{ "cells": [ { "cell_type": "markdown", "id": "07c6d97a-7350-4920-9ab8-26c2454bf5a7", "metadata": {}, "source": [ "# Diffuse 511 Spectral Fit in Galactic Coordinates\n", "\n", "This notebook fits the spectrum for the 511 keV emission in the Galaxy. It can be used as a general template for fitting diffuse/extended sources in Galactic coordinates. For a general introduction into spectral fitting with cosipy, see the continuum_fit tutorial.
\n", "\n", "This notebook uses two 511 keV emission models, first a test model and then a realistic multi-component model. \n", "\n", "All input models are available here:
\n", "https://github.com/cositools/cosi-data-challenges/tree/main/cosi_dc/Source_Library/DC2/sources/511
\n", "\n", "The toy 511 model consists of two components: an extended Gaussian source (5 degree extension) and a point source. In the first part of this tutorial, we fit the data with just the single extended Gaussian component, i.e. we ignore the point source component. This is done as a simplification, and as will be seen, it already provides a good fit. In the second part of this tutorial we use a model consisting of both components. \n", "\n", "The realistic input models consist of a bulge component (with an extended Gaussian source and a point source) as well as a disk component with different spectral characteristics. In the third part of this tutorial we use this model. \n", "\n", "For the background we use just the cosmic photons. \n", "\n", "This tutotrial also walks through all the steps needed when performing a spectral fit, starting with the unbinned data, i.e. creating the combined data set, and binning the data. \n", "\n", "For the first two examples, you will need the following files (available on wasabi):
\n", "**20280301_3_month_with_orbital_info.ori
\n", "cosmic_photons_3months_unbinned_data.fits.gz
\n", "511_Testing_3months.fits.gz
\n", "SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5
\n", "psr_gal_511_DC2.h5**
\n", "\n", "The binned data products are available on wasabi, so you can also start by loading the binned data directly.
\n", "\n", "For the third example, we start with the binned data, and you will need: \n", "
**combined_binned_data_thin_disk.hdf5**
\n", "\n", "**WARNING:** If you run into memory issues creating the combined dataset or binning the data on your own, start by just loading the binned data directly. See the dataIO example for how to deal with memory issues.
" ] }, { "cell_type": "code", "execution_count": 7, "id": "19640dd6-f894-4b9c-9405-aa76f8c8864c", "metadata": {}, "outputs": [], "source": [ "# imports:\n", "from cosipy import COSILike, test_data, BinnedData\n", "from cosipy.spacecraftfile import SpacecraftFile\n", "from cosipy.response.FullDetectorResponse import FullDetectorResponse\n", "from cosipy.response import PointSourceResponse\n", "from cosipy.threeml.custom_functions import Wide_Asymm_Gaussian_on_sphere, SpecFromDat\n", "from cosipy.util import fetch_wasabi_file\n", "from scoords import SpacecraftFrame\n", "from astropy.time import Time\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "from astromodels import *\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "from threeML import PointSource, Model, JointLikelihood, DataList, update_logging_level\n", "from astromodels import Parameter\n", "from astromodels import *\n", "from mhealpy import HealpixMap, HealpixBase\n", "import healpy as hp\n", "import numpy as np\n", "import matplotlib.pyplot as plt \n", "from pathlib import Path\n", "import os\n", "import time\n", "import h5py as h5\n", "from histpy import Axis, Axes\n", "import sys\n", "from histpy import Histogram" ] }, { "cell_type": "markdown", "id": "754b1f19-2b05-47ff-93ce-2b98c477f0a9", "metadata": {}, "source": [ "## Get the data\n", "The data can be downloaded by running the cells below. Each respective cell also gives the wasabi file path and file size. " ] }, { "cell_type": "code", "execution_count": null, "id": "e2c3fd76-534d-4567-9b66-477260a169d8", "metadata": {}, "outputs": [], "source": [ "# ori file:\n", "# wasabi path: COSI-SMEX/DC2/Data/Orientation/20280301_3_month.ori\n", "# File size: 684 MB\n", "fetch_wasabi_file('COSI-SMEX/DC2/Data/Orientation/20280301_3_month_with_orbital_info.ori')" ] }, { "cell_type": "code", "execution_count": null, "id": "8abd531b-b531-4bdc-8ded-4e971767326c", "metadata": {}, "outputs": [], "source": [ "# cosmic photons:\n", "# wasabi path: COSI-SMEX/DC2/Data/Backgrounds/cosmic_photons_3months_unbinned_data.fits.gz\n", "# File size: 8.5 GB\n", "fetch_wasabi_file('COSI-SMEX/DC2/Data/Backgrounds/cosmic_photons_3months_unbinned_data.fits.gz')" ] }, { "cell_type": "code", "execution_count": null, "id": "6370eca6-8791-460c-82a4-7b5f5346382a", "metadata": {}, "outputs": [], "source": [ "# 511 test model:\n", "# wasabi path: COSI-SMEX/DC2/Data/Sources/511_Testing_3months_unbinned_data.fits.gz\n", "# File size: 850.6 MB\n", "fetch_wasabi_file('COSI-SMEX/DC2/Data/Sources/511_Testing_3months_unbinned_data.fits.gz')" ] }, { "cell_type": "code", "execution_count": null, "id": "7aac0743-04cb-4cee-a858-6d1bb2d3b192", "metadata": {}, "outputs": [], "source": [ "# detector response:\n", "# wasabi path: COSI-SMEX/DC2/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\n", "# File size: 350.4 MB \n", "fetch_wasabi_file('COSI-SMEX/DC2/Responses/SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5')" ] }, { "cell_type": "code", "execution_count": null, "id": "a9fc7d5f-66a1-4113-b71f-4f34fa295a5d", "metadata": {}, "outputs": [], "source": [ "# point source response:\n", "# wasabi path: COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_511_DC2.h5.gz\n", "# File size: 3.82 GB\n", "fetch_wasabi_file('COSI-SMEX/DC2/Responses/PointSourceReponse/psr_gal_511_DC2.h5.gz')\n", "os.system(\"gzip -d psr_gal_511_DC2.h5.gz\")" ] }, { "cell_type": "code", "execution_count": null, "id": "30addfdb-433f-4360-aff7-9425a3716f0a", "metadata": { "tags": [] }, "outputs": [], "source": [ "# Binned data products:\n", "# Note: This is not needed if you plan to bin the data on your own. \n", "# wasabi path: COSI-SMEX/cosipy_tutorials/extended_source_spectral_fit_galactic_frame \n", "# File sizes: 689.2 MB, 182.0 MB, 739.8 MB, 697.0 MB, respectively. \n", "file_list = ['cosmic_photons_binned_data.hdf5','gal_511_binned_data.hdf5','combined_binned_data.hdf5','combined_binned_data_thin_disk.hdf5']\n", "\n", "for each in file_list:\n", " fetch_wasabi_file('COSI-SMEX/cosipy_tutorials/extended_source_spectral_fit_galactic_frame/%s' %each)" ] }, { "cell_type": "markdown", "id": "0323edb3-d26e-4a13-a2b8-a2637021f80b", "metadata": {}, "source": [ "## Create the combined data\n", "We will combine the 511 source and the cosmic photon background, which will be used as our dataset.
\n", "This only needs to be done once.
\n", "You can skip this cell if you already have the combined data file." ] }, { "cell_type": "code", "execution_count": 10, "id": "902e9af4-316b-4961-bd69-6985e675aff2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "adding cosmic_photons_3months_unbinned_data.fits.gz...\n", "\n", "\n", "adding 511_Testing_3months_unbinned_data.fits.gz...\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING: VerifyWarning: Keyword name 'data file' is greater than 8 characters or contains characters not allowed by the FITS standard; a HIERARCH card will be created. [astropy.io.fits.card]\n" ] } ], "source": [ "# Define instance of binned data class:\n", "instance = BinnedData(\"Gal_511.yaml\")\n", "\n", "# Combine files:\n", "input_files = [\"cosmic_photons_3months_unbinned_data.fits.gz\",\"511_Testing_3months_unbinned_data.fits.gz\"]\n", "instance.combine_unbinned_data(input_files, output_name=\"combined_data\")" ] }, { "cell_type": "markdown", "id": "f1d1c255-bb2d-4362-8bc1-671d95898e1e", "metadata": { "tags": [] }, "source": [ "## Bin the data \n", "You only have to do this once, and after you can start by loading the binned data directly.
\n", "You can skip this cell if you already have the binned data files." ] }, { "cell_type": "code", "execution_count": 11, "id": "0419e986-5b9f-49eb-a325-0256a8ec50b5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "binning data...\n", "Time unit: s\n", "Em unit: keV\n", "Phi unit: deg\n", "PsiChi unit: None\n" ] } ], "source": [ "# Bin 511:\n", "gal_511 = BinnedData(\"Gal_511.yaml\")\n", "gal_511.get_binned_data(unbinned_data=\"511_Testing_3months_unbinned_data.fits.gz\", output_name=\"gal_511_binned_data\")" ] }, { "cell_type": "code", "execution_count": 12, "id": "2bab6997-38ea-405c-aea0-6f39e88198be", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "binning data...\n", "Time unit: s\n", "Em unit: keV\n", "Phi unit: deg\n", "PsiChi unit: None\n" ] } ], "source": [ "# Bin background:\n", "bg_tot = BinnedData(\"Gal_511.yaml\")\n", "bg_tot.get_binned_data(unbinned_data=\"cosmic_photons_3months_unbinned_data.fits.gz\", output_name=\"cosmic_photons_binned_data\")" ] }, { "cell_type": "code", "execution_count": 13, "id": "236ec730-0327-480f-af51-aa8bc066292e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "binning data...\n", "Time unit: s\n", "Em unit: keV\n", "Phi unit: deg\n", "PsiChi unit: None\n" ] } ], "source": [ "# Bin combined data:\n", "data_combined = BinnedData(\"Gal_511.yaml\")\n", "data_combined.get_binned_data(unbinned_data=\"combined_data.fits.gz\", output_name=\"combined_binned_data\")" ] }, { "cell_type": "markdown", "id": "1bf53b28-fa03-4ff3-9025-e15c821cabb1", "metadata": {}, "source": [ "## Read in the binned data\n", "Once you have the binned data files, you can start by loading them directly (instead of binning them each time)." ] }, { "cell_type": "code", "execution_count": null, "id": "7006c9c0-d8ea-49d2-9ab7-66ecbcf3edea", "metadata": {}, "outputs": [], "source": [ "# Load 511:\n", "gal_511 = BinnedData(\"Gal_511.yaml\")\n", "gal_511.load_binned_data_from_hdf5(binned_data=\"gal_511_binned_data.hdf5\")\n", "\n", "# Load background:\n", "bg_tot = BinnedData(\"Gal_511.yaml\")\n", "bg_tot.load_binned_data_from_hdf5(binned_data=\"cosmic_photons_binned_data.hdf5\")\n", "\n", "# Load combined data:\n", "data_combined = BinnedData(\"Gal_511.yaml\")\n", "data_combined.load_binned_data_from_hdf5(binned_data=\"combined_binned_data.hdf5\")" ] }, { "cell_type": "markdown", "id": "5d833e94-1fa4-4c15-9648-9bff16c77ab8", "metadata": { "tags": [] }, "source": [ "## Define source\n", "The injected source has both an extended componenent and a point source component,
\n", "but to start with we will ignore the point source component,
\n", "and see how well we can describe the data with just the extended component.
\n", "Define the extended source:" ] }, { "cell_type": "code", "execution_count": null, "id": "f459d4ec-8949-4e30-98e8-09d68cf3e4b9", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n" ], "text/plain": [ " * gaussian (extended source):\n", " * shape:\n", " * lon0:\n", " * value: 359.75\n", " * desc: Longitude of the center of the source\n", " * min_value: 0.0\n", " * max_value: 360.0\n", " * unit: deg\n", " * is_normalization: false\n", " * lat0:\n", " * value: -1.25\n", " * desc: Latitude of the center of the source\n", " * min_value: -90.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * sigma:\n", " * value: 5.0\n", " * desc: Standard deviation of the Gaussian distribution\n", " * min_value: 0.0\n", " * max_value: 20.0\n", " * unit: deg\n", " * is_normalization: false\n", " * spectrum:\n", " * main:\n", " * Gaussian:\n", " * F:\n", " * value: 0.04\n", " * desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution\n", " * min_value: null\n", " * max_value: null\n", " * unit: s-1 cm-2\n", " * is_normalization: false\n", " * mu:\n", " * value: 511.0\n", " * desc: Central value\n", " * min_value: null\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * sigma:\n", " * value: 0.85\n", " * desc: standard deviation\n", " * min_value: 1.0e-12\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * polarization: {}" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Define spectrum:\n", "# Note that the units of the Gaussian function below are [F/sigma]=[ph/cm2/s/keV]\n", "F = 4e-2 / u.cm / u.cm / u.s \n", "mu = 511*u.keV\n", "sigma = 0.85*u.keV\n", "spectrum = Gaussian()\n", "spectrum.F.value = F.value\n", "spectrum.F.unit = F.unit\n", "spectrum.mu.value = mu.value\n", "spectrum.mu.unit = mu.unit\n", "spectrum.sigma.value = sigma.value\n", "spectrum.sigma.unit = sigma.unit\n", "\n", "# Set spectral parameters for fitting:\n", "spectrum.F.free = True\n", "spectrum.mu.free = False\n", "spectrum.sigma.free = False\n", "\n", "# Define morphology:\n", "morphology = Gaussian_on_sphere(lon0 = 359.75, lat0 = -1.25, sigma = 5)\n", "\n", "# Set morphological parameters for fitting:\n", "morphology.lon0.free = False\n", "morphology.lat0.free = False\n", "morphology.sigma.free = False\n", "\n", "# Define source:\n", "src1 = ExtendedSource('gaussian', spectral_shape=spectrum, spatial_shape=morphology)\n", "\n", "# Print a summary of the source info:\n", "src1.display()\n", "\n", "# We can also print the source info as follows.\n", "# This will show you which parameters are free. \n", "#print(src1.spectrum.main.shape)\n", "#print(src1.spatial_shape)" ] }, { "cell_type": "markdown", "id": "eee646f3-d591-4819-ab7e-d7759e4de4a0", "metadata": {}, "source": [ "Let's make some plots to look at the extended source:" ] }, { "cell_type": "code", "execution_count": 6, "id": "a531d3e2-1101-4c34-8613-3831f8ebbf13", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Energy [keV]')" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot spectrum:\n", "energy = np.linspace(500.,520.,201)*u.keV\n", "dnde = src1.spectrum.main.Gaussian(energy)\n", "plt.plot(energy, dnde)\n", "plt.ylabel(\"dN/dE [$\\mathrm{ph \\ cm^{-2} \\ s^{-1} \\ keV^{-1}}$]\", fontsize=14)\n", "plt.xlabel(\"Energy [keV]\", fontsize=14)" ] }, { "cell_type": "markdown", "id": "a3eab551-1228-456d-b44c-a5f85f885238", "metadata": {}, "source": [ "An extended source in astromodels corresponds to a skymap, which is normalized so that the sum over the entire sky, multiplied by the pixel area, equals 1. The pixel values in the skymap serve as weights, which we can use to scale the input spectrum, in order to get the model counts for any location on the sky. This is all handled internally within cosipy, but for demonstration purposes, let's take a look at the skymap:" ] }, { "cell_type": "code", "execution_count": 7, "id": "b13d7c3b-298c-4e22-88b7-18038d39084d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "summed map: 0.9974653836229359\n" ] } ], "source": [ "# Define healpix map matching the detector response:\n", "skymap = HealpixMap(nside = 16, scheme = \"ring\", dtype = float, coordsys='G')\n", "coords1 = skymap.pix2skycoord(range(skymap.npix))\n", "pix_area = skymap.pixarea().value\n", "\n", "# Fill skymap with values from extended source: \n", "skymap[:] = src1.Gaussian_on_sphere(coords1.l.deg, coords1.b.deg) \n", "\n", "# Check normalization:\n", "print(\"summed map: \" + str(np.sum(skymap)*pix_area))" ] }, { "cell_type": "code", "execution_count": 8, "id": "34046df6-759d-442e-891e-d70fc282ffdf", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot healpix map:\n", "plot, ax = skymap.plot(ax_kw = {'coord':'G'})\n", "ax.grid()\n", "lon = ax.coords['glon']\n", "lat = ax.coords['glat']\n", "lon.set_axislabel('Galactic Longitude',color='white',fontsize=5)\n", "lat.set_axislabel('Galactic Latitude',fontsize=5)\n", "lon.display_minor_ticks(True)\n", "lat.display_minor_ticks(True)\n", "lon.set_ticks_visible(True)\n", "lon.set_ticklabel_visible(True)\n", "lon.set_ticks(color='white',alpha=0.6)\n", "lat.set_ticks(color='white',alpha=0.6)\n", "lon.set_ticklabel(color='white',fontsize=4)\n", "lat.set_ticklabel(fontsize=4)\n", "lat.set_ticks_visible(True)\n", "lat.set_ticklabel_visible(True)" ] }, { "cell_type": "code", "execution_count": 9, "id": "ee9bde37-f954-414d-aa8f-2dc187f8eb19", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1e-50, 1)" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot weights directly\n", "# Note: for extended sources the weights also need to include the pixel area.\n", "plt.semilogy(skymap[:]*pix_area)\n", "plt.ylabel(\"weight\")\n", "plt.xlabel(\"pixel\")\n", "plt.ylim(1e-50,1)" ] }, { "cell_type": "markdown", "id": "d523478a-c6fe-4905-90d4-957554ab619c", "metadata": {}, "source": [ "## Setup the COSI 3ML plugin and perform the likelihood fit\n", "Load the detector response, ori file, and precomputed point source response in Galactic coordinates:" ] }, { "cell_type": "code", "execution_count": null, "id": "5a3508cb-12a5-4174-8171-422960718cde", "metadata": {}, "outputs": [], "source": [ "response_file = \"SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\"\n", "response = FullDetectorResponse.open(response_file)\n", "ori = SpacecraftFile.parse_from_file(\"20280301_3_month_with_orbital_info.ori\")\n", "psr_file = \"psr_gal_511_DC2.h5\"" ] }, { "cell_type": "markdown", "id": "8bc970eb-4482-4196-9340-1a113a962a39", "metadata": {}, "source": [ "Setup the COSI 3ML plugin:" ] }, { "cell_type": "code", "execution_count": null, "id": "1b2ac4e3-fe0f-4ca0-b65a-1cfcf9a143e0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "... loading the pre-computed image response ...\n", "--> done\n", "CPU times: user 1min 55s, sys: 37.4 s, total: 2min 32s\n", "Wall time: 2min 49s\n" ] } ], "source": [ "%%time\n", "\n", "# Set background parameter, which is used to fit the amplitude of the background:\n", "bkg_par = Parameter(\"background_cosi\", # background parameter\n", " 1, # initial value of parameter\n", " min_value=0, # minimum value of parameter\n", " max_value=5, # maximum value of parameter\n", " delta=0.05, # initial step used by fitting engine\n", " desc=\"Background parameter for cosi\")\n", "\n", "# Instantiate the COSI 3ML plugin\n", "cosi = COSILike(\"cosi\", # COSI 3ML plugin\n", " dr = response_file, # detector response\n", " data = data_combined.binned_data.project('Em', 'Phi', 'PsiChi'), # data (source+background)\n", " bkg = bg_tot.binned_data.project('Em', 'Phi', 'PsiChi'), # background model \n", " sc_orientation = ori, # spacecraft orientation\n", " nuisance_param = bkg_par, # background parameter\n", " precomputed_psr_file = psr_file) # full path to precomputed psr file in galactic coordinates (optional)\n", " \n", "# Add sources to model:\n", "model = Model(src1) # Model with single source. If we had multiple sources, we would do Model(source1, source2, ...)" ] }, { "cell_type": "markdown", "id": "49c2c0fb-6a6f-42b3-b940-8d7a5e75c45a", "metadata": { "jupyter": { "outputs_hidden": true }, "tags": [] }, "source": [ "Perform likelihood fit: " ] }, { "cell_type": "code", "execution_count": 6, "id": "371f159b-dfa8-4475-9aec-679dc6aa91cb", "metadata": { "scrolled": true, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
11:55:08 INFO      set the minimizer to minuit                                             joint_likelihood.py:1042\n",
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11:56:43 WARNING   get_number_of_data_points not implemented, values for statistical        plugin_prototype.py:128\n",
       "                  measurements such as AIC or BIC are unreliable                                                   \n",
       "
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Best fit values:\n",
       "\n",
       "
\n" ], "text/plain": [ "\u001b[1;4;38;5;49mBest fit values:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
resultunit
parameter
gaussian.spectrum.main.Gaussian.F(4.6951 +/- 0.0025) x 10^-21 / (cm2 s)
background_cosi(9.32 +/- 0.05) x 10^-1
\n", "
" ], "text/plain": [ " result unit\n", "parameter \n", "gaussian.spectrum.main.Gaussian.F (4.6951 +/- 0.0025) x 10^-2 1 / (cm2 s)\n", "background_cosi (9.32 +/- 0.05) x 10^-1 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Correlation matrix:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", "
1.00-0.40
-0.401.00
" ], "text/plain": [ " 1.00 -0.40\n", "-0.40 1.00" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of -log(likelihood) at the minimum:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of -\u001b[0m\u001b[1;4;38;5;49mlog\u001b[0m\u001b[1;4;38;5;49m(\u001b[0m\u001b[1;4;38;5;49mlikelihood\u001b[0m\u001b[1;4;38;5;49m)\u001b[0m\u001b[1;4;38;5;49m at the minimum:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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-log(likelihood)
cosi-1.527559e+07
total-1.527559e+07
\n", "
" ], "text/plain": [ " -log(likelihood)\n", "cosi -1.527559e+07\n", "total -1.527559e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of statistical measures:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of statistical measures:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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statistical measures
AIC-3.055119e+07
BIC-3.055119e+07
\n", "
" ], "text/plain": [ " statistical measures\n", "AIC -3.055119e+07\n", "BIC -3.055119e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 6min, sys: 3min 20s, total: 9min 21s\n", "Wall time: 1min 36s\n" ] }, { "data": { "text/plain": [ "( value negative_error positive_error \\\n", " gaussian.spectrum.main.Gaussian.F 0.046951 -0.000025 0.000025 \n", " background_cosi 0.932137 -0.004667 0.004841 \n", " \n", " error unit \n", " gaussian.spectrum.main.Gaussian.F 0.000025 1 / (cm2 s) \n", " background_cosi 0.004754 ,\n", " -log(likelihood)\n", " cosi -1.527559e+07\n", " total -1.527559e+07)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time \n", "\n", "plugins = DataList(cosi) # If we had multiple instruments, we would do e.g. DataList(cosi, lat, hawc, ...)\n", "\n", "like = JointLikelihood(model, plugins, verbose = False)\n", "\n", "like.fit()" ] }, { "cell_type": "markdown", "id": "d7ec9390-e6b4-47ec-be71-c143bc76d7c8", "metadata": { "jupyter": { "outputs_hidden": true }, "tags": [] }, "source": [ "## Results\n", "First, let's just print the results.
" ] }, { "cell_type": "code", "execution_count": 7, "id": "4d1df8b6-a464-41b2-a1cb-2b7d770a7313", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
Best fit values:\n",
       "\n",
       "
\n" ], "text/plain": [ "\u001b[1;4;38;5;49mBest fit values:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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resultunit
parameter
gaussian.spectrum.main.Gaussian.F(4.6951 +/- 0.0025) x 10^-21 / (cm2 s)
background_cosi(9.32 +/- 0.05) x 10^-1
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" ], "text/plain": [ " result unit\n", "parameter \n", "gaussian.spectrum.main.Gaussian.F (4.6951 +/- 0.0025) x 10^-2 1 / (cm2 s)\n", "background_cosi (9.32 +/- 0.05) x 10^-1 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Correlation matrix:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", "
1.00-0.40
-0.401.00
" ], "text/plain": [ " 1.00 -0.40\n", "-0.40 1.00" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of -log(likelihood) at the minimum:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of -\u001b[0m\u001b[1;4;38;5;49mlog\u001b[0m\u001b[1;4;38;5;49m(\u001b[0m\u001b[1;4;38;5;49mlikelihood\u001b[0m\u001b[1;4;38;5;49m)\u001b[0m\u001b[1;4;38;5;49m at the minimum:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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-log(likelihood)
cosi-1.527559e+07
total-1.527559e+07
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" ], "text/plain": [ " -log(likelihood)\n", "cosi -1.527559e+07\n", "total -1.527559e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of statistical measures:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of statistical measures:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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statistical measures
AIC-3.055119e+07
BIC-3.055119e+07
\n", "
" ], "text/plain": [ " statistical measures\n", "AIC -3.055119e+07\n", "BIC -3.055119e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " * gaussian (extended source):\n", " * shape:\n", " * lon0:\n", " * value: 359.75\n", " * desc: Longitude of the center of the source\n", " * min_value: 0.0\n", " * max_value: 360.0\n", " * unit: deg\n", " * is_normalization: false\n", " * lat0:\n", " * value: -1.25\n", " * desc: Latitude of the center of the source\n", " * min_value: -90.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * sigma:\n", " * value: 5.0\n", " * desc: Standard deviation of the Gaussian distribution\n", " * min_value: 0.0\n", " * max_value: 20.0\n", " * unit: deg\n", " * is_normalization: false\n", " * spectrum:\n", " * main:\n", " * Gaussian:\n", " * F:\n", " * value: 0.046951164320587706\n", " * desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution\n", " * min_value: null\n", " * max_value: null\n", " * unit: s-1 cm-2\n", " * is_normalization: false\n", " * mu:\n", " * value: 511.0\n", " * desc: Central value\n", " * min_value: null\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * sigma:\n", " * value: 0.85\n", " * desc: standard deviation\n", " * min_value: 1.0e-12\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * polarization: {}\n", "\n" ] } ], "source": [ "results = like.results\n", "results.display()\n", "\n", "# Print a summary of the optimized model:\n", "print(results.optimized_model[\"gaussian\"])" ] }, { "cell_type": "markdown", "id": "2990c92c-d12d-40a5-ab93-6402345444b3", "metadata": {}, "source": [ "Now let's make some plots.
\n", "Let's first look at the best-fit spectrum:" ] }, { "cell_type": "code", "execution_count": 8, "id": "cf7f47cf-6696-4dfa-949a-307160ccd990", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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+sxda9W4mSRuJyD4etcaLiKgxKLEa8WrgVKPF9ZYjaUTkGnZNNd76BqA95s6dK741SEREN5kX1gNAUET1LczqI9Di+hIGXkQuZ1fgdfHiRWg0GoSEhNhVaVZWFgoLC+26lojI21mPeDUw8LK43jKgIyLXsHtx/YsvvoiEhAS7rpXLOcNJRFSTkhsBko9aCVVAw96BCmjiC5lcBsEkcMSLyA0wAiIiciMmkyAGXkER6gZtkwYAcoUcAWFVbzaWcMSLyOXs+qfU2bNn0aRJE7srbej1RETeqqxAD9ONHF6BDVzfZRYUoUZJThnKSypRoauEyp8pJYhcxa7Aq127dg2qtKHXExF5q2IJ13fZuk9Jrh5NYhh4EbkKpxqJiNyI1RuNDgi8inO4dRCRKzHwIiJyI5brsKScarx5f70k9yQi+0gaeBUUFGD9+vVS3pKIqFGxfPOwoTm8zKxyeXGBPZFLSRp4ZWVlYdq0aVLekoioUXHEGq8gTjUSuY16La7Pysqq9bx5c2kiIrKPecTLx08B30BpFsEHNPGDTAYIArPXE7lavQKv1q1b15pTRhCEBuecISJqrASTgJK8qsAoUIIcXmZyZVUur5JcPacaiVysXoFXaGgoli9fjiFDhtg8f+rUKUyYMEGKdhERNTo6bTlMhhs5vCSaZjQLDFejJFcPfXElKvUG+Pg1LCM+EdmnXk9e7969kZOTg44dO9o8r9frIQiCJA0jImpspNyj8VZV9yuoqie3DKEtgyS9PxHVTb0Cr6effhqlpaU1no+JiUFqamqDG0VE1BjpCm6megi8sc2PVAKa3LxfaUE5Ay8iF6lX4PXQQw/Vej40NBRPPPFEgxpERNRYlebfDLz8m0gceFkEcro85vIichUmUCUichOl+eXi5wCpAy/LEa98Bl5ErtLgwEuhUNw2zQQREd1eqcVIFAMvIu/U4MCLi+mJiKRhGRAx8CLyTpxqJCJyE+aAyDfQB0qVQtJ7+wWpIFfIrOohIudj4EVE5AYEkyC+1Rgg8RuNACCTy8QF+wy8iFyHgRcRkRsoK66AyVi1dCMgVPrAC7g53VheUglDhdEhdRBR7Rh4ERG5AZ0DF9bbui9HvYhcg4EXEZEbcOTCelv3ZeBF5BoMvIiI3AADL6LGocGB16uvvoqQkBAJmkJE1HhZZa13wOJ6AAho4it+1jHwInIJu7enNxgMUCqVeOONN6RsDxFRo+T0ES9uG0TkEnaPeDVv3hzz58/HqVOnpGwPEVGjxKlGosbB7sBLq9Vi5cqV6NatG+655x6kpKSgpKREyrYRETUa5kDIR62ESm33ZESt1CG+kMms6yMi57I78Lp69SoSExPRvXt3HDhwALNmzUJUVBRmzJiBX375Rco2EhF5NUEQxEDIch2W1OQKOdShVfdn4EXkGnYHXk2aNMELL7yAY8eO4ciRI3j66aehUqmQmpqKwYMHo3PnznjnnXdw7do1KdtLROR1yksrYawwAXDcNKOZ+f5lRRUwGkwOrYuIqpMknUSvXr3wwQcf4OrVq9iwYQOGDx+Os2fP4l//+heio6Px0EMP4bvvvoPJxIeciOhWuvxy8bPDAy9zVnwB0BWU116YiCQnaR4vlUqFf/zjH/j+++9x8eJFLFmyBNHR0di8eTMeeOABREdHS1kdEZFXcMbCelv353QjkfM5LIFqy5Yt8dprr2Hbtm0YMGAABEFAdna2o6ojIvJYLgu88socWhcRVeeQV2dKS0vxv//9D2vXrsW+ffsgCAL8/f3xyCOPOKI6IiKPZpU81UEbZIv3twi8ONVI5HySBl579+7F2rVr8dVXX0Gn00EQBNx1112YMWMGJk2ahKCgICmrIyLyCmWFNwMgfwe+1QgA/iEW2esLGXgROVuDA6/Lly/j448/xrp163D+/HkIgoCwsDDEx8djxowZ6NatmxTtJCLyWqUFFiNeIQ4e8WLgReRSdgde//vf/5Camopdu3bBaDRCLpdj1KhRmD59Oh588EH4+PhI2U4iIq9lnvKTyWXwC1Y5tC7/0JuBVxkDLyKnszvw+sc//gEAaN26NaZNm4Zp06ahZcuWkjWMiKixMAdAao0KcrnMoXX5qJVQqOQwVpigK+RbjUTO1qDAa8aMGRg+fLiU7SEialRMRhPKtFWBl6MX1gOATCaDf4gviq+XcXE9kQvYHXht2LBBynYQETVKZUUVEISqz5bTgI7kH+KH4utlqNAZYKgwQqlSOKVeIpIwj5fBYEBiYiLuvvtuBAcHQ6m8GdMdO3YMzzzzDM6cOSNVdUREXqHMYtTJcuG7I1nWw3VeRM4lSeBVVlaGoUOHYv78+cjMzERwcDAE8z/hALRp0wapqalYv369FNUREXkNqzcanTTipQ7lm41EriJJ4LV8+XL8+uuvePPNN5GdnY34+Hir8xqNBoMHD8bOnTulqI6IyGtY5fBycCqJm/Uw8CJyFUkCry+++AJDhgzBwoULIZPJIJNVfyunbdu2yMrKkqI6IiKvUWo51ei0NV4WgRcX2BM5lSSBV1ZWFu66665aywQHB0Or1UpRHRGR19C5OvDiiBeRU0kSeAUFBSEnJ6fWMufPn0dERIQU1REReQ3LXFrOmmpUWyVRZS4vImeSJPDq168fvv322xpHtC5duoRt27Zh0KBBUlRHROQ1nJm13owjXkSuI0ngtWDBAuTn52PEiBHYt28fDAYDAECn0+HHH3/EqFGjUFlZiXnz5klRHRGR1zAHPuoQx2etN/MLVEGmkFnVT0TO0eBNsgFg0KBB+PDDDzFnzhzExcWJx4OCggAACoUCq1atQu/evaWojojIK5iMJujNWeudNM0IVI2u+Wt8UZqv5+J6IieTJPACgKeeegqDBw/GRx99hIMHDyI/Px/BwcHo27cvnnnmGXTt2lWqqoiIvIIrstab+YdUBV764gqYjCbIFZLl0yaiWkgWeAFA586d8d5770l5SyIir6VzQdZ6M3GBvQCUaSsQ0MR5I25EjZlT/4ljMpmcWR0RkVvTuSBrvVgfF9gTuYQkgdeaNWtuW8ZoNOKxxx6TojoiIq9gGfD4hzp3xMk6iSpTShA5iySB19NPP43NmzfXeF4QBEyePBlffvmlFNUREXkFV041cqNsIteQLI/XpEmTsHfv3mrnzEHX//73Pzz11FNSVEdE5BVckbXeTM2pRiKXkCTw+u6779CuXTuMHz8ef/75p3hcEARMmTIFn3/+OWbPno0PP/xQiuqIiLyCK7LWi/VZTG0y8CJyHkkCL41Gg507d0Kj0WD06NG4ePEiBEHA448/jg0bNmDWrFlISkqSoioiIq9hnuKTyeC0rPVmXFxP5BqSvdXYvHlzfP/996ioqMCoUaMwadIkfPbZZ4iPj8dHH30kVTVERF5DdyN5qp/G12lZ683UGhVwo8oyJlElchpJ00nccccd2L59O7Kzs/Hll19ixowZ+O9//ytlFUREXkEwCSjTVgBw/sJ6AJAr5FDfGGXjiBeR89iVQHXp0qW1nr/77rtx7NgxtGjRwqqsTCbDa6+9Zk+VREReRV9SAcFYlbZerXF+4AVUBXxl2grotOUQTAJkTh51I2qM7Aq8lixZUqdytwZoDLyIiKqUFVaIn/1DnLu+y0wd4gdkFkMwCtCXVEAd7JoAkKgxsSvwSktLk7oddabT6bBmzRqkpaWhuLgYMTExmDx5MoYPH37bawsKCpCUlIT9+/dDr9ejffv2iI+Pr7Z59759+5CWloYzZ84gKysLRqMRP//8c7X7Xb16FY8++qjNuhYvXlynNhFR42Re3wW4cMQr1HqBPQMvIsezK/AaPHiw1O2os0WLFiE9PR2zZ89GdHQ0du3ahddffx0mkwkjR46s8bqKigrMnTsXJSUleP755xEaGopNmzZh/vz5SExMRGxsrFj2559/xokTJ9ChQweoVCqcPn261jZNmDABI0aMsDrWsmXLBvWTiLxbmQtzeIn1WiZRLSgHYlzSDKJGRdJNsh1t//79OHLkCBISEsRAp1evXsjOzkZSUhKGDRsGhUJh89qtW7ciIyMDq1atQrdu3QAAPXv2xPTp05GUlITVq1eLZRcuXAi5vOq9g8TExNsGXk2bNkXXrl2l6CIRNRJuMeLFlBJETufUTbIbau/evVCr1RgyZIjV8bFjxyI3NxcnT56s9dqYmBgx6AIApVKJUaNG4dSpU8jJyRGPm4MuIiJHsdymxxVvNQLMXk/kCh414pWRkYFWrVpBqbRudrt27cTz3bt3t3nthQsX0KNHj2rHLa+NiIiwq10bNmxAcnIyFAoF7rjjDkyaNAkDBw6s9Zrc3Fzk5eWJP2dmZtpVNxF5pjLLES8XBV4c8SJyPo8KvLRaLZo3b17teFBQEACgqKioxmuLiorEcvW9tiY+Pj64//770adPH4SFheHatWvYuHEjXnnlFSxcuBDjxo2r8dotW7Zg3bp19a6TiLyDzg1GvCzXljGJKpFzeFTgBVSlpHDEtfbcNzw8HAsWLLA6NnToUMyePRurV6/G6NGjq43OmY0fPx4DBgwQf87MzMSyZcvq3QYi8kzmwEvpq4CPn2v+KrZcW8YRLyLn8KjAS6PRQKvVVjteXFwMAAgODq7x2uDgYJujWuZrbY2G2UOpVGLYsGFYvXo1Ll26hNatW9ssFx4ejvDwcEnqJCLPY17j5arRLgBQqhTwDfBBeWml1YbdROQ4HrWKvG3btsjMzITBYLA6fuHCBQBAmzZtar32/Pnz1Y6bj7Vt21aydgpCVTZqLtInIlsMFUZU6Kr+HnPV+i4zc/26wnLx7y4ichxJI4OCggKsX79eyltaiYuLQ1lZGX766Ser4zt27EB4eDi6dOlS47WDBg1CVlaW1ZuPBoMBP/zwA7p06SLZ6JPBYEBaWho0Gg1atGghyT2JyLtYLqz3d1EqCbH+G4GXscKEyjLDbUoTUUNJOtWYlZWFadOmYerUqVLeVtSvXz/06dMHK1euhE6nQ4sWLfDjjz/i4MGDWLRokZjDa8WKFdi5cyc+++wzREZGAqhKObFp0yYkJCRg9uzZYgLVrKwsJCYmWtWTnZ2N9PR0AMCVK1cAAHv27AEAREZGolOnTgCADz74AAaDAd27d0eTJk1w/fp1fP311zh79ixefvnlGnOKEVHjZplKwtUjXlbZ6wvKofL3cWFriLxfvQKvrKysWs+bgxRHWrZsGZKTk5GSkiJuGXTr9jwmkwlGo9Fq2FylUiExMRFJSUl47733oNfr0aFDB7zzzjtWWesB4OjRo3jzzTetjiUkJAAARo8ejVdeeQVA1dTmli1bsGvXLpSWlsLf3x+dO3fGf/7zH9x9990O+gaIyNPpLPZpVLton8ab9VsvsA9pEejC1hB5P5lQj0l9uVxe69t/giBAJpPBaDRK0rjG5PTp05g5cyaSk5PRsWNHVzeHiBzo1K4s/Lr2BAAgblY3dBwS7bK2/LktAwf/r2qEf8izPdB+QPWUPUQknXqNeIWGhmL58uXVMsebnTp1ChMmTJCiXUREXssqh5ebrPECmFKCyBnqFXj17t0bOTk5NY7I6PV6vhVDRHQb7rrGq4yBF5HD1Svwevrpp1FaWlrj+ZiYGKSmpja4UURE3sxyg2xX5vGqqt9P/KwrYC4vIkerV+D10EMP1Xo+NDQUTzzxRIMaRETk7cTteWSAX7B7La4nIsdihk8iIiczj3j5BakgV7j2r2GVWgmlb1XqGwZeRI7HwIuIyIkEQXCL7YIsmdvBNV5EjtfgwEuhUNw2vxcREVUpL62EyVj1EpLbBF43FthX6AwwVDAdEJEjNTjw4luMRER1505vNJqpLVJaWG5nRETS41QjEZETWa6jUrs4h5eZZQDI6UYix2LgRUTkRJaBjb+Ltwsys06iWlFLSSJqKAZeREROpNNa7tPoV0tJ57HMnq8rZC4vIkdi4EVE5ETuOOJlNdWo5YgXkSMx8CIiciL3XON1MwDkGi8ix2LgRUTkRNYjXu4ReFltG8S3GokcqsGB16uvvoqQkBAJmkJE5P3M6RoUKjl81PXatc1h/IJVkMmqPovbGRGRQzT4qX/jjTekaAcRUaNgnmr01/hCZo52XEwul8EvWIUybQVHvIgczKFTjYIg4OzZs7h06ZIjqyEi8gjGSiPKSyoBuE/yVDO1xbZBTIxN5DiSBF6bN2/G9OnTUVBQIB67ePEiunfvjk6dOqFVq1aYPHkyTCaTFNUREXmksqKbbwy6y/ouM3N7TEZBDA6JSHqSBF4fffQRDh8+jNDQUPHY3LlzcfLkSQwdOhR33nknPv/8c6SmpkpRHRGRR9IVuN92QWbcNojIOSQJvE6cOIG7775b/Fmr1WLbtm149NFHsWvXLhw6dAidO3dGSkqKFNUREXkky4DG301SSZhZZ69n4EXkKJIEXjk5OYiKihJ//uWXX2AwGDBp0iQAgI+PD0aOHIlz585JUR0RkUdyxw2yzaxGvBh4ETmMJIFXcHAw8vLyxJ/37NkDuVyOuLg48ZiPjw9KS0ulqI6IyCNZvjHodmu8QjniReQMkgRenTp1wrfffov8/HxotVp8/vnn6NWrl9War8zMTDRr1kyK6oiIPJLnrPHitkFEjiJJ4DVnzhxcuXIFLVq0QHR0NK5cuYKnnnpKPG80GvHLL7+gR48eUlRHROSRLAMaf4177NNoxjVeRM4hSdrkCRMm4MMPPxQXz0+cOBHTp08Xz//444/Q6XQYPXq0FNUREXkky7VTfm62uF6t4X6NRM4g2X4VTz/9NJ5++mmb50aNGmWV44uIqDEyr/HyC/KBQuleW+X6qJVQ+ipgKDdyxIvIgdzrySci8lKCIIgjSe62vgsAZDKZOOrFPF5EjsPAi4jICSp0Bhgrq3bvULvZNKOZOSAsL6mEsdLo4tYQeScGXkRETmC5bsrdUkmY+fPNRiKHY+BFROQEOjdOnmrGNxuJHI+BFxGRE+g8YMTLMiDkOi8ix2DgRUTkBB4XeHHEi8ghGHgRETmBO+/TaGa5xotTjUSOUe/Ay2Qy4a+//sKVK1eqnausrMTPP/8sScOIiLyJrkAvfnbXES+u8SJyvHoFXpmZmejevTvuvPNOREdHY/z48VabY+fn52Po0KGSN5KIyNN53FQj32okcoh6BV4LFy5Ey5YtkZWVhT/++APl5eUYMGCA1eiXIAiSN5KIyNOZF6srfRXwUUu2aYik1ME3tw3SFeprKUlE9qpX4PXTTz/h7bffRsuWLdGtWzfs2LEDcXFxiIuLQ1ZWFoCq7MdERGRNV1AVePmH+Lrt35NypRx+QT4AgLJCjngROUK9Ai+dTgdf35tD0TKZDMnJyRg1ahQGDRqE8+fPS95AIiJPZ6gwokJnAOC+C+vN1CF+AKpG6DiDQSS9egVeHTt2xJEjR6odT0pKwtixYzFu3DjJGkZE5C08IWu9mX9I1XSjsdIkBotEJJ16BV4PP/wwNmzYYPPcqlWr8Oijj/JfSEREt/CEhfVmaqaUIHKoegVeL7/8MrZt21bj+aSkJJhMpgY3iojIm1gFXqFuHngxiSqRQzGBKhGRg5kX1gPWI0ruyJ/bBhE5FAMvIiIH86SpRiZRJXKsBgdeCoVCTCVBRETVlVnkxFK7+1Qj13gROVSDAy8upiciqp3OIieWu494cY0XkWNxqpGIyMHMI14yhQx+garblHYtrvEiciwGXkREDmaesvPX+EImd8+s9WYqfyUUPlX/aeBUI5H0GHgRETmQyWhCWVHVVKO7TzMCVTuSmNd5caqRSHoMvIiIHKisqAK4sRTW3RfWm6lvZK/XF1fCZGBuRiIpMfAiInKgsgLPSSVh5n9jv0YA4mgdEUmDgRcRkQN5Ug4vM7Xm5gsAXOdFJK0GB16vvvoqQkJCJGgKEZH3sQxc1B4SePkzpQSRwygbeoM33nhDinYQEXmlMk8c8WL2eiKH4VQjEZEDeeJUo/W2QfpaShJRfTV4xMuSyWTCpUuXcPnyZVRWVtosM2jQICmrJCJyax4feBVwxItISpIEXoIgYMWKFUhMTEReXl6tZY1GoxRVEhF5BHHESGa9D6I78w+1eKuRU41EkpIk8Hr55Zfx9ttvo2nTppg2bRqioqKgVEo6mEZE5JHMgYtfkApypWes7lBrVIAMgMARLyKpSRIdrVu3Dh07dsThw4cRGBgoxS2JiDyeIAg3twvykGlGAJAr5FAHq1CmreDieiKJSfLPr5KSEtx3330MuoiILJSXVMJkqEpb70mBF3CzvTptOQST4OLWEHkPSQKv2NhYXLlyRYpbERF5DU/M4WWmvpG9XjAK0Bczez2RVCQJvBYtWoTNmzfj999/l+J2RERewRPfaDTzD2UuLyJHkGSN1+jRo/Hxxx9jzJgxGD9+PHr06IHg4GCbZadOnSpFlUREbq/Mg0e8bk0pEdbKhY0h8iKSBF7l5eXYvHkzcnNzkZKSAgCQyWRWZQRBgEwmY+BFRI2G94x4MYkqkVQkCbzmzZuHTz/9FHfeeSceeeQRh6aT0Ol0WLNmDdLS0lBcXIyYmBhMnjwZw4cPv+21BQUFSEpKwv79+6HX69G+fXvEx8ejd+/eVuX27duHtLQ0nDlzBllZWTAajfj5559t3tNgMOCTTz7B9u3bkZeXh6ioKDz00EOYMGGCJP0lIs/lidsFmfmH3MzlxalGIulIEh19+eWX6N27N/bv3+/w/F2LFi1Ceno6Zs+ejejoaOzatQuvv/46TCYTRo4cWeN1FRUVmDt3LkpKSvD8888jNDQUmzZtwvz585GYmIjY2Fix7M8//4wTJ06gQ4cOUKlUOH36dI33XblyJb7//nvMmDEDnTp1wqFDh/D+++9Dp9NhypQpUnadiDyMZQ4syxEkT2A14sVcXkSSkSRK0uv1GDp0qMODrv379+PIkSNISEjAiBEjAAC9evVCdnY2kpKSMGzYMCgUCpvXbt26FRkZGVi1ahW6desGAOjZsyemT5+OpKQkrF69Wiy7cOFCyOVV7x0kJibWGHhlZGRg69atmDlzJiZNmiTes6ioCOvXr8cDDzxQ41o3IvJ+llN0liNInsCfG2UTOYQkbzX27t0b586dk+JWtdq7dy/UajWGDBlidXzs2LHIzc3FyZMna702JiZGDLoAQKlUYtSoUTh16hRycnLE4+agqy7tEQQBY8aMsTo+ZswYlJeX4+DBg3W6DxF5J3PA4qNWQulr+x+F7sryZYAyjngRSUaSwGv58uXYsWMHvvvuOyluV6OMjAy0atWq2shau3btxPM1uXDhgliuvtfW1p6QkBCEhYXV+565ubk4ffq0+CczM7Pe9ROReyvzwKz1ZgqlHH5BPgC4uJ5ISpLMDf7www8YMmQIHnjgAQwdOhSxsbE2p9hkMhlee+01u+vRarVo3rx5teNBQUEAgKKiohqvLSoqEsvV99ra2mOrn2q1Gj4+PtBqtTVeu2XLFqxbt67edRKRZ6jUG1CpNwLwvPVdZv6hftAXV0JXUC6+mU5EDSNJ4LVkyRLx8+7du7F7926b5RoaeJnv4YhrHfEXSm33HD9+PAYMGCD+nJmZiWXLlkneBiJyDauF9R444gVUtTs/qxgmo4Dy4kr4Batc3SQijydJ4JWWlibFbW5Lo9HYHEUqLi4GgFoXsgcHB9sc1TJfa2s0rC7tsbW2raysDJWVlbW2Jzw8HOHh4fWuk4g8Q5nWInmqxjMDL/UtC+wZeBE1nCSB1+DBg6W4zW21bdsWu3btgsFgsFrndeHCBQBAmzZtar32/Pnz1Y6bj7Vt29au9vz444/Iy8uzWudVl/YQkXfz5OSpZv6hlrm89GgSU/9/oBKRNUkW1ztLXFwcysrK8NNPP1kd37FjB8LDw9GlS5carx00aBCysrKs3nw0GAz44Ycf0KVLF7tGnwYOHAiZTIYdO3ZYHd++fTt8fX3Rt2/fet+TiLyD5VSj2lPXeIUwlxeR1CQZ8fr111/x9ddfY+HChYiMjKx2Pjs7G2+//TYmTpyIfv362V1Pv3790KdPH6xcuRI6nQ4tWrTAjz/+iIMHD2LRokViDq8VK1Zg586d+Oyzz8T2jB07Fps2bUJCQgJmz54tJlDNyspCYmJitfamp6cDAK5cuQIA2LNnDwAgMjISnTp1AlA1onXfffchNTUVcrkcnTt3xuHDh/Htt98iPj6eObyIGjHvGPFiLi8iqUkSeK1cuRLHjx/HypUrbZ6PjIzEd999h8uXL+OLL75oUF3Lli1DcnIyUlJSxC2DFi9ebLVlkMlkgtFohCAI4jGVSoXExEQkJSXhvffeg16vR4cOHfDOO+9YZa0HgKNHj+LNN9+0OpaQkACgakPwV155RTw+b948hIeHY+PGjcjPz0dkZCTmzJnDLYOIGjlP3i7IjElUiaQnEyyjEzvFxMRg+PDhSE1NrbFMfHw8fvjhB+arqsHp06cxc+ZMJCcno2PHjq5uDhE10PY3D+Hyn3kAgCn/HQHfQB8Xt6j+inN0+OKFqqUdre9qhhEv9nJxi4g8nyRrvK5fv44WLVrUWiYyMhLXr1+XojoiIrdXml81QqRQyaEKcOx2ao5itbiea7yIJCFJ4BUSEoKsrKxay2RmZiIwMFCK6oiI3J6uoCrbe0Con8cmHlUo5WIKidICZq8nkoIkgVf//v2xadMm/P333zbPZ2Vl4ZtvvsE999wjRXVERG6tUm9Ahc4AwHOz1psF3Gi/rrAcgqnBK1OIGj1JAq958+ZBp9NhwIABWL9+Pa5evQoAuHr1Kj7++GMMGDAAZWVl+Oc//ylFdUREbs1yWi6giV8tJd2f/432C0YBZUUVLm4NkeeTZOFBXFwc3n//fcydOxfTpk0DULVdjnndvlwux3vvvYdBgwZJUR0RkVsrzb85LWe5TsoTBViu88rXe+wbmkTuQrIVn88++ywGDx6MpKQkHD58GIWFhQgJCcHdd9+Np556Ct26dZOqKiIit2a5HiqgiWcHKv4W7S8t0CMcGhe2hsjzSfqqTbdu3fDhhx9KeUsiIo+j89IRL8uRPCKyj0dtGURE5AlKvXCNF8CUEkRSYOBFRCQxjngRUU0YeBERScxyjZenp5OwXOOlYy4vogZj4EVEJDHdjaz1fsEqKJSe/desb4APFD5VfTBn4yci+3n23whERG7GZBLEDaU9fX0XUJUayNwPjngRNRwDLyIiCem1NzO8e/o0o5m5HxU6Ayr1Bhe3hsizMfAiIpKQN73RaBbANxuJJCNZHq+Kigp88803YvJUo9FYrYxMJkNKSopUVRIRuR3LNxoDPPyNRjP/W95s1EQFuLA1RJ5NksArMzMTI0eOxPnz58Vtgmxh4EVE3s7qjUYPz1pvZjllWsp1XkQNIkng9eKLL+LcuXOYMmUKpk+fjpYtW0KplDQpPhGRR7B8889bRrysphqZy4uoQSSJjnbv3o3hw4fj448/luJ2REQeS2c14uUdgZfVVCPXeBE1iCSL600mE3r27CnFrYiIPFqpF67xstzomyNeRA0jSeDVv39/nDp1SopbERF5NPOIl0IlhyrAO5ZcWI94MfAiaghJAq8VK1YgLS0NX331lRS3IyLyWOY1XgGhfpDJZC5ujTQUSjn8glUAbmblJyL72PXPsaVLl1Y7NnToUDz66KMYPHgwevbsCY1GU62MTCbDa6+9Zk+VRERur0JXicqyqgSj3rK+yyygiR/0RRXQFZbDZDRBrmAaSCJ72BV4LVmypMZze/bswZ49e2yeY+BFRN7Mcn1XYJh3BV6BYX7Iu1gE4caWSIFhalc3icgj2RV4paWlSd0OIiKPV5JnsbDeywITy/6U5ukZeBHZya7Aa/DgwVK3g4jI45VaBF6B4d414hVgMYJXkqdHMxe2hciTcZKeiEgipXll4udAL1vjZTl1atlPIqofyd91NhgMOHPmDLRaLTQaDe644w5msSeiRqGxTDVa9pOI6keyEa+cnBzMnDkTISEh6N69OwYOHIju3bsjJCQEs2bNQk5OjlRVERG5JW+earQe8WLgRWQvSYaiLl++jAEDBiArKwsREREYNGgQmjVrhmvXruG3337DmjVr8MMPP+CXX35BixYtpKiSiMjtlNyYgvNRK6Dy93Fxa6TlH+oLmQwQBE41EjWEJCNeCxcuRFZWFl5//XVkZmZi27ZtSE1NxbZt25CZmYklS5YgMzMTL730khTVERG5HUEQxJGggCbeNc0IAHKFXMxgz6lGIvtJMuK1Y8cOjB492maOLj8/PyQkJGDfvn3Yvn27FNUREbkdfXEFjJUmAN6Xw8ssIMwPpfl66IsqYKgwQqlSuLpJRB5HkhGviooK9OrVq9YyvXv3RkVFhRTVERG5nVIvXlhvZplSopSbZRPZRZLAq3fv3khPT6+1THp6Onr37i1FdUREbqck13uz1psF3pJElYjqT5LA64033sB3332HdevW2Ty/du1abNu2DcuWLZOiOiIit1Oaf3PBeYCXBl4BfLORqMEkWeOVlpaGoUOHYsaMGXj77bcxYMAANG3aFNevX8evv/6K06dPY9SoUdi9ezd2794tXse9G4nIW5RYpZLwzqnGQKvs9XyzkcgekgRelptmp6en25x23LlzJ3bu3Gl1jIEXEXmLUoupxgAvy1pvdut+jURUf5KNeBERNWYljWCqMfCW/RqJqP4kCby4aTYRNXbmESC/YJXXplnwC1ZB4SOHsdJktaaNiOqOm2QTETWQyWiCrqAcgPdOMwJVy0PM/bN8i5OI6s6uwOuxxx7Dxo0b7a60odcTEbkTXWE5BJMAwHtTSZiZp1Erywyo0FW6uDVEnseuwOvzzz/HX3/9ZXelDb2eiMidNIbkqWaWuby4zouo/uxe43Xs2DGsX79eyrYQEXmk4us68XNghJcHXuEWC+xzytAkOsiFrSHyPHYHXt988w02b95c7+sEQbC3SiIit1Sce3OheZCXB15BEf7i5+IcLrAnqi+7Aq/U1NQGVxwbG9vgexARuYPi640n8LIc0SvO0dVSkohssSvweuKJJ6RuBxGRxyrJsQy8/Gsp6fmCmlqs8eKIF1G9MZ0EEVEDmUd+fNRKqAIkSY/otgKa+EEmlwHgVCORPRh4ERE1gMkkiG/3BTVVQyaTubhFjiVXyMWUEhzxIqo/Bl5ERA2gy9dDMFa9NBTkpZtj38q8jq28tJK5vIjqiYEXEVEDWE63BTX17vVdZkFWC+w56kVUHwy8iIgawPLNvsBGMuJl9WbjdQZeRPXBwIuIqAGs3mhs2jgCL8s3N0tymVKCqD4YeBERNYDlVJu3Z60341Qjkf0YeBERNYDVGq9GMtXIwIvIfnYHXr169cJ///tfq2M7d+7EvHnzbJZ//fXXoVR6d34bImp8zFONvoE+UPn7uLg1zqEO9YNcUZU2gykliOrH7sDr2LFjyM7Otjp24MABvPfeezVew30aicibmAwmlOZVBR6NZWE9AMjlMrG/xTk6/t1OVA+caiQislNpvh7mmKOxLKw3M69nqywzoryUubyI6oqBFxGRnYob0R6Nt7Jc51XClBJEdcbAi4jITpY5vIIayRuNZpaBZnEuAy+iumLgRURkJ8vkoY0llYSZ5dRq0TXm8iKqKwZeRER20maXip81kQEubInzBTe7OeJVlM3Ai6iuGpTf4f/+7/9w4MAB8edz584BAMaOHVutrPkcEZG3MAccMlnjG/EKbnYz0Cy6VlpLSSKy1KDA69y5czYDqh07dtgsL5PJGlIdEZHbEARBDDgCI9RQKBvXBIJvoA98A31QXlLJES+ierA78MrIyJCyHUREHqWsqAKVZUYAjW+a0UwTGYDr5wpRmq+HodwIpa/C1U0icnt2B16tWrWSsh1ERB6l6OrN6TXL9U6NSXCkP66fKwRQtcC+SUyQaxtE5AE8bg8fnU6HNWvWIC0tDcXFxYiJicHkyZMxfPjw215bUFCApKQk7N+/H3q9Hu3bt0d8fDx69+5dreyRI0eQkpKCc+fOwc/PD/3798fTTz+N0NBQsczVq1fx6KOP2qxr8eLFdWoTEXkmyzf5ghvpiFdwpMUC+2ulDLyI6sCuwGv69Ol2VSaTyZCSkmLXtWaLFi1Ceno6Zs+ejejoaOzatQuvv/46TCYTRo4cWeN1FRUVmDt3LkpKSvD8888jNDQUmzZtwvz585GYmIjY2Fix7LFjx7BgwQL0798fy5cvR0FBAVavXo25c+ciOTkZKpXK6t4TJkzAiBEjrI61bNmyQf0kIvemtVjXpIlsnCNellOsWq7zIqoTuwKvdevW2Twuk8ls7tllPt7QwGv//v04cuQIEhISxECnV69eyM7ORlJSEoYNGwaFwvYag61btyIjIwOrVq1Ct27dAAA9e/bE9OnTkZSUhNWrV4tlV61ahejoaCxdulTc2DsqKgrPPvsstm3bhgcffNDq3k2bNkXXrl3t7hcReZ4ii1QSjXbEyyqlBN9sJKoLu17DycjIsPpz/vx5jBs3DmFhYXjjjTewZ88enDp1Cnv27MHSpUsRFhaG+++/H2fPnm1QY/fu3Qu1Wo0hQ4ZYHR87dixyc3Nx8uTJWq+NiYkRgy4AUCqVGDVqFE6dOoWcnBwAQE5ODtLT0zFq1Cgx6AKA7t27Izo6Gj///HOD+kBE3sE81SiTyxpd1nozy4CTSVSJ6sauEa9bF9avWLECBw8exB9//IGoqCjxeMeOHTFo0CBMmzYNPXv2xFdffYWFCxfa3diMjAy0atXKKiACgHbt2onnu3fvbvPaCxcuoEePHtWOW14bEREhvq1pPn5r2T///LPa8Q0bNiA5ORkKhQJ33HEHJk2ahIEDB9bal9zcXOTl5Yk/Z2Zm1lqeiNyHIAjiCE9QhBryRpZKwsw3wAd+QT7QF1daJZMloppJsrg+JSUFEydOtAq6LLVo0QITJ05EcnJygwIvrVaL5s2bVzseFFS1oLOoqKjGa4uKisRytV2r1WoBAMHBwTbLWtbh4+OD+++/H3369EFYWBiuXbuGjRs34pVXXsHChQsxbty4GtuzZcuWGqdsici9lWkrUKmvSiXRWN9oNAtuFgB9cSF0+eVMKUFUB5IEXpcuXYKfn1+tZfz8/HDp0qUG19WQJKy1XXvruZrKWh4PDw/HggULrM4PHToUs2fPxurVqzF69Ohqo3Nm48ePx4ABA8SfMzMzsWzZstv2gYhcj+u7bmJKCaL6kWR8vGXLlti0aRP0er3N8zqdDps2bWrwm34ajUYckbJUXFwMwPYolVlwcLDNETHzteaRL41GAwA11mNr1MySUqnEsGHDoNVqaw00w8PD0bFjR/EP86IReQ7LTO3BjfSNRjPrNxs53Uh0O5IEXvHx8bhw4QIGDBiAzZs3i2uX8vLy8M0332DgwIG4ePEiZs6c2aB62rZti8zMTBgMBqvjFy5cAAC0adOm1mvPnz9f7bj5WNu2ba3uYb7nrfXUVoeZ+c1Oubxxrvsg8nZWm2M39qnGSL7ZSFQfkkQGCxYswLRp03D06FE8/PDDaNq0KXx8fNC0aVNMmDABx44dw5NPPlltWq6+4uLiUFZWhp9++snq+I4dOxAeHo4uXbrUeO2gQYOQlZVl9eajwWDADz/8gC5duiA8PBwAEBERgc6dO+P777+H0WgUy544cQJZWVkYPHhwrW00GAxIS0uDRqNBixYt7OkmEbk5Jk+9KZi5vIjqRZI1XnK5HCkpKZg6dSo+/vhjHD9+HFqtFhqNBj169MDUqVNvG7DURb9+/dCnTx+sXLkSOp0OLVq0wI8//oiDBw9i0aJFYg6vFStWYOfOnfjss88QGRkJoCrlxKZNm5CQkIDZs2eLCVSzsrKQmJhoVc9TTz2FefPmISEhAQ899JCYQLVNmzYYM2aMWO6DDz6AwWBA9+7d0aRJE1y/fh1ff/01zp49i5dffrnGnGJE5NkKr1SN7MgUjTeVhJll8ljtVY54Ed2OpFsGDR48WJIAqzbLli1DcnIyUlJSxC2Dbt2ex2QywWg0WiVzValUSExMRFJSEt577z3o9Xp06NAB77zzjlXWeqAqserbb7+NtWvX4l//+pe4ZdAzzzxjlbW+TZs22LJlC3bt2oXS0lL4+/ujc+fO+M9//oO7777bod8DEbmGyWiC9moJgKr1TY01lYSZyt8H/k18ocsvR+GlEjFZNhHZJhNspZqvg9TUVIwbNw4RERFSt6lROn36NGbOnInk5GR07NjR1c0hohpor5biy39WJVJuc3ckhs/t6eIWud72Nw/h8p9Va3sfSxoGf42vi1tE5L7s/qfajBkz0Lx5c8TFxeHdd99tcFZ6IiJPUHCpRPwc0jLQhS1xH6Etb77tXWjx/RBRdXYHXvv27cP8+fORn5+PBQsWoFOnTujcuTNeeeUVHDhwQMo2EhG5jYLLxeLnUAZeAICQFje/hwIGXkS1sjvw6tevH958802cOHECZ8+exVtvvYWIiAi8/fbbGDBgAKKiojB79mxs27YN5eXlUraZiMhlLEd0LAOOxszyeyi8zMCLqDaSrApt164d5s+fj59//hnXrl3DmjVr0LdvX3z66ae4//77ER4ejgkTJuCTTz5Bfn6+FFUSEbmEObCQyWVWb/Q1ZqGWI14MvIhqJfnrOGFhYZg2bRq++eYb5ObmYtOmTZg4cSJ+/fVXPPHEE2jWrBmGDBkidbVERA5nMgliKongZv5Q+DBlDAD4BvrAP6RqQX3hpeLblCZq3CRNJ3ErPz8/jB8/HuPHj4cgCNi3bx82b96MLVu2OLJaIiKHKMnRwVhpAsCF9bcKaREIXWE59MWVKCsqhzqYbzYS2eK0BDQymQwDBgzA22+/jfT0dGdVS0QkGcuF46Fc32XFMhDlOi+imtk94vXMM8/U+xqZTIYPP/zQ3iqJiFzKMqDgG43WQm95szGqc5gLW0PkvuwOvD766KM6l7XMYszAi4g8VQHfaKyRZSDKXF5ENbM78EpLS6tTuaysLCxduhTnz5/nNhJE5NHENxplgCaqcW+OfasQvtlIVCd2B16325OxoKAAy5cvx4cffgi9Xo/+/fvjrbfesrc6IiKXEizeaAxq6g+lim80WvILUsEvWAV9UQWTqBLVQvLF9Xq9HitWrEC7du3w7rvvonXr1ti4cSN+/fVXDBw4UOrqiIicQptdCkO5EQAQGhN0m9KNU5Mb34u+qAK6Ar2LW0PkniQLvARBwJo1a9ChQwe88sor8Pf3x3//+1/89ddfePDBB6WqhojIJfIuFomfw1sHu7Al7ivM4nvJtfi+iOgmSQKvb775Bl27dsXs2bNRUlKC5cuX49y5c4iPj4dc7rSMFUREDpPLwOu2LL+XPAZeRDY1KIHqL7/8gpdeegkHDhyASqXCiy++iFdffRWhoaFStY+IyC3kZdwMJMIYeNnEES+i27M78Bo/fjy2bt0KuVyOJ554AkuXLkXLli2lbBsRkVsQBEEcwVGH+MI/1M/FLXJPmsgAKH0VMJQbOeJFVAO7A6/vvvsOMpkMMTExyM7OxqxZs257jUwmw9atW+2tkojIJUpy9SgvrQQAhLXiaFdNZHIZwloF49qZApTklEFfUgG/QJWrm0XkVho01SgIAjIyMpCRkVGn8szjRUSeKO+iVvwc3oaBV23CWlcFXgCQn1mM5l2ZwZ7Ikt2BV12DLSIiT2c5bcb1XbWzXGCfm6Fl4EV0C7sDr1atWknZDiIit8U3GusujG82EtWKuR6IiG7DHECo/JUIjFC7uDXuLaRlIOTKqmUlfLORqDq7RrymT59uV2UymQwpKSl2XUtE5Aq6wnLoCsoBVI3mcK1q7RRKOUJbBiHvYhG0V0tRqTfAx69By4mJvIpdT8O6detsHpfJZBAEocbjDLyIyNPkXri5sJ7ru+omvE1w1SihUDVaGNmpiaubROQ27JpqNL/JaP5z/vx5jBs3DmFhYXjjjTewZ88enDp1Cnv27MHSpUsRFhaG+++/H2fPnpW6/UREDmV+Qw8AmnUIcV1DPEjT9iHiZ8vvj4jsHPG6dWH9ihUrcPDgQfzxxx+IiooSj3fs2BGDBg3CtGnT0LNnT3z11VdYuHBhw1pMROREVoHXHdyVoy4sv6fs0wXo4cK2ELkbSRbXp6SkYOLEiVZBl6UWLVpg4sSJSE5OlqI6IiKnMBpMyDlfNdUYFKFmxvo60jQPgG+gDwDg+tlCCKbqS1CIGitJAq9Lly7Bz6/2v5D8/Pxw6dIlKaojInKKvAwtjJUmAECzjhztqiuZTCaOepWXVKLwaqmLW0TkPiQJvFq2bIlNmzZBr9fbPK/T6bBp0ybu5UhEHiX7TKH4mdOM9dPsjhDxM9d5Ed0kSeAVHx+PCxcuYMCAAdi8eTPy8vIAAHl5efjmm28wcOBAXLx4ETNnzpSiOiIip7jO9V12s/y+rp1m4EVkJklylQULFuDMmTNITU3Fww8/DACQy+UwmaqG6AVBwLRp07BgwQIpqiMicjhBEMSRGpW/EqEtA13cIs8S3lYDuVIGk0HgiBeRBUkCL7lcjpSUFEydOhUff/wxjh8/Dq1WC41Ggx49emDq1KkYPHiwFFURETlF8XUdyrQVAICmHUIgkzNxan0oVQqEt9Hg+tlCFGXrUKYth1rj6+pmEbmcpOmEBw8ezACLiLzCtdOF4mdOM9qn2R2huH62EABw7UwhWt/VzLUNInID3KuRiMiGKyfyxM98o9E+kRbfm+X3SdSYMfAiIrqFYBJw6XgOAEDpq2DGejtFdWkCmaJqitb8fRI1dgy8iIhukZ9VLK7viurSBAofhYtb5JlU/j5i0FqUrUPRNZ1rG0TkBhh4ERHdwnJ0JrpHhAtb4vla3nnz++OoFxEDLyKiai4dzxU/t7gz3IUt8Xwte9z8/iy/V6LGioEXEZGFijIDsm8k/Axu5g9NZICLW+TZwloFwy9YBQC4eiIPRoPJxS0ici0GXkREFq6eyINgrNrUmaNdDSeTy9DyxvdYqTcymSo1egy8iIgsWE6HtWTgJQnL7/HSH5xupMaNgRcR0Q0mk4DMI9cAAHKlDM27hrm4Rd6hxZ3hwI3E/5lHrkEQBNc2iMiFGHgREd2QfSofusJyAEDLHhHw8ZN0c49GSx3si6jOTQAA2qulyLtY5OIWEbkOAy8iohsu7L8qfm7XP8qFLfE+lt/neYvvmaixYeBFRATAZDAh41A2gKps9TG9mrq4Rd6l9V2RYhb7jANXIZg43UiNEwMvIiIAl//KQ3lJJQAgpmdTTjNKzC9YhRbdqhbZl+Tqcf1coWsbROQiDLyIiACc33dF/NzuHk4zOoLl93p+H6cbqXFi4EVEjV5FmUF8m1Hlr7TKtk7SadW7KRQ+Vf/ZuXDgKoyVRhe3iMj5GHgRUaN39udLqNRXBQFt+kZxU2wHUfn7oFXvZgAAfVEFLuzPdnGLiJyPgRcRNWqCScCJnZniz13vbeXC1ni/Lhbf7187LjKnFzU6DLyIqFG79EcOirJ1AICoLk3QJCbIxS3ybs3uCEF4m2AAQN7FIlw7U+jaBhE5GQMvImrU/tpxc7Sr2+jWrmtIIyGTydDV4ns+seOiy9pC5AoMvIio0crLKsLlP6v2DgyKUCOaubucom2/SKg1KgDAxcPXUHSt1MUtInIeBl5E1Ggd3nBa/Nx1dGvI5TIXtqbxUPgo0HlkDICqNXaHvzjj4hYROQ8DLyJqlC79mYtLx6tGuwLD/dBpeLSLW9S4dBvdGn7BVaNeGQeymVCVGg0GXkTU6JhMAg5tSBd/7jPxDihVTCHhTCp/H/Sa0F78+eCn6XzDkRoFBl5E1OicTvsb+ZnFAICw1sFod09zF7eoceo0NBqaqAAAwLXTBVablBN5KwZeRNSoaK+W4uD/3Rzt6ju5E2Rc2+UScqUcd0/qKP7869oTKMkrc2GLiByPgRcRNRpGgwlpHxyDobwqS32nYdFo3jXMxa1q3GJ6N0XbflV7OFboDNiz6jhMJk45kvdi4EVEjYIgCDj4aTpyM4oAAJqoAPR9vJOLW0UymQwDZnRFYLgfACD7VD5+/+qsi1tF5DgMvIioUTi66RxO3tgaSK6QYehzPeDjp3RxqwgAfAN8MOSZHpDdmPE99s15/LU9w7WNInIQBl5E5NUEQcDx7y7g96/OiccGzuiG8DYaF7aKbhXZqQn6Pt5Z/PnAJ+k4tSvLhS0icgwGXkTktQwVRuxN/guHLBKl9pvSCXcMaenCVlFNuo1pbZVi4te1J7Dv45MwGUwubBWRtDjOTkReKeeCFr+s+Qt5F4vEY70f6YBuY9q4sFV0Oz0fbo9KvRF/bq2aajy5MxO5GVoMnN6NG5iTV/C4wEun02HNmjVIS0tDcXExYmJiMHnyZAwfPvy21xYUFCApKQn79++HXq9H+/btER8fj969e1cre+TIEaSkpODcuXPw8/ND//798fTTTyM0NNSqnMFgwCeffILt27cjLy8PUVFReOihhzBhwgTJ+kxEdae9Woo/vr2AMz9dAm68HKdQyRE3szvaD2C+Lncnk8nQd3InaKICsG/dCZgMAq6fKcSml39BpxExuHNcGwRF+Lu6mUR287jAa9GiRUhPT8fs2bMRHR2NXbt24fXXX4fJZMLIkSNrvK6iogJz585FSUkJnn/+eYSGhmLTpk2YP38+EhMTERsbK5Y9duwYFixYgP79+2P58uUoKCjA6tWrMXfuXCQnJ0OlUollV65cie+//x4zZsxAp06dcOjQIbz//vvQ6XSYMmWKI78KIrpBX1yBv4/l4Py+K7j0R67VOU3zAAx7PhZhrYJd1DqyR6dh0WgSHYi0D/9A8fUyCAJw6ocsnNqVhZheTdGufxRa9oiAb4CPq5tKVC8eFXjt378fR44cQUJCAkaMGAEA6NWrF7Kzs5GUlIRhw4ZBobC97cfWrVuRkZGBVatWoVu3bgCAnj17Yvr06UhKSsLq1avFsqtWrUJ0dDSWLl0KpbLqK4qKisKzzz6Lbdu24cEHHwQAZGRkYOvWrZg5cyYmTZok3rOoqAjr16/HAw88gOBg/mVPJBVjpRFlRRUovq6D9qoOeReLkHO+EHkXi3DrbjM+aiV6TWiPrqNaQa7kclZP1LRDKCa8HYe/tl3Esc3nq/KvCUDWb9eR9dt1yBQyhLcKRkT7EDSJCUJghBpB4WoEhvtB4cMtoMg9eVTgtXfvXqjVagwZMsTq+NixY7F06VKcPHkS3bt3r/HamJgYMegCAKVSiVGjRuG///0vcnJyEBERgZycHKSnp2PWrFli0AUA3bt3R3R0NH7++Wcx8Nq7dy8EQcCYMWOs6hozZgy+/fZbHDx4sNZROGf4a8dFGCuMtZap8/ZodSgn1K2Qc+ur672kzNlYx5tJWWed7iVhhXW/1e0LCgJgqjTBeOOPodJY9bnCiEq9EfqiCpQVVaCyzHDbewWGq9FlZAzuGNISfkGq25Yn96ZUKRD7YDt0HNoS6bv/xqldWdAVlAMABKOAnAta5FzQVrtOrVFBFeADlVoJlb8SPmollCoF5AoZ5Ao55Ep51Wdl1c/mVBY3P9zyo8z8PzKrn2s6LuNmCG7Jv4kfOgxs4dI2eFTglZGRgVatWlkFRADQrl078XxNgdeFCxfQo0ePasctr42IiEBGRobV8VvL/vnnn1btCQkJQVhYWLVy5vM1yc3NRV5envhzZmZmjWUb4timc9AXVzrk3kRuQQaEtghEyx4RaNW7KZreEQo5twDyOmqNL3o+1B49xrdFdnoBsn6/jr//yIH2SqnN8mXaCpRpK5zcSnJ3Te8IYeBVH1qtFs2bV18cGxRU9aZLUVFRtXNmRUVFYrnartVqq/7lZGuKMCgoyKoOrVZrs5xarYaPj494L1u2bNmCdevW1XieiG5S+SvhF6yCOtgXfsEqBIb7QRMVgJDmgQhvEwyVP9f5NBZyhRzNu4ahedcw9JvSGeWllci9oEXRdR1KcspQnFOGkpwylObrUVFmqNMoKZEzeVTgBVS98eKIa289V1PZ+tRfW9nx48djwIAB4s+ZmZlYtmxZne9dV4Of7lG3HDgSDhDU6TuqY311KlbX34l0zapbwTq2q259rNOtGvR82FNn3au7fUGFjxwKlRxKH0XV5xt/lCoF12hRjXwDfNCiezhqGsMQTAIq9QZU6AwwVppgMppgMghV/2sUxJ8F4Ob8ufX/VH24cc7qGKoS9FpXKPGyBZKUb6Dr/5HmUYGXRqOxOYpUXFwMwPYolVlwcLDNETHzteaRL42mKpt1TfVYjpppNBqcO3euWrmysjJUVlbW2p7w8HCEh4fXeF4q0bERDq+DiMhdyeQyqPx9OCpKbsOj/hnZtm1bZGZmwmCwHjq+cOECAKBNm5oTI7Zt2xbnz5+vdtx8rG3btlb3MN/z1nos62jbti0KCwut1mrVtT1ERETU+HhU4BUXF4eysjL89NNPVsd37NiB8PBwdOnSpcZrBw0ahKysLJw8eVI8ZjAY8MMPP6BLly7i6FNERAQ6d+6M77//HkbjzbcBT5w4gaysLAwePFg8NnDgQMhkMuzYscOqru3bt8PX1xd9+/ZtUH+JiIjIu3jUVGO/fv3Qp08frFy5EjqdDi1atMCPP/6IgwcPYtGiRWIOrxUrVmDnzp347LPPEBkZCaAq5cSmTZuQkJCA2bNniwlUs7KykJiYaFXPU089hXnz5iEhIQEPPfSQmEC1TZs2Vqkj2rRpg/vuuw+pqamQy+Xo3LkzDh8+jG+//Rbx8fHM4UVERERWZEK1lYHuTafTITk52WrLoMcff9xqy6Dly5djx44d+OKLLxAVFSUez8/Pt9oyqEOHDpgxYwb69OlTrZ7Dhw9j7dq1OHv2rLhl0DPPPGNzy6D169dj+/btyM/PR2RkJB5++OF6bxl0+vRpzJw5E8nJyejYsWM9vxUiIiLyBB4XeHkrBl5ERETez6PWeBERERF5MgZeRERERE7CwIuIiIjISRh4ERERETkJAy8iIiIiJ2HgRUREROQkDLyIiIiInISBFxEREZGTeNSWQd6svLwcAJCZmenilhAREVF9tWrVCn5+frctx8DLTWRnZwMAli1b5uKWEBERUX3VdecZbhnkJgoLC3Ho0CFERUVBpVJJdt/MzEwsW7YMixYtQqtWrSS7rzvx9j56e/8A7+8j++f5vL2P7F/DccTLw4SEhGDUqFEOu3+rVq28fg9Ib++jt/cP8P4+sn+ez9v7yP45HhfXExERETkJAy8iIiIiJ2Hg5eXCwsLw5JNPIiwszNVNcRhv76O39w/w/j6yf57P2/vI/jkPF9cTEREROQlHvIiIiIichIEXERERkZMw8CIiIiJyEubxciNHjx7FCy+8YPNcUlISunbtKv58+vRpfPTRRzh58iQUCgV69uyJZ599Fs2bN6927ddff41Nmzbh6tWrCAsLw5gxYzBlyhQolbf/9RsMBnzyySfYvn078vLyEBUVhYceeggTJkxwef/+/vtvbNmyBUePHsWVK1cgk8nQqlUrTJw4EUOGDLlte65evYpHH33U5rnFixdj+PDh9esgHPM7HDRokM37zZo1C48//vht2+TOv8Pt27fjzTffrLG+2/VR6t9hXft3/PhxbN++HWfPnkVGRgYqKyvxxRdfICoqyua17vIMOqKP7vYcOuJ36InPYF37527PIFC3PhqNRnz11Vc4fPgwMjIyUFRUhGbNmmHgwIGYPHkygoKCql3rLs8hAy83NGvWLPTs2dPqWJs2bcTPmZmZeOGFF9C+fXssWbIEFRUVWLt2LZ577jmsXbsWISEhYtn169cjJSUFkydPxl133YX09HSsWbMGubm5WLBgwW3bsnLlSnz//feYMWMGOnXqhEOHDuH999+HTqfDlClTXNq/Q4cOYf/+/bj33nvRqVMnGI1G7N69GwkJCZg+fTqefPLJOrVnwoQJGDFihNWxli1b2tU3qftoNmTIkGp/uTVr1qxObXHn32H//v2RlJRU7f4pKSk4cuRIjf/Bu5XUv8Pb9e+3337Db7/9hg4dOiAgIABHjx6t8V7u+AxK2Ud3fQ6l/B0CnvcM1rV/7voMArX3sby8HKmpqRg+fDjGjRsHjUaDM2fOYP369di3bx+Sk5Ph6+srXudWz6FAbuP3338X4uLihLS0tFrLJSQkCOPGjRNKSkrEY1evXhWGDh0qrFq1SjxWWFgoDB8+XHj77betrl+/fr0waNAgISMjo9Z6Lly4IAwaNEj45JNPrI6//fbbwogRIwStVlu3jt0gdf8KCgoEk8lU7fqFCxcKI0eOFMrLy2ut58qVK0JcXJywYcOGevWjNlL3URAEIS4uTli5cqVd7XH336EtOp1OGDVqlPDss8/etj1S/w7r2j+j0Sh+3rBhgxAXFydcuXKlWjl3ewYFQfo+uttzKHX/BMEzn8H69O9WrnwGBaFufTQYDEJhYWG142lpaUJcXJywc+dO8Zi7PYdc4+VhDAYD9u3bh8GDByMgIEA8HhkZiZ49e2Lv3r3isYMHD6KiogJjx461useYMWMgCIJVWVv27t0LQRAwZsyYateXl5fj4MGDEvTIWn36FxISAplMVu0enTt3hl6vR1FRkeTtk0J9+thQ7v47tGX37t0oKyvDfffdJ3nbpCKX1+2vTk98Bs3q2kdPfQ7r2r+GctXvsCH984RnUKFQQKPRVDveuXNnAMD169fFY+72HDLwckOJiYkYOnQoRo8ejX/+8584fvy4eO7KlSsoLy9Hu3btql3Xrl07XL58GeXl5QCAjIwMAEDbtm2tyoWHh0Oj0Yjna5KRkYGQkJBqCefMdd/u+ppI1b+aHD16FCEhIQgNDa1TezZs2IBhw4Zh5MiRePbZZ/HLL7/Ur0M2SN3HXbt2YcSIERg+fDji4+Oxbdu2OrXDE3+HW7duRUBAAIYOHVrn9kj9O6ytf/Xhrs8gIF0fa+Lq51Dq/nnSM9hQ7vAMAvb18ffffwcAtG7dWjzmbs8h13i5kYCAADzyyCPo2bMngoODcfnyZXz22Wd44YUX8NZbb+Huu++GVqsFAAQHB1e7Pjg4GIIgoLi4GL6+vigqKoJKpYJarbZZ1nyvmmi1Wpv1qNVq+Pj43PZ6R/fPlu+++w5Hjx7FnDlzoFAoam2Pj48P7r//fvTp0wdhYWG4du0aNm7ciFdeeQULFy7EuHHj6tU/R/VxxIgR6N+/P5o2bYqCggJs3boVK1aswJUrVxAfH19rezztd5iZmYm//voL48ePh5+f323bI/XvsC79qw93ewYB6ftoiyufQ0f0z9OewYZw9TMI2N/HnJwcrF69Gp06dcI999wjHne355CBlxu54447cMcdd4g/9+jRA3FxcXjyySeRlJRU5wfK1rB/Q8pJdb2j+3fgwAEkJiZiyJAhdXrTJDw8vNqiyqFDh2L27NlYvXo1Ro8eXae3XSw5oo8JCQlW54YMGYJ//etf+PTTT/HII49UW4hfH+72O9y6dSsA1Pkva6l/h1L1r66c/QwCju+jq59DR/TPG5/Bmrj6GQTs62NRUREWLlwIQRCwZMmSek21Ovs55FSjmwsKCsI999yD8+fPo7y8XJzTtrVuoqioCDKZDIGBgQCqIvmKigro9XqbZW1F8JY0Go3NesrKylBZWXnb6+uiIf2zdOjQISxatAh9+vTBa6+9ZveDpFQqMWzYMGi1Wly6dMmue9xKqj5aGjlyJIxGI9LT02st50m/Q4PBgJ07d6J9+/bo1KmT3e2R+nd4a//qwxOeQaBhfbTkrs+hVP2z5M7PoL3c9RkEau9jcXEx5s2bh9zcXKxcubJaSh53ew4ZeHkAwWI7zebNm8PX1xcXLlyoVu7ChQto0aKFOIVjns++tWxeXh60Wq3Vq8e2tG3bFoWFhcjLy6tWD4DbXl9X9vbP7NChQ3jllVcQGxuLN954Az4+PpK0R8rFtw3tY01u10ZP+R0CwL59+1BQUCDJgl6pf4eCnVvaesozCNjfRzN3fw4b2r+auOMzaC93fgYt72mpuLgYL774Iq5evYp3333X5tpSd3sOGXi5ueLiYuzfvx8dOnSAr68vlEol7rnnHvz888/Q6XRiuWvXruHo0aNWOVf69u0LlUqF7du3W91z+/btkMlkiIuLq7XugQMHQiaTYceOHdWu9/X1Rd++fV3aP+DmX/Z33nkn/v3vf0OlUjWoPQaDAWlpadBoNGjRokWD7mXW0D7asnPnTiiVSqvheFs84XdotnXrVqhUKowaNapB7ZH6d3hr/+rDE55BoGF9BNz/OWxo/2xx52fQXu76DAK2+2gOuq5cuYJ33323xt+Fuz2HXOPlRpYuXYqmTZuiU6dO0Gg0uHTpEr744gvk5+fj5ZdfFstNnz4ds2bNwksvvYTJkyejoqICKSkp0Gg0+Mc//iGWCw4OxtSpU5GSkoLg4GDcddddOHXqFNatW4dx48ZZvfWxY8cOvPXWW3jppZcwevRoAFVR/H333YfU1FTI5XJ07twZhw8fxrfffov4+Ph6D69K3b/jx4/j1VdfRZMmTfD444/j3LlzVvW1bt1aTGdgq38ffPABDAYDunfvjiZNmuD69ev4+uuvcfbsWbz88su3XRTsjD5+9tlnuHjxInr37o2IiAhxYe/hw4cxbdo0q7Ulnvg7NMvNzcWhQ4cwdOhQmxmna+qf1L/DuvavsLAQx44dA3DzX70HDx5ESEgIQkJCEBsbC8D9nkFH9NHdnkOp++epz2Bd+2fmLs9gXftYXl6Of/7znzh79iyef/55GI1GnDhxQrxHSEiIGPS523PIwMuNtG3bFmlpadiyZQvKysoQFBSE7t2749VXXxVzkwBAq1at8P777+Ojjz5CQkICFAoFevXqhWeeeabaIs+pU6fC398fmzZtwueff44mTZrgsccew9SpU63KCYIAo9FYbSh33rx5CA8Px8aNG5Gfn4/IyEjMmTPHrm0SpO7fkSNHUF5ejuzsbMydO7dafe+9956Y9dhW/9q0aYMtW7Zg165dKC0thb+/Pzp37oz//Oc/di9QlbqPMTEx+PXXX7F//37xTcD27dvb3IrDE3+HZtu3b4fRaKx1Qa8zfod17V9GRka1BdcrV64EAMTGxuL9998Xj7vTM+iIPrrbcyh1/zz1GazP/0cB93kG69rH/Px8cX3drX0BgNGjR+OVV14Rf3an51AmOGrim4iIiIiscI0XERERkZMw8CIiIiJyEgZeRERERE7CwIuIiIjISRh4ERERETkJAy8iIiIiJ2HgRUREROQkDLyIiIiInISBFxGRG7p48SJkMpn4JzIy0ur8kiVLIJPJsGfPHtc08BaPP/64VXvXrVvn6iYRuSUGXkTkVLcGFLb+3LqPXGPWo0cPLF68GPPnz3d4XatXr4ZMJsNTTz1127K9e/eGTCbD77//DgB4+OGHsXjxYjzwwAOObiaRR+NejUTkEu3atcPjjz9u89ytozuNWWxsLJYsWeKUuiZNmoR58+bh888/R2JiItRqtc1yx48fx++//47Y2Fj06tULQFXg9fDDD2PdunXYvHmzU9pL5IkYeBGRS7Rv395pAQXVTXBwMB555BGsX78eGzduxOTJk22WS0lJAQDMmDHDmc0j8gqcaiQityeTyTBkyBDk5ORg+vTpaNq0KdRqNfr161fjGqfi4mIsXrwYXbt2hVqtRkhICEaPHo1ffvmlWtkhQ4ZAJpOhvLwcCQkJaN++PXx8fKwCw40bN6JPnz5Qq9Vo1qwZZs6ciYKCArRu3RqtW7cWyz3xxBOQyWQ4fPiwzXYtXLgQMpkMmzZtashXUqPjx4+jefPmCA8Px8GDB8XjGRkZiI+PR0xMDHx9fREVFYUnn3wSmZmZVtebg6nU1FSb96+oqMCnn34KX1/fGgMzIqoZR7yIyCMUFhZiwIABCA4OxuTJk3H9+nV88cUXuPfee/Hbb7+hW7duYtn8/HwMGjQIJ06cQFxcHO69915otVps3rwZQ4cOxZdffokHH3ywWh0PP/ww/vjjD9x7771o0qQJ2rZtCwBYu3YtZsyYgZCQEEydOhUajQbbtm3DyJEjUVlZCR8fH/Ees2fPxvr165GcnIy77rrL6v6VlZVYv349IiMjcf/990v+He3duxf3338/goODsXv3bnTq1AkAcPDgQdx7770oLS3F/fffj/bt2+PixYv49NNPsX37duzfv1/s66BBg9ChQwfs3r0bFy9etAoqAWDLli3Iy8vDpEmTEBoaKnkfiLyeQETkRBkZGQIAoV27dsLixYtt/tm+fbvVNQAEAMIzzzwjGI1G8fiaNWsEAMLs2bOtyj/22GMCAGHt2rVWx7Ozs4Xo6GghIiJCKCsrE48PHjxYACDExsYKeXl5VtcUFBQIgYGBQlBQkHD+/HnxeGVlpTBixAgBgNCqVSura7p16yYEBQUJJSUlVsc3btwoABBeeumlOn9PTzzxhM3zixcvFgAIaWlpgiAIwjfffCP4+fkJXbp0Ef7++2+xXEVFhdC6dWshKChIOHbsmNU99u7dKygUCmHcuHFWx998800BgLBkyZJq9Y4ZM0YAIOzatctmu1JTUwUAQmpq6m37SNQYMfAiIqcyBxS1/XnhhResrgEgBAQECMXFxVbHKysrBaVSKfTq1Us8lpOTIygUCmH48OE263///fcFAMK3334rHjMHXps3b65Wft26dQIA4cUXX6x2bv/+/TYDL3MdKSkpVsfHjh0ryGQy4ezZszbbZqk+gdeaNWsEhUIh9O/fv1rgaA723njjDZv3efjhhwW5XC5otVrx2JUrVwSFQiG0bt1aMJlM4vHLly/bPG6JgRdR7TjVSEQuce+992LHjh11Lt+hQwcEBgZaHVMqlWjWrBkKCwvFY4cPH4bRaIRer7e5eP/s2bMAgPT0dIwbN87q3N13312t/B9//AEAuOeee6qdu/vuu6FUVv9rdMqUKXjppZewZs0aTJ8+HQBw+fJl7Ny5E4MHD0b79u1r72w9JCYmYsuWLRg7diy+/PJL+Pv7W50/cOAAgKr+2vo+srOzYTKZcObMGfTp0wcAEBUVhTFjxuC7775DWloahg0bBgBYt24djEYjpk2bBplMJlkfiBoTBl5E5BE0Go3N40qlEkajUfw5Pz8fAPDrr7/i119/rfF+paWl1Y41a9as2rGioiIAQERERLVzcrkc4eHh1Y6HhIRg4sSJ+Pjjj3Hy5El06dIFqampMBqNmDlzZo1tssfevXsBAKNHj64WdAE3v49PP/201vvc+n3MmDED3333HVJTU60CL7lcjieffFKClhM1TnyrkYi8SnBwMADgn//8J4Sq5RQ2/yxevLjatbZGccz3y8nJqXbOZDIhNzfXZjtmz54NAFizZg0EQUBqaiqaNGmChx9+2O6+2ZKSkoJevXrhhRdewKpVq6qdN7f/22+/rfX7GDx4sNV148aNQ7NmzfD111+jqKgIe/fuxdmzZzFy5EjExMRI2geixoSBFxF5lbvuugsymQz79++X5H49evQAAOzbt6/auUOHDsFgMNi8rn///ujevTs++eQTbN++HRcuXMDjjz8OPz8/SdplFhoail27dqFXr1549tln8eGHH1qd79u3LwDU+/tQKpWYOnUqysrK8Pnnn2Pt2rUAmLuLqKEYeBGRV4mMjMTEiROxb98+vPPOOxAEoVqZgwcPQqfT1el+DzzwAAIDA7FmzRpkZGSIxw0GA1577bVar501axZyc3PF6cX4+Ph69KTuzMFXnz598Nxzz+H/+//+P6v2x8TEYOXKlfj555+rXVtZWWkztxlwM8hatWoVvvzyS4SFhXFLIKIG4hovInKJc+fO1Zq5viFZ7VetWoXTp09j4cKF+OSTT9C/f39oNBr8/fff+O2333D27FlcvXrV5pqoW4WEhGDlypWYNWsWevXqhUcffVTM4+Xr64vmzZtDLrf9b1jzIvsrV66gb9++6N69u919qks7f/jhB4waNQpz5syBIAiYM2cOfH198dVXX2HMmDEYPHgwhg8fLuY8y8rKwt69exEWFob09PRq9+zYsSMGDBggrpWbOXMmVCqVw/pA1Bgw8CIilzh//jxef/31Gs83JPBq0qQJ9u3bhw8++ABffPEFPv30U5hMJkRGRqJHjx547bXXbC6Kr8nMmTMRGhqK5cuXY926ddBoNBg/fjzeeusttGrVCu3atbN5nUajwQMPPIDPPvtM8kX1tlgGXy+88AIEQcALL7yAu+66C3/88QfeeecdbNu2Db/88gt8fX3RokULPPjgg5g0aVKN95wxY4YYeJnf0CQi+8kEW+PwRER0W+fOnUOHDh0wceJEfPHFFzbLdO3aFVlZWbh69Wq1dBi1uXjxItq0aYMnnngC69atk6jFjrdu3TpMmzYNqampfPuRyAau8SIiuo2CggKUl5dbHSsrK8OLL74IADa3HwKAbdu24eTJk5gyZUq9gi5LH3/8MWQyGSIjI+263lkef/xxyGQyTJs2zdVNIXJrnGokIrqNn376CTNmzMCoUaMQExOD3NxccS/DYcOG4dFHH7Uqn5SUhL///hvJyclQq9VYuHBhvesMCQmxSnlhb+DmLA8//LBVYtjY2FjXNYbIjXGqkYjoNs6ePYvXXnsN+/btE/N5tW/fHo8++ijmz59fLUVE69atcenSJXTs2BFvvfVWtQz5RNR4MfAiIiIichKu8SIiIiJyEgZeRERERE7CwIuIiIjISRh4ERERETkJAy8iIiIiJ2HgRUREROQkDLyIiIiInISBFxEREZGT/P8dS6oUwHgCGQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Best-fit model:\n", "energy = np.linspace(500.,520.,201)*u.keV\n", "flux = results.optimized_model[\"gaussian\"].spectrum.main.shape(energy)\n", "\n", "fig,ax = plt.subplots()\n", "\n", "ax.plot(energy, flux, label = \"Best fit\")\n", "\n", "\n", "plt.ylabel(\"dN/dE [$\\mathrm{ph \\ cm^{-2} \\ s^{-1} \\ keV^{-1}}$]\", fontsize=14)\n", "plt.xlabel(\"Energy [keV]\", fontsize=14)\n", "ax.legend()" ] }, { "cell_type": "markdown", "id": "5b3cafef-b0c4-4cfb-8aaa-533c3be57f7b", "metadata": {}, "source": [ "Now let's compare the predicted counts to the injected counts:" ] }, { "cell_type": "code", "execution_count": 9, "id": "a2a754b4-5aef-48cb-bf0f-43cad8029e5d", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Error: [2129.064008]\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get expected counts from likelihood scan (i.e. best-fit convolved with response):\n", "total_expectation = cosi._expected_counts['gaussian']\n", "\n", "# Plot: \n", "fig,ax = plt.subplots()\n", "\n", "binned_energy_edges = gal_511.binned_data.axes['Em'].edges.value\n", "binned_energy = gal_511.binned_data.axes['Em'].centers.value\n", "\n", "ax.stairs(total_expectation.project('Em').todense().contents, binned_energy_edges, color='purple', label = \"Best fit convolved with response\")\n", "ax.errorbar(binned_energy, total_expectation.project('Em').todense().contents, yerr=np.sqrt(total_expectation.project('Em').todense().contents), color='purple', linewidth=0, elinewidth=1)\n", "ax.stairs(gal_511.binned_data.project('Em').todense().contents, binned_energy_edges, color = 'black', ls = \":\", label = \"Injected source counts\")\n", "ax.errorbar(binned_energy, gal_511.binned_data.project('Em').todense().contents, yerr=np.sqrt(gal_511.binned_data.project('Em').todense().contents), color='black', linewidth=0, elinewidth=1)\n", "\n", "ax.set_xlabel(\"Energy (keV)\")\n", "ax.set_ylabel(\"Counts\")\n", "\n", "ax.legend()\n", "\n", "# Note: We are plotting the error, but it's very small:\n", "print(\"Error: \" +str(np.sqrt(total_expectation.project('Em').todense().contents)))" ] }, { "cell_type": "markdown", "id": "55c9c56a-7742-4e3a-8ffa-95fee0323df7", "metadata": {}, "source": [ "Let's also compare the projection onto Psichi:" ] }, { "cell_type": "code", "execution_count": 10, "id": "18997c67-c643-428a-beb6-57872daeb3ac", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'injected counts')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# expected src counts:\n", "ax,plot = total_expectation.slice[{'Em':0, 'Phi':5}].project('PsiChi').plot(ax_kw = {'coord':'G'})\n", "plt.title(\"model counts\")\n", "\n", "# injected src counts:\n", "ax,plot = gal_511.binned_data.slice[{'Em':0, 'Phi':5}].project('PsiChi').plot(ax_kw = {'coord':'G'})\n", "plt.title(\"injected counts\")" ] }, { "cell_type": "markdown", "id": "2ee20295-ca20-4736-bad8-c87e6fc6a846", "metadata": {}, "source": [ "Here is a summary of the results:\n", "\n", "Injected model (extended source):
\n", "F = 4e-2 ph/cm2/s
\n", "\n", "Best-fit:
\n", "F = (4.6951 +/- 0.0025)e-2 ph/cm2/s
\n", "\n", "We see that the best-fit values are very close to the injected values. The small difference is likely due to the fact that the injected model also has a point source component (which we've ignored), having the same specrtum, with a normalization of F = 1e-2 ph/cm2/s. In the next example we'll see if this point source component can be detected. " ] }, { "cell_type": "markdown", "id": "c72fd667-9826-42eb-b996-7f39764d6b49", "metadata": {}, "source": [ "## **********************************************************\n", "## Example 2: Perform Analysis with Two Components" ] }, { "cell_type": "markdown", "id": "807821ac-3063-4a53-a613-2fee043e9662", "metadata": {}, "source": [ "Define the point source.
\n", "We'll add this to the model, and keep just the normalization free." ] }, { "cell_type": "code", "execution_count": 11, "id": "ec211c66-d974-48e2-86a8-2c0f63b34fc2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " * description: A Gaussian function\n", " * formula: $ K \\frac{1}{\\sigma \\sqrt{2 \\pi}}\\exp{\\frac{(x-\\mu)^2}{2~(\\sigma)^2}} $\n", " * parameters:\n", " * F:\n", " * value: 0.01\n", " * desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution\n", " * min_value: 0.0\n", " * max_value: 1.0\n", " * unit: s-1 cm-2\n", " * is_normalization: false\n", " * delta: 0.1\n", " * free: true\n", " * mu:\n", " * value: 511.0\n", " * desc: Central value\n", " * min_value: null\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * delta: 0.1\n", " * free: false\n", " * sigma:\n", " * value: 0.85\n", " * desc: standard deviation\n", " * min_value: 1.0e-12\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * delta: 0.1\n", " * free: false\n", "\n" ] } ], "source": [ "# Note: Astromodels only takes ra,dec for point source input:\n", "c = SkyCoord(l=0*u.deg, b=0*u.deg, frame='galactic')\n", "c_icrs = c.transform_to('icrs')\n", "\n", "# Define spectrum:\n", "# Note that the units of the Gaussian function below are [F/sigma]=[ph/cm2/s/keV]\n", "F = 1e-2 / u.cm / u.cm / u.s \n", "Fmin = 0 / u.cm / u.cm / u.s\n", "Fmax = 1 / u.cm / u.cm / u.s\n", "mu = 511*u.keV\n", "sigma = 0.85*u.keV\n", "spectrum2 = Gaussian()\n", "spectrum2.F.value = F.value\n", "spectrum2.F.unit = F.unit\n", "spectrum2.F.min_value = Fmin.value\n", "spectrum2.F.max_value = Fmax.value\n", "spectrum2.mu.value = mu.value\n", "spectrum2.mu.unit = mu.unit\n", "spectrum2.sigma.value = sigma.value\n", "spectrum2.sigma.unit = sigma.unit\n", "\n", "# Set spectral parameters for fitting:\n", "spectrum2.F.free = True\n", "spectrum2.mu.free = False\n", "spectrum2.sigma.free = False\n", "\n", "# Define source:\n", "src2 = PointSource('point_source', ra = c_icrs.ra.deg, dec = c_icrs.dec.deg, spectral_shape=spectrum2)\n", "\n", "# Print some info about the source just as a sanity check.\n", "# This will also show you which parameters are free. \n", "print(src2.spectrum.main.shape)\n", "\n", "# We can also get a summary of the source info as follows:\n", "#src2.display()" ] }, { "cell_type": "markdown", "id": "e71243c5-3c9f-4ec7-b928-2cdbdee045e0", "metadata": {}, "source": [ "Redefine the first source.
\n", "We'll keep just the normalization free. " ] }, { "cell_type": "code", "execution_count": 12, "id": "5bbdd2c6-39b0-4c69-bcaf-5a5b8becefdb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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\n" ], "text/plain": [ " * gaussian (extended source):\n", " * shape:\n", " * lon0:\n", " * value: 359.75\n", " * desc: Longitude of the center of the source\n", " * min_value: 0.0\n", " * max_value: 360.0\n", " * unit: deg\n", " * is_normalization: false\n", " * lat0:\n", " * value: -1.25\n", " * desc: Latitude of the center of the source\n", " * min_value: -90.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * sigma:\n", " * value: 5.0\n", " * desc: Standard deviation of the Gaussian distribution\n", " * min_value: 0.0\n", " * max_value: 20.0\n", " * unit: deg\n", " * is_normalization: false\n", " * spectrum:\n", " * main:\n", " * Gaussian:\n", " * F:\n", " * value: 0.04\n", " * desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution\n", " * min_value: 0.0\n", " * max_value: 1.0\n", " * unit: s-1 cm-2\n", " * is_normalization: false\n", " * mu:\n", " * value: 511.0\n", " * desc: Central value\n", " * min_value: null\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * sigma:\n", " * value: 0.85\n", " * desc: standard deviation\n", " * min_value: 1.0e-12\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * polarization: {}" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Define spectrum:\n", "# Note that the units of the Gaussian function below are [F/sigma]=[ph/cm2/s/keV]\n", "F = 4e-2 / u.cm / u.cm / u.s \n", "Fmin = 0 / u.cm / u.cm / u.s\n", "Fmax = 1 / u.cm / u.cm / u.s\n", "mu = 511*u.keV\n", "sigma = 0.85*u.keV\n", "spectrum = Gaussian()\n", "spectrum.F.value = F.value\n", "spectrum.F.unit = F.unit\n", "spectrum.F.min_value = Fmin.value\n", "spectrum.F.max_value = Fmax.value\n", "spectrum.mu.value = mu.value\n", "spectrum.mu.unit = mu.unit\n", "spectrum.sigma.value = sigma.value\n", "spectrum.sigma.unit = sigma.unit\n", "\n", "# Set spectral parameters for fitting:\n", "spectrum.F.free = True\n", "spectrum.mu.free = False\n", "spectrum.sigma.free = False\n", "\n", "# Define morphology:\n", "morphology = Gaussian_on_sphere(lon0 = 359.75, lat0 = -1.25, sigma = 5)\n", "\n", "# Set morphological parameters for fitting:\n", "morphology.lon0.free = False\n", "morphology.lat0.free = False\n", "morphology.sigma.free = False\n", "\n", "# Define source:\n", "src1 = ExtendedSource('gaussian', spectral_shape=spectrum, spatial_shape=morphology)\n", "\n", "# Print a summary of the source info:\n", "src1.display()\n", "\n", "# We can also print the source info as follows.\n", "# This will also show you which parameters are free. \n", "#print(src1.spectrum.main.shape)\n", "#print(src1.spatial_shape)" ] }, { "cell_type": "markdown", "id": "1677d2c7-8127-4383-a1d3-d0a5c3425e4d", "metadata": {}, "source": [ "Setup the COSI 3ML plugin using two sources in the model:" ] }, { "cell_type": "code", "execution_count": 13, "id": "79816fcd-525e-4892-b179-b4cc8b502743", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "... loading the pre-computed image response ...\n", "--> done\n", "CPU times: user 2min 10s, sys: 41.5 s, total: 2min 52s\n", "Wall time: 3min 10s\n" ] } ], "source": [ "%%time \n", "\n", "# Set background parameter, which is used to fit the amplitude of the background:\n", "bkg_par = Parameter(\"background_cosi\", # background parameter\n", " 1, # initial value of parameter\n", " min_value=0, # minimum value of parameter\n", " max_value=5, # maximum value of parameter\n", " delta=0.05, # initial step used by fitting engine\n", " desc=\"Background parameter for cosi\")\n", "\n", "# Instantiate the COSI 3ML plugin\n", "cosi = COSILike(\"cosi\", # COSI 3ML plugin\n", " dr = response_file, # detector response\n", " data = data_combined.binned_data.project('Em', 'Phi', 'PsiChi'), # data (source+background)\n", " bkg = bg_tot.binned_data.project('Em', 'Phi', 'PsiChi'), # background model \n", " sc_orientation = ori, # spacecraft orientation\n", " nuisance_param = bkg_par, # background parameter\n", " precomputed_psr_file = psr_file) # full path to precomputed psr file in galactic coordinates (optional)\n", " \n", "# Add sources to model:\n", "model = Model(src1, src2) # Model with two sources." ] }, { "cell_type": "markdown", "id": "d46ba4c1-9698-4114-9000-1a02feafa4ec", "metadata": {}, "source": [ "Display the model:" ] }, { "cell_type": "code", "execution_count": 14, "id": "a9423539-928d-41f6-9aab-04a18c1ea0b7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "Model summary:

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N
Point sources1
Extended sources1
Particle sources0
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Free parameters (2):

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valuemin_valuemax_valueunit
gaussian.spectrum.main.Gaussian.F0.040.01.0s-1 cm-2
point_source.spectrum.main.Gaussian.F0.010.01.0s-1 cm-2
\n", "


Fixed parameters (9):
(abridged. Use complete=True to see all fixed parameters)


Properties (0):

(none)


Linked parameters (0):

(none)

Independent variables:

(none)

Linked functions (0):

(none)
" ], "text/plain": [ "Model summary:\n", "==============\n", "\n", " N\n", "Point sources 1\n", "Extended sources 1\n", "Particle sources 0\n", "\n", "Free parameters (2):\n", "--------------------\n", "\n", " value min_value max_value unit\n", "gaussian.spectrum.main.Gaussian.F 0.04 0.0 1.0 s-1 cm-2\n", "point_source.spectrum.main.Gaussian.F 0.01 0.0 1.0 s-1 cm-2\n", "\n", "Fixed parameters (9):\n", "(abridged. Use complete=True to see all fixed parameters)\n", "\n", "\n", "Properties (0):\n", "--------------------\n", "\n", "(none)\n", "\n", "\n", "Linked parameters (0):\n", "----------------------\n", "\n", "(none)\n", "\n", "Independent variables:\n", "----------------------\n", "\n", "(none)\n", "\n", "Linked functions (0):\n", "----------------------\n", "\n", "(none)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.display()" ] }, { "cell_type": "markdown", "id": "e57b7109-e602-4a83-b575-abf8d602b579", "metadata": {}, "source": [ "Before we perform the fit, let's first change the 3ML console logging level, in order to mimimize the amount of console output." ] }, { "cell_type": "code", "execution_count": 25, "id": "c83d4333-90e1-4f55-b3f9-e5da1fd40598", "metadata": {}, "outputs": [], "source": [ "# This is a simple workaround for now to prevent a lot of output. \n", "from threeML import update_logging_level\n", "update_logging_level(\"CRITICAL\")" ] }, { "cell_type": "markdown", "id": "17f87aa8-eade-410e-a793-c15ad4604703", "metadata": {}, "source": [ "Perform the likelihood fit:" ] }, { "cell_type": "code", "execution_count": 18, "id": "85eae192-0970-406c-bbd3-fa9a133d32dc", "metadata": { "scrolled": true, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.\n" ] }, { "data": { "text/html": [ "
Best fit values:\n",
       "\n",
       "
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resultunit
parameter
gaussian.spectrum.main.Gaussian.F(4.6951 +/- 0.0025) x 10^-21 / (cm2 s)
point_source.spectrum.main.Gaussian.F(0.0 +/- 1.3) x 10^-91 / (cm2 s)
background_cosi(9.32 +/- 0.05) x 10^-1
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" ], "text/plain": [ " result \\\n", "parameter \n", "gaussian.spectrum.main.Gaussian.F (4.6951 +/- 0.0025) x 10^-2 \n", "point_source.spectrum.main.Gaussian.F (0.0 +/- 1.3) x 10^-9 \n", "background_cosi (9.32 +/- 0.05) x 10^-1 \n", "\n", " unit \n", "parameter \n", "gaussian.spectrum.main.Gaussian.F 1 / (cm2 s) \n", "point_source.spectrum.main.Gaussian.F 1 / (cm2 s) \n", "background_cosi " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Correlation matrix:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "
1.00-0.01-0.40
-0.011.00-0.03
-0.40-0.031.00
" ], "text/plain": [ " 1.00 -0.01 -0.40\n", "-0.01 1.00 -0.03\n", "-0.40 -0.03 1.00" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of -log(likelihood) at the minimum:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of -\u001b[0m\u001b[1;4;38;5;49mlog\u001b[0m\u001b[1;4;38;5;49m(\u001b[0m\u001b[1;4;38;5;49mlikelihood\u001b[0m\u001b[1;4;38;5;49m)\u001b[0m\u001b[1;4;38;5;49m at the minimum:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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-log(likelihood)
cosi-1.527559e+07
total-1.527559e+07
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" ], "text/plain": [ " -log(likelihood)\n", "cosi -1.527559e+07\n", "total -1.527559e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of statistical measures:\n",
       "\n",
       "
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statistical measures
AIC-3.055119e+07
BIC-3.055119e+07
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" ], "text/plain": [ " statistical measures\n", "AIC -3.055119e+07\n", "BIC -3.055119e+07" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 7min 24s, sys: 3min 55s, total: 11min 20s\n", "Wall time: 1min 46s\n" ] }, { "data": { "text/plain": [ "( value negative_error \\\n", " gaussian.spectrum.main.Gaussian.F 4.695126e-02 -2.403110e-05 \n", " point_source.spectrum.main.Gaussian.F 5.975791e-13 2.623492e-10 \n", " background_cosi 9.320815e-01 -4.914467e-03 \n", " \n", " positive_error error \\\n", " gaussian.spectrum.main.Gaussian.F 2.433950e-05 2.418530e-05 \n", " point_source.spectrum.main.Gaussian.F 1.929678e-09 1.096013e-09 \n", " background_cosi 4.582905e-03 4.748686e-03 \n", " \n", " unit \n", " gaussian.spectrum.main.Gaussian.F 1 / (cm2 s) \n", " point_source.spectrum.main.Gaussian.F 1 / (cm2 s) \n", " background_cosi ,\n", " -log(likelihood)\n", " cosi -1.527559e+07\n", " total -1.527559e+07)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time\n", "plugins = DataList(cosi) # If we had multiple instruments, we would do e.g. DataList(cosi, lat, hawc, ...)\n", "\n", "like = JointLikelihood(model, plugins, verbose = True)\n", "\n", "like.fit()" ] }, { "cell_type": "markdown", "id": "5c045f61-bd7a-44e3-933f-a4f1541b7aa3", "metadata": {}, "source": [ "We see that the normalization of the point source has gone to zero, and we essentially get the same results as the first fit. This is not entirely surprising, considering that the two components have a high degree of degeneracy, and the point source is subdominant. \n", "\n", "Note (CK): The injected model may not be exactly the same as the astromodel, because MEGAlib uses a cutoff of the Gaussian spectral distribution at 3 sigma. " ] }, { "cell_type": "markdown", "id": "0e47eea2", "metadata": {}, "source": [ "## *****************************************\n", "## Example 3: Working With a Realistic Model" ] }, { "cell_type": "markdown", "id": "672fa8bd", "metadata": {}, "source": [ "## Read in the binned data\n", "We will start with the binned data, since we already learned how to bin data: " ] }, { "cell_type": "code", "execution_count": 2, "id": "9bce7e04", "metadata": {}, "outputs": [], "source": [ "# background:\n", "bg_tot = BinnedData(\"Gal_511.yaml\")\n", "bg_tot.load_binned_data_from_hdf5(binned_data=\"cosmic_photons_binned_data.hdf5\")\n", "\n", "# combined data:\n", "data_combined_thin_disk = BinnedData(\"Gal_511.yaml\")\n", "data_combined_thin_disk.load_binned_data_from_hdf5(binned_data=\"combined_binned_data_thin_disk.hdf5\")" ] }, { "cell_type": "markdown", "id": "3466ee97", "metadata": {}, "source": [ "## Define source\n", "This defines a multi-component source with a disk and gaussian component. The disk and bulge components have different spectral characteristics. Spatially, the bulge component is the sum of three different spatial models, with majority of the flux \"narrow bulge\" with " ] }, { "cell_type": "code", "execution_count": 3, "id": "3ca51102", "metadata": {}, "outputs": [], "source": [ "# Spectral Definitions...\n", "\n", "models = [\"centralPoint\",\"narrowBulge\",\"broadBulge\",\"disk\"]\n", "\n", "# several lists of parameters for, in order, CentralPoint, NarrowBulge, BroadBulge, and Disk sources\n", "mu = [511.,511.,511., 511.]*u.keV\n", "sigma = [0.85,0.85,0.85, 1.27]*u.keV\n", "F = [0.00012, 0.00028, 0.00073, 1.7e-3]/u.cm/u.cm/u.s\n", "K = [0.00046, 0.0011, 0.0027, 4.5e-3]/u.cm/u.cm/u.s/u.keV\n", "\n", "SpecLine = [Gaussian(),Gaussian(),Gaussian(),Gaussian()]\n", "SpecOPs = [SpecFromDat(dat=\"OPsSpectrum.dat\"),SpecFromDat(dat=\"OPsSpectrum.dat\"),SpecFromDat(dat=\"OPsSpectrum.dat\"),SpecFromDat(dat=\"OPsSpectrum.dat\")]\n", "\n", "# Set units and fitting parameters; different definition for each spectral model with different norms\n", "for i in range(4):\n", " SpecLine[i].F.unit = F[i].unit\n", " SpecLine[i].F.value = F[i].value\n", " SpecLine[i].F.min_value =0\n", " SpecLine[i].F.max_value=1\n", " SpecLine[i].mu.value = mu[i].value\n", " SpecLine[i].mu.unit = mu[i].unit\n", " SpecLine[i].sigma.unit = sigma[i].unit\n", " SpecLine[i].sigma.value = sigma[i].value\n", "\n", " SpecOPs[i].K.value = K[i].value\n", " SpecOPs[i].K.unit = K[i].unit\n", " \n", " SpecLine[i].sigma.free = False\n", " SpecLine[i].mu.free = False\n", " SpecLine[i].F.free = False#True\n", " SpecOPs[i].K.free = False # not fitting the amplitude of the OPs component for now, since we are only using the 511 response! \n", "\n", "SpecLine[-1].F.free = True# actually do fit the flux of the disk component\n", "\n", "# Generate Composite Spectra\n", "SpecCentralPoint= SpecLine[0] + SpecOPs[0]\n", "SpecNarrowBulge = SpecLine[1] + SpecOPs[1]\n", "SpecBroadBulge = SpecLine[2] + SpecOPs[2]\n", "SpecDisk = SpecLine[3] + SpecOPs[3]" ] }, { "cell_type": "code", "execution_count": 4, "id": "008ec971", "metadata": {}, "outputs": [], "source": [ "# Define Spatial Model Components\n", "MapNarrowBulge = Gaussian_on_sphere(lon0=359.75,lat0=-1.25, sigma = 2.5)\n", "MapBroadBulge = Gaussian_on_sphere(lon0 = 0, lat0 = 0, sigma = 8.7)\n", "MapDisk = Wide_Asymm_Gaussian_on_sphere(lon0 = 0, lat0 = 0, a=90, e = 0.99944429,theta=0)\n", "\n", "# Fix fitting parameters (same for all models)\n", "for map in [MapNarrowBulge,MapBroadBulge]:\n", " map.lon0.free=False\n", " map.lat0.free=False\n", " map.sigma.free=False\n", " \n", "MapDisk.lon0.free=False\n", "MapDisk.lat0.free=False\n", "MapDisk.a.free=False\n", "MapDisk.e.free=True#False\n", "MapDisk.theta.free=False" ] }, { "cell_type": "markdown", "id": "d4dc7eca-6881-45cb-801a-3e796a13dbfc", "metadata": {}, "source": [ "For the Wide_Asymm_Gaussian_on_sphere model, note that e is the eccentricity of the Gaussian ellipse, defined such that the scale height b of the disk is given by $b = a \\sqrt{(1-e^2)}$" ] }, { "cell_type": "code", "execution_count": 5, "id": "924aec1c", "metadata": {}, "outputs": [], "source": [ "# Define Spatio-spectral models\n", "\n", "# Bulge\n", "c = SkyCoord(l=0*u.deg, b=0*u.deg, frame='galactic')\n", "c_icrs = c.transform_to('icrs')\n", "ModelCentralPoint = PointSource('centralPoint', ra = c_icrs.ra.deg, dec = c_icrs.dec.deg, spectral_shape=SpecCentralPoint)\n", "ModelNarrowBulge = ExtendedSource('narrowBulge',spectral_shape=SpecNarrowBulge,spatial_shape=MapNarrowBulge)\n", "ModelBroadBulge = ExtendedSource('broadBulge',spectral_shape=SpecBroadBulge,spatial_shape=MapBroadBulge)\n", "\n", "# Disk\n", "ModelDisk = ExtendedSource('disk',spectral_shape=SpecDisk,spatial_shape=MapDisk)" ] }, { "cell_type": "code", "execution_count": 9, "id": "b5784f63-3712-496b-a724-e64c2b66b180", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
    \n", "\n", "
  • disk (extended source): \n", "
      \n", "\n", "
    • shape: \n", "
        \n", "\n", "
      • lon0: \n", "
          \n", "\n", "
        • value: 0.0
          • \n", "\n", "
        • desc: Longitude of the center of the source
          • \n", "\n", "
        • min_value: 0.0
          • \n", "\n", "
        • max_value: 360.0
          • \n", "\n", "
        • unit: deg
          • \n", "\n", "
        • is_normalization: False
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      • lat0: \n", "
          \n", "\n", "
        • value: 0.0
          • \n", "\n", "
        • desc: Latitude of the center of the source
          • \n", "\n", "
        • min_value: -90.0
          • \n", "\n", "
        • max_value: 90.0
          • \n", "\n", "
        • unit: deg
          • \n", "\n", "
        • is_normalization: False
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      • a: \n", "
          \n", "\n", "
        • value: 90.0
          • \n", "\n", "
        • desc: Standard deviation of the Gaussian distribution (major axis)
          • \n", "\n", "
        • min_value: 0.0
          • \n", "\n", "
        • max_value: 90.0
          • \n", "\n", "
        • unit: deg
          • \n", "\n", "
        • is_normalization: False
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      • e: \n", "
          \n", "\n", "
        • value: 0.99944429
          • \n", "\n", "
        • desc: Excentricity of Gaussian ellipse, e^2 = 1 - (b/a)^2, where b is the standard deviation of the Gaussian distribution (minor axis)
          • \n", "\n", "
        • min_value: 0.0
          • \n", "\n", "
        • max_value: 1.0
          • \n", "\n", "
        • unit:
          • \n", "\n", "
        • is_normalization: False
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      • theta: \n", "
          \n", "\n", "
        • value: 0.0
          • \n", "\n", "
        • desc: inclination of major axis to a line of constant latitude
          • \n", "\n", "
        • min_value: -90.0
          • \n", "\n", "
        • max_value: 90.0
          • \n", "\n", "
        • unit: deg
          • \n", "\n", "
        • is_normalization: False
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      \n", "\n", "
      • \n", "\n", "
    • spectrum: \n", "
        \n", "\n", "
      • main: \n", "
          \n", "\n", "
        • composite: \n", "
            \n", "\n", "
          • F_1: \n", "
              \n", "\n", "
            • value: 0.0017
              • \n", "\n", "
            • desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution
              • \n", "\n", "
            • min_value: 0.0
              • \n", "\n", "
            • max_value: 1.0
              • \n", "\n", "
            • unit: s-1 cm-2
              • \n", "\n", "
            • is_normalization: False
              • \n", "\n", "
            \n", "\n", "
            • \n", "\n", "
          • mu_1: \n", "
              \n", "\n", "
            • value: 511.0
              • \n", "\n", "
            • desc: Central value
              • \n", "\n", "
            • min_value: None
              • \n", "\n", "
            • max_value: None
              • \n", "\n", "
            • unit: keV
              • \n", "\n", "
            • is_normalization: False
              • \n", "\n", "
            \n", "\n", "
            • \n", "\n", "
          • sigma_1: \n", "
              \n", "\n", "
            • value: 1.27
              • \n", "\n", "
            • desc: standard deviation
              • \n", "\n", "
            • min_value: 1e-12
              • \n", "\n", "
            • max_value: None
              • \n", "\n", "
            • unit: keV
              • \n", "\n", "
            • is_normalization: False
              • \n", "\n", "
            \n", "\n", "
            • \n", "\n", "
          • K_2: \n", "
              \n", "\n", "
            • value: 0.004499999999999998
              • \n", "\n", "
            • desc: Normalization
              • \n", "\n", "
            • min_value: 1e-30
              • \n", "\n", "
            • max_value: 1000.0
              • \n", "\n", "
            • unit: keV-1 s-1 cm-2
              • \n", "\n", "
            • is_normalization: True
              • \n", "\n", "
            \n", "\n", "
            • \n", "\n", "
          • dat_2: OPsSpectrum.dat
            • \n", "\n", "
          \n", "\n", "
          • \n", "\n", "
        \n", "\n", "
        • \n", "\n", "
      \n", "\n", "
      • \n", "\n", "
    \n", "\n", "
    • \n", "\n", "
\n" ], "text/plain": [ " * disk (extended source):\n", " * shape:\n", " * lon0:\n", " * value: 0.0\n", " * desc: Longitude of the center of the source\n", " * min_value: 0.0\n", " * max_value: 360.0\n", " * unit: deg\n", " * is_normalization: false\n", " * lat0:\n", " * value: 0.0\n", " * desc: Latitude of the center of the source\n", " * min_value: -90.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * a:\n", " * value: 90.0\n", " * desc: Standard deviation of the Gaussian distribution (major axis)\n", " * min_value: 0.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * e:\n", " * value: 0.99944429\n", " * desc: Excentricity of Gaussian ellipse, e^2 = 1 - (b/a)^2, where b is the standard\n", " * deviation of the Gaussian distribution (minor axis)\n", " * min_value: 0.0\n", " * max_value: 1.0\n", " * unit: ''\n", " * is_normalization: false\n", " * theta:\n", " * value: 0.0\n", " * desc: inclination of major axis to a line of constant latitude\n", " * min_value: -90.0\n", " * max_value: 90.0\n", " * unit: deg\n", " * is_normalization: false\n", " * spectrum:\n", " * main:\n", " * composite:\n", " * F_1:\n", " * value: 0.0017\n", " * desc: Integral between -inf and +inf. Fix this to 1 to obtain a Normal distribution\n", " * min_value: 0.0\n", " * max_value: 1.0\n", " * unit: s-1 cm-2\n", " * is_normalization: false\n", " * mu_1:\n", " * value: 511.0\n", " * desc: Central value\n", " * min_value: null\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * sigma_1:\n", " * value: 1.27\n", " * desc: standard deviation\n", " * min_value: 1.0e-12\n", " * max_value: null\n", " * unit: keV\n", " * is_normalization: false\n", " * K_2:\n", " * value: 0.004499999999999998\n", " * desc: Normalization\n", " * min_value: 1.0e-30\n", " * max_value: 1000.0\n", " * unit: keV-1 s-1 cm-2\n", " * is_normalization: true\n", " * dat_2:\n", " * value: OPsSpectrum.dat\n", " * polarization: {}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ModelDisk" ] }, { "cell_type": "markdown", "id": "ed7ac3ec", "metadata": {}, "source": [ "Make some plots to look at these new extended sources:" ] }, { "cell_type": "code", "execution_count": 10, "id": "73d61cb7", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot spectra at 511 keV\n", "energy = np.linspace(500.,520.,10001)*u.keV\n", "fig, axs = plt.subplots()\n", "for label,m in zip(models,\n", " [ModelCentralPoint,ModelNarrowBulge,ModelBroadBulge,ModelDisk]):\n", " dnde = m.spectrum.main.composite(energy)\n", " axs.plot(energy, dnde,label=label)\n", "\n", "axs.legend()\n", "axs.set_ylabel(\"dN/dE [$\\mathrm{ph \\ cm^{-2} \\ s^{-1} \\ keV^{-1}}$]\", fontsize=14)\n", "axs.set_xlabel(\"Energy [keV]\", fontsize=14);\n", "plt.ylim(0,);\n", "#axs[0].set_yscale(\"log\")" ] }, { "cell_type": "markdown", "id": "db4cfb6e-e812-4f16-9c4c-95176bcc0dee", "metadata": {}, "source": [ "The orthopositronium spectral component appears as the low-energy tail of the 511 keV line." ] }, { "cell_type": "code", "execution_count": 11, "id": "8b588f46", "metadata": {}, "outputs": [], "source": [ "# Define healpix map matching the detector response:\n", "nside_model = 2**4\n", "scheme='ring'\n", "is_nested = (scheme == 'nested')\n", "coordsys='G'\n", "\n", "mBroadBulge = HealpixMap(nside = nside_model, scheme = scheme, dtype = float,coordsys=coordsys)\n", "mNarrowBulge = HealpixMap(nside = nside_model, scheme = scheme, dtype = float,coordsys=coordsys)\n", "mPointBulge = HealpixMap(nside = nside_model, scheme = scheme, dtype = float,coordsys=coordsys)\n", "mDisk = HealpixMap(nside = nside_model, scheme=scheme, dtype = float,coordsys=coordsys)\n", "\n", "coords = mDisk.pix2skycoord(range(mDisk.npix)) # common among all the galactic maps...\n", "\n", "pix_area = mBroadBulge.pixarea().value # common among all the galactic maps with the same pixelization\n", "\n", "# Fill skymap with values from extended source: \n", "mNarrowBulge[:] = ModelNarrowBulge.spatial_shape(coords.l.deg, coords.b.deg)\n", "mBroadBulge[:] = ModelBroadBulge.spatial_shape(coords.l.deg, coords.b.deg)\n", "mBulge = mBroadBulge + mNarrowBulge\n", "mDisk[:] = ModelDisk.spatial_shape(coords.l.deg, coords.b.deg)" ] }, { "cell_type": "code", "execution_count": 12, "id": "b80ae9d2", "metadata": {}, "outputs": [ { "data": { "image/png": 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lRDKKCQQC7Ny5kx07drBjxw52797Nnj17CASsJ5xomkaxpwSXcCMCGpEug8GGIKFOA2EUVhwzcbjtzFwyhbnnzWTyiePZs6aBLa/tYsebdfR3HrkxkcNlNEhlKu4SF9MX1TJ76TSmnDKR+o1NbHp5O1tW7STQf2CTco4kpoh3q7ujMdl0RzHdUezlas5JRE6nMymY06ZNY9q0aUyZMgWPx3OEs5dIji2kVEoko4Te3t6kPG7fvp0dO3ZQX1+P1UdYURSKPSU4hRsxqBJuNxisD6H3D38yzOFEURVmLJ7M/AtnMW1RLQ2bm9n4Ulxo+oKFTu+QGG1SmYrDY2fWkqnMPXcGtSeOp251Petf2MbW13YSDR/di8cnWjeNuGQmfmzlSs4W+zFjxiQlc+bMmcycOZPy8vIjnLlEMnqRUimRHIX09/ezdetWNm/ezLZt29i+fTttbW2WsW6XB5+jGHvIQaTDZGBfiHCXflgnx4w0FRNLOfGyE1hw0Wz6OwZZ88wmNr+yg4Guwne9DpfRLJWpuIudzD57GgsunkPFxFI2vLiV1U9tonVXR6FTOyhMzFiLpieK6YlgeqKUzyymvb3dMr6yspJZs2Yxc+bM5L/FxcVHOGuJZHQgpVIiKTCRSIRdu3axefNmtmzZwpYtW9i3b59lbJGnCI/qgwGNYEMEf0MYwuoRznhk0Owqc8+byUkfmktlbRkbXtjK6qc30bLD+uY+WjlWpDKVytoyTrzkBBYsn01vaz+rn9rI+he2FmSCz0hhagamJ4oRF82Ji2rYu3evZU/AmDFjmDVrFrNmzWL27NnMmjVL7iokkSClUiI54rS1tbFhwwY2bdrEli1b2LFjh2V3XJGnCK9WjOjX8NdHGNwXiu0UM8opqvRyypXzOfnyuXTs7eb9FevZ8urR3516qByLUplA1WLDFU65Yj5jZ1ez5ulNvPfoOrqbj64Z+IeKqRiY3iiGN4LpjTLmxHIaGxuz4lRVZfr06cydO5e5c+cyb948KisrC5CxRFJYpFRKJIcR0zTZu3cv69evT/60tLRkxTnsDoodpSiDdoKNUfx7I4jo6BfIVMafMIbTr1rI9DMms/mVHbzzyNpjrlXSimNZKlOpmFTKoo8sZP6Fs6hb3cA7D6+hbnVDodMacUzVwPRGMHxRTG+E0pleOjs7s+Kqq6uTkjl37lymTp0qlzeSHPNIqZRIRpBIJML27duTArlx40Z6e3vTYoQQlHrLcBleom0mfTuDR/0EmuEw9bRJLPnkqZSPL+HdR9fxwZMb8R+G7RCPVo4XqUzg9Do48dI5LPrIiQx2+3ntz++x7fVdR/WyT8MhOSHIF8YoijDtnAns3LkTw0h/r10uF/PmzWPhwoWceOKJzJw5U0qm5JhDSqVEMgx0XWfHjh2sXr2aDz74gA0bNhAMps9S1lSNElcpmt9JYF+UQH30mOjGzocQMOvsaSz55Km4fE5e/8v7rHtu8zHbxZ2P400qEyiqwtzzZ7DkE6dimvD6n99j40vbMPRj/5ZjKgamL4pRFMb0RXBPtGdtMCAlU3IsIqVSIjkIEt3ZH3zwAatXr2bt2rVZ28s57E5KnKWIHhv9O0NE2g/vNoVHE0LAnGUzOOczp2MaBq/9+T02vbz9uBCJXByvUplACJi1ZCpLPnkariInr/7hHdY9v+W4OidMzNiSRsURjOIwvqnOrB6MVMk89dRTmT59ulygXTLqkFIpkeyHjo4O3n333aRIZo6fstvslDjLULrt9G8PEekyj9mu7HxMP72Wcz+3GNWm8srv3mTra8dul+fBcLxLZSrTTpvEuZ9bjN1l4+XfvcWWVTuOy3MkUzK9Uxz09aVPbiouLubUU09N/lRUVBQoW4nkwJFSKZFkEI1G2bhxI2+//TbvvPMOu3btSvu7qmqUuspQeu0MbA8R7Tyye18fbUycP5bzbjiTokovr9z/Fhte3IZpyMtKAimV2cxeOo1zr19MJBTh5fveZOe7ewudUkFJSKZRHMEsCeMYr2TtijV58mROPfVUTjvtNBYsWIDD4ShQthJJbqRUSiTElvl59913efvtt/nggw8YHBzaBjAxscYR9DC4M0ywwThuurPzUTq2mAu/uITxJ4zh1QfeYfVTG9GjUpoykVJpjaIK5l84m3M+ezqd9d08//NXaavLnkV9PGIKE9MXwSgJM+OiiWzdujVtvUy73c78+fNZvHgxixcvZuzYsQXMViIZQkql5LhE13U2b97M66+/zttvv01dXV3a3512J0VqGdEGGNhx7C3vMxwcbjtLrj2NU66Yx7uPruP1P783qhe9PtxIqcyPZlc5419P4sxrTmH9C1t45f63R+2WnIcLUzMwSsIYJSHK5/mydv+pra1l8eLFnHnmmcyZMwdVHZ0bIkhGP1IqJccNoVCI999/n9dff50333yT7u7u5N+EEJR6ytD6XPRvDaF3Hd9d2lYIAQsvOYHzPreYvesbefHXr9NzjCxyfTiRUnlg+Mo9nPf5M5lxxmRWPfAO761YL4+XBYltJo3SEPM/Mp3169ej60OrKhQXF3P66aezePFiTj31VLxebwGzlRxvSKmUHNP09vby5ptv8vrrr/Pee++lLfdjt9kptVUQaRQMbAvL1sg8VE+t4ENfPQ/NrvHsvSvZuzZ7VxGJNVIqD46xs6q5+EtLsblsPPmTl2jcnL1ZgGQIUzUwSsMYZSE8U21pq1GoqsqJJ57I0qVLWbJkCWVlZQXMVHI8IKVScszR0dHBypUrefXVV1m/fn3aIsRupwdvpJjB7VEiLcixkfvB5tBY+ulFnHLFfFb94W3eeXjtcbUUzEggpfLgEQJOvGwu53/+TDb+cxsv3fcmIX/2VqaSdExMzKIIRlmIcYsr2LdvX/JvQgjmz5/P0qVLOfvss6mqqipgppJjFSmVkmOCzs5OVq1axcsvv8yGDRvSBrUXu0twDHro2xTC6FFkt/YBMvXUiVz2lfNo39PJ03e/Qm9r//6fJMlCSuWh4y1zc9HNS5m0YBzP/s8rbHl11/6fJEliOKMY5SGmXzyerVu3pv3thBNO4Oyzz2bp0qVyoo9kxJBSKRm1dHd3s2rVKl555RXWrl2bJpJlnnLULhd9m4Lgl4PWDwaH287yLy1l2um1PPs/K9m8ckehUxrVSKkcPtMW1XLp7cto2tbK03e/clxt8zlSmA4dvTzInCsms3HjxrTr5YwZMzjvvPM477zzZAumZFhIqZSMKvr7+1m5ciUvv/wya9asSevaLnGXobQ5GNgcQYSlSB4Kk08azxX/cSH1G5p45mevEOgPFTqlUY+UypHB7rJx4Y1LmLVkKk/+5CW2vbG70CmNWkybjlEeYt5V01i3bl3yOiqEYMGCBVxwwQUsXbqUoqKiAmcqGW1IqZQc9UQiEd555x2ef/553nzzTSKRoeVrStxlqJ1O+jeFEUEpkoeKzaFx/r+fydzzZ/L0T1+RrZMjiJTKkWXaaZO4/BsXsOu9vTx37ypCg3Ks5XAwNQOjIsicf5nM+vXrk49rmsaiRYu44IILWLx4MU6ns4BZSkYLUiolRyWmabJlyxZeeOEFXnrppbR9covdJdh7PPRuCCECUiSHS820Sj76nYvprO/myZ+8xECXv9ApHVNIqRx5nF4Hl9x2DpMWjOPhO5+lfkNzoVM6JjAdOnpFkNrzq9N2EnO5XJx99tlcdNFFnHTSSXJPcklOpFRKjipaWlp44YUXeOGFF9JmLjrtLryhEvrXR6BfiuRIceqV8znvhjP5529e5/3HNxQ6nWMSKZWHj3nnz+SS25fxxoMf8MZf3jsu9xE/XBjuKEZlgMpTi2hpGVrWqaamhuXLl3PxxRczZsyYAmYoORqRUikpOJFIhNdff50nn3yS999/P/m4pmqUqhUMbtGJNsvFyEcSp9fB5V8/n6rJ5fzj28/Ququj0Ckds0ipPLyUjS/hqjsvYbAnwGP//TyD3bKlfSQxiW0ZqVcFcU9XGRgYSP7t5JNP5pJLLuHss8+We5FLACmVkgKyb98+nnrqKZ577jl6enqSj5e5KzD2afh36AhddrOMNONmV/PR71zC3nWNPPOzV+QWi4cZKZWHH9WmcuGNZzFn2Qwe/e6z1K1uKHRKxySmYmKUB1nw8el88MEHyce9Xi/nn38+l1xyCTNnzkQI2QBwvCKlUnJECYVCrFy5kqeeeop169YlH3fZXbgHiulfH5UTbg4jJ156Ahd+cQnP//xV1j67udDpHBdIqTxyzFoylcu/fj6v/ek93vrb6kKnc0xjOnT0qgCVi3xp3ePTp0/nyiuv5Pzzz8flchUwQ0khkFIpOSLs3buXFStW8Pzzzye7T4QQlNorCG01iTTKRckPJ6qmcNHNS5mxeDJ/++aTNG9vL3RKxw1SKo8s5RNKueYHH6JpWxtP/vifRELRQqd0TGNiYhZHOOf2U1i1ahXhcGw2vsfjYfny5VxxxRXU1tYWNknJEUNKpeSwoes677zzDo888gjvvfde8nG3w4Oz18fA+qhcT/II4Cl1c/V3L8EwTP7x7WfkwtFHGCmVRx6Hx86/3HERRVU+/vqfT8rdoI4QpmagVwWoWVJMY2Nj8vETTzyRK6+8kiVLlqBpWgEzlBxupFRKRpz+/n6eeeYZHnvsMZqamoB4q6StguAW5KSbI0jNtEqu+eHlbFm1kxd+9ZqUmgIgpbIwCAFLP306p1w5j7/f8TT7NjQVOqXjBhMTsyTM6V+YxxtvvJFcXL28vJzLLruMK664goqKigJnKTkcSKmUjBh1dXU88sgjvPDCCwSDQQDsmh1voJTBDQZKSH5DPZJMPW0S/3LHRbz469dY++yWQqdz3KKoCne8dBP/fd4vpFQWgFlnT+VDXz2Pp+9+hc2vyEX9jzSGXUev9lM0305XVxcQW1j9/PPP5+qrr2batGkFzlAykkiplAwL0zR57733+Otf/5q2HJDPUQT1ThadcSrnXX9WATOUSCQSSaF5+fdv8spTrzLn6klpO/ecfPLJXH311SxatEguqn4MIKVSckhEo1FeeeUVHnroIXbu3AnEu7i1CvwbTYz22MQboQi5vMQRRAg49/rFzD1/Bg/9xxO07e4qdErHPbKl8uigdGwR1/zwcvaubeTZe1Zi6PLWdyQxTRPTiB1zwxthye0LWbVqFbquAzBx4kSuvvpqLrroIrnm5ShGSqXkoPD7/Tz99NP84x//SC4joakavlAZg2sMREhOvCkUiqpw5X9eQGVtOQ9+7XH6OwcLnZIEOabyaMJV5ORj37uMkD/M37/1NNGwXuiUjmtMh44+xo9zpmBwMHa9Ki4u5sMf/jAf/ehHKSoqKnCGkoNFSqXkgOju7uaRRx7hscceo78/NpPSYXPi7CoisMlERGW3RSHR7CpX3XkJdredh77xhFzQ/ChCSuXRhWZX+eh3LsHpc/DQ158g5A8XOqXjHlM10KsDVC72JhsrXC4XV1xxBVdffbWc1DOKkFIpyUtHRwcPPvggTzzxxND6Y3YvSr2L0C6BMGTXdqGxu2xc84PLCQcj/OO/ZOvL0YaUyqOPRKt+xcQy/vyVx/D3BgudkoTYrHGjIsTkD1WxY0dsUpXdbufiiy/mmmuuYezYsQXOULI/pFRKLGltbeXBBx/k6aefTspkkb2Y6DYbUblQ+VGDq8jJJ35yJV2NPTz2vRektByFSKk8OhECLr51GbUnjudPtz9Kf4ccLnK0YGJilIaZ9a/j2bhxIwCqqnL++efziU98gkmTJhU4Q0kupFRK0mhpaeHPf/4zzzzzDNFobCeKIlsp4Y0KRrsqZfIowl3s5Nr/+QgNG5t5+mevJAfBS44upFQe3Zx3w2JOWDaDB770MH3tA4VOR5KCiYlZFGHhddOSG2goisIFF1zApz71KcaPH1/gDCWZSKmUANDW1sYf/vAHnnnmmeRsvGJbKaH1CkanlMmjDZfPERPKTc08ffcrhU5HkgcplUc/y647g7nnzeCBmx+WE9yOUgxvhNO+OJs33ngDiLVcXnTRRVx77bWyW/woQkrlcU5PTw9//vOfWbFiRbKbu9hWRnCdgC65WPnRiNPr4FP3fITGLa08/dOXkJ/goxsplaOD825YzOyl03jgSw8z0OkvdDqSHBjeCCf/+wzefvttICaXl1xyCddeey3V1dUFzk4ipfI4ZXBwkL/97W/87W9/IxCI7QVdpJUQWqdCt5TJoxWn18G1P/sXWna28+SP/ymFchQgpXL0cMEXzmLG4in84ZaHGeiSYnk0Y/jCLLx+qFvcZrNx5ZVX8slPfpKSkpLCJnccI6XyOCMUCvHYY4/xl7/8hd7eXgB8tiLCGzTMDk12cx/F2F02rv3Zv9C+t4snfviiFMpRgpTK0cWFX1zCtNMm8X83/YNAf6jQ6Uj2g1EUZu6nalmzZg0AHo+Hj3/841x11VU4nc4CZ3f8IaXyOME0TV566SXuu+++5DpgHrsXY6sDvUmOmTzaUTWFa354OSF/mIe/86yclDOKkFI5+rjsK+dRPaWcP97+KJFgtNDpSPaDiYlZEqb2w5XJpYgqKir47Gc/y/Lly9E02ft2pJBSeRywfv16fvnLX7JlyxYAnDYXap2byB4pk6MBIeDDdyzHW+7mL199HD0i16EcTUipHH0IRXDVnZdgc2g89B9PyvdtlGBiYlQGqVjqTjaeTJo0iS984QucccYZcsvgI4CUymOYhoYG/vd//5dXX30ViG2n6GwrJrxNlYuWjyKW37yUiQvG8sDND8udckYhUipHJ5pd5d9+ciV97QOs+N7zcrjJKMIUJvoYP56FCn19fQCcdtpp3HTTTdTW1hY2uWMcubfeMYjf7+dXv/oV1157La+++ipCCIpC5ShvlhDZokmhHEWc9W+nMP2MWv7ylRVSKCWSI0g0rPPX/3iSqsnlXPCFJYVOR3IQCFOgNXkIPu/gmmuuwWaz8e677/KZz3yGe++9N7nVsGTkkVJ5DGGaJi+++CL/9m//xl//+lei0ShFohTb6jJC72mIiFroFCUHwQnLpnP61Sfypy8/xmBPoNDpSCTHHSF/mL98dQVzzpnOKVfMK3Q6koNE6AqPfvFlxFtFnHXWWei6zsMPP8zHP/5xHn/88eQGH5KRQ0rlMcKuXbv40pe+xF133UVnZycuzY1jWxmh1+yIQTlIebQxbnY1l331PP72zafoae4rdDoSyXHLQJefB7/+OOfdcCZTTp5Q6HQkh4AIarz3wx3YNpZQW1tLb28vP/3pT7nhhhvYtGlTodM7ppBSOcoZGBjgnnvu4brrrmPdunWoioq7owx9lRfabYVOT3IIFFf5+NgPLueZu1+hfmNzodORSI572uo6efSu5/jody6hYmJpodORHCJKj4OmP/vRdvnw+Xzs3LmTG2+8kZ/85CfJsZeS4SGlcpRimiYrV67kE5/4BI888giGYeDTS1HfKUXfakOYctzkaMTusnHNjy7ngyc2sOGf2wqdjkQiibPj7T2seuAdPv6jK3AXy/UPRysCgdrsJvSik4svvhjTNHnyySf5xCc+wXPPPYecuzw85OzvUUhrayv/8z//k9wD1a150Dc4oFO2TI52rr7rUkzD5OHvPCNnmx4jyNnfxxaX3r6Mioll/OnLj2Lo8kM62jGKwoy7vJg9e/YAsHDhQm6//XY5S/wQkS2Vowhd13nkkUe49tpreeONN1CEgruzlOgqjxTKY4DF15xM+YRSVvzgBSmUEslRynP3rkK1q5z7uTMLnYpkBFD67DT9xY9a58XhcLB27Vquu+46/vznP8uJPIeAlMpRQl1dHTfddBP33HMPgUAAj/ChflCKvsUuu7qPASafNJ4lnziVv3/rKbmDh0RyFKNHDf7xradZsHw2s8+eWuh0JCOAMAVaowfzdR+nn346kUiE++67j3//939n586dhU5vVCGl8ihH13Ueeughrr/+ejZt2oSm2nA1lhF5zYXil7O6jwWKKr185NsXs+IHL9BZ31PodCQSyX7o7xzk4e88w+Vfv4DyCXLizrGCCKms/n+70bYV4fP52L59O5/73Oe4//77iUTkOsEHgpTKo5j6+npuvvlmfv3rXxOJRPAaxShvFWPU2eT2iscIiqpw1Z2XsObpTWx7fXeh05FIJAfI3rWNvPrHd/nX712GzSm/4B8rCARqu4vQPx0sWbIEXdd54IEHuP7669m2TU6e3B9SKo9CDMPgkUce4bOf/SwbN25EUzSce0oJv+lAhOUC5scSy64/A103ePl3bxU6FYlEcpC89bfVdNZ3s/zmpYVORTLCiIjKOz/YhralmJKSEurq6vj3f/93/vznP6PreqHTO2qRUnmU0d7ezpe//GXuueceQqEQbsOH8k4JZoNdtk4eY0w+aTwnXzaXR+96DtOQM3MkktHIEz/6J9NPr2XOOdMKnYpkhBEI1E4n/udsLF26FF3Xue+++7jllltoamoqdHpHJVIqjyJee+01PvOZz/DBBx+gKhrOhlKib7oQIdk6eazhLnby4TuW8+RP/klf20Ch05FIJIdIoC/Io//9PJd9+TyKq3yFTkdyGBBRhbe+twVtexFut5v169fz2c9+lmeffVaua5mBlMqjgFAoxN133803v/lN+vr6cAsvyrvFmHtk6+SxyuVfv4Dtb9ax5dVdhU5FIpEMkz1rGnj/iQ38y7cuQijymn0sIhCobS6iq9zMmzcPv9/PD37wA77zne8wMCAbBhJIqSwwu3fv5oYbbmDFihUAuDqLib7uRgnKgd/HKidddgLlE0p5/uerCp2KRCIZIVbe/zaqTeXMa04udCqSw4gIqWz7dSs33HADqqryyiuvcP3117N169ZCp3ZUIKWyQJimyVNPPcUNN9xAXV0ddtWBbVMpxhanXHfyGKa4yscFX1jCiu8/TyQk16OUSI4VDN1gxfdf4Kx/O5XK2rJCpyM5jAgEf7j2cZQPihkzZgxNTU3ceOONPPLII8d9d7iUygIQCoX40Y9+xI9//GPC4TDuqA/eLELpthc6Nclh5kNfO48PnthA45bWQqcikUhGmI593bz6p3e54j8uRFFl48CxjjJgo/PRKEuWLCEajXLPPffwrW99i/7+/kKnVjCkVB5hEt9onnnmGQQCZ3MJ0bddiIh8K451TrxkDsXVRaz8v7cLnYpEIjlMvPW31WCanH71SYVORXIEELrCOz/YhrrLh6ZpvPrqq1x//fXs2LGj0KkVBGkyR5A333wzebLZFDvahmLMXQ45Gec4oKjSy4VfPJvHf/AC0bBc40wiOVYxDZMVP3iBsz95GhUT5W47xwMCgdbsRrxfRE1NDc3Nzdx444289NJLhU7tiCOl8ghgGAb3338/3/jGNxgYGMCpexBvF6H0OgqdmuQIcclty1j99EYaNrcUOhWJRHKY6djbzet/eY/Lv34+QrYZHDcoAza6VuiceuqphEIh7rzzTn79618fV4ulS6k8zASDQb7zne/wwAMPAODqKcZ42yN3xjmOmHnmFGqmV7LyftntLZEcL7z519U4vQ4WLJ9T6FQkRxARVVj3s71cc801ADz00EN87Wtfo6+vr8CZHRmkVB5G2trauOmmm1i5ciVCKNh3l2BslLO7jydsDo2LbzmH5+5dRSQoZ3tLJMcLhm7w1E9f5oIvnIXLJ3uljicEgke/+DLa1mIcDgfvvfceN9xwA3v27Cl0aocdKZWHic2bN/P5z3+e7du3YxM2tHXFiCZ5YTneWHLtabTVdbD1NbnIuURyvLFvfRM73t7DeTecWehUJAVA7XBivO2hpqYmOUl3zZo1hU7rsCKl8jCwcuVKvvSlL9HZ2YnDdCHeLUbpk8sFHW9UTCzltH9ZwLP/s7LQqUgkkgLx4q9fZ86y6YybU1PoVCQFQBmMjbM84YQTGBgY4Mtf/jLPPfdcodM6bEipHGEeeeQRvv3tbxMOh3EGvZhve+Xe3ccpy285h7f+tpru5uNjLI1EIslmsNvPK797i0tvWyYn7RyniKjCjt+2s2zZMqLRKN///ve5//77j8mF0qVUjhCmafK///u/3HPPPZimiaPLh/G+G6HLQ3w8MvW0SVROKuONB98vdCoSiaTAfPDkBjS7ytzzZxY6FUmBEIbgjbs28fGPfxyABx54gO9///tEo8fWWPtRZzy7d+/mxhtv5Oabb+ZrX/safr+fl156iS984QvccssttLbGdip56623uPHGG3n66acPe06Jbx4PPvggAPaGIszNLrn+5HGKUAQX3riEl377hlyTUiKRYOgmL/zqdc674Uw0u+y5Ol4RCB658SW0HT5UVeX555/njjvuIBQKFTq1EWPUSeXEiRP51a9+xc9//nNmz57Na6+9xt///nfuvfderr/+ev74xz8CMan8xS9+cdg3eQ8EAnzjG9/g+eefRyCw7SxC7JFCeTxz4iVz0KM6G144vOeeRCIZPex8Zw+d9d0s+uiJhU5FUmDUVjdivQ+73c6bb77JV77yFQYGBgqd1ogw6qRS07Tk78FgkOrqaiZPnozNZmPevHns3r0bgNNOO40vfvGLzJx5+LobBgcH+epXv8q7776LKlTUTcUoLa7DVp/k6MfusrHs+sW88MvXOAaHy0gkkmHwwi9f46xPnIK7RN4njnfUbgfm+x48Hg/r1q3jlltuobu7u9BpDZtRJ5UA7733Htdddx1r1qxBVVXcbnfyb4mV68866yx+/etfc9lllx2WHPr7+7n99ttZv349qtBQ1hahdsslg453zvjXk2ja0sKeNQ2FTkUikRxltO7qYOuruzj72tMKnYrkKEDpsxN+3UFJSQk7duzgpptuSg7hG62MSqk89dRT+f3vf88555zDunXr8Pv9yb+p6uEfr9LT08Ott97Kli1b0NBQVheh9Mslg453nF4Hp199Ii//7q1CpyKRSI5SVt7/NideMoeiSm+hU5EcBSiDNgb/qVJdXU19fT233norbW1thU7rkBl1UhkOh5O/ezweXC4Xe/bsIRKJsGHDBqZMmXJY6+/q6uKWW25hx44daNgQq4tQBm2HtU7J6OCMfz2R3e/to3VXR6FTkUgkRym9bf2sf2ErZ33i1EKnIjlKUIIa3U/qjB07lsbGRm655ZZRK5ajTirff/99br75Zm655RZWr17NpZdeylVXXcWXvvQlfve733Httdcetrp7e3u57bbbqKurw4Yd8UERil8KpQRcPgenfWQhK/9P7u8tkUjy89qf3mPBRbMorvIVOhXJUYIIq3Q8HmbMmDFJsWxvby90WgeNMI/F1TcPA/39/dx2222xbRexI973IYLa/p8oOS4493OLKR1bzCN3PlvoVCRHGYqq8F8rv8R3z7kXQzcKnY7kKOHiW89BVRWe+unLhU5FchRhOnTKL7fR3NzMuHHjuPfee6msrCx0WgfMqGupLAR+v5+vfe1rbN++HQ0bfCCFUjKEq8jJaf+ygFUPyFZKiURyYLz+p/eYd8FMiqtla6VkCBFS6XwiQk1NDY2Njdx+++309vYWOq0DRkrlfgiFQvzHf/wHmzZtQkVDrPGhBKRQSoY49cPz2fXuXjr2jv7lICQSyZGhv3OQ9S9s5YyrTyp0KpKjDBFS6XoySmVlJXv37k1u9DIakFKZB13XufPOO2NLFwkVZa2clCNJR7OrLPrIQt546INCpyKRSEYZb/1tNQsvmYPLJ5ejk6QjQio9zxkUFxezZcsW7rjjjrSJykcrUipzYJom99xzD6+//jqKUFDWFaEMSKGUpLNg+Rza6jpp2jq61xaTSCRHnq7GXna9t5dTrpxf6FQkRyFKQMO/SsXlcvH+++/zve99L7kW99GK7MfNwUMPPcSKFSsA0LYWoQ46QW7ZKklBKILFHzuJ53/xKooqv59JrEmcG/IckVjx1t9X87HvfYh3Hl5LNHx0C4PkyKMEHOgfgDY/wiuvvEJZWRm33HJLodPKiZz9bcGLL77IXXfdBcCll17KWWedVeCMJBKJRCKRHK+sX7+ehx56CIDbbruND3/4wwXOyBoplRmsW7eO2267jWg0iq3Fg1ZXVOiUJEcpn7z7w2z45zbWPrO50KlIjmIUVeGOl27iv8/7hVxSSGLJjDMns+yzZ/Cb6x4sdCqSo5hP3H8Zv/3tb1FVlR/96EecdtrRt92n7P5OobW1lW9961sxoex1I3Z6MJA3AUk2lbVl1Eyr5MGvPS5FQXJAGLohzxWJJdte383ym5cyfk4N+zY0FTodyVHKHz71OBfddRHPP/883/72t/n1r39NbW1todNKQw7yiRMKhfjmN79JT08PWtiB2ORFIAqdluQo5ZQr5rH2uc1EQtFCpyKRSEY5pmHywRMbOPXDcsKOJDcCwSv/tYb58+czODjI17/+dXp6egqdVhpSKonN9P7JT37C9u3bUU0NZZ0PYUihlFhjd9lYcNEc3l+xodCpSCSSY4Q1T29i5plT8JS6C52K5ChGmIKt9zUzduxYmpub+e///u+jaka4lErg73//Oy+88AICgbLRhwjJad6S3Mw7fyaNW1vorJeLnUskkpFhoMvPtjfrOPHSEwqdiuQoR0QV2p8K4nA4ePfdd/njH/9Y6JSSHPdSuXHjRn79618DoO7yovTaC5yR5Gjn5Mvn8f7jspVSIpGMLO8/vp6TPzQXITvKJPtB8dv48pe/DMADDzzAu+++W+CMYhzXUtnf3893v/tdDMNA63KhNLsKnZLkKKeytoySMUVsf7Ou0KlIJJJjjH3rGgGYOH9cgTORjAZ+esnv+dCHPoRpmtx11120thZ+E47jVipN0+THP/4xLS0tqFEbyjY5MUeyfxYsn8PGl7ajR46eMSwSieTYwDRh3fNbWLB8dqFTkYwSnv/GO8yYMYPe3l6++93vFnx85XErlU888QSrVq0aGkepH7eHQnKACEUw/8JZrHtOrkspkUgOD+ue28Kcc6Zjc8gV/yT7R5iCPX/pwu12s2HDBh58sLBrnR6XJrVnzx7uvfdeAJTdHrmnt+SAmHzSBML+MI1bCt/FIJFIjk26m3pp293BzLOmFjoVyShBhNTk1o33338/27ZtK1gux51URqNRfvCDHxCJRND6nKhNcvkGyYGx4KJZrHt+S6HTkEgkxzhrn5Nd4JKD46eX/p6lS5ei6zp33XUXwWCwIHkcd1L5j3/8gy1btqCYKspWOY5ScmCoNpWZZ01l4z8L9w1QIpEcH2xZtZPaheNweh2FTkUyShAI3vrRZsrLy9m3bx+/+c1vCpLHcSWVe/fu5Xe/+x0Ayg4PIizXo5QcGFNOmUB3Uy/dzX2FTkUikRzjBPqC7FvfxMyzphQ6FckoQkQV+lbFJuo8+uijbNq06YjncNxIpa7r/PCHPyQSiaD2OlDanIVOSTKKmLN0OptX7ih0GhKJ5Dhh88odzFk6rdBpSEYZSo+Diy66KLlTYDR6ZLcSPm6k8qmnnmLTpk0opoK6zSe7vSUHjKIqzFoylc0rdxY6FYlEcpyw9bVdTDllIg633JBDcnC8cudqiouL2b17N3/729+OaN3HhVT29vby29/+FgCxW3Z7Sw6OySeNp699QG7LKJFIjhiDPQEaNrcwY/HkQqciGWWIqMKNN94IwP/93//R2Nh4xOoeEans7+8v6BT2/fHb3/6Wvr4+1IANVe6aIzlIZpw5ha2v7Sp0GhKJ5Dhj62u7mHGmHFcpOXh+eunvOemkkwiHw/z85z8/YvUOWypXrVrFDTfcwLe+9S0Adu7cyVe/+tVhJzZSbN26lSeffBIAZYec7S05eKYvqmXnO3sKnYZEIjnO2PnOHqaeOhGhyPuW5OAQCDb8di+qqvLmm2/ywQcfHJF6hy2Vf/zjH7nvvvvw+XwATJs2jba2tmEnNhKYpsm9996LaZoo7U6UPjk2RXJwlI0vwVXkpGFzS6FTkUgkxxmd9T0EB0KMm11T6FQkoxAloHHllVcC8Mtf/vKIbOE4bKm02WxJoUwgxNHxreqNN95g48aNCFNBq/MWOh3JKGT66bXsem8vpmEWOhWJRHIcsvPtPUw/fVKh05CMUp786qt4vV527tzJc889d9jrG7ZUjhkzhvfeew+AwcFB7r//fqZNK/wyCLquJyfnKA1OOTlHckhMP72WHW/tKXQaEonkOGXH23uYtqi20GlIRikiqnDttdcCsfklgUDgsNY3bKm8/fbbeeGFF2hvb+djH/sYzc3NyT0oC8lLL71EXV0dwlBQGzyFTkcyCtHsKpMWjGPnu3sLnYpEIjlO2bOmgaopFbiL5drKkkPjd//2MGPGjKGrq4vHH3/8sNalDbcAn8/HN7/5zZHIZcSIRCL8/ve/B0DZ50box8XKSZIRZtzsGnpa+hjs9hc6FYlEcpwSCUVp2tLCxPnj5CoUkkNCmIJrr72WH/3oR/z1r3/lyiuvxOk8PF9SDlkq//SnP+X9+yc/+clDLXrYvPjiizQ3N6NEVdQmd8HykIxuJi0cx561R259L4lEIrFiz9pGaheOl1IpOWR+dvn/UfORGlpaWnjiiSe4+uqrD0s9h9yEF41GiUaj7N27l2eeeYbe3l56e3t55plnaG5uHskcDwrDMHjooYcAEPUuhHF0TBqSjD5qF45n79qGQqchkUiOc/aubWDSwnGFTkMyihGmSDb2Pfjgg4RCocNSzyFL5Wc+8xk+85nP0N7ezu9+9ztuuukmbrrpJn7729/S3t4+kjkeFG+99RZ79+6NjaVskQudSw4NVVMYf8IY9sqWSolEUmDqNzVTWVuG0+sodCqSUcw9V/6B6upqurq6ePbZZw9LHcMebNjZ2YnLNSRvTqeTlpbCremXaKVUGp1yLKXkkBkzs5r+jgH6OwcLnYpEIjnOiQSjNG9vZ+L8sYVORTKKEabgYx/7GAAPP/wwhmGMeB3DnqizaNEibr31Vs477zwgNut60aJFw07sUNi0aRPr169HmAK1WY6llBw640+ooX5j4YZxSCQSSSr1G5sYP6eG7W/WFToVySjm1x97EM/5Hvbt28d777034r427Ka8m2++mauuuor6+nr27dvHVVddxU033TQSuR00K1asAEC0OeS6lJJhMW5WNU1bWwudhkQikQDQtLWVsXJnHckwEbrCJZdcAsRaK0eaYbdUAixZsoQlS5aMRFGHTF9fH6+88gqAbKWUDJuxs6p5++G1hU5DIpFIAGjc0solty0rdBqSY4DHv/Yy4jTBO++8Q1NTE2PHjtywimFLZa6Fzu+5557hFn1QPPfcc4TDYcSghhgYEVeWHKc4vQ6Kq3207izchDOJRCJJpbupFyEEpWOK6G7uK3Q6klGMCGmcfPLJvP/++zz77LNcd911I1b2sO3r+uuvT/4eDod59dVX0ybuHAlM0+Tpp58GQG12IZDLCEkOnbEzq2ir6yQa1gudikQikSRJdIFLqZQMl7V/3gGz4Nlnn+XTn/40qjoyQwaHLZXz5s1L+//JJ598xLdp3L17N3V1dWAKlHa5lZVkeIyZWUXztrZCpyGRSCRpNG1rZezMKja9vL3QqUhGOUqnA6/XS1tbGx988AGnnXbayJQ7IqWksHPnTtrajuwN+cUXXwRA6bTLZYQkw6aytpy23Z2FTkMikUjSaKvrpLK2rNBpSI4BhCk4//zzAXj55ZdHrNxht1QuW7YMIWLdzYqiUF1dzY033jjsxA4UwzCSB0S2UkpGgsraMtY9v6XQaUgOBCHANIcfM5LInA6MozGno5z2ui4qa8sLnYbkGOHpu1bBPHjttdf4yle+gqYNfz7KsEtIzLguFFu3bqWlpQWhC5RuuduAZHgIEWupbN9TwJbKA73ZwsjclEeqvoPJaSTKEgcxdnp/r1HmVJicRuL8PBzHaX9xBRLdjn1dFFf5sDk1IsFoQXKQHDuIXhulpaV0d3ezevXqEekCH3Zf8e2335712Fe/+tXhFnvAvPXWWwCIbrvc51sybIqri9AjOgOd/oN/8oHcvIXIH5d6sx1OPQdb1nDrS4050LJyxY1UzJGuT+Z04PXles5oyWl/5ezvc36gMRlEwzrdzb1UTpJd4JLhIxCcffbZAKxatWpEyhy2VPb29qb9PxQKHdExlW+++SYASpdspZQMn8raskNrpTxYObOKy3zsUGNGsqxDicnFkc7hYGW4UDkdyffhaMjpSNZ3OM+VIy26cdr3yC5wycjxzPdiMvn2229jjkAL/CF3f//hD3/ggQcewDAMzj33XCC2tI/L5eKjH/3osBM7ENrb29mxYweYUiolI0PFpFI69nUf3JOGczNPfIjz3XwOJmY4+RQqp0TsSMUMN/eRzint9xwX7WP9GBSqvuHkNFLn+cHmsx869nZRMan0gGIlkv0h+uzY7Xba29vZu3cvtbW1wyrvkKXyU5/6FJ/61Kf4xS9+UbBtGd9//30AxICGiB6BWd+JC8bRNHBcCBAKGEdoTUVFRSgCM3qExvMoKkJVMSPhI1JdSU0R3U29eWOEpiE0DSMUyhFwkEK1H4SmIex2jEBgWOUcaIuI0DSEw4Hhzz0EQGgawuXCGBgYdn0HEitUFcXtRu/vH1Y5BxpzpOs7kDihqiheD3rvftYoHKmchIJa7D2y9fk8+Y/5gcSMaE4Cxesd/nl+oIIKKC5X3s9ed3MftQvH7b/OEURxOjGCwSNWn7DZj9g1H2LXsyN2TztQFPWI3NeFIViwcCHvvvsu77zzzrClctgmViihBFi3bh0ASo/dOkCI9J9cCBF7A/cXI/ZzuBLlHEBZQtMOLEbJsyCpEAjNhlDV/HGKirDZDyhG5Jv9pagI2wF8D1FUhMOx/7IcjlheeWIUu22/dSlOJ4rTuf+y3G6EI3eLttA0SsaV0dORW94SwoXNhrKfshSPB8WZe0WCmCR4UfJsFpCQmwMRDtXn229Zqs8XKy9vTh5Qcp/riRihaSheb/76iov2H1NSst8YxecDm4bq8+23rJGIUYqLwG5DLS7KX1ZZ6QHElOT8+8GUoxQXgabljUMosdc3EjHFRRB/D0eirHzHHKGgFnlj9eWLg/3HCAXV59tvOarPl/e8SxYXF8t8KF5v3s8VELseeDz5Y9xuUNW8cT0tfZSMK8lfnxAobvf+Y+LXznzXqVhiyn5jhMOR9/p6oDGx+kT+6zkx8RyRGE0DoeS/XzHUmDDcmKQj5Lsfp8YeSFn7i9mPAyUm6CQa6obDIUvlDTfcAMCyZcs499xzs/49EqxduxYApdfipElIYOInF6myKJTc3RcHGCMUgVD2I4vxleuFmkM+U2MUYX3SxIUyLwlRTK3Pqqx4ayCKyP3hShVKVc0d43AgbBpCiLxxit2GEAKhKtYf+oRQKkr+GKcjJkCKEsvfAqFpsbi4qFtd1BKPl9T46G0fzBuTT7ggdpyFyxWLyyGfiRgRz8lKBpNCqcTOh1zCmBZnt+Uuy+uJvSc2zfJmk4yJnwP7i0kcE6sbblIE4+dA3phE3vuJAXKK5VB9Sv6Y4qJYjN2WPybxucxx7UiLyyF6mWWpxfupb7/CGM8pV1xSBJUDi8kljImYxDE/kLh8MXFZzPmlIBGTONa5pDERt7+Y+HmOklsG1cR5pyp5hVHxemNxecRS8Xrj1zI1p8TFPp+x61Re0UtcWxTFWiyFoK8nTEm1LymOVjGKy5UUif3Wl8grhzQmH88TIxyO2DEQIqc0Zsbki4vVl1ssY40kYv8xKb/nlMuUe3suIUx9fDgxsWrEkCfkEsLUx4cTM1RpbncBfnP9QwBs2rQJwzDyl7UfDrn7+7777gMKt6RQW1sbTU1NYIIYyDhZrFoVhQIY6V0Q+2t5PMiyUmVSqCqmrqfFJOQuqywzpYnbIk4oApOUpnALoRSqGhutlYhJiGJWdQIz9ZxJFUqI/Wso6d0BVi2UqoqArBiRctIKITAzj51F66NQFSCluyNFKGP/V+Ibb2bEOB0Z5aiQ0W2S6DpO/TAlPvBmvPs6VTRLqr30tA7kjkkVSpsNBdK6wZNCmUpGXKpQpuakuFzJLu5UUYy9XpE7Jv73ZFn2eH2pcSkiiFCSYpnoZsuKAYTdHisnTwyQ9jqScakimMg9pRsxKyaR935iMl9rWpyaeH0iKTCJbtIsWYSkWOaNUZW0mJxxcYlLdBWPVExaXCqZcamyeKAxYkgGs7q4M495ZlymeOaKSQhlgoz3ZehFZlwn4tKYjMsUz1wxCaGM/1+oZHVfq5nnXfw9Nk0zLU7xeuPXptjxEEZ2WQmhHCpLTftcQYpQJh9QsmKScWkPxMTSGByMFx6TxZ62QTwlLlSbih7R08tKFcpkUiK7PiGyv+zGpTG1m1txOrNzz4hJyOJQ0QIcjuS1M+3xzN8z4rJEMy6Nadf0hFDmiclFVlmZ8icy7n1WMfHH9tddnryHpMYp+7m3W8QkH9tfV3jieUa6T2RUSJq7xGPEoIbT6WRgYIC9e/cyefLk/HXlS+OQnxnn+9//ftZjP/zhD4db7H7ZunUrAGJQi+2ik2xZyCOLCVM/kJiDLMuqdTLZEplLKImdVKn15Y2LN2PnaqFMtkTmEMpk3omTL1MoE6R9YPN0eSdaIi2EMrWs5IfyQLuzU4Uy+XhKi6WFUCZfnk1LfiO1Esqs+BShdPkcqJrKQLc/7W95WyjjLZGJm0mWUKbkD9ZCmZqL4nJlC2WyDGEdY9VCGy8/lwimimXOGOJiuZ8Y4t34yfpyiGBCLHPGMCSW+WJSW6myhDL19ccFxlLeEsTF8kBikvXliotL3EjFHGh9lkJ5oDEpYhn7v5K7tTQRZyWUVjGZQpkgtcUytfXRqiyfz1oorWJShTL5+pTs1kirvDNaLdOEMjUmpcUyUyiTVWa2WFpdN+JimYjLEs/UOI8nTRb1iM5gT4DiqvhrymyNzNH7lYxJCGWu+uKtkVlCaRETK87iGGS0WOZslUyJy9ktntkamev9y2iZzEXq/cHynEppsczb4nigLZMp9z9LT0htsdzPEDXL33PF5fKXTMcBBILZs2cDsHHjxtxlHwDDlspdu3ZlPbZ9++HflzRRhxhMkZQDaH1UHI68Y+GSMW73fstKNCnn6+5W3O4DGo+jFhXlFsFkdfvv8la9HtTS4vwxRV7UinJroRyqLN5lkL8xWykuQquutBZKYhcNpaQYbdzYvEIp1NiFylIok5UpsbIm5h+krpSVoE2pzSuUie7d1AtZUYWH/s7BtAm6alkpyvTJuXMClPIylJlT88aQIp25jlUs91LE3Bm53xdFoJSXwYKZuWOIyXVszFgOEQQQCkpZKcapJ+Q915WKMoxFc/PGiLi85BTBZO6l6GfOy5u7Ul5KdMn8vDHYtNhYTCuhTCYlEGUlRJYuyP/ForSY8LkL88Zgt8XqyyV4ibKKiwidl78s4fPtNwZNO7D6vF7CF56U+xgkYi44Me9xIjHWNJcsJkJdLiLnn7j/mHMXWgtlAlvsfMkpiwlcTqLnLMwf43Cgn70gd31xsTyQcZbCYcc4c0G2UCaID9Uwz5if93OcHC+9n65nYdMQp8zNe+0Qqoo4aU7aedDXPkhxZUr3eGIMZZ4x1QgRG9d5wsz9XqvUOTPyx8TFMu8Y9fiYTXX6lPzHSgi0KbW564LYcd/vGPyYWGoTxucvC9DGjc1/Th3AGEuIX/cqK/cbp1aU5/WEvF3hqSgqakn++zuAWlS039eXeV2ZO3cuAFu2DG83uUOWykceeYRrrrmGvXv38vGPfzz5c+WVVzJjxoxhJXUgJKRSGYiJirDbY98c80iQYrchnPnHxCl2W+zG73DkbA0DUJwO1NJiFFeeiRgOB8Ltzv+BcrlQPG6E25V/AoXLhVpZEZOEXDm5nIgiX96TU/G4EMVFCK8HJc/JqXg9qOPH7DeGspK8Nw/h9UB5KWaRB6Ui99pqwudDTJ6AUp37Ayp8Xswx5ZhantdX5MMcU4Fe6kGMrc4d5/Nizp6MGFeTfMxT4mKwZ2iSjlLkIzqhEtOWv77IpEoipS6YlFt2leIi9IXTYUruC54o8hGaVo1hz3M8fT6C06sJl7swpk3IHVdcROjU6eizJuWpz4t/Tg2mPc8NrcjL4JwaQmV2IifkKavYh3/xDCLza/Pk7mVgXg1RZ77X56V/QQ3BMhuhBbm7YITPy8DZ0wmePCV3jNdD34ljCJZpBE+yLkt4PfSdPJZQiUbg5Dz1edz0nzODwKlT88YkyzrFOi/hcdN36jhCJRr+U/Pk7nLRf84M/Kflqc/lou/U8YSK1ZxlCaeTvlPHEy7eT31OJwNnTyewaFr+mFMmEi5S8x4HgEhR7mMAIGw2/ItnEDwld33YbQROnETUoxI6KXdZKIKoRyW8ME+Xnc1O6NTphE/KU5+mEZ43iahHIzIvT32A7tKI5otRVfT5U9Hn5zmeqkJ0di26U8OYXZu7LEVgODTM2UOvb7AngLs4pbVQVWN/n5GvHAWmTcR0ajBtYu44wLRriMm5ry9A7Ho9JU85ioKYOA5sGmLC2Pz12TTUcWPyxqhja1BTrtfWMdWgqag1VXnj0FTUqor8ZVVWoFbmj1HKyxCaGvuin7cwNe+9FEAtLT6gBiFUNXfrfjIxEWu5zxfi9aY1eD30zScA2L17d/6y98MhS+VFF13E3XffzaJFi7j77ruTP3/605/4xje+MaykDoQdO3YAxLq/7fbYjxCxfy3EMimUEOtis2g1SwhlcgBwDrFUnA6EyxlrCXFZf1tLCCVKbHyJVbdoQiiTXeQ5xDLW2hmfZOF2WYplUihVBeF0oFicdAmhRIl9SxEeF0pRdleX4nYjSosxVQXhcVt+GJJCqSiYbidKaUn264sLJWqsPtPnthRL4fNBZSmmTcXweVAqrWK8mNVlsfo8Tkv5VIp8GDXlmFqsPqPYjRiTfXFRfF708TFZNIrdSbF0lziTUpkqlLrHgRiffTFLCKUZf33REqelWCrFRYRrKzHsCtESJ+bk7JikUGqCqNeOMTlbPhNCadgEpoBwmdNSLEVxEYHpVegOhXCJA326RVlFXvyzqjFsChGPRnR29s0hIZSGXWAqEC61FktR7GPwhGp0h0Ko1EZkjkWMz8vA3Bp0uyDqVgnPq7WM6V9Qg2ETICBUqlmKpfB56V9YE399GqEFFmXFhVK3C0xFoOcSZyHiMRAuthbLhCzqDkGoWLWUpWSMPZa77szVAyCSMeEiaxmMyeI4dIfIH3NKLAYBhiN/faaAiC9HWQ4H/aeMjx1Pn2IpjMLpZOCk8bH6gIhXsT4OdjsDJ0/EFBD1qJbSL2w2Bk+aiO5QiHqtYxJCqTti703UnUMsNY3ggomYIn5eWYmlqhCaH6/PpRJeaCHEcaFMnCdRt2otlqpKZM4kTAG6U7UWS1UlOmcShl3BcKrocy2OQVwoTS1Wn+GwFkshBMb0ibHrmV3FnBWLGewN4ilxxctSMaZPiF3PnBpMt/jypygwZXzyC7JpzyGWQkBcJk2bmlMsxaRxmDY1d4yiIMaPgUQDQB6xFOPHxOvLLZbq2BpMVcHUVNQx1o0Fak3VUINRHrFUE/eOPGKpVpTFGktUFTVHY4hSXoZIDGtSlJximbx/5hHLZI+EEDnFMm04SR6xTMpkHrFUPO7kpKnk0CV/zInq6uqGNVnnkKXS6/UyZswYvve971FTU5P88e1vOYgRYHBwkM7O2K4nqihOCiVgKZapQplAOB1pYpkmlMkHU8Y7Jh5KEcpkWRlimSaU8XKE05kmlmlCmXwwe3yc4nYjfCknU0I+U06WVKFM1ud2p4llmlDur77SYsz446YissQyVSgT5Zg+T5pYpgllan0Z3UpJodQSuZMllqlCmSjHKHKniWWaUKbUlymWSaGMx5mqSIplrKUymN1CqQiiJe40sUwTypT6MsUyIZSmTUkez0yxTBXKWAxESp1pYpkqlAmsxDIhlIZdSZYVLnOmiWWqUCZyCpfY08QyVSiT9VmIZVIoE/UJQag8XSyTQukYen2hUlu2WAqR9vqsxDIplPah3GMxQ2WlCmWCqEtktVbG4obeUyuxTJPFRE4ZYpkVA0Qd2dIlPG76Tkq5aVqIZVIoU+qzjEkIZUp9mcIonE76Tx66kVuJZapQxh4QWWKZKZQJdGfGZzkulMn3WUAkQxpThTIWI7LFMkUok7lbiaWmETxxUtq5lyWWqkJoQW3K6yNbLDOEMnlMM8UyLpRDuVuIZYpQJsgUy0yhTMZliKUQAmPmpKGeCxFvsZxVy2BPAE+JK00oh+rLEMsMoUwe00yxTAhlSl5W0pgQynwxwJBQJrAQSzF+TFpPl5VYJoQyGZNLLDN7IC3EUq2uzJjMli2WSaFMxmiWYiky6rMSS6WkOL0sC7HMGuKSSywzewQtxFL1erIcJlMsE0I5VF1MLFW1GLvdTiAQoLm5Obv+A2TYYyp37NjBF77wBZYvX865556b/DmcNDQ0xH6JqChm9gSRhIGDtVAm4+JiaSmUiRi7HcXpSHZ3ZwplMi4ulllCmSBFLC2FMpmTMzmAW62sQFjFpYhlllCm1hcXS0uhTMk70VqZKZQJUsUySyhTckqIpaVQJspyO5OtlVlCmcwdTK8bpbI8WyhT6kuIpaVQpsQlPoyZQpnMKS6W3vEV+AO6dZd3ilhaCmVqffHyM4Uy9XgmxFIU+QhPrUoK5VDMkFhaCWUyToARz1X4fGlCmVpWQiwzhTI1p3CJneisiZZCmVZWSUwsM4VyKCdBqCwmlplCmVpOqlgKn5f++RY3ihSxzBTK1NwTYmkllMmYYpXgwnh9OeOGxNJKFpM5FasHFpMiln0nWceFi2JxWUKZEeM/dYqlUGbGQFwoTxlH1JH53sTEMnDKlGyhTJY1JJa5hBLAsInk6xN2O4MnTch+n1PEMlMoh2JSxNJCKJNxqWKZIZRpZSXEMlMoU45V1KUSWTD03uRqyU6KZYZQpr6+pFhaCGXyWGWIpeW1iiGxzBLKZO4xsRy0u/CUujGmTrAcnpMplrmG8CTF0kIoU5+bkMZMoUyLmRT/4ppopbQiRSwzhXKorJhYCiGyhDIZkyGWalWOYVMpYqlWVeSYzDYklllCmYzRYt3h8XtXrlbJVLHMEspkskNimXPMdFwsE3KZdzJb/G9ZQpkgQyxzTaxShML48bH3MOlYh4Awh7nZ4xe+8AVuu+02fvSjH/Hzn/+cJ554AsMw+PjHPz6cYvPy0ksvceedd6IMOnHusm6eT7ysnAOu44j4zDozz24lwu0GVcEcGNx/ckLJP8HAF+/G7su9Q4NZ5MW0aSg9+9k1IkGe12gUezCcNrT2vpwxepkXw6Fha+nNEsoshMg7JjVa7iHis+Gqz10fpgmGGTumOS6uAJFyN6FSG97duY9DqMpNsFSjaFeeHS9ME6GbmFr++i795AnsDQTY8NienDHBSjsDNSrlm/LsLpGoTxVZQplKoNJO30SFyrU5duYBApU2+moVqlbnXi5DmKBEDAxVWN7QkmVVaPTMgJq3cy9NEahQ6Z4FY97Kv3yFMEAYZu5uZSBQrtA1z2Tsq7kvMcIANWxgaMJSmpNllSl0naQz9uXc9QVLBV2nRhjzYp6ZmIaJGjZjXeK5uoyBULGge3GImmdzTwwIFQu6zwxR80yeyQMm2KLww1tP56u/fgfDsD4WoSJBz9lBqp/KPY477BN0L80fgwlaKNZ1lSmUqUTcgs5lIcY8lTv3iFvQcU6YsU/ln7CgBk2EaRJ15rkuOAWtS3XGP5s7RpgmStjMex4A6HZB81KY8Fzu80p3CJrPEkx4Mc95bIIaMhBm/vPY1ARNZ2mMfyn3Z9DUFJrPsDF+Zf5dZ5SQjjDM5BfBXPW1nOZk7Ou5d9WZd2I105bUsOJna/LWJ0I6wjDyjgs3FUHHQi9V7/bmjlEFXfOKKF+dfwtbEdFBN7JbKdOCBL1zSihe35m3LPT97yYjdIPBWVV4trbljQtOqcC5M38MUd1a8DKITKjAtqc1b4w+rgKlfj/1HcDrA6CqHFo78seUl0LbfmIME9M0887xOPELVbzxxhvcfvvtXHnllQeWXwbDbqmMRqPMmDGDaDSK2+3mYx/7GG+++eZwi81LU1MTAELPPUlG8XoQ1RUxacyB8Hoxizx5PwDC68Eo9WIUxbuhc8UV+TAm1EBJnu7/Ii96hY9omQez1HrZDrPER6TKR7TchVGWuyyjxEdoejV6dUnumFIfgXE+QhVOotXW4zT0ch/+CR4C1U7C40pzlqVX+OhbUEVoYu6YaIWXvsku/FU2/JNyDziOVHnpOL2Sgem5cw9Xeuia6SCa58YfrHbTNcvO4FiF3hm535tgtZvGc0vompv7eAYrnahVNno8Op0nWM+gDFQ7aDtRY3ACdCzIPcvSP8bB3kvdtJ6We+KVv9pO6yIYnKjTdoq1JASqbLQuNvFPitJ6Wu6b/2C1jV1XaTQuzR3jr9RoWxohWhuk+azc57thA2XyIE1n5740+CtVGj8WYd9F+QRWYfCiAUomd9N4fu6bv79Koe0zAeovzRNToWBc2o29NPcNO1AmUD7UybTJrbRcmvvmH6hQCHyuh+aP5o4JlgqcH25lzqRm2i+3rjNYInB9uJW5k5rouDL3zT9YKohen/9iHyoWuP6llXkTmuj8sHVZoSKB4yOtnDChOWcMxMQzcH0PLR/LfawiHoHxL51MH9dG+4dzf5k2FZg0roOWf8n9pSfiVmj/tJ/6a3Kv2Rd1CXquGKRibC+NV+SOi7gUGv4tSv3lucdz6Q6F5ssiKKW53z/dIWhcbiCqg+y7NM8Xbodg90dV6q7I/bkxbAr7LlSJlEfZd5F1nGFTaDhXI1yus++C3MJvqIK9l7jZe3Hua5WpCRrPdhIuMWk4x/r6YSqChikKLpdK09l5ylIETcuKaVqW+5ptKoK203xEfIKWxSU54wAiXkH7abnLQgg6Tqug8/Q8k2SEoHt+KRG3Qs+J+SfB9C2oon9+/rIG5lYTdSsMnJB7UqZ/RiVRl4p/Vu4YgNCMGkLT88dEJlViOFQiU3JPGIpOqMSwq+iT8pdlTKjBHJ8/xqypjLUm1+xnhrlNgzyTXAGoKkdU5z/mY8bEWpgL2v2txafd19TU8PLLL7Nhw4bkeMfDRaJ8RbjAYva18Lgxve7kJBIrsRReL6YvHuOKd1lnxXgwiuNb1ikKhs9lKZbC50Uv9YCmYBS5wKqpusiLXu6NtQQKMC1a+8wSH5EKb6yFSwiipdZiaZT4CFd70O0K4VInekW2oBolXgJjPLGyFGHZhaCX+/CPc2OoscHwwQo7kTEl2XEVPgYmuNDtgkCFjdD4bGGMVnjpq3ViaLGyAhWapVhGKj30THGiO8BfoTI4OTv3cIWH7ul2DJsgWKrQPy37GASr3XTPtKPbwVDBX20tlsEqF51zbOhO8NcIumdlnwvBSicd8zTsdpWgaVh2+waqHbQvUDEcJqYK/jGmpVj6a+y0n6QQdZv4x5i0nZh9fvqr7bSdAobTBBV0i/tQoMpG6xkmpsMAxSQwzlos/VU22s7UEZ4o4XERms/IblXyV2q0nx1Bc0VRFBN9vLVY+qtUupaEUFUDdbzfUiz9FSq95wbweIK4xw/QuMwi9wqFwQsH8LmDaKpB6bheGs/LlsZAuUJ4eS9lXj/V47tpvDBbJgLlCubF3ZR5/FSX9NO0PFtKAmUC9bJOyt2DqMJg8tgOWi7Jlo5gmcD+oXbG+PqYNqaN1suyZSlYKnBd0Uq1ux+7EsXryZazYInAfWUrNZ4+7EqUWWPa6LgiW84SceO8sRagzsuzZTBUHBPYGk8fmqIzs6bNUhpNBard/Wgid0zYK1A+3BF7fdUddFjERDwC48OdVHoGEcJkclWnpVhG3ILw5T0owmRCZbelWEbcCgNX9FHm9VNT0UvzldnHPOoSdH/IT5EniBAm5RX9lmIZdQraPxTE4wniKx+k/kPZ54LuUGi+NIzTE8Zmj7LvsqyQpFBqnggCUEpDlmJp2AX1F4LwRDFLIuy7OPtzY9gUGs5XMF2xFiW9OLdY6h4j1q1eZFiKpaEKGpfZibpNol6DhvOyrx2mJmhc4kR3mbGyvCaNS63FMqAaOFSVqBualmRf90xF0HK6B90JURc0n5l9nU0IZdQZ78Z3QesZ2ddsUxV0nFQU7+oXtJ9qIZZC0LmwBN0BUSd0nmwxuSUulInhHVGHyCmWfXPLY5P6HMJaLIVgcFZFsizdIXKKZWKoj2FTCMy0jglNqUS3K+h2hdA065jIpMq0snKJZXK8vqZgTMyR09hK0JTYZKccYmnWVCaHI5g2NbdYVsS74jU1t1hWlCU9hirriUeirIQnfv8uAC0tLdblHADDlspPf/rTDAwMcOONN/L444/z85//nFtvvXW4xealq6sLAGHY05pyhccNVeUxoUxZ3DNTLFOFEoiJpdeVJpZpQpnAQiyFz4te5k0rK0ssU4Uyju5zpLVWpgpl8jELsUwIZXJShyqyxNIo8RIYm15WuNiW1lqZFMqUsXxWYpkQytRJJJlimSqUqWWZGeMEE0JpxOdHmWq2WIYrPHTPsCe7wEwVBqvUNLFMFcrka7YQy4RQGvahnDLFMiGUugOcqkJQ1wmWkdZamSqUyddnIZYJodTjcaaaLZZJoXQNlRUqM9JaK9OEMoGFWCaF0hW7SQvVyBLLVKFMFmUhlv4qlc5zQjjdMTGwEkt/hUrveQHc7phgqIqRJZapQplAUw1Kx6eLZaBcIXxxL8WuWJymGFliGShXMC6JCSWATdWZMK4zTSxThTKBTdGZPC5dLBNCWeWJDZOwqzrTx6aLZapQJhhX3EtbSmtlqlAmsCtRZo1tTRNLq7jZY1rTWjUTQjkmo6xMaQwVCRxXDHWlWYllQihrvP3J45kplqlCmcBKLCNuQejKHiq8sTgrsUwIZaknvmsTUFOZLpYJoSz2DpVtJZZJoYyfVwLwVaSLZapQJspxlgfSxDJVKJP1kS2WqUIZCzKzxDIhlIY7vYsyUywNm0LjshQhtRDLpFDGP/Oxca3pYpkUSreZVlbEly6WpiJoOstFKKrjUJX4LPt0sUwVymRO7nSxTBXK5GMCom6RJpYJoYw6hyZf6a4MsUwRygRRl7VYZo4XthLLhFCmxqSJZYZQJsu2EEv/jHTJ0u3ZYpkQyqFyssUyVSgTWIlldEJlVkymWCaEMoGVWKYKZWpcllhWlKX3tFqJZUIoEyTEMlMuFQURv6l2d+cf5pCPYUvlokWL8Hq9TJo0iXvuuYf77rvvsLdUJqVSt8VaKl3OtNZJq4ktCbHMEsoEKWJpKZSpcfFWvyyhTIlJiqWFUMaeDNFiF2aJz1IoE6SKpVnsTRPKZEyKWFoJJcQnKpQ5iFYXo5d5s4RyKG5ILDOFMjUmIZZWQpkgWKImWyszhXIo9yGxDFd46JluzxpTlSqWVkKZwFCHLlqZQpmae0IsU4USwKGqhKJGLKcaQecJLgJVDjrmpwtlWu5xscwUyqGYIbH0V2ULJQCaiX9MTCwDVTZaT88QygQJsTzVniWUCRJi2XK6ZimUyaIUM3mT81emC2WCpFguUbKEMhmTEMtzBIEKhYEL0oUy+RJTxDJQrhBa3pcUymRMQiwvMLKEMkFSLC+KWgplMi5FLIOl6UKZIFUsg6UCx+VtaUIJQ8KYEEtTFWmimBnXcUUg1jWeIZSx16czJy6WVkKZWlZCxEJFAvuH27LiNKEzvbqdjiv9WUKZejwTYmkllAmEMJlU1UXblcEsoUygCJPxFT20fDicJZTJchgSy6gzWyhT60uIZdQpaL8slBTK1LISYqk7FJoviSSFMrWcNLEUpAllallKaYh9lyjZQpkMiovlci2nUCbQi6PUX2hPCqXuyfispoiloQoazxkSygSpYmkplCllJcTSVATNZ7rQnRDUDZxxmUgVyyyhTM0pQyyjFqPHUsUyUyhTY5JiaSGUyfJTxTLeSmlF1CHoWRgTy0yhTI3pn18VE8qZ2UKZQHcIBufEBNQ/I1sEIV0sM4VyqJwhsbQSygSpYhmdkD0JNBGTEEtzTEXOyVBpYplj7H+aWGYKZfK5KWKZKZQJ4q2WIt7KKcpKYv8asS9Ivb25x9fuj2FP1LHiox/9KA8//PBIF5vkk5/8JHv37sXZMQs1XIxp02KTY/T9rK1k0zBVgdBzv2TTpmJqCiKap6z4Gk6mTc07acWwqxg2BSWce0Cu4UjE7H9dKFMVlvI2VJ+CbheooTwD2J1ivzEQ+3BGHQItmDsu6hToDtByD8tKmdAhsoQyrSyXQHeBlmculO6KXajyxSg6iGisSzlTKNPrM4l6TWx9Q+/fj86Yzy827KB+IPaCdKdJtEjH1pt/p4Ooy8T0RVF6ck9oMNwGWlEYvTv3mCvTpeMpCTDYkWcXDkBxRykvHaCjI/cYUbsrwriyXva1Wc9SBDAMgRHQEA49SyhT8TjDzC5vYV1r7sXdi11B5pc18W5b/kWVdUMQitgocec+aUqcARaX7ealtpk5Y0odfpaW7eDp1rl56ytz+DmnbBtPtc3PXZ/dz/mlm1nRdmLOmLCh0TboxabqliKYoNgW5JKy9TzUelryMQXBbfwbP+MvGJiWMVb1tQz4UBUjb31uLcJl5et4sGVRnpgwl5Sv58Gm3DGJuOWVm/hb4yk5YxxqlAurNvNw/Uk5Y0yge8CN15V7LCbEpP7M6t08t3d2zhhN1VlUs4+Ve3MvIm6agmC/A3RhKZUJhGIwo6adzXtzL7ItFJMJ1d3s3bOf8WmKSVl1H9378oxXFCauKj+hfXkWqhZAZQi1Iff8AIgd02hFBEdj7KJWYrfxvdPn8cVXV6eUZRIuN3A15rlemaAFQQnHrqX5CJeauFryT1wJF4OrLf+9RAuCEjFziiAQW73AJ3B15L8Phn0CV+f+75URj4KzK/9EmIhXwdGdf/9uNWzAARhS1K1i78m/97ju0rD15Y8RER2iRk6pTGA4NdT+/J8vw66hDOafOAZg2m0o/licrg0SrNpIWVkZK1as2O9zrdj/PkSHwGHw1DQCiZnaporpsGE64rvqRHSIWJ8kpjMeFzUQunWM4dQwnDZMAWpIj5VnFee2o7s0lLCRUxh1p0bEGzu8qiJQg9l16i6NiE/FFAJVFWgB67KiLpWIT0UNG6gB6w+U7lIIFamYAmyqiebPjou6FULFsYWQNVVgs4iBWNdWqESghk3IcU5G3IJQuYgvaQP2Puv3POwThMoEagjsvdYxUY8gUGnG1qjUBHaLL0lRDwSqjFiMXWDvtr5AhYsgWB1F9Ss4uqw/mBGvSXRsGBSTsN2GvSN2EXaoKsH4F5Oox0AZ78epmgTtDmzt1kYc9Rr4xvcRCmtEckil4dWZMKkDm6rT6vThb7a4yXgjzKttwq5EaXCW0NpgfbPSvBHOmLwblxphj7OcHQ3Z441c3hDLa7fgUiOUOwdZs896hYTiIj8fmreRllARr+2z3iGl1OvnkxPfwacGGePssxSACu8gn5+4iiIlyARnF4/sW2hZVoV7kC9OeJn6cDl/3mctOFXufr42/jmKlRBTHG38tn5JVky1q59vjnuGYkVnkr2dX9VbDOwEqlz9fHvsM5QpClPtrdzTcEFWTKVjgDvHPkeZYmeGvZUfNyy3LGucu4f/nfIPWnU7P2i4xDKm3DHI98b8k1LFxdTxT/PfDZfmjZk+4Sm+W28xMBCodvbzq8kP06HbcsYU24PcNfZZyhQ70yc+wZ37Ls+KKbIFuXPcU7FjUNvGXXs+ZFlWkT3IHeOfplKJMnVyK9+vy87dYwvznxOepkwNMmVqGz/eZX2svLYw/7nwGXp0D/fsPNcyxqlFubF2JWXqABNndHLf9rOyYuyazqenvEW5OsD4Gd38efuplmXZbFE+dvIHDOgOVmxdYBmjqAYXT9tMsRZgjKuPl7Zmf2ERqskZU+oosQWocA3wwZbJlmWhmpwwtRGvLUSnO8CurdmLepuKybjJHXhsYbpdITq35dhNTEB56QCDrjCRHTkmbwJikh+XTSfs0tF2ugjpBs7U5WqESWhCGMVm4HeouHdbf6M2FeibHkUYAs+e3PIZGGNg2GKz4r37rK+1gRoz1jvkAG99zqLonyjAFHgbcniBgECliPVI2RU8TbmlMeoWDNpUPC25hTFYpsTysql4Wq3jgqUqpgpGpYarPbdYBirtYJq42nN/WQkXa7GewHIHjk5r0YsU2TEVMMocOLryTHwrdcZWjOjJLYO6x44pwCx2ovXmjjNtsR5TpS/PZDxXbCtjw+dC6Q8kWyr7+w9w5RkLht39bUXqOMdf/vKX3HTTTXz3u98lEonwhz/8gZtvvpmtW7cecvnBYPxA2hxJoYR4y6HFbjoJoTQFycGxmaQKJYDuUHPGRd22+JIkquWWekmhFICINaXrzvS8UoUy9pzYbg+ZRF0q4SI1tkabQ0F3WTTVJ4RSidUXcQmi7vS4hFAaany9N1dMHjNJCKWpxlorI97sC0pSKOP1Rd0QLrKI8whC5WBq8Zhii26NuFCaSvzbuNckXJwZExNKUzMxFZOoxyRcmn2BinogWBMFzUT36YTKsi9OCaEUmoFQTPBFCFfELjyaEOiGmRRKm01HUQycRSEildkXlYRQOmxRfO4Qoib7A54QSpcWQRMG1UX9uMdkL38kFBO3FkZTDMb7eqgenz2mJSGURVoImzCo9XUyfXz6shUJoSzSgtiEzgxvGydOzL7i+7wB/qV2HVW2PmZ7mlkycVdWTEIoy7QBbCLKfHc9yyel7wubEMpyNRazwLWPj0xcm1VWhXuQWye8SI3ax0LnPj4x8Z2smIRQVqoB7MJggaORz014Lfs4KDqVqoFdCE5ytHHjhFeyy4oLZbWqYRMKlWp283ZCKKtVFzahMt+u87Xxz2XHOQe4a8w/Ga95mW9X+Y/xz2TFJGSxQvWgCoV5dht3jH86LabM7k+LOcFm578mPJVVVqk9wPfGvsB4zcsJds0yJiGUidxn2+DbE5/IilOEkTwGc2xBvlX7ZFZMQihrVB1VCGrU7PMzIZSVagAVk1n2dr42NftYeWxhbpsUe5+n21u4ZdrLWTEJoazU+lCFwXR7CzfMeD0tJiGUlVofijCY4mjjEzPeyypL03SunrKGCls/tc4Orpy1LvsYxIWyVPOjYDLW2cN5s7alxaQKJUCNs5+TZ9dllZUqlAA+W/ZnPlUoAUqdAcpnWgwJU8BTG/sG7XGGsU3PbpFOCKXNHkUIE7sjQnRagIhpoAgRW70uRSgBFKeOf0p2i5gpIDAudn007QaDtdbClRBKAMNhMDDRYpJdXCgh1qgwkGNHx0CVwNTAtMHAeKv1GIeEMlHW4FhrLQlUKEMxNdZCnBDKZFx1dlxCKCHWiBGotG4MiMlirIcwUGndqJAQykRZofLsnqiEUEKsrFCZdW9V1GuLT6oVREqsW64TQgmxIW3RYus4w21PxhhF1k3SCaEEkmIp4koYiUQOeVedQ5bK22+/PedPoj9++/btdHV18Ytf/ILa2lpWrlxJe3s7P/7xj3nppZcOteqkVJq27DcnUyzThJLYByuxvVSCTKFMkCmWCaEkESfIEss0oWQoLvX/mUI59Nx0sUwIZWp9mWKZJpQp9aWKZapQJo+LhVimCuVQTLpYpgllSn2ZYpkUSjUjJkUsU4UymRcpzyFdKIdyzxbLpFCqZrK+TLFMFcpk6iliKQSEXXpSKBNYiWWqUEJsfFdpkT9NLFOFMoGlWHojnDBxaAkHK7FMFcoENmGklZ0qlEMx2WKZEMrS+DgCm9CzxDJVKIfKShfLVKFMjckUy4RQlqtD9WWKZapQJrASy2pXP18f83xKTLZYpgplggmqwS3jX0z+P1Uoh3LPFsuEUFapnpSYdLFMFcoEVmJ515iXsmIyxTIhlKn1ZYplqlCm5p4plkW2IN8e+0xKTLZYpgplgjJF5z8nD+WdKpTJ3C3EMiGUlWp/MiZTLFOFcug4pItlqlAmsBLLhFCWpoyHyRTLVKFMPpZDLBNCmSBLLDOEEmJd+FNnNSX/nymUCbLEMi6UTttQK1mmWKYKZYKkWE6JT5ASpAllsvgMsUwVyuRjFmKZKpQJrMTSyHA1K7FMCGWyvkyxzBDK1LIyxTJQoaTFWYllqlCmxaWIZapQJmMsxDIhlMncLcQyVShTy8oUSzPDsqzEMiGUqTGZYpkqlENlZ4ul4U6PsxLLNKFMIASGZ2joVSSSu3U2H4c8pnLt2rV5/75w4UIee+wxXC4Xy5cvZ9u2bTzzzDMUFxezevVqbrzxRubMmXMoVXPOOedgGAbOwcUIM8duORE9tpyOI1sWIbZgdCLGSihTUUOxuDShTMWMxyiCqEfLOomGYoz4wOtsoRzKy0SJj3dME8qMshILHGcJZUYc8e7pzA9bsj5jaExkqlBmx5hgQKjMOiaZlx+ETrpQWsQoUbKEMlkfoA2IWEyGUKbnJdAGBUpYpAtlRn1qv4oSFkTGZF98k2GG4HeTFvP11rfxq9bdBYahEOxzIPwqvglDQpmKbgh6+93oAzbGTezMurkkiJoKrX0+/P0O5kxqTrtRJWMMhYb+Ejp7vFlCmSBiKuzur6Cpp4gLarel3TzT41S2D1Sxs6siTSgzYzYNjGNzd3WWUKbHafTrTkpUf9qNPzNmXWAiqzqmpwllZn1rgxN5oWNOllCmEjYVVocm8HTHfL4x7tk0ARqKMVkdquLhjlOyhHKoPoPVYR8Ptp+RJZTpcTprwhp/7DgzTSgzY9aHde5rX5ollKnopkFrNMTefX9j0ZTrUER27rppsCEc4Zdt56YJZWZ9m8JR7mk9P0soM+M2RgT3Nl/AneOeynkcNkec3NN0QZZQDuVksjlSzD0NF/D1Cc9Qo1qfVzqCreFKfrnv3DShzIzZEa7hN3vOzhLK9DoVWqLF9BuunDGGqbA7VMVfd5+UJZSp7AlW8MSOeVlCmVYWgqZgCS/vmJHWSplJS9DHB9trmT2liSK7dXdje8DL7h01jJ3cgTfHZ95A0Bt00rmjPEsoUxkM2gnvKMoSylQUU+G+6vO4dufrGLY8Y/aDKq46e5ZQpiLCCp49qqVQptUZinWFp7ZSZsVEYl3hmUKZFhMGT5NpKZSZZXmaDILlCkausiLgadEthTItLgpqKMc9KRlj4mqPZgllKkKPdYVbCWVmWY7OUForpVVZjq5QllBmxth6gpZCmRZnmGi9wSyhzIxR+gLWQhnHxCDoXQXAP/7xD6qr86+jacUhj6lcuHDhfmMGBgaoqIjN6vJ4PPT393Pbbbfx2c9+9lCrBYa614UiUHIcQRFfm9FQhaWXAQhDQaix5uZ8w5GFKkBVWHLWDKZPr2bzlkbefa8uK0aoAqHlLktRY2MQharkqU+gqDH5VOIzuM86aSqzJlezaVczb62ti9engIjXm7uo2AdNy9MkrYJQ45Kdkfs5cyZzwoRq1u9r4a3VdbHNdPJMFIrlE6tLyXVmCVDi9Sk5PuDnTp3CgopqNuxp4fm+XVibNaDE8lF0Ed8Ny7p7RdEEqi7AZuYtq6qsnC9Wnsn7Xft4tXVHVoiqmES12DqVLptuWZaigEMzCCngs0Vy1mcXJk5NJ6zAsspZTPFOYkd/HWt7NqbFuDWdPtWkWI1kf+UF7IBPi2BToEwNWsbE4kyK1DA2BUrVAJgKkz1nUOWaQUtgK3sH38GGSakWxCagTPXnLMuGQY3Wj08J5rxK2zApVQPYFZMyJYiZElfiOh+PfR4D4bWURTZgFyYVSjgtJr0sqFQGsQuDagXLuFiMHzsmVYoDq6/KTsdFzPXM58RIlErldXJsboOKSrUSQENQoRRZxqmoVCgD2IGyHDEAAh9ja/5BWfkYjB4fkC1dApUqJYQKeeurUsLYMKlUvAeQu8lY18Wo9oXo4fVEQ/9MxmioVCshNMh5PBWIlwPVSijne6MA1eoAqoAKxY9pqhS7zsVrX8BgeAM9gX+iADVqP5ogNgwhR1kqUKMO4BR6znNPAaq1fhRE8jxOMMmziBrXLNoC2xmMrkET+T8TKlBuC6AiKNVCOePKbEFUBCW2EFZ37IUlc5kybgr/DIfYa2sm12deAXz2CD0I3DmuHwBuexRdEdjtuWOEMCktLeXLJ5/Fus5mXmrMvl4BKHYTVQhi3y1yXPtsJqoiEDZQ890J7aAIwbLpk1kwtoYNLa28vGt3el72+MTifLsi2WPzavPeSxJxigBbrFN2yexa5k+sYVN9Kys3x++/tniMJvJ3u9pijR15a7QJFCX7Hn7GwsmcMHUMW+taeX31rnhMvns4YLcuKw1F5C1r0WlTmT1rDHVr6nnt/d3564uXlddlFBFzkDw78JkpRzGQZ5fBfByW2d8JVqxYgdPpZPny5WzdupVnn32W2267bdjlnnvuuUSjUb7xjW9QXJx755aRpra2ltLSUjo7O9m3b98Rr7erq4u9e/fKemW9x0S93d3d7Nmz55iuV1EUFiyITR5Zt27dIY9TOhSOp+NcyHonTZpEWVmZrFfWO+rr1XWdO+64AyhAS+WBMGfOHP72t7+xfPly3n33XebNmzci5SrxZXzu/c9XEFpGV1HUQESjJJsqhMB02tPGPYqIgRIe6lYwhcB02dAd6d+glaiBkjJr+9+/ejELFzl49Y19PPDH2PgfJWyghKIIM1EW6B5b1qQbNWSgBmJlJbrJo+6MmPjsbhFvhojFqdz0BTennOBk1fsN/P7Bt2Mzu1NeX8SrEPYoGWWZ2PwGQo81DEQ8CiFf+ncYNQT2QQMRv8+ZCoQ9SnLc49evdHP6NCevrm7kN/94ZyjGK4iUpJelBGMzwBO9e6YSG2MZKU2JCYG9Jz0mUiwIZUy6+Zbm5kzVyStbm7n3mfeIFkGwIr2LRw0oOLpFsiwUCBebhCtSxh8FFZwdanpOJQZmdXo3suHXsHdovDhpEi2BAM+3NvLLtn+mxQT9dkSrEyVRloBoSZSKcT3JmMGAg2CTB6EnBj+DWRZm2rj0yTRdATedjcWIaOw9+0+fg6VeOxvZwF/F4wC0B73saajEDMffV9XEW+Znybj0loHGQDEb9sSW+hGKSVnZAJeM25wW0xQq5o36KUTCWjzOYExZHz9zLsKlnkKL802e8jzKc/WzCUdiMYpiMqG0m2vHpm+52hgu5+GGhfhDdlTFYFppB58b82paTH2kjD81nM5gODZYXFUMZpa0cWN1bNyj4v1Pouq5vKnXcc9gbJyjTdWZVdzGbVXpY60bokX8omkZveFYd68mDGYVt/KNqqE666M2/qfpArrCsfFAmmIwp6iFb1a+kxJjsF78lrnmAt4ztvJn81Fm+1q5ozJ9YkeLHuCupgvpicTqU4TJHF8L/1U5dExbogN8t+X8ZH0KsZg7KtMnMbXrg/yg9VIm8G3KKGal9xd8teKDtJhOfZBvNZ+XVtYsX2tafe36IN9qSqlPmEz3tPNfVWszygpwR9NFdIVj18TPGJezWMyivOgZvLXfj5cV5TuNl9AR8iSP1SR3N3fUvJJSjuC7DZfSGY9RhMkEdzffGPNCWn09hp3/rr+MrsBQXmM9vfzMexJCW4biXUVozN38YO/F9AadyZgqzwA3j0t/n/sNJ3fvvoD+oANFmJR5/HxuQvp51a+7uG/3EvzBoZnNRZ4AH58YG2fpdHwOh3IG/ww08L36WBeeECZud4grJm1IK8tv2Hl8+zyiofhnQjW5aEb6+xcyVFbumIERiN8mBSiuKKfUDn0Bi5oK53ddy/luF6vam/n++rcxnTrTa9N3JImaCnu2jUGEh66bhsOgYtLQuGndEPTuLENNidHtJs6J6a3bhqGg7/by0qRJtPgDvNrcyn/vTT9WmGDf7UJJ6Yk37BAcE0mLce+1oaQ8ZNggUJPRnW4KPPVKsqybL7Oz9EQXbzS38r03302GeeoFSsRMKUsQyliZyd1gZtUXqshuW3M3mSjRlLJUwQ2ftLNsrou3d7fxo8few9NqpMWYqiBQml6WMMHdbiTzMjUIFme3lLvbo2lLDZqKIByP+/xVGmef4mLNe8386hdD47tNVRAuylYoZ1cYERn68hguyZ6Jb+8Oo6QsW2iqgqgnfczm9f+qc+YyB2vebeB/f/IiphDonuwJQ1pfMD13ITDc6XHqQDB9ycW4F2XhH4T4WvQ+X54tp/NwWGZ/J5gxYwZlZWXcdNNN7Nmzh6VLl45IuQ5HbBylEQpihqIYhhn7CeuYoQhG1MDQzdhP1MAcDEEwFmeGdAhGhp5jmJi6gTkYRgSGyiKsgz89TlFEbFP2kB6LCeoQiGDqqWWZiP4wymBKWUEdUso2owZKfwRlYOgxEdQRgzpm1MiIi6LGPcmIGCgDOoY+FGPoBmqfjtavY5gmhmkiggbqgI4ZiZcTMVH7dWy9RkqMidavY0ZTco/GHtN6YnGqIRAG6Gk5mWh9Bmq3gW6a6KYJAROt14iVFS/f1GOPqV2xGDNoonVnx6g9BloXybJEANRwbDiorhuYuonSa2JrV9Ax0THBL9C6wIiayefpuonaA2q7io6JERTY2pW0GEM3UbsFRos9WVbEr6K2qxgRAIEwBQRhoMmTjBn02zBaHJipZRkmolultbEYA5O+gJ3BJjdGdOi16IaJ0WVjW2MlBiYGJh0BF22NRRhRkSxfmAITEYsRJq1BD7saKoiGh2J0HXq7XKxsnIwpDExh0BzysKGxJhkTNaC9y8NTjbOTMY1hH6/WTyYYVlPiBA1dPnYMxK74/bqDZ+pnEYgMxUQM2NNdwgNNZyQWG6UhUsrfGxYwELJhYBIxBNu7y/lNy5J435JOfbSEPzQsoj9sS77miCHY0lPJL9vOQQidAdNJT9RNUFeSMSFdYXNvJXe3L0MIHSF0GnQP9zadQ3fYmYwLm4LOiDMlRuHu5vPpCLuGYgzBxr5q/rvj1GRcVJgEDQ0zWY7Cpv4q7uqYhyJ0FKHTagzw3eYL6IoM1Rc1YWN/NXd2zIrF6L3c2XpuWn1RYONANXd1zEyW1WH08V8ty+gIu5LL3G0brEyL6TL6uCMek1rW5oGqZH0dRh93NJ+XHmPCtsEK7myfn1LWAN9svpCOsDsZZxCTGYGJEDodRoj/arqYtpA77VjV+Uu4q3Vp8liZwqA9JSZqwl5/CT9ouSAZ02uqfLf+UjoC6Xk1DBbx7sAkAMKmyvf2Lqc76EiLaRn0cE/juclzpt+08/92n09v0J6M6Rh08Zv6Jclzr99w8L+7z6I/aBv6TGDSPejkz/tOAWEQAXojLvRoyrluQr/fzmN75yY/E4OmxqPb5xIKpcTp8M+905IxQVPhpR3TiQSGYnTTJBJQeWfPRAwR+6xGTTAiIvYeC+LXHoWte6rTztld22owQinXBtPEDApa95bEPyPQtaMUMmIIweBeb8rnUhDe5UGEYkv3mSYoBtDgSMtT3eXEDJnp9YVMbE1aMsaxR8MMZ8SETezNSkpZ4NonIDR03TYMAxGNDUNLPM+1DwgP3V8M04Swga1tqGxnvQFhMyPGxNZupOXgbDRiZaXce4kYmAN6fJqAwNWsZ8WYEQNH51AOpmHibNUhlHL/CpvYu6NpOThbI5iRjLKiBlp37P4ciRqIqImCyKpP60l3BHtHKOkHiR+1Nz1G6wxBWM8qS+kPDz2nK4AeNWLvryKSniJSYgzDROkJZOeuGzAwFCd6AxhhfciJUrwo7Xn9AczokPE7nfnXTs3FsKXy29/+dtqaRn19fXznO99J/v+LX/wiv/jFL/iv//ovbLY8q18fBJ7klotRCIWTC4aKSEoLZSqmiQiE8y5CLkwTEYighvSsFsoE+3a3s2NLE/U7WrH1hdNaKNPLAnUwghbQUcIGalBPtj4mYwwTbTCK5tezWigz4/btbGPH1mYadnfmfH22AQP7gIEaGmqhTCtHB9uggaPPjLVQDgy1UKbXF/ubvddkd3Mn2+pa2dfclR3Tb2LvMVEzWiiz4vpM3M0mjp48Mb0mjm6BGhLYe2BXUxeb69vY09adjLH1gbNdja0/mdpCmYoB9l6Ba68NZ7uau74eBdHiiLVQtmuIaHxJCMzYOFTdxNajEGj2xlooW4ZaKNPKMkHr1mhvLMEwRLKczJxEl50djVV0Bdx0pLRQJtjR3cmG1lbeagzTHvBSl9pCmYouGOhys6phKi1BH+vqx6NH0uNMQ9DZ5eXphhNoChXz2r6pyRbK9DiFde39vNHWzUuNJqGIxd7HhmBfdykPNJ5JQ7icf9SfiD+U/u1WNxR2dZfzm+ZzqI+U84f6M5ItlJlxW7ur+Gbdh3m6VWNzbzN7B9rTYiK6ypaean7adj710SLubTwv2UKZSqu/iO+3LaU+auOnTRfRFcpeLD5qKGzqHcNd7adTHzX4WcsF7PO3snOgnoZArBUpaqps7qvhzvaFNOsB7mq+iG6L+gxTsKW/hhsbT+c7LRckW/AyYzb1j+HO9jm06YN8q/n8rLioqbBloIY72+fQoQ/yTYuY1PpualzEN5supNPi9RmmYPtAFd9uO5EOPcAdTcuzyqoPtLC9v4EV3SZdRpRvNV5GRzC7vqihsGewjO+2nEunLrizIXtdTMMU7Bss5fvNy+kx7Ny57/JkC2Vm3ObuXt7u7uGRFneyhTIzpm3Qyz0NF9BvuJItlJkxXYNuflt/Nv26i//ddTaDQYuWFaB30MX9u87gyX12NnS2sKuvI+3vpikY9DtYsWc+fsPOiu3zky2UqYT8Nl7aM4OQofHy9pQWyrTCwAhovFc3iaihsGb7JHb2dLGhvYWd3UPXSRFU2b6nhqipsHt7DSKUY5xlWEE3BD070lsoU1HDguA+X6yFcpcXJSSwK0pMnGK1oYREbAF1E+y70lso0+sDZ6MN9570Fsq0mAi4mtXY2pL7lKyy6lq72byvjT11sdfrbUhvoUwvy8TZBp5GM299zo7Y8z1NZs6y6hs62VLfRsOOzrQWylSEbuLqMmMtlG2GZVkiCs6e2AXd3RbNuRmKMEzsvTrN29vZvq2FvXs7smN0E3tfzBUyWyiHYgxs/bGYzBbKzLK0wQi2nljLY8OeDnZsaWLf7qHrpDBN1MHYgcxsoUwrK+4Jan9GC2UqcS8CEINBhG5gxm+aLpcr2SN8sAx7TOV1113H73//+/0+NpJ89rOfZefOnTg6Z6KFSiAUjm2f6Mq9WwmASMS5cxu4CIRia0V5c283IAaDiAE/ps+DUZx79xPFH3vDcq0lBaD6YydIrnWpEmgDYTBNQhW587INRMEwLdfKSo0RukmgKs92M4BtQEeJmPirc38RsPcbKBGDwZrcMY4+A0/9IKEKF30Tc4+2sPeb2AIGfRPyxPTFhLlvUu4pfI5uk5JdIQKVNnqm546z98bK6502dCF//tNXIdxunty0jZ+veht7b6y83twbuwBg6xU4O016ZuX+KNl7FJwd0HtC7i82th4FV4ugd17+pRy0Hg13s6B/YZ7dEnrseOoVgidZz3wF0LsdVL0lCFQqRM7MvWtLoMeJe5cdbVH22pkJ+ntdOHc48Z7RnjMGoLPbi2uDi5JlLTljOvo8iM0+xp7VkDOmtc9HdEMxtUvyjwVt7fcRWFfKjKUWaw7Gae4von91OXPO2ZkzpqG/hMjTlYSLYfYl23OXNVhE57vVzF0WmzjhVJz8aMHXKKeYG9bdgd8I0DJYRMc7Ncw9N385/idqiPhgxqXWkzAA2vw+Ot+sYfp5u3PGdAbcdL9ew8Rz8x+r3pCTvteqqTk393HvCzoJvF5ByTm537/+oAPln6XYLs5/LgTCNsRrJYizc59XobCG4w0fkSW5z89wWKP8WReGDXrOzz25QI8qlL7hoHtx7sWnzYhC+Vs2Ohfl32kFXVD5tkrHaXnGyEYFVe9C+8m5Q4QuqH7PpP2k/JNWhA5VHxi0L4hd03w2jX9cczmG28s7exq487mXYzFronTMyzOqzYQxb8euG60n57kPGlCxPkTX7Nz3EmFA+aYg3TPyxJhQsTa2ikTXnDw7CwGlWwbom2q9ikKirKId/QzU5i9HmODd2Yt/ovVi8gk8u3sITMgdI0xw7ewgNDH3rmQJHPu6iNTkn99ha+pGr8wfozbEPjNGdf46ldYuzLL9zCfp6IbiA+jC7upBFMXiEjvqlJeX89hjj+3/uVa5HdKzUtB1Hb9/6MY1ODhINLqfD+QwSbZUCh0CQczBQcz+foQ/901WBEKYA4OYff2IQesLj/AHMfv6oacPMZBn5pNpYkYi0NuP0mt901YGQ4iuXkRXL1qPdVnqYBiloxeloxdbd+76tIEwansvakcfjg7rOFtfBFtzD7aWHpxt1jH2/gj2xh5sLb24W3JfWO29UVz7enE09uJptv7K6+jVce/pw9XQj7cxR0yfgbeuH8UfxtnUT9E+6/PC2WNSvGMA995BiuusYxw9JqXbBvHt8VOyK7eYKXrseHkagpTssI5zdJuUbwpSVBegdGvKuBYR61oxDBNHN1SuC1GyO0jpppzV4egSVK2JULIzTNkG6xuDo0uh+oMIpTvDlK3NMaO6S6H6XZ2SnRFKV+e+KWhdGjVvG5Ruj1D8rvVNQXTaGfO6Sdm2KJ6382z5GBU4egyK9ujY3rC+uAa6XFS/olG6Xcd4vdQypq/bTeVLDkq36QRW5d7errPbS/k/nRTtMehZWWMZ09bjxfecl9KtBi0vjbeMae4pwvlMEaVbDepfnJSzvqa+IpSnSyndarLr+SmWMQ29xRhPllOyzWTbc9OtY/pLiD5ZgavLwJ7bbWjoLyGwopqSbSZbnplhnftgEf4V1ZRsN3LGQKzV1tVl4G0w2P6MdV6tfl+srJ0GdU9bv752v4fgY9UU7zJofCb3seoKuAk/VkXxboP2Z6yPe0/AibminOLdBv3PWr9//UEHtidL8LToRJ7NfS74Q3acTxRTvEdHfb7EMiYU1ih+ykvx3iiuF6xvjuGwRsUzTpzdOo6+3IKnRxSqn7Xja4hS+ZK1BJkRhbEvaPgao1SvyrP2jC4Y90+BtzFMzas5ZDAqGP+Kgac5wpg3crTiRQXjVum4W0PUvJWnF02Hsa9FcbWGqHkn9oXTpijo8Z4tIWIxY94M4WwPUv1+jmbKuFBq/eFka5dlfQZUv+vH3hmkcm2Oe6UBlasHsXX5Kd9gfQ9MCKUyGEIZDFG22XqJMoCy9X2ovQFKtlh/wIQJxZt7UHr9+Lb15s7dBN/WbpT+AJ5dub+seLZ3IgYDuHZ3Wf49IZSEIzj2WcckcOzpgEAQW2PuOFt9J2YgiNqcO0ZtaMeMRGJukQfR3IEZDsekMRdtXRAKQVdP3rLo7IZwBLM7fkyV2P33UMdTwghI5WWXXcYtt9zCo48+yqOPPsqtt97K5Zdnbxc2kpSXx7a8MtVY6x1G7MccGIDO7iy5FIEQpt8Pug66jtk/kCWWwh/E7B+IlWeaOcVSDAahP742mq5biqUyGEJ092EaBqZhILr7ssRSHQyjdPYlc1I6+yzFMiGU6AbohqVY2voi2Fp7Y2UZBlp7X5ZY2vsj2Jp6EVEdEdXR2vosxdLeG8XZ2Bfb7lLXsTf3ZYmlo1fHta8/NtwgquNsHrAUSyVqIuITokTUsBRLZ4+Jb/cAIhxF6DquxmyxdPSYlOwYRAlGEREdT4O1WDq6TYp3xl63EtEtxdLRbVK2JYQajKJEDbz1waRYDgZCdPQP0NM2SMWGUGzYQtSkaJ+1WDq6BBXrI2iDUZSIQdHebLF0dClUrYmg+fV4TCRLLG1dCtXv62iDiZiopVhqXRo17xpog7G8ivdki6XotFPzlolt0EDoJsV11mKpdzuoeYv4sTItxTLQ5aJ6lYp9IDYgvrguWyz7ut1UvWKPtVpHoajOWiwTQhmLMymqyxbLth4vxS94cPQl6ssWy+aeItzP+XD0mSg6FO2xFsumviJsz5Tg6I0NuyjaY2SJZUNvMeLpMhy9sbJ8e40ssUwIpbMndgN39BhseTZbBhv6Swg/UYmzJ17Wvpg0Bo0gt625izVr1lDXbyewojorJpPmwSKiT8ZGyys6eOuzxbLV70uWJQzwNmSLZbvfQ3hFVWzoiQHeRmux7Aq40R+vGCqrKVssewJOxOPlOHtiw3S8zdlimRBKZ09sv+RcYukP2XE9WTQU12pkiWVCKB29eiymTc8Sy4RQOnpin181ZFLyz+yeHD2iUP2cPVmWqzNbLBNCae+NDaFyderWYhkXSntvvMuzM5ItlnGhtPdGEaaJozuaJZZKVDD2VR17bwQMcPRELMUyIZS2/pho2Hsj1LwTwaYo/7+9+45vo77/OP66k2R5x07iJM5wdshehAQyGAkhgQBhz/YHZZW9N5SyWkoptECAlpRVNi2j7BUChTASQsgiew87Trxtbd3398dJsqbteEQen+fj4Ydt6aPvfXU+S2/dfe97OF0uCiur2FtVQ/63bmzVgcBZ6YkNlmGBEsxDu91+in39DwZKa7XHPNRa7YkJlsFAaakxH2+pcccEy/BAGXrOjvhht/OKSnSHWac5PTHBMhgotWCNyx03WAYDpeYM1nniBsuM9SXmUUtA83hjgmV4oATqDJb2rfvMI6WBunjB0rajxAyBgPJ64wbLYKAM0vckCLuF+yC4087nix8si0vB66mtiRcsS8rMr+Blrf3mtmdYzMcFp4JsjCaHytNOO41LLrmEoqIiCgsLufTSSzn11FOb2mydgk/YUE6UKyxAGgq8PlR1dShYRgTKoKhgGREog+IES63GBZXVMW2FB8vwQBlqKl6w9KuYdqKDpbXag2VfZeSYiKhgGREoQ+shNlhqPoXm84f9HhssIwJlWL/Cg2VEoAyKEyztlQbpOyI/mQaDZdYOX6Ct2kAZqgkGy62BmrBAGaoJBsvNtc/HXqbIXeeMuMZ6KFhuNEI1wUAZqgkGy3UGyzZs5N73P+Wtb1ZhcYWvq0CwDDupOjxQ1i4vMliGB8rImshgqfs0rDXRNZHB0lpqpfsSI6IuFCyXmMFSK02hx/fm2Nna9anI3uYj/YfaYOkvs9P9Gw1bdW1dMFhavzWDZXigrO1nZLAMD5S1NbHBMjxQhrcVHiyLyzPJ/iwjYm9TdLAMD5ShmjjBMjxQ1q6HyGAZHijD24oOll6fJRQow2vCg+Wu6k543suLrdseWed8t3v8mrBgWViTjfO/sXUpYb+HB8rQ8wsEy80fms8vPFBG1Owy2PVR7boKD5QRdWHBstyZivauGShrawLB8mPz7xcRKIMCwdLzce22EBEow+rSi2uDpdtjJfuDQKAMbyssWEYHylA7e/10WlAbLCMCZVhdWomPrl+YwVJ5dfI/s4aConljnGAZFSiDUirD2g4LlKF1FRUsIwJlUJxgqfkh/5vaQBlkq/KRYtHYtGsXF734Nm8/8L9QoAzVVHrottQTer7hgbK2xh0RLDUDui9xmkOtwvoeHiyjA2VQeLCMFyjNfqiYvZXhgTK0TKeHTmurQm2FB8pQTVSwjA6UtXWRzzk8UIZqPF7StpSF2kndXFIbKIPiBMuIQBlWFy48UAZFB0vL7pKYvZPK640JlnpRSW2gDIoOluGBMrwmPFgGw6Q3si1VVoGymP0I7rhrjBadp7KlvP766zzxxBNYyrOwb49/GAZdIzAjdmTgCmexoGWZ4zNUVYJd85oGOdnm9+hAGd2W1QqBvZNxm9J1VG42ymap3UsZpx2ji1lj2VcJvkTL01E2q3lyT6I+6Tq+vGyMNCu2wsrIIBigrBZ83bLxpVliA2VUv1SqDfwqbjsAWC248jPxZlnJ3FIVERYjl6ljpNrQDJW4xmLB2SsDT5ae8JCIslmo6ZOOM1ePCZThDJsFf5q5rhLWWHXOvXwsC3fuZecnRRGhsrbfGpV9U3H0iA2UkcvT8WVYzJOxHPH/NoZNp7KvjaoCQnsp49dYqeoH3ZcY2Krjt6WsGp4si3lCU4Iaw6ZR0c9K1RA/3b/RIgJeuJp8CyWH+GICZURbVg13tm6GnQTtGFao7G/BMdoZEyij2/Jka2BAakXimor+Or6x1XR9M/7hfMMClf10LJPKYgJlOGUBV46O7lcJawwLVPXVyZiyN2IvZbya7Gl7cL/bjdSyxG15O1uYd8Yh3PTUD+aZrPHaKtDJOaLIDJRx2jIsUN1Hp9ORRTGBMuL56WHPr46a6t46aUfujQmU4TyZGsbJJWagLEtwJSpdw5VjnjgXERTDaVCdb8F3VEVsoIzql7uTHmgrwWuaBjXdLFQc4aLXqwnGcgdqSg93xwbKqDp3tvl/Yy9P8JqmaTi7WNgz1YgbKINcXWwUTSYmUEY8P03Dm21B8xEZKMPp4M6xsWeihfxvfKRUxq/rObILs08cwNN//SkmUIbzZZivs9GBMpw3287esXYzUFbFHxalLBp7Du0UN1CGM9JT0PwqNlCG12TYKR2eGTdQRiwzLQUMIyZQRtSk2qke0iluoKytSaFmYG7cQBlRl2IzT15xJa4hxYa7oHP8QBlW4+3VOW6gDKfZzOUpd+Lnp9lsGN07oxfFBs8IPfLiB8pwVqu5syzR+zdw7D2jefPNNznnnHO49NJLE7dVh0aHykceeSR0re9E97eUL7/8krvuugu9JpXUTX3i1iiPB+XzoaWkoKUkPpFE+Q3zCj22OgY3e31mSLXWM61n8FNKWh0n3QQ+aWgpiU+UUYEgqdnrPplGuVzmP0Fm4sHNoT6l1nESk9eHqnGYz69T4kHQmssDPh+qjsG/mtdnBuv6ToYqK0fLyMDoUsdAabd5CL7Ok6a8fvD6Yq5tGk6vcUNxCVpWJr4eOQnrTjtrOFvX7GXJqpLEbbl9aB4fvk6Jl2dxeNB37oWsDDx94o9DNNvyozt9eLrUcSKX28Di9OKuo8ZW7cO2tRiVmY5jYOLlWdwG1ioPrm519N1jYK3y4upW90lv1ho/qburqDqo7uWlVHhx9KjjxLEag/Q1RajMdCqH5SSs070Ke4kHR8/E60H3KlL3eajpWcfyHAaZK4tQGWmUj6rjb+NVpO3zUJOfuC3zsm5111jcipyVe7j9uZMShspQW3s81PSqZ3lFbmp617W9KLKXFaLsKZSPTXwIS/cp0ovc1PSq4//Ur0gvdNW9zn2KrGWFKJuVyjHdEtf5FWm7nTh61XFio1eR+UsxVaMSt2P2C9KKHDh7JG5LMxSphQ5c+XXU+BXpq3aDruMYnmDnBObeK3tRNe5udZxEYoB9TzWeOmsUtrW70DQNz+CeCetQCltxFb68xK+zQ4d3YdLBPfjX8ysT1mAoLJvN65Ib/fIT1wGWfZUYOXWfAKOXVGLk1lFjgLaz0Py5Z92TZmtllajsOtpSClVYjNa97sOwqrAYLT0dLbOOseOYO420jLprjL0l6J0TvyaE2qquRktL/BoKmO+ndeUAwCivQM+qe50DKKcLra7372BNHTkHwKg2h+3p6YnXw+hLuvD9999zww03MHfu3Hr7Fk+jJz+fM2cOAP/3f//X2CYarU8fM0gadg8KRaILEylDQeCTQrwVrjxeM3wCmt0e9w+nPF5U8HJFmo6Wao8f9jxeDKd5yF2H+BuU240ROOSuZ6TF3TCVxxP642uahpaWFvefQblcGIG9qzrEDZbK5UZVmHv5tMyM0F7ZCC43RkUlyu83l6drkBXbluZ0Y5SVh5YXL1hqDhdGaRkohd4pG5UbGxg1pxtjXyl4vSivDx3iBkvNYQZBpRS6Kxuja+yZbmbNPpTfwOLOSXxmnaFQLjd4fVghbrDUqz04i8pJ87qw7S7D2zP2xcVS7UbbucccEtA5F0+v+C9Aml+hHE40j5cUiBssrdVe9K1F4PORWp2Lq2+cmhof1s2F4PORVpmLs3+CFzxDoWpqwOUiHeIGS1uNj5R1u1E+HxlVnalJUGNfuxvl9ZJZ3pnqIfGXZ6v2k7q2EOV2kwVxg6XV4Sd9dSHK7SG7LJfKYfFqDNJX7Tb/vxwusiFusLQ6DDJWFqJcbjqVdaZiRPy2MpfvRrnc5JR2pnxknOfnMMhcUWi+4Dtd5KwkbrC0Og2yfjaXl7MvN36NyzDDVB01Frci+6fdKJf5P5+zopTSOP0KBcEaJzkluZSPjj3z0+JRZP8UrMmhfEzs4SmzZrf5/Gqc5PxM3GAZqnO46LSvExVj4tUEnl+Ng+x9OVSOjq0JBcrqGtA0sldoVI6OHUNp8Sgyfzb/zlml2XFDo+5V5t/P4SBrJQmDpe5TZCw328rcl0n1yNgwqPkVGSt2oRxOMkozqRkRvyZ91W7z/6aOnQWaX5G2ehfK6SStNBPn0Ni2dL/CvsZcnr08E/eQOMsLBErlcEIdl8lDKWzrdqFcLqwVVfgGxQmfhiKzshrHviosmwrxD4wTGA2FZdMu83WvrqlhlELfWojhdKFVVaP6xA/X2rZCDLcbrboG1SdOYAwESuUKjGfcvSdxsNxZhOHxoNU4ID/O3zkQKJXHA3v2JQyWqrAY5fOhKivRHA70bvHrjOJ9KI8XzeFEz4t/WNfYW4Ly+jBKyxIGS2OfubNB+XxoLjd6bk78urJylM8Hbjd6Tvz3JKPcHLJmVFUnDJZGhTkEQPn9aB4veoIQblRWmzVeH3pG/LBrVNeYeageO3bsAKCgoKDe2kQaPabyoIPMeVY2bdrE2LFjI762bEk8fUdz6N27t7l30WpgeKtjxyz4fBiBPXTKUGZwjBrrEAqUhjlJqnK7Q/8QEQyjtsbvRzmdqDjjKAynC5QByjB/dkadiR4MlMGaGmdtWA0XOHEHv998Hg6H+SYR3vdgoAycoGRU15gv7BE1ZqBUfsP8qq6Je4hfGQYqcPhcKWWG0KrItoKBUvn9KL8fo7IKrSLyKg+hQBk4WcioqEQri3PY2jAguBvf7zc/rZVEDcwOBkqfuafSqKhE31cRp8Z8scDvxygtN09oiqI7PLDHnKZB+f2o0nKsReWRNdUetF17cFY4SMtMQZWUYdsdOQA6GCiVx2uuz9IyUnbFDpK2ODxm8MTcDikpJ2VHZF0oULrd5vraV0bqtqiaYKAM1pSUhcb9hLNV+7BtKQqtT/aVkh41OD0UKN0ec3zu3tKYAeyhQOlyh2oy18dbXiBQOpxmXXEJWeui+h4MlE4nGH7YW0b2mugag4yVu2v/Bwx/3NkbQoHS4TDbKi6l0+rYtjIDQQNlQHEpOauinl94oAytqzJyVka1FQyUNY7ENa7awJWoJhQow/93S8vJWVEaWxcMZsqAvWWxNcFAGazZV07O8pLYmqVhy1MGlFaQ8/O+OG0F6gI1nZZH1xi1YVEpKC0ne0XsHH0oal93lIKyCrJX7I1qKxAoHY7QOPWslZFXmAoFyuoa8wNSRWwNhAXKGodZV1VN5qrIqY3CAyWAqqwmY3VsTShQAvgN0n+JnSIpPFCCuYcqbW1kXXigBHOPmH191PLCAyWAoUjZWBizvPBACaAcTqwbd0fWGArrhp2kpeo4K10olwvLpsKYmlCgBDAM9K3xl6dvLUQF3quU04W2I8562FYYOkSr3G60HXuilhcZKIGY99uQnUW1J614PFAY9XcOD5SBGrUndtsLBsrQ7wlmnAkGSsAMjXtjj0IFA2WopjT2dc/YZ74fBZeTcHnBQAmh97eYmvKwcyACwTKmpqIq9H4LhL7H1AUCZbDGiDOzTXSgNByO2BqHA7+zhsJCczsJ7rhrjCafqPPhhx/G3PbRRx81tdk62e128vPNT2eG3Y0RCIgQCJRR4TA6WCqvLxQoI2qigqXyeGPGOyhDRQbL8EBZWxQZLMMDZXhNVLBUHk9ob2eI3x8RLCMCZVBUsAwPlKG24wVLlzsmaEYHS83lCQXK2rYig6XmctcGylCfYoOl5nRjRJ+JFhUsIwJleE1FZVTNvsgXrjjBUnd4oHBv6AUj2PfwYBkMlMrjwVnpJi071awJC5bhgTJifUYFS4vDg76tKOJDR3SwtNSEBcqwvocHy4hAGV4TFSytNT5smwojT1aLCpa2Gh8p6wsjPwhFBcuIQBlVk7mhPGx5YYEyvC4sWEYEyqBgsFxbHqiJCpTBdVXtIHtN2PLCA2V4W2HB0uowyFwZtTxlmEEvPFgqYj6c4Y8MslZXWKCMWJ+1odGsKaqzBswTHOpbnsUTFijD+15SGz4jAmXE84sMlpoRZ3nKiF1edNCNCpa6N2zvY6gmNljqPkXWz1FBJSpYRgTK8JqwYBkRKIPiBMuIQBleV1VN5moz5EQHytAiK6vJ+KW2JiJQBtaBqq6JCJbRgTJUGhYsowNlqCYsWMYESgKvsTWOyGAZFShDNzuc2IKh0VBYN+5GOV2kZafirHKZOz3Cg2XgkHf0DhLldEUGy6hAGV4XHizDA2WoJjxYxgmU5u0G7I4Kn2GBMtRWeLCMCpThNeHBMjpQhhZZvC/m95idSV6feaQsWBMWKCNqwoJlMFDGLC9w5C7895i6qGAZESjDa8Leh4OBMmZ5ldUxv0fXRQfLeHsolaEigqXhcJiPS3FjGAbp6elNOlGn0Ye/Fy1axKJFiyguLuahhx4K3e5wOLBY6pjjq5n079+f3bt3Y6T70CsMDI8XzedLuIs3/FB46Pd4NcF/IF03w2OiOqfT3PgNFRkWa4swnK7a1J6opsZp1lgs5mHveJ9IAsFSczpRwSmUogWCpQ6gWyICZWhxfgOCh9ZtttBh75g6paCiEhzOiE9LkW2ZwVIH8/BRvH4HgqUOkGoPHfaO+/zKK9BqAnsq4n0KDIZPpVCpKfE/CQeDJaAy0sxAGWegtPL7obQcS3UN+I1QjaPKRVqWvbampAwbYGSlxV2e8htQWkYK4M/NiAmUoTqfD62kHHu1w3xMvIHZwWAZaCthTUkZaYC3WxYpGwtj3oRq2yolo9oReNOJ11YgWALebpmJa4pLyARcPbNIW1MY8wYaXpddY+69jLsHPhAGswFn76x6axx9s2MDZVRdTo3TfCOKDlOhdVBGziqoGdDJDJ6xVSiHk5yVZVQP7lS79zFBW7k/mGOYo48KRCxvJVQNyTGDZ7zlOV3krCilamhubFgMb6uknNwf3ImXFwqWUDWsc+LludzkrCihamjn2EAZ3lZpBTmLPXUsLxgsoXp4l9jgGVanVTviB8rwtsoryf7JF5gKLk47oWAJNcPyYgNleJ3DmTBQhhZZUUXGCn9ge4m/PoPB0nlQ97iBMlTqdCYMlKGaqmrzfqXi1iilIBAsPQN7xA2UoVqXqzZQBtZnWradvVsDwScYLDfuCvQvQTuBYGn07RE3UNYuL3AIO06gDNUEg6VK8PoSaCd0GDxOoAzVeczpi+IFyvAa9uwzn2uCvYTK58Mo3oferWvcQFnblnl7vEAZqgkGy/qWV1aOnpsTP1AGBafriRcow2qCO4sS7ZU033Or0bMz4wbK8Dqo+5B3eLAM7enMMPs/aNAg80hwIzX6RJ2NGzeyYcMGnn32WS644ILQ7RkZGYwfP57MzPoHoDbFCy+8wDPPPIO+NxXb+pzIO7VmuKR5MATW1VagRmuGEB3842t64j9mqKY5QrsyD+triU5QCoRJzWKpPYu+DvVthMpvHvbXEoxfUn4D5fOiWSx1nsTUYIZ52D/eWFpd17jpHxfTJT+HPdv28bdrXmDqiQdz1k3Hk9E5jRumP8DeXaVMnDWGs248no9f/JpPX/qmaf3x+zFcbjSbFd1e96Brs5ON/6eGwPp0OsFiqXNgdrMJfPDBYkGv68Sx5lxedY25vAYMdm/68gyMqqoGL++iu09l6Ph+FO8q42/X/YvHv76Jyt1unr7rP2xYvr3+5SmFUVF54J+fpiccu9WsDFW7vAOxvSij9kSFpi6vAWPTAPzVNWi6Vu9JHfEMGtuXyx44G8NQlO+t5M+XzOcPb5knxdpTbeT17cz9v3mc6j0urnn8fHSLzvO/e41lC1bRc1gfrn38N+xYt5snbnwpsutOF3o9J300lBEI3XW9nhlud4Ne7xoSQ1To/Ig6TnL1eNCszXM56OD7UZ01wffIZlmeD/R62jL89dc0lOE3Z7UJOP6RKbz55pucfvrpXHXVVY1uttF7KgcNGsSgQYM44ogjSD8Qb1pRhg0bBoDKDPs0EtowjfhhUBm1NZpWf00D20q0YSlDmX84AN0SNzBG1ACK+usU8YOl8vsjlxdvY1eRn7yUl8TBUpl7DTWIHywNVXsB+uCUSjF9MsMiSoU24ETBEhX4lObxxH3hUH5/7QuL1Ra336Ga8OVFBcspJ06gcEsxD5zzV864aS5TjhvLKVfO4vfn/I0rnjyLc245kUevfp6Jx4ziuql3ctW8C/nE5Y5/Bl4gLKLM7USzWBKfqafMvaIG8V+Ild8fGkqhpaSgxznZS3l99dYAgVBtjs01iH/Gn/L5MAJj67SUlPjh0+/HHxjLV1dN8BCKGfYSvHEHgqDy+822mqGmzsHugaAUaqsZahqyvAGj+pCbm86NJz7MWdcey9Tjx2O327nr3Ec49/o5rPtqZd3LCwTKepcXVteQthr0/KjdGxIjEASV349mtTVLDZh/y0RBL6KteDWBsBh8DdbjXQkkrKZOhqrd1hN9OIquSfDeF6xRfhKcRor5vxfoH5qOHnZCZsnuMm4/5RHcTg/n33Yik6YP5caj7kZPS2X6mYdxwlVHUrm3mgvvPouHL3uG0m3F/PGDW1n2+Qqmzp3Ao1c/x8xzp5HdJZPKEvOwqeF0gRH48KdbEoZLw+UOhZeENU5n1PtknBq3uafdcLlA0xKGy2AdmpYwMIZe0+sQrFFej9lWgnAZ/n5UX01doVH5/aH3SEj8vhb+fltvTV2hMfjeHvYeX2ddQ2rC3ifXrVsH1J4v01hN3qV30003UVVVe9JGZWUlV155ZVObrdfQoUMBUGl+lDUqCKo4h6Sjw6IKhLR4h6UjHtewtmLGNkSFRQzzxJt6z8Ay/HHHQMS0FWcsRX01CZcXfQgg6pB38ISZyMep2n/OwPNPuPs/uK4S1IWCZ3hN9Lia8LCozGXHjIUJrwm25fPGHAbJ79uFjT9tAmDDT5s57sKj2Lp6B6W7K/ApD/1H9Aa/nyUfLuWv/7uXDUs3me1EH+YJD5QQCOx11AX76fGYL6RRfQ8fmxtvfG14oAzVVNfE1vmNiNuUxxMzODs8UCaqCQ+UCWvC+h+xvOhDmuFBsCk1iZYXPdg9Iig1X01D6oYfOoQfP1mGUVXNj1+sZtiEAXg8Hu57+Uq+euV/dS8vPFDWtbyoukbXxHt+cYeyqMh15fPGjPFqTE3C5UFsW9HbQlRYVH6/ufezjhogtp3A0KGIbT24JzyqLqYmzv9DeA0Q9zB66H8v7LXDCDu8X1Zcidvpwahx4PN48XvN9yrD6eLwkw+horKMyr01dO7eiZ2rtuGoqKaypIrszpl88+9vufbx35DdOSMmUNZ2wB9z7gGEBcq6aqICZfRrWei26PfbOCLqlIo/XCkqUDakJtHyQu9ZweX54gxriq5JMPyr3pAbdmJP+G3x6iIY8f7/GvZeHlPXkLaUQmmK9evXA7XZqrGaHCqdTmfEdSKzs7MjrgXeUrKzs+nbty8ARnacMR3xwmA84XUxeyn3ryZi40u07LDQGBMW97em3k/efjPkBOtUgvEh4cEyGCijnmNEsAwPlKEC8/kbbnftGXLhYTGqLqYmTluhk6+iw2KwJk6wjPnbRAdLv59tq7Yx7qgRAIw/ejQAjooavFUunNVubHYrhtvNd+/+yLVT7+SjZ76obSf8RdYw4v6dI+qig2ewJixYRgfKiJrgmZlRgTJUE1g3oTq/EREWI9oKjqGJCpTxaqIDZdya4POL8/8eEQijwmKja8Lq4i4vGJjiBKVG1QRvi/emUkdbmTkZOCrNMdfVhSVk5WSwY8cObpx+N2t/WJ+4nTiBMvx51z4ofl1D2mrIOkAZkWEwThCEqNDYhJrwQ9OhRSZqK3S2efy9jxHBsq6aYDuBoGi+5sX+b0XXxa0J2/4T1YQHy3j/e8H+RqyDGgd5vXIZP2MU37+/FJQiLSOFvF6d8SkvVaUOoPb9oabCQVbnTHZv2M1NM+5l3vUvmu1EB8pEywsPlKEbI4Nl3D2USkUEy5hAGX572M9x66KCZdw9lA2pgYj3HuXzxr7PBNqKeUy85UV/CIq7vPrPRq/rMRGiPgA0uqaux4T3I9ODx+Ohc+fOTTrzG5pw+DtI0zRKS0vp3NmcW62kpKRB4yOaw/jx49m2bRtGJw+WkjiHAZUC1YCV3ZA6pYD692o2aGMy/PXnXcOPUlrdn4YMf+3g/EQbVeC5qURhOLwtj1H7mHhNBQ+FJ6oJGw5QG2QTB/CG1ODxmMMPEtVEheb4HQ+rUwbfv7eUMUeO4KEFv2fr6h1Ul1WTnp2G8nmp3FOF1quOPvm84DKHDBiJps0g8CJWU3e/lMeDPxiK66gxCBw2qWOjUR4Phj/wYaSuthpSQ2DcUj01ut1ee9g7UV1F7V6kJtVUg56WWudhTOXxhM60bHJNVTV6enrsnq8GtFVVbm5PABkZNiqLy+jSPaNpfQoeBs/MSBw89+f51VcTCIN6Zkb8IBheF5gLt8k1gcPgdS4v8D9c53YQFizrrAmeyFDX/5XfnzBQhtf4w8JuopqI6Z4SMGoc6BnpGDUO0jNSuPVfV/HQBU/iD1wQ47ATDubnr1aSUZCCv8ZJ+AmZmTkZVJUGA7y/9mhFHe8NEXsi6wkvdR7yDg+WTakJu6/OQ97hwbKumrAjYAkX5/OiWW3xA2V4W3W9X4Xaqv/9v6GBE6g/LDZ0D2Y9zn1kLs8//zzjxo1r0kk60Ax7Ks8991wuu+wynnzySZ588kmuuOKKAzYh+vjx4wFQOXVcmqg5BQ69HjANWVa8Xd6NbasBzy/eLv2E7dT3wtGAGnN5dVyeKjiMwajncERouINCKcXfr3+Bm2bcQ2VJFW89+gF9h/XGarVgt9op3rG3znaUzxt4ga3jk0F4v+rSgJq6DjtH9stXf1sNqfF4Ig7FJarx1/HGHr68+raXOodOhC+vjjMe92t5DanxePDXEd4i2oqqWfP9Bg6eOQaACceMYfU3a+psA/ZjHZRVHLh14PM2eh202PKU0azbQUNeO+sKlCENGUrVkNcDZWBUV6OjuPWlq3npvn+za0PtVECHn3YYq79fS0VxFRh+SovK6TWoB+lZaWR1zqSyJOxD0P68/tRT15AxlA16f2zge2hDxlA22/JUYBxmM/W92TR072MzWLZsGQDjxo1rcltN3lM5ffp0BgwYwE8//YRSigcffDB0WLqlBVO1SvejUvxonpafykgkQTP/I+d2z+GOV6/F7/Pz04KVrPpmLW89+gEPf3kPmV3TeecfsXOv1tmf6E928Q6xxPv0Fz0GqL6aeMtq7uUF7wvuuW9qTUOX11x9qm95zb0O4rSz6eetlBWV88iX91C8fR//eeQ9Dr9sQoP2zrSXddCiy9ufdZBIa1sHUX0+4szJjJh8EOlZaZx752m89/dPWfzhT3Qr6IrH66Z0ZxkAz97xKjc+ewW6ReeF378ef9nN4UCGqWQsrwNTFoNVq1YBtTvqmqLRUwq1FpdffjmrVq3CuikLS+GBPwtdtC8HnziKfuN68+Y9+zmBf/ibRKJ/qQNZE12XqPZA1jShLXtaChc+cC6HHn8wjionKPjxs+U8e/sr5vW0Eyzv178/A7/Pzyt/fGu/+z5wTD+6FXTlu/d+BE1jyMEDOPbCGTx6+fwGtTP68GGce8ep3HbsH7jry6u598jHMPxGs6/zJ354gCsm3QZK8avfncZL9/1n/9qhaetpv2uas6320Kf9fAs+9tojqS6p4esXl+zX44SIx9/VhW9oBX379uXFF19scntNPvy9YcMGLrvsMmbPns306dNDXwfKtGnTAPB3jj8BqxD7o2R7GV0LElxjuy7heysOVE1D+1TXY1qipgX6dN3Tl5LVOZOLR13PpeNu4qrDbsdZ5cJmt9Wz7MY/v4Fj+3HYiRNCt69fujlxoKyjnUbV7UdNMFAC/Op3pzWuT01YT41bXoLHtMTyWnOfGrFPp2tBLiVRl34VorGOvPIQAKZMmdIs7TX58PcjjzzCddddx4MPPsjjjz/Ou+++i2E04KzrZjJ16lSeeuopVCcPymKg+Zth4nPRYe3bUUqXPrlo9ZwjFdf+HnZr6ZrmXl59A7iDNfW1t5996tG/G4edOIGze/8Wt9McP+11e3n5/v+E+nTFYxcwbNJgUlJT2LR8K49c9BRejy+ivUNmj+XXd52ONcWKz+vnscvns3HZFgAOP+1QzrntFNDAVePmttn3c949Z5KaYWfIwQP5+Lkv2LxiG+fecSq3HHMfACdddSzHXXQ0hmGwa0MR953xcIPWU9denbn+n5fRJT8Xr9vLE1c/y5ofNjD6iOFccP/ZFG4pZsjBAyjaUszdp/4Fr9tLj37duPXFq0jvlM7qRWs5ZPY4rp16J/t2lfKx5zVmp5zFpY+ch8Vq4e8/PUTFvkpuOea+0H1oGiOmDOU3953FjdPvBuDSR85j4rHjKS0sY+/OEnas2w1KkZWbyVVPXET+gO7Y7FZevv9Nvn7z+0b97eqsaeg/WTNvT22qT3F0Lchl3zYJlaLplKb4/nvzf7vVhEqfz8eQIUPw+Xykp6dz1llnceWVV3LOOec0R//q1adPH/r378+WLVswurixFO//1QuECKoucaAMg6y8TCqLq+t/QEfSgm+Udek3og+Fm/aYh70TLO9fd78ROvP18kd/wzHnH8kHT38eLALME2iumXInSikGjevPVfMu4popd1AwtBcX/elXXDf1TkoKy8jqnImz2sULv3+dkVOH8sjFfwdg9BHDQ4sdf/RojjnvSK6d9jscleZULg1dB1c8egGLP/yJdx7/iCETBvK7N67n/CFXAzBgbD/+9H+PU7SlmPvevZVpp07ii1e+4fK//YZPXviSj/65gElzxnP8b4+Jaffv17/ASVcey6Xjb0q4noImzz2EweMHcPGo67Gn23lq6YPsWGde5u+yv57Pp88v5MdPl5OZk8G8xX/i5y9WUVXWzP8PSdqemry8JI4Ys6VayeqSSemu8qT1QbQfRq6b6upqunTpwvDhw+t/QAM0OVRaAzPE9+jRgy+++IK8vDxKSkqa3LH9cfTRRzN//nz83VwSKkWT7dtWRl7fzhIqW5Hwod9HnDGZs289mazOmdx7+sOsW7KRyXMP4YRLjyElNYWMTunoeuwRi849crj1xavp1rcrhs+g56AeAIybMYpFb/9ASaG59yc0LUsdJswawyfPL8RR6WjwY4JGHzmCB8+bB8D6HzdRU+6g1+B8ADb+tIWiLcUArPtxIz36dwNg5LSh/OHsvwLwwwc/Ubkfy4vbhyOG8+Xri/D7/DgqHea40YBDjh3HgNF9uehPvwLAarOQP6AbVUvl/yHZuhbkUlFchc9z4M4MFu3XtCvGs3DhQmbMmIGlmS432eRQef7551NdXc3ll1/OI488gtPp5JprrmmOvjVYMFSqTh45C1w0WdGmvXQflMemJQ24RrNocVtX76DnoB6kZabirHbx1Rvf8tUb3/KXL+7GmmKle988/u/3Z3D5hFuo2FfJ3CtnM3BMv5h2rnriIj6c/zkLX1tEWmYqb5c+b97RiGnZmjqXW4xAaPa6a6fPMvwGFmv817KGLt4IuzpXir325b6u/uu6xg1H/Z6aipa/iIXYPz0G5VG0oY4pz4RoIGUxWLRoEQAzZ85stnabPABx0qRJZGZm0rdvXx599FGefvppDj300OboW4Pl5+czZswY0MDfzVX/A4SoQ+H6veQP6ZbsboiAoi3FfPvfJVz5+IWkpJrXBtY0jZRU87q9aVlpuJ0eqsqqsaelMOPcw+O2k56dzt6d5lGUOZccHbp92ecrmXLyJDr3yAEIHcp2VDpIy4x/5GPxR8uYdf5RpGenRzymIVZ8uZpjLzRPZhwyYSAZOens2lhU52NWfbOW6eeaJyVOmjOerNz4y3M53NjTaq+fXLxtLwPH9gNg6imTQrcv/3I1R545BYvVQnp2OoedMCHiuZ12/Qmh3+MFdJEc+UO6UbihONndEO2A0dWFx+OhoKCAIUOGNFu7jd5TWd+p57/+9a8b23SjzJ49m+XLl+Pv4cSyMx2tMbsfhACK1hdz6Gljk90NEebRS5/mgj+ewz9X/xVHhQOXw83PC1exeflWnNUuln+1mmdW/5Xi7ftYt2RjRLAKeuGu17jx2SsoKyrn+w+Whm7fvnYXz9z2Mg98bI63dFa5uO7w37Hsi1WccdNcnlj8Jz594Uu2rKrdc71swUo++9dXPLrofvxePzvX7+b+s/4as8yRU4fy0pYnyc7L5KUtT/Kvu9/giWue5fr5lzH7gul43V7+eM6joSumJPLUdc9z64tXc/xvj2HF/36htKgcR2XsGNO3H/uQx394gH07S7n9uD8w/5aXuOvfN7B3Rwlrl2wM1X373yWMPmI4T694mD1b97L8q19C9z15zXNc/uhveHr5w2i6xt4dJdwx54+08dnn2oUeQ7rx9YuLk90N0Q4MPL4n69at4/jjj2/WIy+Nnqfyueeeq/P+3/zmN43qUGO5XC5OOeUUqqursa7OwVJmP6DLF+2HzW7l1o8v48Hj/o7HWcfVfIRoAN2iR85T2Qj2tBQ8Li9KKUZMGcr1T/+WC0dc18w9Fa2Zpmvc9tFlPH7OC1SV1NT/ACESMDK9eMeWkpKSwn/+8x9ycnKare1G76k80KGxPqmpqRx77LH8+9//xsh3SKgUjeZ1+yjZUU6PQXlsX7k72d0Rgv6jCrh+/mUopfB5fDz0myeS3SVxgHXpnYPH5ZVAKZps5u2H8uGHH3LkkUc2a6CEZppS6KOPPmLz5s14PLXX4L7ppjjTWrSwuXPnmqEy14NK9aG5mvz0RAe1e+0eeg3vLqFStAprF2/kkjE3JLsbIol6DevB7rV7kt0N0cYpm5/PPzenW5s7d26zt9/kE3UefPBBNm/ezKJFixgwYACbNm0iJSV2PNOBUFBQYJ4kpIGvt5y5KBpv+8rd9BnZM9ndEEIIAApG92T7ysJkd0O0cac/NguPx8PIkSMZOXJks7ff5FC5ceNGrrnmGtLT0zn11FP529/+xrZt25qjb43yq1+Zc6sZ3ZyoFJnLSzTO9hW7KBgtoVII0Tr0GdWT7St2Jbsbog1TFoN33nkHgHPOOaf5p0ajGUJlcK9kSkoKlZWV2Gw29uxJ3i760aNHM3r0aNDB30v2VorGKdlehm7R6dyrU7K7IoTo4NKy7HTu2UkOf4sm+c3zp1BTU0O/fv2YPHlyiyyjyaFy+PDhVFVVMXfuXC688ELOO+88xo0b1xx9a7Tg3kp/DyfKeuCuQy7aD6Vgx6pC+oySvZVCiOTqM6onhRv2ypV0RKMpXfHvf/8bMPdSxrvqWHNo8pkswavnzJkzh4MPPhiHw8GAAQOa3LGmmDRpEoMHD2bDhg34e9dg3ZqV1P6Itmn7it30HdOL5R+vSXZXhBAdWMHoXmxfKYe+ReOd99xc5s+fT35+PkcffXT9D2ikRkdVpRRutzv0+9q1a9m7dy81NTU4nbGT8h5ImqZx0UUXAeDv6UDZ5dOd2H+bf9zOgAkFye6GEKKDG3hIAZt/3JHsbog2SlkNXnnlFQAuvPBCrNaWmxmn0aHyH//4B6+//nro99/97nf885//5Mknn+Sll15qls41xaGHHmoehtfBV1Cd7O6INqhoQzEpqTa69MlJdleEEB1Uek4aXft2Zvty2VMpGueUv82gpqaGQYMGteheSmhCqFyyZAlnn3126Pfs7GweffRRnnjiCX7++efm6FuTaJrGb3/7WwCMbi6MdLkyitg/SsHmpdsZeEjfZHdFCNFBDTi4gB0rd+N1+5LdFdEGqRQ/b731FgCXXHJJi42lDGpS6zabLfTzueeeazao67hcrqb1qpkMHz6co446ypy3sn81Crl2rdg/m5bIIXAhRPIMPKSATUuSN02faNum3TYGj8fDmDFjmDRpUosvr9GhsqamJuIKOtOnTwfA7XZTXd16DjdffPHF2Gw2VK4Ho4u7/gcIEWbzku30H98b3dKyn+6EECKegYcUsGnx9mR3Q7RBRicPCxYsQNd1rrrqqhaZlzJao98pDzvsMB566KGIk3KcTiePPPIIU6ZMaZbONYfevXuH9qL6BlShLDLFkGi4iuIqKvZU0Xdsr2R3RQjRwfQYlIema+zZtDfZXRFtjNIU+XPMmW9OOukkhgwZckCW2+hQeemll+L3+znllFO48MILueiiizjllFMwDCM0lrG1OPfcc+nZsyfYDfx9apLdHdHGrP16E8OmDUx2N4QQHczQwwey9pvNKBm5JfbTBS+ewvbt28nJyeHCCy88YMtt9Hnldrudu+66i927d7N161YA+vXrZ4a3VsZut3PNNddwyy234O/lQC9ORXfY6n+gEJih8qw/nsCHf/sy2V0RQnQgQ6cN5LOnvkl2N0Qbo+x+XnjhBQAuu+wysrIO3FzdTR4o1rNnTyZPnszkyZNbZaAMOuyww5g2bZp50s7gSpQmH/1Ew+xeV4xS0POgbsnuihCig8jNzyanRzZbf5L5KUXDKRQjf1uA0+lk9OjRzJo164Auv0OdfXDdddeRlZWFyvLh7y2HwUXDrf1mE0PlELgQ4gA5aNpANny3Bb9PzgMQDWf0cPLTTz+RmprKrbfe2uJTCEXrUKGya9euXHvttQD4C2owMmTuStEwa/+3keFHDk52N4QQHcTwIwax9utNye6GaEOU3Yd1pJlrfvvb39K7d+8D3ocOFSoBjj76aI444gjzMPgQOQwuGmbrz7uwZ9rJH5KX7K4IIdq5nB7ZdB/YlfXfbkl2V0QboVAMu6g3LpeLcePGcfLJJyelHx0uVGqaxg033EBOTg4qw4e/b+uZU1O0XspQrFqwjlEzhya7K0KIdm7UzINY+/UmuYqOaLD/e/5Eli9fTlpaGrfccssBP+wd1OFCJUBOTg4333wzAP7eDvydZVJ0Ub+Vn65l1NEHoektP4GsEKLjGjVzKCs+W5fsbog2wsj28OyzzwJw7bXXJvWk6Q4ZKgGmTp3K6aefDoBvcAXK7k9yj0Rrt3tdMW6Hh37jDvw4FSFEx9B9YFfSO6WyZalcRUfUT1kNcmZYMQyDWbNmceyxxya1Px02VII5gfvQoUPBpvAeVCHjK0W9Vn62jtHHyCFwIUTLGD1rKKu/WI/hl/cjUTeF4uDrBrF371769OnDddddl+wudexQabPZuPvuu8nMzERle2V8pajX8o/XMPyIQdjTU5LdFSFEO2Ox6oydPZxlH/yS7K6INuD8f53Ed999R0pKCvfccw/p6enJ7lLHDpVgTt5+2223AYHxlXnOeh4hOrLyokq2ryxk1MyDkt0VIUQ7c9DUgZQXVlK0Ua71Lerm7+xm/vz5AFx99dUMGjQoyT0ydfhQCTBt2jR+/etfA+bVdoxMmb9SJLb03ZUcfOKoZHdDCNHOHHziSJa+tzLZ3RCtnJHmI2WCB6UUc+fO5cQTT0x2l0IkVAZceOGFTJ06FXTwDitHpciJOyK+9d9uIbNLhly2UQjRbHJ7dqLXsB6sWrA+2V0RrZiyGHSfm4bD4WDMmDFcffXVye5SBAmVAbquc+edd9K/f3+wG2aw1GWgtIhl+A2WfbCag+fK3kohRPMYf8JIVn2+Do9TjpSJ+JSmGHN1P3bu3En37t257777sNlsye5WBAmVYdLT03nggQfo1KkTKsuHb0gFCgmWItbSd1cycvoQ0rLsye6KEKKNs6ZYGH/8CH78rxz6FvEpFEf/YQJLliwhNTWVP/7xj+Tk5CS7WzEkVEbp2bNnKP0bXd34BlRJsBQxKvZUsXHxNg6eOzrZXRFCtHFjZg2jeFOJnKAjEvIX1PDhhx+i6zp33303gwcPTnaX4rImuwOt0dixY7nzzju5++67MXo6MXwWbLuykt0t0cp8/++fOePe4/jh38vw+4xkd0e0UrpFj/guRDhNg0PPGM/n//hGthERl69bDf6CGgBuuOEGJk+enOQeJaYppWQ3XAJvvvkmjz76KACnnnoqEyZMSHKPhBBCCNFR/PLLL7z00ksopTj//PO54IILkt2lOkmorMff//53XnnlFVCQsj4XS2lqsrskWpHhRw1mytkHM/+S15LdFdFK6RadOxdcyf0z5mH4ZY+2iHTuX+ay7uvNMp5SxPB3cqPGVOH1ejnuuOO45ZZb0DQt2d2qkxz+rsdvf/tbSktL+fjjj/EMLsO6JgdLmZycIUy/LFzP0ZdMod+43mz+Ua7VKxIz/IaEShEhf0ge+YO68dpt78m2ISIY2R70cQ48bi9Tp07lxhtvbPWBEtrYiTqbN2/m8ssv56qrruLmm2/G4XAAsGDBAi677DKuueYa9uzZA8B3333H5ZdfzgcffNCkZWqaxs0338z06dNBB9+wcowcd5Ofi2gfDL/im5eXcMR5E5PdFSFEG3P4eZP47o2f8Lp8ye6KaEWMLA/WSS7cbjeTJk3i7rvvxmptG/sA21SoLCgo4Mknn+Txxx9n2LBhfP311/h8Pt544w0ee+wxLrroIv71r38BZqicN28ea9eubfJyrVYrd955J9OmTTMnRx9ejtHJ0+R2Rfuw7MNfyO3Zib5jeyW7K0KINqL7wK70G9ubxW8tT3ZXRCtiZHixT/HidDoZP348999/PykpKcnuVoO1qVAZntRdLhcFBQXs3LmT/v37Y7PZGDVqFJs3bwZg4sSJXHHFFRx0UPNco9lqtXL33XebZ11JsBRh/F4/37zyI0ecNynZXRFCtBHTfj2RH/7zM+4aeR8RJiPTS+rhXqqrqxk9ejQPPPAAdnvbGm7XpkIlwJIlS7jwwgtZtmwZvXr1oqqqivT09ND9fr95ecWpU6fy1FNPcfzxxzfbsm02G/fccw8TJ04Ei8I7ogx/rhwKF/DTe6vI69+FPiPzk90VIUQr17VvLoMm9uX7fy9LdldEK2Fke7BNdlFVVcWIESN48MEHSUtLS3a39lubCJWvv/46V199Na+//jqHHHIIzzzzDEceeSTvvvsuWVlZobGVABaLpUX7Yrfb+cMf/hDaY+kbVo6/i6tFlylaP5/Hz7ev/siRFxya7K4IIVq5I39zKIvfXo6rWnZKCDA6ubFMdOJwOBg3bhwPP/wwGRkZye5Wo7SJUHnmmWfy2GOPcfLJJ4duy8jIIC0tjd69e7N161a8Xi8rV65kwIABLd4fu93O/fffX3vyztAK/N2cLb5c0boteXsFXQs6M2BCQbK7IoRopfKHdGPAhAK+fXVpsrsiWgF/rhvtYAcul4tJkybx5z//OeLoa1vTNk4nCvjxxx959dVX0XWdnJwcbrvtNqxWK6effjpXX301KSkp3H777QekL1arld/97nekpqby4Ycf4htSiS3dgrG17QyoFc3L5/Gz8NnvOPrSKcy/eDsyA6wQItrRl07hm5eWyF5KgT/PiRpeg8fjZ9q0afz+979vUyflxNOmQuXkyZPjXp5oxowZzJgx44D3x2KxcPPNN5OWlsabb76Js3cZFpWOZVsmGq1/PinR/JZ/vIbJZ45nxPQhrFqwPtndEUK0IgMmFNC1oDOv3vpusrsikkih8Pd24O9XDX6YOXNmaCdZW9cmDn+3Zrquc/XVV3PhhRcC4O/jwDekEqXJbqqOSBmKz/+xiOkXT8ZilX8vIYRJ02DmZVNZ+Ox3+Dz+ZHdHJIlC4RtQZQZK4Oyzz+aOO+5oF4ESJFQ2C03TOO+887jtttuwWCwY3Vx4R5ShLHKFhI5o/bdbqNpXw4STRie7K0KIVmLUzKFYbBaWf7wm2V0RSaJ0xaTbDsLo6UTTNK666iouu+wydL39RLH280xagWOPPTY0DYDK8eIdXYqyyyfSjuiTx7/iiPMnkZHT9qaEEEI0r5Q0GzMvm8onj3+FMuQoVkekbH4GX5zH119/jc1m4+677+b0009PdreanYTKZjZx4kTmzZtHly5dUBl+PGNKMbJkctuOZve6YtZ8tZEZv52S7K4IIZLs8PMmsXN1EZuWbE92V0QSGBleck7QWb16NZmZmTz88MMcddRRye5Wi5BQ2QIGDx7M3//+dwYNGgQpBt5RZfi7y5RDHc2C+d8ydNpAeg3rnuyuCCGSpEufXCbMHcUn8/6X7K6IJPB3cWE5zEFxcTF9+vThH//4B2PHjk12t1qMhMoW0r17d5544gmOOOIIcy7LwZX4+lehkEMfHYWj3MnCZ77juGuPQpPJAITokI695gi+e/0nyosqk90VcQApFL4+1fiGVeByuZg4cSJ///vf6dOnT7K71qIkVLagtLQ07rnnHi644AIA/L0ceEeUo6xyAk9HsfTdlVhsFsYdPzLZXRFCHGBDpw2kS59cFr3yY7K7Ig4gZTE47I5h+PvWAHD66afzpz/9iaysrCT3rOVJqGxhuq5z/vnnc99995GamorK9eAZW4KR6U1218QBYPgV7z/8BUf/dgqZXdruVRKEEPsnNdPOcdcdxYd/XShTCHUgRrqXbqfb+eqrr7Bardx8881cddVV7WbKoPpIqDxAjjjiCJ566il69eoFqQbe0aX48x1yOLwD2Lm6kBWfruW4a9vnwGwhRKyZl01l67KdbPh+a7K7Ig4Qf54T/bAadu7cSbdu3Zg3bx7HH398srt1QEmoPIAGDhzI/Pnza8dZDqxCjaiW+Sw7gC/mf0vPg7oz7PCBye6KEKKF9Rvbm6HTBvLx418luyviAFCawjuwEt9Blbjdbg455BD++c9/Mnz48GR37YCTUHmAZWZmcu+993LllVdisVjw5jrwjinFSJfD4e2Zx+nlvb8s4Ljrp5OaaU92d4QQLcSaYuGEm2fw8eNf4SiXWT/aOyPVR/8LcjHyzQnNzz//fP785z+Tk5OT7K4lhYTKJNA0jTPOOIPHHnuMvLw8VLof79hSfHI4vF3btHgbmxZvY9aVhye7K0KIFnLURYdRsrOclZ+tS3ZXRAtSKPzdnFinOVi3bh3Z2dn8+c9/5oILLsBisSS7e0kjoTKJRo0axTPPPMNhhx0GOvgHVuEbXo6yyaDu9urjx75i4CEFDJ0mh8GFaG/6je3NuGNH8P5DC5LdFdGClMVgyu9G4BtSidPpZNy4cTz33HNMmjQp2V1LOgmVSZaTk8Of/vQnrr32WlJSUjA6e/CMK8Wf605210QLcFW7efuPn3LCTTPkbHAh2pHUTDsn33kMHzzyBZV7q5PdHdFCjCwPuSfpLFy4EIvFwiWXXMIjjzxCXl5esrvWKkiobAU0TeOUU05h/vz5DBgwAFIMfCPK8Q6oROlyOLy92bJ0Bys+XcvcW49JdleEEM3kuOuOZOuynaxeuCHZXREtQGkKX98q/OMq2LNnD7169eKJJ57gV7/6VYc+3B1NQmUr0r9/f/7xj39w2mmnAWD0dOIZV4KRLdcOb28WPL2I7LxMDjl5dLK7IoRoopEzhlAwqhcf/u3LZHdFtAAjw0uvX2Xg7+PAMAxmzZrFM8880yHP7q6PhMpWxm63c/XVV/OXv/yFbt26QZof76gy8xKPstey3fB5/Lx138dMv3gyPQbJYRMh2qrcnp047rqjePsPn+CukR0A7YnSFL6CaowJFWzZsoXc3Fz+8Ic/cMcdd5CeLsOX4pFQ2UpNnDiR559/njlz5oAWuMSj7LVsV/Zs2sfnf1/E6fcehz0jJdndEULsJ2uKhTPum8N3r//EtuW7kt0d0YyMDC8F52XjL6jB7/czffp0XnjhBaZNm5bsrrVqEipbsczMTG655Rb+/Oc/m1MPBfdaDqiUCdPbiaXvrmTXmiJOvOXoZHdFCLGfZl11BNWlDr55aUmyuyKaidLNsZPGhAo2btxIp06duOeee7j77rs77NyT+0NCZRtw6KGH8vzzz3PccceZey17OvGML8HfxZXsrolm8P5fvqBb/65MPHVMsrsihGigUUcfxJDD+vP2/R+jZGRSu2DkuOl6mhV/Hwd+v58jjjiCF154gaOOkkvsNpSEyjYiKyuLW2+9lYcffti8frjdwDesAv+oSlSKzGvZlnmcXt743fscdeFh9B7eI9ndEULUI69fZ467/ij+c/eHOCrkw31bp6wG3iEVeEeWs3v3bvLy8vjjH//IfffdR+fOnZPdvTZFQmUbc8ghh/D888/z61//GovFgq+TE8/BJfh6ytV42rK9W0v54OGFnPmH48nqmpHs7gghEkjLsnP2Ayey8Jnv2LGqMNndEU2gUPi7O0k9xo3RzYWmaZx66qm8+OKLTJ06Ndnda5MkVLZBdrudiy++mGeffZaRI0eCReEfUIV3bKmcyNOGrVqwjp8/+oWz/ngC1hSZ90yI1ka3aJx+7xy2/LSDxW8uT3Z3RBMYmV4GXtwF3+BKKisrGTRoEE899RTXXHONnNndBBIq27D+/fszb948brjhBrKyslCZPryjy/AOqZBD4m3UF/O/pbqkhrm3zkx2V4QQUWZdeTgWm4UP/7ow2V0RjaSsBt5BlfjGlbFmzRrS09O5/PLLefrpp2XeyWYgobKN03WduXPn8vLLL3PiiSeiaRpGN5d5SLx3DUqTQ+JtiVLw1n2f0H1gV6b+6pBkd0cIETD++BEcNGUgb9z5Pn6fzL7R1igU/nwHKUc7MXo4UUoxa9YsXnrpJc466yysVmuyu9guSKhsJ3JycrjxxhuZP38+o0aNMg+J96s2zxLv7JLxlm2I2+Hh1dve47AzxjHiqMHJ7o4QHd7AQwqYedk0Xr3tXWrKncnujthPRo6bXr/OwDewiurqagYPHswTTzzBHXfcQdeuXZPdvXZFQmU7M2TIEObNm8edd95Jly5dIM2Pb3gF3lFlGJneZHdPNFDZ7gpevfVdjr9pBn3H9kp2d4TosHoMzuO0u4/jzXs+Ys+mfcnujtgPRrqX0dcV4B1ZzpYtW8jKyuL666/n6aefNne+iGanKSUzbLVXDoeDl19+mTfeeAO32w2AvteOdWsmmlt29bcFB00ZwNxbZ/LcVf9m79bSZHdHNIJu0bnry6u598jHMPxy2LQtyemRzYVPncGCp7/l549+SXZ3RAOpFD++gmpUvhulFFarlVNOOYX/+7//Izs7O9nda9dkT2U7lp6ezsUXX8zLL7/Msccea463zHOb4y37V6Gs8gbX2q1btJkv/vktv/rLSTLVkBAHUFqWnXMfOoklb6+QQNlGKIuBr6Aa/fBqjB4ulFIcddRRvPjii1x55ZUSKA8A2VPZgWzcuJGnnnqKJUsClxTzaVh2pWPZnY7ml88Xrdn0iydz0JQBPH/1f3BWymTLbYnsqWx7UtJs/Prhk9mzuYT3/7Ig2d0R9VC6eRJO5lgLFRUVAIwYMYIrrrjCnHZPHDASKjugxYsX89RTT7Fp0yYANJ+OfU829n1ZuKpknsvWas4N0+k1tDsvXPsm7hr5O7UVEirbFmuKhXP/fBI15U7euu8jDL+8RbZWSlMY3Z3kHGpn3z5zvGtBQQEXXXQRRxxxBJqmJbmHHY+Eyg7KMAwWLlzIs88+y44dOwDI6ZRD9VI/+p40NCX/jK2NpsHc246hc+8cXrrhbTxOOfGqLZBQ2XZYbBbO+sPx+H0Gb/zuA/l7tVIKhZHnIu/IDAoLzasa9ejRg/PPP59jjjlGpgdKIgmVHZzP5+PTTz/l+eefp6ioyLzRpWPdkYFeLOGytdEtGqfedSxpnVJ55eb/4vPIJPetnYTKtkG3aJx293GkpKfw2m3vyv9WK6Q0M0zmz+gU2hnSuXNnfv3rX3PCCSeQkpKS5B4KCZUCAI/Hw/vvv8+//vUvSksDZxm7daw7M8w9l4aEy9bCYtU54/7j0XSNN+58X978WjkJla2fbtE46fZZZHfL5OUb38Hr9iW7SyKM0hRGNyd5h2eG9kxmZ2dz9tlnc8opp5CWlpbkHoogCZUigsvl4t133+XVV1+lpKTEvNGjmyf0FKahGXJCT2tgTbFw5v3Ho1t0Xrv9PXkTbMUkVLZuukXn1Ltmk9klg1du/i9uh4xXbi2Ubo6ZzD00lb179wKQm5vLmWeeyUknnSTX6G6FJFSKuNxuNx999BEvv/wye/bsMW/0Bs4WL5SzxVsDi83Cab8/lrTsVF655b8yxrKVklDZellTLJx+z3HY0my8euu7eF3y4aw1ULqBP99Jp4NTQkfOunbtytlnn80JJ5xAampqknsoEpFQKerk9Xr59NNPeemll9i1a5d5o1/DUpRmTkXktiS3gx2cbtE5+c5Z5PTI5uWb3sFV7U52l0QUCZWtk81u5cw/noDhN2QYSSuhbH78PR2kD7dQVVUFmCfgnHvuucyePRu73Z7kHor6SKgUDeLz+fjiiy949dVXQ1MRoUDfZ8eyKwO92pbcDnZgmq5x4i1H031gV16+6b/UlDmS3SURRkJl62PPSOHsB07EWeXiP3d/hN8rgTKZjHQf/l416L18+Hzm3uJevXrxq1/9ilmzZsnZ3G2IhEqxX5RSLFmyhNdee40ff/wxdLtWbjPDZVkKGnJSz4GmaXDMlYdz0OQBvHTj25Tuqkh2l0SAhMrWJatrBr/6y0kUrt/Luw9+Ln+TJFEoVCcPvt4OVG7tONZRo0Zx5plnMmXKFCwWORLW1kj8F/tF0zQmTpzIxIkT2bhxI6+//jqff/45/hwvvpxytBoLlsJ09OJUOannAFIKPnn8f1TtreaCJ87glVv+y+51xcnulhCtSte+ufzqLyez4tO1fDH/22R3p0NSmsLo6qLfnG5s3LgRAF3XOfzwwznzzDMZMWJEknsomkL2VIomKy4u5s033+Tdd9+lpqYGAM2vkVKSScq+LDylcmjpQBo18yCOu/Yo3rznIzYu3pbs7nR4sqeydegzMp+zHjiBr577gcVvLU92dzocZffj7+Ega1QK5eXlAKSmpjJnzhxOP/10evbsmdwOimYhoVI0m+rqaj788EPeeecddu7cGbpdL7djLUxHL7fLofEDpP/BfTjt98eyYP63/PTeqmR3p0PTLTp3LriS+2fMk1CZJMOPGsyc64/i/b8sYM1Xm5LdnQ5DoTA6efD1qIGuXgzD3P7z8vI46aSTmDt3LtnZ2UnupWhOEipFszMMgx9//JG33nqL7777juAmlpuby6GHHsrBBx9MRkZGknsphBCiJbhcLpYuXcr3338fuiY3wPjx4zn55JOZMmWKnHzTTkmoFC1q9+7dvPPOO3zwwQehKSIwwFKSiqU4Hb1STuxpSek5aZx+z3H4vD7evPtjmXIoCWRPZXLYUq3MvW0mufmdeOPO96kork52l9o1hUJlevF1c2Drq3C5XACkp6cze/ZsTjrpJPr165fcTooWJ6FSHBAul4sFCxbw1ltvsWHDhto7nBYse9KwFKeieeRMv5ZgserMuWE6fcf04tVb32Xf9rJkd6lDkTGVB16nblmc/acTKd1Vztt/+EQmNW9Bymrg7+akYEYeW7ZsCd3ev39/Tj75ZI455hi58k0HIqFSHFBKKdatW8f777/P559/jsMRmFNRgV6agr4nDb1Uxl62hEmnjeXI3xzKew8t4JcvN9T/ANEsJFQeWIMm9uXkO2ex5O0VfPX898g7XPNTKFSOB38PJ3oPf2huSbvdzpFHHsmcOXMYM2YMmiav4x2NhEqRNE6nky+//JIPPviAFStW1N7h0bHsSUXfm4bukHE3zalgdE9Ov+c4Vi/cwGdPfo3fJyGnpUmoPDA0XePI30xiwkmjefv+T9n4w9Zkd6ndUXYf/u4uukzIoLi4dsqygw46iOOPP54ZM2aQmZmZxB6KZJNQKVqFbdu28cEHH/Dxxx+HppsA0Kqt6MWpWPamonnl8HhzyMhN59TfzyYl1ca/7/qQiuKqZHepXZNQ2fIyctI49ffHkpKewr/v+oCKPbJNNxdlNTC6uvB3c6GyvaHbs7KyOOaYY5gzZw6DBg1KYg9FayKhUrQqXq+XRYsW8cknn/D999/j9wfmuFSgladgKU5FL7HLxOpNZO7VOZQJJ43ivw98xvpvt9T/INEoEipbVr+xvTnlrtms+WoDnz4he9+bg9IVRmc3RjcnWp4/9Dqs6zrjx49nzpw5TJ06Va7FLWJIqBStVnl5OV9++SWffPIJq1evrr3Dr2GrSCOlLBNrVaqc0dwEAyf25aTbj2Ht15v4dN7/8LrlhIbmJqGyZVisOkddNJnxc0bw/sNfyDjhJgpeNtHfzUVqf712vDswZMgQZs6cyYwZM+jatWsSeylaOwmVok3YtWsXn332GZ9++mnExOoZ6Rk4t/jNw+MVKWhKBobvr/ScNE68+Wi6FuTy5r0fU7heLu/YnCRUNr+ufXM59a5jcVa6eOePn1K5V6YLagwzSHrxd3GRMzKN0tLS0H09evRg5syZzJw5U6YCEg0moVK0KUop1qxZw6effsrChQspKwubHseroZfa0felopdLwNxf448fwczLp/Htq0tZ9MqPGH55aWgOEiqbj6bBISePYfpFk/nqhR/4/o2f5Ozu/RTaI9nVTafhqRGvoVlZWUyfPp2ZM2cycuRIdF2GGYn9I6FStFl+v58VK1awcOFC/ve//0V8ysanoZdIwNxfnXvncPLtx2CxWfjvnz5jz6Z99T9I1ElCZfPo0ieHE28+GnuGnbf/8Ilsm/tBabVBMuugFCoqKkL3ZWVlMW3aNI488kgOPvhgbDZbEnsq2joJlaJd8Pv9rFy5ki+++CJ+wCxLMfdiltnRfPLpuy6arjHx5DEceeGhLH5zOf/712L8Xn+yu9VmSahsGt2icdiZ45n2q4ksevVHFr2yVNZjAyiLgZHjwejiJnNQCpWVlaH7OnXqFAqS48ePl0smimYjoVIktGzZMl544QX8fj9nnHEG06ZNY8GCBfznP/8hJSWF22+/ne7du/Pdd9/x4osvMmfOHObMmZPsbocC5sKFC/nqq68iA6YCrcKGXmrHUmJHc8uLaSI5+dmccNMMsvMyeffBz9mxqjDZXWqTJFQ2XveBXZl760z8PoN3H/yMvVtL639QB6bsfozObvyd3Vi7Kbze2imAcnJyOPzwwznyyCMZO3ZsqwqSbfW9RsRqPVuVaFXcbjevv/46Dz30UOhwiM/n44033mDevHmsXbuWf/3rX9x000189913zJs3j7/+9a+t4h/dYrEwduxYxo4dyzXXXMPatWtZtGgR33zzDVu2bEHlePHnePEPqEarsZh7MEvtaFU2uZJPmPLCSl68/m3GHTecsx84kXWLNvP537+hptyZ7K6Jdi41085RFx7K6FnD+Oq5H/jhzZ9Rhuz/iGZeb9tnTv/T2Y3KrJ29weuFXr16MXXqVKZMmcLIkSNbVZAMasvvNSJW69vCRKuwatUq7HY7t956K6mpqVx//fVUVVXRv39/bDYbo0aN4sknnwRg4sSJXHHFFa3yn1zXdYYPH87w4cO5+OKL2b17dyhgLl++HCPDjz/Dgb+PwzzRpzwFvcyOXpYik60HLPvwF9Z+s5kZl0zhipf+jy+f/Z4f/7tCTuQRzU7TYMyxwzn6t1PY/OMOnvz1i1SV1CS7W62KshoYOW6MXA+5wzMoKande6vrOiNHjmTKlClMnjyZgoKCVn+pxPbyXiNMEipFXGVlZRQWFvLEE0+wdOlSnnvuOWbNmkV6enqoJjgh7tSpU5k6dWqyurpfevbsyemnn87pp59OVVUV33//PYsWLeKHH36gpqYGI8+NkWfOe6lVW82xmOV2tEpbhz7Zx1np4v2/LOCn91Zy3PXTGX/8SD7820K2r9id7K6JdiJ/SDeOu+4oUtJs/Pv3H7Lt513J7lKroFCobK85PjLXDdl+gqPWSkpcpKWlMXHiRCZPnsxhhx1GTk5Ocju8n9rre01HJaFSRHj99ddZtGgREyZMYNSoUdhsNsaPH89LL71EVlZWxIS4Fkvb3pOXlZUVmofN5/Pxyy+/8MMPP7BkyRLWrl2LyvThz/SZezH9GtbqVGyVafiKNTSnpUMeKt+9rphnLn2NcXNGcMa9c9ixupAF/1jEvu1l9T9YiDhyemQz/eLJDJrUl/+9sJjFby3v8GNPld0f2huZ1tdKTU3Y3loFAwYMYOLEiUycOJFRo0a1ySvbdKT3mo5EQqWIcOaZZ3LmmWdSUVHBvffeC8CGDRvo2bMnvXv3ZuvWrXi9XtauXcuAAQOS3NvmY7VaGT16NKNHj+biiy+mrKyMJUuWsHjxYhYvXkx5eTm+Tk58nZzQB3Dr6BUp5ld5Cpq747zoKQU/vb+aVQvWM/msg7no72excsE6vnrue6pLHfU3IASQlmVn2v9NZPzxI1n63koeP/t5nFUd8+pYKsWP0clj7o3s5IHU2lBdU+MmOzubCRMmMHHiRA455BDy8vKS2Nvm0VHfa9o7OftbJPTWW2/xxRdfoOs6t956Kz179ox7Rl57ZxgGGzZsYPHixfz444+sXr0aj8cTWeTSzfGYgaCpeTpOyMzsks6R5x/KyBkH8cObP/P9Gz912HAQj5z9HSklzcbEU8cy+azxbPh+Kwv/+R3lRZX1P7AdUbZgiPSiOnlQaZFTdlksFoYNGxbaG3nQQQe167118l7TfkioFGI/ud1uVq1axU8//cSyZctYs2ZNaMxPkOawoFXa0CtTzPGYrvZ/uLxrQS5HXnAoAyf2ZfGbyyVcBkioNIXC5Jnj2bFqNwuf/Z6iDXuT3a0Wp1BgNzCyPRjZgRCZHvl6oes6Q4YMYdy4cYwbN47Ro0dHjCkUoq2QUClEEzkcDlauXBkKmevXr8cwosKDR0evtKFV2cw9mTXWdnviT16/zhx+3iQGT+rH4rd+5rs3luGsdCW7W0nT0UOlPT2FiaeO4bAzxrN95W6+ev6Hdn19+dA0P9leVJYZJLFH/t01TWPQoEGhEDlmzBgyMzOT1GMhmo+ESiGaWVVVFStXrgx9rV27NvZwuR+06to9mXq1td1NYRQKl4f2Y/nHv/D9G8soK+xYhzmh44bKrK4ZTDptHAefOJJtP+/iq+e/p3B9+9szqawGKtOLke3FyPZg72HB5Yr8EGWxWBgyZAijRo1i9OjRjB07luzs7CT1WIiWI6FSiBbm8XhYt24dq1atYsWKFaxatSri2rshLh29OrA3s9qGVm1F87f9S0rm9uzEoWeMY+zsYWxcvI3vXvuJnb8UJbtbB0xHC5XdB3Zl8lnjGXr4IFZ/sZ7vXv+p3VwJR+nKDJCZXlSWFyPTB2mxlzDNzMxk5MiRjBo1ilGjRjF06FBSU1OT0GMhDiwJlUIcYEoptm/fzsqVK1m1ahVr1qxh69atxPwrqsDYzGobepWNVH8GFldK6LC5s7ptHVJOy7Iz4aTRTDx1LGW7K1j85nLW/G9ju7+ueEcIlbpFY8jkAUw8ZQw9BuWx5J0VLHl7eZucDSAt0wx/SlP4Uz24LDWBEOlDyzJih7ZgXrlm5MiRoSDZr18/dL3tfyAUYn9JqBSiFXA4HKxbt441a9awdu1a1qxZw549e2LqdF0nv0dP+vbuyw+vLzcPm9fY0Hxt5w3MYrMwcsYQJswdTefenVj2wS8sfXclZbvj7L1tB9pzqOzULYvxJ4xg3JyROMqdLHlnBSs+WYPX7av/wa2IshioDB9Gpo/J545j+85t7Crchc8X+zy6dOnCsGHDGDp0aOh7VlZWEnotROsjoVKIVqqkpCQUMNesWcP69evjHzYHc97MGitatc08CajG2ibOOO8xKI+D545i1NEHseuXIn76YDXrvtmEz9N+9l62t1BpsVkYfGg/xh03nH7j+/DLwg38+O5KdrWBIQ2hM7EzvKhMnxkkM7wR80KGy8zMZOjQoREBsj3MESlES5FQKUQboZRi3759bNy4kQ0bNrBhwwY2btzIrl0JLmdngOYMBEyHBc1hNb9aYdhMSbMx6uiDGHPscLr178Ka/21kxSdr2PrzLpTRtl+i2kuoLBjVk9HHDGXE9CGU7a5g+cdrWP7JGlzVrW/aKDM8+jEy/Kg0Hyo9+OUHS/ztqUePHgwaNCjiKz8/v9VfO1uI1kRCpRBtXE1NDZs2bYoImtu2bcPtTvBmb1AbMB0WM3i6At+N5L+B5uZnM+qYoYyZNQyb3crKBev45cuN7F5TRFt8tWrLobLH4DyGHzGIUTOHomkaKz5dw4rP1rJvW+u4LKfSFCrNj0o1A2MoPKb5IMFkCjabjX79+oWC4+DBgxk4cKAcwhaiGUioFKId8vv97Nmzhy1btrBlyxa2bdsW+p4wbAK4dfO65qGgGfZzEubV7Dm0O6NnDmXo4QPRLTprv97E2v9tZOvPu9pMQGtLoVLTNfqMzGfYEYMYOnUgVruVtV9vYuVna9mxcndSQr3SFCrVXxse02p/1tJU7AluASkpKRQUFNCvXz/69u1L//796devHz179sRqlSsUC9ESJFQK0YHEC5s7d+5k586dicdrAijMwOmyoLkt5vewn/HoLX5IPX9IN4YdPpChhw8iq0sGG3/YysbF29i8ZDtVJTUtuuymaO2hMiMnjQETChg4sS+DJvXFXeNh7debWPO/Tez6pbDFg6RCQYqBsvvN8Gg3At/N8Kinq7hnXIf6n5FB79696du3byhABsNje760oRCtkYRKIQQAlZWVoYC5Y8eOiO8ORz1TwxiA24LVZ0P3WNE9FjSvFV+lHzwWNLcOfq3ZgmeXPjkMmtiPgZP60m9ML8oKK9m0ZBubFm9jx6pCPE5vsyynObS2UGlNsdB7RD4DJ/Zl4CEF5PXtzPYVu9m0ZBsbf9hG8ZaSZl2eshioFANS/NiyLRgpPowUP0aKD7/Vi7L7oZ7JC9LS0ujdu3fcr5ycHBn3KEQrIaFSCFEnpRSlpaXs2rWLoqIiCgsLKSoqiviKvvZ5XH7QPBZzj6fHgubRwW1+17y6ubfTu//h02Kz0GdkPoMm9mXgxL7k9evMnk372LGykO0rd7F95W6qS5I3X2KyQ2V6ThoFo3rSZ1Q+BaN6kT84j5Kd5WYIX7Kd7ct37fcUQAplnvBiNQOjGRoNVEpgT2MgRKoUA6z1v8VYLBby8vLo0aNH6Cs/P5/8/Hx69+5Nly5dJDgK0QZIqBRCNInf72ffvn0xgXPfvn3s3buXffv2UVVV1fAGDcAbGTQ1r157m09H82m13716xHhPe0YKvUfkUxAIUb2G96CmzEHh+uLA114K1xdTU3ZgguaBDJXpnVLpMbgb+UO6kT8kj/wh3cjulsXuNUVsX1XI9hW72LmqEGdV5LhapQUCojXsu81A2YyY78GfE50IE09GRgZdu3YlLy+PvLw88vPz6d69O/n5+fTo0YOuXbvKOEch2gEJlUKIFudyudi3b18oaAa/greVl5dTVlZW/2H2RPzEhk2fuddTVzqZnTLJycumc49cuvbqTLeCruDXqN7rpKbYQWVRDeW7KindXkllcRU040lJLREqM7um07VvLrm9OpHdM5PsHulkdkvHYtcp3r6PvTtK2LerlLLicipLqzAwwBIWGi2RIXJ/AmI4u91Obm4uXbp0oWvXrqGvvLy80PcuXbqQnp7eLM9bCNG6SagUQrQabrc7FDDLysooLy+ntLQ09HNZWRlVVVVUVVVRXV1NVVVVnSdxNJZFt6DrFnRNQ1M6GKB8oPwK5QPDpzD8yryUZvAVVGnmCU1gfg8EUw2NUcccxMrP1pqHjc0bw74rCDxUt2joNg3NqqFbze+aJXAGtKZQysBv+PH5/NQurHlomkZGRgZZWVlkZWXRqVMncnNzycnJSfg9LS2tWfsghGjbJFQKIdoswzBwOByhoBn95XQ6cTgcOJ3Oen9uqy+Fuq6TlpbWoK+srCwyMzNDwTH854yMDLletRCiSSRUCiE6PKUUXq8Xj8cT+h78ine71+vFMAwMw0Aphd/vRykVui36S9M0dF1H1/WIn8N/D363Wq3YbDZsNhspKSlxvwd/Dn7JSSxCiNZAQqUQQgghhGgyOdYhhBBCCCGaTEKlEEIIIYRoMgmVQgghhBCiySRUCiGEEEKIJpNQKYQQQgghmkxCpRBCCCGEaDIJlUIIIYQQoskkVAohhBBCiCaTUCmEEEIIIZpMQqUQQgghhGgyCZVCCCGEEKLJJFQKIYQQQogmk1AphBBCCCGaTEKlEEIIIYRoMgmVQgghhBCiySRUCiGEEEKIJpNQKYQQQgghmkxCpRBCCCGEaDIJlUIIIYQQoskkVAohhBBCiCaTUCmEEEIIIZpMQqUQQgghhGgyCZVCCCGEEKLJJFQKIYQQQogmk1AphBBCCCGazJrsDgjRGiilcLlcye6GEELsl9TUVDRNS3Y3hAAkVAoBgMvlYtasWcnuhhBC7JdPPvmEtLS0ZHdDCEAOfwshhBBCiGYgeyqFiJKyuBuaCnze0nQ0XQNNB10DTUPTg/cFbtc00DW0YE3oPi30mNAXhN1W22boMdQ+Rmla7ce+sDZCt4c9Lvw2FWgmdJ8OELxdC90XfIwK3Ba6H2rb0AP1ocdELiPiMQRu0+PcF1FPRB9rb9Ni7ot5DJGPibif2sckWlbE7wn6EfOYutoN3a4iHh/dXuj+sLZU4HaiHoemwh5v3q+F3xeqDd6nQm1q4fWB2zVN1W5+gdtrNw8Vul9HhX437wM98Lt5n/l78HGh+zSFRu3j9MBtoS9U6HG6RsTttY8xamtR6JqBJXhf4PfatoxQe5aw9i2Yt1s0I+pxBpZgm9QuL1RPbXs65uN1zOWb95ntWQK3aRhYgo8n2A8DC5iPw1xO8LkFfzeXpQI/E7hPoQfWiwUNHbAE/tg6WuA2DYumoQdeDDQ0vB4Lp17cAyFaGwmVQkTza4GXd8xQSSAABt6ta+/TQK9NUJqZ0AKNBJOHXvtzTNrQYxOPpsXWh7dHVH3EfdE/h9UEw2RYqIy5LSwEhv8e3cXI+jiP0eu4L9HTiNduosfVdXuDl7V/bcYNsRGPa+ZQGe9+on9XobbD+xG+zMjHRIXQ0H3h96s47ak4y1IRX+GhsjaoBr4S3RcvbBIMo0QEveDvFiLvM0OlURvKtPBQZv6sa5oZ+ALfCf2shR5XG2DBotV+t0BYAIxzX6A983cVCKUqFCLNx6l6Q2V4e5bAfTqRtwUDrB543kK0RnL4WwghhBBCNJmESiGEEEII0WQSKoUQQgghRJNJqBRCCCGEEE0moVIIIYQQQjSZhEohhBBCCNFkEiqFEEIIIUSTyTyVQkSzKJQyJzw2513Uwr5rUROSB7+H/Uz4bSrs5zruC94eNmlh7RTVJLi99ruK+JmIxykAFby9tk2FBorQY8PvD7URMblieF/i/K4iuhS1PhJ8RdfWN3ckCW6v77665qKs677wZ1jn4+LNNxn+pRL0MfHk55FzS4bdF6pt/OTntf0Im6eSxs9Tqah9nNJU5Bfmd/M+Im43Qu0ZtctBgWaEzaepIu5XmhFqj4j2A9+Dywr8rgdqgt+BmNuMsLkhDa32u0HtPJVG4DaNRPNUaqEJyy3U/s2Cv+uBx0TPfdnwyc+1wJ9Fw+uJ938pRPJJqBQiimdicbK70DKC79lNEB1nhYDITctIZkcaLXzLlgN4QjSW/PcIAbhcrmR3QQghhGjTZE+lEIDdbg/9/N///pfU1NQk9qbtcLlczJ07F5D11lCyzhpH1lt8sh5EayKhUghA02oP6KamppKWlpbE3rRNst72n6yzxpH1JkTrJIe/hRBCCCFEk0moFEIIIYQQTSahUgghhBBCNJmESiGEEEII0WSaUqqJM9cJIYQQQoiOTvZUCiGEEEKIJpNQKYQQQgghmkxCpRBCCCGEaDIJlUIIIYQQoskkVAohhBBCiCaTUCmEEEIIIZpMQqUQQgghhGgyCZVCCCGEEKLJrMnugBDNzeFw8Nprr/HVV19RVFSEruv06dOH6dOnc+qpp2Kz2RrddmlpKa+88grfffcde/bswW63079/f2bPns2cOXPQNK0Zn8mB0xLr7Nlnn+X555+vt+6VV16hd+/ejeh18rhcLn7++WfWrVvH+vXrWb9+PXv27AHg/PPP54ILLmjyMtrjttaS6609b29CtBUSKkW7UlRUxNVXX01RUREAqampeL1e1q5dy9q1a/nss8/429/+RlZW1n63vW7dOm688UYqKioASEtLw+FwsGLFClasWMHChQt54IEHSElJadbn1NJacp0BWK1WsrOzE95vsVga1W4yrVmzhptvvrnF2m+v21pLrzdon9ubEG2FhErRbvj9fm699VaKioro0qULd9xxBxMmTMAwDBYuXMhDDz3Ehg0buPfee3nooYf2q+3q6mpuueUWKioqKCgo4M4772To0KF4vV7ee+895s2bx5IlS5g3bx7XX399Cz3D5teS6yxo5MiRPPbYY83c8+TLyspiyJAhoa/HH3+c0tLSJrfbXre1oJZab0HtdXsToi2QUCnajY8++ojNmzcDcN999zFy5EgAdF1nxowZKKW49957+eGHH1i6dCkHH3xwg9t+7bXXKC0txW638+c//5mePXsCYLPZOOWUU3A4HDz99NO89957nH766fTp06f5n2ALaMl11p6NHj2aDz74IOK2f/zjH83Sdnvd1qBl15sQIvnkRB3Rbnz88ccAjBs3LhSOws2YMYP8/PyI2ob65JNPQm0E3+TDnXLKKaSlpeH3+/nss8/2t+tJ05LrrD1ryUOo7XVbAzn0LER7J6FStAsul4tVq1YBcOihh8at0TSNSZMmAbBkyZIGt719+/bQyQTBx0dLT09n9OjR+912MrXkOhON0163NSFExyCHv0W7sG3bNgzDAKB///4J64L3lZaWUllZWeeA/qDg4eH62h4wYAA//PADW7dubWCvk6sl11m4LVu2cN5557Fr1y4sFgtdu3ZlzJgxnHTSSQwZMqTxT6Adaq/b2oEk25sQySN7KkW7sG/fvtDPeXl5Ceu6du0a9zF1KSkp2a+2a2pqcDgcDWo7mVpynYWrqKhg27ZtpKam4vF42LFjB++//z4XX3wx8+fP3+/22rP2uq0dSLK9CZE8sqdStAvhb6x2uz1hXWpqatzHtETb6enpDWo/WVpynQH07t2byy67jKlTp5Kfn4/VasXr9bJs2TLmz5/PunXrePHFF8nKyuKss85q3JNoZ9rrtnYgyPYmRPLJnkohRIs45phjOPvss+nTpw9Wq/n51WazMXHiRObNm8fQoUMBeO6556iurk5mV0U7INubEMknoVK0C+F7atxud8I6l8sV9zHJajuZkvm87HY7l1xyCQBOp5OlS5c2S7ttXXvd1pJNtjchDgwJlaJdCB/3t3fv3oR14WMCwx9Tly5duuxX2xkZGW3ijb4l11lDjBgxIvTz7t27m63dtqy9bmutgWxvQrQ8CZWiXejbty+6bm7OW7ZsSVgXvK9z584NPot5wIABMY+PJ3jmbr9+/RrUbrK15DoTjdNetzUhRMcgoVK0C6mpqaHJu3/44Ye4NUopFi9eDMAhhxzS4LYLCgro3r17nW07nU5WrFix320nU0uus4b45ZdfQj8HJ1jv6NrrttYayPYmRMuTUCnajdmzZwOwbNmyiDeQoIULF4YOewVrG2rWrFkAfPHFFxQWFsbc//bbb+N0OrFYLMycOXN/u540LbXOlFJ13u/xeELTu6SlpcnlH8O0122tJcn2JkTrIKFStBuzZ89mwIABKKX43e9+FxqMbxgGCxcu5KGHHgLMK5VEv6k8++yzHH744Rx++OFx38jPOussOnfujMvl4pZbbmHdunUAeL1e3nnnHZ555hkATjjhhDZ1LeaWWmfLly/nuuuu49NPP6W4uDh0u8/nY+nSpVx55ZWhEHveeeeRlZXVkk+zRVRVVVFeXh76Ck4k73a7I26Pnoapo25rQS2x3jrC9iZEWyDzVIp2w2q18sADD3DNNddQVFTEddddR2pqKoZh4PF4ABg8eDB33XXXfredmZnJgw8+yI033sjWrVu5+OKLSU9Px+Px4PP5APNQ5JVXXtmsz6mltdQ6U0qxdOnSUEi12+2kpqZSU1MTWl+6rnPuuedyzjnnNO+TOkAuvPBCioqKYm5/9dVXefXVV0O/z549m9tvv73B7bbXbS2oJdZbR9jehGgLJFSKdiU/P5/nn3+e1157ja+++oqioiKsViv9+/dnxowZnHrqqdhstka1fdBBB/HCCy/wyiuv8O2331JcXExqaioDBgxg9uzZHHfccaETX9qSllhnAwYM4PLLL2f16tVs3ryZiooKqqurSU1NpV+/fowePZoTTjiBgQMHttCzatva67bWUmR7E6J10FR9g1GEEEIIIYSoh3zUFUIIIYQQTSahUgghhBBCNJmESiGEEEII0WQSKoUQQgghRJNJqBRCCCGEEE0moVIIIYQQQjSZhEohhBBCCNFkEiqFEEIIIUSTSagUQgghhBBNJqFSCCGEEEI0mYRKIYQQQgjRZBIqhRBCCCFEk0moFEIIIYQQTSahUgghhBBCNJmESiGEEEII0WQSKoUQQgghRJNJqBRCCCGEEE0moVIIIYQQQjSZhEohhBBCCNFk/w8P8cCe7IkhUwAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "List_of_Maps = [mDisk,mNarrowBulge,mBroadBulge]\n", "List_of_Names = [\"Disk\",\"Narrow Bulge\",\"Broad Bulge\", ]\n", "\n", "for n, m in zip(List_of_Names,List_of_Maps):\n", " plot,ax = m.plot(ax_kw={\"coord\":\"G\"})\n", " ax.grid();\n", " lon = ax.coords['glon']\n", " lat = ax.coords['glat']\n", " lon.set_axislabel('Galactic Longitude',color='white',fontsize=5)\n", " lat.set_axislabel('Galactic Latitude',fontsize=5)\n", " lon.display_minor_ticks(True)\n", " lat.display_minor_ticks(True)\n", " lon.set_ticks_visible(True)\n", " lon.set_ticklabel_visible(True)\n", " lon.set_ticks(color='white',alpha=0.6)\n", " lat.set_ticks(color='white',alpha=0.6)\n", " lon.set_ticklabel(color='white',fontsize=4)\n", " lat.set_ticklabel(fontsize=4)\n", " lat.set_ticks_visible(True)\n", " lat.set_ticklabel_visible(True)\n", " ax.set_title(n)" ] }, { "cell_type": "markdown", "id": "915bc5ee", "metadata": {}, "source": [ "## Instantiate the COSI 3ML plugin and perform the likelihood fit\n", "The following two cells should be run only if not already run in previous examples..." ] }, { "cell_type": "code", "execution_count": 13, "id": "5b3abf0b-7631-419c-b5b7-a31dbfe1b65c", "metadata": {}, "outputs": [], "source": [ "# if not previously loaded in example 1, load the response, ori, and psr: \n", "response_file = \"SMEXv12.511keV.HEALPixO4.binnedimaging.imagingresponse.nonsparse_nside16.area.h5\"\n", "response = FullDetectorResponse.open(response_file)\n", "ori = SpacecraftFile.parse_from_file(\"20280301_3_month_with_orbital_info.ori\")\n", "psr_file = \"psr_gal_511_DC2.h5\"" ] }, { "cell_type": "code", "execution_count": 14, "id": "522db694-3a1d-4d0d-a3d9-0e028bb5cbcc", "metadata": {}, "outputs": [], "source": [ "# Set background parameter, which is used to fit the amplitude of the background:\n", "bkg_par = Parameter(\"background_cosi\", # background parameter\n", " 1, # initial value of parameter\n", " min_value=0, # minimum value of parameter\n", " max_value=5, # maximum value of parameter\n", " delta=0.05, # initial step used by fitting engine\n", " desc=\"Background parameter for cosi\")" ] }, { "cell_type": "markdown", "id": "34287711-a61b-4496-bc3e-b5f2f9e02298", "metadata": {}, "source": [ "We should re-run the following cell every time we set up a new fit:" ] }, { "cell_type": "code", "execution_count": 15, "id": "5ca19bc5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "... loading the pre-computed image response ...\n", "--> done\n", "CPU times: user 1min 56s, sys: 37 s, total: 2min 33s\n", "Wall time: 2min 51s\n" ] } ], "source": [ "%%time \n", "\n", "# Instantiate the COSI 3ML plugin, using combined data for the thin disk\n", "cosi = COSILike(\"cosi\", # COSI 3ML plugin\n", " dr = response_file, # detector response\n", " data = data_combined_thin_disk.binned_data.project('Em', 'Phi', 'PsiChi'),# data (source+background)\n", " bkg = bg_tot.binned_data.project('Em', 'Phi', 'PsiChi'), # background model \n", " sc_orientation = ori, # spacecraft orientation\n", " nuisance_param = bkg_par, # background parameter\n", " precomputed_psr_file = psr_file) # full path to precomputed psr file in galactic coordinates (optional)\n", "plugins = DataList(cosi)" ] }, { "cell_type": "code", "execution_count": 16, "id": "774aba03", "metadata": {}, "outputs": [ { "data": { "text/html": [ "Model summary:

\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
N
Point sources1
Extended sources3
Particle sources0
\n", "


Free parameters (2):

\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
valuemin_valuemax_valueunit
disk.Wide_Asymm_Gaussian_on_sphere.e0.9994440.01.0
disk.spectrum.main.composite.F_10.00170.01.0s-1 cm-2
\n", "


Fixed parameters (27):

\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
valuemin_valuemax_valueunit
disk.Wide_Asymm_Gaussian_on_sphere.lon00.00.0360.0deg
disk.Wide_Asymm_Gaussian_on_sphere.lat00.0-90.090.0deg
disk.Wide_Asymm_Gaussian_on_sphere.a90.00.090.0deg
disk.Wide_Asymm_Gaussian_on_sphere.theta0.0-90.090.0deg
disk.spectrum.main.composite.mu_1511.0NoneNonekeV
disk.spectrum.main.composite.sigma_11.270.0NonekeV
disk.spectrum.main.composite.K_20.00450.01000.0keV-1 s-1 cm-2
broadBulge.Gaussian_on_sphere.lon00.00.0360.0deg
broadBulge.Gaussian_on_sphere.lat00.0-90.090.0deg
broadBulge.Gaussian_on_sphere.sigma8.70.020.0deg
broadBulge.spectrum.main.composite.F_10.000730.01.0s-1 cm-2
broadBulge.spectrum.main.composite.mu_1511.0NoneNonekeV
broadBulge.spectrum.main.composite.sigma_10.850.0NonekeV
broadBulge.spectrum.main.composite.K_20.00270.01000.0keV-1 s-1 cm-2
narrowBulge.Gaussian_on_sphere.lon0359.750.0360.0deg
narrowBulge.Gaussian_on_sphere.lat0-1.25-90.090.0deg
narrowBulge.Gaussian_on_sphere.sigma2.50.020.0deg
narrowBulge.spectrum.main.composite.F_10.000280.01.0s-1 cm-2
narrowBulge.spectrum.main.composite.mu_1511.0NoneNonekeV
narrowBulge.spectrum.main.composite.sigma_10.850.0NonekeV
narrowBulge.spectrum.main.composite.K_20.00110.01000.0keV-1 s-1 cm-2
centralPoint.position.ra266.4049880.0360.0deg
centralPoint.position.dec-28.936178-90.090.0deg
centralPoint.spectrum.main.composite.F_10.000120.01.0s-1 cm-2
centralPoint.spectrum.main.composite.mu_1511.0NoneNonekeV
centralPoint.spectrum.main.composite.sigma_10.850.0NonekeV
centralPoint.spectrum.main.composite.K_20.000460.01000.0keV-1 s-1 cm-2
\n", "


Properties (4):

\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
valueallowed values
disk.spectrum.main.composite.dat_2OPsSpectrum.datNone
broadBulge.spectrum.main.composite.dat_2OPsSpectrum.datNone
narrowBulge.spectrum.main.composite.dat_2OPsSpectrum.datNone
centralPoint.spectrum.main.composite.dat_2OPsSpectrum.datNone
\n", "


Linked parameters (0):

(none)

Independent variables:

(none)

Linked functions (0):

(none)
" ], "text/plain": [ "Model summary:\n", "==============\n", "\n", " N\n", "Point sources 1\n", "Extended sources 3\n", "Particle sources 0\n", "\n", "Free parameters (2):\n", "--------------------\n", "\n", " value min_value max_value unit\n", "disk.Wide_Asymm_Gaussian_on_sphere.e 0.999444 0.0 1.0 \n", "disk.spectrum.main.composite.F_1 0.0017 0.0 1.0 s-1 cm-2\n", "\n", "Fixed parameters (27):\n", "---------------------\n", "\n", " value min_value max_value \\\n", "disk.Wide_Asymm_Gaussian_on_sphere.lon0 0.0 0.0 360.0 \n", "disk.Wide_Asymm_Gaussian_on_sphere.lat0 0.0 -90.0 90.0 \n", "disk.Wide_Asymm_Gaussian_on_sphere.a 90.0 0.0 90.0 \n", "disk.Wide_Asymm_Gaussian_on_sphere.theta 0.0 -90.0 90.0 \n", "disk.spectrum.main.composite.mu_1 511.0 None None \n", "disk.spectrum.main.composite.sigma_1 1.27 0.0 None \n", "disk.spectrum.main.composite.K_2 0.0045 0.0 1000.0 \n", "broadBulge.Gaussian_on_sphere.lon0 0.0 0.0 360.0 \n", "broadBulge.Gaussian_on_sphere.lat0 0.0 -90.0 90.0 \n", "broadBulge.Gaussian_on_sphere.sigma 8.7 0.0 20.0 \n", "broadBulge.spectrum.main.composite.F_1 0.00073 0.0 1.0 \n", "broadBulge.spectrum.main.composite.mu_1 511.0 None None \n", "broadBulge...sigma_1 0.85 0.0 None \n", "broadBulge.spectrum.main.composite.K_2 0.0027 0.0 1000.0 \n", "narrowBulge.Gaussian_on_sphere.lon0 359.75 0.0 360.0 \n", "narrowBulge.Gaussian_on_sphere.lat0 -1.25 -90.0 90.0 \n", "narrowBulge.Gaussian_on_sphere.sigma 2.5 0.0 20.0 \n", "narrowBulge.spectrum.main.composite.F_1 0.00028 0.0 1.0 \n", "narrowBulge.spectrum.main.composite.mu_1 511.0 None None \n", "narrowBulge...sigma_1 0.85 0.0 None \n", "narrowBulge.spectrum.main.composite.K_2 0.0011 0.0 1000.0 \n", "centralPoint.position.ra 266.404988 0.0 360.0 \n", "centralPoint.position.dec -28.936178 -90.0 90.0 \n", "centralPoint.spectrum.main.composite.F_1 0.00012 0.0 1.0 \n", "centralPoint...mu_1 511.0 None None \n", "centralPoint...sigma_1 0.85 0.0 None \n", "centralPoint.spectrum.main.composite.K_2 0.00046 0.0 1000.0 \n", "\n", " unit \n", "disk.Wide_Asymm_Gaussian_on_sphere.lon0 deg \n", "disk.Wide_Asymm_Gaussian_on_sphere.lat0 deg \n", "disk.Wide_Asymm_Gaussian_on_sphere.a deg \n", "disk.Wide_Asymm_Gaussian_on_sphere.theta deg \n", "disk.spectrum.main.composite.mu_1 keV \n", "disk.spectrum.main.composite.sigma_1 keV \n", "disk.spectrum.main.composite.K_2 keV-1 s-1 cm-2 \n", "broadBulge.Gaussian_on_sphere.lon0 deg \n", "broadBulge.Gaussian_on_sphere.lat0 deg \n", "broadBulge.Gaussian_on_sphere.sigma deg \n", "broadBulge.spectrum.main.composite.F_1 s-1 cm-2 \n", "broadBulge.spectrum.main.composite.mu_1 keV \n", "broadBulge...sigma_1 keV \n", "broadBulge.spectrum.main.composite.K_2 keV-1 s-1 cm-2 \n", "narrowBulge.Gaussian_on_sphere.lon0 deg \n", "narrowBulge.Gaussian_on_sphere.lat0 deg \n", "narrowBulge.Gaussian_on_sphere.sigma deg \n", "narrowBulge.spectrum.main.composite.F_1 s-1 cm-2 \n", "narrowBulge.spectrum.main.composite.mu_1 keV \n", "narrowBulge...sigma_1 keV \n", "narrowBulge.spectrum.main.composite.K_2 keV-1 s-1 cm-2 \n", "centralPoint.position.ra deg \n", "centralPoint.position.dec deg \n", "centralPoint.spectrum.main.composite.F_1 s-1 cm-2 \n", "centralPoint...mu_1 keV \n", "centralPoint...sigma_1 keV \n", "centralPoint.spectrum.main.composite.K_2 keV-1 s-1 cm-2 \n", "\n", "Properties (4):\n", "--------------------\n", "\n", " value allowed values\n", "disk.spectrum.main.composite.dat_2 OPsSpectrum.dat None\n", "broadBulge.spectrum.main.composite.dat_2 OPsSpectrum.dat None\n", "narrowBulge...dat_2 OPsSpectrum.dat None\n", "centralPoint...dat_2 OPsSpectrum.dat None\n", "\n", "Linked parameters (0):\n", "----------------------\n", "\n", "(none)\n", "\n", "Independent variables:\n", "----------------------\n", "\n", "(none)\n", "\n", "Linked functions (0):\n", "----------------------\n", "\n", "(none)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# add sources to thin disk and thick disk models \n", "totalModel = Model(ModelDisk, ModelBroadBulge,ModelNarrowBulge,ModelCentralPoint)\n", "totalModel.display(complete=True)" ] }, { "cell_type": "markdown", "id": "5de3240f-7d7e-4cb4-9f23-6f976525cdf1", "metadata": {}, "source": [ "Before we perform the fit, let's first change the 3ML console logging level, in order to mimimize the amount of console output." ] }, { "cell_type": "code", "execution_count": 26, "id": "a9d24b46-70a6-4b3c-be9a-df701d9f26e8", "metadata": {}, "outputs": [], "source": [ "# This is a simple workaround for now to prevent a lot of output. \n", "from threeML import update_logging_level\n", "update_logging_level(\"CRITICAL\")" ] }, { "cell_type": "code", "execution_count": 21, "id": "c424a2e2-9bf9-457d-a54b-23d8ea30fd56", "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.\n" ] }, { "data": { "text/html": [ "
Best fit values:\n",
       "\n",
       "
\n" ], "text/plain": [ "\u001b[1;4;38;5;49mBest fit values:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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resultunit
parameter
disk.Wide_Asymm_Gaussian_on_sphere.e(9.9985 +/- 0.0005) x 10^-1
disk.spectrum.main.composite.F_1(1.643 +/- 0.011) x 10^-31 / (cm2 s)
background_cosi(9.906 +/- 0.032) x 10^-1
\n", "
" ], "text/plain": [ " result unit\n", "parameter \n", "disk.Wide_Asymm_Gaussian_on_sphere.e (9.9985 +/- 0.0005) x 10^-1 \n", "disk.spectrum.main.composite.F_1 (1.643 +/- 0.011) x 10^-3 1 / (cm2 s)\n", "background_cosi (9.906 +/- 0.032) x 10^-1 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Correlation matrix:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "
1.00-0.330.09
-0.331.00-0.60
0.09-0.601.00
" ], "text/plain": [ " 1.00 -0.33 0.09\n", "-0.33 1.00 -0.60\n", " 0.09 -0.60 1.00" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of -log(likelihood) at the minimum:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of -\u001b[0m\u001b[1;4;38;5;49mlog\u001b[0m\u001b[1;4;38;5;49m(\u001b[0m\u001b[1;4;38;5;49mlikelihood\u001b[0m\u001b[1;4;38;5;49m)\u001b[0m\u001b[1;4;38;5;49m at the minimum:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
-log(likelihood)
cosi-166772.754018
total-166772.754018
\n", "
" ], "text/plain": [ " -log(likelihood)\n", "cosi -166772.754018\n", "total -166772.754018" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of statistical measures:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mValues of statistical measures:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
statistical measures
AIC-333547.508036
BIC-333545.508036
\n", "
" ], "text/plain": [ " statistical measures\n", "AIC -333547.508036\n", "BIC -333545.508036" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 30min 29s, sys: 15min 41s, total: 46min 11s\n", "Wall time: 8min 12s\n" ] }, { "data": { "text/plain": [ "( value negative_error \\\n", " disk.Wide_Asymm_Gaussian_on_sphere.e 0.999853 -0.000045 \n", " disk.spectrum.main.composite.F_1 0.001643 -0.000011 \n", " background_cosi 0.990610 -0.003091 \n", " \n", " positive_error error unit \n", " disk.Wide_Asymm_Gaussian_on_sphere.e 0.000045 0.000045 \n", " disk.spectrum.main.composite.F_1 0.000011 0.000011 1 / (cm2 s) \n", " background_cosi 0.003209 0.003150 ,\n", " -log(likelihood)\n", " cosi -166772.754018\n", " total -166772.754018)" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "%%time \n", "# likelihood of data + model\n", "like = JointLikelihood(totalModel, plugins, verbose = True)\n", "like.fit()" ] }, { "cell_type": "markdown", "id": "3e61859f", "metadata": {}, "source": [ "## Results" ] }, { "cell_type": "code", "execution_count": 23, "id": "dd097a0a", "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
Best fit values:\n",
       "\n",
       "
\n" ], "text/plain": [ "\u001b[1;4;38;5;49mBest fit values:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
resultunit
parameter
disk.Wide_Asymm_Gaussian_on_sphere.e(9.9985 +/- 0.0005) x 10^-1
disk.spectrum.main.composite.F_1(1.643 +/- 0.011) x 10^-31 / (cm2 s)
background_cosi(9.906 +/- 0.032) x 10^-1
\n", "
" ], "text/plain": [ " result unit\n", "parameter \n", "disk.Wide_Asymm_Gaussian_on_sphere.e (9.9985 +/- 0.0005) x 10^-1 \n", "disk.spectrum.main.composite.F_1 (1.643 +/- 0.011) x 10^-3 1 / (cm2 s)\n", "background_cosi (9.906 +/- 0.032) x 10^-1 " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Correlation matrix:\n",
       "\n",
       "
\n" ], "text/plain": [ "\n", "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "
1.00-0.330.09
-0.331.00-0.60
0.09-0.601.00
" ], "text/plain": [ " 1.00 -0.33 0.09\n", "-0.33 1.00 -0.60\n", " 0.09 -0.60 1.00" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
\n",
       "Values of -log(likelihood) at the minimum:\n",
       "\n",
       "
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-log(likelihood)
cosi-166772.754018
total-166772.754018
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       "Values of statistical measures:\n",
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statistical measures
AIC-333547.508036
BIC-333545.508036
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" ], "text/plain": [ " statistical measures\n", "AIC -333547.508036\n", "BIC -333545.508036" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# thin disk model to data\n", "results = like.results\n", "results.display()" ] }, { "cell_type": "code", "execution_count": 24, "id": "5b6c0a71", "metadata": {}, "outputs": [ { "data": { "image/png": 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bh729PWvXruXJJ59kw4YNzJ07l6VLl3LDDTdgNBrJzs7Gx8eH//u//2P27NncdtttZfp54YUXiI2NpXfv3jz55JNWr02dOrXSe6+2Zs0a1q9fz969e/Hy8iIjIwNnZ2f27t3L559/zs8//4yzszO7d+9m4sSJ/PHHHwAcOHCAP/74g9atW/PCCy/w9ttvs2zZMpYuXcrs2bM5fPiwVT8JCQns3LkTnU5HYWEhGzduxMPDA4PBwNixY/n666+ZMGFCpWP9/PPP6dWrF8nJydx///3s2rWL7t2788knn3D33XerAaSltLQ0evXqxeuvv86WLVt4+umnGTVqFEuXLmXZsmX88ssvNpXPqCoJ0IQQQjQ7+VlF5KfXXoBWVV999RXdunVDr9czffp0nn/+ed5//33Wr1/P4cOH6dWrF2AqFWLOBhw+fDgzZ85kwoQJjBw5kqioqDod83fffcdjjz2Gl5cXgDrrt2HDBv744w/69u2rXpuSkqIuCQ4cOJDWrVsD0L9/f/71r39V2s/DDz+sbrY3Go08//zz7NmzB0VRSE5OJioqqtwAzTwbB9ChQwfWrFnDgQMHiIqKonv37gBMnDiRJ554gkuXLpW5393dnbFjx6rjNO/Tq2sSoAkhhGh23LydG1T7Dg4OjB8/njlz5vD++++jKApz585l8uTJZa5duHAhR48eZdeuXUyaNImJEyfy3HPPaTX0GlMUhcmTJ/P666+X+7qLi4v62N7e/pp7yyxnqRYuXEhaWhoHDhzAxcWFWbNmUVhYWO59Xbp0KTMb9+eff5abWVnec1eP02AwVDrO2iIBmhBCNFH5BQUcOXWK/IJCPNzd8ffxpnWrVtjZyfbjqiw/1rWdO3fSsWNHAMaMGcPixYu544478PPzo6SkhCNHjhAdHU1sbCxdu3ala9euODg4sG3bNgC8vLzIysqqUd9X33vhwgWGDx9ObGxsmWvHjBnDhx9+yB133IGXlxeZmZl4enpy++238+CDDzJt2jTCwsIwGo389ttv6v6uqvZdnoyMDIKCgnBxceHy5ct8+eWX/O1vf6vy99e/f3+mTJnC8ePH6dy5M59//jmhoaEEBQWV+z1WxNPTk6ysLFniFEIIUTOpGRls+ulncks3b5t5eXjQs0tnOkVGSqDWAJj3oJWUlBAREcHSpUsBeOCBB0hLS2Po0KHodDr0ej1TpkwhOjqaF198kZMnT+Lk5ISbmxtLliwB4JFHHuHZZ5/l3XffZf78+YwaNarK47j63sDAQBwcyg8RHnjgAS5evEj//v1xdHTEzc2N7du3M3jwYObPn8/YsWPVc09Hjx59zQCtR48edOzYkW7duhEZGcm3335b5poZM2Zw1113ERUVRUhICCNGjKjy9wamwrFr165l4sSJGAwGfHx8+N///letNgCeffZZbrzxRlxdXdm2bRstWrSodhtVpVPkYLJG58SJE0ybNo3ly5ern7aEEMIsMSmJzT/vpqSSJaROkW24sV+/OhxV/SksLCQuLo42bdpYLV+Jii1cuJAWLVpw//331/dQGiUtfuZkBk0IIZqQ4pIStv+yTw3OWvj7MyA6mryCAo6dOUNiUhIAsWfjCA9uRbvW4fU5XNFAzZo1q76H0OxJgCaEEE3I78eOk1+6eTo0qCWjBg9Wl6ratQ4n9uxZdu4/AMBPhw4RHBiAu5tbvY1XCFE+2YAghBBNRE5eHjGlG57t7OwYcv31ZfYRdWzThrbhplmzouJidh08VOfjFEJcmwRoQgjRROyP+UMtCdC9Q3u8PT3LXKPT6RhyfW/cXF0BSLh4kZT09DodpxDi2hrdEmd+fj4rVqxg165d5OTkEB4ezsSJExk+fPg1783IyGDJkiXs27ePwsJC2rVrx9SpU9VCgJYOHz7MypUrOX36NC4uLvTv35/HHnvM6hgOMJ0RtnbtWjZv3kxaWhrBwcGMGzeO8ePHW1330UcflXvGmpOTE9u3b6/emyCEEFfJzs3lVHw8AC7OTvTu1q3Ca12cnendrSs/HzLVijpy6hTDLIqLCiHqX6ML0ObOnUtsbCzTp08nLCyM7du389prr2E0GrnpppsqvK+4uJiZM2eSm5vLU089ha+vL+vWrWP27NksWrTIqhJzTEwMc+bMoX///syfP5+MjAyWLVvGzJkzWb58OU5OTuq1CxcuZNu2bUyZMoVOnTpx8OBBPvjgA/Lz83nggQfKjOO9997D3d1d/bq8InlCCFFdJ+LOqY97dOyIs8XvqfJ0jIhgf8wfFJeUcPJcPP2jonBxrt3irUKIqmtUAdq+ffs4fPgw8+bNU2ug9OzZk6SkJJYsWcKNN96oHoVxte+//564uDg+/PBDupV+soyOjmby5MksWbKEZcuWqdd++OGHhIWF8frrr6v7N4KDg3niiSfYtGkTd9xxBwBxcXF8//33TJs2jXvvvVdtMzs7m48//pixY8eqR2GYdejQAR8fHy3fFiFEM6coCidKD54G0z6za3F0dKRTZBv+PHESg8HA8bNnie7cuTaHKYSohka1B2337t24uroydOhQq+dHjRpFamqqejJ9RfeGh4erwRmYjtYYOXIkx48fJyUlBTCdGxYbG8vIkSOtNtd2796dsLAwfv75Z6s2FUXh1ltvterr1ltvpaioiAMHDtjy7QohRJVcTE4hOy8PgNCgIDwtZukr0619e/Xx0ZOnMBqNtTI+Ub6IiAg6depEVFQUnTt35r777iOv9P9jTaxevZqTJ09W+Pr+/fvp3r070dHRbN26lVGjRqnnTF7r3sZi6NChREZGEhUVRbdu3Rg1ahSXL1++5n3nzp0jICCgDkZYdY0qQIuLi6N169ZlspLatm2rvl6Rs2fPqtdVdq/5vxVda9lHXFwcPj4++Pv7V3k8Dz30EEOHDmXs2LG89dZbVfrBEUKIypyIuzJ71jny2rNnZj5eXoQFBwGQnZfHxeRkzccmKvfVV18RExPDsWPHyM7OLnevclVdK8has2YNDz74IL///js333wzmzZtUv+9qusAzWg0lvlAcK2zOavqgw8+ICYmhiNHjhAREcF7772nSbt1rVEFaFlZWWWWDMF0NhZAdnZ2hfdmZ2er11V2r/k8sIr6seyjovG4urri6OhodbZYSEgI06ZN44UXXmDhwoXcfffd7Nu3j+nTp6uzdxVJTU3lxIkT6p/40o3AQghRUlLC6YTzADg5OtImNLRa93eKjFQfxyVe0HRsouqKiorIy8uzSkR777336NOnDz179mTUqFGcP2/6/7xx40Z69OihzhJt2LCBFStWcPjwYWbMmEFUVBSbNm2yan/BggV88cUXLF68mKioKDIzM4mIiODIkSPXvPdqq1ev5uabb+bee++le/fu9O7dm7OlS+xJSUkMGzaMXr160bVrV2bMmIH5wKJXX32VBx54gDvvvJOoqCj27dtHQEAAr7/+OoMGDeJf//oXp0+fZsSIEer3t379egCWLVvG9OnTgSsHn//www8A/P3vf+eNN94oM069Xk9OTo76nv74449Wx06ZA7jyfP3113Tq1Ino6GjefPNNdDodubm5ABw6dIgbb7yR3r1707NnT77++utK36+aalR70MC2TfWV3Xv1axVdW53+La+9+eabrV7r2bMn0dHRPP7443z66ac8/fTTFbbz7bff2vSpSgjRdJ27cFGdeWhXzgrDtYQHB2NnZ4fRaCQuMZGBvXo2i+Sle48vJLUkp9baD3D05LPO167Gbz6LMy4ujl69enH33XcD8Omnn3Ly5En27duHvb09a9eu5cknn2TDhg3MnTuXpUuXcsMNN2A0GsnOzsbHx4f/+7//Y/bs2dx2221l+nnhhReIjY2ld+/ePPnkk1avTZ06tdJ7y3PgwAH++OMPWrduzQsvvMDbb7/NsmXL8PHxYePGjXh4eGAwGBg7dixff/01EyZMAGDXrl389ttvtGjRgnPnzpGWlka7du2YN28eAH379mXKlCk88sgjnDp1in79+tGrVy9uuukm3n77bQB27NhB//792bFjBzfddBPbt29n4cKF6thmzJjB3LlzuXDhAsHBwfz73/+u0vdklpyczCOPPML+/ftp3749//znP9XXMjMzmT59Ot9//z3BwcGkpqbSq1cvBgwYQFBQULX6uZZGFaB5e3uXe+J9To7pL1l5s1lmXl5e5c6wme81z6R5e3sDVNiP5Syct7c3p0+fLnNdQUEBJSUllY4HoEuXLoSGhla6dw5gzJgxDBgwQP06Pj6eN998s9J7hBDNQ8Kli+rjduFh1b7f2cmJVi1akJiURG5+PmmZmQRcVU6oKUotySG5pOzv+br21Vdf0a1bN/R6PdOnT+f555/n/fffZ/369Rw+fFgtA2UwGNQkuOHDhzNz5kwmTJjAyJEjraoQ1JWBAwfSunVrAPr378+//vUvwLR0+fzzz7Nnzx4URSE5OZmoqCg1QLvtttusDhh3cXFRk+xycnKIiYlhypQpALRv356BAweyZ88e9ZqzZ8+yfft2/vGPfzBnzhyys7M5efIk119/vdrmBx98wG233YaiKLz66qtMnjy5WrNc+/fvp2fPnrQv3aP58MMP88wzzwDwyy+/cPbsWau954qicOLEieYdoEVGRrJ9+3b0er3Vp0Tz1GqbSjKXIiMj1c2QlszPRZZO85vbOHv2LP3797e69uzZs1Z9REZGsmPHDtLS0qz2oVVlPJbs7CpfaQ4ICGhwmxeFEPVPURQSLl4CwNHBgeDAwBq10yY0RD2jMy7xQrMI0AIcy255qc/2HRwcGD9+PHPmzOH9999HURTmzp3L5MmTy1y7cOFCjh49yq5du5g0aRITJ07kueee02roVWJ5ALi9vb06i7tw4ULS0tI4cOAALi4uzJo1i8LSo8cAPDw8rNpxd3dXZ2zNS6EVrWgNHz6czZs3c/r0aYYMGYLRaOTrr79m4MCB5c4c63Q6/va3v6l70BwcHNRCzoDVuCwpilLhLLKiKPTo0cMqYbC2NKoAbdCgQWzcuJGffvrJqjDtli1bCAgIoEuXLhXeO3jwYBYuXMixY8fU6/R6PT/88ANdunRRA6DAwEA6d+7Mtm3buOeee9RPLEePHiUhIYG77rpLbXPgwIGsWLGCLVu2MHHiRPX5zZs34+zsTN9rFH48evQoiYmJZYraCiFEVSSnp1NQVASYsjcrKjN0LREhIew+/CsA5xITub57xUVum4qqLD/WtZ07d9KxY0fAtHKyePFi7rjjDvz8/CgpKeHIkSNER0cTGxtL165d6dq1Kw4ODmzbtg0wrRSVt/pTFVffe+HCBYYPH05s6dFhVZWRkUFQUBAuLi5cvnyZL7/8kr/97W9VHkNUVBRr1qzh4Ycf5syZM+zdu1ddohwxYgTPP/88gwcPBmDYsGG89tprPPvssxW2uWPHDvU9bdOmDXFxceqkytq1a8u9p1+/fkyePJnTp0/Trl071qxZo752ww03cOrUKXbu3MmNN94ImGqndunSxapGqhYaVYDWr18/evfuzcKFC8nPzyckJIQdO3Zw4MAB5s6dq/5yWrBgAVu3buWzzz5TpxxHjRrFunXrmDdvHtOnT1cL1SYkJLBo0SKrfh599FFmzZrFvHnzGDdunFqotk2bNlbTmm3atGH06NGsWrUKOzs7OnfuzKFDh9i4cSNTp061WuJ8+OGHGTlyJK1bt8bJyYnjx4/z2Wef4efnp07dCiFEdZhnzwDCWwXXuB1Pd3cCfH1JzcggJSOD3Px8POQA9Tph3oNWUlJCREQES5cuBeCBBx4gLS2NoUOHotPp0Ov1TJkyhejoaF588UVOnjyJk5MTbm5uLFmyBIBHHnmEZ599lnfffZf58+czatSoKo/j6nsDAwOrvZ8RTPu/7rrrLqKioggJCVFrllbVJ598wvTp0/nnP/+JTqdjxYoVhIWZlu6HDx9OQkKC2uZNN93Ee++9V6YP8x40o9GIr6+vGmCFhIQwe/ZsevfuTUREhBroXa1ly5YsXbqU0aNH4+/vz+23346joyNubm7Y2dmxceNG5syZwzPPPENJSQnh4eFqMoOWdIp5TrGRyM/PZ/ny5VZHPd1///1WM2rz589ny5YtfPHFFwQHX/mllZ6ebnXUU/v27ZkyZYpVVofZoUOH+Oijjzh16pR61NPjjz9e7lFPH3/8MZs3byY9PZ2goCDuvPPOMrNir732GrGxsaSnp1NSUkJAQAB9+/Zl0qRJ1V6+PHHiBNOmTWP58uXqJwMhRPPz9dZtXE5LA+CBsWOqXP+sPIf++otDfx0BYPD1va1qpDV2hYWFxMXF0aZNG6ulOVGxhQsX0qJFC+6///76Hkq9sNxzvmrVKlauXMmePXuqfL8WP3ONLkATEqAJIaCgsIhV33wDgJ+3N/eMrvpsSXmS09P5astWANqGhXHzoIE2j7GhkABNVNdbb73Fl19+iV6vx8/Pj2XLltG5GidtaPEz16iWOIUQQpicv3RlebN1q1Y2txfg44OToyPFJSVcTEmudKO0EE3dyy+/zMsvv1yvY2hUhWqFEEKYJF5OUh/bsv/MzM7OjqDSLNCCwiIys2uvRpgQ4tokQBNCiEboUrLpBBI7OztaalSGJ6TFlTIdcuyTEPVLAjQhhGhk8gsKyCo9dqalvz8ONSyvcbVgiwKiEqAJUb8kQBNCiEbmksX5vUGB2hWxDvTzU0srXExORnLIhKg/EqAJIUQjYxmgtQpsUcmV1WNvZ0dQ6XJpXkEB2aWzdKJ2RERE0KlTJ6KioujcuTP33XcfeXl5NW5v9erVnDx5ssLX9+/fT/fu3YmOjmbr1q2MGjVKPU3nWvde3Y/56Ka68uqrrzJ79my1fx8fH6KiooiKiuK6665jw4YNVWpn6NChfPfdd7U5VM1IgCaEEI2Mef8ZaDuDBtDKah9aSiVXCi189dVXxMTEcOzYMbKzs1m9enWN27pWkLVmzRoefPBBfv/9d26++WY2bdpE27Ztq3RvTVkeraSlESNGEBMTQ0xMDMuXL2fq1Km10k99kgBNCCEakeKSElIzMwHw9/HBWePjZVrJPrR6UVRURF5enlUx9Pfee48+ffrQs2dPRo0axfnz5wHYuHEjPXr0ICoqim7durFhwwZWrFjB4cOHmTFjBlFRUWzatMmq/QULFvDFF1+wePFioqKiyMzMJCIigiNHjlzz3vJkZWUxfvx4oqKiGDJkCAkJCYAp0Lvlllt48MEH6d27NwcPHmTLli307NmTHj16MGTIEI4dOwZAUlISw4YNo1evXnTt2pUZM2aoy+pZWVlMmDCBLl26cPPNN3P69OkKx5Kenm71vpm/L7PevXvz448/lrnPfJxV165due2227jtttvUY6VycnKYNm0affr0oUePHjz66KOUlJRc833RktRBE0KIRuRyaqr6j1hND0evTEt/f+zs7DAajVxOTdW8/YbiwRmvkJZRs3Mrq8Lf15uPP3jtmteZj3qKi4ujV69e3H333QB8+umnnDx5kn379mFvb8/atWt58skn2bBhA3PnzmXp0qXccMMNGI1GsrOz8fHx4f/+7/+YPXs2t912W5l+XnjhBWJjY+nduzdPPvmk1WtTp06t9N7y7Nmzh5iYGDp27Mg777zDo48+qgZ2e/bs4ffff6d9+/YkJyfTpUsXdu3aRffu3fnkk0+4++67OXLkCD4+PmzcuBEPDw8MBgNjx47l66+/ZsKECbz++ut4eXlx7NgxUlNT6dmzp/reAGzfvp2oqCjy8/O5cOECX3zxRZXGbWnGjBkMGzaMuXPnkpCQQLdu3bjlllsAePbZZxk8eDDLly9HURSmTZvGv//9b5555plq91NTEqAJIUQjYrn/LFjj5U0Ae3t7Anx9SU5LIzMnh6LiYs1n6RqCtIwsktMy6nsYfPXVV3Tr1g29Xs/06dN5/vnnef/991m/fj2HDx+mV69egGmp0Hze9PDhw5k5cyYTJkxg5MiRREVF1fm4Bw4cqJ5k88gjj/DKK6+oHxwGDhxI+9Kjwg4cOEBUVBTdu3cHYOLEiTzxxBNcunQJb29vnn/+efbs2YOiKCQnJxMVFcWECRPYtWsX//rXvwAICAjgzjvvtOp/xIgRfPXVVwAcOXKEESNG8Ntvv9GqGkWbd+3axQcffABAeHi41ZGR69evZ//+/bz//vsAFBQUaH4Y+rVIgCaEEI2IVYDWQrsEAUst/PxILj3jMyU9ndCgoFrppz75+3o3qPYdHBwYP348c+bM4f3330dRFObOncvkyZPLXLtw4UKOHj3Krl27mDRpEhMnTuS5557Taug28/DwUB9XdCKFTqdj4cKFpKWlceDAAVxcXJg1axaFhYXqfVXVrVs3wsPD2bt3L3fddRcODg5We9/MbZanotMyFEVh/fr1REZGVnkcWpMATQghGglFUUhOSwfAw80NDze3Wumnhb8fnDI9Tm6iAVpVlh/r2s6dO9VZqTFjxrB48WLuuOMO/Pz8KCkp4ciRI0RHRxMbG0vXrl3p2rUrDg4ObNu2DQAvLy+ysmq2bHv1veb9WbGxseVev3fvXk6ePEmHDh1YsWIFN954Y7nBTv/+/ZkyZQrHjx+nc+fOfP7554SGhhIUFERGRgZBQUG4uLhw+fJlvvzyS/72t78BplnCVatWMWDAANLT01m3bh133XVXuWNJTEzk1KlTdOjQAYC2bdty4MABrrvuOg4ePMiJEyfKvW/o0KGsXr2al156ifPnz7Nz5051Fm3MmDEsWLCADz/8EAcHBzIyMkhLS6Ndu3ZVf1NtJAGaEEI0EpnZOZTo9UBpEFVLWvj5q4/NAaGoHeY9aCUlJURERLB06VIAHnjgAdLS0hg6dCg6nQ69Xs+UKVOIjo7mxRdf5OTJkzg5OeHm5saSJUsA01Ljs88+y7vvvsv8+fMZNWpUlcdx9b2BgYFqTbzyDBkyhFdffZVjx47h7e3Nxx9/XO51gYGBrF27lokTJ2IwGPDx8eF///sfYNoDdtdddxEVFUVISAgjRoxQ7/v73//O5MmT6dKlC61bt+amm26yate8B01RFPR6PfPnz+e6664DTAedT5o0iZUrV9KzZ0+6du1a7tgWL17Mgw8+yBdffEGHDh0YMGAA3t6mmc9//vOfPP/880RFRWFnZ4ejoyNvv/12nQZoOkUqETY6J06cYNq0aSxfvlz9tCWEaPpOxMWxY99+APpe14NeFfzDYyuj0ciKr75Gr9fj4ebGg3eMrZV+6kphYSFxcXG0adMGFxeX+h5Oo7Bw4UJatGjB/fffX99DqTUFBQU4Ojri4ODApUuXuP7669mxY4cm/65q8TMnM2hCCNFIpKRfmc1q4Vd7M2h2dna08PPlYnIKufn55BcW4iaBTbMya9as+h5CrTt16hQPPvggiqJQUlLCK6+80qAmPSRAE0KIRiLZIkALrMUAzdS+v1qoNjktjYiQkFrtT4i61qNHD2JiYup7GBWSQrVCCNEIGI1GUtNNZSG8PDxwcXau1f4s97jJPjQh6p4EaEII0QhkZGejLy0dUNuzZwAt/C0SBdIlQBOirkmAJoQQjYDlLFZt7j8z83J3VwvUpqSlVasulRDCdhKgCSFEI2CVIFCLJTbMdDqdOlNXUFREfkFBrfcphLiiRkkCWlTWnTlzJjNmzLC5HSGEaA7qMkHALMDXh8SkJABSMzNxr6XCuEKIsmo0g3bu3DkyMjJQFKVGf+Lj48nMzNT4WxFCiKbJYDSSlmFKEPDx8sTJ0bFO+vX38VEfp8nvbM1FRETQqVMnoqKi6Ny5M/fddx95eXk1bm/16tWcPHmywtf3799P9+7diY6OZuvWrYwaNYozZ85U6d5r9TthwgQAvv32W+bMmVPp9a+++iqzZ8+uUV/NSY3LbDzzzDPMmzevRvfa2cnKqhBCVFVGVhYGoxGAQN+6mT2DqwK0jMw667c5MR+WrigKt99+O6tXr+aJJ56oUVurV68mICBAPfLoamvWrOHBBx9UA6ibb765yvdW1ZgxYxgzZoxNbQgTiZSEEKKBs5y98vf1qbN+fb281A/UMoNWu4qKisjLy8PX11d97r333qNPnz707NmTUaNGcf78eQA2btxIjx49iIqKolu3bmzYsIEVK1Zw+PBhZsyYQVRUFJs2bbJqf8GCBXzxxRcsXryYqKgoMjMziYiI4MiRI9e892rFxcVMnz6dDh06MGzYMA4cOKC+ZjmbdurUKQYMGMB1111H9+7dmTt3bpm2jh07Rvfu3dm8eXON37umqkYzaKdOncLPhj0Qtt4vhBDNiWVwFGAxq1Xb7O3t8fXyIi0zUy3z4WBvX2f916Yvt2yt1cQHN1dX7rrl5mteZz6LMy4ujl69enH33XcD8Omnn3Ly5En27duHvb09a9eu5cknn2TDhg3MnTuXpUuXcsMNN2A0GsnOzsbHx4f/+7//Y/bs2dx2221l+nnhhReIjY2ld+/ePPnkk1avTZ06tdJ7r7Zs2TLi4uI4evQoJSUlDB48mIiIiDLX/fvf/2b06NG89NJLAKRfVa5l586dPPXUU3zyySdERUVds9/mpkYBWtu2bW3q1Nb7hRCiOUm1WF70t5hhqQv+Pj6kZWaiKAoZWVl1lqBQ2/ILCshrAJmp5iVOvV7P9OnTef7553n//fdZv349hw8fplevXgAYDAbsS4Pj4cOHM3PmTCZMmMDIkSPrPLjZtWsXkyZNwtHREUdHR+6//3727NlT5rrBgwczZ84c8vLyGDJkiNVh6D/88AObNm1i69athIWF1eXwGw1Z4hRCiAbOPIPm4uxc52diWi6pNqVlTjdXV9xr8Y+bq2u1xuPg4MD48ePZsmULAIqiMHfuXGJiYoiJieGvv/5SjyVauHAhq1atws3NjUmTJvHOO+9o/fZUqqo18caPH8/evXvp2LEj//73v61m59q3b4+iKBw8eLC2htnoyVmcQgjRgOUXFFBQWAiYljd1Ol2d9h/QRBMFqrL8WNd27typHtY9ZswYFi9ezB133IGfnx8lJSUcOXKE6OhoYmNj6dq1K127dsXBwYFt27YB4OXlRVZWVo36vvreCxcuMHz4cGJjY8tcO3z4cNauXcvf/vY3SkpK+PTTTwkPDy9z3alTp4iMjOTBBx+kT58+3HDDDeprERERfPDBB9xyyy3k5eXx4IMP1mjcTZmmAVpGRgYbN26UN1oIITSSapkgUIf7z8rrsynNoDUU5j1oJSUlREREsHTpUgAeeOAB0tLSGDp0KDqdDr1ez5QpU4iOjubFF1/k5MmTODk54ebmxpIlSwB45JFHePbZZ3n33XeZP38+o0aNqvI4rr43MDAQB4fyQ4RHHnmEP//8ky5duhAaGsqgQYOIj48vc92XX37JJ598gpOTE4qiqN+bWatWrdi5cye33HILubm5PP7441Ueb3OgUzQ8v+OPP/6gZ8+eGErPixO148SJE0ybNo3ly5ern7aEEE3T78ePs+/3GABu7NeXThoUCq+uVd+so6CwEBdnZx6+c1ydz+LZqrCwkLi4ONq0aYNLHS8RN1YLFy6kRYsW3H///fU9lEZJi5+5as2gJSQkVPr6xYsXazQIIYQQ5bNcVgyo4wQBM38f04kChUVF5BcW4l7N/VWi8Zk1a1Z9D6HZq1aAFhERUeknJ0VRGt0nKyGEaMjMy4p2Oh2+Xl71MgZzgAamgFECNCFqX7UCNF9fX+bPn8/QoUPLff348eOMHz9ei3EJIUSzZzAYyMjOBsDHy0sts1DX/H281ccZ2VmEtwqul3EI0ZxUK0Dr1asXKSkpFe57KiwsrHL6rRBCiMplZGdjLD3iqS5PELiar9eVAC09K7vexmEr+fdJ1BUtftaqFaA99thjlR7kGh4ezqpVq2welBBCiPo7QeBqvt5XllYzaljGoT45Ojqi0+lISUkhMDBQtuKIWqUoCikpKeh0OhwdHWvcTrUCtHHjxlX6uq+vL5MmTarxYIQQQlyRbhEM+Xn71Ns4nBwd8XBzIzc/n4ysrEa339je3p7Q0FASExM5d+5cfQ9HNAM6nY7Q0FCbtiVIoVohhGigMiyWE/0s9oHVB19vL3Lz8ykqKWmUmZweHh60b9+ekpKS+h6KaAYcHR1t3jNqc4Bmb29PXFxcuVWEhRBC1Jx5Bs3BwQEPN7d6HYuflzfnL5kyOTOyshpdgAamf6/qK9FCiOqy+SxO2XQphBDaK9Hryc7NBcDPy6velxR9vZtGooAQjYUcli6EEA2QubwG1P/yJjT+RAEhGhsJ0IQQogFKz7wSBFnOXtUXyzFkZEuAJkRtkwBNCCEaoAyrDM76D9BcnJxwK913JkucQtQ+CdCEEKIBSm9gARqY9sIBFBYVUVBYWM+jEaJpkwBNCCEaIHOA5tgAMjjNJFFAiLojAZoQQjQwJSUl5JSe2uLn7V3vGZxmkiggRN2xOUB7+eWX8anHI0iEEKKpsczgbAgJAmZ+kiggRJ2pcaFavV6Pg4MDb7zxhpbjEUKIZs96/5lXJVfWLR9PT/VxRnZOPY5EiKavxjNorVq1Yvbs2Rw/flzL8QghRLPXEBMEAFxdXHAqPfw5M1v2oAlRm2ocoGVlZbFw4UK6devGDTfcwMqVK8ktrXothBCi5izP4GxIS5w6nQ6f0kzO3Px89Hp9PY9IiKarxgHapUuXWLRoEd27d2f//v088sgjBAcHM2XKFPbs2aPlGIUQolkxz041hDM4r2a5zJmZI8ucQtSWGgdofn5+PP3008TExHD48GEee+wxnJycWLVqFUOGDKFz5868++67XL58WcvxCiFEk6Y3GMguzeD09fRsMBmcZuYZNJAATYjapEmZjZ49e/Lvf/+bS5cu8emnnzJ8+HBOnTrFCy+8QFhYGOPGjeO7777DaDRq0Z0QQjRZWTk5KIoCgE8DShAw8/WymEGTfWhC1BpN66A5OTlxzz33sG3bNs6dO8err75KWFgYGzZsYOzYsYSFhWnZnRBCNDmWQY+vV8ML0Kxm0CSTU4haU2uFakNDQ/n73//Opk2bGDBgAIqikJSUVFvdCSFEk2CVIODVcBIEzLw9PNTHMoMmRO2pcR20yuTl5fG///2Pjz76iF9++QVFUXBzc2PChAm10Z0QQjQZGQ18Bs3BwQFPd3dy8vLILF2ObWj75IRoCjQN0Hbv3s1HH33EV199RX5+PoqicP311zNlyhTuvfdePC2yf2oqPz+fFStWsGvXLnJycggPD2fixIkMHz78mvdmZGSwZMkS9u3bR2FhIe3atWPq1Kn06tWrzLWHDx9m5cqVnD59GhcXF/r3789jjz2Gr6+v1XV6vZ61a9eyefNm0tLSCA4OZty4cYwfP77Ssbzxxhv88MMP9O/fn7fffrt6b4IQoskyz0rpdDq8PT2ucXX98PHyJCcvj+KSEgoKC3Fzda3vIQnR5NgcoF24cIE1a9awevVqzpw5g6Io+Pv7M3XqVKZMmUK3bt20GKdq7ty5xMbGMn36dMLCwti+fTuvvfYaRqORm266qcL7iouLmTlzJrm5uTz11FP4+vqybt06Zs+ezaJFi4iKilKvjYmJYc6cOfTv35/58+eTkZHBsmXLmDlzJsuXL8fJyUm9duHChWzbto0pU6bQqVMnDh48yAcffEB+fj4PPPBAuWPZt28fe/bswd3dXbP3RQjR+CmKos6geXl4YG9vX88jKp+PpxfnL5m2rGRk50iAJkQtqHGA9r///Y9Vq1axfft2DAYDdnZ2jBw5ksmTJ3PHHXfgWFptWkv79u3j8OHDzJs3jxEjRgCmDNKkpCSWLFnCjTfeWOEvtO+//564uDg+/PBDNWiMjo5m8uTJLFmyhGXLlqnXfvjhh4SFhfH666/j4GB6i4KDg3niiSfYtGkTd9xxBwBxcXF8//33TJs2jXvvvVdtMzs7m48//pixY8fiddUSRW5uLu+99x5Tpkzhq6++0vT9EUI0brn5+egNBqBhLm+a+VqV2sgmpGWLehyNEE1TjZME7rnnHrZu3UpYWBivvfYa586dY/Pmzdx11121EpyBaQnV1dWVoUOHWj0/atQoUlNTOXbsWKX3hoeHW83oOTg4MHLkSI4fP05KSgoAKSkpxMbGMnLkSDU4A+jevTthYWH8/PPPVm0qisKtt95q1dett95KUVERBw4cKDOO//znP/j7+19zCVQI0fxYJwg03ADNR0ptCFHrajyDds899zBlypQq7f3SSlxcHK1bt7YKnADatm2rvt69e/dy7z179izXXXddmect7w0MDCQuLs7q+auv/euvv6zG4+Pjg7+/f4VtWjp8+DBbt27lv//9b4NduhBC1B/LBAGfBh2gSakNIWpbjQO0Tz/9VMtxVElWVhatWrUq87w5+SC7kk9y2dnZ5SYpXH1vVukhxVcvTZqvtewjKyur3OtcXV1xdHRU2wJTcsM777zDPffcQ7t27SocZ3lSU1NJS0tTv46Pj6/W/UKIxsGqBloDLFJr5u7qioO9PXqDgaxcCdCEqA2aZXHq9Xr+9a9/8dlnnxEbG0u+xUG6MTEx/Pe//2XmzJl06NDBpn5sSeeu7N6rX6vo2ur0b3ntsmXLcHBwYNKkSVW+3+zbb79l9erV1b5PCNG4NJYZNFOGqSdpmZlk5+ZhNBqxs6u1sppCNEuaBGgFBQWMHDmSX375hYCAALy8vMgrPUsOoE2bNqxatQo/Pz/efPPNGvfj7e1tNStlllN6Hlx5s1lmXl5e5c6wme81z6R5e5sKQ1bUj+UsnLe3N6dPny5zXUFBASUlJep4jh07xvr163nzzTcpLi6muLgYAKPRiMFgICcnB2dnZ6vsUEtjxoxhwIAB6tfx8fE2vY9CiIYpq/T3kauLMy4V/D5oKLw9PUjLzMRoNJKbn4+XR8MsCSJEY6XJR5758+ezd+9e/vGPf5CUlMTUqVOtXvf29mbIkCFs3brVpn4iIyOJj49XZ+bMzp49C5gCwcruPXPmTJnnzc9FRkZatWFu8+p+LPuIjIwkMzPTavmxvPHEx8ejKAovv/wyo0ePVv8kJydz8OBBRo8ezfr16ysce0BAAB07dlT/tG7dusJrhRCNk16vJ6+gAAAvD9trRtY2b4sxZsmh6UJoTpMA7YsvvmDo0KE899xz6HS6cpcBIyMjSUhIsKmfQYMGUVBQwE8//WT1/JYtWwgICKBLly4V3jt48GASEhKsMj31ej0//PADXbp0ISAgAIDAwEA6d+7Mtm3bMJSmuwMcPXqUhIQEhgwZoj43cOBAdDodW7Zssepr8+bNODs707dvXwD69OnD4sWLy/zx8/Oja9euLF68uExmqhCiecnOvbLq4N0IZqMsi+hm5ebW40iEaJo0WeJMSEhg3LhxlV7j5eVV7rJhdfTr14/evXuzcOFC8vPzCQkJYceOHRw4cIC5c+eqmZELFixg69atfPbZZwQFBQGmUhzr1q1j3rx5TJ8+XS1Um5CQwKJFi6z6efTRR5k1axbz5s1j3LhxaqHaNm3aWJXUaNOmDaNHj2bVqlXY2dnRuXNnDh06xMaNG5k6daq6xOnv718m0xNMh8t7eXkRHR1t0/sihGj8si2CnMawXOjtKTNoQtQmTQI0T09PtY5YRc6cOUNgYKDNfb355pssX76clStXqkc9vfLKK1blPsx7uxRFUZ9zcnJi0aJFLFmyhMWLF1NYWEj79u159913rU4RAFOx2XfeeYePPvqIF154QT3q6fHHHy+zT2zWrFkEBATwzTffkJ6eTlBQEDNmzJA6Z0KIarHMhmyoRzxZsg7QZAZNCK3pFMsopoZuv/129u/fz+nTp/H29ua1117j9ddfV5cIExMT6dixI3fccQeffPKJzYNu7k6cOMG0adNYvnw5HTt2rO/hCCE0sPvwYf46eQqAcTeNIFiDD7S1SVEU/vu/LzEYDPh6eXHvbaPre0hCNCma7EGbM2cO6enpjBgxgl9++UXdxJ+fn8+OHTsYOXIkJSUlzJo1S4vuhBCiybGchWoMe9B0Op06zqzcXIxGYz2PSIimRZMlzsGDB/Of//yHGTNmMGjQIPV5c0kKe3t7PvzwQ3r16qVFd0II0eRk55kCNAd7e1xdXOp5NFXj7elBelYWRqORvIICPN3d63tIQjQZmhWqffTRRxkyZAhLly7lwIEDpKen4+XlRd++fXn88cfp2rWrVl0JIUSTYjQa1SxOLw8Pmwpy16WrEwUkQBNCO5oFaACdO3dm8eLFWjYphBBNXl5BgbpE2BgSBMysa6HlEhpUj4MRoomp07M5ZI+CEEKU1dhKbJhZ10KTUhtCaEmTAG3FihXXvMZgMHDfffdp0Z0QQjQploVevRvBKQJmUmpDiNqjSYD22GOPsWHDhgpfVxSFiRMn8uWXX2rRnRBCNCnZOZYzaI1nH5e7q6t6SLoUqxVCW5oEaP369ePee+9l9+7dZV4zB2f/+9//ePTRR7XoTgghmpQsqyXOxjODZmdnpy7JZufmokFZTSFEKU0CtO+++462bdsyZswY/vrrL/V5RVF44IEH+Pzzz5k+fTr/+c9/tOhOCCGaFPMeNJ1Oh6e7Wz2Ppnp8Spc59QaDeti7EMJ2mgRo3t7ebN26FW9vb2655RbOnTuHoijcf//9fPrppzzyyCMsWbJEi66EEKLJMQdoHm5u6pnCjYVlUV1Z5hRCO5plcbZq1Ypt27ZRXFzMyJEjuffee/nss8+YOnUqS5cu1aobIYRoUgqLiykqLgYaVwanmSQKCFE7NC2z0aFDBzZv3kxSUhJffvklU6ZM4b///a+WXQghRJOSbTHr1BiOeLqal5TaEKJW1KhQ7euvv17p63369CEmJoaQkBCra3U6HX//+99r0qUQQjRJ5hMEwDrYaSxkBk2I2lGjAO3VV1+t0nVXB3ISoAkhhDXLWafGuMTp6eaGnU6HUVFkD5oQGqpRgLZr1y6txyGEEM1StlWR2sYXoJlLbWTm5JBVWmqjsZwlKkRDVqMAbciQIVqPQwghmqWsnMZ5zJMlL09PMnNy0Ov15BcW4u7qWt9DEqLRq9OzOIUQQlgzz6C5ODvh7ORUz6OpGSm1IYT2JEATQoh6YjAYyM3PB8DLvXHOnoEkCghRGyRAE0KIepKd17gzOM28pdSGEJqTAE0IIeqJdYJA4zmD82o+MoMmhOYkQBNCiHqSbZUg4F6PI7GNh7u7mrkpe9CE0IYEaEIIUU+yci0DtMY7g2ZvZ4enuynAzMrJQVGUeh6REI2fBGhCCFFPrJY4G/EeNLgy/hK9noKionoejRCNn6YBWkZGBh9//LGWTQohRJNlDtDs7ewafe0wyz10sswphO00DdASEhJ4+OGHtWxSCCGaJEVR1ADN08Oj0Vfft8rklEQBIWxWrZMEEhISKn394sWLNg1GCCGai/yCAvQGA9A4j3i6muUMmuXSrRCiZqoVoEVERFT6KU/OYBNCiKqxThBo/AGal9RCE0JT1QrQfH19mT9/PkOHDi339ePHjzN+/HgtxiWEEE1aU0oQAPByv1ImJFuWOIWwWbUCtF69epGSkkLHjh3Lfb2wsFDSq4UQogqym9gMmoODA+6uruQVFJCdJwGaELaqVoD22GOPkWdxNMnVwsPDWbVqlc2DEkKIpi4rp2kFaGD6PvIKCigoLKK4pAQnR8f6HpIQjVa1ArRx48ZV+rqvry+TJk2yaUBCCNEc1PUMWlFxMXq9AXe32ivn4e3pwaWUFMD0/QX4+tZaX0I0ddUK0IQQQmjDHKC5u7riYG9fa/0c+O0IG7b9zM8HfkcxKjz64J1MHHcLdnba1ym3DDSzJEATwiYSoAkhRB0rLilRq+3XZoLA19/vZMF/1lg998HKL9j361+89fxj+Hp7adqfZbkQSRQQwjY2f4Syt7e/Zn00IYQQV9TF8mZGVjb/Xv2lRT9XDjQ/FHOM1xau0LxPy/NEs6QWmhA2sTlAk6xNIYSonro4JH3Z/60jNy8fgFuH3cDWTz/gP289h6+3qb+9h/4g9vQ5Tfu0nA3MllpoQthEDksXQog6Zrn85+3hXsmVNXP6XCLrNu8CwM3VhRlT/oaDgwPXR3Vh2sQryV5r/vedpv06OzmpmZuyxCmEbSRAE0KIOlbbM2jL1n6N0Wha3Xjo7tsI8PNRX7v9pkH4+Zj2nu3Ye5j4xCTN+tXpdOo+tJz8fAxGo2ZtC9HcSIAmhBB1zHL5T+skgZzcPPYc+gOAAD8f7ht3s9XrLs5O3HuH6TlFUVj71fea9m8+8klRFHIrqZsphKicBGhCCFHHsnNNgYuToyPOTk6atr37QAx6vekQ9hGD+pTb/oTRN6r10Dbt/IX8gkLN+rcqtSHLnELUmARoQghRhwxGIzmlM0teHh5qZqVWduw9pD4ePvD6cq/xcHfjlqH9ACjR6zkUc0yz/q1KbUgmpxA1JgGaEELUody8PDX73VvjEht5+QXs//UIYFre7NG5XYXXDrg+Sn2851CMZmOwLlYrmZxC1JTNAdrLL7+Mj4+PBkMRQoimz6oGmsb7z/Ye+oPikhIAhvbvVelpAddf11nNuPzl0J+alUzy9ryS9GBeyhVCVJ/NAdobb7yBl5e21aiFEKKpyqrFIrU79x5WH1e0vGnm4uJMrx6dAEhOy+BU3HlNxuDu6qoGhjKDJkTN1eoSp6IonDp1isTExNrsRgghGg3LGTQtlziLiovZW5q96evtSVS3Dte8Z2Cf69TH5nttZWdnh5e7qbZbdm6eFDMXooY0CdA2bNjA5MmTycjIUJ87d+4c3bt3p1OnTrRu3ZqJEydilJo4QohmzjKzUcsZtOOnzlFYVAzADddfV6UD2C33oWkVoMGV70uv11NQqF2GqBDNiSYB2tKlSzl06BC+vr7qczNnzuTYsWMMGzaMHj168Pnnn7Nq1SotuhNCiEbLPINmp9Ph4eamWbsxR0+qj3t261ile0KCAmkT1gqAv2JPk5mtTdalZW03OZNTiJrRJEA7evQoffr0Ub/Oyspi06ZN/O1vf2P79u0cPHiQzp07s3LlSi26E0KIRklRFDVA83R3r3QTf3VZBmjXdbn28qbZDdf3AMBoVPj9SKwmY5FaaELYTpPfDikpKQQHB6tf79mzB71ez7333guAo6MjN910E6dPn9aiOyGEaJQKiooo0esBbTM4jUYjfxw7BYCfjxfhIS2rfG+URTB35MRZTcbj7WGZySkBmhA1oUmA5uXlRVpamvr1jz/+iJ2dHYMGDVKfc3R0JE+O/RBCNGPWh6Rrdwbn2fgL5OblA6bZs+oUv+3Wqa36+OiJM5qMx8tTaqEJYStNArROnTqxceNG0tPTycrK4vPPP6dnz55We9Li4+Np2bLqn+qEEKKpsaqB5uGuWbu/WyxvRnVtX617A/x8CAr0B+DYyTj0BoPN4zFncYJ1UCqEqDpNArQZM2Zw8eJFQkJCCAsL4+LFizz66KPq6waDgT179nDddddV0ooQQjRt1jXQtJtB+8MqQKtagoAl8yxaQWERZ+Mv2DweBwcH3F1NZ33KEqcQNaNJgDZ+/Hj+85//0LVrVzp06MA//vEPJk+erL6+Y8cO8vPzueWWW7ToTgghGqVsi+U+bw33oMUcMwVori7OdGgbXu37u1sscx7RapmzNFGgoKhIPd1ACFF1Dlo19Nhjj/HYY4+V+9rIkSOtaqQJIURzZHn0kVY10C5dTuVySjpgmgmrSv2zq3XtaBGgxZ7hzluH2Twub08PLqWkAKZZtACLLS9CiGuTw9KFEKKOmJc4XV1ccHTQ5vPxX7FXZryiqlFew1LHtq1xcDAFdkditZ1BA6mFJkRNSIAmhBB1oESvJ7+gAND2iKcTZ86pjzu3b1OjNlycnWjfxrQ0Gnf+IjkaHHJu+T1KooAQ1ScBmhBC1IHsWjok/cSZePVxxxrsPzOz3Id27GScTWMC6yQImUETovo024NWV/Lz81mxYgW7du0iJyeH8PBwJk6cyPDhw695b0ZGBkuWLGHfvn0UFhbSrl07pk6dSq9evcpce/jwYVauXMnp06dxcXGhf//+PPbYY1alQ8B01tzatWvZvHkzaWlpBAcHM27cOMaPH2913fbt21m/fj3nz58nNzcXLy8vOnbsyMSJE+nevbttb4oQosGzOiRdowQBRVE4eTYBMB2QHuhf831e3Tq15X8btwOmRIG+PbvZNDbL7zFbaqEJUW2NLkCbO3cusbGxTJ8+nbCwMLZv385rr72G0WjkpptuqvC+4uJiZs6cSW5uLk899RS+vr6sW7eO2bNns2jRIqKiotRrY2JimDNnDv3792f+/PlkZGSwbNkyZs6cyfLly3FyclKvXbhwIdu2bWPKlCl06tSJgwcP8sEHH5Cfn88DDzygXpeVlUX37t2ZMGECPj4+pKWl8cUXXzBjxowy/Qshmp7amEFLScsgI8sU/HRs27paBWqv1qlthPr4dNx5W4eGs5MTTo6OFJeUyBKnEDXQqAK0ffv2cfjwYebNm8eIESMA6NmzJ0lJSSxZsoQbb7wR+woymL7//nvi4uL48MMP6dbN9MkwOjqayZMns2TJEpYtW6Ze++GHHxIWFsbrr7+OQ+lG3uDgYJ544gk2bdrEHXfcAUBcXBzff/8906ZNU4+1io6OJjs7m48//pixY8fi5eUFUGZGDaBv376MGTOG77//XgI0IZo4yzMptQrQTpxJUB93aNvaprbCQlqqAdWpc4m2Dg2dToe3hwcpGRnk5OdjMBqx1/DsUSGaukb1t2X37t24uroydOhQq+dHjRpFamoqx44dq/Te8PBwNTgDUzHFkSNHcvz4cVJK08FTUlKIjY1l5MiRanAG0L17d8LCwvj555+t2lQUhVtvvdWqr1tvvZWioiIOHDhQ6ffj5uaGk5NThUGlEKLpsFri1CxAs9h/FmlbgOZgb09k61YAnL+YRGFhkU3twZUjnxRFIVeO+hOiWqodoBmNRo4cOcLFixfLvFZSUmIVwGgtLi6O1q1bWwVOAG3btlVfr8jZs2fV6yq71/zfiq617CMuLg4fHx/8/f2rPB6DwYBer+fSpUu8//77KIrCuHHjKhw3QGpqKidOnFD/xMfHV3q9EKLhMQdoDvb2uLq4aNLmibOWCQK2BWgA7SLCADAaFc4mlP0dX11WpTZkmVOIaqnWEmd8fDyjRo3i+PHj6HQ6Ro8ezapVq9QAJT09nWHDhmHQ4Cy38mRlZdGqVasyz3t6mrKFsrOzK7w3Oztbva6ye7OysgDUpcmrr7XsIysrq9zrXF1dcXR0VNuyNGnSJBISTMsS/v7+vPfee3TsWPnRLN9++y2rV6+u9BohRMNlNBrJLp1B8vb0tGmvmKWTpTNobq4uhLVqYXN75gAN4PS583TpULOyHWZWpTYkk1OIaqlWgPbcc88RGhrK1q1byczM5Nlnn2XAgAHs3LlTDZwURamVgZrZ8outsnuvfq2ia6vTf3nXvvHGGxQUFJCcnMyGDRuYM2cO//jHP4iOjq6wnTFjxjBgwAD16/j4eN58880qj0MIUb9y8/MxGo2AdvvPsnPyuHg5FYD2bcKw02B/V7s21gGarayL1UompxDVUa0A7aeffmLr1q2EhoYSGhrKli1beOSRRxg0aBC7du3C2dlZs0+G5fH29i53Vionx/QXv7zZLDMvL69yZ9jM95pn0ry9vQEq7MdyFs7b25vTp0+Xua6goICSkpJyx9OmjekTaZcuXRg4cCBTpkzhgw8+YNWqVRWOPSAggICAgApfF0I0bFm1UGLDXF4DoENkzeufWWpvEaCdirM9UcDb4velzKAJUT3V+siVn5+Ps7Oz+rVOp2P58uWMHDmSwYMHc+aMNkeEVCQyMpL4+Hj0er3V82fPngWuBD8V3Vve+MzPRUZGWrVhbvPqfiz7iIyMJDMzk7S0tGqPB0xJCh06dOD8eds/qQohGi7LMhPeHmW3WtSEdYFa2/efAfj5eOHnY/pgeTruvM0rIu6ururMnuxBE6J6qhWgdezYkcOHD5d5fsmSJYwaNYrbbrtNs4GVZ9CgQRQUFPDTTz9ZPb9lyxYCAgLo0qVLhfcOHjyYhIQEq0xPvV7PDz/8QJcuXdQZqsDAQDp37sy2bdus9tIdPXqUhIQEhgwZoj43cOBAdDodW7Zssepr8+bNODs707dv30q/n6KiIo4dO0ZISMi1v3khRKNlubyn1QzaKYslSK1m0ODKPrTM7BzSMsquJFSHnZ0dXu7ugGkGrba3wAjRlFRrifPOO+/k008/5f777y/z2ocffoiiKFb1xLTWr18/evfuzcKFC8nPzyckJIQdO3Zw4MAB5s6dq5arWLBgAVu3buWzzz4jKCgIMJXiWLduHfPmzWP69OlqodqEhAQWLVpk1c+jjz7KrFmzmDdvHuPGjVML1bZp08aqpEabNm3URAk7Ozs6d+7MoUOH2LhxI1OnTrVa4nzssccYMGAArVu3xsPDg6SkJNavX8/FixdlP5kQTVxt1ECLS7gAmFYy2oSVTZ6qqXZtwjgYcxQw7UML8POxqT0vDw8yc3LQGwwUFBbi5uqqwSiFaPqqFaC9+OKLvPjiixW+vmTJEpYsWWLzoCrz5ptvsnz5clauXKke9fTKK69YHfVkNBoxGAxWn9acnJxYtGgRS5YsYfHixRQWFtK+fXvefffdMkVio6Ojeeedd/joo4944YUX1KOeHn/8catTBABmzZpFQEAA33zzDenp6QQFBTFjxowyhWm7devGzp07SUpKoqCgAG9vb7p27cqTTz4pRz0J0cSZ91/Z2dnh4eZmc3tGo5G40jIYIUGBuLg4X+OOqrPeh3aefj1t+/3k7ekBl0yPs3JzJUAToooa1UkCYCru+vTTT/P0009XeM1LL73ESy+9VOZ5Pz8/Xn755Sr1c/3113P99ddf8zoHBwcmT57M5MmTK73uiSeeqFK/QoimRVEUNUnAy91dk2zLyynpFJQWkm0Trt3sGUC7iFD18RkNThS4uhZacGCgzW0K0Rw0qpMEhBCisSkoLFQTm7zKqcVYE2dLlzcBIsO13cPaJrwVdnambPzTGgRolkkRkskpRNXZHKDZ29urhVeFEEJYy8rR/oin2gzQnJ2cCAkyFb2NT7yk1m+rKS9PqYUmRE3YHKBJVo4QQlTMMijRKkHgbLxFgNZa+yzw1qHBABQWFZOclmFTW+YsTrAuNyKEqJwscQohRC2ymkHTqMSGOUFAp9MRURpMaSki7Eqb8ecv2dSWg4MD7qWJAbLEKUTVSYAmhBC1yDIo0aJIraIoxJ03BWitWgZomsFpZhn0nUu0LUCDKzOHBUVFFJeU2NyeEM2BBGhCCFGLsnIslzjdK7myai6npJNfUAhAG433n5lZBWg2zqCB9cyhzKIJUTUSoAkhRC0yl9jwcHNTi2nbwipBoBb2nwG0tih8q+UMGsiRT0JUlQRoQghRSwqLiykqLgasDw63hXUGp7Y10Mx8vDzw8TKN91zpcqotLLNXsyWTU4gqkQBNCCFqSbbF8qZWJTbMCQKgfYkNS+ZEgdT0THLz8m1qy8ti711Wbp5NbQnRXNgcoL388sv4+PhoMBQhhGhasnK1z+C0LLERoeEZnFdrbbEPLd7GZU7rPWgygyZEVdgcoL3xxhtWh4ILIYQwsT4kXZsMTvOesOAWAbjWQganmWWpDVv3oTk7OeHk6AhILTQhqkqWOIUQopZYzhZpMYOWkZWjLje2Dg2yub3KaJnJqdPp1CXenPx8DDaeTiBEc6DpYelGo5HExEQuXLhASQW1bgYPHqxll0II0WBZz6DZHqBZLjWGh9RygKbhDBqYjnxKychAURRy8/I0S5oQoqnSJEBTFIUFCxawaNEi0tLSKr3WYDBo0aUQQjR45ppfri4u6hKfLSwDtNqeQQtuEYiToyPFJSU2nyYAZUttSIAmROU0CdBefPFF3nnnHVq0aMHDDz9McHAwDg6aTs4JIUSjUqLXk1dQAGiXwRl/IUl93DpE+yOeLNnb2xEe0pLT5xJJuHgZvcGAgw113CxPUZBitUJcmyZR1OrVq+nYsSOHDh3CQ6NfREII0Zhl10IGp/UMWu0GaABhrYI4fS4Rg8FAUnIaocEtatyW5SkKWZLJKcQ1aZIkkJuby+jRoyU4E0KIUlpncALEJ5pm0JydnWgR4KtJm5UJa3UlIEu8dNmmtiyXNGUGTYhr0yRAi4qK4uJF26tNCyFEU6F1Bqder+dCUgpgShCws6v9JPzQVi3Vx+cvJtvUlrurqzpmOe5JiGvT5G/43Llz2bBhA7/99psWzQkhRKNnGYRosQctMSlFTbJqXcsZnGbhFgFa4kXbZtDs7Ozwcjctc2bn5qIoik3tCdHUabIH7ZZbbmHNmjXceuutjBkzhuuuu67C4rUPPvigFl0KIUSDZnmKgBZLnHVZYsPMagbNxiVOMGVyZubkoDcYyC8sxN3V1eY2hWiqNAnQioqK2LBhA6mpqaxcuRIwFSa0pCgKOp1OAjQhRLNgPofTydERF2cnm9tLSLTI4KzlEhtmgX4+ODs5UlRcQqKNS5xQutRbGmdm5+ZKgCZEJTQJ0GbNmsUnn3xCjx49mDBhgpTZEEI0awajkZx8U8V/bw+PMh9Ya6KuMzjBtCwZEtyCs/EXSLyUjMFgxN6+5jtjrq6FFhwYqMUwhWiSNImivvzyS3r16sW+ffskMBNCNHu5eXnqHisvjQqyJljWQKujAA0gLLglZ+MvUKLXk5KWQVAL/xq3JbXQhKg6TZIECgsLGTZsmARnQggBZOVYZHBqXKTW39cbD7e6WxoMtSi1cd7GRAEvi2xWqYUmROU0CdB69erF6dOntWhKCCEaPasMTg1KbOTk5pGemQ3UXYKAWViwdokC5ixOgGwptSFEpTQJ0ObPn8+WLVv47rvvtGhOCCEatcycbPWxj2f5Ge3VkWAxc1XXAVqoVakN2xIFHBwc1MQAWeIUonKarEn+8MMPDB06lLFjxzJs2DCioqLKLbOh0+n4+9//rkWXQgjRYGVmX1m+8/GyfQ/a+QsWAZpFwFQXLE8T0KrURl5BAQVFRRSXlGhyiLwQTZEmAdqrr76qPt65cyc7d+4s9zoJ0IQQzUFm6R40Z0dHXJydbW7PMjAKC6nbAK1lgD8ODvbo9Qabi9WCacn3UorpRITs3FwCfGv/yCohGiNNArRdu3Zp0YwQQjR6eoOBnLw8ALy9vDQpsWE5g2a5J6wu2NvbERLUgvjES5y/lKzWtKypq0ttSIAmRPk0CdCGDBmiRTNCCNHoWW5+99GoxIZl9mRocItKrqwdYcGmAK2oqJjU9EwC/WseVFlmtWZLJqcQFar903aFEKIZsU4Q0CpAM5XYaBHgh4uL7Uum1WV9aLqNmZwWtdCyJFFAiAppEqDt3buXWbNmkZSUVO7rSUlJzJo1i/3792vRnRBCNFiWCQLeGiQIZOXkkpVjWjKt6wQBM8tEgcRLtmVyWpYdkVIbQlRMkwBt4cKFbNy4kaCg8tO/g4KC+O6771i0aJEW3QkhRIOl9Qya5cZ8y6KxdSnUYt+b5YkGNeHs5KRmbkqpDSEqpkmAdujQIQYOHFjpNYMHD5YZNCFEk5dpcYqAFgGaVQ20VnVbA80szLIWmo0zaDqdTt2HlpOfj8FotKk9IZoqTQK05ORkQkJCKr0mKCiI5GTb/mILIURDl1W6xOnu6oqjBjW+LGfQwuppiTO4hT/2dqZ/LmzdgwZXjnxSFIXc0oxXIYQ1TQI0Hx8fEhISKr0mPj4eD43OpBNCiIaosLiYgqIiQJsCtWA9g1bXNdDMHBwcCG4ZAJhm0MwHwdfU1aU2hBBlaRKg9e/fn3Xr1nH+/PlyX09ISGD9+vXccMMNWnQnhBANUpZlgoAGRzyBdQ20kKD62YMGVzI58wsK1XNBa8rbIpNT9qEJUT5NArRZs2aRn5/PgAED+Pjjj7l06RIAly5dYs2aNQwYMICCggKeffZZLboTQogGqXZKbJgCtJaBfrg4O2nSZk2EWdRfs/VEActMzqwcqYUmRHk0KVQ7aNAgPvjgA2bOnMnDDz8MmDaCmqfB7ezsWLx4MYMHD9aiOyGEaJC0PoMzKyeX7FzTHq2wekoQMLOqhXYpmeu6dqhxW94WwWumBGhClEuTAA3giSeeYMiQISxZsoRDhw6RmZmJj48Pffr04dFHH6Vbt25adSWEEA2S1hmc9XlI+tUsj5iyNVHA3dUVB3t79AaDzKAJUQHNAjSAbt268Z///EfLJoUQotHIKl3i1Ol0eGqQFJVw8UrNsfqqgWZmXazWtgBNp9Ph7elJWmYm2bm5GIxGNUtUCGEifyOEEEIDiqKoS5xeHh6aBBznG0ANNLNWQYHqIennL9peMsm8BGxUFHJypdSGEFeTAE0IITSQV1CA3mAAtEwQuBII1VeJDTMnR0eCAv0BU+Boa6kNH4ssV8vkCiGEiQRoQgihgSyN95/BlUPSdTodIUGBmrRpC/Mya25evno+aE1ZJlFYJlcIIUwkQBNCCA1YZ3DaXgNNUZQrJTYC/HB2qr8SG2aWiQK2ltrwkUxOISolAZoQQmggM9uiBpomJTbyyMnNB+p/edPMMlHhvI2JApalNrJkiVOIMiRAE0IIDVjOAnlrUWLDIoOzvktsmGk5g+bi7IyLszMgS5xClEcCNCGE0IA5QHOwt8fd1dXm9ixroNV3kVqzUMvTBC5pl8mZV1BASUmJze0J0ZRoVgetuLiY9evXq0VqDaXZTJZ0Oh0rV67UqkshhGgQDEajeqakj5enWo7CFpaHpNd3DTSzEK0DNE9PklJSAVOAG+jnZ3ObQjQVmgRo8fHx3HTTTZw5c6bS1GsJ0IQQTVFObq76u0+rQ9ITG1ANNDNXF2f8fb1Jy8giMSnF5vasS21IgCaEJU0CtGeeeYbTp0/zwAMPMHnyZEJDQ3Fw0PSQAiGEaLC0PuIJrsyg2dnpCAmu/xIbZqHBLUjLyCI9I4v8gkLcXF1q3Ja3RTJFluxDE8KKJlHUzp07GT58OGvWrNGiOSGEaFS0zuC0LLERFOiPk6OjzW1qJTS4BX8cOwXAhaRk2rcJr3FbUmpDiIppkiRgNBqJjo7WoikhhGh0tJ5By8zOITfPVGIjNLhhZHCaabkPzdvivFIJ0ISwpkmA1r9/f44fP65FU0II0ehYlonw1qBIbUM64ulqWmZyOjg44OnuDkBWdrbNx0cJ0ZRoEqAtWLCAXbt28dVXX2nRnBBCNCrm2R8XZ2dcNKj43xBroJmFBF0J0C5okihgmnEsKimhsKjI5vaEaCpqtAft9ddfL/PcsGHD+Nvf/saQIUOIjo7G29u7zDU6nY6///3vNelSlZ+fz4oVK9i1axc5OTmEh4czceJEhg8ffs17MzIyWLJkCfv27aOwsJB27doxdepUevXqVebaw4cPs3LlSk6fPo2Liwv9+/fnsccew9fX1+o6vV7P2rVr2bx5M2lpaQQHBzNu3DjGjx9vdd13333HL7/8wunTp0lPTycwMJDevXszadIkAgICbHpPhBD1p6i4mPyCAgB8NZg9A0hogDXQzCxn0C5oVAvtfJIpIM3MzsHVpeZJB0I0JTUK0F599dUKX/vxxx/58ccfy31NiwBt7ty5xMbGMn36dMLCwti+fTuvvfYaRqORm266qcL7iouLmTlzJrm5uTz11FP4+vqybt06Zs+ezaJFi4iKilKvjYmJYc6cOfTv35/58+eTkZHBsmXLmDlzJsuXL8fJ4hPywoUL2bZtG1OmTKFTp04cPHiQDz74gPz8fB544AH1uo8++ojo6GimTZtGYGAgCQkJrFmzhj179rBy5Ur8JL1ciEYpI+tKgoCvtzYB2vmLlgFaw6iBZubr7Ymbqwv5BYWa1ELztiq1kU1wi4aTsSpEfapRgLZr1y6tx1El+/bt4/Dhw8ybN48RI0YA0LNnT5KSkliyZAk33ngj9vb25d77/fffExcXx4cffki3bt0AiI6OZvLkySxZsoRly5ap13744YeEhYXx+uuvq+VCgoODeeKJJ9i0aRN33HEHAHFxcXz//fdMmzaNe++9V20zOzubjz/+mLFjx+JV+ol65cqVVrNvUVFRdOjQgUceeYSNGzcyadIkbd8sIUSdyMjOUh/7epVdOaiJRMsSG0ENK0DT6XSEBLfg1NkELiWnoTcYcKjg925VSCanEOWrUYA2ZMgQrcdRJbt378bV1ZWhQ4daPT9q1Chef/11jh07Rvfu3Su8Nzw8XA3OwLRBdeTIkfz3v/8lJSWFwMBAUlJSiI2N5ZFHHrGq5da9e3fCwsL4+eef1QBt9+7dKIrCrbfeatXXrbfeysaNGzlw4IA6q3f10ihAx44dsbe3JznZ9k+hQoj6kZGt7QyaoihqDbSgFgE4Oja8mpKhQaYAzWAwkJScZrXsWV2WZUnkTE4hrmhUZ3HGxcXRunXrMkVw27Ztq75ekbNnz6rXVXav+b8VXWvZR1xcHD4+Pvj7+1d7PGBaSjUYDLRp06bS61JTUzlx4oT6Jz4+vtLrhRB1J91yiVODPWgZWTnk5Zv2tDW0BAEzLfehebi5YW9n+qcoS2bQhFBp/tFMr9dz8uRJsrKy8Pb2pkOHDpqdKpCVlUWrVq3KPO9ZOkWebfFJ9mrZ2dnqdZXdm5VlWq7wKucXraenp1UfWVlZ5V7n6uqKo6Oj2lZ58vPzWbhwIS1atGDUqFEVXgfw7bffsnr16kqvEULUj8zSv+eODg54uLnZ3J7l/rOGVgPN7OpSG31taMvOzg5vT0/Ss7LIysnBaDRiZ9eo5g6EqBWaBWgpKSm89NJLfPbZZxSUZjSBKVi57777eOuttwgMtH3zpy2HEFd279WvVXRtdfqv6NqioiLmzp3L5cuX+ec//4nbNX6pjxkzhgEDBqhfx8fH8+abb1Z5HEKI2lGi15OdlweYZs+0OCTdKkGggdVAM7MqVpukRaKAKUAzGI3k5ufjZVHAVojmSpMA7cKFCwwYMICEhAQCAwMZPHgwLVu25PLly/z666+sWLGCH374gT179hASElLjfry9vcudlcopnRYvbzbLzMvLq9wZNvO95pk0c3mQivqxnIXz9vbm9OnTZa4rKCigpKSk3PEUFxczd+5c/vzzT95++226dOlS4ZjNAgICpBSHEA1Qpsb7zwDOX2i4NdDMtCxWC2X3oUmAJoRGe9Cee+45EhISeO2114iPj2fTpk2sWrWKTZs2ER8fz6uvvkp8fDzPP/+8Tf1ERkYSHx+PXq+3ev7s2bMAle7lioyM5MyZM2WeNz8XGRlp1Ya5zav7sewjMjKSzMxM0tLSqjSe4uJiXn75ZX7//Xfmz59fbv01IUTjYZUgoFEGZ8LFhlsDzaxloJ+aMa9JLTTJ5BSiDE0CtC1btnDLLbfw97//HZerigy6uLgwb948Ro4cyebNm23qZ9CgQRQUFPDTTz+V6T8gIKDS2ajBgweTkJDAsWPH1Of0ej0//PADXbp0UWeoAgMD6dy5M9u2bcNgMKjXHj16lISEBKsM1oEDB6LT6diyZYtVX5s3b8bZ2Zm+fa/szDAHZ7/99htvvPEGffr0qdmbIIRoMGqjBlripSslNlq1bJgz5w729urYEi8l23xEk4/FakNWTsV7iYVoTjRZ4iwuLqZnz56VXtOrVy/27t1rUz/9+vWjd+/eLFy4kPz8fEJCQtixYwcHDhxg7ty56ie6BQsWsHXrVj777DOCgkyfQEeNGsW6deuYN28e06dPVwvVJiQksGjRIqt+Hn30UWbNmsW8efMYN26cWqi2TZs2ViU12rRpw+jRo1m1ahV2dnZ07tyZQ4cOsXHjRqZOnWq1xDlv3jwOHDjAAw88gJeXF0ePHlVfc3d3JyIiwqb3RghR97SugaYoCudLTxEIbqAlNsxCgltw/uJlCgqLyMjKwc+n5gGq1QyalNoQAtAoQOvVqxexsbGVXhMbG6vJkt6bb77J8uXLWblypXrU0yuvvGJ11JPRaMRgMFh9qnNycmLRokUsWbKExYsXU1hYSPv27Xn33XetThEAU7HZd955h48++ogXXnhBPerp8ccftzpFAGDWrFkEBATwzTffkJ6eTlBQEDNmzChz1NMvv/wCwNq1a1m7dq3Va1FRUXzwwQc2vzdCiLplnkGzs7PDy8Pd5vbSM7PJKygEICykYS5vmoUGWe9DsyVAc3F2xtnRkaKSElniFKKUJgHaG2+8wU033cTq1at56KGHyrz+0UcfsWnTJn744Qeb+3Jzc+Ppp5/m6aefrvCal156iZdeeqnM835+frz88stV6uf666/n+uuvv+Z1Dg4OTJ48mcmTJ1d63c8//1ylfoUQjYPBaFTrdvl4eWpSGsIyg7OhJgiYWScKXKZH53Y1bkun0+Ht5UVyWho5eXno9XrNyjMJ0Vhp8jdg165dDBs2jClTpvDOO+8wYMAAWrRoQXJyMnv37uXEiROMHDmSnTt3snPnTvU+Lc7mFEKI+pCVk4OxdJZeqwSBxlADzUzzQ9M9PUkuTbjKzMkhoJzTV4RoTjQJ0CwPT4+NjS13uXPr1q1s3brV6jkJ0IQQjVW6RSkef2/tA7TwBloDzSwk6EpdSy1KbfhZvIcZWdkSoIlmT7MZNCGEaE7SM68EaH4+GgVoFjXQwhr4EmeIxrXQLLNgMyo5FUaI5kKTAK2+Dk8XQoj6kp6VqT728/bRpM3zpYGOvZ1dgy2xYebq4oy/rzdpGVkkJqXY3J7lOaYZlRyTJ0RzIQeeCSFEDZhn0Ozt7TXJ4FQURV3iDG4Z0Cg2yZv3oaVnZJFfmn1aU14eHmqihcygCVHDAO2+++7jm2++qXGntt4vhBD1Sa/Xk5WbC4Cfl5cmGZxpFkFOQ1/eNLNKFLDxTE47Ozu1Hlpm6aHpQjRnNfqt8vnnn3PkyJEad2rr/UIIUZ8ysrPVOoua7T+zShBo2DXQzGprH5rRaFQDYCGaqxrPocfExPDxxx9rORYhhGgULDM4Ndt/ZnUGZ2OcQdNiH5o3cB4wZXJa7ksTormpcYC2fv16NmzYUO37bD2zTQgh6lutZHBa1UBrUcmVDUdorWZyZgGhNrcpRGNVowBt1apVNnd89fFKQgjRWKRZzaA13yVOrYvVXl0LTYjmrEYB2qRJk7QehxBCNBrpmZkAODk64uHmpkmbCaUBmr29PcENvMSGmY+XJ+6uLuQVFGoyg+bj6YlOp0NRFMnkFM2elNkQQohqKC4pITc/HzAtb+p0OpvbVBSFxNIALaRlAA729ja3WRd0Op2aKHApOQ29Xm9Te/b29ni5m0qWZGRlyZYY0axJgCaEENVgtf9MowSBtIwsCgqLAAhtJAkCZuaEBoPBQFJKms3t+ZYuc+oNBjUQFqI5kgBNCCGqIc3qBAFt9p8lNKIjnq5muQ8t4cLlSq6sGstEgXQ5UUA0YxKgCSFENaRmZKiPA3x9NGmzMR2SfjXLhIbES7YHaJZBrwRoojmTAE0IIaohLSNTfezv46NJm9Y10BpHBqeZ1jNoVgFapgRoovmSAE0IIapIURRSSzM4Pd3dcXZy0qRd6wCtcdRAM7OeQdOgFpqXl5p4ITNoojmTAE0IIaooOzdXzVTUankTrgRo9vb2BLVoHCU2zPx9vXF1cQbgvMVeuppycHDA28MDMGVyypmcormSAE0IIaoo1Wp501eTNhVFUQO0kKDARlNiw0yn06mZpxcup6I3GGxu03w6g95gICcvz+b2hGiMahyg9ezZk//+979Wz23dupVZs2aVe/1rr72Gg0ONT5YSQoh6VxsJAilpGRQWFQONL4PTLKx0H5rBYCApOdXm9izLl6TJPjTRTNU4QIuJiSEpyXo6e//+/SxevLjCe6TooBCiMUsr3X8GEOCrzQya5cb61o3kiKerWdZuO39RgyOffCwTBTJtbk+IxkiWOIUQoorMM2hOjo54lla8t1V84iX1cevQYE3arGvhVgGa7fvQLDM50yRRQDRTEqAJIUQVFBYVqZXt/X18NDniCSD+wpUArbEckn41rWfQvD09sbMz/fOUblEYWIjmRAI0IYSoAuvlTR/N2o1PvDLj1Dq0cQZo1jNottdCs7ezw9fLdKJAVnYOBg0SD4RobCRAE0KIKrBMENAqgxOuLHG6uboQ4OejWbt1KcDPBxdnU004LQI0uLLMaVQUMnNyNGlTiMZEAjQhhKgCqxIbGs2gFZeUcKk067F1SJBmy6Z1TafTqRmoF5JSNC21AZIoIJonm+pe/N///R/79+9Xvz59+jQAo0aNKnOt+TUhhGiMUtLTAbDT6TQ74inxUjJGoym7PbyRJgiYhQa35FTcebXURmiwbSVD/K8qtdHexvEJ0djYFKCdPn263MBry5Yt5V7fWD8dCiGatxK9nozsbMA0s6NVMVmrDM5Gdkj61cIsxp9w4bLNAZrlDFqazKCJZqjGAVpcXJyW4xBCiAYrNSNDreMY6OevWbvWCQKNewbNsoZbwoUkbujdw6b2PN3dcXJ0pLikxGr/nxDNRY0DtNatW2s5DiGEaLDMy5sAgX7aJwhA4w/QLEuEWAaeNaXT6Qjw9eFicgp5BQUUFBapZ34K0RxIkoAQQlyDZYDWws9Ps3YTLA4Xb6w10MwsS4RY1nazhWW2bFqmzKKJ5qVGM2iTJ0+uUWc6nY6VK1fW6F4hhKgvyeYEATs7zRIEAOJLA7QWAX6NfnbIx8sTLw93snPzrAJPW1jWm0vNyCQ0qHEHsUJUR40CtNWrV5f7vE6nK/e8TfPzEqAJIRqbkpISMrNNdbj8vb2x1yhBIDM7l6zsXKDxz56B6fd869Ag/oo9w+WUdE2WJC3PO5V9aKK5qdESZ1xcnNWfM2fOcNttt+Hv788bb7zBjz/+yPHjx/nxxx95/fXX8ff35/bbb+fUqVNaj18IIWpVakbmlQQBf+2WN633nzX+AA2sS4VoMYvm6+2tZv+nyhKnaGZqNIN2dYLAggULOHDgAH/88QfBwVf+gnbs2JHBgwfz8MMPEx0dzVdffcVzzz1n24iFEKIOJVslCNRSgBbSuBMEzFpflSjQsa1tyWQO9vb4enmRnpVFZlY2BoNBsxlMIRo6TZIEVq5cyd13320VnFkKCQnh7rvvZvny5Vp0J4QQdaa2EgTizl9UH0eGt9Ks3fp0dakNLZhPbTAqCulZWZq0KURjoEmAlpiYiIuLS6XXuLi4kJiYqEV3QghRZywTBMznQ2rhbPwF9XGbJhKgWS5xapXJabkPTQrWiuZEkwAtNDSUdevWUVhYWO7r+fn5rFu3jtDQUC26E0KIOlFUXExm6QkCAT4+mi6vxSWYZtDc3VwJ9Neutlp5iowlnCtM5nxRarmJXFoJa9VC3TOmRS00ML3vZpIoIJoTTQK0qVOncvbsWQYMGMCGDRtIS0sDIC0tjfXr1zNw4EDOnTvHtGnTtOhOCCHqxOXUNPVxy4AAzdrNLyhUD0mPDG9Va8fgbc/4k7FHFtDn9+cZe3QBtx2Zz81/vcFr8V+QWJR27QaqydnJieCWpvcpIfGSJsGgv1UmZ6bN7QnRWNh0FqfZnDlzOHnyJKtWreLOO+8ETMsBRqMRAEVRePjhh5kzZ44W3QkhRJ24nJaqPg4K0O6Ip3Pnryz/RYaHaNauWaY+j/kJX7M1I6bMa5dLMvkm9QA/ZPzJO5EPcoNXR037bh0SxMWkFPIKCknLyCLAz8em9txcXHB3dSWvoEA9ckvOdRbNgSYzaHZ2dqxcuZJdu3YxadIkoqOjiYiIIDo6moceeohdu3axcuVK+UslhGhUamsGLe685f4zbQO0fEMRj5xcahWcdXQN4VbfaPp7dcRZZ/pcnmMo4IlT/+WL5L2a9t/aah+aNsuc5uzZ4pISsnJyNWlTiIZOkxk0syFDhjBkyBAtmxRCiHqhKAqXU00zaK4uLni6u2vW9tmEKxmcWiYIGBQjz8et5USBKQD0tnfjhfBx3OrbU/2AnGMo4OW4T/kp6yhGFP5x/hvCXAI0m0mzPpPzEr26d7K5zUA/P85dMH1PKelp+Hh52tymEA1djWfQVq1aRUpKipZjEUKIBiMzO4eikhLAtLyp5QpAXMKVGTQtlzgXJn7Lz1nHAPC0d2F1x6cY5dfLauye9q78s+3DPNhyKAAKCi/F/R+XizM1GYPVmZzntcnktCxvYlmXToimrMYB2pQpU2jVqhWDBg3i/fffl1MChBBNSlLqlf1nLf21W96EKxmcbq4utAzUprbawZxT/F/yzwA4YMf7kQ8T6dqy3GvtdHY8E3Ibg7w6A5Chz+O5sx+jVww2j8My4LSs9WaLQL8riQIp6ZLJKZqHGgdov/zyC7NnzyY9PZ05c+bQqVMnOnfuzEsvvcT+/fu1HKMQQtQ5ywQBLfefFRYVcyHJtPoQERasycxcsVHPW/Ffq1/PDhtLX6/2ld5jp7PjzTb3EexkCn5i8s7xdYrtv7v9fb3x9HAD4KzFTKEt3FxdcXcztZmSnl6rpUKEaChqHKD169ePf/zjHxw9epRTp07x9ttvExgYyDvvvMOAAQMIDg5m+vTpbNq0iaKiIi3HLIQQtc48g6bT6Wih8Rmc5gBDqwSB1Zd3ca4oGYAe7q35W+CAKt3n4+DO/DYT1a8/vLiFbH2BTWPR6XS0CTPtq7uckk5uvm3tmZmXOUv0ejJzcjRpU4iGTJMszrZt2zJ79mx+/vlnLl++zIoVK+jbty+ffPIJt99+OwEBAYwfP561a9eSLvsHhBANXHFJCemZpmOF/H28cXTQLp/KclYpMsz2BIHEojSWX/oBAHvsmBs+ATtd1X+19/SI5BbfaAAyDXksT/rB5jFZBp7xmi1zXgmSU9Lk3xHR9GkSoFny9/fn4YcfZv369aSmprJu3Truvvtu9u7dy6RJk2jZsiVDhw7VulshhNCM1f4zDZc34cr+M9BmBm3Fpe0UK3oAJrYcTEe36rf5dMhotfzGp8m7SSi0LQHM8mxRy4xVW7Sw2IcmiQKiOdA8QLPk4uLCmDFjWLlyJZcuXWL37t0888wzJCVpUxtHCCFqw8XkZPVxq8AWmrZ9+tx59XFka9sCtMSiNDamHQJMWZvTgm6qUTutnP14oDSrU68YWJ603aZxWX5fcRoFaFYzaBKgiWagVgM0SzqdjgEDBvDOO+8QGxtbV90KIUS1XUq+MoPUqkWgpm2fOmsK0NxdXWjV0rbZuRWXtqPHdGLL/S2G4OXgWuO2JgfdiKe96f5N6b/ZVHbDcmZQq0QBy1p0KRkZ6kk1QjRVNd5Y8fjjj1f7Hp1Ox3/+85+adimEELVOr9dzufQ8YW8PDzV7UAs5uXkkpZjabtcmzKYMzqtnz+5rMdimsbnbu3BP4ACWJ21HrxhYe/knZoeNrVFbLfx9cXd1Ia+g0Krmm60C/fzIyctDr9eTkZ2Nv8VB6kI0NTUO0JYuXVrlay1/CUmAJoRoyC6npamzM8EttF3ePBV3ZXmzfZtwm9pac3mXZrNnZve2GMTHl3+kSNHzVeo+pgWPwNuh+ico6HQ62oSHcOTEGS5eTqWgsAhXF2ebx9fS35+z503v4eXUNAnQRJNW4wBt165dVbouISGB119/nTNnzshZnEKIBu9ibS5vWgZokWE1bidbn8+3aYcBcLVz4r4Wg2weG4C/oydjA/rwv5RfKDAW80XKLzwSXLN9bW3CW3HkxBkAzp2/SOf2bWweX5BFwkZSaipd2rW1uU0hGqoaB2jXOnMzIyOD+fPn85///IfCwkL69+/P22+/XdPuhBCiTlyyTBCo1Rm0mgdo36Tup9BYDMAY/+vxctBuGXZSy2F8lbIPIwr/S9nLw0E34qizr3Y7lmeMxiVoE6AF+vlip9NhVBSrQsJCNEWaJwkUFhayYMEC2rZty/vvv09ERATffPMNe/fuZeDAgVp3J4QQmjEYDGqJDQ83N00PSAc4FZcAmJYA27YOrVEbesXA5yl71a+1mj0zC3X2Z4hPVwBSSrL5KfNojdqxPPLpjEb70BwcHPD3NZXbyMjKpqi4WJN2hWiINKu+qCgKK1eu5LXXXuPChQu0atWKd955h8mTJ2Nnp10cmJ+fz4oVK9i1axc5OTmEh4czceJEhg8ffs17MzIyWLJkCfv27aOwsJB27doxdepUevXqVebaw4cPs3LlSk6fPo2Liwv9+/fnsccew9fX1+o6vV7P2rVr2bx5M2lpaQQHBzNu3DjGjx9vdV1cXBzr1q3j1KlTnDlzhsLCQhYvXkx0dLRtb4gQQjMp6RnoDabzKINbBGq6LcNgMHIm3hSohAa3wM3VpUbt/Jh5hEvFpvMoB3l1JsJF21k+gLsDB7Ar8wgAX6b8wgjfHtVuwzJAOxuvXaJAUECAWmbjcloa4cHBmrUtREOiSeS0fv16unbtyvTp08nNzWX+/PmcPn2aqVOnahqcAcydO5ctW7bw0EMP8c4779CpUydee+01fvih8urXxcXFzJw5k19//ZWnnnqK+fPn4+vry+zZs4mJibG6NiYmhjlz5uDr68v8+fN56qmn+PXXX5k5cybFV31iW7hwIZ988gnjxo3jvffeY9CgQXzwwQesXbvW6rrY2Fh2796Np6cnPXv21OS9EEJo60LyZfWx1sub5y9dpqjI9PvDluXNz5L3qI/va2lb5mZF+nm2J8zZH4D9OSeJr0Hh2paBfmpiwNn4RM3G1jLAX318OTVNs3aFaGhsmkHbs2cPzz//PPv378fJyYlnnnmGl19+ucwsk1b27dvH4cOHmTdvHiNGjACgZ8+eJCUlsWTJEm688Ubs7cvfK/H9998TFxfHhx9+SLdu3QCIjo5m8uTJLFmyhGXLlqnXfvjhh4SFhfH666/jUHrES3BwME888QSbNm3ijjvuAEyzYt9//z3Tpk3j3nvvVdvMzs7m448/ZuzYsXh5eQFw8803c+uttwLw448/8ssvv2j/BgkhbHL+0pUi2qFBQZq2fepsgvq4phmccYWXOZxr2ngf4dyC/p4dNBnb1ex0dkwI6M+iC98B8FXqPp4NHVO9NuzsaBcRyl+xpkzO3Lx8PNxt3ytnmShwOVX2oYmmq8bTW2PGjGHIkCEcPHiQSZMmcerUKd57771aC84Adu/ejaura5mjokaNGkVqairHjh2r9N7w8HA1OAPTfoaRI0dy/PhxUlJMnxBTUlKIjY1l5MiRanAG0L17d8LCwvj555+t2lQURQ28zG699VaKioo4cOCA+pzWM4lCCG2VlJSo+8+8PDzw9vDQtH0tEgS+TtmvPp4Q2L9WM+PHBvRRkwM2pB6k2KivdhuWgejpc9rMonm6u6szc5fT0tSD54Voamo8g/bdd9+h0+kIDw8nKSmJRx555Jr36HQ6vv/++5p2SVxcHK1bt7YKnMB0WLv59e7du5d779mzZ7nuuuvKPG95b2BgIHFxcVbPX33tX3/9ZTUeHx8f/P39y1xnfl0I0ThcTE5R65+FaTx7BraX2Cg26tlYWlrDUWfPbf5l985qydfBg5t8r2NT+m9kGfLZnXWM4dXci2b5fZ6KO09UV9tn/HQ6HUEBAcQlXqCouJjM7Bx8vb1sbleIhsamJU5FUYiLi6tyIGLrp72srCxatWpV5nlPT08AsrOzK7w3Oztbva6ye7OysgDUpcmrr7XsIysrq9zrXF1dcXR0VNuyVWpqKmlpV/ZaxMfHa9KuEOKK80mX1MehwdoHaCfPmP7euru5Etyi+kc87cj8i0xDHgAjfHrg66DtDF95bve/nk3pvwGwMf1w9QM0ixk0cwarFlr6mwI0gEupKRKgiSapxgFafc0O2RLkVXbv1a9VdG11+tdq+eHbb79l9erVmrQlhCjf+STT/jOdTkdoy5aatp2anklyminzsnO7iBr9bvg6dZ/6eHxgf83GVpm+nu0JdPQipSSb3VnHydDnViswbBdxpZSI+QxSLQRbFBC+lJxMl3JWPIRo7GocoLVu3VrLcVSJt7d3ubNSOTk5QPmzXmZeXl7lzrCZ7zXPpHl7ewNU2I/lLJy3tzenT58uc11BQQElJSWVjqc6xowZw4ABA9Sv4+PjefPNNzVpWwgBufn5ZGSZfj+08PPD2clJ0/aPnbrygbZLh+oXbD1flMqhHNPvmnDnQHp71E1AYq+zY5RfT9Zc/hG9YmBregz3tKh6PUt3N1dCggK5kJTC6XPnMRqNmuzHbeHnh729PQaDwerkByGakka1cz0yMpL4+Hj0euvNqmfPngWgTZuKf/FFRkZy5syZMs+bn4uMjLRqw9zm1f1Y9hEZGUlmZqbV8mNVx1MdAQEBdOzYUf1TH8GxEE1ZYtKV7M2wWljePHbySoBWk4r635Yeig5wR0CfOj0273b/3upj8x646mgfaVrmLCwqJvFS8jWurhp7e3uCSstt5OTlkZOXp0m7QjQkNZpBmzx5co060+l0rFy5skb3AgwaNIiNGzfy008/WRWm3bJlCwEBAXTp0qXCewcPHszChQs5duyYep1er+eHH36gS5cuBJSmbgcGBtK5c2e2bdvGPffco5btOHr0KAkJCdx1111qmwMHDmTFihVs2bKFiRMnqs9v3rwZZ2dn+vbtW+PvVQhRdxIuWew/q4UEgeM2zKAZFaMaGNmh4za/2k0OuFp711Z0dA3hRMEFjuQncK4wuVrFcdtHhPHjL78CpkSB8BBt3t/gwBZcuGwK+C4mJ9NRow/EQjQUNQrQKtoPpdPpyk15Nj9va4DWr18/evfuzcKFC8nPzyckJIQdO3Zw4MAB5s6dqwZTCxYsYOvWrXz22WcElf6yHTVqFOvWrWPevHlMnz4dX19f1q1bR0JCAosWLbLq59FHH2XWrFnMmzePcePGkZGRwbJly2jTpo1VSY02bdowevRoVq1ahZ2dHZ07d+bQoUNs3LiRqVOnWi1xFhYWsn+/KUX+6FHT0SkxMTFkZWXh4uJCv379avy+CCFqzmA0knDRFKA5OTrSMqD6G/groyiKOoPm4+VZ7QSBQzln1JMD+nt1pKWTj6bjq4rb/XtzonRT/ndph3kyZFSV7706k3P4wOs1GVMrq31oKRKgiSanRgHa1QkCRqORp59+mv379/P0008zaNAgWrZsyeXLl/n555/54IMP6N+/f5lAqCbefPNNli9fzsqVK9Wjnl555RWrGTWj0YjBYLAKFp2cnFi0aBFLlixh8eLFFBYW0r59e959912ioqKs+oiOjuadd97ho48+4oUXXlCPenr88cdxumpvyqxZswgICOCbb74hPT2doKAgZsyYUeaop4yMDObNm2f13KpVqwAICgrif//7n83vjRCi+pJSUiguKQGgdatW2Gtcs/BSciqZ2aa9rp3bVz9BwHJ5c6x/H03HVlW3+kWzKHEjBox8l/4rj7e6BTtd1d6nWsvkDAjAzs4Oo9HIxRRtlk6FaEh0igZV/hYsWMCiRYuIiYkhuJxz0S5cuEB0dDSzZ8/mueees7W7Zu/EiRNMmzaN5cuX07Fjx/oejhCN2p5ff+PPEycAuOmG/rSPiNC0/e27D/LiP/4DwJR7x/LoA3dW+d5cQyHD/3iFQqUET3tXdvR4FWc7R03HV1VPnPove7JjAVjR4XGu92xXpfuMRiPD7nqM/IJCglsE8O3q9zUb0zfbflCLCz807g7cXF01a1uI+qbJR8WVK1dy9913lxucAYSEhHD33XezfPlyLboTQghNKIrCuQumpTs7nY6wcuos2sqW/Wc/ZPxBoWKa3bvVL7regjOA2/yvLE1WJ1nAfOQTmGYTs3O029BvWW7jYopkc4qmRZMALTExERcXl0qvcXFxITFRuwNzhRDCVhnZ2WTn5gIQ3KIFLhqX1wDrDM4u1czgtFzeHOOvzd6tmhrm0xUPO9Pv+R8y/qDAWFzley0zV4+fPqfZmEIsDrS/eFmWOUXTokmAFhoayrp16ygsLCz39fz8fNatW0doaGi5rwshRH04V7rxHSAiJETz9o1GoxqQtPD3JcDPp8r3JhSm8FuuqWRPpEtLurnV7IB1rbjYOXGTr+m4vHxjEbsy/7rGHVd0bh+hPj52smwJo5oKCgzErnRP33mLUilCNAWaBGhTp07l7NmzDBgwgA0bNqh1wdLS0li/fj0DBw7k3LlzTJs2TYvuhBBCE3EXLAK0UO0DtHOJl8jLLwCqv7y5Mf3KMuIY/+vrtPZZRSxron2f9muV7+vSPlJ9bFm011aWWbdZOTnqbKgQTYFNZ3GazZkzh5MnT7Jq1SruvNO0AdacXQOmfR4PP/wwc+bM0aI7IYSwWU5eHpdLN5j7eXvj7aH92ZYxR06qj3t0aV/l+66ufTa6jmufVSTaow1Bjj4klWSyL/skaSU5+DuWPeP4aq1Dg3B3dSGvoNBqyVcLYcFBXCrdf5aYlESXdlVLXhCiodNkBs3Ozo6VK1eya9cuJk2aRHR0NBEREURHR/PQQw+xa9cuVq5c2SA+AQohBMCZhCslH9qF187y4e9HT6iPo7tWPePasvbZDV4daeHkrfnYasJOZ8etfj0BMGBkW0ZM1e6zs6NT6TJncmo6qemZmo0pzKKwsCxziqZEkxk0syFDhjBkyBAtmxRCiFpxKt4iQGtdOwGaeQbN2dmJjm2rfkSbdXJA/dQ+q8ho/56surwTgE3pv3Fvi0FVuq9z+zb8+qepTMexU3EM7hutyXgC/fxwdnSkqKSExKTLmp33KUR9k59iIUSzk5WTQ0p6OgCBvr74WJz6oZWk5DSSUkz7cbt3bIujY9U+D+cZCtme+ScAnvauDPXpqvnYbNHetRXtXU0llf7Mi+d8UWqV7rPMYD2u4T40Ozs7Qkpn0YqKi0nJyNCsbSHqkwRoQohm53RCHcyeHb2y/yyqW4cq3/dDxp8UlpawqO/aZxUZVbrMCaZZtKro0sEiUaAW9qGZnb8ky5yiaZAATQjR7JyKj1cft62l/WcxFvvPorpUPUD7Nu2g+ri+a59V5FbLAC3tt3LPYL5aq5YBeHuZEjGOnYyr0j1VZbkPLTHpUiVXCtF4SIAmhGhWUjMySM/MAkznOXrVQvYmwO+lM2j2dnZ071y1zMLzRan82oBqn1Uk2MmXXh6mGbFzRckcz792EXKdTqcWrM3MzuFSctWWRqvCy8MDb09TNumllFQKi6teRFeIhkoCNCFEs3L8zJVCqR0iqr5xvzqycnI5G2+qsdahbWvcXCs/acXM8gilhlL7rCKjLEp/fF/VZU6LfWhHYs9oOp6IENMxXYqikHDxoqZtC1EfJEATQjQbeoOBk+fOAWBvb6/5wehmVvvPulat/pmp9pkpe7Mh1T6ryEjf63DU2QOwNeN3DIrxmvf0sJhJtHyPtBARcuWkGssTIoRorCRAE0I0G3Hnz1NUuvzVNiysVs7eBDj4+1H1cc9unap0z+HcM1xsgLXPKuLl4MZA784ApJRkcyjn9DXvua5Le3VWMObYKU3HExwYgHPp/8+ES5cwGAyati9EXZMATQjRbByzWN7s3LZtrfWz/1fTOZX29vb0jupSpXu+TW24tc8qMtpqmfPaRz95uLvRvk0YAKfjzpOTm6fZWOzs7GjdyrTMWVxSwsXS0wWEaKwkQBNCNAtZOTlcuHwZAG9PT1q1CKyVfhIvJZNw0dRPj05t8XBzveY9eYZCfmjAtc8qMti7Cx52pv11OzL+pMB47c350d1MJyooisKfx68961YdlgfeyzKnaOwkQBNCNAtHTl1ZUuvSNrLWNuDv/+0v9XG/Xt2rdE9jqH1WHmc7R0b49gAgz1jErsy/rnGHaZnT7PcjJyq5svrCgoPUUwTOXbigaSkPIeqaBGhCiCavqLiYY6dNWYP29vZ0ioy8xh01t//XI+rj/lUM0Cxrn41tJMubZrf791Yff2uRhVoR8wwawB8a70NzdnKiVYsWAOTk5amnRQjRGEmAJoRo8o6fOUOJXg9AxzYRuLpUrexFden1eg7/cQwAX2/PKp2/GV+YYlX7rKtbWK2Mrbb09IgkxMkPgAPZJ7lcnFnp9QF+PoQGm4KooyfOqkkbWmkbfuX9szwxQojGRgI0IUSTZjAa+fPElZIO13WsWlZlTfx5/DR5BYUA9InuVqVDu79J3a8+vsO/T4OufVYeO52dOotmRKlSskBUV9PJCiV6vebHPkWGhmFX+h6ejk+QZU7RaEmAJoRo0s4mJJCbnw9A61at8PXW/mB0s32/XtmD1b9Xt2teX2LU821p7TMHnT231+LRTka9EaPh2rXKasJy3BvTDl8zKDIHaKB9PTRXF2dCS49+ys3PJylVuxMLhKhLDvU9ACGEqC1Go5Ffjx5Tv47qXHuzZ4qisOsX0+yRTqejb/S1A7Sfso6Srs8F4Eafbvg5anPslEFvJDEmhfMxKVw8mkZeRiGGYiPowM3XGa8WboRFBRLZPxjPQDeb+wt19qenRyS/5Z7lbOFljuQn0N294uXdXj2u/H848PsRHv7b7TaPwVK71q1JuGQ6k/N0fDzBgbWTsStEbZIATQjRZJ1OSCA9q/TcTX9/dQN5bThzLpH4RFNQENWlPQF+Pte852uL5c07A/rZPAaD3sipnxKJ2XCG3NTCshcokJ9eRH56EUmxGRz6/CRh0YH0va8TPiG2BYdj/K/nt9K9dN+k7q80QAsNbklIUCAXklL449gp8gsKq3wcVlVEhoXy00E7DEYjpxPOM6BnzyotNwvRkMhPrBCiSTIYjRz688qSY9/retTq/q4de68Umh0+6NqZmBeK0tmXbVreC3Hyo69n1Y6EqkhqXBbrXtzLnpVHrYIzOwcdvmEetOzgS0CkN67e1qcnnP89ha+f38P+tcfRF9e8+v7NvlG42TkDsDn9d/IM5QSIFswlSPR6A4f/PF7jfsvj5OhI69KzOQsKC7mQnKxp+0LUBZlBE0I0SSfOxpGVa1o+DGnZQt2XVFt27DYFaDqdjhsH9L7G1fBlyi8omPZqjQvoi52uZp+XFaPCHxvP8utXp1AMV/Z+hV4XSOcRYbTq6o+ji/Wv+uzL+Zzdd4lj2+PJTy9CMSoc2XyOS8fSuPHpaLyD3Ks9Djd7Z0b59eSr1H0UGIvZkv474wP7V3h9/57d+fr7nYDp5IXBfaOr3Wdl2rduzdnziYApizeslv//C6E1mUETQjQ5JSUlHPrryuxZnx49arW/M/GJxJ2/CJgKsQb6+1Z6fYGxWM3edNDZ13h5U19sYOe/Yjj8xUk1OPOP8GLMa/245fnetO7VskxwBuDV0o2oO9py9/tD6DWhPfZOpn8K0uJzWP/yXhL/rNkxSeMtvg/L5dvy9L6uM/b2psPWLZMrtBIREoKLs2lG7+z5RAqLijTvQ4jaJAGaEKLJOXzkKHkFBYApc7O2N4mbZ88Ahg+8dibm5vTfyDKYMktv8Y3G39Gz2n0WZhez6a2DxB1IAkCng6g72jLm9f60aF95gGjm4GxP9J3tGPvGDXi3Ms2alRQY2Pbur5zZd6naY+riHkYnV9NxS0fzzxObX/FxS+5uruqpAomXkkm8dLna/VXG3t6ejm0iAFOyyIm4c5q2L0RtkwBNCNGkpGdl8UdsLAD2dnYM7NWzVvtTFIVtPx9Qvx52jeVNRVH4NHm3+vW9LQZWu8+C7CK+f+sgyacyAVOgddPsXvS+uwP2DtX/te4X5skdb95A6+tbAmA0KOz6dwyxu85Xu63xgVdm0b5M+aXSa/v1vJLpus/iBAatdG7bVn18/MwZqYkmGhUJ0IQQTYaiKOw+fBhj6T/E0V264O1Z/dmp6og5elLN3ozu1pGWAX6VXv9r7hlOFZiuv849gm7u4dXqLz+riE1vHiTjfA4Abj7O3P5KP8KjbctQdXRxYPjT0XQcFmp6QoE9K45wek/1Dh0f5ddLTRb4Lv1XsvX5FV57Q+8rS8/7fv2z+oO+Bj9vb4ICAwBT4H45LU3zPoSoLRKgCSGajKOnTnPhsiljz8vdnZ5dOtd6n99s3qU+Hnfr0Gtev+byj+rj6s6eFeeXsGXBITISTckP7n4ujJ7XF/8IbYrv2tnpGDi1G91GRZieUOCnpX9x7lBSldvwsHdhTGnh2kJjMesszhm9Wvs2Yfj7egNw8Pej5BdUnvlZE10sZtGOnNT27E8hapMEaEKIJiE9K4u9v/+ufj34+t44ONRuonpmdi4795gOCPf2dL9m9ubJ/Iv8nGUqnBvk6MMIn6onLxj0RrYv+p30eNPMmbu/C6P/3qdGGZeV0el09J3Yic4jTDN7ilFh17//4PLJjCq3YRl4fp68B4NS/gkGdnZ2DL2hFwBFxSXsORhT84FXoG14OM5OptIipxMSyMuveEZPiIZEAjQhRKNnMBjY/ss+DAZTHa9u7dsT3qpVrff7/fY9FJeUADB6+EA1EKjIR0k71MeTgobhaFe1AFIxKvy87C8uHjUt0Tl7OHLri9fj1VLb4MxMp9Nxw0NdaDfQ9B4aSoz88P6vZF+uWnAT4dKCAV6m0wIuFqerQWl5Rgy8UjNuu0WyhVYcHRzo2q4dYEoW+POktkdLCVFbJEATQjRqiqLw8+HDpGaYZnh8vby4ITqqTvpdt+VH9etrLW8mFKawNSMGAF8HD8YF9K1yX4e+OMGZvaYyHvaOdoyc3QufVtocC1URnZ2OwY90p1VXfwAKc0rY+u5hinJLqnT/fS0GqY//7/JPFV4X3a0jfj6mJdpfDv9RK8uc3Tt2UE8SOHbqNCUlVfsehKhPEqAJIRq1P0+c4PgZ0xFD9nZ2jLihf60vbQL8fOB3NTmgZ/dORIRVPmO36vJOjKWFae9vMRhXu8pn28yObj3HnxvjAFMpjRufiqJlh6qV0bCVncP/t3fe4VFV28N+z6RMJr2S0JIAoRMJEDqhd7GhV0SKdGwXrngFK2C5XssVfnIVRKpwAflQUFACiKC0SA1FEAwkoYWSRhJSp5zvjyEnM5mZJMAEZuJ+nyfPzNln7b3XOnt2Zs0ua6voM7WNEoIjJy2fnz9NRK+r/ND1Lr5NiVQbNy4cunmOYzdTrcq5uKjoZTbNecw+ypvgpdHQJNJ49FSxVssfySl2r0MgsDfCQRMIBE5LyqVL7Es8qlz36tSRkMCKd1HaA1mWWbL6e+X66UcHVCh/viid7zOM03feKg+eDOlapXpSDlwlYUXZMUhdxrYkIjb0DjS+c9Tebgx4JRYPX6NDmXYyk71LT1YaskIlqRgb1lu5XmIyvVuePibTnD/vsb2p4G5o3azsgPajf/yhTIcLBI6KcNAEAoFTcv5yGlv37FUchXYtW9IkMvKe1L334DH+OJsKQJOG4XTvVPExRZ+lxaPHOOo0KrQHvq6aSuu4ejqLXz4/xq1BN2IebaQs3L/X+IZ60m9aW1zcjF8Zf/5yieObkivN92BgW8Lc/AH4NeckfxakWZVrE92UAD9jOJS9h45zs6DQPoqbEOTvr6xLvFlQwKlz5+xeh0BgT4SDJhAInI7zl9OI370bg8Ho9DSOiKDDA9H3pG5ZlllsMno24elHKjyE/WT+RbbdWnsW6OrNqNAeldaRffkmP31yBL32ln3d69Lub3d3mPrdEtokgO7Plu06Pbj2z0rDb7ipXBkd1lO5XmpjFM3VxUUZRSsuLmHLzooD3N4ppp+Rw7+fRKvTVUs9AoE9EA6aQCBwKn7/M4nNu3Ypzlmj8HD6dO5UoZNkT3b9lsjJP42jR40b1KdHJ9snFciyzKeXf1CuJ9Xuh5eLR4Xl52cXsfXDgxTnGxey13sgmLgJre6ZfRXRqHNt2j1xy1GU4Zf5x8lIzakwz9DgTgS4Gtewbck+ytlC607dowPLHNf18b9US9T/WoGBNKxvDMRbUFQk4qIJHBrhoAkEAqdAp9ez6+Ahdh06pHx5NwoPp1+XzsoOveqmsKiY/3zxP+V6wtOPVlj3zzdOsD/P6ATUcw/iieDOFZZfUqBl64eHuJlh3MkYFOlL76ltUN3B8U3VRcxjjWjUpTYAumI92/5zmPxs2zsvNSp3ngntBYCMzH8v/2hVrmmjCFo2aQhAUvIFTp6pfAr1TugQXTYKeOTUKXGIusBhcZxeLxAIBDbIyM7mmy1b+T2pbMQjpnmze+qcAXy5agNX042xyDrEtFR2H1ojX1/Ehxc3KNf/qDekwrhnSiDaC8ZAtN4hGgZMj8VdU/07Um8HSZKImxRNrcb+ABRkFfPTfw6jK7a96H54rW7UcjOeGPBLzkmO3LTufA0d3Et5b3pCgz0J9PdT1ioWl5Sw/5j9j5gSCOyBcNAEAoHDUqLVsi8xkW+2biMrxziVplKp6NWxA13atLmnztmZc+dZs2ErAO5ubrz64jMVTjvOT9vCda1R526+zSo8NUA2yOz64rhZINqBM2Lx9Ffb0QL74eruQt9pbfEONm52yEjJ5ZcFx5AN1qclPVTuPFenbKfrp5d+tDqF2b97R7y9PAHYtms/eTfzq0F76BTTWgnFcvLsWXFGp8AhEQ6aQCBwOEq0Wo7+cZpVmzZx9I/TynqzIH9//jZwAM1Nzle8F9wsKOSNDxegv6XH2GEPUb+O7XAXv+dfYPX13QCoJVdeC3+8QmfuwJoznNtnjKl2rwLR3i2efmr6v9ION40LAKkHrnH4G9truh4Oak9DD+MzO5qfwrZsy3hnHh5qBvfuAhg3C3zz445q0By8PT3pEN1Kud518JDyGRMIHAXhoAkEAochKyeHfYmJrPx+I/sSEyksMq4PclGpaNeyJU8M6E+Qv/891clgMPD2J18qQWmjIusx+m+Dbcrn64t4NWWlEpR2Uu3+1FMH2ZT/PT6FEz+aBKKdcu8C0d4tgfV96P1iDKW+59HvzpG0+7JVWVfJhal1hyjXH1/6jpt6y7Vrwx7uh0plLHDVhi3VcrIAQHTTpgT6Gadd07OyOHbmTLXUIxDcKcJBEwgE9w2DwUBGdjaHfj/Jui1b+frHzRz94zTFJSWKTKPw+gwf8iAdWz+Ai4vLPddxyZrv+SXhCAA+3p58/NYU3N3cbMq/f2E9F4uNU2bRXuE8E9bLpuy5hCv8tvK0ct11XEsi2t3bQLR3S/02teg4srlyvXtR2Zmh5enh14Iefi0BSNfm8tnlzRYy4XXDGNDDuJkiJ/cm636wHeD2bnBRqejevuxw+/3HjivHhQkEjoBw0AQCwT1BlmVuFhRwIS2NA8dPsHHHTpZ+u57/F7+FA8ePk56VpciqVCqaNmjAUw8OZkC3bvh635/pviVrvufLVd8BxsXx777yLPVq23agvss4wA9ZhwDwUqn5oMEo3CTrTuXFo+n8uqBsmq/N0Cia9bk/gWjvlpYDI2jWpz4ABp3MT58cJj3ZMvyGJEm8Wv8xPG4dc7U2fS+/51+wkBs3/GFlFO1/38ZX2yhanVq1iGluPGHAYDDw0959IjaawGFwrO1BAoHAqZBlGa1OZ/zTainWaiksKqKwqJjCoiIKiorIy88nJy+P3Js30VVyvE5wgD9NGzSgSWQDNB73b4G8wWDgi5XrWbZ2k5I2ZfwwurZvbTPPwbyzvHthnXL9ZsQTNqc2Lx5N56c5hzHojNOgTXrWo+3jUXbS/t4jSRJdxrSgILuYC0euoy3Ss/XDgzw4sxMBdc2d6zrqQJ6t3Z//u/wDBmReT1nF182n4elS1t6R9WrTr3sntv6SwI3cPNZ8t5Xxwx+pFt07PvAAl65eIyM7m+zcXHYdPEjvTvcurp5AYAtJro5ogIJq5cyZM0ycOJFFixbRtGlTu5RpMBjQ6/Wlp8ogy7Lx/a2Ph/GlLM3s9Za82Wu5vDIyyEoJynvTj59pXtmYyaROyzJKdSqvb1myXFa3aRlm8uXqkGXLOs3sq1in8mnmOpbpZLMOWZEufXwmz6W8/eWeg2zy7MqXYaqLWR0yBoOMwWDAIBss3996lQ0G9Cb3dTodJTodurscbfDUaAgLDqZOrVpE1q1z30bKTMm6kcus/yzktyO/K2lTxg9j1OO2150lF15j9Jl55OmNRxQNC+nK6+GPW5U9f/gaP3+aqDhnDTqG0evF1qhcnH9CQ1eiZ8sHB7l62jhVqPFzZ/CbHS2cNK2sZ/TpTzlVcAmAR4I68E7kU2YyqRfTGPbc6xgMMmp3N75e8D71ateqFr2zc3JZt2WL8gOiU0xr2rZoUS11CQRVRThoTkh1OGiply+z+ddddilLICiPSqXCz9sbPx8f/Ly9qRUURFhIMN6eng4zUqHXG9i8Yy+fL19HZrZxek6SJKZNepqnHulvM19y4TUmJS0gXZsLQJxvc/4vahyuVqY2T++8yN7FvyuOc01yzkopKdCy+V8HyEgxPg+NnzuD3+hAQD0fM7nzRekM++MTCg3G9YYfNBjJoEDzUxnmfrma1d8ZQ5t0ahfNvHderrbPy7kLF9i6Z69yPSCuG43q16+WugSCqiCmOAUCQaWoJAmVSoVKpUKSJNxcXXFzc8Xd1e3WezclTaP2wFPjgcbDA0+1B95ennhpNPc0ZtntUKLV8vOeg6z8Np6k5LL1UIEBfrz7ymQ6xLS0mfdMwWUmJy0kW3cTgKaaunzUcLSFcyYbZI6sP0vi+rNKWqMutenx3AM1yjkDcPd0Y9BrHdj8/gEyU3MpzCnhh3f2M+CVdtRqXLY7NcIjhDfCH+fN1DUAzE5dS111EA94RSgyk0cNZfueg1zPyOK3wyf4add++vfoVC16NwoPp8MDuRw4fgKAn/buwyWuG5F161ZLfQJBZYgRNCekOkbQrmVkGCNqSwASEpT9UpWM19xKk27J3LqlyCtykpKivFfklB+/krEspSjzvFbrKFeGZBQ2f7Umb1qHmbxSobm9VvKW3iuf17pdtuowsatcGVJZgnleqdyzVfS0fA5K+5SzqzSv6ciDYo8k4XLL6Sp1wFTl3ku3/moSRUXFHD5xmt0HjrJjz0Gyc/LM7vfo1JbX/j6GoAA/m2X8nH2cmalfc9NgXMDeTFOXBY0nE+hmPp1XUqDll/nHuXDkupLWalAkHUc0Q1LVrOdqSvFNLfEfHCTj1mYBF3cVfaa0Ibxt2TSlLMvMPP81GzMPAhDg6s3/mk01W7v3y77DvPLePMC4i/ar/5tdYQy6u0GWZX5O+I0/U1MB48jvQOGkCe4TwkFzQqrDQRMIaholWi1Z2blkZt8gIzuHi2nXSL14hdNnUzmbclEJOmtKs6gIpo4fTmzr5lZKNFJs0PJ5WjxfXftFSWvtFclnURPxddWYyV5PyuaX+cfJvVYAGH88dHi6GdEPNrCPkQ5OSYGW7XMTy8JuSBD7tya0fqSh4vSXGHQ8l7SQQzfPARCuDmFxk+cIdfdXynn1/c/4eY/RiYuKrMfSOTOrbROJwWBge0ICZ88bR1NVkkRcbCwtGzvvJg6BcyIcNCekOhy0Eq2W3DzjsSqyLNtYsF+6uL78AnaTzQCy+cJ05PIL1cuusVqWST2VlmWSp9yGBdnkujSf6WJ7o9rlrsvZXnZtZSG/zbLMN0xYbGSwuinA/PmB9VezDQClz9oir7Wyyp6f6bVlWRU9g8rKMmlDG2XJJm1R9uwq/zzo9Qb0Br3xVa9Hd+u1NF2n01NcUnJr52gxRUUl5OUXcDO/gKrg5upKzy7teOLB3rRp1bTC0cLfcv/kXxe+5UJxupI2MKANsyKeNNuFqCvRc/S7cxz7/pxij9rLjV5/b029B0KqpFdNQa/V8+sXJ0hOuKKkRbQPJW5iKzy8jeE2cnUFjD4zj5Qi4yhjHfdAFjV5ThlJu1lQyNiX3ib1orGMPt3a868Zz+NSTdPD5Z00gOgmTejSJua+xOIT/DURDpoTUh0O2p4DR3lp9ly7lCUQODKSJNEwvC7RzRvRJfYBOrZphafGo8I8R24ms+jKT+zLLYs274qKafUf5umQOMWpk2WZC0eu89vKP8i7XqjIhkT50euFGHxDPavHKAdHNsgc/f6c8SioW984ngFquj/7APWigwFIK85iUtICJchviJsvcxqNVdakpV5MY8w/3ib/Vky0AT06Mfufk3CtJofJYDCQcPQox06XtXlwQAB9u3RWTiAQCKoT4aA5IcJBEwgskSQJD7U7Gg81Xp4aAv19CQrwI9Dfj8AAX+qGhhBRL4zI+nXw8tRUWl6mNo+t2UfZmHmQP26FgyglxiuSNyOeoLGmDmB0zC7/nsmRb5O4/ueNMp1cJNoOjaL1ww1r3GaAO+FC4nV++fwYJQVl4VmiutWhw/CmeAZ4cL0kh8lJX5BcdA0wHg/1Sr1HGBbSFUmS2HPgKK+8Nw+dzhgOo1eXWN755yQ8qjFm3qlz58zO6nRRqWjTogVtWjTHzVXssxNUH8JBc0Kqw0H7IymFpV9vNF5IksmCdpOF5yYLy5WF7aXyJgvWJZNF9eUXqFuWZb4A37j+XbJaluVr6QL5qpRVqnfZNabX5TcZ3HoGpuWWX2QvlSvbfKF+ZWUpJZldS5jUUyprpU7Ta4tNE+WfgfLMyrWpSdmlbVimp6U95mWVa9MKPw8m9lb6eSivB7i4uODiojK+qozvXU3SVCoVHu5uqNXud7yZQZZlMnR5nMy/wPH88/yW+ycnCy5ayNVxD2Ry7f48HBSLSlJRUqDl3L4r/PHzBbLOm280qN0ikC5jWliEl/irk59ZyK4vT3D5RNlxUG4eLkQPaUDLAZHkuxczLXkZiTdTlPudfZvyev2hhHuEsHv/UWb8679KxP+GEXV5/9XnaRRRr9p0Ts/KYntCAtk5uUqal0ZDbKtWNG3YoNpG8QR/bZzOQSsoKGDx4sXs3LmTvLw8wsPDGTFiBH369Kk0b3Z2NgsWLCAhIYGioiKioqKYMGEC7dq1s5A9dOgQS5Ys4ezZs3h4eNC5c2eee+45AgICzOR0Oh0rV64kPj6ezMxMateuzWOPPcbjj1sGqUxLS+Pzzz8nMTERvV5Py5YtmTx58m07WWKTgEBgiSzL6DFQYtChlXVoZf2t93pKZB15+kJydQXk6ArI0ReQrs3lUnEml4ozuFicqcTjskYLz3oMrxXHoMC2aG9ouXwik9SDV7l0PAO91nyzgX9db9o9EUVkh7Aat/vVXsgGmdM7LnJo7Z8U52uVdHdPV5r3DSeqdx2WFO9g5fVfy+5JrjxVqxujQ3ty9vh5pr83j6JiY5up1e6M+dsQRgwdWG2bB3Q6HQdOnOD46TMYTL42NR4etGrcmGYNG+Dj5VUtdQv+mjidgzZt2jROnz7N5MmTqV+/Ptu3b+eHH37grbfeol+/fjbzlZSUMHHiRG7evMnkyZMJCAhgw4YNJCQkMHfuXGJiYhTZo0eP8tJLL9G5c2cee+wxsrOzWbhwId7e3ixatAh3d3dF9qOPPmLbtm2MHz+eZs2aceDAAVavXs2ECRMYNWqUInfjxg3GjRuHj48P48aNw93dnVWrVnH27Fm+/PJLwsOrfgZfdThov+df4MsrPwEmUfGh7J3ponFr903SzdJsfLysypqWayVfpfXK5tIV62hal/U6Kq1XtrTBvF7LfGaL723UYTW/DR2tv6s4n219q66jVX0ryWezXqs6Wi/LdBOEaR6drKdE1lvV605pqqlDR48mdMyNwueiB1nnc8lIzSUnLd+qfEiUH9GDG9CgQ1iNDp9hT4pySzi07k/O7LyEbDBpOwnqRQeT1bWA5b6/cE2Xo9xyl1wZHNiWDkUN+N+8jZxNLZt+DgnyZ8Rjg3iwbzf8favnVIobubnsSzxK6uXLFvfq1KpFg3r1lFMxhIMuuBucykFLSEhgxowZzJw5k759+yrp06ZNIzU1lXXr1tncYbNhwwbmzp3L/PnzadWqFWD8RTRu3Dg0Gg0LFy5UZCdNmkRRURFLly7F9dYagxMnTvDCCy8wbdo0Hn30UQBSUlIYM2YMEydOZOTIkUr+jz/+mG3btvHtt9/i6+sLwIIFC1i3bh2rV68mLCwMgPz8fJ566inatm3L22+/XeXnUB0O2q6cU/z97GK7lCUQOBMusopgvQ/BxT6E5foTdtWP4BQfXK6Atqjis0M1fu5Edgijaa96BEeKheN3Su61fI5+n0zS7svIevOvJK27jt8HXmZ/o3NoVebtUVvyw+9nmdRfUzGYOHjubm5069CauI5t6NS2FcGB/nbX+XpmJol//EHyxUtWf1B6engQGhxMaHAQoUHBBAX442Hy414gqAynWuG4e/duNBoNPXv2NEsfPHgw77zzDqdOnSI6Otpm3vDwcMU5A3B1daV///58+eWXpKenExISQnp6OqdPn2bSpEmKcwYQHR1N/fr12bVrl+Kg7d69G1mWGTRokFldgwYNYtOmTezfv18Z1du1axdt27ZVnDMALy8vunfvzrZt29DpdGb13WsyUnIqF6rpmP6AN/t/K1lJs5EPySLd1m9oSbZyp5KyLMqTrcjaLK80TbJMq7AOy7Jt3S+ro+plgfVna/X52LivMki46FW3/iRUyvuyNPdiVzyK3PAockNd5IamwB2/HA3eeR6oytVlQI9llDTjov/gBr7UbRVM3ehgQpsGoBKjZXeNb6gX3SdFE/u3xpz59RJndlziZoZxF6xbiSttNkbQxDOMo7HnOfHAJbRqo6N2Rc7hSm8g2g/XbfmoThunS0u0WnbsPcSOvYcACA72p2lUBBG1w6gbFkLtWiHUCQsmwM8Xby8N7m5ut61zraAgBnTrRl5+PmdSUjmTkkJOXtk6xIKiIlIuXSLlUtkIn9rNDV8fH3y9vfD18kbjocZD7YGnhxoPDw/Ubm64urri5uqK6631lYK/Lk7loKWkpBAREWHhyDRq1Ei5b8tBS05OpnXr1hbppnlDQkJISUkxSy8ve+LECTN9/P39CQoKspArvQ9QXFxMWloa3bt3t1pmcXExV65cof59PPettSGCCfN7WL9pzWmoxGGwJWuKrS9g61/y1p2VsrKslmDTqbLp0AgEgKvaBa9AD7yCPAgM9yEo3JfACB/863rj4iq+NKsLzwAP2jwaRczDjUg/d4OUA9e4eDSdG5dv4lWgpuuuJnTY14hzja9zukUal+tnY3CRIcQF3QhfSNfjcqgI1dFipIKyzp+RcYOMjBvs5Zj1il0kVGoVkpsKyUVCUknKK6XvTTfHyFB6Oogx0fhfx0ejoW5QICG+fgT6eONe7ruqWKslPSuL9KysKj0PvcGATq9HZzAoMQUNSozIstiI1tKsYW3JitX7NnCiCTe7UDssjL//7Yn7Vr9TOWg5OTnUqVPHIt3Hx7hLKjc31+JeKbm5uYpcRXlzcowjSaVTk+VlTevIycmxKqfRaHBzc1PKysvLQ5Zlq/WX5s/JybHpoGVkZJCZWbbj6exZ43l+58+ftyp/J2Rcz0HlVmh5o5wfU5UlFZXLWBmRKZ9U7tri30K5DNb+bZT+H62w3soSrNhi4dxVKU8lVMVfLGdz1dri9h1Ryyy331539hCqoEslj94ik2Q8rsfF1fjF6+IiIbmpcHGRULmpcFO74ubhcuvPFbW3Gxpfd1w9zP81GrhJRtFNMs7dvg2CO8c/VsI/thZFef5kpuaSe7WAG1eKCU9VE3KsLlrXMNJDc0kPzSUzKJ/swGK0rUDfUo10TYfqvA7pqg7S9UjaCirSg1xSuYNSGfnAVcqC23p7aQjw9yEgwBsvTw1enmo0GrVd16ZJgNhDWj0kn03izJkzlQveAREREXh4VBx/0akcNLizL5yq5C1/z5bs7dRf1TIru7dx40aWL19ukf7ee+9VWReBQCCokaSVvfW49eco6AohPQPSKxcVOCgT4+OrpdyqrCF3KgfNz89PGZUyJe/WvL+10axSfH19rY6wleYtHd3yuxUh2lY9pqNgfn5+ymiWKYWFhWi1WkUfHx8fJEmyWn9pWkW6P/zww3Tt2tVMj/Pnz9OkSROzHaV3y/nz53nvvfd48803iYiIsFu5jkJNtw9qvo013T6o+TYK+5yfmm7jvbCvKuU6lYPWsGFDtm/fbrGgPjk5GYAGDRpUmPfcOcv5idK0hg0bmpWRnJxM586dzWSTk5PN6mjYsCE///wzmZmZZuvQyuujVqupW7eukl6+TLVaTe3atW3qHhwcTHBwsFlabGysTfm7JSIiokbHV6vp9kHNt7Gm2wc130Zhn/NT02283/Y51WrXuLg4CgsL+fXXX83St2zZQnBwMC1atLCZt3v37ly4cIFTp04paTqdjp9++okWLVooDlBISAjNmzdn27Zt6PVlW7pPnjzJhQsX6NGjbCF9t27dkCSJLVu2mNUVHx+PWq2mY8eOZrofOXKEa9euKWkFBQXs2rWLrl273tcdnAKBQCAQCBwLp/IKOnXqRGxsLHPmzKGgoIC6devy888/s3//ft58800lBtoHH3zA1q1bWbNmjRLWYvDgwWzYsIGZM2eaBaq9cOECc+ean0H57LPPMm3aNGbOnGkWqLZBgwZmITUaNGjAgw8+yLJly1CpVDRv3pyDBw+yadMmJkyYYDZtOXz4cLZt28aMGTMYP348bm5urFq1ipKSEsaOHXsPnp5AIBAIBAJnwakcNDAujF+0aBFLlixRjnqaNWuW2VFPBoMBvV5vtiXY3d2duXPnsmDBAj799FOKiopo3LgxH3/8sdkpAgBt2rTho48+YunSpbz66qvKUU/PP/+8xZqvadOmERwczPr168nKyiIsLIwpU6ZYHPXk7+/PZ599xvz583n//feVo54+/fRTh5nDDwoKYsyYMRZhQ2oKNd0+qPk21nT7oObbKOxzfmq6jY5in1OdJCAQCAQCgUDwV8Cp1qAJBAKBQCAQ/BUQDppAIBAIBAKBgyEcNIFAIBAIBAIHw+k2CQggMTGRqVOnWr23YMECWrZsqVyfOXOGL774glOnTuHi4kKbNm144YUXrB6Z9e2337JhwwauXLlCUFAQgwYNYtSoUVUKAaLT6Vi5ciXx8fFkZmZSu3ZtHnvsMYvNEvfLxosXL7Jx40YSExNJS0tDkiQiIiJ48skn6dmzZ6X6XLlyhWHDhlm9V36Tyv2wD7B61ivApEmTGDlyZKU6OXobxsfH8+9//9tmfZXZeb/a8Pjx48THx5OUlERKSgparZa1a9fajH3oKP3Q3vY5Wh+E6mlDR+qH9rbPGfugXq/nm2++4eDBg6SkpJCbm0toaCjdunVjxIgRVo9gdJQ+KBw0J2bSpEm0adPGLM00kO758+eZOnUqUVFRzJ49m5KSEpYuXcqLL77I0qVL8ff3V2RXrFjBkiVLGDFiBO3bt+f06dMsXryYjIwMXnnllUp1mTNnDtu2bWP8+PE0a9aMAwcOMG/ePAoKChg1atR9t/HAgQMkJCQwYMAAmjVrhl6vZ8eOHcycOZNx48YxZsyYKunz+OOP07dvX7O0evXq3Xf7SunZs6fFP8DQ0NAq6eLobdi5c2cWLFhgUf6SJUs4dOiQzS/G8tzrNjx8+DCHDx+mcePGeHl5kZiYaLMsR+yH9rLPUfsg2LcNwfH6ob3sc8Y+WFxczLJly+jTpw9DhgzBz8+PP//8kxUrVrBv3z4WLVqEWq1W8jlUH5QFTseRI0fkuLg4eefOnRXKzZw5Ux4yZIh88+ZNJe3KlStyr1695Pnz5ytpN27ckPv06SN/9NFHZvlXrFghd+/eXU5JSamwnuTkZLl79+7yypUrzdI/+ugjuW/fvnJOTk7VDDPB3jZmZ2fLBoPBIv/06dPlfv36ycXFxRXWk5aWJsfFxcmrV6++PUNsYG/7ZFmW4+Li5Dlz5tyRPs7QhtYoKCiQ+/fvL7/wwguV6nO/2lCv1yvvV69eLcfFxclpaWkWco7WD+1tn6P1QVm2v42y7Fj9sDrsK4+j90GdTiffuHHDIn3nzp1yXFycvHXrViXN0fqgWINWQ9HpdOzbt48ePXrg5eWlpIeFhdGmTRt2796tpO3fv5+SkhIGDx5sVsagQYOQZdlM1hq7d+9GlmWzIL6l+YuLi9m/f78dLLLkdmz09/e3eiB98+bNKSoqsnpO6v3mduy7W5yhDa2xY8cOCgsLefDBB6tFP3ugUlXt36yz9sOq2ueMfbCUqtp4tzh6G1rD0fugi4uLcsa2Kc2bNwfg+vXrSpqj9UHhoDkxc+fOpVevXgwcOJCXX36Z48ePK/fS0tIoLi6mUaNGFvkaNWrE5cuXKS4uBiAlJQUoO4+0lODgYPz8/JT7tkhJScHf398iqF9p3ZXlrwh72WiLxMRE/P39CQgIqJI+q1evpnfv3vTr148XXniBPXv23J5B5bC3fdu3b6dv37706dOHCRMmsHnz5irp4axt+OOPP+Ll5UWvXr2qrM+9bMPbwVH7ob3ss8X97oNgfxsdrR9WZxs6ax88cuQIAJGRkUqao/VBsQbNCfHy8uKJJ56gTZs2+Pr6cvnyZdasWcPUqVP58MMP6dChAzk5OQBmx02V4uvriyzL5OXloVaryc3Nxd3dHY1GY1W2tCxb5OTkWK1Ho9Hg5uZWaf57YaM1fvjhBxITE5kyZYpyTJgt3NzceOihh4iNjSUoKIhr166xfv16Xn/9daZPn86QIUPuu319+/alc+fO1KpVi+zsbH788Uc++OAD0tLSmDBhQoX6OGMbnj9/nt9//52HH34YDw+PSvW5H214OzhaP7S3fda4n30QqsdGR+qH1d2GztoH09PTWbhwIc2aNaNLly5KuqP1QeGgOSFNmjShSZMmynXr1q2Ji4tjzJgxLFiwoMqdztp0w93I2TN/ddv422+/MXfuXHr27Fml3TXBwcEWC0R79erF5MmTWbhwIQMHDrytA++rw76ZM2ea3evZsyevvvoqq1at4oknnrDYUHA7OGIb/vjjjwBV/qfuqG1YVe51P6xu++53H4TqsdGR+mF1t6Ez9sHc3FymT5+OLMvMnj37tqZ373UfFFOcNQQfHx+6dOnCuXPnKC4uVubcra3ryM3NRZIkvL29AeMvg5KSEoqKiqzKWvtFYIqfn5/VegoLC9FqtZXmryp3Y6MpBw4c4M033yQ2Npa33nrrjjudq6srvXv3Jicnh0uXLt1RGabYyz5T+vXrh16v5/Tp0xXKOVsb6nQ6tm7dSlRUFM2aNbtjfaq7DW8HZ+iHd2OfKY7aB8F+NpriSP3QXvY5Yx/My8tj2rRpZGRkMGfOHItQRY7WB4WDVoOQTY5VrVOnDmq1muTkZAu55ORk6tatq0wblc63l5fNzMwkJyfHbDu2NRo2bMiNGzfIzMy0qAeoNP/tcKc2lnLgwAFef/11YmJiePfdd3Fzc7OLPvZaRHy39tmiMv2cqQ0B9u3bR3Z2tl0WJldnG94OztIP79S+Uhy9D5qWaW8cpR/awz5n64N5eXm89NJLXLlyhU8++cTquldH64PCQash5OXlkZCQQOPGjVGr1bi6utKlSxd27dpFQUGBInft2jUSExPN4tV07NgRd3d34uPjzcqMj49HkiTi4uIqrLtbt25IksSWLVss8qvVajp27GgHC+/ORij7YnjggQf417/+hbu7+13po9Pp2LlzJ35+ftStW/euyoK7t88aW7duxdXV1WwawBrO0oal/Pjjj7i7u9O/f/+70qe62/B2cIZ+eDf2geP3Qbh7G63hSP3QXvY5Ux8sdc7S0tL45JNPbLaDo/VBsQbNCXnnnXeoVasWzZo1w8/Pj0uXLrF27VqysrJ47bXXFLlx48YxadIkZsyYwYgRIygpKWHJkiX4+fnx1FNPKXK+vr6MHj2aJUuW4OvrS/v27fnjjz9Yvnw5Q4YMMdvlsmXLFj788ENmzJjBwIEDAeOvggcffJBly5ahUqlo3rw5Bw8eZNOmTUyYMOGOhuXtbePx48d54403CAwMZOTIkZw9e9asvsjISCXMgzUbP/vsM3Q6HdHR0QQGBnL9+nW+/fZbkpKSeO211ypd4Fzd9q1Zs4bU1FTatWtHSEiIsjj54MGDjB071mzdi7O2YSkZGRkcOHCAXr16WY0CbsvG+9WGN27c4OjRo0DZL+n9+/fj7++Pv78/MTExgOP1Q3vb52h9sDpsdLR+aG/7SnGmPlhcXMzLL79MUlISf//739Hr9Zw8eVIpw9/fX3EMHa0PCgfNCWnYsCE7d+5k48aNFBYW4uPjQ3R0NG+88YYS2wUgIiKCefPm8cUXXzBz5kxcXFxo27Ytzz//vMVC1dGjR+Pp6cmGDRv4+uuvCQwM5Omnn2b06NFmcrIso9frLYaQp02bRnBwMOvXrycrK4uwsDCmTJlyx8cE2dvGQ4cOUVxczNWrV/nHP/5hUd+nn36qRKK2ZmODBg3YuHEj27dvJz8/H09PT5o3b85//vOfO1poa2/7wsPD2bt3LwkJCcqux6ioKKvHpzhrG5YSHx+PXq+vcGGyI7VhSkqKxcLxOXPmABATE8O8efOUdEfqh/a2z9H6YHXY6Gj9sDo+o+BcfTArK0tZ+1feDoCBAwfy+uuvK9eO1Aclubom2wUCgUAgEAgEd4RYgyYQCAQCgUDgYAgHTSAQCAQCgcDBEA6aQCAQCAQCgYMhHDSBQCAQCAQCB0M4aAKBQCAQCAQOhnDQBAKBQCAQCBwM4aAJBAKBQCAQOBjCQRMIBAInJzU1FUmSlL+wsDCz+7Nnz0aSJH755Zf7o2A5Ro4caabv8uXL77dKAoHDIRw0gUDgsJR3PKz9lT+G5q9M69atmTVrFv/85z+rva6FCxciSRLPPvtspbLt2rVDkiSOHDkCwNChQ5k1axaPPPJIdaspEDgt4qgngUDg8DRq1IiRI0davVd+tOivTExMDLNnz74ndQ0fPpxp06bx9ddfM3fuXDQajVW548ePc+TIEWJiYmjbti1gdNCGDh3K8uXL+f777++JvgKBsyEcNIFA4PBERUXdM8dDUDV8fX154oknWLFiBevXr2fEiBFW5ZYsWQLA+PHj76V6AoHTI6Y4BQJBjUKSJHr27El6ejrjxo2jVq1aaDQaOnXqZHMNVl5eHrNmzaJly5ZoNBr8/f0ZOHAge/bssZDt2bMnkiRRXFzMzJkziYqKws3NzcyBXL9+PbGxsWg0GkJDQ5k4cSLZ2dlERkYSGRmpyD3zzDNIksTBgwet6jV9+nQkSWLDhg1380hscvz4cerUqUNwcDD79+9X0lNSUpgwYQLh4eGo1Wpq167NmDFjOH/+vFn+Uqdr2bJlVssvKSlh1apVqNVqmw6cQCCwjhhBEwgENY4bN27QtWtXfH19GTFiBNevX2ft2rUMGDCAw4cP06pVK0U2KyuL7t27c/LkSeLi4hgwYAA5OTl8//339OrVi3Xr1vHoo49a1DF06FCOHTvGgAEDCAwMpGHDhgAsXbqU8ePH4+/vz+jRo/Hz82Pz5s3069cPrVaLm5ubUsbkyZNZsWIFixYton379mbla7VaVqxYQVhYGA899JDdn9Hu3bt56KGH8PX1ZceOHTRr1gyA/fv3M2DAAPLz83nooYeIiooiNTWVVatWER8fT0JCgmJr9+7dady4MTt27CA1NdXM+QTYuHEjmZmZDB8+nICAALvbIBDUaGSBQCBwUFJSUmRAbtSokTxr1iyrf/Hx8WZ5ABmQn3/+eVmv1yvpixcvlgF58uTJZvJPP/20DMhLly41S7969apcv359OSQkRC4sLFTSe/ToIQNyTEyMnJmZaZYnOztb9vb2ln18fORz584p6VqtVu7bt68MyBEREWZ5WrVqJfv4+Mg3b940S1+/fr0MyDNmzKjyc3rmmWes3p81a5YMyDt37pRlWZa/++472cPDQ27RooV88eJFRa6kpESOjIyUfXx85KNHj5qVsXv3btnFxUUeMmSIWfq///1vGZBnz55tUe+gQYNkQN6+fbtVvZYtWyYD8rJlyyq1USD4qyEcNIFA4LCUOh4V/U2dOtUsDyB7eXnJeXl5ZularVZ2dXWV27Ztq6Slp6fLLi4ucp8+fazWP2/ePBmQN23apKSVOmjff/+9hfzy5ctlQH7ppZcs7iUkJFh10ErrWLJkiVn64MGDZUmS5KSkJKu6mXI7DtrixYtlFxcXuXPnzhYOZqlT+O6771otZ+jQobJKpZJzcnKUtLS0NNnFxUWOjIyUDQaDkn758mWr6aYIB00gsI2Y4hQIBA7PgAED2LJlS5XlGzdujLe3t1maq6sroaGh3LhxQ0k7ePAger2eoqIiq5sQkpKSADh9+jRDhgwxu9ehQwcL+WPHjgHQpUsXi3sdOnTA1dXyX+6oUaOYMWMGixcvZty4cQBcvnyZrVu30qNHD6Kioio29jaYO3cuGzduZPDgwaxbtw5PT0+z+7/99htgtNfa87h69SoGg4E///yT2NhYAGrXrs2gQYP44Ycf2LlzJ7179wZg+fLl6PV6xo4diyRJdrNBIPirIBw0gUBQ4/Dz87Oa7urqil6vV66zsrIA2Lt3L3v37rVZXn5+vkVaaGioRVpubi4AISEhFvdUKhXBwcEW6f7+/jz55JN89dVXnDp1ihYtWrBs2TL0ej0TJ060qdOdsHv3bgAGDhxo4ZxB2fNYtWpVheWUfx7jx4/nhx9+YNmyZWYOmkqlYsyYMXbQXCD46yF2cQoEgr8svr6+ALz88svIxiUfVv9mzZplkdfaqFBpeenp6Rb3DAYDGRkZVvWYPHkyAIsXL0aWZZYtW0ZgYCBDhw69Y9ussWTJEtq2bcvUqVOZP3++xf1S/Tdt2lTh8+jRo4dZviFDhhAaGsq3335Lbm4uu3fvJikpiX79+hEeHm5XGwSCvwrCQRMIBH9Z2rdvjyRJJCQk2KW81q1bA7Bv3z6LewcOHECn01nN17lzZ6Kjo1m5ciXx8fEkJyczcuRIPDw87KJXKQEBAWzfvp22bdvywgsv8Pnnn5vd79ixI8BtPw9XV1dGjx5NYWEhX3/9NUuXLgVE7DOB4G4QDppAIPjLEhYWxpNPPsm+ffv4+OOPkWXZQmb//v0UFBRUqbxHHnkEb29vFi9eTEpKipKu0+l46623Ksw7adIkMjIylGnNCRMm3IYlVafUSYuNjeXFF1/kv//9r5n+4eHhzJkzh127dlnk1Wq1VmPDQZkzNn/+fNatW0dQUJA4ykkguAvEGjSBQODwnD17tsKTBO7mlIH58+dz5swZpk+fzsqVK+ncuTN+fn5cvHiRw4cPk5SUxJUrV6yu2SqPv78/c+bMYdKkSbRt25Zhw4YpcdDUajV16tRBpbL+u7h0s0BaWhodO3YkOjr6jm2qip4//fQT/fv3Z8qUKciyzJQpU1Cr1XzzzTcMGjSIHj160KdPHyVm3IULF9i9ezdBQUGcPn3aosymTZvStWtXZS3fxIkTcXd3rzYbBIKajnDQBAKBw3Pu3Dnefvttm/fvxkELDAxk3759fPbZZ6xdu5ZVq1ZhMBgICwujdevWvPXWW1YX99ti4sSJBAQE8P7777N8+XL8/Px4+OGH+fDDD4mIiKBRo0ZW8/n5+fHII4+wZs0au28OsIapkzZ16lRkWWbq1Km0b9+eY8eO8fHHH7N582b27NmDWq2mbt26PProowwfPtxmmePHj1cctNIdqQKB4M6QZGtj+gKBQCCwK2fPnqVx48Y8+eSTrF271qpMy5YtuXDhAleuXLEIE1IRqampNGjQgGeeeYbly5fbSePqZ/ny5YwdO5Zly5aJ3Z4CQTnEGjSBQCCwI9nZ2RQXF5ulFRYW8tJLLwFYPTYKYPPmzZw6dYpRo0bdlnNmyldffYUkSYSFhd1R/nvFyJEjkSSJsWPH3m9VBAKHRUxxCgQCgR359ddfGT9+PP379yc8PJyMjAzlrMrevXszbNgwM/kFCxZw8eJFFi1ahEajYfr06bddp7+/v1kokDt18O4VQ4cONQvAGxMTc/+UEQgcFDHFKRAIBHYkKSmJt956i3379inx0KKiohg2bBj//Oc/LUJnREZGcunSJZo2bcqHH35ocWKBQCD4ayIcNIFAIBAIBAIHQ6xBEwgEAoFAIHAwhIMmEAgEAoFA4GAIB00gEAgEAoHAwRAOmkAgEAgEAoGDIRw0gUAgEAgEAgdDOGgCgUAgEAgEDoZw0AQCgUAgEAgcDOGgCQQCgUAgEDgYwkETCAQCgUAgcDD+P7SyxYwOWgBNAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Best-fit model:\n", "energy = np.linspace(500.,520.,201)*u.keV\n", "fluxes = {}\n", "\n", "for model in models: \n", " fluxes[model] = results.optimized_model[model].spectrum.main.shape(energy)\n", "\n", "fig,ax = plt.subplots()\n", "for model in models:\n", " ax.plot(energy, fluxes[model], label = f\"Best fit, {model}\",ls='-')\n", "ax.set_ylabel(\"dN/dE [$\\mathrm{ph \\ cm^{-2} \\ s^{-1} \\ keV^{-1}}$]\", fontsize=14)\n", "ax.set_xlabel(\"Energy [keV]\", fontsize=14)\n", "ax.set_title(\"Best fit to model\")\n", "ax.legend()\n", "ax.set_ylim(0,);" ] }, { "cell_type": "markdown", "id": "b9fea8a7-5e10-46fa-a094-87c260c5f6b2", "metadata": {}, "source": [ "In summary, we fitted the flux and eccentricity of the disk only, with the all parameters of the bulge component fixed. Considering $b = a \\sqrt{(1-e^2)}$, we recovered the following fitted parameters:\n", "\n", "##### Component..... Injected........... Best Fit \n", "b...................... 3$^{\\circ}$..................... 1.6$^{+0.2\\circ}_{- 0.3}$ \n", "Disk................. 1.7e-3/cm$^2$/s.... (1.64 $\\pm$ 0.01)e-3 /cm$^2$/s \n", "Background .....1........................0.991 $\\pm$ 0.003 \n", "\n", "You can play around with the fitting to find the best parameters for fitting the scale height of the disk, changing the initial values for the fit and which parameters are allowed to vary. " ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:analysis]", "language": "python", "name": "conda-env-analysis-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.13" } }, "nbformat": 4, "nbformat_minor": 5 }