{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "
\n", "\n", "**This is a fixed-text formatted version of a Jupyter notebook**\n", "\n", "- Try online [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gammapy/gammapy-webpage/v0.13?urlpath=lab/tree/cta_data_analysis.ipynb)\n", "- You can contribute with your own notebooks in this\n", "[GitHub repository](https://github.com/gammapy/gammapy/tree/master/tutorials).\n", "- **Source files:**\n", "[cta_data_analysis.ipynb](../_static/notebooks/cta_data_analysis.ipynb) |\n", "[cta_data_analysis.py](../_static/notebooks/cta_data_analysis.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![CTA first data challenge logo](images/cta-1dc.png)\n", "\n", "# CTA data analysis with Gammapy\n", "\n", "## Introduction\n", "\n", "**This notebook shows an example how to make a sky image and spectrum for simulated CTA data with Gammapy.**\n", "\n", "The dataset we will use is three observation runs on the Galactic center. This is a tiny (and thus quick to process and play with and learn) subset of the simulated CTA dataset that was produced for the first data challenge in August 2017.\n", "\n", "**This notebook can be considered part 2 of the introduction to CTA 1DC analysis. Part one is here: [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb)**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setup\n", "\n", "As usual, we'll start with some setup ..." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\r\n", "Gammapy package:\r\n", "\r\n", "\tpath : /Users/adonath/github/adonath/gammapy/gammapy \r\n", "\tversion : 0.13 \r\n", "\r\n", "\r\n", "Other packages:\r\n", "\r\n", "\tnumpy : 1.15.0 \r\n", "\tscipy : 1.3.0 \r\n", "\tmatplotlib : 3.1.1 \r\n", "\tcython : 0.29.12 \r\n", "\tastropy : 3.2.1 \r\n", "\tastropy_healpix : 0.4 \r\n", "\treproject : 0.4 \r\n", "\tsherpa : 4.11.0 \r\n", "\tpytest : 5.0.1 \r\n", "\tsphinx : 1.8.5 \r\n", "\thealpy : 1.12.9 \r\n", "\tregions : 0.4 \r\n", "\timinuit : 1.3.7 \r\n", "\tnaima : 0.8.3 \r\n", "\tuncertainties : 3.1.1 \r\n", "\r\n" ] } ], "source": [ "!gammapy info --no-envvar --no-system" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "from astropy.convolution import Gaussian2DKernel\n", "from regions import CircleSkyRegion\n", "from gammapy.utils.fitting import Fit\n", "from gammapy.data import DataStore\n", "from gammapy.spectrum import (\n", " SpectrumExtraction,\n", " models,\n", " FluxPointsEstimator,\n", " FluxPointsDataset,\n", ")\n", "from gammapy.maps import MapAxis, WcsNDMap, WcsGeom\n", "from gammapy.cube import MapMaker\n", "from gammapy.background import ReflectedRegionsBackgroundEstimator\n", "from gammapy.detect import TSMapEstimator, find_peaks" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# Configure the logger, so that the spectral analysis\n", "# isn't so chatty about what it's doing.\n", "import logging\n", "\n", "logging.basicConfig()\n", "log = logging.getLogger(\"gammapy.spectrum\")\n", "log.setLevel(logging.ERROR)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Select observations\n", "\n", "Like explained in [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb), a Gammapy analysis usually starts by creating a `DataStore` and selecting observations.\n", "\n", "This is shown in detail in the other notebook, here we just pick three observations near the galactic center." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "data_store = DataStore.from_dir(\"$GAMMAPY_DATA/cta-1dc/index/gps\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Just as a reminder: this is how to select observations\n", "# from astropy.coordinates import SkyCoord\n", "# table = data_store.obs_table\n", "# pos_obs = SkyCoord(table['GLON_PNT'], table['GLAT_PNT'], frame='galactic', unit='deg')\n", "# pos_target = SkyCoord(0, 0, frame='galactic', unit='deg')\n", "# offset = pos_target.separation(pos_obs).deg\n", "# mask = (1 < offset) & (offset < 2)\n", "# table = table[mask]\n", "# table.show_in_browser(jsviewer=True)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "obs_id = [110380, 111140, 111159]\n", "observations = data_store.get_observations(obs_id)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "ObservationTable length=3\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
OBS_IDGLON_PNTGLAT_PNTLIVETIME
degdegs
int64float64float64float64
110380359.9999912037958-1.2999959379053661764.0
111140358.49998338300741.30000202119542841764.0
1111591.50000565682677411.2999404683352941764.0
" ], "text/plain": [ "\n", "OBS_ID GLON_PNT GLAT_PNT LIVETIME\n", " deg deg s \n", "int64 float64 float64 float64 \n", "------ ------------------ ------------------ --------\n", "110380 359.9999912037958 -1.299995937905366 1764.0\n", "111140 358.4999833830074 1.3000020211954284 1764.0\n", "111159 1.5000056568267741 1.299940468335294 1764.0" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "obs_cols = [\"OBS_ID\", \"GLON_PNT\", \"GLAT_PNT\", \"LIVETIME\"]\n", "data_store.obs_table.select_obs_id(obs_id)[obs_cols]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Make sky images\n", "\n", "### Define map geometry\n", "\n", "Select the target position and define an ON region for the spectral analysis" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "WcsGeom\n", "\n", "\taxes : lon, lat, energy\n", "\tshape : (500, 400, 9)\n", "\tndim : 3\n", "\tcoordsys : GAL\n", "\tprojection : CAR\n", "\tcenter : 0.0 deg, 0.0 deg\n", "\twidth : 10.0 deg x 8.0 deg" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "axis = MapAxis.from_edges(\n", " np.logspace(-1.0, 1.0, 10), unit=\"TeV\", name=\"energy\", interp=\"log\"\n", ")\n", "geom = WcsGeom.create(\n", " skydir=(0, 0), npix=(500, 400), binsz=0.02, coordsys=\"GAL\", axes=[axis]\n", ")\n", "geom" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Compute images\n", "\n", "Exclusion mask currently unused. Remove here or move to later in the tutorial?" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "target_position = SkyCoord(0, 0, unit=\"deg\", frame=\"galactic\")\n", "on_radius = 0.2 * u.deg\n", "on_region = CircleSkyRegion(center=target_position, radius=on_radius)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "exclusion_mask = geom.to_image().region_mask([on_region], inside=False)\n", "exclusion_mask = WcsNDMap(geom.to_image(), exclusion_mask)\n", "exclusion_mask.plot();" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Tried to get polar motions for times after IERS data is valid. Defaulting to polar motion from the 50-yr mean for those. This may affect precision at the 10s of arcsec level [astropy.coordinates.builtin_frames.utils]\n", "WARNING:astropy:Tried to get polar motions for times after IERS data is valid. Defaulting to polar motion from the 50-yr mean for those. This may affect precision at the 10s of arcsec level\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['counts', 'exposure', 'background'])\n", "CPU times: user 4.03 s, sys: 512 ms, total: 4.54 s\n", "Wall time: 4.51 s\n" ] } ], "source": [ "%%time\n", "maker = MapMaker(geom, offset_max=\"2 deg\")\n", "maps = maker.run(observations)\n", "print(maps.keys())" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# The maps are cubes, with an energy axis.\n", "# Let's also make some images:\n", "images = maker.run_images()\n", "\n", "excess = images[\"counts\"].copy()\n", "excess.data -= images[\"background\"].data\n", "images[\"excess\"] = excess" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Show images\n", "\n", "Let's have a quick look at the images we computed ..." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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hq3tbXSZYPlhMeGLhAA7uETBFRXNbmzM8/5soquZImV1V7X16poY7OIZ2LOFIhMEwns6UneG6Z9ZNC6jOfOYFYh2Q3NPrZdRoH1si40C/YLyMi7N5Z3ZTBaPmN3Bw9nqMDnzlguMB9nj4vSLRbZUeDK9ZPKzBH1afMLW6qVnuaTyz43h/om59wPJ6tIEtqi6OWzZhy4BdV1H9eOxv7lX1e1qmOrp9ck3Lr1+Kh6PAbGBC7twADAEDgMTtloCHg8RcXRX1SUUklnnH3abndsWhuuzSq/6c2fG+EFS6CGDcv9TNEOK+y8gA2Tned/+ce1yWecJvyH34rog9GPbyVMQdB6h2HnfnNqJamb0QL+fMjInDZMPx4DF0znTwSMIUUZeYJCMFo3BmAbtyliF1q6vggXXbmDMNZ7A+mZjIgIJnqJRhIRj9AUKOfVnSSwqVHtbJuWR/AHCPFQ6hkhl5+f7Sw146J+iTq/9+P16swh0TXtfQ23JV3hePMsSpXMTQLDwP2Uu4uXOMMCB+f0qQ4YRD1XZmz+/vOdC3WV3uwfAaBfWSPXV5mGfKXsllKW8+wQAhJurE2iQkhUnGhER1RN0iHs2dK1KwrG0FWyAkBUbFBPPCoovinvjMvcquVtbWNpIU5fZRE90LvGHnY1OcKAMhdkJsau5Z5xyYDbZAWBVj4M6o0mvsf2XWDb8VaY8DdR1Bw3Y8UWtPFMUdSkcHY0Q7bsfzMWR8J8omiomCxXs9S39+PC60DJZnQeb/Pg6cRxvuxLmN0oPhNQkPtW/SzqQEuA7aV38wF7qYHueqNiyzLK8ldT2GUpfNuH3SVULPNeYcjnMvrqtd2LsoLnGqAGGO9XhHzxwBpL0wASprqX6XjgkWBwd0wNJZ89u6CLSArYcX0U4Jhs5mJ8VxPo6lowh26oUVTuz4ZezzSZ5rtw2jHQxtfPweHLB5lrwosKcAshjAvMtyZt4uY+JM9jZJD4bXJKiCniKGx26k7qZNA2WAG0n6lC6Wi5cd6+CB2uoA5zGAbqtzR4FXgQFUvcwUgA24YSeUtYljxp08bnuClXp2DM4Atf0kRARmCduD9SAeKlQryo7x3j3e44E0rHO7D5RVZe5Bdr+ogh6PRz+dSU/Utf1x7wTEA04nbXtHCpBGPXXAKu1wDryoqV6BxiMCnNU6qPqkBgxZ5E7VFUARD3m5cPGn4rvbqC73YHgNwgPn+bIlu3JjP+8JmfEH3j1+MAgpJmLpFcS76barxZLjnBmN7Rh34lwWJlIpMmbc9ueGf6mr6sHeABwWC7c5upMBcLirrnrIOLlXmn6Nx9JkIA1nWY0/VLA2HzsmP+DB966u+uJCv3xMytg97wcgwr2408O91S4jRWVzQpFgeTifvII2fRlYe0NFaM6ZHV+OKeYaXzDdcSLFM/w0tmB4HqUHw2sQd5y4CgJjkvKD5fvy+qR2cVYnBUspY+JKJ4Db/3xy+8NfqotMLuokLtQFHGcifF+2Sd/cG+735uofLPJJwn0Q20i7gAr9do/7wBAGNdfvwdVcXlPxWto9y0XC9zJxsPcFw+/3SXGAfp+lFoDd1p01bhuWQh2nDfoIq8fLXrLRZY6vZVqEs9nbqCr3YLhiAQj3lLNE8NauKWxbZaT/QFE5hPQ3Jq8HZuP0WFM3nczZmwMqQcwOYgBMWbEZNunbjHpcm6vM2JoQn1TYteYK9op4qiHXnusic1P7fqcdxztDab29yaqSzmqpqVtWVGcWdUKfZvn/ODUmCkeTLxTuUHFVEvApgdNDZ3BaYM/zdl0VLsfO23HxReSo/f+x9cePZ6HimnisvSI3z80yAKN/vqiUQF56+11zuE3OlB4MVywY03mYfL9bHsIyvQ6WVdu52OR8IjUKdlQClHtMpbABulGd69XF9wNrZ11dgCiBVOp6L139A8xKzyngc2DfeXtMakAWb/p95dTFjUlmfFWV/xbtjJyO2/tZdO/7wPqHQ8OrRLv3F9tpCWT0EYYN23LvLOc6yJXOCNrZUbBbB5+FumOIKcCdHNiX8WIDSthapS6glhqGO3q4R18MHdRdiylNJrdNrvWeUkqfJel/VN6psZb0Q03T/K2U0muSfkzZvv3NTdMcXtLMjRG3FZbxdkwkVwtLe9eWnY9R3kHTAZDXcuIycQjJGSqzPWc/bgdz+9ZcwfhgoWdFW+VEHxR/DhjeL9LGSrsm9+BFC7CdvSJpfSgtFhkM5/OuvW29lkbDfMywktaG0pEhAQuTb+guhROqNC8g5+0rmHiZyuYs3NVJ9+T7ePmCsSwdjv97kHXpzGBB5PrlYun9ctug2y8dROlrZdfxRaG0gS5T52+yXDfAV5L+YtM0H04pbUv65ZTSP5H0rZK+S9LnSPoWST94zf166uLsakcBbJ7hMFM3Pk7qeghRhYlHlLp7DbsdqpxMqD2ucrLaO8vzPTa4pjs/vKaeOy3In/VMGmL5yklJn3jvKjXnkgYIUNXWBpunDyTNqi5IYkI4ar/bqKXhUBpNpLqdqe5JJZuHe4HhSV27JfdFILMUOdscC8Pmvv1cZ8sOGthdy9TFZewNG++4HYOyaIIzQT+vZOYOjNSjRCMpgdTbkI2Dq8U812Wq402XawXDpmk+KemT7f8fp5R+TdJ7FA69Wt25cmPFgRBWyIPIQ4w65uqUG+mlACse8A111Uk32LudCjsdE8C3BiXWD5bj7NSrbDvQ0Rf3egKKSOkxLtkegIqqyqbn/HketU90Z6Q+SbfH0nTagt5BBsTTWposssp81na83Oide2F/EcbS74vzNtWt64faDvBtte0whvSdIHov1FsuOM7SnI056zpRDq4ui7DS39IO6NWBlu2F4tuWImVANs8u/2fMHWDx/JeOqJssz0z1Tym9V9IXS/oFSb8u6YPK8bHf9Kz69DTFbXMOhoTPsBr7JAQQ/aEnsJgH33N5l00It705Q/OVn/6VzhQp4uhglqz+VfHnDz+gBRiW94QQ0Etx2HUF66JdbKQDdTcoYlEA8NeUw2bWhtlpgqOGY9ZraW0Q/ec6AOO6YvMmZzzed8Y62XHuLGHh2VQ4LMrNonw8BsVnrgIjbkJhAZkW57smcBk7W7PX0svvzDupm4YpddmqPx+lucNV7psuzwQMU0pbkn5S0p9vmuZA2cb9lZcc/0FJXy9Jo9HoSYc9VwLzIu3Ojfc8nG4sR5wVoHoCdnXxOineDxUTc1laltSdeC5MPGeMHO+2P6+XCHAzsXxfEr8nwN1tT7Bc1FBiFHGenFnbBB7PFYvLeJDVYSk7UcqJLkmTSf47PMxOlgNFwQacD0ndmEoPduZ+qOJzqG6xU8wMI0Xsn9q+T62t8jeVlnvKMZE42y9NHQ6E9A8pQb18bhC3c7I4cb+eu16KO4a8rfJ+nmf56Ec/qpTSkX30oaZp3i89AzBMKY2UgfDvN03zoauc03b2/ZJ09+7dZn9/f4U9/L0LKzYqIfYu9/yWIONMymMPpe5K7mou7EJ2rgfYDotzmZRPYiKyY6QI6wC8fY/i0iPpYALbAJBl9+55zoyP1AV2GNt2+/nL9t1Y2UEyap/cs0o6OMj9IgyIh3qxyIA5Hkv1PJ9/pEgXrBV2R7zrsE6AhuygSl3vN4yMXONyifacZAfP0rYK2JKOiImCZ8R/s/P7UgAfgEvbC4XTzLeGBcS8L/57ufgCyvUBXVg1hS3c830T2OEbb7yhhw8fbi777rq9yUnS35X0a03T/M3rvPZ1iqtFDoCU2nIVFJAZKIqLAmjY+2B6UkT/S92QCmeB/t7tPr6qY+9rimP3FQ+35xdzbSbw1F6n6u7rgdA2qqnsGO6PSeRMlElF4VZCD7BDbrTIWdcZ8MjO2NuRRmPpdCEdzaS355H+Vv4OjB9jUQKCV+Qpg+Ol+O280KxX/5Ed78DFgsV3A4XjyGtLYioYqFu1qFzMykByB02/NwdSrkE7nvZYFa+0i/OI2Ni327/bJNfNDL9CmeH9akrpV9rPvq9pmp++5n6sVNy248Z0QhzcnrhMzXB26PsQuxOESebG7dr+nHEOi1eOJ0QEBsC5B+qqd7Jj6O+k+MNT7iE7gJrv9oYHF6BEJR8qVPDSaD8aSpvTHEqzWGS1lzEbSNoYSFtb0suv5GNns6w6P6pyrBZjeaoMzM5IGVMmvjMf7sWLHEihurra76YKAN9DVgBycs4xHfBbe8EFZ36lKizFb4NTBcBi4fF+8rzhUOFYf1b4jYntXObUWVdk5LB4PcnkclPlur3JP6db4i1+kjCRqU4DgMD+/M9VjLJ45h0FoBFcDYC6bYnPuI7H9HmFFfrGdZlEbqiXupPbq504yMFGADKvEeigCvvzNDU3CRAy4l5lwopQXefK2SWTNlRmfxH3MlYA5e6utL0lDQb5uPFYGs26ZgnUYpisO2+4d8IajorPASQvm8Z3jB+/k2+bUP6umBAAHsYWezLiYT6lrdBVY4ATAAbIPRCfPvObUQTDTR61uumgZfUiQp6kbtGOm6YmXybPzJt8WwUVh60/txXqJsJD5oxM6jopeNj9IWSlZ2c2VCgYJgzUvdLY4vzBJ7fXYxY9q8CZJ/dEAVmKTbjqSRgPzhtXv8qMCvoC6DpjYQychc4kPail4X6Eymy1THA6lU6rDJZSZo68LtobK1MApfCebrfvyy0x2fsFZuaqI/cCy3VVH8F26ZoAC4hs3JzFc4zfP78BqZm+kJR2WdRt2ucepLBvSmGHLQstlPUefSH134779vhYxuWmOFGeJD0YrkDcHoMKWOa3luqV7HPPNCiLN6BWsXMegc+u7pQ2wjOFilM6T1y9K3Oa6+KPye2MhuuVISXltdzh4u0v1N3Xw//4/kA5dhDnxtZW/ptMpLcPskp81KrGdZ0B8mRxccLDUr2QAzZcQNuruvhYSF2zhAer01/6J7uOq/y+2Hg4lI+1jxcg5KaRcizLZ8jLi/k98Fu5o4cx9rEu2/Xnwm3CjX1/W9hhD4ZPWdxLjHqMOAvgfa2LwIG6yIQgE2HetrejqPBcFlGoi3YWitXc2eaRuqq2G/WdCS2rl+cbF1HU1VkP94VX1gFhre27s0Y+J8QD8ZqGSZnV7CozwvE4s7+jQ2k2jzFnTJy9DK29uWI7BSY9tQcdrHwBKgEaBo/67dfwwg3uTR9aew6iLA5uiy1ttd4f2fluV5XdrwMV/caDXhbMcABw0Oe32bI2eBZZuHhWMLeUxT5umvRguCLhAXaHQAlWT7LtOZPwGDPCOzDG83C6DcfVTc/i8InB3hfOmgBM9yJyHxyHjbCcSG6LchsTzggpdqKTgkF5/2kHm9eJQvXjuvTp8LCNHVyEOow6iY1sZyCN6ohfdJZ0YMf54uSmAUAK0wDsG486v6tnapQOhbIIw1CZ0fPb+eLoTi4cLCyArp4jDkTcF+15qJCs74eKauoqjvMF1ceD+5y2/dpWZNmg+qOSl+aGmyY9GK5A/CHCCO52m9Kz62oG6taw+E7Wnjs9XCXeUDcI2mPVnH24uuXeQ5+05crP9x6KQzuwR5/4jX1/prCbVuoWT0V8ywDCYe4qs0jAiDHcP4z+T1od7vGiGN9hbmN/kT3KgO+ewmSB6cADppno3DPsiM8Z/zKYmt/OGfayjbpYCHyLVBwynE9sqhRhQx4PuLBXd5A4GPsCi6rtIMcrOeb+HHA+woK6rnAw4YhiXMsF/SbKTe//cynubfTYsNImNC4+43OfDACbAxMPHwA1Uzg23EvqAMvEY+K6N1TqApPbgWTfuyruDhmCjrFNwWhQ9aVuiTBXwVks6A/scVOx4RHpcFyXMSW4uKoi6wM1jtJebLalti22CGgUXtdddcuezZTNCO7Y4X7dtsn4OZukf86S/Vj3lrsDjXAftxHzLNAP7IG+uJU2X2eIDnC+ADooPi7O82uXlZZg95WieAbiz9pNVZV7MHzKwkPkgbKokQ5oG7q4oTsPEqs1oOZ2QWw5POxM4NLD620S6gFYscHUMvXQwQqm4tuOcryrVNjbfDL5jnGcWxVt+D1IUahhV5kVvqxQ653ZALJJWU0G4MeShu1BVR17w0ixTwkZGqUThbb9twPAiZ9084Hfr9saUUN94SqdU9xLsvY8Y8hl3rbJAugs3X9/B9q0kbUAACAASURBVCFAF/br6nbZL1l7btv1PsNsZd+VAfvLzAQ3TXowfMoyKP546Mj75HPPVPCJjmDDky7uEFd68YhR81AXBzTUoGXZH/7n/XcwfZJ9qrbvveKJ96mcpA66HoAO+yH97Y6k7fbphPmpaMuzNs7NA3V3/LwOo5snllXbcRuhlyLz8V9m83WgW8awnAH6OPhvXjJCjmMBhEHLjikdKL64+Fi7U8zPd5OK/3YlsPk9+XOEI62zzUJxnZskVwLDlNJnS/q8pmn+t5TShqRh0zSPV9u1myfO0rbU3XMEO4sLVVzKEA3f7Ik2ad8fNMCQ6i+emO82QymAAxUZdRYViQcBW5jntfr1XFWjv85Y3fbljGVbwXAJMvYgcfqDurihHEwtSadm9XcvKva1WlFwwUGyVla3KfJA8Qfu2WMiAXTuwe22y0DMbYVcw73MsmPcDlcuNLJjOC+1f3hovT0WmdLDzP+dyXvbvoBKwfxg3s403WbsvxGf8ayh3TTW3k2WdwTDlNK3S/qzyrbnf0+5+voPSvqjq+3azRQM7neVH8oDZZtVWdXa9zaZ6aJRnrZYiQEXJjOgkxSTsAy3YOLRtrO1gSLlrCz2MFY3fxcABcwJ05G68ZMTRcgKifwsCF60gvNddeNvrmyv+5Sk0UFWez2ecUPduEquP1JOy1vUeXKftNfcVJgJPHxG6nrHPU/8SNJDdVP13Mkle8XbXTJXzwpyO62X7JcifIj2Fgq1lnEivAWWC4jjvV3GQt3EQT94vjjHc5J94XItxGM1/d69Crqz0ZssV2GG3yHpy5TrDqppmv8vpfTKSnt1Q8VX+mPF6s5Ed+bGKot9x2PuYFs8YLAmqbvVKO2gDgKQvm+wezLdplgpPLwOLp5C5mosk/htBZPgewoNeMYLYMi9ANTOkjyLw1nXY0XIxqgOMJ2OdV7u3+9rc5hZ5HCYVerqIJifmxO4h6P2z3OiHykA6ETL2Z2bPliI8LC66cHziV2Vhll76l2jiMfkeUA1pwSc7DfxhbG0+bkJxUN+pFjkJvZ7uEdd1ob/blI8V34/vue17LybDIhXAcOTpmkWueCMlFIa6mKGUy+tAHJ4DQGbZaqH23Tc0D4s2itXfLfjAUqwRZjimbVNXjQxfQRdH9o13FgOyxsWfwt1QU66aDd0mxyTzceD+8AJUtofYTSSgfxA2tnJWScHBxkMaf9U0rQdsDTIgDhWlBtz8Nptq9r87oOocu1s9KToS+lE8N/LmaGPYbltKN/5wuZM1+MyqZnIM+OawEDddEtUbpgp4kzT++xscaww0cDujtQtT8b9sIiUHmxf+Lz9m8wQrwKG/zyl9H2SNlJKXy3pP5X0j1bbrZsp/jC4147gY2LV5soPNsCDSuUTj/aI5WKSuVfZ1b6kbokwznXPr7PCkvm4/c/vx9U5JiIbm3vANBPPq2YipaeZ9lytZ4J7yAZFKtbqzPhmswyGD9pzAWbNpY1FzkyRgnHCprYljQcZCDen0vFUms7iNzpTZPQgpTMIO5nbD+lj6XQoVVf/jAwVwooqXWTTbkOkghDX9/AmVN9tRRYQuwGWBSIAfZ4RBzvYeQmcY3UZLZ/Rpu/n4yz0pspVwPAvSfo2Sb8q6c9J+mlJP7LKTt1kKSe923rcWeH2w2UqD8ehQklRFYXjSs8yjgMAivAWHtTS+VKpK86KyrAPJjGsoXQOcCwqA04A74czlRJU6JOrkLClJGlwmO2HqOm0hRNlvc5hNlXVrbADuxy3Az6f52NcXd1UXpx8IXHVE3Ub8EzWtoNSqW6WQviMm01g9lKo7f6bOjiWtkGuQ9of40yspP+eUjdYHxZbqv7lHzGeCNf2tMMT++4mA+I7gmHTNLWkH27/erlEyofG1RC+d88rx1A9BZuVx3TBCpl4gCN5ymWMl4MV9iuu47Y7P6dUV5fdj6efeepd6XF2VusGfNorc3o5B9VLugiIR8p2xEEdNlbPVDkvN7WIgGnaGCmX+RoOpZO5dHAYKXoem8kYuyffzRfuQOE3OFOwMB8bTBOyazAGy1RnN494KS5A7cDO4fekrYWys4cgcSoS+bV4JkibQ/1msZWerPI26laz8fhZZ588YzdZntj/lNKv6hLbYNM0X7SSHt1g4QFyz60UIOD7bbihWgpDvHtamZTOhCgPBijwwOOEwWPp3kIeXt8YnLZhEmQ/cDweTcQnPKqlFyLw+3e2RPqWgzM1EN12Wto+UVu9Lt+o/RxvtRefGA5a9jePe2TsTyqpmeUqN9wLC0utsJ86UJfFFLCb8ee5w25DG+tiPrQDS6mK0g/+79sgDJUXAVRxwrVYGMt8acbb1VYPdypDr9xb7CBNxW5yxF1TOVHXjMEz4qaXmyqXgfnXta/f0b5+sH39ZsVi0YuJr5JMerfzMGFwILjtz+vrlRkiHgDsEx0gcK+01PVwOqB52lWZ30wlY9LfONcZHA8/QEBIihRg5ZtReZEHZz/r6gID3y8UVXmkyNBhIZkq4hVLz+WwZX+TiTRoZ+WszmAiSZt165GeSJN5NzuFfvp4umcf9Z0sHvomdbc9aJS90rBCZ4PcKwzM2ftIXTCSul7l0slUmhtger73iTvB+E3cFinFs+ELNL+Tm3E8U4r0PcC1BMCb6jyRLgHDpml+U5JSSl/RNM1X2Fd/KaX0LyT91VV37qaJr7ioh84CCcWAPfJgu+cRhgZIue3H815dtfVJh2d0mSOnrFCClLakqbXnKh7nnTsu1AVYGA6vzhwAOB8rn8iEuDiA4vGUuimG68M2dnCcAZCirlSwGY/zZ/vKzhYpLzCTWXaklEUWaNfBvGSzLBYcP1M3rvKRMlB8Sl0V3Jky9kAPoi8954wnZoDazuN3L3/bLWXGvKsAefpd/na+iJQFH/jcY2JdW1DRD7dtyu73pspV1PzNlNIfakv2K6X05YrNvHpZIsseCFRLD1/YUHj4yD+VusZzKdQSHlrfTN2B1SfL2NoqWcegOJ/yS0wsd8BIF21CeBGXxah5P/08t0/5mLjzCJUNu99LiknN+IwkrQ2kwUDamMbmUI8OQlXcaj9ztoPRfziUposuc10owKjcgIsAZ363Uv0tq3uXC4qHUNGnWlEJp6y9yELizpUthapM+w6GqOBvq2v/hPny3JVsGkHt5/4WyguJax0eZsPv6p7l0nt9E+UqYPhtkv5eSulO+35f0p9eXZduvjgYwm54SJxRkY1B+X08gzzM2MXcjlTmqgIWzgAp5SV1J7Hs/w5iPrFqBTNFHU12jk+QZeJB1A52yxwIDpKeDQGjLFW286KibSOD1i4wn0cg+DnQjHN17Im1syad77VcL7rjAitj0fItTf3V791/H9R/Sm6VNlh3evikg/2tFe+9XyULcxUbJx3jxvWkboGJMvzFwRuV2h0jvoj4/33BcHOLq+43Va7iTf5lSb8vpbQjKTVNc9t2CHyqggp1pMwayFt1+6AUcWE+2fAIlk4RAINUNFRnWBypZlRceVkBnM50mGiAlBu9AS0P8nU10plAWY6LVynshSVYunrJ/WPblCI8Q+qq15NxtgOuz3I5/7mked1ed5ZV37mk32mP35S0s8gB2vcWMcHPWVWrWleVdFp39/JgUSmdTa5uMukdsLYVTHld3S1DKVLr5gSABYA6VXiPMZt4cdySjbpdetzes3/ued/cTxmsXaq3ZDbhQOLPFyUpnFb+jDjDvtXMMKX0l4v3kqSmaXqbYSE84AeK0AseutIu4+IMr9yjQooHtMwFLXfFKx0uPoGwecFW3LFCH/jjPjxez+1UDuCARgmeKo4tAaRkSPSBezvfp7iS6jrbB5taelx3VTLYmReqOK6laZ2Bb7yI0mCTSdgTKfHlmRdSxOoB+B5byL7B7ol9qDbsxz53z3KZtwyTZKycEXvZfqkbmuWqNN+VZhXGVfYe9sZ9lFktzib5nlxofjPPScdEc6YAcJ7dm2wvlK6mJntSwUTZy/xrq+nOzRcmCeAEM1tmpMbT6azMwZDA5SM7XwoV2bND3NHibA+1BnubtJxp0HdskmUYjl9/aufBOkp7JK+0wXc+aRywaYP7YhKnWqoPAyxIJ/O0tpHCeYB6enDYLew6UmaEbCV6qq4aSZ+IIdxUN0jetyzw2pTcg2cGDRQpcaWdlN8GVuzbKHgGDOYGj21zVXS7vae5sq2Q39YBzwtN8PmOLlal9kUOwJa64OyajdspnfHedLmKmvwD/j6l9Dck/cOV9eiGixvmsQFKXSM1woTxWDpXSVCTKKjgq/hYF8UfagcnWKHHHdJX2irB2mPXnIUCaExi3juDQQBDB1xA2fdbAUzctnqg7KHdVJ74fj7xbgDFtqTdsc4LvdL/h+3YndftqzIYTqc5tW9Qdz22jInbxlig2EyJ38gLFfi5AAWhSU17LOYS+ufOE/KJvbI2vzfjzHgBhqWDxD3ILBhkPjG2e4oYVdTwHbsvYhgdRL1aEf3G+YcKj9Pr1qvJS2Qq6XOedkdumzDJedAAQsCFAgZSABHFC3igCTAGIJ3x8bA7E3DnDD8szARbHp5OZ5Cuxrv66sZzPM2u3nmRT67lhWURmAjtEzxNvwBdP4YA8jVJn6EMYou6CwKMw1YLcGw0v1hI80VX3Rwq2xwPD0NdrueRJ+7ZIwjs1mMbsemR6eE50AA/vyVjSNiQ/5burIEB+rj58wMzo09ujrijbiA2duNaAcBcl0XBFyzfVsDvm9exMutmmwTYt9eJ9LCdmyxXsRl6Jsqasn3+r62yU7dF/OF2w7R00WvoxwKI2BwHxbmAqdsRZd95vBfBzazay8JcytXcDezDJeeUk3bZfbsa7v1FfMPzss+cX7X9x+lRz7qFAZjYVZ3tgHUtndXSWRXfA1BJ2ea4WISq7JV9SlXf++GOFNg5zMqP1ZL/O9NzeyHHuX3Ur7dMvH/uTQbQsI26p9j3bAE0ZX0neN5/o8bawNEH23RhYXph1GRFJoqUf9PfaZrmpi8CKxMmsXuNPVZrXBzn4qlRqFEc66qv1I1ZLNUTt1WRMgb74txlD7Eb12GzDoylp9gn+mUGfOmibczDNTjeQzkAqLmk2SKzv7Wh1FRRlBa2daYMhnjMUaFhX9jm6jrvsXw4D087vwljX2ZfzBTmCo8dpB5iUsQBlil8fs9e4ac0Z7AwVPZHG5zrnl6O9dhEQI30OR9TVH76KAW7ZH8ZmC5hVZzvdmdsx9w/2gWpjDcdEK8Chv910zTv9w9SSh8sP+slxB9qqasaYWuRugUHlrEzV8tgiyXYShfVZ1ZyKeyNzr7cwePZEIRYLPMyel61e30HirJQ7kDYaM8HQN0+OLN2Sg+7V27BOfBxSa/M854oTG7saF7Agr4AEns2jnznTBl2x4LloO5Onk8p7KLEhALE2FKxLTpAIaQ5ritAzPORMTs4QAJkMDlXj30sATM3W3A8Cyrszu+pUhTA4DfDtuw2UX5Xj0TAwUURiRcJDL/Q37TFXd+3mu7cHnFAhKGMFbXnCN/Ac7tQ5JbyvRcU8BxgVuSZuqDEpKTeYKUw/LuXlmrW2JekmKBu93M7F0HJHgDt6h1tAihMdmyCpU2qnNi8DovvT5VteknSWtUthwZA3R3kuML5PO+fDGvbHuYMldks2xvdVEBgNUyoTJN0dZMJP7bPGAd+o7EixnCmSFl0dsVvwvhJFx0WHjaF48YdXYAlgOabwvvY+oJ2qrB7YmY4UTwbPEsE6+/Y+PM8ePV0WO7M/m6680S6BAxTSt8r6fuUi7oy5hCEH7qGvt1Y8ckthV2IlTrZ51I8SNsK7+mxLoZnMEldrZPCseFt+grv3lqpu3fvTtvO2+qyI59QPjnpr8e9MZlcBcPeCSPxiQKgrSmYjXvTYVmEJTFua8rluAZVVpk3Jtn+t7WVnSIPHmTHybS9r+2tbG9cn2Q74sFBjkFcb69zpDAHnNkf4uAnGwMv9OpqLUzTHWcUccABgwMCW97MznMnGcLvPVGwP54LD+J3m3KZfeTjTpssNB5z6PUwyTBxTzIB5IQaleE5N12eCIZN03y/pO9PKX1/0zTfe419uvHC6j2WdE9drx7pd6iqXqx0S5G9QCUbr03nNkaP4fMwD+IEiSnbVrdcFuqVq04nyuoSYLRl1/WHvKwgLXVZqXRxsuy01yZvFnV/V8EePUZypKjewz4gr0p6bSq90u68M5tlh8rWVgZD4gerKlez3qvyNgGDFh3G4wDNw8MMpCdz6ewwjwMLwVF7jycKFgeobygCrr2iD0Dii5//n1diTWkPMGJBAaDdVspY7io/Q4TgEGngCxKmAyrmSN3JTbD0tiK/mDZpFyDmeXIzirNXgN0jEG41GKaUvqBpmn8j6cdTSl9Sft80zYdX2rNbIEz8TXXVW5gXTIQHCtbABkteLZpVH9tSqcqd5+0qQM1tlcuM86hMZXCuFAzN2/PYQoDZbYjeHx8Dvwc36HtAOADhqWyonxuS9vbyX1WFd3ljmos2VFX2Eo/G0nbraNmcZofJ8TwD4WCQGSL/XxtkUFUd+cS+TQL3lqzPst/LHUMeP8h9OhtuiuN5DmhPWh4d4CYErsM2qzBrYhExSfhC5Sqth754mTYpFgD30LPwAdKekQQrvS0hNchlNsO/oLxF6A8s+a6R9FUr6dEtEB52QIaiC8ft9xje3fEhhWPBg3W9AonXNUS9caDx2EUvecVE8zARvMOwAsCINslB3VJ3EpH1gOHdWbDb4ty4zwRzBsm4MB7YtGCsUoDASBnIhsO86dN0mgFxaysDHptErQ2k0UTa3ZU2tzL7GxzoPNh6fZyPOavzZ1Wd27+jCOz2FLtKse0A/aG/bjsF0GFUeFh9n5MjRSyjM7+y7Blj7La4Q+UF4XwsFKYRFg4pM1z6yWK2Zp/VCi+7Rxtg091RhOkcKT+vtIMMFfGG2FJvg71QulxN/rPtf7+2aZqO+SGlVCZT9FIIA/YJxYMCOLKywkZQV7Bhkf8Ie3TG58KPB9jCOmrlB/mRurF0pTpT2sP4DPWNWn2c75PVi7N6vwBvgAX7pNvfnCETtrLV/m201z6w9mpJp4sMeKjEUgZCAqgnE+nRo2CJOtR5tgmVamYzaX8//731KBxEu5MMnqNhPnd/X3pURzqfgz4P/lABdhTRQAuggg5jhu3VYwxZQABHX3A8Iwn2BUsDDGkTmyMqMmovwCv7vahc/VixqHnRj3vtfR0oEgBYnAF7TCCc+6IwQ+TnJZVq8rLPejHhIXqkYFgeW0iGBfY5KtaUub5MQvcmenygq5gcx+Tdt+/8gV3m2R3Zcd6HPQUbOFV4an0XOzzJ9EWKODT6yGbuhBZN2v/DIieS7k2zKjybSZ94lMcOmUyke/fazJGW2WE73N3Nf5PWczyfq1Po1XOSU/tKkdfxuGtfpL2tFlRn865dzUNzDtr/w6jcSeIFLPg9YOCk57EYqj3nrGjDWTy/DeefKoMadk4P4vfQGzQC1zJwzvH7o2VwLdIQZW3Bej1lz23Qt0Eusxm+Kuk9yt7kL1ZoCzuK37CXS6RShM/grPAwm9JzilqDjQaQIj5tmVrqAITBH9XWVbXajuN1mfHeH3DPTyWw2Csy+8MDo3R1DNDbVAbVqULd22rZ2PEsskc2phmYxuNgd5VyZevdXen+/WwX/NSjfM7JImyAOzuZBdZ1lwEeHgaD3JjmdtYG+T3fzefSUUthN1p1fDLJ7U0XOt91T9J57cQHuggCjN++wuQBkDmYeZ73iUIlRmDVgOVIoTWgnp+01zm282gTVggQHilAHBUfcMSE4gsdvzPPFvueYLc8UrDH28IKpcuZ4ddI+lOS7kv6m/b5Y+WQm16uIB52squw7bmqI3UfYrdJoCa64R7Q5EEkUNrDW9wBAhACYBxP+SvEWQUsFMBkAiNu6Ke9B+qqxdvK1ao9tnIyDvDa3omd66pKurOTQYj9THYOM+BJGZAePMjnklK3u5sdJaNxMDyATwpg9DJgd9prDgbBIA8OotI3G0fRj9Mq2pxOc3/W9qVxFeDDwuHpbjArt9W65x2zxZGCRZchSBPFwkbs4lCxYGG78+uwUAKap4pYxdJe6/GDUmwXwXPhgeOYNTBhEAFxm+Qym+EHJH0gpfQNTdP85DX26dYJAOPM0LNJeKjcW1vGcPG5hzt4TNpYocr68VwPQBzZ+cTClQzHr+/ql6eUcdypLlas4bps4ORMSIpwGIAQNXY87qq1kjSct8HUh9Kbb2Y1d2OSHSrr4wyEsLm6bgvAzrMXuary8VxzMMjvh8OwMw4GLeC2PwLHc47UPV7K151UXceCx2e6F5dxKYshwLqPFMHznqrpwMmYuomE490O7RoD78vfi98MAHeQXLPjOdcdYjwrHn1wm+QdbYZN0/xkSumPK2eiTOzzv7rKjt0Wcc9ypbCZ4SiYK6+yBOK6nYiH10M8NpTVTh7ksgIJYRSoswTrEqgrdR0fPNBMJEo8+cZUTACp6zn1+6va+yLHdVvZS7s36AIMwAJ4Ee5S1/H5cQuAMLf5PKu0v/1b2YP83vfG+RuTbGes66wWH8+lhw/CmSIFEzye52OkDKL37uVjJhNp7UH2Mm9Ogxly7vo4XwNw3NmRXp3FeMLISVlzVgiIed60O0fwxuIddrV6pMhKgk1K4XgpnS/EtW6oW9ACVddTHYkrxJE3VrDBbXXrPfK7s4fygV5QMEwp/aDy4v5HJP2IpD8p6RdX3K9bIwDJvroVQBzEAErCaZhkZAgAjISBbClYIROHYNypYjUnJs2373TVV+oyDxw9sEmM5Khz2Ba9fiGexYGyGeAz2z6iso5bujNr9WfscXzmDG2xkD7xifz5bJbf13Wo0fsLne97QkjNdCq99MpAg6rOsYem4ko6D8aezTKgPniQAfXuXpeFDofZbrg2iHJgp5XOg7t3dnI7h62XertFJ9TK43ZssRE7UHiMoIOhq5mESwFkMwV4sqi56gq7AxgH7bjfU4CkPyOwOY9AILgfjzhgiYnE92zGLOMhP7dNruJN/vKmab4opfSvmqb5KymlH5D0oVV37DaJT5Ithf3Pk9+xAXmFEOIN8fbhyPBy/7BDwJIcWQ+lcYYCIxmoW7GaoFsefCYdYIgjZ6gMeoDFw6ob1/bZu9JL9zLDOprllLi1ofS7b+l8S0+36cHCJpPWdneY262q7MmVcujLeJzzjmdz6e2DzDYHgwxu43F9DmDIaZVT8KoqH4NTRcoAd9YC5Fmd2d9WS8GqKvd3MmmLK4yz4wVQ76jR/C6DzIDXBhmw31QGkrIaN4uUq9O8wvS2FZoEoMPezLA3FikcIOzQR3C/553zfqHQKjxbhQK4CAvfsbqgTp9wDt02VihdDQwZq1lK6TXl8XtjdV26fYIqyd4oXkxB6q7GvkpLXVUWjx8Ahn2IsA/AjooxTBqpG4PINVF93O7EJCMOjfSuPUXubK3sCW5q6exRhMhMlIEQj+1i0W7MdC87LlB9KcBKGAtMDrV2pw4Ak3SeSofT43iWQeqlvahafXgYOcrrE+nlexkQj2dZZa7rbjuPHuVzpK4n+mQRTHA4jBAdKb/fbLNeThbS2kHYPEcY/A5yfvRAkeYHM3Pnyrn9VAGKMHKq3PB7kRHi9j/ORXNAo/ACETxf8+Iz36wKT7XbMz0jBTMNIEg40W2Uq4DhT6WUdiX9t5I+rPzc//BKe3ULhVCXgUIV5UHm1bM1pO5DzooNSLEZz9DOJdgZdimFrYqsAy+gQFtunPec22SvvjXkY+X83/FYeu21zJykDBKvvJKBBTsfqvLnfm7YBh8+ynY9KYAQh8fWVjeWEPa4syN9xqs5q2Q2i89ffTUzOcJt6joyVCTpdJjPlQJwDw4yGJ4sMqjyfd2uFDhbsEs+PszAP5kE4A6HmfXO5xl0m7a/Z3XsM7KhyGZhUdlRN0aT0CMpQlYqhUnF88E9TpHfDwD1KAWOKaMF5soef7cbnqoLwJhxBurGVMJUPd3vtslVHChUtf7JlNJPKY/XF6y0V7dU/MHCfuPOCBdUXh5UbIAAm5e0dyeIP+Tu9XOHDOfBEJhw7vFM9j39w9h+prDlEfCMzW+9VWnPChV4b09an2aEmUwWatr4PpwSZy3dgGXhWXbHCul0sDzsj+NxPh81HIaJuj1uVV1sh1X7eWPgx7V572B81gZg06fBQOdbDJDxgn2zqXNA9/ogh9/wW7yt0ADIRGGxoY7gkaLmIswdxk87tOEpdf57scjyO3kJNWx+vuByLrZl2iAkDBbonuzbKldhhufSNM2JpJOU0o9Len01Xbq94g8j2RXs8+G5xFIApT+YHo7R2DGs5rA3HmLSswbtuahnDojEIqLGnVlbzjpQ90Ztn7e2MsDdv5/VYCnb5AAaKYPk3T3p5Vek9c95Tz7h3j3dffBAd/+fX9Vv/1awPFTqySQD6WCQVfG1trNVFel44wIs03ioO6+t6878WKfzWrNZZouwTRw0pPSNx6FeSwHs2A3H48xq0yAKQQCMCCE6Dpq8bm1lhlzX0vBjwcBZ4NzhRSolnlocMfw+MMIyAgDQ8/04+OzeII/76aINJq+C1T1S2ALPS53Zs1Mp7NL76jpNbjMrlN4lGJosIzPvfFJK/5Gkv6X82/1I0zT/TWuH/DFlbeKbm6Y5vKyNmy48XFJXZcbhAcC5usvkwfbothx+QEJ1YHkcw+TDbsSEkYIJDuwzwndQkVwFG6ktp/Wq9PrrGexeey2/AgSHh60TYiANx9nGtrUzyCe89plZX37wQJodaevRR85tcq+8Era/4xbMPut+C2qzaJfrjMetA+eR9BnDSqP796W9PY0Wp7rziX8nHRzoZF7p6LCr/u7sZOY5nWbwPq0ifAcWe76PSiWd1MFEZ7OsYqMWA8zn9kLpvCjEcBjseHueU7kcWNwzTFD0gbqAs6kIo+J3d+3Caw3iSDtVtrmOXNl6vQAAIABJREFUhmG3rar4/d2BhpOFXe5YPFHLybS5rUHWpXy6YNi88yFdSSmtSfo7kr5auZL7v0wp/UNJ3yrpu5R33PsWST/4afbpRgiqxkx5lcajKwX4nBcytfPcw4xNCRW7UjCKWvHjYHdiEg6t3aFi8uCJ5Npkwfik2Vb2In/e5+Y4v894JTOgV1/NzKxZ5KkyHofqCMPL6STbGfE2XpdeW5cmGx2b4O5u9hLDFDenue3JJNvsPvmJDFjkHldVthOezHM4zUs7d6Qv/VJpOJI+8m+lD39Y9SfeOldfYYg4fh49ClvlWWvrGw4zSEoR44iThftCzSZI/LxyThVB3YtFBmlMARNJnz2UZpX0b9VNa2RRq9QNeSJUZksBSphWHDjxMp9au4fKoI3dlN8dtZxnB9umL7I4S95W9orvK4DwNrNC6RIwTCn9Iy0HvaScZfVu5csk/UbTNB9p2/8Hkv6Euo7OT4tx3kQBoLyQg8cXYh+ixBKOD1RXKphg/3GWiAwVoTzYg5K6HmYpWCAFALxgBDGFU0n3X8tg+NprYaurKqmaV6qqsOEBVueZJFWVadgnPpnR5uBAWpycH09b6y1jO60ysyEFbjLJKt9BW8pmsYhtP4fDDFAv1bX0mZ8n6T3Sy18iTad6+eCndbKYa38/HCt4umF1ALfbPwnHQS1HzT44CNaHkwZ7I/ZP2jxpBxlAmk6ls/34jdfsdV1ZVcZG6+FULFww9KFChT3UReZO0DvXXhtKe/NuQQcP6fEiDyzCxDke6sUBQulyZvg3Ps3vniTvkfTb9v7jkv6Aspf6g8qL0Td9Gu3eWMGuN1NmAagrHtNVpmjh8WNvXFQXWB2hMjzAVL32iiPH7f93FROnNI4P7fuhcqzfe98rved+BqqDgwwwqMaEreBFXizCsyxJ+shHMhh+7GPSIEmPHmkyySrmaBiqKJVnYHM4QLDnEQMoReGFrS21//xhSV+av/wP/qT06vfp/k/8uPTht/S4rXm4v59Z595ezo0+q0J9nk7z/1HJuQeAELsm4ULzeQC0FLZId6pIOi8GcaK2UK2NtTvQ8OgSfE84ixR2YQKjN9RVeTn3jqTNYajpbJs6an/PkbI9igXUGapve8Bz+KIAoXQJGDZN88+f8rWWsb6maZrflPSVl56Y0gclfb0kjUajyw69UeI2IM/rLVPdnBnAAAi7QHyfjdpeT+wcPNJMILIQ8FbDMgnbuKMAS8JK7uzERMfWNp9nkCIOcDbL6ufeXnhozyOq58fSeF2an5wzq9Q6NwhpYf9jwPCsDra5NsggOGrZGX+abkh6r43IjvTyl0mv/pw2Jm/pyGyOIwu3kbKafWdvIE03c/8O8xLj7BHVeDrN4zCdxv0fz8MkQNwhTiG3V2KCKGtBAkKAICaMRft7UdQDNgmLw7bsWsG557+1FZ4s8oKIpjFRBA5jt+S5QlV2ILxt8tGPflQppSP76EPs9Pnp2gw/Hfm4pM+y9/eVa5++o7Sdfb8k3b17t9knleAWyELBAAlsxomCOushD1J4DmEKlSLNCyHMxlPzfNtO2seGxOoPY9iT9PmvRDmt6TQzqe29PNMXi1oHB5lpLRbSziQAcTCIIgyoieelZqCUg4HWtiYZGCWNZkcaLarz80l9A1wfPspt7u1J93YzIG62hVvXt4bSgn307tko/H7p/n3t7v7f5/Y/QI0uLRa5XXT6ZlHp4OAiO8ULvbvbtSs+epTH4KwK9Xs4jFhGxnoyySE323WUwcLORzwgHmZAEcdZuVACoEQaeHzqY0nz9kdG5WVLUBY5ABNwxkZMWS5U5NvoPX7jjTf08OHDzWXfXScY/ktJn5dSekPSv5P0jXrB1OJlgjHcwxrYsQ4Gt6NuMv1IAYDkr5K6B7Nw2xSTB/YHy/T9VPBowwzWdB4Jc84yThfS4X6lrd2h9vbq80wOqZtiNxxGia7JRNLWtjRca12yxzp5dKT1iTITW5yc69ukxR3NpNP9ACTA6d693KfPeDXbF89L/n+i0r3//f9QevV7pS/8auXdKhaS/oU0P9ba3h29Onj7vG4hMYL8zWbSp95caDRe6HiWHTmwOvrghWEByMetOWB9LNXDsCF6/jULWjVvwbD1gFCfECAEzAiCxjZ8Zt97MD2/LWFTUgaxNxWMjmeGfuCB5nf3akMUjThQhNTcRmZ4mVwbGDZNU6WUvlPSP1b+Hf9e0zT/73Vd/3kWbIce3uChM4Ci1M0kccO3peV2NvPB04htiq0gpa59ke+dfZ5WOYgan8eDBxkMXn+9Os9NlvL3hMDMZjrffAnAWqtraZER5ezgSG++mUFvd/fo3L4oRRrcfN7NNJFC7TyeS0eHGUz296WPfzzY6ef84k/o9dd/Qp/5Jf9V9l7PT6SDt6X5sdKgtU8uMqh53OBiEd7l2SzfB7nN2AqlDHZNHVsJnC6CLRIszvakpPe9+WZOz6sVjpe1WT4XGzGhNgCb24Jre2WrzoniXK9GJAVT9DAtVPO5YmdGwI5g8ENlZ57Hs75o8o5gmFL6J5L+k6Zp9tv3dyX9g6ZpvubdXqxpmp+W9NPvupcvgOBdZgVHfYGxEXxL+hYqUxmG0yjUqrFiq86FAgyxSeGh9kBsMlxGyoB0PIuYvscHAXZbW1F4ddw6QU7NXnYyD414r358Xmvw6DCYnhShMvN52P/w/ErBNHFIz+fZByPl/nzsY7k4wkLSv/71XEF776c+qfH4k9rby57vV17Jbezv5/uZTPLGUa4C46hBKOTw4EFkn7AhVVVFP0nN25hm2yNASdUdj08cGGqtq1s78MT+j1YghWrrW3kyaUvAwq6IdkB86cI+RwihARgJ7C8daS+SXIUZ3gMIJalpmk+llF5ZYZ9eWHE2wP+JE+SPysjEEPreFkyYw6INjO3YEdX+n2wS1C0pA+GmpDtWPAEbIBMb1Xg0zmqrFJ5g7HyPDzOLe2kvQMbzlckRRgWdzzPwSFG8wbM6SPcj5IVzfkcRtPw7kkZzafKJfJ9bH5Pu/7r0+Z+f2yRjBWA+WURWyv5+MLqzuptihx0wDaLCzZ4ViSAInNAd+id1w28A31nr1PCsI34jPsN84RuG4QXmWSlTO8vSbGd2HIsr5hFA122DLyoIIlcBwzql9HrTNL8lSSmlz9anEXTdy9XFw2twcvjnbucDyAjIdjWpVqhJXhpM6qpRvJciZ9mLHUhdzyrgRHkrcnfxAONlXR9L82nE4PG5Byc74J07NFoAcbAixW+xkA5m3UBlt7fxSoUfHUrTj+c2Xn01GOdp2zbeavpGzCHXW59kxwhAOp1GSA/jg6pPoVopgE/K9zqZxP3R99Jry8LmixZmEGf+/P5lsL6n5vG7whD9eMDW+/GiA6F0NTD8LyT9XEqJUJuvVLZQ97IiYZL4/90pQoodteywHzkDZEKRlTCUdLc9BpAFDAEQKRgEecLjcRcQAAtJ55VbiDVk/2LYZF1nh8WDBzovh0XaW92qzNgdaW82y7UP8dCS9QGQHB7mSjBMfLyqEwWw4BkFEGdvSS+9JX2xpC/4gqideDQLIMcmKkXw9WicS4GhIkvZibO7m5nheJzv5+2DCLKmjuPJoutNXx/rPPibBYpbZ+dE/w3V3gdaAIAPeKEZsGhKEZTv3mcHQbYKxTZ4m/Y8fhryjmDYNM3/mlL6Ekl/UHn+fXfTNA9W3rNeOnFfTCC8jFJWD5kghOSw1zGrPnZCQNHrJHIuMmjPJ+tjNM4ODeLqAD0KIUhd9uOB03hUmzqDBQUPFovuJk0wKbJNqio7HR4fRngOXuOHh2HnQtjrhdhuQEMKNvWW8nn61wFOeMdR1x88kN46aD3zbYzk9lbESnKfmAo+/vF8z5QcI9prscgAizrNouB7Pm9N2owjY5GPFhnk2TIWEGMXPK9xSXEHgqV9oSSv2PdeZoEgcoGy/bcxdOb3Ik8Ew5TSFzRN829aIJQiJvD1Vm3+8Oq71wsPMjYeKorgecYDuavsLMGxAgDShhRq9KFiW0gpQHQq6RVlh8Nk0mYvLLF9pVZFptI0WRjYA/240TDYn4emeMUYXvFQ13UGqpN5xC0eHOZ4rJm6xVGl8ICyIRZsETDcV6SYHf9KdrrsFbbMuraCGW1/14ahVhNQ/rsPct+kXLHnM19rc6PvtaFHLds9rfIicNTmNpPuB5jSJuaA6pF01I4FTizYPfdMmS32PXZblYdoLexcbIZoCeX2sb2EXMYM/4KyOvwDS75rJH3VSnrUywVxxwp/FHjgoXfWCOvzB75WFA7lFVBhF7uXJb1+P09aPKCwsoODUB/JHz5dZBb35pv5GoSgeD6vWlBdaz3OZ+OwFeJskcJDi5pd1xkAmcgzxabpMGHY4KL9HMGrSuks4uoOJP2GpEf70iv70t44HB+wXwocLBYZyN56K1RkHEB4np3Zbba1+QHN04XOUwBRl7e2QiX3zJRz+6S6+5IAZpgyCH8i3AqNARAvw2pghYf23W3NLHkaclk6HnbBr22axjUTpZQmS07pZcWCvYgwHMDP9zR2NRrhPcyQc5GJMrPcmwR7oRp1qSICHINBFEclOBl7In/UE5QCKHmP6khRBrb4PDiQfuetvLfKvkIdhOkNlGPjSFHzB7EMSmZBQI0EPFET9xfSZCHtHUq7O+G4kbqFF0bjqEBz1nqO2RbgdBHhOqjBFJ/Ytu0EYICHh9kbvzbM7HprqzUf1NHXdWXgd6eWFDvcuR1wqG6eujvSCNWivmXPBi+XqzhQfl7Sl1zhs16uQcqAXCYGqz4Tn5gyWFJTnAOjkIo9V9rGKWDg1aRPFln1g+mkQZ7UgMCgQOGmjtp/hLRIGVx8y1AHoIMD6VGVS1Z5EVJSEIcKR8BckbYGSOCAqNRVIxkTvuNc7HOnB9JGq8avDaWdRcQMrg2kqu3/2iBAcq1dKE4WAXiYAdhoqlMctrWXziRNqqxew0K9BuVQkWXE71M+Ay5sDYFDzKMR3G7Yy+Vymc3wVeVKMxsppS9WzK8dxSLbyzOQMsTG2Q8qMz9WWdQBhsSPWCszkTNlMHrrrQgj2d3N9kNiCd98M9cQbOoodYWjwKtAo1aiUkqhDuOlPlWAR11nlfTwUPrYYVZlKQZDXBzFJihJRin9E4U9zReKsnJ4rQBHZ8rHkj7Vjt+obve0rqT1NiNla6vLdgmk5h7Z1vSsDtCvqq6KLJnH+lEGw6m6qvNae2/EfuIEIl8ZEPd78+eA92za1McPvnu5jBl+jaQ/pVxQ4QcU8+tA0vettlu9XEXchrgvnW8rSdkt6iRuKiYY9qepoqI1G9tLoc5SpYbsk6PDCEx+8CAzxNNFZGdstoB4Vmf1j2IFOAto92SR23n4SHqMo0IZBGbKjJDQD3ciHCtybQE1j6tz7ygsSYoQJQDQd57zzdA5h2KpzUx69LHc193d7CzZ2YlMkvE4s77jRdfuCTiSIki8JmFDs/ZaeONxLo0H0la7CBGUTY4wlYTKsk84w6g56HbDPmTm3ctlNsMPSPpASukbmqb5yWvsUy/vUvAUMjlQJ8eKGnZ37HiKNxwr8lyHCsbjMYZVJVWHUbNwPM5xdI/fjBAZ1MnFIirXoAqTandctx7uw8zo9hUAN1F369TS5umxdACiq5NUd2a/CD6XonjFyD4n1hIwxNRAu8TgTRTOFhwtHmNJIVtYse+8N5tF3UPsgvv70nC/9WxXUrMfweauZjMGFPYd2v3DimF/eIedHfYg+OnJVWyG70sp/dMiN/kvNk3zX662a728G3Hvo+ewEmBNJW2PWdxQeCgrSQObmFJMYDy/JxY0jSeYcJPRMDys43E+5sED6bdmEdoCCM8UHl4M/AsFIG4owAm7HnFyTHTPniErAy8qTpUzBRD6tgmy9jA1MIauQnPsqaTBr4enGZB31ouazLid1RkEX3sts+bjWTY37D6QDufS+jDbDM+97mo90Qud70KIaryviBJgzFCD+awHwN+7XAUMv7ZpmnO1uM1N/mOSejB8ToWJ4RkZnpkCG9tVZoVbCrB43BZO2N2NoquA4b4yuGxLmlKiatHa9yppOO8ylH2FIwTnBsVkKVRAqAysbty2v61w8BA2gxMEcKPPDmoDBSsEMHl/rAy8qOWe+eFqpgcxV8pg+KakR2/G4nHnI2FPZV8VKRge3mc2kDptPe3ELVJZe20o1YQwzfJ4ebxkqQaXdsJenp5cBQzXUkrr7TahSim5iamX51xKZ4sUE2miPPFmdnxSO7H3dV46vqmj6Od5sdF5qJQE8eLp9fp4sD4pVD/i4s7smpW1Q9+ozu2VeWC32AtLT6mDIZtdka74WFERaF3dXQA928cZIm1SBAOgbCTVb2VWSDgSW4sezQIIHzzI7M83kzqtunnch4fS2/PsyHE7IdcsGWCvCq9GrgKGPybpn6aUflT5GfjTkj6w0l718lSlnDxMrIky61pX1NRrlNPCHtTSdBFhHafK4HbSnnOgUGFxCozVjXFzI74DFqCH/Q/HAOBJpsXQzveN12mvbvt1om4gNmWMj9Xtv6u+OJpQ3fkcIPRdBAHGE0UYz1zZ9vnWvnR3X5q2YTTzRQbdRtKjWTidCCJ/1J778EHkmO/bX6Vgv4wlr72sVq6Sm/zXU0q/KumPKv9Of61pmn+88p71sjJxYMSR4JOe8IxlAdx4owEPAMqrxSzUza91MMbZQ4oZDh7PmKBfFK91RgQo0tZJ21ccKlwHkAbcON+3ZkUoagu4Eo5E0VzGhnusFez33ENfBbBVyvbPmaT9FoFh6KjA2AF9vHF+YfN0u2gvq5crjXXTND8j6WdW3JderkkADi8eW9nn7oyQAmCoaEP9RFTjEjQ9+FmKrIpGXVAc2HcAjufRntr5AB1qNm3AmAgnGSgz17ky4NR2Ptur0majrgq/VvwfT/WBurUA2V2QtlgcqJLjzpoHCrbnVYVYNJw9e2YJ//dFqpfVyjuCYUrpD0r67yX9+4oSekdN0+xcemIvz7WgUm4rgwLhGR5qUoKhq5yACEURYIdSqLKkjxG/x7lslC11nRyc76yTNLw1ZeaUlG19DsrY1DgWlbgEGkDXMzPo75pdhyrggFujCFJnEYA1DhRFVymOkawNzvdahTBVVHyya3xxYVwcIHtZrVyFGf5t5c2bflx5U9pvlfS5q+xUL6sXj9OTumlbzkh8tzYcD+5wwbmxrm59PLfDAV5l6px7cWFux9YGNf8AFhwYUqjLqLTudCGjBk9zbefRL6/niIcYsPTFoVJkt7ABlztpSAv0jBH2pvaS/V4zslR/fctONwm4h5zx6mV1clU1+TdSSmtN05xJ+tGU0s+vuF+9rFDc5sZ7VE/Pe3avqucvl9WYpciPLSds+d43Ki/7kawd//NUQgDa7ZBewZu9PryCDywW0AUQXd129uV2SswJI/uO13IbT2yJp8XxbvtEvfb++g54Xn6rzJ7pZbVyFTCcpZTGkn4lpfTXJX1S4bDr5YYKIHGq7MTAE+zxaz4hXa3lleKwc13cUsC9xxwHsOGEcHWR71EZ/Vpseu6ZKnhZAR7fJQ6ASeoCLg6PZQwLICtrQE6Vs3eSYmc52qKfvBIM7aE/5ZhyLP2CJbLv9cw+53j2Ne49yquVq4Dh+5Wfr++U9N3KG8F/wyo71cvqxVkcrM8ZkquVUgDATGHXIvzjsQKMULc9CwbA5PuyuADAKnsv+562cOCovZ6HA1XqFmIA3DgPZgbwTpTtpbTHroEsEKXHulF3G1e+dzsl16P/niKIAPheaQY5UTBa7mGiDMiectfLauQqoTW/2f73WNJfWW13erkOcSO9V8Qu1bK6eO85woSoOPiVWS6opQAiwOYFSIk1VPGZM0iPiwQA3XHiaiUMCifOprpeYY9xxLvs3nUAD0kK7zRAiBfRd7TjnL12bObqbujOOACenkK4oSjZxRhyP6UK38vq5Ilg2MYWPnEXvKZpvmglPeplpeITH1ZUZjiUmSqy90zukvFwHgDjYSNsQwBoMum3lFV0QFXKwIDnGDD0PrgzBWCj0gxteFEHKZxAHn4D42O/4m2Fo8TblPIeKoc2bnyOLRMwHCir1GzU5I4oQN/BE5UbVdhrGDKmPRO8PrmMGX7dtfWil2sTJibVsWFeZb4rjKuyP84d2jmL4nPyNF3FHVr7hMBMrB28zIDzoaKe4VDZTqj2dVuhxrJ9AYAi6xPnAjzOSGGvvq9wowjJQYh39CKz9MVZMu0kBcASQI04u2ZDJw/v2VbYSwFZNyNg0+3BcXXyRDA09biXWyZlMO8yD7AzxEFxnnthqyXHu3rtxwBEHuxN4QT3EKOqerwdVaoJa3G7nhTAyjXdroet0O+fz8sCDYQR0WdXmwHt8lwXZ4ssErW6LK8MrCZ8iO0NBgrW68fx/x4QVyN90PULJCW4wZacwTh7AoykrrqHis25XuQAZ4PsuzJMZa/9nP1mvabi24r0QCqC+B7DFIJwYCWOESlBx9kXIEzfnOF56A5skq1JPbgaQPJtV6VQxbF3eukwP44FxRcKxkGKIheepeO2xF5WI33Q9QsmJWMCEFCZ3UngzGusiwwFT6fb3s7snNLrChgCnDgxNpXth3iEx8qA+YrC2UD1a69OjWq9WbRPJR1XlyeKArcEhwNOHnc4UTfomn56zKKD+kAZwDnW7a+ALtkty+I6Zcey1adn+AztnF5WK33Q9QsopZroKhwshFQzT3Urvb4DRRCxb2jEZx5LyIPmOcOkA3roC6l7HvJCcQPf6U1Ff2pFwQcpHCx4oblnrsW9emEEqevxdsbmcX+wNTJvvBoOfXOW6fUXuQ/UaZijl0KTtTFUzwavS/qg6xdMAB3S0byMvtsS8fAChgt1PalSV3VbZjtr7DiuTZUcjt+0NnDGsIHVAwVQc7yDGeftKwOJOzecPbJlZq3svZad77F+yxYHj/lDcJTsKyYCgd7YNFH93ZFUVuEpnT9uV/W+eZ96YFydXDXoeqA+6PrGC0wNFXGq2JFNirg5QMvZEZ8hMC3i+TjP4w6ZzDA9d7QAyMfq5hGfKTzSqLqopvxhqyOEZ19dtdiBUPZ/gH1DYXfkXjyecZmZwJ0yXPdYXYeLA/bL7SuluWZF2/QR++iWultOLgO+ZcDcy9OTdxN0PVcfdH1rBFW4rO9HGIx00Rsq+9zVQBjgovhzTzDtYJN0NuaqNiBVhv2U1y9T7cocZAcOBzovMuHiXuihvZZODsCYcSoBlzFxe+mZteFtu0oPQywrA/VZJ9cnlwVd/wlJ95um+Tvt+19QXvAk6XuapvmJa+hfLysQ2JrvnYwNC28oNj32CYFVTRWVYVCxYUSws9LzzH4nbrcb2zn0x0NaBupueuTbhnIPlX1ffgfLchvjQuGA8Swc+uvMUOqqpoAVCwjXndu5Hl5ENRtnrb4gcP0tdYPEtxRZL86Me0BcvVzGDL9H2YuMrEv6/cpmkh+V1IPhDRVnTYcKDzAMj4m3prCJoebCJN1G6OX7fdL6jnjHinAUAozd6+thPICSFzlwW6bH53kQt/eH0B8/z1VtBFAaKAMYYFZee9yOBXUUGT8PhGYBOFPez4TcZHckwfZwymypa2KgLY4rnSq9rE4uA8Nx0zS/be9/rmmah5IeppR6B8oNFoCGEvVSTE53drjKuqnY2e7YzhvYuXhWZedW1hbeV98Q3dVAAqsBBX84y4BuhGt7cdSt9rsDBQuTIpsFZufqPx5r3pfpiV6Ygj9XvT0YnSIShPBwbdotYwcrOx41mf71NsLrk8vA8K6/aZrmO+3ty+rlRoo7EzwG0FVXz98lQ8RDXdi60osP1IqAaA9PkbrsC/Z4am3glKAvAIKrnaW3W21bMCuEfVXcY/4kdgjo4m2GZZaTwr3rh/ZZKW4LrYvjaIOxZh9rNpnieC8GUHrre1BcrVwGhr+QUvr2pml+2D9MKf05Sb+42m71skpxzyd5ylROKT2oqGuPFZMTsCS/GbuhZ2QAMDhqcJQwuYm3K4OSKZBAfnKZvUIhh8ralIJ5UsTBS2p5fcQ1BQDx8KPOugru9kSAi3uiTcBvYq9exotQn9L26CzXFwUWJHf6cGzpIe/l6ctlYPjdkv6nlNI3Sfpw+9n7lDWd/3jVHetldbJsYpblidxDW6qLrr45sJaqrF/HPcQOuLBC2oOFls4JB561tl/Y+Og7O9UBhF7I1dmpl8YqQ2qcreKIwclUFnHwe+Ac3/SKLU/Z68RTHfGyexv0x73PyxhoL6uRJ4Jh0zRvSfrylNJXSfrC9uP/pWman72WnvWyMgFUyMyAyWHYRx10u1lVnMtnsLehou6fx9PJrlGmt3nQN0ABkKFKEu/ooTyo1NJFJwlpga6qe3zgurqVtV1cHSU2ckfBVMtwG+6tVN/duUSfPXazjGX0uMuSFbqq3LPC1cpV4gx/VlIPgLdIUHEJm/EYvZG9HyicEV523kEEJ8FQ3XJXqN9ubwOgSrub2xmPFBVcStbIfsMwtZG14ywLZwjXBJzYCmBToU4743W7XKVgc7TpC4M7nnCuwALVHnes2LLAmbGsXVRsVHAHSC8mUWb49PL05Uq5yb3cHgF02CTe6xrCutwOho1uqmCLM3UzNJjEy+Lykrpe2sGS/3uIChVfnFl66I8HTnu2im8b4OyL/UNoG1Xa7Y701dPiCGlhl7syANrti54VA7C76k0/YLplbKQvGO5koR+Mey+rlR4MX0CZK1eBAQzJ/mALAJwLw/YzGJUXGC3jAt3GJvsOBlZWfobJeRkt1HYYm9vovCAs13TgdADiWmx05ba4g+JY7pVFAXXVmax0kRW7+uqec0DLbZWe7TNRZrcElLt9tYyjdJW5V5FXLz0YvoBSqnpSN65N6sbAIW7Ud1ZEm1J4hylScFl1Zi/F746LUgAUnCK+hYADN/1YFp/n5oB5cQ6bQxFH6DY7r+xdglKZsUJfvf4iYAxHk97kAAAYBElEQVRjxFbrBTDcTOH97AHweqV3Vr2g4owED2jpKFkrjn2SOIsBCF2NHtj/HVBKr7a/5zxPm6OclzO3koGVjgx3WizzfnN8uRf0sthE77Psvb+WDhW3d/q9+32VY+Gqfq8eX5/0zPAFFibbSOGUgGkBZjgEcGSUYObMzqtgU7vPwQQwmivS/Kric9p1lZjMFOoZyr4DcLxwA6/so+Kf8X8PFsdxs64u23RmuNGeO1vSBn1zlrqM4c0UjpipYrF5bGPhQE5NRlhjL6uVa2OGKaVvTin9q/bv51NKv8+++8aU0odTSn/+uvrzoktp68J5sq5uqAfMiqBmwG5YHFcV58wVtsZ1ZefBlp1XslGvneiMCqAitGVH2Ra4rSh75Y4PAMw/d2bqjhnvM9sNOKC5fVIKkPOtAqaKFENnw9yTO3NgiFJU+ebcHeXK2bs2Tr26fL1ynczwo5L+w6ZpPpVS+lpJPyTpD7TffaNyEYi/n1Laapqm3Imyl6csJRhKYYsrj8OrSUrewL6DHXkV6iMFYwIMnYVV1i4Myz9z5umgsqOLVYUBVUBmqCiuumzzdWdtZbyfO4DYy4XrlxNlmcfYF4hlTiO/Z9pgsWEcvW3+38v1yLWBYdM0vlXA/ynpvr3HudioGzLWy4qktJ8RI+eFX0eKvUl8gkoZZAgZIUbP7VyozWN77xs5SV0QAWhdZS5tje5d5lg/xsEXDzkMz50UE3vvoSwwXgdCpHSoeOC6b3nAhPJ9UwA9xqFk1twLoFjeVy/XI8/KZvhtkn7G3n9I0i9J+rGmaR4vP6WXpylMvpmyzWpLF9nijrobzbtn2FVHwMQnt7OfhbrealRY4g/xJE/seClsj2NFxejS602YD+A9UgZE76/bB6UIBidAnGsOFAwX4PUJAtiVqjSbVtUKMN5QVK8pS3M52HnfcOSs2XGlw6aX1cm1g2FK6Y8og+Ef4rOmaT4g6QOXnPNBSV8vSaPR6EmH9fIuBcbiZa78u1I9vMxzKl1MQ+NYj5VzOx6pcbwvnRGA5kgBUB7vV14Dh4TnB5fsCsBx4PVAaOmi99kdSt7eQhn8YHq+QGAXHRbHe0Wgcvx8Iy0fs16ennz0ox9VSunIPvpQ0zTvl1YMhiml75D07e3bPybpnqQfkfS1bW3EK0nb2fdL0t27d5v9/f2n3dUXUipldgQzAYyY8M6sECYnKjDxeY91Me7OVdEymBiQ8RQ1ABEbIPshkxtcZoD45lAAO2A3Uma2sD1nZBNJL7V9n0l6S1HbsYx1dC95WYPR0+TY9xnPN4DmKjj2S2yTrt57Op/XQ+xDa56uvPHGG3r48OHSeqwrBcN2ywC2DXhdWR1+f9M0v77K6/ZyNQGUKE6KrdDDYcrQGGdmQ0VwNSEjg+JYwMptcuQwT4rrjO07P489Rwj/KR0w3AtMFtWae/ECCDDBgbLndmr9hB26nbFWBs1tZZDyND6EVMCkyOKhtiPj4cUhPIYT2yQB5VT/fqQuW+1l9XKdavJfVl6Q/4eUkiRVTdN86TVev5clAhhKYR+EIbqzgHL25Bvj6fKMDakb0uJeVFgT1/RsFgK12fsD4DpSBhWAqWRsgDf9HhZ/JSsEpN9uz3m1veZue+zbirJgzu7W1N3rmHvxIO25Ig/bi9/6ns3YaB10uRfahRF6lexerkeu05v8ZyT9meu6Xi9XE3ceSF37l8fIwXSwt+F5ftSeV1a1dvbjFV8Qj8s7U1SywQNcxiAOis/Ka9XF+XifKbiAesznv9se73sb06bv+KdiLLwSz5l9zzUoglEp4gVLJ4ysjfJ+3Mvf2wuvV/oMlF46XktAgzg91LdjdW2JgOG8OB9nDLvdHakbdOzhOFKArMfkSV1AKO2QqNRb6obJ0D5s0nfuK2X+/7d3tjGaVuUd//1ndpdh2AVRqEEWs0uqNbRRS6FFoXEDhtBW20K1Maak2FRrC1ppCJZ+kg9NaGOtiWgxxZetYtQqsQ0loC1CW6XoQl0GBIl1V0tLRIq6uyzrsjNXP5xzcV/PmWdmZ5aZ52X2+iVP5n6/z3l25z/XOdfLoSza5LnU3iefv4uluPy5ce4wCm37XcapBW8z4RnrKPOZHsYTvfRZsmt4pBgmQPdL70K2iTKn4cPovXTzXvGXd6o55gJ5PF29wTi3FwXVf/H9WXFZ0rbAQ7SaIv2CnefoXbQ+ipmH9jjPhE+b7RFDjdyS8/jKtgJ4FMHjw3fZhsf48Ql6pw28z3vIFfGGRYph8izxl9brGvrQ2HON+2WPtKEi/iz/zxXn1qIXNjoI4lC3FaU2SwU64VtPb0GJOJRu4x79OTGEJVbBaa3QVsii9ze2OX4XbapfJH4Hnrft7/a4xrhEaTJYUgwToPvF3UeXRxxj++InCkvMuPDnRMspPr8VqygOLghRaPq1z4e+LrALFXWFXlH16z0n2Evxu/c3OlmiR/l45schztE5itq0u7h4vV/r31cU/lm6obZX/85KNcMlxTABOkHyCtgxiDim2C1kEcYV7mbphp79LDPoHfa2ToSYDROF0s9Hb3dckS8KZszzjX10R4+LYCs+E3Rzkd7mdvganTo+LdAuMeqiG9ePjoVmD4Sf/eIWk8GTYpg8i/9y/ojOunJLJw6B27hDt7igywt+huJ0ifm//RwkcUjqtJZUK5bxujbur5/zol/At8fzxXlSD4U5ic7q85AZX14gDvHjHwx/l/fX74l9mGie0YphDo2HS4ph0kMMwnbrKM6N+TVxyNsWKY2i2c67HWrOE867mEw198fYwY3hOXHoGkVvIeLcYjtf6R/3pM8113mprb30enz9ev9jEB040AVex2mEVqxbR1IyHFIMk3m40Oyjf4hIOyT1lfbicReWKHQuolF42lg7pw1R2UgnSJ7hEesPEq5vHSBx+BnF0q3BtnTWj+kNHfL7jqMMr32ez8XQ6yp6OA50sZiE+30dGZ/n9DVZcng8GqQYJvOIVlqM34P5llcUrNlwPNZha2MGo+OkfVY7XJygy9t18ZoM59vwmXhfDLeJw3n/xGraMbD7aeZ7df2nvz8Krvfb2xUt1FgKzD30PtcY4zST4ZNimPTFPZw+xPO0N7f2ohfZc2pdGOI6yK2Ht/U0x9S99j+ji4pbhMfSzUmuo4hW9NpGB487dOIaKP5Ot+aOr/teZMLbBr1CeIj5az3HpVEP0M0pEu5xx4u/14f4s5TMnf2U+dkUxNEgxTDpi/+Sx6wJDyfx3GTo8nGfptc6iw4St+igd4jp533IHJ0y7TKah+o7XGjjcNufEWsAehkvz3iJ83/Reyt6w3PiPKD3w+/z9aIJzzxE5zGO391BOrH2OUR/7x7gCXqrgyfDJ8UwWRAXABctF4k4HJ2jd9GiKIYej+eWndMWOPXPhvA8t0qn6LzTLlpxnjGKdRxixxCeWOorLjoVrcrj6Iqq+jFv46Z6LIYKeTv8vfvopgbci+xDb09t9NAlXzc55wpHixTDZFHi0DMWV41zgLH6dBt/6HNsnpo3SRkuxqyUODyNzhY/5+E9/v4ooC6W7TzeBF0lbb82Fk6IMYe+bvIknTXn57ymomfhtNalz0v6dzBFN2RurVcPW8qh8WiSYpgcFheOPXQCBJ0IxIo1cW7QLSIXgjmKF9jPt2Lgz9lAmc/z+oT+aZcPiGuQeNyfwrNicVpvl1u20SpbR5ceFy3OdRSL0bNevIiDfyc+NxnnK6Nl6rGKPjR+khTCUSbFMFkSPqx0YYme334B01HE3Hrql4I31zzTw0/aZykcg95MlNk+z2pjIeM8I/S2O877tcsQRPGD3tJeLobtcJ/QDxddD/KO30EyWqQYJkvCf6Gjk8GJThDPNInxdxG38KIwuIC4t9hFyENVvGRWDFj2vOHpei4WWyC0oy2JtSGci5agV7H2VfWgszh9rtCdRTFMZy7sr6Mr/x896u5VzoKto02KYbJk3CPrv+QecuPiFCtjnwicQFevDzorC+bnBMcCs63ldIBSF/EAvRkfcX3kScoQ1EXIi9C2z4ZuHtIF+RBFTF18J2u7D9b3+nB9gt61WDxWMfbD++gC+CS9hRiS0SXFMFkW0RJySy2m7blAbKr7P6Y4JXyY264FAp3QeJWcqeZ8WxnGnTJebMG3PZzGxStmuLRzgbHijM99Kjwj3hOr0bTFHfqlAHox3GgNphCOPimGybLpl0kShc0dEgfo4g+hC16Ow9243rIXTo0eX6fNFvE6hNFSjSE7vkaJW68ueE5rmR6iWIPRwz3XPCOuIR2XE4jfiR9/giKG6SwZH1IMkyMiZl/EY24pPUU3vxZT4qKH11e7g95CC9G54WLkVWBciDxND+aLk2fF7K3nfXW9GG8YF4qPpbXaeczomInPdw/5IXqF1QVwTzifjAcphslzwoXOs1V8DjGKWnSYxODs1rMaQ2AiXpla9OY8RwswDoPbGMYNzX2t6MX6jf083IR2t+LmfYpZLTEFMBkfUgyT50w7h+hluFyU3AqLWR1tuMs0860ztwA91MaXFH2GXvGL7YDe6jq+cFQU2ijCMYRmLtwbh+u+H8Xch937mr7FqtnJeJFimKwIPl8GXbXsdhnPmEccPc8xLMctq1h8dZrimZ4M9x8AHq/P3UCv+LQOkBj6Et8f276eEtoTj/uzPJ4QOgt3f/jEFL827jIZH1IMkxXDrTnoFTqvRxitNOi11DwDxK2+aKU5LmJufe1vzsXYR7/XrTWPfYxiF625DXT5ybHyTszNjkPgffQuCJ+MPymGyYriVlEs3eXhNh6bFzMzogPFPc+xyEMcJrdWV/zPG/OA/XnR2x3zpqPTI76fej7WZfS5RBff/WE7hXBtkWKYrBpx2BjDTNyL3M7PuZcWunAWd55AZ5X5Yu8b6fVWx+F3FL/4TG9X3Pfzz4SfsbirD4vdGjxICuFaJMUwWXVioLaXuW8zQjyOMBZ6iJkt/oyfNPf48/28pwq2oujXOf3+47fOkRi/GOcHM794bZJimAyEg+HTWm0ekjNHb3B1rKPowmR0RRDcC+wWnq+JQvMcwv1OLCIBvU6bg/RagDFUJh0ka5cUw2Sg+NAy1iX0/QMUUfSK2p6aNxmugSKIbmm29RGj1bm/2fc5S58HjKIWRS9WmGnnFpO1S4phMjSilRUDluOqfBvorUjdrmTXhsm4wPpz2swU92ZHkYsZMnHb35McHaQYJiNBDKfxUBgfTu8J+zF1Lqb/xYwW33cxdNbRBXJHMez3SY4+UgyTkSMKUrt2cb8qMRPNfX5NmxIXM0jmmp9JkmKYjDxtvGBkos91C9VFTKsvWYwUw2Ss6Cdwh7smSZZCvyIhSZIkRx0phkmSJKQYJkmSACmGSZIkQIphkiQJkGKYJEkCpBgmSZIAKYZJkiRAimGSJAmQYpgkSQKkGCZJkgAphkmSJMAQxFDS2ZJmJb0hHHuTpPskvWvQ7UmSJIEBi6GkSeAvgNubU28CzgbOkbRxkG1KkiSBwVuG7wA+DzzeHFf9aWE7SZJkYAysnqGkU4GLgfMpVmDkZmAH8Ekz27vYc4455hjOPPPM1WlkkiRHLYMs7vp+4N1mNiv1Gn9mth3YvtCNkj4BXAJFDDdv3rya7exh165dbN26dWDvGxTZr/FjrfZtkP2amZlB0lPh0M1mdimAzGzVXizpcuCtdfcEuiHwSZS1ed5mZl9YtQasAJKeMrPjht2OlSb7NX6s1b6NSr9WVQwXfKn0ceAWM/vcwF++TEblH2qlyX6NH2u1b6PSr4wzTJIkYUgLQpnZZcN47xFy87AbsEpkv8aPtdq3kejXUIbJSZIko0YOk5MkSUgxTJIkAVIM5yFpUtJ/Srql7r9I0h2S/mFcUwUlnSbpy5IekvSgpD+ux9dC3y6S9C1J35b0p/XYWPRL0pSkr0naWf9drq3H3yPpfyR9o35+tR5fL2m7pJn6b3lNeNY2STsk/eWw+hNZbt/quZdLurtePyNpqh4fTN/MLD/hA/wJ8ClK6A/AdcDPAq8H3j7s9h1hn04Bzqzbm4BHgDPGvW/AJPBfwOnABmDnOPWLEne7sW6vB+4BzgHeA1zV5/o3A5+u29PAbmBL3f8McCzwV8DLxrBv64D7gVfU/RcAk4PsW1qGAUmbgV8DbgyHJ4G5+hnLvGkze8zM7qvbe4GHgFMZ/779IvBtM/uOmR0EPg38BmPSLyvsq7vr62cxj6YBx0laRxGHg8Ceem6inh+JPh9B3y4E7jeznfX+/zOz2XpuIH1LMezl/cDVlC/duR74MPB24JPDaNRKImkL8POUv9Tj3rdTgf8O+4/WY2PTrzot8w1K8ZIvmdk99dQVku6X9FFJJ9ZjnwOeAh4Dvge818yerOduBL4KTJjZQwPswoIss28vBUzS7bWc39XhUYPp27DN6VH5AK8DPlS3t1GHyWvpA2wE7gUuGXZbVqg/bwRuDPuXAh8YdruOsC/PA74M/BzwQop1OwH8OfDRes25wE0UK+ungG8Bpw+77SvUt6uAXZRU3WngbuCCQbYzLcOOc4Ffl7SbMtw6X9JIWxXLQdJ6Svm0m8xsJIJcV4BHgdPC/mbgf4fUlueEmf0IuBO4yMy+b2azZjYH/C1lOgDKnOFtZvaMmT0OfAU4aygNXgZL7NujwF1m9oSZ7QduBQZanirFsGJm15jZZjPbQik2e4eZ/c6Qm7UiqJQJ+gjwkJm9b9jtWUG+DrxE0lZJGyj/bv845DYtGUknS3pe3T4WeC3wsKRTwmUXAw/U7e9R/khL0nEUh8TDg2zzUjmCvt0OvFzSdJ0TfQ3wzUG2eSjpeMnAOZcyhJypczgAf2Zmtw6xTc8ZMzsk6QrKL9IkZcj14JCbtRxOAbbXCvATwGfN7BZJn5D0SorTYDfwB/X6DwIfowiIgI+Z2f2Db/aSWFbfzOyHkt5H+QNnwK1m9k+DbHCm4yVJkpDD5CRJEiDFMEmSBEgxTJIkAVIMkyRJgBTDJEkSIMUwSZIESDFMFkDSCyV9StJ3JN1bSytdfJh7tkh6YLFrFrn3MkkvCvs3Sjpjifdu85Jrq4Wkr9afWyS9+Qjuv0zS9SvfsmSlSDFM5lEzVr4A/KuZnW5mv0DJ7ljNBasvA54VQzP7fTMbaAbCYpjZq+vmFkpaXLLGSDFM+nE+cNDMbvADZvZdM/sAPGsd/VutLnKfpFe3D1jsGklX1+KdOyVdJ+kNlBzbm2rBz2Ml3SnprHr9RfUZOyX9y1I7IekClUK9M7VCyjH1+G5J19Znzkh6WT1+sqQv1eMflvRdSSfVc16O6jrgl2s7r2wtPkm3SNpWt98i6RFJd1GygAjv+bykr9fPs+eSITLsihb5Gb0P8E7grxc5Pw1M1e2XADvq9hbggcNc8yuUckzTdf/59eedwFnhHXdSBPJkSpmurfH6pj3baKoMAVP1vpfW/b8D3lW3dwPvqNt/RK18Qyn9dU3dvoiSFnZS3d/X710Ui/b6sH9LveYUSi7xyZTCs1/x6yjFg8+r2y+m5IwP/d/9aP9kbnJyWCR9EDiPYi2eTSkhdX3NMZ2l1KJrWeia11JyavcDWFePbyHOoQzXdy3xeudngF1m9kjd3w5cTqlZCd3ylPcCl9Tt8yjFAzCz2yT9cInv6scvAXea2Q8AJH2G3u/gjDIbAcDxkjZZKbybDIkUw6QfDwK/5TtmdnkdLu6oh64Evg+8gjLVcqDPMxa6Rixe8bhludfH+xbjJ/XnLN3vwZFUUT5E73TTVNheqN0TwKvM7OkjeF+ySuScYdKPO4ApSX8Yjk2H7ROAx6zUpLuUUjGmZaFrvgj8nqRpAEnPr8f3UtZnabkbeI2krc31h+NhYIukn677lwJ3Heaefwd+u77nQuDEPte07dwNvFLShKTT6Orz3QNsk/SCWkvyjeGeLwJX+E61npMhk2KYzMPKZNZvUkRol6SvUYaZ766XfAj4XUn/QRn6PdXnMX2vMbPbKDUHd9RyYlfV6z8O3OAOlNCWHwBvA26WtJOyOFA/LpD0qH8oSxu8Bfh7STOUpRxuWOBe51rgQkn3UeY2H6OIX+R+4FB15lxJmQvcBcwA7wV8rZnHKIsf3Q38sx+vvBM4S6X0/TcpyxMkQyZLeCVJpXqbZ63USXwV8DdmllbbUULOGSZJx4uBz0qaoKw899YhtycZIGkZJkmSkHOGSZIkQIphkiQJkGKYJEkCpBgmSZIAKYZJkiQA/D9jVMmUmmdrZwAAAABJRU5ErkJggg==\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "images[\"excess\"].smooth(3).plot(vmax=2);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Source Detection\n", "\n", "Use the class [gammapy.detect.TSMapEstimator](..\/api/gammapy.detect.TSMapEstimator.rst) and [gammapy.detect.find_peaks](..\/api/gammapy.detect.find_peaks.rst) to detect sources on the images:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "kernel = Gaussian2DKernel(1, mode=\"oversample\").array\n", "plt.imshow(kernel);" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['ts', 'sqrt_ts', 'flux', 'flux_err', 'flux_ul', 'niter'])\n", "CPU times: user 967 ms, sys: 177 ms, total: 1.14 s\n", "Wall time: 9.96 s\n" ] } ], "source": [ "%%time\n", "ts_image_estimator = TSMapEstimator()\n", "images_ts = ts_image_estimator.run(images, kernel)\n", "print(images_ts.keys())" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=2\n", "\n", "\n", "\n", "\n", "\n", "\n", "
valuexyradec
degdeg
float32int64int64float64float64
21.387252197266.42400-29.00490
10.282207204266.82019-28.16314
" ], "text/plain": [ "\n", " value x y ra dec \n", " deg deg \n", "float32 int64 int64 float64 float64 \n", "------- ----- ----- --------- ---------\n", " 21.387 252 197 266.42400 -29.00490\n", " 10.282 207 204 266.82019 -28.16314" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sources = find_peaks(images_ts[\"sqrt_ts\"], threshold=8)\n", "sources" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "source_pos = SkyCoord(sources[\"ra\"], sources[\"dec\"])\n", "source_pos" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot sources on top of significance sky image\n", "images_ts[\"sqrt_ts\"].plot(add_cbar=True)\n", "\n", "plt.gca().scatter(\n", " source_pos.ra.deg,\n", " source_pos.dec.deg,\n", " transform=plt.gca().get_transform(\"icrs\"),\n", " color=\"none\",\n", " edgecolor=\"white\",\n", " marker=\"o\",\n", " s=200,\n", " lw=1.5,\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spatial analysis\n", "\n", "See other notebooks for how to run a 3D cube or 2D image based analysis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectrum\n", "\n", "We'll run a spectral analysis using the classical reflected regions background estimation method,\n", "and using the on-off (often called WSTAT) likelihood function.\n", "\n", "### Extraction\n", "\n", "The first step is to \"extract\" the spectrum, i.e. 1-dimensional counts and exposure and background vectors, as well as an energy dispersion matrix from the data and IRFs." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 4.67 s, sys: 204 ms, total: 4.87 s\n", "Wall time: 4.86 s\n" ] }, { "data": { "text/plain": [ "(
,\n", " ,\n", " None)" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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H2tAc3o80vBHZfcOHkdpfg70gptJ9Swgxy5Cqm5DgVlTid1Dpf8RIexwj7UlU+p9Q7hmI7y2k+idIOLaih0gs2VPCgIxuzMiLrLjBYbPx0LSLKT5eQVEMxRhL9pQyLTefOy+azK/Wrmblvr1n/dBR2eDl3mVLyEtL58pBVu/Km8aMJxAO8/DK5ZTVN52QjtTV8uD7y3DYbNw0djzTcvNYWBLdzA/g+Q3rGJOTE9UMzlCKSwcMjHqmqbU8/QysCxNpgIY3rOVBW0+U8wJQvawmt4H14P1fcE1BjF7nchcwsiDwCeL9ByR86azPpMSsQWoeRjnHoJyjAaznXymPgO8dpOZhxNbdqoI80Y1eAh+DHEe5ZkHSzZ9tfFaGB5LvQWoeALMSEq5pdDP1Z5uV636P8nwFCX4E4U8hhp6IEtwEwU9QKQ+hnCPP+HOlnOCaBM6LwPcmUnMXpDwa1TO+iOIQYX7xbn44ZnxU47ISExnRI5vnNqzjV7PnRTzOHwqxZE8JT86cQ8/kZB6cOoMn1qzktR1bmVcwkIl9+pLkdBIyTYqPV7KgaDfrD33K5QMHc93Q//SndNps3DVpKn/fspnbFs1ncLfuzMzvT/dEq6L0SF0d75UWs7uigksGFHLdecMxlGLugELuWLyIKwcNIcUVWaVgpdfL2k8P8KfLr4zqewRwUd9+vLjpI47V15OVGGO1q3bOdALrosSsQmoeAlu21SXjc8uDKuFyJHwMfG9ZiUxFX5UGgFkGRhoq7efWht/gTki4BBwXnFbhJ2Yd+JcivretzvCer54ej5EInmutZ1OBDRAuBbMClAfl+eIZX++zcbYsSH0Uqf8LHP8euMZb3TNUMhCAUDHiWwQqAZV0M8o5CoxUpOGfKPf06F5q6DD43oXUZxpNXqfFpRQkXAESQuqegpRHWnQT9M6KcuzKYEhW9DPnG88fw23vvkNJZQX9M5pPrCLC/2z+mPOyutMz2XqGlJ+ewXPzLueTo0dYULybFzdtJBAOo4CeScnM6j+AG0eNbnTTsd0wuGHE+Vw79Dze37eXd4p2Ue23VgPS3QlM7pvLHRMnn7bkl5Ocwsz8/jy0cjkPTJmBp5kqwVq/nwffX0qKy8WontF/QHPZ7fRLTeVwXa1OYO1IJ7AuSKQBqXkI5TwfEr7S5BunsmVB4rcQWy5U34kZ+AjDOSq6m/kWo1yTUEY6pD4C/tWI9zWQPyL2Aj7rRh/aDY7RqKQfoxyDmvxyStnANQ4YF3EIykhBJf8IMautzhkNb1mtoJQTZeuJSroV7IX/+T44LoD6PyKh4s+64kek/jmwD8RwR9FKKeFK8C+G0C44y+uOVnl9PX1SU2NKihf06kVmgoefv7+MeyZNY0Bm00nMFOF/N3/MJ0eP8NjM0zesG0oxMrsnI09siA6bJoZSEcfktjuY1X9AxMelfG34+Ty/YR13LnmXG0eNZmhW9zPuJSJsKTvKHzauZ3BWd47VR/ls9hROm41A2HqOWR8IsO1YGXWBAA7DICsxkYGZ3TpFZ5aOTCewrqjhDbD1PGvyOpXhno7pmwy1T0Nm5BWFIgGrE0fqw8DJI0+modzTrGdZ4cMnGuMmgv0WlJEa80uKhDJSwXMViqvOfp0yIOFqpO630EwD4pPM4O4Ts6/HootJGeCeg/gWnTVxN6U+EOCYt55AOEyiw0l2UhI2wyAkJvYYu2LYDIMEh4ObxozngRVLGN0rh3kDBlKYkfnZz4svFDwxO9qN227nkRmzmi0rt8UYT6QMpfj+6LEsLi3hufUfYjMUM/IKTll+rGVxaQmGUlw9ZCiT+uayuLSYkBnb96o2EKDK7+PZ9R+yev8+CjIySE9IIBg22Vt1HKUU8woKmZaX3+yMUIuNTmBdzMmSeJVyf3SfDpNuhYorMP2rMVwTI7iPQP3/gH0gynbmEo2y54E9r5GRHYRrFip8EKm5D5LvQtmaPkNKgp9AzSNW1aRragz3mg7e7yByS2SnU4tQVFnB/KLdfHjwAJkJHpw2G7UBP2ER5vQfQFaih+M+X/SxYG0mTna6GJvTm99fcgVLSkt4es0qBCHNnUDQDHOsvp7B3bpzw4iRnJ/d66wVjm1JKcXF/QuYmd+fT8qOsmr/PrYfs7q5pLkT+MGYcafNzAZ1y2LdwU+Z0Ce6bjFH6+rYWnaUo3V1XFo4kN/Nu/S0QzlFhG3Hynh7907e3L2D+6ZMJyfKvXFa83QC62oC6080143uf1jDnoPpvhRqfoGkPmotPzZBxATvS0hoOyrloXONuF0opRDPN1G+fyPVtyGOUVZPR/sglDJO7FNbZx3ZEj5iPZsLbotpyUgZyQgK8AFnr4bzh0L85sMPKKosZ25BId86f9RpRQulxytZULyb13dsp9rvo9zrjbpR7fK9exibY23ETnG5uHLwEK4YNJiDNTXUBa0lsm4eT9QdM9qSUooRPbIZ0SP7rNfNKyhkfvHuqBPYU2tWohQ8PWtuowdvKqU4r3sPzuveg0UlRdyzdDGPz5xF98TOe/xOe9Bl9F1NaKdVbRgDlXAJOAYjdc9g1jyEBDZYyeoEq/z9LaTqh0hoHyrlF1bxRZxSSqESrkSl/R5lL0Dqfo9UXoNZ8SWk8iuI712U+xJU+gvWdoFzv+NZ/zQYDvPQyuUoBc/Ou5yrBg89o+IuPz2Dm8aM58mL5xAyTX61dnVUEZgiLCwpYm7B6c+dDKXok5rK4G5ZFGRkdujkFY3xvfvwaXU1m48eiXjMhkOfsnhPKY/PaPrU6FPN7j+AKwYO4pcfRPd3oTVPz8C6GmmwSuVjoRKtar30x8C/CvG+AuYziEoBwlb7JudoVNJNYB/caR5gKyMJEi5DJVx2ImEHAedpr0+MdDAPI2JG3D/xs7HhCsBAxAnBzdavE0UmGNngmowyknn5k024bHZ+cuFFzS7Z9UlN5dEZs/ju2/9mbsEALuqbG1Esb+7aQXdPYkTVh52Bw2bjxxdO5Mk1K7l70tRm+ymWe73cvXQxcwsGRNytH+CywkG8uXsnpccrYzoyRmucTmBdjXJZhROxEB8oF0q5wD3D2pBrVoFZA8phlctHefhkvLGSUyPnTdn6gPJAcAs4R0T1NcX3Lhg9oPoWRNlRzglWI2IJIKFiaPgHQdsFbDqUwP3Tvhbx86bRvXK4ctAQ7lu2hL9edU2z/QkXlRTxxq6dPDEz+uNv4tnwHtn8cOyFPLRyOZcMGMis/AIyP7fs2hAMsnzfHv7flk8Imya3T5gU1T1shsGc/gNYULybm6Lcm6c1TSewTkrMOgisBbMcEGvfk3MM2PpZ3SoSoj/5luA2lO1z+8WMNOvcri5OKXWimnC+daJ0hEyzHur/AI4RqKQfnDFzVYCY1ezY9zK3Dp5PhmMiEHmz29vGT2TV/n38eNF8Li0cxOyCAWR5/rOsKyJ8UnaU+UW72FdVxcPTZ3bJfU1jc3rz+IzZvLFrBz9c8Dbnde9OTkoKhjKo8HpZf+hThnXvwdyCQnZXlpMeQ+/FKf3y+OnihdzU8Q4riFs6gXUyEjpgdXjwfwDOESe6wBsQPoBUvwr2/hDYjISPWfu8Iv26EkD8S1Cpj7Re8PHONRka/on4V6JczX9CN80wHP8uGOmotKdQTRw7o4xUXikt5PrBg5HapyDlXpQ9svZQSU4ns/sPoEdSIt5gkFsXvkNuWjppp3SjdxgGcwsGcuu4CV36mJCclBR+MGYc3xg5ig8+3U9lQwOmaVKY2Y3rh4+km8fD4tJiyryxnQmW5nZTFwi0cNRdm05gnYgE1iN1z6Lcl6LSf2fNjk674FvWsyv/WqTmF5D2m8ifU/mXgz230ZJ4zaJUAiTfbbWukhDKPa3Ja0VMqH0Awocg819NJq+Tqnw+khIno9x2pO73kPpkxH93WYmJ2JXBjaPGcP2wkWwvL6POH8BuM+juSaIgI6PTPK9sCR6Ho8n+kTbDiKjRcGNi3W+mNU0nsE7COi35OVTKPU12jzj57Ers+VB5PVL7KCrlrua/dnA74v0bKuX+lg6701H2fpDyIFL7OOJbiHLPAddEaxM3Vq9H/Eus9lWhfZByL4at+SVYQynrxGLnJPD+P+uYGEdkHSpOPRMtweHggp4xnM2mAZDlSWRfdVVM58ztr646bflWO3c6gXUCIkGk7hlU8o8jan1k2PMw056D4zdiGukozw2NlruLBMC/3EpeSbeh7PmtEX6no+x9Ie23VoNg30KofwFRiYAJ4ke5LoSEr4L3JZRrckRfMz0hgSN1tfRLSwP3bMS3ABVhAjtSV8f5UVTMaU0bktUdfyjEroryqE+AXlhSZG2wPnqEosoKvMEgCXY7+ekZjMzu2WE2g8cTncA6g8CHYOuNcgyLeIjhHIGZ+B3wr0QCa8A5AZyjrVJ58UFwG+JfCvZ+VtcOnbyiopQBzjEo5xjrWBqzDpQBKsmajfneBef5TS4d+kJBagMB7MogyelkSr9c3i0tZlzvPlavRt+SiOKo9vn4+Mghvjd6bEu+vC7LUIq5BYXML9odVQIrq69nQfFuclPTcNntnJ/dC4/DQV0gwMufbOL5DeuYUzCAuQWFXfo5ZLR0AusErKWqS6IepxKuQgKrrP59/lXWbEEarFJ5Wz9U6sP6mVcLUMoNts89+JcGq+z+FGHTZN3BT5lfvJud5cdIcjoJm4I/HGJC7758fPgwR+vq6J6QaI2PwOI9JYzv3YeURrq+a7GZkdeft3fPZ9le6/yz5lR4vXz5n6/Q3ZPIreMnMrhb1ul7CEXYXVnBv3Zs4/39e7lv8rTT2lJpTdMJLM6JhCG0A5wPRD1W2bohRk+UWYXyXHsOhzhqUVPu0/bjlR6v5NFVK8hM8DBvwEDunTwNp80GWL0J3y0pxhsK8o03/smrV04iUTWfkPZWHeffO7fz4NQZrfYyuqJkl4v7pkzj3mWL8QaCzB1Q2OTyX1ldHV9+/VWyk5L4ny98sdEiDqUUAzO78bOJk/nHti08sHwpj86YRWIzzZE13Uoq/kkDkNBsFVuTjGSr64PWtmz9kOBWRITiygruX76EG4afz2MzZzO5X+5nyQusJrTXDh3Gm9ddT7LTyVMrX8AnZ58ZF1VU8MDypdw4aozu/NAK+qam8eiMWSzdW8r33n6Df+3YTrnXS9g08YdC7Cw/xq/XruHLr79Kz+Rk/reJ5HUqpRTXDR3GgMxM/rZlcxu9kvimZ2DxTjmBQExVUYA1C4jg07zWwuwDQTnwejfy8Mp93DRmPON79znrEKfNxt+vvIYPd/6T21YMY0L+R8zpX/hZPz4R+ewAyS1lR7ll7IXWMzOtVfRKTuGpi+ewu7KC+UW7+L+F26gPBrArRVZiEtNz88hOSuLR6bMiPkpGKcV15w3n1oXv8LXhI/XzsGboBBbnlHIiRhqE90CUhRYiAQjvA0NXqLU1q3PHXA4f/RtDs65qNnmdZDO3Ma5nInvrDjPc8yxFe6rZZro47OvFqrJC7PZs5g0YyI+6+KbktnJy+W9gpnXczqkfJFfu20tuWjp9UqM75y7Lk8iQrO6s2LeXOQWRVZp2VTqBdQLKNQt8iyDp+9EN9K+yTiKOoiOH1nLEOZWyupf4av+tiFzU7Aza9K2AmrsxjJ70TR9OqT+XSwYOp95fCcGPuKb/CuzOwajEMSibTl7t4dS/w0/KjjKhd3THtJx0Ye++bDx8UCewZuhnYHFIJGBtXPavQvxrEHs/xL8aMauj+Bqm1bfPPacVI9XOpvh4La8fuIIeriKof/ZEV/oziYQx6/8C1f8NnutQmf8gv9eN/KsY7M4BpCaPIzXj+zgy/4xyDEGq77ZOvNbalTcYaPaU6qYkOZ14g8EWjqjz0TOwOCLho+BbZO3PsvUEIwMQCB8EqUGO/wBJ+w3GWU4PhpOnJf/Z2vPlGNU2wWtnON7QQJonG5X6MNT/9cTBmedZ3ehVMhCEUAnS8G8IH4CUBzES5gGQnZhEld+HKfJZBZxSLki4EowspOZhSH0cZesax6J0RC6bnUA4HNPYQDiM65RCHq1xOoHFCfGvQepfQLmmolIfOW1/loggwZ1Q+xBUfAEz9SkMV+NHNohZjdS/BOGD1gblKM+u0lqOKQKc6KGYdCPI9eBfgfhXgx8T71kAACAASURBVNSBcqKMbDB6oBK/e1pvxbMtNyrXRVarKd+/IfHbrf46tMblpKSwq6Kci/s33x3n83ZXlDd7/I2mlxDjgvg/QOr/jEp5AJX4zTM2FyulMJyDURl/BfcVUHUL5vH/tpYVQ3uR0H4ksAmz9jdI1c0o5USlxvdpyZ1BmtvNMe9/tjAolYByz8FI+RlG6i8wUu4F92yQGnBddNrYcm89iQ5n0+2H3PMQ/wqrC4jWLqbn5rPmwP6oO9D7QyGW7Cnl4vzoE19Xo2dgHZyYlUj9763kZc8767VKKVTK7ZjOEVD/IuJbDFIJYoKRjHJeCInftk4Y1tpdYWY3avz+s5/S61+Mcs9EqdOLMpbsKWVin6YLBJStO2IfBP7V4NYbmdtDekIC5/fsyXslxVw5eEjE45bv20NhZiY9k5NbMbrOQSewjs73Lso5MapehMp1sdVeKuFylPP8VgxOOxc2w2BOwQAWFBdx05hxjV4j4QMo92Wn/V7INHm3pIj7p0w/69dXjkEQ/rTF4tWi96Whw7h76Xv0z8hgeI/sZq/fcayM361by/AePXhg+RIMpcj0JDItN++MFlSaXkLs0ERCiO89iLJSUCmFcs9BfAtaKTLtXIgIxxsa2F9dxYju2azev5etZUebuPjMjeZ/37KZPimp5KalN3On09tVaW2vb2oat0+YxJNrVrJkTwnhJs4SC4bDPPz+cr76r9fokZjElH55XDZwEHMKCumVlMwz6z7gRwvfYeX+vW37Ajo4PQPryEKlYKRYZ0xFyzUZ6v+AiKkLNToIXyjI+/v2Mr94N8fq60lxuQmZYWoCAW6a/yY/nTiZeQWFp3/KVolWJ3usxPePbVtYc2A/j8+c3fwNpe6MhsFa2xveI5sHp87g+Y3r+Osnm5nTv4BRPXPwOBw0hIJ8dPgQz67/EJth8OTFc848TDMHrhg0mE+OHuG59R9ysKaG684b3j4vpoPRCawjkzr4/KnKEVLKjeAC8YLSz7za2ydHj/DkmpUMzMzihuHnn3b+U43fx4sff8R9y5bwx43ruXfyNEb17GXNpB1DCPnX8v7Bbswv3g3AozNmkeo++7H2IoIEPkR5vtrqr01rXn56Bk/MnEPp8UoWFBfx3IYPaQgGcdvtHK6rZXxObx6eMavJfomGUozM7skTF8/mriXvkex0cUnhwDZ+FR2PTmAdms0qwIhZGGJt8qu1mI8PH+KXa1dz+4RJjT4HSXG5uXX8BL45chT3LH2PWxfNJz89nW6eROwqzNf6zmdDWQHXnTeCC3rmRHbwYajI+vDiGNkKr0iLVX56xmnPO7eWHeV369fy82kzm232C1Zj5/umTOPHixYwNTevy3es1+9uHZktC8KfIhJGqeg2NUr46IlGv7pRb3s65q3nl2tXc+dFUxiS1f2s16a63Twz91J+tXY19cEg1ww5D4dh0FPt5ae9K1CJvSO6p4iJNLyCcs/Wy8cd3Pyi3Vw2YBAue+RvxdlJyZzfsyfL9pZyaeGgVoyu49M/3R2YsvUCW3cIbox+sG8RyjVNVy21s4XFRUzpl9ds8jpJKcX3Ro9jZ/kxsjyJ9M/IJCH1O0jgA6ThnWbHi5hI3W8gfBhRGUjgIyRcfq4vQ2sFVb4GNh05zNTcs2+Pacy8gkIWFBe1QlTxRSewDk65ZyMN86MaIxKw2k25I3jQr7WaQDjMeyXFzC0ojGqcx+Hgor79eLe0GABlpKFS7kd885G63yKh/WeMMU0Ts+EtpOJqaPgnqHQIfID43kKqf4xZ8wgS+Bg5pyVprSUdqKkhNy0tpmXAIVndOVRbQ6iJqsauQi8hdnTOCdDwL6ThLVTCZc1ebn0C/x04Rp7RsUNrW1vLjtIzOZmclOhbAl2cX8DTH6zmyyeqzZQtG1IfB9/bSM2DiC0b5RgCJCBSCw2vgVkFrtmQdDOG7T8l9iI+8K9EvC+BLQeSbkWprv3spCNoCAajWjo8lVIKt91OQzBIsqvrPibQM7AOSsw6xLcQvH+zTu+tfx6z9hlMs+nmoCI+pO5XYFaikn7QhtFqjTnuayA7KbYK0B6JSVT7Tm8DpYwklOc6VPoLJzY3263k5f8AbHmQuQgj9d7TkhdYFanKfTEq9UnAhtQ+hkgoxleltRSPwxFzx3lThIZQqMuf+aYTWAcj4cNI3XNI1feR4DYw0lH2QeC+0mrOWj4Zs/oBzNAxa7YlYavXYf2fkePfBRyolPv0J+xOQJBGf18pO8o1HuX5EsrWG4wkVNqTGLaz97ZUyolKuhVQ1jKj1q76paaxv7rqjA8qkfj4yCHy0tIjqlzszPQSYgciwe1I7ZNW9Vjab1Gn7AFTgCR+G/Evgro/QOXViJEJygCVjnJPQ6U+hbJFViygtb40t5ujdXUxjS2rr4tsr5fvbZTnGyh19mtPUsoGnq8jNQ9AwlVn9FjU2k6yy8X43n1YvKeEqwcPjWrsgqIi5kX5bLUzatP0rZTqo5RappTaoZTappT60Ynf76WUWqqUekOprrnrVkJ7kNonUEm3WstEjWxgVkphuOegMl+BhMvBOQ7SX8HI+BPK81WdvDqYYd2zOVRby8GamqjHvldawpR+zVSnhXaBBMAxLKqvrex9rWdhgXVRx6W1rHkFA3mnaFdUHetLj1eyo7yMyf1yWy+wONHW888Q8BMRGQyMB25SSg0BbgF+CPwJuL6NY+oQpO45lOfrKOeIZq9VyoFKugXMClTwgzaITouF02ZjZn5/FpzooBGphmCQlfv3Nn+cRmAdyjUppr1eyjUF0Qms3Q3IzGR8Th8eXbWChgiehx2ureWhlcv53gVjYy4A6UzaNIGJyGER+ejEv9cCO4AcwAaYJ351uY1LEioGqQXXlIjHKOVEJVylG/Z2cHMLClm+bw87jpVFdL2I8PzGdYzulUM3TzN9DKUOjOYa+jbBSLd+5rR2951Ro8lOSuLOpe+y6cjhzw46PZUvFOKPH63nG2/8kyxPIgdra1h38NNGr+1K2i2FK6VygfOBD4HdwMtANfCV9oqp3fgWoNyzov8k7RwD9X9CQntR9txWCU07N1mJidw2fgKPrFrBTydOZlj3Hk1eGzZNnt+4jkO1tTw0bWYEX90GEtuR9RBGPwLvGAyluHnMeJbsKeHFTRsJhMNM65dHpseDLxRicWkJq/bvI9XtZlb/AgoyMvEGg7y2fSsvbFzP7P4FXFo4CE8XrEhsl5/gE8+5/gncKiI1QA0wuT1i6QgkuBPlviLqcUrZwTnKehaiE1iHIiLsKD/GwuIiSo9X4g+F+NYbr9MvLY2vDx/JJYWDTmnm62dJaQkLinfTOzWVn0+dEdnykNEt9vO+QvtRRrfYxmotTinFzPwCZuT1Z2dFOR8c2M+eQwdZuX8fGQkJ/GbOJUzo0/eMzjollRW8vnM7dyxZxH2Tpzc/a+9klLTxFFRZZU9vA4tE5JcRjvns3PWMjAxPRUVFa4XXLszKb6FSn0TZMqMeK/UvgZGKSriy5QPTYrK17Ch/2LiegBlmbkEhw3tkk2C3c7yhgX9s28KikiJEYFC3LFw2GzV+P+N692begIEUZmRG3P5LwuVI9Y+tfWEqIeL4REyk6geo5P9G2fWx9R1RQzDIXUvf4/zsnnxt+Miz/kyICK9u38rKfXt5bOZskjpZg9/MzEwqKyu9J/9bRD7bL9KmMzBl/S38GdgRafKC0wMePXp051v0VS4gxoMHxQeq6WUprW2t/fQAz65fy01jxjM2p/dpneOzk5J5cOoM7ps8jXeKdvG/n2zi6yPGcmHvvjFtSFW2boh9CPjfj65tWHAjqGSdvDqw17ZvpXdKSrPJC6zZ27VDzqPcW8/ft2zmuxeMaaMo20ZeXh4VFRWNbnJs6yrEicDXgOlKqU0nfs1r4xg6HlsfCG6PepiIIKEdYOvbCkFp0dpdUc6z69fywJTpjO/dp8ljT2yGweUDB3Pf5Gn8ZdNHlHu9jV4XCZVwNeL9BxLaF9H1Ei5H6l5Aea6N+Z5a6wqEwywuLeG6ocMjno0rpbh26DBW7NsTUTVjZ9HWVYirRESJyHARGXniV3Sdajsh5Z6D+BYS9XJuaLt1Xph9SOsEpkXl71s28/UR59M/I7Kl4OE9svnCoCH8346tMd9TOQagEr+N1DxgdW45CwntRWruRiVcgXJ2rk/pncmaA/vpl5YWdQ/NLE8iQ7O6s2Lf3tYJrAPq2n1IOgrHSKskOhT5LExEkIY3Tpz51OV2HnQ4h2prKDleyeTmNh9/zqz8AtYfPBhTO6GTlOsiVNLNSO0vMavvRvyrENOLiGCaXsz6lzErrkEqvw7YwSxDQiUx309rXduOlTE+p09MY8f17sO2Y0dbOKKOS9fRdgBKGZD4baT2l5D6EMrWs/lBDa+BWQ7uGa0foNasxaUlzMjrj9MW3cGjyS4X43r3ZtneUr4wKPaZtHJeAOkvQGCd1QS67ndgloFZAyrNekaWeKH1sxb+FKl9HFFpKM81ejbWwXiDgZgLMZKdLuq70BKiTmAdhHKOAU8VUn03JH0fHBc0ui9MzCrwvoqEtqFS7o+q+kxrPYdqa5jYt19MYwvSM9lXXXXOMShlB9cEcI6xTiUIV6OSvtl4sUbCFyG4Aan/A4QPoRKi38ahtQ6XzY4/HNtpAf5QCFeUH6LimU5gHYSEj4F5DJQHqb4DxESc54NrHsqeA1KL+NdAcCPKOR6V8jDK6JJtIzukgGnissX2v5PLbiMQjnVD8ulEBKl7DiSESr2/yVMJlDLAORZs/ZGae6yqRPf0FolBOze9U1LYWV7OrP4Doh67s+IYfVJSWyGqjkk/A2tnEj6CWfMoUv0TkAZU4rcg9XeQdBuYdVD7IFJ1G+J9DWXvj0r7PSrpJp28Opgkh5Maf2zPsWr8/pbbuxPaAaFdqOSfRHSkjrJlopLvRLwvWQdfau1uel4+az89QK0/uq01vlCQ5Xv3NN9DsxPRCawdSagEqb4L5RhkbUZN/DbKOQrDORjDczlGxh9QWUtQybdZszN7rk5cHdTwHj1Yc2B/TGNXH9jP8B7ZLRKH+Bai3PNQKvJTepW9L9gHgX9li8SgnZs0dwIX9OrFu6XFUY1bUlrKkKzuZCWe/Vy4zkQnsHYi4TKk5hFU4o2ohCubfJallNOqNEz+CVL7NBKK7U1Sa12T+uayq6Ii6vO/iioqqPb5GN0r55xjELMagh+Da2rUY5V7LuJbdM4xaC3juqHDeWPnDjYdORzR9dvKjvKPbZ/wlWHNn2bRmegE1l4a/olyT0e5LozocuUYhkq4BvH+rZUD02LhstuZmd+fv23ZHPF+PlOEv2/dzNwBhU1ueo5K+FOw9Yltlu4YBuE90e9F1FpFTkoKP5s4iac/WMXC4iKCTTwjDZkmS/aU8Ojq9/nJhReRlxbj6QRxShdxtAMx65DAGlTaM9ENdM+AhleQ8DGULat1gtNi9uXzhnH30sX8ZdNHfGPkqLMmpbBp8uz6DwmZJpcXDmqZAKQBYqxKVcqOYAcCQOTLj1rrGdq9B7+YNpM/frSBv2/ZzMX9CxiV3RObYbD+0EE2HTnM1rKjZCYkcNPY8YzMjmD7TSejE1h78L8PjpGoKM9yUsptnRnmXwyeL7dScFqs3HYH90+ZxkMrl/PgiqVcNWgIw3tkn7bR3BRhw6GDvL5jG267nbsumoKjpcqeVQJIbG2pRAJYR6x0rkaw8S43LZ2Hp1/MgepqXtu+lbuXLeZgTQ3pbjf90tK4dMBAbIbBCxvWs7C4iMsKBzGmV06XaW6gE1h7CO9DOYbGNtY+BPG/3/VO/YwTHoeTSwcM4uVPPubmBW9jikl2UjIFGZn0TEpma9lR0txu5hYUMiU3D7vRgqv4tn4QOoCY1SgjylLq4CawF3SZN754UxcMsOnIYa4YOJh5BYX0SDp9mfg7o0az9tMDvLTpIz4+cogbR41pmWXpDk4nsHYgEkDFukyjXIAud+5oRIS3i3bx+o5tZCcl85VhI+iZlMy+6ip2HCtj05EjbD5ymBn5/bl13ISWm3WdQhlJ4BoH/qUQ5fE6VvXinBaPSTt3e6qO88jK5dw6fgIX9Gy82MdpszG5Xy4X9OzFL95fxosfb+Q7o0a3caRtTyewdqBUAkh98xc2RrygutahdR2diPDchnUUVZZz35Tppz1IH9Qti9knNqQeq6/nhY3r+fn7y7hn0tTIDq2MlnsuUvsEuC6OuJhDQsUQKoXkO1o+Hu2ciAi/XruGb468oMnkdapEp5O7J03lJ+8uYGxO7xbbntFR6SrE9uAYhAQ2xDRUAutR9hZ66N9JmEcK2/X+/2/rJ+ytOs6j02edtQosKzGRuyZNIc3t5ldrV7dKxZ+yF6CcY61eh9LQ7PUSPoTUPIZK/K+INj63tvxnnm7vEDqUneXH8IdDTM2NvEl0ssvFFQMHM794dytG1jHoBNYenOMhvA8JH4xqmJhVEPwIXNNaKTAtWlW+Bt7evYu7J02J6FBKQyl+OPZC9lZXsaP8WOsE5fkWytYDqb4HCWxGxDzjEpEA4luCVN+N8nw54u0cWtt6p2g3cwui32YxLS+fT44coeIczpqLB3oJsR0o5QTXDMT7f5B0S+QPzhv+bfVB1N04Oox3S4qZ2Lcvae7Iy9edNhvzCgqZX7SbIVndWzwmpQwk8SaUfyni/QtIEHFOsLq5mMfBrIRQCTiHo5JvRzn0eXId1dayo9wwYmTU4zwOB+d178728jIm9c1t+cA6CD0Day+eqyG8Dxr+EdFSkjTMRwIfguerbRCcFgkRYVFJMXMLol/CnJ7Xn48OH4q5f2JzlFIo9wxIugNsvcH7EgTWgHnEKgRyTYPwUaThVSSwvlVi0M5dfTBAsjO2gq8kpwtvJz9aRc/A2olSCZByL1LzEIQPQcLVKHvuGddJ+BA0vIEEt1jHpxhpbR+s1qhAOEy1r4H89IyoxyY5nWQnJXGkro4Ul7sVogMJbofaJ1Gu6ZDx9zM2v4sEIPABUv8SBLeA5xuNHuGjtR+nzU4gHI5oefrzAuFwzCckxIvO/eo6OGWkQ+pD0PCm9bwCwJYNyg24AR+ED6Jc01Gpj6GM6I4Y11qXPxw6p0pCl92Ov4WOUfk8CZUgtY+jkn6McjbeH89ayp4CjguQ2odQ3r9C4g2tEo8Wm5yUZHZVlDM2p3dU40wRiisruGLg4FaKrGPQH7faW3A7EtoJyg72fiChE88oiiD4CTjHgHuGTl4dkMfhpD4YJGyeWSQRibqAn8QYPlk3xzoT7BmrUXQTyetUykhCJd+FBFYhwV0tHo8Wu9n5A1gYQzXh5iOHcdntFGREvzoQT/QMrJ2ICHhfRgJrUZ5rIfnOM8qYxawE37tI9V2QdFtEb0Za27EbBoWZmWw4dJBxvftENfZgbQ3VPj+9W+PwwdB2EAHnxIiHKCMF3JdYG5odA1s+Ji0mF/Xtx182f8SnNdUR/6yICG/u3sm8AYWdvrOKnoG1l4a/W8+1Uh9HuaY2ugdHGRkoz3Wo5J8idb9EgjvbIVDtbOYWFMa032ZB0W5m5OfjbIWOHOKbj3LPif7NyzUdAuutY1m0DsFlt/OV80bwyMoVERf8vLZ9K5UNDUztF/nesXilE1g7kFAx4luGSrkbZSQ3e71yDEEl3YzU/brRPT1a+5nYpx97jh9nW9nRiMccratj2d5S5vRvpQ3Ywe3gHBf1MGUkg6MQQp1/A2w8mTegkAl9+vLTxYsorqxo8rr6QIA/fbSBZXv3cN/kaa3T6aWD6fyvsCM6eWpuNBWFjtGgXrEOLHRe0HqxdSBm7TNQ/7vIro2kG0fizRjJt5xjVKdz2mzcOn4Cj69eyf1TptE/I/Os15d7vTy4YinXnTf8jIasLUa8EOteQZUUc0f7s/n12jU8s+6DiK6NpBvHLWMv5NbxE841rLhx/fCRZCcl8ciqFWQmeBjTK4cMdwIOuw1DGXxy9Air9+/j/J49eXzmbFJcXeNIHJ3A2ph1FtiHqLTI3phPUkpZfe58C1BdJIEZybdABAnHPFKIkd1+s4ZRPXvxvdFjeWDFUi4fOJhZ+QWkuk8vjW8IBlmxby+vbt/CpQMGcllLnQHWGOUCCZxo/Bwl8dMa54HdOn5CRAkn/5mnKb3lJy1+/85gfO++1AeD/H3LZj48+CkgmKYQNE3y09P55ohRzMjvj60lTzjo4HQCa2uhIrDlR3/cBVjLQvV/avmYtHM2oU9fcpJTeGPXDr739hv0SU3DFwoSNE0agkEO19Uyvncfbhs/kWHde7RuMLYcCO20KlijIBKCULHeLN8BbT56hKfWrGR4j2zumzyNIVndP3vGGQiH+eDAft4p3sU7xbu5d/I0unm6RsPvrpOqOwqpP4flnUQggEjr7B3Szk2f1FQGdetGekICxZXlGEqR6nLRNzWViX36UlRRwbI9pRysrWnVOJRrFuJbGP3AwHqwZaPsfVs+KC1mm48c5qk1K7l9wiRunzCJod17nFag47TZmJKbx+MzZjO5Xy53LlnE8YbmGzl3BnoG1tZOLu/EJAjY0J87Op5gOMyvP1xDWX09/3XBGIb1yD6jAWuVr4F3S4q5Y/Ei/nvCJEa01lEXrongfQkJHUDZIyvvFzER39so99zWiUmLSZWvgac+WMXPJk7mvGZm7koprh48lGA4zJNrVvLIjFltFGX70e+Ebc2WA6ESRGLoURbaBbZenX5vR7wREX63fi3+UJiHp1/MiOyejXYPT3MncO3QYfx04mSeXLPyrBVl50IpJ8rzFaT2MesEg2ZYexL/F5CYqhe11vNeaQljc3o3m7xOde3QYZTV17faz1dHohNYG1O2XlYSC6yLeqz4FqJcnf9TVbxZf+gge44f5/YJF0W0r2tY9x58d9QYfrtubaucCQag3LNRrslI9Z1IcGeT9xGzCuqftfYkJt+JUi3fGUSLjSnCwuIi5kXZLNpQijkFA1igzwPTWoNyz0F8b0e1p0vCR63WUq6prReYFpMFxbv5wqAhUe27uahvP/yhEDsrylstLuX5EsrzJaT2CeT4NzBrfolZ/wqmfx0S2IhZ+2uk6oeADZX6UER7ErW2U1RZgcdhb3ZrRmNm5PVn1f59rRBVx6ITWHtwjgMUeP8nsqNUzDqk9jFUwtUoo2tUF8WLw7W1FFVWcFHfflGNsz4lF7KgqHU+JYuYSGAd4l8OEgaVAcF11rEq1T9Cah4ADEh9DpX0fet0BK1Dqfb5yPIkxjQ2ze0mGDYJtFKz6I4ioo+MSql+wAARWaysn3S7iNS2bmidl1J2SL4LqbkfVf8s4vlak2X1EtqD1P0a5Tgf3Fe0caRac3ZXlDO8e3ZMLaHG5OQwv6jlm+eK+JDaX4JZiUq4FJLvOq1VmYgf/KsQ35vg/ROSdFOjrcy09qUUnMsCs4lEfZJzvGk2gSmlbgS+C2QA/YHewPPAjNYNrXNTRpJ1lEr9S0jVzYhjtPXMQqVAaBsEi6yuG+IFz/Uoz1XtHbLWCG8oSKIztudGiQ4H3lDLHjgoEkJqHwOVjkq9vdFnWkq5wD0DXJOQ2qeRul9D0n/rs8A6mMwED4draxGRqAu3yurrSXI6sXfyTc2RvLqbgIlADYCIFAEtfw56F6RUgrV8k/Z7MHogtU/C8Rug7jcQXA/2fHCOBd+/rOcV+qiLRrVnFw633Y4vFIpprC8Uwt3SBw42/AuwoZJubrYgQyknKvknYFZBLPvGWoHuwvEfeWnp2AyDbcfKoh77bmmxbuZ7gl/kPxuXlFJ2zm1mq32eeRT8i1GuSaiMv2FkLcHI/AdG6s8xUu5Apf0eZe+P1D6JNLzeapVrWvT6paax/dgxzBj+TraWHaVfWsudsC0SsipVPV9HqciWNK2S++sR3zv656qDUUoxr6CQd6JcZg6Ew7xXUszcKKsX41EkCWyFUuouIEEpdTHwGvBW64bVdUjoAFLzECrx29ZszJ57xjXKSEIlXIZKfRzxrwDfG20fqNao/PQMMhIS2HDoYNRjFxQXteybTGAd2HpG30nDPhiUw6py1TqUqbl57Cwvj7iiUET440cbGJKVRU5K5z8EN5IEdgdwDNgC/BcwH7inNYPqKqyTc3+F8nwV5bqw2euVLROVfB/S8AYS2tMGEWqRmFtQyL93bo9qFra17Cg1fh+jevZquUCCH6Fck6IeppRCOSdBcGPLxaK1iESnk3snT+WFjetYtrf0rNeGTZPnN66juLKCH43rGp36m01gImKKyB9F5BoR+eKJf9drDS0htMPq/u2aHvEQZcu02v10kGcWGkw6UUL/4scbI1qGO1hbw1NrVnHjqDEtWiUmZi2oGD91G2mIWddisWgtJz89gx+Pn8jzG9Zxw7/+jxc2rONw7X+KwKt8Dby6bQvfffsNyr1eHp5+MQmOrrEhvcknyEqpLZzlWZeIDG+ViLoQ8S08cXJulJVC7plI1Y/AvAFlxLZPRGs5DpuNOy+awgMrlvL0B6u5YcRIuiee2bA5bJp8ePBT641oxEjG5vRu2UCUHYh1309Id+HoYEwRPj5yiPlFu9lZXs6QbllU+X28sXsnz274kDS3mwx3Ai67ncn9crl70hTy0zPaO+w2dbYSqEtP/POmE/98+cQ/vwq0/Il3XVFwEyR+I+physhAbP1PHJnRNc4G6+iSXS4emX4xL3+yidsWzWdwt+5M6tuPVLebA9XVLCwpYtORwzhsBoMyszhUW0tZfV2jiS5WyugB4X3ARdEPDu0FI6vFYtHOjT8U4ldrV3OotpbLBw7ipxMmndbppdrXwLslJSwqKWJwVhbfHTUGRwx7EeOdam7JQym1WkQmNvd7bWX06NGyYcOG9rh1ixIRpPKLqIxXrI3NUTJrn0Y5x6D+P3tnHR7VtfXhd4/PxEOIQCBKCBAI7u5SSovU6a3LbW/1Vu/9equ37n5LlVKjLS2luLu7hkCChQSJJ+OzlJ237QAAIABJREFUvz8mUCQyMzAQOe/zzNPOnLPPWWfInHX22mv9lr6vH6xTuBAsDjtLD2SzMGsfG3OPUm6zkxYZxZjUViSFhWO221mXc4RF2Vm0imjM7R06ERN04TJO7oSg/yDCPvVqNiWlGVlwNyLkbYTae9kihYuL0+XixWWLMWm1PNitZ7VF8laHg9dXLkejVvF4zz71snC5c+fOrF+/vtIL8+TOGSCE6C2lXA4ghOgJKHGrC0QIgUSLu0WKD7VA0g4oIZ/aiEGjJTIgkMMlJTzesw/94hLOezpOj45hYrv2zNybwZML5vCffgMvOPwjNM2Q6liwrQR9P88HWheDNk1xXrWEX3btwOly8XD3XjUWIus1Gh7v1YdnFs1n1t4MRqW0vERW1g48WXy5HfhQCJEthMgGPgJu86tVDQV1FDiqzyyqDCld4Mx2j1eodewvyOfNVct5qldfBicmVxna0Ws0XN2qNXd16sILSxdxvLzsgs8tTNciy75COj1L65eO/cjyHxFGRemlNuBwuZiVuZdbO3TyWEVDp1bzt/QO/LF3t0/1iHUZT7IQN0gp04F2QLqUsr2UcqP/Tav/CP1gpGWO9wPtm0EEgrr+V9rXRaZs28L1ae1o42EPp17N4ugfn8AvO3dc8LmFtg3CdDOy6BmkverjSSmRto3I4ucRAXcjNMkXfG6FC2ftkcNEBQSQEBrm1bjUiMbo1Gq25eX6ybLaiSdaiM+c8x4AKeXzfrKp4aAfAOU/Ip0nPQ7fSCmRlj8rshfrX7y7rpNXWsruEyd4vKd39VijWqTy4OwZ/C29g88p0NJ5DKzzkLaNIEuRBXciRQgYrwTjOIQIBGkG+0akZTbIckTQIwitklBcW1iXc5i+PkhACSHoH5fA2pzDpEfH+MGy2okniy9nxjUMuLMTd/nHnIaFUAWC8QpkyWsQ8hxCGGoeZPkNXCfAh4JVBf8zd38mA+ITvOoNBhBhMtE2MoolB7IZntzCq7HSVYgs/RQcOxD6foiAu0AVgnRZwDofzL9C2ZdIVSNQNwFNEsJ0E2jTFQHfWkaJ1UaYwYP7QCWEGoxkF9bcgbs+UeOvTEr55pnvhRBvANP9ZlFDw3gtwpWPLPo/CPonoop1LZfLCuYpYF0OQf8BlPYXtZHDxUX0jYv3aWxqRCSHi4u8GiOdx5HFzyB0vSDowbMegoQa0N4BgXe42/KUvIHQ90SYbvTJPgX/o1EJHF40uj0Tp8tV79Xnz8UXKWwTkHixDWmoCCGQAfcizL8iix5DalIRhqGgbg5Cg3QchvKv3Y5L6ECTBMVPIVUhYBgO+oFKJ91ahNXhQO+jwrxBo8Hq9FzZ3t3360V3ONlYfa84oUmAkJeRRU+DKgJhGOaTjQr+JcIUwKEi7x5iTnGgqJDGAQ0rQdyTNbAzFTnUQGPgBX8a1dAQQoBpHBhHuRsNmn8B53Fw5oLrOGjbQui7qPTdAfc6GI4M9zqG+e9guhFhGH6Zr0IBwKTVUWqz1bxjJZTarJi0XsysrYtBFQWGKz3aXaiCIehxZPF/QD9AaWJZCxmUmMTzSxZxTZu2Xs2mrA4Hiw9k8caQhnUf8ORR8Yoz/t8B5EkpfWuApFAtQhjAMBhhGIws/wFpXYkI/vy8sKIQArQtEdqWSGcusvgFcJUrTS9rAW0aR7LmyCH6x3u/EL/68CGuadPWo33dyTyz3F0MvEjmEZrmSHUc2FZ5VyumcElICA0jKiCA1YcP0btCY9MTlh3MJiW8EdGBDSsa44mLf1FKeaDidURK6RBCTK55mIKvSOsqpHUJIuT5KtfETiHU0YiQF5DW2UjbuktkoUJVDEhIZEtuLifLvVNb23vyJIUWC52bNPVsgCMDpBM0njm8MxGG4UjLPK/HKVwarktrx6SN68ktLal5Z+BQURHfbNnMhNZpfras9uGJA2tz5puKhpaKAJ8fkeZfEQF3IFSeNTsUqnCE6VakeZqfLVOoCZNWS5+4OKbu3O7xGJeU/LhjG8OTW3guBeQ66s4m9KWUQpPkDk8r1CqcLhcbjh7haGkJLcLDuXvG72w8Wn1B+q7jx/j3onnc2qEjrRpHXiJLaw/VqdE/BZxqZFl86mPABvzvEtjWIJGOTJAloO3g3UBdVyj7HOnIci/YK1w2bmrbnifmz+HnndsZ16pNtU7GJSWfbVxHqc3KlS1beX4SafddPV5ocf+MFWoDhRYzszP3MmdfJhEmE/GhoUQEBNAsOJjbp0+jWXAIN7RNZ3RKKkatlnK7nU1Hc5iZmcHRkhLu69L94nc2qCNU6cCklC8DLwshXpZSPnUJbWrYWJcg9IO9rs8RQg2GgWBdBooDu6wE6fU8P2Awzy1ZQFZhAWNTW5MUfnahupSSHceP8fPO7dicTv7Vp3+1oq3nIQKQrmJ8KmV3lYBoWNlqtZX9Bfm8sHQxnWKa8H99+5+nh5lfXs5nm9bz3tpVfLZxPYE6HQaNhuTwRlyR0pJuTZs1uNT5M6luBpYqpdwNTBVCdDx3uyIn5R+kKx+h81GQUxWDtG/17aamcFGJMJl4dfBw/ty7h/8uX0q40UjbyCgMGg3ldjvrc47gkpKRLVIYmtTCO+cFoG0NZR8jXaXugnhvsK1EaNO9G6Nw0TlcXMSzixdyd+cu9GpWecJGuMnEE736cnuHzjy7eAED4hMY1wDXuqqiuizER4C7gDcr2SYBz9sIK3iBBF9dkBCAb0WQChcfk1bLhNZpjGvVhvU5R8guLMDicBCg03FXpy60jYzyWQ5MqEKR2o5gXQTG0R6Pk9KBtMxFBP+fT+dVuDhIKXlz1QpuapdepfM6kwiTiWf7D+LRuTPpENOkwTWurIrqQoh3VfzvCCml5cxtwiPNIwVfECLYLRXlC84T7lofhVqFSgi6No296OsUwjACWfom6Pt4nPCDZRaooxGa+Itqi4J37D55ArPDzuBEz0WUI0wmRrVoyazMvdzXpZsfras7eBI8XenhZwoXA31PpHUhNTUaPRcpXUjrItD19JNhCrUNoU1F6Acii19EumpWb5DWxUjzb4jAf1wC6xSqY9beDEYkp3jdgHJIYjIrDh7wuVi+vlHdGlg00BR3FmIH/oprBeOWk1LwB5q27voexy73Ooen2LdVSE2l+s82hdqH8ToELmTRE2C8CvT9EMJ41i7SsR8sM93ro8H/QaijL5OxCqfYlJvDzeleZhoDYUYjSeHh7DpxjC5NGmbm4ZlUtwY2DLgFiAXeOuPzEtzp9Qp+QAgBxiuRZZ9DyIvn3YwqQ7rK3Pvrh4IrFykMIEIUpfEGgFuG7EbQpiMtM6H8O6Q23R1SlDakIxtkPkI/DBFysxJiriWU2myE6PU+jQ3W6ymz2S+yRXWT6tbAvga+FkKMk1L+cgltUtAPQTgykcUvQdCT1WaZuRyHoehxcBWALERaZ4C0ABowDAHDEIRKWfCt7whtGkKbhnSeBPtWkKUgtAhdt4q2KV5mOSr4FZ1ajd3lqrJbd3U4XC7vs1brKZ60U/lFCDEKtyKH4YzPlYaWfsKtUH8PovxrZOEDbkekH3pW00vpPI4sfRssc91Fz6HPotKm/LXdcQAss5CFD4JhTEVDQyXBvr4j1I1APeBym6FQA9GBQewryKeth127T+GSkv0F+VzroWZmfccTNfpPcK95DQAmAeOBtX62q8EjhAoCbgX9ILDMQRY9jFSFgTCBLAf7HhAaCP0Mlf78WLrQxEHgPeC6Bln8IkKWQ8DNl+FKFBQUzmVoYjKz9mZ47cA25eYQpNOTEBrmJ8vqFp6o0feUUrYTQmyVUj4nhHgT+NXfhim4EZrmEHgnyIngPArSjHTsc6vPh75aY3hQqMIh+Hlk0ZOgaY7Q9780hitcODYbTJsGq1ZBcTEEBEDbtnD99RDUsFTH6wsOlwu700m/uHimbNvCifJyIkye5cRJKZmRsYeRLVKUaEoFnjgwc8V/y4UQTYCTgKJVdIkRwnBaIkqWT0EE3OLx2pZQBULAncjyL0HXT/njr+2UlsKrr8KkSSzMzeVPoBAIAPoB45580u3Enn4amnqoXq9w2cg3lzN3XyZz92eSbzajValwuiQBWi2Pzp3JRyOvJEBXc2+2abt3crK8nD7N4/1vdB3BEwc2QwgRCrwObMQtFfGZX61SqBLpOOBWEtd5WciobQfS4X16vsKlJS+PjdHR7MHdNXbXOZvfB5oWFPDgRx9x7Ucf0XzbNkhTpIVqIy4p+WrzRubv30ev5nH8u09/EkLDEEJgcdhZdiCbd9asYsi3X/LWkBF0b9a80uNYHQ5+3LGNFYcO8NLAoeg1vnX8ro8IbwpmhRB63IkcqVLKNX6zqho6d+4s169ffzlOXSuQZd8CIAJu8n6s+Tdw5iIC77nYZilcDEpL2RAUxGzg3x7sfgPwKhB74AA0r/zmp3B5cEnJm6uWU2ix8GSvvgRVkTIvpeS1lcv4YftW+sUlcEPbdOJCQlGrVBRZzCw+kM3CrP20imjM/V27EWqouaymvtG5c2fWr19fadjIK1cupbQCViHEVMDrX4wQYjjwLqAGJkkpX6kIS36Lu77sRillqbfHbVDIQt+LlVVRSPsuRezXjxzNymPLoh2UFpahUqkIjQym09B0QiI8qL965x324ZnzAvgOaAE8+8QT8P33vhutcNH5YftWCsxmnu0/qNqUdyEET/TqS9+4eF5cupjvt2+l2GrF4XISpNPTuUlT3ho6gqhALwWbGwi+zkW9vgcKdyHKh8AQ4DCwTggxHbgZ+AeQCNwEfOKjTQ2ECxD7RVSMV7jYbF26k4VTlpF74Didh6YTFhWKy+niSGYuMyctoFW3Fgy+uR9xrapQT3A44NNP+a+X530HeHb2bMjLgyjvMtoU/IPZbufPvXt4d/gVHtdr9YhtzpUtUwnQ6ripXXs/W1h/8NWB+XIX7ApkSin3AwghfgDG4J6NuSpeyuSgJkQIuI75NtZ1HKFS0m8vJlJKfv9wNpsXbmP0vcNI798Gjfbsn9X4R65gzZ8b+ejBLxj/6JV0GVbJDWrGDFYcPswWL89fBHxWWMidn3/uTupQuOwsPpBF28goj7MLTzEiOYX/WzSfa9u09anAuSFSnRbiH1TuqATQqJLPa6IpcOiM94eBbriTQybj/i3e4MNxGxb6XsiSV8F4rVdSUVJKpHUBwnRrxXsngKLQcIHM+nwhu9fs5Z9f3EdgaOVNIo2BRvpf24sWnRJ5//7PMZj0tO1zTvfltWuZ7asNwJ1rldLM2sLCrP1cn9bO63HNQ0KJCQxiU+7RBtth2Vuqm4G94eO2qqhsdiWllAeAvj4cr0EiNElIEQr2DaDr4vlAxy5wFSNta5Clb7mlhgApAhC6PmAY5q45U/CY3OxjLJm6kn9991CVzutMmibHcNdrE/n0sW948Y8n0eq0f20sKaHYRzuKwV0nplArOFFeTmywb5qTscEh5JvNNe+oAFSvhbjkIp/rMNDsjPexQI4nA4UQk4GxAOHhiq6fMI5Bln0FmpYeibO6nMeh8GEQBoQqCEJeA1Xjio3HwboQWfwsUpOECHzQ+w6/DZRlP6+m15iuBDfyvKg4sV0cTZNj2LRgO11HnKGgEhiIr996ICiFzbUIl3Sh8lFIWyUETpfSlPZMsrKyEEKUnfHRr1LKieBZP7CLxTqghRAiQQihA64DpnsyUEo5UUoZIKUMSEhQaqiFvhdC183tdFz51e7rcuRA/rWgbgbhPyNM1yPUUQihcr/UUe7Pwv6HUMcgi/+FdCmJoDVhNVtZO2sjva7u6vXYfhN6sHTqqrM/bN/e5xbnAwHS030crXCxCdEbyDeX+zQ232wm2EeV+vpKQkICp+7/Fa+Jp7Zdsoo4KaVDCHE/MAd34sYXUsodl+r89Q7TRITZhCx8CPT9wTAcoW5yerN05iHNs6F8EmjbIULfr3bNTAgNBNwGZV+719iCn1cUO6ohN+sYYdGhNIrxPikmrXcqnz0xGZfLhUpV8W9y9dUMiooiNS+P3V4cKwB4ICwM7rzTazuqQ0pJ5qYsti3bRVlROWqNmvDoULqN6khYlIfdn+sxUkp2nzzB0gNZFJjNuKQkxGCkd7PmdGsay6Ls/aQ0ivDqmIUWMzuPH+PBbj38ZHX945KWdEspZwIzL+U56yvuPlDjQd8HLPOQRf+q6ANmcrdTkSWgaeUOM9bgvM7CNBEKHwTHTtC28e9F1HKK80vYsmgHxSdLAAgKD6T9wDSCw4Mwl1owBfpWVKrWqNHqtdgsdgymiqdtnQ7uuIN/vvQSd3hxrLsA+vWDZs1q2tUjpJSs+G0ti35YgcvposvwDkTFNcbpcJKzL4//3vAOSe0TGH7bQOLbXJxz1jWWHcjm5107sDocDE5MIi0yCoHgWFkZkzatp8xmJ6e0hIlt22PyQCLqFHP3ZdKjWbMqi54VzscTNfp5wAQpZWHF+zDgBynlMH8bp1AzQh0FATeB6RpwnXAr1QsjqBojS99HGK/2KltRCBUYhiEtsxEN1IEd2HWYhVOWsWPlHtJ6pdKoaThCCPZvPcD0j+bQqnsKqV2SsFp8a+vucrmwW+1o9ef8/B59lF4vvcRDuOu7amIk8DjAK6/4ZMe5OJ1OJj83lbwDx7nmn1eS0jnpvFn4Vf8YwbpZm/j44S+55rExdBrScEKXUkqmbNvC8oMHuKtTF9pHx6A65/sZ0zKVXSeO89Ccmdw7czpfXDkWtarm319OSTEzMvbwbH9fA8kNE09mYBGnnBeAlLJACBHpR5sUfEAIHZwZQpRmsG2AAB9ko/T93Z19pdmjjtD1idUzNjDt/ZkM+1t/rnl8DAHBZ9fylJeYWfPnRqZ9MIuiY8WUFZeft09N7N9ygMi4xqjPrfUJCyM1K4t7ExJIAF4BjlYyPhi4B3gYiF61Clq29Or8lSGl5IdXfqMkv5SHP70bnaHymYPBpKfPuO4ktIvj/fsnYQw00LrHhZ+/LvD7nt2sOXKIVwcPI8RgqHQfIQStG0fy3dgJjPvpO+6fNYMPR44+z9GdyZHiYp5dsoAb2qaTGKYkqXmDJ4/mLiHE6fxqIUQcipxD7cdVAKoQhKrm9O5zEapAUAWDq7DmnesRG+ZtYfrHc3j407sZeEOfSh2TKcjIgOt68fiX92Gz2vnuJe+blS+Zuoo+Y7tXvjE+npTjx3ng3nvJCQvjJ9xSNVfiLpL8BCgKDeXVa68lOiMDuldxnArMdjuzMjP4v0XzeWD2DB6a8ycvLF3EsgPZ2J3O0/vt25xNxvp93PnaxCqd15nEtojhtpdu4NsXf8F5xnHqK4UWMz/t2MYz/QZW6bzOJMIUwHdjr2VTbg73z/yDRdn7sZ3zPR0pKWbSxvU8Pn8217Ruy/DkFv4yv97iyQzsX8ByIcSptPq+VITeFWox0smFJZmqK44BUlrcCvjS4g5PqmPcM756RHmJmR9emcaDH99FdHzNAYbI5o35+9u38NqtHzL+0SsJiwzx6DwncvLZtTqD65+6uuqdIiLgo4/glVeYMHkyE87sB5aWBrffDtHR1Z7H7nQyeetmFmTto21kFKNTUokwmXBJSU5JCbP37WXSpvVcndqGMS1TWTJ1FQOu6/XXmpwHtOycRHhUKNuX7ya9X/0ON8/fv4/usc1obPL8gbBpcDD3du5G5smTLMrazxebNtAsOAStWk2R1UJ+uZnBiUm8NXSkonXoIzU6MCnlbCFER6A77mLkh6WUJ/xumcKFoQoGWYyUTq/VNqR0gqsI6SqC0plI23JQhQEGkGa3oLB+gLv4+YywZV1mzZ8bSe2WQmyK59fTdWRHmrdsyuu3fMjzv/0TtbqgYg1SD6pwdw+3MygtLOPjh79i5J2DMQV5EJoNDob77nO/vMDqcPDCssWYNBreHX7FeZJGyeGN6BsXz8GiQt5ds4p9ecfIWZ3BDU9X41SroG9FSUB9dmAuKZmduZcne3uvtzAiuQUP79vLF1eOpchqIa+sDJvTQYBWR2JYuMdaiQqVU52UVKqUcneF84K/io6bCyGaSyk3+t88BV8RqhCkOrZCscO7WiVpXet2VKVvgmEoIuRthPov9TDpzAPLHGTR02AYXiFrVXdT7qWULP15FTc8PdarcUII7nt3PPO/eI7sVWNomtwYfUA4SDvIYtD1dH8/6nj2btzPdy/9Qqch6Qy8vrefrsR9LW+tXkG4wchD3XtWu/bSPCSUlwYO5oEfp+Hs3hijD1mVbXq15MfXfrsQk2s9ZTYbZXYbyeHeK+hFBgQSrDeQV1ZK85BQIgOUmdbFpLoZ2CO4Q4VvVrJNgs91lwqXCGEYhrTMQnjhwKSUUPYGqEIRoe9Wqsrhzny8GYxXIotfQkgLBNxyES2/tJQUlFJaUEpyB++K5KV1CYlxn5HYWkXWvnFMejmX6LjGdB3VkUYxKgINK9Cp/smOtTqWz+nAqLuG0GV4h5oPfAHsOnGcA0WFvD/8imqd1ykMGi03RSTxTGguBWYzYUbvnJghQI+13IqUss4+xDhcLtYeOczSg9kUVsg4hRoM9ImLp1vTZlgcDgwabQ1HqRqTVovZ4bhY5iqcQXVSUqfWuUZIKS1nbhPnxkYUaie6nlD2LdK21mMnJss+BGceRHxZo6SUUIVC8H+QRU+BJhmh99/Mwp9YSi2Ygk1e3YClZT7S/BMi5L+sXvQTd746mgETG7Fl8Q42L9zu7gemNtEoehzDrt1C33EORJD3Aq/eMnNvBiOTU7xSM28UFEhsqYp5+zO5pk1br85nLbehM+rqpPOSUvL7nl38vmcX0YFBDE5IOr0WlVdayoyMPUzauJ6hicmU220+O+kyuw3TBThAharxJIljJdDRg88UahlC6CD4SWTxCxAoEDWI/7qsa6BsMoS8iMoDjUWoyFgMuBlZPrXOOjCtQYfNi5ou6chElk9BhLyEUDfBZrGjNWjRaDV0GpJ+Xm2UlNcgS14E809guv5im3+aYquVjUdzuKezdyHjJsnRBG4+ycwOe85yYFJKyux2zHY7eo2GQJ3uvFndnnWZNPNi3bC24JKSd9esJKekhP/0G0h86NmKKmmRUQxKTCK7sIAP1q7mpLmcXSeO07qxdxVER0tKKLXZlCQNP1HdGlg07hYoRiFEB/5Skw8GvCt8UbhsCE0yBP0LWfIqUrscYRgOmtTTT5JSSnDsRlpmg3WFW3ZKP9i7k2g7gZyEdGS6z3cGUtpOZy8KUTufQoPCAnDYnZw4cpKIpjWvc0jzDIRxLELdhPzcAqzlVkIiqhbTdct03YMsegKM4/yWwZlXWkpUYCCBXqg/AIRFhtC+RTy/5uVjdThwSsni7P3M3JvB8fIyTFodVocDvUbN0KQWDE1MplFFYsiSn1bR86qu7Fi5h6LjxTidLoLCAkjt1sKrjMZLzRebNnCivJwXBwxGr6n6OT4+NIyXBg7htunTeHn5EiZfPcGr88zet5fBCUlKsoafqG4GNgy4Bbdq/Jv85cCKAaVzXh1CaFMg9F2wLkKWfgAIpLqie68zD5AIw3AkAqE5X32hxuMLlbv42boSNMluMWDrAqRljlsdRBhAliPVcW4Hqu+LELXn5qbRaug+qhPLflnDVX9vA44MdxKL0IM60R0ePeXwXYXuxJgAt+DT8l/X0mV4h7Nbo1SCUEcjNS3AugwMg/xyHTanA63at9KJvhN68M28P1iQuZcpO7fRLiqauzt3Ja1x5Olrzy4sYFZmBg/MnsEVKam0KdCwdelOju7PI7JZIyLjGqNSqSjIK2TKiz/TeVgH+k7oTkxC7eoUnVNSzJIDWXw8aky1zusUeo2GN4eOYPiUr9h4NIeOMZ7NOAvMZhZk7eP1wcMv0GKFqqhuDexr4GshxDgppffVmgq1CqEKBONoMIwC535wFbk3qEJAnYgQKmTxy6DyToD0NKoIpH03mP9Amn8CbWdE4IOgSUEIgZQusG92z/TKJ0PAPQh9z4t3gR5SVlzOmhkbWDVjA4V5hTgdLgLDjPQa6SAoYDmOgqZojB3d9W7SgjT/5taXNAwHfT+wrQVtB4QqEEu5lZXT1/Hgx54J6Qr9IKR1PsJPDsyk01Fq9U3eqkWXJKwrVLw9fT6f3HY9SRHn/x3Eh4Zxb+duXJ/Wjod++JUPf93M1b1acsNTY4lJPNtJFRwrYsW0tbxz96eMfegKuo30/4qD0+ViXc4Rth/Lo9xuR69RExsUQr/4hLNmpbMz9zIoIcmrmWp0YCDDk1rw9MJ5fHv1hBq7LZdYrbywdBGjWrQkRml14zc8WQPrJIRYcI4W4qNSyn/71zQFfyCECs4J8/2FCt9FVlzg2IZ0ZiJC3kSoz14rEEIFuo4IXUekYz+y+L8gzX67mZ9nncvF9A/nsHzaGtJ6pXLtY2OISYxEpbLhKHqT/CPZfP92BF+/HsrLs28kPLpiTUS6wL4Faf4drItA0xqhisRus/P5k1No17e15zMMdWO/qpvEBgVTZrdxsKiQ5iHeKcb/vGs72hAjg3Zp+POZaYx9aFSlNXFOh5NVU1ZS8O8FNHqsK22uHHSe8wIQwTqSxrXH2LkJ37w6HakWdB/mnwxMm9PJb7t3MnvfXiJMJro3bUbzkBCsTic7TxxjyrYt9GzWnAmt0wg3GlmQtZ83h3o/K3q4ey8mTpvKY/NmcVuHTvSIbY7mHJ1Dl5RsOHqELzZtpEuTplznZVKMgnd44sBGSClPhwwrtBBHAooDq2cIVbhbccMHpHUlOPMQ4ZNrbLIpNIkQ8jyy6F+gborQpv51HCnBsQNpmQfOIyBtoApAaNNAPxShbly9HdIOtjXg2OMuKsaAVDXjq5eOUnzSzjM/P0pweFDFvk5kyVvoQyIIbPosD3/l4j9XvcY/uj3NM7/8k5adkyocbwfQpkP5V0jzH5RYevP5858TGBbItU+M8fKb8l+2nlatZkhiMrMyM7i7k3eJHJO3buGaNm158NbuzJ/trT/hAAAgAElEQVS8lI8e/orwqFC6jOhASETQaTX6lb+v5eCuI9z+zLWkTOjIW6tWMDQpGZUQSCnZdiyPmZkZbM3NpWlwMDq1GtuEFjy0bC63Blm4ql3bGhMajpQUk3HyxOnkkYTQsCo1AkusVl5atphAnZ5/9+l/3n6jU1IptJj5c28Gj8+fzb2du6FTq4kO9H5WFBUYSGxICNentWPW3gw+37iBgQmJxAQGIQQcLy9nYdY+gvUGbkhrR5+4eK/PoeAdnjgwtRBCL6W0Agi3umvtWcBQuHjo+yBL3wPjVV4p2LtcVrDOhaAXPeoQDbgVPEzXIc3TENqnAJC2Dcjyb0BKhGGYO+SJzt0axrYaWfQoUtMKEXDXWYXVUCFebP4VaZkP6uYIXafTrWUyVk9j8BX7aNJmAupA+1+DLDNBOhFB9yOEBr0B/jvzad6+61P+b/TL9Bjdmd5ju9GoSThCwImcDgRrfwXXVFK7/Ydhtw74q5+XJzhzKxRN/Mew5BY8NPtPrkhJpWmQZ/8WSw5kc7SkmDs6dEKtVjPslgEMntiXbUt3ufuBFZah1moIjw5l8E192bRgO1feOwwpJQE6HZtyc2jTOJI3Vq7gaGkJo1qk8EDXHpi0f60LfrT3RzK3ZvNI7mGuT2vLFSmpZ9ngkpI1hw8xMzODA4WFtIuKxqjVYnM6mLJtC42MJkYkp9CnedzpEgGb08nLy5eQEBbGnR27VFn3FmowcmPbdFqEN+KNlcswaX1PojGoNbRsFMGQxGQOFhWy5EA2u04cxyUloQYDj/fsS4tG3hc8K/iGJw7sW2CBEOJL3PGl24Cv/WqVwuVB09KdcGHf4p51eIr5J8CEMHhZ267vB+VTkM7j7jBd+feIwH+ANv38RBJtGzDdCObfkcVPQvBzp2WspKvAXSqgbo4IfgGhiT09rDi/hEkvrOe5X/+NWr0AWfQkBP0b1LHuIu/AB9xZghWoVCoe+ewe3rnnf0Q2j2DD3C0U55cipSQ4PIieo+8mre1ztBjQzjvnhbt2zOvvyEsamwKY2K4Dzy9ZyPP9B9c429lz8gT/XbaYK1JSCT5DpFatVtN+QBrtB6Sdtf97902iz3i3gLAQgiGJySzK2s+vu3YSYTLx7vBR54XVAK4c34ePHv6K17+/jxeWLcHhcnFVamvA7YjeXr2CnJISxqa2pkez5mdl7bmkZH3OEX7bvZP5+zN5qnc/gvR65u3LRKtWV+u8zqRr01jGpLbio3VrfarpklJSarOddoDNQ0KZ2K69V8dQuLh4ooX4mhBiGzAId/zjBSnlHL9bpnDJEUKAcRyy7H+geQWhqlmgVjqPQ/k3YLzah+xFA+h6Icsng30HIuRFhDqm+v1N14IqzO2wQl4DoUEWv+Au1K5E0mrlb+voMLAtAaHNgFtAHYcsfh5MN7mdteb8ViBCCAZe35t53yzhn1/8/bztrpPfQOn/IORfHl+rdB4B5wHQVa8efzEYntwCh8vJE/PnMK51GwbEJ56XsHCivJx5+zP5c+8eesQ2p11Uzet4LpeLvRv2ce/bfzv9WUxgIF9s3kDnmCY82K1q6arYlCboDFrksXKeHzCIx+fNIaVRBKkRjXlj5TJUQvD6kOGVppurhKBr01g6N2nKZxvX8fzSRbzQf5A7VNq5q0fO6xRjU9vw1qqVrDx0kF7N4zweB7A3/yR6jZpwL9VKFPyHRx2ZpZSzgFl+tkWhFiD0vcB5EFn8DAT967xkjDORziPI4hdB3Qyh9+3GLFUxUP4ZIvj5ap3XWTYahrrXuCyzASeom1apx7jqj/Xc9t8bzhg7AFy5yPKvEYZRVTrdtD6p/Pj67+RmHztfnd4wFso+QzpuRGjia75GaUOWfoAwjL5kKv5XpKSSHN6IPzJ28/22rXRq0qRCjd7df2rn8WP0iYvj1UHDmL1vr0fHNJda0Jv0Z5UM2JxOjhQX88moMTU6kqCwQMqLzTRNjmFC6zSmZ+wmq6CAYquVFwYMrlE9RCUEd3Xswusrl/P26pVIIM3LwmKjVku/uHj+t3G91w5s5t4MRiSneOUwFfxLjTEQIUR3IcQ6IUSpEMImhHAKIYovhXEKlwdhuh6hH4wsehRXyXtI+153cgXuMIq078BV8iay6EmEcTxo4vC5dYsrB6QErZehGMMVSPNspGUewji+UkckpST/aAGxLc5xjIbR4DyApOobplqtJjo+kvyjBedtE9pk0KYii59H2jOqNVO6St1OXhUFxqs8u7aLRGpEYx7r2YcPR44mLTIKk1ZHiF5Pr+bNmXTl1dzbuRtNg4MJMxg4Xl5W4/E0WjV2q/2szxZl7ycmMLDGtHIAh92BRud+Zh4Qn8DW3KNM272Tm9q191j6SgjBxHbtWXRgP+2ionySdprQOo09J45zqKjI4zGHi4tYe+QwgxOTvD6fgv/wZAb2AXAdMBXojLu/XlV52Ar1BGEc7V6jsi5Alr4JrmJkRUEyqgh3QXLAPQhVANK+zV2w7Au2taCrZM2rJvs0CUgBCDVCU/mTtJTSvdahOvvYQhWIVMeBfTNQdQsRjVaNw15Js0ZpA00CQt8fWfKiO7HEMMKtYlKR/CKdOWCZjbQuRuj7g+kWrxJjLiZhRiPDkqpultgjtjmPzZ/NLekdqy3s1Rl0GAINZ81K52ft44a09CrHnMJqtnLi8EkaxbiTWIxaLc1DQtmbf5I2Xs6iYoKCaGQ0kVNS4tW4U0QGBBAfGsbzSxfywoDBNWYk5pWW8tyShdzeoRPBekUGtjbhaQgxUwihllI6gS+FECv9bJdCLUCogsF4NRiuqugDZgaVCTCc5XCErjvSMt0d2vMCKR1u1QvT32reuVID9dVm9alUKnRGHaWFZadT50+jbQvW1dUevqSgFFNwJesdjn0IVZRbWzLsU7Auc2dPOnORqkCQVkAg9IMQIa+71ftrMTFBQbQIb8TyQwcYlFD1DEMIQa8xXVn2yxomPDqa/QX5lFpt9PYgFLd+zhaS0uMJbvTXv0OJzUZ8SKhPs6jWjSPJOHnS63EAZoeD+NBQ+sbF8+T8uVyX1o5+cfEYtWerqZjtdpYcyOaH7VuZ0DqNQcrsq9bhiQMrF+7A/WYhxGvAUcD7PvUKdRYhhDslvSoJTF0XKJuEdGQhNF60JLGtBaHzaB2pciQ1hS7TeqWyfs6W83twabu70+5dxZWm/h87eJz83ELiWsee9bmUNqR1ISLkZQCEMIJhKOiHgCxzv4QeRJDXjUQvJ1e1bMW7a1eRHhVTbTiw19VdeeWmdxl650A+2bCWZiEhiBpq21wuF0umruSq+0ec9bnVYaeRjwkRiaHhLMnO8imbcGteLglhYYxs0ZL40DB+37OLyVs30SO2OZEBAQghOFZWyspDB0mLjOLxXn28FvFVuDR4EtOYCKiB+4EyoBkwzp9GKdQthFAjjKOQZZ+7xXs9QLqKkeVT3FqD0rdQENJJTYXBfSf0YOnPq06v4f1ls3Anf1jmVjpu6c+r6TG68/kah9ZloEk8L+FECIFQBSLUUQhVaJ1yXgDp0TFc0aIl/7doPnmlpVXu1ygmjHbD0rnlnS+JMJhIj4rhcEnVa0lSSn55+09MgUZSu50dxiy12TD62GYkLjQUh8vF3nzvZmEOl4u5+zIZkZwCuGdyT/XuxzvDR9EsJASzw0653UZscAjvDB/FU737Kc6rFlOjA5NSHpBSmqWUxVLK56SUj0gpMy+FcQp1CMMYUIUgS15zFxVXg3TlI4ufQ+i6u+uibGu8Pp2UDnAdr1DbqJqk9Hj0Rh3Lp609e4N9K+gHIC1/Im1bztp0dH8ea2ZupPfYbmef07EfWT4ZYbzOa3vrAmNbteGKFi15ZO5MPl6/huzCsxNYTpSXM2XbFua1cBCGBt13u+kWHsXcfZXfDopPFvPKze+zYMpSAsICmPrGH6ycvg6bxcbJ8nIKLGbUXtbSnSK7sID06Bh+3bXjvIeT6liSnUWToKDzpLYamwIY07IVf0vvyN/SOzKmZSsam5RAU22nunYq26hGGE9K6f/ufAp1BiFUEPgwlP0PWfgg6IeDYaC76WUF0pkHljnuEJxhFBjHg+sksugRMN2IV31SbWtBk+pOiXfmnC5qPt8uwe3/vYE37/wEvVFH1xEdkK5ypG05IuQdt/pIyetguhn0/cjNOsEHD3zO+EdGE9HELUskpQts65BlHyMC7nGr+9dTRqW0pFtsM+btz+S5JQvRqFTudipOByVWK33j4nlx4BBixwQz/aM5zHrwR7YOa8RCbWPap8QjVCpyMo/y3Uu/snNVBrEpMYx9cBRB4YFYyqxsWbSDae/NRI5KZFD7BDbl5lBstXiVHGF3Opm3P5N/9enPh+vW8MOObVzXpm2NocQdx/L4cstGnuunNJOvL4iqnl6EENWuzEopD/jFohro3LmzXL9+/eU4tYKHSEemOwPPtgZUjU+3U8GV787IMww/y+G4il9FaOIQJs9mNlJakUVPIYxjwZEFsgQReHbBsbnMwto/N7Lqj/WczMmnrNjMsYMnaN4qlnteCiG5rR1V8BMV9mZhOf4ehblZLJsRTMseE2g3oIu7j5l9m1tBX+gQAXcgtG0u2vdU23G4XOSVlWKx2zFotESYTOdlKZpLzbz/yzzmZ+2j/QYzzlIrOZm5pHZtwcRnJ5DY9vzbyOpdmTwzey7t1pURfmsHWjSNZkLrtPP2q4ol2VnM3Z/JSwOHkG8u5z+LF9CyUWOuTWtb6azJ4rCzYP9+ftixlUd79KZ9tGf1hgq1g86dO7N+/fpKn06qdGC1FcWB1R2kqxRcue6sPGECdZNK+4BJV35FTdk4twZidceUVmTJGyACEYEPgCxDFj2BMIxAGK9ASsmszxey8LtltOySTJ9x3WjWsglqrYa8A8dZ/esntGw9ly9fTyO5Y08CQwMoOl7MkcyjDLquGb1GFBAQeLiiH5gB1Alum85oAqpwNlJKPt2wjp25uRi/2c3I8b3pd03lrXK25B7ljVXLebBbT0qXZTPj9xXkXNWcp/sPIC2y5mzNg0WF/HvhfJ7o1Yc2FfuX2Wx8t30Li7OzaN04ku6xzQjS6bE6HOw5eYJF2ftpFRHJje3SSQj1rxalwsXnghyYEKI78D7QCtDhTugok1J6phR6kVEcWP1EOnPc8lCaVgjj6POyGaV0gG0N0vwLqOMQgX8/3eFZOvOQxc+BtiO/fKQla1cJd75yE2FRZ4QvXaXuWaHlT5zGx5n6zi5WTFvL6L8Po1lKE5I7xKM3KhrVviKl5LG3JrNZXcroHu0ZkZxCi/BGCCGwOZ2sOXyIWZkZHC0t4dEevU87qx9f+51DwsLmZBV3dexC7+ZxlSpdSCnZnHuUt1ev5PYOnegXf36266m09x3H8yiz29Gr1cQGhzAkMYnIgOo1IRVqLxfqwNZTSSGzlNJzIbiLiOLA6i+nnYx1jrtYWtOCU2r00rYe1DHugmFdz/NmQ9JVRMayl9Br1tG09TA0xm6gCnDPpOw7kLZV7kaUputPZxCu/H0ds79cyFPfPoAxUNG3uxAs5Vb+b/TL3P/139lQcpw5+/aSV1aGXq3G6nTSpnEkI1uk0K1ps7PEfvNzC3j5xnf52zd3M2n7Rsx2OyOSU+gU0xSTVovF6WBbXh4zM/dgczq5q2MXjzsiK9QPqnNgSiGzQq1BqALBNN5dPG3fBM4cd/hRFYYIHoXQNK9yrNViYNLzJp6aMgWNYTPSvsW97ib0CHU8IvT9sxJKAHqO6cKu1RmsnrGRAdf18vfl1WvWzdpESqck4mIjiSOSsa3a4HC5sDmdGDSaKvUDw6PDSGqfQMGag7x99Ugy8k8yc+8eZu/bi9lux6jREh8ayu3tO9E2KlrRIVQ4C6WQWaHWIYQadJ29GnPqBhoe3QRogmCkR+P6XdOTKS/9Qv9rz5/VKXhO9o5DtOpxdnamRqWqtLXKubTplcrBnYcRY7vRslEELRtF+MtMhXqGp4XMKpRCZoVazMrp6+g9zntF/KT28ajUKrK2HfSDVQ0HS5kVQ4BvOoGGAD2WMstFtkihIeBJP7BT6fIW4Dn/mqOg4Bv5Rwto2iLa63FCCJokRXMyJ5/Edt6111D4C4NJj83smQrLuVjLrehNSgKNgvdUOQMTQowRQtx3xvs1Qoj9Fa/xl8Y8BQXPcNidqDW+yTdpdRrsNsdFtqhh0TQlhj3rfBPo2bNuH81aKokZCt5TXQjxcWD6Ge/1QBegP3CvH21SUPAaU7CRkvyqNfyqo/hkCQEhNfezUqiabqM6smPlHorzvdO1LD5Zwq7VGXQd2cFPlinUZ6pzYDop5aEz3i+XUp6UUh5ESeJQqGWk9WrFutmbvR5XfLKE7B2HSOmU6AerLi5DVBMutwlVEhBsov2ANBb/4F2C8sLvltNhUFuljEHBJ6pzYGeVrEsp7z/jbWP/mKOg4Bt9x3dnxW9rcdi9CwWu+G2tcgO9SIy6ewir/9zA2lmbPNp/zcyNrJuziZF3DvazZQr1leoc2BohxJ3nfiiEuBtYW8n+CgqXjZjEKJokRjF/8lKPx5zIyWfxTyvpN6GHHy1rOIRFhnD/e7fx2wez+OPjOZQWllW6X2lhGdM/msP0j2Zz/3u3ExYZcoktVagvVJeF+DDwmxDiBmBjxWedcK+FXeVvwxQUvGXis9fwxm0fYgwy1uiUTuTk88E/PmfYLQOITVESCC4WTZKieeyLv/PHx3N5duzrpPVOpWWXZI5kHuXovjwOZxzl2MHjtOnZkkcn3Ut4tKJNqOA7nkhJDQROSXDvkFIu9LtV1aBISSlUx4kjJ/nggS+Ijo+k/7U9adkl+awC5aITxayYtpYlP69i+K0D65QCxxDVBOa5pl5uMzzm+OGTfP3MD2xdugu9UUdk8wgaN4sgtmUT9m3OorSwjD5ju9P/2p7oDLrLba5CLUVRo1doUJw4ks/3L//KutmbsFsdBISYCAgxERYVSklBKZ2HtqfvhO40Ta5bbTXqkgPLzy3ggwe+IK5VLENu7keTpPNr9A7sPMScLxdReLyYe9++haAwRXBX4XwuWAtRQaEuUF5i5pe3ZrBlyQ7S+7fhyckPUJxfSv7RAvIOnGD32r0YAgwktY+vc86rLlFWVMZ7902i11VdGTKxX5X7xbVuxp2vTeS392fx0UNf8tAndykdARS8QnFgCvWC4vwS3vv7ZyR3SOS53x4nIPj8ui4pJVnbDvLVMz+Qf7SA4bcpnXn9wR8fz6VVt5RqndcphBBc9Y8RfPH0d8z7ZilX3D3kElioUF/wRAtRQaFWY7fZ+fjhr0jv14ZrHx9TqfMC980ysV0c//zi76yesZ6V09ddYkvrP+YyC+vnbmHYrf09HiOEYMQdg1jx2xqcDqf/jFOodygOTKHOs272ZowBBq64Z6hHivLB4UHc9frN/P7hbOw2+yWwsOGw9s+NtOySTGhj71LjmyRFE9ksgi2Ld/jJMoX6iBJCVKjzLPtlNaPuGuJVO5QmSdE0TYpm88LtdBl+eWWMvnn2JyY/71lyhidqHBOfmcDNz15zoWb5xL4t2bTr19qnsW37tmbf5mw6Dm53ka1SqK8oDkyhTnNozxFKC8tofU4vKk/oO6EHi75fftkd2M3PXuORw6kLWYjmUgvGQN/aqpiCjRzdl3eRLVKozyghRIU6TW72ceLbNEflQePEc0lo25zcA8f9YFXDRW/UYbP4Fpa1mW3ojEo9mILnKA5MoU5jt9jR6bU+jdUZtNh9vNkqVE5MYhT7Nmf7NHbf5myiEyIvrkEK9RrFgSnUaYxBBsqKKtfcq4myonIMPoa7FCqn51VdWT9nE5Zyq1fjik4Us2vNXrqOaO8nyxTqI4oDU6jTJLaLI3NzNuZSs9djNy/aQUrH2t9GpS4RFhlCi46JrPzduxKFJT+touPgdkpXAAWvUByYQp0mJCKYVt1asHamZy08TuFyuVj2y2r6Kkr0F53R9w5jzpcL2b12r0f7b1ywjdUz1jP8tgF+tkyhvqE4MIU6T98JPZg/ZSllxeUej1k7cxOGAD0JbZv70bKGSUxiFHe8chNf/vt7lv68qspaO0u5lXnfLOGn13/n3rdvUZTpFbxGSaNXqPO06JhIer82fPLwV9z7zq2YgqoPQ21fsZtp7/3JAx/d6VXtmILnJHdI4OoHRjH1zel8/vR3xLdpRnKHBNoPTEOlUrFjxW7Wzd5EUvsEHp10L41jG11ukxXqIIoDU6gXjH1oFL+8NYM3bvuQEbcPov3ANLS6s7MTTxw5ydKfV7N21ibufuNviqCvH5BSsuqP9Sz+cQXWchv9JvQEJDtXZbB6xgb++GQujWPD6TG6C09/9xBhUaGX22SFOoziwBTqBSqVign/vJKtS3ey+IcV/Pz2DNL7tUGtUZOxPpOMDfspyS8luFEQzVKbsHvNXsJjQr2WPFKoGqfDyeTnp5J34DhX/WMkqV2TT9fnXfn34YBbqX7l7+uZ/+0SOgxqqzgwhQtC6QemUC85uPsIk578lkN7ckhKj6fTkHb0HNMFrV7L8cMnWfnbOjbM20J6/zZc+8RVPteSKbiRUvLtCz9TfKKEO1+7qcYGlfu3HuDTf37NXa/fTFJ6/KUxUqFOojS0VGhQlJeYeffe/9G8VSzjH7miyh5T5jIL3730K4XHivjHB7crXYEvgJ2rM5j6xnSe+OYfGEye9fTasmQH096byTNTH/VJSUWhYVCdA1P+ahTqFVJKJj3xLUnp8dzw9NhqGyQaAwzc+uJ1NGoSxtf/+ekSWln/WDp1FQNv6OOx8wJo17c1Wp2GjPX7/GiZQn1GcWAK9Yq9G/dTeKKY8Y+O9ijDUKVScdP/jSdr+0EOZ+RcAgvrHwV5hezbnEWX4d6paAgh6Du+B0unrvKTZQr1HcWBKdQrlk5dRb/xPbwKSWm0Gnpf3Y2lP6/2o2X1l+wdh0hqn+DV7OsUaX1asX/bQT9YpdAQUByYQr2hrLjcrac3qqPXY3td1YX1czcrDS594EJaqBgDDVjKLBfZIoWGguLAFOoNRceLCY0MwRjg/c00JCIYnUFHWZHnah4KbvRGHTazzaexNrMNvdJCRcFHFAemUG+w2xyoNb7/SWt1Ghx250W0qGHQJDmarO0HcTq8/+72btxPTGK0H6xSaAgoDkyh3hAQYqIkvxRfSkOcTielhWU1ylApnE9MQhSNYxuxZfEOr8cunbqKvuO7+8EqhYaA4sAU6g2NYsIwBhnJ3JTl9djty3bTNDlGcWA+0md8DxZ+txyXy+XxmAM7D3Hs0AnS+7fxo2UK9RnFgSnUG4QQ9PMxLXvJ1FVKaxUfsZRbiW8TC8APr/7mkRM7kZPPp49NZtzDo1Fr1P42UaGeomghKtQruo7swIz/zSNzcxbJ7RM8GrNj5R6O7s+lw6A0P1tXf7Db7Gycv41lP6/mUEYOASEmLGUW1s3exKYF27jj5Rto2aXFeeNcLhc7Vuzh+1emMexv/ek8NP0yWK9QX7hkUlJCiBuBJyrelgL3Sim3VGy7Dngc+EZK+U51x1GkpBRqYueqPXz97E/c88bNJLSNq3bfdbM38fEjX5PSOQmDSY/BpCOuTTN6julCSETwJbK4brF3434+f/o7miZH03dCD9J6p6JWu2dRR7Py+N9jk9myaDuxKU24/umxhEWF4LA7ObL3KMunrSEgxMQVdw0hrXery3wlCnWBWqGFKIToCeySUhYIIUYAz0opu1Vs+w0YB0wB7pBSllZ1HMWBKXjC9uW7+Oa5qXQd0YE+47oTFdf4rO1bl+3kq3//QNb2gwy+qS+9r+6G3qTDUmZl56oMNs7fSmrXZK56YCQRTcIv01XUPnauzuDrZ37g1hevJ7Xr+TOsU5QUlPD6LR9x/MhJUjolodNrCYsOpddVXYhr3ewSWqxQ16kVDuyskwoRBmyXUjateP87MBb4FrhLSllS1VjFgSl4Sn5uAct+WcPK6euIjG1EeEwYUkqydx5ix/I9dB/dib89ew2RzRufN9ZcambJT6tYMnUl9717G7EpTS7DFdQuTuTk8/otH3DnaxM9Cs86nU4+efhrYhKjGPvQqEtgoUJ9pDaK+d4OzDrj/a/AemB9dc5LQcEbwqPDGHPfcF7840lG3DmY1j1b0iy1KQVHC/n3jw/z2Bf3Veq8AIyBRobfNpDxj4zmo4e+JD+34BJbX/tY+tMquo3q5PHaolqtZuKzE1g5fR3lJWY/W6fQELnkDkwIMQC3Azu1HoaU8mspZQcp5ZuX2h6F+o9Wp6V19xS6jezI4T05jLxzMB0GtvVobKch6XS/ojMzP1vgZytrNzarnVUz1tNnnHc1W8HhQbTqnsKaPzf6yTKFhoxfHZgQ4j4hxOaKVxMhRDtgEjBGSnnSi+OUnXplZXlf46OgAFCcX8L2Fbu9Tpfvf11PNi3cRllxw5WZ2rlyD81SmtA4tpHXY3tf3ZW1sxQHpuAbWVlZZ/mAM7f51YFJKT+UUraXUrbHnbL/KzBRSpnh5XECTr0SEjwLXygonMvqPzbQfkAaAcEmr8YFhwfRpmdL1s7c5CfLaj9FJ0po3CzCp7GNmzWi6ISyMqDgGwkJCWf5gDO3Xco6sGeARsBHFX2aHFLKzpfw/AoNnCN7j9K6Z0ufxrbolMSBHYcuskV1CCnxoL1apQghoI51fleoG1wyByalvAO441KdT0HhXKxmGzqD1qexBpMOq4+K6/WBwLAA8nMLfRqbn1tIYFhAzTsqKHiJosSh0GAwBOgxl/rWe+pCel7VNWwWG3vW7aOkoBQhBCERQaR0TuL7l6dReLyI0MYhXh1v9R8b6DionZ+sVWjIKA5MocGQ0DaOHSv20PPKLl6P3b58N+0HplGQV8i+LQcwl1rQGbREJ0QS1yrWD9Zeeo4fPsnSqatY/ecGmiZFn66bO37oJCdy8jEFG5k3eSkTHhnt8THLS8xsWmIECIQAABV9SURBVLiNZ35+1I+WKzRUFAem0GDoOrIDMz6Z4/Us4viRk2xfsRuQTHv3T1I6JWEMMmKz2Jjx6VwCQkz0Hd+DLsPbo9X5FqK83GxetJ3v/vsrPUZ35omv7yei6dnZhkf35zHj03l8/99fiUmMovdVXWs8ppSSn17/nfT+bQgOD/KX6QoNGMWBKTQYjAEGOg1J5//bu/PwKKp8jePfX0L2IAZQVjEJoigIASKLCqLsuCHLqIOKuA2juI2KOo9X4T7eO+qIOjMoMiIKDo6goI4OIy4sgiwSUPZFJaDIEkQQSEK2PvePrsSASUjnhiRl3s/z5El31anq04em39SpqnM+fHUBv3ngynJtU1BQwNMjXyAvJ59ze7Thpv8dTnRsVNH6QCDAhqVbmPf6YhbPXs6oZ0b47st6zacbeOPJd7jjrzeVejTZJLkRtz55HQ2aJvDsrRMJDw+j2+WlX4NVUFDAjCffJeO7H7hn4m0nqupSy2k6FalVLhvVlw1LNzP/jc+OW9Y5x+O/eZZdW/fwxNxH6D64y1HhBRAWFkbbC1pz54Sbad25FX+7YzLZh/0z6kTmwSxeGzeTUeNHlKsrdPDdlzL8kaH8eeTzTH1sBts3HH1lZnAIriX8z7XP8eOu/dw54RYioyNPVPWlltMRmNQq8SfHMXrCLUy482V2bd1D7+t7cGoJ9zft3pbB1EdnsDnta55ZMI4GTRLK3K+Zcfnv+3L4QCazn5vD8EeGnKi3UKmWvbeSNhe0JrFN+QfYHXz3pWxdvZ3szCNMfmg6GNRNiCcvN5/9uw/QuvMZXPPgIFp1TMYqeu29SDkowKTWadi0Pg9MuZ0Ppy5k/M0v0PzMprTu3IrouChvNPrN7Ny6h+xD2dz1wq00TmpUrv0Whti4IU8z6K4BId8wXdUCgQCLZi3lhrFXh7xtr+u6M+/1xYx7ZwwZ3/5A9qFsIqIiSGhUj7h6umReqoYCTGqluHpxXHXXQC4b1YdVH69lx+adZHz3AzFx0Zw/qDMNm9fnpTH/4Lz+KSHtt25CPG0vbM2y91bSa3j3E1T78vtu8/fs2LKL3OxcouOiSGzbomhqmR927CM/r4Ckc1uEvN92F53Dq4/OICc7l8aJp1Z2tUXKRQEmtVpEZARdBnaky8CORy3/cOoCOvY6t2iixlCk9m3PvNcX02t496KLPBbPWsbubRnkZOcSEx9Ny/ZJ9BjWldPOalZZb6VIfl4+aXNX8+lbSzn042FapiQSFRPFkcwjzP7rHJq1bEz3oV2p17AudevHV6ibLzw8nLh6sWQfyiYmrnbcHyc1jwJMpASZP2URnxBfoW3r1o8n61A2qxes561n3yu6zH5wyqVEREeSfSibNQs38OJ9Uzn51Hpc98hQmiSXr5vyuPU+mMXf75+GmTHg5l60ueAswsJ+vlYrLzePL+ev54Mp84iKiSL3SF6FX6sgL586kfoKkeqjT59ICepE1qEgL79C2+bnFbBv535mPPUOIx+/llYdk49an3BqPZq2bEyfERex7L2VPDdqEqPGjyDp3NN/sa/tG75j0azlfP/1LnKycoiKjSKxTQt6DO36i9DLPZLL83dNIenc0xly76VHBVehiMgIzuuXQsrFbXhpzD9YMfcLsg5nExsfE9J73J/xE/l5BTX+PJ/8uinARErQoGkCaz/dWKFtl7y7gj3b9/LMwnG/uCG4uPDwcC4Y1Jl6Desy6YHXuH/K7TRsWh+ArWu28+b4f3H4QCbdB3flwsFdiIqJJPvwEdYv2cxfbn+JxqefwtUPDioKsvdf/IiGzeoz9A+XHbdbMCIygtv+fD2r569j2qMzGPXMjSG9x8/e/pzOAzoSXif0LlaRyqL7wERK0LF3O77+Yiv7M34KabtAIMB/Xv6Eax4aVGZ4Fdf2wrPpdnkq86YvAmDtoo1Mun8qva/rwbi3x9B3RE8S25xGk+RGJLc7nctH9eXx9x6iU78Unhs1ia1rtpOTncPS91ZwxR39y31Oq05EHYbdfwUL3lxKQUFBud9jXm4en72znB5DQ5vcUqSyKcBEShAdG0WnviksemtZSNstnLmEQEGAfiMvDmm7HsO6seKDL9iyciuv/feb/P7ZkXTq077EbkAIhk/3wV24YezVTHpgGp+8vpjkdolFR3Dldcnw7kRGRTDpvmm4ckx5EggEeG3cm5zRIbnSztuJVJQCTKQUva/rzmfvfs7G5V+Vq/yBvT8xbexM+tzQM+SrFxNOrccZHZKZ+tgMBo0eUO4bi9ucfxYXDTufD19dQMc+oY/4HhYWxuB7LmXd4k38809vk5OdU2rZrEPZvPzQdA7+cIjrHxsW8muJVDYFmEgpGjZrwK1PXMer//VPPv/PFwQCgVLL7tiyk/G3TKR+44QKd60lNKrHrm92c96A0O496z6kC7vT91T4isAGTevTeWBHsg8f4ZHL/sSbT/+LHVt2knkwi8yfMklf9y3TH5/Fo1c+SdzJcdzxt5uIjPLnoMXy66KLOETKcEaHJO6ccAtTx85kzuSP6TGkK+16tiG2bgw52bmkr9nOp28uZff2vVx110AWzPiswkGydc12WpzdPOQR7esmxNOweQPWfrqRTr1DPwrLz80nJj6aq8dcyY+797N49udMfng6h348TFiYcVLDkzivXwqPvnWf7wYqll83BZjIcTQ/syl/nH43W72w+uT1Rd58YJE0TjyVC4d0JeXiNtSJqMPyf6/i8P7MCr3Ovp37adkhqWJ1bNWEbeu/rdC2O7bspGnLxgDUb5zAFbf344rb+1VoXyJVSQEmUg5mRsv2ibRsn1hmubO7tmLVx2s4t/vZIe0/EAiwe1sG/Ub2rFD9zul2FrOfe5+CgoKQzr9lHsziy/nruHJ0/wq9rkh10jkwkUp0/hWprPl0A4cPhHYUtnHZV0TFRFK3gl10MfHRxCXEsXr++pC2W/LuCtpe0Fpdg+JLCjCRShRXL46Unm2Z89LH5d4mLzePOZM/pstlnVizILQAKvTlgnX0v/FiZvz5XTK+3Vuubb5ZvY2PX1sY8iX/IjWFAkykkg2+91I2ff4VH0yZd9x7q3Jz8pjyx39Sv9HJDH9kCFtWfhPyzdPfbvqeAxk/MfC23gwaPYBnfzeJr1ZtLbW8c44v5q1l0v3TGDHu6qLzXyJ+o3NgIpUs7qRY7nz+Vibe+wrb1n9Hr+HdOaND0lEjZOTn5fPl/PV8NG0Bp7Y4hRvGDiMiMoLUfh34z+RPuPbhq8o1okYgEGDO3z+i++CuhIeH0+3yVOLqxTJt3EziT46jx9ButOqUTHRsFNmHj7Bu8SYWzVqKhYUxavwIktv9cvxFEb+w8tx9X5Okpqa6tLS06q6GyHHlZOew7L2VLHxrKWZGcrvTiYqJJOtgNuuXbqZpciN6DOtG+55tikbcyDqUzfhbJtKpdzsG3NKrzBALBALMfOpddm3dw+gJNx91+X0gEGDDks1HDQQcHR9dNBDwsYEqUlOlpqaSlpZW4odVASZygjnn+PqLdHZv20uuNx9YUrsWNCllpucDe3/ihXte4ZRmDeh9w0UktjntqLBxzrEl7RvmvjKfQEGA256+gdi6oY0mL+IXCjARnzmSlcOiWctYNGsZsXVjOLNTS6Jifx6NPiw8jB5Du3H+lakh3/gs4icKMBGfCgQCbFr+Fd9/tZsjWTlEx0WR1LYFLVMS1QUotUJZAaaLOERqsLCwMM7pdhbndDuruqsiUuPoMnoREfElBZiIiPiSAkxERHxJASYiIr6kABMREV9SgImIiC8pwERExJcUYCIi4ksKMBER8SUFmIiI+JICTEREfEkBJiIivqQAExERX1KAiYiILynARETElxRgIiLiSwowERHxJQWYiIj4kgJMRER8SQEmIiK+pAATERFfUoCJiIgvKcBERMSXFGAiIuJLCjAREfElBZiIiPiSAkxERHxJASYiIr6kABMREV9SgImIiC8pwERExJcUYCIi4ksKMBER8SUFmIiI+JICTEREfEkBJiIivqQAExERX1KAiYiILynARETElxRgIiLiSwowERHxpSoPMDM7z8wKzGxosWXXmNkqM7unqusjIiL+VKUBZmbhwJPA3GNWXQOcB3Q1s/iqrJOIiPhTVR+B3QnMAjKOWW7eb1fssYiISKmqLMDMrBlwFfBiCatnA2lAmnPuUFXVSURE/KtOFb7Wc8CDzrkCs6MPspxzU4GpJW1kwcKZBI/OqF+//gmupoiI1BTp6emYWab31IA455yDExxgZnYHcKv3tB7whhdeDYGBZpbvnHunrH14FY0tfJ6amupOUHVFRKSGSUpKYt++fXElrTuhAeacex54/tjlZvYq8P7xwktERKQ0ug9MRER8qSrPgRVxzt1YHa8rIiK/HjoCExERX1KAiYiILynARETElxRgIiLiSwowERHxJQWYiIj4kgJMRER8SQEmIiK+pAATERFfUoCJiIgvKcBERMSXFGAiIuJLCjAREfElBZiIiPiSAkxERHxJASYiIr6kABMREV9SgImIiC8pwERExJcUYCIi4ksKMBER8SUFmIiI+JICTEREfEkBJiIivqQAExERX1KAiYiILynARETElxRgIiLiSwowERHxJQWYiIj4kgJMRER8yZxz1V2HkDRs2NAlJiZWdzWOkp6eTlJSUnVXw1fUZqFTm4VG7RW6mthm6enpbt++fSUebPkuwGoiM8t0zsVVdz38RG0WOrVZaNReofNbm6kLUUREfEkBJiIivqQAqxyzq7sCPqQ2C53aLDRqr9D5qs10DkxERHxJR2AiIuJLCjAREfElBVgFmVm4mX1hZu97z5ua2Twze9fM4qu7fjWJmZ1mZvPNbKOZrTezu73larNSmFl/M9tsZl+b2UPeslrfXmYWbWafm9lq77M0zls+1sy+N7MvvZ+B3vIIM5tqZmu9z9/DxfbV08zSzOyp6no/VSHUNvPWtTOzpV75tWYW7S2vUW2mc2AVZGZ/AFKBk5xzl5nZE8BrQDLQzDn3YrVWsAYxsyZAE+fcKjOrC6wEBgE3oDb7BTMLB7YAfYAdwArgWtRemJkBcc65w2YWASwG7gb6A4edc08fU/63wBXOuWvMLBbYAPR0zm0zsxnAjcDjwEvOuU1V+V6qSgXarA6wCrjeObfazBoAB5xzBTWtzXQEVgFm1hy4FJhcbHE4EPB+rDrqVVM553Y551Z5jw8BG4FmqM1K0xn42jm31TmXC7wBXInaCxd02Hsa4f2U9Ve4A+K8L+UYIBc46K0L89b/qtuzAm3WF1jjnFvtbb/POVfgratRbaYAq5jngDEE/xELTQAmAaOAf1RHpfzAzBKBDsBy1GalaQZ8V+z5Dm+Z2oui7vsvgQzgI+fccm/VaDNbY2ZTzCzBW/YWkAnsAr4FnnbO/eitmwwsAcKccxur8C1UuRDb7EzAmdlcM1tlZmOK7apGtZkCLERmdhmQ4ZxbWXy5c267c66Hc+5y7yhDjuGdt5kF3OOcO6g2K1VJf9k6tVeQc67AOZcCNAc6m1lbYCLQEkghGFbjveKdgQKgKZAE3Gdmyd5+5jrnOjrn7qvq91DVQmyzOsCFwHDv91Vm1svbT41qMwVY6C4ArjCzbQS7di4xs1r713B5eX3vs4Dpzjlf3SxZDXYApxV73hzYWU11qbGccweABUB/59we70s6ALxEMLgAfgt84JzLc85lAJ8RPHddK5WzzXYAC51zPzjnsoA5QMdqqfBxKMBC5Jx72DnX3DmXCFwDzHPOXVfN1arRvJPILwMbnXPPVHd9fGAF0MrMkswskuDn7F/VXKcawcxOMbOTvccxQG9gk3ehUKGrgHXe428J/pFpZhYHdAV+lRdrlKYCbTYXaGdmsd65w4sIXvxS49Sp7gpIrXABcD2w1uuHB/ijc25ONdapxnLO5ZvZaIJfJOHAFOfc+mquVk3RBJjqXakZBsx0zr1vZq+ZWQrBCwy2Ab/zyj8PvELwy9mAV5xza6q+2tUqpDZzzu03s2cI/iHlgDnOuX9XT9XLpsvoRUTEl9SFKCIivqQAExERX1KAiYiILynARETElxRgIiLiSwowERHxJQWY1Dpm1sjMXjezrWa20ps24qrjbJNoZuvKKlPGtjeaWdNizyeb2Tnl3LaneVP2nChmtsT7neiN3h7q9jea2YTKr5lI2RRgUqt4o4K8A3zqnEt2znUiONJF8xP4sjcSHIsPAOfcLc65GjOygXPufO9hIsGhl0R8QQEmtc0lQG7xubS8QXL/BkVHIYu8UbhXmdn5x+6grDJmNsabAHC1mT1hZkMJjr033Zs0MMbMFphZqle+v7eP1Wb2SXnfhJn1suCEqmu9kcSjvOXbzGyct8+1ZtbaW36KmX3kLZ9kZtvNrKG3rnCqjSeA7l497z32yMrM3jeznt7jkWa2xcwWEhxphWKvM8vMVng/RetEKpsCTGqbNgQn6ytNBtDHOdcRuBr4a3nLmNkAghN1dnHOtQeecs69BaQBw51zKc657MKdmNkpBAdRHeKVH1aeN2DB2XFfBa52zp1LcEi43xcr8oNXt4nA/d6yxwiO29kReBtoUcKuHwIWefV8tozXbwKMIxhcfYDi3aF/AZ51zp0HDOHoOfNEKpXGQpRazcyeJzhlRK73pRsBTPDGiCsgODfSsUor05vgWHtZAMXmnSpNV4JdmenlLF/oLCDdObfFez4VuIPgPHUAhaP9rwQGe48vJDhgK865D8xsfzlfqyRdgAXOub0AFpylt3gbnBPsqQXgJDOrW5unf5ETRwEmtc16gkcGADjn7vC60tK8RfcCe4D2BHsojpSwj9LKGGXPdHusUMsX364sOd7vAn7+P16R2XPzObqXJrrY49LqHQZ0K36kKXKiqAtRapt5QLSZFe9yiy32uB6wy5sj6XqCo8Efq7QyHwI3mVksgJnV95YfAuqWsJ+lwEVmlnRM+ePZBCSa2Rne8+uBhcfZZjHwG+91+gIJJZQ5tp7bgBQzCzOz0/h5vqjlQE8za2DBed6Kd31+CIwufOIdpYqcEAowqVVccPqFQQSDI93MPifYBfegV+QFYISZLSPYLZZZwm5KLOOc+4DgvF1p3rQxheefXgVeLLyIo1hd9gK3AbPNbDUwo5Rq9zKzHYU/QAdgJPCmma0FAsCLpWxbaBzQ18xWAQMIzsB7bLfeGiDfu6DkXoKTP6YDa4Gn8c4dOud2AWMJBvDHHH1O8S4g1YLT1G8ARh2nXiIVpulURGoB7yrFAm+usW7ARG+KeRHf0jkwkdqhBTDTzMKAXODWaq6PyP+bjsBERMSXdA5MRER8SQEmIiK+pAATERFfUoCJiIgvKcBERMSX/g9fWJGxjoVlQwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%%time\n", "bkg_estimator = ReflectedRegionsBackgroundEstimator(\n", " observations=observations,\n", " on_region=on_region,\n", " exclusion_mask=exclusion_mask,\n", ")\n", "bkg_estimator.run()\n", "bkg_estimate = bkg_estimator.result\n", "bkg_estimator.plot();" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 788 ms, sys: 21.4 ms, total: 809 ms\n", "Wall time: 739 ms\n" ] } ], "source": [ "%%time\n", "extract = SpectrumExtraction(\n", " observations=observations, bkg_estimate=bkg_estimate\n", ")\n", "extract.run()\n", "extract.compute_energy_threshold()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Model fit\n", "\n", "The next step is to fit a spectral model, using all data (i.e. a \"global\" fit, using all energies)." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OptimizeResult\n", "\n", "\tbackend : minuit\n", "\tmethod : minuit\n", "\tsuccess : True\n", "\tmessage : Optimization terminated successfully.\n", "\tnfev : 75\n", "\ttotal stat : 226.10\n", "\n", "CPU times: user 247 ms, sys: 5.19 ms, total: 252 ms\n", "Wall time: 250 ms\n" ] } ], "source": [ "%%time\n", "model = models.PowerLaw(\n", " index=2, amplitude=1e-11 * u.Unit(\"cm-2 s-1 TeV-1\"), reference=1 * u.TeV\n", ")\n", "\n", "for dataset in extract.spectrum_observations:\n", " dataset.model = model\n", "\n", "fit = Fit(extract.spectrum_observations)\n", "result = fit.run()\n", "print(result)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Spectral points\n", "\n", "Finally, let's compute spectral points. The method used is to first choose an energy binning, and then to do a 1-dim likelihood fit / profile to compute the flux and flux error." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SpectrumDatasetOnOff\n", "\n", " Total counts : 2376 \n", " Total predicted counts : nan\n", " Total off counts : 34922.00\n", "\n", " Effective area min : 1.60e+06 cm2\n", " Effective area max : 6.08e+10 cm2\n", "\n", " Livetime : 5.29e+03 s\n", "\n", " Number of total bins : 72 \n", " Number of fit bins : 72 \n", "\n", " Fit statistic type : wstat\n", " Fit statistic value (-2 log(L)) : nan\n", "\n", " Number of parameters : 0\n", " Number of free parameters : 0\n", "\n", " Acceptance mean: : 1.0\n", "\n" ] } ], "source": [ "# Flux points are computed on stacked observation\n", "from gammapy.spectrum import SpectrumDatasetOnOffStacker\n", "\n", "stacker = SpectrumDatasetOnOffStacker(extract.spectrum_observations)\n", "stacked_obs = stacker.run()\n", "\n", "print(stacked_obs)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "Table length=4\n", "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
e_refe_mine_maxref_dnderef_fluxref_efluxref_e2dndenormloglikenorm_errcounts [1]norm_errpnorm_errnnorm_ulsqrt_tstsnorm_scan [11]dloglike_scan [11]dndednde_uldnde_errdnde_errpdnde_errn
TeVTeVTeV1 / (cm2 s TeV)1 / (cm2 s)TeV / (cm2 s)TeV / (cm2 s)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)1 / (cm2 s TeV)
float64float64float64float64float64float64float64float64float64float64int64float64float64float64float64float64float64float64float64float64float64float64float64
1.5651.0002.4481.110e-121.634e-122.437e-122.717e-120.9252.2860.191370.2020.1811.3507.47555.8810.200 .. 5.00027.984966330999157 .. 150.568763834041531.026e-121.498e-122.122e-132.243e-132.006e-13
3.8312.4485.9951.513e-135.455e-131.992e-122.221e-120.8461.9560.205230.2200.1911.3156.90647.6970.200 .. 5.00020.634204716592542 .. 120.321864619560341.280e-131.990e-133.106e-143.324e-142.896e-14
8.7995.99512.9152.379e-141.666e-131.415e-121.842e-120.56110.8220.26870.3010.2371.2353.1239.7520.200 .. 5.00013.581463576745378 .. 71.416396622609161.333e-142.938e-146.369e-157.162e-155.627e-15
20.20912.91531.6233.740e-157.113e-141.370e-121.528e-120.5455.5520.35130.4220.2871.5412.7617.6230.200 .. 5.0007.176513233902151 .. 36.717194682218552.037e-155.764e-151.315e-151.580e-151.073e-15
" ], "text/plain": [ "\n", " e_ref e_min e_max ... dnde_err dnde_errp dnde_errn \n", " TeV TeV TeV ... 1 / (cm2 s TeV) 1 / (cm2 s TeV) 1 / (cm2 s TeV)\n", "float64 float64 float64 ... float64 float64 float64 \n", "------- ------- ------- ... --------------- --------------- ---------------\n", " 1.565 1.000 2.448 ... 2.122e-13 2.243e-13 2.006e-13\n", " 3.831 2.448 5.995 ... 3.106e-14 3.324e-14 2.896e-14\n", " 8.799 5.995 12.915 ... 6.369e-15 7.162e-15 5.627e-15\n", " 20.209 12.915 31.623 ... 1.315e-15 1.580e-15 1.073e-15" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "e_edges = np.logspace(0, 1.5, 5) * u.TeV\n", "\n", "stacked_obs.model = model\n", "\n", "fpe = FluxPointsEstimator(datasets=[dataset], e_edges=e_edges)\n", "flux_points = fpe.run()\n", "flux_points.table_formatted" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot\n", "\n", "Let's plot the spectral model and points. You could do it directly, but there is a helper class.\n", "Note that a spectral uncertainty band, a \"butterfly\" is drawn, but it is very thin, i.e. barely visible." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "model.parameters.covariance = result.parameters.covariance\n", "flux_points_dataset = FluxPointsDataset(data=flux_points, model=model)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 6))\n", "flux_points_dataset.peek();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises\n", "\n", "* Re-run the analysis above, varying some analysis parameters, e.g.\n", " * Select a few other observations\n", " * Change the energy band for the map\n", " * Change the spectral model for the fit\n", " * Change the energy binning for the spectral points\n", "* Change the target. Make a sky image and spectrum for your favourite source.\n", " * If you don't know any, the Crab nebula is the \"hello world!\" analysis of gamma-ray astronomy." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# print('hello world')\n", "# SkyCoord.from_name('crab')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What next?\n", "\n", "* This notebook showed an example of a first CTA analysis with Gammapy, using simulated 1DC data.\n", "* This was part 2 for CTA 1DC turorial, the first part was here: [cta_1dc_introduction.ipynb](cta_1dc_introduction.ipynb)\n", "* Let us know if you have any question or issues!" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 2 }