{
"cells": [
{
"cell_type": "markdown",
"id": "b3277ae5",
"metadata": {},
"source": [
"# EFIxTCT (Cross-track ion flow)"
]
},
{
"cell_type": "markdown",
"id": "a371f176",
"metadata": {},
"source": [
"> Abstract: Access to the 2Hz & 16Hz cross-track ion flow data derived from the Thermal Ion Imager (TII), part of the Electric Field Instrument package (EFI).\n",
"> \n",
"> For more information about this product, see the [release notes](https://earth.esa.int/eogateway/documents/20142/37627/swarm-EFI-TII-cross-track-flow-dataset-release-notes.pdf)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "28b01839",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:01.883506Z",
"iopub.status.busy": "2025-06-21T21:46:01.883105Z",
"iopub.status.idle": "2025-06-21T21:46:01.888792Z",
"shell.execute_reply": "2025-06-21T21:46:01.888202Z"
}
},
"outputs": [],
"source": [
"SERVER_URL = 'https://vires.services/ows'"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "ff2a5d9f-7caf-41ab-ae80-cd4b386ad28d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:01.890684Z",
"iopub.status.busy": "2025-06-21T21:46:01.890531Z",
"iopub.status.idle": "2025-06-21T21:46:02.578844Z",
"shell.execute_reply": "2025-06-21T21:46:02.578162Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Python implementation: CPython\n",
"Python version : 3.11.6\n",
"IPython version : 8.18.0\n",
"\n",
"viresclient: 0.12.3\n",
"pandas : 2.1.3\n",
"xarray : 2023.12.0\n",
"matplotlib : 3.8.2\n",
"\n"
]
}
],
"source": [
"# Display important package versions used\n",
"%load_ext watermark\n",
"%watermark -i -v -p viresclient,pandas,xarray,matplotlib"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c627e1ad-05c4-48dd-a9a5-40015f3a7570",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:02.581511Z",
"iopub.status.busy": "2025-06-21T21:46:02.580878Z",
"iopub.status.idle": "2025-06-21T21:46:02.768696Z",
"shell.execute_reply": "2025-06-21T21:46:02.768122Z"
}
},
"outputs": [],
"source": [
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import xarray as xr\n",
"# Control the HTML display of the datasets\n",
"xr.set_options(display_expand_attrs=False, display_expand_coords=True, display_expand_data=True)\n",
"\n",
"from viresclient import SwarmRequest"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "10830394-2e07-439f-81cc-4104cfe425e9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:02.770885Z",
"iopub.status.busy": "2025-06-21T21:46:02.770696Z",
"iopub.status.idle": "2025-06-21T21:46:03.225420Z",
"shell.execute_reply": "2025-06-21T21:46:03.224855Z"
}
},
"outputs": [],
"source": [
"request = SwarmRequest(SERVER_URL)"
]
},
{
"cell_type": "markdown",
"id": "3c7ec541-936a-4dae-b8b5-29d565da2aee",
"metadata": {},
"source": [
"## What data is available?"
]
},
{
"cell_type": "markdown",
"id": "49105a46-02a5-4eea-9fd0-a798d0b8b5f8",
"metadata": {},
"source": [
"There are two sets of collections available, one for 2Hz and one for 16Hz, and for each there are three collections, one for each Swarm spacecraft."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "7da5c124-d927-4ee6-87bf-03ddab4dcc7b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.227832Z",
"iopub.status.busy": "2025-06-21T21:46:03.227548Z",
"iopub.status.idle": "2025-06-21T21:46:03.233160Z",
"shell.execute_reply": "2025-06-21T21:46:03.232629Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"{'EFI_TCT02': ['SW_EXPT_EFIA_TCT02',\n",
" 'SW_EXPT_EFIB_TCT02',\n",
" 'SW_EXPT_EFIC_TCT02']}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"request.available_collections(\"EFI_TCT02\", details=False)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "22e7cf35-0160-4b99-82a0-2b7b29de10f9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.235125Z",
"iopub.status.busy": "2025-06-21T21:46:03.234809Z",
"iopub.status.idle": "2025-06-21T21:46:03.238453Z",
"shell.execute_reply": "2025-06-21T21:46:03.238037Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"{'EFI_TCT16': ['SW_EXPT_EFIA_TCT16',\n",
" 'SW_EXPT_EFIB_TCT16',\n",
" 'SW_EXPT_EFIC_TCT16']}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"request.available_collections(\"EFI_TCT16\", details=False)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "ef1baa54-f3c7-4207-a094-8c16112503e3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.240092Z",
"iopub.status.busy": "2025-06-21T21:46:03.239915Z",
"iopub.status.idle": "2025-06-21T21:46:03.243146Z",
"shell.execute_reply": "2025-06-21T21:46:03.242701Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['VsatC', 'VsatE', 'VsatN', 'Bx', 'By', 'Bz', 'Ehx', 'Ehy', 'Ehz', 'Evx', 'Evy', 'Evz', 'Vicrx', 'Vicry', 'Vicrz', 'Vixv', 'Vixh', 'Viy', 'Viz', 'Vixv_error', 'Vixh_error', 'Viy_error', 'Viz_error', 'Latitude_QD', 'MLT_QD', 'Calibration_flags', 'Quality_flags']\n"
]
}
],
"source": [
"print(request.available_measurements(\"EFI_TCT02\"))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "fda2fbce-172b-472e-b73a-c745ec7e1fb9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.244773Z",
"iopub.status.busy": "2025-06-21T21:46:03.244612Z",
"iopub.status.idle": "2025-06-21T21:46:03.247694Z",
"shell.execute_reply": "2025-06-21T21:46:03.247259Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['VsatC', 'VsatE', 'VsatN', 'Bx', 'By', 'Bz', 'Ehx', 'Ehy', 'Ehz', 'Evx', 'Evy', 'Evz', 'Vicrx', 'Vicry', 'Vicrz', 'Vixv', 'Vixh', 'Viy', 'Viz', 'Vixv_error', 'Vixh_error', 'Viy_error', 'Viz_error', 'Latitude_QD', 'MLT_QD', 'Calibration_flags', 'Quality_flags']\n"
]
}
],
"source": [
"print(request.available_measurements(\"EFI_TCT16\"))"
]
},
{
"cell_type": "markdown",
"id": "1480f25c-b1e2-456f-8e19-8e61c724df8f",
"metadata": {},
"source": [
"As seen above, the variables available for both the 2Hz and 16Hz datasets are the same. Here is a short description for each variable:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "d3273e1e-6ecf-474e-b439-101024ccfef7",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.249379Z",
"iopub.status.busy": "2025-06-21T21:46:03.249226Z",
"iopub.status.idle": "2025-06-21T21:46:03.252829Z",
"shell.execute_reply": "2025-06-21T21:46:03.252311Z"
}
},
"outputs": [],
"source": [
"tct_vars = [\n",
" # Satellite velocity in NEC frame\n",
" \"VsatC\", \"VsatE\", \"VsatN\",\n",
" # Geomagnetic field components derived from 1Hz product\n",
" # (in satellite-track coordinates)\n",
" \"Bx\", \"By\", \"Bz\",\n",
" # Electric field components derived from -VxB with along-track ion drift\n",
" # (in satellite-track coordinates)\n",
" # Eh: derived from horizontal sensor\n",
" # Ev: derived from vertical sensor\n",
" \"Ehx\", \"Ehy\", \"Ehz\",\n",
" \"Evx\", \"Evy\", \"Evz\",\n",
" # Ion drift corotation signal, removed from ion drift & electric field\n",
" # (in satellite-track coordinates)\n",
" \"Vicrx\", \"Vicry\", \"Vicrz\",\n",
" # Ion drifts along-track from vertical (..v) and horizontal (..h) TII sensor\n",
" \"Vixv\", \"Vixh\",\n",
" # Ion drifts cross-track (y from horizontal sensor, z from vertical sensor)\n",
" # (in satellite-track coordinates)\n",
" \"Viy\", \"Viz\",\n",
" # Random error estimates for the above\n",
" # (Negative value indicates no estimate available)\n",
" \"Vixv_error\", \"Vixh_error\", \"Viy_error\", \"Viz_error\",\n",
" # Quasi-dipole magnetic latitude and local time\n",
" # redundant with VirES auxiliaries, QDLat & MLT\n",
" \"Latitude_QD\", \"MLT_QD\",\n",
" # Refer to release notes link above for details:\n",
" \"Calibration_flags\", \"Quality_flags\",\n",
"]"
]
},
{
"cell_type": "markdown",
"id": "138d2148-dd03-438e-a0d1-e116228b7943",
"metadata": {},
"source": [
"## Fetching and plotting data"
]
},
{
"cell_type": "markdown",
"id": "f80e0301-da65-4b8c-8529-13c633691296",
"metadata": {},
"source": [
"For demonstration, we will fetch the 2Hz data from Swarm Alpha (`SW_EXPT_EFIA_TCT02`)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "126de639-6842-4042-878d-e392445b5930",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:03.254895Z",
"iopub.status.busy": "2025-06-21T21:46:03.254532Z",
"iopub.status.idle": "2025-06-21T21:46:07.668019Z",
"shell.execute_reply": "2025-06-21T21:46:07.667440Z"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e66c8fd708ee4a6589e1903a50ce6127",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Processing: 0%| | [ Elapsed: 00:00, Remaining: ? ] [1/1] "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c2624732d4b74f6c8bffe722475409a8",
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"version_minor": 0
},
"text/plain": [
"Downloading: 0%| | [ Elapsed: 00:00, Remaining: ? ] (4.163MB)"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"start = \"2018-07-17T11:00:00\"\n",
"end = \"2018-07-17T16:00:00\"\n",
"\n",
"request = SwarmRequest(SERVER_URL)\n",
"request.set_collection(\"SW_EXPT_EFIA_TCT02\")\n",
"request.set_products(measurements=tct_vars)\n",
"data = request.get_between(start, end)\n"
]
},
{
"cell_type": "markdown",
"id": "d95fc734-28e1-48f0-b091-1d53934fee89",
"metadata": {},
"source": [
"Data can be loaded as either a pandas datframe or a xarray dataset."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "e1eadca7-b684-44cc-b50e-1a8ea44a1e76",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:07.670373Z",
"iopub.status.busy": "2025-06-21T21:46:07.670199Z",
"iopub.status.idle": "2025-06-21T21:46:08.231163Z",
"shell.execute_reply": "2025-06-21T21:46:08.230585Z"
}
},
"outputs": [
{
"data": {
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"<div>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Vixv_error</th>\n",
" <th>VsatE</th>\n",
" <th>Evx</th>\n",
" <th>Bz</th>\n",
" <th>Quality_flags</th>\n",
" <th>Ehz</th>\n",
" <th>Vicrz</th>\n",
" <th>Vixh</th>\n",
" <th>Evy</th>\n",
" <th>VsatN</th>\n",
" <th>...</th>\n",
" <th>Spacecraft</th>\n",
" <th>Longitude</th>\n",
" <th>Viz_error</th>\n",
" <th>Latitude</th>\n",
" <th>MLT_QD</th>\n",
" <th>Vicry</th>\n",
" <th>Viz</th>\n",
" <th>Viy</th>\n",
" <th>VsatC</th>\n",
" <th>Ehx</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Timestamp</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th></th>\n",
" <th></th>\n",
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" <tr>\n",
" <th>2018-07-17 11:28:49.231500032</th>\n",
" <td>-14.849242</td>\n",
" <td>1978.689941</td>\n",
" <td>-101.939255</td>\n",
" <td>47833.585938</td>\n",
" <td>0</td>\n",
" <td>-13.000871</td>\n",
" <td>-0.658330</td>\n",
" <td>-4369.472168</td>\n",
" <td>-304.620270</td>\n",
" <td>-7367.485352</td>\n",
" <td>...</td>\n",
" <td>A</td>\n",
" <td>83.452042</td>\n",
" <td>-14.849242</td>\n",
" <td>80.103966</td>\n",
" <td>17.152279</td>\n",
" <td>83.115257</td>\n",
" <td>240.197159</td>\n",
" <td>2120.916016</td>\n",
" <td>5.364216</td>\n",
" <td>-101.939255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-07-17 11:28:49.731500032</th>\n",
" <td>-14.849242</td>\n",
" <td>1972.037720</td>\n",
" <td>-105.307312</td>\n",
" <td>47837.687500</td>\n",
" <td>0</td>\n",
" <td>-13.498644</td>\n",
" <td>-0.661254</td>\n",
" <td>-4536.605469</td>\n",
" <td>-303.078125</td>\n",
" <td>-7369.272461</td>\n",
" <td>...</td>\n",
" <td>A</td>\n",
" <td>83.500351</td>\n",
" <td>-14.849242</td>\n",
" <td>80.072952</td>\n",
" <td>17.153959</td>\n",
" <td>83.389847</td>\n",
" <td>134.010635</td>\n",
" <td>2195.653809</td>\n",
" <td>5.380056</td>\n",
" <td>-105.307312</td>\n",
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" <tr>\n",
" <th>2018-07-17 11:28:50.231500032</th>\n",
" <td>-14.849242</td>\n",
" <td>1965.429321</td>\n",
" <td>-103.137848</td>\n",
" <td>47841.738281</td>\n",
" <td>0</td>\n",
" <td>-13.564169</td>\n",
" <td>-0.664178</td>\n",
" <td>-4604.627441</td>\n",
" <td>-311.114258</td>\n",
" <td>-7371.040527</td>\n",
" <td>...</td>\n",
" <td>A</td>\n",
" <td>83.548347</td>\n",
" <td>-14.849242</td>\n",
" <td>80.041931</td>\n",
" <td>17.155634</td>\n",
" <td>83.664406</td>\n",
" <td>139.632843</td>\n",
" <td>2149.880859</td>\n",
" <td>5.395850</td>\n",
" <td>-103.137848</td>\n",
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" <tr>\n",
" <th>2018-07-17 11:28:50.731500032</th>\n",
" <td>-14.849242</td>\n",
" <td>1958.853638</td>\n",
" <td>-103.988091</td>\n",
" <td>47845.742188</td>\n",
" <td>0</td>\n",
" <td>-13.433209</td>\n",
" <td>-0.667102</td>\n",
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" <td>83.596039</td>\n",
" <td>-14.849242</td>\n",
" <td>80.010902</td>\n",
" <td>17.157301</td>\n",
" <td>83.938942</td>\n",
" <td>-8.017212</td>\n",
" <td>2173.743652</td>\n",
" <td>5.411608</td>\n",
" <td>-103.988091</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-07-17 11:28:51.231500032</th>\n",
" <td>-14.849242</td>\n",
" <td>1952.320923</td>\n",
" <td>-100.248749</td>\n",
" <td>47849.816406</td>\n",
" <td>0</td>\n",
" <td>-13.663168</td>\n",
" <td>-0.670023</td>\n",
" <td>-4699.985352</td>\n",
" <td>-303.803864</td>\n",
" <td>-7374.530762</td>\n",
" <td>...</td>\n",
" <td>A</td>\n",
" <td>83.643425</td>\n",
" <td>-14.849242</td>\n",
" <td>79.979858</td>\n",
" <td>17.158964</td>\n",
" <td>84.213448</td>\n",
" <td>172.994843</td>\n",
" <td>2087.728027</td>\n",
" <td>5.427329</td>\n",
" <td>-100.248749</td>\n",
" </tr>\n",
" </tbody>\n",
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"</div>"
],
"text/plain": [
" Vixv_error VsatE Evx \\\n",
"Timestamp \n",
"2018-07-17 11:28:49.231500032 -14.849242 1978.689941 -101.939255 \n",
"2018-07-17 11:28:49.731500032 -14.849242 1972.037720 -105.307312 \n",
"2018-07-17 11:28:50.231500032 -14.849242 1965.429321 -103.137848 \n",
"2018-07-17 11:28:50.731500032 -14.849242 1958.853638 -103.988091 \n",
"2018-07-17 11:28:51.231500032 -14.849242 1952.320923 -100.248749 \n",
"\n",
" Bz Quality_flags Ehz \\\n",
"Timestamp \n",
"2018-07-17 11:28:49.231500032 47833.585938 0 -13.000871 \n",
"2018-07-17 11:28:49.731500032 47837.687500 0 -13.498644 \n",
"2018-07-17 11:28:50.231500032 47841.738281 0 -13.564169 \n",
"2018-07-17 11:28:50.731500032 47845.742188 0 -13.433209 \n",
"2018-07-17 11:28:51.231500032 47849.816406 0 -13.663168 \n",
"\n",
" Vicrz Vixh Evy VsatN \\\n",
"Timestamp \n",
"2018-07-17 11:28:49.231500032 -0.658330 -4369.472168 -304.620270 -7367.485352 \n",
"2018-07-17 11:28:49.731500032 -0.661254 -4536.605469 -303.078125 -7369.272461 \n",
"2018-07-17 11:28:50.231500032 -0.664178 -4604.627441 -311.114258 -7371.040527 \n",
"2018-07-17 11:28:50.731500032 -0.667102 -4507.862793 -312.692871 -7372.794922 \n",
"2018-07-17 11:28:51.231500032 -0.670023 -4699.985352 -303.803864 -7374.530762 \n",
"\n",
" ... Spacecraft Longitude Viz_error \\\n",
"Timestamp ... \n",
"2018-07-17 11:28:49.231500032 ... A 83.452042 -14.849242 \n",
"2018-07-17 11:28:49.731500032 ... A 83.500351 -14.849242 \n",
"2018-07-17 11:28:50.231500032 ... A 83.548347 -14.849242 \n",
"2018-07-17 11:28:50.731500032 ... A 83.596039 -14.849242 \n",
"2018-07-17 11:28:51.231500032 ... A 83.643425 -14.849242 \n",
"\n",
" Latitude MLT_QD Vicry Viz \\\n",
"Timestamp \n",
"2018-07-17 11:28:49.231500032 80.103966 17.152279 83.115257 240.197159 \n",
"2018-07-17 11:28:49.731500032 80.072952 17.153959 83.389847 134.010635 \n",
"2018-07-17 11:28:50.231500032 80.041931 17.155634 83.664406 139.632843 \n",
"2018-07-17 11:28:50.731500032 80.010902 17.157301 83.938942 -8.017212 \n",
"2018-07-17 11:28:51.231500032 79.979858 17.158964 84.213448 172.994843 \n",
"\n",
" Viy VsatC Ehx \n",
"Timestamp \n",
"2018-07-17 11:28:49.231500032 2120.916016 5.364216 -101.939255 \n",
"2018-07-17 11:28:49.731500032 2195.653809 5.380056 -105.307312 \n",
"2018-07-17 11:28:50.231500032 2149.880859 5.395850 -103.137848 \n",
"2018-07-17 11:28:50.731500032 2173.743652 5.411608 -103.988091 \n",
"2018-07-17 11:28:51.231500032 2087.728027 5.427329 -100.248749 \n",
"\n",
"[5 rows x 31 columns]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = data.as_dataframe()\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "8bc5ac7b-f218-4221-a8e3-5739eff21ecf",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:08.233212Z",
"iopub.status.busy": "2025-06-21T21:46:08.233025Z",
"iopub.status.idle": "2025-06-21T21:46:08.343569Z",
"shell.execute_reply": "2025-06-21T21:46:08.343033Z"
}
},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
"Dimensions: (Timestamp: 32535)\n",
"Coordinates:\n",
" * Timestamp (Timestamp) datetime64[ns] 2018-07-17T11:28:49.2315000...\n",
"Data variables: (12/31)\n",
" Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'\n",
" Vixv_error (Timestamp) float32 -14.85 -14.85 ... -14.85 -14.85\n",
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" ... ...\n",
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" Ehy (Timestamp) float32 -208.5 -216.8 ... -209.6 -206.1\n",
" Longitude (Timestamp) float32 83.45 83.5 83.55 ... -143.5 -143.5\n",
" VsatC (Timestamp) float32 5.364 5.38 5.396 ... -11.04 -11.03\n",
" Bx (Timestamp) float32 -1.942e+03 -1.948e+03 ... 9.496e+03\n",
" Ehx (Timestamp) float32 -101.9 -105.3 ... -65.88 -61.85\n",
"Attributes: (3)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-431f699e-cd96-4a1a-94e2-77f1c807c04f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-431f699e-cd96-4a1a-94e2-77f1c807c04f' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Timestamp</span>: 32535</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ea95f772-29c7-4be0-b9b5-33bff6f807e9' class='xr-section-summary-in' type='checkbox' checked><label for='section-ea95f772-29c7-4be0-b9b5-33bff6f807e9' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Timestamp</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-07-17T11:28:49.231500032 .....</div><input id='attrs-c3c1a806-7432-445a-a756-80bd95bf6ec9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3c1a806-7432-445a-a756-80bd95bf6ec9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e09a1570-fb16-4664-b4ee-8357c048b8e8' class='xr-var-data-in' type='checkbox'><label for='data-e09a1570-fb16-4664-b4ee-8357c048b8e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>UT</dd></dl></div><div class='xr-var-data'><pre>array(['2018-07-17T11:28:49.231500032', '2018-07-17T11:28:49.731500032',\n",
" '2018-07-17T11:28:50.231500032', ..., '2018-07-17T15:59:58.731500032',\n",
" '2018-07-17T15:59:59.231500032', '2018-07-17T15:59:59.731500032'],\n",
" dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c5acb5f1-009b-463b-b9ba-8a6644d36650' class='xr-section-summary-in' type='checkbox' ><label for='section-c5acb5f1-009b-463b-b9ba-8a6644d36650' class='xr-section-summary' >Data variables: <span>(31)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Spacecraft</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'</div><input id='attrs-e3e05b28-8b06-42df-a4c5-a2b5b0c5f5c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3e05b28-8b06-42df-a4c5-a2b5b0c5f5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aea5a226-3ebf-42d3-b085-3b1adfd124c0' class='xr-var-data-in' type='checkbox'><label for='data-aea5a226-3ebf-42d3-b085-3b1adfd124c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>description :</span></dt><dd>Spacecraft identifier (values: 'A', 'B', 'C' or '-' if not available).</dd></dl></div><div class='xr-var-data'><pre>array(['A', 'A', 'A', ..., 'A', 'A', 'A'], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vixv_error</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-14.85 -14.85 ... -14.85 -14.85</div><input id='attrs-d6f94632-78ad-4338-bafb-ed0a43611796' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6f94632-78ad-4338-bafb-ed0a43611796' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a72abd30-da71-4e19-828d-ffcc10e81e8a' class='xr-var-data-in' type='checkbox'><label for='data-a72abd30-da71-4e19-828d-ffcc10e81e8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Random error estimate for along-track ion drift from vertical TII sensor in satellite-track coordinates. Negative value indicates no estimate available.</dd></dl></div><div class='xr-var-data'><pre>array([-14.849242, -14.849242, -14.849242, ..., -14.849242, -14.849242,\n",
" -14.849242], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Bz</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.783e+04 4.784e+04 ... 4.539e+04</div><input id='attrs-d1da8ff5-4f49-4b18-a926-e6f99ce5988a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1da8ff5-4f49-4b18-a926-e6f99ce5988a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39c043cf-9447-4214-9148-23e3c18e5e6d' class='xr-var-data-in' type='checkbox'><label for='data-39c043cf-9447-4214-9148-23e3c18e5e6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>nT</dd><dt><span>description :</span></dt><dd>Geomagnetic field z component in satellite-track coordinates, derived from the 1 Hz product.</dd></dl></div><div class='xr-var-data'><pre>array([47833.586, 47837.688, 47841.74 , ..., 45365.473, 45375.383,\n",
" 45385.22 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Quality_flags</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-d52a7be3-b110-49f3-9ca5-8227a691b93c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d52a7be3-b110-49f3-9ca5-8227a691b93c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aafdeacf-81c8-41a2-bad6-6237af2f88d7' class='xr-var-data-in' type='checkbox'><label for='data-aafdeacf-81c8-41a2-bad6-6237af2f88d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>description :</span></dt><dd>Bitwise flag for each velocity component, where a value of 1 for a particular component signifies that calibration was successful, and that the baseline 1-sigma noise level is less than or equal to 100 m/s at 2 Hz. Electric field quality can be assessed from these flags according to -vxB. Bit0 (least significant) = Vixh, bit1 = Vixv, bit2 = Viy, bit3 = Viz. Refer to the release notes for details.</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vicrz</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.6583 -0.6613 ... -0.7706 -0.7679</div><input id='attrs-d7c195cc-1c50-4057-b35d-3939ae8535ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c195cc-1c50-4057-b35d-3939ae8535ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc01c281-95fc-4c69-9c5a-c37d033e80ff' class='xr-var-data-in' type='checkbox'><label for='data-fc01c281-95fc-4c69-9c5a-c37d033e80ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion drift corotation signal z component in satellite-track coorinates. This has been removed from ion drift and electric field.</dd></dl></div><div class='xr-var-data'><pre>array([-0.6583297 , -0.6612539 , -0.66417783, ..., -0.7732744 ,\n",
" -0.7705635 , -0.7678632 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vixh</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.369e+03 ... -4.744e+03</div><input id='attrs-d7c74d19-6bf7-4df5-980e-aa7f0bf1e7b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c74d19-6bf7-4df5-980e-aa7f0bf1e7b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d27fc30-59b4-4772-b280-823f95706d41' class='xr-var-data-in' type='checkbox'><label for='data-3d27fc30-59b4-4772-b280-823f95706d41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Along-track ion drift from horizontal TII sensor in satellite-track coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([-4369.472 , -4536.6055, -4604.6274, ..., -4788.499 , -4790.931 ,\n",
" -4743.668 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Evy</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-304.6 -303.1 ... -208.1 -205.5</div><input id='attrs-27c0e51a-c108-4430-8785-f71cdf3ffab2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27c0e51a-c108-4430-8785-f71cdf3ffab2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d77a225-583b-418f-94ba-6c821dbd3d99' class='xr-var-data-in' type='checkbox'><label for='data-1d77a225-583b-418f-94ba-6c821dbd3d99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field y component in satellite-track coordinates, derived from -VxB with along-track ion drift from vertical sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-304.62027, -303.07812, -311.11426, ..., -205.25725, -208.14996,\n",
" -205.50984], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vixh_error</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-14.85 -14.85 ... -14.85 -14.85</div><input id='attrs-43fb0fbc-283a-4e70-b27a-184f61759840' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43fb0fbc-283a-4e70-b27a-184f61759840' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec5c6838-ac54-435e-b781-db031f7c2c48' class='xr-var-data-in' type='checkbox'><label for='data-ec5c6838-ac54-435e-b781-db031f7c2c48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Random error estimate for along-track ion drift from horizontal TII sensor in satellite-track coordinates. Negative value indicates no estimate available.</dd></dl></div><div class='xr-var-data'><pre>array([-14.849242, -14.849242, -14.849242, ..., -14.849242, -14.849242,\n",
" -14.849242], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vicrx</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-19.13 -19.12 ... -24.47 -24.46</div><input id='attrs-3927c093-81ae-4308-b291-525f3ff6e553' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3927c093-81ae-4308-b291-525f3ff6e553' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0f2a05e-55d6-4cf6-bbb4-c0e94f16e5ad' class='xr-var-data-in' type='checkbox'><label for='data-d0f2a05e-55d6-4cf6-bbb4-c0e94f16e5ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion drift corotation signal x component in satellite-track coorinates. This has been removed from ion drift and electric field.</dd></dl></div><div class='xr-var-data'><pre>array([-19.13314 , -19.119896, -19.106642, ..., -24.473228, -24.467243,\n",
" -24.461264], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vixv</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-6.378e+03 ... -4.731e+03</div><input id='attrs-ae61e086-a556-47e0-aeed-d68c6372adc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae61e086-a556-47e0-aeed-d68c6372adc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86455d7e-16c4-4e1a-b3aa-2fc67f6eb609' class='xr-var-data-in' type='checkbox'><label for='data-86455d7e-16c4-4e1a-b3aa-2fc67f6eb609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Along-track ion drift from vertical TII sensor in satellite-track coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([-6378.092 , -6341.0054, -6508.6826, ..., -4725.7544, -4759.509 ,\n",
" -4730.5474], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude_QD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>75.22 75.19 75.16 ... 65.81 65.84</div><input id='attrs-7bf9d1af-7868-4233-b1ce-353e314bcc05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bf9d1af-7868-4233-b1ce-353e314bcc05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb5ee3f8-8125-48d8-a689-1bb042c99794' class='xr-var-data-in' type='checkbox'><label for='data-cb5ee3f8-8125-48d8-a689-1bb042c99794' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Quasi-dipole magnetic latitude.</dd></dl></div><div class='xr-var-data'><pre>array([75.22192 , 75.19315 , 75.164375, ..., 65.773445, 65.80656 ,\n",
" 65.83968 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Viz_error</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-14.85 -14.85 ... -14.85 -14.85</div><input id='attrs-b7f3b75c-1cfc-4c0f-84c8-64e5464147e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7f3b75c-1cfc-4c0f-84c8-64e5464147e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffea1297-01da-4436-a17c-1f0f0316e7a2' class='xr-var-data-in' type='checkbox'><label for='data-ffea1297-01da-4436-a17c-1f0f0316e7a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Random error estimate for cross-track vertical ion drift from vertical TII sensor in satellite-track coordinates. Negative value indicates no estimate available.</dd></dl></div><div class='xr-var-data'><pre>array([-14.849242, -14.849242, -14.849242, ..., -14.849242, -14.849242,\n",
" -14.849242], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Latitude</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.1 80.07 80.04 ... 64.75 64.78</div><input id='attrs-1a083533-197a-4d33-af7a-5c7d6ed468ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a083533-197a-4d33-af7a-5c7d6ed468ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27701427-5032-4fa1-ad16-f99c6510768e' class='xr-var-data-in' type='checkbox'><label for='data-27701427-5032-4fa1-ad16-f99c6510768e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Geocentric latitude.</dd></dl></div><div class='xr-var-data'><pre>array([80.103966, 80.07295 , 80.04193 , ..., 64.718864, 64.75087 ,\n",
" 64.78288 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MLT_QD</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>17.15 17.15 17.16 ... 4.769 4.769</div><input id='attrs-fd6553d0-7872-4a36-861f-7080ec898c5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd6553d0-7872-4a36-861f-7080ec898c5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f57cc544-774b-4a0e-b5a3-cee8020ebada' class='xr-var-data-in' type='checkbox'><label for='data-f57cc544-774b-4a0e-b5a3-cee8020ebada' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hour</dd><dt><span>description :</span></dt><dd>Magnetic local time.</dd></dl></div><div class='xr-var-data'><pre>array([17.152279 , 17.15396 , 17.155634 , ..., 4.770182 , 4.769397 ,\n",
" 4.7686114], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vicry</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>83.12 83.39 83.66 ... -210.3 -210.1</div><input id='attrs-4aa0e656-9f4b-4ab7-9fe8-355867df0b5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4aa0e656-9f4b-4ab7-9fe8-355867df0b5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93759c4a-f194-481b-be7c-fd26448aa5b8' class='xr-var-data-in' type='checkbox'><label for='data-93759c4a-f194-481b-be7c-fd26448aa5b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Ion drift corotation signal y component in satellite-track coorinates. This has been removed from ion drift and electric field.</dd></dl></div><div class='xr-var-data'><pre>array([ 83.11526 , 83.38985 , 83.664406, ..., -210.56429 ,\n",
" -210.31236 , -210.06041 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Viz</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>240.2 134.0 139.6 ... -821.6 -967.5</div><input id='attrs-4c8854f5-89c0-4588-b06b-65f0c55df7f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c8854f5-89c0-4588-b06b-65f0c55df7f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cdada20-c4d3-4cc5-946c-4d333f744ae8' class='xr-var-data-in' type='checkbox'><label for='data-3cdada20-c4d3-4cc5-946c-4d333f744ae8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Cross-track vertical ion drift from vertical TII sensor in satellite-track coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([ 240.19716, 134.01064, 139.63284, ..., -958.19977, -821.6499 ,\n",
" -967.49774], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Viy</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.121e+03 2.196e+03 ... 1.317e+03</div><input id='attrs-c5b0a350-1eae-4b1b-a422-368dcbc70070' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5b0a350-1eae-4b1b-a422-368dcbc70070' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9898e84c-4b0f-4f61-8ac8-2b1ce0999d35' class='xr-var-data-in' type='checkbox'><label for='data-9898e84c-4b0f-4f61-8ac8-2b1ce0999d35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Cross-track horizontal ion drift from horizontal TII sensor in satellite-track coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([2120.916 , 2195.6538, 2149.8809, ..., 1381.8344, 1413.2754,\n",
" 1317.4438], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VsatE</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.979e+03 1.972e+03 ... 619.0 620.2</div><input id='attrs-a10ac39c-1d61-461a-9dc0-1884c0eae342' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a10ac39c-1d61-461a-9dc0-1884c0eae342' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a155c7bc-b533-4f4b-9274-b411df9cde46' class='xr-var-data-in' type='checkbox'><label for='data-a155c7bc-b533-4f4b-9274-b411df9cde46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Satellite velocity E component in north-east-centre coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([1978.69 , 1972.0377, 1965.4293, ..., 617.733 , 618.9672,\n",
" 620.2036], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Evx</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-101.9 -105.3 ... -65.88 -61.85</div><input id='attrs-77323c91-afe9-4a3d-8b87-747df7bb8e26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77323c91-afe9-4a3d-8b87-747df7bb8e26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58028a11-78e4-40f0-9fd2-83292d47b52f' class='xr-var-data-in' type='checkbox'><label for='data-58028a11-78e4-40f0-9fd2-83292d47b52f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field x component in satellite-track coordinates, derived from -VxB with along-track ion drift from vertical sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-101.939255, -105.30731 , -103.13785 , ..., -64.735245,\n",
" -65.88076 , -61.85222 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ehz</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-13.0 -13.5 -13.56 ... 23.66 22.61</div><input id='attrs-8212308c-f104-4ae2-8377-10b063a0107a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8212308c-f104-4ae2-8377-10b063a0107a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d536b9c-b065-4d00-9309-b9b3ba1dc288' class='xr-var-data-in' type='checkbox'><label for='data-8d536b9c-b065-4d00-9309-b9b3ba1dc288' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field z component in satellite-track coordinates, derived from -VxB with along-track ion drift from horizontal sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-13.000871, -13.498644, -13.564169, ..., 23.398798, 23.662386,\n",
" 22.609276], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VsatN</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.367e+03 -7.369e+03 ... 7.606e+03</div><input id='attrs-fba937d8-d76b-4d03-b0d2-407461580a0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fba937d8-d76b-4d03-b0d2-407461580a0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d5aa1b4-a39b-4cc7-9291-e8cb2b35d33e' class='xr-var-data-in' type='checkbox'><label for='data-2d5aa1b4-a39b-4cc7-9291-e8cb2b35d33e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Satellite velocity N component in north-east-centre coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([-7367.4854, -7369.2725, -7371.0405, ..., 7606.1753, 7606.067 ,\n",
" 7605.9585], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Evz</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-17.08 -17.17 -17.44 ... 23.6 22.58</div><input id='attrs-b1dcc217-7c2d-4add-bbfa-4b071295ef4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1dcc217-7c2d-4add-bbfa-4b071295ef4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ce1cc5a-fce2-4004-be17-482b8c566e11' class='xr-var-data-in' type='checkbox'><label for='data-9ce1cc5a-fce2-4004-be17-482b8c566e11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field z component in satellite-track coordinates, derived from -VxB with along-track ion drift from vertical sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-17.083946, -17.166695, -17.435713, ..., 23.26466 , 23.595432,\n",
" 22.58133 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Calibration_flags</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>50529027 50529027 ... 50529027</div><input id='attrs-538d1864-bc90-4150-9546-2394d45708bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538d1864-bc90-4150-9546-2394d45708bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dccbc547-4154-4fb4-ba5a-7c5309f7315d' class='xr-var-data-in' type='checkbox'><label for='data-dccbc547-4154-4fb4-ba5a-7c5309f7315d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>description :</span></dt><dd>Information about the calibration process. Refer to the release notes for details.</dd></dl></div><div class='xr-var-data'><pre>array([50529027, 50529027, 50529027, ..., 50529027, 50529027, 50529027],\n",
" dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Viy_error</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-14.85 -14.85 ... -14.85 -14.85</div><input id='attrs-9c48c696-796c-48a8-9a67-f42830e7b1da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c48c696-796c-48a8-9a67-f42830e7b1da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e992d7ce-02b0-4286-b10a-9a85b208a985' class='xr-var-data-in' type='checkbox'><label for='data-e992d7ce-02b0-4286-b10a-9a85b208a985' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Random error estimate for cross-track horizontal ion drift from horizontal TII sensor in satellite-track coordinates. Negative value indicates no estimate available.</dd></dl></div><div class='xr-var-data'><pre>array([-14.849242, -14.849242, -14.849242, ..., -14.849242, -14.849242,\n",
" -14.849242], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>By</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.033e+03 -2.033e+03 ... 2.129e+03</div><input id='attrs-07e366c0-141f-496a-8713-7afe4e778d54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07e366c0-141f-496a-8713-7afe4e778d54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a10d550-6ced-4856-a778-d15b0970cabf' class='xr-var-data-in' type='checkbox'><label for='data-1a10d550-6ced-4856-a778-d15b0970cabf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>nT</dd><dt><span>description :</span></dt><dd>Geomagnetic field y component in satellite-track coordinates, derived from the 1 Hz product.</dd></dl></div><div class='xr-var-data'><pre>array([-2032.7795, -2032.8347, -2033.3342, ..., 2137.1267, 2133.3162,\n",
" 2128.9656], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radius</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.806e+06 6.806e+06 ... 6.807e+06</div><input id='attrs-ddbdc6f4-db1b-4b01-a125-6a121732761d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddbdc6f4-db1b-4b01-a125-6a121732761d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f33de77d-4394-4197-a5e6-82e4439d63bf' class='xr-var-data-in' type='checkbox'><label for='data-f33de77d-4394-4197-a5e6-82e4439d63bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Geocentric radius.</dd></dl></div><div class='xr-var-data'><pre>array([6805732.5, 6805734.5, 6805735.5, ..., 6807047. , 6807043. ,\n",
" 6807040. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ehy</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-208.5 -216.8 ... -209.6 -206.1</div><input id='attrs-b1a58387-46ab-45a2-87f7-f8ac201a820d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1a58387-46ab-45a2-87f7-f8ac201a820d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b0cfd60-3a70-498b-98cf-66d116554fd2' class='xr-var-data-in' type='checkbox'><label for='data-5b0cfd60-3a70-498b-98cf-66d116554fd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field y component in satellite-track coordinates, derived from -VxB with along-track ion drift from horizontal sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-208.5411 , -216.75945, -220.02112, ..., -208.10353, -209.57594,\n",
" -206.1053 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Longitude</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>83.45 83.5 83.55 ... -143.5 -143.5</div><input id='attrs-0439b861-bec8-4d6b-8367-d22f529c5961' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0439b861-bec8-4d6b-8367-d22f529c5961' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e35840e0-441a-4f3b-b7f8-3a757e4f2bc2' class='xr-var-data-in' type='checkbox'><label for='data-e35840e0-441a-4f3b-b7f8-3a757e4f2bc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>description :</span></dt><dd>Geocentric longitude.</dd></dl></div><div class='xr-var-data'><pre>array([ 83.45204, 83.50035, 83.54835, ..., -143.52657, -143.52048,\n",
" -143.51434], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VsatC</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.364 5.38 5.396 ... -11.04 -11.03</div><input id='attrs-f4c5fda4-3082-4003-96d0-41628d9f3a09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4c5fda4-3082-4003-96d0-41628d9f3a09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf19f407-77e0-4575-9a38-0b3775feeb21' class='xr-var-data-in' type='checkbox'><label for='data-cf19f407-77e0-4575-9a38-0b3775feeb21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>description :</span></dt><dd>Satellite velocity C component in north-east-centre coordinates.</dd></dl></div><div class='xr-var-data'><pre>array([ 5.364216 , 5.380056 , 5.3958497, ..., -11.048979 ,\n",
" -11.039476 , -11.029797 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Bx</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.942e+03 -1.948e+03 ... 9.496e+03</div><input id='attrs-95fa31ce-17dd-4b64-8e67-4624cb0229f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95fa31ce-17dd-4b64-8e67-4624cb0229f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ac143bb-6fac-4fd5-b887-c599211308bd' class='xr-var-data-in' type='checkbox'><label for='data-9ac143bb-6fac-4fd5-b887-c599211308bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>nT</dd><dt><span>description :</span></dt><dd>Geomagnetic field x component in satellite-track coordinates, derived from the 1 Hz product.</dd></dl></div><div class='xr-var-data'><pre>array([-1941.9697, -1947.7678, -1954.2805, ..., 9527.154 , 9511.255 ,\n",
" 9495.771 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ehx</span></div><div class='xr-var-dims'>(Timestamp)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-101.9 -105.3 ... -65.88 -61.85</div><input id='attrs-e193d1e6-2609-40b9-bce6-0ae393082c7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e193d1e6-2609-40b9-bce6-0ae393082c7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acedac15-32c6-4e46-9a9c-6e067d734556' class='xr-var-data-in' type='checkbox'><label for='data-acedac15-32c6-4e46-9a9c-6e067d734556' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mV/m</dd><dt><span>description :</span></dt><dd>Electric field x component in satellite-track coordinates, derived from -VxB with along-track ion drift from horizontal sensor.</dd></dl></div><div class='xr-var-data'><pre>array([-101.939255, -105.30731 , -103.13785 , ..., -64.735245,\n",
" -65.88076 , -61.85222 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fb0a8f51-d945-43c0-9fed-d344ad8a74ec' class='xr-section-summary-in' type='checkbox' ><label for='section-fb0a8f51-d945-43c0-9fed-d344ad8a74ec' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Timestamp</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1f910085-36ce-4246-9d4c-629cf070167e' class='xr-index-data-in' type='checkbox'/><label for='index-1f910085-36ce-4246-9d4c-629cf070167e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2018-07-17 11:28:49.231500032',\n",
" '2018-07-17 11:28:49.731500032',\n",
" '2018-07-17 11:28:50.231500032',\n",
" '2018-07-17 11:28:50.731500032',\n",
" '2018-07-17 11:28:51.231500032',\n",
" '2018-07-17 11:28:51.731500032',\n",
" '2018-07-17 11:28:52.231500032',\n",
" '2018-07-17 11:28:52.731500032',\n",
" '2018-07-17 11:28:53.231500032',\n",
" '2018-07-17 11:28:53.731500032',\n",
" ...\n",
" '2018-07-17 15:59:55.231500032',\n",
" '2018-07-17 15:59:55.731500032',\n",
" '2018-07-17 15:59:56.231500032',\n",
" '2018-07-17 15:59:56.731500032',\n",
" '2018-07-17 15:59:57.231500032',\n",
" '2018-07-17 15:59:57.731500032',\n",
" '2018-07-17 15:59:58.231500032',\n",
" '2018-07-17 15:59:58.731500032',\n",
" '2018-07-17 15:59:59.231500032',\n",
" '2018-07-17 15:59:59.731500032'],\n",
" dtype='datetime64[ns]', name='Timestamp', length=32535, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa975699-0634-47ea-8f97-9543ee9686bf' class='xr-section-summary-in' type='checkbox' ><label for='section-aa975699-0634-47ea-8f97-9543ee9686bf' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Sources :</span></dt><dd>['SW_EXPT_EFIA_TCT02_20180717T112849_20180717T160504_0401']</dd><dt><span>MagneticModels :</span></dt><dd>[]</dd><dt><span>AppliedFilters :</span></dt><dd>[]</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (Timestamp: 32535)\n",
"Coordinates:\n",
" * Timestamp (Timestamp) datetime64[ns] 2018-07-17T11:28:49.2315000...\n",
"Data variables: (12/31)\n",
" Spacecraft (Timestamp) object 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'\n",
" Vixv_error (Timestamp) float32 -14.85 -14.85 ... -14.85 -14.85\n",
" Bz (Timestamp) float32 4.783e+04 4.784e+04 ... 4.539e+04\n",
" Quality_flags (Timestamp) uint16 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
" Vicrz (Timestamp) float32 -0.6583 -0.6613 ... -0.7706 -0.7679\n",
" Vixh (Timestamp) float32 -4.369e+03 -4.537e+03 ... -4.744e+03\n",
" ... ...\n",
" Radius (Timestamp) float32 6.806e+06 6.806e+06 ... 6.807e+06\n",
" Ehy (Timestamp) float32 -208.5 -216.8 ... -209.6 -206.1\n",
" Longitude (Timestamp) float32 83.45 83.5 83.55 ... -143.5 -143.5\n",
" VsatC (Timestamp) float32 5.364 5.38 5.396 ... -11.04 -11.03\n",
" Bx (Timestamp) float32 -1.942e+03 -1.948e+03 ... 9.496e+03\n",
" Ehx (Timestamp) float32 -101.9 -105.3 ... -65.88 -61.85\n",
"Attributes: (3)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ds = data.as_xarray()\n",
"ds"
]
},
{
"cell_type": "markdown",
"id": "5066ef77-7a0d-4ed2-a36b-921d70239f4b",
"metadata": {},
"source": [
"An example plot:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "8c253679-ebb8-4940-a0ff-2dfb63132f36",
"metadata": {
"execution": {
"iopub.execute_input": "2025-06-21T21:46:08.345836Z",
"iopub.status.busy": "2025-06-21T21:46:08.345471Z",
"iopub.status.idle": "2025-06-21T21:46:09.623271Z",
"shell.execute_reply": "2025-06-21T21:46:09.622623Z"
}
},
"outputs": [
{
"data": {
"image/png": 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DTCbD/v37YWlpqXVagYGBuH79Oi5cuCBavnHjRshkMvTs2bOi2dVI165dYWJigt9++020/P79+zh69KiosMPAwADdu3fH4cOHcfToUf6c69atG+rVq4eFCxfywau2WJPbd999F7/++qvSApMhQ4bg6NGjolGCc3Nz8ccff2DgwIGSI2qXx9nZGdeuXVMY0OvUqVMAwI+w7OzsLKqJb9OmTYXyxWrpJ0yYoPA3Q0NDhZp/CwsLjfeNOXfuHC5fvoyQkBCtjhEhhLwK6O5ICCES+vTpg4YNG+LNN99Ey5YtUVpaioSEBCxfvhzm5uaYMWMGv66+vj4CAgLw559/wt3dnW+K6O/vDyMjIxw5cgTTp08XpT9gwAD88ccfmDp1KoYPH46UlBR89tlncHJy4kd9rQ5r165FvXr1sGDBAlFwzUyePBnTp0/Hvn37JPsuAsA///yDwYMHw9HREQsWLEBCQoLo715eXloHmaNGjcL169fxyy+/ICUlRRSINGzYkA9i1DFr1ixs3LgR/fv3x+LFi+Hm5oZ9+/bhp59+wvvvv4/mzZtrlUdtWVtbY9GiRViwYAHGjBmDt99+G5mZmYiIiICxsTFfY88EBgZizpw5AMDXoJqYmPAjHHt7eyuMvBweHo6IiAjExsaiR48eSvOyY8cOTJgwAT4+Ppg8ebJotGsAaNeuHV8AMXfuXGzatIk/jkZGRli6dCkKCgoUphO6fv06rl+/DqCscCYvLw87d+4EUHZesBGdZ86cicGDB6N3796YNWsW7O3tcfr0aXz55Zfw8vJCv379yj2emuQLeDldk5+fH9/vWxNxcXF49OgRgLLRre/du8fvW0BAAOrXry9aX1VgTAgh5P9V8wBPhBBSI23bto0bNWoU16xZM87c3JwzMDDgXF1dudGjR3PXr19XWP/777/nAHCTJk0SLe/duzcHgIuOjlb4zNKlS7nGjRtzRkZGnKenJ7dmzRp+dFwhANy0adMUPs9Gkz179qxoOUvj0aNHouUhISGcmZmZ0n1+9OgRZ2hoyA0ePFjpOmzE2jfffFPpOuWN8BsbG1tuXplWrVqJRgN2c3NTmm5YWJjSPLHPyo/Qeu/ePW7UqFGcnZ0dZ2BgwLVo0YL7+uuvuZKSEn4dZaP5chyn1nbVHQ2Y+fXXXzlvb2/O0NCQs7Ky4gYNGsRdu3ZNId1Lly5xALhmzZqJli9ZsoQDwM2ePVvhM3PmzOFkMhmXmJioMs8hISEqv0P5PN+6dYsbPHgwZ2lpyZmamnKBgYHc+fPnFdJVdW7IH8ejR49yr7/+Oufo6MiZmJhwzZs35+bMmcM9fvxYZd61yRfHvRw9ed26dWqnLxQQEKDWOc9xHJeXl8dZWVlx3bt312pbhBDyqpBxXAWHsiOEEEJIrdCpUye4ublhx44d1Z0VQgghpFwUrBJCCCGvgJycHNSvXx8JCQlaNXMlhBBCqhoFq4QQQgghhBBCahwaDZgQQgghhBBCSI1DwSohhBBCCCGEkBqHglVCCCGEEEIIITUOBaukVhs7dixkMhlkMhlat27NL2/cuLHCPHqJiYkYPXo0mjRpAmNjY9jb26N9+/YIDQ1FTk4OACA0NBQymQzp6emiz2ZlZUFPTw8GBgYKk9Tfv38fMpkMs2fPVjvfPXr04PMt/9O4cWN+vcWLF0Mmk+HgwYMKaWzbtg0ymQwrV64U7bcwLXNzc3Tu3BkbN24EAKxfv17pdpXlQZW7d++qTEf4HQi/K/mfvXv3itL75ptvJLcXHR0NmUwGOzs7FBYWqpVHdfMq/Ll79y4A4M6dOwgNDUXz5s1hYmICU1NTtGrVCgsXLsSDBw9w7NgxtdNknj17hpkzZ8LZ2RnGxsbw8fHB77//LsprSUkJvv32W/Tt2xcNGzaEqakpPD09MX/+fDx9+lSj/dYmrRUrVqBly5YwMjKCu7s7IiIi8OLFC9E69+/fx8yZMxEQEABra2vIZDKsX79eMr3CwkJ8/fXXaN26NczMzNCgQQP069cPJ0+eVFj3xYsXiIiIQOPGjWFkZISWLVtixYoVCuvJn+vCH2NjY9G6GzduxFtvvYUWLVpAT09P6fmt6hyVyWQ4ffq0xteQJsdp7969GDNmDNq0aQMDAwPReSN0/vx5TJs2DW3atIGFhQUaNGiAoKAgHD16VHL9Xbt2wd/fH7a2trC2tkanTp2wadMmyXWZhw8fws7ODjKZjJ8rVCg+Ph59+vSBhYUFzM3N0bNnT5w4cUJlmlKOHj2K8ePHo2XLljAzM4OLiwsGDRqE8+fPS65/4cIFBAUFwdzcHNbW1hg6dCju3LmjsF5kZCSGDh0Kd3d3yGQylXPKxsbGonfv3nBwcIC5uTm8vb3xww8/oKSkRGHdmJgYdO3aFaamprC3t8fYsWORkZEhWic8PFzluSG83q9du4apU6eia9euMDMzg0wmw7FjxxS2W969ZsqUKQCg9v2IbUOT4wQA//vf/xAQEABLS0uYmZmhVatW+OWXX7Q6TqruyfL3RKDsfjx06FBYW1vD3NwcvXv3xoULF1Tmt7zzWB2///47fHx8YGxsDGdnZ8ycOVPhPUDer7/+yj+Dpej6PA4PD1e4r/n4+PDHc8CAAWrtKyE1Ub3qzgAhFeXo6Ijdu3fD1NRU6ToXL16Ev78/PD098emnn6Jx48Z4/PgxLl26hN9//x1z586FpaUlevbsiR9//BHHjh3DW2+9xX8+Li4O9eqVXS7//PMP+vbty/8tNjYWANCzZ0+N8t2kSRNs3rxZYbmRkRH//wsWLEB0dDQmTpyIq1evwsrKCgCQlpaGqVOnomfPnpg2bZro8/7+/nywd//+fXzzzTcICQnB8+fPMXz4cJw6dUq0fteuXTF8+HDMmTNHMg/q+OCDDzBq1CiF5Q0bNhT9bmJiIvlC3bJlS7W2s3btWgBlhQd79uzByJEj1c6jk5OTwr5PnToV2dnZCt+Dk5MT9u7di7feegv29vYIDQ1Fu3btIJPJcOXKFaxbtw779u1DXFycQppDhgyBh4eH0oB76NChOHv2LJYuXYrmzZtjy5YtePvtt1FaWsofw/z8fISHh+Ptt9/GxIkTYW9vjwsXLuDzzz/Hn3/+iXPnzsHExESt/dY0rSVLlmDRokWYP38+Xn/9dZw9e5YPzoUvpbdu3cLmzZvh4+ODN954A1u3blWah0mTJmHz5s34+OOP0atXL2RlZWHp0qUICAjAiRMn0KlTJ9F3smnTJnz22Wfo2LEjDh48iBkzZiA3NxcLFizg19u9e7dCgUVycjJGjhyJIUOGiJZv2rQJ6enp6NSpE0pLSxUCb2bRokX8S7/Qm2++CSMjI3Ts2BEeHh4aXUOaHKfdu3fj9OnTaNeuHYyMjJQGbFu3bkV8fDzGjx+Ptm3b4vnz5/j5558RGBiIDRs2YMyYMfy669atw4QJEzBs2DAsXLgQMpmMX+fx48eYNWuW5DamTZumEPQzZ8+eRffu3fmgl+M4LFu2DIGBgYiNjUXXrl2V7qO8VatWITMzEzNmzICXlxcePXqE5cuXo0uXLjh48CB69erFr3vjxg306NEDPj4+2L59OwoKCvDpp5+iW7duSEhIQP369fl1f/75Z5iZmaFXr174888/lW4/JiYGffr0Qffu3bFmzRqYmZkhOjoaM2bMwO3bt/H999/z68bFxaFfv37o378//ve//yEjIwPz5s1DYGAgzp07x3/nEydOFD0jmEmTJuH27duiv507dw579uxBu3btEBgYqDSv7du3Vzjv2PHbuHEjf87Lr/PZZ58hNjZW4b7r5eWl0XECgKVLl+KTTz7BlClT8PHHH8PAwAA3btxAUVGRaD11jxMj9fxo1qyZ6PdHjx6hW7dusLGxwbp162BsbIwvv/wSPXr0wNmzZ9GiRQvJPKs6j9WxefNmvPvuu5g4cSK+++473Lx5E/PmzcP169dx6NAhyc88ePAAc+fOhbOzM7KzsxX+XhnnsZRNmzbh+fPnCvdDQmqdapzjlZAKCwkJ4dzc3BSWu7m5iSaYHzNmDGdmZsbl5ORIplNaWspxHMc9fvyYk8lk3OTJk0V/nz59Oufn58d17dqV++ijj0R/Gz9+PKenp8c9ffpU7XwHBARwrVq1Umvdq1evckZGRtyYMWP4ZW+88QZnYWHB3b17V7Sum5sb179/f9GyJ0+ecJaWllzTpk0l0wfATZs2Te28CyUlJXEAuK+//rrcdUNCQjgzMzOt00tLS+Pq1avH9erVizM2NuZ69+6tVZ6FlH0Pd+7c4czMzLh27dpJfq+lpaXcrl27JNOU+g6Yffv2cQC4LVu2iJb37t2bc3Z25oqLizmO47ji4mLu8ePHCp/fsWMHB4DbtGlTufvGaJLW48ePOWNjY+69994TrbtkyRJOJpNx165d45eVlJTw/3/27FkOABcVFaWwnYKCAk5fX5979913RctTU1M5ANz06dP5ZVevXuVkMhn3xRdfiNadNGkSZ2JiwmVmZqrc1/DwcA4AFxMTI1ouzGv//v0l7xnKHDt2jAPALVy4UOk6qq4hdY+T/LrTpk3jlD2iHz58qLCsuLiY8/b25jw8PETL/f39OTc3N1HapaWlXMuWLTlvb2/J9Hfu3MmZm5tzGzZs4ABwO3bsEP29T58+XIMGDbjnz5/zy3Jycjh7e3vOz89PMk1lpPYlNzeXa9CgARcYGChaPmLECM7e3p7Lzs7ml929e5czMDBQuC8L97dVq1ZcQECA5PbfeecdzsjIiHv27Jlo+euvv85ZWlqKlnXs2JHz8vLiXrx4wS87ceIEB4D76aefVO5nUlISJ5PJFK4DYT7ZNRkbG6syLaa0tJRr0qSJwvcrVN59V93jdO7cOU5PT4/76quvys2XusdJk+fHhx9+yBkYGIieednZ2Zy9vT0XHBws+ZnyzuPyFBcXc05OTtzrr78uWr5582YOALd//37Jzw0YMIB78803lR77yjiPw8LClN7XVD2TCKkNqBkweSVkZmbC0tJSaZMc1tzOzs4Obdq0UWiGdezYMfTo0QMBAQF8Tarwb+3bt+drPXWtVatWWLx4MTZu3Ijo6GisWbMG+/fvx7fffgs3N7dyP29tbY0WLVrg3r17lZK/qrJhwwYUFxdj1qxZGDp0KI4cOVJp+/Ttt9/i+fPn+OmnnyS/V5lMhqFDh2qc7u7du2Fubo4RI0aIlo8bNw6pqak4c+YMAEBfXx92dnYKn2c1kCkpKWpvU5O0/vrrLxQUFGDcuHEK+eM4Dnv27OGX6emp9/jQ09ODnp6ewnG0tLSEnp6eqNZjz5494DhOcvv5+fn466+/lG6H4zhERUWhSZMmoto4TfIqZe3atZDJZBg/frxWn9dk2+qu6+DgoLBMX18fvr6+CueGgYEBzM3NRWnLZDJYWlpK1jhlZWVh2rRpWLJkCVxdXSW3f+LECfTo0UPUmsXCwgLdu3fHyZMnkZaWptZ+KNsXc3NzeHl5ifaluLgYe/fuxbBhw2Bpackvd3NzQ8+ePbF7925RGuoeSwMDAxgaGiq0VLC2thYdnwcPHuDs2bMYPXo038oGAPz8/NC8eXOF7ctbt24dOI7DxIkTtcqnlNjYWNy5cwfjxo3TOh11P7dy5UoYGRnhgw8+ULleRY+TMrt370avXr1EzzxLS0sMHToUf/75J4qLi0Xrq3Mel+f06dNIS0tTuB+NGDEC5ubmkvvy22+/IS4uDj/99JNkmpV1HhNSl9FVQOqku3fvivpLdu3aFWlpaXjnnXcQFxeH/Px8pZ/t2bMn/v33X/6FKzMzE1euXEFAQAACAgJw4cIFvo9rSkoK7ty5o3ETYKa4uFjhp7S0VGG9OXPmoGvXrpg0aRJmz56Nfv36Kbz0KPPixQvcu3dP1LRI10pLSyX3RYr8OlL9wqSsW7cOTk5O6NevH8aPH4/S0lKlff8q6tChQ2jQoAG6dOmi03SvXr0KT09P0UscAHh7e/N/V4U15WvVqlWF8yKVFtt+mzZtROs6OTnB3t6+3PxJMTAwwNSpU7Fhwwbs2bMHOTk5uHv3LiZNmgQrKytMmjRJtP369evD0dFRlIY6xycmJgb37t3D+PHjlfb11FR2djZ27tyJwMBAuLu76yTNylJcXIzjx48rnBsffPABEhMTsWTJEjx69AiPHz/GN998g/Pnz2Pu3LkK6UyfPh3u7u4IDQ1Vuq2ioiLJrgJs2ZUrVyq0L9nZ2bhw4YJoX27fvo38/Hz+XBDy9vbGrVu3UFBQoPG2pkyZgqKiIkyfPh2pqal4+vQpNm3ahN27d+Ojjz7i12PnnrLtqzo32b2qadOmCAgI0DiPyqxduxZ6enoKwVRl+Pvvv+Hp6Yldu3ahRYsW0NfXR8OGDTF//nxRM2BtjtPSpUthaGgIU1NTvPbaa4iOjhb9PT8/H7dv31aaZn5+vkJ/T3XO4/Io2xcDAwO0bNlSYV8yMjIwc+ZMLF26VKELDFNZ53F4eDg/1gIhdQ0Fq+SVMHfuXAwePBhbt25Fjx49YGFhgfbt22PhwoV49OiRaF0WeLLa1bi4OOjr68PPzw/+/v4AgOPHjwPQvr8qUDawhoGBgcLPe++9p7Cuvr4+li9fjoyMDLx48QK//vqr0nQ5juMDQRYUZGRk4J133tE4j+qaN2+e5L78888/ovWeP3+usI46L2/Hjx/HzZs3ERISAn19ffTq1Qvu7u6IiooCx3E635/k5ORKCU4yMzNha2ursJwty8zMVPrZBw8eYP78+ejQoUOFB8tQllZmZiaMjIxgZmYmmUdV+VPlu+++w+zZszFs2DBYWVnB3d0dJ06cwNGjR9G0aVPR9qWOj5mZGQwNDVVuf+3atdDX18fYsWO1yqOUrVu3Ij8/HxMmTNBZmpUlPDwct27dQlhYmGj50KFD8ccff+Drr7+Gg4MD6tevj08//RQbNmxQqOHft28ftm/fjjVr1qis0fHy8sLp06dFBWvFxcV8ywBtzxNm2rRpeP78OT755BN+GUtT2fXDcRyePHmi8bY6d+6Mo0ePYvfu3XBxcYGNjQ3GjRuHJUuWiPogl7d9Vft86NAhpKSk6PQ8evr0Kf744w/07t1b65pDTTx48AD//fcfpk+fjunTpyMmJgZjx47FN998IwqWNTlORkZGmDRpElatWoWjR4/i119/RUlJCQYNGiR6xj158gQcx6l971T3PC6Ppt/51KlT0aJFC7z//vtap6nteUxIXUYDLJFXgpGREXbv3o3ExEQcPHgQ586dQ1xcHJYsWYKff/4ZJ06c4AdoCAgIgJ6eHo4dO4a3334bx44dQ4cOHfgmxO3bt0dsbCz69++PY8eOoV69enjttdc0zpOHh4fkiIfKakAjIyOhp6eHwsJC/P3336IBoIT2798PAwMD/ncTExN88MEH+PzzzzXOo7pmzJiBd999V2G5/MBJJiYm+Pvvv0XLLCwsyk2fDazEmmLKZDKMHTsWYWFhOHLkCIKCgrTNepVTVeun7G9ZWVl44403wHEctm3bVqEXsPLS0iZ/5VmyZAm++eYbhIeHo1u3bsjJycHKlSvRu3dvHDp0CO3atavQ9tmAW3379oWLi4tWeZSydu1a2NnZ1fgBSn799Vc+uBo0aJDob3/99RfeffddjBgxAsHBwahXrx6io6MxduxYFBUV8YFGdnY2Jk+ejHnz5olGVpfywQcfYMKECQgNDcUnn3yC0tJSRERE8M3yK3J+Llq0CJs3b8aKFSvg6+ur8Hddn5/nz5/HkCFD0LlzZ6xevRpmZmY4evQoFi5ciIKCAixatEitbaja9tq1a1GvXj2dFqRs3rwZBQUFarewqajS0lLk5uZi69at/LOnZ8+eeP78OSIjIxERESEqeFLnODk5OSmMJDxixAh07twZ8+fPx9ixY0WtUNT57jU5j9Wlzr7s2rULf/75Jy5evKjWeVgZ91lC6ioKVskrxdPTE56engDKaiAjIyMxe/ZsLFq0CNu3bwdQ1lfJx8eHrzVlgSkj7LcaGxuLDh06qBVwyTM2NkaHDh3UWnfHjh3Yvn07IiMjsWfPHoSGhqJnz55o0KCBwrqvvfYavvvuO8hkMpiamsLDwwOGhoYa508TDRs2VGtf9PT01N5nJjc3Fzt27ECnTp1Qv359frqVIUOGIDw8HGvXrtV5sOrq6oqkpCSdpgmU9YmWqoHJysoCIF3a/uTJE/Tu3RsPHjzA0aNH0aRJE623X15adnZ2KCgoQF5ensLo2llZWZLBQ3kSExPx6aefYtmyZaJmp/369YOXlxdmz57NX092dnZISEhQSOP58+coKiqSPD5AWT+xwsJCnb64X758GefOncOMGTM0Hh27KkVFRWHy5Ml477338PXXX4v+xnEcxo8fj+7du2PdunX88qCgIGRnZ+ODDz5AcHAwzMzM8Mknn8DAwAChoaH8Ncam58jLy8PTp09hZWXF99999OgRPv/8c6xatQpAWVeLuXPn4quvvtK6wCAiIgKff/45lixZotB8k/W7Vnb9yGQyWFtba7zNadOmoUGDBti9ezf09fUBlAVhenp6CA8PxzvvvIMmTZqUu31l5+bjx48RHR2N/v37KzRvr4i1a9eifv36CoUTlcXOzg7p6eno06ePaHm/fv0QGRmJCxcuoGnTplofJ8bAwAAjR47E/Pnz8d9//8HT0xM2NjaQyWRq3Ts1OY/V2We2L/LPWuG+PHv2DNOmTcMHH3wAZ2dnfrusefTTp09hYGAAMzOzSjuPCanLqBkweWXJZDLMmjUL1tbWCn1Pevbsif/++w+XL1/GtWvXRE1VAwICcPHiRVy+fBl3797Vur+quh4+fIipU6eiR48emD59OtatW4eCggKlTY2srKzQoUMH+Pr6wtPTs9ID1cq2detW5OXlIT4+HjY2NvyPt7c3OI7D7t27dd5sqk+fPnj48CFOnz6t03TbtGmDxMREhf68rI+ffE3AkydPEBQUhKSkJBw+fFiyn5O61EmL9VWV73OYnp6Ox48fa1VTcenSJXAch44dO4qWGxgYoG3btqJrr02bNnj06JHCPMfKjg+zdu1aNGjQQKdzCbLa/KqqudJGVFQUJk6ciJCQEPz8888KL+APHz5EWlqaaGogpmPHjnj+/Dnfz+3q1au4e/cuHB0d+WvszTffBACEhITAxsZGNA3HvHnz8PjxY1y5cgV3797FyZMn8eTJE5iZmWlVqBEREYHw8HCEh4eLpihiPDw8YGJiItkf9sqVK2jatKlWU5QkJCTA19eXD1SZjh07orS0FImJiQBennvKtq/s3Ny0aROKiop0eh5dvHgRFy9exJgxY0StaCqTsnsP64bBatO1PU6q0jQxMUHTpk2VpmliYsIXvGl6Hqui7H5YXFyMGzdu8Pvy+PFjPHz4EMuXLxc9o7Zu3Yrnz5/DxsaG74ZTWecxIXUZBavklaBsdMrU1FTk5OTA2dlZtJwFoBEREdDT0xM182X/HxERIVq3skyZMgUFBQVYt24dZDIZ3N3d8dVXX2H37t2SzYjrmrVr18LCwgJHjhxBbGys6Ofrr79GYWGh5Hy1FTFr1iyYmZnx87DKY0GypoYMGYJnz55h165douUbNmyAs7MzOnfuzC9jweWdO3cUmspqSt20+vbtC2NjY4WBq9avXw+ZTIbBgwdrvG12bckH/oWFhbhw4YJoIJJBgwbx84DKb9/ExERy7spz587h8uXLCAkJURi4SluFhYX47bff0KlTJ501JdS19evXY+LEiXj33Xfx66+/StYU2djYwNjYWLLQ5dSpU9DT04OTkxOAsm4G8tfXd999B6CsP2xsbKzCaOpGRkZo3bo13NzckJycjG3btmHSpElqzwHMfPbZZwgPD8fChQsV+twy9erVw5tvvok//vgDubm5/PLk5GTExsZqNTo3UHZ+njt3TmGgNzZfKTs/XVxc0KlTJ/z222+idU+fPo1///1X6fbXrl0LZ2dn9OvXT6v8KUsTQJX2pR42bBgA4MCBA6Ll+/fvh56eHl8Ype1xYl68eIFt27bB3t5e1Kx4yJAhOHr0qGiE6NzcXPzxxx8YOHAgf+1rcx4r07lzZzg5OSncD3fu3Ilnz57x++Lo6KiwzdjYWPTp0wfGxsaIjY3lu+FU1nlMSF1GzYDJK+G9997D06dPMWzYMLRu3Rr6+vq4ceMGvvvuO+jp6WHevHmi9bt37w59fX3s3r1boZmvtbU12rZti927d8PAwIAfdElT+fn5Smvu2Ci0mzZtwp49e/Dzzz+LBvyZOnUqdu7cqbI5cFVKTk6W3Jf69evDw8ND63SvXr2K+Ph4vP/++wrTkQCAv78/li9fjrVr11Zo1Ed57u7u+P333zFy5Ej4+PggNDSUD/CuX7/OT0OhaV/Gfv36oXfv3nj//feRk5ODpk2bYuvWrfjrr7/w22+/8bU7+fn56NOnDy5evIjIyEgUFxeLjq8mx1WTtGxtbbFw4UIsWrQItra2eP3113H27FmEh4dj4sSJ8PLyEqW9c+dOAOBH4jx37hz/Ijh8+HAAZYU7HTt2RHh4OPLy8tC9e3dkZ2djxYoVSEpKwqZNm/j0WrVqhQkTJiAsLAz6+vro2LEjDh06hF9++QWff/65ZBNCdV7cr1+/juvXrwMoqyXOy8vj8+7l5aWwX3v27EFWVpbOasPUOU4AcO/ePZw9exZA2aihws82btyYb0K/Y8cOTJgwAT4+Ppg8eTLi4+NF22vXrh2MjIxgZGSEqVOn4ttvv8WYMWMwcuRI6OvrY8+ePdiyZQsmTJjAH1MfHx+l+W/VqhV69OjB/3716lXs2rULHTp0gJGRES5duoSlS5eiWbNm+OyzzzQ6NsuXL8enn36Kvn37on///gr3EeGI3BEREejYsSMGDBiA+fPno6CgAJ9++ins7e1FgyEBZceY1Rrn5OSA4zj+WHbs2JGfAmXWrFmYPn063nzzTUyePBmmpqY4cuQIli9fjqCgILRt25ZP86uvvkLv3r0xYsQITJ06FRkZGZg/fz5at24tOSLvmTNncO3aNSxYsECh5pbJy8vD/v37Abws0ImLi8Pjx49hZmamEOQWFBRgy5Yt8PPz47u0VIS6x2ncuHFYvXo1pk6disePH8PLywsxMTH48ccfMXXqVNGUMuoep9mzZ+PFixfw9/eHo6MjUlJSsGLFCiQkJCAqKkp0zObOnYtNmzahf//+WLx4MYyMjLB06VIUFBSIRv7X5Dwuj76+PpYtW4bRo0dj8uTJePvtt/Hff//ho48+Qu/evfnCM2NjY8l0169fD319fYW/VcZ5TEidVpWTuhKiayEhIUonwhY6ePAgN378eM7Ly4uzsrLi6tWrxzk5OXFDhw7lTp06JfmZTp06cQC4uXPnKvxt5syZHADO399fq3wHBARwAJT+vHjxgnvw4AFnbW2tMCE5c+fOHc7MzIwbMmQIv0ybyb8BcNOmTdNqP9ik7sp+3nnnHX7d8ianF6bHJolnxzkhIUHpZ+bPn88B4M6fP69x/gMCArhWrVop/fvt27e5qVOnck2bNuWMjIw4ExMTzsvLi5s9ezaXlJQk+ZnyvoPc3Fxu+vTpnKOjI2doaMh5e3tzW7duFa1T3nENCQlRex+1Sev777/nmjdvzhkaGnKurq5cWFgYV1RUpLCeqnSFnj59yn3yySecp6cnZ2pqyjk4OHA9evTg9u/fr5BmUVERFxYWxrm6unKGhoZc8+bNuR9++EFy3/Ly8jgrKyuue/fuKo9BWFiY0nyGhYUprN+7d2/OzMyMy8nJUZmu8DiouobUPU5RUVFqfU8hISEq0xSemyUlJdyaNWu4Dh06cNbW1pylpSXXrl07buXKlZLfqVBsbCwHgNuxY4do+b///st1796ds7W15QwNDbmmTZtyCxcu5J49e6bW8RIq714o79y5c1xgYCBnamrKWVpacoMHD+Zu3bqlsJ6qYxQVFSVad9euXdxrr73G2dvbc2ZmZlyrVq24zz77THJ/Dh06xHXp0oUzNjbmbG1tuTFjxnAPHz6U3LdJkyZxMpmMu337ttL9V3V9Sj3bNm/ezAHg1q1bpzRN+eOg6r6ryXHKzMzkJk+ezDVo0IAzMDDgmjdvzn399ddcSUmJQrrqHKe1a9dynTp14mxtbbl69epxNjY2XJ8+fbiDBw9K5vXWrVvc4MGDOUtLS87U1JQLDAxU676v7DxW15YtWzhvb2/O0NCQc3R05KZPn87l5uaW+zlVx74yzmNltHkvIKQmkXFcJcz7QEgVGTt2LI4dO4Zbt25BJpMpLb0mhBBCCHlVlJSUgOM4NG3aFK1bt8bevXurO0uEaIX6rJJa7969e/xgLYQQQgghrzpfX18YGBjwU0oRUltRzSqp1e7evYvHjx8DKBsxsFWrVtWaH1aSqUxtqf3lOE5hwBF5+vr6NWo+uNLSUpSWlqpcR1cD8NQUdeV8I3XPq3g9ktpDfkR2eXp6ehWaL7gmuH79OvLy8gCUjbUhHLCKkNqkdl+J5JXHBh3p0KFDtQeqQNmw9AYGBkp/AgMDqzuLaomLi1O5HwYGBgojtla38ePHl5vnuqaunG+k7lm8eHG51yMbOIaQqnT37t1yz83FixdXdzYrzMvLi38/okCV1GZUs0qIDl25cgWFhYVK/25hYYEWLVpUYY60k5ubi3///VflOu7u7vwE5zWBsJZdGTaaal1RV843UvekpqYiNTVV5Tre3t61fh5oUvsUFRXh8uXLKtdxdnZWmNKOEFI9KFglhBBCCCGEEFLjUDNgQgghhBBCCCE1DgWrhBBCCCGEEEJqHApWCSGEEEIIIYTUOBSsEkIIIYQQQgipcShYJYQQQgghhBBS41CwSgghhBBCCCGkxqFglRBCCCGEEEJIjUPBKiGEEEIIIYSQGoeCVUIIIYQQQgghNQ4Fq4QQQgghhBBCahwKVgkhhBBCCCGE1DgUrBJCCCGEEEIIqXEoWCWEEEIIIYQQUuNQsEoIIYQQQgghpMahYJUQQgghhBBCSI1DwSohhBBCCCGEkBqHglVCCCGEEEIIITUOBauEEEIIIYQQQmocClYJIYQQQgghhNQ4FKwSQgghhBBCCKlxKFglhBBCCCGEEFLjULBKCCGEEEIIIaTGoWCVEEIIIYQQQkiNQ8EqIYQQQgghhJAah4JVQgghhBBCCCE1DgWrhBBCCCGEEEJqHApWCSGEEEIIIYTUOBSsEkIIIYQQQgipcShYJYQQQgghhBBS41CwSgghhBBCCCGkxqFglRBCCCGEEEJIjUPBKiGEEEIIIYSQGoeCVUIIIYQQQgghNU696s7Aq6q4uBgXL15EgwYNoKdHZQaEEEIIIYS8qkpLS/Hw4UO0a9cO9epRiMbQkagmFy9eRKdOnao7G4QQQgghhJAaIj4+Hh07dqzubNQYFKxWkwYNGgAoOyGdnJyqOTeEEEIIIYSQ6pKWloZOnTrxMQIpQ8FqNWFNf52cnNCwYcNqzg0hhBBCCCGkulH3QDE6GoQQQgghhBBCahwKVgkhhBBCCCGE1DjUDJgQbXzVDMjPqO5cVLlSAHr6xsCsq4B5/erODiGEEELIK+2nn37C119/jbS0NLRq1QqRkZHo1q1bdWdLZyhYJZUn9hsg7rPqzgXRkdL//08pCqD3TdPqzk4V0wPePwk08KzujBBCCCGEAAC2bduGmTNn4qeffoK/vz9Wr16Nfv364fr163B1da3u7OmEjOM4rroz8Sq6f/8+GjVqhJSUlLo7wFK4VXXngOhIKcr6DLB/Va1DCKmFmg0A3tlc3bkghJBXljaxQefOndG+fXusWrWKX+bp6YnBgwfjyy+/rKysVimqWSWVJ2BR3a5ZfUWaw6Zk5aHbslgc/6gnGv3aDshLVwhM+VpXPQpYCamV/ttLBYyEkNrNuD4w/1Z156LCcnNzkZOTw/9uZGQEIyMjhfWKiopw/vx5zJ8/X7T89ddfx8mTJys9n1WFglVSeXrOLfshOpGSlYdGtqbVm4eJFwEA3ZbFYvvkLujkbsfnKz4pE8GrT5cFtdWcT536phXw7H5154IQQgghqhQ8qu4c6ISXl5fo97CwMISHhyus9/jxY5SUlCjMy9qgQQOkp6dXZharFAWrpNrUhOCrqmm7z5oEgpVxXI9/1BMA+BrWlaN8ELz6NLZP7sL/28ndjl+P5aFOfMdzr1VKspV5bOrEcSdVY9sEIHFndeeCEEIqzrhutHS7fv06XFxc+N+lalWFZDKZ6HeO4xSW1WYUrJIqIf/yLGpaWsNeqlW96Kdk5QEA/3dNggJV+yx1fITbYAGhOoFqecc1PikTndztyt03+fSAsqA1LTsfoVsSsHKUD5ysTACAD6Qv3X+C0C0JAKAQyKoilSddBVw1KXATBvGanv9S3498uuz/a+q1RRRV+/k5ci2AtdW3fUIIISIWFhawtLQsdz17e3vo6+sr1KJmZGQo1LbWZtS9jFQ69vKckpWH+KRMxCdlAnhZW6fqc1VNmFfhMvbTbVks/3epdeXTkqcsUBWmE5+UKfq9ka0pjn/Us9yAj730KgtSUrLysPfyAwSvPs1/B8L9E+4b08jWFBEDPXHp/hN0WxaLS/efIHj1aUQM9ETolgSkZefz6+66kIzQLQkY5182+tyBq6kAygJZ4TGUx2qN5fOk6tiqg51v3ZbFYsPJO9hw8g7ikzL541DV55fwe2XfE8un8F8pUt8P+3fv5Qf8PjLyBRvVcS2R8mlzntN3SQghBAAMDQ3h6+uLw4cPi5YfPnwYfn5+1ZQr3aPRgKvJKzEaMMQvVsJaNwDo19oBB65miIIrZTVPwuWAdO2Suvkpr9Y0LTufDwxZPgBg5SgfZD4rRFh0Il9byAKsjNwCDPB2EaUjrJFkv8v382RYzSLbnjq1kULlNRMW7sfMIA8Ma18WULLvZPvkLnwtKfDy+G44eQdh0YkAgHH+rog6kSxKd+UoHwAQfa/Ay+92ZpAH/Dzqw8nKhN++/L6lZOXh0v0naNvQht/u3ssPRPnSpPYxLTsfGbkFCnmSsnKUD/+9qUpT0/MtPikTB66m4npqDgpflKBHSwdExtwGABjqAQb6MrRuaIUzSU8BAMN9nbHzfCrG+bvizqPnqG9hhB4tHJD5rBC9WjoiLTsfTlYmWHfiNtKzC9DC0QKRMbdhZiDD8xccPOxNcPtxPjwdzZCY/hwA+GPHvmOqaa2ZlLV0kKJtjTx976QypWTl4fsj/6KhjQmGtXettedbTbpWalJeSNXRJjbYtm0bRo8ejZ9//hldu3bFL7/8gjVr1uDatWtwc3Or5BxXDQpWK0jbiXhfhWBVGCBFDPTkgx55/Vo7oL+3M4CyoCdioCfuZj5H1IlkDPctW77zfCrfrBQoCzLaNrTBpftPMMDbhQ8aWQApDAilAmCGLT96I12Uv+2TuwCAyqBHfp9WjvKBg4WxQl9OFkSmZecrLGPkA3OWN6D8JrLCAJcFdixoE35u7+UH/DGW2g92TFlaAPjjXVGd3a1xJukpvy2W/vZzydh5PpVf7/hHPRW+C5ZHTycrUeDK9jExLRueTlYK35UwcFNlnL8rxvt7AFAsBFE3OBB+H8IAX5csDPWQW1Sq9ec97E2Q+awIQ3xd+P2VP0foBeklXR8LqfS0CT73Xn5QbgFLeekLB0UDoFHBGCFCwuc8IwMQPrBsTuoQvybVkCvVhM9Y9vw/fScTB65mYJy/K8LebFNuwbgmhUzqiIy5gZlBLfm0WQsmVlhJ1+irQdvY4KeffsKyZcuQlpaG1q1b47vvvkP37t0rMacvtW/fXqP1ZTIZoqOjRX1yy/0MBavaY6UZwol4f/31V7Um4n0VglXgZQ0ZANiZ1kNmXrFW6ThbGuLkgt4YufoEXxvFsFol4GVQxGoBV47y4Zum9mvtzH+GBWGqgmh1sBpE4f+z2kQWmMoHWMJgUmqQIvbwZwEa+1tGbgHaNrQBIK61ZentupCMyJjboqCebZ9tix0fZpy/K3zdbPnvSFh7XBkczA2Q8eyFwnIWWErV3spTFtDqQsRATzzJK+JrB9gLi7Dml32Hey8/UPg+KitflYkVFrHvnfU9drAwlmwFIEXVOvFJmRrVjlcVYUuKjNwCAOD3mb0sCltQVORlUVnQGBlzA5Ext/kWCpnPCiVf7oXnHGtxoE5+pI49K0xhtfmAuMDm0v0nAIC2DW34YyMsGCRVj93fWTBTHdg1IDyn2Pmrij6ANg0tsKB/q2q/D+y9/ACLo6/xzyBDPUCq/M9ABrz4/zfjfq0d0MLRAv+m52KcfxPJ+4O2Npy8gxC/Jhi88m8k3M/FzCAP2JgaSj5DOrtb45sR7WrcfZToVm2MDfT09DBnzhyYm5uXuy7HcVi6dCmuX7+OJk3UL8iiYLUCKjIRb208ITUlVeJaEcoCnZqKBcLsBVXYJ5PVAm6f3AWJadn8w2nlKB/su5zKB8CstlZYa8iCVBYYyQdJLEAHypr8RsbcVgjKhS+qVc2kHpCvXZkFAMDVxgjJTwp1lyElWGAvrKFlBRLCZfK1xrWd8PgKCxGsTAyQnf8C6dkFMDOqh+eFxfxL3IGrGQhobodeLR3we3wyGtubIe1pPpo2sFAIiKqzloC9aH+x/xp/jcmTLzBh15CmTdIB1UGmshr4mUEeoqCEvRgLr+t+rR2w4I1W/H1F6niybbKm7vFJmYg6cUfpfqsjoLkdmtQ3Q7/WzsjILdCoQKOqsJrn+KRMJKZlw87cCA4Wxvx3x84BAPx3w/4uJF/A2C/yGACgT2tH+HnU54OWk7cfoamDBXacS0F9CyONmsI2+3gf6luUFcSyGj4AsDM3wr7LqVj1bkeErDuNuJtlz47hvs74ZkQ7pGTlYeGeyxjRoZHG3RjkW92wQpujN9Lxe3wynhcW42FOIQpLys2+1swMZAju1AhWJgZ8l5SjN9LxJK8IM4Na8l1D5PdNWasCtk9A2bP1VkYu/Dzqi87R7l/F6OS5MdzXGcEdXCscrLLrXxgYWxvr42mB6gPfr7UDHK2MEfZmG4VWZMzcHRfR0MYE/6bnYtW7Hflr4cqDbLRxsVJopVQXpGTlofuyWCQt7V/dWamQ2hgb6OnpIT09HQ4ODmqtb2FhgUuXLlGwWhWKiopgamqKHTt2YMiQIfzyGTNmICEhAXFxcaL1CwsLUVj48kb54MEDeHl51aoTUlO6DlZrK/mAVEj4AiolYqAn7MyN0LahDb4/8i9mBLYA8LKvKXuxFb74Hv+oJ9aduI2oE8miWueA5nb8S4+QVODKCgbUbUpLpFsOKCtgYQGQFGdLQ6TmFGm0bRZgOpgboJ6eTOPPV7V+rR3QpYkderV0rNQXJlZA9PGuS8gtKK5QYRe7VtV9QWX3P+E1Liy4OnA1VWkrAqlWFvJdDlggKtW3W/7eW959piLYPWacvysa25mhV0tHPvBo6mCBzGeF8HSyqnABhXzTZVbjO3fHReTkv8C/6c+hfSN5ReyYdlsWKxlElHedBjS3w4bxXfjf3//tLGKuZcDV7uU9uTxG+lAIGjUpFJMBqMsvePUAVKDcU2vsWSosPAA0G0tDV+9HbNyCzu7WyMl/gdsZzyVri6UENLfDiA6NRONFSOVTk9kPWCuAPxNSYVhPD7cePodhPRn+mtUDjWxNMXfHRdx6mAsnaxOserejJruqIDLmBk7dzsS/abn89SkDanXAWhuD1Xv37sHV1VXtqXJSUlLg7OwMfX19tbdBwaqWUlNT4eLighMnTohG3Priiy+wYcMG/Pvvv6L1w8PDERERoZBObTohNcVqBF51qgI+9tATNidWRaqmVL5mldWCldc8i1QuqSbXrGm6sOaH9eFlAyhFnUjmm5JL1YQJa/7YYFnsJV7YrLy2cLY0RFtXa76JXUWwl6nImBvYHp+i86CdXafCgFWq5gpQHFAOgKhpf3lYYCvVbFfYh5sNviVsZixfa6vu/aUy2ZnWQ09PBzzKLRQFcUJ7Lz9A5rNCPMkrwv0n+WhoY4L7T/IRfyezSlpTyKtoP/FXgZlBWSDCajZZX8u60MpEHcL7sSZ9z4U15jWBhaEeTAz14elsCVNDfeQVleBcUhae/3+1L2syXQ9A64YWGNK+IfZfSYOtmSHi72ShpJQrt1a4KjiYGyB+4evVnQ2t1cZgtSrQPKsVpO5EvB9//DFmz57N/85qVusy+WZVrypVNZPsYVXei6TwRVW+luTS/SfYePIu/3vUiWR0drfWOr91gVRT4eG+zmhoY1IlQTwrhBC+tI3390C/1s58kONkZcIHLaxWLOzNNujX2hnBq0/Dz6M+3wdamGdhbZywuSG73pysTPh+p20b2igUZJTXJ7iqpeYUIfVqBg5czYCzpSGCOzXim1mWhwWGX+y/BqDsOhI2q9O1A1cz4GBugODVp0X9y1QNyCa8doXrlofVTrLvXtj6wc7cSNQvXTgVUmUN8FVRmXnF/D40+3gfpgV6YNPJe8gtKEZpafXUkJXnVQ9UA5rbITE1BxnPXvAFHmxqMnYfiRrfGY1sTfn7EAvYWIsgYaFNdXflEdaQK2tppCnh/fSdNSfx97wgtT5X38KowtvWpdyiUuQWlSJDyTFhl0IxgIT7uUi4X/PuMdbG+rU6UK0L/vrrL5ibm+O1114DAPz4449Ys2YNvLy88OOPP8LGxkardKlmVUuaNgOW9yqUnqhq5rJylA/O38sq98VZVw+UuiRioCeuPMgW1bJU18tpVdQ8aNMsVh4L8NmozEBZYKHsHKzoS5WwxlNVEzFlf5MayRoAX4vG/lX2OantsJdGdr6wf1kwxX5ngb6mfYOF39NwX2c8yi3kr11tvkPWpDny7fZ8k0/Wx/DYvxmi9GsyYVN8QDcFBvJN94Ujkb+qWCFFZ3drFL4oQcL9XL6PLXM9NUdhgD5N+DS0QML9XJXryLeokMKCpoj/HzF32YEbfA2WNlSNA8CuPWX5Yi1x7j/JF51TwtYDrK+ocFo2VrsvVagkP/J+t2WxopYlDhbGAF7Wwno6WfGtTFjXF6Bs5HoPexNYGNdDRk4hUnOKVN6bNblnKXtuVnQ8B5+GFlgxqkO59+b3fzvLF1Kr01dVUx72JjCsp8cXlgc0t4OpoT4OXM1Q6zyujSo64FVNUNtjgzZt2uCrr77CG2+8gStXrqBjx46YPXs2jh49Ck9PT0RFRWmVLgWrFdC5c2f4+vrip59+4pd5eXlh0KBBNMASxCMByxNO5SK0cpQPbmXkSg4KJMRKeSt7oKDacFOXfxmuSdQ5fsq+Q/nm0+o2ZWQvP4xwOh+pFwhhyb/w/AMqVlhSE+c1lQ+C5eezVVa4xPo2AS9HiQWAk7cf8aPZCl9mpebLFfbbroyXM3WxGnYAiIy5zQ/8xEbTrmrCY6HLPniaFLgI7yH9Wjsg7Wk+Eu7n8oO5sOC6uu+HZgYy2JkbouBFKXwb28DMqB7auJRd6yF+TUTBFKB4DQoLfYCyYEmbZ4j8Z+RHn5cnLKCQLxySes6xacRG/nxCaSEPC3RZ7TvbBkuPBaEzg1qKuggA4Ee/BiAq5GDbBVT3v9R0hHDhIGHCAZKkpmATfmfy84cLBw2TH7WepS313sEKD1krk/Lud7og31VAft/UGUlZHcIAXf6+Kn9ubZ/chb9nqxo3QRV9AOXduQOa26GdqzX/bBB+VywPw9q74vsj/4quI/lBDeWfv8JzHAA/eBobSEvVXPO1RW2PDczNzXH16lU0btwY4eHhuHr1Knbu3IkLFy7gjTfeQHp6ulbpUjPgCpg9ezZGjx6NDh068BPxJicnY8qUKdWdtRqBlZ4q08ndjn9oAOI5H1mtVK+WjgDKRrcTlgoveKMV+ns78w+l4b7OsDCuV+5LFVsubMokX1PJ0tt5PhVD2jesEc1d5ANSYSBXGYGqOjWmUseYPVzYQ0fViy17yFoYS9+GhIGq8KErVavEAqjg1af5PoHyDy1Vc1wK57wVDlzz+WBvUTNalg9VD/qA5nb4fLB3jXxgsjyxfwd4u4gG1xAeB+bojXSF6VRYwCsMVIXpMgO8XfjRODu52/FzBrJmtOwYVsVAXuwFR9jXmzXj7dfaWfR9qlM7pivCl0tdNoVVN1CVfyEUFggJ/5+9fG84eQe9Wjoq9Mllx0xYi86+YzY1z77Lqfjn5mOl9xaTeoB3I2sYG+jzL7vsBVUYYCh7IZU/j4UFM8LAhz1nWDptXKwQFp3I39Ok7n+sxi90SwJmBLbgnzfCearZ9SQsiGXLhSNhzwhsgUa2pvy9ih0fFiiyvG+b4i+aQ5vdi+Tn9G7qYKEw4BYAvjsBw561wmnV5OfoVoc66wnX6eRuJ/mdyd+f5dcRfi4lK0+hYE1YOBC6JQFtG9rw9yJ2PNhx8vOojxC/Jvw7hbDpPKDY7L6ipJ5Badn5/O/D2rtWaFszgzxwMfkpRnRoxB+DpwUlouey/HOLfe+RMbfh51GfPzeEXQpYICnsCy985n4vOObs3iE8zsKCy8iY23CwMOa/k7DoRGTkFmBYe1f+vNt5PpU//9nnhKOcs24NEQM9EeLXBP1aO4tG807JyhMVxJDqZWhoiLy8skLBmJgYjBkzBgBga2uLnJwcrdOlmtUK0nYi3tpeeqIO+QGW2Fyn2gyZLj9JNgD+hYAt67YsViGIKK95nHzzUFZCB7x82MhPCyOVnrYDmGjSPJJNazPOv4nk6MLVMRiIugPGyDc5lfq78EVBOOAQmx9X/rsWvpAJX2iU1aJKUVbbKmx6K/8yJz8qKdt39l3KTz1Sl2k7ZYnwGAqP68I9lyvctFe+hkm+tkvV3McA+BpW9iJWlV0RqrrmUv66FF5Twlo24OWLoTBYZNcAO54bTt7hAzr5UZABKIxsLJxjGoCoCZ98U1JNRiSVT0N+LmspwueVsCZUqnZKfnAtqemD1B0hVnifER4n+XuacH1hzaP8FDTy348wIGXrCgN3dfJYU0iNTCucs1x4/ORH1AYgeXxZWsJaVjavubCVDaPJfPHCeZrZuSX8boTPTeE7hLCwTP6eICwAErYIEr6XsNYirEBJGJTLb1t4bUi1QpI/zux8EuaDBaPy56r8eSb/Pcg/Z5UVQsmf5/ItJzR97tdktT02GDhwIIqKiuDv74/PPvsMSUlJcHFxwaFDhxAaGoqbN29qlS4Fq9Wktp+Q6opPyuQHHalI8wypPjBCwhpa9jf5m2hadr7C6KvKXgbkH+7CFw/hzVJYki31olMeqT427PPygZ3w94o2f1ZVcyTMk/BFnU1NIexfBIibdAsLC+SblAlfnIQvgOz/2QurVCABKD6wtHl51UZ56bNmZ8J9V/dcr6y818aHttRUL8JrSWoaD+BlgQnr1wpAIchh1y/7vTyqujDoEruOpZo1VgV235I6VuX1sZZvogkoNveUT0vY/JzVuCubJ1a4fkWo+yIrvO/Lz30tNT2QptvXZL2K7LeqAjht8lVbqDp+ys5D+c8w8s95bZvMsnNGfqo54OU9hhXiA1Ba6NuvtQPG+TcRDeDGrl3hew5LUz4QL+9ali+YLa85rToBJltPvuCFbVNqXU0KoZSlU9vV9tggOTkZU6dORUpKCqZPn44JEyYAAGbNmoWSkhL88MMPWqVLwWo1qe0npLqkAr+KpCN/0wPEzYfZuoDyG5mm/W2U/Z1tmz0w5GsTlFHVx1Q+0BU+JNnfxvm7wtfNVnI7Un082DQ2UgGqNs0dhfsqbEIqX1IsVQMhX+jAvjtlNRPlPQxrApZP4bRC8s1mVX1O1/tXW46bFOFLkDDgEbaiYAUb8oVgui7AEAZelRW4ssFYgJeFbLqsyZWaPok1RxWO1i5fwyR17kgVGErd11UFn/JpqfNiXJXkmwwLW3Jok8fafC3Wdep8N/LPeVWknqXCFgvs853drbFtsr+oH7Gw9lV+ajKpwl9G/p2oou9aumiZpM065KXaGhscOnQIPXv2hIGBQaWkr1cpqRLy/1i/kIqO0Cbfn6WRrSn/I582W64qLXW2V97f2ba3T+6CAd4uOP5RT/5hwvrHSVEWqA73deYH6WD8POpjZpAHAKCxnRn/r9TLc8RAT9FL7spRPhjvX1aSOzPIg3+QCqe1OZP0FP1aO4jSYduLGOjJ52X75C78ckb+wcmOBdt28OrTSMnK4x+i7KEl/B7ZOrV5BL9GtqZ8PyAAOH1HvUBD/ljoMj+19eWYXVfHP+op6gfL+q6xLgBOVib8NSd8URMWYlUU2+YAb5dK6w81pH1D0T4f/6gnpvVsprP05V+ehTU4adn5Ci1UVJ07wr+puq+rcy0LP1+TzlWWj8S0bNEybfNYm6/Fuk6d70b+Oc9+ACg8D78Z0U707AZeTje1/dzLAugzSU/RL/KYwrY6udth5Sgf0TtAUwcLAGXP4rYNbfjrVXgNCt+JKvquJUxLk/Urug6p/aZMmYL69etj5MiR2Lp1K7Kzs8v/kAYoWCWVTlc3q5p602MPB+EDhL1UAy8DV2EAKz8P6swgD74Elr2Es9JY1i+EpSkc6ZYZ5+8KO3MjhSCZvcDPDGqJlaN8EDHQU+EFtr+3s+h3FnSFRSfCwcKYfwDODGqJ7ZO7iAbw6LYslu+3xo4Fe8GXf7GVfxCW97JQm170hIH6gjdaqf25ytq32nDMVFEWLKlzLukycGXpy88ZLf+iqilWQBQWnShqCdLI1lTp/NQ+DS003o58PoX95th8vPLHWt2CvoqeY5q+GFcldq8VDsajrZq4f6SMJt+Nk5WJKBC0MTXk/39mUFlrhdAtCfy1bWf6cuDAR7nirj6J6c9x8vYjhW2w5yYrIGPP2hC/JpLPQ02uXUIq0507d/D333+jTZs2+O6779CgQQMEBgbihx9+wN27dyucPjUDria1taqfqE9+cAHWlEjZYEzyzXeETZDYQBHAyz4mwqk2WHMjqWZD8s102XLhaJ6sWaU60xjID7QAiAdMeFWxqQg0GWCJmkhVjso4rvLBr6ppL9QdKElZk/GUrDx+WgepkZLVaSrMputg+WRNWuWb49P5p4iODxGS6r4CQKHZrjJSz/yZQR7w86ivsiZUnSb1pG6pK7FBamoqoqOjER0djdjYWDRv3hyDBg3CwIED0aFDB43To5pVQiqJfJ8w9juryVw5ygcrR/mIBhZihIM7OFmZ8L+nZefzL+KsiRAAfq5BVtobMdATA7xd+BfTlKyXw7sLh/bfPrkLX3M6wNtFlAcHC2N0WxarUEvFgu5L95/wTRdZk0JdNsOsbYa1dxX9W57KaLpKylRGgCHsesBqOcb5uyq0kgCgEKhun9yFb9kw3Lfs+h/u66y0b3MjW1PMCGwBAJjWq6xZMGs1sXKUDz4f7C1aJlXrKhxZG4Bo8Kba1GqhOrBghP1LXm3segFeFlKxgl9hoMqubWdLQ9Hnlc0UoGpgMfbMpucDqY2cnZ0xZcoU7N+/H48fP8aiRYtw9+5d9O3bF1988YXG6VGwSkglUdanpG1DG36oeeHUDvLNe4QPx6M3yiZSDl59Gt2WxSqMVno38zlWjvLhX0hZU2H5Yd6FTZZZTa7UCyuraZXSyd0OEQM9RdtnD27hQC1ENQoYarejN9IRdSJZcoAyFkSyZrjCUTx3nk9Fv9YO2Hk+lX8pVeb4Rz35qbQ8naz4JoLyQZR8cDwzyIM/t5Q1K6bzjhD1CQupAPG1yQqjGtqUXWvqTEcXGXNb8tqXmpqFkNrMzMwMw4cPx8aNG5GRkYFJkyZpnEa98lchhGhL6kEjfBCtHOUjOR2L8LPC+SKFE84LRym1MjHAAG8XOFgYIzEtWzTCprKRPeVH4ZR/cEqN+AuUNU1iI7Ky5ax/rTB/r9qDlhUAaLLPr9LxqWtC/JrgbuZzvmaFTe0UFp3I93VkhUdtG9rw01iERSfiwNUMfhAVqeamwmaHLNiUmjbF08lKdB8Y7uuM4A6uCF59mq/hF75g0/mmHtYHnZpgEiHhyOTCUfFZN53z97IqvA0qxCS1XXx8PI4dO4aMjAyUlpbyy2UyGZYvX4769etrnCb1Wa0mdaVdOtGc/HD4yiYqZ+uyeUntzI1EcxemZeeLamyE852y35U98KTmnWPbF05rIRXkSs1By5obs/14FV/0qJ/bq0d+2iLgZbNbYf9w+cIeYWGOsil3ypuKh81bLN+HXdv5QAkhygmfxfLTZ7HCWk3mWAfEc8ETAtT+2OCLL77AwoUL0aJFCzRo0AAymYz/m0wmw9GjR7VKV62a1ZycHI0TtrS01PgzpO6hAWQUsZdLNo8fG0BJ2cicwjnaMp8VIiw6kX8oCkcaZs2UIgZ6wtPJSmWgyoIqNoADK82VD3al8i5fGysfoFGwRl4VwutB2FeZtZ5wsDBWuBbYtChHb6Tzo3wCitdSeSPvsgHOhNuPjLlNgSohlUD4LF45ygdOVib8/7Pnd1p2vspgtV9rB3RpYse3uGDNiAmpK77//nusW7cOY8eO1Wm6avVZtba2ho2Njdo/tra2uHPnjk4zSmofGkBGuUa2pnwf0+DVpxGflKlQo8oI+5zZmRsBAP9AZH1Tw6ITEZ+UyTfRZWkq27YwMGXrsd9VzRHLPi+fli6ntCCkNhH2SRf2a2MvtvL3v14tHSVHAda0+Z+yPvGEkMrBglJhkBm6JYEvlGfPavm5y5kDVzPwJO9lf1bhfL6E1AV6enrw9/fXfbrqrrhz504cPXq03J8jR47A0NCw/ARJnUd9L6Sx4FD4wGMj/gIvg3y2HgtsAYgGNWKfE74YO1mZ8OuqGkmwka2pqF+WcFob+f6o5aHvtwz7nuh4vLqk5hyWatbfq6Wj6HpnND13lPWJpwJCQioHK9RNy87nR8OXvw7H+UuP8j3c11nUAkNqznRCarNZs2bhxx9/1Hm6ajUDdnNzQ/fu3WFnp14ftCZNmsDAwKBCGSN1A724iwmDQmHgefRGOh8kstJZYX9WNpAD6x8DiAdcERYMNLI1lZwfVQobGIJNa9PJ3U6hjx1RT3xSJkK3JMDBwviV669LXl7brE+b1EvspftPAIivd2X9V7VBBYSEVC5Vg2+x649d5/J2nk/FjMAW/D1C2Yj7hNRWc+fORf/+/eHh4QEvLy+FWPCPP/7QKl0aYKma1PZO1ER7rJ8om35GODgLIO4rqmyk3ka2pqIJw+VfcjV96aW+xbpBk7i/2oRTSkmNwCscoEw4OBL7lwboIqR2E44YLBQx0BO9WjrStU5Uqu2xwbRp07B27Vr07NlTYYAlAIiKitIqXZ1MXfP06VNYW1vrIilC6jwWzLCpZjq528HPo77SEXgZ9pIrrL1ho40KH3zaPAjpgakbFKi+2gZ4u/DTN0lN4SQcpEU+mKVaUUJqN+EcqUDZyOAHrqbyY0zQtU3quo0bN2LXrl3o37+/TtNVu88q89VXX2Hbtm3878HBwbCzs4OLiwsuXbqk08wRUtexAJWNyKvsYXb0RjqOf9STb4IUFp2IiIGeoloceuklpHrFJ2XyQSpr7i9/Hcr3ZZXqs6ppn1Pqo0pI1ZNq8bR9chd+3AigbA50ALib+VxhPXpGk7rG1tYWHh4eOk9X42B19erVaNSoEQDg8OHDOHz4MA4cOIB+/frhww8/1HkGCamr1B0tecPJOwiLTsTRG+miAVzYyMCAYomtrh6C9BJMiHpYn1Vh8z82UqiQ/Pyp8vcATUdRp1HXCal6yq5d4fXvZGWCmUEt+anmhIOqqRoAkZDaKjw8HGFhYcjL0+25rXEz4LS0ND5Y3bt3L4KDg/H666+jcePG6Ny5s04zRwgBQvya4EleEezMjRC8+jRmBpWVWrVtaKO0BlUXfVCpXw0h6mOtHgDwA5bJz3nKAlo2QIuyqZ+0ncKG+p4TUjWkrlM2sBJr8ZSWnY9Gtqbo19pZNP8q1axWHroHVq8ffvgBt2/fRoMGDdC4cWOFAZYuXLigVboaB6s2NjZISUlBo0aN8Ndff+Hzzz8HAHAch5KSEq0yQcirSN0HVkpWHj8A0zh/V9FgTMoCVV0EmdScmBDNsOBU6roRjgQu7MsqdX1pM4UNFS4RUnWkgqIB3i4AyqalY1PJCUfbF7aokO/PTiqO7oHVb/DgwZWSrsbB6tChQzFq1Cg0a9YMmZmZ6NevHwAgISEBTZs21XkGCamryntgsYchm78zdEuCqHSWldrK01WpLZVQEqI+VS9KwhdW1k9d16hwiZDKx5ruKrvWWcAq/JuyGthL95/Q9apDdA+sfmFhYZWSrsZT17x48QLff/89UlJSMHbsWLRr1w4AEBkZCXNzc0ycOLFSMlrX1PbhqYluKAsIWS0MGzFUON0Fm6NRVZBb0dJF4fbpxk+IelQV8Aj/RlMcEVL7CJ+tgOYtIIT3gL2XH/CBLdGdJvP3wUC/bGArT2dL9GrpADtzIzhYGGP7uWTsPJ8KD3sT5BYUw87cEG91cgVQ1t2qJqDYQJraNasLFizA4MGD0alTJ8ydO1fh7zNnztRlvgh5JSgLNoXNhlhJLquRCYtOrNQ8STVbIoSUT9X1Qk0ACandWM0d+39NyBciU6Cqe03m70MpgMISIOPZC2TczETczUyF9W4/zgdQtg57n1q6PxGJn+t2upWaqHHjxrh3755o2bx587B06VKt07S1tcXNmzdhb2+v1vqurq44fvw43Nzc1N6G2sFqWloaBgwYAH19fbz55psYPHgwAgMDYWRkVP6HCSFqU9WUJS277CYrNSWG/DrKmglXZPuEkIqhwVUIqd20abkk/1ylmlXdszTWx9MC7cbOyS8GfBcfxPlP++g4VzXP4sWLMWnSJP53c3PzCqX39OlTHDhwAFZWVmqtn5mZqfEYR2oHq1FRUeA4Dv/88w/+/PNPzJ49Gw8ePEDv3r0xcOBADBgwQO2omhCimtTooAD4AVpCtySgbUMbyYclG5W0Is0M6UWakMpBNauE1F4VKcwVBqpsxGAKWHUnIbwv2nx6ALlFpVp9vnVD9YKt2s7CwgKOjo46TTMkJESn6cnTuM+qUGJiIv7880/873//w7lz59C5c2cMHDgQb7/9Nlxc6AJUhdqlv7q0GbiIfYb9S6WyhNRc5V3j1GeVkFdbZMwNzAxqWd3ZqHOEc9d+sf8aDlzNEP29X2sHHLiagYiBnnwT4IiBnjh6IwMbxnep0rxKqezYoHHjxigsLERRUREaNWqEESNG4MMPP4ShoaHOt6VLehX5sKenJz766COcOHECKSkpCAkJwfHjx7F161Zd5Y+QOkVqInFNPsMC1dAtCYhPyqRJxQmpYcq7xlnNKl27hLya4pMyERlzG/FJiv0pifbYvRco6wZ14GoGxvm7ImKgJwKalxUOdmlS9m+vlo7YPrkLtk/ughC/JjUiUBXKzc1FTk4O/1NYWKiTdGfMmIHff/8dsbGxCA0NRWRkJKZOnaqTtCtThWpWifZqY80qTWWiG5oeR3YDXjnKB20b2vA34+2Tu1BzQkJqIFXX+N7LD+BgYUw1q4S8wqh1ReUQTi0k3x2KtUirye+yLDaQFxYWhvDwcMnPhIeHIyIiQmW6Z8+eRYcOHRSW79q1C8OHD8fjx49hZ1dzz0eNg9WCggKsWLECsbGxyMjIQGmpuG34hQsXdJrBuqq2BatsKpN+rR2w4I1W6l3oRc+BxL2A5wDA0KzyM1lHpWTl4dL9JwjdkoCZQR6IjLkNACpHJazJN2NCXlXCvmpUyETIq4uC1cpVW9+BWGxw/fp1UXdKIyMjpQPaPn78GI8fP1aZbuPGjWFsbKyw/MGDB2jYsCFOnz6Nzp07VyzzlUjtAZaY8ePH4/Dhwxg+fDg6deoEmUxWGfki1UB4cbMAaYC3CyJjbvAB0oGrGThwNUO9F63EvUBeJnBjH+AdXNnZr5NYrer2yWVNVNj3wFTWPKuEEN0b4O2CzGeF6NXSka5NQuoAbYIiVvhf0YEQiXK1/f5qYWEBS0tLtda1t7fXeoDbixcvAgCcnJy0+nxV0ThY3bdvH/bv3w9/f//KyA+pJizAcbUxwuZJfnxT032XUxU6qAPAyJ9PYNsUf9U3BM8BZYFqy7o/d1VlEY48uH1yFySmZZc7zypNjUFIzZSSlcdfvzVlEnpCiHa0LRjOyC0Q/UtIVTh16hROnz6Nnj17wsrKCmfPnsWsWbMwcOBAuLq6Vjj94uJibN68GX369NH5aMMaD7Dk4uICCwsLnWaCVL/3NsYDAJKfFPKBKgDJQBUAUnOK0G1ZLD9AQEpWnmjAkJSsvLKmv97B1AS4ghrZmvIlsczMIA+lD0cawIWQmunojXQAQFh0IvZeflDNuSGEVIS209gM8HbBzCAPGtGfVCkjIyNs27YNPXr0gJeXFz799FNMmjRJZ4Pi1qtXD++//77OBoMS0jhYXb58OebNm4d79+7pPDOk+rRy0W5+qeDVpzF3x0V0WxaLbstiseHkHcQnZfKjYVLAVHEs+AQAO/OyPguRMbeVHtuKzANHCKk87Pod5+9KL6qE1AGqCo2VodGASXVo3749Tp8+jadPnyI/Px83btxAeHg4TE11967YuXNnJCQk6Cw9RuNmwB06dEBBQQGaNGkCU1NTGBgYiP6elZWls8yRqhNz7aHWn915PpX/f2ETVTbHFQVOFcOa9QavPo22DW1EAysp6y9Dx5uQmocFqBSoElJ3ldc82MnKRPQvIXXF1KlTMXv2bKSkpMDX1xdmZuKWld7e3lqlq/FowEFBQUhOTsaECRPQoEEDhQGWQkJCtMrIq6amjQYc8ecVRJ1Irpy0B3pS/ywdYCW1LEgFQAMpEVID1daRKAkh6invGi/v72waFUKEalpsoCk9PcUGuzKZDBzHQSaToaSkRKt0Na5ZPXnyJE6dOoW2bdtqtUFSM/Vr7awyWB3u64yd51OxfXIXRJ24o7Qvq5Qfj96iYLWChMHpylE+CN2SgOMf9aRAlZAahkbjJqRuY2NIqLrGVV378UmZCN2SQPMtkzonKSmpUtLVOFht2bIl8vPzKyMvpBp1crdDxEBPpSPN9mjhgBmBLQAoH3RJme4t6lc4f68y4fQ1LFAtb7RfqtkhpHpQn3FC6i7hGBLa6uRuR9PWkDrJzc2tUtLVuBnwoUOHEBERgSVLlqBNmzYKfVbVnRfoVVdTq/rZpPUzgzwU5vRkL2Cslm/XhWTYmBqWO5UKvbhVnHA04JWjfCSbD7EAlWp2CCGEkMoh7JKjrfikTApWiYKaGhto4vbt24iMjERiYiJkMhk8PT0xY8YMeHh4aJ2mxqMB9+3bF6dOnUJgYCAcHBxgY2MDGxsbWFtbw8bGRuuMkJqhbcOy77Cpg3h6ImFNHvs3MuY2PJ1ejiI8zt9V9C9Q1l+VAqaKYwMxsJpV+ZEGWYDKAlaaZ5UQQgjRvUa2phUOVINXn6bRgEmdc/DgQXh5eSE+Ph7e3t5o3bo1zpw5g1atWuHw4cNap6txM+DY2NjyVyK1FmvCxuYDZORHrRM2dTv+UU+kZecjePVpbJ/cBU5WJnz/17DoRPRq6UiBk44IRwMWEn4frJkS1awSUjNRM31CXl3bzyXz/1LtKqlL5s+fj1mzZmHp0qUKy+fNm4fevXtrla7GzYCJbtSGqv4NJ+/AztwIbRvaqPViJXwBYzV/adn5dDPWAfma1PKa+dLLMCE1EzXTJ4TM3XER34xoV93ZIDVMbYgNVDE2NsaVK1fQrFkz0fKbN2/C29sbBQUFWqWrVjPgy5cvo7S0VO1Er127huLiYq0yRGoOTycrhG5JQFq2egNqCV+82P8Hrz6tcnJsUj72cpuWnc//u3KUj8oXXXoJJqRmogGYCKnd1HmnKW8dClRJXVS/fn0kJCQoLE9ISICDg4PW6aoVrLZr1w6Zmeq3re/atSuSkytnzk5SdTJyCyo0Yh29lOkGO45OVibYPrkLglefRuiWBOrvQkgNo27BnPCeSIV5hNQe8UmZ/PgQygjHkCDkVTJp0iS89957+Oqrr3D8+HH8888/WLp0KSZPnoz33ntP63TV6rPKcRwWLVoEU1P1go6ioiKtM0RqBjYq8MpRPhVKhwJV3WFNB7dP7oLEtGxqXk1IDaJN815qEkxI7cHGgyhvAEMqqCevqkWLFsHCwgLLly/Hxx9/DABwdnZGeHg4pk+frnW6avVZ7dGjB2QymUYJb9myBU5OTlpnrK6rDe3SI2NuYGZQy+rOBvl/rJS227KyQc5onjZCahZt+opT/3JCag+6Xkllqg2xgTLFxcXYvHkz+vTpA0dHR+Tm5gIALCwsyvlk+WiApWpS009INrQ6BURVq7wHIQtYL91/IjnXKiGkZqOXXUIIIVJqemxQHlNTUyQmJsLNzU2n6Wo8zyp5NbCpauSnrCGVp7x+LsKBlqTmWiWE1GzsGqb+5oQQQuqazp074+LFizpPl2pWq0ltKD2hGoCqV94xj0/KRCd3O/5fQkjtQq1WCCGESKkNsYEqO3bs4Oda9fX1hZmZmejv3t7eWqVLwWo1qe0nJKl6rFaGjQhMAzgQUjuxgJWuYUJqHyrIJ5WltscGenqKDXZlMhk4joNMJkNJSYlW6ao1GjAhpPoJRxikl1xCajZVL7ROViZ0DRNSC8mP4E2BKyEvJSUlVUq6GvdZzcujfnKEVBf2UKSHIyE1l6q5GNnLLiGk9mlka8pPXUPzqRLy0osXL9CzZ088f/4cbm5ukj/a0jhYdXBwwOjRo3Hw4EGUlpZqvWFNLVmyBH5+fjA1NYW1tbXkOsnJyXjzzTdhZmYGe3t7TJ8+XWHO1ytXriAgIAAmJiZwcXHB4sWLId8SOi4uDr6+vjA2NkaTJk3w888/K2xr165d8PLygpGREby8vLB7926d7SshhJDaqby5GKllBCG1F7u+WY0qXcuElDEwMEBhYaHGU52qQ+NgdePGjSgoKMCQIUPg7OyMGTNm4OzZszrPmLyioiKMGDEC77//vuTfS0pK0L9/fzx//hz//PMPfv/9d+zatQtz5szh18nJyUHv3r3h7OyMs2fPYsWKFfjmm2/w7bff8uskJSXhjTfeQLdu3XDx4kUsWLAA06dPx65du/h1Tp06hZEjR2L06NG4dOkSRo8ejeDgYJw5c6byDgAhhJAaj73AqhpJXduXW6rBIaR6yQeoFKgS8tIHH3yAr776CsXFxTpNV+sBlnJzc7Fz505s3boVsbGxcHd3x7vvvotPP/1UpxmUt379esycORNPnz4VLT9w4AAGDBiAlJQUODs7AwB+//13jB07FhkZGbC0tMSqVavw8ccf4+HDhzAyMgIALF26FCtWrMD9+/chk8kwb948REdHIzExkU97ypQpuHTpEk6dOgUAGDlyJHJycnDgwAF+nb59+8LGxgZbt25Vaz9qeydqQggh0ipjACX5vnKEEELqltoeGwwZMgRHjhyBubk52rRpozAa8B9//KFVulrPs2phYYFx48bh0KFDuHTpEszMzBAREaFtchV26tQptG7dmg9UAaBPnz4oLCzE+fPn+XUCAgL4QJWtk5qairt37/LrvP7666K0+/Tpg3PnzuHFixcq1zl58qTS/BUWFiInJ4f/yc3NrdD+EkIIqXnKawasLWpySAghpCaztrbGsGHD0KdPHzg7O8PKykr0oy2tRwMuKChAdHQ0tmzZgr/++gsODg6YO3eu1hmpqPT0dDRo0EC0zMbGBoaGhkhPT+fXady4sWgd9pn09HS4u7tLptOgQQMUFxfj8ePHcHJyUroO246UL7/8slqDeVK70YiDhNQObACWyphDle4BhBBCaqqoqKhKSVfjmtVDhw4hJCQEDRo0wJQpU+Dg4ICDBw8iOTkZX331lUZphYeHQyaTqfw5d+6c2ulJdeplc/soW4e1gtbFOqo6FX/88cfIzs7mf65fv17e7hACADTiICG1iHAAFkJI3UPXNiHKFRcXIyYmBqtXr+ZbkaampuLZs2dap6lxzergwYPRv39/bNiwAf3794eBgYHWGw8NDcVbb72lch35mlBlHB0dFQY4evLkCV68eMHXgjo6OirUfmZkZABAuevUq1cPdnZ2KteRr20VMjIyEjU/zsnJUWu/CGHN/wghNR811yWk7qK+44Qod+/ePfTt2xfJyckoLCxE7969YWFhgWXLlqGgoEBydhV1aByspqenw9LSUquNybO3t4e9vb1O0uratSuWLFmCtLQ0ODk5ASirBTYyMoKvry+/zoIFC1BUVARDQ0N+HWdnZz4o7tq1K/78809R2ocOHUKHDh34wLxr1644fPgwZs2aJVrHz89PJ/vCcByH4uJilJSU6DRdUnX09fVRr149nQzlzR6Qadn5cLIyoQclITUUXZuE1E1UGEWIcjNmzECHDh1w6dIlvoIPKBt4aeLEiVqnq3GwumPHDkyYMEFheXFxMRYtWoQvv/xS68yokpycjKysLCQnJ6OkpAQJCQkAgKZNm8Lc3Byvv/46vLy8MHr0aHz99dfIysrC3LlzMWnSJD64HjVqFCIiIjB27FgsWLAA//33H7744gt8+umnfDAxZcoUrFy5ErNnz8akSZNw6tQprF27VjTK74wZM9C9e3d89dVXGDRoEP73v/8hJiYG//zzj872t6ioCGlpacjLo+YmtZ2pqSmcnJz4AhJtsAdkWnY+glefBgB6YNYB1BeZ0DlASO1C1ysh0v755x+cOHFC4X3Xzc0NDx480Dpdjaeusba2RmBgINasWQNbW1sAwI0bNzBq1ChkZ2fj9u3bWmdGlbFjx2LDhg0Ky2NjY9GjRw8AZQHt1KlTcfToUZiYmGDUqFH45ptvRM1vr1y5gmnTpiE+Ph42NjaYMmWKKFgFgLi4OMyaNQvXrl2Ds7Mz5s2bhylTpoi2u3PnTixcuBB37tyBh4cHlixZgqFDh6q9P6qGpy4tLcV///0HfX191K9fH4aGhpUyyS6pXBzHoaioCI8ePUJJSQmaNWsGPT2tB+Dm7b38AG0b2tADs5aj5mSEzgFCah8qYCKVpbZPXWNra4t//vkHXl5esLCwwKVLl9CkSRP8888/GDZsGB4+fKhVuhoHq0lJSRg9ejSSkpKwfv163Lx5Ex9++CGGDx+OH3/8ERYWFlpl5FWj6oQsKChAUlIS3NzcYGpKN8TaLi8vD/fu3YO7uzuMjY21SoM9HNV9uaWHae1A31PdFZ+UqdaIwHQOEFJ7VMYcyoQwtT1YHTlyJKysrPDLL7/AwsICly9fRv369TFo0CC4urpqPVqwxtU87u7u+PvvvzF8+HD07dsXs2bNwrp167Bx40YKVHVMF7VwpPpV9HsUjgasTn8ZGj249qCXnbqJvdDGJ2WWuy6dA4TUDpU1hzIhVWXJkiXw8/ODqakprK2tJddJTk7Gm2++CTMzM9jb22P69OkoKipSK/3vvvsOcXFx8PLyQkFBAUaNGoXGjRvjwYMHGs8YI6TVPKt79+7F1q1b4efnh3///Rdr1qxB9+7d4ezsrHVGCCHSNB3QgQaAIKR6dXK3q7S5Vgkh1YNG5ie1XVFREUaMGIGuXbti7dq1Cn8vKSlB//79Ub9+ffzzzz/IzMxESEgIOI7DihUryk3f2dkZCQkJ+P3333H+/HmUlpZiwoQJeOedd2BiYqJ1vjUOVidPnowNGzbg888/x5w5c/Dw4UOMHz8ebdq0wapVqxAcHKx1Zkj5HjzNx5Pn6pVw6IKNmSFcrLU/wTTVuHFjzJw5EzNnzqyy9MLDw7Fnzx5+0K6aiAWe6jYDpkCVkOpFgSohdRP1Mye1VUREBABg/fr1kn8/dOgQrl+/jpSUFL4Ccvny5Rg7diyWLFmi1mwwJiYmGDduHMaNG6d0nf79++PXX3/lZ28pj8bB6okTJ3DmzBm0bdsWQNmco/v378ePP/6I8ePHU7BaiR48zUevb46hsLi0yrZpVE8PR+f2UCtgffPNN5Gfn4+YmBiFv506dQp+fn44f/482rdvXxlZlXT27FmYmZnxv8tkMuzevRuDBw/ml82dOxcffPBBleWJEEIIIbUPtVwiddmpU6fQunVrUUvZPn36oLCwEOfPn0fPnrppWfD3338jPz9f7fU17kx3/vx5PlAVmjZtGs6fP69pckQDT54XVWmgCgCFxaVq1+ROmDABR48exb179xT+tm7dOvj4+FRpoAoA9evXL3eQKnNzc9F8UDUR9T8lhBBCCKn7cnNzkZOTw/8UFhZWyXbT09PRoEED0TIbGxsYGhoiPT29SvIgReNgVTgNjLwWLVpUKDOkdhswYAAcHBwUmhfk5eVh27ZtmDBhAk6ePInu3bvDxMQEjRo1wvTp0/H8+XOlaSYnJ2PQoEEwNzeHpaUlgoODFYa+jo6ORocOHWBsbAx7e3vRFEKNGzdGZGQk//9A2eTEMpmM/z08PBw+Pj6iNKOiouDp6QljY2O0bNkSP/30E/+3oqIihIaGwsnJCcbGxmjcuHGlzS8MaD7AEiGkZqPCJ0JqJxrAkFQFLy8vWFlZ8T+q3jHDw8Mhk8lU/pw7d07tbUtNlclxXLVOoalWM+D27dvjyJEjsLGxQbt27VRm+MKFCzrLHKld6tWrhzFjxmD9+vWiuWt37NiBoqIitG3bFn369MFnn32GtWvX4tGjRwgNDUVoaKjkcNYcx2Hw4MEwMzNDXFwciouLMXXqVIwcORLHjh0DAOzbtw9Dhw7FJ598gk2bNqGoqAj79u2TzN/Zs2fh4OCAqKgo9O3bF/r6+pLrrVmzBmFhYVi5ciXatWuHixcvYtKkSTAzM0NISAh++OEHREdHY/v27XB1dUVKSgpSUlJ0cxAlUIBKSN1Bc6sSUnvR85hUhevXr8PFxYX/XVVFYWhoKN566y2V6bHKmfI4OjrizJkzomVPnjzBixcvFGpcq5JaweqgQYP4AzVo0KBqja5JzTZ+/Hh8/fXXOHbsGN+2fd26dRg6dCjWrFmDUaNG8YMdNWvWDD/88AMCAgKwatUqhTlIY2JicPnyZSQlJaFRo0YAgE2bNqFVq1Y4e/YsOnbsiCVLluCtt97iO40DkGymDpQ1CQYAa2trODo6Kt2Hzz77DMuXL+draN3d3XH9+nWsXr0aISEhSE5ORrNmzfDaa69BJpPBzc1Nu4OlAU0HWCKE1Ez0sktI7UbXLqlsFhYWag1mBAD29vawt7fXyXa7du2KJUuWIC0tjR/86NChQzAyMoKvr69OtqENtYLVsLAwJCQkwMfHB+Hh4ZWcJVKbtWzZEn5+fli3bh169uyJ27dv4/jx4zh06BBmzJiBW7duYfPmzfz6HMehtLQUSUlJ8PT0FKWVmJiIRo0a8YEqUNY0wtraGomJiejYsSMSEhIwadIkneX/0aNHSElJwYQJE0TpFhcXw8rKCgAwduxY9O7dGy1atEDfvn0xYMAAvP766zrLgyr0oktI7UfXLyGEkKqWnJyMrKwsJCcno6SkhJ8Fo2nTpjA3N8frr78OLy8vjB49Gl9//TWysrIwd+5cTJo0Se3guTKoPRpw+/bt0a5dO0ycOBGjRo3iX9wJkTdhwgSEhobixx9/RFRUFNzc3BAYGIjS0lJMnjwZ06dPV/iMq6urwjJlbeSFyysyb5OU0tKyAazWrFmDzp07i/7Gmg23b98eSUlJOHDgAGJiYhAcHIygoCDs3LlTp3lRhl50CSGEEEKIJj799FNs2LCB/71du3YAgNjYWPTo0QP6+vrYt28fpk6dCn9/f5iYmGDUqFH45ptv1Eo/Ly+v3EFNAWDBggWwtbVVO99qD7B04sQJtG/fHvPnz4eTkxPeffddxMbGqr0h8uoIDg6Gvr4+tmzZgg0bNmDcuHGQyWRo3749rl27hqZNmyr8GBoaKqTj5eWF5ORkUX/Q69evIzs7m6+F9fb2xpEjR9TOm4GBAUpKSpT+vUGDBnBxccGdO3cU8uju7s6vZ2lpiZEjR2LNmjXYtm0bdu3ahaysLLXzUdlo8AdCaja6RgkhhFSl9evXg+M4hZ8ePXrw67i6umLv3r3Iy8tDZmYmVqxYobLPrJCDgwNGjx6NgwcP8pU/Uj7++GNYW1urnW+1g9WuXbtizZo1SE9Px6pVq3D//n0EBQXBw8MDS5Yswf3799XeKKnbzM3NMXLkSCxYsACpqakYO3YsAGDevHk4deoUpk2bhoSEBPz333+Ijo5WOsdpUFAQvL298c477+DChQuIj4/HmDFjEBAQgA4dOgAoa6K+detWhIWFITExEVeuXMGyZcuU5q1x48Y4cuQI0tPT8eTJE8l1wsPD8eWXX+L777/HzZs3ceXKFURFReHbb78FAHz33Xf4/fffcePGDdy8eRM7duyAo6OjRhdeZaLRCgmp2egaJYQQUtds3LgRBQUFGDJkCJydnTFjxgycPXu2wulqPHWNiYkJQkJCcOzYMdy8eRNvv/02Vq9eDXd3d7zxxhsVzhCpGyZMmIAnT54gKCiIb+Lr7e2NuLg4/Pfff+jWrRvatWuHRYsW8Z245clkMuzZswc2Njbo3r07goKC0KRJE2zbto1fp0ePHtixYweio6Ph4+ODXr16KYxkJrR8+XIcPnwYjRo14ps/yJs4cSJ+/fVXrF+/Hm3atEFAQADWr1/P16yam5vjq6++QocOHdCxY0fcvXsX+/fvh56expdTpaB+rYRUv/ICUbpGCal9UrLyqJCJECWGDh2KHTt24OHDh/jyyy+RmJgIPz8/NG/eHIsXL9Y6XRnHcVxFMvbs2TNs3rwZCxYswNOnT1U2sSQv3b9/H40aNUJKSgoaNmwo+ltBQQGSkpLg7u4uGiH3wdN89PrmGAqLlVet65pRPT0cndsDLta67Rv6KlH2fRJC6iZVo3bTiN6E1E7s2gWosIlUDlWxQW11/fp1vPPOO7h8+bLWMaLaAyzJi4uLw7p167Br1y7o6+sjODgYEyZM0DY5ogYXaxMcndsDT54XVdk2bcwMKVAlhBANqGrd0MjWFNsnd6EXXUJqGXZds/8nhEgrKChAdHQ0tmzZgr/++gsODg6YO3eu1ulpFKympKRg/fr1WL9+PZKSkuDn54cVK1YgODgYZmZmWmeCqM/F2oSCR0IIqeGUvcymZOUhePVpqpkhpJZqZGuKlKw8un4JkXPo0CFs3rwZe/bsgb6+PoYPH46DBw8iICCgQumqHaz27t0bsbGxqF+/PsaMGYPx48ejRYsWFdo4IYQQUhcpe5mlPuWE1E6sGfD2yV2owIkQCYMHD0b//v2xYcMG9O/fHwYGBjpJV+1g1cTEBLt27cKAAQP4+SYJIYRoj0rn66by+qXSd05I7SMsaKJAlRBF6enpsLS01Hm6ag9fGh0djUGDBlGgSgghOkDTl9Rd9DJLSN3Ermm6tglRtGPHDsnlxcXF+Pjjj7VOt2bMtUEIIa8YCmjqNvpeCSGEvErmzJmDYcOGISsri19248YNdOrUCdu3b9c6XQpWCSGkmlBAQwghhJC64OLFi3j48CHatGmDw4cP48cff0T79u3RunVrJCQkaJ2u1lPXEEIIIYQQQggh7u7u+PvvvzFr1iz07dsX+vr62LhxI956660KpUs1q4QQQgghhBBCKmTv3r3YunUr/Pz8YG1tjTVr1iA1NbVCaVLNam3zNAXIy6y67ZnaAdaNqm57hBBSB9BIz4QQQl4lkydPxoYNG/D5559jzpw5ePjwIcaPH482bdpg1apVCA4O1ipdClZrk6cpwEpfoLiw6rZZzwgIPa92wDp27Fhs2LBBYXmfPn3w119/6Tp3hBBS45Q3dQ0hpPaigihCpJ04cQJnzpxB27ZtAQCOjo7Yv38/fvzxR4wfP17rYJWaAdcmeZlVG6gCZdvTsCa3b9++SEtLE/1s3bpVct0XL16otUwd2n6OEEJ0iUZ6JqRuoinHCFHu/PnzfKAqNG3aNJw/f17rdClYJTpnZGQER0dH0Y+NjQ0AQCaT4eeff8agQYNgZmaGzz//HOHh4fDx8cG6devQpEkTGBkZgeM4JCcnY9CgQTA3N4elpSWCg4Px8OFDfjvKPrdz5060adMGJiYmsLOzQ1BQEJ4/f15dh4MQ8gqiQJWQuocKoghRzsjISOnfWrRooXW61AyYVLmwsDB8+eWX+O6776Cvr4+oqCjcunUL27dvx65du6Cvrw8AGDx4MMzMzBAXF4fi4mJMnToVI0eOxLFjx/i05D+Xnp6Ot99+G8uWLcOQIUOQm5uL48ePg+O4atpbQgghhNQVFKgS8lL79u1x5MgR2NjYoF27dpDJZErXvXDhglbboGCV6NzevXthbm4uWjZv3jwsWrQIADBq1CiMHz9e9PeioiJs2rQJ9evXBwAcPnwYly9fRlJSEho1Kusvu2nTJrRq1Qpnz55Fx44dJT934cIFFBcXY+jQoXBzcwMAtGnTpvJ2lhBCCCGvDOqzWkMVPQcS9wKeAwBDs+rOzStj0KBBfI3qoEGDVAar2qJglehcz549sWrVKtEyW1tb/v87dOig8Bk3Nzc+4ASAxMRENGrUiA9UAcDLywvW1tZITEzkg1X5z7Vt2xaBgYFo06YN+vTpg9dffx3Dhw/nmyETQgghhGiDBk+rwRL3lo2xcmMf4K3dQD5Ec2FhYUhISICPjw/Cw8MrZRvUZ5XonJmZGZo2bSr6EQarZmaKJV7yyziOkyydkV8u/zl9fX0cPnwYBw4cgJeXF1asWIEWLVogKSmportFCCGEkFcY9VmtwTwHAGb2QMv+1Z2TV0779u3h6+uLVatWITs7W+fpU7BKaiQvLy8kJycjJSWFX3b9+nVkZ2fD09NT5WdlMhn8/f0RERGBixcvwtDQELt3767sLBNCCCGkjqNAtYYyNCurUaUmwFXuxIkTaN++PebPnw8nJye8++67iI2N1Vn6FKwSnSssLER6erro5/HjxxqlERQUBG9vb7zzzju4cOEC4uPjMWbMGAQEBEg2I2bOnDmDL774AufOnUNycjL++OMPPHr0qNwAlxBCCCGEEKKZrl27Ys2aNUhPT8eqVatw//59BAUFwcPDA0uWLMH9+/crlD4Fq0Tn/vrrLzg5OYl+XnvtNY3SkMlk2LNnD2xsbNC9e3cEBQWhSZMm2LZtm8rPWVpa4u+//8Ybb7yB5s2bY+HChVi+fDn69etXkV0ihBBCCCGEKGFiYoKQkBAcO3YMN2/exNtvv43Vq1fD3d0db7zxhtbpyjia06Na3L9/H40aNUJKSgoaNmwo+ltBQQGSkpLg7u4OY2Pjl394mgKs9AWKC6suo/WMgNDzgHWj8tclkpR+n4QQQgghhEB1bFAbPXv2DJs3b8aCBQvw9OlTlJSUaJUOjQZcm1g3Kgsc8zKrbpumdhSoEkIIIYQQQsoVFxeHdevWYdeuXdDX10dwcDAmTJigdXoUrNY21o0oeCSEkBqO5mIkhBDyqkhJScH69euxfv16JCUlwc/PDytWrEBwcLDkLCCaoGCVEEII0SGai5EQQsironfv3oiNjUX9+vUxZswYjB8/Hi1atNBZ+hSsEkIIITpEczESQgh5VZiYmGDXrl0YMGAA9PX1dZ4+BauEEEKIjlGgSggh5FUQHR1dqenT1DU1GA3UXDfQ90gIIYTUfilZedWdBUK0tmTJEvj5+cHU1BTW1taS68hkMoWfn3/+uWozKoeC1RrIwMAAAJCXRzfFuoB9j+x7JYQQQkjtwvqiU8BKaquioiKMGDEC77//vsr1oqKikJaWxv+EhIRUUQ6lUTPgGkhfXx/W1tbIyMgAAJiamkImk1VzroimOI5DXl4eMjIyYG1tXSnt+AkhhBBS+agvOqntIiIiAADr169XuZ61tTUcHR2rIEfqoWC1hmInCQtYK5vttn6ojyeVkvYjKy9k9V1XKWnXBjXtoieEEEKI5rQNVGkqqyqwtClQ8Ej7z7sHASG7dJefWiw0NBQTJ06Eu7s7JkyYgPfeew96etXXGJeC1RpKJpPByckJDg4OePHiRaVvz7CSAlUAqJ99HVbu7pWWfk1mYGBANaqEEELIK4qmsqoiFQlUASApRjf50IHc3Fzk5OTwvxsZGcHIyKhKtv3ZZ58hMDAQJiYmOHLkCObMmYPHjx9j4cKFVbJ9KRSs1nD6+vpVE+wY16/4ha5Mg44wNjaunLQJIYQQQmooaj5cRSr6HusepLu8VJCXl5fo97CwMISHh0uuGx4ezjfvVebs2bPo0KGDWtsWBqU+Pj4AgMWLF1OwSmqA+beqOweEEEIIIXUOBapVoA69x16/fh0uLi7876pqVUNDQ/HWW2+pTK9x48Za56VLly7IycnBw4cP0aBBA63TqQgKVgkhhBBCCCGkBrCwsIClpaVa69rb28Pe3r7S8nLx4kUYGxsrneqmKlCwSgghhBBCCCF1WHJyMrKyspCcnIySkhIkJCQAAJo2bQpzc3P8+eefSE9PR9euXWFiYoLY2Fh88skneO+996qsz6wUClarSVFREQDgwoULSEtLq+bcEEIIIYQQQqoLiwdYjKBrn376KTZs2MD/3q5dOwBAbGwsevToAQMDA/z000+YPXs2SktL0aRJEyxevBjTpk2rlPyoS8ZxHFetOXhFrV+/HuPGjavubBBCCCGEEEJqiKioKIwdO7a6s1FjUM1qNQkICAAAHDlyBE5OTtWcG0IIIYQQQkh1SUtLQ2BgIB8jkDIUrFYTAwMDAEDz5s3RsGHDas4NIYQQQgghpLpYWFgAeBkjkDJ61Z0BQgghhBBCCCGa++mnn+Du7g5jY2P4+vri+PHj1Z0lnaJglRBCCCGEEEJqmW3btmHmzJn45JNPcPHiRXTr1g39+vVDcnJydWdNZ2iApWpy//59NGrUCCkpKXW3GXDsN0DcZ9WdixqnFDW3lKgm56166QHvnwQaeCr8JSUrjyZ8r81O/gwcmqeTpOj6IaTuKf3/f+na1l6V3RuN6wPzb1XFliqFNrFB586d0b59e6xatYpf5unpicGDB+PLL7+srKxWKeqzWkE//fQTvv76a6SlpaFVq1aIjIxEt27dqjtbNYMOAtVSiWW1+YFR+v//KdWreftRk/Oma1LnFaBqv0uBVV0U0ygFXITpCRJQ5xjSS1DtJf/yJbx+GPpeCandSvn/iK9tgK5vdfH3RgCo7PeLgkeVmXqVyc3NRU5ODv+7kZGR5DynRUVFOH/+PObPny9a/vrrr+PkyZOVns+qQtdaBbwKVe8VErCo3FVKBf8q/EguVB5oVDb57Zb3e3mJSa1fXfsG/P/N4P8fJMq+FwiW11b8y4fUuaXm+VUqf0CEiQvTEv5A4hhqcU7X5mNfVwhfvtgPu35qwr2qLlF2qRGia/L3Z2Ggyr8t15Lru6ZcN6Jj+P//r+5zVivG9Ssr5Srl5eUFKysr/kdZDenjx49RUlKCBg0aiJY3aNAA6enpVZHVKkE1qxXw7bffYsKECZg4cSIAIDIyEgcPHsSqVavqTNV7hfScC/ScyzeTTMnKw6X7T3ArIxenbmficW4hbj/O1yppVxsj/D0vSMcZlpaSlYe07HwErz6NlaN8cP5eFu48eo64m5mYGeSBYe1dAQDdlsUiYmBZM9FeLR2Rll22b53c7ZCSlYd1J24j6oS4ICNioCdC/JoAAOKTMhG8+jS2T+6CTu52VbJvQvFJmejkbsfnY2aQByJjbovW6dfaAeP8m/B/9/OoDycrk1rTDDYlKw/dlsWis7s1ziQ9Vbqe6Dv4phXw7D7/t1Jtn7JKSuclVgHwMu7Rk1suX3snvy7k/p+UrxSAnn1rxPeP5q8B9q/w/GbL9QBE/HlFdD2vHOWD0C0JAICA5naIu5mp0bVcGc3JI2NuYGZQSwDA3B0XcfK/xwju1AhNHSzgYGHM75vwHp2WnY+Ttx/h2I0MOFmboIVj2eiUTR0s0LahTZVd6ylZeQhaHovCkrLf7UzroVMTW6x6t6NO0mffJdvWmz/8jacFJXC2NETk2+01vgezYwegWu7fDNuvlKw8AFD5fdWVLgzy+yH8boXrAEBadj5/fNj/s88Erz6Nfq0dcP7uE2Q8e6F0e/1aO+DA1QwAwPGPeur8GKrzvahaZ+6Oi9h5PhVA2X1pgLcLImNu4P6TfDzKLYSpoT5upufi9uN8GOoBBvoy/DWrR6WcCz2+ikHyk0LJvwnff3Rhw8k7Ok2vOl2/fh0uLi7871K1qkIymUz0O8dxCstqM+qzqqWioiKYmppix44dGDJkCL98xowZSEhIQFxcnGj9wsJCFBa+vGAfPHgALy+vut1nFcDeyw8QuiUBZgYyPH+h21NtZpAH/yKma+zBBpQFoQBUBjiuNkZKb8jsxVWZlaN80LahDb8dAGq95OryRUNVgKqO6gqwVYlPykRGbgGO/ZuBb0a045cFrz6tdhryL66N5+/TWf4czA1EL0TCYAd4ed542JuUW6gzzt8VUSeSRecSe4kSnsvKzpf4pLLz08nKBLsuJCM7/wUOXklHYXEpcguKwZ4SxgZ6KOU4lHIcSkqBdm7W2DbZX8sjUPXYfn6x7xqcrE1w7EYGioqBEgD6KPvXpB6QXwzRPcvZ0hBP8oqQX1z2vbnXN1NZ2MGwF0VG2TXLClF0eR2FrDuNuJuZ6NfaAWZG9fiXV3nsvlZeAQ7jbGmIkwt66ySPyrDjIaVfawe1A9aUrDwcvZGOEL8mfHDyxb5rSLifC6DsvqXqfiAD0LahBRLTclFaCrzgAAMZ4NfMDhvGd+G3AUCUX2XPJnb+se947o6LsDCuh/H+Hrh0/wl/rsgXkqgjMuYGVsbcRjHEBVzs/w31AH09wLuRNVIy85CaUwQA8HQ0Q8SgNjXu/q2O+KRMnLz9CJExt2GkX7asuKTsOq4HwMhABmMDfeQWFKNIUOLnbGko2v+3OrkiLDpR7e0KrxX5a7yi2LmvKgiWX2fv5QcY4O2C+KRMRJ24wwfSjEKBpwo+DS3Qo6WDyoLo+KRM/Bj7H0Z0aKRy3yNjbuCP8/eVvhuN83dF2Jtt1MyZcsLnuq4D4KqmaZ9VTWOR2oqCVS2lpqbCxcUFJ06cgJ+fH7/8iy++wIYNG/Dvv/+K1g8PD0dERIRCOnU5WNU0MJAi/6JuqAf+oWNhqIcri/tVKH158UmZOHA1VaEGtLJJBYmaPKxYYKZtzYcuvqvKKGHWRkpWHj7Yco5/IQXKHsB7QrurfAmuqOG+zkoDgqrEgqyIgZ7wdLISfa9SD/J+kceQmP68wts1kAFBrRyw4I1WNeI8AF4GEgv3XMbp25l8LV1VER5vVS+hwvOyotdRfFImEtOyRS/f6gai6jLUA25+0V9n6cmTr7UW8rA3wZG5vRSW7738AF/svY7C4lJk5xWjuNJyV8bB3AAr3/FF8OrTkoWx8gGr8DqzNtbHs4IShTx62Jvgy2Ft+WtWeH9XFkxuOHkH3/z1L3KLKtaw0tPRDL+M6VRjrl1l4pMysfzQDZxPelrp37E6KqPQvLxa8fd/O4sDVzMQMdATa4/fQfKTQlEArkusMIMFroNX/i16tjqYGyB+4euiz8QnZeLt1adR3u3W09EMB2b2ULnO3ssPsDj6GrLzX8BQX0+t8/zu0sq7N1U2bQdY8vX1xU8//cQv8/LywqBBg+pMK09qBlxB6la9f/zxx5g9ezb/O6tZrct+jP1P7XXZw541r9k+uazUupO7HV87C0BUOppbVIqRq0/opGZn7+UH+HB7AvKr+OnHXiKlajNZjYCURramolJVYY2cNrUz289VPDhfd+K2TkpJK0JZMJpwPxcbTt5Br5aOOtvWzCAPNHWwQOiWBL5Gc+f5VGyf3IUv7QfETcaqAntplqopCItOxBf7ElFPT4bCF5xOX/ZecMCBqxk4cDUDegD6aFADVhnkr4vqEBadCDtzIwzwdsGl+08AAJfuP1F4CW1ka4qIgZ648iC73DRV1c6y7gr9WjuI/pb2VLvuFsoUlZbV3LLaRV3LLVB+Zt5+nC86Bqz2VJOaMV3IePaCDyqlWg1FxtxGUwcLDPB2gefCfaJny9MC6df424/zRYVLadn5eGfNSSQ/KcRwX2e+hQhQdn7/ePQ/nRQ0AUBi+nO+K0tNrJmKT8rEhKj4Cgflupadr7y5cEUoK9iK+PMK/zwRnvPaBKp2pvWQmaf6KZCY/lxlQXbGsxdo8ck+LB9ZVsMsbIJcnowc6RrXlKw8fLH/Gk7dyhRdK4Ul5X/3rCvWq2T27NkYPXo0OnTogK5du+KXX35BcnIypkyZUt1Z0xnq1qQle3t76OvrK3RgzsjIUOjoDJS1N7e0tOR/LCwsqiqr1ebzwd6Syzu7WyssixrfGQD4m3BiWjaCV59GfFIm/8K5cpQPgLIggTmT9BRzd1zUOo/xSZno9PkhhG6p+kAVgMraDk8nK4Vl8k06U7LyFF7Ig1efFq1Xnr2XH+ikRjDqRDIi/rxS4XS0lZKVh10XlAfdduZlfT4CmisG8tsnd+ELSMrj09AC2yd3wcyglhjg7YLjH/XEAG8XvgChk7sdZga15M9Xdk4Lz9vqVFhS9nJdmad7Kcr2u/H8fQj85mglbkla969iNApUnS0NYVBJ3XtCtyQgPikTmc/KXswcLIwV1omMuYGw6ETsPJ+KbstilV6/rDBG/u/CQpqVo3yQ9Vz84sqa4Rlq+MQXXivyATDr2rDh5B34Lj6IwG+OwnfxQbz/21kEfnO0LJg9eUezDQIYvPJvtHFRvPcJfX+krOUS2++KBqrj/F35/Svrl+8quZ5PQwuNXppCtySgzacHtH62jFt3hv/udp5PRWTMDQBlNWuhWxJ0FqgKhUUnotWi/fy2qtPeyw/Q/asYNPt4H4JXn9Y6UK2qF11dHTNhYTTw8rmfkpWHfq2dK5y+T8Oy98/pQc34ZfLXtyYKS8rO9cbz92n0LpGZV4y9lx+Ilm04eQfdlsXiwNUMpYU6yozzd62RBS2VbeTIkYiMjMTixYvh4+ODv//+G/v374ebm1t1Z01nqGZVS4aGhvD19cXhw4dF7cQPHz6MQYMGVWPOaqaIgZ78C4UwQJNv/spe8NmLppOVCY5/1BNA2Q28bUMbABB9JvpiqqjEWR0pWXl8ibUmWLNk1keQvdRURrPhk7cfiWpIWVNd4UPs6I2Kj/Z2/l6W1p+V73fJjoOqGlZWA6TLgZnYsfF0NFO5nqomwJ3c7XD8o574/si/Kh+4K0Z1EOVb2f8P8HaBg4WxaNAsP4/6yMgtqPYaP21tn9yFb2Iq7GOrqgn07cf5aDx/H+xM62G0nxuGtXettKaG5ZXqWxvr42lBiUJtt7q1Ep6OZmoHCMJrQ9i1ICO3gF9n7+UHyHxWKLqfzQzyUHp82PUu7IfZyNaUH9invKb8Hg6q88/ua0zczUx+WZcmdgotBIR9uFkNDVvn9uN8xN3MxJK9iTCqp4fi0lIkfq66eV6nzw8h49kLpD59OU+iVBNmFsw2sjVVu5+9p6MZHCyN0aulA8KiE2FhWNakcPvkLnCyMuHvDaxlj6+bLY79myE6nxLu5yr0LZcnX1tVkZpA+Rrbi8lPERlzQ+2WGuzYsOtzZpAHbEwNERadyPeJlzqnn7/gEBlzG5Ext9HZver7pY9cfUKtZuvCsSLYNc1q1sKiE0UDAgrXkf98RcbUiDqRDCsTAwBl7yUXk5/qtMWBsD978OrTsDbWV+tzwncueRO7eyB0SwJ6tXQUDQZZ2S2Ayrt29l5+oFXBE+vyUhv7XevK1KlTMXXq1GrZdnR0tMaf6d27N0xMTNRen4LVCngVqt515Ule2csgG0GWNZMc1t6Vf3kVBmEsKJVqLidfq1BUWv4ocMJmY+r2zxQ+9ADxi5yvmy2iTiSXG6TKv/xpgh0fts/yeY5PypS8sUcM9ERadr5o1ENA9aiQ6vCwN0E7Nxv+5U1Z89aoE8nILSjGjMAWomPuZGWiEAgGNLfDtJ5lpbvbzyXDwrgeGtuZ4fSdslobdfo/Co+NUb3yy9CFfXvY+SgsBJgR2AI7z6cqPOzZS60mx5EFwOwzTlYm/KjS5QV6Ui/hrLlxWnY+MnIL+GCY8WloIepPpA2239sndxEF1qwgiQWqwmCcNX9WFYhn5hXzL8BA2cOnt46aCqdk5aHHsliVfaTY8ZSv8Rb+TfgyL0XdQFU+nX2X0vi/sRpWZc2UI2Nuw8bUUPJ+xu6jT/KK+PtYeS+A8vmXum5Z4CJ1r2LLerV0hJ25kcYFLUWlQNH/B2yN5++Ds6Uhtk3xl2zeyIL7ktKXgcPoro1xJkm8TdbqZO/lB0oDVfl7r3AQoV4tHUV9QVOy8vhCUVaQxu4JwR3KCiTZue1gYay0f6Aurj9VElNzEH9H+WB9DBulvpGtKT9QDtuP4NWnRceGndPKgv4zSU9FhRK6HlBInjqD2LFzfqhvQ/66jYy5jXH+rujV0hHdlsXyyxa80Yr/f/nzngW6qgJVVuOoLJBztTFCZMxtvrYy7mZmhUelZQEqu1eVbV/xmaSK1HrC7lXy41uw7bHru7zuKzODPHD/Sb5aNans2SmFvesBL++N5RE+o2rTbAR11eDBgzVaXyaT4b///kOTJupfIxSsVsDIkSORmZmJxYsXIy0tDa1bt65zVe8V0cjWlC8NjIy5zfeFScnKQ2TMbWyf3EWtGiqpdI9/1BO7LiTzD9fP/0xU+nBgo2ICL2tWpLDSOaDsgc5eaFjJY/Dq0/xNsm1DG37f2DIWdAhLsVn+hDWw6g7Es3KUD38cWJ+2sOhEvs+bk5WJ5MNL+Lvw4SMcHZalu/fyA7WD6duP8+VqlZvwJdnyedh5PpUP+J7kFSl9oYy7malypOQDVzNUvhyxwZSY66nKXxRvZZT9TfiS6edRXyGgFBacCPu4avtAlD+vWdos0Avu4IoeLRwQuiWBLyBhAyOx70/4ksGCc5YOO/7seylv9GCp0alZoCmsCWYv7IwwH+wFo5O7HX8dOFmZ8C8k6rxUFaPs+x288m/sCe2u5tFUpGowHkCxtYbwJY0F/qzWG4Doml45ygcOFsYKAxYxyoKT7PwXonNe2PqANUcXvqTJC4tOlKwpsDE15P+ffTehWxLKHXGciRjoiV4tHfmXUHbOsM+yINvTyUrh5bKRrSnfuqUifURTc4oU+uNtOHlH9B0WFSvWRg73dYaFcT1EnUhGYlo2v+9Cno5m6NPaEZExtzHe3wP9Wjvz15HwWAoLANn5y/LD8iT/O1DWhLuTux36tHGUPOdWjOrAFyTJ522cvyt83WwRuiVBshBTne9QajoVFlSwgiy2fwyrNWb3EnZus3NBiAVdqgLu0C0J+PHof0oHxmHdMTRtQaGqVYQMAAsnIwZ6ilpYsfcKNn7AeH8P/jtl9yt2Laoq2JHab+GxUha4sYBX+Fl2jWtCagRo4TNBk0Jv4bnACl8A5e9YwueS8PqWKsBg7y+skFedwdsycgv46+/4Rz2Rlp3Pj1q860IyP0DV6mPS7wnsXL10/wl//2bvZ6RmSE9Ph4ODek3JtekGSaMBVxNtRvyqraRq9nQx7Yr8YDpSw6ALA1UprPmPOlNMCOcilO9Lwl6+2PQDwhJ7YZNXqWkOVBEOliQcTVRVGq42RpjQrQn/kGUvleyGL3xRVGcwBPYyxF6whC93wMsXP/kReHXJ2dIQbV2tkfW8CHNeb4lO7naSeZdqFsbIB1A1YSARYdNudp4Iv2NAeqAN+XNQ6jPsRUOqhjR0SwL/0qHq3BfOTSg/J6eQsmuCKS941ba2ps2nBxSaWTqYG+DTga344JodU3VL4ZXNU8lqQsf5u/JTjbRtaINL95/wx7a8ggI703o4/2kfAOUH2WyUUfnCJTagFwDR91ge4aid8q1TLt1/gsxnhXxthXx3A3nKBjJj1xxrWqrqRdbCUA992jgi5tpDyQJE4f2GtcRhAR2718vfA9h5JH8+qtoPZee0KsLvjgU5Ac3F09l0WxbLnw/CEWPl57Nm5yUrEGX7senUXbWawrKATNW5LT+Ht7LRhdlc6OrWnrN7ztwdFyXzqu517RP+l+Q5IDx/IgZ68oOVsbwK50lly6S+d+G1zIJCAJKFLuxexb4z+ZZY6lxvUu8iylo4sZH82TFn3ycrNAOka0mFhHnS1fRXwvvg0RvpfAGq8LkvPDbCYJ+d0wv3XEbczUzJ86D7/8+/ykb3lmpp0tndGqO7NkboloQaM9tAZauNscG4cePwww8/qB2Evv/++/jss89gb2+v9jaoZpVUOqkbjC5uOsKaW6Cs5HG8v4foAaUqUBW+DMnf3FXlWap0Ur4UnqXHfpefZkZdwpfGtOx8UW00q/UJXn1aVCov7IfLmg0CZaW9rAQVKHsYST105YM8VoPar7Uz/4Im9eCozOZvqTlFSP3/PAWvPo16gOQAQZ2a2CH5//dJqiRcWFIcFp1Y7aWzwtorYckzoHhuCSnLs7BAZFh7V77mGBA3rWc1RMEdXFWe+6rO+fI+I2xWya5RdvztTOvhaV4x32x31tYEjYJVVVMQZTx7IerzzvKiTvAi/Awgvm7ZwEi+brYK17X8CNDKlDWFvoGZQS1x8d4Tletm578Q9VdzsjLhm8llPiv8P/buPK6qOv8f+AtRNkUElE1RkVIxVBRzwTE1SVMRnVJqKMelX9FCRmqm1YTUqGnWMBNl1EzodxozJ8eGNMsNTVGkodBM1EkpQCEUEBcQFO/vD+ZzPPdwd+7O6/l43JJ7D+d+7uUsn/dneX9wb/8go4YFTh0c3OI5sW95RVk50kCTUD8vtV4qbXOZpwwM1hpwXWm8pbPS39v/9vxz8b3OGhb6v7VjQ5qHfvcLkPYR0tlNOoaMGaWjbxtN5o8Ol66Fvx3aA4VlRZg1LFRtv/LePfk5Jv6taUSHvEFFNIQAzXkFNDVsiB5jfWtzKt9LVzAjz24uD1w1BWn6Gl3FsGld79f3pe1QTuuV9wyKXmHl9UHZ6y2e0/Vv5aiUOTF9pFEE4joVEewjHcMPDu0pfXfiuzCkYUjMYRW0LU2lDIRTYsOl8smDVn2em9APz03o1+Jzt4a8DiMadZXH1/Awf+m7Kiy7onb8yutfyuG9pdV1Uj1lSK/mv/P2Yy2/V9EwbeqSfGQdWVlZRm2/bt06o9+DwSo5NOVQtTFrcvDzG1M1ttKJhCfyRdDlwW1rGDJsWT70TFslU1sCF/lNTfTCJW8slDIrK4Pyrd+VAUCLyrNoVdZVyZAPKTtaViPdrOVJXOS9eKLyf2DJeHyUe0bvcCVlUiYReIrEJO6uQA9f3T1U2pJryueayoe9/Vx1zepLWxhCfmzIySue+o5P5T7kDRLKlnBBXmG2FGUlPCEzD3cENLe8VtXdVDsHbqggLWyvj64laeSVXEHe66yvUq98XVnBF8eU8j2CfTylOXNZuSXISIySeiqVxFIX7h10J0oRjW/zRvdsUWFNzS5S27emHt3JkQGYOihE+q6yckswOTJEradZ/jkB44I38R2IYGx4mL/U+CNvGPHv5K412FIaEdYFA0I6S9vKg2cA0jWo8sr1Ft/J+cuNZhmxYwxRPnmPn2Bo0K/8HaDlcTi4h2+L708eBGu7juh6L23bKK8l8ukKnxWcN3o9z8Wbv8c3L8ZqfC3iFfVAVX5vFszZo6bpe5J/h/JRBcrtRBAvzmttw6UnRwZoXXdVOfXp0JkLaq8rl8ExJFCVTxeyNE3vI3IXKHv2RTK4EWFdWoxgCvXzkq6VPXw9UVpdp7FxWdPwZXIsly9fxt69e9GvXz9ERJi+rBCXriGHJm4wcr2Xbm9Rmd2cNBL5r0xs7gGouGb1i6Cy4n5v/yBsThrZYokEZaAaEdQRoX5eUkVZ3EDFTU5br4W4icqz4/5UeQUJmXk6MwiL8oi5fGLZDQBSL4Gyl0q+lIa2CqkoR1p8BCqv3lBLHCECT5FBs6GpeX6spiVmtAno1EHav3y+0OakkUjNLlLL3Aw09xLYy7AiTb0DxpZN0z7kQYiu5VCsQVTc4wZ1l/729/YPUvub6Bt6WFpdh4hXNJ/b4iGWEJI/tM1H1kTT9nJiqSLlvkUQ1RwQNs8/lo9qkPPx7IDS6jqDhngu/uf30j51LX2kqWFnZB9/jUG1ckSK+JzGngvi8yvngir3FzeoO1KnDZSGNGpbFgYA1s4agvmjmz9nanaRtAyXsnwB3h44sGQ8ZkaHSM8pAwFLUn52bY0sppZH03Eov88ZOhrI1PeWE+eu+P+hl+7D5qSRWpdBmhkdonZ915ZxP2blLrUlfdLiI7AjZZzFPpeu/Ylro7yBQdkzK0YgiEYibSOJRvZped8Sf0954/qGQ2dbNCaL9YXlo1EcwfAwf61/pyPFlzSOJhO9z18Unpeun3LWDMLJfBISEpCRkQEAqK+vx7Bhw5CQkIBBgwZhy5YtJu+XwSo5PHnLuybyG7shrd2WJHpWx6zJadErnBYfgQNLxqsFaUUV17Dh0Fm19VRLq+vw4FDtFT45EfyO7esvZU3U1sOYkRilNvROlE9UcEWFRXkTV1beNa1XWlRxDRmJUZgT00cKWjYnjZQqNWnxEchIjJJ+d3PSSLVhdbpEBHWUemr9O7lLFfTBPXylIB+4XREAmntgNd0g7YU5K56mBL+WIA9eRHlSpw1Uq/RqygQ68NUd6L10O8asyVGr3MpvXiLBk6731fazvu11va7sdQVuDz/XNiQ4ffcZjceePPASREC743il2v40LV9hzDApc10Hjfl9kcxn/uhwKXAFmj+3vBFM/t3oC0DlQzLlSwJZg6XPJ21Bo7KBwBqUjTfDw/zx8ePN1+rwrs3nnWhMXTtrCOIGdVc7npVrLU9O39eid1aZ7MlalA2u2v6uIpmcnMgALJeaXaSxYbC8tl7tffI0ZHX+TJrConuosbhfAprXbbYHc2L6IKRzc0K4d3P+2+J1UYc5c7E52ZK8YX3e6J4WzThNlvPNN99gzJgxAICtW7dCpVLh0qVL+Mtf/oI//vGPJu+Xw4DJaXm7tcPf5g23eEutMeS9XUfLatR6IiOCfRDq54U/zhgkDdMd29cfqdlFUi+NyIAsb7mWkycYktt/ukrn/DZlIgeRKEpXL5P8M8n/Lf+MooVYPudIPhxaBLfahn3Jh1JqSpAENN8UxTBpMexXXskVN/Offm1uCR8R1kWaC9NW2DpQVZKX5+PH1Xv5ei/djnmje2JzfqnWJSVEUg75EHRbf0ZxnBmS1TXYx7NFps3nJvRDD19Pg9YM1ZSMRjk0XlxP5Mm7NAXa1iL/O4ms6wAwrl+A2nB1MWpkZnRIi3NUBKSVV64j2MdTbX69vVbazcnWx7icCN7EnFll2cQSYEBzQCKmoDz43kGNWY1txZjrh7JBTNm7qi2Jm6al56qvaR9KrW/IvDyw19ZIZ2v5xVVSg4SXW8vGNWWDnXxU2eTIlg135Bhqa2vh5+cHAPjqq6/w4IMPwsvLC1OnTsULL7xg8n7Zs0oWZa2hh+KGI+9hnXl3D2kYmT0RAZ2mIXrA7Yv45MgAqdIrlqwQ2V21VcwmDAiU/u3vpd4WJYbHinXj5O7tHySVJy0+QmOiEmOIzygf/ql8XVQQdDUmiJ7YzUkjMSemj1rL9r39g6S5MOJ9ZkaHqA0flBMViyPFl+z2Bt8WDQ/zV+tpA5ora7rWPlz/v6yr+hpSrEkcU4YsIbP3ZIWU3RZoPudC/byk81zMRTfF5MgAtaVaxDlmD9+RvGdOPnRbHiyIeXufFZxvcQ6La1SAtwfGrMmRAtW0+Ig21fhkL5SJBOVC/bzUeh7FiCJloKqcWmILhr63uG+JoezyIe2iAVnTvuSBmfj3qHDtx6vyeqgkEm/Zs+Fh/lLvuqah0cPD/KXr388XbweqPX3deS47sNDQUBw+fBjXrl3DV199hYkTmzPQ19TUwMPD9AZFBqtkMcrhNZYm79VLiQ1H6rSBNr8J6iJuWuKCrrwByddCnBPTBymx4dIQMG3DhOQtsmIOqCCGEWtKZFBeW49QPy9pqK45GdIjq+/3lTcvTfNZjpbVSOvbyv/umgJTex4C3BbpGwKYkRiFn9+YqjZv217Ihw8eWDJeZ0VTVN7FCAER2EYE+6C0uk563pD5rNqIpEr21kinJJIyAerXAjEVISW2ZfI7eYIlOVsNISXdPk++R2clU/TM2tP5rI98RNTkyBBpJI9IRKVpfqb8HiQaUuXJlOTD+jMSo9RGHmgisuPa27VQrrS6TmfmZJEteERYF4yUBe5rE4ZYo3hkISkpKXjkkUfQo0cPhISEYNy4cQCahwcPHDhQ9y/rwGCVLMZWF9NQPy8pG5+9XsiB2/PcRAZbbRXMrNwSbDt2Dum7z0jJkeTDZEQvTEZilMZeU0PlF1epJVSyR6JHRtN8FtHrYuxi9GR7mkZGAM0NNSKxSWl1nZRAyV7IG+TEUEhlRVMk89qcNBLj+jefnyJoFQ1VlVeuS41FmvT0ddf4vPJ9gObzwJ4rsfqIwFPTvHxR6ZePLNEU1JL92K8ln4S51gO1ptLqOunYy0iMQkJmHlKzixDs46k2LDq/uEp6iLVr5Y6W1ajlh1AO6y8qr1X7WT7SQj7FxZ6Pe/n1TFPwHernhbT4CBwpvqTWyM5RT47t6aefxuHDh/HRRx/h4MGDaNeuOczs06cP56yS/bLni6k9EAHWvf2DpGUfxEVcPj/zp8rmIayp2UWICPZRS3nv19FN+vdLU+7S2HOqi3wInbEVCGsvFQFoX25F9LrsPVmh1jusqRd1839KHK6i5OzEcSRfj1i+9qw9Xkvk87PFepCiMiuWZnhuQj+p7Om7z6gteTGuXwB6+HpKjS9xg7rjp8orLeatyueha5uXPrC7j5Q4zJGPbXG+itEech/lNn8vWblnpefSd59hA5UdU54jgOMGqvIl3zRNxRGBqnJ+qjIxk1gGR5CvYSuWeZLPfRcjLeTD+x2BqN/oC0C93drhinKxXXIoo0aNwowZMzB9+nQMGzYMw4YNU3t96tSprdo/e1aJ7Ix8OKCgXH9Nbt7o5sBMDA3S1jtjCJEsw9By2npJFE1Ss4vUeoeVN8qoHt4a58ORfZDPa1Q+Z49EA5NYg1Wso6wpSUhafIRaUpZ//qcU6bvPqB2vYt6qNspAVcz7igj2ccggQElXxTZ12kDMjA6RrnkCh/XbN/kUHVtkMzYHebZ7+TI0oqdz27FzACAl/pLb/J+WCZP2nWpuVE6JDcfaWUOkkRGil1E+912MMHG0DLmGjq4TgerM6BC7vtaTdk8++STy8/Nx9913o2/fvnjhhRdw4MABqFTac08Yg8EqkQ1t+a5E+r+uwO/shWtSMofKK9fVKrSVV66r3RDiBnXXuZahLsYEoPY2Z0Y+j1de4ZVXZMf29cfnyfdYdU1GahviBnWX1kIVSb4EcV79cE59eN+Qnl3UAkxNDVX6iEqtruV7HJGmJGliHpyy58qZPrczE0GrIxPHnrj/DQ/zx7Zj55C8sRAbDp1VS/wliEz0cuP6NQe0orFK1/zO+aPDHTLAB3Q3NCqvhz18eR47qjlz5mDLli24ePEi0tPTcfnyZTz00EMICAjA3LlzsXXrVtTVmd5BwGCVyEZKq+uktU9TYvtLgZ8IYJVEi2vV1QYps+/M6JAW8/hKq+v0pr4XRoR1URsya2wAak8VD9GTpUy+JE/Gsv90FdJ3n7TLLNHk2MS8ctFQJF9CSZxXCcNaNiIpe5A1rVOsjXwtS01JxxyRru/A2O+HyNLEXPqMxCj8XHVN4zbBXVoGYVVXm0dIZCRGqTW2aGtodsb71bUG9SSQdwS0XLeWHIu7uzumTJmCzMxMnD9/Htu2bUP37t3x6quvomvXroiLi0Nubq7R+2WwSmQjtzMX91eb+5kS27/FMKI+3TpKKfPnxPSR5oJoGs5qzFDgI8WXpOFLjk4sgaIcKiVfIigiqCPSd5+RlgohMofS6jppjV/RUKRcQknT8RYT3q3F+Ts8zF/qodVH3hujXArLkSmz/Wp7rTUJ5YhMIdYtFqMlxEikuEHdta4PqimPRN7Z5hERYvqOyCIurh/ya8DRshq7nHLTWusevRsdXGxdCrKkESNGYMWKFfjhhx/www8/YMKECSgvLzd6PwxWiWyovLZ5sXTljeilKXepbdfbvyPKa+uRlVuC/OIqvT0Mg3v4Sku4bE4aqTV4TYkNVwvu7HUeqiHyi6tazFdVeubeO5EWH2H25XmIgOZEaeKcEz2ruuZTZuWe1Xi+pcT2lzIGizmpgq7z2RmIrOTaFPxSLf17x/FKDuknqxD3xqNlNUjIzEN5bb1aBnNjs+jLj11x7wKaz++U2HC1JGvJGwud8jjfcOgs5MtpO8KSW2S4q1ev4vLly9KjW7dueP755zFz5kyj98VswEQ2Is8aqLwRKSu4P1ddk9K/iyFDw8P8NQ7ZlWctvCPAG3GDumvtPVUuD2Fv81CNITIkHzpzQev8HpFpUWReJjIH+XlTWl2nMRvo8DD/FnMr+wV546Upd0nHohhhkV9cJSViKpNV3pQJlERQ5yxDgAG0SFyjNH90uNo0B129sETmIs5x+b1ZnO/ifisflq9JSmw49p2slM5tcazLrwuHzlxQC1TT4iOc9n41J6YP8s5WYcfxSsyMDlHLnE6Oqbi4GMnJydi3bx+uX799bVapVHBxcUFTU5OO39aOPatENiZfOkZJDAWK7uXXogKsbdmYUD8vad6LSK8vHyIobqjahsI6280i1M9L6p2K7uXnsME42TflMSV6VgHtCYBiwrupBaqil3V4mL90DvcNau5hTYlVT7ISN6i7NHTQmejL7Ktcs9Le14Ym5xHq56W2nqp4Toym0JcgyNfLDb8d2kP6WRzrYh8ZiVFqgWpKbLjTjwISmb11JZgix/HII4+gpqYGH330Efbs2YO9e/di7969yMnJwd69e03eL3tWiWxkeJi/tNxFRLCPWkVUfkMUvaMi4JS35ioDL7EAuTLBkhg2nJCZh4RhPfFZwXmNC3U7spjwbkjffQYx4d3Unk/ffVLKmDq4h6/G9RuJzEW+rqSuNUNnRoe0SK4kP59FD+LUQSHYcbyyxXEtHzqYvLEQAd4eDpsxVE5c+7QF+GLJDzlmAyZbEknUlL38kyMD1OarisSIQlF5rVrQKxpixDDgOwK8pRFYztrIKupBYu4uObZjx46hoKAA/fr1M+t+DQpWFy5caPSOX3nlFfj5+Rn9e0RtyeAevlIQqbwZiTVPkzcWtriQaxquKwJY0dui7ImRDxvW9p7OKCW2P2rrb2D+6HCU19YjITPPKdajJPs2Zk0ONieN1HqsGbpMg8gaqqwIi4RiImB1poCtqLzWqOsTG6DIWkTwqOm8FiOZhH5B3mrBqmhQ+vvhn3Gk+BJq6hrV9iuG9Yt11cXPzjhfVRB1HNHAR47t7rvvRmlpqW2C1fT0dIwaNQpubroXKxcOHjyI5ORkBqtEOsh7R7VVypRBqXzor3J7EYSKSq2mNPCiV1bbfFdnJJbymRwZonGOEJG5KRuE5M+L3hZlT6lytIQ495XDXuXklV1nse3YOaPWms1IjGLDE1mNchiwtuk4Ypva+htqI53yi6twpPgSAPV7dFH57TVH5ds7e8OqufNkaPt7kHX89a9/xZNPPolz584hMjISHTp0UHt90KBBJu3X4GHAW7duRUCAYWnivb25VpKz0LXsArWOoRdpEWACUKvMKi/KIrGLrnls2oYPOwMRpCt7oOSBg8iiyp4YsgT5ORns49niPEvffVLjMhZAyyRNImAVv69ckkms0+xsiUnkvVNHy2pafK6B3X2k+W3zRvds8b0QWZo8UJXfT+VD2MVxmzptoLSkjRgtJYhjvbS6DqnZRVJDlvi/cnSUszJnoOqs9RtHceHCBZw5cwbz5s2TnnNxcWl1giWDgtWsrCz4+Bg+vy0zMxOBgYEmFYhsZ0bGNxjSyxdXrt/E7h9/hX8nN5y52Dznyt0VcHNth5l398CV6zcxrl8A4gZ1R35xFYrKa3Fv/yBs+a5EGm75Ue4ZVNRex7zRfdrExdZUhlxQ5RdgMRxIPKcp0cPekxUAbg8fVL6fMyZlAW7f+JVDsQD1IdBVVxt4TJLZyc9TAGr/Fh4c2lMtgYqStvnomgIysZ5y8sZCjOsX4DSVM9HYpC8QHdvXH1m5JfDx7ICU2P7WKh6RRFODs6Z7i3JuupiTKuasyhtU543uicmRzfPU03efwYNDezrNuW1pjryagbOYP38+hgwZgk8++QSBgYFwcTHPQroGBatz5swxaqeJiYkmFYZsZ0bGNygsuyKlVAeAS9dvZ2VsaAIamm5Jw1M+KzivthaefNiWfAiLWEuMwYFmxgxZEfMtdc07DfXzkhInaUqglL77JNJ3n0FqdpHT/V30DfGVr2enTGhF1FrKnlFNlSaRcCktPkLncWpohUskXdM0r91RiQBVU6MT0LyWbWp2EWYNC8X+01VSUjWez2QLppxzm/NLAQCZ+860yPYrpqykxUcgItjHKc5pa4t+7WtcbbiJBlknniuAWwBUaA58osO6YMrAYNzbPwh/3nMKCcN68hpiBr/88guys7Nxxx13mHW/Ri9dU1pairKyMunn/Px8pKSk4IMPPjBrwci6/vvrVYvtO1Gx5Ao1ky9VoYuovCrnmRo773TbsXNqvToJmXltbgFu5XwjInOTr7uojX8nd53nfluvoAZ4eyAhM0/nkjQimNW19BeRJbT2vpn+u6Fq/wea700pseGYGR2CovJapGYXtcl7dGuIa29VnXqgCgBNaA5UAeAmgCPFl5CaXYQxa3LwWcF5vdcbMsy9996Lo0ePmn2/RgeriYmJyMlpvhFXVFTgvvvuQ35+Pl566SW89tprZi8gWcc9/brp38hEf3DSYaetJV/WQh9NSZW09cpq6mEUGffkaz86G0N7pFixJUsQFSVd5/OhMxcANA/RN+dwNWfLFhrs46m1UUneeCeyIbNCT9ay7dg5gxqZleTba8qvIBqTPys4b1SCMbpNXyOhPnP+xo6V1po2bRqef/55LF++HFu2bEF2drbaw1RGB6vHjx/H8OHDAQCbN29GZGQkDh06hI0bN2L9+vUmF4RsK8hH85ArIarH7aRZ4V0Nz6TaFha1NpWuCpk+unplNQVtYthwanaRlPjFGed2GDoHmMjc5EGUpuBRJEQCmntWzXnuOVN2a0N6puVD+jMSo5zuOkb2Sb68jGDI/UR5vxbD98X/5eR1LR7bxpE3xHdwASKCOiKgUweEdHZDxw4ucHfV/ftvJkRZtoBtwJNPPomysjK89tprmDVrFmbMmCE9fvvb35q8X4OzAQs3btyAu3vzwsa7d+9GfHw8AKB///4oLy83uSBkW2IBeqV5o3siK7cEL029CzuOn0dWbgmmRYVIlS6R+U4sr/BT5RW1oaYPDu1pnQ/gYOQJkkyhrxdR0/NtYbkafXOAmS2QLEnMV5UvWSMfFSGWojFXBltnTChi6DrQHNJP1qbM9mvo/UScp4J8VJX4PTGsXeQNyUiM0hjMknbyRru9L2heh17UaQ8sGa82CqbyynVmFjeDW7duWWbHKiMNHz5c9eKLL6q++eYblYeHh6qwsFClUqlUhw8fVnXv3t3Y3bVZpaWlKgCq0tJSWxdFUlJ1TbU+94yq14vbVF8cLVP1enGbqqTqmuqLo2XSNkfOXlSpVCrVF0fLVCVV19R+V759SdU1tdeppSNnL0rfmabvSvkcv0/dxDEojlFt9L1O1FrinBbnt67tzPVezsaQz8RzmWzN0HNPfj0Q93758SteFw95/YAMp+t6KJ635+/U0rFBr169VGievis9XnzxRYu8lzkZPQx49erVyMzMxLhx4/C73/0OgwcPBgBkZ2dLw4PJMckzyQ7u4Su1BCZvLJSGr4hW7LhB3VsMMxWti+I1Z2rttwTR0wmgxZBe5bAhQ5MxtWXyHhlt35Po9eL3SJYkrn/KpWvkzHFOi30447VB31z+/OIqJkUhm5Ovg65vO+V6rPJRAcrjvai81ulGTViDrrqnptwfbdFrr72G8vJy6fHKK6+0an9/+ctfcP36df0b/s/777+PK1eu6N9QxkWlUqn0bwZcvXoVnTp1AgA0NTXh8uXL8PW9PUTh559/hpeXFwICAowqQFtVVlaG0NBQlJaWokePHrYuDgD1oanyi6gxy6uQ8USlS3ljUn7v8hsi/x7aGTIUmN8fWYO+YYKtPRa1XbMdnbgm6vtc246d49A9silzTi3ZduyclAmbgWrbZOnYoHfv3khJSUFKSorZ9unq6oqKigp062ZYotbOnTujsLAQffoYns/G4GDVw8MD48ePR3x8PKZPn46QkBCD34RassdgFWBF3toMrZQB6olHeCMjcgzarqnmuNY68xzs/OIqnddEZ/7s5FjMeS6nxIYDaM73weO67bFGsNrQ0IDGxkaEhoZi1qxZeOGFF+Dm5mbyPtu1a4fIyEi0b29YGqQffvgBp06dMipYNTjB0qlTp5CdnY0tW7YgJSUFgwYNkgLXQYMGGfyGZN94cbQeMSTVUPJhhfw7accGF7In2gJVBlq6OVNPMTkvc91vQv28MG90TylBZfruM7w+tGFXrlzB5cuXpZ/d3d2l5Lat8dxzz2Ho0KHw9fVFfn4+li1bhuLiYvz1r381eZ+pqalGbT99+nT4+fkZ9TsG96zK1dbW4ssvv8S///1vfPXVV/D19ZUC17Fjx8LVVU9+aLLbnlWyrtLqOpTX1ptt2E9bD9QMCQL09dgQWYO5zlVnPOcN+UzOOgSaHIc5G52USzbxuG6bRGyglJqaiuXLl2v8neXLlyMtLU3nfr/99lsMGzasxfNbtmzBzJkzcfHiRfj72+/xZlKwKnfz5k3s3bsXX3zxBbKzs3HlyhW88847eOSRR8xVRqfEYJXkOCTQfHR9l8YMuyYi6zPmOqZtvj+RJcnvMeZsdGKwSiI2OHHiBLp3vz0fX1fP6sWLF3Hx4kWd++3duzc8PDxaPH/u3Dn06NEDeXl5GDFiROsKb0GtDlaVvv/+e9y8eRN33323OXfrdBiskimYPKj12LNKZN9EMjlDelfLa+t5PpPVWKpRWD5nNSa8Gxth2ihrxwbbtm3DtGnT8Msvv6Bnz54Wfz9TGTxnVe769es4duwYKisr1RaAdXFxwbRp08xWOHJwjdeAom1ARBzg1tHWpXFoovKm7ybJG5tupdV1rNiSRbHByDz0XeuYcI5sQb4Ejbn3m5EYheSNhfD1cuMxTWZ3+PBh5OXlYfz48fDx8cG3336L559/HvHx8XYdqAImBKtfffUVfv/732vscnZxcUFTU5NZCkZOoGgbUFcFnNwODEqwdWnsliG9paLixhuYbrq+Sw6TJkuzxbBUZwyOLRUQEJmDpY7LuEHdUXW1AanZRYgI9uHxT2bl7u6OTz/9FGlpaWhoaECvXr3w+OOPY8mSJbYuml7tjP2F5ORkzJo1C+Xl5bh165bag4EqqYmIAzp2BfpPtXVJ7JYIoHQtKq4pC7Ahi5C3Nfq+S1aAyZJEdu/NSSOtGqjqu344Kn3fYaifFzYnjbRSaYis497+QchIjOIIIDK7oUOHIi8vD5cuXUJ9fT1OnjyJ5cuXw8vLPPerGzduoE+fPjhx4oRZ9idn9JzVzp074/vvv0d4eLjZC9OWcM4qAcbNzRK9goD+IXJtlTP2MpHjEMefNY/Dtn7Mcw46OQsObSdHjw26d++O3bt3IyIiwqz7NbpndebMmdi3b59ZC0HUFimz/+ki7xVkD6F2/E7I1sR5nV9cZZX3a8vHvOjNdsaeZWp7xLxVACivrbdtYYhM8Oyzz2L16tW4efOmWfdrdM9qXV0dZs2ahW7dumHgwIHo0KGD2usLFiwwawGdlaO3npB5tPVeESJnIR/9YM61k0k3XkPJmTC3Qtvm6LHBb3/7W+zZswedOnXCwIED0bGjenLVf/3rXybt1+gESxs3bsTXX38NT09P7Nu3Dy4uLtJrLi4uDFaJyKa4vA/ZgphDKY4tVjatg98xOQpD7j0cOUWOrEuXLnjwwQfNvl+jg9VXXnkFr732GpYuXYp27YweRUxE/2NKCyoDLd30ZWNlqzVZijzBkjgGybJ4PSRHYci9h8czObqsrCyL7NfoaLOxsREPPfQQA1WiVjK2BdWZM3+agyHZWNlqTZYijq3hYf48xqyA10OyB4Yef/ruPfK57jyuydFduHABBw8eRG5uLi5cuNDq/Rkdcc6ZMweffvppq9+YiDiEzZzkwYK+7YgswdLHFiuwt7HhiWzN2AYTXccqG7vIGVy7dg3z589HcHAw7rnnHowZMwYhISF47LHHUFdn+v3L6GHATU1NWLNmDb7++msMGjSoRYKlt99+2+TCEJF2rJzpx++GbM1SQ805hL0lfg9kS+a+J4tlr4gc1cKFC7F//3588cUXGD16NADg4MGDWLBgARYtWoR169aZtF+jswGPH699Ho6Liwv27t1rUkHaGkfP+EVkrzjvh2zNUscgj20i58V1VsnRY4OuXbvis88+w7hx49Sez8nJQUJCgslDgo3uWc3JMWxdSCIynCEZbIHbPQmstGrG3ieyB5Y69nhMt8RrITkLrq1Kjq6urg6BgYEtng8ICGjVMGBmSSKyMX3zXsTrYhsmFtGOQ6WJ2g5eC8kWLHW8DQ/zx+akkchIjOI9jBzSqFGjkJqaiuvXr0vP1dfXIy0tDaNGjTJ5vwYFqw888AAuX75s8E4feeQRVFZWmlwoorZEU4AlvxmK18U2DMh04/dC1DbwWkjWZo0GkuSNhcgvrrLY/oksJT09HYcOHUKPHj0wYcIExMbGIjQ0FIcOHcKf//xnk/dr0JxVV1dXnD59Gt26ddO7Q5VKhdDQUBQWFqJPnz4mF8zZOfq4dLIcfUNZOexNt/ziKr0ZgYmIiExh6Xsw72FtlzPEBvX19fj4449x8uRJqFQqDBgwAI888gg8PT1N3qdBc1ZVKhX69u1r8psQkeE09RaImxfnZOqWX1wlrbXKmz0REZmbchSUuRuVg31Mr9QT2cqNGzfQr18/bNu2DY8//rhZ921QsGpKUqXu3bsb/TtE1EwZqCZk5iEjMQpxg7ozUNVBzPlhoEq2xNEPRM5PW+NxaxqV2SBNjqpDhw5oaGiAi4uL2fdt0JzVsWPHGv1wd3c3a0FXrFiBmJgYeHl5oUuXLhq3KSkpwbRp09CxY0d07doVCxYsQGNjo9o2P/zwA8aOHQtPT090794dr732GpQjoffv34/o6Gh4eHigT58+eP/991u815YtWzBgwAC4u7tjwIAB2Lp1q9k+K5Hc8DB/ZCRGIXljoVQJZkIR7dgqTbbEpD9EzktTPgllUNmaudSch02O7Nlnn8Xq1atx8+ZNs+7XYbIBNzY2YtasWXjqqac0vt7U1ISpU6fi2rVrOHjwIDZt2oQtW7Zg0aJF0jaXL1/Gfffdh5CQEHz77bd45513sHbtWrz99tvSNsXFxZgyZQrGjBmD77//Hi+99BIWLFiALVu2SNscPnwYDz30EGbPno2jR49i9uzZSEhIwJEjRyz3BVCbFjeoOzYnjZQCVVaGNeN3Q7bGyiaRc9J0f9F2nvP8p7boyJEj+Ne//oWePXti0qRJeOCBB9QepjIowZI9Wb9+PVJSUnDp0iW153fs2IG4uDiUlpYiJCQEALBp0ybMnTsXlZWV6Ny5M9atW4dly5bh119/lXp+33jjDbzzzjsoKyuDi4sLXnzxRWRnZ6OoqEja95NPPomjR4/i8OHDAICHHnoIly9fxo4dO6Rt7r//fvj6+uKTTz4x6HM4wyRqsh75XMxgH08OE9KBQzDJluSjH3gcEjkXS5/XHAbctjl6bDBv3jydr2dlZZm0X4PmrDqCw4cPIzIyUgpUAWDSpEloaGhAQUEBxo8fj8OHD7cYojxp0iQsW7YMP//8M8LCwnD48GFMnDhRbd+TJk3C3/72N9y4cQMdOnTA4cOH8fzzz7fYJj093aKfkdqm0uo6JGTmIS0+AgmZeWrL2BCR/RAVzc1JI6Vz1ZznKQNgItuy9PkX6ucljaIiciQ3b97EuHHjMGnSJAQFBZl13w4zDFifiooKBAYGqj3n6+sLNzc3VFRUaN1G/Kxvm5s3b+LixYs6txH70KShoQGXL1+WHleuXDHhU1JbFOrnhbT4CKRmF0k3Md7INOMwYLIlMQR4eJi/RQJVHtvq+F2QozD0WBWN0zy2ydG0b98eTz31FBoaGsy+b5sGq8uXL4eLi4vOx3/+8x+D96cpA5VKpVJ7XrmNGAVtjm10ZcBatWoVfHx8pMeAAQP0fRwiAM1DgFOzbw9L501MO84XJFsTx565j0Ee2+oYvJOjMOZYZc8qObIRI0bg+++/N/t+jR4G/Ouvv2Lx4sXYs2cPKisrW2TSbWpqMnhfycnJePjhh3Vu07t3b4P2FRQU1CLBUU1NDW7cuCH1ggYFBbXo/aysrAQAvdu0b98e/v7+OrdR9rbKLVu2DAsXLpR+PnfuHANWkuga3ieWYwGAhMw8AMCBJeMBMImDJvxOyFnx2L6NwTs5CmOOVdGzymObHNHTTz+NRYsWoaysDNHR0ejYsaPa64MGDTJpv0YHq3PnzkVJSQn+8Ic/IDg4uFXr6XTt2hVdu3Y1+fflRo0ahRUrVqC8vBzBwcEAgJ07d8Ld3R3R0dHSNi+99BIaGxvh5uYmbRMSEiIFxaNGjcIXX3yhtu+dO3di2LBh6NChg7TNrl271Oat7ty5EzExMVrL5+7urjZX9vLly63/0OQUDEmoMDzMX2qVzUiMAgAmYSCyU5xbah38jslRGHqsshGGHNlDDz0EAFiwYIH0nIuLizT61JgOTTmjswF7e3vjwIEDiIqKMukNTVVSUoLq6mpkZ2fjzTffxIEDBwAAd9xxBzp16oSmpiZERUUhMDAQb775JqqrqzF37lzMmDED77zzDgCgtrYW/fr1w7333ouXXnoJ//3vfzF37ly8+uqr0hI3xcXFiIyMRFJSEh5//HEcPnwYTz75JD755BM8+OCDAIBDhw7hnnvuwYoVKzB9+nT8+9//xiuvvIKDBw9ixIgRBn0eR8/4ReZlSOW2tLoO5bX1UqsrwMoakb1hNk8iYoMVmcLRY4NffvlF5+u9evUybccqI0VERKi+++47Y3+t1ebMmaMC0OKRk5MjbfPLL7+opk6dqvL09FT5+fmpkpOTVdevX1fbz7Fjx1RjxoxRubu7q4KCglTLly9X3bp1S22bffv2qYYMGaJyc3NT9e7dW7Vu3boW5fnnP/+p6tevn6pDhw6q/v37q7Zs2WLU5yktLVUBUJWWlhr1e9Q2lVRdU/V6cZuqpOqaqqTqmq2LQ0Q68Bwlarvk92siYzA20MzontWdO3firbfeQmZmpsHzSaklR289IesS66yyR5WIiMh28ourMDzMX+c27FklUzhDbPD3v/8d77//PoqLi3H48GH06tUL6enpCAsLw/Tp003ap0HZgH19feHn5wc/Pz88/PDD2LdvH8LDw+Ht7S09Lx5EZF4i4YJ8riozYBIREVmXaDjOL67SuR0DVWqL1q1bh4ULF2LKlCm4dOmSNEe1S5cuSE9PN3m/BiVYas0bEFHriHVWkzcW4sCS8UxrT0REZAMiO7++nlWituidd97Bhx9+iBkzZuCNN96Qnh82bBgWL15s8n4NClbnzJlj8hsQUevI11nde7ICqdlFvFkS2SEx9I9DAImcF++9RJoVFxdjyJAhLZ53d3fHtWvXTN6vQcOA5f72t79pfP7mzZtYtmyZyQUhIs2CfTwBAGnxEUjNLkJafIRBw5CIyHpEFuD84ioO1SciojYnLCwMhYWFLZ7fsWMHBgwYYPJ+jQ5WFy1ahAcffBDV1dXScydPnsTw4cOxefNmkwtCRLrd2z8Im5NGqgWsrBAT2QexPqIYJsieVSIisicrVqxATEwMvLy80KVLF43blJSUYNq0aejYsSO6du2KBQsWoLGx0aD9v/DCC3jmmWfw6aefQqVSIT8/HytWrMBLL72EF154weRyGx2sfv/99/j1118xcOBA7Nq1C++++y6GDh2KyMhIjdE0EZmfGArMCjGR/RBDgNmQRERyvB6QPWhsbMSsWbPw1FNPaXy9qakJU6dOxbVr13Dw4EFs2rQJW7ZswaJFiwza/7x585CamoolS5agrq4OiYmJeP/99/HnP/8ZDz/8sMnlNnrpGgC4desWnn/+eWRkZMDV1RX/93//16pCtEXOkJ6arEfMgROZCAFw3iqRneKcVSISxBSBA0vG87pAOlkrNli/fj1SUlJw6dIlted37NiBuLg4lJaWIiQkBACwadMmzJ07F5WVlejcubPB73Hx4kXcunULAQEBLV7Lzc3FsGHD4O7ubtC+jO5ZBYBt27bhk08+QUxMDLp06YIPP/wQ58+fN2VXRGSCtPgIBqpEdoa9J0SkJKYIMFAle3f48GFERkZKgSoATJo0CQ0NDSgoKDBqX127dtUYqALA5MmTce7cOYP3ZXSwmpSUhISEBCxZsgTffPMNjh07Bnd3dwwcOJBzVoksQLTKllbXSfPhIoJ9bF0sIpJhgiUi0oaBKhnjypUruHz5svRoaGiwyvtWVFQgMDBQ7TlfX1+4ubmhoqLCbO9j7KBeo4PV3NxcHDlyBIsXL4aLiwuCgoLw5Zdf4rXXXsP8+fON3R0R6aGpVZbZgInsU7CPJ3tRiIjIZAMGDICPj4/0WLVqldZtly9fDhcXF52P//znPwa/t4uLS4vnVCqVxuetxaB1VuUKCgo0jjF+5plnEBsba5ZCEZE6UfEtra6TlrIR/yci2+NQPyIiMocTJ06ge/fu0s+65nYmJyfrzRvUu3dvg943KCgIR44cUXuupqYGN27caNHjak1GB6u6vrB+/fq1qjBE1ExTghaRXGne6J4AgKNlNawYE9kRno9ExARr1Fre3t4GJzPq2rUrunbtapb3HTVqFFasWIHy8nIEBwcDAHbu3Al3d3dER0eb5T1MYVCwOnToUOzZswe+vr4YMmSIzq7g7777zmyFI2qLNGUOlGcBzsotAQAEeHvYrIxERESkjpl/yZ6VlJSguroaJSUlaGpqkpYcveOOO9CpUydMnDgRAwYMwOzZs/Hmm2+iuroaixcvxuOPP25UJmB9jB1SbFCwOn36dKlHdfr06TYdt0zk7JTDCcW6jZuTRiLYxxNHy2qQvLGQw4CJiIjsCKcDkD179dVXsWHDBunnIUOGAABycnIwbtw4uLq6Yvv27Xj66acxevRoeHp6IjExEWvXrjVrOYxNsGTwOquFhYWIiooypUykAddZJWPkF1dheJg/SqvrpGCVN0Qi+8WhgEREZAzGBpoZnA146NChiI6Oxrp161BbW2vJMhGRjOhZFUtiJG8sBACU19bbtmBEpJF8uSkiIqK24Ndff8Xs2bMREhKC9u3bw9XVVe1hKoMTLOXm5uKjjz7C0qVLsWjRIjzwwAN47LHHMH78eJPfnIj0E0FpUXkt5o3uiazcEowI64LhYf42LhkRacKhgERE1NbMnTsXJSUl+MMf/oDg4GCzTRs1eBiwUF9fj82bNyMrKwsHDhxA7969MX/+fMyZM4dd1kZgVz8ZKn33SaTvPgMAyEiMknpWMxKjEDeou47fJCIiIkfB6QNtm6PHBt7e3jhw4IDZp40aPAxY8PT0xJw5c7Bv3z6cPn0av/vd75CZmYmwsDBMmTLFrIUjIiAmvJvG56uuNli5JERERGQJnD5Aji40NNTo5EmGMDpYlQsPD8fSpUvx8ssvo3Pnzvj666/NVS4i0uCnyisAgHmje2JOTB8bl4aIiIjMgdMHyNGlp6dj6dKl+Pnnn826X4PnrCrt378fH330EbZs2QJXV1ckJCTgscceM2fZiNoMXUN/5EvUiOHAkyNDrFIuIiIisg4GquRofH191eamXrt2DeHh4fDy8kKHDh3Utq2urjbpPYwKVktLS7F+/XqsX78excXFiImJwTvvvIOEhAR07NjRpAIQtXX6FhEP9fPC5qSRAICEzDwAQOWV61YtIxEZjvPOiJwXz2+i29LT0y3+HgYnWLrvvvuQk5ODbt264fe//z3mz5+Pfv36Wbp8TsvRJ1GTeem6+cmDWbHGKgBsThrJjMBEdkZf4xMROS5Tz28GuGQIxgaaGTxn1dPTE1u2bEFZWRlWr17NQJXIjHTdxMQ8lvLaesQN6o7NSSMZqBLZKc47I3JeppzfTJxEbcXf/vY3jc/fvHkTy5YtM3m/Ri9dQ+bB1hMyRn5xFRIy8xikEhERORj2rJIhHD026NKlCyZMmIAPP/wQfn5+AICTJ08iMTERtbW1OHPmjEn7bVU2YCKyjqLyWunfpdV1bKElIiJyEAxUqS34/vvv8euvv2LgwIHYtWsX3n33XQwdOhSRkZEoLCw0eb8mZwMmIuvIL65CanYRUmLDEezjiTFrcgCAQw2JiIiIyC6EhYXhm2++wfPPP4/7778frq6u+L//+z88/PDDrdove1aJ7JzI/Ju++wz2nqyQni+vrbdVkYiIiIiI1Gzbtg2ffPIJYmJi0KVLF3z44Yc4f/58q/bJYJXIzgV4ewAA5o3uidTsIswb3ROA+vqrRERERES2kpSUhISEBCxZsgTffPMNjh07Bnd3dwwcOBCbN282eb8cBkxk50RQmpVbIv0/JTbclkUiIiJqc0S+CE7BIWopNzcXR44cweDBgwEAQUFB+PLLL/Huu+9i/vz5SEhIMGm/7FklsgO6EiZpGu6bvvsMU+ETERFZiViChvdeIs0KCgqkQFXumWeeQUFBgcn7ZbBKZGP61mATc1aJyL6Jc5gVWSLntTlpJHtWiTRwd3fX+lq/fv1M3i+HARPZmL5FxuMGdQcADO7hCwDYe7IC9/YPkn6XiGxPNDptThqJhMw8ZusmcjL67tVkY43XgKJtQEQc4NbR1qVpM4YOHYo9e/bA19cXQ4YMgYuLi9Ztv/vuO5Peg8EqkR3Qd/MTASsAzInpY+niEJGR5BVZVmiJnBPPaztWtA2oqwJObgcGmTY3kow3ffp0qUd1+vTpOoNVU7moVCqV2fdKepWVlSE0NBSlpaXo0aOHrYtDRERmUFpdZ1CF1tDtiIjIAI3XmgPV/lMdtmfVUWODwsJCREVFWWz/nLNKRERkBvnFVQYlX9E3T52IiIzk1rG5R9VBA1VHNnToUERHR2PdunWora01+/4ZrBLZAVZaiRxbaXUdEjLzDEq+wqHCRETkLHJzczF06FAsXboUwcHBePTRR5GTk2O2/TNYJbIx9rIQOT4RgA4P8zd4eyIiIkc3atQofPjhh6ioqMC6detQVlaG2NhYhIeHY8WKFSgrK2vV/hmsEtmYIb0s+cVVKK2uQ35xFTYcOouHMnOtWEIiMgQDUCIiaqs8PT0xZ84c7Nu3D6dPn8bvfvc7ZGZmIiwsDFOmTDF5v8wGTGQH9AWqCZl5LZ5/KDMXnyaNtmSxiIiIiIiMEh4ejqVLlyI0NBQvvfQSvv76a5P3xWCVyM4ND/PH5qSRCPbxRHltPYrKa/HlD+UMVImIiIjIruzfvx8fffQRtmzZAldXVyQkJOCxxx4zeX8MVokcgJgHF+rnheFh/lxrlYiIiIjsQmlpKdavX4/169ejuLgYMTExeOedd5CQkICOHVuXoZnBKhERERERERntvvvuQ05ODrp164bf//73mD9/Pvr162e2/TNYJSIiIiLSo7S6jonUiBQ8PT2xZcsWxMXFwdXV1ez7ZzZgIiIiM+IyVETOh8vMEWmWnZ2N6dOnWyRQBRisEhERmUVpdZ1Uod127Jyti0NEZmTIMnNE9mzFihWIiYmBl5cXunTponEbFxeXFo/333/fugVVYLBKRETUSiJIBYCMxCgkbyxEfnGVjUtFRObEQJUcWWNjI2bNmoWnnnpK53ZZWVkoLy+XHnPmzLFSCTXjnFVq9sYdwPULltl34N3AU7sts28nxXkxRI5H9LqE+nkhwNtDyuKtCc9xIiIzam09NiwWmLPFfOWxQ2lpaQCA9evX69yuS5cuCAoKskKJDMOeVWpmqUAVAH791nL7dkKcF0PkWOS9qoK+QJXnOBGRGbW2HltsP50qV65cweXLl6VHQ0ODVd8/OTkZXbt2xd133433338ft27dsur7KzFYpWYe3Sy378C7LbdvJ8R5MUSOxdhzluc4EZGZtbYeGxZrnnKYwYABA+Dj4yM9Vq1aZbX3fv311/HPf/4Tu3fvxsMPP4xFixZh5cqVVnt/TTgMmJot/cnWJSAZVmKJHIux5yzPcSIiM3KieuyJEyfQvXt36Wd3d3et2y5fvlwa3qvNt99+i2HDhhn03q+88or076ioKADAa6+9pva8tTFYJSIiIiIisgPe3t7o3LmzQdsmJyfj4Ycf1rlN7969TS7LyJEjcfnyZfz6668IDAw0eT+twWCViIiIiIjIwXTt2hVdu3a12P6///57eHh4aF3qxhoYrNpIY2MjAOC7775DeXm5jUtDRERERES2IuIBESOYW0lJCaqrq1FSUoKmpiYUFhYCAO644w506tQJX3zxBSoqKjBq1Ch4enoiJycHL7/8Mp544gmdQ5EtTkU2kZWVpQLABx988MEHH3zwwQcffPChAqDKysqySOwxZ84cje+Xk5OjUqlUqh07dqiioqJUnTp1Unl5eakiIyNV6enpqhs3blikPIZyUalUKpDVFRcXo0+fPtizZw+Cg4NtXRwiIiIiIrKR8vJyTJgwAWfPnkVYWJjRv79q1Sq89NJLeO6555Ceng4AUKlUSEtLwwcffICamhqMGDEC7777Lu666y4zl95yOAzYRjp06AAA6Nu3L3r06GHj0hARERERka14e3sDuB0jGOPbb7/FBx98gEGDBqk9v2bNGrz99ttYv349+vbtiz/+8Y+47777cOrUKen97B3XWSUiIiIiInJAV69exSOPPIIPP/wQvr6+0vMqlQrp6el4+eWX8cADDyAyMhIbNmxAXV0dNm7caMMSG4fBKhERERERkQN65plnMHXqVMTGxqo9X1xcjIqKCkycOFF6zt3dHWPHjsWhQ4esXUyTcRgwERERERGRHbhy5QouX74s/ezu7q41G++mTZvw3Xff4dtvv23xWkVFBQC0WB81MDAQv/zyixlLbFkMVolMsaYfUFdh61LYhqsH8PxxoFM3W5eEyG6UVtcBAEL9vFBaXYfy2noMD/PXuX2on5e1ikdEZsDzlqxhwIABaj+npqZi+fLlLbYrLS3Fc889h507d8LDw0Pr/lxcXNR+VqlULZ6zZxwGTGSKthqoAkDTdWDfKluXgshulFbXYcyaHIxZk4P84iqMWZODhMw85BdX6dxeBLhEZP943pK1nDhxArW1tdJj2bJlGrcrKChAZWUloqOj0b59e7Rv3x779+/HX/7yF7Rv317qURU9rEJlZWWL3lZ7xp5VIlN4BbXdgNXVAxin+cJJ1BaF+nnhwJLxav/W1bMqtmEPDZHj4HlL1uLt7Y3OnTvr3W7ChAn44Ycf1J6bN28e+vfvjxdffBF9+vRBUFAQdu3ahSFDhgAAGhsbsX//fqxevdoiZbcEBqtEplhyyqK7Vw41yi+uQrCPJ8pr61FUXosvfyjHp0mjLVoGIjKc/HwN9fPSW6FlhZfI8fC8JXvi7e2NyMhItec6duwIf39/6fmUlBSsXLkSd955J+68806sXLkSXl5eSExMtEWRTcJglcjOiKFGogU3v7gKCZl5LbZ7KDOXASsRERERabRkyRLU19fj6aefRk1NDUaMGIGdO3c6zBqrAOCiUqlUti5EW1RWVobQ0FCUlpaiR48eti4O2Rn2rBI5HiZfISIiUzE20IwJlojskLLCG+zjiVA/LwwP88e9/YMYqBLZGSZfISIiMj8Gq0R2TlSC84urpEyj2rKMEpFthPp5YXPSSPasEhERmRGDVSI7V15bDwBIyMxDQmYe0uIjkJCZxx4cIjtSWl3H85LIyZVW17GxmMjKmGCJyM4F+3gCADISowAAyRsLATQHsezFIbIP8uVrDJm7yvmtRI5FjHICgM1JI7UuTUVE5sVglcjOhfp5IS0+QgpS543uiazcEimIJSL7ISqzutZjVGb8JiL7Z8gaykRkfhwGTGTn8ourkJpdhHmjewIAsnJLAABHy2psWSwiUhCVWX1BqNiOgSqRYxGJDi2F0wiIWmLPKpGdGx7mj5TYcKTvPgMAmBkdgnH9AhA3qLuNS0ZESoYGoAxUiUiOIy7IHixcuNDo33nllVfg5+dngdI0Y7BKZIrGa0DRNiAiDnDraNG3Kq2uQ/ruM0iLjwAApGYXYWB3H4u+JxEREamz5Fxzjrgge5Ceno5Ro0bBzc3NoO0PHjyI5ORkBqvCN998gzfffBMFBQUoLy/H1q1bMWPGDOl1lUqFtLQ0fPDBB6ipqcGIESPw7rvv4q677pK2aWhowOLFi/HJJ5+gvr4eEyZMwHvvvae2+G5NTQ0WLFiA7OxsAEB8fDzeeecddOnSRdqmpKQEzzzzDPbu3QtPT08kJiZi7dq1Bv9xycEVbQPqqoCT24FBCRZ9KzHcNzW7SEqylJpdBP9O7uxdJaLW+fQxoOgzW5fCNsb+ARi/2NalIAdhjZ5PBqpkD7Zu3YqAgACDtvX29rZwaRxszuq1a9cwePBgZGRkaHx9zZo1ePvtt5GRkYFvv/0WQUFBuO+++3DlyhVpm5SUFGzduhWbNm3CwYMHcfXqVcTFxaGpqUnaJjExEYWFhfjqq6/w1VdfobCwELNnz5Zeb2pqwtSpU3Ht2jUcPHgQmzZtwpYtW7Bo0SLLfXiyLxFxQMeuQP+pZtmdrnkqcYO6IyU2HEBzJmB5VmCrp9BvvAYc/bT5/0Tk+NpqoAoA+1+3dQnIgbDnk9qCrKws+PgYPnovMzMTgYGBFiwR4KJSqVQWfQcLcXFxUetZValUCAkJQUpKCl588UUAzb2ogYGBWL16NZKSklBbW4tu3brh73//Ox566CEAwPnz5xEaGoovv/wSkyZNQlFREQYMGIC8vDyMGDECAJCXl4dRo0bh5MmT6NevH3bs2IG4uDiUlpYiJCQEALBp0ybMnTsXlZWV6Ny5s97yl5WVITQ0FKWlpWq9utT2GNJau+HQWaRmF2Fz0khUXrkuBa1W71k9+mlzj3LHrhbvUSYiK2DPqq1LQUQEgLGBNg41DFiX4uJiVFRUYOLEidJz7u7uGDt2LA4dOoSkpCQUFBTgxo0batuEhIQgMjIShw4dwqRJk3D48GH4+PhIgSoAjBw5Ej4+Pjh06BD69euHw4cPIzIyUgpUAWDSpEloaGhAQUEBxo8fb50PTU4h1M8Lm5NGag1Utx07h9TsIqTEhts2UAWae5RPbjdbjzIR2dhv/wL0n2iV+fdEROQ4SktL4eLiIgXO+fn52LhxIwYMGIAnnnjCauVwmmC1oqICAFp0RQcGBuKXX36RtnFzc4Ovr2+LbcTvV1RUaBynHRAQoLaN8n18fX3h5uYmbaPU0NCAhoYG6Wf50GRq20qr65CQmae1ZzXA2wMApGzAAFB1taHFdlbh1pE9qkQGsGQiFrOy4vx7IrKSLcnAD3+3dSmsz6MbsPQnW5fCaSQmJuKJJ57A7NmzUVFRgfvuuw933XUXPv74Y1RUVODVV1+1Sjkcas6qIVxcXNR+VqlULZ5TUm6jaXtTtpFbtWoVfHx8pMeAAQN0lonaDmPmwYzt27y+W2p2EbYdO2fpohGRCfKLqzBmTY5jrJlo5vn3RGQH2mKgCgDXL9i6BE7l+PHjGD58OABg8+bN0kjUjRs3Yv369VYrh9P0rAYFBQFo7vUMDg6Wnq+srJR6QYOCgtDY2Iiamhq13tXKykrExMRI2/z6668t9n/hwgW1/Rw5ckTt9ZqaGty4cUPrJONly5aprV107tw55w9Yc9Y6dwILVw/g+eNAp26t3pWuQDXYxxMAkJEYheSNhdLzg3v4avkNIrIVMVJC19B+u8LREkTOZ+DsthmwerS+Pka33bhxA+7u7gCA3bt3Iz4+HgDQv39/lJeXW60cThOshoWFISgoCLt27cKQIUMAAI2Njdi/fz9Wr14NAIiOjkaHDh2wa9cuJCQ035zLy8tx/PhxrFmzBgAwatQo1NbWIj8/X2pNOHLkCGpra6WAdtSoUVixYgXKy8ulwHjnzp1wd3dHdHS0xvK5u7tLf3AAuHz5sgW+BTvjzIEqADRdB/atAuLetujbhPp5IS0+AoN7+OLAkvHY8l0J0nefQXltvWNUhonaEGYMJSKbezCj+UHUCnfddRfef/99TJ06Fbt27cLrrzfX68+fPw9/f3+rlcOhhgFfvXoVhYWFKCwsBNCcVKmwsBAlJSVwcXFBSkoKVq5cia1bt+L48eOYO3cuvLy8kJiYCADw8fHBY489hkWLFmHPnj34/vvv8eijj2LgwIGIjY0FAEREROD+++/H448/jry8POTl5eHxxx9HXFwc+vXrBwCYOHEiBgwYgNmzZ+P777/Hnj17sHjxYjz++OMGZQJuM8b+wdYlsCxXD2DcMou/jUiwNGZNDvaerFCbu0pE9oeBKhERObrVq1cjMzMT48aNw+9+9zsMHjwYAJCdnS116FmDQ/Ws/uc//1HLtCuG1c6ZMwfr16/HkiVLUF9fj6effho1NTUYMWIEdu7cqbZg7Z/+9Ce0b98eCQkJqK+vx4QJE7B+/Xq4urpK2/zjH//AggULpKzB8fHxamu7urq6Yvv27Xj66acxevRoeHp6IjExEWvXrrX0V+BYxi/msgBmIB/um5pdZMOSEBERkbEcJuEaEZo7Bzt16oRx48bh4sWLuHz5str0ySeeeAJeXtY7nh12nVVHx7WUyFBijVWged5qwS/VyMotweakkRgeZr1hGEROKT8L+DLF1qWwvX4zgN9tsHUpiJyOIWupEwH2Ext4eHhg/PjxiI+Px/Tp09WW6rQFhxoGTNQW3ds/SPp38sZCZOWWICMxioEqkTkwUG126nNbl4DIIejL8q18nfPYydGcOnUKU6ZMwZYtWxAWFoa7774br7/+Oo4dO2aT8jBYJbJz5bX1AICZ0bZt2SJySlPSzb7LW2bfoxX0m2HrEhDZPdFLqi1g1fc6kSPo1asXnn32WezevRuVlZVYuHAhfvzxR9xzzz0ICwvDc889h71796Kpqckq5eEwYBuxl65+sn/i5gcAafER0pBgDgMmsj8c8kfkvEQQquvcVs5P5TWBDGXvscHNmzexd+9efPHFF8jOzsaVK1fwzjvv4JFHHrHo+7JnlcjObfmuRPq3fyd3HVsSkS2JSiorpUTOR95wrIvy3Df2mmCWXtnGa8DRT5v/T2Qm7du3x8SJE/HOO+/gl19+wZ49e9C3b1/Lv6/F34GIWiUltj9q628gK7dE9lw4e1WJ7Ah7T4icW2saoowJVM1yHSnaBtRVASe3A4MSTN8PtXnXr1/HsWPHUFlZiVu3bk9ycXFxwbRp06xSBgarRA4gddpATI4MwfAwf1RdbUBqdhEeHNrT+pXiNyOAa+et+552oR3w1CEgMMLWBSE7Fernhc1JIxHq54X84io2JhE5IYdpiIqIaw5U+0+1dUnIgX311Vf4/e9/j4sXL7Z4zcXFxWpzVjkMmMiGxHAf5bAf5c/5xVVIyMxDfnGVNGdVJF6yqjYZqALALeCzubYuBNmx0uo6JGTmYduxc9K5SkRkE24dm3tU3TrauiTkwJKTkzFr1iyUl5fj1q1bag9rBaoAg1UimxHDffKLq9SyByqzCYpK8OakkQj28QTQvN5qQmae9TMOdmyrGYnbATPX27oQZMfEEMG4Qd2Z/IyITMI572RPRCbgwMBAm5bDoGzAQ4cONW6nLi7Izs5G9+7dTS6Ys7P3jF9kHSIhi6bsgcqfAfXe1GAfT97QiNoQ5XWBiBwDz10yhL3FBvPnz8fo0aPx2GOP2bQcBs1ZLSwsxKJFi9CpUye926pUKrzxxhtoaGhodeGInJ24eWnKHqikzEIo5scRkfNjAici+yAPPLUFocptDD13DVkah8haMjIyMGvWLBw4cAADBw5Ehw4d1F5fsGCBVcphUM9qu3btUFFRgYCAAIN26u3tjaNHj6JPnz6tLqCzsrfWE7J/pdV1OFpWg+SNhQDASitRG8PeGSI9vvkLsPcPFtv9LfGfdrIn2qnPqbul4Xn5r+jdN1ru02Th9wOzPzXHnsgK7C02+Otf/4onn3wSnp6e8Pf3h4uLi/Sai4sLzp49a5VyGNSzWlxcjG7duhm80xMnTiAkpK3ObSOyjPLaegR4ewBo7lUlIvtlicCSgSqRHhYMVJXaAbilIajU9Lwhgaf4PUO3N8iZr8y1J2qDXnnlFbz22mtYunQp2rWzXZojg965V69eatG0PqGhoXB1dTW5UESkTmQDFomWKq9cV0vCRET2obS6rkXSNCKykntft+ju2/3vP+3kP2vbzlS3bnewtlr4/ebaE7VBjY2NeOihh2waqAImrLP61VdfoVOnTvjNb34DAHj33Xfx4YcfYsCAAXj33Xfh6+tr9kIStXXBPp7ISIzC4B6+KK+tR/LGQmQkRrGnhciOiLlpAOeUE9nEPQuaHxZkyWp7O3C4P9mPOXPm4NNPP8VLL71k03IYHay+8MILWL16NQDghx9+wKJFi7Bw4ULs3bsXCxcuRFZWltkLSeTsdN2c5BXgA0vGS88P7sGGISJ7IpadEP8mIhIMDUJ57SB70dTUhDVr1uDrr7/GoEGDWiRYevvtt61SDqMbiIqLizFgwAAAwJYtWxAXF4eVK1fivffew44dO8xeQCJnp1xXVSnUzwubk0biwJLxKK+tR0JmnpVLSESGCvXzUltiiohI331ebMOpA2SMVatW4e6774a3tzcCAgIwY8YMnDp1Sm0blUqF5cuXIyQkBJ6enhg3bhx+/PFHg/b/ww8/YMiQIWjXrh2OHz+O77//XnoUFhZa4BNpZnTPqpubG+rqmk+m3bt34/e//z0AwM/PD5cvXzZv6YjaAH2LgJdW10lzVUWgyiGGRPantLpOalDanDQSw8P8bV0kIrIDhtzn5SOoeH8nQ+zfvx/PPPMM7r77bty8eRMvv/wyJk6ciBMnTqBjx44AgDVr1uDtt9/G+vXr0bdvX/zxj3/Efffdh1OnTsHb21vn/nNycnS+bi1G96z+5je/wcKFC/H6668jPz8fU6dOBQCcPn3aLtIsEzkSY9ZUC/bxxIEl43FgyXhWgonsjKhsivnlljhHNfW6sCeGyDHous+LEVQAODKDDPbVV19h7ty5uOuuuzB48GBkZWWhpKQEBQUFAJp7VdPT0/Hyyy/jgQceQGRkJDZs2IC6ujps3LjRxqU3nNHBakZGBtq3b4/PPvsM69atQ/fu3QEAO3bswP33M+sYkaEMGRYEqM+DEz8TkX0J9fNCRmIUACB5Y6HZg0hN1wtDryFEZP+CfTwBAAmZeTynySS1tbUAmke7As1TNysqKjBx4kRpG3d3d4wdOxaHDh3SuI8HHnjAqJGyjzzyCCorK1tRav1cVCqVypANd+7cifHjx7eYXEumsbeFf8k2DO1Z5RAhIgtpvAYUbQMi4gC3jibvRiwvJXpHLNWzqjz3mTmUSMZM53NrmXpepu8+ifTdZ5AWH4E5MX0sUDKyZyI2OHHihNQZCDQHmO7u7jp/V6VSYfr06aipqcGBAwcAAIcOHcLo0aNx7tw5hISESNs+8cQT+OWXX/D111+32I+rqytOnz6Nbt266S2vSqVCaGgoCgsL0aeP5Y5Xg3tWn3zySXTr1g0PPfQQPvnkEyl6J6LWGbMmB9uOnTNoWy5XQ2RmRduAuirg5PZW7WZ4mD82J41EsI+nxXpGNJ37vB4QyZjpfG4NU0c85BdXIX33GaTEhiM1u4i9q23YgAED4OPjIz1WrVql93eSk5Nx7NgxfPLJJy1ec3FxUftZpVK1eE7+Wt++feHr66v34efnh2vXrpn2IY1gcIKls2fP4tixY8jOzsaf/vQnzJs3D6NHj8b06dMRHx+P3r17W7CYRM5JDB1M3liIAG8PqTdGW6ts8sZCDO7hywoqkblExDVXbPtPbfWuxPnL0Q92zk5632zirYHAlRJbl8Lyug0GBiXY5K21JVPSt0SdSKAYE94NDw7tyWtIG6apZ1WXZ599FtnZ2fjmm2/URmsGBQUBACoqKhAcHCw9X1lZicDAQI37MiWpkryslmBUNuBBgwZh0KBBeOWVV3D+/HlkZ2cjOzsbL774Ivr27SsFrsOGDbNUeYmcTtyg7i0C1TFrctRudiL5gr5lazgkkCzikznAqc9tXQrL6hoJJOeaZVeGnoM8X21E3vtmo4DGZtpCoAoAF45a5W20ncOaAlXlfV25vbjHV165ziSKbZy3tzc6d+6sdzuVSoVnn30WW7duxb59+xAWFqb2elhYGIKCgrBr1y4MGTIEANDY2Ij9+/dj9erVGvc5duzY1n8AMzM6wZIQEhKCJ598El9++SUuXryIP/zhD/j5559x//33Y+XKleYsI5HTk9+YtLXKDg/zV0u0pMRkK2Qxzh6oAsDF463ehaZ1ErWdj9oSJpEVRMQBHbuapTfd4Xj3tHUJrCNgqEV2Kz/Hjbnn6lu6Bmi+x6fEhiN5YyHyi6vMVmZyXs888ww+/vhjbNy4Ed7e3qioqEBFRQXq65szSru4uCAlJQUrV67E1q1bcfz4ccydOxdeXl5ITEy0cekNZ3CCJUPdunULVVVVBk3MbcuYYInk9PWwiNflrbOA5tZb9tSQ2bFnVS95EjSxxqq+3hT5+apvW13vy3OeyPI0JTo05/m37dg5JG8sVNs/tS3Gxgba5p1mZWVh7ty5AJp7X9PS0pCZmYmamhqMGDEC7777LiIjI81ZdIsyKVjNz8/Hvn37UFlZiVu3bt3emYsL3nrrLbMW0FkxWCXgdk+Kvgqt/PXS6jqU19YjITOPNzQiOyHOUzEHXR6wWmpYsKkBLhGZRtx/zT1MVx4IA83JFOMGWXYeINkfxgaaGTVnFQBWrlyJV155Bf369UNgYKBaVK8twieilsTNaXPSSIMrmyK4FUtktKaCyh4ZIvNRDvMzpTGJ5yOR/bNGQ3GAt4fF9k1kCJVKhZKSEgQEBMDT09OmZTF6zuqf//xnfPTRRygqKsK+ffuQk5MjPfbu3WuJMhI5NX1Jk0QlGIDaEKTWtOxyfisZpfEacPTT5v+TVmLkg+hZ1TRM39zvx15VMgrP5VYRiZDkw/fNuV/BUstfERlKpVLhzjvvRFlZma2LYnzPart27TB69GhLlIWoTZEHofoqm+J1c1VMWck1wtq7gKu2v1jbhSPDgSd22boUdk3XshUcsks215YzIZtBfnGV1LMK6J7CY6q0+AhEBPuYbX9EpmjXrh3uvPNOVFVV4c4777RtWYz9heeffx7vvvuuJcpC1OaE+nkZNfzXnDdEVpgNxED1tvP5ti6BQ9C2NIW8UmuOXhMRADNzKBmsLWdCbiWxFqroWVX2sppj3wDwc9U1JGTmcfQT2dyaNWvwwgsv4Pjx1mfLbw2jg9XFixfj1KlTCA8Px7Rp0/DAAw+oPcix6Vt2gRdO8zKkkqmskBryN+DfyYw6McmBJGKmrUvg0JSZf1t7nob6eSEjMYpDBslwbh2be1TdOtq6JA5HNDjJ10S3xLmXldu8Fm5afAQblcmmHn30UeTn52Pw4MHw9PSEn5+f2sNajB4G/OyzzyInJwfjx4+Hv78/kyo5ETG8RWSxFD+nxIYjJba/2vAXeTY8Juoxjfg+MxKjMLiHr9bvUL5YuMg0qmvYkSHDDfk3M8LiH21dAnIw4vzKL67SOLfcXMPwxfxYMtJ744HK72xdChtyBZ7KBQIjbF0QhyTOb/lUHlP3IRwtq2mxDYcCk62lp6fbuggATFi6xtvbG5s2bcLUqRxC0hr2lp5aBDj+Xu1RVXcT80b3RFZuCUaEdcGR4kuYGR2CzwrOIyMxClVXG5CaXSQFWWPW5CAtPgJzYvowCDLShkNnkZpdBED/fFRlY4K+fYq/iZwhS+UQkem0LWFj6ffiMhdGWM4gAN36A88csXUpHIpynVXB2PupskFZ3Ns1scR6rmS/7C02sBdGDwP28/NDeHi4JcpCNjTx7eYLcFXdTQC3h6EcKb4EAPis4DwAIHljoRRcJW8sRHltPQAgNbsI6btPYsyaHGw7dk4Kijg0TbvS6jqkZhdhc9JItSyAmrYDgOFh/i2yAGv6fmvqGgEAP5yrbbGfMWtyUF5bz0CVyMICvD0sGqjKJW8s5LxVYwQMtXUJbMwVmLne1oVwOKInVZ5cyRz30+Fh/kiLb9nLnRIbLgWqnL9KttLU1IQtW7bgj3/8I1asWIGtW7eiqanJqmUwehjw8uXLkZqaiqysLHh5sbLrLHy93FB/udHo35vzt9utgem7zwCANCzts/mD8PH697D4uUXoEdjVLOV0NpuTRiLYx1OttVZ+05O3wCrJh2XLf8fXyw1AcwNDwrCeUmVZPr/twJLxbKklsgD5sP3NSSMtdp6VVtepDR20xtqPTuPpHFuXgByU/PwS57mxQ4FFI395bb3W83Xe6J5I330GMeHdEOzjabZETm2J/NrL+o5pfvrpJ0yZMgXnzp1Dv379oFKpcPr0aYSGhmL79u1W67w0ehjwkCFDcObMGahUKvTu3RsdOnRQe/2779ryPBDD2VtXv3w4qjnMjA7B2r6n8UvpL+jVszdT5CvIhxOJgFU+D1i5bXltvTRMSN6qq22or9i3/HX585qGKMpbbY0ZzsQbALVl8nMgv7gKwT7Ni6drOmc1nSumnEPycxlortjOH3270sBzksi8xHkqv0+W19Yj2MfT4Iz+8u0W//N7rJ01BAB0DgNOiQ2XOgLYGKVf76Xb0dPXHUsmR0j5PQDdQ7UtsdqCqewtNpgyZQpUKhX+8Y9/SAmVqqqq8Oijj6Jdu3bYvn27VcphdM/qjBkzLFAMsjVzT+T/rOA8the0x8R2NXjh7vmw/SlnX+S9L4YkThI3sozEKOl18TsRwT5qQa5otQVuDwmWP58W33wRl/eyyivWgGE3Ra4bSW2d/BzQdA6Jc1S8pmvkhK55aem7TyIltr/0sxglIUaxZOWWYHJkiFpwbO1zkg1Xlsfv2DbkyRCVCc3k92RtlOd5+u6T+KzgPHr4eiIltj+CfTzVglK59N1npHVX7fVvry2RnLX1XtocOJXUNEh/pzFrctAezR0oe09W4N7+QQAgXW+VjYr2+h3byv79+5GXl6eW+dff3x9vvPEGRo8ebbVyGB2spqamWqIcZGOiN8Cc6uGBf9/6Db76yxGcWsGEXIB6C578OxfBo7YLpbwyLDIHxw3qjp8qr+i8SdwR4C29r7ggix50MacOgDRkEYDBLcW6Mpq2tlKl7fftqQWUnJe242/bsXNqiYw0rbMoEs8BkEYvaLq+ivcQ552o0IrRDuL19N0npUpsSmx/afhv8sZCpMVHSMnUxJx2XUMLLcVWDVdtKXjT9x23pe/CmsS9UzTyArdHQ+09WSE9py+jvzyZ0r6TlQCAfScrERPerUWvqkhwmRIbjtr6G9I9W9/KAbZgaOJHa4gI6oiiimstnr+J5g6UzwrOaxxBGNXDG4VlV6xQQsfj7u6OK1dafjdXr16Fm5ub1cphdIIlcm5j+7a82MifUyYBSInVP179qfFMyAXcrmyIRAny+WbzRvdE8sZCjevayof7ySvG246dQ/ruM9h27Jza7wwP88fkyAAAQNXVBgDAlu9KpPcR/xe9umK/wO0e3PziKpRW10nlkSdv0TdcWFMyCOXn0pUMJr+4Svr9DYfOqq0vK74/5WcmzcyRkKOtJfXQlsxk27FzSN5YqHbsyddZFIGn6EkVIxkqr1xXG+0gfw9R0RPneEpsOBIy89TOgVMVzRWFspp66Xl5705KbDhSs4uw4dBZAJB+3xrkjUfa5tTJryPmfm9bJp0R37e1yJdJ0XQ91fVdtLVzWDD1c5dW10nnkDi2RTJE8Tc4WlajlmxS37EY6ueFbcfOISEzTwqMCsuuSPdced2qt3/zGrjfl1ySkl0a+j6tJc5X5f1b23sOD/PX2iBnbR/8frhJvyf+Hk/8X745i+MU4uLi8MQTT+DIkSNQqVRQqVTIy8vDk08+ifj4eKuVw6Bg1c/PDxcvXjR4pz179sQvv/xicqHIdvafbr5Az4wOkYax7T9dJQU/P1ddUwtQRTIfISMxChmJUdL2APDg0J5WKLn9E1kDNyeNRHltPZI3FkrBY1ZuicZsgKKCInpV5QuQF/xSDQDYfqw5U7N4ftuxc9hxvLnlNjW7CIv/+b3UMyNufPIb4N6TFWqB65/3nJIq0CIwFBVgQyuI8tZ/ecW8tLpO2t+2Y+ekCkF+cZX0uhhuteW7EqRmF0nvHernhZnRIQB0Zz/VVDZ7qaxZK0u2qGyJv5Wp72vrgMBWNPVexQ3qLi0RIw/S5AGESIQi7ylJ3lgorVet3Gewj6d0nT1aViOdp0XlzZm8/7znlHQuf1ZwXtrv5MgAzBvd839Z2Jt/JzW7CK98fgxAc8Cavvuk1s9nrkYM+fElzmnl8SauI/JGJ/m1ylTmWqvWFCLHw1Mff2vV993yXYlag6f8u9fVWKCv8dAZKQN4QwN58X2J+46Yhy4CsqNlNUjIzEPyxkK1eo5yf5oCvuSNhUiJDUdAp9u5XjYnjZRGSAji36I+JqTEhhuUaMmUv68orzi+xqzJwYZDZ1ucw5oa8YrKa+3iPiEfqSK+q6ge3gb/fmfPDvo3amP+8pe/IDw8HKNGjYKHhwc8PDwwevRo3HHHHfjzn/9stXIYNAz40qVL2LFjB3x8DJvXWFVVZfW0xtQ68kqXGGKWMKynNJxtx/FKzIwOUQtyAEjrrYphrAHeHmotheZM2mRJ+oZQKV+XJ1tQ/p6mDHSiB0X5nci/z9TsIqRmF7UI9IDm3hkl0fq643il1OuTkRiltk1UD298VnAeY/v6q934Qjq74fz/sj/v/d+QJEEsUzQzOgQJw3pK82mGh/ljw6GzUrANtOxZlQ9VE+RZiOVE75D8OxHlV84L2nH8PN7N+a/0GcK7qrfiijkzmobKmWOIojmG2MmHeYpj4d7+QXqH9OkaEq1M+CFf5kAQ57N8XrTYVh9DAwJ7HIKoqUya5lbJt5Nn2BZDfsUoiABvDwzu4au2jTgP5Me26H3Ze7JC7X3Sd5/BHQHeiBvUXeP1VjQCzhvdEz9XNQ9lE+eiIIariQBWSX6Op+8+g9r6G4ju5YefKq8gJrwbKq9cl67R80b3RHQvPwzu4St9PnnviLZh0GIYYqifF9LiI6TfBdTPW2+3drjSeEv6WXn9k1+T5EOrDTmWxDaWyrJs6H53HK/EhkNnWyS5s8T7L/7n99LxIBo2xXVNeb1T/r64ZsuvD7p+xx7PZyXl9U9ZfvnUFuUQe+X9Qtx3RH1HqLxyvcW9CGj+/n+uuqZ2/06Lj5AaleUNVpuTRqLyynX8VNnce6ecl/rWzpPSEoFAc0OUtvM7ffcZaQ6rWNceuJ3oSdA1D15eJxHfgfweIcyMDkFqdhHyzjafo108XNU+k6gPiPNZU2OcPrrmupp6DIrv4cGhPRHq54XPk++Rvqct35VonBcsLJrYX+trbZFKpUJtbS0++eQTnD9/HkVFRVCpVBgwYADuuOMOq5bFoGzA7doZP1r4p59+Qp8+5ruA26v33nsPb775JsrLy3HXXXchPT0dY8aM0ft79pbxS05eGZMTFzjlcA95MLY5aSR2HD8vzbdI331GrTeitWnELXET1RfMKAMweeUyffcZtTlm4mYlEiLIb5hZuWelm5B4ffN/StQqpJuTRuLQmQtIie0vBaDieWUSAPlcNjHHxZJGhHVRu6nKyyIqseKmKTIbi5vEmDU5agkktDVkaJtzoo28gUT+dxDMkbZe2/GhvOnr+n1RaThaVoPBPXzVgknlfpXnn/zYUyaFUCb8OLBkPP6851SLIEcQWWPF3+PBoT2lgEsZqMgrM/L3Vn4HyuRBygqUOf4GxtK0rJP8GiWOUeD2ki97T1aoVbxEpVBbg9vM6BCt37OmRCzid0QGUGWjgjXOYWMoG5zk16MDS8arld0YY/v6o/jCVZTUNE9RkM/DE++hK+GUtiW7dJEfy9p+R36t0nSuy7O1ywNH+d/UFPJGEXmwI86d0uo6fJR7psWxkRYfAf9O7mqBvnL+oDLLrHI+tLify68xmpKBWTqBjq6/i/y95ddSEWTKj0lxfZVf08asyVE7t8S5nRIbjpjwbjh05oJaAKOpDqONttdFuXQFnroYci3Qtk1GYhSqrjbg3v5BaseTMjiXN2ACuoNkTTRdG5WrD+g6P+VJq+THsPhdbUv2AfobWrV1IiiPBUE0zNt6zi1gX7HBrVu34OHhgR9//BF33nmnTcti9NI1dNunn36K2bNn47333sPo0aORmZmJv/71rzhx4gR69tQ99NWeDkg5eQuk/CZmSKVAfmNUXhDkvTqiUqiplVNX6645esi0UbbOKlttlcGW+HzyRAiaAkddFVpNRLAmfm/e6J6YHBki/S3EzUBZCRHbWzNRgDzJhPympazoa6u4m4sIopU3ZAAtAihDew+UAZe23lr5TV8erIv3Ei3P8u/ABYD8ojsirAs+TWrOqifvgZdXNnQFT/5e7VFVd1Pnd9Sxgwuu3Wh+15TYcBw+U9Wi5rNWlQAAtz5JREFU4UFOnrhHvJ+mNQWVQbcyI654Xmxr7nNX099Vfm4oe5HFUFRlBb6ovFbtexWfW1mBE+eZvoqdriBXNLAoK8m2Inp003efUbt2yT+DuO6kffGDxQJqce0SlVdNQam8wpk6baDG/ciDG/nfW3weTceg8r6n7XjJSIzCT5VXWvzd9PVsKonjVlw75d+7/N+e7YF63ae2dPyKxlH58/LG0sor19WGsGvqTRPXKHmSMGXAY+hnNJTyvq78+8k/g6ZAXFwrNfWaWereI85/bfsP6NQBlVdvqD3XxcMVl65bbsShvsBa3oAurkHyNd7NZWxff/xxxiDp/qgMROXmfJSH/aerNDYOHS2r0XiuAcafb2I75XKBgObGGVuyt9jgrrvuwt/+9jeMHDnSpuVgsNoKI0aMwNChQ7Fu3TrpuYiICMyYMQOrVq3S+bv2dkDKaWrJNJS8BTq/uEqqkIkhX8rgTRnQyHthlb2Zyt5Zc5K/n3Ioj7zSJm+VFRdRbQGppgqtvOdQU0+l0B7NGewEec+qtqGyQnhXT5y5WK/xNXPSdKMWN2lR4ZoZHYJ/FZzHLc27MKvwrp7Ys/hetcqY/FgC1INX+d9b3qKqbAiQ9/yIIX9iG3P1hskbh2xJedwBUBshEeDtIQV2omcHQIuKz+TIAFRfa8SR4kuYGR2C5yb0k3o7isprpeUDRE8IgBZ/B0N7wQC0uG4oew409SxUXW1AanaRxkqe/JxXnqfK810EWeIap290gPyYsXUWSm3Hr6bn2wEGnceGbqdNBxdg7wvj1YZtCvJhh8o1pvOLq6TRK57tgZtNwA1Vc0NN400VbqhuJ5IDbmc9F72LIniTz000NNARwbMon2iUFdcK+agF5X6NOQY0BTwdXJo/pyhHRe117DheiRFhXTBlYDD8O7lrnHIhtpf/nTWdC5MjA1DX2IQ/zhiktfEO0N5wpG/UiZz83gtAGmp6b/8gqbFWfL/A7fNflFt+bop/y8918XnEfXne6J7w8exgcqORIQ2F1qac8mNq7665KHvzxf8fysyVrqva1oM3lHydaX3TuQR7HfZub7HB9u3b8cYbb2DdunWIjIy0WTkYrJqosbERXl5e+Oc//4nf/va30vPPPfccCgsLsX//frXtGxoa0NDQIP187tw5DBgwwG4OSMGcvZfyYWNKnu2Bh0fcvlEq53iIG6L8eWXlxJQLjHwopnxIZbCPJ/685xR6+HraRW+HXE9fd/zj8Ri1C7ixPbb2zlyVdhEoiBv05qSRSP33DyiquKbx+BGt8SGd3XDl+k1cv3FLqvhZW1p8BN74skhvT4ozUwaVyqGoyiHQ2lreyXosURnu2MEFXz0/DsDtRgx5oAo0Byhi7VllA5O1dfFwxW+ju7cYUWPuod1dPFzh38nNKo2R+ni2B3YubG7sk8/tFIGmaKiWN/bJ79ny+oG8cangl2q7GA7v7go0WDD1inJON3A70NTXS2ptHTu4YPKgYJPqHPIeXfG5lOfF5MgArHv0brXru6n01V0tOULPHOwtWPX19UVdXR1u3rwJNzc3eHqqTwOsrq62SjkYrJro/Pnz6N69O3JzcxETEyM9v3LlSmzYsAGnTp1S23758uVIS0trsR97OSDlzNXKJIZ4GMPdtXmpG18vN/h3cpfm94mLnHIIorbhIMreYZEExJYVmtaQt5amxIbjVIX2JCuGsHWLsLIFPGFYT7W/jfxmZmiPlXK/gPrnlFduAbSo/DoLMeRX2cLu6OxtTqctWHoooTE0DRVXJlC6t39Ai3PMkIa2yZEBGNnHX/pdbb+jaf6+tWj6W2gamWAubu0AEdvIE+SR44kI6ogdKeMQtnS72pQQW/aCiqRd8pFu8qBZ06gyQ4jtRYO0ts8o3rO1iTkDOnVA/isTdW5jTz2pSvYWrG7YsEHn63PmzLFKObjOaiu5uLio/axSqVo8BwDLli1DbW2t9Dhx4oS1img0TfN5TLFh/kiN67bq0tDUPHcqNbtIWlMMaH6uPYBnN/5HSqMOQBpaKE9TL1rZ5UutiOUjHEEXD1eNz4tlW2LCu+Hni9d0bjsirIvO97BloJqRGIWB3W9nFhdLcsiXAYju5Qeg+Qa6/3QVRoR1UQtUxZI/St4e6gnO6xpvf075mrSl1XVWCVQ7dmh5LRC0fQZjiGNC/D8jMUqam2pIoCrOT/lSCvbKUQNVY5ZO0GVsX39cut6EiKCOZtmfKeTLa4nzR1RuDywZjzkxfaSeNW3HX8KwntJUBk3LdSn3D7TMigw0nz+it85agar86vLHB1rOmTXHVVXb37fx1u1lTkSgastjgVoaEdZFZ51HXPOLKq5hw6GzUPYUiSBOvvyfoX9j7Xcaw9zbPwhzYvrgwJLxUnZv+Xml7xwTn83fS/0evO9/qw2IkVOaAtWoHs1Z0sV6tq1xQTFXWBN7DVTtzY0bN7Bv3z6MGTMGc+bM0fiwFgarJuratStcXV1RUaG+PEFlZSUCAwNbbO/u7o7OnTtLD29v81RgLE0Ee6YGrM+Mb84gtjlppNp8IR11eK1uAi2GiiZk5iFm5S4pEP0o9wze2nkSY/v6Iyv3LCasNX4OoLJoM6NDpMqVfI1ZESBoI9/WGMFdPFo8t/90FT4rOI+0+AgMD/PHpMjmOX+XrjdprQzrqggKPX3dtb6maQ05JW0B1+TIALWbtvy7ks8fEjISo9RuYoN7+GJz0kjMiemDjMQoHCm+hLT4CGlZkNRpAw0K9pRDapVLE5jbvNE9Mbavv/R5r8nGFKfEhkvr7B5YMh6TI5u3CenspnFfmiiPuYRhzd/BcxP64cCS8dLnU55vGYlR0vEo/7uKgEKZDER+7Mj/vTlppHQuiO9f7Ff8fcT7ifcUn1fTOWQunu2bK3Xyip3yfXQdL/LvSk7+fSsrod5uht0+RdIg5bJSxpo1LBQzo0NajC7Qdx0SRPk1nddp8RFqfyPgdoOXfP8RwT7SUiniO9ucNFJajgdonmco9iWCV/E7GYlRGB7mr1Yx3Zw0ssVnqGvU33uclVsiZco1hmjgk//9xHfSnNDu9vcT3tVTreEv/X9/x81JI82auEd+DRDXdvm5Jn4eHubfnOjqf+fkw8O1H9Oaru0pseFq1wJxTsjPXfF/8R6iDJY8f5W6eLgiLT5COmZHhHVRO0Y0HcPi7yI/NgHt57ac+Btra/wVlEumyUUEdcSR4ks6GwlFI6w4NzRdE9LiI1B1tUG6H8rPd/EdpMSGt7i/axoiKT7XvNE9pb+baFiS3yMyEqOk8zfUz0uaYy0/BsTvPDj09jEnvvPNSSOROm1g8/zguptIi4+Q/kbuHXR/p0DzNVKMhlNeC5TX2bT4iBZL7Mh9oyWDMBmvQ4cO2Lp1q62LAcDAdVblxo0bh/nz52PWrFktxi63JW5uboiOjsauXbvU5qzu2rUL06dPt2HJzMvQdRY1EWudAS3XK7uhup3yf9uxc9IQXVOSc8iHQxnT+yISxIihxvIMcUfLagBAWm9WPO/r1VypEMPS5ENnlGLCu+HBoT2ljI/6Eh+J4TKahrqKIZ2p2UW4t38QYsK7SS2dmuZ6Him+hNmjeuvNhiiWj9BE3Cw1DcET5Zkc2XLtXfnvyrMZi+9rTkwftcyV8u8duH2DFBn64gZ1l+Y8yc0fHY6s3BK1+a7fnLqg9fNMjgyQ9iF65E0hz+YqhqsLyqFTwO3KnRiCLK8UyLNc9vR1l/4e8qQ+4rsWc3/kf4tgH0+N6/KK5DHyhGEHloyHr5eblPRFngFXZBQVyVju7R8k/Y3kx7Y4j0VCI/G3FWvaAS2zAsu/C2V2YVFWMVJCHGvKpE5iX2L4o3welKYsxGLfmpZKEuseGhJsDOx++/vef7pK7VhTzjfTRbmGqSAfzqlp3rZ86HOAt4fGNZM/KziPmdEh6OHriVMV6r0X8t/ff7pKuh5oGlItroHCkeJLaseyWCtZHG/67g3JGwsxuIev2nQM8Vyon5cU1Ip/j+sXIM1XvH5Df7Aq1nUU603ro0yqJZYHE8eX/FopzgexlqVI7iNfJkVMSRHLyrQmsdT5y43SsS++b5G9VzRAyc9x5fBrOfF8SU2D2rGi6V4gjgHROw40J0CTPycvA9C8fqVY8ko5WkmZ/C8lNhx3BHirva/83vlz1TUpwZE8sZXIIDsnpo+0TNDsUb3xWcF5KWhP331S2rdyCRv5uRbs46lzWCsA6VqrbYi9uHfL79/K4axFFddafH7l9Uue7E1Ofo+VJ8QS56n4O4ptRDIpQP3+IP5m4jifPao3jhQXqp3rogziXBb/lt9j5ed2RLCPVF7xuqbfAaB2r763fxB2HK9E+SXD7rViLXllx8hv+naV8k8AkMoiPy/ENKLNSSPZa2pmv/3tb/H5559j4cKFNi2H0XNWFy1ahH/84x+or69HQkICHnvsMZunNLYVsXTN+++/j1GjRuGDDz7Ahx9+iB9//BG9evXS+bv2Ni7dUpSJL5Q3WHlqc9GyJrInype4Sf5HQYveH2PNG90T0b381NL3a1rDUp45Vl7R17aMiKaswYI8QZQmkyMDMHVQSItlfZTkNyCRsMKQjHn63l+TeaN74uyFa2oVYnmlR35j1fXZxevaMktrWi5IZNDUtL0myqyw+uY1ihuwvvmqmrJkxoR3U1vWQry/fO60SBqirKTI31sT5RIb9/YPUlsvVf43ly87oCmjoaFLPsmX65AHofIKiHx5CJGFU561V1eyCvGZlOu3iu9efmzIl6iQL4+jDMKVGWKVf395w4fI9Cq+V+XalfLsovLKrra5U8bMpcpIjML2Y+elyqyhx52SfO1I8XmUc7uNyWaqq/FKnthO+ffW9DfRR9tah4YkPzF0frK25ZIA9UBBeZ9Rfh7l8aXMeCvKLdaT1nQeyZMEiWu1tvm8ygYtUT4xTUG+1qy270lZXkA9m64y27GmBGXyAE4ca/KMyLr+fsrrR4C3R4s8EeJzyMum/C7kf0ttSwop12pXZoxVJmKTf0fa1mXVxdh5mSIbrTJ5lKb1bjWt/ayc/62rnPLXlFlw5ceFprVUtSW7Mmb5F2N+Z8Ohs8g7WyVdB+XzruXG9vXHhvkjtc491xTg6yqbI7O32GDFihVYu3YtJkyYgOjoaHTsqN44uGDBAquUw6QES01NTdi2bRuysrLw5Zdf4o477sD8+fMxe/ZsjUNgndl7772HNWvWoLy8HJGRkfjTn/6Ee+65R+/v2dsBaUnKdOGiwibS/StvvMq1HMVrogJj7ER8bWvy6arEi7KKn5U3F23p2EVlA4DaTWHvyQrsPVmpFgDKEwbJL8aasiiLzyAWkJff/DTdWOXr5JlrOZTJkQGYN7pPix4seUVI11Ik+rQmS5/ypq+NCASV34m8V0tZcVAmZtL03tqWXNGWKl8b+d9eVMSV6z5qqvTo+u70vSavYGlaE0/+nvLz09iKjnKfymNDW7CtrbzK5wH1iqm+Morn5Os8y/chDw51NRDJG29Eo4Y8o7EyuJYvtyN66EUPkbxnU1uAqK2CKz9eNfVKyyv8yqBE/h6a/g7WqggaG6ymxUegpq5R7fqn7IHR9rcHNDdWavvM+hp9ALQIDOQNo+L9UmLD8eDQnlJAIb9PKMtjyPdlbIOAfBvl/czQ31fuR9d3o/xZGVDrW+dS3zkPGP5dAeoNW5VXrqPqagP8O7mrTU8xpG4hRmaJjOTK8isbRTQtxQRA7Z4uAlv5yA/5+Sy/pysbVeTfg/IcFt+7MfdjTd+fMfdnXatBaKIpE7S8IcUZAlFD2FtsEBYWpvU1FxcXnD171irlaHU24AsXLiAzMxMrVqxAU1MTpkyZggULFuDee+81Vxmdkr0dkNYmb3lUBqfyVkFNPRLKyoWm3k/g9s1EVyu1qcvfaNuXvoBBOUxIBIDygERe+RHDQbX1XImKprwSLYZIyisfmnofxHbyXmz5ciCislt55bp0E9G3WHxrtaZSXFpdh1c+PyY1CGjKHqxpPVP58FtN63Ia0hNkzpupsrFESV4J0lUxVO6zNeXTFMjZM3OWUVvjg6Z1OOXHjdhGuT60/HyUj86QT0HQNPpD099a3pMvgmltvdL6ghpDGgusQVzX5n6UhzMX63VOn1D2QCmXp9JH13esbXtDGkvEv5U09eoasn9LMtd7mhLkmrsMhr63oAwg5b3QYn1XcZ4r12sFWt4vNL2XvgYzeeCp6ZoirzOIY1S52oH4LJYO6oz5O2laTkrTVAdxn9Y0SkRbD78za+uxgTatClbz8/ORlZWFTz75BD4+Ppg7dy7Ky8vxj3/8A0899RTWrl1rzrI6FR6Q2itHmnovlUPTdLV4Kyvz1r4RGhIwaBoOqGsZBvkwNk37HbMmR5pDI68AK3v8lDdDeauvctiQcu1b0dqraRiTPbR8avp8SlKSEtmySpqGUhnzWSxxfBkSJNv6+3ZU5vjulJVM+VqTyqH32q5bItAUAZayh06c77oCJDH3WjmE2tggVP55bHk+y78DfcR5K9ZKFkwpu73cI8i6dDX8KYeByxtnBUMaNHXRdLzLhwIDtxu2Na1BbauA3xDi+iafQiTqKCPCumD2qN5S1mHxvW7+T4naknZrZw2xWfltxV5jg8bGRhQXFyM8PBzt2xud7qjVjM4GXFlZibfeeguRkZEYM2YMLly4gE2bNuHnn39GWloaPvjgA/z73//G+++/b4nykhMRF1blBVYk3pBP6hfLImiqiIjXxfPyxB2a9m9Jut5LPtxSDIMGbmfiFK/HhHeTnhd0ZbEN9fOSsunOG91TLeGPcrvBPXzV9lteWy9VeAO8PdQCVdHTIxKrDO7h2+L7V37XtqK86c8b3VNjltSEzDyk7z6pNhw7K7cE5bX1Jh8vlghU9WXgtvX37agM+W4NIa45w8P8EerXnD1T3sMismRmJEZJDUfKiqVoGErNLpIqmiJjrrxhStcoDvmQcGWyLfl28qW99H0eezif5Rln5dcreUbn6F5+GLMmR0oqBahnNTWGvdwjyLq0He/KOgUAtQZ08RDbGkLTuSfeR54tW9Rz4gZ1l7JmA1Abrq+tzPZE1FnEihAAMG9086iHI8WXWiSdO3TmglrywOcm9LNSSUmXuro6PPbYY/Dy8sJdd92FkpLmYdoLFizAG2+8YbVyGB0e9+jRA+Hh4Zg/fz7mzp2Lbt26tdhm+PDhuPvuu81SQGqbtF2ItV2Q7f3CLcgrqXGDusPHs0OLYWsiG+PPVdcMTpAkWiizckukOR/K7KPKgC4jMUoaYiOCU/Fe8t8V+wY0f6/28F2LG7jg49lB45w3TYkrUmLDzTaM2Ry0VUao9cz53cr3Ic8uLZ+rpW25Gnk5lFk4DSmb+H0xD00+rUJeNvn76Pvctmjc01QG+QgPUaEVo1Dk53TV1YYW57Oll6Yi52NonQLQfE815HzRNV1EPkpJni1b7FtTQO0I9wb5NUc+AgVoboCSz7edN7qn1dZKJuMsW7YMR48exb59+3D//fdLz8fGxiI1NRVLly61SjmMDlb37NmDMWPG6Nymc+fOyMkxT1IXImciv4DnF1chffcZKSGLcG//IKRmFyErt0Ral00f0ZujK5OjMqADbs9zEe+vnEtlaEXXHojyzYwOabF0jHKYoJjbOravv9q6cfbC3r9rR2aJ73Z4mL9ag49I5BXq56WWJVVTOUwtjwhsRSU3LT5CY/ItewhCjSECTnmlXZBPRxDz7YksTdM90Jh8BfruoaXVdWpLryiTsznKuaskrk9iqLW4TsrrG0fLapCVW9JiiTz5aCeync8//xyffvopRo4cCRcXF+n5AQMG4MwZ6zUwGD0MWF+gSkS6yYcrZyRGtajIit4FAC2G3uoavhg3qLta4KntveUPTS22mlpwHeGmkV9chW3HzrVYE1YeqIpeYjEMeEjPLmYZFkokKpWbk0aqzUc3ttfe2GNRVADF8EFHaFgyhuiNEddK+Tw3eY+2WHeVyBIMGSpszO9r2pd8aLEYVeXI9yZ5/hF5vUeQfyfeHrf7zuaN7mlXo53asgsXLiAgIKDF89euXVMLXi3NoGB16NChqKmpAQAMGTIEQ4cO1fogIsOIIcHKm5F4Xlzg5YGqIXMZtx07Z3AA5iyVO3FTDPD2wMzoEKTFR0hDIuVz3sTC48KDQ3s6XeWebEs5bM+Yyqapc2rllVxHP5ZFACr+L4JxkSFZ9B6P7ds8b1Cc32KuP5G1mPNcU+7LXuaPm0p+ruoin8IkGDqijCzv7rvvxvbt26WfRYD64YcfYtSoUVYrh0HDgKdPnw53d3fp39aMpomcla5ECcY8LyeGBOpLNGIvy1SYi+ilLiqvxWcF5+Ht0V7qaQIg9XT9VHmlxbw2Z/j8ZF+UDUyGVjpNGXKvb6kjRyOG9sqH+Grqcdp/ugppX/xg0HqsRI7IWc5pXZQNyGRfVq1ahfvvvx8nTpzAzZs38ec//xk//vgjDh8+jP3791utHAYFq6mpqSgsLERUVBSWL19u4SIRtR3G3oz0bS+fO6eNvSxTYU6iN/rAkvH4ueoasnJLMDkyRJq7K+at1tbfwNGy5lEiHDZIlmZK8GlsoCqSpjnDeQzcDki1Eb2pyqW/iMh+iPP40JkLRg3pnTe6p9Zl+sj6YmJikJubi7Vr1yI8PBw7d+7E0KFDcfjwYQwcONBq5TB4zurQoUMRHR2NdevWoba21pJlImrTWru8hsiyp2uZCpHkwFkquHLyIUTie/D1cgPQPNSo4JdqAM1zWR15PhA5BkueXyIYVi6N48jE8EFt17DS6jqN2YGZbIksjfcLw4nzOH33GWw7dk7rdtuPqeeYyMotQX5xlZatSZv33nsPYWFh8PDwQHR0NA4cOGC2fQ8cOBAbNmzA8ePHceLECXz88cctAtU33ngDly5dMtt7KhkcrObm5mLo0KFYunQpgoOD8eijjzLjL5EFtDb7rqGZB51lCLDc3pMV0jBoEYwDt4cBp8VHoLd/R1sWkcjsHD0Ri5x8eQtN1yd5Ajr5/53tWkb2xVxrNLcVoX5eGtc6V3ppyl1qP6fFRzC5kpE+/fRTpKSk4OWXX8b333+PMWPGYPLkydKaqNawcuVKVFdXW2z/Bgero0aNwocffoiKigqsW7cOZWVliI2NRXh4OFasWIGysjKLFZKorVGmyG/N72t6zdl6VEUFNjW7SFqfUTwvPm9GYhTu7R8E/07u0u/Js4kSOSJnO5/lw3y19ayKtVV/qrwCABoT1RGZk7OdZ5Ymz8wvX6tdSXkPlt+fyTBvv/02HnvsMfy///f/EBERgfT0dISGhmLdunVWK4NKpbLo/o1eusbT0xNz5szBvn37cPr0afzud79DZmYmwsLCMGXKFEuUkajNslRrrrPdcEUFVgSqCZl5yC+ukr638tp6JG8sxJg1OVJFNyU2nC245BSc6XwWw3y19ZaKoEHMQ0+JDWcQQVbBY8xwcYO6Y3Jk85InuoboK18T03TIMI2NjSgoKMDEiRPVnp84cSIOHTpko1KZn9HBqlx4eDiWLl2Kl19+GZ07d8bXX39trnIREdiaa6zkjYUI9vGUkkyNWZMjLWsDNAeoKbHhACDNYyUi+6Ort/RoWQ3Sd5/BvNE9kb77DEdIENmZDYfOYsfxSgDAR7lntG6nTKg2OVL/0OG24MqVK7h8+bL0aGho0LjdxYsX0dTUhMDAQLXnAwMDUVFRYY2iWoXJwer+/fsxZ84cBAUFYcmSJXjggQeQm5trzrIREdiaawhxwxOBvcgCLBZaFzdDkREY4HAjInukL1u3WJ5rZnQIl60hslPi/trT1x2p03Rnjd1x/LzO19uiAQMGwMfHR3qsWrVK5/bKJUVVKpVTLTNqVLBaWlqK119/HeHh4Rg/fjzOnDmDd955B+fPn8eHH36IkSO1p5snIrIUkTTqaFkN8ourpKHTmiq7kyNDkBYfwfT4RHZIrIOsLVv38DB/pMSGS/PhAGYCJrI3cYO6Y2xff5TUNCB990md24oM/mP7+nNqzv+cOHECtbW10mPZsmUat+vatStcXV1b9KJWVla26G11ZAatswoA9913H3JyctCtWzf8/ve/x/z589GvXz9Llo2IyCAiwZKYjypfykMEspuTRqLyynVpSHBEsA9vjER2RvSs6iIfwq8tazAR2U5pdR32n25egiYmvJtBv7P/dBU2HDqLOTF9LFk0h+Dt7Y3OnTvr3c7NzQ3R0dHYtWsXfvvb30rP79q1C9OnT7dkEdWMGTMGnp6WazQ0OFj19PTEli1bEBcXB1dXV4sViIjIFKKndHAPX7XKqxgODEBt7mpCZh7nAxPZmaqrzXOztA0DBoA5MX3ww7lafFZwHqnZRbi3fxDPYyI7EurnJSVBq7xyXee2YjQFANzbP8jSRXM6CxcuxOzZszFs2DCMGjUKH3zwAUpKSvDkk0+2et/jxo3D/PnzMWvWLJ3B6Jdfftnq99LF4GHA2dnZmD59OgNVIrJL8iUtlMQSNpuTRiItPgLpu89wbUYiOyQqq3cEeGvdprS6Dp8VnEdafIS1ikVERiitrkP6bu2JleT0zVMn3R566CGkp6fjtddeQ1RUFL755ht8+eWX6NWrV6v3HR0djSVLliAoKAiPP/448vLyzFBi47UqGzARkb3QlzlZDAcWy2JwziqR/UreWIj84iqd20QE+1ipNERkDHmWX3nPqSb65qmTfk8//TR+/vlnNDQ0oKCgAPfcc49Z9vvWW2/h3Llz+L//+z9cuHAB99xzDwYMGIC1a9fi119/Nct7GILBKhE5DV1LWIibJwNVIvuXFh+hdU65OM/1DS8kItsR56e+eeh7TzrPEivOyNXVFdOnT8fnn3+Oc+fOITExEX/4wx8QGhqKGTNmYO/evRYvA4NVInIKYj1Vbb0x4vXkjYXYduyclUtHRIYI9fNCWnwEUrOLtPayKLP/cp1VIscln6fKc9l+5efn49VXX8XatWsREBCAZcuWISAgANOmTcPixYst+t4GJ1giIrJnYj1VTctYiCHAADBvdE8kbyxskYiJiGwvv7hKGqqv7/wc3MMXKbHhzOpNZIfiBnVH1dUGvSOZ5AEql6GyL5WVlfj73/+OrKws/Pe//8W0adOwadMmTJo0SVrHNSEhATNmzMDatWstVg72rBKRUxFrrGqTlVtixdIQkTFEZTXA20PvtntPViB99xmOlCCyQ6XVdTpHSAjinJcvOUf2oUePHvjrX/+KOXPmoKysDJ999hnuv/9+KVAFgOHDh+Puu++2aDnYs0pETkH0nhrSI8O1GYnsk5hbrmtpKbFNUXktAMMCWyKyLn1JD43djqxvz549GDNmjM5tOnfujJycHIuWgz2rROQURAU2eWNhi5ZcseabkJpdpDfTKBHZRrCPp85eFnlm78mRARwGTGSnDA1AGajaJ32BqrWwZ5WInEawj6fWFtoHh/ZE+u4zmBkdgs8KznNuDJEdKq2uw5g1za30hvS27DheiQ2HzmJOTB9rFI+IyKkNHToUe/bsga+vL4YMGaI25Ffpu+++s0qZGKwSkVMQldwDS8ZrfF0kcfis4LxBQ4WJyPrEeWroOTozOoSBKhGRmUyfPh3u7u7Sv3UFq9bCYJWI2oThYf6YN7onsnJLmA2YyE6JrN6GrqE6sLuPhUtERNR2pKamorCwEFFRUVi+fLmtiwOAc1aJqA2ZP7p53iqzDhLZr6LyWp3rIYv56Smx4Zx/TkRkZkOHDkV0dDTWrVuH2tpaWxeHwSoROQdDMgr+ec8pAFzLjcheieUuUmLDta7PKBIspe8+g4zEKCZYIiIyo9zcXAwdOhRLly5FcHAwHn30UYtn/NWFwSoRtQlpX/yAzwrOA1BfhJyI7EeonxcyEqOQvvuM1vUZ5efvvlOV1ioaEVGbMGrUKHz44YeoqKjAunXrUFZWhtjYWISHh2PFihUoKyuzankYrBKRUxAJlrRVcKN7+Un/TsjM07tQORFZX2l1HZI3Fuocqi/mnwPNCdO0DRcmIiLTeXp6Ys6cOdi3bx9Onz6N3/3ud8jMzERYWBimTJlitXIwWCUipyDWUtVWwR3cwxcApEouEdkfMZxf19De0uo6ZOWWSOdygLeHtYpHRPaq8Rpw9NPm/5PZhYeHY+nSpXj55ZfRuXNnfP3111Z7bwarROQUNhw6i/TdZ7Dh0FmNr4uhg1m5JUiLj2CCJSI7pitpkkiwJBKmcQ46EaFoG1BXBZzcbuuSOJ39+/djzpw5CAoKwpIlS/DAAw8gNzfXau/PYJWInMKcmD6YN7qn1jUX5RXa1OwiDgMmskNiOH9CZp7WgFUkWDpaVmPl0hGR3YqIAzp2BfpPtXVJnEJpaSlef/11hIeHY/z48Thz5gzeeecdnD9/Hh9++CFGjhxptbJwnVUicgr5xVXIyi3B5MgQnUMIMxKjuMYqkZ1LiQ3Xeh6LJEzJGwuRkRjFc5mIALeOwKAEW5fCKdx3333IyclBt27d8Pvf/x7z589Hv379bFYe9qwSkVMQSVd0VXDT4iOQvLGQ2YCJ7JToLU3ffUZnz2ryxkLpfOYoCSIi8/H09MSWLVtQVlaG1atX2zRQBRisEpGT2HDoLLJyS7TOWc0vrkJqdhEAZgMmslciEZqu9VNFz2pqdhHnnxMRmVl2djamT58OV1dXWxcFAINVInISP1c1ZwD84VytxteHh/kjJbY5IQsruET2yZB5qKJndd7onkjNLtKZjImIiBwbg1UiciqfFZzX2muaEtsfGYlRWpMwEZFtiZ5V8X9NRM+qyOyta446ERE5NocJVlesWIGYmBh4eXmhS5cuGrcpKSnBtGnT0LFjR3Tt2hULFixAY2Oj2jY//PADxo4dC09PT3Tv3h2vvfYaVCqV2jb79+9HdHQ0PDw80KdPH7z//vst3mvLli0YMGAA3N3dMWDAAGzdutVsn5WIjNfbvyMA6FxrFdBdCSYi2xLrrOob+SDWVvXv5G6NYhERkY04TLDa2NiIWbNm4amnntL4elNTE6ZOnYpr167h4MGD2LRpE7Zs2YJFixZJ21y+fBn33XcfQkJC8O233+Kdd97B2rVr8fbbb0vbFBcXY8qUKRgzZgy+//57vPTSS1iwYAG2bNkibXP48GE89NBDmD17No4ePYrZs2cjISEBR44csdwXQEQ61dQ16t1mw6GzGLMmh/NVieyYMUP0mWCJiMi5OUywmpaWhueffx4DBw7U+PrOnTtx4sQJfPzxxxgyZAhiY2Px1ltv4cMPP8Tly5cBAP/4xz9w/fp1rF+/HpGRkXjggQfw0ksv4e2335Z6V99//3307NkT6enpiIiIwP/7f/8P8+fPx9q1a6X3Sk9Px3333Ydly5ahf//+WLZsGSZMmID09HSLfw9EpFlMeDe1/yttO3ZOSrD0Ue4Zq5WLiIzD4JOIiASHCVb1OXz4MCIjIxESEiI9N2nSJDQ0NKCgoEDaZuzYsXB3d1fb5vz58/j555+lbSZOnKi270mTJuE///kPbty4oXObQ4cOaS1fQ0MDLl++LD2uXLnSqs9LROqCfTzV/q8khv9GBHVE6jTNjV5EZFul1XVGjX7gOqtERM7NaYLViooKBAYGqj3n6+sLNzc3VFRUaN1G/Kxvm5s3b+LixYs6txH70GTVqlXw8fGRHgMGDDDhUxKRqUL9vDBvdE8UVVxD+u6Tti4OEWlg6JzVyivXrVQiIiKypfa2fPPly5cjLS1N5zbffvsthg0bZtD+XFxcWjynUqnUnlduI4b/mmMbTe8vLFu2DAsXLpR+PnfunH0FrG/cAVy/YJl9B94NPLXbMvsm+h9DKrmTI0OQlVuidagwEdmeIT2lIsGS+D8RtXGtrceGxQJztujfjqzOpsFqcnIyHn74YZ3b9O7d26B9BQUFtUhwVFNTgxs3bki9oEFBQS16PysrKwFA7zbt27eHv7+/zm2Uva1y7u7uasOPxTxau2GpQBUAfv3WcvsmktFXyR0e5o/NSSO51AWRg9M37J+I2pjW1mOL2alir2w6DLhr167o37+/zoeHh2GtpqNGjcLx48dRXl4uPbdz5064u7sjOjpa2uabb75RW85m586dCAkJkYLiUaNGYdeuXWr73rlzJ4YNG4YOHTro3CYmJsbo78BueFiwpynwbsvtm8hIDFSJHJ+hw4WJqI1obT02LNY85SCzs2nPqjFKSkpQXV2NkpISNDU1obCwEABwxx13oFOnTpg4cSIGDBiA2bNn480330R1dTUWL16Mxx9/HJ07dwYAJCYmIi0tDXPnzsVLL72E//73v1i5ciVeffVVaQjvk08+iYyMDCxcuBCPP/44Dh8+jL/97W/45JNPpLI899xzuOeee7B69WpMnz4d//73v7F7924cPHjQ6t+L2Sz9ydYlICIiMhgDVSKSsB7rtFxUYkKmnZs7dy42bNjQ4vmcnByMGzcOQHNA+/TTT2Pv3r3w9PREYmIi1q5dqzb89ocffsAzzzyD/Px8+Pr64sknn1QLVgFg//79eP755/Hjjz8iJCQEL774Ip588km19/3ss8/wyiuv4OzZswgPD8eKFSvwwAMPGPx5ysrKEBoaitLSUvTo0cPIb4OIiIiIiJwFYwPNHCZYdTY8IImIiIiICGBsoI3DDAN2NmLe7Hfffac2z5aIiIiIiNoWEQ/Ic+sQAJWDWLlypWrYsGGqTp06qbp166aaPn266uTJk2rb3Lp1S5WamqoKDg5WeXh4qMaOHas6fvy42jbXr19XJScnq/z9/VVeXl6qadOmqUpLS9W2qa6uVj366KOqzp07qzp37qx69NFHVTU1NWrb/PLLL6q4uDiVl5eXyt/fX/Xss8+qGhoaDP48WVlZKgB88MEHH3zwwQcffPDBBx8qAKqsrCyjYiRn5zDDgO+//348/PDDuPvuu3Hz5k28/PLL+OGHH3DixAl07NgRALB69WqsWLEC69evR9++ffHHP/4R33zzDU6dOgVvb28AwFNPPYUvvvgC69evh7+/PxYtWoTq6moUFBTA1dUVADB58mSUlZXhgw8+AAA88cQT6N27N7744gsAQFNTE6KiotCtWze89dZbqKqqwpw5c/DAAw/gnXfeMejzFBcXo0+fPtizZw+Cg4PN/XUREREREZGDKC8vx4QJE3D27FmEhYXZujh2w2GCVaULFy4gICAA+/fvxz333AOVSoWQkBCkpKTgxRdfBAA0NDQgMDAQq1evRlJSEmpra9GtWzf8/e9/x0MPPQQAOH/+PEJDQ/Hll19i0qRJKCoqwoABA5CXl4cRI0YAAPLy8jBq1CicPHkS/fr1w44dOxAXF4fS0lKEhIQAADZt2oS5c+eisrJSyj6sC8elExERERERwNhAG5uus9oatbW1AAA/Pz8AzT2VFRUVmDhxorSNu7s7xo4di0OHDgEACgoKcOPGDbVtQkJCEBkZKW1z+PBh+Pj4SIEqAIwcORI+Pj5q20RGRkqBKgBMmjQJDQ0NKCgo0FjehoYGXL58WXpcuXLFHF8DERERERGRU3LIYFWlUmHhwoX4zW9+g8jISABARUUFACAwMFBt28DAQOm1iooKuLm5wdfXV+c2AQEBLd4zICBAbRvl+/j6+sLNzU3aRmnVqlXw8fGRHgMGDDD2YxMREREREbUZDpkNODk5GceOHcPBgwdbvCZfLxVoDmyVzykpt9G0vSnbyC1btgwLFy6Ufj537hwDVke2ph9Qp7lhwum5egDPHwc6dbN1SYiIiKymtLoOoX5eti4GUZvicD2rzz77LLKzs5GTk6M2njsoKAgAWvRsVlZWSr2gQUFBaGxsRE1Njc5tfv311xbve+HCBbVtlO9TU1ODGzdutOhxFdzd3dG5c2fpIRI+kYNqq4EqADRdB/atsnUpiOxaaXWdrYtARGZUWl2HMWtyTDq3eT0gMp3DBKsqlQrJycn417/+hb1797bIkhUWFoagoCDs2rVLeq6xsRH79+9HTEwMACA6OhodOnRQ26a8vBzHjx+Xthk1ahRqa2uRn58vbXPkyBHU1taqbXP8+HG19VF37twJd3d3REdHm//Dk/3xCrJ1CWzH1QMYt8zWpSCyW62p1BKRfQr188KBJeON7lnl9YCodRwmG/DTTz+NjRs34t///jf69esnPe/j4wNPT08AzUvXrFq1CllZWbjzzjuxcuVK7Nu3r8XSNdu2bcP69evh5+eHxYsXo6qqqsXSNefPn0dmZiaA5qVrevXq1WLpmsDAQLz55puorq7G3LlzMWPGDIOXrmHGLyIi58XhgkQk8HpAhmBsoJnDzFldt24dAGDcuHFqz2dlZWHu3LkAgCVLlqC+vh5PP/00ampqMGLECOzcuVNtyO2f/vQntG/fHgkJCaivr8eECROwfv16KVAFgH/84x9YsGCBlDU4Pj4eGRkZ0uuurq7Yvn07nn76aYwePRqenp5ITEzE2rVrLfTpiYjIkbBiSkQCrwdEpnOYnlVnw9YTIiIiIiICGBto4zBzVomIiBwF56cRERG1HoNVIiIiM2JCFSIiIvNgsEpERGRGpmYNJSIiInUMVomIiMyMgSoREVHrMVglIiIiIiIiu8NglYiIiIiIiOwOg1UiIiIiIiKyOwxWiYiIiIiIyO60t3UBiIiIiIgcQWl1HROoUZv2wAMPGP0777//PgICAkx6P/asEhERERHpwTWUiYDPP/8cbm5u8PHxMeixfft2XL161eT3Y88qEREREZEeXEOZqNlf/vIXg3tKP/vss1a9F3tWiYiIiIgMwECV2rqcnBz4+fkZvP2OHTvQvXt3k9+PPatERERERESk19ixY43a/je/+U2r3o89q0RERERERGSU7777Dj/88IP087///W/MmDEDL730EhobG83yHgxWiYiIiIiIyChJSUk4ffo0AODs2bN4+OGH4eXlhX/+859YsmSJWd6DwSoRkY0woyQRERE5qtOnTyMqKgoA8M9//hP33HMPNm7ciPXr12PLli1meQ8Gq0RENsAlEJwb/65EzonnNtFtKpUKt27dAgDs3r0bU6ZMAQCEhobi4sWLZnkPBqtEDoY3SufAJRCcFxsiiJwTz20idcOGDcMf//hH/P3vf8f+/fsxdepUAEBxcTECAwPN8h4MVokcCG+UzoWBqnMK9fPC5qSR/PsSORk2MhKpS09Px3fffYfk5GS8/PLLuOOOOwA0r60aExNjlvfg0jVEDiTUzwtp8RG8URLZsdLqOiRk5rFSS+SEeE4TNc9V7du3LwYNGqSWDVh488034erqapb3Ys8qkQMQPanbjp1DanYRth07Z+MSEZE27H0hIiJnNmTIEERERODFF1/E4cOHW7zu4eGBDh06mOW9GKwS2Tn50N/BPXwBQPo/EdknBqpEzqm0uo5TcajNq6qqwpo1a1BVVYXf/va3CAwMxGOPPYbs7Gxcv37drO/FYJXIgbDHhoiIyDZE4zFzR5A9WLVqFe6++254e3sjICAAM2bMwKlTp9S2UalUWL58OUJCQuDp6Ylx48bhxx9/VNumoaEBzz77LLp27YqOHTsiPj4eZWVlOt/bw8MD06ZNw1//+leUl5dj69at6NatG5YuXQp/f39Mnz4dH330ESorK1v9ORmsEtk5ZYDKQJWIiMg2DiwZz0Zjsgv79+/HM888g7y8POzatQs3b97ExIkTce3aNWmbNWvW4O2330ZGRga+/fZbBAUF4b777sOVK1ekbVJSUrB161Zs2rQJBw8exNWrVxEXF4empiaDyuHi4oKYmBi88cYbOHHiBAoLC3HPPfdg/fr1CA0Nxbvvvtuqz+miUqlUrdoDmaSsrAyhoaEoLS1Fjx49bF0ccjKl1XW8kRLZEM9BIucielUZqJKltDY2uHDhAgICArB//37cc889UKlUCAkJQUpKCl588UUAzb2ogYGBWL16NZKSklBbW4tu3brh73//Ox566CEAwPnz5xEaGoovv/wSkyZNatVnqqqqQnV1Ne68806T98FswEROhjdUItviOUjkfDgNh+xdbW0tAMDPzw9A81qnFRUVmDhxorSNu7s7xo4di0OHDiEpKQkFBQW4ceOG2jYhISGIjIzEoUOHDApWz507h9zcXFRWVuLWrVvS8y4uLnj22Wfh7+/fqs/FYJXIyfCGSmRbPAeJnBPPabKGK1eu4PLly9LP7u7ucHd31/k7KpUKCxcuxG9+8xtERkYCACoqKgAAgYGBatsGBgbil19+kbZxc3ODr69vi23E7+uSlZWFJ598Em5ubvD394eLi4v0mghWW4tzVomckMVuqI3XgKOfNv+fiIioDWEmYLKGAQMGwMfHR3qsWrVK7+8kJyfj2LFj+OSTT1q8Jg8ggebAVvmckiHbAMCrr76KV199FbW1tfj5559RXFwsPc6ePav39w1hkZ5V0f1sKBcXF3z33Xfo1auXJYpDZH6N14CibUBEHODW0dalsZ6ibUBdFXByOzAowdalIbJLHAZM5HzEeQ2A5zZZ1IkTJ9C9e3fpZ329qs8++yyys7PxzTffqM11DQoKAtDcexocHCw9X1lZKfW2BgUFobGxETU1NWq9q5WVlYiJidFb1rq6Ojz88MNo185y/Z8WCVYvXbqE9PR0+Pj46N1WpVLh6aefNjjjFJFdsEHQZhcJWyLimj9z/6m2LQeRHeMwYCLnI85r8W8iS/H29kbnzp31bqdSqfDss89i69at2LdvH8LCwtReDwsLQ1BQEHbt2oUhQ4YAABobG7F//36sXr0aABAdHY0OHTpg165dSEhors+Wl5fj+PHjWLNmjd4yPPbYY/jnP/+JpUuXGvsxDWaRbMDt2rVDRUUFAgICDNre29sbR48eRZ8+fcxdFLvFbMAOrvHa7aDNCj2r7Kkhcix20bhEREQOw9jY4Omnn8bGjRvx73//G/369ZOe9/HxgaenJwBg9erVWLVqFbKysnDnnXdi5cqV2LdvH06dOgVvb28AwFNPPYVt27Zh/fr18PPzw+LFi1FVVYWCggK4urrqLENTUxPi4uJQX1+PgQMHokOHDmqvv/3228Z+DS1YpGdVngnKEPK1fogcgltHqw6DZU8NkeNg4xIREVnaunXrAADjxo1Tez4rKwtz584FACxZsgT19fV4+umnUVNTgxEjRmDnzp1SoAoAf/rTn9C+fXskJCSgvr4eEyZMwPr16/UGqgCwcuVKfP3111KwrEywZA5cZ9VG2LNKROS82LNK5Jx4bpOlOGJs4Ovriz/96U9ScGwJFs8GvGHDBmzfvl36ecmSJejSpQtiYmKktMlERETOhJVZIucjRk0wIzBRM3d3d4wePdqi72HxYHXlypXSuOnDhw8jIyMDa9asQdeuXfH8889b+u2JnBJvlESOi8tfEDmmUD8vZCRGsTGK6H+ee+45vPPOOxZ9D4vMWZUrLS3FHXfcAQD4/PPPMXPmTDzxxBMYPXp0izHWRKQf58MROS4uf0HkuLYdO4fkjYUI8PbA8DB/WxeHyOby8/Oxd+9ebNu2DXfddVeLBEv/+te/Wv0eFg9WO3XqhKqqKvTs2RM7d+6UelM9PDxQX19v6bcncjpMtkTkuJTLX3D+G5FjKK2uQ/LGQmQkRjFQJfqfLl264IEHHrDoe1g8WL3vvvvw//7f/8OQIUNw+vRpTJ3avD7jjz/+iN69e1v67YmcEiu3zoGBStsk/uYcJUHkONhQTNRSVlaWxd/D4nNW3333XYwaNQoXLlzAli1b4O/f3BpVUFCA3/3ud5Z+eyIiu8REHW2X+Juz8kvkWHiuElmfxZau+eCDDxAfH4+goCBL7N7hOWJ6arKd0uo6HC2rQdyg7moVXXJs7Flte9ibSkREmjhKbDB06FDs2bMHvr6+Bm3/m9/8Bp9++im6d+9u0vtZbBjwJ598ggULFmDw4MGYPn06ZsyYgQEDBljq7YicljwhS9XVBqRmFwHQnZyFQZBj4N+o7WFvKpFj4/2V2rrCwkIcPXoUfn5+Bm/f0NBg8vtZLFjNyclBTU0Ntm/fjuzsbKxevRpdu3bF9OnTER8fj3vuuQft2ll8FDKRQ9F0ExSVW9Gz6t/JHYN7+GpNzsKeGyL7xvOSyDHx/krUbMKECTB0cK6Li0ur3suiCZZ8fX3x6KOP4tFHH0VjYyP27t2L7OxszJ49G3V1dZg6dSri4+MxefJkdOzY0ZJFIbJ7um6CoX5eCPXzktLmZyRGAYDG7dlzQ0RERESWUFxcbPTvtGZYs9W6Nt3c3HD//ffjvffeQ2lpKb7++mv07t0br7/+Ot5++22D9vHNN99g2rRpCAkJgYuLCz7//HO111UqFZYvX46QkBB4enpi3Lhx+PHHH9W2aWhowLPPPouuXbuiY8eOiI+PR1lZmdo2NTU1mD17Nnx8fODj44PZs2fj0qVLatuUlJRg2rRp6NixI7p27YoFCxagsbHR6O+FSNAXZIq0+WnxEUjeWAhA+1BgBqpEtsOkWUTOiY3BRECvXr2Mfri6upr8fjYbhzts2DC89tprOHr0KJYuXWrQ71y7dg2DBw9GRkaGxtfXrFmDt99+GxkZGfj2228RFBSE++67D1euXJG2SUlJwdatW7Fp0yYcPHgQV69eRVxcHJqamqRtEhMTUVhYiK+++gpfffUVCgsLMXv2bOn1pqYmTJ06FdeuXcPBgwexadMmbNmyBYsWLTLx2yBqpusGKG6SEcE+Bm1PRNbHLM9Ezo33XSLrsvg6qyqVCp999hlycnJQWVmJW7duSa+5uLhgy5Yt6NChg0H7mjx5MiZPnqz1fdLT0/Hyyy9Li9Nu2LABgYGB2LhxI5KSklBbW4u//e1v+Pvf/47Y2FgAwMcff4zQ0FDs3r0bkyZNQlFREb766ivk5eVhxIgRAIAPP/wQo0aNwqlTp9CvXz/s3LkTJ06cQGlpKUJCQgAAb731FubOnYsVK1agc+fOJn9fRNqIym9CZh7mje7JGyYREREROTWL96w+99xzmD17NoqLi9GpUydpaK2Pj49Zg7ri4mJUVFRg4sSJ0nPu7u4YO3YsDh06BKB5bdcbN26obRMSEoLIyEhpm8OHD8PHx0cKVAFg5MiR8PHxUdsmMjJSClQBYNKkSWhoaEBBQYHG8jU0NODy5cvSQ97bS6SP6K0pr61HSmw4snJLsOHQWVsXi4gUOEyQiIjIfCzes/rxxx/jX//6F6ZMmWLR96moqAAABAYGqj0fGBiIX375RdrGzc2txbpAgYGB0u9XVFQgICCgxf4DAgLUtlG+j6+vL9zc3KRtlFatWoW0tDQTPhlRs81JI5GQmYfNSSPh6+WGOTF9bF0kItKAgSpR28BlbKgta2pqwsGDBzFo0CCD11w1hcV7Vn18fNCnj/Uq1cr0yCqVSm/KZOU2mrY3ZRu5ZcuWoba2VnqcOHFCZ5mIBNGrGuzjiYzEKCRk5qnNWyUi+5JfXKV3G85pJXJsnJ9ObZ2rqysmTZrUIgmtuVm8Z3X58uVIS0vDRx99BE9PT4u9T1BQEIDmXs/g4GDp+crKSqkXNCgoCI2NjaipqVFrAaisrERMTIy0za+//tpi/xcuXFDbz5EjR9Rer6mpwY0bN1r0uAru7u5wd3eXfr58+bIpH9Ox5KwF9r9u61JYjqsH8PxxoFM3i7/VgSXjAUDKBpyQmcehhkR2KL+4ShoBMTzMX+c2PIeJHBeH/BMBAwcOxNmzZxEWFmax97B4z+qsWbNQU1ODgIAADBw4EEOHDlV7mEtYWBiCgoKwa9cu6bnGxkbs379fCkSjo6PRoUMHtW3Ky8tx/PhxaZtRo0ahtrYW+fn50jZHjhxBbW2t2jbHjx9HeXm5tM3OnTvh7u6O6Ohos30mh+fMgSoANF0H9q2y6FvI56qG+nlhc9JIpGYXYXPSSN4giezQ8DB/bE4aiWAfzY2zpdV1UjDLc5jIsfEcprZuxYoVWLx4MbZt24by8nK1/Dzm6pizeM/q3LlzUVBQgEcffRSBgYF6h+TqcvXqVfz000/Sz8XFxSgsLISfnx969uyJlJQUrFy5EnfeeSfuvPNOrFy5El5eXkhMTATQPCT5sccew6JFi+Dv7w8/Pz8sXrwYAwcOlLIDR0RE4P7778fjjz+OzMxMAMATTzyBuLg49OvXDwAwceJEDBgwALNnz8abb76J6upqLF68GI8//jgzAcuN/YNzB6yuHsC4ZRZ9CxGgisqtqABrqwgTke0F+3hizJocjb0u7I0hIiJncf/99wMA4uPj1WI8MTVSvjSoqVxUKpWq1XvRoWPHjvj666/xm9/8ptX72rdvH8aPH9/i+Tlz5mD9+vVQqVRIS0tDZub/b+/M46qq1j7+OyCzQKCCDIKKE06omHOXMkMtRZvo5nW2MkuTJod761W7tyyztKvX0jIbrKuWQ2alaaLmkAOCw3VAUUMRJVFxAAHlef+gtV17n31GzoGDPN/P58A5e6+9pr2mZ61nPWs+Ll26hM6dO+M///kPWrdurbi9ceMGXn31VXz99dcoKirC/fffj3nz5qFBgwaKm4sXL+KFF17A6tWrAZS/gLlz5+Kuu+5S3GRnZ+O5557Dxo0b4ePjg0GDBmHmzJkqVV9znDlzBg0aNMDp06cRGRlpZ44wNYU1+3Mw9usM/DrhPuQWFJlUL2QYxjVgwysMwzCMLVRH2WDz5s1m7yckJFQ4DKcLqy1atMCyZcvQtm1bZwZT7aiOBZKpGoQqsFhZNbViwzAMwzAMw1RPWDbQx+lqwO+99x4mTJiAjz76CA0bNnR2cAxzxyGrDZ6+WMiCKsMwDMMwDOMSXL58GQsXLsThw4dhMBjQsmVLjBw5EoGBjjm5wukGlgYPHozU1FTExMTA398fwcHBqg/DMJZpEOyLXSfzcc+M1KqOCsMwVQQfkcEwVQvXQYZRs2fPHsTExGDWrFm4ePEiLly4gPfffx8xMTHYu3evQ8Jw+srq7NmznR0Ew9zxCAuiALDvzCUAbIWQYWoSYjsAa1YwTNXAdZBhjHnxxReRlJSEjz/+GLVqlYuVN2/exFNPPYWUlBRs2bKlwmE4fc8qow/rpTO2cPpiITYeOYcpqw8r17jDZJiaBRttYpiqRayscj1knEF1lA18fHyQnp6OFi1aqK4fOnQIHTt2RGFhxbURnKIGbOu5OlevXnVGNBjmjkDM5sqC6txB7bizZJgaBtd5hql67pmRyurADPMnAQEByM7ONrp++vRp+Pv7OyQMp6gBBwUFITc3FyEhIVa5j4iIQEZGBho3buyM6DBMtUYYWMotKEJYoA9yC4qQPP83xEUG8eCVYRiGYSoJPieZYdQ88cQTGDVqFGbOnIlu3brBYDBg69atePXVV/Hkk086JAynCKtEhE8++QS1a9e2yn1paakzosEwdwxyxxgW6INlo7tUTWf5bixw/Wzlh1vluAFjtgOhsVUdEcaFYTVdhmEAbguYmsPMmTNhMBgwdOhQ3Lx5EwDg4eGBMWPG4O2333ZIGE7Zs9qwYUMYDAabntmyZQsaNGjg6Ki4LNVRL51xPNZ2aEIVWKZKZnenOsYMebWkXgvg+Z1VHQvGRWHjKwxz5yOfe96pUR2zbrgtYGyluskGt27dwtatW9GmTRt4e3sjKysLRIQmTZrA19dxZZ8NLFUR1a1AMo7H1g5tzf4cjP06Q/ldJR0hr6xWdUQYF4ZXUxjmzmfXyXwkz//NbB/MbQFjD9VRNvD29sbhw4fRqFEjp4Xh9KNrGIbRp0Gwr03qvHGRQVg2ugsO5xYgNizQ7HNO6yhfPWzZDcMwDMPcoXRqVMdi382CKlNTaNOmDU6cOOFUYdUp1oAZhrGMODvVGquCu07mK2rAsWGBus+J32LFlq0VMkzlwfWOYWoGtvTdDHOn8+abb+KVV17BmjVrkJubiytXrqg+joCFVYapIqy1Kig6xmlJsUie/xuS5/+m64YHygxTddhrJZTrLMNUL+S6zvWXqWq2bNmC/v37Izw8HAaDAatWrVLdJyJMnToV4eHh8PHxwb333ov//e9/KjfFxcUYN24c6tatCz8/PyQlJeHMmTNWhd+nTx/s27cPSUlJiIyMRFBQEIKCgnDXXXchKCjIIWlkYZVhqhBrBrYNgn0xd1A7TFl9GNOS9PdMyp0nm9ZnmKrBHkGVJ5kYpvohBFWuv0xVc/36dcTFxWHu3Lm692fMmIH3338fc+fOxe7du1G/fn088MADuHr1quImJSUFK1euxJIlS7B161Zcu3YN/fr1w61btyyGn5qaqnw2btyofMRvR8AGlqqI6riJmnEstloCnjuondUGlti4A8NUD7iuMkz1hesv40gqKhsYDAasXLkSAwcOBFC+qhoeHo6UlBRMnDgRQPkqamhoKN555x2MHj0aBQUFqFevHr788ks88cQTAICzZ8+iQYMG+PHHH9G7d2+T4ZWWliIxMRHz589Hs2bNbE+wlTh9ZbVx48YYMWIEiouLVdcvXLiAxo0bOzt4hnFJbJmRFSul/dpGYNnoLgCAuYPamRVUebaXYaoHPNBlmOoL11/GGVy9elW171MrQ1nLyZMnce7cOSQmJirXvLy8kJCQgO3btwMA0tLSFKFTEB4ejtatWytuTOHh4YGDBw/afFyprThdWD116hS2bduGe+65B7m5ucr1W7du4ffff3d28AzjkggB1FpyC4pUv8d+nWFSGGU1YIZhGIZhmOpJy5YtERgYqHymT59ulz/nzp0DAISGhqquh4aGKvfOnTsHT09Po/2lshtzDB06FAsXLrQrftbi9KNrDAYD1q5di1deeQUdO3bEqlWrcPfddzs7WIapFlhzzqo4002oAU9LisWU1eaPkGFBlWEYhmEcD6v+Ms7m0KFDiIiIUH57eXlVyD/tyicRWVwNtcYNAJSUlOCTTz7B+vXr0bFjR/j5+anuv//++7ZHWIPTV1aJCLVr18aKFSswdOhQJCQkYPHixc4OlmFcltMXC5XOzhqLgmGBPgBun7M6ZfVhm85ntTeODMMwDMPchrfZMJWBv78/AgIClI+9wmr9+vUBwGiFNC8vT1ltrV+/PkpKSnDp0iWTbsxx8OBBdOjQAQEBAcjMzER6erryycjIsCveWiplZVUwffp0tGrVCk8//TSefPJJZwfNMC6H6OgAqARVa1ZYZfKu3nB6HJeN7oJOjeo4LRyGqYnwqgzDVF94mw1TnWjUqBHq16+P9evXo3379gDKV0I3b96Md955BwAQHx8PDw8PrF+/HsnJyQCA3NxcHDx4EDNmzLAYRmpqqvMS8CeVsrIqM3jwYGzcuBE//vijs4NmGJdDdHRiZVReYdWinbndd+aSIqSKPavOmN1tEOyLZaO7qA4951lkhqk4u07m86oMw1RzWFBlXIlr164hIyNDWcU8efIkMjIykJ2dDYPBgJSUFLz11ltYuXIlDh48iOHDh8PX1xeDBg0CAAQGBmLUqFF4+eWX8csvvyA9PR2DBw9GmzZt0KtXL6vjcfz4caxbtw5FReU2Vhx52IzThdWysjKEhISornXt2hX79u1z2Pk7jItSch3Yt7T8P6Mief5vRgNX+bueqtHYrzNUR9fkFhQ5beDbqVEdo5VfHmAzjP2cvliI5Pm/KRa9GYa5c+H+kqks9uzZg/bt2ysrpy+99BLat2+P//u//wMATJgwASkpKXjuuefQsWNH5OTk4Oeff4a/v7/ix6xZszBw4EAkJyeje/fu8PX1xffffw93d3eL4efn5+P+++9Hs2bN8OCDDyrGdJ966im8/PLLDkkjn7NaRdSIc1b3LQUK8wG/ukDb5KqOjUtx+mIhcguKlMFrp0Z1jNQDxW/5nFUAisAqVmNtneW1Rw2RVRcZxnrW7M9Bv7YRRtfliSlWJWSYOxN7tvYwDFA9ZYOhQ4ciLy8Pn3zyCWJjY7Fv3z40btwYP//8M1588UX873//q3AYTtmz2qFDB/zyyy8ICgpC+/btzVqT2rt3rzOiwLgCsf2AIz8ALR6q6pi4HHIHJgwoaTs18Vuo5QLqvar7zlzSHRCbw95OlDtchrGONftzlAklbf0U9chU/eNJIYap/vC+VqYm8fPPP2PdunVGwnXTpk0ddkSpU4TVAQMGKJarBgwY4PTDYhkXxdOPV1TNsO9MueW13IIis52aUB+UmZYUa7OgCnAnyjBG7FoE/JjiMO/6AXjQG3BbAWCFvpsGOtfKAESUAWVulbA/R4/mA4EnP6+KkBnmjoMno5iawvXr1+Hra1yuL1y4UOEjdwROEVanTJmCjIwMtGvXDlOnTnVGEAxTrTl9sVC1/9QaZDXgni3q2x22vZ0ld7TMHYkDBVWBJWGzTMeNG6pQUAWAo6uqKmSGueNh1WDmTuUvf/kLvvjiC/zzn/8EUH4KTFlZGd59913cd5+x8VB7cFq/2KFDB8THx+PDDz9EQUGBs4JhmGqHEPqE8Jl39QZ2ncw36V6shvZrG4G4yCBdy8HOiKP2NxtZYu5IHpztcC/LLN0r03dTZYIqUL6yyjCMU2CtJuZO5d1338X8+fPRt29flJSUYMKECWjdujW2bNmiHI9TUZxmYGnHjh349NNPsWzZMpSWluKRRx7BqFGjHCZlV3eq4yZqpuLIs6vCwJLA3Lmmu07mIyzQRzG0NPbrDKd1fKZmgHlllWFMozWIZq5+cl1imOqPmLzlusw4iuoqG5w7dw4ffvgh0tLSUFZWhg4dOuD5559HWFiYQ/x3ujXgoqIiLFu2DIsWLcKvv/6Khg0bYuTIkRg2bFi1ehGOproWSKbiyBZBgXL13hB/b7OCavL83xR3QsA1J9w6Io7cATOMdWgFVDG5VBl1iOsqw1Q+os4Dpg2mMYyt3MmywXPPPYc33ngDdevWtflZp2sd+fj4YNiwYdi0aRMyMzPx5JNPYv78+WjUqBEefPBBZwfPMC5Hg2BfRSVo7qB26Nc2wiqhc+zXGQgL9MG0pFgA5We1mlLLrai6Lne8DGM9oj4Dtw2iVYbaPKvnM0zloq1ry0Z3saq/5DrK1HQWL16MK1eu2PVspW6RiYmJwaRJk/CPf/wDAQEBWLduXWUGzzAugdxpjf06Q/ltqTMTe1ynrD4MAEjpFWOkpiv+V2QAq33O3H5ac88xTE1ALvfySoueGr3e94rA++AYpvKQ+1ZxpJw1E808qcQwQEUUeStNWN28eTOGDRuG+vXrY8KECXjkkUewbdu2ygqeYVwCbWcnBFBznZk4hzXE3xu5BUUAgMfiwzF7Q5YiSGr9tXcAq42HUEHWCqzmDDBxh8zcSZgrz6bqrdCe0HNnzcDVljrEgirDVA5y3yo0KKypqzypxDAVw6nC6unTp/HPf/4TMTExuO+++5CVlYU5c+bg7Nmz+Pjjj9GlSxdnBs8wLoesLrhmfw7Gfp2hrMZYUieSjTF9m3YWKb1ilM5S2xlaOrdV/i++y7PF4lpYoA/mDmqHTo3qGK3cyoKynC6eQWbuFMwJltZMDOlpJZh7xlph1hTWakEwDGMfch87d1A7qwXQihwZxzA1HacJqw888AAaNWqEefPm4bHHHsPhw4exdetWjBgxAn5+fs4KlmEqBXv3isrGlcZ+nYGUXjEAoFgG1luxlAVImdkbslSdpbX7ZoSgqV3pEdfFfjvxGft1hsq9iI9YcZWv8wwyU+0ouQ7sW1r+X4Op8izXI1NCp6yVYE29qKjBFhHemv05Nj3HMIx59FT4d53MV/pGW/2w1p3cvzJMTaaWszz28fHB8uXL0a9fP7i7uzsrGMZJsIVJ05g6mkIMFs2tmtwzIxXLRndRjp+ZvSFLEUT19riJcGSWje6C7Vl/YPaGLIT4e9scfxGOEHRFZzt3UDtF5VgbXligj3LcToNgX+W3Vi1KCKxcfu4w/jsMOLqqqmPhXNZHAq/8z+iyJW0Hud7KR1IJQ2h5V2+o/NG2H/ZO9Mh1TNaCGPt1BuIig7j+MYwD0PbD4nunRnWUvlG4M3dUlaXjrPTCEtpUot8V7DqZ77STABjGFXHayurq1asxYMAAFlSrIWwMwDx6g0qxf0VPlVerYps8/zeM/ToDQLmAeDi3AMnzf0NuQZFK1VZWrRWdVvL835A8/zdlVVVejTVlwEWrvgvcVkFesz9H6XT7tY1QxXvZ6C6YlhSrnO+68ci5P8M+ovhz+mKhEm9b9uQxzsXheX+nC6oAcO2M2dtynoq6KavM3zMjVXV2cmxYoGLtW0Y7wSPXFVsEVfGcWH3hYzSYmkRl9S9yfZW/y2efW1oBFX2/OWFWIE9OizZG9PNajQ2GqU4MHjwYAQEBdj1bqdaAmeoBq3JaRps3Is/kvZ3A7UGl6MjklctpSbEY+3UGpqw+rBIKRcen1xnNHdROMcoU4u+NXyfch31nLukOXmXBcdfJfMU408Yj5zD26wwlfDm+ws2y0V2Qd/UGpqw+jI1HzgG4bYV49oYsTEuKRW5BEe6ZkaoI2nodOlP5OGWyoGk/x/nlqtRtbfKWdp+2QKjMi/Iv1+/k+b8hLjJI9z1UtG5oJ7JkbY19Zy4pcWaYO5HKnhAVE0viuxAYRb3v1KiO2T7PnDEm7dacfWcuKWOG3IIixW+gfFU3LNDHqWesM4ytNG7cGCNGjEBxcbHq+oULF9C4cWPl94cffmjXGasAYKCK2BJm7KY6HvxbEdXOmqIWqlXj0XZy8uomAGWAqVUxkldopiXFYsrqw0jpFYPZG7JU18T/uYPaIcTfWxF45c5MdKwAVH6M6B6FRduylf/i3rSkWAzrVt7ArNmfg/xrxarjcoJ8PZXfIg13tNrhzFYWV93spQzOmTF0lr8I7wQ8s94ZPrs0ch2SB6VCs0CoAwvEpE/e1RtK/TY3kJX9s7YeCVVA8cyuk/nK9gBtu6Kn7WFPmAzjKji63NqixivqvS0CoyX/gdu2K0R/rt1mUB3ranWMc1VSHWUDNzc3NGnSBHfddRe+++47hIWFAQDOnz+P8PBw3Lp1q+JhVNgHpkZgaSbTnuMd7lSEaqBIc25BkTJ4tYTomMTsKQD0bFEf05Ji8WiHKEUtSAiqsWGByt44eTAtr/AINd9lo7soA9m5g9ph0bZsPBYfrgisszdkoW/rEExZfRi7TuZj18l8laAKlK+qCuFYNvokrzrJq093xDt3oqCKsj//OxhTDXuFwzq7q6I+VEtEHdITOsXKh1gREQNOoe4/LSnW5B52wHgvq9CIMMXpi4VYsz8HyfN/w+fbTwAAZm84omwPAMrPb5bbIVGf9cJJnPET8rd/oWtgimFcFUcLqnpjFLkuyuq/YoVTuKlofDceOaf4KSaaDucWGBlWrG5CX00b+9VUDAYD1q5di8jISHTs2BG7d+92eBgsrDJmEQMcc3suLDVIFT330xHYY4nP0n29jk1WiwWAfWcuKQPXNftzkFtQpAiXAJS9q0KlVvYHKF+1zC0owpTVh5VropOcsvowkuf/himrD2Ps1xkqy8Dy+xAqSMLQS1xkkBL+t2lnAUARWH86mIeUXjHIu3pD8XtE9yiM6B4FoHxFV6gPA+WCuQhbpFHsp1mzP0cZKFfrzqq2/uxmRQU/tz//VFYj7BDhOPYxx0SmirGlPAq3nRrVMTJyIsq3rFoPQFHVB8rrqWxBVPipJ5guG91FaQvMqQyK+ifahdkbsvBYfLgS/rSkWORdvaGoBMttEACVyv7WpOuoY7gGHPnB6jxhGGdQVf2Edh85AKX/kveDCw0L0dcKN9bGW67/gjX7c5R+VrQjwO3+Xe5DLZ137mrwlqCaARGhdu3aWLFiBYYOHYqEhAQsXrzYoWE4zRowU/0RDbOweGfK0q01DZK9gqo1FvQc5Y8pd0KNRdxP6RWDbjH1lE6rX9sInL5YqAwMZWH0eN5V5bvohPQ4nFsAAIpqkTCqIJPSK0bVmQJA39Yh+OlgHqYlxSqGXPTOXBWztQCwfG+2sgIDAI/Fh+PbtLPo2zocgT4eStrE9UXbshW38iqrSL9YVZL56eBZRbVYpEOrmiy+a9WEnKE2VCE/dSzEWlOmrAmzMmcL3VA5KlmurvZlS3uw78wlZZUyLNBHGaAKFT1Aff6xXD+A22r3QrtCtKfafWhCnV8vDloVQKF2L+rx3EHtkPb7RSzalo02EYG68RBtkmgDRNi7TuajU8dHkfXrEsTEP2R1HtYUXL0sV2f02n1H9PfmwjDlRhsHUW9ldVxRf0d0j1Lqkfi/78wli+GI8ZTwW9TBuMggZSsOAN3vchsj2g9hJNGe/auVWa65/tz5GAwG5fv06dPRqlUrPP3003jyyScdFgavrDJGaGf7tceZ6KmpWWPlTmDtSpt8vIo12LuyK6vjybOrsoEisSLRt3UIZm/IUjodYVFXrHY8Fh+uDBSFaq1gWlIsHosPV4Xdt3UI5g5qp+xJFUYYhMAqM3tDltEZij8dzANwe/VGb7VXdGqyPzJidVWoEYqO8du0s6r4itWihGa3O8axX2dg+d5slf8pvWJUe2DFcyJtotOeveGIkRVFebVKq1ast6ptTTnSrvybe8bUzLU2b62x7uhI9SdzqqG2hCELPub8NqdBYC4Orqr2ZU3eye9eW6fFCsewT8tVe7UTSQCUM5MBKGryszdkKVoJgHrCRt4aINqMvq1DlGtCrVjbDo39OgMbj5xTqfyKwe2BnALddE5ZfVhpY4BytUNFlXjPedy/vj7WHLmstBfW1i9Xe8+2YE3aLJVlW+qGpeum6pwpd3K9NeeXtdjSptrin95vvbx19Cqcqfcn+ha5XskGjQB1HykmlsICfTAtKVbRQhIaSim9YowsfptD7hNFuPKEsPw90McDAFRtiEiD6HNFXyqnW7ixlC+m+hVHlwXmzkZr+mjw4MHYuHEjfvzxR4eFwcIqoyAacNGAymcFisE5cLuBtdSJC7/kjkEIKqY6ERkxMNNrdLUNrV5Y5gbhes+JdMpHQew7c0lZlbxnRip+OpinCJiiQ9t0tFxgFCuRQHkHInc6QPmAUdwX/HQwD9/sOQ0AqjNXgfJJAjG4HNE9Slk9FR2qPDhO6RWjqA+K+MsDbgBoF+lvlI/y4FjLiO5RmPl4e8XND/vL4745U/0+hFEmAMrZsXMHtVP22IqzYMXEg1BHlgVjQG3ERqgtfr79hKK+qGfh2JTVZOB2GZEnPcwJrtojAYTbz7efUMrD59tPKP7KxwnIfogwtYYxrOn4TQnmIvw1+3NUbvSOTJAHK6YGItq8lCdk5PvWHEovu9dTp6tqTA1aZWFQq74uT77IdVaUfVl7Arg9iaWHWBmRy7oIL7egSFXnxeSTaHNMTYjIK6dyO6BtXwRCfV/EUWwdEMhtnPhvTsVRLjv2CHPWlo2KlCFLg3BLcddOSOn1JXL7o3dfW3/0wtfmpbn6J09ayPVWz425tOlNyll659o8NIdeO6vtZ01padkTrt49bbsP3K53YgwiLN2LOpR39QbmDmqHaUmxSp1Ysz9HaSvq1PZSJmOX7y3v32dvyMK07w8YtfFyOyxrqWmPs5LrL6Duk0V9FWOJaUmx6NSojtKHCvezN2QpfZPop7R9mfgvWxIXZUg7bpL7V3vqsLX9nTlcpf9gLFNWVoaQEPVYsmvXrti3bx82btzokDDYGnAV4WoWv0RjakodTbYuKYQlreqJaAhFYyfUQ+VBkazeKndWcmMuLFwK9bhh3RorfgMwGkwKf7TXtWGKtInfIi2yxU4AKmu9wG1VW/HfFCKPTOWhNWit/AJqtSCRP59vP2EyDFl1KaVXDJqE+JtVQRZEBXkh+1Ix2kX6I+PMVaOwrYm3HAc5L8Rv+f/xvKtKZyyXCzkPhnVrrDrPTi4f8juXBSSt1WU5TKGyLdD6Kf+WhWctIr6yUAHcVgkVaqO5BUVK3MV1U/VG3g+ltSB7+mKhqi7Jat3y4EeuN+J9yGGevliIjUfOKatsj3aIUrmX0yHSqH1ezmdtGsR3kbeVsV9JGxdtPMU7kN2IciNWOMT3uMggo/ovT0IJ5LbAUrsAlNej+OhgpfzdMyNVqaeHcwuMhM9uMfUAqNtYMfA0VSZlS9+WEHFO6RWDuhvGY5D3n34KM9JiY7Pb7X+qW2X694y8+POHPCuuva4JyqQ7W9B7VhtvlAF/dJmE0AcnK+VEzm+5HwP0y7OpOiu3Hdr2RWtRVu6LtEefiXISFxmk3JfVP0XfJYcj4g7oC39ynGUr7to+WA+9NFijsST7b8pCtTm04Ypr2vGGuXcjt5nyVh7xW2vl3lR9stS/y9b85TCB2/1GSq8YpPRqoduPa5/R8x+A0o6LuKb0aqEqd+L9ArfLkTzOEWjHaNqTDMxtiTLVn4k21Jr231T7bW05u9NwNdnAVeCV1Qoyb948NGrUCN7e3oiPj8evv/5a1VGyC9loj5bH4sOVxuzTbVnKzKQ8aydWn3adzFfN3Ok1ur9OuM+oERNqryIeYlZ7yurDKkM9svqLbJ3z9MVCo05BDLyFhT2RNrE/dOORc4rFTjGDLuL+64T7lIGsGIg+1DZcmXXVQ5tW7YypKR6LD1fcCiFCVtmLjw4GUN5Jinw311nGRQahU6M6ykqKWPkV9G0dokqDUPXNvlR+RpYQVDs3ustmQTW2vh8AIP9asZIeoPxMWNkYU4i/t7KSLFSstJaOhWqzEDTkw9Hld663aiqfFys6bHmVXqh8CcNQYmAlwpA7fe37FrPb8qAief5vSrkS70loJ4jVee3h7gCMZq/F6rm2fjQI9kW/thHKzLxIkzB2pTWEJvJdTp8Ia8rqw8ps/Ae/HAUA1KntpYQl0i2f56c34y6vzoj8FnVV5GVlCKp6K8vyKpFs8Ezcl/ecie8h/t7Kaoz8zoWgOndQO6WuyMKpVlAVqzIyi7Zlq840njuoHfKvFStGzIDyevhYfLiicSCXldMXC5VrI7pHGW0nAID07Mu6eSRUCOX2SMS5SYg/BnlqhF+tBa4ytXEurWEw+Z6eO61RL/l5RYDUMfxl6nlTmApD75r4HrrrbaW8yH0aoL/6py1Hcjsgyrt4V0D5exaDeT3/hHAohBtRt4R70WaK+MmCaligj9L+yW2LwNSqmBxnuR4LdVc9QVUWPOU+VxuGPCaQDYWJdtySATFT6GmqyOMNvbZGhBfi760SWIVWlGxxX1i5l9EKqmLFUxhD0mPuoHZYvle9x7RdpD8Smt1WJRZ+z95wxChMoV6sV7+B8rZFrPL2bFFf6TNlQVXYkci/Vqxqi0W5Efkv+sCxX2cgpVeMalwm27sQyO9b2x9r35Upy+mmtBMsrdI6YrWfcSwdOnTApUvltkrat2+PDh06mPw4AhZWK8DSpUuRkpKCf/zjH0hPT8c999yDvn37Ijvb8gDf1ZA74fJZOn3VMiG8yNZfxQBY7O2SB87aQZsYvOcWFBk1MGIFStu5ydZmxTXt8SyymrLwS74vBvpiID93UDv0bFFf8UsMyLXqUfI+UzGwFWkVPBYfruq8RAcU5OtpstOR+TbtLGZvyFL2gopOUvz/z8ZjRvmkJzCLOOw7cwmnLxaiZ4v6iv8yPx3MU3WS4n54gKfK3c6Tl83GO6FZHdUeXQA4fK78+As9YVqoLsl7/rZn/YHle7NV+4VkYUse2IhJB3lVQvgnlyVhgRmAsroprxgK1S95ogK4feC6PPO8bHQXDOvWWBESRdrkVXwhnOilWexrHvt1BrZn/aFKkzy4EHEWfpsS8sRKirAqLQZOot6JAbQYxAjBV6RXlJufDuYhoVkd5d3LA2CBmMwRdVwY0RLvQbsH+fPtJ1SrldqBjN6Awtz+dWtUyeSJMa1bkSbt7L88ISXevZhgEO9VFiCB28dRyXVJ3rsN3J6oESq22vvLRndRBppyGIJv086q/J+WFKuyEi7yddG2bF11X616voiPaLO1g+8R3aPQr20EssIelCRNGI8K5OVPqAVS+Rk36HzX+60ThHaVVeXOgsCqFZKN4ihf0/qd8DoAtfVmWWVS/BdtjSjn8oSIvMoJ3O5LxUSSPDElhyEbpRPtgKi7ov6L+jgtKVaZeBPlWRZmte0WAFV/qEW0C9oJNL12RyssyIKMLCTK7YAQroU1e3lrkdwOCf/18kh+B3K48jV5YlF+X0LoP5xboLTzshV7sfop8lfUc21/Lffr8qSU3iRuSq8YlbaQMMSUceYqNmfm47VV+5XJQUB/cmnRtvK+UNRvkU+iLZHV92VL30K9GbhtR0Ke8JYXA8QEiRj3iEltS0aitBMGWlsmAnmyRntdK3TKfsr2OMztX7ZH4GUcz4ABA+Dl5aV8N/dxBKwGXAE6d+6MDh064MMPP1SuxcbGYuDAgZg+fbrZZ11tqf+Vb9JN7ncSxNT1QdaF8o7YGvVQrUVbPfUZWeUSuN0AyjOCskqiOFtUVq3UU6GSO1A9NRURhnaW2BZkddmKIuctYKxa2Ld1CB5qG64MjIS1XZnY+n6KsAhYr8IrEx7gibNXSnTv1fGthfzCmzb5ZwptXGU6N7oLO09exrSkWGXFT1bPlMuRWKXVU9tdNrqLomIpq7kKVTqhKq2d5JAtwMpqd3J4YoVr0bZsXRVmLbJKmaxmJfstBhZixVmrumpOLVlGPCvUtH46WF6vTZWFx+LDcW/zEEXV0FydFfVPTm/PFvWV+mfKyrN2a0C/thGq9OhZ4DalOq2nmqZVO9O2A3qDXoF24kFP/d4aVV9LiHJt6rc5RLzsjYcQBIVKs/gv1xFLyGqjcp5p22i5Pgm1T3Mq46JcyCqxeu/X1EqNKOei7soq8QCM2ne5DMrpkN+3ngqofE20TXLdFccHzXy8vbJ1QZ4ElldbTamjPhYfjvH3N1f1X2KCSn5OpEFoWMjbWbRqpHIbKfJECGra+Gm3WYj/ol6LdAG31UflfsHTDSix4Wwsud8TeWhqW4Z4p+KaEIaFar12y4VAT41fvOsR3aPQsI6f1dt2wgM80aCOr1G9FVtoKht5G4MWuTzLq/95V2+o1L+16u6A8YqqduuXtnzI7rT9gLin57dA3pYh11+99lu8fwBKHymXa1stI7sariYbmCMjIwPt2rWrlLBYWLWTkpIS+Pr64ptvvsHDDz+sXB8/fjwyMjKwefNms8+7WoEcOHeLzYKXdrAlN/zyoF7Gz8OA66XlRS6ktgfyrpWqGvrOje5Cg2BffJt2Fp0b3YUhXRsi/1oxeraor+qEhP+ycCGrR8oDKjGgbhDsi9kbjuDRDlFKAyc6/HFf73GY4OlsTOWt1s0nW7KsTpOXO1B8y1ExdDxuAHyksuPlDrgZgKI/ZWd5lfHQ2Svw9nBHPX8v1SAlKsgLrSIC8VDbcPyw/yzqB3qbFeYTmtXBrhP5ShgCf083XJVGZHd5u+PyDXXmCaFCVj8Tx4vIgwJ5L5EeKb1icOZSkXIkycJfT5gcFMmTJ44QrrTI6dRONmj3lsuDdXmQK45bEe7X7M8xGjjJE09aAUYrnMj+A1A9dzi3ALFhgXjv5yOqdioqyAvBfp4ovlmGMxeLcLWkzOZBtrPQW12sLPTKMVBeD9pH3QUAqiM3RLsrJjD0JoxkQQmAaiVSXPt8+wmlfTclLJn7L8qI3l53eT+omGDacvQPZF0oMpogNEUtAI6ZorMN0c7E1vdDgI8H9py8DEtNtLlybKlNkAU4rTV3PSG4Munc6C4E+3miS+M6qFPbC/nXipVJM7k/1BNMKxNzk72VgWiX5XgkNKuDzZn5yn+Bdm+qPFEpTwLojbu0e56122ZkmwiyvyO6R6Fv63DkXb2hGF6U2w0hhGrtiHy6LQuLtmWbXPCQJ9xsPcrH1fbDuppsYA43Nze0b98eTz31FAYNGoTAwECnhcXCqp2cPXsWERER2LZtG7p166Zcf+utt/D555/j6NGjKvfFxcUoLr49yMzJyUHLli1dpkD2nb3J5EqXFiFkViYeBqBUp6SKDlU7Ey5+ywK1LBSP6B6F37LyrU5zVdO50V14sE2YqkG2tMpWVbO9zG20EzqPxYfD37uWajCoHUTUFNwB3EJ5nkQG+SjGngDjM3nlVWatURIu55WLAQChvB8oKrmlTNyIiZVv086qtAQAGBlU0yKErBHdoxDo46FMaIiJT/lcWSFkmuoTrMEHN9DbbQ/WlXVEEbzt84RxSQZjNd7wXFLV0XAZVpbE4WVMrOpoVBo+tYDD/7LuzGhzWhtVRXUSVnfs2IFPP/0Uy5YtQ2lpKR555BGMGjUK9913n+WHbYSFVTsRwur27dvRtWtX5fqbb76JL7/8EkeOHFG5nzp1KqZNm2bkj6sUyNkbjlhtSVImPMATyZ0aKM9W5cymtTPl1Z3H4sNxvfimQ1fOqmICgmFM4edhQNPQ2ii+WaZMKIkVJmtVZxnGFGvcxqJlrYtVHY07B5Mbjv9E754LaDJUCtak1cn50bjka+d57mL4eRiw9sV7TVqIl38DlWe13lqqk7AqKCoqwrJly7Bo0SL8+uuvaNiwIUaOHIlhw4Y5LA1sYMlO6tatC3d3d5w7d051PS8vD6GhoUbuJ0+ejIKCAuVz6NChyoqqVTzaQd+6nSXOXilRCbmyoFrLzHPudoVmnuomqPZtHWLSqqAW+YzUb9POqgTVzo3usit82YiWqwuqtWC+PNUk7G20PQyW3XjqeG7FYw7neikh48xVlebD4XPXnSaoehhMp9Pnz4JXx9c1SqC/3kuygL1txJ2KVYKqYjZY890atM/pPe+m+a/9bilOroLbbUNYbm63/yvRFKahpY9iOAvG93TzxYFx1b1m0QKYg8LSu6c9+8lUnKz1W8Oem/aN7aori0Z2VhnqBNQW4mXL9rkFRS4lqFZXfHx8MGzYMGzatAmZmZl48sknMX/+fDRq1AgPPvigQ8Jwjd63GuLp6Yn4+HisX79etWd1/fr1utavvLy8FMtZAHDlypVKiae1yIYWZCpiREi7z0esumoN/wjVryBfT5zKv45fDp1H9qXiKt//IWNrXEytMMvXrVkZFfuMnvpLjMrIT1xkED7dloX46GCb9hHJed8kxF91T+x3MWf8yFbMGZGJre+HkABvZW/pY/HhaBMRiEuF5RMgQpBftC1bKUvy2YJ9W4egeX1/FBSVYtG2bMTU9UH76CBEBvmY1BIQKqPivzAuJNAa/tFDnJkJwMjIjKCiK9VCRVi8L3m/2ZI/wzKnxRBS2wPLn+uhOkNPqzIp/JbVLfu1jcDn208gNqx870ny/N+gp3ojvwdh5EM2giX2NuVdvYFNR/Pg710LV2/cVPai7zp5WddfezEA8HAD6geW70cVbZbYT3k4t0ApVyK+slrqV8+Uqx2PWbxbOX9Uq6Kd1D5ceReW9jsLHosPR3LHKIz9Kk23PGj3B+o9L96x2FM6/bG2OJ5Xnj6hLnsq/7rKGNRDbcNVaRR1UNv2CmujslEp0aZoz6DNv1aMjUfyHKayntIrBl//Vh6XC9dK7VpYCqntAW8PN2RfKla1W9qyrd3jfH52G9S7fED3vFij81m1woQVgoKb/Bxu+yf7JX4r1wGTq5NyFIzyydQKpjaeWoHI1OG4mngb+a3JDznfytx05DAda9B691Tn4GryRS97VHmhk7ZzAbHoduF1I+Nd8h5nrZEs7VmrwG1bHLJbS2gN+mm3LmgNnZnzQ4t2b7FcZ+X7U/EfDPXcho61snECg0xa3DZZZkwenqxBW170yom2PFkRpl59NLlAL4Xzx9f18OuE/ap3Dty2zA/cPtpQ3F+zP0cx7MRUjJiYGEyaNAkNGjTA3//+d6xbt84h/rKwWgFeeuklDBkyBB07dkTXrl2xYMECZGdn49lnn63qqNmMbIZcNlZjqzVZc4jGWW8QIVs/XLQtWxnsArC4N7My0AqqQngQAySRV0K4N9UBaa/LRiv0hMQR3RsbCbUiXxZty1bej6lJBdlSo7bz03a8ImxtHGSBU1smxCD2txP5qniKTnhI14bYeTJDCV90+GJwLsKSDTf8OuE+dIuppxhaERZ3gfJyKo6I+OlgHro0rqMS6qY/GoewQB80CfFHXGSQYt5fCE4ijOxLxUreC+ubssVBYbRBHqAI94u2ZSuGxEQ6xLE0Io3mDH4IASgqyAuXrpfiakmZYoxCHPQe5OupEoBF3k5LilXqqny8gWzUTD7eRhgc01pGrlPbC3GRQVi0LVuxuCzK1bBujQHcPkZCTI7Ix3eI9ySXX3EcgmyRcdfJfHybdlYZMHybdhYzH2+PBsG+imGd3IIibM/6A7M3ZCn1ypxRG0834C7f8skAYU1Va5RHCM2XCkvQqVEdpY1pEuKviq/4HRbog9MXCxWjWHGRQXi0QxT2nbmkCGeLtmVb3OYwLSkWB3IK8G3aWcTU9VGOoxHpkvfXirwTBoEA4+Nl2kQEKuEJ40ff7DmNzZn5qqOUBDF1ffDTwTyjNkNYmV2+V92eT1l9GL9OuE8xVlMujJef+ywmbgAohlRiwwKxOTNfZU04LNAHH/xyVHUerTwRICaERPkShAX6IKVXC6P3Jh9loSccmDOgJOqC6EP6tY1QjD8Bty2RhqZsBQDFwJfWMry80uIGtcogAFWYAlHGZb9kw1/CLznesnEa8bzwV2soRsRDGGUDoDJCI5Att+rFWy+v9az/inekNX6mF7ccHYvcwiKskEX0DNnI92TDaabiJlsClsORz2dX6v8F9VnP8gqaNs9EnZePEwLK2+qR3WOUtJmaVBKI+z1b1FeMOp6+WKh7TJWM3lhLPj5LnoAV7uT/gT4eiltxfaj3tnKPJEFOO1kCSBMl0MiN5iZQZCFUK2CanJnQuaa95aYj72oFVc3EhHZiqF7pH8hBeT8ltMdkI1F9W4co91J6xSh97qajeZj5eHudyDPWsnnzZnz66adYvnw53N3dkZycjFGjRjnEbxZWK8ATTzyB/Px8vPHGG8jNzUXr1q3x448/Ijo6uqqjViFEIxkfHWzUgIqBtmhcrT1+QQg1wu/YsECjzh24LZjmXytWrEbKHYtoWOT9qRUxtCGQOwu97/JxDEIYkGc2+7Yu7ySEwGipUxN5Ig/g9FYzxbEjm46qB5+iU9V2ZFqGdItW7sWGBVplmEn4q7cKLr5rBc+fDuapBvLJHaOQ3DFKSSdwe8ArrDhrDWOJQZB2QCOXE4EYlMrH0oizMgWm3oFwHxcZpDqj05Jl3vxrtwVcUY67xdT784D38nBkA1h6kz4i3zZn5isC8/G8q4oavhCARXpE/sVFBillX7xH+QgCcaauqEvyYFJ7zqp87I9MWKCPMsAUZ+WJswnFucbyYfDaPJWPL9HWZ0B9dt6uk/lKWkRZ0B4VpD2GRqwSL366i5G1YPFe5LZiRPcozN6QpQiky0Z3QYi/t+I2LNAHnRrVQYi/t2qAnn+tGPfMSFWVH/FdlG9zllWFG9E+zR3UTqm/nRrXwYQ/jwlqEOyrTCacvlioKquiLolJCCHUTll9WBGe034vV2UVbbA5LZhv084qhr20KzHi3ctnEQvklWigXADS1qt9Zy7h27SzKqvrpy8WIsjXU2kjkjtGqY4jEWgFD/n99WsboQgQIv3Cv54t6qvOJJXLlpgASZ7/m2oCTBa6RBzlPkY+P1SLcC/HT+8oGr2zKLV74uR4651JqT1rVRsPbXsoC82inspCnd55q5bOsRTPyXHX5rOpeMkCuPYYGkvp0gqWeseqiDNl5XBE3dCekS3aNFEGtO7l8YVWK2TZnvLzjDceOae04dr+RLb6DkCZ5JLTKOeNOF5HlGnRVshjLW39ssYGiDxhm9IrBk1C/OF2bAjKDnx525FmdV8IgXqypWpRVbtUbgLdlVBZsDXxXXtes3aV3mj1VBKiVW7+vH70hj8em7VJyRftOxPttvb6t2ln0SYiUJk4ZKzj9OnT+Oyzz/DZZ5/h5MmT6NatG+bMmYPk5GT4+fk5LBw2sFRFuNomalMztvvOXDJ5BIopNRVAXw1LzGaJRkJ0JgL5OBkhDE7p30aJH1DeoWiFRHEkhrBEqUUWvEZ2L59Jk83ei/TK3+WVKO1sLwCVeiUAXeuXWqFHPr7EGkwJjGIAIFQWLaFd/RKrWHLcxRmB36adVeWDpdV1bTrlczj18kDvXFtt/LSDLe2Kg7mVFeGfmBgxdfyC3iBKXjnUutcOIOSyqxWY9OqF9rghPUFaTq84B1Je6RDPysKipTNI5evyOafao4/k+MlnH2vD1AqQos2Q4yr/F/mjd5SA3pms2jC15y3Kg3JtvmvPY5RXXbQCknw+nzyI1qrrCcFOVnHWoqdOLQtX4lkxsNU7N1LvvegNwM2dBW3NRJS2PgDq+ifiYeqeyHNT1tdl9XDtCptILwAjFT29Mx/lcixPYMjuzWHqLEjtyqfe2a7y86bipT3H1VScLB2NoT1D0to9dNrwxXe9tGvva/3Ra28tpcsSemdt2uOX9j1ojeToWRDXrijL/Yo8uSnql9y3yMfkmev/RLsnH9Olt+psKk3yeaGivZW1f/TCk/tkud3Tnk+vTbPearTe+fN6baI2n2XtGb36o/eOtCvjsiaM/L5kDTtr/ZV55Zv0Chn4tMWSsLOwVzaYN28e3n33XeTm5qJVq1aYPXs27rnnHifGFHjggQeQmpqKevXqYejQoRg5ciSaN2/ulLBYWK0iXE1YBYwbeEvnqsmDcnmlQRZYBHKHoJ3B13aS8qqGWFXSHhxfrsLRQnVun3bwLZ+5qtdxyh0ZAFXDrnf4tXbALNAevi0P+oXKqnYQCkARhOW80OarnB5ZEJI7rpHdY1QDTHnwLFbctCprAmtWgPUQYciDW62Ap02HfOA3ACNhU+SDdrAEwOj9663Ki3TKZzqaEqK0naJWYNY769GUupmpFQV5Bl32U64HYmCv14ELtCpyImxbD0DX5qWcZ/J70DvM3dTA1ZJwrB0kWYqfqQPfZYFOe+ajngBjyvKjXp7pqQ9r2z6RDnkiR6478jmzgPr8XHlQKQvbptQrBXoD39MXC5UjXIRbsQKk3buqnbQRq/d6GgR62zHk/BfopUvbJomwtXvATKmearH1uq1YM+g1NWB3RPi2xK2y0GsbqwNaAUjvPmAsxMuTWHoCnNw36a3sy+Vbr92wtr0zN4kikPda67XhegKl9pxUbZ9qShg1VzdNTarYUmbMTQ6Zyx9raTjpB5vcy7gDyHq7agVVwD7ZYOnSpRgyZAjmzZuH7t27Y/78+fjkk09w6NAhREU5z8BWUlISRo0ahX79+sHd3RlmU2/DwmoV4YrCqkArRPx08KxZIyAyemrB2oZdO5sGqBtfeWCqfU6vY5AbZqB81VOo2ZlCT+3T3Ky9dl8RcFulR17h0UunHJ52ZVlvBQuA0cBYK9jIq0V6e3dkQVxWzzSHrB4oC5ra73KHLSYSTAljh3MLVGp52k7KXOerfV96g0bt8/YMtGTVV1Phm8IaAc7cLLYpP6wJx15sETodEY4tfpua3ddOMJh7X3oDNFviLBDtg2hLtHEQdVDeNyvQToLoaZHoxVmur7KwqB1UaifUZG0ROT56g0PthIoteWRq4kf+b24SpSqFIVvDrm6CW02lIu/J2hVxvQlOe1bZrY2Ltg2zZuLEVNug1zdWtA9wVp5XFHl82C7SH+2jg3TtegjjjNrxrL1jCEdij2zQuXNndOjQAR9++KFyLTY2FgMHDsT06dOdFdXKhZgq4fTp0wSATp8+XdVRMWLniQsUPXENZedfV659v+8MRU9cQztPXFDui8/U1fspeuIaGrpwh+q3+Ow8ccGqMAVyuHpk519X3Gj9luOm9UcbhnCz88QFs2EKt+bcWZtGPX+y86+r8jd64hrltxw/bbrk96SNl7gmx134+9m2LIqeuIZmrT9M0RPX0GfbslThiY8cX/GsNu/Eb720ys+bcmdL/pnDUplhqh8Veady2bfXH2uek9sbbRmW64c1cdHWa7nea9sL+bt8X9RR+Z5evCqSL9WRmphmxjKmyoM1YxBb3NuD7Ke1/aNePGpamRdjGb3xlLY9FG2s3hiqqhCywaFDh6igoED53LhxQ9d9cXExubu704oVK1TXX3jhBfrLX/5SGVGuFMxsl2ZqIqcv3jb4IFQzT18sVFYfwwJ9VMY4piXFKiqnwvCHsEwnEJY2LYVp7cpWg2BfxY12Bl9evZARs6FCvaZB8G2jB5ZWHIVbsZKilxZr1DGF4QxT6sgi/r9OuA/92kYos3yyYRu9tOYWFOGeGanYdTJflYfiI8L8dcJ9CPH3VlZJH+0QZWRsSOSr3t44oVatlz96ae3UqI5qltfUexXvxlwZsURVz4bKaNNRkXRZ8vtOpiLvVC779vpjzWq3qINzB7UzagPE8yIuesbD9NyLeiNrW8jPmatHY7/OMGrj9OLlCisIlUlNTDNjHtH36rXXpq4L9LSmHN02y6uo1vaPeuW7JpV5MVYVR9OIcY8YT4n2UIyVRBsrjyldhZYtWyIwMFD5mFohvXDhAm7duoXQ0FDV9dDQUJw7d64yolo5VLW0XFNx5ZVVsaqmvaa3Upedf50+25ZltPooZrNsXVVwVvyJTM9O2hK2I+KpzQ/tCqQ5t6ZmdM2tKGsRq556Ky/acGT/5WuOWqUwtfpTXdF7X47OK1eZAa7JyO/Cmvdhz7uzpe2U21wuIwxjHdaurFqqh9bWN2dqeTDlWGo3TWm4uQq2rqzm5OQQANq+fbvq+r/+9S9q3rx5ZUS5UuA9q1WEK+9ZtYR2f5J2j5XsRvtMZcWvInsYhR/OiK+pfXyWDNVYa5AAMD+TKu/xlC0RmgtLXv21x6iCJe60vWHOLPt3Wl5VZ2QjRNbgiL1s5tzYu0+XYRjLVLTtdcS4hLEec+9Lz46Eq2CrbFBSUgJfX1988803ePjhh5Xr48ePR0ZGBjZv3uzM6FYaLKxWEdVZWNXiihXfVgM22med0anY629F0mIqfO3ZfJb8N6UCxTA1Eb0JnKrGUe0EwzDOgeslYwl7DSzFx8dj3rx5yrWWLVtiwIABd4yBJd6zylQYVxNUAWNz7rbsJ3G1/U3WpsVSGuV0ib0c2nSaSrO8l7Um7ZtkGD1EXdKeO1vVcQKct4eOYZiK4SpjijuWkuvAvqXl/2sQL730Ej755BN8+umnOHz4MF588UVkZ2fj2WefreqoOQxeWa0i7qSVVVfHlWYzHaFKVFF14YrgSnnJMK6ALcdDODsevLLKMEyNZd9SoDAf8KsLtE2u6tjYhb2ywbx58zBjxgzk5uaidevWmDVrFv7yl784MaaVCwurVYTLCatvNwFu/OEcv0PvBsZscI7fjAIPUBmmatDbp1yZ+9PsCY/bC4Zh7iimxwDFF+x/vlEvYNhyx8XHDlxONnARWA2YKcdZgioAnN/tPL8ZBR54MkzVoK17lb2VwNbwWFWYYZg7jooIqgBwkhdVXBUWVplyvOs5z+/Qu53nN8MwjAtS2ZNHtoTnavvyGYZhKkxFx7GNejkmHozDqVXVEWBchEnHqzoGDMMwTCXBgirDMHcUPI69Y+GVVYZhGIZhGIZhGMblYGGVYRiGYRiGYRiGcTlYDbiKKCsrAwDk5uZWcUwYhmEYhmEYhqlKhEwgZASmHBZWq4jz588DADp16lTFMWEYhmEYhmEYxhU4f/48oqKiqjoaLgOfs1pF3Lx5E+np6QgNDYWbm2tpY1+9ehUtW7bEoUOH4O/vX9XRqTZwvtkO55l9cL7ZB+ebfXC+2Qfnm31wvtkH55t9uFK+lZWV4fz582jfvj1q1eL1RAELq4wRV65cQWBgIAoKChAQEFDV0ak2cL7ZDueZfXC+2Qfnm31wvtkH55t9cL7ZB+ebfXC+uT6utaTHMAzDMAzDMAzDMGBhlWEYhmEYhmEYhnFBWFhljPDy8sKUKVPg5eVV1VGpVnC+2Q7nmX1wvtkH55t9cL7ZB+ebfXC+2Qfnm31wvrk+vGeVYRiGYRiGYRiGcTl4ZZVhGIZhGIZhGIZxOVhYZRiGYRiGYRiGYVwOFlYZhmEYhmEYhmEYl4OFVRdi6tSpaNeuXVVHg2EYhmEYhmEYpsphYbWSMBgMZj/Dhw/HK6+8gl9++aWqo2qS8ePHIz4+Hl5eXrpC9Y0bNzB8+HC0adMGtWrVwsCBA63yd+rUqWjRogX8/PwQFBSEXr16YefOnSo3xcXFGDduHOrWrQs/Pz8kJSXhzJkzDkgVsGXLFvTv3x/h4eEwGAxYtWqVcq+0tBQTJ05EmzZt4Ofnh/DwcAwdOhRnz5616O+BAweQkJAAHx8fRERE4I033oDWntnmzZsRHx8Pb29vNG7cGB999JFD0lQZOCPfjh49ivvuuw+hoaFKnrz22msoLS1VubtT8w2wrj7oUZPLG2BfvnF5UzN69GgYDAbMnj3bor81vbzJWJtvXN6A4cOHG41/unTpYtHfml7e7Mk3Lm/lHD58GElJSQgMDIS/vz+6dOmC7Oxss/7e6eWtusHCaiWRm5urfGbPno2AgADVtQ8++AC1a9dGnTp1qjqqJiEijBw5Ek888YTu/Vu3bsHHxwcvvPACevXqZbW/zZo1w9y5c3HgwAFs3boVDRs2RGJiIv744w/FTUpKClauXIklS5Zg69atuHbtGvr164dbt25VOF3Xr19HXFwc5s6da3SvsLAQe/fuxeuvv469e/dixYoVyMzMRFJSklk/r1y5ggceeADh4eHYvXs35syZg5kzZ+L9999X3Jw8eRIPPvgg7rnnHqSnp+Pvf/87XnjhBSxfvrzCaaoMnJFvHh4eGDp0KH7++WccPXoUs2fPxscff4wpU6Yobu7kfAOsqw9aanp5A+zLNy5vt1m1ahV27tyJ8PBwi35yebuNLfnG5a2cPn36qMY/P/74o1k/ubyVY2u+cXkDsrKy0KNHD7Ro0QKbNm3Cvn378Prrr8Pb29uknzWhvFU7iKl0Fi1aRIGBgUbXp0yZQnFxccrvYcOG0YABA+jNN9+kkJAQCgwMpKlTp1JpaSm98sorFBQURBEREbRw4UKVP2fOnKHk5GS66667KDg4mJKSkujkyZMOi782nnqIuNtDQUEBAaANGzYQEdHly5fJw8ODlixZorjJyckhNzc3Wrt2rV1hmAIArVy50qybXbt2EQD6/fffTbqZN28eBQYG0o0bN5Rr06dPp/DwcCorKyMiogkTJlCLFi1Uz40ePZq6dOlifwKqCEflmx4vvvgi9ejRQ/ld0/JNWx/04PJmjDX5pkdNLG9nzpyhiIgIOnjwIEVHR9OsWbPM+sPlrRxb802Pmlbe7BkbcHmr2JhKpqaVtyeeeIIGDx5skz81rbxVB3hl1cXZuHEjzp49iy1btuD999/H1KlT0a9fPwQFBWHnzp149tln8eyzz+L06dMAyle07rvvPtSuXRtbtmzB1q1bUbt2bfTp0wclJSUAgE2bNsFgMODUqVOVnp5Tp07BYDBg06ZNuvdLSkqwYMECBAYGIi4uDgCQlpaG0tJSJCYmKu7Cw8PRunVrbN++vTKiraKgoAAGgwF33XWXcm348OG49957ld87duxAQkKC6pDp3r174+zZs0q+79ixQ5Um4WbPnj1Gajp3Atbkm5bjx49j7dq1SEhIUK7VpHzTqw8AlzdLWJtvWmpieSsrK8OQIUPw6quvolWrVrpuuLwZY0++aamJ5Q0oH4OEhISgWbNmePrpp5GXl6e6z+VNH1vzTUtNK29lZWX44Ycf0KxZM/Tu3RshISHo3Lmzroo1lzfXhoVVFyc4OBj//ve/0bx5c4wcORLNmzdHYWEh/v73v6Np06aYPHkyPD09sW3bNgDAkiVL4Obmhk8++QRt2rRBbGwsFi1ahOzsbEVA9PX1RfPmzeHh4VHp6fHw8EDz5s3h6+urur5mzRrUrl0b3t7emDVrFtavX4+6desCAM6dOwdPT08EBQWpngkNDcW5c+cqLe5A+b7cSZMmYdCgQQgICFCuh4WFISoqSvl97tw5hIaGqp4Vv0WcTbm5efMmLly44KwkVAnW5pugW7du8Pb2RtOmTXHPPffgjTfeUO7VhHwzVx8ALm+msDXfBDW5vL3zzjuoVasWXnjhBZNuuLwZY0++CWpyeevbty+++uorbNy4Ee+99x52796Nnj17ori4WHHD5c0Ye/JNUFPLW15eHq5du4a3334bffr0wc8//4yHH34YjzzyCDZv3qy44/Lm+tSq6ggw5mnVqhXc3G7PKYSGhqJ169bKb3d3d9SpU0eZYUtLS8Px48fh7++v8ufGjRvIysoCAHTq1AlHjhyphNgbExERoRv2fffdh4yMDFy4cAEff/wxkpOTsXPnToSEhJj0i4hgMBicGV0VpaWl+Otf/4qysjLMmzdPdW/69OlG7rVxoz8358vXrXFT3bE13wBg6dKluHr1Kvbt24dXX30VM2fOxIQJE5T7d3q+WaoPXN70sSffgJpb3tLS0vDBBx9g7969ZtPC5U1NRfINqLnlDYDK5kXr1q3RsWNHREdH44cffsAjjzwCgMubHvbmG1Bzy1tZWRkAYMCAAXjxxRcBAO3atcP27dvx0UcfKSvMXN5cHxZWXRzt6qfBYNC9JiplWVkZ4uPj8dVXXxn5Va9ePedFtIL4+fmhSZMmaNKkCbp06YKmTZti4cKFmDx5MurXr4+SkhJcunRJtbqal5eHbt26VUr8SktLkZycjJMnT2Ljxo2q1UE96tevb7TqKyYUxGycKTe1atVyaUNbtmBrvgkaNGgAAGjZsiVu3bqFZ555Bi+//DLc3d1rRL6Zqw96cHkrx9Z8E9TU8vbrr78iLy9Ptapw69YtvPzyy5g9e7bJrSI1vbzZm2+Cmlre9AgLC0N0dDSOHTtm0k1NL296WJNvgppa3urWrYtatWqhZcuWquuxsbHYunWryee4vLkerAZ8h9GhQwccO3YMISEhyqBNfAIDA6s6elZDRIp6S3x8PDw8PLB+/Xrlfm5uLg4ePFgpwqoQuI4dO4YNGzZY1RB17doVW7ZsUfYJA8DPP/+M8PBwNGzYUHEjp0m46dixY5WoaDsae/JNDyJCaWmpMmt5p+ebHnJ90IPLmz6W8s3UMzWlvA0ZMgT79+9HRkaG8gkPD8err76KdevWmXyuppc3e/NNj5pU3vTIz8/H6dOnERYWZtJNTS9veliTb3rUpPLm6emJu+++G0ePHlVdz8zMRHR0tMnnuLy5IJVlyYm5ja3WgGUSEhJo/PjxqmuyFcLr169T06ZN6d5776UtW7bQiRMnaNOmTfTCCy/Q6dOniYho586d1Lx5czpz5oxN8T527Bilp6fT6NGjqVmzZpSenk7p6elUXFysuPnf//5H6enp1L9/f7r33nsVN4IzZ85Q8+bNaefOnUREdO3aNZo8eTLt2LGDTp06RWlpaTRq1Cjy8vKigwcPKs89++yzFBkZSRs2bKC9e/dSz549KS4ujm7evGlTGvS4evWqEk8A9P7771N6ejr9/vvvVFpaSklJSRQZGUkZGRmUm5urfOR0T5o0iYYMGaL8vnz5MoWGhtKTTz5JBw4coBUrVlBAQADNnDlTcXPixAny9fWlF198kQ4dOkQLFy4kDw8P+vbbbyucpsrAGfm2ePFiWrp0KR06dIiysrJo2bJlFBERQX/7298UN3dyvllbH7i8OSbfanp500PPqi2XN8fkW00vb1evXqWXX36Ztm/fTidPnqTU1FTq2rUrRURE0JUrVxQ/uLw5Jt9qenkjIlqxYgV5eHjQggUL6NixYzRnzhxyd3enX3/9VfGjJpa36gYLq1WAM4VVIqLc3FwaOnQo1a1bl7y8vKhx48b09NNPU0FBARERpaamEgCbj7NJSEggAEYf2Z/o6GhdN4KTJ08SAEpNTSUioqKiInr44YcpPDycPD09KSwsjJKSkmjXrl2qsIuKimjs2LEUHBxMPj4+1K9fP8rOzrYp/qYQ+aH9DBs2TImv3kekgaj8XSUkJKj83b9/P91zzz3k5eVF9evXp6lTpypmzwWbNm2i9u3bk6enJzVs2JA+/PBDh6SpMnBGvi1ZsoQ6dOhAtWvXJj8/P2rZsiW99dZbVFRUpAr7Ts03a+sDlzfH5FtNL2966AldXN4ck281vbwVFhZSYmIi1atXjzw8PCgqKoqGDRtm1JdzeXNMvtX08iZYuHAhNWnShLy9vSkuLo5WrVql8qMmlrfqhoHoT10AhmEYhmEYhmEYhnEReM8qwzAMwzAMwzAM43KwsMowDMMwDMMwDMO4HCysMgzDMAzDMAzDMC4HC6sMwzAMwzAMwzCMy8HCKsMwDMMwDMMwDONysLDqAgwfPhwDBw60+/nPPvsMd911l8PiYjAYjD6tWrVShafn5saNG2b9JiLMnDkTzZo1g5eXFxo0aIC33npLub9p0yZdf48cOeKQtFli6tSpaNGiBfz8/BAUFIRevXph586dKjdZWVl4+OGHUa9ePQQEBCA5ORnnz5836+/Nmzfx2muvoVGjRvDx8UHjxo3xxhtvoKysDABQWlqKiRMnok2bNvDz80N4eDiGDh2Ks2fPOi2tjsLWuBMR+vbtC4PBgFWrVpn1u2HDhrrl4fnnn7crbFfAUlkAoJtmg8GAd99916S///vf//Doo48qeTZ79myz8Zg+fToMBgNSUlIclLLKwZZ3vmPHDvTs2RN+fn646667cO+996KoqMik39a8G2vaCFfFUtxPnTplsux98803Jv21VE8BYMWKFejduzfq1q0Lg8GAjIwMZya1wlhKkz119N5779V95qGHHlLcbNmyBf3790d4eLhVbaSrYs37Hj16NGJiYuDj44N69ephwIABFvv6O72O6o2/unTponJTXFyMcePGoW7duvDz80NSUhLOnDlj0e+cnBwMHjwYderUga+vL9q1a4e0tDTl/rVr1zB27FhERkbCx8cHsbGx+PDDDx2eRkdjKV0yo0ePtqp/tKauWlMWGcfBwiqj4oMPPkBubq7yOX36NIKDg/H444+r3AUEBKjc5ebmwtvb26zf48ePxyeffIKZM2fiyJEj+P7779GpUycjd0ePHlX527RpU4em0RTNmjXD3LlzceDAAWzduhUNGzZEYmIi/vjjDwDA9evXkZiYCIPBgI0bN2Lbtm0oKSlB//79zTZQ77zzDj766CPMnTsXhw8fxowZM/Duu+9izpw5AIDCwkLs3bsXr7/+Ovbu3YsVK1YgMzMTSUlJlZLuimBr3GfPng2DwWCV37t371aVg/Xr1wOAUharY75ZKgsAjOrVp59+CoPBgEcffdSkv4WFhWjcuDHefvtt1K9f32wcdu/ejQULFqBt27YOS1dlYe0737FjB/r06YPExETs2rULu3fvxtixY+HmZrrLs+bdWGojXBlLcW/QoIFR2Zs2bRr8/PzQt29fk/5aqqdAedvZvXt3vP32285NpIOwlCZ76uiKFStUzxw8eBDu7u5G+RQXF4e5c+c6N4FOxpr3HR8fj0WLFuHw4cNYt24diAiJiYm4deuWyWfu9DoKAH369FGVkx9//FF1PyUlBStXrsSSJUuwdetWXLt2Df369TObb5cuXUL37t3h4eGBn376CYcOHcJ7772nWuR48cUXsXbtWixevBiHDx/Giy++iHHjxuG7775zVlIrjDXpEqxatQo7d+5EeHi4RX+tqavWlEXGgVTpKa8MEZUfSDxgwACT99977z1q3bo1+fr6UmRkJI0ZM4auXr1KRPoHIk+ZMsVhcVu5ciUZDAY6deqUcm3RokUUGBhokz+HDh2iWrVq0ZEjR0y6EWm5dOmSnbF1LAUFBQSANmzYQERE69atIzc3NyooKFDcXLx4kQDQ+vXrTfrz0EMP0ciRI1XXHnnkERo8eLDJZ3bt2kUA6Pfff69gKiofU3HPyMigyMhIys3NJQC0cuVKm/wdP348xcTEGB3MbU3YroI9ZWHAgAHUs2dPq8OIjo6mWbNm6d67evUqNW3alNavX08JCQk0fvx4q/11VfTeeefOnem1116zyR973o22jahOWBP3du3aGeWJJczV05MnTxIASk9PtzW6VYqltsfWOkpENGvWLPL396dr167p3renjXQ1bHnf+/btIwB0/Phxk27u9DpqaSx4+fJl8vDwoCVLlijXcnJyyM3NjdauXWvyuYkTJ1KPHj3Mht2qVSt64403VNc6dOhgcztamViTLiKiM2fOUEREBB08eNBs/2gKvbpqT1lk7IdXVqsBbm5u+Pe//42DBw/i888/x8aNGzFhwgQAQLdu3TB79mzVSucrr7wCoFwdpmHDhhUKe+HChejVqxeio6NV169du4bo6GhERkaiX79+SE9PN+vP999/j8aNG2PNmjVo1KgRGjZsiKeeegoXL140ctu+fXuEhYXh/vvvR2pqaoXiby8lJSVYsGABAgMDERcXB6Bc/cZgMMDLy0tx5+3tDTc3N2zdutWkXz169MAvv/yCzMxMAMC+ffuwdetWPPjggyafKSgogMFgcJh6d2WiF/fCwkI8+eSTmDt3rsWVPz1KSkqwePFijBw50uzKrKvnm61l4fz58/jhhx8watQoh4T//PPP46GHHkKvXr0c4p8roH3neXl52LlzJ0JCQtCtWzeEhoYiISHBbB0FbH83em1EdcGauKelpSEjI8OmsmdtPa1OWEqTvXV04cKF+Otf/wo/Pz9HRbXacv36dSxatAiNGjVCgwYNTLqrCXV006ZNCAkJQbNmzfD0008jLy9PuZeWlobS0lIkJiYq18LDw9G6dWts377dpJ+rV69Gx44d8fjjjyMkJATt27fHxx9/rHLTo0cPrF69Gjk5OSAipKamIjMzE71793Z8Ih2ENekqKyvDkCFD8Oqrr6q2s9mCXl21Z1zHVICqlpYZy7NpWpYtW0Z16tRRfpta6ZwzZ47Ns70yZ8+eJXd3d1q6dKnq+o4dO+jLL7+kjIwM2rJlCz366KPk4+NDmZmZJv0aPXo0eXl5UefOnWnLli2UmppK7dq1o/vuu09xc+TIEVqwYAGlpaXR9u3bacyYMWQwGGjz5s12p8FWvv/+e/Lz8yODwUDh4eG0a9cu5V5eXh4FBATQ+PHj6fr163Tt2jV6/vnnCQA988wzJv0sKyujSZMmkcFgoFq1apHBYKC33nrLpPuioiKKj4+nv/3tbw5NW2VgKu7PPPMMjRo1SvkNG1cNli5dSu7u7pSTk2Nz2K6ErWXhnXfeoaCgICoqKrI6DFMzx//973+pdevWil93wsqq3jvfsWMHAaDg4GD69NNPae/evZSSkkKenp5m2yhr3425NsLVsSXuY8aModjYWJv8t1RPq+PKqqU02VNHd+7cSQBo586dJt3Y2ka6Ipbe93/+8x/y8/MjANSiRQuzq6pEd34dXbJkCa1Zs4YOHDhAq1evpri4OGrVqhXduHGDiIi++uor8vT0NHrugQceMDsG8fLyIi8vL5o8eTLt3buXPvroI/L29qbPP/9ccVNcXExDhw4lAFSrVi3y9PSkL774wvGJdCDWpOutt96iBx54QNGKsHVl1VRdtbUvZyoGC6sugCVhdePGjdSrVy8KDw+n2rVrk7e3NwFQVBLsUcu1hrfeeovq1KlDxcXFZt3dunWL4uLiaNy4cSbdPP300wSAjh49qlxLS0sjAGZVg/v160f9+/e3PfIWWLx4Mfn5+SmfLVu2EBHRtWvX6NixY7Rjxw4aOXIkNWzYkM6fP688t27dOmrcuDEZDAZyd3enwYMHU4cOHWjMmDEmw/rvf/9LkZGR9N///pf2799PX3zxBQUHB9Nnn31m5LakpIQGDBhA7du3V6kbuwqm8o3IdNy/++47atKkiaK6TmT7QCwxMZH69etn8r6r55vAlrJARNS8eXMaO3asTWHodcbZ2dkUEhJCGRkZyrXqIKzaU962bdtGAGjy5Mkqv9q0aUOTJk0yGZa178ZSG+EK2Nu+CQoLCykwMJBmzpxpU7iW6ml1FFYtpcmeOvrMM89Q69atzbqpLsKquTpq6X1fvnyZMjMzafPmzdS/f3/q0KGDWaG/JtRRmbNnz5KHhwctX76ciEwLq7169aLRo0ebDMvDw4O6du2qujZu3Djq0qWL8vvdd9+lZs2a0erVq2nfvn00Z84cql27ttktTlWNpXTt2bOHQkNDVRNNtgqrpuqqrX05UzFYWHUBzAmrp06dIm9vb0pJSaEdO3bQ0aNHaeHChaq9nc4QVsvKyqhJkyaUkpJilfunnnqK+vTpY/L+//3f/1GtWrVU1woLCwkA/fzzzyaf+9e//kUtWrSwLtI2cOXKFTp27JjyKSws1HXXpEkT3dmyP/74Q8n/0NBQmjFjhsmwIiMjae7cuapr//znP6l58+aqayUlJTRw4EBq27YtXbhwwcYUVQ6m8s1c3MePH68I9+IDgNzc3CghIcFimKdOnSI3NzdatWqV7v3qkG8Ca8sCEdGWLVsIgErAtAa9znjlypUEwOgdiPdy8+ZNm9NSGdhT3k6cOEEA6Msvv1RdT05OpkGDBpkMy5Z3I2OqjahKKtq+ffHFF+Th4UF5eXlWh2mpnhJVP2HVUprsqaPXr1+ngIAAmj17tll31UVYNVfWbHnfxcXF5OvrS19//bVJNzW1jr799ttERPTLL78QALp48aLKTdu2ben//u//TIYVFRWl0mwiIpo3bx6Fh4cTUflYzMPDg9asWaNyM2rUKOrdu7fNaassLKVr1qxZJsce0dHRFv03V1ftLYuMfdSqBE1jpgLs2bMHN2/exHvvvadYsly2bJnKjaenp1lLcPawefNmHD9+3Kp9OESEjIwMtGnTxqSb7t274+bNm8jKykJMTAwAKLr+2v2wMunp6QgLC7Mx9pbx9/eHv7+/RXdEhOLiYqPrdevWBQBs3LgReXl5Zi3QFhYWGlkhdXd3V1kQLi0tRXJyMo4dO4bU1FTUqVPH2qRUKnr5ZinukyZNwlNPPaW61qZNG8yaNQv9+/e3GOaiRYsQEhKiMhtvbdiuhjVlQbBw4ULEx8c7ZK/V/fffjwMHDqiujRgxAi1atMDEiRPh7u5e4TCcgT3lrWHDhggPD8fRo0dV1zMzM81atbXl3ciYaiOqkoq2bwsXLkRSUhLq1atndZjm6ml1xVKa7Kmjy5YtQ3FxMQYPHuyoaFYp1pY1a7BUl2paHc3Pz8fp06eVMVB8fDw8PDywfv16JCcnA4BirXbGjBkm/enevbtueyjGXqWlpSgtLbUrb6sSS+kaMmSIkX2G3r17Y8iQIRgxYoRF/83VVXvLImMnVSkpM+UMGzaM7r33XkpPT1d9fv/9d0pPTycANHv2bMrKyqIvvviCIiIiVCurQu1tw4YN9Mcff9D169eJqGJ7VgcPHkydO3fWvTd16lRau3YtZWVlUXp6Oo0YMYJq1aql0unXhn3r1i3q0KED/eUvf6G9e/fSnj17qHPnzvTAAw8obmbNmkUrV66kzMxMOnjwIE2aNIkAKCowzuTatWs0efJk2rFjB506dYrS0tJo1KhR5OXlRQcPHlTcffrpp7Rjxw46fvw4ffnllxQcHEwvvfSSyq+ePXvSnDlzlN/Dhg2jiIgIWrNmDZ08eZJWrFhBdevWpQkTJhARUWlpKSUlJVFkZCRlZGRQbm6u8rGkgl3V2Bt36KwaaPONqLzcREVF0cSJEx0WdlViqSwICgoKyNfXlz788ENdf4YMGaJSaS0uLlbajbCwMHrllVcoPT2djh07ZjIu1UENWIu173zWrFkUEBBA33zzDR07doxee+018vb2Vu2Js7WeWttGuCK2xP3YsWNkMBjop59+0vXL1npKRJSfn0/p6en0ww8/EABasmQJpaenU25urmMS6AQspcnWOiro0aMHPfHEE7rPXL16VanHAOj9999XxgLVCUvvOysri9566y3as2cP/f7777R9+3YaMGAABQcHq9R1a1IdvXr1Kr388su0fft2OnnyJKWmplLXrl0pIiKCrly5orh79tlnKTIykjZs2EB79+6lnj17UlxcnEo7Rptvu3btolq1atGbb75Jx44do6+++op8fX1p8eLFipuEhARq1aoVpaam0okTJ2jRokXk7e1N8+bNq5wMsANr0qVFT/PInrpqbV/OOAYWVl2AYcOGGR0/A4CGDRtGRETvv/8+hYWFkY+PD/Xu3Zu++OILoyNenn32WapTp47q6JopU6ZYpeqg5fLly+Tj40MLFizQvZ+SkkJRUVHk6elJ9erVo8TERNq+fbvKjV7YOTk59Mgjj1Dt2rUpNDSUhg8fTvn5+cr9d955h2JiYsjb25uCgoKoR48e9MMPP9gcf3soKiqihx9+mMLDw8nT05PCwsIoKSnJyDDDxIkTKTQ0lDw8PKhp06b03nvvGR1nEB0drTo+6MqVKzR+/HiKiooib29vaty4Mf3jH/9QBtdCVUrvk5qa6uykVwh7464nrGrzjah8jzA0e50rGnZVYqksCObPn08+Pj50+fJlXX8SEhKU9oHIdF6YU7OujsKqLe98+vTpFBkZSb6+vtS1a1f69ddfVfdtrafWthGuiC1xnzx5MkVGRtKtW7d0/bK1nhKVb1XRe2eOPGbN0VhKk611lIjo6NGjZre+6B1FJ48FqguW3ndOTg717duXQkJCyMPDgyIjI2nQoEFG9itqUh0tLCykxMREqlevHnl4eFBUVBQNGzaMsrOzVe6Kiopo7NixFBwcTD4+PtSvXz8jN3p19Pvvv6fWrVuTl5cXtWjRwmh8l5ubS8OHD6fw8HDy9vam5s2b645vXA1L6dKiJ6zaU1et7csZx2AgIqrw8izDMAzDMAzDMAzDOBA+Z5VhGIZhGIZhGIZxOVhYZRiGYRiGYRiGYVwOFlYZhmEYhmEYhmEYl4OFVYZhGIZhGIZhGMblYGGVYRiGYRiGYRiGcTlYWHURhg8fjoEDB1Z1NHDu3DkMGTIE9evXh5+fHzp06IBvv/1W5SYzMxMDBgxA3bp1ERAQgO7duyM1NdWsvytWrEDv3r1Rt25dGAwGZGRkGLkZPXo0YmJi4OPjg3r16mHAgAE4cuSII5Ony9WrV5GSkoLo6Gj4+PigW7du2L17t3J/6tSpaNGiBfz8/BAUFIRevXph586dZv38+OOPcc899yAoKEh5ZteuXSo3DRs2hMFgMPo8//zzTklnZXH+/HkMHz4c4eHh8PX1RZ8+fXDs2DHl/qlTp3TTbTAY8M0335j0907NL1vTtWnTJl33cl0pLS3FG2+8gZiYGHh7eyMuLg5r166trCQ5hZycHAwePBh16tSBr68v2rVrh7S0NOW+pXJnitmzZ6N58+bw8fFBgwYN8OKLL+LGjRvK/enTp+Puu++Gv78/QkJCMHDgQKOD6F0NS+3txYsXMW7cODRv3hy+vr6IiorCCy+8gIKCApW7N998E926dYOvry/uuusuh4QNAAsWLMC9996LgIAAGAwGXL582b6EOhhHx724uBjt2rUz6ZegtLQUEydORJs2beDn54fw8HAMHToUZ8+eVbmzpn92JaZPnw6DwYCUlBTV9cOHDyMpKQmBgYHw9/dHly5dkJ2dbdKfzz77TLfNk+upNeG6GtaUNwERoW/fvjAYDFi1apWuG2vLGwBcu3YNY8eORWRkJHx8fBAbG4sPP/xQ5SYrKwsPP/ww6tWrh4CAACQnJ+P8+fM2ptLxOCrfkpKSEBUVBW9vb4SFhWHIkCFGdU7L8OHDjcphly5dVG5ctX2rzrCwyqgYMmQIjh49itWrV+PAgQN45JFH8MQTTyA9PV1x89BDD+HmzZvYuHEj0tLS0K5dO/Tr1w/nzp0z6e/169fRvXt3vP322ybdxMfHY9GiRTh8+DDWrVsHIkJiYiJu3brl0DRqeeqpp7B+/Xp8+eWXOHDgABITE9GrVy/k5OQAAJo1a4a5c+fiwIED2Lp1Kxo2bIjExET88ccfJv3ctGkTnnzySaSmpmLHjh2IiopCYmKi4icA7N69G7m5ucpn/fr1AIDHH3/cqel1JkSEgQMH4sSJE/juu++Qnp6O6Oho9OrVC9evXwcANGjQQJXu3NxcTJs2DX5+fujbt69Jv+/E/ALsT9fRo0dVzzVt2lS599prr2H+/PmYM2cODh06hGeffRYPP/ywqh5XJy5duoTu3bvDw8MDP/30Ew4dOoT33ntPEaCsKXd6fPXVV5g0aRKmTJmCw4cPY+HChVi6dCkmT56suNm8eTOef/55/Pbbb1i/fj1u3ryJxMREs/5WNZba27Nnz+Ls2bOYOXMmDhw4gM8++wxr167FqFGjVO5KSkrw+OOPY8yYMQ4LGwAKCwvRp08f/P3vf7fa38rA0XGfMGECwsPDLborLCzE3r178frrr2Pv3r1YsWIFMjMzkZSUpHJnTf/sKuzevRsLFixA27ZtVdezsrLQo0cPtGjRAps2bcK+ffvw+uuvw9vb26x/AQEBRv2G3jOmwnVFrClvgtmzZ8NgMJh1Y215A4AXX3wRa9euxeLFi3H48GG8+OKLGDduHL777jslbomJiTAYDNi4cSO2bduGkpIS9O/fH2VlZVaF4SwclW/33Xcfli1bhqNHj2L58uXIysrCY489ZtHPPn36qMrhjz/+qLrvqu1btaYKz3hlJIYNG0YDBgwweX/Tpk109913k6enJ9WvX58mTpxIpaWlyv2EhAQaN24cvfrqqxQUFEShoaF2Hbju5+dHX3zxhepacHAwffLJJ0RE9McffxAA2rJli3L/ypUrBIA2bNhg0f+TJ08SAEpPT7fodt++fQSAjh8/blsibKCwsJDc3d1pzZo1qutxcXH0j3/8Q/eZgoICq9MruHnzJvn7+9Pnn39u0s348eMpJibG5Q/hNoc4SPvgwYPKtZs3b1JwcDB9/PHHJp9r164djRw50qaw7oT80sNSulJTUwkAXbp0yaQfYWFhNHfuXNW1AQMG0N/+9jdHRrXSmDhxIvXo0cPkfXvL3fPPP089e/ZUXXvppZfMhpWXl0cAaPPmzTakoGqwpb1dtmwZeXp6qvoVwaJFiygwMNDhYVtTlqsCR8T9xx9/pBYtWtD//vc/q9+BzK5duwgA/f7778o1S/2zq3D16lVq2rQprV+/nhISEmj8+PHKvSeeeIIGDx5sk3/Wlj9z4boylspbRkYGRUZGUm5uLgGglStXGrmxtby1atWK3njjDdW1Dh060GuvvUZEROvWrSM3NzcqKChQ7l+8eJEA0Pr1621Kn7NwRL7JfPfdd2QwGKikpMSkG0tjdRlXbd+qI7yyWg3IycnBgw8+iLvvvhv79u3Dhx9+iIULF+Jf//qXyt3nn38OPz8/7Ny5EzNmzMAbb7yhrNIA5eoL9957r9mwevTogaVLl+LixYsoKyvDkiVLUFxcrDxXp04dxMbG4osvvsD169dx8+ZNzJ8/H6GhoYiPj3dYmq9fv45FixahUaNGaNCggcP81XLz5k3cunXLaIbWx8cHW7duNXJfUlKCBQsWIDAwEHFxcVaHU1hYiNLSUgQHB+veLykpweLFizFy5EiLs6euTHFxMQCo8tPd3R2enp66+QkAaWlpyMjIMFrVMcedkl9abElX+/btERYWhvvvv99IDb+4uNjqMl0dWL16NTp27IjHH38cISEhaN++PT7++GPlvj3lDihv79LS0hQV/RMnTuDHH3/EQw89ZPIZoSprqi5XVwoKChAQEIBatWpVdVSqPefPn8fTTz+NL7/8Er6+vnb5UVBQAIPBoFK/ttQ/uwrPP/88HnroIfTq1Ut1vaysDD/88AOaNWuG3r17IyQkBJ07dzap1ipz7do1REdHIzIyEv369dNdTTYVbnWmsLAQTz75JObOnYv69evrurGnvPXo0QOrV69GTk4OiAipqanIzMxE7969AZS3qQaDAV5eXsoz3t7ecHNzqxb9iDX5JnPx4kV89dVX6NatGzw8PMy63bRpE0JCQtCsWTM8/fTTyMvLc1S0GVNUtbTMlGNutubvf/87NW/eXLXS8p///Idq165Nt27dIqLylVXtasDdd99NEydOVH5PmjSJhgwZYjYely9fpt69exMAqlWrFgUEBNDPP/+scnPmzBmKj48ng8FA7u7uFB4ebvWssaWZsP/85z/k5+dHAKhFixZOXVUVdO3alRISEignJ4du3rxJX375JRkMBmrWrJni5vvvvyc/Pz8yGAwUHh5Ou3btsimM5557jmJiYqioqEj3/tKlS8nd3Z1ycnIqlJaqpqSkhKKjo+nxxx+nixcvUnFxMU2fPp0AUGJiou4zY8aModjYWJvCuVPyS4s16Tpy5AgtWLCA0tLSaPv27TRmzBgyGAyqlb4nn3ySWrZsSZmZmXTr1i36+eefycfHhzw9PSsjGQ7Hy8uLvLy8aPLkybR371766KOPyNvbW9FUsKfcCf7973+Th4cH1apViwDQmDFjTLotKyuj/v37m115dSWsXVm9cOECRUVFmdQm4ZVVY0zFvaysjPr06UP//Oc/rfZLS1FREcXHxxtpQljTP1c1//3vf6l169ZKXyevcIoVLl9fX3r//fcpPT2dpk+fTgaDgTZt2mTSzx07dtCXX35JGRkZtGXLFnr00UfJx8eHMjMzrQrX1TFXRp555hkaNWqU8huaFUJ7y1txcTENHTpUKUuenp6qVfu8vDwKCAig8ePH0/Xr1+natWv0/PPPEwB65plnKpReR1GRfBNMmDCBfH19CQB16dKFLly4YDbMJUuW0Jo1a+jAgQO0evVqiouLo1atWtGNGzeM3Lpq+1YdYWHVRTAnrD788MM0fPhw1bWMjAyVilBCQgI999xzKjdJSUk0YsQIm+IxduxY6tSpE23YsIEyMjJo6tSpFBgYSPv37yei8oYxKSmJ+vbtS1u3bqW0tDQaM2YMRURE0NmzZy36b6khvXz5MmVmZtLmzZupf//+1KFDB5MCnqM4fvw4/eUvfyEA5O7uTnfffTf97W9/UwlQ165do2PHjtGOHTto5MiR1LBhQzp//rxV/r/zzjsUFBRE+/btM+kmMTGR+vXrV+G0VDaLFy8mPz8/5bNlyxbas2cPxcXFKfnZu3dv6tu3L/Xt29fo+cLCQgoMDKSZM2faFG51zS9L2Juufv36Uf/+/ZXfeXl5NGDAAHJzcyN3d3dq1qwZPffcc+Tj4+PI6FYaHh4e1LVrV9W1cePGUZcuXZTftpQ7QWpqKoWGhtLHH39M+/fvpxUrVlCDBg2M1OMEzz33HEVHR9Pp06cdkzAHoFcHBdYMXAsKCqhz587Up08fk+pvd6KwWtF8MxX3Dz74gLp160Y3b9602i+ZkpISGjBgALVv316lgklkuX+uarKzsykkJIQyMjKUa7LQmJOTQwDoySefVD3Xv39/+utf/2p1OLdu3aK4uDgaN26cVeG6AvaUt++++46aNGlCV69eVa5phS57y9u7775LzZo1o9WrV9O+fftozpw5VLt2bZWK77p166hx48bKwsTgwYOpQ4cOZif0HI2z8k3wxx9/0NGjR+nnn3+m7t2704MPPmjT1qKzZ8+Sh4cHLV++3OgeC6uOg4VVF8GcsDpw4EAjoTM9PZ0AUHZ2NhHpN8wDBgygYcOGWR2H48ePG+37IiK6//77afTo0UREtGHDBqN9DERETZo0oenTp1sMw5aOu7i4mHx9fenrr7+2Og0V4dq1a4rAnZycTA8++KBJt02aNKG33nrLop/vvvsuBQYG0u7du026OXXqFLm5udGqVatsj3QVc+XKFTp27JjyKSwsVO5dvnyZ8vLyiIioU6dORpMpRERffPEFeXh4KO6soTrnlzkqkq5//etf1KJFC6PrRUVFdObMGSorK6MJEyZQy5YtHRHVSicqKko1S05ENG/ePAoPDzdya025E/To0YNeeeUV1bUvv/ySfHx8FK0VwdixYykyMpJOnDhhbzKcgrk6aKm9vXLlCnXt2pXuv/9+s5OCd6KwWpF8IzIdd3mSSHzEBMrQoUPNxqmkpIQGDhxIbdu2NVrhsaZ/rmpWrlyppFVOuxB2bty4QbVq1VJWAQUTJkygbt262RTWU089RX369LEqXCHIVSX2lLfx48craZDT5ebmRgkJCURkX3krLCwkDw8PI1sdo0aNot69exu5/+OPP5RyHhoaSjNmzLA/I2zEWfmmx+nTpwkAbd++3aY4NmnShN5++22j6yysOg7enFINaNmyJZYvXw4iUvaxbd++Hf7+/oiIiHBYOIWFhQAANzf1VmZ3d3fF+pspN25ubk6xEEdEyn40Z+Pn5wc/Pz9cunQJ69atw4wZMyoUr3fffRf/+te/sG7dOnTs2NGku0WLFiEkJMTsPjlXxd/fH/7+/rr3AgMDAQDHjh3Dnj178M9//tPIzcKFC5GUlIR69epZHWZ1zi9zVCRd6enpCAsLM7ru7e2NiIgIlJaWYvny5UhOTnZEVCud7t27Gx0Xk5mZiejoaCO31pQ7QWFhoW57R+UTuQDK6/q4ceOwcuVKbNq0CY0aNapochyKuTpojitXrqB3797w8vLC6tWrLVpjvdOwN98s8e9//1tlT+Ls2bPo3bs3li5dis6dO5t8rrS0FMnJyTh27BhSU1NRp04d1X1r+ueq5v7778eBAwdU10aMGIEWLVpg4sSJ8PLywt133211XTYFESEjIwNt2rSxKlx3d3c7U+Q47ClvkyZNwlNPPaW61qZNG8yaNQv9+/cHYF95Ky0tRWlpqdVlqW7dugCAjRs3Ii8vz8hKtTNxVr7pIdp8W8ac+fn5OH36tG7/yziQqpOTGZlhw4bRvffeS+np6arP77//TmfOnCFfX196/vnn6fDhw7Rq1SqqW7euytqvNSurlvaslpSUUJMmTeiee+6hnTt30vHjx2nmzJlkMBjohx9+IKLyGbY6derQI488QhkZGXT06FF65ZVXyMPDQ6WC07x5c1qxYoXyOz8/n9LT0+mHH34gALRkyRJKT0+n3NxcIiLKysqit956i/bs2UO///47bd++nQYMGEDBwcFWq9vay9q1a+mnn36iEydO0M8//0xxcXHUqVMnKikpoWvXrtHkyZNpx44ddOrUKUpLS6NRo0aRl5eXaoZ7yJAhNGnSJOX3O++8Q56envTtt99Sbm6u8pHVUojK1ZmioqJUe4urO8uWLaPU1FTKysqiVatWUXR0ND3yyCNG7o4dO0YGg4F++uknXX969uxJc+bMUV27E/OLyHy6tPV21qxZtHLlSsrMzKSDBw/SpEmTCIBKDem3336j5cuXU1ZWFm3ZsoV69uxJjRo1qrYzvLt27aJatWrRm2++SceOHaOvvvqKfH19afHixYoba8qdtp5OmTKF/P396b///a9S/2NiYig5OVlxM2bMGAoMDKRNmzap6rI8w+9qWGpvr1y5Qp07d6Y2bdrQ8ePHVemSV6F+//13Sk9Pp2nTplHt2rWVfklux2xt64nK9y6mp6fTxx9/rFiXT09Pp/z8/ErIHdM4I+6mVn/kfCstLaWkpCSKjIykjIwM1fsoLi4mIuv6Z1dEOzZZsWIFeXh40IIFC+jYsWM0Z84ccnd3p19//VVxo62nU6dOpbVr11JWVhalp6fTiBEjqFatWrRz506rw3VFrClvWmDBqq015Y2oPH9atWpFqampdOLECVq0aBF5e3vTvHnzFDeffvop7dixg44fP05ffvklBQcH00svvWR3eh2FI/Jt586dNGfOHEpPT6dTp07Rxo0bqUePHhQTE6Pafyrn29WrV+nll1+m7du308mTJyk1NZW6du1KERERdOXKFeUZV23fqjMsrLoIw4YNIwBGHyFsWnN0jSVhddiwYWZVIIiIMjMz6ZFHHqGQkBDy9fWltm3bGpnK3717NyUmJlJwcDD5+/tTly5d6Mcff1S5AUCLFi1Sfi9atEg3fULgzsnJob59+1JISAh5eHhQZGQkDRo0iI4cOWJV/lWEpUuXUuPGjZW8ff755+ny5ctEVK5G+fDDD1N4eDh5enpSWFgYJSUlGRlYSkhIUOV1dHS02fQK1q1bRwDo6NGjzk5mpfHBBx9QZGQkeXh4UFRUFL322mvKgEtm8uTJFBkZaaRuKYiOjq4R+UVkPl3aevvOO+9QTEwMeXt7U1BQEPXo0cNosLpp0yaKjY0lLy8vqlOnDg0ZMqTaG6P6/vvvqXXr1uTl5UUtWrSgBQsWqO5bU+609bS0tJSmTp2q5GeDBg3oueeeUwn1evVY2765GpbaW6Gepvc5efKk4o+pfik1NVVxY2tbT1Q+SeCKeeqMuJsSHuRnhBtLeW1N/+xq6I1NFi5cSE2aNCFvb2+Ki4sz2vqgracpKSkUFRVFnp6eVK9ePUpMTLSoqlkdhFVrypsWe4VVbRnNzc2l4cOHU3h4OHl7e1Pz5s3pvffeU+3XnDhxIoWGhpKHhwc1bdrU6H5V4Yh8279/P913330UHBxMXl5e1LBhQ3r22WfpzJkzRs+JfCssLKTExESqV6+e0s8MGzZM2Y4ncNX2rTpjIPpz3ZthGIZhGIZhGIZhXAQ+Z5VhGIZhGIZhGIZxOVhYZRiGYRiGYRiGYVwOFlYZhmEYhmEYhmEYl4OFVYZhGIZhGIZhGMblYGGVYRiGYRiGYRiGcTlYWGUYhmEYhmEYhmFcDhZWGYZhGIZhGIZhGJeDhVWGYRiGYRiGYRjG5WBhlWEYhmEYhmEYhnE5WFhlGIZhGIZhGIZhXA4WVhmGYRiGYRiGYRiXg4VVhmEYhmEYhmEYxuX4f2+ghEALVEAXAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 1000x700 with 8 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(nrows=4, sharex=True, figsize=(10, 7))\n",
"# Plot velocities with left axis\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Vixv\", ax=axes[0], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Vixh\", ax=axes[1], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Viy\", ax=axes[2], s=1, linewidths=0)\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Viz\", ax=axes[3], s=1, linewidths=0, label=\"Velocities\")\n",
"# Plot velocities with right axis\n",
"axes_r = [ax.twinx() for ax in axes]\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Vixv_error\", ax=axes_r[0], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Vixh_error\", ax=axes_r[1], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Viy_error\", ax=axes_r[2], s=0.1, color=\"tab:orange\")\n",
"ds.plot.scatter(x=\"Timestamp\", y=\"Viz_error\", ax=axes_r[3], s=0.1, color=\"tab:orange\")\n",
"fig.subplots_adjust(hspace=0)\n",
"# Add legend to identify each side\n",
"blue = mpl.patches.Patch(color=\"tab:blue\", label=\"Velocities\")\n",
"orange = mpl.patches.Patch(color=\"tab:orange\", label=\"Errors\")\n",
"axes[0].legend(handles=[blue, orange])\n",
"# # Generate additional ticklabels for x-axis\n",
"# Use time xticks to get dataset vars at those xticks\n",
"locx = axes[-1].get_xticks()\n",
"times = mpl.dates.num2date(locx)\n",
"times = [t.replace(tzinfo=None) for t in times]\n",
"_ds_xticks = ds.reindex({\"Timestamp\": times}, method=\"nearest\")\n",
"# Build ticklabels from dataset vars\n",
"xticklabels = np.stack([\n",
" _ds_xticks[\"Timestamp\"].dt.strftime(\"%H:%M\").values,\n",
" np.round(_ds_xticks[\"Latitude\"].values, 2).astype(str),\n",
" np.round(_ds_xticks[\"Longitude\"].values, 2).astype(str),\n",
"])\n",
"xticklabels = [\"\\n\".join(row) for row in xticklabels.T]\n",
"# Add labels to first xtick\n",
"_xt0 = xticklabels[0].split(\"\\n\")\n",
"xticklabels[0] = f\"Time: {_xt0[0]}\\nLat: {_xt0[1]}\\nLon: {_xt0[2]}\"\n",
"axes[-1].set_xticks(axes[-1].get_xticks())\n",
"axes[-1].set_xticklabels(xticklabels)\n",
"axes[-1].set_xlabel(\"\")\n",
"# Adjust title\n",
"title = \"\".join([\n",
" f\"Swarm {ds['Spacecraft'].data[0]} 2Hz ion flow, \",\n",
" ds[\"Timestamp\"].dt.date.data[0].isoformat(),\n",
" f\"\\n{ds.attrs['Sources']}\"\n",
"])\n",
"fig.suptitle(title);"
]
},
{
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"id": "1ee742b6-03b4-4cae-b5b9-514f554dea82",
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]
},
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"id": "9606d8db-d884-4291-9a43-293eb4520986",
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"source": [
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]
}
],
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