{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Statistical study of cosmological friction and its effect on the redshift vs inferred chirp-mass relation of gravitational waves\n", "\n", "* This is in reference to the [paper](https://arxiv.org/pdf/2309.03833.pdf)\n", "\n", "* From the paper equation 2.13, we have the following equations for the effect of cosmological friction on the luminosity distance of gravitational waves:\n", "\n", "$$ d^{GW}_{L}(z) = d^{EM}_{L}(z) \\exp \\left\\{ \\frac{c_M}{2 \\Omega_{\\Lambda,0}} \\ln \\left[ \\frac{1+z}{(\\Omega_{m,0}(1+z)^3 + \\Omega_{\\Lambda,0})^{1/3}} \\right] \\right\\} $$\n", "\n", "* This represents the relation between the gravitational wave (GW) luminosity distance and the electromagnetic (EM) luminosity distance, taking into account the cosmological parameters for matter $\\Omega_{m,0}$ and dark energy $\\Omega_{\\Lambda,0}$, along with a redshift $z$ and a constant $c_M$.\n", "\n", "* The goal is to study the effect of the cosmological friction term on the luminosity distance of gravitational waves and how it affects the inferred chirp-mass of the gravitational wave source." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from astropy.cosmology import LambdaCDM\n", "import matplotlib.pyplot as plt\n", "import astropy.units as u\n", "import numpy as np\n", "from ler.rates import LeR\n", "from ler.utils import get_param_from_json" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Function to convert from luminosity distance to redshift" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dL_to_z interpolator will be loaded from interpolator_pickle/dL_to_z/dL_to_z_0.pickle\n" ] } ], "source": [ "# let's set up interpolation for with scipy\n", "# conversion from luminosity distance to redshift\n", "from ler.utils import interpolator_from_pickle, cubic_spline_interpolator\n", "from numba import njit\n", "\n", "# the follwoing code is to create a spline interpolation\n", "# the interpolation is saved in a pickle file for later use\n", "# the interpolation function is njited for faster computation\n", "z_max = 10\n", "cosmo = LambdaCDM(H0=70, Om0=0.3, Ode0=0.7)\n", "dL = lambda z_: cosmo.luminosity_distance(z_).to(u.Mpc).value # luminosity distance in Mpc\n", "resolution = 1000\n", "create_new = False # important \n", "spline_dL = interpolator_from_pickle(\n", " param_dict_given= dict(z_min=0.001, z_max=z_max, cosmology=cosmo, resolution=resolution),\n", " directory='interpolator_pickle',\n", " sub_directory=\"dL_to_z\", \n", " name=\"dL_to_z\",\n", " x = np.geomspace(0.001, z_max, resolution),\n", " pdf_func= dL, \n", " conditioned_y=None,\n", " dimension=1,\n", " category=\"function_inverse\",\n", " create_new= create_new,\n", ")\n", "dL_to_z = njit(lambda dL_: cubic_spline_interpolator(dL_, spline_dL[0], spline_dL[1]))" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1.])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# test\n", "z = 1\n", "d_L = cosmo.luminosity_distance(z).to(u.Mpc).value\n", "dL_to_z(np.array([d_L]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Functional form of change in the luminosity distance due to cosmological friction" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# here I have consider dL=dL_EM=dL_GW at CM=0; no cosmological friction.\n", "Ode0 = cosmo.Ode0 # dark energy density\n", "Om0 = cosmo.Om0 # matter density\n", "\n", "@njit\n", "def dL_GW_CM(dL, CM=0): \n", " \n", " # Compute the GW luminosity distance using the formula\n", " dL_GW = dL * np.exp(CM / (2 * Ode0) * \n", " np.log((1 + z) / (Om0 * (1 + z)**3 + Ode0)**(1/3)))\n", " \n", " return dL_GW" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1570.58372199])" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# test\n", "dL = np.array([1000])\n", "dL_GW_CM(dL=dL, CM=2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## BBH events (O4 sensitivity)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* `ler` initialization" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "interpolation for each mass_ratios: 100%|███████████████████████████| 50/50 [02:35<00:00, 3.11s/it]\n" ] } ], "source": [ "ler = LeR(verbose=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* sample GW source parameters" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "unlensed params will be store in ./ler_data/unlensed_param.json\n", "chosen batch size = 100000 with total size = 500000\n", "There will be 5 batche(s)\n", "Batch no. 1\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 2\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 3\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 4\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 5\n", "sampling gw source params...\n", "calculating snrs...\n", "saving all unlensed_params in ./ler_data/unlensed_param.json...\n" ] } ], "source": [ "ler.batch_size = 100000\n", "unlensed_param = ler.unlensed_cbc_statistics(size=500000, output_jsonfile='unlensed_param.json', resume=False);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* let's consider three cases: CM = 0, -1, 2\n", "\n", "* replace the luminosity distance with the one that includes the cosmological friction term" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "new_dL_cm_m1 = dL_GW_CM(dL=unlensed_param['luminosity_distance'], CM=-1)\n", "new_dL_cm_2 = dL_GW_CM(dL=unlensed_param['luminosity_distance'], CM=2)\n", "\n", "# new luminosity distance\n", "unlensed_param_cm_0 = unlensed_param.copy()\n", "unlensed_param_cm_m1 = unlensed_param.copy()\n", "unlensed_param_cm_m1['luminosity_distance'] = new_dL_cm_m1\n", "unlensed_param_cm_2 = unlensed_param.copy()\n", "unlensed_param_cm_2['luminosity_distance'] = new_dL_cm_2\n", "\n", "# new snrs\n", "snr_cm_m1 = ler.snr(gw_param_dict=unlensed_param_cm_m1)\n", "snr_cm_2 = ler.snr(gw_param_dict=unlensed_param_cm_2)\n", "unlensed_param_cm_m1.update(snr_cm_m1)\n", "unlensed_param_cm_2.update(snr_cm_2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### rates of detectable events per year" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 441.8357225693884\n", "number of simulated unlensed detectable events: 2134\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_0_det.json\n" ] } ], "source": [ "# CM = 0\n", "_, unlensed_param_cm_0_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_0, \n", " output_jsonfile='unlensed_param_cm_0_det.json'\n", " )" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 856.9625378231952\n", "number of simulated unlensed detectable events: 4139\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_m1_det.json\n" ] } ], "source": [ "# CM = -1\n", "_, unlensed_param_cm_m1_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_m1, \n", " output_jsonfile='unlensed_param_cm_m1_det.json'\n", " )" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 112.63291147035956\n", "number of simulated unlensed detectable events: 544\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_2_det.json\n" ] } ], "source": [ "# CM = 2\n", "_, unlensed_param_cm_2_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_2, \n", " output_jsonfile='unlensed_param_cm_2_det.json'\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* there is significant difference in the rates of detectable events per year for the three cases" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### redshifts plot" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# getting param from json file\n", "# uncomment the following lines to get the parameters from the json file\n", "# unlensed_param_cm_0 = get_param_from_json(\"ler_data/unlensed_param_cm_0_det.json\")\n", "# unlensed_param_cm_m1 = get_param_from_json(\"ler_data/unlensed_param_cm_m1_det.json\")\n", "# unlensed_param_cm_2 = get_param_from_json(\"ler_data/unlensed_param_cm_2_det.json\")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "z1 = dL_to_z(unlensed_param_cm_0['luminosity_distance'])\n", "z2 = dL_to_z(unlensed_param_cm_m1['luminosity_distance'])\n", "z3 = dL_to_z(unlensed_param_cm_2['luminosity_distance'])\n", "z1_det = dL_to_z(unlensed_param_cm_0_det['luminosity_distance'])\n", "z2_det = dL_to_z(unlensed_param_cm_m1_det['luminosity_distance'])\n", "z3_det = dL_to_z(unlensed_param_cm_2_det['luminosity_distance'])\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.hist(z1, bins=100, histtype='step', label='z CM=0', density=True, color='r', linestyle='--', alpha=0.5)\n", "plt.hist(z2, bins=100, histtype='step', label='z CM=-1', density=True, color='g', linestyle='--', alpha=0.5)\n", "plt.hist(z3, bins=100, histtype='step', label='z CM=2', density=True, color='b', linestyle='--', alpha=0.5)\n", "plt.hist(z1_det, bins=20, histtype='step', label='z CM=0, snr>8', density=True, color='r', linestyle='-', alpha=1)\n", "plt.hist(z2_det, bins=20, histtype='step', label='z CM=-1, snr>8', density=True, color='g', linestyle='-', alpha=1)\n", "plt.hist(z3_det, bins=20, histtype='step', label='z CM=2, snr>8', density=True, color='b', linestyle='-', alpha=1)\n", "plt.legend()\n", "plt.xlabel('z')\n", "plt.ylabel('pdf')\n", "plt.xlim(0, 5)\n", "plt.grid(alpha=0.4)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* redshift distribution almost the same, the detectability is limited by the sensitivity of the detector" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inferred source chirp-mass vs redshift\n", "\n", "* detectable cases only\n", "\n", "* inferred source $\\mathcal{M}_c=\\mathcal{M}_c^{obs} / (1+z_s^{obs}$)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# getting param from json file\n", "# unlensed_param_cm_0 = get_param_from_json(\"ler_data/unlensed_param_cm_0_det.json\")\n", "# unlensed_param_cm_m1 = get_param_from_json(\"ler_data/unlensed_param_cm_m1_det.json\")\n", "# unlensed_param_cm_2 = get_param_from_json(\"ler_data/unlensed_param_cm_2_det.json\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* for CM = 0" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "# detector frame masses\n", "m1_cm_0 = np.array(unlensed_param_cm_0['mass_1'])\n", "m2_cm_0 = np.array(unlensed_param_cm_0['mass_2'])\n", "# chirp mass\n", "mc_cm_0 = (m1_cm_0*m2_cm_0)**(3/5)/(m1_cm_0+m2_cm_0)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_0 = np.array(unlensed_param_cm_0['luminosity_distance'])\n", "z_cm_0 = dL_to_z(dl_cm_0)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_0 = mc_cm_0/(1+z_cm_0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* for CM = -1" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "# detector frame masses\n", "m1_cm_m1 = np.array(unlensed_param_cm_m1['mass_1'])\n", "m2_cm_m1 = np.array(unlensed_param_cm_m1['mass_2'])\n", "# chirp mass\n", "mc_cm_m1 = (m1_cm_m1*m2_cm_m1)**(3/5)/(m1_cm_m1+m2_cm_m1)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_m1 = np.array(unlensed_param_cm_m1['luminosity_distance'])\n", "z_cm_m1 = dL_to_z(dl_cm_m1)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_m1 = mc_cm_m1/(1+z_cm_m1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* for CM = 2" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "# detector frame masses\n", "m1_cm_2 = np.array(unlensed_param_cm_2['mass_1'])\n", "m2_cm_2 = np.array(unlensed_param_cm_2['mass_2'])\n", "# chirp mass\n", "mc_cm_2 = (m1_cm_2*m2_cm_2)**(3/5)/(m1_cm_2+m2_cm_2)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_2 = np.array(unlensed_param_cm_2['luminosity_distance'])\n", "z_cm_2 = dL_to_z(dl_cm_2)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_2 = mc_cm_2/(1+z_cm_2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Contour plot of the inferred chirp-mass vs redshift" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from scipy.stats import gaussian_kde" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "# cm_0\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_0 # Your mass data\n", "redshift = z_cm_0 # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X1, Y1 = np.meshgrid(xgrid, ygrid)\n", "Z1 = gaussian_kde(xy)(np.vstack([X1.ravel(), Y1.ravel()])).reshape(X1.shape)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "# cm_2\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_2 # Your mass data\n", "redshift = z_cm_2 # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X2, Y2 = np.meshgrid(xgrid, ygrid)\n", "Z2 = gaussian_kde(xy)(np.vstack([X2.ravel(), Y2.ravel()])).reshape(X2.shape)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# cm_m1\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_m1 # Your mass data\n", "redshift = z_cm_m1 # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X3, Y3 = np.meshgrid(xgrid, ygrid)\n", "Z3 = gaussian_kde(xy)(np.vstack([X3.ravel(), Y3.ravel()])).reshape(X3.shape)\n" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:matplotlib.mathtext:Substituting symbol M from STIXNonUnicode\n", "INFO:matplotlib.mathtext:Substituting symbol M from STIXNonUnicode\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting\n", "plt.figure(figsize=(6, 4))\n", "plt.contour(X1, Y1, Z1, levels=levels, colors=['red', 'red', 'red', 'red', 'red'], alpha=0.8)\n", "plt.contour(X3, Y3, Z3, levels=levels, colors=['green', 'green', 'green', 'green', 'green'], alpha=0.8)\n", "plt.contour(X2, Y2, Z2, levels=levels, colors=['blue', 'blue', 'blue', 'blue', 'blue'], alpha=0.8)\n", "plt.xlabel(\"observed redshift\")\n", "plt.ylabel(r\"inferred $\\mathcal{M}^{source} (M_\\odot)$\")\n", "plt.title(\"Chirp mass vs Redshift 10%, 30%, 50%, 70%, 90% contours of density\")\n", "# plt.colorbar(contour1, label='Density')\n", "plt.xlim(0, 2.0)\n", "plt.ylim(5, 40)\n", "plt.grid(alpha=0.3)\n", "# Add legend\n", "# Create proxy artists for legend\n", "proxy1 = plt.Line2D([0], [0], linestyle='-', color='red', label='CM=0')\n", "proxy3 = plt.Line2D([0], [0], linestyle='-', color='green', label='CM=-1')\n", "proxy2 = plt.Line2D([0], [0], linestyle='-', color='blue', label='CM=2')\n", "plt.legend(handles=[proxy1, proxy3, proxy2], loc='upper right')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* This plot shows no significant shift in the plots\n", "\n", "* The plot is much different from effect caused by lensed events, as shown below. So we don't expect significant degeneracy between the two effects, in O4 sensitivity.\n", "\n", "

\n", " \"zs\"\n", "

\n", "\n", "\n", "* Let's look at the chirp mass only " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Looking for outlier in the inferred chirp mass distribution" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "# create cdf function of mc_source_eff_ distribution\n", "def cdf(data):\n", " \"\"\" Cumulative distribution function of a 1D array \"\"\"\n", " x = np.sort(data)\n", " n = x.size\n", " y = np.arange(1, n+1) / n\n", " return x, y\n", "\n", "x_cm_0, y_cm_0 = cdf(mc_inferred_cm_0)\n", "x_cm_m1, y_cm_m1 = cdf(mc_inferred_cm_m1)\n", "x_cm_2, y_cm_2 = cdf(mc_inferred_cm_2)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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CA1HH0ia2dqxfb7a4hDCXUbtG8SD6AQBH+h+hfOHyZo5ICJEVknRYqPJP/qZeuvRkR69e6v22bfDggVliEnlPTEwMr7/+Oq+//nqOTYOe3fIPBB/g+5PfA7C7125JOISwYpJ0WKjWrdX79eshNhZ11rCqVdXF33791ayxibxDr9ezdu1a1q5dm2PToGen/F2Xd9FtbTcA+lXvR9OSTU0dohAiF0nSYaGaN4dixSA8HJ4sXQHt26v3R4+aLS4hcsuJkBO0+akNIeEheLt4878W/zN3SEKIbJKkw0JptdCggbp97dqTndWqqff795sjJCFyTYIhgXc2vYNe0dO4RGP+GvQXhZwKmTssIUQ2SdJhwdzd1fvz55/saNkSbGzUHevWmS0uIXLa7MOz+fvO3xRyLMQvr/9CEeci5g5JCGECknRYsBYt1PvffweDATULSdwpo1hEHjXr0Cw+3vkxAFObT5WEQ4g8RJIOC9a2LTg5qZdXzp17svODD9T7Y8fMFpcQOWX7xe0E7AgAoG+1vvSv0d/MEQkhTEmSDgvm4gIvvaRuBwU92Vm7ttrh48IFOHTIbLEJYWrn751n4JaBALxX6z0Wd1osU5wLkcdI0mHhGjZU79esebKjcGHo0EHd/uEHs8Qk8g4nJyciIiKIiIjAycnJbOUfuX2Eeovrce3xNYq7FefzZp+bPBYhhPlJ0mHh3nxTvd+zB65efbKz/5Mm561bQVHMEZbIIzQaDc7Ozjg7O+dIq0JGyg+NDOX9ve/zOPYxZTzKcKDvATwcPUweixDC/CTpsHDly6tXVACWL3+ys0ULdTnaO3fgn3/MFpsQ2aUoCgO2DOBB7APKepTl2LvHKFGghLnDEkLkEEk6rEDisivGLhwODlCvnro9a5ZZYhJ5Q2xsLH369KFPnz7Exsbmevmf7/+cTRc2oUHD3Ffm4u7gbvIYhBCWQ5IOK9CsmXq/d++TobMAAWoPf1atgshIc4Ql8oCEhASWLVvGsmXLSEhIyNXyAy8HMn7veABG1xxN85LNTX5+IYRlkaTDClSooC40GxMDd+8+2dmhAxQooO48ccKc4QmRaQmGBD7Ypg7/7lC2AwNeHGDmiIQQuUGSDitgawsvvKBuG4fOajRPJwoLDDRLXEJkxYPoB7y86GXOhp7Fw9GD79t/b+6QhBC5RJIOK5Fivg54uhTtd99BVFSuxyREZkXHR9NpVSeOhaiT2817ZZ7MOCpEPiJJh5VIbNRItqp9r17g7w+3b8PKleYIS4gMi9fH02VNFw4EH8DN3o1j7x7jzRffNHdYQohcJEmHlUhc1f7mTfj44ycdSu3s4J131Cd27DBbbEJkxLyj89h2cRsONg5s7r6ZWj61zB2SECKXSdJhJQoXhgFP+trNnKkOWgGgfn31fv9+yIEhj0KYyoR9EwCY3Xo2jUo0MnM0QghzkKTDiixc+HSGUuPK9g0aqBnJnTswebLZYhPWycnJibt373L37t0cmwb99p3bNJrbCL1OT6tSrXi35rsmP48QwjpI0mFFNBp498nf6+3b4d491EssX3+t7vz66yQTeQiRPo1GQ5EiRShSpEiOTYO+L3Qf++/tx9HWka/bfI1WI392hMiv5LffyjRtClWqqPOB/fbbk52vvQZOThAeLsNnhUWJSYjh092fAjCs7jDKFS5n5oiEEOYkSYeV0WigZUt12zgtuq3t074dffpAXJw5QhNWKDY2lsGDBzN48OAcmQZ9yu4pXPzxIk47nPiw9ocmL18IYV0sMumYN28e/v7+ODg4ULduXY4ePZrm8bNnz6ZcuXI4Ojri6+vLRx99RExMTC5Fm/teflm93707yc7ENVhCQtT50oXIgISEBObPn8/8+fNNPg36+Xvn+Xzf53AMog5G4WLjYtLyhRDWx+KSjtWrVxMQEMCECRM4efIkVatWpXXr1tw1zv+d3MqVKxk9ejQTJkzg3LlzLFq0iNWrV/PJJ5/kcuS5p0ULtXHjwgU4f/7JzkqV4O231e1Fi8wWmxCJpv8x3dwhCCEsjMUlHV999RXvvvsuffv2pWLFiixcuBAnJycWL16c6vEHDx6kfv369OjRA39/f1q1akX37t3TbR2xZm5uar8OgD//TPLEB+paFqxdC9ev53pcQiQ6c/cMS04tMXcYQggLY2PuAJKKi4vjxIkTjBkzxrhPq9XSokULDhk7MCT38ssv89NPP3H06FHq1KnD5cuX+e2333g78b/+VMTGxia7fh0WFgaAwWDAYCWjPxo10nDihIYFCxS6dlXQ6YAaNdA0bIgmKAjD4sUwbly65SS+Z2t535bImuswacymeg8GxcAHv3+AgkKHsh3YzOY0y7fm+rMUUofZI/WXPZmpN4tKOu7du4der8fT0zPZfk9PT/79999UX9OjRw/u3btHgwYNUBSFhIQEBg0alObllalTpzJp0qQU+69fv46rq2v23kQuqV/fnlmzvNm/X8OoUY/44IPHADh36kSRoCDi163jVu/e6ZajKAoPHz5Eo9HkyJDJ/MCa6zAqyZo9169fN8lcHfP/mc/uq7txtHHk3bLvGpOO55VvzfVnKaQOs0fqL3vCw8MzfKxFJR1ZsXfvXr744gvmz59P3bp1uXjxIsOGDWPy5MmMe85/+mPGjCEgIMD4OCwsDF9fX3x9fXFzc8ut0LPFzw++/trABx9omT27AEOHulOiBNClC4wYgf0//+CXeGAaDAYDiqLg6+uLVmtxV9usgjXXYWRkpHHb19cXZ2fnbJV35u4ZvvrzKwDGNRpHkxebpFu+NdefpZA6zB6pv+xJvFqQERaVdBQuXBidTsedO3eS7b9z5w5eXl6pvmbcuHG8/fbb9O/fH4DKlSsTGRnJgAED+PTTT1P9ANnb22Nvb59iv1artaoP3JAhMGMGXL+uYdcujTpxWMmS0Lgx7NuHdulSmDgx3XIS37c1vXdLY611mDTe7MYfHhtOl1+6oFf0tC7VmlENRhEdFZ2h8q21/iyJ1GH2SP1lXWbqzKJq187Ojpo1axKYZIIrg8FAYGAg9erVS/U1UVFRKd6wTqcD1CazvEyjeTot+siRYEw2Bw5U77/6Ch49Mkdowko4Ojpy5coVrly5gqOjY7bK+iLoCy4+uIivmy9LOy9Fq9GatHwhhPWzqKQDICAggO+//55ly5Zx7tw53nvvPSIjI+nbty8AvXr1StbRtEOHDixYsIBVq1Zx5coVdu7cybhx4+jQoYMx+cjLPv8cihdXc4vly5/sfP11qFBBnaF09WpzhicsnFarxd/fH39//2z9h/fvvX+ZflAdIjunzRy8XLxMWr4QIm+wqMsrAN26dSM0NJTx48dz+/ZtqlWrxrZt24ydS4ODg5P98Ro7diwajYaxY8dy8+ZNihQpQocOHZgyZYq53kKusrODvn3Vtd7WrlUvuWBjAz17wtix6nK0iS0fQuSA6Phouq3thkEx0LZ0WzqX72zukIQQFkqj5PVrEBkQFhaGu7s7jx8/tpqOpEmdPavODWZrC1FRas7Bn39CjRrqASdPQvXqqb7WYDAQHByMn5+f/CeaRdZch3FxcXz6qbo2ypQpU7Czs8vU6+9H3afLmi7sv7YfD0cP/hr0F8XdimeqfGuuP0shdZg9Un/Zk5nvUKndPKB8eXW9t/h4OHPmyc5q1aBZM3V7wgRzhSYsXHx8PDNnzmTmzJnEx8dn+vVDfx/K/mv7cbJ1Yn239ckSDlOUL4TIWyTpyAO0WkjsZ3vgwJOdGg0kzlWyc6faBCKECf0R/Ac/n/4ZDRq29dxGoxKNzB2SEMLCSdKRRyQuAnfsWJKdzZqBry/ExMDcuWaJS+RNUfFR9N6gTj7XuXxnGpZoaOaIhBDWQJKOPKJyZfV+61a4fPnJTo3m6Xoso0apfTuEMIGJeydy6eElirsVZ3Gn1NdFEkKIZ0nSkUd06AClSsG9ezBzZpInhg+Hdu3U7ecsmidEZqz8ZyUzDs4AYP4r8yngUMC8AQkhrIYkHXmEg4M6ZwdAkrnVkrd2rFwJSRa6EyKzrjy8Qt+N6pw5H9b9kA7lOpg5IiGENZGkIw9JHCF74QIEBSV5onlzKFYMHj6EHTvMEpvIG4b8PoQ4fRx1itXhy9ZfmjscIYSVkaQjDylTBtq2VbcXLkzyhE4H7dur27//nutxCcvl6OjI6dOnOX36dLrTlG86v4nf/vsNG60NyzovQ6tJ/89HZsoXQuR9knTkIRoN6qJvwKlTzzzZubN6/9NP6vToQqBOU16pUiUqVaqU5qRI4bHh9N+kLqrYv3p/yhcub9LyhRD5g/wVyGMaN1bn7Th7Fq5fT/JEy5bg768mHNOmmSs8YaW+PvI1oVGhlPEow5y2c8wdjhDCSknSkcd4eECVKup2r17w4MGTJ3Q6eOMNdfubbyAuzizxCcsSFxfHxIkTmThxInHP+UycCDnBpH2TAPik4SfY6TI+VXpGyhdC5B+SdORBX3yhrsOydy+89x4YV9cZNUq9Dw+HzZvNFZ6wIPHx8UyaNIlJkyalOk15TEIMr/3yGvGGeDqV60Tvqr1NWr4QIn+RpCMPatsWNm1SL7OsWQNjxjxJPDw84MMP1YN27jRniMJKzPhjBlcfXcXVzpW5r8xFo9GYOyQhhBWTpCOPatMG5s1Tt//3PzX5AKBmTfX+229h+XKzxCasw+m7p42XVea3m59iMTchhMgsSTrysEGDnjZsLFjwZGf79lD8yZfHe+/B33+bIzRh4QyKgQ+3fYhe0dOsZDN6Vu5p7pCEEHmAJB153ODBah/Sfftg3TqgQAG4cgWqV4eoKDR9+8ospSKF7098T+CVQOx19ixot0AuqwghTEKSjjyudGkYOFDdHjhQzTewsYEtW6BgQTSnTuG2ZIlZYxSWJTQylE93fwrApCaTKFuorJkjEkLkFZJ05AMzZ0K5cnD/PkyZ8mSnjw9MngyA+7ffwokT5gtQWAxFUei3qR/3o+9TwKEAfar1MXdIQog8RJKOfMDR8WmysXGjugQLAAMGoNSsie7RI7R16si6LPmQg4MDR48e5ejRozg4OLD4z8VsvrAZO50dO9/eiaeLp0nLF0Lkb5J05BOvvAJly8K9ezBu3JOdtrYoGzY8PWjAAJkiPZ/R6XTUrl2b2rVrczvyNqMDRwMwsfFEavnUMmn5Op0u2+UJIaybJB35hKPj0xEs334Ljx49ecLHh+t//IFSqBBcuwbDh5srRGFmo3aN4l7UPUoWKMnQukPNHY4QIg+SpCMfadZMXX4lISH5SFm9jw/K8uXqinHffw/nz5stRpG74uLimDFjBgHjA1h5aiUAy19djoudi0nLnzFjhkyDLoSQpCO/eeEF9X7sWIiOTvJEmzbqNRiATz/N9biEecTHxzNy5EhmTZ6FoldoXao19X3rm7z8kSNHyjToQghJOvKbTz4Be3sICno6Y6nRk9EsrFsHx47lemzCvIo6F2VRx0UyJ4cQIsdI0pHPNG8Os2ap28ap0RNVqwb1n/yX26wZnDmTm6EJM/j17K/G7dmtZ1PMrZgZoxFC5HWSdORDL7+s3p8582SysEQajdrKUacOREQkGeYi8iKDYmBK0BTj4w7lOpgxGiFEfiBJRz5UubJxFnRq1NBw+rTd0yc9PdXOpFotrF8PX35pvkBFjtpyYQvn7z/tNCyXVYQQOU2SjnxIq4UNG9S+HWFhGkaMKExUVJIDqlSBvn3V7REjoHdvMBjMEarIIVcfXeWtX98ydxhCiHxGko58ys9P7VQKcP68Hc2aaZJ34fj6axitThTF8uUQEJDrMYqcM2nfJMLjwmW5eiFErrIxdwDCfD75BAoUMBAQoOHYMQ1Vq6pXVDp0AJycYOpU9XLLRx/BnDlqE8m0aWBnl27ZwnIt/nMxS08tBWBlt5Xo6+oBcmSacgcHB/bs2ZNj5QshrIskHfmYjQ0MGQIlStxiyhRvjh3TMHPmk6Qj0bBhsHevumjLrFlw+zasWKF2OhVW59qjawz9XZ1tdGidoTT0bwj+OXc+nU5HkyZNcu4EQgirIpdXBFWrxrFkiQLAwYPw339JntRo4NdfYcYM9fHPP0ONGvDdd7kfqMi2gVsGEhUfRW2f2sxuM9vc4Qgh8hlJOgQAFSpAvXrqFOkVK8KqVUme1GrVDqVff60+PnUKBg58OpmYsAp/3vqT7Ze2AzC/3Xy0Gi3x8fHMmzePefPm5ciMoTldvhDCukjSIYyWLlWn6EhIgEGDnpkmHWDoULh8Gd58U308ZQpcvZrLUYqseBj9kN4begPwesXXjSvIxsXFMWTIEIYMGZIja6PkdPlCCOsiSYcwKlsWdu2CggXh8WO1H2kKJUvCypVqs0hsLLRqBfJlYvE+2/cZ/9z9B09nT2a2mmnucIQQ+ZQkHSIZV9en84FNnqxeVbl27ZmDNBr49lu1J+p//4G7O9y4keuxiozZeWknC44vAOC7Dt/h5+5n5oiEEPmVJB0ihR491AYMUBOQMmXUKynJVK4MP/ygbsfEQKVKcOtWrsYp0nfy1kk6rupIrD6WOsXq0L5se3OHJITIxyTpECnY28O2bbBlCzRuDPHxMHYs3L37zIG9e8PmzeqcHmFh0Lq1erCwCGGxYbT5qQ0xCTFULlqZHW/tQKuRX3khhPnIXyCRKo0G2rWDPXugQAF1X4UKMGmS2rBh1L49HDumJh7//AMffmiGaEVqBmweQGhUKCULlGR/3/24O7ibOyQhRD4nSYdIU+I0Hb6+8OABTJyoXn5JpmJFdeIwgPnz1bk8hFntv7af1WdWo9PoWNp5KQUcCpg7JCGEkKRDpK9pU7h4Uc0nQJ0qff58UJQkBw0YAGPGqNsffZRK71ORW26E3eDV1a8C8E71d2hUotFzj7W3t2fLli1s2bIFe3t7k8eS0+ULIayLTIMuMsTODt57D4KC1IaMwYMhIgJGjkxy0PjxsHq1OpdHpUpw5QoUKWK2mPMjRVHot6kfD6IfULloZf7X4n9pHm9jY0O7du1yLJ6cLl8IYV2kpUNkStIFZ0eNUrcfP37ypIMDbNgAbm4QGQnNmsHZs+YKNd9RFIUhvw1hx6Ud2OnsWP7qcgo6FjR3WEIIYSRJh8gUGxt1GZaaNdXHs2apS7EYp+moXFltCtFq4fRpePFFdU4PkeO+PfEt84/PR4OGRR0XUc2rWrqviY+PZ+nSpSxdujTHpkHPyfKFENZFkg6RaVqtOqR2yhR1XrDLl6FKFXX0LACvvAJnzqhTmyqKOqf63LlmjTmvu/TgEqN2jQJgRssZvFXlrQy9Li4ujr59+9K3b98cmwY9J8sXQlgXSTpElhQuDJ98oo6WLVUKHj58etkFgPLl4fp1SFzWfOjQJFmJMCW9Qc87m94hLDaMl4q/xIcvfWjukIQQIlWSdIhsKVMGAgPV7cuX1eTDyNlZffLll9XHHTvCBx+AwZDrceZVcfo4+m7sy/5r+3GydWJpp6XotDpzhyWEEKmSpENkW4kSasOGwQDz5j3zpFYL33+vLhAH8M038OOPuR5jXjVy50h+/Futz/mvzKdc4XJmjkgIIZ7PIpOOefPm4e/vj4ODA3Xr1uXo0aNpHv/o0SMGDx6Mt7c39vb2lC1blt9++y2XohWgDqEFWLXqmfk7QJ087OBBGD5cffzuu+rYW5Et4/eMZ86ROQAs7riY3tV6mzkiIYRIm8UlHatXryYgIIAJEyZw8uRJqlatSuvWrbmbYuEPVVxcHC1btuTq1ausXbuW8+fP8/3331OsWLFcjjx/69IFdDq1/2ji5KQpfPYZ1Kqlrs/y4YeQkJCbIeYpuy7vYvL+yQB0qdCFvtX7mjkiIYRIn8UlHV999RXvvvsuffv2pWLFiixcuBAnJycWL16c6vGLFy/mwYMHbNiwgfr16+Pv70/jxo2pWrVqLkeev/n4qCvSAowYAX/8kcpBTk7qnOru7nDyJHh6ws6duRpnXnDy1kne+OUNANqVacea19aYOSIhhMgYi5qRNC4ujhMnTjAmcTptQKvV0qJFCw4dOpTqazZt2kS9evUYPHgwGzdupEiRIvTo0YNRo0ah06XeoS42NpbY2Fjj47CwMAAMBgOGfNbJMfE9m+J9DxkCJ05o+PFHDQMHKhw/rmBn98xBxYrB9OloBw6EBw9QOnZE2bXraZ8PK2TKOkzPhfsXaLSkEZHxkfi5+7G442I0aLJ8bltbW1atWmXcNvV7yEj5uVl/eZXUYfZI/WVPZurNopKOe/fuodfr8fT0TLbf09OTf//9N9XXXL58md27d9OzZ09+++03Ll68yPvvv098fDwTJkxI9TVTp05l0qRJKfZfv34dV1fX7L8RK6IoCg8fPkSj0aDRaLJdXkCAlq1bi3HmjI7OnaMYP/4BPj765Ae1aoXu4EGKDB2Kw4kT0LQpt1avJq569Wyf3xxMXYfPE6uPpef2nkTGR1LKvRQ/tvyRqHtRBBOcrXLr1q0LQEhIiCnCzHT5uVV/eZnUYfZI/WVPeHh4ho+1qKQjKwwGA0WLFuW7775Dp9NRs2ZNbt68yYwZM56bdIwZM4aAJJNKhIWF4evri6+vL25ubrkVukUwGAwoioKvry9abfavtvn5qSNYevRQ2L7dmf37nfjuOyXlyrR+frBhA8pLL6G5eRPvd96BPn1QPv0UPDyyHUduMnUdPs/wHcM5GXoSnUbHz6//TE3vmjl2rtyUW/WXl0kdZo/UX/YkXi3ICItKOgoXLoxOp+POnTvJ9t+5cwcvL69UX+Pt7Y2trW2ySykVKlTg9u3bxMXFYZeifV9d+TK1FS+1Wm2+/MAlvm9Tvfc334Ry5WDYMAgK0jBggIZOnSBFI1Lx4ursYvXro7lyBWbPRvPtt7B2rbpui4ODSeLJDaauw2ftv7af2UdmAzC7zWxqF6ttknITEhJYv349AK+++io2Nqb9k5DR8nO6/vIDqcPskfrLuszUmUXVrp2dHTVr1iQwcbYp1Aw0MDCQes+55l+/fn0uXryY7JrShQsX8Pb2TjXhELmjenXYuxdcXCA6Oo0Rst7ecOqUOqc6qAe3a6euTiszmAJw8cFFeqxTm4q6v9idIXWGmKzs2NhY3njjDd54441k/ZyspXwhhHWxqKQDICAggO+//55ly5Zx7tw53nvvPSIjI+nbVx0S2KtXr2QdTd977z0ePHjAsGHDuHDhAlu3buWLL75gcOLEEcJstFp48mPjk09g4kR1ldo//lAXoTVyc1MPuHdPbR4BiIhQZzBt3x7+/DO3Q7cYEXERtPyxJTfDb1LGowwL2y80d0hCCJFlFnV5BaBbt26EhoYyfvx4bt++TbVq1di2bZuxc2lwcHCyphxfX1+2b9/ORx99RJUqVShWrBjDhg1j1KhR5noLIonevdVJSP/6S70lcnFRE5KZM3k6wqVQIZg9Gz7/XF2d9to12LpVbTLZt+/p0rb5yKeBn3L10VX83P3Y12cfbvb5q8+RECJv0ShKivkj852wsDDc3d15/PhxvuxIGhwcjJ+fX45dy9yzB44cgUuX1Nu//8KtW+pzy5fD22+n8iJFUft7fPwx7N8PZcuqE4D07k3KcbjmlVN1eOj6IRosaYBBMbD9re20KtXKZGUnioyMxMXFBYCIiAicnZ1zvfzc+AzmdVKH2SP1lz2Z+Q6V2hU5rmlTGD1aXYJl9264eRPatlWfGzgQTp9O5UUaDdSpo04mVrgwXLgAAwaoK8wtXarOapqHRcZF0mtDLwyKgZ6Ve+ZIwiGEELlNkg6R6zQa+OUXqF9f7Tfarx8EP2+qiUKF1F6onTuDra16YN++0LIl3LiRm2HnGr1BT9+Nfbn44CLF3Yoz95W55g5JCCFMIsNJx9dff53uwmtCZJSzMyxbBgULwtGj6kq11avDhAnw33/PHFy+PKxfD3fuwNix6r7EPh55LPFQFIV3Nr3DL2d/QavRsqTTEgo4FDB3WEIIYRIZTjo+/PBDtm3bZnys0+mYPHlyjgQl8odSpeC336BBA3Wky6lT6ppwVarAqFFw/DjExSV5QcGCMHkyHDigDrW9e1cd7ZLsIOulKArDtg1j+V/LAXWp+hYvtMjRc9rZ2bFkyRKWLFmSI0PMc7p8IYR1yXDS4ejomGycvaIoSB9UkV0vvaRePbl9W+2q0aABxMTA9OlQu7Y6yqVGDXUEjFH9+rBokbr9669qJ9Pt280RvsnoDXoGbRnEN0fVN/ppw08ZWGtgjp/X1taWPn360KdPH2xtba2ufCGEdclw0lGyZEm2b9+ebLZQmaNemEqRIurAlL17Yc0atQtHgQJqf9E//4QPPoDXX4fAQHj0CLUn6urV6kHXrkGbNjB8OCQkmPNtZMmft/6k7g91+e7kd2g1Wma2nMnkptKKKITIezKcdAwYMICTJ0/i4+NjnHJ84sSJ6HS6NG+mnlZZ5G06nZpcrF8PDx7AlStqAgLq7OgtWqgL1W7bBrzxBpw5o865DvDVV9C/v7lCz5KtF7bSaGkjTtw6gQYNa15bw/CXh+daQp+QkMDWrVvZunUrCTmQsOV0+UII65LhjOCDDz6gaNGibN26lZCQEPbs2YOfnx/+/v45GJ7IzzQa8PdXL7t8+606bcfRo+oAlq5doWdPGDHCh7Jnz8KSJfDuu2rvVA8PmDFDzWAs2O///U6XNV2I08dR37c+q19bTTG3YrkaQ2xsLO3btwfUeTRM/U9CTpcvhLAumfoL8Oabb/Lmm28C6gIvffv2Zfz48TkSmBCJ3N1h5Eh1Oy4OXnlFvczy/ffw88+wcaOWZv36qTOOjRsHs2apM5L9+KM6s6kF2vDvBrqv606cPo62pduy4c0N2Omko6UQIm/L8jwdS5YsoVOnTqaMRYh02dmpfUZ374aqVdUlWpo3hz59wPDJWLVJpEABdShM5crqpZcVK8CCFhtb8fcKXl39KjEJMbQv256Nb26UhEMIkS9kOeno3bs3VatWNWUsQmSITqfOcvr77+o9qFdVBg2CfxsNgH/+gWrV1CcuXIC33oJKleDQIbPFnOhG2A0+2PYBoK4Y+8vrv2Crk1EdQoj8IcOXV5YvX57lk/Tq1SvLrxXieby91RaPOXPgww/Vyy1LlsCqVcXp+uef6vzqP/2kjr+9dEnNUNavfzoHey57EP2Azqs68yD6AS8WfZGlnZdKC4cQIl/JcNLRp0+fZD3qFUVJt4d94jGSdIic9MEHaofTadPg8GF47TV45x1YsOBF7KZNU2ca69JFHY/77rtw/rw6JWouCn4cTKsfW3H+/nkKORZi05ubJOEQQuQ7GU46lixZkmLf2rVr2bp1K82bN6dhw4Z4enpy584d9u/fz+7du2nfvj1du3Y1acBCPEujgU6d1Kk6PvlE7Ue6eLG6mu3KlVCiREF16tOKFeHqVfD0VA94441ciW/v1b288csbhEaFUtytOL/1+I2SBUvmyrmFEMKSZDjp6N27d7LHGzZsYOfOnWzfvp2WLVumOH7Hjh107NiR/lY2b4KwXvb28OWX0KSJOqT24EF4/33YuhVwdIQfflAXiouMhDffhJAQ9bpMDtEb9Mw+PJtPd39KrD6WCoUrsPHNjZQpVCbHzplZdnZ2zJ0717htbeULIayLRsniXOZ16tShfPnyafb1ePvttzl//rzFLxQXFhaGu7s7jx8/xs3Nzdzh5CqDwUBwcDB+fn5otXln0eEDB6BRI1AU+OIL9QqLVguEh0OzZurCLgAffwxjxqjrumRRanWYYEig36Z+xnVUOpbryOrXVuNg45Ddt5bn5NXPYG6SOsweqb/sycx3aJZr98yZM/j6+qZ5jK+vL2fOnMnqKYTIsgYNYMgQdfuTT+Cjj9QEBFdXdRRL4nDvGTOgbl11jg8TOXrzKLW+q8Xyv5ajQcNnTT7j1zd+lYRDCJHvZTnpcHV1Zf/+/Wkes3//flxdXbN6CiGyZdYstRED4OuvYcqUJ0/Y2MAvv6gdPry84L//1NXlTp7M9jl3XtrJy4te5q87f+Fk68T6busZ13gcOq1lzo6q1+vZu3cve/fuRa/XW135QgjrkuWko3Pnzhw8eJD33nuPu3fvJnvu7t27DBo0iEOHDvHqq69mO0ghskKnUxONqVPVx7Nng8Hw5ElbW+jeHXbtguLF4eZNdUjtjh1ZPt/lh5fp8WsP9IqeGt41OD/kPJ3KW/YEejExMTRt2pSmTZsSExNjdeULIaxLlpOOqVOnUqlSJb799ltKlChB5cqVad68OZUrV6ZEiRJ89913VKpUiamJf/GFMAONRl181tUV7t9P0tqRqFIlOHECypaFsDB1dbnAwEyf52rYVVqvaM29qHtULlqZP975g+JuxU3yHoQQIq/IctJRsGBBjhw5wvjx4/Hx8eHMmTPs2bOHM2fO4OPjw/jx4zl8+DAFChQwYbhCZJ6tLQwdqm6PHw+ffaYuzRIa+uSAokXVSysNGkB0tDp52PTpGZ46/efTP9NmUxsuP7yMt4s3v/f8XfpvCCFEKrI8euVZ4eHhhIWF4ebmZnX9OGT0St7vta0o0K6dOnV6Uu3bw+bNTx5ERalTpq9frz4uV+7p5ZdUy1QYvWs00w9OB6Bi4Yr81vM3ShQokUPvwvQiIyNxcXEB1FVgnU08aVpGys8vn8GcJHWYPVJ/2ZMro1f++OMPAgICuH37NqB2LC1WrJgx4bh16xYBAQEcPnw4q6cQwmQ0GjWXmD5dHbhS7MkK8lu2wOXLTw5ycoI1a2DePHVlufPnoXfvJ8NeUlpwfIEx4Xij9Bsc6nfIqhIOIYTIbVlOOr766is2b96Ml5dXqs97e3uzZcsWZs2aleXghDAle3t1Wo4NG+DGDSjzZI6uyZOTHGRjo84otmOHmqns3q0uHhcebjzkVvgtRu8azdDf1Ws2nzb4lGkvT8PFziXX3osQQlijLCcdx44do0GDBmke06hRI2npEBZr7Fj1/siRVJ5s3BgmTFC3//4bGjaEmBgOXT9ExfkV+d8f/8OgGOhWqRuTmkxKdx0iIYQQmZgG/Vl3796lWGIb9XN4eXmlGE4rhKWoUUO9P3cO5s59OpmY0YQJULMmdOgAf/3FuYpFaNInljglnjIeZRhVfxR9qvVBg/UmHLa2tkyfPt24bW3lCyGsS5aTjgIFChAcHJzmMdeuXTN2IhPC0rz4otra8fnn6uiW0qXVReOSad8eFi0iaHYAb7Z8TJwCDQtWY+uA/bjaq/2XDMbJP6yPnZ0dH3/8sdWWL4SwLlm+vPLSSy+xfv16rl+/nurzwcHBbNiwgZdffjnLwQmR0z77DAYOVLffew8SElIec7p9HVp3iyPEDVxj4eupp3DdfSB3AxVCiDwgy0lHQEAAUVFR1K9fn+XLl3PrydoVt27dYtmyZdSvX5/o6GiGDx9usmCFMDWNBmbOhEKF1FXv27aFf/55+vyaM2totKQR0QnRVHYrw8Xfy1DtNuoqteksA2AN9Ho9x44d49ixYzk2DXpOli+EsC5ZTjoaNWrEV199RUhICH379qV48eLY2NhQvHhx3nnnHW7fvs2cOXNo1KiRKeMVwuRcXNRZS0GdlqNLFwiLDePDbR/SbW03HsY8pLZPbfYOOkzRw/9AnTrq7KWtW6tDbK1YTEwMderUoU6dOjk2DXpOli+EsC7ZmgVl2LBhnDx5koEDB1KjRg1eeOEFatasyXvvvceff/7J4MGDTRWnEDlq9GgICgKtVuHiRagyrR1zjswBoE+1Puzrsw8PRw913O3u3Wrn0pgY6NYNzQcfoImONvM7EEIIy5fljqSJqlSpwvz5800RixBmo9Gos6B7lb9GyFl/rq35gMK9zzOv3Vxer/h68iGxzs7qTGMjR8JXX6GZN4/CV64kmdpUiNyh1+uJj4/HYDCg1+uJiYmRGTWzQOovfXZ2diapm2wnHULkBXci7jD1wFRCGgTBv4fh7OsUXvoqnnVtSHUKDp0OvvwSmjdH6dAB599+wxAYCC1b5nrsIv9RFIXbt2/z6NEj42O9Xs/Vq1dlzpgskPpLn1arpWTJktjZ2WWrHEk6RL4WERfB2N1jWXpqKY9jH4MPtPlgK3sXdubfczb07Kn28yhf/jkFvPKKul7L8uVoW7WCFi1gyZLnrtcihCkkJhxFixbFyckJgPj4eGxtbeVLMwsURZH6S4PBYCAkJIRbt27h5+eXrTqSpEPkS+Gx4aw6vYpPd39KaJS63GxBh4LMaTOHt6p04tF4qFABbt5U76dNg1GjUi9LmTULw+bN6B4+VDOUV16BTZvA3z/33pDIN/R6vTHhKFSoEKB+aWq1Wuzs7ORLMwuk/tJXpEgRQkJCSEhIyNZEf3LxSuQ7n+//nCIzijBgywBCo0Ip6lyU8Y3Gc+3Da7xd9W00Gg0FC8K2bfDCC+prRo+G7dufU2CBAlw/cQLDvHnq43/+URd2mT37uYvFCZFV8fHxAMYWDiFyQ+JllewOfZeWDpFvGBQDw7cPZ/aR2QDYam2Z0mwK/Wv0p6BjwRTHV6umTpH+4ovw33/qwnAtW0Kqfak0Ghg0CJo1Uw+6cQM++ghu3YL//S9H31d22NraMuHJGjM5NQ16Tpafn8l/5CI3merzJkmHyBcuPrhIx587cu7eOQDeqfYO33X4Dp1Wl+br7OzUVWlr1oQ//lCnTB8/Po0XlC8PJ07Au++ql1imT4eoKLXVQ5f2uczBzs6OiRMnWm35QgjrIpdXRJ731+2/qP5tdc7dO4ernStft/maHzr+kG7CkahiRZg1S92eMAHq1YMLF9J4QdGiaqYyZoz6eO5ctYNpZGS23ocQwjzOnz+Pl5cX4eHhACxdupQCBQqYN6hUTJw4kWrVqqXY5+npiUajYcOGDYwePZqhQ4eaJ0Ak6RB5WGxCLNMOTKPW97WIiIuggEMBDvc/zNC6QzPdVNi/P/TqpV5aOXwYli1L5wUaDXzxBaxdCw4OsHcv9OihtnpYEIPBwJkzZzhz5kyOLFyX0+ULkRkxMTEMHjyYQoUK4eLiQteuXblz5066rxszZgxDhw7F1VVd5LFbt25cSPM/D8tw7tw5Jk2axLfffsutW7do27YtI0aMYNmyZVy+fNksMUnSIfKkiLgI2q1sx5jAMSQYEmhbui2nBp6iYpGKWSrPxkZNNBIvrdy+ncEXdu0KS5eq25s2QffuEBubpRhyQnR0NC+++CIvvvgi0Tkwq2pOly9EZnz00Uds3ryZX375hX379hESEkKXLl3SfE1wcDBbtmyhT58+xn2Ojo4ULVo0h6PNvkuXLgHQqVMnvLy8sLe3p3DhwrRu3ZoFCxaYJSZJOkSeEx4bTtc1XQm8Eoidzo7vO3zP1h5bKVGgRLbLrlpVvd+xAzL8j3u3bpD4C75pk5qIyKgWkc8YDAamT59O6dKlsbe3x8/PjylTpgAYJ+Vas2YNDRs2xNHRkdq1a3PhwgWOHTtGrVq1cHFxoW3btoSGhmbp/I8fP2bRokV89dVXNGvWjJo1a7JkyRIOHjzI4cOHn/u6NWvWULVqVYoVK2bc9+zllcTLGj/++CP+/v64u7vz5ptvGi/HfPfdd/j4+KRo7evUqRPvvPPOc89948YNunfvjoeHB87OztSqVYsjR44Yn582bRqenp64urrSr1+/ZOsbTZw4kQ4dOgDqxF5JW3c7dOjAqlWr0qmxnCFJh8gzFEVhyZ9LKPi/guy4tANbrS2b3txE/xr9Tdbzuk0bcHJSB6cEBWXihYMGwfLl6vbWrRAQAAkJJolJ5HOKovYXMsctE8nzmDFjmDZtGuPGjePs2bOsXLkST0/PZMdMmDCBsWPHcvLkSWxsbOjRowcjR45kzpw5BAUFcfHiRcYn6cm9YsUKXFxc0rwFPflFPXHiBPHx8bRo0cL4+vLly+Pn58ehQ4eeG3dQUBC1atVK9/1dunSJDRs2sGXLFrZs2cK+ffuYNm0aAK+//jr3799nz549xuMfPHjAtm3b6NmzZ6rlRURE0LhxY27evMmmTZv466+/GDlypDFxWbNmDRMnTuSLL77g+PHjeHt7J1uSZMSIESxZsgRQV39PXAkeoE6dOty4cYOrV6+m+75MTUaviDwhKj6KUTtHMffYXAC0Gi07395JY//GJj2PgwOULQunTkGTJjBkyNNOpul6+204fVod0TJ7tpp0fPONSeMT+VBUFBpXV+zNce6ICHUtonSEh4czZ84c5s6dS+/evQEoVaoUDRo0SHbciBEjaN26NaAuKNq9e3cCAwOpX78+AP369WNp4uVKoGPHjtStWzfNcye2UNy+fRs7O7sUHUA9PT25ncb10mvXrmUo6TAYDCxdutTY7+Ptt98mMDCQKVOmULBgQdq2bcvKlStp3rw5AGvXrqVw4cI0bdo01fJWrlxJaGgox44dw8PDA4DSpUsbn589ezb9+vWjX79+AHz++efs2rXL2Nrh4uJifK9eXl7Jyvbx8TG+N/9cnsRQWjqE1fvlzC+U+rqUMeHoW60vlz+4bPKEI9H06VC9uro9d646UCXDpk5V5+8AWL1aLrOIfOHcuXPExsYav3Cfp0qVKsbtxFaQypUrJ9t39+5d42NXV1dKly6d5s3R0TFbsUdHR+Pg4JDucf7+/saEA8Db2ztZrD179mTdunXEPunTtWLFCt58883nLqJ26tQpqlevbkw4nnXu3LkUCVe9evXSjRMw1kmUGTq2S9IhrFZUfBTvb32fN9a+we2I2xR3K86a19awuNNik/TfeJ6WLeHkSbXhAuDrrzNx6UarVRMPJycIDVUvtQiRHU5OKOHhxN6/jxIerrY+5NYtg7OiZvSLP+kEcomXRJ/dl7RfRGYur3h5eREXF2dcJC/RnTt3UrQEJFW4cGEePnyYqdhTi7VDhw4oisLWrVu5fv06QUFBz720Ahmvs6x48OABoE5tntvk8oqwSrsu72LgloFcfqgO++pVtRfftf8Oe5vca2QeMwZ+/BGCgjQcP26Pn18GX2hvr3YuXbIEXnsN/vxTXeBFiKzQaNRLHLa26mx2FjhTaZkyZXB0dCQwMJD+/fubrNzMXF6pWbMmtra2BAYG0rVrV0CdfyM4ODjNFoLq1atz9uzZbMfq4OBAly5dWLFiBRcvXqRcuXLUqFHjucdXqVKFH374gQcPHqTa2lGhQgWOHDlCr169jPvS6hCb1OnTp7G1taVSpUqZfyPZZLEtHfPmzcPf3x8HBwfq1q3L0aNHM/S6VatWodFo6Ny5c84GKMzCoBiYtHcSLX9syeWHl/Fw9GD1a6tZ1nlZriYcoOYJT/52sXdvJv8rmToVChdWh882aAD375s+wAywtbVlxIgRjBgxIsemQc/J8oV1cHBwYNSoUYwcOZLly5dz6dIlDh8+zKJFi7JVbmYur7i7u9OvXz8CAgLYs2cPJ06coG/fvtSrV4+XXnrpuedo3bo1hw4dyvaaI6BeYtm6dSuLFy9Os5UDoHv37nh5edG5c2f++OMPLl++zLp164ydXocNG8bixYtZsmQJFy5cYMKECZw5cyZDcQQFBRlHCeU2i2zpWL16NQEBASxcuJC6desye/ZsWrduzfnz59McG3316lVGjBhBw4YNczFakVsexTxi0JZBrD6zGoABNQYwudlkijqbb7x8mzawbh1s3uzMjBmQ4d9hT084elTtHPLgATRurPZOtcndX0k7OztmzJhhteUL6zFu3DhsbGwYP348ISEheHt7M2jQoFyNYdasWWi1Wrp27UpsbCytW7dONuIjNW3btsXGxoZdu3YZO7lmVbNmzfDw8OD8+fP06NEjzWPt7OzYsWMHw4cP55VXXiEhIYGKFSsy78nCkt26dePSpUuMHDmSmJgYunbtynvvvcf2565M+dSqVavMtzyBYoHq1KmjDB482PhYr9crPj4+ytSpU5/7moSEBOXll19WfvjhB6V3795Kp06dMny+x48fK4Dy+PHj7IRtlfR6vXLlyhVFr9ebO5Q0nb5zWinzdRmFiSjaSVrl2+PfmjskRVEUJTxcUby9DQooys8/Z6EO9+5VFLU7qaL06WP6AK2AtXwGLUV0dLRy9uxZJTo62rjPYDAoMTExisFgMGNk1iu9+ps7d67SqlWrXI4qZ/z2229KhQoVlPj4+Ey9LrXPXaLMfIdaXEtHXFwcJ06cYEziuhWoE5u0aNEizbHUn332GUWLFqVfv37GjkPPExsba+xBDBAWFgaoQ57y21TNie/ZUt+3oih8HvQ5E/dNBKCoc1E2dNtA3WJ1LSJmJyd49VWYP19DUBC88UYmY2rYEKZPRztyJCxdimJrizJ//nOWsjU9g8FAcHAwAH5+fs/tSZ+T5Vv6Z9DSGAwGFEUx3p6V2j6RcanV34ABA3j48CFhYWHJRqhYo4iICBYvXoxOp8vUZyXx85ba72pmfnctLum4d+8eer0+xaQxnp6e/Pvvv6m+5sCBAyxatIhTp05l6BxTp05l0qRJKfZfv37d6j9QmaUoCg8fPkSj0VjcUtk3I27y+fHP2XZtGwAtfVsyuuZovPXexi8yS1CliiPgycaNegICbmZ+MdnXXqPA1asUmD8fzfffE335MvdmzMBQsGBOhJtMVFSUsTPZmTNncMrgaARTlm/Jn0FLpNfr0ev1xMfHJ0viEmSyuWxJr/4+/vhjQP3H2Jp17NgRyPz7iI+PR6/Xc+vWLXTP/JFLnHk1Iywu6cis8PBw3n77bb7//nsKFy6codeMGTOGgIAA4+OwsDB8fX3x9fXFzc0tp0K1SIn/Nfn6+pr8v9zsCAoOoutvXbkffR+dRse8V+bxbo13zR1Wqt5808DHH+u5edOWVav8SNJIl3HffIOhYkW0Q4bgFBiI77BhKHv25PhIhMgkK9/6+vrinIGJnkxdvqV+Bi1VTEwMV69exdbWFjs7u2TPPftYZI7U3/MZDAZ0Oh3e3t4p5i1JvFqQERaXdBQuXBidTpdi5b/njaW+dOkSV69eNc4xD0+bemxsbDh//jylSpVK9hp7e3vs7VOOdNBqtfnyj17i+7aU9/7lwS/5eOfHKCiU9ijNz11/ppZP+jMCmourK4wc+ZBx4wqxdKmWTz/NYkGDB6tDYtq2RRMUhObAAbWDaQ5K+jPPic9ARsu3tM+gJUtcRyNpy1DSZnJpLco8qb/0JX7eUvs9zczvrcX9htvZ2VGzZk0CAwON+wwGA4GBgamOpS5fvjz//PMPp06dMt46duxI06ZNOXXqFL6+vrkZvsimvVf3MmLnCBQU2pZuy7F3j1l0wpGoQQN1BdWbNzOxEFxqmjV7Og53yJDsByaEEBbE4lo6AAICAujduze1atWiTp06zJ49m8jISPr27QtAr169KFasGFOnTsXBwYEXX3wx2esT55t/dr+wbEHXguiyWl1muvuL3VnZdaWZI8q44sUTsLdXiI7WsHkzdOqUjcJmzoQ1a9R1Wo4fhwys+yCEENbA4lo6QB1/PHPmTMaPH0+1atU4deoU27ZtM3YuDQ4OTrZinrB+C44toNHSRjyMechLxV9iUcfsTRqU22xsIHEIf5b6dCTl4wOJY/g/+UTWZxFC5BkaRcZXERYWhru7O48fP86XHUmDg4NzZLhkRn195GuGbRsGQMsXWrK+23qc7UzboTEnJdZhfLwfZctqsbGBmBgyP4olqYsXoVIliIuDfv3g22+zWWDqIiMjcXFxAdShdDnRkTS98i3hM2hNYmJiuHLlCiVLljR26FMUhbi4OOzs7KRPQhZI/aUvtc9dosx8h1rk5RWRf/xw8gdjwjGmwRimNJtitb/0/v7q8hfx8XD9uvo4y0qXVqdKHz4cFi2CokXhiy9MFOlTNjY2vP/++8ZtaytfCGFd5N8KYTY///MzA7cMBOC9Wu9ZdcIBakNE1arq9pQpJigwIADjUJjp09U+HiZmb2/PvHnzmDdvXqojuiy9fCHM5fz583h5eRnnqFi6dKmxP6ElmThxItWqVUuxz9PTE41Gw4YNGxg9ejRDhw7NlXgk6RC5TlEUlv+1nD4b+2BQDPSv3p+5r8y16oQj0ZdfqlNr/PADHDtmggInT1ZnLdXroUsX9bqNEMJkpkyZQv369SlYsCAFMzEh35gxYxg6dKhxQslu3bpx4cKFnArTZM6dO8ekSZP49ttvuXXrFm3btmXEiBEsW7aMy5cv5/j5JekQuW7YtmH03tCbOH0c7cu259sO36LV5I2PYqNG0KqVur1rlwkK1GjUkSze3vDff9C3r0k7liqKQmhoKKGhoTkyfXZOly9EdsXFxfHaa68xYMCADL8mODiYLVu20KdPH+M+R0fHNBcktRSXLl0CoFOnTnh5eWFvb0/hwoVp3bo1CxYsyPHz542/9MJqfLTtI745+o26/dJHrHltTZ5JOBI1aaLer15togK9vGDZMrXDyKpVsHeviQpWpykvWrQoRYsWJSoqymTl5lb5wnoYDAamT59O6dKlsbe3x8/PjylPrkNevXoVjUbDmjVrjEuu165dmwsXLnDs2DFq1aqFi4sLbdu2JTQ01KRxTZo0iY8++sg4XX9GrFmzhqpVq1KsWDHjvmcvryRe1vjxxx/x9/fH3d2dN99803g55rvvvsPHxyfFuiWdOnXinXfeee65b9y4Qffu3fHw8MDZ2ZlatWpx5MgR4/PTpk3D09MTV1dX+vXrR0yS1tGJEycaJ9JMnGQuUYcOHVi1alWG6yCr8tZfe2Gx4vXxDPltCLOPzAZgVP1RfNX6KxxtM7oWvPVo3169P30akswCnj0tW0K3bur27t0mKlTkBYqiEBkXaZZbZlqvxowZw7Rp0xg3bhxnz55l5cqVKdbYmjBhAmPHjuXkyZPY2NjQo0cPRo4cyZw5cwgKCuLixYuMHz/eePyKFStwcXFJ85beAqBZERQURK0MzJ9z6dIlNmzYwJYtW9iyZQv79u1j2rRpALz++uvcv3+fPXv2GI9/8OAB27Zto2fPnqmWFxERQePGjbl58yabNm3ir7/+YuTIkcbEZc2aNUycOJEvvviC48eP4+3tzfz5842vHzFiBEuWLAHg1q1byaaeqFOnDjdu3ODq1auZro/MkO7kIscZFAN9NvZh5T/qZF+fNPiEKc1N0dPSMpUqBYULw717MG2a2i3DJBo3hp9+gu3bTViosHZR8VG4TjPPQpURYyIyNLw9PDycOXPmMHfuXHr37g1AqVKlaNCgQbLjRowYQesnE94MGzaM7t27ExgYSP369QHo168fS5cuNR7fsWNH6tatm+a5k7ZGmMq1a9cylHQYDAaWLl1q7Pfx9ttvExgYyJQpUyhYsCBt27Zl5cqVNG/eHIC1a9dSuHBhmjZtmmp5K1euJDQ0lGPHjuHh4QFA6dKljc/Pnj2bfv360a9fPwA+//xzdu3aZWztcHFxMbbGPLusiI+Pj/G9+Wdr6F3apKVD5ChFUejwcwdjwrGw3UI+b/a5maPKWY6O8PmTtzh7tgn7frZvr85CduwY/PqriQoVIuedO3eO2NhY45fr81SpUsW4ndgKUrly5WT77t69a3zs6upK6dKl07w5OqqtqYMGDUrWApId0dHRKeaqSI2/v3+ylcu9vb2Txd+zZ0/WrVtHbGwsoLbcvPnmm8+dr+bUqVNUr17dmHA869y5cymSsNSWD0lNYj3l9GVQaekQOSbBkMDgrYP57b/fAFjRZQU9Kvcwc1S5o39/+OADiIiAEyfgyT9q2ePlBaNGqeNx338fmjaFTPS2F3mTk60T4aPDzTK5lZOtU4aOS/xCS4+tra1xO/F9PLsvaR+IFStWMHDgwDTL/P3332nYsCGfffYZI0aMyFAc6SlcuDAPHz5M97iksUPK+Dt06ICiKGzdupXatWsTFBTErFmznlteRusxKx48eABAkSJFcuwcIEmHyCEJhgS6r+vO2rNrAfi+w/f5JuEAdc6OJk1gxw7YutVESQfAuHHqaJb//oMFC9Rp0kW+ptFocLZzxhZbi51Rs0yZMjg6OhIYGEj//v1NVm5mLq8kdmg2herVq3P27Nlsl+Pg4ECXLl1YsWIFFy9epFy5ctSoUeO5x1epUoUffviBBw8epNraUaFCBY4cOUKvXr2M+w4fPpyhWE6fPo2trW2mOtRmhSQdwuRCI0P5cPuHrD27Fq1Gy7LOy3irylvmDivX9eunJh0//qhebjHJDN/29mqi0bevOinI4MHg7m6CgoXIOQ4ODowaNYqRI0diZ2dH/fr1CQ0N5cyZM8b+B1nh6uqa7PJFVgQHB3P//n2uX7+OXq/n1KlTgNpX4nmXYVq3bk3//v3R6/Xosrk8Qc+ePWnfvj1nzpzhrbfS/jvZvXt3vvjiCzp37szUqVPx9vbmzz//xMfHh3r16jFs2DD69OlDrVq1qF+/PitWrODMmTO88MIL6cYRFBRkHDmUkyTpECYVEh5C+bnlCY9Th4Ut6bQkXyYcAG3bgpMT3LgBCxeqV0RM4q234H//g3//ha++gkmTslyUjY2NsWNfTk2DnpPlC+sxbtw4bGxsGD9+PCEhIXh7ezNo0CBzh8X48eNZtmyZ8XH16tUB2LNnD00Sx78/o23bttjY2LBr1y5jx9esatasGR4eHpw/f54ePdJuDbazs2PHjh0MHz6cV155hYSEBCpWrMi8efMAdYKyS5cuMXLkSGJiYujatSvvvfce27dvTzeOVatWMXHixGy9lwxRhPL48WMFUB4/fmzuUHKdXq9Xrly5ouj1+myXlaBPULqv7a4wEaXgtILKT3/9ZIIILV9addinj6Kos3kpyogRipKQYKKT/vKLWqiLi6LcvWuiQs3DlJ/B/CA6Olo5e/asEh0dbdxnMBiUmJgYxWAwmDEy65WV+ps7d67SqlWrHIwq9/z2229KhQoVlPj4+Ocek9rnLlFmvkNl9IowifDYcN5e/zY/n/4ZrUbL2jfW0rNK6mPN85OFC9UOpQAzZ6pXREyia1eoWVPtqfpk3L8QIvcMHDiQRo0aGSf7smaRkZEsWbIkV1ojJekQ2Xb4xmEKTS9kTDhWdV1Fs5LNzB2WRbC3hzlzYO5c9fEnn6h9PLJNo3m6qty8eeo1nCxQFIXIyEgiIzM30ZOllC+EudjY2PDpp59mu0+JJXjttdfS7ZBrKpJ0iGy59OASHX/uSLwhHkcbR1Z1XcXrlV43d1gWZ9Ag6NRJXbdt8GC4edMEhbZqBS+/DLGx8PHHEB+f6SKioqKM8xbk1DToOVm+EMK6SNIhsuxxzGMaLW1EaFQo1byqcWv4LUk4nkOng7VrwdcXwsPVXCE6OpuFajRqp1JQ12SRWUqFEBZOkg6RJWGxYbRb2Y6Q8BAcbBxY+/pa3B1k6GZabGzg99/B1RWCg8EkS0IMHAivvqpuz50LCQkmKFQIIXKGJB0i0+L0cQzYPIA/rv8BwKquqyjlUcrMUVmHSpXgySKP7N9vggK1WnU524IF4eFDGD3aBIUKIUTOkKRDZEq8Pp4OP3dg9Rl13fbN3TfTqXwnM0dlXRLXiTp/3kQF2tqq83aAOjxm7VoTFSyEEKYlSYfIsHh9PL029GLHpR042jiyvPNy2pdtb+6wrE6ZMur9hQsmLPTddyFx6mMZQiuEsFCSdIgMCY8Np+uarqw6vQobrQ0/dfmJt6u+be6wrFLVqmof0L//hpMnTVhw4myCJ0+aaHiMEEKYliQdIl0JhgTeWv8Wmy9sBmBRx0V0qdDFzFFZL19f6N5d3Z4xw4QFlyypriynKNCzJ8TFpfsSnU7Ha6+9xmuvvZbtNSTMUb4QueH8+fN4eXllayKwJk2a8OGHHxofR0VF0bVrV9zc3NBoNDx69IiXXnqJdevWmSBiyyVJh0jX+D3j2XR+E7ZaW9a9sY5eVXul/yKRpjffVO/37IGQEBMWPG2auuDLvn3w9dfpHu7g4MAvv/zCL7/8goODgwkDyZ3yhcioBw8eMHToUMqVK4ejoyN+fn588MEHPH78ON3XjhkzhqFDh5p0IrBly5YRFBTEwYMHuXXrFu7u7owdO5bRo0djMBhMdh5LI0mHSFNIeAjT/5gOwML2C6WFw0RatAB/f7hzB+rVg8hIExXcoIG6CBzA9OkmmAxEiLwhJCSEkJAQZs6cyenTp1m6dCnbtm1Ld5Xb4OBgtmzZQp8+fUwaz6VLl6hQoQIvvvgiXl5eaDQa2rZtS3h4OL///rtJz2VJJOkQzxWTEEP3dd3RK3oqFK5A76q9zR1SnuHoCIkLPwYHw/HjJiy8Rw9wcYHQUFi0yIQFC5F1BoOB6dOnU7p0aezt7fHz82PKk6n8r169ikajYc2aNcbl1WvXrs2FCxc4duwYtWrVwsXFhbZt2xIaGpql87/44ousW7eODh06UKpUKZo1a8aUKVPYvHkzCWnMb7NmzRqqVq1KsWLFku3/448/aNKkCU5OThQsWJDWrVvz8OFDQF3LpFevXri4uODt7c2Xzyy61KRJE7788kv279+PRqMxrmar0+l45ZVXWLVqVZbeozWQpEOkSm/QU39xffZf24+zrTOrX1uNTivX5E2pbFl44w11e8UKExbs6goBAer20KGQZNnuZ0VGRqLRaNBoNESarLkl98oXaheeyEjz3DKznM6YMWOYNm0a48aN4+zZs6xcuRJPT89kx0yYMIGxY8dy8uRJbGxs6NGjByNHjmTOnDkEBQVx8eJFxo8fbzx+xYoVxmn2n3cLSmMWvsePH+Pm5pbmQmdBQUHUShzn/sSpU6do3rw5FStW5NChQxw4cIAOHTqg1+sB+Pjjj9m3bx8bN25kx44d7N27l5NJeo3/+uuvvPvuu9SrV49bt27x66+/Gp+rU6dOmjFbvSyvhZuHyNL2KZcVn31otsJEFCaiLDi2wEzRWYfsLM0eFKSuUG9vryi3b5swqLg4RXn7bbXwokUVJZXlqBVFUSIiIhRAAZSIiAgTBpDx8mVp+8x5donxiAj1x2yOW0Y/MmFhYYq9vb3y/fffp/r8lStXFED54YcfjPt+/vlnBVACAwON+6ZOnaqUK1cuWbn//fdfmreoqKhUzxkaGqr4+fkpn3zySZpL21etWlX57LPPku3r3r27Ur9+/VTLDQ8PV+zs7JQ1a9YY992/f19xdHRUhg0bZtw3bNgwpXHjxilev3HjRkWr1Vrc74OplrbP+XVshdU5dvMYw3cMB2Bsw7EMqjXIzBHlXfXrQ+3acOwYNG6sTpNesqQJCra1hR9+gG3b4O5dGDVKXe5WCDM4d+4csbGxNG/ePM3jqlSpYtxObAWpXLlysn137941PnZ1dc1S586wsDDatWtHxYoVmZg41Pw5oqOjU3SCPnXqFK+/nvo6U5cuXSIuLi7Zqq0eHh6UK1cuQ7E5OjpiMBiIjY3F0dExQ6+xJnJ5RSRz9dFVGi1thF7R06FsBz5r+pm5Q8rTNBqYPRs8PNQZSnuZcmCQnZ1aOMD8+fDggQkLF5bCyQnCwxXu348lPFwhIoJcuzk5ZSzGjH552traGrc1Gk2q+5KO7MjK5ZXw8HDatGmDq6sr69evT1Z+agoXLmzsq5HZ95MVDx48wNnZOU8mHADS0iGSCdgeQExCDP4F/Pmpy0/GX3yRc15+GU6cgBdegAMH1CG0Pj4mKrx7d5gwAS5ehC++gJkzTVSwsBQaDTg7q41bdnbqY0tTpkwZHB0dCQwMpH///iYrt2PHjslaFFKTtANoWFgYrVu3xt7enk2bNmVoGHf16tU5e/Zssn1VqlQhMDCQSZMmpTi+VKlS2NracuTIEfz8/AB4+PAhFy5coHHjxume7/Tp01SvXj3d46yVJB3C6Ke/f2L9v+sBWP3aatzs3cwcUf7h769Oj37hAgwZAsuXqwNQsk2jURONzp3VdVm8vWH4cBMULETGOTg4MGrUKEaOHImdnR3169cnNDSUM2fOpDtkNS2ZubwSFhZGq1atiIqK4qeffiIsLIywsDBAbc14ntatW9O/f3/0er1xgrsxY8ZQuXJl3n//fQYNGoSdnR179uzh9ddfp3DhwvTr14+PP/6YQoUKUbRoUT799FO02oxdWAgKCqJVq1YZOtYayeUVAcD5e+cZ8tsQAMY1GkedYnXMHFH+M3u2+t/q+vVQrhzcvm2igjt1gpEj1e0RI9SMRohcNm7cOIYPH8748eOpUKEC3bp1S9Y/I6edPHmSI0eO8M8//1C6dGm8vb2Nt+vXrz/3dW3btsXGxoZdu3YZ95UtW5YdO3bw119/UadOHerVq8fGjRuNo2BmzJhBw4YN6dChAy1atKBBgwbUrFkz3Rhv3rzJwYMH6du3b/bfsIXSKEpmBj3lTWFhYbi7uxuHT+UnBoOBPy/8Sfut7bkdcZvaPrU52O8gNlppBMsog8FAcHAwfn5+Gf5v5nl27oTEf3IqVICFC6FRI5MECe3bqz1VnZzUiUEqVCAmJoauXbsCsG7dOpPPGpqR8k1Zf/lBTEwMV65coWTJksb6VBSFuLg47Ozs5JJoFqRXf/PmzWPTpk1sT5xcJ4eMGjWKhw8f8t133+XoebIitc9dosx8h8o3Sz6nKAqj/hjF7Yjb+Lj6sPaNtZJwmFHLluqkYV27wrlz0LQpHDoEdbLb8KTVwi+/QI0a6jWcmTNh0SIcHBzYunWrSWJPTU6XL0RuGDhwII8ePSI8PNykU6E/q2jRogQkzrGTR8m/FfncgesHCLwRiAYNP776I37ufuYOKd9r1Qr+/RfatlUbKIYMUe+zzdkZ5s5VtxcvhlOnTFCoEHmfjY0Nn376aY4mHADDhw9PMWFaXiNJRz4WmxDLe1vfA6Bf9X40K9nMzBGJRMWKqTOYu7ioc3hs3myigps1gyc96unSxYSLvgghRPok6cjHZh+ezbl75yjsUJhJTVIO/RLm5e2t5gUAgwdDfLwJCtXp1P4c3t5w5QqRS5bg7OyMs7Nzjk2DnpPlCyGsiyQd+VRUfBQzD6lzNoyuNRovFy8zRyRS88UX6v3Nm7BggYkKLVIE3n9f3d64kaioKKKiokxUeEo5Xb4QwnpI0pFPzTk8h3tR9/Bx9aFjyY7mDkc8R7Fi6ihXUEe2mMyTESUkGQYohBA5TZKOfOj64+tM2qdeTvm04afYatOeBliY16uvqvc7dkBMjIkKrVBBXY9FCCFykSQd+dDMgzOJ1cdSy6cW/aplfTZAkTvq1VOviMTFmbi144svoEePp4//+ceEhQshREqSdOQzN8Nu8u2JbwH4vOnn2OqklcPSaTTqCrSgzmRuMlotfPPN08dJt4UQIgdI0pHPfHXoK2L1sTTwa0CrUnl3fv+85rMni/3u32+iUSyJ7O2fbq9cCVevmrBwIYRITqaezEduhd/iu5Pq9LpjGoxBo9Egs+Bbh3LlwNERoqPh7FmoWtU05Wq1WnXly7/+QvvoEYwdCz/9ZJrCk5b/ZFvkHN3kyeqQ6NyaBn3ixNw5jwnFxMQwfPhwVq1aRWxsLK1bt2b+/PkULVrU3KHlG/JXIB+ZdXgWEXER1PKpRZvSbcwdjsgErRZatFC3N2wwXbmOjo7s3buXvRs24AiwYoXarKLXm7b8vXtxdHQ0SZlCZNVHH33E5s2b+eWXX9i3bx8hISF0SZwMR+QKSTryieMhx5l9eDagjljRauRHb20S+3XMmgWXL+dA4YnDZCZMgLVrTXwCIdTF/aZPn07p0qWxt7fHz8+PKVOmcPXqVTQaDWvWrKFhw4Y4OjpSu3ZtLly4wLFjx6hVqxYuLi60bduW0NDQLJ378ePHLFq0iK+++opmzZpRs2ZNlixZwsGDBzl8+LCJ36l4HvnmySc+3f0p8YZ4Gvg1oFO5TuYOR2RBr15Qpgw8fqzmBybt2wHqeiyVKqnbs2ebaMEXIZ4aM2YM06ZNY9y4cZw9e5aVK1cmW2tkwoQJjB07lpMnT2JjY0OPHj0YOXIkc+bMISgoiIsXLzJ+/Hjj8StWrMDFxSXNW1BQEAAnTpwgPj6eFolNhkD58uXx8/Pj0KFDuVcJ+ZzFJh3z5s3D398fBwcH6taty9GjR5977Pfff0/Dhg0pWLAgBQsWpEWLFmken9/suryLHZd2YKO1YXHHxbL0tZUqUgT27oVCheDvv2H0aMhul5zIyEiKFClCkSJFiLS1Va/d2NjA4cMwfXq2Y05WvkyDnq+Fh4czZ84cpk+fTu/evSlVqhQNGjSgf//+xmNGjBhB69atqVChAsOGDePEiROMGzeO+vXrU716dfr168eePXuMx3fs2JFTp06leatVqxYAt2/fxs7OjgIFCiSLy9PTk9u3b+dKHQgLTTpWr15NQEAAEyZM4OTJk1StWpXWrVtz9+7dVI/fu3cv3bt3Z8+ePRw6dAhfX19atWrFzZs3czlyy/RJ4CcAvF/rfcoUKmPmaER2+PjA11+r2199pbZ4/P579lo97t27x71799QHpUvD1Knq9uefgwn+GCcrX+Rb586dIzY2lubNmz/3mCpVqhi3E1tAKleunGxf0u8BV1dXSpcuneZN+hJZFotMOr766iveffdd+vbtS8WKFVm4cCFOTk4sXrw41eNXrFjB+++/T7Vq1Shfvjw//PADBoOBwMDAXI7c8ly4f4FjIcfQoGFMwzHmDkeYQI8eT6fU2LgRXnkF6tdXL7uYREAAVK6srkArs5YKE8nIl7+t7dN5gxJbZJ/dZ0hy2S8zl1e8vLyIi4vj0aNHyc55584dvLxk7ancYnFDZuPi4jhx4gRjxjz9gtRqtbRo0SLD192ioqKIj4/Hw8Mj1edjY2OJjY01Pg4LCwPUTk6GPHYde9ahWQC0K9OOok5FU7y/xPec1953bjJHHb7/PpQvD2vWaPj5Zzh2TMPUqQpffJG56y1JY072HhYsQNOwIZrlyzEMGgR162YpzueW/8wx8hnMOIPBgKIoxtuzcm0YfCbPk9jqsGvXrmSXVNSiFON90u209gF06NCBOnXqpHneYsWKoSgKNWrUwNbWll27dtH1ydpD58+fJzg4mHr16qWIRSSX+HNI7Xc1M7+7Fpd03Lt3D71en6xzEajNav/++2+Gyhg1ahQ+Pj7JOgwlNXXqVCZNSrmU+/Xr13F1dc180BYqKj6Kn/5W51x4s+SbBAcHpzhGURQePnyIRqORvh5ZZK46LF0aPvkEatVyZOBAT775RqF79xu4u2f8D0DS1V+vX7+Ok5OT+qBYMQp37IjLxo1EzprF/Sz273hu+UnIZzBz9Ho9er2e+Pj4ZHOfaHI5adPHxWXqeK1Wy/Dhwxk1ahRarZZ69epx7949zp49S9OmTQGIj48n7km58U+uGcbFxRn3JSQkGPcBxhEw6YmLi8PR0ZE+ffoQEBCAq6srbm5uBAQE8NJLL1GjRg1j2SJ18fHx6PV6bt26hU6nS/ZceHh4hsuxuKQju6ZNm8aqVavYu3cvDg4OqR4zZswYAgICjI/DwsLw9fXF19cXNze33Ao1xy04voCI+AhKe5SmW51uqQ6TTfyvydfXVyZvyiJz12G/fjBnjsLZs1q2bCnO6NEZnx8qaedOX19fnJ2dnz45eDBs3IjL+vU4f/65muVkUprlP2Hu+rM2MTExXL16FVtbW+zs7Iz74yZMQJfkcU7TpX9IChMnTsTe3p7JkycTEhKCt7c3AwcONL6PpO8p8bKKnZ2dcZ+NjY1xX1bMmTOH4cOH0717d+PkYPPmzTOWl9Vy8wODwYBOp8Pb2zvFd2vi1YIMUSxMbGysotPplPXr1yfb36tXL6Vjx45pvnbGjBmKu7u7cuzYsUyd8/HjxwqgPH78OLPhWqzb4beVgtMKKkxEmXN4znOP0+v1ypUrVxS9Xp+L0eUtllCHM2YoitrerSidOytKQkLGXhcREaEACqBEREQkf1KvV5RKldRCq1VTlHv3Mh1XmuUbT2P++rMm0dHRytmzZ5Xo6GjjPoPBoMTExCgGg8GMkVkvqb/0pfa5S5SZ71CL+7fCzs6OmjVrJusEmtgpNOl1t2dNnz6dyZMns23bNuMQqfzs450f8zDmIdW9qvN+7ffNHY7IYQEB8Omn6vaGDfDzzxl7nVarpVatWtSqVStlK4NWq/ZUdXeHU6fg9dczfR0/zfKFEPmORV5eCQgIoHfv3tSqVYs6deowe/ZsIiMj6du3LwC9evWiWLFiTH0ytO9///sf48ePZ+XKlfj7+xvHXCf2Xs5vLj64aOzL8W37b7HRWuSPWZiQVquOcI2IgDlzYOhQaNUK0ltSwtHRkWPHjj3/gFKl1MSjSRPYswd27IDWrTMcV7rlCyHyFYv816Nbt27MnDmT8ePHU61aNU6dOsW2bduMnUuDg4O5deuW8fgFCxYQFxfHa6+9hre3t/E2c+ZMc70Fs/rmyDcoKLQt3ZbaxWqbOxyRi8aMAU9PePRI3TaJxo3V6VAB3noLbtwwUcFCiPxGoygyPigsLAx3d3ceP35s9R1J70TcofQ3pYmIi2D7W9vTXb7eYDAQHByMn5+fNH9nkaXV4W+/Qbt26vatW2CSKQjCw6FRI/UyS/XqcPAgPKejdmZZWv1ZupiYGK5cuULJkiWNHfoURSEuLg47OzsZAZQFUn/pS+1zlygz36HyG57HzD06l4i4CGp416DlCy3NHY4wg8aN1SnTAaZMSfvYqKgo/P398ff3Tza8NQVXV/jlF/DwgD//zPCCcBkuXwiRL0jSkYfE6eNYcHwBAGMajJGMPZ9ydoYF6seAb7+Fv/56/rGKonDt2jWuXbuW/qRIpUvDsGHq9qefZmju9UyVL4TI8yTpyEP2X9vP/ej7FHUuSufync0djjCjV1+FmjXVvOCDD0xY8Mcfq51GgoOhQwfIzPh8IUS+J0lHHrL4T3VtmlfLvyojVvI5rRbmzVO39+8Hk6196OioXrPRaGD7dnXIjBBCZJAkHXnEw+iHrDq9CoD+Nfqnc7TID+rWhapV1e0TJ0xYcL9+TycCmTcPjh41YeFCiLxMko48YtXpVSgo+Bfwp5aPTI4mVImrgi9alOl5vdL22mvqfB1RUdCsGRw/bsLChRB5lbTB5wHx+ni+OvwVAINrDzZzNMKSjB4Nq1fDpk0QGAjPWQMx83Q6dTRL5cpw7Rq88QacPWuyYbQi8yYHTUan0+VaB/KJTSbmynly2pQpU9i6dSunTp3Czs6OR48emTukPE1aOvKAn/7+iYsPLlLAoQADaw40dzjCglSqBF26qNuzZ6ds7dBoNFSsWJGKFStm/svK1RUOH1anPb1yBVJZiTZb5QuRCxInlhwwYIC5Q8kXJOmwcgbFwLQ/pgHwSYNPcLV3NXNEwtJ8/DHY2MDWrfDll8mfc3Jy4syZM5w5cybVZefT5eWlNqcATJigzkxmyvJFnmIwGJg+fTqlS5c2Lks/ZcoUrl69ikajYc2aNTRs2BBHR0dq167NhQsXOHbsGLVq1cLFxYW2bdsSGhpq0pgmTZrERx99RKVKlUxarkidJB1W7s9bf3Lh/gVc7FwYVGuQucMRFqhmTZg8Wd3++GMYMgQSEkx4gvfff9p5ZMAAtdVDiFSMGTOGadOmMW7cOM6ePcvKlSuNy1sATJgwgbFjx3Ly5ElsbGzo0aMHI0eOZM6cOQQFBXHx4kXGjx9vPH7FihXGNbaedwsKCjLHWxXPIX06rNyWC1sAaFWqlbRyiOcaNUodRjtqlDrgpEYNeOcdExVubw8HDqjDZf79F9q3V2cks5E/L+Kp8PBw5syZw9y5c+nduzcApUqVokGDBly9ehWAESNG0PrJgoLDhg2je/fuBAYGUr9+fQD69evH0qVLjWV27NiRunXrpnneYsWKmf7NiCyTvwpWLCYhhoUnFgLQuVxn8wYjLJpGAyNHqo0QCxfCtGnQuzfExkZRu7a6KOCxY8eyfgnEzU3tqVqunNqhtEIFOHCAKFdX05QvrN65c+eIjY2lefPmzz2mSpUqxu3EFpDKia1oT/bdvXvX+NjV1RVX14z9szVo0CB++ukn4+OIiIgMxy5MRy6vWLFN5zdxO+I23i7evPnim+YOR1iBDz5QE5D//lMXjNXrFc6ePcvZs2ezP025j48677pOBxcvwuefoxgMpitfWDVHR8d0j7G1tTVuJ3Y8fnafwWAwPs7M5ZXPPvuMU6dOGW/CPKSlw4p9dUgdJtu7am9sdbbpHC2E2gDxww8waBCsWgUVK5r4BD16qIu/dO4Mc+eqM5gKAZQpUwZHR0cCAwPp3980Exhm5vJK0aJFKVq0qEnOK7JOkg4r9e+9fzly8wg6jY4P6ppycQ2R173zDuj1ap/PL77IgRN07Khey5k+HWbOzIETCGvk4ODAqFGjGDlyJHZ2dtSvX5/Q0FDOnDmT5iWXtGTm8srzBAcHc//+fa5fv45erze2gpQuXRoXF5dslS1SkqTDSiWus9K6dGu8Xb3NHI2wNv37qzOZ79mTA4VrNGqnkQMH4ODBHDiBSM24huOws7Oz6PlQxo0bh42NDePHjyckJARvb28GDTLvqLvx48ezbNky4+Pq1asDsGfPHpo0aWKmqPIujSIXWgkLC8Pd3Z3Hjx/j5uZm7nDSdT/qPt5fehNviGdDtw10Kt8py2UZDAaCg4Px8/NDq5UuPllhrXV44waULRtJdLT631xERATOzs6mO8GuXUS2bEni/4rPK99a689cYmJiuHLlCiVLlsThyQywiqIQFxdn8UmHpZL6S19qn7tEmfkOld9wK/TH9T+IN8RTrlA5OpbraO5whJUqXjzVSURNp3lzdX2WRHfu5ODJhBDWQJIOK3Qg+AAAjUo0kqxcZMtLL2mAEkAJvv/exJ8ljQbN0qWU0GopAWiaNoXoaNOeQwhhVSTpsEL7r+0HoIFfAzNHIqxdjRpOtG9/FbjKRx858c8/pi3fycuLq0eOcNXREafgYHWcrlzRFSLfkqTDytwMu8mRm0fQoKGpf1NzhyOsnFarrkBbo4b6eO/eHDhJrVqQ2FHv119TrM8ihMg/JOmwMlv/2wpAnWJ18HX3NXM0Ii/QaKBRI3U7IACSTNpoOq+/Dh99pG4PGwbnz+fASYQQlk6SDiuz6M9FALxa/lUzRyLygujoaGrXrs3evbVp0SKahAR1evQFC0xzFSSx/Nq1axP93ntQtChcuqTOUta/v1xqESKfkXk6LMjEiWk/f40gjmqOolVsCN3VB6RLh8gmg8HA8ePHAQgLM/D++2pLx/vvw//+B4sXQ7Nmpinf4OMDJ09Cnz6waxcsWgQvvQR9+5rgnQghrIG0dFiRE6iLu1WmBy54pnO0EJmj1cKcOeoM5g4OcO2aOqv5kwVATaNYMdi5U50OFeDdd9H06iUtHkLkE5J0WAk98VxmFwCV6WnmaERe5eEB69dDaCiULatOrdGgASQkmPhEX30FbdoAoFm5kqL9+0N4uIlPIoSwNJJ0WIlLbCdScxcnpQj+yKgVkbNcXGDjRnX75k0YPNjEJ3B2ht9/h9mzAXDavRtN5crq9Rxp9RAiz5I+HVbiT9S1VqrwFjpkRVmR88qXV1eiffNNdWXazp2hbVsTn2TYMAyVKqF0747u+nXo108dw/vrr+r1HpFhkyfr0OnU0Ui5Ib0+aJbmwYMHTJgwgR07dhAcHEyRIkXo3LkzkydPtorlL/IK+a22AgnEch71385q9DFvMCJf6dYN2rcHg0Ed1RIXlwMnadaMG/v2ofTpoz7euBFeew0iI3PgZCK/CgkJISQkhJkzZ3L69GmWLl3Ktm3b6Nevn7lDy1ekpcNSJZml6USxX1HKGnCMd6PogfvAk+cm7k35Omv790OYXeHChdN8fsUK8PZW+3l88knmV6tPr3wAxckJZdEiNDVqwAcfqB1LmjVTV6nV6TJ3QmGxDAYDM2fO5LvvvuP69et4enoycOBAevbsScmSJVm9ejXffPMNx48f58UXX2TFihU8fvyY9957j3///ZeGDRuyfPlyihQpkulzv/jii6xbt874uFSpUkyZMoW33nqLBJN3WhLPIy0dFk7BwGHfXwB46frraJC1VoTpODs7ExoaSmho6HNXmHVzUxMPgC+/hG++yXi3i4yUn8zQobBvnzp85uhRGDVKbWYRecKYMWOYNm0a48aN4+zZs6xcuRJPz6cj8SZMmMDYsWM5efIkNjY29OjRg5EjRzJnzhyCgoK4ePEi48ePNx6/YsUKXFxc0rwFBQU9N57EVVFtbOT/79wiNW3hNrkF8sjxNlq9LXE3arKXq8bnJia2eCS1d6L6XJOJuRGeyCc6d4YPP1T7fX7wAdy/n4ONao0aqcnGpElqlhMUBLt3q51PhdUKDw9nzpw5zJ07l969ewNqa0ODBg24+mRc9ogRI2j9ZGXiYcOG0b17dwIDA6lfvz4A/fr1Y+nSpcYyO3bsSN26ddM8b7FixVLdf+/ePSZPnsyAxOHbIldI0mHhrr7wKwCF7tXARu9o5mgEpPyy1WjUoaYPHqTeApBXrnjNnKm+z/Hj1XzgxAl1SRUPjxw42bhxcP26Oprl6FF44QV1QrHKlXPgZCI3nDt3jtjYWJo3b/7cY6pUqWLcTmwBqZzkZ+7p6cndu3eNj11dXXF1dc10LGFhYbRr146KFSsyMa/8gloJubxiwSJtH/LI/QIAJa52MHM0Ii+Kjo6mSZMmNGnShOh0lp3X6dRcYOpUsLGBLVugcWNYuRIePsx++SlOtmgR/Pyz+vjuXahSRV08bu9eGVZrhRwd0/+nydb26cg8zZNhOM/uMyS53JaVyyvh4eG0adMGV1dX1q9fn6x8kfOkpcOCHS22AbQGXML8cY5K2US4d2+flC/aq96ldullYpOU+9Bo1GEJIl8yGAzs27fPuJ0Ro0dDixbq8NnTp6FnT7C1hUGDoGNHNS8oUCDr5Sfz5pvg7q5mOn/8oTavNG0KlSqpSUk6TevCcpQpUwZHR0cCAwPp37+/ScrM7OWVsLAwWrdujb29PZs2bcLBwcEkcYiMk6TDQuk1CfzprS4BXvxGKzNHI0RytWqpCcfs2bB5M5w5o3Yw/eYb9flXX1VbQEyibVv1dvcuTJigJhtnzsDLL8Py5WrWIyyeg4MDo0aNYuTIkdjZ2VG/fn1CQ0M5c+ZMmpdc0pKZyythYWG0atWKqKgofvrpJ8LCwggLCwMyNsJKmIYkHRbqtstFwh3uoU2wp3BoTXOHI0QKnp5qA8TUqerkosuWwbFjcPmyOuJ1/Hg1RzCZokXV5W8/+0ydPOToUXjrLfWk06eDnZ0JT2Z9xo3TY2eny7XJwbJi3Lhx2NjYMH78eEJCQvD29mbQoEG5cu6TJ09y5MgRAEqXLp3sucuXL+Pj45MrceR3GkWRi6NhYWG4u7sbh0+ZS2J/JgUDSx9XJ7jA3xS+W4tKZ0wzB3WTJktT7NNotHjUe5UHtg9QNIqMesmAlB1JDXh4BPPggR+Kkr1uUrndpy0yMhIXFxcAIiIiMjasNR0LFqir1AJ8/HEkM2akXb7BYCA4OBg/Pz+0GZ2FNCFBzWi++EJ9XKaMOqdHPviPNSYmhitXrlCyZEnj5QFFUYiLi8POzs7YF0JknNRf+lL73CXKzHeotHRYoGsEEVzgb0A6kIokspqR5HImM2iQOvBk6lSYMePp/tOn1csyJpnry8YGpkwBLy91DO9//0GRItCypXrSqlVNcBIhhKlJ0mFhFBT2MxmAGiHtcIn0M1nZqXU81WqhkuLDmWu2GBSNcZJTGUVmHmnW+94mKY9PrXNwZgpNMq/5lCltsLN7khE0SXmuVItOpWVMo4HPP4erV2H16qdze730Ejg5QbVq0KULDB+eoVOkbehQtXVj5Ei4cQN27lRP8Npr6gnbt4dy5UxwIiGEKUjSYWFOs4ormkA0Bi31r3Xnb+LNHZKwYBOfSUSSTh6XmmcvscWhx9Y2lUsaSabhz/D5n0lUyg6AoZ10zH3bHoNei9Ymnqgo9SrIwYNw6ZKanCSOdMmy7t3V27//qs0s+/bB2rXqbcQItQXE2xt8fODjj9XRL9KELoRZSNJhQWIJYxcjAagf3B2PmGKQzpeIsFIZ/FI3/Wn7pNj38svqglcHD6Y8PrV+QJlRwFPP2B2jATDo53D/RiF+m92Oq6dKsmCB2v/DyUmDk5MvBQtqcHNTp113dcW47eYGJUpAr15qS8lzlS+vzly6Z4/a4rFtG/z1l7poTGgo/P23uq9mTejbF6pXV1tDZDVbIXKNJB05yNiqncEvmP0vfEtYiRu4x3jS8Jp5hgHuvboXgImZ/FK05g6olngpKb0WC4uUzmdGCxQBenVcy8WKddi1ayB375YiKkpDVJSOe/fSLn7U+MfM+Nyd1q3Bz+85jRVaLTRvrt6mTVM7l9y8qTarbNigrmB74oR6A7WZpW5dqF1bnXysaVOr6YwqYwBEbjLV502SjlyS3pfIdd/tXC6xCoBi/73GQcOdXIjqifv34FocJJ27KbNJR2or3qbmSRN8Tn7RW2ISIZ7SaKBMmaOULn2U6Gg34qo1xyGsCHfjYoiNsn9ys1PvI+2JjXTg3wPleXynAAMHqmUULw4NGkD9+lC6tDoVe+LN3T1JZ1VfX/X20kvqfB5XrqjzfJw6pV6GefQItm9Xb4n8/NR+IfXqqdOvlyunJiQWckkmcQbNqKioDM3yKYQpxD3p/6XLZk9wGTJLzg2ZTdrSkVbS8ajAv/xVbTpoFLxvNqXshV4miyE9Wi1UqmTHmTNxubOYp78/AE367AVypoUky0lHFi95aLQKHpXieXDGFsWQ/IvJ0lssDIZ4zpyZC0ClSkPQarM+JXRql2ISEgysWXMGgDfeqISNTcpLGZrGTfGI9zAO205NfKwNR3+ty+M/W/Lnn+qI2efRaNQGDA8PKFRI7cpRrNjTm4+PesnG2T4Blxv/4nz6CC7njmG/fyeaK5dTL9TGRr18U7KkevP3f7pdooSa6eRiUnLr1i0ePXpE0aJFcXpyzSk+Ph5bW1sZ8pkFiqJI/aXBYDAQEhKCra0tfn5+KepIhsxameASW0CjUPROXcpceNvc4eSsJ6tJJn7BP9sRMqMmksbr9jbJ8OiLjEoredAClbDjDHHkRt5mSopi4MGDv43bpmYwKPz33wPjdlbZ2idQv/sf0P0PWkTbcvPfYgT/48fNs8UJf+BKdJgj0eGOxEXZoyjqWjAPH6pXVZ7PBnjxya0fWi04uyi42MXiTCQuSjjO8Y9wibyDc0IEzqcjcTkdoT7HI5w5gAvb1Mc2sTh72OPs446rtwsVioVhW9DlaeeUxHsPD3U4b6FCWa4LAC8vLwDj4meKoqDX69HpdPKlmQVSf+nTarWpJhyZJUmHmYW5XeKhxxlQNJS8/Boa5AOfmmc7QDZJ8+irsHdpToUiTG3/PvCoBA/OQAYSHzugZJMmlKx+NcVz+ngdMREORIc7EvXYkajHzoTfc6Wacztu3lS7d9y6BRER6i0yEmJi1NcaDBAeoSEcB8AByERikADcfXI7BUW4S1t+x4vbFOImhbhPIe5TmHsU4j6eNg/wcIkDFxdwdlZvLi5qMvLii+oiNjVrPrf1RKPR4O3tTdGiRYmPj8dgMHDr1i28vb0zPsGaMJL6S5+dnZ1J6kaSDjOKt4ngXMVvASh0ryoOMdbRgU0IS6Wz1eNcMBLngpHPPHMMf8A/ldcY9BriY+yIi7ElLtpO3Y62Iy7alldLvU1kpJqcJCYpKe7D9EQ+iicyTE/EYz2hYfaExhRlOWkspJgAhR7do8Kjc5TnXwpzDxfUVhTn9bdwnvwVzk7g7F8E5yJOOBdywLmoM86lvXGu/ALOvh5oi3mjc3NDp9NhMBjQ6XQ4ODjIl2YWSP3lHotNOubNm8eMGTO4ffs2VatW5ZtvvqFOnTrPPf6XX35h3LhxXL16lTJlyvC///2PV155JRcjzpwEXTT/lVtOjGMounhHyuRiPw5LkOoKucKqpfYz1etjgQMABAW9hU5nb3wuW8Nxs9L/5jmX3LQ6BXvnWOydY1M81zX1lzxD9+SmSkiAHTvgzz/h/n31du/e0+379xUePtRwn8IcoCEHaJh6sVHA2dSfciWM5uymrncwrvZxONrGY6dEUMAZXGzjcLaLf3qzT8CpsBOOxQuhcbAH+yzcChdWW2OEyCaLTDpWr15NQEAACxcupG7dusyePZvWrVtz/vx5ihYtmuL4gwcP0r17d6ZOnUr79u1ZuXIlnTt35uTJk7z44otmeAdpe+x+gX+qzEZvEw1AxTPvYx9X0MxRCSFMwcYGXnlFvaVOQ1QUXLgA587B+fPqIJrEFhW19cRA5P1otQUlSkNkjI7IWBsiE9Q1L8JxYwOd2XAr43FpMOBEFB48oAihSW43KUIontyhODfw5Tq+XMeFZ1qLChdWRwJ5eqqL7yXeXFzUN21r+/z7tJ5L7176WOQpFpl0fPXVV7z77rv07dsXgIULF7J161YWL17M6NGjUxw/Z84c2rRpw8cffwzA5MmT2blzJ3PnzmXhwoW5GvuzYnjEv17buKm7QbxtOBEuwdwvcgoArd6Osuf74PHQ8hIjISxNZlvHUrSkZKF1ZGIOdEpOxlu9FQAK7N2bdgdpQFEgKt6Wc/eKsP0fb/5zqkZkjJaIaC1h4Qbi9A5Exj5JUJ7cYuLVP/MKWiJxIRIXrpP+8goFNI8oxAN0JKBTEtDd06s31JsWg3H7eTctMeiIzMBxaZSlMaDTqiPtdDrQ6RR0Og06rYLOwRadu4t6b69DZ2eD1t72yWMbChZQaF7+pvqGNJqnt6SPn3B9+FDtU5P0uGePNcfjl15Sh1zlERaXdMTFxXHixAnGjBlj3KfVamnRogWHDh1K9TWHDh0iICAg2b7WrVuzYcOGVI+PjY0lNvZpU+rjx48BePToEQYTjhuNjYVHXGJjyf8lfyIGCj6oTLkLvbHVO2Eg2mTnzIr4+AQMhvjcGTKbR1lrHRoMsUm2o9FoTPsG0ip/9+5ugPplUr68Lf/+WzGd+svc70li+dm22zTFpK9bJk6lB9sb4KV+SWk1CpV94/n3ui2OioakvcMUA+gNOvTxOgwJWhLibIi/8Yi4OEcSEuyIi3MgPt6B+HhHYmMdiYlxxmCw45Gi5REW0M9MAfRPbqmtCnH7+S+tyGkOkbGJFm2BiMxHl+MMy5dDB8te+DMsLAzI4ARiioW5efOmAigHDx5Mtv/jjz9W6tSpk+prbG1tlZUrVybbN2/ePKVo0aKpHj9hwgQF9aMsN7nJTW5yk5vcTHC7fv16ut/xFtfSkRvGjBmTrGXEYDDw4MEDChUqlO/GaIeFheHr68v169dNOjFafiJ1mD1Sf9kndZg9Un/ZoygK4eHh+GTgMpDFJR2FCxdGp9Nx507yacDv3LljnBDnWV5eXpk63t7eHnt7+2T7CmR7qUvr5ubmJr9s2SR1mD1Sf9kndZg9Un9Z5+7unqHjLG5Asp2dHTVr1iQwMNC4z2AwEBgYSL169VJ9Tb169ZIdD7Bz587nHi+EEEKI3GdxLR0AAQEB9O7dm1q1alGnTh1mz55NZGSkcTRLr169KFasGFOnTgVg2LBhNG7cmC+//JJ27dqxatUqjh8/znfffWfOtyGEEEKIJCwy6ejWrRuhoaGMHz+e27dvU61aNbZt24anpycAwcHByWaNe/nll1m5ciVjx47lk08+oUyZMmzYsMEi5+iwNPb29kyYMCHF5SaRcVKH2SP1l31Sh9kj9Zd7ZJVZIYQQQuQKi+vTIYQQQoi8SZIOIYQQQuQKSTqEEEIIkSsk6RBCCCFErpCkI5/Yv38/HTp0wMfHB41Gk2JdGkVRGD9+PN7e3jg6OtKiRQv+++8/8wRrgaZOnUrt2rVxdXWlaNGidO7cmfPnzyc7JiYmhsGDB1OoUCFcXFzo2rVriknr8rMFCxZQpUoV4wRM9erV4/fffzc+L/WXOdOmTUOj0fDhhx8a90kdpm3ixIloNJpkt/Llyxufl/rLeZJ05BORkZFUrVqVefPmpfr89OnT+frrr1m4cCFHjhzB2dmZ1q1bExMTk8uRWqZ9+/YxePBgDh8+zM6dO4mPj6dVq1ZERj5d/vujjz5i8+bN/PLLL+zbt4+QkBC6dOlixqgtS/HixZk2bRonTpzg+PHjNGvWjE6dOnHmzBlA6i8zjh07xrfffkuVKlWS7Zc6TF+lSpW4deuW8XbgwAHjc1J/uSADa7CJPAZQ1q9fb3xsMBgULy8vZcaMGcZ9jx49Uuzt7ZWff/7ZDBFavrt37yqAsm/fPkVR1PqytbVVfvnlF+Mx586dUwDl0KFD5grT4hUsWFD54YcfpP4yITw8XClTpoyyc+dOpXHjxsqwYcMURZHPYEZMmDBBqVq1aqrPSf3lDmnpEFy5coXbt2/TokUL4z53d3fq1q3LoUOHzBiZ5Xr8+DEAHh4eAJw4cYL4+PhkdVi+fHn8/PykDlOh1+tZtWoVkZGR1KtXT+ovEwYPHky7du2S1RXIZzCj/vvvP3x8fHjhhRfo2bMnwcHBgNRfbrHIGUlF7rp9+zaAccbXRJ6ensbnxFMGg4EPP/yQ+vXrG2e9vX37NnZ2dikWDpQ6TO6ff/6hXr16xMTE4OLiwvr166lYsSKnTp2S+suAVatWcfLkSY4dO5biOfkMpq9u3bosXbqUcuXKcevWLSZNmkTDhg05ffq01F8ukaRDiEwaPHgwp0+fTnYtWGRMuXLlOHXqFI8fP2bt2rX07t2bffv2mTssq3D9+nWGDRvGzp07cXBwMHc4Vqlt27bG7SpVqlC3bl1KlCjBmjVrcHR0NGNk+YdcXhF4eXkBpOilfefOHeNzQjVkyBC2bNnCnj17KF68uHG/l5cXcXFxPHr0KNnxUofJ2dnZUbp0aWrWrMnUqVOpWrUqc+bMkfrLgBMnTnD37l1q1KiBjY0NNjY27Nu3j6+//hobGxs8PT2lDjOpQIEClC1blosXL8pnMJdI0iEoWbIkXl5eBAYGGveFhYVx5MgR6tWrZ8bILIeiKAwZMoT169eze/duSpYsmez5mjVrYmtrm6wOz58/T3BwsNRhGgwGA7GxsVJ/GdC8eXP++ecfTp06ZbzVqlWLnj17GrelDjMnIiKCS5cu4e3tLZ/BXCKXV/KJiIgILl68aHx85coVTp06hYeHB35+fnz44Yd8/vnnlClThpIlSzJu3Dh8fHzo3Lmz+YK2IIMHD2blypVs3LgRV1dX4zVed3d3HB0dcXd3p1+/fgQEBODh4YGbmxtDhw6lXr16vPTSS2aO3jKMGTOGtm3b4ufnR3h4OCtXrmTv3r1s375d6i8DXF1dU6yc7ezsTKFChYz7pQ7TNmLECDp06ECJEiUICQlhwoQJ6HQ6unfvLp/B3GLu4TMid+zZs0cBUtx69+6tKIo6bHbcuHGKp6enYm9vrzRv3lw5f/68eYO2IKnVHaAsWbLEeEx0dLTy/vvvKwULFlScnJyUV199Vbl165b5grYw77zzjlKiRAnFzs5OKVKkiNK8eXNlx44dxuel/jIv6ZBZRZE6TE+3bt0Ub29vxc7OTilWrJjSrVs35eLFi8bnpf5ynixtL4QQQohcIX06hBBCCJErJOkQQgghRK6QpEMIIYQQuUKSDiGEEELkCkk6hBBCCJErJOkQQgghRK6QpEMIIYQQuUKSDmEVrl69ikajoU+fPtku6/bt2/Tu3RtfX190Oh0ajSbFegvWxt/fH39/f3OHka9MnDgRjUbD3r17M3S8KT/DQlgrmQZd5Dt9+vRhx44ddO/endKlS6PRaGTVTiGEyAWSdAirUKxYMc6dO4e7u3u2yomLi2Pnzp20aNGCFStWmCg6IdJnqs+wENZMkg5hFWxtbSlfvny2y7l9+zYGgwEfHx8TRCVExpnqMyyENZM+HcIqPO96eJMmTdBoNMTHxzNx4kT8/f2xt7enbNmyzJ8/P8WxJUqUAGDZsmVoNJoUZSqKwuLFi6lfvz5ubm44OTlRq1YtFi9enCKmpNf0ly5dSo0aNXBycqJJkybJYouJiWHs2LGUKlUKW1tbJk6caCzjypUr9O/fHz8/P+zt7fH29qZPnz5cu3Yt1XrYuHEjtWvXxtHREU9PT959910ePnyYqbo0GAz88MMP1KlTBw8PDxwdHSlevDgdOnRItX/CkiVLqFu3Li4uLri4uFC3bl2WLl2a4rilS5ei0WhSfW7v3r1oNJpk7x1Ao9HQpEkTbt68Sa9evfDy8kKr1SaLY//+/XTu3BlPT0/s7e3x9fWlS5cuHDhwIFlZmfnZpSej50y0cuVKqlWrhqOjI97e3gwbNozo6Ohkx6T3GX7e56RPnz5oNBouX77M9OnTKVOmDA4ODpQsWZLPPvuM+Pj4DL+vpPXdo0cPChcujKurK+3atePy5csAnDt3js6dO+Ph4YGrqyuvvfYad+7cSVHW4sWL6dSpE/7+/jg4OODh4UHr1q3Zs2dPqudet24djRs3pmjRojg4OODj40OLFi1Yt25dsuP27NlD27Zt8fHxwd7eHk9PTxo2bMh3332X4fcpLJe0dIg8oXv37hw9epS2bdui0+lYs2YNgwcPxtbWlnfffRdQ/3hXq1aNOXPmULVqVTp37gxAtWrVAPVLq2fPnvz888+UKVOGHj16YGdnx86dO+nXrx9nz55l5syZKc49Y8YM9uzZQ6dOnWjVqhU6nS7Z8127duWvv/6iTZs2FChQgJIlSwJw5MgRWrduTWRkJO3b/7+9+w+KsvgDOP4+fkbIgZxYnI1iBowjREYKJshATEMiHUoR0DQIlZkV5Yw14+QM6tCQJgoqUeRE2EQ5IWCgkJoJSCiFvyoDNaHySPEHQkgCyn7/sHvyPH4catfXZl8zznif3Wf3eW4fntvb3ee5WXh6etLc3Mwnn3xCeXk5tbW13HvvvUo5GzduJDExEbVazTPPPIOLiwtlZWWEh4fT09ODnZ2dWe/V4sWLWblyJRMmTCAhIQEnJyf0ej179uxh586dSqcJICUlhXXr1jFmzBieffZZ4OqHR1JSEgcOHCArK8usOgdz7tw5pk2bhqurK3FxcVy6dAm1Wg1AVlYWCxcuxMHBgdmzZzN27FhlXwsLCwkKCgJuvO36Y26dBuvXr6eiogKdTkdYWBgVFRWsXbuWs2fPDmsKb6DzxOC1116jpqaG2NhYRowYQWlpKampqRw+fJjCwkKz62lrayMoKIi7776bxMREjh49SllZGQ0NDWzZsoXg4GD8/f1JTk6mvr6ezZs3c/78eXbt2mVUzksvvYSfnx/h4eG4ubmh1+spKSkhPDycoqIidDqdkjcnJ4cFCxbg7u7O7Nmz0Wg0nDp1irq6OoqLi4mJiQFg69atREVF4eLigk6nw93dnTNnznDo0CE+/vhj5s2bZ/ZxSv+n/s2fuJUkczU1NQlAJCYmGsVDQkIEIAICAkR7e7sSb2hoEDY2NsLb29uscoQQIjc3VwAiKSlJ9PT0KPHu7m4RFRUlAPHdd98p8dTUVAEIR0dHcfjwYZPyDPv2wAMPiHPnzhml9fT0CA8PD+Hk5CT2799vlFZdXS2sra3FrFmzlFh7e7tQq9XC0dFRNDY2GpUzY8YMAYhx48aZvnH9cHV1FVqtVly8eNEk7dr9rKysFICYOHGiuHDhghI/f/688PLyEoCoqqpS4nl5eQIQeXl5JuV+/fXXAhCpqalGcUB5zy9fvmyUdvDgQWFlZSW0Wq1oamoySuvr6xN6vV55Pdy2G8hw6jS0v7Ozs2hoaFDiXV1dwsvLS1hZWRnlH+oc7u88EUKIxMREAQg3Nzfx22+/GR2boe0LCwuHPDYh/n6/Fy5caBR/8cUXBSBcXFxEZmam0THPnDlTAKK+vt5omxMnTpiU39LSIrRarfD09DSKP/jgg8LOzk6cPn3aZJuzZ88q/58zZ44AxMGDBwfNJ92+5PSK9J+Qnp6ufDsG8Pb2Zvr06TQ2NvLHH3+YVcb69etxdHQkOzsbW1tbJW5nZ8dbb70FwKeffmqy3bx58/D19R2w3GXLluHq6moUKysro7m5mddff53JkycbpQUFBaHT6di2bRsdHR0AlJSU0NHRQXJyMl5eXkpeW1tbZd+Gw87OzmREBjDaz/z8fODqNNK1ix9HjhxJamoqQL9TKTeyLytXrjTZn/fff5++vj7S0tJMbgdWqVRG63JutO2uN5w6DV599VW8vb2V1w4ODsTHx9PX10d9ff2QdRr0d55cX88999yjvL722IbTDiNGjCAtLc0oFh8fD4BGoyElJUWJq1Qq4uLiADh06JDRNtePxAC4u7sTExPDsWPHTKYIbW1tjdrGQKPRmMQcHBzMyifdfuT0ivSf4O/vbxIzXKAvXLiAk5PToNt3dXXx/fffo9VqWbFihUm6Yd68oaHBJG3q1KmDlt1f+t69ewFobGw0WecAfy94PXr0KA899JBywQ8ODjbJO23aNGxszP9TjouL491338XHx4e4uDhCQ0OZNm2ayYX+wIEDAEbTLQahoaEAHDx40Ox6BzJ+/HhGjRplEq+rqwPg0UcfHXT7m2m7G63zWkOde+Ya6jwarO0NbWUOT09P7rzzTqOYu7s7APfffz8qlarftJaWFqP4iRMnSE9PZ9euXej1erq7u43SW1palDVUcXFxvPHGG/j4+JCQkEBoaChBQUFGXxQM+YqKiggMDCQhIYFHHnmE4ODgfs8P6fYkOx3Sf8L1Fy9A+SC+cuXKkNu3tbUhhECv17Ns2bIB8128eNEkdtdddw1adn/p58+fBxhyzt9QX3t7OwCjR482yWNtbT2sb4FZWVmMHz+evLw80tLSSEtL44477iA2NpaMjAzlAt/R0YGVlRVubm79HpNKpVJGYm7GQO9fe3s7KpVK+dAbyM203Y3Wea2bPfcMbuQ8MrS94fwwx2D7O1jatQtWjx8/ztSpU+no6CA0NJSoqCjUarWyCLiystKoE7Jo0SI0Gg05OTlkZGSwatUqbGxsiIyMZM2aNcqoyZNPPklJSQmrV6/mvffeIzs7G5VKRWhoKBkZGcr6K+n2JadXJIm/L7b+/v4IIQb819/K/Ou/GZqTbqivtLR00PpCQkIAlOmN1tZWk7KuXLnCuXPnzD5WGxsbFi1axI8//oher6egoIDg4GA2btzI008/bbSPfX19nDlzxqSM1tZWhBBGH1JWVlcvJ5cvXzbJP9iH4kDvn4uLC0IIfv/990GP52ba7kbr/CcMdR71dweJoe0t/eyPNWvW0NbWxkcffcSOHTvIzMxk+fLlLF26tN/bglUqFcnJyXz77becOXOG4uJi5syZw5YtW5g1a5ZR50yn01FZWUlbWxvl5eU899xz7N69m4iIiNv+ycGS7HRIEgBOTk5MnDiRn376ySIXtoCAAABqa2vNyu/n5wdAdXW1SVptbW2/H/Tm0Gq1xMfHU1FRwX333cfOnTuVWz0Na036u43WELv2m+fIkSMB0Ov1JvmHM/xvYJhu2L59+6D5bmXbmVvnv2Gwtr9+XdA/7eeffwYwukMFrt5FVFNTM+i2Go2G6OhoNm3aRFhYGEeOHOH48eMm+ZycnIiIiCA3N5e5c+dy+vRp9u3bd+sOQvpXyE6HJP0lJSWFrq4unn/++X6H4puammhubr4ldel0OsaOHcvq1aupqqoySe/t7TV6JoROp0OtVvPhhx9y9OhRo3xLliwxu97u7m6++eYbk/jFixfp7OzE1tZWGbFITEwEri5wvHYapb29XZnGMOSBqyMNKpWKzz77jEuXLinxY8eO3dCttfPnz8fa2polS5aYLEoUQhitMbhVbTecOi0tKyuLkydPKq97enp48803ASz+ey6GtRrXP7fk7bff5ocffjDJv3v3boQQRrHe3l5lmtHwMwRVVVX9TkkZRvjkzxXc/uSaDkn6ywsvvMDevXvJz8+npqaG8PBwtFotp0+fpqGhgX379lFQUHBLfljN3t6ewsJCHnvsMUJCQggLC8PX1xeVSsUvv/xCdXU1Go1GWfzo7OzM2rVrmTt3LlOmTCEuLg5nZ2fKysqUB1KZ488//2T69Ol4eXnh7+/P2LFj6ezspKysjFOnTrFo0SLs7e0BmDFjBq+88grr1q3Dx8eHmJgYhBBs3ryZkydPkpKSwowZM5SyDaMmBQUF+Pv7ExERQWtrK8XFxURERJg8BGoovr6+ZGZmkpKSwqRJk4iOjmbcuHGcOnWKqqoqIiMjyczMBG5d2w2nTksLDAzEz8+Pp556CkdHR0pLS2lsbGTOnDnKcy4sZf78+eTl5RETE0NsbCwajYa9e/eyf/9+IiMj2bp1q1H+6Oho1Go1gYGBjBs3jt7eXnbs2MGRI0d44oknlE5MSkoKLS0tBAUF4eHhgUqlYs+ePdTV1REYGGjyjBTp9iM7HZL0F8PTNGfOnMkHH3xAWVkZnZ2djB49Gk9PT1atWkV4ePgtq2/KlCkcOnSId955h23btlFTU4O9vT1jxowhOjpauY3RIDExEWdnZ9LS0sjPz8fZ2ZnHH3+clStXmj287ujoyIoVK/jqq6+orq6mtbWVkSNH4u3tTXp6unJ7pMHatWuZPHkyOTk5yhMhJ02axPLly0lKSjIpf8OGDYwaNYpNmzaRnZ2Nt7c3ubm5aLXaYXc6AF5++WV8fHzIyMigvLxcaY+AgABiY2OVfLey7cyt09IyMzP5/PPP2bBhA7/++ivu7u4sXbqUxYsXW3xfJk+ezPbt21myZAlFRUVYW1vz8MMPU1NTwxdffGHS6UhPT6eiooK6ujpKS0txdHRkwoQJ5OTkKA+dg6sPrisqKqK+vp4vv/wSW1tbPDw8WLFiBQsWLOj3Nm/p9qIS1495SZIkSf835s6dS35+Pk1NTbdklE2S/k1yTYckSZIkSRYhOx2SJEmSJFmE7HRIkiRJkmQRck2HJEmSJEkWIUc6JEmSJEmyCNnpkCRJkiTJImSnQ5IkSZIki5CdDkmSJEmSLEJ2OiRJkiRJsgjZ6ZAkSZIkySJkp0OSJEmSJIuQnQ5JkiRJkixCdjokSZIkSbKI/wFUDcmtF3dYJQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot\n", "plt.figure(figsize=(6, 4))\n", "plt.figure(figsize=(6,4))\n", "plt.plot(x_cm_0, 1-y_cm_0, label='cm=0 (inv cdf)', color='r')\n", "plt.plot(x_cm_m1, y_cm_m1, label='cm=-1 (inv cdf)', color='g')\n", "plt.plot(x_cm_2, 1-y_cm_2, label='cm=2 (cdf)', color='b')\n", "plt.hist(mc_inferred_cm_0, bins=30, density=True, alpha=0.5, label='cm=0', color='r')\n", "plt.hist(mc_inferred_cm_m1, bins=30, density=True, alpha=0.5, label='cm=-1', color='g')\n", "plt.hist(mc_inferred_cm_2, bins=30, density=True, alpha=0.5, label='cm=2', color='b')\n", "plt.xlabel(\"inferred source chirp mass\", fontsize=14)\n", "plt.ylabel(\"cdf\", fontsize=14)\n", "plt.legend()\n", "plt.grid(alpha=0.4)\n", "# include a vertical line at 25\n", "plt.axvline(29, color='k', linestyle='--')\n", "plt.axvline(26, color='k', linestyle='--')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* outside 90% of cm=0 distribution, 15% of CM=-1 distribution lie beyond, and thus inferring a higher chirp mass for CM=-1\n", "* outside 90% of cm=2 distribution, 20% of cm=0 distribution lie beyond, and thus inferring a lower chirp mass for CM=2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## BBH (3G sensitivities)\n", "\n", "* let's do the same for 3G sensitivity " ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": [ "ler = LeR(batch_size=100000, ifos=['CE', 'ET'], verbose=False)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "unlensed params will be store in ./ler_data/unlensed_param_3G_cosmo.json\n", "chosen batch size = 100000 with total size = 500000\n", "There will be 5 batche(s)\n", "Batch no. 1\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 2\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 3\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 4\n", "sampling gw source params...\n", "calculating snrs...\n", "Batch no. 5\n", "sampling gw source params...\n", "calculating snrs...\n", "saving all unlensed_params in ./ler_data/unlensed_param_3G_cosmo.json...\n" ] } ], "source": [ "unlensed_param = ler.unlensed_cbc_statistics(size=500000, output_jsonfile='unlensed_param_3G_cosmo.json', resume=False);" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [], "source": [ "new_dL_cm_m1 = dL_GW_CM(dL=unlensed_param['luminosity_distance'], CM=-1)\n", "new_dL_cm_2 = dL_GW_CM(dL=unlensed_param['luminosity_distance'], CM=2)\n", "\n", "# new luminosity distance\n", "unlensed_param_cm_0 = unlensed_param.copy()\n", "unlensed_param_cm_m1 = unlensed_param.copy()\n", "unlensed_param_cm_m1['luminosity_distance'] = new_dL_cm_m1\n", "unlensed_param_cm_2 = unlensed_param.copy()\n", "unlensed_param_cm_2['luminosity_distance'] = new_dL_cm_2\n", "\n", "# new snrs\n", "snr_cm_m1 = ler.snr(gw_param_dict=unlensed_param_cm_m1)\n", "snr_cm_2 = ler.snr(gw_param_dict=unlensed_param_cm_2)\n", "unlensed_param_cm_m1.update(snr_cm_m1)\n", "unlensed_param_cm_2.update(snr_cm_2)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 91937.23512506043\n", "number of simulated unlensed detectable events: 444043\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_0_det.json\n" ] } ], "source": [ "# CM = 0\n", "_, unlensed_param_cm_0_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_0, \n", " output_jsonfile='unlensed_param_cm_0_det.json'\n", " )" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 93944.75113538507\n", "number of simulated unlensed detectable events: 453739\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_m1_det.json\n" ] } ], "source": [ "# CM = -1\n", "_, unlensed_param_cm_m1_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_m1, \n", " output_jsonfile='unlensed_param_cm_m1_det.json'\n", " )" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "using provided unlensed_param dict...\n", "given detectability_condition == 'step_function'\n", "total unlensed rate (yr^-1) (with step function): 82931.36426067396\n", "number of simulated unlensed detectable events: 400546\n", "number of all simulated unlensed events: 500000\n", "storing detectable unlensed params in ./ler_data/unlensed_param_cm_2_det.json\n" ] } ], "source": [ "# CM = 2\n", "_, unlensed_param_cm_2_det = ler.unlensed_rate(\n", " unlensed_param=unlensed_param_cm_2, \n", " output_jsonfile='unlensed_param_cm_2_det.json'\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### redshifts plot" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "z1 = dL_to_z(unlensed_param_cm_0['luminosity_distance'])\n", "z2 = dL_to_z(unlensed_param_cm_m1['luminosity_distance'])\n", "z3 = dL_to_z(unlensed_param_cm_2['luminosity_distance'])\n", "z1_det = dL_to_z(unlensed_param_cm_0_det['luminosity_distance'])\n", "z2_det = dL_to_z(unlensed_param_cm_m1_det['luminosity_distance'])\n", "z3_det = dL_to_z(unlensed_param_cm_2_det['luminosity_distance'])\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.hist(z1, bins=100, histtype='step', label='z CM=0', density=True, color='r', linestyle='--', alpha=0.5)\n", "plt.hist(z2, bins=100, histtype='step', label='z CM=-1', density=True, color='g', linestyle='--', alpha=0.5)\n", "plt.hist(z3, bins=100, histtype='step', label='z CM=2', density=True, color='b', linestyle='--', alpha=0.5)\n", "plt.hist(z1_det, bins=100, histtype='step', label='z CM=0, snr>8', density=True, color='r', linestyle='-', alpha=1)\n", "plt.hist(z2_det, bins=100, histtype='step', label='z CM=-1, snr>8', density=True, color='g', linestyle='-', alpha=1)\n", "plt.hist(z3_det, bins=100, histtype='step', label='z CM=2, snr>8', density=True, color='b', linestyle='-', alpha=1)\n", "plt.legend()\n", "plt.xlabel('z')\n", "plt.ylabel('pdf')\n", "plt.xlim(0, 10)\n", "plt.grid(alpha=0.4)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* now the detectable redshifts are much different for the three cases" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Contour plot of the inferred chirp-mass vs redshift" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# getting param from json file\n", "# unlensed_param_cm_0 = get_param_from_json(\"ler_data/unlensed_param_cm_0_det.json\")\n", "# unlensed_param_cm_m1 = get_param_from_json(\"ler_data/unlensed_param_cm_m1_det.json\")\n", "# unlensed_param_cm_2 = get_param_from_json(\"ler_data/unlensed_param_cm_2_det.json\")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# CM = 0\n", "# detector frame masses\n", "m1_cm_0 = np.array(unlensed_param_cm_0['mass_1'])\n", "m2_cm_0 = np.array(unlensed_param_cm_0['mass_2'])\n", "# chirp mass\n", "mc_cm_0 = (m1_cm_0*m2_cm_0)**(3/5)/(m1_cm_0+m2_cm_0)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_0 = np.array(unlensed_param_cm_0['luminosity_distance'])\n", "z_cm_0 = dL_to_z(dl_cm_0)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_0 = mc_cm_0/(1+z_cm_0)\n", "\n", "# CM = -1\n", "# detector frame masses\n", "m1_cm_m1 = np.array(unlensed_param_cm_m1['mass_1'])\n", "m2_cm_m1 = np.array(unlensed_param_cm_m1['mass_2'])\n", "# chirp mass\n", "mc_cm_m1 = (m1_cm_m1*m2_cm_m1)**(3/5)/(m1_cm_m1+m2_cm_m1)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_m1 = np.array(unlensed_param_cm_m1['luminosity_distance'])\n", "z_cm_m1 = dL_to_z(dl_cm_m1)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_m1 = mc_cm_m1/(1+z_cm_m1)\n", "\n", "# CM = 2\n", "# detector frame masses\n", "m1_cm_2 = np.array(unlensed_param_cm_2['mass_1'])\n", "m2_cm_2 = np.array(unlensed_param_cm_2['mass_2'])\n", "# chirp mass\n", "mc_cm_2 = (m1_cm_2*m2_cm_2)**(3/5)/(m1_cm_2+m2_cm_2)**(1/5)\n", "\n", "# redshifts\n", "dl_cm_2 = np.array(unlensed_param_cm_2['luminosity_distance'])\n", "z_cm_2 = dL_to_z(dl_cm_2)\n", "\n", "# inferred chirp mass\n", "mc_inferred_cm_2 = mc_cm_2/(1+z_cm_2)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from scipy.stats import gaussian_kde" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# cm_0\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_0[0:5000] # Your mass data\n", "redshift = z_cm_0[0:5000] # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X1, Y1 = np.meshgrid(xgrid, ygrid)\n", "Z1 = gaussian_kde(xy)(np.vstack([X1.ravel(), Y1.ravel()])).reshape(X1.shape)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# cm_2\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_2[0:5000] # Your mass data\n", "redshift = z_cm_2[0:5000] # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X2, Y2 = np.meshgrid(xgrid, ygrid)\n", "Z2 = gaussian_kde(xy)(np.vstack([X2.ravel(), Y2.ravel()])).reshape(X2.shape)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "# cm_m1\n", "# Assuming your data is loaded and you have mass, redshift arrays\n", "# Replace these with your actual data arrays\n", "mass = mc_inferred_cm_m1[0:5000] # Your mass data\n", "redshift = z_cm_m1[0:5000] # Your redshift data\n", "\n", "# Perform a kernel density estimation (KDE)\n", "xy = np.vstack([redshift, mass])\n", "kde = gaussian_kde(xy)(xy)\n", "\n", "# Define the levels for contour as percentiles of the density\n", "levels = np.percentile(kde, [10, 30, 50, 70, 90])\n", "\n", "# Create a grid for contour plot\n", "xgrid = np.linspace(min(redshift), max(redshift), 1000)\n", "ygrid = np.linspace(min(mass), max(mass), 1000)\n", "X3, Y3 = np.meshgrid(xgrid, ygrid)\n", "Z3 = gaussian_kde(xy)(np.vstack([X3.ravel(), Y3.ravel()])).reshape(X3.shape)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "INFO:matplotlib.mathtext:Substituting symbol M from STIXNonUnicode\n", "INFO:matplotlib.mathtext:Substituting symbol M from STIXNonUnicode\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting\n", "plt.figure(figsize=(6, 4))\n", "plt.contour(X1, Y1, Z1, levels=levels, colors=['red', 'red', 'red', 'red', 'red'], alpha=0.8)\n", "plt.contour(X3, Y3, Z3, levels=levels, colors=['green', 'green', 'green', 'green', 'green'], alpha=0.8)\n", "plt.contour(X2, Y2, Z2, levels=levels, colors=['blue', 'blue', 'blue', 'blue', 'blue'], alpha=0.8)\n", "plt.xlabel(\"observed redshift\")\n", "plt.ylabel(r\"inferred $\\mathcal{M}^{source} (M_\\odot)$\")\n", "plt.title(\"Chirp mass vs Redshift 10%, 30%, 50%, 70%, 90% contours of density\")\n", "# plt.colorbar(contour1, label='Density')\n", "plt.xlim(0, 10.0)\n", "plt.ylim(4, 20)\n", "plt.grid(alpha=0.3)\n", "# Add legend\n", "# Create proxy artists for legend\n", "proxy1 = plt.Line2D([0], [0], linestyle='-', color='red', label='CM=0')\n", "proxy3 = plt.Line2D([0], [0], linestyle='-', color='green', label='CM=-1')\n", "proxy2 = plt.Line2D([0], [0], linestyle='-', color='blue', label='CM=2')\n", "plt.legend(handles=[proxy1, proxy3, proxy2], loc='upper right')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* For CM = -1, it significantly overestimates the chirp mass\n", "* For CM = 2, it significantly underestimates the chirp mass\n", "\n", "**Conclusion :** The effect of cosmological friction on the redshift vs inferred chirp-mass relation of gravitational waves should be prominent just by comparing high redshift events with low redshift events.\n", "\n", "**Note 1:** For low chirp mass high redshift events in CM=2, it can have degeneracies if primordial black holes are considered.\n", "\n", "**Note 2:** For high chirp mass low redshift events in CM=-1, it can have degeneracies with lensing events.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Rates of detectable events per year\n", "\n", "| CM | Rate (O4) | Rate (3G) |\n", "|----|-----------|-----------|\n", "| 0 | 441 | 91937 |\n", "| -1 | 857 | 93944 |\n", "| 2 | 113 | 82931 |\n", "\n", "* Rate differences are expected to be more prominent in O4 sensitivities." ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "ler", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 2 }