{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction\n", "\n", "thumbnail\n", "\n", "This example gives a general overview on how to pre- and postprocess ASCOT5 simulations.\n", "\n", "1. First simulation: step-by-step\n", "2. Contents of the HDF5 file\n", "3. Python interface to libascot.so\n", "4. Input generation\n", "5. Post processing\n", "6. Live simulations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## First simulation: step-by-step\n", "\n", "Go to `ascot5/doc/tutorials` folder and type `ipython3` to begin this tutorial. Then repeat these steps:\n", "\n", "1. All pre- and post-processing is done via `Ascot` object.\n", "To create a new ASCOT5 data file, use `create=True`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:37.336692Z", "iopub.status.busy": "2025-04-01T09:03:37.336517Z", "iopub.status.idle": "2025-04-01T09:03:39.039204Z", "shell.execute_reply": "2025-04-01T09:03:39.038704Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "File created" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "import numpy as np\n", "from a5py import Ascot\n", "\n", "a5 = Ascot(\"ascot.h5\", create=True)\n", "print(\"File created\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "2. The following lines initialize test data. We will go through the input generation in detail later." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:39.041238Z", "iopub.status.busy": "2025-04-01T09:03:39.040761Z", "iopub.status.idle": "2025-04-01T09:03:39.207950Z", "shell.execute_reply": "2025-04-01T09:03:39.207407Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Inputs initialized" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# Use pre-existing template to create some input data\n", "a5.data.create_input(\"options tutorial\")\n", "a5.data.create_input(\"bfield analytical iter circular\")\n", "a5.data.create_input(\"wall rectangular\")\n", "a5.data.create_input(\"plasma flat\")\n", "\n", "# Create electric field and markers by giving input parameters explicitly\n", "from a5py.ascot5io.marker import Marker\n", "mrk = Marker.generate(\"gc\", n=100, species=\"alpha\")\n", "mrk[\"energy\"][:] = 3.5e6\n", "mrk[\"pitch\"][:] = 0.99 - 1.98 * np.random.rand(100,)\n", "mrk[\"r\"][:] = np.linspace(6.2, 8.2, 100)\n", "a5.data.create_input(\"gc\", **mrk)\n", "a5.data.create_input(\"E_TC\", exyz=np.array([0,0,0])) # Zero electric field\n", "\n", "# Create dummy input for the rest\n", "a5.data.create_input(\"N0_3D\")\n", "a5.data.create_input(\"Boozer\")\n", "a5.data.create_input(\"MHD_STAT\")\n", "a5.data.create_input(\"asigma_loc\")\n", "print(\"Inputs initialized\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "3. **EITHER** close the ipython session and edit options on terminal (opens a text editor):\n", "\n", " `a5editoptions ascot.h5`\n", "\n", " Scroll down to \"End conditions\" and set `ENDCOND_MAX_MILEAGE = 0.5e-2`. Save and close the editor. When prompted, set \"Fast\" as a description.\n", "\n", " **OR** set the options in ipython:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:39.209633Z", "iopub.status.busy": "2025-04-01T09:03:39.209454Z", "iopub.status.idle": "2025-04-01T09:03:39.288370Z", "shell.execute_reply": "2025-04-01T09:03:39.287913Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Options updated" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "name = a5.data.options.active.new(ENDCOND_MAX_MILEAGE=0.5e-2, desc=\"Fast\")\n", "a5.data.options[name].activate()\n", "print(\"Options updated\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "4. Now execute `ascot5_main` which should take less than 10 seconds.\n", " \n", " **EITHER** in terminal:\n", " \n", " `./../../build/ascot5_main --d=\"Hello world!\"`\n", "\n", " **OR** in ipython:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:39.289975Z", "iopub.status.busy": "2025-04-01T09:03:39.289801Z", "iopub.status.idle": "2025-04-01T09:03:42.069330Z", "shell.execute_reply": "2025-04-01T09:03:42.068757Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ASCOT5_MAIN\n", "Tag e37fd83\n", "Branch docs\n", "\n", "Initialized MPI, rank 0, size 1.\n", "\n", "Reading and initializing input.\n", "\n", "Input file is ascot.h5.\n", "\n", "Reading options input.\n", "Active QID is 4001368339\n", "Options read and initialized.\n", "\n", "Reading magnetic field input.\n", "Active QID is 3675640460\n", "\n", "Analytical tokamak magnetic field (B_GS)\n", "Psi at magnetic axis (6.618 m, -0.000 m)\n", "-5.410 (evaluated)\n", "-5.410 (given)\n", "Magnetic field on axis:\n", "B_R = 0.000 B_phi = 4.965 B_z = -0.000\n", "Number of toroidal field coils 0\n", "Magnetic field read and initialized.\n", "\n", "Reading electric field input.\n", "Active QID is 3854342190\n", "\n", "Trivial Cartesian electric field (E_TC)\n", "E_x = 0.000000e+00, E_y = 0.000000e+00, E_z = 0.000000e+00\n", "Electric field read and initialized.\n", "\n", "Reading plasma input.\n", "Active QID is 4088076269\n", "\n", "1D plasma profiles (P_1D)\n", "Min rho = 0.00e+00, Max rho = 1.00e+01, Number of rho grid points = 100, Number of ion species = 1\n", "Species Z/A charge [e]/mass [amu] Density [m^-3] at Min/Max rho Temperature [eV] at Min/Max rho\n", " 1 / 1 1 / 1.000 1.00e+21/1.00e+00 1.00e+04/1.00e+04 \n", "[electrons] -1 / 0.001 1.00e+21/1.00e+00 1.00e+04/1.00e+04 \n", "Toroidal rotation [rad/s] at Min/Max rho: 0.00e+00/0.00e+00\n", "Quasi-neutrality is (electron / ion charge density) 1.00\n", "Toroidal rotation [rad/s] at Min/Max rho: 0.00e+00/0.00e+00\n", "Plasma data read and initialized.\n", "\n", "Reading neutral input.\n", "Active QID is 1155656345\n", "\n", "3D neutral density and temperature (N0_3D)\n", "Grid: nR = 3 Rmin = 0.000 Rmax = 100.000\n", " nz = 3 zmin = -100.000 zmax = 100.000\n", " nphi = 3 phimin = 0.000 phimax = 6.283\n", " Number of neutral species = 1\n", "Species Z/A (Maxwellian)\n", " 1/ 1 (1) \n", "Neutral data read and initialized.\n", "\n", "Reading wall input.\n", "Active QID is 3486110016\n", "\n", "2D wall model (wall_2D)\n", "Number of wall elements = 20, R extend = [4.10, 8.40], z extend = [-3.90, 3.90]\n", "Wall data read and initialized.\n", "\n", "Reading boozer input.\n", "Active QID is 3784806280\n", "\n", "Boozer input\n", "psi grid: n = 6 min = 0.000 max = 1.000\n", "thetageo grid: n = 18\n", "thetabzr grid: n = 10\n", "Boozer data read and initialized.\n", "\n", "Reading MHD input.\n", "Active QID is 1391302864\n", "\n", "MHD (stationary) input\n", "Grid: nrho = 6 rhomin = 0.000 rhomax = 1.000\n", "\n", "Modes:\n", "(n,m) = ( 1, 3) Amplitude = 0.1 Frequency = 1 Phase = 0\n", "(n,m) = ( 2, 4) Amplitude = 2 Frequency = 1.5 Phase = 0.785\n", "MHD data read and initialized.\n", "\n", "Reading atomic reaction input.\n", "Active QID is 0550834107\n", "\n", "Found data for 1 atomic reactions:\n", "Reaction number / Total number of reactions = 1 / 1\n", " Reactant species Z_1 / A_1, Z_2 / A_2 = 0 / 0, 0 / 0\n", " Min/Max energy = 1.00e+03 / 1.00e+04\n", " Min/Max density = 1.00e+18 / 1.00e+20\n", " Min/Max temperature = 1.00e+03 / 1.00e+04\n", " Number of energy grid points = 3\n", " Number of density grid points = 4\n", " Number of temperature grid points = 5\n", "Atomic reaction data read and initialized.\n", "\n", "Reading marker input.\n", "Active QID is 3057719270\n", "\n", "Loaded 100 guiding centers.\n", "Marker data read and initialized.\n", "\n", "All input read and initialized.\n", "\n", "Initializing marker states.\n", "Estimated memory usage 0.0 MB.\n", "Marker states initialized.\n", "\n", "Preparing output.\n", "Note: Output file ascot.h5 is already present.\n", "\n", "The qid of this run is 2093344910\n", "\n", "Inistate written.\n", "Simulation begins; 4 threads.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Simulation complete.\n", "Simulation finished in 2.353104 s\n", "Endstate written.\n", "\n", "Combining and writing diagnostics.\n", "\n", "Writing diagnostics output.\n", "\n", "Writing 5D distribution.\n", "\n", "Writing 6D distribution.\n", "\n", "Writing rho 5D distribution.\n", "\n", "Writing rho 6D distribution.\n", "\n", "Writing COM distribution.\n", "Writing orbit diagnostics.\n", "\n", "Diagnostics output written.\n", "Diagnostics written.\n", "\n", "Summary of results:\n", " 98 markers had end condition Sim time limit\n", " 2 markers had end condition Wall collision\n", "\n", " No markers were aborted.\n", "\n", "Done.\n", "Simulation completed" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "import subprocess\n", "subprocess.run([\"./../../build/ascot5_main\", \"--d=\\\"Hello world!\\\"\"])\n", "print(\"Simulation completed\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "5. Open `ipython` again to read the data and plot marker endstates.\n", "\n", " Hint: You can add the line `from a5py import Ascot` to your ipython config file (`~/.ipython/profile_default/ipython_config.py`) so that it is automatically called in beginning of every ipython session:\n", "\n", "
\n",
    "        c = get_config()\n",
    "        c.InteractiveShellApp.exec_lines = [\n",
    "            '%load_ext autoreload',\n",
    "            '%autoreload 2',\n",
    "            'import numpy as np',\n",
    "            'import scipy',\n",
    "            'import matplotlib as mpl',\n",
    "            'import matplotlib.pyplot as plt',\n",
    "            'from a5py import Ascot',\n",
    "        ]\n",
    "   
" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.071133Z", "iopub.status.busy": "2025-04-01T09:03:42.070810Z", "iopub.status.idle": "2025-04-01T09:03:42.223024Z", "shell.execute_reply": "2025-04-01T09:03:42.222447Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Inputs:" ] }, { "name": "stdout", "output_type": "stream", "text": [ " [only active shown]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "options " ] }, { "name": "stdout", "output_type": "stream", "text": [ "opt 4001368339" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "Fast\n", "+ 1 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "bfield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "B_GS 3675640460" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "efield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "E_TC 3854342190" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "marker " ] }, { "name": "stdout", "output_type": "stream", "text": [ "gc 3057719270" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma_1D 4088076269" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "neutral " ] }, { "name": "stdout", "output_type": "stream", "text": [ "N0_3D 1155656345" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall " ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall_2D 3486110016" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "boozer " ] }, { "name": "stdout", "output_type": "stream", "text": [ "Boozer 3784806280" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "mhd " ] }, { "name": "stdout", "output_type": "stream", "text": [ "MHD_STAT 1391302864" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma_loc 0550834107" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Results:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "run 2093344910" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39." ] }, { "name": "stdout", "output_type": "stream", "text": [ " [active]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\"Hello world!\"\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Average mileage: 0.00490" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from a5py import Ascot\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "a5 = Ascot(\"ascot.h5\")\n", "a5.data.ls(show=True) # Print summary of the data within this file\n", "mil = a5.data.active.getstate(\"mileage\", state=\"end\") # How much time passed for each marker\n", "print(\"Average mileage: %0.5f\" % (np.mean(mil)))\n", "\n", "# Plots markers' final (R, z) coordinates and wall contour\n", "ax = plt.figure().add_subplot(1,1,1)\n", "a5.data.active.plotstate_scatter(\"end r\", \"end z\", axes=ax)\n", "plt.show(block=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "6. That's it! Now you have prepared inputs, ran ASCOT5, and accessed the simulation output.\n", "\n", " For actual simulations each step is more involving, but the basic premise was illustrated here. ASCOT5 development aims to integrate most input generation and post-processing tools so that they can be accessed via an `Ascot` object. Therefore, it is a good idea to always check from the documentation if there is an existing tool available.\n", "\n", " Next in this tutorial, we will go through each step in detail. However, don't forget to try ASCOT5 GUI for fast and easy access to the data (type `a5gui ascot.h5` in terminal to open it)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Contents of the HDF5 file\n", "\n", "ASCOT5 stores the data in a HDF5 file.\n", "The file contains **all** inputs necessary to (re)run the simulation and the simulation output.\n", "The format supports multiple inputs and multiple outputs so that all data relevant for a single study can be stored in a single file (but remember to make backups!).\n", "To separate inputs and simulations from one another, each input and each simulation is assigned a quasi-unique identifier (QID) which is string of ten numbers from 0-10.\n", "\n", "How exactly the data is stored in a file is not relevant, as the data is accessed via `Ascot` object.\n", "Or to be more precise, the contents of the file is accessed and modified via `Ascot.data` attribute which is an `Ascot5IO` object.\n", "\n", "The contents of the file can be quickly viewed with `ls()` method (GUI is also very good for this purpose)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.225248Z", "iopub.status.busy": "2025-04-01T09:03:42.224708Z", "iopub.status.idle": "2025-04-01T09:03:42.279970Z", "shell.execute_reply": "2025-04-01T09:03:42.279407Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Inputs:" ] }, { "name": "stdout", "output_type": "stream", "text": [ " [only active shown]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "options " ] }, { "name": "stdout", "output_type": "stream", "text": [ "opt 4001368339" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "Fast\n", "+ 1 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "bfield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "B_GS 3675640460" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "efield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "E_TC 3854342190" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "marker " ] }, { "name": "stdout", "output_type": "stream", "text": [ "gc 3057719270" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma_1D 4088076269" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "neutral " ] }, { "name": "stdout", "output_type": "stream", "text": [ "N0_3D 1155656345" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall " ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall_2D 3486110016" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "boozer " ] }, { "name": "stdout", "output_type": "stream", "text": [ "Boozer 3784806280" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "mhd " ] }, { "name": "stdout", "output_type": "stream", "text": [ "MHD_STAT 1391302864" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma_loc 0550834107" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n", "+ 0 other(s)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Results:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "run 2093344910" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39." ] }, { "name": "stdout", "output_type": "stream", "text": [ " [active]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\"Hello world!\"\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# In ipython terminal:\n", "from a5py import Ascot\n", "a5 = Ascot(\"ascot.h5\")\n", "info = a5.data.ls()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The `data` attribute provides a *treeview* of the contents.\n", "At the top level are *input parent groups*, e.g. `bfield`, and *result groups*.\n", "Each input parent group contains all inputs in that category, e.g. `bfield` contains every magnetic field input.\n", "The one that is going to be used in a simulation is marked with an *active* flag.\n", "Again, `ls()` method can be used to view the contents of input parent groups." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.281755Z", "iopub.status.busy": "2025-04-01T09:03:42.281579Z", "iopub.status.idle": "2025-04-01T09:03:42.291556Z", "shell.execute_reply": "2025-04-01T09:03:42.290983Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "opt 4001368339" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39" ] }, { "name": "stdout", "output_type": "stream", "text": [ " [active]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Fast\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "opt 0624051230" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "info = a5.data.options.ls()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As can be seen, each input has a QID (the quasi-unique identifier), date when it was created, user-given description, and name that has a format \\_\\.\n", "Note that when we used `a5editoptions` to modify options, the old options were preserved.\n", "\n", "Objects representing the inputs can be accessed via their name, qid, or tag which is the first word in the description.\n", "Both attribute-like and dictionary-like referencing is supported." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.293290Z", "iopub.status.busy": "2025-04-01T09:03:42.293120Z", "iopub.status.idle": "2025-04-01T09:03:42.297161Z", "shell.execute_reply": "2025-04-01T09:03:42.296603Z" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# These all point to same object (note that this cell fails if commented lines are uncommented without using proper QID)\n", "#a5.data.options.q1234567890 # Ref by QID, note \"q\" prefix\n", "a5.data.options.FAST # Ref by tag, note that it is always all caps, no special symbols allowed and max 10 characters\n", "#a5.data.options.Opt_1234567890 # Ref by name\n", "a5.data.options.active # Ref to options input that is currently active and will be used in the next simulation\n", "#a5.data[\"options\"][\"q1234567890\"] # Dictionary-like access" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each input object (as well as result group) has methods to access its meta data and alter the description (and, hence, tag).\n", "The inbut objects don't read the actual data when `Ascot` object is initialized to keep it light-weight.\n", "The `read` method reads the raw data from the HDF5 file but for post-processing purposes there are better tools which are introduced later." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.298702Z", "iopub.status.busy": "2025-04-01T09:03:42.298527Z", "iopub.status.idle": "2025-04-01T09:03:42.362096Z", "shell.execute_reply": "2025-04-01T09:03:42.361632Z" } }, "outputs": [ { "data": { "text/plain": [ "{'ADAPTIVE_MAX_DPHI': 2.0,\n", " 'ADAPTIVE_MAX_DRHO': 0.1,\n", " 'ADAPTIVE_TOL_CCOL': 0.1,\n", " 'ADAPTIVE_TOL_ORBIT': 1e-08,\n", " 'DISABLE_ENERGY_CCOLL': 0,\n", " 'DISABLE_FIRSTORDER_GCTRANS': 0,\n", " 'DISABLE_GCDIFF_CCOLL': 0,\n", " 'DISABLE_PITCH_CCOLL': 0,\n", " 'DIST_MAX_CHARGE': 2,\n", " 'DIST_MAX_EKIN': 1e-12,\n", " 'DIST_MAX_MU': 2.5e-13,\n", " 'DIST_MAX_PHI': 360.0,\n", " 'DIST_MAX_PPA': 1e-19,\n", " 'DIST_MAX_PPE': 1e-19,\n", " 'DIST_MAX_PPHI': 1e-19,\n", " 'DIST_MAX_PR': 1e-19,\n", " 'DIST_MAX_PTOR': 1e-18,\n", " 'DIST_MAX_PZ': 1e-19,\n", " 'DIST_MAX_R': 8.5,\n", " 'DIST_MAX_RHO': 1.0,\n", " 'DIST_MAX_THETA': 360.0,\n", " 'DIST_MAX_TIME': 0.03,\n", " 'DIST_MAX_Z': 2.45,\n", " 'DIST_MIN_CHARGE': -1,\n", " 'DIST_MIN_EKIN': 0.0,\n", " 'DIST_MIN_MU': 0.0,\n", " 'DIST_MIN_PHI': 0.0,\n", " 'DIST_MIN_PPA': -1e-19,\n", " 'DIST_MIN_PPE': 0.0,\n", " 'DIST_MIN_PPHI': -1e-19,\n", " 'DIST_MIN_PR': -1e-19,\n", " 'DIST_MIN_PTOR': -1e-18,\n", " 'DIST_MIN_PZ': -1e-19,\n", " 'DIST_MIN_R': 3.5,\n", " 'DIST_MIN_RHO': 0.0,\n", " 'DIST_MIN_THETA': 0.0,\n", " 'DIST_MIN_TIME': 0.0,\n", " 'DIST_MIN_Z': -2.45,\n", " 'DIST_NBIN_CHARGE': 1,\n", " 'DIST_NBIN_EKIN': 50,\n", " 'DIST_NBIN_MU': 100,\n", " 'DIST_NBIN_PHI': 20,\n", " 'DIST_NBIN_PPA': 36,\n", " 'DIST_NBIN_PPE': 18,\n", " 'DIST_NBIN_PPHI': 15,\n", " 'DIST_NBIN_PR': 14,\n", " 'DIST_NBIN_PTOR': 200,\n", " 'DIST_NBIN_PZ': 16,\n", " 'DIST_NBIN_R': 12,\n", " 'DIST_NBIN_RHO': 11,\n", " 'DIST_NBIN_THETA': 13,\n", " 'DIST_NBIN_TIME': 2,\n", " 'DIST_NBIN_Z': 24,\n", " 'ENABLE_ADAPTIVE': 1,\n", " 'ENABLE_ALDFORCE': 0,\n", " 'ENABLE_ATOMIC': 0,\n", " 'ENABLE_COULOMB_COLLISIONS': 1,\n", " 'ENABLE_DIST_5D': 1,\n", " 'ENABLE_DIST_6D': 1,\n", " 'ENABLE_DIST_COM': 1,\n", " 'ENABLE_DIST_RHO5D': 1,\n", " 'ENABLE_DIST_RHO6D': 1,\n", " 'ENABLE_ICRH': 0,\n", " 'ENABLE_MHD': 0,\n", " 'ENABLE_ORBITWRITE': 1,\n", " 'ENABLE_ORBIT_FOLLOWING': 1,\n", " 'ENABLE_TRANSCOEF': 0,\n", " 'ENDCOND_CPUTIMELIM': 1,\n", " 'ENDCOND_ENERGYLIM': 1,\n", " 'ENDCOND_IONIZED': 0,\n", " 'ENDCOND_LIM_SIMTIME': 0.5,\n", " 'ENDCOND_MAXORBS': 0,\n", " 'ENDCOND_MAX_CPUTIME': 10.0,\n", " 'ENDCOND_MAX_MILEAGE': 0.005,\n", " 'ENDCOND_MAX_POLOIDALORBS': 100,\n", " 'ENDCOND_MAX_RHO': 2.0,\n", " 'ENDCOND_MAX_TOROIDALORBS': 100,\n", " 'ENDCOND_MIN_ENERGY': 2000.0,\n", " 'ENDCOND_MIN_RHO': 0.0,\n", " 'ENDCOND_MIN_THERMAL': 2.0,\n", " 'ENDCOND_NEUTRALIZED': 0,\n", " 'ENDCOND_RHOLIM': 0,\n", " 'ENDCOND_SIMTIMELIM': 1,\n", " 'ENDCOND_WALLHIT': 1,\n", " 'FIXEDSTEP_GYRODEFINED': 20,\n", " 'FIXEDSTEP_USERDEFINED': 1e-08,\n", " 'FIXEDSTEP_USE_USERDEFINED': 0,\n", " 'ORBITWRITE_INTERVAL': 0.0,\n", " 'ORBITWRITE_MODE': 1,\n", " 'ORBITWRITE_NPOINT': 100,\n", " 'ORBITWRITE_POLOIDALANGLES': [np.float64(0.0)],\n", " 'ORBITWRITE_RADIALDISTANCES': [np.float64(1.0)],\n", " 'ORBITWRITE_TOROIDALANGLES': [np.float64(0.0)],\n", " 'RECORD_MODE': 0,\n", " 'REVERSE_TIME': 0,\n", " 'SIM_MODE': 2,\n", " 'TRANSCOEF_INTERVAL': 0.0,\n", " 'TRANSCOEF_NAVG': 5,\n", " 'TRANSCOEF_RECORDRHO': 0}" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a5.data.options.active.get_qid()\n", "a5.data.options.active.get_date()\n", "a5.data.options.active.get_name()\n", "\n", "a5.data.options.active.set_desc(\"New tag\")\n", "# The tag was updated\n", "a5.data.options.NEW.get_desc()\n", "a5.data.options.active.activate() # Set group as active\n", "#a5.data.options.active.destroy() # This would remove the data from the HDF5 file\n", "a5.data.options.active.read()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Most of what has been said is true for the result groups as well.\n", "Result groups also hold direct references to inputs.\n", "Again, `ls()` shows overview of the group's contents." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.363635Z", "iopub.status.busy": "2025-04-01T09:03:42.363466Z", "iopub.status.idle": "2025-04-01T09:03:42.398005Z", "shell.execute_reply": "2025-04-01T09:03:42.397454Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "run 2093344910" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39.\n", "\"Hello world!\"\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Contents:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Input:\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "options " ] }, { "name": "stdout", "output_type": "stream", "text": [ "opt 4001368339" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "New tag\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "bfield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "B_GS 3675640460" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "efield " ] }, { "name": "stdout", "output_type": "stream", "text": [ "E_TC 3854342190" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "marker " ] }, { "name": "stdout", "output_type": "stream", "text": [ "gc 3057719270" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "plasma_1D 4088076269" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "neutral " ] }, { "name": "stdout", "output_type": "stream", "text": [ "N0_3D 1155656345" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall " ] }, { "name": "stdout", "output_type": "stream", "text": [ "wall_2D 3486110016" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "boozer " ] }, { "name": "stdout", "output_type": "stream", "text": [ "Boozer 3784806280" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "mhd " ] }, { "name": "stdout", "output_type": "stream", "text": [ "MHD_STAT 1391302864" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma " ] }, { "name": "stdout", "output_type": "stream", "text": [ "asigma_loc 0550834107" ] }, { "name": "stdout", "output_type": "stream", "text": [ " 2025-04-01 09:03:39\n", "TAG\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "a5.data.HELLO.get_desc() # Recall we set run description ascot5_main --d=\"Hello world!\"\n", "a5.data.HELLO.bfield.get_desc() # Inputs used in a run can be referenced like this\n", "info = a5.data.HELLO.ls(show=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This concludes the tutorial on how the file is organized and accessed.\n", "For input generation and post-processing, the `Ascot` object, its `data` attribute, and the result groups are mostly relevant." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Python interface to libascot.so\n", "\n", "Many of the Python tools in `a5py` make use of the `libascot.so` shared library that provides direct access to same functions that `ascot5_main` uses to trace markers and interpolate inputs.\n", "The `Ascot` object automatically initializes the interface to `libascot` via `ascotpy` package provided that the library has been compiled.\n", "\n", "However, inputs must be initialized and freed manually. Here's an example on how to initialize magnetic field input." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.399846Z", "iopub.status.busy": "2025-04-01T09:03:42.399338Z", "iopub.status.idle": "2025-04-01T09:03:42.424466Z", "shell.execute_reply": "2025-04-01T09:03:42.424000Z" } }, "outputs": [ { "data": { "text/plain": [ "{'bfield': '3675640460'}" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from a5py import Ascot\n", "\n", "a5 = Ascot(\"ascot.h5\") # Use the same file as in the previous tutorials\n", "a5.input_init(bfield=True) # Initialize active bfield input\n", "\n", "# To initialize specific input, provide its QID as a string. Since a bfield is already initialized,\n", "# use switch=True to switch input or else exception is raised.\n", "#a5.input_init(bfield=\"1234567890\", switch=True)\n", "\n", "a5.input_initialized() # Shows what inputs are currently initialized" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Routines that require the Python interface will raise an exception if required input has not been initialized before the routine was called.\n", "Since magnetic field is now initialized, we can safely interpolate and plot it.\n", "Once you no longer need the specific data, you can deallocate it to free some memory.\n", "Note that marker and options input cannot be initialized (here).\n", "\n", "You can ignore the warnings below.\n", "They just inform you in what units the functions expect the arguments to be in.\n", "The units in ``a5py`` are implemented via ``unyt`` package; see the documentation for details." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.426149Z", "iopub.status.busy": "2025-04-01T09:03:42.425838Z", "iopub.status.idle": "2025-04-01T09:03:42.570198Z", "shell.execute_reply": "2025-04-01T09:03:42.569632Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_7794/2993582828.py:3: AscotUnitWarning: Argument(s) r, phi, z, t given without dimensions (assumed m, degree, m, s)\n", " psi, rho = a5.input_eval(6.2, 0, 0, 0, \"psi\", \"rho\")\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_7794/2993582828.py:4: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n", " print(\"psi = %.2f, rho = %.2f\" % (psi, rho))\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "psi = -5.15, rho = 0.22" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/home/runner/work/ascot5/ascot5/a5py/ascotpy/__init__.py:621: AscotUnitWarning: Argument(s) r, z given without dimensions (assumed m, m)\n", " out = np.squeeze(self.input_eval(r, phi, z, t, qnt, grid=True)[:,0,:,0])\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "psi, rho = a5.input_eval(6.2, 0, 0, 0, \"psi\", \"rho\")\n", "print(\"psi = %.2f, rho = %.2f\" % (psi, rho))\n", "\n", "ax = plt.figure().add_subplot(1,1,1)\n", "a5.input_plotrz(np.linspace(4,8,50), np.linspace(-4, 4, 100), \"psi\", axes=ax)\n", "plt.show(block=False)\n", "\n", "a5.input_free(bfield=True) # Deallocates just the magnetic field input\n", "a5.input_free() # Deallocates all inputs (except markers and options)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Input generation\n", "\n", "ASCOT5 is modular when it comes to inputs.\n", "Several different implementations of magnetic field, electric field, etc. exist.\n", "When planning a study, check from the documentation (see `a5py.ascot5io`) what kind of inputs would serve you and what kind of data those need.\n", "The required data is listed in the `write_hdf5` function corresponding to that input.\n", "\n", "Once that is decided, there are two ways to proceed.\n", "Templates for different kind of inputs can be found in `a5py.templates`.\n", "Some of the templates import data from external sources, e.g. EQDSK, to ASCOT5 and using those is strongly recommended.\n", "\n", "If no suitable template exists, one must generate the arguments for the `write_hdf5` function themselves.\n", "\n", "Running `ascot5_main` requires that all input parents (`bfield`, `efield`, `plasma`, `wall`, `neutral`, `boozer`, `mhd`, `marker`, `options`) have at least one input present.\n", "Some of these are actually rarely used in a simulation and for those it is sufficient to provide dummy data.\n", "\n", "No matter how or what input is created, all is done via `create_input` method." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.572312Z", "iopub.status.busy": "2025-04-01T09:03:42.571936Z", "iopub.status.idle": "2025-04-01T09:03:42.693004Z", "shell.execute_reply": "2025-04-01T09:03:42.692394Z" } }, "outputs": [ { "data": { "text/plain": [ "'B_GS_2534690499'" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from a5py import Ascot\n", "a5 = Ascot(\"ascot.h5\")\n", "\n", "# Call explicitly E_TC.write_hdf5 function that requires exyz as a parameter\n", "a5.data.create_input(\"E_TC\", exyz=np.array([0,0,0]), activate=True, desc=\"Zero electric field\")\n", "\n", "# Use template\n", "a5.data.create_input(\"bfield analytical iter circular\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Post-processing\n", "\n", "Simulations are post-processed by using the corresponding run group in `data`.\n", "Run groups provide access to the data, supports evaluation of quantities derived from the data, and host many routines to export or plot the data." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.694964Z", "iopub.status.busy": "2025-04-01T09:03:42.694528Z", "iopub.status.idle": "2025-04-01T09:03:42.901239Z", "shell.execute_reply": "2025-04-01T09:03:42.900750Z" } }, "outputs": [ { "data": { "image/png": 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fl/5umlKxjKvVkTQPWZGJ6SnSqQyZfBIjqhJIPo1WhXbLwghSWE2PwA+QJPDcgPJik+J8E8/x187JU9o4Wg1PbeNLLoHsYbb66O8b4Md/6b7X9D5sxrVcv0XLjSAIgnDbeOWVV5idneXee+8ll8ut+14QBARBgCzLlEolvv71rzM3N4emaZcEGkONYugmiVgSRZXwcbFsi1yyl1y0HzoRcFWMFBhJCTOpokXBlxxqtRqlUolIJIJhGOTzeSzLYnl5me7ubmKxGK1WC8Mw2Lp1K5qmcccdd7CyssLi4iIvvfQSTz755Nq5SJJEEARomGhWmpa+BPhE2n0YXgovVqWtFPECG8lXUbwIrtYAD+hc9KKWgdMSIAF+eANIvoJmp1GdOK7WxNEryL6OGo1heGm0lEeLIm2vesn7PdA9xMBI+gb85G4s0XIjCIIgAGE3xPJUjZWpOolshGx/jHjGgNU6EEnilq8J+f3f/31mZ2cBSCdz+G6AKukEPtStIp7vEjUTtK0mvu9deGAgEWn3oFs5NDuFHFzfZ3/dVEl3m5hJHVmWiCZ1knmTRC5CIhvBiKqUFposT9UpzTfJ9sXY/Ugfnutz8pkFivNNCtYkLVZoe3Wandrq+bEWRjYrm+rC0Exc16XeKtOx2+u+r0gakiTh+vamjidJEoODg3R1dRGPx9F1nR07dtDd/cZ0SV3L9VuEG0EQhLe4RrnD9/5ynOlXSnQaV+5mUVQZI6YSiWnEUjrxbIR4JkIkpuF7Pr4X4Hs+juXTLtWpHzqOZfm4jo9it9BNFT2TRM1mUHNZlFiMIIDAD/A8H88JjxEEEE3qJLIRIMC1fZqlFs3ZZTzbRcukiGST+H5As2LRqtl0Gg6yCkGiyoo9SVsqXDUMaFaaaHMYCNClGNv2DpBWG7TPnsMulHFsn7an0fEMLD0FBEQ6JSJWiXhMIjLQgzu0i4ZjUFtpUy93whByA/mSQyD5yL5KfHsTJd/krrvvwjQjPPHEt7Esh/7uQfLJAeJaBiPvYgdNRkdHSaVS647lOA6NRgNJktA0jWg0ShAEzM3NMTMzw+LiIslkkp07d2JZFjMzM0xPT5NOpxkdHWVsbIxYLHZjX+A1EOFmAyLcCIIgrGe1XT79H76L7wfopkrv1iTNik15qYnvvjkvEZ7cwci5ZPtiSIaLpAZkEt14bYlysYwky2RieeROk5S1QG7qaewXnsUrFC57PCkaRdZ1/GaT4FV1NtGHHiSyYyeuH9BoytRaKnagonT3Yie6qNd8mnWPpqVgORJJwyat1klobZbtDEv1GEgwkG7Rl2ohAQ1Lo9bRaNsKtqswmGmyf7CMfC2tN0FA4HpImooUiWCfm8CenQHXw9i1EyWRAElGSSWRYzEkRcFvt/EqFSRNQ+3uRhsYxNixHdkwrv+HcYOIcLMBEW4EQRAudezJObJ9UXq2plCUcAo03/OxO6tdNwHYlovVdOk0HJpVi3qpQ6PUwWq7yIqMokjIioRmqOimgnvoBSLpGHo2iadEaM2v0FlYwl1axllehgAkAtTeHigXoVFDCnwgwDLSWEYaKfCRfRfNqRNJ6GgxE2tuAVcygICIVUa3a2hOA1/WsPQUmuyR35YnsX0ESZZAkpGjJnI8QeC5ONMz2FNTdI4fx2801r0PcixG/LHHiD70IGo2i5xIoA8Nofb2rnXJuSsrtA4epPb3f0/96/8AnsdrYWsxpMBHc9tX3/lmUBSURALJNFFSKYyxMbTeHuRkCiWVIv74Y2g9Pa/7aYhwswERbgRBEG4+6+xZln/7t2l845sX7lQUInv3Erv/PiL77yCwLdxiEUnTiD/yCProKAB+u03rpZewTp3Gnp7CmZ7BazQI2m3clRW8SmXT5yFFo5h33EH0vnuJPfAAkTvuQNb1TT/emZuj+tWv4jebgIQUMZCjMQLbxjp1Emv8HLJpoqTTYUuKY6Nksqj5HMgKfqNOYL+2EVcbUhUCx8FvNNFHR9FHRwCwTp4icGwCz8erVQlarbCVx4ygptP4to27tIw9MYFXLm/4FMN/9EfEHrj/9XsNq0S42YAIN4IgCLeO9rFXsCcm0Ldswdi6BTkafU3HC4IAe3yc1gsv4CwsslrUg99q4dUbIIE+OIQ+MoyxYwfG9u1I1zkJ31tBEAS4y8v4tRp+x8JdWcEaP4tXKOBVa3i1Gj3/6X9HHxl53c9FhJsNiHAjCIIgCG8+Yp4bQRAE4Zbj+x7tWo1WrUqnXiM3OEw0lb7ZpyXchkS4EQRBeAsLggDXsbGaTaxmE8fqEE2liWezyLKytp/veTTKJUrzsyycOcni+BkURSXV00uqu5dUVzeKpgFSWMQbBFRXlinNzVCcm6E0N0N1eYnAvzDjrayo7HjwEe587wfo37Fr3Rw6QRDQaTZoloq0alVyg8PE0pk38q0R3sREuBEEQXgL8H2PpXNnKcxMUZqbpTQ/S3l+llphBe8ySwhIskwilyeaStOslGmUiuuCyXWTJMx4Ai1iUltZ4uTT3+Hk098h3dOHrKo4VgfXsrA77XXnJckyW+68h72PfR9b73kAVdNe+7kIty1RcyMIgnAL8FyH0twsvu9jJhKYiSSaEXlNx3SsDpNHXmb8hec499LztOu1K+4rSTJGNIpqGLSqFfzLDG+WFYVkVze923bQt30nIFFdXqS6vEitsILvukDY6kIQEM9myQ4MkRsYJjswRKa/n1gqg6yELUJL587y8t//NaeefhLXufwsuZF4AiMWo7q0uHafbkaJplIoqoasKKiaTiQeJ5JIEonHiSZSxLM54tkciVyeRL4LPWK+hndSuBWIguINiHAjCJt34unvkB8aIT80cstPu/9qge8zfewIZ174HmYiSc/WMXq2bCOezb0hr8V1HBbPnKJRLuJ7Hp7nEng+vucRBD6BH35dXphnaeIshelJvNVwcJ6iachK2MAuSSCrGl1DI/Rs206mrx8C8H2fwPfwPQ+73cZqt7DbLZqVMtPHDuNa1trxjFiM3m07yPYPhtvAIKnuXiLxBHokgiSvzm/jezTLZWqFFVq1CrFUhmS+i2g6va6r6kZp12ssnTuLomlouoFqGGhGhFg6g7o6LLs0P8sr3/kmx5/8Fo1S8ZqfI9PXT/eWMXq3jtG9ZQyr3aQwNcnK9ATteo3djzzOnse+76otQoHvUyusUJ4PW786zSZmMkk0mcJMhAtbdpoNOo162K1WKVMvFmiUCtSLBXzfJzcwFG5Dw+QGhskPj2JcNEosCAJKc7MUZ6fIDY2Q7R980/3/ez2IcLMBEW4EYXPsTpv/7z/9KTzHId3Tx9j9D7H9/ofoG9u5dhG8mVzHoTQ3Q2VxniAAWZaRFAVZlinOTnPkm39HZXHhksdFU2l6t22nf+ceBnbupnfbDhRVpby4wNLEWTqN+rr9jWiMWDpDPJMllsliRGOXvdA4tsXK5ASzJ44xfewwcyeP49rWJfttxIjGUHWddr2O77lXf8AmJPJdbL/vIbbd+yADu/agvMmHPfu+x8rUJI7VwXc9fNfBcewwTNTrdBp1mtUKjVIx3MpFrGZzU8eOZ7LsfOQxFEUJQ2MQ4FoWrWqFZrVCq1qmUSpd88/1qiSJTN8AvVvHkBWVqaMvrwtwkXiC/h276B3bgaJqeI6D5zoEQUAimyfZ3U2qq5dUd89aGLwdiXCzARFuBGFzaivLfOsP/xeTh19aV/ugqCqyoiLJ8lqgiMRimMl0+Ok1mcSIxtBNEyMaZ2T/neQGh9YeX1lcYOLwQWRZRtUNVF1H0XQ8x8Zqha0OVrNBvVikvvpp12m3iGXCLgZZlinMTFFenL9qDYhuRtn18NvxXIeliXGKs9OXPEZRVRRNx263NvW+GLEYmd5+Mn0DpHp6aZSKLI2foXCZY0dTaXIDQ8iqiqKqSLKCrMhIkrz2/sVzeXq2jNGzdYxUd8/aCtBOp02n0cD3/XCuFsBqt1ieHGfp3Dj1wvLqMZTwVlHQTRPdjGKYUfRojP4du+jZOvaW/9TfqlVZnhhn6dxZls6dZXnqHLoZpWt4lK6RLQS+z0tf+6tNtwjJikqmr59s/yCRRIJOvU6rVqVdqxIEQdhFFotjxOJEU+mwa2x1AyjOzVCcmaY4N0NhZopG8dIlH1RNJzswRGlu5opddq+mqCoDu/ay5c572HLXvZjJFIXpSQoz05jxOAO79pLsemMWuXw9iHCzARFuBOHa2J02k4cOcub573HupRc2HQIuNrh7HzsfepSJwwc599ILaxfr18qIxcj2D6KoWvhJ2/PwfR/dNNn1yGPseuTt62otHKvDytQkC2dOMXfqFeZOHqdVrQDhxaRrdAuJbH5tFWzOj9iplDfVAhBNpenbvpPhvXcwvP9OcoPDb/lg8WbhOg4nn3qC5alzyLIMkowkSai6TjSVJpZKE02miWWzpLp61uqGboRWrcrSubMsjp/GtW2G9t7BwK49aLqB5zosT55j/tQJVqYmAAlFU8ORaQHUCivUlheprixht6++fEMi18XArj2M7L+TsfseIhKPX3Y/3/coz89RWphDUVV0w0SLRFB1A7vTotNY7Xpr1Inn8my/76Eb9n5ciQg3GxDhRhCun+c6NCvltXoRf/XWajRo1au0qlXa9WpY+9FqUi+sMHXkEEGwvkVjaM9+jFgM17ZXNwtVN9CjYauDEYsRX22piWfz6KZJo1SkXlzB97ywXmF4hHjmtdXPBEFAdWkRx+qQHRi6apeNY3WoLi1SXpinvDhPZWmBWCpNz9bt9Gwbe83n80ax5xo0X1zEK3VIvnsEfTBBEAQEtoffdPHqNl65g7PYxJ5r4DfDljslaYT7D1z+gng9vKZD6+ASrcMr+A2HwPXDzfPRemNEdmSI7MyiDyXCIeaEP7fA8nDmm1jTNbxyJ9xvVxZJufldpjdDEASUF+aZPPQi515+kdkTx/Ach1RPL/mhEZrlEguTZynFOsznO8x2tSmmbLqDNHdnDrBLGaWvmcAt16kszLMyPbnp7ret99zPD/3v/6/X+RWKcLMhEW4E4Y1VLxY4+q2vM3n4IN1bxrjrfR8gNzB09QcKmxIEAV7VAjcAWULSZOSYthYELuZbLuUvn6V9aOXCnTIYW9M48w381ibqfGSIPzpI7J4e1FyEwPHpnCnjFjthg5ckIZsq+mgSNW+uC3tuuYM1UcWrWvh1B7di0TldCs/9KqSIiqTJBJZH4HhwmYfIcY3IjgxKUkeO6chRFUmVsKfrWFM1JFVGzZlE78hjbM9c8h4FQUDg+Mj6xq0ygR/gLDTxGjZKVEPtMpEjN7eW6VjhGF8d/ypLrSVW2itUOhXSeoqeeC9JPcl4ZZwTpRNY3pUDi+RDrqrTW4rQXTZwTRmnx6Sst6goLQLfR/EkNFQMWcdQdAwlwvbMdn7px3/jdX+NItxsQIQbQRBuB85ik9o3prAmamstK+fJMRVjaxq1O4psqnhVC69iYU/XwyAkg7m/C/yA9tFX1XuoEkpCR0kbaF1RtIE4StoAoPXi0vr9z4cD//KXEclQULMRlLSBs9zCK3Yuu5/WHyP2QB/6QBxJlZFUmQCwJ6t0TpXpnCkTdC4zND2hY4wmkeMa7aMF/MbmF6BUshEyP7KdyLY0AF7Npvj5k9iTVSK7ssQe6COyY30A8uo29e/O0jq4vP49l0Hrj4etRhKYu3NEdmeRTZXA8fFqFpKmoKQNlNiNmZ/Hq9vYM3WWlxf51PIf8Dftf9jU4xJaggPdB3h04FG20sczL3+dl8qHmTJLVJTNFV6/2sP9D/O/3v2/ruux10KEmw2IcCMIwu3AWW6x9FsHw38oEpIqgx8QuP5lWzXOU9IG2X+0C2Mk/PvXOV3GWW6hDyfQemNXbbVoHy9Sf2IGZ7FJYIfdjWqXiT6UCHcIwK10sGfql7bIyKAPJlC7oigJDTmuY4wk0QbjG3bnBV6AsxheeGVDQTq/afLa4wLPp3OqjLPUxK87eA0bv+MRWB5abxRjawqQsKdqtA4tr7VSxe7rRUnpNJ5duCQcKRmDyK4sfs3GWWziXhTOJF1BzUXwmg5+bXMFvwBab5Tovb2o2UjYDWh5BLaPktCI7MoiR1Q83+NM5Qx1u05Gz5C240xPn+N7c8/wXO0gBadAxNUxfYPxyCxNJay1eax6L3vb28i6SRJejJrSpKhWqEVajKa3cOe2exg7sA8tcfn5k+Yb87y49CIvLr7I8eJx0kaa4fgwQ7FBhjMjyJKM5Vl0vA6WG9523A7dRjc/tOuHNv0eXC8RbjYgwo0gCLc6y7N4fuF5smaWHekdaMqln/aDIKDx3Tn04QT6YCIMN0Dg+tizdazJsBbFb7soSQMlbaBmDIyxNLLx2rtQAj/Aq1kQgJq59GIZuD5usY1b7OCVOyiZCMbW1Fr3je/7VKtVGo0GhmEQjUYxTRPlVYW6jhMOedZXhzhXq1WOHz/O8ePHcV2XO+64gwMHDhC9htXE/Y5L9W8naD6/uO5+rTdK6ge20jlVpnpwjopToS1bWJKNJdu4kkemq4uBh3bSs3uEZtBiujbNucWzlJdXeFvqYfrdLk4cfZmnGs9h+xa7rK3sMLbhODbNdoOW3OGEOcGR2GkWtQIFrYIrefTbXQw43Vgxj1fk0zS5enHweTuUrfy7zL/kQHLfWsuX13SwzlWxJ2sE9kWtXhLoo0nMXVmUlIFsqkiagle1cIptGrNlvEIHqeoiORfigSf7tDWXlmLTxqYZdCgFdQp+larc4pf+6y+/7vVmItxsQIQbQRBuVa7v8pWzX+FThz/FUmsJAF3W2Zndye7sblJGClVW0WQNTdYwVZNMJEMmkiEbyZKJZEjpKZTLTLTnui7qGzTHjed5zM/PUy6XSafT5HI5AM6cOcPp06dZWlqiXC6Hw9xfJRaLkUgkUFWVSqVCo9EAIJlMYpomS0tLlz6f6uH1eiypSzTkBq7s4qs+gRbgSA5+4DMQH2AwMchwcpihxBDDiWH86RZnTx5nNlhgTl9iPlqkYBUotovU7CvP5ryR7mg3y63l63rsxUwvQs5NUVHrNJQW0SDC3cp+Hsjcx/b+XbgZibbUIapGeaT/kcv+zGG11Wu+QedUifbxIs789XU9bWRaXuHeX/nAWgB9vYhwswERbgRBuFE8z6PVatFoNKjVatRqNer1OpqmkclkyGQyKIpCtVpd+767OgvxsruMruh0pbrozfVywj7BZ05/hqn6FAC5SA7Hd675IishkTbSjKZG2ZncSaqRwpqyqM3XyGVzjI2NMTY2Rk9PD6V6iZOFk3Qr3Qx2DxKNNgiCFonEvnWfwovFIpOTk9i2jbI6UWI0GmVwcHDt72ipVGJ8fJzx8XEmJiZo2A3KRpmyUaau1UnZKYYbwxi+sXZcRVGIx+PYtk17E8OYz+sb6UMdUTnePM7LhZdZkVbgdWg0kCWZmBojokYwFANFUqg7dapWFS8IW0O6jC76zD4I4Gj1KAEBmqRxV/4usmaWV8qvMFOfQZVUolqUmBZjJDnC2wbexlh6jJ5oD4qshC1Ac6eh6nFHZA/bIlsx4hHU7ihBSqVSqzA7PUu5XKZSqWDb9trvWDabJZfLkU6nw2HsG2gsVDjz94dpjZdQPRkj0NBQaEoWdalNQ7FwE9A2XDwD9GiEZDJJVk+RDCIYrormyKiWhFR2CIo20Xu6yfzAthv/A3gVEW42IMKNIAjX43xrxLlz55iYmGB5eZlW69rn/Dnvb4b+ho56aYGt4Rvc79/PPeo9uJZLwS6wrCwjdUtku7PImozt2bStCpXWEqVOiZprUXc7NL0rBwTVV0nZKZJ2Et3XKUQKlIwSgRSgeRrb6tsYq42SjViYpkosNkQk0su5lXPMt+aJO3FMz8SRHGbiM0zFwxC21d/CiD1IrdGirtWp6BWWzCXKRvmSwCEHMnvMPWQSGWRVRtd0MpEM6UiahJZACzQkR6LeqlOxKliKRUtq0bAbNK0mHaeDp4T1KG6wfmRXr9HLrvguerVeNF+jXW1TXi7jNsP9mlqThtrAMi38pE85KGO7NqZlErNjxJ04CTdBTs/Rn+5npGuEvkwfxUKRmZmZdS1GkixhSzayL6MEF1pMmmr4HFkrixaEXYmxWIzBoUFGR0bp6enBNE1M0yQSiaDr+hXDiO/7NBoNTp06xeHDh5mdnd3gt2n1Z6yq5PN5urq66Onpoa+vj1gshuM4OI7D5OQkzz33HNbqkhyKIiPLoCgB+a4Ovb1ltm0dIpu7m1TqLiJG71WfE8LWIUl5/adAEOFmAyLcCILwau12m0KhQKFQoFgs0m636XQ6tNtt2u02rVaLZrO51upyMUmSiEajJJNJkskkiUQC27Ypl8trXS+pVGrt++eb7v+Ppf+DmlfDISxi1XyN7dXtjFXH1i6Mlz4XmKaNZUl43qX7+PjYik1H6VDVqxSNApXoMlW1xZXmctZ8BUcOWyFkXybuxtF8DTmQqek1LOXC0OGYFMMJbGw2Nyopo/gM6z7dqsJpJ8lUp371B21Sf6yfB/sf5P7e+7m35156Yj2X7BMEAeVymdnZWWZmZjhx4sRaN9fFEokErVYL7zKLhW5EkiTi8TiGYaCqKqqqIssy7XabZrO5qfCr6zq6rqMoyiWPv/jyLEkSIyMj5PN5MpkMmqZRLpcplUpr22bPP51WGBp6mVT6CJJ05Qig692Y5iARo59IZAAj0oumptG0i7cMqprY1PO+ViLcbECEG0G4/fm+j23bBEGAoihrm+u62LaNZVkUCgXOnTvH+Pg4y8ubq5EwTZPR0VG2bt3K4OAgiUSCaDR61a6AiwVBgGUt0GicotE8Tb1+kkL9JHZrAt9RsKwothXF81UUxUFVHBzXYGF+J5VK37pjSVKAqgaoqo8sW8hyh2jUI502yebSDA1mSKXyoCSYb9eZbC5xtjLBQvUUPcEC240Og4lRTjppvlaocLI2d8n5ykBKCah4EKw2xXSpPo/EXWRf4eWmzqTnoUsS/ZEIA5Eou+JJ9sZM0io4TpFWawKAWVtiysuTSOwiGd+OYQxSc5ph65Ndo+22aTttFFkJa4mMsJYoZaTQFR1N1jAUg52ZnQzEB+h0ZnCcIq7bwPUaeG5j7WtFiZJM3EEisRdVjQFh3dGJEyd4/vnnmZmZIZVK8Z73vIc9e/bgunUqlVlqNY9yucPKSoFyuUwul2NoaIihoSFM01xrBZEkiVgstuHP3nEc5ufnmZ6eZnp6mkqlshaYNxtEent7OXDgAPv27SORuDREuG6TZvMM9fopSuUSlYpDpeJSKjoUizaO46OqoCig6xb5rufI5SaRJFDVJInEXqLmKBFzCFnSqdWP0GicpNk8C1eMxBckkwe4954/BxAFxTeTCDeCcHs6ffo0X/nKV7As67ItLFeTSCTI5/PkcjkSiQSRSGRtFM/5LZmM4vvnCzKl1T/m0tq/wadjLdFpz9LpzGHZKzhOCccp49hlbKeMZS3ieZe2HgAoSpx4fAex6Bie38HqLNCxFrDtAtHoFmTpThRlO/mufeRzOzHNyy/iuRlB4BMEPrKsrv47YLwyzkp7hYbToOXUSXmLGPUnadcP0/Fs5h0ZWVLZkx4lnthJNvM2crnHQE2iyRqydOmFPggC6vVjzC/8GYuLf7XutcuyQTp9P7nso+Tz7yQa3bLB+Qa025OUy89SrjxHufwstr1yxf0vkInFxkgmD5BM3kEqeQBNy7KychTbPkWzdZJG/TjtzvS6R6lqaq1lQlOTKGocRYmhKFFUJYaimMiysX5TDGRJBwI838K/aAt8B1VLYRi9GEYPqpLHdbW1sO15Hq7r4vs+pmkSj8cxTR3HWaLdnqHTWcCyl7CtFRyniuNWabXO0enMbOrnfTHTHMYwenGcCra9gus2CYKLh7PLZDIPksk8SCQyiG2v0G7P0mpNYFkLOE4Fz2vh+xaybAAB9937ZeLxHdd8LtdChJsNiHAjCLen06dP87nPfW5T+6qqSjweZ8uWLWzbto0tW7YQi8Uu2e/8BbVYfJJi6buUy8/i+5svfL0SSVKJRrcQi+0gHt9JPLaTeHwXkcjALbt8g+/beF4LRYkhy9c3EZ3ntVkpfINS8buUSk9h2etHPkWjW8jn3kk293Z8r02rPUmrNUm7NUmzNX5JmJFlHUPvRVHjqGocVYmHXysxbKdErXYYy1o/3HsjihK/YvB8PShKFE3LoSgmihxBVkwUJYLv27RaU1jWAhtOWrRKkhRAeVVAuT6ybK77HVfVBLHoGI3mKTzvyt1sdx74DLnc21/z829EhJsNiHAjCLenTqdDpVLBMIy1OgZZlnFdF8/z8DwPVVXX6huuxHEqlMvPUSp9l2Lpu3Q6Vy/kvJimZYlE+olE+jGMXnQti6Zl0fQMmpZB13JEoyOrn3jfuoIgoNk6S6n4XYrFJyhXnicINq7lkSSdVOpOMukHyGQeJJm8C0XZ+H20rCVqtSMXtvphXLdJLLaNRHwP8cQeEvE9JBK70bQMvu/iuhUc5/xWwnFreG4Tz2vhek08r4HvhS0yr26h8X0LSVKQJf1Ca45sIEkqzmrLnWUt4ro3rv7oPFmOkM0+Qjp9H57XxrZXsKxlbLuA45TxvCa+75KI7yKZupNU8k5McyQMhmoCRYkiSQqt1hSLi19mYfEv6HTmLjq+SSKxh3h8d/g7bvRiGH1EIr0YRi+yLIaC3zQi3AiCcLGw1uKFsLuj/Cz1xnEu/rQsSRrp9L3kso+Szb6deHznRY8OLir6DG+vt1Xj9RAEPrZTwurM0+7M0WlP027PhFtnGstaJhbbRip1L+n0faRT92AY3TflXF23TrH0FMXCtyhXnkfTUpjmKNHoKNHV23h8N4piXv1gq4IgwLYLWNZC2PLkd/C9Np7XIgi8Cxs+BP7arRkdJZN+6KrB6bXwvBadziKV6ouUy89QqbxwSStTLLadrvx7yHd9H1FzGFk217qBXLeB61Zx3RqOUwVJIpW8C0W5/OzD1yMIfCqV57GsJeLx3cRi21ZbiW4OEW42IMKNINzePM/CsuZpt2fpdMLal05nHtdrEvg2vm/jB05463dotc4RBOuLO6PRMbLZh8hl3046/cBaQerrLQgCPK8V1ug4JWynhO9ZSLKKJClIkoosqSAp+F4b12vguvW1zXMb2E4Rq7NIx1rAspau2hryaqY5TCp5N7rRhaYmUde2BLrRRTy243X/hH49bLtIs3mGRvMMzeYZmo3TNJpncN3KdR1Plk2y2UfI599JPveOK4Y+37exnRKOXcK2i6stJC08PwxRF7bw3+HPrYnvtbGspXVdc5Kkkck8SFf+3eTz7yAS6b+uc79dXcv1++YuYyoIgnAdPK8TXsCap2k2x2l3Zul05ul0ZjdZZLqeaQ6TST9IJvMQmcyDb1jrRRD4lMrPMD//BarVl3CcMr5/5VWbr4+ErndhmoOYkWEi5iCmOYQZGUbXczQaJ6hUXqRSfZFG4yTt9jTt9vQVjybLOvH4XlLJAySS+4kYvWhaFl3PoqrptQLlq3GcGrXaIaq1QzhOBdMcImqOYJrDRCJDa60mYevLMs3mWZqtc7Sa43SseRwnbLU4v125HkTCMHpeVQAcQZZ1JGk1NCKBpCBJMgQB1drLWNYihcI3KBS+AUAisY94fFfYVWUXsZ0itl16zTU6ihIll32Mrq73kM+/4w0bVn27Ey03giDc0ixrmVrtEPX6cRrN0zQap1YvvlcepqooUSKRASKRQSKRAcxIP6qaRJK1C7UQsoYk68SiW9/wT8iWtcT8wpeYn//iZUe7yLIRBgYti6xEVrtPHILAw/ddgsBFUSKoSiKslVitmVDVBJqWIWL0YUR6iRh96HrXprvKHKdGtfYS9foruE4V56Lw4Lo12u1ZXLe6wREkVDWFrmdX64vCW23137JsUK+/Qq12iGbzzIbHOV+v1GpPbTpAmJFhYvHtxGLhFo9tJxrdds1dNUEQ0GicoFD4FoXit6jVDm+4vySp615vOLLKRJFNFCV60Rb+W1bMcMSVmiCZ2H9Du5JuZ6JbagMi3AjCrcv3HWq1w1Rrh6jVDlOrHqJjzV92X03LhKONYjswzaHVMDOAaQ6iqmksa4FK5UX8wF43imbtVomu1jDoVxyhFAQBrlsLu3hWh2V3OvNrX7tuDVnSVruNtLXWAPl8iFIiyLIRjoSRdWQ5Qq1+lGLx22tdYaqaoLfnw/T0fCC8oOtZZNm8JUdNhaPHplZ/RodpNE5g2wVsu3Rd3T8Xd4GFtUBhq9GlYUbGNIeJxcaIRbdimsOoWnpdt5lhdKEom18881pYdoFi4QkseykMMHoWXcuttljlwuB8C/68bjci3GxAhBtBuLX4vkWp9AzLy19jpfCNy7QMyMRj20kk9xOP7yIe20EsvhNNzQDuWlGo6zWpVl+iXHqGUvl7tNuTmzwDebXLIrL6yTr8xO16LSxrAc+78QsNAqRS9zLQ/xN0d7//mopkb1XnRxnZdmm1Xqi8Or/P6jw/ThnXaxKLbSeVuotU8gC6nr/kOEEQ4Dgl2u1pbKeEGRkSo8sEQNTcCIJwDWbnPkdh5R/WFdoGgUPU3EK+613kc+9A01JA2LJSLj9DtfoypjlCMnkH0eiWsFbhKmy7uDor7ymajTNYdjjZXas9ta7oVZKMsFtDTaGoMWTZIAg8Go1TVCrPrxbP1i4pAr6UTDKxD01Lh8N33Qau18R1G3he86Ln9PG8Jp7XxLlC7a2mZVe7evrW3WpaarWryCEInNVbd/V9tNaGC/t+Z3XIcAdNy9DX+0PEYmOb+Om8eciyiq7nLxtYroUkSeh6Dl3P3aAzu7U4nsNSa4meWA/aVboLXd/lpaWX+PrU1+mOdvPY4GPkzfza6vDClYl3RxDe4lqtcxRLT15yf6NxkuWVryFJCun0/UQiAxQK38Rxyuv2kyR1bY4MVU2iaWlkObIaJuq4bnN1BMnm6iaCwMKyFlYnMLs2sdgOspmHVwuDH9iwONP3nTB0eG08r7369eqoFr+NIkfW5qq5HVpWhJvD8R2OFY5xcOkgh5YP8cLiC7TcFpqssT+/H1MzSepJ9ub2rq02HlWjTNWm+Ob0N2m5Fwqlf/fl3wUgpsX48NiH+Y/3/kcU+eYNzb6ViW4pQXiLq9YO02qeRZL1sC5E0kGSqFYOslL4Bs3m6XX7a1qOXPZR2p0Z6vVX8P1LV7a+OgVDz6Mb3USjoxh6T1jgK2mrt+pqjcqFqe0VxbwwLFlLoqxOjBYOkVbWvhaEG6HttjldPk1STzIYH0RTNj9/0ZnyGT597NOMV8aZrE3SdtfPaq1ICt5VWx5DCS3Bu0beRdkq8+Tsk/jBhUL64cQwqqzyvtH38baBt7HcWma2MYssyfzgth8kZaQ2fc5vBm+amptPfOIT/MVf/AUnT57ENE0efvhhfu3Xfo2dO3du+Lg/+ZM/4dd//dc5c+YMqVSK973vfXzyk58kl7t6M6YIN4JwbVqtKQqFb2BZS+Ryj5FOP7A23Ndxm8zMfJpWaxLbXsG2i7huGddtIsv62igRVU1hmsOkU3eTTB4gFtu+6SHDwu3tmfln+MLJL7Avv4+H+h9ib27vNRfnLjYXeW7hOUzVpCvaxXJrmanaFJYXDquPaTEyRob+eD+jyVFOl0/zxdNf5HjxOI7vICExkhxhODlMw26w2FzkZPkkrh+uUaZICtsz2znQdYCYFmOptUTTboIE2UiWXdldjCZHKXVKvLz8Ml86/aV14SVtpLmv9z7u7LqTe3ruYVd2FzP1GQ6vHMYPfE6UTvBK4RV2ZneiKzodt0PSSPLOoXdyR9cda2t2WZ6FLMl8beJr/Oen/vOG70k2kuXjd32c79/y/US116fQ+o32pgk373vf+/jJn/xJ7rvvPlzX5T//5//M0aNHOX78+GXXeQF46qmneOyxx/gf/+N/8MEPfpC5uTn+xb/4F2zfvp0vf/nLV31OEW4EQRBuHb/z0u/wfx39v9b+vSOzg5/Z8zM8OvAolmfxzPwzNJ0mpmpysnSSE8UT6IpOQk/gBi6ldokTpROvy7nlIjlabuuSlpfNeNfwu/jw2IcZSgwxmhq97KKir8Uzc8+w1FpClVW+NvE1jhSO0GV2sT2znZOlk0xUw5XYZUlGRqYn1sODfQ/i+A7lTpmd2Z3c1X0X3dFuFElhsjbJmfIZCu0CdbuO4zs83P8w7x197y3TAvSmCTevtrKyQnd3N9/5znd4+9svvwDXJz/5ST71qU8xPj6+dt/v/u7v8uu//uvMzFx9dVQRbgRBEG4dp0qneHbhWQ6vHObJ2SfXWluuhYTEHV13ALDSWiFv5hlNjRLX4gQENJ0mxXaR2cYss/VZYlqMD419iPeMvIeYFsP2bSaqE8zV50gaSfJmnt3Z3QzEBwBYai1xZOUIh1cO4wUePdEeEnqCgIDF5iIniieYqc+QM3MMxAf4ga0/wMP9DwNgtZqsTE2wMj1Ju1a75Nw1w6BrZAvdW7YRTd6YEGF7Np8/+Xn+7NSfMV2/8oSMm6HJGu8bfR8/tfun2JbehqnevPqzN224OXv2LNu3b+fo0aPs27fvsvs888wzvOMd7+DLX/4y73//+1leXubHf/zH2b17N7/3e793yf6WZWFZF/6z1Go1hoaGRLgRBOGGCoKATrOBLMvIsgISFGammD91ksXx02iGQe/YDnq37SA/NIK8weKdb1VVq8pfnPkLvnDqC8w15pAlmQNdB+iL9dF0mowkR9ZCTMNuoMoqUS3KnV130hXt2tRzOJ6DLMk3pBA3CALsdptmpUSzXKKxujXLRarLS6xMTVBdXrr6gVYl8l30bBmjb/tOBnfvpWfrGIp6/WuV+YHPSmuFgIDT5dMcXDpIXIuT1JMcKx7j6MpRanYNy7MYSgyxI7ODvlgfSSNJ223ztYmvcbq8vuYuG8kS02Loss72zHZ+47HfuO7zu1ZvynATBAEf+tCHKJfLfPe7391w3y996Ut89KMfpdPp4LouP/iDP8iXvvQlNO3SX4Jf+ZVf4Vd/9VcvuV+EG0EQbpTJwy/xrT/8/1Ge39wK4pFYnLH7H2Lng29jaN8BFFXUH72a4zu4vntTWwoup7w4z0t/+xUmD71Eo1LCta7e0hTP5eke2UIilwfW1xO1G3VWJscpL1w6WaWq6fSO7aB/xy6iqTSqbqDqOpphoOoGiqohqwqyoqKoq5umo+rhpq3uL8nX3yV2rHCMTx/79Fr34MX25fbx+Q98/rqPfa3elOHmYx/7GH/zN3/DU089xeDg4BX3O378OO9617v4d//u3/He976XhYUF/uN//I/cd999/MEf/MEl+4uWG0EQbjS73WL8xedYnpqgMDPF5KGDl90vEk/Qv2MXfWM7cWyLxbOnWRw/g92+MLxXN6P0ju2gb7VVp2frGPFs7pKiWqvVorI4T2VpgVphhXpxhXphhUapSHZgiLu//0P0bNn2ur7ua+W5LsXZaZbOnWXp3FlKczOohoGZSGLEYriWRafRwLE66BETPRrDc2yqy0tUV5bwXZfebdvpHdtJPJvDjCdI5LtI9/YRicVv8Lk6LJw+RWl+lna9Rrtew3NdErk8iXwXeiTCsW9/g7MvPguvumzqZpRYOkM8myOeyRLLZEnk8uSHRukaGcVMXP1aY7WaLE+Mszh+hvnTJ5g7eZx2/dJurGslyTL54VH6t+8Kfxd37CLd07f2++W5Ttj6VC5RXpynvBD+jlmtFoHn4fsevutiddrUrCpFr4qciDByz73suOtB7um/9zWf42a96cLNxz/+cf7yL/+SJ598ki1btmy478/8zM/Q6XT44he/uHbfU089xaOPPsr8/Dx9fX0bPl7U3AiCcDULZ0/xvS99nlR3L+mePhL5PFarSatSYWniLBMvvYjr2Gv7S7LMXe/7IA/9yD9CNYy1i4JuRi8JKb7vMXfiFU597ylOP/c07dqlazVFU2l6to4RTaYoLy5QWZynVa1c9byH9t7Bne/9AbJ9A0RTaSKJRNhFdgNZrSayoqAZ69dDqq0sM3X0EHMnj1NdWaReWKFeLOB7mxvyfK0i8QTZgSHyg8OYyRRGLIbTabM8OUGzXERSFGRZQTMMUt09pHr60CMmrVqFVrWC57phy4ZhUJydYfrYYZzO5gqHt9x1L3e+5wfI9g8SS2fQIq9tbahwVmYHXdfX3VdemGPu5HGWzp3BbrdxLAvXttZufdfFc118z8NzXTzXwbVtXNvG99wrv3exOEgSTqeN5155v6uJJJIceNf7OPCe7yeRfW2TN27Gm2aG4iAI+PjHP86Xv/xlnnjiiasGG4BWq4X6qiZcZbXv+hbIaYIg3AYK01NMvPzihvtk+gYYvfNu4pkcW+++j/zQyIVvXqaL/DxZVhjaewdDe+/gnR/956xMT7I0foaFs6dZHD9NcXaaVrVy2eePptKke/pIdnWTyHeRyOWJJtOcfeF7nPred5l55QgzrxxZ21+SZMxkklgqTbK7l3RvH5nePtK9/WR6+4nncpsKP3anzdnnv8fx736b6aOHCQhI5rvJDQwSTaWZO3WcyuLlJ100ojF6tm6je8sYXcOjeK5Lu17DajbQjAiReAItEsFut7BaLWRFIdXdS6q7B4KA+TOnWJ4Yp12v0q7VKBcL1D0fS49QX1hgZuIc0urcL5LrIgU+vqrhmTGQFQJZRj57FqXVWNvvSsxkir6xHZiJFGYyiawoNIoFasUVmpUKAzv3cO8HPkxucBjf9zl06BCnvv0EhmHQbrdJp9M0m03K5XCiy2QySV9fH5Zl0W63ueeee0in01QqFRzHYWFhgampKWZnZ2m1WkSjUVKpFK7rEgQBsViMeDzO0L57GBsbI5e7tEXvSnzPw7XDlrHF8dPMnz7J/OkTLE+M02leOqGmEY2Fvxd9/aR7+4kmk0iygqyENWRaxMSIRtHNKAtnTvLS175KbWWJ5778Z0iSxCM/8TObOq83yk1tuflX/+pf8bnPfY6vfOUr6+a2SaVSmGbYz/qLv/iLzM3N8dnPfhaAP/zDP+Tnfu7n+J3f+Z21bqmf//mfR5Zlnnvuuas+p2i5EQThasqL88wcO0JlaYHq0iL1UgEjFieWypDs6mLbvQ/SPbr1dVks0bE6rExNsnTuDFarRbqnl0zfAOnePozo5afIAKgVVnj5777KxMsv0qxW6GyiS0NRVZJdPaR7ekn1hK1UkXgCq9mg3WjQadRplktMHD541doSSZbpHdvB8N4D5IaGSea61gLYtbxPQRBQqVRYXl6mWCwCIMsyKysrTE9Ps7KysuHjdVXFvkxrhASYMiQjBn25LN2p5ForSCydYfTA3eHP9Ar1KZ7nMTs7S61Ww7ZtXn75ZWZnN1djdaMkEgm6urowTZNqtUq9Xicej5PL5ejp6WF0dJS+vj5kSYLSOVg4BE4bnDZ+p0atZRNTPTo2qLVJjLlnCHr2I+14D3J6CPoOQKJn/ZM6HTj251CfBy0Gbhs6NfzRtzFejnHo7/+a9//rXyCeyb7ur/9N0y11pV/4z3zmM3zkIx8B4CMf+QiTk5M88cQTa9//3d/9XX7v936PiYkJ0uk073znO/m1X/s1BgYGrvqcItwIgvBWcL6FpFWt0CyXqCwvUlnt4qosLlBdXrymLol0bx97Hn0nu9/2OHo0Sml2huLcDI1yid5tYwzu3o8Rvb7J4ubm5jh69CgLCwssLi6uq5O8nJ6eHnp7eykUChQKBXzfX13B/cLr6e3tJR6PoygKCwsL1F41DDuXy2EYBrlcjq6uLlZWVhgdHSWdTlOv11EUBVmWOXLkCJOTk5c9J03TeOihh9B1nUgkQrFYxDRNenp6kCSJpaUlKpUKsizTaDQ4efIkQRCQMlU0M06uq4eRkRGGh4fJZrNUKhXq9TqapiEFAc1GjUqlzPjkDFNTU/j+xi1PAIbkMiwvMeqNk6KOi8IiXRxnBzUS6NgMsoCFziJdpKgzyCLDzLGX05jJLjjwkzD8IEw9Ay//MTSXL/9kez4MH/xtMDNXPa8b4U0Tbm4GEW4EQRDC2p9GsUhlaWGthaqytIjVahKJJ4jE4uFtPE7/jt30bd/5urRUARw+fHjdJKyyLJPP5+nq6kKWZTzPI5VKMTw8zPDw8BUneW21WpTLZVKpFPH4hYLjIAgolUrMz88zPT3N4cOHsW37ssfYiKnJdMdlFKdJfybC/R/6ZyTzq3We7TJ0qtBYgYOfgdIE9O6H0beFLSilc7RnDqPUptFxwUjB7g/C1segew8k+8NjlCfhpc/C8a8Aq5dnPY5lWyyRp0CWDgYp6iRoUCdOkTSz9DHFABYb1f8EvHq01sVUXPZyisd5lgwXhcHUUHieThtUE3wXjn4R8tvhn38XVP2Kx7yRRLjZgAg3giAIt5ZSqcRzzz1Hb28vvb29dHV1XVJbeU0ayyDJELt8kWunXuHsc19DLpziVEXFVmLkBsc4N7OA4zgkEgnKy3O02h3uTpbZV/s2Sa9AlDYKF10yU0PQvRvmD125dePVtCjEe6A8sf5+RQfPATa6JEvha9rzIajOQn0xfK16FB74F/iqyWIjYLJpMFW26VgOqqoSj8fZvXs327Zto1gsMjs7i67r9PX1UalUmJub4/jx4ywvh69BlTweMsa5f2sadevbaQw9huV4yLKMoihEo1HM6jiq5MPA3Zt73TeACDcbEOFGEIRbReAHtOo29WKHdt2mezRJLGXc7NN6c3La8Gf/BBYOQ2MJkGDkYUj0wsKRsLUhNQjNFSicgVcvXCkpYVdMcgBWTsLikfXf79oN2a2gaJAbg6N/BpVXzf6rmiBJsOsDYYvN8b8MQ8jwQ+FjuvfA6CMga3Dqb8JQdPRL0CrC+TlkJAXMNPzop6H/rjCk1RYg3g2R1RmMX4cWtCAImJ2d5Zvf/CaTk5Obesxg3wg/+eM/RSytv26tehcT4WYDItwIgnAjtes2naZDIhtBVmXstovVcmk3bCqLLcpLLZyOR+AHDOzMkOoyOfKtGWZPlWlVbXz/wp9gWZYY2JkGwO54qJqMEdUwExrdo0n6tqVI91w6vPw8z/OpFzpUC210QyE3GEePXNoC4rk+zYpFp+nQaTi0G+GtY7n0bEkxsCONrNzYtZDeEJ/cCY1Fwq6Xq1zaEv0w9k7w/TAQLb+y/vt6HO7+J5DbBj37YOiB9aHCasChPwm/7r8buneBkbi+8w4CmHsJZCUs6g388OsN1EsdZk+WsVoOvh8Q+AG+F27tuk2rFm7tuk2r7qDpMrG0sbbF0wbRpI6qKyiqjKLJRJM6XcNxTp06xTPPPLO2pJFhGEQiEeyOi2XZ+IEDEuidPKnKHlRdpm8szQ/+mzuv7/Vvkgg3GxDh5o3nd1xKXzyNbChIhoIcUZEjCnJcR0kZKCkdJWkgGwqB6+MW2zjLbdzlFs5KC3e5hVvsoOZNzH05zH15tK7bY5Vb4c3Jarsc+sY0515eoTR/0aytm7imvpokQSxtoBkK5cXWVfdXVBndVNAMBUVT1q63ruNTL3YILgpLSJDpidI1nECSJGrFNvVih2bFevU8dOuYCY2xe3rYfm83vVtTSPLr/6n8hjj1NYjmoGdvWL9y/K/C0T19B8LuoMoMRLMXalwuDivlSZj4blg3I6uw/0ev2K31RmmULaaPF3Esj0hMQ1FlFserTB8vbup35XrkBmIc+L4hdtzXS7vTojTbZuJQibMvLtNpOgBoEZn8iEmt1KZVDINV//Y0P/QfXt8uKhFuNiDCzRvPLXdY/LUXrrqfZCgEjg/+1X8l1Z4o5q4skiYTuAGB669tkiKhDyTQRxKoXdE3zx9m4ZZ26BvTNCoWjuUx/tIyVvPCyBzVkHGtCyNZFBV8t4nrlAi8IgQdkDQUYy+SpGPGCgztNth2z06G9m1fWzqmMNtg8VwVTZfRDBXP9bFaDvVSh4XxKsuTdTx34xEziiaT6jKxmg7N6pWLZhVVxkxoGDENM64RiWlIssT08eK61xbPGmy/p4ehPVmS+QjxbATlzdiqc4to1WzaDRvNUFA1hWbVol7s0KrZ+J5P4EOn6TB1rMjKdP2Kx5Ek6NmSJJk3kWUJSZGQ5XCLxDWiSZ1o0sBM6pgJDdf2aJQtmpULW6vu4Lk+nuPjOj6lhSauFXbXmUkdWZZoVi6MEkvkIhx45xC7H+5DN8MWwfOthZ7rkxu4sbNGv5oINxsQ4eaN57ddWodXCCwXv+MRWB5+28Wr23hVC69mE1gX+r8lXUHtNtG6o6jdUbSuKGougj1dp3WsgHW2sqkABGFg0ocS6EMJ5PilE6tJkgSqhKTISKqMpEqgykhyeB9K+EdDUmWUjIFsXLnI0W85tE+WcGYbyAkNNWui5iIoSQPJkJE0RQStN7HP/cqz6z4t6xELRTpKs3wUu10GKQJIENhA+Pt8fs2fIAhwbQtQABlw1o4TiScY3L2XVHcPsUyORDbH4O59xLO5S87Bc32aVQun49GsNFg6N0EA6BETIxald2sP6e7k2u9Zs2qxMl2nMNNAkiGZM0nkIiTzJmZCu2z3luf5zJ4oc+aFJc4dXsHprK9NOd/SlO2L0b0lSe+WFD2jSSKX+f/1VmW1XYqzdcyETiIXYfqVEhOHVpgfr1Jb2dwsyABI0DOaJJGNYLUcrLZHfiDG0J4cg7syRGI39j3vNB2OPzXP0SdmaZTDUKObKlvvzDN2bw9DuzI3tbtShJsNiHBza/ItF69qIxkKSnLj4jS/5dA+UcKeqoHEaiiRw1CiygQdF3umjj1bJ7CvPi/EtVDzJlp/DK0/jt4fR0kbWGcrtI8Xsc5V4CpPJ2ly2DVnqkR2Z4nd04PWc+WJ2YTXl+e6LJw5Sa2wQm1lmVphGYKAZFcPqe4ekl094SzAqTTf/uyzzJ48S215Ht8r4jtnuLgPKppKI6sqBAGyorL7bY9x3w/+6NrcL3a7Rb1YoF5YobQwz8wrh5k+dmTdOlMX6922nW33Pkj/jl2YyRTRZIpIPM65l17gyDf/numjhy+dYl+SSHf3kh8eIdXdQ6fZpF0LZ/aVFAUzkcRMJIlns2T7B8kODJHtH7hkKYXzXNtj6pUiZw8uU5xtUCt28JzL/5JHYhqBH+CtfvDo25Zi651dbDmQXyuSdm2P6kqbxXNVFser1EsdknmTTG+MZFcEu+3SrNr4rs/Wu7rJD76+LQEXC4KA+dMVykstVE1mYFsKU5bwauEHMK9qEwQBajaCmgs/uHRsn+WpGq2ajaJIFGYbTB8vUVporv1qyLK0rq4KCSJRDcf28BwfM6GRyEaIpQ2U1Q9WiirRvz3NyL480eQbM8z6Yp7nM/1KCUmCoV1ZFO3WaKkT4WYDIty8dQRegLPUDIPOTD3s8no1f7VLywvC73vh1+dv1752fPzW1Sc803qjGNvS+C0Xt9TBLbbxm86GdRj6cILoPT1ED3QhR1T8tos9XcOaquHMN1ESOtpgHH0wgdYTDYPcDRAEAX7Nxq1YaL3RDVulbld2p83v/uyPXduDJInerWMM7NpL/87d5AaGSXZ3o+nXPsrJ97xw2YWzp2iUSzRKRcoL8yydO7Opx2f6+tEMk06zTqdRx25fQ6vAeZJE19AIw/sPMLTnAANbd9Op1ChMT1JaXkBWpbVwle7ux1+WKZ0qs3KuSqHYoeQGNK8S6uNJHcvycKxrW2eqd2uSvY8OsPWurssWRl+J17Bxl9thy+lqsPI8n9J8E8/10QyFTE8Ur9CmPddg/EiBE6+UKNcvtKjJwIAuEZMlsopEXpVYdAJqq0Fl0QmoeFf+jx3PGLTqNr4bEM8YbLurm+G9WXq2pjBMlcAPcCsWXrkDQYDaFd3wg13gB+HfEkBJ3NjAU1tZZv7MSSBciVzVdWLpDMmunrVwHgQBVquJ3W6TyOZe00rj132eItxcmQg3wvXyGjbOQhNnvoE918CZb+KWOuhDCcy9Ocw9OdS8ecnjgiAA18e3PALbJ7A93EKb5sElOqdKa609khZ2fbkr7SuHIVVC64ujZgzkiIp0vjjbUPAdH3eljVto4660CNwAOaGhxLSweDuhIcc0/JaLs9jEWWoRtFcDmyJhjCaJ7MwS2ZVF7TKRJCn8g9pwLnx6rdsQhH9claSOnNBR4tpa4Lr4tRKAHL9818et5I9/8efRzSjJfDfJri4g/GNfWVqkXgxX3fY9j0giyf53vJs73vV+0j29r+s5NStlxg8+x/jB56ksLoStL406BAFGLMad7/kBdj/6DnIDQ+se16pVKUxPsjI1SaNcJBKLYybD1prA92nX67RrVWrFFYpT0xRnp7E6zSucxeXF1BR5Y5BcpI+03k063kvganS8AIkwFHjAgu2y6AZUvPU/f1WWyOci9GxJktuWol6zKS+2qBU7RKIq0ZSO3faYPFJY1+JhxFTimQiJbIRUl0mqyySZN4kaMrWJGrPHS5SXWyQ8n4Tjs+IGzDs+siyRjGtU2i72RS25ERkikkTdCzgfuRQgr0pYAZcEF0OTsS7zASkuQ0yW8FeP2aPKdCU0ommDIKLS0WRS+QhqXMe3PdxC+KHHLXbgVfVTki6jdkXD/3+yhNdw8Ovh/zu3YdFyath+B6XbQN0ax9iSQolpIEnIsoKsKsiKSjSZIppKo6zOFRQEAbPHjlKYmMI0E/ieS6NSolpYYub0UcpL81f8eRvRGIqq0WnU8f3wnYoYcfoz2+mLbOXAL/8oZuI6R4ldIxFuNiDCjXAjBUHwmi7eXt2m9fIyzRcXcZcvfOpWchGM4ST6YByv7mDP1bFnGxfCyI0iEwaeiz6xAihJnQDwV8PMVQ8TVQkCwtqpi4c2J7TwdYysbv1xpFukiXuzfN+jXasRicdR1GuvcfAtD+tsBd9yUdMRlKyBktDxG07Yure6eaUOKBJabwytL4beF0OOXng+3/foNBroZjS8aHnBhq14QRDg1x38jhvWuVkefsvBmqhina3grrQJgoCO12SlM8NSZ4ql9hRNt4KERMLIkdRzSIGM5bboeA3qTongMr8Qqe4e8kOj5PtH6NTrzJ0+TmF+GghAiiPJSUxZJaMnyel5YmoSQ4liKnHS3X3IqhKO8vIDCAKkiIqXjTDVcjk7Wae+QWH0tdCkcLN8uLgNKWoo7NiWZNeBPNGeGGraYGmlzfSZCs2qxfhLK3hO2OKz9c4uAgK6+uNs2ZJEazk4S621DwxhS8wmT0iWULNhl6BbaoMf/txWOjOUrAUabpWWW6XhVmg6Ffyr9Xu/iqFGiahxAt+jZhevuJ+ERMboRZU0vMDFDRzabgPbv7QlUEJa9zsgyTKjB+7mh/7Tf33dP8iIcLMBEW6EW1EQBDizDby6jT6UuGyzcxAEeKUO9lwjLMLuXFSg3XGRFAk1b1745KfJ+E0nbHlp2Ku3DrKhoPXGUHuiaN1hN5dTaNM5VaJzsoR1rgre+hoBebWl5vx5eXUbvx4elys1zV9uWLQihRfuwcRaobeky+AGBJ4fjnzzfCRFRs1HrtpVFqx+8r1RXXU3ilvp0DlRon2ihDVeufJ7dBVKSkfrjSHpSvizbDl4TQe/6YIfIJkqatpAOb8ldLyqhbPYwllqEnQ26AaSQBtMEBlLY2xNhS1xpkbHbmCkEqgXrWweBAH4YLeaLE6cZfbkKyxPnGVlapJ6ceOFLK8mo/eyJ/0QcS1NEIRF/oZsYigmsqSExdgBdAyFWqNNxe3gYGAFKi0/oB2Aqkj05CLkBuJUOh6lUof8UIJd9/UQVDqUzlSINB0yvo8+kEDpj1H0wY+oZPpjZPpiyBsU+zerFtOvlBjZl7tqDYxve3ilzrr/c+f/H0qaHP4fza8ONkhHkJTweX3HY/zp53jur77A0tz4ZY+taDpmPIHsSeBKsNqSFBAQBAEBPl7gYXktglcFIUVS6TKHsYM2sqRgqgmiapIuc5Du6AgaOrjrf08d36blVvHxMWMJzK4set6k6C4wWzjF9MRRystzjN33IB/6hV++6s/6tRLhZgMi3AjCxnzbw5mtI+lKOP9QXLviKK/AD/DbLn7DDpvGV+cyknQFvCBscZqqYU3WsKfrazUDmyUndNR8BDUTCeue2m54oWi7+C2XwA4v3lJEQYnryLGw601JaCgJHXk1kCmJ8HvhuTphOFsNfZKuYAyvjqiLXt/oE69hh7VdU3U6p0o4C+u7epRcBDVthDUWFSsMOzIo6UhYoJqNoGTD1+gsNHEWm2FLzmslEXZdrv5M5IiCNhBfDTRpZPO111m16zVWpiYpTE+wMj2JoukM7dnHwK69GNEovufj2haF6SkWx0+zPDVBs1yiXatSXV7Cc6/8O6GpBgoaCgqOb2H74XsiSwo79zzCfT/ww+T2jb7h9WKLZ0/z8t//NZOHXyISi6+tfp7Md4eF6N09JPPdtGtVirPTFOdmqK0sk+rupWfrNtK9/cQzWSLxBPXiCieffpITTz1BYXoSCOtett77AJnePpJd3aS6esn095PI5tfVurjFNq3DK7SPFvAtLwy6KQM5peEYLh2adLwWbmAxfOedRPOZDVtXgiAAb7UO0fHDDzaGEg7WuMLjqsuLuLZNbnD4hr7HlyPCzQZEuBGEmyMIAryytVbgbc/UceYbBH7YvSIpq8PwFYnA9sLWiTeY2mWiDyfReqPhmOcAzs92F/hh0Xm4rdZPWS72QhOv+KogIoE+nMTckyWyO7dWw3T+OH7LQTa1tU/tl+N3VmujFpsEboAS15Cj2lqAk3UZr2bjVsPA5FXCuigloYVdW70x1Lx5y7VqXaxVrfDCV/+Ck888ie+6SLKM73l06nWC4PJdMEY0htUKw6OsKOx9/F08+EM/QbKr+3U913a9xtkXn+XIN/6OxbOnb8gxFVVdtzK7qhscePf7ue8Hf4RY+o1ZafvNRISbDYhwIwhvDn7bDYujC23cioWsy8hRDSmqokQ1ZFNFjq5OJLbW/ebgN+wL3WarxZhezV4NFGrYwpPQ1m79uoM9XQsLPF+D88HI2JoisisbFnoK1yXwfTrNBp1GHde2cawOWsQk1dWNbkaZPX6M7/3555k+dhgI5xPa94530b9jN57j4Do2Vqu5ttK50+ngOjae62CYMQZ27WFwzz4Gd+8jmkxhtVrMnjjK9LEjLJw9RSQWJ9XdS7qnDwgYf/E5Zk++QuCHgUtRVXY+/Hb2vePdBH5AvbhCvbBCdWWZ2soilaUl6sUVIvEEucEhcgNDJPLdVBbnWZoYp15YodO4MEHf4J597H7kcbY/+Ahm/I0pzn0zEuFmAyLcCIJwOV7Dxp6uY0/Xw+JOSQq7deDC17oSzlWkyWtfa13RsEvrBnTxCNdm9uQrfO+Ln1sLOdcj2dVDvbiyFlw20jWyhZ0PPcr+73sv0WRqw30D399wuLTrOLQqZRRNE600myTCzQZEuBEEQXhjNEpF6qUCyXw30VR6Xd1Gq1ZlafwMleVF8kMj9I7tuGSuoGalzMwrR9YmWWw36qS7e8gNjZDu6SWWzhBNZ1g6e4aDX/sK7XqdwPcJggDDNMn0DdA1Mkosk0PVVCRJprq8zPzp4yycOUVhZmrtudK9fQzvO8Dgrr04lkVleZHq0iKO1WFk/12M3fcAqe7XdwoAYWPXcv0WHzUEQRCEG2ryyMu8/LW/YuLlg2u1M4lcF8P7DuC5DgtnTlJdXlr3GFlR6d6yld5t20l19zJ5+CWmjx6+Yu3NxVTdWF3e4lXncfglIByu/OqWmcHd+3jPP/83xLM5coNDJPOvb82O8MYSLTeCIAjCZZXm51gaP83Y/Q+tW6LBtW1qhRUqi/NUlhZRNY1IIoGsqBz5h79l4tDBtX1jmSzNSpnLLUOe6R8k3dPL8uQ5muXSZc+he8s28oPDJPLdROJxKovzFGamqRcLtCplXOfCHDiqbhDPZDFTKaxmk2alhNXceJLCWCbLvsffzeCuPXRv2UY0lb7Gd2nzyovznHnuGSRZ5sC73oduRq/p8a1qhYlDB1eX0MiF8x1JEnarRadRx7E6eI4Dskx+aITcwBCyotCslJk/fYLaygr9O3bRs20MWVZep1f5+hHdUhsQ4UYQhLe6IAhYGj/D3KkTRNNp4ukM9WKB8sIcjmUhKwpL584wfewIAOmePh79xx9h8expTj795FXntpEVlQPveT93vucDZPsHcKwOcyePM3P8KKqm07djF31jOzCisbXzqS4vsXD2FEvjZygvzNE3tpNdjzxGrKuH2XKbvlSEiLb+ghwEAXa7TbseTrJoRGOXDFl2rA6dRgNF01A1DUXTaNWqHPnG33PkG1+jVa2s2z+eyYbLDsRiGNFwyw0Ns/2+h9YtZup0OkwdPcTSxDjF2SlKc7Mk8l3c/4M/wtDeO4DV5TXOnOLcyy8w8dILrKwO9YYwVL39H3+U7pEtOJZFu16jXa9hxOLkBgbRjAhLE+OsTE3QaTaw2y1OPfPdK65FdjmqbmAmkpf8vCLxBMP7DpDIhUPLZUVBj5j0bd9J3/adV1xr7GYT4WYDItwIgvBmVV6Yo7q0SNfo1kuKUDuNBpNHXmLu5HHqxQKNUpFmuUgsk6V/527yQ6P4rkunUef0s0+tu9BeiSTJGLHYupE952lGhHRvH6nu3nAW53oN33VJ9/bz8I/9Y7L9A9f8+l6cDBdrTJkapq4yVWjyy185xrmVJrIEO3uTfPjOfn7iviHS0de+vpLnOpx57hnOvvAsy5PnKC/OX7aFCQBJYmDnbkbuuIvF8TNMHzm0rtXoYgO79hKJx5l55ei6MCLJMsP7DqyO4lq4rnPODgyhKAqt1ffb970whMXi6JEIiqrhuQ7LkxM4nfbauYetX13MnzqxNpT+si9TUYj0juB0jTK0/y4ig9toezKPjOXpTd3c0CPCzQZEuBEE4Vbi+x6e66JqV140cf70SZ7/ypcYf/HZtfvi2Rw9W7eT6etn4cxJ5k+f3NSIn/MUTWN43wGcTodmpUQ8kyPTN4ARj+N7HmY8we5HH8eIxvnu5z7D0W99naG9d3DgPd/P4K69ROKJGz7d/uO/8W0mi5e2TCiytLbaOMBA2uTTH7mPnb03dti03WlTmJ6kWSljNZtYrSbtep3pVw6zcPrkJfununsY2nuA/NAwmb4Bzr38Ise+9ffr5q6JxOKMHLibrXffx+iBu4kmU7i2zYtf/QsOff1v8D0PLRLBTCSJxBO0qhXK83O4rkNuYIieLduIpjNohoGa7SO//z66khHmKm3+7+9NMVlsEtNVPD8gE9PZ0RPn8Z3ddMd1FmdmWF4uoHYNUrBlig2LB0czJOvzzJ44htVu4XsevusxObfI0pmT6J3autfoSCqzkQFmokOkunvQFYmkLpMxFaKqRH7vPfzsYztv6M/hSkS42YAIN4IgbJZjW9QLK3iOg+95ZFe7CzZid9rMnzyOrGrEszkS2Rxa5MJjAt+nMDPF9LEjTL9ymNnjx7DbrbBrwIyim1Ei8Tjp3n4yvX3MnTrO7PFj4YMliXRPL9WlpcsW2uYGhxk9cBfp3gESuRyxVIbK0gJzp05QXV4MV3w2DPrGdrDrbY9f05wqvu+97nUaP/37zzFdalFtO7QdDwn48J0D/NL376bjenzr5DK/951xpootEobKI2N5yi2bUtOm43p0JyK0bY+VhkXcUNEVGUmC+0az5OMG9Y7D/VuyTBabDGdjPLAli6kr/O63zvAPx5ewXZ+hbJT7RrOYmkJ30mAoG6U/ZaJ2Khz+7lMUxk8wPDbG2H0PkR8auSTg1UsFjn37H1BUjZH9d9I1umXtfXM8n4lCk5btUWpazJbbjHXHeWhrbt1xzgdeRdU5OF3m6bMFvn1ymcOz1RvyPufjOkPZKF1xgwA4OFWm1LQhCEi4dQ5oJcbcRfTF0xjOxjVL/7Dv/8Hf/ZcfuiHndTUi3GxAhBtBENr1GoWZKVRdRzMiaEYEVdfxPW+t9mT84HNMHDqIa10YhaObJjsefJTdb3ucrpFRIqvhoLK0wOzxY5x94XtMHT0UFnVeRFaU1XW2VtcAusY/u7Kisuft7+DeD/4wuYEh7E6b5clzLJ87S2l+lvzwFrbceQ+p7p7X+tbc8spNm3/+fx/k+cnLFyBfq6iu0LI3WIPrMn7yviF+6Qd2k4xsPFFjqWnz7Lkir8xXOTJb5eBU+bLPtSUfYygbJRPV+JkHRxjImPzly/N8/vlppksXdWtJYKgyHccnosncvyXHDx7op+N4KLJEoW7x0nSZp88WsT0fVZbIxnTihko6qhGPaDx7rojtXhqMExGVH793iJ9+cIQt+Qu1UIXpSSYOHeTUSwep1xogy7gB2B64yKiP/SN+4Yfvv6b373qJcLMBEW4E4a1l7tQJCtMTOJ0OVrvF7IljzJ04vqkhxgBaxEQzjHBZgFfVnuimiayol9wfNyJIjkvbdXAvsy6X4vlkmx1yjTa5Rouo5eLJEq6uEXTl8XJZWokYjcDH0HR2dA8Qj8eRNO3CpuvIsRj6li0Y27ahpDaeVG4jQRBgT0zSfPppmk8/TevllyEIkE0T2TSRoiayGb3wbzMCno/fbK7bvFYTv9kC10Xfto3I7t1Edu0ismc3xq5dKPH4dZ/jxSzX468OzdNxPJKmRj5uYKgyK3ULQ5PpTkRoWi6uH1DvuHz3zAqW6+N6Ps9NlNjZm2C23ObscgOAnqTB//P9u+hPmRybr3FyoYbt+SxUO8yWWizVLTw/QFfltWAQ1RW29yTY158kFzcoNS3uHs7wwNYcQRDwueem+czTk7Sd9WEmbqikTI2kqdGXivDcuSLNDcJVIqLy2I4uHhnL8327u+mKG7QdD1NTrtgt6Hg+QQCaIl2yT8t2GV9uMltuUWzaWK7PnUMp9g+k0W/hpTpAhJsNiXAjCG8t3/z0pzj0939zyf2p7p7wot7p4NoW7uoooVgmSyLXxdCe/Wy//yG6t2xDkiQC32f25Cu88p1vMnn4pXVDl2UgZXvki1V6a03iHZvzlxRHlvBTKbTubtSebrSeHmJ9A0jtFs78As7iIs7CPO7SMnjX1oJwMaUrj7FtDGPrVvSxbeHXY9tQstnLXgTdcpnWs8/SfOYZGk8/jTt/fQWu10IbHg7Dzr59mPv3Edm7F+U6/g4Hnoe7soIzN4czP48zN4dbLOGvhqsLty38ZhNcFzkWRY7GkGMXNjdiUpd0ciN9xLePYWzbhtrTc8n75fkBtbZDytR4carMf/rzI0wUNu6uOW97d5x7RjLsHUhx70iGnT2JdSuQNyyXJ0+v0LY9Xpgs8aWDs7h+wP1bsvzI3QP84IEBTP3NN2z79SDCzQZEuBGEt5aj3/o65156fq0FJjc4zLZ7HrikCycIAgiCDafMD4KAxrefYOX/87u0Tpykrat4skS8Y6MEgCShb9uKuW8/kf37MPfvR9+6dVMtFoHr4hYKYeBZDTuBbRHYDoFz+c2rVLDOjW8YTJR0Ogw7W7dhjG3DLZVoPv0MnWPH1o0MkjQN8957iD/yCNEHHkSORfFbbYJ2C7/dxm+1w9vKEsHsKxDLIPeNoaRyFwJDNIoc0UHR6Jw+jXXiJJ0TJ+icPIm7cPlz1EdGiOzfH4adffuQdAOvUsGrVsPb81u1eiHQLC6Cc20rzG+WFI1ibNmCvnUrxtYt6Fu3oQ8PgSwTOC64Dq7tMF+oMVuoc26hitOxicoB44sVlkpNtMClOx3n8XffyyPvvBc1s7nlFYIgoDi/gr28QrJVwZmdw5mZxp6ZxZmZwW+1kEwT2TCQzAiyEQlvIyZyPI6SSqEkkyjpVNiSp6rgugSeR+C6F33tge8hGRFkM4IUiaB1d6OPjiJpt+6aaCLcbECEG0EQrlUQBDSfeYaV//N36BwJ535BktC3bCGydy+RPXuI7N1DZM9elHjsDT8/r9HEnjiHdXYce/ws1vg5rPFxnJmZKw9tBozt24k98gixRx4meu+9yKYJVgMqU1CeBFmF9HC4c7sMJ74KL34a3POLjEqw/d3Qux/Gvw2FM2DXYeAe2PUB2PE+6NoV1mmUy1gnT9I5fpz2sWN0jh7DmZ297Hk1zCjRThs5CGhETIrpDNFOh0Y0yqnhrTxzx92Uk2nuWZhhYngLtUSSmCJjShJ9UsAdeDysSfTETORYNFxtvNXCazYJVm8vdKe1cBbmsc9NYE9Pg3vjV6Nfa1XbFgbMwPdxCwW8QgF3pYBbWN2KxQ1DW1s3OLhrH4lWk22zU3iKQtOMkqlVMS8zQ7OtqlTj4XWuFosz292L7jh85+4HUHyPdL1OR9cpJdMU0hl8ReVAeYV/WV4gv30ban8/eB6B4xJ4q+HIdTmmRni+q49WIskv79uGpL/2YfmbIcLNBkS4EW6GwLZB02740FnhxnCWl2k9+2wYBBQVSVWQVBUUhcCyKf/xH9N68UUAJNMk+9M/TfZ/++imP5HfLH6ngz0xgXV2HOvcOPbZcaRIhNjDDxN7+CG0nlcVIFsN+MQm5qfp2g1WDWpzV9zFllS+l76Tb3e/nSdyDzOlpnk8WOZHkjLv2rKTldgA35pbojo3z3tOHiV2+BCd48chCPivP/VzvDCyjS2NGqfTWTrK9a0UNBY1sP2AuCLzU31ZHkrHWbZdZjo2dhAQlWWiikyXrjJiGvRIAeXpWbSpCbxzE9jnzmFNnMOZnQNJQlJVAk2nHY3SisZIuxYRSQ5roFR1bUNTCTrWVVvVIKwzr8USJFoN5NXLsZJKoXTl0QcGUYaGODm2k7/tHuQvJYMGl/8bEvNcIp5LW1YIgoBsq8lCIoW/QUvklcRbDbZPT/Jj3/xb7jl5lOf33kkpkaIWj/Pc3js5NrYLAMO2+Ov/8HOY3V3E3/V99P7SL13zc10LEW42IMKNcDMs/Ndfofa3f4s+NIQ2Mow+NIw+Mow2NBT28+dyVz/Im0AQBHjFIl65jNrXf1NaMa5F5/hxSn/0Wap/+7dX7eaQdJ3MP/pJcj/3c6j5/Bt0hjfBr2+FwIf0CAQeVKZBUsBMQ2YLPPQx2PbOcOhOcRye+R2wW+F9A3fjqhH+7MTL/GYzw5x6+SJnw7ew5AuLZEYCl5+yjvMv7VcYisd5WH0v5/z1rQEKkNIUBgyd9+STJFWFF6stdsYi7IpFaHgebT9gvNXh+WqTI/X2Nb90idVBbUBeU7kzYXJPKsbbMwlWbJfPzhd4slzHDS7s329o3JWM8qM9WR7LJqi7HmXXQ5VAlSQmyjVemZnnaLnGGdenv7jCB2fGicdjvNA/wtcyPUyqOhFgzFBJRXQ0WUGSwPEDxtsWC9aF383BiEYQwNzqfRFZouNf+TKurmYhTZLYHotQtF3enk0waOiUXZeILNOtq/RoKo1Ckd9YrrEoXajx0TwX51XhUvM8Hj53ir3Hj/CBb/0dpm2R+vCH6f9/f+Ka3/NrIcLNBkS4EW6GqY9+lNb3nr3i99W+Psx9e4nsDesOInv3vO6tAoHv41WrBI4DjhOOrujp3nSfe+A4tF58kcZTT2GfHceemsKZnw9bqVapPT0YO3eQ/uEfIfGu7ws/1d7o1xEE2JOTNJ95hvbhw8hmFDWfR+3Ko+bzKOk0fse6ZGRP8+mnab3wwtpxInv2oGSzYfO7s1qb4Hnguph3HiD3z/4ZWu9bYFVouwn6RUOBHZeYohBVZIIgoO75LFgOBduh5npUXY+669P0PJqez98VqpxphV0keU3hXRGbx+1JRpwif2NF+QsGmNcyKIHL3bUTOJLKoeRuAFTf5ftKzzLankXRY9CzlzuXvsfDZ79A1q0iJ/rCLq+Be8KusJ59kOxbO3XL91m0HOYthxONNn+1XOG5apM3+0Uursi8J5/iJ3qzPJqJI0sSNdcjIkvoskzN9SjYLm3fx5RlfAKWLZctUZ1ePfz/HADyJlqOO57P6VaHryxX+OP5IlXXI6ep3JeKElMUdsci/Ehvhj5DDz/MFArYMzPIsRiRna/vZH4i3GxAhBvhZvA7HZyZGeyZGeyp6bBIcGoae3o6rDu4zH9Drb8fY8/ucDjtnj0Y23egduWRDeMyz7DJ82i3aX7ve9S/+U0aT3wHr1hcv4Oqog8Po4+MgO/jNRqo2eza6BY5kaB96DDtl1+m8dRT+LXapU8iSciJxCXfU/v7iD38MM7sHPbkJEjSWuGmPjSINri6DQxetsUncBzcYhF3eRl3ZQV3ZYX20aM0n/neFYtVr0pVSb73vWR/9p9g3nHH9R3jNuQFAV9drvDbU0ucbIb1NRFZQpYkWt7Vh9BnNYV/M9zDRwbyRJT13SJeEHC6Vqe/MUWq8ApBcZyn5R7+T8b4bpC+4jEN36LHKpJ1qqiBh4yPHPgoRpxGrJ95JcGKc/nRZo9m4vzcYBcH4hE61QWW5o/zUmGJF70YB9VeFpTwWvADnVMcKL7Ed83tPJu+E0e+chjPqDIV179icFIlkJHoNzR2x032xk22xwz+oVDjaKNN2/PZHo3wQz1p3p1LUnQ8zrY6tDwfNwjwAtBliaym8mA6hnEd3UuvleX7nGp22BY1iCk3f8SWCDcbEOFGuNV4jSbWieO0j71C59gxOseOYU9NXXF/OR5HzeVQ8vnwNptBSaZQkgnkZBIlmUROJMDzcEslvFIZr1zCGj9H85lnCDqd9QeUpLAg0PfDVpxroGSzxB9/HPOO/eijo2E46e5G0nW8ahXr3Dka3/kOlS/8GV65vOnjqt3dGGPb0IaGcVdWsMfHsWdnrzhUWtI0zLvvJnr/fRCAW1hZLdRcwatUwtEkFw0BluMxtP5+0j/8w7d0a4zjB7Q8j5bv0/R8qk7Y5VFxXGKKzPZYhJGIgXaZuXSulR8EHK63eaJU40uLZcbblxaonpdUZbp1jZSqkFQVEqpCXJGJKTJDEZ1/1JcjoV77xfBwvcXzlSYzrRYzC2eYtj0WtAwlNl+wavgOfdYy/dYy2+1l/on1CnutWWgWoDobdrW9ypzRBcCAdWGBSReFZT3LfKSbcXOQw4ldHI1vp89a4V/OfoG7VAtPj1PyAs5GBnkptY9nI1t5wRyholwYHbfdLfJI5xyVWD9lLYksKUR1g0Qkxlgyzd5ElF3xCD26tqmWlbcyEW42IMKN8Gbg1evhENrjx7FOnKBz/ATW5OQNGf6q9veReMc7SXzfOzHvvRd5daRD4Pu4S0vYE+GoEUlVkeNxnLl52seO0jl6DL/ZDIc433knsQcewLzzTqRNfKLzOx1qX/s77Okp9OERjC2jYXfSuXNY58KCTWd2Fmd2Fq+6wRTzqrra5dSF2tWFPjpK7KGHiN57TzjS5zbxleUy//r4NM4m/jyrEmwxDfbETfbETHbEDAxZRl6t+dgWNejVr1zMXnVcPj1X4A9mCxScCyOFMqrCzw118b8N5FEkibLj4gbQY6hv+Kd4y/dZshwWLYey6+Gvtmx47TLB1DNEzn2b/sIh+q1lck71CiW3q2QVuvfA0AOQ3wGqEdYPtcvh9/ruhNQgLByGhUOgmuH3Xvw0uG0wUmBd+XfUQ+ZofDt/3vNuPt/7/TTUzdWdGYHLIB0GdZm+iE6frrIjHuVAVx+j8fiGwScIAlqej0cYUgNAlyRi1xEwb2Ui3GxAhBvhzSoIAvxaDbdYxCsWwy6aQhGvVMKr1/FrtQu3tRooCmomg5LNomQz4eRxDz+MsWvXLT1qy6vVwtAzPo49M4Pa1RVOTLd1K2pX14bz0NwuvrZS4aPHJtf+rUgQU2TSqkpaVUhpClXX42zL2lQ3UUZV2BY18AmDgibJHEiYRBWZP54vUl89RkKReXs2wTuyST7cnSb+Zrk4BgHMHQyHo2dGYfgBiOZg+STU58PQYiTCguhoDrTrWN3a6QABaKthZ/5Q2ApkpMB3oVUI99Oi4HuweJj68ln+PPMIC0YXudokmc4KvtuhZbUouz4nols4Ht/GhDmAL135vU66Te60ZnivPc4HrbN0SzYtX+IptZ9vJvbxDWOMOSl6yeMGIxr741H2xk32J8KusbSqcLrZ4WSrw+lmh/8/e38eJtl91/ejr7MvtVf1vs70rBrtsiTbkrzKBhsDBgKOCbHjYPIjNzy+IU+ee7ORhDwPweTJBQIPSUwgGNu58PMlJiaAw2JLliVbsmztGs0+0/tWXXvV2c/53j9OT8+0pmemZzQjy6Zej45OTfdZvnWq+nzf57N2ohhZkpBIY3JiIXDjBC9J8JL0tRMnW/E89xcyvKWY4f5Clop+42PorkRf3FyBvrjp06fPGx0nTmiGEbYiYykyunRpGX1In9JX/JATPY9Xui7Heh5nHJ9YCBIEXiyY9Xziq9zlD2VMfn56mB8cLN4QF1efXZDE0KtCe4mwtcxys8pic53FTovVRGFRKXDUnOBoZmZbZpkkEm7tnuG0PYWnXH/83Y3g+3ItPnvvO163813L/P36yq4+ffr06XNVbEXGVq4eZyJLEuOmzrip8+7Kzjd7L0445XjMugGaJGHIEu045rm2w7If8sGhIu8fKPTjPV5vZAVyI5AbQRt/E9PA9Ku3EYKwW+PExiJPNLr8767Cs7HFy7kDAIxLIQ9LVd7jHOMt9WcwOsvIzVlkr0VHtTma2c/R7H5eyh7gaHY/J+09RLLKYFBjXzDHRDJPUbRIJJlYkghlhcgARQnRCTCkiKyWIadn0AlY6VU5Lg5wnCMsSlNo3SeB10/cXAt9y02fPn369PmuIgybgIymfe/fw+PYR5b1LcvdvOvz7bbDLZv1fZLEZXbuU/j+Ghl7hmLhfvIOSHNPsh6d5EzyFDExkqzRCWsE6GRwrnhOedPUlyg7NX0FU8rh5e9EsaZ48NZ/i3yFrLIbSd9y06dPnz59vqsRQtBqPUOn+wqqkkFV87jeIuvrf0Gr9QySpFApv52RkQ9SqbwDVc1t7hfT6Ryl55xFkU0UxUaICN9fJwiqBGGNIKgRxy7Z7GEK+TvJ5W/H0C9tmHk1Ot3jOL3TJIlPIqLN81no+gC53G3I8s7WtySJcNxzuM4sYdgginuIJETXBzHNMWRZp7rxZTY2HqHXO4mmlamU38bY2IfISQoPiGXCRpPFpsz6+pdoNp/ednxNK6EqOdxw/sIPYzBknZxexvdDTGOUUukt6HoFJAVFsVEUm5w8RL7WRjrzKO7sl/BFF8+QETIUWhG2GyOxAcoy3PczMNOCzBuvCOmuLDe/+Zu/ec0H/vt//++Ty+Wua1A3k77lpk+fPn2ujhAJcdwjjh3i2EWSNDStiKLYNy0gPY5dur2TNBpPsbLyP3Gcs7ve17KmsKxp2u2XiKLmNZ9bVXNk7P1Y9h4scxLLmiKfvwPb3oskvapWT+xx9uyvMb/w3y97PFk2KRTuplR8C+XyA8iKTbd7nI3ql9moPUqSeJfd91qRZYuxsZ/A91ZoNJ8iijoASJLG9NTPMDDwMFHUpVC4G1XNIoTY3WcYh7Dw9GbF6qk0WHrleXji12Hu6yDJ8I++CYMHb9h7uRI3PKBYlmUmJiZQdpn+t7CwwMmTJ5mZmdndiF9H+uKmT58+fS5Pu/0iZ87+Go3GNxA71ISRJRNNHUVTR7HMw2Tt2zDNMcxMBtPOYVnjl4gBSC0xnrdMr3eSOElbI4gkwnXn6PZO0u2e3BQzF7K/ZNmiXHoriQiJog6KYjM48DCDg99HHDusrv4Ja+t/huvObzuXomTJ5W5FiGhTmMkY+hC6PrC5VJAklU7nKK32czjO2R3fK4CqFsjYM6haAUXJ4DqzdHsnECJNmy/k70ZVc0iSSpx4JLGL484RhvUrXmdFsbHtfej6AKqaRULB91fxgzWiqEsud4SRkR+lVLwf111gYfEzNBpPoapZDGMUXa8gRIQQCXv3/Bz5fFqEMkkCut3jOM4s+fyd2PYlkTyvHSHgzCOp0HnbP73xx78MN0XcrK6uMjQ0tKsB5HI5Xnjhhb646dOnT59X4XVDus0LBfIkKZ0rRCKIo4QkTohjQRwmhH5M6MeIRJAftCgN22SKBpIkEccJ9aUea7NtqgsdTFtleG+BkZkCdv7aujR3Okc5e+43aLdfIQi2V3sWiYyINZBjZOXqHbOTIE/i3k3Wup/cQIxiLtHpnsRxTiHoXnV/TSuTy93K0ND7GR76AKqaveo+Ydig03kFx50jmz1EPnfnNcWBJImP48zS7Z3Ecxdw3QV6zlk6nZcva2ExjBEOHfx3DA6+55LfCSHoOadpNr5JvfEkjcZTQEwmc5BC4W6Gh3+IXPbIjiKwz+W54TE3//bf/luy2at/wc7zL//lv6RcLu96+z59+vT5XiT0Y1bPtlg926I636G60KFbv3zl392g6jK5skm75hGHO9e4yQ+YZIoGgRsTeBGBGyErEvkBi8KQRXHIRrdUeg2fTsPDcV8hf+tXABCJRHv+zdSO/QChU0mFzWZLSdWMMHNtjHwTLbOGmjmLlp9F1ttIUoisech6G1l/DI/H8NrARV04RKLgt0dIggyKJmPYOpY1Rr54mIHhI5TKt6Prg9fs9tK0EuXyg5R58LquqSwbZLOHyGa390ZKkpBu9ziev0wUtomiDqY5Ri53O6Y5dtlxSpJENnOAbOYAExN/N33vu3UF9bkh9LOl+vTp811HHMe4rovjOLiuS6lUuuLfsxCCjY0NZmdn8X2fOI5RVRVN09B1nVwuR6VSIZ/PI19nkUAhBK11l/W5NmuzbdbOtanOdUh26Nhs5dKKweLCziiqjKxIyIqMoqZrzVDQTAUEtKou7aq77XiGrTK0J8/gVA6vG7J6tkV9pce1doqU5JDivsfwm1MY2kHKI0NUxjMUBi2yJZNs2SBTNFCUy1+b0I9p1ztsrH2LWv1rON5zeG2b3sYwUXccy9pPsXyQ1nrE6pnWztclr4NIrVZxLNLCcpvXJT9gcejNwxy4bxgru90yJYQg9GO8XkjgRkiShLyZ6RP6MYEbEcfpNVY1mVzFJFP4ztaIea3EYUJ9tUdz1aGx2sNpBwRuRODFqLpCrmKSK5vkKib5AZPSsI18hc/vu4GbUsTvrrvu4md+5mf4qZ/6KUo3uVvxzaQvbvr0eeNTrVb50pe+RBzHJElCkiSEYYjnefi+T3BR5/HzjIyMcPDgQfbs2YMkSYRhSBAEWzGAjV30tlIUheHhYe645R7K5jjNVZeRfQWmjlQQQiCE2CZ+kkSwcKzO2eerzL24Qa916bjsgsb4wTJD0zkGp3IMTOYwrOtLVI3jhM6GR6fmkRswKQxal1gDfDdifbaN70QYlopmKeimShwmtKourapDa93FdyOyJSOdADcnwdJoBk2/sVWJ3W6AbqnbhFHgRSyfbLJ4okFtqUt9OZ2cd4OsSIzMFLCyGkjQ3vBoVV0C9+ous4spj2WYOFwiDhNqSz1aVQcrp5MfsMgUdEI/xncjoiDBzutkSwbDe/KMHyphZrTLHjeOExCgqDdOSMRxQn25R3Wuw/pcm/W5DrWlLsnVqjNehKLJVMazDE7lsMcFa6VzrLDAvsI+bh+8nSE7DTuJgphW1cWwVaysjqJdeB8Nr8FLGy+x2Fnk/pH72V/af8Pe4264KeLmZ3/2Z/n85z+P7/v8yI/8CD/zMz/Dww8/fEMG/HrSFzd9+rzxWVpa4nd+53euup1pmpimSbPZvOq2iqIwNTWNGReJuhp+C2IPsAI8qUGv66B6BfSgiBJv71Mlch3amZPEikehUKCQK6F2BnDmDYKLwkgkWZAYLoHSwldahFqbRPGwbIvp6WmmpqaoVCrEcby16LrOxMTE3/j7kdcN6dQ9ZEVKrViqBAKSOI1FWjrZ4PiTq1TnO5c9hqxKGLYGQpDEAiFANxU0U0VRJeIwIQoTOnXvmq1bW0gwOJkjP3ChhUMcCXpNn17Tx+kESEBhyKYynqEyniU/YKVjStLYqiQRW7FXvaaPokpkigbZokmmpKNqCo3VHvWVHo0Vh/pKb0cXpGGrlEczFEdssiUzFbOmQujFtDYczjbPcdR7nmPS86za55CQkIWCo3VA2n4BSlKFYW+aQnUMLTDxtB6e2sXVO7hal67RoG3Utu0zbezlX7/p33L//nteF5fbTWu/4Hkef/RHf8SnP/1pHnvsMSYnJ/npn/5pPvaxjzE1NfWaB/560Bc3ffq88XEchzNnziDL8taiaRqGYWwJGtM0tzI4e70ep06d4tSpUywvL6MoCrquo2ka5XKZ6bF9OEsGp765Trdx9ZgXgSBWe8SKi+5XkJARJCRygISMlKhIyHT1JqcGvkXHWqNr1ghUB0lI2JHNTGeGYlzcDP7dORPnYgqFAsPDw4RhuOVu8zyP8kCZwkSBpKAy73Zphh2yhklZ11C9gG6tS7fdZWhgiAN7DvDWw2/F1E2SJEGW5UuyXJe7y7iRy0xh5rsyBqS21GV9vk292kSRVQbHCxSHMuQqJpqh7Oo9ed2QheN1Vk410S2V8niG4pCN1w1pVV3cTmpt0i0VRZVx2gHtqsvSqSaNld5rGn8o+zStdWIpQkgJRmRhRBkSKWaxeILFwgk6Rh010dFiHSXRUIRKVuS5z3yQN43fzdB0gaHpHLmKiSRJzLXneGLpCV5Yf4F22KYTdDjTPEMvvPxYi+4wld4YTWuNur2CkHYnBUrOMHZQYCV/BiElfPyVX+b/+R8+8N0tbi7m3Llz/N7v/R6f/exnWVpa4uGHH+bjH/84H/rQh65r0K8XfXHTp8/fHEI/5tm/muO5v5rfevI1bJWRfQUGJ3NYOZ3aYofqQhchBOOHSkweLjO0N8vpsyepVqvoIsvi0xG1ue1ZM3oOmtOn+Gzuty57/ofGH2LMHuNM7QzLnWXCMEROZFRJJSTEkzwCEVDwCgy5Q8S9GdrBCO2oRFMYhFJCLCUIFET86u7SEVrhObTK11CMKgAiNhD+ECW5Qykskk2yDBYHmRiaQMkrPLXxFMcbxwGYyk3x/Xu+nwfGHmAiN0HFqnB04yhfX/466846D089zINjD6LIr0/zzDAOqXk1BqwBVFkliANerL7IurPOWHaMidwEcTvm+eef58UXX6TXuzBxK1mFjfwGXaNLR+nQkloomsL94/fz1vG3cqR8BCVSSLyEhIRaUGPNX2PdX0fTNKbz00wXphmxR676fnstn/kTG0TOhalTViTsgkG2mMYmiURQW+5SW+pRX+rSbfo0lQ2eMv+ab2mP4kvXX+NmIjvBWHaMRCQ0vAbrzjqdcGdrlqVa3Fq5lYfGH+Ito2/BUAyCJGDQGqSkllk522LpeIO5c2s0isu0BpdZ1ecQWkzJKJFT8hTVEiW9TMWoMJM9gOzobCx0WVhY4fmNF7hDu48f+sSd1/1+roXXtXGmEIIvfOEL/OzP/izNZnNXTyjfSfripk+f732EEJz69hpP/vGZLUvNyEye2981wcxdg6jatU3YQghqS13iUKDqaaBvrmzSDJr8ytO/wqA1yKA9SF7PE4uYJ5ae4JH5RxDX6PtwF/8OUeeOy/5elgJkKUIgEycX3CJ2/jTIPZzWLSB0lMwJzNEvIGvtS44hCQlFUoi4eozKsD3Me6ffy52Dd3LbwG2MZ8cveUJvB22yWhb5MmnNG+4G/+fc/2G2NUveyGMoBnPtOc40z6DJGnkjT9NrcqJxgjAJUVAoyAVacYtY2j6fWJHFqDNKNsxiyiZRErFoLVK1qru2PCBIk792QBEKWTlLUS0ylBnCtE2c2KETdOiFPXphDyd0CJKAnJZjNDvKWGaMQXuQjJbBVm1szSYWMZ2gQ9tvs9hd5FzrHCu9Cyn2JaOErdnIkpxuF6Sf020Dt/HA2AMcLh3Gj33cyMWPfcIk5ET9BF+e/zJu5F4yblVWedPQm3jL2FsYsAbIalmm8lPMFGZQb1JrhPMxaNJlmrreDF43cfPoo4/y6U9/mj/+4z9GVVU+/OEP86lPfWrX+3/yk5/kj//4jzl+/DiWZfHAAw/wH/7Df+DQoUOX3edjH/sYn/nMZy75+ZEjRzh69OhVz9kXN336fO/j9UI+9wtPErgRubLJgz++n5m7rz3F+LWw0F7gi2e+iBCCidwEo5lRZEnGj32COMBSLYpGEUVWeGbtGZ5eeZrnzxqsb5RIjLOYdo37R+/ibZNv497huxgvZSlYaSBrkiQ8v9Dkvz52lr9+ZW3H8xtaTDHXoePICBFiaMuM0uPWOMFEYsVeYTGzSFNv4qouQhJoscawO4wRGyxkFwiU7UG+JaPELZVbuKV8C3W3zuPzj7MRbjBujvP3jvw9fvzIj6MpGu2gzaPzj/IXs3/Bk8tPEl+mQN4lvEp4GLFBNsziqi6O4lxWlADsy+xjn7WPklxC7+ksry4zl8yxbq3TVbsk8oWYFTVRyUQZMmEGgaCrdelpPRJp59T6G8VbRt/CR498lAfHH9wSg0IIwigEGfSrNEt1QodvrnwTL/aQJImCXmDYHmY0O4qlWlfcF9LvTa1WY3l5mV6vtyVMJElicHCQvXv3XvVvpNVq8dJLL/HCCy/wjne8g9tuu233F+A1clPFzfz8PL//+7/P7//+7zM7O8vb3vY2Pv7xj/MTP/ETWNbVL+7FvO997+PDH/4w9913H1EU8a/+1b/ipZde4pVXXiGTebUJNqXVauG6F5RrFEXceeedfOITn+AXf/EXr3rOvrjp0+dvBi9/bQmvG3LXeyZRb3AG0M2mE3TQZA1TNa+67en1Lv/jqTn8KOHH7hmnZGv8k8+/wEtLrR23H8upfOJuk2zcptvtUiwWKVVKxEaMu+FyZn6F5eUV3MBh3V6lbq3QNBu09NbW5C+EAomKpGyPX5JEOjG+2opyuHCYt46/leXqMisbKySNhKyfRUIikANUoVL0i4znxskMZ6AI+4b3cdfUXZimied5tHotTvunea7xHHWvvmVBedPwm3jfnvcxld8e9ymEoF6vb93zzYyJJzyEEJTNMpIkEUXRVnxTp9dhvj7PUmuJ5dYy59bP4fZctERDSzQs2eL2w7czkBug1+6x3l2nETdoJS06ooMbufSCHr7wkYSElmjktBxTpSluG7uNW4ZvIepEVKtV6vU63W6XbrdLr9cjSRKy2SzlcplyuYxhGPR6PXq9Hq7rMjQ0xMGDB9m3bx+mabK+vs6ZM2dYW1sjDEPiOCaKIjRNY3x8nImJCYrFIs1mk3q9viVoVlZW8P3Lx5wNDQ3x4IMPctttt6EoCkIIOp0O9XqdarXKsWPHOHv2QkuMQ4cO8ZM/+ZNX/Y7eKG6KuPmDP/gDPv3pT/Poo48yPDzMRz/6UT7+8Y+zf/+NSwWrVqsMDQ3x2GOP8fa3v31X+3zxi1/kx37sxzh37hzT01cvM90XN336fO/hui71ep3h4WFUtd8POIwT/vLoKmGcMJwzabkh355r8OcvrrDa9rA0hX/6fQdRZImFustiw2G+ni5OsN3KIiEwiNCkiACJUKgkm/VfbcXjYFkm4BVW7CcIrSWkTWGTC3JM9iaZ6E2QCy/tM5jJZJianGKmOMHQ4BCVgQpmzkYkgqjqIBsK+lQe6QamVF8rGxsbnDx5kmeffZaNjY1d72fbNq7rcjPKyKmqShRdW9r7xSiKwuDgIIVCAUhFYBzHzM3NbR3Xtm10Xafb7e54runpae68806OHDmCaZoIIWg0Griuy/j4+HWP7WrcFHGj6zof+MAH+PjHP84P/MAPXHehqytx+vRpDhw4wEsvvbRrU9cP/dAP4fs+f/VXf7Wr7fvipk+fNxZxHLO+vs7i4iLdbpeJiQmmpqYwjO1F1s6b1JvNJo7j4DgOvV6P5eVlZmdnSZIE0zQ5fPgwt956KxMTE5im+V2ZEXSzqPcC/vH//RyPn9r9RH0t6AoMZWVGcyoTOYMBNcZsbGBXNyjHGkpOY/jWSfZPzJDtqnSfXCGuXT64VtJktPEsatkkavgknQB1wELOashGao2TdIXMvcOoFYvECXGP1YmqLlHdpRGHfMNr8HKvyxnHp+aFjNBgn9YiqyYoirKVUaZp2tai6zqyLNPr9eh0OnS7XZLkIreWqpLL5SgUCuTzefL5PHEc4zgOzWaTtbU1PC99XxdnrGWzWSqVCqVSKS0pUChQtHLoscqpM6c5vXiWpeoKYRhe1/VXVRVZlrfKDJz/93kBc/F7uBZs26ZYLLJnzx7uvfdeyuUyjuNw9uzZraXZbDI5OcnHP/7x6zrHbrgp4mZ9fX3XvaWuByEEH/zgB2k0Gjz++OO72mdlZYXJyUn+4A/+4LJZWr7vbzPDtdttJicn++KmT5+biOd5tFotms0mzWaTTqezdWM9f8uJ45i1tTWWl5cvuZnLssz4+DjT09OEYcjy8jKrq6tXvOnrun5JcT9d19MJpFhkcnKSmZkZxsbGth7OfN9nY2ODVqu1NQmpqookSSRJsjVJWJbF5OTkTXmoe72JE8GnHjvDo8fXGcobTJRsxosWYwWdghyiRx1EN0D73xuYwsApGgS3D+BoErmKRWW6QCGjI0vwwkKLb57e4JvHq7yw0cWPLz95lhGMEjMqxYySMCIlDBOTVVIRI0RCHCUIBFJGIQliZB80FDShoKOioaAIOa3XgrS1FrKEP6ZQXdnguAh4QSicEjorwkJw6WcmIRiR24zLLcbkNiXJZTca2FB1/Gj7dywSEnVhU5JctItidmRkJCDm2gWFLqnMjEwzPDyMkCXiMCKRBB4BXuAhyfKWuO/1ejiOs+tjS4AmqSBLIEsIxFZwsBDiqgJI0zRyuRz1+vbGoLIsMz09zUc+8pGb9ndy0wOKP/e5z/GpT32Kc+fO8eSTTzI9Pc1/+k//ib179/LBD37wugb9cz/3c/z5n/85TzzxBBMTE7va55Of/CS/+qu/yvLyMrq+cyDWL/7iL/Lv/t2/u+TnfXHTp88OeC2SU1/md7/0DAPUGSuajI6PM7L3NoyJOyA/xsWzQLfbZWVlZWtpNBo0m82tp9bdYhgG4+PjZLNZ5ufnL1uU73zdmkwmg23b2LZNqVTi4MGDlEol5ufnOXr0KMePH6fT2Tk91jAMRkZGtsTXbhkcHOSBBx7g9ttv/650fQkh6PV6NJtNWq0WrVaLRqNBrVajVqvRal0ao2NhMBTnGUoKDCd5CiKDnrfI3jqILMsk3RDvWI0oiGjgcE7yOCeFzBOzDKwJmQ2h0+PygbIGEQXJJSsFSDtkl4kdfioBqhSjE6NtruvCZjEu4L7qXHkpYFKL2YNMKdT4llA48aojZoEZBHsUwYwlsTcDRQP0ukDrSiToyGgkyATENHBZlzy+RsI3hYGHgknMQ5LDD0sS0yJHUWSQkOhKLk3JoSn1aEoOXcklkCICoq11IglyWAyKIQaDMreIAiqXiROTUmuVNprB2JNHJJCEEb4U0Wu06aw28ZSIZEBDi2WkJR/NlTBQMYSGhoJ0PjJbkci8aZjs28ZRKxaSnFb2bjQa1Ov1S5ZWq7XN1TY0OMjeqb3sO7Sf6enpS6ytN5qbKm7+63/9r/ybf/Nv+Pmf/3n+/b//97z88svMzMzw+7//+3zmM5/h0UcfveYBf+ITn+CLX/wiX/va19i7d++u9hFCcPDgQX7wB3+QX//1X7/sdn3LTZ8+myQJ1M/A8nOw/grEr7KCrL4Ic9+gmuT5z/y9V+0sUrEjN8ibCuuixEqYpRNdfpK3LGvLapLP51GU7QXWJEmiUqkwMTHBwMDAtqe9RqPBuXPnmJ+fxzRNRkdGGC1nGLAlZEUFSQFZAUlOX2smGNvjOoIgoN1u02w2qdVqnDt3jrNnz15i3TEMAyEEQRCgaRrZbHbLinN+Xa1Wt/bL5XLceeedxHG8FRTqum7az2hz+2KxyPDwMENDQwwPD5PNZllfX2d+fp65uTnm5+eJoojx8XEmJyeZmJhgfHwc07x8APHRrkszjHATQSwEqiRRCyNebDusuB6TMpSSiJOOx3IQMRj6jHhd8u0mWm2dTqt11VgN0zQZGBggSRJWV1ev/BQvQNm0T4TSlbOhQlRCq4JrlKjHBlVPpurLNAMJcaUUqOvAUOCuYYMHZkp8351T3DI5uPW7xIvwTzc58cIajy41+FbP4zk/wN1BVA0ioQIbCK7mJDIUectqZSky7xsr8qMzA7xpNI+sq0R1j3C5C4lAslSUrI6S11GHbUTF5NGzG/zPZ5f46okqcSLIKjJ7VZUZSeFBWeOtGQs1iIl3aO9xORIEZ0noIjAtjeItZbITebJlk1zdJ3i5hn/2IkErgZzRkBRp2wOMPpEl85ZR9LEsXq1HfbFKfXaNbFVBX4nIPjRO8QMzux7Xa+GmipsjR47wy7/8y/zIj/wIuVyOF154gZmZGV5++WXe+c53XlPQlRCCT3ziE/yv//W/+OpXv8qBAwd2ve9Xv/pV3vWud11TfA70Y276fA+SJOBsQG8Dgh4EHXAb0Ktd+PnGSVh5AfxL6568Gr9yC7OD72VFHmN5fYOVpn8FEZOKnlHWGWWdARoUcxkKI3sxBqYh6ILbBK8FXhNCF/RMKkSMXFoJT9/MjBQxJPHmOgG3Dt016K6nS7LzFLNOhSplLE3BzpdR8sNIhXGUyl70kVsQ5RnOLW9w5swZzpw5c1mLznkUSfD2N93C3W//ga17hOd5PPPMMzz11FNX3X8nZFneVbxDoVCgVCptZc2cf10sFnn3c2c452+KEyHYlR9lE0kkWIGPEYUosowqy5iyzKQC78ga7C8VODhYYaZU2NrnvDtwcXGRxcVFFhYW6Ha7lz2HruuUSiVKpVKagbU59vP/3sna5QYx5zZ6nKl2WW5eWr9FliQkKRXCEulbFgISIej6ER0vouOFdLyI4bzJuw8P8eaZMoa6++y4IEo4udbhhfkGL56p88Jyi5N15xJnkipLaGqMai4j22fAOgPmPIaiULaKEFtstFW6joGIs4goR17eQ1k5gK1lEEDLCWg4IW4YoysyhioTRAkd/4LolCV4dU/RvKny/ttGef8tQxwqZajIEutzbV5Za9PTJB6UdfQgoaXAt6WYr83VeWKpSS3cWXSqssRIwWTC1jnsCG5thNyGSu4ahKaPYIWE6lSW9/z0neTMy/fbulHcVHFjWRbHjx9nenp6m7g5deoUd9xxx7Y07avxj/7RP+IP/uAP+JM/+ZNttW0KhcJWWvm/+Bf/gqWlJT772c9u2/cjH/kIp06d4qmnnrqW4ffFTZ/vTpx6KlDq56B+Fprz0F6C1gK0lyHe5ROdasLIHTBy+wVRcX6SzI3BgfdCZd8lu3U6HVYW51k+c5ROq86QLTFqhQxrPYygkY5n9cV0PDcTPUtqh4+3xNBXuZ+v8sCuD6EQMcwGLiZtsuTocTdH2ccsj/EWTnHhKTRrKIxNTFMZGt6apGu1Gmtra9i2TSaTIZvNYtv2VtBmu91mcXGR9fV12u321j1RkiRM0ySfz1MqlbYyas5bly6uuHsxLa1FzaxxanAMSSRUek2soEXD8GlYAZHUQ08KSPoeEnMfA5JNUYpoaTIbskpVLuIrJRIlD9KrBIYQKNEqqn8KNVxiUOkxKHfxggZ+7CIkhYS0onLerJC1ZpD0KfL2Xu4sTLHX0JGTBNs0mMrlGDV1NHn3E2Q1CPl2q8eCF1ANIppRjClLFFSVd5RzvClvI0sSQghe7ro8UuvgJQmKJOHEIeudM8jeSeTgLKNWiVsHbuXWyq1M56eRkGgHbTbcDapulapTpebWqLpV6l6djJZh2B5myB5iODPMeGackewImqzhBBFPnDvDmfZLrHgnWXXnmO/MsdxdvubCjEJIJP4oiTeMSCxEbJKEFaL2HSBSQTCQ1flb90zwE/dOMFm2OVft8ZdzNb45W+fFkzW6znZhLxQJYasIQ0YKE9RQoAQJYbRdktm6wkjexAtjvCihHURpXNMOb0ECDlYyHBrIMJ23mC6YjNo68mwbcayBF8a8pAueVxKOxRFrQbR1Jf7oH76V+/aUr+m6XA833XLzyU9+kg9+8IPbxM1v/uZv8pnPfIZnnnlm18e6XBbDpz/9aT72sY8BadG+2dlZvvrVr279vtVqMTo6ym/8xm/wD/7BP7iW4ffFTZ83FkkMZx8FvwOZIcgOQWYQkgjmvg7nHofZJ6B67CoHksAup5O/ngWrCHYFMgNgD0BxCsbuhsHDoNzEeBGnDmsvw8qLqegyC+liFcEsgmZB6KTv12+n66CXjl9WUheTtPnaKkF2OL0m2eH0+qiXxm4888wzPP/cs7i9Dq7jEsdRGpyaCCKRurqGqLKfOfYxxxRLaMSg6IjMMFJpOr0+pWlEdpiXnn+Gry/COuUdg1EBbENlcKCCkSlsua86nQ5ra2tXrCNyPZzKn+LFyouv+TgSEraeJ6PlsfU8sqSz0D5NGF27JQogkSwi4wChcZDQOADIyHGDPC0supSyB9k38ADjls24qXNnzua2rMW86/PfZ1/hkeoyi56DJGLYspNsn44KikJeU3GjkIa3QdZZRogmMXWU4Byy2Dm2S1cs4iQiFteWdSQhU7GHUSVYvaii8MWUzTK3Dt7DwcrdvH/yzWiKRr1XZ35tnsXaIsvNZVZ6G6wFNaryKoG6s7VLElkU5e1MZ95NbNlsxDGGrFDMZegYFkd7m98jIZDrAfKqg1zzkdz4ivaVJKtiD9sc3lNCLunUkoR9lsEZ1+dEz0tNX16M5MXIvQipGSA3fGTn2rsLZAyF6XKGX/jBW3hg38A173+t3FRx8+lPf5p//a//Nb/6q7/Kxz/+cX73d3+XM2fO8MlPfpLf/d3f5cMf/vBrGvzNpi9u+rwhCBx4/v8LT/5naJzb3T6FKSjvgfIMFKehMAmFcciPQ250x4n/bzpxHBP3aujNc6loMgupyDILaZzO5ejVCJ75A1af+VNWWh4NijQosEGJOsXLih5IXVCDg4MMDAxgWRaWZW01+pQkCc/zcF0X13VxHAfP87Z+dv71xbflZWuZ+fx82jxU0SjkCwyVhtAcjeZsE8mV6GgdmkaTht4glmM0WUOX03RmB4eO6JBcJmtHkzSm9CkG5VG8yKJNHlkvo6hZbDnBIiaIQpo0CcQaTrxEw58nTq4u4hI5Q2C9GVvciu1XCaRZ/OQUUlK76r67QU00SkGFAbdEIAc0jSZNvUksX5ioZWGiCRstSRdd2CjYxASEcpeYLqHUwVO6JNtihyQy9l4ymVvQzT0YxjimOcFiaHDaDdDDgDvbG9zeWEVbXUK6TOshV3GpmTV6ao9QDgnlkBV7BVd1N9+Dih3ZyEJGEQqZMIOZFEi0MYZKd6FWpjGKJe4YynN3wcJAo9qJ6LQjOk6AZah803V5rNHADR3WLJvoMg8wQ7rKu8p5vt3qsewHuJv+LwkQfozcDJB7EaOxRNwLcXohXhgj4nS7pKCTlA2Soo7IqIzlDJ598HukQjHA7/zO7/BLv/RLLCykJujx8XF+8Rd/8abmt98o+uKmz03n2c+m1pPKPijvAyObipn1Y6nrZvUleOWL4Gze4K0SDByCXjVdzsfFDB2BPQ/Bnrela/vmm337vAohoHYGmrOp6605T1hfoLq2wka9RSggQSZGxsJjhCoVGqjFCZh+EKYfgKkHoDgJ6u4ySYQQ+L6/VXFW07TLptYGQcDzzz/P6dOnaTQaNBqNHYOGBQJf9gmUgEAOCJSAUA7JBTmKQRH5CmJtxzEiaOmpu6xu1akbdWRkbJHBJouKzqIyhyNdzmohYcYmspCRN1O7L/7d1nkkgSTJIARGbJCJM2SSDIZvUAyKFILC1r6SLINlEzkdemoHRSiYkYlyuayjHd6Tp3j01LQNQy4cYKU0jqcZ+OqFeJKM7zLUaVB0t7sRe7pBLVOgli3g2FkOVko8MDzAHZUiZRl8z9uqg1Nr1PhG4xt8I3qSptK40qDIRBkCOSBULlihZGT26nvZl+xjsF0maUoEfkBP7TGbnyW0BXvs+zgy/hBjExMsKAbtRPB3xyqMm+lDkBACLxEYskQnivmrWps/Wq3ztcaln9mEqWHLCk4S48UCJ0lw44R9tsETb75lV9f3RvC69Zba2NggSZKbWv/mRtMXN31uKkLAr0yDf1EWgl1JA3zFq56ci1Pw1k/A3T91If4F0qDbOASz//18QxNHqdVt/RVYO7q5vAyN2Z23V00w8ptWIyt1PcZB+lnHIU5xnDN3/gSnC0OcaZ7hdPM0y71lCnqBilVhwBqgYlYom2USEtzIxY1cJCTGsmNM5ibJa3leWHyBlxZeYnZtlmaviZqo6OjYkk1JLZGRMvTcHr7vE0vxljUhlEOElIqIrMiSk3PIEsQiIBYBSiyjRSrEKlKiI11FEAkE69Y6c9k5Vu0VconBiD/CQG+YkjOIKlR0XWNoaJhKpUK9XmdlZYUoishms+RyOdbW1rYCsffv388P/dAPUSgU8H0/tXT1esh+g2zcxHSWkJeeIajNsdSOqLvQ8GViFDLZDPrB9yBnB5FWnifprCKKe5GGj2AogmxQxXCWob1EjQpfXVGoN69eO8ZSHKKshJSJUdWIGdtgZmCMQ4NjZGbeBrmRK+6fiIRjtWN0wg5hr0bv8f/IXPMsJ4wSrxgaS+ruXJxqopINs7T0JhdpQwp+gQPtA0x3JygrPmUtoJgxCNBohzKdxKDjCyzT4ODBgxw+chvx0AhfazlEiUCRJN5SzHBb1iJIAo5uHGXQGmQ8N562zhAC43Ws/fS6dgX/bqMvbvrcVCIf/vQfp0/79TMXrDOQxtKM3A7Dt8Hkm+Hg+25u/Euf14X59jy/9fxv8f497+fB8QfRApfTJ/+UJ879H77ZPEEn6BAjiJGIJIiRSCSISWu4JBKESGxcQ4bPjWLcKDMom2QEhLHHQtRhNQm3TZA7IkAVKmqioggFRSioiYqVSGRjmXwsMRrBaBSRkdd5yQ54xjJoyTJHvIC7PbjDjXi3X0ebfDMc/gAc/gBxcQ++72PbNgCh77L8rT9FOv3XTC7/ZdraQdFTK5hI0my6Vz803AAEMMsEVSo4mHikVjcJMPEY07qMTe0lowrorKSxZs257QfRbHjH/xve/A/Th5vIg9LenbPc6ufgf/yt9J5xEVVF5qymUY4T7MiiJYqsSWXmlCyn7C7H7TZnzYjookPe64YUQ5PHsgmhnE7vZmQy05lhujONFVu4iktbb9PVunTVLo7qbLnJspHJNCYPlg7z7vv+LqN7jvD1ha/wy8/8GoubcUhl2eS+gdu5dfJt3DV0F3cP3X1DrvvVuOHi5p577uErX/kKpVJpVwN46KGH+PznP39Te0xcL31x0+d1xW2mN73sCOSGv9Oj6XMT+O0Xfpvfev63AMhpOTJ6htXe6nUdayBO2BcE7A9C9ltDTAzeRmfuCWpRjw1FYUNRqCsyKmAlCZYQREgsaQqLqkpNUTgYhNzj+dzj+dzl++hC0JZlaorMSV1nQVO3thnaIU7El+C0pnPU0AllBdsexM6N4WcHaRtZrOww5eJejNw4z9Vf5omFr3G0fuyas4gAJsKQn2m2+eFuDw3SyX/mnTD1Vlh+Fl76n2k5g92iGmnguZ5JXcOZgTRof+Hp7dZUAFlLywtIKgwchKHDUJpOLW/N+VSQ6Jk0IL8wkf5u4FD6gFLac6lIaS3Byb9I60gtfAs2jl86PqucupuLU2msnF2G2cfh5F+m2X9WBd75z9JMyOY8eO3UsufWoHry0nIImk0YOpy1C5wb2s/BMGRm9TjEAU1Z5v+Xy/J/53NULxLOeiIRyLv7rKzIYrI3zMnCLABmLBNJCdFFxpp7PJ3PfPzJ1yXm74aLG1mWeeSRRyiXd+fzf+CBB3jxxReZmXl9CvtcC28UcZN4EVHVJdxwiaoO0YaLpKR9VPSJLNpYFvk71Mk48SKihk/c8Igb3oXXvRC1aKAOZ9CGbbQhG6VsIl1D6qcQYle9fkQiQJAWlOrT5w3MifoJ/uTMn/CX5/6SdXcdAEMxuG/kPh4af4jRzCiqrKJICoqsoEgKsiRvrc8vY5kxinEMT/4WPP3f0hpB58mOwF1/B27/8dS9FXkQehC5qYDurqXxWt219OfZoTTIPDecZqQtPQtLz6SuMxGDlkkn/szg5jJwUVba4ObrkXRCV65evyRMQnpBj07YoRt0WZv/OieXvsEJArwk5C6txL2V2xicfIDn3WWeWXuGr8x9hYafxpuMCIX3dFoc9n1u8QNmwpAtm6Zdgcm3pDFMViG1lMx/E07/dfp7xYA7PgT3/1+p8Ljc/WXlxdRtOP8kHP2TS8WOaqVB5pqdXmPV2FzMdCntgeFb04xDq5jG0628AEvfhsVvweK30wzB6xB5u0az0pINkpRae8QVMpzsAdj7NsLDP8hfqRF/eOYLvFQ7QYJAAcaTiPHNdhiDkmAkM4HtSZzrxHw7CXnZ8vGUC8ff09nDHbU7UIRCzaxRM2o0jSZ7PItP/fwX4HVwT90UcSNt1hrYDZIkcerUqb64uQjvRB3npQ2iDZdowyXpXiVFUSIVEOM59IksStFAUmUkRUbSZFCktFuuBCJIEEGMCGKSzdfEIq0GpUhIMiDLmyJEkLgxiRuReBHCjdLXbkTc8okaPsK7ho6zqow2ZKEN2ajDGdSKifBi4m5A3AlIuuG2tQhiJF1BNhUkQ91cK8imiqRIxJ2AqOkTN31IBErBQC2bKCUTddBCG8mgjWZQ8volIkkIQdIJCVd7hGs9JEVGn8qhjWaQlO/+nkB93tgkIuGF6gu4kcs9Q/dgqlfIxroaTh2++SloLsCRH4b9770xLszQSyfEi2O8XgtCpMJp8ekLwfPPfg5e+EMuO8lX9sPtH8I5/AH+Z/Vpfv+FT1GNt9dH04Vgb5RQjBOycUgmScglgnIccyAMORgEjEUx0p1/B97zb7diW0SYEHcCuq0W1dY6oRIhqTJCl0CTMU2TPZUZ5CSAU38FL34+tZpcpkDkDUPW0s8vCnYUJEIoCElHEq/ucZXes68JzSYUHs28Siuv0sxrdHIqiSLhJtCKJQZUgXoZDagoNoYxSs+r8Wizx+NdlXuMMj/u3Utc7+GHMYGSIRAqfpSQKw3wgx/4QGrdsivXVFzyWrnh4mZubu5qm1zCxMTEVifUNxLfKXHT/uoC7b+Y3fYzOaehDthogxZqxUJECcFih2CxS9LZfZntm4Fsq6mgKBkoxXQtZzWiuk+01iNccwirLkQ33t+92/FpIxm0kQxCCKI1h3C1R+JcKswkTUafzKFP59NlNIOc1a/JKiSihHA9PUe42iNad1FyOtpEFn0ihzZi9wVUn9cFIQRJL0REAtlWkTT5O9P5PPTgP99/aazJefa8DTqrqdUjP5paNdZf2R4jI8n4JHzZtnnZ0Dmm6xw3dHq7sAJkMJmR9rAnGsONPGrJOnV5lZrq0VUu/4A25Q/xA+138l7/QYqlMuqAglZS0EoSqr6G8vS/R1p8+lqvxnbMYlqReweEVYLifuJAJ/Cn6XTeSuhfaDskST6yCXLORi7k0IqgZlxUvYYiL9BRzlJnnma8TCxCEiAWMQkxiQgRBCTSpYHIcmihBgXkMIMS2ciRhRTryImKLEOQW8bJzJEoOwcxS4lgZN1nesEl4+5gMZI1+IX1m2rB6QcUX4HvlLgJFjq4x+upkBlIF9m8/JNY3PYJFrsEix3CpS5xL4RIIOIEESabawFCpJYQQ0lvcrqCpKcWHoRI3Tvx5vp8TQNTRbZetZgqcl7fEjOycXVhKhJBXPdSobOeCp644afHy2ooOR0lqyHndJSsjpzTkA2FxI8RfpyuvZjEjxB+jAgT5JyOWjBQSgaSLBGdd4vVvS1xEVUdLttoVwJ1wEIbthFhgj/X2dkSJZGOK6+j5I10XbjwWiSCcCUVMuFKj6jqXloT/WJUCX00uyV29Mkc6oB1TS67a0EIAUnfbXc5Ei8iWOhsLVHVTQV70UhFe9FIXxfT15KpXJNAEFFCVPeI1h3Cavq9T/zUeirC85bUhCSMIUxAk5H1TSuloaR/p5uvZUtFzmhbi5LRkG2VxI2I6h5x3UvPVfeIaul620OFKiHbWnocO93XC2KavYiWG7HRDmj0IorTOUb3FZEk8LohYZhQGDAZ2pOnMpbFyuvIF31fRZQQrvYIFlP3mHmgiFqxtl+IT38gjTGZfiDNHOuspcHB9/40TL350gvnd+D4n6cWk7OPpVaM7DB837+HvW+HpWdIqsdZJGRWkegYWbpWgbbv0FyrsrK+yGnvLAv6KtFV+lmZSYIpQN60fMgCOrKEvzn5monM93clfry7xB1+sC33SwiNTvxjJCKHIb+MIb+ILDnEoogX34eTvJ2C+ll0+RSJMHDi9xCLArp8iiA5SFf9SRS9iaxpSBooSgNZcRFqAW9jlLizw9hfZaQRJERmDT+7hJ9dxC2dxCkfRyi7e/DVeyNYjQNYzXTRg2EU1UVJqhA6xGKQmApc9M4FCUF2iUhvo4RZlCBPaC9Rn/kivcrpzY0kSuEhpnoHKXkdlN7pNN5Iz8A/fn5XY7te+uLmCrxRYm76XD8iSlJBtSk8kEEbTq042pCFpF0QZiIRRFWHYK6DP9cmmG8T1dzLi6MrIJkq2qi9eR6buBVsWdp2ElCSrqAO20iqlIoc+cJ66/X5hjmb/XN2+rcI4i3XYeJEJG5I4qbnS4Xc5nsfsdGGM9ccB/VGRwgBUULipeJhJxIvvkjMtFMxeg13NklXNsWOkYrrooGyuZY0mdrKE3TaLxH1ukSuS+w7CClCCXJoXhnVL6N6ZZTIItK6xHqHWG8T6x0SxcVsz2DVDyGLG9N/R4g0fFe+BkEWJIJeIvDFZn8m0uX8ayGBbqtMHCiitgPC1V7q3r4IddDCPFzGPFzGmM4jdeZTcaJZO52SJBFpATiJ9Dvpx0QNj7jhE210CRc2COsQ1X2UvIE2mrqd9dEM6oBFMN/BeXkD70RjS9Cp0gJCfYml3HGWlReYVSOyScJgFDNY3MdQfoKh6hkytTNIIkZoNt7oO2kGw8TVr/F4Zo0Xx2wOFKCsJnQTiSCCcpKQ1wWyJKM5o2i9abTWNFr1LtRohCTTplqQmC7swSzbRH5I2HwGjw387Ck65nOEWg3NL6G6A2heGaMzTX7lLSjRq9yAsoQ+nkXfm8eYLiBGPXrRcXrtU3Q7p+g5p3GCsyTi0nR0xc+Tqd2GXT+C6ueRdRPVyqDYNqpto+ay6NkSRq6y+WCZPmBKmkxtqcvGYhdno4mzXiWrdZnMbZAJGsSdhNgziD2TyLOJgxxRkKUjuSzrVezMBtLE1+kNP7c1lkLzQW774f/GbHuWs/VTdGOXDx360K6/k9dKX9xcgb646SMSkcYAtX3iVpCu2wFxa3Pd9gEpFQujGbTRLNpIBqVwaZwPpBNNVPMIFzcn16Uu4VIXEX5nXHaSJqMOp0Ln4slCtq8+scadgGC5iyRLm9YsA8m4NqvGbhFCkDjRNstEXPeIGh5JL9y07EUkfnzJJLsblJKRuiMn82ijdhpXthnPFTX89PNueDu6Ml/N2qH/QXP6y9fzNreQJYuCdh8l+QEKyf2oYRnhp4J19Vgdv+FhSBK6DDoQAb0YnE1R4iTQSwSxqWIOW0RhQnvdRfLjdB9JQpPStWXIDFUsMgpobgS7eI87ITSZMK+jqzKsO9sFoy5jHighKhYbCx26dY/Qiwn9mCSMEQmoCGxZwpIlbBm0a/weqdISZe3/QyxK+EkBVT5JVtnuBuvEAxx338Wp4J345h7MrIZhq1hWgu7OMz9v4gQWqtWgOPMY5f2PIhtXr2FzMTXPYDGO0eQEE4UCOkXdQ1GubD0CkCWDivEeBpUPoCeDaOUcxkQZNzxHrfZVarWv0eke3XFfSdKw7X1Y5n4s4zC2eh9Kc5zEi4k1hVhXkDUFRZUI/RinHeB2AjRDpTKeoTSSoTrf4czzVeZfruG0d7b6ZMsGhq3hCZcl4zQbQ3Ms22dYCudpRc0L7wWZW9Q878z6zGTrPN4q8iedYCtTLqNlePInn7xpbtK+uLkCfXHT5/VAxKnFKKq5Wy5BkTrH09cidRciRNrETpD+T3DRzzZdT5qMbKvI1nnXQ7qIhAvxT5uxQOG6A9HOf9JK8cKTsTaaRRu2iVsXuT8XO8StS29+ki5f5LrbXOd1UOQLgewXuWJEGG8FuSdhAnGSPr0nF9ykJGLLPXk5/st+neN5ha4q4ajgKhJmAsVQUAwFo55g0k2YdBP2+TA2kN0UM+mi5HaXmpoEcSp0NoVP3PLToPbNn4kgobP3aXqlF1HNDIplo2ayyKZOGNbwvRU8fxXfXyGKemhaEV2voGlldK2MJGs0Gk8RBOvbzpvN3kIudyuZzAFay4MsvWKwNreGoI2id8kNBGQHI1Sjh6IlFHPvYnr/w+QHMluTh+dtsHK6xbnnfISQGJjIMjiZY3gmj3JRDFgSxEQ1j7jmphawOEk/j0hAkpCECUEvYv7lDZpVl3YsaMapoDqPKsGwJjGkygypEuZ1WAcTBH4i8BPoJdCJBe1E0I1FKoAUyCsSA4pMVoaE55m2/vX2Y0gqvcK91NV9rKjjLEc5/KBK5JvEXo7IzxN5eWI/D0LCHjxB5fBj2CPPIkmb1h9lGD36IEHzdmK5wbLyEnPiJN9yZ+nGPoNqwrAmOGDGHDASLuf9jQRUI4mzvsIJT2Y1lMkrgrIiGBcZ7s2qZMzqrq5N4I+hxfswlL2EvTEaC4NsnMsSBa89hqWrNzlTeY7l0klMS8fWbDJaBr8XUe818WUHV+tSt1cQ0qUPZXaQx1ddYvlC4HVBSfASCV9I5PU8+4r7mCnM8M/u/2dY6s6WvNdKX9xcgb646fO9jIgFUd3dFDtOGje00iVu7LKZo5S6HkAibvsI79qb6V0rcl5HLZtbi1IyUfI6f7e2zhOue/UDbLLX0nmolOPBYpaDGZMxQ6Og3hyr0+W4XKkDIRI63VeobTzKRu1R2u0XuZ6UYdMcZ3TkbxFGTer1b+A4aRyEomSxrElMYxRVy2PoQ5jWJKY5gROPM1icwtKvbrlLEsFTXzzDi48solsKpZEMuqWmlpnN71C2ZGBlNZJ1hwEJMrKEldfJVUw0U0W2QnpqiypVArXLmtRlPWrTDNv0gg6m4jFqxwzaEYrskeCQCAcJjyiBWKiYikZWM7FVBV0EyFIMwiVWJGJVI05cwrB+lXejIJFFcCHlu1h8MxMTH2Fw4L3Ichrz6AYxCw2H+ZrD2VqLE40TdJKzNOOzbIRnyUg2t+kFskmerlciUdsomQ3momVkvcxbRx+k0pxkbmGZhqhTE2s8K76BL7uAYI+e8EA24ogZo0upSJSl1Cp3wlN4xVM47il0EwlJyJSdEQZ7k5ScUUAQySGe2qORWaVj1hgIxpjxb2V/eDsDYhiRQBwJNF3GzutYeR2/F3F67RzHkueZHX6RxczJXdchGtZHmRGHGa7PUO6Oke1UkFwNzwlwtA4do07b3EAtCO45dCvf/963UjErr8vf2esiboIgYH19fas09nmmpqau53CvG31x0+dvIokbEa70CFa6m4IntfgoeR39fBD0RBZtPItsXAh037JqtIMt112yuRYCZP18EPtmILueBrbL5/+tKWnQs7IZY6TIF+KPNBm1ZGyLkbqYv95oUQsjsopCTlWwFRknTmiEERthxLwbcM71mXV9zjj+jmFUtiIzYxncnbe5O2dzd95mxjZuWMl4J05oRekYM4q86xiYINig0XyaXvcUvV4aY+F5S6hKDk0voalFVK2ItrlEUZe1tf9NFLVfdaTdpQr7sU47HEXR91LJjzNSGiZrlrCtUUxrAkkZZbVZZ6F6hqXaPLXOOgptdKmNLKUurTTJSQFZIxYaYazi+KDKDUpGlZK5gS2vo0i7F6SvFVUtYFlTmOYoceQQhBsEQY0gqHE+sE5RMoyM/AgT4z+FbR9kueVybKXD0+dqPH2uzsvLbeIrJQtcgemKzTsODvLuw0M8tH8AddNa1vJb/M4zv8fnT/8hnnAZjiaYah7BaheJpACh+HhygK96BLqDW2xQU9bwxLVdu4yWIaNmsDSLgl5gJDNCRsvw7bVvs9BZ2Lbt3UN3897p92KrNk7k0At7CAR5PU9ez5PTcxwuH2Yks3PLiF7L59vPrPLH315kdr1LSyQEWYXP/twD7B/KXtf1u1Zuqrg5deoUP/3TP803vvGNbT8//8QSX6Yz6huFvrjp0+e7h0Yv4OnZOk+eqfH10xuc2+hxy2ietx0Y4Kcf2stANi2L345inmp2+Xqjy1OtLgteQD3c+V4kA1OWzj7LZNzUGNBVKppKTlVoRzGNMKIRxnTiGD8RBEmCIknkVYW8qhAlgjOOz2nXY9HbXh8lq8i8KZ/hH04O8s5yDkmSiBJBPYyohhHrfkgtjDBlmZKmUNZU9lgG1mXKCHhhzKm1Lq+stDixsoHkPcqg9iRrvSwvrB/keP0AQaIxaNUYtGoUjRa25lAymgzYNYasDYbsDVT59b0v+7FGJyjgxVlkJYtt5MlZRYrZImFicroqWG5LyHKGrJVnpFBmvFxmrGCw2Ojw5WNLvLRYI4gCVDlCkRKCWMOPDbJmjqmBCmPlSYaLQ4wWTEoZHUtTeOLUBl85vkbX8zHkJpbSohONIskZ/Cjh3EYXb4dYuJypMl2xmSrbDOdNgiih60d4YUw5ozOYMxnMGQxmDRbqDo+eWOdbs3XCi2LBBrIGH7xrjB+9e5xbx/JIkoQTOriRS8WqABDHCU4rjYsRCUgy6GWDuhey2vI411ziROM4s53jVP1FokjBD2VcX6XTKRN6RRRrCSVzCtWeA+nysVSqpHLn0J28bfxtvG/v+xjPjpMkgvWOz2LDYaHhsFh3Wet4aIqMrSvYuoqtK4wVLY6M5pkoWUiSxOxGj//86Gn++LmlS4TgZ376ft5xcPAGfXOuzE0VNw8++CCqqvLP//k/Z3R09BJT1J133nntI34d6YubPn3e+PzBN+f5zDdmObHWuew2tq7w0w/uxdIVHjtRZanpoioSqixhagrlrIFtq2AoNETCShyzHEe4Shooiy4jdBleLSyiBKkTIndCJDdG8mMIEiQ/RgoThK4gDBlhKGAooMtpureXbiv5m9smAslQiDe3FaZyYa3LoMoIVaJganx0apD3ZTLU6i6n1rucWO1wcq3D6fUu0RWsCsKQSfIaIqeR5DQQIHdDpG6EsFWSigElhWF/hQlnlolwiVLcxKBDVu9SMRsMWDUs1ScREt2wSCAGkbUSIXl6SRYn0VGkNCbGkgWaFCFLITIhmhKjqhV8RljvlVnuFJkanOYdh/cwM3h9T/NRIvCTBCFgbqPLU2dq/MXLq7yy3KZ3mWy5a0FTJPYOZHjTdJk37y1z394y48VrjxHp+hHfOL3Boyeq/OXRVeq9C/Fqh4Zz/Og947xlpkLDCah2/EuW9Y7HesfHuYb3JEmQNzVabghSgKS2kWQfSQ6R1C4DRYdKLuJI5VbeNf1W7pkcpd4L+MaZDb5+eoOnz9Wv6RrmDJW9gxleXmptVcJ4cH+F+/dUGC2ajBZM7hgvUthFssKN4KaKm0wmwzPPPMPhw4df0yC/U/TFTZ8+b3z+29fO8MtfSnvzHBjK8uaZMg/uG+DQSI6Xllr83hPneGGxdZWj7A5Nl9EsFdVQib2I3mUySr5TCE3CKBoUSxZLqkjFkaVgZFQO5GwOZkwyikwjjFnxA5b8EFOWeFM+w72FDPttg0frHb6w2mA12LQ0JWl6vRQKEAmW4RGqBqFkXHU8w7rKrVmLu/I2d226+gZ3Ec/zaoIk4YWOy1PNLt9q9ZjzAqpBSCOMtznazr+XtxYy3GIYHFvr8Mx8g7maQ6Pj4zkhcZgghQlKXqc0mePQYJY3FTPcmbfRkAiiBFWW2DOQYbJkbbmPbhRhnPDYiSr/67kl/vqVNYL42jIls4bKUM5gIGtQymiUbJ2irVOyNQZzBmNFi/GixXDeRFdlNro+Ly21eHmxxYtLLV5abLHa9nZ1LkWWGCuaTBRtJkoWowWTKBE4QYwTRPT8mHMbPU6td7ZZpt51aJBPPHyAe6Z212PyZnBTxc19993Hr//6r/PQQw+9pkF+p+iLmz593vgs1B1eXmpx/94yleylE64Qgr88uspnvjFHxlB556FBjozlEUIQxgI3iNMn5G76lNz2QjpeRNsNabkhDSeg4YQEl6mwPZw3uHWswMxAhqF8OukM5gzypkbDCVhv+6y1PVbbHg0noGjrDOdMhvMGw3kT21ZZiiJCJ8J3I7q9V+3TC+h4ER0v2poIhQwioyGyKkl2c53TwFS2lbR/byXPz04O8tZiFuUagjhjIfh6o8uz7R7n3IA512feC6iFEf4O1qFBXWXU0Bg1NHpRwmnHvyCOXsUB2+D7Bgp8XyXPXXn7sjFNQgieazt8bqXGn6w3ca5RBFwrqgR35zLcX8xwfyHDvfkMFT2NKQuShFYUo0gSpRsYeN5yQv78pRW++NwSs7UeA1mDSk5n5LxrK2cwtPl6KGcwlDew9dfeWqPW9Tm20uGVlRZHl9u8stzmTLWLqSncvzd9OHjrvgqHR3K7EndBlHCm2uXUepd9gxluHSu85jG+Vm6quHnkkUf4hV/4BX75l3+Z22+/HU3brtjf6IKhL2769Ll5hInATRKaYcSiF7LgBSx6AQtewHoQokoSmixhyDKaJKFJEgKxWUJekGaKp8foxQndKF334picqvDOco73VPK8uZBF2yEVebeNWc9v2/Uj1to+622PtY5H0da5bazAYO7qFowbhRfG9PyIs2HIUcdDldK6MOOmzoSpk1Fknm07nHE83lXOcyDzGnpW7YAQAidJCBOBKkkom5+LusP1bUcxJ3seL3Qcnu84PN92OO342ywtigQzlsGhjMkBOx1rL07oxjHPtx1e6V2wMJQ1hbcUsry5mOFwxmJQVxnUVbKKQiIEkRCsBxHfaHb5erPLix2HYV3jUMbkcMZkn51mxY0YGl6SsB5ELHkBTzS6PFJvc9q5NEuwoqn04hjvIkGnSxKDusqwoVHRVIqagi3LW7FQTpzgxAkJcGvW4v5ChtuzFrEQvNx1ebHjctLx8JKEWIAbJ1SDkGoQsR5EuEnCPsvgneUc7yjneGsxS069+e2J/E3xdrGYSYTgrOvzYsdlyQvSvznSax0mglYU04xiWmFMKAQZRSaryAwZGgdsk/22wbip041iGmFMM4rIqwoPlXI3/f3cVHEjbyrynZoW9gOK+/T53qUZRpxxfM66PmcvWlc3b95OnBC+TpUlcorMPtvcOu/5xU0SJkyNnxgu87dHy+yxtosUIQT1MGbO9Zn1As45PrOez5wbMOv6dKKY23M29+Yz3FuwuSefYVhXvzO9m75LaIURj9Y7/HWtzSO1No3oKm0RZIkfGiryd0cr3F/I3NRrO+f6PNXs8a1Wj2+2upzaQexcL5okEYndJlhvR5HgzpzNA8Us9+Yz3JO3GTJ2du0lQrARRKwFIat+SD2M0wcBUhH1fMfh6VaPXhwzZuiMmxojuoYuS0hIBCINaG+EEfUwYs4N6N5gi9nbSln+6K79N/SYO3FTxc1jjz12xd+/4x3vuJbDve70xU2fPldHCME5N+CbrS5Pt3o83exxxt39xKBLEuOmxuSm9WHS1BnWNQQQCEGYJPhJ+rQoI3G+E4Uipa9tRSajKGQVGXtzWfACvlJr80itw0a4u4q7+yyDaNMSdF78XGux4y0ripG+lwlTY8/mU3hRuwGdur+HEEKw4oec6Hmc6HmccX0USSKnyGQVhSFD5f0Dhe/YdauHESt+SE6RKagKWVXZsg6t+yHrQSoemlGME8e4sUAgyChpKYJo0632rVZv6zs4omvckbO4NWuRUeQty+SApjKkqwzqGhlF5tvtHl+td3is3mHOuzSua9xI/14qukpZU+lGMacdn9OOj5vcWDFiyRK3Zi322gbaprVOBnRZoqCmlquCqqBJ0pbVbckLOeV4nHI81vzUWlPSFIqqwl15m186MHFDx7gT/SJ+V6Avbvr0AT9JYyg2gohqELIRpLVjUjN6yMtdl2pwqYAYNTRmLIMZ29hajxpaKkA2zfi2IqNL0k17Ik+E4MWOy3oQXnJeU5Z5stnl86t1Hqt3LttCbNTQmDZ19lgGe6zzawNbkXmu7fDtdo9vt3oc73mXfTI3ZIn3DRT42yNl3lHOoUgSsRA4cepKczbdad04oRvFm5NEQixS90+6pIKuoCoMbE6EFU3d0eXW542DEIIFL8CU5ctaXK7Eohfw9UaXp1tdnmk7nLjC9wzS8gUDusrwRd8PWQJVkjiUMXlLIcuArrLshyx5Aat+uGXd0SSJsqZS1hQqm8c4YJs7uh3f6NxwcfPiiy9y2223IcsyL7744hW3veOOO65ttK8zfXHTpw+c6nm87enjV9xGlyTuztvcX0iDMe8rZL6rLBWrfsipnoelbIqfTRFUUJXL1pV5NX6SsOyFadyQn8YPLXoBL3RcTlwUO2LJ8lZrgRtBUVW4O2/zA4MF3jdQuK5spD6vnSRJ2NjYYGVlhSRJ0HUdTdPQdR3DMMhms2Qyma1wjeulE8W83HW3LEe1IMKQJQ5m0hiXKdPoC15ugriRZZnV1VWGhoaQZRlJkthpt37MTZ8+3x00w4gHv3mcQV1lQEuDOM9bDgY0lRnb4K6cjXmDU2a/VxBC8FLX5fMrdf54rXFJnInMedda6o7JqOk6q8iom7EaoRDEm+tWGLMRRtTC6BK3mQTcV8jwAwMF3j9YYNp6/YKdz5MIQS2MWPND1jbjP9b9EC8RlDSFkqZSUhUqmkpp00qQ38xAaoYR32r1eK7j4Cdiy2I1qGs8VMqyzzLeMDFNvu+zuLjIwsICCwsLLC0t4XlXTrGWJIlcLkcul2NwcJCJiQnGx8cZGhpCUS4fNJwkydY8KkTab06W5W37CCHwPI9ut4sQAtM0sSzrkkSe3RKGIY7joKrq1nKlMb7RuOHiZm5ujqmpKSRJYm5u7orbTk9PX9toX2f64qZPn+8u1vyQXzi1tGVWr2jpMqCrDOkaw7q6NZF+JwiShDk3wJClrdgMU74+t1wiBI0wZtkP+Gq9w59XWzzf2d7B+kjGZMrSU7GkpoIpq8hbrwublZQvXudUZVtriCgR9OJ4MxPtQkZaL05Y9VNL1dKmi2PRT90cl+nHekUU4GqPu+OGxttKOcqawqof0o4TEiHwkgvZck6cIBDocnptTTl1QY4aGnfnbe7IWRQ1leymlS5MNht0imSzynQqwqYMncj36HQ6tFotms3m1npjY4P19fVLHtw1TWN0dBRd1wmCgDAMCYIA3/fp9Xo7PugDKIpCsVikXC5TLpcplUpks1lWVlaYnZ1leXl5x30VRUHTNFRVxXXdHQ0GqqpiWRZjY2Ps3buXmZkZBgcHt33ngiCg1WqxvLzM4uIiS0tLrK6uXtIySZZlBgYGmJ6eZnp6mqmpKfL5PN1ul+XlZVZWVlheXqZer28JsvNrIQR33nknDz/88FU+5RvDTY25aTabFIvFHX93+vRp9u+/+RHTr4W+uOnT57uL59oO73/m5BW3MWWJYV1jr2Vwe87i9lw64U2b+g0XPW6csOQHnHV8zm1mjC14AX6SWmHCzUBpW5G3iQxtM1hakdLJeczUmNjMbqloKoYsY8jSJf2plryA/7PR4v9UWzzZ7F42juhKSEBOlVGAbpwQXodQkUjTqIeNVFQOairhpkWnEcbMuz6tXWThKMCwoWHJMnOef12i6XqRkoSs71DudSg5HYpOl4LbJec52IGHDBSLRSYnJ5mYmGBycpLh4eFt1o1ks2SBKqeeil6vtyWWVlZWWFpaYmlpCd+/tsysWJLoGRZmGKDFERd/C0zTRJIkPM+7rJjKZrNUKpWt8Vzu/JfzvFyMaZpXtVid5/C+Ge47cphcZYChPTO72ud6uani5oEHHuCRRx7BNLfXWjhx4gQPP/wwi4uL1z7i15G+uOnTZwcCBzRrW7E4AOIQGrOwcRK66zBxLwzftm27+fl5/vRP/3TLxH2xufu8sDi/tm1725NssVjEMK7slljzQ/602qQWpG6b+qb7ZmOzhkjrCqnHeVXmSMbicNbilozJLZu1Ubwk2eohVQsj2lEa+LuTNaMdxTQ3M2iaYYR7g+JqLoclyxzIGBzJWBzJmtySsbAVmXjTqvNi16ERRnSihE6U9r9CYqtGUDuKaUUR7SihE8fXLB4MSeJw1uSAnY7h7nyGaUtnUNcIkoS/rrX5i40Wj9Y7l1x7VYL/a2KII1lzMytOMKApBAK+2erx5Vrrkn5cF5NXZAqaikQasG1sWmrOFwUMkmTruG4UUw9COokguQECVgFKqowuSyRIxKQuNBkptQJtZvgFm1OmKUHuvHjVVAqqwgHb5J68zd05i5znUK/XOVZv8kKrx3E/YjWRGDBU9hXy3DI0gKaqPNl2eKHnc8b1CTY/K0uSsGUJsfm5hgI0GYZ0jRFNQUdQ9UNWvADLdxldmWe4UUWPI0JFQY8ijCgkKwkmhoYYHx/fcpcVi0WEEERRRBRFBEHA0tISp44d49zZM7QcB5BACOTAQ/YcFM9B9l3YtPpICNL/BIkQ6L7Lnd/3Ad7z8f/Ha/4crsRNFTcf+MAHiOOYP/uzP0NV0+DCY8eO8e53v5sPfehD/MZv/Mb1j/x1oC9u+vTZgV+/DZwaZIfTxciloqZxDpJXZU1lR2D/w+my9x2cWKzxh3/4h9d9ak3TyOVyZLNZ8vk8w8PDjI+PMzY2dslD1E64ccL6Zg2Qk47HS520qNqxnnvDAnxfzflu43stg72WzrRlkNmMp9HlNLXWiZNNoZEKpGgzxiYRaVG7JT9gyQtZ9IMrV+oVCXIiSG5QbIQty7y9nOW+fAZrs5P5khdw2vH5drt3SZacJkkcsA2GdI2nWt1txe+yirzVdHTC1Ph/7R3l1uyFPk1RFFGv19nY2KBWq7FRq3G01eFZoTFbqCCQGGnXGd5cyqpCqVRiaGhoaykUCnQ6HZrNJs1mk2qjwbH1DVZdD08zQAi6hsV6roSrG1iqypgqMaip2LqGpxk0FZWGpLASw0oQsbtCAq+N3fVrfzVic88bR0aSmLL1zexGkz2WwbSlM6nKvHLqJF85N89zbkQ3EVSa65SbdbJej5HEZ1xTkJp13E6HwHWIFJVacZCViX0sju9lbniSB8+9zPfPH+PA/W/lzT/6oRs69ldzU8WN53m8973vZXR0lM9//vMcPXqUhx9+mJ/6qZ/i137t117TwF8P+uKmT59XIQT80hDEl+mppNlQ2Q9WCRa/BeH2GJBk4BY6A3fRG3oTvfw+IqEQCZlQSCSShpDkzdMIut0u9XqdRqNBvV7Hdd0rDm1gYIDx8XHGx8fZt28flUpl128rTASnHI9Xui7Heh7Hui7Hex7LfogmSVuBsGVNoaiqZDYDgDOKsvX6fBxLabNqbVFNO3lnFfma3V0iSYibTaLqBnFtA8my0MbGUQcHiJHwkwQvETSjiOM9j2P/9Gcg8JE2b9Gd0gDrUwepTh+gN7kPJZPDVKQ0oyeIWA9jGlGMBFsdzMc3Y1LuydkcsHSGTJ2ipl7i+jr/+bi+x58urvFEL+R0mF6/Vxd8G0oiDi+eZqq+xoxlkM9myW4umUwGx3GoVqtUq1Xq9fplXSCyLFMulxFC0G63CcPLW3QAmlaGV0b3cmJkCl/Tr3q9R3SNNxVs9lkGe2yDiqby1XqHL1WbrO1Q5uCNjOk5VBpVPMPEMyxAQokjElnCNTPEqpb+Hd+EuDNbkZkwNIJEMO8Fl7hF31XO8Yd37rvh592Jm17nptVq8c53vpN9+/bx+OOP89GPfpT/+B//43UP+PWkL2769NmBoAedVeiupWuvBaVpGDgIuTE4n+oa+TD/JJz+Mpx+BNaPXvXQkWQQZCdRR29Dm7gDafAQZAbAbRJ1q/jNNcLOOlG3QVvKMx8WOVZXWNuhgWWlUuHQoUMcOnSIiYkJlCSE1ZegdgokBVTjwqIYoJoIzWS90aXZCxCqiStpaLKKLMvbskYkSaLRaLCxsUFjbRFv9Ryx16BBnp4wSZKEJEkYGRnh8OHDHD58+JIgToAkCOg+8gjNP/qfuM89h4hjSJKt9auRNA1taor8+99P8cd+FG1sjCiK+K2PfYg4vHwTT03REJpBoBkkqoqmKBiSjBmHaFGI8ANI0uDPOEkQkkyiqGAYBKZBqEhIoY/kdMH30yDRi96KgoQhSUiSgmNmaFoZLLeD5jtIcSoOokwBf3CMxMpcdpy6rjMwMEClUtlaDw0NUS6XURSFFT/kZM/jTKfHQqdHwXcpdRr4G1VW6g0WhMSx8RnOZi80bNSl1EUzoGsI0oBhazOwuh0lvNx1ruiOy6syDxZzVDR1UwjKFDWVaVOnoitECZx1fZ5udXm66XDGTdti5NRU+BqyTDeKWfR3FmRKFJLvNDF9h2KniZLJsjIwhqRqFLweyvoKmU6DjNNBFoLawCiz4/vo7XAdpSSh4vc4XFvmzrljDK3MEboOgeMiRIKsqGCaJIbJ3OQBZoenWM8WqeZKeLpJrFy9fIONYI9tklEVlv2QWhhts9Bt23bTanlr1uT2nM0ttsktOYvy61Am4oaLm3a7fcnPVldXec973sMP/uAP8iu/8itbP3+jC4a+uOnT5wbS24DZJ+g8878Ijv0lBc1DlW+MK8iR87TNSRrmFEvSEK/UVWQRMs4q46wxKa0xJKooV83HuZQIhRCVAI0QjQANYsgmXWzZQ1UuiBAhYCkZ5oSyn5PsZY0BzrsOKpUKB0dGKDZbWOtraEtL8Myz0Lp8x3KlVEIqFomdHqK6sU3wCEmiu2+G00NDdIRAyBKbEQ6Y3SZap0VXk+mZV7dc3FTOTxubwq6cyaMPjdJFIEuQKRQplCuUh4YoD4+SrVToNeqsnjnF0qkTrLQ71IwM62aGk6N7ObX3yFXdbhLw7nKej41XeHclf8WmoU6c8Hzb4ZlqjZO1BsuyxoaQuN1UubezwfRTj+EcP0bYqGPICrqsoEsyGhJyNos4tJ/cvfcxnMnT+da3aL/wPOFGDdFqgecRJjFBErM4MMyzt9xBPZcjFgGFJOTI2BiDzSqd9TVa1TXiy1ikiiOj3PqO93Dkbe8iNzAIwAnH44lGlycaHU710samr25pMmMZ/K3hEj82XGTK0DjlBXy75fDtVo9QCI5kLW7PWtyWsyipCkHg03McNhyXs12Xl3oex7yIs4nMUgKdK7hES6pMN0q4sk0N/tute/jhoeJVtnrt3JQ6NzuZYM/vej76ul/nps/3MtfSlPFvGr1mg0/97EfIVgYY3jPD8J69DE9PIiUhG688jTf7DHLjDGWtR9lw0OUYP1bxzi+JSpgoFHWPQaNHUd9dpgZAD4tVBkEI1CREFSGqlKDIoEoxKhGaCNEJr8lqn8QQBzKatf3mHyQZmn4RvxehdXyUXkQSppYtWRXIakJsKrgFi8iUkaWEdYY5Ix1g3pzAR96KxZCSBMt1GaxW2Xv2HMPr61cdl1BkvMOHaKkyPaeD63l0DQPfMIh0g0Q3MCWZjCxhbMZLxUlMEIUEcUQYxxheQM71yHoBGT/AzWbxDx5CmpxGdRykVpMgjgkkCBCYcYTi9DDqDbIbdfI9F19VOT1cZKmUe83uECdboHXPg6jTM5zNDfC8pNFLBLacugR/eKjIR8Yqu6rx063XOPnNb3Dqm19n8fjRLSGW9QLGGh3Gml3si9xSAohlCSURrynaJRoZwvjJDzPxob+Nadkkroucz9Nt1NmYn2X9zHGasydQ8sPc8o53M37oyFXvJ7EQrPohR7suf7Le5EvV1rZWDBlFpncFcTJuaNyatRDA7GYX+MvFoakSW9YuCbg3b/NwJc/9hQydOOEbjS4vdBzqm20nJNJg5wjBJw9O8M7yzZ9Pb7i4uVo/qYvp95bq873Kvb/0ZbKGwkTJZqJkMVlO1xMlm8myxWB2d8XI2l7IqbUO1Y7PbeMFJkr26zD6m4/TbmHnC5f9feh7VOfOkUQxsqqgqBry5tN66PuEvre1jrs15PVXECsvoLfOkI/XqOg9BBJrXpYVN8dyPMCSNEbdGiHJFkh2mJpk38Vo18mLCJmExHeRQhcp9tDlGFWO0aQEXY4Z7PYo1QKcoUm0ex5C33sQXngZ7cVvkItOkx3zyAwHyOr1W6Za5DjBDMfEfubiYYhipCiCJEJKYrKdHtNLy1QaDZQoQr7o9hwoMivFHM8dOMTJvbewOjRGvTBIO1dEXKZCrpzEZNwettPBdntknC65Xot8p0m5WWeovoEgxjUMIlVFyRW45a1v49aH3oGVyW5Nrit+yLIfUA/T4GgpCrlbFtzjdvC+/TTfOPYSK7JCM1sgkVWkJCZUZUzfJdvrkO218A2LlaEJVoYmyBeKfJ8B5Xad6pOP4ba3W7qKI6Pse9P9zNxzP7nKAF6viyIrZBUVJRboe/ekD9VhSOsv/oLG41+ju7FBc3WFereFa2jIQuBqKk4ug+b5lLoupZ6Hq6s0MxZhxiZUFRwEEamwySkauTDGaLQwPB8hQaDr6OUyQ6PjBLkcXWK8wMcPfDRFRQlD1hbm6egKYvPv3wgjzCAia5jsu6XCvtxxwsYyfiwxXFTQR29BHPoRxKEfQq6M7PqhqRfFfGmjxRdWG3ytkbYXsWSZezYriZuyzEtdh5e7LrPuzi5NVYLJzdYjBzMmd+ds7srbTJs6z3dcfm12lb+uXeqtudyxJkyd37plmnsLl3dN3ij6vaWuQF/c9LkeWm7Inf/ur664TdZQ2TuQYU/FZrRis6eSip+Nls+JtQ4nVjucXO2w3NpulZgsW7xlb4W37quwZyCDG8T0/Ag3jHHOvw5i/CghTBLCSBAlCWEsCOOEOBFkDZVSRqdsa+k6o1OydUoZnZypom7WT1E2M3nk77JS7nEUUl+cY2N+Fs/1MDNZzEwWI5OlPD6BZlpsbGywtrbG+vo6QRCwf+8e9uzZi7ZZI+RiRJLgtFvUFheoLc6xdvY0cy89T7de2/H8lh9S6bqYSchIrkvW8NFtBalkoxQtTENC0TSUTAmzNEQ3P8azUY6znozptDnYfZm7a18jm/S2jrmojvCF3Hv4SuEejo4cJpIV3nLuaW5bOoppQEnzGJHqIMs8n7+VFwqHeL6wn45+6SSixz65oEcu6GILn4ZZYM2okEjfueqzRujzfd98nA88/gjjeyaxH3iI+O67kfbs4ZZcZqu3URSGHP/6Y5x79ltsLMzRWFm6Yh0WI4wwJBlF07AbLfQgQkLgaSptU6d7kyo4G3YG3+ldcRstSQiv0opBlyNuya9zV2mFkuLSWbSJKZIZdlCtGGGPw/BhFFtHcleRBg/Dngdh6gHIpu6rcHWVtZ5Ls1DgsC2hmoULcXEAcURv8Rnqx/+acPUoud4y+d4Ksp5BzQ0jnc+KLIzD+L0wspkteeYR+NZ/50yk8djYe/m6PsU3zD201CxFKaakmRR0jdZmcPH5eklfvf8QhzPWDu/2xnLTxc3jjz/Ob//2b3P27Fn+6I/+iPHxcT73uc+xd+9eHnrooese+OtBX9z0uR6SRLDS9lioOyw2XJ5ba/GtlTbNjk+3E+A44TXlfY4WTMoZneOrHeKbXDdlJ6TNYnKyLDGYNdg/lGX/UJYDW+scBftvVj8jIQT1pQXmXnyOxWNHCQMfSZKQZBlJkrFyOQanZxia3svA9B7MTHbH4/zkC2d4tN655OcysFeJKPh1qrFgwRi+rnHmoi7vrH+Lh5rPcsCZY7+zwGBYv8RuFaJS1Uus62WqxiDVqbdTHb2PJaXAUqKxGCYs+jGukDAlgaFqKFFI5DtpoTpJQhaCIb/GeLDOWFgl67voiUxHL/JSZoJj+T0EisattePct/IstztnKBkemhJzV/s4paBDb1mnvWDirBlEnoycL6AWbLKlVTKVBpKcbC4gKwmRIjPXKzLrlZl1ikRCQZciImR8cfXvpCwJpoYHkWQLt1an3HXJ7dmDMz3J6uIcdrHE1G13ki2VsXJ5cpUBcgNDeN02C6+8TGt9Da/bxmm3IUmIwoDVM6dwWk1kRWH69ruoTE5TGBzGd3oE7Q2G41lGopPk1p8k8ENq6iS9nk+1p3G2W6bqZtDjBITAu6h1woHcBm8ZmGfIvLJoOk8sFfCbMlLURbViVDO9bkkiEyVlEnsczQ6Qu7NI0ZUzEXdLIgBJQkYQeTJBW0UxY5Sc4Hj1CK1f/FPuHShu1SK6mdxUcfOFL3yBj3zkI/zUT/0Un/vc53jllVeYmZnhv/yX/8Kf/dmf8aUvfek1Df5m0xc3f7OIo4j68iIbc+eIowgzm0uf+LPZrad/1TBwO206G1U6tQ06tfPrDXynh2Fn0v2yOXzT4q+dmK95CY5p084V6VlZECA5Ubr00kV2IvBiMBWSrIbIaQhb5qGKxt+bKPP9M1N4EXxrts5TZ2o8dbZGrReQ0VUsXcHWFWxdxVTBkATZjIWmyKiKjKZIm68lVFmi60XUnYBGL6TeC2g4wdY6fHWzol0ykDUuiJ3hLPsHs+wbyjKYNb7rLD+vJz/3yhxfWGswbmhMmDrNKGbFD2hHl8ZG3BZv8O7Gt3i48zK+rPOZ8juY0yrokkSs2XTUDBEyt4kGdzuz3Nt8jnu9ebTBAzB0BAYPQhRAcw6a82mW2+gdMHFfmul24kvw5H+GpWe2zvnqjOGtyiqymgYaIRACOpFBKzCRpQRVEniJSjfU6UYGTqRRMXpM5lroOmSS7dbIMJHxYpWctt01IhJIIglJEcjXYVRyY5V2YNCLdNqhSS82iAQIIWEpEWXDYdxqY6shSHJar8kehJE7YPAQZAfAroBVBrt8Ya0Y2y0fryIKQ1ZPnaA0PEzm3J/B8rNp5mDoppmDF5dHkDVINkNwx++F932SQIyQOA6SbbO8OM+LTzzK6Wef3ooHGsrBxGCZYc3CqJ1DdRaRuw5ST2AXA+yhAKMQXVvMWKIRKHuJrH2I3Djkx5E1iXj+GOGZlxD1BfRsiDUQoFkJSSQRdBSaZ23cmo6Rj5AUQWfRJDvuMXxXG0Xffi9pzmYofHrpdYtFvKni5u677+af/JN/wkc/+lFyuRwvvPACMzMzPP/887zvfe9jdXX1NQ3+ZvN6ips4CqkvL7ExP0t1fpbW+tqOqaAAsqqSKRbJlipky+eXAbKlMoqq4jsOXq+L1+2kS6+L1+2iaCqFwWHyA0PkBgZQ1L9ZT9sX4zs91mfPUp07t7WuLcwRR1epaSFJF7I/rgOh6SiVQeyhEUrDowwPD6NHIU6rSafZYKNep9NsEnRaKE5vM/cFYlnGzxYQxQqUKqjlAUqDQ4wVCti1NdyleTbmZ2msLoMQKJpGYXCY4sgohaERisMjFIZHGdl3gEyxtPPYhMCP0l49cSJIEoiSJC0mt/l6uelxer3LqfUOp9e7nF7vstK6fECvpkgM501GCyYjBYvhnEEioOuH9PyYjh/R8yNsXeGt+yq8bf8gR8byKH9DBNGKH2DLaaXd8wghWAsiTvQ8nDhmUNe2qv6+VpI4RgiBol44n9NusXrmJI3lZRorS7QWTtNZnaPT8YgTKBk+JcMjXy5ilkYwu2cxuvO0Q4OVZJzVrkHP393fxGDF5vCUyWF7nlz7GCQRkT2M2l1BukqziCQBJzaIZBtV11FVBaFoCElF89fRokstYKkNTHCJqVRSoLQnLTwprqNJhSRDaQYOvQ9G70xF0NARyI+mvz/7VfjLX4C1ly7dd/xNcOdPwvSDUJ5Jt9VM2PuOywZbbyzM8dQff54TTz5+xfuPIivossxInHB42GD6zgmkw29iuSMxe3KOxmqVsN0gdFqEvocIIhQ/Rg4FapxghRF5NyDv+mS9gIslnJzPoxQLqKUskplD0nQkVUUyTWTDQDJNtPFxzFtuwdw/hRKv4y28TLcH3TBHnGjs/8APX/u1vk5uqrixbZtXXnmFPXv2bBM3Z8+e5ciRI7vuR/Gd4maJm9DzWDz2MtX52S0xU19aJIlvQLGo3U6+kkS2VCY/OEx+YJD8wCBmNodhZ9BtG9POoG9ZIVKrhfxd1BH21Xi9LkvHj7Jw9CUWXnmJ9dmzO14n3bIYmNqLbln43S5er4PX7eL1uoiLxKZdKJKrDG6aqQfIVQYxM1l8p5du323zlwsrGJ7LlAih26FT37hmYSQkCYGEfA03YCFJW8XcLkGSmLjlVg6++UEO3P8A2fLuC91djo4Xcqba4/R6l+eWWzyz3KLWcKm1PK7Hi1a0NR7YV+HemQrvOjjInrL9Nz7zLIljzjzzTdZnz9Gtb2DYNuOHb6U4MgZC0KlvsDE/R7Zc4fADb9/6W3XaLc49920Wjr7I+tw56ksLSEiM33IrI/sOsnTiKEvHXkFczwR/EZIsUxweQSSCKAzQLZtsuUKuPICZzbBx4nkO9r7MhNWibOzsAqkGOc44Y9SCAn4cY2sJRcMjlGwWxTQBJqphMbzvAKP7DzKy/yDl0XEkWU7/rlaeh2N/llqezlunLq6YrefSStm3/wTsezfoNrSW4NifgltLW4YsPQvrr1xaaXu3ZAZS4dRdS/9tleCej4GZ2xRU0zD1IIg4FUTqtaXpdxt15l58jrkXn2P55DF81yXyfaJg595Q2coATrNBch2ZyTJQ0AwGJ6YYvvNuBg7dQnFkjMLQ8DZx7DsOjeVF6itL1JcWqS8vUF9apLm2si21vTw+yd//tf96zeO4Xm6quNm3bx+//du/zXve855t4uazn/0sv/Irv8Irr7zymgZ/s7lZ4qaxssTv/fzPXvJz3bIZmNrD4NQeSqPj275AFxOFAd1GnV6jTrde21qii4p4aYaJkc1iZbKpaMlkiQKfdnWddnV927a7RbfsC2InmyM/MMj44VuZuOU2CkPDb6gJyOt2WTpxZTGTHxxicHrvVmzE4J4ZCoND6c3yVQghCD2XwHUxc3lU7epP0a0w2taBOo5C2tV1mmurtNZWaa6t0N5YRzNM7EKRTKGIXSxdeF0oYuXzBEnCqdV1ziwtsba2hlOr4tU38GobRL0uK/ky65URquURqpURXNMi321RbNcptBsU23WK7TqV5gYD9bVtY1wbnWb5wO1sHLoDigMUVYUBPe2iPaCplDSVXhzT6Dl0luYJF84hLc+jBAHt6QO0991CXKwgAYtewLHeRQ8siWAEmf2yiuwn+E6I70SoioSuKWiaTKhIhDI0ugGNlR5O1UG8qqKarsNoHg4NqNw3YnBX0SCrq6z6IUt+yHIQsRDELAQxrhC8pZzn/UNlZjI7t2PIlitXzNR6NaHvoWr6jt+Li0l78HTwvAUc5xyuO48kKVjWHixrCsMYJHXqSEBCkoQkSUCSeERxlzjqkiQBsmwgywaKmiH2VY4/9jQvfvkrlw1gfjXl8UlG9h1ACMGpp76+q7/1ysQUlfFJSmPjFIZHyFdS666sqDRWlmisLNGpbeB1u/i9VOxbuXwqMg4cYnjvPjTjCu0vogDxK5NEQcCik+d4e5iznRJBoiBLAjnzYSSlDFIqZEXSI4mrIML0WkVrJNEyCAdJziGSFiJpoxkm40duY+LQEQw7A5KESGIC1yVweoSdFtNTRWYOzSBNv+WKYiIMYlbPtoh7HXK9F5Dn/wIzrmON7AO3AQtPQ3kv3PlhOPsYPPtZriV4rhGY1H2bgu4xYDhgFODWH4G7/g5Mvvk1pcgnSbz5YNWgtV7n2OP/f/b+O8rS877vBD/Pm2+OlWNX54gMEADBTAoSJVGBIqkZH5urteesJXPXnvXsHC9ndSSLPjryObuaHZ9de6UZyZZkWSNRTDIpihQpgACRQwOdQ1VXzjenNz/7x1uo7kJVVwegQUC8n3Oe83bf++b31n2+9xf/jovP/xB/oyFmtn+AsRP30jexFzMWB9XDD5fptGepV6/QaZUQQQa3HqOx4lGZX8ft7Gx8EEJB0TZ+6Ep5Q2u3GU8Qz2TJDQ7x8/+3X7/ta7xV7qi4+bf/9t/yn/7Tf+IP/uAP+PjHP863vvUtZmZm+Bf/4l/w67/+6/yzf/bP3tLJ32nulLgJw4D//H//78kNDNEzOr4paFLF7RVMbxYpJXarSej7mInkrpOvlJJ2rUp9PRI6tdUVmuUSTquJ02njtFo47RZOux29doOof4h+IYwcPsbw4WMMHzlGbmDoHRU77VqV+fNnmD97etMq9mYxkxscZuTIMUaOHGf4yHGSufw7dn53EjcMqXhRE8dmEGAHIcZG1+ipjsOT5QZPlBvM2i7pRoX9U2c5OHWGoZXZrfvRDNrxBO1YklYsSTuWQA18+tYWKVTXtqQaX8tavo+p0QNMjR5guW+Ue/Npmn7A+Za9xdGgyACBJETZbLPwBiIMyNSr9KwvklytENSh6qdY17Zn8ST9BsOdRYbtBYY7C6SC5q73R497JIdaxAoOVt4hlneQoYa0ezHVCTKZu8gPHEaIgHppkUZ5mWZ1iXZzFbtdwrPbdFYLZAuH6duzj949e+mb2IeeqrG0/Oc0mudw3TVcd40wvPUfDbthVwzO/3lUrl6zfDJ7OnTW4phWFq+j4W2k8CZyeYrDo8yePYXd2Jqa2zM6zp577mfgwGGKI2P4rsPM6ydZuXKZvj372PfA+8j03jhguVWtsDx5kdUrU6xOT7I2O42VSDF24m7Gjt/D4MHD2753XLvDyuQlZs+cYu6577C0XCHcodaKkf48inprf48ybCGDCojoR6AMSpEgQiCEhaINIrRBkB6qtsDgIQMjHiIDiSoCkA6dRofVOQXPHQJZhGscMVJKZFhFNQN0HTS1RO+4SX5oiL6xIknNR7YbqJaA1BD6/NOEF56k1kzRx2usLi0w1cyRN9rMtHJcahQ3970vVeKDvVNXazTl9kSuqrs+G7nLrjkH2wuRYZswWMZxVnCcN5bRcN21jeU6UvooioVhFFEo0llJke3rIds/TChdms1zNBvncdytP3K23VsJfjNB0BjFrRZwqibtsk9jrYrvbv+MJ7I5coND5AaGSPemiRdVrLQDxjpeuEosNk4+9zDp9F0oyjsTDnHHs6W++MUv8ru/+7ubLijTNPmX//Jf8lu/9Vu3d8bvIN2A4ogwCDbjduxmA6fVpNNsUJqbYf7cGZYnL21zqVmJJKqx8StJym3pmqqmo+patNR0VE1D1XWkDPFdj8D3CDwX3/MINoZQVcx4HDOWwIzHMeIJdNNk9cok5cXtHeZzA0OMHD3+907M3C7ztksriCq8KALsSom5F59h4eUXqF06f0OXmUxl0IbHiI/sQdE0Oudex52+vGU7PWYyfGQfvfsGsYMylfYKtrOOGpRRgzogkaHAbep4LSNaNjW8lsqWev4beEJjLVNkMT7ArDrCktq/Texkgyoj/jyj3iJ7vEXCUKHjX52kiqNlDn3w8lu6dwDtNYvK5TSBo1I4XCHRdx23ephAV/qwrFF0U8cLV7DtOTyvsmU1IXQUxUBRTDQtiaamEIqBDF2CsEPgt/CDBrNPJYkVHLJ763gtjXN/tm/bIc1iij0f/RjMV1i+fIHA91F1jdFjdzF24h4C10WzLHJ9A/iuywtf/zKLF8+R6e2nMDxCuqcPw7LQrRixVDqK0ertx241ufT8D7nw7NMsXjy36/3RTJOBfQdxXJd6pYJTryJ3cJekij2MHr2LkaPHSRV6EIqguuLj2S3s5iqN0jLlxRZBkELVDCTQbhq4nRwy1BBKCxmmiHpz3z5SuoCKuObzJMMGMmwjlAxCub4lSkoPUBBCRYZNECaRRS7KlovEyBqhP09gvwq4CEUl0dtPcyWKi1M0jcxIL61OnU7JoW0kmcrsZSk5RkNN0gw02r5GKKPPcsao0WOVKMZKFOJlirEyxViJvFUlY9aIaTu7pq5HLDZKMnmIZPIwMWuEhcY0S7ULqM4V/PYqcbW+zZgkJSjBAJY5igx9wtAh0BwCtUMY2ihBFeT1LTmqGiebfYBc7hHyuYdJJg8jxO4W0dvlHalz0263OXv2LGEYcuTIEZLJndMi3210xc3N4Tk2ixfPM3/uDPPnTrF06cJ1y4jfSYqj4wwfPsrw4eMMHz563cDZLlc5d+5fsbj0FxAmCO0koRMncGIEHYPAtlC1OPmRPnrHx0gXB3GdNZrN8zRbF2g2L+K2HRrzSeqzCepzSQL79nvGCDXEyjnECg6xgo2Vd0j2qpgJC1VNoGkJPJnmQmmQ15dTnF7pZao2QCivTk6m6vC+gRfpTalMe8c5XS/geg77zUtIU8M247T0FFmnTL+/SJ4qptomkApeoOOFFl5oEkgLjxgeMdxQIaPNMZqaYzQ9z3ByCUP1CAOoTaWpXknRaVk07TiubUAgEEiElAgknmri5odx0gM0YzkcM0Mqkyabz2OZBoamXB1qtNRUhRXP51LH4aLTZsZvoegeqaDKg5efZWL9Ela5jSIkXkvDfwv3/eYfkKA4PErv+AQ94xOIwVGmV1ZYOHUS+8Jp1ObOxdya8SSzgxPMDkUjzBYo6gGDapOc6hPXLWLCwsDCClXi5WnU1VP46zN0yiV8J8CWJm09TktP0BQJml4G3S0ivARGp8WgvUox1IgTQ5E+Pj5NbNZFjUG3SUwbRagFIvFhIdQ8YsPiE/qrBO45Qm+Suu4TqjpqGBJqKXQlj+qpKJiY6iia1rNxK65fH0eGHYRytY6LlCF+WOOKodFRY2QCj0TnHKn2syAjQSLUXkAig3VOpw7zg/yjBMoOz1RCLhT0BQqFQKAAM1rIvBYSU116dJtew6HHtCmYLpbuo2seuuZgaiFpK006lkNrBqxPL1KancOtlijFi8xZ/azqRdxAx0fDN3TMtMeQucS4mGbEmyPWsnHqOm7DIHAUzKxLrGATKzgoWoBY1wgqOnbHRFcgpkliaohh+GhWCzXmoMYD5D4XO6Fy/31/QSZz7219HG9Et4jfLnTFze3hu+624lpCCBACQWRqDXw/ssj4fmSl2fi/UASqpqPpBqquRUvDQNV0Qt+LXGWdyGXmtlu4nQ65gSGGDh0hluo+o1vl1OkvsLp6+yUZFMXENPpAREknzVWF6hWV9rqGqsajoSVQlTiaFkcIDaFAIpclkc+SzOVI5NOkCz0kckU0zUJRdITQo3Vv4NqsdxyevTzLM5eXeeJSg5nynf+KEoQkEjZSiYMn8DyJ+w52klFNFUWLBJSOQzxscPfqK/S016nEs7RSCSzdIRPUyFaqaNJH0wKUIEA2FKQP5qhLYn+HwFZxyzp+U8W3VUJXIfQVhC1RfIkEvKJJayxLe88g5PJIJaARdDBEi6RXJ+HUMewO9pqJUzJohCkqZGmpCdp6HFc1I0sFAcqGo9LxDTpeDNs3sQOLgLcuzjTpEfdbpP0GShgiBPiajjQMhv0KhbCFFbqkVZ/k+AEKxSz6yuskrEvUF5YpXdJ3tB7uhFDygB8JGa0XwhZrhQmaoyMIYxalkQAvx2BlmIS3c8G6kBBPltBJoIio8rgMbUJvEjV8iZy1QFpzyBoaQu1j0b+HdecYody+vyYez1ghp4wAQ9qk/CYpv0nSb5AMWliBjRk6mKFDwa0QD98U1C1MFG0PQhiE/gIyvDa+y0CoORS1d0MUxkGJgbQJgxKETaT0ozio4MYZ0ALJp/5BwFKuziOP/ABlJxH3NtAVN7vQFTdd/r4TBFeDWYOghe+3NpYNPK+C65Xx3BKuV8J1S+h6dsOUfYhk4hDx+NgWs/6PEiklz02V+cuXr9BqTxOTJ0lrV9AVn6qTpuakqToZak6aQKpoioeheOhqtDRUDxSVhpKmoWbwtQShnkRqKRzbxK15NMo2vrOzkpFEGcJCRv+TGxOlJjwKRpmcUiUnq8TsDk7LwHUNAqFeMxRCRUUaIDWFUI2GKwyaMknDSxLyFk34UkatJXZ5ZqoI2Jed5K78GVQR0AwT2L5F2c5xpT5K2c4hkPQnVpnITDOcWmQwsUxfYhUBOIGB7Vtcrk5wav0wAGmjTspo0vISlO0cVSdN003S8uNwTUlBVfgMJJYZSS1SsMoUYmUUEdLxY3jSoOZkaHpxes01BhNLFBNl0kaDlNFE2CGrrxconcsSert8Jq0YPeMT9A8Nb/Y6lKHEbteoLs0hhY8eD1EMm5A6oVLGSHjoSQ8zCbncA9jhcZbbbRLWPNXnp1g/G03QQg1JDbcii8exIYYPn6BeXmdtJqCxZgABQvFpzL0fu3o1zkkzVQTgXfPZkmELULe5x6T0kcEqYVBCoKDoexDKG+Koht95lsA9xxvBzkLJo2jDoFiRy0iooPYhtR6koqAqAWqYQVzr5pM2UgYgVITYJVD8TYRBFdu/hCskqlJAEwkk4Atw5Aq+/yomHn/7ic+SPXCYu9NJ7k7H+WRPBuNtLuzXFTe70BU3Xbq8d5EypFx+mqWlv8QPWqhqDFWJoaixzX+ragzXK1Grvky9cWYjDmM7QmhoWgYhDOpujiv1fuxQRzUCAk3SViUppcR+cYEY9jXnEC1rSh++uZds6jC9qT3YIkm5LlmbLdG8MoU3P0+4WIbrCCeAEIGtWLTVGL6iI2EjODsqFyARhELBVQzaaoy2Gqejxq7+W4vhaDqPDT/H43u+h6m61J00DTdN00vS9FKkjBqHcheI6dcv01FzUmiKT0J/61VtpRQEG25FTdEQItiIZ7k+mpYhk30fnnqCmVo/88vziOAZLHWFuGZjqAGmGcfQEyihSqMVUKv5hFUHo+IQdhScmkGnZCLD6/TZ0kJiPTZG0kVP+qj6RhB0pFyRvsBIe8R7bcyMS3slxtKLgzQXt2ZjpXv7SOYKQGSt9t12ZMGWGp4bJwgTyNBGyBVAIkUPgb8fKfZsxqJIGSKDdUJ/kcC7gPSXgBAn30O9OEDg+vSupYhpdyGU5MY2PqEIAQX1Jq1i6UQLJaxQ6/Qh2Rr0G2WvrSODtUh0yQ6IOIpaiKw46ChaH0JcPxut413mKaPEa5kTeEezBMNRa5CYIrj02InNFhtvF11xswtdcdOly7uTP39xjlMLNYZzMYY2GpIO52IUEsZtZ+kFgUOjcYpq7WVazQvY9iK2s4jjLEe/Ym92P0qKNf0ofvxuxgoPcnfv3WStG6eeSymprixRW16iXlqjvra2kdG4RKO0huc6hL5PGASEoUQGIbplkshmSObzJHNFUoVeUoVeEtk8ZjyOZpropoVumjTtV5hd+F3anakbnouu50kY99Jc71AvL+B0ypjZKNPsjfhPGapItxddDmJoY8SsvVjxLKopQGnQ7LxEq3MKRbUIyeOT3gjYXYWwCnKnonsg0RD6fjx6aXhFWo4kCMrookyPcQlD3Sqq3EBnrjHEbGOIucYw0/URZuvDSBQEIQ/0v8ovH/xL0ubWrLogVCh1CjS8FDI0kRi4MqA3trRhMdp9unMbOnbVIETBESbtRYvmudhbiju7ioFQM4RCYS2tMjc4SrpRoae0Qke1cB2NklGgbOTwhA5IUoFDvzLMvqAX6xorjI9kWZfYBgwoDgmvTlCfJHBWgBCEigzKyLC6sYWKULIb/5bIsIFmCIxkGjWeJpXPkS8UMJJJqoHBki1oSo1ULIFV0/FWonR8K+FixVzsapnq3CyhV0Y7upfSsZ/koaO9NBIqJ+ttfCn5twdH3oZ7tpWuuNmFrrjp0uXdyT/9k5f569Pb/ftxQ2UkF2d/X5KPHOrlwwd7ySVurVDam5EywHFW8P0GYehs1KZxCaVLELQ3spqaKIpJNnMficT+O5YBcjOsrX+PmZn/H/HYOPH4OJY1xPLy1yiVfwCArudI9/xTphsH6Eu26E200Khg26s0XUFDPkAxfy9HB3ObQtFuNTm3VOf7k+sk1WnG8hn2DZ9gvJBBU7dfqxeEXFhu8O3Ty/z16SUm17aXk9CER8ZsMJRcYji1QNasc7Gyl9Prh7CDneNUFBEwnp7lcP4iB/PT7M1OY6nb993yYpwvH2C6PkLZzuGEGX76UIv7h5YJ/AqN5gV8v7JtOynBC3WcwKRBL542RlP2stTKsd40qTYVBvUrPNDzDP2J1R2zieorSc5PHqDUmiAuQ4TTRmlUUTYK6cU7zS29vTxFRRoWMpkhNEzUdgO9Vrp+Ic4NmmqCupZiwRrkQvIAFSNKoFAlpEKxWVGphcvh5lnuqb1GMrh6r2pamnWjgBk6xIIOZuhQ19IsWf2smH2sGUVsxcSKx3ACcK5pCXJ8KMNPHu/n3tEcLcdnreHw6myVF2fKTL3pWasiYMBa4dFYjSPHHuNnPngP+bf4N3kzdMXNLnTFTZcu707+5swyr89XWah0mN8YKw17Wza7IuCukSz7epKMFxOM5iMLT2/aoidpYmjRxFy3PS6tNJleb5Ew1c33M3GdlHnjwOZ3E1eu/DumrvzP214XQofEp/mzsx/lO+fbW97LxHQatrelovRgxuJjR/oYzsX4+slFzixuz4YyVIV8wiAb18nGdVpOwFLNptRytjwLQ1Xoy5joapQRpqkCVVHQlaj7vKaKqLZKIHGDEC8IycR0+tMW/RmL3pRJwoz6qOXiBvt6k/SmTEDSbl+h0TgTZfE1z1Grv4q/YyuGCMdP4ssMLmlqToy1dpqLlSEulsdZbPZspl7fiPGE4P2ugi98lnMVOkoVp+ljeCqF0KVPuWop8lQVu1dDzbXxZIfYJRPV17AVHV1KjDdZBp1QoS4t6jYUK7MMOMsgRBSTJRR0u4l4U3sekR/EGD2IrilooY8auHiNGo2Zi8iNUh2u0JmOj3EyfZxVs5dirMRIaoGB5Aq+q9FoJmm0EzTCPFUKVIOrWWGqIuhPWyzVOrtWHs+aVR4bfpWDuXP0xFbJWxUUIXli7lH++NxnURXBl37uGL/84OhN3efbpStudqErbrp0ee/g+AELlQ6z5TYvz1T47tkVzi9ff5IDyMV1DE1hpX79GiGqIsjEdAYyFnt7EuztSTHRk2BPMcFYIU7KunNFyaSUBDUHJaajmCpSSi6sNDi9UMcPQkJJ1JVbSlw/xPFDpL8I3lk8ZwYlmCelr7DeKfD1y4+z0IwKyQkBJ4azrDccFqpX3TyWrjCci7NQ6dDxtk64hqrw0cO9JE2NiysNLq40t61zLTFd5YMHevjJ4/18+FAv6Tt4n64lCDymzz/H9MXv02pNgbaGHq+gxkuoyu7uRdu1KDX6KNd7WWgOsdwZxHUzWIkcqZ5higmV9amzGPVVcr6BFmqIDTHU0VsI/ernzZcKF4IehpUaGWX3VkO+VKhKi/UwwYhaJSF2jzsSQjLcb3FsdD8Lr59mYeoFrNGATlCgWc8h3RC9sobqRsfN9A1w+LEPYSRgvfJXeJkzaIaPFbioqwJtRaC0QLggPBCuABeqSp4GKZQwpC8soeUEs/kMZ/37WAsz1DSNTKHMvsw0I7FJknoL1dx+j6WE+eYg//Hs55mu9fNfv/B+jg3dfJXw2+E9I25++7d/m6985SucP3+eWCzGI488wu/8zu9w8ODBXbdzHId//a//NX/yJ3/C8vIyw8PDfPGLX+RXfuVXbnjMrrjp0uW9zXwlEjozpfbGaLFY7bDWdLZ1QO9Lm0wUkzh+wHKpTantcjP9IPOmxkjcIK1rxDSFmKpQ1DU+3pvmcMKMklZCGfVnDGWUsZQy0PsT6AMJ1HQUJxQ6PkHdJWy4uEst5i6VuTJTZaXjsUrIpCV42fco+7efd54yNX7p/hH+4cNjjBejgM6m4zNbalNIGvSmTIQQ2F7AM5PrfPfsCgtVm48d7uVnTgxucfGFoWSx1tnoKO9RbUdd6vszkbUlHzfesY7w06+vR60TAsn8+TLrcztVrQ5RjRaqVUe1auhWA9WqYyTWSBSm0bNzCGV7ATopBY4Tx7ETdOwUrVaWditHrdaL3AiGVlUXXbexO2lMu4jqJ0gZccSRZ2kaeVYX07gNDyXwSQuHmrSYMQqkjTUysTVyqVV6Euv0J1ZJaU2azQKeZ7K8tJ9Gs4BAIESIqgaEoYLjJFBVl0JxloH+y6Qza1evMlRoNvPUar20Slka9T7cMEa40VpdCQNGlmeZmLuCWgvwdY1aJkMll0PzfEzXwdUNlgYHaKZSb9wFCizRm5xFjLWJxRpYVhNF2V5tWkpoVgu05nsY/+ESmUUHo3cY4/g+jLsO4R79WcYOjN5xa+h7Rtw8/vjjfO5zn+OBBx7A932++MUvcurUKc6ePUsikbjudp/61KdYWVnhS1/6Evv27WN1dRXf93nkkUdueMyuuOnS5e8nYSipdjxWGzYdN2CimCQTv2pZaL26SuV/v4CDpIGkjmSRkJmNMUvIPCHVG/QW2oPC4+gMoDBDyBwh7jXbKMC4qnFYqBzyBQkET+LzdVxOsrOIsYDDqMSJirgpRLEVOqAjMIA4ggEUBlDIILCAZCHG8Ilesnf3ovXeWjPSoOFGwqvjIZ0AYySNmr7zcRM3yw/+ywVOPbmw+X9NV9h3by979mVIugFTTy1wabVDVhMcMFUSGYM1J+BM2aW2IXJDtYHof51EZol4bh4rtYoVr6JpO1tRAjeGXDmBDDS04RcQmkdgp/FWjlJbOUSrPIbfGOCAqbHHUDAUQUeGzIkOPbkM/Ycy+MPLVM0naNpnoxRvGeK6q7juVbFimn3kc48Sj+9DN7J0OrPMz38Lz5tDUTaytyS0W3kso4lqbM/4CwIVKRWkFNddBoGObSexOyk6nRQgSMarpBJVrGQZY4eGpzIUtNpZatU+6vVebDuB4yTxvKvp41angxKGjF+Z5vjp0wB4qSTG8WP0ffwTJD/yUfS+3lt/6DfgPSNu3sza2hq9vb08+eSTfOADH9hxnW9/+9t87nOfY2pqinz+1kvvd8VNly4/nvg1B2+hiTBVFEuLloZK2PHwSzZ+2SYo21TLHeZdj0XPpxWGdEJJW0ou2C5P1lq4t/iVaQBvTE0KMJqJMViI05cwGEThXqFxuB2iuSGhEyC9ECWuoffE0friaPmNSSWMardIL8S+WMG+UIZrGpKqWRPrQA6tEEMGUb8lpEToKmpKR+uJo6YM7Atl2q+u4s6+yb2nQOxIgcRDA5gTGcQOQcVvJ/7aGko6jWJurQwsXRd0nclX1lg4WyJYaWO0XQaaa6ilFZR4EREvREJOE8SPFfEOx6jFHMbGxggdl+f/7lVOnT9FqbO2w5ElhuoRtzrkpcZAoo7IrSCz0yjWm+6JVEBstWSEvoHXKhA4KaSbIJQKEtDjJazsHEK9vhVO9wr4ahW5iytNWTcQp+Ikng5ILDk4RorKnlHaR7L4E1X03nms1E7XdeuEvk6jPEZ7+QheeR9eq4jbzuKYFQKtjRQhmh9HhNGPhE58Hs+sbW7fNzvDva+8Qsp2twRUj/7hH5B4+OG35Ryv5T0rbi5fvsz+/fs5deoUx44d23GdX/3VX+XixYvcf//9/PEf/zGJRIKf/dmf5bd+67eIxXaOxr+Wrrjp0qXL7VLreHzz9SW+8doCtheyrzfJ3p4kSXMjTVcIbMfnzHSFUysNpiptpIT+tMXnHhzhsw+MMJC58ffUzRDaPp0zJTqvr2FPVrcInZtCgJI0UOIaQoC3fDUgWegK+mASYySFMZZCK8TwV9u4802EppB8/yBqcquVx6/atF9exVtpoeVjaH1x1LSB9EKkGyA9F+fS63ROPk/7hR/iL86DqqEPT6BmswTVdYL1NcJWA2EYKIksUiTA7RC21uCaAF1hJjAmDmDuHyMor/OygNeGhlCCACUM8d9o9iklmu8jpCTZbKIEIaVi4TrdukNyuSX6+iYxNBfm9tJbHaKdK9HOLRJLr6Mly6Du3jHbt5PYlXF8OwOhQuAm6JT20intRa863HXu/w17q5Tu6afVYxIkWigyhCs96KeLmMs6IKjkDlDLTOBr8W3HGBiHQs7n8uUyIQFCCUCECBGCEiBEELm8jBZGag09sYqeXEOIEKc+iFMfRDpjNJZGMIwY/YMJRCBxag6G7SHcOkK2UJEoQhCg0pYmK0EMV/WRwo+ET6hxQs4RfyCNVl0iXW+izcwx/O/+F5RdvC+3y3tS3Egp+dSnPkWlUuGpp5667nqPP/44TzzxBB/72Mf49V//ddbX1/nVX/1VPvKRj/AHf/AH29Z3HAfHuRpYWK/XGRkZ6YqbLl263HEatsdCtcO+nuSO6dVvF6Eb4Fyp4VysEHb8yOqiRhO49EKCmoO/1iaouehDSeJ392IeK9DxQxplBxlKRNWBi2XEVA25S+FBACWhk/7oKAgIai7uQgPncpWdPHphu4Q3/QO86aeR7u7B4LshDBOtrw9veQne1Ofu/MGDXDqwn/bGhBpvtRibnWXv9AyJ2lVLg5JOE+zfjz8+xnQoeU3XCBSFWLtNtlJF9zzKhfw1cSnbroZYrIFhdEjIBvGwScy2yZfWSa02YDGHWoJGapylgYdpx3vxtDi638HTE9iWim3N4xltfL2NVLa7xwy7gO5m8YwqVqcP0y1QGEoxejhPz1iK4nCSbF/kgmzVHObPV5g/U2L+bJmMpVLwQ9ZbHklF0KcLMqqgHkgQoJoaqqUST+qoTY+gEdkU3+zOFLoCqgJhCIpAHU1g7csh8nFOPrnA7FSNVicgmdL5xX94CGM8g5q488Hl70lx82u/9mt885vf5Omnn2Z4ePi6633iE5/gqaeeYnl5mUwmisz+yle+wqc//WlardY2681v/MZv8Ju/+Zvb9tMVN126dHk3E4aS2mqb8lKLylKL8lKbds3BtQM8J8CMa2R74yRzJsm8RaYYI90TQzdVGiWb64+ypgAAoDVJREFUeqlDealFbbVDImuS64tjN1zW5puszTaol2zkTvm/AvbuzbBnII7V8VErNuHaGuHaC0h7BdmB0BGg6ghFBxkgfRvpOyhWiBITSMcndDykbeOvXNws6yziWbShE4j+4wTDx/HCFmJ5EqXTQYvlEIk8IpEBv4OkTZD1kb0Z/NwgjpkjCEGEPurKDNrSFKZbJzYygDU6RJgpUHI8fKGw5/BeEsVE1Iqh08EvV1AsE7VQ2DKRe55H6LqwvIy3uERod/DabS6vrrLYaDDdapFUFIZ1nXYYUg9CXClZ9b1t0VMxKRnSdXTLwtV1pKZhJhL09Pez78gRTr7yGq+cfIVrFaCiqBwavRu77bJcnaZ9HfE3MjLCpz/96c05bzdkKHHnG9hnSnjLLfxy5HIl2HmqV+IaatpASZvoIwn8IYPsvj5UXWV1dZVnn32W119/HU3TOHDgAOPj4+TzeWq1GstLq3z4Ix/Esm6+ncNb4T0nbr7whS/wta99jR/84Afs2bNn13X/0T/6R/zwhz/k8uXLm6+dO3eOI0eOcPHiRfbv379l/a7lpkuXHy+klIQyRFVurj+WF3pcqlxisjrJYnORfbl9PDzwMHF9uzvg7cZ3A9YXmpTmm7RqLnbDpdPyqK1GwiTwtmeuvJ2oukIqb6FqgjCEwA+pr20EmUpJpjbJ8MIP6Fl/NXKd3CbhwbtZ3fsRJuU+nM47M+VoukJuIMG++3s5+FA/icz1u35fj8pyi/nzFVIFi8H9WQwrqlTsui6Li4uUy2WuXLnCxYsXt8wzuzHYN8KxY8cY3TNEX18fun7V4rG6usr3v/99Wq0WxWKRU6dO4fuRGyydTvPwww+TSqXQNI21tTX6+vrI5XI8+eSTzMzMAJDP5xkbG8OyLOLxOP39/XiuR9D2yMXSWFInbPu4RsipxQtcmrzE4uIiYRhGfzthSCKRQNM0atdYva7Hr/zKrzA6emfr27zBe0bcSCn5whe+wFe/+lWeeOKJbcJkJ37v936Pf/7P/zmrq6skk1HPja9//ev8wi/8As1m84ZxN92Ymy5d3nu4gcv58nkuVy9zuXqZyeokU7UpOv7VbI9QhniBhxM4SCSH84f5yOhH+MjoRxiarBOUy4SNBkG9QdioU2mucyqc44fOWeaNFtUEVBPQMcHULB7ofwBTNVlsLrLSXsFSLYrxIn3xPu7ru4+PjX6MvkQfoQy5dGmOVssm3i8oZvMUY8Vt1+B0XJ567SXcFQWzkmZtrkl5qbWz9WSDNybo/GCC/ECCVN5Ct1QMS6Vd96ittWlVHBplm9pah/q6TeCHJDIG6YJFT2eS7IUnkOurBLaDIgM0NUTTFfR8Dr2YQ81mUTNZhCKQfoDTdKgs1pEXTmGWZjfPpZqeoFQ4DoQoobcxfKRQCVSTQDUIFAOp6Fd7YwmVRmqUdqL/6jUZCv0TGQpDSTRDQdWi4bsBTtvH6fj4bojvBfhuiAwlRkzDjGuouhIFVQcS1wlolm0aFQen6UX3JaaBhGZla/FHISBVjKEbCpoR3b9Y2iCeMrCSOoqqoKiCMJCb5zF3rkx58WplXkUV9O1JE08b6IaKmdQZmMjQtydDEPjMzs6xvLaIFdeJxWKoqkqn0+HKlStcuXKF4eFhHnvsMfbu3XvTn/swDCmVSvzZn/0ZpVLpxhvcBP29Q8StBLMLU/jB7vFDiqJw8ODBzUzkCxcuMDczz+ryOrgGppKixxwnFcty98dHGT1SeFvO8Xq8Z8TNr/7qr/Knf/qnfP3rX99S2yaTyWyKlH/1r/4VCwsL/NEf/REAzWaTw4cP8773vY/f/M3fZH19nX/8j/8xH/zgB/n93//9Gx6zK266dHnvMdeY46e+8lO3vf2//w9QqOz+Rf4GtimY6pVM9wmu9Amm+wTzRQjU7UGoezN7WWot8dC5n+fg+oNIQqqxNZSCy2hhmLSVwvV81uea+GvKRqL3VmIpnZ6RFKmChZXUiSUNknmTfI+JUZrBuzKFNzePNz9H2LHRR4YxRscwxkYxRkfRikXQ9cgFE0r8epPGN79B5U//C+7k5G3fMwBhWcQ/+ThnPzDO33SmmJ5eoscZYig5zFBqkOH0MEP5fhIpCyulYyV0qitt5s9XmDtXprrSRtEEg/uyjBzJM3QgR3EkiXqHM7GCIKSxbrNwscL5Z5dZnrqxBWInFEUwsD8TufnWdy/a9wb77+/lkV/cTzJ365ai69FqtXjuuecol8vU63Vc16VQKDA3N0ej0WBiYoLHHnsMTdOYujDL9JVZ2g2HRrNOJ6gjwsiKGapbrUuqlyDWHkB3MxiGQe9Yip7BPDV7FUURFLL9GLqBUARCwNy5CrNndhZZH/+VIxx4sH/H994u3jPi5no1Gf7wD/+Qz3/+8wB8/vOfZ3p6mieeeGLz/fPnz/OFL3yBH/7whxQKBT7zmc/wpS99qZst1aXL31NCGfLTX/1phpJD7MvuY192H3uze0mbW/+GTdXEVE380OeZxWf4/uz3eXbxWX7tLzvkGpKWJWhb0DJBKoK9ssiYlyHZ8AjWS4SN6wS8Gjrh3lHa+wZZHk7wRHyWVzoXUENQQrh//qMM1Q6hywF8LYG8jkusaVZZi81Qt2ZJ50KG+9OMpvIcSUwwrBYIKhXs06fpnHwN+9y5KC36JhG6jtB1pOchNwJulXiczM/9HPEHH0QYRjR0HcKAoFYjqFY3RjT5C03FF1DyKiyYbf7ugMf3Ks/hBNd3uaT0FPf03cOJ4gnG0mOMpEcYTY2SMlK06y66qaKbN+civFM0yjbNioPvBpFlpuPTrrt06i52yyMMJWEgURSBZqrohkpxOMn4iSJWQkdKSW2tw/JUDbcT4Dk+zYrD4qUq5cXW5nau7YME3VS5/6fGOfrYIGb87Qu0lVJSW+3QrDq0qg7Nqk2t1KRV8qmudmhcL44KEIrASAW0zWVQQnKxQfKpHnw3ZOVKHe8GQeRXdwR7ThQ58uggqqbguVEM2MDeDOni25MJeD3eM+LmR0FX3HTp8uNF22vz4vKLNLxIuAgEilC4p/ce+hNbf2mGto07O4tz7hz22bPYZ89hnz9/fdGzA1IIPMuiaWhIIdCCEFX6mELB8EKkfXMWAIBOQqc5mic5vp+BA3djJlLYszO0rkzizs4gFlcRwfZYmFKvxdTHDiIf/yATg8c4mD9IT6xnxx+UNafGS8sv8cLyC7y6+iqXKpfw5VYr13h6nMf3PM4nxj5By2vx8srLvLTyEq+uvkrL297kEiBn5jaFzkhqhLSRxtRMLNXCVE0szdoUo8Op4R1dee8FwlBuVm1em23wgz+7wPJU1LNL1RUm7u7h0Pv6GdyfRTNuT+Q1Kw4Xnl/i3A+XqK1tL7x3LbqpUhxJ0juWpmc0RX4gQSJrRu6361SXDoOQ0kKLpckajVKHMIjEXrBRLymUUTXuZNbkyGODZHvvfDzaTnTFzS50xU2XLl1uBSkl3txcZFE5fQb79OnIquJ5CFUFTYuWQUBQr8MtfKX6poZjCJqaT0eXtE2Y6RVcHhRcHBSs5NisyWIoBjE9Rs25JrU5lFguaAHoQbREsmW7N8iYGdJGGkMxMNRodPwOlyqXkG/K4c5beY4Xj3O0eJQPDX+IQ/lDOwojP/S5ULnAS8svcalyibnGHLONWdY76zd9D95gX3YfDw08xEP9D3F///2kjOulY7+7kaHkwvPLvPrd2W0xO71jKXrG0pgxDc1QMCyNTG+MXH+CZNakvNRi+tQ6M6dLtOsuYRAVbmxVrzYtVXWFdMEinjFJZA0SGZNMT4xsb5xMb5xE1nhPNYW9FbriZhe64qZLly53ChkEBNUqfqlEUK4ARK4g00AxDIRlocTjKLEYwrIQShR7Yvs2r6y+wmx9luXWMhCJkYSe4Hz5PE8vPM1Sa2nzOJrQ6Ev0sT+3n/3Z/ezJ7CGux1GFiiIU2n6b6do0k9VJLlUuMV2fJpDXdzvsyezhwf4HeaD/AU4UT9Cf6H9LE2TLazHfmGe2MctsfZa5xhxtr40d2DiBg+1HSydwaHttFluLW7ZXhMKxwjEeGniIRwYf4d6+e1HEnY3TebuRUrI22+DcM0tMnVyjXdvdxfhGQPP1GNiX4fAjg+y9t2cza+vHja642YWuuOnSpct7DSkls41ZvMCjGCuSNtO3NNk7gcN0bZqO38ENXJzAwQ1dBILjxeP0xHvu4NnfmIpd4YXlF3h+6XmeX3qe2cbslvdHU6P84oFf5FN7P0Uhdmczcu4EUkrq6zZLl6uUl1r4ToDnhTgtj+pKm9pqhzCUqJrC8KEc4yeK5AcSKKpAUQWxlEEq/87Uknk30xU3u9AVN126dOnyJsIA7Bp0KmBXwUxD8calOe4US80lnl9+nueWnuOJuSc243o0ReNjox/jFw/8Ivf13oeu3nyw7npnneeXnufZxWe5WLlIxszQE+uhGC8ymhplIjPBRGaCrJW9Mxe1C0EQ0izbxNPmjzz4+t1MV9zsQlfcdOnS5ccaKaFyBWafi8bc87B2gW29E3qPwolfgmOfhuzIj+RUIQoI//b0t/mLC3/B6dLpzdct1eJEzwnu67uPe3rvQRUqi61FlppLLLWWqDgV2l6bltei7taZa8zd1PH64n08PPgwjw4+ysODD5Mxb1wV+F1HYwWm/g40C3Lj0Yhl78yxAi8Sxok7HxDeFTe70BU3Xbp0+XtFdQ7OfxMufScKIh64CwbujpaaBatnYe08rJ6Lxtp5cOo770tPRJNgaw2Ca2JEMiMbk+RYtM/GcmTlKeyD0fdFI7dnaxCz24bS5Whf7TJ0ymBloe8IFA+Adut1YM6VzvHli1/mOzPfoepUb3n7w/nDvG/gfdzVcxctv8Vae43V9ioz9RmmalNb4pogiv05nD/MPb33bI4tLrzmKiyfgng+EoOawXXxHTj9lUhYttahNg/V2aghaGY4useZ4egeWWmwMtG/Y7nomcgwOlZpMrrPigaKCnoc9Fi0rEzDma/BzA/ZJlbjBRh7BCY+BBMfhvxEtJ8wiARKaw1qc1fPKwxg5EEYeQiMN2VHtUpw+btw8dtw+Xtw4HH4xRvXmXurdMXNLnTFTZcuXd6TnPpyZGEJ/WhC9F2YfQaWXrv1fSk6DN4Dow/B6MPRv+PFq5NzpwJnvw6v/wXMPH1z+4zlIneWZkbCqDLDjp00AYQaHfPg43DgJ6Hv6HU6de9MKEOuVCc5M/N3PFu9xKulU2iKxkBigKHkEAOJAfKxPAktQUJPENfj7M1MkLfyux6n7bU5f/lbxJ76f6FU5/iGpfDNZIKaovATrTb32zZDWoq9apxcq4LeqWxu6ykqK4Vx6mPvI77/Jxka/zC6mQSvA3MvwLf+B1i/cNPX+JYZuBtUIxI8rdXt7yt69Fm63jO6dr2h+2D8/ZGIuvSd6Hqu3a54AH7thVt6hrdDV9zsQlfcdOnS5T3Jf/lluPCtHd4QkUA59EnQrUjsLL0GK2cjEZTbA72HoedQtOw9HFlcbtZy0ipBeRLKV6KJMnAh1R9ZFpZPRa6tpZNbLT1vEC9AaiCybMRy0FyD1TORG+Na0sMwfF9k/eg/Hgmf9ED0XuBDfSGyJlRnomtbPAkrZ8BrRRN4YT/seSy6B2OPRq63K09GIm322ciy1VyJLFOFvZEVpTwFyd7ofhQPwPolWL8YHeNNfbQcVccMtnfwDoEZXSMfhGTCrdt4QFMzyPnX3JdED+GhT1JWVaZxWTfi6KpJrF3Caq6ht9YRTh3VaWF6NnHfIeF7JDaOXUoWCYsHyMQKmEJFBB74NoHbxLEr1KTP2eIY6bv/Ifcc+Fk0ZSOrymlGVrsrTyCnnoDZ5xHh1usJhIpMD6LlxiMrUuhHFqD6ws6fi/7jkcXmwOMweC8odz6brStudqErbrp06fKe5KU/iATLG+4IoURBvwd+EpI7ZDv5bjRJ63c+y6bTmKIx83XUACy9iGkOoPXdha35rJf+jtL631Grn0TXc1jmAKkwS7ZUJ7lwBXPhLMLfXgE5jOcINR21WUKEN1k9FyDRC2YqEmS3y76Pwb6Pw2v/ZcMyJiHRS+f4L3DaKfFcbZLzwsbqv4v9vXczEO+ns3KK9NwLjCyfZ6yxTvoasdMQgu+nMvx+/zCr0tvSE+1mEFKiAv41lpGYFiNtpKk5Nexge2HIYqzIR0Y+QiADynaZkl2i1IkGXptsGOIj8EW035YQCEXl0cFH+bk9P8dh6zBrK6usXnoBdfY5elsXSBoKjd4HEAcfZ9+9HyCRSNDxO8S0O1uZ+A264mYXuuKmS5cuXa4SdYJ28P36NaOJrmexrCF0Pb+l5k0QODjOIp3OLOXyDymVf0CrdWnbfnU9h+dVtr3+ZpRAkq17JJs+yVZAshUtr3VwhAK8RAqZGYaegzD0IMboh1CKB6C+GAmQi38DF74ZWWsgshT1Ho1ihY79fPRvpx5ZaFQjsuC01mDhlciK03MwsuLk9161GkG0v9IU9B+7aWuXDENWV17j1PTf8hcrL/BM9dwWl01ci3O8eJy+RB8dv4OmaFiqRUJPkLfy5K08CSOBoRioIsqeanktXll9hZeWX2Kytl24ZcwM9/fdT87K8b2Z71FxovugSIW0mybrZAlFyHJ8GVd1SepJhhJDjAaj5N081XKVTr1D0ksSC24sVkIRspxY5nLqMt/5x99BU+987Z2uuNmFrrjp0qXLu50g6NDpzNGx55Chj65nN0cQ2HTsOTqdWezOHJ5XRTcKmEYPhtmDafQikdiduc19dDpzOM4yMvQIpYeUwcbwkNJH7lLgT1EsLGsQVY1j20t43k6NExUy6btAKLTb09esI8ik76ZQ/DD53CMEQRvbXsS2F+jY89j2Ip5XwfOqeF4FKSNXialkyDlJDCVFWSzRFNVt8Ry6XqC39yfp6/tpspn7EEKJAmMn/w6ay3DkU5Hr7F1AqVOi5bVwAgdVURlLjaFep//YzeAGLguNBZbWlnArLkE7wNItNE1DCEGlWuHS4iXKpTJhM9wSHiOEYGh4iFQyxdTUFI6zc98wR3Fo6A1KVomyWaZm1Eh5KfJOnv52Pzk3t7nuZ/7hZzgyceS2r+dm6YqbXeiKmy5durwbkVJSqTzDlen/D9Xq8z+CM1DQtDS6lkbV4rhuGdfdIRAVUNU4pjlIJn0XhcIHyeffj65fFRK+36DTmcU0BzCM/E0dXUpJELQQQkVVY9e8HlJvnGJ9/XvUa69hO8vY9gJheNW1E4uNMjT4Ofr6P4UiNIKgja4X0LTEbd6L7bRaLTzPI5VKoap3rhaNba8yO/u3LC0/R7WyBGIUwQiOX6DjmLQ6NiJwqayvXVeYvJlYLMbAwADtdpvl5eUt78XjccbHxykWixQKBQqFAulcmpZsYWomcS2OqZrYgc18Y575xjwAoiFYOr9EdW2Vz/+jzxCLDex06LeVrrjZha646dLl3cHi4p/T7sySTOwnkdhHPL4XVd0eH+J5Ver116nXX8MPWvQUP0Ymc2/0S/1HQBC0gWiC341osm4Shg5CqAihoSgWiqJvW69cfpor0/+OWu3lzdc1LUUsNoqimBuWjWgoik4sNoplDROLjaDreTyvhOus47iruM4aEkksNkzMGiEWGyUWG8GyBlEUa/NcNoeioqlJVDWxreVCGDrYdiQmgrCDL3t4ad4gkElOjGQZLySu24zxThKGHpXKM6ysfJPVtb8hCJqstQt4oU7OquAFOhnLJpO5l1z2IXQjTyw2SiH/GEJcX5hIKXGcZRxnZcOSNMblyyucO3eO2dmoarIQglQqRT6f5+677+bo0aPoevRMax2PybUmDdtHEdBu1Lh88QIVO2Rd7yWbSjKQsTA0BSE7BO15astX8FolNK+FbwfYHR0pb1I8iZBYMiSbTeGLIh1XJQwCrESKVCZLPp9noL+PgZ48xaRFzFCpVqucO3+BaqNFojhIW0+zWHXww5DBbIyhbIz9fSmS5nY3kxeE1Dseaw2HhZW/w67+F8zgRUZHf4UD+7946w/yFumKm13oipsuXd4dvPrqP6Rc+eE1rwhisRESiQPE43twnGXq9dfpdGa2bWtZQ/T1/Sz9fT9DMnnwjp+rbS8yv/CfqZSfodE8g5Qh8fg4yeRhDKOAlAGB38JxV3GcNTyvjO/Xtrl7FMWiWPgwvX2fJJU8wurqN1lc+vLmNSqKweDgZxkd+SdY1uA2sSFlCIh3rDGiH4ScW2rwwnSZvzu/ynNTJfzw6pSRtjTuHcvxgf09fOhgD3uK2wXSnSYI2vzRk9/mS9/VCeRVwXtf36t89sDXKMSuxv3E4xMMDn4W256n0TiLZQ2STBzCDxrY9gLV6ovY9jK1Wh8L84cpl4fhmugfiUSw9fpcNNoJnbUwzXQtjS8VevUae5QKea5aVgIpWFMsssU5DhUu0FgboVQaBnYQ6SIkUCS21NF0m1SsRj5ewjLaaJqLqnnE4zXi8SqKcvV5zNaHOLl2jNfWjjFTH0FVAvJmlZxVIW9V6U3UyJlVBC5+qBLIjRGq2IHJbH2Eydo4LS/BaD5Of8ai3vGobQzf7/DQwEt8fOxJhpJRTaBQCvr7f4HjR//tW3ySN6YrbnahK266dHl3sLT0l9TqJ2k1L9FsXcL3q9ddNxYbI52+C4HC2vp3CYKr3ZY1LY2qxlHVGIoSw7IG6en5OD3Fj29xlbzxVXejyTcIHFZXv0WzeQ5VS2Lbiywvf20zHuROoKoJBgd+ibGx/w7T7Lvt/azWbabWWwxt/AJXFEGp6XByrsqTF9d4ZbbCWD7BI/sKnBjK0vEC6h0PXVMYyFj0pSxmy21enC7z7FSJ5yZLNBx/yzEO9CVJmBpnFuu4/tb05760yaH+NAf7U3zwQA+P7C3ccbFzZrHGJ/+XqBaPrgq8NzWfPFKs8mDfAro7Sc5YphgroQiJabaJxeqboTyOE2d9bZSVlX20WlfjSdLpFYo9sxSLsxhGG8eNM12eoFLpJ6gWkP4uhfuQZLPLeJ61ZZ/XkkxXiKV8bCXBgpPhdG2cnuIEx4az7O9NMZqPM5KPUUyodNoXaHemcdwWS9UKC+Uyi5USCXGGkeQkirh67V5ooCu7N+u8HsutXiar45TsPAWrTE+8RDG2Tt66msLvBhbTnY/QVH+e/9NHHyNl3XwrjNulK252oStuunR59yGlxPNKNFuXaLUu025PYegF0um7SKePo+vZzXWDwGZ9/Xssr3yDUunJ64oOIXRSqSMEQRvXLeP7VYQwMIwiplFENwroeg5dz6JpKcLQxfOqrK5+C88rb9tfLvcwAwOfJpd9EEUxaDTP02ycxQ9aCKGhKiaG2RsF9hpFND2DrmVRVQspQ6T0abYusrryTVZWv4Vtz5PNPsjgwKfp7f3JG7q5rnffpktt/uzFWb5xcpGl2tWU4IShEtMVaq0OHiqws8gw8MmJDlVp4bB9gkpZGveP5Xh4b4GPH+lnTzGKY/GCkAvLDZ6dLPHExVVeuFJ+k7CQPNYPHxkWHB7pIZtJk0wmSaVSJJNJVFUlDCVrtSbSaVGr1QiCgD179hCLXT9bx/d9Ll26RKlUotVq0Wq1OD27ThiGjBdieJ5Ps91hvdZE+i6GCK+7L10XZHMetqvQqF61oPgoTPp54sUlPnX4G8Q0h1jiCIqATuvUNfdfUCoNs7p6GM8VhKFKEGioqkdv3xLF4kVMM3JjNps5Vlf2sbZ2gDDUOHHiOO9736P09vZe9/xuBdctUyo9wfr69ymVf7D5A0BRLCxzAM3oRyq9aHofMSOBrgYIsRFYHnq4Xpl6/STt9pVdj2OaQ4yO/CMGBz+DpqXelnO/WbriZhe64qZLl78/+H4Dx1kjCNsEQYcwaFOvv87q6l/TbN1+NVjT7Ken5xPI0EMSMtD/C2Sz979t5x2lX3dQ1ThSShqNxpbRarUwDINYLEY8HieZTDJZh5fnm5SbLtXKOp3KKnajiu2HhAjCDfdGytLpOC5Z2hSVFpbwcYWOlswzMDBA3VOYLDt0GlV6qZEMmwiihJpSGGddyVEsFBnPm4xldXoSBocPH6Kvb3eLUsvxOb9c5/xindNnTtOcO0dBtHZcVwKeMCAMMMSbXXcKExMTHD58mJGREXRdR9M0Op0OTz33EmdPv07gbq/rshuhUPAVk04gCDfcainhoF0jfKSEVZlkOsgxGRTpyab4b983ymfuGyQXV1HVKA3cthep1V7B9cqEoUM+9wjJ5BF8v8ra2ncJpU+x8GEsa2Aj7qqN55Vx3XVisVE0Lbd5nXeKMHTodOYika1lbsl65nkVarWT1Oqv4rolYhuxXVZshJg1gq7n3nHX4xt0xc0udMVNly4/HrRakzRbF9C1DLqeRzdyhIGD663jOuu47jqeHwXp+n4DRTFR1RiZ9N0Uix9DUe583Q6IhM5vfelLhMGNC9W5G4GmbxYEb5VUKkWj0dh1nYmJCd73vvexb9++HSdm13V56aWXeO6556jXN3pXCZUFsvh+QFx4xIRHHG+L+wTAlhpNaWCpkqS8cYG7ltRZCtP4wiCVSpJJJkjGdGbLNldKHRyp4EoVF42O1PBQ2VNMoilwaTUSXAJJVnToUZoALIY5egpZxgtxjg9lePxYP6OFxI6BtV1+NHTFzS50xU2XLl3eDTh+wJMX1vjyi7NkrnwPlRBXGmiaRTqWoNW2CX0HXfgowkURV91vQtVI5nsZHBggmzAQUhIEwYZFKERRFHp7exkaGiKfz1MqlVhaWmJ1dZVOp4PjOCSTSfbs2cOePXs2xc3U1BSTk5PU63Usy8KyLDqdDhcvXtyMWcrn89xzzz2cOHGCTCaD4zi8+OKLPPPMM7TbkQsmkUjw4IMPcv/992NaMV64UuZvzizT8QJ6UyYFU1K0JMO5OAO9Rb7y2jJ/+MNp1hoOadFhTKkwplZICQcViUqIBJZkBic7jpEf5OXZGpX29eOgEobKBw70kI3r/NVrSzQ3YocUARPFBClLRyLxAslCpUO1s31fQsC9ozk+eriXjx3uY39v8o5YLUIZ8tVLX+XLF7/MQwMPcbznOOaGpehY4RhZK/u2H/O9SFfc7EJX3HTp0uWdxK/Y2JcqBCUb1/ZZLLVZXm8T1hx6pKAHgQLbsnC27YeAhugQCkkxW8DIxRCaApqC2BhKQsPck8GcyKC8jRaHarXKCy+8wMsvv7yltsr4+DgrKyt0OpG1JZfL8f73v58TJ05spkffDDKUuGHI355dpeX6JAwNRcB0qU255TBRTHCwL8mhwQxxI7quMJRMrjW5vNpkrtJmueZwoC/Jo/uKDGQsFCE209Rbjs93z66gKoLH9hfJxrcGAUspubLe4uRclVdnq7w2X2Wu3N4mnopJg0P9aUYLcfpSUUp3b8pkb2+SfNwgl9B3DKyda8zx7OKzzDfmKdkl2l4bX/ok9ASqUHlx4TQziwNIP4WaPI9qLuE3jhJ0RhBCMJxNcKxvlIPFPUyt16jYFXpSOmvVGD1Jg/50Eksz6O9ZZcWZwZC9nLyUJ2NkqHck6606Hz6a4LP3HOVM6SznymdouDVeWH4BVaj88qFf5qOjH0VX9c37cal6iZOrJzmQO8CJnhPUnTpCCDLmj64wYlfc7EJX3HTp0uXtYqcMrKDl4U7XcCZrdC6UCUo3jg+RAhRdBU3gAI6UaDGNVNpEi2kITcGv2PhrHQLbZ9oNmXZCAqIwYQXQhMAQYAiIq4J0TwyZt1ByFomhJHvv78OM7S54pJQEfoiiCNp1F0VViKcN7JZHp+ESz2mcPXuWkydPMjNzNUU/n8/zgQ98gOPHj9+wwF1o+7RfXcWZquFXHYKKTdj00PrixI4WiB0poA/dnoXE9m1qTo2O38EPfUzNZCg5hLJRE0lKSctr0fE7CCEwVTOykISghgp4IV7g0QlsNEWj0hL89fk5vnLqEpdXVYJw9zgZVRH8zIkB/rsP7KU/7/Ps4rP8xcW/4OWVl7esJyVIt0jg9BG09uHV74Hw2hpPITumiN8I4aAmpgjae960vw0UG0IdoXbQUmcwer6DokVuupgW43jxOL3xXk6unmS+GRXrk6GGIQu4oozwergr/XPc3/t+8rEUP3G0n770ne9d9gZdcbMLXXHTpUuXt0L9e7N0Tq0TtDzCtgehROgqQldAFYT1m0u/DWIqib1Z4seL6CNp1ISGMNTrTuphKLnw3BIv/tUVGpWbq0x7LaqAnpiHQZOO7VMTOay4xoGHBhg+1MPqK6u89tIqLXdrdlEyZ9KquchQMjCgcCA2g9JuYAyYzBkamd5ejt57H0ZfL+I6QbJSSvy1Dq3nlmi9vIJ0do8ZUtIG1t4s5kQGc28WNWcinYCw5RHaATPVaU6vnWaxuchie5E1Z401t0QrbOGLgICQYCMu6ZA/wcPePRxpTjBQyyMkeCLAFz6BCDFDA0vuls4dYSOZJGCakMuizaLaoSYc1oFKYOFJnVBetdoo5jJq4hJCbYJXIKMNktDT+L5FtaHRtLfeqz3FGHt70jw3VaLp+OwpJvjEkT7afpPTK/PMV+vUOjbJhE1Kz1BrGsQTFTquwPEkjp0icAub+7MSSwTGFEJx0RWTTuUuQj+BKuGgpxIC9YzHIw+u89zaX1HxlhCKjVAi953qD5HsfIKFpVHkdXpNCRHyyaOD/PNPHGRfb/KG9/Ct0hU3u9AVN126dLkWKSXulSu0X3iR9osv4s3PI2IxlHgc5Y1lPIaIxxFC4K33E7o3X2peWALFdCGUqPk8SIG70IRgh69eBYSpYgzFMcdjGBMpzD0DlBdbfOf3TuGsdYgpAiWhcehjY/TsyxD6Et/xqD//MuUnn6NdamInh7DjA+iagaYnqaHRuH5G9M7nTVS07o0UciFD5DVVoS27wuj6yxhIUkGblPDQskWUZAYlnkJYSYSRAuJIX4+6X26g9cSI39dHkFP469J3eL7+Eh+SD3Nf7RDqlIN8k8DaTOf6ESJFdDcUeX2L0lk8/lA0eUEqBDdwM5qawolCkkOGxQN9aT74wVEyPTFsL2C+0mGieGvVn6WUvDRT4cXpMncPZ3loooATdCjbZQaTgwSB5G/+9hyrT1bpVK4K8IaQOBvDFeBaAaUkvN4O8ZE8Zusc9FQaQtJWJbriEuKihgZp30IAn/qNBznQd+fTwrviZhe64qZLlx9vZBjiXLpE+8WXaL/4Iu2XXiIo7dQMcmeU9BDCzCDdJtJtQhiAqiNUA1QdfBfz+C8RVC/jz58kbCxe3TaZJPvZz5D93D/AW3RovTCDt+QhA23HtgBShsjWCiKeARHbbtVRJUJx8Feu4M29ir96Btla27qOEGjjx2mOfYC2NYwjUhioZFRohLDkhrRDiUXAhLdOXlfQkn2wIWR8GQXWhhIWvZCKL6mFkkYQOU/eIK5AUhHoItIhmohcZW4o6YTQCSVB6GF4DeLUkUadGV5jMn2ShbzHch46pmAsPsqH5PvYVxklv1IgUU+SUxQMReAIF1e2Uf0AwwclCKOTExpC1UDRQCh4KNRCBVeC6rcQ/ipto0IpYaJYE9RbcRx3Qy8JiaIqCDPA1tuk0jH27R0hNxRDKXo4tkvaL9CuuTgdH6/l4dYchB1gITHdAL3lYNRd1I0QnQaS5/B5FR8HGESQVVSMpE7a0FE64NQ9Wo1rYnoEDB/Mse++Xvbc1UM8fWNr0vVwbZ/aaodWzaFVdVierDF3vkKrGln8EhkDPaFTXdw5Vf9W+Se/+wGMG7g83w664mYXuuKmS5cfL/z1dTqvn6Jz6nXs10/ROXWK8I1U5Q2EaRK76y7iDzyAeeAA0nUJ223CTpuw3UZ2OoStNlKGqIkEIh5HiccRuo6/vIw7PY07M4tfLhNUKnBNWrdaKGBOTOCXy7iTk9GLigLhm6wTio7Q44hYFq3vGNrA3ajZsS2rSN9BdioIM4kwdnYDKCkVY9hCKBLpA6qJ9EHaPtINCN0Q2fEJ3WBn69Et4EqJLaHmS+qBpBFImqGkfU0jal1AWhHEFDAUgSkgrohrhJBEhj4SgQSkiKKI2iFUA0k1kNQ8j2T5NMMLz5BqzqF7LRQZEGo68u73Y/ftp9bRqXoJ6mRpq+980KtQBMmMQSplkLBUEqogHkj8ukO77mIHkiUvpPWmx56xVIyUztraNbFZAvr3ZBg7lmfkcIGesdQNrTi+GzBzusTFF1eYOVUi8Leb6jRd4a6PjnDv42MYlkan6dIo2bh2gNP2KFVtLl2o0JhtIGseYSDJDyZ45Bf3EfohTttH1RWEECiqIJW3SBUsrMSdr04MXXGzK11x06XL3w/Cdhv73Dk6p07hTk4R2jbSdZGOEy1dF29xEW9xcdu2Ih4nfs89xB+4n/gDD2AdP45i3P4v5WuRYUhYr+NXKqjZLFout/l688knKf9vf0D7pZcAMCYmiN19N9bhwxjjYxijo2i9vQjTRCgK3nqT9gsXcOen8GbPE9bXCRp1wmYLYcZR4nmUWB597z0IYwh37jrurptAWCrmWBpzbzaKc0kZBHWHoOYS1B38so231CKo2gRVF7nD5Ll5D4DQVJFSor3ZxXSbtENJLZBUfcmKH9IWUb+m8JrrzajQoym4UlJLGcTSOk69g9v28NyQVFgl27hCauF1jNrSxoVDqOj4WhxPi+OYGZrpMZq5CZp6Hk2ExOOQzBrE8kn0ZAxVVwm8gGbFoVG2aZadHcXETqiqYKTHYkgRZFou+oY1rhVIFiQsB5JKZ2tMkm6q6JaKogoUVUERRM9ZgOeFuHaA96Y4plhKJ5E1SWRM8oMJRg7nGdibQTNurilnGIR0Gh7xtIH4ETRH3YmuuNmFrrjp0uXdg/R9UK8fRAsQui7+4iLu/ALu7Az26TPYp0/jXL683fqxE0Jg7J0gduIuYieOYx0/jnXgAOIWUpXfbtz5BdRkAjWbfVv3GzoBzmQVZybqmSRMDcVUEaa6uRRGFPysvPFvQ4kCom8xviNseQRVJ8riWu3grbTwVtr4JRveNNGrWROtGENJ6ChxDS1rovXEEXGN+loHp+EifA9ZrSCrJWStiq5YKGGCsGMQtrefWyeUlHxJCyjENbJSol0jdNSMQfKRIWJ3FdGyWzN6pJQE1Sre3BzOzBze7DzOdJWgHiOoVghKU4T1BfzWGiJwt0TPCF1HzeVQ83m0fA41l0ctFPDSfXRiRdpqmpZv0WgLmo0Q1dCIZ0xiaYvesRRj+zIoDQ99KEHY9OicL2OfL+NcqUU+wI1rW/ZC1nzJmifZ2t3r+sQUGNIVhnWFtA5aLoaWMxGmhtAEQlMIO3703KoO0glQYlr0GVAEKAIlrkfPK2tuPjdjKIkS3/73Ir0AFIFQ71y15Wvpiptd6IqbLl1+NDiXL2OfOYNz+TLOxUs4ly/jLSyArqMmkyip1OZSSSQIKhW8hQX81dXr7lPr6YnEyqFDKKkUwtARhoFiGAjDQM3lsY4dRU3e+UyOLhFSSsKGh1+Oat/ofQmUtxiPEXZ8vKUW7mITZ6qKfakK3nZhK0wVcyKDt9AkuCZrzTqUJ/P4OGrOJLQDwoaLX7ZxZxt0Xl/bsu6brgaEjbTX8Jdexz711xDcegNVYWUwDtxL7K5PErTSG5neAmM4SexED9ahOM7FCyiJPggTuIvNSCiutvEqNq0wMtRIJGF0VoiYDlKi2gGaiNx/htgoS6CKt+xyfDNaMYbeFye0fYKGS1D3kLZP8Z8cx9qbfVuPdT264mYXuuKmS5cfDXP/7J/R/Nvv3da2IhbDGB5CHxzCPHyI2PHjWMeOo/e9PU0Hu7y3kH6Ic6WGO9fAW22jF2OY+7IYwymEpiC9kNYrK7RPruFO124q00pJaFiHCghDwVts4a20kPab+l7FNZSYgpoBY8glqFfwSy2Caouw4RN2QoLqLN7i64SNMkrmMOahn0OJ5990ATaIq9ak0GngTX2fYO08xp4+Uj/5ETI/+ThaoUDoBPhrbbylFt5yi7DtEztexDyQI6w5+HWXoGIjgxChqQRVe/P81ayFPphEzRqIQCJ9ibDUTcuMMDWkvRF/FUoIJUEzssi9Yd3xVlq71mqK39sbZQIWYmQ+Pnbd9d4OuuJmF7ripkuXHw2l//V/pfnEkxj792Hu34+5bx/mnj3IICCo1wmbTcJGg6DRJGw2UbMZ9KEh9OFh1Gz2R9asr8t7G2+tTe3b09hnNjLiFFASBlrOROuNEztcwNyXRTG3xqJIKQmbHt5qG2++QfOZRYLazdUwgsgttrm+AGH4BOuX6bz8l4TVGUS8gNZ3HGPfx1ESPVuP7dmErVWgCTgIdaMKtWUhjCyQQvpmVP3xJhBGQOL+QeL3DaIPJm75b8lvujjnSthT9avuyFJni3VIH0jQ93+595b2e6t0xc0udMVNlx8XpO8jtHe26Z8MQ8J2B6GpKNY7V7l0N7zFRdyZGYy9e9F6eroi6ceU0A0QAlCV2wqQlX6Iu9gkbPu0XlzGPltC6Cpq2kCJa6gZEyWm4czU8VeiHltogvSHRkh9cBihR+LJvnCR6l9+GefSJazDR7DuuhslPoF9sY230iSse3CDGjmb5xS4SN/eWF9AYBNUZwkr04StVdTeI+hD9yP0+OY2SkJgHcwgtFW8hfM4F87hnL8AUqKPjKEPnUDJDCOsLAQ6oSsImyB38MYJU0EfjGEMJTDH0liHe+7od05X3OxCV9x0+XFh8X/8H2l87/tofX3ofb1ovX1ovb1ofb2omSxhs0FQqxPUagT1GmGtRlCrIz0PsRGzEg19M4ZFul6UIn2dITtXOzqrxSL60CDG0HBkgRkciIrjGUaUDWSYKIkE5t4J1Mz1U3dvV6R1zpyh/L/9AfVvf3sz8FjN57EOHcI8dAjFMvFWVvBXVvFXVgjq9Y26+BKJRAgFfWQE88B+zP37sQ4cwBgbQ83nETu0GIh+6TcJymW0YhElkbjlc+7y3kEGEqHuLEKCpou32ELrjaNlzVvbrx/il23s83O4MyXCtof0guhvz3HBrxN21gjrS4S1JdRCAX1wEH1oEH1gEKHrSM/dzBh0ZuZpPnUBYe5B6zuO0K5mBYbtMv7ya4S1OdTeI2i9RxH6ztWIZeAR1mYJKtMbY2pbTaXsL32agd/6rVu63luhK252oStuuvy4MPP5/wPt5577UZ/GTaENDGAdOBCJjngcd24Wb3YOd3YWf3kZJZOJUqXHxjDGx9EKxY0vbydKAbdtgmqNoFolqFTwSyXcK1c2968PD0cp4TeTXXUjhEDN5dAKBdRcjrDdxi+VCEolpLvhhtB14vfeS/IDj5F4/2OYB/bf0GIkgyCqlbO2RlCpRNdSrYIQJB56EOv48R1F1XX3JyX+2hru1BRqOo25bx/ibUp3vxNEGVhtwnqNoNFAaBrGxETX0vY2IKWk8/LLVP7yG3ROLqD2nEDrP4ZQdvg8KB4EK4SNVaRdI3QbSLuMbC1Hosn3o+F5mwLqjbpOuf/mv6H/1/8fd+w6uuJmF7ripsuPC0Gzhb+6gr+yssVC4a2uENYbKOkUajqDmsmgZtKomQxKOh398nOvfnFJ1938JSh0fbOAXTQSKIlrl9GQto27sIA3v4C3sIA3P4+3uoJ0NurQOA6h6xLUqviLS3fmBqgq6Z/6KQr/x1/BOnSI0LZxLl3CPn8e59x5ZBCg9fWi9/Wh9fah5nKRu0JEQ3o+7vSVKLPr4kXsSxfxl5Yj684uCNNEOlt7P2k9PZiHDmGMj0cibXwcNZON9nv2LPaZM9jnz2+xfL0ZJZMh+egjJN7/GIn3P4reezWY2q9UNjLQLuFcijLRnEuXCWu1q+el65gHDmAdPYp15AjW0aOYB/ajmLdmWbhVpJR48/PYZ87gzs0RVKoEG8UO/WqFoFIlrNcJGo0txQ8BjL17yXzqU2R+9mfQ+/vv6Hn+uCA9L/oMCw17sop9toS32sbck7natPQW3XYyCCKRI8QddUd3xc0udMVNly7vLoJGA+fiRTrnzmG/ehK/tI6ayaIW8mi5HGo6Q9Bo4K+u4q+v46+tEXY6UX0NRY3ECERWDVVBzWSJ33sPqccfxxwff1vPVQbBpmUoKJXwyxWURDyy4uQLaIU8wrLwZmZoPvU0zaefov38C0j7xp3BIcoK0wcGULPZqJZKNkPYaNJ67rltVZXNQ4dQs1mcy5cJ1td33qGioI8MbwqInd7XenvR+/vRBwfQ+gcQmoZ0bMKOvbkMHRvZsTdF6WahRMdBmGZU8yWXQy0UNmu/BNUKndOnsc+e2yKyboiuo6bThM3mVZEoBImH30f6kz+Ndewoxvj4HRdldwIZhniLS4StZmRJuwVL3E0fw/dxJqewT5+ORPOZM4SOgzEygjE2ij46ijE6hjE2itbXt9nsVEoZPd9OJ/ohoyigaQjdQOha9MPmOo1R3ym64mYXuuKmS5d3D9J1Wf7Sv4msDZcuETabb9/OdZ34PfeQePRREo8+inXkMATBRluFyEIitI0v7Y0lun5bbhC/UokEhqpGE4CqbogtFaHruJOTOFeu4E7P4M7M4E5PE5RKmPv2RZaUo5ElxRgf3zmex/fpvH6K1tNP0XzqaezTp7dZkPTh4atZaAeipTExgWKa11hPNqxEG9aioFq9rVt7y+h65Hbctxc1X0DN5yIxlMtFQi6dRklnUNOpKCNICIJGg8bf/A21r319s6LzJooSTdb79mHu3Ys+PLQR1zWIPjj4tgmf0HE2rUxaXx9aoXDjjYCw08G5eDF65lemca9c2WjRMbMp2NSeIqmPfpTUxz9O4sEHb6uopAwC3KkpOqcjEWOfPh1ZAG9WTBsGSjy+6drdFU0j+eijZH7hF0h9+EM/EhdnV9zsQlfcdOny7kFKyaVHHo36MUFk1o7HI5/+m1w76DqKZSEsC8WykL4fpY+3WlEsjaKg9fSgpFIEpdLVfd4KioI+MIA+MoI+NIjQdGTggx8ggwC9vw99bByhqXizc9jnzmGfP4+/tLtrTS0UonihN8ZG/JCIx3HOnUcfHMA8cGCLSV9KibewSPulF/GXltD6+tEHB1Fz2aiT+eQk0nEx9+/DnJi45QBmKSXB+jre0hLe4hLe0hL+8hIylNF9jlko5jVLy4xeN0yEaaCYJsIwCG37qjWrXCEob1i0YrFIuB07irV//1uaDN25OWpf/watH/4QZ3JyZyvUNWi9vcTuuYfEw+8j8fDD6KOjm6J1U+idPYdfWo8C6au1KLC+FsVt+eUSQam8TWxrvb2Yhw9hHT6MdfgIWm9PZO2wbby5+U1LiTM5ed34LqHrCF0nbLc3X1MyGVIf/jDmoYORNVJRoqq/QgFVQToufmmdoFSOzm29hF8u46+u7ihKlHh8QzQfxTp2DCURx5ubw52dw52dwZuZxV1YAP86tY81LXIRXkceqNks6Z/5GbK/8PNYhw/v+izeTrriZhe64qZLl3cXlT//c5R4gtbzz1H7iy9veU9JJAhdF7wbVIXdqRHlO4zQ9ShWZyPjCoiWb4ojuf4OBGpPEa3YA56HOz+/awwOqoqaSqHmciipJIoVI2g2N4ORpe9HLR7yhcj1NDiIefAAife9D3P/1gDnSEgt4Jw/T1CtYh0/Hq3zI3ZD7MRmoPTkJM7lSdwrU1F818IC3uIS8hrR8Aba4ACJBx7AL1ewT526NYvVhpssKJdvGG91LWqxGFnP9oxjjo9j7NmDsWcP+uAgBAGt51+g8d3v0vje926pK/2bEfE41pHDxI4ei4Tk0WMY42M3fHbS9/GWl5GOs+VHg7CsTeuhDILN4GF/eZna179B7etf31I1vPBP/gm9/9f//rbP/1boiptd6IqbLl3enbSefZb6d76DuXcf5r69mHv3ohaLsNEHyF9bi+JuVtfw19ZQUknMPXui7Kn+frzFRexTp+icOo197ixqMoV15DDm4cPoAwO4M7O4szNRUPXiUvRLdm5uZwGhqmjFAmqhiL+8HE1st4lIp9GyWULHIazXdxcs7xDCNFGLhSjA2/Mi69ebfsUrqRTxhx4k9bGPkfzgBzcbgF4Pv1TCPnc+Ch5fWcZfXomsZ1rkmlOsGLG7TmyzpLydvNEzyr1yhfbzz9N65lnaJ09uE8dC1zEPHtyIb4qC6pVMJnKRZTIbMVR5tEIhaushBGGrhX3hIva5szjnz2OfPUdQr6NYUVkDrVi8aqk6euyG1bP9SoX2c89FgdSAc+lydL/CABmEEIbIMFoKXY8+jxtxXWqhgFYooBWL6MPDdyR253pI36f2V39F+T/9Ec6FC6Cq7H/yiZt22b0VuuJmF7ripkuXLm8gpSQol3EuT9J5/TU6J1+jc/Lk9l/Suh4FtP7ET5D8yEcQQtB5/XWCSiUKsHXdTaEgPY+w08Y5d472yde2WRKEZRF/8AGSH/gg8QfuJ6zXsScnsU+dxj57lrDdRknEMcfHiT/2GLFDh6JzdV2UZBK1p4dgfZ3Gd75D84fP4K+tRjWG3Kg+kZpKYR09glYo4K+uRe6m1VX8tbXtrr6duI4VTFgWai63EXw8CKqKtG3CZhPn8uVde4C9GX1wkNjdd0dxMhs1kJREYtNlIzQtOg8RFaeTbhT74pcrBJUK0nWQfhC5DEOJdeQIycfev2PcSthu0375ZTqvvopaLBI7fhzz4MG3rQv8zRK6Lp1XXqH1w2doPfMM9tmzWy1Buo65fx+xo0dR84UoDkxTo6BeTUe6LmGrFY2NulJaIY+xZwJjYg/mxARaf//bIho30/LbLWS7TdBoYJ89t/k34k5Obll/6H/+XdKPP/6Wj3sjuuJmF7ripkuXLrvxRqxL57WTOOcvYO7bS/LDH0a9je8L6XnYFy4SNuqgqCiWiXn48Ds+scJV11P75Zdp/t0TBJUySiKJkkwiTAN/YZHOqVOEG5aE20EtFtF6ejayvbKoqVT0hhBI28a+eBHn4qXrx3q8BdRcjvQnP0nmUz+LdezYLU3yQa2GMzWFO3UFv1RCHxrctAoq8fh1twtt+6rgeNPwlpZx5+fw5uYjK+Hi4jYLknngAFqxgH3mLMGtZJRdBxGPRLF54MBGuv8RzIOHUJNb47Gk5+Gvr+NeuRKVR9gI6A/W1gmaUfuTXd28ihLVcfrYR0l99KMYIyNv+dxvhq642YWuuOnSpUuXnZFhiDszA0GAsGIopoF0XexLl2g98wzOxYu4V6bx19becoyTME1ELBa5VN7Yl7LRRiAMo0rRG/FLQtc3U8zVXC4KvFZVkJLQ7tB+7vktAeRqoYDe34daKERlBTKZKE5nbhbB1VpGSIm3vLxrzIs2MED8/vvJfvYzKKkU9quv0nn1VdqvvIo3N3dL16wWiyQeeZjko48Sf/jhzVpFbwjqqN7ROcJmC+l74PuRhcr3I9deYqOeVCKBYsXwV1dxrkSizJ2d3Vk0ChG5bvv6ovIF6+s3H2yvKJu1q4y9E8RO3EXsrruI3XP3Dd2Ud4KuuNmFrrjp0qVLl7eGdF2cK9N4iwuR22tpCW9hkaDZgCAEGV6NG3mjkq3nErou4UZm0m6IeBxzYmIj7qpAUK5EWUIbVZvDalTF+O0MIldSKbTeXpRkAn91bWvF6VtB01BMc0OIJFCSCZRkCjWTIf3JnyL10Y/ekUBt6Xm4c3M4k5M45y9E6f5nz+KvrOy8gapijIxE5QP278c8sB99YAAllYrcn8lkJD7fRRWiu+JmF7ripkuXLl1+tERumyW8xcVoLCzizs1FGVDT0zfOjrsWVUVNJqNJOR7Hr1ajmkPXCh9NBf8ms9ZuA2GayCC4KXebefAgxX/6T0l94uNvi8jxFhZw5+bwV1ejSuSra2iFPOmf/mmM4WH89XXss2cJqtUoELnYg9ZTRM1m35XZcLvRFTe70BU3Xbp0eSv8+5P/nsXWIuuddcp2mYHEACd6TjCYGEQiCWWIRGIoBmkzjaVazDfnmapOsdJeoe7WaXktVKGiKzqBDKg7dZpek4P5g3z24Ge5v+/+d9Uv5neSTQvE5cu4k5PRpPxGllAuF7ULyWZR0mnU1NWif1v2EQT46yX8lWWURAJ9zx7skydpv/gSyBC46pYK2+2oiWzjaqyJ1tuL1tMTLTf+rVgmjR88Re3P/xxvbY34PfcQf/BB4g8+QOzYMVAU/FIJf3k5cnVVqxAEm4HP/vIK1S9/ebN2jrFvL5mf/RSKZW4EDUfVgI3xMayjR3eMy9qsffTii7Sff572Cy9EPdOuQ/zBB8n8ws+T/sQnQMprUuYXEZoeFVPM51FzebTeHtRk8uaeURBEsUXNJmqx+I7FkHXFzS50xU2XLl3eCh//8sdZbi3f0WPsy+7jMwc/Q0+sh6bXpOW16Pgd7u+7n7t7776jx/77ghu4tLwWaSONqtxeqvRsfZZvT3+b9c46uqJjqAaGYmCoBsVYkcHkIIPJQfrifZTtMq+uvsrra6+jCpW+RB/98X4SRoKV1gqLrUVGtB7u//4itT/6ky2B2yHQjMFiHuZ7BJeHVC7tMXHiGu8PJ/jATIKxMyX86ZntdXw0DWNkBK2vD70vEmL22bO0nn3uajaWpm2xKrUNePqo4MUDgoEy/NLTIakOqJkM+vAwWk/PZiFN6bqEnovsRJlxQau15RzG//c/I3bXXbd1f2+VrrjZha646dKly1vhP57+j3ihRzFWJGtmma5P8/ra69TcGgpKZBRA4AYudbdO22vTn+hnb3Yvg8lBsmaWpJ4kkAFu4KIIhYyZwVANvjvzXb459U06/vVr4dzdczefP/Z5PjzyYRSx1a3QdJtM16c5vX6a19Ze4/T6aRJ6gmPFY+StPJqioQgFL/RwAxcncBAIxtJj7MnsYU9mDwk9Qdtr0/bbSCnpifcQ02JbjiOlfFdZlqSULDQXeHH5Rb4/931eWHqBth9NwCk9xQP9D/DQwEOc6DlBQk8Q02LEtBimahLKEF/6+GE0HN/h6cWn+a9T/5XX116/qeMrQiGUNxf/M5wc5qMDH2TqwnPMuCvUVIeG5hOK3adi05XsXYL7pgQ/4R9g4J5Hce47THVvDwPFcQpWYcszac/P8PI3/5CXT3+XilNFDSWabrEyaPHDoRaOevV8Ux34b78f8IHTEu0WwpiEYTDye79H4n0P3fxGb4GuuNmFrrjp0qXLu5m6W+cbl7/Bd2e+C0Bcj2+KoSfmnsALo3iU8fQ4PzH+E6x11piuTTNTn6Fk336l293ImBmyZpaW16LhNhAI7um9h4cGHmI8PU5/sh9NaMw2Znlt9TWeWniKptvkgyMfZDQ1yksrL/Ha2mv0xHu4v+9+DucP44UeHb9DUk8ynhlnPD1O3spvnaC9Nt+b/R7fuvItlppLHC0e5a6euxhIDLDSXmGxuchkdZLX1l67I9euCIWHBx/maOEoXujhBR5e6GH7NqvtVRZbiyw2F/FCD4HgYP4gd/fcjaZorLRXWGmt0PAa9Mf76Yn38PTC05Tt6xeEHEgMMJGZYJ82wOGSiTt1he/HZng+tUpHXI1D0hSNtJHesq+EniBtpNEVHU3RmG/M44bXD4ieyEzwU3t+ir+Z+RsuVS5F+xUao2oPe2SeCa2fvJ4laSRJGEmSZppYMoMWT6ImEqjxBJphoqAwkhq5bevYrfCeETe//du/zVe+8hXOnz9PLBbjkUce4Xd+53c4ePDgdbd54okn+PCHP7zt9XPnznFoo9jVbnTFTZcuXd6rrLXX+M/n/jN/fuHPaXg716MpWAUO5A5wd+/dnOg5QdNtcrZ8lrbXxgs9gjDAUA1M1cRQDbzQY6Y+w1R1ioXmApJoSnjDWrObFentJm2kGc+MkzbSrHfWmanP3PTxNaFxuHCYx4Ye44MjH2QoOURci3O+fJ7nl5/nucXnuFK7Qsfv0Ak6+OH24F9VqGiKxr7sPn564qd5fM/jFGPFXY8bypD1zjpxLU7S2D1mpe21+erlrzJZnWRPZg8TmQmKsSI5K0fWzGKoO8euBGHAVG2Kl1Ze4muXv8bZ0lkgshDmrTxlu7z53K4la2Y348FCGRLIAEuz+Inxn+DunrsRQuCFHn967k/5/VO/T825vVo7z/zyM6SM1G1teyu8Z8TN448/zuc+9zkeeOABfN/ni1/8IqdOneLs2bMkrtME7g1xc+HChS0X19PTg3oTJai74qZLly7vdVpei69e+ipnS2cZSg0xno4sH6Pp0bc0yTiBQxBGE6AiFKSUNL0mK60Vqk6VpJEkZaRoe22eX3qeV1dfZam1xFJrCS/0GEuNsS+3j0cGHyGpJ/nuzHcp2SXu672Pe/vuZbm1zEsrLzFTn8FSLWJ6jIpdYbo2zVJraccJejQ1yicnPsmRwhFOrZ/i5OpJKk6F/ng/g8lBRlIjHC8e50jhCJZm7XBVO+OFHo7voAgFXdFRFXWbm+/dymR1ko7fYSIzQVyP4wQOC82FTQHrBi598T7G0mNbLGGBlFxq27SDkE4QUvUDyp6PguBDuSRKUOZS9RKXKpeYrE0x0yqz0qkThm3CINq3H4a4oU8gJVKGWAo88Zm/JaHfWuPW2+E9I27ezNraGr29vTz55JN84AMf2HGdN8RNpVIhm83e8jG64qZLly5d3n3Yvs1MfYYr9Su0vTY9sR4GEgPsze59V8X3vNPsFt+0Wrd5aabCcs1mMBtjNB8nbqjYfoAfSGwZYqoKKV3jfMvmSxfnmap1IAQZU5GWCtpVQTdiGRR0jXYQsuy61P2NAJxQghNERRZ1BUKJsmqjLrb5H37hKP/nvQPvxK24pflbe0fO6CapbRR2yufzN1z3nnvuwbZtjhw5wv/0P/1PO7qqunTp0qXLewNLsziYP8jB/PXDEuwg5Olqk3nbZdX1uNJ2mOw4WIrCoKnjhJFlIqYo/GxvlqPJGEVDYzxmktbe/piQiufznfU6Fc8nrauoCIqGhiEEq66HpghMoRAiiSkKuiL4QbnBc7UWcy2Hlu1zV9zi/T1p7skn2Z+ycEPJdK3D919f5m9eWaDcdMmnTUZyMXrjJklTY73pcGaxznLdvuVzfrPjy7BUtKRB0/NZdUJWAakJCCRWIEkldDotD9+NhM5GBv0m8RUb9t7+PbxTvGssN1JKPvWpT1GpVHjqqaeuu96FCxf4wQ9+wH333YfjOPzxH/8x/+E//AeeeOKJHa09juPgXNMsrl6vMzIy0rXcdOnSpct7hEstm/+0uM6XlytUb6MYnwAOJCyOJqM4Il0I/uFggfsy210pUkpeb3ZwQ4mlCHwJx5MxFAEnG22mOy6X2zav1ts8XWni7TaFSolo+4iah9LwEE0PYQfR8LdvJwWb6uEGyVPR+oBMasi4Fu2zE0RWFlVEFy2J/r+xL8tQGUqaGKrCYrVD3b75Hl+6KghCSbixr9F8nF+8d5jPPDDMQCa2+8ZvE+9Jt9Sv/dqv8c1vfpOnn36a4eHhW9r2Z37mZxBC8I1vfGPbe7/xG7/Bb/7mb257vStuunR5j7F6DiozkBmORiy7fZ3AjyaH62VuSAl2LXpfs0DRNjpP3wRhCAsvw/n/CuUp6DkE/cejkR2L1rGr0C5DpwyJHsiN3/z+u2xS63jMlVtUYwr/fnKF75frSCN6poOmztG4iVb30dsBh4oJJkbSLDk+uiLYH7eYs13+eq3Giuux6nqsutsncQV4JJukGYQcS8b4B4MF5myX/3BlhVdW6+BLRCDBCylKAW5IyfMj0WCohIlIVOwzDQZCQaliUy91aFQdwlCiKQK35RF418+tVgSoqoLnb19HTeuo42kyvTE0O2ChahP4IfgSNEGY1hEpnf2ZOB/Kp7jYspm3XU6k4tyfSXBXMsb+RGQJOt3skNVV7kptbQJaa3tMl1pMl1qYmkJfOiqI2HJ8LF3F0hVWGw4pU+Oe0RwCWGs6KELQkzLfyiO+Ld5z4uYLX/gCX/va1/jBD37Anj17bnn7f/Nv/g1/8id/wrlz57a917XcdOny7uE709/hyxe/zGp7lbXOGsVYkbt67uJEzwkOFw4zlBgiY2Z2jjH43r+Gp/6fV/9vppFGgtBrEXo2auihSEmIoBNLY8fzuMleiOWId2ro9UWMxgqaf9WULwFf0bA1g46q09J0GopCXYEqUCGkLALGQsEHmk3y/s6ptYFqoIQ+4s21TmJ5GLwHhu6F/N5ITCnqxlIDIw56IloaCTDTEMv9vRVEthfQsH3CMORPX5zjuckSK3UbU1ex4hodTdAUkpUrNQI3RFoqwo4sNUZMY29PgnrdZanW2bQgACRNDVURZOM62ZiOqgge3lsgFzdIWRqvLtR4fqZCqAosU6WlwGRORWYNRMNHXekg6m5kXXHevn5VAKamcHQwzZHBNAf704wX4vSnLXpTFilLQ1Eii0jT8Wk6PmEoURTBYGZr5eV2EHKy3iaQkoyuUtQ1eg0dTfn7+VnZifeMuJFS8oUvfIGvfvWrPPHEE+zfv/+29vPpT3+acrnM97///Ruu2w0o7tLlR8efnvtTfvuF3951nZgWYyQ1wgP9D/DwwMPc339/lInx7P8XXv8zZHUO0bl+rZA7SVMIfhCPcc4w2ON5HHQ99nku5jXfom1VwzeSJJ0WSngLPZLeIJaH3sObIyweZM2wuBJ2mGktMduYpepUcQMXO7CjpR8tAe7pu4cPDH+A+3rvQ1f1t+nKbwHPhsoV7LWLLC2cpbI+w7++cj9zToayG0Nyc5OxQO66bi6h0pfWuLTiENymHrEMFdvd7ubSNB9V6yCFS8aw0JQsCcPkcD5BImmwVLO5st5ivtLG1FQGsxaDcZNhVaM3UEnENDRLpSdtcWgwRSr9/2/vz6PkOgs7//9919qXrq6uXtSt7ta+epFsbBzjDQfsLDCYzcQnjhPCwJAQCCEL32EOZma+4Mx35mTIL4R8hwGHNU5sY/gGE4MZkPdVsmTte+977Xvd5fn9cVsttSW1WlJbUsvP65x7qrv61q17n+qq+6nnPosPf8jAHzZw9AZ9pT4sxyLqixI1o8TM2MV5rc7RYHGQnZM7maxOMl4ZZ7IyyW8v/21u6jx1R6CFsmjCzSc/+Ul+8IMf8OMf/3jW2DaxWIxAwLuG9/nPf57h4WG+853vAPA//+f/pKenh/Xr19NoNPje977HAw88wKOPPspdd911xueU4UaSLp6j+aPsnNpJS6CFZCDJcGmYHZM72DG5gyO5I6cciE1VVNpD7XRHu4maUZ4beQ67lqfNdvALAYafNS1X0hpdiqWo4DTwVzKY5UkC5QxGvcCoAml/mEq4BSucImpGiOtBQopGEI2wgLBjEXJsIo5DyHUI2hZ+u45hVWloOiMdV9CX6GSyUZiZV6pslanViwTKU0zaFXZXR7Gnv20bQrDOcvk1Aqyr10jaNgYqPkUjoJkEFB2/EOh2HaVRBqviLXOY0lQmNI1xXWdc0xjTNQQKEdc9aQkLBZ8ZJuhvIhpoxjCCEGmHlb8OK94J/tjxDdfycOj/QH4QHAtcG5yG97NVwalkqJXGsCqTOPUittPAdR0UXBTXxXBtTNfB5zoYpzil3Fr/HxwVs3vUrFSG+Kj2U3rVMarCZEI0MUmMCdHEWqWfd2lb2equZJ3aT5wSr7vL6BcpTGOKYiDLgL/Kbr/JPi2Ka0eJuw7hRpCwZaI5QQ7Z66gbQVQRJex36W6rEtTD2LZG3wT0jzbjuhrg0KrmWdYw0X3jlCP7mYjvI2CF2Dh6C72ZK7yRp6f5mhUi610K0QnS/TXcER/hXDOaM79w4uJQM8pU9RI1o0TVKFHTS5TDWapNGZZ0J7mp5x28Y8k7aAm2zGubF4LlWjw1+BT/sv9feGH0hZP+/smrPsl/uPI/vKn7sGjCzem6tz344IPcd999ANx333309fWxZcsWAP7bf/tv/K//9b8YHh4mEAiwfv16Pv/5z/Mbv/Eb83pOGW4k6dJVd+qMlcbYN7WHlwZf4OXRV+hvDJ20XkughXf3vJvblt7GVS1XndO33ka1wuihA4wc2MvIgX1MHD2MPxwh2dU9szR3dRNva0Od5+ir4+Vxnh5+mldGX+HV8VfJlKZIZX205Hw0dId82CYXtqj6HI5VSoT1MMsjvSyL9FKoTzIx9Dzd9QorGhYrGg16LZtWx8G3gB/VjqIy0LSE4UQ3nYVxuiaPoImFmzW7gsGA0c6+6HKmiHK0HCSgjLFMHSAl0uRUjaImyOoBSkYU1QDNMNF8EXxmhKjmI6aaBF2BUsvRMjVEz9QYCTd70nPZnL7bb1pVeSHg5/mAnxcCAaaO9ZgSEKm00jN6B1emNxJ25/7/GY0foqjn6M1sxHBP3dakppUZix4lExzBcHz47BB+K4TfDuG3g/jtMKZz5nF4HMVmKjTERLgfs1WwYulSrly+jmuXXUXQDJ7x8afiuoL0UInRwzlGDuaZ6CsghEAzVHRTwzBVbNViVB1gl72NRrRIT3c763tWM1mbYFd6Fzsnd1JoFABv8MArWq5gSXgJqWCKVDDFptQm1ifXn9P+zdeiCTcXgww3knTpaVQrfOOP/gDbsrCtxqy+pv5oFH9bM25zgFqTzsquDaxr24gvEMT0+4m2tKLpc49qUSuXmOrvY3LgKJP9Rxk7fJCpgX7EPOYD0g2TxJIukl1LibW24QuG8QWD+IIhzGAQXyCI6zo0KhXq1SqNWoVSOs3A7tcZObAX1z65Matrqliqi2K7GLaCcsLlFxeB0ED1+wjFm4g2JUk0t9LcFKY5qhH3OwQoUxvZR338EJV8jmpDQQ2n0CNL8Cd7MZo6mWhUGCgcZTTXT7mcI+iY9DolrhR9tCon15CNEmefHqas16noNRqqwEbBQsdyYuhOOwG3G8NsItjiJ5LyY8Q0NNukcDBEZo+PRtWHJXzURRhXUVBP7DLcotF5Y5DUFT6iwQhR07sk88ZgWsrWSA+XadRsrLrD1ECRvS+OYdcdgmqWlHGQZS2D9CQHMKZ2oNveECKO0Km4cSpOE5bw0WoewlBmd5W2MaiJEA0nTN0NU3dD1EUYLRqnaWk71bJLIWNRzFoINJJLY7St78G3/u280JjkiYNPMr6rwrLxqwlZMYw2m0RPgNSyMNVIgVw9S6aWIVPLkK15PweNIMtiy1geX05veBntWhdGw0+taFEtNSgX6uRzZSaHCmQGqtiVU5+SbcWiHizRCJWoRLOk2/twkiWiviitwVZu6ryJa9quwVC98izn6xzeNkn/rinGDudp1M4+vDqKg6NauIqDqzigCgIBH62pBMnWOJGEn0jCT1NbkFT3m38+leFmDjLcSNKlx7Et/uc97zunx+qmj/YVq1iyZh3+cJRauUS9XKJWLlErFkgPD1KYnDjlY6MtKTpWraVj1Rralq+iVi6RHuxnanCAqcF+0kMD2I36KR87X+FEM51rN2DVa2SGB8mNjc0rVJ0fHUVrRtWSKFozihpDUaMoahQUP3F9jG7fq7QZB0jb3RypXUfW6Zp5tKs6iFgdU/hwcqevtfIFdRzLxZ7uERRN+ulYGUc3NDRDRdNVrLrD/hdHZ06uqqoQTviINAcIxU1Mv47p16lVLIb3Z8lPnHq6heYlIZasamLPcyMzY66AIKymcRUTQgl0U0fTVQrpGsKq02bsp8u3nS7fDlL6YZT59K8+nVALLL0elt4AmgFTByF9yFuKo16D8Y6rjy+RVqarpEBRIXMURl+D0R3e4jrQvByaV3hLchWiZTWFgsZ4X4G+A+OM9R2irfgSy3mNgFogY3czZfUwZfeQsbvJGFWONO/gcPNrTIT7aVWWcJv9XpqGu3FHfHBCaLa0OmORI4xGDjMWOUpDq6G7JrproLsmhuNjo7GZlcoG6lOCatpBceY3YnPHyjjv+7NN51628yTDzRxkuJGkS48QgszIEIbpQzMMdNNEM0xcxyYzNMjUYP/MUi0UsOpVrFqNWqWMXZ9f+IgkW2hZ2kNL9zJSvcvoWLmGcKJ5zse4rkNhYsJ77oE+Stk09UqFeqVMvVKhMX2r6hpmIIjpD+ALBvGHwnSsXkvX+itpau9AURSKmRpTg0XSw3nGjg5SmCxRzLhYNRUUA1BAOICNEA6KUkc4JVy3Am4J4RamlzzCLaKoTahGJ6q+BJQAujaO6wzTqAwh5mjIbPhCpJZtpGv9Znqu3ISimKSHy0wNl8gMl0gPl7Hqs7/l+8MGzUtCNHeEEQIm+gtMDZa8rslAy9IIm97dzbKrW1BP0XunUbXZ9cwwO/7PIJX86SdzBK+jWKIjhD9koPs0AiGDVde10bmmCUVRKGVrvPCjwxzZPkVqaYTV17WxfFMLvuDxGiDbcpjoKzB8IEel0EA3NUy1RlAvEo82iITqhHxVNCsP1ZzX5qhR8toauc7xW+FAfhiGXwX77AfMOydNPZBaD1YZjj4z/T9xMiEUsk4Hk9YKJqzlDIsOXKsZIXQEKgKVgUCGPYn9DMcPkgmOIBSBgkLcFydkhAgZIXpiPWxMbuTmzpvpifXMbN91BZV8Hcd2cWyB6whcx6VetSmmaxQzNUrpGsVsjdTSKDe8f8WbXjQy3MxBhhtJunwI1yUzMsTw/j2M7N+H3ajjD4fxhcL4Q95ton0JyaU9+MNzT2p4Vs8rBNWiRSnrfcjbDZdw3Ec44SMc96MZKrWSxdD+rLfszZCfPM0EkAqomoJ7ikHdjtFNdaa3jT9kEIiYxFuDxFsDxFNB4qkgZsC7NOc6Drnx0elA1k9muuYqPzlOJZ+btV1V02lfudprX9TZRWJJF8FonMJUkfRIDuFYBCIKmu7i2DaO1UC4LuFEM+HmFK4TwRcMk+wKz2uKBOEKyvk6hSlvTJhq0fIuP1UdVE2hfWWcjpVxfIFLavB8sOsw8hr0Pw+DL3sJrHkFJFd6t+FWryZn5DVvGd3hjXnkWMfDSbAZ2q+Cjqu8W90H6cOQPug9dnI/lE9Rw9i6Adb8llfLM74bxnfB2E4ojc9r1+uaSS3UDLFO9OaV+Ns2orWsheQqr4F5cfT4PqQPeY3alROGK1A1MMMQTHg9+QJNEGyC2FIIX9gGzzLczEGGG0mSzkRYDk6+QW24ROZAlqn+ArlCg4IlKNQdKnUHxzn9R6c/bFArW5w4D6SiQGJJmER7iKa2ILFmP2HbxV+x0E0NxaeCoSF0FVdXEQoIW2D6VHyJAHpL4LznWLIadcYPH+Tw1pc5vPVlsiMnN9Y+W75giCVr17PpzvewdMOVb+l5oE7Jdb2aIM048/hF5SkvwEzs8dqdrXq3F2pOpTQBI9th5DXc4W24wztR3RoqDgjXC1ZnmlFd0U5bMzQvieXQ/XbvUl3326Gp900do0mGmznIcCNJlwfHdsmMlsmNVzB8mler4dPQyhZKtoY9XsEaLeMUG/jXJgjf0IEe9yOEwBqrUN01SXFnmuJEhYauUlMV6o6gUrWpWS4lV1B0YK7WMX5NIejX0A2VquVSqTo4J4wuF1GhRVdJ+lRagjo+3/REhULg5BvMGonuDNSoiX9FHKM9hFNs4GTrOLk6atjA7I7iWxrF6AyDALdq41ZtRMPBaAmgBk/dGygzMsTowf1khgdJDw+SHhqgVi5j+HwYPj+G6UPXTTTdQFN1NE0HVaGUz1BIT1Ap5GZtL9nVzabfeC9rbrwZw7zwI9hKb9AoQ2HE6+KfH/JG1p48AFMHvJ+F4wWcRK9Xk9O8whsi4NilOeF4IalehGrWG3m7Mn1bGIE3zuIeaffaJXX/Gix9O6TWgbpwM63LcDMHGW4k6dInhGByoMihVyfIjlfQdAVVU9F0BdcRpEfKZEfLuHPUnpgKGAqYitcXSSig+DRcy6Vhu9RdmM93Vk1ViDf5SKQCxKMmUV3BzNTQxspob3h6IQSWgKoAv6niA5hjH7W4D19vDFQFUbNx6w5u3UHUbYQtUDQFVAU7XYNTDNE/X3prEF9PFLMnht58wsi30zfCdrHGKlijJayxCvZkBbfmnDF82a5F0c3Q7+zj8MQ27OkRnBVFRff5pkOSD930zQQmMxj02icFgvhmfg6gmya6bqI2FJSGghH0Y4QDmLEgZiRIrKUVZQFPlG95dsO7tBVuBf2N02nOQzULAy/BwPPQ/4J3Oe7Etl66H/5q8Ny2fRoy3MxBhhtJunRlx8oceGWcg6+Mn7bXzIl8QZ2mtiC25VIrW9SK1kzPnfky/RrBsEEgZBAM6oSa/IRaAkRbgySXhIm2BE7ZSNat2zQGSziFOm6xgVOxEVUbxdTwr2nC1xMDTUE0HNyKjbBcb7FdUEALm2hNvvm1VbFc6v0F6ody2OkqWtREa/KjxXw42RqNgQL1gSJuYbqxrqagBnQUTcXJn19vLwDFVFF8GoqhIezp47Acb56jaQ2nxpHS6xzMb6XiFM77Od8ooIdZmlrP8iuvo/vtmwksi6MYCz/T97lwGw6NgSJOroZTtHBLDRSfhtEWwmgNogZ0hC1ACLS43wutl5tGxZt7beAFr22S7offeWhBn0KGmznIcCNJlybXFfzjXz5Lteh9+9MMlZ6NSZasigPeZahjNTVNbUGSXRHCbwgHQghcW1CrWNTLNrWKRa1kIVyBk6tjDZcwmnyElscJJ/0EYz4M89I4QZ4vIQRuxUYxVG+ZLhen1KDRX6DeV6DRV8ApTgegmU9+AaqCkQp6J+P2EHprCC2oe4HG1FBOM3+RcAVOpkZ9sEijv0BjsEhjpEjNKuMIC1tY2K6FI2xsYeG4DSy3gSXq3q1bx3Lr2G4DR9jego2rOtiOhePYOK6F5TZwT6hn86kBOsIrWdZ7NUs3XU2gqwmjPYQW9512X9/ImqpS2TaONVoGRUFRAU3F7IoQWNeMnjg+4J5j22SPDjF54DDp/gGK2TSVcp5KMUe1WMAvAoT1BBEjQdRI0OzvwK+dPOM4gNbsJ/buHgIbk2fVPsmt2VjjFUTd8QKmI1AU0FNB9GTgpOOu5HMM7d1Fo1olGIsTjMYIxuL4w2Fc18WxLOxGA8e2cKzpxbZxbAurXseqVKllijRyJer5Mk7FIhiMkVjWSdO6buJL29H0CztlhAw3c5DhRpIuXc8+fJDcRIWV17TSe2US03+J9ZqRzshtOFijZa/N03gZa6KCNV45XqsEKKaGGtBRI4YXqlqD6KkgRiqI1uSfdaIWlkujUKHvtdc4+MKz9O1/jfoJ01QoqAT1CEE9SsiMEWlKEohEvfBk1bBdC0vUQVMIhKME/GHUNOg5haAeI2IkMNTZl04qdoFsYIrJ+hCTU/3kKxM44uTBGOeSiC+hLdxLkg40V8NVXBzXxnVsHOGgJ/zEOtuJmAn8WhC9KYDeGqDmq5IbGyE7OILaUDHrJnpBwyzquMKl6pS8xS5huTX8WoiQP0a4NUklUGaiOsDI6AHSIwPn+ArOX9AfJdKU5J0f/Q+0b1z7pj+fDDdzkOFGki5dQgjZ2+Yy5VZthOPOXC475+04DoO7d7L/6ac5vPUlKpX8ee9bOJIg3tSKoQeYGD5CuZ47aR1V0Yj5W2iKtRGOJAgEogRDMSJdKRqhBrnCBNnR4elBIPvP6vk1xSCghag6pbMOUXNpCrfh18LUaiXqdpmaU5lVA6YpOqqiebdoqIqGqqhoioGuGuiaieH3Y/j9qH6dcilLMZ+mUs/P2s8P/s4XWfreaxdsv0/nbM7f8muRJEmXDBlsLl/qAo1do2oa3VdcRfcVVyFcl1I2443jMzFOrn+Y/PAYtWIR0wxgGH4MzURXTETDoVouUquVsMwGdbXm9fjK5ygVM5SKx2eaV1SVZKqL1rYVdKxaS9u6VSRWLj3jNB/HVPI5+nftoP/11xg7dGB6HicDTde9nmeKhpWvUSqmKZUyOMKiZOe841NUwr4EkXAzrupQs8pUakXq1RKKohKMxwk3JQg1JfAFQ1RyWQqTk5SzGQK+CK2hHpJuOy2+pfi1E+ai0hS0hB+adMphk4OWTZPPoDVg0hQw0HTVWydiojf50RJ+1KB+yvekU26Q2ztMdu8A2b4hklcsO6/X9M0ga24kSZKktwTbcTk4UeLwZIllyTBr2iLUKyUyw0NkRgapFgq0LltB+8rVmP7ABdknx7YoTE5QymaINLcQTbagaie3A3NsC0VRT/m3Y2zHZdtAjl/uHiM7VUFvuDR0lQIurqYSDxpkKw227J/EPqEnnE9XWZEKszIVJlOxODReJFe1SEV8tMX8XNkZ57plCd7W20zYd/HqRORlqTnIcCNJknTxOa5gOFvlyFSJsXyN0XyNUt3Gdlwajkup7lCp2yRCJqvbInTEA6TLDSaLdcp1m5rlYDnHe8bVLJdS3aZuO0T9BvGgiU9XsV2X0VyNwWyF/nSF+gld6uNBg41LYqxMRViRCs+c4JtC5999OVNu8PPdY9y4Mkln07nN5n1MsWZxZLLM6rYI/ukeYq4r+NfXR/j5nnE6mwLULZefvD7CVGnu6S2OWZoIUrUcpkp15psCTF3l1tUt/NYVHVy/rJmBTIV9YwVaI35uX9d6roc3bzLczEGGG0mSpIXz052j/GKvNxWAEJAuNxjP17Bcl0TQJB40qdsOuYpFoWZhOwIhBFPlBo3zGLvnXEV8OstaQhycKFFpnHqko2UtId6/qZP3XNlBV+Lsgkm+avH3vzrEt1/oo2a5xAIG91y3lIMTJTLlBv/PB65gWcvppwI5NFHkX14doiPmJ1e1ePbgFK8N5nBcQVvUz3XLEgxmKgznqowXTu7mHw8a3LY6RXdziIbj4Nc14kEDRVHIV72eiLevbWV1WwQAy3EZzlbZN1bk8GSJpqDJqtYwzWEfE4Ua/ZkKW/uyvHAkzUCmctLzAbxzTYpv3ndptbmR4UaSJEk6Z//Pz/bxtV8dPqfHmrpKT3OQJfEA7fEAUb+BoSnoqkrYrxM0NcbyNfaPFZko1mgO+0hFfEQDBj5dxdBUFMULVX5DI+LTMXWVfNUiV7GwXRcFSEX9dCWCdCeCLE0EUVUFy3HZNZxn/1iRgxMlDk0vw7nZ4yutaYtw54Z23ntVBz1Jr3u3EIID4yUe3TZEf7qMENARD2C7Lv/f9hEKNa+xbdSvz/x8TDLs40PXdPLS0QwRv85ta1IoQNVyGMnV+KeXB2bVLh0TMDSq1uwwFvHp/M71SylUvRqvOze28Y6VLRjn0WD7dIQQ7B0t8pPXR/jJ66MMZCq0Rn2saYvy9uXNfOLm00wTsYBkuJmDDDeSJEkL5+WjGV4byM783hQyaYv6MXWVTLlBttIgYHi1B1548QJJPGCypCmANs9xaeZDuC7VrVtxGw3UYJD6/gPUDx7EXNqF/4orMJcuRdE03GqVRr/Xoyl47bUoJ7RjKdYsntg1xmOvDfPS0cys6TRWpsIkwz4OTpSYKp1+cMQVqTD/8TfWcsOKZv5hyxH2jxdYlgzzf/ZNsHf0zAMcXtebQNcUEiEf1y9LcNPKFloiPn702jCZSoPe5hAtER+r2iJE/Rd2rBmYnjjWcgiaF7b9jQw3c5DhRpKkheQUi6iBAMo8e9JIC08IQWnLFib/9v9Hfe/es3qs2d1N4g/+gNh734M9OYnR0TETdnKVBr/YO8H/t2OEZw9OzpqNwtAUbluT4tdWJFGAwWyVct3mjg1t3LA8ecrQVqxZ/MurQ+wZKbC2PUKm3ODIZBmAgKnhN1RuW9PK7WtTsufgKchwMwcZbiRJWkhjX/4y+UceJXDVVQQ2byK4+RoCV16BGrgwvW0ud42+PoQr8C3rPelvTqFA4Wc/I/ud71I/eBAANRTCWLIEp1jE7OnGv2o1jYEBqq+/jpNOew/UdczOTuxsFjc/e5wcs7ubpt+7l+iv/zpOqUSjrw//qlXkokl2jeTJlBr0JIOs74jNNO6VLgwZbuYgw40kSQup/3fvpfLKK7PvNAwC69ZhrlyB2dmF0dmJ0d6GW6lgT6Vx0lM4+QJupYJbLuNWKgjHwbdsGf51a/GvXYuxdKmcKBIY+pNPU3zySSK//usErrwCAHtyivqRw1ReeBFheY1k1WCQpt/5CImPfhS9qemU2xJCgON40y1oGm65TO6RR0j/47exR0dPuw+KYdD0Ox8hcvvtqJEIbrmMFotR2rKFRv8AweuuI3rnHbMuby0EIQT2xCT1A/tRTB+Bq65E9flm/nZW0zdUKlhjY5idnSjm2fUGs6emyD38ME6xhKKp+FaswL/xCszengtawyTDzRxkuJEkaSEJ16V+8CCVV1+lunUrlVe3Yk9MnPd2lWAQLRpFDQZRg0G0WAz/FRu9mqGrrkILn3ruovMlHAe3XEbYNjgOwnUBxZsSQVVRdB01GEQxvLYeTrFI4+hR7IkJtEQzeiqFnmpB0TTsiQmsoSEaw8NYIyPYExPY4xPe7dQUimGgxeOzl1gMLRpBjURRQ0Ey3/4O1W3bTru/Rnc34ZtuInzbrRipFGoo5C2BAGjaPCcmtSi/8AJGZxfl554j+4Mf0Dh6FCUQQE8msQYHz7gN36pVRN71LkI33IDZ1Un5pZexBgcQlk3wbW8jeN3bZvZF2DaoKrU9e3Eyae/1nD4fVXfupLptG/bUFIWf/xyr//g0CoppojU34+RyiFrNuxxqGAjHQQ2F8K1Yjn/degJXb8LO1qgfHqG69RUaR3bhFqe8bQSjBDbdgn/1aszuVrQmP7iON0O8K7DTUziZLEKYCEvHnipSfOIHiOrJbYWUYBPGkvUkP/VRYu+6/oxldL5kuJmDDDeSJL2ZhBBYw8NUX3uNRv8A1tCQt4yNoYbD6M3NaM0JtFgcNRScORnjCuoHDlDbu5f6/v2IxhzjlagqejLpdRPSNAIbNxK++Sa0piYUw8AtlagdOIA1PIIWjaKnUig+E1Gt4pbLOPkCTi6Hnc3gTKW9miPhIire3+dDMQwUnw+3VDr1Cprm1ZIsJEVB8ftBCK983DN0JVcUFNOcCVH+tWvxr1+P2duLWyrh5LI4pRJaOIwaiaBFY6iRMFo4jOLzoYYjYOjUduyg+MQTVF7bjlupoJom9tSUF2S6l5L/15/gFotz7opvzRqMjg6cfJ7a66/P1Dgd20/f6tUoqkpt715mDTyjqt7+FgrYk5PnUXiAqoN7btM7qNElaKn14DRw8oO4uf6ZbTXd9yeErltD+Nd+7axrhc6GDDdzkOFGkqRLnbBtGoODuCXvkpVbrWCPjVN9bRuVrduwhoYuzI4oihdSwAsSpwkTeksLelsbTjaLPTFxPJjpOkZ7O0bnEoyODozWtumanRR6SwvCsnByudlLsYBbKJ5wW8RJp3FyuVPvos+HFo+DqnqX+MrlhQ9Vqkr45puJf/CDhG++CVQVLGvmRG5nMhR//nPKL71E+fkXcPN5fGvX4l+3FmFZFH/2c0T9FL2rNA09kTgptPg3bEDx+UDTEWoXEMOtjOPmDmOPHAJ7OhhpPrTmlWipdWjRDtxKGidz2AseyvQlTd0PCBQ9CGYIGiVEfTqICQcUDUU9fjlN8UVRzDDCKuFW8wirjKL7UUItKEKAcBCug3Asb1uNEsKug11l5TNPo7e0LGzZn0CGmznIcCNJ0mJnjY97l3VUFbdapfzss1S2bkPUaojpk65v5QrM7m6cQtELHJaFGgygBIJo8RhaNIbenEBrbkYLh0FVUf1+1GgUNRz2amZOcUlHNBq41ep06Kqhp1q8xx/7uxC4+TxurYbe0rIg7VCsqSrWeBEtWMfNp1H8/pnLWKrfP3v/pmt13EoFbBthWYhGA2tsjNruPdR278YaHkaNRdGbmlBDIa82q1DEKRRwSyXcYhGnXEbU614oOeE0aSxdSuLee4nf9T7U4MkD/AnbxikWZ7X7afT1UfjZz9FiUdRQGN+qVTiFIooRR9ghnFyazPf/X6qvPodihlE0E615BebKO1CDiZOfw7UB4QUT5Xi7LDWs41sWxOw20eMCNRBADQZQ/X6U6UuJTiZD48gR6oeP0BgaxinUcEs13GLJO+ZqDQxQNQvF70P1+RGNOnY2h5PN4mQyiEbDq9kKBFCCAdRAEDUQoPNrX8NoTZ336306MtzMQYYbSZIuZUIInHwda7SMNVbGKTTQwiZa1ESNTN+GDETD8Wbartq4VRunZOEUG7iFBm7NRov7MFqC6C0BnGKD+sEctYNZ3JqNnvCjNwfQYj5Uv4bi18EVuDUH0XAwO8MErmhBNReugaxbt3FydZx8AydXxxovY41XsCcqqEEdoy2E0R5CSwTQQgYoUDuQpbo7jT0xPTKupuBfEce/vpnA2ma0yOkvgQhX4GRrWBPecziFBr7lcfyrmlD0+TfUFkLQOHKE3COPkvvhD2d6V6mxGLHf/m0i77oDzC7s0TJ2vo7ZGcG/Mo6eCp4UDu2pKtW9GWoHMjT6C4jGmUdoVkwX37IATt7BnrIR1uy/6y0BAuua8a9rxuyKeG2j3kRCCBDiojR2l+FmDjLcSJJ0KSo+M0R1dxprrIyoLfBllXOg+DSCV7ZgdIZR/TqKoU4HKscLXxMV7Mkqiql6ISoZQE/60RMBhCuwp6rYU1WssTLWaBknd/pB785IVdCi5uxtKGC0BlGm900xNBTDO+HaU1XsiQrCOjk8KH6d4MYkgStb8C2LnVUYcCsVco89Rubb38PJWajxbnyrfxM1dIpLMYqFsOveJTpVRTH8KOobapmsKk62z1vdF8RoW4ISCCMsB9WvE76hg9A1bTPHJVyBW7bAFQhXoGgKWtQ37/1f7GS4mYMMN5IkXYqyPzxI+eUx7xdNwWgJYLSF0OJ+3LKFU6jjFBpe7UzFQjE1VL+OGphewgZaxKvdUf0adqaOPVnBnqqi+DT8K5rwrYyjx33YmRp2uopTtBA1G7fm9ZZR/TqoCrXdU9jp2oIfoxLQ0WMmatQ3c3x6axC3bB0PQXnv+ETdweyJerUSqxMofg17okJ1T9oLgUOnach8Ik3xgldrENWvUd2TwS2e0FBbVVCD+vRieOXo11F8GmpAR2vyoScC6E0+7HSN+uEc9SN5GiMlcI6fOt1KBnvsdUQ9j5ZYgZZciaKdXKskXAdn6gD22A6cyX24xVG0WJTwLTfT8qd/itHWthDFfNmS4WYOMtxIknQpqvcXcDI1jPYQejJwVpdOFpoQgvqRPNUdkzjTl7mE5aL6vEtYWthATwUxUkFEw8GarGBPeYHJTldRVNWrxUkGMFpD3iWntiBqcOGmCrDzda+Wq+EiLAdhuV5NjSvQm/3oqSB6IoCiHa+ZEa6gfjRPdfsklV1TiOq59RwCr2bLaA9hLg1httdQfarXEHxgkHpfP85UDWNpN77lKwBB/dBB6od2oag2eqIZvSVJ4Oqr8a9bt+Dj41yuZLiZgww3kiRJknAEbqmBU7FxKxZu2fJCXM3Brdm4FRsnW/NqubI1tLCJb3kc37IYvp4oWsIvp0i4wM7m/C0nQ5EkSZLechRNQYv50GJnbrNytqMBSxefHNtbkiRJkuYgg83iI8ONJEmSJEmXFRluJEmSJEm6rMg2N5IkSZL0VlcvQWkcKhmoZqE6fVvJgFWBSBtEl0Cs07uNtIF66fbykuFGkiRJurw5FlhVML1pJhYtuw4Te2Fsp7c0ytCyClrWQmqtFzxO1z5ICKjloDgOmSOQPjS9HPZuS2Nnty+KBpF2iC2B3/tX0C+twQRluJGkS8noDsj2QbwbmnogED+37QgB2aMw8hqMbIfR7ZDt9ybRMwInLEHvVjO9D0VF8ybc00xI9EJyJSRXQbTz+EmhXoLCMOSHvKUwDPlhMPzQcTV0bIKW1af+VmdVYXy3d5yjOyA/CHYDnAY49RN+tkA3vf0zQ8f31QxBIEE2vIxhcxlW8ypUXxRdU9BUhbrlUrUcapZDw3aJB02awybNIZNY4NRzJUmXocxRGHoFhrfB8FYYex3sGqCALwK+KISaYdPveYt2DqdCIaBegNLE8RoP1wLX8WbLPrYIF/xxCCUh1OItgcTpn1MIqKS990Z+yPs8GN8No6/D1P65Z/U2I957L7XGO9bypLdvpUkoT3jvrbmYYW/fgk3ebaAJggnvc6M4dvy9Xhj2Jt0sDEG9eMkFG5Dj3Fzs3ZGk2Z74v+DFrx3/3R+bDjrdxwNPU4/3s25Cecr7ADu2lCZgYo8XHGr5hdsvPeB9KyxPet/+zsQIQcdVXtiJtMHYLu8EM7nf+1BcQEMiyX63iwOik5owCSk1wlQJKTU0HAZFikPuEo4qSzDb1vL2tT3ctibF+o4o6ps8D88Zua5X/V+a8E4+pUms0iQZEaG5aw16ywrvBCOdWX4Idj0KOx/x/tfmK7kaNt17QsBXwLG9MGTXj99aZS8klMaPv172uY7irHiv67GwE0x4QenYF4a5tuuPQ/sV0HaFF9Qm98HEPkgfnDv4HOOLeZ8nzSvesCyb//+a63jlkB/2PmdW3j6/x50nOYjfHGS4kS5pz/8d7H4Mcv1ekDgfmg9a13sho/0q7xuda3u1J42yd2tVvOXYN0zheidcqwKZwzB10Ku2dt8wW58v5lVHH7sGH1vifcgNb/Nqiqzy6fcrmPT2qe0K70PV8Hv7qvtAM7yfNWP6hDK9f43K8Z+LYwwf2IaZ2U+LSJ91sYyKBIfddob1pRRDSymFuqlGeyHeRWssTFciSFciQFdTkJDvNN+uHcs73moWqjnv53re+xZbK3gnqmM/W8fKenqxa9PHVEaUp1DOEPZcfxNq83JILPOWaLtXhsdqAoLNXgheyFop1/FqDyppUPXjr4vu82oWSuNQHPW+zRdHvZq1ph5o6vVuzZNny14QhRE4+owX4K0q2FWwapAbgMEXj6+n6l6wXrL5+BJp916TetF7rQZfgaf+2guX58MXhXDKex0003tuVZu+nf7/qeWPfwGpZIB5nHbDbdPvrU5IrYO2jV6oiS459WttN7z37MRe70uEqnn/H+FWb//CKQilvPfbIiXDzRxkuJEWjUbZu5SU6z/htu/4z67tfVidWN0daobEcu+DPbXWOymdL8f2ni8/5H1ARpeAf473juvA1IHjlwQqU5BaD+1Xeh/OkfaFOxFXMtPfXPd4315dG3xhr3reFwYUyBzGndiPmNyPVpk47aYaQmNQpOgXrThomFhEdIcmn0tEdwmqNopVQWvkMZ3Kwuz/tKyqklb8TBEhQ5AWyix1C7SK+dUMOKpG1QxS0nSKQB4HywgQCrcRj3aSiHUTCrej+CLepQe75tXA1fIzi1PJYOVGEcVxfPUMKudew5YxYmyNdvKrcIytfh9N/i5afEtpC/Ry45IbWJlqoi3q92rOKhnoexY3fYjsyKs0JvdBLYcINpNoXo0/1oVdL+Ac2YIvPzTHsyrQ/Wuw8f2w9r3ee+FManl48eteIMCb7RoEqIZ3KUb3Hb81AieEhVYIt3jvPzOIK1z2ZfZxKHeIfD1Pvp4n7otzS9ctdEY6Zz+n63jHXJ703hvlSSinvffU9JeFgj8Muo+oeeHOUZZroSkaqnLptkmS4WYOMtxI0ltYNQdTB7HG95Lu2wWZI/gLRwlXBtHds5+1uiACFAiRFyHKSohoPEFLsoWyEiRt+RirmwyVVfryLgVbR7T9lIZZpKqoVBWFjKaS1TTs04S9gOvSZdt0WTbdlk2XZdHsuiQch4Tj3YbepI9wF8grJioKPlx010FXvFm2M4qPCdVkUtOY0nT8wqXLrtPlVImJ2TNxp1WVX4aC7DZNRnSNYSXMmN3NtVaOD9YnuKk+jjHPS5UOcNAfJJNchhlMohohFCNISVXYEU0ypmu0h9vpCHXQcBrkG3lKjRJ+3U/UjNIb6+WKliuImBEGCgM8NfQUxUaRW7tuZU1izUltsmzX5kj+CLqqE9JDxHwx/LofIQSDxUF2TO7gxdEXeW74OdK1U9cirmpaRVAPUnfq+HU/QT1I2AwTMSMIIZioTGC7NslAkrpTZ096D0OloZnHXtt2LTd03MCNS25c8OBRsSo8NfQUPz3yU54deZaoGeXWrltZFltGzBejyd9ES6CF1lArTb6mi95mTYabOchwI0nSSVzXaySZOezVjglBRRgMFhwOZywOpC2O5Gz8gTDRpiSJ5hStqVa6klH60mW+9exR9o0V53wKU1Np6X6SaMiiPdLE0niSzR0rWd+yGtd12Z3eze70bqp2lbgvTsgIMV4eZ/v4fgYK/TQozN6gUPCpMVqNJtb4m1gbjOGv6eTTDuNjdTR7kog5SlTPEFZKhFyHsBAEXZe6olBUVQqq6t1q3s9Tmja9qGQ0DecNJzNVCBQ46f4TxR2FG6wk7yyXeXupn4hbPWPxHzQM9psGI2YApXkNyebljE3upJQ7SrPjBZ9dgQQvmyp57fzabCkoJANJJquzL/suiy3j1q5buTp1NT2xHp44+gQPH3iY8cr4rPXCRhhFUSg2Zr/eOn56o2vpjqdoDsQ5kj/C1vGtuG8Ie+dqRXwFf7jxD0kFU0xUJjA1k45wB53hTqJm9KyCR9Wu8r093+Nbu75FyZrH7OpAMpDkuvbruL79etYm1tIV6SJovEmXH09Dhps5yHAjSdJCE0Lw/OE0//uZI2wfzLGkKUBvMkxvMsTylhBr26P0JkMY2rl/885Xqzy++wj/tmuM5w+ncSw/cLxHmqJMX1WZFvXr6JpKptwAxcIXHGdpe5ZAaIwGOTRVx1ANQoaPZChCKhylLZygO9pNzBdjsjLJQGGEl4f3MlA8RNYapjWUYmV8Jcvjy0kFUyQDScJmGFe4OK6DX/ezMbkRvz7drsOxoO8ZOPAzyBxB5AZwc/1oVpWaGeblxEa+6UZ5WaniVpdSn7oFXO+EGfHphMJZJutDuLV2hB0DxUEL9BOO97O6Q2Vps4ZNjaAeJBVMETSCjJZHGS2PEtACRH1RwkaYml0jW8+yN713plZEV3Q2t24mYkZ4euhpGu6pexIJxwRUUBsoyglBRWg41SU41W7s0mqcSg+go6kKG5fEuHV1induCDJU24mmaAT0ADW7RtkqU7JKFBoFhBC0BlsxNIOp6hQqKmua17A2sRbLtdg6vpVXxl7h8SOPzxlCwkaYJeElhM0wQgj8up+YGSPmi7G2eS2bUptoD7ezL7OPbePb+O6e786Eu85wJ3f23sm7e95NupbmueHnmKxOUqgXyNQyTFYnSVfTiFO0E2oJtHDP2nv46MaPnunfd0HIcDMHGW4kSVrs0qU6r/RleH0oz87hPK8P5clXLUKmxrvWt/HbV7Zz44oWdFVhz2iBhuOyviOKT78EBl0TwmvrYoZnukPvGSnwTy8P8NyhKcYKNSqN2bUzPc1BNi1tojMR5IfbhhjKerVBPl2lKxEkETJJhk2agiZ+Q8PUVUxNxdRVXFdguwJXCBxXgFbA1iZZGV9FKhxnJFfltaFRtk4+y2h9N/j70HyTOJWlNLJvxy5uJBEMkq3UEUoNRS+hKBZuPYWpmWzqjnNdbzMTxTovHJ6iL328PZaiwI0rknz42i5Cps7ukTy7RwocnCgR9et0NgXpbArQlQhOB+EwybB5Ui1MoVHg+3u/z48P/Rhd1UkFU9SdOsPF4dNeDnsjBWVWQFkSXsIfX/3H/Ebvb5zxclfdqfP65Ou8MPICr4y9wtHCUfJ1rzfmZzZ9RoabS4EMN5IkXW6EEIzmayRC3sl9sSvVbcYLNbLlBr3JEM3h4+Oo2I7Lv+0a4/99+jC7hgtzbOXcRHw6V3RFuLqrmau64lzZFacl4qNmOQxkKhyZLDOcq7KqNcw13QkC5uzyHs5Vee7QFD/ePsxzh86+N1/Er7OmLcKHr13Ke67swNTnDh41u8ZwcZih3A5qVgEFlZoaptCoMFmdZMfkDnZO7qThNkj4E2xMbuTGJTdy18q7MDUTANetMzn1f8jlXsV1a4RDq2hpeRd+f8dpnzdfzzNYHKTZ30x7uP2sj/NcyHAzBxluJEmSFj8hBIcny0wUa6RLDTJlb6nbLg3bpW47WI6LpiqoioKuKiiKQrXhkKs2yFUs8lWLZNjH+iVR1nfEWN8Rpbc5tGDjHw2kKzy8dZB/3TGCrqms74iyoSPG6rYI5brNULbKYLZCf7rCkakSQ9kKhmLRcL3Q0Rr18fu/1svta1vJVhpMFOpMFGtMFOv4dJXf3NhOT8Jm954/J53+1czzKopOMNhLNHoVHe0fwB/eQKFRoCXQcnKtUOF1drz+MRqNqVn3K4pJNLKeam0Q2y4RCi3HNJNEwuvo6fkkmnZh29t4+yrDzWnJcCNJknTpc90G+fxrxOPXolzC3ZPPl+taWHaefO5Vjhz9O8rlvTToZNdkJypFwkYZV6jUbD/9hS76i51YjoGhWXSExri9+0WiZhrQ0PUIQlg4zuxxpoLB5QSDKynbMTQ9TtgfxKrupFTaRaMxhRA2Pl8bqdSdaFqQbPYl8vlXT7vPmhYmHF5DS/I2Uqk7CQSWvsml5JHhZg4y3EiSJF36JiZ/xs6dn8Tv76K97X2EI2swjWai0atQ1eODK9br40ylt6BpQVItd+A4VQzjwny2C+FSq40iRAPTTKFpQRqNKSwrg+OUcV0by85SLOyk0UgTCq3E9LVQKOwgn99OtdqPZZ3nIILAeLmFv9/xB+i+ldy4spmrl9iE1T4M6ymcypOozD3MQc7eQCX8AF3NzXTEA7RGfTQq2xnL9DFVa+eV/hoHhrfh2Fnu7PkFzYHszGPDibu57qr/+7yPYT7O5vwt55aSJEmSLjmN+hSaFqZWG+Ro39/O3O/ztdG55B5AZXLqSQqF7TN/26NoCOEQiWwklboTBQXTl8LQo6iqj6amty9ILZAQDoOD/8jg0Heo1Y4PLKhpQZxzGuBRwTRb6Gj/AB0dH6RU2keptB/DbMY0m0EIGo00hcJ2yuVDCOGgKBqa2c3R/BJ+MnI1o5UGTqlCX7rC9wDwAe8ioL+DdYn9xHx5UqESEbOKIsoMFjs4kF1OvhFlqtoMHJleThSCmSEINhAyNfbkbkYXQ6yMH2Zz6w7uXHnHORzvm0/W3EiSJEmXJMepMjn5cyYmn6BRn6RS7cOysietFwj0UKsNIcTccytFIhtIJG5EVQyKpT0oqDQ1XY/r1qlU+6nXRmlYWdra3ovf10EksoFAYAml0n7SmaexrQLF4i6KpX00Gt5o14pioKrmCZeCVAwjjqaFUFUTTQsQCa/D9KUol/ZTb0wQiWwgHruGUGgFPl8rhhFHUc6vIXihZvHi4TTPHpriyGSZquVQbTjEAgY3rkxy44okG5bE0FQF23HJlBsM56ocnixzcKLI4YkSQ9kqo/ka+ao33YrfUOlqCrJxSYw7N7bzjpVJ/IZGpWEzkqsymK1y08oWtAs0R5u8LDUHGW4kSQKoFBqU83UiCT++oH7RR1+Vzsx164yPP87o6KOomo9k8nZakrfj86Ww7RKWlUFVA4xP/IRc7mVUxaReH8dxq1QqR09qi3ImqmoSi20mm30Jb8zmE//mZ+WK/4v29vejaX4ajQyWlcXv70TTLr1Zss9GuW5TtRyaQyd3S7+YFk24+cpXvsIPf/hD9u3bRyAQ4IYbbuCv//qvWb169bwe/9xzz3HzzTezYcMGtm/fPq/HyHAjSZefRtVmor9AYapGfqpKcaqKbbkk2kM0Lwmj+zQKU1UKU1WyYxWmhkpUC8cHbTP9GqEmvzcQnut9JIabfGy4uZPeK5IoZ/HNtJipMTlQpG1ZjGDUXPBjlc5NvT7J+MRPqFb7EcLFNJpxnDK12giKohEMLsPnS+G4NUZHH/VqcyrHL9MkEu/A7+8gFFoJQtDcfDOh0PKLeERvPYsm3Nxxxx3cfffdXHvttdi2zX/8j/+RnTt3smfPHkKh0JyPzefzbNq0iRUrVjA+Pi7DjSS9xfTvTjO0L8vIgSyTA0XO+pNMAX/IoFay5lwtlgqw8eZOUKAwVaWYruEPGTQvCZPoCIGAYrZGMV1jYHeaiX5vWH5VV1h1bStX3NZFsjN8xm/AjuNSztYp5xs0tQbxhxdg0lPpnAkhyGSept6YJBxaTTS68WLv0lveogk3bzQ5OUkqleKpp57ipptumnPdu+++m5UrV6JpGj/60Y9kuJGkt5hH/vpVxo8eH8QtmvQTbw0RTfqJJgOomkJmpEx6uIRju8SSAaLJALFUgObOMM0dYQyfht1wKKRrVPJej5JjIWRgT5rdz4xQr8zdjuMkCkSb/RSmjs/orRsqkWY//rCB3XCxLRfHdmfmS3BsQSVfnwloiqrQsTLGsqtaWLqumWDMxPBpl9QlAkm60BZtb6l83hvOOZFIzLnegw8+yOHDh/ne977Hf/2v/3XOdev1OvX68W5whcLCj2gpSdKFt/KaVpo7QnSsamLJqjjhJv85bUc3NRLtIRLts2uLl6xuYvOdPex9fpSj2yfxhwyiyQCRZj+VQoPMSJnMaBlFVYgkfISb/KS6I/Re2UIwajJ2JM+OXw5yZNsktuWSHTtzLxpVVwiETcq5OsP7cwzvzwEHvb9pCtFkgBWbU6y+ro1464UfRE2SFotLpuZGCMF73/testkszzzzzGnXO3jwIDfeeCPPPPMMq1at4v7775+z5ub+++/nS1/60kn3y5obSZIuBMd2KWVrFNI16mUb3VTRDRVNV0FRUBQvuITiPoIRE0VVyE9WObpjkiPbJxnvK+DaJ39Mt/ZGWfW2NpragwSjJvGWIJpx6m7OQghqZYtaySLaEkA7jwk8JeliWZSXpf7oj/6Ixx9/nGeffZbOzs5TruM4Dtdffz0f/ehH+cQnPgFwxnBzqpqbrq4uGW4kSVoUhBDYlkutZDF6OMf+F8cZ3JM+qY2RokA0GSAYM9F0L0ApqkI5Vyc/WZ25vKbqCsklYVqWRoi2BNANbSZwKdNTFCgKhOI+WnuiZ9WYWprNsV3G+woY07WDpwufi1mtPN1tPPTmtxFbdOHmU5/6FD/60Y94+umn6e3tPe16uVyOpqYmNO34eACu6yKEQNM0fv7zn3PbbbfN+VyyzY0kSYtdOV/n4Cvj9O1MUy02KGVqNGrOGR+nmyp2wz3jescEYybLr06xYnMLTe0hDFNDM9ST2v7UyhYHXh5n3wuj1Ks23eub6b0qSceKuFdDtUhMDhQpZb0G4/6wgenXZ0KkZij4g8acYU8IQTFdY/hAjv6dUwzsyWDVvddFVRWa2oPe5UThBR+AZFeE9hUx2pbFMP2nbikihCA/WWX0UB7Dp9G1LoEv8Oa2KnEcl6G9Wcr5Or1XJgmEZ/f8G+8rsOvpYQ6+Ms7V71rKdb+97E3dH1hE4UYIwac+9Skee+wxtmzZwsqVK+dc33Vd9uzZM+u+v//7v+eXv/wljzzyCL29vWfsZSXDjSRJlxshBJVCg+xomVrZxrG9Bsuu7RKM+oilAtO1NCqFqSoT/UUmB4pUCg3shoNtuV7oEQIhvO7w6ZEyjerJjakVBQyfhhnQMXwahk8jPVLGsU4OTbpPo3N1E90bmlm6PkG0OeDtr+udrHMTFcJNPqLJwGlP7K7jkh4uM9FfwPTrdK1LnFUtgRCCUraO3XBwHYHrCMyARjjhn7k8N3wgyyuP9zG8/+QBAmcdu6oQCBsEoiaBsIEvqOMLGhg+jexYmYn+4km97wIRA9cV1MtzN0xXVIVER4h4S4Bws59A2KBWtillaoweylHOHx+6QFUV2lfEaOmOTl/iVFB171Kntyj4QwZNbSGiLQEUxRuiYKKvSGGq6q1jqJgBjUgiQDTpxwzo5Ceq5MYrDB/IcmjrxMyxaIbKqre1suyqFqYGixzZPsXkQHFmf5auT/Dbn7pq3q/JuVo04eaTn/wkP/jBD/jxj388a2ybWCxGIOC9CT7/+c8zPDzMd77znVNu40yXpd5IhhtJkqQzcyyXwX0ZDm+doG9neubyw+k0Lwmx7sYOIgk/R3dM0bcrPWssIYCm9hChmMnkQPGkXmjBmEkwanq1JiEDq+FQyXuBzT4hOCmqQvvymFcDMl2JEoyYxFuDNLUF8QUNhCvIjVfo2zlF/640pezJcysdu/Rm+HWyo97gfqqq0NwZpl6xqJVtrJrttYsCXHd+p0pVVUh2hene0EzPFUlauiKgQClbJz1UIj9VRdO8MOJYLuNHC4wcylFM1+berqbQ2hOlVrbm1Tj9GE1XMXzaGV+/UwlEDIJRk/TwyYMfqrrCis0pNtzUSduy6AXpybdoekt9/etfB+CWW26Zdf+DDz7IfffdB8Do6CgDAwMXeM8kSZLe2jRDpWdjkp6NScA7udt1B2t6adRsGjWHRtUmkvCT7Do+lk/vlS0IVzA1VKJ/V5qB3WnGjuTJjpZngoRmqMRTQcq5OrWyRSXfoJJvnHJffEGdVHeEct7rpTZyMMfIwdy8j0XVFAyfhqopqKpCrWLjWO506Kmj6grrbujg6ncvnaldeiPHcakVLSqFBpVCg1rZol6xqFdsGlWbaDJAqjtKc2cI3Th5KoVIwk8kcXKPvo23eLelrDf4YzHjNT6vlSz8YS9cpJZGaF0WwzC97eYnK/TvSlNM13BsMVNT59XWeb8fq8k7NuzAseDW1B5EuGA3HOoVm2K6RilbQwivnOOtQZo7QizflKJzTROKqjB2OM/rvxpiYqBIS1eEztVxlm9OnXSp6lJySbS5uZBkzY0kSdKFVytbDO3L0qjatHRHSHSEZi4L1coWhakq1aJFrdSgVrYxfBrBqEksFSCeCs60dSlMVRnYk6FW8oKQEFDK1cmOlsmNV7Aa3oncHzboXpege2OSJavi6ObxwCFcQaXYoJiuUc7Vae2NnvNQApcy4QqKmRq1skWi49ShC7zgZtWcS34akkVzWepikOFGkiRJkhafszl/L55m7JIkSZIkSfMgw40kSZIkSZcVGW4kSZIkSbqsyHAjSZIkSdJlRYYbSZIkSZIuKzLcSJIkSZJ0WZHhRpIkSZKky4oMN5IkSZIkXVZkuJEkSZIk6bIiw40kSZIkSZcVGW4kSZIkSbqsyHAjSZIkSdJlRYYbSZIkSZIuKzLcSJIkSZJ0WdEv9g5caEIIwJs6XZIkSZKkxeHYefvYeXwub7lwUywWAejq6rrIeyJJkiRJ0tkqFovEYrE511HEfCLQZcR1XUZGRohEIiiKcrF3501TKBTo6upicHCQaDR6sXdn0ZLluDBkOZ4/WYYLQ5bjwrgY5SiEoFgs0tHRgarO3armLVdzo6oqnZ2dF3s3LphoNCrfwAtAluPCkOV4/mQZLgxZjgvjQpfjmWpsjpENiiVJkiRJuqzIcCNJkiRJ0mVFhpvLlM/n44tf/CI+n+9i78qiJstxYchyPH+yDBeGLMeFcamX41uuQbEkSZIkSZc3WXMjSZIkSdJlRYYbSZIkSZIuKzLcSJIkSZJ0WZHh5iL4+7//e3p7e/H7/WzevJlnnnlmzvWfeuopNm/ejN/vZ9myZfzDP/zDSes8+uijrFu3Dp/Px7p163jsscdOu72vfOUrKIrCZz7zmVn3j4+Pc99999HR0UEwGOSOO+7g4MGDs9a55ZZbUBRl1nL33XfP/+AX0GIuR4AXXniB2267jVAoRDwe55ZbbqFarc7v4BfQYi3Hvr6+k/4Xjy0PP/zw2RXCeVqsZQgwNjbG7/7u79LW1kYoFGLTpk088sgj8z/4BbSYy/Hw4cO8733vo6WlhWg0yoc+9CHGx8fnf/AL6GKU4/3333/S+7CtrW3WOkII7r//fjo6OggEAtxyyy3s3r171jr1ep1PfepTJJNJQqEQ73nPexgaGjr7QhDSBfXQQw8JwzDEN77xDbFnzx7x6U9/WoRCIdHf33/K9Y8cOSKCwaD49Kc/Lfbs2SO+8Y1vCMMwxCOPPDKzzvPPPy80TRNf/vKXxd69e8WXv/xloeu6ePHFF0/a3ssvvyx6enrEFVdcIT796U/P3O+6rrj++uvFO97xDvHyyy+Lffv2iX//7/+9WLp0qSiVSjPr3XzzzeJjH/uYGB0dnVlyudzCFdA8LfZyfP7550U0GhVf+cpXxK5du8SBAwfEww8/LGq12sIV0jws5nK0bXvW/+Ho6Kj40pe+JEKhkCgWiwtbUHNYzGUohBC33367uPbaa8VLL70kDh8+LP7Lf/kvQlVVsW3btoUrpHlYzOVYKpXEsmXLxPve9z7x+uuvi9dff128973vFddee61wHGdhC+oMLlY5fvGLXxTr16+f9X6cmJiY9VwPPPCAiEQi4tFHHxU7d+4UH/7wh0V7e7soFAoz63ziE58QS5YsEU8++aTYtm2buPXWW8WVV14pbNs+q3KQ4eYCe9vb3iY+8YlPzLpvzZo14q/+6q9Ouf5f/MVfiDVr1sy67+Mf/7i4/vrrZ37/0Ic+JO64445Z67z73e8Wd99996z7isWiWLlypXjyySfFzTffPOsNvH//fgGIXbt2zdxn27ZIJBLiG9/4xsx9b3zcxbLYy/G6664TX/jCF+Z3sG+ixV6Ob3TVVVeJP/iDPzjt398Mi70MQ6GQ+M53vjNru4lEQvzv//2/5zjqhbeYy/FnP/uZUFVV5PP5mXUymYwAxJNPPjmPo184F6scv/jFL4orr7zytPvluq5oa2sTDzzwwMx9tVpNxGIx8Q//8A9CCCFyuZwwDEM89NBDM+sMDw8LVVXFE088cdptn4q8LHUBNRoNtm7dyrve9a5Z97/rXe/i+eefP+VjXnjhhZPWf/e7382rr76KZVlzrvPGbf7RH/0Rv/mbv8ntt99+0vPU63UA/H7/zH2apmGaJs8+++ysdb///e+TTCZZv349n/vc52YmI71QFns5TkxM8NJLL5FKpbjhhhtobW3l5ptvPqmc32yLvRzfaOvWrWzfvp2PfvSjp/z7m+FyKMMbb7yRf/7nfyaTyeC6Lg899BD1ep1bbrnlDEe/cBZ7OdbrdRRFmTXmi9/vR1XVC/q+vtjlePDgQTo6Oujt7eXuu+/myJEjM387evQoY2Njs7bj8/m4+eabZ7azdetWLMuatU5HRwcbNmw47f6fjgw3F9DU1BSO49Da2jrr/tbWVsbGxk75mLGxsVOub9s2U1NTc65z4jYfeughtm3bxle+8pVTPs+aNWvo7u7m85//PNlslkajwQMPPMDY2Bijo6Mz691zzz380z/9E1u2bOE//af/xKOPPspdd901/0JYAIu9HI+94e+//34+9rGP8cQTT7Bp0ybe+c53nrJtzptlsZfjG33zm99k7dq13HDDDXMf+AK6HMrwn//5n7Ftm+bmZnw+Hx//+Md57LHHWL58+fwL4jwt9nK8/vrrCYVC/OVf/iWVSoVyucyf//mf47ruaf9f3wwXsxyvu+46vvOd7/Czn/2Mb3zjG4yNjXHDDTeQTqdntnHscafbztjYGKZp0tTUNO/9Px0Zbi6CN85GLoSYc4byU63/xvvn2ubg4CCf/vSn+d73vjfr28eJDMPg0Ucf5cCBAyQSCYLBIFu2bOHOO+9E07SZ9T72sY9x++23s2HDBu6++24eeeQRfvGLX7Bt27Z5HPnCWqzl6LouAB//+Mf5/d//fa6++mr+5m/+htWrV/Otb31rPoe+oBZrOZ6oWq3ygx/84ILW2pxoMZfhF77wBbLZLL/4xS949dVX+exnP8sHP/hBdu7cOY8jX1iLtRxbWlp4+OGH+dd//VfC4TCxWIx8Ps+mTZtO+f/6ZrvQ5Qhw55138v73v5+NGzdy++238/jjjwPw7W9/+7z2bb7rvNFbblbwiymZTKJp2kkJdGJi4qQ0e0xbW9sp19d1nebm5jnXObbNrVu3MjExwebNm2f+7jgOTz/9NH/3d39HvV5H0zQ2b97M9u3byefzNBoNWlpauO6667jmmmtOe0ybNm3CMAwOHjzIpk2b5l8Y52Gxl2N7ezsA69atm/Vca9euZWBg4GyL45wt9nI80SOPPEKlUuHee+89+4I4D4u9DA8fPszf/d3fsWvXLtavXw/AlVdeyTPPPMPXvva1U/aaeTMs9nIE79LP4cOHmZqaQtd14vE4bW1t9Pb2nnvBnKWLVY6nEgqF2Lhx40xt9LGeU2NjYzOfgW/cTltbG41Gg2w2O6v2ZmJi4qxrZGXNzQVkmiabN2/mySefnHX/k08+edoX7u1vf/tJ6//85z/nmmuuwTCMOdc5ts13vvOd7Ny5k+3bt88s11xzDffccw/bt28/6ZtFLBajpaWFgwcP8uqrr/Le9773tMe0e/duLMua9c/6Zlvs5djT00NHRwf79++ftf6BAwfo7u4+y9I4d4u9HE/0zW9+k/e85z20tLScXSGcp8VehpVKBQBVnX0q0DRtpobxQljs5XiiZDJJPB7nl7/8JRMTE7znPe85u8I4DxerHE+lXq+zd+/emXNDb28vbW1ts7bTaDR46qmnZrazefNmDMOYtc7o6Ci7du06+8vNZ9X8WDpvx7rpffOb3xR79uwRn/nMZ0QoFBJ9fX1CCCH+6q/+Svzu7/7uzPrHuun96Z/+qdizZ4/45je/eVI3veeee05omiYeeOABsXfvXvHAAw+ctrvjMafq9fQv//Iv4le/+pU4fPiw+NGPfiS6u7vFXXfdNfP3Q4cOiS996UvilVdeEUePHhWPP/64WLNmjbj66qvPupve+VrM5SiEEH/zN38jotGoePjhh8XBgwfFF77wBeH3+8WhQ4cWoHTmb7GXoxBCHDx4UCiKIv7t3/7tPEvj3CzmMmw0GmLFihXiHe94h3jppZfEoUOHxH//7/9dKIoiHn/88QUqoflZzOUohBDf+ta3xAsvvCAOHTokvvvd74pEIiE++9nPLkDJnJ2LVY5/9md/JrZs2SKOHDkiXnzxRfFbv/VbIhKJzDyvEF5X8FgsJn74wx+KnTt3io985COn7Are2dkpfvGLX4ht27aJ2267TXYFXyy+9rWvie7ubmGapti0aZN46qmnZv72e7/3e+Lmm2+etf6WLVvE1VdfLUzTFD09PeLrX//6Sdt8+OGHxerVq4VhGGLNmjXi0UcfnXMfTvUG/upXvyo6OzuFYRhi6dKl4gtf+IKo1+szfx8YGBA33XSTSCQSwjRNsXz5cvEnf/InIp1On30hLIDFWo7HfOUrXxGdnZ0iGAyKt7/97eKZZ56Z/8EvoMVejp///OdFZ2fnBR9P5ESLuQwPHDgg7rrrLpFKpUQwGBRXXHHFSV3DL5TFXI5/+Zd/KVpbW4VhGGLlypXif/yP/yFc1z27AlggF6Mcj41ZYxiG6OjoEHfddZfYvXv3rHVc1xVf/OIXRVtbm/D5fOKmm24SO3funLVOtVoVf/zHfywSiYQIBALit37rt8TAwMBZl4GcFVySJEmSpMuKbHMjSZIkSdJlRYYbSZIkSZIuKzLcSJIkSZJ0WZHhRpIkSZKky4oMN5IkSZIkXVZkuJEkSZIk6bIiw40kSZIkSZcVGW4kSZIkSbqsyHAjSdJFs2XLFhRFIZfLXfDnVhQFRVGIx+PzWv/YviqKwr/7d//uTd03SZLOjww3kiRdELfccguf+cxnZt13ww03MDo6SiwWuyj79OCDD3LgwIF5rXtsXz/0oQ+9yXslSdL5kuFGkqSLxjRN2traUBTlojx/PB4nlUrNa91j+xoIBN7kvZIk6XzJcCNJ0pvuvvvu46mnnuKrX/3qzKWdvr6+ky5L/eM//iPxeJyf/OQnrF69mmAwyAc+8AHK5TLf/va36enpoampiU996lM4jjOz/UajwV/8xV+wZMkSQqEQ1113HVu2bDnr/dyxYwe33norkUiEaDTK5s2befXVVxeoFCRJulD0i70DkiRd/r761a9y4MABNmzYwH/+z/8ZgJaWFvr6+k5at1Kp8Ld/+7c89NBDFItF7rrrLu666y7i8Tg//elPOXLkCO9///u58cYb+fCHPwzA7//+79PX18dDDz1ER0cHjz32GHfccQc7d+5k5cqV897Pe+65h6uvvpqvf/3raJrG9u3bMQxjQcpAkqQLR4YbSZLedLFYDNM0CQaDtLW1zbmuZVl8/etfZ/ny5QB84AMf4Lvf/S7j4+OEw2HWrVvHrbfeyq9+9Ss+/OEPc/jwYf7pn/6JoaEhOjo6APjc5z7HE088wYMPPsiXv/zlee/nwMAAf/7nf86aNWsAzioYSZJ06ZDhRpKkS0owGJwJNgCtra309PQQDodn3TcxMQHAtm3bEEKwatWqWdup1+s0Nzef1XN/9rOf5Q//8A/57ne/y+23384HP/jBWfsiSdLiIMONJEmXlDdeBlIU5ZT3ua4LgOu6aJrG1q1b0TRt1nonBqL5uP/++/md3/kdHn/8cf7t3/6NL37xizz00EO8733vO4cjkSTpYpHhRpKkC8I0zVmNgBfK1VdfjeM4TExM8I53vOO8t7dq1SpWrVrFn/7pn/KRj3yEBx98UIYbSVpkZG8pSZIuiJ6eHl566SX6+vqYmpqaqXk5X6tWreKee+7h3nvv5Yc//CFHjx7llVde4a//+q/56U9/Ou/tVKtV/viP/5gtW7bQ39/Pc889xyuvvMLatWsXZD8lSbpwZLiRJOmC+NznPoemaaxbt46WlhYGBgYWbNsPPvgg9957L3/2Z3/G6tWrec973sNLL71EV1fXvLehaRrpdJp7772XVatW8aEPfYg777yTL33pSwu2n5IkXRiKEEJc7J2QJEm60BRF4bHHHjvrqRTuu+8+crkcP/rRj96U/ZIk6fzJmhtJkt6yPvKRj9DZ2TmvdZ955hnC4TDf//733+S9kiTpfMmaG0mS3pIOHToEeJejent7z7h+tVpleHgY8HphnWm8HkmSLh4ZbiRJkiRJuqzIy1KSJEmSJF1WZLiRJEmSJOmyIsONJEmSJEmXFRluJEmSJEm6rMhwI0mSJEnSZUWGG0mSJEmSLisy3EiSJEmSdFmR4UaSJEmSpMuKDDeSJEmSJF1W/v+6fv6ZBpd6xwAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "([(np.int64(98), 'TLIM'), (np.int64(2), 'WALL')], [])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from a5py import Ascot\n", "a5 = Ascot(\"ascot.h5\")\n", "\n", "# Get final (R,z) coordinates of all markers that hit the wall\n", "r,z = a5.data.active.getstate(\"r\", \"z\", state=\"end\", endcond=\"wall\", ids=None)\n", "\n", "# Plot (time, energy) of confined marker orbits\n", "ax = plt.figure().add_subplot(1,1,1)\n", "a5.data.active.plotorbit_trajectory(\"time\", \"ekin\", endcond=\"not wall\", axes=ax)\n", "plt.show(block=False)\n", "\n", "# Summarize simulation\n", "a5.data.active.getstate_markersummary()\n", "\n", "# Visualize losses\n", "\n", "# Etc... see the documentation of RunGroup for details" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Live simulations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Python interface to `libascot.so` provides a way to run simulations directly from Python.\n", "These \"live\" simulations are equivalent to those run via `ascot5_main` except that the markers, options, and results are not stored in the HDF5 file.\n", "These simulations are convenient to use, but the main intention is to use them for post-processing or light simulations on a desktop.\n", "\n", "Running live simulations requires that you have the inputs (excluding markers and options) present in the HDF5 file." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.902927Z", "iopub.status.busy": "2025-04-01T09:03:42.902753Z", "iopub.status.idle": "2025-04-01T09:03:42.955855Z", "shell.execute_reply": "2025-04-01T09:03:42.955401Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/runner/work/ascot5/ascot5/a5py/ascotpy/libsimulate.py:298: AscotUnitWarning: Argument(s) r, phi, z, time, mass, charge, energy, zeta given without dimensions (assumed m, degree, m, s, amu, e, eV, rad)\n", " r, phi, z, t, m, q, energy, pitch, zeta, anum, znum, w, ids = parse(\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Input initialized" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "from a5py import Ascot\n", "a5 = Ascot(\"ascot.h5\")\n", "\n", "# This method initializes and \"packs\" inputs in a single array. No input data can be freed while the\n", "# data is packed.\n", "a5.simulation_initinputs()\n", "\n", "# Marker input can be anything but here we just use the on ascot.h5\n", "mrk = a5.data.marker.active.read()\n", "a5.simulation_initmarkers(**mrk)\n", "\n", "# Options input can also be anything but here we just use the on ascot.h5\n", "opt = a5.data.options.active.read()\n", "a5.simulation_initoptions(**opt)\n", "\n", "print(\"Input initialized\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Running the live simulation returns a `VirtualRun` object which in many ways behaves similarly as the `RunGroup` introduced earlier." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:42.957522Z", "iopub.status.busy": "2025-04-01T09:03:42.957228Z", "iopub.status.idle": "2025-04-01T09:03:45.173749Z", "shell.execute_reply": "2025-04-01T09:03:45.173223Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[8.4246827 4.05556308] m" ] }, { "name": "stdout", "output_type": "stream", "text": [ " " ] }, { "name": "stdout", "output_type": "stream", "text": [ "[0.30535659 0.92601604] m" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "data": { "image/png": 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ZwkwkaNdrVBfmqS0u0K7XMBOJle8lUYDA9wl8L/65OQ5uq4nbbuE2G2iGQc/oGL1jWyj2DVzTrsZWrcrJ/fuYfG4v5bkZnEYdd+V30W01z1lfNy0ynV1kO7tWA0yrWqHdqJ9TRbwQw7JJ5Qso6umgFIUhjXKJ0PfPWd9Kpugd24LntGlVK0RhSLazm2xXN7mubsxEErfVwm01cJtNAs9D1XU0TUPVDaxUikQ6g51Or1ZJu0c3kUhnruzAnYcQAoQgiiKEEAgRYZjWVd3H5bplws2XvvQlNE1jbGwMgE9/+tN89KMf5emnn2bnzp3nrH/ixAl27drFz/7sz/JzP/dzfPvb3+bnf/7n+Zu/+Rt++Id/+JL2KcON9FL20Ec+xMTep8l29ZDr6SXX1YOZSFBdmKcyP0tlbma1CqNbFnYqTbrYwcDW7Qxs3Unf5q1EYUhteZHG8hJRGNK1YSMdA0M33afRwPc58dTj7P/WN6gvL9I5vIGe0U10b9iEmUiwMH6c5x7+Kif3P7f6mlMnYyEiojAkiiIKfQMr738HXSOjN937vJAwCAg8F0030E3zBd/zmT9+jJlD+5k/cYyF8eOUZ6avevXsFDORpHfTZvo2b42Xsa3Y6Qyh78ft9D3a9VocMmpVWpUKTqO2GpadRh233ULTdQzTQjNMPKdNe2X9ZqV8Se24kgqhncmS7ewi19VDtqubYv/gSmgfIFUorlkBElFEs1qhtjjP8vQUE3ufYWLv0ziN+mXt+5IoCj2jY4zsvoOOgSEC3yPwfALPJfBcfDd+jIIQVddQVQ1V19FNCyuRwEwm0Q2Tyvwcy1MTLE1NUJmfJQrDs3bzgb/90prv9Xq5ZcLNWorFIh/96Ed597vffc73fuVXfoV/+qd/4sCBA6vPvec97+HZZ5/lO9/5ziVtX4Yb6aXMbbUwbfu8n6CFELitJrppoRvGdW7djVGZm+Xgtx/hwKMPU5o5ecF1FUUlkc2SzOVJ5vKk8gXyPX3xuKCBQSA+xm47/sTdNbyBfG//VT8hRFFIeWaGxYnjLEycoDI3sxoATlUqAs89fXJSFDLFTgp9fWS7eqkuzDF75BCB556zbTudQYgIt9UCIVA1nWxXF9muHpLZHJ4TV8/cVgsA3TDQDRPNNDFMCzOZxEqmsJJJvHaLuWNHmD9xjMA9d19XW+fQCEO7dtMzOkYim8VOxRUOK5mKf6dNE03XCXyf+vIi9aVFakuLaJpGMlcgmc+TzOYwbHslAGgoinrVfn5RFDJ/7CiLkyew0xlSubjiU1tcoLa0GHcTOw5WMoWdSq22OwoDwjAk9Dzcdmv15+w06zTLJcqzM1elfRfzC3/zjzd0DNstGW7CMORzn/sc73jHO3j66afZsWPHOes88MAD7Nmzhz/6oz9afe6hhx7i7W9/O61WC+MS/hjLcCNJ0lqEECyuBAVV01F1DQQsjB9n5tB+Zg4fXLN742LSxQ6Gdu5maMdt9G/dTrF/8LJOlu16jdL0SRYnTrAwcZzFiRMsTU6sGUwul53JMrB1B72bNtM9upHuDZtIF4pAXHnwHAfDtl70CS0KQ5ZPTjJ79BCzR+Jl+eTk2SspCol0Jg6O2RyJXJ5EJkvijO4XM5GIqzyuS+D7mLYdr5vNkensIpnNvah23qoapWUm9j3DxL5naFUrcYgzTAzTjEOdZWFY8c8xikKiIA5LgeuuhlXfcch0dtE5OEzn0AjFgSH0ldcoqoKiqhiWLSs3l2rfvn3cc889OI5DOp3ms5/9LG95y1vWXHfLli28853v5Nd+7ddWn/uP//gPXvWqVzEzM0NfX985r3FdF/eMTwy1Wo2hoSEZbiRJuiynuhla1QqtSplmtUKzUqY0fZLl6UnKM9OomhaPR0kmURSVxYkTRGFw1nbsdIb+LdvoGBxGUZSV8QyCMIgHvIaeR+B51EtLlGdnztuNoVsWXSOjdI+MUhwYJpnNroYAK5nEsGx0y0I3Lbx2i/LsDJW5GSrzc6QLRQa374yD1g265N5z2oRBgKbraLqBqmk39MQp3fwuJ9zc8GvUtm7dyjPPPEOlUuHzn/8873jHO3jkkUfWrNwA5/zyn8pm5/tP8eEPf5gPfehDV7fRkiS95CiqSrpQXK1sXArfdZg5fJCT+/cxtf855o8dwWnUOf7U4xx/6vFL3k66o5PukVG6RkbpGtlI18go+d7eS66o6EaOZDbHwNbtl7zPa820Eze6CdI6dsMrNy/0ute9jk2bNvFnf/Zn53zvSrqlZOVGkqSbRRj4LI6fYPrQAWqL8ytX2CigKPEEhoax0qVgkMwVKPYPkO/tw7DsG910SbrhbqnKzQsJIc4KI2e65557+NKXvnTWc1/5yld4+ctfft7xNpZlYVk39vI1SZIkAE036B3bQu/YlhvdFEla127o/Oa/9mu/xre+9S3Gx8fZt28fv/7rv87DDz/Mj//4jwPwwQ9+kJ/6qZ9aXf8973kPExMTfOADH+DAgQP85V/+JX/xF3/BL/7iL96otyBJkiRJ0k3mhlZu5ufn+cmf/ElmZ2fJ5XLs3r2bL3/5y7z+9a8HYHZ2lsnJ0yPqR0dH+dd//Vd+4Rd+gT/5kz+hv7+fj3/845c8x40kSZIkSevfTTfm5lqTl4JLkiRJ0q3ncs7f8ra7kiRJkiStKzLcSJIkSZK0rshwI0mSJEnSuiLDjSRJkiRJ64oMN5IkSZIkrSsy3EiSJEmStK7IcCNJkiRJ0roiw40kSZIkSeuKDDeSJEmSJK0rMtxIkiRJkrSuyHAjSZIkSdK6IsONJEmSJEnrigw3kiRJkiStKzLcSJIkSZK0rshwI0mSJEnSuiLDjSRJkiRJ64oMN5IkSZIkrSsy3EiSJEmStK7IcCNJkiRJ0roiw40kSZIkSeuKDDeSJEmSJK0rMtxIkiRJkrSuyHAjSZIkSdK6IsONJEmSJEnrigw3kiRJkiStK/qNboAkSZIkXQthvY6zbx/e1EnCWhUtkyHzutehd3be6KZJ15gMN5IkSdItJVhepvKFL+AeOIA5uhFF1wgWF1FTadRsBm9iAm98HOfZvQjfP+u1c7/126Re8QoSe/ag2hatp59B+B6KbmDv2IE5uoFgfgEAc3QDid270Ts6ru37KZdpPf44qmWRvPtu1ETimu7vpUARQogb3YjrqVarkcvlqFarZLPZG90cSZIk6TKIIODIq19DuLx8SesbQ0NYGzeiFQq4x4/j7N17eTtUVZKvuJvEzp3o/f0kbrsNLZ+n9b3v4c/MErVaaIUCemcHwg/wpiZxDx3G3DhK9g1vILFnD4qmAeDPz0MYIqKI9rPPEjWbOAcOUPncP0AQxLvLZCi+4x2kXvkKrG3b0dIpALyTJ6l96Uv4Cwsk77iD7A/+IIr60hpZcjnnbxluJEmSpFvK3G/9Nu29e0m/5tX4MzMgBHpnF2G1QtRsYQ4NYY5uwN6xA2vTprNe6x47RvM736W991miRpPk3Xeh5fJEjQbtZ57Bn53F6O1FiAjv6FHcI0dfVFu1QoHUvffiTU1dMFhZm8cIm02CmdnV5xTLIvmyOwkWl3CPHDlr/eQ9r6TwX38Uo6+XYLlEsDBPsLCIMTQEUYRiW3jHjmPv2kn6ta9FUZQrfg8iiggWFjB6e694G1eDDDcXIMONJEnSrU14HoppXpd9eVNTNL7xMN7JKbzxcdrP7iVqNEjs3o21dQtqMkVYKhGUS6imidbRgbVlC86ze6l//etE9frpjakqaBpEEfaOHeidnSiGQeHHf5zUK+5GRBG1f/5nav/6bzgHDxLMzZ1+raKQvPtu9I4O6l//OsJxLv1NKApoGkZ3N7n//J/JvvlNGAMDRI0GYa2GcBxEJAjm5/Amp9C7urB3bMc7cYLGww9T/8bDqMkkm/79yy8qJL1YMtxcgAw3kiRJ0pUSUQRBcEnhSvg+raefpvXd76Hlc2Tf8ha0jo64srLSVXXe1wpB++mncQ8fRu/uIbH7ttWB0O7xE5Q+/Wmc55/HO3ECxTCwd8fdZf7EJGoqSVCpoCaSOM89h3DdF/2+1XSajf/yLxg93S96W1dKhpsLkOFGkiRJWi9EFIGinLeiErVahI0GRBGtJ5+k+vnP03ryqdXAo2azqLYNgN7ZiTE8jD8zg3vwIHpvL+n77yfzfQ+SfPnLr1u17HxkuLkAGW4kSZKklzLheUSui5pKnXdQshDihnZBreVyzt/yUnBJkiRJeglRTBPtIlWYmy3YXK6X1nVkkiRJkiStezc03Hz4wx/mrrvuIpPJ0N3dzdve9jYOHTp00df9yZ/8Cdu3byeRSLB161Y+85nPXIfWSpIkSZJ0K7ih4eaRRx7hve99L9/97nf56le/ShAEvOENb6DZbJ73NZ/4xCf44Ac/yG/+5m/y/PPP86EPfYj3vve9fOlLX7qOLZckSZIk6WZ1Uw0oXlxcpLu7m0ceeYQHHnhgzXXuvfdeXvWqV/HRj3509bn3v//9PPHEEzz66KMX3YccUCxJkiRJt55bdkBxtVoFoFgsnncd13WxVy5bOyWRSPDYY4/h+z6GYZyzvnvGNf61Wu0qtliSJEmSpJvNTTOgWAjBBz7wAe677z527dp13vXe+MY38ud//uc8+eSTCCF44okn+Mu//Et832dpaemc9T/84Q+Ty+VWl6GhoWv5NiRJusVcq+J1GAkmlps4fnhNti9J0vndNN1S733ve/mXf/kXHn30UQYHB8+7Xrvd5r3vfS9/9Vd/hRCCnp4efuInfoLf/d3fZX5+nu7us2dPXKtyMzQ0JLulJEkC4D/9/77NXNWhO2vTnbHozdps7kmzrTfLcDHJ+HKTA7M1JkstikmTnpzN7sEcW3syq5fLLtZdnp4sc7LcZrrS5sBsjWenKjS9kFzC4EfvGuInXjnCYCFxziW2QggqLZ/x5SaLdZeaE1Br++STBrsGcmzqSqOpl3ZZbtMNeH6mRt3xMTQVQ1PpTJts7slc9eN2q2h7IQfnaoRRPG9LxtYZ60qjvuCYLtQd9k5V6c8n2NabOef70o13y03i9773vY8vfvGLfPOb32R0dPSSXuP7PvPz8/T19fG///f/5ld+5VeoVCqoF7lLqhxzI0nSme7+7f/LQv3yp6cf6Uhy31gn+2drPDNVYa2/pKoC0RnP66pC2tZJGBqqoqCqUG351JzgvPtJGBrb+jJs6Egx0pFkuJjE0FSCKMIPBQ0nDjR7T1Y4uthYsx2vGC3y379vM/ds6rjg/CVNN2Cp4ZIwNDrT1jkneCEEB2brfP3gPF87uMDR+Qb9+QQbOpNs6Egx3JFkpBi3s9r2eexEicfHS0yVW/TnEgwXkwwWEqRtA9tQUVB4ZqrM4+NldFVhuJikkDJpOAE1x6fuBKQtnaFigqFiknzSZHypyZGFBieWGiRNnf6cTcY2UBRQiOdnURWFSAj2TVfZe7KCH559UApJg3s2dVBMmUyV2kwsNxlfbq1+v5gyuXO4gKJAytTY1pdlpJik5viUmj41x1/ZF+iqykA+wXBHfAx6stYtP0fMzeqWCTdCCN73vvfx0EMP8fDDD7N58+Yr2s6rX/1qBgYG+OxnP3vRdWW4kSTpTDOVNgt1l4Waw0LdZbrS5vBcnYNzdaYrbQbyCbb3ZRntjE/Y05U2T4yXcYPorO1s682wsSvFQD7Bxq40dwzl2dSV5pHDi3z6P8Z59Oi53eZn6s3a9ORscgmDjK2zUHN4fqZGy7u8bq2+XFyB8kKBH0ZMLrfwwritLxspsKUnjRcIgiii6YaUmi5LDY+lhnvWvkxdpT9n052xcYKQuhNQanpU2/5ltedm0JWxSJkakeCc93mKosCmrjQzlfZlH/MzDeQTvGFnD2/Y0csdQ/nVyt/BuTqVlsfW3iw7+7Ps6M+StY2LbxCYqzo8M1Vh78kKE8stsgmDrrRJMWWST5rkkgaFpEl/3qYrvX7D1S0Tbn7+53+ez372s/zjP/4jW7duXX0+l8uRSCQA+OAHP8j09PTqXDaHDx/mscce4xWveAXlcpnf//3f56tf/SpPPvkkGzZsuOg+ZbiRJOlShZFYs0uo6QY8cniRx06U2NyT5vu29dCbs9fYwmktL6DWDmi4Pi0vJBIQCUHK1BkuJkmY595IMYwEJ5YaHJprMFFqMrHUYrLUIhJipdtJwdI1tvRm2D2QY/dQju7M2e2Yrbb504eP8TePT+G9IJCtJWFouEF4VsXpTLahct9YFw9u62bPcJ75msP4Ulz5mCy1mFhuMlVuY2kqL9tQ4K4NRTZ3p5mrOUwut5ipxuGh5YV4QcS23gyv3NiBrilMllpUWz4ZWyebMEhbOtW2z1SpzVS5RaXlMdKRYnN3mo1dadp+yGylTdMLQQgEIFaOayRgY1eKV452MFQ83R3ohxF7T1b47vESjh8yWEgwkE+yayBLPmniBfH3901XMXWVSstn/2yNmUqbXMKgmDLJJQwU4uqQG0ScLLeYWG4xXWkTnu/ArWGkI0l3xkJTFRKGRm/OpicbL3NVh+dnquybrjJfu/TKYsLQGC4mGV7ZthtEtL2Qth/iBiGuH+GFEaqi0Ju16c3ZdK2s13ACsgmdl40U2DNcIG3dVNcc3Trh5nzp8pOf/CTvfOc7AXjnO9/J+Pg4Dz/8MAAHDhzgx37sxzh06BCGYfDa176Wj3zkI2eFowuR4UaSpJei+ZrDPz4zjetHGLqKriokTI2OlEVH2qQ7Y9GZtkhZOn4YMVd1mF6paqVMjYwdV5RGO1PYxoXvaB1FIu4mWqcVhPNpeyHfOrLIV/bP87UD85RbPllbZ1tflu29GXIJgwNzdZ6frjJTdS55u6oCW3oy3DGUZ6w7Td2Juw8rLZ9K26Pc9Cm3POZrznlD6eVSFdjel+WVGzu4b3MnrxgtkjRvbNi5ZcLNjSDDjSRJknStBWFEueXTmTbXDHmlpseB2XjwdxAJmm7AXNVlruYwX3MoJE12DWTZNZBjZ3/2koKFF0RMV+IxRJOlFksND9tQSRoaCVPDNjRMTcUyVLwgDrBzNZelhottqKQsnfmqwxMT8eD4M5mayl2jBT79rrvRtRtzofUtO8+NJL2kNZfhkf8JG18DG+4DO3ejW3R1BS60K2AkwJYfLKT1TddUujLWeb9fTJm8aqzzqu7T1FVGO1OMdqZe9Lbmqg6Pj5f49tElvnVkielKm4YT3LBgc7lk5UaSbhbPfQH+4V3x14oK/XfGQWfjq6F7JwRt8Nvgt04/Gino2QHWdb7UNwqhVYLmIjQXoLGyNBeguQTtchxknMrpr4MzPgkWNkDv7njpW3lMd4N64e6Oc9pQn4XGfLzPxkK8LzsHmV5I98TbjML4eAXtOGAZSUgWIVEA3Y5Hkp5JCHCq8TYTeUhd5ATkNWFuH8w8AzNPx8ekbzcM3g2Dd0G6K37/S0dg6TAsH4m/bizEIXbXf4aeXee2Q5JuEkIIxpfjMU97hgs3rB2yW+oCZLiRblozT8NTfwUnHoHlo5fxQgWKG0+HhN7bQLfAd06f0P02iAgyfZAbgOxAfHI/dUINA6hMwPKx+OS7fDQ+SfsOBM5KoFrZnlONgw1X8qdDucjrFFB10AxQDUh1nA4p6d74taUTUD4B5QmIXuSVO4oahx0jCWYyPg7NBQi90+tk+uJj2rMrXs9rxIHGqcDcc7B0KD6252Pn4mN2IR2bYed/gq1vhq5tcVskSTqLDDcXIMONdEuoTMUh5/gjcPzh+ISrGqdPwkYi/rpVgvrMle3DSMYhR1GhdPwKgoISB6R0d7ykTj12xs/b+fgxkV/5Og9WNj7Rz+2Dub0wuzd+XDp84YBwPqq+st+u+DFRiENHfW6lorO4ctwS8aJbcTBplyE6/9wyAJjpOMhcikwf9N0B/XdAqisOqiefgMWDrIa5TD90bobOLfGjmYZD/wpHvgrhmVfDKJAfjkNO1xbIDYNbO10Ba5fjRVGhY2McjDrG4qWwAXTzMg8icahza+DW4+qZmYrbp61cquzW40rTqeN6atGslX1vipf11pUq3VRkuLkAGW6kW44QcdeKdp4hco3FOCCcCgsLBwARd7mcOqHrifi52gzUpqG1fO52dBuKm6Bz5USZ6Vupatjx6w17JVyl4xCTKJ6/TZfLX6kOhX4cOiIfAg9aS/FJtL5yMhUhFEbjSlVxNA5nF+rKEmLt7h4hTldgvObprj5FWwlKXfGxc+swvz8+tgv747aZ6dMn/65tcaDJ9K69f6cK1ZNxWDlf16FTg8Nfjrslp74bB5crpWjxz00z4vCjavGjosbfU5T4a4jfv1uP9x+0196eZsXrn+/7L5TqigMWSlzxC9z48dTvTLo7XifdHVfkrEz8sxDR6QXi7+WHIdt/6V2V9fmV/wPPxkv5RNz+Ux8ErDR0bYf+PfGS6ri07a4l9OMPFooSH1d1ZdHM+P/behSFK79HN677VIabC5DhRpKIw0RtOl6iIA4z2UG4yAzf0jUmRDzWZ+lQXPVZPBSPK7JzK1WwM5bAg9KxuAtx+WjcpXiplabz0e04YJzZLXfKakDpPR1O/Fa839KxOHxebaoeB9j8cLzoVnySFWH8GIVxGJzbe/n7zw/H49r698ThdLUqurKIEKrTcTitveCxMX/+SmN+BAbujLc98DLouz0OVhD/fAMnDr1ONQ7UUbgS6M9YFCX+Wej22R8wFGXl/Udx+04FwmjlUdXiKqmdu/QPHqe6YutzK5W5uTgonhrPdur55iL88rH4d+8GkeHmAmS4kSRpXRIiPgnVZuIT5Go1ZOUkGIWnqySIOKzY2bh6Yq08nuqGCrzTla3Ij7v8Tp2gz8epxd2blYm4mqHb8UlZs+Iur+biSnfWwumv3cbZ1SWUuH2Nubhr9rK6SpW4u+/UIPXOrfG2TlXlToWg6afiMPaiXWz82KnVVMgNxm1wqmsHx2vBzKx0BWfin33oxb8XoRdXnkJ/pULqcsnj537+e9C97Vq2+oJkuLkAGW4kSZJuTlEUUS6XWVxcZHlpiYwRMpQOyQeLKNUpHM+n5qnUPAiEimVomHYCs2crZt8OEtkipnn+MUdCCHzfJ2qViWb3Imb3wvx+wnaNhhvS9EKiwGMwmiWleZDtR2QGaCQHKendlEWWtprGyHRiZToYHBqikMuuVpMit8nJ575NuHCQwcY+jLmn4mrPCylqHCjN1EqXln7GosUh1G+vDOZvnx7UDyvdi+oa3Y5qHF6upHqnaHElLtMTV+YyZyxn/jvVdXlXNF5lcp4bSZIk6boKw5B2u41pmhiGsTpxnRAC13VpNptUKhUWFxdZWFhgcXERxzk9S28URVQqFcLw3Ps6pVIpgiDAdde6DUENmAe+iaqqbNu2jT179rBx40bK5TITExOMj48zOztLtVrF919YDRpa8/10dnaSVJMsnFhYaWd5ZTlbb28vQ0NDaJrGwYMHqVQqAGjaVoaHX8/ue0bY3qlhZwpxd5Gdi6splzt25Xzjx14o9OMqmlOJB6C7tZUrEM24q0oz40H22sqiJ+KpEW5gaLkWZOVGkiRpHQnDkFKpxPz8/OqytLSEYRgkk8nVJZVKrd7DL4oioigiDEOiKELTNAzDQNf11aDi+z6e5+G6Lo7j0G63aTQa1Ot1Go0Grdbpu2orioJt2+i6TqvVWjOwnI+u63R2dtLR0UGlUmF2dpYoOj2+xbZtstkshmHged5qmzzPO2s9TdMueb+KopBKpUin04RhyOLi4jnfz+VyFAoFkskkQRDQbDaZnp7mhadQy7IwDING43QFRVVVstks2WyWoaEhNm/eTKFQwDRNbNt+yd2m4krJbqkLkOFGkm5tTzzxBFEU0dnZSWdnJ5lMZs2TQxAEqKqKus4GSUdRdFbQaDabzM/PMzc3x9zcHAsLCwTBRS5zvwEMwyCTydDd3U1XVxfd3d2kUqmzfna5XI58Pn/Wz8zzPBYWFrAsi2w2i2Wd/2qkubk5nn76afbu3Uu73UbTNAYHBxkZGWF4eJhCoUAqlULTNFRVRVGU1eVMrVaLyclJPM+jq6uLzs5ODOPcO3g3m02OHDnC8vIynufR39/P9u3bMQyDpaUlDhw4wLPPPsvy8hpXJ66wLIve3l5yufgy+iAIKJfLlEolABKJBJlMhl27dnHHHXdc8P2vdzLcXIAMN5J0a/vjP/7js04WpmlSLBZJp9Mkk0nq9TrLy8vUajU0TVv9xJxMJrEsC9u2yWQy5HK51ZPrqbEYruuuViQcx6Grq4vBwcHV9ZaXl5mcnKTdbqOqKvl8ng0bNqDrOocPH2ZycpJ6vU673Wbjxo3cc8895PP51baeCiWpVDw9vhBitcpy6k+xqqrYtk0ikUAIwcmTJzl58iSlUolKpUK9Xr/oMTIMg56entWlq6uLMAxptVq0Wi2azSatVot2O77E+9TJ/tRyKkCdWoQQGIaBYRjYtr26pNNpMpnM6mMikSAIAhzHwXEcgiBYrRRdaCzM1RYEAcvLyxSLxTVDyfUkhKBarVKr1SiVShw/fpwTJ07QbDbPqjRdCtM02bVrF6OjowwPD5PL5VarbusxyL+QDDcXIMONJN3avva1r62O2SiXy+d0C9xsisUiPT091Gq11S6WZDJJZ2cn5XL5ksLKWhRFWe3W6Onpobe3d/WxUCis+xPdeuD7PsvLy8zNza1266mqSqFQWP0ZtlotZmdneeyxxy5YAYK4ynOqe61YLNLR0UFHRwepVGr1/4llWTdF6LsSMtxcgAw3krR+BEGwWtE4Ne4jnU7T0dFBoVDA931qtRq1Wo12u706XqRWq1GtVs8aJ2IYxmplJ51OY5omc3NzzMzM4HkeQgiSySQjIyPk83nCMGR+fp6pqSmiKGJ4eJixsbHVk9Ljjz/OiRMnLvoeNE2jp6dn9WQThuHqmJYoiujr62NwcJCenh5yuRy5XG51XIccq/HSEUURJ06c4MiRI0xOTjI7O/uign0ul1v9f6LrOoqirHbVaZpGd3c3Q0NDq91lNwMZbi5AhhtJkq4m3/eJomjNsRCtVouZmRnm5+fJZDIMDg6STqdZXFxkaWmJbDbL4ODgVfkUHbkBwosQYYRwQ8KGD1H85905VCasOCAgckOilo+WtdCLNoqloZgqasJAtTQiN54Px95aRC/al90OEQkU9ezQFTZ9gsUWwVKbsO4RNXwiN0TLmGgFC71go3ck0PLWOa9d3a4Q1z3MiUiAECg34Z2wT425UlUVTdPwfX+1y7Fer1MqlVheXmZ5eRnHcVaPXbPZPM9VZ2s7NQj61NLb24um3Zgrq2S4uQAZbiRJWo+WPvkczqEXceuGNRh9KdSMiZrQEUEEoUBNGWgZAzVloib1+E4Lyw7BYgtvukFYctCLNlpHgqjuEZRdhHOJA5x1BT1vo6YM1KSOoquIIMKfaRI2PKyRLPbWIonbOtEyJv5Sm7DmItrx9tWkQdTyCSouWsZE70zgzzYJFle6fNIm9uY8Rn96zRAlwnhfzuEy7okq3mQd4YeoGTMOYF0J9M4EakJfDYJR3SNqBSi2Fu+/4ROU2iiGhpa3MPtTGAMZtJx5U1TahBA0m83V4FOtVlfH7QghVsdbzczMMDc3d051yDRNfvmXfxldv/4zych5biRJkl5qTlUXdAXV1FBTBoqmIEKBMZDGGolPBoqto9oaYdUjKDvgR0ReSNQKEG6AYukIJ8A9XsWfbcJs87KbEiw7BMvOWc9peQu9K4GWs9BSBoqlEdY9wrJLsNwmKDkQCIKlNiytfS8r93gV93iV6r+duOQJgl+o9u+gpg3sbUWMrmQ8D8/xKv50nai5dgiLah5ezcObqF3+DleoaQNzMIMxkMboSqB3JFCzZvwehCBq+oQVl7DmxVU4N0JEAqM7id6VIKzEx1TRVVRbRzFU0BQiJ0A4cQAz+1OoKYOo6aMY2pqVN0VRSKfTpNNpRkZGLthmz/OYnp5mamqKqakpTp48ST6fvyHB5nLJyo0kSdI6ICIBCletOhBUHPzZJlHTJ2qHKIaKoiqETZ+o4RE2fKJ2AGGEXkygd9oY/Wn0zgTBcpuw7K5UPCy0go1qXrgrQ0QiPrlXHMJmgGgHcbUIMHqTqCkD92iF9v5l3ONVEHFQ0wsWaiI+2YZNHzWho+ctgopLsOxg9CTjSo0C/lIb92gF4Z5//hvF0rDG8thjecwNObS0QVhxCUptgsU4hEVOiHACFEtDy5hxxcYJiJo+aspA77ARQUSw5OBPN/AXmnAFN71/sYyhDKk7u0nu6Ua1X3wgEULQarVWr/a73mS31AXIcCNJknRrC5vxeCI1ffmDqkUQ4Z6o4hwpE9V9RBhhDmWxRrNoeQs1aZx33M+VEn6IN9vEn6rjzTbjStWyQ9RcmS1ZATVhoOetuPvK1lFNLZ6iYK5JsOyg5y30zgREIg5XQTy+SrXjLrKg4uLPNBFeiJrUiZzgdKDSFBRNQTE0Unf1YvQlQVEIqy5azkLvSkIkUHQFvSt51d//1SLDzQXIcCNJkiStR/EAaFA0hbDh0XpmkeZjcwQLrYu/eIWS0DGHMhhdCbSsCZpKsNDCm2mQefUQyds6r+E7uDA55kaSJEmSXmLOrLhoaZPMfQOkX9W/OjA6agW09y0RNX1EKNCyZtzlttwGXUU4cXege7iMe/jcweneVP2GhpvLIcONJEmSdFMTQhBEAYZ26008d6MpirI6mBwgubvrvOuKUODPNPBmGwQLbaJ2gPBD9KKNMZDGHL51ejtkuJEkSZJual+b/Bp/9NQf8Rv3/AZ39d51o5uzbimagjmUwRzKnPX8odIhthQ6b4pL2S+VDDeSJEnSTUsIwZ/v+3PGa+P89L//NA8OPcgPbPoB7u69m5x1evZcP/Q5UTtBT7LnrOeliztRPcFnD3yWqfoUGTPDbZ230ZPqYao+xVfGv8KB0gE+8+bPsKd7z41u6iWTA4olSZKkm1rNq/Hxpz7O3x/6e8TK5DYKCv3pfvpSfST0BHuX9lJ1qwB0J7r5/o3fzz3996yesHd37WYgPQCAEzi4oUvKiO+59OTCk1TdKv2pfnZ17rqkCsWldJXNNecIooCCXSBlXN/LpyMR8eT8k+xd3EvTb7Iht4HhzDAdiQ7Gq+NM1idZai/x+NzjPLv47AW3ZagGv3r3r/L2rW+/Tq1fm7xa6gJkuJEkSbo1HSkf4Z+O/RPfmPoGE7WJc76f0BO0g7UnAAR49eCrCUXIo9OPrq5vazZl9/Tg2R0dO/ihTT/E9uJ2QhGyIbuBrmQ8TkUIwb6lfXzp2Jf45slvMtOcIWNkSBgJclaOB4ceZE/3HrzQ44tHv8jXp76+ut3Xj7yen73tZxkrjGGoV3/sUN2r89jsY8y15jhRPcGj048y3Zi+pNcqKLxm6DW8Zug1lJ0yj88/Tstv0Z/uZ1fHLr5/4/dTsAtXvc2XS4abC5DhRpIk6da31F5iojbBQmuBlt9iIDPAXT134YQO35v9Hp87/DkmahOMZEeoulWeX36eSKw9k15nopOhzBDPLz2PF3nnfD9jZuiwO5hrzuGEzhpbWJuqqJiqedZrNEWjO9nNg8MPMpAeYKI2QShCNuc389axt55V4QmjEDd0SRrJs7YrhEAgUBWVqlvlE89+gs8d+tw5bc+YGe7tv5esmWWiNrFarRnODLMpv4miXWRLYQsPDD5Ab6r3kt/XjSLDzQXIcCNJkvTSc6J6gr/Y9xfYus1PbP+J1WBRdsvc0X0HhmpQckr887F/5muTX2OpvQTAVH1qtSsMwNZsXjfyOt604U3s6txF1aviBA7HKsf45slvcqh8CE3RuL3rdn5qx0+xMb+RQ6VD/K+n/xdPzD9Bw2+ct40pI0V3shtbszFUgyOVIziBszoGZqG1wFR9ipJTAsDSLNzw9E0wR3OjbM5vZiA9wM7Onbx68NXY+uXf/PRmJcPNBchwI0mSJF2qlt9ipjHDsrNMb6qX/nT/FXcrCSFYbC9ysHSQvz/096iKylh+DFVR+ffxf2e8Nn5F2x3NjfKrd/8q9/Tdc0td0XS5ZLi5ABluJEmSpJtNJCIOlA7Q9tu0ghbtoM1YfoyUkeI7M9+hFbToTnYzmB6kK9mFgkIraFG0i9d9sPKNImcoliRJki4o8EMURUHTVVo1j4PfmWXueJWOwTT9m/Pku5PopspzczXKbR9dV2l4IftOVnD8iA6hkpt2GSzYFIfS7J2vc2ShQTJnsmdLB/ft6iGXNNfct4gEpdkms8eqVBdahIEgCiN0U8NM6Bgr91WKQoHXDmhUXIQQbH1FLyM7O86595EQ4ppWLIQQOH6E44e4QUS55bHUcFlueCgKJE2dpKmhKgqqAmPdaTrS1mXtQ1VUdnbsXPN7/2nzf1rz+Q46Lvu9vFTIyo0kSdJN6jsPHUNRIJExSeZMBrcVSKTjwCAiQb3sEHgRYRARuCFuO8BtBSgqmLZOKm/R0Z9CURUWJ+sc/O4c04fKNCsubitAVRVy3QmqC22iaO1TwRdSLseMy7+ltSqgV9Fw1XhyOEtXMXWVlKZCxUd4EYaA/kClN1TxFXAVgQf4ikBHIRcppCKFJS1iWo+Y0+IAZJsaKUVlRGj0NwV6MyTXnaRrOEMqZ1IvubRqLh0DacZe1k3fWB71jEAU+hFhGGGucadsIQRHFhp89/gye09WObrQ4NhCg7obXPJ7V4DdfVnesLuPV27sYKw7TS4Rd2VVFlqUZppkO22ynYk12yCtTXZLXYAMN5Ik3Sr+939/BN8NV/+tqgpDO4ropsr0oQrOqbtKX4BhaSSyJrXF818iDdAzmmX09k6Wp5vMHq3QqnlEoeAbts+0HhIBBgrFUCEpFGa0iFlT4K+cQnKayrZ0ErflM+F4lLXrd2pJRWAKBVOAesbzCgoqUBQqw4rOkKbjuyHTYcCSJtA7LBLdNoGhxlUZP2S60mapce4VU6doqkIuYdCZMkmrKl47oOWHuKEgCCJcP6SinvveU5pKGhXLiVCBQIFUpLAlaXPXSIGtu7ug02Sp6a9WiPwwXoJIoCkKmqqQsXUGCgm60hbjyy32z9RImCr3bupkR1/2rBB3tUSRIIgEpq5efOVrSIabC5DhRlrPfvXwSQ43HbpMPV4Mgy5Tp3NlSagqhqqgK/FiKAqGqmAqCqYa/3s9D0i8lYhI8MS/jdOu+7QbHuW5Fssnz77SRtUVDEtD09W4opHUMRM6Qgi8dkh1sY3XjisOmq6y8Y5Oxl7eQ647QSpn4bshpZkm6YJFx0D6nDZEkSD0I6IwIgwE04fL7Hv4JPVlh/vevpmNd3TR9OLwlTK11d+dMIh4/kSZ5yYrJEJollzqNZe2E1D3Qsxem/xAmlLL47ETJY4tNklbOhlbJ23HXTwNN+RkqcVy06M/Z3PXaJHb+3I4yw6OFzLTdHlmqc7R8qXf8fpSmarCsKIzjE63otFrGIx0p+jqTeHVfeZO1CjPNeE8Z0/RabGv1eaI4rOgRTSuUyZIqyq7C2nuGsoz2JMin7XYd7zM18eX8RTBho4Uiy2Pk5U23RmLLT0ZLF0ljAShEDh+iBcIgiji2GL8uxaGgsWGyy++YSs/9+pN1+eNnIcMNxcgw420nr3xiUM8W7/wJ/SLSagqowmTzSmbLUk7fkxZbExYmOqN/eT2Uleea3LsqUVAMLC1SPeGDJp2/p/JqbEttaU2/ZvzWMlb78aTbhBi6dp5v19qesxVHRpuQNMN8MPTXWgCcL2QveNlnjlZ5bn5GrqqsK03y1ghiTfTojbVwAjjqpQmICGgJ1TRuXjIz3Ul6N2YI1Ww0HSVZMZgaEcHua4EURixPN1kebrBwkKTycUmrqmQHM1gJg0sQ+XwdI1vH1pk33ydIBJkIoW0UDBEPCDWUFV0TYFAxN2GuoKjQSkIaaqCbKTQHaq4imBSj/Cv4eeSd71qA//fH1x7TND1csuEmw9/+MN84Qtf4ODBgyQSCe69914+8pGPsHXr1gu+7q//+q/53d/9XY4cOUIul+NNb3oTH/vYx+jouPjgKhlupPXs8WqTk47Houez6AWnF99n2QtwIkEg4q6EUAj8SHCpoyk0BYqGvlrlMVX1BRUf8CIRL0LgRRFB/Pd4tUqkKwr6yvqacuqR1UqStlJJ0hXoMHT6LINey6TX1Om1DHosA0sGLOkKRZFAUTirOtkouxz63ixHHp9nebqJbqgMbiuw+a4eUnkr/r12QqoLbSrzLcykTu/GHD0bsiSzaw+YvlxhJBCRYOFEleNPLzF1sERlrnXecVAAfWM5ttzdS6bDxrA0nLbPdw8t852JZQ5VWzS9ECeKSOoad9oJEq2Q+bZPOoJ8pFJXBRUTcj1JkhkDO2mQTuqUJxssTtQpKCq5vE0ioWM7EVorZNNtnTz4k9uvynu+ErdMuHnTm97Ej/7oj3LXXXcRBAG//uu/zr59+9i/fz+p1NqXtj366KO8+tWv5g/+4A/4wR/8Qaanp3nPe97D5s2beeihhy66TxluJOlsoRC4kcCPIjwhqAcRR1sOh5sOR1ruyqNDI7z8QaXXQtHQ4tBjmvRacegZsk3GkjZjSYu8IQdoSlfGafiYSf2ajFu5XGEQUZlvEYUCMxF3PbqtALflky7Eg5EvV+CFVBbanDxY4rlvTlNduLwq78htHfzAe2+/7P1eLbdMuHmhxcVFuru7eeSRR3jggQfWXOdjH/sYn/jEJzh27Njqc3/8x3/M7/7u7zI1NXXRfchwI0mXTwjBnOdT9kPcKK7K+KuhSOCKCCHAekFFR1eUuEIkBIHgrIpRsPJ1ICAQYnU5FbaWvIBZz2fOPb14l/DnqsPQ2Zy02JS02JS02ZS0GE1YjCRMWfW5RH4kaIQhhTOCohdFPF1r8UStxaFmGwUFhfhnaqkK9+TT3F/I0Gtd/a6vZS/goYUyD5fqHGs5NMOIoqHTaeh0WwYdhsaSF5DRNV5bzLApabPg+VSDkGYYkdJU8rpGp2lQ0DVSukpSVc+q4DTDkO9WmhxotDnccjjechHAoG3yqnya/9RTIHOe7jF/ZcyKfYEuwpuNiATTRyosTNSozLdoll2aVY9if4o73ziMaeuU51p4ToCdNkikDZJZ66pVq67EVQ83H//4xy+7Ee9617vIZDKX9ZqjR4+yefNm9u3bx65du9Zc5z/+4z947Wtfy0MPPcSb3/xmFhYWePvb38727dv50z/903PWd10X1z09PXWtVmNoaEiGG0m6xQghKAchc67PrOszv/I45/mMt12OtVxm3PNfPaQCA7bJxpWgk1BV9NXB1WAoCp4QtMOIVhjRiuJHTVHoMXW6zbhbrMeMB2l3GDpFQ8e4CT7lX6lQCP7fz4/Tv9L9d6jZ5tvlBjOujwBGbJM92STLfsAT1Rbt6OLVu9GEyeakjaEq5HSNt3TleXUhw5TjMe/5jNgmPZbBkhcw5XiYqsLOdAIVWPACTjoe5SBkyfM50nJ5vt7m25XG6lVZV4uhKHSZOmNJix7L4MuLVeoXqE4mVJU3d+V4oJCmGUZMOh7P19scaTkseAGqAjtTCV6eS/GqQpoBy+TPphb4dqVBv2UynDBJayrNMKIehGxKWrwsm6Jo6Iy3XRphxFu78wzYNy483OyuerhRVZXBwUE07fyDus40NTXF4cOH2bhx46W1mPgP11vf+lbK5TLf+ta3LrjuP/zDP/Cud70Lx3EIgoAf+qEf4h/+4R8wjHM/Mfzmb/4mH/rQh855XoYbaT0LGw2C+XnCWg3hegjfQ7guwvOIXA/hrfzb94hcF9WysLZtw96xA71w4+/+ezEiCPBPnsQdH0c1TcyxMfSuLlphxLG2y9GWy9GWw7GWy4mWy7G2S/MadavldY1B22QkYTJkmwzbJsMJiz7LoGhoFA39pq0YzTged35n/yWv32HovCKX4rZMAl1RiER8ZVHJD3ikVGdfo73mBUQqnDW2S+HsC42yK5cY14Lz/4x2ZxL85+4CuzIJsrpG2Y8D0LwXsOQFdJg6M47HN0p1Fj2fHsugoOukVgJFOQhY9gIqQXi+i5wYtA1elk2xNWUzlrRRgaMth8/PlznScs/zqqvHUhV+qr+DsaTNeNslErA9bfN9HVm6zFtvMPjVdk3CzdzcHN3d3ZfUgEwmw7PPPntZ4ea9730v//Iv/8Kjjz7K4ODgedfbv38/r3vd6/iFX/gF3vjGNzI7O8sv/dIvcdddd/EXf/EX56wvKzfSehK1WgRLS/GyuESwtEiwsEgwP48/P0cwv0AwN0fUuvLLY43+fuydO1eWHWjZLFGzSdRqETWbhM1m/O9mE8UwSOy+ncQdt6NdZqV2LUIIvBMnaH7rW7SeeBIRBCi6jmLooOtErRbeiXG8yUnwz67SaLkc1ubNmJvHsMbGsDaNYY1tQlu50GDRCzjedjnedplqe/hnDKwOBCtziUBSU1cWjaSmEkSCec9n3vNZcAPmVwZrl/3gkgdjpzWVnK6R0FQsVcFWVfotk7Ezus/GktZqt0d81+c4BFzLS/MrfsDn58tMOz6zrkefZfLaYoZtaRtbVflOpcGRlktB17gjm2Rbyka9QHuqfsBj1SbzXkAgBEdbDl+YL1PyQ2xVocs0mHE9wpX5aPosg3oYroaaU891GDp5Q2Nj0mZ7yubuXIrt6csfY7KWSAjaUUTFD5l3ffY3HcbbLvcXMtxfSK/5/oQQPFVr8Y8LFZ5vtCkYGr2WwY5Ugm1pmyHbxIsET9SafK/S5FvlOsdaLm/qzPHTg53UgpAZ16cRhKQ0DVtT2N9weLLWpB1GDNsW9TDksWpzzTZrCry6kCGra1SDECFgNGkxbJukNJWCobM1ZTOasG7pSuLFXPVw86EPfYhf+qVfIplMXmxVIL4K6r/9t/9GPp+/pPXf97738cUvfpFvfvObjI6OXnDdn/zJn8RxHD73uc+tPvfoo49y//33MzMzQ19f3wVfL8fcSLeq5b/8JAu/+7uXvL6ayaDlciiWhWKZqIYZf23Gj6ploqw8F9ZrOPv3409MXlnjFAVr82YSe/aQ2HMHyT17MIaH1zwxr/7JWXmMmk1a3/sejW89SvNb38Kfmbm0XVoW5oYNCNeNw855ukzUXA5r0yassTHsHduxd+zA2rIF1X5xd0sOhaDihyx4PlOOx6TjMdn2mHRcJtsei35AyQ8IL6M3RVcgEqerHCqQ1TWyukZe18gbGpuSNttS8bI1Zd/0A6i9KGLW9RmwTHRVwY8Ey35Ax0qXXhAJDjTb6IrCxqR101a5LlckxAWD4AsJIfhmucGfn1wEYEMi7p76XrXJ3kuc3kFXYDRhMZa0uSOT5GW5JLdnkueMFbpY2/xIMOHEVc/Zle7f13dkuTN3Y+9hdcsMKBZC8L73vY+HHnqIhx9+mM2bN1/0NT/8wz+Mruv83d/93epz3/nOd7j33nuZnp6mv7//gq+X4Ua6VVUe+iKzH/wgim2jd3Whd3bGS1cnek8vek83Rm8vencPRk836nmuOLyQsFbD2X8A5/nn4+XAASLXQUulUJMp1NTKkkyiplKE9TrtZ57BX2Mwv5JIoCgKIoogDONQE4aroeZ8FMMgedfLSd17L2o2iwgCCAKEH6CYJuboKNboBvS+PpSVE2HkOHgnTuAeObKyHMU9fjxu11r703WSd95J+oH7Sdx5J9bYGNoafw/8MCKKBLrrEFbKRPU6WrGI3tW1uu8zRZ6HaLcRvo/wPIJGg1qtTq3RpOn7+GGEWyhQG93EhONzbKX77HjbZcG79On9z9Rt6owmLIYTJhtsiw0Jkw5TJ6fr5FeCUU7X0G/gJ/qWF+AHgtwtOM/OmUQU4Tz3HI1vfotgcREtm0HNZNGy2dWv9e4uzOFh1MSVVZqEEATz80StFlqhgJbLcbTt8dXlGpoCeV0n8DyOlqtMN9u0PY+FIOKwatI+TzAcCn10BWqKSh2VQIH7VMFWJeTfA5WFlcHhmSjEiCLmdJPwBeHnV62Q93SkUVNptEwaNZ1GucShKlfLNQk3d9xxBz/zMz/Dj//4j1O4Sn3yP//zP89nP/tZ/vEf//GsuW1yuRyJlV+MD37wg0xPT/OZz3wGgE996lP87M/+LB//+MdXu6Xe//73o6oq3/ve9y66TxlupFtV1G4jwgg1lbzpZhEOFhdpPfMM7aefof300zjPPYfwL35rgFPMDRtI3Xcf6fvvI3nXXaiXWCW+mNXQc+w47qFDOAcO4OzfT1gq0dItlu0sNTNF3UzS6uzF6erD1U2aqsF+NcdzRge+qpPy2+TcBv3NZUZqc4y0lhhIaQx0Zejr74Jahfb+A3gnxjGii4cUvbub9KsfIPGyl2EODGD099Pq7KK9crsARQEVhUAIqkFILQipBiGLK4NsDzYcDjbbTF9gAPWZFOLuniF7ZVxQwqTLNGgEIZUgpOqHVIKA6srX9TCkaOgMr65vMWSb1IMw7tpruThRhEJcXeqYHKf/ySdpHZ6mESjU7RSlRJYZq8CcnqWsJgCFtBbRl4CUodOV0BnKWfTnbAqZBIZtMtuOqAYKGdugmDJ4+YYiGztTKIpCFAnqTnxsVRXSln5d/h+EtRrNb3+bxsOP0PjWtwhLpUt6nd7XhzW6AXPDKOaGDWiFQlw1NY340TBQTZOw0cQ9egT36FG8I0dxjx0japwxE7WqouTzzI+MMJ1Js5hMUkunSbTbFEslFCFwTYtmKolj2wSGgVAUHM1gIVugnMqiIrB9j4zTwtENljJ5AlUj5TkEqkbLtGmZNk3TomEnUYSg0KgxvDhLR6NKpt1k97N7uevAvrPeo5JMoqXTDH/6U1gX6XW5Gq5JuPm5n/s5/u7v/g7XdXnb297Gz/zMz/B93/d9L6qh5/vF/OQnP8k73/lOAN75zncyPj7Oww8/vPr9P/7jP+ZP//RPOXHiBPl8ngcffJCPfOQjDAwMXHSfMtxI0rUXeR7BzEx8FlI1FG3lUVVWnjv9CVPRtDWrJteKEAJ/cpL/9YXH+Pj81QlRZ9pQneXlCwe5a/kom4MKGUtHSyZA0wkVlZn5MuVIx9MMPE3H0UyEomCaBultW8js3El2wwAboiZWrYxwXIz+PozBQYyBQbR0ChFFBAsLVI6fYPzoOMebPscCg/FAZ8bXKAUaji8gDFCDAD0K0cMQQwRgqvgpk1YuTaWYwzEtCOO+MMUNUdoBSitE8SOEqoCmIEwVkTOJ8iYioZFstth16BA943ModY85q8ihwjCufvWv9BkI6tgqnFSTuJyuFPRpPq9NuTyY9dmegaRtopgmaiKBmrBR7Pjx+dlZJpaW2LNzJ+3AYLHcZIflYztNokaTqNEgasWP7UaLEy1BotWg2Cih1yo4hw7FFccVajpN6lWvwhobI2o0COt1wlqVqFYnrNUI5uYIK5Xzvp9IUWgnEpiehx4E+IZBPZOhkUmj+wFG4KOoKs1CAS8IMT2Pg9u3Ub3EYR7Xylv27iW/sEhUryPcswdXj339axgX6TW5Gq5Zt9SpsS6f/OQneeSRRxgaGuKnf/qneec738nw8PCLbvj1IMONJEkAf//EFL/1z/sppEzylkYm8kj6DklVYCuCjRmNV4110DnYQ81KsxyoHF9scmi2yuGTJWbKLeZaIa64cPXA1FQ60iamrjJTaeNf4iAcRUQMNJYYq5xkc+UkA41FlhJ55or9zJg5ZhN5lhI56uaNHQdxprwW0J/WSIiATOQxHDUZ8aqMNucJaxWO+yYLkU7gB7QUg4qepmqkaGsWgaLR3S6Tdxs0DZvFRIHnOzYQqJc2pqi7VaKnVcYIA4wowAo97NCjaxiMRByml6IkFZEgjBTMhsPQ/DRF0WI6UWQu18W43U1W94hQCFHpCOqkQoe0GtKVNNk42MnQ2DCO5zI6OkoURczMzFCr1TAMg1QqRTKZJKvr6KUy1alJcotLVGemmRCCJcNgwbbxr6A7J2EYbB0YYHR0lJ6RDdQ8l4WFBVRVxbZt8vk8yWQSy7IAmJubY2lpCcdxzlqnVquxuLhIGIakUimiKKJer1Ov16nVatRqNTRNI5FIUCwW8TyPLVu2cPfdd6+OuxWeF19YUK8TNRpYmzejrHG18tV2XcbcnDhxgr/8y7/kM5/5DNPT03zf930f7373u3n7299+RY2+XmS4kSTpahFCUFu5MaWiguOHfPd4iYcPLfCtI0ss1s+9fNjQFLrSFrahYRkaCUNFVcBrtHBqDbxmizo6y+a5N7I8H0uE9IQtevw6PV6dbqdCR+Si2xbCToBtg52grWjM1T3mHcFCpFNVLYwowIwCzDAg4zXpay7T11ym4NbxNANHM1lM5tlf3MChwjCOHp88zShgs+GxZzjP7t2buH20iy096UvqKoqE4KTjcbDpcLDpcKDR5mCjzWylht5qkm41SbdbJBotgrog4Tl0uRVyfhMr8CGIWFByjJvdTBmdtLTzDw7vUhps1RcYVUtoys0xZ62iKJx56nWETkUk0Iiw1QhbV0ikshRzKbSgzUB/Pw8++OBZF/UIITi22MTSVYaKl1eBFELwjSOL/PuRRSYWm1SqDilTpz+foD9vs7M/x53DeQby8fCQqh/yzXKdr5fqpDSV395y/iuar6XrOqBYCMHnP/95fu7nfo5KpUJ4RvnuZiTDjSRJ14vjhyw3PZbqLo4fMlhM0pu10S5hcO9Sw2XfdJXnTlbZN11lqtymL60zZISMdKQY3dBDf0eG3qxNNnFl40+iVgt/ZoZgYYHIcRCOQ+S4RE57ZX4kP54jyfMRvo/v+TCygY5X309ieOhKDsnF27QyQ7UbRbiRwIki2lFEM4ioBSH1MKKxMgbppONxrOVyqNJkrtRGccK4ey0SEAl6NI3NlsW9fTnu70/iLk4ShQHzpRoHDx3CbVRx9RSWKkgkk4jAxc7nUVUVEQRYyQxRKHBClYVSleV6Gy8Ci4AetUFDmCxGaerCwlBCLAJsJSCjuFhKQKgapEULRdXI9Y4QJjvYXzP4j5mAMAjQiPDQQFEZ6UgxWWoRvuB+UrqqMNadJmPr2EZ85/UgjDgwW6Pcisdcbe3J8IadPbxhRy87+7OoahyeDrdc/p9j83ztuTlKMw3QVYysSXuuSVC79DFxAN7uAlFfkpyu8fyrdt2QAerXLdx84xvf4JOf/CRf+MIX0HWdH/3RH11zluCbiQw3kiRJ608rjDjRdnmm1uKfFyt8s1w/6zL8Ydskb2hkNI2MrpLWNIIoYtL1mWh7LPvnHwhuqwrdpsGWhEW+GRKVXLIo5A0dlXhagFLDY6baZqbiMF1p463M3WMSEKIQcnZXVFfG4oHNXbx2Wxf3j3WRSxo4fsiB2Rp7T1Z5YqLM4ydKzNWc87fLUPFDcVYg0kwNNWfgBxGRH6E0gjXvby40BaM3iZkzqVhKHAqdeLyVWvVQ6j5nFrryL+vmh+7o53UdWV5VSKPdgIsarmm4mZyc5FOf+hSf+tSnGB8f5/777+fd7343P/IjP7J6hdPNTIYbSZJuBUIISk2P52dq7D1Z4cBsnULKYGd/jh19WZpuwN7pKvtOVjm60KDS9qi2faIo7voydRVL1xjrTnPf5k7uGMqjqcrqlfGWrtKVsbB0lYlSi3LTY7CQZKQjiW1c30t8r4WSH/DlxSr/tFDhW5X6Jc03VDTi2aaDSFDyQ0p+cMH7mSnASCKelTqeoFHFVhUsRUF4Ia2ax3LJoVRqUyk76JZGb3+aV23q5E0bOtieTlwwJAghOFluc3SxwVLLY3+txaTjMeX4nFQjSkmVHAr6kkttpoG65KKs8UZHBzLcv6MbEcHUQpO+jgTvfMUIW/LxlZdzrs+z9RZHWy7HWg6zrk9BVelUNAYTJnflUuzIJ7HOc2+t6+WahJvPfvazfPKTn+Qb3/gGPT09/NRP/RTvfve7GRsbuyqNvl5kuJEk6UaKIkHN8VlqeCw1XBbrLgt1l7lqm5mqw2ylzXzNZbHhrn76v54UBQYLCXb0ZRksJPGCiLYfEkZidZzIYCHJ63b0sHsgt9oFMlt1mK22ySdNujIWmet0qfalWPaC1TvbN4L4Uvf6yrEdSZiMrFzunn3ByVsIQSuMWPYDTjo+h1oOh5oOh5ptDjUdSv6LG4aR0lTuzCbpMg0WPZ8FL2DR82mHEQVDp2BoFHSdkh9woOmc97YRAKai8MZihu2BRtD06UmaDKRtdvRk6M/f/IWHS3FNwo1pmnz/938/7373u3nLW96CeovOIinDjSRJ14sQguema3zvxDIHZuscmK1xdKGBdxn3uRrpSLJ7MM+u/iylpsf+2RoHZmvYhsbuwRy3DeTZ3pehI2WRSxjomoIfRnhBRNMLeXqyzLeOLHFssYGqxJO1oUDLDVlquASRoC9nU0iaTJVbq3PJXIqerEVv1ubYYpOGe/brMpbOroEctw/luX0wR1fGoub4VNs+bS+imDLoyth0ZywG8gnUqzSGI4oETS/gVE9N1r46IcsNQgxVXW2nEIIlP+BQM650nBof5EYCJ4xwowhfCAxFWb1Bq6EoNMP47upP1ZoXvFHnWsaSFndm41mHb88kGbZNKkFIxQ/YnLLPuov7enRNws3CwsIl31vqZibDjSRJpwgRj1fQtRf/YU0IsXoSnam0+eIz03zhqWmOLjTWXD9j63SlLTozFl1pi96cTV/Opj+foCcbn/S7MtY17SKKIoEfRavdDUIIlpseh+frPD9dY6nhYhkatqFiqCqKEk/4/MxUhYcPLdD0TlcudFWhJ2tTc/zLCkgASVNjW2+G0c40lZbHdKXNYt0lXDk9WbrKG3f28hOvHCFt6Zwst5kqtWh5AbqmoqkKLTfgu8dLfOf4MtX26cGyPVmLezd1sq03Q90JKLc8Wl6IuhI6/DCi3PIot3y8IIonUFSU1fdac3yWGx4NN8DQFLozNt1Zi7YXMl9zsA2N7X1ZdvRl2dKboTNlkksadGdsujLWed9zKASHmw5P1JrUg4julTvPd5k6SU2l7IeUV27hYWsqd+dSL/mbZ17zAcV/9Vd/tTqJ3ne+8x1GRkb4wz/8Q0ZHR3nrW996xQ2/HmS4kaT17QtPncQPIwwtPhn7oeBbC39P1Z+nI1GgO1WgYBeZmRvg355pU2p6DBeTbOxMMdqZwtBVXD9C1xTuG+vknk0dGCvhx/FDao6P40U4QcjxxSb/cXSJ7xxf4thiEwUFU1do+6c/kZuawgNbutk1EJ8At/dl8ZRFnlz4HiWnhBM4uKHLaG6UB4cfpDPRSc2rcaxyjJJTYk/3Hop28Zz3KYRgojbB0wtPU3bLjOXH2FbcRlei67p0B7lByPeOl2i6AWPdaUY6Upgrd/dueyEnlprsPVnh2ZNV9p6s0HADcgmDrG1gGyqlpsdC3WWh5l5WJetWsmc4z1tv72fnQI7lhstiw6PhBHG1qpCgP5cgaWkYmkrK1C4ashfrLk+Ml3h+psbBuRqH5xv0Zm3esLOHB7d105dLYBsqB+fq/OMzM/zfA/MosBqc05ZB3fFpuAGREIx0pNjUleK2gTxbezNrXsW3UHN4eqrC05MVDszW+OQ777pqVbbLdU3DzSc+8Ql+4zd+g/e///389m//Ns899xwbN27kU5/6FJ/+9Kf5xje+8aIaf63JcCNJ64/vl1EUA1W1ePlvP0yp6Z31/cTIJ9CTE+e8LmwPEtS3E7Y2Ebp9EL3gk7biYVpVDLtEqC0SqQ0it4ewPYLwC8RDSgWKXkW15lGNKopWR9EbIFREmESEKQw9ImG7ZFMuvnmEajC95vtQFZUOu4PF9uLpJqBwe9ftbMhtIBJxCKh7dZ5dfJaSc+6tAIp2kc2FzQxnhhnKDDGUGeLOnjvXDEg3gyCMOLHUZP9sjcnlFh1pi/68TU/WxtAUQGG60uaz35vgq/vnURWF/nyCwUKCrG0QrlTfVAXuGMpz71gnO/qyaCtVmWcmK3z72BIny21yCYN80iRtaUQCwkigqQqFZPy8pavxuJZT93ZFkLUNiimTYsqk5YXMVh0Wag5JS6c7Y9FwAw7M1tg/U+PYYoNKy6fS9llquBe7jdpZdFVhpCPJpq40GdtguemiKgpZW0dTVZ6ZKnNsce27hp/J0JRLnijyTClTY2d/DlUFx49Ybros1T3aLxhX9NVfeIDNPZnL3v7VcE3DzY4dO/id3/kd3va2t5HJZHj22WfZuHEjzz33HK95zWtYWlp6UY2/1mS4kaT155vfejm+Xwbg/+z7SdpBkjBSiVDQlJCWfRRPbeAIgUtIqNVR7ZO88BpZVZiIyCQKTVAdFL113n1GQRoiA0VroWjnTtZ3IUKoRO1h7ChH2hBkrYiaukA5Wlhdp8PuJm9lOFY9dt7tmKrJrs5d9CR7OFw+zInaidUAdCZN0bir9y7euOGNvHbotRTt4lnVnTO71E4JgiauO4fjzuK6c7juPK47TxQ6dHY+SGfna1HVOAxGkY8QAZp2bQeuOn6IsdINdbNbqDn8895Z/nnvDEsNj860SWfaImXpLNQdpsttZqsO7mUMGleUeE6b2wfjcVZbejIcmq/z78/P8cR4mWBloJGpqbx2Wxc/eHs/+YTJbDXeV9MLyNoGGVsnigTjyy0Oz9fZe7J6zpipU1QFtvRk2DOcZ89Qgdfv6KGQuvq32bgU1zTcJBIJDh48yMjIyFnh5siRI+zevZt2+9JuzX6jyHAjSevPw4/cRhieG0QMo4hl9aBraVTNRlUtFEVDQaXk1vmP+efY22wx5alUw7W7BHQ0kqSwQhsRJmioDVythDhjEhAVQbcuKOqCjCbIqIIIaIYK9VBDCA1NWLhejlZzA3OLr6Ti9J6zL8UooWgNIq8LogRZW2fnsCDfcZxi1qc/lyRp6piayY6OHezs2ImpnT7ROIHD0cpRjpQPM1k9zlR9kuPVExypjp+9H8BWNUxVwVYiOjWfXgN6TY2CYQAhYuV4egIaoUIjUnAihaIe0WcIhhIpUmYe3y8ThvG4Ik1LYZqdKHoPdb+Htp9iQ0dEwkpj2/3YVj+J5AjJxDCaduX39fK8ZVx3jlRqbDVgnSmKfCqVx1ha/gbNxmG8lTbmcy+nt+8/U8i/AkVZuaN85OK6SwRBBUXRURQNTUthWb1XrXvP8UNmKm0URSFj62Rs/axxTn4oWG66HF1ocHShQdsP6UxZCOIZsFteyPa+DHePFskn1w4WQggabkC17a9Upy59cHEYCQ7P1zk8X0dVFCw9vmVIZ9qiO2OTMG+OqQEu5/x92UOrR0dHeeaZZxgZGTnr+X/7t39jx44dl7s5SZKkF+3VDzxLFHlEkUsUuQgRYJoda574zrSz4fLm3/88/alJXt4xxbaeRZL6DG6wgK1E5HVBQgFFqQNgmt0UC/fQ8mscXHwKL6iTUAW9iRyWnsHzloiiNrqeJZu5jXR6G5qeQVVNgqBGs3mEZvMYltUk0O9l0dvGeMlnfNml2ljEcaYRBCy1HI5XR6g58J3DAKf/3mbNFhmzQT7xBEP5p3jdNpuxTg3Ha9JwmowvzjC5VGK5bVNxc3juA4wYu9Ayz1ExZigJDwG0o5B2BFVg3td4fnWuuFODcc9/S4NYCIGL8AdQghxamEELMnhuB65RRksdRktMwHEVQxiktYisHpBWdLoUi36rQJ/dh20W6cml2dCRw7Z7saxudLML9E4SZh5TMxEiotk6RqX8PRYWv0y5/D0gQlFMMpmdGHoGgUCIgDBo0mqfIAjq57S43Z5kZvYLhFoOWzNBeARB9ax1IgG+AKFlyaS30Zu/jVRqEwl7iFAdYL6R4WTFZbbqoK+MlbH0eEJAPxT4YUSl5TO+1OTEcpOJ5SbztXMrewlDY1N3im298Tisbb1xJea+sc4rClVxcDLI2Jc/6FhTFbavjAdbLy473PzSL/0S733ve3EcByEEjz32GH/zN3/Dhz/8Yf78z//8WrRRkiTpghRFRdNstAvcY2gtnWmLn37gFWzsepAHt3WvDhwOwxaNxmE8b4Eo8hAiIp3ZTio5tnriebkQOM4UimpimT2r9wuKojaqmriiE1QQNFla+hrLpW+yuPQ5jpcMjlZGOV7dwPHqCAutbmpekpqXZLoBzy/Cl4+cevWpcRCb1t743H3xo+KiqB6o8aOitVCtRVRzAdVaRNGaxINOBCgRRCYiTK0sFqq5jGrPoep10Bvx+CKmCIFTozPOjpQhAT4VoBIABIADXhVRnUaE8c9MVSJU1QfFJzqjKpZUVbJaRE4L6dIgg4Ud9eMF3ZRchWao4tDAMMtoeoVAa9OIBJqSImN1kEt0kzIylNwGk7VJltwGAT4KPraikNFsQMERKu1I4K/uOgCeg/AISlBA+AX80ABFIIIMkddB5HUQtochungVKmnGl+E3vXgHbT/kuekak1N1TnpzfDtSMABLVdEyOoWeJDu3dHLPzm56epNoK7+bQghaNY9GycWwNJJZEyupo6zRVSeEYK7mcGgursrsn6mxf7bG+FKLgUKCbb0ZtvVmeeXGIi/fULxod99a3Zc3qyu6Wur//J//w2/91m8xNTUFwMDAAL/5m7/Ju9/97qvewKtNdktJknQrEELgOCfxvEU8bzmu/PgZyk6GimMwW57niYkK3zxuU3dNdE1gaoLuNAwVswx1dNCTTdCdsam7Ac9PV3lupspSw6Mna9ObjSNI2w9xVq7uGi4m2dCRZLgjRaXlrZ4Mjy40MHWVXQM57hjKs6UnQ8p2CdQlSt4cM41pZlsnmW/NUvEX2ZjbwAODr+Lu3ldwdKHFw0dO8NjUScpOBdVcIDInCfRJhHr+Wwvc7PTQpKPVjxrpGEERy4srLr7eJDDrpAnIBUnSbpasHtKZLNGTqWLbDULNo+5lKB16I/rcDhRx8akIIkWgwMotEZQXfA+aOY2FoQSzWYVU2aEw69BuxzG1kTdINUNwQhY1wREjpKKdfervTJu8fkcP3Rkb79Q8SW7AYt1lvu6wUHPZNZDjL99511U7hpfrut1bamlpiSiKbqn5b2S4kSTppiIEBA5EIYgwflQUMJKgmfHXN5gfRqiKclUH8kYiYqo+RTto44cRRxca7J9pcnjWZWIpZGrZJxQ+ql5H0WuoRgXVmke3F9HtBRTVw1BSWGoaS03ju2mqjSStVhoRZOIUoLooK4sIk6hhkazeQ4fdiWUGHFuepx3VQCiIyEZENnk7wwNjfbxu2wAbumxO1qeYrE9Q9RYpeEkYN2mf0FAXMijiyseiCKCUVpnPa5T7KywXItq6TnezRuSkaEVZ8lWNO074ZM64+M/XYDmtUrIUHFtlvtNgsktnIX92R0yqHTC0UONYfw5/Za6kbDOkrxySckJSSkRkwJKp0YgUUiUPt9xirnX6XlTblycYa5Zw7G6ezvfQOVzgy+9/4Irf84t1Xe8KfquR4UaSpOsm8GD5KCwegIUDsHQE2mVwqitLBZxaHGrWomhgpuKgYybjr60smGmwMpAoQLIIiWL8mCxC3x5IdZy1mfJck4XxGs2qR6vq0ai41JbatBse2Y4E+d4kmYJFq+pRL7sk0gZbX9FL/5b8JXVD+F6I1wrQLQ1dV3GaPq2ah6opWEkDRYXAi0jmTIxLHJzqBRHjy01KNQf98DEsp0HHUBehluPEYRe3HSAEqJpC4IVYSYP+zXmKW/OMV1ocna8zWW7TmbbY1JVirDtNf+7smZDDMOLEcgs/jEh7TaxD++HwAdyFEs5yDa/p4uYHaeSGKS1HeLPzGH6denqYemaYVN5CsWBRaVEXbXxVRwgL3dXI+wGJtI+WD5kTDY5qJst2mki1cE2byS6TZuLiFRsDwZawjd9yWRYapVQacZ75cPqWFhidnmL/xjEqmdzq88VqmUo6S6Rd/NhbnkehVifpOuQaFTZNjXPnoecp3P0Ad/30DzDYOXgJP71r46qHmzvvvJOvfe1rFAqFS2rAfffdx9/93d8xMDBwaS2+jmS4kSTpsoUB+E3w2+A1wW+B1zrjuZWvvVYcWpYOx2Fm+QhElzdb74um6rDpQbjtR2DrW8BK88S/nuB7/3TisjeV7bTpH8vTMZimoz+NbqrMj9eYO15jfrFJM6FS8kKadRdQiBTwdAVPh0BTyLQjsq2IjBNhBPHA1c6hNH2b8hQHUuiGykypxfj8AqFRozh+hMJXv4SqQbujG6EYJKfGKZZm0c44VTWSvSwXNjPVv53F4ijNRJ5QV4kUMBM6HZZBNNkkjUIyo9OfrFFUlkDXaaeTiMUJ/P1PoUweJV+rYSgKiu+d/0CsaNoJZjp7ONndy/Htuzi2ZTsH01nKyfSa6ycCn1QYsGSd5xJ54aF7U9jBLDuFoKfiUTI70UKB4jQ4VBhhNj90zssyzQb5epVco87mqXFuP3KA244eoliPB0cHqsbjt7+Mme07ednRg2yaOEYz9Hm+o5+pnn5qqTTVdIZQ0+islNHDgOc3bmHv2DZq6bXnsFFFyO5kwIM9w/zX3iIjiQsP1r8Wrnq4UVWVr3/96xSLlzYJ1L333svevXvZuHHjpbX4OpLhRpLWp8o//ANqJou1ZTPm8DDKJXxKBSCKoLkA1ZNQnVp5PHn2v1vLV94wMwPd2+OlayukusDOgZ1feczFFRlVB1WLqzUiigPUmSHKa8XByquDu7K0y9Aqxe1rl6A+FwerU/QEbLiP47Wd7JveRioRkEyGpAopMgM9JPpHqDUtKvMtGhWXZNYknbdYOtngyBPztPyQ+bxGpCg4hsKJXoMTPTrVpIZnXH4Xle0GdNSaFOptGgmLxXyS5iWcJPUgoG9pie7yMrVUgqVckUomi7jIPQ4tz2NgYY7e0iJLuQInu3tpJc4e/KtEEYV6le7yMoPzy/SVHfpKbdRUkvnePPNJhclMiunOLsrnOfErUUTSdTACH8MPcE3znJAwOj3JjuNHyLUa5LJZtiYFycnHaE4cpv9km+7qmpvm0PAoT267jUhVSTpt9hx6nt6lk0x0w3SvQdRdJFHoJFfsI1PowU8aNAsJGjmLalBnyVliqbXEYnuRbCOiz+yio2OAPr2TvlJEstBNrtBDUrOoeOMcfO4wlUUX11ep9BZ4rqeP/dYgZeX0+f/zt4/yqmJu7QZfQ9ck3Jy6EuBSKIrCkSNHZLiRpJeyKILadHzitnPxifuUdgUW9sPcc3GAaJdWTtKnTtTl+DWFDVAYgfzI6a/tPAQuhG78GDgI3+Hw/+tXiZrxPFuKqWP1FzG7UiiagqJGKIpA0SI0Q6CaAk31UKMyuljESDhoprj48BZFBSMVdxEZiTO+Tp7ddVTcBN074kCTG1xz3Mw1u/Jk6Qjs+1y8lI5ffP1kB3Rtozp4L4f67uNAZjPPOxFPVpscbDpc6L7XNgo5p4XaqKFEAlUIbM8l6bTRw4DlXIH5YieOdeGr2DoqZYqNBpVMluVMNp6Hxw+JVIX2Be6tpYchmWYD0/fQwwAtjBAKVNPZ81YgANQoQo8EoaoSXuY4og5DZ4OlM1YtsWVxjt0deXZv3ki6swMRBIh2G392lsrMLPPlKmU/YHBpHvvIEdyjRwnm5tbcrtBUGhu6cdIGnqVhJtMkklnUXI5aZ4KyHdJamEVMniQ3vsTgtIcagWuAY4Knx1+HajzAWKwsoargmPE67ZVFAYwAjDB+tH3ItASZNmRbkGnBmbExAg6MdPHo7l08N7adPxMKAw++AXvLlss6di/WVQ83ExPnTlt+MYODg2iX+snpOpLhRpJepNAHrxGHjBeenJ0aHP8GHP53OPLVuCICgAKJfDxGJAygOnlVmxQFMPdkDrdq4FZ1xHkm5LsQRQczb6Blk2i5DFqhiFbsRu8fRh8YRe8bRO/tRwQBYaWK8FyEH4CIEFGEohto6RRqOo2aySB8H/fwYdxDh3AOH8Y7dpyo2SRqt4kcB9Fuo+Xz2Dt3riw7sMY2o2XSqMkkSiKBcpHKxAUJATNPwezeuOvMb+EGHs95Oo85KscDlUVhsGAWmbW6mLXWvjCkR4OMaaIoCq/MpXhNxmC70qDbK5HK9VJ//DCLf/AHKLaNe/Ag1tgmEi9/Of7EBK0nniTyPIKhYRzLoppIUtpxGwvZHOlqlf65k2y/9x76f+gH0Fd6BiKxclXQyu+WHwnmPJ9jLYcZ16fT0OlqN7E+9/cof/3/QLMZHyvDIBIKYbONZ2ZwDZNaQjDd3cdCsYNitcLw/Ax9SwuYQQCqirltK+5dr6C66zZmuno4kshwSNE40HJRhWCzoTImQsZCn1ERMBJ6ZNwWtMso6RxqtgMllUHR9dUF3UAxDRTDQDHN+Pkzfo7e3Bytb3+b9rPPoiYSaJ2dGP39GIODiFaLYGmZYHmJcGlp5etlgrk53GPH4g8M10mkQCupogdgu+fut/dDH6LwX99+3doDckDxBclwI0mXKQxg9lkY/yaMPwqT343DjZ6A3ABk+yE7CLWTMPEdiE7fkTnuYjnPZ//cEPTshOLGuHqQ7FgZFNsRB6d2GcrjUJmA8sTpr90GGDZoFugW6PZZj0I18WrgLoUEjQghNCKhIiI1vhjJiQidgMgJCJ0Qf7lGuHzuPZqul4nefr5z2524hknKaTM0P8PozBTTXb2c2LCJKJlkemCIfYMbKCdSbPba7DBUonyehUSKJtBtGvRZBt2mQYep02noFA2NgqHTjiL+71KNryxWeLLewr3AX/x+b5lt9SNsbx5nT/0Ad9YO0O8txhWrdE/8MwnOvnw70Hpx1C04zQ7cmoaS7kBN51ATCbBMtHweo6MDrVBAKxYxR0ZQDJMv/sHTmAkd09bQdBXT1jFsDd8NyfckyXcatCZmOPi9ReYXBAm1zZAySX9zP+FT30U4DgKo5Dez0LWHcmEbrWTPWW2zcOjwT1IsHcQoTaEFLogIX0/i6DkQkGzNYbslQs0mUnUst4Kh+DSMTpqpPrTQw/RqtJLdlAvbcK08auSjB206lp/HcsvUsqNooUuhcphUcxaFsw+yb2dppIdoGzlC1UQP2pheFdstk2gvo4qASFFppvqpZUZopAcJNROBih46JNqLdJSeJ1c0SL3sThJ3vozEnjtQkylEuxUH5raDV2+xsBBRrUWISNCRi2jUI2wcwrbDUllB8V0Sho+vWHRmPTJplZKfpqM/hWPkaCsp2pFFo6mS6UzQsyFDZy4kODmFNzGBNzmBPzFJ8V3vJHHbbVfpf8GlkeHmAmS4kV7ShIi7crwGuLW4e8ipnP3YLsfdRLWZeLxJZQqCy7itSnETbHkTbHkDDN8bP+dU4i6ndnz/J7q3xVWcm0TkuvgzM/jTM4TlEmG5QliJl2BpiWBxMV6WllBMEy2bRbEtFCOuaKAoCN+PKzONBmGzCYqCtWkT1pbN2Fu3Yo2NoeVyzJs2/xKo7AsEz9TbjF/nG2Ln6jV2Hj/M5qlxik6LzjCgKwrY0KiRjUIgQPEbKEETJWiCX0eJPFBAhAoiAiF0BDp+PSRoXWaFXlVQhkb52uj/54rar0Y+PfOPk8qolPrvpFQ793YEmhZPQhheQQXvxTL8BqZbRY0CQt3CM9IExtoDjgEQEZZbwTczROqFZxe2EgqFLpO+TVlG9/TRuzm+Km5hos73/uk40wfLRNHVP6VbSZ073zjCnW8cufjK15AMNxcgw410Uzj+MBx/BEbvh6FXxmM1Ts13ErjxZb6nxqgIAaEHzUWoTp+uoszvj7t60j1xULAy8WKsjAfR7Xh7iwdh4WB85Y5TvbKrd+wcjNwXt3fDfdAxBvXZuD216TgEmWnY/HroOM8MuS8hQggQYs1upaeqTd7y1Oq0whiKwv2FNIO2SckPONBwONZ2GTA0bjM17MCnw21ze61EV2mZ/V7AoQCMxUU6Z06ScB1KuTyL+SLlTI5qJkslnaGWylBNZxAK3H7kAPfufZK7Dj3PSLWMaF787tKXw+zJYXcpWHYF3BpRqCAChShQCD2V0FUJPRW/pRH5KqFqsNyxC19PEmoWkWoQ6DahZqFGAY30AI7dgSp8Cv4Uo9FjNO1Oxs1XUNLOHstpKG3G7EcZtR6nxziMrrgYikOEzqy3jSnvDma9HThRhlC1QTMxTIVMso0II8qNNA0ngal7qIS0/SQCFUtt0mnPEGopWmGeZFplcFOC4sYBQj1DbbHFsafm8ZyA3gEVr9FiZlohCNYOe1lllpw2i6G08USSlihSj7rxxekrqUylSbdxlG7jGJYa3z7CjxIs+GOc9G4j4uzwYyotVFXghKnV5zIpl65OHz80WVo2yBVVWi0FTdco9qUIIhW3FWDaOjPHqgTu6cqqldIp9qaw0wa5rv8/e/8dbFmW1/eCn7XW9sdf7/Kmq6qsqq7qqq7uamhDQ9MNamzroREiggD68UYxIcPT8EIjjQaFHjJPgBSIYd6TRkxMSAIUjJAEwjQI27SnaVs2y6R31997/PZrrflj37xZWemzMru64X4id+5zzz3bn7vXd/9syGA75dKrXbJxyTf9tQd56/uvzdz6arIvbm7CvrjZ52uC3/478KX/UL2WbiVO0l4lYi7jhJVLR986RfWucGuVOLqctRN2rsTFBO3K3dRarNxHnUNXBwTvc9ck2vC3jp/j8UbIWxsR72hGtNyrC7CVxuLcRqBr2e2SnThBsbICWmNLjdUllBqwyIlJxOQkwfQUanIS1WohpKzihoZDzHCI7g8wwwEmz6EsX7OOK69tWVZizfMQrov0PHBdnIkJ/GPHUPXXWCbSPmy+UqXCb75SifJsCNkAm/YpdwZkWwXZtkEnFumYahIZytMozzDyAzr+CMc3V4V1WQsr+Vs4U76HjCYz/gXatZc5bdsccnvMRwYvqEHQrOoBTRyG6YerLLXJByrRfwu0NuRxSVB37zjgW2vD9sURWVyi8xKv3CLQ69TdPp7pX7GOFjEgsAjizGcQR4RBQauWVm0Uynw3Q25cuWGzIWU8pj/02BpNcGF8jFPpuyl3G10INA8Gn+Lp+n+m7azeeke9Onh1tFUMsxZNtUqhXbzARSy9DZbeUZ03XWCyhI1VTTMcEz39Yai/eUV798XNTdgXN/t8TfDy78BLvw1nPlXFqtwO0oXmfBWjcuibqhtQPobRejWgZMMqoLeIqwDSMq0EydRDVebO1ENVPItf3dj2xco+X1O8xmX6oX/7DJf6OY9MKQKpuTSCRuBSC3yWJhs8stDmkfkm//mLF/mNZy6hX+OKmax5vHWpxSPzTSZqHg/NNnj7wQ6r/ZRX14c8d7HP2a0xh2Yi5hYanPPg+MaQM1tjsDAbG0bdlN4w512HJvjwOw8QOZLRMOf01pjIU7xtuUNeGl5ZH/LofJOnlm+v2OHtYKylV2oupjnDUuNLiQX0bqB13VE8EjjoQZfhyhp6sEXH38BJ1ojHO2xmOdulIS0yalmXTa142ZnkjDPJBX+aC/4ca/4UoU6ZLHrM5ttMFT2c3di4NW+SC8EcgcmYLPqMVMhI1fjNZ36M6R/+z3DgnffkOO+Gr4q4yfOcjY0NzOuit5eXl+9mdV819sXNPl9TWLsbJDu8YkFRXhUTk4+qgFzHB+WC34I3kj2zzz5fB2hjefwnf584vzYQ3SqBDRQ2cqq5J8GRRIFDlpeYuERuZiBAL0bYyAFHVLnMpUGMS9R2hp4P0QsROLf592QtYlAgUo2tO4hEgwXZzRDDggeEw/semOKdhyf5wCMzFNpwbjum3fIxSjDjuZyOMyJgOylYTwv++2DIpaLkqWZE21G8NE75k50BO8XNku8rZj2Ht0YhUsB2XrKWFuwYTXwfbRX/+uJv8Vc+9NcqK9ibxH0VNydOnOBHf/RH+exnP3vV+5drNmh96wvzZrIvbvbZZ5+/qJhcY8ZFFdQrBUIJUBLhyut2lX6zyEvDiY0hv/3sKuOsZHXB52NxfO8Hb2ORWylNDY8vtMhcwZfzjKui0qy9ZX8v0c8RoxJ8Cb6qeqr7Ejx12+t4PdOuQ9tVxKVBG4sxljgvSSWUN7tW2kKucSwYJbC5QYwKxLhEJhqRlJBpkKISh/6uSERU/3KNSDRWCnBlJQpLy7/+7sf4nsfm7+gY7jV3Mn47N/3tdfjIRz6C4zh89KMfZX5+/uum/fk+++zz5wdrLVqPKIoBWo/QOgEs2qSMhi8Rx6dxvQnCYJla7QhRdBTHaX5d3a9MUpJfGJKdG1BuxMjQQbX8aur4ePM1ZHT97BprLeVmQnayR3qqR7kRowc5NrvBw6cA4StkzcWbr+EdaOIdaODORYjQue55M2lJfmmEcCXubA3pK2xpKLeTakANFEIKirWYcitGBA6q4VX73/aRUbVeayzlZkyxNkb3c/QwR7V8HjzY5O9/+0MIJflfT14i3g2CbjmKg6HHou8x7Tk0HIUnBIW1PDeM+dPemNJavn2qyQcmmoRSMshLCgFfGIz55M6QhcDjnz6wyHvaNbpxQTt0cXb7NRXGIgWU1jIoNQ2l6JWaj20PWM0KHq4HnIkzSmt5fpTwR1sDspaHbV2btVWdKEu1QlNZioxFFgZGBXI9xdYdrBKI3KA2UkRcQmGYnIiwwPZ2fNXqlAAx6UPNwVoIESxEPjVtWduIGY1z8vKKR8VVgsV2SD8pqAcOTx+eZqFV/bw9zgBYbIccmqphjN1z8TVDl7rvIHev/VsPfPUrEr8R7thyU6vV+NKXvsTDDz98v/bpvrJvudlnnzcfPaoGWtX2wVjGZy8RX7yAacWU0ztoO0QIhZQ+1paMxycYjV4hSzcQQx85CrDWABYrLFYWu1P1zC2sAisRViKMgywjVNnA1RM0/MfoTLwLN2xVFovLk5JXLBmOqKwbSu5aOaievKVACBCBszc43yustmRn+6THt0lPVILkVjhTYSVCFutgLXpUoHsZ2ek+ZniDQHS1u8/6NivOe3JXjLiVdUeAHuSUm1eXB5ANDzPOKxfQ7SAFwpVYbauB/3rbdiXuYp3uo214bJKFZkjDUdjCUO4klNspepRj4rL6PjU90o6PnQyYnq5dd533ujL0+STjE90h/ULTcRQ60UxELocaATtbCS9f6jM1GfKexTZh4NBwq+/NpV7CH764xpfO93hpdUDddzg6XWdzlPG509t7AkVJwfJEROgqPvjoLJ4SHJtr8k0PTqGkwJHimuPpxTmr/XRv2eAmVZ6/nrivbqmnn36an/u5n+O9733vG9rJN4t9cbPPPm8+g49fYPB7Z6s68IKrBkSjEuLOq6StU6SN8zh5E288jz9aIhgcRhU3qRny1cSROK1dS0QnwJ2NcOdqONMhWLClweYaWxpMprFJidmdbGF2xVMlmMqNmPTlHUx8dZq+mgzwl5u4CzVMqtH9DN3PqkF9J73Bjl3ZP/9QE/9oG+9AHdX0UU0PGVQGe2stGLDaYDNdFTXs5+QXh+Tnh+QXh5jBzTP1VNvHanuVkBK+QoYOJq2O050OcWZr2Fyjhzm6n2GGxVXrEZ7Ena/jdHxk3aPcSsjODrBp+ZrPKNzFGnonQw8yuMXIZSdSzJE+/sNNagsH0HJMlm9Q5DtYLNaW5PkWWbZOWfRRTg0pI4RQJMl5kuQ8WbZGFB6k3XkXU1PfQrv1DqT0MSYjzzfIsg2ybB1rC5rNJ4miI/dEOO2Mc56/1MeRgrcsNGlHN7AK/QXjvoqbj33sY/zDf/gP+ef//J/z+OOP47pXm0W/1gXDvrjZZ583n/4fnGX4yYtQ7t5+IktaO4vXn0PmN0/XLUVJLxriuyE1t4Yn/EpIlKayAAj2YkoQlYAQvoTAYtyEYf4ieb6N1C5C+0jjIrSHtB4SHyUaOKKOMA4YWQ2i1mINlYvBWmx+fyrvycgheHiC8NFJvENNVP3Gg5oeFxQXh+QXhuSrY4QjUXUX2fDwlhr4B5sI9/oBs8YU5MU2AoGUHkK4u3MHY3KMSdF6TJ70cdIJGCjIdhe2Fhk4OAs1RKTROqUcjim3E2RToVoBQbCAEIKi6DMavUxRdCmKHlqPcd0JfGcWz87gi3mElKhOcFXMjzEFZTEi3xhgLyjGn1u/xpJl3ZKy3sNGGSK0WKekzGNkL8TrLiHt1WNT6fXJozXS1mmSzgmS9gm0N7y7C3UDXHeSTvudtDvvZKLznnsmdvapuK/iRu5ma7z+gu0HFO+zzz53gjUWMy6wxqKa3l78RbE6Jj/bZ/PkJbbOr7DjDDjjXOCse4lXg3OcCS5Riiv3melwmvcsvof3LL6Hd869k4lg4iZbre5Vg+FzDAbPMhw8z073T8my69cGkdJjavIDzM5+D/X6QwTBQuUqKwzZzg7dC58n2Vyj7Ca4/Wmc/iSi71auH6fqV4ULwgUCgfVySqdPaXsU+QCrDa7Txq3XCR7uUH/oKMYm5PkmWbZJnm+S51sURXfXTRcipYdUAY7TAGswJiPLNxmNXiZNL1IUPawtAYmo/GlI4SKVDwiMydA65pamj+ty2dRmb7r8ZcGk9c2LBSoZUqsfo1Z7kDS9yHh8ijzf4mrflsRRNSglxhRYq7FCgyyrXbkeFlw9hTdewO3P4SYdVFFHFhHaH5BH6xTROlnzIkWweb0jQEofIRTGZFhbXOczCsep43mTSOkxHp+65nOeN8VE573U68cAiwWEkNRqD9JqPonrtm96fu4FWmfs7HyKXv+LlRWq/TRRdPS2RZfWMWvrv83G+u/yxBP/H6S8dRf3+8V9FTef+MQnbvr7b/7mb76T1X3V2Rc3++zz9cm4GLMZb7KZbHKyd5LPXPoMn1/7PMnrWkM80H6Ap+ee5p1z7+Rg8yANr0HdrRO5EZnOGOZDRvmI0AmZr8/vBSfn+Q5JcpbNrT9mZ+fTZNkGxlzbdsJ1J/C9aZL04i0H732+2ii4aR/zaxHGobb1OI21p2kkT+FPTeHNNqsUcm2xxoKxaJsyzl9lmDxPrrcRAowssCrDqAztxJR+H+MN0c4Yq/Ibi69dQv8wjmyg9QhrLZP+B1ho/DU8fwIciXAk0ldVjFegqhiw66B1TByfpSyHldXNpJTlkO3tT7K9/fFrvqeu26HZfCthsEwQLhIES/jeNK7bxnXbOE6bJDnHpUu/wurar1GWlYXrLY/+HHNz33tH5/desl/E7ybsi5t99vnzQ6YzvrT+JT596dN8bvVznOjutjWwlvYYDm5YljdhecNiBLx8QPDSAcFaBxCCI60jfPPSN/O+pffx5MyTOPJKAqm1ltHoJdbWfoPtnU+SJBevETtRdJRO513UosPkxQ7j8SmS5BzGFIAlzzfROkEIBykdpAx3B5AJPG8CXY6J49Nk+QbGZNwIpWpIGWBtibXF3vpB7lppLL4/R73+MO3WO6jXH6IsR7vuoG61fp1hrcGYlKLso3WG69SQMkSpAKkCPG+KMFgmig4Shgdx3QnyfJMkObc3eCoVoZwGrtNEm7iKW0lX0SahakBldo9ZkRfbZNkaRdGnLPtoHaNUjTBcxnUndy1Tm2gd43mT1GrHaLWeQqmw2u9sA2typPRAKGrRETxvilKP0OUQ1+3geVN43jRBMI/rTmJMthszc444OUearlAWPYqii053CHVIXXSI8gh3u8TdLLC9jHIUoc0khT1IYZeBNxbnYmTOeOI44+mvUISbGJUjjIOwiiLapIg2rruc0C7N1W9E5e3L30S0N6T0u5RhF+0Od21Au583DlJ7YBUgKj1lJAiDcVK0k1RWLimwQmOtRlgBVu3uj6yC7xFgBVbq1wToV5WuhXRwnBae2+Gxx/536vWH3tC5uVvuubh57rnneOyxx5BS8txzz930s29961tve0d/6qd+il//9V/n5ZdfJgxD3v3ud/MzP/MzHDt24yJBH/nIR/jFX/zFa95/9NFHefHFF2+5zX1xs88+9x+TpqQvvUT6woukL76I1RpveRnv0EG8Q4fwDh1CNRq3t64kYfhHf0Tyla9Qbm1Tbm+jt7bQwyGyVkM1GshW9bec97qk3S1sf4CbXM+VUNGrC9baEOSWIIcwh2FdsX6wwdlFh1OzMG55NDtzTHQWmK3PMRfNMhfUmXQdWgo60Tyt1lM3Ne9/5ZmPsLPzqTs6d5dxZIOJ4m0sXgB18Ju59NhTZEKT65zIiXiocQC/ex5bm8Je+iLy1Mdh5xQ0FqoeX/NPQPsgWAMrX66qUs89dmUDuqgqWtcm72r/zHhM/KUvIet1vOVl1OTkLV0dxuQIcedtDa5CF1W/tNVnoXe+Knx5uau8V6+O15TV7zZfrqbuORiuQX57MTZWOJSNpygnPkAx9QGE4yOHLyKSNdTgGdzunyD0CBCU/uOkwfsp7QKlmaXMZzGFqYKhbzK6andE3H4F4yRgFaXfZbD4afL6yt2fm68C73z6t2k0Hn1Ttn3PxY2UkrW1NWZmZpBSVr7x6yx2pzE3H/rQh/iBH/gBnn76acqy5Cd+4id4/vnnOX78OLXa9dP4+v0+SXLl6aksS5544gl+7Md+jJ/8yZ+85Tb3xc0++9xfhn/0R1z8O/9XuMW9QE1N4S4soOo1ZK2OrNdx5mbxlg7gLR/AakP/t3+L4e/9PuZuGj1KiXfwIP5DD6IePEqejCi//DzFCy9iixsLn9djgNSDUl2ZRgGMa4qiGeGHNSLtQJYjjcXDwTOSInDoLytGc4ZRO0OIIVKnuBZc6aAchaCGYyfx4wZsFIheH7Hdo32hR3tVo6Tlge9ZR/mW0abHSuIRtgqaQUnN1bcssFslREmUqGJY4myJcqzxvW28KEdIKPQEiXmQXCxSilksbtVTqixBl4DAmZ3FnZ/HXZjHlprhH/w+w4/9CTa9krElowjvyBGa3/EhWn/5L+NM3p1oumrnu2dh5/SVaeWZSqiVt8gUuxluDWpT1dSYh+YiuAFmtEGyfQJv81XcbHDXqx8ql+fbs7y8+CRm8j0ss8hMMYkYakYiZtvvs6G22VRnKMxpQrPJhBgyI2MieYO/GSMQxsWWAcPCZaAlAy3oaclYQ2IFoQlomYC69XGkQViJLgNMEVLLW7R0k2ZZByEoZYpRKdbJkCrDcQoclSOcDFVEOOkEfjJFLZtCCltZcERJ8Fibhb/0nTjOm5OxeM/Fzblz51heXkYIwblz52762YMH774l+ubmJjMzM3ziE5/gfe97320t8xu/8Rt83/d9H2fOnLmtbe+Lm332ub9kJ05w+nu+FzU5SfjYYwSPP47wPfJz58jPniU/dw69uXVH63QPHKDxbd+Gu7CAMzWJMzmJbDYx4xgzHKAH1WCkmk1ks4lqtXAXFpBBcM26TJqSPPccemdnV1TVIPA5+dKfUr74Et6r51EnzmGHI4S+P1lRt4MWsLaoOfLgkEPT8XU7b+hcIF2LTiWD8yFpz8VvFdRmcrxWsdc+rEwlyjNVvZ6bYA2kXZd4w0MoCCdzvGaJziRlrCgziTUCa6i6fNtZ0n6d5Ox2JUYu47o0vvVbaX34w4RvfRxnaur2Djofw+pz8MrvwIu/Cf3z199Pv0k+8wiD+hRZskOYx9SKFK/MkNKt+qbVZ2HmkaoB5ORRaCyQRh1eGp3nuc3neH7rec4PzlP36sRFzOn+6Sp+y1oOlCXvjxO+YxTzWF6luZ91HC64Dhcdhz+oRZx3HSJj+dY44ek0ZbbUHCyKq5xZ5x2H36lHnHZdvhL4rDs3q5traSvLsmeYdCyZgcQIYiOILYy1oKurZptKKBbqCzw88TCPTDzCdDTN+nid1fEql0aXWB1XAfItv0XbbzPKR5zonWB4C8uVFJKHJx7mHbPv4PHpx2k6DQLtE+QuHdNkanIOd+rWzUfvF/c15qbX69Fut6/7u5MnT/LAAw/cyequWf7BBx/k+eef57HHHrv1AsD3fM/3kGUZf/AHf3Bbn98XN/vsc3+xWlNubuLMzt7Q/aBHI/IzZyk31jHjMXo0wgxHFCsrFBcukF+4gBmPqb//W2j/D/8D4dvf/lVPqbXWYtMUMxphxmNsUVRTnpN1d9hZPUNv7RzDuMtYlbhBhHYksc0YmYQgLuhsZjTWhwTbI5Tno2p1TBSg0ZRZRpEnlHlK4gvKdg0z0cKdnmbysbejHnmIkSqw1vKo26b1xf+GOfcVtA7JxEH6o5y1nQEMBjhxgTPK0NIyDgRD35CHDnUModH0hwX9cJODE1t0PcGfRQFnpEu7B9+SpTziJiy5OU11d2IuCzsY4SGzDJnEVUdxLTClwJSS0viU4SRlax4ztYycWcCpKRAxebKB7Z2ntnOGxmgL8RpfTiEkG0Gd9SBi1Y84H0R8yVV8qexT3qBaYNtvs1RfohW00EZTmhJtNeNizOneaUpbXnc5gIbbYL4+T6ACPOWhrabIxxT5iG2bY61lob7AfG2exfoi8/V52n4bKSRKKJTRtLdPM3HyY8yd+iR+cbWF6VRjihOzD3H+4NM4nUN0/A6doEPgBDjCwbUWxwnxnQBf+fiOj698XOniShclFfJ6CrV3Ho7/JiRdqE3D8jfC3BNXetHlY+zpT5C8+ruojZdwehfAr2NbS5j6DGU0RdE+gDf9MGHrILSWwL32weDN5r6Km3e/+9187GMfI3jdE9Err7zCBz7wAS5evM0Ox6/DWsuHP/xhut0un/rU7fmoV1dXOXDgAL/yK7/C93//91/3M1mWkWVXAvUGgwEHDhzYFzf77PN1iNGanUsXWD9zio2zp9m6cA5T7g5WogqnDFtt2rNztGbmaM/O05yaJmg08KPaX+iaI9ZaVsYrnOieIC5ikjKhNCUWi7EGYw3+eIupjVeY2TxFIQQX2wtcjFqobEAQd3HSPuvDS5gyZU6XPJHmHMvzO+/jcxO2peQlz+PXGzU+GYVkUoK11Kxl/BrzlSMd5mvzzNfmScuUi6OL7KQ7AHjG8i1JgmstiRDUjGHFcfhK4DMRTfP41OO8dfqtHG0dJSkTQifkQOMAR9pHri8eLp9DYxn3cxxP4t+qQnU+hhd+Dc7/GWbtReTaV/Z+ZVD0gyeI7AZSGCwSVfRQeoRFUooIK12MCklrD5JNPEW58C6cw99ArRMSjZ5HPvefqua6/Ytw7rNg9a4bUlWTP42eehTPDnDWvwzm9l2xSAdmH6tit468H4arsPkKvP//ccc9su4l91XcfNd3fRdaaz760Y/i7JrYXnrpJb71W7+V7//+7+fnf/7n72qn/9bf+lv8zu/8Dp/+9KdZWlq6rWV+6qd+ip/92Z9lZWUFz7t+ZPtP/uRP8o//8T++5v19cbPPPl+7WGvZOHOK01/5AtsXLzDu7jDu7TDc2qIsbl4190YIKQnqDYJaHbAYYzBaY43B9QNaM7O0ZmZpTM3ghSFeEOL6Pl4Y7S0X1Bu4QUBvbZXNc6fZPHeGrQvnKPMMIRVCSqSUuH6AG4R4QVCtK4zwwohaZ4Klh99CUK9iFtLRiO1LF/CjiM78Aspx0Vqzs7PD5uYm3W4XKSW+7+N5Hp7n4fs+QRDszT3P26s/9tVAG83LOy/zudXP8cLWCxRpn5nhBoXOSHROIarr5xmNbzSNrOBgN2ZpkDKT57RNQdsr8Hxz03Fy6E9y4dg3U9/ZYHr1eULdJ40DTKEQrkPJNCpQCKAsPOLhBPlQ40/t0K6fwRPXpvHraAqx8A5oLGGDKcTkMmLxccT0MXCu1G8xxrJ9ccTOyojeRkJ3Laa3EdNfjymLymLkeJLGREC941OPcmr6PLWaIFo8QDQzjVl7iQsnYi6sRGxs+kSyy2H/8zwQfoZF79bJL9cj1m3OZE8z0lPI3faeQz3NwMzR04skuoHh2n5joezR8AbU2y7hRBtVb+GIAlUOUOUQVfRwkjVUtonKtnD0ECUKFDmeTPBEXE3/8ydRUwfftIeE+ypu0jTl277t25ifn+dXf/VXefHFF/nABz7AD/7gD/Kv/tW/uqsd/rEf+zF+4zd+g09+8pMcPnz4tpax1vLQQw/x3d/93fzcz/3cDT+3b7nZZ587x1pLf2Od9dMn2DhzingwoMhSijRBlyVeEOKFIW4Q4uwOrmI32cANQlozszSnZmhOzxC12re8GZZ5Tn9jne2L5zj77Jc5/ZUvMu7uXPezbhAyc+gIs4ePMn3wMG4QArZyI1nLuLtDb32N/voqvfVVRt0dyuzGadZfbYSQTB08RDLoM9rZvvK+lMgwojBglMIqB7vbqRkEVimQu+8LsfsEXb3v1Bp4jSZBGOL7/q4Y8nHKCDPykLh4whIk6zjZCLIUnRuKQpAWPmkZkeoAIQqEyIAcKwJM6aKNVw1yYowSKa4c4Tt9fHeMH+QoX+L4Dqo9S7D8Vuozi9Q7E9Q6E4T1BkJKGG9XAcGjdehfgGf+f7D2LGPdYbV8C2N5CJEOcWwfKS2pbZDQIjFtFAVL/nMsec/hyytVio2VDPU0fT1PYlo4IsMVCa5IcUWKSHPMWOOoAqFLok6C65V7gkpbh8KG5CYgNyFxPsF68RZWzcOsl0fJ7fVjS4TVWHHnvZra6iIH/GdY8l7AIUXjsF0cYmw6eDKrsr5qU/ghBONTmMEaxjoEckhDbTHpnMWTtw6k1lZRWp/EtOiWS+yUS3TLJZQoaaoNGmqDutokNh3OZW/nfPYUsenc9nFIJfiGDx/hqW+/+/jau+W+17np9/t8y7d8C0ePHuVTn/oUP/zDP8y//Jf/8o531FrLj/3Yj/Hf/tt/4+Mf/zgPPvjgbS/78Y9/nPe///13FJ8D+zE3++wDlcXgt372f6PIs93YjwxdVPEdWEuRZeTJrRs33g6O5zO1fJC5ow8x/8BDRM0WO6sr7KxcpLtyge7qKsOdrasDUgHXDzj41idZPPYo9ckp6p0J6hNTtKZnqgHzDijznGQ0IB0OycZjkGJPkEmpyOIx/Y11+hvrjHa2yNOEIsso0pQ8HpOOx6SjIUWW7u3b1PJBpg8eZmr5EEGtXokrY9BlSZnvLpsm5ElCnsSk4zHbF8/TX39dNWTPx5YFwryx4GUL4E4jwmNIdwnPToD96sVNWJthy02M3sCaHtb0EWZA6CREMqHu5DT9CM+dJGGR9eIYAz132+sXaGbdEwRySK9cYKBnrmuluDkGRYlF3HJZV8RMO6dpO5doOyt01Apt5xINtYFFMtKTjPQ0IzPFsJxibCaITYex6RDrNgaHBfdFDvjPsuS/QNCcQ5gUma6g7B22fZAOPPBBjKph+muUhaTMJTYb4ZabuHoHZUd3eC6u0C9n2SiOslUeolcuEJsO2vqU1qsEoA1QoqS0PoUNee9ffZAnPnDgrrd3t9xzcTMYXJsWt7a2xgc/+EG++7u/m5/+6Z/ee/9OBMPf/Jt/k1/5lV/hN3/zN6+qbdNqtQjDSjX/g3/wD7h06RK/9Eu/dNWyP/RDP8SJEyf43Oc+d9vbu3ws++Jmn7/oZPGY/+N//Gs3/YxyHKaWDzN75CjNqRlc38cNQqRSe+InT5LKTWRN1U7BGLLxiP7mBoOtjcoycZvPT24Y0pyaYfLwA8w+9AitA4fQxlAUBXme702v/fmyZTZNU7IsoygKgiCg0WjQaDSo1+tXva7X63sundf3xbsddFmQxTFhvUGSpuzs7LC9vU0cV0LwtRYqYwzdbpednR12dnbo9XpVm5oiRyUjrPLQfghKgbXMT0+yODVFJ2pjEsGoV5CNBVkiyBJJkYIQBZAgRYqQGZCQJwPScQ3kQaS6uvWEtQWmXAM7rq4RBmwJFFibg82xNgWTIlVO4NdwlF+1ayAltxmxMRjjgPWQMsB12ijVBtvEmAhjXeBu3WKWUKxQV1t40iARGCSBHBLJHqHo0S0nuZQ/SWyvFUKKnIZaxxM9chNQ2IDSBlg8ND4GF8vNrSyKDE8muCKh5Wyw6D7Pkv8s085ppLgiOI2FXIQUKsIon0a+jnxNNWRrIRvXiLciRisOybrFZAK3pikSBebKd8NvFbQOxUTTOX67QF4naMlqKJKqQ710QEpdpe6PFdlQYcvdVkjSIpRF+Rq3plG38bW2BspcIgQ4/rWi2looS0VeOrhOietohIDhwb8JH/5f8QKFH935388b5b7UubmeWfnyopfr3txpnZsbmar//b//93zkIx8BqqJ9Z8+e5eMf//je7/v9PvPz8/z8z/88f/2v//Xb3h7si5t99gEwRvPq5z6D6/s43u7kurD7N3z+wgXcRhNjoSgKyt2g3SAI9ibHcaq4FWN2WxhoyrKkLEuKoiBJErY3N9laucR4cw2VjGE0AF3itdqoqEHhOFWqqzZY5dw4WNEKpHGryqzCYoUBLMJKhFVXJuNgha7K4sui6kF0g1UqpfaEzmtjVi7fl5RSuK6L53m4rovrulhr6Xa7bG9vk6Z3UGvFglPW8HSbGlPIrIZJ7mUY7u6+S6i3Mor0JP31ZwmcTSbaPp2pSdpH34pqzpIlCXk8psxz2nPzTC8fYurgYWrtzt6x53nO+vo6q6urrK6usra2xvr6OuY61iXf85mbXWCyMQfbY0YrXYqhIS8bFLqJtQq7K36sHWLLDUy5iS3XMOUq8JqO4q6LIzS+KBACxpnE2N0LKBso5yAgsaaLMT0wt7CACBCeh3FCnKBG0JnGm1zCioKD4z/jUPYsyuTowpDmgm4eMigCNA4FCmk0hZFkxiHXCiksNScncgoaTooXOti5RzBzx0jaxyDs4Pt+JaTDkKjbxb10ifLkSfJTpxGeh2i3oNmkCEJyIch0SpS/Qjt/Ac+OkFIRMMDX3Tf0XUhHLr0TIVnPxauXOIFBeoZ022O06mOK6pooX1NfyKjPp/jtAq+ur1sywFoYt76X+v/yy29ov94I91zc3Kqf1GvZ7y21zz5f34zH47tyM98LPM/DUwFe2cIp64gshNTDJC7YOw9iFNIiPANuTqkSckZkDDEqBarCaNIohHURVmFkhnYSShWDvLWbqNFoMDExQWO32rLd7R5ejhV65CDzGnrkEG8bdFHdatfrZzk59WWivFlNRZOwqDPyu3TDdVJ3TEdNMB3OMFef5UBnkQOTi9RaAdm4IB7kr5ky0lHJ1FKdQ2+dYvnRCbywEk3GaKS889iQG1GWJRsbG3uC57LoKXUBcsRYCnwd4FgHgcBxHObn51lcXGR6enrPelYLQ4brq6y++hLbFy+ws3KB7sol0vH13SquHzBz+Ah+VCPu9xj1uiSDAUaX2F2xJT0f/ACtHEoLni4gGWNv8LAtlcILwhtu806xQmJf6yqVEuu4GMfFquqhobJg2sr9aAzC6j1XpN2Nn0JKynqboj1JRwxomBG13ghK6AdNRlGNljNikh5q12qkUWgUCT49WgypMZYlPTcmUQkDkTKUKZlKEFoSxg2irIPO5uilM/RUA2ENLhmOzWiLmHc2V6hHX2GrtsIlH9aUw6PB2/jpd/1T/KNH78k5uxvuZPy+rUeHr3XBss8++9w7PM/j4MGDe9YKx3H2rBZpmu65gMqyRAixZ9lVSuE4zt7nfd+n0+kwOTlJo9Egz/O95dM0xXEc2u02rVZrzxUthODSq11+41995Zq+00JWXcNfj5ACL1C4gcL1HcpMkwxzysJUBedSBWmIJCRggtuNQgmaiqij8OoCS+XSEQLCKCCqRbjKR+eWPC3J10uypCSLS3rrMUa/dj+rQcgLFLOHmwwWXuT5+PYfGOmDN/Q40DjAg50H+Z63fA/vXng3jnTQRjPMh3jKw1c+6rViRghe3HqRV7uvMlebY7m5zFw0d/VnXkeuc072TvLyzsuc6p3CYglUdcYuDC9wbnCOQuc4+RhVyxktj1izGdlrLG6+sbSEi/Fr5NYQ9n0esYd4VDzFojpIOkxJdEJ8MCZdtBi7gLFzlHlOniZYbfBwiETAdGee+ellmn6Lpt9EIFgdr3JxeJGV0Qrb6TZTwSTzjSUW6gss1ZeYj+YJvRBjNL21NXrrK4x2dhhub7Jx5hRrp04Q93t7wkY5DrXOBO25BWqTU2RIhqMxnYkOCwuLRPU6fq2OF0XooiDu94j7PbprK1x4+UV6ly5hdHl1wUcNFPktHGLXxxn1UdvrrE8cYK19AH/iyndJC81pr2A7cNj2+xSqICpqRHmTkpiRf5G+3ydxby+A3trdXlTC7tnP+sCVUr0B87VFvuvg9/FDj/1V/PD2A4/fbO4qoPhTn/oUv/ALv8Dp06f5L//lv7C4uMgv//Ivc/jwYd773vfej/28Z+xbbvbZ52ubdFzw6//yS0wu1ZlcrDO1WGdyqU69U6XqGmMxpUWXBseVKPf6bvNiV+SM+zmDrYT+Rkx/M6G/mTDYSlCOxI9c/MjBCx1cXzHqpnRXY9LxHdQEuQ5+5DB1oM7UUoPpA3WmlhtMzNUQUvDMxjN87MLH2Iq32Eq22Ew26aZdpqNpDrcOMxlMspVssRFvsB6vszZeQ9urLRAz0QxL9SVe2nnpqq7ornRpeA2aXpNBPtir+/La3y83ljnSPsJ0OE1ucrIyYz1e58LwAmvjtauaMt4JoTEkX8WU9BshEcyrkINFgS8UY+UwlJIEQ1UJqbKiOAhCo/F1xmyecjTLOZqlLNUXmTzyAdrL70amA7QpoDGPHncZvPwJamt/RhCvIsq0imNafAfJwW8jn/8GrHSx1pCNtjm9cZxXui+wOrzEkwNwxzXOJSGfyR5m07YppEshJaU/wAY7lLV1dH0FHXTxC0mQSdzSoxQueajJvYLUyXZdsremHjvUEkUtdYhSRS1VELj0m5pevaQbJmRcW1ZBComvfN4x+w5+4OEf4L2L771p7Z+vJvc1W+rXfu3X+KEf+iF+8Ad/kF/+5V/m+PHjHDlyhH/zb/4NH/3oR/nd3/3dN7Tz95t9cbPPPvvcimSY012L6a6NGXUzjLZobTDaYrTFaoPjKQabFzn95c8wc2iJA295hMVjR+nM12lMBPesFkhpSlbHq5wfnOezK5/lt079Fr2sd1vLRk7EY1OPsZVscWF4geI2Crm1nBoPD7d5MM9xLWRCoAUsFSWHipLAGnQ0SbnwNqL2IeaWvpHZpW/Ei3eIxxtsZ136X/z/4q4+h5uP6Lk+L/kBx5VlSykCawmtJTSGULo4fqsqeFcmVTo0EGcDBlIwkJKhlPSVZCCr8N3FUrNQliyUJZNas6UUK47Dym57hPE9EljKWhxryaTEtZbDecGDRcGRvCCyFs9aSmDNcVh1FBuOYiwkIynZUfIaofdNccJfGY64qAI+5T7CRW/Eqt/nYL7AB/rfwFvioxSipJAlBkMuCk4FF3k5PEMsUwLrIa3EliXhyGCGfbwUhrWCfq1EGcGineJodJA508H0Y5LBgHjQv27mo8WShYJDT7yNR7/xfTRbU4R+RKM9SdRqoZyvfsDwrbiv4uZtb3sbP/7jP84P//AP02g0ePbZZzly5AjPPPMMH/rQh1hbW3tDO3+/2Rc3++yzz73i9/7f/09e/Pgf7f0ctdoce9c3MXf0wb26P5aqJYXRei8OpjUzS2t2nsbE5B2ntec651OXPsW4GPPoxKMcbB6kMAWZzkjLlEE+YJAPUELx+NTjuLvpM9po1uI1zvTPcLp3ml7W23NnTYVTHGgcYKmxxOS4h3j+v8D6C7B1Ahqz0DkEeVxVxH3gg/C2H7q98vxlzl76Tv8iHP8NOPMpNscFre4LeMkGANZKtJ3FoqpMJztD5h+lmFqmdvBBXHMc9cy/QRZx1ehy4kjVZkCqqtv3aB1GG9i0x3Z9inMH38m5qcOUAhpFRi2LiUzVLdxazSDJGeQ5O6rFlwYezyY5qTeg9LdRTo/CuXvLnbSCR5IjvG/wBI+Pj9LSbWqmxrq7zXl/lUPZIkv5LACpyAns9QvQ3gqjDMW0QR4OaDwxT3txsUoKuA66LMniqpxBOhqxeuIVXvzkH7N59vQN11/rTNCZX6Azt8DUgYM89Z0fvqv9vJfcV3ETRRHHjx/n0KFDV4mb06dP8+ijj95ZBsGbwL642Weffe4V1lpWT7zMS5/+OK989lMkwzvrJq1cl1p7Asfzqsn1KPKMPB6TxTHKcZhYWGJicYmJxQM0p6tB0WpNkaWk4xHpaITRJZ35RaYOHGRyaRnnBhXbb4XJNWZUoNo+Qt6d5clai8k04/Vt8u6Iop9i4gLPDXGDAMf1+K+/d4JOUtImpw5MEOLeIp38LCVnRUGvXUPNhCxPRjww3WBhyqHXX+P8xdMMV05x9tQ5BsZlw5+F5gGmZg5yeKKNDV1Oxhl/ttLn+Uv9q9YtBRyeqrHQDkmyEtFboTM8iapH1BaOMHtggtmwS6s7YHu0zbibIOMCEERORCibTBSTTGV1OmMXt7z5ubNYxOU0PlESBscJnT+FMsaWGpAYGhTiUfLiEBaFIEMIg1VNtG1iyytCRviK8NFJgkcm8JYaqI5/W5bDjbOnOf7JP+bMM1/G7NZnigd9zOsCsSeXlvmRf/mvq+yzP6/tF44ePcov/MIv8MEPfvAqcfNLv/RL/PRP/zTHjx9/Qzt/v9kXN/vss8/9QJcl559/hlf+9FOMujt7Rf2EEEilkEohpKLMM/obaww2N64ZRO4JQlDvTNCcnmXu6IMsPfwWwkYT5boIISh3MigMndlFFA4mKcjPD8nPDsgvjcBYhKdw52u4sxGq46NaVbyTzTU2M5isxKYak+sq6ttYsu6YfH2ISEDeRd2bQlg0htJatijpC0NUlnRQTKnaLZev+mNdaYophXPdWJHYlmxjEZ6DloLIhbqvEYEltSPOnX6e7e4F4nKAtiXLtUc50n4rLXWbnc2BUpTEzTHjaEjuZDiNgFYwTU00kW2XuBYTD/oU2yNymWOEwVqDF4SE9Tph6BK0pylLTZGMyc9+AV75Xdrxq3S8hFBqCo4xFh8kMe/FFlefH+NY9CxEb5tm4umjuP7VYtcWmnInRQ9yhJIIt5qQAj3MSLeHjNe2STcGlFsJXuHj5R4zf+epP79dwf/Fv/gX/OIv/iL/7t/9O77t276N3/3d3+XcuXP8+I//OP/oH/0j/vbf/ttvaOfvN/viZp999vlawGjNYGuTuN+jzHPKIqPMc1zPx6/V8KMaRZqydeEcl145znBri2TYQyoHoRwc18WLIjw/wAlCeisX2bxwjvQW1qMPLf5PtLwbD9RXWRXeANqWFCYjJyW3KXmR7qVuj8s+3XyNwuSUtmBUdBmX/Ruuy5cRk/48bX+WjjdL3Wnv7aenQgJVu2HQa6pjCpPiywhPvbGKzd1sncwkWGtRnouUldtR65J+ukk3WaWXbzIotquCifcJzxF4ImNUuIBg0l9kufYwU8ESLW8a9Zr2EHE5JJcp7m49K9d4yPTuru/kjzxK+MjkPTqKO+eep4K/lr/39/4e/X6f97///aRpyvve9z583+fv/t2/+zUvbPbZZ599vlaQqoq9qU82KIou1lZxHtZeToLPCVAIb4rf/7d/ePXCe3VTKhzPZ+HYI7z9O7+XzvwSRmuy8YiNc6dZO3WCMk0p8hxjNIXISfSQ0pQYW1Kagm6+zlZ6kc3sIkk5pOFO0vamaXpTNIIJIqdJWeSUJtsTJIXJKE1RpclbS24SUpngTkU0FmZoL86Tjob01te49Mrxm4ouISXScQhq9arqdX4lldnxfbIsZiU5xUpyiubUDK3OLHG/TxqPSYZDbFHgqwgp1J4w01aT6XhPZEjHwfci3NLFlxFKOEihUMLBER6R0yBymtWkqteOdOlma5waPsvF8atk5urA3KDeYObwUSYWlmhOLTMVHiMdj1h99RUG25sk/R66LFGOg91tawLgRRFBrUFjaop6u4Pj+SAEg80NuqsXKdIUYypLjh/VcH0fYwz9jTVG3R3y0pJTWWMcaZHiVQb5c4wKi/DbRNHDNOxDTMkHquOiASVwxbBFrlMyM8RVEscJUNJDIBE+yGaAO9FE1V3K0NAdrZKqhMWH/pynggPEcczx48cxxvDoo49S3+1y+7XOvuVmnzeTqpLviDzfIs+3KYodiqJPUXQpyj5ax3juBJ4/g+9N43nT+P4cnjeJuMt0zLIcMxg8Q6/3BdJsDcep46g6jtPAcRpIFSKFh5AOUrgI6SKlhxQeUvrV672p+lkI7031vX8tUxQ9hqOXKMsBZTGk1EPKYkBRdimK3mumHfJ8G2NuHqeYdj1OfvQgJpeY8jrfAQE3zN7erUN0K/eXF0ZVzMVddly/HbwwYubwEZLBgMHWJlZrpOOgixxdltd89olv/06e+o7vpd6ZoLe2yld+/6M88/sfve6xCClpz84xtXyIsNEEC83pGdpzC7Rn52hOzxDUG3vf2cH2Jquvvkzc7+HX6tTanUpEBAFGa/I4JotH5MOEvNjtM5alFFlK3O+zcfYUW+fPYfTl/bYo34AFoaqLYQ0oz1BfHFObS0i3fXZeaaPza6vf1DoTSKkYbm/e1bmVGI61u3zr3CkCcUUYGuPQL59kUDQZFD6Dwqeb56wlMf3ixt8J6Wo68yM6UyN8r8RuKdhxieod3vmjf5/wkQ/c1X6+Ue5748yvZ/bFzT73i+3tT5Dlm+T5Nnm+RXF5vitadDmmKLsYc+cDiBAuvj9L4M/jB3M4qo5UAVIGqF3BYa3GmAK91cP8yauYb55nqE4wGr2Etfc+tkMID6V8XKeD603guh08t3od+PME4QHCYIkgWECpCLi2Ho21BmNyjMmR0kcp/w3vlzE5ZTlC69HuPN4VZgFKhUgVomRAWQ6I4zPEyTmS5BxFvkNZDin1CEfV8fxpPG8G35vC9+eIokMEwSJSXhusa62lP/gyly7+Chubv3vH1/hqwfjaye6enxSoqh/rQmJLiXAM0jEIWQmg0UqN0UpEuuNTpg46e90gKqr+Q8ozhJMZzXlBazGks9QhrE/iOhOkXY9s6NCZW0SnAee/co7VV07iBiFRq01nYZHm1AyLxx4hajfJkj5CWBzfIRn2WT15kp2Lq+hMUGQptXaH5vQsM4ePMP/AMZRzrbMgHY145vc/ytnjf0JnqcGBB76LI089hR/VEa/rvr114Ryf/83/CsCBRx9nYmGJoBFgvAv0ep8hL3ZoNp+g3Xo7tdqDSOnufifK6gGi6FKWA1x3giCYRwgXYxK6vc/T632eJLlAECwQhYcIw4N43gT9wbMMB88T1Y4wPfVBQBAnZxn0X2Bn8xnGo1OUdhXkbWRYGQ90DUuOyT2MTUAWjNcikm0f5SraCx2kbZLGA5J+zNbxGmXq4oQF0ZTAV4dpLdaoTUIYLSN0m1c+81k2z50hVDkPNLeptxO8VoEjNVnhkEuF1yqQoQYHSh8KT5A7EqsEeqzI+h66FKjAEC0mSHW1NDCF4NyfLPBX//LfovWNN+9Ld7/YFzc3YV/c7HO/+OSnnqYodm79QUCpOp43getO4rotXLeN67SRKqTIt3dF0gZZtkmeb8Ed+O/rvydp/paDlZb0CUv8Ho14cp52551E0WG0jin1iLIconcHf2PLqsmiKXbnWTWo6gx6OWIjR+5oREE1ldVECdiq+bQNwIS2eu2AsylwVgXOisBdE1gFpg26JXbnFt3SlNOW4qAFCa47ge/PVUIumCfwFwmChb3J82Yoyz5Jco44PkucnCNNLpBma2TZKlm2cUtLyBtDEgSLhOES1pQU5RVLzGW3EkAYLON5k7vWsWY1d9vVdXbbu0JwAs+bxHUnUSq6qSXMWou1JcZklOWALFvfPeY1snSVvNh5jUWoshB9vjfiCzsevUKyLQ2FsrQcmHIMxwLNk6FmyrE3bOd1GdftEEWHESjKckBR9inLAVpfcdE8/eUeAKkviSNF/9DDzDz6PzM7+93XFYPXO75nn/uf2N7+BK3WUwyHxxFCUq8/gut2cFRtV2xO47kdjClIkvMMR8fp9b5w3WsupY/nTVOWI8qyd8t9uLdcNqdJms0naDYeo9v7M8bjV+9qbUrV0Xq8t87X3w+kDJG2QZlbrNpG3EbrkFuSetg4whiFbA0QboE8+R184/f+L4RzR974+u+CfXFzE/bFzT73i+df+DHKcojnTeF5k9XcncR12yhVQzk1XKeD502i7iCw0ZiCPN8kTVdIs1WybL0SJDrFmAxtUqzJEcJBSA/xp6vY//YS9pWtvXU4C/O0v++vUP+Wb0E1G8haDVmvY4uScmOdcn2dYq2alxvrFCur5BcvUFy8hP0qlHcoJyzJ04bknZpy/t6sU6kIpeooFWJNgTYpWicYU1X0FcIhDA8QhoeIokN43nQlQlSNshyR55tk+QZ5tkmarRDH5zAmYbsUnEjlXnuIUMIBzzDteszNfjeLSz9Is/HWr6rbrjAF28k2G/EGm8kmo3zE81vP86uv/OpNl4ucgIWww4GoxdF6i0HaZyPt0i9iBnnMsCyIjcARllBCJC2hsEQSaspSk5aGMPz9ZzZ43YM+p0KXjTAgbSyx0z7EhWgCGzQpnYB6bZaZaIaZaAYlFF9Y/VOcnV/jmFq/pdi6Hp43Q6P9jdTDAwwHzzIYPktZvr6ppsBxWjhOg6LY2RULFWF4kE7nXdRqD5Clq8TJWeL4HHm+Sb3+MM3mWxkOX6DX+/zu92aZWu0hfH8WIRRGZ1hKjMkRODSbT9DpPE0QHERKidYZ4/EJNjd/n3F8ijyvHoKUCpDSJ893SNOLV8Ve3S90UbUx8R2Lmxv83KC0xSiB1JYo0Uzt5Ex0CwSQu4I4VDj/509Sazxy1+7xe8G+uLkJ91Pc9NZWaUxNX9f0ejtUAWdVVPudFva6HYzW5ElCniYUaTVXjkvYaBI2mnddG2Ofr03SV16h919/jf5v/Ramf+NMlFsiJe7cHM7CPDKKEJ6H9DyE6yH8KhDSjMeY0QgzGqFHI2yS4C4t4T/wAM7hA7hHlrAYyo0Nyo1Nyo1N9OYOemOH/KVXMKMrA43z0AHUtz6Mefc0Wb1Pmq6Qpauk2erejd/354miynUQhcv4/jx+MI/vzeyJSSkdbFlSXLpEubWFcBxwHITjYpVGeCFOWKuOKQyv+puzWqMHA3SvtzeV3S755gX+KP8KP9380jWnqSEjHqgd5GjnASZb8/hOwHQ0zWJ9kdlolppbo+7VKU3JF9a+wJ+t/hme8nh86nEen3qcTtDhVO8Ur3Rf4WT3JOvx+l4LBmstj04+ylum3sLjU4+jjebF7Rc5vn2c49vHWR2v3rRtQt2t0wk6WGspbckoHzEq7k3TSGEtD+UF82XJQqn5hjTlm+Pkpn2V1pTivOvg7VYrHkjJjlIIBaED61byqu+x3XAYeIpQQUdZ5jyHhgIhFEPrs14ojieCV+IYbStrRV05KEqaUjPpWDqOxFEe66XH0Dg83jnMty+/n+XWUYxOqDkKib0SG1V06aebPNc9x8Zoi8mdLt9+8SKBNpyu1bBA1xGcCyzHGx4ogQMoYXGwuAIaDrSVZSacYjJokidnbts1LGVIs/4WWrVHCeUEYu0FxMbLaD9gPDWHTTap9UaUfsgr9Qan0yGdwQ4PJQnzozFuZhEaHK3xdI5f5oxrE/RmjzGOmpT5mIVzX2Yyvf3rP3Rd/uN3/VP+xpN/47aXuR/si5ubcL/ETZGm/L9+5P+EkJLWzCyd+UU6cwuEjWaVCaDUVfNsNGLc7zLudhn3uox7O4x7Pco8w49qzD3wEPMPPszCg8eYe+ChKkjuBlhrd7MSVumvr9FbX6O/sUZ/fY3B9iZ5HJOnCbq4+ROB6weEzeae2PHCCNcPcAO/mvsBru/v+t9b1CcmmTl09K7F3D5fHUyWMfyDP6T3679GfvJUJUTiKy4FWa/jzM3izszizM7izM7gzs3jHljCW1rCnZ9H3Efha7KM0Z/8Cf3f+m1Gn/wkvCa41Dt8mOid76T2De8kfMfb0U2BY0OEFtg8r6Ysw+Y5xfoG+bmz5OfOkZ87R3H2HPmlS1et72aIMERGEbYsMYPBVdlIr+XlJfiNb5TI3V9364JzM1A6b8xSI4XE2Lt3JzjCYSqaYiaaoebU2Ew2WRuv3ZaIEYi77in12nWETkigAibymCeGPaaLjKWy5IG84HBR4Ft7x80kR0Jw3q3uMXOlJhWCE57LedclFYJH8xxlLT2leMH3eM73yITkyTTjqSxjR0qeC3wyIUiFwLGWWa0ZC8Gq43C4KPjWJKGGZcdXJEbQyjWLZcmBouRmTQi2peR36zVe9VweyXM+NIrxrWXFcSgENI3BIPhy4POnYcCOUrgWYinYkYq+45C7Hi3H5QkR8ba05O07axztbyDf4PW4HXJgw1GMhKRRWkoj6FrFutPhs7nDoCyZNppOYVhPIv7GAx/BjEdgLfM/+ZP3ff9ez764uQn3S9zsrFzkl//vf4cyu71urHdKZ36B+QeOUZuY3OtKW0194n73mmyDm6EcBzeMqvTCsiQZDu66mJgXhiw/9iQH3vI4juthrcEai7UGv1YnaraIWm1q7Q5ho4lUd9Mnd597jTUGE8dVgbnarQukfbUou10G//2/M/it3yZ59tkbCow7Qfg+zuwsGIMtCmxZVvOiqFxuN9mGrNdRrRaq09md2sgw2hVUGSbNsFlGlo45a7c4q7qcjxJiHwoHdhqw0RJ065D6V8TPbNfyxBmLFnByQXB+GqwU1DI4tClZXjfMdDUTQ+gMLUbCyXnBqd1JWjiyZjmyajm6BotblmYMyvcrsToxsSdU89kO21M+44kQJtrYiRbGc/b6TB1uHeZQ6xAXhxf59RO/zrnBOeIy5qHOQzwy8QhKKLbTbdIypTQloRMyV5tjKpzCUx5KKFp+i4X6wjW1ZtIyZW28RuQE1Ih5dvXj/NnZP8Zun+NgWRL6HhN+yKyw+IXBwUPhksVj/M0LdPobyDcg+O4FXSn5w1rEp8OAo0WBQbBUlnxTnDB3D4owFlTuzes9Pmjgogo569Ro2ZhH85ixlDzve8yWmmO7D6ybXo0LfoMLsoFRU0QmQlmPuFZnELnk+Vlm0lVqpkSbkrOtWc5PPky6voN3bp2Z0z0muyXtkaUzgs0WfOEhyQuHqr5iXgleafkH/9ng6upv6uFnn3nDx36n7Iubm3A/3VLWWkbdbXqrK3RXV+iurZDF42og0bqaG4PVGi+qUWt3qLXb1DoT1Fodap0JwkaT3voqqydeYfXEy6yeeIXu6qXb2n69M0Frdp727BytmTnas3M0pmcIolplhQlDvCC4piGatZY8SUiGA5Jhv5oPBmRxTJGllLspkEVapUPmaULc79FdW71lwbCrEIKw3iBqtfcEz97rVpug0cRxHKTjohwH5ThIx0Ht/iwdp6r7UKvtpyH/BUD3+8Rf+hLxn32e8ec/T/byy9cKEddFui7C81CTk3gHD16ZDlVzZ3b2hm5eay02TTFxXE3jMcJ1Ue02qtlE3KBXz82wWqN7PfJz58lOniA7eZL85CmSlQukNqcoCxojXVmdkir+J3Uh9qEz4tryeVKSBgFaCMI0RV12C/p+dU8Zja4bF6WlRBpz3XJ8stnEXVjAnZ9H1uuY4RA9GmKGI/RwgBmOMHGMjCJo1KHVxq/VUI1GFbPVaFbzegMZBiCq6rZCyt3XEqs1SRIzGscM0oRhljHMC4qisriRZbQGQ5o7O4ylZLB8gO7EJLLRYPHIYQ4cO8bsZJum3kZ2z1BozVrhkne3cXdeJSq28U2KnXucwgugf4Ha+os4689hdcnAmeFVNY0q+xwpLpFbF9cWWCvo0cITOU3GxAS8zAOMqDFJF4OkT4MuTS6JiIuegZqgPdmmNd+i0WkwGU6yVJtl8Nx/Ij/9J8yOu+w4Ll+ZO0Y0/TCPqDougqFU2KzP0sZJDuycwzElRrr4OidKR7jlleuWorgo2rxij3DCvoVY1ChxMK+p9mzI2PH6JG6GEYaQhETm9BxLLnMc61DPIybjiFomiJKc1jAjZ8Srs0OeWR6RuAUCgbSSQAe08zatvIWvfTzj4emqQefQHdLze/S9Pn2vTylLfn/lB3BrTWS9zsT/+JGv+n14X9zchK/HgOJkOGDt5KusnnyFdDyi1rosCnatIrs/f7VjZqwxrJ8+yZlnvsTG2VO774q9njTZeFxZlwZ9ksEAe4+ewJTjELUqYRi1O9TaHeqdCTrzi0wsLNFZWMQL3rwS4fvcH/TuIC4878p0H2LTvppYY7BpSj4ccuHMGc5fuoRyXRrtNrVmk9XtbV49eZLV1VUApJS0221arRa1Wo0oinAch/FoxLDXYzQakSQJSZZRGoMrBJPWMjmOCfo9utrQrUUMmk3CJGF6Y5OZjQ1a/T5xFDFsNhg2GsRRRBoEpEFA5vtYKXGKgiiOieKYME72XhspyQKf1A+qeRCQhCFJGKLvgctaGoNfliSuy11FG98mQZIQjWOywCcJQ8wNrMyNKGJxeZlGo0Gj0aDeqJOJjE7UIXB96Pawa6uYCxfpra2ylabsaM2OEIyVQmqD0CWyLLEOiEggJPRpYl8jRf00JdCawPVASbalpHyTHuqcwOGp73+K7zzynW/K9i+zL25uwtejuPnzgDGadDhk3O8R93rE/W71enca93tkoxG6LNFlgdFl9boodt8rMWVx2+63+uQUE/MLBPUmfhThRTX8MNp7HTYatKZnac3M4QZvrCT7PvvcCa+++iq/8zu/Q6vVotVqkSQJ586do7hFTJxSCn0/elHdZ3xrqQN1KWk4Dt6uMNWOw1aes50kNMKQKQSd7g7F6iobRcFOp8Ow0cC+RsC6eU5jMMTPMnLfI/N8Cs9FK4VWCrtr3aoXBTVjUa4DnodwXTzPIwoCwijCFQKVpKg4xh+PafR6OL1eFRQ/HqNHI5KyZOR5e4JvZ2KCzenpeyLYXo/SmkZRMI3g4OwMRx57jJmnnsKZvNLqQGvN1tYWKysrZFmG1po8z0mShPF4TBzHuK6LU3PI3IzNbJPNwSaD4YAoj2jkdUx69XCvlGJmZob5+XmazSZhGOIHVdPNrc0t1tfXWVtbY3Jykh/5kR+558d9p9zX9gv77HM3SKn2XFAs3/16yjzfFUNdxr0eca8KyB5sbdJdvcTOykWSQZ/R9haj7a1brxCIWm1as3O0Z+Zozc7Rmp6lOT1DY2qaxuQ0zutcE7osyOJ4t4rpmDyJKfKMMssosowy351nWfV+nu+KtOI1Yq0ayJrTM7RnF+jML9Cem6c1PXvbcUnWWuJ+j52Vi+xcukg6Gu6676649fyoVp33duX6c4Pw68qlZ61Fl+U11+DrmW63S7/fp/+6DLZarcbhw4dRSjEcDhmNRkxMTPDQQw/x4IMPUqvVGAwGdLtdBoMBcRwTxzFFUVCr1ajX69TrdaIoIooigiBgOByyurrKysoKw+GQqakp5ubmmJ6eptvtcvbsWc6dO8f29jadTofJyUkmJyfpdDrU6/W99Xqex3A4ZDAY0O/3r5orpajValdNjUaDZrNJo9HAvYtrZ7KM7NVXyS5eIpaCRAhanQnqnTYqDEHKykVpbeWptAYRRahmE3kPvysmy8hPnyZ54QXSF15k/OKLXOjusN70Kf0Q7dVIwpDCvSKwtHIoPQfruIRKMel5tF2XhuvgSUla5qS6pHAdchfOuJcYiiFnRZdYZHzD4jeij7k0Gz6vrfuvlGJ2dpbZ2dm7Pp4syyiKAqUUjuOglELehvWzvIOYzq8V9i03+/y5IxkN6a5UJuF0PCaPx2TJrhCJY7IkJu73GGysk45vnUlSa3fwwmhv+ftZol4qRX1iiqBeJ6jV8Gt1/KhOUK/jR1WsUXdthZ1LF9hZuUg2Ht90fdODMW5p2KmHpJ6D4/l7Lk0pFUaXGG0qS5nWWK0xxuy5+TrzC3QWFpmYX6Q1N4/r3biCsLWWZDhguL3FaGeL4fb27rz6Oe73cYOAoFbHr10+puo4vahGFo8Zd3cYdXd259uMu12KLMXxfWqtNlGzEmqX47Si107N6rheW2b/zeTy+bh8TJePJ8szRNSAIKQUirBe58iRI8zMzHxN7PdfBNIy5YWtF7g0usR6vI4nPVp+i8X6IgcaB5gIJ8h0Rq5z8jJnK9nkM6uf5U9X/pRTvVMM8gEOird5R1gsGtS1Iq37rMkxp9KLrBVbuFYSpQo/EbilpHANuWNQWuAXkjBTXJhJyPzru+tdHJ7sPM6TS+/gkclHeO/iewmd23e3n+2fpZ/3kUg+eemTLNYXOdw6TFImrI5W8ZXPkfYRHmw/yMcufIxfeelXEEKwVF/irdNv5ZsWv4nCFPzJhT/h86uf5+fe/3M48s21h+y7pW7CvrjZ57WkoxH9jSvp8731VQabGwy3NhlsbV7VwO/1uH5QubnCCDcIqo67vn9l7vu7nXg9lOvuBUYr10W5LkZXjfB6ayv01lbpra3euXASgtbMLBMLS0StdhXMuuvG02XB4n//GM31ql/N2HPYrofs1EO26yGZe+c3qplagynpIpMUsgyb5ZDniLyAoiCXkLrOayZF7qj7GivxehzPpzE5Sb0zSbPZoumH1F0PH4EvFJ6QVV0Sa1ETk7hzszhzczgzs6h6jSLPSIdDkuGAMs+rnktlUVkEd7YZbm1UYqXXpUxT3DjBH41RaU4WeMShT2k07so6rVFMI80J8hJPa0aBRz/06Uc+vSigVBLH82nNzNKemyeoN6pyC/6V75NUDkJKhKz6RAkpEaKaK8fBC0P8sFZ1CA+j6ueodk9KNBijGWxssHXxPN2Vi0ilCOqNPXEa1hsE9QZeFGG1ptyzUJboIqcsCkxZYrTGGI0pd+daY3RZifnOJI2p6apsxh18T9bGa5wfnEcIgbaajXiDldEKa8NV1karbMWbFGWBNYYIn7eLYzycLfL59Hn+yP0KI3n/i1PeDlOizWE5z7ScwMkMX+m9QM9PGNautpY4wqETdPjA8gf4wMEP8ED7AWpujc+tfI6Xd16mHbTp+B3ODM7w6Uuf5rnN525r+77yyfSts3z/3V/6dzw99/RdHeO9Yl/c3IR9cbPP7bJnidjapMhS/N2ss2oe3vO0dmsMo+4Og61NsnhENh6Tjq+em7KgPb/AxMIBJhaXaN/CmrL5f/xrRp/4BOmLL4J53RNio4FotRCtJqLdQrbbyHYH2W6RSsFw2Cc7dQp74SLu5ja1JMUxd367sFJWBfSUAimwQmKlwApRpWdrDdogsAgEQohKCwmBUA7OxASi08E0G+haSOH7pI4ixVLs7GC6XWy/jxyNcJIMvyzxSo1XGtQd3t60qMrmS1tlLRkBhZSUSiIAr9RXnQPLdbKbbve8AP3IZ7sWst0I2akFmNsJkLb2lmJRiMv1thZozy/sWuEW6czNV80q80qElHm+O69+zpOE7uolti+eZ/vSBbqXLt624La71+9uUa5LY2KK+uQkjclpGhOTOL6PNZbEpJzVK3TNkB3b5zlzknOs3/W2AMJU0R651BKFkZB6mlFUMgxL7Gsug9Tgasnsjs/SRshU36cRO4wDzfpEyjjQ5K7BKwWR8TnSOMSxucdoHljETIVkviEVBQ2/QdNtkuqUXtZjZbTCweZBvuPwd1xlEdFlyZlnvsQff+bX+NLqF9iupaxMJYyiO4u3UkLR9tsM8yHvXXwvq+NVBvkAT3nMR3PE+ZhXeyeIdYIvPP6S/y46ecSldJUTzirn5QYCwdumn+QDhz7Idxz+DqbCqTd0zt8o++LmJuyLm33+IqJHI+IvfpH4zz5P/PnPkx4/fnc1ZDwP5ucQkxPIIETuFr5TtQgVhMgsQ29uUl5u5bC1dU9q1bwRjOOgfa+KcRBQGEMhwArwCk1QlASFxn29+LtdXBcxM41stTAbm9itKtZLzc8RPfkk4WOP4y4uIut1sldfJX3hBZLnn6e4cOGq1VjHQR9aJj98kCIIYDCA4RARJ6hxjDMa44zHyKJE+x7a9yl9j9xR2KJA5gWyKFClRmDJlSLbtZxlTjUvlaRQklJKCqXQqpKUFkBcbi4uKJREq2qEd1yPzuISEwtLCCFIxyPS0ZBkNODXD71IMIbE06xOpQS5ZKrvMzUOaRYBOApfODTLkLoOkEqRu4bctQgpMbpkK91i1e2x3czJXYOw4JWSmZ2A6b7HpamUk0sjSud13yMLzbGDsJWgijJFPVFEqUMtc2jJBoEf4YchO42CZ2vnWZc9WqLOX659K+8L34ErnUpEI6q5AOV7mNClXmvRqF1xcybDwW7mZ594UJXNiPs9lOsye/gBZo88wMTiElLeu4eedDTilT/9FC988o84ef5F+vWCE0sjtls5w6gEAUEmWdwMKRxD6hnqicNM12d5PaShA4JmE6VcyvxKPKDd/a4bYenVC2qpwi+u3u/M0QgEXimpT0wytXyIqQMHmTpwkKVHHqM1c/exP3fLvri5CfviZp99QA+HFCsr6O1tyt1Jb+9Q7lye72DGY7zDhwgeegj/oWP4Dz2Ed3AZcQcWK1sUlDtdbFGALrFaY8tyt6BeWdVGcZxqnVJRjTG7T/9CVMtvbVNubl6ZNjYoNzfR3S6y1cSZmsaZmqqm6SnU5CTO5CSqM4Ez0alqtbx2n6ylSBPifp9xv0cyHOB6Pr6UuKUhaDTw6g2E62DTFL3bVgIEzlRVh6U6iRqEQHU6V6WkmyTBpClOp3PTc1OsrhJ/4QuMP/dnjD/7Wcq1tds+r/cbKwRyaZHwySdpvutdRG97G96hQ2Q6YzvdZjPe5ET3BP/kc//kq7ZPk3nAdB7RKj2OphO8szjEdG0a79hDhEvLVZxavYETBRTK0AraV7m5rLWsx+tMBBN46t6VzbDWMipG9LIeg3xAWqY81HmIhte4Z9sA6K5eYvPcmb0WOqN4QJKOcbb6iNV1Ml0yLnJGyZii14c4RljLKPD2hOpVCEHYaF4ndq1FlsRsnT/L1vlzDLc3r1n0/R/5v/DUd3zPPT2+22Ff3NyEfXGzzz77fK1hrSU/c4bxpz/D+HOfw6YJqjOBmpjAmZxATU5WLTHm55D1etXvqtul3NlB9/tV4cF6vWqIWquBlOidnUoYbm+ht7bRvS56uFuob7dgnxmPK6EJldvS2qowYFlwcRJeXRScWBScnBdstwTxjT2gewhjqaUQFBBllWtvHMAoqFx4tbR6X+0aymopHF63HF6rquMaAdtNOL5cVWNe2LZ88/OWgxtVpeZSVsv6JTglbLbhwoNtLjzU5syU5pTYIrMFjnSYDqc51jnGkzNP8t7F93Js4thNr8HqeJVhPkRbzcXhRV7tvkpSJnjKY1yM2Yw3KU251yNsZbzC2f5ZBvnVxUyVUDw29RjvWngX75x7J09MP3GVoDJxfHW/M9etXgtBfvIkyfMvkL7wPMkLL5KfO4czPY23tIQzPY0tckySYpKE/Pw59OYtskKlRB44gHv4ELJRR0UR3oFlmu99D8FDxyoL2nhM8vzzpC+8AFLhzMwQHHsId2GB8elTbH/xiwxGAzZrPlvnz/HeH/hhFh9+9NZfhnvMvri5CfviZp999tmnYivZ4isbX+Fs/yzDYsgoH3F2cJYXN18g1sl1l3FLS3sEE6OqNcRU7tORdS7OSF7sxGx411/utXgoFBJ2Y5s8o2gYl0bp4JWCWJaMVcFYlQxViZb3Zph62n2Qv1QcIx53Wc02eVlt0BMpxmq2g5KRf/fb8a2iKSKkcljX3at+5+FwsGxRHxtq3ZT2xpipvmVyAO2xpZFAM66E20YbNtqCjXbVt2wYwjCEUVhZoSaGlskhTA4sE0PwtEBNTkJR0N5ImFvLaBLgNJpgLfnmJhsdWGsLotzilOBoWNgBL4hAyqrX3C3csrVvfh/Lv/ALd31+7gX7dW722Wefrxt0YShyjTUWYyxCCMKGu58WfQustZzun2aYD3mw8yA1t4a19pbn7XTvNB89/VH+8NwfcnZw9oafC52Qx6Ye44npJ3i8/SjzW5r6pS6t1izu9AzOzHQV7P26ujKro1W+tPElntl4hpXRCpvJJhvxBr2st9cYNEcDei8aO1YFPZVysy6VoRPiSAdXupSmJC1TcpMz4Xd4QM1zeOBz6EzM0hcvMnGhTz+CrWbVu+v4suDLDwi+UJzgC5yAGtX0OpSuhIawlXg7uG6pp1Ao8ItKWDi6apUhLUwNYH7HMtcFvyyBKutoqwnPHRI8d1jw4rKgXy854WxDi2o6dPeVtc/MXe/6vlZMOTS8kIONBaSUnNhJSPS1mWFuCYfWM45dtDx52vJ4OUfzsScRrktx8SLZK69ULTjqddzDh/COHr3rfX4z2Lfc7LPPPm8qz3/8Ip/8T69e9V59wmf5LZMcfHSSxWNt/OjNL+JnjSWNC5JhQZ6U+JFDUHPxIwf5upgGay2FKdBW40qXXOdsJVtgoJ5MENQ8ouat4z6stbzafZXPr32eF7Ze4NzgHOvxOqETkpYpm0kVDyEQ1XZMjhIKX/kEToCvfOZr8xxpH2FcjHlp+6WrBI1A8GDnQR6eeJiW36LhNpitzfLY1GMcaR2547omZaHJ4pKo4e21YXntseQmJy5ikjLBWIO1FoMhLVMG+YB+1ifVKXW3Tt2t0/AatPwWk8Ekrrr2O2CsuaZZp7WW4tIligsXKFZWqteXVri4c4bfWN7g1cmcjqwz5bQ5Fh5ksb6IE9ZpNyZ5cPoR/KiBHo72XH+6163cfq0WstEEazBxgkniKiZrOMQMBpWLcHubcnMLPRggAh8ZhIjA5+KEZWPSIVmYYDxdo9uQrOsua+M1ttNtelmPcTFGIJiJZlhqLLFYX2Q2mqUTdGj7bdp+G0sVN7Q2XmN9vM5GvLHXAFVbzcpohfX42iwyT3osN5dJyoTCFCRFwrAYXvWZ0Al5eu5pjraOUvfq1J0ag9E2x0cneWHrBX72W36Wt8287Y6+D/eafbfUTdgXN/vs87XFC5+8xCd+5ZWbfsYLFLW2T9TyaUwESAV+VAmLsjDkcUmWlORJiS4Nrq+otXyUIzAGsrigLAxSCqYO1Fl+dJLOfA0pb2zlKHJNfyPh/IvbnH1ui/UzA8wNUuGlrHqqne28wB8c/g+UMseK63/WK0NmRgdZzh/kYPMg7ck6p3mJ57MvMzYjJsQ0T9p3M8wHPCs+x6ZaueE+OsbFLyPGXv+Gn7lmX61kefAoT+bv4T2L7+HBY4ssPNgmbNxabOnCkMYFWVwy7mdsnh+yeX7I9sUR435OnlS1WTrzNZ7+rkMcfWrmpuf4Rlhj2Vkbs3qyz/rZAeNuSjwoiIc5OteYXSufUpKZQ03mj7aYXKzTmAxoTAR7lj9rLUZbdGnQhaEsLs81uqzeN6XBGEtY96i1fcK6uyfMjDYUmcbxFep6Qbk3OwZryVONUgLlyr39SYYFg+2EzXND1s70WTs9YLiVEE4pOnM1pmdbBPVKyAkhcH2F6yscTyHEbiUACbOHmtQ717aOScqEC8MLnOufQ6N5qP0Qy83lq4SqtZYLwws8t/Ucn1/9PJ++9Ok9oXwj/t7Tf48fevSH7ugc3Gv2xc1N2Bc3++zztYUxFmstUlQCocg1K6/2OPfiNqe/ssm4d+sCY3eDkKCcatBBVK8dV2K0pcg0RXb9uiJ+5OAFzp6Yei3n2y/xu4/82+su52gPKwxa3lkpe2UcFvsPMTs8xES8QD1vU8oCsEyPlnGsS+KMKGWOY1yMMJSyQMucQuUMgi264TqOcZkeHWB6vExQXuuT6cxFzD/YZma5gdGWLC5I45JxN2OwlTDYSknHN+9/db11Lh3rVAHLdjfV3FosUOaacS8n7mfEwxzXV4R1D9dXbK+MyMZ3X/JfOrvipLzz4U1IgR86FLlGF7txKAJqTY9aJ0AIKHNDmWvKXCOkwAsd/NDBCx2kEgx3UgabCXlafYekqj5TpBpd3psGwgDTyw0OPDqBLkx1Hgc58bAgGeZk44L2bMQDb5/hgXfMMjF/HT/cLpcthJ9b/Rwb8QajYsQoH+Eql0cnHuXx6cd5eOLhO6qQfD/YFzc3YV/c7LPP1w+/+r99nq0L17bIcDxZtRYyFiEFyhEoR+6KFcgSTZ6UVVVfVf0eC0ZbyuIOBxcBfuBQ6/jU2h5B5OJHLtIRWG3R2jAxX2PpkQkKkbPWX6foQ9GH8U7OaJjQnqhxYLpDIxJcHJ/ima3neCY9zqbZYaxTpuwCb+Ub6MhJzrsneN5+gZbX5unmN/KNnffSCpooV1ImJfnqCKeb4aclylgoDDYtMZmGXGOVQCtJAWQGROjgdnzC2RruZIBq+6imR3c95tIrPS69skN3NQYu17m5PpcLAGgBfugQ1F2mFutMH2wwfaBBYzIgbHgIAc/9yUWe/eMLZPHdCxTHlcweaTJ/tE1rOiRqeoTNSvzI3euaxSWrp/qsnerT34wZ7mSM+9kND0Q6AsdVKFfiOBK5+70RApJdUXDfR8RdoTS5WGf2SIu5w03acxHD7ZTuWkx3bbwnrK22FLm+RmwXmWbr4ujmF+x1tGcj5o+2mDvaYuZgk6Dm4HgK11NIR9x2jJvWlaX0dix995p9cXMT9sXNPvvcmiLPMKXGC9/cRpt/9B+O01uPcX2FH7nMP9Di4Fsmac9Gt1z2RsG1lWWoy6kvb9LbiNGlxZSmKuDmShxXkWclw+2UZHj7lgrlSg49PsXyIx0m2x5RpikvjcjPDSjWY9A3udUqgTsd4kyGCFeCkgglQIk9F0mxOia/MMTeqTi7HrsVoHmdm00rQSEE2hEYT4Hv4BuDm5SIXaEifIVqeaiWjzMV4s7VcGcj3NkaMrzi+siSklc+t0Yyyq/a7F6xPFdSa/l7rqAi16SjyuXVmgmZXm7csSsIQJeGeFBtUzlyV9xKlCtv6SIz2pAMC9K4wPUUXuDg+oosKRnupHtWRNdTOJ7E8RTW2sqKt+sa1YWhMRHQnAppTAYYY8l3rXyuX7lXlXP3AcWXiQc5Z5/fYv10Hy9yqbU8opZH1PAIGx5e6LDyapcTX9rgwvEdzE2+f37kMHWgztRSg+kDdfxa5RazFpJBTm89prse01uPGWwmzB5u8n3/t7e/4WO4U/bFzU3YFzf77HNrXvzEH/N7/+bnkMohbDT2eh5Jx8VxLzfg7FCfmKQxMUnYahE1WoTNJkG9AdZSZBlFllLmedU3qVa/9YbvI1Zbys2Y/NKIYmWEHhWVcJCVW0oogYxcVMfH6QQ4nQATOqRJSTIsiPsZ+XqM3owR3RRnXKAKg7XsDmrVk3UoBcF1BlErwEYu1F1swyP0FbabUm4mdyRYZOTgHWrhLdWRNRcZOMhAIQIH6StMrjFxiRkXe5Me5JS9FN3P0f3s5kLrDaB9hZ0IiJs+Z7spqYHObER7rsbc4SYzh5vXFSy6MNX5v4X4uBzHUub6ukHL+1yfdFywdqrP6unKyrV9aUSR6ZsKnptRn/D5kX/+nnu8l7dmPxV8n332uW2stdhMY8YFdvdmV27ENN0pBCBjBYnGiBwhNEY4FKJgyJiRWGGdKm4lLodspRcp7bW9iFw/4Mm/9F28/bv+MlHr6sqxZZ6z0+sxHvRhOMDGGpUqVAIiFoiRhaHey6wxQmMxSM/B8bzdxqTeayobU1U+3hUtGCjWxxSr47uyesimi4o8vO0E9wbL+wCveRo3FvrasFNadrSlpy2JAdstEKbE7gZ3TizUOPDWaSYaHm5aopISnWvKVGMKgyk0Su26UDo+Rctna5jTXYvpn+gTNTzasyHt2Yig5lJkmjy94sYospIi1VgLru/gLfqMax5bJ/uUaYml8mwYQAKBEiwcqLN4oEE9VMQbCb1RwXovY2QsbujgC4FMS1SmCQpNQwoaShBJgco0rI5pro553Fr62hKvjBhay4aBRAqi5QaNgw3aczUGWykXXtph4+xgdx8VXugQ1KpMNMdXZOOSdFyQjHLyuNxzG3mBYnq5wfRyg85chGfAzTVeqAinQqLpELfhYZUkGeYk/Zy4mzLYTul3MwabCdZa5o+2WXiwzdRy/a4sRW8GtjSU3RSEwJkMbmhdtcaSXxhSXhox7StmH+4gn5quRHzkoI0l30oYXRwxWBnR7+Vs76TEpaWUgJT4oWKq49OJHOpK4JcWOc4xcYH8GshivBH7lpt93lTSk92qy7ErEZ5EOBLhKYQj0YOMYj2mWBtTrscUGzE2N1c6Fe7NdwcyJRBKIJSsXrsSb7lJ+Ogk7kLtDbtX9DAnXxlh4xITF5ikrKa4mgtP4i02cJfq1VO171QD8iAnvzgivzSkuDRCxyUydPYmjMXkGptVk8l1NeLI3QaSuwO1CBxU3a2e1msuquZitUH3MnQ/p+xn6N2ncxkonJkIdzrCmQlRDR89ytGD6sndDHP0qMCMCvQ4h7sIvLwe1hq6+Tqb6QW2yzXGYkCkGni5R93t0HA7uDLASosVllIXlGVG2l7ED6ZYSAzBvYu3vAbjSZiLCJcaBJ0AozXjnS7DzU2G21vkO2PcwiVSTWpOC0deffO2ymKaAtO06LpB+2a3y3U1xxpqs1PMvP0hrIzY/tLLDD/3BbKTJ+DiafydCzjJgLhzkO3aEZxiTJhsEWRdpM5RJkftpvYa4WCkIvNajGsLjGtzGOkirEWanCDrEqQ7OMUYKxRWKox0KZ2Q0gkZ1pfoto8xqi9W0dMA1uDlQ5wyIWvOEjYDXF+RJxnj3jq62MHqHazpY81gd4oRsolwppFqGiE7QIm1OdgcP3SZPXKMmaXDmO0MdydlojRE+Y0bPWpbib3CWkoLhWV3boFi90/b3esPaqgEo95d1liDLwV1KakrQU0K1I0G+Ne5J621jAx0S0tXW7raMNCgfEVrKqDW8olaHl5QZeKVhcaUlnbbZ7Ll0lls0Fqqo+ouQkmssYz7OcPthFE3I6i7tGcj6m3/DVuWTFyQXxqRXxpRrseU3RS9k6KH+V68jWx6BA92CB5s4z/QRniK7ESX5PgO6cs7mDsMAt9DgoxcTFJe19I3/TefwF/+6o6hXzduqZ/6qZ/i13/913n55ZcJw5B3v/vd/MzP/AzHjt24RDZAlmX8k3/yT/iP//E/sra2xtLSEj/xEz/Bj/7oj95ym/vi5muLi//wM3APswduhGp5BI9MEj46ier4CLUrpBwBzq64et3N0ZaG7OyA9ESX7NUuxer49jcowJkKMWmJuYO4jTeTy+LyyhvVf2JXKO6dJ2c3HuSydeRyTMh6jN65tljYnaKBjUCwEkouRJILUfVaC3AN+AY8Y/Eu61xrcLSmdFykBWktAlC2KrQGcL4meampuBDtdiMH/CyhMerTHuywsH6exbULzGyt4pYFAosXRkR+C5mALyOGRZdzDZcL88usTS8irMXPU7w8I8gSwjQmTGPagx1awy7tmVke3h4x+eXn3vA5eSNY5VQNTx0PxkOEqUSHdhTjdpN+6LMtLSPPZey7aCWrYytK/FKTq6rpppYCxxjc0iCA2HOu6k7u12osv+UJFh9+FC+McEoXd+ggc7EnusVQEJQBStx7p4G2mnHRA8BTIZ4MrqmBc+NlK7GVWku2O88NhBLqStCQAv86QqWwkO8KNGPtngiDKutqt8k8UGVMKVciPYVfc4naPk6gqnuRe+WBTChJvlG5T+1NMgWFK7HWXvtgosTVYsSTiPk6SoC47LKMS+yu+JSRg2x4qFolZPQwrwTRa1frCJyJEGcywJmqYsPCRydRt1Gr6V7ydSNuPvShD/EDP/ADPP3005RlyU/8xE/w/PPPc/z4cWq1G6etffjDH2Z9fZ1/9s/+GQ888AAbGxuUZcm73/3uW25zX9x87WCtZeN//wq2MNjcYEu9OzdVWXZf4c5GlQViN2hRhs7eH91VX11jK5eKttjSYLXBxCXZq13SE93K4nMzRLU96TuIQCFcSbkeX+PGcGYiVNOrrC6Rgwzd3bmDHhcUF4bkF0dVXMNr1u3ORriLDbylOqrpV6InqSxAQlXWKukrhF+93gv2tBa7e8c0yZU4Cj3avQFJUQV2tv0qC6ZVTSYpKTcqa1e5maBHOaruVYGgzSpb5vINTV62BnlvvJtx2c/Iz/TJTvfJzvQptxNU+/INMUC0HIxrKdMMnRUooXAcH7cZots+WdNjXHcYYRmUmnNJzqk441SSspoWu4NHNYj0Cs1GXr13mbo1dPIELx7iJGOcNIEiJ/VDkqBGHEaMwwaFd/MmSQrwpCRSkhCLW+ZslobRdQrJXY8gjZnfuMi3fe7jvP/LXyRxJcPAYxh6ZI5iYpTSSjIyRxH7LonrUCqJlgKzKxguC7UoL6inOfWsQFiLUA7hxATh8kHqDzxA64EHqbfa2LKsisoNhmTr68Rf+iLZM89CerXgtLArVK5/69dBgMxzxOvK8VshEK/5m9NKkU90yFt1ttKYoYSx5zKIImLfR2JwyhJpNK+XBTWnReQ0cISHK31cXAJt8coSp0iRWYIoM4zrU3ohxq9D0ES6IUo4SOFQ6JRhucOw6DIsdojLAfZ16UOO8HBR/P/Z++9gybL8vhP7nHOuTZ/58tnyrn33TM/0OIzBwHAAgiIggSCCFLUhiARDIYCz3NByFUKQ4gJBSjSrWHElcckNKAgKABHchQAQQw4x5BLAOMwAGNMz3dOuqrrse/VcvvSZ155z9MfNelXV5bur3Ux+Kk7d+zLz2rx5z/f+zs94aUrdc2mUq1QOHEa1TyH6gmDqUzENXHkPRbOAyMRIFJ5w3jJH+/FsWHOoLRNTiLCJtZTaITrVBOOMRUew5ErqqtinibZs5YatzLKXXzsrQkC54bN6ssHRx5ocemyBsH7t2I027Fwcsf7iHv1LY1pNj8UTDZaeWHhHJNJ814ib17K7u8vS0hJf+MIX+MQnPnHLz3zuc5/jL/2lv8S5c+dotVr3vY25uHnns/80ch/hiXdcX2aIX+0Tv7hHfKaHiTToayLqTsiqR3CqQfBQE/9kA1W5tycVPUrJrowRgYO7Wn4gwuHdyL2UA3gj5MbSyXJGuWbFd6k6N59nYzTpNCJLY4QoLHRjY9nKNFu54VwOXxtO+dPBhE5259DlUEreXyvxTL2MKwQjrRnlmn6u6WY5e6nmQpSQvua2upbFrCYTwiyhZg2553PBLzNSLo7RSJ3jpwmVyYh6FrPoSFq+B+UKulQhihOyrXXiS+dxBl2CmZUojKf4aYLre1RbbZLphHg8IrOW2A8ZlWtMSk2GtQUm5RrYnNXA5ftWF1mOE5wrm7jrG/iXL+NvbOD2r6Xx145DXKvjj0c46TU/qsjzkdbgZ3e2SI7DEuOwROJ5pK5LrlxwFJ7j4DuKShpTHgxwRkPE9O71qGAmsKQohtmEQNaqeCdP4p46hffQKbxTD4GA/le/yuhP/xR95ize3h6vzaeYKslOrcR2rUzsOpRlmZLwKWeWMM3xsww3y7DZlBxNjiFShlgJtJRIwBEOEoUSDqNGm3FjESkL4XXdHt+wXYFAColAIYWPFCARKCFRuUEqD+n4RDqin43o5Sm5KCFkA6/UotJqkcWGST+dmS0lQtbxQh8pBW5x2ySZOWdfHRazFqJRepMDsRAQVNwiKixQDHYjsvjm4UQh4MiTbf7czz11T9/Tm8W7VtycPXuWU6dO8fzzz/PEE0/c8jM/93M/x+nTp3nmmWf4tV/7NcrlMj/+4z/O3/t7f48wvDnBUJIkJMm1p+jhcMihQ4fm4mZOIaLMzNKTGEySFz4vceH74iwEOMuleY2j7xGstYy1ITWWzFoSY5jqa63iKJ6ohLh38aNIjOGlccxX+2P+096QPxmMH5RL021xshQ3z3B0Tup6JP7rS7ZWjqas7O0yqFTp1hoYKcFawiQmTGJGpTKZ67HkCKrb26xevsiRzXUO7G6z1tlmtbNDazDAMbf3t7kdWimieoNJvUG3WmcvCAgHQxYGPdr9LpX43gTQrRC+j2i1yMolzJVN3On0da/rdkzrNXAU7jRCWEvSbhFVyjjDEe5ojEozVJ4jrCV1FKOwxKBSI0xT2oMBYZpgEPRqNTr1Or1KhcSROOkUkcdkjiJTksj32Vw6yDQsk3gBaVjGX1njwEKbJw+uckAK/J0NxpsbAFSaLSrNFk69SezX6aY+L10Y8e3tIZesplNVxJ5gaaBZ7eUcjuCZxSqHDtfobU7ZfLXPsBPz0AeX+TN/9fEHft7uh3eluLHW8hM/8RP0ej2+9KUv3fZzP/qjP8rnP/95fviHf5i/+3f/Lp1Oh5/7uZ/jB3/wB/kX/+Jf3PT5X/zFX+SXfumXbnp9Lm7mzJnzVjDMNV/tj9lKMvqZppfnKCF4ohKy5rszIWUZ5JqtJGM7zdhJMvq5pqQkFaXwpGCY62L5LKeb5/QyzUTfebh10XN4vBzyRDXk4XLA5Tjl64MJzw6nWKDhKhqOQ91RBErgCkEgJRVHUZ1tO1ACT0qWPYdjoc/R0CecRRVNtKaTFvsSKkljtpw3HhHt7REPhmRxTBLFZElMdxqzMZqyNZ5wycCLfpmdWp1etc6oVMbKm31kinMgaWYJ/cGY3OjCqdpaFgZ9Tq5f4MTli5xcv8jxjUsIa3nlyHFeOnqSrYceofSep5gstHlpEnMuSrDa8KELZ/mpl77FY88/S5ClCNdF+D6srNJfXOJyrcHZoMy6FyByjcxSSqMh7fGQhtEEnksZSzsMaCcRfPaz2PiN+5vdK4nr0q/U6NYa9Gp1urU62602G0urbCwuc6W9ROK5qDynFEe4OsfLDV6eFRFyQmApognr4xHHrlzm+MZlDuxuMQ1CBpUqql6n3l6gvbzEVnOJ544/xDaGWFv+7ftPvWXHej3vSnHz8z//83z2s5/ly1/+MgcPHrzt5z71qU/xpS99ia2tLer1OgC//du/zU/91E8xmUxust7MLTdz5sz5biUxhlFumGpNZCyRNpSVpOU6NFx12wiidwqZsZyLEk5PYoa5JjJF3qCDgcuR0OdQ4N0w1BhpwzeGE77aH/PV/oRz04TUGhJTOJEvOpK2q5gieGkccyvp91p/2wdBc9jnQ9/5FuNSmZ3mAtIaHrp4noO7W2y32lxeWmVUrjAJQnKlaIyHHJ6MeI9JWVxdQRw8iFpbo5Qm5Bcvoi9dgvUN4itXUNtbLHU71MZjyvEUeY9ddux6BNnNaRleD8+feJj//G/94v7fFz7xFMHbEDb/rstz8+lPf5rPfOYzfPGLX7yjsAFYXV3lwIED+8IG4NFHH8Vay/r6OqdO3agofd/H9+/NWWzOnDnvfIxJyfPRrA3ROsZShGFbW3RnQXCAMDyElG+/E+SbiS8lvid5h9zK7xtXCh4uBzxcvrkA5K0IleRjzSofa1bv+tlJrvnWaMo3h1OkEDxaDnikHLDkuTw7mvL7e0N+f2/IxTihiEUoRMOJks97qiXeUy1xouTjCYEjBFIIBrlmM0nZSjLORQkvT2LOTGJ6tQaf+75PAtBwFI+UA1of/TAHSj7P+C5LnkvdKSxwjigsZG3PQd5KfD58/IY/I214YRzxrdGUEvART7CWRJhul3xvj7zTId/dJVvfIL14kfTSRXRn70ZhIyWiXEb6PtYYrNYYrdFZSmpN4eweeEx8r3BkVx7aL2OMxc8yOtUKP/zK1/nx/+VPcijw3vGiGd7mX4S1lk9/+tP8zu/8Dp///Oc5duzYXZf56Ec/ym/+5m8yHo+pVIqMp6dPn0ZKeVdhNGfOm421Fms1Qqg7+uoYk6P1hDwfo/UYrSc4Tp0gWEWpu5cWuHGbRYcu7jHs9e3GWksUXWQ4fI5cj7F2Jkwws6KKGmNSsqxHlnZJs+5sukeW9THm3sz/QjiE4RHKpeNUKo9QqT5KtfI4QXDgrn5UWk+J4y3SdJc028PoCGNSjM1wVBnPa+N5bRynjpJlRl1BEPqUG/fv63K1TtDupRGdyyMmgxQ/VHglFz908MsO1WZApRVQbRWV0V+bydfaIsV/NMpI4xy/5BBUPLzgztfhdzNlR/HRZpWP3kIIfaBe5gP1Mv/n46v3vL7JIGHj1SELkea9rsTxQqRTIg004ygjTzTWWKplF9+4+JmDEykmmwmDTp/LuxHWWCqtgErTJ24V32lQdslTTZZq8sTsz19NxJinGpFonsoMru8wDRWXSz7lxlHKBx6iVveRjmDST+isjxmuj+me22GyvotxAqwfIlwP6UiELCrYIwR5UmwnmWbE4xidWYy59T3ELyl+9IqD/68vMqn72L/8EATvbEH9tg5L/dzP/Ry/8Ru/we/+7u/ekNumXq/vDy/9wi/8AhsbG/zqr/4qAOPxmEcffZQPf/jD/NIv/RKdToef/dmf5fu///v55V/+5btucx4tNedesNai9ZRcX7MQXLMWjMjSves63e51HXGvSG4GCOEihIOUzv48WPJ8jDG3d450nBqBv4ofrOD7q4TBQcLSEUrhUcLwMNZqBoNv0h98g0H/6wxHz2FMMhNUHlJ6SOkihYeQHkGwSql0nFLpGOXSCUql4iEiywfk2WA2HaJUiOs2cb0WntvCdZso9caqAFtrSJJtptNzDIfPMRg+y2DwLFnWfR3rApOWyeMaJg8ptbrkfoORXCIUORUR40uLtTlRtH7bc6xUBd9f2hcoxqoik3Au6OYGmW6wqM9Q5lpeI4NkRAWmFUR3hWy0RDZpkwzXSPqHMHlhefDr69TWLlBd0lQbNeoLa7jqJDpaYNLPGO6N6e92mAympBHoJERnt4/Ai13BxBdoJZh6gq2mYqvlsL3gkkpYmBoWxoZmP6c51LRGmjC1ONrialBKEFRcwopHueFRafiUm0XnWmn6eK2YsX2ZZPJt4sE3GI2/Q24yhjTpiCU6tBlTJSYkESWk0+DhUPL+eoWT9UNUyqcIgtV9YW1MwlbnK7zUfZGpe5wsfJxuHtDtxSSTjErocqQV8nCrzJoH3+pe4Pf3uvzJpEyCT8t1abkOQsBUGzJjC+uUFLRch0O+pMSQKO1zdhrx3NTlXFbhcBjwoXqZ46WAzSTlUpTiCMHh0ONw4FFWClcKptrwreGUbwwnDHPNB+tlPtqs8t4woNRNqTiKoOzi+ophJ2bvypi99THrr/ToXrmPPFdvMY4nye+W7uJBIeD/8P/+JPIdPiz1toqb2z1R/Mqv/Ao/8zM/A8DP/MzPcOHCBT7/+c/vv//yyy/z6U9/mj/6oz9iYWGBn/7pn+bv//2/f8toqdcyFzdzbsWFi/8D29v/7rqhjplF4U1GSg+lKihVIsv6aH1zBey3E9dtUSodLYTVbOp5CyingqPKKKeKkiFZtkcUXZ61S0yjC0TTC0yji7e0tAjhUa0+ju8vISjCese7LbZePEI8LBEPS+jMm4VuS6yVJBOYGan4//5Ale2mQ+Jeu4cI4EP1Mn9+qcGfbdeo2w5xdJ5zgwv8XifhD6cL7JoSrs1wyIl0lbEsEctbD4lU7Ji6mDIyNUbC30/+V59olvqalb5mpZez0tM0khi0Q1HE4O5oAd2KJMws5djiBn385iWC5kV0eci3wkf5WuVRTldWMW/AIqe0xc0tfm7xMounIVMQe4LIlWTXnz9rcW2OQZLLu6cuKNsRxzjHcXGJhgy5mJ3gVVPmirOAEe/O1AdhYqjEBqVBGXC1JUwtpcQQJpZ6pagIb7TFakMltbSsZFFIlqSijCCLNMk0J41z0lhTrnvU2yG1xRCpBONuwqgb77c40WQlhSkp8lChvKLIp3KL4pxtqVh0HJQjyRNNEuUkk4zJIGHST9GzJKhCCporJRYOVGgfrNBcLSNVUbneaIsxFmtmU2txPYXrKxxf4QXFvOs7qKspOGaXhs6KQqTTQcp0mBBPc97zg4felu/nXSNu3g7m4mbOrTh9+u9xef1f3vS6EAqlqjhOFdepoZwKrlObWTgWCgvHVUvHbKpUCWNzrMmwNsfafPZ3kUPFcSo4TgWlykh541N7no+Iky2SeJMk2SKON4niS0ynF4mii/sWjzA8SqPxDI36M9Tr78d1G1ibFUMnJsPYFGtStEmIo8tMp+eYTM8xnZ5jOr2IEBLXqeO4NRynjuNUMSaeWaB6pFkXax9MZmUhHILgINXKo9TrT1OvP021+jjyNYnTLjzf4bP/9O7ZfP2Swz/9/jKbtaID9TJLpsDeIkTbsZDfw6iMMFc7MUvsCcbhLQSFtTdk5L2eshTUlSTMDd40w401XpzjTzTVuE893cZRU7ZaVS4tHOBiuEiKwM1SGtmEI3bIoXyESFJe7YOTJPhpjDQa16Q4VuOS4zZdvLWcA2KHwEbsOG22ZZttp822WmSHZRJxb/4rdzsf1chQnxrKscWbCSQjYLPpsNVQGHX7E+tllkpkKCez5U2G8CIyfPpeQK+iiHxJmBhObGWc2Myoxhl6cZus2UO5U0JngMgdoukSiQ0YiRodp0qOxCWjYXKOp2OW+uuMZZ1OpUbuLrAwCnFGllhCf8Hj1apkLIvSDtLASj/nwF6On1kuLrpcXFRkJUkJQT2zNFJLqIsM18papIVcQiwFsSpyyIwcQd8r2kSxf100HMXxks/xsGhhZnl1b0IvkGyanF6WkxpLai2ZscTGEN8mmeL1rCB5NJF8qF7mo0s1TpQD6oshdpqTjjPiKC/yfhpLrRVAqvdL1exnFfeLRKE4N2djf7cwFzd3YC5u5tyK8fgVkmQLx6minGtiRsrwHXUjyLIBYHDd5utex2sT62lr2UoKIbPsuThSzIblxoUVZnrhBktMlg3QerzvLwQgpU8QHCIMDxKGh26w9ATBgXty7B11Y1740ga1dkhtIdjPiHr1FhVWPUpVD+VKnh9OSXsJ2ZkhOy90WT/dp+cLXj7o8eIhj432df4A1nKok/PY5ZS1bo6WglxCPXBolzxKqaUqJGHJJYtzonHMXuc8O8EBpoFkrRHy8NE6jz7UonKkytk848VJxPOjiO+Mp7wyiffz2ITRhEfPPsfJCy9RGw0oT4d4+c0iMZcKac09R77cgBAsHz9I+1SALF+hVG/QXn2MxbVnqNWfQDo1Yq2Z5inTPGGcJwzTCf1swiiN8JlSthPaYYuVyiPYgcv25pitrQndfoJONZWJwQGkI5GzhHBprInHKfEkYzTJuBIUQmezKclFwto04uikz/JgGzXawPFcaktNKssJMjyHcBJcZ5nhumD3bJ9hp4sbVHC8GnkWksUZ1kzBTrE2htl1Wvyj8MW6i+B2hEegSviqTM1doOWv0PCWcZxFJkYxNraIKpuVVmg7kkXn1qUV7pVMQM8V7AaCPV/Q8SUdX9DxBRuh5EJZsh2I2wrjq7hZISKvlgwRswSAo0DeKNyt5fu3cv76uZRHxvc/FKVdiThUpf7eJapPtous73dbxtp3hBPxXNzcgbm4mfOgWI9Tzk0THq0ELHpvfVRObiyjWZ6R3TRnN8vYTfPZ3xmJsUX5ACkJldyfj43hclz4JVyME9bjbFawsAiTXfVdDvoeB4OiLbgOTVfRdB1arkPLVbRch4qSgEXrCKXCuzo0T7VhJ80Y5ZpRbvaz+460YdlzeH+tzLJ/6/M4yTXPjqZ8bTBhI84o6qQK1GzqRIbgzAj/pSHq8pTUgWzJJ18MaC2FPHGsyaNHGnhCkMUaqQT1pVsL11e++mX+3T/5hywcPMyTP/hnefKHfhgvuPWQdzKdsLt5hbMXznPxT75C5/ln4RYJ7PIgBAQqiW4oYQAglEIGISYsYYISC/U6i/U6QbmMVE5RWFYIrDFsvPIS2+fO3HJfpHKottuE1RpeEOIGIdNBj/72FtksB4sQoqik7vt4QYhfKuOVSuA4pAgSC3GakhhLGpSgVEbVm6hWG6fewPED7KDH9OzLZBdehW4HNerv16t6pyKQVN0mJadGSVUpOcW9f5IPSPSU0KlQ8muEbhXlKZSncF2FVRpDhKsMoQogLSGyCjIr4VoPZQthkJuU3Ob7zv3a5gyzPaJ8xGJwEN9v0xOgZYIMhlitiHKHXi4ZRAEqh7IoBFcpTAiCHMe6mNgjloIrTZfNdkA4THlsqDk6va4MBkW5kKvzRkAiIJbFIKlrwLPg36Kn18CZmuSFhsO5BZeo4bGmBQuZJckMPWvoWE1Hwm/+hffdOrrrLWQubu7AXNzMeVD88uVd/i9niyygbdfh0UrAY+WQRyoBj1VCDgdeUcnYWvJZM0BuLbE2TGaZbyf7Te+/NtaasTaM82J+og3jfPaa1kz1vZmz7xVnds+6n0y6nhA3iJ26qygpSWlWk6mkJLGxvDKJOT2JuRynd6t2wcHA5f21Mu+vlVhwHb4xnPL1wYQXJtE95ybxU0PmCMxrnsYFcDDwOFnyOVkqcqjUZwnsao6i4RbTy//p3/O1/+nXyZKZIJASv1whKJVxPA+tNSbPSKZT4vHopu2vnDjFox//AZaOHKfcmmWH9XwwljPjiH+7vsWXN7YpTy1rmUdTK0Zlh2HZYXlqeHIj4dhuwkDC0BOkJYe85jKtesS+xI77ZJe+g9k4jZgOsfEYHQ2vOSS9TVgEeVDB1g6iqgdxrSCc9KmN+xidkNsMay1Nf4Wl4BBNf5lER0R6TJSPkULNrC4lfBkUvlZK4LR8qPmUVmsEK3WC5RoqcIGivICqughPobOM/k6HS9+5yKWXn8fkm6TTPXrrHZLJ689ufJXy8pRwMSbu+iRDD+UapGNJRx55fGdhH6oKFotEEjpVyk6dslNHCQeLwViDsZqq22KtdBJPhSS6cGAOVOWmAqDa0Zw7Av9xqcyZks9lR3BFaLI7/EaEtZQ0PDrQfLST87FdzbHJvV0zu74g/M8e55GTr99i/CCYi5s7MBc3cx4Uv7LR4Zcv73I+Su7aab+Z1BzJouuy6Dm0PYdFz6XtOgRKEmvD1BgibYhm5QQcITgcePuRJEdCn9WZxWQ7yViPUzaum/aywlegezU7blYkW3s9hFJSdxRVp8h+W3MUZSW5MMsZcqe1HvBdPlAvc6oUFMUfrxOL2lqMvTavZ/OptVyKEs5OE/r5vVsXgiTmmbPf4onnv0q1v3fHzzrVGqXFZZYfeYKHP/4DHDx8hJK65tdwIUr495f2+PFfefWet3+/GGuI9JhpPigEAwnonECFVJwm3sxp2mLRNiO3OblJyUxMahKM1bOikxaJwmJJTUxkJ0zMkHE2INYxQme4wmcxOEg7OEjNXaDk1AhUCcntw863fcHLNcXFsuBySZLOKox71hSWBQOOFJRDl2bZpdr0sU2PpFLsS2Qsg0zTyTS7mSExhqarWHA0izJiTY1Yk33adJGmX0Qz5n2MjslNSjxImXZSslFOPjLEI4uwAr8u8EqCZCSI+hD1crIoR2cSk0mEsihHkEXyrnXormIBlCBq1Ol5dVa2LqPeoPBsVhocbZ6icTBjWHqFvrpArnOsFlhTWOO88iKT0lH2xBoJTayoYEUJbRy01oRCUJKCUAoqvk+1uQTDEHc9xdmcUh6lBAZGEq4Iw561nNSCwAq0sSz+rx/l5NNLb+g43ihzcXMH5uJmzoNmojWnJwkvTSJeGke8NI55cRLRzYrOVACOEDgC5GwoJZCSspKUVdG5l9SNf1dUkQK/PHu9ohSVmSAoz96rzN7zbpGy/kFgrSWOLzMavcho9AKj8YtMJq8SBGtU6h9CVN5PFDxOTyv20pzhfh2maxYoRwhOlQMeLgU8VA5oe7cf3x/Pkq59YzDl68MJ/Uzz3lrIM/UyH6iVWQvurWjp7Y5lL9Ocnca8Ok04M43ZTDKGuWaQ6/3SBoNc7w/RzRakMhnhpxFBEuPmCaGKqMgxFWdMXnWYeDUiQqaUiCgRETKhQtlxCZVkJ82pZpY//IMbI+GMJ0mbkiyIcMYZ7thFu5r+wTF7BxI28jJ7o4DpJKAydVmNDZWsGHbQonCUjhxBpCBSgokj2PMEPZVw9NzvY4Qgc1y69QU2FlbYqzeRKOqZZGGS0BoOqY17uHEXm48JREidKlXtEhpJREIkUnKhGRMzEQkNW6JJg165Sj+wHDCaRuawFJfoOlOsH+DVV4iUIXEsvbjD+mgdNe6SOC65UihjyJTD2A/pVOpcWF5mXApxyKgyosYAgBFVxtQYUMPeY/SVaxNqDGnYPkfEOd7DszzB8wTcPTdSgkeXBaaU2VSP87J8ivPiESJRwR8NOf7KNwkmQ7oLqwybiwidQRKzV6rTr7VIPf+WfjVrOuVjesJDFZcjokOye44/XR+ztVfUtjMItHJACta2LrG2s15cH0JiBajX+SBxr0RuSN+vM3SrDN0afVmnIxfoeAt4ZQjXJGI5ICs7pFbxI9F3+Hsf+hjNxbe+ztRc3NyBubiZ81ZgrSW3hQ/L2z1OfT3GZIwnrzAYPMtw8C2m03NY7MxfZua6KSTWaiaTs3cNTZfSo1p5HD9YI/BX8P0VfH951lbw/cWboqLeKNYa0qxLkmyRJjtoPRtyEOLaMVCEs0oZolSIVAFqNq9UiJQhUvr7lgatI9K0Q5J0mCQdhvEu42SXKNklTbbJ0x1Evo3K9xB3tC8VGCR9GvRp0qdJ6C1xQnq05QjyPlnWI7brWO4tPf4mq+yyRJURlVkLhGbqHGPonWLsP87AOc4my2zsxjz+hX9/y/VkUpErRfiA0vI/KHYqDTaai+RS0S9V2Kq1MFIircUiEGhausuK2WbR7lC2E9IkJE9CstQnMz42l9TiKfVoQjmN6ZaqrDeX2K3WcVSGFZLI9Rj4JdJZLh1RXP2k+GRiJp6tZWEyYHWwh7SWVDlkyiF2fSZegJaSchJRTmOCLGWr3mKvXEcJgRCF5cbYGw09Eqhazdp4wNK4z+p4QCONUNEUM50gpcQLHLSjmEoYOh4bQZOJE9AcD1nu7VCfjnDjCPIYVA5iSiw9JqaEiA1ulOJkOQiwEnLjoIXCCoFBYhH76Qxck9HIBpTukG9rKgPWw4NMVIlm1qfhjKiN+0hr+cG//pd5+of/ypt2PdyOubi5A3Nx82DJezHCkajq63+q/l6l2/sqr77631AunaRcPkG5fIpy+SRBcPCesg1ba0nTXaK4yC8TR5fJ8xFCOIhZ4kA5m8/SLoPhtxgOn7vnDL9Q5KOpVE5RrTxOpfoY5fJJoukFev0/odf7E9J0567rUKqC57Vw3YXZtIXrNnCcKo6qFFOngnKqSOGS5YMiJD3rz6ZFS5IdkmSbNN3F2vyej+FOSFk4Ct8pqeJrEcLZF3BKhuTXZZrO8xFa33uyNyE8SqWjlEsncL0mRsdoE8+mEVK4+MHqLKljMfW8RTyvjes2bnudZFnGxcGQ569ssf7yywxePUOe3Pi9N9ttDh06xImjR1lZWaHX67G7u0sURaRpSq1Wo1qt4nkelUqFarXKxYvPc+HCt9ne3WJXa7ZUE5kKSuOMSdmjMo0JIoORFgTo0OIuDTjefI6qnmKtolo9Sbn8DEaf4Mz5DpfOXeCt7oZS5dCp1LncWma9sYhjNIujPsujHgf6HYIsuftKrmMQlDmzdJBXVg8zCsoAhGnM0rDH2qDDan+P9rh/j1mQ7g0LXLE1Xs3aXDINcm62bpmSwgYKkVvIDEiB9RX4Ehs6eE5KK+nSHu9SnQxoxmNqyYTGpI8/HiD1zb8z7Sr++CM/yCtPfoRQGAJpCaXh6TDmv1jqIaSDFA5KlWm3f+ABHvFc3NyRubh5sHR/8zTTb2yj6j7eoQre4Rqlp5fetWLHJJp0fUR6aUS6PgJtEZ5EuArhSaSnEG6RdA4pKAwexbyqejitANX0kWX3riHkly79C86c/b/e9LqUAaXSccLwEEKoWUmCwh8CLMYkRNEGcXwZY+7vJgzgOFVqtfdSrz1NtfooQrhYo8l7MdnumLwzJe9EqF6bIDuAdPwiT4Z7XXMkuILU3yJtrWNaY/KwT5puF3l6km2SZHs/W/OD5MofL6EziTQ+wvgIHNxQUD8kqR9SuOUiTMRagzEJWkcYE8+mRRmFWyGFh+su4MoWrm3imAYqq+EmTZyoiavbeLaNQ6P4XkSROE2EDk7DR9V9VMNH1R0yNSTNdkhngixJd5HCm2VFXpi1Nr6/XKzrTcYYQxRF+4WEG43GPSU9vft6M7KsR5rukWZ7rHc6/Mn5EV9fF1zqSw7XOhxvXOaJFcV7jn+Q5cVP4nmtG9YxHo955ZVX2N7eJs9zrly5wtbWFgBSyllJE4vrujiOg5QSKSXVapVGo7EvwDzPo1arsbCwQKVSYWNjg7Nnz3Kl02Gc5VhjyKcT0vHdE2VaqejLBqlVSHIcq/HJCWyCwKBVQCp9MiOo5n3kzJpngT1Tpqoy/Ftc+471saaKNmVcGxLagDY+qbWcEQlTkaFJsSJFiBRExo51GVmfyLqURUJDxDTllCV5TURrBD2vSa+1xEa1zYZTwq341D3F8mTE4e4Wy1HEinBZMg6RtnR1TJ6mOPGEPlNibr6XpAhyIHE9Yi9gu7HAH5948pbDb++zX+O/5B/u/+15i3z8Y39813N9P8zFzR2Yi5sHS+fXXiR+ce9GG6wjKL9vmcrHD+Au3l+dJBPnmESjat6bml/GaoseJOSdiHwvItuekl4ckm1N7tlx8E4IT6GaPk4rwGkGRafX8PfnZdklSbcYDr/NZHKGyeQsk+lZptNzt+18b40kCFYJgiK/TJHMT2NNjrGzJIImR6mQWu09VEtP4U1W0d2EvBMXx9+JSDfGkL/BsX1H4B2s4h+p4R2pIasuuR2R6R6Z7pLpPmnUIZ3uksY98nREno3QZow2E7SaYmWOysrIrIzKKqi0WkyzMk7SwEmafO75f0uqby3qBIKWv8pa7RQnjz5DZblNFqQESw1KKw3chRIWTdoZkHb7pN0+eT+CXQ/TEYgHFNEsXFkI3H1BqPbnZeggS+5sOpsvOaiah9MOEXdJa29zQ96LybsxuhuT78XoYYLVhQ8Hxu7P29n4iHAlKEGsJzieixeWMMqihaY/2mS7c57t7XPkOiMolQnrNaorS7QOH2LhwCFaBw7i+teSA9rMYKKMfpTxla0hn3/xCl85u8vmHaJvPCU4uVTBUZJJkpNpTkfzZgAAbpxJREFUizaWw60S/6v3HeDoQpmLnRFfv7BHZxjz8VNt1hohk8ywUPaYZBZHCt57qEGr7JMZg6ck2sKVfkSr7PHS5ogLnQlPH27QjzJKnuI7GwO2Bgk7o5gvn+1QcQUtJ8ONOlSSPeq6T4aiT4WOKXEpLdOxZcxd7CwVoIYgQVOXPU6pDqtqeO0cWXBtyFHT5KBpsmoalLn/BItTLM9JzZ/anFQJnhCKNSuQOmIkt7mkthnJGy2PwgrqNiTHMJb3bql1rKSEh8UwEjffh5ZWJO/5fo9Iw9RAZCAygqmR1MWYx53Ls3tPjuvWeerJf3bfx3sn5uLmDszFzYPHJJpsY0y6PiL6Tof00iw8VjB7kr3aPFTNxztUxTtY2b+Jm2lG9OIe0fMd4rN90BZZdvEOVnAPFp91lwtTr9UGdHHzttpAbrC5xeamaLowv1ptrr2WW8gNJtX7nUHei7ldbLGq+3iHq3iHq0jfwaQamxUZP22qsZkBO0suN+s8rDboQUreizHDexAnSuA0fJzlMu5qGW+tjLNYQtYcEnOFyeQscbwxO4/XfEmsBaEVPst4egUnbUNkMZMcM80w06w4B5bi7mrBGosepuR70R33TQTOvvXNO1TFaQXXzmF2XctNcT4yg4016caY9OIQM3njGY1l2UW1Apxmcc1IXyF8ZzYt2rNf+Sx5mmJzA7nFZpZhZ5srm6eZJP07rl/c1GEVVjFHeLjSx1MBvhviegHK8/DDEvXWErWFZWqNRarVFkFQLZLKGQqH0ElG3k/QgwTdT+7rPET5iN34Mr10h0RHpDbCuAa3VMLzAxzhIo1EGInQgjxNSKIJqUnQNp3lb1mg7i1QcVpU3DqBqpDoCZvRefaSK8T5mKkeMc565K8767QgcMsIK2aWxOLM/dMDP02krnXYwhoW0w4Ho3UW0i573gJb/jK7fptMPnhrbj0bIIWg5zy4e/nBZsiPPbrAAdPDrl+mvDGlrksofGJRpNZbFTWWufbgdtUzaCimbIsBdVuiaSu4s6GiibBs65RRukPdGgIs2uRkaAZAWbkseFVcWQwlO8rDES5CC8RdnjkslqGIuCz32JB77Mghibj2PUsraAqPRlBCW01i8qK4LwYpBIFyqEofL9LE211EavFkgFQ+UeBglUIKl+C9bY4/854b6kC+1czFzR2Yi5s3F2st6cUhoy+sE790++KIwlf4x+pYbUheHRQiYf9NHoj15K44AqcV4iwEOIsh3qEq/uEaqv7GHGBtZsj7MbqXkHcLIaX7yazF6GF6x+MTgVMIwdl+mGmGjXLMrL3RcyNLDk47xFmYHXs7xD1QwVkIEa8zU6u1trAAXRySXBiSXhph47zY1av/WZCBc53g9faFr9P0Uc0A6b3+IZrz3/oGv/0P/uvXvfy9IqRCOQohFVLJYjobKnF8H88PcVwf1w3wXB/H9bFak0YRrhviOwGTYZ+d7XOMJvdeQFSiqLoLVN1GkdRvJjIEEKgySrh0knW6yVZRYf0eKYV1llvHWKofxZMhSTwmHo8Yj7uMsi6DbI/0Op+kqzmDDYbfW/oUXbfJ4egSD2dD3oPHqtfG2JxYT4n1hCgfM9FDNoFdt4awBtfmKKsRwHqwxunKKXLhUM4nLKW7BDrmfOkoWkg8kxGpAM9kpNKl95phLWC/NEYpn1DVE5a9ZZ4xsCxdVq1F6IihzciSK2wkO0wEHHIXOOQv4UsfKKycBk0SXSSKBxypPMpa6RTqDsOGuUlR4toQtLGaUdYj0VNc6ZOZhMREbExOc2ny8n19L1fPddNbZqV0nJXwGL4MmeoRUT5img+Z5MMi/N9MCVWNqtuk4jZwvQYEFZRUrJgmLopER4yyLo50cYR3w/Re0D8UcuTPPHNf+/+gmYubOzAXN28depQWpvPB7Kl2UPydXhhgpjc6qrkrZcIn24RPLOC0QtLNMdl6YQ1K10fke3HR8SqJcARCzeaVKPw/nNnrjrzWlJi9Lvd9RlTDLzr1dlgMfb2BtOuvF6tNYUnpxmSbk6JdGZN3Y2xyb+MiV4c9ZNndH9pQs/midgywX/xOoCruTNAEyNJbn035rWA66POr/6dPs3TsBMvHTlBpteleWefSC8/h+T715RWqC4uU6g2klOgsm+kuy7Czy3B3m8HONsPOLln8xpO+vdORQtEK1zhce5Ql7xCOcYntFCfw8GolnGqAsAKrDXmeY9OceDxiNOoySXuM9QDH9amVF6iXF6moJr72EZkshvfEdaU+bGFhML5Fuzn4CllSECicio+jHOzQYAcZdqSxsQZhQQrwJKKkEH7xO9ZSYARYV3KmHzFMUx7xcrJxjJpmlHQZ7wHU17pKoiNym2Ls1YOC1EzppduM8wGpjshtTpSPmeZ9Ij25rYg5/MRTHH3P+1GOg1CqsKpmKXmWorOcPEvJooj+9hW6G+ukcUxz7QD1xWXA0t/aZPfSBew9hIc7wmU5PMaB0knWSifw1e1dBDKTEOsJsZ6S6ojUxKQmxqn4NI6s0X7oOMsffgSn9mAjH++Xubi5A3Nx8/ZjjSXbnJC82gcgeGwBt/3GnRu/GzBxvi8E9SABKa75ZlznqyGcNye3zZwCnWdM+n0m/S7jXpfhzg6DnS36W1fobl4hGvRJ71MAOaLwZdCvifQSCHxVxpXeLLFe0ZEKIQsbyX59paLchZ2Z7q6GvEupkEIipUPdWSBUVQJVxpchgSrvZ7vtp7sM0l124kuks4g5JRzKTp1x1segb9gnT4a40seVPhbDMN274TO3QwmXQJVJTURmEgJVJlQVhJDkM3+yklOj7DRYDo+wEh7FfcDpAoSv8I/WkNXCOmi1wcY5+U7hX2a1wZQskZqQiwxp5P7wn5/4KOXiLldwFkOUq2a+gDkYi2oFuMtlZN0rLHdKIgK1/zvFEUwHfbbPn2Xr7Gm2zp2lXG/w9I/+eZaPn7zl/lpriSdjRp1dhrs7DDu79DbX6Vy6SOfyxZsyYbcPH+XUBz/CyomHWDp6nFKjyXTQp3PpAruXLjDY2SYej4jHI9I4wnU9GmoZpRWD3g6D7jY44NUq+M0SQaOGcl2U4yCVQ3fjMusvfQeji++7trjMz/6//j9ve529ubi5A3NxM2fOW0Mcx3S7XXzfJwgCfN/HcW5O4metZW9vjyiKWFpawvffnKdDawsH1txYUm3ItSXXhjgzxLkmzjRxZjDWslD2WKz6VDzJdDoljmPK5TKlUmn/Bp9nGdFowHQwIJmMMVpjjMZog9E5QjlIx0U6DsrzEL/bRexprLUY9Cz82d4wrJHoiL1kg914nWG2hys8mv4KmUlYn5wm8SIe+vDHeOSjn2DxyHHcIEBdd05tboi+0ymGBi+PCmtgfONQpjY5lyYvc2b4dXrp9v7rQkpc1ydNbi/aBHK/jKUjPaRQxXm1+cyf5/67k0LclQo/D+GQ6AmZSXCkNxNpJRzpom2ORKGEg6eCfQHnu2X8Uhkn9HCDANnycJfLxJMxJtF4xuP8q99ke/c87dJBlv2jkMMk6dGJ1kl0hK9CSqpGOzhA2z+AI70bhpoEN1fSllUXb61SPGx4ahY9WUROIgurqVYa42kiPabf26Lf2aLf2y78ptKINJ6STCbE0zH6FgVW98+REDQX1jj+2DM8/NFPsPToCaR/3fduLWY887mb+cUVOykQSuIshjcM+VpjELdI/mmtZTrok0ZTXD/k8gvf5uzX/4Rqe4nHPv5JmqtrNziWv9XMxc0dmIubOW8Fr628/U4kTVOiKGI6nRJFEXEcI6XcD7l1HGd/3nVdSqUSSt3ZJyZNU774xS9y/vx5rly5clP+klqtxuLiIu12G9/32djYYGNjgzi+FtHRbrdZWVkB2N+vOI5xXZdqtbrf8jxnOBwyHA5J03R/uZWVFarVKv1+n16vR7fbZTQa8Qcbgs9t31/0nsTgomcp0ECKImLHUZKSA3UP6r6g4UtCkSLSCTYaYqMhPhnudd6gH8xOUrclhHRw8WjpEN9KLngZX6vknHc1nVGPatqjmfUpx138yR4qneIeeZTa4x9k8ZGnqJQCxnHO3iRhkmhcJXCVxFWSJw/UefJg/YZjsNZiU1P4bA0Tkssj8t0IayzdeJPUxjQWViiXm0hEESkTDdjZ22Kw0yHrjCilLi3TpiLrs9IMEZN8wCQbMMmHCMCVAa7wyFRGJEYYY8jjhDifEOsxsZ4yznv7lqd3OoWIK2xlUjqUwzq12iJu7pJNErTNMNYAlsykJCYiNwm5ybCY13WcrvApOw0qbp2K26DuLlL3Fqm5Cyh544OB8BWq5oGFvB/fuTCcI/CP1QkeaoIUxJsDLp1+jkFvmzSJSdIJg7jDINm9wb/KES5CSLJZyom//Pf+G9YeevS+j+tBMRc3d2Aubua8FTz//PP83u/9Hs1mk1ardcNUKbWfb+RqS9N0P5+HtRZjzH5uj6s5PK62q4JDKbWf98MYc0PTWmOMYTqd7guA4XDIYDBgNBoxnU7J8/tPhBeGIaVSiXK5vN9arRYHDx5kdXUVpRT/+B//432xUiqVyPOcNL1zBJlSijAMGd9DDpK7cvWO9hpt+VK+xJ/kR254TWBRmFmzOKLorGLrknL7UhH3ioMmEDkBOTmCifXIrltvCDxo7573LlX56SDk+/oGNzWgzX5uIj3N7q866mtIyJiUcsSiT3WxQcX62H46C0dPbwwMAHAEwckmwWMtwkcXMJ5h88wrbJ05g8hB4ZBPE/IsJY7GTEZ9SpU61WabjZ0NLna30cYQBAGyVMHPE7xeh+7mBll67yHOt0MqB+k4GJ1jXsfv4c1ASsXCyiECv8J0OCCejkjSiGqpRStcoUqLOBkzzvpM9ZBQVai5C1TcJkFYxvNCHM9HCYWwsvi+o0JsdeINtqLzXJm+Sn6bHFQCgRLOTZF1vlfmz/0f/yuOPf32ORXPxc0dmIubOW8FX/jCF/jDP/zDt3s37oqUcl+wBEFQPG3nOXmek2XZDfN3u1VIKVldXcVxHNrtNkePHqXdbhOGIUEQkOc53W6X3d1dOp0OcRyzurrKgQMHWF5exnEcxuMxm5ub7Ozs7O9bEAQEQUCWZYxGI4bDIdPemFLqUqdMRfs4E1s8vY41bipxrERjsJKZI7ogEZBai2sFjgHHgnQlouIUrepCWWFLClMSGN8ldlxSx8UqSWYM4yRmPJ0wnEzoTlI604xulNONNaNcMNGSYWrpR5rkDnmDqr6kXXJo+lBzDGbSJRxOOWJDJA5dcnrkZI6HFSG5dUlziI0gAsoImghCBDmWnCIfyjfQXO2iXeAxFE+heBTFMSRj4LJIOc+Ypkh4FCjjzqKfLBaDROIgCZwAJ3SxCy7bpsfp7nk6yfAG0SilYHFxiZVWhZVawPKhJ1lurODkApuZIt/RbDjEWsuZacKXeyOaZDwVKlrVFr+90+f0YMDFQZfnUoVRLqmFqb71+XuyEvJXDyzwAU+wJCxSJ1w+fYbdi+eZDgc0FxqcWMiothpEtgTKA+lA0IByG7dUwQtCHN+/ybqapyndK5cZdnaZ9PsIQBtNd/0yncsXGO7uoLNsJooU1hh0liGkpNJaoLa4RGN5lUqrTbneoNxsUqo3cX0f5TiFT4tTJM0c7u7Q396kv7VJf3uT3uaV4hgG/Tv+zh4UlVqLteOPEpTL+JUKzdUDtFYOsrB8AKlcknhCPJ1AFlHSXQI3QT3xQ2/Jvt2Oubi5A3NxM+etIEkSut3u/rDI9VMA3/dvaK7rImUxrn99y/N837JztWVZhtaaPM/RWqO1RkqJUtdCkq+2IAio1+vUajVqtRr1ep1qtUq5XCYMQ/xb3OBvxdUMt5PJZL9Np1PG4zE7OztcvnyZyeTOZQeuWmeuiqmr7VZ/W2v3hdXVY/W/McXZznAmFvnOKo10jVmUmjWGCOhh6WHoY3ERLCvJkhaUKHwyrka86UFSRAjdAxpDR4zYkj1GIsZiCfF4JD9AgsfvkPC7JPTuIdl/4MD7D9U51i6zUnEouaCAcrUK0iHXBikFrhLIr/0y48vP06PJhDKRrGDxbpGs1rLoJRwMUxbLAqfcRAZV/kb1vVxw67fYi9ucSmv4ULbBQVewg4fQGV9Ty0zFjRY1z6Qspn2qWUo/9xnnLhU9ZSEfEDopyrF8ZPRtfmbrd2nnI86c+kn6x36IQCn0tEt3uEc3zymVF/ihdp3ywjGorULYBK8C8QCyCGprt8zMu48x8OX/Fv7ov4NDH4ITPwDbL0AyRDeP0l1+P+2Tn0CUF/YXyYxFmRwpJcjCf2nU2WXr1dOkcUypVicMXLxoi+7uHjsbW3QvvEI5vkyjBJVWm7G7RDcOGHT7JJMxSRSRpRnGgjZFPrDCEmxY8COO1iYcX3VZPbSGOPZxOPbxIpR+uAG7L8Orn4fBJVA+FugOO2x7TcphmerPfoZWcItQ/LeIubi5A3NxM2fOg8daS7/f5/Lly6yvr7O1tUUURfs+PeYBVDb+VPoUh83i/t8TEoZiylBGjETEWMRMiBmLBK0Mgevjuz6ecnGVgyMV0lEIJZFKIh2Fh4OMbJHccKrxM0XJ+pSsj4NEWYmDQiJQFPP3fE4AvFnW49skjLweETgEJ+uoVoDuJaS7U3Sek5UhDjU0XFgsshi7vnfTcGWapOyd3qRnxwynI9YHKa8OBeeGcHFouDLW1HzFctVjsV7iO1eGdMZvTCV6ZFSIcEVRmrGoSSGoiJSaiKmJmKaIqIqE33vyw6w3F1kd7JErh065jlaKhfGAI3tbVJIpD03WOZBvEJqEajYm1CkCS0BKQEzqOPzegY/xx60nOV05ipH3kRfJWKQ1mDv4jVXyCZ/a+woPTy9wfHqZE9Fljk/XUWieP/QpLh3/szysUo7ZMTulNfJ4hHPhi5yJc/7EO8xIejw2OcdSusdL5eP8QetD7LotNoIlUulxbLrO+6JzXAnXuBCssCXKuDbnSLzJJ50hH19a5unlQzTNFKfzCpz5D/DK5yC/efDSWMFlu8iGbe+/poTBmUW0bdsmF+0yO7ZBSIovppx2Q77GKfayw/gioqH2WFR92rJHJdBEQZ2R16ITLrFVXaNbXigqlgNPn/8aT+2c5b/+z/9rSqX78117UMzFzR2Yi5s5c95aigKf6Q1i5+r0tfNXI5OEEDf4FSmlaMcVfBwiP2ckIqL8mkXrqnVL6zdePyEIAhqNBuVymSiKGI/HjMfjQqBZrtYcv77++CxQ+9qrOZqUfH8IR1mJN5NJORqNwUERWo8Qj6Bewiy4aKP3LVavbVBYv65vUkqyLCOOY5Lk9nXGHMfZL4RZq9WKmky1Gns65MJI0Ikt6/2YSaJJtcGRhZOyIwXGFhFmubYYW7TdUcJ6LyJ/rY/NbfDIaVZylkWMp3xyFRSp+9EQ5eTakOWGWd5cNAJtC/dmRxgcik5bCBgZnwkeVhZ5rJACGyj8EA6XM9qhpW9deloSZYJJLomWStjmLAovN4hEY6VAWCAziMxAycGUbvazEtbg2ZzkTciwfDvEIMUbTKlFQyp5jBYOIjO4gxijJagyvVwxCT1M3cOWnKL0eGpwLk9AgKm6+/5nZjHA1Ir8VrbmFRp0kBbnoeQUy98hvYSTZhy7eJn3rJ/l737kSbzplPLHPoa7vPwWnI1rzMXNHZiLmzlzvnvRWt8wfHd1/vphvOuH8/I8x3Ec6vX6frtVKLq19gahE8fxDdu4fltXo7uub0mSUCqVaDQaNBoNADqdDru7u3d1tr5fPM8jDENc12UymRBF9+ayXKlUaLVarK2tcfDgQQ4cOECj0bjtsGWuDZuDmEGUEWWaSZKT5oZxknNxb8r5zoSzO2PO7oxI78Fydb94QlOTMctixBHZZVFMbjtqFFuHda/JiAAVa0q1Flr5TDLDMIXNSBIbiW16mKaHKbnYsoMtO+DOOv1UI6YaW5kJgVkdL6RAxDl+f0wlHyMqHsZ1qSYJh7vb1CcjVJIzSRzOL6zS86vkMaQTi4mK5U3NLQRIw8NW7jHJ5iwr803M9um+MRYRa8Q0R0xzZD8tBFCkCxEIfGT3Bf7OV/4l0loO/vN/RvWTn7z/7bwB7qf/fuPhAHPmzHl7SafFWPnOi7DzUnHTC5sQNopp0ADHLxwrlVtMnQD8KvgVcEt39iW4HVEfBuvQOgZe+Y0dQxbD3lnovgpuGaor2Ooq1qlgkwQTx9g0xSbJ7O8Em87m0xSn3cY7ehSn2dz364FZbpt+H93r4x4+jHydlbCFEPs+QUtLS2/sWK/DWstoNGJ3d5fJZLIfgn+rBuyLsuub4zj7xxwEwU3h+lcdsa86Y1+Nmuv3+/stTdN94Xbp0qX9ZcvlMgcOHODAgQO4rntThN/Vedd1abVatFotvCAlaW0yKb9Kr/4KuwunmUwrmHgFky6CyBEyQcgURF5kIsaCMAiRF++LnKtpjq3xwHiEWY0wq9C0sKRhMSuqagNoNJmc+Z65CqMMqUiJbUxkI3JyytZlLa1TUiWYXLnxe3BhYAP2xmU6wzJD6zOaNeM5WEcgpkW5CIcc3zPY1BLj3lBgc4wEcqpiXAwD2RIj20JfHc7cALgWlSWAikhY3Ruy2huyKMZkvstms02nVGfkh2TKwQpBFASMyuVrv1Uh8PKM5WGX1mSIozWXWsvs1poIa2lMh2AzDIJD25d45uUXqU0yHrp8ntpwyAvHH2JUKnNwZ4uDO5sEo4j1yhJTxyeTDolymboBXb9GL6zRKzd5T9qj/J73oOp1VLX6xn8AbyJzy82cOe80dF449HXOwt4Z6JyGzhnoni/ed7yZUPEhm8xefwM/YyHBqxZiJ6iBX5tNqxDUobQApTaU28VnL/8pXPwybH1ntl0BzSPY1ilyd5U0bZHaJUweYtMEkyTYmRgp5qe45gquuIKvdnDdIY47vaW+sqbQatiiaKg1gjySZBNFPlVkE0UWK3QsySOF8Rqo1eMI5ZDv7JDv7GCzWUirEHiHD+M/dAr/1EOz6Sm8I0cQt0gu+L3CVatUv99nc3uTl869xMbGBlEvekOXlcEwdaZMnAmJl2ADiw0sqqRwSg5hJaQVtmgFLZqySUVUKJkSk+mE7rBLf9RnMpighxpGPPB6cwZDohISmRA7MVNnysgZMfUmBJ5LTZZYTMu0Jos09AKHVo5QW1umWq8RBAFWFsOtk2HCzpU9zm6P+XpX8u2kRPYaZ25lNIfGO5zob3BisMFRGXGoVaZ0oE2v3WI4i96ScYSMIsR4jB9FyFaV9RVDulhClOuksSAZa/JEEZZqHKvWKU8Sxs8/z+j0aeIsp9NoceLCeR5xFeHyMk5rAae9gLo6XVjAWVhANRpgDDbLipam1+bzHFmpohp1VL2OLJdvmfTvrWY+LHUH5uJmzuti0oG9V2GyA+MdmOzCdA/yGHQGyQimXYi6s9cTMDkYXfTQ1RVoHi1a61ghJqwu3jc5jDahe67YRv9i8dr9UGrD8mOw9FhhpYl6s9Yvmk5nLSumeVzs8xvsMQw+klv7emSRJN7z0JlASBDSonxD2MqQzs3b1akgHToIZXFCgxO8Pidkkwuijstkx2e64xF1PWRQxkynt/y8cF28o0fwjh7DO34c79hRhOsWFp/BAN3vYwZDVKOBe/gQ3uHDeIcO4SwvY7W+Zk1KEpx2+3U/0WZbW0y+/GXSi5cw0+l+s2mKNRq0Ka4XISl/30eo/+RP4jSb97UNay3f2P4GX9r4EtZalFQIBJdGlzjTO8PF4UW0LfyWpJE00gatpEUjbSCsIJMZucyLqcj3/3aNSyWrUMkq1PIalbyCNHfuDIUQBEFAHMd3TTMAxXDb8vLyfqLGlZUVFhcXi3xO0ZTznfOc7ZzlSvcKrnEpUcI3PjKXpFFa+HRNpsTTiCy7/5w2whjcLMMHfMfBi2Kc8QhnMsFLU9wsw00zjLac9VZItOLgaJcD412Wp10c+8ad6p3VVfzjx8Fa0vV1sitX4Lr8PKrdpv4TP07jJ38S/8SJN7y9dxpzcXMH5uJmzj2Rp3D5T+DV34ezvw9bz72121c+LJyA9iloP1S01gmQ6ppQyZNimGnxEajc/1DJ7n/3/2T6ta/gNEu4jRJO1cepeKiSQnoWRnuY/nYh5OIeMh+Bjok7ismOT7TrkccK5Wv8eo5fzwhXFGFb43ojhLj9rcWoCnn5YUzjMUz9JLZxAlFbQQQhMvARQYBwQNoI4TpFgVRriuMebhTDYf3LMLgM420Y72DH2zDtIl4j2KwTItqnsFZikgwTp+hpgp7ETNdzRhcVSd/hpqx/1yMsblkjyprIAZUJVC6Q+SzbvmeQrmVaNbzwSJNnD5T4Rk0TO4LDlTWO1o5wpP0YRxrHWSmtUPNrVEUJ9dzLTL/8FSZf+hLJmTM3bDKXMAotsQfNsSB4TXZ+4XlUf/RHCJ96D6pWJS57XKnmbCzA5mSTXtKjH/cZZ+PCOhI0+cL6FzjTu3E7r6Xm1Xh04VEeaT6CtprNySZXxlcYpkMCFeA7PoEKcKSDIx2UUFTcCk8tPsXTS0/zUOshHOEwGo3odrv7Q19Xh8IGgwGDweAm528PCJUi9P0iUWStRmNpieV2m4UsI+zskW+sI1wXZ2kJZ3ERp90GKQtrQ5KQXrpM8upZ0rOvkpw7R7a5WYRoWzszAYLNczQQlULG5Qrjyo0tCQOMUmilMEJgX2emcUdKDiwtcWh1lcNra6yurMBVB/DNLaLLl4mubCA2N3EvXsSZTIvjWl7GWV5CVWukly+RvnqO5NVX0Xt7t9yO8DzKH/sYjZ/6C1Q+/nGE++YVxs2yjMlkQrVavWu28jeDubi5A3NxM+eufPtfw2f/S0hfky23frgQEZVlqCwW1hI3KIaI3FIxbBO2oNSa+bHIInkYwPAK9C5A73wxzePifaGKaWWpEDOt40WrrsGbbAa+/Df+BuP/9Pv3v6CUeIcOFVaO48fwj58opseOFaZuKPyAtp6DK98CncyG0bzCN2ft6UKs3aLT0EazPd3GkQ6L4eIdc/DsTnd5Ye8FXth7gdPd0zSCBidrxzkpA071t6hf/gbZpT8ijbqkQpAKSIWgLxWveg6vuh6veg59qXgkFzxp2jzRl6x1Juw68Gpdcb6ScMFL2XQ0VxzF7qzDux5h7evuAKWxlDOLY4v8MkoKpBSMpGX8GqfQhtas5oaqMaQI4lwQWclUCGIlGJXubR98LfmkPkl7+Si2XsH6PmuVNU42T3KycZLlUhEBk56/QLaxjhmPMdMpzsoK4eOPX/uO7wNrLdnGBtOvfx0zGCAbDaZK0fnc58i//Ed4aYp6AOkC7hVRKuEfP45/4jje8RPF9OhRnKUlZLV6w3V31fE8SRLGly7Rf/47TPc65PUGea1KViqRGnODA/n29jbT21gKb4fv+/v5qCqVyk3ZyVWWMdnaYrK7S6w1ieeRCEEuxH5W86uZzaWUtFotFhYWaLfb+9PwNT5nV48zjuMbMpkPh0PG4/ENea3G4/G+8/vf/Jt/k+Z9Wg0fBHNxcwfm4mbOXbnwR/AvfwzKi3DiB4t2/Aeg+taGPb7ZxC++SHrpMrrfQ/d65N1iqns99GBQDMOsruCsrOCurM7mV3EPHkB6DyYsNs5j/uGf/kM2xhtsjDfYHG+Sz6pm1/06JxtFh7tUWmIv2mM32mVnusOV8RV2o90Hsg+vxTOW9PVEm8w4rh0+MIUPdse0ozHrJcl6SXExcLjoOuwpxUBKonsQr8JaAmvv6bMAzcxwaKxZHRiqI0F5LPAmMPAkvYpgrWv5/uctlesqF4hSCe/AAVR7AafZwmYZ029+87aWAvfAAbwjR4ohukOH8Y4eQbgu6fo6+fYOzkIL9+BBnMVFzHjM8Pc+x/iLXyTf2rr1TktJ7cd+DHd1lbzT2feVyra3McMhAM7SEt7hw7iHDmF1Tr6zS767S97pFMfgOAjXxV1dxT95Ev/kCbwTJ/EOHbzmTyWKHDwohbN4Z+H8RrHW0ul0uHjx4n4bzo5FSnlD3ba7hfG/01BK8df+2l9jbW3tLd/2XNzcgbm4mXNXdFZEHi0/+aZbT77XsdbywX/1QWJ9rbd1pIOxZlaU8PZIITleP85jC4/xSOsRBsmAs/2znOmd4fLo8g2FC5VQeMrDlS4Vt8KxxjFO1E9wsnGSmgp4/tx/4NnOc3wn2SPFoBAcU2UeKq9xqvkQBxefYK39OGu1g9S9OpnJ9hsUuW6kkMX6vcq148sy4tOnib/9LdLn/ghz6Zv4lYTSkRKmVWLcXGCkXHLXxygfHVQxpRaVyhqtxlGqjaMoJ2CUDLgyvsLmdItpNsFLxrh75wg7Zwl3XiKc9ljUmvptrB9WKGzQhsoaMccYXvAYf/PVa8M2t0B4Ht7x46hKBRGGpBcvkl0XSXXfOA7hE0/grq2i+33yfp/gkUdZ+Os/i3/s2C0XueonJd+mpHEPCmstWZbt5yd6LXEc3xDNNplMbkozkGUZnufdkNX7asj/1ezmVzOTZ1lGt9ul0+mwt7dHp9NhMBjccR/DMLwhi3mlUqFSqdxQR65SqdxzVvM3g7m4uQNzcTNnzjuLf/XSv6LsljlYOcjB6kEWw0Vym3N+cJ4zvTOc7Z9lL9qjHbZZKi3tt5ONk5TcW3d6cR6T6ARPeXjSQ91jJttUp1wZX2G1soqvbs53847E2sIvau/VIpT+6rR7HkZbxXu3chxfeRJ79JPkpZMk+RJ6nKN7PWyeE77nPQRPPXWThU4PBiSnT5Neukx66SLZ5YukFy5jtcY9cAB3ZZl8t0O2uVlYVbSm8slPUv3Upyg98/7XHYo/542TZRlZds1x6/qu/+oQ2Dudubi5A3NxM2fOnO8pdFY4XY+2Cj+oF38Xzn+piNa7nvbDxdBrEXNfRGZJp/ArcwJww8Khe7xTrGu8Ddm08BtzgiJKzy1B49C1yMDm0cI3zSuDVypqNfm1wmdtzpz7ZC5u7sBc3MyZM+d7nsleUbfo4leKqMDO6bd2++2H4bEfh0d/HFaefH1JJOd8zzEXN3dgLm7mzJkz5zVM9mD9a0WEoBDXovhMXkT2ZdEswk8V1p3KSjENGtfyJuVJkTupf3EWGThrUa+InksnhaXntfmVmscKoXPs+4tIulKrsBrtvAgXvwqXvlJE3QlZWH/cmRXILUH9IBz8ABx8BhpHQAjO9s7y33/7v+cb29+g4lZQUnG4ephD1YOY6R4XOy8yjPvUkbwHjx/SLkeyjG+Wyuy2jlJaepx11+Obu99ikA5YLa9Sckq8sPcCm5NNjtaOcqx+jMAJKDklTjROsFJe4ZXuK5zunWYv2iPSER9e/TB/7tifY7Wy+nZ8o9+VzMXNHZiLmzlz5sx5G4kHcPo/MHzht/nc1lf5TMnnFc+lYiwnsgzlBFxBM5RwMs1oa01fSjpKMZWCJa15Ok4wCNZdh6kQfDPwaVlA+WyQ3XUXXounLal6c6xHS6UlTtRP0PAb1PwaR2pHOF4/zsHqQdbKa7jqzctL893GvLbUnDlz5sx5ZxLU4amf5ndUxP89fWH/5VhCx7nq+F1M/zS82RF83XX5ZhDc9PoGABmOtXx8EPOjL+aw5xDnissVyU61iHxc27NUI+jU4PmjgmdPCFIlaI4sBzuWxBVUI8sjly0Lo+Jzk0BwdNuy3LdcWRDs1CFXgnEIFxcFezU41LEc34SFocWUfL72gSrPlXvsTHfYme7c8lS4VvI+fYAP1Z6g3FpkWhJcSbaJsyk/tvIRPnrok4jKYuHPdJ/sRXucH5ynGTQ5XDuMEgpjDY506EQdXu2/CkCoAi4MzhOblNAJqbgVDlQPUHWrtMM2g3TAf7zwH3mi/QRPLT513/vxdjG33MyZM2fOnLcUPRqx8eLX+C9O/wN+cHyYZy45DHfWOV+LcasBB+oHqR17iotNzcS3NBqrrNQPUHbLvNJ5iTObz6NHI9aSEtLAE2KFeHwFs32B1lcv4529ddizCEOcdruorbSwgPQ9Riqn72UczGs4taIgpJIxIt7E9HfR3T30YIAddxH5rPK4tCjXogKF9AyCFJ1KsrHD8FJIHhWibOrB5UXYbAmmPgxLgvUFCoHUgNS9s7Xo8EBzdKR5YmD5Cz2P8oElvJMncQ4/jGgeAScgjlO+cu6bvDy6QFLK6OQdvpX3uWSvVZsvSw8hFZFO8ZXPNL+3BIOOUBgsxhp+4sRP8Pc/9vfvabk3i3fNsNQ/+Af/gN/+7d/m5ZdfJgxDvu/7vo9/9I/+EQ8//PBtl/n85z/PD/zAD9z0+ksvvcQjjzxy123Oxc2cOXPmvHVYa8kuXWL67LNE33yW6NlnSc6e3S+HcK/IUglZqRQh5nfLZuw4VD72Mao/8iN4hw4WgmZxEVl+A9XrrS3C7M/9IZz/Apz/YjHEdj1uGSscppuCwTmHdCj2i77uTymSdQtXs7Fg+cqa4pW6g84lfgJLfZj68IdPCWL/mvhZ3bM8cdFy6oplZWzIGpotX/HZpxyuLNwskoS1rOWavpJMXpOvS1jL4TzHsZaRlBzIc5raMJWCoZRsOA5TKclmjt5PZpqfNGV+6un/PXzgZ1//OXyDvGuGpb7whS/w8z//83zgAx8gz3P+9t/+23zqU5/ixRdfpHyXi/CVV1654eAWF+ehhXPmzHlrscaQb26ix9dKdQjPw11Zed05Xay1ZOvrpBcuIitlVK1WFOSs1x/Ubt/TPuSbm0UW6wsXUM1mkcdmbQ13ZQVxm5wout8nPn2a5MwZktNnSGbzZjy+6bPO6mpRsPTwEbwjR/AOH8IaQ3rxIumFC0XSwPUN9N4eNsv2C4kCCN+f5dVZAfdaNyYcl/JHPkLtx/4sTqv1YE+KENA+WbQP/vXC6bl7rqjvFtSLEHepEEB51u7GYeAjZlYzTSr0cEx6+TLpxYv8je4mfxy/zJV0m98svcTmQsbmguB/fh8Uw3bXfHVqkeU964Jqz1BOLMe34JHLluZCk/BkiyutHo7YZsnpEQewkmtKzeNw8ofh1J8p6tN1zxVRc7svw+4r2O55tqMdhMlZvloH7NHhgz2nbyLvqGGp3d1dlpaW+MIXvsAnPvGJW37mquWm1+vReB01TuaWmzlz5rweTJKQvPQS0fPfIX7hBZKzZ0nOncPepoaQajZxlpdR9TqqVkPWa6hqDVWvIUsl8s4e+fY2YBGlEjIsoXs9pn/yJ0W15+sRgtL730/1z/4o1R/+YVSlyIJsrS3KEGxtkW1tY5MYlEI4LgjId3bJrmyQbVwh39lBKIUIgllx0hDVbOAstHHaC8hyhfT8OeIXXyR+8SV0v3/rEyEEzuIi7toashSS9/uY/qx6+h0qrwePP074vvcRPv1eSk8/XRS9vAestZjJBL23hx6OcJaXcNptxPdQ9vBBMuArV77CS3sv8ez2N+mOdgi1ZClc5IkD7+M/e/pnqXpV0vUNxn/wB4z+8A+Yfu3rN1QMv4pqVAvxXakjwhAZBIgwQPqzaRCiGg2c9kJxDVdcHC9DqSli8WRRA+9t4l0zLPVazp49y6lTp3j++ed54oknbvmZq+Lm6NGjxHHMY489xt/5O3/nlkNVAEmS3FC3YzgccujQobm4mTNnzj7JmTMMf+9zAKhWC9VsIMtlsosXiV96mfiVV4qq3bfoLHDdwqoyGxkwk+ltBc894zj4x45iohg9GmHukjr/TcFxijpNx4+jBwOyK1fIrlzB3qUOknvgAP5DD+GfOlVMHzqFf/Toba09c94c9GDA+MtfJn7hxf1K6dnGxutfoRA8/Ow3kbdw5n6reFeKG2stP/ETP0Gv1+NLX/rSbT/3yiuv8MUvfpH3v//9JEnCr/3ar/HP//k/5/Of//wtrT2/+Iu/yC/90i/d9Ppc3MyZ891B/Mpphr/371H1BqrRQDXq1+brNWS5jLhFPRyTpoz+w3+k9z/+a6Kvf+OetqVaLcInnyR48kn8hx/CP3ES7/Cha8UZmVkaRqOiBMHWFno4Qg8HmOHw2vx0itNawFleRii1P+QiPI/SM89Qet/TN/iHZFeuMPwP/5Hh7/0e8XPP3bBPolTCXVkpnsbLJWyusXkOWuMstnHW1vaHk7AWE8XYJMZMp0XB1M4e+d4eZjjAPXyY4LHHCB59DP+hU0j/xigday262y2EzsYGNk1n57leTBfaqMob8GuZ86ZiJhOSc+fJO7vYJCmuhTjCRDEmjrBxUlwX/T75Xgc9uzZ0r4cMQx7+5r39Tt4s3pXi5ud//uf57Gc/y5e//GUOHjx4X8v++T//5xFC8JnPfOam9+aWmzlzvrvp/86/YfMXfuHOHxICWSohSmHhmBqWyLe30b1e8b5SVH7gkziLi+heH93toodD3IMHCB5+hODRR/AfeRT3wNrbVjTwKiZNC4fa2a1bBMHbvk9zvruxWqOHQ5xm823dj3eNQ/FVPv3pT/OZz3yGL37xi/ctbAA+/OEP8+u//uu3fM/3fXz/XVIAb86cOfeNd/QIzb/yV9D9ftEGg/35fUfWmd8GkwnXV1Rylpdp/PRfpPFTP4W7vPy27P/98tpilnPmvNkIpd52YXO/vK3ixlrLpz/9aX7nd36Hz3/+8xy7Tdn7u/Hss8+yujpPcT1nzvcipaefpvT007d8z2pdmNynE2wU7Q//mGmEcF1Kz7z/hiGlOXPmfHfwtv6qf/7nf57f+I3f4Hd/93epVqtsbW0BUK/XCWdhlL/wC7/AxsYGv/qrvwrAP/kn/4SjR4/y+OOPk6Ypv/7rv85v/dZv8Vu/9Vtv23HMmTPnnYlQClUpz/1A5sz5HuNtFTf/7J/9MwA++clP3vD6r/zKr/AzP/MzAGxubnLp0qX999I05W/9rb/FxsYGYRjy+OOP89nPfpYf+7Efe6t2e86cOXPmzPmuYTKZcPnyZba2tuh2uwghGA6HdLtdqtUqS0tL/PiP//jbvZv3xTvGofitYp7nZs6cOXPmfDeQ5zn9fp8kSZBSYq2l1+uxs7PDkSNHOHbsGEIIsizj4sWL+8IlCAIcx2FnZ4czZ86wvr5+x+0sLCzw6U9/+i06qtvzrnMonjNnzjsTayxmnKFHKWaS4a6WUdW5Q+ucOQ+MZIzpXKRz9hU6vT0a9TpLC22EEhhlGYz67O7sEAQ+TlhjY6i51E3Y3O3SuxrtdxtarRZSCMb9DugEhxyFQc6aRtGnBgja7TYHDhyg3W4jhCAMQ9rtNqPR6K05Dw+YubiZM2fODaQbY3q/fQY9TDHjFK637QrwDtcIH18gfGwBp/36Sgy8HZhpRnymhzWgyi6q5iGrHrLkPLBQahPlpFfGYCxOK0A1fIR66zLpWmuxmcFMc2SgkMH8Fv/AySLs1ovYK9+GndPQPY8YXgQENlyC+jKisYrwq0VZhTyGPIU8gnSKzaYkgy7x3mXCbA/fTpHA0qxdjwLas3aVQ8CHgQifERXGVIhkDSMkoYgpiYSyTFHJAL8b494QH3gzuVuFtadxjnwIWi2QWyBV0YbnIYuKY/jKH8KTfxGqKw/uXL6JzK/8OXPm3IiAbGN8w9+y4iF9Rd6JSC8OSS8OGfz784Uw8BTCV0i/qISsxxlmlIIUOO0QZyHAWQhxWgGy5CJDp1gudIplpEBIAUqABT1MyPdi9F5M3ouRgVOsZ7FYh3DuLBZsbtCjFD1KsVFO3kuIXtgmeXUA5hbLKoFwJUJJhBLFsZTdYl99hfAkwlWzzwhwJEIKbG6wqcGmGj1Oya5MyDvRTedSNfxC6DSD4lw0A1QrQFU8ZOggfFUc/wyT5Ohhih4U4lKPM8xk1uIcqy1oi9UGm1swFptozDRDT3PIrxWVVDUPZ7mEu1zGXS4VYi50CuETOojAKY5rJu6ssdg4x0Szdt28jfT+awhm39nsnCkBUhT7oi3WFPuIsQhX4h+v4x2rIz11nxcj++sqjnd2zNpgYl1YFEcpepxiRhl6kqEaPv7hGt6RKqpyZyujSTVmmBbne5xiphlmkmMmGQwv4PS/gow3ENkeMt9D6R2U3UAIw63ksOBFuPMIDwIIZu0qMT5TQiQKbQ1WgEUUzxVW4OBgsTgkVBijhCYkISRhiT24Sx3R/XOJBOEWwkU4oCOcbAQXv1i0u6AXnkY9PBc3c+bMeZdhrWUQKpKfPEGp4RM2Q8K6jzfrAPNBQvziHpPvdBif65NNM7JpSgLkQBNB+brbfrYxvlEo3Q3BjZaiW7yv6j5OO0RVPfQkQw+SokOeCQ30zSsI5ZdZc/8f5M4JdHCKzBwjiQ+TRS3QLla7GDyKZ2ULu5aix7AIUqSYIJkgxRjBGEmExccQYm0ZQxljSwjKyGYd4Srybgy5QfcSdC8BblNCQbAvcsw0xyZ3ftK+J2ZCQ8867uRM//afVQIZqEKUJPrO5/91MvrCOiiBf6xOcKqBf7IJAnQvJu8mxbQXkw8ThvEYJxOoVLCVd5maBGyAsSWWcGggELeUFgAZmi7nKKMIOdEqER6p466UMVGOHib75yQbxGwkOa+iSYBlOizJs6zI79CWzxLKK7fehIDUVhnYA4xYIWUFJY+ghMLQYaLXQXSBKSmCXChyFDkOKS4ZDpn1qKlVbPUAWWOF4+95P8efPIXrumRZxnA4xFEKHxeVgt6JyLYmZJsT+tbiLuQ4lTFiug29TWx/g7w7RUcljK1iqMymZaz1sU6I1Q7Y13b5Ga64iCdP44nTKNGluO41QmisdbF4WFwsPkHQeEBXxJvP3KF4zpzvYuJM8//7xjolT1HynNlUEXoK35Fc7ka8ujvm7M6s7Y7pT7Ob1iME+I5ECUGqDdktBAQU2uRYI+SptTpPLVd4LPBZSAxqkOIMU+JpxvYkZSfK2E5zdq1mBGjs7JYKvhAcK/mcbJY4tVSmoQV5JyLvRPfe8SuBumqlKLvU5K/hX/ofXu9pvD+kA34Vu3ASu/ZR8sYHydwn0QNL3i06cd1NimGyTLOB4SKGHpY6ghaCBdehXfNp1PziOMouquIhAoVwCmuJlYLIWiJriIDUkWhPYnxJLgVplBPvxaTdmKQXkQ4S0liTZ5o81ZBpjlrFcST+a8SCcGVhWbvaAgcRKPJAEbuCaW6Y5pppahhlmmGaM8g0I60ZGssg1wy1ITKGNDMkUVZcN0A2U09lBCUsa6LLYbnBIXmBZblOW3RYoIdLzogyIyqMKNOzVV6xh7ho1ygJy4KYcFxscUxssMZlGnaPCoWQNlZw1q5x3h5iyCqxbRGQ4IsUx8ZYMUESEYiYBiNOiCvUxOSGc6CRXOIAmywyFjUm1mdEmV0WGFGG2wqsm3GEouqXadWbHD12HHXoGN/Zy/jT8z2+frFLmhsONkMONkscmk0PNkMOtUqs1APc2xQJ9RxJeJ01LO/G5HsRNiusXKrq4SwEyKqHTTTp5RHJhSH57rSwshkK65ojCutkoFA1H1X3UFVvJnhzTKKxsabyfWt3tZy+mbwryy+8VczFzZzvJbaHMR/6v/3+fS/nOZI0v0dbN+ApiaME0/QBWB1eQ8V3WKr5rNQClkoeTSGoaKhaWKmHfPj4Ao1mUAyPeRLpKUT4Gj8ao2HvVdh6jnjjOeLL38LZeYEg6+HcxScBILYuE1klcSpor4b1qrg2wdcTvHyEm4/xsjHiNuMDRnpMa8eJRcBIu/Qyl14qGaWWzCoyHPpU2LM1dm2dIWUMAiUl1dBFlRp0aHElqzLMYJrkTDPNg7h7KyE40Srx2HKFWsljnBuGSc4wzhjFOcMoYxhnTFONNhaBocGYBTFkgRGhSHjBHGGXaxlsPTKWRI8l+iyKAYtiNr3u7wNijwYjXHF/14xBEONTIr7l+7mVOOLer93r19uhySW7ykuc4AV7kly4VERavG/hvGkhAQdNgoO1gkBktGSExKKFQ081GLsNYlkikx5aOBgUCIEQcLkbEWUP7ndSDRxW6wHLtYCVWlDM1wMWyh710KNRcosWegRuIUx2Rgmv7o45tzvhfGfCud0xF7tTjLG4ShbNkXhK4CqJ70g8R+I7xUOR70o8pfBdyV98/0GOL1Ye2PHcibm4uQNzcTPne4ndUcLf/p3niTLNNNVMknx/Ps40q/WAk0sVTi5WOLFU4eRShePtCqGnsNaSakOSG5LMkORF5+Y5Ek8VN7ur81eFxO4o4fmNPt++POC59T7PbwwZzp7ar9Iqe7Mbsc9KPaBZ8nCUxJECJQXDKOPszpgzO2Mu96Z37cCVFHzgaJMfemSZR1aryFknYgzsjGI2BzGbg4iLe1PObI/ZGt7YKXrS8uHDZdaqilBZXEeS5oKNYcx6L+biIGdq3Hs425YSCVWm1MWEp+Q5vk++wEfld1gW/fv85m6NsYI9qvRslR5V+raCR0ZbjmmJERLLH6v380X3o7ziPoZ1fFxVnFdXSkrELNOhafuYPOVKb0wcJ4xsiQt2mR0aWCSL9Ph+9RyfkM/xhDhPKFI8MnwyQhKUuPlL2XOWmLgtWvkOlax7X8cVi4Ces8JucIRu9SF06wTlsMyqN6Vlu5SSXczuGdh6HjctzqVBsuUd4VVxlEvqKJG/yF5vRIRPhSlrbHFIdjjg9AnMiFgExNYnwcP6VVRQQ3hlMlVCrjzO8Q//L6i3V0hyzd44ZXeUsDtKuNLps7O3RzdV7MSKnVHMzjBhd5ygzevrPhsll2eOtPjgsSYfPLZALXDY6Edc7kas96Zc7s2m3YjO+M5V2O8Hb2Z9fZDi6lf/6gf5xEOLD2x9d2Iubu7AXNzMmfPWY0whlIrhrXt3Ko0zzZV+xNYwZnsYsz1M6E1TBtOM/jTjzM6IV3cnd1/Ra1ipBTx9uMGPPL7CDzy8RL10e/GSa8PmIOZ8Z8LFvQnnO1OGcUY+G55LtSHNC/GX5IY4MySZxliLlAIFHGGDFbtL29ccrsBa2bJcErTLkopjETqDqAvjHZjsQtzHGEtuLFprRNzDjzsIe5+dkvLAr4JXgWQI0Z1DhzPpE3stqvHm3dcdNKC8CEJC5zQ3Oes4AVSWoLJctPJiEWkze21gAlKnzsKRR5H+PWaQthZGm0VbfBS80g1v93o9NjY28H2fMAxZXl7Gde9FmN4/xtjZ962Jc02czeYzTZqb/bNxtYe1WLDQrvqcXKwg5b0Na2ljuV03Pc00O8NCwG9dbbPfSm+a0Z+mDKLit5JfJ8SUFBxqhhxfrHC8XebYYpljC2V8V5LkxXWd5Wb/2r72kKOL+czsT/83Hz48t9y8E5iLmzlzvru4uDfhD17e4Q9f2WVnGGPtrCMBFqs+K7WQ1XrAwWbIqeUKJ5eq1MM3p8N7UzEapnsw2iqE0HQPpl1wfCi1odyGeAAv/ht46d9B3L/1evx6ITAcfxby6xSip3cR9sWTgLX3wskfhqMfK4SMExTLuCUotUBddw6TEWx8A5Ix1A9C4zCEzcJZa87bjrWWSaoZRBlZblhrhHhvo+/M62Uubu7AXNzMmTPnux5jIB0VouNq8ypQPwBB/dbL6AwGl2GwAUuPFmJpzpx3EPMMxXPmzJnzgLDWMpmcod//GsPR80jp0Wx8iFrtSXx/GSn9t3sXb0bKQsTcTsjcCuVC63jR5sx5lzMXN3PmzJlzC7JsyLlz/y2dvT8kjm/MzLax8a/25x2nilJlXLdFqXSUMDyC7y3iuHWwGqXKtFofx3Fu7VeSph3G41ewViOEg5AuUiiEcEBIBJKrYcfWZhibYU2OUiGOU8d16zhOFSHuP0HedwPGZEwmZ0nTHcqVhwn8d0eSuXcDxcCOeVdeW3NxM2fOnDm3QKmQre1/Q56PkNKjUf8Atfp70XpKr/fHTKevYkxKno/I8xFJssV4/OJt1lVicfFTVCuP4flLxNE6w+G3GY6eJ0m23vC+CuFQrz3NwsInCMMjuG4Dx6lhbUaadkjSDmm6R5buoVSI7y/j+yv4wSpBcADPXbhjCQprDWm6h5T+TEjd+rPWWpJkk9HoRbKsj9YTtJ6iTUyj/j5arY8jxBvz9UiSXXq9r9Lv/ynD0XeYTF7BmHT/fc9bolZ7anZcLVyvhevUcd0GyqkghEIgSNMuSbJJmu6R50OMSVEqRKkSUoUoGSClT5LuMp2eZzx+mTTdpVZ7ilrtvfj+Mq7bIEt7bG79FtbkHDr0v6Pd/uRdrXnG5MV+vEk+SZPJOXZ3P8fe3heJky1cp4bj1nDdJkFwgCA4QBgcJAjWcL2FYqGZh0qSbNIffINB/xv0B18nTXeR0kepMkqVcZwyhw7+b1lb++k3Zd8fFHOfmzlz5sy5DRtX/kc8r02r+RGUujEyx1pLlvXI8wF5PiZNd5lMzxHHGyTJDjofIYRiGl0kii7eYSuCMDyCUqXCMmMysAZr8yK1obWzFIeFiJHSRQgHrafk+RCtp2/4OKX08P21/Q7bdYrhrDjeIIrXieNNrE1n++DieQt47gKu18LzFnCcKtPJeUbjF8iy20dkBcEhDhz4yyy2fwitp2TZgCzrkaQ7pMkOSbKNEArHreM6DZRTKo5ZuEyjC3S7f8Rkcvqm9SpVwfeXiaIL2PuNKHsTkDLEcaqE4SFarY9TCo+QJFvF/k/PkiRbCOHiuk0a9ffTbH0fAHnWnwnRDq7boFJ+mFL5OK7TwHXrSOkhhAuIQrQmm6RpBymDfQvexpX/iY2N3+CeazK8Dk6e/AWOHP7ZN239t2PuUHwH5uJmzpw5byXWWgbDb9LZ/X3ieIM42cL3lwsLQPVJqtXHcZzXH0prTEocX6Hb/SN6/T8mTTtkWZ88HyKEg+e1Z20Bz22hdUSSbBMnWyTJJkmyzb3VXLhbbYzZp4RDuXwK31+aPe2XwBp2O/8zef5gKkxXK4/TbH6YWv29VCuPE4aHEEKidcRo9AKj0Qsk6S5ZukeW9cjyAXk2IM9H+4LRcesEwSqet4jj1JDSQ+sIracYHaFNjDEJrtukFB6lXHkIz11gMPg6k8mrJOkOeT7AWsPi4o9gbcb6+q8+sGN8o7RaH2ex/WeoVB6eWReHpOkecXKFOFonjq8Qxevk+YBr2ZYFjlOlXn8fjfr7qTeeoVw6htYJWo/RekKup5TCI4Thobf8mObi5g7Mxc2cOd8ddDod0jSlWq1SLpeRUhLHMb1ej263S5qmNBoNGo0GtVoNpd59fgNvBcakhdiJrxQddjYgy/pYLGGwNhvGOIjvL2OtJsu6pLNhrjTbmwmIAWF4iGr1cSqVh285LKN1xPb2Z9m48htMJmdxnNrM2lDH95eKoTJvCYslz/pk+QCtp1iTY2yO5zZptr6PZuPDeF7rbThTd8daQ56PyfM+WT5kOHyOweAbxPEmSpVYaH2MWu09BMFBrM32Relg+CxKBjhuvRCibqvwxZq8QhRdJs+HZNlw33oGV61VK/j+IsYkZFmfLOsThoc4ceK/otX8yNt4Jt4c5uLmDszFzZw53x185jOf4Zvf/CYAUko8zyOOb52SXwjBwsICy8vL+21lZYVarfam+T28WSRJguM4c7H2PYi1thiutAal3oFRem8y81DwOXPmfNfjui6VSoXxeIwxZl/YlMtlms0mnufR7/cZDAZorel0OnQ6HV544YX9dZRKJdbW1jh06BAHDx5kdXWVIAiQtylU+FaR5zmDwYDd3V22t7fZ2dmh2+3S6/WI4xgpJe12m8XFRVqtFlJKjDGUy2VOnDhBu92+QbSlaYrjOLc8LmMK34y3+5jn3B0hxMznZs7dmFtu5syZ865Ga814PCZJEur1Or5/4xOtMYbRaMTOzg7b29v7bXd395Zp7YUQhGFIqVSiWq1Sq9Wo1+tUKhUmkwm9Xo//f3t3HhxHeeYP/Nvn9Nwzkka3bNmOb3PYhjVxATbgJVCbcoLDYULFS3aXJbWBhRCSQBVbtrNV2Fu1Wym2kpAqlngDG+Ks7ZjUBkJiKrFjLgP2z2BswLJsSdYxkiXNPT19vr8/Who01mHJOkc8n/LUSDOv3n770dGPn/ft7mQyiYqKCixfvhy1tbXQNA0XLlyAqqooLy9HKBTKJxe2bSOZTMK2bYTD4YKkw7IsdHV1oa2tDR0dHYhGo4jH48hkxn5LiYFCoRDq6uqQSqXQ3d2NdDoNl8uF6upq1NTUwOPxFMTBsiyIoghJkhAIBBCJRFBeXo7y8nKEw2HYtg3DMMBxHCorKyftlgaEjISmpUZAyQ0hBAAMw0BnZyfa2tpw/vx5nD9/HolEYsz9SJIEwzAKXuu/r5Gmaeju7s6/rygKamtrUVZWhq6uLrS2tkLX9aG6hSiKBVNppaWlCIfDCAaDyOVyuHDhArq6uhCPxwE4SVl3dzeam5thWZN3xpAgCKipqUF1dTVKS0tRWlqKsrIy+ntKJh0lNyOg5IYQMhzTNJHNZvOPVCqFRCKBZDKJdDoNj8eDcDgMr9eLpqYmfPLJJ/nkpL9q1N3dnZ/q6cfzzp3Th0o6XC5XPlmoqqpCSUkJAoEAPB7PZa0H0nUd586dQzQaRSgUQllZGcLhMJLJJNra2tDa2gpN01BeXp5PnGRZhmma0HUdsVgMXV1d+eQpkUhAFEWIoghd14etKvn9ftTW1qKmpgaMMWSzWWQyGWiaBsuyYFkWfD4fQqEQwuEwwuEwIpEIfL6puekiKX6U3IyAkhtCyEQxDAO9vb0IhUL56TDTNPNTYIqiIBKJIBwOgzGWrxR1d3cjEolgzpw5iEQiRbPehTGG3t5etLS0oKurCz09Pejp6UFvb++wd66+lP41Uv1TgV6vF1VVVZgzZw6Cwc9uH9HZ2Qmfzwevd5R3ECezDiU3I6DkhhBCJpau62hvb0drays6OjogiiK8Xi+8Xi8URYEgCOB5HqlUCrFYDPF4HL29vejt7R2xX5/Pl5+Ka25uRjqdRmlpKXw+HyRJQnl5OQzDgCiK+fYrVqyAz+eDaZqQZXlQn7ZtF00ySQpRcjMCSm4IIWRm6F+InUqlkM1moaoqkskkzp8/j2g0etnVoH6KoqCiogKBQACWZaGzsxM9PT1YsGABrrjiCsyfPx9ut7voF0iPJWHL5XJIJBIwDAOJRAKSJKGmpqYoKmKU3IyAkhtCCJn5+hOfRCKRfySTScRiMRiGgXQ6DV3XwRgDz/MQBGHQwu7REkURoVAI5eXlAJypRU3T8qfXl5SUQBAEpFIpuN1ueL3efBVJVdX8mqRTp05B13XU1tbi6quv7rujfAaiKKK8vBzNzc1oamoCz/NIJpNoaWnJX7eovr4eixcvxtKlSyEIAjKZDILBIBhjSCaTiMfjyOVy0DQtvzaqvb0dnZ2dUFUVHo8HJSUlWLFiBZYtW4bW1lY0NjaiqakJmUwGHMfBtm1omjZo//vPEOQ4DmVlZZBlGYlEAtXV1Vi4cCGCwSBqamqm/ZpQlNyMgJIbQgiZPQZWLQzDwLlz59DW1ob29vZ88lBMOI7LV6wGfjydeJ7Hxo0bUV1djUgkMm1JDiU3I6DkhhBCPh8YY+ju7kZHRwc4joMgCBAEAaIowu12gzGGs2fPorm5GW1tbVBVFS6XC4qiQJIk8DwPVVWRy+Uuuyo02crKylBZWQld1wsuDQA4yZGiKPlblAw84y2ZTEKSJJSWlkKSpPyFMAdeuuBisizjiSeemLY1S3SFYkIIIZ97HMchEokgEokM26ampgY33HBD/vT14U7B71+jwnFc/uA+cIG0YRj5e5lZloV4PA7LsiDLMmRZhqqq6OnpQXd3N7LZLAKBAAKBQMFaF9u2oes6fD4f/H4/MplMvnLTn2CJogiPx4NgMIg5c+YMOsgbhoFYLIaSkpL8Quux6J8Gy+VyME0znxy2t7fPiKt3jxZVbgghhBAy443l+F0cKRghhBBCyChRckMIIYSQWYWSG0IIIYTMKpTcEEIIIWRWoeSGEEIIIbPKtCY3O3bswLXXXgu/34/y8nJ89atfxaeffjrqr3/zzTchiiKuvvrqyRskIYQQQorKtCY3hw4dwre//W288847OHDgAEzTxK233opMJnPJr00kEtiyZQtuueWWKRgpIYQQQorFjLrOzYULF1BeXo5Dhw7hxhtvHLHt5s2bsXDhQgiCgJdffhnHjx8f1TboOjeEEEJI8Sna69wkEgkAQElJyYjtdu3ahcbGRmzdunUqhkUImUGS3SqaT/ag+WQPoucSM+LeO4SQmWXG3H6BMYbHHnsM119/PVasWDFsu4aGBjzxxBM4fPjwqC4trWlawY3TksnkhIyXEDI9zn3QjTf2NOQ/r1oQxFUb6uD2yxAlHoLIg+M5uNwivCHXNI60uDCboac9DVEWEIy4p/0O0MXINCzEOrLo7cjA0CyAMTDmHN+Y7TzLioiSGi9Ka3yQZGF829MtxDqziPVtT1ZESIoA2S3C5RadZ48IySV87r6fMya5eeihh/Dhhx/ijTfeGLaNZVn4+te/ju3bt2PRokWj6nfHjh3Yvn37RA2TEDLN3H4JZXU+AEA8mkVHYwIdjYkh29ZfUYrVt9fDX6pAkgWIMg9emFEF6ymlpnWkezVoqgldNaHnTGhZE53nkjj/cS9yaeeGid6QCzWLQyifE0BZrQ+ltT4oXumS/WuqiXRvDum4BpdbRHl9ADw/Ow+qlmWj82wSbadj6GlLo7c9g3iXCmaPrpLIcUCw3OPEt8aH0r6Ex1+qwDJsZBI6MgkNalKHnrNg6hZyGQPpuIZMXEM8mkWyW8VoCpe8yCFS50fVgiCqFoRQVucDL3BO4mUz5DIGskkdasoAzwOCJEBSBHj8Mtx+CW6/DEEsrt+bGbHm5uGHH8bLL7+Mv/zlL5g3b96w7eLxOMLhMAThs2zXtm0wxiAIAv74xz/i5ptvLviaoSo3dXV1tOaGkFkgHdPw/qvn0NWcgqaasE0blmnDthn0rDnkH37RJaCiPoCqBUFILgG2ZcO2GGybgeO5fPXHthgs04apWzA051mUBXgCMjxBGW6fBI7nwPEceI4DxwO8yEMQeDDGkI5pSMdyznNvDoZmQZB4p3+JB89zzjYslh8DL/S9L/MQRR6i7IxFkHhwHOc8eMC2GNS0gVzGgK6azvj798Ni4AUOkkuAKAvgeQ6JCypinRloGXPEeEqK4MTPHBy4fDXAI0Lxin0HPhmaaiIWzSJxITuof5dXRM2iMKoWBBEs94DZDBwHSIrTl8srQlZEpHpy6O3IIJPQYGgWPH4ZsiIgfkFF8oIKXTVhGja8IRdC5W4EIx4EytwIV3kgK5P/f3RmM2iqCTWlo70hjpaTvWj9pBd6zhrU1uUVUVrtJIMcB6Dve+Z8/wA1baD7fApqaug7b/MiN2T8h+Pyiiip8sLlkWBoJnTVKkhcbWv8h3h/iYItT68ddz/jNZY1N9Oa3DDG8PDDD2P//v04ePAgFi5cOGJ727Zx6tSpgtd++tOf4k9/+hP27t2LefPmFdxhdSi0oJiQz4dYNIP3fncOzR/1QNcsYNr/GzczeIJyfspCdjvJRajCjTnLSlExPwDbYog2JtB+Jo6e1jS6W9NI9eRG3b/LK8IXUpCO5aBlR06mxovnOVTMD6B8bgCixIMXOFh9Sak36ELlvADK5vihZUwke1QkulTEohnEolnoqolAxI1QuRuiLKDjTBztDXHoOQvigCTU0CzkMuaQFRnFJ6FuSRiROYF85cUTlEc1BZRJaPn49rSn0dOaQSyayScjgsTDG3LBG5AhKQIkWYDL40y1ekMuBCNuhKu88ASG3x5jDJZhIx3X0Hk2ka9yxjuzTgPOSboUrwRPwEnYGWMwDRt6zoKacqo5kTl+3PXENZf/jZogRZPc/NM//RNeeukl/Pa3v8XixYvzrweDQbjdbgDAk08+iba2NrzwwgtD9rFt2zY6W4oQMqL+P/KmYSMT19BxJo6u5hQYY+B5DrzAgxM4MNv5w24ZNgSBcyotsgDJJUCQeJi6hWxCd0r4aQPMZvn1FLbdVz0xGRgYfCEXfCUKfGEFvrALLrfYVwnqqy5ZDLzIQRCcgzIvcLDM/nFa+fFahtN+4LoNnueg+CQoPgkutwh+QB9cX0XI0JypDMuwEAgrCFV6ECz3QHKJABjQ15czNwFwsgBumCkkTTWhJnVoWRNa1iiYxhBlHuFKL0IVHgTKlHwlxbZsdDal0HEmjo7GBLIJDRzvTIUYOROaakLLmLBMG4pXQkm1F/4SBaJLcLalmgiWKQhWeKB4JQgCh1SvhkRXFoluFYkLKrIJfQp/igDJJaCs1oc5y0swZ3kpInX+YWN2OSzLRrpXg+J1Es+ZsE6G2QyGbk1JhexSxnL8ntbRPvvsswCA9evXF7y+a9cu3H///QCAjo4OtLS0TPHICCGzCcdxEGVnmkbxSiit8Q3ZjjEGO2uCdwngLlpjYOecKgR/0R95ZtkwolmY3VmY3TmYPSqYYUMIuyCGFQhhBXKVF0Jw9Iubmc3AdAvMsMEs23k2GWDaYP0Pq+9zy3mPWTZg2rB1C1ZcgxXLwYw5z8ywoQHoGmmjIg+pwpN/cCIP27DBdAucLEDySHB5RPAeCXyZAt4ng/eIYIYNO6XDSuowG2JgQRfkGj94ge9b4xEcfj+ZU2URRP6yDuSJCypaP+lFokuFZdqwLAZB4MCLPBJdWUTPJaEmdXA8B3+JC/5SN0oqPQhXeSG7RSS7VcS7stCyJirqA6hZHIYv5MonlaZuQXaLULySk2BJk7vuRBB4BCPuSd3GWHE8NyMSm7GaEWtuphJVbgghRjSD7AcXYOdMsJwFWzVhxTWYvTkw3QI4QAi6IJYoYKYNs0eF3beeRCxVINX6IQRdMFpT0M+nwAx75A1ygGtBCJ5V5XCvKAMzbOgtSejNSegtKVgZA0yzwAwLtuYkKUWBBzDEUDlFgGt+CK76AHivBF4RwbtFcC4BnMSDE/m+5JH1/wOvCE71aBRJDrMZzG4VRnsaRmcWZlcWRrcKK5YDwIETOUDgwAk8GAdIEQ9c8wJw1Qch1/phqyaMC1lYMc2ZmhF5cCLnjElwzrZzvp4D+tZVoX9YfeMblFyaNuysATttwMo4z3ZaBzjOiYFPguCVnI+9fR97REB0qoZc3zMuM9H7PCiaaanpQMkNIZ8fjDHYdg6M9S/8dA4a6qlexF86C26CLvXFKSKkSg/EUjfEUgWcLDjJUiwHqycHIzrgqusiB5gMDDZsUYXhvoBcoBma7zw0/3mYSi94UwFvesCbbgiWDy61Fu7sfLi1eRC5gHPwFnlwwoADYv8BUuLBByVwIRssoIH5NNiyCstWYVs5WGYOjOVgMQ0208BxHHy+ZfDYi8H1iDCiWRhdWcBmTrIh8WC6BTtrOgfvrOkkY+pn62k4iYcQkMF7JRhdKljuMtfaCNxnB36/DMEvQ/BLAMd9tu2kDqMjDaYXSQI4RrxHhFznh1znh1Tnh2tuYFC1cLRs1YSV1iGGXOCk8Z12PhNQcjMCSm4Imbla215CLPY2XK5KuFwVUFyVEKUQDCMGQ++BZWUhy5H8+y5XBKp6HsnkCSRTJ5DNNsI0UzDNNCwrA9NMY8jSAgCeeeBnVyIoXoug61r4wksglbohhhTYmgmzx5li4kQ+n7Qwi8FoT0NvTcNKaJCqvZDn+GH6e5FMHUcieRy63g3b1gY8DDDTgp0xYGVzsLg0LCkDW1QBbux/fhWlFqLoA2OWsw6HmWDMcLbT92xZ2WH3eyQez3wEA1cjEFyJYOAqeL2LwfNDH1iZacPOGE41ZsB1VJjNYLSlkTsTg9GRgd1XGWOqCbt/qs2wAct2cs3+KsUYz+rhJB5SlRdSlRdixAMp4oZQ6gbHOVUVZjHAssF0G3p7GnpzEtq5BOy04VTmShSIJYqz/Yun+yzmLCC2+j5nQL7E1K+vMuRUe5zEkveIn1VnfDIErwQGBru/kpPpq+r0P1Qzv71hiRzci0vgvroc7iUlsHUL2pk4cqdjsOI5CGEFYpkbYlgB0yxYaR1WSofekoLRns6PmQ/IEEsUCH5nOpH3SM73rS9BtlK6k4zHnbVRvEeEEHBBrPRAqvBCqvBcdpI1USi5GQElN4TMXCdPPoZo52+nZduyHEFJeC28vsXgOAEceHAcD3A8OAhO9cDW+pKnFEwzCV3vQTL5IQyj57K3K0lh+HxL4PMthd+3FIq7DraVzSdput6NVPpjpFInkcudH1PfPC9DFIMQxQAEwQ2eV/qeXRB4BbygwLY1JJMfQlWbh/h6BV7PAohSAKIYhCQGIEoBSH19Og8/BMGNXK4DqtqMrNqMXK4dHvdchELXwO9fAY4TwJgJm5ngwEFRaiBJJQXTL3Z/dSjjTOdYKQNWSoedchYN8x5naov3SZAqnYRmrIt5GWOwUwZ4jzhoTdV0YqwvoTJtmBdU6Oed6U6tJQlrwJlqnMw7ieEYjtqcxF962nSUAn89F4Fb5kxIX5eDkpsRUHJDyMwVix1BKn0KmhaFpnVCy0VhmAlIUhiyXAqBV6DpF5z3tE6YZgKiGEIgcAUC/ivg8y/tO/D6IQg+iKIPguAFx/WdIQT0PTNksmcR630TvbG3EY+/B9se/enOF+M4CX7/cgQDV8PtrgPPK+B5F3hBAc+J6J8O4zhhQHIQhCQFwPOjX2hsGAmk05/AtnVwHO8kYZwInpfBcRI4XgTPSRAED0QxCEEYfd+63otk8gMkkseRTH6AZPI4TDM11lCMmigG4fHMh8+7EKHQtQiHr4OiVE/a9oqV3pGBerwL2eMXYCWca7aJFR4oC8OQKr2w4jmY3SrMuAbeJTgVI78EqcIL1/wg+IDsTOf15mD2qrDSRn6K0Vmo7qzx4r2SU9kJKUDfwnqzNwejKwszmoGV1BG+exG8qyqmLRaU3IyAkhtCZg/L0voO7ONbgGnbGhKJ/4fe2FvQch1gsMGYDTB7wMcWeN4FUfTnKxaiFITftwQ+3/IxJRLFgDEb2ew5qLnzMI0kDDMB00zCNBIwzdRnn5tJWFYWLrkCbs9ceNxz4XJVIpNpQDxxFJnMGQAceE4Ex4tgtglN7xxym4pSh3B4DcKhNfD5l0FxVUEUA0N+fw0jgWTyA2haFLzghiB4nAfvBi8oEHhXvlIlCB7wvDwhcbFtE6rajFyuFaaZhmmlYZlpGGYCut4NXbsATb8Ay0pDcVXD7ZkLt3suFKUalpmFYcZgGHEnbmYGppWBZaZhs/7T2nlw4CCIPij56dcqyFIZ+JQXLn8l3KWV4PlLXzF6ItmqCfAceNf0rd2h5GYElNwQQsj0siwVWbUZ2ew5pJInEIu/i1TqwwELvz8jCB64XFXgeXnAuiINmhYd0zYFwQtJDEKSwhClADhOdKYd0VcBA+dMQXICeE4Gx0t9CZkEnpOQ06LIZs4gkz0Hxqb2+jpD748PkhTq26cQfL4lCIZWIxS8BrJcOt3DmxSU3IyAkhtCCJl5TDONROIYYvEjiMeOIKs2wzB6R/wat3suPJ55zllgVhamlYVt52DbOVhWDratgbGhb3MwHjzvhsczt289kw+i4IMg+pzF7nIEsisCQfAgl2uDmnXWIWlaFKLg7UuuQn1Tk76+ipN3wPSkcxFI00jkp2dzWodTFdK7oes9uNRicY9nPtzuuZClMCQpDEkKwWYWtFw7cloHcrl2mGayr6rljEHsG4cgeiEIXoiCF0Lfvomib8BUrx+i6IckhSCKQ18varIUzUX8CCGEEAAQRR9KS29EaemN+dcsS4WmRZHLdYAxK7+miONEuN11o6pQ2LYJy8o4Z9wZcRhGDKaZ6qsSOVOODH1TkMzuW/hsgNn9zzpsZkCWwvB6F8Hr/QIUpaav6jP1GLP79iUB00zAMOLOwvbUB4jH30Mm04Bs9iyy2bOTOo6amvuwZPEPJ3Ub40HJDSGEkBlJENzweObB4xn+hsqXwvMieD4ISRr+SsnFhON4yHLpoMSuGncCAAwjjkTyODStM5/MGUYcHMdDcVXBpVRBcVVDkoKwLBWWle2reqWdj/vXAVnpvo/Tztqi/FmCKVhWGqLon47dHzVKbgghhJBZQpJCKCtdP+nbYWxmX0Rx5pzoTwghhJCiMF3TcqM1s0dHCCGEEDJGlNwQQgghZFah5IYQQgghswolN4QQQgiZVSi5IYQQQsisQskNIYQQQmYVSm4IIYQQMqtQckMIIYSQWYWSG0IIIYTMKpTcEEIIIWRWoeSGEEIIIbMKJTeEEEIImVUouSGEEELIrCJO9wCmGmMMAJBMJqd5JIQQQggZrf7jdv9xfCSfu+QmlUoBAOrq6qZ5JIQQQggZq1QqhWAwOGIbjo0mBZpFbNtGe3s7/H4/OI6b7uFMuGQyibq6Opw/fx6BQGC6h1OUKIbjRzEcP4rh+FEMx28mxZAxhlQqherqavD8yKtqPneVG57nUVtbO93DmHSBQGDafxCLHcVw/CiG40cxHD+K4fjNlBheqmLTjxYUE0IIIWRWoeSGEEIIIbMKJTezjMvlwtatW+FyuaZ7KEWLYjh+FMPxoxiOH8Vw/Io1hp+7BcWEEEIImd2ockMIIYSQWYWSG0IIIYTMKpTcEEIIIWRWoeRmiv30pz/FvHnzoCgKVq9ejcOHD4/Y/tChQ1i9ejUURcH8+fPxs5/9bFCbffv2YdmyZXC5XFi2bBn2798/bH87duwAx3F49NFHC17v7OzE/fffj+rqang8Htx2221oaGgoaLN+/XpwHFfw2Lx58+h3fgIUc/wA4O2338bNN98Mr9eLUCiE9evXQ1XV0e38BCnWGDY1NQ36+et/7NmzZ2xBGKdijSEARKNRfOMb30BlZSW8Xi9WrVqFvXv3jn7nJ0gxx7CxsRF33HEHIpEIAoEA7r77bnR2do5+5yfIdMRw27Ztg37/KisrC9owxrBt2zZUV1fD7XZj/fr1OHnyZEEbTdPw8MMPo6ysDF6vFxs3bkRra+tlRmIIjEyZ3bt3M0mS2HPPPcdOnTrFHnnkEeb1ellzc/OQ7c+ePcs8Hg975JFH2KlTp9hzzz3HJElie/fuzbd56623mCAI7Omnn2Yff/wxe/rpp5koiuydd94Z1N+7777L6uvr2ZVXXskeeeSR/Ou2bbPrrruO3XDDDezdd99ln3zyCfvHf/xHNmfOHJZOp/Pt1q1bxx544AHW0dGRf8Tj8YkL0CUUe/zeeustFggE2I4dO9hHH33ETp8+zfbs2cNyudzEBekSijmGpmkW/Ox1dHSw7du3M6/Xy1Kp1MQGagTFHEPGGNuwYQO79tpr2ZEjR1hjYyP713/9V8bzPDt27NjEBekSijmG6XSazZ8/n91xxx3sww8/ZB9++CH7yle+wq699lpmWdbEBmoE0xXDrVu3suXLlxf8HnZ1dRVsa+fOnczv97N9+/axEydOsHvuuYdVVVWxZDKZb/Otb32L1dTUsAMHDrBjx46xm266iV111VXMNM0JiQ8lN1Por/7qr9i3vvWtgteWLFnCnnjiiSHbf//732dLliwpeO3BBx9k1113Xf7zu+++m912220Fbb70pS+xzZs3F7yWSqXYwoUL2YEDB9i6desKfqE//fRTBoB99NFH+ddM02QlJSXsueeey7928ddNtWKP35o1a9hTTz01up2dJMUew4tdffXV7O/+7u+GfX8yFHsMvV4ve+GFFwr6LSkpYf/1X/81wl5PrGKO4R/+8AfG8zxLJBL5Nr29vQwAO3DgwCj2fmJMVwy3bt3KrrrqqmHHZds2q6ysZDt37sy/lsvlWDAYZD/72c8YY4zF43EmSRLbvXt3vk1bWxvjeZ699tprw/Y9FjQtNUV0XcfRo0dx6623Frx+66234q233hrya95+++1B7b/0pS/h/fffh2EYI7a5uM9vf/vb+Ju/+Rts2LBh0HY0TQMAKIqSf00QBMiyjDfeeKOg7S9/+UuUlZVh+fLlePzxx/M3Ip1sxR6/rq4uHDlyBOXl5Vi7di0qKiqwbt26QfGdTMUew4sdPXoUx48fx9///d8P+f5kmA0xvP766/HrX/8avb29sG0bu3fvhqZpWL9+/SX2fmIUeww1TQPHcQXXfVEUBTzPT9nv83THsKGhAdXV1Zg3bx42b96Ms2fP5t87d+4cotFoQT8ulwvr1q3L93P06FEYhlHQprq6GitWrBh2/GNFyc0U6e7uhmVZqKioKHi9oqIC0Wh0yK+JRqNDtjdNE93d3SO2Gdjn7t27cezYMezYsWPI7SxZsgRz587Fk08+iVgsBl3XsXPnTkSjUXR0dOTb3XffffjVr36FgwcP4l/+5V+wb98+bNq0afRBGIdij1//L/+2bdvwwAMP4LXXXsOqVatwyy23DLk2ZzIUewwv9vzzz2Pp0qVYu3btyDs+gWZDDH/961/DNE2UlpbC5XLhwQcfxP79+7FgwYLRB2Icij2G1113HbxeL37wgx8gm80ik8nge9/7HmzbHvZndaJNZwzXrFmDF154AX/4wx/w3HPPIRqNYu3atejp6cn30f91w/UTjUYhyzLC4fCoxz9WlNxMsYvvRM4YG/Hu5EO1v/j1kfo8f/48HnnkEfzP//xPwf9GBpIkCfv27cPp06dRUlICj8eDgwcP4vbbb4cgCPl2DzzwADZs2IAVK1Zg8+bN2Lt3L15//XUcO3ZsFHs+MYo1frZtAwAefPBBfPOb38TKlSvxox/9CIsXL8bPf/7z0ez6hCnWGA6kqipeeumlKa3aDFTMMXzqqacQi8Xw+uuv4/3338djjz2Gu+66CydOnBjFnk+cYo1hJBLBnj178H//93/w+XwIBoNIJBJYtWrVkD+rk2mqYwgAt99+O772ta/hiiuuwIYNG/DKK68AAH7xi1+Ma2yjbTNan7u7gk+XsrIyCIIwKCvt6uoalOH2q6ysHLK9KIooLS0dsU1/n0ePHkVXVxdWr16df9+yLPzlL3/Bj3/8Y2iaBkEQsHr1ahw/fhyJRAK6riMSiWDNmjW45pprht2nVatWQZIkNDQ0YNWqVaMPxmUo9vhVVVUBAJYtW1awraVLl6KlpWWs4bgsxR7Dgfbu3YtsNostW7aMPRDjUOwxbGxsxI9//GN89NFHWL58OQDgqquuwuHDh/GTn/xkyLNnJlqxxxBwpn8aGxvR3d0NURQRCoVQWVmJefPmXX5gxmC6YjgUr9eLK664Il+B7j9zKhqN5v/uXdxPZWUldF1HLBYrqN50dXVNWCWWKjdTRJZlrF69GgcOHCh4/cCBA8N+M7/4xS8Oav/HP/4R11xzDSRJGrFNf5+33HILTpw4gePHj+cf11xzDe677z4cP3580P80gsEgIpEIGhoa8P777+MrX/nKsPt08uRJGIZR8AM8WYo9fvX19aiursann35a0P706dOYO3fuGKNxeYo9hgM9//zz2LhxIyKRyNiCME7FHsNsNgsA4PnCP/2CIOSri5Ot2GM4UFlZGUKhEP70pz+hq6sLGzduHFswLtN0xXAomqbh448/zh8H5s2bh8rKyoJ+dF3HoUOH8v2sXr0akiQVtOno6MBHH300cdPME7IsmYxK/6l7zz//PDt16hR79NFHmdfrZU1NTYwxxp544gn2jW98I9++/9S973znO+zUqVPs+eefH3Tq3ptvvskEQWA7d+5kH3/8Mdu5c+ewpz/2G+qsp//93/9lf/7zn1ljYyN7+eWX2dy5c9mmTZvy7585c4Zt376dvffee+zcuXPslVdeYUuWLGErV66csFP3LqWY48cYYz/60Y9YIBBge/bsYQ0NDeypp55iiqKwM2fOTEB0RqfYY8gYYw0NDYzjOPb73/9+nNG4PMUcQ13X2Re+8AV2ww03sCNHjrAzZ86wf//3f2ccx7FXXnllgiJ0acUcQ8YY+/nPf87efvttdubMGfbiiy+ykpIS9thjj01AZEZvumL43e9+lx08eJCdPXuWvfPOO+zLX/4y8/v9+e0y5pwKHgwG2W9+8xt24sQJdu+99w55KnhtbS17/fXX2bFjx9jNN99Mp4IXs5/85Cds7ty5TJZltmrVKnbo0KH8e3/7t3/L1q1bV9D+4MGDbOXKlUyWZVZfX8+effbZQX3u2bOHLV68mEmSxJYsWcL27ds34hiG+oV+5plnWG1tLZMkic2ZM4c99dRTTNO0/PstLS3sxhtvZCUlJUyWZbZgwQL2z//8z6ynp2fsQRiHYo1fvx07drDa2lrm8XjYF7/4RXb48OHR7/wEKfYYPvnkk6y2tnZKrylysWKO4enTp9mmTZtYeXk583g87Morrxx0avhUKOYY/uAHP2AVFRVMkiS2cOFC9h//8R/Mtu2xBWACTEcM+69ZI0kSq66uZps2bWInT54saGPbNtu6dSurrKxkLpeL3XjjjezEiRMFbVRVZQ899BArKSlhbrebffnLX2YtLS3jjMhn6K7ghBBCCJlVaM0NIYQQQmYVSm4IIYQQMqtQckMIIYSQWYWSG0IIIYTMKpTcEEIIIWRWoeSGEEIIIbMKJTeEEEIImVUouSGEEELIrELJDSFk2hw8eBAcxyEej0/5tjmOA8dxCIVCo2rfP1aO4/DVr351UsdGCBkfSm4IIVNi/fr1ePTRRwteW7t2LTo6OhAMBqdlTLt27cLp06dH1bZ/rHffffckj4oQMl6U3BBCpo0sy6isrATHcdOy/VAohPLy8lG17R+r2+2e5FERQsaLkhtCyKS7//77cejQITzzzDP5qZ2mpqZB01L//d//jVAohN/97ndYvHgxPB4P7rzzTmQyGfziF79AfX09wuEwHn74YViWle9f13V8//vfR01NDbxeL9asWYODBw+OeZwffPABbrrpJvj9fgQCAaxevRrvv//+BEWBEDJVxOkeACFk9nvmmWdw+vRprFixAj/84Q8BAJFIBE1NTYPaZrNZ/Od//id2796NVCqFTZs2YdOmTQiFQnj11Vdx9uxZfO1rX8P111+Pe+65BwDwzW9+E01NTdi9ezeqq6uxf/9+3HbbbThx4gQWLlw46nHed999WLlyJZ599lkIgoDjx49DkqQJiQEhZOpQckMImXTBYBCyLMPj8aCysnLEtoZh4Nlnn8WCBQsAAHfeeSdefPFFdHZ2wufzYdmyZbjpppvw5z//Gffccw8aGxvxq1/9Cq2traiurgYAPP7443jttdewa9cuPP3006MeZ0tLC773ve9hyZIlADCmxIgQMnNQckMImVE8Hk8+sQGAiooK1NfXw+fzFbzW1dUFADh27BgYY1i0aFFBP5qmobS0dEzbfuyxx/AP//APePHFF7FhwwbcddddBWMhhBQHSm4IITPKxdNAHMcN+Zpt2wAA27YhCAKOHj0KQRAK2g1MiEZj27Zt+PrXv45XXnkFv//977F161bs3r0bd9xxx2XsCSFkulByQwiZErIsFywCnigrV66EZVno6urCDTfcMO7+Fi1ahEWLFuE73/kO7r33XuzatYuSG0KKDJ0tRQiZEvX19Thy5AiamprQ3d2dr7yM16JFi3Dfffdhy5Yt+M1vfoNz587hvffew7/927/h1VdfHXU/qqrioYcewsGDB9Hc3Iw333wT7733HpYuXToh4ySETB1KbgghU+Lxxx+HIAhYtmwZIpEIWlpaJqzvXbt2YcuWLfjud7+LxYsXY+PGjThy5Ajq6upG3YcgCOjp6cGWLVuwaNEi3H333bj99tuxffv2CRsnIWRqcIwxNt2DIISQqcZxHPbv3z/mWyncf//9iMfjePnllydlXISQ8aPKDSHkc+vee+9FbW3tqNoePnwYPp8Pv/zlLyd5VISQ8aLKDSHkc+nMmTMAnOmoefPmXbK9qqpoa2sD4JyFdanr9RBCpg8lN4QQQgiZVWhaihBCCCGzCiU3hBBCCJlVKLkhhBBCyKxCyQ0hhBBCZhVKbgghhBAyq1ByQwghhJBZhZIbQgghhMwqlNwQQgghZFah5IYQQgghs8r/ByxfXtbQxeYpAAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "([(np.int64(98), 'TLIM'), (np.int64(2), 'WALL')], [])" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vrun = a5.simulation_run()\n", "\n", "# Get final (R,z) coordinates of all markers that hit the wall\n", "r, z = vrun.getstate(\"r\", \"z\", state=\"end\", endcond=\"wall\", ids=None)\n", "print(r,z)\n", "\n", "# Plot (time, energy) of confined marker orbits\n", "ax = plt.figure().add_subplot(1,1,1)\n", "vrun.plotorbit_trajectory(\"time\", \"ekin\", endcond=\"not wall\", axes=ax)\n", "plt.show(block=True)\n", "\n", "# Summarize simulation\n", "vrun.getstate_markersummary()\n", "\n", "# Visualize losses\n", "\n", "# Etc... see the documentation of RunGroup for details" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To rerun the code, free the simulation output.\n", "Once it is freed, the previous `VirtualRun` becomes an empty shell and it is no longer usable.\n", "Once you have had enough fun, the markers should be freed and inputs unpacked and deallocated." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2025-04-01T09:03:45.175413Z", "iopub.status.busy": "2025-04-01T09:03:45.175248Z", "iopub.status.idle": "2025-04-01T09:03:47.306457Z", "shell.execute_reply": "2025-04-01T09:03:47.305867Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Summary of results:\n", " 98 markers had end condition Sim time limit\n", " 2 markers had end condition Wall collision\n", "\n", " No markers were aborted.\n" ] } ], "source": [ "a5.simulation_free(diagnostics=True)\n", "a5.simulation_run()\n", "\n", "a5.simulation_free(inputs=True, markers=True, diagnostics=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Need help?\n", "\n", "1. Ask in our ASCOT5 Slack channel.\n", "\n", "2. If you have an issue to report, use the GitHub issue tracker.\n", " For bugs, state which version/branch you are using and try to provide the HDF5 file.\n", "\n", "3. Join one of our \"weekly\" meetings to present your research and discuss any issues." ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 4 }