1xtOXAtP4qtMPI/3vPQycvg8VeSAf+UfRiZ45il7kX2hXjzkyeHTlZf6y8TFo+e3THwYmWRLz2+ZeBk5fJ5JyoTcPMVaHx3ulbIyISdPw/LSiF+efHk6fuUrXxmmwZQe2y8lEx4s1iDBU57N8uxEedZJh+uQwQbj0F7L2CMvTx7veek8Scvjw3qkIjm05sUGkbBWC9n13T7xj0eBaRCINMqHkE08wLtswFt8kkVH8vu4riN9UBwebfDr91kpm1EO3hy8bd42Pg7vBKhM3PNbJj5IDur1efLkGJSOTJQT92N1yES9b3nLWxClT8PIxBos2pVkpf1B/Ee+abMT/Qw86x7oK6fGSB1rsM4zeQBV+1kAOH3QwpUWbrcQ002WwJzd+yyQ900WAFQXWoAOt/B/Laxq4W8tvNPCqRYqkW98lS7sMk9EA9hj8eLF8zq6iVTUFVpJA6PYhTU/mj5SpeYN6786rbSyR0BG1c/kqGyBAf1n4BCIUdqkjwxeLPg2T8fAFw7EmwY4ptf8oviUXQAbDCa6RvLIBpq2VfqoR3iM60qVOYrdUuW1OS1llzbzG/OWWuTOgxLgahoJ3gGH2KUpqgNg4UFi6g8wxIT9thZeY0H0FYsQRPtYZCcL5H2rhT0tzK34nnsT8Sz7Dwi70QKLkD5toRLpabbSRV3miWkAe7DOpLPLxFQ8VMGj2IUBXWs4VDkLgCHeGK1C8IG3xIOMKtfTyXK9qCmApfY96I3OQQArZRcGQa7TehzJKo+EPFxKH/UY6zRVHt40wrB2S5XZ5rSUXdrMb8wbgAQwL6ItqS0qbRqPuu+a4L0uaHeFCbdJjoDzfZtzbwg+Jycv3qwPLAs5WbrkadQAT7odtU8Dw9oFD1YMpIYFWPKUMAAMQzzBqgyuB2wBEOokDzIGeZM0qMEz07OxBwu+U3bhOi8n+QBY1DduL4Tqgr+8sjVYD+t5hP9po5RdpkUGebBkU9rSsPfctMg8aT7r8GBNWobK5fu5+8oXdxeMXQPYY/PNN5+3HmTslXQFVtbAKHYBYHkPFusgeLNx0aJF/S05yjIk0CDgUfY65Yu9LZQ3bFkqs+pRAIs3mgZNWYg3gCCBaUVdT715dhHo8bwJYPm0ccTFIx6qPBLYmBWAlWeXPP20LZ02RluTTReKBwu7NEUzCbCadBk2Zeg214s9eJ27s0u7rDSKXQBYdNDyYsh7xWvsdOLaNqGMxJr20qBe5hqfp00Aa5D3Cr7lXQMISnYPsPLs0gTAEvj1+lZctve869xCPObZZVpklZ1kN2y7EDxYTY4rMwmwpqXBd3x2GphWDQhIaJE1AIsNJ9n4FI9GPH1YJKcG8WE7e4BHG9ZgIeOg9VfkEZBEbg12Gvw4n0foR7oiD1M9k/JgeRCYx8+sebDy9DAt6WpjanMLxYPVpP5nEmA16TJs0thtrRt78K28zi7tstAodsGDBWmaEIDF5n+s11l77bWHAlgCHlW1NG0eLMmZB7Dy7MJ1HmABcPgvsFtVb0X5PY95+QSwNHDn5Vso6Xl2mRb5ZCd5TWk7wz7UtEnmJseVmQRYTboM29Tw2sIL9mC3784ubbHIHB+j2AVvFR2b9tGyDRD7n6wAYLHjuG0cmtmGlfO8SykNqMPXoJ7KU5QGwGJdCR4dqMlF7mU8WGy3oIX58iZo8IP/PLvEAEvew0kCLO8ZhDdP8I4c8nb5cwsxnmeXaZFVbUxtbqF4sJocV2YSYE1Lg58lPmdlIey02XRYu+CpwovFIM8Go3TW+nzFU57ylPC1e0DWj3/84/A5qCK9yCsz7NO0BniBAcobFqwV8Vl0jm0S9t5772yjjfRZ1aLcc9OE8KnBToOfrkrZBZkERsnHppfQJACWdCrbhIqiHzxYMd9RlgX3N2WXaRFS95faHLZV2rTI0DY+ZxJgNekybFsDaAM/2GPDDTfspgjbYAzHw6h20ZuEeCcpi2+kQXhx3vzmN2f77bdf+K9pxPAn8UNHz/WEYUhgoEmABd+AK/EySA7yCWDJo6Vr8uzC4K5pOfICbgFdkxj0BVCLABYD9STqlh7adsyzS9v4zOMHm/JgJIC1UDxYw/YbeXqqkj6TAEuvoVZRVJd3chrAHvZ9uP7rwZOrqSu5igZGtQsA64477sguueSS7HnPe95y3gyejvFwDAJYo3b0AjVNA6wqumewE8BCR36vqTy78CmhBx98sF8NW2OsuOKK867tnxwxIoAlnaaKmzUPVp5dUrppYxptjLYmgEX7WwgeLOzSFM0kwPKdVVOK7+p9WAPYA69GZ5eHddKG2Kh2AWA99NBD2Zprrpk9+9nPToqkacTkyWWJdPQa0Ivy5Z3zAIt1WKOWl1fPONNjgOXLzrMLAAvAg3wQYIu0SZD28lJdqTpmzYOVZ5eUbtqaBqDCbqxbApiMct+1RcYmx5WZBFhNugzb0ujaxAf24PX9zi5tssrchpaj2GW11VYLHfQee+zR/1BsLCEAiw1Ii4hBfJQnaQ+wGDgAWW0fOOAPsIT3Ll7HlHe/6HM4gFpokgCLQUsgMM92eLBmbYpwlPslT491ptPWaHMCzqPcd3XyXVRXk+PKTAKsJl2GRQ1hVs9hj4svvribImxZAxjVLqyre/e73509/vGPz5WsjAdrnFOEGjimAWDBK96EGGDl2UXeKk0TThJgYVCtE8szbor3vLwLIT3PLtMkG4AYgM49B7X9PimjW+zSFM0kwGLRaEft0QD24A2zzi7tsQmcjGoXeTmKpAJgaSuHvHwAjVE6el3rp8+Ulldn0+nwJ4AVexHy7BIDrAceeCBs7jopWeCxW4P1sHbz7PJwjvbHVl555ey+++5bUB6sJseVmUQaTSq8/bdY/RxiD/ZG6uxSv+6LaqzDLmwhICCRxwvnY5CRlzeV7qcIKQtqO8CSdyjlBcqzi6YI8VzxOSI8EQJdKb2MmiYQmFcOvM/SFGGeXfL008Z0pvXZVkXTzKPcd22Rr8lxZSYBVpMuw7Y0ujbxgT0uuOCCboqwTUYxXuqwCx4sqOhNQkDRKIBIAItyBLCUFipv4Y/ASwpg5dmFtSYAGgCWBshJA6w8Dxbp8BlPb7ZQ1WNjKc8uY6ughoIAWKxR1LdDR7nvamC3VBXYpSmaSYDVJKJtytBtrhd7rLvuup0Hq2VGqsMuZQDWqGuwtMh1GqcIkT0GKUV2wYsFwCJA7Kg/KZKXLVU+wBCaNQ/WtPdjq666arDbnXfeGY6dByuoYeifRwx95RRf2AGsdhkPe2iX73ZxNtvc1GEXfVJHn3VJaXxUDxZrwQAD0wiweOsxHuSK7ILHCu8V66+gSXuw5BGM7aYNT2cNYE17P0ZbY8ucu+66K5h0IXiwmhzvZ9KD1aTLMO6Iuv9zU1HnnHNON0XYssbAfTJpuwB+2AxzklOEqJWBYtoAFt4rbBB7sIrsAqDyHqxJAyx06un0008Pg7M8WDHvPu9CixfZZZpkZZoQgIznV97faeI/5hW7NEUzCbCaRLRNGbrN9WKPjTfeuJsibJmR6rILC92LABZAI/biVFVV7MHSRplVy6krv/ccxCClyC4eYCGzL2fcvMdThAC7yy+/PLvmmmv6n+yZNQ/WQujHAFjQqPfcuNvbsOU1Od53AGtYq3XXjU0D3ADM/Td5I4xNmAVUUF120VYNKdXxNhxPoKMCBQ+wKAvPWZvJy5sCWHn3i9ZgTXqLBnQHj36KkI93QyyQ1hRhzHvIsEB/6rpfJq2+DmCNT8N1AazFxvI1Fthi+HwLa1vIoyV24noL/7+F11vw9Hr7c5UFtn7+uYX3WahMsVu7cgHdBWPVAPY444wzCvfUGWuFXWGlNFCXXYoAlgZwDzhKMR9ligFWdLp1f728MUgpsov3YE1yehCFxR4sAaxf/epXGd9B5HzbPYXjNHyRXcZZz6TLEsDybXDSdU6yfOzSFNUBsB5pwp1g4SALK1m4yMKRFvLoFjvxLgvki+lRlvB2Cytb2M7C6y3sY6ESLYR55UoCtzwz9li8ePGCmO9vuaorsVeXXQBYeFxSayUEsEadrhDAorOdhoHD8xgDrCK7AKrw+v32t7+d6AJ3GhI8+sELzxULpHnN//bbb19u7VilxjeFmYvsMk3iYENsO+o91xaZsUtTVAfA2t6EY9/9r1ng3d2PW9jCwjoWUgT4OsPC3Ae15uf4iv292AKQ9A4LALf0V2TtRB51U1F5mmkmHXustNJK3RRhM+rPrbUuu2irhtQ3CVl/BXnAkctwwQmuv/feewPwGLWsgmrGdsrzGAOsIrvIa/XrX/+6FoAlAAyoA2BtttlmwXP185//fKa2aMDwRXYZW8OooSCmz5mCXigAC7s0RXXU/DQTbqkTEOB0q4WNXNqw0W3tQqYT8wjv2YouPJaMesOFV6AJkI/zJK104nQeUF6cpzjlIc4THKQ4/+M455VOnOvJo7ie5klPxeFP6Z73vDh52yoT6zVOPfXUYJeFIpOXw8dlg2mwE+DmlFNOCe3St0N4H6dMvEUIaaE794HuJ22YCeCI7yHuH38P+Xh8P2211Vahfd10000BAMT32bhlonx0JDm8TJKDPIqLd8mkNWIcFZdMXINdtM6JdNlDi8oBPqzHUnpee/Pp5OU/5HnPizNwUTfXAF6pc6211spWX331kA4wjOWjbMlKXDIpLn69TD5OXcrjec+Lk5dzUJ4cPh1+qQ8S7z4u3mUn8kD8p63Sj3HfKN3znhdvo0w77bRTts0228yTY1pl0kNAMFTNP3UALHa6Y82UJ/6PugMe04grWTjCFxzF32///9OFuzlPJwvdcMMNIRBfunRpdvPNNxPNrr766uDiJs5bMdoT5GL7IPE999xDcth5nE8KQLzKrn18zjzzzLD+gPTTTjutDxqIcyMD7ohDrFMgP8T1lANRLjubQ9RHvRB8wA+ECx4+IfiGf2gaZUIObmbWcCwUmRaCnWiHeERYRzPJtidQwNodyN9Pavs8TY9yP+FRedvb3pZtuummAXhQzyRlonzu4WH7CN3/AMuzzjqL4vp9BPbYaKONsksuuSSk+z5C/RAn6GsmeT+pH2UAUz+2xhpr9D8ULJvNSr937rnnhn6M6e5p78sByniWZddpHp9of03RX4yhYtZKPSenHKYDf2thGwt7ujzXWhzwc4pLi6M/tITvWDg8PmH/X23hkxbwYN1uIY/wYBFEeLDuvv/++8NaAT3ZMEfr4xiEp0bSifOkRsiLg+zJSx7idIBcrziVc60WfBJnTQhPPYrzdAMPpBMnkD8vTl6uJ4/nPS9OPZ1MnZ3U3trU9rg/DjjggGz33XfPtthii3Df6H66/vrrs+OPPz77p3/6pzBN6O8hH19o9xPekAMPPDBjC4v999+/3y8M6iM4//GPfzz0DXvuuWf21Kc+dWJ9xI033pgde+yx2Tvf+c7svPPOy375y19mb33rW7Nrr702O+GEEwKY3W233bp+r+vLucXDGNnE+MTSA+4jI77L9QciddEjxlDRcweUsbOd39/lebTF17VQNLXnsi8X3cNSPmNhRwtF4IoLWcBBmEeAFohOXOTj6rg5VyZO5y6qEgfwKL9AHOWUiXt+y8TLyOHziC/4qRIfRiZuupNOOinbdddd+3VNu0zYECojh8/jbVAmXsU28KP8ZeyEXfAayS6TlInpJE15iUf4VYeMJ8enp+JlZMq7t7wNysTL2MbnSfHr7RHH9eFm9KJrxTsPbrIL1ymdOLxrqwamXsXDJGQSj/ADuNIu5ny4HcIzKd75r/hCspOXCRnjfszbJi9exjY+j2xKfWXi4pH8VeILxU48VDZFdUwRnmfCAar2s4A36YMWrrSQB45AK7wtCG8+bn8DqPq6HV9sYViANq9RUmhHzWqAToI5f99ZNMtRVzsaqNMuDMYCWF77TD/R0c9a20BmQGW8wL2MXbTQXUevz3HGNVgztc+i+kWLFoXiAXarrLJKtvLKvOw9O1Tn/TI7Wh1d0ib7jjoAFh6kl1p4p4XfW2Ba7zUWRLwZSBB91SJ/svACC4cti3MN9CEL+PrOscDHtgj+Wvvb0TRqoMmbYBr1VRfPddkFb0gKYGkXdwDHrFEewEIPRXYRsJrkh57hAf4g1h4xBcO6MNFb3vKW7JnPfKb+zsyxyC4zo4RO0L4G6gBYVHaFhU0s4MkCLP3cgugtFiGIXm8RelMfzrP/0PMsMK3JAnkFf60lD6YmXYaDuZu9HNiDKY/OLu2yfZ12KfJgaSBvl3Ymzw0eopQHa5BdAFhMKU36NXvZhTUu22677bzpcKbDZo0G2WXW9NEWeZscV2bvLjCrd08ZbWn6c3xgD9b5dHaZXbvgwdKWDF4LTBFqIPfpsxDnjTztqu3lHXS/ALAIk/b6aYqQjSl5O3PWaZBdZl0/Tcnf5LgyjkXuTemtq3cBaYCnjCZvhAWkyrGKUpdd8GCx3UBMmiKM02fh/957750rZpFdttxyy2y99dbLvXZcJwC+gKsdd9wxLLQfV7nTXE6RXaZZro734TQwkx4sboKO2qMB7MF+K51d2mMTOKnTLgCslAeLN9Rm1YOV1xoG2YWvItQBsJgGfMc73jFv7VUez7OQPsgus6CDNsrY5Lgykx4subbb2BhmkSfsscce7L7RUZs0UKddtMid/bn81BYerA5gzW8Vddplfs3dvyINdHYp0k5z57BLUzSTHiw68Y7aowHswULZzi7tsQmc1GkXPFjsTxd/1oL/k16s3S6tD+amTrsM5qbLIQ10dpEm2nVsclyZSYDVpMuwXU2vHdxgjwsvvLCbImyHOfpc1GkXbVoZTxMCsJp8Au0ro0WROu3SIrFbz0pnl3aaCLs0Rd0UYVOa7+rta4ABlE9qdNQuDdRpFzxYEHthsXBaNMuL3KWD+FinXeK6u//5Gujskq+bJs9gl6ZoJj1Y+lROU0rv6p2vAezB9yE7u8zXS9P/6rRLkQerW4M1vyXUaZf5NXf/ijTQ2aVIO82da3JcmUmApe+bNWfyrmavAexxxRVX9L8758918eY0UKddvAfLSzzL+2B5Pfh4nXbx9XbxYg10dinWT1NnsUtT1E0RNqX5rt6+BnDh7rwz3wTvqE0aqNMu1MXu434NFotTu0Xuy7eIOu2yfO1dSp4GOrvkaabZdOzSFM2kB6tJl2FThm5zvdiDj8V2dmmXleq0C1sz4MXy3yMEXEHdFOH8dlGnXebX3P0r0kBnlyLtNHeuyXGlA1jN2b2reZkGuAGuu+66DmC1rEXUbZf4czl//OMfg0Ye+9jHtkwzzbJTt12alXZ6au/s0k5bYZemaCanCLtPsjTV3NL1Yo8ddtghfbJLbUwDddsl9mD953/+Z5B9xRVXbEwHbay4bru0UQdt5KmzSxut0uy3hzsPVjvbxExxxRPGL37xi86D1TKr120X7eYuNbD5LNQBLGlk7li3XebX3v3L00BnlzzNNJuOXZqiDmA1pfmu3r4GuAFuvfXWDmD1NdKOSN12SXmwVlhhhbD4vR0aaQcXddulHVK3n4vOLu20EXZpiropwqY039Xb1wCu9W233bb/v4u0QwN12wWA5d8ixIPVea+Wbwt122V5DrqUlAY6u6S00nwadmmKOg9WU5rv6u1rgCeMn//8550Hq6+RdkTqtktqivBv/uZv2qGMFnFRt11aJHqrWens0k7zYJemqANYTWm+q7evAW6Abg1WXx2tidRtFzxYfBpHGwOyyL3zYC3fHOq2y/IcdCkpDXR2SWml+TTs0hTVBbAWm4DXWHjIwvkW1raQR0vsxPUW0MrrLXh6pP35qoX7LPzGwpEWKr/D3aTL0PjtKNIA9th6662zzi6RYhr+W7dd9Lkc9sJik9EOYKUbQN12SXPRpcYa6OwSa6Qd/5scV+oAWICiEywcZGElCxdZABjl0S124l0WyBfT2y3hGRY2tLCOhVUtfMBCJdITcqWLuswT0wD2uOWWW/qei4lV1BVcSQN12wUPFgTA+q//+q/sf/7nf7JuinB5k9Vtl+U56FJSGujsktJK82nYpSmqA2Btb8L9t4WvWfgvCx+3sIUFAFKKAF9nWMDbFdMiS/ihhd9aYBfC71t4moVKxNNxR+3RAPb43e9+F7wW7eGq46Ruu8iD9eCDD2bdFg357a9uu+Rz0p3xGujs4rXRnjh2aYrqAFgAoKVOQIDTrRY2cmllo0dYxudawHPF6tc9LZxpIY/wnrFLoUKYTuSzHBDIVujWx//3f/+3n05cc7h5cZ60lYe4DKo4/+M49SudONeTR3HqKorDr/J43vPi5OUclCeHT4eXumSCp8WLF2fYZaHI5OXwcdlgGuz0l3/5l9nmm28epm5pC14OHx+XTHir+G7YnXfemf3+97+nWWSAru5+erhf4L5kymOLLXhGnSNvGx/HLpOwk+8XfHzW7YT89GPcN7Pal/v25uPj6iN8e/PxorbHN06bojoA1gom3B8iAflPelVi+pD1V/da+J0FUMhXLOTR++0E20Er3E3Ga6+9lkN2ww03hEB86dKl2c0330w0u/rqq7Pbb789xC+//PLsrrvuCvGLL744u+eee0L8ggsuyH7zG5aBZdk555zTHxDOPPPMTJ/4OO2008JUBw2NOEemPohD5CM/xIBCORDlUj5EfdQLwQf8QPAHnxB8wz80rTLdeOON2W233bagZMIe02wnXjw4++yzAzCvo+3hxVx77bWzq666Krv33nsD4L7kkku6+ynqIxisuPfPP/98mtjM9BHI2vb7iX7s/vvvn+m+vG12wiPeFM25ckarnbVSz8kpgulApvO2sYC3SQTCAfycooTEkanA71g43J07Zln8TXYEHH7VAqDpXRZShAeLIMKDdfd9992XPf7xj+97dEC4QtjEAUJ4UxTniYRAeirO0wp59eTCEybX62mTyrlWi+2I86QO6lYcNA4PpBMnkD8vTl6uJ4/nPS9OPW2VCT399Kc/zTbaaKOgw4Ugk+w3zXbCLgD3zTbbLLSdOmS69NJLs3PPPTd4Aq6//vrs7W9/e2jj3f001y/QnuhnrrnmmnC/PPKRj5yJPqKOtqf+e9i+nDdgecDdeOONw3gzi315G+3Eg9vKK6+MTZj1wrlTG40DYA1idmfLcLCF9ZdlZCUroIspwjk30bIT0SEFsHi7EDDFGi1odwuAuE35U4KYKrSXk7rXv0voqsvSaaB2DeCxPeyww7LHPe5xGR953m+//Wrnoauw00CngYWjAdZzLntZpnaAVccU4XlmKkAVPSXepA9auNJCHrj6P3buURbgzcftb/ZjC/taeIyFv7bwGgtz830WKUvy8pTN3+WbrAawx3XXXdf3xE22tq70shpowi6rrbZa9qhHPSpMmXd7YKUt1YRd0px0qV4DnV28NtoTxy5NUR0A679NuJdaeKcFVq5uawFgJGINlV9HxbTfnyy8wMJhy+JcA73HAuCLRVF3WgCw/ZOFjjoNdBpYABpgmmbRokVBkg5gLQCDdiJ0GphhDdQxRdgm9XZThG2yRsdLp4GEBniR4/TTT89e+MIXZltttVUiR5fUaaDTQKeBchpocorwEeVYXFi5+O7d3/7t3y4soaZYGly4LA596lOfGl4WmGJRFhTrTdmFhdusk+SN27vvDi/+Lii9jipMU3YZle+Ffn1nl3ZamEXuTdGsebB4HL60KWV39XYa6DTQaaDTQKeBTgONaOBZVutlddY8ax6s8DiMB4u3lDpqhwZ4tRdPxZprrhleQW8HVx0XnV3a2QY6u3R2aYsGTjrppLBP3WteM7esmj3ADj300OyVr3xlts4667SCTfaYZH89o9rd4bMGsILBV1hhhaxbQNuKth+YYI8u5smxi/YKaw93s8tJZ5d22r6zS2eXtmiAvfKe8IQn9MfTv/7rvw5fX/jzn//cT2uaV+6XpqiOtwibki233m4Qz1VNIyewx9Zbb92Bq0a0n19pZ5d83TR5ZiHYBU8H6+wWEi0Eu1S1R7ynJJu0rrTSSv2vnFQtbxL5sUtT1FzNTUls9bIYMUW//OUvsxNPPDG74oorsoceSn1rOnVVlzaqBtiRHn3z3Tl27O6oHRro7NIOO8RcFNmF3cN5WeTFL35xtskmm8SXtuI//B911FGhH37rW9+a8VLDQiDGFT7lw9QYQGOhE/Lyubd4uQ27pv/2t+wl3g7KG+/r4K5OgLWKCXS4he0t3G1hfwtnW4hpb0tgb6vNLPCpnNdbEC2yCBuU+o8Lvdn+H2WhDLEnV//jsf4CPjD7pje9KcO1iTeFtwy7wd5raHJxOlxczQwOnc4np+eqJXd2qaqxevIX2eVPf/pT+F7pD37wg+zTn/50tu222kKwHt7K1MJ6SzxY3OtnnXVWtvvufJBj+gm78Maa9nGbfomKJQBcIfOyXdL7mQFYfOaqLQSPyyiM//pTx7FOgPUlE+heCwCt51s4zsL6Fu634In/B1rY2sJK/sSyOO6nFRLpZZL+TKaUy/Dwww8PC6yPP/744OIsU1iXp9NAp4FOA23TAE/s73znO7PPf/7z2TbbbNO6h5af/OQnYVDmQZb9zp72tKdlT37yk9umxsr8MK4sXry48nXTegGLx6EYYPGdX6YO9dDctHxuvA/jf5381LUGC0D0EgtLLDD3drIFPnGzh4WYzrGE4y38Oj4xrv8pl+Ell1wSNjZk/rijejXAEwZP3u5Jo14GutqSGujsklRL44mD7ML01Mtf/vIMr/wvfvGLxvn1DDDo4t3YdNNNAxjB23PyySdnfCh52olx5cYbb8xdgjLt8sX8aw1dCmCRFy9lGyg13tfFV10AC0/VAxb4xI0IgMUHn6sSk9u/tPBzC5+3wHcJ84jJ/RVdeCwZpXCOioPGV1kF59rcFKIGe46D4rw2rTypOOeUrrjqIT0VV3kcR43fcccdwWtXpRzxC2+pOGUpXfGUHF6+ovo5p6ByivJ/4hOfyN72trdV0o34HZdMu+yyS/ad7zCLXb3NIBvrNXi6qiJ3XFcs07nnnputt956y9lGdXh75MW93n0enx7Ht99+++zb3/52JXuIp0EyqS7Jyv84rjI8vz6uMvLqnHS6+IXPVLyqTL6MFO980xHSWhjf1+XFedtK/SFx6S8vDlhSHuLwASnO/zgOAAFMbbTRRsGzxvQg6y+ZKqQsvfGVF4c/5cmTw6eTd9IyIbNk5UER3pEbypPDp7ddJskRywTAYt0sn7dSHvTNFCH0q1/9Khy9PfLik7ZTYKSBn7oAFh6sP0Ty8b/qVN9v7JotLKxlgcUFrNP6lIU8er+d4FUVBdZ+hV3DdWQHcYhdo3UjcsPTCfB0xdYB2gn2gQceCK7Pxz72seGcbnTmoj/1qU9la621VnCXPuMZzwiL/9h6QJ2fj3/lK1/J1l9//YxyWJB66623hropB6JcxWnU1AsdfPDB2eabbx7WKv3Lv/xLfyE+vHNjM83JXlI8Ufzd3/1dfzfscLH96CnxwQcfDGvNSKds3TjU6WWSPuCdDgHycsRxTbN+4QtfCHm5/pZbbgkdaZ5MrHnTAnfFuVgyKc5/CDmJf+ADH8j+/d//feIyUSeyIyuETLINT9677rprSPd2Qg50DKFz5INimWQPyUQetT3ik7ITZadkor2ff/75Qb4lS5Zkf//3fx/ysVamjEzoILYTdZWViWupizZD/Qy+cds744wzsic+8YnhntS9dd9yWLH9AABAAElEQVR994X7lPuJ7VcoQ1uxcOTllW9+85vhszt8SBq5IMl04YUXZgBEvNerr756tt9++2WUCcHTZz7zmWyzzTYL993HPvaxkC6ZeClmyy23DAt94etd73pXXwfx/XTaaadlG2+88XIy8Zo7L9Yg6/ve974wYDF1BmEnrttwww1D2/vSl74U+g0AFLIiH6/GM8jxiSHJhA6459S/3XzzzdnSpUtDmaQpnTTOQVdffXUA/cQp66675p6HL7744uyee+4hObvgggv6b4idc8454aPcpJ955pn9+wJ+0Rv1E+fIf+JMD6In5IXgk/9XXnllOEf5EPVRLwQf8APxUAKfUFtkghdsffbZZ4f+mTi6gX7zm98EnRGfRpmwK4QDIpaJtEc/+tHL2QnQxYsL1113Xbi2aTtpfAvMLNCfzU2u2F94kKUdWCDv++zc4QXnOcXOrEU+8NiD9UTL37PO0/rmXs9u/BCIP+tZz+qZN4Jozzq1EGxzsp4BoZ49mffT7e2XkMY58kEHHXRQ73nPe17PNjAN5Vkn0rMOpWeDcb8sxW3xac/e7umZmzycv+mmm3rmSg35yAOp/jh+wgkn9L7//e/3XvGKV/T+9V//tV8/+a+55pqevc3Ru+yyy3oGCHs77rhj74Mf/GDIY51Sz6YN5uUX73l1iV94SMW5TumK2yDWs5cDek960pN61tGH+myKgsfaEM+rk3JswOqXR526nngej1XTxS9lpuKSQ+WSB1J6Ks45pVeN33bbbX27VL1W+WM5rBPsrbvuun35yKc8iovfWD7atA1wQd4Pf/jDPQMaPQN5ff2rTo5xfLvttut961vfWi5ddcX5U+nYnLZCm7FOuWcvPfTsKbhfJvy+9rWv7f3jP/5joUyUYaAq5FE9P/zhD3u2vrJnb6317GUWkvtyGVDuGVDq2cDYs0Gj96IXvaj39re/vZ/nu9/9bo/79qUvfWnPPKf9dGRCZvO+hPZrA2jPwFbvwAMPnJeHP/BuAKNnnps+70o3sNQzABHS//mf/zncQ/QnEHXYwN17ylOeEuKyJXaR/bAT97vOcc3Pfvaz3hZbbNGjL4J8X5cXt4Go3x8SV/l5ceylPP5+VRw+fNzARs+Ac++qq64K6fDF9fag0fv617/eo/+gLqWn4vCu9Dw5fDp5+Q8RF7958aoykR9CVntQ6l177bVBNqVTn/jNi7dZJi+HjyMT4+IxxxyTlO9rX/tauN/QjbdHXpzyJmUn8+KGfsX6BWazaqW6PFg8IuGtWtNJt7HFr3f/h4niVvmLgguZ2Mf1oBBcRHqFlqPiPEkRIB9/1atelR199NH9dF4vfvWrX93/bzdNxnTVV7/61cyARSiP9QUgeJ4qVZbiBxxwQPbZz342LOwkbYMNNui/sch/SNfEcevgsz322CM8Lcd5rKFne+21V/9p+kMf+lCYsiGfSHGegnki//Wvf50dccQRmXXO2Zvf/Obg+Xr6058ePAgf+chHMhYr4mmzDrGvG8lBWXGcevDeLTJPiHWW4ZpYJp5Gd9ttt+AtYHErXiDxtcMOO2QGHLNnPvOZ4cncbrjwxIonA1540jcwG/Lj4XjjG9/YvxbZearHC8H6E3kdKVvlwwvyUg+vh+Ppw6NgQCd4TKjDBrLwNC35sC3y8Crys5/97Mw60CA3stogGF43J46+2M34ZS97WfAsGGAPvFMOT++0I3jDfa6Fx+LLOqNsjTXWCN4TG7D7/PKEuM8++wTZmfY77LDDqCqcp92hq3XslXB42948MLIHeRS3ATt7wQteEDx/kklleNv4OF4s5IaXVVddNXjpuPbf/u3fwo7I6I0Fyng/SJccHPHKwQ/T0ko/77zzgl5Vr9I5puLwgrwGELLvfe97/TyUjcdo33337cvH9Z73vPjOO+8c7g/kies0QJW95CUvCW0O2fBwXXrp3Be1yLv33nsHb5q8Y14OeHn+858fnuTxftE3+GtVF3zlxVWe8lAfXjy8OVyTJxPnuO9PPfXU0A51veqhXC3w9X1dXpy86g+Jq968OG/9Ko9/A1hx+PDxn/70p+E/9z3pENf/1V/9VVjkjrdH/JKeisOf0vPk8OnknaRMkkOySial58nh06dVJvon7nXZw8tEX6rpaW+PvPik7RQaWwM/dQEs5rhOsrDEwqMt7G5hEwukxcQaq0dZeIQFHyfflhbWtwBqWMPCv1k42UIl0g1X5iIGY1ydTBnQATCo0KGKeOWY6QLePmSAZ4AGbKWIQRGwQnlMJ/LmDFMOBvJT2Sul0Xn5fW8ASixy1fSiCrOn6+wb3/hGcPcy2EBMkQCyWJS41VZbBfkYTJhDBzS8+93v1uWljh/+8IfDAG1PJcvlB2iw/uLee+/NDjnkkFA+U6S4miEGDNY1aQElYIw3c1isa96+7DnPec5yZZKw5557BkBzu00h4KL/6Ec/msxHYhV5mZr58Y9/HDoLgIp5UHLLZfDff//9A7ijHSwxEAgB6pjuY6oKUAt4EdEmaA98vglAw7oy+IfMixKO2JGyAc2AFYgpafPKBFmwGwDPE23qHe94R2ivp5xySlgr4c8Xxbc3sMYU7Ote97rQfjRdVUYXTMFhC61Nox5sClCsSrQ9PdxwLZ/l4L5hmnySBLChjQ5Do1yr+gAcTBXGNtV5BnPuF+4bHhSOPPLI0PfofBuPtEemBwFXqX2vGJC5R5gun1ZiXOGBrcr4Mq2yYk/6aB5IUiSANY6xLVV+lbQm7VEXwEIf+1sAFLED2WctvMIC04a4g7wna1/7z112gAU+cET8Qxag9SycZQHAxqT8Ty38k4VKxKBWljAO3pFjjz02DBrEvcEY+Glo5pIPT+02nRAGJzramAAseGWY18YTwpw2gyod5KgEkAIUiRT3AAswhxw25dBfiEh+1oHh9eEpgqdnnkxYS8J/0m36UcWWOgJKGQhZk+UJ7xVgBfBDJ8tAjnfquOOO669TesMb3hC8FwzUrLsAbOCp4T8y4dVIEYMxa1G44W0KKbvoootS2UJaFXkBC7z8wBMpoAOA7XXqKwGk4tVCb3yLS3rjWp7m8JRxDg+WJ+RjUN1pp50CENKaPNoSYIw1DYBnPCuAFQjdfvzjH+97TW2Krl8kndpb3vKWUB8eQoHXfoaSEcrh4UGdZFldYAvxCcjGCzUMwEKHtAHAJ4T3mLInSXjv8L4CZqsSYBDvFcA2j1j7xFO/D4DumLgPeKDgYSAm7IGHlnsTEO4f+OK8bfmvva/w7qeIARniIXZaiXGF9WFVxpdplZV+gbGMdpwiPPU2pZjbV6aumVRak/aoE2CxanRXC4+xsIGF/7AAHWXBPy4ebv/xUPmwxP5DR1tYZOGvLaxp4f9aAGxNlHD703n66UFVqMGLQZI4AyEDg576lY+j8jJtQ8NctGhRmJpj8eeoxGJXLcSmLMVJh2yNQNgXB28Um6h6kieLNHiks9M0A//zAIUvI46nvFh4cAAr0gPX2Lqf4NlRfSzSF9Epcx7XcxFxo7PvD3kBYYBEuadT11WRF28k3gyAG1NADG55ZePBFAGKpDemkQBfTPHCI1NtIsC63rohTdcx0ABOmHYWSVf8RzfrrLOOTs07MmDzRp+twUt6C+ZlHvBHdiFbWV0AnAEAvI7PonT4ZCq8KqEXQCdgDZ3zYDIMUCtbL4MjoAXvG1OUVQg5Afbcy0VbvQDueYDxwbdH1ckDSJEXC7DPA0Wel0vltOWI94p7iD4vRboHphlgIZfv21JyLpQ0zTAUebCQddrtOaq9ikeuUUtv6fXeA1WGRdYEMQ3DoBFvJMfAgffBD0R5ZQJsWGtTJm9eGXnpuN7xiomYdmJwFsACpDClBBBJedd03biOPFUjK9NjIv4z1cqaJBHTX7xFpI7J6wYvGN4LeVB0TXwE+J5nU2e8dQSwZLp20DVxGan/rCNCX8jAgMhbQOixatm0D7x2eDkZiHnLEn6LCJCL5wv9iIijQwjdwF+KAHp4v/C26m2xVL6iNOxAwC4cq+gCHTEVDDAiaM1iUX155zRNiOeVdW2AzEkQ2wfwRijT1kwFVyG8pfBpL6HMm6avUkYqL2sMsV/sjbUXXYJ90W3VvixVz6TTuF/wxjF95u9vXy9tnYfOaR6QsQXT6NNgE6/7YeL0h1AewGKsox9ogz2btMdMAiw8HlWJzpMQE0+ReEyYrmERLh0iU156fT/O//rXvz5sL8DUF14IvAKsMypD8A04weXp41zLkz1TMbzuzNMF/MTrhQCK8MZTOlN1kya8WJ/73Of61QAKmOIjHfcxQI9PejD1xPqLmHj9nVfveTEAuQFPyBcTumQKkZuaG5p1ZuMgPFB0Enjd8CbBd1VwBR/n2t5UeHPwIuJhY5pw0E3PedoVU1W44wHM9qZV8I5SJu2Ic0y70h5i0Eyb4mUKFnezLg0CJAkshYSCH7wqgFt0gMxVdQHgYOqb9V/21mtBTcWneKkDPlhzNsr0IDqiDXHfKM4RQi+AKqbQAaUx+XtNcWwJsaYSzyQew7z1gXF5Zf/jxXrve9877x5CF0wVs9ULDybTQNyT3N95HlfJwENFGwZk8VP1SNtg+wmOC50YY+jH8LiniP6L/jjP25+6ZlJpTdpjJgFW3lNUkYHxEBFSxFt5dAx0EAArAIHW2eBd8QtmGaR5G46pMJ7IAUYaOFhvIY9Tqh4GADwKvHUGgCJOxw6xqJ0BlY+8UjaejtQ6Er5NxiJ38rEwviqxuaZfpF10PdM78dQQT92sTWIA581FvEPkSQEObmAGaDxT6IyF4+y4HxNAkpuZMtH7C1/4wjjLUP954oZHpn0X2dQGAwTeqKqE54u31ABXeEApU+2jqCz2PaNzAJhiryVLloQ1Xlzznve8J0w78jYfU1Kci4mpavZLAzzAg6ZcywzMgDtAFW2Jt+yq6gKdIS+gXl43+MPeeetwYv75D3AG9LB+kTc0PXEvAW7KEA8y3C/cN9w/xPlWH3TooYeGlyj+4R/+Idx/3IN+rR/3EfkBjOiTOA8qEGXg3UZfXEfwPNmWGeHBJ2Qe4ofvo/pF4fCKJx2AzcOH6uTIA1YbCQDLgwrtuIimHWAxrtAPDTO+FOmljecAWHgci2Rl2rcNAKuIx0nr9i8mXUHLymcVuLWN/wydv+eNgYrpILw7HXUaWIgaYO0XYAyAVwfxAgNggwXbHdWrATZ3ZJoWQOsf8OrlYq42puzxPrOBaxHhnWbLCdaX8XDVUXs1wJQ9Xn05B1Kcsjs/D/E8uDRJtL1lU5m88siWTbXRTHqwmnQZ1mbZKapIU1DDTL9NkZiNs/r+97+/ErgaxS50rHgeuweW8Zt9FLuMn5viEuEVD1aZtXN4sMiPR3AaiXGFNj8L4wtOirz1V7IdHizWagHEmqQm7TGTAAt3dUft0gCLXDtqnwaGsQtvyTL9/clPfjJMY7VPqunnaBi7NCG11l8xxT6IAFjQtK7DYlxh+n0WxheA0yCAJXs2DZibtMdMIo2UwlkD1CTSHdT5LOTzzJGzzqTJufKFrN9hZRvWLnwjErc864c6Gr8GythFfVmqrxs/R/klll1/RQksmGZ92zQDLDx1Tes83xrjOcMLSmwIWxZgNb0Oq0l7zCTAUufjmxtPHryq3VH9GmBagDcBOXbUHg10dmmPLTwnZexCX8bAwsshTRJvPdK3lnk5BOA4zQvdGVd4mzc1vjRpg3HXzfQglLfJqOprC2Bu0h4zCbBSiJZ9m1iUx15RTRpEjXPWjv5NqVmTvc3ydnZpp3Xy7AL4YksP3pTkDc5Bg+AkpYOXsuuvxAfrdqbZg8Vbo6nxRfIthKMA1iAPFrK24U3CJu0xk69qpBTOd9d46uOVbLZD4BXobspqIXQHnQydBmZHA0zd4A1mk+HU1h11aqLK+ivxxZ5z7BkHOJu2/pdxpcwWKJJ1Wo8ALGzDGDmI8EimPgU16Lpxnk+N9+Msv6ismQRYKQ8Vi0bZ04bXm9ksLrXxZZEiu3PDa4ANH9H7+uuvn9wPa/iSuytH0UBnl1G0N7lri+xCP8a2DOzjldpbbnJcLV9ylfVXupoBmbfOAInsozZNxLjCFCF7DS7kbSZY4A64KtO+8GCx+XaTgDk13tfVrmYSYOUhWlA5m17Gm2PWZYxZrYddsXnapXPNs82s6qZJuTu7NKn9/LqnxS5V1l9JWvoAiE9qTRvAou9iQ96F3ofhwSo79czGq3zhhK8o8AJDE9SkPbo1WE1YvKtznga4AdiFvckbYR5D3Z+ggc4u7WwI02CXYdZfoW0Gbjwj07gOaxrsMo4WDcAqs/6KuvgSAwTIaoqaHFdmEmA1vfFZUw2trfViDz6C3NmlXRbq7NIue4ibabDLMOuvkI/BcFoXuk+DXdSGRjlWAVh6GaNJgNXkuDKTAKvM3PEoDbC7tpoGsAff6OvsUk1vk87d2WXSGh6u/GmwyzDrr6QNpgmb3jtJvFQ5ToNdqsiTysv0tPv0TCrLvLQ2eLCaHFdmEmA16TKc1/q6P0ED2INv5HV2aVeD6OzSLnuIm2mwyzDrryTftHqwpsEu0vGwR+1XWHaKUB4s1mA1RU2OKzMJsJp0GTbVyNpcL/bgI6+dXdplpc4u7bKHuGm7XVh/BcAq8/1ByeSPeLAYyJsclD0/ZeNtt0tZOYry8QYhVHaRuwDWJKcI+f4jHtM8anJcqRNgrWIKONXCgxZusrCjhRTtbYmXWgDyHm4hpl0s4RYLlHOShb+1UIkW8iu0lRTRkszYY5tttlnQrza3RNWV2OjsUkldtWVuu12YQnrggQeG3hOKvbCgaZsmbLtdxtFAWX8FlfVgsW0Ib+dPCmCx79t//Md/ZJdddlmueNilKaoTYH3JhLzXAnfPeywcZ2ElCzHxKfUDLRwSn7D/q1o4xsI7LFAOcPqLFirRtG1gV0m4KcyMPXglu7NLu4zX2aVd9hA3bbfLL3/5y8DqsJtuMkUITdubhG23S1DqiD8ALLZbKPPpI6pCJ3ixJgWw2D9RHlOOKYKHpqgugLWCCfgSC0ssPGThZAvXWtjDQkznWMLxFn4dn7D/L7XwYwunWaCcJRZeZqHSBhtNugyN144iDWCPk046qZsijPTS9N/OLk1bIF1/2+3yi1/8ImxEWWan75SEDN48cE0bwGq7XVK6rpqGd7Lq/mQsdJ/UdO9NN92U4SXDk5W3Yzx2aYrqAljrm4APWLjLCQrA2sj9LxN9mmVa6jLebnG0t65L89FH2h+2A1YIe/sL0bIjMgHycXZ+VTpx3pyA8uIYUHmIC0krzv84TnlKJ8715FFcu8+SnorDn9I973lx8rZVJmTeaaedwtPOQpHJy+HjssE02InFoTvssEOYuvXtEN6nVSYvh49Pk0xMefDtVJGXw8ebkgmAtcYaa/T7N/o539f5OPym+j3WYWnAbINMcf+dkok0+jHum5RMXg4fb8pOZWTychAHyODB0v3v5fBxLxOAWQCLdALk45SndOKUBeXF4eXPf/5z+ALIlltuGd5AZx1WSqZZeIsQD9YfgsYe/uE/6VWoajnvt8KZNFa4m8r41hXEFv4EaOnSpcFYxK+++urs9tvBbll2+eWXZ3fdNYcLWUx3zz33hHQ+iaAnrHPOOSfT4r8zzzwzLNAk02mnnRYaFo2EOEcaGnGIhZzkh7ieciDKpXyI+qgXgg/4geAPPiHcpPAPTaNMfJqIQYMbZKHItBDsdO+992ZXXXVVaFcLte1Nq52YqrnwwguDbdrURwAy7rzzzrBx8Cj9Hl6Pu+8O3fXU9HtnnXVW6McWcl8OwAJAVhmfaBP0JdA4xyc+ag6gQt+rr756GD/yxtxQ+QL+2dxkuz+S7yD7f2CU5v++z/4c7hMs/gULn43S/mj/N47S9Df2YD3RTvR+9atfmc17PesAQojjZrR+OnFD1iF/XtyQdD8PcUPfIb/i/I/jZFA6ceogj+LUVRSHd+XJk8Onk5f/UJ4cPh1eJLd451rFxTtHxTnv42Vleuihh3rf//73e3bzLhiZvG18XDbwtvFx8iqPt0defJJ2soeBYBfV4eXwcfHr5fBx8ipPnhw+XfX59ubjamPjaHteDh8Xv14OHyev8nje8+LjlImyuF+4byDuM/Hu4/CndM97Xpy8o8pkD4e9JUuW9Oyhr98XDGMne6jsHXDAAaGMpmUq2/bs+7XBLtw32KjINtMik5eD+KGHHto7+eST++3Ky+Hjvu0deeSRvaOPPjroY5xtz5aV9L74xS/2bH1X7+yzz+596lOfCnHf3ojbZ5dYnEVgJqtWekRNtd1s9eB9WtPC3GPJHCj6VsX6f2r5ectQtMgi/8fCrUqIjuzPv9we/Xp11LsOfdy/dVAmzhywqEqcqUrl56mAAJWJe37LxMvI4fOIL/ipEh9GJp5Wd9111/D0p+nbaZdJtiwjh8/jbVAmXsU23pZl7IRr39tlIciUd295G5SJl7GNzzNOO9lI1bcLNm2TTH6Bu29jVdseC91twO5/9Hka2h5TZ/5+KbKNt1mZ9ubz+HZVJj7OtscMDHKqXi+Hj3t+yc9sDeTTfVzlkads/Gc/+1m2ySabhAX366yzTvDo/u53v8tWW201iumPW17+cKLGn7rWYLH+6iQLSyywIH13C5tYIC2m/88S+IAR4M/HyXeihcUWXmjhMRY+bOG7Fv5koaMp1oA92Uwx9wuX9c4u7bRtW+3C+is+8MugOgpRBnT//fHExyilTv7attplXJJrDVaV8nhQG/dbhEwfm8cw23DDDQMra665ZnjQYJlJm6gugIXM+1tYw8JvLTDN9woL3D2vtjC3KMoiRvtaADAdYOE1y+IfsiP0awv7WPiShd9YWNnCOyxUooV+E1RSRgsyYw/WonV2aYExHAudXZwyWhRts13wYA27PYNXsQAWHolpoTbbZRw6tOm2sIa4KniexFuEvD34mMc8JgNYQXipiLPBbUxNjit1TREi830Wdo2Ft/9HLQs6dbhFCHnECvG5VeJ5OQakN+kyHMDaTJ7GHnvskdqxYybV0RqhO7u0xhTzGGmrXRiAWXD/1Kc+dR6/w/xhmojtAKbJg9VWuwyj/9Q1TA9CVQHWJPbBuvHGG7MNNtigv6wGvvhywJVXXhneWNVSE9KxS1NUpwerKRmXq5c1DB21RwPYg/1VOru0xyZw0tmlXfYQN221iy0mDl5otmgYB+HFmiYPVlvtMg5bUAbTg1DTAIu37NnlX9ODgSn7WbRoUWYvfmS0Q09NjiszCbCadBl6w3fxOQ1gD1457+zSrhZRt13wgPzoRz8K+9u0SxPt4qZuu5SVnvVXeA6e8IQnlL2kMN+0Aay22qVQyRVOjgKweGFhXP073iu8Uk9+8pPncb/WWmsl12GNq955lZX8M5MAq0mXYUm7zFQ27LHbbrs16sqdKYWXFLZuu/DkyXfF2Neto3wN1G2XfE7mn2H9FRuEsqh5HLTSSitN3RThQu7HhgVYrMGCxrXQnfVX66677nLjBfcF6//idVikN0UzCbB4Uu6oPRrAHqy16OzSHpvASd124QPBkHbwDn+6n+U0ULddlmMgJ2FcC9xVPB4s1v1oYFd6W49ttcu49CU7DDNFCA/jAFi2F1eGp3S99dZLisU0IW8S+mnBJseVmQRYuCs7ao8GsAe7uXd2aY9N4CS2Cx3bLbfcMjEmO4BVTrWxXcpdNdlcTMPYBs7hEznjqgkPFjQt67DaaJdx2YJyALvsXeX3qSpTvvad1CL5Mtfk5QHEA5709mCcL7UOq8lxZSYBVpMuw7hBdP/n3vLYeeedl3P5drppVgPcJ7KL7fKdHXfccZntmDwxprQZYefBKlaxt0txzvrO8ikUPAXjWuAO59qqYVreJGyjXcbZAvBg4b3yb+iVKV8AaxweLPa/Ygp6lVVWSVad2g+ryfF+JgFWky7DZKuY8UTswaDa2aVdDcHb5ZJLLglvemqaYBKcyoPFgAqg6yitAW+XdI76U/EssJO3dtEeBwcM5qzfmRYPVhvtMg47qAwBLP0vexznGiy86IB42lqKAF+8ZEF7FDU5rqS5FGcL9NikwheoSkcSC3vw4c7OLiOpcewXyy58WPiiiy4KG/vxGvSkCIClzjh+1XpSdU5jubJLm+4XBjQ+uFt1+miQ/qdpoXsb7TJIv1XODwuw5MEaxxQhAGvQRra0GQ/Km7xPZhJgjbsTqNJIu7zLawB77LDDDmPvnJevqUupogHZ5YILLgi22XbbbYNnaVKvPQOw2CwQ6qYJ8y0lu7SpH5NnIZ/r4c5M01YNbbTLcFpPXzUswNK6rVGnCNkrkWUEgwDW4x73uOz3v/99X4gm75OZBFhNItq+1btIXwPYgw66s0tfJa2IYI+lS5dmP/nJT7Ltt98+06LjSXmx6DwZUAksmO4orYG23S8AbjZ/HNf+V17qaQJYbbOL1+M44sMCLOoex27urL+C8ha4h5P2A8ACjOlBsMlxpQNYskp3bEwD3AC33nprB7Aas0C6Yt6+Offcc7OVV14522KLLcIUITknBbDwYD32sY/NVl111eV2Y05zOJupbbtf2FUbYg+scROg3g+W4y5/nOW1zS7jlI2ymgZYPITz+ST6iCIClEMsbYA6gBXUUN9Pky7D+qScnpqwB9NPnV3aZbPbbrstuNp32mmn8Hq29r+hox03sb8NYYUVVggAq/Ng5Wu4bfcL3itoEgBLg6VfU5OvmWbPtM0u49YG973WSFYtGw/WqGuwyqy/gi88WJCmCZscVzoPVjBF99OkBnjCYPfdJp80mpS/jXVjC3ZVZ9qHXZMhvl4PTcKDpTcI5cHi/yTqCQJM+U/b7hc8WIBvtY9xqlfT0tMAsNpml3Hagb2nRvFgAcx4gBqW0C0vUgxaf0X5eLnYSkIAi2ubog5gNaX5rt6+BrgBujVYfXW0InL99deHdTV830u7IvMUSsc1CeAjgIUHS6/6dwvd002hbfcLHqxJeK+QHsDNIulp2AurbXZJt57hUgFH9APyYlctZVQPFn0BW7cMWn8FX7QXQJZAeQewqlprxPxNugxHZH1BXo49tt56626KsCXWpUM6//zzs/XXXz/bZZdd+nYBXOGlmMQUoTYZBWDhtWCfmw5gpRtE2+6XSQIs2ty0LHRvm13SrWe4VN3zowCsUd4i5AGctlD2RQqmCbUGq8nxfiY9WE1unT9c817YV2EPPsHS2aUddmZPMqZ9ttlmm+XsAsCalAeLJ0+mEjiyU3MHsNLtoU33C14N2govQkyKANzyRkyqjnGU2ya7jEMeX0bTAIs3CHn5peyHxD0ob3JcmUmApSkP34C6eHMawB50oJ1dmrOBapb3aoMNNghPi7FdeIJVZ6trxnFkihDvFU+pEJ1pB7DSmm3T/YLnkemjSU0RogEGy2mYImyTXdItZ/hU3fNNerDKrL+ShH4vrCbHlToBFh8POtXCgxZusrCjhRQ92hKPtPBHC3daeJUF0fYWYcXaAy5sY/FK1KTLsBKjM5IZeyxevLg/FTUjYrdSTPa9YjBj36uUXSbpwfKvXwtgNdk5ttJAxlTKLk3xOsk3CCUTAIsFy02upREvRcc22aWIz2HOjQqw8EwP+xYhU4t82aHM+ivJBsB68MEHw7ot7NIU1QmwvmRC3msBoPUeC8dZmPtcukUcfcTibKjyRAsvt3CIhadYEN1mkRVcuFAnyh6bdBmW5XGW8mGPG2+8sZsibNjo2IFd2zfccMPgvUrZhSfYSUwR4gnBgyUCYNGxsgdSR/M1kLLL/Bz1/WN6kPVygKBJEVOEyKx1epOqZ9Ry22SXUWWJrwdg4V1msfowxHXcz8M8MOm7glU9WPAJMMcuTVFdAIue8yUWlljgY2YnW7jWwh4WYtrXEj5mgZ71UgsnWdjHQkcLWAN6QlrAIrZeNLxXTAlut912fV5ju0xqkbumCFUxAAvqpgmlkfnH2C7zzxb/Q9dXXXVVcaaSZ/Fg6aWEkpdUzibwNg3ThKPYpbJiarwAuXi4+n/tnQnYJUV1929CCCYKRKKfgAjDLgwM+74N67CDIEJY/AZEIJgERPyMmoUkLskXWRQQ2RzBQVAEHJgZhAEyAQaBYVgHGGBkN7gkRBMWUePk/Hre81Jv09Vd1be6q9976zzPuV3dt7qWc7qq/nXqdLUu4ftmrcCszlYN+F/he+WzDK3PTGzfvbYA1rqiEJb1XjAUA8CaaJwTZBq0svDDnIxQPt775PpPhZ8S/hvhZYRtBNxeweAxW8CCbBXdmmG22NfrhNU0bQvz+qjGIawoXcOc58MUWK8T5n7iaNjc5r8oTPn0ull2W5i4Xa0Tcthss82yunexTpTpe9/7Xu+uu+7KZD6oelqwYEEP3yvtyOhMN95448zpnOcTOagFK7SeGPTf/va3Z88A8mW5kE71pZdeSu3J6BeQDS8BbLLJJqNyUd3k+w5bH8Hu/DfccENmHTT7C3Tq20foG4SUq6l+j1fuIQZLW53MepjhOnWq25dzH/0Y7WbQ+ggAlm4yanvezOt5PS277LKZDrF+8x/kqicAFtYr0och5GuG888e1nAsq1iwOMaitnLGgpW39XP+5prAUgnoOf5XSma8RXJxE2FAGNYvlhBPFbbRp+WPXxj8IhEfeQTM1us9/vjjGRNm9v7UU2C2Xu+BBx7oPfPMM1n43nvv7b3wwlJcyABLhw+xlKL+B7fddtvopmY333zzqCl79uzZ2bozjZwwR9ahCUOYvIkP8SCQDkS6pA+RH/lClIPyQJSPckKUm/JD47VOvLnGzuFdqxMN99prr83kO2fOnN6ll17amzVrVibrQdLTrbfemlmLeBtMnz1ejWazUTpCffawYGHqB4xBIZ49Okr8JZRoB7xijRXroYce6lR7YvuK888/vzd//vxofQT6uO+++7KtNJCZTx/BQIlMIfTbb7+HbwzPTJP9HvVjcMeC1fV+j36Mcg5aX057VOtTnX5PvyPoOz7Nmzcv63sAWD5jLm0E3yt0YfYt2YPf4s/SV3aazxDzxK3CKxlZnSvhN4RPN669U8IvC68oDLCCPiG8nfAHOcnREXL+58I75K7rKRYsc9EYC9aLdArM0lECxIzQDAOEmIVwnTAIGLaFdVZJHMIoVmcx6mDHvWYYRM/gzXXCDDKUQcOcE59jUZi43E8cs+y2MPl0tU7IjIEa6wky7FKd7rzzzqxhH3TQQdlSyIwZM7KZ/2677ZY55vP8DIKe6IgADkcccUS2czt1Qi90iBMnTsyeHZ5Dvhl51VVX9U455ZTskxS25828XvXs0QGeddZZvcMPPzzz/9L2BJAFBJx44omdaE+U88ILL8wA36GHHtrbYIMNovQRtJHHHnssay8svfj0Effcc082+GMd3HzzzXu77rorj/BoPXz6COTxpS99qUfb4BnhmWmq37v88sszC+chhxzS2X6PiQfbzay//vqZTAepL6fN046PPvpo6/NmPoe0f3N8Yqn/oosu6k2dOjVzVncdc7Fsn3nmmT3aG76hPPs6zpKGhouevW9+85uZz9iee+6p24iYuCLTUdM/bbnXYxrCOrWacGZFkuNGwpcLm/SfcoIj/MbC80b+IN6jI+H8AXthGUgEwMFjSPfSQEFKZhhlKbmEaUhKPmE6I42vDw7puITN8rqEXephxtFyUR6fcJ06MUhstBFqfpO6UCd2M2fWtPvuu/c23XTTrHAnnXRSD2sPM3YGmD322CO7btOZSz3MOKYOXMI+uqGgGj+vJyyoELuoa77EnTRpUnadH+qIBQsCBEFm2W1hTY/4RWF1XtalIC2jWrDoqM3yko7GMcNmHJs+bNdtZTevY73CAr3iiitmA6k+s0V1olzm9aLymmW3hW11YulWybVODIBYwCk3YADnYbN+ZnldwvoCApNVn/rZ6mSrB9fx8/rxj388prxm2W1hl3qYcXzqYeqMOmFl02eiSjdmXW1lt103y+sS7qdOei/PvbZPs+y2cL7sZr+h/+kRWdnqoW8e4jJgxtFymTrIh/HD4hk37yNOm9TWEiH+VzOEzxBmG4b9hem5uZan6XLhr4SxNm0tfJDwt4ShycL4YEH4dRHvek58SGfXPvekuM1JAH2wNNglvbBciZ8Ks/wddnjTQErD3nvvvXvbbLNN78EHH8xmc81Jpr2UsepSN8CDUpFedB+ckG8SMkuFzG0aOAdgUQasa23Rs88+22NZIv8sssTBsiAWH8DNk08+GU33RXpxkc8TTzyRLb1uvfXWmU8L1kFAV13iDUKoyU1GtWzkQX6A7a5SXb10tT5mudTJ3bzmE1Ynd4C9D+nky3zD2PV+3Qsr35Zd7w8Rry2ARVlPFl5VmFZ5lvDhwvScRwmbFqq/Gbn+khyvEf4z4SeEoS2EebMQhw2cl74n/CXhRONcAjpwd6EadCZXX311b6211urtt99+mfUkXy6cjLFgsWQ2CKTL5szETcrrRWeiTQAsdXLX/PVNQsrWNDFwsxzMUhR+Z5dddtnoFhF00DNnzsy2rgBYswTEM6K+mU2XrSj9vF6K4uSvsTzItyVXXXXVDGDhU6MgKR/X5RxfHHRWpywu6ZtxeBYor37+xPyvS+E2ZBGjvrEAlm3y5SIDLFhYwNQK5nJP6DhtAix6yX2FWWNYT/gWYegKYfNtwtflHND1DmGsVWq9kmDvTOH3CvO60ZrCgLHfCHuRaZr0ujFFbkQC6IP19a7oRS0YBx98cLYsVlTplVdeOfuci75cUBRnPF0DxPB5GpOK9KJvEoUEWMxSGahZbjAJMAfgA8g2SXTA3/nOd7Kl3x133LF33HHHZQM5/lZYMu++++7sBYD9998/KyMOt5QXi1DbBBBksFt77bW92gvLa88991xmeaXMgCwIK1ZdAmDpG6d103C9T8F2l7ftKGovrvXrerx+ARbtGNecOhYs7lO3Hh85YcGCFKT53Bsq7pvORqFSHAfp4KyXqDsSQB8sEfKKc8z1ciRCY8RPBUtF3qJiSowOA/8k/HLoNNQEbsYZL2EGbQZLXjIwqUgvgCBm6XS4oQiZFy0BIGNAVkgwly8zFpwrr7wy0zsO/uqgjGM9b49Onz49A1UsqykooVzIimXCvfbaK59k0HN0A+DnJRCsN4BRlvUAwyeccIJze8F6hQ8NExmI55U0WPpU/0LfgiM7lYnvvb7xKTuDLAAr/5z6ptVU/KL20lRebaaLvyV169c6x+TM15pk6xtc6q8Aq00Xg3y5xk4Z8/8O6DkdZKLuSAB9YM7tgl5YJgJEbL/99pUCwheHjoc37cYz0YnR8eUtWDa90NGGBD3kn/e/UnkCsJq0YLEFCktPgBUFV+RNvkceeWRv5513zpbTeGvUJIAKAANg2iSxZxUvVQBAed7w/9t2222zT4e4LpchP7am4XNUppUYS5zuku1bBwXlbVmweBaxYrWxXOwrC41vay/6/3g9KijqF2AB6n0tWGV9Q5U8mSDjV6ovY1TFb+L/oQRYZifThFBTmn4SQB/rrLPOmM7fL4UwsWmI7C+03XbbOc3WcAifMGHC6B5kYUoRJhUGQHyJXGZvOmjlAZZNL4CPNixYSCJ0XnnpYhHCCsNbankCaE+ePLl37LHHvmWJYs0118ysR00uEwL+7rjjjuwt1sMOOyw7ApJwtMeao/v55cudP+dlDAZ/XtgwiXr/5Cc/GX0j1PyvKgy4Y3LRFsCiPACsri8RdqEfq9Kd7//a1tU9wPd+jV8HYNE+i6zbmmbZkWceK1YCWGVSauA/OoZE3ZEA+mAwia0XtmRg4MJC4EosE7L5YcxGXFRWgBVLS7z5VkUALMCUfl5C49v0AugJbcGydaKh89K66bFuB87MGD+opgAWG7mysS0+YbBJAD/AMMvqLm8BYmFl4EeWJunu2Phn+ZI6x7cNsHhWXersW58Q8W3tJUTaMdNQgBXLgmXrG1xkAsCK+bmcobRg0UEl6o4E0AedfUy90AgZsNiSwcefasMNN8wsGa7WhLakrm+4AQCwZpURgxYDZV7+Nr3Q0WqnW5auy3+UrQzktAGwbMuTVeVnSRE5h17CZP813lrEWpVfmqRM6AW/KUA9TvhlhKUJR3Y2Rc0Te54BrOs4urM0yr3mth759EOfY8HijU4Xq2zovF3Ss7UXl3u7HEfber8ACwuY7xIhfUPd9olMAViuS+lN6GAokUZ+IGlCsClNdwmgjzXWWOMtA7x7Cv3HxFmdDgRnZh8CjOGPw9uEVUDGJ91+4z7//POZPAGOVX5C/J9fHiR/m15Cgh78Oxg0bbPUkHnlZUq+gKO6Hbg6W+PsHop4hm688cYMEO2zzz6FfonoZYstthi1YpXljfWK+FpWMy4AaZVVVqkNsNibirTboq6/SWhrL3XlA7DBBy8mQKDsoQAWqwPqz+UiE5zrAWS2vsEljQSwXKQUOE7spajA1Rn3yaEPludi6QW/DgDSTjvtNGZHalfBskxIGvizdIV4OwynaJayqpax1IKVL7tNLwDRUEuEOLFCNpDTJMBSy5Mt77w88uc40bKvVJV88/eVnQOIKRcWKnxIigi94JtFnEWLFpVa0ABYLGXa/GewHNexYLFE2ObyIHJA3jwPXfXDsrWXIh26XMMqTr943nnnZUBLvwXocm/IOAAsJpL9gmlfC1ZV3+BSRwCWfnXCJX7oOO1NP0KXvI/0+n1Q+sg63VogAfTBIBBLLziD0xC33HLLgtJVX2JDUjr+kHtisfT05S9/uVbnQIcIaMIRG7mWWVgYzAFLNgtWkV6oK3mE8IXRTtQ2SyUvOsgmOkmWH6C6AIt7sQyx2Wyo8ulHcVdbbTWSLyRtL/oZI9tzh2yxZBYtD2rCACxAnS9gxurZxg7uWk49dvlNQtVLqH7sWfmqAC8i4BOKPyVAK4YrAm293+VB9Ofr5K7t09Y36DNRdsz7lZbFbeK/BLCakGpK00sCdEixfLDwYWGPIb4pyJJJHeI+gIgOjnXSyN8DwOL7gHX8TbQcWFcAAGV+Qrp8aANYRXoB9EA+5v58/fS8qhPVvHwBgKZfdtS8+wFYgBcsF2UgtqwM+f/QHcBF653/n3NtLww85I/vYNHyNNYtrGDm9hP59NAv5GPFYsBFdm1bsChnl98kVL2EAFjok41h6Vf4FurHPvaxrI9kb7a6W2sgvzoUC2Dp5Kuf9snEOSYNJcCiQ0zUHQmgj9tuu631JUI6Md7UwlpQNst3kRQdP0uERQOdy/35OPrxZawLvoTVguUUZm/qewOILCIsXQwIRdsU2PSis1k63n6JThTfDLiIFGg0BbCou+ZRlH/VNcAQIMVmRaq6P/8/AKvMekV8Uy9szosOiwASy4MTZBuRsvrxjKDPovvzZdNz3pqFVl99db3U2pF2xvJkF/twUy/9CgSd8szjmwqhpw9+8IPZkr/Kv988XO9nIqVt3vWeongsEWLpxffRhQDxTF5ty9suaXCvz0tLLmn6xBlKgBVihuEj5BS3XALog6/Qt60XBkVeUWc3bpu/S3nJ3/yXN7JCfitNAVZdCxbWK+oE0GLAtvkJ0ZEDroqsdza96IAdAvQAsMpmqCHzelNbS0N04FiB+tU9vm6LFy/2XmbLl4fnh+exCmCZemF5mjf5+PqASYBfBuKqiQN1ByD6ACysvgDLGNYBABaTGLW8mnWOHTb10m9ZsF6RHu1YiTbKOf+1SSEtWJTb1ZeMvqHf9snz3eabrnm9JICVl0g6b10CdCR0nBzbImZSWM3YZsHsxOrmD8CCQjm61wVYzA6xgph1YokIP6GiWT8Aq2h5kLrY9BIS9GgnSn5FFDKvfPoArDJwl49vO2dywKC/cOFCWxSn6yz9kI6pu6IbTb0wgPByBr45vAmrpNtz6Kdx9HrRUQGWi/WVODxLALsYpM9qFx3dTb30KxtAFP5XecvuBLFI8l8I/0fXMgKw+rEiaT5qSXJ1LaiafGm6VccYEwEtU3sjmubYgWMoh9QOVGUgioA+brrppmCOwi5C4QO+NGD8G0IQAzWdUAiAxSCmAMt3iZD8AVLmIA3AQsZFSwtlAMumF10uCLVEWObEygDD9ylDWMvyeg7VgWMlZCPPfh2QAcbUV0FEvrx6ntcLWzbsJp/ymTt3bvZ2IfFYHuQZcAGQWMzQpW4eqvkUHXkeeTbxDYpBtDG+S9hFgJXXS1350P5xcAdM5YklQ7V05v9r6jy0Bct1Lyy1MPdbrylTpvSbRO37hxJgFS2H1JZgurFvCaCP/HfS+k60JAH2leGbg+x5VeR7VHKr9S8sCVixQnT8vNlHZ80yjO8SIf5XyJP9jZRwRsaHI79MSMcJyLA5K9v0wnVmoyFAj0snihVLt1TQOoU4uuTtmg9v9AGQXECKLU3ux5pUZckt0gtWrMmTJ2dWWfZOwspUtTyo5cCXijRZ5qwi0qV8RYN/1b2h/sfazcSga1Sklzpl5BnieVf/KzMNng8mHACwtigUwFIrmCvAom8qm3y51l+t4K7xQ8YbSoBV1YGFFHBKq1oC6AOg04ZeWEL77ne/mzlt8iHfkETHH8KCpdYrlmEAg65OodSFNwZZWqATVgL8YcXiTTdzGUj9WGwWkzK9YMUKAbBcrEh0kCHyUnnoMdQSIekhX6xPda1Y6AXdVflfkZdNL7vsskv2cWr2TuKZcQVYlBuQBXiqIvyvKKMu91TFb+J/2lmIiUzostn04psP4Ik2a1qhNQ1AHNfb8sNiKRJApFZrLUedoz4zrgArVPtsY1yxyWMoARbWgUTdkQD6mDVrVitLhLw1iK8LH88N0WmYUsSCFeINJxNgmcuFZl5FYR2kizpmAAAdlvmKN1YAOnIsZUVUppcQoIelTPwxqmap5MUsOiQBQABtLktoLvmyoSv+fLw4YYJYl3uJg84pjwvAKtMLViw+Bs0mpD6+Jyz5MbAX+elpHRhsWWaO5X+l5QBgIS/XgVrva/pYphefvNX/SgFJ/l4sW235Yam/VIi+UuujaebrZZ5r+6zqG8x7bGH0EouGEmCZs/tYgk/5vikB9MESR9N6eeyxx3r33HNP9tYgpvbQRMfP4Nrv8gV+LpjTdZnPdZkQaxcgqghgcQ0wMX369Gx3aDo5ysnSIeCgiMr0EgL0YL2CqjrREGAuXz/NOxTAIn2WCdEdS32+hPUKcgFYZXoBMGOZPeigg7yKgA8Z4IolZhvxpiGgJpb/lZaLdgb12840vVDHMr245kH/AdAtWh7UNCaIbxZ6CGEt1zRtR53YhABYyAdrkgswDtk+yTcWDSXAohNK1B0JoA8cV5vUC5alGTNmZFYG3+8NukpKO/5+ly+YnWN9QCYsCbgCLB2kiwAW6Rx//PEZCGAJiV3iAZy25UHqXKYXOlztfF3lk4/Hx4qhKpDTBMACiLrknUVy/GHgQ2d19sQClGFJpK5VVKaXqntt//PsAnTL/LBYQgT4swQdk9RnsN92FroOIfRCWwdc8CzZqE0/LG3jIQAW8sGK5QOwqiZfNhmZ18k3FrUJsN4tlZwl/KrwE8K217f+QP6bLkwPyHTqT4RNmionTBHpnacJF+9QKH/YKKbJ0FamYb6OPgA/TemFwfTqq6/OBpADDzywMSBH5wEw6ndmCcDCskTHgG+aD8AiPm+1FRGDPx8QPuWUUzKgxZJUmSWvTC8hQI86hFPXMgqRVz79JgAW+mLLhkcffdTLb46yAbBcrFfELdML/9chyo4Vq8wPC/8rPr8U06eFumFx5TnvGsAKoResV+iibBNXLDI8K234YYUEWOjOFWCFbJ9NjSvUp4raBFjnS2F+LAzQ+qTwd4RXEs7T38mFdwmzhvMh4a8Kry8MbSx8tvAHhNmBDf5rYS+KaTL0KuiARsYMbvqpoA82+wytF2aCbP/wla98pYe15EMf+lDjzrkh3iRUCxbqB3y4btWABausY9bHCYsRQOuTn/xkb4cddtDLbzmW6YUZbb+O5zjZA0htS5RaIAVY5jOj/9U90oEDFELMzM0ysOkog1LZUpsZn7C+du8KsMr0kk/b55ylP0CLWhbNe1lSBgTGXh7UMmFx6+ISYb/9GKAJ1wD1V9L65o/qhxWyTeTz4FwBlr4BWBTH5xrpuPhg0XcDNF0sulX5hx5XqvIz/29rcfIdkunBwmye8prw9cKPCOMogBXKpGPk5DBhLFR3C88QPlL4b0eO18hxvjD0OeHLhL1AFgMWDpv6cKJISI+E9T/CdUjT4khaJnMNpoPP/0+59H89kr+W1/xf7yce1zUOefGfz//co2nk89D8cTxUJg5hvYdGQ2Nk0OWo5xpmEGEmgZ+HzihYtuLh50iHQmNSZoZKZ85yBPXzIXyR8LWaP39+lvaOO+7Y22abbYJslldVDjp+vg1Xl5CnCbCQg+0zN2YeyBfLmc8Hq3l7rIpsnRN6Qrc8N7760TyxYOlyj14rOpIXcmFpIVRHD8ACaNYte1E5uYb+AYy8TIC1x4VcNxg107LpxYzjG1bndaxYfILHJJzb0bXGMf+LEUbOCxYs6Ov5a6Lc/egF+WLBwgpaRRMmTMg2lqXNr7zyylXRa/9PG6dOVZMg1wzo5+mrqoj2iSWeMWw8U1sAa10REh6tSz05l0oMgDVxaXD0l7UCnpaHR68sBWLbjZxvKMdbc//xQSwA3FKPWeNPCS43wnp1eQIXXnhhsI5aE07HXgZmsAgwCDIocsQCQ5jBXIEUDZYBkw4FwMXAyR5N+KAAzFgS40O17OfDvQxU6667bo9dqbUDIy3uZYAkTKNlELj//vszQEKHsP3222eAQxsqwI64NFrCpMX9GkaHpKl5ECYdLSdhyg2w1DDnWh/CWLCYfQHy+EQDcbmfOIQhymALA65IB8sO+asFi/qRBmXnOketB+lhDSIf8odC1Ik8v//97/f23XffrMxaV8pOR8k5gBo9l9WJ8qqezLJTZrWImNfzelIrEzLVmT3x+9ETOsK/Q9Px1RP3FdUJmWCBADSV1Ymy67OH5ZH2gc7RIcS9tmeP/2fPnp1ZfZENeapuzLBvnSgDExoAFpY4fcYoC9cA+4BS8jCfPQ2bdTJ1Y4ZtdbK1J+4tqhPlxJeQZwg/Qlt7sunJ1I0Zzj97PnUCjPCW8t57753Jx7dOWA4BFmqFLqsToIo2x7ItYBMdmPUww/3Uif249BmjPL51Qn5mPXjGkBNkXqe8ZnvSCZBZDzPsUyfixqJlWsoYgLWf8DlGfjtKmE9dzzSusXz4ceHPGteA85sKTxf+qDDWqweFIb7ajPXqXOEigMV/3xf+9AifJsfeaaed1mN3V3xSMLVOnjw5G8jp7HmbjQGDwVzfbOPtIJZSeAA233zz3nbbbZc1eqwiMArESoLzNA8P6WFJ4OHcY489eptsskl2nYFq4sSJWXj//ffPfB54aFiuYWZII9lvv/16E2R2woNIGelIAAiYnum4GXD33HPPbOZPx0JeXCMeuzkzqHM/1wEnpEvZqBP74rBXDg89HSgABOKVbupE586R6wyu1J8NQKkTafMfdcKPiXozuB5++OFZXQFJJ5xwQjb70uU4/Hsw49PhUAdmW6RJPlxHpoRJ/4ADDhi1YiEbOnPqRRo43j744IM9dl8HiAFCsHzMlZ2r2duJXatnzpyZxaEDQBbkySx83rx52UBK/rfccksG4ugwAA50UgzY3Ktv7TBw8RwouOA5oLED9vhwMtZP0sRfhTpgJQMAMqDi3EyYazwTxKcDBPhRD8rKm1joEQdzBgc6x4ceeihblqFODBosxfAmGHsqMbgwuPGcoE+eWeoNODDrhGyRw7bbbptdD1En0kTH1AkQAOjFgZ46PSszbeqCjpBDWZ2wNACc0Sk6ROcM1DfffHMmd+RdVCfVE885sgVgAbShfvVEmSHKpXXy0VNRnQBIbGCLztAhaef1pHUynz3Kgi51iXMn7AAAOChJREFUCa7q2UMGPAe0CfPZ4xlmadLUk2+dyBv90hdBWic+A8Qzz3PuUqdQ7clWJ7YdoR3S79Cv2dpTmZ7oK2ztqUhPVXXiU0X0O/QXZX1EUZ1o47R3+gSeR/qLsjrRv9AP8swwqVI9ha4T/R5ponvfOhU9e/SNyIex0uz38npiqZQ2QZvvt06MWWeeeSaP8z8Kv0GgLfqdljLC3ozlaSUjP0ARlT3duIYF62XhFYVZIoQ+IYwF64PCM4RJ5yvC0B8L/7swlqkigFVkwXqRpQk6exNBm2EGMxNN09k0NUMgLx4gOmXKoGHO87M3rul14jJQ5WcIZj3McJfrRDlVDqLHwjrRmTBw0NHzQVwl5AVIYcACKNIxkV6RzuiUmPXxH2Fkp1YEwhDlMMOkj5y1fFV6Iu0vfvGL2V5EAFXK4qMnLHA33HBD7zOf+UxWNup9/vnn94488sgM+OWfQ60TwIzO6/TTTw9WJ8oOwGJApQ7ms4cOLrnkkt6xxx6bydzXggVQPe+883rHHHNMNglAvqozrZPqCQB+9tlnZ3uX6eaZ/erp4osvzsCd+sz46on8bX0EQPfaa6/tnXrqqRmQ1HoUPXsAGnwEmQwAql2ePeKgFyZhZf1FnToxYF922WW9qVOnZgM9ZWe5nQnJEUccMfoMltVJ21aI9kRdbf3epZdemskX30rqCuWfwzI9UQe47Nkjf9c+gnpTDvRCmct0Y9aJZ+C6667LJmBsr8EkPF8Ps35aJ23zn/jEJ7L4Zj3McL49+dTpmmuuySzyH/7wh7O6udbJ9uwx8eMZO+mkk8boTOtEvQl//etfz/p0jBL96gmQxkRQyMQVnDdObS0RPiU1YRlvNeEXR2qFZerykbAe/lMCjJ4bC88buUi8R0fCj8mR/5T473nhInBFHADcWxArgwWEMpXMMA+gkkuYh07JJ0zD1fj6EJGOS9gsr0vYpR5mHC0X5fEJ16kTjRFrBo1J88rXieVDLF4wAJlZP8CKhkOeJpn1MMOadtN1wuKiFpJ8PbSctutY/5i5aVmZCPA80ElwhIrqxLIqMlJZ6P3ELwq76IlBgA9iq140f8qOBQrCgqB10SPXzbBZXg0zU4eQFaTXCefLq/kyEJXVz6VOpAXrEoTma5bXJaz35cvOdXVWx2Eci3JRnbKL8oP8mGFjdc3XmzhFdWLAxBqLXiCtUz7sUg8zDmVneQqrLhZKLCkAKwAWlmwsZ6oL8ioqr8v1ojrly+5SJ6x39913Xwb+zXqY4TI9kSdkxumnTtQr34/Z6qHX0SVvOGPtAShimVMy62GGtbxYwgBZ9DVMMPV6yDoxkULOWl7Sdgmb5TXDrKTwzEPm9XzZWcKnj8lfz26UHx89KTjVe9s8Lu2xm88RAIT16QxhtmHYX3iSMNfyNF0u/JUwPfjWwgcJf0sY4nio8BbC9FwsJeZBmlwqJ1M55THTv21IAH0wc3PVC0CCpTvAB51a16ifNwmxWGHuV6IzY5Cu2qoB0IlcQlKZXlhCgbAu1SEAFjN9rGNVREfMoI/VJgQxQ6bcChJDpGmmgf6QD0uoVaTWWAZIVyrTi2satng8b7gVsBR/5ZVX9u69994MyKklwXZfjOuUEz2qDGOUwczTVy8AjSuuuCLbbgELtQmuzHRtYcAwkzFAZhMEyKFf0aXREHmYAMuWHhM79ZG0xfG57jqu+KTpGrctgEV5ThZmh7r/ED5L+HBhlgOPElYLlQR7fyPM9ZeErxH+M+EnhKFHhPGjul4YS9i/CX9O2IvUguV1U4rcmATQB5abQdELljWsF3QUvgTAGjFnj94KkCzbqgG5NQGwyvRCpwXXBT0ALHzOXAEy/mdYekIQnTfUFMCiTlik8FeqIvzcAI8mqK66p0wvVfe6/I9P3EsvvZT53R111FGZ9crlvrbjYCnEwoH1pwvkoxf6u2nTpmXg8Oijj85ArW8dqLv6MoVqG2YZdKsRdbo3/6sb5lkHWCIrG9Gn8H+o9lmWl60Moa63CbDwKsWm/YfC6wnfIgxdITwxCy39YUoM6GJq+z5hrFYmfUNO3iuMhWuq8FuWAOVaKTGDTdQdCaCPO+64I1t7706p6pcECxZ1KgNFttS5Jz/YArDKLFh0SHRaxAtJVXrBSlMXYPkCQgBW3bzyMmF5EArVgefT51wBVlXnDsDieXEFmqRdpRfi9EN8UxF/xo985COjb3n2k15T9wIwsK50BWC56kX9F7G+HXfccaNvDdaREy9T8ezgfxmacDRnsseLAKEIgMXEE1nZSCdALtZtWxrm9bK8zHhNhNsEWE2Uv1aaMU2GtQo84DehD96eHBS9YMGCGDx9CF8BBv88wKKTA2DZBmvACtTEEmGZXgA9/SwRuuyBpfLrJy9NQ48KsEJ14JqueQRgYVXAUlFGDLYALB9qur0AnFmyV/84n7K1HRf/IIBATD8brbOLXtjTDgdunj0+XaV9habhe6RdAIb1zWXf+8viI9eQy4PkBcCC1A8rO8n9aPsMNQGKOa4MJcCqs3STewbSaUAJoA8AxKDohc4T3whfgIUjOyAqD7CwTDEL05ldXvRq3QptwarSS12rEpYogJkPIKybV15WnNOB49elfmRFcfq9xtusUNkyIQ7OgGMf/yvSrNILcYaFAFjIkTfTYlOVXviEEn5t+I5Nlbc0QwEItmahPbHtQSgiPfqv0ACLdgyVWaO1nws1AYo5rgwlwOrCbCdUQxiEdNAHM7BB0ov6YfnoB/8rqMgHi+sKpAibxCCNGT/0TK1KLwCUOhYsfYPQ14JV1imb8qgKA7AY3HyW5arSzP9P+nCZozt+egBqXwtWlV7yZRnkc8ApzyF7d8WmMr3QTti7jW1GeFuQFzxCERMr0v3BD34QbJKqH44PDbB0uZHJpI1on+jUfMvQFtflesxxZSgBVuiByEXJKY5dAuiDTVUHSS9YZ3x9sDS+vtqvElPAVQawfKxBmm7VsUovda1KuqTpY3Grm1dRHZkhh7IeFKWv19QPS8/zR5YHAXm+y0RVesnnM8jnvPU4QTZW7oIfVple5s6dm1mhdZf30DphE2j6BzYzDkEsD9JG8tb0ftMmTZ75sqXz0O0z5rgylAArpsmw3wd0EO9HH3XfuuuqPOiY1CLlWkbiM8PLz9xw5uW6DWBx3QesuJanSi8sg9Z5ewkLFvLx6fgAWFgBQrRdZsihlh/KZKkAy+Y7xxIMwNhHDuRXpZeyMg3ifywTYiks8+tpo942vaBnLPRsJNsUsOeNSt72u+uuu4JUVf2vQlt5AcTIoMyCBcAK2T5D9Bl1hZoAVl3JpfuCSYAGwA7tMRtCsMqMJIQVig6fz6W4EgDLNmMEQKmFy0yPwRuLUBMWrCq90AnSGfrqjfL6LA9SX/XdqLMkacqLsC4R5q+HPgdg8QzYgDEDr6//FWWs0kvoenQ9PXyakAmgICYV6YX2yWattF98pZokrFgs7ZUtS7vkz4a+bNMRcnsGM18mi2UWrNDt07d/Msvab3goARYWgUTdkQD64FuHg6QXBUo+Vizi6nJgXjv6JmH+Oh0VDvBNAKwqvehs3NeKhQXLt7wKsEL4YYXuwPM60XMAFlTk6M7AW+cNQtKr0gtxhokALwzasZcJi/TC9wSflV3xWRrMW6ZD64hvn1IG9Z+qmz4vDABKQvtfaXmYfJYBrNAWLGQSi4YSYMVEtLEU3eV80QezrkHSSx2AVbQHluqNQQRLSH65Sa0jvoBF0y07VulFARaAxZVwOKWedS1Y/QIs3jjDqqhldy13nXiAQoBxkUUBMI2loK4Fa9DaSx356j0sY2HFig2w8u0F/fLpHHZo52PJTRPLb7Qr/UxX3fywBOJk3tQ2HYBh2xIh/Rv9SVoirKu9Dtw3SAN5B8TZdxHQB1+THyS94J/EzMnVgsXAjyVIgVleqAAslpvyAIPlNgYY2335dHzOq/SiIMUHYAGuSNcXECJPKF9/n/oQl9kxpGXPThr8UT+sfBZYryDfNwi5p0ovxBk2wtGdJVefJfnQMsrr5c4778zaNB8Ub4sARfqWbt082cEd61Vo/ystjy4R5ieL/I/+mISFbJ/oJRYNpQUrpskwlqK7nC/6wAF0kPRC54Qp3DZTy+tDgZhtiVD3VVq8ePGYWwFY3NPE8kOVXrDQUE8fgKWdv68Fi2+YkVe/AEvLGnKGPEYhuRMAFv4s+U4egIX86pSjSi+5IgzFqQJ21/bWhFBMvdCecTjHL4rJUVtEu9LtP+rkibsBS4RN+V9RJvpF8ilqy+pnGnLCGHNcGUqAle/s6jyI6Z5wEkAfmKUHTS90EgqcqqSl8WwdC50SnR4vA5jEEqEOLub1EOEqvbAkAUBQ0OKSJ4DQ9SPPZnqAK5Yt8p0yZSyaCZv3mmEta8gZspl+PgwwZjBh0DNJHdyply9V6cU3vUGIT/uAYgIsUy9z5szJnteddtqpVfFiwcIK5OsXqYXEX5DntSn/K/LBggUV+WGpy0NIUIpeYlE8769YNZZ8Ywo8YrU7mzX6wKeEwYhBe1CITh/rhQsBsPQVZlv8jTfeONuskM5Tl8wALE35d7joBaCioMVWbvM6Fixm2XWABRYfc+AAWF1wwQXZkgif4MDKBTOoTZxoft70zRJQVma0xGuDsGABDLFmHHLIIaNZArDYHLIOueilTrrj+R6APu0nNsCiHwOg4Nx+8MEHB91Q1EU/6jeFH1Yd6ygTXSZAdXwDXcpHHBMMr7LKKmNuoz+jvcChKOZ4PzijmYc2YpoMPYo5NFHRx/bbbz9QS4Qoz8eCxWwOsFIGMPkIL8CET25AdByY1JuyYLnohTKrX1NWqIofOlDf5UFNEoBlbtOAUzOAbfLkydkS86RJk7LBreyTIZSVMtcBeFoOnyN7XOGD88gjj4w6YWNhAFDXHcRc9OJTxkGIiz7LnKfbqCN6YSsGrFdMFnke2ybcBehDdCneJ3+AIX0LlvKyfsgnzaK4TA5xabBZsEL3Z+glFg0lwIq5dX4sRXc5X/SBb9Gg6YWZGoDAZQNELCsM/GUEwFh77bVHlwkZpAFZoTskLYOLXnyXCOn465aX+ptLhA888EAG1vDfA6Cz1QeWK5Y5bMuGdOp1ZvYqkzrHTTbZJBu0Zs2alQFArFdQXYDlopc65Rzv99DeYlqw0MtNN92UOduzLUNbIN7UG8CF9uX7JiHtZcaMGdmeekxYmqQyMMwSYcjlQeoRc1wZSoBl63ybfKhS2nYJoA8sMYOmF/Wncun0GfjVN8EuqV5vo402yva5AVxhDYLqApayfPjPRS+AQtclQsARgLMfC5YCLNJ5/PHHe5tuuumYgYwlOZYRi2bH1Ikl2zpv7nFvXWJA2W+//bJnnKVCHNx1IKyTpote6qQ73u9pG2B9+9vf7p1zzjm9G2+8MbNO8tw9+OCDPZby2Vk9FrFM6Auwbr/99mzixrKmvlDTZPn1TcJ8HvRpoQFWzHElnu0sL9kWz2OaDFus5rjJCn1stdVW46a8rgVVgAUYqvreHCClKg75vv/978+WUnF2R26wCzBzLbMZz0UvACwGFmaJVW8yquWmLiA0LVi6839+GQaABWHFUl8PrROgDAvajjvuqJdaO6Jb3ihjIHvf+96X7TFUJS9b4Vz0Yrt3kK+jbzb1bIOwSvPdP3S5aNGi3r333pstq6HTPfbYo40iWPMAYN13333W//N/0Jb4VuKuu+5q9V3M39PvObqiXzSJ9gnX7R/MtMww7SUWDaUFK6bJMJaiu5wv+qCTGjS9AD7wZch3JEW6wOJStUTIfTigsnEhnaLO9ppainDRi5bZdD4vqh/7fPHJEKxXISxYWArWXXfdt8iM8rAEWLR7Oq+fQwyKMWiXXXbJygsIqLs8SLld9BKjfrHzZNBmotKGUzP+f+Rz0EEH9U499dTeRz/60WyZmomivoASSx60L9ojYKWKaBMsDWJ1a/ONxyJ/uaYs8jHHlbYAFuaJh4RfE/5X4TWEbbS2/DFPmLj3C28irHSGBH4tzG6ByhJMNN4l4NIZjLc6Anzo9KuWCJkNs+uzqyWKzhBr0FNPPRV8tpeXcZVeFGBVLRMCrvCvOOywwyotXfky6DkWLOQEeIJZHiwiljiK3t7kEyKkYdtrrCitkNdweN9nn32yJPtdpqzSS8hyj5e0aGssB1U9iyHqg88oS1k8S7RzLKf4LtWdPIQok6Zhvkmo12zHG264IQP7Bx544Jildlv8UNd1idAEw01s0RCqvHXTaQNgLSeFu1b4XGF2XLtTeLqwja6UP24RJu7FwtcJmza+y+T8HQZL0I/qmub9ckmxXSWAPjbbbLPaA69rPjHiubxJqAOCgpWqcuLozjYDALfQ/gpm3i560TJrHcz7NcwbdPfff38GLlyWQfW+/BFwBM2bNy8DSnx7rYh49RsAlve9YLaO9aopi19RWfLXKPPhhx9uBYf5+EXnLnopum/QrwGwoKoJTb9y4LniyxO0Q5O6oheW2HjGq/yweKOW/dm22Wab1t/gVjBsvoGMBQvrH1uuhCT0EovaAFiTpXJvCF8i/EvhzwtvIbymcJ7WlwsbCn9BmLgXCFPGoLu1xTQZSl0S5SSAPljyGkS9uFiw1CHb1YKFT4HuoRTaX8FUjYteAD0sg9oAFp3mzJkzsyUIQHQ/pAAL53Z8r2wdJ9YELDzm0iwzZfYoiul8rHXHj66ffbhc9KJ5DdNR20/TAIsXcni28gCrK3qhf2DiVQWw1F9twoQJrT8mqivt+ygAFqwm+rOY40obAAvA9LChQZb+fihctBMgcZ8UBpApPSIBM+4H5ZzXpx4QfnPnPjkpIKAw28YqZ+/Bq8A5FoXZD0SvE1Yzpi2Mf4nGIawzZw1zng9TVr1OmPuJo2HyKgtTPo1jq4d5nbipTu3riY5EB3pTH2ZYBwSsQa56YpkQYomiyWdP0+ZoPm8a5jqzTgCWWSfCLH1+97vfzXyi9LV17tM0bWHagcbRdkNd8T+DaDe8TcnRbEMaVkd3lgQh0mLJkOVFlg/NsmuY8pphzqF8nfQ6cc2wlpfrRWFbnbR+WnZbnSgL6RIfIp6Wl+tFYcqn1231MK8TN2adbPUwr5fVCWABcAUAmfUww6QFUdeisIuennjiiWxSATAx9aFh0jXDqgOzHma4rE5ado4adtETQEUBlq1OTz/9dLakSfsljuuzZ5bdFq6qk1ob0ZXqQ31Kbboxr9vqlK+H1inLJMJPGwCL5bz/ytWNc67nqSrud+SG9wu/R/hTwtOEtxa20aflj18YnHm5MgOGOGr44YcfznxauM7+Ovpldt4O0Y6aV6zVt4O3gXQzt9tuu210EOXr6Tqbnz17dvbZAh4MwhzZZJAwRDziQwzCpAORLulD5Ee+EOWgPBDlo5wQvjiUHxqPdVqwYEE2YPKR0UGpk+qJBo/DKUebnrgOeMBHx/XZo1M88cQTs5cDFMCFfvZYPiBtLEVlzx7/Y+rPP3u33npr5ivGBqnqdN5Pe7rjjjuyZ5wlQN6SsrUnZANYvfvuu7P4tKe5c+dmgyLWtvHenpA3PlwslULD0Edoe6rq9xi4iUObglzbk09fznOFJRRwYfblPO8Af/r12H05Flz9PJNtfGK3eeoRY3wCCPMcA/IgXAjQAZa3fvqIojGXvnc8Ez5VSyz8Obn+cWF8sEzCKrW/eWEk/AE53p+7foOc/1nump5+TQIsOdoob8F6r0RcIshegO2SJfJgZZwPi0JGrxMWNJ7Ft4VlZjwah7A0vCy+hjnPh4mg1wmTB3E0TF5lYcqucWz1MK8Tl3PIVg/zOmXRemvZuVfDWnaOGuZ/M+xaJwGdS6SBLRGLx8DUSXUjvhpLzjjjjOyZM/VhhsXRdMlXv/pVxJfVvyt6QtcCZLLnBl1qnSifGb7yyiuXTJ8+PYunZecoG2suOffcc4PViefj7LPPXiJvEL7lOUR25rN31VVXLZk2bRqXs+f4mmuuWXLRRRdlYS17WZ3MehSFSUOvE9a2YguHbE/kK5OSJbQbrd94r1NZPXz09K1vfWv0WSTN0HoivS984QtLZAI85nnj2RNQk/Vj6BoOVSfSQefm82aGi549+lP6HZ6RomdPluay/8U/crQe1MFsQ2aYPELXib5BAFEmJ5nIZeWRneQznRXVyWxbRXUiIa6b9SAsljHFJ6xktUqm83jdjKs2lZkiCZ9sJM5HhvAOXPq9D+MPCT4mvK4wwEiXCTeS8FnCRYS993eK/hi5Rhqazmg0kDOkx3zY3DfDJYzlQcknjCOixmdmDUMuYVvZbddd6mHG0XJRHp9wnTqRL9+eouxafj2Svy1sltcl7FMPs9516qS6VCd0LEHmG0ZmnbD+qE+CSz3MOE3XCWsQZD6TZtkJYy3CwpW/zgwaS4tZXpewrU5Y+U455ZS3OKlrfFNPLBNi4ZE+Nys7/ld8s9GshxnOlz2rtPzYrrvUw4yjZSRdn7BZJy2vDD6Zk7+mr9dJ2wzbym67rumRjkvYpx6kqfGL6sT/ZtltYVvZ9ToWLL6np+cu9TDjaBnN8pphXpSQQTx7lsx6aJh+jLJr/rZ6mNc1Lvm4hM3y2sK6DQhWIXPjUK2f+l+tueaaWXvS62ZdtU5cM8vrEnapB7rS1R71xWJp01Yn83pRec2ym2HqEYvaWCKcK5UDVB0nDHD6rPAC4WeE8/SEXGD97i+FiXuCMOhz6dpAr3eghHlVhHLvJnyU8ExhLzKV73VjityIBNAHjr+DqBeAEw1cl/GKBEgno2/jFf0f65qrXii7+TYQ5QXYALD6eWuwqN6unSUACx8wHGdZouUYa/+ronr0c81VL/3kMV7vZdBWn8Ym6sD2DLxsoQDGzKNLetHJnPphmeUkDMBiOwedQOX/b+OcvlF1hf8VpBPSkPnHHFfaAFhYkFj6O1WYrVt3Fj5aWIllPljpSAnsJUzcPxXGkX2px3evx38AM/yqzhEGgN0l7EViXvWKnyI3KwH0MX/+/MwXoNmc2k+d2Z7ZkRSVgNlbFwGWq14oOyAGy4oSgAs/kH73e9L0fI/q6I7vl24w2oU3CH3rURTfVS9F9w76NQAWwBpf1yYInyHeHiwC+l3SCxYetogpA1g46cckdKWWKwAW/YhpmQpVNvQSi0IsEbqUfb5EmmSJeFLu+mI53yF3TU+P0EA/x6LG0U966d7+JIA+dMO+/lLq5t1le2GJj0AGTnSJsEs1cNWLfjwZUEWnCelncUJbsFzlw1INzxQAixksnbeWzTWNrsZz1UtXy99kuVTHDNz9bIVRVEYmEbxQwL5RRdQ1vWChUud9s7zIBovu7rvvbl5uPUyfR5/BxKypLRqoFHqJRW1YsGLVzZpvTJOhtVBD/Af6wD9mUPUCwFJTeF7NdDAsp3XRguWqFy27+lNQR5YHmY0CcmIRViy1YGG9itnRhpSBq15C5jle0lKAZWtv/dSDzUWh/P5XmmbX9MIyYZEFS/2v1lhjDS16lKPqSgFfE8uDVCzmuDKUACumyTDKk9zxTNEHr84Pql7oSGw+WGoi76IFy1UvCrAAi0rqfxUT1ACwsDh0ZYNRlU2/R1e99JvPeLwfayrPXFMAC98rtdjm5dM1vWDBYp8peftuTFEBWFiWY/pfUSDt8+gDdQ+sMQUNdBJzXBlKgIVfTKLuSAB98KbLoOoFCxbWnaKGrlYfBSnd0crSN4dc9FK0mztLhLGWB1WGACwGF+Q+KA7u1G3Q24vqr84R2TBwhwZYLA+ywSiWdht1TS/6TcL8MiEAK7b1ChmqBYsJEO20iV3cySfmuDKUSCOmwFF4orESQB80+EHVi3Ykaq0ya881TNj6GRjzv9hhV71gMWBWr2ARvzKWJmIDLDYkhZCvhmPLNET+rnoJkdd4TIP2FhpgsYkoz/l2221nFUnX9KIAiw2AcUOAkAtWLbZniE1su4KfnC5ZJoAVWyOB8i+yJARKOiVTQwLog53rB1UvWLCgomVCQAnWq5hLaTaV+eiFOijAwtyP42qsNwi1Pnw0lk4bcGXuoaP/j9ejj17Gax37KXdogIUfHzvC77rrrqUToa7phed/22237fEFBNkMOGufCma6YMFCx+iKfcugpvw1Y44rbb1FmAmwKz+Dainpinx9y4E+cBwdVL2oBasMYPnKrI34PnoBYKkPFv5XUGyARRkYFPUbhpwPAvnoZRDq61sH2huf3QpBWH5uvPHGzBq75ZZblibZRb1MmTIls1Zdf/31vQsuuCADMbTLrljMWc7FnQCdNTUJijmupCXC0iaT/mxDAjQAF1+fNsrSRB4sUQFAipYtWCJUZ88m8u4nTR+9mBYsOkyWDLvQiU+cOLG37rp8HGJwyEcvg1Nr95owWNOuWKrul+RTMtk+anysvGqg7qpe1ltvvd7JJ5/cmyD7XmGN64r1Ct1o39fU8iB5VOmNOE3RUAKsmCbDphQ5ntNFH3yQdJD1YtsLS5cIu6g/H72YPlj6BmEX6zQIZfLRyyDU17cOACwsT2pR9b1f47Nh6Zw5c3p8rNzFZ6nLemGyc9hhh/WOOeaY3i677KJVjH5EV1BTWzSQdsxxZSgBVkxEi8ITjZUA+uAr9IOslyKAxSDQdQuWq16wYL322muZ71UCWGOf79Bnw9Be+pGZDtpFFmOfdPFdYkf4Pffc0+m2rusFP8+11lqrE5ZlFWiyYKkkBug4yAP5eFQT+uCNs0HWC34P7MlkzqaYIfN6MuCki+SjF60DOzLzllIX/K+6KNMQZfLRS4j8xlsaIQAWwOqee+7J3hrUl1Sq5JD0UiWht/6vumrSghVzXBlKC1Z+47W3qj1daVMC6OOmm256y4Z4bZah6bzYP4d66hsz5Kdv3eksruky+KbvoxcFWLrbdewtGnzrOp7i++hlPNUrVFl5ew7ux4LF1gZMhqoc280yJ72Y0nALs1fd5ptv3lt99dXdbqgRC73EoqEEWDG3zo+l6C7niz622mqrqJ80aFo+AA6A1JNPPjmaFcuDkIKT0T86EvDRi9YBgMVShO7B05GqDFQxfPQyUBX3qAyWkX4A1sKFCzOncJ/JT9KLh4JGovKG7wEHHBD8u5FmSdBLLBpKgBXTZBhL0V3OF31gIh5kvQA6eJtt8WK+Zb6U1IKl4ESvd+Xooxc+rkx89tlBl3yHMFEzEvDRSzMl6H6qACydwPiWlnb5zDPP9DbeeGOvW5NevMTVWmT0Eovi5RyrxpJvTJNhxGp3Nmv0MWvWrIHXCwALHyU24oQYAHi7p6n9X/pVuI9eAJAARZZVkv9Vv5Ivv99HL+UpDe6//ViwsF4xKG+wwQZeAkp68RJXa5HRSywaSoDV1QEt1kMQO1/0sdNOO3UWaISSD696Y65+6qmnsiQBWF21XlFAX71oXZL/VagnpjgdX70UpzLYV/sBWOx9xWQIq6wPJb34SKu9uOglFg0lwGK2nag7EkAf+DoMul7wN2CTP10mZCnCx8ejbY356iUBrHY05KuXdkrVrVwAWK+//nrvV7/6lVfB+DAyb/v6Lg+SSdKLl6hbixxzXBlKgBXTZNjaUzWOMkIfM2bMGPglQlTCzBg/JTp+AJaCki6qy1cvbDYKpSXCZrXpq5dmS9PN1AFYUNHnqcpKjPWKNxBpp76U9OIrsXbio5dYNJQAK6bJMJaiu5wv+thrr70GfokQHdBx8yFknGjHwxKhj17YL4jBqamPtnb5GW6zbMPUXurKVfeu8nmTkI1/AVj4XtV5SSPppa62mr0v5njfFsDaSkT4kPBrwv8qvIawjc6QPx4V5kNSU4Xz9Jdy4WfCLwv/f+G03idCGO8UsxG0KTu+ucVbdosWLeq9+uqrnV4iRC4+emHPoOOPP37gl3rbfF5sefnoxZbGIF/HMoyjuo8F60c/+lG2SW6d5UGVZdKLSiIdkUAbAGs5yeda4XOFVxK+U3i6sI14j/00YeLlaV+58DHhbYU3FN5H+DhhLzJ30/a6MUVuRALoY/bs2WN2OW8ko44kyqajjz7KHOLNj512pGhjiuGrF3zM3vWud41JI52El4CvXsKXoPsp4nfDMqEPwMJ6xTL3BPkoch1KeqkjtebvQS+xqA2ANVkq94bwJcK/FP688BbCawoXEeDrJmGsXXk6Ri5cKPxD4R8Lnyn8YWEvSrMML3E1Hhl97Lvvvl7WksYL1WAGLBOqX0CXfbCGTS8Nqjxo0kkvbuIs+v6n7U6WB5n0TJw4sfZ+fEkvNunGvY5eYlEbAAtL08NGBQFOAKSJxjXXYD6tRyrSwXq2gsHZR9/wgYE4FoVBvHqd8G9/y2rl0q9yF4UZLPU6YRorpGHO82H+1+uEuZ84GlbUzfWiMOXT67Z6mNeJ2+U6afkGqU7oskhPzJDVx4O3CLusJ77Jln8mi+qkddVnrMt10mfMbFvjrU68JFFUj/FcJ7PstrCPngBYfBdTn0nkRbpQPkw8lux5y1fjaJ9NfA1rn81Rw/yvYU13mPty5OGjJ+IjNxc9mboxw8gfsukp+zPCTxsAi1eLln4T5M0Kcr70laM3r7mE8mlVpfNpSfQXBr9IJpiCIb43BUMPP/zw6P5EDzzwQOaEzPV7772398ILLxDs3XXXXdkrvIRvv/32Hq/0QrfddtuoKfrmm28e/cYcy14MUDw8ugTGOWGIt8iID2HKJh2IdEkf4pVh8oUoB+WBcJKmnBD7KlF+aLzWCTnwmZVBqhP6KNITMyqW0vARedvb3tbZZw+fFJ5Jnt9BfvZseuJ6F9sT+rjllluGro/w1RMAi019aYNQWV/+9NNPZ3H4lJUuK/r25XPmzMn6c/Ic5r4cQRb1e1yP0Z5eeeUVso5CIRzE8ZXawVJ6lgPZtnon4UOMOCAcwM9M41o++H25cJXwN4w/cJT/a+HrR66x1Mhyos3xAwsWrIQF60V20+ZNJ0XMbP5ohunAWMPnOmEGQtgWBjUTlziEGUC5X8Nkzr1qqiSMBQPUrWHQOGXgOmGY+LYwcbmfOGbZbWHySXXqjp4AxQDKvffee4z+kp6WtqHUnlIfUdQH+vR7LPldd911vU996lPZRIa2ZevL58+fn4Gi008/PeuDU18+OOMTb2uPvFXK3h0YZVqjEACrqrBTJMJ5wrqxCNvjArpYIlw6tZBAARUBrCsl3kJhgBv0f4WPE96FEwdiufAXzFB0nxSHe1KUhiUAUNQ9oQCBibohgaSXbughX4qkl7xEis+ff/753rRp03onn3xy5cfHZ86c2XvxxRd7J510UnFiDleTXhyEFCEKW3XEAlhtLBHOFZkCqgBCWJM+K7xA2AaulpX/3iZM2cywnGZvH54ox7WE3yN8mvDlwl7ETCZRdySAPu64447MmtedUqWSJL108xlIenHTy8igOrrkV3YXy3r9vgGb9FIm4Xj/oZdYBIhpmt6QDD4gfKrwz4V3Fj5aWOlrEoCVLpbA68J7Cl80EuYeaJbwBcI4Ii0SZnnw68JepA7GXjelyI1JAH3st99+o47fjWWUEvaSQNKLl7hai5z04iZqtlxgqU99qsruwu+VPer6oaSXfqTX3L3oJRa19f7ifKngJEsl8zbZqRIPttEX5Q+4NrG2n6g7EkAfdILMOOkQE3VDAkkv3dBDvhRJL3mJFJ/Tl7jshcWLRzhC92vBSnop1kPsq+glFg3laKaO4LGEnvIdKwH0gZNp0stYucQ+S3qJrYHi/JNeiuVSdJVJW9XncvRt8H4BVtJLkQbiX4s5rrRlwYovZaMEMU2GRjFScEQC6GPKlClJHh2TQNJLxxSS2ou3QrBg/exnPyu9TwFWiCXC1I+VijrKnzHH+6G0YMU0GUZ5wjqeKfr46U9/OrrBX8eLOzTFS3rppqqTXtz1ggWrygcLgAUQ41NP/VDSSz/Sa+5e9BKLEsCKJfmU76gEaAALFy5MAGtUIt0IJL10Qw/5UiS95CViPwdgsUM7exLaKMQbhKSd9GKTcNzr6CUWDSXA0g0/Ywk95TtWAuhjt912G92Idey/6SyWBJJeYkm+PN+kl3L5mP8CsKAyK1aINwjJI+kFKXSP0EssGkqAFRPRxlJ0l/NFH3yWJemlW1pKeumWPrQ0SS8qiepjFcDCAZove/Tr4E5Jkl6q9REjRsxxJQGsGBpPeY6RAA2Az8bEbAhjCpROMgkkvXTzQUh6cdfL8ssvn239YnuTkI88I89QACv1Y+66aStmzHElnu2sLekW5BPTZFhQnKG/hD523nnnoZdD1wSQ9NI1jSwtT9KLu16q9sLSNwhDAKykF3e9tBkTvcSiZMGKJfmU76gEmGE899xzyYI1KpFuBJJeuqGHfCmSXvISKT8ve5MQgLXccsv12PW9X0p66VeCzdyPXmJRAlixJJ/yHZUADSD5YI2KozOBpJfOqGJMQZJexoij8qRsN3d9gzDER+aTXipVESUCeolFQwmwYpoMYym6y/mij+233z69RdgxJSW9dEwhI8VJevHTS5UFK8TyICVKevHTS1ux0UssGkqAFXPr/FiK7nK+6GPx4sXpUzkdU1LSS8cUMlKcpBc/vQCwivbCWrJkSS/UFg2UKOnFTy9txUYvsWgoARYNK1F3JIA+eJsn6aU7OqEkSS/d0oeWJulFJeF21K0a8m8SArr40HMoC1bSi5s+2o4Vc1wZSoAV02TY9sM1HvJDH1tttVVaIuyYspJeOqaQkeIkvfjpRQFWfrPRkG8QUqKkFz+9tBUbvcSioQRYMU2GsRTd5XzRx6JFi9ISYceUlPTSMYWMFCfpxU8vuhdWEcDCuX2llVbyS9ASO+nFIpjIl9FLLBpKgBVL2ClfuwRef/11+5/pn2gSSHqJJvrSjJNeSsUz5k/2wlphhRXe8rkcLFiAq2WWWWZM/H5Okl76kd7g3RvPdhZRliEbVMRqDEzW6GOzzTYbmPoMSkWSXrqpyaQXf70UvUmoWzT4p1Z8R9JLsVxiX0UvsagtC9ZWUsGHhF8T/lfhNYRtdIb88agwm1dMFTZpqpz8RvgVg1eXsBfFNBl6FXRIIqOPhQsXpiXCjuk76aVjChkpTtKLv16KAFbINwgpUdKLv17auAO9xKI2ANZyUrlrhc8VZrH7TuHpwjZaLH+cJky8IporF9l2V/n5okjpWpJAkkCSQJJAkgASAGDpW4S8VfbMM89kS4ah3iBMUk4SKJJAG0uEkyXjN4QvGSnA5+X4ceE1hZ8ZuWYeFHwRpxGKaTJspELjPFH0sdFGG43zWgxe8ZNeuqnTpBd/vQCwXnnlld6TTz7ZmzdvXu/555/vrbLKKr311lvPPzHLHUkvFsFEvoxeYlEbAGtDqdzDRgVZJvyh8EThIoBlRC0MbitX/0P4J8JfEf6asI2wnsFKyxNg7R1S0yEKMMO/+c1verxdwnXCOEnCtvCvf/3rLC5xCPNaKPdrmLy4V18XJbzssstm+wxpmO38KQPXCcPEt4WJy0yMOGbZbWHy6WqdkBNvEW6wwQaZnAehTqq/8awn9MLS7aRJk7JnZxDqNAjtiX7mkUceydoL39EbhDq10e+x59W0adMyYLXvvvv21llnnazvfPnll0f7eJ55+v06ffkbb7zRe+KJJ3obbsiQ1xvKvryLfQR7LMaiNgAWS3n/lasg51z3Jfy3MHWwLIhf13XCPxO+RriIPi0X/zb/x1prrZW/lM6TBJIEkgSSBJIEkgQGVwIrSdXyWKTR2oYAWHdKCXewlJLlQMxFK+T+5xxHdV8yLV73yM1fET5E2Aawvij/nSWstLwEXhReTfi/9WI6RpdA0kt0FRQWIOmlUCzRLya9RFdBYQGSXgrFEv2i6uXltksSAmDtWFHoKfL/yUacP5Dw2sK8Kdgv8abh75Qkgu8XnCfAVatINl+AdF4ogaSXQrFEv5j0El0FhQVIeikUS/SLSS/RVdCNArTxFuFcqSqg6jhh/KE+K7xA2LRGyekoLSuhtwlTNjNMhL2F301AaHPhvxC+npNESQJJAkkCSQJJAkkCSQLDJgH8pR4WZrvu24XXEFbCSd10VP+GnC/J8WQ5h84U/qnwq8JPCv+5sA+xNEnaHBN1RwJJL93RhVmSpBdTGt0JJ710RxdmSZJeTGl0J5z00pIusKCdIcwxUXckkPTSHV2YJUl6MaXRnXDSS3d0YZYk6cWURnfCSS/d0UUqSZJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQAclULZ3YweLOzRFCq6XeF9B7IbONpZi7CbMtg8/70aRUilEAkkv3XwMkl66qZdJUiw2fGYLG7bCSdQtCTBwbyN8lPAGwvcLJ4ovgaSXBnXwT5L2C8LzhO8QrtqRXqIkakECSS8tCLlGFkkvNYTWwi0XSx4/Er5HeLbwROFE3ZLAFCnOg8IzhOcKnyX8R8KJ4kog6cVT/uz8vrXwp4TPF2bWwI7wecJqBbBi5gddIny58LqcJGpUAmdK6v8ovGJBLkkvBUJp+BIfXT9WmA+nM0jzhYQ8Jb3kJdL8+TqSxenCVwh/WPgPhfN0jFy4VXiVkT9ukONXhf945DwdmpMAqz+7C/+zMHri6yN50iWnR+SPvxj5cz05Pi6MNStReAm8S5I8SPhzwicIgwny1Jpefjef8zg/R6AXCm8m/Jrwl4X/VFiJRgEBvH4m/CgnQucJ813GXTlJ1JgEtpeUjxYG2L53JBcedlMvLHPY9KINY+TWdOhDAirLIySNI4XvEqYdvCysZOoltReVSvPH90gWnxfeQ5gvYJws/NfCSvRV0JbC6OUlToTOEebebTlJFEQCANsdhCcLmyBqfzlHRysJ7yWM7CcIQ9q2+GrIesLPCS8WhvgCyS3CB3OSqLYETL38wUgquDAw/tNWmGQcKnyW8GrCUOt6GTSA9UMR4seFGTQ+KYxJlgf594VN+k85WVP4f0YuPi/HHwlvOnKeDmEloM/ZVpIsHQ3yVoBFTnREEHpZS9imF20gxE3UnwSQ+UbCBwp/RpiZ+DeFnxVWMvWS2otKpfkj/dc6wszE/0mYQYO+aQ1hSNsH4Mq0Vj0l5z8XniicqH8JrC9JfEv4duF/EKZvUgL0ApQ+IvznwgziWBqh3xXWvmoFCTPZX05Yaa4EaE9/pBfS0UsCeb2sPXL32+V4uTDjDIaVM4RXFd5dGEInreqFB2GQ6PtSmbnCCqgWSHg94V8JU1ftmJhFaGclwd5/C/9UmNlIovAS+K0kuZYwAzodFXJmpq3E/1CVXjTe0tjpt18JMIgDdH8ifJXwxcJYd5VU3lV60fjpGEYCz0kygFu1mPyHhOmvuM4AwX/Qs8LvJjBCAK5XhN+pF9KxLwkAVllyPVb4h8K6FDtJwr8Qvk8YekJ4jvAhnAipfgijE8gcWx6U89WFi5aviJuoXAJ5vfyfkejoA6OKyv8FCf9aWPsxrut/rehl0ACWyC/rgABU0EeFmYFAKmTCPODLC+sgjxKWEUZxam6UYKKAEnivpEWncrMwD/nKwpA+8ISTXpBCe0Qns7Yw1l4GEIDUNcLbC5uU9GJKo/kwlpGrhb8pfJkwyxx/LwyZ7WWRnNOu1DryuoTfLvyqcBq8RQh9EpNu+qu7hAG7qwpDvxReUfg3nIzQrXJcV5gxlbFG9fSShP9deANhiP9fFP4j4V8JJ/KXQF4vCnxVH0xCIIwr9GXf5kRIdUK4Fb0MIsBSITKbYPA4B2mOEPWFXxZ+VPhPhFUZUyT8jDCdVKLwEgDs/j9hOp9nhd8hTCcFoQMALnp5TBi9KO0tAQb/pBeVSLjja5IUAzKz8c8K/7PwtcJHCq8gDP2ecGovmSha+8EKRf9EG0H25wr/rfABwtpfcWTGzqDyAWGlbSTwb8JMGhP1JwEdSxjQAVXvGUnuBTkCYLX/4vLTwkzOAU4Q/RljDSDqduGdhQFg9H/7C6M72l4ifwnk9aKTdU2J/9HF342wCWQVA7SiFzrPQSQawmeEcdr9iVFBHm6lf5LAicI0EoTNf8xCEoWXwDslyU2EAbH7CDMgrCq8h/Axws8I/48w9I/CqhcGCa7/i3Ci8BL4oSTJ8vhcI+kHJLyLMBbe/xLWWWFqLyKMFumrktcZwl8fyZNBhLbzA+F/F2YQgZhA0l7o894l/JzwncKJwkmAdvBzYeSLJet1YUDWBsJ/KMxEBcBFP0a/BijW/kyC2fL7MXKkb0M/uwvTngDCAGXVpQQTeUhA9fJuuef3hRnHlT4pASaO1+qFkaOJAa6Sa43qBZQ9SMTDCn1G+GnhL3EyQsvJcU/hDYVZM39EeLHwocIThOmomGkkCi8BljF2Ft5MmNk5HQsP/z8IM6AzM19f+EnhpBcRQkv0huSzjTAz6xuFGRQ+JkxndaXwXsKpvYgQWibkj5WDwfgHI3kfJkesI9cL7ya8mvCzwncLA7imCq8kfKbwAuFEYSSgYwp9F+DpQWHAFtan/YSfF2asOVyYfg79ALAAUVx7SvhV4VnCTFrWFv6G8AxhJpCJ6kkgr5f7JRnGFGgj4Y8KHy+M9RFaRhggm/SCNPqgKXIvD+5twtcIM0OfLcyD/QnhDwsnalcCNAYecCUG9ZuFGcB/T/hTwswkErUvAXTxTeGZwnOEmWRsLswgn/QiQohEfyH5Aq6+JkxbuU94R2FA1t8LHyCcqHkJ6ECOvNHFe0ey/F05niP8L8LThJkYHiustKsEpgpj4UoUXgJ5vQB+IcaTW4SfFT5PeIEwIBiwBe0uPFW4Fb1oISW/gaGDpCZ0QAwWWKjuEX5I+LfCieJKgE4JPfBwv1P4R8KJ4kuApQ8A7uvCdE60m0RxJbCMZL+jMJasp4QZyDkmal8CgNpPCzM5pw9jBeRE4SeFPyS8hfCtwujol8KJ2pGAqReA1XzhK4QPFeb8MWEmJvcKA7LAO0uEW6NBBFitCS9llCSQJJAkkCQw0BLAknup8LbCLPMtFGbAflg4UTwJ5PXyqBQFiy/6SZQkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkkCSQJJAkMNQS+F990GWA+aYZZQAAAABJRU5ErkJggg==\" width=\"600\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# customized plot\n",
"fig = custom_plot(stream,zoomarea=[1.8,2.8])\n",
"# save in pdf\n",
"fig.savefig(\"material/fig1.pdf\", bbox_inches='tight') \n",
"\n",
"# customized plot\n",
"fig = custom_plot(zoomedstream)\n",
"# save in pdf\n",
"fig.savefig(\"material/fig2.pdf\", bbox_inches='tight') "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# A soft plot"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def sticker(t,a,x=0,y=0,ha='left',va='bottom'):\n",
" \n",
" o = list()\n",
" colorin=['None','None']\n",
" for i,c in enumerate(['w','k']):\n",
" o.append( a.text(x,y,t,\n",
" fontweight='bold',\n",
" zorder=999,# alpha=0.4,\n",
" color=colorin[i],\n",
" ha=ha,va=va,\n",
" fontsize='large',\n",
" transform=a.transAxes,\n",
" path_effects=[matplotlib.patheffects.withStroke(linewidth=1.5-i, foreground=c)]))\n",
" \n",
" return o\n",
"\n",
"def soft_plot(stream,\n",
" zoomarea=None,\n",
" figsize=[6,max([6,len(stream)*1])] ):\n",
" \n",
" # make a figure so the plot is interactive\n",
" fig = matplotlib.pyplot.figure(figsize=figsize)\n",
"\n",
" # default obspy stream plot\n",
" fig = stream.plot(fig=fig,**specs)\n",
" for i,a in enumerate(reversed(fig.axes)): \n",
" # adjust Y range\n",
" a.autoscale(enable=True, axis='y', tight=True) \n",
" \n",
" if zoomarea:\n",
" # add rectangle for next zoomed plot\n",
" a.fill([date2num(obspy.UTCDateTime(min(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(min(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(max(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(max(zoomarea)).datetime),\n",
" date2num(obspy.UTCDateTime(min(zoomarea)).datetime)],\n",
" [min(a.get_ylim())*.99,\n",
" max(a.get_ylim())*.99,\n",
" max(a.get_ylim())*.99,\n",
" min(a.get_ylim())*.99,\n",
" min(a.get_ylim())*.99],\n",
" facecolor='.9',zorder=-9)\n",
" # add grid\n",
" a.grid(linestyle='none')\n",
" # turn every element off the big axe so we don't see it\n",
" a.tick_params(labelcolor='none', top='off', bottom='off', left='off', right='off') \n",
" # turns frame off\n",
" a.set_frame_on(False)\n",
" # turns texts off\n",
" for t in a.texts:\n",
" t.remove()\n",
" \n",
" return fig"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
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BISAEKgTAtX8J12nKWVGCGQjMH/+fPfeqTQNnxgZ6bHS9EmoVq60L8K5yI/roh7fizV16tSkbWNYhnaK9vl6qPvfInQECnYtWuSrpp13aXr+mCFeo5Kup5padePhWuY/WMCxWgKYOlEdhJ+BjW2Q962DLZkQAkJACHQZAmkX+i6bXBMJASLgc5Cbbrop+sUvfhHZ29uzELIxFqGyNn4LMHrzzTeTYdZv5bPPPuv6TD9RzKlUoesiWLGpvHOLfdUSmJ94LtYlgoV1ZRIszJXnv+dKw6u21lbxp+EL1gRCQAh0DwR00eoex7GtV5FGYG6//fayNfkRLOs04mTtsLR+myMsQ/20ttlI6wtlsG/EKe/cSuurJiqVqTtx4sQtzzvvvG1Dv4K2mx8/oG2+Bt2umeZjml6jZY5g4dinbWc2em7ZFwJCQAjUjEDef7A1G9VAIdBoBIoSJSNHob610/ycNWtWiThPt0SxNCqVR1DYl0duArNlzUyCBdI0M9bOs+98w5vxK+qUzdzFAhCr1TH+eXh2sVeaTggIASFQGQERrMoYSaPBCBQlML4e608++WT04IMPOu/8vjR3jWhZmaZjsip+GseGJCX3CGNfMskLiQ2IUDImrmSSplARbds2S+kqF+Hh8P0g/ckYpCOPPJIPsZtvaaQlr6/ceB0keOHpGXgtxHXjxo17ITQHLO23ERXBCsFRWwgIgZZGIO0C29IOy7nuh0AlcpS14unTp2d1lcmNWNlcVpYpQpDXZ/ogLWnnjv+Qu+sn37IxXpk21uuuWD0B85fZhSzr237nwOIO+FHsgbFlNz9eP/HfIDdfTZuNRDGUA5cyWahTbZs2kSfBl+v8sVjLbvDtZMiMTHYWM9+86kJACAiBhiOgi1bDIdYElRAoQmhow9ebOXNmhLecJ6b9vkToVaw/LD2V6Omnn3ZN0/H7UuodobPSDvISIyHu3IKtiaUqrtWo8255ylwUuUg1Hv4v8w3+TQaZsVczUNeIW2+SnPPPP38jCpluvPHGqvzG+I8hu/d4dVgo/xv/XA87wmj6w/DtUshFsMphk0QICIE2QKCqC2YbrEcudmME8ohPXh8hCSNYaTDde++9TlzJVjz2nSk2yiJYKTokijzvjOyYStg2eT1K91b2gQMH2jZbeN6Hbc5J2T+XL1/e8bVLNF577bU0PepmpZvQ8UBWJ+XDhg3L8sneJO8IFnir6eWZU58QEAJCoGUQqPaC2TKOy5Hug0BBQpO7YCNQWUo2R1im6VeylTYmlpVFsNJ0sR22aYq8rgQL6/TtuejQsmXLjKSUnfeINIUyaycvOAXZMlmK+7WJYNMiV76/NObmAqB6Bqs2aDVKCAiBJiNQ9wtmk9ej6dsQASM9lVzP08vro10jTVbm6ef1VfDRJwl+PRzG3/YL++t6LmLrzf9pHSNWfW+44QbW0+ay57fMrzIdbMmanXA9NbexbWk2y+aLjWqLsGZ0NVAICIFmIpB1UWumT5pbCFSNQCVSFBKrPP28vgqOFdoihI3hKXbqei7269dvA28OixL997Rp08q+vkg9bB8O8PS5jWlEyxc7HxHtWg95P7+j1vqAAQOMYKXNV6tZjRMCQkAINB2Bul7Um74aOdCWCBQlNHl6RqCyALCxVmbp8cH58D1YWbopcn+LsFrCUNdzET8XNNjzzwjWhzxZSRXbhyUEC51p/vDB95Ho+x7yvajbtxJLbFXTwPEw31LxQn/y0H01dqUrBISAEGg2AnZxa7Yfmr8HI7DuHlo7CEUJlunZ+7PCGX/961+HomraRSNYtBkSijRCU83cJbp9+vTpx28A4hmnX6HDnvla9yONJdquYVuE1pPmz+fQeTnyTCrFUa9lrNea8NNGFsFKm4+/nt2Hnw+Wtc6hcUJACAiBZiCQelFrhiOaUwhUQiCPiOX10a4RK9N74YUXKk1XUz9DWPHAas+tavVz/cM6+4O8fAJKH0TeJFZekTUIhKxIBOuAeLyLXCHq9bMse1XI7Z88w61kKNbh/EJp3yos6VdDCAgBIdCqCNT1ot6qi5RfrY2AkZ5KXubp5fXRbkiwKs1Vh/5qz61q9UtcxPpLCArWS0ISPm+VSbDwzUZGp5jMTpo/RobswfNDO4bU/hdvtbfIlM0bGrNtSJs77FdbCAgBIdCSCKRdRFvSUTnVfRGoRI6KrLySjZdeesmZqaRXZK4cnWq2CEMznToXvRd2Orv46Zk0ghUSLt+H8X4D9TR/jAzZc1HBkOwmntcaBh/PCIkg2kac0ubj1qBF1kwve5KUHsz54Xo9kJ9iXiIhIASEQCYCqRe1TG11CIEmItAZcvSPf/zDed4ZGwWWzh1Ci8RYmTUs7O/Uuei9sNPm4zNVIaHKncMnP1hG2pZcGcmZMGHCjjahlTGZ+rC14/JS2J80ceLEUejfyvoQOTPSZqKSEmPcs2EZ/iS68GNP5PckgriC8Xeiem8oV1sICAEh0GgEyi6YjZ5Q9oVAiABugqEotV1UL3VwLKyHjRz71USwQoIVtnOmKe/yXtjpOrlFCFISEqzc853kB4O/QgPAKY9gbegmwR/M8ySKXiBNJG+T8CzXFSBNP8J4PvvlJzcGfYyUfW7SpEnDv/Wtb72K+r6+Ukq9UAQLfjwaj+0UjinzN1wE7IZiks+cffbZP8IxK3YyNNwrTSAEhEBnEci94HbWuMYLgSIINJj0lLnwyiuvlMnqJODNfbfYVm60KGW+3EhOin6JyHthp8nvSsE11yeQn31sMMrwW4XssutFGQnAe7c2w6shToON/aHnv4OL45jsxaduDjyAvyWIxWuQ/9T1rvsNxLiZFPaQe1/o9x88eHC/JUuWfA5r49bfIYlWXPn2t79NP96PJgnX4rC/2vZ55523PdbEH50+EfOFhLVac1n630DHmdjOfBhlR6g1S7NKOXzeH8+5/eess856ORw6efLkAfj5o31B7O4K+9QWAkKg8wjYBbPzlmRBCDQYgRTCUNOMt912W03jCgwiSfp4rJdLZqDDqIWfOht5KXIu55I4RE8GeBjzdQxhsjkeRMcBficiSEPiNolUGQGDzB5Wt3U+ANnG8RhXXHHFFf3mz58/FOTLl+8Z6zCidh+I5F7+mLAOcjXHk6X54XVXroJc3QitXZEXIZ9eeURxDZCf0dD+ArJ7fQbw36z46MKad69atepFaCfbsjYS73w7D/VTQUo3P/PMM+v6XwfWdhls90F5os0XlujjC3dPQz4V9TVhv9pCoN0RsAtmu69D/rcxAt5NPXcVRfVyjXRdpxGJojNWq19it3///n1ATEpkKY1c0gd8bTsuZagT2fWCZKckYawRLN4oS9aCm+eHILOImPWRcJk9Z2v27NmMOJmek+HPu+MKdXPJlQ3wSpsrEcEXvih1L5S3JsL8yvpx9/vy1Wrq/U886gdxGa69kNELLrhgQ2wR74FI1N0ZA7b05Vj7J/AliNkgxcSC27xcY10JFuydRNtImQQLfecjH4tt5StRPoWsJAS6FQK5F9xutVItpmURaDPiVBTHas+tMjJQdCLqAcMSspIxtlIEq4w4BXZsfBkR8AjWaroTjPud1zYbEUihPx/HlNn1xvm6Tgyi8HfkLFLhDS2p8qH3W0okXgPr4PNkx1588cX2JnyLvO3FPlOlDrb0jrJ2J0uL2A2E3bOQ96/GHt5H9l349hduj/rj4N9n/bZXvxGk6n60HSPH2PW8vqQKP96G7EhYIqxvxX0WECUcjHm+Ff9OZn1nkDUh0EQEilyUm+iepu4JCOACX2iZRfUKGWu8UrUE6721uoSb0yHYBtqwwPhcn4BvGYkJbNr1Ik3Pj2DtEoxj0w5yshWEiFuanZShTmRz+/1jvcZy1CtF4Ki+Bf/wZn7kkUeSDLrfXQQZOXzEiBG/wYP+b4Hop9iK5LN0jL4kpA8670f7z8hMP+XnEdi/hvpvkbdAfRY7LKHNsZcjj0OUhoSt77hx41zUCmN7wZ6pDosrJHPnxfWEzJlSTrk7+0BU6HsSicIc/5szhl2OYIFspT0zx35GlYhRGvbsL0lYL8nYy4iOjYXNpI9bv4hObob+lxJhR8XW+DU0/3v69OkPoLw30FFTCLQtArkX3LZdlRxvKwR4oyqSiuoVsdUFOlnn1uwGzH1bgZspp02iRxk+JGQio3+jWJ6mZwQrrY/D7CCPim08hIevfYJl/XF3WVHpJr/ujl42NIpIoHCDZ6TG2cGPXiekAg+yj4H8JpCAb4OkGEbbA1MSgJmeuTQf+IA603dgfxIrKI9F5nq4pXkc8pmw+zzyM6i7dOONN/qfD/dTRpgvIYgYvxXtmL6VkH0I+TtskyRyexBVW7tF20w9KTHmObzG4p2JoKOyigWe/bJoXQS9O5ATP9FteHSMCP5C93yOoRh2dmUJcnUwS0vA9VLUXyTRgu5a5JviPsPAfXYwzj5frpvrg65bE0r+9uUFZjOrhM76zFn9PU0OLDZBnopM8l048bOPMd9EDp8VLWyjFRTh/8AwstuVfqVdMLpyfs0lBLorAnbzCNdnN8NQ3hXt3PMdN8h+uLDm+eGiP1BII1FGsBLiEhgKDfM3BnP9CcYzopSXLBqSqoO5bkYHfTC9r6M+jsq4sZMEMX0Q+ReuFkW7g5Rxi80esqfY/e4i5Ad7OG0b638qLr+F8uS4bjenhPjggr92zJgxfUHwfOLiR7DioRG3MneEPonLDNR34GscUP6OCvBhHmxsjerxyI9RhnV8Avr3IIK0LyJlf4MOxZZGof9EkKzJKE3mSqzFETuM3RyCj1KIsad6a3R6uFGNwJcIHoA/X4cvtzhh/OA/xiZrjOV+8RE2QLQ+GQs/Fpd2LDgv1zkI834S8/4H9v6B9fFYEFfq7ccM+SX4xmofPpQPYrwtSOun4cv5GEviNhw6FsEz2xB1PnF9yMtoCeUOKI7Cu+cm4YsCA9DmFyCShHZfREN7Yb2XQLgb2u9lJwnmvHnzNgGGB8Pnn9DnZFCdK5hzf9jfAljyc7Yz6oej/n0Se4vc2pTQ3Q/9W8Onn5sMx+HtqF+IvCXyV01ebQnbF2HMUSjt2lFmAn0jMf9nx48ffxHKemNyK/DmeV3Xz0PZIjIE1VzgMkxI3KoI4IPLm/xOKKd2tY+4kO+ME9rfwsl0AXqZfX7H1Kldvgx/+mrrWSd06d2tWqud0/dv6maJoO7CBo5DGnEyPb8s0cOx3h03bSNWJVEIf1BQ74ebYzURLEaD8lIW3v4YX+csdIzDufFNlCfGStwOY5SLiYSBN1I/HQP9Z4DT7Z5wE68eoZ8Ea6dYZlGDEvKBrbBdhgwZMn3RokU2tIyIoWPHuNNtRbKO7cvbsRXsxPBhUtzPwj5TJ7nGmjUP4wb5Xa/fqgtxnB62BkqHB25qjmChPdv6YJ83xpKEG9UsCtD3/1DcgrX6OkshJykkUUK15JxeSTnSqI7CkZQ9ULfPo+E0DOO+H+vQN5IrYjoylrF4GX70h2wffH544/8M1vprlIy6lX1GoEcbF4M8bAU9RvC+gWf/jsc72Oaj7hJ09gUhemTu3LmjYfMLEF4J2fS4O0J9GOrzMf6/4d8jqD/NPpCrA1HsjXe6bTJ69OiFRxxxxBroPATZO0GuqJIk2BgL2d9NgGN5N+puu9hkLCHfEgR5GbbPHwaOE+H31X4/7BDDRSjnUX7hhRdusHTpUmK1GJmf6R8i8/icy2MAGyfGx2IhfKNTmyH75wGa0b2xTkKwIDNuMIAKeQm+8FjOpE+Y48uwdRjqB8RjTk0by6gSPsufge6/0D8B5bsx9gqMI4kdinIO8oeAxWsgXo+gznsZ/eMxfi/yy1jbh4DPH1CP0E9/L0NU/BK8kmQGjsnGIOLLsNX/QfY3K4VAN8uPtp83/gDwv5wlXAzKO/DhuBgfjnttcZC5/2yOP/54d8FB+wODBg16BCfIZvhv6MUTTzxxOU8YnFwj8R+oO4ltrF/yPyHawPi34UP2XnzIrvD78eHaFDZeQx//C+WF+ATUX0P9Rsw3+LTTTnvD12edvqHgf4h/Cfvy2tDvj//IV6f8V0QcBh177LG8IEf4sEcLFy6Mhg61e0kUvfHGGxHfSQVfo/vvvz9vmu7UNwOL2bpJCyLI+wZzX4e2u5Gh5H/c3wj605ozIdwq6ODnjOQiK92HjvfEnfxsPIfz49O44T+ZNaCoHJ/tA/EZ+2NRfU+vD+okVZb+BlunwxbPAd6wrkR2pMUUUD6KPNZr51UNk9uhdIgpYo7/GThw4LU47xeZLC5/ivILgaxI829Q4o2nUroUCqd4SrNQJ3khGQvXmajB30OACdeQJBy7XXDspiaC0gqJ1zdjEYk3SckY5CnIxyG/huwT8eVo80b+J2R3Ywbh6Q9CQkKwMXJWIvk4Bvl1XId4U/486o6QoM4trr3RfgiZyf9sH4++KfjH4N1Y2zyQqoRMdaiCXQ8cOBQEYCiI8Bxct3YzYgr9k4AF8SpLwGQ/6P21rCOK/g+ybVLkFG2Ba+NakEZ+FkmUX6YwTvPgp9s+NgHaa1lHyfW9C9UH4j5GB69HLvkMwd/x8HcC5Ech/xKZ6YPIs+DvhvB3EOrEnWSMusT8KvTtiT5+rrieIzDXXOQDUSehuRD10+Nvr37ew+NO9H0EmYnnOq8TvN5F0Ke/PEfd8aUsJW0H2Q+RPxjru7WifT7yGcguwbe94Rv/UbgDZPlYzN8bx+pIlJMh48t6Z6B+AerXIH8e2c3PsqtTr66esNnz4cC9Dh+eRb4ceX9mHBD+RtpVqA9EZnoHZHwGgxdffmjD9Bf0XwNhb+icgzpPuluphPoXwaLvtP/22IcHXH+ND8BL7I/Tb1Ceg/wY8j+Q90C+EfkaZD4wy0R/fs4KfL4HeX9U72Y7Tv5F6uf4oJ0MokKitT+yXZR4wvZGtsQP7/9DPg35QvhmJ59d+KjH/4z6o+8wrOkw1L+MzJOfJyVPrgjrGY0P+Fj0j0DzMuSXkecgX4S8EBfHu3FtXIF6tN5660V4MWSEF0RG+G+Coujggw/mA7nRn//8Z0eunLDn/HkeSx3VpOU+hHn3Cea+Fu3PxDJ+3nmsK6W5UBheSSno/yva+8UyXsQ5D7N9VuOuphaMMExC5vbXUmSSCt64/EQ5b0pF0s+h9NkMxVowzDAV0e93ZHUWkP8bOjsW0CuqciMUj8hR5jVmk5z+ol0/g+LRsfIFuGbNxTWJJJLpceTdXC34A71PQe/rEBOzmchbBSp+cwka63mCC1Hn9ZNpFvJIV2vMHxJYft7eicxzhr5sh8x0B/JvkX/Ehpd4H+J12xL7T0Du7Oft+7DxFTMKkrMT7gGca7TJUsoXINs2lhf5jH0UulwTk39d6pCs+5v2+fklukki/cR7/YYU4P7ZFK7TlEl9BLq6DqCNFXf11JpPCBABkvu8i1IjUXoUxsPoS96FLMuX5MKVpZAi/xdku6bIW1W0HI4NaFXn5FenECBpKUqSOzVRCwyuRCBbwMWGucDtRhc0aRbB6t2wpcmwEBACaQgwqtis1C9l4vAfDv6XXClZpLeSnt/fTHL1mu9IwbrIVUGg6qz2VCftue2uCjZ6CrkiDHnRuQowFe5+vLBm1yrWcp2qq4c9mWCtRqj4G0Dz08iP+Kgi/Mn/8rdHvsyXB/VvB23XxNi9PPkUzHEc2i96Mm4Jfs9rW5XhVD99GI03MP505AOxBbiJ34n6+UF7cjA3uy8KdNg8I0VWIsJzB+thzi9CeKp1wPb+qHMrwtI7UNnTGiwx5iQU26G0LafooIMOSlS4TThq1Kho0003jXbeeedo7NgwmJKodudKqxGsWrAm+XiploFNGsP/ZP3EKGI7pFca5OSDsd3na7DPyF4j0zQYP9mbYFVc/70n86u2FpOVfS5xPeJ1vlKqRMJ/lWHgDxnyLhFjbf+Die6JJ+PWGbcVyzCI+4sU/lbxrJQBp6XInkmR2ZcIwn/gUlTLRIeWSdIFz8ViRiRbMvU4goWHyQeSQOHB7AF4OJzvrrkOeW+SCsj3wAf2E3gw/THInkU+BUftHp6gqHM7lfvDJELfQ5tvXO6F55FGof9IEKDhePbqLRhLEtIPtnuj/3iUP0G5FWzvBvnXUCcpOQUPmw/heGb6hHIU5Lvy4cpY/nuUQzD+QuQ/xd96+T50FsT930KdFyM+EzUKsq/Fc/OEvxaZe98/QGa6iL6h5BuTL4Av+9Ln2A7XtTsxQXkd8ohTTjllKeb8KfovYR90D+LD+mjvxblgaxvUH0UmWRwR+98LY4jL8yh/hdKtbeTIkdGBBx4Y4SH46Kijjoo+8IEPRIcffni0zz77RHvssUd0yCGHwESPSl1BsLIuOP0LIF30sYF/4XNxXAF79VapBb+FvhPw+7t+O67vniLjlzPSnrFZkKabITOCkNGdKy4STQwNFBkzJx60KByMtrumoCQpTYviLU4Zc2GKrFbRPBwf//NrZCGLAD0dTOSv6QL24Xkru8nbDZliPv+X/JOMa1byLCDmP5EKfsLngM9sWVqByhvIvNbaP+c/jDtnxKUVX4O9s+LGkyaMy6t5nYzvHdt4fcfwOov2VciHe/IJqPMfb0tr4PcVsD8xFvC9YbuiPcUU4jL8553iVDwx3o4/dW7nH6SrOwr3LBP/aec9jJ8Dw/Ni60d5Anwir9grln0G5XnIv4rX9M5YzoJ2LP0YlcuRvw0fbscaPm8dcXl80GaT9+cHMN9g3oNQT7DC/exdVIhTWuTe+hpaFr2YNtQJGa8dAX7rMO1bgWYRH1a+aI7/2TQlzZo1yy5uqfPjm1TRz3/+89S+birkRXanBq+N/z1unDLHTMi2CuS/RNt/OJQ3t0GBTlrzFlwEf457181pnQ2U8cK+fpX2vwP9r9sY/IOwFb50QiyShHOE/xC8CYH/QHM0YMCAYfidvycg3yJR7ohuk7S96slYfS/yvYGM594myK8gbxb0pTV5M3sG+XzkZ5FHI1eTuNaPI2+TM+hH6DsB+T7k9wR6d6L9EeSbgcfH8dX5r+IYT/Z0/DH22TkG/clN2NP9GeqTkEMS5Km4b2p+0ROQLFyI/EYsexAlb5aXIvOGuhI5uWHiM3gW/OOYWcgjkS+D7BHI/on6WORf8maN43griMwKvBqD/m+EtW136aWXDkKb4+yfWhKaQbhh89UPd2PcL2HnCBCDE/ClnBnoI+H4MPLRyL9AZtT+UOjcjPKLKAdDRBujkTn/U8j8x5o3/9eRv4p8ObJL/MxZnSXm/CxsfBFVfovORV1RkqxcCIJ3Kd79NZt68bfEicEw9D+Jb0PyG3+Pos1/5o9D3hf1++ATX4PwCOpMJEP+/ANgc2PahP6ouD9CnefBWrTpL4/pSchc8++QJ6JvHErqMYCwhnUm1L+HgsT0s6g7bFAycODWQR1LkI1BfQeUtyLzmJ2NAMdJ/MfedFgCD375jJ+f+dDjfewbOBa34Fi8H7LFaF9LPUvQ7YUxJGfXoH4L5KuRX4He5qbT1WXfrp5Q89UXgTxyxZnw4eIFvmUT/tNoWd8a5FhyUWqQfZpdgrxxiv3kxuT1rYovxCUXK68/q8obXa3RmT0x9rEMw7+G/BMpff8H2TbIXNv6yGUJ6+BXtnmDY7oM+WTk65EnIH8dmekFkKuSCzlkLtKLG/BW+CZuyfkCcrUcUeUd8Xt/JFSW3HuIcG5RNtSEIG60zeZy5AXII5B5AyfBWoy8GTJ/g3E45pnLeko6DjLedEiwNvD670edN04/HYrGw8iv+ELgwPcKGQ5+l9XnxJVF0P0QdH9vHSiJ747I/4fMNLOj6PiL8/U03MwfjGWPoiQ5nxq3WfwE+UvI2wOfZylA2QcFb3ZMBKhvfKzuQn0Y8heRLb0Kfd48/wzBB5ANp7+j/mncYP8Zv1aBJIAv3HoBJXFYD/lXyP1BkHjMOS99P3nzzTe/1l6Ng1fc7MM+Jt7QobMlqluxjfqxcclif/5B4nosfcQqVuJt87fjhajHb7TRRr/ga3Zi+eOwRaK2HOuknyvQ7oNdk17QdQQL8m+aDSuh/3PUmZOEcbxenJoIUMFuhhF7frYiHJO5OCYke8Qowpj7J0+ePNDzh+/XegveD/Uy+q6ByuYoV6B0hA3155F/g/bByEwXwuZtKBfD7jEoH0Z/CRlEm375ydmCD/wnxSXolJErdkA+DQUz61zD8ayHCcfW2YQvPL7UvSTWeS7UZTvG2tZA/YkQ35Km21Wy3l01keYRAmkI4IKZJu7OsvDC1Ii1hgTC5kgjWNxCecoUUJZcSD15WF2BcSRZVSdc+P6BQe6imTKYN/gwvYqL51WxMK3f9P0LOm/kvOg+gPkWocobBrfTP4iixAb6v8I+/+WTbMdpxemnn/66NeLSJ1tJl0fcZiM6sHvcwS2vU1D/lCnGN8ibrO2XuMmuRn4RMhLCPZBJoJhI0Jh+3VFEs0D87sV//m/E7ZficiHGM/JwJ9u4Oe0by/1ii7jBV9GQ5PhpNfCYhlyCkSngUYGHUL+XbWD5O0b4oMvj6RLmPh5tRkGeNRnq/mf+n5TDL960Z4KUzje9uDRCZfemabGcpPY6vh8QeP43xr8vlv8D8ttRn8k2+hKyCfky5O8auWI/634b/SRzNgdVqkp8/x/GT/HJDA1Atgy+kFy5hPYa712BdwGni62vsyWI04vAcRscmyvNVugPyRX74AfXmxwb00d5GLK7PqD/dB5n5CdQZ3Qv9fPujeXx5OeC5VRf3pk6MPoZMPwv+PFALXbg9zjk5LNZi43OjunbWQMaLwQ6gwBOyM4Mr2nsxhtvHM2fH17XazJVyyD/ZlPL+CJjUm+OGMhISlqqxaeVuPitxA2a9vif+wDkVciFrim48N2ODPWyZFEAv2O1R+ay1kai6BNL+sLE/9SZFnUUUW9cuJdiKyFuumeNrF5WwkezY318zsXhhc/uf2HODyBfFHeab0v5Uy6Y45vA6E7cIP7N/ni9N8S6IWlzYujbTfnSeMzJKHnzehL5Q+ifCv+PYJ8l2N0HvixHtIE3kz9SjvZEtLl19BiaJJ7cptoT+UvIlyEzUnYqxq6K/ULTpdeswhJrWx23r+Ja4vqPUY7Fl1Zmhts6nv+xalI8g9oOyAsoATlzRIrkgL8FiagUoxMfgd8WnfgZ2v8FojoZxJVk/s8cx4T1/7KjVvLPAN98ftIGG2wwJe5r1WJ3EOMX6u0ccJyBXLNZfAb4ma7lOuDmxGf8XtjoAwJcs43Q+fizdHcob6d2oYthOy1IvrYXArigdrnDzZjTW2TdLkCezbC6WyjIafcCHmtxIzaVXlapUC7GTc8iWNwWIMFiNGWjeNzWuEDy98++G7fzCl5ELSJhBMPX5zd+jcwZibH+36LyUTagw59rMblVHMFC3+/Q91msldti/N26d0Dxa8i32YAiZXwjcqq4qTAa80/IjGBZBO0JKoAIhFEKP1zriIYzlPMHth/Gz4psjhcXkxx9A2soOz7UoQmUCfmDbyRlm1MOovctjLsI/SRgJ1CGVGYHuByHm/91Hd0df/HS4D/Mnj17AsjURaeeeiqPM+e5DvauJ46e7tGoz/HaYXVPbI0OAJEagnz8GWecsQCRPKeDm/JTsPkWNkConmWJ9v+iYGY6t6PI/gt9foC/l63RGj3w8/HW8KT+XsTHoP6G29iiCFYbHzy5XhsCW2yxRfTqq6/WNrjzoxIm03lThS2QlKyXoc0bbS0+Dce4VbFNbl8NQ+YN2AjWHNyA/4EbcaxS+hMeJozLmV67v1e36irYMTI324RxyUjMy6wjKjItfgaKTUcgbBzIzq9wA/gtIksukoX6o9D5LBWDdBpI2F0gnHwW5u1BX1bzo1jrRphjDey+B0qpN1H/BgT9qR42WXadnNEw/CzJA3gO7HFsBf0sS9m37+vAL0asmPPSKuj9JFSIt9PODuUBuYowt5GhUNW10c/PCDNDx6ejjaIkEe+LQbxeK5GqIQTaGAERrDY+eHK9GAJ899bzzz+fKPeACFayVlT4KpJvICdMx+9kHTfLWgjW+4Hjd+LIF2+cTEa4GL3hFuJ9mPdUyBnJyWO0tg1FG4yEhYn9ZvtfqB/sKTBC9WXkv3G7CdEabtmRcDGiwuQiWKzAF9smZDM1QcdFo1Dui/UVIljQta2zCPX7Uw0HQvjIb7eROF6LrjwC7EbGz4HtHpipV3MmfOEWXdMScOP8TfWhaYvXxN0WARGsbnto229hw4cPj/CL9nV3HA8C191mJwzWQmY6MV10TzzYiA6bxyNfEctZ1OLTX0CuLKpkBCshcbhhuzrKf8aRGp9E2dTzUNkE2UWbKIT+Y9D/NKo/QCZxYuIWIcRr2f8s8n6I5EzHN/F2xI2ZNn7otPAHxO4u1iHvzRK65iObhRPGcwvvAW/Ax1HP2wLzVCtXYZ+YM6pGgsWtVX7RgNuAXZ7gw9ZdPqkmFAI9AAERrB5wkNtlidjiaRdXO+NnLWSmM/MZ0VgeEx1GgJKIC+q1bhF+GRGeLYMIVpmfmNMOKgnW1cgWiaLuMch8EMcI1sEgRK/EfiZkDf0kIEnC80X3xY17EmF5xdmErZoIVmgOJOTmUFbH9mQ8+/QDbAFuVkebMiUEhECTERDBavIB0PTrEMADrusaDazhJt5A6xVNdwXB+hG8sIeZHcEC0bBv561F9Get/6wSHjr2yUzJAoDV6Rh7QYkQDbzT5zW802d0LOezV0y0cznG/Me18Af1PiRMKPnW6WNNzhKk5Q4Ud6D8WSzne3fs4Pg4LYCNTB/jsWHh1g1hskUYKrRCG2u39dKd11vBJ/kgBIRAfRCwi1B9rMmKEOgEAninTidGN32o25oq4IVPHAqoF1LhV/GTBDLzUNLAN/ZZh8wIVl+Qq5Cs+D75dX5N319XYpfv9EEEy6JDM+P5+O28E0GkLrf5Md5FsFAygpWVjGQwumXXJN+Pq7MG5sidTazbfMxRVZcQEAJCoP4I2MWs/pZlUQhUiQC+xl3liGLquMmWKIbtks7aG3kPcftWfeLgyztTv8YfHJAZd45DZgSLhCf0wW/7dZr12/72XoStuseA5ZHQsdcUhMSNX7t35A9k7DYay0h2HVoFPTtYybwgbddiHifHOqw/w1QiNmIngpVAoooQEAJdiYC2CLsSbc2Vi0CjCFbupPXr/CVMfaqAuYQ4FNAtpALu0Q/Ew9dNiJARE3SarBdIz1q8V8n0SVh8n0oMgfCsjp+zon4yyAYjWnUjCBAfVGcyotTRwl+8YmA2ikqkyK5DfI/UoHiw+Rs3qy7seaa6PZhetQcaIASEQI9GoOyC2KPR0OKbigBu5k2dvzOTg2TweaIiySczRfRDnRICFHcaQYngBzlVsh0H4vU0dTxZb5Ar30ZIsHz/VoFcJbZgpoxg0Tafx2KJNLSjqPqv+b/sbW97298wehIe+p7kW8E6fJ/9rqz6T9GxBC/KnJGlILkQEAJCoJEI2IWtkXPIthAohABIQCG9Rilx/irv4yQDe1Xwh1GZgZ6OT2A8ceEqiYYP1Ap8+/I6PFdl23Q0ZNGfy0C4psaWTdYLkcK1eMVBLHaF75NfXw3beAY+4Vgv+IOsHv8eG5t8iWQtyX27AXMtj3+v7Uwage+12HJjMPbPqAyu2YAGCgEhIAQ6iUD7hgw6uXANbz0EGhXBColb2K4VCdi5qsDYMPLiE5gCw8tUSuyBlLyNL9j0tUASjREt8eRGsHrDb6uz220Zenq+/VUeu1qK94mdAj3a/L2nb9UD8O3E91ujytIRLBx/klE/zULjbF8A331y6XepLgSEgBBoKQQUwWqpw9Gznekswdpnn32ihx5KvuhWNZi8dxeNYMHX/bB99gAm+XGFiXzCQtW6Eiz4nGbPJ1DOPY909V6+fHm41efb8OsPeRGsP/KHfWFnfRoMo0txxMjNVcOfVIIFm1vUYEtDhIAQEAItgYAiWC1xGOQEEehscKLo+Cy9LHna0QG54isJjIy8kqYTyxpKsDCH+ZC4gHVYBMuP9hjp6jVs2DCfYEG9hKT59g73IlhODt21zMlk9am4f/RA/OybjmVWQfTuohDE9q9lnRIIASEgBFoQAUWwWvCgyKUOBMaOHRs9+uijheHobAQMxKGauRzJwJhTMO+tOQNDMuITmJxhmV1F7KXNkRCsBQsW+ASLE/n6iX0QyMXIw2JPfJ1M52rs4ItR90cOtwgTc+PGjfsPGsUPUDJSFSEgBIRAcxAQwWoO7po1BQEjOPxx5j322CNatCj9t3k33HDDaMmSJZH3qgFnzcZvvfXW0YwZM0pm4JjXX89/UbaNLxlYoYHXFFxWQSUhLLFeZ4lKyXj4XNLmHNjGMwLlv1jMCFZvRt6QY3cYOCyxUWYvVgzXYeM7XcKXG2CEWUkICAEh0G0Q0BZhtzmU3WchJEjYxspc0BFHHBEdffTRZf0WwRo8uPzLYx//+Mej/fbbz40JiRTJF5ONd40Kf7hFWEHFukO9LAJj+pXKivawnWZblpubMawtbduQ7Opa7Mz5Nkv8w4PrFjXydcysSiEgBISAEMhAQAQrAxiJm49A1gPnJEJpZCgkTrYCvpIARCHKepEp3rnkVKlTNGH+ooSjhLDAftguOqXplcwbRJ+cDp6begGVufBxig1CmUSwPFmECBzfsO77ZETMqeH1DyJYPmCqCwEhIAQKIlD8jlLQoNSEQLMQ8EmX/43C8NnpkIhZmwTszTftd4vzV9HKESxsufElV/Ymc1tIKsGKO32CVULg0G/jFpohlUJACAgBIVAZAUWwKmMkjS5CwIhOVuSqkhs2nnrbbLNNov72t7/d1bPsmjwrwpUY8ipVRLC8Ua7qk5mwr0i7hABhzYXsgRBaZMoiUv5cvg2/HoGsvQTFLwwaNOgb/gDVhYAQEAJCIB8BRbDy8VFvExEw4lPUBT+CZWNHjx4dbb558ihSYmqvvfaK/vY3voh9Xdpxxx2j4cOHR0888cQ6YUatighWCWGBOSM6GZYriksIVvD8VN5gi0RVRbBoECTrqjzD6hMCQkAICIFyBBTBKsdEki5GYMstt3QzGinyI1G+K/jNu+hzn/tcIjr00EOTOiv+ODzo7frw9vFEx+xTsNtuu0X43bukjxX8CHLErcUiqYoIVgkhgu2QcBWZztfJsjcdSlN9xaBuBMs/5/8Z6/g+hfYDM2oKASEgBIRAEQQUwSqCknQaisABBxwQ8UH0559/3s1jRMknROwYMGBAZA+ks73ZZptFBx10UHTHHR2/s2zj2MdvEh5yyCEuIsW2n3w9ysN5fN2sehURrJCw+GQmy3wROd85wa8/OnuIMnXsg2aM9N7IbgTrrcDSfdsQP4i8dvbs2TZyDcjjWDQy30lliiqFgBAQAkIgGwERrGxs1NNFCPDbe8y1EJ2RI0dGu+yySzR16tSybxambQ3mLSkkXnm6DYxgfQfzfj1v7rjPiFshwoa1WQTLjQMhe8bm2Gijjdb4BGv8+PGPWZ9KISAEhIAQqA0B+2+2ttEaJQQagIARnfB9VlkEjM9TffrTny4jWFmumf2s/iLyBkawriwyP3Q6RbD8OfBeMZ+kmV1fRXUhIASEgBCoEgERrCoBk3rjEAgJFCNQm266aTLh9ttvn9T9Ch9u32CDDUqewfL7rc4tRaa3vOUtJiopqyFeRSJYeKaLT9eHhCVsl/iAhkWaQrm1w4fUfXJkOmUl3nqf+XA91u37VMhe2QQSCAEhIASEQAkCIlglcKjRCgj4RAfbV86lww8/PLJ6JR/98b4uSdhxxx0XDR061BdX3JrkGJI4PxWJYJ155pl8xsknLzSRS6D4rJQ/T07d2eXzUzk6flfuvJ6iCJYHhqpCQAgIgVoRKL1r1GpF44RAHRAII1i+ySzSVK2Orx/Wi8xhY4pEsGLdkADlEij4UIngOHvQuwD2F+PZqVx75i9KI1ihP56Kqz4SCtQWAkJACAiB6hHQQ+7VY6YRDULACFY1RMd3xcZZ6fel1fHyTCe2VzqYzr777hvNmzcvmj6dbz5IT0UiWPHIkNCE7ZIJ8NM0RphYdrxrokQjcluEIHh3jBs37uLSruwWnmdbXeQt9fgNyC9nW1GPEBACQkAIFEVABKsoUtJrCgKdJV15Tu+xxx7RJptsEs2cOTOaM2dO8gwX37fFefMIVhURrDAilUuw8NzWajwvRbcZcUojWG5J+L3BXDtOyfuDV1ysqkCwzgMxferEE09c7g1TVQgIASEgBGpEQASrRuA0rHEI+BGoRhIsRq623XbbaMaMGWWL8X0o64SgThGsyTB1om/fexidBGuA3+fX4XtVBAtfGFi1YMECmkgdh9c2jPftqy4EhIAQEAKdQ0DPYHUOP42uIwJGptJMViI8HFNEJ822yfLGh75VEcEy81amEhzrRGkRL3tmyrr4A85JqjaCFbyKIbGjihAQAkJACDQGARGsxuAqq51AII3opMmypqhGN8tGJXkVESwjTGYyl2BhK89/BsvGsDSC5Z7BqjaCBUxy5/UnUl0ICAEhIAQ6j4AIVucxlIU6IWBRIp8gmaxOU+Sa8efNVURnFQQnJDZ+268v5ZzwwQhZGMF62Pep2giWN9af0xOrKgSEgBAQAvVEQASrnmjKVsMQKEJ+upKMVbHQkND47fClodGyZcus3ydYq/GNx49hzp1t3ioIng1RKQSEgBAQAl2IgAhWF4KtqfIRSCNIJitCsMx6Nbo2hmXeuAMPPNBX5bcM1ysReA3YOQz5yFhkhMk0wrbJXQkiZf0lBOu00057Aw+iPwklR8o6EcGaWzKhGkJACAgBIdAQBPQtwobAKqO1IMAffGZCdKZseB75KVOuUmAkLm/Y1ltvze7/Q94Gmd8i3IBlWjr77LNv8+RGmExkz1ix7fe5+tKlS02WECys/SQbbGUtESzY+RjG/c1sqBQCQkAICIHGISCC1ThsZblKBHbaaSf3kzQjR46scmR91KshcSCD/yk4qxEmU5yJ5AUAAEAASURBVHcvubKGV7pnr/BC0LXx+6r4RvVRyDNB2H7k6blqLREs2LkltKO2EBACQkAINAYBbRE2BldZrQEBRq523nnnkq06iy5VQ35qmLroEHtmatBZZ531csFBJQQL68glWCBXa4HD24YMGfKF2L7NadO5NgheiV3rVCkEhIAQEAKtgYAIVmscB3mRgYARrIzuErHpVkvGTN/KEqOlDTtf7Jt+pb3prRJd+JhFsBxhArFai5/AefqUU05x3yqESZuzxDp+UkcEqwQRNYSAEBACrYVA6sW7tVyUN0Ig/wF0w8cIlrUbVY4YMaIaclOiWymChchUCSHDGsIIlluWIliNOrqyKwSEgBCoDwIiWPXBUVbaGIECkStbnSM7G220UUiCrD+tLCFYOREsZxM/Z1OiD4MhwXJtRbDSoJZMCAgBIdA6CIhgtc6xkCcpCFhUqgoSVPIMV4rJMpHZtrJMYZ3AkZtp06aFJGidRnmtRBdz+FuEfp8jWCnRsZBguRkUwSoHWhIhIASEQCshIILVSkdDvjQVgaIEC9/G84lRrs+w+QNfIYhg9cJvGu6E/j2RHcGaPXt2aDv1HFUEy0dVdSEgBIRA6yGQevFuPTflUU9FwCJYjVx/AWJVMj30QxJk/SP69+8/3Bos+YoFvCA0iUJhrB/BisaPH/9v9P8Dqo5gjRkzJrSdjI3tuna/fv1CvbhbhRAQAkJACLQCAnoPViscBflQEYFqSVBFg7UphGSnxAqI0pwSQUoDhNF/i6pPkhzBStl+fDXFTLRy5Up/bJqKZEJACAgBIdBEBBTBaiL4mrq+CFi0q1oyVoV+LsEquJrkp2rwvqvJ3hhHsILtx0PRf4Cnk1QVwUqgUEUICAEh0JIIKILVkodFToUIFCFBeIeUG4YHxcPhhdpG0HKUayZYIFOjYX9zbAk+gEjXpsjzgnkcwcI6k8gUdG4PdNh0PiiClYKMREJACAiBFkJABKuFDoZcKUdg7733jgYMGOByeW+pZIMNNoi+9KUv1fwtwlJrUTR27NhovfVKftO5ZoKFl4c+B/vMUQq5otgRLFaKJDzrlRCxIvrSEQJCQAgIga5FQASra/HWbFUiMHTo0Oh973tf4VFFIl2hMRsTRrD22GOPULWR7aoI1ooVK0SwGnk0ZFsICAEh0EkE9AxWJwHU8B6FQM0RrAIoFSVYzgdFsAogKhUhIASEQBMREMFqIviaujUQyIpgpXjXyPOlKMFybimClXJ0JBICQkAItBACjbxhtNAy5YoQqIxAuEVYeURdNaoiWHguTVuEdYVfxoSAEBAC9UVABKu+eMpaGyJgEawCrjdyi3AS5i95CWkBf6QiBISAEBACLYqAHnJv0QMjt7oegQIRrIYRLHyz8BdYMXOhtHz5ckWwCiElJSEgBIRAcxBQBKs5uGvWFkKgRSJYVSEycOBAEayqEJOyEBACQqBrERDB6lq8NVsLImAEq0AE69oWcN9F0ZYtWyaC1QIHQy4IASEgBLIQEMHKQkbyHoMAXnng1oq3rVda81eHDRs2sJJSV/QPGjRIBKsrgNYcQkAICIEaEdAzWDUCp2HdB4FddtnFvbF9+PDhuYvCc1L8pt/yXKUu6ly6dKkIVhdhrWmEgBAQArUgIIJVC2oa060Q6N27d7TDDju01ZoGDx4sgtVWR0zOCgEh0NMQ0BZhTzviWm+7I+CewXrzzTdFsNr9SMp/ISAEujUCIljd+vBqcd0VgSFDhohgddeDq3UJASHQLRAQweoWh1GL6EEIuDe+L1q0SASrBx10LVUICIH2Q0AEq/2OmTzu2Qg4goVvM4pg9ezPgVYvBIRAiyMggtXiB0juCYEAAUewFixYIIIVAKOmEBACQqCVEBDBaqWjIV+EQGUEHMEaMWKECFZlrKQhBISAEGgaAiJYTYNeEwuBmhBYzVGzZ88WwaoJPg0SAkJACHQNAiJYXYOzZhEC9ULARbDGjBkjglUvRGVHCAgBIdAABESwGgCqTAqBBiLgCNa0adNEsBoIskwLASEgBDqLgAhWZxHUeCHQtQg4gnX22WeLYHUt7ppNCAgBIVAVAiJYVcElZSHQdAQcwerVq5cIVtMPhRwQAkJACGQjIIKVjY16hEArIuAIVis6Jp+EgBAQAkJgHQIiWOuwUE0ItAMCIljtcJTkoxAQAj0eARGsHv8REABthoAIVpsdMLkrBIRAz0RABKtnHnetun0REMFq32Mnz4WAEOhBCIhg9aCDraV2CwREsLrFYdQihIAQ6O4IiGB19yOs9XU3BESwutsR1XqEgBDolgj07Zar0qJaBoGRI0f2ahlnuocj7qdyusdStAohIASEgBAQAkJACDQIgXPOOWc95LXIk4tMsXbt2l7Q/QjLIvrSEQJCQAgIga5HQBGsrse8R804a9asbvNCzAZG4/rHH4q3FvlwTJgw4WPQ+zXKw1DeVmSMdISAEBACQqBrEdAzWF2Lt2YTAmkIVHUeInI1gkZQbpBmTDIhIASEgBBoPgJVXdib7648EALdD4H+/fv3qXJVLuKFn8tZWeU4qQsBISAEhEAXIaAtwi4CWtP0LASwfbfPmjVrHsSqt8bzUjPzVo9IVFXnIYhVP4xhBEsEKw9Y9QkBISAEmoiAIlhNBF9Td18EQH4OjFe3U6VVrly5sl8lHb8ftk1/BeWTJ08ecO65537U16lHHcTwauSD6mFLNoSAEBACPQ0BEayedsS13i5BACSomof7LYJVdEzJFuGCBQsmYro7Jk6cuEWdF/d52Lu1zjZlTggIASHQIxAQweoRh1mLbBYC2M4r8ioFI1hFdLkUF8ECqbItwi0pXLVqlUW22KxXqvb5sHrNKztCQAgIgbZGQASrrQ+fnG9VBMCrXDQKJKgIaTKCVXQ5Iemx8/iF888/f6OiRqQnBISAEBACjUPALsyNm0GWhUAPRADEyhGsIhGs3r171xp5svM3IVx4nmubHgi3liwEhIAQaDkE7ALdco7JISHQDgjgIfBfIJ8b+moRrFCe0bYIVtFnsJwZzGHEykrKzVbGVBILASEgBIRAVyAggtUVKGuO7ozAUVjc+E4usFpSZNuOdv4mBAuvhkjqnfRJw4WAEBACQqATCNgFuhMmNFQICIEsBKp8BsuIU5Y5k5uenb8JqcJ24wBTUikEhIAQEALNQ6Da/5yb56lmFgItggDfO4VXI5wwZsyYy6dNm5bqlT2DldpZLjSiZMSpXCNFgjmMWCVbi4hgDU5RlUgICAEhIAS6GAG7sHfxtJpOCLQvAiBXp8L7y6ZPn/6urFXYM1hFHnKHjVrPQxu32vOjLv80FYy8edOqKgSEgBAQAj4CdoH2ZaoLASGQj8Db2Y1o0RtZahbBKkJUoGPnYdEIlunZuIRgeQ++Z7lWSI43w1t0rJC+lISAEBACQqAUAbtAl0rVEgJCIA8Be86p4vlTJILlkbCK9gKnTN9eOMruukSwhg0bJoIVgK2mEBACQqAaBOwCXc0Y6QqBno6AEaxMMmNbhAWBquk89KJVb9o8IGt1IUbYBq2LHfNLpRAQAkKgpyFQ04W9p4Gk9XYPBJ555ploypQpEUhIZxc0kAbwjb2KJMSLTuXNaeehbf3l6bLP9GzcEm9AJunzdCpWBw0aVHFtFY1IQQgIASHQgxGwC3QPhkBL7ykIPPXUU26pdSBYLoKV984pzFH4Te5wys5DI05FD0nZOC+qVdRGqt7SpUtFsFKRkVAICAEhUAyBuvy3W2wqaQmB1kCgDgQriWCBZKUuiluEReeBLpVpJ5dg4Y3xH4POOOS7qYwxRoKMaFFcl3O6f//+fVasWEF7Eeal/R/DzevPPvvsu5xQf4SAEBACQiAXAf/CnKuoTiHQXRAoSnxy1lsxgmVjMVcuaYr17Dx87wUXXLChjQ1LEJxtIdse2WzaOCt90hUOz21PmjRp0xtuuMEIWwRyldQxcCjyl7CWKblG1CkEhIAQEAIJAsmFOZGoIgRaFIFXXnklYq41GbGyslY7GFf2kHsc5UlMYo5qHvRKzsNly5YdDFubT5gwYefE2LoK9YxcUWrjrKSs6ggWiRUI1Vy8NJXRMZf69euXEKy+ffvay0s3s36VQkAICAEhkI+Af2HO11SvEGgyArfddlvE7KeVK1dW/dB6ddzHny2pO4KFiFJCQvBag35Jr1eBjk+IvJ51Vfjj6/CcfAJbj1PXaSQ19jE7fW/+5Dz2ZMmgShUQq41inf1MF7gma4N/68dyI1qmplIICAEhIAQyEEguzBn9EguBlkWAzz9dffXV0b/+9a+qfKwDwXLPYMFOQkLC1xqA6LgIVkCesvxMzsOYIG2SoWjkyua1cWwvjcdUHcHCOJsv+TYiolY2R7R69WoRq4wDIrEQEAJCIAsBu0Bn9UsuBFoWASNKM2fOLOSj6VtZaFC6Uv9YnJCZ8LUGmMO2CIucY76OXy+ZHSZJethv5Md0Wf4d+fVYB9XiCa+b2CDWTl5YumrVKpuDXeuZNWxfJms2mUohIASEgBAoR8Au0OU9kgiBFkfAOIyVRd3N+uZf0fGmh2hTsi0YvtbAIljQrXiOQTfcIrQpwpK2qGs2/ZJfZ+RP5tRCgGxMsp4+SLBlyQhlNGDAACNj1qdSCAgBISAEUhCwC3RKl0RCoLURqBdRqnWVIHYJIeFrDdLsgDulygNd/zz064GaI1bsdza9aBVljmAVnK/ELnA0HxMihW1Bk1HXCFi0fPlyEawS9NQQAkJACKQjkHcxTx8hqRBoEQSqjVyZ20WI2eLFi91b3+fPn2/D/NJt/4HMJAQreK0BH7yv+xYhHCDpYQTLyI+dv0awVqEvIUOoF002xsqSt9T76/S2E4valp4QEAJCoEcikFxQe+Tqtei2RIAECTf6qAhR8he4jvP40vT63LlzXceLL74YbbzxxqGS29KDvYRg+a81CJSNBAXikmaiA5tGnkoU4gb10ggWx7gIFsYntvC81CjIn0HeBvWXUKYmRr1ibNy6qORFtdj0rxPuAX8KlYSAEBACQiAbgeRinK2iHiHQWgjgAWznUEwKqnauCDED6ciza50J8fBfa+APrECYbB1mL8K8Sd23E9ftfHUkjMTIk/P5K5IspwNCtQvq30Wmzt7Imcnz0eyXRLDQnxBJGBHBykRSHUJACAiBdQgkN4h1ItWEQGsjgAfKIzzzVHUEq46rciSIBMdInv9ag2CehLT48nPPPfcItEfjp2fOR+nrkCS5BNvkW7bVSJkRKjtvbRxLjksIFurJuytg4zW085LZ83XMNmVJP3wSwfJRUl0ICAEhkIGAfxHNUJFYCLQGAtiGc468/vrrrjRyw9KiWnmemn6RCFaeHfRZlCkhHnytAaJGvZnjsa4kCUuzBV9uQJ7k68b1hGBNmTIlsR/omdyfKyRYadOmyjwfbV0lW4To38IbKILlgaGqEBACQiALAbtAZ/VLLgRaBgE+d8WEb7i50ogSn5e66qqrujKi5RwBQUrIU/xag1lwbJpzbl1UquI5BgKTEBvYTOqzZ8/2t+Zo1mxVS7CSbwfGvpUU3jrMfrhFeJE3oG4EC2R0KCJ5B3i2VRUCQkAIdBsE7ELdbRakhXR/BEAI3CKttBXjm3zRwIGV7/9GzGycXzISltcf6zpixciP+RC/1oC/1We/11dGwvx5gnpCbCBP6uHLS70+d956xIj+rEBmFCshfai7BD377UQThWXZdQAYlNmJB1UGOLSe3f49fHsnuhNSma2qHiEgBIRAeyGQXMzby2152xMRMDJjZUiE+LuEeSnUT9O9+eabo2uuuYYPm7tubkembD868gE/EhKC6FpSj+3auWVl2nQm83WSOvwNiY/NYXLTZcmwHrPJzDbL3AgWiWKsnBCdlPUYuAnBmjRp0qbxw/T+XNXUSa74Sotk3moGS1cICAEh0MoIpF2MW9lf+SYEkh93NqJlkBQlWCmEyUxECxcuTOqsPP3009Fdd91VIkPDCIkRnZJnlmJld2555CW04bftPHzT18dLPW0e0zU9m9fa1EuewZowYYIjLjYINnMjWB5RNHtp61kOe4ySJQQLEUM+SJ88TG/zVVtimzDcCq3WhPSFgBAQAi2HQHJBbTnP5JAQyEDAiJWVpsYtwrxkEaxbb701LSqVOdTeieUpOOLjk6Ew4oM+i8pUPMewDuqSIIURKCNSNrXZMrkRMJZ8dwVt9MY6H7YBLGE/l2D567Bxnuy+WEb7y5ATgoX6iLivUwW2QnP965RxDRYCQkAINAkBu2A3aXpNKwSKI2CEykojTGbh9ttvz31+ytfPi2KZvbQy/pagI0/wwwhOWsTHzi0r08yZjDouAuXbTHn1g81nER+zTcKVECwzaqVHlkwUlkbYjBSSlNlcjFwxcYswJFiuo7N/8Pxa7hZmZ+1rvBAQAkKgGQjYBboZc2tOIVATAkaUrPSN5BEnX9++ieiPzaoboWP/iBEjjHiwmdTDCBb63LnlEZUI5GwktsPOhiwhMjSCRF0+uV8WwcKYPZCHUQnJzlcjRH6bY10Ey2mW/jG9Umnc8nxM9DxSZgTLRbCg60ewUu1VIXTfVkDkURGsKkCTqhAQAu2BQHJBbQ935aUQWIcAbvbrGnHNJ1Fhp9/n10O9vDZenZCQKuglddhL6hwP3+zcspLi70N+Dh4OH86GJZAZ2yJc4xEbbmPS5mPIN8W6Zsvm8tsWwbI+M+9HoxKZX/HmTMbCT6uXECyMqyfBIiFkKolggVAeBiJ6cEeX/goBISAE2hMB+0+4Pb2X1z0KASNFVnaGYNUawRo8eHCfN99803BPzh9GsMyvuNORH4+8UOwYIR7Gty0+s0Ndko2SCBZsbhDb3DJWNEJl440E0Q8jWKYTD3FFmszvt3WYXX6L0l5BYQSr8BbhpZdeOmjRokWnItp3/vHHH2/fPvTnszrXzFeIhRGsW+JjG0b6bJxKISAEhEDLI1DpwtvyC5CDPQcBI1RWBoTGARESp2effTaaP39+WV+oF6Joc4RykCsjNexK6vAlqcdj3LkFO/45Zk/hl0RsoE8dkq810E/soG6RrgWxTeszQmS2jWCVELR4jCNLVk8rvTnNrh/1MoLltggxviyCdcMNN5hfzjzI1VdROXfOnDkfSJvPk7kIFuYP8fBUVBUCQkAItCcCdoFuT+/ldY9CADdit96w9EEISddf/vKX6KabOnbY/L5aCRbm8s+ZhFgEkSq6ZNGXRAcyI1gJScFaqEebZREs9FlkxxGRWA9F8tuA/GkegrIzcs3PYHm+JwTLkxnByoxgvfTSSyFB2opOwv+O3zRiIz25A4rjMgBbguOwlgfT1SQVAkJACLQfAv7Nov28l8c9BgGSKmYmK33CZEBUIk5F9XzbNl881j9nEvIEnaQe6Pn6brsMW3+DzA8QC27FcawRpMQOSI4RLCNrZsuIUKKL8WlbhPdDvjDFN5velV5/skXoyYxg0f5S5IQcmhFErMxPE5lf5qfJw9KIY3/MNwGd+4QKXdUGudsPPhjOXTWt5hECQqAbI1DpAtiNl66ltRMCuPkl7lrdyqQDFZ8YWR2vO/BVXD1trK/k9/v1/v379/Het2VEgkPDSYwM+TouggW/EoKFcb0ZLcIcJFjhFl8YGTJbNpdPbNII1iuw+XbOgZyXzJ6V/jNYfDUDU2YEC32hnwlxciOz/xTVy7ZQhx68mPXdOCb3ovwczP28DiadCZA24nn+gAEDJp1xxhmv1cuu7AgBIdAeCFS68LbHKuRlt0fAyBIXaoTHl4GkOAx82eLFi50ML7J0pf/H1/PlVr/77rutWlJibv+cMcJDnTCyY3pWUqeMUAwZMiQzggV9Iy574ea/K9pmy4jQYBqNUxrBon8l30w0Zb/0tgPNLjG2tfkRLJKtMjBBYH2iR9MkiiRpoZxiPzk8fD2QEluzr9fQOtb6Fk6AckQ9J0Kk8h2w9w28kf9b9bQrW0JACLQHAnbBbg9v5WWPRQA3v2TtVreSHRal8rcIsXXlxoDEJGOt4o81WZES3wA04kH1hJCAJITEw86tRMezn8jgr4tgoc+2CG0c1ROyAUL4ONrWZ+N9gmXjff9oI4yKUVaSgIWNSbYIjXShNIKVGcHC+MTP2LAdrFBeMi8aZYQT0R5/TaF+TW2QtvUqDNyE/Vir+V1BvXB32foKjwwUSTyR7fgHvWoKASHQigjohG3FoyKfyhDwCZFFn6ykshGsF154IZoyZUrE3yU0soXXAOTaK+vMF/jnTGIY/oUEy57nSUgLzFrEJpHxW4kxwSERCslQSFBsbiNY63uupkWw6MPq2L6nWla1dZhdP4JFu0wsU9/kDpzDSJVbJ+YN5c6Q98cRGl8P0Z66EiyQEn4T802UX/TmLali/q0oQOnjWaJTY8MIluFboxk3jP8tXNUZAxorBIRA1yJgF+yunVWzCYEqEfDJFG6EbrSVbBiJevLJJ10f3+huBAtbNU7m//Ht+fK0uj8P+n1jyY3Tj2DhZs6Q2UmxLZ8kWYQkITKxPdrxI1BlxCO2ZfPZeD8yQwIUEjQSLN7kfZ9jUyVFaNde7UByRptMJQQLciOQ7PPXyLYRi1DOPj+l6SVrCl//4A8sWsex3zbW/VDOGCN1G+bo1NJl28Z2vGqxQeJHrElWj67JgAYJASHQFAQqXXib4pQmFQIhAj7JsbpPkoxg+ePsZ3NIsGyM9b/88svRo48+as3CJeYxMsIxyY0T9pMIFubb0TNYRjKgm0Sw+NA8dJlJZIwgGRELx9r5aj74/SRAaWSKNk0f1dRk60j8go/mk5Ggki3CG2+80XyJsN7USBVIZ6rc88DZ9vVgy8hONG3atB97uoWr+GbmJ0Fyr8AaeiFvHg/Me8jc/CzfSy48a7kiPp/2mejLl6/Cp7Xw7fByzXzJZZddZkQtX1G9QkAItBQCdmFtKafkjBAIEfDJFG6arttKNkp5T8eD8BbBwg28jGD9+9//djbGjh3ryrw//jzQS4gF6glxYQTL9ODrxp69hLRAZsTJP+9ozyczrJueT6Bo0ua28YltzM9oU0iwOhXBgr3VsV3OXRLBwktEzQf2hX5aXyinrp9sPYkesEsIFhQ/ifwlf0BaHcTlWyBmD4wfP/5e9sPvySiG44sBd6C+WTzmjbhMK2z+miNYV1xxRT/8jNIK4HXs2WeffTUn8T4TfZYsWeJeGgt/voGuW9KcyJItW7as3luXWVNJLgSEQB0RsAtcHU3KlBCoPwK4MSVGrW4lO/IIlq+XGKmxAtKWkCpOa2YwR7K1BZlFfdhtN2/W3SJw402IEV75QBvMRSJYNp+Vvu20CBYJVpEIltnji0vdNQHrcT6h5HimkggWnpUyEsVXY1gEqEMzitz6MDaUW7+VaXo+jv8yxQrlt+HDPZ6O1UdBZhGsBHNPz6qGY80RLJCr7WgMa/66GUXdIlh9EE010s1jUlXCZy4hWLBZ9fiqJvOU8VkYy8ibJ1JVCAiBKhAQwaoCLKk2DwHcQJPJcZNxdYtQsZFGsGyLkGNtTGIkrvh2wz6/jShChBsOJ/6EJzdiQlHWjWggxtmN21hiQk4wjuegIzMouUjfpt34IXbJzlcbv4N1oCTBYvaJBG/GYVQLorLkz+lsgwT6PnHAKsiSF40Ce/OBfaGf5kMop66fzIav5xOsp3zlKuoWBePWmkWwysgejsv+55133tuhY312nKqYKlE1Imdv62eHbe31BXZGsHiMqkrAOomsXXLJJT4+VdmpRvn888/fCPp/xzdxv1/NOOkKASGwDgG7wK2TqCYEWgiBuXPnRv369eNzPolXRpZ8gmXfIjQlEiLrp76NsX4r+W1DvBrAmqklx2KLx/oOsgpKn5gkBIvkxJuP+vzJGJIdi9gYAeG3HxndMDLDaBEXakTMJx4QJ1uErIeJN27e3EOSUCSC5V8HWF8B/51PWAu3HjnXKpR8ZYMjDSCmyRjohAC6vhQ57ZCoMiKzFbLhYESE22qDPexqJRM+wTLiE/pIV+6OPyO/ZQNpQxIuyF6Aj8tIMvD52AFbj490dGf/hd8bxH7bmvwtQn427LjYsc02FvTA9maGCb51SuKT/Np4oFq3Jta9U2xs97oZlSEh0MMQWHfX6mEL13LbA4Fbb701wgPVJQTJok5WciU+AWP75ptvjp56qiMAYjcnysP03HPPRa+/Tv6TnzJs+ATLbqA0VHZe4YY9BvIN4lkSchLrGsGqFMHy54tNdRTwj0SKBCskZZ2KYMV2OYkRuD5YS2/I/TWEcxqRDOW0w/RrZD4EZ2QkidBA5pOqQXy2CfMZSUL3ugR5X+Z1kqTmCBZ8JLHJjGAl2usiWNuBXE2D/HL2YRv0+/iMPTxx4sQtPd3UKuayY5usOZ6f+ut7/VUTLIzd1ibF55wEq+EJc46MJ1mWNxm/6Ylj4J4vy9NTnxDoiQiU3Qh6Ighac+sj4JMpXPydwxahYiOMYFFmUSfq2xjK/XT//fdH119/ffTAAw/44pJ6znj/5n6kDYJ+GhEioRhKHUQkjFjw+SVGc/4f8m7InY1gkUy9B5nlfGByQmwzzR90JSnpx7cajRxxS4v+0BYTH3jnc1jRsGHD+mGNydpRD6NDtr5QzuFM7+wokr8OF7Zgy6JPvLEPwrNNJ6OcPWnSJNtio5ol+jPFGl5p9hgZM3KW5QuHWZ+t6Quxrf1YIsJoJC0WlxeMYMXShCBCRoLHxD4j4PwyRC98m/DDVTzfxM+GIzr4vHQJwcJ8RprsWEJUnvBNz0mQvgKSpXtJOTyS9HAEdFL08A9AKy8f31RL3MNNqazuE6zwGaxEGRWSM3+832d1fqvQflrHZBml/5BxQkwC3azzahPqwZfkpoX6W7yxJDO+zSQaEutk2WU3I0xHmx5u7mecddZZL6JNm2Xj8A27HXFTPDHWT+aEP32xTcaICYnN5rBDksVEO4yQRUuXLqVfRkYoSvyEzb3QNrKZyKnkpWS+WJaQBsxnBIvbYMTJkTF8GWA7G4859kB+JG4fY3KW7EOxfSwjwXGYo0wwj/v8giTXT71ghx84d2wQNTKffJ2SOnAzgjXMOiBLI1gbAN990Xcnnm8ixkUSbT5DReCTYFVkYCd0jBCmEVvf7CFxw/T9vrat4/j0qsd72AgAPkv9L7zwQvt8tC0m1TiONX8IeQlycj5UM7676JZdeLvLwrSO9kfAXhrKlaRFsHxZuEXorx4XS7+ZWedWZFby5qpIsHATDAmEmbWogE9O/BuTkSFzOCQoeecrCZafaIuJBKnMH6znd5B/jwpIiT/Aqi9ySPqoQ58cwQKx7U89CpmwXosAsXk9/8RpU6sEZehPchGGXSMzizGG62fJNBwX6+8h/wf1o5BJ5NLSY56QESzzrYRgTZ482eRU5xbly6ykJfgUErA0NbuBrgcfDZtUggXs/xobSNadZtCTUe85tuFLlxAszGOfy4RgYV2949/E9FxLyHXRtfhjW7aOdY5HdG6Bdyw74+s1+KdkETB11w7YPBb5N50x2AZjT4CP/Pzvbb5izZsbBibr7mXeBbu7r13ra3EEhg61nR53Y3HeMlKFk9TV/QgWbvKZq6G+jclUQgcfeE9LHOsRLF8lJArso3NZ55XbaoKv/s3evzGRDHGsLcYnARCXEyUKmWDTIk0dgo6IE+skWll+RvE2ld/fF2tNbGHtVk8iWIgm0X8jEZzDJ4JG7CgfFT+jE+LhjyUxfB+V42RbbIxg8ceXd43l70J5IvJoZB+zuLusmAsJL/CGoY85o5VGIDhwCPD7ESsZqRqCxS9NbICbCdc8KrZH8mXz+c+b2e88Zkzroh+ce19krudN+LkRbPN3Ca9F3i9zYBUdOMaM2P0IeS3yr+Oh5ucQPgcXyy7BZ+Nx6Ng/ChQ7fLvi2TDMeyC2Vg+NfWlYwS83AJNzMAGP2TbIEeYeg3wY6zWkT3IMfLd/OH6K5kGw5/6RQflDZL6E9tQabGcO4Tpgd6tMBXTw2GP73fzKU622z86ZHTjw29/+Nq99s7HG06o11M764YWvndci37sJAn/+85+jK6+8kqTBrYikyggOI1W4KDi5ydjIi2BRz8a4gTX88cmcN9wnJibmf6ppcva7myz6fYKRfIMO/SQnHGvjfeICcSZxYx+Jip+M6JAgpZ3nS6iMbSpGKDifG4/njXgztbE+cVsDv42BlkSwIDcSg6HJNyBZH44oAInS3Wx4ydbHPWAfC6r4Eazt0TaC5ZMq/wbPMS7BD35gXkG+BfkRZF7kOz5EwRYhSKJFnKDiIlgLWUlLsGs+pXWbLLGHzwoJ28fRYTdk+mEEK9GDLFy72fLL69AgvnwGayF84X8duyB/Gnk8cqcTbnoTYeR/YkP0m8n8jebPn885mWxLc2RH0/219dgN1euqrQpSsB/yVfDraFpAeQYyidUfsP5bQ6s87hdccMGGobxIG/McgjzDf8YPX274kjd2m7j+T5S3QNf+AfBUKlZ5DjAZ4V7KBq5Z28X2TmAb67iIZb0S1vE8bM3Iswdcp+BcmFuv7VBvrrfF9XezxHWFn1km/qPUY1LahbfHLF4LbU0Enn/+eUeoZszouDYMGjQoIUhZEay8leDClYzP08vrSyFYZHlpN0iSh0rnlUUEOKVvg2SI442A1EywsOYOFpqxRYg5rH9gPJ9FU+hPQrC8OmVuixAl/Ur8BpkwfyFO7LK+DTLJAW+YPiamTx9+huwnu4HZTcn6TM72aBP6JW4WO6K9Gfz5AUoSEiMJvKH5mKOZ9LHOvoWsZKQi5IE67saJm8nlqNsNhiaJFQlRmHKJWxxd/Gg8iET4NWRGBP4ey9iuR/pgihFi5zDBZ38ojp9/vDfz9B3G+CcmWQt0T8ex+Jqnk1u9+OKLB2OMj/GvMOAYfISv4Y0f5STkhFhBl5/ZJGE77/N4LctCyDc3Ier+583EaeWREG6F6PUe7ITfx6C4ENnOgU1gayu07Vwk/tUm988MBn0uHvgGS2C2LQraThLmsnkSWScqQzkW2PUyG8Qlfvebib7ICv4RGmGCzpbxGkjCn0I+nM+fwQf7/C/qrP12Gp+cNO3ktHzt3ggwcoUTMpo3b55bqB+B8qNZPunJi2DRVmcTfQgSIz5GFPyuPiQcFeZMzjvo+Td+TuK3w4tt2nw2N18Eehjs2Y3IHGaZdrMxHzgH6yRYvEn2BZb9bL2wV7ZFCB0bg6q7gDu/cGHlTWq0E5b/ISnYs1wcXQfZ0Z7cbtT27JV1+QRrBxP6Jda/KXFHngE5yc6GcT/Jmo8rowcb2BqpgzGvx7osbkc+BPlS5M8i+zd/NFMTIzn/QuYzJwfD3j9StB6CbB9PnmsX0UUfr8sx7hLkT3njE5+B/Wcg/+WYMWP6HnnkkXbMPNXyKsY8Dek4ZBKTOXEZQf4V1IndTOShWAtv1LxhuoS2I1gkgPDRxP5azocO5d+zzrDEHPys7ILyGrzbizdi2rfPJKOQbr6nn3467Viz73lklzCXwwTHf1fY2w/C69kBsvQJ/GzRTU4p+88CdsHGjij+hPKqWPVBlO+IP1NjYxkjuiRFj1s7q4QfPEe2QvksykGx3qi4tM/4KNhbSaxQfgolzwXqTI/1ChcTJ07cGsSeeH8Ocy5C3sQGX3TRRTw2jtSh/Aium78BNgdivrtMB+cD1/USI4HwZc1pp51m+k4F9reEfX5+D4TtaTaOJT8HILjroX8M3hl3H95buDEft4CdX2GOCYikjYGaYbiRP7ZoHXZ6gRi+CzbnjBs37rmi45qtl3bhbbZPmr+HI7DxxhuXIMAbod0MSaRwsrl+k5UopzSoxxeWdiZ5ZM7+G8wiWDyn7Lw6M2NOXnxdwgXDv/Hzxpj0BXXqm13WSxIwWQ1snvSEJFZMtJlGzJwMYzg/68uQSTxIrhKf4B/HM61FX7JFiLbdDNln9h9jIyPxhlqWYLPkQg4FI1J5EawyO7FgSFxyLczWLiNYWKNtbbkh8CMhK1jz/bGdV1GuQN4ubucVvInxws+bJNNpHUU0Ky55w7nM6nFpN9pA3NGEviOIuGGNxE3tb5AmxyUeYDduNj/DPyAko1hWSrBHbHZAvgiZJxxJjqXLUWE/iSrPPd4Ut2KdCX45goXn2Hwy7RMsp4c5+NNLn0FObvaMnqA9EAr8rFztFKNoS5R8n9bHkHlyb418Bftw3h3FMkiOfHkyOz7cOnbkin04JxidimBzCPIVyM5HkIvPom5z2zEYA/kXqB+nmSjnwcYmWO8I1PnZX4o2iUiR9BUo/QfrfStKYsnP46bxlytszlGw9wHIH8c/ju4zh7m2R7vqBHLzaQw6FNk+Y/9lRrAFyCgcvyCyP2RjKMe878GcyVw4xm5dIEq38oF8w4q6TDgO+6LYAvkTbFuC3n4g2UswxzzY+CvaJ0HXHW/McR/0IF6zM8pt4jGbIuL4Htahuzdy8rmK+ylnxNRF30yGMcfCzv2wTcJK8nw4dHay/lYt+7aqY/Kr5yKAk7Vk8Xwr+0svveRkWVuEuDCVjPEbONGjP/zhD76o6jr+y7YxNlEWwWL0qg+U18Kn5Zw7JQ0wGfr9myZJUdKHuk+2OKQ3/2SkZZjPB84IFsu0cbYOzkF/HcFCyZ914XuuUHXJt+Psk4Shx792+PV4WOHCtk9sgN18FpsgLo14BeKSpl2UKxIsjDLyZQYWWgVrt4NNH4iPuyFYf0bJm/diYPMD3Ag+hTpJBH/C6QO4Kbj/+GH3ZcritACl3fA/iL43cMN40Drj0q0HW+TmmxGLL6P/IGRHsLgFg5uiu1nCDnX+E4+PYJN+rEBpx9F1wa8t4BfrPPbU4Zj3IVtKCBY+D1vC7pVxx2zUSWR45/T13VowT/JZwLgvQffHUGVk5SQ+54Rz22HB8UzQt2PG5rf4B2kYxj6CscegfqaTeH/Q93Y076co/pHtbVmHviN+rMfpSERevgnycRTax2HcnbgxMyJ3DfsxN3G0z8FOkH+J8jgxNPcq8iaQE6M5yJS5uVC6BBt/ROVRlOZ73NPxLVdgtH8seBLlcJARRz5Q5/EfjfxO5OvPPPPMWfCNa7gd26J9sWV3DuSnwuePQ3YI6qMxx/tRZiWSQCaSll1Q/hCZ16i+OM5boDwxzvSDaVvIP4xyOTI/G3th/lcw1/6ok0SfgOJi1mGPLxa+lnXIkwsD20ihT5dhzV9gBz5jL2KOGaiS1PEfGuL5DvSTiPGcug/5NeRhyH76ExpjkXuZEPPvY3WM5TOgN7MNnxmJuxDVWwcPHvydU0891c5dU29qmZwMTfVCk/d4BBhS5rNXW2+9Nd+gXYbH1KlTnQw3MF6EXB0naqKHEz+phxXTD+XVtB9++GFTt4myCBbJDDN/YmalDQpKn0S5cxDr2h/r+Sr0eEO35NcpSyNKpjsPGKywBkoDh3fRPp7cqg5EzEmyxH4Dnf4k82IN7i4M2RrPPvv9a0ea/Xugsz9ypeT7TGJkRCq8UPqYZdm0mzXt0K676aOkrZKLONZiP22DLixuzRo/guWIMXRY8kL+AaeU/4dzLcbLXed4/yDMxXbGU7ghuJE4xm96n9nZEA5mB+b4vVPADQW6Q1C/AfkCyBnBWnnyyScvO+WUU6hi62P/+5H57NLpIFfns5MJY+wGHqGPx2gp8gXIZyBTtguKbXDjcyQJ9ZGUI/FG6KdN0SAh5Jcbdvc6nkfdiMxWqD+DzAiXYb056i5h3OS4ui1L4PLWuJ0UwGQ7DxNGtfZkJ8bOAP4noSRRKEmQfQiCn+Dmevjs2bP52bPzYlSJIhogVyRN9JM2+Vn+IutMIACbAQfizZTcwDua7sb/CuocOxCZx2suslsLSmLJz9QBzKhfinI8bP6Ixxx1d95gThIopqeR3wp/DLuH0P4oO5Bex1r5DU7XQBRyNCpnsYHxvCZ8kHX0MxI1j/WUtGMso0/XIDMq+SjyWNjeE3ZQdWmnuNwGJcnNc8gkPl+GzpdRuoT6GKtjTW8FTianXRKbj0KH58xurqP0z0/ZROR1HsbR/jvi7v+g5OeKya0J5Ub8B4Fbkljbd+Hry7BLcsX1LkHxHOb/BOwYbiR574YOVYjPH10linbHP8EDUD8TUUP+IsOb+Gxtic/WZPhxGAgsj2WXJ56APSrhoPFiy08Lb5D9kHljIQ48YmzzZOUFOu2mwT7qJZ/WoG191m9tqLkxvDkPjuuccw0y/aAe+5hsDNvM1GEym6zTT46zMVZyXfSbJXU4ltlscYxdjFB1ydcnIfDnoQLHmg77ByGb3/xAcy4ms8t2YuOaa65hH08El3Gy8GbmZDhRXJ1vYedNifItttjC1Z1Cyh+Ot5PLTnqq0dZuu+0WPf7442WjbL6yjtoExJWJWNpnhHU7l3rDF0axuEje5MO0CALiZsnZAwZPAgOOScgN6qNNKS5tvkDsmgtAUumHpQ6QO46VHRvrY2n9Rpb4mecxoD+2RuJqv0WYrAdr4xizyTXa2lFNEj8D05CTCzUuymdibAnpxHx+mxdUnh9MizuK5C8xo037rCcdVoFt3uiZuBbfL9pKLtBUgG5Je+DAga8zUhonWxvXPBOZRKdSWh9YvYFjON9TPMarE9ulXnsW6rxh2lzWtTcqH0Tmsb8KeSHs2vnkyACeK5oPLIkVyVRyU0Sd69oYuRf6efN8iTKkg7DFch3K9eHDT1G+lcI42fzT4/aDKN+FzOOwEJk30W2R+Vn4Cmz/F6qG3Raocx38vBjB+gjqlvg5YRqDr+mPALl4J8Z3SOK/aO/gCbayOs7zGfC1VLmjcyqK7VnF2Js7RO4vz6sd/z97bwJ3WVFdi9+G7mZoaOapgQYZFQFFESeeY9REnCMGJUaNCZin4gSiiIAyiRMRfCZg4hwHePr3bzQ+oyjRRI0DiCJPZhDoZmxmuumBfmvtW6u+fc49d/y+O+/6/erWtGvXrlV1qtatc+65KX06bL0W5cSPm/uBzEceX7/Aufo7+AOwfpAsEFN//SJpa5pI6WuQ/j38cniSmwOwgfP0h3Pis/B0xOlq+C2Rfxj6+jRci6xHpzlwFeKbwwaeBjL/UvjDGMFrPd7DEGWvYJ/QbxJIuYMUQfnjEL+Iacwb4nYMnrl7G067mP8s+Bvhd4PfEZ7O1gPofEc9mT+/hdhL4A+F/zH8u+G/A8/5RMfr1jBmAvbszhCO15Hm17ctp/jxb0jm8Qdpug/z8BrkvSmJMc65Rcd5bg5fEPZEhAv32xI29YL6XrM/MP0kMjgHfwr/NMgQd+4zB8MTR7kTgAtPjA9Bxq2wm+P2FMw72sQ6A3dVC+PAjRhkg5ikJ2CAuFGx73wwmAs3/8h2HsLVSK9HuDHS/GsQBCiAQx4dF1wtSLzAWWRlijOkIPOr4ihaBc+Jz7Z1O4k6eULgddEOukJ79az65lFvYmbFoj6U8xsnH7Tmw5PUxw3fdKV8TszskMdO0A5udLw9ZDZkAURQRiyomwvmQ6yCkLKmC2nqKNibZGoHHXTQRyBLPBgYicI3C+q0NOM8sbrlllvsT511K9AKKz5IxlQXF1KWoH4cEee0j3TyX4Nevk2cGNBxDHX9GHaWW/9gPo1bnfK4YIlocAPmnJMzMgP7ObdYR/pZvjE/nMtzweUR27/Gpns7FhduFnLUR0edHLuys3LU5e1AlnNe0vlbhIejLIMMvNlPOm8jv6BU6ecAF/Kh6zRW9g4b6Ro3jg+hTIPIxZyO2HFh3hOeOhvmJ/LktkBkLXBYi4Wdf1it/AcRMZyZgfJDEZzKuFzaDCyJevYtHYnb4Vlva9Th80TC1ORKHyQYD1AG/rGIX4NQ4y9R9k+OG/bz4I9VBkOMh07W2BdunCQOcj9G5BmQ4WkHdW0KTwK0C7zc3uj7o5BgfXq6e7HZNH7zqJfp8xr8TdK22Ix2hOzlzEQ7vB1I8kB9vO4uRMATkD2YhlsCfzP8tvCb8fkqjOV5iHv3KyQOBuFY5jMVh84nK44wb7rQcxPWhk1RrmKOIecGN81Xo48vdWWUYf/2YQTuAlwPv4XM9pAhUTKH+FaI7A3/DfgD0D+SBV4zPF3imMm9G/iSHNyOcs6FneB/Dn8/PDf86xB6R5w1L+9BX0/0hSl+FUPo25cB2r4ccSt673vfe3cq+0kK/9QK6qTnsBRn8HjYtSvCv4a/A/4VIFfU+wl4um/Dv9li9Q/GL4bfrZ6sHY7wdrS9J9omwaLbBjp/gVutS3AaqPn6HeS/zkrrH9un+H8i3Bq3end0ZYx+DP5d0Hsx9H4E8R8xE2nO088i+qaUvkZ9RjqPNeIvxy9Jr3aPYVDcu2cgwevwHPinwbM/X4Xu32CM/gY612Cu/A7z9hLkHwJPRxvNTpQfaDlD+OBGMFUOF54m41T1e1idXbZsGS+4tu7ggw+256xEsPCtzogXFv3CiZYnWLigsl5czLygc7qPEV7odGvhRSBIPHiyZw4XNGVonBYsLsxyPKrWCQDzTB9IJokM63jywnLvKgkWfrnzOcxrEsx1bpESOAw3wLfqHUrH5OuTYrbHfpAo0XFNMBsWL178HTzI/ISEM+1Uf/gMhIjXKuQLB0Szo/626wvGTDpZkaTBsEH+g2iDedw06EhQZbNluI9bEN8Zfkt42kPn9XJzNpytZOb9VClZewHaW49Tnv0RrgXpuxMnUTuj/e9B4GXwWL83OADPxlxe9Qs9yM3DQr855B6gQiz8VzAsu5122uk2bGIkTNzURZzO8nLQtSilubG/ypdhfF+IecI+0hH/g+FJsLw7FonLfAbi25XSVcl7TjjhhLvwK7K1Osl7zGMe821s4CdD+CB4zvcV8DZ/0d/XwtZnIH06/FJ4nt6ci7DsWP5VeH2puB5xI2wIfwn/Wng59u0bGIPPYD6vxpzlg9Mquw6RA+BZn0Tlmwyd+yPitIdf1O5gCD0/gByjdFTEdrdB/q+Rz+fDSIw4Fr+Afyy8OYw1x51t8MsQx+Px8F+HJwYktd4dj4TG8GeIcx5snARejfArjKNNPt/EKNvhw/PLmYDLHUSc+NIZwUKdr0PuMKR/A8/b1Y9DeCS8XwfegrQ5yP8rZN6ckn+OeXgJ/B1I06aTEf/fLEPo23wR844++ug1yGeUju0dhzSx4ReVnRByni2DfywI5McQyl0GvC7EOL0LcpehzsXwlGfdGuK/gGeU7vJ6YJ+b4VPXwklYt25yZcTr7UiTYL8O4b7wK7AXfAXX5QGI/w3ixyCsYZ78M0M6tHMygg/Ac869D/5GeF4Lj4YfivMDNRQDotFAQAjgT4QVrW22Ga8/fF152tNyHiMkWFp0FTIfFyR3QUbnxG277ba1HXbwPCirFQHyBIvx7GALN3NugNrk/YL2U+Tvn4VnSAhl6KXfieRoFZFh323lBin1dqhN2vEELIq3YlP8s6xpZmFne9RrxIS2Y1Gj/XwJKYmjCAvzrD+pXOTpYeQrjmh2tKntgODEhG3IkQjZBoY2GKdjOdtthctdFITbEl72CnvmZ4JFoon0u5gJtwNfa4CF+d+ZAFH9PZ6fuZJEA3lvhacO2/Qw134DsnEe5coOuB6OPD4I7Im0F2P5t7iJIeRmTjevHsx8or1nIVWf+DPlP5cEH+DF/0vektL7pZAk4RyM23MQ2kkIwi+mMgX7KNIitH6+5z3v4UZ6Ffz7E5m0uYU0ceKpOwkWT4ZI5Oi+AM9NfHv458JzPh7BkA7X5PUI6OW+rgjCa+F50d8Mfyk83VXYNL/DCOasxpXJt8D/GN7KmEGHtv4GwZ/Dcx6aw7V7JyMYz1+j/PWIfhT+D/BPgmedSxjCLU7+SkvhA32cx3nANOR8+z9FWvhKnOF/usT/QXx/+L+A/yZ0fRXhD+BPBl6q+1dI/xYknpjR5WsW8rxmNb48Dfpvk6iTBZIeEd2UbcHe+KTccZD/PkLZzHbp7qkHM79mRZrjS/chtHmDxeofxPfb8NekvCcgXAl/Jjztpe5t4J8K/0N4ukXAi+1vAl12HSG8FV5tmBA/YB/H7nPwn4Gn45hzDtB9kB/A+BgEn4bOczAPzoR/DPJehLwn4rq8A9frmxDfmXGEBYcvhB9BxkFo+0SETwbGz0PILzsHwg/FbTCUVqPRQKACAb5QVE63+zbddNPannvuadm4YOw2IhZeS+OClTgvTPM5Y5YRkrUmhE0bPRdGEYu6QalN2LUAUd7yVT4XTjluYEYiUgZl6ShDMiT9zCs7f73+bblwxYoVrC+nNhnunDL9QmPgJVszwYKc3SKkPBa3dSAW6gPtWs18OMbVd25srF921F+VX5ADKZR+5lMX8WA/RJRoP/M3glefEC24P6ZUM4L1AMoNZ8wdW8gpj4X49qoTqaTLAswBbYxMv8KXufjXGMd4Nyz6zEc7/xv+pYzDHQ7/bPiNmSi5HyG9WSnv5FJaSU/Q7sNY/QhtzHxDgRTSMGmG7KgiwhUublHIEiPF90X6NCZwzb2mnmsbLKO3Mxv+QOg+FnLcSJn3KHhi8BrMqe8yToe/uyKx0TxYhvip8DfD/xhemys3QeEsglCDbs03xvnLs2fC/xR95XXAB/znIf7PCHnqJV12GoNycyj/PMqPQ4L6n85MnH7QZpJhzpfN4W+Avw+edmSHfsgWnu78EAUet28ivQXWKZ6QML43bLgFIR11LmcE9fgA/AdxqmZp5sF9CmliQXdBPcifvEafiC+Sf4l6tGcLhP+G8FfwJG8L0c5RCEl0zoJfC1meVn0U/hGsoY/CnD0YcfaHzq5TZ1sNZRwvkqT3U0AO+cT3xbgmr055nI9ye0EH8dgRfik8yRId+0qdul6ZLLvnoe57IMNfs74B9n2GAsj7FwSHwnMsdoInCfssZPiLT64flFmPMfwO8m5gmtcr4sKOWdnhhyArUfYbZiD8Bb4sXY36/4nkkiw04IiBP+A2o7lAoBIBXAw5nydVdFiIuMhbnCHzcephaVyMFvKDdX39XNBjhOSKvsItTHk0QhuHJwkspgxJgjYITwy4EEkHovnWFWXoN2JmhWOZN0i6sygWonU4TVFabdIOc8BrBuAZskJbCDZJDBe4ZyB4Lrw9j4jnavSM1AKcMK4BiaMY60g/+yMcWCb3dkT+XYkm4XqM52r3q1HhyL5Z/zCmtJ+3R9jmzIAnhSh/O8bp33F7it9yt4LXQu/xeRD5RrAQlgkMspo7EEwSYjmPn/JyCFseyokmESz896Do4tNOO+16zOM3Vogt8nnoGzefKvdaZN6YCrzMncjbVhXwBeXb6bYxsTUMQAqWIk+E6gzk7yv5csgTPcyBPWCH4Ypx+IlkEP9linPD3ifF78Q8vF/z8JhjjnkYfea40JFs8K+klqKcWL6emXC3wosc0v6WDjhzHhSwhk6eXjwW/lFNKtsGzjKe0tEORJfAQ928e7G27I8+FnSijP2i+wo/0IYRLsifiD6ezrzkXs4Qp6MP6ssfkuxTdjhxuT1hcjra/gYLEB6E4I9ZqJ7HC8wuMuZDxogS7PsvzHFmcQ38Fm73U+Y9yTPbXHpB6K+VRmgECLZrrlgR9P7cyRSifCYM5cojkeILUYnBMni7fpC+DDp/iPCTEmwWQtcPUEZvDqdT/8U5hbl1PTOAC5+n+yHjkNW8ZHLWDvP/Ysx1rQmz1tetAr9gd1s35AOBOUeAvwTca6+98h8v49ddmeiQYGER5H+jWbu4KHP7uNCzXM6cRYTtUGeF40ZP5wkW43QyaFPEM0lAPJMcxMsXu216eD6HMvTSj2jBkdDk6xW2eZ0miDy1z7QIkELbSUyw/mGyqMP2SZBk1zsRfxy8kR0s6iQndPe+9a1vZZ/Y1zNQT5syidn80n+Z8VvoFcin3pYOi59IFeVEipinOO1nfCN4754IG/hw/ycwL7QpbwkB3tKgU3322wgW5gsHtAE3k27+YRtcKuZpQh4D5iWdjF6XuVJpAABAAElEQVQDMvYzRjpxuNXHDe//q5DlBuYxqdxwYAc3ZtXPNmLzfYLXmd4LtAAnGzzxIBav8e8Kgp73wb/S1ynHuRFiQ1/OfMiKdDB5CT/gch7083Uhmoe2qSP9Qcjchds7V1KY5dDDE97rmYajvM0V5NUvbsvu/AP6+OMGnvo8vUmtPVL+LSkkcX4H42jzVozHTbw1nMosgK7rEHk51qBjUv5/IjwVY/75lC4ExAi6+MWCOm/zhUhbHzFf36986P8NfCZTyq8Kt99++2uUX3qWUtmVIdr9BAruxpejaysFmmRi/TsYng/V80+p94PdpwKHb0ocp4B8vuu5yNccVFFHocgVhaHjRwi+Af9bpufSca6jH8+aS53d6KofE3RTI2QDgT4icMghh5j2q666qnbTTTfVNt9883yCxdMrPQSPh6+5uWVLsJBwUcvp2UZIsLCIVKkxQoQCT7C0ITJkpS3g74c9+iVbJjnIF5FB1Jzp22qrrR5Zvnw55SobRT7LPGHxOk1R6UPlmVAAr5fhQe5v0y4QJ4HF9uhFTKTG+oRF9I/4hnkET0JQjxsjN03+CombJh37syGeTxIuzNuAH3AK66nGzwVYXNekb/YsFSni6ZleD8FxJokr4AI7uLnTc34I062Q1GYvXaxvJBHtsPy1rNOpw8Z0bzq1YxVi9iO0/QGEfwrC8F68w8e+0SP9fuQLcyQ7chqbSyF9UKrxeITL4HdjGjhUEiyWwdnmDJl8gkWiADv4moKb6iJGijhX7wcO+RfFSL8RMndIpsvwbyG/J9qRbSK4/JJjcYT8ccT11IsxPhcBfcFB5gaeysCOn8G2V7AQYYHkIOuN8JlAUqZH9zrUezme03lNqk9MzMHO3yleDtHHTCoQ55w6qSxTSstWjmHBoT5/YVrI6zSRHkLnCRuvv44dsP8E2jwXJ4ldzU2cMv263Eh6VxVvhe6mXz6WZXpNw85XXnjhhe3Wi57Up2fEeqo720pBsGaLYNTvCwL77LNPjZ6OJ1d0/AsdPo910UUX8a8b+k6wDj30UHv5qTU+86GNvopgcQFmuREsLNwkBmUnMqB8ytYOP/zwR0AAuOFKv8oVcoH0C1C7BVPl2sSp5xDYpG+JdpqADY3EiA+/aWOgHF0mKFj87Bmjerb9B9yeKc6AfeQ64u2WnXkTo2DJ8bmZT8GTtKlIeK1B/j2wjWO8NQpvgfdr1Q9VgSGe81mFd+kwuhhe+Gb7oUu/SNydQt24dIvLV3kGEqfBPxWk8jiE32ch2iicWDCvA6cx4omn3HMQ4UmYESzM80yeJOBC62uZlADPE51MjhJrJSDzGcW7DVH3n0p1LlYaRNwIFjY1ksaWjqcYuFX0aJDCqzD3X0xhXOsFHGdjp28cer6ANL3cgYygvUfDDiOqKphNiC9KXwYh5ytyvjMbPVV18YVvd/yKrtV8qKpWQ981zyrLu8mErmsgTz+nLs1Nv1bNqf5hKdNCOKz2o91AoC0CIlh8HksPv4ModESw+Gb4svMP05fLlOYJFm9PPvaxfKyj4HiKQbcWvs786nHm2UkJwu3g+e1ez3RIDlmZADBOty0/0gLDhVD6me0dy/z12m7RVLlCr4txERYSo03Qvk4jJKdTOaUVXq8IQuomDkvg/wleTnb6PJUpfAeI20VKpFCkaDVOK/+Q8i6CbSJezHorvG3Gqbx21FFH0Qb1s4FgYbPTuNDOXhxPrLx7qks8j3HYqJMzV9Q2amOAuseVJO926fK4uKL6/EL9ZmPlZfsWx6Z7K66VLdHAQXzQuJuGQG6uhP38n8uTUe/DIFvXdVN/FrKnou5DJHez0NFQNRHyL80lqVEj/OUc9Gp+KzvCEUZAC+EImximTTsCIlgMFa8iWCRFZVcmU8997nNrr3jFK8piDWks+pbHk7Imjpu6SIo2uHuS7KMR3gFbtbF7w1jPu52RUCMKfbniPBnIRA2koZUs64hwNJPT5m4nWNDHjVH9YP2yncwrO8rQPwP+cFdo/QWBOgWkeEfkl0/HePu1aiMWwVrD52GwmfCvY76N+spnE3yhqogr0yKn0qcNyNdR3lKr0OUH2jsFVTZvVQ2EsBeCZc+VAftLMd+Ocfo1b3h7zZNLJ2LRT+LzJyA3vygXDDqdHhz/Ta/t8pYUYD6eZKtXHd3UQ1snwS8aVHvd2Bayk4OAX/gnp1fRk4lCQMSJoeKd3iIUIRMgrMdTsCOOOEJZlaEIFolcE0diIcIjYnJvkt0e4R/QljZKyZEMeMJDorAtvBpRmNTk4HzEWM9fr81kVUnlCpWvUORQJ1gkKJ64+LZUpxwSA98flRs75ebFB3IRnqgChRgXkR5lMRSZ8OSIJ5XKJ3457isiLn0Woo7GhHPmriT71FKdjpPYjHmSdEapwjdS+pHSX+SUxJomr2YJ5uPdeKnnpxDV6SDbMkcMFS+HsOmP8M9IvxwrF0c6EAgEhoxAJ4vokE2M5qcdAZEkhiJYVSdY2IwaoFJdFfC2n3d8rusNb3hD7ZWvfKXPznE9B5YzZiKeWJBo0OkEi3ESFm36TJvDxu/r6VaQSJAve63qIOTDyLxW/fWqOk6sEFW51+kFjGDBHgLCN7PTXp0CeblW8WYEy9vJ+gXCxAw8M1VFlCSXyRFl4ZRfjlth+hDWCnMdnJbxZIU6/xKev/R6PcInw3fryvhclRTw1o3w7lgnHqB/D+bzIfylU3of18Wpsoh5x7pCMBAIBEYPgfJCOHoWhkVTj4BIUi8Ei3+5I7fjjjvWli5dqqSF/KWgf9dWoRCJJUuW1J7//OeXs7mZ+g1VhCDfCuNJC27v8ETrA9hEj5IC5HvCIxIgXQop/lPVQchTDLLHfBKGuJdFssGpXGFZQCdYi1kAu0ge/AlWI1uta/AnKiRYIpf10vpnYV3xp0lJaD2wEWa+nvBQaGXEUkLQlePKS6GIlUhQ1pHeTv51yaFtvnyy69tqCSNTgzF9FtIi1IUHs0t2NU3yeR3cGvulE9DJVRAsB0pEA4FxRaCwEI5rJ8LuyUZABAsbWsMJlk60fJlHwxMsvGsqF/HZLN4qfOITn2h50pMFXETtuyySFk80RBYyQSERgE38hdwpaOsG1UV+FcFSnidDnrgwn9dqvl6hW3WkuhCiP7KvmVyBYMGuMsEq6GuSoI1V+rOdqV4mOylt2FTolJzwNBH0Vfkc/3YES0Qr10ntXJZCEbCK5ttm5fHFM1f8s16dQPby/FVVYyJWIm5VMpEXCAQCY4KAFtkxMTfMnEYEPMEREdItQhIrOoaKe4w8wfLlPLU68sgjs6hvI2emCGVLjqTCkyERAm2QFM8bPHR7WR+XjPI8WfEESydYnrioTsm0nFS515kLEdG1vwUzgc1KEIZMILxgKX6FS9NGb6eKfq9ICtVPZYsEKa1Q5Kkgj7GuxFWVUiidCgs60L970T+Kqo1S9fbJREJNEM9c0SaNx9Xta7eXgI0P0UaEJG5vQnzmG0H76iERCAQCI4aAFtkRMyvMCQRmEBDBwcbT8CtC5tExVHymJljE/JkpLnLmyxXvsozkRSdEVCGClU9HYEveyGGDyA5tzC/QRD2RAJUrpE5PXJjPzVwbOsuZR0K0KRMVTrraESy7RZjIgydYlbcI8dzQeXjPzzPRHn+KSRsL+tG/V0DXv3p7kMeXXPoskSCfR2z0YlbhqXLdOuMffWeMVZhC6VQobK0Y7esHCB7DkorWSdhHEmpCuM34MN7ddEmq8feta3ZcarahDf5VyQUd1wrBQCAQGEkEZnafkTQvjAoE6i8YJQ4777xzwy1CbHoGEcMqkuTzfLyMa6uysizSJBUiMCwWIVDIvLzB4xQty2Lz9IREMspTyNcYrMMpCfWQeKDaem6+nvRQ567wW8NXObWZdZaEdO3bCRb6v7IFeclV+dwQiMVvYE8lwYKe3+DdRp4c0n7+/1zWgUgmnz4TceGhUMWZYCHDx1XO0IgV2rIQp4b6D0WTQb5OsGYeyvO1O4ijD5nccUxQhc9x+THpQEtzEehfmErjFmFzmKIkEBgbBLTIjo3BYej0IbDZZpvxZZLWcf3R87XXXmsvGsVGZ/kKy+gwn54bfDMZ1uFJF94IXttll11ql19+eUEN/64nOT7MvAM8yYsIDItEKDKZQXuZRKS/waEcSeA63t5MTkRCGQopJ50UZX75WuXfbqxAPn2Vk65sU0lID8wbwUrkyp9glcRnko5o0EZvJ9+wf9OMZD0G3RmLVOaJKLOeCkJ0F+oe1qTckyofT+IW6ORKREvYWiFs1glWw/1er6RVHPMnn2C1kptFmWxTX2ahKqoGAoHAsBHo+bh82IZH+9OJAIiHdfz6668vkCaRqDIqlBexUt2yDNMsw0/la3rzu+qwjA/EJ4KnW18kLf5IRiQjkxnUz6SCf4NDPXQgG1kGSclYOerkMhAO6WQ/2ZYIEdUwL8taRuOH2mwntyhVJSHpiGBBTgSANhb0g/Rlu5NevhH/asRJvD6c8goyqPNznHpRRqRIYRIv2NWMYOl0yWwDES+QOIyvCFbBXjXQSQjM1UYn4r3I2HyArf1upxfbok4gEAh0iUAQrC4BC/HhIuCJj7eE+XUe4nPrxEl1FBYliqk2MtqcSV5EYKhA+Z44ZJIAnZmMYfOULOtJRroU1h588MEsl+oXCBbqZlkqqnAqz3oqZJi1Scqn7Z5gNb31BXtEANgvr//MpKsQpLd8L0W936QCj5OXFR4icFYGAqa+tHqzuel0JEi6TAeIrQiWSK1vt6N4v4kPftX6IWD0dpDNX3VkUAgFAoHASCMQBGukhyeMKyOADaiQpTTDZgRLFbBBKto0lL4mAiIG3PAzaULcSAbqZrIBWyo38tIJlkiA1UOdXB861ZZOsBpuETaxUdkiJV6nynyoh+TZnidYvn9envaobyR9svNHIEInFARLCdc/1SlIAD/prSynMGSa2aV8I2cgK4UTLFRdBv871D+LenpxGDsRy16qt63DF47i4flPtOhjWx0hEAgEAqODQHnRHh3LwpJAoAMEsBmZFENs4A01SKokMwcES2SFoQgM27R8RyB4y1FkoWAT8jt5Bov/t7cWXnXZVqcnWAQBXZ5n9iH0v1qUPoUkMnruh3FPIIpMVjXqoYghGaswaUqKXFXJKHRFFtXtP9lULm+Vlr1GsBYvXrwap4BZnngicWDO6C3iCWhvGqJWIBAITA0C7b/STw0U0dFxRoAkqopAMU/EizKzdCIGJC+ezRnJIJlx+kVClPXviJxeOsESCctkKAnzeaTsoJdtFb4MkahlgWLEdCHLQk/6imKW+p3y8KvFNWjHE4imYEFOdvsTLGEjlQ2hw6dSFraq37s2VK5n/LpJvs82goVn5irb8ILdxvG6EBFQP/bdqgn5QCAQmBIEgmBNyUBPajexaVvXGO6www61pzzlKYWuqpyZVQSsIIyE5BWWykVqGIrIUMTyPZkBkRIJMRU4QXkB/Il4eF06mK/ngqRL4eVWKX1ALzf08rUqWS/KuDZ/K0c/fHtl2euVATkSkkywkH6dysohzFHfujrBQj3dtiuTT2sC79gSwdqs3CZ+aLAY5U8v51ekjWDBfuFQIdJb1po1a4Jg9QZd1AoEphKB8qI9lSBEp8cXAWykZjxD+gMOOKDQmW5PsKSvoGQmIbJC8uI3cMtHXZXzhagiITO1EcOrCLIMkkYGmJ2ERJpERCwben1bSbRA8JTHUDosBKmRbi+jeP7vRODkCdaZeBbo+xKqCEWQeIIl/Z2cGInAycaCar5jC319E7B7TaEAieOPP/5+lpfzK9LClEU3wVc+eF9Rr20W/mpJBMu30bZeCAQCgcB0IlC47TCdEESvJwEBESOF6pMnWJ2cYKlek1AkgqTCkx4jGZ7MwA6RkIIqnmA5jiWiUSZDasfqQq9vS/pUV2mFJos2LIQdegaL5IB5eqid8vxLFnO4/bV21apVIkBNbw9SGDg+jBM6i+JDtopoMb/Sod6DqV5Vf6wOiN15lZXbZ6r9TH6gazf0v2lb7VUWJY4++ug16bk44VQUiFQgEAgEAg6BOMFyYER0PBA44ogjsqEiVApzQYp4gtVMxtcRCavmNPm0huzCrh3ofD3ixjYQ1yZfw3uYKk9bICNCwmYlL7Kk0MvwZK6KJEiWeqqc6XCkj098F0gf9P5EFe+77741kNUJjd4oruJyKD0buj4XbC5XSGkRk6r+NKnScfYfKInxyw/IN8GtY4UtBL/coiyKAoFAIBAwBIJgxUQYOwTwC7FsMzZRiyvMBSni80WeyjI+jRMmS6aTFl/EuEgEiZE2cpINIzuOzPDlmpUEq0S8RLAshK1Kqx0Snj9KP8LsYJ9kc16KGCA4kbLbjE5nWf7TkBfh4fulWK50S4KFttU3rh+yVWEyozFw9fKtyUapnnP4EtM3DuAdUpvvt99+7+zZyqgYCAQCU4NAEKypGerJ7qgnUr6nnlQ1k/HyrQiWIyskVLq9rtMcqskkA7/K8/m5CfwvocgJT6Z0CtUs3BLP/ewF4lZ14qM6WXeKGMHCA9lGsBzpo21ez1q0n2+nIc4yESyRx7JuSwMj9WHDkv5KeZdpf+uDtr7g8uYkilt3q+E/k/oxJzqrlKCNB/DG/zJZrRKNvEAgEJhyBLRJTDkM0f1xRQAbqpmusNwPT7B8vCyndCuCBTJhpAWyJDciISRSZgRs0PNONdxyEwmRagsfhlOGIydGlsppkgbK4s+VUeS5kWloRrBMECdo+QQr1S3LkyRkQmgaOyRYkBV53MD1uawrqZwJ0J8VsIV1GjozIxWxQCAQCAQmA4E4wZqMcZzaXohYKSwD4UlVMxlfpxXBQn0RLJITT7BMBchDPtkAmSgTGpPB7aVMsKBP8pJVWCAg0FtIJ3slm5I5MFk8sF4+wcoCKdJAsICV+ndjWdin8QC9+sD7qSJWCr1oQxx9rupLg1xkBAKBQCAw7ggEwRr3EQz7DYFm5MkTrE6gakWwwHNEQDK5QR7JRj7BQrwlgSjdXpIeI1oVhEt9a9AJO0XOyt2STiM8TmdZbm35OS48v/QbyPMXBGeUhUtpnWB1e4uwpCaSgUAgEAhMLgJxi3Byx3aie0ZCxYMdhnQKy532+SAU5eKGtAhWQwEyoIu/tGMRFUlZvkWIsmakh3UanJOXLgvRToFQQa6QpiLIqE5Zr+XjoXV7pYBrgzq8noYTrNTu18oKy2m89PPhlSvtB4d8jku3RTs6wSrrinQgEAgEApOKQJxgTerITni/sLFbD7fbbjsLm5EnyVHIvX/K6lR98MSLb4N/9rOf3VAMsqITLJaJrGSCRbKB/Pz3Mw0KihlXIimSZKEjQ8pXjXKa+VV5OR+2mH3JJunxIQlRT6QI5Eq3CNl36VDo24h4IBAIBAJTi0AQrKkd+sno+KMf/ejai170IvubnHY9akbCyvUOPPDA2mabNfxbi51gJVk+e2TXDgiZ3h3FE7V1+PXgc1D2pLJOnwbpeSFeo/BsR35EliyEHpE3qwa5QjrpUh2vmvGCrCNtLPMn1uta3GakbFPH07FUuNrpb2ZPUz1REAgEAoHAJCPgF9xJ7mf0bcIQAOmwHjHEqww66h1+WdeRXDMhkAkRCxIsUwbSxrehmzEkTCeccMJdSNM3dSAo32UhHoTXLUULWT9xqwJZQV6BNLEu3qelukx6V6jrdFJHBoD5SPd06oS662E721zmdDTYSIFwgUAgEAhMKwJxgjWtIz8h/cZm33FPlixZ0rFslSDaEsHidSOycg/iZgR4UDPSU6WOeSJDCk0ukZ9ch4QmJ2YihToz2bUfuLidqrm0f4HoWtwy7dZep6r2apzCvaxsqxeIeCAQCAQC04xAEKxpHv0J6Ds2+IH1AgRKBIt/EfN1NozTKN4i1HXU1YmQIydGlqBfRK1AqJBfSKcONyNYr50/f/4uSYa3NStJFFT2fIJF3TjB+ur73ve+5UkPs5rZw7JwgUAgEAhMHQJxi3DqhnyyOlxFsI466qja6tWra/fff7919lnPelZtiy22mHXH0ZZ+RTj/pJNO+vD555//ceTpdllTMtOs4TI5ga55iUsVyEo9u4FjFWTUBogP385+i9KuDSo4H/6oVEYy2BUhTPXKgXRUErmycKQDgUAgEJgWBPTNe1r6G/2cMARAPip7hIfNa9tss42V7bPPPh09BF+pyGWCrOgEayVJz9FHH620Tp66JRllkmTXI3W7ZhktyzXLK1Wz1zlkm0C+jobuN1EI4Trc4stlDRU7zKCeJKqww5ohFggEAoHAZCMQBGuyx3die4eN3fqmcBAddW8654Pt3tl15Mp9WdO4IyciaGKLBUIFYlcmXDW8i6ojQuNOsGSH6WY+2tfpk8q6DqFHr2yQ7V3riAqBQCAQCEwiAkGwJnFUp6hPgyRY+MWgTqzq9x5ncG7425yZouaxCvJj1yPyC4QKfSykqRFkrkDCmrUCOREx0+HafARlsyZYsE0Ei7+sDBcIBAKBQCCQEAiCFVNhrBEYJMFyJ1RlcmPPMoKAiWx0imlZj67HQn6ZcFE53mFVkGnWIGwSwZKI1SNpw/8Vlssk03HoCFs8z9kxaiEYCAQC04CAFvRp6Gv0cYIQELFSOIiuuROsMrmx0xuQHp1wdWQObC8THLseSX68gnKaZfilYNkGXyXH3QmW8qweSRveH9YtIZQOH+oULE6wPCoRDwQCgalHIAjW1E+B8QQA/MAMB4EYWAccgSoQIBhgpzd4rVRXBAv1RJLs+SUQKT3HpHzrG8lQuZMrVqwok7OyiKXdCVZBB0mbe0i/sm6Hmfy7HDoRrXoqPgOBQCAQmHIE4lh/yifAuHZfnGOQBMsRqAJZAYa6jroiGehDmSQZW6wgVAXClcasKq9hOHmCBZKV80niiF1FG1mmy8ivoPIEvCX/k13WC/FAIBAIBCYaAW0ME93J6NzkIjBIgoXbcmvwFzUEc4ax1KG16wjlZcLUEngQE/01jsmB9FSeYNU5UZHT4QWn+f1bLRuZOVky3WqDOtvU66gYr34gFmd2JBxCgUAgEAhMEQKDu78yRaBGV/uPAE9h6AZJsNCciFWZnBjBAmnp6gTL6ROx0vWodtjFytOmTgkSTq/0nJU9I4V6IlrlPlhb8REIBAKBQCAwNwhoQZ8bbaElEBgQAkMiWLpeCgQInOWf2e3NN998RTfdRx904mWkB2TxMtZHeKnX0ymZ8nUUx6ka/8qHzv6HcK5PsOqq4zMQCAQCgUCgjEDcIiwjEumxQmCQJ1i4PWgvGAXh+VcPEm7XMa1TKF/UMg49hVuE+PudX59zzjkbH3PMMTp1svogRT2fNgGfh5IR/o+emWVkETb8JdRfmWQiCAQCgUAgEJgjBIJgzRGQoWawCJBY4aHzgd4ixPNG911wwQXzX/WqV+nkabadLpyEUVmZXDGPJ1i9ciz8J6NOsPRrv1upE/qWMAQ5/BeG4QKBQCAQCATmFgHd8phbraEtEOgzAnhlgrUwyBMsNjiH5IokR0St3elXAxHrFN799ttPBMtOshYvXvwj1P0Gbh3yj5/DBQKBQCAQCPQJgTjB6hOwoba/CIhY4XSnvw31UTv6UHiFQrOmej6+gkISQpy8UfXn+fHOd76ThOvPGQ8XCAQCgUAg0D8E4gSrf9iG5j4ioBOsPjYxCNUdnUzxFuEsjdkItwJPnaWOqB4IBAKBQCDQBQJBsLoAK0RHB4FnPvOZtaVLl46OQT1Y4t6y3rL2bE6wqBgnWKvngKS1tDEKA4FAIBAIBIoIxC3CIh6RGhMEdtlllxr9mDudYLW8zzmbh9zHHJ8wPxAIBAKBsUUgTrDGdujC8HFHgM9gddKH2Z5gddJGyAQCgUAgEAjMLQJBsOYWz9AWCHSMQKe3CKFQJ10d6w7BQCAQCAQCgeEiEARruPhH69ONgIhT21uE0w1T9D4QCAQCgfFDIAjW+I1ZWDwhCLhbhC0JVtwinJABj24EAoHAVCEQBGuqhjs6O0oIdHqLMH4BOEqjFrYEAoFAINAZAkGwOsMppAKBfiCgW4QtdccJVkt4ojAQCAQCgZFEIAjWSA5LGDUNCOBlqfoVocLKbscJViUskRkIBAKBwEgjEARrpIcnjJtkBPBn1SJWa9v0s6OTrjY6ojgQCAQCgUBggAgEwRog2NFUIFBCQMSpJcGKW4Ql1CIZCAQCgcAYIBAEawwGKUycTATmz5/f0QlW3CKczPGPXgUCgcBkIxAEa7LHN3o32gjoBEtEq9La0gnWw5VCkRkIBAKBQCAwUggEwRqp4QhjphSBlgTLn2AtXLhwZ2BEHy4QCAQCgUBghBGIP3se4cEJ0yYeAV1/HT+DdcIJJ9w18ahEBwOBQCAQmAAE4gRrAgYxujC2COgW4R1teiC5NmJRHAgEAoFAIDAqCATBGpWRCDumDoETTzzxJnT6yEWLFr27VefxlzrrW5VHWSAQCAQCgcDoIaBbFKNnWVgUCEwBAqeccsqX23UTf6kTBKsdSFEeCAQCgcCIIRAnWCM2IGFOIFBGIE6wyohEOhAIBAKB0UcgCNboj1FYOOUIxAnWlE+A6H4gEAiMJQJBsMZy2MLoaUIgTrCmabSjr4FAIDApCATBmpSRjH5MMgLxK8JJHt3oWyAQCEwkAkGwJnJYo1OThEDcIpyk0Yy+BAKBwLQgEARrWkY6+jm2CMQtwrEdujA8EAgEphiBIFhTPPjR9fFAIE6wxmOcwspAIBAIBDwCQbA8GhEPBEYQgTjBGsFBCZMCgUAgEGiDQBCsNgBFcSAwbATiBGvYIxDtBwKBQCDQPQJBsLrHLGoEAoNGIH5FOGjEo71AIBAIBGaJQBCsWQIY1QOBfiMQtwj7jXDoDwQCgUBg7hEIgjX3mIbGQGBOEYhbhHMKZygLBAKBQGAgCATBGgjM0Ugg0DsCcYLVO3ZRMxAIBAKBYSEQBGtYyEe7gUCHCLgTrPUdVgmxQCAQCAQCgSEjEARryAMQzQcCHSCgh9yDYHUAVogEAoFAIDAKCATBGoVRCBsCgRYIbLjhhiJWCltIR1EgEAgEAoHAKCAQBGsURiFsCARaILBu3ToRK4UtpKMoEAgEAoFAYBQQCII1CqMQNgQCLRCIE6wW4ERRIBAIBAIjikAQrBEdmDArEBACcYIlJCIMBAKBQGB8EAiCNT5jFZZOKQLuBGvdlEIQ3Q4EAoFAYOwQCII1dkMWBk8hAvoV4dop7Ht0ORAIBAKBsUQgCNZYDlsYPU0IuFuEcYI1TQMffQ0EAoGxRiAI1lgPXxg/DQjELcJpGOXoYyAQCEwaAkGwJm1Eoz8Th0CcYE3ckEaHAoFAYAoQCII1BYMcXRxvBObPn6/3X8UtwvEeyrA+EAgEpgiBIFhTNNjR1fFEYO3atSJY8ZD7eA5hWB0IBAJTiEAQrCkc9Ojy2CGgXxHGCdbYDV0YHAgEAtOKQBCsaR356PfYIBC3CMdmqMLQQCAQCAQyAkGwMhQRCQRGEwF3izBOsEZziMKqQCAQCAQaEAiC1QBJZAQCo4XAggUL4hms0RqSsCYQCAQCgbYIBMFqC1EIBALDRWDNmjVBsIY7BNF6IBAIBAJdIxAEq2vIokIgMFgE3AnWg4NtOVoLBAKBQCAQ6BWBIFi9Ihf1AoEBITBv3jz9ijAI1oAwj2YCgUAgEJgtAkGwZotg1A8E+ozA+vXr56cmgmD1GetQHwgEAoHAXCGghXuu9IWeQKCAwJIlS+YVMiLRCwI6wfpdL5WjTiAQCAQCgcDgEYjNb/CYR4uBQCAQCAQCE4rABz7wgcNx6nwBunfqKaecctKEdjO61QECcYLVAUgh0jsCy5Yt0y/gelcyIjXjNG5EBiLMCARGG4GHknl7j7aZYV2/EYhnsPqNcOgPBAKBQCAQmCYEFqbOxh2iaRr1ir4GwaoAJbICgUAgEAgEAoFeEMDtwY1SvSBYvQA4QXWCYE3QYEZXAoFAIBAIBIaOgE6whm5IGDBcBIJgDRf/aD0QCAQCgUBgshAQwYr9dbLGtevexAToGrKoEAgEAoFAIBAINEVABEthU8EomGwEgmBN9vhG7wKBQCAQCAQGiAD+eUHPYCkcYOvR1CghEARrlEYjbAkEAoFAIBAYdwR0chUEa9xHcpb2B8GaJYBRPRAIBAKBQCAQcAgEwXJgTHM0CNY0j370PRAIBAKBQGBOEcBrGoJgzSmi46ssCNb4jl1YHggEAoFAIDB6COjWoIjW6FkYFg0EgSBYA4E5GgkEAoFAIBCYEgRErES0pqTb0c0yAkGwyohEOhAIBAKBQCAQ6B2BIFi9YzdRNYNgTdRwRmcCgUAgEAgEhoxAEKwhD8CoNB8Ea1RGIuwIBAKBQCAQmAQEdGtQ4ST0KfrQAwJBsHoALaoEAoFAIBAIBAJNEBCx0klWE7HInnQEgmBN+ghH/wKBQCAQCAQGicAmqbENB9lotDV6CATBGr0xCYsCgUAgEAgExhcBEaz549uFsHwuEAiCNRcoho5AIBAIBAKBQKCOwKYJiDjBmvIZEQRryidAdD8QCAQCgUBgThHgCdZKajzllFNij51TaMdLWQz+eI1XWBsIBAKBQCAw2giQYD1AE3faaac4xRrtseqrdUGw+gpvKA8EAoFAIBCYMgR4i9AI1vLly4NgTdng++4GwfJoRDwQCAQCgUAgEJgdAjzBup8qFi1aFARrdliOde0gWGM9fGF8IBAIBAKBwIghkG8Rrlu3Ln5JOGKDM0hzgmANEu1oKxAIBAKBQGBiEVi/fv08dI63CO0Ea9WqVXGCNbGj3b5jQbDaYxQSgUAgEAgEAoFAWwTOPfdcvr2dJMuewVq4cGEQrLaoTa5AEKzJHdvoWSAQCAQCgcAAEVixYgVvD9LZCdbq1auDYNXxmMrPIFhTOezR6UAgEAgEAoE+IKCXjNoJ1vz584Ng9QHkcVEZBGtcRirsDAQCgUAgEBhpBDbccEOdYBnBWrt2bRCskR6x/hoXBKu/+Ib2QCAQCAQCgSlBAL8aFMGyW4TodvyKcErGvqqbQbCqUIm8QCAQCAQCgUCgSwQ22GADI1jz5s0zgoUTrTjB6hLDSRIPgjVJoxl9CQQCgUAgEBgmAoVnsHCiFQRrmKMx5LaDYA15AKL5QCAQCAQCgclA4JFHHrETLLwPy06wcKIVBGsyhranXsT94Z5gi0qBQCAQCAQCo4DAKaecsjHs+Cj8iYjfM0ybcGtwE5ArmmAPuYNwBcEa5oAMue04wRryAETzgUAgEAgEAr0jAFLzAtR+M/xRvWuZs5qFW4RxgjVnuI6loiBYYzlsYXQgEAgMCgGciiz94Ac/+MRBtRftdIcATowWsAaIFt+gPlQHW/QrQjvBgjFxl2ioIzLcxoNgDRf/aD0QCARGH4FP4VbPr0477bSdR9/UqbRw69Troe9nvEUIW1bBr6VNcYuQKEyvC3Y9vWMfPQ8EAoHOEFhKMbw0clcEt3RWZe6kcIK2x4IFCx583/ved9vcaZ3RdMYZZ2yDv3R5F3L4DNMjMyVjE9uRluL0aNsRsJi3CFfi7Qz4AeE6nqo9D5h+F3k7IFw9AvaFCQNEYOiMf4B9jaYCgUAgEOgFgXWpEv/Idxju2jVr1tzUr4ZBrk6F7vfC79+vNvqsd5ukf7s+t9OJes6RVcauEAHp+wsEW8I/Cz7clCEQBGvKBjy6GwgEAl0jYM/24DRio65rzl0Fe85o7tQVNBlxxAPZIpKFwjFIiPgqHJrJIFS0YTVPsJIRf0jhXkMzKhoeGgJBsIYGfTQcCAQCY4bA0DfwPuFlj4qAQNpzQ31qo2e155133gLcXntGCwUin6PwSgTOkTUOSyPlSI+CbS0gjKJ+IBAEqx+ohs5AIBCYJATsBAunE8M8weonntr8R/L5q+XLl78Pnf8P/MiAz8BVuVEjWKvxvJ5OsPiOLrp43rmOw1R9BsGaquGOzgYCgcAsEJjUEywjWCP8ty57cMxAcEVWykOocRFRLJcPMk1bVuNHCSJYsi0I1iBHYUTaCoI1IgMRZgQCgcDIIqD3K2mzHFlDezTMNv8Rfimm4Q8CaK9Ir+jjyJ1g4UcJIlh26glyOArkrwK6yOonAkGw+olu6A4EAoFJQMDWySE/5N5PHLX5j8wpywc+8IHj8NzVD1KntU8pLGMhgjUK9tsJ1sKFCwsECwaPgm1l3CLdZwRi0PsMcKgPBAKBsUdAG/hEn2BhlEZmP8CJz4fdrDFihRM2jYMrsqjGRUSxXD7ItBEsvPoiCNYgUR/Rtpp9IxhRc8OsQCAQCAQGjoBu80z0Q+4j9tbxhzjKZ5555lYItE+JSJUngIjXKBAs2sIXiuoXmZozI0Ney+BFun8IaOL2r4XQHAgEAoHAeCOgTbLZBj/evavVRExGiQTcRFDxLNMeCOwZLBBAEaky3spXP8rlg0zbCdbixYvLJ1gDsw3/m3nQ6aefvtMgOx1tVSMQBKsal8gNBAKBQEAIGMEaxjNYuFWmB+xlSz9C2/xH7CH3e9lR9J//M6h9qhnBVf7ASEyLQaAta+67774ywRoYeQURvQTEdFkLG6NoQAho4g6ouWgmEAgEAoGxQ8AIFjZ7beQD6wAe9h4EabA20L9MAnhrDm2/eGAdbWxoJbNg0xYIbJ8CwdVJVVla+YPAqtx2Oc05snq//fYbGsGSQfiRQOzvAmNIYQzAkICPZgOBQGBsENAtQoUDMxy3mkQe+tmmiJXC2sMPP/xLkJtvDXGTXsUOg1RlgoVkM4IrjEaGYB1++OF6aavmTMa2nwPpdW+88cab+3TEB49AEKzBYx4tBgKBwJggcMEFF3DT1sbdbIPvW2/wa7RBtGn9A6FSP9mfPVOnmr3cs299ToplUycESxgNnMRUgEBbVoMY8p1dJFmyzWNbUW1usvi3QtK0atUq/kAg3BARCII1RPCj6UAgEBhtBK644opFzkKdRris/kaxSeYNs48tiZgo9E1t6hPdxnECNh9+227rQV7EJBMsEMBmWCh/ICSmTV+MYCUZ/ZKQySps26jqvhh/K0S8zOGZuoETLDxgfwBuLZ8sG7oJUe91mCtHdFNn1GWDYI36CIV9gUAgMEwENnONa9N3WXMfxSazWFrxlysiD3weqV8PvNvmj1MXIyho359a3YH0wbKnh/AfUeeOHuoJaxIG9Vt5ZXXCqC3BQl9OIQkoK5jDtCdYeg6L6gdCsDbccMNMsPCw+8AJFtr8LebpKb3giXqfQ72v9FJ3VOsEwRrVkQm7AoFAYBQQEMHi7Z6+n2ClB8vvPfXUU/dk57HpZFKBMhGJucZFbYgEbO8bAPF6gU93GX95l/ISV19JNm2fgh3Kk4xC2d+SYCWCejJIwNdVsQ/hUAkW/k4oEyzgNXCCJTzTrXUlpzbUBTW1AETHA4FAIBBohgBus2yODZnFK+C1kTcTn3U+SMAhVII290Bw7dq1az2p4HrNl1jOtbN+oW0RlALBQn7etHtouFfMVI+hDgKUVzZDGMn+crmlQVD10PfDlQJzk0kSrjHyJ1gtbZubpgHUzHwlOR8awbr55ps5VvZL0Nn0jUQNt+nXgiz+9cknn/zZ2egaRl1N3GG0HW0GAoFAIDDqCOgE6y4Y2vcTLGwktjljcxRpyKRik0026dcmrTb0hdvfIuT45FuWPQyWYYb+6DZfpypkE/ts+5TDpKyDWBG3lvjMnz9fhMN+oVhWMkfpTTCGIhaeYAnbOWqmWg2I+SYqGeYJ1lz9OOP666+3ZwAx9seoX+MUBsEap9EKWwOBQGCgCGBh9wRLm34/bdDph7WFEwkRLZ5q9WuTVhvSr1D9nA3BMt3nn39+Wad0NwuFNeuJOCmvXIf5JE2SK5dbGvhtmQpEgCrlZplJQmB/84Nw4AQLbYocP4C5K0I5yy51Xx0/zuj5y4j/JeTKlStFGIfWl+57P1MjCNYMFhELBAKBQKCMwEAJFjbFNTQApw9l0sNbPt2SlHJfmqWNuKBNEZRyO233Cdx+ezb83zVrAL9uU3+aiZTzRaZaEixgwpMxbuYPwpftLugEwdIm3ReClWwhIRDBGvivCNG2CNYyxPkW/GE5jV/X7d91112Z0OPUMQhW1whGhUAgEAgE+owAfjC2KfxX4Ht5TYCsE8G6Gxk9fyuXsnYhSI4RLGzW1hZIgUhPPwmWNmUjKI7cydy2myXs/SH8p1ShHOKll70SLPbfCF6FXTWQOuolySLBylgh3uBQXwSrL7cIzz77bOEoguVPsFra1mBsjxnoowjJcqg4GnP/f/WoalbV8GvGnq8V3F7McwXPIKo/mXTNyrABV277zWTA9kRzgUAgEAjMFQJ/AkVHwB/Vq0KQBr4Hiyce9G2JRq/tqB7a06Zsz57gFmHemFFWeUKDXxzujY10Pfz+0tNlaJsY9KutcjsiDl2qnRHv4X1e2mRpi9kF+6rsUF5bggU9IstGYmesm5sY+qh3hlURrDKmc9NooxbiwZOzx6Wi/9ko0lsO5teN8F9mbRBbkre9Wmjq+VrBqZXGng/ti2C1aGp0i4Jgje7YhGWBQCAwCwTwbV7fons+sUgnAiRXfDZK+mZhVeuqaM82F4T2glN/goVv8yJABSWQeX7KOKpQ0EECm+ShENOGZiQAREZpaRCJUbrr0L/Pq8PK2qAzwUK9qs1WtnVCsERyKnHs0K6mYhiHUSFYnO96FcV6/0xTU+M7K1gKsVdTFHPkHxF8h/Eqh9dF9Hyt+F/OAtOqMa9qciTzgmCN5LCEUYHAZCOAjf35OHl5zMc//vF+LqC2+YKs9PyzfGwktI8bFnVo0+/n4KgNO23xJ1hoVASh0D5sfGzK6OU2yk+cMulXqCKRGKW7DmFjWWc7HcKBZEiEqGGu4LRDG3k3BKtMINvZ0lG5bmdhvg37BGsVXmnwtzD6z+Hn3XnnnXP6LBbGUr8ILcwLl0+8NH6Md+VwezGPD7BsGPOulA1ZOAjWkAcgmg8ExhEBvg0bBOlRs7D9e/iWe8V999132yx0tKyKBd82X4Q9Eyw0wE1kYCdYzmYjWP4EC3Y0IynbJCB0gpKSHQUZG2xmIjLWDtJ/lTQUNtKOtJaE/KlEqaghmTZq9ZWh9qmG/kFWtnVDsETKGtqeZYbZhzHjfKHT7V7GDVt8sdgf/hfnnHNOX2wAHiQkKzF260HO7dpas2aN5gftmLU799xzRZ7sBXFSiNuGmj+8tddz/7AuvBy6Xp70anzVzFiFmrhjZXQYGwgEAsNFAJvIb7EQXjcHVmx+xhlnzOkG4GzS4ux/zeWKO4rahgXJQZ9g2S1CR3porEhH2XC9QNPqlAvbpH/pykWs7AQBm/XXUHY2vHB0ot1F/alEu5oXXnih35dokzbudgSrGT7WJPojPYX+gPDsAr9HO7s6KJd9OsHy8062nQQ9T1qxYsVOHejrRYR9s1vimDt3JgWz+ZFHgw2wndcEXYFgLV68OJ88AWuRsLpkm8/Sm9/PRP1vsApCtdVGw2gWa9BH07qwKhAIBEYaAWxMG8Pbgt6poR/5yEcWPfggDxzqDt+wD0TsR0rPVYgNZhEWaL7yoOdv07BFBKsvz2CdddZZm+Ph6Jfgls6/pH5rY9ID2X6N9vEacH8G6nBTnw3BIun4HPxhwEoERO2QIHBsO97koANwz1uPOgUHMp4330JBRQJv7pYdJLWMKy0C42uJLHVzgqU60nNTiujWl/K7DWWfCJY/wRKms3krfif2ZIIFzPlyXM5/+wKD+bIPkl+AfxbiXV2z1COH27Kb40SSyQLBwml0HmPMg66uOYx5rqt2YOMGsH0TXsPj6vw3hXHtQ9gdCAQCQ0IAi23Xp08gFNuXzN2rlJ6TJBZmeyap28W+1DjJBTcjEiyRn5JI70m8SPFTsO9LZ555pl4hoDaMYKFM5IK3XXI8tfgfCL8LLzKmDb4bg/h8zgp47phGAtAmN7tHsMFxA2Xfy4QEWdWu2QtFYXvDBlqtwXJFRtg24+p3FdGTbW0JFjZr6VGdFib0VCS9Ii9VBMvmJLRLtqeGWlTSF4Lafvvtx1eLYDjX6xp9O9JPxlg8pkX9tkUgV5qrBYK1cOFCP8aax231JYEq+R1hex7z0ilXpV7M2d3h+YvafSoFBpwZBGvAgEdzgcA4IIAFals8Z3VQO1vdYttONJfjm/V2TGDDOxbB9VhE+0KwoFu32br6Nk3bnONGyGdaeJrSVA/6MA+YHeLqdRrdk4K45aoNRm0YaXKkgGIiHox7N5sTrK3RBgkWyYD0M7QjCpTxeaKOycDy5ctlP6rNOPTPb74zBdUx2UHMGdc+1UAgoVdkgQRrA45DtUrLld6O+9NCV0MRsLK+b7TRRrSbzhMskTs7wZrNM0p11U0/SUis/Ve96lVsn2RPuNmzYcAsk5ayFp4uYx5/Cv7gcplL66H5AsHy768SFq5Ou6jmf5ZLr2vIY3XjjTfmeBZqjByasv60sWjwOZq4g285WgwEAoFRRuC/sBBfUmUgFl+/0GmxrRKtzMPia5sMNsOvQ+BOeH0jrpSfRaZteGinctPvUC83I25MPMFa0GwDTw/l/jeweU6HeiVmWOA2qTY9bTRGDtGeNmbKiyCorsLZECy2y1ta3CxFTtiO3hXV9gTLY4JTjEqsezzBIlFg/4WBiAKysjsvxUiwanx+C2PxZozDPVliJiL88vyd41+x2tiBGHCu0HmCpbY1VtmGuujsP/GF6H9Ay5Hwf3Ta1uB6E7k1goWyKhytCm7dH4bI38EfYRkVH9CnE7ECwUqESDU0j5VuFzbI48sbx1241WCbrpFWuuyLga/XSrjfZUGw+o1w6A8ExhOBfVqYrf90o0jXBEuEB+9G4gbadAPHrxT3xWZ5dAs72hVps1fYTr6qnIs6NybayRcsNtO1C8vhltSDjj+FpTZcbTTdnmDdjhabbpzeGhIiEJC/gj8K+XzGhePAzdKITNqQtVHZ+HgS5XUx7m8LQk72F8S6OcECSROhYtvcYJUubLDeJthsBIvPbyH/eNTZAv0r2IJ86TGsWR+3q3V7tWBvjwlrD0SAeNJVESwrAB7N5pGV9/IBnSekestdfZI9swsYGcFCWMDRyTJano+lYkvqmi8QLBAiETnel+yqf1VvfkfehmkuygZdI0o3hJDXF4NMzBqEBpgRBGuAYEdTgcCEIKBFmLf5uj59Qh1bfHFq05Jg4VbiN7FQ/yM3wh5x0yKvsBc1BYKFv3yp1IU+aTPtdk21DR4nPNr0RAosH30XKeCmlTeNEiasexu8nXq16yROOl4Imc/DnwfPTYzjQPtlO9uxjQrtGFlwP81HUdHhtmDeWLHJV26CaCPLFGs3plw/2bYnWAUCCbJrt5qTBnuwHL9kI17LU97SFCoQfvxhxntQfxVua+lESTI9h7Cbc2M9frCguSCSSp1qW2WVOPXceL3ipan+x5yeNbDLsEdoBAuh5poTy1E9I2Ynqzm3GKkkWKVfimoeF2s2T1XhQcyEWw36W9ltmtE3rRW5XvMm+1+iC6r/LUULgUAgMHYIlE8B2AGQAb8pabHtpm+2+C5atIgbKBf9qsU168MD4L3+zFyLfCUpyg20jtA2nqTYCRZIXzNb9W1+S2DWzSmW1QMx0eYhW/X8WCZYsCFvGh/60IcyyU3m34BwU7fBpOzGADL7+lykOQ60w/YDpLkhGzkAMTKi9fDDD+e2fV3G/f8MAp/r0H8jQv6h5KSzXLUyDVm1RbvYf9pFYqLxRNScTg1/gDp2ggXSzrrLUvnuKVQgvSSvZ8IvRP9erMI5CGnfaujUz95Epqha42h5kNE4z0GzWQXH7Srgf2vOKf44w+Yw2vbXrxO1qMqafnEC1rrmff9qGPtMorvtH+pq/md7kMfTyKyzSiYLpwjaNT0Ic72yzCDTmnCDbDPaCgQCgfFBgJsRH4LODmTAn5TYSUsu7CCCRdM2l3QrhYt+s8X8bqrDrQdupHcw3qXTJqawy+ombpsmYrY5wfZKgoV8baqfgCy9vkmbkhYfOuWQXpGIrbBR8qFtbcw8wcpxnLy8qaTzeqbT7TrdJimJ5GSBsGIzehi6M8GCFPcFswv5tolic2u6V+A2W3kz4ynIQ7feemuu082Gl569obHEnDrYb51mIVp3IPqLMBd5svEW2HcAc/GrTMreV5douH2d8UvlxPTpis82RB83gj7aKScCQiyFhYi4xluycxFSp81Tp4xzQeOjAxWdUjmxHFVZs2uSgiJY6otV5nN2HI/kNI+VbhcWTicpDH0bQp9wY1ZBJ64PfsngGvFSxL9FAeBvBAvhbK55qpoTJ8DnRFkoCQQCgYlDoIFAYSMRwbofC1lDeTsEuBFBhq8B4MbDDaHh22vScQ9DtLFLSncbaJHdCG0txC2hl3arAPJc4PmgcEuCBZnC4t9FO0aGoF8YUA8JwsYgDrsh35OCvNkAkzN8G5C7gWmQ1izjy0txf2uN+BZOsCBrfU51jGiBRHk7CurK/zOIh50Nd3/qhTa0yRfqNkmoDyJVbJvxgg7otE0ZfX8I3shMen7L4sgTpmpGepX+ESK9/PJT9cshx47PPMmJYIkoMt/yYLvmpmSbhpi720O+E8JeRbD8M1iGH3TplKqqTRGsvdBuJuL+NBKVRLD0pcL0gAzl8emmf8mIBoIFfRz3rJMELslagPTOKf1qly89rfroxPsbDYLVX3xDeyAwdgj4xRybvMhU7gfKlXcrMrteyNLiq42Im0+zb/N6ZkS/Wso2dBjRJrYxNtt3oN1vYtM4sMO6EuOmzE2xHcHSwm710M498C+TkhahERiUCwNu0pdQHhvM/gg8KfBximSHvi1nwr/sMRc2Rrhxfk/ZwIbkhUcPIlHcyMwuERekm7aN23KFjQ+2GBb+1At6CjLQ18qpLdpFm0SwlK+61g422ofQphEXnOxR1sgI8soES/1jffaXmGmTJtHshMSwbjPXjGCxH7JdRzwa72a6LB9zaHdEbsOXgw8j/qGWwvU5ZPPUyfkTLNlAO5s5EaztIXC7hPxpJPIkU+YP0s9qrdqQ2hxifpTHSu99o04bW0/gWBFpfVHIdZ2ertelbMwcRsoAzaHqUBUIBALjiMDZZ5+dF39sOg0nVFjERLBuQ/8ayjvoMxdfbjp0rQiWLdJor9UDt3Ut1Z9a5Pksh255cOPoxnFTJtnQxpWxKSkRJsqmzc9VokVoJ1iODJAU/jHJb4t8TwpsA0NeFREwwlp62WOzZkmw8uYJfRwLbmLaD9iO2YVQBNBvnsiecSDhBfIEfUZ8/K3DUj9mKlfEeGsoZRNztku7PElJxfVfTeIZsHyChdM01jV73GYred8HPhTPE9KcBxJT6IcqdRqijxw7zWtWM2KQ8tQnaw+2Ubatg9xzk9CxCI9HG1VjLz3l9pmfT7BQV/3LfVZFF4o8MSu35U8jkS8Z9UnVvd6O+qeKCG3OuDQJlMaSY0Wn69kSwGYHi7gTcPRRepby/1JT+dACXVBDMyAaDgQCgdFCABujFil+q28gUMgjmeBGci98198U0+aijagVwRJp4bMWvTgt8vPRpp2GuUW5U33cNNaiXjuClTFzivMG5fLKUW3CIm7cRLihrCbOaNdvYraBgQjYN3aU/bWUIW6EyL/sUWUVIW21h8JTGTdhnqxoP+BGLGJlIW77eTtStXqAkypt3JaBjVEnCn7D9fFC/YqEZEWq2DbjhXaAj7Xzjne8YxXihiNO0yhrG7HKnX7pZRbnA+dvdptssonmS87rMsJ2dTLLqsJQRJF56oPGm3lNHfrwKF/40Y9+tGqeSYQ6NU+VV3WCJRsk40Nec/Y8n8/0p5HIl00FwoN84cv5Wy7z6hribqx0PfgTLF27BbtRRwTLz03NvWdjHv62oaEBZ+iCGnCz0VwgEAiMKgJYmPIijkVMJMebfNSypgAAQABJREFUS9LFDfp++AYC5gWr4tDpv2m3IlimG/KzJlipTZqztMqmFnkkZ+vgbeOCnmYbYxVO+RmWFvptDYZ+bQzapB9EHv9LkZuH3VZC2jYSnFJZWyi7C2XckD4Pr81cmxyymjpuVDqh4kZG8uIJFnWYPrRhGx7CpnpRv7Dxoa7mT65D2/Fes8fgNtdt8Esgkx0I41uZnzNmNmraxT7TM74B5PyexXb4ln3+AaLZmYigiJIwhZg5wy/FdYKVkvaAvOpZHvo8D7a94Zxzzink5wqNEcp5giWy0ECwoLtTnYVW8Ixdq9PcKoJFe0R2NE4KC7pTgphdoQJiwDjWhDyWSOrWnPSauOYnEsS2bf8wljoJY32OJW3NBBFtcrxoK/Xxy17Zbj0L5tvS3GOVGuacyKClB/3hJ+ug2472AoFAYAQRwELmF6kqQsENngTrAfiuT7BQhwsiN0y+R6sVwRJpqSRYWKCfD/8c6vGOmzD8XyJPGyw3B1uM0bcPdLFhUi0X+bUgEVr4q/CgnNpiXK6TZ8ds44Jdqs9Ni9g8iDydYBlWyDNZnCaI1D6Ady4tgH8DZI0wlW/XyZBSKBJn2djIqL9MsETAjGihTU9OCupQv7zxaf7kTRn2bQgdJ6Li9vBP8ApQ9tGUr2zVo12Ms23DYKeddvJ2sB3bfBGKEFJeG78wRZY5ltlpCMIVmHuFEyw9nF8XtZfKPhm2fWbFihXvANGiP1llTUKNnYpFsNQP5qtvzeaR6io0gqMEwoZrgX9pBdv+DmVVBMufYGmcFDq1OUrMroY/mjl6HYg7GV3O/OTUl3KaY6IxUFkhTNftvbqNh7FguxwbzTuuDRxrtqExLuvUPPMEqzDmmHPXoQ+tSCnU988FweoftqE5EBhLBLCpaOGi/VUbgQgWT7B6JVj2TR9tcVGtaoNttyRYKP8e/EUU9A4L8+FIfxF+j5TPRVrfdhdgwzws5XcSsO5aEBcjWLDXL+a+ftWmpW/6Xq4c1yYlDKif2JDA6gTLsELaZGGDESyQPp5y8fRmPeK2MWFDqbIDVQuOMnkjQ99IAEiwRF5YboQFekUSZCeKGlzlxufJXtoshZ0IohQV6qeTC5aJmHCfYrz8K8lMsICJ2ZmIoPTtjI1cuLK6jSUjcFegToFg4fUQss8EYLPmNsfh4/CnWEHzD7arsaKUfmVH2/kcIMmSxqfQFoWbuALuGI8GsgC8LoHuT6E++2o4OV20R3hIl4UkN8BHeapiRAd9v5EZwFNjJbm7JYhQfbEs2KD5w2u6Xf+ey0qwfSerXD/BEpFKWTZebMPyYZO1xy9IsJtzQuuUH2PlSQf74Mtz/iAiQbAGgXK0EQgMAQEsQkvgH91t01j0RGxYtWpxEsHiwlf4xthhW1zwtRF0coK1NfrR0Us02T4W+t1KdnBz4O2I7zAfC3XDJsX8Jm4+9K3bcsst251gaQOimnfAnwvvb4Ewv8qpnnDUJk2CtSls5aZF8kAvWW16PEE0hzEzwoQNuLDpqbwUqg3LxgbEsaB+7QdsRwTMiBbSahvRoqtoU5ucr8O4CEe7W6eqR8zZf3qbL6VfSRIz23xFBEHqKCtCcQTi34KXY9m18A9A/mMI71EBQ1QtkwLTgzHwpMlXKcdZ38vq9MnmDv8nEeUan6rrqqyPaWFhZRjnVnOX7Wuemjw+aI/azCGvJ+j6Lco+JMEUboL+kiBZPzD3haXs4LyU4/ryT+edd57pTXOVZRwT1ZNsOdwuZdgYoB0jdsiz2+EsQx7Hi+3aGCNt7eALEvvI8dM88+Om6wjFdef6oKyBhbqgBtZgNBQIBAIDQ+AWtPR/e2hNCxerVm0EJFjc3LnweVkkO3JcED3Bmo+FWgu4V8B2uNEfCP8gboO81he2iJdvo1A3F16eWHBxFkFBtK3jIr/2qKOOItHg4l+FB5Vo8yKBuxrpO+EbFnsKlpz6Lb3cmLi5EVudYJH8sH2TxYZh9mODzJsdCIMRIuRlOyDfzLENEaha+k9If4uQOkSsLIR+4lDpXJsvTgI2J2Cn+qbNUnh0SrA0R7hPiThknchjOyQDPAkhRjytoJ1+c38e85Nj3Tsx1zY/6aSTLkWfCidYqOs3alaRnkyaULeV7ZSXzawvQmm2p1cdaHw03pRr5Xx/2305oE7hJJ0cZ/VDuhbgOT6NxXMlmEL+NyWfa1Ofy3XznEvyb8RfJT0pxaWfc7eMZRLJgXAUB+E1ex+8jSOlEmEjXjbGCGULi98Mr7XHt6U8ypgLgiUkIgwEAoGOEejyWaKO9UIwL1JY5LQQ+/p2goUyLnxV5V62Kl4mWJQpbDjYyLjwUveV8CJMeyDe4LCA6qRAZVspkkIu/NRPe0kMGwgW2jsC/gKUlR3r8leE3Cy5eWVsSoLaOLkx3N4OG7T19/DHQIc2JeHIv2/hJs2NTM9gGcFCP0VyDCsQI208NEWESPqY18zRVm6gv6AAfnlHPZ5gWZ9ZJuKCaFO9sNf6jmeYLoMcn22yvjjipc2S84Zuu3pQ/AQettmivvrpyYri3o48j0CWbGNORNBvxP6WFvUKJ/atQLBQ12/UNE56RDaYdwc/mjjW97Jqy2xPrzqQ/eW2mqicIe4UwBx4AnD6aBPhcvsUoz2amwrno++63nYs6SqcYIF05jpJjtdP2S1lhpufJFgvxheiw8uCLi2CJTx4C59fSjgPzSV9LGcf+EOTBe6Fp7RL16L6wnq6jhiX0zgqPbBQ7HFgDUZDgcCkI4AFcDO3EPSlu3x+gkflCJ9a1QBs0MJVQ7yr6xwLmZ494fG9X7zUlBEsLIDcmDu+dafKCLkRaMPUN+5yO1o8r3T1JOuy7GFk2at8n+YmRyy48BrBgt0NBAtl/wB/OPB8LELv7FeEKcN+2ecLXTzjjY36dmHjysvRtyHjE/Cqp/5zM+CGYgQLelhuBEuyyLNND8Qon0Jhw7Q42taGCPGmTm08DxJ/gfnBk4MywZJuIwnQL9LToFT24Bkm1uHf7og8qG/afDWm2lwLurbeemvZrnp+vEVcVMa6tMmIFexTyDy/od5FweRYV6SHWZzf2UGH7Fae2Yv+CAvlNws5ht5m1bO5DrLC9mW/xruZLuVLXul3I/Iu/D9n+UsEy4mf2mSajmnhIV0L0Ce1v4NJ4SOtWSzjdSK8ra6bV1UEa/ekQ/pJsDjmF6T8Wnpu6hVKIyyPNX8QwrHSqZ9IOeU4ZnxtyYIbb7xRdiMrEyw/bppjLP9f/Kg4mWT2QFxXC+9ALIpGAoERQADPetTuv5/PcHfnsFntgxr3X3HFFR/srmZ30tgMjAhg0XlKk5r++R9+O+zYQSef8+ACew/ifkGTDhIUEgAupBvgm6oWS5W3C7kgagHXhlRoB6czJHFcZH/tlHnilLNxclLO9wSKJxhc+DPBQtyXS49tgsB1V2Wg7zwZ4xqpTdl+2afyUpgxANG4A2XExn/jLonnpIgLb82wPWHDjYx2spzt02sD04YpDPn8kG2ssD/bAflmbgFwXUNiBa9NkARLtmhT4yscjLigzNqG/B746fueXjFPFpjGbSfaQBy14cleFjOuza+SYOELg2y3etBrY8LKcBbHWEuGebTX7JOdCJknfCjjT7CoV/2p4c/GCydYaE92sx6d5omfA/WS6k/OYc1nSmh8LA8bvZ/j5baqNc6MeaEcp2GFMUiFG6EPuX8pjzYIsxw60pFPf7Fm2ekPdKzEPBJRE5YaS173Zbc7M1CP2NMZwapH65933333WxD7OubPwT7f1RHBUjsi5UzTFvqFeE2FP6HSfPJY+vKbU1vqQ0oOLgiCNTiso6UhInDHHXfULr74Yt4WaGsFNrraV7/61do3v/nNtrIVAiI8b64om7MsLEz6ppcXJK8cGy5JkjlsOvlbqvLahLwlx2/33Bj8pqBqJD88zeE33RrepO0XNcm0CrngafPUhlRoB4czRrAg9wt4Lera8Aq6y7/+QqHqUm4FPDGijbRXxAXRgjOM0Ke8WIM4asMQwWJdr9sr4OZFW8/EJsI3ixs22rS8YCmuTW+T9EfNLOamSGLAUwrawE2T3sYauq0OTny0CfJbusVVBtlKl0gc8dfmLznq137AdqTP+p6IC2WvRVvXMCIHnWYPfsrPOpUEC3axH8KukmBttNFGpgf6DHeEmiNsyuYJ8vx8p5zGRiHLOYYfgae7sh7Yp5evHXvssQUiAN157FMdm2+wnfnE67fMh1wmJUw7xzls457yND7WD9Tzc9zHnYqGqO9vLoRNe+bETIRzXDgolzaIYGiuMWxoX89lwU72QfNDdWWHrkXpZ3g05vyxCCVTIK5J0BZe2L1vSitQHREszUERNtrKPvH/QBeAYPu1hgSLZRu7McnlkL8FZXTqQz01wM/cmQG2GU0FAgNH4Fe/+lXtqquuql133XVt2165sr5GMsSF21beC+Ci3jmlt8Ci40+RLBt5P8TG/be+TlUccttX5bs8kiC6vFCizsbQfSQXG/jcNuI71kXbf6L+8ZA6FZ6LJDe1vGAhLseNUidY3Nz1TVLl7UJuWNo8KwkWNnTbjGH7g3jPE0+ofg5fPqlSOxmDlOGJWCZYGBu21UCwSrdzvS5b/GGDTgXYZ5EEta2QG8HvMQYnpAzbvLVpSagi5KZPtzFOTW0jQHvEhnbz5JHlbJ8biexhWzWc+GgDr2HjsTjqWhns4LvA9qGcdyKNkMt1Uzk3QO0H1KGN2kLIayM0caQzyeDGx8zFixdTJ203oqJ8lkGe/dCGuB3zys61obY0Nyiq+aIy5jFuY4MvTgrZDu3hOP8IvlIe+dzACxc30hsBn+cBtz+wf/CaR5wTtJ1fOmqQsf4yXnKU8zYLY8vDFwFdS7TVMCrVr0p6+3M5bCMhKTvh6/NJlEQwpGs+rq+G9kGQzT7g0C3BYnsfgU07pIZvT6EP7kyJ3VMo7PkrXc4lkm7K6HrQnKHNxNFuEUKWfZRjnNfJPIzJJzFu/4Z4LofsLRTkuDIchtMFNYy2o81AYCAI4EKr3Xln/frGptS2zYcemvliiyPptvJeAG3tojQWsb0VZ4gFgNfbsyFzvs8vx9NzQPyD18PKZS7NBYmLUCZiWEjehfSXcAvnKdhw8gkW8p6Etg9xdRuitA3tvRayH0qFBIEbgyccqmcEC7LGRHHapI1D5ezrXujHk3MGItDPN3a/G1EueLZhAiPTgXShHdhvRAbl9q4nlPN+rTY89jtv8OW6SHsSlAlWsreBYOGUKRM3yOTFGLeQtNiLbLQiWNoI0LyNi/UL/cgLvhU0/9gEG7A2wtUYy7sgWiZYZg/KuME/AizzcSzyZKNtoki/DTJXAvPDIbce3uYL8nIbiHvnCRZ1mD6QZyMuSJteVTjjjDPyvANmRjhAEAsEy9XhZkrbicWN8PyPRT9+yMIOunq16UFUfRCpsmJ+oJ63gzrNPpzYWoj5wjzZT3ukE9Gcz7jc74HVKUxw7OE/iui+wI31DCvk6cuMESzlIzQHbPng+c1IkPRUESz1Q3Occ1Bx09Hiw/fXi1XWh60aL8l6DISFfwZLcrwdvBMTwIPXTOEEC/NYc6/Vgsj5ynnE09eCg13WNkJdD5lgYZ14EYTZnxvgrR2EDSdYyFqI6ejXGupSW/8T8T+Dz+WYE8uRptOcr6cG+BkEa4BgR1PDQeCBBx6o6VSKz1a1c55Use71119fw8OV7arxbxn2hNDe8D+jMBYlpr3LBMFnYnE+Bp4LuzksQnswgvBPkd9wjWLxJ0l7Wl26tkMKKb8P42j36QgWKx/hmfD/7dJV0UNR/wuuYGfESRKqFnISGL5LSORIi6arXrsadvycGVhAD4Jungicg+RZ8NywbAHHYq4NqdAO8o0kQYcWdG5KRoSAyWeBwceRlivURabHmQswF3f9Oor6fDlPf7ZAnjm0u5HiWMxtc0OeNq1WBIttcDMzJ2zcqYWKqkLDGc/VWJ/RHtPc5LgxcBzZPgmP2QMcC20hn78EtLZRl2WcC09M4ZsYwu3CD9zOtXLIZVuZD1cmWCo3ogV9eeMz4UceEengRmg6cdJIO0kmhKHIAfMYZ/9uhl/w4Q9/uDAGyOM4mB5GmUabIiZM2jzBfJAM82iTjY2IIMqZxx8m0P6MGeJ0LLP+WAofmEv7o53TmUYd2s3bsnTEXvaTONDZZq5bmfUs+zwSnzvDk6BoPrNAJMWIMOaENn9+WRBGlGvlZENZpjznVV7oHzJpgwiGdBHDXB/9N7KLkGvKKmB4WaqXxxa2a/z5xauZY//WYhwvTAK6doUts6UnidR4gvWtlLihVE576TmW9AschkgahuXbkVyLjsdYvhJz4g4Kwan/9dQAPxsW7wG2HU0FAj0jgD8krvmTplaK7rqLhwG12q677lrrhGB5vfhWXfv+979f+973vtfQBBbn+R//+Mdt0TzttNN2xgV9DYSeB/8zeC50OjVA1FzelM4666x8aoKST8C/C/rsesSCw8Wa7i3w/2ExfKD8PfDHoPyHSL4w5e+gcoSKL8ECk0mDylFXC6xlIf14+NczAXnb3K2g/sENkJuFNgXLhfyXEKHtJAC22JYWPZPTB8kgFuxLEL5UeQh3h7fNE+1qQ8oLPuWEAU6RbmMazp9gvR7ptzMzuUJd5PnNm5uiEUDoJHGhzYU+gQRlrCCTNz7YLby0aTUQLOBxMfxvoZObluQQbY8NhZJj32iTzQ/YQJuJLx1PigoEC2luGNq8ETXixA2IuNEOOm1k21hiww1ts0OftNkU6kOGJEB1cl/wYwMjMCgTFlTH28J+/lInn5HhqQTHVRiqDvMow/lt44kvPIY57LXNHfk1jIPZDj2yQ3OD89PmC8Skk1UYN/uwqVuY6jKfY2GbMkK5LK8Mhhg/yj6Sxr4VwbqH8iDCwphJuqvrgV1H3mYbE5TputY87dsJFtryc5C4eQxkN0+wNEa1s88+2+xC3uNQ/7fAg3ND88PmC+aNxqQdwVp34okn3oL6J8NzXptz7fnx43yV3hr+bPt6COd0KqPN7BPtWQA7/LXLPtwH7x26PO8mkP2vI7PQBy80qHgQrEEhHe3MGgGeLH3xi1/ksyf8SXHtS1/6Ukc677nnHr5MsYb/MTOChQu3ZT2SKjl/S1FkSmUIvwnCZgsONodsDC7wm1F2F0Lb3CQPIpI3crSxhPmwJW8wSO6XZHdLIYNDTz/9dBGnM5EmGfNuR5fQpsdTD3ouTF9TOY7Md1UciyhJx6Xwn00/+c5kEHafAFufgTJuyp6sIFk7kh9wP8RiR8LCEzO/6BX6hP49nzLQ+SiGyVG+TLC+r8IU7ovw5uOOO07fgvMJVkmOSW1cKiJZ/C787fB3wxsusIH20hfs9eOCsqwLY6TFXpsWbdkO3rtnInEAPDcObajExLBBnpE7hK1cgWBBkL/epN10HBeSB9rANoglN53cFvPwhcPSqYxZJotwJyZAiGyewS7bMKG/UJ8i8NoPcl+gz/qOUFjo4snzArq8PRxXbdjMpyPp0IZ+p+UkMnnuueeaPczD/JS8+ilSxTmluPplVfBh9uH6M4IFOdpJGeazj5XyyC+7h9FH2qh+0S7VNdKFco1JtplKkC9MaKfGnXFhLIKlece5bHjgOtz+tNNOy9cl9ZWcMCllz8xTXwBbDAeXx8VM9qo/DPM8x9xRn/dC/tWs635AYXWhV+NfJlg3QnwZ68CxfzYeCNlH6UW0wQbm0dGW/wv/s+OPP57Xgdp5JLXJco0l3xEnDJFtJ6L3MuIdcFeeLeRIa+55sYHEdUENpLFoJBDoBAEslrzl0SB62WWX2a2+ZcuWcUOxclw8OcTmUahDGd4aJMHCX53wIVw+58FvoAW5coLlODmx7OXLl+diELzdc6IeOYxBIiv7I/oF+I+BzH0J4Z2wjZujd/kEC7YawcLJji3eSeiz0PVuxHlL4ib4v2c+8DgE+XlBZJ5zO7i4FrTFaHsL5PNn+Edg4zLihrylTvY5igOTp6Esk0HcRvok3nT9S5RzoaKesvtv6P0jMrXYFkhE6fbP01kZ+vcuKbFBgG35G3+pnPK22Kf88oLtxTM2sItrGu35BuLEhu3YogwbuPnR5oK9GIvcRyzgfjHm4k7btWndhST/v+105pccN8I8aXGiYsQQuusTyQlDnyfVLOHJCMdO8+Me4MLNho7zg3ppg+wptIV8fnmwtqGbZXTaqLa3BBQyxFxSuW0+zEuOFw+xo6OMbZTAQxumta18hJprZcJHvIWh6jQQLJFaXJ/a/EkCZRu/HDyEvmQ8YYcuWumEiPXRxkYnbZBjP3lCw7q0XToRNfzUH6a98+/vYj7tUlu8Huk4Tp4IMkmX5x/ieT7DFtmv8ZYc57LiN2NMeC01c7KB5d521S/X8zIiecIgh7BNY8Q1cfM0J/dG/tVU6H5AYeODcps/CPWFR+0+iLF8fkrwOrPxgB7K8Z8IrO+uPdkgUqr+/Tzp0Lxdl9qkPHGk57h6gsX5qusE0ex0qqU5nudYlhhQRBfUgJqLZgKB9ghcdNFFtS984QuFW4AkRtdee61VxkWWlZBE4S8oap/+9KdrX/va1yyfhIqyX/7yl817gkWBdrcJ2RZIBp8Jqd122225LWwAu+aEi2DxeDaSJFP/PzbfY0844YQ7EOdmXCBYsFsbKIpqRrAQivSwUwfDnwXPDebq/fbb71iEXDB3gZc8otlx0eGvFbXY2kkN8nSCZd/kYDft4WKrjYKb4t7IIuHgxsI4bb0F/jHpmySiRYKFdmyhQt3zWIhfyLE+dflFj6Q2kzUUP54ycOpnPZVOsDbddNO8IUG/X49IjpZJGCEXUvXPZVtU/WdC5OmBJOQ3nFWwtYFgIU8E6y5gkTce1NfibzpwC+M05HEDekrS7QNuBLkt8Bkt8hyLggOp1iaifG7c7Jvmxz2wSfYTS5IL6lY9tsWxzy79lQ/TslmhyWAOqK6NITbFQn0IeYLFulaOLxu2YTq9lg/78lgAM9qjzayKYDFPY3QX4pyL1lfMlYw3bKIelnHseeFlPJFHHSJzjNKxT9rQJUvbmc80bTWdCOlYpv5Yhvvg3Mi2IJ84CUN9CeI4eSLIJO319fJ8ls0UoRz06zrhXFYdbx/Fyk42MN+u5yQgPMvywkH5HBcbc4TSxTZzfeC+FebkZ5C3PWy+FGEN1yLnA3VZXdiu+aMvVRSjW4svEZpL1Gn4Qg/XhnnQa/10GMkG1qVjmvZIx4XMhOOb29kmy2kH+0E5XSOImtN1pjQf1jecyn3IAgOM+AVtgM1GU4FANQI8neID5dgQjCTxAfMrr7yy9rnPfS4/qK7TK2rgbcOf/exnpowvBtXtQ5I0noRRD15yl0+wKFgmWFggaj/4wQ9qN9xwg+khwQJ5sNuKjG+zTZ0v4ILf1QRKH1g8nsUsbKq/c0V3Il6vmDIhp42ci4kRJqfzOcjj4rwCnpvX/a961au4WC1DvV2waOyMeNldwwwQQW5IdDpV4KbOtrT42MaAdCZY0Lk30lfD3wjPftHW27Ao/QGhOdjGerKZeFh/UNcIG7DhIkonUlNPFYmlNuJHqTCFtiG/9a1vtZB50O9vv5HwEUM5Eo7NYF/VmpU3C8qwAmzXN+284QBD2ttAsNAf9otld8Nr4+N4alMxHYl4fgsyNg9Qz76dI01nL++sR2u1PffcU9hfCJtJmr3Thqc8tsuH8GnHw5Bfhbl7fypkHjGiDdqcWD/jhjj7y03c/k6EaTjZbgn03dIIuUnRFeoj7QkWZYSbheir9HFO0mmuifRog8wECzapLc5r4aox1UbpsVD/OJ8LBAu6jGAhXzKIWtzswVy0EHaqHdpNm7w8+6B+IVpwbU+woJvjROdtZv/VJssywcKJ+T8j/VF4kQbNU85lxRFt6bz9ntxU1oeNGh9TCtuIgcbBh7k+6rwQMq9nBTzA/xOGydmrERiHjMaf65N3xFNziQTS8HXjJayEkfqja4dp2mXzByexR+LLLedG1QkWdXFd8M6TTsvHeu7z+Itcte3rDSSuzg6ksVFoBItX3mT6ZQ8m6cwRS2oE3wQ1odo2W1W/baUhC/j+gZzkvnoyRBNxoRYsZZpECH3mhmZkabvttsunRyJPvhJv+8nxdh5J1v7771/7/e9/X7vkkktUlEPebsQzBUaa2E6ZYPEVDnw/Fj1OAuwWIuWw4Rup4+1C9gPtPEpKMY88qXgm8lfuu+++16kcITeS3VyaCzHf1s2saxEuSWVLEXJR+jHK3478TyHOBUa6bkZ8KRaNrRCWnS24wI8b0o3wJDNsgASLXt/k1sJePtfDzbqG+LUI9oC/AJ55tIFOm58lIM/6mWCBrGpxk5xtJpDTN3Orhw/JKc2Q7WWnBRjhenzL/Svo+AL0ExNurHTboMxOO5hA/H7IbIrFd/PynEJx3iwwhxaRVMNxE2M9LtSM6rkoTp4qe9mnTA4oD2frI0hJ3rSg7ybo2xV+Hn6oQIzlOLYiGTWSY+Cstt4GoeMliFCbjrJs40b9XZBBUktn9iPkxsYNjHNE63XekJDn3Rro0CYqWSvH/NEGaW0jnW1NCh5BKBnWtY0S18269Byi9Mn2zVI9XtPeHo+h6uS8NI7sjxEsjNdGabw4PrKd8/k24o48awZtEEs66WSc9pqdmBfrOC+gn69aYBnz6aWTeaybx5IZzmUbUx77qbY0v2xsHEk1UbTnN/BMsN75znfS5uPwK9oD2A/Iad5xbH0d09PkQzawWBgwLl2Me2d4uAxivQHf9YbXkQgL/nJPcdr1Z5Dhtb7/e9/7XpFIqmBdG2/guiHkmHczP5x7CF/w1nANh6NNhi9kiSfXXPVTodq1fiW9+cvJ0UcfzXl5L64dO8GCHv4idC1C5rOu/xKmdQHZMw5zwda9lEOSqLZnhAYU84M3oCaH3kxetPtlCTf92bjZ1p9N23NRl6c+crzV16nDwmWiL3nJS+yloLz1591WW21lJIknUnJcVEm4tthii9qOO+5oJIlE7cUvfnHt9ttvr/30pz81UZbRUY63DL275pprcpLY037KkWDR4YKtsW0QrAMkiDb4q0Eln4TIL9KJk/K4YZeJBkkZF+Bb4HeB5+L2TASXYkF5BESDdQjCbvCXwdP9DP6N8D9houS0SO2A+oxzI6BubvxbwOsUBVE7GdOXCyM7WLguQfu7o+wl8ASBdbND+b0o3xi6F8KvxiZBnSTCtoDRZnjeWikv9uq3FsXbUW37rBgR6M0XCcb9VwlLI60o460F6iAectyUSHR3UoYLtQFSr238CBtOsGD3SrRDUrrgvPPOW5AWc6pRW9xBsi7EtT7a7kFBuGXwfKHrFpgfvt/E3MtRtj6hwfOYcM42LZfWhOScsDhwJSnmhso2eEFRt+zhxCwTJGTV33bNCFxhI0LabMEY2mYDzDP+Jl3fGGWvXnPAa2otCRbGmBssx8XqI04yL+ftoV5taLSXdvNCMVxRj3azj1vC02Us0Ab10O0A/yv4jCfKVqIux1cylCPBsosQ80Ibu7UNeZJNzT/K0smeeqr46e1mCe0S3iYJzO4lUYL3NrBM/WWc86PgIC+sbW6ikHN5AcZXeNdK89HXpw2fRtufhp7TEd8Hnrj4eYpkdhkz5iQMaolcqT+0X3GKPRX+PNhzMxPOZYIFPcSaX4RXlvanh2CbFnzOVWsf+PNEkGupsNE4q13TB3mm9cwcotnlE6zUB7ZBu3mteufXOMvHXNDpL9OcA2rTygf5MbSGB9lJ3xYG/hU+jcErLH4o5/t6jKp7OcZZVM4rp72+VrrK9ZTupY7qzjZk27PR4XGDKsPqT/7kT77RSi3L+KwTT6Ho99hjDyM3JEdYFLI5O++8c+2www6r8daffxs7T6M4XHg+prbtttvWli9fbrcDt99++xo99eA5HzshozKejt10001ZL3VdfvnltQMOOMBCPrtFAsdXOui/CFmfJOvmm28+DIvQtai8ATbq92cl9ciPS2kS+cJiADu5AHGDpw4+uL4fwpfBnwDPftitN0R3gdfCcT7i74J/KTw3ES1MnI//gDr/gDyyRy3eNyNOvdzwGZdbgcjWaNNIDDNR/4eovxWib4JfAn8ufHYoMyKFBfSxqHcs5C9AHm+7irxQliQg60yVeSLGulxcuSheCv8CeDr2f1Po0qbDPC6e7L8twiQvSLKfdzI/OW5KdLSz4KArEx1sQotSoeTzhgO7aSvb5zxhHZEUjhPbIobaENhPYZ11wEZbvDFnF+FklH3LDnZIn/K0qRSuK9RdkL7xS85IFRK7wivOMvaBdhIrjr3Wa7ZbbgtZtrlJZndmyGEM1RfbmGFrPmlJMjwq0oZP/dbnww8/nMSfIvNFrpiA82Pu7aGtwpC2UA9tFyFgmqepRtaBsWQ5/sKTBOs22JhxR1r2ykZkzRAs3I5bl06mfTvlzZUYeJ3UIeftZh7HTlgy/ZAjShpX5tOpzTPxeoBf4lr5f+2dfdD1RXnfb0BAAqigvIoKKsRoMtKa0UjrtGqD0ZJkmpZpkvpH0kZpU5NUCtFAINFgY2bSNnWSptMxbTJp3jSJedNUkyHoxNhoEl8BBVRQ8AEUROSBB/Cl38919rvPnj2/33m573M/3PfzXDvzO7u/3Wuvvfa7e/b6nv29nMhsPmy7SWnMIdl8tHfTNR9/+qqrrvrv5RUHTdWw4WEeOpFe1hTCF3VEm8LssDI+USDMwLoN8d1SBjYbX3aMIMzIxrzQ+dvbSiUNfkfLrqfwXZA8u/u9/vtFojwXmatRLtn4futHjcfXsTFt47qD1dhQd7CUx5jRBn3gu3qnjpN1MGdijSLtIJwm256TDN/L5eIDGruTB7TRR7IxfQHe9ki2f6i1/YpXvGJTXT7uOPOF6eoQHb7oDh/4wAciCcHyvVLcP+Xwohe9yMmIIV1cSmSXCiLFvVeQqec///lxQztPKlKGXLk0EuSNJxA/8pGPsBg9tSj89RLHl10L1IfKuSMc9rH6srMD5AWWBegByd6kPny/0lfo+IyOX9RBoI5DLMKarzdqAb1VmS/TwcIKIdqQznDail+v01N1GLBblH6eDhai63Q4BMGScz+pOPf/xKItO1ig/0RCF+hApgY5ZV4Wyi/2a5TJk4mfpFD4tgSLp73o14be7n2Sxuc+OY0f0+lHdTyHfAWweUmkJrtkZ6tOLMDkCY/WCZD13JL/cWKC5AMPJelXG3ha06SK/MBB/bSN1aFqx+kBkaIgWJKDIJjEnqT07TpwQHYESk4crPpfnYow2QsmavM4OY+4xw9BgvLsaCYZ6lpJHO4MYsntn6A6V//vUB5FZ+iofVaaPmMb+NCPcIaKqW/MlKwhLhG+8Y1vfKx+xcc8cYlstiONS2hymBX/ItMSLC4hRV9kG2+Bp//4ChMJqrQ4gZv7XomKdJCP3RyuSxqn+Dgd3JB8NHgS1BY7GczHk8FENlbcdb4PjBQbA6pgU8hozkWs8q1cIrSN6Abj1j/u1Xg/jElqg361ASwgQJfpaPOd3lcSQbBU/z76IrLStneZvpcvlNx5rlRibAAzwucmURDuqCuselssG6JqiznBd/ZIrWvoYt5QhzTzK8ZBMnuU7gOyV8quKxVfSqFul/iq3hP4/Uqerjo/r/h+5T3Mj2OFWN9IaFwfZFyF19HC5N8q6wfIV7C9HkfsGJrPnnNBvtQW84s+M69v0xEES7G/w0oOBu+EDRZud+bUF3+7G0v9icCyCPQEy69NgGAR2K1qA5f0zjrrrMg6++yz26KptPWyILBzRXjuc8Ofx84Xu1a80oF3ZmmRiPLjjz9+4/TTTycdq0hkTj5uVhQLuxaATzf5JL9QzltDYwGS7LUqgwh8r453agHyAuw6VI2FQwsknvcTZCjcK+JwpuJncVICN8GfrsXfv45tx9NVDiFzgDw9Xoue7fk9Cor+nytCLVGBWF2vfOx4TCmPuhoDkxSy2RWCrEBM75Sj8+JH3d8hX+FvJlF8+lc4i3cE2eA0Cy3hPB2fv+KKKyYDpBOIDQUKtn9yps0oJSqZkK7og+TvKwLV4YhcQW6xl8ucjIXD05QAt0oOSgGLP6HqUDr0CvPjcB5Ruv+jlSP33aXI/bOk+xnn0nVLKXiS4nsspNikkvrotj1HKm1Co2QN5B2pfp5aciqJEh52aJMv0P4dIVcOgvWGN7zhNGU8VkfbF+6BOUIEte1vm672CN8WQ+xFD98Ry3NOH8OxK65YqI0jRRgYS4jWHYqrDZqL0RfsUL4DactErPK2ncDDwoqPkH2Wb7IjiX7PczKwy3hzzl82eRyrzRQo0GbYF2fdh378xZxTdnxHZWOMqwiWbXWNpzrRxMaQrL8o+XsUx/yV7l5H37+wWW1iM+OELRBosPN3hKsI6OyD+0v+iXxo3fyqfvT9lrB4F+cKD+jHp+WYW7Eeerw077DvlxEswZh6HDkfukQYc05l7j9tYD/f/8/pcFhIsCTotlzngMVJsA4Y1NnQKgiYUFHnZS972cZ5550X1b07dc4552ycf/75VSWX8bhnih2zZzzjGTW/T1gvW/O33XbbxrOf/ey68wVJIzz5yU+OG+79AxqChW4FFhnIzcc4UXifjtsjtbFxc4kd3URCC1FLhlgUHxB5+zPF7HwRbpxE8dnuILXp0CWJe3UJ4RYRsuuaOiw2p2nBhLARbo5PLfpqu9UBsTlRcixQhErmtGC+V+f/Tn38L1FSPtQOThcy6HCaEl9/9atfbUJIPmTrmKv2vywxyI7G6SeUf5EW2G9VfIMOBxZcCNPnnaG0F2icAAFHdLfsh1xG0IIdTkp5k0FygYiYkuGsdTPxs9S/f0KRyJ4JWetw/JoGdpGCFKqP4PYk6b1e8ZRDll1emKsOyd2HftlzrMqjL5wTVEb9NnyHTt6sw/2LMrXtfsa5yN5tkRAsir9U0kQmstTHBjsnJmPflrIm9mvemnC+j0yC7I2+qG3b3I5hiOjjCJGz3+FEYbKtNEnjNB+lsnDqk6y6I8Up/Ql7pB+i4Tawl/xRgiW7LBs7Q8LiFMkzP+5QVHFX2va2Pos+hUMvc1WnE7tkB+1yGDPKSLc6yXPAbpM+8uhTW3evdnLcx1gMECqBPlB/MOgHm20PgiWhmEOKISRtiL63GUrXsVYf/0TnT9EBcX+MDu4/rfhxrn4HHqQJBQfeK4ge+sP3yOnoj8550Ai8+9DO27BVa1fo17h5LtzfvCKEvMBX42c8pua6yo2dsSUevESofMbX5Atb0fUEHbfpcDCWPu9j7PX3uC/b9vN2sm57Y9lAIrAsAt6pQp77r0ystFCECojSmWeeGTezv6i5DCgnN7cJiBhBl/viyUA9+Vfl2fnicuHTn/70yPON8RAsgha4h3RAbn4qMjY2rlH8ch2/osNES0kJ6NKeos9rgfuHkTH5YAG6v9xc/Wclv+7uSHe7+FcCJLmbiqx3NMppRHv0+US1A1Eg3Byfk4+WYJGGYJmgsIsQQZhxGeh/XH755ejqwyeajNOUvh/5Jo8Fmz8qfl6T95CeRrobvHQZ8m+Vf2tTFu1rgfauDb+evZB7MWaQTC6iqhwv7eAwbH/k64N+BKGQzo8p/cM6viL8vcBXTJXH5LHeb5AuJktgqj59XGnK7QCUnDhYtV2dlsiLidtxLTlAWPqoX4P6D6H7kDLsjFzmfsa5dFayqYw6LkpHnxXTF/php4SNU23pnGD7Hzc53Xh/iSEvdjLhKPV0oPGxCH3EH8ROhWLroPwrpb4JAbYcTUEJ1R7Joddl2IssR1uXPoZ+yVtWWRuPEhYe33s0LyruKguS0vQj5PXRypCu7UiWdqfGU2PUyqPDAbvdNnmMkfHmfK/WoMBceludlNGHHk/yIxQCAmFdRLBKjanIGEam5tRnlLhLh8fJ/XUl+tyG9ruF3cx/YvRWLKS3r6fiqR8GMYf37NnjOqFXWHxaB+sB2CAT5fpuBB79d0TlxjTmo8Yjxr//7hQ92Ml3FNvQzxp3vNq7VbGDyavP+xh73GZftu3nSbC2HeJsYDMI6EtUq7Vpkx5uVifoF1UlRLXCnIQW7bhhXQvFximnnBKXAy3O5cOXvvSl9fIjr354+ctfXsmd5dTmH8umH9D5/9LCdJ2OH9LR/uLHobHovFfHq3TZ44WKCSxA4TS1WP+Y0v9I9f6Sgj7oFyCLqMNNJbEfFGccdtgnlTxHC5Sdw82liGiGYMmuWOT1ElMThUZ8MPmJJvc0pft69AdCdG4j9/XS/8gSsfliKfuo4rBTGN5m+eYSg4nHDMESHl5IW8ePCnT3eWp+QgLbhZs8LfiBv+JjNC6Ptw06p58mKJGtPJOS1vn4F/Nx0teSA+qYvEX98kEeT2G2i7z7GSL6sWAixXlLoq0PZ9Y6CuqHs6dCE7CTdozHh10mHKIvtrl9/1iRYf7iD2zLya6r2G3bmbPL1vYdRxj2qB0cq8vIxybqO49zxiwIguSPVTqC0vyZL3XYceO/DVvcY/zdj0mN2JlAt8NUO5KdGk8JgUGr0/WIsdu4cT5DsES0W7KCjAN9o/5gYN6pAFx7guUfRbWe5smbZHf7PWc8e5v5Xp8g2cNlk3G1jilZ4RnjIjlw5fD40r8pWSto4naOxdirzVjnFH9Icv/0m77pm95U5JFl/linCVhvn78HjoO4CaO2LVTWsSxl6DuNAoVPTSIN6BFHjOJeZLDH32NXO2BxEqwDBnU2tCoCF1xwwcYLXvCCqWrcC8W7qnwv1VThkie+TGiSNlZNX+x4ArEvZwdKpOHXtMh4MelFfP5uJR6nBfPqkgFxiAVOb3u/S/XfY8E+loNpCZYXFBOVVpxdisfo+FYy1bfPEhNkfyVYSqOPXRuY6f3dKyUQHwyq94mmgAXOTt/ZEAIcx7k6vOs2taBJB4TrRSrnuEzHzc0rEhjPwFG2hXNVOYvuVDvaubRjCIKmcod7lGgdI/m1fbXrepYPvcoHh7c4U2Nxr9Is8raBIjuBOs4mpqrP34BMOQ/l9eQTHdGe7pUJR0KGwhTB0n0t1UlIR01LzhjgXFpHgY3hwBS3wfaDB47wr1wovUfwKgCdMwf53712FxIx5PEHJrKnkFkCbT9Kztp9APO27+gNB1nsP1x4gh0H+dVZKs1u2J2KT9ZBYO5GUD5/5hv4y3FOESxdvg5cJFPHVpVI17FRurYDsZAsbXsMlYx0K0+eA/rbuTVDsHQ5LvrYzFPXhXy04+b8NgbXIFiyzSS6n7fI/0j7/4w6x/7eZr7Xh+uVCY/Vjl87DlxaBYM2xDyRze6Pvw/Y3Mu29Ui3c4yxn5LXGL+jWUcsGzIer/47Ih0xvoo9jjGnJBfYKt8BPe4b/ac85ozG9WalIyjtdp3Vx+hxW33Ztp/zhcqQCOxIBCBT+oW0dtt8mZAnA7c5vNn6tYDwq5TFxAuci/r4WjLkj1uCdYOyPqDjCsraIL3k4yxfTHzJJZfglMNJtiRNcp9WPuFcHd6FiYx5H+1iJjkWx55EQPq4RIfeP9VBuH4S7f8UIf0LLchf0PE/dZy1vySIIPazUOIECJAAk4vI0Icdf++UcDaPf9Ob3uTF2PKOXc/noVd4vEIZLyyZrykxi7gdAFnhnOXEwmmQURwKOmd2sKSzx4Yq0Z4uodKnCJJzP/+N8P0PwgMHEm2orHXUxgBskDFZwMbeISkr8igDo3uk92bFz9FBOHzPnj28dPEXlO4xodwEC6JJ+KlJFJ9xw7HqtjtYTiNAm+HobL+IPuNhckDfPD70A4J1PH+erv5DasCNp724FyfwF+QP6z66irsItnE5/Kqrrnqi+vb/VIddsCpT0m07tBX6FBN4v1crP8mdfKK/nVsmJJbZK3IdmNtGFyimzSFMG5EoD4KlzPj+SY/PWzmeXp6yWYX0ow3Mee6bOlGEyv11+ZQsO4EUFOKKXs8pxm9KFrkuxJiWvBmC1cl6PoZOj5f6WHcoi7znsOMgWJJzfatlnGKOaV5Q1pZ7joKBySo/KP+1iPkzraDE6EmC1YGSp4nAtiHg+7l4WnA7g5wAC+k/ow29wuBkRcsQrO9C/Md//McrCZKefTp4b9bfoasNymOxuU7Ht+m4T4sMZOVHdPySSE0lOuqz089VWV2UlJ4btDBD+N6m44Ei6AXa9SBY5+h4oo536HijLsN+p+JVw1yCpb7YwfaDdrsaeoIeWji5abA6US3OttvFtr9d+H++FLKIV+cmLL0w946IsTlOuqecm5zdDMFy+3I44UhKOyZY71C//lvJi/6pTfeT7LC95GGDnRI2tg4HWYLtByMu4xFu5UN2uC+ctm1wToBgIYPT/w3Nq+sUO4AnbYfDU3yPjrbv1R7br105yqmD3RxRl50p2XKHzvmvUcbsMTqYw+w4cUNz4K8dEPrS4s78UPHXjxD5+iGln6eDftaxLmnbCCk0HiqKQP9anSU7IjBpNxxmCFYh1+Dk8XN9+jqEqcuJGcsgVPpOxTyRfXHeCpHWzlSdgzo1hlVM8+zznKj+GdLVjgPZff9MksAFXf4+MB/B7p9L37cqHgquS5nlh+TI83yM8RDBDjxkIwSa8Ns63qwDGwiej/G9KGM1KZl8osd9o0/VFs0Tf4e517WuZdLxh3ry+PpWidLocVtd0fafthNq+1vLFhKBHYDAueeeG08lcvP8dgctXrfQhpzCkxXh1CtxIr8Pcmyf0nG5FhGI0rLhY0UwFhvVf7OOV7U6uCQpGRZmdo/m2lB0RSQ93Nj/PTr565IPoWoDv6ZPIkPOkzfS/wRPOrYCS6ZZQO24ZnawSl/YJWDBthPhtQt70K9fsmcTK/yMjm+OlD6Evx1KZBWiBranWUY24zQJvUO2M3B7EyntuGgxP1Zt2wGEU7HjtFCJ7QzqDpby3c/qNJQXbUhv66hdFznKbU8lNMprg+3Hrui3iHXYpnMTD+SHdluQwx+Ar8mZkhFoGydlHaMEy/aLIGEDdlIX3WG7MOOcHSzG7BTJV4KldN3BEiF9WDvMtp2/uqJvfvlkS46rjMrByThzKZI6vJLgMI0xfTtc6VZeWTW0uJNpguW5YfIc7xqrtSYJ+trX70TqDtZXNSahS/ad0Atxrnnk+cEpuIFZDXpK+jqd3Cm5l2p+ew5GufKm+qe2goyprVMkcJgOfx8YS/4t4PfLgyhRv/to5yfyU7pHZMPW5rI3JJjdpd9WRNsmj57LQbCU37al02gr5lsZR8YygtZSjwV623XS3xeLEmNzEqwWkUwnAtuJAC8k5QZ2fTm3s5nQrQUvFjjFj1cGN7UuTW5WMO7mIrtnQZ3rS3n91bdAvi32/VWOo0wYmnDdrycyb2orrJhmgbVjmSFYRRcLNAs29xBdqfg8xbdTpvgbiRV+X07j45Nk5E+RCcmxIKPnaUXmw5ZVbILirHACDUlxPmPY7mChj6ch68JvQcVe9O34KYp+6jJwdRrKs6NoHY3rkoejsFOifiun0wg4N2RwulHuy2zqdyWUKpvCROcEiAQkBDv7fkTbIid2hhCwcOzC+mVKv1hH9EXtBNEQP6IcW8hvHTM23qqDMXuSIhMsCFHdwdJTxA9rFyScNbK6bIYe29gSrCqjcsbBu0TIR5keZjhCD1XYybbyEqmhJ0hgjP3GwnHstNVakwR97et3IoF5EGONCT92IGpn9kKcCzv+RufJV+kN6jqtf1tk2bKTBsniPzGDhLhM8VT/SlvkPbnIxFxVmnrtuJTiqaidY4z9PPkYf8lEHdlPm4wXhJ3dNtolD0wJHo+YUxp715+UTtpy36hXy/W98VhYNuJml7vNx2a31eYfkHTuYB0QmLORQxUB/QpnMSU8QQePGG+G3ISCOR83l7IgG3PkWJQJmyF5QRRV13Eo0ocX4bc2N7y6bJWYBXQRwYIYBMHSYvozWsQ/JOK6h0a0gD+DWLtoU7sv+rVrh8Ji72Di8nfKOM+ZirHBv7DRGQuzdglY4NsQBEtjaccai792ZIYW/mhLOkxO0GOCZeyqbulsHbVtpt+tcwpHXSvtT9j+loCFDvXl9P1ig2QAOfwBfe4dqdu2wwNjp9+uNCEwUDthv8bBBIu6tZ/qH6/Q4DvB28zZTYVgoY/6kInAX/W/smf/KwE2NNbY57dy80MlguRbW8EpCJZiXyLc0HfwSOmyk+3HcqJomiAxjiZYniseW/rieeq6YNGOm/Pb2HoeLn25TYVPbQWcVt/B4BbNp2sVkx6ymXnNQyvg3IYp2dLWHslB1gi2A5unZKN0+iPGtGQtIlgeY8dUA7OTSn3GJsa4nJtoxfdC9rVtIYJtMcdKWdV71lln8aqYK3VcVnTdRKxz/0gp2RExP9xWm39A0kmwDgjM2cihisDFF1/MQshCA8Harh2sjxV8Ty3xWHR9KeASz6rBO1eOo76IwzVKXK3jksjY/AcLqB0X/1VoYtRqJI8FmcU6gm48hvDhfJ9BhgjVFMHS7pP1IONgJ3OtHJDTlLHIh4MvgrEw4+zLuSPG008R4ljDOWiXhPw+hH4RQTt+yqOfZVfG8uEc5ExaR/0sCoXF+xVhg0kCNvYOSVnVfvSHQ9IukAlI7CQgpFDxm5zGJ/jgD+hz31+3jcNDL33qHXvgrPkQ9mscKDc5CFt0Tl/YqaKvn9IBwQAXcItLb+p/4K9LTCYiKqrB/yt3rHMk7/6RhQ3GGZujH9oRok8xlmq7lVf2JCi/xZ05BIbUcVufmUhO7CxpR/S1re/8NvaN2cb2syp8WivgtLDzHKRtxsR1LELMGPCQgO2LMs3Vof59ToVnhsAEI5KLCBMyddyUZuyHdCNH8Hx0TN6dOoLYaV4wNvTDffNcDoKl8raexKItzzFf7iV/Hz/k+IGl42fJUHixcHj5JDnzic1ua6ZwuzMYvAyJQCKwvQhASk7SsS0ESyTjfcX8dy7oxg2lfGWCpQXsFup2jmhDN5V+QiTlxTqmiNcCO4aKWcyDeJR4iAQ4rzqzsmtG/vkoFcmZ2iGUw3Gd1jmwA0XA8bSBRd4OgPxwynL2bV3yqe+nCLElHGD76gmESrhd8R4dL3GGYvrJ/S8t6QuC1eH7Bsn9avnLINoIexRjY++QlDVFsAKjxvajESih4ucMxdiCI+Lo+8s5u0smt9Rv9ek0+sj9Q6FbDpNy7MXu6qiVH1gpj/n0JB3ohCwE9moj8JfzHOrf10SosI/LmBEk39rKWPMd43KtX9PA286P1CVHO1m3H/X90RBbcIDwMUbYH/oU36yDQF/aOUIeffU843womPi7X3dI6IlDgsqj7TYM2QxhOUZ2n6C4LW/T1nGTEs8sJ0GElYYwDckWsYja+ck4tVi3cqTdrzrWyoNgnU+h5oUJluewY+yg3PU5JdBWlEG+1E+Xz/yI0ffoM5ovvxG1Zj/oo8d+tnSbc5JgbTPAqT4REAKQD5wJN9lOEYB1oAPJ0GUQnM4V8/TpxuMPUy6n9JZ5ckNlsvvXlf9ftdj9/lD5GvJagoUDG1r87Rx6gkDfI/QkR87VdVpn8cki/rkSO2IR98IPTl6Ye1uCYAkTHCu2fJ+O/6NjJmjxp+41Op7tQtWjf60jchGXJWvfVPdDOn5QdkC+0GPbcMBD9W1/LRfhxFERsNVhiAwghz/g//pcx/K0DRY4POpy4HDb8C5ORGjDfjlM2sNebKq2NruBYH+6DvQwRsj5Hix2qoJwKq8NtrEta8cGPVxyjJ0yYYlO/uaK92sZu1aeYofYadQJfaMPYEidX+YQju9TTEAnZW3gb6nquLUFTdo/asIm5UMUuNw9FOp8LoVDNmMvcifquLvIsYPbjx1F1+k4u8j4+8BYDskWsYgOa04WESyPsftH1W9xfY17O8boNfeIeQSJsmyJsc1zlv5bv8epEx89RY+/x6NC21XgSbdd+lNvIpAITAjWWQUI756sFZdyKXKuzssnf4XTLmjRZW4AACUVSURBVJpz5dtCOXoWuIvbvDWn0W/Hxbo05FRMDMac2Q/2NkFwdJDdEixfRvpYKy8n2T8hFuujfh1/teiwOM6RSzM4gAdV9h7FHGPhDhWc2xTSTzsMZwdpkKMZ6xuOwuv10H+3oQfMIG/YFfr37L+PydiqaPByFvgEwRIx6R1vtK38IFjC6ctKc5P/YbqBnIccfkEYvB/F8u9hv2SOVrmJcnWeegWBx/VzEj9dx506GFdkkKePVV7pNvgpwjqWaqO1FT0xtrosyBhFW5IxbhDYVr7V3X4vPRfZtftscykKedsZdaUPDOjr2Li5jX4Ha5QoqM3jpc/1iI1ZmwdhgZywg8UYnKyDMKNXc+rdIpiT0gmxI81YDum1HHGQn5KB/Lwfhx6zdl5XrDUveOL3QfXr6Le+9a0mV7WNeTtYlJW6yLf6OV8UsOERI1htRxcZmuWJQCKwOQTYwTqzVG0X8s1pOzhr2anROx6t94Ld9ta/vntn9vck9Dw5+V9thbt09TDK/xkd79JxjY4aSps4eQcc89e0uE95O+Uxhlw6CoKleG5QfUiEHSCyowRLzqTvm3XjDE0U/Ae4LnNs51/1CxP327sByJqouh4xckGwZG91jEXAbeNkHxBOONpHiVhAZtiFgSxF0KW5sB9HqgzbUZ2i7ztTG3tUfooOdNTdDeWD/9DYK7ve5F79Vmer5wey3AgdenSz+JEiXHayg6RCsr70hJznInj38pTVOSIMSKv6/B0slXsHy+M7Q4SkJ4Kw8w8AZ/U2kE9fTbDqDpbyfK8XMhH0Gob3Oi07PlvS1O3H2WKOGR+HRfIeY8fUe5Eri1gzb8Lm22+/3fOY4iBx2uHqxxzbPGfpv/Hqv4vomBeSYM1DJ8sSgYMAAQjWGaUfXmgPgm6ttQut4xpybDRmYuA4DBCJ4FJa7KCMWHSH8l/rMslereMlOkw+okjOxwQlzuUQcLZDzs0EywTCqsdiCNbj1Z4dy1A973C0DqrVhx0mCWM7WLa/1986K3Taybf6K8FSv3vH67ZxhvyBtXcycKDsiH7IikRmQrdkTLA4d5/4U3FjzneCuqfqwPHSBsR6HsGC7IJBJTidrZ4XD9COyuy0wT2wV/2+byqK4B8+6MdeMByah+ikLIJeGRAkQG0NYWoxds48vo5NGKqME7JximA1/bAIjI7636CDS4TsYEVQv421s6Zi1ftUyYAsj2HhOiZY7ts8eWPteEO2/J2I0zPU5iv15+9fVMw4H929qZ4+0J/ebtrCRgJzw3hthmD5exfKDuTHI9bwgexktpUIPMII4EwcbnYi4ykEwqlpUWZ3goNFtQ8s0AQv+JOzBZ/SiRNfGIojq85bFYYcLM4gXjSqcpzrMrZAsAhP0HG7jp4AUQYJfKoc0pi+ICAIKhw15HSVj3PDfkhMq4dz7wYoWYkqaQdkIBdDfcbZkY/D26e2TbC+S+f36iGLDyqOIMLxILe9ScYEi3G182wdtB0mpI1xDduFbb8790cqox0Cr2lgblSCo3Q7Tzw/vBsVZcL0SF2ion+EVn6So0+1y2sjOKefMRdLupc3xshyA33gqvot3lHWfXiXyQTB/a9i2v07UwT1ZtkxRbAk0NsAvvQV7B6jg7mzVNAO6V1FkLGc0dspsa3M2afoaMevE61j7LGOch6CUYLDNnNP3LHaUYxyfcRYqt81oxTQFv0joNN42aYoWOIDPe3cX6LK+kSYrBkSgURgexGwg/2a7ueovza3t8ldp711ahg/tPh7h2KRM9tU5+UkWeSPkPNiZ4WAsx1yKt7BYuFexpZwDnL0dhhjBAtHP9RvbCEfewiQqClHFrn7ZXr9vZMxjqVaEAxk8AeLbnLHsfsyFMTnPe37z0Q4Ag/1Y4hgVawKQVD1aLsSLOXTt+psRd6+R+d2kNg4tYPVERv3K/D2jdMiV68S9tSbh693sBBr52I/HpRVEi5SZNvcNvWHAiSFYHkThkmuPk0y1KeFBEsyJlgQJdKLwr+UwK/wdGURHJvbrZ7v1sm/0uFxG/ouWN56HTu/xsVmXqTq/lV9ep1KX4+y2N3isrPqGq/NEKwY+2rIAUwkwTqAYGdThywCf156focWilUXiEMFtNap4Qj7BRcc7Ei84K8VGzn3aPP1r3/9Bbq35rtlAwtz72D5Jc4OCSSG+7AW2iL5kJGjt3PtCRD9fbN08XqBwUvIKsfhxN++KF50iZB2WgJGXbet5KDN7PAEwZK91fEhrBBtK4Yg7hNX8Q7W43V+rY4a9AMiMJQO2nM/bUvFSuTHY+mdDepBXKYIFuRNO5Cu71029EZQO+08sc7YwWpunP5hCQc5VV7ft9Aje0yw6BvtYT91+vGnvdq+SFHg6jFW2WAQZntKQcgrbcJQ5U0ypMsExGW9DeRTHzt42GIRudsQhm/R8UMmcapDGNI7KdGn5Pnbrt9U0hgPYlcqWMZjVfU0CdvJ94ZQ54PeOO/6k5KJbcFPNDboNF6rrp/YfL6VHug4CdaBRjzbO+QQYKFSp79Tx3mHXOeX7zCLKA7DuzRDi78X6LowL69+saRJnRzcH+n4A9UYu4xiZ8z9L8vYYqdD/wjEzosMEZO3a54c9trXvtb36ER+8wEe3Fj+7eTJvt4hkU0eBKXXj5OxY1dy0CFXglXIHHIO0bZOwGOfiKIJFsRwyl6d4wDZcaA92+G+tg7aDhMdECPbPkWwlN8G6uOzjCNl1k3a82PqEiEFwutxxHLWrQ1kRWgIFrvN6KSvhH4eYucZGqsgCbL9aQiJQN1GPBb0Hq7bS1mMg+rZRrI/puNNhUhwzmW/NvQ2mJQic4IO97utM5g2iSuFg1gMVDTG8+Qt43hGjcYgCLD6aQJZZfWamX4+17ZEvh4UMW7xmtE9J2MGuzmyay/yYrZ2xakwEUgE9iOgBflP9p9lagABFlut/0cdqQWV4qGF0TsUSzuUgXZGs3rSovMzJVwX+qaiCRY7OL782xTPJKNDciwmOcTVucxID2eAB+v1OymWg+4dEtkmKUFyyCiBPrht6g6RQu8OHaZ+931225AOLg/WewolO0WwSnvoR7YnWHX3QQ7TY2myYNsXESx2FZFxqDiqXzypRn44Y5Geh0UGQ07555QKVb6cR3Tcccfdp5uvSX9UBzJxeUpxPw8pe4mOd+t4jvQ+R/GX1c6NikfDpZdeuldrAOVvK0KVYCr/W8hT7Da9w1NEZ2wIUlr6CskHy5/VUcfYFftYGLX9adO9aHtuzPp50crEfByZlyGn+f+Axp3xdv/q9/jee++N+o3Cti3ar3g1MsskWz3LyK9VJnew1gpnKksEEoFNIsACy83b8aNPcb/gotYL8hBB2GSz+6sNEA9+ac84ITkK/5peagdLjt72eueFS22VYOy3YG4KOwaJhWsV54aMiY2LcDJumzzj6HJiCFbISE/vlDhnXMJuEQEc3s/pIEC4+hDvO1Km7bCDrgRLNzrX/qs90u7fPIJlEtj2xbqxwf2K8RHpqXNI8+mxCMjB1zzOHX70R3+UMbpQO00/oBidJjv9+Lv+35cMAYL1QWGCbYvC8bqn7DUIyZ7af1fSy0yt2zs8LuptIN+E41jht0/tX6bjP7rCWPzggw+6DUT6cR6r5jrz5D0Ojmd0NaTaBMvfiw3t4Pa623N0ur91Ds00MJzR6hmW2MbcJFjbCG6qTgQSgaURYBGtBEvpGadSHDEK68LMyRqDF3GrHCRYKmx3sJaxJZyOnKqJwWYJlu3CQdvp1TwlwAwiZGLjskqeSsYMGZA+HJHt67HnnJ0jdqVMYsJxaUzGdrDYTTlK5eAz43RFOivWahtCRH8gV/MIFm1O7WCJ7FYcpMekxQS49kN2BGlhV0s6BoMIyu+WS7TYO0awwIBgDCFafxs5Cz6k/77mgQDjWGu98pWvtL1TBKvto4WbvpI1o8tyfXziiSe2/Xd7vVh/7vGbJ2+9lu11cBnV42OCZbt5kWhPnEyM4i+lRD5dt5ebaafLsJ4u+8CcJsE6MDhnK4lAIjAfARbmo3QTLg6WMLSYe0FehtRMtKzwWRx9WwNHMLNAyxmYYGHrQlu0kxIy0u9LOFsmWLLBDq3aK/3kYRPttI6OPrhtyNkzdd4HCEM8Panyvs+cQ9xaghXjU9rsdTFOtGc7WltCdt++fXaY3Bf1ZWVyQCwWEayl78Fqnpijz7GDJf0ztiivD4yXSUA/D63nrlLpiRqLT/cKljj3XK6ihWQwhm7bZb0NYFbxk9CMLlfsY7/oteT349yL+9yYzZvrMR9H5kPo0ffANrt/1jczl1XBtkXbzV9grXqrhfW4Lwc0ToJ1QOHOxhKBRGAEARZSdlDiEqHiGaeixdsLtBf8EVWbzjZxsgIc/owdchTeIUHOTsJ1hmLb6x2ilQmW+j7lKHR+R99QIV0QlH4Hi7qQHdv9h31dnXtHhvt7ptpSGRiYYHkMQkay7Cj1AUxoz3a4/3X3wU8bUlGXjiBXX9TBDduLCNbUDpbkrTvuS9I5IXbHuifm4sbx9rLhRHTwk3lgIjU1/tqFeUWpcUOJ2XVdZg5MNSSCNFYHsuHds6gjjKdsIFN5dQdQp0sTLO2iMc4ehxm96B4IJkBjNlPFOut49Hp0+ZVxhuyeVcqsb6iO56BlqHKCLrFeVuouG1nPsvJrlUuCtVY4U1kikAhsEgEW2Uqwhi6LqPz2ohtHvPYg52kCYt0QrKEFuiVirQNwvT4OByKnCOkgrEywVGfKGcpZ3Riamg85LhxhECy11dpFH2j7fjnYw3TwhGQfKsGSnr7PtA2xwe7Qq92h/630+/UXKH+puA/IVII1NJayzw6ZuvfqvCVYU31tlGMjdpio9vdUmWh4HFs9fjJvyJk3TQR5oT59JbQ6NvTizOuV91s6HnrLW96CLTJ9djdR+XOD6tjWXo4x5NULbZiygYJmNwjCYtLb1pmXNmHqx3msjjFr51Qv60unY/3aKJdfr1bFC0tl67M9rU7b5rY3NG/vaS6xtrLz0tYzT2bbyvxrcdsaSMWJQCKQCCxCQA7nITkKyIHXpBmnorIbip6nLNK3mfJuZwoVXMpoyVSo1a/ovdddd12k9WEn4fOZWI+gP6inpHCEr5aT+EcS2DLBGnqdA45ebZh8VMek9sCSy39DmCo7QiVY0tM7Jc4ZFxx/4PGTP/mTn1X6eTqGwhTBkoCd7uAPer39/ct6QWlLsIYcLu1gB6SGeeJQ+2miIftHCVb3mgLr6ON2zIcwoz+PvvXWW4ew7nUNnmuujc0b+gPOYOB+ztjAQwLN29CN72BbA5noxvYZvQOyZBnjMZuReQ4f+pHyAeI54RaV/YNSbruHxttz0G3PUTm3yHrmCm1X4eCE367GUm8ikAgkAiMIsJAepd2OUaeiG10/Weri3Ncejj32WDtm6x68RFh+RYdzkDOPyx6uMBSfccYZdhLPV/m/18Hlp1V3HaozlBMbuoeKpquM0m6zzW/Lya+hI1W9HOeMy/HL9FdyOGIuc+FfHlIdvzzVu0LK3h9ErvZKBoIFiWN3csjhUgFniU4TG/LafsaYiGjFOOqG7pYQxA7WwAst0dGHRQSLsTtGpDnmqtobs7fXW89FkFrbar4S6AK7qlPY9OPBC2k3dYmwNGTdLXalaDCy3JjNVHqNjl/VDt+nBzXsz+T74p1c67M9+6X2z2XLtGWrpGewW6XyVmWTYG0VwayfCCQC60CARRzHObqDVW50fZZ2hC5ZR4O9jr1797akh4UZQjD2C9hkbOg1BVOqCyFr9XBjdNvWlPzISXUU5TLVjFjn6O0UkXNdxzN1lVF3sKSntRVZziGF7MItJJQSwylCTgkPabcG8kSYurdokrXBpR/+mNkypyt/yOEijo2QmtZvtf006Y2xKa9eQP5LOpa+RCjZSrCGyI3KaYdLYiZ6rQ3KXhz0QyJsHZCk7+xgVZ1DNoiUtvNnTNeA+siKeSC9tY0xwZLv8RglOxrDv9Lxgwv0UNzOH9tt/W11z8FlbWzrtmnrafMOWLqdqAes0WwoEUgEEoEOARbSSrDG3lekRfy6iy++uHUunZrNn+Lom9puYx4pQXwhwSo6pxyFCIX1N02OJ+UMFzoKybSOqm3PfXA81FDt+0Bb1Is3oausdZBDesjDcQahUT8f1E4SBIfA5b022MHyhtm/VQGYnK2j7UcrDwa+1yfy20t+Ii2Bqdo0+d3QmGI7+WGPLu+O6Q595aMSLJ0PYYa+Y7QLFTtYHe6tntG03kc1Rlawj+9BtVOXAmcwL/0K/eq38R1tryuw7naOdCJTp5Ybs3lKeN5JN3+sz/a0VT3f3XZbtkraelapszbZJFhrgzIVJQKJwBYQYCE9SsQqnJbSQ45tC+pXqvqnkrbzH7Mj1k4582WdW+8orH9Zw2zHkDMKHbKllkFsGsWu67gpqslKsFS3d0rUOwFJlc04+6phf4K+hbwc6oNlJ2l/6f7Us5W8kNPLLrvs84puJK1Q+zE5rZ8zBEvkouKqtoxpe/mMyuSzA/e1ZW6Slp5FBAt9jxYWsYOleMxeiQ0HEb12fFoh96fq1BOXlTC2gk7L3rudXjIO3SvYbZvGbF6y2Zn5Y321r40iz0HLNEXLJ5l/y0uvX9Lb8evXnBoTgUQgEVgeARZxbsT2DsU8MrC81tUln6RLkHfp/pqPl6pe6HtN3o1ZdgerX+h7EtDr78+Nh+O+nMfZuMnd+XaKnNuBjdaVTCVY0tP3ufZRhGYZgsUOz+k0PM/5axfmBolwOJgg2V7nO54hWNrBqv2UbffocuTX1eZdrlBi7DlDx5jeTnz/JUIVzGAm/fwlzzHNO9uqDb2isXOInvo/VGwbq061Vwd1qILux9oUwZKu2saQ3ibPNvVzuBFZOtmSV+sbIpCeg8vaOGaA7/8bK9/W/NzB2lZ4U3kikAgsg0Dza9r36cw4tmX0bFVGTu/WcgkSp0ywE5ic7f9clWBNOQqRgRv3q1qckpM1HnZ2Q5UsQ1nbnvMdz9QV/nZo7FLVdBGsDry8s2qmfpcBUfIlxVpXeYucnTEf6yMkcOpG+eYBgo3LL7/8DuH6nCuvvPIaybUBe9hMGNPbyvbvmBrCDH3M09jBUptL6Z1qZPzEuhyPS5YSXW1cdhfVutyndo64bCgOOc3Bse/CUJ3BPOloCbr1+f67to7noOdEW7ZKuv44WKXSumSTYK0LydSTCCQCW0HAi30QLN3esrSD2Uqjc+p6YbddvaifZFx2Accp1yCi8sF6slzCTtHxTK2GpFLW2u06jmfqKqPuYCndy1WSpHFpHeSQHvKMHe9r8m7Ss7XT8s1jFUq+MRobe5yudzijSn/JT+TqgwM7PnbkLSajpsjm2n5DbFt5iOKjRKy47EhYSu9EdOGn23a8sIJ+FLRjt1DeAurbsm24f46tYuVYc7SdPx7veQRr2e/XoC1qb2h3bFB2OzKTYG0HqqkzEUgEVkUgFm8t+jxBxS5C7+RX1bdVeZOEMafyEjXwSzpuXbKhuCSofl2p4wI5xfZSyUIVImT+RT/qFKW3lsn5m1Sg21g6HmqvOmnVdVshJ712gF/SvVJ3DlXu8uw4yQ5ypv5+RO/Ouq2T60+Nee1HJ9ASrD/uyuadGosxvVN1RQRbuSHMok8ak1OoqLiVn9K1iRPPN8fzVNw0r3BOGZfiCcu0EZeeERZZMY6cbipobnmMqW99nl9Vp+ac5+CWCJYUrnopvtqwjkTeg7UOFFNHIpAIbBUBL/aPQZHeV+TFd6t6N1vfjsB2TekRYfiMMl41lTn/JBy1nNQtqvv2+aKDpXb0o85cumuZHFRrt/OtY6iBSrAaMhdy0msH+BfSO/d+oKLYBOtL6uu8Nns7XM/29uXYGJcI5ah/TrtV39ULjJx7LrWYjIgGuW/lZuw3HsLiFKXR08qP6h0oYHfll7t8952YOWai0Ynp+uRRR32bvicnzRQszliJYEld9E/9NY6LWxiR0Nzy9wri9oWCn+1paxn3JFgtKplOBBKBRGATCMQirgX3VNX9ip6c+rKc8ybUrK2KHcFmnWdvSFwtkFPBqW4m2OHYAQ/psAxlrd3OdzxUtxKsfgdLwrFjI9vfMVSxz5McN4GT7cuDvcjY+SKChf2+R6/t35g+55sYzMPOsht6LUKVU1+GMAs81MdTqKQXv1b5qmSJhOa3//S4lbauh/Sk4VPbgj6t3UTwXRVj1JjQLIth7Fq6v70dq5wLqwd0CTaqCNv3l3ny9AEdXyh5nhMDIktlLbvDvJSyVYXiS79qpZRPBBKBRGDNCHixv0R692nxXWanZM0mTKlbN8GKqwVyKKvekBxGNaTnk1NWNieSsXNmd8B4ImGSUMubapGUfN0p6XewRARukNCztGP05r7eyLmd4qrO35iP2Ul+EKwVL8uZYLWYjJiuLbJjjqntCxdj18oHwVJGEKwO61ZuM2m3/TD3l/X3mG1G4UCdIFiai25rQGR/lv738g90xvy4en/u5lIiVx5jduA+Li3XaN6+bkDb50qeCfWAyOIs5q70n7tYcnsk4ku/PapTayKQCCQCSyPQOr+hX/ZLK1qToB2BnfNW1Xqt3dIlDznzd40Z0pIOOZUWT5OENq9XM28Ha0OO6jodfZ3BczluY2ciMig3kBnETH0cc/zk2+HO60uv2rJjeqfkRbAe8ovSRwiWn4Y8lYp6XcNSeqcaGT9ZydZxNXNLVtrBes1rXsON6Z6/cxUvKtRDEvU/FPft2/ew5tQLh+poDu0p+XFP5pDMsnn6YfDhZWXXLZc7WOtGNPUlAonAZhCwY9lM3e2oY5KwLrvsoDZFsOQkrlUnv12O5z+PdVaXXyoZ7O5hM8GaRwQqwRohFWPNDuV7B2vVy6GB+ZydFeyP12OseFnOuMzrf+3H3XffXeWGsBApAE/G8ZRSaV1zBHVue506i5k1Wolg1VprSGjcPDfQ5nk5o1kPGvDiWYIvFU7OdtlnEqxdNmBpbiJwkCKwnQ5lM5Ctm2D5DfWbIlh0QI79z3VUItR3SmSgdV4tnnbajvuqnFe9uoxTLxcOCS6RZztW0mP7FY/ZWfMl0/ZvkUkmWEvVaTHWO6bG+sDuXBAsXUKrdi0yZIly63K8RJWVRYJgtZeUV9awyQratfL3akP3mI1hu1GeOH2pmvnpTTa1I6olwdoRw5BGJAKHPALV+cl5nr8D0LAjqHZt0aYgWMcee+ym7sFapm0TFGT1kIBJBafeKZjntCvB0i7DqOND2aKg+h9FRva8b5FsV25iZnu74rq7099j1sv158ZiXv/7OnF+2mmneR705TxZGQSLS1194RbOrcvxFlSNVvX4rmtujzbUF2he1n5deOGFdc71cpyL6P5fHZ4TQyI7Pi8J1o4fojQwETgkEKiLvS4RreqYtwOgcKwr7pTMsyMuEV5yySXb9l6e9vKL7G4fEjBhqRj3hgpzO11eDlrTvdwy51dcccUnJPfYU0899ReXkW9k4nKQbPFuX1MUyeqc2yf9eqGBcxOs0f4P1Imsiy66qLbZybCDdXzJW1lvp6s9tS7Hbdm60rcXRdvZxqCt7bxs04PCB0Gm7ws4CLqSXUgEEoFdjEC72G8bCVkWHy3+e+XoEW/tWrb6kNxfK/M7t9OpaCfFRKJv3wRrjCwgX3cTdP/LlggWyrTzsPKlUOHNfWaEcybRzKf7QcEq42LZef2faWxBht8N9hX1tbVrQbWFxbZx1fvXFipuBOJfCDQX65g3ZZlcIwK5g7VGMFNVIpAIbA4BPbJtx4JzfsQXfjn7eMWAYt8QvLmOlVq6NPh9Sn7jlpQsqNxdFmylTQAqxm1hSVfM9VTclgnWgP6FWcLIBOtvRoSr/fpD7poekW2zTTxXqdPWH0qbYK37EpZ/XDgeanurefEWfBGs7WxjqzYeFPWTYB0Uw5idSAR2NwK6vOVdhh3RETkfP8X0mHUYdOmll+4VcbxhHbrGdMzZHTOxmIdxJVjSb0I21tS25IORFB8jovgrIw24HxvtnzyPyNZs4WKCNa//VX7JhP/qaK0ES7Za77aRH83D39TrEk7VjeS3LNnXdYvxjite/XDQhyRYB/0QZwcTgZ2PAO8e2klWytH58fDH7iS7NmmLCVMlKAN6KsE6+uijH5EdLGyS8x99yazGxPZ/fZUXcGoX0gTL9Qe6v3KWCdBaCZZsjUuD6qv1r2zYMhUuv/zyO5aR2w4Z7Vafe+KJJ560Hbp3ms68B2unjUjakwgcggi07x7aCd3XSzv9tN8hQbD0yP5X1eeAfs6rCR7RoRH5MEFaiYyLrDyoutju+lvuh3T6Hr21EiwZ5h2sdevdcp/XpUB/8ePd4XWp3LF6cgdrxw5NGpYIHDoIaOei7qDshF5rR+22YsfVO8GeLdrgHax5xKTir3uhHrEdrHn9bHawViJKIld+1UL7ZOW8ppYp8w7TWokQxG2ZxlNmdyCQBGt3jFNamQgcKgi8dyd0tPw9yNG6H+jXdoI9W7QhCFZDUIbUVYK1d+/eHUmwNruDpc6aDI29/mEIj7l5ssVEaB5pnatjpND60jePALSbsnMQd9Nopa2JwMGNwAvUvQt2She1q/aQSMk6dz0eka6ZWDUEZciOSrBU6B2vIblHMs92rbRrpP57B2udt8SYtK0bjxgHjdVanl5dt3GpbzUE1jnhVms5pROBRCARaBAQofnL5jSTa0LAuy0mWkNqdf9V3bXSrt1XNRZDYo9oHvarL9jgXZ5l7TEZWqe/s861blKofyb0a9W7LFApt14E1jnh1mtZaksEEoFEIBFYFYF3q8KNXaU7OZfvPqbLb0/rDpaIjJ18W/6Ip2W/772qZHAZo1Rv5R0svTbkmXqhvevNNCOMfJN7/Pn0jMAmM6T3S4Vj8ab4DLscgSRYu3wA0/xEIBFIBIyAdp7+sdOO5bQ/X5z2Cc4biCvBGijbEVnqh3ewViJYMt67TUv7O/3dz/XzOi1b7i+YrnWn6corr7zmda973YX6I+S3zWs/y3YHAktPuN3RnbQyEUgEEoFEoEVAZODuQgZObPO79I4nWOrDpnaw1E8TrLXd5A6mBb+1vs9Jetk9/N1ubPJ0lyKwVva9SzFIsxOBRCAROGgR0OWuuESoDt4zp5M7nmCJfJhgrWSr/lvRl/rWtqGgt6B/XFj+jmy6cg6mWXSII7C2CXeI45jdTwQSgURgRyKgt3bv0WWn7zj++OPfM2agSJhuOVr1ytuYtu3J3+wOlvp2v/5fEaPW5u/KTtP3bk9PU+vBgsDaJtzBAkj2IxFIBBKBgw0BPRn4zgV9WmlXaIGubSkWqfEb2Vd6hYHeTL/2Haxt6WAqPegQyEuEB92QZocSgUQgEVgNAZGX3UCwfN/TN6zSO5FL/xfh1avUS9lEYKsIJMHaKoJZPxFIBBKB3Y/AjidYelfXXQXmY1eBm8t5+oPhJ+jJvCtXqZeyicBWEchLhFtFMOsnAolAIrD7EdjxBEv/kXiX/sYHpI9bFW79wbDJ2apVUz4R2DQCuYO1aeiyYiKQCCQCBwcCugl8Z9/hLpgvueQSv25hpR2sg2OEshe7EYEkWLtx1NLmRCARSATWi8CO38EqT+7Ra//R8noRSG2JwJoRyEuEawY01SUCiUAisAsR2PEEC0xFsv6FXtdw7S7EN00+BBFIgnUIDnp2ORFIBBKBFoFHP/rRD+/bt6/N2pFpPRH4ezvSsDQqERhAIC8RDoCSWYlAIpAIHEoInHDCCb6/6VDqdvY1EdhWBJJgbSu8qTwRSAQSgZ2PwEUXXeS/odn5xqaFicAuQSAJ1i4ZqDQzEUgEEoFEIBFIBHYPAkmwds9YpaWJQCKQCCQCiUAisEsQSIK1SwYqzUwEEoFEIBFIBBKB3YNAEqzdM1ZpaSKQCCQCiUAikAjsEgSSYO2SgUozE4FEIBFIBBKBRGD3IJAEa/eMVVqaCCQCiUAikAgkArsEgXzR6C4ZqN1q5umnn37YbrU97U4EEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEIBFIBBKBRCARSAQSgUQgEUgEEoFEAAT+P9AbCm+JtUm8AAAAAElFTkSuQmCC\" width=\"600\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
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"output_type": "display_data"
},
{
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BGspUI82x0FAxuuwOsHisZQRLO6s/B2siU6wqMeNrb5G7idO42DcKYtyUn0iDnqBfgtBefqj5D6HctULpkum1Po6VCUwJo3hW/hdeCcjldRYlzK+B974xjeKXN2BXzCCBTk3gkUbPudE+5xIo9aWE6M+gTETnIQeFqcsY459Jv0YqEiA9JC8E+pxqzJ55lA/s3EU+ykTLK5Pn1dlh14hf9T5k2N0LZ9g8UqCCKx+G3DeGN91112XUAVq8Si9NyqCNY09rqrGdkGwxoYsCiwyAjJetulSu7rT8dOaRe7KdJpj4xvBQonICO7BT0SwqMeNrV6AnrZxF8HSSY8UlQjcOsjT8boe4N5A3nbkpDgPRSfytw2/E+/kYZJ+ao3q22UHCBeUYPEjpiJYWjNNIg3m0umn4fVtw/X6BiDhpM5f2tc4jzg3Ozvrxl7kSrrIr+eFBTdYRnzZTyJYu/APsHbOmFdlh14hx+aJY3RNekJ6fYZH4HoMKzdvPYY+1Cn7AfbK5wg1Z0t2sxcEC/TDHdIIaMNqk5hDEWkjDjPwSfrQDFAA5QmWyMtEj/XAxAnWFuqaNjbqmxEsQp36yJ05F3R+XpZyHtUpsbQZuqPdiZdxmxbB8psAESwnJESn5oys8htqIuVqa1VHzUqXXr9W4Q033DCN8bmxW4hxdQzj0En23zmDEAn3QdiP1Gn2qwjWA5dccsm3IcQPEd9B3YfL6aDrssczJr0bOorTDbNuHGbOP/987UlhslHX83SPodzmV73qVZor/S5gEKx5AhnFDn8EZDC0UcyxaUWwDqcTrIm/FQkmIlgiQXqUN+1To3yCxaMNnWDJ6RHbIKc7cz1SfOIgoSXME+mQIpdfN4V+aI36TcBCnmDtTwZZbanNlnOCbd825HfMnHy3ZEdNc2Ll4ajlDgs59pdjLdyli/yUZl7joz49Dtyqb82lCkT2p7EO59WfKRdanepbxbuho669fIKVMNHp8iQneo+ivE5w5YJgzeEQn4FAE4HWCdayJlh+ggVh0aMBI4wo3VHv9logSZHN4q2ulsAEaTIudmzP8b2UlZwIyiBn72EwprMHCS1hnoyZjJoIafNR25h9K9eoCNY06qy7ICNkd/mEIxMsZCc5CfA+6ARLRu+kCdep17esQsZcEixhr/mexOWbllSJ1uLhQrB0gvUFjYtXIexRqOJDXD7BSnJbCUVC5+t0wr4lFV5SbOMR4XynMMotOAJJmUu5Sam504nPsctZ0UOq7BEh72I8wDhEilZwt2dpPkh9E4bTiu/36yGhESzqlQGe9glWxv/KK68UeXiQdvwutatbftJxyBmN97///VLmIgy78Dr1mwYZyhhR3278MAKKyNhuXIJlj3OZK62NSZ3wuhV/NOtU+E3daT+n98emXvcUKtT8yuk9u7sJg2AZHM0P6YYvKoc5Pa8p0Z+otS096E4Ea5ITrHXMk98M7qGuNV7xYodBsBYb8WhvZASSMte3baTUzCVCMvOBD3xgIiKBMl8lpe71LmZIu0ameLdD79OIMM7wQmaP4brjjjveSPL/4pfGH678IU5GdGvCpqeeIeVGyZYxMfyZB73EvRc/TGEdsgSLd5hO06AZy078NAmWr9GFumPOBCvth6aR59TA/2JEZFhkb6ITrPSSvNqS0dMvbPvc6nJqjr3+F1RmjzWnVumUKmJfZYJFXPPs1/Nt4XA+wRLBmsXfClbzPcG6hfKj6L0+/NN6PY22tQ/ltAeG6SsTXIiPIFgLgWrUOS0EXJHlEyyMi93pYCjnTSQgV3rp8U6U+o1vf/vb102rs6PWwxiMYPHbN/6IcObee++tx2NEAJkLR6hXBGs2YVPXM0LxgSKag4w/8T0or2EKy43wQpzkDOzssEwIiM13UsAiIaum8E27jBFzMBbBoh86ufkL/DMH9R25TLCQ03ycSJmW/vZ3sETc9XtZExGszZs3+x40gsUvbPvcDurufPKeT6FHMCZvbz51LFQZ75OfYOl0uYX9qO3XBGsXBRddD43a2THltD70SsGN+HFOsPzxt5oT0T5He0MX47hrrrlGepNtaPtQEZ1gmS4dp55pyU6ySKbVh6gnEGgiUH17x2TYdEawuJOehEj48/1zMRi/P+pGRqluxP8exOy7mx0eMZH2jGAxBn9EOMNY6/HoN5WkIEb5nzIjWIgv1CNC3bW7G+XI3Y3wIWc0wN5J3y7iOsGaQSl7f32M44YywEZCqVME6yTWiROdgXWxls5H4AX4qwcKzj36dSOktlaceOKJflpVFvV2RbD03pTWxrwdBF+PB7UOb1UIQZ0UK1XTcv7C95NamUuZxpzqBG+Gb/1pH9g8Ez5MafN0NcHSntLJz+HgtP609m7Cj3qCpZsH0+uEWmsqeyJ7Y+xvVlY3UHpMuZu6ht0QqtkFcUGwFgTWqHQaCPAyeL5z9PrYfLYRIUY1IXGRoWFhJF6D8PezkZ86tNCcwO8S/Hs27Q+OKN8lJoUywxjyCRaGrB6PEQHaGngX+M53vlMGT3/jodMKYXP0FE5k1D13J1K3GxWlLetHhGBkpI9Hsv6IUORWBm8SJwNsGIGVCJbqHIlcIu9k/UtDOqD1URIsrR/fH7ko4ysJ1iwZE51gsS6dUNkJFvX1tZkbnyyiUw8Z17Mmq2ZBSmvM95X/lccXPox0zbM1rTednroTIZn2vvW6FyR897vfrRPUnp9rYe3pxEnrdD4ES69LmKMeEaxxXpKfK8gnNsP2HV8gsn1Iksjr0VlgkSNBsBYZ8GhuLARMmUOIdOdojs1nBIsLNyQpZ/SATWhGg034R5R6CKV+6bDSKJPHIvO8JDeJcpURsROsk08+OZ9g0ZeaYLlh1LdyOh1G1pQcuNxKvYYNJzJ1XZ3lB2Ukhak5KAnWKHfbKrMdf+qUyd6g7o6aJ+K679WvfrUe95iRg0RMSrA0Xluj1Gkv17LGfP4G9guMz00Cw4yASLkRLMpYW8UNSNmG7wsZuW34TWXmPOJ2gkU5I1i+d+ZRT2cR9pbskO1JxnaoEiwn0IOw7xxjlaH1ZqenSp/2vq3aWpDLu+++WzcE3y4r50bV9JrGg9djvtXMra+fUrSO57WdMjYrLPZGLT/o2vQlXyDam4Skr5bMBcFaMuij4WEIoMyNyLBZs4GHbBmJIJw3iaA+U+Zswt30QS+Hj6LU/x2yIg1/i5/IINOeKSJeZH/Ax0OaG0aqN+fH4wMJFmO4UNLcUX+DwE84pLAmdumLBEfTt0xwqVQKa9iRuwiHPVK66aabRlGw8+4rCvzHrrrqKsNgxErWIbeLNXCA9eVGbtI+6gTR1ignY9dR/37qfvyI/fFvSw3rQ2mErC3m3tZx1Y6vIxGs2/DD6q2K9176XmEN2Hz6da/UxFda404wh/3G2sSNzaOCfJPhewHs53WTRXmd8pwMjr721B3NlZzP3dzVIfqZvonbd7LuX9RhjPvws+o+N46jEHzpQ9ddM+xpre/t1PFI1TGOA1efF9sj6Ffp+CVzQbCWDPpoeAQEpNhmUGalgTdlhAGbN8GiSjc62oQ340dR6s9H7s/xe/Benuj4DiVgBIv/rtN7J13jsbGTP5BgkX8R/rbXvva1+jVoI5+QrUmwobo5x396eR9MWaVkjX8YwVL7IqP6E9th/ZfYvByKWPrrD1kf141RwVpkdyZ5O8FiPiYizNQlnAyj9OvRX+D6GamNYYE/Zhm2pjLBwmjY+3mEJzQqdyOtdSXfkmkU60yyfvG+oBlM1liL1HUWHiUDIyzSK6fTv1Fudkx4ET/y/NKmzTPYuyEfqxuc8mhviEyWe8p0AGk+d2PVudjCfMEoEx/WQ34RnX1o/Wc/SQ9tVb9IG4Vg5bVdjGWcd7iKYrYXH0S3mi5knqSvlswFwVoy6KPhYQjUdyOSh1j5xpk3iUhG4m4M9ENU+S38KEp9I3I34GWUJzLItC+CpfevdIrSNR43jMMIigjWdaorKbYZfr173thQV3b0zQgW9ZYEVwprGMGSwjQSg4KdCKvcmUYEw3yOJzOXw/rkovpGkd3V8pK4nSIwH/PuYyJ5MralwfxfXD9f76l4owPCsU+wmA8zyB03GTJy+uNprS8RMV9HA7owMMsIFo+i9yJ1H3VOnWCBvxP562jD8RjYqUXOzASLNWd7AexHmdu+bh533HE+H06q9CjMdAB1T2Xf9jU65QTWwPleJYQxrwfWiPf/Pk6zZiWD7CaXHRBKXzxQ5U9CsPx/QXWDZ3u9qnvRLoNgLRrU0dA8EHDFe4+XRQmZMuowLi42MExGwl6qRXAb3u+gm+VQgLpLcyUro2xGpyk8QiLtG8GSKC9Dd41H31KSMh+JYKkunB+zS2FN7FBOZkTob0keRLD0NXW7W+1oRO3vUh53kEPJCz+VcRr1/TO/+TWWcWUNPKpo/7FFfFBUc2cnV6985Su1rnSKOO/59G/ysUbM8KaGP0S4ivdUfjhdDwpOT5nDcBKmNr+QVlszzIsbtLJ+zYuIEF06IIK1EmxXlgLjxKlDBvRe6thPqD3je3KcagbKMo9OOm5EcKw1MLDi6WX63s+n6eA7L4LFWG3fpLnxHjrZau4psNffzryKcCr72hudb0jfM8Gijnxj4wSR/H38KLHWivSGr+9BzeW17ULgOwnBynuRGw3Fa/LmzSx4GARrwSGOBuaLABtVSuweFItOmswNMS4uNjCkXhkNM7IpHGjcymN9Nr7KDZQf2DiZtJ8JFiSmz1iSL0Ino6O7wE6CleQuok+68893wpCaluGVyLjOv4qeCS5t7VUlPIZc3aosvdSu/u9UPgZlKFbc+X4Pok9hbn9CZcZwZyMr0nEv/bp8xHKaeyOMlDlA/A7CoX3sqpu+O+HIJJT1ugX5f8C/pKuc0pETvjKqW/DDSF42QmBva4b5b82zESzqkxtouOdEhn5mQorknbQp/KbqwN8JlozqqvTN2Km2MWFl0kNmtCHUbrx93vuqRl+8gLn9930ZJHC6bGNlzPaYN8nYPLH+W/OpU6AXgPu7kP1/WnUuQdrZ3ia6JusB7z9ptj6R2Ua/N7jsgFD60G4eCpnNxNePuxZoL5Nh1QV22uN7FF8KFwRrKVCPNkdFoGezqNAQ4zJqvTISdoLFBhzlRMqVqYyoCNYwYziwH7SZCRaPDFwZ5btXFLTytTe3qq2ub+IhJ+UlcmAEyxUbpKapqJEby1GfGQPqy8aAvpuyQpnmO9ey0ltuucXuspEzgkU4CnmxulCOzTrL+ss48lLuu/BfJ35pmTcgrrm0uU8yt1N2lD42qwSbcm2UMh/j4mldc5cEfbzf5HrYmsoECyPdR8qLhrWObL7A3kLen3ICU4iNHFW/7kjSWv9TJ1jg7/3TCZZ+dPdQO8XSHBuB5lRSmNLlud/GUn9rR96fkPZ7kKyz6zzfU8yNk1+d8vbpgLIc9W1K188t05cwvpG2tWZ1A5UJFpemw0jz8ewmzde4xLtcXtsuwJhFtmf27dt3rqeNGIoM55udVEb9WBIXBGtJYI9GR0Qg3zm6vBsXrjMh8bwxwqww2cgiWAN/zZujbzcqdyV5PSIzIjFGm1mUOkqCZYqWtJIU+cnRrAoN+CbeRcpHQRvBIup3gfPum+pzR58c42wMMAxGsJBpKk5OdLxtGWUp2s4TOG+H0F+avbhIGyWqPqg/1+INixEKaS57CBbXIhHzcmDUJFjMyT9T4Sp+MmMQ8XMMv42s1vogJ1zNcPHzHhZWa8bKpjnzNWUEizlxAjOo/q68Ei/h5nuhS37sdNaU988IFteHLMFi3+s0/R76OGi+jBwg8z0NMGxPVTctvr98v9XFzkkJj2d+dTq81G49HTCdwxgzwWLNuw7z8WhvnjZCZ7W2XXeZODfShiHjHZdgZd1etOs6q0hanGgQrMXBOVqZHwJ9m8WNCxvbN/N8alZZv8sSERhEYnS7WhpRe1x2/PHHu1GYT/uZYPFTDdaPcjwoF697pyrntMjbr9sSqdi/fv16HadP5QsAZQOM2/pBf8xQK4++7FVInpMDXWaH4TCCRb7eexj1dOjsVMGGXNFoEfVB/ZGyv5g2RzE+IgjlHa7mf5ITLDO0GBd/dER19vV0M0BEz9Z1yzHnbny2kX/MkP5nI9RaM0X9MtJu4DzsMtxFsc6oyKftEUIRrK612FnBsAzGbeuMPeVG9ZAlWGksd9PnQQTL8pB5Uj129oeNlZu2vKdYBzZPpQ6oyolgaT+dyqm14kvttE9vSJ3INyeMzXSyvydL/m58U0+ksh5obWt82XEjLd2n9/5Oz4mjRbQ+e/Yi1+rHkrggWEsCezQ6IgJSVD2bxY0LymsSgpUJDkpNJ1giDllRNPrmRkXfTjFCdN99902l/XRHvL8cD4rKTrBoa5f64i+bN/olgnXjz/7sz5pyGvDCfKPo8CTad2PghnpmzZo1hhelm3g5wSJfd6SSHYW8+CmXEw6KjeR097yHfl5LKOMzCkHTb1aJKLgbtY8uX4eGA+Mu69S7NlLq+mbnurpAce3GZ1Zp6dFwkd0TzQTL1wy5LeKUCRakz4w4oc1jT22jX4iQlgRL11N1aZ09xIvRauc2/LhGdar9aVSm/V+Scukk1wk94uxjkXxfh4/tyeQijVXJeU/5e5ikteZTsqrv44pQ/kKFS+zUn1vxD5V6i76ZTkSX+s3rHmR8jQ/qcl7bLpTWuN7h2uhpI4b1XM3w3txLRiw7dbEgWFOHNCqcIgJ9myVtPH0FfRKCkzc09ZjxQMl1EgE2uSlTCIyMqB9lq475ukzwUgX65eM8HhSUGUTa1V2cHgHaHXGjMf3Ynz1WUR51TKNvZTOm8CGTZqiV8bKXvUzKUz8k2MQLHDU2uXEIlpO1cQmWlPde+nKttTjkMWF6H0rktTSWmv/mWFKdwwIjh3wtfW8pyDrV3bcMjB6ndDn1Xy/h7kgCg9ZUXrNJVnOQ10xKU5AJFnEz4pC/SQiW5sbJo3CbOsFiHOqfvqggLGS4z8AfSq7WQyJYzT0JSRbp1x74PL512mR7ij2e9xRyTra6CJYwvybJXUC4ZC79yOgpzNV2OqF+l322uL8ni4zW/yh7Wni57iKa3SyxTflqtEg9VzPpt+lGKz1lqSBYUwY0qpsqAtosPSdYqfYe4/KWt7zlMgzaR4e8UFx2TBvaTn0wPjrBkHMjP3fV+2kEC6Kjd7Ds7sy/ktwrNvJVbj+V0F/mKM2cnzigoIxg0cemMkdYhuiWuVL2DSXrG+VahtfFRg6T4XtIv6lUFRIp6cLLScK4BEtjPZl59PJVk81LGbO9mzZt0qOl/Yz74qZUSty8ebPNI+NywqAczX/XWFLJgYEI1kP6652GlH78tZNgkSfjI2JmBnbIH5jXBEs/xdCaZxk5J1ZmxJGblGBpvuWE1SRk1CqpP1L/nHDcSv4hQ7CYI51I6f84Sz2kue7akz7f/4LMae94xzt68KI+mwseh/p4EZubL/Ja86n8k2hf2N+IzFQJFrrzyW9729tGJjE8QfDx6aagZw16/9GNtv643o3MGkJhOMjVa9tltxEZuW+pkOaltRe9zkUNg2AtKtzR2JgIdG2WnhMfCMgbqPcHhrxQXDadNzR3W1JcOv3pUYSlMArC7tpXrVqljet3Wqpjvq6PYNF+JlhUao8ICXepAfK6lLkMkQySOY7CjWC5ovP0CUIz1rSvk4XSDTK0hgskUaRskFxZn7C3byUR6lRnVLeavu1Nj0hvYNyPGlSQ0zUjWMiUCnjUPnZVLYJ1WwMjycsIrVOkw2msMkK2puj/oDWV12yqq+cmo6g/EyxOXN2IK22+Tmt/QQkW4xbp8L5qPZ85387Opxyk/pKumzNOpER6jsaXa6bzBMtPm1kPX1FfOP3tOcUi3QhWeSpc3MB0zdPJYKSbguvx56veaTjGdiW68zM8zv48GNhJ7LB62UMbJEN/thNI3+Q+MzYjiIzN9BDXe8k/jnZszMT7HPWIfB2DbH0TJ9lZ/EZFxnDa4+VcjVF0+qJBsKaPadQ4PQS0Wco7R6+5Ni5GMtikT3WBIeEx5NuG5tTAjAcbvZNgUa8IzoMvfelL70eBmvLgiL/rbnNI05ad20/C6kv+MUiUnikk+rQz5TsxSJczM+mofh19s7Ergy8ATIP85TaoW/1ww5fTiQizLrycJKgvIi+jKG6dINmL+uA7yiMFxM2Vxv/zpDwhpTcDjIPk5bICZoyDxjInPfjTCFaHiAiW3/G3RNaQuAc/L4JFudYazAQLLP0kodPAtTpVpel/8+zEj1DzOclpX1V1vszrjDZEtHtISZZagAjEYi3Vfv3aa6/95Y7qfe/lNYOcdJKn9xTzvcs4vpYyzu0RmCMkBwpSpRso3cD0nAZ5GfonG+3vDYpgXeB5k4T6UV/0y1uo4yP4tfThP45Yn61nyPt25O+jjkywiPt69PWs9aKf1vF919cE5Eu6UM7KzEXzpwjWpnw1WkRYtWzGaKWnLBUEa8qARnVTRaDzBItWfDOrQdvAbPCLR2w9nwaM+GvektepWf5rG66dSIzYZI9YTbD0krsrGgn2nGCR13eCxf+BmeIh71av+YorrtB7P3qxusTGs8cOqTsb66rwIEPruEhhSq6LiFmVH/zgBzVuGVg7wcJAjUSw0onDCfTRlelnqUOPir19q7/6MFwhHl5Gd+I2FsJhjzGqqvKlxndbvuqNKH0QwTSC5aSdPgzqu/JKIySi35pnYWnEip9nMHLMelDafJ0IlUioY3UiGOebgflWWpVT/6yvYKDHvWtpYyGIXNWsXdoJCe0+sZVJmhOpmmD17clU3tYY61g/vSFi2kOwaMfGKl2S5D3QfGay4om822ftUO5OylxP+iPApk/O5UcNudl4FbL34H8G/yfU/+9GKUsf7ARr3bp1unmo16D6dT/9e0h1sa6NmINF51xy6u56r1zbKi63Db++63TRJPo/NF/lXPVLLGJKEKxFBDuaGhsBbZZsDIvStTKyTU/+ukJmUFSb2k6wkqK7nbCTCKB8ZMhcAViI8mgZt0Ftlnm5/ZSovrii0R2tGUROpGT89W5RS5mvVVn6sVOhXBpLfbo3lzm/z2z4quKdpz70x8ZBX4TTUII1Ozvrd7ffUhuUW1211bz85je/6STUlennEDyO9i9tFiCRPMOVqBEQydGe+rhy0GMMyQ1wg06wZGB8fK0qRCZ3421NDTkVHZVgycj5+CxMRr3V/sC0RH6Pl3GXYMJK0U6Dqcx5uHKd2UkmdfQQk3nUOWqR05Ng3n9VQSNYjN3XmbIVb+1JYWRrjJNxEUaNpWccKd/IJHmlq3Wa5fH4zrCmnH5F/wYSdSPQU2dZyShx6lEdP47/TciQ9vKH8Y8hfgHhQEdZ6do96bG81lcme/RROlHjcOfEvHO9QPT8psL2gBdUSH2zBEffcMMNpuvKvFY8ETHphXKuWqKLlnbUorUUDQUC4yMgJdbaLPWd08ZU9agEqzZWd6A4OpUAdWd5/40X7somJVilQukhWPTFlPTLX/5yKbDmb+6gfMxw0w8zfmn8ClSvK60ieV7R0vCVFXQSJ/rubd9PHzvlisrcgNysNMqPRLBQzGb4KOLr40vE9bXxJ6ielgMrw5WwNHBmBHiM0UmwW3UVaYMIlvo2iGCtIX8P3teCY1dUn6N5DaaUeg+4YCZY6SRBp5qD6vVyfWFBft1Qaj5n2APzxaqvjZSgPvucLCrBYo1uSn0YSLCQ8XUmcd30NQmW7910ethHsMjP86OKCqcvuuhdrx7nj7XJ0z63L7TQ5zNKoauvvno1c/1mvNbTUMfNxPkIraGej0uYG7m/Irib6x/R9RCnR4Q6vZLrIVj0sYdgUZ+vm07dyl70tel7YK5mPim/TRfceLh+z3mtSOOmqyW2qGlBsBYV7mhsTARkREvF5sVr4+LEatD7Ll5WoZSpSI27YUQgGzc2vSsCVwxexzhh3b6MYPnYRXdh9oe9hE1ljjIzww0xqAlWzxcAxulUQ7bLGAivLqVpuKAUZTAk9zAUfzm2uhknWLvIkJJfXQu0rlHMPQSLNvS4Q3+Z00mwqNsIFpi5MffHXvqR1q7xtJov0wYRLM2N97Ms43EZuT1cjLKm8hpMhbUHND+1q+dMdc9rrfKejZNDM5TUYyFzOzLBYl7ejn9h3cnqOhN53k3aSZ7W/ESnNFX9gy5PT5kbOoRs/pinUg+pf8159TV2ySWXaI1tx7tu8urzWD0hhdIBfSSPU9c8B/wGnU505LzPdsHfyfwOkTfQ9g9bwvAP2yPslX+R6Cte8Qr19WNcP3d4URu3r4daD/cQLIi4EywfQ1/1tGlrk7DUxybHnrTxEjoJ7itfJvAXS0Z6qUvzc0i4IFiHxDREJ2oEUMraeCtRGq3NojsnbWZ3UnaSq5WZ59eh6najpjwpgkFGQ/JSJvrRTwvpV9m+ssZxNcHqOcFKSlqEQU6Kve9uGRlTWjxCqAnW/SiYSfpmjaaPLmMwCC9TmJTXCZbNHV9J7+t/0YgTLNWp37QaiWBh5K1ODFC5Pj5HHZ0Ei7o1Hv0IaCZYlBcJ1F3yoPmXSJcbRLA0dyfRbtf7XWvI34MBsTVF3LHraSuV15op16zKtOa5Jlj6zbg+w93TQMcFa90wASNbYxhMw4rrkbBiD6svr8H/OfFBtiavM/qqd5P6Tn46ujhxMtg6sWquO/pj64z1kddZWtfNNZ3W2AMvfvGLH6RzNv9VJ/NYq3TpgL4bEdaG7XOwvzP9Bt1u2jjDy6afWHiRrkm/3NOHhCKvO5iT21yOMX2S+JPTnHlyK9TNn++fnhMs0nvWHqd4rps6b17os6/5cm1buxDK7akDI51gIeukV7gfEm7Qoj8kOhidOGIRGLRZauOiTb8Fv54N22XMSiDrrwXLcHQqAfKkBFwBeOiKoax31PhAgsUYSiUmxd6nzJGR4tVvVLmy87aFzSR983oU9ihMz0AZC6+mkaVfbsxF9MwoYZw0nqajLjfiRrAQEmEZxdn6oHxWpsQ/S8HHpG9Y9tVBvhEsFHfGjDS1q8cRzfH0VdKfcCpls6Eqs0mXgTmq9X4XhkzG1N9vsjWFfIswlb/w7mtPzdQ3GUqTO556lOdOZea7HtaqEurbpZB51LzrtG8krCBi2eBDEM5R2Q5Xkw696C4SsBjOT1c8rNts6SGtub49mQpqrfvNkea/rldjLecnFbO/hekjWGBv7RQEbysFTs+F9u9/PnGR0v+Nf6ynDwnPJv/mUoZ2/olrrb9hdZRzpXFIR7hTeekfc+gmxUUcO3Ur48r6Yq7Uwc9EKPVPDZsOpg6MteZqYIGFzgyCtdAIR/3zQoDHE6ZY3EhXlWjjmjFKhkoGZAt+JT/sN4qBlnxprDoJA3JyasvkMc6mQOiXtW+543/UBKt+RCgl5kq6SbBQOlLc+mZR69tIk/StHE2pTMt0kRL9Nk+LzLoxzydYnBh1GSPVaco3/VzGXq5XK3EEZ8qU8ZcE6xrKreQblk1jTn81ngP6uQ2v30kDeSORBi9XhFpvtxXXOUqdfgfvij/nFad66r/3x7HLcini6S6n5LwHKuGaFOtRrRuxSnTopREsMNopyfSli5HJKETsUm+B+GM83gjrdbZoJ1j0xddm13rW3B0ob2TAU3vyuNa321iPeSzEWwRL85MJPnF3zUeEZPrNieuDraSd7oXoy/OJfwr/RXw+2fL8jvBs0reUeczPV7nWnn2i0q+66qqL0a0XlDIprvF5X+o1KL1j+lGy1CXdZLpC1x2utbZL0VnGuKlMGBD3fZZ1wgDZRckKgrUoMEcj4yLAphq0WfLGLgzVN9UG7yOsG6Et/bGu7qzcjaIEzLhhvL2cKwavY5ywJliqszSC9QmWY5HboP8iWC1Fon5O0rfcBhEp0767bdoWIV3xrne9q69fpHvbUtauiN1IkN3nRLAeSj+XIaIyFsHiZCRjgJHQyYcU+yMVNpwZt6T4LRvCLGOpMm5oG8XaSelxiupsEizSrW/0sT7F0KNmw4521b4TJ8eubtDTXU75eQ9UwjXBUplybVXi3Zf0TXvpAciFEcX0pQsRtlHJ6HrK78Lrsdaju1uydZZJB+2KYJ3dIjBeB6eCPwz+W/CT2jBfw82TRtpTvv6DNN/IpDmb4YeN+9YM48wEi7hw089alH3M+T6WFNY3WZac6pvh3wocnx1kmI6jXs31c+jPRwm34Tci37rpIavHnc1VzwkWdWmdfJnyT3grv5EFqb6G6z/D167UTQNPsFLBFsks67S1zWmn69UyT/FZ/MY6sePa5pKbc9vTHTKLmlxO/KI2HI0FAoMQYKPbZmHjtTaLjIuUix5bmPFGyWzRNU5KfZjTpi6N1bATrCyPInqIspP+F+IwglUqYY2/T5GTZidYhLXrMry13CjXwtgVeylvj9V4qbRlaE1hYpQfhPDY3DGHrf57fSJYdyQDtpf4SAQLeasTQl2uj62U1/jPxfc5ypS4Wn46zXqQ9Taoj311KaH45mGTYDFuIyas0T6C5eubPt3Fbx2pz3KG3Vy059PTyzXbN8/UKeOqU4SSFMtwefmeSke4WIvMzjQ3fiIx8CdNqjo3cL0dfz2+OSdJvp4XEaxjrr/++jNTfl/AWN9J4llgfHFfZiMB0vBw9u5+/CVVtvSMrWfms2+eyDOCVZahbVtzyLfWTDkWI9j+W1apDuWX8+NVa576HhGSJv223//QnfgOvOk4xn6p8pmfT+C3Ez8W4tnak2T1uE3Ia6/U7rMkPAHyf0WdUVyX49M4tN7cSV/UYxvl5lXly7Xt9SkUcdxUJnTFGZPNR3nT1SW7WOlBsBYL6WhnLAQwzrZZ2DSmpKrC2bgUj5+2SAb5dZVsz2UyQq13sAYpJhkoN4KqT8pgvkZL5VsEq1SuUmL3SBAnZW5Y2NXBj8UgWKUyzS2j2EVI5ezx3lw0fwoXnV7pjt/G4HOZJYoI86E6vL6RCRZlZPgeSHfeVmMiv1uoc9Ajwh7CmPqpE4oWxlZv1wfjOlV5lG0SLNJt7YJXn+Gmj3YDIRKKATbjQlpprMpmfa2VRijvARfEuFp56inHqDI9J1jvfve7T+Q/6J7h5bpC6hHB2lXl3056a94rMbsUERAh+Bb+LEtpf5wAVrnP4CWCpVO+rpNIZduJEn35Dl3UjrWwCv9/kW8nOpBcyelnEF5SyWreZ5WGLumapx4d5H1FXvujdiJENhbkjGBzI1LW23XT0jzBoi7V57pAa20n16bjGJuRVojejaSLiMhtnAvan8KFnIdRdnstQR2fI+0S/MtTXosf5PEhozWo8bjT+iv1pNIHEizm2tYmbZdr2+tTqLkZOKZC2PZUddNVZC9+tAXg4vciWgwE+hGwzYJitLvFKjsbFzaoGUY26C3I6HRJSr3TYYSkZKV0yw1tSsCVcaOwkYYifdIf86wJlpRraQRLJTYuwdK43CAXXZ5XVMqzviNVRXbHD/Z9pJR50DgMWxS/z53G0+XsBCtlimAZaekSLtK1PnoMX8rbTbimkCujTcKIQPO3xsqCrTjrxfvaJFisXTOwyNlaLusoSOddwx47c0duxIny5ZrNe6Co14wdc1Aaub4TrLvvvvsnaf8TGNufKMq2ojLku6oMkeG+ea9k/NIJ1s0kPMITG6F+kT8TrPXr14tg6ZT44oasvi2n/XuG8oif35Ih7a/xf8p+vzzlGxkhflG69kBzYwSL9VwSIc+XfvF1bGneV+RbBCuvMeRs/qtHxDnfG0hhrQMsGQx65KlTBGu1fgSWuAjoba95zWv2Mp/bVYA+bVDY5eiL52+rZajv71OacPhj/Opahmv1xwmfdIOtuSTXIljCoJOQ06bpKsZZru1UnQXq56YyYUBcc6lfku+qa0DRhckKgrUwuEatEyLAhjPiRDUtI1oaFzPeKBhtZCmfgQSLF3WNyLCxZXjM0ZaMxjHve9/7SmWRci2Q4ig3rdqfhMSoD7n9FLd+EZcrlarG71hYZvrQuHsUf0ovsSnl5xMv+5HLg7Xw6vo2WSaj3OFb/4q5zHUUERlrI2zIiWC1lHohPhdl/qRMW2tDZMeJT12uOR6E1M8WxnX5nmv6YO04Hj2ZcxduiFoEU/2XuwuDoBsDGdjmmnIjRH69Buv16u14uxSxdVauLaX5adJLdTHArSVPe6p0mvuxCBbz+i3K6BFdl73pOcFKj8OuY9yPLhv2OKRJc6W5lOs73Xj729++jvSnWy7fKlVIXZekayda6dLmXUZcrkUE+tYZJMbIIPPufZgrPfeZ1xhyRrCqR8TKb920NE+w6LfmtJzPHWpm165dmhuNRWRUzsaAfB8ec9lzn55P37aX6YozP5qnn2e+riD8OH4N8nYCSNxdOVcah5N/5Ws9Sv+Uzm5ey4QqbmueNsu1nUVIF/nVe2y+X3JeI9I3Vw2ZRU3qWvCL2oloLBBoIGAbih/sa5GIvLFRcm4YpYR2oBDWN+rKSfw2ixuxckObgb/jjju6DIfKlPKKl4ol1z9iZBjBKpVql/GXMmsp6mkSrPor/z48w4uLlkESVkYe048tqozG0+VUh9XH3IlgHY8y1djMEe8iS5r3FsEaRACy8UvVeyCMR1HgLm8h/T1NEf5PbXdPxsELN4yt8Vt7fEnD1/cg0t5as3kPeHOcTmh8IhP5NIhLrVUvr2y5c+aCmSeA7+kp3grWkbiryujBV2SG9moj7EW0F0UIZLi15jfiexztywYdV/VZMl/BP1aRhvM9rr5tqvPZ489LaerrZSnucmdW8pqHrUpDl5xU5elS+T3rDDnDF5JieFdllGbzDjmwcoRlvVrb5fx4ce2Z8jUBT1d9WZ42jfBy86K5ORdvX+xIX0TQmujDmLTs6PsGXRBuz4lFhPn4r9T1WyTtwa9sfJFFjxetP4xLazbvVeLSiepD6bS3y/GXeYrb2mQ8pjPqTNoSwdK/B/j81SL5GlnNle+nnL6UkSBYS4l+tN2JAJtFBvS+9IN9tZw2thEcNrkRLL7mr40lpWEKpC7g1/fdd5/dzVMub2jakiKWaxEGpUsJlARL7ddGS3Kjuppg1XevWanST43LxlhV3kWwWga1KjryZc+jm6KUG46+foFlxirN3X1pLoviPVERKMf/NuXwaHG1wne+851SzHs5sXi5rivXpUxVVxdRzrhWdXVhXIn1XjI3Ilj70jcgezO5wlBpnehdoT6C5euW9egGQe+tdZF2X2v1GuyRB2dvx4md+qR1bmteF8nJMH80xb/DExvhWvq0s0rP+GKMHwaZ2cH8XFnJzKRvAK4lXTc9N6f8R9RyXJuBph0z2kX+p4k/Pq2BItmiTrC+zFXL8D6b9C/hVcfZeDn1RcZefyRdkgKtIzPi9KFFBPoIFt9Ss75CUrSeapfXmL/eUK3/nF8VrHWAZ2tO83zSRxFWOWGgR4R2gkW61tk22hqo/5BTvtoSgep0yOlmR++lramE1H/vj8hUiaXWo9Z86XSK16VXJdda22X5bbpgXAOJYyogfWS6KV0veRAEa8mnIDrQgUCfYivktInduJhRQdHLUGkzDtuIfRuau0IZDb2/0GWYVaZUHDJ03r6KjutqglUbwayEUSxm/AnrUwIptvpuUf0osRm3X7V8+Tgg52GgpKDVtuaodhpbSQSkjN3w17K6lgLfrQj4u1JfrWteVhURkHJ9rcLKda0PzaVIW8tlXKvMeREs+iWCtTsZt6pKe/ldRk91t8av/u9LWKqsMPO1qevSeXrGlTb75tkNPjiWZKVV7+mU/xwNyDg/rWzI42m9reN6l6elUPj6Prkkpb2wkpm58cYbNa+yLzvw31I+bfqjSV2a48ZIc1KfuinpY/iVENDn6KJyIhdyX8Zvslj6SP1+Fpf/gBc51BjkNFeS12nIGQrBXrjqCy+S0/9YjkSwePne8W3Nq9Is/7jjjrOQ+ktd0dxTlNGeqokwST3vPOlb0054TyfvEdRtJ1gSxG3HD9R/jHEDMvoV94dUoMshZ3uRNZUJViLNx9GmjQuZeg32ESxk76CNToJFHT5mrdM+xwnvrBKR03iHuS6dMKzcguUHwVowaKPiCRHQ3YiMU59j09pdEZtuBV5ycjL4QxUMd5+2oSmXT7CSEtAm7lIEUsSlAqgVi9ofx9XfYqwJVlbS9E0YrPzABz7gRtbbWVCClZSpsGqROPVB/ZJCq12NleR8jmpZXUuB71EEZW5KHYKwWtfMx9kKcTp9qF1TmYJXSQDqMjLmrfHorndQH+t6/NoIll90hF0EU/0v17d++b6eY6uySM9rkLTWGjSDDwZ+wqDy9dpSmta5DN/n8Zfj+xynUiIbepF6Z5WZ8aWdR6c8fXGkx0FCjAQxl9sx5jqZVHuP6BHighsjI1jUZUbb8ylzI/Gv0P6PeVoRqu4DlPka4anvfe97rQ7l0+9zCEQ8MsGiDt2caA19Ga91daZCCJDPueZf3yQdiWDxrU8nTrld1Zec0iyf+m2t0V4p17VvRbBajwizLlD9nIpqzaj+J+Blv0WS3ekGc4NfdIQbSZfcQMe82dp00i7hm2++WX0XfjY+ohrfscyV8wjla12WbiDBQtDWPK8TZH1cFr7yyitVXvrhvDK9I97UCR2yi5LswCxKY9FIIDAGAoM2yy7qOVbvB6AUpSTvSXdkQxUMysGNWDZW3BXKaMh1nXzUpEFlvR4r2PWBwn8W/qeq/PqHTmvlqjGZgqO/FvJNMzcGXpWUmSlwT0hhX99o/3ng8yH8/yH+3ZV887KhTGu5u+ib5qh2NVZSxqWBqeXXkGAEy0PqVZrc2fbJR+NRkfCQYaydjPkp1CGjWrts/KoMYVzjW4k0L0ciWPSlr27S1Beb21SzDFPXmjLDxs1BNl6se5OvxtkiWFoPfkowwxqQzld/ZLi+hH9sVQdJ5kRI5LTXsqPdTLAod2HKeHgWSBEMsxl65HekpG8j3yfX8d6YV/c/iLyQPosQZkedwl3zfIsS+VakSIM58p6sCG19iqmh3wUAAEAASURBVPhOoutY8xqvsO0hWOx7X79aR3dQpqcd0uQk07PO+NkFIxjIt9Z1XmO80+nzZfNntbEXKGfl07UHIhhdBCsTZsakU1GN6ykqCBGqCVbGQvkNp3nZ3kjvSaId1y257+Bs4yXP+28yfHHIT+gUejmrj7HqZvjEAT8aq3l5sONVEJ16arzXUM8lVuHgD81VuacGSy9CbhCsRQA5mpgXAlKKzc3CZpOCmUHPrSOQUXG5bcRPRiGboSHe51CqZmxQTOUdk5S1HhFIcbecFEcmZMSlOF2ptORzGnX+Fv536dNjc+LcY4myfcWzESR+IorFx2TKFeNaK3Mpvh5llurv6ZsMKu3/OXlPxp9J/E1JbmDAuxeuWFttqKyMjhuosi4pzHJsUsZ1300+/Weg5rmHYHFtBIu+5hMP5vocK3Two6lMKSMCcPR73vOe1hpQP9w4HKxpbv20xjIDfk/B/04pXMRHIljIt/pSz5/WV3NNMSbDDzKSDS1pZrzLk03WjMkVj7DUVc1FSdxsnJSX4bsOfzIEpG/dsz+0t2TAba8pLpfwPSkZTJ0kya0lvSa0lscjwB1zIjbHq1M8B+xH6zPt9M0La/4PERRO358LEKEtESH94OlWpVPHJoXJXUCoR2B7kFPfV/sL0sjfzLX2up1ggZPWnoy41rLwaJ1gScb3IlF7tKgbov2OtyUe/MhrjD48RLLm1fYS1yJQ8q09Vd9kIWYu1+cJhBrXE/H7Gfu3i/TtxDcU162o8iU30FGvrS/GmNck8+Fx6z95JgOR9HSFluaVIyNcZzZv3tzcX2TV+sKLluE1XFxSJnTE1UYPGe6QW7TkIFgDoGZDXIDy+akB7HtA6eFZ2nD41/Kjf5d3STcUV5fooqbT70fhP4d/4aCGdXyPzIfA8SWD5Bp5gzbLriQvxS4FaIaHzWyKA4U6SMm4scmEif5JEepdGjMqjb6oTJZPca/HxKnjhxjjDzTKShnK/dBcYJ/1CZaMoBEs6tGe1Dd1XKlbuxgDV2JeTW2gPV0KLsvyDoM96iHtVxjfVYTfwf81+js0XqYv7Hp0UwgOIlglVjKcMhJ9jlM5N7hGsBi7yulkzA2+iJbdodP3R1YVdK0Pnczo0ZOMcO3UD/WndsJa66jl/pnEn+7ATP3c3SpUpGltjkqwetaU18HYDT/eSct9J80MGRjmuS7asf2QygvTTN4xkkYiKC/DZ/uI/eJ4pyJGYtbqgjzfa5ZHORFY/U2M6jEZwmM4Yazx3kj6va9+9avd4InYnIqvneZRzuXmrvh8/etfL/Kgd4yekhPnIlq/t3NKNqtL+rRpLtn6fQHxb6R023uQhQvTtcZyC+vLCBZxa5t6NP/Cw7AhLJ1k+vpG2r3U01rXeseqxF9zZgSL0NYB+b63ScpOBCvPU06dK1PWp6wdKf9m9ozKmaPebUQ2JB2SUvsCzcv2vtT+BCNRJHvfRWx9ffr+rmX0fpatS6+OMrZmeZeuXKeerbnTmL2+nF5GkLmG64tGsMPaw625Kqtb1HgQrA64r776ain/z7BAfhdl8nYX0yTrzptFnI9ziYts/Bn+SS7XCsk/G//HGOLvTfmvJnwbG/wfXYGTfxF+rfIJRfBuIPw7/fpyKtMMkFlVvotQCqnP1PPj+JcjlzdMKTNOHEx0t6q7+sfjf1s/eqfyb+XvKDyuaznubn6J4Mcp898bj3lMpuNDiq2liGYwEqY42XjrkBEuJse1FIzuaDcobDnulK2vYF6eskh00E88HEvdpeJQvFYYf8wYPwq+66t2vS/PVTr52nNHUV/ZvuK2nvjKvylt8m1M9NfbdeWmauQ0j67gLCF9SFllWRSbkRjq24v/nGQgH49RSF8exdfs+4yr8jCsbjxabUhEiswMlC4KVytMlfe6CjGL2kkVMSNYKVOExfsko30DXv9/d0bK96DL8N0jAU7gWm0qzRS+V5JCYd23v8An73EwO7sqo0v1U/0d5NSfLoLlc6vyPfNWVsjY1e8D6VuJlkWal837uSWHsNZWXg8QdSMRyN7J2rK+s18cb6tbH+RrbwnHnvGRbgSLLM2N9JROhWZYZyaveHKar1tZc3rEI6f361oES/Xo/bs7FTbcv5L2pCpdZe4AD9WpH/3dVORfQPx6XZPueuJiXdOGxnIL3ggW4/c511pW+4YNoblk0DV3yq/dvYyttcbyzxikAlr/Pke+X1r1iSjl9VY01lqz16T8Gwo5jXd7qsP3VZntcZHTPX4xILR9T52lnrN1xLidELlu8PHVY1f1tUzdpOr0+uo8u6YPXydyPHb4nKbAwcQunXBQYpFjrQld5C4sbnMozQ/R4ivwWhTvwevOWH818HEm8o/Itztg7hZfQ7oW1wfwvwQ5kQH+QSb56VzL3cbJ0/N/5Vd+5dPkqc7L8U+j/GPw2yRQOsquQO6/k/Z04s9FRpv+F/B/iX8u7b2MNBGXN+NvJ/5Cwl/Fr8efxfPvXyP8D/gZ8rSQ3ot/Il591PXDITO7yXsu8S8xnl+inWcT30+fNUa1J/cY/E/xb+nno1gvI/4F/Dbk/yPyuv4v1PEF9RcZvZ/xFNLWE0o5aWNfxzieRvgkyryS9PfMzs5+L2mrUd6/T/xfIKDPetnLXrZPRJQ77J9H9u/wz+Exz3cT/hl+FCflN9sS5Jn/LupVlhS8FODduoB4bcMQKrpRHx3OlAR59aaWMq6NhFdRKwGVzcoYvPKjLNKfg/8DFRSG4HI60evwjxMBpo8Pqe/kyfC5k3I14odBM2NMvo0Jo2CGFGNQKjqV0/p15aVrc8xJ/Svzpmypb+/GjRuvY370MvVj6bPG+1Xw+jDhj86VPviJjClNwhYhkaCMhNZd7WqsVN7qqgUZ0zrGJzKnteVOcTcQMga78NpPpRHl0ghRn6GizntVJ85wVKRwLWOlbGGt9Va7sz0BHBT/sl+n8DTwLvteZdul6m71pZ4/zbOvzboelb+PtpysKN/mnvVUrgvJyfCXclqrtrZUCHxOEj6EdxJa35E/TXmV096SHurZJ5TTyZHKn0Ko/XItXv8JqPiNeHdGsPyCsHmCRdsnga1eOBfBaTnV+Z1VhtaFHhEeoH9biT9c+dSj/XYB0f+pa9wOfZDuuk9r6Rb8Y1O6rV/94wD7Tu2frHR33/zmN33e+tYZMvdQr9ZTdqn9+luCmieTY52fiM5Vf7Qmaid9sLJO5Fp9uKdK/1q6/lKVrn2iudlAoLG2nN5bbbXfI8ufS+9DVygt71367evT1gTXppsY13G6sUZeJ1j1PLqOyvX0NDS35nvWWJWvSyOU1H0p8XKN1aKaz9Zc1XKLdt2a0EVrfIkaej7tvgCvkwQtho/hL2Gx/Abh1WzYzxMejX8W/m0stKtYOI8j/z1cfxb/c3gt+JejYH6dDf0fiItc/Qz+7fhPUsdfsxi08XdRbqdCyNgTCUXOfhSvtr6Nl3st/pvIvcWuZmbeR/h4/CfxshRP1cIi/3dpSy+K/jFpV+PVv/+B12aRUt1M3i8Q/wj+08RfQvhXeClbjemn8Rfhf4/+rWejfy9xjVNO7x+pre34F9POVfgXEX8qXsZfY5DCzYqa+N+84Q1veC9yP0H8jZSXYrsO/yQIxFto41cTudpI2nfjRayel0KCoW4VEk1FIPJG/XfS5jpkTsSbAoIs7Cb+IF5tNh1zZmNAKUihlU5jVH0tJ8VSKgEpFuHh7lEpInIuUvsHuuZU8lQCGUDN2esgwI/HkHyduI7G71WYnPpi/WIMGo/ybewoy30yaHjVY46xa9/K3zeXcvATTNS3LEs9q0mTwB79QjZlv8a1DMwjlYgT4e5ztGdGgfbLfpZyUmRnlgkpLqxKbFXexlTL0sYZSmMt3lrkaQ5PS9cypJvxW/GbUpoHWh8tZerGyI2jyyuUkm+NR/X09RHsLkzYySieowrcgaPGKXKg/g5y6o/6Wjv1pZw/ra88b6Uw/dCL0T4uyyJNRFr/15fLtOQQ1lyor+bA/CRFCKX77C6Fehxvk0kf2gu7ygTFKXd7CjU32gMfxX8fdSheutO5KOf1Nq61H3oc5aw/3GCqP32OMem/D9VW6USEtCbkbsCfrwi6aAOB8q7XNd/225neR5feu485uwcZPSJ8vvJxNi+Q1LsgWNq751pq+gBbnzetj9ppHdke8Yz0Ppy+2VyuMc2x5lpraFB90rMte9wiWML8H/C/js8OnbY9ETjpP9MzOZNIIkFaC63xlKIzV1xxxX6wkk2wvqdMX0euC239Mq7j0fU2NuL1PPoaL+vJbSGvOkt9kfM8wknlLH3Zy7V01Z97eiNUH0xvNvKWJOmoJWl1CRvlbuVimv9t/Ad5AfMyNt1P45/C9Vl4PfbS4pMyMHIlowTJehaL9zwm+snI/gb+Q2z8VyBzGf5P8LP4D2GMvofwOvxzWDivxqsdLYhPEf/PhP8fZT9M+Gq83Ie5/hrh6/C/hX8pbfwSJzTfR/zn8M8g/18hMr9P/H3UIbmv4pX/YvJ+Fv8K/Oso9zv08d+QLgXzEvr3C6R/P17fwvlx/GeQ+X/Jex/+0eS/GcUiA/kC/C/iL8RfgP8Y7byDUGtDeSdRVsryYdR/EeVeSPxH8T9EXJb71/BPwGvTPZ20XyHU+Lbj34B/F+WvIfwr/POoewXhKE4GT3PR5XaRsRYvOdtUtCOFsIM+bCDscqYkkHEl4XI7iaz3iyqUESvlFXdlI9HT8cLiz/CX482hoNU/uY/j76bNp2JIzJCDQ1YEpD9AvilX1lBPPgZNhEl3pdmQ8hjR4668JOKup2+0s1oZEDspKLkv4R+H/xG8ZM8Ht5byszT61mqDYjY3bjB07U64qF53MjY9hsgzqPsM4nfQfjnPe0hzg38K8dvxs/hMsJAXVrpbzhhybY60e1K0RbDq0wUvo3pWUm85p8q7AK/+fwu/Dl+6NelC63CQU39sTish4Vti2zNvpSxzKPzUj+xI61sXpGnMPXJca20d4wXBxwgNuu9Oxqs27yTN8XYxhVq72hM9Dv2p+ZBT/qmUlb4Teajx0dxuVZ4cctKpthYtIX2k/txLX0QwWk7Ex1+q93xfF7q+Hq95kvNQaTPp/S/hdDHe5+kW4npP6Vj6bPNyzjnnaI5EDAwbQnPsPV/f5fr07L51Dcmwdc6YyjnQHPv+svrQo33rFhmNP8+TN0LYt2bp+y78s/EaS3boBeEt4n1ZTiwis7OzPbqlyOqLMgbps32Ermskc2wS1LqRs/ULTseh1ww75IVj6XyNOwZlnuKq0+ur8+w69UVPVS5vChxMFL6tuTooscgxU+qL3OaSNve6171uOx14Vd2JtFivrNN1LZJFcBOPA3M2pOcTsOp/JOE78a+hvDbIV/EvwpsjTfhKEa+V4bzooou+oAzSf5vHb5/iT01vTNdaFFekuAJt0N9QRC4tMBGptxK/nLq20Jeb5nIPfioNmQvYwKcQ/+bBnLmY18PVK4q8W4u4oj+k971e9apX9SgB6tX4vpG85MxB2n4PHKQEP4PMbWyCd3Ba9znCk+jHF4t+/CkyL0NWpPD38b7x5irq/9Rm6elDJSLlvw4vo+JKXyLbaXujIi0HBnrBXHf+mtPsSNcjYNXX40hbQZ9rJSClnRUPZTchp/58Ef9ivbuhrx2TZgqV+dJjlc9y/VQw+QvdZZJWji0rV+RMCRb5pnykxLxj3G27surDkL5Iwcp4EF2hD51gHUABGkZcS1H9dKrrzYRvxAuvLfjskNOpiU6XSmOR84lozdr4ykTiwqqcD/XR+9sjSv0ywvX6203aRUlQNwuqaxb/tJQ2w4v7J/LOjy77lCn9bhIs2tI8akx94yHN50LjEcEzR/qZRESuNN/qS+nW6oJ5Un8HOfWnRfaESYmT5lnYtVwfwaLdvpNNCqodH7/X01MvYzJDyEmpG8LdpJ3mwkWovbCruLYoa2+vIuB8PuUU3Yq/jeu8d9jb0ntnkbaF0J0I1ok6RUn61NJTf7wvLptD8g0jXnNQv1WHnOZCOkf9uB6ZK9LrCBeQ9NCaNWtMN5KnR4jal5rHLXg5kZIV3FxuSidU92qvIqc+GDYSkmPt214k2rfOSNM6MkJF6M7mmf6Ua0xxW/++t+lXqz7po5Y9bs2pt9cTvuIVrxBR/WsSX0If3qfxlwKM+UTGLMx8vZfZrXjP3nUdRHnTSeiyfdJluONZj/bomXbrubSNKplWA6SJVFp9Hfme/AUiL/aLOhzndK4uu5DXrQldyPYOm7q1eHkE9AIMl47H/2drYCx2Gc4dyfeIQDyu7UkY4YL6pPz/fpBokpHcvF1NrgZVlDbxR1wmXf+tX3sIEfskBu4vuf5v+HcR/0WRM89vhFJuLUXkolL+MnKSkwF2t43IRr9ohG7EejY1c7gTWX0rkSEcVEz0U49RdewvI+tOca9Hd++nc72Vcl8lfvw3vvGN87j+Bl4GWwpN4/g0/mdcaaOsspKjjJSr3b0ieyLXehRj+SjFfVKKuNwexvE4JeBcec1d8UlZ62d6XKG4CL7epdHpnt5T+whG8r8Q3YdS/FPaaRIs8l0h9rWhenAak43Prg5+1ApTBqY2RC7dRbDUZ7lTwEMGVvhvshQ+kmHUpfrQ48hTe8K8p03m0TAj3fLLQqTdLcxlgEgv944Mswyyyp6Czw7sTgM7zdMkBGt7rnCOxKn9lpOR7ek37do8k+7zpHJ9cqTltSUB3Mn4/ew9PWbXtQhTz9iUiFuLv85ixQdl9KhN3/S8SMlgp9cg5CVvDsN7FutcNzLf8DTiRpQ4RVFb2rvuRGpqo+x5ql+PCDU3KucEy9eF1rv04bF79+79PsIL8Fv0CgGhO+1rzaPNE/XpEaHmTT9Gqr3ma6iPYFHG1jfjyXvVKyXsW9fInZAIR0lytX98jrw+b7OobkabvMceg7OuhWPP3JeF6jhj+nXkP6b3g8mTvs2OdGsfmVb7Wa6IlH1XsukgypvuJHTdcDx4GjllX9RzmWWKesuo6uzRxWWmx2nri/T/VfpSzmtf+9q+Peenc8iPOjavekFDPQYKN08EfvmXf/l2FJVejDfjNc9qjohibJADYPUiBnsp/pNslrfrrmPA4KUMBm0WKc51eBmlUgFu43oDvulo19rkFESGJzv6p/qOwRDXxsaJTakEFHeSozpOx2/l8clXdIGSfbRClI76JiOhcfwzfgPxS5VWKm3SshGkf1ZGL95KDsJgxgKZsj1X2K68JOrO+sm7J9bvVF/GMZ3gPgPhczFaW1WIujd5YQ8pZwTFf7Xa04tQdZrCLtIUrRVmnyEq5IXbrcW1oiI4p7GnVI/GqR+AnCVclwyOjOogQ+HGTWQjOx6R2ngo22esSHOsDftcaM4wi2CJHIiYZMfcnqYLHrX1KfssNBdRf3r6kvI1tnL+6jWVxCxQ3+t+2ziZOxtXEpaR6zFw5KteWwuS4dpkCP10Q2Ovxy3RtfhdijScxnyR0qlHMjvx63QtBzYXzMXs8Z1FkfN+1Wumr8+prAXMjREz9kG5LzUXdoLFmriG+JeRewmh2r0eXzqtHbmt+qBvNxDYFz0oo7743lB9PXPMtfWVvrsMSdn1rWv2vc0FJKOcK82xpVOP4cxNua23XNNcpI9gsfd8bn1NV0X6L3my8nekfoKxvanOpX/WPhi02q/Fda3T8FLv2DpiHFpTPbqJNM2j6zpF3fkad53l6R6qTqvPE1ohmH5B6dwcPraVT5rP1ahj66hmuslBsKaLZ9Q2AAE2oY7sr2GzvB2xjdu3b29ulkS89NMIgzaLlLqMgIxXKbdddeO7nCkJDGPPpkaRqD659XNB/jR5rkp5kZ5S8ZzO9Sx3VqpD7T8aL2ebHiIjBf0ZJdDOcxSi7Mo+Z+XKmE0JQsBMqaJjjWBVis6VlSsvVWmO8iYPwfL+SbZHjjn4P/itg74UQD2m3E899dSesqkZBRrTKvpVv1MnvEQY3am8GwpP8/AMIlv9QiHtyng/DMw26Jr69W0xGUk91vE0w7VlKHQyo2L4HlKDUbM+UFdp/BCzx3w2F6xLw94S5z7OJBABlPEtDbz6KYJ14LzzzvNTFS77HXKqu6cvSUrzU2Kr9eVrLYnkQH3vMbJOwMGn7HMfWSFfc5FvZLiuZdQ/wzO3NhdZR7CrSvNLpV+sC+ZEca17ybu7gIjGJnJqjnbVjlzdlvpjZMlyqw/2gREs5sbwZ91qPesRuKUn8T8gfCH++/HXpjQPvp4i1yikvHAWIXsiofpi/WKeRADt23CE7qyv9GEkgkUhm2fWZbnGhIPvV9WnL5qUusTbkg7I86RE9rDvm5659wKtkHFo7X8A/zjaOa+Scexb46lE7bLsuxJsfdKG99/X7/FpXUmvOZH2+rKMJ1Sh6iz1RZU9d0m9NxBTvx/XFEjrir6NOraOaqabHARrunhGbSMgsGrVqi8h9iCK6PKW+CjHvWykXZRdh5eBKRXQNq43suFrw0+yGXBTYnyjr97UO5SPIled2WHInKi4UlGe4qZskuAmwq0p/lXCS1PcFBrvC92NslN/b8Z/p/IgeKbYFaev6ssKvbtF3AymyigPJWuEifF6P5TsCtuVl9LMUd7kMXwuL9k+OQnTJ528dr2zpnIPlu/LqEzhpMj0+2rejmcJl4wV/Zax8f66jNqW7tGfDovAZEf/RbB0d3yOQvL1iGg2pQnnfDJItE+ZIi8Do/XQQ2owkmasqKs0fohZG1YP69GwV1rRv+YJFvWchtjerr/4UB3J9fUlpdfzUq8pL69Qfe/pN3fyvn7KcdbkSWVVb2m4a0KjevK4VSDd4OgF9p26bjit5dX4BznFF8HU9Vq8ObC5gIh+v6882TeMGyRWp0a1UZ6riE8MqxEp5sYJrp8yZVLG6eRvIap1qHH+GT47xmDriYRM9oh/Fv9EvOZwD1570PqA7hE+7mz/dpw4aT5K7FXGrllrPjdK097z9a/6yjzlm6Of0gEr06UHVh95PXPvmV0hL7v/DXnC/pmlDPXYPKMbmn0oZVNcfS/3t+k8bsxMx5DneuV46jbceP+tnsss06hfST36okNG+1HjETEeSLCQ6dMJXXUuRnoQrMVAOdroQUAvY5JwLb5JsEg3xcZmGqQIpDBPxZ+BNyVJKLcNfwKGv1SUlpE+tKH1uNLezvQMCI8ZE9pc72kKuTalQrQkDVIwpnjSjxFu5HorXu5beJ18yGkcemdFd6dyn8cbcUBJ5bEl5apfx9afQEsJ3u9l6KcUr/pRKjpX2K68JOLO+ln0uzbkLufhLBH1v8dRvs+o9wgcVGQ2V0WejFzGino0134nXoiZQdb7JT0ECwO8W0LgYDiRfzskV31UmhEsot5mlzLt+40iDLX3oQ8z8mwuEvZqSk7rQAZP60xG3g08UXMyztbXdN0VGMFiPmtdW8+L1pSvtbquvrngz3HN6FZ9Fi49Bo58rZ+yXu2LUkYYmuElNAfJ0Njkds0FfZ8+7l3UL0KrvbOukDqf+A3FtaI2V8ynz51na+1t94s6hCwYwaIdwx/yYiHrxNIl/5rXvGYv1zK8r8H/k9Lc0d4fEd+M/ztPI/ws/qLkfW0ZJpAP4eNOfe06cepb1z4XhJpzd5Kz/UpfhHPXmpWO0HornROssr4yvxlP79AKU9dDLmfYM8auPrich1qT1veU4OvI9nc6LdZP/GhchlX1/pv+nFrrT2ukrCdVZ0GPvigzGvEvkDbQZoD9qGNrVD/9pHrTT7+FqDEQaCNwDckXtrJQoq7k8l1qLcem1mmQOTZVqaCd6Jzu+WVIOW3oByijTZ9delwmJddDNpDvUSqpgBSMpUOKZFiOpj5T1MTVvrctpZOJFPHP4+UOJOU0d8WBTYqsTMoql0n9zO0lOVdWfWQBQyOlqDv/4wrZPrmUp2AbvmfMKU9tDCrnisyUdiqjQLiov+bovxkixrXC0xTSzzNS2EOwkPcTBSNYyNxx/vnn75AsdWxQiPM2vQ9zqQc/1aYZp4NJc9e0m7H1PE5APM3rVZYZJ/ojgqV1eLISCycS4kSjSO6LunH0OXMB3fWX+AoznzOX8VBj0ZiySydnKl+OU/umJE+SV71a8+5qGY29HLfk1uoDvEWcWs7mgwxf87qpKP/F4UKuewhWxyNN1S2cv61Iy/EDyz5uGyd98nno0Q28e/RFSOw78OWp2QzXW/CPxGudm2MNiGDJPR6v/aqxGm6cnAofc8yPyFwmcinZA/XrBL9IofWROnw9KVlz5HOvvnetWemAHoJFP63+6pEjYiM57SvbYy7NGEWE9Kv7Zf88uxWWfVe+6bxEmnTDIx2qE8xTqft0wr71kmTqehDNrkdf5NR25AskX9D6RxDasbH5zVK7+OKnBsFafMyjxTkEpIDPb4HBJum7S23IbfE0NldWnqTJIMqZgZyL9nw2NzQKWIp5K4qiLmdKBWVnxEU1IaO4GUPSNymNPmxViJPR2UR92lsyXFmhIvN5ruWIHiR41PeAEjH0MoRSFLUCrH+PxhW2FFePQxlbP+mX9Y9MyfbJFYWE3cbi2qNS7m7cPK0MbVy0Y4qtyNC7c5lgka62V5R/SixZ+mkEirvpLbp2x9zvTvFzFXKyeHsiE3oXa3XKM0LAKU6NU8ruf0RIhpWh3ZqAzPBYw8bCPGTjirytA+T1dy8ysrYmvQHC0/De1yK5L+oEqyRCEqrnRZjZWuurYY7c9fUbOX37scRf/e+RS2vrqHTSqqprGWFY1iGZNfrA7ZkLej/B42spRSdDWszXEqzk5EtERmUfgf8KPjvm0fdBJnPpUaT2j+/ZLO+RtC+1pm3NMx82D4RdxMeLdoaUVX+17tV37Vc5J2xO4LTPFe9qp5NgUcbnXPVq/TsR0/ptYkq6CFZJhLnM5LmsT+mjuD6CxVg1z/r2qNoaxQl31yOS1/qsb073kqZxPRb/ZXzLCQObv0am1dlI70tC13yRxBW8NnFZX2ba33x5qUsnNIosfFIQrIXHOFpoI3AjyWd2/H+iKTk2lCu9vhowrq4YZay3FwJOdMxAFukWRclIiRmhqfO41p30w8t0lKwbvZI0KL5SJIp8a4e+ersKV2JQZICl0NywzHAX/wWu+xx9sv7wrkcnwaKdUtG5spLiqp330/st2Zacl5OhkZGrnYzCoHI+rmwwUwV6ATnjS9xI2j333HM8eK3Hv/9tb3ub2rsAfxuPd3alch7ojlh3xkbAOFl0A7eXuqTIZRSF630D3n+SQaoJjffT+62qzKX3zO6hXjPeKVnzqnGof1qHx9J3x53LRSVY6+lbucbVvlw9zpo8ScbWgx4/6wLXI0O9wqMmWHr0Lqe56HPMQ48hhSRfJyHqejTB4xTnFPrzCt35SRQyuS0ImdaBTjY7CVYqX/6xsukG0jt1QyrTGTCPupn6Wwkwlp0KGYMRU/onfNxpPfj68zQP+wgWdWls+6nf96BktYd83Wj97lVi7SirtdZzgoVec2I2FYJF/doD4xCQsu/qsnRKOTalaTwa1+X4L+Jbrq6nlGnVWebn+IYNG67h4n7mSG3Vzvb3ueee27e/a8HFvA6CtZhoR1sZAQjJDbrgZfNH5sSDEVOiHLXffjCpN1YaV05+svFBuWkz72QTntFbIl8N2tBS9D3EDCXnxCYrFurWnZ2cyISIgH6ryggf47KQ69NJ16bPGz59y3AHaT0uKVelScFKSddKUO15P4hmha2x9jgMm/Wt6PcoBKv1pQCVM3LU08DBCxsXfTfFdjB5RidYMhbmiFsdPJaQsXgh/qW8oP2HhCJY15Pf86g2GT8pbZ1g6f01x30P11Lkcj24ziX1fNbEQ8bfDWeej54SGFLGcoqnIS+CrF/M1jsmvg7duEtM+bsVGeQo63OZCR91Su9qHeb5oz3Nm9J6XJJdS2LfuiFNdRthoR0RFf3PnBEF4ua49rnwuoVDlkn9q+fQCBYnez7uVNtcQPpXif09a/1NSmFdbyPQC8j/jfDX8bs5ibT9TdyccCSi/ua2KH+WMgk7HxEqH6f/YTSyQehzNG+CNVel/djyR4h/QtfsV8OEMfg6UbLaamJAP/oIFrKa45oMleRC61dru+X2k6gvuWgezfmYuTFzfeNZQ0PKak42lILUrbXStf5LUY+XfVea1pDvR5fReC7Db8J/1hOrsK6nzBbxr+ss83M83Qh9hXEYic8ZRNLY9pV2ocxfqngQrKVC/ghvFyJwY4LgvAYUZsg4pcqGoCGjpF/TR/omk6Lu9J+Nprw9wUPSh51gybCXzgwTCqtUAhbnOFqk52z8zcmA6DRtpwoTriNoEYFzuFvWI5TSSbnqLlp9k5KWISqd2rN+pESRnxnwaSle6xv9dUIm2WzIU/kykCLW739J+ZdOBs3IUZlYxF1RZ4OZ8lQuGxnwtjqYb6VfkmSeQfhTeN2RtpyIy+n40rhJkVsfqbOFa1lPy/ipzEO8P9I1JrV1ildCG1qD3r4Zc8aQ88kb5Y+eVZ1joXk1x19h+dyU86J58/QkaYHIjoj3jjIxxbVOrN73vOc9CnWi2rNnuDaCxYlq1wmW6jCSluoUGdU476tfWPb89F+gz+G9JxEtyYskPxv/KfwFXOs/XUWoaqcfKM1tEb8IgYf4KRDXBbW8X+sEy9Y8CZqXkni7zFgh/RN5/hH8llTQ1jN9H4lgUUbzaqQvlRcOGlu9d0tyofWrddxypgN+8zd/U3NtjjHbnHFD0trnLtYMKat2/CTSZbQH6v55XitUu+Wa7CJYT1Jh1tg/tiohTRj0YFXIteossvuiXyTl8jo1Ye86qc5esusgWEsG/ZHdMHe9Mhj6H7TzayRIk4K/e9jdCMby5citRl4KvnTXcyHl3XKdG5p6/okCZ6F0fw//KX4NWT+p4MTGiIsqRHmZkuIuXUbtHPwWvDlIl8iB3Bp8n0Kj3nte//rX99yx064ZQe6ipVBbSrpWdDI2D7TwoU+ujL3fki0NOZc9blu62tiTOndK1lnOv44NFporc4xNbeqbgaUStzrolxTspfi/wH8JL4P0YYUN5xgasUn5MhgyUHLDCJaMn+amdFamsVZc5nYieSwpbu1zwqI8fydHoU4Z1hB6P5Xd5YxgUUcmFjwK1pzIlfh2Eaz1EqStnQorp7qtXh6lanzCtIdgkWTrlvK+Hk5GpsRVRkmPuz2fSzPMtykyqqP8HvyLkD+OffmrHeW0LqyfyqdPFxNs7iJykkkuE2bKaI5sPjxzGiF9F8ERnuUpZWdb9EN9Ojq9R2ZdIE1rzubbEvgAa8n5fGv97vG8KjSCxaPUTLDI9znJuqcqM+hS83cc4/K2Jau1Mg4J0fosy6s/dV/2kib3eXR6135QGR+LCRcfrTqL7N4oeH6ZlEsYV4mT1pLGVuqd3oJLdBUEa4mAP9KbZaOIFN3IxjivgUV5etDInktSHWy0liG4FomLOgqKxPhjkx4RyNHHSZAC+kn8ZZxC/RChKYaCuOiRhil47iylgC/A34Q3d+WVV8p47advpxEOIwJWBgysP5yQjEOwSuNs9eiDu0gjWNTpd55SkE1ZydPmrELcxrkgf4oQyTg0XTKKIsjrXIBHtWbsuc5KHKy8DvXjLPxmcH4m5X6MPv6Nl61CV9SlMZIiX5PkhilTGbkmwaraKS+1jjSf7vIaZB3YfBNafvq1f31z1PvpZVqhGVzKOjY63TSjxfidDMtAyDjUREdrzfHd0ahcZaxe1uJJKT9jr2v6aGuLfBFfEUN940tYmkvtKl4Sn1O5bu0rKzPog/1YG+BSXH3LOBDXHtVeHea0hvwERPNSEsRhZcfJvxM8HEeV03zb3NeVgKut69nZWe+XRFrr0khKwl43gxn7ss5inkriYLpn06ZNTX1Vlm/Eff40l+40x1ozozr13fWIyrTIkBFD8n5XAh1uGMEaZ3zX08Yx6C3pktK1sC/zlyQeBGtJYI9GEwI3EPadYKGMJlKiKCspbf21Sk0a1GxLSSh9BnJ0JyRBj+9kAP8S/wS8KTnC0nCYgqedTaTLSHwBb440Ecc9jEEES5u+x+CZUP+HKSnKSLm2FIXaLhWd+ifl1+c4yXCjLRm5TlllQhy3K8TVWMlwNNsw6bmPnfR5rV9zMqO+y6hnJQ6ZMEMEUVB9eqy2a4S/mNqT6tySQgVKW52uhxHXPoJFP4eVkSE1ApXaUNwNuYdalyKlmluRoqEEC8Jr40fc5yMTLNJKfG2dFCRVTUhWa0zfMPV50qW7TLDA14gBfbrTM1Po6/bYd73rXcJAOt+Nb54rHk/b3KUyncQi5c83UH/VB3cXE7nOLwaEwknrR26h+qa6hV1NsDJWEnAHzjavvB/l/VJW3wkWaTbHiZTrz8b3eh1VaDqA+e4jWFdccYWTmKrIwEvrN2vV94yER9VHXrF0SV63xKWDfD25zG+yp1/NxW94QiNUPa5H6+xOfVwL6hr8ZDOkt2q70dKbEl1SFwRrSeE/4hu/EQS6TrDcqI0NEkrvExTSOyDPbxTuPMGSrH60MN2Ff5nLR6M8nNhkxYISlDGW+y48tu2oz9vVwQ8ZXhnhYUbdSlDe7uCot+sES20rz90g0mSGmn67oRgkO8NYJX8X8mbIvQFClXNyUCT3RHdxta5IMeOJEswECwVvdZAm4zPSYzX68o1U5xavm7SSAA3DVW2Whk/VqExNPpTurqxfaSJTPs9OqGXcpdw1t5p4zfNA54SX/vs6krwbLTO+SiDf+kbdhqHSkjuT8O7Ge4bKlhE9VRHWjs03ePeMEdxtbZF+DKdYJpvKqZifnOkl75JgSU51T9tprVk7rDutB51CXDdCI5pPx0zzMm/dMKQtYef7RqKdZI75sjUOpiVuituJpQonZ3MM/ra/KDeQYKVvEntZIx+U0U3bWI61ae0w/z7nKq+1lffmCBWq7467xPvIEPP4FR4Jv5tQ+rbLSX91ESzptaxbuyrwdN471esVkq/thrA33eeyh0IYBOtQmIUjtw+6G3l446caVpPepYiGopW+rff3CP4nFIwei5SuT0mUmR5Hqd1K/BTKS8nKlUrAFDx5z1I6xu3rJnHwQ4ZXRngYEbASlDcjiFJ0glUraeWPRLCSotPLxG4o6h+0tDarj23Ib6zSRFDMOFTp5eVOLtZ5Av13Y5MVHWlWB/XLwBwFrsJmoEP2y0mgnDthbidIhMNw7TvBGqFMTbA07zbPYKq5v49+2VpgDJpbkZqhY+FdtX2SpWwmWMTdaGV8qdMwI68mWGdQ/BbyW0Y240++zTcErYdgUdbWLenH0F83tiV5snaLuVN3Nc5SRmnTcGrLx3cBcc3vdSNUXBJm9c2J7whFxxLJBIs5l544CVybc+zzhYyPRw2JNNYExuYY/J1g7ZFgw/kpVT7Boo2xyEdZJ/Np88d68jlX9rgkRGs3r1viI+lONVQ5rUGVbbn6d/NaMjktvXe6nYQNOXEuonmosa9EFv8yCNbiYx4tHkRAJ1gzd91117kHkyy2hs8uRVSJdl6+g5zHczT/vEpCSssITZXec4li0iaW89/F6iNY5D0D/5VkgCXrTkrZCFahiD2vFZbKVUqwVhQjE6xUeUlGZMyzIW81Tto2/MYqT+Vk2Aa5XWRmgoUBN4LF3XruP3f4XodOYuRUZpj7VwlgJP63CzIfMqrHvv/975fCb2HkojoNahEsEZBM/LLwwUhNsETmSkOuHzo1gkVfTLlDnnYeLN6OvfSlL/V1Izzdebycly6CJdxu9YJlSH8y/vTJCBZ/Dt5DsMDQ17oMnBvbTJ6KuZKBcie5cuyePmmodWHt0PeLVRmPPq8doVLhdEKS07wY8R2h3Lgi5b6RDpJr6iHWuuNc4ta3xpgXW/+M1wgW5fbOVdv7iZzPUyZYSMyX0AhXn2OfczWovua9qYQhTrj7WpXofPszkGAVYx/SnZy9i9jafDUXGagTKtlFuwyCtWhQR0MNBL6lNDaYG18XWU2kqYhcYFjIsfU/ICND/XOV7KhKYlsqJ4L1ECTKSdBMivsp0+eq+nWZCRZjG6rQMHKmXFG+In8tRdEiWHYy0mhbSflOnLgUZGnIlV87jXVjlSiD5uSoysqXO4iZ4UgpZmy4W89jhoR4HWdIBjyEzUAHvjvwK/gZgE8WgmZUIeMysGpnEFlqEayBawoDKEJhBCq1WRvy/KfYyVjuGeHbbyJ7Onnq+SV+MHCjlecFuS6CJdyaBIt6RPBOSqTTsOdXrjP2aRxG8CBaesndja0bXz3uNHknx6mM5LJMSptGoDFqfWsdXEIwq0fyuh7itIYcM83RQpA/dSHvG/A6TQn0s2u92nwxbyJV7hR34uVpNsfUY/uE1xe6xuv6pSZYphu8slHDV77yldoDD9Cu1r07YT9o37ich+q746406c5BekcyLac1WJ6ElTKj6uOyjNb92jKBuMZWr/1KZPEvg2AtPubRYkKAb8fMEkUHHPBTIsdGd4/NO0cXGBbKsOH/BLlnJwPkRUba0CjC7anAWYR+CuF1KHyYPmjj7xRWTkpZhEWEaahCw8iZEqUuI1iEtaKo7wCl9LJxJl47kZGT0t+jqM5Bsiq7Da/+lm5YGxr7tRTQz1qYcefajCdpeczpBEckw0g0L1N3Gayy7VbcCBZYzZdgyWB2rinWoIz2cVorCTc9HioNud79sHWK7OnEt+JHdfsoUxoYN1p5XjDojplhWVT8SOKbi+scpX8yNDN79uxZR1zG/S7mouddGIiTG2iteyNYkN5yXNZuMXeq8hSuF4JgaV37+C4mrvUzihPBEuGX0/zbWrCr6X5kgkW10kH6QkNzvXJC5ETKxyNxxT1d13I+x1ozM5zoDiRYtKf9ao41M5KucvkyZP605zSHNucpT/2rdUvK6g+oQ2RKP6bsj+rn259af5WNabzKH8ftQnhtVSAIVgVIXB7hCKRf5hXJMuNbwKG7ri5FVIgNjqIgPo3EwzBAMlLuhhIHCfIHw9rEMlZ6mbJWmiTNORRtH8GiXSllETM5N5xzV41PSIcbQZE2/eFzrQSVnxUv8WFjUH9P5u9R3Ki7kie56TQH5UmUhE5gHDJsnY78r5C5AnJwqYTotxEsiHPuPzJS9GrfyAkvUzcNlsoPcU6wdIKhXyzvxJV+qN/HQDbK0wAZzM62qc9IB2vllM2bN8sQyVmbc1H7Oxdfp8JKmI3q6hOsvnnh24Y2Hvp+kldK/0UmNtK3GzytDEnXGtWj1HWpXGudmvFKp6PC4N7y5I2Xhn2ubMzUI2Oqn3IoSZiamYbTGG2NEOoE65oRK9X6cYKl+V+Ivqkrws/wB6/TlAChb64ZXkbvwU2yOJHyeg5872nN3Muc+rUVKD72Kw7u5ZqdL6HxamuCJew7940XKkLrK69Z+Hqdb3+MqBX1WjSttfnUqXW/tqpv3LFVxRfmMk6wFgbXqHV0BG5BNJ9gpR/uk5LrPG0YtWqUpClHDJAIm7th5MTk0suUO7l4BL40tJaPIv1PRJ6nnxywhN6Psu9DFRp1uXKV8dDJkCtvr7VFsKS0upz6Kww1VrkupT6XO3eCdRrKX8rOnQzawHKrVq2SgdRfyTwmFZKRfiAR55RkgQiPyMndAwxMKd+K+xyIdJxImzVGZRk9HpnhfSQzykmRy2CW81LKy7DZPHKCcAp/62Pz4GlJsFynOo0Yh2DpBXmfC1Xn8Yxv+q8+kVEjOhLCnacPyjYJFutb61P5Mjaa79q4698BtHbkdBKxnnCHXaWPtM51wiYDNYMxFWYi8wtxgqW9sCrt8fOJX4sfxWn96CcORP40/74WRik7sgz7TmvATnyIG8HiuokD61jEVb6cr5PoYz0HPsdaM3vxTYeO8nkqCdZ8TnfK+tV30330V7b+YQ3dUsrXcet7+scK5c2HDKmccCp1i9K01o4m0Jwqf2THGLoI1iCdMHL90xQMgjVNNKOu+SCQH72o8O7du/9/9t4E7rKivPN/m9777YXeaBoUGmhlF9ncF4xGR5Oo0YgT/cc4MaJjRhP4g4iyRBAUUcjAZAxmccwyUeISjdEo7mtAkL1ZhWbtpumd7qb3nu+v3noO55571nvPve+5t+v5fOpWnVqfeqpOPb/zVJ1zbYHLXIzKNmLnHVBEbpHx5aTcbNErqmqlz5BcNEc443U1i9Z/pFXAIuuAnU8rVAZsG9ji6vpO+eRCoQUobsGSEkzmibMifqWI2hR5PFMs/JgPSwkYTYMPKbZMOuOMM5R+D/me4zOpfBqIUb6FuLhcfJHSnslRYEKyyAOuDmBxHsmBBv83MnpbKbN9FJwDWFgsBK4kO5G1qfBduAUohd/BPxqXCnqITyOBYbMCKL1tXJhLspZqTCOFDb/HuszTpt0tP0mjo6MGsCTbWbi2eYrF0M0t6pLM2gCWr1Of6XCy4p5x4JL4VGDh83fk0Yb6N7pixYpn4QtILCtZkebPNP8dL6pp2botWUWpbJq7c5nPE3DzCa9nXNzDT0bp6MOkHsC0/RckANfuId0beWuatRMHWJ0CGmNX7bk1Bd8dacDPu2+snPORgXuI456w+dopP1q/2gCWxTGetv61tJ9zoXGar3GK5ZHsNb8aRQFgNWo49kpmHqHXsm444maepwA3T95iNJa54Dd23sHV6bNL0ZUFWI/7MnFFW9Bq2/eRDLxklsPQYguMWwxR9smFQunxBUqLpQMRGZWKXylcWxiL+nu/r+dQ+SgLLfKTWLBMOfjkVO9WYp/jU16N//2UXFaPnjw7oti5IQOBeYrCxssBJaxDUpYiLcypBAh3AIs+z0H+DmRgzXJxvsBX8L/BvPw6vur9Ia4spQGsXSnKW+0Zr7oHXsT1HRlW0pGzzjpL8+QpeF6IPxeXds9IuYk0f7IA1mbacsAOOdgcjPfdVVDDj8ZM8+o4X1cpgOXn4XTuZzeelLXxrYGllio0P6Z4QK5xWNOS2n6h/hggTgUwACybp0vJu7K9iijGASzkH3+Q0pjZ2hBlrBAQSDaA5fhknJNrS151bt2gjK0j4sfmU165ZJrKqGySLK5SnfCjuTn5iiuucHxxLaA1o2Lfkrz05DoArJ6INVRaVgIsns6C5W8SnXmQohBpseuKUGBaIKTc58Uq0k1ZBDgsuy2IlRZ0+hTfhrE6rM42H6uBPb06xc4im1wEtcjGF94igPUk+aWM3AIEP0X9XU7e3eSzs2quHHFF5bSdeQP5TkLWz8E/EScAkiRT/EUKK1kuuvbnhrQQL/aRpriiPBYAILn28G0uufFnjmW2zxkoByjIo2+fSXbqWzTu9G83QPhtRF+NuxZ3Pa4spQGsNNneSIUvVKX+fnglwZ/pOodWk1cAS300OUfZsXI5BU0ezZ9MgEWas2CRzylkA5xRRfUE3JjRxslUtxYrsLPAlahaspqONc7dH5R3Y1WiXNUsbs3hfJVkKeeucyrRfeaAC/fwLOWDN8VFZH+d5SMyt5WRtwGpOi1YEcDiYcGNL3xk3jcR0z7A/aN5q4/QmvW1G4BldUTNcM/ZmlYJYHFfuvHfuHGjmw9+W1sgq3TfIiZ6HIgPZo+bCtUHCaRK4BFiZ1566aVSarpxtLDp7EibslB8B6RFcm6snMBDmnKLZYmCHVmwAIm/thpQzIWLBwuFLa5uwWAx7ApgCRiw0GvBLwWUxCPuYco4CxYL33S+QC5lYZYn606bT55vEflJ3HU4AZh/xSXJAKfSu6GNFD7QV5C5mKKs3NzBd+OOPLSdoGKZCpP+ukWbPDrg7Z6sUSwW55rUXykReK+7qPaj+WZjoZKpcxA+f0jbl1x22WWjKI1jySfAW9SeQIoAlvoazTvCjmbPnr0dC57C6pMA1o90kSD10wEr2nf3H9eZskqUrXIphS96CW4Z/XWD4mJyfuBJ81D8Ox7xNQ9qJ/jRX1zpA7KSwXxc0XzVfNC6pbcDZ8kHlLQALPWRe0v1LMKtVJ4MsoesuE7uFNBYE7oPNC90LzsgCH/JtcXypvm2Ttrc7ZQfrYEq20LI2eIK18h4Qfri7kudlyR+JevVqNYrZF2lb/EqexYOFqyeiTZUXEYC3CyyYI1wsPhg+dwkbkGYMWNGXQu8FhlTGmoiVbkpIUnw8qiPq3TjlgFV8bZ4kt/lr50CAaAl20suUEUWLCkgLfy2MNpCGW82GZZydhYsFiud8RIVloP3O8j3PZy+GH8WfU8rYwBrtSrtgtSvA1Q+T1FgaXIAy+YS2d34c1g3U2HCtxSc/rxa80+y203fkuNAdEeUZsFy1oF4bdwL/8b1NADRa/HfgXuUt/x+EM+TEhbAWoBTH12/43nsf+zol7Ng4dtDQzybgTTFOVnh13X/Re3QP7ufTiZS86YUwbMBfQFEPXw5BVuqcIVMtOP6DJ+SQRmAJcDo7lnmowNYgIYWgOWbt3mXacEiXxrA0phVAh++PefRH7W7UBfw5SxY+FXmtN3Lto7ICtUJP8n1SywJ9DmAhW8PmC6+6AdZu/FnnRTAGmG9cn2jnip9K2qmlvQAsGoRY6ikUwnw9HG3yrIYHO7r0OK2zR+g9lFdeVI6DrT5WgQE2pRbWgvku9nHO6Welicn7hrS/iMnPUqiHT3Ja4F1izX+lihxLKAFSIut0ShlknksTQuXFnkd6nYLEL4tlFGelIDOYTmAhe8WVBYyU2wp2ceiPO+v52nyCADJ5zIymoK5NyO9bPRGMrqxoN1MC9YHP/hBpe1CDm7c8aUsd/ntmry21qmMl9tG37e8/GXTkgBLALZNtoC8+4i/Dncl7l24z/m3/AhmksDr/jjx3QaKfB/0wUnNBVkxDOwSjEhxThHj6/7bkgGUowKdBNiuNICl+/3GCnXY/FU/BbA0D2on6jX5SQZlAFZ8bXEWIu6DNIBloGRlDtMOYCGX+H3eqcXINcOYS96zGUvx5vjDz7xvXKHYD2DM5ugMH90RP/RJ89+sVbEWojiTTzwtMwxfDmBRr1vfWKccwMIPACtTaiFhr5QA/xso5asn6KMkACk4PFvoFNUtaUFxN6CvSODBFuzcurmRb/IZTPnk5o8nsqi9FSdLRFkSiHILBts6yYUiCbC04GUCLNKcAkKWjm8WojL9dRYsyui7VgIAojLlRujnlvPOO88B5bFibb+2uC9rS6kWoX4tVhF4zFQU9FeAdR2+A1j4UpZrfbyKZ5Hmnd4im41fpxKXgjErgNrOHD/6dTbp4vtBLG6fUuYCepD0Q3Da2pTCTyMpyiU+YVVKBt1/+ymeOpysUvJ0HeUP5bt6aKc0wCKvU/SM3yIVxtqdBmK65o+zV1Lc+uyIZDCP9orWIaULjEV/to1VJY23pcrD2N4iP404w6V7XJTcIrT4sdQKv7TnAC2g70D64tZAHmiTa0tmjfBkfbH7tyOARQMCUG0AC1kZmKwEsPj2oMZJc9WtlwSNv8w1QfnHg4IFazykHtpMSmAZN4sDWCRowcpSFMlyZa4FRKTQdENOwCsNsAAOsmKcyUL1RyrfY9JCKsW6+/TTT28BNvAQASz/lXGZ6jMBFvndwojvABb8t9SX0Q9ZT+Zw9kfKxYGB2BNsRpHS0WbBuqt0ifSMAj3OyoeiKFpMnTVK1TDumlNFylJZNe80Blq43SKOXwdJ/hozo0yA5f8e6GBA9nFZbw9aJfIZ4+V4DnQSzrpvNB+cdZI8bQDLx7m5Qj7JysaLYG+Irc9bytYMfw5gMY4CWE9yX+4uW7ZKPl/vasrsj1uAUziPbL5oHGb5jGnz0h0B4CEk8wGD8s6CRR1JgFUJfMSZpc5HdM19/Aw8B0L4dl0af/FiURiLnuU1AFPpj5mjijIAFukGuir18bDDDtM6IJnrPu10+1NFe04BYPVcxKGBEhLQwhMHWGWUYYlqXZYIYAEe9MQkkFUGcLjCbHt9GqV3h7vo7Y8WGS3qaVtTSnOLEV9nN+tSHsByCxAKaT+xzJNoYX9FwMl4AABAAElEQVR5ynUKj0XrRBZkt3CJF5WvgT5Gva9GgbkFv4v6ItDjP8yZV5VAguQpEmgsAxqkMAUwZuPq6jtVuf9viwMsjaEDDUpMEnJaVWGLfLmVZ7ydxcKuY74UpQNYjHMbwKKcLFgzaVfAT/2v8/6juhaSVff5JbY+o0LwZ7ISwIrmQJSh3sBKqtNapLXisbyqmdMRwIJHAaw9Gef2XkLe1+FkWU0lHoJqB1hsyTr+4e2ZOFmwdsX+fDyVj3ik/a8lfBt41BpUCQz5+lRmH+ZXHDwqya1p+JXq9HNnE31y6xT8Oesc61xp65wa7wcFgNUPKYc2iiQggHW4vwG1iD5eVKBCum46KQ592duUXCHgqFB/XVkFmLRgtCkQFpLIgkW66wt+JsACIDkLFnmcVQIwoi2qXDr33HNlwZLV5/ksWAIkklcZUJJbrxIZ160onmsLMxZnMNCjL8IXWTHuprojfZVlQYMpzNRxKGYvM4fkb3NPmTSGmeOnDGWJ8dLWrpHuozTSfDhUCQsWLEizytyjNMb9hXgae8mhJ8S4/Qfu+oqV2/26P+VsDlSsonR2rT3HKzfyyAVYyF5ysi/Ty8qjD7a2gSj6ezvz/1uqM4sAvg5gUadtmymrwpXAR7x+D9J1H7wIvrQWrEnjL14mHvb3mNbPyIIFf5rLVcn6YIDKyrtr+q71rSppndR9KnL88SaneG0UBYDVqOHYa5mRYtBishS3GLcCVxdJkTlQwp6/nYOxBbuuNuqoxxaHNgXColgJYMGM1bEf4Z0slPZ0nMmnX3h/QoZXs4hKyW73h8Uzy4xDgvVrfYm2byXPMX5LVYq5DGiX5WYerm4LluabzT2C9QEsFPeDqlDEOJt8xiKe/pUFayJudcrfGOlfCX5Jmr7I/9/wZemK6iQ87oQCjluwsvpYF5+aJ89WZViVcgEWWZyljy/T6wUDWXkEZDsiHoIMZMStPAIgBk46qpdC38S9jrE9EP/RDiqJvlZP2U75sT6ofJzs2tLjaUXhOMCSpVoPcbaGFpXtW3oAWH0TdWgoRwJShqLn4vTntjLT10URwMKy45Rch09hdfGTVY8tDm0KBH4dwMLX9qYDi8hI/coiq0MAqwqY/Cr5X4Q7GlfpaZf8/SDbuipUFMjnNhiacffdd8tyU1a5yLqjxVpPxm2WROI6JT31xy1Y07k20NBpna4c/ZTF5C24P82pyBT/Q2l5fB2fI+3tuMO87NKyjkscD0Ymq0UwUOe4pPUnWnsWLlwYhdMyAsDWKR4AqBcjugJYVGMPQUmApXu/GxLA0vx/Le6xDioSOJ/pH1QE0iuDodh6a4DKscE800O1LIWV66RYBLCoX+vcKj+PVWVjKACsxgzF3ssIT95SbFr8n49biMtd2EgvTdx0AiJuj54b0QEsrquAjtJtdZnRAFaaAnEL0Gc/+1ktvg5g4atfqeSf5LRgH4Az5ZSaNxH5da51IPdduFq2BxP1d3upT0mICvvEAV0H2gHVDrRTpgwok/VCh+g1Bw2kEuyakgBLY5g5flVb4/75Eu7KnHK5AMuX+xsrz31yh4Ub4tv9qq2gOselrXusF/f5yLVp1r54AeaWA1jIax7xXQEsxk9b3gLLSYDVCfiI2OQvpn7ChWR2EK4TgKW5M5Oznw4MEe6EHyvTArCoy10DVC2dqNIUASxKOIBVumQfMwaA1Udhh6ZyJaBtijcoBwtWr7YIZTkQ2YI9dtWMXwNYbQqERd89xbIVoUWu0ILln+QEWvXkWrqvLPKyEF2LUztOeeA3hliI7byRjWMmbx/5yEcEllYxl34TX+tcoXIhr8qIDkKGaUB3LLXiL3X1FGCVYEdWCJEeYlKJsdd8ORJez+ANvxtTM41TJGcB44C6tnFJ6w5z4Gc+vvC+AcS7ewSgNZcyAn8GZNOqLhO3E/nr3jMSAOkEfFj5Ef8XU5/xEU9ECeUDmjsCjwaOOuHHylgd1rq75kOhbn2zyJL+QACsOFou2a+QLUigfgmwsPyAxe3Nvua76mqBOgVcpqNApGR1tkYm/Z4u0mqjAzKA1cYbfXALEN9Fmsw3gBzAYtvE8mc1JQvU/rgy55WiOgAxH0dhvJYI27KI0sY7AF8GsIoOuBurvyLwVl3Qr0ctMsdfFUtrA7qxtKpBKWuznqqsAGIcNCiulySAp62Y5XmNcI/ovqvt3strq0oab7PFZVXnuKSxsYzIh5DVB9MS43H6twn+5kpytS1CA7LxbFXCus/jOnkydRs4qVJPS16sWBesW7fuCdaRr7YklLtwW4RkNXDUCT9Wxuqwlu3a0i2+jK91cqnPKAvWPWUK9TtPsGD1W+KhvVQJoAC/aQlscT1g4Rr8Lb4OfcF9rsK0VQl01MBDmSoMMLUpEPh2AAtwpadbB7DwrV9ZdcsiIapkieKTFD9BPicBQt89Vrw5vwAAyeYCeHtnSa6+RT4Hqvfdd99lRWWwSJgFq1YrKoqtzYLFmBaNXxG7VdJPVGba/G6VQk3Jy7gL7Jt1qO0BpE4+aWs37mDWoC8W1evf0tPYzsNpa7lb3tTPOMASAOkEfFDsaZIVi/58mn7ZFvvTicUhrZXzuDfcGUJbi4qLteRwfWBdiZ9DVIZuAdYc38oz8KN718c1wgsAqxHDEJjgI3wPcPO+F0m8H19nEeoiU2QCJloE9ceslUBHXYwU1GMAKw382SKrBakswJIFS6Rtv0oEyLqR8TBrUaWyvc6Mkriw4KvxcRau8Rc3+62SeFpbmEPNqywSZVAbyGc+O4AF0NJLCiJZsGxeuohe/tD+J6n/DuR2ey/b6XHdtr3V9gDS43aLqrcP2mpt6XZd2ckcadki5LqT7bMinqukC5Qdxh+fu3OszKVOrHTx9Stq2/d1D+BP5z4rEXwIzM65+OKLF+HrfJms1Y2jALAaNyR7L0PcaFejQP9XzRIwRSZgokVwG21oy6ZpZPfi8iRjtsjyFGkWLC1KbtsnmTd23THAitUx0EHGWS9LHMhX319dpiPxQ81sR9YGsBg/jdUEfeiWsHsTFD++7VWGvY7zMFe+hiyOQSnV+eDSMT8dFrR71iyzHVZTezE9wMgyLtc1wKKO2i1Y1NkxMWfupvCBuAN8JZ0A3FSARX3OQtfhvNSD6L4AvxeJL9bGX8hvGtmi3jS+Aj9BAnVJIAmw0ixEdbXVTT37qzCWkzbLEQuQe4plMTGAtaXEoiRwIep20R+rZUB/ARaP8X+XZv0o04uHlAlQUqfcHDjQh26vuuoqKRWtuzYv1VygYgk4C0qdlsXiJkvlEMCaj6sDYOk+b7FgcW3ghGD/iXXmHrWKb9vMlQEWW/ruYZCHCs39OOm6Uwud7lM9sPwh/q/5UPLD8YqbEg4AqykjEfjoiQRYkN3WG/4oN2MdZvye8EmlDmDFDnJH7bC42SKr/wKToimjnG/1FcQX7KjOEMiUwItJeQ1yrs3aQ11OwXBWe+qmTZv0tpmok62WsZJ756/eZNP/ztVmWaxJjDr7ozNAui+7fXjTfe5AiP/ulPSz3fsE+0/8/YwDWKydJ6t1Xq7R1lwliq9fiYLqa0f9g597fV1vwP+PRL2NuQwAqzFDERjphQS4uQ2MaItQT5ndLoK9YFNPiBdR8d1YTmxrL2oHpeKe8gCJemJTP6xPUZ5kgKfGG33cwmRauM6WABavR3Dfyc5RPYUxcwBLB4UZywCwqotQJUxuZpntrJb6S4mfI1Ut93C3Vk/NE3cQvMvvTomdWuicc85Rn2QBdgCLNxLtZYPS9WcBLOL18NcRwIKPCGizLn6+NDN9zhgAVp8FHprrrwS4iR0Y8cBEFqxGAiyA1bdQ7EfAb5vlhAXEASyUc7RFWCRFTObLyfNxgNZHivKG9J5LwG0RMgenBYDVsaxfS8m/4B4p+4mOjhuqUpD7dQX5nfWZ8e0WYAls2Daa86nf3ftVeOpB3rup81DctjIviyTbZ/1yIAr5OPBo6Vx3bMHyfHyJuv6Cl3J+aXU2zY8fqGsab4GfIIGuJcDNbdYeO+Quk/5AUdyCRbiUBcsDtQ8PVEeHlFnm4DbGTdsrUwk7Swx+ZUvAkIqnVLcAVt8no1yjCJAggOWIMe0WYEUWLCo0oNWRhcezVJent09fgqt8/koMYLndvm2bM+JanxQt6hhgqTBz4i3ym0zBgtXk0Qm8dS0BvhK82VdiAKvbRbBrnjqowBZZLUilAFYHbYQiPZIA4MppFxTwVBSyA1gA4HAGq0fy7nO10Zbl1KlTl3fZtuaJgRDz7d7vsuquiv/Il57eSS2zZ8+2PlifrBpdN8FCZ/zU7geAVbtIQ4VNkgBbb1q0tO0mYNLYM1h5MmObzy1CKOrSW4R59YW0/koAYOUAFuOnLRIHsBjTALD6Oww9aQ3rzC1W8dlnn92tVVJAxG2jUa+9nGLgxJoZD98sh27uVmXgtNNO0wdUtQanAawm9K9ql0rnDwCrtKhCxkGUgN8q0zahWbAaeQYrT7ZsLTmARV8CwMoTVEPTGDd3Bgv2puGckuJvjwLAauh4VWGLs46PVslfkFdA3AEsfz5JB+fHHYCwFbcKPn4P3t5dwH9qMmUFrtSPJMDSejbu/UtluqbIcAarJkGGahotgS0sWHrNew43+8BtEfKqNB+f36G/bzGA1famYaOlv5czB0B2FizmnrYINQ93n3766Vv5q5W9XDLD0X3G9VWMqx1F6KZTEQihPgdGsHo2YguNnYAvd9MxykZ9i9WjPgaAFRNICAYJDKIEZMHSXyroK9oDZ8Fii8kWIS1I4QwWQhgkAiBvE0CGzIK1yT/VD1I3Aq8ZEgB8fC8jqWq0gLhtw5m1x+79qnU1Lf92PWAkmFIfGwEgE3zVdhm2CGsTZaiowRLQ0+UBnr+BA1i8gZPcIqzjabnBwzVcrHHeyj7TYGewwvbgcA1xXb0RwHLAyp+3VL1DA7Csb+qUJ/V1WPpnfWrxA8BqEUe4GFIJyIJ1oPrGU9TAASw+qucAVmyL0D49MaTDNVzdmjFjRvIMVgBYwzXEdfVGYMOsPENnwbJtz5iwhv4MVgBYsdEOwaGVgADJoeodT4YD9x2stWvXtliwAIkBYA3QVH3/+99vT+nRFuEAsR9Y7Z8EokPuNDlsACuyzsXEqftB8UNLAWAN7dCGjsUkoNenF/rrlbH4gQjyFo++Xr0Lp0U3nMEaiFF7mkl/3kpWrACwnhZLCLVLQEDcgJXz+VyDe7hqzzpwMfG+GfP6/8ahPu4QAJYNdfCHWQKrfOfWAFbMmjBo/d0RtggHbcha+N3qD/nqEHPYImwRTbjwEmizYDFnBnW9Sg6q+pb8UGkAWEkphesggQGUgFmtVgwg78aynmSlnPVQFLYITSqD4wcL1uCM1XhxGll5AFY6nzQSe4N4vHiqq109VAhQxSkArLg0QjhIYBAlwGJl564MaA1iN7T47usZDwBr8EZwKxbIsEU4eOPWN45Zp9osWPofv74x0NuGtBUYAFZvZRxqDxLovwRQbAawlve/9dpalAUrAKzaxNn3ioIFq+8iH6wGWafaAFbsf/wGqzPt3MqCZd/4slQBrqHeLg9nsGyogz+0EuDJ0N7Cu2GAO6k+zBH/9CdYsAZvIAPAGrwx6zfH0RYhDbtD7v5//PrNRy/aawFYgEl99HmUtSwccu+FtEOdQQL9ksDcuXO/wY18Jjf15/rVZg/aiQAWdQeA1QMB97jKCGAxF4f6qb3Hchza6pkXzoLlwYcA1g7i9D9+w0Ca89EW4VVXXaX+TaKvQw2wwn8RDsPUDX3IlcAHPvABLVyfzs3U/MToDBbf8nqq+ewGDhMSiAAW8QFgJYQTLkf0X6NapyZ89KMf1QH3YfsIp4BUtEXIt/0c2AJADjXACluE4c4OEhgMCciCNc+zunEwWA5cxiQg5SkFoy91B4AVE0wIRhJw9/WUKVP0h+Cy8AzLAXd1UHM+Algc3ncAa9gtWAFgaegDBQk0XwIBYDV/jPI4lAVrP2VAqejDt4GCBJIScABr165ds0kYRoAVbRHu3LnThfkMRbBgJWdBuA4SCBLouwQEsOar1aOOOioo6L6Lv+sGBbAWqxa2RdZ1XVuoYBglYADLLFi654eC/Fbg9GuuuWaiOgSwcgCL4w4BYA3FCIdOBAkMtgTs3NWWU089VX+bE2iwJCCAtb9YxoIVANZgjV2/uLWt/2G1YI0sW7bMgNUiL1T7l41+ybiv7YQtwr6KOzQWJNCxBMxqZYtwxxWFguMiAQEsnb8SrR/zwm+QQIsE7N4WwBqqQ+6xh4oFvsdL8HdgjR/kf9fwXcn2AsDKlk1ICRJokgQCwGrSaFTnJb4VEgBWdfntDSXiAGvYzmDd4wfwCO8vwX942K3xAWD50Q5ekEDDJRAAVsMHKI89zqCstXSe2jdYOPhBAiaBCy64QCBc370axi3Ch+jXFu6DI31/D8Zf7sND6wWANbRDGzo2ZBIIAGuAB5QtkjWe/U3D/tQ+wMM0rqwDPgSuZMUygDU0h9z//M//fDf9upv7wADWs7i+HzfUFADWUA9v6NwQSSAArAEeTJSnASwpmkBBAlkSiAOsYfoOlvp7J+5IwJZwx+H+Gm94KQCs4R3b0LMhkgAK2gBWeANtMMfVtgh12D1QkECWBAxgDdUhd3WWNWwZ3pF8ZPSZ+DNwd+GGmgLAGurhDZ0bFglgWncAi0XqwWHp097Uj9gW4eN7U79DXytLwADWsB1ylyAEsObyIdXXeanc7v2h9QLAGtqhDR0bUgkM9XdjhnTM1C2zYAWANcSDXEPXhhZg8ZDxM8kH/yK8h9gqfKgGeTW6igCwGj08gbkggUgC9v2YALAikQxUYCXc6lX18waK68BsvyUggDV0X3KXEAFUWrtuwM3HXYsbepo09D0MHQwSGA4J/B3dOH7GjBn/MRzd2bt6gXLRgWUd7A0UJJAnAQEsnVHSG4TDdshdf5FzGn+PcyF9Ox839BQA1tAPcejgMEjAP/29dRj6EvoQJBAkkCkB2yKUP3QA6/zzz7+Jfv1OZu+HLCFsEQ7ZgIbuBAkECQQJBAkMrAQMYA3jIfeBHZROGQ8Aq1PJhXJBAkECQQJBAkEC9UogDrCG5kOj9YpocGoLAGtwxipwGiQQJBAkECQw3BIQwNIhd7lNw93V4e9dAFjDP8ahh0ECQQJBAkECgyEB/RH4BNwzYx8XHgzOA5dtEggAq00kISJIIEggSCBIIEhgXCRgn2GRbpY1K9AASyAArAEevMB6kECQQJBAkMDwSGDixIlPWG/s3xvsOviDJ4EAsAZvzALHQQJBAkECQQJDKAEAllmw1LtgwRrwMQ4Aa8AHMLAfJBAkECQQJDAcEti+fXv8z9wDwBrwYQ0Aa8AHMLAfJBAkECQQJDAcEuCDwrutJ3z13P3Bu10Hf/AkEADW4I1Z4DhIIEggSCBIYMglwFuEwYI14GMcANaAD2BgP0ggSCBIIEhgqCRwp3qza9euYMEaqmENnQkSCBIIEggSCBJoiATYMrsDt6ch7AQ2ggQqSSBYsCqJK2QOEggSCBIIEuijBI5SW4CsGX1sMzQVJFCLBALAqkWMoZIggSCBIIEggR5KYGkP6w5VBwn0RAIBYPVErKHSIIEggSCBIIFuJHDllVdOjZV/diwcgkECAyGBALAGYpgCk0ECQQJBAnuXBJ588sl51mPeqFto4eAHCQyKBALAGpSRCnwGCQQJBAnsRRLYsWPHHOsufxsThS0u+EECTZdAAFhNH6HAX5BAkECQwN4pgX1j3Q4AKyaMEBwMCQSANRjjFLgMEuibBHhj6wzcn/WtwdBQkEC6BAxgrSE5AKx0GYXYBksgAKwGD05gLUhgnCTwadq94qKLLnrWOLUfmg0SkAQMYD1IOACsMCcGTgIBYA3ckAWGgwR6J4H494b4kvTv9K6l3tR84YUXnkwfDupN7aHWPktAAGsX7lFcAFh9Fn5ornsJBIDVvQxDDUECQyMB/mD2SN+Ztfj/ZZA6xkHoCbt3774enm8aJL4Dr+kS4M1BgaoN3gWAlS6mENtgCQSA1eDBCawFCfRbAoCU/X2b/4D/4quvvnpyv3notL2Pfexj9q2keVixwtrWqSAbUo65KAvWepxAVgBYDRmXwEZ5CYRFqLysQs4ggaGXAEptrjqJJeureDMef/zxkwal01ivTjBeJ02a9EwLB39gJRAHWLMHtheB8b1WAgFg7bVDHzoeJJAqAX3ccRtg5Wf4mwBcp6TmambkfsbWzp07F1s4+AMrAQNYm+nB6MD2IjC+10ogAKy9duhDx4ME2iXAuRdZsNaxxbYT/6cArJe352pmDLwKYG3y3B3QTC4DVxUkoG1BbRFuwQWAVUFwIWszJBAAVjPGIXARJNAICfgtwnViBrD1Q7yXDNA5rEXweyduOy4ALIQw4CQL1gbmoSxY08O5ugEfzb2Q/QCw9sJBD10OEsiRgLNgKd0DrNEVK1acmJO/SUmyYD2OW4ELAKtJI9MZL26LENAvgDUyOjo6vbNqQqnxkgCgeAqfTnnpeLU/3u0GgDXeIxDaDxJolgQigLVo0aJfwZq23E5pFouZ3AhgrcKtxMmaFWiwJWBnsLRFOLJ58+awTTh443kJ5zl/DNCyt5MHrwddcBwAVhfCC0WDBIZQAgJY+gbWyHve854deD/FvULXA0AGsMS/DusHGmwJOIDltwjVkxmD3Z29kvsXq9eM4dF7Y+8DwNobRz30OUggWwKRBctnuRb/ZTyBTssu0piU/VjIZcESwFI/Ag2oBLS1BOvaElxvW4R8OiRYsAZvPOeLZcYwAKzBG7vAcZBAkEDNEmgBWCi1b1O/wFWjv+p+2WWXSfnKGcAKFiyEMcAk65VoPc5tEbLVFACWE8lA/dhW/dKB4romZoMFqyZBhmqCBIZEAnOxArm3CNWf888//w68X+I+4kGMohtHnM9Z6JkKAKtxo9MRQwt8qdUTJ050h9yZlwFgdSTK8Sl0+eWXywI527dugHl8mBmnVgPAGifBh2aDBJomgSuvvHIqPE3HnB8BLM/j/8A/EhBz3cUXX9zUD3jq/JW2IvQWYTiDJWEMNkUAiz8ddwCL7oQzWAM0phs3bjTr1VbYDgBrgMYusBokECRQswTWrl3rzi3FLVhqgvMw1+M9Dzd/x44dlyuugeQAFnyt8vzru0mDcG6sgaJsBEsOYE2ZMmXNtGnTHMACPAcLViOGphwTHC8wgHU3JQLAKie2kCtIIEhgGCXAVowDWCkWLIGsZfT573HPb2jfDWCthj9ZsEYmT55c+aA7/dwHZ9saDe3qXsGWANbupUuXrp87d+4W9ThsEQ7WuLOO2KcZ7oLzALAGa/gCt0ECQQJ1SoCtGAdIePJMbhFaMw8QeOY111wz0SKa4qN89bS8BnC0k7ADWPSnk4Pul1HPBuo5qCl920v5EMBae+qpp+7ynwvRJ0PCFuFgTQbb5r0PtgPAGqyxC9wGCQQJ1CkBgIkDWLytlQqwSH+Q9ibdc889jftKOk/LsmDpgLssHQ5gEawEsGS9osz7VQf07jEv/I6TBKSc18Ta3hy2CGPSGIyg7r/13I8ax8rW5MHoYj6X4ZB7vnxCapDAXiMBFJhbBGfPnp0KsLBsLZcwdu7ceUgDhRIBLLY6HcCiP5UA1qRJk55JvybjnsS9uoF93JtYkgXx4ViHtU0YzmDFBNL0oF9PtJasx83kAWZS03mum78AsOqWaKgvSGBAJeAtWNvOOOOMp9K6AHAxC5H7eGBannGMiwDW9u3bHUA0wFiWJ7YUn+3zXol/8iWXXNLEfpbtzqDn03eTtLVkpIPuYYvQpFGDL4st7msf/ehH/7CG6tKq0AOOHnYEsEZ4YWGO/L2JAsDam0Y79DVIIEcCsSfO1FwAF1l2RLPHvEb9RgALpbETzjbiKlmw6P/hlNmOJeuv8SfwxuSr8AP1WQKMwwSaXArgTwKsYMGqdyxeR3WvR96n11ttVJvuP7NgjfAAU+ocFvfvq66++mpZkgeeAsAa+CEMHQgSqE0C2iJ01p+0Gln4thOvb9o0EWDJ2qQ3CI3Uj0oAi/yH4h4499xzddbsdhRPo79eD49DSVhU9MKCwFQcYIUtwvpH+xW+yvvrr9rVqPVkLUDZWbC4nwoBFmuMrMjXrlix4uwe8dTXagPA6qu4Q2NBAo2WQC7A8pzLMtREgCUwpe0II4WrbvEdSJlHfAXfxH8dC/5ed27E9388PW0P6mWFOMDK3SJknKbhfmM8mR7Atl/keS4EPh32zd2TVQAWeZ/l2zqqwzYbVSwArEYNR2AmSGBcJVAKYPEk2iiAJeWK1PS3HHGAtYHrqnw+gzIOYHGg//8S1p9H/xZ+oD5KAJkfpuZmzpwZt6wIYOVtEZ5G+vcuvPDCl6tsoHwJcA9rG/ZIn0v3fS/IrSdsDZpVvBDIwZe26UX2iYexqwH9DQBrQAcusB0k0AMJlAJYtFsVuPSA1aertA+KophtIVfiJtzMp3OVCkUAi/9gvIUSv2TB/+O0kp/4xCfmsJX1Fq+o0rKEuA4lgExlwXok8bJFEcCS9XGET4y8o8Nm96piH//4x2VdmoO7F1cIfDoUjlmVN1J+T8l27EUTvdE78BQA1sAPYehAkEBtElhITU8U1KbFslEAyz4oCsCKW7B0IH9WQV+iZP/xVH3fy1mwfMLf4GubUMCrhbZu3fqvAIFrLrroope0JISLOiSg7SH9vUqcis5gmeXjhHihEE6XAC+sOCshqTfgardg+ftpjh56uH9208ZG7pcy7VieYMFKH7oQGyQQJDCgEtDh4lUFvG8gvVEAC370pCzrRccWrHvvvVdvIU5CITyqukTTp0//Zzx9suKduIhkveLipYqgzTdFCSFQlwSeS0U3JyrLPYNFXp3dkZXkaP+n5Yni4TIuAea5A1j4NxI/GxBUq7HlvvvuM6uYPfSspx2Li7OSDOveEs1r4j9GjLFW/rdWoZZvNuQMEggSaJIEWGCnwM9cFtzHC/hqnAULkGNPvbaYqwvaIixtwcIK5qxU9D+yYJ199tmygn0R9674ViDWq9cSNxEn5TQUh3HpRyPIg9dDYSYNYOWdwRLI/iFu8oYNG5bgB8qXgLZhVzOv9cbshKlTpxqwyS9VMjXFqiyAZfdpXi16eNMas08MpOXlb3RaAFiNHp7AXJBAfyTAt5+0PTjCgjtwAAu2pVxHFi9eHLdgCRyVPoMFSHNneJBDBLBUJ4DrS3hLOG9lWyqKfgPuJtwPcfF4LgN1IwHA63Eqz0sGkm+cirYIpZgdKGMsBdAC5UiA+1zz9tc4yVXfqJohvy6iPgemGIt1vk75+5aoX+PoXm5gG7PqW8Alqu9vlgCw+ivv0FqQQCMlwN/faHtQim1QAdYm/6fATr4Ao0oWLArJgrX9nHPOWe0q8D8ool8Q3EN9bkvQW/pey/XXcFJQS4blo4jxfo9j+Lm0vQ3F3HIGC1lnbhF6+QsgLMPtwAWAhRAKSADrPpy+bae/v5oqv0ZyDz3UZ1Zl+RaX10wEsMg08OewAsDKG+qQFiSwl0gABeYAFoptEAGWnpZtIbcRE8CaCUDS6+hlSBasx5CDzvFEBKDS1sYy6nm+j3wZvg7vfh1fT9oTV61a5bYXfXrwupPA8RS/DbnvjFeD/AWwphPfprP4KKXbCmZMZCVZTt4AsOLCSw9rzj7MA9U2JfM3WLUCLMbCWbBGR0fjFiwXl85OFCuA9YC/CgArEksIBAkECQysBFBKDmDNmzdv4N4iROh6Mm4BWPRHW4QTr7jiCn0jqwxpMc/qu960OslX8nr8h88777ybUSKPKY7tkMU+bWi8NCDTp87JgnVzSltuK4v4tK0sKWXRRpxAbwBYkkY+afv8SR6oHMBiDtcKsKhbY7LrzDPPtHHT/ZlrweKe1cPQbO4rnQvT9nwZQKasjaW2p4HGchoYCxIIEuiZBFjMBLDWf+ADH3ALbk5DUmJTGvamlhZue1I21mXBGuFMjxRJGVIdUgJthGx+SeRzfJ/fQPjrxO1BOa1QZsJDBbA4b/a7dGsXn6A4RP3rFwHq9KLF0bibkm0iY1mwRG0ACyvMHCWgoDfgBYAlYRST7otNZsHCrxVgMRayKm7SfSJW8HV/5gIm5t2osuJW4wTM9sUNNAWANdDDF5gPEqhHAiyI+1FT0fagGhPAGtm0aZNZDXQ53qSFOwmOHMDiybwKwFqT1hGUww3ET163bt3/h38Q119TvgsuuED5dyC7oQJY9Ocy9Q8Aqe3QftJRNKY/+W2zYMGTA1hsZUkJJ8nmouamA1jkl6IOlCIB//kDWXY3mQULv1aARd2672RFNtL9ObdgXOLjuI68uYDMKm6yHwBWk0cn8BYk0D8JyIJVGmABXGwx7B+H2S21WZ94In9K2eFzenaxlpS2OiwV5XML4Z0s+Ffia+H/kdL80/lKgkMDsLAi6WyOezOSfj5P/ewjaXtwD98fuy3ZJuPpABbj2Qaw4NPm4kbGROd3ZvKlcm35BkqRwLJly0yGmwCsZrGW9bBOEsByDzmqlDGSBWsiVip3Xk5xKeTGkTEUUF6PCxasFCGFqCCBIIHBk0AlgBVTak3oqZ50tYDHaasuUMxlAZZeCV8br8DCgA7V9WOctqf+D9fuzSufrm3C/X14GLzfphO7cN/H6VtJ/aTjaew+//2xZLvuLA/jaeAgnh4HWO5cHG/FDdOYxPtaR1jgRw8ImwGsDmAR7oUFKwJY1G/3px5ksigaRzIUbilmVdKk+GDBatJoBF6CBMZPAtoiXFWieT1dimwxHLsa3995LOAt4Airk7NgwVbZQ+5a+FO3CH3X/gT/L3gr6jx/bZ4A1tBYsOjL7+J+grsHtxDXT5IF6+a0BhlPZ8EC2LedwSJuDmV2s2W7mXkgi6IsJgFgpQlyLM4A1qYpU6Y4gIW86gZYslTFAZa7PwHIehjKIremMIbBgpUloRAfJBAkMJASWMjC9kQJzh3AQuFJqY07YU3SQ6IW7RaAxdaHA1jwWWjBuvzyy5VHrqUOriOinbtwp5911llO0UcJIyNDA7Do30vo16uZB3+PL7At0N0XQsHrzNRzafumtAb5Q28DWFkWLG0P7sEi87jKU58ssoHSJeAAFkmb+JhnLy1Y0Rks7kNZpDQuepDJIgewGMMNZFD+PDCWVUej4oMFq1HDEZgJEui/BLxyW4BfGmDBpVsM+89tW4viYwK8uwXcUlmkHcBC6RYCrC1bttiinwmwrN4Uf+ABlsafszGyzP0A9/O5c+f+X+QmgLXQz42UbtcbRfsHU+Ns2rslrWYAs9sihK9MgKVygETle5J8AWClCZI422ZFRpv494OOLFjI+VW4czOaULRAXGTBIuzuLcY3DzS5NQWeBMzCGSyEEChIIEhgwCWAcptDFyaz4BYCLBZVnUfaTl6VaQJlgSPxqSfmQoDF03VWHYX9Qw4CWPshl0mFmRuagfF/C3K6EPYuwb1Cn+rgWnNhyqWXXuqUXh9Yd+e9AFJ3p7XF5zbMcti2RUh+zcWNsXKPw3/YIowJJB5ENs6CxUPI5tNOO20nafqngqpbhN+m3EU5n2tJAiyNj9opAlhP+X9k0ANTXl6Sm0/BgtX8MQocBgn0VAIotYVqwCvVMm1tIG+jABZP5VqQI+KDqc6CRUSZM1gOYCGHvDNYUd3xAHIQwNL2Vt+20+Lt1xQ+nXquBSRegLMD/LJgjezYsaNf/TqU5nbvt99+D6ndJMGXgID+BicNYAkEboiVcda32HUItkog2iIE8Og7VQLUVQGWmx/r168/obXq6KrlDBbjt5sU3aPuXotyxQLwojVFQEwH8IMFKyabEAwSCBIYUAnwJOsAFiCl0ILlu6hFsF+WjVyp2hMxvK+NZ3z/+98voKAn5kILFsrFLfoArJY64vVlhWlXAEvbLouz8pSJv+SSS+ajhETHlMlfVx7aE4B6AXL6p0Sdq3XN3NDblf2gQ2jkofj/SaY0KqtkGmDWXHSK2ZfROA689cP3pXaP+W7brNpOFW1j/KsCLLdWUFfWfBWIi85guVYAWOTPHBfSonEkLDA2c9D/5zNYsPzIBy9IYC+WgLNSsFVWFmDJWqCnzSaQA0ccgm4BRygMPZk/xUJdBmAJROxZunSpnporETJzAAu/Y4AFjxM4bPwlGr4A945KDHSf+TdUBTxoyydOThbIMVMhxjPXENYZrAcL6qkCsNy8KKhvr0z2YGoPb13KIijazvhXBVgLVJBy7uFM4QTNpJ34GSwl6x7NA+wRwCKfm3/8z2RT1hnxX5kCwKosslAgSGC4JMBCqEVyz1FHHVV2i6wxAIsFXgv2zg9+8IPJxVyDtJW+FQIs8kkZrz/11FP1/aeqpK0SWco6BlgXXnjhq6jjFN9wv7bkfHMjLyBwH5Ys93kDi7Q/6UW+/QJYUqSyWuSRAHOaBUtlNSeNpMgDwDJptPuSoe4NPYSItuFKAyz/JXh7iaBtvjJG2jJv2SJUI1DRuEQAC4uwmwtYlfs1/8Y4rPk3AKyaBRqqCxIYNAmwIApgra0AMKTMtBg2gbTAr4opizhPWQo5nkdhKWMt/pUJYKKzQauQYccAi7JnU8eNuK/iTHER7AsJYP1nsiX/J707kGu/FJy2lNJAcpy1shYsKecAsOKSi4WZbwJTAlVGlQAWX4IXoDXs0AawrrrqKn0VXi99JMdzNXGVLFjwui9lBpZMSAPbgcB4kECQQNcSEMAquz2oxjbitMg2gRzAymBEB93LWLC06HcEsHy72ibsCGAB0GRNeAVA5q/xH8f1DWD5tk+g7TaARZysGwIq/VJwaRYPmm8hAay08ZwNv5qTRhrLov+9s7xtPnL5NO6NbQlDEoGsugJYkyZNsjNcetBq2yLkf0oFlrV9+GRCZLKQL0jExS/10ObGEQuW2yJk671fAD/OR23hALBqE2WoKEhgYCVQFWBpYR0mgCVrhxb/TknAqO1JvmRlR5BvH5TerfiqZ/+S5brOhhI7nkr0eY42gOUrzz2U3DUDrRVIKScVcmsOtrWIECBNkuZiEmBN5fMTaWAsWbblms9SCOidgfuqXjxoSRySi24tWPwNkQGsBxBJ27wHFDmARVrSgqV7LE+mEcCiDYF7vU0YAJYEEShIIEhgYCUwyAArj/csi0dyoASwurFgFSmOZHvx62N0wV+WLEOZOKCGAtQZlp4TivBEGtm+aNEigbs0khWhXwpOwCapkJM8tQEsLE3ajpqGzAT6jWwsNa6VaNu2bQdZAT5R8TYLD5kvkJrcIpQcy5IBqFSABTjSWIpaxpP57e6TnPkdASwO4Ats6xB+nsVLbTSaggWr0cMTmAsS6IsE8kBKGwMslBuJ1GLYBCraIkyzeCT51lO1KeVkWplrla2szH3FS/BXf+hDHxJAkFwnYnkpfeCY/N3QsRS+M+fTCLIi9AtgSWm3KOSUjmnLt2U8AaamzCU7R3ZAGr8y7yh/A1j3EX6N1TlkvuaXwKpRpTNYyNUsWPdTwUJAbhJHOABGPoGkiJCnANbkT37ykwbQojQfiAAWa4y2qHVsIQCspJTCdZBAkMBASaASwGKhFBjQ35r0xdJSIMkDSF+ZkafsGSyBIy3+nZLKCqR1QpK9+2gj8hS/ohljXs9/n0MLt+a00heA5RX0KEq1RSGn8NVmweLzFtoeFEUAi3oMLGtcq5IAlt4m/TzuFHgb2C/053S8qzNYzFMHkJCzLFgTAblJIGsAqwUwk9/dY0899VTbveLXkghged5XEx8AVs5AhqQggSCBBkvAL2yVABYLpQDWPjlPon3pMcpPB7B1wPnBjAarACxTyhlVZUd7xTHfyzI7Y3pKXPZblIVDxJXPDqVXnR3rQc2x8H5bdq6+HXIXoBRYb1HIKXylbflKKetDr5qTjuyDsYxHZYBFGb2s8Dj1/QR/FP/IsVqH6rdbgOUsWMhKAGsEkKs5HKdUgEV+B7CQaRvAuuKKK2SZFJiNgDLh1bgAsBBCoCCBIIEBlIAHSVNRtDLHlyIWSqfMOKPilFupQj3IxEJ9sKqF9+UZ1acp5Jasl19+ucCMXMcAyyuOqZ/61Kc6sTxFW5z0x1mwqK+Telr6VXQBCDmEPFKUt+bk7YsFi/adQsYvA7Batggp4+YgcyBSzLEPxlYGWL6+DZxPu5HwbsbiefjDRl0BLGTtABZCWe4FozkcEemzdDFz5syW8eTBwQEsZNsGsLBq2VoSjSNVBIAVSTUEggSCBGqTABaGebj3+o/61VZvsiIWNvf0iSIpDbCowy2CHGa17ZlktX25huclaogFO8+ClVTILbxt2bLFlHDHAIsKXVkOSFtdLW0UXLRZsKoALPLK8lOZ+AucY1WI8pkWLBRlXwAWYM8pZHh5sqAjbVuE5HeKGXAaKWb/PTf9X2Zy66qgepcsXp7k3hM4WIXTFvSwke6J5CF3ga6yJEC8derUqSt8gRaARZzSd+hPw32688gvwCRqs0pxD2cBrKR1bKyGAflNHk4bELYDm0ECQy+Bj9LDz9x5553v62VPUUxuAcMvDbDI6yxY+OMNsGSFkdKVIkyjwi1CFnYHiuiLe7pOq6QozsoCONuezIvKkt4GsIgrZcECBHyRA/E3lWgjLctSIjfztpYpybQ8eotwdq9BPkDI9Rc52hm0NF4Up/QWwAwIdHOQc0ARwPKFBXo7AbwOYPk61sObtqGHjQSmdN8YVTrkjkxkwdrMixmaH/oY7SKryPsCWC3WK8X7j9fqfw/b7hPqTANYWpPawJjqGhQKAGtQRirwubdJ4PXqMAvP7/ey4wAMB7DwSwMs8jqAhT+uAAu5HI67B6CxO0NGhQCLck4Js+hLIXdEyMGBszTFkVchYyvr0wLKOdlTjwMY+GXPYJ1K+ePofydKaAllH6Btva2VSvC3Tgn+y92peWqKdKDJ+p9TZ9uWLzwKEO32yjtetA6ApXleGWAxHhfjbrn44osXxxlqUFgAK25dqgSwKCuAtcnPnZWMwf7xvnGdCrB8/jWktwEsxt7WkjhQlsVrAfk7stLGeRqv8DC+ITFesgztBgnUIgF94JCDo3qb6fu4Uz7xiU/M8a/x11J/vBIWvYUsYIoy8308OStsi6A9dWbl63X8ETRwV04jbQo5mZeF3S32djA6mV7metq0aWu2bt0qMNymOPLKY32SUplMOQO3W3z+QgsWCjz+3aLnUe6beW2lpMn6tzwlPopibuhDoyPIRlttHQPQqMLsgFmlNF6ZBD9b4cfyunzEzSLOlH28rMCh+I4Ieb+HvH9CxEH06YXnnXfenVHi0wHNaXd4G18WmsoAizLvxB3AGcWL8f8Il0uM5fvI8CLcOwhnPSzk1lExMQmwtlNecWVJAGqzz7wSvwVgcS3Q22bB8vn1MJJ2n7i1BEuke3jzebUm6YOxDtD5uIHyggVroIYrMDtsEtD2C4DKWZGsb4Cr43z4L/H34WzPCZZWt4/CUdsbWNi1yJYlLZ76g2N76ixbru58uQAL/mQRalHIKQzIgrUndjA6JUt+1Nlnny3AqVf7VZcj5LkPiuEPr7zyykzFhZK3cV/li5UGWJQ9zJfRIX+Bpaq0hAIGJFLLMjcEUkY4r9UCVFIzdxFJOzZGuQCLJpRueV2LlJUyf9JdtP4IEEbjwR9qH0fevyLuQdwcO4PWWsRdxeurDLAYdwEFWa6W4d7GdS5Ag68Xkk/3+dsZx1fg94Mkw64tWJ7Rlfjqb5wEwNLGRHn0MLGfAglyAIuD8bqXjNxDX+w+sfiB8QPAGpihCowOowTYfvkogGoVC/Hf+jfa1M3n4gQOvoHbjGI4Eb9XJCVvFpRSbcCrnrI3wte4ASxZ9eBhf5TSXVlMw59kWLTdJiW8vsIfXbc1Bw8yAa7Fj57MpSxp//+sXbv2v7cV8BEoeQewOHvk5L948WLxKyq0YFlZZaadSgCL/BMotgQecwEWb305gEW+XgMsA6GVARb9yFLmLQCLPh8qWUHvwukcUBIUuER+ugJYlH82TvI9G6d+vR6XSVhQTyfxTtxj8PiatIxXX331ZO65N/lxS8tSNU58xWUtsGVjUKYuyXyzz7gCf/9EIaVnWbDSAJmKC2BtTxyMdwCLfi9QhkGkALAGcdQCz0MhAS2cdORPcQ/j3rZx48ZvsJBKuQpg3UpYVqWbcI0CWPAj0pOme+p0V33+YUvucDWJoswEWKSVBVhSxt1S8mzJ83yFOkyeSvDnABZK1gEs/0X1ncQXgUL128Dcr6jcwENqO8lILGtqV/NseTItfg3AkgVHAK6nAIsmzCoVV/pxVlwYPjSe+lscARgjAaI0ZS5wGFmwKPNMrrdxqF+yFpjJA1hmRVH/98WVJsbF1Tt58uQbKfRL3G9lFeb+FnB4I2X0R9+34dycTuZfuXLlHxH3Zcbtlcm0Dq+nUk6gyhHtVwVYoxQ0gCXAVAVgPUb+NNlrLTG5E3Tfg9NYaf4FgCVBBAoSCBIoL4EVK1YcTW497b0NK8ar8V+A+zzuZNwtOJEW6pNcqDc/UrZuIatY/Qbyz6lYps7sR6iy6dOn35NTqRT2RA9ks7Jp8V6TlVghXnUY6JFSMFAssJxK5JHs9xx11FHx9gUiCi1YlFVbspzdinsGrgotUWbqyLVgAWKfJJuslZVAhuquSKUAFnVqPCdcddVV8fNns4gTn0kSaI4DQwGsRwATktkKXJqSJ3pkFnlcffia41X7LrCx+1nPetYq/Otxbp7ip9GpRE4AjP0j/t24VIDFOB3kC7/c+916LQCL+jsBWJvEBDISwFoEWIwbazQmLl15EpQl+zaAxVu5dl/oHh1IigtlIDsQmA4SGFQJsDgJSO0eHR296fzzz/8J4T/A/R7uCNK+ga8F7Ea8pX5LTFF10yADrIfOOuuszVkCQXEIrIysX7/eFHha1k77n6xLikbK1UgKXZSlyDW2anttYntyC3GFAIuyAljrcbIILMJVoSU+8/K8QihNgav1tBUHKnlFOk3T+OzBuqQ/980jAawRvl0WH089oGQBrDn0wV7kEgiVpViUquR9XlnIrD5ZVAQWcolyn8F9VJkoq/F+wo+pQFbaeSNlFb0Md/2HP/xhPeAIYB2W8UmM55AmMn/sqvPfFoDF+ApgxUFrUc2Subvv6K9kOYnD6ZqPRlljojmv/KOXXnppUq5tAAuZarwF1ALAMskGP0hgGCXAYdSTueFrvdFZnE5GVrcbSKD+r7AAaTvg74488shvSo7kuVM+1oTD5PeAOgUYTbBgSSllErJ0AIuPqeZtuWlMO7HgJduV8jZLg9Kk0KWoM8EPYzuP9LW4OD1FfCHAIo8Ums59OSXOdXzbLF5fW5gyGvMdABqNYRHpTcJ+AKyt8CXrUh45gMX5szjAkqKWEm4h6tIWocgsUJL1ahczJvM26ysfwnRKn7IOYNFvzZ/JGaDHVXXRRRcdQuC9uPO9pVQge6USqUfzagH3dZYh44Wk/1x5oeW4SZzJXKyLBBlYr2qpTFQTXU6DN4EqR/RT4akV5tAo+R3Awnd95RxpnG8BrLYxIU7r2aPyuSetT7oUCWA5uburp3/0f4SarwNJWQM/kJ0JTAcJ9EICLJDv5JzM9dR9E2EtBHXRyVT0y3hlKL3P0ca7zKrBk6Ft4xwaz1djWItXJwBDT/d1yqJql46gwF15hViYHcAq+G8/9d8Ub151uWkorIfIcJCUFOMnq4kU7Q24Ua6lcNJIwKUNYBE3LS1zIk4AS+e+Hld+zuckLQKJ7E9fUkbgYgM8FwEaFRJQ6QvAUmN5BL9uPOE/Lh/1u00xk9fJlTfQjHfNVc1Z0WZc25jwtq6TIfW7+qw9QE8mQAfsvdDVyA9b/sfjCWjISiMS+NVcMJCnOEd+HTmINm72UZo/ojhIH4t52oJTF8CaSsUOrKoBeBDAGmEO6UxoGZLsDEA5gMW15ruR5CgZp9F9iqTNZyUS4+MTT1rNhR6CBpICwBrIYQtM90sC/jX7T9DedTjd6OewOL4Mdz3uRhalCzrZvrvsssv0FHgMC00LwCKuhc455xwpCimG2gGWf2txFB46AVgb4KnNCtDCfI8uvKVgKdXnAizSnRLhLEemgiRPpwAz2TspyBkf//jHZSmRstHaegNOFFc+YzFjv8rrgEAsUjzHAUQsqSXoABZjJ4Clb1VlWspaSo1dOICVEp8WpW1IAylp6XXEqb9urPIqo68uTwJgSdm3ASzinFzJKxmL4gpc4ED3X5KUR38c7eqjrAN0POTkzZ/DKWJg4wjCGuuVOIEIASyNjeZYkjR/ZdG51ydo/ohaABbpskxqrG/B7ceaU2UrjyKt5OuTtcqBKqVamPOMAl5lSLIzAOX6yrX6bTSPvifntUvjAVLgU29GJwGWQJnWuSRpbQoAKymVcB0kMAwSWLdu3ZvoxyIWyf+GfynuQ7gf4XRe5A4Wig+xffdlfC2EpYlzJC8g8yTK6exVJrFQycogK1btAIu3Ft3CDw+dACwp3rYn88yO1JiApUBKbTKK8La8akl3CpI8UuBt5IHavsi4k/631IcMf60IwJyUrLM0UO+NPlNc+fgo56UBLPGcp9CtvJSuWbCkJPPO+lgZ86sALFmwej3OGp+txlyO7/JgNYrLR4fSDeBERRn7PIAlcCBg1kKUcRYsrNUOYFGvmz9sf8XbaynDhcZb4/wITvMysmDZ26FpY0PdDmCwLekAFsBJ4EIPLS0Ay/+BuORzM050wJjX2a9ZqWg/AlgWZtuuCsByModvjYnO6anfI/7BUfJy4FJxcSKf1jP1+dnxeMKSvZN7Ij5YsBICCZdBAkMjARbH99GZH+irz3yn6GLCZ7NI/Bn+y1lc3oH/+7hXsnAdh1+aqPfVZF7NE92dJQpp8a5reyBqDoXiABZ+JwBjPRX12rIR8RoPIP9jdc3bV7fH45NhFJxTkPQvVUEC1ARSBE466X+yOfGyhbpehO/GivBNPtOCZGZ/LYAlABMnKSwp1CJyAItMTpHR10VFBWLpcwhLmZch5XOWnTKZO8xTCWDRRlw+s5Bzm2IG6JpcJWPRbOaNQIxI4GDUhWI/yNABLKJcPup184eHq9T544sKVN3l3ZH4++NW4kQG8toAKnULYK3BQm18Kr+sWC0Aa/PmzW6OwvstygB1tQ6YlYr2I4BlYbbSCwEWa54sszPgxyxY4in6uxweNh3Qp868e0oAK2nB0hxrG0fiAsBCCIGCBIZOAiwmWixewmLyeXVO3yki7pOAov+Jv1Nx8+bN+xaeFhsBplLkD82+ncz/Qt1lzsEIYB1YqvIKmVAoDmDh5y2GqTXCtxTDviyklSx3qZVVjKTNYyjyaEI5tdWCYnQKkv6lKkgDmBTUIt4V+flwHbwZwNoCIJflUdSmYMeiHUB1SthfyxPPcQARS2oJzmcM1hCj8rsIL2pJzb+oArAENpS/l6T+Rgo/qyH6KPApcvJB5lL22uJuU8zco5LjNsZjrp+jAk8OOJFf9+u05OF14h3Awqrk6mN+uPmTsJhRdIx8+7LEGMB6PuGp1LPCZxGQE4A34OajnactwvviEYTbABZxDpxTRy0Ay14QgMdI3hYGlBYCLPiZIZ7hpwVgESVgqa/+uzWl4KFNn1ZJAqxofFRPjHRvujpjcQMT1AQNFCQQJJAiARaeVyiaxeTalGQX5b88/EMuSgMsDs2q3gNZhBxwcxXl/MDHo8qfk6XTJPe0OXv27MoAC5kIYOnvYNKUR6f8lC13LBlvL8qM3JxCxk8FWAYwAWKV+5/R9s+IfzFOb0g94j8cqv/Jm5uRP+2sinhO5dfqQPYCtfPw16DkdxOWFasnW4TwLlAi60ItxHx5BTw/J1GZAJMbq0R8yyXK2wEeIh3Awhoz6jM4IBPPDN96cBH4nEebyieZOYCF7/JzH1p5+N4ZHgAAQABJREFUop4GQhx2dwCL+eHa4z5NHQ8sPhrn6bR1N+4uwm77jvBK1edBnsZnpq4TJIBxbyIuE2CR736c5lJX6wDbnQaiInkzjxzY4j6wtARbT1/SZ5vLsmAbCVAu9hduHlKXs6xahrhPH9TvA/12oiVF3x+zCO8LYM1LguFEnsZeBoDV2KEJjI23BFh4XgkPd6EQHivg5TukvzSxYOQV+R8k3sm24/V5mSwNPgSwFsb/1464CR/72McOlm/5OvClENadccYZprhKV8EiKYA1EltwS5etIWMpgMUTufXLKeRku/TBPRmjuOsEWKrzNThZHUXrGSNTSmMx/PqxlDVAICBOUnyp/FomviEkwDMJ/tf4uMdpY5Gll/BVfkOJfMpSK8CCz+9T5y2JttXfSOEn0uKXLg/9doCHM0MO3FNnmwXLF9IcnYdTf0UOYJF/89hlK/ChXtW3lfvdWaeLLKDMr8NVD/XdjXeXwiLuCRemPoE8gSLHp0t8+mcp8YUWLPLM90UENB6hrWc8XUX1kIEo6oksWABIF+Y+KARYgE4D8nEAJUC5v7iBX3dPLViwQPymEnlkwdKnGmT9G/HgaRSe0sZR9exz3333ZVmBVUVjKQCsxg5NYKwBEhDA+l4RHyxa3ybPFA6uv6woL9/TOpY8b8B9koWmzPagFi0BrBH+126xfBTAJJ7Kv84Cvxz/fyuuQ9LTsKu7anl4ck+w8NAGHqrWVSU/fRcoWYJbVlQOy5wDWCzcqRYIymv7ZTuWhrSFvaj6tPQfEynryNE4A89S8m0yYixdHLw5oEoeI/Gcxa/LwzkXp3Qpu8YXkrIzxeejcr05pG7IzeETaUP5ZtZhQeBPzQ0sjMT+d1MtVQJYPr/KzdQPACFr/AReI4DFnHUAizhnweK+TbNgRXWZxYxyWeNxKHXtwj2EnK7Dd+Q/HGqXasvxaRHMYQG+/SiTtGAJlM9NPKhpjuovfgQKlS6rWcdkIMpAla9ou3ziCgEWPNs8iwMsPYAeSNoE3BGEzXqratuItzLdvQtY030ycv/995t8bHyiMvDkHn7gW3LIJeS6L05zqTEUAFZjhiIw0iQJcKMugR8toN8t4uvcc8/VE5kW2dxtQikVFpW/Ju8DnM/5p6J6LZ16HQhisREgEuD6//Feh/tX3HsBbcfhd0KyYBVZ51LrpR8OGMBLG3hILVBTJDI4zFflnoLzqj399NNbLB7JvMhVT9ur6UMpoJssn7xmzmwh7p99/I+8LzmlyUiKXyQQECfxnKskkIGzEpjyIf/juCoWrDn0uRTAol6n9NhOS7PCkFye2J463nLzBuuzLIzfEcCi/8aTA0yx+iwo5SxZOQsWc9aBJ8oJrMjyZIpdlyKNU7T1xVmsIoB+CPkfZtx34sSDxv6vcHF6MtkO7VvfkxaslSrIwfZoLCk7n6g1fo4+SHgJrhtycwtZRBYsC+OXAVhu7nH21AEfz8hD+DP5XI2sTCfhfunjU70PfehDmnsP445RBh7S3PjQxwjcKl5E3Gr5yCEXYCF/9Uv3mtbXxtCkxnDSJ0b8QGS2xsSpZbHNbKDDBJ54G8UXAGHPaaedtlPdwYoylfMQvNQ1eScLp57otODo7EGtxE02gbaeyU13MuGTqVxOIEiLhRZDKZoH5MjzAHl+AB/uBiWuElH+lZRXH35YVJC8e2jnO+TLBFjUJd7/ljzPwb3Mn88pqtqls9A/yrmQERbAA7UtyIL05yRcgfsQ7lHi/xD/DFxVEmC7s2oh5ecpdB0KUwuflFLfiL465cRcu7eoUT8uOuicZYGQsogriqIqy6S/j0xfwuJwLXNC+asCLM3jLH5Vn2QuYKytKAPHaiMCL0rLInjSQ7XevJOSK0NmVZASjMBHmYLJPIzHYtq16CUEbvUXUo6F/MC71pVdsfF0AIk50aaYfb0a2xNxToHju77AhwNklBv1+cwTsNEa4oh7TmMhJZ81HgJYWm8cwdvbLBzz1ZYBQRcN/0sV4L5umcMAr8fhSZYk8XG/yzxmZXVrGHw8QNk3+viOPOqeqjYgAXlHWPK2YSFSPwsBFgVkwdroz56OVTB2OH9kx44dWotPop5PWEKOfztpRyud9czJh3I216Ji8LZavMGzA3ZRQiJA2TcgG8Wekkga18u9DmAhbXfTZEkdIJOVFOJjEuAVdwGrKIb9dO2pR9csNgrrTi5yuis247QYysn0/Dg3jBY6LSxTuHEOxj+B9rRYyrSO57a2fon/Bdxk3AycFM8LcW8jjxbV1fDxdpzATyWi/Jsp8DPKllIq8Psdyvwx+Z+BeyTZGFamU4n7ffL9V5TvDcn0vGue+NbT96coeyCL0XvJu43/L7yAv9iRwtFT8+/jfxDnAG9eXYm0Z3D93URcqUvAlZS6wLQW3H7Ss2lsI9swqz7ykY+UaVeTUgo8jeYTuSYtodM4PwbfwbcqJKfD7SLmz/Ph5IIjxZfFryvCPBMw3sFblKuRg+IETmQ9KKRp06bNYouRqVTNgoVinlNYeUEG+JaSlJVvIu3rnjZSfyOFb5EZ/pPEG7Byihmwrbg00lqi+dkCsFDYWm9Erp6xoPsVsIkAFvfpNu472M4E6AJYBhJj1bQEBbBa2qE+PSSsTb4FC4hwbeOLDyPN0dX+Yjn+fP2P39lnn53VZ5813aNuB6IEqiwH8nBh+CoDsBZTTnKNCPk/CLgSCPpdIvU5jB9GidmBO0h6s5KZW7Moq/JtffLrjBb8BcqbRfB+kk/TA0RjaG8EWH+QJX2tOllpIb5NAvswqQVs9kFsWrB2cj0RX4dvXbzSzJEm2UbXFibvRNK0AGnx1WK4FPdi4hTWAqqbSwvPr3Cfxf2SG/qXKNcVhFNJbbEwSgn9Ne7fUXYCWdekZk6JJO/LiH4NvAnMlCJ4+j6LwR7K/CYFPpcsBE+nEfc9Fu0vJtOKrqlTFjIdcNWC/lbc39v/F7I4/RML05/iv5j4HxXVZek6ZM3DxAHU/YDFVfHhZzdOYyBQ20+ScrpXMinZqIDp9Iy8Ul61AqyUdgSw5ibj4UmfDxjBEqz0iIjXfxFm8Wv5JPPHTAb4GyhTCgABrixfm7XAKo/7KOINsiBABlLiyVXDUpJSzjvgd0mscBWApQceBybptyxxsuQJxLQR6atI3w9/jvIha6fAsRxtlkWY+NFEIQGb+yyOdN13QqNZ46H78WuWP8NXmy0Ai+ujcQIYLXTUUUetYSs2+ckNyczNUfrg7lV4X0LcbS2FS17QF33FXZ9TiAAW1uhtskZDU/Kq0f8uUk768xvxfICrx7l+CncmbuOiRYtuiKenheHjdvg4E/nOxHdzi7nmxieen3Q9ROoekRzy6ASfeEA3ADSvgU7S9jqAxWD9YyeCCmX6LwEPAvTtKVnBSpMWRjI/Qrnfwf887u8J348rvPF1EJfF5p8o81P+cPnv8EsRlgS9Mn8Di8WrKfC5eCHitcC+FHdGPL5i+Nfkf7/KAKautrJHHHHEr1iUpZRPIq40wAJcHUx+HUp1i7bVV9F/jPzjAbDuqcBnHmCZRz2Sa8+IuZj1Z8lqe1PKVnGhBYtyenh41JhmDGXBmqWD6PYflpaW9Jk7c2Qt8GWSyW3X8L9RkeSfzTyWvriIh4m/4AFHSrUq6SFKVmqBJM0/o44AFjzNUgVYzvWA10akq62pOM3Rp0zWABTLnwQ+i+hvi3VG5ainDWBJidOuvkVWdP9sog49LMbpGC5+Eo9QWGOHjMXz/rE0yexef71cPvwswesIYFFW8tBHeiOAxXrnwvTFpSk9SfC1H+Dqp8RvpOxH4umk6WHrF8T9Bu7zJud4nmSYtgSwtJYdyXx04wjAcnMtmZdrySQTYFGPHqiPJ88PcacwLgLKbWCNuL5To8xpfe99aLDREtA+v27eTpmkrLbM3oW7GffViy++WDdeJulGZbH5azLMwL29SFmlVPQd4n6TdlvuKxYR3fyTcT9OKVMqigXphz7j9eeff/4dVsjzeCu8P9fiyvjUp6dv/U9akYLIq248ANazYcgUTh5vlibA0qYgfeJ8/DWWsRc+46Knb2dxiddPvADW2nicwsTLEiDAkUeSwXLLwFgKYI2UOYiOMnMWLFmmrHyejzI1pScrwym4D2GxuCSvTE6awIKU5YO4JTijqgDLrHDi6cmcNcKBJWS6lHzWjxHyb+daVrRRY8D/bdJC4pLAUePRNn+8FUnjVXT/SNFHQI62p3B9BO52XBrJ6hYHE4sZ3xU+40p8gaEl/roTz80txjACWFj2XJh2p+ZUeB5pKvuytN0DePwL0n6BNfFjOXVESczDO7mgyT36P1YHsFh7s0DRavLGZRLVowDr+kF4c6nHjjvo3moEtSiCRnAUmAgSqFECLGhbuenfTJWTWFT+xS+kqS3wFPQaEn4X9x7KPZKaKT9SAGs+gOrEeDYWE11L0S+Lx1cJU+c15P8R/h+nlLuNuKNT4vOiDiWRh9JdepunU3qMggd2WrhqOf/tKFkZllcomwdY0j70WaHq4qzwKoA1NfFZAhWUElBakjRPJmbNUy+DE8hznRVESRlYagNylsd8+HHghHG3MpaU6nvrkBShyun+EFUC82NF3K8DWH78WixYxKnfZWg9mayfAlh5/TBr1GHkiwCWb2QTfgR8Vq5c+WquJ+L+06eblwqwuKfdAwoAtAhgqR0HIFQh96+2uCfhbtd1CglMSE4jrEHKp7CAla71sPkgY7FE150QcjYQFcnbv6yk4w2W1lI17U0g4o24f4AH3fNtxNGHfyPtRbxRXWo9Ie8WKrmfurVuaRz1MC3gm0aRTNISOZd6vOLh3wEs/Plp+cYjLgCs8ZB6aLOvEuCm13bKm3Ev4HD+p9Ia99/5uZS0n7BYfDktT1EcT4K/IM86Ft/fSeQVwLqFBUQWtY6Ij5I+QPlTsF4JTCVJi3xcYSXT265Z2KQgHuqGJ8rLkvRs6pAi6DnxhqrbaoH3FRUaS1WQ8DyFOnSGZ02FuipnpX4HouB9bqKwrtcm4nTpFN/69eudpSGZTvwLiBPvP7c0lLYDGfgOPFl8mg8/Lg8vSbgyaXnicchJSl3gRErQQPyzqEdKtyoJLEhZLsctoO6Z+CL1NVL4Lib7Jw6w1JfMfgB+nvDVLMVPAqzNxI0qHT50nvRcgjdz79+iuBilzh+UuO6frRwNcOAnlj8ZbAFytHOMMnDu6Y5kRn8t+SzwYc13bePH57vudT0cdUo2ryIwQ1/2UJnetp2aVikPngKozyDft9PSu4iTDI6hXQHQJ3PqicskLdvxRD7BuuvWRuqbn5ZpPOICwBoPqYc2+y4BFlEppD/DfYDwO5IMsL3yB8Q9ByV1tl9wklkKr/3Zg2+S8fWJzLI4/CoRV+flciqbR7+kBMuSFIQW644JWd1EYS3YR3RcSYWCLKD7KzvtJrdx8mpJVZAUmOcLrc0r3G0avK5THfhzE3Wp/ba2mXviV+eK2ralFI8MZEmQwo3mE3EOZOA78KR8WUT9yrPrzDPPlAWhLAmcaG5JsT+Em4XS7USJLaD9J1CAD1KHZGIPBVLsnQAs8STeUgmLtcCzwMNiXDJfHPi8k3QB1z9NufdT5w990P2zPCU/0U8T6QIOBiS1JyaAtUJnNp/O1RKKwATyEd+iOIjTQ42sYB0R7Wv807ZVt8FrKsAi/lg1RtmbOmo0u9Ayko7E1QGwbmL905zWPNK91QgKAKsRwxCY6IcEeDr9DO38He5vuBn/i7X5sY99TNtcV+C+gIXoFxbfof91yh1HnU550I4W1yNYpG7ssL4yxZYrU0xhlSnTNcDiKfxmNUTf9ATZc2KBdwCL80NxhVPUrhbcNLDiFmFklqXoiuotlY5sZHERMCoFsMgqfkXTxrynf+n/BK7ehPsq80qWJUdYahzAoi0pz1zyCnYDeQU8ytJGMop/zRk75yKwVZr8lqfenJRVabkKIpODfZ/UV+u3kjLJy3Nfn0H9dX1PK4CMZDE2EKs+xMlZsMgjHfhh3L8Q/nE8gw+nAizSyt4/AnKylGrsRAJYt7tQ+o/k4yxYlDlAWTjisMKy0v97CC8t82V95aFPr8O5ue7rkOzWWX0xP9OCRR7xvIb1s8qDTazqzOCdpByESwPAUSH6HMkkimwNPJfLm3yUxrsT8N9aY01XAWDVJMhQTfMlIKXCNt574VSmbp0ZeJ8WIfbwP8e1FtI/wXVFfGdIde/kjMtvqyLafCUeenyfn+q6R7Rc9bIgL5FfRPRb9/2z4U1Pwx2T/yKzzlEc33ElFQrSziKy78EyoQW3LGlc28AK4+EWYWRgCrhsfZXyMQ+cMqMdAZQ4Sem1KTr6KH718kEbKMRqdBxJUkhfVR4j+0wBZUctLsefQ1omKMkoJ3AiS4O2Jr/n8yzxfimPrXmT9xN8jkCAQeBnyWc/+1ltL2s+lgJY5HsMt8ifacu1YJFPZOewdEwgTgI+o8j5cHxtgX02nhgLazzaxoK4KgBr0lVXXSXZiYoA1mryLGAstTUovrayPkUAi2sBrKl333235kEuYZW/kgz/jvtuDJBpHrbNO+K24abi2gg+NPbLmMNVQHlbPSkRsmCJnoeTpS+LJJPZ/vxhSx6+Hq/5rI9P3+YT9MAUB5Qt+ft9EQBWvyUe2htXCWgbD5D1Jpj4SzkWIS3Yv8EN+ocAj66VrQcdP2RRer1fJP+Y+u/iDNXd+L2ilVS8HbekTAMoFVnXZJa/tUz+gjw3kd4XgMUYCWDp47FSzmUpVUFiPXEKHwDUUwsW/wzhlBlzIQmw9NZT2nxzQIP8baCQ/C+l0xrnFrB+yCGHaGtEYL5XAEuAzMb4V4S3+7FQs6UIQLtQGenXE/7N14e4PDh21qwUwKJdtT+RM23H4Uu5irc8cgCLcmovTrJgzWT8T/SRN8QTY+G2+aP7mvRSAIu8Djhs2rRpJvN2JuUOgxcDA7FmoqDAxNRPfvKTyqutwF9TbrelIkcBLFn/nm1xaT7frFLZ9+G+hDv+zjvvfKPPJwvWeh+Oe5kAi0xaLx6IZ64pfJevRwAu76FJMtF/sbp71pdxHt91O1oBZGpWQd1Tbflc5nH4CQBrHIQemhxfCQhksWj9GTfl6+Dky/ivxfx9bV1cUd/XqesVWBz+O/5vc31uXXWn1eMX4NJvF6FUpJxkJekaYNG366jqeSlvyaWx2lUcykoLZ1VA1KYgPRPzvJ8GcrriM17Y/6WIPnYaASzGS+uurtvaRoGKXynQ6fLjRP9fxPWNlG8BIx6wqJyUchGVASXJOgRiJK89AEYp2sfhZVEyU941/XEAizxOWeI/iFvCXDQg2dKnrLr23XdfKdIdyPNE/Nm4IoC1nDwCdmovTs6CRcQJOIGYNNCh/G3zx58/mwkPZUCH2hnhEwSzyH8yQbwJ1ysug5x8yL+AdIGkFivz4YcfLqAokJ0LsJCrwJXuFZ0t/QH9PwcnYKh5tw6XJNWZasEiXtayJEBNlq98jcwlG6v3vqwKkJfNGckkSccQwfTabQ+w6rPd28m8fb/WjR4oSGCvlACg6lvc5O+rE1xJkCxkX5WH+0vcP1D/l/F7TctpYElRI/RX9/zbcb/mezay3nVFAIJvUMEMLAp/Rd23e9erdUULZ1WAJcXdBlZYtAXWNsJvFWsYRToiKTRZDhzxJXGBHCm7NoAFXwY0DHiMFRr7lTK5OR4RC0tZzYxdZwXVdhEoSZZd7iMe8YDxca4rASz6ZQBrla9LdS5BMVo/rd8+Od3z7d/GPXYSOfSZjSxg5Cog/Q4F8DUGcZK8ZuEE1G6MJyTCbQCLOX+I8sBDIcAi75O+Pn2x/IWEN9DnO31cm0d+Z8kh7wIS2wCWB9P3kZ4JsJjT2nZ9J+5vCetL9B8nfCJ/1/V6fM3DpCyISt8i9Gfn9I8PBoSUt05yAJL6W4BkvAHSWgAWfdIbqLbG6J64V/30ZXRP6d5uBBmTjWAmMBEkMAwS4GZ/hIXyVSwMf0R/5PpBy2lkSV5DPHmfRfpK3O/B21U4gcCuiE9g3EUF38C9A7cUdzR9l9LqBQlgtYGSgoakIE2JR1lRUJ2Atah8xUDL19z5SKWsCFLQbYoOy4P4FbXw7BWKzuS4LSKXo/VnM/X1aovQ2nzIN1kZYFFuf9xWHjYMcCzn+mB4dv1kLpqCJLqQbiDHKTidVcoFOaRrnp+Jb2fHrHIBGfF0POm/ssgUvw1gUZfmuej+MS/3V0BOhzAF5gSwrmMsoy0/pcWJfA5MAMIOJP4geEsDHgKNJ8fLxcP+CMC+lP2u4nlxR/434fsL+OKhbd4R19ZP4kaeeOKJA/D2wdnYK7o2gsdv+coy6+eecKCTfAv8mStdf92XOxr/dh+Wpwcw3duNIAkuUJBAkEDNEmBR0/e0Psdi2g8LibhfjluCSyX4mMcCeymJOr/zUvi7MjVjxUgWSG0b/R6LupTOTNwm2jmlYjVls2vhrASw4C9VcVCPnnLTFE1ZXqrkUzsOVPlCpgDS+uKABnwnrW5SdIq7z9eR9KTIJf8imkOGTi1Yv/aVVwZYzAmBmZWaL6oD/0G8RShPJxcAxTbFl6RfkG+J8gJIjCddthHzXqDu08n7kPZXkHkJTm/4VbJgkf9Iyq2gzlzrGXnEnwNY9E8A6wU48Z5JHGgXQBAJQOn7XG0AC96/RtrzeWB6Fzy0jTkyleVLAN6Vlcy5R99E1BcVz/Vy+QlKnT/wre1B9SMTACXqqXQJj/8Tft7G35I5MJhW2INyd+6Ph5P/6vP8Fn1/BuHn4CKARV2SX7BgeSEFL0ggSKAeCSynmsxvYbHwvJz0CbxxdjoL00+57tp6ZWxr24ZD/DrHIjCptwoPsbSa/coAC16yAJYU08aa+cuqrjLAoqIWCxYKTtYrURbA2kxam7J1JVp/ZnNZCWDxUdLrKPMl5s6HfVWVARblFuFUzhHzb7kPPlc+AL00T2yxCmA4gqcseViWVJ95IYDliM+N3GThFD9t/hxFvjtT8rZFAZg09iK9KafvgOUCLO4hAWyBnRfj9ImGNoA1a9asr5D07/Thb/Dv9Z+ZUXYjbR9u523Nhy1C9yh1v5O3nPel3F9afMzXvSAQ2ELkdQAL0BbV1ZKhywutGQCof/Zbn6m1+bXqMXg5ACeQqjHfgftT3ALcr3BGawnMod5JFjGefrBgjaf0Q9tBAvVJYLmqQhEfnFYlC5MU2Uq29GQ56CWp/lQeamhUf65rT/hlq5PCagErvuAMfPf2XdmKushXGWAxXtPj7XH9DF0DdrIUnZTyaLxMMkwdE4hbWFWGZ5111mYU1lv8PyLIAuIAlq8v2UzW9f4krLREANVdPvxS+Sjw0uN6zjnnSJ7vwX2FsBRqZeI+iQBWzkc/VW8awDqW+GVlGkVuAi7aFn2L8iOz6+QXkLbA9EC0Ju2c5BlnnPEU9f426doe2x8Q9xr8OC3hYnkaaNFbzpRN26IUj20AizgBrLWU0fwaT3qUxmXFPQH3A9y1uDNxAqE3yhchXzePAM1zx2LG9zcArPGVf2g9SKAWCdh/omHSN0tHst4lRNyfjOzBdU8Allfm2uY0i0Ap1gEDUpBTYt8BsnL9BFiyzuhwsSN40uKvJ3dZnVoIRbaTCLkWUEi/DyRug8BOS4GnL6QAcy1YbClJgc6grghcPF28fIjyAljTfH1lCwpgqZwjQI0Ou6/GvWwsptrWL3L6LO7NyHKPL1/J4z4xGfwor6CfP9MtD23OI6xvyF1vcSX8R8jzHNwdlC/cViSfWcduzOsfdQnk3YM7HhenRVxEYDaekBNOBViMtQCW7unxpsdg4FCcQOWvkMs/eoZWJkCoA9y8hdmIbcIAsPwoBS9IYJAl4P8TTYr8qIx+LCF+eUZandE9AVif+tSnBIgmsbBWAlgoCAGskQcffLAFsBCl+vplwUpuv0hJr8tRnvqsQ6TUySsSwNJTfBYJeOUCLNIFcmTlNHChy8oEbw4oYYWSIi8kxmACmfT9pwjg+77fTrwUuKwqApX9JPFyNpaON+c1Cu8CHtNjf779POVHhv+ZVy6RZmDnW4n4rEsnJ2T046wMsfibCR8bu1ZQ4xKB2URa1mUqwCLzfrhVWYX6GC+A9RLcRGR/E2dIv0D4o4Tf6OeSY4VrZ8HiQvfYuFMj9inHXQqBgSCBAZeAFhmUlBSWnvDSaAmRP01LqDMOPh5FKemjirNxAha1EIdbzQJUxgIQtQk/T8HPyObNmwVY4tafvgEseHgSHmQ9ckR4AQFZb7JoKwlJQFgEsGTBGs2qUPEon8VYbvTRoK4AFvWsZEtP23pS5Pfmtak0LF3KNxsna0ucbuDiFJwpxXhaT8PMzd008MkSjbhxWjH2JXod0n8+47eW7dL7OHdYorjLYoaMfypZ4B/I92ra+UyJ/A+R54REPsn7zkRc7mVyjsYya05pbo0rwd+9yMPxMHPmzFu51sWfJ5kC9K/VHCe9ERasALCSIxSugwQGVwJ3wPoLkuzr6RsF8QwWneXJtLqvWQTNyqLzErUBLM6ZzBGv1C8rXRUSWBElAUvfABY8J60DC+HnCcdV+o9AYdKCtZis96Vnd7FSgrkWLBSP6hCZRWXsquIvSmyVABYk60YZ0qFrjd3dicy/8NcCX40kwOQTUtj4GrOV9EH31396BV+W5/eS/2C2hGVtKiTA3/VkOrww41gGgeXF8EUT0XapAFYlCxbl3RxN1KMWNKe6mi+qpFuCL527Eu3RGbSxYPsvLwDwwXe3S9gIC5Yh63ZOQ0yQQJDAoElAAOsIFuiWByfA1TOJ172+HNdrkilfJIBVJ3VkwWJhdosxoCAJWPoGsFB8Ul6TY/+lVgiwyJ/kV2AmT2luJj0XYJF+JG4dil78dEzz58834FwWGAlg7eZTAb9ONPpdf+3AcyKtEZeAKweEmUf6uKVA+ktxP6nCHOXuQubfrlKmbF7mlgDWqJ2H8/e+3lbMmytt1fs5Ool6piYSZcHS3BpXQn6yyF2DOyWPEf8hWn0Tbn5evn6lBYDVL0mHdoIEei+B22liCmAiedB9iZrmKXy5/F4Sb7lpwRf1BGDxxlAlCxZ9dgALi0sSsAhg9UVxsNg7QMOTtW0TFgGsLfCW5LfoLEzhFiF1vhZ3Lcq0o4PhlHWkv5oisA1XBOjGCoxZY5Z75WdxI4ABAbWXMkYCLU2l1WKMMdTbl5LfKPz+W1OYhSf3QMM9b9bJBfCmM2+rqvBoc5QzaTZHrXhTtgh1BOKtuB8bYzm+tpwjCxag8bycvD1NCgCrp+INlQcJ9FUCAlg6G3NcotUlup4zZ85DifjaL/1bbgJBtQIsFImzcvANpEpnsLBAOICFUkwCln5bsPStJ1NeZQCW+HOEUpHlRNaiPKUpgJUJePiblJNJPxk5fgm/DnqSuqw/RfXJgnVPWib69lMOLF+XltaEOCwnBujPA4T8b3j6MWevljWBN/HA/HYPNNzzBrAExAUIH5dflhhL9xCg/0xMlNGc6suDSKLdbi4FsAQ0HSGLN1m4334AWP2WeGgvSKBHEkBZSQE/jDsp0cQRXD+UtCAk8tR5qafqWgEW9WmLcOeZZ565pSKj7gwWiigCWMhJ656uq9ZVsemx7GYdwJ+Nk3VB1pC8M1jiKwJYWO0EyESZAIv6pAQn0bcpypgk+v8R4u7hi9lfSaZ1eK0v9mcCukSdmQArka9xl8hV1j4d5D8G93PG4m0+rhG8Tp8+3QEseHIAC3+RGAPMVwJYNkd5EEkCrFHqHDSApbcwteaN+PvhaIXHgwLAGg+phzaDBHongeupOnnQ/UTiftW7Jttq7hXA2lBVuaEQnQULDmUFMrJwXwAWjbozS4CcWZdeeqksUTrnkgmWSGsBWJTbjzht8eYpTVmwRG2gByWzP/Gvx3067eOTKtQByeKRVMZt1dC2dMwhjFveAf22cg2LeIG+gE5f3mwfW20Kf2effbbGQWeOHMDCdwALi1beXGljH0DmLFiao5ZIXXoY0HyyuWVJTfe11h2vuQcJXE0eL4YDwBovyYd2gwR6I4HvU+2LLrnkkvmq3h+sPpHgjbruE9UOsFjstUVYaXtQfeXtQwewUPCyWBmZdagvAAuQ55QXPMzaunWrKUI7q2Y8xf0WgEXfDWDlgTJTgm0Ai4oFrnZzvubL8Ua6DKu9SBln1UXfDyRNgNJ92ykrX5PjUdRr9QX0BvOouRS3YG2C50pzG0AWzVHrpz/wrv9DHCgLFvfZTfRhNqDxEADj8YS7OnNo8ujEDwCrE6mFMkECzZXAV2BtD2cp/kQsrlu37h14WmzqVK6qOo9qB1g0pi3CykqOQ/cOYKEkxg1gAfKc8oKHWSz+ThEyHqUBFv12AIt6MrcVTQlS72jKwJxM3G0FfwmTUiw3SgArDcy1FIJn98IF/CXfIGzJFy66koDmktuSR86aXyur1oaFLpqjVhZA7uYSc3agABagXhYsnUUVuJJLPf+nPL2mALB6LeFQf5BAHyXAk6sW10/jPkz4BSy4Hyb8JQ7m3tkvNliQ9S0s/TGrthjqIgGsyhasgw8+2J3BgqdxA1jw7axL8DDLK0At/nkAS6DQrGySnwDWesZzuy4yyLVB/WmgRy893JJRrtNoKeRCCxZ9FsDawycaHui0oVCuUAIRwCLnsbhlhSUSGQ499NBojloS1h+bSy7N4pvu89c52h7VQ94JuJNwDnDh950CwOq7yEODQQI9l8CFtKCDub/ALcCdi+snaXGbyhbD3Bob7Qhg+TNHO+DDzl2JJQMvlbZROu0LwGg3ZWUFmI2TpUFbOHlKS3wZj3ojTAArb3tQh5qdlSEJsLgWyD0GoHMbfp0k/k0BZ9ZL+4eS+EgfX7DI5GWIE+6ib8f6sRaguLlqX/19soU6ItCM9dFZsIgbKAuW7/t/4r8GdyLu5z6u714AWH0XeWgwSKC3EkB5b+FzBi+jlXfjTua6ryZylLkAlkhgoi7SGawNHVbW8mV0Dr7aNlpfAJbn2f4uR1s4edYr/c1HC8AifyHAok8OsKEMrW+uWc7iqex04uveoitlwaJtWbDqbtv1LfxEEtCD1HweaGQ5nsf8+XGUUi3Q8umN2H2S9zBQrYX+5f53mpIFazL9+Fn/mm1tqeWLz61J4SpIIEhgUCVwzjnnrIP3vxkP/lnQHmN7QUBBB5xvr4mHjixYvu2WP08GbDjrEGc1+vlkrjcJZR0oBFjkEcCKb2kWAiz6smnHDhnqWq1KbEUepEjooTGvtl/JrgXMZdQsgFX39mRGU3tttCw0eohaxT33br7d9b0OJWEPAa4494mzUJp1tMM6x6vYl2j4ctxdHI+4mW+tjQsfAWCNi9hDo0ECwyuB2bNnr/T/B9ZiweJjl8cCvK7iQO0bOngra1+UR6cWrK0oizhgcQALICgg0y8yi48Alln4stoWX9EWIeH5uIezMiv+kEMO2bJs2TIFW7btkPfBiuTA8oPyaySdE4vLNKtqfSLiW1mJIb57CWChFng/vPuaRmyOuqq4ZxyABqT380Gkhm64719tRC5af3azboS3CGuRaqgkSCBIYNwl4M/brIaRFoCFsr+YuJdv27btbR0wqS3CyofcfTsCA21nsAB64wWwcrcI4VV8TUFB2AOwzm5JiWaSP0MjS12LVYlrAazNWDTXZhbuIIF6ywKsOeTtFBh3wFko0oUENMc01xzF5tIgbhGOcP9swbmXXKxP/fbDGax+Szy0FySwd0jgMZ6AWwAW3dbbbDq0/ZtVRMAiOYX8OkfUqaJOggFnHTr99NP7ufiadeAAFFcZgDXCV7rNQlQIsLw8pQhbLFjITFuED9FmrU/x1JuUqWfhaY9xk37Rm5OdjtvTlYVQPySgYwXaijeyudTPBxFreyj8ALCGYhhDJ4IEGicBbYNFAIsvmOv8kZS9LFt6lbwKuYUekCCQ0gklwYAA1pa6QUcBY+Jd8pAcymwR6iOptk2o72eV6bu+6G1K0diRBavu7UHVLXA6jfYyP8WBhVB9FeVa38ayhN8GSEAW4rnGB2Mra+hTAOXdFhf8ahIIAKuavELuIIEggXISaAFYTz311JG+2BfwD2PRTgKBzFo5wO22vVjwOz0LIjBg1iC14wBWZoO9SRBAMgveAwVNOIsBW6ozvBVIsioDUmTBatki5LonAAvAJ9A6csUVV8S3XhUVEV+t17auXnYIFqxIKo0OyIIVASzCmncDuT3YFCkHgNWUkQh8BAkMlwT0ynhkwSJ8FG4PB8uvwZ+AfzR+KYpZZTpd7AUGIiBAfeMBsFbCg52puj+v4wASB7A8nw6IEi5jwWrbIqQdt0WY114nafDjANbGjRvjwLWlKsbYASzyBoDVIplmXjDvBLDiW4QC650+1DSzk33mKgCsPgs8NBcksJdIQBasxd4Coy4LUD0wc+bMG/AxzuwuvU2IgnYgg3LdAKw4EBgPgGWgag+v0T9OX/LIzrzMwHpXZZut5dMJ/n8o9V0kgd1aiTodwIK/uFxb2mCMHcDiNf8AsFok08wL7rOkBUsAq9N7rpmd7DNXAWD1WeChuSCBvUQCAlgTJ0+evND3VxasZWeccYYU8z24E3x8oTdkAEtv+uUeOCc9Alj03b3VhTWosgWLT2U42VPHE4VCrpiBOh3A4pxYJsCiSsc7r/kHgFVRvuOUXWewpl5++eU2pnqwCRasLgYjAKwuhBeKBgkECWRKwB3kRrnafxIKUN3mc38b/61Ytz6L+8xll12mJ+U86taClXYGq9+KwyxY/5bXUaUZwALEzEB+zoKFNagMwFKfTFYjgDIHsPBrB1jU6QAWvinjtm7RD2fBIqHM+bG28iGivxJgvGTBGmHb185h6b7s933S3073uLUAsHos4FB9kMBeKgEHsAAJB/AXHvqa9/64n3pZ/C98vdkm0PXeLVu2/LaPz/IMNHS6XSEwEJ3BItz3LUKApOTx+3x54d1ZnbR4ttQiCxZx9l2iMiBF8jFZaR/WASz82gEWdTqARXtxuVoXnM/YC2DtYks0KOkWyTTzAoC12nO2wPsCWJ3ec83sZJ+5skOXfW42NBckECQw5BJYRf9243TQ/Wic/sfl57gRwMZ9eAJXCt+EIv4tgl/UdQYZaDDgkZEtM1pgIG5p6TvAEmf09QuZHMYSRkf/X3tnAm9HUab9mz0hewiEsJkFEogoYXdBxWXcxtHxU9FRB5fxMzoqI9GQEAgIBMLioDI6YxzHZfRzYXSYRQVUREVABAQUQtgviyQECElIyJ58/6fpcz333LN0n+4+p/ucp36/OtWnuuqtt57qrnr6rerq0c+yGati9mDQ2wU+2ok9igVLU3ElQqb8wUCJvNQJFiRwM9Y1kbhyXFVmn5MFC903ENadEu3L4IO2IkBbPi4FaK8poSK67/Ryhl2TCNiC1SRwzmYEjEBtBCATOzi7igH2MMJP4b9BnNZ4VLrbiGj0mQ919JvIL8IW2zFg5IJgRVX8E5/4xDbSiliJvASEadu2bVEIlvAtTe9ooJQFa/OCBQtStyBBrgILFmXUJFjoL929/goQiuD4xFVAsNBV1mY5WbBSv3YCyV3yY4LVJQ3tahqBNiBwHWWejJ+Ev6BG+Zoq1F5N9ZwIVpKpimprsJq1htXTM5VzkBZZfKTfHpAUrcHaCrkU6arryKc1NBPIE2z+SSiClbr1SkpgUQsIFmXUJFgk0xRhlKlNibRrMwLhCyjraVN9L1Mu6X33nJQu/jXB6uLGd9WNQMYIXB7KPwWCUFrk3a9ISIEI1hTO11vLk6ijZ8AQGSiX35Ypwn4Vb/wnIFgkkxUoKkmRBWvIRRddJLzkRLCeDI5S/sGi1tCCRZEiWLZgpYx9xuI0JWgLVkogm2ClBKTFGAEj0B8BFjd/n/U/YyBPX+x/5s//ID8iWD2s6Tngz7EDjhJNVUDiAoJFWYFlB+mSl1sLVlj7EsGSBSvK9KC+8SgLVs/27dsnhDIys2AhX1ZBldnIgmWCFTZGQQIRLK2blNN9ksRyHAjp5h8TrG5ufdfdCGSIgKa6Gq3/gVgFm2AyUJc69WoapWHBKv+sS9EsWJEIFlsmBASLvalK67AyI1iQZq2x20Eb1yNYXoNV7WrOd1wv6pWm7MfQvpvyrW6+tTPBynf7WDsj0NEIsFg6WFjLG0xT6lQ0EcFCbmBtKfusSxEIlqxu0lMWrEhThAyGmiKUK1mw9BZhJmuwglJYQG8LVohE5wSayp9x2WWXDSHUx7xNsBK0rQlWAvCc1QgYgWQIMI2oKSTtSVBa91FNYCKCBfEI1gshWAOGpgm1/UHeB47YU4SQ1cCCRd36LFgcZ0qwkF/PgqU1WJHIYbVGd1xbEBDB2vvee+/dOyzdU4QJmsEEKwF4zmoEjEAyBBig9cacrFiZWbAgVQHBYjpyFJueDqMsPZ0XZQ1W3EXuVK1nQmiBmETdMyVYyG9EsLwGSy1SHBe8jMI082FSmfsz7w8iuUbWBCvXzWPljEBXIJApwSp91gULj8iApt3kikKwIi9yZ12UtnJQvSasWLFiT0LGx2wtWJRRlWCFlsLxlG+CBUgFcgHBov1eIJ0JTbASNJ4JVgLwnNUIGIFUECh/NbyawERThKzvKg3yWptUNIIVx4Il7NYxKE6EVO6lPxCcJxVm5GQZ7CNYIlWQvOX4l2MpVPwQ4krYZ6SCxaaJAFP2jyNP7Xp4KNdThAkANsFKAJ6zGgEjkAoC6tTrThFCFJJ09GtCLfdmmlCvnot4FMaCha6R3iIM66h1WCKSWuCuT9lkOkVIEX37i5177rkv5/+H8d8aNmyY1l/JeQ3WczgU4pdrTVP2smK9SAoPHTpU96ZdkwiYYDUJnLMZASOQGgKyYNUlWJxPQrDWkn8nfm+mCQPLTsbEg6ISOxFAWYFiW7DIM5H6BfUcMWJE1gRLOgaOMl8XHu7DXlyaouzBkmYLVghKgQJ9K3SW9GUtlglWgoYzwUoAnrMaASOQCgLqxKdoiqlSGtNN6qNkdWqaYCFjF/lFNPbmCb30GRCRujw7ESxNjY4Bl9gWLOopgrVj0aJFpa0bsqhrvylCCtDCaH3Uezh+Ll4WNBMsAVEgx7Vza6juU9w7DT/RVKCqtVxVE6yWQ+4CjYARKEeADl0Ea/gFF1ygqa1+jp3gSxaSpglWKFDThLKSaTuI7aw10VRanp0I1t5SEHziECwRqomQMhGsJ8mrKZ+sXDWC9YOwsGMVMsVkgpUV+hnJ5dq5JRStBxu7BAiYYCUAz1mNgBFIjgAkILAmbd26dcA0Id+8kxUnjbeZROKOZPA4kHB1xsRDKid1IlilBflx1jGJOE7Ei2BlOT2I+GAxdECAsXSonabjf4oXGT4Or08gxdFdWezaj8AvQxX61te1X6ViamCCVcx2s9ZGoGMQgOz0LUKvrBRTTAHBIj6pBevzyDgSfyo+a+JBEYmdCFbg4kwRgqXqJnIVWLCek5DZr3bIL1kY54Sl/IFwJV4WrN0zZ840wQqBKUoAWd7I2rkT0PelRdE5r3qaYOW1ZayXEegSBFh4/pSqCjkIFkaXVxtykQrBYtD4CXJfgf8B5XytvIycHvcRLPSLTFLAS5Y6kStZA7Mmkn1ThGCqfZN2jxs37i5CESy5R0888US9XGBXMATOPPPMX3HPXF8wtXOn7tDcaWSFjIAR6CoE5syZ8zQbY2qt0OQqFU+FYEkuA8ZvCd5RpYzcRUFYNkGWAr2YZouzBkvWQD04z8bfGQjI7kdWxbESj65HE6ycP3/+ZvbAWhnq3qtzdkagWxGwBatbW971NgI5QSC0cqxlUM7MgpWTqkZWAyxkiQpc6RuDpf/1QqZ2SvmmQtIytWCF8iejq97+fAk+sHjw/9pQR1nS7IxA1yJggtW1Te+KG4FcIaBpwkwtWLmqbWNlHi0lCT+IXfpbN4T0lNazyaqUKcFCEZU1EovVoYQvoOxfhcr9JgwvC0MHRqArETDB6spmd6WNQO4QeBKNBliwiEttijB3Na6v0GOl0xCXyFstjBw5snx/rz6SVpKVclgic59C7mbK/i/JZypW+44Ngxh+Rv/tjEC3ImCC1a0t73obgXwhUM+CtZ1Bu6s2PGy2vgsWLNhU1qy3lR2nflhmLfsgwn+wcOHCvrVi6L8jDjFMXTkLNAI5QMAEKweNYBWMgBHo0edstH9TpZMFS4upu9HpkyVfaqLiAdHBgvRIE3kjZ2HxfcmCpTz/EjmjExqBLkHAbxF2SUO7mkYg5whoB/IJlTqyjqhrCRZWoIMr8Yj4/2isRwdnbUE6+OCDn+TtT23JcC266g1NOyNgBMoQMMEqA8OHRsAItAcByMDTkKlqFixtA9CtFqymGgOycw8Z5TN14dufWuBuZwSMQBUEPEVYBRRHGQEj0HIEqlqw0GI8XufsjIARMAKFQsAEq1DNZWWNQMciIBK1B9aX4RU11LShCVYFKP5rBIxA/hEwwcp/G1lDI9DxCDA9qI8Uy4lQlTtZsNaXR/jYCBgBI1AEBEywitBK1tEIdD4CJStVJcHS/9K5zkfBNTQCRqBjEDDB6pimdEWMQHER4BMvgQWLsHKhu9dgFbdZrbkR6GoETLC6uvldeSOQDwQgVoGViqnCARYs3jC0BSsfzWQtjIARiIGACVYMsJzUCBiBbBAYNmxYiWD1WbAgW/qI8HhCr8HKBnZLNQJGIEMETLAyBNeijYARiIbAqaeeqr2uduL7LFgXXXSRNhkdgrcFCxDsjIARKBYCJljFai9rawQ6EoFw13ERqT6CtW3btsmqLOee6MhKu1JGwAh0NAImWB3dvK6cESgUAlroXj5FuLe0Z4rQBKtQzWhljYAREAImWL4OjIARyAsC/SxYu3bt2itUrPyjwnnR1XoYASNgBOoiYIJVFx6fNAJGoIUIiGD1WbA4DixYU6dOfaqFOrgoI2AEjEAqCJhgpQKjhRgBI5ACAv2mCJEngrV23rx521OQbRFGwAgYgZYiYILVUrhdmBEwAnUQeJxz+5Sd1xSh11+VAeJDI2AEioOACVZx2sqaGoFOR+BPVHDfskrKguX1V2WA+NAIGIHiIGCCVZy2sqZGoNMReIwKTvrMZz4zMqyoLVid3uKunxHoYARMsDq4cV01I1AwBESweoYMGTI11NsWrII1oNU1AkbgzwiYYP0ZCx8ZASPQXgQCgsW+V/uHaohgeQ1We9vEpRsBI9AkAiZYTQLnbEbACKSOwANI3AnBmoPXdwg1Reg1WKnDbIFGwAi0AgETrFag7DKMgBFoiABrr7aQ6C7I1dwLL7xwHMfD/ZmchrA5gREwAjlFwAQrpw1jtYxAlyJwO/U+fMuWLQeo/hCsR7sUB1fbCBiBgiNgglXwBrT6RqDDELiN+rwQYjVd9Ro8ePDDHVY/V8cIGIEuQcAEq0sa2tU0AkVAAGIlC9ZopglfSbhj1qxZwcL3IuhuHY2AETAC5QiYYJWj4WMjYATaisCwYcN+jwK78e/GP3riiSfubKtCLtwIGAEj0CQCJlhNAudsRsAIpI/A4sWL9WHnm/BT8LJm2RkBI2AEComACVYhm81KG4GORuBfVTumC/+3o2vpyhkBI9DRCGivGTsjYASMgBEwAkbACMRCgK1V/pMMr8P/An87D0WPsH7yLI4v59zHCLvaDe3q2rvyRsAIGAEjYASMQGwEli1bNnHr1q1vhVR95KyzzlpeEgCxegHHb4JofZxzWk/Ztc5ThF3b9K64ETACRsAIGIHmENi2bdvRyslWKr+skCBr1vPOPvvs0jdFK053z18TrO5pa9fUCBgBI5ALBLByHI1/FVYOL1PJRYvEV4K2O4pcz+zcufPe8txDhw69Rf+xXh1RHt+NxyZY3djqrrMRMAJGoE0IYNl4C0XrTdGrOf6aSVabGiJ5sQcj4m6I8q5yUaeffvrD/H8aP7c8vhuPTbC6sdVdZyNgBIxAGxBgMB4MofosRV+FheODhO+HZH2gDaq4yOQIPA8RD1WKCddd3U07H1R5rtv+m2B1W4u7vkbACBiBNiHA4PtKij6IdTvnsjD66xx/G38RxGtSm1Rysc0jIILVWyP7/cTPrHGua6JNsLqmqV1RI2AEjEB7EcCq8WY0eGTJkiXXh5osINwD4vWJ9mrm0uMgIEsk6Q+k3QZYsEI5DxCaYMUB1WmNgBEwAkbACDSDQLjW6k3k/XE4jdTDQL2a///GuZMvvvji0c3IdZ62ILAPpQ7H91YrnfaVBWvfSy65ZFS1890SZwtWt7S062kEjIARaCMCrLWaTfEzGHx/VKHGP/J/wqZNm/62It5/84vANKkGMa5qwSJeBKtnw4YN0xV2qzPB6taWd72NgBEwAq1FQNarzWPHjtU+SX0OK1Yvf0S6PtAX6YNcIwBJ1vqrnpEjR1YlWJzSFKG2aujqaUITLF0FdkbACBgBI5A1AiJYV8+fP39zZUEMxD8g7ljIlqae7PKPwDRUXLdo0aL11VTlBYZVxG/GkmWCVQ0gxxkBI2AEjIARSAMBfVYFOcdXmR4MxDMQXxWW8/I0yrOMbBGgvfajhEdqlUI77+ZcL34avmudLVhd2/SuuBEwAkagNQjwzbrXUdIQBuYfVysRy9Ua4jXddEy1847LHQKyNMpKVc89ykkRsa51Jlhd2/SuuBEwAkagZQhoevA2iJQG3VpOu7sH37erlcDxuUFABOvxBtqorfdvkKajT5tgdXTzunJGwAgYgfYicNlllw1Bg9fjf9JAkxWcP7RBGp/OBwIiWNpio577EydNsOoh5HNGwAgYASNgBJpFYOXKlUeSd092b7+yngzW7azk/BSsXBPqpfO5XCDQkGDRnrJgTQ0Jdi6UbrUStmC1GnGXZwSMgBHoIgR27dql9VfPTJky5bf1qh0SrB6I2Ox66XyuvQhAgMeggTaFbWTBEsEasmLFiint1bh9pZtgtQ97l2wEjIAR6AYERLB+Pm/evO31Kjtq1Kh7dJ6F8IfUS+dz7UVgyJAhJcJUl2CFFiwp27XThCZY7b1WXboRMAJGoGMRuOCCC8ZTuRcz2Ja2YahZ1wULFmzi5CMmWDUhysUJ2kfTg3J1CRaWS63BkjPBeg4H/xoBI2AEjIARSAeBLVu2vBJJ2p6hIcEKS9Q6LE8RpgN/JlKiEiw2G30KBbbiTbAyaQkLNQJGwAgYgW5G4GVUvpd1O70RQdA04ayIaZ2sPQjIgrUdAvV0veKxWmqzUa3D6tq9sDxFWO8K8TkjYASMgBFIgsDxZL4uqgAGZX0keAZWkkFR8zhdaxEILVirQwLVqPCu3gvLBKvR5eHzRsAIGAEjEBuBiy++WG+aaYuG30TNzOAtgjXq7LPPnho1j9O1HAEtctfO+1FcV++FZYIV5RJxGiNgBIyAEYiFwLPPPnssGYbiIxMstmgQwZKb8Vzg3xwisDc6NdrFvaS2LVglJBwaASNgBIyAEUgJAU0PrsNrh/ZIjjfPHlRCpp9mRsrgRO1AQAQrkgWLdgwIVrdO+dqC1Y7L02UaASNgBDocAQbVl1LF61jgvitqVUn7LGlXkdcEKyporU8Xx4L1GOoNX7Zs2aTWq9n+Ek2w2t8G1sAIGAEj0FEIhJ9HeQmVijw9WAaApglNsMoAydlh5DVYWLACS9e2bdv2ylkdWqKOCVZLYHYhRsAIGIHuQYDPo7yA2o7FN0uwvAYrh5cLFsY9UEufyok0RciU7xOqBmvrTLAEhJ0RMAJGwAgYgYQIaP3VNvzNTch5gDy2YDUBXNZZhg4dWiJKkQjW8OHDA4IF0Srly1rFXMm3BStXzWFljIARMAIdgYAI1s1YPLbErQ3TSpoi3OvCCy+UBcwuRwhAlLT+ShapSG8RMjWozUh30qYmWDlqR6tiBIyAETACBUQgfGNMBKuZ6UF97DnYqmHz5s22YuWs/WmbgGDxwedIFqzwBYenyC5GWsgAAEAASURBVJcJwdJea5Txj+yb9jc5gypQxxasPLaKdTICRsAIFBSB884770BU3w+rRVMEi2kl74WV07aHKGmBe8/kyZOfjKGipgknx0gfOemmTZvOIvF89PrOueeee2jkjC1KaILVIqBdjBEwAkagGxDYuXOnrFc9w4YNu76Z+p522mkavDdC0GzBagbAbPPIgrV23rx522MUs56042Okj5T0kksuGUXCj+Avwa/mutNxrpwJVq6aw8oYASNgBIqNANaEF1GDuxcvXvxUMzWBWOkjwfcjxwSrGQCzzSOCFWl6sEyNDRyPK/ufyuGGDRvegKCxTFd+hfBy/Ju4ZnL1DUsTrFSa2kKMgBEwAkYgROA4whsTouG9sBICmFF2EazHY8rOxIKFDq/B37tkyZK7Ca/Ez2At1vMIc+NMsHLTFFbECBgBI1BsBFhwPJIazMWnQbBmFBuNjtQ+8iajZbWXBSv1KUJknoC/Bt/Dur0bFGL9FLnPjTPByk1TWBEjYASMQLER4PX9I6jBMMKkBEt7YT1v+fLlw4qNSMdp38wUoSxYqU4RQuT3QeahEKpfCmGmo7WQ/gGmCE2wBIidETACRsAIdBYC7JOkAW7LlClT/pCkZgycmiIcsmbNGr2RaJcfBGITLNoydQsWMl8hSCBUvyqDRqTeBKsMEB8aASNgBIxA5yCgAe73Md8yG1B7Bs5gqwbeDPNC9wHotCcCq5FmvPaC3MRag0Vbpm7BQuYJ6HIPOulj0oFDLxGso4gbHka1PfAUYdubwAoYASNgBDoGARGspNODAuNh/E78DP2xaz8CrHOaiBZDIDfB529iaCQL1qiUp3tPQGaw/qqkBwRLn2UagT+kFNfu0ASr3S3g8o2AETACHYDA+eefr926p4eWhEQ1wgqxAwEP4W3BSoRkepn57I0Iltza54LIvyJYPU899VQq67C4NrT+6hCus/LpQS10vyPU6IVh2PbABKvtTWAFjIARMALFR4ABOFj/goUjDQuWANE0oQlWTi4NXlwI3gQk1JRfZAcRCtJzfaT1JuHLVTjXWT+CtWjRIpXTizfBAgQ7I2AEjEAfAppCYB+bU3hC1UJau+IhcAwqP3HWWWfJ8pSGM8FKA8WUZEBoJkgUhGldHJGkDyxY5EnFgoWcE/D30k/0rb/if8n9gQMTrBIaDo2AETACQmDVqlVvoRO/hMP/NCKFROAItL6VAXV3StqLYM3gmhiUkjyLSYAA7RBYoHjxIJYFizdLg/QlC1gCFUpZ9QZhP+tV6QShCVYZGD40AkbACJQQeGt48OJwPU8p3mExEAgIVoqqai+sMVg1tbbLrv0IBBYs1ChZpKJqFKSHoCW2YIX9whwKrkqwIPciWFPz0n94DVbUS8TpjEAXIyArAib5dzHYvSFDGGYj+0f4wazXeHWG5Vh0yghwbUxG5P4McLemJRqLhyxYPYReh5UWqMnkiGA9Q1vrBYTIbty4cYEFq2QBi5yxSsLt27cH66+GDh1alWBRxh+Vjf7jBVWytzzKBKvlkLtAI1A8BCBWC9D6u3RgP6SDzarfmMkAfT3l9OK1nseuIAjQbrJeaeFxagRrxIgRsmD1MMVkgiUg2u80RRiQpTiqnHLKKVtIL1KW2ILF9aXpwQfPOOOMR2rocB/xKu+FNc63NDqrjrKllXBhRsAIZIfA0qVLD0D6Ofgb8KOwKByVdmmQtknInEAHKqvFTfij0y7D8rJDgHYTwdqI1wCXilu4cOEzCFqDn5GKQAtJioAsWLEWuKtAyLfW5K0nDNZwKS6BE8H6Za38oXXtTs6bYNUCyfFGwAjkB4EdO3Z8Am30VPjX0orBNIuN/A6UbFwv/g78oXi74iAggnU7A9yulFWWFcsWrJRBbVJcUxassKwN9BuJCFb4EPYCiFrV6cGyOmkdlglWGSA+NAJGIIcIXHjhhWNR68P45XRwsiasxe+PT9tp88Ae1lasIrgHv9eyZcsmKs6uEAiIYP0+A01l0TTBygDYJkQ2ZcEKy9FC93FNlNmXBWL1Mv4MgqhFIVjPp78a2pe5TQeeImwT8C7WCBQBgS1btnwQPUfj/ynU91E6OE0Zpu0CgsWC2DVMQd4t4Vu3bp2ddiGWlz4Cl1566QikHoyX5SBtZ4KVNqLNy0tiwdJ0rx7Wmnb0O5oefBji1NtAiCzgI/Ftn1o2wWrQUj5tBLoVgcsuu0zfHfsk9f8+ndqjIQ5aXJqVBevpk08+eeuoUaNkwZKb9Vzg3zwjsHbtWlmY4MXPEeOUdRXB2ofrb4+U5VpcfASSWLASEyzUFcFqZL1SrUrrAE2whIadETAC+UNgxYoV70OrafhLyrT7E8f7lf1P63AKglZL2IIFCzYRiNDZgiVAcu6YugnaaciQISVinKbGwZuECGz7YJlmpQoqq20WLAj2GDCbi/91I+zmzJmjh8DtXJdtn1q2BatRa/m8EehCBMK1V+dR9e/RuZWvrXmSuD0zgERThI+XydU0oQlWGSA5PpSlccPixYu1Ri9VN2zYMFmw9CZa2wfLVCtWTGHttGAdCWTiK79rBN2JJ564kzS9WN/bfs2YYDVqLZ83Al2IwObNmxdS7QksOl9UXn0GOhGsyeVxKR1L5hNlsmQN0boeu5wjwEAmgnUP18butFWFtMmq+WweBsu061YkeeA/CH1lwVrXpN6aIpQVqinHtaV98TbjV0QUIGI+I2LazJKZYGUGrQUbgWIigMVKWyZ8Cn8JG/o9VF4LOtqn+D+aNFpEmqaTVUyyA0eH+iAH08OOPYx1kFMEAoKVhW4hadM0YdsHyyzqVxSZF110kcjRYNpjfZM6i2A1vcidfkAE6/f0Ozsili+CZQtWRLCczAgYgdYhoKnBdSw2v6BKkbJgaTsFEaI0XT+CheBe/Fh2kPdWDWminI2sWQy8Way/KmnrvbBKSLQp5BM1mh6Ua8qCxfWRiGBR7rF4bUAcyVFeYMFq9wOaLViRmsuJjEB3IMAT4mHU9D10UJ8Jd9LuV3HeFAusTGw+mjrBosw+CxYdoyxYctOCX//kEgGuFw28e+OzJFi5sEbksgFapBT3e7BJKPdlUxYs8gUEqxnCE15j06nqLVGrSzm6Zvbgo8/B9i9R86WdzgQrbUQtzwgUG4ElqK8Fol+vVg1IUGDBIkyNYNGBarpxNGX2ESzpEJY/LQwd5BABCHewTo7rITOChWwNltO0bUgOIegWlRJZsABpI34wFulRcQHjGnt+mCfOPmu9yoPl7Xlh3rYEJlhtgd2FGoH8IXDeeedpq4T/w4D2OUjPtmoaMjW4VvGQodQIVtl0Y0DeJP+ss84S2dqELnpytcspAlwHwV5lfJD53gxV1BThsHvuuSeL/dcyVLtzRHMfBhYs3upsyoJFflmwesg/Ni4qXGOyqu+cNGlSsAFxlPwjR44srR3VetK2OROstkHvgo1AvhBgGuAkNNo5fPjwb9fSjN3V1cHuLnW4tdLFiS9NN5amH5UX+bsJZEmbpv926SFwzjnnHAWB/jg+cf8fEqzVyNKnUDJxlCELVg/XSdsXLWdSwWIIDSxYrMtsag0WbRgQLCxKzRKse7QJcVSoFi1apH5qA/1IWy1Ybf9WT1TAnM4ItAsBBo/XUvZ8/NP4r/P/p+3SJcty6QTfhfz/Ou2001TPqo667woH09KUQdV0cSLpBPek7B6sIOVThBLRi5+Gt0sJAdpuFjj/FnHq+0WwLk0oOrM3CMv06uV4F9eJCNYvyuJ92CIEuD9lwdp2yimnbJk/X11hPMfD0zNcd8o0Jl7OILUsWPr8TVz3MHofGDdTmukTP8GkqYxlGYG8IcCagTeg00/wIhSH4K9ikPoafjjHHePCjUXnUqGfR6jUejqu1AgWsoLpxhEjRlQSrAfRJVdThLT7+fgHsAK9OAJOeUxyGkqtxl+B/9sUFMycYIG3pqsf4TqxBSuFBmtShO739aFlObYIyFVgwYJoxbJg0eaDKOwF+GYIlqYJ22rBMsGKfak4Q7cgQMd+IDf496mvBqPjWRd0JB3MBzl+D/7y8CO3HBbfsbGo9plRf3B9hNqsI01qBEsWLOTtCqcf+4onvpc/08JOti++XQdcD2+ibBGU6QwYX8qLXlHxQH9t5vo3+C/hv4c/mresAnLLcWwX1j/rLRpKej3AwYzSH4ctR0D3u+77phzrLAOCxX0Ti2BdcMEFKlfX6MomCn6YPLZgNQGcsxiBTBEIB4/lFLKBBZPvZXDaoac3SNbXCTXQvpqP3H4lUyVaK3wOxW3nO153RyhWHa06vlQcWKsDXQvGwRxCmdBejkdjRWyaBJTJSuNwMUKuxf8l/gj0OjwNoS2UcVJY1lcJg0+OsCZmbrPlh6/Aa8rnnmZlxMindVi2YMUALOWkmiJsaoG79GD9XECw6DtjESweugILFJYvWaNiOcqyBSsWYk5sBFqEAFNAGoxej/9IuGCyr2RI1s+4eecRcRLpXtp3otgHmuq5L/yOV6OapEqwKEwE6qnKQsG4N4ybVnkui/8QvGn4xfgLzz333OnlZYTt/GJ0uph4TaNquuQt5WkKcHwiOl5B/Z6ESOutP32C5ohm9d65c6eumR4Gv1YQLOl7cPjg06zKztc8Anqg0n3frNM2DXr7OBbBIktggcLyFZtgkVcWrAlc7+MI2+I0JWBnBIxAGQLckPvSEXyeqG9z/KOyU32HnP8Wf+7ixl/YF1nsAw2WUaxXqmVLCBbTCr0qDDct+M3wB2vUBxC/Aq9vL34I8qDPchxdKpJ2/jTHK2n3HxO/jeOrOX5l6Xzew6VLl8oScBz+P6RrSKRv57BpgkX9dc3sGj9+/AOSmbHTFNFYthLZN+NyLL46AoksWNwzuxCrbVdiESzS67rV/Rb7Q+LkFcGSC0jac4et/TXBai3eLq0YCCxFze1sV/DJWuqGHcZFnP8rjmfUSlegeE2/BK/DR9C5JQSLtxm159ZWOsqpEXRqOgnk6n2Qha8h4Lt4DeDCQgP6z2nbY7FmzeZY1qp/DNudw2Cq8LhWrsNDx0GUPwk/DT9SSkR1EMa3k3Yrr9n/b1meWzlOSrAeivP6fFnZcQ+DNTjU45C4GZ0+FQQmIEX3fRL3DNdwLIJFepGjR7jeRdBiuTKrlwlWLOSc2AhkhACDqQbXk/DnL168eMC0VXmxo0ePljXgWQjAO8vji3ZM56UHLXVCvRF1T5tgTabcJyvLBtfdxK2mk82MYFH3I5H/Fcr5N6Z+P8T/jXjV73X4O/E/Z1D/H8JH8d/GB45psWs5GLlu3bo+K1d4KtUAXabhP4+/CSIovXRNPoi/G6vUflELo47vIO0VFZ8/EsGajew9osqpSCeyc1dFXFZ/H0DwNupxaFYFWG5dBBJZsELJGwm1Zi+OU7/UzPRgD9Pgq8i7k35EVrC2OFuw2gK7C80rAgymp6PbE+PGjVveSMcFCxZsIs3/0Om/q1HaPJ9nd+Up6DecjihSR0a6lhCsEDN1kvtkiN9CZGvw/nhI6IKiIB0bsPZoDd5V+C0QqncStyU4yQ9Px5pe20j4slJc2iHrviT7Nvx78H9Ev/MJ30H414RjWDh8GmFDVzk9WMpAnf7IMcHg2aW4mKEIVmBZipkvdnKw30EmrcMywYqNXioZJoT3fRJhWugey4JFepGjh5spNJwGf5T+WSStLU6bzdkZASMAArJeQbBO4vDTbKa3OSIo2sbhcgaAWfh7IubJPBm6aGHnOQye3zrzzDNvqVdg6XtddESRCBayRLDGUMZQvAa+pE6L3AdYsEKhqwkzsWChux4wtY7qKxz3kaew3J7Q2iPLzwCneuOv44RI0AUDEiSM4Fo8mGvxR4hR2/01ZW0oF8l/Wd3+L+En8XXbADlvJ23l9KBIYmB9Inw+52XNiuw0NcpbtDMYdFtCsELFpK9InV3rEZAFS/d9EtcMwRI5ujJBoerT2kawbMFK0HLO2lkIxLFelWrONOHPON6Gf30pLiehrB3/wOD5vwzAdR+kGCQDE3rZ97saVSHoaFmjpk43kQt1m4iQWgRLFqxMCBZy1fHuRf1FlGI78mma8KVpf4R4+fLlw7gWL0O26j6AXElRiPMPCPZEh1fofz0HcRZJvLJierAH7EXaNPU5p17+aueYGj2I+MGU32qCZQtWtQbJMC5cZziK62h9wmJiESyuz+GUN5Vr7JEE5cr65SnCBAA6qxFIjEBp7RU38wUxrFc94TThr1HgDYmVSElA2CH+LeI0vaUO6tX1RNNxqgNaX7kdRZ08AcGCBEyokybqqUlKiI5aW1TNiXjJwpW6o8zpEkr9729GOPnV7uNXrlw5t5n8tfKsXr36k5x7If7dIQkakHTJkiW/J/IhdH/bgJNlEexVtRd/j0PXy8uiyw/v5I8sWLEc5QaWJN70bCXBUllT2XwyMbGPVdkuT4ylsoR3cN8ngCMWweLamhKW9ViCMm3BSgCesxqBVBCALJyJoCfGjh2rqZdYjsFLJuwTLrnkklGxMmaUGOvCixA9DiuH1ujoEyOvaVCUCJY6okiO+gYdLXInRMpQP9FknUZmVQsW8U9zOo1yBmiB/gHBmjRpUuS6lwvBOngj/zcR/kV5fJJjfbIIvc5AxpcgVyJRVR247ObEf+H/ivSDqiYikunfl+vckCFDflEjjbamiG3BIo8I1lre9KzabjXKShTN9RxMaW7ZsqUrrFh6iYFrYBn+I20mlcH9B/4ttWBxX+2tC4ZrfU2CC0cWrP0S5E+UdXCi3M5sBDoAATqww6iGLD7nxrFelarOAHcFxyM3bNjwilJcGmG9gbOefDqmV3J+LaEWYv8Gf3y99JxrG8Gi0w6sU7UIFrqtw4/RtFmDOjRzehqZHmt2mwGuG00N/xKfGsGCPGi91Fie3i8mrOvA7Mck2B/rq67fqo5rSNfC/WeccUataRYRrJlxHw6Qezj57giJXtWy047ker4bmSKWXbEOi5cYvkldF+H/ieviQd4ifSfH7XCBlRn8a1mZo+oUy4JFeYEFi/DxqAVUSSeC1Tae07aCqwDhKCPQLgSWUvCD+K82owCv9+vJWjdyauuw6Ezfir+PjRWDTiamXkeR/ncQgF2EIlhHcbxHHRnTOPdQnfP9TjH4i/TIBU+2zx0298tAHViwsCBW7bw5LwtWz6pVq0rTFM0VVD3XAUSr3ZK4n5P5+Ab4RpZPfUXWbqlDiPpkTZw48df82USeN/ZFDjw4gahfDox+LgaCqynCQTwcxH2T8Gjy3VxLbhbxYPwscnWddrwFi/te6w5fBYF9P6EegK6inb9Hn3AW4SD+t8yhQ/AQxNvGVe/RGIqIYI2JkT6wYGFhfiJGnn5JsdxG7tf6ZUzpz+CU5FiMESgkAnTamk57C53ImRzLIhHbhU/xmoIJpmNiC6iSgU70i0TPYIrn76ucbhQ1lwSyXsmJYA1jID0m+FfxE3bW06nDAxWnav6dOXNm6Y22xASLQkSwdrNnTUCkqhSaGpmrIlsdeJLpB4n8EV6Lcd+sP0lc2BavQoZIW0MXWt5+Tr6qZXM9q37Pp22vqSUM64AeDuTmPBc0/g0/EK1rpqUEK9RsJWHHEyzue62bHETb6ssBj/EQ927+n87/z7B9x5tCLFoVBBYsdKp1j0bSg+sllgWL9Hq4XNeshVlK8eLOw5GUyyiRCVZGwFps/hEIB7RlaPoHjr+bUOPryH+41tAklNNDhyrism8oRwQwsiOvOsP98bcpE8RFFor11O94/a90PBGrE9uD85EXeof7y4hkJSZYlKun47W1voEIMQw6dcKJlbqn8H8vZDT9dKzywfs+guvx79P/JI620GJztcfVMeT8gLQvQY9plXkYoF6hOJ7if1l5rvSffCKwj+FVdiS3bdu2o5SQNmkHwRIh7HiCRR2PwD9I+zxJqHVIuyFZ6qt+xT3zKcW1yoX36LPosiVJmcgRwRpDGMkCRzo9ICSZHiy9hJTU8tZ0tU2wmobOGYuOAAOapmNOoPPSB341nda0YxATwRq8efPm45oW8ueMmn6Ruwx/eHAU8Ye6BOnRJ7BghcTlRjqrF9cQMSOMj2zBCtOvQ+b4GjLjRMuCVbMDZBAXAdCbfonJXBWlEhOsUOY3CV/LNVQixVWKihQlC+h2NrnVtRTV/RcJRUJPrcwAZrq+72G68U+V5yr+38b/gDRVxNf6q+tzPdO6kUl5LUFx47m+9cAwA6z3iJu3YOlFsG4t11kki//fwb8stCKWn87yWA9tNe/RGAVvJO3gz372s1HbTg8ba2LIr5W0bVYsE6xaTeL4jkaADlrTOp/D/4aNOH+StLIMNlqAu5ZO8KVJZSFD1gQ9Lf4QPwVdRUKiurkk3II+2vW65G7g4EUMuNWeHAOCxX5eD5YSRwzXkW5CxLT1kqluwVN6tUQs9BV5EMHKpQUr1FlEWNPL7w3/NxuIuPwxzosWXBsbuV7OJd9HOH5NqeCwrd/I/yjX9o2kO7bG9VESWR7qIeJmykv0UFIuMOoxdf0DaeHdgyNb3KLKzku6sB3mUlcR30p3JRGDsSIm7mcqBdf5vyfn1tY5H+kU9ZEFq2fTpk1jI2Xo6UlswQrLMcGKCLiTGYG0EJiPoNn4j3Hj68kwkQsHm9/SOSa2YCHjIJSRRalkVTowqnLkPZy0f0SfHWV5NIW1Jxa7g8viSociWI+H+3mV4qKEaREsWZFqEizO6alXA3kaZA4xz7nwrbnRtP0TpbhmQ7AWFpfj3x8Ojs2KkhXplriZKfML5NG04rfCfa96aGtdB3o9/cf4ug4MRLAm1rg++uUN6/cSInVNtdyxZkwWrF3o8cKWF96iAlngrvt9InW8tbJIpgn1NugqfKylA5VyYv5PxYJFfQKChXU9KsFKy4J1Usz6ppbcFqzUoLSgoiDAa+3T0fVMvD6iqyfitJyeODWwJXUzEaDpl9KTlzrcqE7lB9ODpQws9NQAupuBtNpTrwjWA6W0McK0CNb+lFlzCiskruvQPVULFm/NidjJMpaYYIWYfY3wUEhKUwQ7JHxakB6bYAkj3vA6ifKHYtn4bijrrfzfyBtY14b61QzYkf93OknZDXWnfro2ZXVsC8Girs9S9r2dTLCwPs+ljnLqT/o52kgPg7qfW0mwUrFgYXUMCBb1i0OwHu8HQBN/uGY2NJEtlSwmWKnAaCFFQYCOeRA3+D+h71P4z6SpN52fOsR9S1aEBLIDgsXTqgb/rfhIBIuORNOeGqT7dczhDu03UXdNGVW6dhOsA9D3kUqlKv5rvdeEirhEf+nsA4JFmBbB+gUKiRD/XTOKbdy4URaZIWDx+2byn3766avIeyJ5XwJ51JSwLLT/HuUNLDYLfZq0d4NxlEFb1queESNGaJBvl9MDRBoPMu3Sv265tMMRJHiS+7/qgwft/FvOH5P2J5rqKCULVuIpQqyPAcFC1pg6ZQWn6MvETXSPrmmUNs/nTbDy3DrWLXUEeMX53Qj9Szqpk7mJNf2UmqNjVMffgxWh6c4fGVonJavOI+iop1WRj0gEi3Sz8MOQ8UfCSvffRLyROu9TOhGWdRjlaP1YXLeODIlIz8UXXzwaGZoKaUiwkpZVWTk6+4BgEaZCsMB1F2V8Hf8ujhsOIJX6gMGRxO1An2ptV5m86n8G5GsgjK/kpNpGFqazqyasHinC1NCCRRq9LLEiJGXVJWUcy/X6B4p4YXj9ZlxaW8TPpdRbw/t/gALEi2CN4RNNcwaczCZCBEsPpIkcVtaAYKF/QwsWVtU9KUzfukxswUqkdMLMJlgJAXT24iDApycOoFP+Ehp/h8Ho8rQ1Z0sETettolNommCxzcM4ZOyBfyzUT1aRqAQr6HDpnO4M85YHX+bPZvw1EIDDdCKc7pnI4e/0P6ZLTLBY7HpAWOajDcp+mvPSMzVHGwUEizf2UiFYoWL/Tihy9ca4inJdalC9i7bZEjdveXpe2LgRGSfgX4dfU36uwbEI1uERdnRv2/qrMv1FsLRmTGvMOtEdQaVuq1UxrIeycnLJ7D62VpqU40V2Eluw2EcrIFjo3ZBg8XKLFrirkiZYKTemxRmB1BHQwMFN+30EP0MH9fHUC0BguCXCH+kUNFg25fgkxtQwYznBKhGRRjKfT4LHFy9ePOBpk8FWHeTxeC1+v4X//0J4Ln43T5Y3E8ZyEJTEBIsCZanTPk0tt2DRRiJYG+O8sSdd6zkwfYDzt+LfWi9djXMi5TUH1Rp5UovG8iWCNZTpRQ3uVV34PTyRc01Bts3Rdrer8CQPMm1TvkHB4fYLB1I3XUdV3cKFC0VU7gKHY6omSDEy/ETVOPQZ0KfELYaH2k3k0VrQhgQLS+6UUH6ch4S4KmWe3haszCF2Ae1GgIFvEgPH5egxl4Hk7RlPb9xBOXMS1HnfMG85wYpqwRLBurNW2eCwknPH0cGdQ/gW/LvwX61GyIhv5ESwxiJzaKOEtc6jR0Acx48f33ILFjqJYKVpvSpV8z85+MtLL710RCmiURiupXkheATEoVH6LM5PmTJFVqEt6FBzmhDy/2rSDIYQX5OFDlFlMlCLkGtdXk0yGFVW3tKVlhfQTzUi2zehe+YEi09UTQwxSmzB4trSkoeNtFtDgkW6wII1atQoW7DCBnBgBHKFAIP/SLysVSIW6ozerCmULJWkE1FZh1Busw8vAcFiXyq9ii2nwWQq8oYH/+r/1CVYyoqcZxmgzsNreuV5+L9XfBNOBEtu3HNB/F86WhGsNREWYqusUkcfv6DqOTIhWAyM/01xY9euXfuy6sUOjL377rsPInYUeNw+8GxrYubNm7edkn6PDjUJFuffgL97yZIlD7ZGq+qlhAP17zhbT9fqmfMf+yJUfGb27Nn31FMVDESwXsj9PLJeuqTnuJ51n8ha+GRSWWH+Z5DVkGCRRhasLaeeemqq62RTqkNkMU0/fUYuIWcJWYejQWWAY/pIi4urOp7Yqp7jbbS++Mo0tc4liedi7ysPE2rfcdbxAqWijGHcABoQRlUJRxOvRZHymrsvHY/mWE/15X4n/zdVeJmiZdHQIu8bkHUtnUism0wfSA6/4fdR5EiHb/KB4iURdrQmaTKHvnchYQ/KE3l4qAlpIljrS/tSgcEjyFRbK74XX9XJYsKgfjDpP181QUUk6fQ0+XBFdOS/6LQ+TDyBsNmnW2HUaHpQnXtau8aX1y8TggX5uIO1QRqMXoH/eXmBtY7pEzQ92MPaubYRrFA3LZ5+W3jcL9A1SL1EsP6j34n2/bmBoj8mvcJruX2apFuyiPn1tT4dVSqKeotgDaVf1rWT2UMj44zu0R7Chvep0kVwkSxY1E8WrMeL3rZdR7AgUr0RLoJ+SegA+/2v9qdemlrn4sZzkVcrWhd/pvESXlkGN0BQZlmoiC38F2ESSdKgq/B+vDoDLf7eyvmtZeEQ/ot4lXsRotn4N3JuCeFmCNaPyPNd/l/B8RbiBjjODWJ/qyPR8+OQq3eTQE/kX8d/gTz3DciQUQRE+y61K/4QimiWYJWmB7XIM3hVm45UFqfeWmqvW7duFueE55210qQcX7JgiWA169R5i0zXddRJZG583UTxT4pgNfP2ZN2SNCBwvV1LouPrJux/UoPkY0zVPtE/uuX/NFDPR/998KvLS+fe0oJqXYM/Lo9v47HI4Fk8MB9EeG8b9UitaDDXvfQKrqGzGgllf7PbeaDaTn93DGkzI1jooheDNMD09UmNdGtw/hnOj2mQRqdlwSr0+itVousIFnV+nTpBVb7ScSFVjVe6KHnK05TLYnDsk8sN0XecRnwaMlS/OHJIu5N6bGZx9GbIzGZu9s2f+MQntpXXXzKTOPAbROc5i3L+muN34f8TeU/TCX2N8N/xj0JmpkBkjuL4pTxd/wXhTLwsX2dgDfhqxmutKGqgw7T/8IoVK0Q0D+XsVQNTNIyRpaqvM2NB/p+2bt0qoqX4mg6cnq+TpC8SwZqGyldK73qO9tTHqkfQ9pryrUqw6+WvcU4E6zc1ziWKRt9b0PfTeA6r9zUVBczl/20VcS3/y/18Lfezyn0V/jvlCnB9fYz/j/Cm7DXl8e065jq/UfcF97+2jegIgkU9Po0fznXz/xrhqml17gVZPEWwMnPociDCH6OsHSkVsg45EyPIEsF6PEK6XCfpOoLFhfLTXLdIQZXjhk9V83BgkoXhQnmeoA+lM/0gx/KfwqtzVSCnaTlNx/z91KlTrwnXkyi+5U6mfa4x6S2C1YwTkXqglJFNQtdBHkXYZD2o50SwVrWQVKqjlJvwXBDvF4wGk2Ma7fxgo5zUXRasHgiArFhpEay9KTsri5HI0oTwkydRrJiyYP07vq1Om5XSLlrs/lp8H8Ei7lX8fy/+5EZTV6RpidN1jl5/pLBX4tuOXdJKU5eTkHE61+QZrI/se8BqIPd6zusBlGyRiHwDcVVPi2ClNT2oAjR9PlkHDZymCO9okCb3p7uOYOW+RaxgVQRY2yIStYDtFs585plnXsTxZDqVNax1uqPJt+CqlpNSpHRNQrD6LCvqOOl8NU3YiGAdRJp7UtI/ipgNYaKmCBZkSevkRiCjN0JhAZkjvQhW4qfacL3aOAamTAgWltXbWIqgB4C56FuXYNG2GmzUtiJleXA/Q4l3lwZt9JvG/8vwV+O/jM+T+wnKfAAdB+N35UmxqLpId+7x08H7HPJ8lZdwzodgRc1+BQlP5uHzMEKRzSyclmvogTEtp2UjWj7RyE0hga65QrvBhdbeyncdAtq3iA7oGvx/0Bn9KofkStPJK2mYKJ1Iv/bToEaELFiVT7BRCJaeNB/uJzDDPwwMmjJ4Bt8UwYJ8TJN61LmhBYsp6cCCRSiCldixZUfwBE07ZUKwsASp/fSkLoJV16GDrFfaC0zTPW136HMVSkzFanocbTyDY1n8NzDlrh3q1eZ5ciJYsnQcmSelourCpsJjSftDkStwP5PjeYS7o+ZnacY1pH2S6du/i5onTrqwPzoUnVbEydcgre6LPeulCcuVhTnxw1S9clpxzgSrFSi7jK5CgA5CFqy9wk0DI9edjRxFVmTVqSRY+i/iVc9pwXjLCFaoyDrCpggWg8L0UEZvGNYMSBsQLMJUCBbWJa2/EhHOZBFtOEjexnVwRM1KhSdI8wION7N2775GaVtx/tBDD/0F5UiX/8ZrPZ/GiNfk8UGG5QA3oNt68P5LwkI5rE4Hb968WQv1X41/Cw+M50JgY1nhwu1N/pX8suKNSRsAprjV58jSq/4sFUdbiWBNRqYeJqu6iy66SHUZhc/k/qxaaEaRJlgZAWux3YsAlpagQ2Igj2XFYgqsRKIqCVZdCxadq6b696XzSnOtRJQGbJpgIXwafi26l6Yaa5bHguaAYJGgKTJXRbCsHnqxI8sO/HaKeGGVsiujZhFxb17WNoV6vAOdrsOfhz+SNnqAMHcuXGv5UwbrN+ZOuToK6YUcLLi/I4nu22PB93/qJG90StO2o/EfbpQw7nn6r5J1NbXpR9pKU4QjP/vZz+5RSx82Ww36Qfqzyn6wVpbcxptg5bZprFhREcDScr90Jzw4Th3ofIKOhemiVeX56GgCglXrqY91aFNJPwRfGAsWusqC1XB6kDQ9M2fODEgYOKRiwUJkQLAYQDKZIpTO6CqCNZ3Bc5z+13G6Ru6tc77lp9D5Nvz/wS/FNyTALVewf4E/4e8x6Bm0af9T+fuHnh/kPr4CzW4YOXKkyJWWEzTtyK97/pv4hRzXJC1NFjCXfOvZP7C3yfzVssmC1cN3SGtOE0I+91Ma+k/1e4V2JliFbj4rn0cE6OieRS91Dlp4HscFBIsOph/BokOWrFHhFOIAeRAFTQ9qPVPRLFi9AypTJSK0qjxD/dIkWBvDdqpSYvIoCNYfJAUrmaYA6zkRrFxMD9ZTMsfnrkQ34B70uhzrGKiG5eqdHPwb/qv4N/OGcMkyG5xv9ocHsqXknQQGH21WRo18RxB/G3IjrwurIacvmvtBFiy5em8S7q8EfIjdBEtA2BkBIzAAAVklNHjGcSJYmjbbUp6JTikgTuz7ExCp8nM6pgMM4nkiLhLBimzBCuurwShNgrUmlJtJwNO3pol3QAprThOG3yvUh31zZcHKBJCMhHKvrEa09h17Q0ZFpCIWPWeg4zcQ9m3WW32U/ztSEYyQ8NNF30D+qRdffLGmC9NyIli3piVMcujLAgsW13xNCxbnZMFam+aH2NOsQxxZtmDFQctpjUB0BDRoxrJg0UGKYA1Yd8ATam9Y7LQwrAwOJGJDWk/ElcLr/NcarIl1zlc9FX7cWMSit2qC6pGFIlgMoNuoxl206eHVq8Pcy/r1MzgHDINswaoFUrR4TRO+LryuouVofaqLKPIpvjH6Edo7NYtQWTXO43gSU2+pWLG4fjW1PRNdbysrI/Eh6ykDgoWgmhYs7hkRrMJbrwSWCZZQsDMCKSNAxySCdTCdxaAYoqsSLBa/P46Mrfhp1WRRhixYrbZeSZW1+Ek6iOPY6V5rxoahd6Q1WKFskbkJccqpk1brdTK1YIVla5qwpgWLqeDAwom1S9eKXZMIYBW5mqyTVq5cOadJEZlmg6y8nALehl9U+sZo2gVSRi8ytRbrkxwnHtfpv46SjtyjtyhMy33605/W8gn1ZTUJFuc0RfgovvAucUMUHgFXwAhkg4CsEmPZqkGDeVRXlWDRYer17Yfwz6shSATr4RrnsowWSdkrJonUNMH0UKneGMoVyoKlejFI3U7wgloDHudFsJ5lyqjfmjvltYuOwKhRo24m9U6uw5dEz9WalGHbf47SbsJ/J+NSv4H8/bi/XpxCOSKFT+NXpCCrTwTXvKx3T9JWNacIOW8LVh9iPjACRmAAAnQggVUCK0WcaUIRrFqDrQhbrW0fNEXYcgsWnaXewhvG4t3xhJEd2Kgeu9go8f7ImZhRI22scurIbqUFawxTvCVC2U8lcNC1cV846PQ75z/REQitQreDZxrEInrB0VKeRLIj8bIs6UEpS3c9wteBwwlJC0GGCNa1Gemshe6NLFieIkzaiM5vBDoYgcCixPSPrEsNHR3aIBLtw2Bbi2BpuqnWG2kqo+UEC52DbQ4gEMHGnQ0rGSYg36EcPhBulBg1WyoEK8RZu0RnPkXI9hnB+hVIdjDdUqWismB5erAKME1E3UCeXFmwICdj0GkZ/vsci/xk6kIy9Fuu8UQ4IGc4ir6Ye+TXGSmsfqNqn7F8+fJhnJuC9xRhRuBbrBEoPAJ0UhuoxAY6qUgEK7QCDadz1HqrAQ45IlgHIHdS+Um+zTiK/+qs2jVFqHUacaZBpb4Ilt6yi+NSWYMFzqMpVJhlTrD4ZI7a8gF8rQFPBMsL3AEhBfdbZBy8bNmyiSnISkvEpxE0EaK9MC2BEeRouvSICOnqJXkRJ0dlSLCCpQXVFFi1apXWZ1J0sPdftSSFihtcKG2trBEoFgKPQj60YLOhwwqkpzatT9KgPMAh56YwUp1fn+O7egGBo0NquQWL79MFFiysdFWfRvuUHHigKcKVA6Prxmg9SD9yWTd1jZMlnMEz0L1GsjSjf4OwV1cKhCjvQZza7p7Kc/7fFAJ6AOnhhZA5TeVOOVP4ncF/QOw/s1Gn1k+2yskiOjXhdg1vR8afuK9TXeBeBoAIVtWHMvo/rb/SQ5unCMsA86ERMAIDERDpiWTBYhopIFh0alUJFguh70eWOp0T8H0OYhWs76FDivNGXl/+JAcHHXSQ3iLUupKqnWU12SGxeB56x7JgkV7rNiaQf2i5XL2aXxlXfr7yGHwPDONaZfH7IeUdds455/Sb3mUgOZR4TQvfEerjIBkCIqq7uA9yQbC2bNnyIfQZg/Xqc8mqFS8311Uw5cx3Dg+Kl/O51NxLMrrojccfcKx7OwtXk2BxfwYEi0IfzaLgVsu0BavViLu8bkJAnUQkgkW6EklR5zPAQTD09s0v8Sfg+xwDigjWDnzLO6Rwh/Wn0C2yBYsBYDa6DkLvWASL9CJYPVjN+qaAGAAOYssHTcFt53gbXpu03ol/l9LWcNPC+FYRrCspby0Dx3vK9aE+h4X/V5TH+7g5BGjzLeR8AFxFXNvqtI4IPeajxHewXrXUssx1FhAsQk0/N+NeRaZ9uU//o5nMEfOoj5tMmw2tkl4W/y08UMpiXXhnglX4JnQF8ooAxEOda6QpQtLKgrW9XsdCml+R5ig6Jm0CWHIzOHiYOJGsdrg1DCYlctiwfDp+rQ8RWYxFLOjwA4LFh2DLX+9egpxh4PJhwk/iL8Kvxn+51hQJuk7j/KpwQOYwW0c52yjhe/j3czyyVBp6PJ/jXuI2luIcJkZAVt7AoptYUgIBrCP6G7Lrvr84gZimstJ/6D5Zxz0Rm2BxTcqiehb+NnaHz3JRvgjWoGHDhpXfy0QFThasR9FffUThnQlW4ZvQFcgrAnRYIlhTGET1Vk5dR1oRrDX1OhZIxi9JM5g0Ly0TpgFFVpx2Oa1limzBIq1epZeVaUMchSFmAcECg6BTJr/IyjvwX2RQ+Vf+/zP+Av5r3cv4Z5999ljCak54PVTtRIZxX0C2SOh7y8qQBcvTg2WApHDYi4xpKciJLCIkJX3pw7fgziDiR1yPLW/fsP+4D70O6lMqwoHqwQsgF5L0eGScWq8fiiCuUZLASs+yiGoPZiKmHbH+SiCYYDW6FHzeCDSPgKbtBrGwWk9ljZwIVtX1V6WMTDfcx/FjdIavLMURyoL1YNn/Vh+qs6zWUQ7QIxyMTuDEdQNONojgaTcgWBCt0lPv8WQZBeH634qsK/i/gbJq7YmkKcq7K/Jk+peBVuuDLscv4LjU54pg3ZlpwV0mHFKg+0AEOnNHO2o94I2QkqcIv4d/la5vrFfzKFzk5vTMlahdwL2cimzBkt7UQ9tJLADDT/LA8rPaolM5ExAsyq3Wb6ivNMFKBWYLMQIdjADEKlh/QUeip7JGriHBCp8qf46gN5QJ04DSbgtWtY6yTMXnDunED+foIOrx3wNONoiYPHmyFtTr/e0SwXo9fx9jKqOflYCBbhfxt+IHfKJGAwnxhyLjLsKWOojgRRQ4i7Lfc955503lWGvzgn2yWqpIZxfWS/XGcw1MyLqatOP/pYwj8d/A67q+muu7l/Bz+K+gQ/BWI8ftcCJYkS1Y6K1pwYX4UyBXsrZm7QKCRSHV+g0RLD2YdoQrPU11RGVcCSOQJwRYkB10FFhdoix0b0iwwrqJnBx27rnnzgwHkol09u22YEWdIjwD3R+B6Fwdt53mzZu3nTxPkVfkRO51+Kuo++7gX/8fWahm9Y/q6WEgUec9Fi8rV0vdmWeeeSMFfh/9v8BWAh/lWHqLLNulhADXQm8oalpKImuKoR3fzckfcg/Oh5TM4fgV+P/Bn4U/Gd9O9yCFTw33yKurB/q/hgRngd0ZHH++buKUToLXJkRtxvcjWGCqByDdo7ZgAYKdETACdRBYuHDhM5xej0/FghUW9VPCraxfeAvhIYqjY7pXYTscHXOwBovOue7DGuTmY+j3NtKfRlot/G7GqePdb+nSpeqED0PWVdWEEK8puVlhh92XhPhD9Yf4lluwVC6EWxiswy/BXwEOTxLapYQAFuPeUNS0lERWFUO7TebEXK6nHysB4W7ifo3/BP58fLPXd9XymogMLNqbNm2aVi9veH98iTRXc6wpwpY44UVBA16OoY+QdXoE3haslrSECzECxUdAnUUkCxYdz+ONqkvnvZE0IhbvIf1xhFvx/abJ+N9KJ3P/EHzNaRk6zo/SgX+RNJ/HkvOdBMoFBAty+Vpk7GZdVi0LkAjWaMqdWl4WOohgbZ0zZ46e8FvuFi9e/BQk6xja7UOEJ7VcgQ4vEHx1LW4B36zXYb1cUHI9XZNTSAOCheVc6zNrOqzgx3JSll6Rwl01E2ZzQm3Vz4LF/+BBlOn0jrFgDc0GO0s1AkYgREDrsOoSLDq3MaTZgw67IcGSTAaQL5P2J3itAbmxnU/M6CALlpw6y2CdVPAv/EG315NGT8mXMjUwH9319NqsU8c7F3maHrxZhKWaIDroeyBhOqXB47GyNJrKuTvcv6ssunWHoc7/1roSu6ckXVtcb71cH9MyrrWIyaOUlVdLi675beBQl2hy/jWk28ADx68yxquaePV1/QgW7bcfOvVADDuGYNU161dDxXFGwAjEQqChBav0+RY6mEgECyuQNq8M3p4jz/JY2qSfWE+i+sTPXpWiw8+FfJP4K+nEk5IriRdZ1bToa/Gy4lV1kCtZqMSwRLDKnSxYK8ojfNxxCOgaiTIln6TiIli/SyIgy7wQP1mjevF1LViQmeNJc12bHjjUb2jdablTu0n31eWRRT42wSpy61n3IiDQ0IIFIQg6Gjq8SARLT+oQlrdS+WMgW99oJwhMdQUWLHTv9zQqnfhcyHsJJvG5kHlpdOLU+1rkydo3Ef//8FUdA4zWwIhkza5IIAtWW9ZfVejhv9khIOuH1uhl4vRpJgQfzbWYW4IVVvwBwpoEi/t1EOdFFH8bpm91IILVr89AJ7Xbau7fHa1WJqvyTLCyQtZyjQAI0BGLYO1FpzGyFiCkCQgWZCUSwZIcERZk3kzeJFNutVSKHM/O6k+TeCed4wALFnGv59x1aX0uBHnXIa8Xr41FVxLWc8FC91KC888/X/pNxq8oxTnsSARkMZYlJBPHp5lE2sdyLd6USQHpCdUDRk2CxfpEkZlJ9B+3pldkdEmUO4BgkVs6dcz0oNAwwRIKdkYgOwQeluh6m43SWYtg7YSsVF1TlJ1qySVDdGTS19twlU+jekJ+Gf4X+FQcZW1jHdcMwg9HENiPYLE1wmHKQzvcGSGvkxQXAQ3Q+4SWptRrATE4DqG7R44ceUvqwtMVKAvWdPoW3YfV3FxFcj/cVu1kC+JEsEZXfNLqecQF/WULym9JESZYLYHZhXQrAnRwsmD1MA14QC0M6LRFsJ4IyUqtZHmOV2fZz4IVvsGnqbxUN1wEq0gWO9KJYM0IP10i7PRCwLOzZ89WvF2HIkC7i2ANwdIUWIXTrib380uQeceiRYu0/UqenQjWmGXLlslqW82JYK09/fTT27VQX31GD1tJlPcbIli9iu8UZ4LVKS3peuQVgaADo+OvSbBCC1bk6cEcVlTrsPpZsKjv86VnGy1GIlJD16xZM016gLEI1m1prAWTPLt8IsB1VyIMWU0TimBdn8/a/1krXjrRFGHPjh07Zvw5tt+RCNZt4BXpgaVfzhT+cD8G/R16Blup8HApLnIg+jyUgvjciDDByk1TWJFORICO41nqpR3IaxIszutpu8gEa4AFi/ocgt+GxUhP0i13ELvAUsUr36U3CUWwft9yRVxgSxEoveLPQJ36QnesQbLIzsHnnmCxnjO478BjZo0GOIL422ucyzwa/YK1VugXtBN72qkPHE4/aYKVOfouwAh0FgKaJuxkgjXAgkVHqSfn3nZZjHhyVwe+GT8r3C5iNoOuCRaAdLjTesDtXH+pE6ytW7e+OMQu9wQrnMJchb7B2sPyNg+Jou7Pm8vjW3l82mmnac+8rSUizBpJTQ9quxcTrFY2hMsyAh2AQBSCFaxJKGhdq1mwplOXYJqiHXUK17Pdy0A7e/PmzcegwyCO874wuR1QdVSZYbuLXGcxRfhm5PbyosX9BQFNDxSyVPVzvExzdBjRNoIFsdLU5J9KRJj/AcHComWC1a+1/McIGIFGCKjTmFYn0d50MIWdIkR3WbAmh+soStUUwWrL9GBJAUK9IaXB5C/wIoF34O06HwERrFQtWBdccMF4ZL4Tf1lIDoqAoh4ojuO+HF6hrO6J9fj7KuJb/bePCEO0RLA2oOu6ViuRZXleg5UlupZtBECADlnrgQ6q9uo4HYr2xxpHB1NYgoX+Ii/qSybhtaB8EMF06t02C5b0oHxN5egJ/v14fVx5F6Fd5yOQOsFi09x/ALZR+C8UCL4foutE7gMRwz7H/SmL7i05uB/04BlYrsJQ/zvKmWB1VHO6MnlEgA7tbvQawavjpc6kT012OdfiTpGBwhIs6icLllzwJiFbNOzJ8Vh8Wy1Y6KXP6aiP2wf/FbxddyCQ6majS5cu1X27AP8vkJLHigIhuv4BXX/AfbD8nHPOeZn0Jk73g9aS3aT/bXaaai0twj+I46JMvUaGzQQrMlROaASaQwASJYIlEqVdoPs5FmMHBItOsLAEiwoF68dK3yMk1PSgLFlttWAxmPSC+Umo8j6Oc78wWZjZpYJAYMHi+pMlNZGTDO7Rf0XIOjYX/UwiYW3IPG7cOF3/N7C26Wc8+JzCsb6usA/36I/boE6/Irk3RaimhJuNzuF4Rb8EHfBnaAfUwVUwArlGgA5ai9w301mLYF1RriydzBTie3hNubAEa8SIEU/whpUIVWDBojMPCBbxbSVYwpkFyd8qx9vHnY8A95QWT+8BodC6qURrerD8vB8Zf4F/QwE2F0XN/m7+/PmbL7300jeuXbv2H8Hks5yVUeXOQw45pO0PHLTTfer7eAlFW6jsz/+OI1i2YPW/Hv3PCKSOANYTrf25Fz/AgkUHIwvWbl5TLk2zpV5+1gIZeDSI7cAHBIuOUmb/dbyK/XTWZVu+EahEgOsvlc1GuW8nh6Tk2xxfWVlOUf6ffPLJW9H/4+h7MNi8i/BV7do+pRwzHsD00sluHsj+TvHopinNjnK2YHVUc7oyOUZA04TafLOfo1ORBespOkARlEI66rAb/Z+gHnupAoRaTyFCaWcEWo4AA7amCDVg603CJG+Onk7+IfhP4QvvuEe1JlI+F27hwoXPoJM+2v4+/NO02525UCxFJWzBShFMizICtRCgs/8j5+bSofS75yAjsmAVdnqwrL6ywAUWLEIRrHa/Al6mmg+7DIFgITr3lghWU+7888/Xw8I8/Oe5Z4M1hk0JcqZGCPw0TPAzcJalv6Ncv86+o2rmyhiBHCFAZ38j6kzAi3yUu04hWBqEAgsWoQlWeQv7uKUIMFBvo8A1oQWrqbLZjPNjZNSAf2lTApwpKgJLSfhlXgSaHzVDkdINLZKy1tUIFBiB30l3Ov3jCLQvVsmJYBXm1e+S0lVCWbD20xtBmzZt2pdjW7CqgOSoliGghe77N1Pa8uXLh61aterD5P0WZE2fdLHLCAHwfRLRH81IfNvF2oLV9iawAt2AAB2JFoLfTacvglXuOsqCxRtBM8LKmWCVt7KPW41A05uNQq7+CmWnspXBl1uttMvrLARMsDqrPV2bfCMgK1anEqzV1G1fFqoeHDaBCVa+r8VO1+5RKtjsGixZVG4488wzb+90kFy/bBEwwcoWX0s3An0IMD2odViHY83S53F6wlCfsljVl6igB9RBb0lq36FX4tez/1Rht50oaBNY7f4IyIIVe4qQXdsPIN9r8F/pL87/jEB8BEyw4mPmHEagKQTChe7DmHrQ9/F6hgwZUnrC1tN2oR11Kr0O/wEqchOEa3ehK2TlC40A158I1mQ22RwRpyI7d+58O+m3sWv75XHyOa0RqIaACVY1VBxnBLJBQBvpbWUaLZgmpDMPCBbkpPAEa/bs2dpfR29djcbLUmdnBNqJQHBPrV+/Xi9cRHY8BL2TxFcUcdf2yJV0wpYhYILVMqhdULcjwJTgNjD4Pb60DiuYwoBo6Wm70C7cGfoHYSW+UejKWPnCIwBRCu4pwsjThOedd95UKq57s3QdFx4HV6C9CJhgtRd/l959CPyWKr+Ejn8QoTr/9RCvjR0Cw98y7TmL+tzXIfVxNQqKAFN8AcHCWlyahm9YE74Z+loS7R4+fPhVDRM7gRGIgIAJVgSQnMQIpIUAa0OuRtaBfIj2YEJ9m/DetGS3W44sdEuWLOmY+rQbT5ffPAJ8hmUDuTdyv0UmWDz0vJ48Ny9evNgvaDQPvXOWIWCCVQaGD41A1gjQif+KMrbi34w/BK9vcdnB2HhSAAAGWUlEQVQZASOQIgLhSxaRNxvl4UBjoSxYtl6l2A7dLsoEq9uvANe/pQiE04E/ptD34+cwEJhgtbQFXFgXIaBpwqgWrINIO4n78dddhI+rmjECJlgZA2zxRqAKAl8g7vn4CVi0flblvKOMgBFIjoDeJIxKsI5UcdyPtyYv1hKMwHMImGD5SjACLUYAK9aveVLWx02/yHHwjcIWq+DijEA3ICALVtS3CA8n7aPcj/o2np0RSAWBoalIsRAjYARiIcBO55+LlcGJjYARiIUADzFag7UvpGkwXnu01XMzOOm3X+sh5HOxEbAFKzZkzmAEjIARMAIFQEBThEOHDRu2VwRdp5PmwQjpnMQIREbABCsyVE5oBIyAETACRUEAC9Zj0nX79u1R1mFNJ70JVlEatyB6mmAVpKGsphEwAkbACERHgE9QBQQL4qQd2ms6pg/HcHIy04kmWDVR8olmEDDBagY15zECRsAIGIFcI8DO7I+jILxpd12CBRHT9GAPoQlWrlu0eMqZYBWvzayxETACRsAINEAAy9QOkmhX9roffIaATZMoPqtjgiUg7FJDwAQrNSgtyAgYASNgBHKGwCr0qWvBgmDJgrUVvzpnuludgiNgglXwBrT6RsAIGAEjUBMBrcOqS7A4L4LVG2Erh5qF+IQRqIaACVY1VBxnBIyAETACnYCALFh1pwg57y0aOqGlc1gHE6wcNopVMgJGwAgYgVQQaDhFSCnT8L14OyOQKgImWKnCaWFGwAgYASOQFwTYokEEax+m/6qOday/GsR5W7Dy0mAdpkfVi67D6ujqGAEjYASMQHcioDVYQ4cPH75nteqfffbZE4kf501Gq6HjuKQImGAlRdD5jYARMAJGIJcIYKGSBauHPbFqrcOaofOku1+hnRFIEwETrDTRtCwjYASMgBHIDQJDhw4NCBZ7XNV6kzAgWCj8QG6UtiIdg4AJVsc0pStiBIyAETAC5QiMGzcu2NuqzudyRLCeZo3WuvJ8PjYCaSBggpUGipZhBIyAETACuUPg5JNP1gaiT+FrTRHO5JytV7lruc5QyASrM9rRtTACRsAIGIHqCKxijVW9KUITrOq4OTYhAiZYCQF0diNgBIyAEcg1AnqTsJYFS1OEJli5br7iKmeCVdy2s+ZGwAgYASPQGIFekkyrTLZ8+fJhxB2IN8GqBMf/U0HABCsVGC3ECBgBI2AE8ogAC9xFoGSp6ucef/zxWURoDLyn3wn/MQIpIWCClRKQFmMEjIARMAK5REAEa/yyZcu0qWifY13WkfozcuTIW/sifWAEUkTABCtFMC3KCBgBI2AE8oVAaRPR7du3y2LV54h/EX/uX7Ro0fq+SB8YgRQRMMFKEUyLMgJGwAgYgdwhsAKNdpQsVtJu6dKlBxC8C3+5/tsZgSwQ0Icu7YyAETACRsAIdCwCbCSqaUD5D7Em622QrX/ieCs7vR9/xhlnPNKxFXfF2oqALVhthd+FGwEjYASMQAsQuIIyZLHqhVxdRngj/hiTK1CwMwJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRiASAv8fcV4fpHnPqpkAAAAASUVORK5CYII=\" width=\"600\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# customized plot\n",
"fig = soft_plot(stream,zoomarea=[1.8,2.8])\n",
"# save in pdf\n",
"fig.savefig(\"material/softfig1.pdf\", bbox_inches='tight') \n",
"\n",
"# customized plot\n",
"fig = soft_plot(zoomedstream)\n",
"# save in pdf\n",
"fig.savefig(\"material/softfig2.pdf\", bbox_inches='tight') "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Also plot all the other data \n",
"But it is not as nice as the first plot."
]
},
{
"cell_type": "code",
"execution_count": 277,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" this.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" // select the cell after this one\n",
" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
" IPython.notebook.select(index + 1);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
"
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