{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"This notebook sets up and runs a set of benchmarks to compare\n",
"different numerical discretizations of the SWEs\n",
"\n",
"Copyright (C) 2016 SINTEF ICT\n",
"\n",
"This program is free software: you can redistribute it and/or modify\n",
"it under the terms of the GNU General Public License as published by\n",
"the Free Software Foundation, either version 3 of the License, or\n",
"(at your option) any later version.\n",
"\n",
"This program is distributed in the hope that it will be useful,\n",
"but WITHOUT ANY WARRANTY; without even the implied warranty of\n",
"MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n",
"GNU General Public License for more details.\n",
"\n",
"You should have received a copy of the GNU General Public License\n",
"along with this program. If not, see .\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#Lets have matplotlib \"inline\"\n",
"%matplotlib inline\n",
"\n",
"#Python 2.7 compatibility\n",
"from __future__ import print_function\n",
"\n",
"#Import packages we need\n",
"import numpy as np\n",
"from matplotlib import animation, rc\n",
"from matplotlib import pyplot as plt\n",
"from matplotlib import gridspec\n",
"from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
"#import mpld3\n",
"\n",
"import subprocess\n",
"import socket\n",
"import time\n",
"import os\n",
"import gc\n",
"import datetime\n",
"import logging\n",
"\n",
"import pycuda.driver as cuda\n",
"\n",
"try:\n",
" from StringIO import StringIO\n",
"except ImportError:\n",
" from io import StringIO"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#Get root logger\n",
"logger = logging.getLogger('')\n",
"logger.setLevel(logging.DEBUG)\n",
"\n",
"#Add log to file\n",
"fh = logging.FileHandler('output.log')\n",
"formatter = logging.Formatter('%(asctime)s:%(name)s:%(levelname)s: %(message)s')\n",
"fh.setFormatter(formatter)\n",
"fh.setLevel(logging.DEBUG)\n",
"logger.addHandler(fh)\n",
"\n",
"#Add log to screen\n",
"ch = logging.StreamHandler()\n",
"ch.setLevel(logging.INFO)\n",
"logger.addHandler(ch)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#Finally, import our simulator\n",
"from GPUSimulators import Common, LxF, FORCE, HLL, HLL2, KP07, KP07_dimsplit, WAF, IPythonMagic"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Registering cuda_context in user workspace\n",
"PyCUDA version 2017.1.1\n",
"CUDA version (9, 1, 0)\n",
"Driver version 9010\n",
"Using 'GeForce 840M' GPU\n",
"Created context handle <241084750752>\n",
"Using CUDA cache dir c:\\Users\\anbro\\Documents\\projects\\GPUSimulators\\GPUSimulators\\cuda_cache\n",
"Autotuning enabled. It may take several minutes to run the code the first time: have patience\n"
]
}
],
"source": [
"%cuda_context_handler cuda_context"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#Misc plotting setup\n",
"def setBwStyles(ax):\n",
" from cycler import cycler\n",
"\n",
" ax.set_prop_cycle( cycler('marker', ['.', 'x', 4, '+', '*', '1', 5]) +\n",
" cycler('linestyle', ['-.', '--', ':', '-.', '--', ':', '-.']) +\n",
" #cycler('markersize', [5, 5, 5, 5, 5, 5]) +\n",
" cycler('color', ['k', 'k', 'k', 'k', 'k', 'k', 'k']) ) \n",
"\n",
"#Set large figure sizes\n",
"plt.rcParams['figure.figsize'] = [12, 8]\n",
"plt.rcParams['figure.dpi'] = 100\n",
"plt.rcParams['animation.html'] = 'html5'\n",
"#plt.rcParams['legend.markerscale'] = 1.0\n",
"#plt.rcParams['lines.markersize'] = 6\n",
"plt.rcParams['lines.markeredgewidth'] = 1.5\n",
"#plt.rcParams['savefig.dpi'] = 400"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def save_figure(fig, stem):\n",
" if (not os.path.isdir(\"figures\")):\n",
" os.mkdir(\"figures\")\n",
" \n",
" fig_filename = os.path.join(\"figures\", \"convergence_smooth2d_\" + stem + \".pdf\")\n",
" \n",
" metadata = {\n",
" 'created': time.strftime(\"%Y_%m_%d-%H_%M_%S\"),\n",
" 'hostname': socket.gethostname()\n",
" }\n",
" \n",
" legend = fig.gca().legend_\n",
" if (legend != None):\n",
" fig.savefig(fig_filename, dpi=300,format='pdf',\n",
" transparent=True, pad_inches=0.0, frameon=None, \n",
" metadata=metadata, \n",
" bbox_extra_artists=(legend, ), bbox_inches='tight')\n",
" else:\n",
" fig.savefig(fig_filename, dpi=300,format='pdf',\n",
" transparent=True, pad_inches=0.0, frameon=None, \n",
" metadata=metadata)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"def downsample(highres_solution, factor):\n",
" assert(highres_solution.shape[0] % factor == 0)\n",
" assert(highres_solution.shape[1] % factor == 0)\n",
" ny = highres_solution.shape[0] / factor\n",
" nx = highres_solution.shape[1] / factor\n",
" \n",
" if (factor == 1):\n",
" return highres_solution\n",
" else:\n",
" return highres_solution.reshape([int(ny), int(factor), int(nx), int(factor)]).mean(3).mean(1)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1.0, 2.0, 0.2726356370001644]\n"
]
}
],
"source": [
"def wall_boundary_conditions(data):\n",
" data[0:2,:] = data[4:2:-1,:]\n",
" data[-2:,:] = data[-3:-5:-1,:]\n",
" data[:,0:2] = data[:,4:2:-1]\n",
" data[:,-2:] = data[:,-3:-5:-1]\n",
" return data\n",
" \n",
"\n",
"def gen_test_data(nx, ny, ref_nx, ref_ny, g, num_ghost_cells):\n",
" width = 100.0\n",
" height = 100.0\n",
" ref_dx = width / float(ref_nx)\n",
" ref_dy = height / float(ref_ny)\n",
"\n",
" x_center = ref_dx*ref_nx/2.0\n",
" y_center = ref_dy*ref_ny/2.0\n",
"\n",
" #Create a gaussian \"dam break\" that will not form shocks\n",
" size = width / 5.0\n",
" dt = 10**10\n",
" \n",
" h = np.zeros((ny+2*num_ghost_cells, nx+2*num_ghost_cells), dtype=np.float32); \n",
" hu = np.zeros((ny+2*num_ghost_cells, nx+2*num_ghost_cells), dtype=np.float32);\n",
" hv = np.zeros((ny+2*num_ghost_cells, nx+2*num_ghost_cells), dtype=np.float32);\n",
" \n",
" x = ref_dx*(np.arange(0, ref_nx, dtype=np.float32)+0.5) - x_center\n",
" y = ref_dy*(np.arange(0, ref_ny, dtype=np.float32)+0.5) - y_center\n",
" xv, yv = np.meshgrid(x, y, sparse=False, indexing='xy')\n",
" r = np.sqrt(xv**2 + yv**2)\n",
" xv = None\n",
" yv = None\n",
" gc.collect()\n",
" \n",
" #Make sure that the wanted resolution is suitable\n",
" assert(ref_nx >= nx)\n",
" assert(ref_ny >= ny)\n",
" assert(nx/ref_nx == ny/ref_ny)\n",
" \n",
" #Generate highres then downsample\n",
" #h_highres = 0.5 + 0.1*np.exp(-(xv**2/size + yv**2/size))\n",
" h_highres = 0.5 + 0.1*0.5*(1.0 + np.cos(np.pi*r/size)) * (r < size)\n",
" h[num_ghost_cells:-num_ghost_cells, num_ghost_cells:-num_ghost_cells] = downsample(h_highres, ref_nx/nx)\n",
" h_highres = None\n",
" gc.collect()\n",
" \n",
" #hu_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))\n",
" #hu_highres = 0.1*0.5*(1.0 + np.cos(np.pi*r/size)) * (r < size)\n",
" #hu[num_ghost_cells:-num_ghost_cells, num_ghost_cells:-num_ghost_cells] = downsample(hu_highres, ref_nx/nx)\n",
" #hu_highres = None\n",
" #gc.collect()\n",
" \n",
" #hv_highres = 0.1*np.exp(-(xv**2/size + yv**2/size))\n",
" #hv_highres = 0.1*0.5*(1.0 + np.cos(np.pi*r/size)) * (r < size)\n",
" #hv[num_ghost_cells:-num_ghost_cells, num_ghost_cells:-num_ghost_cells] = downsample(hv_highres, ref_nx/nx)\n",
" #hv_highres = None\n",
" #gc.collect()\n",
" \n",
" #Fix boundary conditions\n",
" #h = wall_boundary_conditions(h);\n",
" #hu = wall_boundary_conditions(hu);\n",
" #hv = wall_boundary_conditions(hv);\n",
" \n",
" scale = 0.7\n",
" max_h_estimate = 0.6\n",
" max_u_estimate = 0.1*np.sqrt(2.0)\n",
" dx = width/nx\n",
" dy = height/ny\n",
" dt = scale * min(dx, dy) / (max_u_estimate + np.sqrt(g*max_h_estimate))\n",
" \n",
" return h, hu, hv, dx, dy, dt\n",
"\n",
"h, hu, hv, dx, dy, dt = gen_test_data(nx=100, ny=50, ref_nx=1000, ref_ny=500, g=9.81, num_ghost_cells=2)\n",
"\n",
"plt.figure()\n",
"ax=plt.subplot(1,3,1)\n",
"im=plt.imshow(h, extent=[0, 100, 0, 100])\n",
"divider = make_axes_locatable(ax)\n",
"cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
"plt.colorbar(im, cax=cax)\n",
"\n",
"ax=plt.subplot(1,3,2)\n",
"im=plt.imshow(hu, extent=[0, 100, 0, 100])\n",
"divider = make_axes_locatable(ax)\n",
"cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
"plt.colorbar(im, cax=cax)\n",
"\n",
"ax=plt.subplot(1,3,3)\n",
"im=plt.imshow(hv, extent=[0, 100, 0, 100])\n",
"divider = make_axes_locatable(ax)\n",
"cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n",
"plt.colorbar(im, cax=cax)\n",
"\n",
"plt.show()\n",
"\n",
"print([dx, dy, dt])"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def gen_filename(simulator, nx):\n",
" return os.path.abspath(os.path.join(\"data\", \"smooth2d\", str(simulator.__name__) + \"_\" + str(nx) + \".npz\"))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def sanity_check(variable, variable_name):\n",
" maxval = np.amax(variable)\n",
" minval = np.amin(variable)\n",
" assert np.isnan(maxval) == False and np.isnan(minval) == False, variable_name + \" contains NaN values\"\n",
" \n",
"\n",
"def run_benchmark(simulator, courant_number, nx, ny, ref_nx, ref_ny, num_ghost_cells, g=9.81, force_rerun=False, datafilename=None):\n",
"\n",
" if (datafilename and os.path.isfile(datafilename) and force_rerun == False):\n",
" print(\"WARNING: Existing simulation exists, skipping simulation\")\n",
" return[0, 0, 0]\n",
" else:\n",
" #Generate high-res initial conditions\n",
" h0, hu0, hv0, dx, dy, dt = gen_test_data(nx=nx, ny=ny, ref_nx=ref_nx, ref_ny=ref_ny, g=g, num_ghost_cells=num_ghost_cells)\n",
" dt = dt * courant_number\n",
"\n",
" #Initialize simulator\n",
" with Common.Timer(simulator.__name__ + \"_\" + str(nx)) as timer:\n",
" sim = simulator(cuda_context, \\\n",
" h0, hu0, hv0, \\\n",
" nx, ny, \\\n",
" dx, dy, dt, \\\n",
" g)\n",
"\n",
" t, nt = sim.simulate(1.0)\n",
" \n",
" h, hu, hv = sim.download()\n",
"\n",
" sanity_check(h, \"h\")\n",
" sanity_check(hu, \"hu\")\n",
" sanity_check(hv, \"hv\")\n",
"\n",
" if (datafilename):\n",
" dirname = os.path.dirname(datafilename)\n",
" if (dirname and not os.path.isdir(dirname)):\n",
" os.makedirs(dirname)\n",
" np.savez_compressed(datafilename, h=h, hu=hu, hv=hv, nt=nt, t=t, elapsed=timer.secs)\n",
" \n",
" \n",
" gc.collect() # Force run garbage collection to free up memory\n",
" \n",
" return [timer.secs, nt, dt]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"KP07 [50x100] simulated 1.000000 seconds to 1.000000 with 5 steps (RK2)\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"3360"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datafilename = \"temp_data.npz\"\n",
"elapsed, nt, dt = run_benchmark(KP07.KP07, \n",
" courant_number=0.9, \n",
" ref_nx=500, ref_ny=1000,\n",
" nx=50, ny=100, \n",
" num_ghost_cells=2, force_rerun=True,\n",
" datafilename=datafilename)\n",
"\n",
"with np.load(datafilename) as data:\n",
" rh = downsample(data['h'], 2)\n",
"\n",
" plt.figure()\n",
" plt.imshow(rh, extent=[0, 100, 0, 100])\n",
" plt.colorbar()\n",
" plt.show()\n",
" \n",
"gc.collect()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"LxF [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"FORCE [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"HLL [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"HLL2 [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"WAF [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"KP07 [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (RK2)\n",
"KP07_dimsplit [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed warmup in 0.6409273147583008 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"LxF [8x8] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"LxF [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"LxF [32x32] simulated 1.000000 seconds to 1.000000 with 2 steps (Euler)\n",
"LxF [64x64] simulated 1.000000 seconds to 1.000000 with 3 steps (Euler)\n",
"LxF [128x128] simulated 1.000000 seconds to 1.000000 with 6 steps (Euler)\n",
"LxF [256x256] simulated 1.000000 seconds to 1.000000 with 11 steps (Euler)\n",
"LxF [512x512] simulated 1.000000 seconds to 1.000000 with 21 steps (Euler)\n",
"LxF [1024x1024] simulated 1.000000 seconds to 1.000000 with 42 steps (Euler)\n",
"LxF [2048x2048] simulated 1.000000 seconds to 1.000000 with 84 steps (Euler)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (LxF) in 4.651306629180908 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"FORCE [8x8] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"FORCE [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"FORCE [32x32] simulated 1.000000 seconds to 1.000000 with 2 steps (Euler)\n",
"FORCE [64x64] simulated 1.000000 seconds to 1.000000 with 3 steps (Euler)\n",
"FORCE [128x128] simulated 1.000000 seconds to 1.000000 with 6 steps (Euler)\n",
"FORCE [256x256] simulated 1.000000 seconds to 1.000000 with 11 steps (Euler)\n",
"FORCE [512x512] simulated 1.000000 seconds to 1.000000 with 21 steps (Euler)\n",
"FORCE [1024x1024] simulated 1.000000 seconds to 1.000000 with 42 steps (Euler)\n",
"FORCE [2048x2048] simulated 1.000000 seconds to 1.000000 with 84 steps (Euler)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (FORCE) in 4.5882568359375 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"HLL [8x8] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"HLL [16x16] simulated 1.000000 seconds to 1.000000 with 1 steps (Euler)\n",
"HLL [32x32] simulated 1.000000 seconds to 1.000000 with 2 steps (Euler)\n",
"HLL [64x64] simulated 1.000000 seconds to 1.000000 with 3 steps (Euler)\n",
"HLL [128x128] simulated 1.000000 seconds to 1.000000 with 6 steps (Euler)\n",
"HLL [256x256] simulated 1.000000 seconds to 1.000000 with 11 steps (Euler)\n",
"HLL [512x512] simulated 1.000000 seconds to 1.000000 with 21 steps (Euler)\n",
"HLL [1024x1024] simulated 1.000000 seconds to 1.000000 with 42 steps (Euler)\n",
"HLL [2048x2048] simulated 1.000000 seconds to 1.000000 with 84 steps (Euler)\n",
"HLL2 [8x8] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (HLL) in 4.203984498977661 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"HLL2 [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"HLL2 [32x32] simulated 1.000000 seconds to 1.000000 with 4 steps (dimsplit)\n",
"HLL2 [64x64] simulated 1.000000 seconds to 1.000000 with 6 steps (dimsplit)\n",
"HLL2 [128x128] simulated 1.000000 seconds to 1.000000 with 12 steps (dimsplit)\n",
"HLL2 [256x256] simulated 1.000000 seconds to 1.000000 with 22 steps (dimsplit)\n",
"HLL2 [512x512] simulated 1.000000 seconds to 1.000000 with 42 steps (dimsplit)\n",
"HLL2 [1024x1024] simulated 1.000000 seconds to 1.000000 with 84 steps (dimsplit)\n",
"HLL2 [2048x2048] simulated 1.000000 seconds to 1.000000 with 168 steps (dimsplit)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (HLL2) in 6.730779647827148 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"WAF [8x8] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"WAF [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"WAF [32x32] simulated 1.000000 seconds to 1.000000 with 4 steps (dimsplit)\n",
"WAF [64x64] simulated 1.000000 seconds to 1.000000 with 6 steps (dimsplit)\n",
"WAF [128x128] simulated 1.000000 seconds to 1.000000 with 12 steps (dimsplit)\n",
"WAF [256x256] simulated 1.000000 seconds to 1.000000 with 22 steps (dimsplit)\n",
"WAF [512x512] simulated 1.000000 seconds to 1.000000 with 42 steps (dimsplit)\n",
"WAF [1024x1024] simulated 1.000000 seconds to 1.000000 with 84 steps (dimsplit)\n",
"WAF [2048x2048] simulated 1.000000 seconds to 1.000000 with 168 steps (dimsplit)\n",
"KP07 [8x8] simulated 1.000000 seconds to 1.000000 with 1 steps (RK2)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (WAF) in 6.931923866271973 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"KP07 [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (RK2)\n",
"KP07 [32x32] simulated 1.000000 seconds to 1.000000 with 3 steps (RK2)\n",
"KP07 [64x64] simulated 1.000000 seconds to 1.000000 with 6 steps (RK2)\n",
"KP07 [128x128] simulated 1.000000 seconds to 1.000000 with 11 steps (RK2)\n",
"KP07 [256x256] simulated 1.000000 seconds to 1.000000 with 21 steps (RK2)\n",
"KP07 [512x512] simulated 1.000000 seconds to 1.000000 with 42 steps (RK2)\n",
"KP07 [1024x1024] simulated 1.000000 seconds to 1.000000 with 84 steps (RK2)\n",
"KP07 [2048x2048] simulated 1.000000 seconds to 1.000000 with 167 steps (RK2)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (KP07) in 11.319036960601807 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"KP07_dimsplit [8x8] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"KP07_dimsplit [16x16] simulated 1.000000 seconds to 1.000000 with 2 steps (dimsplit)\n",
"KP07_dimsplit [32x32] simulated 1.000000 seconds to 1.000000 with 4 steps (dimsplit)\n",
"KP07_dimsplit [64x64] simulated 1.000000 seconds to 1.000000 with 6 steps (dimsplit)\n",
"KP07_dimsplit [128x128] simulated 1.000000 seconds to 1.000000 with 12 steps (dimsplit)\n",
"KP07_dimsplit [256x256] simulated 1.000000 seconds to 1.000000 with 22 steps (dimsplit)\n",
"KP07_dimsplit [512x512] simulated 1.000000 seconds to 1.000000 with 42 steps (dimsplit)\n",
"KP07_dimsplit [1024x1024] simulated 1.000000 seconds to 1.000000 with 84 steps (dimsplit)\n",
"KP07_dimsplit [2048x2048] simulated 1.000000 seconds to 1.000000 with 168 steps (dimsplit)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Completed simulation (KP07_dimsplit) in 6.86387300491333 s\n",
"Completed simulation in 45.2971625328064 s\n"
]
}
],
"source": [
"reference_nx = 2048\n",
"force_rerun=True\n",
"domain_sizes = [8, 16, 32, 64, 128, 256, 512, 1024]\n",
"simulators = [LxF.LxF, FORCE.FORCE, HLL.HLL, HLL2.HLL2, WAF.WAF, KP07.KP07, KP07_dimsplit.KP07_dimsplit]\n",
"simulator_ghost_cells = [1, 1, 1, 2, 2, 2, 2]\n",
"simulator_courant_numbers = [0.9, 0.9, 0.9, 0.45, 0.45, 0.45, 0.45]\n",
"\n",
"\n",
"\n",
"sim_elapsed_time = np.zeros((len(simulators), len(domain_sizes)))\n",
"sim_dt = np.zeros((len(simulators), len(domain_sizes)))\n",
"sim_nt = np.zeros((len(simulators), len(domain_sizes)))\n",
"\n",
"#Warmup to compile kernels\n",
"with Common.Timer(\"warmup\") as timer:\n",
" for i in range(len(simulators)):\n",
" run_benchmark(simulator=simulators[i], \n",
" courant_number=simulator_courant_numbers[i], \n",
" nx=16, ny=16, ref_nx=16, ref_ny=16,\n",
" num_ghost_cells=simulator_ghost_cells[i], \n",
" force_rerun=force_rerun)\n",
"print(\"Completed warmup in {:} s\".format(timer.secs))\n",
" \n",
"with Common.Timer(\"simulation\") as timer:\n",
" for i in range(len(simulators)):\n",
" with Common.Timer(simulators[i].__name__) as sim_timer:\n",
" # Run the simulation for all the domain sizes\n",
" for j, nx in enumerate(domain_sizes):\n",
" datafilename = gen_filename(simulators[i], nx)\n",
" [secs, nt, dt] = run_benchmark(simulator=simulators[i], \n",
" courant_number=simulator_courant_numbers[i], \n",
" nx=nx, ny=nx, ref_nx=reference_nx, ref_ny=reference_nx,\n",
" num_ghost_cells=simulator_ghost_cells[i], \n",
" force_rerun=force_rerun, \n",
" datafilename=datafilename)\n",
" sim_elapsed_time[i, j] = secs\n",
" sim_dt[i, j] = dt\n",
" sim_nt[i, j] = nt\n",
"\n",
" # Run reference with a low CFL-number\n",
" datafilename = gen_filename(simulators[i], reference_nx)\n",
" run_benchmark(simulator=simulators[i], \n",
" courant_number=simulator_courant_numbers[i], \n",
" nx=reference_nx, ny=reference_nx, ref_nx=reference_nx, ref_ny=reference_nx,\n",
" num_ghost_cells=simulator_ghost_cells[i], \n",
" force_rerun=force_rerun, \n",
" datafilename=datafilename)\n",
" print(\"Completed simulation ({:}) in {:} s\".format(simulators[i].__name__, sim_timer.secs))\n",
"print(\"Completed simulation in {:} s\".format(timer.secs))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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AAKgYPptkBwcHX9T5u3fvVnh4uHr27Kn4+Hh3eUREhE6cOFGovmVZF3W9/GbNmqWPPvpI9913n7799luNHDlSgwcP9qgTGxvrcY8DBgzQv//9b6/FAAAAAAAoO59NsquzwMBALVu2TJ06dVLr1q01d+7cQnWio6O1cOFC9763etIBAAAAAOXns0l2WeZUv/TSS3r88ccLlT/99NN66KGHPMoOHz58saGVyqeffipJSk5OVnJycqEk2uFwKCoqqlJiAQAAAACUjs8ufOZwOEq9TZ48WZ07d/Y4v3Pnzpo8ebLHfOwLtetN//3vfzVlyhS9+uqruvbaazVq1Cjl5uZ69RoAAAAAAO/z2Z7ssggODtYnn3yiBQsW6ODBg4qKitL48eMvel53SVJSUrRr1y6PsksuuUQjR45Uv379dM8992jAgAHq2LGjXnzxRU2dOrVC4wEAAAAAXBySbJfg4GBNmzatUq8ZHx+vrl27epQZYxQeHq61a9dKksLDw7V48WINHTpUffv2VZcuXSo1RgAAAABA6RlvropdUYwxoZJSUlJSFBoa6nEsIyNDCQkJioyMVFBQkD0BwifwLgEAAADIk5qaqrCwMEkKsywrtbTn+eycbAAAAABA1TBlyhRt3rzZvb9582ZNmTLFxogqDsPFAQAAAAAVZtWqVZo7d67mzp2rESNGSJKWLVsmSerRo4cGDx5sZ3heR082AAAAAKDC9OnTR+PGjZPkTK7zEuxx48apT58+doZWIUiyAQAAAAAVJiQkRAsWLNCaNWvcZStWrNCCBQsUEhJiY2QVgyQbAAAAAFChfvrpJ/Xu3du9379/fxujqVgk2QAAAACACjNnzhy1b9/eY+EzX0aSDQAAAACoEDk5OVq3bp3S0tL0zTff2B1OpSDJBgAAAABUCH9/f73//vtatmyZpk+fLsuyZFmWHA6H3aFVGJJsAAAAAIBXpaamun+uXbu2hg8fbmM0lYskGwAAAADgNQcOHFDbtm31yiuv2B2KLWp8kj1v3jwdOXKkUPmRI0c0b968CrtuTEyMjDGFtoMHD0qSfvzxR917771q1qyZAgMD1bp1a02aNEknT570aKdXr17ucwMDA3XppZdq+vTpyszMLHTNuLg4DRw4UA0aNFDdunXVoUMHPfTQQ/r5558lSfHx8UXGZIzR0aNHK+xZAAAAAPAdb775po4fP67XX39dWVlZdodT6Wp0kj1v3jxNnjxZ0dHRHon2kSNHFB0drcmTJ1doot2/f38lJiZ6bJGRkTp06JCuuuoqHThwQG+99ZYOHjyoRYsWadOmTerevbuSk5M92hkzZowSExN18OBBzZ49W6+88opmzpzpUefvf/+7+vTpo/DwcL377rvau3evFi1apJSUFL344osedffv318orsaNG1fYcwAAAADgO5588knNmzdPH3zwgQIDA+0Op9IF2B2AnQYPHqy//e1vOnTokKKjoxUXFydJio6O1qFDh9SmTRsNHjy4wq5fu3ZthYeHFyqfMGGCAgMDtWHDBtWpU0eS1KpVK3Xt2lWXXnqpZsyYoYULF7rr161b191Oq1at9Oabb2rDhg169tlnJTm/Sffggw/qwQcf1EsvveQ+LyIiQj169NDp06c9rt+4cWPVq1fP6/cLAAAAwDdlZ2crICDAPRL2wQcftDsk2/hsT3Z6enqxW0ZGhiRnQhoXF+fuPY6KilJUVJQOHTqkyMhIvf/++2rUqFGp2vWW5ORkrV+/XuPHj3cn2HnCw8M1fPhwvfPOO7Isq8jzv/76a23dulW1atVyl/373/9WVlaWpk2bVuQ5JNQAAAAAyisnJ0fDhg3ThAkTlJOTY3c4tvPZJDs4OLjY7bbbbnPXa9WqlRITEyU5//qSnZ0tSUpISFD79u01YMAAj3YjIiKKbLM8YmNjPdoYMmSIvv/+e1mWpfbt2xd5Tvv27XXq1CklJSW5yxYsWKDg4GDVrl1bXbp0UVJSkqZOneo+/v333ys0NFRNmzYtVVwtWrTwiKtdu3bluj8AAAAAvu+TTz7Ru+++q8WLF2v37t12h2O7Gj1c3G7R0dEew74dDkeRi7Dll9eDbYxxlw0fPlwzZsxQamqqnn/+eYWGhnr8IcGyLI/6JdmyZYtCQkLc+wEBvCYAAAAAitazZ0/3aNuuXbvaHY7tfDZ7SktLK/aYv7+/++cjR46oadOmSkhIcA+xzs7OVmRkpD744AO1bt3a49zDhw97LUaHw6GoqCiPssDAQBljtHfvXg0aNKjQOd99950uueQSNWzY0F0WFhbmbmfZsmW64oortGTJEt17772SpMsuu0wpKSlKTEwsVW92ZGQkQ8gBAAAAXFD+zrwhQ4bYHE3V4bPDxR0OR7FbUFCQpF9XEU9ISFCbNm108OBBHTx4UG3atFFCQoJuuukmj2HZF2rXWxo0aKC+fftqwYIFOnfunMexo0ePavny5brjjjuK7ZmuVauWHnvsMf35z3/W2bNnJUm33367AgMDNXv27CLPKbjwGQAAAABcyNq1azVgwAClpqbaHUqV47NJdmmsWrXKvYp4XFycWrVq5V4MrU2bNjp06JBWrVpV6XHNnz9fmZmZ+v3vf6///Oc/+vHHH7Vu3Tr17dtXzZs311/+8pcLnj9s2DAZY7RgwQJJUsuWLfXSSy9p3rx5uvfee/Xxxx/rhx9+0NatWzV27Fg9/fTTHucfP35cR48e9djy5qoDAAAAqNnS09M1evRorV+/vkI/eVxd1egke9KkSZo7d647wc6Tl2jPnTtXkyZNqvS42rZtqy+++EKXXnqp7rjjDl166aW67777FB0drc8++0z169e/4PmBgYGaOHGiZs+e7R42P378eG3YsEE///yzBg8erMsvv1yjR49WaGioHn74YY/z27Vrp6ZNm3psX375ZYXdLwAAAIDqw+Fw6IMPPlBMTIymT59udzhVjinuU1BViTEmVFJKSkqKQkNDPY5lZGQoISFBkZGR7mHgQHnwLgEAAADIk5qaqrCwMEkKsyyr1OPia3RPNgAAAACgZKdOndLgwYN16NAhu0Op8nx2dXEAAAAAgHdMnDhR7733nn788Ud9/vnnZfpEcE1Dkg0AAAAAuKAXXnhBP//8s+bPn0+CXQKSbAAAAADABTVr1kxxcXEk2KXAnGwAAAAAQCHPP/+8tmzZ4t4nwS4derIBAAAAAB7effddPfroowoKCtK+ffsUERFhd0jVBkk2AAAAAMDDwIEDdcstt6hLly4k2GVEkg0AAAAA8FCnTh2tXLlSfn7MMC4rnhgAAAAAQLt379Ybb7zh3vf392cedjnQkw0AAAAANdzx48fVv39/JSYmyt/fXyNGjLA7pGqLnuwSbN68WVOmTPF6uzExMRo0aFCh8vj4eBljdPr0aY+fizJz5kx16dLF67EBAAAAqFkaNWqkmJgYXXnllbrpppvsDqdaI8kuxpkzZzRu3DjdeOONmjt3rlatWmV3SAAAAABQIYwxeuaZZ7Rt2zZdcskldodTrZFkF2Hz5s3q2LGjFi1a5C7r06ePjREBAAAAgHdlZ2dryZIlys3NdZc5HA4bI/INPptkp6enKz09XZZlucuysrKUnp6uzMzMIuumpKS4e69/+OEHjzohISEedfO/iNnZ2RV4JwAAAADgfWPHjtXo0aM1duxYu0PxKT6bZAcHBys4OFgnTpxwl73wwgsKDg7WxIkTPeo2btxYwcHBuuKKKzx6r4sSERGh4OBg7du3z122dOnScsUYGxvrjjNvGzBgQLnaAgAAAICyiI6OVlBQkG699Va7Q/EprC5uo+joaC1cuNCjbPv27azkBwAAAKDCjRw5Un379lV4eLjdofgUn02y09LSJEl169Z1l02dOlWTJ09WQIDnbR8/flySdP78eU2fPr1Q4pvf4cOHJTk/zp4nJiamXDE6HA5FRUV5lP3000/lagsAAAAAShIXF6du3bq5516TYHufzw4XdzgccjgcHh9PDwwMlMPhUO3atYusGxYWpgULFmjTpk1q3bq1R50zZ8541PXz+/XR1apVqwLvBAAAAAAu3kcffaTf//73uvHGG5WSkmJ3OD7LZ3uyL0bv3r21Z88ePfLII+5e7Y8++kiDBw+2JZ49e/a4F17Lk/d97HPnzmnXrl0ex4KDgwv1kAMAAACo2RwOh0JCQtS6detC+QW8hyS7GCEhIVqwYIFuv/12rV271rYEW5J69OhRqCxv1fQDBw6oa9euHsd69uyp+Pj4yggNAAAAQDXRvXt37dixQy1atPAYmQvvMvk/cVVVGWNCJaWkpKQoNDTU41hGRoYSEhIUGRmpoKAgewKET+BdAgAAgK85duyYsrKy1LJlS7tDqXZSU1MVFhYmSWGWZaWW9jz+fAEAAAAAPujMmTMaOHCgrrvuOu3du9fucGoMkmwAAAAA8EGpqak6e/asMjMzWay5EjEnGwAAAAB8UPPmzfXJJ5/o559/Vtu2be0Op8agJxsAAAAAfIRlWfrhhx/c+w0aNFCnTp1sjKjmIckGAAAAAB/xwgsvqEOHDvrwww/tDqXGIskGAAAAAB+Qk5OjuLg4nT17Vvv27bM7nBqLOdkAAAAA4AP8/f21evVqrVy5Unfeeafd4dRY9GQDAAAAQDV2+vRp98+BgYEk2DYjyQYAAACAamr//v267LLLNHfuXLtDgQtJNgAAAABUUytWrFBSUpKWL1+urKwsu8OBSLJtExMTo0GDBhUqj4+PlzFGp0+f9vi5KDNnzlSXLl2KPJadna1HHnlEHTt2lMPhULNmzTRq1Cj98ssvXr0PAAAAAPZ57LHHtHDhQr3//vsKDAy0OxyIJNstPT1dxhgZY5Senm53OBft7Nmz+uqrr/T444/rq6++0sqVK3XgwAHdcsstdocGAAAA4CJkZ2fLsixJkjFG999/vxo3bmxzVMjD6uI+KiwsTBs3bvQoe/nll9WtWzcdOXJErVq1sikyAAAAAOWVk5Oju+66S/Xq1dOiRYsUEEBKV9X47G+ktL3RefXy109PT9f58+eVmZmpkJAQ1alTp8R2HQ7HRURbOVJSUmSMUb169ewOBQAAAEA5fPbZZ1q1apUCAgI0fvx4/eY3v7E7JBTgs0l2cHBwuc9t0qSJ++eePXsqPj7evR8REaETJ04UOidvuEZZxMbGFoozJyenzO2URkZGhh599FENGzZMoaGhFXINAAAAABXrd7/7nVauXKmsrCwS7CrKZ5Ps6iA6OloLFy70KNu+fbtGjBjh1etkZ2frzjvvVG5urhYsWODVtgEAAABUPMuyZIyRJN166602R4ML8dkkOy0trVT18g8Xb9OmjSTp2LFjql27tnu4eH6HDx/2WowOh0NRUVEeZT/99JPX2pecCfbQoUOVkJCgzZs304sNAAAAVDNr1qzR3LlztXLlSqZ+VgM+m2SXdo50Xr38c60dDkex51eHudd58hLs77//XnFxcWrQoIHdIQEAAAAog7Nnz2rs2LE6evSo5s2bpyeffNLukFACn02yfcmePXsK9ajnfR/73Llz2rVrl8ex4OBgRURE6Pbbb9dXX32l2NhY5eTk6OjRo5Kk+vXr8w09AAAAoBqoW7eu1q1bp5dfflkzZsywOxyUAkm2i8PhKNfiZZWhR48ehcryYj1w4IC6du3qcaxnz55aunSp1qxZI+nXhDxPXFycevXqVTHBAgAAAPCqzp07a/HixXaHgVIyVTWxzM8YEyopJSUlpdCc4oyMDCUkJCgyMlJBQUH2BAifwLsEAACAqiA5OVl33323/vrXv6pt27Z2h1NjpaamKiwsTJLCLMtKLe159GQDAAAAQBUyadIkxcbG6qefftJXX33lXlUc1QNJNgAAAABUIXPmzFFiYqLmzp1Lgl0NkWQDAAAAQBXSpEkTffTRR3aHgXLyszsAAAAAAKjpnnnmGW3evNnuMOAF9GQDAAAAgI1WrlypGTNmKDAwUPv27VObNm3sDgkXgSQbAAAAAGw0cOBA3X777bryyitJsH0ASTYAAAAA2CgoKEjvvPMOi5z5COZkAwAAAEAl2717txYvXuze9/PzI8n2EfRkAwAAAEAlSkpKUv/+/ZWYmKiAgADFxMTYHRK8iJ5sAABf000XAAAgAElEQVQAAKhEDRs21OjRo3XllVdq0KBBdocDLyPJdjl//rxWrFihFStW6Pz58xV+vUWLFikkJMTjWmlpaapVq5ZuuOEGj7pbtmyRMUYHDhxwlz3zzDPy9/fXc889V6jtpUuXyhhTaMs/HAUAAACAPYwxeuqpp7R9+3bVq1fP7nDgZSTZLvHx8RoyZIiGDBmi+Pj4Cr9edHS00tLS9MUXX7jLtmzZovDwcH3++ec6e/asR2zNmjXTZZdd5i57/fXXNW3aNL322mtFth8aGqrExESPbfjw4RV3QwAAAACKlZ2drUWLFiknJ8ddVrduXRsjQkWp0Um2ZVlKT09Xenq63n77bXf522+/7S63LKtCrt2uXTs1a9bMI6GPj4/XrbfeqksvvVSffvqpR3l0dLR7/+OPP9a5c+f01FNPKT09Xf/5z38KtW+MUXh4uMdWp06dCrkXAAAAABc2duxYjRs3Tvfee6/doaCC+WySnZckF7VlZGRIkg4fPqzg4GAFBwdryZIl7nOXLFniLt+/f3+p2i2PXr16KS4uzr0fFxenXr16qWfPnu7yrKwsffbZZx5J9pIlS3TXXXepVq1auuuuuzxiBwAAAFD19OvXT3Xr1tWQIUPsDgUVzGeT7LwkuajttttukyRt3bq1xHYGDx7ssR8REVFkm+XRq1cvbd26VefPn9eZM2e0c+dO9ejRQz179nT3cG/btk3nzp1zJ9mpqal69913NWLECEnSiBEjtGLFCqWmpnq0nZKS4hFfeHh4uWIEAAAAcPHuvPNOJSQk6KabbrI7FFQwn02yS2PIkCH6y1/+csE6jRo1qrDrR0dHKz09XZ9//rm2bNmiyy67TI0bN1bPnj31+eefKz09XfHx8WrVqpXatGkjSXrzzTfVpk0bde7cWZLUpUsXtWnTxmO4uySFhIRo165d7i3/8HMAAAAAFW/Tpk06c+aMe79x48Y2RoPK4rPfyU5LSyv2mL+/vySpdu3amjRpkmbMmFFkvWPHjikkJMSj7PDhw16LMSoqSi1atFBcXJxOnTqlnj17SpLCw8MVGRmprVu3Ki4uTr1793af89prr+nbb79VQMCvv7rc3FwtWbJE9913n7vMz89PUVFRXosVAAAAQOl99NFHGjhwoDp27KhNmzaxingNUq4k2xgzXtJUSU0lfStpsmVZWy5Qf7KkcZJaSTohaYWk6ZZlZZTn+qXhcDi80kbBxcK80W5+0dHRio+P16lTpzR16lR3ec+ePbV+/Xpt27ZN99xzjyRpz549+uKLLxQfH6/69eu7654+fVo9evTQN998oyuvvNKr8QEAAAAou7CwMIWFhalt27YKDQ21OxxUojIn2caYOyTNlTRe0lZJYyV9aIzpYFnWkSLqD5f0nKT/kfSppMskLXUdnlK+sL2nbt26eueddzR79mz9z//8jyRnb/G0adMqZUn96OhoTZgwQdnZ2e6ebMmZZI8bN04ZGRnu+dhLlixRt27d1KNHj0LtdO/eXUuWLNFLL71U4TEDAAAAuLCrr75aO3bsULNmzeTnV6Nn6dY45enJ/pOkJZZlLXbtTzbG/F7OnurpRdTvLmmrZVlvuvYPG2PektStHNf2OmOMhg4dqqFDh7rLxo8fX2nXj46O1rlz53T55ZerSZMm7vKePXvqzJkzuvTSS9WyZUtlZWVp2bJleuSRR4ps57bbbtOzzz6r559/vrJCBwAAAJDPsWPHdO7cOUVEREiSIiMj7Q0ItjBl+Q60MSZQ0llJQyzLWpWvfJ6kLpZl9SzinDslLZLUz7KsHcaYNpLel/SGZVnPlfK6oZJSUlJSCg21yMjIUEJCgiIjIxUUFFTqewEK4l0CAABAeZ05c0a9evVSYmKi1q9fr44dO9odEi5SamqqwsLCJCnMsqzUkurnKWtPdkNJ/pKOFSg/JqnIb0RZlvW2MaaRpE+MMcZ1zYUXSrCNMbUl1c5XFFJcXQAAAACwW1pamrKysnT+/Hk6bGq48q4uXrD72xRR5jxgTC9JM+Scw71dUpSkecaYRMuyni6m/emSnixnbAAAAABQqZo2baotW7boxx9/VNu2be0OBzYq6wz8E5JyVLjXurEK927neVrSvyzLWmxZ1h7XMPPHJE03xhR3/WclheXbWpQxTgAAAACoUJZl6dChQ+79evXqMUwcZUuyLcvKkvSlpL4FDvWVc+XwotSVlFugLEfO3m9TzHUyLctKzdsknSmqHgAAAADY5YUXXtAVV1yhNWvW2B0KqpDyDBf/q6R/GWO+kPSZpPvk/P71IkkyxvxT0s+WZeWtNL5W0p+MMTv163DxpyWtsSwr5yLjBwAAAIBKl5ubq61btyojI0MHDx60OxxUIWVOsi3LescY00DSE5KaSvpG0kDLsn5wVWklz57rWXLO154lqbmkJDkT7xkXETcAAAAA2MbPz0/vvvuuVq1apSFDhtgdDqqQMn3Cyy58wguVgXcJAAAAJUlOTlb9+vXtDgOVoLyf8CrrwmcAAAAAUCPt379f7dq10/PPP6/q0FkJe5BkAwAAAEAprF69WidOnNC7776rrKwsu8NBFVXe72QDAAAAQI0ybdo01a9fX7feeqtq165tdziooujJtklMTIwGDRrkUbZixQoFBQVp9uzZmjlzpowxMsbI399fLVu21OjRo5WUlOSuf+rUKY0cOVJhYWEKCwvTyJEjdfr0affx/G3k3xwOR6XdJwAAAFCdZWVlKTf313WdR48erUaNGtkYEao6kuwqYvHixRo+fLjmz5+vadOmSZKuuOIKJSYm6siRI1q4cKHWrl2rUaNGuc8ZNmyYdu3apXXr1mndunXatWuXRo4c6T7+8MMPKzEx0WPr0KEDqx8CAAAApZCTk6Nhw4YpJiZG2dnZdoeDaoIkW9KUKVO0efNm9/7mzZs1ZcqUSrv+7NmzNXHiRL355psaPXq0uzwgIEDh4eFq3ry5br75Zj344IPasGGDzp07p3379mndunVavHixunfvru7du+vVV19VbGys9u/fL0kKDg5WeHi4ezt27Jj27t2re++9t9LuDQAAAKiuduzYoffee0/vvPOOdu/ebXc4qCZ8dk52enq6JKlu3boyxkhyDvXIzs5WQECAew7FqlWrNHfuXM2dO1fDhw+XMUbLli2TJHXr1k2DBw/2+JxTXrt16tSRn5/zbxTZ2dmqVatWueJ89NFH9corryg2NlZ9+vS5YN06deooNzdX58+f12effaawsDBdc8017uPXXnutwsLC9Omnn6pdu3aFzl+8eLEuu+wy3XDDDeWKFQAAAKhJunfvrrVr1yo9PV2//e1v7Q4H1YTP9mQHBwcrODhYJ06ccJe98MILCg4O1sSJE91lffr0UUCA828Ny5cvdyfY119/vYYNG1ao1zciIkLBwcHat2+fu2zp0qXlivHDDz/U888/r9WrV5eYYH/33XdauHChunXrppCQEB09elSNGzcuVK9x48Y6evRoofLMzEwtX76cXmwAAACgBPk/zzVgwADdfvvtNkaD6sZnk+zSCgkJUWBgoEfZmjVrKuVfpE6dOikiIkJPPPGEzpw5U+j4nj17FBwcrDp16qhDhw5q2bKlli9f7j6e10Ofn2VZRZavXLlSZ86c8ZjTDQAAAMDT6tWr1bNnT508edLuUFBN+WySnZaWprS0NDVs2NBdNnXqVKWlpWn+/PkedY8fP65jx46593v37q0JEyYoLS1NS5Ys8ah7+PBhpaWlqX379u6ymJiYcsXYvHlzffzxx0pMTFT//v0LJdrt2rXTrl27tHfvXp07d06bN29WVFSUJLnnWBeUlJSkJk2aFCpfvHixbr75ZoWHh5crVgAAAMDXZWRkaPz48dqyZYv+9re/2R0OqimfTbIdDoccDodHr25gYKAcDkehb9rl1c2vVq1acjgcHvOx89fNm4+dV7e8WrVqpY8//ljHjx9Xv379lJqa6hFvVFSUIiMjC8XcvXt3paSkaMeOHe6y7du3KyUlRdddd51H3YSEBMXFxTFUHAAAALiAoKAgbdiwQffdd58ef/xxu8NBNeWzSXZ10qJFC8XHx+vkyZPq16+fUlJSSjynffv26t+/v8aMGaNt27Zp27ZtGjNmjG6++eZCi5699tpratq0qQYMGFBRtwAAAAD4hCuuuEJ///vf3es2AWVFku3icDhkWZYsyyrUq10Z8oaOnz59Wn379tXp06dLPGf58uXq2LGj+vXrp379+qlTp07617/+5VEnNzdXS5cuVUxMjPz9/SsqfAAAAKBaSk5O1oABA/Tdd9/ZHQp8hMm/cl5VZYwJlZSSkpKi0NBQj2MZGRlKSEhQZGRkoaHdQFnwLgEAANQ8d999t/75z3+qU6dO2rlzp8e0UNRsqampCgsLk6Qwy7JSS6qfhzEQAAAAAGqsF198UceOHdOcOXNIsOEVJNkAAAAAaqyGDRtq3bp1docBH8KfagAAAADUKLNmzdL69evtDgM+ip5sAAAAADXGe++9p8cff1y1atXSvn37dOmll9odEnwMSTYAAACAGmPgwIG66667dPnll5Ngo0KQZAMAAACoMQIDA7Vs2TIZY+wOBT6KOdkAAAAAfNrXX3+thQsXuvf9/PxIslFh6MkGAAAA4LNOnDihAQMGKDExUYGBgbr33nvtDgk+jp5sAAAAAD6rQYMGmjhxojp27KjbbrvN7nBQA5Bko0xiYmI0aNAg936vXr00efJkGyOSli5dqnr16rn3Z86cqS5dutgYEQAAAKoKY4wee+wx7dixw+O/GYGKUmOT7ClTpmjz5s22Xb9gsipJK1asUFBQkGbPnq2ZM2fKGCNjjPz9/dWyZUuNHj1aSUlJ7vqnTp3SyJEjFRYWprCwMI0cOVKnT592H8/fRv7N4XB47T5Wrlypp59+2mvtecPDDz+sTZs2ufeLetYAAADwXdnZ2Zo/f77Onz/vLgsKCrIxItQkNTLJXrVqlebOnasbb7xR48aN05kzZ+wOSYsXL9bw4cM1f/58TZs2TZJ0xRVXKDExUUeOHNHChQu1du1ajRo1yn3OsGHDtGvXLq1bt07r1q3Trl27NHLkSPfxhx9+WImJiR5bhw4dNGTIEK/FXb9+fYWEhHitPW8IDg5WgwYN7A4DAAAANhk7dqweeOAB3X333XaHghqoRibZffr0cf+8aNEidezY0dZe7dmzZ2vixIl68803NXr0aHd5QECAwsPD1bx5c91888168MEHtWHDBp07d0779u3TunXrtHjxYnXv3l3du3fXq6++qtjYWO3fv1+SM9kMDw93b8eOHdPevXtLvdhDTk6O/vSnP6levXpq0KCBpk2bJsuyPOoUHC4eERGhWbNmadSoUQoODlbr1q21evVqJSUl6dZbb1VwcLA6duyoL774wn3ODz/8oD/84Q+65JJL5HA4dMUVV+iDDz6QJMXHx8sYo/fff1+dO3dWUFCQrrnmGu3Zs6fYuPMPF585c6beeOMNrV692t2THx8fX6r7BwAAQPV08803Kzg4WMOHD7c7FNRAPptkp6enF7v5+Xne9g8//KAbb7xRY8eOdfdqnz9/Xunp6Tp37lyp2i2vRx99VE8//bRiY2NLXIihTp06ys3N1fnz5/XZZ58pLCxM11xzjfv4tddeq7CwMH366adFnr948WJddtlluuGGG0oV24svvqjXXntNS5Ys0SeffKLk5GStWrWqxPNeeuklXX/99dq5c6duuukmjRw5UqNGjdKIESP01VdfKSoqSqNGjXIn7BMmTFBmZqb+85//aM+ePXr++ecVHBzs0ebUqVM1Z84cff7552rcuLFuueUWZWdnlxjLww8/rKFDh6p///7u3vzrrruuVPcPAACA6umPf/yjEhISNHDgQLtDQQ3ks5/wKpiklcY//vEPrV+/Xq+99ppOnjypoUOHqmfPnh49nxERETpx4kShcwv28JbGhx9+qNWrV2vTpk3q3bv3Bet+9913Wrhwobp166aQkBAdPXpUjRs3LlSvcePGOnr0aKHyzMxMLV++XI8++mip45s7d66mT5/uTv4XLVqk9evXl3jewIEDNXbsWEnSE088oYULF+rqq692D1N/5JFH1L17dx07dkzh4eE6cuSIbrvtNnXs2FGS1KZNm0JtPvnkk+rbt68k6Y033lCLFi20atUqDR069IKxBAcHq06dOsrMzFR4eHip7x0AAADVy8aNG9WtWzeFhYVJkho2bGhzRKipfLYnuzro1KmTIiIi9MQTTxQ5L3zPnj3uJLFDhw5q2bKlli9f7j5ujCl0jmVZRZavXLlSZ86c8ZjTfSEpKSlKTExU9+7d3WUBAQG66qqrSnVfeZo0aSJJ7gQ6f9nx48clSQ8++KBmzZql66+/Xk8++aR2795dqM38cdSvX1/t2rXTvn37SnUvAAAA8G0bN27UTTfdpB49eig5OdnucFDD+WySnZaWdsGtKGPHjtWePXvUu3dvDR48WGlpafrwww896hw+fLjU7ZWkefPm+vjjj5WYmKj+/fsXSrTbtWunXbt2ae/evTp37pw2b96sqKgoSXLPsS4oKSnJncTmt3jxYt18882V0ptbq1Yt9895CX9RZbm5uZKk0aNH69ChQxo5cqT27Nmjq666Si+//HKJ1ynqjwkAAACoeRo2bKj69eurffv2fKYLtvPZJNvhcBS75SV3eVq3bq1NmzZp0aJF7pWyAwIC5HA4VKdOnVK1W16tWrXSxx9/rOPHj6tfv35KTU11HwsMDFRUVJQiIyNVu3Ztj/O6d++ulJQU7dixw122fft2paSkFJpznJCQoLi4uFIveCZJYWFhatq0qbZt2+YuO3/+vL788suy3mKptGzZUvfff79Wrlyphx56SK+++qrH8fxxnDp1SgcOHNDll19eqrYDAwOVk5Pj1XgBAABQdXTt2lU7duzQG2+8UWj9JaCy1cg38KOPPnL/PG7cOHfvtV1atGih+Ph4nTx5Uv369VNKSkqJ57Rv3179+/fXmDFjtG3bNm3btk1jxozRzTffrHbt2nnUfe2119S0aVMNGDCgTHFNmjRJzz33nFatWqXvvvtO48eP9/gOt7dMnjxZ69evV0JCgr766itt3rxZ7du396jz1FNPadOmTfrmm28UExOjhg0blvrb1xEREdq9e7f279+vEydOlGrBNAAAAFRtx44d03//+1/3fqtWrQp1TAF2qJFJ9uDBgzV58mRt2rRJCxYsqBLfec4bOn769Gn17du3VMns8uXL1bFjR/Xr10/9+vVTp06d9K9//cujTm5urpYuXaqYmBj5+/uXKaaHHnpIo0aNUkxMjLp3766QkBANHjy4TG2URk5OjiZMmOD+w0G7du20YMECjzrPPfecJk2apN/+9rdKTEzUmjVrFBgYWKr2x4wZo3bt2umqq65So0aNtHXrVq/fAwAAACpPamqqBgwYoOuuu047d+60OxzAgynPqtiVzRgTKiklJSVFoaGhHscyMjKUkJCgyMhIBQUF2RMgKkx8fLyio6N16tSpCp9fw7sEAABQPRw7dkz9+/fXzz//rE8//dS9bhHgTampqXmr1YdZlpVaUv08PvsJLwAAAAC+qUmTJvr444915MgREmxUOTVyuDicgoODi922bNlid3gAAACAm2VZOnjwoHs/NDRUV155pY0RAUWjJ7sG27VrV7HHmjdvXomRFK9Xr16qDlMaAAAAULFmz56tJ554QsuXL9ftt99udzhAsUiyazCG1gAAAKA6yM3N1Y4dO5SVlaUff/zR7nCAC/KZJJveTlws3iEAAICqyc/PT//3f/+nNWvWVMjXbgBvqvZzsvM+S5WVlWVzJKju8t6hsn7qDAAAABXjxIkT7p/9/f1JsFEtVPue7ICAANWtW1dJSUmqVauW/Pyq/d8NYIPc3FwlJSWpbt26Cgio9v9aAAAAVHv79+/X9ddfr0mTJunPf/6zjDF2hwSUSrXPJowxatq0qRISEvTDDz/YHQ6qMT8/P7Vq1Yr/AQcAAKgCPvjgA508eVJr167V1KlTFRQUZHdIQKlU+yRbkgIDA9W2bVuGjOOiBAYGMhICAACgipgyZYrq16+vgQMHkmCjWjHVYbEnY0yopJSUlBSFhobaHQ4AAACACpCZmckUUFQZqampCgsLk6Qwy7JSS3seby8AAAAA2+Xk5GjYsGEaNmyYMjMz7Q4HKDeSbAAAAAC2+/LLL7V27VqtWrVKe/bssTscoNx8Yk42AAAAgOqtW7duev/995WamqqrrrrK7nCAciPJBgAAAGCb3Nxc9xzsvn372hwNcPEYLg4AAADAFqtXr9b111+vpKQku0MBvIYkGwAAAECly8zM1AMPPKBt27bpb3/7m93hAF5Dkg0AAACg0tWuXVsbN27UuHHj9OSTT9odDuA1fCcbAAAAAIAC+E42AAAAgCotOTlZ/fr10zfffGN3KECFIckGAAAAUCkefvhhbdy4UXfddZdyc3PtDgeoEHzCCwAAAEClmDNnjpKSkvTcc8+5P9sF+BrmZAMAAAAAUABzsgEAAABUObNmzVJsbKzdYQCVhuHiAAAAACrEmjVr9Pjjj8vf31/79u1T27Zt7Q4JqHAk2QAAAAAqxIABA3T33XerTZs2JNioMZiTDQAAAKDC5OUbxhibIwHKhjnZAAAAAGz39ddfa968ee59YwwJNmoUhosDAAAA8Irk5GT1799fR48eVe3atXX//ffbHRJQ6ejJBgAAAOAV9evX10MPPaTOnTvrzjvvtDscwBbMyQYAAADgVZmZmapdu7bdYQAXhTnZAAAAACpddna25s6dq+zsbHcZCTZqMpJsAAAAAOU2duxYTZkyRcOHD7c7FKBKIMkGAAAAUG5//OMfFRoaqnvuucfuUIAqgTnZAAAAAC5KcnKy6tevb3cYgFcxJxsAAABApVi3bp1OnTrl3ifBBn5Fkg0AAACg1DZu3Kg//OEPuuGGG3Ty5Em7wwGqHJJsAAAAAKXWtGlTNWnSRB07dtQll1xidzhAlRNgdwAAAAAAqo8rr7xS27dvV8OGDeXnR58dUBD/VgAAAAC4oKNHj+rAgQPu/ebNm/MtbKAYJNkAAAAAipWamqoBAwbouuuu0xdffGF3OECVR5INAAAAoFhZWVkKCAiQv7+/6tWrZ3c4QJXHnGwAAAAAxWrYsKHi4uJ05MgRRUVF2R0OUOXRkw0AAADAg2VZ2r9/v3s/ODhYHTp0sDEioPogyQYAAADgYfbs2erYsaPefvttu0MBqh2SbAAAAABulmVp165dys7OVmJiot3hANWOsSzL7hhKZIwJlZSSkpKi0NBQu8MBAAAAfFpubq5iY2N1yy232B0KYJvU1FSFhYVJUphlWamlPY+ebAAAAAA6fvy4+2c/Pz8SbKCcSLIBAACAGu67775Thw4d9Oc//1nVYaQrUJWRZAMAAAA13MaNG3Xy5Elt3LhRGRkZdocDVGt8JxsAAACo4R544AE1aNBA/fr1U506dewOB6jWWPgMAAAAqIEyMzMVEBAgf39/u0MBqiQWPgMAAABQKjk5ORo2bJiGDBnC8HDAyxguDgAAANQwO3fuVGxsrCRpz549uvrqq22OCPAdJNkAAABADXPVVVdp/fr1Sk5OJsEGvIwkGwAAAKghcnJy3HOwe/XqZW8wgI9iTjYAAABQA7z33nu65pprdPToUbtDAXwaSTYAAADg4zIzMzV58mR9+eWXevnll+0OB/BpJNkAAACAj6tdu7Y++ugjTZgwQf/7v/9rdziAT+M72QAAAAAAFMB3sgEAAAC4JScnq3fv3tq5c6fdoQA1Ckk2AAAA4IMeeeQRxcXFacSIEcrJybE7HKDG4BNeAAAAgA+aM2eOTpw4oVmzZrk/2wWg4jEnGwAAAACAApiTDQAAANRwTz31lFatWmV3GECNxnBxAAAAwAfExsbqySeflJ+fn7799ltdfvnldocE1Egk2QAAAIAP6N+/v8aMGaOWLVuSYAM2Yk42AAAA4CPy/tveGGNzJED1x5xsAAAAoIb5+uuv9cILL3gk1yTYgL0YLg4AAABUQ6dOnVL//v119OhR1alTRxMnTrQ7JACiJxsAAAColi655BJNnz5dnTt31ogRI+wOB4ALc7IBAACAaiwrK0uBgYF2hwH4HOZkAwAAAD4uKytLc+bMUVZWlruMBBuoWsqVZBtjxhtjEowxGcaYL40xN5RQv54x5hVjTKLrnH3GmIHlCxkAAACome6//35NnTpVd9xxh92hAChGmZNsY8wdkuZK+oukrpK2SPrQGNOqmPqBkjZKipB0u6R2ksZI+rl8IQMAAAA10x133KF69erpvvvuszsUAMUo85xsY8x2SV9ZljUuX9k+Se9ZljW9iPr3S5oq6XLLsrLLFSRzsgEAAABJ0unTp1WvXj27wwB8XqXMyXb1Sv9W0oYChzZIuq6Y026R9JmkV4wxx4wx3xhjHjPG+F/gOrWNMaF5m6SQssQJAAAA+IoPPvhAJ06ccO+TYANVW1mHizeU5C/pWIHyY5LCizmnjZzDxP0lDZQ0S9JDkmZc4DrTJaXk234qY5wAAABAtbdx40bdeuut+t3vfqekpCS7wwFQCuVdXbzgGHNTRFn+axyXdJ9lWV9alvW2nPO5xxVTX5KelRSWb2tRzjgBAACAaqtFixZq2rSpunbtqgYNGtgdDoD/Z+++46qu+/+PPw4giqI5U1NTQTTTvBxozjJHpTYceZlmwzRzlVsDRIaAuHLmuBzlznKVM80Ux1XucuDeA1ygCCJwOJ/fH347P+1S4SB4GM/77dbt5me8P5/X55YWT98rFZxsvP86kMz/9lo/y//2bv8tAkgyDCP5vnNHgBImk8nZMIzEfzYwDCMBSPj72GQy2VimiIiIiEjWV7lyZXbu3EnhwoVxcNDuuyJZgU1/Uv8vEO8Fmv/jUnPgv49otlIGt88AACAASURBVAOoYDKZ7n9XRSDiYQFbRERERCQni4yM5MiRI9bjkiVLkjt3bjtWJCK2SMtfh30NdDOZTJ+aTKbKJpNpPPA8MB3AZDLNM5lMI++7fxpQBJhoMpkqmkymVoA38M0T1i4iIiIikq3ExMTQokULGjRowB9//GHvckQkDWwdLo5hGEtMJlMRYDhQEjgEtDQM49z/3fI8YLnv/gsmk+l1YDxwgHv7Y08ERj1h7SIiIiIi2YrZbMbFxYVcuXJRrFgxe5cjImlg8z7Z9qB9skVEREQkp7hz5w7nzp2jcuXK9i5FJEd7Kvtki4iIiIhI+jIMg/DwcOtx3rx5FbBFsjCFbBEREREROxo1ahTVqlVj7ty59i5FRNKBQraIiIiIiJ383YudnJxMdHS0vcsRkXSgOdkiIiIiInZksVhYv349LVu2tHcpInIfzckWEREREckiIiMjrb92cHBQwBbJRhSyRURERESeoiNHjlClShWGDBmCxWJJuYGIZCkK2SIiIiIiT1FYWBhRUVGEhYWRkJBg73JEJJ052bsAEREREZGcpEePHhQpUoTXXnsNFxcXe5cjIulMC5+JiIiIiGSwu3fv4uTkhJOT+rhEsgotfCYiIiIikgklJyfTqVMn2rZty507d+xdjohkMP1VmoiIiIhIBjpw4ADr1q3DMAwOHTpEnTp17F2SiGQghWwRERERkQxUo0YNfv31V65du6aALZIDKGSLiIiIiGQAs9lsnYPdoEEDO1cjIk+L5mSLiIiIiKSzlStX4unpyaVLl+xdiog8ZQrZIiIiIiLpKDExkYEDB/LXX3/xzTff2LscEXnKFLJFRERERNKRs7MzmzZtom/fvgQGBtq7HBF5yrRPtoiIiIhIOjAMA5PJZO8yRCSdaJ9sERERERE7uXHjBo0bN2b37t32LkVE7EwhW0RERETkCXl7e7N161Y++ugjkpOT7V2OiNiRtvASEREREXlCY8eOJTo6Gj8/PxwdHe1djojYkeZki4iIiIiIiPyD5mSLiIiIiDxF/v7+LFmyxN5liEgmo+HiIiIiIiI2Wrt2LQEBAZhMJl566SVefPFFe5ckIpmEQraIiIiIiI3eeOMNevfuTYkSJRSwReQBmpMtIiIiIpIGf/8crb2xRbInzckWEREREclAf/75J8HBwQ+EawVsEfknDRcXEREREUnBzZs3adGiBZGRkeTLl49+/frZuyQRyaTUky0iIiIikoKCBQvi5+dHjRo16NKli73LEZFMTHOyRURERERSKSkpiVy5ctm7DBF5CjQnW0REREQkHSUmJhIaGsrdu3et5xSwRSQlCtkiIiIiIg/Ro0cPvLy8eO+998gKoz9FJHNQyBYREREReYjOnTtTuHBh+vTpo1XERSTVNCdbREREROQRYmJi9POnSA6lOdkiIiIiIk9o9erVXLlyxXqsgC0itlLIFhEREREBNm7cSJs2bWjQoMEDQVtExBYK2SIiIiIiQLly5ShTpgx16tShWLFi9i5HRLIoJ3sXICIiIiKSGXh4ePDHH39QsGBBHBzUFyUiaaP/eoiIiIhIjhUZGcnBgwetx88++yzOzs52rEhEsjqFbBERERHJkWJiYmjRogUNGzZk+/bt9i5HRLIJhWwRERERyZEsFgsFChQgT548lCxZ0t7liEg2oTnZIiIiIpIjFSxYkF9++YVz587h7u5u73JEJJtQT7aIiIiI5BiGYTwwBztPnjxUqlTJjhWJSHajkC0iIiIiOUZoaCjVq1dn5syZ9i5FRLIphWwRERERyREMw+DUqVNYLBbu3Llj73JEJJsyGYZh7xpSZDKZCgC3bt26RYECBexdjoiIiIhkUYZhsHHjRl5//XV7lyIimVxMTAzPPPMMwDOGYcSktp16skVEREQkW7t06RJ/dyyZTCYFbBHJUArZIiIiIpJtHTlyhGrVqtG/f38sFou9yxGRHEAhW0RERESyrf/+979ERUXxxx9/cPfuXXuXIyI5gPbJFhEREZFsq2vXrhQpUoSGDRuSN29ee5cjIjmAQraIiIiIZCt3797F0dGRXLlyAdC6dWs7VyQiOYmGi4uIiIhItmE2m+nYsSNvv/02sbGx9i5HRHIg9WSLiIiISLYRHh7Ohg0bSE5O5vDhw7z88sv2LklEchiFbBERERHJNqpVq8Zvv/1GRESEAraI2IVCtoiIiIhkeWazGSenez/aKlyLiD1pTraIiIiIZGkrVqygRo0anD9/3t6liIgoZIuIiIhI1pWUlMTQoUM5dOgQU6dOtXc5IiIK2SIiIiKSdeXKlYtNmzbRv39/goKC7F2OiAgmwzDsXUOKTCZTAeDWrVu3KFCggL3LERERERE7MwwDk8lk7zJEJBuLiYnhmWeeAXjGMIyY1LZTT7aIiIiIZCk3btygUaNG/PHHH/YuRUTkfyhki4iIiEiW4uvry44dO/jkk08wm832LkdE5AHawktEREREspQxY8Zw69YtfHx8rNt2iYhkFpqTLSIiIiIiIvIPmpMtIiIiItnW8OHDWbBggb3LEBFJkcbXiIiIiEimtn79ekaMGIHJZKJ69epUrVrV3iWJiDySQraIiIiIZGqvv/46/fv3p0iRIgrYIpLpaU62iIiIiGQJ2htbRJ4mzckWERERkWxj//79+Pv7c3+HkAK2iGQFGi4uIiIiIplKTEwMLVu2JDIykvz58zNw4EB7lyQikmrqyRYRERGRTKVAgQIEBwdTq1YtunXrZu9yRERsojnZIiIiIpIpmc1mnJw08FJE7ENzskVEREQky0pMTCQoKIj4+HjrOQVsEcmKFLJFRERExO569uyJr68vbdq0ISuMtBQReRSFbBERERGxu48//piiRYvSr18/rSIuIlma5mSLiIiISKYQGxuLq6urvcsQEQE0J1tEREREsphVq1Zx+fJl67ECtkj2ZjabWbp0KUuXLsVsNtu7nAyjkC0iIiIiT93GjRtp27Yt9evXJyIiwt7liMhTsGXLFtq3b0/79u3ZsmWLvcvJMArZIiIiIvLUVahQgXLlytGgQQOKFy9u73JEJIMYhkFcXBxxcXF8//331vPff/+99XxWmMJsC83JFhERERG7uH79OgUKFMDZ2dnepYhIBjlz5gxubm4p3lOuXLmnU5ANNCdbRERERDK1yMhI9u/fbz0uWrSoArZINrdjx44U79m+fftTqOTpUcgWERERkQx369Yt3nzzTV555ZVsPRdTRB7Uvn17goODH3k9JCSE9u3bP8WKMp5CtoiIiIhkOJPJRJEiRciXLx9lypSxdzki8pScPXuWvXv3PvL6l19+Se7cuZ9iRRnPyd4FiIiIiEj2V6BAAdauXcv58+dxd3e3dzkiksHOnTtHYGAg3333HRaLxd7lPFUK2SIiIiKSIQzD4M8//6RGjRoA5M6dGw8PDztXJSIZ6cqVK4SEhDB9+nQSExMBePvtt2nUqBFLlizh008/BWDOnDkMGTKEvHnz2rPcDKHVxUVEREQkQ4SEhDBs2DAmT55M79697V2OiDwFtWvXZs+ePQA0adKE4OBg6tata+eq0kari4uIiIhIpmEYBhcvXsQwDJKTk+1djohkkNjYWBISEqzHQ4cO5eWXX+bXX39l06ZNWTZgPwn1ZIuIiIhIhjAMg99++42mTZvauxQRSWcJCQnMmDGD4OBgvL296du3L3Dvzz3cW+wwq1NPtoiIiIjY3YULFx74IVsBWyR7MZvNzJ49Gw8PD/r27cvVq1dZsmTJA3/uHxWw4+LirNfj4uKeZtlPlUK2iIiIiKSLI0eOUL16dXr16qUh4iLZjMViYcmSJVSpUoVu3bpx4cIFSpUqxYwZMwgLC8sWPdfpRauLi4iIiEi62LVrF9HR0ezfv5+EhIRsuWqwSE41YMAAJk6cCEDRokXx8vKiZ8+euLi4pNj2717r+3uv7/91vnz50rla+9KcbBERERFJN6tXr6Zu3boULVrU3qWIyBNKSkoiV65cAPz111+8+uqrDBw4kH79+pE/f/5UPyelXu7MmknTOidbIVtERERE0iw+Ph4HBwdy585t71JEJJ3s3r0bHx8f3N3dmTZtmvV8XFxcmnqdc1rI1pxsEREREUkTs9lMp06daNmyJTExqf75U0QyqcOHD9O2bVvq1KnDxo0bmTdvHtHR0dbrtgbso0eP0qlTJ+txgwYNrL++cuUKsbGxxMbGPnnhmYxCtoiIiIikydGjR/n111/ZsWMH4eHh9i5HRNLo9OnTfPTRR7z00kusWLECBwcHPv74Yw4dOkShQoVsft6xY8f44IMPePHFF1m8eDEAbdu2ZezYsdZ78uXLZ/0nu9HCZyIiIiKSJlWrVmXLli1cvHiRunXr2rscEUmD5cuX06FDB8xmMwDt2rUjMDCQF1980eZnHT9+nMDAQBYvXozFYgGgTZs2DB8+nOrVq2frbbvupznZIiIiImKT+xdDEpGsxzAM6zzp69ev4+bmRv369QkKCsLT09Pm5x0/fpygoCAWLlxoDdfvvvsufn5+1KhRI11rf5o0J1tEREREMtyKFSuoVq0aZ86csXcpImKjmJgYAgICaNOmjXWxsaJFixIeHs769ettDtgnTpzg448/pnLlysyfPx+LxcI777zD3r17WblyZZYO2E9CIVtEREREUsVsNuPt7c3Ro0eZPn26vcsRkVSKj49n3LhxuLm54e/vz08//cT27dut10uXLp2m5/r6+jJv3jwsFgtvv/02e/bs4aeffqJmzZoA9O/fn99++y1dviErUcgWERERkVRxcnJi06ZNDB48mODgYHuXIyIpSEpKYvr06VSoUIFBgwZx48YNKlWqxA8//PDASt+pderUKS5dumQ99vX15a233mL37t38/PPP1KpVy3ptxYoVTJgwgaZNm9KzZ09u376dLt+UFWhOtoiIiIg81v3zN0Ukazh58iRvvPEGp0+fBuD555/H39+fDz/8ECcn29e/njhxIgMHDuTjjz9m9uzZKd5/+/btB7Jb2bJlmTNnDk2aNLH53faiOdkiIiIiku5u3LhB/fr12bp1q71LEREblC1bFkdHR4oXL87kyZM5fvw4Xbp0sSlg398hW6dOHZKTk7l27Zp1cbPHyZ8//wPH586dyzG92urJFhEREZFH+uKLL5gyZQoeHh6Eh4enqQdMRDKWYRhs2rSJadOmsWjRInLnzg3A4cOHKVeunM17UZ85c4bg4GCKFCnCqFGjrOfDw8Nt2trrUSNgSpUqxbx58zJ9r7Z6skVEREQk3Y0ePZqPP/6YlStXKmCLZEK///47TZs2pXnz5ixfvpxZs2ZZr1WpUsWmgH327Fk+++wzKlasyOzZs5k0aRJRUVHW62nZO/thbt26lS7PyawUskVERETkkVxcXPjuu+/S7YdrEUkff/31F2+//Tb169dn8+bNODs7069fP9q3b2/zs86dO0f37t3x8PBg1qxZmM1mXn/9dTZt2kThwoXTte4iRYowffr0TN+L/SQUskVERETkAb6+vsyZM8feZYjIQyQmJtKxY0eqV6/O6tWrcXR0pGvXrpw4cYLx48fz7LPPpvpZ58+fp0ePHnh4eDBz5kzMZjPNmzdn+/bt/PLLL9SvXz9NNZ44cYKPPvrogXPOzs4EBQVx7do1PvjggzQ9N6vQmB8RERERsdqwYQNBQUEAeHp6Uq1aNTtXJCL3c3Z2tg637tChAwEBAVSqVMmmZ5w/f56RI0cye/ZskpKSAGjWrBl+fn40bNgwzbUdOnSIkJAQlixZ8sDiaO+88w7z58/PMetraeEzEREREbEyDAMfHx9cXV3x9va2dzkiOd7Vq1cZNWoUgwYNomTJkgAcOXKEhIQEqlevbtOzLl68SEhICLNmzbKG66ZNm+Ln50ejRo2eqE5fX1/rX9ABtGrVCldXV7p3755lh4andeGzNPVkm0ymXsBgoCRwGOhnGMa2VLR7H1gM/GQYRuu0vFtEREREMo7JZCIkJMTeZYjkeDdv3mTcuHGMHz+euLg4EhMTmTx5MgCVK1dO0zO3bt3KtGnTAGjSpAl+fn688soraa4xOTkZR0dHAOrVq4fJZKJdu3Z4e3tTo0aNND83q7N5TrbJZOoATACCgRrANmCdyWR6PoV2ZYGx/3e/iIiIiGQS+/fvx8fHJ1V734pIxoqLi2PUqFG4ubkRFBREXFwcnp6evPvuuzY/69KlS4SFhVmPO3ToQJcuXdiyZQubNm1Kc8DesWMHr7zyCsHBwdZzLVq04NixY/z44485OmBDGoaLm0ymncA+wzB63nfuCLDSMAyvR7RxBMKAb4FGQEFberI1XFxEREQkY9y+fZuKFSsSGRlJaGgoQ4cOtXdJIjnWzJkzGT58OJGRkcC9LbOCgoJo3br1I/ecfpTt27fTtGlTihYtyqlTp8iTJ0+61blkyRLef/99SpQowfnz58mVK1e6PTszeSr7ZJtMJmegFrDhH5c2AI9bem44cM0wjNm2vE9EREREMlb+/PkZM2YMnp6e9OjRw97liORoR44cITIykvLlyzNv3jwOHDhAmzZtUh2wzWaz9de1a9emePHiuLu7c/Xq1TTXZDabWbRoEQsXLrSee++99wgMDGTPnj3ZNmA/CZt6sk0m03PAJaCBYRj/ve+8N/CxYRj/s6ydyWRqACwBqhuGcd1kMn1HCj3ZJpMpN5D7vlP5gYvqyRYRERHJGPfPrRSRjGexWFi2bBkVKlSwDq++du0aS5cupWvXrjg7O6f6WREREYSGhrJ582b27duHk9O9pbciIyMpXry4zb3gcG+rsHnz5hEaGsqpU6coWbIkp0+fTtce8czuqfRk3+efydz0kHOYTKb8wALgM8MwrtvwfC/g1n3/XExjnSIiIiLyD4mJifj7+xMXF2c9p4At8nQYhsG6devw9PTk3//+N0OGDLFeK1asGD179kx1wI6IiKBfv364ubkxadIkDh48yNq1a63XS5QoYXPAjo+PZ/LkyVSoUIHPPvuMU6dOUaRIEXr16qV1G1LJ1tXFrwPJQIl/nH8WuPKQ+92BcsCq+/7lOgCYTCYzUMkwjFMPaTcS+Pq+4/woaIuIiIiki169ejF79my2b9/Oxo0b09TLJSK227ZtG97e3mzfvh0AV1dXGjRoYPNIksjISEaNGsX06dO5e/cucG9174CAAJo1a5am2m7fvs20adMYN26cdXh5iRIlGDx4MN27d8fV1TVNz82JbArZhmEkmkymvUBzYMV9l5oDPz2kyVHgpX+cC+JeaO4LXHjEexKAhL+P9R9+ERERkfTTtWtXVq9ezeDBg/VzlshT8Oeff+Ll5cX69esByJMnD7179+arr76iaNGiqX7OlStXGD16NNOmTSM+Ph6AunXrEhAQQPPmzdP05zkqKopJkyYxadIkoqOjAShbtixDhw6lS5cuOWp4eHpJyz7ZXwPzTSbTHuB3oDvwPDAdwGQyzQMuGYbhZRjGXeDQ/Y1NJtNNAMMwHjgvIiIiIk9HvXr1OHXqFPny5bN3KSI5ws6dO1m/fj1OTk5069aNYcOGUapUqVS3v3LlCmPGjGHq1KnWcP3yyy8TEBDA66+/nqZwfeXKFb7++mumTp1KbGwsABUrVsTb25tOnTppQbMnYHPINgxjiclkKsK9FcNLci9EtzQM49z/3fI8oMH6IiIiIpnIypUrqVWrFmXKlAFQwBbJQGfPnuXSpUs0aNAAgE8//ZSjR4/Sp08f3N3dU/2cqKgoRo4cyTfffGMN13Xq1CEgIIA33njjiUaizJ07l9GjRwNQrVo1fHx8aNeundZnSAc275NtD9onW0RERCTtNm7cSMuWLSlRogQ7d+7kueees3dJItlSREQEwcHB/Oc//6F06dIcPXrUplXC/+nq1auUK1eO+Ph4ateuTUBAAG+++WaawvXJkye5efMmnp6ewL2Vs9u3b88XX3xBq1atNHXkIdK6unhahouLiIiISBZSsWJFKlSoQK1atShR4p/r14rIk4qKimL06NFMmjTJ2uPs7u7OjRs3KFmyZKqfc/36dZYvX0737t0BePbZZxk3bhxly5alRYsWaQ7CP/zwAx07dqR69ers2bMHk8lEgQIF+OWXX9L0PHk8hWwRERGRbK5s2bLs2LEDV1dXHBzSuoOriPzT7du3mThxImPGjCEm5l5HZ7169QgODua1116z6VmxsbFUrFiR6OhoXnzxRRo2bAhAz54901RbfHw8Li4uADRp0gQXFxdKlChxf++sZBD9V1ZEREQkG4qIiGD37t3W48KFCz/RsFUR+V/79u3D19eXmJgYqlWrxqpVq9ixY0eqA/b9e9W7urrSvn17atas+URDt7dt28abb77Jm2++aT1XtGhRTp48yZo1axSwnwLNyRYRERHJZm7dusWrr77KiRMn+Pnnn2natKm9SxLJFpKSkvjrr7+s85oBevTowWuvvUb79u1TPVIkKiqKcePGMWXKFLZu3cq//vUvAO7cuYOLi4vNIdswDDZu3EhwcDBbt24FwNHRkSNHjuDh4WHTs+T/S+ucbPVki4iIiGQzjo6OlChRgvz581O+fHl7lyOS5VksFhYvXsyLL75I48aNuXLlivXa9OnT6dChQ6oCdlRUFMOGDaNcuXKEhIQQExPDvHnzrNfz5s1rU8C2WCysXLmSOnXq8MYbb7B161acnZ3p3r07x48fV8C2E83JFhEREclmXF1d+fnnnzl//jxubm72LkckyzIMg9WrVzNs2DAOHDgAQLFixTh69CjFixdP9XOio6MZP348EydOtM7d/te//oW/vz/vvvuuzXUlJyfzww8/EBISwqFDhwBwcXHh888/Z9CgQTbtwS3pTyFbREREJBswDIO9e/dah7E6OztToUIFO1clknVt3rwZb29v/vjjDwCeeeYZBg8eTN++fXF1dU3VM6Kjo5kwYQITJkywhutq1apZw7WtCxEmJiYyf/58QkNDOXnyJAD58+enT58+9OvXj2effdam50nGUMgWERERyQZGjhyJj48PX3/9Nf3797d3OSJZWmRkJG+88QZJSUnkzZuXvn37MmjQIAoXLpyq9jdv3rSG61u3bgHw0ksv4e/vT+vWrdO0yv/GjRvp2rUrFy5cAO4tZtivXz/69OlDoUKFbH6eZByFbBEREZEszjAMrl69CoCTk368E0mLCxcuUKZMGQBKlChB3759SUhIwNvbO9X7yycnJxMUFMT48eOt4bpq1ar4+/vTpk2bJ9pC77nnnuPChQuUKFGCQYMG8fnnn6e6R12eLq0uLiIiIpINGIbB1q1befXVV+1dikiWcvLkSfz9/Vm8eDG7du2iVq1aT/S8Zs2asWnTJqpWrYqfnx9t27a1OVxHR0czadIkbt68yfjx463n165dS5MmTciTJ88T1Sipk9bVxRWyRURERLKos2fPUrZs2SfaU1ckp7p06RIjRoxg9uzZmM1mAEJDQxk6dGiqnxETE8PkyZP57LPPrPOh9+zZw5kzZ2jXrl2ae6537drFyy+/jKOjI6dOnaJs2bJpeo48GW3hJSIiIpKDhIeHU7NmTbp162YNCCKSsmvXrjFw4EDc3d2ZMWMGZrOZFi1asHfvXpsCNkD79u0ZNmwYY8aMsZ7z9PS0ac9suDdUfenSpdbjOnXq0KdPHxYuXEjp0qVtqknsT5N2RERERLKg/fv3c+vWLQ4fPkxiYqLmYoukgsVioWHDhhw/fhyARo0aERISQsOGDVPVPiYmBgcHB+tc6L59+3L+/Hnq1q2bpnpOnTpFaGgoc+fOxdHRkUaNGlm3Bps8eXKanin2p55sERERkSzogw8+YM2aNaxevZq8efPauxyRTOvOnTtYLBYAHBwc+PLLL6lZsybr168nLCwsVQH79u3bhISEUL58+QfmSLdo0YJDhw7Rrl07m2o6fPgwH3zwARUrVmTWrFkkJSVRr149bt68advHSaakOdkiIiIiWUR8fDwmk0mLHomkQmJiIrNmzSIoKIhx48bRsWNHAMxmM46Ojqlay+D27dtMmTKFsWPHEhUVBUDdunX573//m6a1EPbu3UtwcDArVqywnmvZsiU+Pj7Ur1/f5udJxtKcbBEREZFszGw28/777/PGG2+ot0vkMZKTk5k3bx6VKlWid+/eREREMGfOHOt1JyenFANybGwso0aNonz58nh7exMVFYWHhwfz589n+/btNgfs7du306JFCzw9PVmxYgUmk4n33nuPffv2sWbNGgXsbEaTd0RERESygBMnTrBlyxYSEhI4cuQI9erVs3dJIpmKYRisWLECX19fwsPDAShevDi+vr5069YtVc+IjY1l6tSpjBkzhuvXrwNQoUIFhg8fTseOHW1a+8AwDDZu3EhwcDBbt24FwNHRkU6dOuHl5UXlypVt/ELJKhSyRURERLKAypUrs3XrVs6fP6+ALfIQ3bt3Z9asWQAUKlSIoUOH0qdPH/Lly5di27i4OKZOncro0aMfCNe+vr506tQpTQsLrl+/npYtWwLg7OzMJ598wtChQ3Fzc7P5WZK1aE62iIiISCaWkJBA7ty57V2GSKZksVisW2Vt2rSJd999lwEDBjBgwAAKFiyYqmfMnj0bLy8vrl27BoC7uzu+vr588MEHNoXr5ORkTp06RcWKFa3HtWvX5tVXX2XQoEGUKlXKxq8Te0vrnGz1ZIuIiIhkUsuXL2fo0KGsXbsWDw8Pe5cjkmns37+fYcOGUbt2bfz9/QFo2rQpFy5coFChQjY9Kz4+nmvXruHm5oavry+dO3e2uef6+PHjtGrVitjYWM6cOUOePHlwdHRkz549Nu2XLdmD/o2LiIiIZEJms5nhw4dz8uRJZs6cae9yRDKFY8eO0aFDB2rWrMnatWuZNGkS8fHx1uspBew7d+4wfvx4Vq5caT3XrVs35s6dy9GjR/nkk0/SNDS8XLlyJCQkkJiYyOHD6tJrwAAAIABJREFUh63nFbBzJg0XFxEREcmkrly5woQJEwgKCsLR0dHe5YjYzblz5wgMDOS7777DYrFgMpno2LEj/v7+No3yGDt2LIMHD6ZSpUocPnw4TX+ubt++zfTp01m5ciVhYWHWUL5//348PDxwdXW1+ZmSOaV1uLhCtoiIiEgmYhhGmvbfFcmuFi1aRJcuXUhMTATgnXfeYcSIEVSrVi3FtvHx8URERFgXG4uJiaFJkyb06NHD5l7r6OhoJk+ezIQJE4iOjgZg8eLFvP/++2n4KskKtE+2iIiISBZ3/fp1Xn75ZX777Td7lyKSadSrVw/DMHjttdf4/fff+emnn1IM2PHx8UycOBE3Nzc6dOjA3x2LBQoUYPfu3XTr1i3VAfvq1at89dVXlC1bFj8/P6Kjo/Hw8ODbb7+lXbt2T/x9kv1o4TMRERGRTCIoKIjdu3fz+eefEx4eTq5cuexdkshTFRsby6RJkzh//jzTp08HoHz58hw6dMi6avfj3L17l5kzZzJy5EgiIiKAe9tnXbp0idKlSwOkeqTIxYsXGTNmDDNnzrTO+65WrRre3t689957msIhj6SQLSIiIpJJhIaGEhcXx4ABAxSwJUdJSEhgxowZBAcHc/XqVQD69OlD1apVAVIM2Hfv3mXWrFmMHDmSy5cvA1CmTBl8fHzo0qULzs7Oqa7l1KlThIaGMnfuXJKSkgCoU6cOw4YN46233tJ0DkmRQraIiIhIJpEnTx6tJC45itlsZt68efj7+3PhwgXg3j7VgYGBvPjiiym2T0hIsIbrS5cuAVC6dGlruLZlj/lLly4xdOhQFi9ejMViAaBx48b4+PjQtGlThWtJNYVsERERETvy8fGhTJky9OjRw96liDxV4eHhtGnThuPHjwNQqlQphg8fTpcuXVIcyZGQkMDs2bMZOXIkFy9eBO6Fa29vbz799FObwvXfcufOzYoVK7BYLLRo0QIfHx8aNGhg+4dJjqfVxUVERETsZNOmTTRr1gyAffv2UaNGDTtXJPL0xMXF4ebmRnJyMt7e3vTs2RMXF5cU223ZsoWPPvrI2vNdqlQpvLy86Natm03hevv27axevZrQ0FDrufnz51OlShVq1qxp+wdJtqMtvERERESyGMMwCAgIIHfu3Hh5edm7HJEMFRYWxoIFC5gxYwYODvc2Odq5cyeVK1e26Wf806dPU6lSJZ599llruM6TJ49NtVy9epXSpUuTlJTEtm3baNiwoU3tJWdQyBYRERERkUxnz549+Pj4sGHDBgB++OEH2rdvn6q2iYmJfPfddxw5coTx48dbz2/atIkGDRqkOlxbLBZ27txJvXr1rOe++OILEhIS8PHxoWzZsjZ8keQUCtkiIiIiWcC+fftYvHgxoaGh2gJIsrXDhw/j6+vLihUrAHBycqJ79+74+Pjw3HPPpeoZhw4d4qWXXgLgwIED1l+nVnJyMj/++CMhISEcPHiQ/fv3U716deDeSBItZiaPk9aQrYXPRERERJ6S2NhYWrVqRWRkJAULFsTHx8feJYmku9jYWHr16sWCBQusQfbDDz/Ez88PNze3x7ZNSkpi586d1uHbVatWpXfv3nh4eFChQoVU15CYmMiCBQsIDQ3lxIkTAOTPn5+jR49aQ7YCtmQU9WSLiIiIPEU//PAD48aNY8OGDX/3kIhkK4ZhULt2bfbu3Uvbtm0JDAykSpUqj22TlJTE/PnzCQoK4sKFCxw/fpzy5cvb/O74+HjmzJnD6NGjOX/+PACFCxemX79+9OnTh0KFCqXpmyRn0nBxERERkSzCYrFYF34Syepu3LjBhAkTGDJkCPnz5wdg165dODg44Onp+di2SUlJLFiwgKCgIE6fPg1A8eLFmT9/Ps2bN091DbGxsUyfPp2xY8dy5coVAEqUKMGgQYP4/PPPcXV1TePXSU6m4eIiIiIimVBiYiIjRox4IIAoYEt2cPv2bcaPH8/YsWO5ffs2zs7O+Pr6AlCnTp3HtjWbzdZwferUKQCeffZZhg4dSo8ePcibN2+qaoiOjmby5MlMnDiRqKgoAJ5//nmGDh3Kp59+avOq4yLpQSFbREREJAP17t2bWbNmsW3bNjZv3qx5oJLlxcfHM3XqVEJDQ7l+/ToA1atX5+WXX06xrdlsZuHChYwYMcIarosVK8aQIUPo2bMn+fLlS3UdkZGRVKxYkdu3bwPg4eGBl5cXnTt3JleuXGn4MpH0oZAtIiIikoG6d+/O2rVr8fLyUsCWLG/mzJn4+/tz+fJlACpVqsSIESNo167dY0domM1mFi1axIgRIzh58iQARYsWZciQIfTq1SvV4To2NtY69LtEiRLUrVuXyMhIfHx8eO+997Riv2QKCtkiIiIiGah27dqcPHkSFxcXe5ci8sS2bNnC5cuXef755/H39+fDDz/EyenxkeLy5cs0btzYusp30aJFGTx4ML169Ur1XOm7d+/y5ZdfsmTJEo4dO0aJEiUA+P777ylYsKCmYEimot+NIiIiIuls+fLlnD171nqsgC1ZkWEY/PTTT9Zh3QABAQFMmjSJ48eP06VLlxQDNkDJkiUpUKAARYoUITQ0lDNnzjBkyBCbFiPLnTs3Bw8eJCYmhuXLl1vPFy5cWAFbMh2tLi4iIiKSjjZu3EjLli0pVqwYu3btonTp0vYuScRmmzZtwtvbm127dvHBBx+wYMGCVLVLTk5myZIlTJ06lXXr1lkX+zt+/DglS5a0Hqdk7969jBs3jm+++ca67dYff/yB2Wy27qEtktHSurq4/tpHREREJB29+OKLvPDCCzRp0oTnnnvO3uWI2OT333+nSZMmNGvWjF27dpE3b17Kly9PajvmDMMgICCAHTt2MG3aNOv5ihUrpipgb9++nRYtWuDp6cnixYuZMmWK9VrdunUVsCVL0JxsERERkXRUqlQptm/fjouLi4axSpZx4MABhg0bxqpVqwBwdnamZ8+eeHl5Ubx48Ue2S05OZsWKFbz11lvkyZMHJycnQkJCOHr0KD169EjVuw3D4NdffyU4OJiwsDDg3jZ3HTt2pF27dk/+cSJPmUK2iIiIyBOKiIjg7Nmz1KtXD+Dv4YUiWcbKlStZtWoVDg4OdOnSheHDh/P8888/8n6LxcKPP/5IYGAg4eHhTJkyhd69ewOkOhhbLBZWrVpFcHAwu3fvBiBXrlx88sknDB06FHd39yf/MBE7UMgWEREReQK3bt2iRYsWHDt2jJUrV/LGG2/YuySRFF24cIHo6GiqVasGQP/+/Tl37hxDhgyhUqVKj2xnsVhYunQpgYGBHD58GICCBQva9O7k5GR+/PFHQkJCOHjwIAB58uShe/fuDBo0iDJlyqTxq0QyB4VsERERkSeQK1cuypQpQ2RkJB4eHvYuR+Sxrl69ysiRI5k6dSrVqlVj165dmEwm8ufPz+zZsx/ZzmKxsGzZMgICAqzh+plnnmHAgAF8+eWXqQraZrOZ+fPnM3LkSOt2Xvnz56dXr17079//scPSRbIShWwRERGRJ5A3b15WrFjB+fPncXNzs3c5Ig918+ZNxo0bx/jx44mLiwMgX758REdHU7hw4Ue2s1gsLF++nICAAA4dOgRAgQIF6N+/P/369bOpF9tiseDn58eFCxcoVKgQ/fr144svvrCuHi6SXShki4iIiNjIMAx27txJ3bp1AXByclLAlkwpLi6OKVOmMGrUKKKjowHw9PQkJCSEZs2aYTKZHtrOYrGwcuVKAgICOHDgAHAvXPfr149+/fqlKhjHxsYyb948unfvjpOTE87OzgQHBxMZGUmPHj1SvZ2XSFajkC0iIiJio+DgYHx9fRk1ahRDhgyxdzkij7Ru3Tq++uor4N72ckFBQbRu3fqR4Rru/SVS06ZN2bJlC3BvSHe/fv3o379/qnudDcOgTp06HDlyhAIFCtC5c2cAPvzwwyf7IJEsQPtKiIiIiNjAMAxu374NgIuLi52rEXmQ2Wzm6NGj1uO2bdvSpk0b5s2bx4EDB2jTps1DA7ZhGNa9sE0mE6+99hr58+dn2LBhnD17lsDAwBQD9rVr17BYLNZnfPjhh3h4eODq6pqOXyiS+ZlSu7G8PZlMpgLArVu3blGgQAF7lyMiIiLCjh07aNCggb3LEAH+/9xpX19foqKiOH36NPny5UtV2zVr1uDr60tISAhvvvkmALdv3yYxMZEiRYqk2P7ixYuMHTuW//znPyxatIjWrVsDkJCQgJOTE46Ojmn/MBE7iomJ+XtLxmcMw4hJbTv1ZIuIiIikwunTp629dIACtmQKhmGwfv16ateuTfv27Tl69Chms9m6NVZqbN68mf379zNmzBjrufz586cYsE+dOkX37t1xc3Nj4sSJxMfHs3r1auv13LlzK2BLjqSQLSIiIpKCw4cP4+npySeffEJSUpK9yxEBYNu2bbz66qu0aNGCffv24erqip+fH2fOnLEuyvdPhmGwevVq9u3bZz03ePBgvL29WbJkSareGx4ezocffkjFihWZOXMmSUlJvPLKK2zYsIGZM2emy7eJZGVa+ExEREQkBYcPHyYmJoYTJ06QlJRErly57F2S5HCnTp3ilVdeASBPnjz07t2br776iqJFiz70fsMwWLNmDf7+/uzdu5fmzZuzYcMGAIoXL05wcHCK79y3bx/BwcGsWLHCOn/7zTffxMfHh4YNG6bTl4lkfQrZIiIiIin497//TeHChalRowZ58+a1dzmSQ127do1ixYoB4O7uTufOnXF1dWXYsGGUKlXqoW0Mw2Dt2rX4+/uzZ88e4N7+2DVr1iQ5OTlVw7l37NhBcHAw69ats55r06YNPj4+1KpVKx2+TCR70cJnIiIiIg8RHx+PYRgK1WJ3Z8+exd/fnyVLlhAeHk758uWBewH6UVtxGYbBunXr8Pf3Z/fu3QDkzZuX3r17M3jwYGtYfxyLxULLli355ZdfAHBwcKBjx454eXlRpUqVdPo6kcxLC5+JiIiIpBOz2cz7779Ps2bNuHHjhr3LkRwqIiKCPn36ULFiRebOncvdu3dZtWqV9fqjtuJav3499erVo1WrVuzevRsXFxcGDRrEmTNnGD169GMD9v0dcA4ODpQtW5ZcuXLRrVs3jh07xoIFCxSwRVKgnmwRERGRfzh27Bj16tXjzp07bN68mXr16tm7JMlBoqKiGD16NJMmTSI+Ph6AZs2aERwcTJ06dR7axjAMNmzYgL+/P3/88Qdwbx/3Xr16MXjwYIoXL57ie5cuXUpQUBDffvstNWrUAODy5cskJydTpkyZdPo6kawjrT3ZmpMtIiIi8g+VKlVi27ZtnD17VgFbnqqkpCSqV6/OhQsXAKhXrx7BwcG89tprj23n7e1NaGgocG8htF69ejFkyJBUheu/LV++nL/++otx48axYMECAJ577rk0folIzqWebBEREZH/c/fuXfLkyWPvMiSHSUxMxNnZ2Xrs7+/PihUrCA4OplWrVo8cFp6QkGD9/frnn39Sv359evTowZAhQyhRosRj33n37l3mzJlD8+bN8fDwAO6tor9s2TK++OILChUqlI5fKJI1pbUnWyFbREREBFi2bBmDBw9m7dq1vPDCC/YuR3KApKQkvvvuOwIDA/nuu+9o2rQpAAkJCeTKlQsHh4cvn7R792769+9P1apVmT59uvX8zZs3KViw4GPfGRsby/Tp0xk3bhyRkZF06dKFOXPmpN9HiWQjWvhMREREJI2Sk5MJDAzkzJkzzJ49297lSDZnsVj4/vvvqVKlCt27d+fixYtMmTLFej137tyPDNhwrxd6x44dLFq0iJiY//9z/+MC9s2bNxkxYgRly5Zl8ODBREZGUqZMmUfO8RaRtFPIFhERkRzP0dGRTZs24ePjY53XKpLeDMNg1apV1KhRg44dO3LixAmKFSvG+PHjWbx48SPbbdmyhVmzZlmPGzVqxKRJkzh69GiKozyvXbuGt7c3zz//PMOHDycqKooKFSowa9YsTp48SY8ePdLt+0TkHg0XFxERkRzLYrE8tsdQJD117tyZhQsXAvDMM88wePBg+vbti6ur60PvDwsLw8/Pj7CwMPLmzcuZM2d49tlnU/WuixcvMnbsWP7zn/9YVyivWrUq3t7etG/fHicnrX8skhINFxcRERGxwfXr16lTpw6//PKLvUuRbOz+Dq1WrVrh4uLCV199xenTp/Hx8XlowN66dSuvvfYajRs3JiwsDGdnZ7p06fLQBdD+6fTp03z++ee4ubkxceJE4uPjqV27NitXruSvv/6iY8eOCtgiGUw92SIiIpIjDRw4kK+//hp3d3fCw8MfWN1Z5EkdOnQIX19fmjdvTq9evYB7IyeuXbv2yG21tm3bhp+fH5s3bwbA2dmZbt264eXlRenSpVP13ldeeYVt27ZZf+3j40Pz5s1TFdBF5EHaJ1tERETEBiNHjiQ+Pp4vv/xSAVvSzalTp/Dz82PRokUYhsHu3bvp3r07Tk5OODg4PDRgb9++HX9/fzZt2gRArly5rOG6TJkyj33f/v37KV++vHXRs6+++op8+fLh4+NDw4YN0/8DRSRF6skWEREREXlCly5dYsSIEcyePRuz2QxA+/btCQgIoHLlyg9ts2PHDvz9/fn111+Be+G6a9eueHl58fzzz6f4zgEDBjB+/HgCAwPx9fVNv48REUA92SIiIiIp8vLyomTJknz55Zf2LkWykTlz5tC7d2/u3r0LQIsWLQgKCqJmzZqPbLNu3TpatmwJ3AvXn376KV5eXpQtW/aRbQzDwGKx4OjoCECdOnVwcHDg6tWr6fg1IvKk1JMtIiIiOcLmzZtp0qQJAHv27KFWrVp2rkiyi7179+Lp6UnDhg0JCQmhUaNGD70vKiqKwoULA2A2m/nXv/5Fw4YN8fb2TjFcr169muDgYDp06ED//v2Be/u7nz17Fnd39/T/KBFJc0+2QraIiIjkCIZhEBISgoODA15eXvYuR7KoO3fu8M033xAbG0tAQID1/L59+6hRo8ZDFxi7dOkSXbt25ciRI5w4ccK6BkBiYuJj1wNITk5m2bJlBAcHc+DAAQDc3d05fvy4tp4TeQoUskVEREREMkhiYiKzZ89mxIgRRERE4OzszIkTJ1I1dzo+Ph53d3euXr3Kr7/+SuPGjR97f1JSEgsXLiQ0NJRjx44B4OrqSu/evenfv/8jVycXkfSlfbJFRERE/mHfvn307dvXuhCViK2Sk5OZN28eL7zwAr169SIiIoKyZcsyY8YMnnvuuYe22bVrFz169CA5ORkAFxcX5s+fz/Hjxx8bsO/evcu0adPw8PCgS5cuHDt2jEKFChEQEMD58+cJDQ1VwBbJArTwmYiIiGRLcXFxvPXWW0RERFCkSBGGDx9u75Iki/nzzz/54IMPCA8PB6B48eL4+vrSrVs3cufO/T/37969G39/f9auXQvAq6++SseOHQFo2rTpI98TFxfHjBkzGDt2LBEREdZ3DRw4kB49epA/f/70/jQRyUAK2SIiIpIt5cuXjylTpjB27Fj69etn73IkCypZsiTnzp2jUKFCDB06lD59+pAvX77/uW/Pnj34+/uzZs0aABwcHPjwww+pU6dOiu+YMmUK/v7+3LhxA4AyZcowZMgQunbtiouLS/p+kIg8FQrZIiIikm21bduW1q1ba5EoSZUdO3awevVqRo4cCdzrTV65ciWenp4ULFjwf+7fu3cvAQEBrFq1CrgXrjt37sywYcPw8PBI1TtjY2O5ceMGFSpUwMvLi86dOz92MTQRyfz0fxwRERHJNhITE/H29ubWrVvWcwrYkpI///yTt956i4YNGxIaGkpYWJj1WrNmzf4nYO/bt493330XT09PVq1aZe25Pnr0KHPnzn1kwL548SL9+/dn9erV1nO9evVi0aJFHDlyhE8//VQBWyQb0P91REREJNvo06cPI0eOpFWrVmSFHVTEvo4dO0aHDh2oUaMGa9aswdHRkW7duj1y3+n9+/fTunVratWqxc8//2ztuQ4PD2fevHkp9l5Pnz6dCRMm4O/vb/39WaBAATp27IiTkwaYimQX+tMsIiIi2UbPnj1Zv349w4cPf+h+xSIAN2/eZODAgXz33XdYLBYAOnbsSEBAwCOD8s2bN2nQoAHx8fGYTCY6derEsGHDeOGFFx75niNHjpCUlES1atUA6Nu3L7t372bAgAHp/1Eikmlon2wRERHJVu7evUuePHnsXYZkYomJibzwwgucOXOGd955hxEjRliD8P1Onz6Nm5ub9XjgwIFERkbi6+v72HC9f/9+QkJCWLZsGa+++iqbN2/OkO8QkYylfbJFREQkR1q2bBmnTp2yHitgyz9FR0czatQokpKSAHB2dmbGjBn8/vvv/PTTT/8TsC0WCx06dMDd3Z2dO3daz48dO5aFCxc+MmD/97//pVWrVtSsWZOlS5diGAYFCxYkPj4+4z5ORDIdhWwRERHJsn799Vfef/996tevz/nz5+1djmQysbGxhISE4ObmxldffcW3335rvda8eXPq1q370HYODg7ky5cPk8nE1q1brecfNgXBMAw2bdpEkyZNaNCgAWvXrsXBwYFOnTpx8OBBVqxYoa24RHIYhWwRERHJsqpWrUrVqlV5/fXXKV26tL3LkUwiISGBSZMm4e7ujo+PDzdv3qRq1aqUK1fuofcfOnSIf//73xw+fNh6LiAggIMHDzJ48OCHtjEMg9WrV1OvXj2aNWvG5s2byZUrF127duXYsWMsXLiQqlWrZsTniUgmp4XPREREJMsqUaIEYWFhuLi4aKsuwTAMvv32WwICAqwjG9zd3QkMDKRDhw44Ojo+cP/hw4cJDAzkxx9/xDAMTCYTS5YsAaBMmTIPfUdycjLLli0jJCSEv/76C7g3ReGzzz5j8ODBj2wnIjmHQraIiIhkKZcvX+bkyZO88sorAFoUVaxMJhOLFy/m/PnzlCpViuHDh9OlSxdy5cr1wH3h4eEEBgbyww8/WLfSeu+99xg2bFiK7xgyZAhff/01AK6urvTq1YsBAwZQvHjx9P8gEcmStLq4iIiIZBm3bt3ilVde4ejRoyxbtoy33nrL3iWJHRmGwbp166hduzbFihUDYM+ePYSFhdGrV6//mQt95MgRAgMDWbJkiTVct2vXDj8/P1566aWHvuPu3bvExcVRpEgR4N7Q8saNG/PFF1/wxRdfULhw4Qz8QhGxJ60uLiIiItle7ty5qVChAoULF6ZKlSr2LkfsKCwsjIYNG9KqVStCQ0Ot5z09PRk4cOADAfvo0aN06tSJKlWq8P3332MYBm3btuXPP/9k6dKljwzYP//8M25ubg/My65atSoXL17Ez89PAVtEHkrDxUVERCTLyJMnDz/88AMXLlx45CJWkr3t2bMHHx8fNmzYANz7PZEvX76H3nvs2DECAwNZvHixtee6TZs2DB8+nOrVq6f4ruLFixMREUFYWNgD+69rmzgReRwNFxcREZFMzTAMduzYQcOGDe1dithReHg4vr6+LF++HAAnJye6d++Oj48Pzz333EPbNGnShM2bNwPQunVrhg8fTo0aNR5677Vr1xg/fjwmk4ng4GDr+dWrV/P666/j7Oyczl8kIpmdhouLiIhIthQcHEyjRo0ICgqydyliR9OmTWP58uWYTCY++ugjjh07xjfffPNAwD5+/DhRUVHW4+HDh/POO++wb98+VqxY8dCAfenSJfr370/ZsmUZOXIkX3/9NVevXrVef+uttxSwRcQmCtkiIiKSqSUmJgL83ZsgOcTly5c5ffq09djHx4cOHTpw8OBB5s6di5ub2wP3BwUFUblyZcaOHWs917hxY3766aeHhuszZ87Qo0cP3NzcmDBhAvHx8Xh6erJ48WKKFi2acR8mItme5mSLiIhIphYYGEjLli2pW7euvUuRp+DGjRuMGjWKyZMn06RJE9asWQPc2xP9+++/f2S7l156CYvFwtmzZx/7/CNHjjBy5EgWLVpEcnIy8P/Yu/OwqMr2gePfAVlU3EFRTBZTEUFgwF3LXSu3LNfUct81MVdwIYHQ3OvNfc0llzQzy0x567VMTWEAUXBBVAQURPYdzu+P+XFeJ6y3Tcfl/lyXVzHnmTPPOeo499z3cz/Qrl07fH196dq1KxqN5h+7FiHE80mCbCGEEEI8ca5evYqTkxMmJvqiOwmwn32ZmZmsWLGCZcuWkZGhX/qYlpZGdnZ2mcZm165dIzAwEBcXF9577z0AevXqhU6nw93d/aHnDwsLIygoiM8//1xtgtatWzd8fX1p167dI7wyIcTzRsrFhRBCCPFEiYqKonnz5gwePJj8/HxjT0c8Yrm5uSxbtgwnJycWLFhARkYG7u7uHDlyhB9//NEgwI6NjWXkyJE0atSILVu2EBwcTG5uLgAajeahAXZoaCivvfYaWq2W/fv3oygKffr04ezZsxw9elQCbCHEP06CbCGEEEI8UWJiYsjKyuLmzZtqOa94dn366ae89957pKSk0LBhQ/bs2UNoaCivvvqqWrp9/fp1Ro0aRaNGjdi8eTPFxcW88sorfP311wb7YT/MlStX+PrrrzExMWHQoEFERkZy8OBBmjVr9jguTwjxHJItvIQQQgjxxPnhhx9wdXWlRo0axp6K+IeVlJQQHx9PvXr1AMjPz6dLly688847DBs2jHLl/ruaMS4ujsDAQLZu3UpRUREA3bt3Z+HChbRo0aLMuRVF4ciRI+Tm5tKvXz8AiouL8fX1ZeTIkTRo0OAxXKEQ4lnxV7fwkiBbCCGEEEaXm5tLcXExVlZWxp6KeEQUReHw4cP4+fmRl5fHxYsXDQLqB924cYPAwEC2bNmiBtfdunVjwYIFtGrV6jdfY+/evQwYMIDatWsTGxuLpaXlI7kWIcTzQfbJFkIIIcRTqaioiIEDB9KxY0eSk5ONPR3xCJw4cYKWLVvSu3dvIiMjSU5OJioqqsw7unnmAAAgAElEQVS4GzduMHbsWBo0aMCGDRsoKiqia9eu/PTTTxw9erRMgF1YWMiVK1fUn/v06UPjxo0ZOnSouvWbEEI8btJdXAghhBBGdf36dX766SeysrK4cuUKNjY2xp6S+IecPn0aX19fQkJCAKhQoQLvvvsu7733HtWqVSsz/sCBA6xfvx6ALl26sGDBAtq0aVNmXF5eHlu2bGHJkiWYmJgQExNDuXLlMDc3JzIyElNT00d7YUII8TskyBZCCCGEUTVo0ICffvqJa9eu0bp1a2NPR/xDwsLC1Myzubk548aNY+7cudSqVUsdc+vWLe7cuYO3tzcA48aN4/Tp00yePJm2bduWOWd2djbr1q1j6dKlJCYmAlCzZk0uX76Mi4sLgATYQgijkzXZQgghhDCK3Nzc/9kZWjxdMjMzqVSpEqBfg921a1fq1avH/Pnzsbe3Nxh75MgRXn/9dRo2bEhERIS6J/rDpKWl8fHHH7Ny5Uru3bsHQN26dZk5cyYjR46kQoUKj+6ihBDPLVmTLYQQQoinxv79+2nUqBGRkZHGnor4B9y6dYsxY8Zgb2+vBsEajYZvvvmGTZs2qQF2SUmJ+pw2bdpQoUIFatasqT7n15KTk/H19cXe3p558+Zx79496tevz4YNG7h27RqTJ0+WAFsI8cSRIFsIIYQQj1VxcTEffPABt27dYtu2bcaejvgb7t69y7Rp09RGZffv3+fgwYPq8dLu4bdv32by5Ml06tSJ0irKqlWrEhkZSUhISJl1+AkJCfj4+ODg4EBQUBAZGRm4uLiwc+dOoqOjGTVqFObm5o/vQoUQ4k+QNdlCCCGEeKxMTU357rvvWL16NfPmzTP2dMRfkJaWxrJly1ixYgXZ2dkAvPzyywQFBRmsq09ISCA4OJj169eTn58PwM8//6yOeeGFF8qc+9ChQ/Tv31/tDu7l5YWvry+9e/f+3ZJyIYR4UsiabCGEEEI8FiUlJRIkPQOys7NxcnLi7t27AHh7exMUFETnzp3RaDQAJCYmEhwczLp169Tgum3btvj7+9OhQwd1XKnCwkLMzMwAfYm4g4MDWq0WPz8/unbtWma8EEI8DrImWwghhBBPrOTkZLy8vPjqq6+MPRXxFxQXF6v/X7FiRfr27YuLiwsHDhzg7NmzdOnSBY1GQ2JiIu+++y5OTk6sXr2a/Px82rRpw/Hjx/nPf/5Dx44dDQLmuLg4+vfvT/fu3dXHbGxsiIqK4uTJk3Tr1k0CbCHEU0cy2UIIIYR45GbNmsWSJUtwcnLi4sWLWFhYGHtK4g8oKipix44dvP/++xw8eBB3d3cAsrKyKF++vLpdVlJSEosXL2bt2rXk5eUB0Lp1a/z9/enUqdNvBsrx8fE4OTlRWFhIVFSUug2XEEI8CR5rJluj0UzQaDTXNRpNnkajOa/RaNr9ztjRGo3mpEajuf//v45rNJrmf+V1hRBCCPF0CggIYMqUKRw5ckQC7KdASUkJ+/fvx83NjeHDh3P9+nWWL1+uHreyssLU1JTk5GR8fHxwdHRk5cqV5OXl0apVK44dO8aPP/5oUEKuKAohISEsWLBAPU/dunVZs2YNEREREmALIZ4ZfzqTrdFoBgCfAhOAn4CxwCjARVGUmw8Zv/P/x50C8oCZQF+giaIot//ga0omWwghhBDiEVMUhW+//RZfX19CQ0MBqF69OrNnz2bixIlltsu6cuUKzs7OlJSU0LJlS/z9/dXS8QfPeeTIEQIDAzl9+jQAOp1OzYoLIcST6q9msv9Kd3EfYJOiKBv//+d3NRpNN2A8MOfXgxVFeevBnzUazWjgTaATsP0vvL4QQgghngKzZ8/G2tqa9957z9hTEX9Qv379+PzzzwF9tnr69OlMmzat9EMmd+/e5fjx4wwePBiABg0aEBAQgKenZ5n108XFxRw4cICgoCB0Oh0AFhYWjBo1Cmtr68d8ZUII8fj8qSBbo9GYA15A8K8OHQNal33GQ1UAzIDU33kdC+DBWrJKf2KaQgghhDCy//znPyxevBjQb+3UrFkzI89I/BFt27blyJEjTJw4Uf2SpNTdu3dxcnIiNzcXrVaLs7MzAHPmGOZYCgsL2b17N0FBQcTExAD6ZmkTJkzAx8cHW1vbx3dBQghhBH82k20NmAJ3fvX4HeCPvmMGA7eB478zZg6w4HeOCyGEEOIJ9tJLL/Hhhx9SVFQkAfYT6tKlS8yfP5+BAwfyxhtvADBu3Dj69euHnZ0dALm5uZQvXx6AmjVr0qVLF27fvq3ujf2gvLw8tm7dyuLFi4mLiwOgatWqTJkyhSlTplCjRo3Hc2FCCGFkf2pNtkajqYM+QG6tKMrPDzzuCwxVFMX5fzx/JjAbaK8oSsTvjHtYJjte1mQLIYQQQvw9cXFx+Pv7s337dkpKSmjSpAmRkZEGpd4pKSksXbqUDRs2oNPpeOGFFwD9+sRKlSoZjM3Ozmb9+vV8+OGHJCYmAvptuKZPn8748ePls5sQ4qn1uLqLpwDFlM1a16RsdtuARqN5D5gLdP29ABtAUZR8RVEySn8BmX9ynkIIIYR4zM6fP8/EiRMpLCw09lTEQyQlJTF58mQaNmzI1q1bKSkpoU+fPnz22Wdq0JySksKcOXNwcHBg8eLFpKamsn37f1voVK5cucx2XFFRUfj4+JCYmEjdunVZtWoVcXFxzJo1SwJsIcRz6U+ViyuKUqDRaM4DXYCDDxzqAhz6redpNJoZgB/QTVGUc39lokIIIYR4cuXk5NCrVy8SEhKwtrbG39/f2FMSD1i7di0+Pj7k5uYC0LlzZwICAmjRogUA9+7dY9myZXz00UdkZWUBoNVqWbhwIT169DA4V0pKCqdPn1Yfb968OaNGjaJ58+YMGzZMtmgTQjz3/kp38eXApxqN5hzwMzAGqAesBdBoNNuB24qizPn/n2cCi4DBQJxGoynNgmcpipL1N+cvhBBCiCdAhQoVWLduHcHBwUyfPt3Y0xG/4uDgQG5uLi1btiQwMJCOHTsCkJqayrJly1i9erUaXHt6erJw4UJ69uxZJmt97do1mjZtSklJCXFxcdSqVQuADRs2PN4LEkKIJ9if3icbQKPRTEC/33Vt4AIwTVGU//z/se+BOEVR3vn/n+MA+4ecxl9RlIV/8PVkn2whhBDiKaAoSpnATDxeeXl5rF27lnLlyjFp0iRA//ty8uRJ2rVrh0ajITU1leXLl7N69WoyM/Wr8jw8PFi4cCG9evUy+D3MysrCyspKPU/r1q0pKChgy5YtNG3a9PFfoBBCPCZ/dU32XwqyHzcJsoUQQognT0FBAX5+fsyePZvq1asbezrPvaKiIrZu3Yq/vz/x8fFUqVKF2NhYg9+b/Px8AgMDWbVqFRkZ+s+L7u7uLFy4kN69exsE19HR0XzwwQd89dVXXLt2japVqwL60vLq1avLlylCiGfe42p8JoQQQggBwOTJk/nwww959dVXeRq+tH9WlZSU8Nlnn+Hi4sLo0aOJj4+nbt26LF26lEqVKhmMNTMz49ChQ2RkZNC0aVM+//xzQkND6dOnjxo063Q6+vfvj4uLC9u3byc1NZXDhw+r56hRo4YE2EII8TskyBZCCCHEXzJp0iQcHBxYtGiRBF1Gcu7cOTw9PRk0aBBXrlzBxsaGFStWcOXKFUaNGkV2djZBQUHqvtYmJiYsX76c/fv3ExYWRt++fTEx0X8cPH36ND179sTT05N9+/ahKAq9e/fm7NmzDB061JiXKYR4yq1atYqbN2+WefzmzZusWrXKCDN6tP5K4zMhhBBCCNzc3IiOjpZu0kZUpUoVoqKiqFy5MjNmzGDq1KkG2esuXbpw7tw5zMzMmDFjBgCdOnVSjyuKwvfff09AQAAhISGAPhAfMGAAc+bMwc3N7fFekBDimbNq1SreffddVq9ezb///W/q1asH6APsDh06EBsbC8DUqVONOc1/lGSyhRBCCPGH7du3j5iYGPVnCbAfr7Nnz7Js2TL15wYNGrBnzx6uX7+On58fJSUlFBQUqMcnTpxIkyZNcHZ2NjiPoigcOXKENm3a0LFjR0JCQihXrhwjRowgOjqaXbt2SYAthPhHvP766zg5OREbG0uHDh24efOmQYDt5OTE66+/buxp/qOk8ZkQQggh/pDjx4/TvXt3qlatyrlz53BwcDD2lJ4bkZGRzJs3j0OHDqHRaIiMjKRJkybq8YyMDFavXs3y5csJDg5mzJgxABQXF6PRaNSScIDr16/Tt29fdDodoP+iZPTo0cyYMUPNMAkhxD/pwaDazMwMgMLCQpycnAyy208aaXwmhBBCiEfK3d0drVbLq6+++sR+IHrWXLt2jSFDhuDu7s6hQ4cwMTFh2LBhatIhIyODwMBAHBwcmDdvHvfv3+fgwYPq801NTQ0CbAA7OztSUlKwsrJixowZxMXF8dFHH8nvqRDikVEUhUmTJmFiYkJhYSGFhYWYmZk90QH23yFrsoUQQgjxh9jY2BASEoKFhUWZwE38s+7du4evry+bNm2iqKgIgDfffJP333+fxo0bk5mZSVBQEMuWLSM1NRUAZ2dnFixYQL9+/dTzlO5nvW/fPo4ePUq5cuUwNzdn3759NGjQgBo1ahjl+oQQz6aCggKioqIIDQ2lW7du1K1bF4CDBw/i4+Nj5Nk9PlIuLoQQQojflJCQQHR0NB07djT2VJ4rGRkZODk5ce/ePV555RUCAgLQarVkZmby8ccfs3TpUoPgev78+fTv3x9TU1OD82RnZ+Pg4EBKSgo7d+5k8ODBxrgcIcQzKC8vj/DwcEJDQ9VfkZGRFBYWArB9+3Z1Z4IvvviCQYMGkZeXp1bYPMvl4pLJFkIIIcRDpaen0717d6Kjo9m7dy99+vQx9pSeWRkZGezcuZNx48ah0WioXLkya9aswdbWlnbt2pGVlUVwcDBLly7l3r17ADRq1Ij58+czYMAANbhOT09n165djB07FhMTEypWrEhAQAB5eXny+yeE+MuysrLQ6XTUrl2b+vXrA/o+HT179iwztlq1ami12tLglJs3bzJ9+nTy8vJwdHRkwIAB3Lhxg2+//VZthhYQEMDZs2dZsWLFY72uR0WCbCGEEEI8lKWlJS4uLiQnJ+Pu7m7s6TyTcnJy+Ne//kVwcDCpqanUrl1bDYZLy77/9a9/sXDhQlJSUgBo2LAh8+fPZ+DAgWpwnZKSwqpVq/joo49IT0+nTp069O7dG4CxY8ca4cqEEE+rtLQ0wsLCDDLUMTExKIrC/Pnz8ff3B8DLywsbGxu8vLzQarXqLwcHBzQajXq+gwcPEhsbi6OjI5aWlgQHB6vHzMzMiI2NVatsXnrppWei07gE2UIIIYR4KAsLC3bt2kV8fPwTW8r3tCooKGDTpk0sWrSIxMREQJ+ZrlChQpmxSUlJpKSk0KBBA+bNm8egQYMoV07/ES4xMZGlS5eydu1acnJyAHBxccHS0vLxXYwQ4qmVkpJCdnY29vb2AFy9epUGDRo8dKydnZ363gNQu3Zt7ty5YxBQP0hRFK5fv069evXo1q0bpqamfP311wZjSkvLS3Xu3PnvXM4TQ9ZkCyGEEEKlKAo//PAD7du3N/ZUnkklJSXs3LmTBQsWcP36dQDs7e1ZuHAhQ4YMIT8/nzVr1tC8eXNeeuklAO7fv8/hw4cZPHiw+gE3Li6OJUuWsHnzZvLz8wHQarX4+fnRu3dvaUwnhCgjMTGR0NBQzp8/r2aob926xeDBg9m5cyeg3/avatWqWFtbo9Vq1Sy1p6cntWrV+s1z5+XlERUVhU6nQ6fTER4eTnh4OBkZ/13GbGtrS1JS0u/O8UmLTWVNthBCCCH+toCAAObPn8+8efN4//33jT2dZ9KyZcu4fv06tWrVws/Pj9GjR2NhYQGAn58fixcvpk2bNpw8eRKNRkO1atUYNmwYADExMQQHB7Njxw6163jbtm3x9fWlW7duv5lREkI8PxRFeTA4pKioCEdHR+Lj4x86/v79++r/m5qakpiYiJWV1e++RmRkJN9++60aVEdHR1NcXFxmnLm5Oa6urri7u/Pll1/+jat6ukiQLYQQQogyatasaewpPBMUReHEiRO0atWKihUrYmJiwpIlSwgLC2PSpEloNBpSUlKws7MDYMqUKRw+fJiRI0eiKIoaNIeHhxMUFMS+ffvUTE+XLl3w8/NTM95CiOePoihcu3bNYP10aGgo9evX58yZMwCUK1eOatWqkZCQgLOzs8Eaag8PjzKVwr8OsA8dOsSZM2cYM2YMDg4OABw7dowZM2YYjKtRowYeHh7Y2tqyZ88eatWqxfXr1zEzMwNg0KBBfPbZZ4/oTjxZpFxcCCGEEAbOnTuHt7e3safx1Dt16hS+vr58//33BAcHM2vWLPVYbm4ua9euZfHixXh5eXHkyBH12IPBNej3zK5Tpw4FBQUA9OrVC19fX5o3b/74LkYIYXS/fm8YMmQIX331Fenp6WXGVqpUifv376vNEa9du4atrS0VK1Z86LmzsrKIjIwkPDychIQEg0qmNm3acOrUKXbu3EmnTp2oVasWp0+fZvny5cTFxfHLL7+wcOFC5s+fj0aj4f79+1SvXp3KlSuTkJCgvmZycjIajYY1a9awe/duLl269NBrfJJIubgQQggh/pLLly9Tv3599cOYBNh/j06nw8/PTw2cLSwsyM3NBfTB9bp161i8eLG6NvHixYukpaVRtWpV9Rzh4eFqR/caNWowYsQI0tLSmDt3Lm5ubo/5ioQQj1thYSGXLl0yyE7funWLuLg4NdDOyckhPT0dCwsLmjZtatDh29XVVX1PB9RttxRFITEx0WDttE6n48qVK2qAa2JiwvTp0wGoUqUKffv25cUXX2TChAlkZ2eTmZlJy5Yt2bt3L/7+/vzyyy/cu3dPnVe1atWIjY3F3t7eoD+EjY0NAPPmzWPevHmEhIQwYsQIbty4oY7JzMykUqVKj/DOPh6SyRZCCCGeY1FRUbRt25YOHTqwa9cu6Ur9N8TExLBgwQL27NkD6Nc2jhgxgnnz5mFtbc369esJDg5Wg2t7e3v8/PwYNmwY5ubmgP6DdadOnTh58iRhYWF4eHgAZTNYQohn0+rVq9mxYwcRERFqU8MHXb9+XS3ZDg8PR6PR0LhxY7Uk+9fu37/P119/rQbVOp1O3Q7w12rXro2HhwcFBQX8+OOPjBo1io8//hjQvwdZW1uTnp5OeHg4TZo0AfTdyTUaDTVq1PhL15uZmcmsWbNYs2YNAAcOHHiitvCSTLYQQggh/rRr166Rk5NDUlISJSUlxp7OU23+/Pns3bsX0K899Pf354UXXlCD69KtuurVq4efnx9vv/025ubmBuWRZmZm2NnZYWFhYRBkS4AtxLMhJyeHiIgIgw7fJ06coHr16gDEx8fzyy+/AFC5cmU8PT0N1lC/8MIL6rlKq11KRUVFERISQqNGjejatSug7yg+ZMgQg3GmpqY4OzvTtGlTvv/+exITEzl16hStWrUCYOfOnZw4cYLo6Gj1ORqNhp9//pl69eoZfBlrbW39t+5HpUqV+OSTT3jzzTc5fPjwExVg/x2SyRZCCCGecz/99BONGzdWP+SJP+bOnTsoioKtrS0A0dHRzJo1i/fff59GjRqxceNGPvjgAxISEgB9cO3r68s777yDubk5RUVF7N69myVLlnDgwAF1b9qbN29iZmZG7dq1jXZtQoh/TkhICFu3biU0NJRLly6V+ULz+PHjdOrUCdAvN7l8+TJarRYnJ6cy2/EpisKNGzfUMu8xY8ao7xWLFi1i/vz5DB06lM2bN6sVMF27dqVChQr88MMPuLq6EhISQvny5QFo2bIlZ86cMcggp6Wlce/ePRwdHZ/77QD/aiZbgmwhhBDiOZOTk0NRUZH8m/oX3b9/n6VLl7Jy5Ur69+/Pli1bDI5//fXXjBkzhtu3bwPwwgsvMHfuXIYPH46FhQX5+fls3bqVxYsXq3tljxs3Ti2XFEI8fVJTUwkLC1Oz0w/2T1i/fj1jx45Vx9aqVcsgO/3yyy8/9EvO/Px8Ll68WGb99IONzg4dOkT37t0xNzcnJCSElStXkpiYyIULF9i/fz+vvfYaAGfPnqVFixbUqVNHfW8C/ZeD1tbWfzsj/ayScnEhhBBC/E9FRUUMHDiQW7du8c0336hZWPG/ZWdns3r1apYsWUJaWhqgX4ddWFhosB6yZs2a3L59m7p16zJ37lxGjBiBhYUF2dnZfPLJJyxdulTNbtvY2ODj48OECROMck1CiL8mNjaWzz77TA2qS78wK9W+fXs1yG7fvj3+/v5otVq8vLweWqWiKAohISFqIK3T6bh06RJFRUVlxpqZmdGkSRPq1avHxIkTsbS05MqVK3Ts2JGOHTsyZMgQzp07R0REhBpku7u788svv6hrqUs5Ozv/U7dEPEAy2UIIIcRzJDY2llatWpGRkcGJEydo3bq1saf0xMvPz2fdunUEBgZy9+5dAFxdXQkICKBbt25s2bKFe/fu4efnpz7n8OHDdO3aFQsLC9LT0/nXv/7FihUr1IZDdnZ2zJgxg9GjR1OhQgWjXJcQ4vcpikJCQgKhoaGcP3+ejh07qvvSh4SEqCXepZycnNTsdM+ePXF1dX3oee/fv8+JEyfIyMhgxIgR6uP16tXj1q1bBmOrV6+Ou7s7ubm5REVFMW7cOAICAjA3N+fevXtqBjojI0Ptyn358mVMTEweWm4u/hzJZAshhBDif3JycuLUqVNcvnxZAuw/aMWKFcyZMwfQ37/333+fgQMHYmpqyvfff8+ECRMwNzdn+PDh2NnZAdCzZ09SUlIICAjgo48+Uss7nZycmD17NsOGDcPCwsJo1ySEKCsrK4tjx46pQXVoaKj6xRroq1lKg2xPT08GDRqkZqc9PDyoVq2awflycnK4cOECOp2Oxo0b065dOwCuXr1Kv379sLGxYfjw4YC+sdhrr73G7du3CQ0NJTU1lYiICOrXr49Go2HhwoWcPn2a5ORkdTeCGjVq8P333+Pi4mKw7VXDhg0f6X0S/5tksoUQQojnQHZ2NhUrVjT2NJ4KJSUl3Lt3T93TNS0tjXbt2jFp0iSGDBnCxYsXadasGaDPdA0ePJg2bdowatQoLC0tKSgoYM6cOaxdu5acnBwAGjdujK+vLwMGDKBcOclxCGFMJSUlXLt2jdDQUKytrdWM9M2bN7G3tzcYa2JigouLC1qtlj59+vxm9+ukpKQya6cvX76sNjkbN24cn3zyCQB5eXm0b9+e8uXLc/v2bV599VVWrVoF6N9TatSowf379zl//jxarRaAuLg4kpOTcXV1VZuWiUdPGp8JIYQQ4qH279/P1KlT+eqrr/D09DT2dJ5YiqLwzTff4OvrS/ny5fnpp5/UrbPy8/PZtm0bgYGBpKamEhcX95v7wiqKQqtWrThz5gxarRZfX1/69OkjZZtCGEFJSQmXLl1S106HhoYSFhZGZmYmAH369OHgwYOA/u9up06dqF+/vlr27ebmVmZJx7Vr1zhz5ozB+ukHM94PsrGxwdPTk6SkJBITE/npp5/UnQR27NjB0KFDadu2LSdPnlSf8+9//5u6detSv359ed8wMikXF0IIIUQZJSUlfPjhhyQkJLBjxw4Jsn/Df/7zH+bOnctPP/0E6PduvXbtGvb29mzdupXAwEBu3LgBgK2tLdHR0bRp0wbQNz9bvnw5wcHBVKtWDY1Gw9KlS8nMzKR79+6yx7UQj0lBQQEXL14kIyNDLesuKSnB29ubvLw8g7GWlpa4u7vTtGlT9TGNRkNISIj6s6IonDp1Cp1Ox8iRI9X9oRcvXsyGDRsMzqfRaGjUqBG1a9fmypUr2Nvbs2/fPmxtbdFoNDRv3pzk5GR0Op0aZHfp0oVjx46V2e+6Q4cO/9xNEUYhmWwhhBDiGZeens7q1auZO3cupqamxp7OE+XcuXP4+vpy7NgxQP/Be/Lkyfj4+HDkyBECAgKIi4sD9NvuzJ49m7Fjx6rlmoqi4OnpSXh4OO+//z7z5s0z1qUI8VzJy8sjMjJSzU6fP3+eyMhICgoKcHNzIyIiQh3buXNn8vPz1ey0l5cXzs7O6tINRVGIj48nPDycnJwc+vfvrz5ubW1NamqqQen25s2b2bhxIzk5OSQlJTFnzhxGjRpFxYoVOX36NK1atcLW1pbExER1DidPnsTS0lLKvZ8yUi4uhBBCCFVxcbEE1P/D999/r2aMypUrx+jRo5k1axYnTpwgICBA3ZKnVq1azJo1i7Fjx1KhQgXOnDmDq6urusb9s88+Y9euXcybN09dqy2E+OdkZ2cTGxurbokF4ObmxoULF8qMrVKlCs2bN+fo0aMPLbUuKCggOjq6zPrp1NRUABwcHAy24xo8eDCJiYnk5eVhYmKiVruUHtu9ezdBQUFqc8ScnBx1ac6LL74olSxPOQmyhRBCiOfYtGnT6NmzJx07diQ5OZmWLVvi4uLC4cOHjT21J0p+fr7a1bu4uBgvLy+aNm2Kr68vp06dIiAggNjYWEC/3/WsWbMYN24c5cuX5/vvvycwMJATJ06wYsUK3n33XWNeihDPpPT0dMLCwgzWUEdHR1OhQgXS09PVLw+HDBnCt99+i5eXl5qh1mq1ODo6qoFtZmYm58+fNwimo6KiKCwsLPO6pqamuLi4UL58eRRFYdSoUYwZMwaA5ORkatasCRhulXX27FnS09PRarW/2aNBPN1kTbYQQgjxnDp48CArV65k5cqVDBkyBJ1OR2xsLLGxsezdu1ctfXyeJSYmEhAQwNdff83FixcpX748pqamnD59mlu3bvHKK69w7do1QB9cz5w5k/Hjx1O+fHm+/vprAgMD+fnnnwF91vvOnTvGvBwhngn37t2jevXqalA8ZsyYMmudS1WpUoXExETq1q0LwIYNG7C0tFSfe/PmTc6fP09hYSGNGjUC4LvvvuONN4OSepwAACAASURBVN546LlcXV25e/cuOTk5fP7557i7u2Npacn8+fNZtGgRbm5uapBtY2PD1q1bady4sUGpd/Pmzf+5myGeKRJkCyGEEE+5pk2b0qtXL7788kt27NihPj5w4EBeeeUVI87M+O7du8eSJUv46KOPyM3NBeDLL79kwIABgH4Ntr29PcXFxdjY2BgE1wcOHCAoKIiwsDAALCwsGDlyJDNnziyzzY8Q4vclJSUZZKfPnz/PzZs3iY+PV/eXr127NgD29vYG2WmtVoutrS2gX4sdFRWFTqfjnXfeUTPbc+bMYdeuXQQGBjJ37lwAPDw8cHBwwNbWluTkZLy9vQkODlb//larVo309HQsLS3Vpmb9+/fH1dW1zNKPt99++9HfJPHMkHJxIYQQ4imm0+nQarVUqVKFzZs307dvX0AfSPbs2dPIszOezMxMVq5cydKlS8nI0Ff4tW7dmkWLFnH79m127NjBV199hZmZGQARERHUr18fCwsLdu/ezQcffMClS5cAqFixIuPHj8fHx0cNAoQQD6coCoqiqOuhN27cyPz58w2agD3o2LFjdOnSBdCXZWs0GqytrQG4e/euWuZd+t/o6GiKi4sBiI6OVrPWq1atYvv27VSpUoWcnBx27dqFk5MTANu3b+ftt9/mpZde4ocfflBfe9euXVhbW9O6dWusrKwezQ0RTzVZky2EEEI846Kioti+fTsNGzZk5MiRgH5dcZ06dahXrx6ffvopjRs3BiArK0ttzPW8SU1NxdnZmeTkZADc3d0JCgrilVdeITc3F0dHR+7evcvmzZsZPnw4oF+rvXXrVhYvXqw2PapSpQpTpkxh6tSpst5SiIdQFIXr168bZKdDQ0P5/PPP1S20SveC1mg0ODs7G3T49vDwoEqVKpSUlHDlyhWDYFqn0/1mYG5tbY2TkxNVq1bFycmJNWvWqMe8vb05f/48+/fvV0vFb968ydGjR/H29lY7hAvxR0iQLYQQQjxjcnNzMTU1xdzcHNCvQRwzZgzNmzfnzJkz6riMjAwqV65Mdna2mo153oJsRVEMuvj27duXqKgo/P39MTc3p0+fPmpmbcOGDaSmpjJx4kSsrKxQFAWtVotOpwP06y+nTZvGhAkTSj9cCSEecOrUKfz8/AgNDSU9Pb3M8QcbA6akpHD58mWaNm2KlZUVOTk5hIeHU1xcTNu2bQH9+1XlypX5dVyi0Who0KAB5cuXJycnh5EjRzJkyBDq1KnD6dOnad26NXXq1OH27dvqcz7//HOKiopo3749tWrVeoR3QTwPpPGZEEII8QyZOnUqGzduZMeOHbz++usA9OzZk0GDBtGnTx+Dsc/zF9DFxcV89tlnBAUF8c0331CvXj0A1q5dy7fffsvChQuJiYlh79699OvXD4DRo0eTkZFBhQoVAP0H+X79+nH37l1mzpzJ6NGj1WNCPI+KioqIjo42WEM9btw4Bg8eDICJiQn//ve/ATA3N6dp06YG66fd3NxQFIWEhATCw8NxcXFRvwD8/PPPGTZsGO3ateM///kPAFZWVri7u6PRaMjPz8fS0pKPP/4YNzc3rKysGDhwIHv27AFQ1283bdqU4OBgPDw8DL5ke1ijMyEeu9J1E0/yL6AyoKSnpytCCCHEs+bq1avK+vXrDR6bNm2aAiiTJ0820qyebCUlJcoXX3yhuLq6KoACKFOmTFGKioqUXbt2Kc7Ozurj1atXVzZv3qw+d/HixUqVKlWUL774Qn0sOztbycvLM8alCPFEiI+PV8aPH6+0aNFCsbS0VP/+lP6aOHGiOjY7O1vZtGmTEhYWpuTn5ysFBQVKZGSk8umnnyrTp09XOnfurFhbW6vPXblypfrciIgIpXbt2krr1q2VgQMHKrt371YURf93OikpSQEUjUajZGZmqs85evSosnbtWiUmJubx3RAhFEVJT08v/XNcWfkT8atksoUQQggjysrKwsXFhYKCAtq1a4ezszMAkyZNYsiQIXh6ehp5hk+eEydOMHfuXM6ePQvo107PmDGDunXr4ubmpjYsq1atGtOnT2fy5MkG2f60tDTS09PZs2cPvXv3BpDMtXgu5ObmEhERoWanPT09mTBhAqDPSD+4trlSpUp4enqq2elWrVoB+n2sw8PDyc7O5qOPPkKn03HhwgUKCgrKvJ6pqSkNGzbkm2++4bvvvuPgwYO4urqSkJCAn58fgYGBaqZao9FQq1Yt3n//fRo2bKh2DQfo1q3bI74zQvyzJMgWQgghHpMrV66wfPlySkpKWLduHaAvk+zatSs5OTlkZWWpY0u74or/UhSF3r17c/jwYUAfGE+dOpUXX3yRZcuWcfHiRQCqVq3K9OnTmTJlCqmpqcyePZt+/frRoUMHAKZNm4aXl5dahi/Es6qgoIA1a9aoQfWlS5fUztygD15Lg2wbGxs1wNVqtTg5OXHr1i1iYmIMgtxevXqpZd4PqlSpEo6OjpSUlODq6sp7771HkyZNMDc3p1q1amRkZBAdHY2bmxugX/5SqVIltUFaqXnz5j2KWyHEYyWNz4QQQohH5P79+xQVFWFjYwPot9vy9PSkfPnypKSkqNnTkpIStSmX+H1z585l2bJljB07Fjc3N1atWkVUVBSgD659fHyYMmUKSUlJBAcHs2PHDoqKiujQoQMhISFGnr0Qj0ZaWhphYWGEhoZiZmbGlClTAP0XU6V7QZeqWbMmXl5eaLVa2rRpwyuvvEJ+fj4XL16kuLgYb29vQN+wrPS9KyMjg0qVKgH6fhFffPGF+vPkyZPp0qULDg4ObN++neHDh9O+fXt1zTbA0qVLsbKyom/fvtSsWfOx3BMh/gnSXVwIIYR4ggQGBrJw4ULee+89PvjgA0D/gXf27Nm0b9+ezp07q3s0i4e7cuUKCxYsYNy4cWq2Ky0tjdTUVPr378/58+cBfbm4j48PU6dO5caNGwQGBrJv3z61U3GnTp3w9fVVM9lCPO1CQkI4e/asum1WbGyseqx+/fpcvXpV/dnX1xczMzM1sDY3NyciIsJgu6xLly5RVFREt27dOHr0qPpcR0dHLC0tad++Pba2tixYsIDi4mJMTU3RarWEhYXx+eef07dvX0D/d3bTpk20bNmyTINGIZ5G0l1cCCGEMBKdTscXX3zB5MmT1f2UnZycKCoqUtcHg76L9eLFi401zafGrVu3WLRoEZs3b6a4uJj4+Hh++OEHNBoNVatWpWrVqrRo0YKrV68ybdo0pk6dSkxMDEOHDlVLyUFfjurr60uLFi2MeDVC/HUJCQmEhoYSHx/PuHHj1MdnzJhBaGiowVhHR0d1/+nS5kvXrl3Dw8OD8PBw1q1bh06nM9ju6kGlJd0TJkzgnXfeoXnz5ly7do1Tp07Rrl076taty4IFC9S10mPGjCEtLQ1XV1f1HA0aNCA4OPgR3Akhni6SyRZCCCH+JOVXezK7u7sTERHBtm3bGDZsGKBvaJaUlMSLL75orGk+dZKTk/nggw/45JNPyM/PB+C1116jY8eObN++nU2bNuHl5QXoS1lNTU0JDw8nMDCQ48ePA//djmvu3Lm4u7sb7VqE+LPi4+P55ZdfDLbNSkpKAsDMzIzMzEwsLCwA1K3pSpuSNWrUiISEBBo0aEC1atUAWLx4MbNnz37oazk4OGBlZUWlSpWYM2cO7u7uvPDCCwwYMIB9+/axZMkSZsyYAegzeTNnzsTDw4MxY8bI0hbxXJFMthBCCPGI3blzBx8fH8LDw4mIiFA/bA4aNAgnJydeeOEFdayVlZUE2H/Cxx9/zJw5c9Tmby+99BJBQUG0adOGoUOHEh4ezuLFi9m7dy8A586dY9GiRZw6dQqAcuXKMWTIEGbPnk2jRo2Mdh1C/C+KohAbG0tYWBh9+/ZV30emT5+u/vkuZWJiQuPGjfHy8lKD7KSkJDp37szChQvVcc2aNePcuXMGpdtubm5YWlpib2+PpaUlrVu3ZvDgwTRt2pTc3FxsbW3RaDR07NiRihUrAvo9ph0dHWnTpo167sqVK7N27dpHfFeEeLZIkC2EEEL8htu3b5Oamqp2w61atSpffvklWVlZnD9/nmbNmgH8ZrZI/HGVK1cmKysLb29vXnvtNd566y0aNGgA6LsN29vb4+Pjo47ftm0bp06dwsLCghEjRjBz5kwcHByMNHshHq64uJjLly8bZKfDwsLURmRXrlxRv4xr0aIFly9fVku+3d3dKV++PDExMeh0OoYMGYJOp+POnTuYmZmRlZWFubk5oK+miYuL4/Dhw4SEhLBy5Uq6dOlCZmYmCxYsICgoiBYtWtC2bVtA//dt1KhR1K9fn6KiInW+AwYMYMCAAY/5Lgnx7JFycSGEEOIhPv30U4YNG0bHjh05ceKEweNOTk60bNnSYB9X8ccVFBSwYcMGatSowcCBAwEoKirC39+fr776Cp1Ox1tvvcWOHTvUY5999hktW7ZUA5LIyEi2bdvG9OnTqV27ttGuRYhShYWFXLp0CScnJ6ysrAD9F0QBAQFlxlpYWNC0aVM++eQTvL29yczMLNOMLDIykry8vDLP1Wg0ODg4MGDAAFxdXXnrrbfIz8+nXLlyVKtWjczMTC5cuECTJk0AfZO0PXv20K1bNzXLLYT4Y6RcXAghhPiLTp8+zd69e3njjTfUMsnWrVuj0WgoLCxUu+kCDB061JhTfaoVFxezY8cOFi5cSFxcHHXr1qV3794cP36chQsXqo2crKyscHR0VNe+T5gwgQ0bNjB8+HA2b94M6Ethly5daszLEc+x/Px8Lly4oHb3Dg0NJSIigvz8fL755hu6d+8OgIeHBxUrVsTDwwOtVounpyd2dnY4OTmpXxhduHBBrZb5tYoVK2JnZ4eVlRUDBgzg5ZdfxtXVlT179jBy5Eg6dOjAW2+9pa7VHjVqFGZmZmr5N0DHjh3p2LHjI74jQogHSZAthBDiuZOXl4elpaX686ZNm9i4cSMFBQVqkF2/fn3u3Lmj7hMr/jpFUThw4ADz5s1Tu63Xrl2bHj160KZNG8LCwgB9QDF58mTGjx9PpUqV1OZyI0aM4ODBgzRu3Nho1yCeXzk5OZSUlKjZ6YMHD9K/f3+DMutSlStXJjk5GdBXbDg4OHD79u3STBjvv/8+I0aMYPTo0axfvx7Qd+QuV64c1tbW2NjYYGdnx4gRI/Dw8KB+/fpotVpCQ0OZN2+e2im/ZcuW9O/fXy3/LrV8+fJHdh+EEH+cBNlCCCGeG8XFxbzxxhscO3aMmJgYtVHZgAEDKCgooFevXgbjJcD++86cOcPEiRPVPa2rV69O79690el0ajOlihUrMmnSJMaOHctnn32Gt7c3gwYNYtWqVYA+oLh165bBFyNCPAoZGRnodDqDNdSXLl1i1apVTJo0Cfjv9nzVq1dX955u2LAhFhYW3Llzh5CQEJYvX05UVBSFhYUGmW0XFxfKlSvH9evX+fDDD+nevTtubm4kJycTERHByy+/TFpaGv369VPn9Oabb9K8eXPq1KmjPubi4sKePXse780RQvxhEmQLIYR4ZsXExHDlyhV69OgBgKmpKSkpKeTm5vLdd98xYsQIADp37kznzp2NOdVnlqIonD9/HisrK3r27El0dDRbtmwBoEKFCkyaNIkRI0awc+dOtFotaWlpAJw4ccKgTF8CbPFPe/DPV0xMDL169eLy5csPHRsTEwPo/zyXL1+eNWvWkJCQQHh4OLt37+bmzZsPfV7lypX5+uuvuXTpEtOmTaNnz55kZmYydOhQZs6ciUajwc3NjapVq+Lu7k7nzp3x9PQ0mJufn98juHohxKMkQbYQQohn0pkzZ2jZsiXVqlVTu/ECfPjhh1hZWeHq6mrkGT6bQkNDCQ8PZ/jw4YA+C71x40ZOnjzJtm3bAH1wPXHiRIYOHcr27dvx8vIiOzsbgMaNGzN37lwGDhwojeXEP+bu3btqZrp0DXWfPn1YsWIFAHXq1FED7Hr16qHVamnatCl169alR48eanO9Ro0aceXKlYe+hp2dHTY2Nnh6etK7d2/c3d0xNzfHzs4OExMTxo4dS4UKFQDo0qULGo2Ghg0bqs+vUqUK33333aO8DUKIx0SCbCGEEE+9M2fOsGHDBrRaLRMmTADA29ubOnXq4OrqSkpKivohuVWrVsac6jMrOjqa+fPns2/fPiwsLOjcuTO2traYmZkxcuRI6tWrx969e5k4cSIDBw5k8+bNNGvWjPz8fAA8PT3x9fXl9ddfV/cNFuLvyM3NZeDAgZw/f57bt2+XOX7u3DmDsQcOHKBt27bY2Nhw7tw5WrZsSe3atRk9erQ6zsHBgbi4OOzt7alWrRqDBw9WA/LFixcTHBxMixYt6N27N6DPfHft2hV7e3uys7PVIHvMmDGMGTPmEd8BIYSxyBZeQgghnjopKSlYWVmpJcQbNmxgzJgxNGvWjLNnz6rjCgoK1H1kxaNx48YN/P392bZtGyUlJWg0Grp06UJKSgo9evTA398f0AcbZ8+eZe3atezYsUNtGtW6dWv8/Pzo3r272uhMiD9CURRu3LhhkKGuVasWW7duVcfUrl2bpKQkNBoNjRo1wtPTkxdeeAELCwsyMzPVPagTExOZMmWK2gegdNue6tWrs2rVKqytrenevTt3796lSpUq1KhRg+zsbKKionBxcQHg8OHDfPTRR/Tu3ZuJEyca45YIIf5hsoWXEEKI58KwYcPYuXMn+/fv5/XXXwegZ8+eTJo0iT59+hiMlQD70UlJScHf359169ZRWFgIQO/evVm0aBExMTH069eP27dv4+vri7m5OfPmzSMoKIjSL/c7d+6Mr68vL7/8sgTX4k/x9/fn5MmThIaGcv/+fYNjD+6ZnpWVxbvvvsvdu3dJS0sjKiqKQ4cOkZOTU+acGo2GK1eusHHjRnr37o2NjQ2JiYl89dVXDB06lM6dO9O9e3dq1qwJQK9evSgqKuLBZFXPnj3p2bPnI7pqIcTTRIJsIYQQT6SSkhLOnz/PDz/8wHvvvac+bm1trR4rDbJtbW356KOPjDXV51JBQQEbN26ksLAQrVbLG2+8wdy5cwFo0qQJQUFBvPPOO+oXHa6uriiKQs+ePfH19VW3IhLi14qKioiJiVEz1CkpKXz66afq8ePHj/Pjjz8CYGZmhpubG40aNaJNmzZ4e3ujKAozZ85k2bJlPKxis3z58tjb21OvXj1ef/11PDw8cHV1pU2bNowePZqaNWvSq1cvbG1t8fb2xtvbGw8PD4Nz7Nq169HeBCHEU03KxYUQQjyRMjIysLa2prCwkEuXLuHs7AzArVu3KC4uxsHBwbgTfM5kZWVx+PBhBg0aBOhLdX18fDh+/DgXLlygZs2axMbGUrFiRU6fPs38+fN55ZVXmDZtGqDv5Hzx4kXc3NyMeRniCfXll19y7NgxQkND0el05Obmqsc0Gg3p6elUqlSJwsJCNm3ahJmZGVqtFhcXF1xcXIiNjeXChQs0adIEgBUrVuDj44ONjQ1169alefPmdOjQAQ8PD27fvk2nTp2wt7cnLi5OfZ13332XqKgoZs6cSZcuXR73LRBCPIGkXFwIIcRTKyIigoCAACwtLdm+fTug3/qmtHlQ6fpdQN3bWjweeXl5rF27lqCgIJKTk7G3tyc/P58FCxZw8uRJACwsLBg4cCAFBQVUrFiRyMhIvvvuOy5fvszUqVMxMTHB1NRUAuznXF5eHpGRkWogvXr1arXr/8GDBw3WUlesWJGmTZtSp04dLC0tmThxIlFRUVy4cAFHR0eio6PVsbVr1yYuLo6jR49y8eJF+vXrx9tvv81bb73F+PHjOXDgAEOGDGHAgAEA1KpVixdffBEPDw+KioooV07/cXjlypWP72YIIZ5pEmQLIYR47G7cuIGZmRl16tQB9KXh+/bto3z58qxdu1btwLtv3z5jTvO5VlhYyLZt2/D39yc+Ph7Qb1E0fvx4IiIiAH1wPXr0aNzd3alZsybVqlUD9Ovmr169yvjx46VT+HPs0qVLHD9+XC37joqKori4WD0+YcIE3NzcUBSFVq1acf/+fcqVK0daWhpXr17l559/fuh5ExIS+Oabb7Czs6Np06bs3r2b/Px8GjRogKmpKT169KB69eoAtGjRghs3bpRmogCoWrXqb27DJYQQ/wQpFxdCCPFYzZo1iyVLljB79mw++OADQF96/MEHH9CpUyeaNWsmgZkRlZSUsGfPHubPn8/Vq1cB/Tr46tWrq/sIm5ubM2rUKBo1asS6deu4ePEi9evXJzo6Ws0KiudHeno6YWFhhIaGMnjwYGxtbQEIDAzEz8/PYKy1tTUeHh40a9aMMWPGcPXqVd58803S09Mfeu46depQp04dunXrhlarxcPDg7Vr1/Lhhx8yfvx4PvnkE0D/HuLi4oKdnR3btm3Dzs7u0V60EOK5IOXiQgghnjgnTpzg0KFDLFiwgBo1agDg4eGBiYkJSUlJ6jiNRqM2zRLGVVhYyOzZs7l58yZVqlTBxsaGq1evkpKSgrm5OSNGjMDR0ZF169apAU6VKlUYNGgQBQUFEmQ/49LT0zl79qyanQ4NDVW/jAH9PtJ9+/YF9M3uevTogVarxcvLi8OHD7Nlyxa6d+/O9OnTAf3+1Onp6ZQrVw5HR0caNmxI586dcXd3x9XVFQcHBxISEvj000/VvgxeXl7Ur19fzVaD/j3k0qVLj/FOCCHEb5N/CYUQQvxjHlzfCODj40NERATe3t4MGzYM0G/zdOfOHaytrY01TfErP/74Iy1btqRcuXJYWFgQHBzMgQMH2L9/P+np6ZiZmfH2229jZ2fHxo0buX37NqDPSvr4+DBhwgSDclzxbEhKSiI0NBRnZ2ecnJwA+Oabb9Tmdw+ys7PDzs6OgwcPsmXLFnQ6HfHx8Vy/fl1tUhgREUFxcTE6nY6QkBC0Wi0NGzZEp9Nx6tQpJkyYgIODA++++6563ubNm5OZmUlGxn8TSAMGDFDXVwshxJNIysWFEEL8bfHx8YwePZqYmBiuXr2qlnuvWLGCCxcuMHbsWJo3b27kWYpfO3v2LL6+vhw/fpzNmzfzxhtvqP/OZmVl4ezsTLdu3bCxsWHz5s0kJycD+hLeGTNmMHr0aCpWrGjMSxD/AEVRiI+PN8hOnz9/nsTERACWLFnCjBkzAH2g/Nprr1GrVi3MzMzIyMjgxo0bZGdnP/TcmzdvpnHjxrRs2ZI7d+5QUFDAq6++yoULFzh8+DA9evQA4JdffqF79+507tyZPXv2GMxN9lEXQhiLlIsLIYR4LBRFISoqitzcXJo1awaAjY0NP/74I1lZWYSHh+Pp6Qmgbt8kniwXLlxg3rx5fPHFF4B+r+HAwEBWrVpFaGgoJiYm5Ofn8/bbb/PJJ5+QlpYGgKOjI7Nnz+btt9/GwsLCmJcg/iJFUbh+/TqAmp0OCwvDy8urzFgTExOcnZ2pUKECubm5eHl5ERMTQ0lJidoMr5SFhQVOTk54eHjQpk0bPDw8uH//Pj179sTR0ZHY2Fhq1aoFgKenJ7m5uQbbdHl7e5OSklImoJYAWwjxNJIgWwghxJ+yfv16xo0bR8eOHTlx4v/au/P4mq718eOflVlGESKJBCGENCQxFTVVe1UNbdFyi9JqS2lrqmov/baUXwetis7Vq6UoVaVU3VLDVUrNCSqJIYgpyHwyD2f9/jjJvjkJikZieN6v134lZ++191n7ZJE8e631rA2A5Q/sb775hqZNmxrzJkXlKywsNALnRx55pNz86GPHjjFlyhQWLVqE1hobGxuGDBnC6NGj6dy5MydPnjQekkRGRvLWW28B0LRpU/71r3/x+OOPy5zrW4jZbObIkSNGz3RJL3V6ejrDhw/niy++ACA4OJhq1arRuHFjWrRogZOTE0uWLCEsLIxNmzYZ18vKysJsNlOzZk0aNGhAly5dCAsLIzw8nMmTJ/Pjjz8yfPhwnn/+eQBSUlJwdHSkRo0a5OXlGQ9mvv76a2xtba3qKsG0EOJ2Ir8phRBCXNbatWtZvHgxw4YNo1OnTgDcf//9ODo64u7ujtlsNoaG9+nTpyqrKoD//ve/PPbYYwD8+uuv3H///VbHR4wYYTwYady4MStWrCAkJASAmTNnUq9ePWMUwujRo9m0aRPjxo2jT58+kvH9JldYWEhKSgre3t6AJSD28fEhMzOzXFl7e3uioqJ49tlniY6O5sCBA7z33nu88MILAOzevZvPPvuMQ4cOcfz4cWxsbKhXrx4rVqxAKUWLFi1IS0tj8+bNODk5AZaEhr/99hu5ubnG+9SoUYPMzMxyD2bKBthCCHG7kSBbCCGEISUlxSpj77Jly5g/fz6urq5GkN2wYUNSUlKMtaxF1dJak52dDcCSJUuM/UuWLKFRo0bY29vj6+uLUorHHnuMqKgokpOTOXz4MOfOnSMkJIRvv/2WUaNG0aFDB7p16wb8bwqAuPnk5eXx559/Ws2hjo6Opn379sZDFGdnZzw9PcnPzzfmT5tMJi5evEhBQQE7d+5k586dxjUPHjzIvn37aN68Oc2aNWPHjh18//33NGjQgOeff56PP/6YFi1aoLXGy8sLDw8Pzp07R2BgIAD/+te/eP3118v1SMvIByHEnUj+5xNCCEFBQQFdu3Zl27ZtnDhxgoCAAAAGDRqEq6truUy+EmDfPE6cOGHMrS1t7ty5zJ07F4Dly5czZ84cfvnlF8DSkzhkyBCCgoIA6NixI0opbG1tycrKkmRmN5GyGfu7devGf//7XwoKCsqVPXr0KFprRo8ezbfffktKSgoAp06dsirn5+dHcHAw7du3Jzw8nGbNmnH33XfzxRdfEBcXR+PGjWnTpg1HjhzBwcHBeIgDlmHdp06dolq1albXdHBwqMjbFkKIW5oE2UIIcYcpKipix44dnDx50liKx97eHrPZjNlsZuvWrcb+Ll260KVLlyqsrbiScePGGcN1r6Rkliv/hwAAIABJREFU3WJbW1t69OhBTk4OycnJ1KtXD4CAgAAOHz5sLLUkqobJZCI6OtpqDnV2djbHjh0zymitKSgowNPTk+bNmxMTE0Nqaip79+4lJCQEpRT5+fmkpKRga2tLUFAQERERtG7dmrCwMOLi4nj++edp1qwZ06dPN64bHBzMkSNHOHPmDI0bNwbg0UcfpX///tjb21vVs2yALYQQwpos4SWEEHeYrVu30rFjR6pXr86FCxeMP6CjoqKoWbMm/v7+VVxDcSnp6enExMQQGxvLqVOnCA0NNYJnNzc3TCbTZc9VSvHAAw9gMpn4/fffAUvm6OPHj1O3bt1Kqb+4vClTprBkyRIOHz7Mpf4ue+mllzhy5AhRUVE0aNCAr7/+2nhAUqtWLZKTk9m+fTs+Pj7Ur1+f2NhYcnJyGDlyJDt27ODnn3+mR48egGXZtrvvvpu2bduyfft24z3S0tLw8PCQBGRCCFGKLOElhBCinA0bNvDJJ5/QsWNHYzmtdu3a0ahRI1q1akVaWhq1atUCLImLxM3jxx9/ZP369cTExBATE2OsWVwiISHB+P5KATZAixYtrIaKDx48mFdffVUC7Epy8eLFcvOno6KijGkXZ8+eJS4uDgBXV1ccHBzIzMwkPz8fsCSlK83Dw4P09HSqV6/OypUruXDhAp06dSIgIIBjx44ZGf6DgoLYu3cvZ86cMc6NiIgwAurSqlevfsPuXwgh7jTSky2EELeRY8eO4efnZwzn/PLLLxk+fDht2rRhx44dRjmttfRYVaGioiJOnDhhBNAlPdTr1683Aq8RI0YwZ84cq/P8/Pxo2rQp+fn57N27l6ysrKt+TwcHB55++mkmTpwow8IrwYoVK5g/fz579+4tNyca4I8//uD06dO88cYbxMTEYDaby5VxcHAgODiY1q1bEx4eTnh4OHPmzGHhwoVERkYyZswYAJKTk6lZsyY1atTg9OnTxr//5ORk3NzcZL60EEJcJ+nJFkKIO1zv3r1ZvXo1y5cvN5bTeuihhzh9+jSPPPKIVVkJsCtHbm4u9vb2xpJFn3/+OZ999hlxcXHk5eWVK7906VK01sTGxrJv3z48PT1JS0tDa81PP/1Er169AJg3bx5btmy5qjo4Ozvz3HPP8dJLL+Hn51dxN3eH01qTkJBg9E7v2bOHyMhIYz5zfHw8K1euNMpXr16d3NxcHn/8cQYPHkxoaCjnzp3jzz//BMDLy4vQ0FBj7nRAQAAPP/wwMTEx7Nq1y1hjev369YD1SAYvLy8SEhLw9/e3+rft5eV1wz8HIYQQ5UmQLYQQt5iCggI2bNjA1q1brRIXBQUFYWtry+HDh419tWvXZurUqVVRzTtKyXzpstvx48eJjo4mNDQUsAzr3r9/P2BZ2sjd3R1bW1uys7PJysriqaeeuuT1XV1dycnJMV7HxMTQtWtXNm7ceNk6OTs7M378eMaMGUPNmjUr8G7vXAcPHmThwoVGYJ2cnGx1vHbt2jg6OhIVFUVcXBwzZ86kVatWhIeHM2rUKBYtWkSDBg2IiIigWrVqdOzYkZ9//pk//viDd955h+bNm/Pee+8BliDexsYGpRTx8fE0bdoUsKxfPm7cuHLDu0tWBBBCCFH1ZLi4EELcAkoP787IyKBmzZoUFBQQExNjzL9MTEzE0dERT0/PqqzqbUtrzfnz54mJiSEsLMxYT3zWrFmMHz/+sucNGDCAVq1aMWHCBI4ePUpMTAyDBg265DxqHx8f/Pz8cHd3x8bGhtzcXJKSkqhWrRpRUVFGuTZt2rBr164r1vfMmTPSc30dioqKOHz4sBFI9+vXj/bt2wOwcuVKq1EhSikcHBwuOSoB4NChQ/j7++Pm5kZ0dLTxIOXw4cMcOXLEWEJt4cKFPPHEE3Tv3p3//Oc/xvnHjh0jICBAhnsLIUQVkeHiQghxG9qxYweTJk2iRo0afP/99wC4u7szcOBAnJycrNbP9fHxqapq3naSkpL4448/ys2ZTktLAyxJyR5++GGSkpKMNYRdXFxwcnKiTZs29OzZk6ZNm5KcnEz//v3Zu3cvEyZMICgoiJo1a9KmTRtSUlJwdHSkoKCA1NRUzp49S2JiIomJieXqY2dnZ7Ve8ujRo7lw4QIvvfSSUaZevXp89dVXdO3atRI+odtHcnIyq1atMoLqqKgoq3Wh3d3dCQgI4KmnnmLfvn1W52qtjQDbx8eH5s2b06JFC8LDw0lKSqJ9+/a0a9eONWvWEBYWBmAkHIuJiTGC7N69e3PixIlyiegaNmx4w+5bCCHEjSNBthBC3CS01kRFRVGjRg1jeR5HR0c2btxItWrVyM3NNdZEnjdvXhXW9PaQl5fH4cOHjSD6oYceIiIiArDMey1ZK7w0pRRubm68+uqrPPPMMyQlJRnHsrKyyMrKIjw8nOeffx6w/JxCQ0O57777jHLr1q1jw4YNl6yTnZ0dgYGBNGrUyNiCgoJo1KiRMa8bYPDgwaxYscJ4PXLkSN59913c3Nz+3odyG8vNzeXgwYPs3buXhg0bGj+T8+fPM2zYMKuyNjY2+Pj40K9fPzp06ECNGjXYuHGjMYS7cePGRjAdFhbGhx9+yLp16xg7diwPPvggANu3byctLc2Yc11i4cKF1KpVy2rEiYeHR7ls30IIIW5dEmQLIcRN4vnnn+ezzz7j1Vdf5e233wYgLCyMTz/9lG7duhkBtrg+x44dY86cOUZQHR8fb5XR2dHRkWrVqtGkSRNCQ0Np1qwZqampnDt3jqKiIsDyICQjI4OMjP+NGKtRowYeHh7Y2NhQWFjIgAEDjGM///wzBw8etAriGjdubATOpYPoRo0aUa9ePavRCVfSp08fxo4dS+/evaX3uozCwkJ27dpllZTszz//pLCwEIDOnTuzdetWoqOj2bdvHy1btqRz5860aNGCM2fO8Morr9CgQQNmz55NYWEh9vb2fPvtt5jNZiZNmkRRURGLFi0y3m/evHkUFBRw4MABI8iOiIggKirKmEtdoiQxmhBCiNuXzMkWQohKprXm+++/Z9WqVcyePdvIALx48WKeeeYZRowYwQcffFDFtby1lJ4vXXobMmQIQ4YMAWD37t20bt3a6jx3d3eaNm2Kv78/P/zwA9WqVSMzMxMbGxu01jz88MP89NNP2NnZ4enpiYODA4WFhaSlpV12Hm5CQoKRhGr+/Pns3r2bvn37cu+9997YD+EOlZGRQVRUFEVFRcZnnJ2djZubW7llsZRSXOrvng8++IAXX3wROzs7zp07x/bt29mwYQPffvst06ZN44UXXgAs6117e3ujlMJkMuHi4gLAkSNHsLe3p169epK5XwghbiPXOydbgmwhhKgEmZmZuLq6Gq/DwsLYv38/8+fPN4LA3NxctNbGGreivKKiInJzc43gJj4+nsGDBxMTE2PMly6tR48edOnShdjYWA4ePEh0dLQRHPft25dly5ahlGL//v20aNECFxcX4uLi8PHxYceOHbRt2/aydbGxsaF+/frleqQ7d+5s1E9UrJSUFPbt28eePXuMXuojR44A0LZtW7Zv386LL77I5s2bOXjw4CUDant7e0JCQox1pxs0aMD//d//ER8fT3JyspFk7PXXX2fatGk8/fTT/Pvf/zbO37JlC6GhoZJgUAgh7gCS+EwIIW5C8fHxDBgwgHPnzpGQkICNjQ0AI0aM4MSJE7Rs2dIoK8PB/6fsfOmS7fDhwzz33HPMmjULAE9PT7Zv3w5YeimdnZ1RSpGdnY3ZbGbNmjWsWbOm3PVdXFzw8vIyeh2/+eYbioqKeOqpp4wEckFBQdjY2FCvXr1yw7obNWpE/fr1JevzDXT+/HkSEhKsRh+Eh4dz6tSpcmXr1q1LYGAgAAcOHODAgQOAZW3q8PBwIiIiCA8P5/jx48ybN48uXboQGRkJWEZBDBkyhMzMTCNzPMDTTz9N3759yw337tix4w25XyGEELcP6ckWQogKUlhYyO+//46NjY3xh3heXh41a9YkKyuLgwcPEhISUsW1vLlkZGQQExODnZ2d8cAhOTkZb2/vckN9S5T0Hi9cuBBvb2+WL1/OypUr+eabb6zK2draGsO7CwoKyl1ny5YtdOjQAYAlS5Ywd+5c+vbty8iRI40yeXl5ODo6VtTtikvQWnPmzBmjZ7pkDvXZs2epXr0677zzDtHR0URHR5OSkkJBQQEtWrQgODjYWCc+PT0dNzc3lFKsXbuWvLw8IiMjiYqKYteuXUaW7m+++YahQ4fSqVMnNm/ebNTht99+o27dujLcWwghhBUZLi6EEFXsww8/ZMyYMXTt2tUqe/T69etp1qwZtWvXrsLaVS2z2czmzZvL9UyfPXsWgF69erF8+XKOHTtmrCNdWFiIg4MD1atXZ/To0cbc6R49epCYmMjmzZvp1KkTycnJ1KtXj6ysrMu+v1KKunXrWvVGP/roo+WWTBI3ltaaU6dOWX3uffr04ccff7yq8++//35+/fVX4/XcuXPJysri66+/JjAwkOXLlxvHWrVqxZ49e1i2bBn9+vUDLL3jhw4dIjw8XIZ7CyGE+EsSZAshRCVaunQpCxYsYPz48UaypWPHjtGmTRv69OnDl19+ecf1iJnNZk6cOGEE0M7OzowaNQqwBFceHh6YTKZy5zk6OuLo6Eh2draR/bk0T09PUlJSAPjoo48YPXo0ERER/Pzzz/j6+qK1xt3dnczMTAICAi65/FWDBg1kOH4lM5vNHD161KqHeu/evaSmppKamsp//vMf5s2bx9atW63WpS7N29vbmDsdHh7OL7/8wpYtW/jss8944IEHANi2bRv33HMPfn5+nDlzxjh369atuLi4EBISIqMRhBBCXBeZky2EEDfQ8ePHjTmfAL/++iurV6+mXr16RpDdsGFDLly4YLWe8e1uxowZ7Nu3j5iYGOLi4sjNzTWOlQS6zZo1w8fHh27dunH48GFjvmyJvLy8y2bqBnjllVfQWqOUIjg4GH9/f1q0aIGvry9g6aWOiorCz89PksZVkcLCQmxsbIycAzNmzGDatGlkZmaWK2tvb8/hw4c5efIk69atAzB+tiXBtJeXF/Pnz6eoqIi1a9ca565cuZLjx48TFRVlBNnh4eEsX77cmEtdomQqgBBCCFHZpCdbCCGuIC8vj4iICGJiYjh16hT+/v6AZT7v5s2b6devX7nESLeLjIwMYmNjrYZ3K6WshvaWZEkv4eDgQHBwME2aNOGPP/7g1KlTLFiwgMGDBwOWgCg6Ovov37tOnTpGkD506FDuueeeir9BcV3y8/P5888/rXqno6KiePvttzGZTERHRxsPU5ycnAgLCyM+Pp6LFy8yY8YMxowZg4ODAwcPHmTbtm3ExcWxceNGRo0axbPPPgtYhnX7+PiglCIjI8PIzL9r1y4yMzOJiIigevXqVfkxCCGEuANIT7YQQvxNOTk5rF+/nvPnz/PMM88AlqHMNWrUwN7enj179hhBdseOHW+LLMNaa1JTU6lRo4axb/jw4axZs8Zq6G0JOzs7Xn75ZeLi4oiNjTWWTyqRlJSEm5sba9as4fvvvy83TDc/P9/43s/Pr9yw7kaNGtGwYUOcnZ0r+E7F37V27VomTZrEgQMHLplIbty4ccb3tra27Nmzh+bNm2NnZ8eKFSswmUwsXbqUr776iv379xMaGkpoaCivvfYaUVFR7Ny50wiya9euzcKFCwkJCbEa5l92nXMhhBDiZiQ92UKIO1rJMGSwzOHs2LEj1atX58KFC9jb2wMY6yYXP8m8JZWdL116KywsJCMjw/gcHn30UX744QfA0jNtNpsvOVe6rPDwcNauXYu3tzcxMTGEhITQuHFj4uLijDLbtm3D1dWVhg0bylrSFWj27Nn06dOnXCK3hIQEVqxYwZgxY/7yGpmZmURHR1v1UL/++us0bdqUGTNmsHXrVo4dO3bJc21tba3Wns7KymLTpk106tSJKVOmAJY26OnpSUZGBvv376dZs2YAHDx4kMOHD9OqVStJRCeEEOKmIj3ZQghxDVauXMkHH3xAz549mThxIgDt2rWjZcuWtGvXjqysLGM4anBwcFVW9Zrk5eVx5MgRDh8+TJ8+fawC5xUrVlzyHKUUoaGhPP3004wfP55JkyZRWFjIypUrrXqeL8fHx4dGjRrx5JNP4u3tDUDjxo0xmUzGMN8S7du3/5t3KMqaPXs2Y8eO5cMPP2TTpk1GoJqQkMC9995LfHw8wCUD7aNHj/LGG2+wd+9e4uLiKPvgvWT5q/nz5xv73NzciIiIICIigrCwMP7zn/9w9OhRli9fTv369QGYN28emzZtsrqejY0Nn3/+ObVr1zaW1AKMHm0hhBDidiFBthDitmc2m9m9ezehoaHGMOTz58/z22+/kZOTYwTZtra27N69uyqrek1iY2PZsWOHVa90fHw8RUVFgKWHMDU1ldjYWE6dOoVSCltbWwoLC3n++efp0KEDLi4uPP744xw6dIioqCgAWrRoUS4Rmbe3t1XW7pIh3kFBQbi5uZWrm62tbbkAW9wYffr04cMPPyQ+Pp4uXbowYMAATp48ydq1a0lJSaF+/frUrFmTd955h127dhEcHEyDBg2Ijo7mjz/+sGrzbm5umEwmIiIimDJlCm3atKFGjRpMmTIFFxcXNmzYQN26dfniiy+Mcz766CP27dvHvn37jCC7a9euzJ07l1atWlnV9fHHH6+Uz0QIIYSoSjJcXAhx2+vQoQO///47y5cvp0+fPoAlyP7uu+946KGHjMDgZqO15sKFC1ZB9Jtvvmn0sI8bN47IyMhy55VkeDabzZe99qpVq+jduzdZWVlGMBwVFWVkaF63bh2pqalGMC3/9958zGYzJpOJ1NRUzp07x6BBgzh+/Pg1X2fo0KH079+fFi1acPr0abZt20Z8fDwHDx7k9ddfp1OnTsD/plP4+/tz6tQp4/wVK1agtaZjx47UqlWrwu5PCCGEqGoyXFwIccfLyclh+fLl7Nixgw8//NDY37p1a6Kjo60SedWuXZvRo0dXRTWvaOPGjXz77bdGUJ2ammp13MvLixYtWtC7d29at25NkyZNiI2NtSpzpeDaw8ODRx99lF69egHg4uLCvn37CAwMtJpz3q1btwq8K3E5ZrOZ9PR0Y+3o0puvry+dOnUiIyOD5ORkxo8fbwTVSUlJZGRkGMOxe/fuzYABA3jnnXf+8j3d3d1p3bo14eHhBAQEsHPnTr766it69OiBj48PrVq1on///mzYsIEHHnjACLLDwsJ4//33iYiIsMplUPLgSgghhBAW0pMthLil5efn4+DgAFieNtasWZOCggJiYmJo0qQJACkpKbi4uJTLdF3Z8vPzOXLkSLnEY3PnzqVFixZorXnnnXeYNGmScY5SisDAQBo3bszOnTtJSUnhnnvuYevWrQCMHDmSzz//3Op9XF1dCQwMJDQ0lCZNmlgN75Zljype6YCzoKCATZs2GYHyuXPnSEhIICsrC601rVu3ZsKECbz99tukpKTwwQcfXPX72NvbXzKrt6OjI927d8fZ2ZnFixdf8RrdunXjySefNIZtJyYm4uvri1IKk8lkJKNbt24dp06dokuXLlbzp4UQQog7ifRkCyHuKJs3b2bs2LHUr1/fSOjl7u7O8OHD8fDwsJoPXHp5qspgMpmwtbU15n+vWrWKl19+mWPHjhnzpUsbPHgwWVlZJCYmlks09t577/HSSy8B/7uP0kHPQw89RO3atWncuLERSHt6et6oW7ttFRYWkpaWZgTHHh4eBAUFsW/fPhITE/nyyy9JTU0lPT0dk8lEZmYmOTk55Obm4u3tTUBAAOnp6aSlpZGYmHjZ98nLy2PixIm8+eabV5VUDiwZ3j08PBg0aBD33Xcfnp6eJCYmsmTJEho0aECvXr3Iy8tjwIABf3mtdevWUb9+fSPI9vHxYfr06TRp0gRbW1ujnIxkEEIIIa6f9GQLIW56BQUF/Pbbb9SvX98IMKOiooiIiMDNzY2kpCSjN7uylMyXjo2NLdczffr0aRYvXkzfvn1xcHDgl19+4cEHH7zm9/D29uaHH36gQ4cOAPzyyy94enrSvHlzqlWrVtG3dMsrKioiISGBU6dOcfbsWc6dO8f58+e5ePEiycnJeHp6GsHwhQsXiIqKIjs7m9TUVEwmk9W1hgwZwueff35d63U3bNiQOnXqGMtV7dixw8i+HhQURK9evRg7dixgyQDu5OTEvffeS40aNfDw8CA6OpotW7bQuXNnRo4ciZOTE1pr/Pz8SEtL48SJE9SuXRuAt99+m0mTJuHq6kpmZiZ2dnZXXG7t/fffp1OnTrLetBBCCHEVpCdbCHHbevbZZ5k/fz6vvvoqb7/9NmCZH7po0SK6det2QwNss9nMyZMniYmJISgoiMaNGwOwZs0aY17zpQwePBhfX19OnTpF27Ztefrpp5k7d265cvb29tSqVYv69evTrFkz2rRpQ0hICI0aNcLLy8uqbPfu3Sv25m4iJUm8Lly4QGpqKvn5+WRkZHD+/HkKCgrIz88nNTWVPXv2cODAAdzd3XF3d6dXr148+eSTNGnShLS0tCvOR78adnZ2+Pn54eHhgZOTE4GBgVSrVo3k5GScnJzw8vKievXqeHp6UlRURG5uLiEhIXTu3Bl3d3ccHR2ZPn062dnZfPfdd8YUhcmTJzNu3DjGjRtHr169iIyMpKioCDs7y6/h2bNnG0nDdu7cycqVK/Hy8sLJyQmwTBvIysoiNzcXk8lkBNl+fn7UqlWLixcv0qBBA1577TVeeumlcnP5S5SMihBCCCHEjSNBthCiSowbN47evXvTtWtXwJLwa9WqVQQHB7Nq1SoWLlxoBJkPPPAAa9asMQIOsAQdAwcOrNA6paWlsX79eqte6bi4OHJycgB44okn8Pf3Jzo6mpiYGKtzW7VqxXPPPUfTpk0ZPnw4f/75J6dPnyYnJ4fq1aszcOBAjh07hq+vLy1btqRt27YEBwfj5eVlzOe9VRUWFpKenk716tWxtbUlNzeX33//nV27duHl5YWvry9169bF29ubcePGceHCBQ4cOEBubi55eXkUFhZed3Bcv359XFxcSElJsdpvY2ODnZ0dDg4O2Nvb4+DggJ+fH+3atTMC6OjoaNzc3Jg8eTJFRUXk5OSwcuVKfvzxR4KCglBKER8fT2pqqjFUPy4uzgicX3nlFWbMmEFISAgPPfQQYOlNX7NmDWCZNlBStmSuc3p6ulFHW1tbOnXqhL29vdU0gq5duzJjxgzCw8Ot7umPP/7A2dmZOnXqGPuGDh3K0KFDmT17Nn369KFu3bo8+uijvPLKK3z22WfX9ZkKIYQQ4u+R4eJCiEq3YsUK+vbtC8C9995LnTp1WLhwIQD16tXj5MmTzJ8/nyFDhgCW4eI2NjZWc0avl8lkshrifffdd/PII48A8OeffxIaGnpd1x02bJjRU/3dd99x8OBB+vfvT7Nmzf52nW+kvLw80tLScHR0NJKipaSksHLlSlJSUoiPjycpKYmUlBTS0tIwmUyYTCays7NRSpGXl0d2djYAtWrVwmQykZubW+59xowZw8SJE60CxMtxcHAgICAADw8PoxfZy8uLkJAQcnNzSU5OprCwkKKiIvr06cOoUaOIiYkhOzubfv36UVRUxOnTp43rjRgxgjlz5jB16lRef/11AKvAOS8vzxgNMXHiRN577z3Gjx/PzJkzAUvgbG9vj6urKydOnDDOW7x4MT/88IPRm17iq6++wsXFhd69exvDzTMzMyksLMTNza1C2vHV2LhxI8OGDePkyZPGvoyMjEuuay6EEEKI8mS4uBCi0hUUFGA2m43eupSUFL7//nsKCgp44YUXjHKvvPIKy5YtY/LkyQwbNoz777+fgQMH8u2337Jp0yaj3MiRI7nrrrvIzMw0lg0Cy5Dq65WSksLUqVOt5kuX5u3tzaJFi1i8eDGNGjWiYcOGHDt27LLXq1atGrVq1SIwMJC77rqLtm3b0qVLF/z9/Y0yAwYMuKokVH9XQUEBFy9eJD093dgyMjKMBFxJSUlcvHiR7Oxs8vLySE9PJykpif79+5OXl0dqaipr167lyJEj+Pv74+rqyjPPPEP37t0ZNmzYNdfn4sWLxvdKKezs7HB2dsbT0xNbW1u8vLyYNWsWeXl5fPbZZzg5OTF06FB8fX3x8/Pjs88+Y9WqVbz33nvG8mrHjx+nQYMGODs7GxnVAYYPH86XX35Jly5dUEoREhJCSkoKCQkJxmdT0m58fHwICAiwGgnh5ubG008/jbu7u1Uv8lNPPcV9991HUFCQsc/W1paCgoJywfHjjz9uJBAr7VKfXelEfJWla9euHDhwwKpXe/369bLklhBCCHGDSU+2EMKQkpJCYmIitWrVMuaHnjt3jvfffx+ttdVyQ0888QQLFy7kk08+YdSoUQAcPXqURo0a4erqapVIqiQgateuHdOnT6dr166kp6cTFBREUlISAG+++Sb/93//d031NZvNJCQklEs8dvfdd/Pcc89x6NAhtmzZYvRIlvD29qZp06YkJCRw/PhxAI4cOUJQUBBRUVH06tWL/Px8/P39adKkCa1bt6Zz586EhYVVSC9kyfzjsoFx2WB5ypQp5OTkkJqayrvvvsu6devo3r07LVq0IDw8nJycHCMpWkUZMWIEb775Jk8++SRms5kNGzZgb29PjRo1cHNzw8PDg4sXL5KRkUGfPn149dVX8fDw4PDhw7Rv357atWsTFxeHm5sbNjY2DBgwgKVLl/LRRx8ZD17i4+Np2LAhLi4uZGZmGu/97LPP8u9//5tp06bx2muvAZY22blzZzw8PPjtt9+wsbEB4KeffmLfvn3ce++9dOzYEbD0OO/evRt3d3eCg4ONssLSq/3TTz8xa9asqq6KEEIIccu43p5stNY3/Qa4Azo9PV0LIa7N/v379YoVK/TRo0eNffHx8br1UZ/nAAAbLklEQVRXr1764Ycftirbr18/DeiPP/7Y2Hf06FENaBcXF6uyzz77rAb01KlTjX0ZGRn6oYce0sOGDdNFRUXG/kOHDum33npLAxrQTz/9tD537pweMmSIsW/IkCE6MzNTZ2ZmarPZbPVeeXl5+vz581avIyIitJOTk3H+1W6NGzc2rrNw4ULdqlUr/cQTT+hTp05d1edZUFCgk5KSdHx8vN63b5/+7bffrI4vWbJET5w4UW/bts3Yt23bNn3XXXdpPz8/7ezsfNV1tbW1veyxN954Qx84cEDb2NhoV1fXK16nZcuW+tNPP9WLFi3S06dP125ubrpOnTp68uTJ+p133tFz5szRYWFhGtAffPCBUe89e/ZoQNepU8fqHh977DEN6I8++qhcO6levbpV2XfffVf37NlTr1ixwtiXmZmpZ8+erb/++murn/WFCxf02bNndU5OzlX9LIQQQgghbqT09PSSv6fc9TXEr9KTfZ3KJm26krS0NF544QUSExO57777ePHFF8sNHbyW64k7S1FRESaTyZgvC5bM1gcOHKBbt25EREQAEBMTw8MPP0y1atWIjo42yj722GMsW7bskj2Jzs7OZGVlGWVHjhzJ0qVLmTJlCi+++CJgmUs6depUatasycsvv2z0Dpb0QJcMBf4rJpPpqv/9Pvfcc+zZs4c6deoQExPD0aNHadCgAW+99RY9e/Y0hmyX1OFK7OzsqFmzJoGBgYSGhtK9e3f69u1LbGwsZ86coWnTpvj5+QFw8OBBvv7663K9yiXDr9PT0y8533jixImkp6eTmprK5s2bOX/+PDVr1sRsNjN16lQiIiKuqsfZ39+fVq1aGb3FJQm0HBwccHNzw9nZmfT0dLKyshg9erTRQ//zzz/Tu3dvAgICWLBgAZ6ennh6evLkk0+yceNGFixYwODBgwHYs2cPrVq1wt/fn1OnThnvPXDgQNatW8fMmTMZOnQoAGfPnuXll1+mdu3aVqMYtm3bxoULFwgLCyMwMBCw9M7n5eXh5OR0yydyE0IIIYQA6cmuVMuXLzd6iJ577jmdkZFx2bKrV6/W7u7uVr1KYWFh2mQyXdf1KsLYsWP1hg0bbuh7VLaSe4qMjNQnT57UqampetCgQfq+++7Tb731lj506JCOjIys6mpqrbXOzc3VcXFxet++fVb758yZo4cNG6Y3b95s7NuzZ49WSml/f3+rso8++mi5nsT4+HgNaGdnZ6uyb7zxhm7btq1etGiRsS87O1t/+eWXesWKFVY9iWV7kP+K2WzW2dnZOikpSSckJOjY2FgdGxtrVWbVqlV67ty5+qOPPrrmXudLbRs2bNCJiYn6zTfftOrpdXBw0J6enjogIECHhITosLAw3axZM92wYUNdq1Yt7eXlpZOTk/XRo0f1rl27dMuWLTWghw4dqt9++229e/duvXr16quuh7Ozs/b19dW+vr5XLDd8+HCdlpamf/31Vz1x4kQNaFdXV92jRw89ePBg/eKLL2o/Pz8N6JkzZxqf2y+//KIB3bRpU6ufy/33368BvXDhQmNfVFSUbtiwoe7evbvVZz9nzhz96quv6j179hj7TCaT3rRpk46Kirqmn7UQQgghxJ1GerIrUdkeuXr16vHVV19Z9UJnZGQwfvz4S66LCzBt2jQmT56MUuqqrldRSmd1bt++PV9++SV169bl008/5ejRowQFBdG7d2/WrVvHmDFjKvz9b4TS9wSWz69sdmEHBwfy8/OJjIz8y/sq/Q/EbDaX+97W1tZI9GU2m41ezgMHDqC15uGHHyYtLY2cnBxmzJjB77//zsiRI+natStms5no6Gj69OmDj48PmzdvNq47YcIE1qxZw4cffsiLL75IdHQ0p06donfv3lSrVo3s7GxOnDhBYmIiy5Yt49ChQ9x33320bt0arTV5eXkcOnQINzc3AgIC0FqTkZGBo6MjTZo0ITs7m+zsbDZv3ozJZOKee+6hZ8+eABw6dIg333yT5ORkcnJyjKWV8vLyyM/Px9XVlXbt2pGXl0dubi6//PIL2dnZVgmjSjg7OzNq1CheeuklEhMTuf/++0lOTr6un+27777L0qVL2bt3Lx4eHphMJubOnYudnZ3RM1tRpkyZwqBBg5gzZw4HDhzgl19+KVdGKYXWmtGjRzN79mwA5syZw4gRIwgICGDChAlGL/LLL79MbGwsS5YsMZKgrV+/nn/84x+EhoZy4MAB47qjRo0iNjaWN954g86dOwNw+vRpFi1aRJ06dazu9fjx45jNZnx9fY3M1UIIIYQQouJdb0+2BNnX6VLDIZ977jlmzJhBz5492blzJ3l5eVe8xsCBA/H09OTjjz++4vDKqKgozp8/z/bt25kwYQLOzs7XPRyzbEBva2tLjRo1rLIC29raUlRURJcuXbCxsTGWxOnWrRvBwcGAZa3YZcuWUadOHaula6ZPn05aWhpFRUUUFRVhNpuN78tuJceeeuopevToAViWUBo/fjx+fn58/fXXxnWfeOIJ4uLiLnnNgoIC4uPjr+r+q1evzpNPPmkk/3nwwQdZv369VTD9Vxo3bkxaWhqzZ8+mW7duxlrOAHXq1OH06dM8/vjjLFmy5KrqVKJ+/fqEhIRw1113ERISwrBhw9Ba07dvXx5++GEeeeQRJk+ezMcff3xN170cpRR169Zl6dKlrFu37pqTjl3qeqU/vy+//BKz2cyIESOu+5odOnQgOjoak8mEvb09BQUFfPHFFwQFBTF+/HjS09M5ceLEZc/v168fY8eOxd3dnS+++IJPP/0UW1tbfH19jWB4z549ZGVlMXPmTMaPHw/AN998w9ChQ2nevDlLliwxyt5zzz3Exsby448/cv/99wOW4df/7//9P+666y6mTZtmvPdPP/1kZEkvWbYqLy+PrKws3Nzc/lbGdCGEEEIIcePJcPFKRgUMey3ZSg8Xv9QWEhJi9drGxkZ7e3vr4OBg3bZtW/3ggw/qgQMH6ueff16/9tpreubMmXrt2rVaa60TEhL0kiVL9IIFC7TJZNJms/m661l6eOqKFSs0oNu1a2f1ufzV0NlLbbNmzTLO//333zWgg4KCrK5bkpSporZWrVrpwsJCY+jttWx2dnYaLAm0xo4da+y3tbXVrq6u+syZM7p///4VWl+wDJOeOnXq37qGs7NzuWRakZGResGCBcaQ5YraXnzxRb1p0yb9xBNPVOi1X3nlFaNdvPHGGxrQtWvX1k899ZQeP368njZtmq5Vq5YG9OLFi63abJ06dfTgwYOt2taUKVP0mDFj9OHDh419586d0z///LPeu3evVdnSydyEEEIIIcTtTYaLV7KKTOzzV+vyXo/HHnuMpUuXGj1yJc6ePWskebpa/v7+2NjYUL9+fZo3b87QoUO5cOEC33zzDXFxcXh4ePDII48wduxYpk2bxt69e9m5cyf5+fnA/3o4i4qKKCwsRCmFs7MzZrMZs9lMbm4uSik6depEy5Yt+fPPP9m9ezenT5/G2dmZjIwMVq9ezXfffceSJUsoLCyskM8oIyODo0ePGsOgK8off/xBRESEMaS8oixbtox+/frxxhtv8N5775GTk3PZsi1btqRWrVo4ODiwc+dOEhMTL1u2dFKse++9l//+97+XLfvFF18wZMgQ7O3tGTBgAD/88IPV8ZLeZoBPP/2UkSNHApZloebMmWNVtmzP96UsXrzY6EWeMGECOTk5/Pvf/yYsLAywjPL48ccfCQkJoX///sZ5+/fvx9bWlsDAQBlSLYQQQgghrosMF69kt0L23JCQEFxdXYmNjSUjw9Im3N3dje8rmtaaHTt20Lt3b6vh5xVx3f379xuBVUVJSkqiqKiI2rVr/2VZV1dX7O3tycrKoqCg4IrBYVxcHI0aNeLrr79m7NixmEwmbG1tsbe3N4YIm0wmlFKsWrWKJk2a4OLiQs+ePdm3bx+BgYEEBgZib29Pfn4+mzZtwsbGhqNHjxqZnLt3787atWtp27Yt7dq1w87Ojvz8fGOecHx8vFF28ODBLFq0iO7duzNgwADs7Owwm83Gw5djx47RoEEDAMaPH8/HH3/MY489xoQJE7Czs8POzo4HH3wQOzs7Nm7cSN26dQHLkOp58+bRo0cPxo8fb2QdHzVqFGazmenTp1OzZk0AduzYwezZs1m8eLFRpy1btnDy5Mkrfu63wv9PQgghhBDi9lSpQbZSahTwMuAL/AmM1VpvuUL5fsA0oCFwDJistV5xDe93UwXZ17IU0dXw9PQkNTW1wq53JVfTe1iWnZ3dVfUea63ZvHkzXbp0+cs6dOrUiezsbHbt2lXuvZRSFBYWorXGycmJnJwcjh8/Ts+ePYmNjUVrjaOjIw4ODkbZ7Ozsa7onPz8/Tp48iVKK/fv3079/f44ePWokKHN2dubo0aOMGTOGgIAAjh07ZgTIXbt2ZdOmTbz33nsMHDgQOzs7Dh06xL333ouvry9nzpwxHsIMGjSI1atXM3PmTJ555hkATpw4Qc+ePalRowZbtvzvn83777/P5s2bGTZsGH369AEgNTWVSZMm4eTkZMwjB1i7di379++nQ4cOtGvXDoD8/Hx++OEH7O3t6du3rxH0Hj9+nAsXLlCnTh38/f2Nn9XZs2dxcHDAy8vLKHujjRs3jjZt2vDaa68RHx9PvXr1jEDb1dWVzMxMq/IZGRm4ublVSt2EEEIIIYQordLmZAMDgHzgGaApEAlkAnUvU74dUAj8C2hS/LUAuPsa3vOmmpP9V3OoK3vz8vLSZ86c0d99953VHGNfX1/dsGFDHRwcrN3c3DSgGzRocM3XP3z4sH7ttdeMubyjR4/WH330kf7888913759NaB79+6ttdY6JSVFr1u3zli2bMmSJTo6OlofOnRIT58+XSul9COPPKK1tsxvzc3N1c2aNdNeXl5Wywz9+OOPOjAwUA8ZMsTqs+/bt69u0aKF3rVrl7Fv7dq113xPpZdK0lrrpUuX6tmzZ1vNy01KStI//PCDXr9+vVXZkuW3kpOTjX0FBQU6KSnphi+/djuIjIw02uLJkyeN/SdPntT169e3+jktX768CmsqhBBCCCHuZJU2J1sptQPYq7UeWWpfDPCj1vpflyj/XXGlHiy17xcgVWv9+FW+503Vkw2WHrkHHniAtWvXEhkZ+beutXbtWj7//HPatm1LTEwM8+bN+8tzzGYz8+bNY/Xq1fTt25dBgwYBUFhYyIQJE7C3t+fNN9+kWrVqAGzbto1du3ZhMpmMLNJubm6YTKa/fK+SNnLw4EGUUjRq1AgHBwfA0qufnp6Oi4sLnp6exjkmkwkbGxuqVat2w3tJyy7hVbNmTWrVqkVMTMxlz7nWdi8q1uzZs+nTp48x9LxEQkICK1asoFmzZvz0009WvfdCCCGEEEJUpkoZLq6UcgCygcd0qeHeSqnZQLjWuvMlzkkAZmmtZ5XaNw7LEPN6V/m+N12QDZaAoHPnzldcQgjAycmJ3NxcALy9vblw4YLV8ZIhsVd7Pfh7QeK4cePIz8/n008/varyt8KQ3XHjxtG7d28OHDhQLnjbuHEjQ4cOtVo3+1a4JyGEEEIIIUTVud4g+1q7GGsCtsD5MvvPAz6XOcfnGsujlHJUSrmXbMBNGQ2tWLHiLwPiGjVqsG/fPuP15s2bqV+/vlWZ9evXW13P29ubpk2bGserV69erjf4anqgL2fWrFl88sknxtfw8HDjWHh4ODNnzqR9+/bl6nczmzVrFl27dmXMmDHleke7du3KoUOHjEzXcGvckxBCCCGEEOLWc6092X7AGaC91np7qf2TgSe01k0ucU4+MFRrvbjUvkHAXK2102XeZwrwRtn9N1tPNkBkZCQODg589dVXDBs2DICpU6fyz3/+k4SEBGbPnn1NQ2IvN4z20KFDDB8+nN9//x2A5cuXG8mxbpSNGzfedkN2b8d7EkIIIYQQQlS822q4uFLKESi9yLAbcPpmDLIrmwSJQgghhBBCCHHjVdoSXsWJz/ZorUeV2ncIWHmFxGduWusepfb9B0i7lROfCSGEEEIIIYS4fV1vkG13He/1AbBAKbUb2A4MB+oCnwMopb4BzpQKuGcDvymlXgFWAg8D9wMdruO9hRBCCCGEEEKIm9Y1B9la6++UUl7A64AvcBDoobU+WVykLmAuVX6bUuqfwHRgGnAMGKC13vF3Ky+EEEIIIYQQQtxMrnm4eFWQ4eJCCCGEEEIIISpTZS3hJYQQQgghhBBCiMuQIFsIIYQQQgghhKggEmQLIYQQQgghhBAVRIJsIYQQQgghhBCigkiQLYQQQgghhBBCVBAJsoUQQgghhBBCiAoiQbYQQgghhBBCCFFBJMgWQgghhBBCCCEqiATZQgghhBBCCCFEBZEgWwghhBBCCCGEqCASZAshhBBCCCGEEBVEgmwhhBBCCCGEEKKCSJAthBBCCCGEEEJUEAmyhRBCCCGEEEKICiJBthBCCCGEEEIIUUEkyBZCCCGEEEIIISqIBNlCCCGEEEIIIUQFsavqClyLjIyMqq6CEEIIIYQQQog7wPXGn0prXcFVqXhKqTrA6aquhxBCCCGEEEKIO46/1vrM1Ra+VYJsBfgBpqquC+CGJeD35+aojxAlpG2Km5G0S3GzkrYpbkbSLsXN6E5vl27AWX0NgfMtMVy8+Iau+snBjWSJ9wEwaa1l/Lq4aUjbFDcjaZfiZiVtU9yMpF2Km5G0S675niXxmRBCCCGEEEIIUUEkyBZCCCGEEEIIISqIBNnXLg+YWvxViJuJtE1xM5J2KW5W0jbFzUjapbgZSbu8RrdE4jMhhBBCCCGEEOJWID3ZQgghhBBCCCFEBZEgWwghhBBCCCGEqCASZAshhBBCCCGEEBVEgmwhhBBCCCGEEKKCSJB9jZRSo5RSx5VSuUqpPUqpjlVdJ3H7Ukr9Sym1SyllUkpdUEr9qJQKLlPGUSn1kVIqSSmVpZRapZTyL1OmrlLqp+LjSUqpD5VSDpV7N+J2VdxOtVIqstQ+aZei0iml6iilFiqlkpVS2UqpKKVUy1LHlVJqilLqrFIqRyn1X6XUXWWu4amUWqCUSi/eFiilqlf+3YjbhVLKTik1vfjvxxylVLxS6nWllE2pMtI2xQ2llOpU/Dv3bPHv7EfKHK+QNqiUaqaU2lx8jTPFbV1Vxj3eTCTIvgZKqQFAJPD/gAhgC/AfpVTdKq2YuJ11Bj4B2gL/AOyAdUopl1JlIoE+wD+BDoArsFopZQtQ/PVnwKX4+D+BfsDMSroHcRtTSrUGhgP7yxySdikqlVLKE/gdKAAeBEKAl4C0UsUmAuOBF4DWQCLwq1LKrVSZb4FwoHvxFg4suNH1F7e1V4DnsLS7plja4cvAi6XKSNsUN5oLEI2ljV3K326DSil34FfgbPE1XgQmFF/3zqK1lu0qN2AH8FmZfTHA21VdN9nujA2oBWigU/FrDyAfGFCqjB9QBDxQ/PrB4td+pcr8E8gF3Kv6nmS7dTcsgfNh4H7gv0Bk8X5pl7JV+ga8A2y5wnEFnANeKbXPEUsQPqL4ddPi/2PvLlWmbfG+4Kq+R9luzQ1YDcwts+8HYEHx99I2ZavUrbjdPFLqdYW0QWBk8TmOpcq8CpyheOnoO2WTnuyrVDyEsSWwrsyhdUD7yq+RuEN5FH9NKf7aErCnVLvUWp8FDvK/dtkOOFi8v8RaLP95tkSI6/cJ8LPWen2Z/dIuRVV4CNitlPq+eHrNPqXUs6WOBwI+WLfLPGAz1u0yXWu9o1SZP4B05He9uH5bgfuUUo0BlFJhWEbwrCk+Lm1TVLWKaoPtgM3F55ZYi+VBe/0bVfmbkV1VV+AWUhOwBc6X2X8eS6MU4oYqns/yAbBVa32weLcPkK+1Ti1TvHS79KFMu9Vapyql8pG2K66TUuqfWILhVpc4LO1SVIUGWHpRPgDeAtoAHyql8rTW3/C/dnWp3+P1ir/3AS5c4toXkHYprt+7WB6SxyqlirD8PTlZa724+Li0TVHVKqoN+gAnLnGNkmPH/1YtbyESZF87Xea1usQ+IW6Ej4HmWJ5+/5Wy7fJSbVTarrguSqkAYDbQTWudey2nIu1S3Dg2wG6t9aTi1/uKk/aMBL4pVe6vfo9LuxQVbQAwGBgI/IllHmukUuqs1np+qXLSNkVVq4g2eKlrXO7c25YMF796SVjmD5Z9WuhN+ac+QlQopdRHWIZC3qu1Pl3qUCLgUJzwp7TS7TKRMu22uLw90nbF9WmJpY3tUUoVKqUKsSTpG138/XmkXYrKdw44VGZfDFCSnDSx+OuVfo8nArUvce1aSLsU1+894B2t9RKt9QGt9QJgFvCv4uPSNkVVq6g2WO53e/E14A5rpxJkXyWtdT6wB0uG59L+AWyr/BqJO0HxcgofA32BrlrrssNs9mDJpPuPUuf4AqH8r11uB0KL95foBuQVny/EtdoANMPSG1Oy7QYWlfpe2qWobL8DwWX2NQZOFn9/HMsfgKXbpQOWB0Sl26WHUqpNqTJ3YxnqK7/rxfVyBsxl9hXxv7/DpW2KqlZRbXA70KnMcpzdsGQbP3GjKn8zkuHi1+YDYIFSajeWRjQcyxPyz6u0VuJ29gmW4WUPAyalVMnTwXStdY7WOl0pNReYqZRKxpIQ7X3gAFCSjGodlt6dBUqpl4EaxWW+1FpnVOK9iNuE1tqEJYmZQSmVBSSX5AuQdimqwCxgm1JqErAUy5zs4cUbWuuStdwnKaWOAEeASUA2lmVp0FrHKKV+Ab5USo0ovu4cYLXWOq5S70bcTn4CJiulErAMF4/AsqTRVyBtU1QOpZQrEFRqV6BSKhxI0VonVFAb/BZ4A5inlHoLaFR8nTd1carxO0ZVpze/1TZgFJYnMSW9LZ2quk6y3b4blvkrl9qeLFXGCfgISMbyn+FPQECZ69TFsoRIdnG5jyi1vIJssv3djVJLeBW/lnYpW6VvQC8sD3NysQwVf7bMcQVMwTK0PBdL5tzQMmVqAAuBjOJtIVC9qu9Ntlt3A9yASCyjKnKAY8B0wKFUGWmbst3QDehymb8p5xUfr5A2iGWk22/F1ziHJei+o5bv0lpbblgIIYQQQgghhBB/n8zJFkIIIYQQQgghKogE2UIIIYQQQgghRAWRIFsIIYQQQgghhKggEmQLIYQQQgghhBAVRIJsIYQQQgghhBCigkiQLYQQQgghhBBCVBAJsoUQQgghhBBCiAoiQbYQQgghhBBCCFFBJMgWQgghhBBCCCEqiATZQgghhBBCCCFEBZEgWwghhBBCCCGEqCASZAshhBBCCCGEEBXk/wOZwQ7Zij744AAAAABJRU5ErkJggg==\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure()\n",
"setBwStyles(fig.gca())\n",
"plt.title(\"Elapsed time vs number of cells\")\n",
"for i, simulator in enumerate(simulators):\n",
" plt.plot(domain_sizes, sim_elapsed_time[i,:], label=simulator.__name__)\n",
"plt.legend()\n",
" \n",
"fig = plt.figure()\n",
"setBwStyles(fig.gca())\n",
"plt.title(\"Dt vs number of cells\")\n",
"for i, simulator in enumerate(simulators):\n",
" plt.loglog(domain_sizes, sim_dt[i,:], label=simulator.__name__)\n",
"plt.legend()\n",
" \n",
"fig = plt.figure()\n",
"setBwStyles(fig.gca())\n",
"plt.title(\"Number of timesteps vs number of cells\")\n",
"for i, simulator in enumerate(simulators):\n",
" plt.plot(domain_sizes, sim_nt[i,:], label=simulator.__name__)\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" 8 | \n",
" 16 | \n",
" 32 | \n",
" 64 | \n",
" 128 | \n",
" 256 | \n",
" 512 | \n",
"
\n",
" \n",
" \n",
" \n",
" | LxF | \n",
" 2.003205 | \n",
" 1.108404 | \n",
" 1.773299 | \n",
" 1.130052 | \n",
" 1.394525 | \n",
" 1.455519 | \n",
" 1.585847 | \n",
"
\n",
" \n",
" | FORCE | \n",
" 1.867314 | \n",
" 0.870359 | \n",
" 1.428936 | \n",
" 1.068607 | \n",
" 1.262256 | \n",
" 1.322907 | \n",
" 1.568040 | \n",
"
\n",
" \n",
" | HLL | \n",
" 0.943084 | \n",
" 1.279804 | \n",
" 1.014578 | \n",
" 1.016539 | \n",
" 1.114954 | \n",
" 1.308043 | \n",
" 1.563977 | \n",
"
\n",
" \n",
" | HLL2 | \n",
" 2.009889 | \n",
" 2.450615 | \n",
" 1.795770 | \n",
" 1.097155 | \n",
" 0.857898 | \n",
" 2.472569 | \n",
" 1.115190 | \n",
"
\n",
" \n",
" | WAF | \n",
" 2.033824 | \n",
" 2.556362 | \n",
" 1.334464 | \n",
" 1.836761 | \n",
" 1.277028 | \n",
" 1.950514 | \n",
" 1.486304 | \n",
"
\n",
" \n",
" | KP07 | \n",
" 1.521576 | \n",
" 2.250884 | \n",
" 1.592267 | \n",
" 1.968830 | \n",
" 2.322592 | \n",
" 2.239914 | \n",
" 2.130361 | \n",
"
\n",
" \n",
" | KP07_dimsplit | \n",
" 1.876796 | \n",
" 2.291666 | \n",
" 1.748966 | \n",
" 1.171141 | \n",
" 1.041746 | \n",
" 2.382555 | \n",
" 1.137007 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Max | \n",
" Min | \n",
" Mean | \n",
" Stdev | \n",
"
\n",
" \n",
" \n",
" \n",
" | LxF | \n",
" 2.003205 | \n",
" 1.108404 | \n",
" 1.492979 | \n",
" 0.301957 | \n",
"
\n",
" \n",
" | FORCE | \n",
" 1.867314 | \n",
" 0.870359 | \n",
" 1.341203 | \n",
" 0.302020 | \n",
"
\n",
" \n",
" | HLL | \n",
" 1.563977 | \n",
" 0.943084 | \n",
" 1.177283 | \n",
" 0.202903 | \n",
"
\n",
" \n",
" | HLL2 | \n",
" 2.472569 | \n",
" 0.857898 | \n",
" 1.685584 | \n",
" 0.618592 | \n",
"
\n",
" \n",
" | WAF | \n",
" 2.556362 | \n",
" 1.277028 | \n",
" 1.782179 | \n",
" 0.420403 | \n",
"
\n",
" \n",
" | KP07 | \n",
" 2.322592 | \n",
" 1.521576 | \n",
" 2.003775 | \n",
" 0.301797 | \n",
"
\n",
" \n",
" | KP07_dimsplit | \n",
" 2.382555 | \n",
" 1.041746 | \n",
" 1.664268 | \n",
" 0.516944 | \n",
"
\n",
" \n",
"
\n",
"