{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adaptive PDE discretizations on Cartesian grids\n",
    "## Volume : Algorithmic tools\n",
    "## Part : Tensor decomposition techniques\n",
    "## Chapter : Voronoi's reduction, in dimension 6, application to Hooke tensor decomposition\n",
    "\n",
    "We rely on Voronoi's first reduction of quadratic forms to decompose symmetric positive definite matrices in dimension $\\leq 6$, in a form which resembles the eigenvalue-eigenvector decomposition but with integer offsets:\n",
    "$$\n",
    "    D = \\sum_{1 \\leq i \\leq d'} \\rho_i e_i e_i^T\n",
    "$$\n",
    "where $d'=d(d+1)/2$ (except $d'=12$ in dimension $4$ in our implementation), $\\rho_i\\geq 0$, and $e_i \\in Z^d$.\n",
    "\n",
    "The six-dimensional case is especially interesting for its applications to the [Hooke elasticity tensor in three dimensional elasticity](../Notebooks_Div/ElasticEnergy.ipynb). The approach is (very) unlikely to extend to higher dimensions (including dimension 7), in a computationally efficient manner, due to a combinatorial explosion in Voronoi's theory.\n",
    "\n",
    "**Note on excecuting this notebook.**\n",
    "The implementation of Voronoi's decomposition involves a rather large data file, which is not included in the agd library, but provided in the AdaptiveGridDiscretizations repository (File `Miscellaneous/Geometry6_data2.h`). Executing this notebook thus requires a bit more effort than the others.\n",
    "\n",
    "<!---\n",
    "The quadratic form defined by the Hooke tensor is reformulated, using Voronoi's decomposition, in the form\n",
    "$$\n",
    "    \\sum_{1 \\leq i \\leq d'} \\rho_i \\mathrm{Tr}(M D_i)^2\n",
    "$$\n",
    "where $d'=21$, $\\rho_i\\geq 0$, $D_i$ is a $3 \\times 3$ symmetric matrix with integer entries.\n",
    "\n",
    "The matrices $D_i$ usually have rather small entries within $-2,...,2$, since the the Hooke tensor associated with physical materials is not too large.\n",
    "--->"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[**Summary**](Summary.ipynb) of volume Algorithmic tools, this series of notebooks.\n",
    "\n",
    "[**Main summary**](../Summary.ipynb) of the Adaptive Grid Discretizations \n",
    "\tbook of notebooks, including the other volumes.\n",
    "\n",
    "# Table of contents\n",
    "  * [1. Computing the decomposition of a tensor](#1.-Computing-the-decomposition-of-a-tensor)\n",
    "    * [1.1 Case of a $6\\times 6$ tensor](#1.1-Case-of-a-$6\\times-6$-tensor)\n",
    "    * [1.2 A family of tensors](#1.2-A-family-of-tensors)\n",
    "    * [1.3 Case of a field of tensors](#1.3-Case-of-a-field-of-tensors)\n",
    "  * [2. Under the hood, Voronoi's first reduction](#2.-Under-the-hood,-Voronoi's-first-reduction)\n",
    "    * [2.1 Voronoi's perfect forms](#2.1-Voronoi's-perfect-forms)\n",
    "    * [2.2 Computing Voronoi's first reduction](#2.2-Computing-Voronoi's-first-reduction)\n",
    "    * [2.3 Most common optimal form](#2.3-Most-common-optimal-form)\n",
    "  * [3. Voronoi's first reduction in lower dimensions](#3.-Voronoi's-first-reduction-in-lower-dimensions)\n",
    "\n",
    "\n",
    "\n",
    "**Acknowledgement.** Some of the experiments presented in these notebooks are part of \n",
    "ongoing research with Ludovic Métivier and Da Chen.\n",
    "\n",
    "Copyright Jean-Marie Mirebeau, Centre Borelli, ENS Paris-Saclay, CNRS, University Paris-Saclay"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 0. Importing the required libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.077779Z",
     "iopub.status.busy": "2024-04-30T08:46:55.077240Z",
     "iopub.status.idle": "2024-04-30T08:46:55.087455Z",
     "shell.execute_reply": "2024-04-30T08:46:55.087022Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys; sys.path.insert(0,\"..\") # Allow import of agd from parent directory (useless if conda package installed)\n",
    "#from Miscellaneous import TocTools; print(TocTools.displayTOC('TensorVoronoi6','Algo'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.089951Z",
     "iopub.status.busy": "2024-04-30T08:46:55.089758Z",
     "iopub.status.idle": "2024-04-30T08:46:55.342673Z",
     "shell.execute_reply": "2024-04-30T08:46:55.342379Z"
    }
   },
   "outputs": [],
   "source": [
    "from agd import LinearParallel as lp\n",
    "from agd.Selling import GatherByOffset\n",
    "from agd import AutomaticDifferentiation as ad\n",
    "from agd.Metrics import Seismic\n",
    "from agd.Plotting import savefig; #savefig.dirName = 'Figures/TensorVoronoi'\n",
    "from agd.Metrics.misc import flatten_symmetric_matrix, expand_symmetric_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The routines for tensor decomposition are for efficiency purposes provided in a small c++ library, named FileVDQ where VDQ stands for \"Voronoi Decomposition of Quadratic forms\". This is in contrast with the two and three dimensional cases, where the decomposition algorithm is coded in Python (the c++ library can also be used in smaller dimensions). A function named `VoronoiDecomposition` provides the interface."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.344714Z",
     "iopub.status.busy": "2024-04-30T08:46:55.344549Z",
     "iopub.status.idle": "2024-04-30T08:46:55.347808Z",
     "shell.execute_reply": "2024-04-30T08:46:55.347320Z"
    }
   },
   "outputs": [],
   "source": [
    "from agd.Eikonal import VoronoiDecomposition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.349918Z",
     "iopub.status.busy": "2024-04-30T08:46:55.349799Z",
     "iopub.status.idle": "2024-04-30T08:46:55.355730Z",
     "shell.execute_reply": "2024-04-30T08:46:55.355433Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np; allclose = np.allclose\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.357302Z",
     "iopub.status.busy": "2024-04-30T08:46:55.357216Z",
     "iopub.status.idle": "2024-04-30T08:46:55.359135Z",
     "shell.execute_reply": "2024-04-30T08:46:55.358903Z"
    }
   },
   "outputs": [],
   "source": [
    "def ReloadPackages():\n",
    "    from Miscellaneous.rreload import rreload\n",
    "    global expand_symmetric_matrix,VoronoiDecomposition\n",
    "    expand_symmetric_matrix,VoronoiDecomposition = rreload([expand_symmetric_matrix,VoronoiDecomposition],rootdir='../..')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0.1 Optional configuration\n",
    "\n",
    "Uncomment the following line to use the GPU implementation of Voronoi's decomposition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.360530Z",
     "iopub.status.busy": "2024-04-30T08:46:55.360445Z",
     "iopub.status.idle": "2024-04-30T08:46:55.361985Z",
     "shell.execute_reply": "2024-04-30T08:46:55.361774Z"
    },
    "tags": [
     "EikonalGPU_config"
    ]
   },
   "outputs": [],
   "source": [
    "#VoronoiDecomposition.default_mode = 'gpu_transfer'; allclose = ad.cupy_friendly(allclose)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Choose to use, or not, large instances by uncommenting the following line (computation time may become longer)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.363368Z",
     "iopub.status.busy": "2024-04-30T08:46:55.363286Z",
     "iopub.status.idle": "2024-04-30T08:46:55.364948Z",
     "shell.execute_reply": "2024-04-30T08:46:55.364704Z"
    }
   },
   "outputs": [],
   "source": [
    "large_instances = (VoronoiDecomposition.default_mode == 'gpu_transfer') # Large instances on GPU only by default"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Computing the decomposition of a tensor\n",
    "\n",
    "We illustrate our tensor decomposition method on random positive definite matrices, of the form \n",
    "$$\n",
    "    D = A^T A,\n",
    "$$\n",
    "where $A$ is a square matrix with random coefficients w.r.t. the Gaussian normal law."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.366323Z",
     "iopub.status.busy": "2024-04-30T08:46:55.366243Z",
     "iopub.status.idle": "2024-04-30T08:46:55.368394Z",
     "shell.execute_reply": "2024-04-30T08:46:55.368144Z"
    }
   },
   "outputs": [],
   "source": [
    "def MakeRandomTensor(dim, shape=tuple(), relax=0.05):\n",
    "    A = np.random.standard_normal( (dim,dim) + shape )\n",
    "    D = lp.dot_AA(lp.transpose(A),A)\n",
    "    identity = np.eye(dim).reshape((dim,dim)+(1,)*len(shape))\n",
    "    return D+lp.trace(D)*relax*identity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The inserse operation to tensor decomposition is, of course, reconstruction, defined by \n",
    "$$\n",
    "    (\\lambda_i, e_i)_{i=1}^I \\mapsto D = \\sum_{1 \\leq i \\leq I} \\lambda_i e_i e_i^T\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.369691Z",
     "iopub.status.busy": "2024-04-30T08:46:55.369612Z",
     "iopub.status.idle": "2024-04-30T08:46:55.371297Z",
     "shell.execute_reply": "2024-04-30T08:46:55.371078Z"
    }
   },
   "outputs": [],
   "source": [
    "def Reconstruct(coefs,offsets):\n",
    "     return lp.mult(coefs,lp.outer_self(offsets)).sum(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.372602Z",
     "iopub.status.busy": "2024-04-30T08:46:55.372525Z",
     "iopub.status.idle": "2024-04-30T08:46:55.373942Z",
     "shell.execute_reply": "2024-04-30T08:46:55.373724Z"
    }
   },
   "outputs": [],
   "source": [
    "def LInfNorm(a):\n",
    "    return np.max(np.abs(a))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Case of a $6\\times 6$ tensor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.375263Z",
     "iopub.status.busy": "2024-04-30T08:46:55.375165Z",
     "iopub.status.idle": "2024-04-30T08:46:55.376831Z",
     "shell.execute_reply": "2024-04-30T08:46:55.376615Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(42) # Reproducibility\n",
    "D = MakeRandomTensor(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.378084Z",
     "iopub.status.busy": "2024-04-30T08:46:55.378007Z",
     "iopub.status.idle": "2024-04-30T08:46:55.380540Z",
     "shell.execute_reply": "2024-04-30T08:46:55.380286Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 5.86365855,  0.78781668, -1.53319092,  2.11419436, -1.32247999,\n",
       "         1.41133885],\n",
       "       [ 0.78781668, 11.28811803,  0.62779508, -0.31702439,  2.97614926,\n",
       "        -1.20780797],\n",
       "       [-1.53319092,  0.62779508,  8.66990649,  0.95257212,  2.59215657,\n",
       "        -2.21101525],\n",
       "       [ 2.11419436, -0.31702439,  0.95257212,  5.82259858, -1.14947197,\n",
       "         0.71740399],\n",
       "       [-1.32247999,  2.97614926,  2.59215657, -1.14947197,  3.91888129,\n",
       "        -0.97283498],\n",
       "       [ 1.41133885, -1.20780797, -2.21101525,  0.71740399, -0.97283498,\n",
       "         5.55749118]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The compile time can be quite long on GPU. The execution time may not be instantaneous either, especially on GPU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.381905Z",
     "iopub.status.busy": "2024-04-30T08:46:55.381828Z",
     "iopub.status.idle": "2024-04-30T08:46:55.393789Z",
     "shell.execute_reply": "2024-04-30T08:46:55.393424Z"
    }
   },
   "outputs": [],
   "source": [
    "coefs,offsets = VoronoiDecomposition(D,retry64_tol=0.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our decomposition of a $6\\times 6$ symmetric positive definite matrix involves $21$ (non-negative) weights and (integral) offsets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.395420Z",
     "iopub.status.busy": "2024-04-30T08:46:55.395301Z",
     "iopub.status.idle": "2024-04-30T08:46:55.397927Z",
     "shell.execute_reply": "2024-04-30T08:46:55.397670Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Coefficients :  [0.06272357 0.08321161 0.09108027 0.17300802 0.25543099 0.33765603\n",
      " 0.37974797 0.43206798 0.57262901 0.60285459 0.90199881 1.01424559\n",
      " 1.02162947 1.14710001 1.20004529 1.32672471 1.71589609 1.77768024\n",
      " 2.17099232 2.50835894 6.57177511]\n",
      "Offsets : \n",
      " [[ 1  1  1  1  0  1  1  1  0  1  1  0  1  0  0  0  0  1  0  0  0]\n",
      " [ 1  1  0  0  1  0 -1  0  1  0  0  1  1  0  0  1  0  0  0  0  1]\n",
      " [ 0  0 -1 -1  1 -1 -1 -1  0  0  1  1 -1  1  1  0  1  0  0  0  0]\n",
      " [ 1  0  0  0  0  1  1  1  0  0  1  0  0  0  1  0  0  0  0  1  0]\n",
      " [ 0  0  0 -1  1 -1 -1 -1  0  0  0  1  0  0  0  1  0  0  0  0  0]\n",
      " [ 0  0  1  0 -1  1  1  0 -1  1  0  0  0 -1  0  0  0  0  1  0  0]]\n"
     ]
    }
   ],
   "source": [
    "print(\"Coefficients : \", coefs)\n",
    "print(\"Offsets : \\n\", offsets.astype(int))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By design, the coefficients are non-negative, and the reconstruction is exact up to numerical precision."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.399289Z",
     "iopub.status.busy": "2024-04-30T08:46:55.399185Z",
     "iopub.status.idle": "2024-04-30T08:46:55.401262Z",
     "shell.execute_reply": "2024-04-30T08:46:55.401035Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimal coefficient :  0.06272357357338984\n",
      "Reconstruction error :  6.545874953189923e-13\n"
     ]
    }
   ],
   "source": [
    "print(\"Minimal coefficient : \", np.min(coefs))\n",
    "print(\"Reconstruction error : \", LInfNorm(D-Reconstruct(coefs,offsets)))\n",
    "assert np.allclose(D,Reconstruct(coefs,offsets))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 A family of tensors\n",
    "\n",
    "As we interpolate between two tensors, the coefficients and the offsets vary. \n",
    "Voronoi's decomposition is not unique, hence we select a decomposition among the optimal ones by minimizing a linear form. This linear form has fixed coefficients, which were initially randomly generated, and with probability one, it should select a decomposition in a locally Lispchitz manner w.r.t. the metric. \n",
    "(An alternative selection principle, which involves no randomness, would be to select a decomposition which minimizes some lexicographic ordering, but this is numerically more complex and costly.)\n",
    "\n",
    "<!---\n",
    "In the present implementation the coefficients may vary discontinuously, due to the non-uniqueness of Voronoi's. It is in principle possible to fix this issue, as in the $4$ and $5$ dimensional cases, and obtain a decomposition with Lipschitz regularity w.r.t the metric, by using an appropriate selection criterion.\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.402741Z",
     "iopub.status.busy": "2024-04-30T08:46:55.402606Z",
     "iopub.status.idle": "2024-04-30T08:46:55.404675Z",
     "shell.execute_reply": "2024-04-30T08:46:55.404435Z"
    }
   },
   "outputs": [],
   "source": [
    "def Interpolate(a,b,T=np.linspace(0,1,100)):\n",
    "    return T, np.moveaxis(np.array([(1-t)*a + t*b for t in T]),0,-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.406168Z",
     "iopub.status.busy": "2024-04-30T08:46:55.406042Z",
     "iopub.status.idle": "2024-04-30T08:46:55.408372Z",
     "shell.execute_reply": "2024-04-30T08:46:55.408090Z"
    }
   },
   "outputs": [],
   "source": [
    "T_interp, D_interp = Interpolate(MakeRandomTensor(6),MakeRandomTensor(6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.409839Z",
     "iopub.status.busy": "2024-04-30T08:46:55.409728Z",
     "iopub.status.idle": "2024-04-30T08:46:55.413615Z",
     "shell.execute_reply": "2024-04-30T08:46:55.413347Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(43)\n",
    "a,b = MakeRandomTensor(6),MakeRandomTensor(6)\n",
    "t0,t1 = 0,1 #t1,t2=0.8,0.85\n",
    "T_interp, D_interp = Interpolate(a,b,np.linspace(t0,t1,1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.414956Z",
     "iopub.status.busy": "2024-04-30T08:46:55.414880Z",
     "iopub.status.idle": "2024-04-30T08:46:55.972735Z",
     "shell.execute_reply": "2024-04-30T08:46:55.972357Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.36 ms, sys: 3.41 ms, total: 4.77 ms\n",
      "Wall time: 555 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "coefs,offsets = VoronoiDecomposition(D_interp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.974480Z",
     "iopub.status.busy": "2024-04-30T08:46:55.974364Z",
     "iopub.status.idle": "2024-04-30T08:46:55.977079Z",
     "shell.execute_reply": "2024-04-30T08:46:55.976830Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  0,  1, -1,  1,  0],\n",
       "       [ 1,  0,  1, -1,  0, -1],\n",
       "       [ 1,  0,  0, -1,  0, -1],\n",
       "       [ 0,  1,  0,  0, -1,  0],\n",
       "       [ 0,  0,  1, -1,  0,  0],\n",
       "       [ 0,  1,  1,  0,  0,  1],\n",
       "       [ 1,  0, -1,  0, -1,  0],\n",
       "       [ 0,  1,  1, -1,  0,  0],\n",
       "       [ 1,  0,  0,  0,  0, -1],\n",
       "       [ 0,  1,  0,  1, -1,  1],\n",
       "       [ 0,  0,  1,  0,  0,  0],\n",
       "       [ 0,  1,  0,  0,  0,  0],\n",
       "       [ 0,  0,  0,  0,  0,  1],\n",
       "       [ 0,  0,  0,  1,  0,  0],\n",
       "       [ 0,  1,  0,  0,  0,  1],\n",
       "       [ 0,  1,  1,  0,  0,  0],\n",
       "       [ 1,  1,  0,  0, -1,  0],\n",
       "       [ 1,  0,  0,  0,  0,  0],\n",
       "       [ 0,  1,  0,  0, -1,  1],\n",
       "       [ 1,  0,  0,  0, -1,  0],\n",
       "       [ 0,  0,  0,  0,  1,  0]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "offsets[:,:,0].T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.978432Z",
     "iopub.status.busy": "2024-04-30T08:46:55.978338Z",
     "iopub.status.idle": "2024-04-30T08:46:55.987077Z",
     "shell.execute_reply": "2024-04-30T08:46:55.986819Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reconstruction error :  1.5241141682054149e-12\n"
     ]
    }
   ],
   "source": [
    "print(\"Reconstruction error : \", LInfNorm(D_interp - Reconstruct(coefs,offsets)))\n",
    "assert np.allclose(D_interp, Reconstruct(coefs,offsets),atol=1e-4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:55.988538Z",
     "iopub.status.busy": "2024-04-30T08:46:55.988433Z",
     "iopub.status.idle": "2024-04-30T08:46:56.038815Z",
     "shell.execute_reply": "2024-04-30T08:46:56.038552Z"
    }
   },
   "outputs": [],
   "source": [
    "decomp = GatherByOffset(T_interp,coefs,offsets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:56.040292Z",
     "iopub.status.busy": "2024-04-30T08:46:56.040216Z",
     "iopub.status.idle": "2024-04-30T08:46:56.425164Z",
     "shell.execute_reply": "2024-04-30T08:46:56.424852Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZWUhPT7frJtfNmzdx+fJlHDx40K5cSkpKsH37dt7stRLr921ZWVlISUlxeGcG63fv0NvbgSU5OTl46KGH7OrMAHidJyIiIiIiIqKewREaRERERBLxuwoRERERERGR40kdocFFwYmIiIiIiIiIiIiIyO2xQ4OIiIiIiIiIiIiIiNweOzSIiIiIiIiIiIiIiMjtsUODiIiIiIiIiIiIiIjcHjs0iIiIiIiIiIiIiIjI7bFDg4iIiIiIiIiIiIioB7S1tbk6hV6NHRoOUl1djeDgYJSWlro6FbLSO++8g/nz57s6DbfG+t07HDx4EFFRUTAaja5OpU9iO+i9eJ0nIiIiIiIiV2tra8Nnn32GXbt2sVPDDuzQcJDNmzdj3rx5CAsLM5WtXbsW0dHRUCgUmDBhgs2xMzIyEBkZCYVCgcjISBw4cMDqGLt27UJsbCz8/Pwgk8lQV1dncz4dXb9+HQkJCRg9ejQ8PDyQnJxsUxwhBNLS0hASEgKlUonY2FicP3/e7vxaWlqQlJSEcePGwdPTEwsXLuz0mRUrVuDMmTPIzc21e399lbvX79bWVjz//PMIDAyEj48P5s+fj6tXr1odp7CwEBqNBkqlEsOGDcPGjRshhLA6zp0++ugjxMfHIzAwEDKZDAUFBTbFKSsrw7x58+Dj44PAwECsWbMGer3e9P7cuXMhk8nwwQcf2J0zdebu7cCSTZs2YerUqfD29sbgwYMdEhMAzp8/j8cffxxhYWGQyWR46623bIrTU22X13kiIiIiIiJypfLycrz77rvIy8tDZWUlLly44OqUei12aDiATqfD7t278Ytf/MKsXAiBZ599FkuXLrU5dl5eHpYuXYrExER88803SExMxJIlS3Dq1Cmr4jQ3N2P27NlISUmxORdLWltbERQUhFdeeQXjx4+3Oc7rr7+ON954A++88w7OnDkDtVqNWbNm4ebNm3blZzAYoFQqsWbNGjzyyCMWP6NQKJCQkIBt27bZta++qjfU7+TkZBw4cAD79+9Hbm4uGhsbMXfuXBgMBskxGhoaMGvWLISEhODMmTPYtm0bfvvb3+KNN96w9rA6aWpqwrRp07BlyxabYxgMBsyZMwdNTU3Izc3F/v37kZGRgXXr1pl9bvny5azLTtAb2oEler0eixcvxi9/+Uu7Y3XU3NyMkSNHYsuWLVCr1TbH6am2y+s8ERERERERucKtW7fw5Zdf4g9/+AOqqqowaNAg/Pu//zvGjh3r6tR6L9HD6uvrBQBRX1/f6T2dTieKi4uFTqfr6bTskpGRIQIDA7t8PzU1VYwfP96m2EuWLBGzZ882K4uPjxdPPvmkTfGOHj0qAIja2lqbtu+ORqMRa9eutXo7o9Eo1Gq12LJli6mspaVFqFQqsXPnToflt2zZMrFgwQKL72VnZwu5XC6am5sdtr++wt3rd11dnfDy8hL79+83lZWXlwsPDw+RlZUlOc727duFSqUSLS0tprLNmzeLkJAQYTQaJcfpTklJiQAgzp49a/W2mZmZwsPDQ5SXl5vK9u3bJxQKhdn1tLS0VAAQly9fdkTK9C/u3g7uZs+ePUKlUjksXkehoaHizTfftHq7nm67jrrO99bvKkRERERERNSztFqt2LFjh0hNTRWpqaniww8/FE1NTa5Oy21112/QkXuP0BAC0De55mXFNDPHjh3DxIkTnXIK8vLyEBcXZ1YWHx+PEydOOGV/rlBSUgKtVmt2nAqFAhqNpseOc+LEiWhra8Pp06d7ZH/A7Se7mwwGl7xEH6rf+fn5aGtrM4sTEhKCsWPHWhUnLy8PGo0GCoXCLJdr1665xZoJeXl5GDt2LEJCQkxl8fHxaG1tRX5+vqksNDQUwcHBOH78uCvStJoQAka9wSWvvtQOeqOebruuuM4TERERERFR/2MwGHD8+HG8++670Gq1UCqVWLx4MZ544gl4e3u7Or1ez9PVCXSrrRlID7n755wh5Rog95H00dLSUrObjI6k1WoxdOhQs7KhQ4dCq9U6ZX+u0H4slo7zypUrPZKDj48PBg8ejNLSUmg0mh7ZZ7PRiHuPFfbIvu50ecY4+AwYIOmz7l6/tVot5HI5/P397Y7TcW2E9hjt74WHh0uO5QyWzpW/vz/kcnmn4xw2bJhbdMJIIdqMuPaqa27ch2ycCpm8b7SD3qin264rrvNERERERETUv1RVVeHjjz82rQ85evRozJ07F76+vi7OrO9w7xEavYROp8PAgQOdFl8mk5n9WwjRqawnDBo0yPRavXq1w+Pbe5wPPPCAKb9HH33U6v0rlUo0NzdbvV1f11vrty1xLOViqbwr77//vlk7cfQoCUt5WDpO1mXHc/d2sHr1arO65yhlZWVmcdPT0x0WuyvObLtsG0REREREROQMRqMRJ0+exM6dO3H16lUoFAosXLgQTz75JDszHMy9R2h4ed8eKeGqfUsUGBiI2tpap6ShVqs7PalaUVHR6WnenlBQUGD6u5+fn8Piti8oq9Vqcc8995jKrT3OzMxMtLW1Abh908paNTU1CAoKsno7W3l7eODyjHE9tr879y2Vu9dvtVoNvV6P2tpasye9KyoqMHXqVLtzATqPHurK/PnzMXnyZNO/hw0bJnn/UvK7c5Ho2tpatLW1dcqvp+uyPWReHgjZKP3n5Oh9S+Xu7WDjxo1Yv369o1NDSEiI2bU/ICDAYbFd0XZ7U9sgIiIiIiKi3qG2thaffPKJabaMkSNHYsGCBVCpVK5NrI9y7xEaMtntaZ9c8bLi6dCoqCgUFxc75RTExMTgyJEjZmWHDx+26maPo4waNcr0Cg4Odljc8PBwqNVqs+PU6/XIycmx6jhDQ0NN+Vl7I/ny5ctoaWlBVFSUVdvZQyaTwWfAAJe8rHn62d3rd3R0NLy8vMziXL9+HUVFRVbFiYmJwbFjx6DX681yCQkJ6TSdTVd8fX3N2oktHWvd5VdUVITr16+b5adQKBAdHW0qa2lpweXLl3u0LttDJpPBQz7AJa++1A6Cg4PN6p6jeHp6msV1ZIdGT7ddV1zniYiIiIiIqO8SQiA/Px87duxAaWkpvLy8MGfOHCQmJrIzw4nce4RGLxEfH48NGzZ0esr00qVLaGxshFarhU6nMz3lGhkZCblcLin22rVrMWPGDGzduhULFizAJ598gs8//xy5ublW5ajVaqHVanHp0iUAQGFhIXx9fTFixAi7b1C1H1djYyMqKytRUFAAuVyOyMhISdvLZDIkJycjPT0dERERiIiIQHp6Ory9vZGQkGBXbgBQXFwMvV6Pmpoa3Lx505TvhAkTTJ85fvw4Ro4ciXvvvdfu/fU17l6/VSoVfv7zn2PdunUYMmQIAgICsH79eowbNw6PPPKI5DgJCQl47bXXkJSUhJSUFFy8eBHp6el49dVX7Z4Cq6amBmVlZbh27faIswsXLgC4/WR5+wilu4mLi0NkZCQSExPxm9/8BjU1NVi/fj1WrFhhNmLq5MmTUCgUiImJsStnMufu7aArZWVlpvpnMBhM+Y0aNcquqan0er2pg0ev16O8vBwFBQUYNGiQ5A6Vnm67vM4TERERERGRozQ0NOAf//iH6V7riBEjsHDhQoc+CEhdED2svr5eABD19fWd3tPpdKK4uFjodLqeTstuU6ZMETt37jQr02g0AkCnV0lJiekzAMSePXu6jf3hhx+K0aNHCy8vLzFmzBiRkZFh9v6ePXvE3X6UqampFnPpuG+NRiOWLVsm5XDNWIobGhpqev/o0aOdjvtORqNRpKamCrVaLRQKhZgxY4YoLCw0+8yyZcuERqOxOr/Q0FCLOXYUFxcnNm/ebHXs/sLd67dOpxPPPfecCAgIEEqlUsydO1eUlZV1yvdu9fvcuXNi+vTpQqFQCLVaLdLS0oTRaDS9X1JSIgCIo0ePdhvnTu3HcOcrNTXV9Bkp9fvKlStizpw5QqlUioCAAPHcc8+JlpYWs8+sXLlSrFq1yqr8SBp3bweWLFu2zGJ+HetwaGioWV2Uor0t3PnqWIfdqe0K4bjrfG/+rkJERERERET2MRqN4ptvvhGbN28WqampYuPGjeJ//ud/hMFgcHVqvV53/QYdyYT418qZPaShoQEqlQr19fWd1mFoaWlBSUkJwsPDnbr4qjNkZmZi/fr1KCoqgofE9QlKS0sRERGB4uJiRERE2LzvtLQ0ZGdnIzs72+YYABAWFoa0tDQkJSXZFedOe/fuxaZNm1BcXAwvLy+b48TGxiI2NhZpaWmOSw5AUVERHn74YXz//fccDtYF1u/bsrOzsWjRIvzwww9mT+k7giPqd2VlJcaMGYOvvvoK4eHhjkuOAPSNdnAnnU6HgIAAZGZmYubMmQ6N7U5t15HX+d78XYWIiIiIiIhs19TUhIMHD+Lbb78FcHvdyYULFzp0av7+rLt+g4445ZSDPPbYY7h48SLKy8sxfPhwSdtkZWVh5cqVdt3kAoDPPvsMb7/9tl0xvvvuO/j6+uKZZ56xK44lWVlZSE9Pt6sz4+bNm7h8+TIOHjzowMxuu3btGv785z+zM6MbrN+3ZWVlISUlxeGdGY6q3yUlJdi+fTs7M5ykt7cDS3JycvDQQw85vDMDcK+2y+s8ERERERER2ePbb7/Fp59+iubmZnh4eECj0eCnP/0pBgwY4OrU+h2O0CAiIiKSiN9ViIiIiIiI+g+dTodDhw7h3LlzAIDg4GAsWrQI99xzj4sz63s4QoOIiIiIiIiIiIiIyAaXLl3CJ598gps3b0Imk2HatGmIjY2FpydvqbsSzz4REREREREREREREYDW1lYcPnwY+fn5AIAhQ4Zg4cKFkqefJudihwYRERERERERERER9XulpaX4+OOPUVdXBwCYPHkyHn74YcjlctcmRibs0CAiIiIiIiIiIiKifqutrQ1ffPEFTp48CQBQqVRYuHAhwsPDXZwZ3YkdGkRERERERERERETUL129ehUHDhxAdXU1AODBBx9EXFwcBg4c6OLMyBJ2aBARERERERERERFRv3Lr1i3k5OQgNzcXQggMGjQICxYsQEREhKtTo26wQ4OIiIiIiIiIiIiI+g2tVosDBw7gxo0bAIBx48bh0Ucfhbe3t4szo7vxcHUCfUV1dTWCg4NRWlrq6lTISu+88w7mz5/v6jTcGuu3+yksLMRPfvITNDU1uTqVfoPtoHc4ePAgoqKiYDQaXZ0KERERERERuRmDwYBjx45h165duHHjBry9vbFkyRI8/vjj7MzoJdih4SCbN2/GvHnzEBYWZipbu3YtoqOjoVAoMGHCBJtjZ2RkIDIyEgqFApGRkThw4IDVMVpbW/H8888jMDAQPj4+mD9/Pq5evWpzTu2uX7+OhIQEjB49Gh4eHkhOTrYpjhACaWlpCAkJgVKpRGxsLM6fP293fi0tLUhKSsK4cePg6emJhQsXdvrMihUrcObMGeTm5tq9v77KUv0uKyvDvHnz4OPjg8DAQKxZswZ6vd7q2O5UvwsLC6HRaKBUKjFs2DBs3LgRQgirYhw7dgzz5s1DSEgIZDIZPv74Y6vzAIDa2lokJiZCpVJBpVIhMTERdXV1pvfHjRuHSZMm4c0337QpPlnPWdf58+fP4/HHH0dYWBhkMhneeustm+Ls2rULsbGx8PPzg0wmM6sv1nBEO7Dko48+Qnx8PAIDAyGTyVBQUGBTnLtde+bOnQuZTIYPPvjA7pyJiIiIiIio76isrMQf//hHfPnllzAajRgzZgz+4z/+A5GRka5OjazADg0H0Ol02L17N37xi1+YlQsh8Oyzz2Lp0qU2x87Ly8PSpUuRmJiIb775BomJiViyZAlOnTplVZzk5GQcOHAA+/fvR25uLhobGzF37lwYDAabcwNu30gOCgrCK6+8gvHjx9sc5/XXX8cbb7yBd955B2fOnIFarcasWbNw8+ZNu/IzGAxQKpVYs2YNHnnkEYufUSgUSEhIwLZt2+zaV19lqX4bDAbMmTMHTU1NyM3Nxf79+5GRkYF169ZZFdud6ndDQwNmzZqFkJAQnDlzBtu2bcNvf/tbvPHGG1bl0tTUhPHjx+Odd96xars7JSQkoKCgAFlZWcjKykJBQQESExPNPrN8+XLs2LHD7nZMd+fM63xzczNGjhyJLVu2QK1W2xVn9uzZSElJsTmGo9qBJU1NTZg2bRq2bNlicwyp157ly5fzmk5EREREREQAAKPRiLy8PLz77rsoLy+HQqHAokWLsHTpUgwaNMjV6ZG1RA+rr68XAER9fX2n93Q6nSguLhY6na6n07JLRkaGCAwM7PL91NRUMX78eJtiL1myRMyePdusLD4+Xjz55JOSY9TV1QkvLy+xf/9+U1l5ebnw8PAQWVlZNuVliUajEWvXrrV6O6PRKNRqtdiyZYuprKWlRahUKrFz506H5bds2TKxYMECi+9lZ2cLuVwumpubHba/vsJS/c7MzBQeHh6ivLzcVLZv3z6hUCgstu2uuFP93r59u1CpVKKlpcVUtnnzZhESEiKMRqPkOB0BEAcOHLB6u+LiYgFAnDx50lSWl5cnAIjvvvvOVNba2ioUCoX44osvbMqPpHPmdb6j0NBQ8eabb9oV4+jRowKAqK2ttXpbZ7SDO5WUlAgA4uzZs1ZvK/XaU1paKgCIy5cvOyJlM731uwoREREREVF/0dTUJEpKSsTp06fFwYMHxY4dO0RqaqpITU0Vf/7zn0VdXZ2rUyQLuus36MitFwUXQkB3S+eSfSs9lZDJZJI+e+zYMUycONEpeeTl5eGFF14wK4uPj7dqSpL8/Hy0tbUhLi7OVBYSEoKxY8fixIkTiI+Pd1S6NikpKYFWqzXLT6FQQKPR4MSJE1i1apXTc5g4cSLa2tpw+vRpaDQap+8P+Ff9bnPNk/VKrwF21e+8vDyMHTsWISEhprL4+Hi0trYiPz8fM2fOlBTbnep3Xl4eNBoNFAqFWS4bNmxAaWkpwsPDJedkr7y8PKhUKkyePNlUNmXKFKhUKpw4cQKjR48GAMjlcowfPx7Hjx/HQw891GP5OZIQAm1tbS7Zt5eXl1tc592JO7UDS6Ree0JDQxEcHIzjx49j5MiRrkqXiIiIiIiInKilpQUVFRWoqKhAZWWl6c/GxsZOn/Xy8kJ8fDyio6Ml3wsg9+TWHRq6WzpM/mDy3T/oBKcSTsHbS9pCMKWlpWY3VxxJq9Vi6NChZmVDhw6FVqu1KoZcLoe/v79dcZylPQdLx3nlypUeycHHxweDBw9GaWlpj3Vo6NoMiHz1sx7Z152KN8bDWy6t+Vuq35bqpb+/P+RyudV1013qt1arNVsboT1G+3s9eSNXq9UiODi4U3lwcHCnYxo2bFivXqS6ra0N6enpLtl3SkoK5HK5pM868zrvTtypHVhizbWnt7cNIiIiIiIiuq21tdXUYdGx86K7qeoHDx6MoKAgBAcHIygoCCNHjoSfn18PZk3O4tYdGr2FTqfDwIEDnRb/zl5DIYRDehKtjdNxTrmnn34aO3futDuHjuw9zgceeMDUATJ9+nQcOnTIqv0rlUo0NzdbtU1/0FX9tvSzsaVuukv97ioXS+U9Qer5Zb3tGc6+zrsTe9vB+++/bzay7tChQ5g+fbrT8gPYNoiIiIiIiPoCvV6PyspKs9EWFRUVqK+v73IbPz8/U8dFe+dFUFCQ2cwD1Le4dYeG0lOJUwnWLQ7syH1LFRgYiNraWqfkoVarOz11WlFR0ekJ1bvF0Ov1qK2tNXuKvaKiAlOnTpUcp6CgwPR3R/Zoti+Cq9Vqcc8995jlZ81xZmZmmqauUSql//za1dTUICgoyOrtbKX0GoDija6Z7kvpNUDyZy3Vb7Va3Wnh7traWrS1tVldN92lfneVC9B59JCzqdVq3Lhxo1N5ZWVlp1xqampw77339lRqDufl5WXXItb27lsqZ17n3Ykj2sH8+fPNpksbNmyYQ/OTeu3p6Ws6ERERERERSdPW1oaqqqpOoy66+7170KBBpg6Ljp0X/eXhQ/pfbt2hIZPJJE/75EpRUVF47733nBI7JiYGR44cMVtn4PDhw1bdqI2OjoaXlxeOHDmCJUuWAACuX7+OoqIivP7665LjjBo1SnriVggPD4darcaRI0cQFRUF4HaPbE5ODrZu3So5TmhoqM05XL58GS0tLab99wSZTCZ52idXslS/Y2JisGnTJly/ft3UCXX48GEoFApER0dLju1O9TsmJgYpKSnQ6/WmaYgOHz6MkJCQTlPwOFtMTAzq6+tx+vRpTJo0CQBw6tQp1NfXdzo3RUVFeOKJJ3o0P0eSyWSSp31yJWde592JI9qBr68vfH19nZaflGtPS0sLLl++3KPXdCIiIiIiIjJ369YtVFdXm422qKioQG1trWk2gDt5e3ubdVi0/+nt7f73iKlnuP/d1F6gfcHUO58Qv3TpEhobG6HVaqHT6UwjHCIjIyXfwFu7di1mzJiBrVu3YsGCBfjkk0/w+eefIzc3V3J+KpUKP//5z7Fu3ToMGTIEAQEBWL9+PcaNG4dHHnnEqmO1pP24GhsbUVlZiYKCAsjlckRGRkraXiaTITk5Genp6YiIiEBERATS09Ph7e2NhIQEu/MrLi6GXq9HTU0Nbt68acp3woQJps+0Lxzbm590dxZL9TsuLg6RkZFITEzEb37zG9TU1GD9+vVYsWKFVaN33Kl+JyQk4LXXXkNSUhJSUlJw8eJFpKen49VXX7VqyqnGxkZcunTJ9O+SkhIUFBQgICAAI0aMkBTj/vvvx+zZs7FixQq8++67AICVK1di7ty5pgXBgdvrOpSXlzukHVP3nHmd1+v1KC4uNv29vLwcBQUFGDRokFUdyVqtFlqt1lT/CgsL4evrixEjRiAgIEBSDEe1A0tqampQVlaGa9euAQAuXLgA4Paoi/aRencj9dpz8uRJKBQKxMTE2JUzERERERER3Z3BYEBNTU2nNS5qampgNBotbqNUKs06LNo7MXx8fHo4e+p1RA+rr68XAER9fX2n93Q6nSguLhY6na6n07LblClTxM6dO83KNBqNANDpVVJSYvoMALFnz55uY3/44Ydi9OjRwsvLS4wZM0ZkZGSYvb9nzx5xtx+lTqcTzz33nAgICBBKpVLMnTtXlJWVdcp32bJldz3WO1k6xtDQUNP7R48e7XTcdzIajSI1NVWo1WqhUCjEjBkzRGFhodlnli1bJjQajdX5hYaGWsyxo7i4OLF582arY/cXlur3lStXxJw5c4RSqRQBAQHiueeeEy0tLWaf6W31+9y5c2L69OlCoVAItVot0tLShNFoNL1fUlIiAIijR492GaO9vt/56rjv1NRUszZiSXV1tXjqqaeEr6+v8PX1FU899ZSora01+0x6erqIj4/vNg45jrOu8+316s5Xx+udlHaQmppqMU7HffdUO7Ck/RjufKWmppo+I+U6L+Xas3LlSrFq1Sqr8pOqN39XISIiIiIisofBYBCVlZWiuLhYZGdni7/97W/i97//vXjttddEamqqxVd6err4wx/+ID755BORl5cnLl26JBoaGsx+zyQSovt+g45kQnQxvsdJGhoaoFKpUF9f3+lJ7paWFpSUlCA8PLzXzX+WmZmJ9evXo6ioCB4eHpK2KS0tRUREBIqLixEREWHzvtPS0pCdnY3s7GybYwBAWFgY0tLSkJSUZFecO+3duxebNm1CcXGxVXPW3yk2NhaxsbFIS0tzXHK4PWXPww8/jO+//x4qlcqhsfsK1u/bsrOzsWjRIvzwww9mT+lbqz2HvXv32hyjtbUVERER2LdvH6ZNm2ZzHJKO7eA2R7UDSxxxna+srMSYMWPw1VdfITw83HHJ/Utv/q5CREREREQkhdFoRF1dndloi/bFug0Gg8Vt5HK5aUHujlNG+fn52T3in/qH7voNOuKUUw7y2GOP4eLFiygvL8fw4cMlbZOVlYWVK1fadZMLAD777DO8/fbbdsX47rvv4Ovri2eeecauOJZkZWUhPT3drs6Mmzdv4vLlyzh48KADM7vt2rVr+POf/8zOjG6wft+WlZWFlJQUu2/i5uTk4NixY3bFuHLlCl555RV2ZvQgtoPbHNUO7uSo63xJSQm2b9/ulM4MIiIiIiKivkQIgfr6+k5rXFRVVaGtrc3iNp6enhanivLz85P88B+RPThCg4iIiEgiflchIiIiIqLeRgiBhoYGs9EW7X/q9XqL2wwYMACBgYGdFugePHgwOy7IKThCg4iIiIiIiIiIiKifEEKgsbHRbLRF+99bW1stbuPh4YHAwMBOoy78/f0xYMCAHj4CortjhwYRERERERERUR/QfjOzuroaVVVVqK6uRnV1Ndra2nD//fdj3LhxUCqVrk6TiBygqamp01RRlZWV0Ol0Fj8vk8kwZMgQs06LoKAgDBkyhB0X1KuwQ4OIiIiIiIiIqBdpbW01dVZ07Liorq7ucvqYkpISfPbZZ7j//vsRFRWF8PBwThtD1AvodLpOoy0qKyvR1NRk8fMymQz+/v6d1rgYMmQIPD15K5h6P9ZiIiIiIiIiIiI3YzAYUFtba7HjorGxscvt2m9mDhkyxPRqa2tDQUEBKioqUFRUhKKiIgwePBgPPvggJkyY0O1c5UTUM1paWjqtcVFRUdFtex88eHCnNS4CAwPh5eXVg5kT9Sx2aBARERERERERuYAQAjdv3jQbYdHecVFbWwshRJfb+vj4IDAw0KzjYsiQIfD397f4FHZMTAyuX7+Os2fP4ty5c6irq8OXX36Jo0eP4r777sODDz6IiIgIjtogcrLW1lZUVlZ26rxoaGjochuVSmU22iIoKAhBQUGQy+U9mDmRe2CHBhERERERERGRE7W0tJh1WkiZIgoAvLy8TB0Vd3ZeDBw40KocZDIZQkJCEBISglmzZqG4uBhff/01ysrKcOHCBVy4cAF+fn6IiopCVFQUBg8ebOdRE/VvbW1tZh0X7Z0XdXV1XW7j6+vbaY2LoKAgq9s7UV/GDg0iIiIiIiIiIjvdunXLbIqoji9rpojq2HHh6+sLmUzm8FzlcjkmTJiACRMmoLKyEvn5+fjmm2/Q0NCAnJwc5OTkYNSoUYiOjsZ9993HBYOJunHr1i1UVVV1miqqtra2y218fHw6rXERFBQEpVLZg5kT9U7s0HCQ6upq3H///Th9+jTCwsJcnQ514eDBg/jVr36F/Px8DqO1Auu3+yksLMSjjz6KCxcuwMfHx9Xp9AtsB33L+vXrodfr8bvf/c7VqRAREVEv0j5F1J0LcUuZImrQoEGdpocKDAzE4MGDXbpQb1BQEGbPno1HHnkE3377Lb7++muUlJTg0qVLuHTpEgYNGoQJEybgwQcfREBAgMvyJHK1W7duoaamptMC3TU1NV22faVS2WmNi6CgIP4eT2QH3tF1kM2bN2PevHlmN7nKysowb94807yWa9as6XYoqSXnz5/H448/jrCwMMhkMrz11ls25dfa2ornn38egYGB8PHxwfz583H16lWr4xQWFkKj0UCpVGLYsGHYuHFjt1/YpProo48QHx+PwMBAyGQyFBQU2BTnbud87ty5kMlk+OCDD+zOuT9xVv0GgIyMDERGRkKhUCAyMhIHDhywOoYj6ndLSwuSkpIwbtw4eHp6YuHChVbn0W779u0IDw/HwIEDER0djePHj1sdY9OmTZg6dSq8vb0tDvUeN24cJk2ahDfffNPmPMk6ltrB2rVrER0dDYVCgQkTJtgc2xHtYNeuXYiNjYWfnx9kMlm3w5itcf36dSQkJGD06NHw8PBAcnKyQ+ICrs35pZdewp49e1BSUuKQfRIREVHfdv36dfzxj39Eeno63njjDfz5z3/GP//5T5w8eRIXL1403dCUy+W45557MHbsWGg0GvzsZz/DihUr8PLLL2P9+vVYvnw55s+fj2nTpmHMmDEIDAx0aWdGR56enhg3bhyWLVuG559/HtOmTYOPjw8aGxuRm5uL3/3ud/jTn/6EoqIi3Lp1y9XpEjmNwWBAZWUliouLkZ2djb/97W/4/e9/j/T0dGzfvh1///vfcezYMXz77beorq6GEAIDBw7E8OHDER0djUcffRTPPPMM1q9fj5deegnLly/HnDlzMGnSJISFhbEzg8hO7vG/Zi+n0+mwe/duZGZmmsoMBgPmzJmDoKAg5Obmorq6GsuWLYMQAtu2bZMcu7m5GSNHjsTixYvxwgsv2JxjcnIyPv30U+zfvx9DhgzBunXrMHfuXOTn50seOtrQ0IBZs2Zh5syZOHPmDL7//nskJSXBx8cH69atszk3AGhqasK0adOwePFirFixwqYYUs/58uXLsW3bNjz99NN25dxfOLN+5+XlYenSpfj1r3+NRYsW4cCBA1iyZAlyc3MxefJkyXEcUb8NBgOUSiXWrFmDjIwMyfu+01//+lckJydj+/btmDZtGt599108+uijKC4uxogRIyTH0ev1WLx4MWJiYrB7926Ln1m+fDlWr16NDRs2cAi4k1lqB8DtJ/SeffZZnDp1CufOnbMptqPaQXNzM2bPno3Zs2djw4YNNuViSWtrK4KCgvDKK684vAPNlTkHBwcjLi4OO3fuxNatWx22byIiIupbhBD46quvkJWVBYPBAOB/p4iytCC3s6aI6mlDhgzBrFmz8NBDD+HChQv4+uuvcenSJZSUlKCkpATe3t4YP348HnzwQQQFBbk6XSKbGI1G1NbWmo22qKysRFVVlam930kul1ucKqqvtH2i3kAmHPF4vRUaGhqgUqlQX18PPz8/s/daWlpQUlJierK5t/joo4+watUqVFZWmsoOHTqEuXPn4scff0RISAgAYP/+/UhKSkJFRUWnY5ciLCwMycnJVj8dW19fj6CgIPzlL3/B0qVLAQDXrl3D8OHDkZmZifj4eElxduzYgQ0bNuDGjRtQKBQAgC1btmDbtm24evWqQy7cpaWlCA8Px9mzZ61+2lnqOb9y5QrCwsJw+fJljBw50u6c+zpn1u+lS5eioaEBhw4dMpXNnj0b/v7+2Ldvn6QYjqrfHSUlJaGurg4ff/yx1dtOnjwZDz74IHbs2GEqu//++7Fw4UJs3rzZ6nh79+5FcnKyxSfX9Xo9/Pz8kJmZiYceesjq2CSdpXbQUVpaGj7++GObRpc5oh10lJ2djZkzZ6K2ttbhCznGxsZiwoQJNo8W7Iqrcv7Tn/6EX/3qVygrK5Mcr7d+VyEiIiLrtba24tNPP0VRUREA4L777sOsWbMQEBDQLx8oqq2txdmzZ3H27FncvHnTVD5ixAhER0cjMjISXl5eLsyQyDKj0Yj6+vpOa1xUVVV1OdrIy8vLbIqo9j9VKhU7LoicpLt+g47ceoSGEAJCp3PJvmVKpeQL1LFjxzBx4kSzsry8PIwdO9Z0sxcA4uPj0draivz8fMycOdOh+XYnPz8fbW1tiIuLM5WFhIRg7NixOHHihOQbvnl5edBoNKbODOD2MW3YsMHUEeFKUs95aGgogoODcfz4cdd2aAgBtDW7Zt9e3oAb1O+8vLxOI4/i4+OtulnqqPrtCHq9Hvn5+Xj55ZfNyuPi4nDixAmH708ul2P8+PE4fvx4r+3QEELAaHTNdd7Dw77rvKM4oh2QbSZNmoQff/wRV65cQWhoqKvTISIiIjdy48YN/O1vf0N1dTVkMhkeeeQRTJ06tV/fyPT398dDDz0EjUaDS5cuIT8/HxcvXkRZWRnKyspw6NAh/Nu//Ruio6MxdOhQV6dL/ZAQAg0NDZ3WuKisrERbW5vFbTw9PREYGNhp1IVKpeLaq0Ruyr07NHQ6XHgw2iX7Hv11PmTe3pI+W1paanZjFwC0Wm2n/8D9/f0hl8uh1WodlqcUWq0Wcrkc/v7+ZuVDhw61KhetVttpIdz2Y9RqtS7v0LDmnA8bNgylpaU9mJ0Fbc1AesjdP+cMKdcAubQ5G51Zvy3FsaVeOqJ+O0L7sFR7j8kablGX7WA06pCdM84l+47VFGLAANuv847iiHZAthk2bBiA2z9fdmgQERFRu7Nnz+Kf//wnbt26BV9fXyxevNiq6WP7ugEDBmD06NEYPXo0GhoacPbsWXz99deor6/H6dOncfr0aQwbNsw0aoOjWsnRhBC4efOm2WiLyspKVFZWorW11eI2AwYMQGBgYKdRF/7+/uy4IOpl3LpDo7fQ6XQW/4O29OSGEMJtnuiwJZc7P98+Y5nUOO+//z5WrVpl+vehQ4cwffp0q3KwJj/A8nEqlUo0N7todEQv4+z6balOOaKNuLKtOeuYLGFd7hldtQNH6ck6051BgwaZ/v70009j586dDombnp6O9PR007+tXVOmO/bkrFQqAYBtiIiIiADcHnH9z3/+E9988w0A4N5778XPfvYzLuDbDT8/P2g0GkyfPh0//PAD8vPzceHCBZSXl6O8vBz/+Mc/EBgYCH9/f6hUqk4vX1/ffjl9F0nX2NjYaaqoyspKtLS0WPy8h4cHhgwZ0mmNi/46VRxRX+TWHRoypRKjv8532b6lCgwMRG1trVmZWq3GqVOnzMpqa2vR1tbW40Mv1Wo19Ho9amtrzZ5ir6iowNSpU62Kc+cTwxUVFQAg+Zjmz59vtsht+9OxjmDNOa+pqXH9wmVe3rdHSrhq3xI5s353VaesjeGI+u0IgYGBGDBggN3HZI2amhrce++9TondEzw8lIjVFLps31JZageO4oh24Cgd1wCxZa2nrqxevRpLliwx/duRo13sybmmpgYAXP//AREREblcZWUl/va3v6GyshIymQwzZ87ET3/6Uz65LZGHhwdGjRqFUaNGobGxEQUFBTh79iyqq6tRVVWFqqoqi9vJZDL4+flZ7Oxof3GER//Q3Nxscaqorh4+kslkCAgI6DRVVEBAADw93fp2JxHZya1buEwmkzztkytFRUXhvffeMyuLiYnBpk2bcP36ddxzzz0AgMOHD0OhUCA6umen0YqOjoaXlxeOHDliuqF0/fp1FBUV4fXXX5ccJyYmBikpKdDr9ZDL5QBuH1NISEinqai64uvrC19fX6uPQWp+Us55S0sLLl++jKioKKfkIZlMJnnaJ1dyZv2OiYnBkSNHzNYPOHz4sFUdEY6q344gl8sRHR2NI0eOYNGiRabyI0eOYMGCBU7ZZ1FREZ544gmnxO4JMplM8rRPrmSpHTiKI9qBo4waNcopcQMCAhAQEOCU2PbkXFRUBC8vLzzwwAMOzIiIiIh6m2+++QYHDx5EW1sbBg0ahMcff9zlUyr3ZoMGDcJPf/pT/PSnP8XNmzdx48YN1NfXW3y1L9ZcX1/fZTyFQoHBgwd32eHh6+vLjqdeRKfTmXVYtHdiNDU1dbmNv7+/2WiL4OBgDBkyhIvQE/VTbt2h0Vu0L4zd8QnxuLg4REZGIjExEb/5zW9QU1OD9evXY8WKFVY9QarX61FcXGz6e3l5OQoKCjBo0CDJN3FUKhV+/vOfY926dRgyZAgCAgKwfv16jBs3Do888ojkXBISEvDaa68hKSkJKSkpuHjxItLT0/Hqq6/aPTVKTU0NysrKcO3a7RELFy5cAHD7yWW1Wi0phtRzfvLkSSgUCsTExNiVc3/hzPq9du1azJgxA1u3bsWCBQvwySef4PPPP0dubq7kGI6q38DtaXD0ej1qampw8+ZN05PfEyZMkBzjxRdfRGJiIiZOnIiYmBjs2rULZWVlWL16tVW5lJWVmdqFwWAw5TJq1CjTFDulpaUoLy+3+jjJepbaAQBcunQJjY2N0Gq10Ol0pp9TZGSkqeP3bhzRDoDba3FotVpcunQJAFBYWAhfX1+MGDHC7s6E9uNqbGxEZWUlCgoKIJfLERkZaVdcV+d8/PhxTJ8+3TT1FBEREfUvbW1tOHToEL7++msAQHh4OB5//HGzKS3JPt091Gg0GtHU1IS6urouOzx0Oh1aW1tx48YN3Lhxw2IcDw8P+Pr6dtvpoVAonHmYZEFra2unaaIqKipw8+bNLrcZPHhwp6miAgMDJf9uRUT9g0y0L4LQQxoaGqBSqVBfX9/pxmdLSwtKSkoQHh7e64YUxsTEICkpyWx9iLKyMvzHf/wHvvzySyiVSiQkJOC3v/2t2X+kMpkMe/bsQVJSksW4paWlFp8M0Wg0yM7OBgDs3bsXy5cvR3c/ypaWFvznf/4nPvjgA+h0Ojz88MPYvn07hg8fbvpMbGwswsLCsHfv3i7jFBYW4v/+3/+L06dPw9/fH6tXrzbr0GjP9+jRo4iNje0yzp3aj+FOqampSEtLAwAkJSWhtLTUdNyWSDnnq1atgkwmc9jc8P2Bs+o3APz973/H//f//X/44YcfcO+992LTpk342c9+Znq/J+t3WFgYrly50qm8fd9S6/f27dvx+uuv4/r16xg7dizefPNNzJgxw/R+Wloa9u7d2+1i3klJSfjTn/7Uqbzjvjdv3oycnBxkZWV1GYccx1I7iI2NRU5OTqfPlpSUmEau9VQ7SEtLw2uvvdapvOO+pbQDSyx1WoeGhprqcHZ2NmbOnGl23FK4MmcAGD16NF577TU8+eSTkuP25u8qRERE9L+qq6vxt7/9zXSTXKPRQKPR8El/N9Pa2oqGhoYuOz0aGhpgNBrvGmfgwIFQqVRddnoMGjSIP3sb6fV604LcHTsvuht14+fnZzbaIigoCEFBQex4Iurnuus36IgdGg6SmZmJ9evXo6ioSPJ/gqWlpYiIiEBxcTEiIiJs3ndaWhqys7O7vdEvRVhYGNLS0rq96XY32dnZWLRoEX744Qezp5gdITY2FrGxsaYODltUVlZizJgx+OqrrziE2Aqs37c5qn6352DtDdqOWltbERERgX379mHatGk2xyHp2A66tnfvXmzatAnFxcUOH/btrJz/+c9/4j//8z9x7tw5q+bY7c3fVYiIiPqbpqYm0/oNNTU1CAgIQEREBEpLS3Hw4EHo9Xp4e3vj8ccf79Xr0vVnRqMRjY2NqK+v77LTo6vFozvy8PAwreXRVadHfx8l0NbWhqqqqk5TRdXV1XW5zaBBgzqtcREUFMTv0URkkdQODaunnCovL8d//dd/4dChQ9DpdLjvvvuwe/fuHl8Xwt089thjuHjxIsrLy82eCu9OVlYWVq5caddNLgD47LPP8Pbbb9sV47vvvoOvry+eeeYZu+JkZWUhJSXF4Z0ZN2/exOXLl3Hw4EG74pSUlGD79u3szLAS6/dtjqrfOTk5OHbsmF0xrly5gldeeYWdGT2I7aBrWVlZSE9Pd3hnhjNzbmpqwp49e7hgIBERUS9nNBpRV1dn6riorKw0/V2n03W77YgRI/DEE09YNW0uuZf2jgg/P78uv6O3tLSgoaGhy06P9lEedXV1qKurszhqHwCUSqWpc8NSp4ePj0+fGOVx69YtVFdXd5oqqra2tssR497e3p3WuAgKCoJ3L1gXl4h6H6tGaNTW1iIqKgozZ87EL3/5SwQHB+Py5csICwuT/DRDXx2hQURERH0fv6sQERG5RmtrK6qrq02dFe2v6upqGAyGLrdTqVQIDAyEv78/SktLUVVVBaVSiYkTJyI2NhYDBgzowaMgd2QwGEyjPLrq9Ghtbb1rnAEDBphGeVjq9PDz83OrUR4GgwHV1dWdFuiurq7usuNCqVR2Gm0RHBwMHx+fHs6eiPoip4zQ2Lp1K4YPH449e/aYyu42V3Zra6vZhb+hocGaXRIRERERERFRPyCEQGNjo8XRFt3dS/D09MSQIUMQGBho9hoyZEinG8gGg4GdGGRmwIABpk6HrrS0tJh1cNzZ6XHz5k0YDAbU1taitra2yzje3t5mnRx3dnr4+PhYXAvOHkajETU1NZ3WuKiqqupy/RGFQmFxqqhBgwY5PD8iImtZ1aHxj3/8A/Hx8Vi8eDFycnIwbNgw/Md//AdWrFjR5TabN2+2uOAnEREREREREfU/BoMBNTU1nUZbVFVVdfskvLe3NwIDAxEUFGTWcaFSqSRP9cPODLLFwIEDMXDgQAwdOtTi+waDATdv3uy200Ov16O5uRnNzc24fv26xTgdO1csdXr4+fl1Oc1rx46Ljot0V1VVdTmKSS6Xm00R1f6nn58fOy6IyG1ZNeVU+9QKL774IhYvXozTp08jOTkZ7777bpfzW1saoTF8+HBOOUVERES9Dr+rEBERSafT6UzTRHUcbVFbW9vlk+EymQz+/v6dRlsEBgZyPn7qtYQQkkZ5SOHj42PWwdHU1GRqX111XHh6enbquAgODoafn1+fWPeDiPoGp0w5ZTQaMXHiRKSnpwMAoqKicP78eezYsaPLDg2FQgGFQmHNboiIiIiIiIioFzAajWhoaLA42qKxsbHL7by8vEwdFR1HXAQEBMDT06pbFURuTyaTQalUQqlUQq1WW/zMrVu37jrKo62tDU1NTWhqasK1a9c6xWjvuOj4Cg4OxuDBg9lxQUR9hlXfEu655x5ERkaald1///3IyMhwaFJERERERERE5D7a2tpM00R1HG1RXV2Ntra2Lrfz9fW1ONqCU9oQmfP09IS/vz/8/f0tvi+EgE6n67Rgube3t6njwprp14iIeiurOjSmTZuGCxcumJV9//33CA0NdWhSRERERERERNTzmpqaLI626G6hYw8PDwQEBHRa22LIkCGcopHIQWQyGby9veHt7Y177rnH1ekQEbmMVR0aL7zwAqZOnYr09HQsWbIEp0+fxq5du7Br1y5n5UdEREREREREDmQ0GlFXV9dptEVVVRV0Ol2X2w0cONDiaAt/f38utk1EREQ9wqoOjf/zf/4PDhw4gA0bNmDjxo0IDw/HW2+9haeeespZ+fUa1dXVuP/++3H69GmEhYW5Oh3qwsGDB/GrX/0K+fn5HIZpBdZv91NYWIhHH30UFy5cgI+Pj6vT6RfYDnoHXueJiIj+V2trq2lR7o6v6urqLhcPBgCVStVptEVgYCB8fHw4TRQRERG5lNW/6c+dOxeFhYVoaWnBt99+ixUrVjgjr15n8+bNmDdvntlNrrKyMsybNw8+Pj4IDAzEmjVroNfrrY6dkZGByMhIKBQKREZG4sCBA1bH2LVrF2JjY03zlNbV1Vkdw5Lr168jISEBo0ePhoeHB5KTk22KI4RAWloaQkJCoFQqERsbi/Pnz1sd527nfO7cuZDJZPjggw9syrO/clb9Pn/+PB5//HGEhYVBJpPhrbfesim/1tZWPP/886ZfsubPn4+rV69aFaOlpQVJSUkYN24cPD09sXDhQptyAYDt27cjPDwcAwcORHR0NI4fP251jE2bNmHq1Knw9vbG4MGDO70/btw4TJo0CW+++abNeZJ1LLWDtWvXIjo6GgqFAhMmTLA5tjtd5wsLC6HRaKBUKjFs2DBs3LgRQgibYnX00UcfIT4+HoGBgZDJZCgoKLApDq/zRERE5oQQuHnzJkpKSnD69GlkZmbiz3/+M9544w1s3rwZu3btwkcffYRjx46huLgYFRUVMBgM8PT0xNChQ/HAAw9Ao9Hg8ccfx6pVq5CSkoIXXngBTz/9NGbPno2JEyciLCwMgwYNYmcGERERuZxVIzTIMp1Oh927dyMzM9NUZjAYMGfOHAQFBSE3NxfV1dVYtmwZhBDYtm2b5Nh5eXlYunQpfv3rX2PRokU4cOAAlixZgtzcXEyePFlynObmZsyePRuzZ8/Ghg0brDq+7rS2tiIoKAivvPKKXTdWX3/9dbzxxhvYu3cv7rvvPvz3f/83Zs2ahQsXLsDX11dSDKnnfPny5di2bRuefvppm/PtT5xZv5ubmzFy5EgsXrwYL7zwgs05Jicn49NPP8X+/fsxZMgQrFu3DnPnzkV+fr7koe8GgwFKpRJr1qxBRkaGzbn89a9/RXJyMrZv345p06bh3XffxaOPPori4mKMGDFCchy9Xo/FixcjJiYGu3fvtviZ5cuXY/Xq1diwYQOH+DuZpXYA3L6B8Oyzz+LUqVM4d+6cTbHd6Trf0NCAWbNmYebMmThz5gy+//57JCUlwcfHB+vWrbMpZrumpiZMmzYNixcvtvlhCF7niYioPzMYDKZFue98tba2drld+4LBd4624OLBRERE1BvJhCMeu7RCQ0MDVCoV6uvr4efnZ/ZeS0sLSkpKTE829xYfffQRVq1ahcrKSlPZoUOHMHfuXPz4448ICQkBAOzfvx9JSUmoqKjodOxdWbp0KRoaGnDo0CFT2ezZs+Hv7499+/ZZnWt2djZmzpyJ2tpai0992yM2NhYTJkyw+il7IQRCQkKQnJyM//qv/wJwu6Nk6NCh2Lp1K1atWiUpjtRzfuXKFYSFheHy5csYOXKkVbn2R86s3x2FhYUhOTnZ6lE+9fX1CAoKwl/+8hcsXboUAHDt2jUMHz4cmZmZiI+PtzqXpKQk1NXV4eOPP7Z628mTJ+PBBx/Ejh07TGX3338/Fi5ciM2bN1sdb+/evUhOTrb4tL1er4efnx8yMzPx0EMPWR2bpLPUDjpKS0vDxx9/bNOoA3e6zu/YsQMbNmzAjRs3oFAoAABbtmzBtm3bcPXqVYc8lVlaWorw8HCcPXvW6lEt7nCd763fVYiIqPfQ6XSmaaI6rm9RW1sLo9FocRuZTAZ/f3+L61t4e3v38BEQERERWa+7foOO3HqEhhACt/SWv7A5m6fcQ/KNm2PHjmHixIlmZXl5eRg7dqzphgsAxMfHo7W1Ffn5+Zg5c6ak2Hl5eZ2eXI+Pj7d5ah53VFJSAq1Wi7i4OFOZQqGARqPBiRMnJHdoSD3noaGhCA4OxvHjx13aoSGEgO5W1wvuOZPSU+kW9dsR8vPz0dbWZlZ/QkJCMHbsWJw4ccKmDg1b6fV65Ofn4+WXXzYrj4uLw4kTJxy+P7lcjvHjx+P48eO9tkNDCIHmLn4xdzZvD/uu847iTtf5vLw8aDQaU2dGey4bNmwwdUS4Um+7zhMREXXFaDSioaHB4miLxsbGLrfz8vJCYGBgpxEXAQEB8PR061/viYiIiBzCrb/x3NIbsWttjkv2vfJtDbwU0qZwKS0tNbu5AgBarRZDhw41K/P394dcLodWq5Wch6U4Q4cOtSqGu2s/FkvHeeXKFaviSD3nw4YNQ2lpqW0JO4julg6TP5A+nYwjnUo4BW8vaU9qObN+O4JWq4VcLoe/v79ZuSvaSVVVFQwGQ4+2WXeoy/ZoNhpx77FCl+z78oxx8JE4VZelduAo7nSd12q1nRY8b89Nq9W6vEOjt13niYiI2traTNNEdRxtUV1djba2ti638/X1tTjaon2tLCIiIqL+yq07NHoLnU5ncdoJS180hRBWfwG98/O2xHCEQYMGmf7+9NNPY+fOnQ6N74jjlHrOlUolmpubrU+yH3J2/XYWV+bSk22WdblndNUOHMVdrvNd5WKpvCvvv/++2ci6Q4cOYfr06U7LD+B1noiIXK+pqcniaIva2tout/Hw8MCQIUM6dVoMGTKE0xoSERERdcGtOzQ85R5Y+bbGZfuWKjAwsNMXVbVajVOnTpmV1dbWoq2trdPTpd1Rq9WdnjqtqKiwKoajdJwb3pY1ErqiVqsB3H7y9p577jGVW3uc1pzzmpoaBAUF2ZG1/ZSeSpxKOHX3Dzpp31I5s347glqthl6vR21trdkojYqKCkydOrVHcwkMDMSAAQN6tM3W1NTg3nvvdUrsnuDt4YHLM8a5bN9SWWoHjuJO1/mucgE6j6Lryvz5880WMx82bJhD8+tN13kiIupbjEYj6urqOo22qKqqgk7X9VSyAwcOtDjawt/fHwMkjhYlIiIiotvcukNDJpNJnvbJlaKiovDee++ZlcXExGDTpk24fv266Sb94cOHoVAoEB0dLTl2TEwMjhw5Yja/+uHDh3v8Ri0AjBo1yilxw8PDoVarceTIEURFRQG4vRZBTk4Otm7dKjmO1HPe0tKCy5cvm/blKjKZTPK0T67kzPrtCNHR0fDy8sKRI0ewZMkSAMD169dRVFSE119/vUdzkcvliI6OxpEjR7Bo0SJT+ZEjR7BgwQKn7LOoqAhPPPGEU2L3BJlMJnnaJ1ey1A4cxZ2u8zExMUhJSYFer4dcLjflEhIS0mkqqq74+vrC19fXafn1pus8ERH1Tq2traZFuTu+qqurYTAYutxu8ODBFjsufHx83GYUMxEREVFv59YdGr1F+4KpHZ8Qj4uLQ2RkJBITE/Gb3/wGNTU1WL9+PVasWGHV6Ia1a9dixowZ2Lp1KxYsWIBPPvkEn3/+OXJzc63KUavVQqvV4tKlSwCAwsJC+Pr6YsSIEQgICLAq1p3aR240NjaisrISBQUFkMvliIyMlLS9TCZDcnIy0tPTERERgYiICKSnp8Pb2xsJCQmS85B6zk+ePAmFQoGYmBirjrO/cmb91uv1KC4uNv29vLwcBQUFGDRokOQONJVKhZ///OdYt24dhgwZgoCAAKxfvx7jxo3DI488YtWxFhcXQ6/Xo6amBjdv3jTV7QkTJkiO8eKLLyIxMRETJ05ETEwMdu3ahbKyMqxevdqqXMrKylBTU4OysjIYDAZTLqNGjTJN/1ZaWory8nKrj5OsZ6kdAMClS5fQ2NgIrVYLnU5n+jlFRkaaOgTuxp2u8wkJCXjttdeQlJSElJQUXLx4Eenp6Xj11VftvhHTXp+vXbsGALhw4QKA26Mu2kfq3Q2v80RE5ChCCDQ2NlocbdHQ0NDldp6enl1OEyX1/34iIiIisoPoYfX19QKAqK+v7/SeTqcTxcXFQqfT9XRadpsyZYrYuXOnWdmVK1fEnDlzhFKpFAEBAeK5554TLS0tZp8BIPbs2dNt7A8//FCMHj1aeHl5iTFjxoiMjAyz9/fs2SPu9qNMTU0VADq9Ou5bo9GIZcuW3fVY72QpbmhoqOn9o0ePCgCipKSkyxhGo1GkpqYKtVotFAqFmDFjhigsLDT7zLJly4RGo+k2FynnfOXKlWLVqlXWHma/5qz6XVJSYrH+dPw5S6nfOp1OPPfccyIgIEAolUoxd+5cUVZWZvYZKfU7NDTUYj535nv06NFu4/z+978XoaGhQi6XiwcffFDk5OSYvZ+ammrWRixZtmyZxVw67js9PV3Ex8d3G4ccx1I70Gg0Fn9OHa93ve06f+7cOTF9+nShUCiEWq0WaWlpwmg0mt6X2g7u1H4Md75SU1NNn+kN1/ne/F2FiKg/unXrlqioqBDFxcXi2LFj4qOPPhK7du0S6enpIjU1tcvX66+/Lv74xz+Kf/zjH+LEiRPi+++/FzU1NcJgMLj6kIiIiIj6pO76DTqSCfGv1T57SENDA1QqFerr6zs9yd3S0oKSkhKEh4f3ukXQMjMzsX79ehQVFcFD4rzspaWliIiIQHFxMSIiImzed1paGrKzs5GdnW1zDAAICwtDWloakpKS7Ipzp71792LTpk0oLi6Gl5eXzXFiY2MRGxuLtLQ0m2NUVlZizJgx+OqrrxAeHm5znP6G9fu27OxsLFq0CD/88IPZU/rWas9h7969NsdobW1FREQE9u3bh2nTptkch6RjO7jNUe3Akt5wne/N31WIiPoynU5nmiaq44iL2tpaGI1Gi9vIZDL4+/tbnCbK29v9p4YlIiIi6ku66zfoiFNOOchjjz2Gixcvory8HMOHD5e0TVZWFlauXGnXTS4A+Oyzz/D222/bFeO7776Dr68vnnnmGbviWJKVlYX09HS7OjNu3ryJy5cv4+DBg3blUlJSgu3bt7Mzw0qs37dlZWUhJSXF7pu4OTk5OHbsmF0xrly5gldeeYWdGT2I7eA2R7WDO/E6T0REd2M0GtHQ0NBpbYuqqio0NjZ2uZ1cLrfYaREQEABPT/5KTERERNSbcIQGERERkUT8rkJE5HxtbW2oqanpNNqiuroabW1tXW7n6+trsePCz8+Pi3ITERERuTmO0CAiIiIiIiK31dTUZHG0RW1tbZfbeHh4dLkoNzuaiYiIiPo+dmgQERERERGRUxiNRtTV1XUabVFVVQWdTtfldgMHDrQ42sLf3x8DBgzowSMgIiIiInfCDg0iIiIiIiKyS2trq2lR7o6v6upqGAyGLrcbPHiwxY4LHx8fThNFRERERJ2wQ4OIiIiIiIjuSgiBxsZGi6MtGhoautzO09Ozy2mi5HJ5Dx4BEREREfV27NAgIiIiIiIiE4PBYFqU+85Xa2trl9v5+PhYHG2hUqng4eHRg0dARERERH0VOzSIiIiIiIj6IZ1Oh+rq6k6jLWpra2E0Gi1uI5PJ4O/vb9ZhERQUhCFDhsDb27uHj4CIiIiI+ht2aBAREREREfVRRqMRDQ0NFkdbNDY2drmdXC63ONoiICAAnp78NZKIiIiIXIPfRB2kuroa999/P06fPo2wsDBXp0MACgsL8eijj+LChQvw8fFxdTq9Gut337J+/Xro9Xr87ne/c3UqvQrbQe9w8OBB/OpXv0J+fj6nNyGifqWtrQ01NTWdRltUV1ejra2ty+18fX07dVoEBQXB19eXi3ITERERkdvhb/oOsnnzZsybN8/sJldZWRnmzZtnmkt2zZo10Ov1VsU9f/48Hn/8cYSFhUEmk+Gtt96yKb9du3YhNjYWfn5+kMlkqKursylOYWEhNBoNlEolhg0bho0bN0IIYXWc7du3Izw8HAMHDkR0dDSOHz9udYxNmzZh6tSp8Pb2xuDBgzu9P27cOEyaNAlvvvmm1bHJnKX6vXbtWkRHR0OhUGDChAkO29exY8cwb948hISEQCaT4eOPP7YpTm1tLRITE6FSqaBSqZCYmGhzve/IUW2ytbUVzz//PAIDA+Hj44P58+fj6tWrdud3/fp1JCQkYPTo0fDw8EBycnKnz7z00kvYs2cPSkpK7N5ff+Ks6zwAZGRkIDIyEgqFApGRkThw4IDVMdztOn+njz76CPHx8QgMDIRMJkNBQYFNce52zufOnQuZTIYPPvjA7pyJiNxRU1MTrly5gvz8fHz22Wd4//338fbbb2PTpk3YsWMH/v73vyM7OxtFRUXQarVoa2uDh4cHgoKCcP/992P69OlYtGgRVqxYgZdffhnr1q3DsmXLMGfOHEyePBn33nuv6f8SIiIiIiJ3wxEaDqDT6bB7925kZmaaygwGA+bMmYOgoCDk5uaiuroay5YtgxAC27Ztkxy7ubkZI0eOxOLFi/HCCy/YnGNzczNmz56N2bNnY8OGDTbFaGhowKxZszBz5kycOXMG33//PZKSkuDj44N169ZJjvPXv/4VycnJ2L59O6ZNm4Z3330Xjz76KIqLizFixAjJcfR6PRYvXoyYmBjs3r3b4meWL1+O1atXY8OGDRgwYIDk2PS/LNVvABBC4Nlnn8WpU6dw7tw5h+2vqakJ48ePx/Lly/H444/bHCchIQFXr15FVlYWAGDlypVITEzEp59+ald+jmqTycnJ+PTTT7F//34MGTIE69atw9y5c5Gfn29XXW1tbUVQUBBeeeWVLjvzgoODERcXh507d2Lr1q0276s/ceZ1Pi8vD0uXLsWvf/1rLFq0CAcOHMCSJUuQm5uLyZMnS47jTtd5S5qamjBt2jQsXrwYK1assCmG1HO+fPlybNu2DU8//bRdORMRuYrRaERdXV2n0RZVVVXQ6XRdbjdw4ECLoy0GDx7M78JERERE1CfIhCMeu7RCQ0MDVCoV6uvr4efnZ/ZeS0sLSkpKTE/u9xYfffQRVq1ahcrKSlPZoUOHMHfuXPz4448ICQkBAOzfvx9JSUmoqKjodOxShIWFITk52eIT11JlZ2dj5syZqK2ttTiqoTs7duzAhg0bcOPGDSgUCgDAli1bsG3bNly9elXyU1yTJ0/Ggw8+iB07dpjK7r//fixcuBCbN2+2KicA2Lt3L5KTky0+jazX6+Hn54fMzEw89NBDVscmy/W7o7S0NHz88cc2P23dHZlMhgMHDmDhwoVWbfftt98iMjISJ0+eNN0QPnnyJGJiYvDdd99h9OjRDsnP1jZZX1+PoKAg/OUvf8HSpUsBANeuXcPw4cORmZmJ+Ph4h+QXGxuLCRMmWBxF8qc//Qm/+tWvUFZW5pB99XXOvM4vXboUDQ0NOHTokKls9uzZ8Pf3x759+6zO1R2u890pLS1FeHg4zp49a/XoLqnn/MqVKwgLC8Ply5cxcuRIu3PuqLd+VyEi99Ta2orq6upOnRbV1dUwGAxdbjd48GCL61v4+PhwZAURERER9Urd9Rt05NYjNIQQuNXa6pJ9eyoUkn8ZOHbsGCZOnGhWlpeXh7Fjx5puuABAfHw8WltbkZ+fj5kzZzo0356Ql5cHjUZjuskF3D6mDRs2mG5Q3Y1er0d+fj5efvlls/K4uDicOHHC4TnL5XKMHz8ex48fd7sODSEERDdP2DmTTKm0q367u7y8PKhUKrOn26dMmQKVSoUTJ044rEPDVvn5+Whra0NcXJypLCQkBGPHjsWJEycc1qHRnUmTJuHHH3/ElStXEBoa6vT9dUUIAV1b1zdsnEnpNcAtrvN5eXmdRvvEx8fbPJ2ZPRxxnXcmqec8NDQUwcHBOH78uMM7NIiIrCWEQGNjo8XRFg0NDV1u5+npiSFDhpiNtGhflFsul/fgERARERERuQ+37tC41dqK3y17wiX7XvOnv8NL4pOXpaWlZjdXAECr1WLo0KFmZf7+/pDL5dBqtQ7LsydptdpOC+G2H6NWq5V0o6uqqgoGg6HTuRk6dKjTzsuwYcNQWlrqlNj2EDodLjwY7ZJ9j/46HzJvb0mftVS/3Z1Wq0VwcHCn8uDgYLdof1qtFnK5HP7+/mblzmwHdxo2bBiA2z9fV3Zo6NoMiHz1M5fsu3hjPLzl0v4bdOZ13lKcnqwLd+Zi73Xemaw55+567SeivstgMKCmpqZTp0VVVRVau3lIq31NoDtfKpUKHh5c8pCIiIiIqCO37tDoLXQ6ncVpJyw9+SuE6NXDwO/MvX3GMmuPyVIcZ50XpVKJ5uZmp8TuD7qq3/Y6fvw4Hn30UdO/3333XTz11FMOi29v+ysrK0NkZKTp3ykpKUhJSXFYfpZY2w4GDRpk+vvTTz+NnTt3St5WqVQCANuGRM6+zvfkNdGWXCyVd+X999/HqlWrTP8+dOgQpk+f7rT8AMvni9d+InIWnU6H6urqTiMuamtrYTQaLW4jk8ng7+/fabTFkCFD4C3xIRMiIiIiInLzDg1PhQJr/vR3l+1bqsDAQNTW1pqVqdVqnDp1yqystrYWbW1tnZ4u7S3UanWnJ2ArKioAQPIxBQYGYsCAARbjOOu81NTU4N5773VKbHvIlEqM/jrfZfuWylL9doSJEyearbvhyJ+/Wq3GjRs3OpVXVlZK3k9ISIhZfgEBAY5KD2q1Gnq9HrW1tWajNCoqKjB16lTJcTrmZ+26PDU1NQCAoKAgq7ZzNKXXABRvdP4UW13tWypnXue7ura64v8KR1zn58+fbzbdW/toIEflJ/Wc19TUuLx+E1HvJ4TApUuXcOHCBVPHRWNjY5efl8vlFkdbBAQEwNPTrX/1IiIiIiLqFdz6W7VMJpM87ZMrRUVF4b333jMri4mJwaZNm3D9+nXcc889AIDDhw9DoVAgOto10wzZKyYmBikpKdDr9aZ5ew8fPoyQkJBOU5R0RS6XIzo6GkeOHMGiRYtM5UeOHMGCBQuckTaKiorwxBOumbqsOzKZTPK0T65kqX47glKpxKhRoxweF7hdV+vr63H69GlMmjQJAHDq1CnU19dL7jDw9PR0Wn7R0dHw8vLCkSNHsGTJEgDA9evXUVRUhNdff11yHHvyKyoqgpeXFx544AGbYziCTCaTPO2TKznzOh8TE4MjR46YraNx+PBhqzq3HMUR13lfX1/4+vo6LT8p57ylpQWXL19GVFSUU/Igov7h+vXrOHz4MEpKSjq95+vra9Zh0T7iwtfXt1ePxiYiIiIicnfufxepF2hfMLXj09ZxcXGIjIxEYmIifvOb36Cmpgbr16/HihUrrHqSWq/Xo7i42PT38vJyFBQUYNCgQVbdzNRqtdBqtbh06RIAoLCwEL6+vhgxYoTkJ88TEhLw2muvISkpCSkpKbh48SLS09Px6quvWvWL24svvojExERMnDgRMTEx2LVrF8rKyrB69WrJMYDbUwLV1NSgrKwMBoPB9LT6qFGjTFPxlJaWory8HI888ohVsel/WarfAHDp0iU0NjZCq9VCp9OZzn9kZKRdC1U2Njaa6ikAlJSUoKCgAAEBARgxYoSkGPfffz9mz56NFStW4N133wUArFy5EnPnzrV7QXBHtEmVSoWf//znWLduHYYMGYKAgACsX78e48aNc0hdbf9ZtC9AWlBQALlcbjaF1vHjxzF9+nTT1FPUPWde59euXYsZM2Zg69atWLBgAT755BN8/vnnyM3NtSpHd7rOW9J+vb527RoA4MKFCwBuj7pQq9WSYkg95ydPnoRCoUBMTIxdORNR/1RfX48vv/wS33zzDQBgwIABePDBB/GTn/zE1IGhsGI0NxEREREROZDoYfX19QKAqK+v7/SeTqcTxcXFQqfT9XRadpsyZYrYuXOnWdmVK1fEnDlzhFKpFAEBAeK5554TLS0tZp8BIPbs2dNl3JKSEgGg00uj0Zg+s2fPHnG3H2VqaqrFOB33rdFoxLJly7qNc+7cOTF9+nShUCiEWq0WaWlpwmg0dsr36NGj3cb5/e9/L0JDQ4VcLhcPPvigyMnJ6ZRvaGhotzGWLVtm8Zg67js9PV3Ex8d3G4fuzlL91mg0Fs9/SUmJ6TN3q9+WHD161GLcjnVTSv2orq4WTz31lPD19RW+vr7iqaeeErW1tWafCQ0NFampqVbl56g2qdPpxHPPPScCAgKEUqkUc+fOFWVlZWafkdImLbGU353n67777hP79u2zOnZ/5qzrvBBCfPjhh2L06NHCy8tLjBkzRmRkZJi93xuv83dqP4Y7Xx3b4LJly8zakiVSzvnKlSvFqlWrrMpPqt78XYWIutfS0iI+//xz8etf/1qkpqaK1NRU8eGHH4qamhpXp0ZERERE1Od112/QkUyIf6322UMaGhqgUqlQX1/f6QnWlpYWlJSUIDw83CmLEDtTZmYm1q9fj6KiInh4eEjaprS0FBERESguLkZERITN+05LS0N2djays7NtjgEAYWFhSEtLQ1JSks0xsrOzsWjRIvzwww9mT/Nbqz2HvXv32hyjtbUVERER2LdvH6ZNm2ZzHHJt/bbEEfVDp9MhICAAmZmZmDlzpmMS+xd3apOW/POf/8R//ud/4ty5c5zP2wq8zt/mqOu8JbGxsYiNjUVaWprNMSorKzFmzBh89dVXCA8Pd1xy/9Kbv6sQkWUGgwFff/01srOz0dTUBAAYMWIE4uLi8JOf/MTF2RERERER9Q/d9Rt0xDtZDvLYY4/h4sWLKC8vx/DhwyVtk5WVhZUrV9p9s/ezzz7D22+/bVeM7777Dr6+vnjmmWfsipOVlYWUlBS7b3Ll5OTg2LFjdsW4cuUKXnnlFXZmOIAr67cljqgfOTk5eOihhxzemQG4V5u0pKmpCXv27GFnhpV4nb/NUdf5O928eROXL1/GwYMH7YpTUlKC7du3O6Uzg4j6FiEEvv/+exw5cgRVVVUAgICAAMyaNQtjxozhWhhERERERG6IIzSIiIiIJOJ3FaK+4dq1azh8+DBKS0sBAN7e3tBoNJg4cSIGDBjg2uSIiIiIiPohjtAgIiIiIiLqoL6+Hl988QXOnTsH4PaC31OmTMH06dPZSUlERERE1AuwQ4OIiIiIiPq0lpYW5Obm4uTJk7h16xYAYNy4cXj44YcxePBg1yZHRERERESSsUODiIiIiIj6JIPBgPz8fGRnZ6O5uRkAEBoairi4OAwbNszF2RERERERkbXYoUFERERERH2KEAIXLlzAkSNHUF1dDQAYMmQIZs2ahdGjR3PBbyIiIiKiXoodGkRERERE1GeUl5fj8OHDuHLlCoDbC37HxsYiOjqaC34TEREREfVy7NAgIiIiIqJer66uDl988QUKCwsBAJ6enpgyZQp++tOfcsFvIiIiIqI+gh0aRERERETUa7W0tOD48eM4efIkDAYDAODf/u3f8NBDD3HBbyIiIiKiPsbD1Qn0FdXV1QgODkZpaamrUyErvfPOO5g/f76r03BrrN99y/r167FmzRpXp9HrsB24n8LCQvzkJz9BU1OTq1MhIhcwGAw4deoUfve73+F//ud/YDAYEBYWhpUrV+JnP/sZOzOIiIiIiPogdmg4yObNmzFv3jyEhYWZytauXYvo6GgoFApMmDDB5tgZGRmIjIyEQqFAZGQkDhw4YH/CADZt2oSpU6fC29vbrl/4cnJyEB0djYEDB2LkyJHYuXOnQ/LbtWsXYmNj4efnB5lMhrq6OpviFBYWQqPRQKlUYtiwYdi4cSOEEKb3V6xYgTNnziA3N9chefdFzqzfdzp27BjmzZuHkJAQyGQyfPzxxw6L7U5tsrW1Fc8//zwCAwPh4+OD+fPn4+rVqzbn1O769etISEjA6NGj4eHhgeTk5E6feemll7Bnzx6UlJTYvb/+xFI7KCsrw7x58+Dj44PAwECsWbMGer3e6tiOqFOOuGa2tLQgKSkJ48aNg6enJxYuXGh1jHbbt29HeHg4Bg4ciOjoaBw/ftzqGLW1tUhMTIRKpYJKpUJiYqLZcY0bNw6TJk3Cm2++aXOeRNT7CCHw7bff4ve//z0OHTqE5uZmBAYG4t///d+xbNkyhISEuDpFIiIiIiJyEnZoOIBOp8Pu3bvxi1/8wqxcCIFnn30WS5cutTl2Xl4eli5disTERHzzzTdITEzEkiVLcOrUKXvThl6vx+LFi/HLX/7S5hglJSV47LHHMH36dJw9exYpKSlYs2YNMjIy7M6vubkZs2fPRkpKis0xGhoaMGvWLISEhODMmTPYtm0bfvvb3+KNN94wfUahUCAhIQHbtm2zO+e+yJn125KmpiaMHz8e77zzjkPjAu7VJpOTk3HgwAHs378fubm5aGxsxNy5c01TZdiqtbUVQUFBeOWVVzB+/HiLnwkODkZcXJzDOh/7A0vtwGAwYM6cOWhqakJubi7279+PjIwMrFu3zqrYjqpTjrhmGgwGKJVKrFmzBo888ojNcf76178iOTkZr7zyCs6ePYvp06fj0UcfRVlZmVVxEhISUFBQgKysLGRlZaGgoACJiYlmn1m+fDl27Nhhd9shot7h6tWr2LNnD/7617+ipqYGPj4+mDNnDn75y19i9OjRkMlkrk6RiIiIiIicSfSw+vp6AUDU19d3ek+n04ni4mKh0+l6Oi27ZGRkiMDAwC7fT01NFePHj7cp9pIlS8Ts2bPNyuLj48WTTz5pUzxL9uzZI1QqlU3bvvTSS2LMmDFmZatWrRJTpkxxQGa3HT16VAAQtbW1Vm+7fft2oVKpREtLi6ls8+bNIiQkRBiNRlNZdna2kMvlorm52REp9ynOrN93A0AcOHDA4XFd3Sbr6uqEl5eX2L9/v6msvLxceHh4iKysLJvyskSj0Yi1a9dafG/v3r1i+PDhDttXX2epHWRmZgoPDw9RXl5uKtu3b59QKBQW/4/riqOv8/ZcMztatmyZWLBggU3bTpo0SaxevdqsbMyYMeLll1+WHKO4uFgAECdPnjSV5eXlCQDiu+++M5W1trYKhUIhvvjiC5tytVZv/a5C1NvV1NSIDz/8UKSmporU1FTx61//Wnz++edsi0REREREfUR3/QYdufUIDSEEjHqDS16iw5REd3Ps2DFMnDjRKecgLy8PcXFxZmXx8fE4ceKEU/Znra7y++qrr9DW1uairP5XXl4eNBoNFAqFqSw+Ph7Xrl0zmwd/4sSJaGtrw+nTp3ssNyEE2loNLnm5S/3ujRzRJvPz89HW1mYWJyQkBGPHju2xtj1p0iT8+OOPuHLlSo/sr0tCAPom17zsbAd5eXkYO3as2dQm8fHxaG1tRX5+vuTY7n6dt5Zer0d+fn6nY4qLi7PqmPLy8qBSqTB58mRT2ZQpU6BSqcziyOVyjB8/3qYprYjI/el0Ohw+fBjvvPMOioqKAADjx4/H888/j4cffhgDBw50cYZERERERNSTPF2dQHdEmxHXXnXNDZ2QjVMhkw+Q9NnS0lKnzdWr1WoxdOhQs7KhQ4dCq9U6ZX/W6iq/W7duoaqqCvfcc4+LMrtNq9WazXcPwJSvVqtFeHg4AMDHxweDBw9GaWkpNBpNj+R2S2/ErrU5PbKvO618WwMvhevrd2/kiDap1Wohl8vh7+9vVxx7DBs2DMDtn29oaGiP7NOitmYg3UX1K+UaIPeR9FFL7cBSXfD394dcLre6Prjzdd5aVVVVMBgMDmknwcHBncqDg4M7xRk2bBgXayfqY27duoWvvvoKOTk50Ol0AIDw8HDExcW5/PslERERERG5jluP0OgtdDqdU58Ou3MuYCGEVfMDr169GoMGDTK9HM1SfpbKu5Kenm6Wn7VzrDsqP6VSiebmZofuuy9wVv0+fvy42c/9/fffd1jsRx991BT3gQcecFjcdva2ya5YG6fj+Vu9erVV+1IqlQDAOi9RV+3A0s/LlvrgrDrlSo44Jqnnl9dvor5DCIHi4mJs374dWVlZ0Ol0CAoKQkJCAp555hl2ZhARERER9XNuPUJD5uWBkI1TXbZvqQIDA1FbW+uUPNRqdacnUSsqKjo9+dqdjRs3Yv369Y5ODUDX+Xl6emLIkCGSYqxevRpLliwx/duRowG6yg9Ap3NYU1ODoKAgh+37bjzlHlj5ds+MBrG0b6mcVb8nTpyIgoIC07+tqdN384c//MH0NKeXl5fD4gKOaZNqtRp6vR61tbVmozQqKiowdar0a17H8+fn5yd5O+B2fQfQo3XeIi/v2yMlXLVviSy1A7Va3Wnh7traWrS1tVldH+ytU+4kMDAQAwYMcEg7uXHjRqfyyspKi9fve++917aEichtXL16FZ999hl+/PFHALdH0M6cORNRUVEYMEDayFIiIiIiIurb3LtDQyaTPO2TK0VFReG9995zSuyYmBgcOXIEL7zwgqns8OHDVt30DA4OtjhthyPExMTg008/NSs7fPgwJk6cKPlGckBAAAICApyRHmJiYpCSkgK9Xg+5XG7KLyQkxGwqqsuXL6OlpQVRUVFOycMSmUwmedonV3JW/VYqlRg1apTD4wL/O52SMziiTUZHR8PLywtHjhwxdeZdv34dRUVFeP311yXHsef8FRUVwcvLyykjWKwik0me9smVLLWDmJgYbNq0CdevXzc9MXz48GEoFApER0dLju2IOuVO5HI5oqOjceTIESxatMhUfuTIESxYsEBynJiYGNTX1+P06dOYNGkSAODUqVOor6/vdG6KiorwxBNPOOYAiKjH1dbW4vPPP8f58+cBAJ6enpg6dSqmTZtmtg4aERERERGRW3do9Bbx8fHYsGFDp6etL126hMbGRmi1Wuh0OtPT1JGRkaab63ezdu1azJgxA1u3bsWCBQvwySef4PPPP0dubq7deZeVlaGmpgZlZWUwGAym/EaNGiV5aqrVq1fjnXfewYsvvogVK1YgLy8Pu3fvxr59++zOT6vVQqvV4tKlSwCAwsJC+Pr6YsSIEZI7QBISEvDaa68hKSkJKSkpuHjxItLT0/Hqq6+aTVly/PhxjBw5kk/4WuDM+m1JY2Oj6WcOACUlJSgoKEBAQABGjBhhc1xH5eyINqlSqfDzn/8c69atw5AhQxAQEID169dj3LhxeOSRR2w5NDPtx9XY2IjKykoUFBRALpcjMjLS9Jnjx49j+vTppqmnqHuW2kFcXBwiIyORmJiI3/zmN6ipqcH69euxYsUKq0bMOOo674hrJgAUFxdDr9ejpqYGN2/eNNWnCRMmSI7x4osvIjExERMnTkRMTAx27dqFsrIyq6ZGu//++zF79mysWLEC7777LgBg5cqVmDt3LkaPHm36XGlpKcrLyx3SdoioZ+l0Ohw7dgynT5+GwWAAcPta89BDD1k98pCIiIiIiPoJ0cPq6+sFAFFfX9/pPZ1OJ4qLi4VOp+vptOw2ZcoUsXPnTrMyjUYjAHR6lZSUmD4DQOzZs6fb2B9++KEYPXq08PLyEmPGjBEZGRlm7+/Zs0fY8qNctmyZxfyOHj1q+kxoaKhITU3tNk52draIiooScrlchIWFiR07dpi9f/To0U7HLUVqaqrF/DqeL41GI5YtW9ZtnHPnzonp06cLhUIh1Gq1SEtLE0aj0ewzcXFxYvPmzVbl1584s37fqb2+3Pnq+HNOTU0VoaGhVh+HO7VJnU4nnnvuOREQECCUSqWYO3euKCsr65Tv3eq3JZaO8c7zdd9994l9+/ZZHbs/s9QOrly5IubMmSOUSqUICAgQzz33nGhpaTH7TE/VKUddM0NDQy3GaVdSUtLp/wpLfv/734vQ0FAhl8vFgw8+KHJycjrle7d2XF1dLZ566inh6+srfH19xVNPPSVqa2vNPpOeni7i4+O7jeNIvfm7CpG7aGtrEydOnBCbN28WqampIjU1VfzpT38S169fd3VqRERERETkIt31G3QkE+JfKyT3kIaGBqhUKtTX13d68qqlpQUlJSUIDw936iLbzpCZmYn169ejqKgIHh7S1icoLS1FREQEiouLERERYfO+09LSkJ2djezsbJtjWKLT6RAQEIDMzEzMnDnT5jh79+7Fpk2bUFxc7PD1DMLCwpCWloakpCSbYxQVFeHhhx/G999/D5VK5bjk+hBX1m9L2n/ee/fudWhcd2uTjqjflvzzn//Ef/7nf+LcuXPw9ORAPan6wnXeEXUqOzsbixYtwg8//GA2astajmjHra2tiIiIwL59+zBt2jSb41ijN39XIXI18a8Fvz///HPTukRBQUGIi4vDqFGjzEbPEhERERFR/9Jdv0FHvJPlII899hguXryI8vJyDB8+XNI2WVlZWLlypd03ez/77DO8/fbbdsWwJCcnBw899JBdnRnA7eNMT093eGfGd999B19fXzzzzDN2xbl27Rr+/Oc/szOjG66s35bk5OTg2LFjDo/rTm3SUfXbkqamJuzZs4edGVbq7dd5R9WprKwspKSk2NWZATimHV+5cgWvvPJKj3VmEJHtfvzxR3z22We4evUqAGDQoEGYOXMmJkyYwAW/iYiIiIhIMo7QICIiIpKI31WIrFNTU4PPP/8cxcXFAAAvLy9MnToVU6dO5YLfRERERERkwhEaRERERETkEs3NzaYFv41GIwAgKioKM2fO5ILfRERERERkM3ZoEBERERGRQ9y6dQunT5/GsWPH0NLSAgC49957MWvWLKjVahdnR0REREREvR07NIiIiIiIyC5CCJw/fx6ff/456urqAADBwcGmBb+JiIiIiIgcgR0aRERERERks7KyMhw+fNhswe+HHnoIEyZMgIeHh4uzIyIiIiKivoQdGkREREREZLXq6mp8/vnn+PbbbwHcXvB72rRpmDp1KuRyuYuzIyIiIiKivogdGkREREREJFlzczNycnJw5swZGI1GyGQy04Lfvr6+rk6PiIiIiIj6MHZoEBERERHRXbW1tZkW/G5tbQUAjBo1CrNmzcLQoUNdnB0REREREfUHnNTWQaqrqxEcHIzS0lJXp0LdOHjwIKKiomA0Gl2dSq/C+t17vfPOO5g/f76r0+gT2A56B17niRxPCIHCwkL8/ve/x5EjR9Da2oqhQ4ciMTERTz/9NDsziIiIiIiox7BDw0E2b96MefPmISwszFRWVlaGefPmwcfHB4GBgVizZg30er1Vcc+fP4/HH38cYWFhkMlkeOutt2zKb9euXYiNjYWfnx9kMhnq6upsinOn69evIyEhAaNHj4aHhweSk5NtiiOEQFpaGkJCQqBUKhEbG4vz589bHedu53zu3LmQyWT44IMPbMqzv3JW/QaAjIwMREZGQqFQIDIyEgcOHLA6Rn+p33dqaWlBUlISxo0bB09PTyxcuLDTZ1asWIEzZ84gNzfX7v31d5bawdq1axEdHQ2FQoEJEyY4bF/Hjh3DvHnzEBISAplMho8//timOLW1tUhMTIRKpYJKpUJiYqJN7SMnJwfR0dEYOHAgRo4ciZ07d1odg9d5ot7pypUr+MMf/oCMjAzU1dXB19cXCxYswKpVq3Dvvfe6Oj0iIiIiIupn2KHhADqdDrt378YvfvELU5nBYMCcOXPQ1NSE3Nxc7N+/HxkZGVi3bp1VsZubmzFy5Ehs2bIFarXa5hybm5sxe/ZspKSk2BzDktbWVgQFBeGVV17B+PHjbY7z+uuv44033sA777yDM2fOQK1WY9asWbh586bkGFLP+fLly7Ft2zabc+1vnFm/8/LysHTpUiQmJuKbb75BYmIilixZglOnTlkVpz/Ub0sMBgOUSiXWrFmDRx55xOJnFAoFEhISWOftZKkdALdv0j/77LNYunSpQ/fX1NSE8ePH45133rErTkJCAgoKCpCVlYWsrCwUFBQgMTHRqhglJSV47LHHMH36dJw9exYpKSlYs2YNMjIyrIrD6zxR71JVVYX9+/djz549KC8vh5eXF2bOnInnn38eUVFR8PDgrxFEREREROQCoofV19cLAKK+vr7TezqdThQXFwudTtfTadklIyNDBAYGmpVlZmYKDw8PUV5ebirbt2+fUCgUFo9ditDQUPHmm2/ak6o4evSoACBqa2vtimOJRqMRa9eutXo7o9Eo1Gq12LJli6mspaVFqFQqsXPnTslxpJ7z0tJSAUBcvnzZ6lz7I2fW7yVLlojZs2eblcXHx4snn3zSplz7cv2+m2XLlokFCxZYfC87O1vI5XLR3NzssP31N5baQUepqali/PjxTtk3AHHgwAGrtysuLhYAxMmTJ01leXl5AoD47rvvJMd56aWXxJgxY8zKVq1aJaZMmSI5Rl+6zvfW7ypEUjU2Nop//vOf4rXXXhOpqakiLS1N/OMf/xANDQ2uTo2IiIiIiPqw7voNOnLrR6uEENDr9S55CSEk53ns2DFMnDjRrCwvLw9jx45FSEiIqSw+Ph6tra3Iz8932DnqC0pKSqDVahEXF2cqUygU0Gg0OHHihOQ4Us95aGgogoODcfz4ccccgI2EEGhraXHJy13qd15entnPvT2ONT93d+eo+m2PiRMnmhZydTdCCDS3NbvkZW87cHd5eXlQqVSYPHmyqWzKlClQqVRWX1sttdOvvvoKbW1tkmL01+s8UW/S1taG3Nxc/O53v8Pp06dhNBoRERGBX/7yl5g3bx58fX1dnSIRERERERE8XZ1Ad9ra2pCenu6SfaekpEAul0v6bGlpqdnNFQDQarWdFkj09/eHXC6HVqt1WJ59Qfv5uPN8DR06FFeuXLEqjtRzPmzYMJcv7HurtRW/W/aES/a95k9/h9fAgZI+68z6bSnO0KFD+1QbcVT9toePjw8GDx6M0tJSaDSaHtmnVLpbOkz+YPLdP+gEpxJOwdvLW9JnLbUDd6fVahEcHNypPDg42CHt9NatW6iqqsI999wjKUb7dnfG6cvXeaLewGg0oqioCF988QXq6+sBAGq1GnFxcRg5cqSLsyMiIiIiIjLn1iM0egudToeBFm4Oy2SyTmVCCIvlvcGgQYNMr9WrVzs8/p3nxZZzJfWcK5VKNDc3W59kP+Ts+u2In7sjuHv9fuCBB0z5Pfroo1bvn3XePl21A3sdP37crO69//77Do3vzHbaVXxr4/A6T+Q6paWl+MMf/oCPPvoI9fX18PX1xcKFC7Fy5Up2ZhARERERkVty6xEaXl5eDl/k15p9SxUYGIja2lqzMrVa3Wlh49raWrS1tXV6urS3KCgoMP3dz8/PYXHbFzvXarVmT/pWVFRYda6sOec1NTUICgqyI2v7eSoUWPOnv7ts31I5s36r1epOT1Vb+3N3FHev35mZmabpfZRKpdV5uEOdt0TpqcSpBOsWgXfkvqWy1A4cYeLEiWZ1z5F1X61W48aNG53KKysrHdJOPT09MWTIEMkxgP53nSdyV1VVVThy5AguXLgAAJDL5fjpT3+KKVOmSB6hTERERERE5Apu3aEhk8l6xS9VUVFReO+998zKYmJisGnTJly/ft108+bw4cNQKBSIjo52RZp2GzVqlFPihoeHQ61W48iRI4iKigIA6PV65OTkYOvWrZLjSD3nLS0tuHz5smlfriKTySRP++RKzqzfMTExOHLkCF544QVT2eHDhzF16lTHJG8Fd6/foaGhNudw+fJltLS0uLzOWyKTySRP++RKltqBIyiVSqfVvZiYGNTX1+P06dOYNGkSAODUqVOor6+3qo3FxMTg008/NSs7fPgwJk6cKLnzv79e54ncTVNTE7Kzs/HVV1+ZRjZFR0cjNjYWgwYNcnV6REREREREd+XWHRq9RXx8PDZs2IDa2lr4+/sDAOLi4hAZGYnExET85je/QU1NDdavX48VK1ZY9fS3Xq9HcXGx6e/l5eUoKCjAoEGDrLoJptVqodVqcenSJQBAYWEhfH19MWLECAQEBFhxtJ21P13c2NiIyspKFBQUQC6XIzIyUtL2MpkMycnJSE9PR0REBCIiIpCeng5vb28kJCRIzkPqOT958iQUCgViYmKsOs7+ypn1e+3atZgxYwa2bt2KBQsW4JNPPsHnn3+O3Nxcq3LsD/W7K8XFxdDr9aipqcHNmzdN+U6YMMH0mePHj2PkyJG499577d5ff2WpHQDApUuX0NjYCK1WC51OZzr/kZGRdnXINzY2muozcHtR7YKCAgQEBGDEiBGSYtx///2YPXs2VqxYgXfffRcAsHLlSsydOxejR4+WnMvq1avxzjvv4MUXX8SKFSuQl5eH3bt3Y9++fZJj8DpP5FptbW04efIkjh8/Dr1eDwC47777MGvWLI5kIiIiIiKi3kX0sPr6egFA1NfXd3pPp9OJ4uJiodPpejotu02ZMkXs3LnTrOzKlStizpw5QqlUioCAAPHcc8+JlpYWs88AEHv27OkybklJiQDQ6aXRaEyf2bNnj7jbjzI1NdVinI771mg0YtmyZVIP2ewY7nyFhoaa3j969KgAIEpKSrqMYTQaRWpqqlCr1UKhUIgZM2aIwsJCs88sW7bM7LgtkXLOV65cKVatWmXtYfZrzqrfQgjx4YcfitGjRwsvLy8xZswYkZGRYfY+63f3QkNDLebYUVxcnNi8ebPVscmcpXag0Wgsnv+O9UFKO7hTe72689WxDqempprVRUuqq6vFU089JXx9fYWvr6946qmnRG1trdlnQkNDRWpqardxsrOzRVRUlJDL5SIsLEzs2LHDYr794Trfm7+rUP9jMBhEQUGB+H//7/+J1NRUkZqaKnbu3Cl++OEHV6dGRERERERkprt+g45kQvxrZc8e0tDQAJVKhfr6+k5Pcre0tKCkpATh4eFOWXzVmTIzM7F+/XoUFRXBw0PaWuulpaWIiIhAcXExIiIibN53WloasrOzkZ2dbXMMAAgLC0NaWhqSkpLsinOnvXv3YtOmTSguLrZqbZI7xcbGIjY2FmlpaTbHqKysxJgxY/DVV18hPDzc5jj9Det319ypfltSVFSEhx9+GN9//z1UKpVDY/c3rmwHlrTX5b1799ocQ6fTISAgAJmZmZg5c6bNcdypHTj7Ot+bv6tQ/1JSUoLDhw/j+vXrAG6vD/Xwww9j3Lhxkq9hREREREREPaW7foOOOOWUgzz22GO4ePEiysvLMXz4cEnbZGVlYeXKlXbf5Prss8/w9ttv2xXju+++g6+vL5555hm74liSlZWF9PR0u25y3bx5E5cvX8bBgwftyqWkpATbt29nZ4aVWL+75k7125Jr167hz3/+MzszHMCV7cCSnJwcHDt2zO4YDz30kF2dGYB7tQNe56m/q6ysxJEjR/D9998DuL3g9/Tp0zFlyhS72igREREREZE74AgNIiIiIon4XYXcVWNjI7Kzs5Gfn29a8HvixInQaDRc8JuIiIiIiNweR2gQEREREfVxer0eJ0+eRG5urmnB79GjR2PWrFkIDAx0cXZERERERESOxQ4NIiIiIqJexmg04ty5c/jyyy/R0NAAAAgJCUFcXBzCwsJcmxwREREREZGTsEODiIiIiKgX+eGHH3D48GFotVoAgEqlwsMPP4yxY8dywW8iIiIiIurT2KFBRERERNQLVFRU4MiRI7h48SIAQKFQYPr06Zg8eTIX/CYiIiIion6BHRpERERERG6ssbERR48exddffw0hBDw8PEwLfvv4+Lg6PSIiIiIioh7DDg0iIiIiIjek1+uRl5eH//mf/zEt+D1mzBg88sgjXPCbiIiIiIj6JXZoEBERERG5EaPRiG+++QZffvklbt68CeD2gt/x8fEIDQ11cXZERERERESuw1UDHaS6uhrBwcEoLS11dSrUjYMHDyIqKgpGo9HVqfQqrN+9A+u3c7Ed9A5sB9TbXb58Ge+++y4++eQT3Lx5EyqVCo8//jh+8YtfsDODiIiIiIj6PXZoOMjmzZsxb948hIWFmcrWrl2L6OhoKBQKTJgwwebYGRkZiIyMhEKhQGRkJA4cOGB1jNbWVjz//PMIDAyEj48P5s+fj6tXr1odp7CwEBqNBkqlEsOGDcPGjRshhLA6zvbt2xEeHo6BAwciOjoax48ftzqGJXc753PnzoVMJsMHH3zgkP31F5bqd1lZGebNmwcfHx8EBgZizZo1pukwpDp//jwef/xxhIWFQSaT4a233rIpv127diE2NhZ+fn6QyWSoq6uzKY6j6vedPvroI8THxyMwMBAymQwFBQU2xbnbOWf9di53bweWbNq0CVOnToW3tzcGDx5sc5ycnBxER0dj4MCBGDlyJHbu3Gl1DCEE0tLSEBISAqVSidjYWJw/f97qOLzOU19148YNvPfee/jLX/6CGzduQKFQYNasWXjuuecwbtw4eHjwazsRERERERF/M3IAnU6H3bt34xe/+IVZuRACzz77LJYuXWpz7Ly8PCxduhSJiYn45ptvkJiYiCVLluDUqVNWxUlOTsaBAwewf/9+5ObmorGxEXPnzoXBYJAco6GhAbNmzUJISAjOnDmDbdu24be//S3eeOMNq3L561//iuTkZLzyyis4e/Yspk+fjkcffRRlZWVWxbFEyjlfvnw5tm3bZve++gtL9dtgMGDOnDloampCbm4u9u/fj4yMDKxbt86q2M3NzRg5ciS2bNkCtVptc47Nzc2YPXs2UlJSbI7hqPptSVNTE6ZNm4YtW7bYHEPqOWf9do7e0A4s0ev1WLx4MX75y1/aHKOkpASPPfYYpk+fjrNnzyIlJQVr1qxBRkaGVXFef/11vPHGG3jnnXdw5swZqNVqzJo1yzSdjlS8zlNfc/PmTfzjH//Azp07cenSJXh4eGDy5MlYu3Ytpk2bBi8vL1enSERERERE5D5ED6uvrxcARH19faf3dDqdKC4uFjqdTgghhNFoFLduNbnkZTQaJR9TRkaGCAwM7PL91NRUMX78eKvPlRBCLFmyRMyePdusLD4+Xjz55JOSY9TV1QkvLy+xf/9+U1l5ebnw8PAQWVlZkuNs375dqFQq0dLSYirbvHmzCAkJsep8TZo0SaxevdqsbMyYMeLll1+WHONuujvnpaWlAoC4fPmyw/ZnC6PRKAytt1zysrd+Z2ZmCg8PD1FeXm4q27dvn1AoFBbbthShoaHizTfftGnbdkePHhUARG1trdXbOqp+d6ekpEQAEGfPnrV6W6nn3F3qt1RGo1EYmppc8uqr7cCSPXv2CJVKZdO2L730khgzZoxZ2apVq8SUKVMkxzAajUKtVostW7aYylpaWoRKpRI7d+60KS9XXefv/K5CZKvW1lZx9OhR8d///d8iNTVVpKamiv3794uqqipXp0ZERERERNTjuus36MitFwU3GnXIzhnnkn3HagoxYIC3pM8eO3YMEydOdEoeeXl5eOGFF8zK4uPjrZqSJD8/H21tbYiLizOVhYSEYOzYsThx4gTi4+Ml56LRaKBQKMxy2bBhA0pLSxEeHn7XGHq9Hvn5+Xj55ZfNyuPi4nDixAmJR2Sf0NBQBAcH4/jx4xg5cmSP7NMS0WbEtVd75pjvFLJxKmTyAZI+a6l+5+XlYezYsQgJCTGVxcfHo7W1Ffn5+Zg5c6ZD8+0JjqjfziT1nLtL/ZZK6HS48GC0S/Y9+ut8yLxtv873xXZgSV5entn/H8Dt49y9ezfa2tokPT1eUlICrVZrFkehUECj0eDEiRNYtWqVQ3Pube2A+hej0YiCggJ8+eWXaGxsBAAMGzYM8fHxGDFihIuzIyIiIiIicm9u3aHRW5SWlprd0HIkrVaLoUOHmpUNHToUWq3WqhhyuRz+/v52x+k4d3x7jPb3pNzwraqqgsFgsPuY7DVs2DAu7CuRpfptqV76+/tDLpf36M/RkRxRv53JmnPO+u14/aUdWNLV/0O3bt1CVVUV7rnnHkkx2re7M86VK1ccl2wHbAfkji5duoTDhw+joqICADB48GA88sgjeOCBByCTyVycHRERERERkftz6w4NDw8lYjWFLtu3VDqdDgMHDnRaLnf+giuEcMgvvbbEsZSLpXJb4lgT49FHHzUtJB4aGmr1wrJKpRLNzc1WbeNoMi8PhGyc6rJ9S9VV/bb083JU3XQVe+v3+++/b/ak+aFDhzB9+nSn5QdYPufuUL+lkimVGP11vsv2LZW7t4PVq1fjvffeM/27/alvR3GXa781elM7oL7vxo0bOHz4MC5fvgwAGDhwIGbMmIFJkybB09Otv44TERERERG5Fbf+DUomk0me9smVAgMDUVtb65TYarW605O+FRUVnZ5yvVsMvV6P2tpas1EaFRUVmDpV+g31rnIBOj9125XAwEAMGDDA7mP6wx/+AJ1OBwA2LZZZU1ODoKAgq7dzJJlMJnnaJ1eyVL/VanWnhelra2vR1tZm1c/RnTiifs+fPx+TJ082/XvYsGEOzU/qOXeH+i2VTCaTPO2TK7l7O9i4cSPWr1/vlNhdtQ1PT08MGTJEcgzg9kiNjiM6rL32W6M3tQPquxoaGnD06FEUFBRACAEPDw9MmjQJM2bMgHcvuPYRERER0f/P3p3HNXXm+wP/BEhC2CLIJiqLQlWqVYSq2FrUKrigrdNWZ2ipdtE691ql1TuteKdQp2Kd9tdNa1vvdPR2Zqq9HWu3sRR1ZCu4lIqCqHVhUSSKLAlLNpLn98eBSCTgyQIJ8H2/XuelOTn5nufgcw7xfM/zfAkhjob/Y9qkW1FRUSgrK+uV2LGxsTh06JDRuqysLLMSEdHR0RAKhUZxampqUFpaalac2NhY5ObmQqPRGLUlKCioy1Q93RGJRIiOju5yTIcOHTKrLcOHD0d4eDjCw8MREhLC+3MAoFKpcPnyZURFRZn1ucHKVP+OjY1FaWkpampqDOuysrIgFosRHW2fegjWskX/9vT0NPTL8PBwSMwYAcCnfXx+5tS/e4ejnwf+/v5Gfc+Wuvs9FBMTwzuhHBYWhsDAQKM4Go0GOTk5Zl37+aLzgNibWq3G0aNHsX37dpw6dQqMMURGRmLNmjWYN28eJTMIIYQQQgghxEKU0LCBhIQEnD17tsvTu5cuXUJxcTFkMhmUSiWKi4tRXFxsdMP0btatW4esrCxs27YN58+fx7Zt23D48GGkpKTwjiGVSvHcc89h/fr1OHLkCE6dOoWnnnoKEyZMwJw5c3jHSUpKglgsxooVK1BaWooDBw4gIyMDL7/8sllThrz88sv4y1/+gr/+9a84d+4cXnrpJVRVVWH16tW8Y3SHz8/82LFjEIvFiI2NtXp/g4Gp/h0fH4/IyEgkJyfj1KlTOHLkCDZs2ICVK1fCy8uLd2yNRmP0b1RdXY3i4mJcunTJrDbKZDKjz5WUlKC4uBj19fW8Y9iqf5tSX1+P4uJiww3xCxcuGPopX3x/5tS/e0d/OA9MqaqqQnFxMaqqqqDT6Qz7MWdKqtWrV6OyshIvv/wyzp07h7/+9a/49NNPzRoRIhAIkJKSgoyMDBw4cAClpaVYsWIF3NzckJSUZNYx0XWeODK9Xo+ioiJs374dOTk50Gq1GDFiBJ599lksXboUPj4+9m4iIYQQQgghhPRvrI/J5XIGgMnl8i7vKZVKVlZWxpRKZV83y2rTpk1jH3/8sdG6uLg4BqDLUl5ebtgGANu9e3ePsb/88ks2ZswYJhQK2dixY9n+/fuN3t+9eze72z+lUqlka9asYT4+PkwikbDExERWVVXVpb3Lly/vMc6ZM2fYjBkzmFgsZoGBgSw9PZ3p9XrD++Xl5QwAO3r0aI9xPvzwQxYSEsJEIhGbPHkyy8nJMXo/LS2NhYSE9BjDFD4/81WrVrEXXnjB7NiDman+XVlZyRYuXMgkEgnz8fFha9asYSqVymibu/Xvjv5y5xIXF2fYhk//TktLMxmn8777sn/fqeMY7lzS0tIM2yxfvtzouE3h8zOn/t17HP08MGX58uUmY3fuwyEhIUZ90ZTs7GwWFRXFRCIRCw0NZR999JHR+0ePHu1yrb2TXq9naWlpLDAwkInFYvbQQw+xkpKSLu2923lg7+t8f/6uQnqPXq9nv/76K/vwww9ZWloaS0tLY++99x4rLS01+j1CCCGEEEIIIcS0nvIGnQkYa6/s2UcUCgWkUinkcnmXJ1hVKhXKy8sRFhbWq0W2e8PBgwexYcMGlJaWwsmJ38CXiooKREREoKysDBERERbvOz09HdnZ2cjOzrY4BgCEhoYiPT0dK1assDhGdnY2lixZgitXrhjV6zBXRxv27NljcQxTamtrMXbsWPz8888ICwuzaeyBjPo3x1b925SZM2di5syZSE9PtzgG9e/eNRDOgzsplUr4+Pjg4MGDmDVrlsVx9uzZgy1btqCsrMyiukYd+sN50J+/q5DeIZPJkJWVhStXrgDgCn7HxcXh/vvvp4LfhBBCCCGEEMJTT3mDzuh/WTayYMECXLx4EdXV1Rg5ciSvz2RmZmLVqlVW3eQCgB9//BHvv/++VTHOnz8PT09PPP3001bFyczMRGpqqtU3e3NycpCbm2tVDFPKy8uxc+dOutlrJurfHFv17zs1NTXh8uXL+P77762KQ/27d/X388CUnJwczJ4926pkBsAdZ0ZGhlXJDDoPSH+jUCjw73//G8XFxQAAJycnTJ06FQ899JBNaygRQgghhBBCCLmNRmgQQgghhPBE31WIWq3GTz/9hIKCArS1tQEA7r33Xjz88MNUI4MQQgghhBBCLNQrIzTS09Px+uuvG60LCAgwq7AtIYQQQggh/Y1Op8OpU6dw9OhRtLS0AABGjhyJ+Ph43qO2CCGEEEIIIYRYx+wpp+69914cPnzY8NrZ2dmmDSKEEEIIIcRRMMZw8eJFHDp0CLW1tQAAb29vzJ07F+PGjYNAILBzCwkhhBBCCCFk8DA7oeHi4oLAwMDeaAshhBBCCCEOo6amBllZWSgvLwcASCQSxMXFISYmhgp+E0IIIYQQQogdmP0/sYsXLyIoKAhisRhTp05FRkYGRo0a1e32arUaarXa8FqhUFjWUkIIIYQQQvpAS0sLDh06ZCj47ezsjKlTp2LGjBlU8JsQQgghhBBC7MishMbUqVPx2Wef4Z577sGNGzfwxhtvYPr06Th79iyGDh1q8jNbt27tUneDEEIIIYQQR8MYQ3FxMbKysqBUKgEA48ePx8MPPwxvb287t44QQgghhBBCiIAxxiz9cEtLC0aPHo0//OEPePnll01uY2qExsiRI01WK1epVCgvL0dYWBhcXV0tbRYhhBBCSK+g7yoDU0edjJycHFRXVwMA/P39kZiYiODgYDu3jhBCCCGEEEIGPoVCAalUajJv0JlVk/+6u7tjwoQJuHjxYrfbiMViiMVia3ZDCCGEEEKIzXUkMv79739DJpMB4OrFzZw5E7GxsXB2drZzCwkhhBBCCCGEdOZkzYfVajXOnTuHYcOG2ao9/VZdXR38/f1RUVFh76aQHnz//feIioqCXq+3d1P6Ferf/QP1795F50H/tWPHDixevNjezSAOpqamBp999hk+//xzyGQyCIVCTJ8+HevWrcODDz5IyQxCCCGEEEIIcUBmJTQ2bNiAnJwclJeX4/jx43j88cehUCiwfPny3mpfv7F161YsWrQIoaGhhnVVVVVYtGgR3N3d4evri7Vr10Kj0ZgV9+zZs3jssccQGhoKgUCA9957z6L2qdVqvPjii/D19YW7uzsWL16Ma9eumRVDpVJhxYoVmDBhAlxcXPDoo49a1BZTvvrqKyQkJMDX1xcCgcBQhNNc69atQ3R0NMRiMSZNmtTl/cTERAgEAnz++efWNXiQMdW/7/az5sOR+jcAlJSUIC4uDhKJBMOHD8fmzZthxax8BtS/B4beus4DwP79+xEZGQmxWIzIyEgcOHDA7Bi7du3CzJkz4eXlBYFAgMbGRrNjAI5/HtyJz++mlStX4uTJk8jPz7fJPkn/JpfLceDAAXzyyScoLy+Hs7Mzpk+fjpSUFMTHx8PT09PeTSSEEEIIIYQQ0g2zEhrXrl3D7373O4wZMwa/+c1vIBKJcOzYMYSEhPRW+/oFpVKJTz/9FM8//7xhnU6nw8KFC9HS0oL8/Hzs27cP+/fvx/r1682K3drailGjRuHNN99EYGCgxW1MSUnBgQMHsG/fPuTn56O5uRmJiYnQ6XS8Y+h0OkgkEqxduxZz5syxuC2mtLS04IEHHsCbb75pVRzGGJ599lksW7as222eeeYZbN++3ar9DCam+jfA72d9N47UvxUKBebOnYugoCCcPHkS27dvx9tvv4133nnH4nZ1oP7d//Xmdb6wsBDLli1DcnIyTp8+jeTkZCxduhTHjx83K05rayvmzZuH1NRUsz7XWX84D+7E53eTWCxGUlISnRuDnEqlwpEjR7B9+3acPn0aAFfwe82aNYiPj4e7u7udW0gIIYQQQggh5G6sKgpuiZ6Ke9xZaJMxhlY7TZ3i5uQEgUDAa9uvvvoKL7zwAmpraw3rfvjhByQmJuLq1asICgoCAOzbtw8rVqzAzZs3eyxs0p3Q0FCkpKQgJSXFrM/J5XL4+fnhb3/7m+FG6PXr1zFy5EgcPHgQCQkJZrdlxYoVaGxsxNdff232Z3tSUVGBsLAwnDp1yuKn/gEgPT0dX3/9tckngCsrKxEaGorLly9j1KhRljfWSowxaLVau+xbKBRa1b876+lnbQ579++PPvoIGzduxI0bNwx1f958801s374d165d4/3z6slg6t98McbQprHPdd5F5BjX+WXLlkGhUOCHH34wrJs3bx68vb2xd+9eM46Ik52djVmzZqGhoQFDhgwx67P96TwwpaffTTk5OYiPj0djYyMkEonF+6Ci4P2PTqfDL7/8guzsbLS0tAAAgoODER8fjxEjRti5dYQQQgghhBBCgD4qCt7bWvV6jM4tscu+Lz80Ae48507Ozc1FTEyM0brCwkKMHz/ecJMLABISEqBWq1FUVIRZs2bZtL09KSoqglarRXx8vGFdUFAQxo8fj4KCAosSGv1ZSEgI/P39kZeXZ9cbvlqtFhkZGXbZd2pqKkQiEa9tTfVvR2Kr/l1YWIi4uDjDTVyAO2c3btxouAHbHzhK/+arTaPHrnU5dtn3qvfjIBTb/zpfWFiIl156yWhdQkKCxVOwWWOgnAemxMTEQKvV4sSJE4iLi7N3c0gfYIzh119/xaFDh3Dr1i0AgI+PD+bOnYuxY8faJEFHCCGEEEIIIaRvOXRCo7+oqKgwuqEFADKZDAEBAUbrvL29IRKJIJPJ+rJ5kMlkEIlE8Pb2NlofEBDQ521xFMOHD6fCvjyZ6t+OxFb9WyaTGdVG6IjR8V5/upFL/dv2evM6byqOva7PA+k8uJO7uzuGDBmCiooKSmgMAtevX0dWVpbhWiiRSDBz5kzExMRQsW9CCCGEEEII6cccOqHh5uSEyw9NsNu++VIqlSannTD15B9jzGGeCLRHW/7xj3/ghRdeMLz+4YcfMGPGjD5tA8Dd2Ghtbe3z/XYmFAqtmuve2n3z1V3/dnSW9O87t++YkY9vHOrf5nMROWHV+/a5uewicpzrvKm+Z6/fFY58Htx7772orKwEAMyYMcNomi4++tO5QSwjl8tx5MgRnDlzBgDg7OyMadOm4cEHH7RqqjFCCCGEEEIIIY7BoRMaAoGA97RP9uTr64uGhgajdYGBgV0KujY0NECr1XZ5Ere3BQYGQqPRoKGhwegp9ps3b2L69Ol92pbFixdj6tSphtfDhw/v0/13qK+vh5+fn1323UEgEPCe9smeTPVvR2Kr/h0YGNjlifibN28CAO9zlvq3+QQCAe9pn+ypN6/z3fW9vv5d0VNbAMc4Dw4ePGioPWTJzen+dG4Q86hUKuTn5+PYsWNoa2sDAEyYMAGzZ8/uMoKPEEIIIYQQQkj/xf/xVNKtqKgolJWVGa2LjY1FaWkpampqDOuysrIgFosRHR3dp+2Ljo6GUCjEoUOHDOtqampQWlra5wkNT09PhIeHGxZ7PC2pUqlw+fJlREVF9fm++yNT/duR2Kp/x8bGIjc3FxqNxrAuKysLQUFBXabg6Q7174GrN6/zsbGxRv23I05fX5872uLI50FISIghrrmJksuXL0OlUtG5McDodDqcOHECH3zwAfLz89HW1oaQkBCsXLkSjz32GCUzCCGEEEIIIWSAcegRGv1FR8HUzk+Ix8fHIzIyEsnJyXjrrbdQX1+PDRs2YOXKlT1Wab+TRqMx3ETTaDSorq5GcXExPDw8EB4eziuGVCrFc889h/Xr12Po0KHw8fHBhg0bMGHCBMyZM8esYy0rK4NGo0F9fT2amppQXFwMAJg0aZJZce5UX1+PqqoqXL9+HQBw4cIFANzTwoGBgbzjXLp0Cc3NzZDJZFAqlYb2RUZGGkZDHDt2DGKxGLGxsVa1ebAw1b8Bfj/ru3Gk/p2UlITXX38dK1asQGpqKi5evIiMjAy89tprVk/9Q/27/+vN6/y6devw0EMPYdu2bXjkkUfwzTff4PDhw8jPzzerjTKZDDKZDJcuXQIAlJSUwNPTE8HBwfDx8eEVoz+cB6bw+d2Ul5eHUaNGYfTo0VbtizgGxhguXLiAQ4cOoa6uDgAwdOhQzJ07F2PGjHGY6T0JIYQQQgghhNgY62NyuZwBYHK5vMt7SqWSlZWVMaVS2dfNstq0adPYxx9/bLSusrKSLVy4kEkkEubj48PWrFnDVCqV0TYA2O7du7uNW15ezgB0WeLi4gzb7N69m93tn1KpVLI1a9YwHx8fJpFIWGJiIquqqjLaJi4uji1fvrzHOCEhISbbc2d7jx492mOcO3Ucw51LWlqaYZvly5cbHbcpcXFxJuOUl5cbtlm1ahV74YUXzGrfYGeqf/P5Wfe3/n3mzBk2Y8YMJhaLWWBgIEtPT2d6vb5Le6l/D069dZ1njLEvv/ySjRkzhgmFQjZ27Fi2f/9+o/f5nAdpaWkm+0fnfQ+E88CUu/1uYoyx+Ph4tnXrVrNj36k/f1cZKKqrq9nu3btZWloaS0tLY9u2bWPHjx9nbW1t9m4aIYQQQgghhBAL9ZQ36EzAWHu1zz6iUCgglUohl8u7PMGqUqlQXl6OsLCwfleE+ODBg9iwYQNKS0vhxLOgeEVFBSIiIlBWVoaIiAiL952eno7s7GxkZ2dbHAMAQkNDkZ6ejhUrVlgcIzs7G0uWLMGVK1dsPs3DzJkzMXPmTKSnp1sco7a2FmPHjsXPP/+MsLAw2zVugKP+zaH+PbjRecBx9PPAlNLSUjz88MP49ddfIZVKrYrVn7+r9HeNjY3497//3aXg94wZM+jfghBCCCGEEEL6uZ7yBp3RlFM2smDBAly8eBHV1dUYOXIkr89kZmZi1apVVt3kAoAff/wR77//vlUxzp8/D09PTzz99NNWxcnMzERqaqrNb3I1NTXh8uXL+P77762KU15ejp07d9LNXjNR/+ZQ/x7c6DzgOPp5YMr169fx2WefWZ3MIPahUqmQl5eHY8eOQafTAeAKfj/88MMYMmSIfRtHCCGEEEIIIaRP0QgNQgghhBCe6LtK39HpdCgqKkJ2djZaW1sBcIXh4+PjzS4KTwghhBBCCCHEsdEIDUIIIYQQ0u8wKvhNCCGEEEIIIaQblNAghBBCCCEOobq6GllZWaisrAQAuLm5YebMmYiOjoazs7OdW0cIIYQQQgghxN4ooUEIIYQQQuyqsbERR44cQUlJCQDAxcUF06ZNw4MPPkhTexFCCCGEEEIIMaCEBiGEEEIIsQtTBb/vu+8+zJ49mwp+E0IIIYQQQgjpghIahBBCCCGkT+l0Ovz888/Izs6GUqkEAISGhiI+Ph5BQUF2bh0hhBBCCCGEEEdFCQ1CCCGEENInGGM4f/48Dh06hPr6egCAr68v5s6di3vuuYcKfhNCCCGEEEII6RElNAghhBBCSK+7du0asrKyUFVVBYAr+D1r1ixMnjyZCn4TQgghhBBCCOHFyd4NGCjq6urg7++PiooKezeFtCspKcGIESPQ0tJi76b0e9S/+68dO3Zg8eLF9m7GgEDnwcD3+OOP45133rF3MwachoYG/POf/8Rf/vIXVFVVwcXFBTNmzMDatWtx//33UzKDEEIIIYQQQghvlNCwka1bt2LRokUIDQ01rKuqqsKiRYvg7u4OX19frF27FhqNxuzY+/fvR2RkJMRiMSIjI3HgwAGzY+zatQszZ86El5cXBAIBGhsbzY4BcEmCuLg4SCQSDB8+HJs3bwZjzOw4O3fuRFhYGFxdXREdHY28vDyzYzQ0NCA5ORlSqRRSqRTJyclGxzVhwgRMmTIF7777rtmxiTFT/XvdunWIjo6GWCzGpEmTLIp79uxZPPbYYwgNDYVAIMB7771nURxb9e871dTUICkpCWPGjIGTkxNSUlJsEhfou3Ny5cqVOHnyJPLz823U8sGrt84DU3Jzc7Fo0SIEBQVBIBDg66+/tijOli1bMH36dLi5udm0wLKtzl1T7Nnm1157DVu2bIFCobDZfgczpVKJrKws7NixA6WlpQCAiRMn4sUXX8TDDz8MV1dXO7eQEEIIIYQQQkh/QwkNG1Aqlfj000/x/PPPG9bpdDosXLgQLS0tyM/Px759+7B//36sX7/erNiFhYVYtmwZkpOTcfr0aSQnJ2Pp0qU4fvy4WXFaW1sxb948pKammvW5zhQKBebOnYugoCCcPHkS27dvx9tvv23206xffPEFUlJSsGnTJpw6dQozZszA/PnzDVNQ8JWUlITi4mJkZmYiMzMTxcXFSE5ONtrmmWeewUcffQSdTmdWbHKbqf4NcPOgP/vss1i2bJnFsVtbWzFq1Ci8+eabCAwMtCqOtf3bFLVaDT8/P2zatAkTJ060aey+OifFYjGSkpKwfft2WzR70OrN88CUlpYWTJw4ETt27LAqjkajwRNPPIHf//73NmoZx1bnrin2bPN9992H0NBQ/OMf/7DpvgebtrY2HDt2DB988AEKCgqg0+kQGhqKVatWYcmSJZBKpfZuIiGEEEIIIYSQfkrALHm83goKhQJSqRRyuRxeXl5G76lUKpSXlxue3GeMQam1z41oidCZd2HKr776Ci+88AJqa2sN63744QckJibi6tWrCAoKAgDs27cPK1aswM2bN7sce3eWLVsGhUKBH374wbBu3rx58Pb2xt69e804Ik52djZmzZqFhoYGs598/eijj7Bx40bcuHEDYrEYAPDmm29i+/btuHbtGu+f19SpUzF58mR89NFHhnXjxo3Do48+iq1bt/KKce7cOURGRuLYsWOYOnUqAODYsWOIjY3F+fPnMWbMGADcjTEvLy8cPHgQs2fPNudwex1jDHq90i77dnKSWNW/O0tPT8fXX3+N4uJiq9oUGhqKlJQUq0ZBWNO/72bmzJmYNGmSTZ9EB/rmnMzJyUF8fDwaGxshkUhs2n5rMcbQplbbZd8uYrHDnQemCAQCHDhwAI8++qjFMfbs2YOUlBSbjV7qzBbnrin2avPrr7+OI0eOIDc31+Rn7/yuQm5jjOHcuXM4fPiwUcHv+Ph4REREUMFvQgghhBBCCCHd6ilv0JlDFwVXanWIfO1Hu+y7bHMC3ET8fjy5ubmIiYkxWldYWIjx48cbkhkAkJCQALVajaKiIsyaNYtX7MLCQrz00ktG6xISEmx+U5VvW+Li4gw3TjvasnHjRlRUVCAsLOyuMTQaDYqKivDqq68arY+Pj0dBQYFZbZFKpYZkBgBMmzYNUqkUBQUFhoSGSCTCxIkTkZeX53AJDb1eieycCXbZ98y4Ejg7u/Ha1lT/Jo6B7zkZExMDrVaLEydOIC4uzl7NNalNrcYHyx+3y77X/u8/IeR5Q5rOg8FjypQp2Lp1K9RqtdG5RXp2Z8Fvd3d3zJo1C1FRUVQjgxBCCCGEEEKIzTh0QqO/qKioMEpcAIBMJkNAQIDROm9vb4hEIshkMt6xTcUJCAgwK4atyGQyo7njO9rS8R6fhMatW7eg0+msPiaZTAZ/f/8u6/39/bvEGT58OBXxtYKp/k0cA99z0t3dHUOGDEFFRYXDJTT6CzoPBo/hw4dDrVZDJpMhJCTE3s1xeA0NDThy5IihRoaLiwtiY2PxwAMP0AgWQgghhBBCCCE259AJDYnQGWWbE+y2b76USqXJ/7SbmlqBMWb2lAt3bm9JDFsx1RZT6y2JY22M7uJIJBK0traaFbsvODlJMDOuxG775qu7/j3QeHh4GP7+1FNP4eOPP7ZJ3IyMDGRkZBhel5WVITg42CaxAf7npKOeBy5iMdb+7z/ttm++eus8yMvLw/z58w2vP/nkEzz55JM234+lqqqqEBkZaXidmppqs1o1q1evxt///nfD6+bmZpvEtbbNHdOyOeL54kiUSiXy8vJw/PhxQ52qiRMnYvbs2VQjgxBCCCGEEEJIr3HohIZAIOA97ZM9+fr6oqGhwWhdYGBgl8LdDQ0N0Gq1XUYn9CQwMLDLiIObN2+aFcNWumsLAN7t8fX1hbOzs9XHFBgYiBs3bnRZX1tb2yVOfX09Ro8ezTt2XxEIBLynfbInU/17IOpc+4BvjRs+Vq9ejaVLlxpe2/Ipf3POyfr6evj5+dls37YiEAh4T/tkT711HsTExBj1PXtc23sSFBRk1D4fHx+bxd68eTM2bNhgs3gdrG1zR+0HRzxfHEFbWxt+/vln5OTkQKnk6kCFhYUhPj4ew4YNs3PrCCGEEEIIIYQMdI6fLegHoqKijJ4yBYDY2Fhs2bIFNTU1hv/gZ2VlQSwWIzo6mnfs2NhYHDp0yKiORlZWFqZPn26bxpshNjYWqamp0Gg0EIlEhrYEBQV1mfamOyKRCNHR0Th06BCWLFliWH/o0CE88sgjZrVFLpfjxIkTmDJlCgDg+PHjkMvlXX42paWlePxx+8zRPxCY6t8DUXh4eK/E9fHxselN4M74npOXL1+GSqVCVFRUr7RjMOit80AikfRa37MFFxeXXmufv7+/yakDrWVtm0tLSzFixAj4+vrasFX9X0fB70OHDhmSe35+fpg7dy4V/CaEEEIIIYQQ0mcooWEDHUV4Gxoa4O3tDYArch0ZGYnk5GS89dZbqK+vx4YNG7By5Uqznv5et24dHnroIWzbtg2PPPIIvvnmGxw+fBj5+flmtVEmk0Emk+HSpUsAgJKSEnh6eiI4OJj3zdakpCS8/vrrWLFiBVJTU3Hx4kVkZGTgtddeM+tGxssvv4zk5GTExMQgNjYWu3btQlVVFVavXs07xrhx4zBv3jysXLkSn3zyCQBg1apVSExMNBQEB7h576urqzFnzhzesYkxU/0bAC5duoTm5mbIZDIolUrDE9GRkZGGm+t3o9FoUFZWZvh7dXU1iouL4eHhYdYNSVv07+50HFdzczNqa2tRXFwMkUhkNKWNJfrynMzLy8OoUaMccqRSf9Gb54Epzc3Nhr4BAOXl5SguLoaPj49ZU5ZVVVWhvr4eVVVV0Ol0hvaFh4cbTbNmLludu47Y5ry8PMTHx1t1DAPN1atXkZWVhatXrwKggt+EEEIIIYQQQuyI9TG5XM4AMLlc3uU9pVLJysrKmFKp7OtmWW3atGns448/NlpXWVnJFi5cyCQSCfPx8WFr1qxhKpXKaBsAbPfu3T3G/vLLL9mYMWOYUChkY8eOZfv37zd6f/fu3exu/5RpaWkMQJel877j4uLY8uXLe4xz5swZNmPGDCYWi1lgYCBLT09ner3e8H55eTkDwI4ePdpjnA8//JCFhIQwkUjEJk+ezHJycrq0NyQkpMcYdXV17Mknn2Senp7M09OTPfnkk6yhocFom4yMDJaQkNBjHHJ3pvp3XFycyT5VXl5u2OZu/bujv9y5xMXFGbbpy/5tiqm4nfvm0aNHuxw3H311TjLGWHx8PNu6datZ7SNd9dZ5YEpHv7pz6dwf+Fwnly9fbjJO52t0SEgIS0tLM6t9tjp3Ha3NSqWSeXl5scLCwm7j9OfvKuaqq6tj//d//8fS0tJYWloa+9Of/sSOHDnS5bsMIYQQQgghhBBirZ7yBp0JGGuvINtHFAoFpFIp5HJ5l5EKKpUK5eXlCAsL63dFiA8ePIgNGzagtLQUTk5OvD5TUVGBiIgIlJWVISIiwuJ9p6enIzs7G9nZ2RbHAIDQ0FCkp6djxYoVFsfIzs7GkiVLcOXKFaOnmM3V0YY9e/ZYHEOtViMiIgJ79+7FAw88YHEcQv27J3v27MGWLVtQVlYGoVBo09i2aHNpaSkefvhh/Prrr1So10r2PA9MscV1UqlUwsfHBwcPHsSsWbNs07B2tjp379Sbbf7www/xzTffICsrq9tt+vN3Fb6USiVyc3Nx/Phx6PV6AMCkSZMwe/Zsm9YYIoQQQgghhBBCOvSUN+iMppyykQULFuDixYuorq7GyJEjeX0mMzMTq1atsvom148//oj333/fqhjnz5+Hp6cnnn76aaviZGZmIjU11apkBgDk5OQgNzfXqhiVlZXYtGkTJTNsgPp39zIzM5GRkWHzZIat2nz9+nV89tlnlMywAXueB6bY4jqZk5OD2bNn2zwxANjm3DWlN9ssFAqxfft2m8ftL9ra2nDy5Enk5ORApVIBoILfhBBCCCGEEEIcC43QIIQQQgjhaSB+V2GMoaysDIcPHzYq+B0fH4/w8HAq+E0IIYQQQgghpNfRCA1CCCGEENKjq1ev4scff8S1a9cAcAW/Z8+ejUmTJlHBb0IIIYQQQgghDocSGoQQQgghg0x9fT0OHz6MsrIyAICLiwseeOABTJ8+HWKx2M6tI4QQQgghhBBCTKOEBiGEEELIINHa2orc3FycOHHCUPA7KioKs2bNooLfhBBCCCGEEEIcHiU0CCGEEEIGuLa2Npw4cQK5ubmGgt+jRo1CfHw8AgMD7dw6QgghhBBCCCGEH0poEEIIIYQMUIwxnD17FocPH0ZjYyMAwN/f31DwmxBCCCGEEEII6U8ooUEIIYQQMgBVVVUhKyvLUPDbw8MDs2bNQlRUFJycnOzcOkIIIYQQQgghxHyU0CCEEEIIGUDuLPgtFAoxffp0KvhNCCGEEEIIIaTfo8fzbKSurg7+/v6oqKiwd1NIu5KSEowYMQItLS32bkq/R/17YNmwYQPWrl1r72b0O3Qe9F87duzA4sWL7d2MXtfa2orMzEzs2LHDkMyIiorCiy++iFmzZlEygxBCCCGEEEJIv0cJDRvZunUrFi1ahNDQUMO6qqoqLFq0CO7u7vD19cXatWuh0WjMinv27Fk89thjCA0NhUAgwHvvvWdR+9RqNV588UX4+vrC3d0dixcvNkxBYY6SkhLExcVBIpFg+PDh2Lx5MxhjZsfZuXMnwsLC4OrqiujoaOTl5Zkdo6GhAcnJyZBKpZBKpUhOTjbMDw4AEyZMwJQpU/Duu++aHZsYM9W/161bh+joaIjFYkyaNMni2Pv370dkZCTEYjEiIyNx4MABs2PYqn/fqaamBklJSRgzZgycnJyQkpJidcwOu3btwsyZM+Hl5QWBQGDUd63Bp81/+MMfsHv3bpSXl9tkn4NFb54Hd8rNzcWiRYsQFBQEgUCAr7/+2qI4d7tOWqq//W5auXIlTp48ifz8fIva6eja2tpQUFCADz74AMeOHYNer8fo0aOxevVqPPLII/Dy8rJ3EwkhhBBCCCGEEJughIYNKJVKfPrpp3j++ecN63Q6HRYuXIiWlhbk5+dj37592L9/P9avX29W7NbWVowaNQpvvvkmAgMDLW5jSkoKDhw4gH379iE/Px/Nzc1ITEyETqfjHUOhUGDu3LkICgrCyZMnsX37drz99tt45513zGrLF198gZSUFGzatAmnTp3CjBkzMH/+fFRVVZkVJykpCcXFxcjMzERmZiaKi4uRnJxstM0zzzyDjz76yKzjJMZM9W+AKzT77LPPYtmyZRbHLiwsxLJly5CcnIzTp08jOTkZS5cuxfHjx82KY4v+bYparYafnx82bdqEiRMnWhXrTq2trZg3bx5SU1NtGpdPmzsKAn/88cc23fdA1pvngSktLS2YOHEiduzYYVUcPtdJS/S3301isRhJSUnYvn27xW11RIwxlJaWYseOHcjKyoJKpYK/vz+eeuopJCcnW/VvQwghhBBCCCGEOCTWx+RyOQPA5HJ5l/eUSiUrKytjSqWSW6HXM6Zuts+i1/M+pv379zNfX1+jdQcPHmROTk6surrasG7v3r1MLBabPHY+QkJC2Lvvvmv25xobG5lQKGT79u0zrKuurmZOTk4sMzOTd5ydO3cyqVTKVCqVYd3WrVtZUFAQ05vx85oyZQpbvXq10bqxY8eyV199lXeMsrIyBoAdO3bMsK6wsJABYOfPnzesU6vVTCwWsyNHjvCO3Vf0ej1rbmuzy2LOv5ep/t1ZWloamzhxokU/g6VLl7J58+YZrUtISGC//e1vecewVf++m7i4OLZu3Tqbxetw9OhRBoA1NDTYPHZPbd6zZw8bOXKkzfdpLr1ez3TqNrssjnIe3A0AduDAAbM/x/c6aa3+8rspOzubiUQi1traanZbO+vyXcVOKioq2K5du1haWhpLS0tjb731FisqKmI6nc6u7SKEEEIIIYQQQizRU96gM8cuCq5tBTKC7LPv1OuAyJ3Xprm5uYiJiTFaV1hYiPHjxyMo6Hb7ExISoFarUVRUhFmzZtm0uT0pKiqCVqtFfHy8YV1QUBDGjx+PgoICJCQk8IpTWFiIuLg4ozm4ExISsHHjRlRUVCAsLOyuMTQaDYqKivDqq68arY+Pj0dBQQHPI+LaIpVKMXXqVMO6adOmQSqVoqCgAGPGjAEAiEQiTJw4EXl5eZg9ezbv+H2hVa/H6NwSu+z78kMT4O7szGtbU/3bVgoLC/HSSy8ZrUtISDBr+hpb9e/BZsqUKbh69SoqKysREhJit3YwrR7XX+N/7ttS0ObpEIjsfx70Fr7XSXvp699NMTEx0Gq1OHHiBOLi4mx7MH2orq4Ohw8fxrlz5wBwBb8feOABTJ8+HSKRyM6tI4QQQgghhBBCepdjJzT6iYqKCqPEBQDIZDIEBAQYrfP29oZIJIJMJuvL5kEmk0EkEsHb29tofUBAgFltkclkRnPHd8ToeI9PQuPWrVvQ6XRdfjaWtMXf37/Len9//y5xhg8fTkV8rWCqf9uKqfPEkr5gi/492AwfPhwA9+9rz4RGf9Gb50FvMec6aQ99/bvJ3d0dQ4YMQUVFRb9MaLS2tiInJwcnT56EXq+HQCBAVFQUZs2aBU9PT3s3jxBCCCGEEEII6ROOndAQunEjJey1b56USiVcXV27rBcIBF3WMcZMrrcHS9py5/asveiqLeJYG6O7OBKJBK2trWbF7gtuTk64/NAEu+2br+76t63Yoi+YYm4cDw8Pw9+feuopm9WXyMjIQEZGhuF1WVkZgoODbRLbmjZLJBIAsPu5IRA6IWjzdLvtm6/eOg/y8vIwf/58w+tPPvkETz75pM3iW/t7qKqqCpGRkYbXqampNq/7cqfe/N3kqL8PetIxqiQ3NxdqtRoAEB4ejrlz53ZJCBNCCCGEEEIIIQOdYyc0BALe0z7Zk6+vLxoaGozWBQYGdils3NDQAK1W2+c3IAIDA6HRaNDQ0GD0JOzNmzcxfTr/G4mBgYFdnpq9efMmAPA+Jl9fXzg7O5uMY87PJTAwEDdu3Oiyvra2tkuc+vp6jB49mnfsviIQCHhP+2RPpvq3rXTXp8ztC7bo38XFxYa/e3l58f7c3axevRpLly41vLblU/7WtLm+vh4A4OfnZ7P2WEIgEPCe9smeeus8iImJMfp3tOXvB3Ouk90JCgoyap+Pj4+tmmeX30319fV27/N8sfaC30eOHEFjYyMA7njmzp2L8PBw+zaOEEIIIYQQQgixE/6Pp5JuRUVFoayszGhdbGwsSktLUVNTY1iXlZUFsViM6OjoPm1fdHQ0hEIhDh06ZFhXU1OD0tJSs24axcbGIjc3FxqNxrAuKysLQUFBXab76I5IJEJ0dLRRWwDg0KFDZrdFLpfjxIkThnXHjx+HXC7vEqe0tBRRUVG8YxNjpvq3rcTGxnbpC1lZWWb1BVv17/DwcMNiapoeS/n4+BjFdnGxXR7ZmjaXlpZCKBTi3nvvtVl7BrLeOg8kEonRv6Mtpw4y5zrZHRcXF6P22TKh0de/my5fvgyVStUvfh9UVlbiL3/5C/bv34/GxkZ4enrikUcewQsvvEDJDEIIIYQQQgghg5pjj9DoJzqKj3Z+yjQ+Ph6RkZFITk7GW2+9hfr6emzYsAErV64060lqjUZjuImm0WhQXV2N4uJieHh48L6pIZVK8dxzz2H9+vUYOnQofHx8sGHDBkyYMAFz5szh3ZakpCS8/vrrWLFiBVJTU3Hx4kVkZGTgtddeM2t6kJdffhnJycmIiYlBbGwsdu3ahaqqKqxevZp3jHHjxmHevHlYuXIlPvnkEwDAqlWrkJiYaFTotqKiAtXV1WYdJzFmqn8DwKVLl9Dc3AyZTAalUml4ijsyMpJ3Ydp169bhoYcewrZt2/DII4/gm2++weHDh5Gfn8+7fbbq393pOK7m5mbU1taiuLgYIpHIaBoeS8hkMshkMly6dAkAUFJSAk9PTwQHB1t905hPm/Py8jBjxgzD1FOkZ715HpjS3Nxs6BsAUF5ejuLiYvj4+PCesozvddIS/fF3U15eHkaNGuWQI/Y63Lp1C4cPH8b58+cBcAW/H3zwQcTGxlLBb0IIIYQQQgghBABYH5PL5QwAk8vlXd5TKpWsrKyMKZXKvm6W1aZNm8Y+/vhjo3WVlZVs4cKFTCKRMB8fH7ZmzRqmUqmMtgHAdu/e3W3c8vJyBqDLEhcXZ9hm9+7d7G7/lEqlkq1Zs4b5+PgwiUTCEhMTWVVVldE2cXFxbPny5T3GOXPmDJsxYwYTi8UsMDCQpaenM71e36W9R48e7THOhx9+yEJCQphIJGKTJ09mOTk5Ru+npaWxkJCQHmPU1dWxJ598knl6ejJPT0/25JNPsoaGBqNtMjIyWEJCQo9xyN2Z6t9xcXEm+2Z5eblhm7v1b8YY+/LLL9mYMWOYUChkY8eOZfv37zd6vy/7tymmjrFz3zx69GiX4+YjLS3NZOzOP6/eajNjjN1zzz1s7969ZscezHrzPLhTR7+6c+ncH2x1nQwJCWFpaWlmta+//W5ijLH4+Hi2detWs46zuzbb+rtKc3Mz+9e//sVef/11lpaWxtLT09m3337LFAqFzfZBCCGEEEIIIYQ4sp7yBp0JGGuvnNlHFAoFpFIp5HJ5l5EKKpUK5eXlCAsL69UixL3h4MGD2LBhA0pLS+HEs+ByRUUFIiIiUFZWhoiICIv3nZ6ejuzsbGRnZ1scAwBCQ0ORnp6OFStWWBwjOzsbS5YswZUrV4yeYjZXRxv27NljcQy1Wo2IiAjs3bsXDzzwgMVxCPXvnuzZswdbtmxBWVkZhEKhTWP3Vpv/9a9/4b/+679w5swZm06BNdDZ8zwwxRbXSaVSCR8fHxw8eBCzZs2yTcPaOdK5W1paiocffhi//vorpFKpVe2x5XcVUwW/IyIiMHfuXJtOfUcIIYQQQgghhDi6nvIGndGdLBtZsGABLl68iOrqaowcOZLXZzIzM7Fq1Sqrb3L9+OOPeP/9962Kcf78eXh6euLpp5+2Kk5mZiZSU1OtSmYAQE5ODnJzc62KUVlZiU2bNlEywwaof3cvMzMTGRkZNk9m9GabW1pasHv3bkpmmMme54EptrhO5uTkYPbs2TZPZgCOde5ev34dn332mdXJDFvR6/U4e/YsDh8+DLlcDoAr+B0fH+/QU2IRQgghhBBCCCH2RiM0CCGEEEJ4sva7SkVFBbKysnD9+nUAgKenJ2bPno2JEyfyHvlDCCGEEEIIIYQMNDRCgxBCCCHEQVDBb0IIIYQQQgghxHqU0CCEEEII6SUtLS3IycnBzz//DL1eD4FAgMmTJ2PmzJnw9PS0d/MIIYQQQgghhJB+hRIahBBCCCE2ptVqcfz4ceTl5VHBb0IIIYQQQgghxEYooUEIIYQQYiN6vR6lpaU4cuSIoeB3YGAg4uPjMWrUKDu3jhBCCCGEEEII6d8ooUEIIYQQYgOmCn4//PDDuO+++6jgNyGEEEIIIYQQYgOU0CCEEEIIscKtW7dw6NAhXLhwAQAgEonw4IMPYtq0aVTwmxBCCCGEEEIIsSFKaBBCCCGEWKClpQXZ2dn4+eefwRiDQCBAdHQ0Zs6cCQ8PD3s3jxBCCCGEEEIIGXBo/gMbqaurg7+/PyoqKuzdFNKupKQEI0aMQEtLi72b0u9R/+6/duzYgcWLF9u7GQMCnQeOx17XecYYfv75Z7z//vs4efIkGGO455578Pvf/x6JiYmUzCCEEEIIIYQQQnoJJTRsZOvWrVi0aBFCQ0MN66qqqrBo0SK4u7vD19cXa9euhUajMTv2/v37ERkZCbFYjMjISBw4cMDsGGq1Gi+++CJ8fX3h7u6OxYsX49q1a2bHKSkpQVxcHCQSCYYPH47NmzeDMWZ2nJ07dyIsLAyurq6Ijo5GXl6e2TG2bNmC6dOnw83NDUOGDOny/oQJEzBlyhS8++67Zscmxkz173Xr1iE6OhpisRiTJk2yKO7Zs2fx2GOPITQ0FAKBAO+9955FcWzVv+9UU1ODpKQkjBkzBk5OTkhJSbE6Zoddu3Zh5syZ8PLygkAgQGNjo0Vx7nZOrly5EidPnkR+fr6NWj54DYbrvEqlwooVKzBhwgS4uLjg0UcfNbsdAJCbm4tFixYhKCgIAoEAX3/9tUVxHO06zxiDUqlEU1MTjh07Bo1Gg8DAQDz99NNISkqCv79/n7SDEEIIIYQQQggZrCihYQNKpRKffvopnn/+ecM6nU6HhQsXoqWlBfn5+di3bx/279+P9evXmxW7sLAQy5YtQ3JyMk6fPo3k5GQsXboUx48fNytOSkoKDhw4gH379iE/Px/Nzc1ITEyETqfjHUOhUGDu3LkICgrCyZMnsX37drz99tt45513zGrLF198gZSUFGzatAmnTp3CjBkzMH/+fFRVVZkVR6PR4IknnsDvf//7brd55pln8NFHH5l1nMSYqf4NcDf2nn32WSxbtszi2K2trRg1ahTefPNNBAYGWhzHFv3bFLVaDT8/P2zatAkTJ060KtadWltbMW/ePKSmplocg885KRaLkZSUhO3bt9ui2YPWYLnO63Q6SCQSrF27FnPmzDFr/521tLRg4sSJ2LFjh8UxAMe6zqvVaty6dQtNTU3Q6/Vwd3fHkiVLsGrVKowaNapX900IIYQQQgghhJB2rI/J5XIGgMnl8i7vKZVKVlZWxpRKJWOMMb1ez1o0LXZZ9Ho972Pav38/8/X1NVp38OBB5uTkxKqrqw3r9u7dy8Risclj787SpUvZvHnzjNYlJCSw3/72t7xjNDY2MqFQyPbt22dYV11dzZycnFhmZibvODt37mRSqZSpVCrDuq1bt7KgoCCzfl5Tpkxhq1evNlo3duxY9uqrr/KO0dnu3buZVCo1+Z5arWZisZgdOXLEoti9Sa/Xsxa11i6Ltf27s7S0NDZx4kSrfx4hISHs3XffNftzturfdxMXF8fWrVtns3gdjh49ygCwhoYGsz/L95zMzs5mIpGItba22qLJNqXX65larbbLQtf5ni1fvpw98sgjFn22MwDswIEDVsWw53Veo9GwW7duserqalZdXc0qKyvZL7/8whQKRa/sjxBCCCGEEEIIGYx6yht05tBFwZVtSkz9fKpd9n086TjchG68ts3NzUVMTIzRusLCQowfPx5BQUGGdQkJCVCr1SgqKsKsWbN4xS4sLMRLL71ktC4hIcGsqXmKioqg1WoRHx9vWBcUFITx48ejoKAACQkJvNsSFxcHsVhs1JaNGzeioqICYWFhd42h0WhQVFSEV1991Wh9fHw8CgoKeB4RfyKRCBMnTkReXh5mz55t8/jWUGp1iHztR7vsu2xzAtxE/E5/U/3bkdiqf/dHfM/JmJgYaLVanDhxAnFxcfZqrklarRYZGRl22XdqaipEIhGvbQfLdb4/6q3rvE6nQ1NTE1pbWw3r3NzcIBQK0dLSAqFQaLN9EUIIIYQQQgghhB+acsoGKioqjG5oAYBMJkNAQIDROm9vb4hEIshkMt6xTcUJCAgwO4ZIJIK3t7fVcUy1peM9Pm7dugWdTmf1MZlj+PDhVMTXCqb6tyOxVf/uj/iek+7u7hgyZAidB1YYLNf5/sqW13m9Xo+mpibcvHnTkMwQi8Xw8/PDkCFD4OzsbJP9EEIIIYQQQgghxHwOPUJD4iLB8STz5hC35b75UiqVcHV17bJeIBB0WccYM7m+J3dub0kMU2zVFlPrLYlji2MyRSKRGD1h6ygkQmeUbbbPU9MSIf8bct31b0dnbp/y8PAw/P2pp57Cxx9/bJN2ZGRkGI1AKCsrQ3BwsE1iA/zPSUc9D4RCoVV1RKzdN1+D6TrfH9mif7P2gt8KhQJ6vR4A10e8vLyMRkERQgghhBBCCCHEfhw6oSEQCHhP+2RPvr6+aGhoMFoXGBjYpaBrQ0MDtFptlydxexIYGNjl6dqbN2+aHUOj0aChocHo6d2bN29i+vTpVrcFAO/2+Pr6wtnZ2epjMkd9fT1Gjx7dK7GtIRAIeE/7ZE+m+rcjsVX/Li4uNvzdy8vLZu1bvXo1li5danhty9Eu5pyT9fX18PPzs9m+bUUgEPCe9smeBst1vr+y9jqvVqshl8vR1tYGAHBycoKXlxckEsmgSAgRQgghhBBCCCH9BU05ZQNRUVEoKyszWhcbG4vS0lLU1NQY1mVlZUEsFiM6Opp37NjYWBw6dMhoXVZWllk3qKKjoyEUCo3i1NTUoLS01Kw4sbGxyM3NhUajMWpLUFAQQkNDecUQiUSIjo7uckyHDh3qtZtupaWliIqK6pXYg4Gp/u1IbNW/w8PDDYu/v7/N2ufj42MU28XFdkksvufk5cuXoVKp6DywwmC5zvdXll7ntVot6urqUFdXh7a2NggEAnh6esLf3x9ubm6UzCCEEEIIIYQQQhyM4z8e3g90FOHt/GRsfHw8IiMjkZycjLfeegv19fXYsGEDVq5cadbT3+vWrcNDDz2Ebdu24ZFHHsE333yDw4cPIz8/n3cMqVSK5557DuvXr8fQoUPh4+ODDRs2YMKECZgzZw7vOElJSXj99dexYsUKpKam4uLFi8jIyMBrr71m1k2fl19+GcnJyYiJiUFsbCx27dqFqqoqrF69mncMAKiqqkJ9fT2qqqqg0+kMT9iHh4cbpg+qqKhAdXW1WcdJjJnq3wBw6dIlNDc3QyaTQalUGn7+kZGRvJ+412g0hpvEGo0G1dXVKC4uhoeHB8LDw3nFsFX/7k7HcTU3N6O2thbFxcUQiUSIjIy0Kq5MJoNMJsOlS5cAACUlJfD09ERwcDB8fHx4xeB7Tubl5WHUqFEOOVKpvxgs13mAmxZNo9Ggvr4eTU1NhnNg0qRJvGM0Nzcb+jYAlJeXo7i4GD4+PmZNudZb1/nuCn57enpSjQzSd/Q6AALAiZ4vIoQQQgghhBDeWB+Ty+UMAJPL5V3eUyqVrKysjCmVyr5ultWmTZvGPv74Y6N1lZWVbOHChUwikTAfHx+2Zs0aplKpjLYBwHbv3t1j7C+//JKNGTOGCYVCNnbsWLZ//36j93fv3s3u9k+pVCrZmjVrmI+PD5NIJCwxMZFVVVUZbRMXF8eWL1/eY5wzZ86wGTNmMLFYzAIDA1l6ejrT6/WG98vLyxkAdvTo0R7jfPjhhywkJISJRCI2efJklpOTY/R+WloaCwkJ6THG8uXLGYAuS+d9Z2RksISEhB7jkLsz1b/j4uJM/vzLy8sN29ytf3f0lzuXuLg4wzZ92b9NMdW+zn3z6NGjXY6bj7S0NJOxO/+8bHFOMsZYfHw827p1q1ntI10Nlut8SEiIyb7Zgc91vuO8uHPpvG97XOd1Oh1TKBTs+vXrrLq6mlVXV7Nbt24xjUbD6/OM9e/vKsQO9HrGFDWMlecxdvKvjGWmMvaPZYx9EM3Y6z6MbQ1m7Ov/YOziIcba+PdDQgghhBBCCBloesobdCZgrL2CbB9RKBSQSqWQy+VdnmBVqVQoLy9HWFhYvytCfPDgQWzYsAGlpaVw4vmkXUVFBSIiIlBWVoaIiAiL952eno7s7GxkZ2dbHAMAQkNDkZ6ejhUrVlgcIzs7G0uWLMGVK1eMnuY3V0cb9uzZY3EMtVqNiIgI7N27Fw888IDFcQj1757s2bMHW7ZsQVlZmVlFpvmwRZtLS0vx8MMP49dff4VUKrVd4wYhOg84/fE6z2xY8Ls/f1chvUglB+ouA3WX7lguA5pmfjEk3sC4RcD4x4DQGYATjRYihBBCCCGEDB495Q06oymnbGTBggW4ePEiqqurMXLkSF6fyczMxKpVq6y6yQUAP/74I95//32rYpw/fx6enp54+umnrYqTmZmJ1NRUq25yAUBOTg5yc3OtilFZWYlNmzZRMsMGqH93LzMzExkZGTZPZtiqzdevX8dnn31GyQwboPOA09+u83cW/HZ2doanpycV/CbW07UBZ74A8t8F6i52v53ACRgSAgwNb19GA74RgM9ooKECOHsAOPct0FIL/PIZt7j7A/cuASY8Doy4H6C+SgghhBBCCCEAABqhQQghhJABR6vVQqFQQK1WAwAEAgE8PDzg7u7Oe4SNKfRdhQAA5NXA/ueBqoLb6zwCbicshkbcTmB4hwIud6ktpdcBFflccqPsG0BZf/s9aTAw/jfcyI3ACZTcIIQQQgghhAxINEKDEEIIIYOOqYLf7u7u8PDwoILfxDZ+/RE4sJpLOog8gbj/AiY/zU0ZZSknZ2BUHLcseAu4kg2U/BM4/z0grwJ+eo9bfO/hEhvjH+NGeRBCCCGEEELIIEMJDUIIIYT0e3q9Hi0tLWhubkbH4FNXV1d4enrafEo4Mki1aYB/bwYKtnOvh00EHt/NjciwJWchEDGXW7RK4GIWULqfS6Tc+hXI3sotgffdTm4M4TcNHiGEEEIIIYT0d5TQIIQQQki/ZcuC34R0q6ES+OezQPXP3Oupq4G5mwGXXu5jQgkQ+Qi3qBTAhR+A0n8Cl/8NyM5wy+E0YORUYPzjwL2PAh7+vdsmQgghhBBCCLEjSmgQQgghpF9SqVRQKBRU8Jv0rrJvgW/WAGo54CoFHtkJjEvs+3a4egETl3FLaz1Xa6N0P1d74+pxbsl8BQh7iBu1MW6RddNgEUIIIYQQQogDooQGIYQQQvoVUwW/PT094ebmZlXBb0KMaFXAoT8CJ3Zxr0fcDzz+V2BIsH3bBQBuPkDMM9yiqAHKvuZqblT/zNXfuJINfP8yED6HS26MmQ+IPezcaEIIIYQQQgixHiU0CCGEENIvUMFv0mfqLgNfruCmdAKAB9YBs//I1bdwNF7DgGm/55aGCm7URulXwI1S4NcfuMVFAoyZx01LFT4HELrau9WEEEIIIYQQYhFKaBBCCCHEoVHBb9KnznwJfJ8CaJoBt6HAkk+4At39gXcoMGM9t9w8357c+CdQfwU4e4BbxF7cdFTjfwOEzQSc6b8DhBBCCCGEkP6D5mWwkbq6Ovj7+6OiosLeTSHtSkpKMGLECLS0tNi7Kf0e9e/+4fvvv0dUVJShMDKxLToP+h5jDK2trbh58yaamprAGINQKMTQoUPh4+NjMplB5wGxWJMM2L8S+Op5LpkR8gCwOr//JDPu5D8WmL0JePEXYFU2ELsG8BoOqBVA8T+Avz8G/L97uKmpKn4CLD1nGAOUDUDNGeD8QeD4LiDrj9wIl7/MAf7fOGB7NPD5b4G8d4CqY0Cb2pZHSgghhBBCCBlEKKFhI1u3bsWiRYsQGhpqWFdVVYVFixbB3d0dvr6+WLt2LTQajdmx9+/fj8jISIjFYkRGRuLAgQNmx1Cr1XjxxRfh6+sLd3d3LF68GNeuXTMrhkqlwooVKzBhwgS4uLjg0UcfNbsdHXbu3ImwsDC4uroiOjoaeXl5ZsdoaGhAcnIypFIppFIpkpOT0djYaHh/woQJmDJlCt59912L20k4pvr3unXrEB0dDbFYjEmTJlkc21H6tyk1NTVISkrCmDFj4OTkhJSUFIviMMaQnp6OoKAgSCQSzJw5E2fPnjU7zt2uKYmJiRAIBPj8888taifpGd/zgDEGbZseLeo2tKjboNbq0KbTG0YW8JGbm4tFixYhKCgIAoEAX3/9tUVt3rJlC6ZPnw43NzcMGTLEohgAkJOTg+joaLi6umLUqFH4+OOPzY5h7nmgUqlQW1uLxsZG6PV6ODs7Y8iQIWhtbcXjjz9O5wGxHb0OOPE/wPYYoOT/AAiAuFeAp78FvILs3TrrCQRAUBSQsAVIKQWe+QG4/3nAzRdorQN+/hTYswB4917gx01A9S9ckqKDTgs0VgGVBcDpL4Dct4HvUriEyIdTga0jgG2hwCczgH2/A374L6DgA240yLWTQNN1oO4SN/XVkdeBvyYAbwYDuxcAR/4EXDoMqBT2+ukQQgghhBBC+hkaY24DSqUSn376KQ4ePGhYp9PpsHDhQvj5+SE/Px91dXVYvnw5GGPYvn0779iFhYVYtmwZ/vSnP2HJkiU4cOAAli5divz8fEydOpV3nJSUFHz33XfYt28fhg4divXr1yMxMRFFRUW85x3X6XSQSCRYu3Yt9u/fz3vfd/riiy+QkpKCnTt34oEHHsAnn3yC+fPno6ysDMHB/AttJiUl4dq1a8jMzAQArFq1CsnJyfjuu+8M2zzzzDNYvXo1Nm7cSPOrW8hU/wa4m5PPPvssjh8/jjNnzlgU25H6tylqtRp+fn7YtGmTVYmxP//5z3jnnXewZ88e3HPPPXjjjTcwd+5cXLhwAZ6enrxi8L2mPPPMM9i+fTueeuopi9tLuup8HjDGoNUxaNr0UGra8HhSMkJPnMC5s6U4L1NAq2MmkxcCAM5OAjg7OcHZSQAXJ0H7665/r29UYPyE+7B8+Qo88cTjFrdbo9HgiSeeQGxsLD799FOLYpSXl2PBggVYuXIl/v73v+Onn37Cf/zHf8DPzw+PPfYY7zh8z4OeCn4zxpCYmEjnAbGdG2eBb9dyxbQBYHg0MP/PwIgY+7artzg5ASHTuWXeNqA8h5uW6tx3XOKhcAe3uPtztTlabgFNNQDjMXrDzReQjuCWIcG3/+41ghvxcqOUS4pUHQNabwGVP3FLHgCBExAwnmtXcCy3eAb0+o+DEEIIIYQQ0v8ImDmPjNqAQqGAVCqFXC6Hl5eX0XsqlQrl5eWGJ/cZY2BKZV82z0AgkUAgEPDa9quvvsILL7yA2tpaw7offvgBiYmJuHr1KoKCuKf79u3bhxUrVuDmzZtdjr07y5Ytg0KhwA8//GBYN2/ePHh7e2Pv3r28Ysjlcvj5+eFvf/sbli1bBgC4fv06Ro4ciYMHDyIhIYFXnM5WrFiBxsZGi54anjp1KiZPnoyPPvrIsG7cuHF49NFHsXXrVl4xzp07h8jISBw7dsxw4/vYsWOIjY3F+fPnMWbMGADczTwvLy8cPHgQs2fPNrutvYoxQNt69+16g9CNe2KTB1P9u7P09HR8/fXXKC4uNrsZjtq/TZk5cyYmTZqE9957z6zPMcYQFBSElJQUvPLKKwC4RElAQAC2bduGF154gVccvteUyspKhIaG4vLlyxg1apRZbbUHxhj0evtc552cer7OM8agbtOjWd2GA199hVdffhEFpeXQmBht8dE7b+Loj//C//3IjTYTQAChMxe7Tc+gt+JX7cSR3vjg038gYeEiE0kQ4+RI5/c7H9uePXuQkpJiNIqNr1deeQXffvstzp07Z1i3evVqnD59GoWFhbxi8DkP+BT8doTz4M7vKqSf0iqBnD9zIwn0bVxdiTlpQPSz3E3/wUar4kZKlO4HLvwAtN1xXXYWcdNVSUcA0pHAkJG3ExbSkdx7Ijd++2KMG7FRWQBUFXJ/NlZ23c5nFBA8HQhpT3D4jOL93YUQQgghhBDS//SUN+jMoUdoMKUSFyZH22XfY34pgsCN33/McnNzERNj/CRfYWEhxo8fb7jhAgAJCQlQq9UoKirCrFmzeMUuLCzESy+9ZLQuISHBrJuqRUVF0Gq1iI+PN6wLCgrC+PHjUVBQYLMbvnxoNBoUFRXh1VdfNVofHx+PgoIC3nEKCwshlUqNnuKfNm0apFIpCgoKDAkNkUiEiRMnIi8vz/ESGtpWIMNOU1mkXgdE7rw2NdW/bWWg9W9TysvLIZPJjNonFosRFxeHgoIC3gkNvteUkJAQ+Pv7Iy8vr18kNPR6JbJzJthl3zPjSuDsbHyd1+kZWtRtaFJp0aRqg0bHPZWck5uLcRMmQd2mA8CNGhA5CyB0doLIxQnuYhcInZ0w2s8DQmcnCJ2NEwp6xqDTc0ubnkGn17f/2b7omOF15/UMzNAulVZn1vFxCQ4u4VHbpAZjwPVGZTcJECe4OAng5NT1ZmFhYaFR/wW4vvfpp59Cq9XyKsrd03nw008/ISkpqUvBby8vL7i4GH9NGajnAeljV7K5KZMayrnX4xZxozIGwvRSlhK6AuMSuUXTAtReAJpvAO5+XNLC3d92iR6BAPCN4Jbo5dw6xfX25EYh9+eNs1wh8/orQPHfuW08AoDgabeTHAHjAScafUsIIYQQQshg49AJjf6ioqLC6OYKAMhkMgQEGA+V9/b2hkgkgkwm4x3bVJyAgACzY4hEInh7e1sVxxZu3boFnU5nk2Py9/fvst7f379LnOHDh1MRXyuY6t+2MtD6tykdbTB1nJWVJp5I7SEO32sK9Xn+OkZhNKm4JEaLRmc0+kIgEMBd5IxbNdcQGjwSo3w9IHLpmrDwELvA2UkAd7HpX6tOAgGcnAUQmnHvjbHbIzuGSV0R5utulPBoMyRC9LcTI3oGHbudBNHpuSSISqsDA8Ot5p4L8ToJbo/w6Eh4XLtegwdmPozaJrVhnZf3ULS1tUF24yZGDA+664hGU+cBYww+Pj4oLy9HU1MTAEAoFMLLywtisbjbOHQeEIu11AFZ/w2cbq+v4hkELHwbGLvQvu1yNCJ3YPjkvt2nVxAw/jFuAQBlI3D1BFBVwCU5rv/CJVjKvuEWABB5AiOntI/gmM5NFyakUVOEEEIIIYQMdA6d0BBIJBjzS5Hd9s2XUqk0Oe2EqRs8jDHeU1l1F8eSGKbYKo4lbHFMfH++EonEaAoThyF040ZK2GvfPHXXv23FUfq3h4eH4e9PPfWURUWPe0J93jQnJwlmxpX06T71eoZmdRtqFECzugmaNuO54UUuTvB0FcJT7AIPsQucnARgbRpIPdzg4WrbX5t5eXmYP3++4fUnn3yCJ598EgD37+3c/m8rFjrD0/XuIyEA49EgHYkPb3chBAIB/DzFRqNBOidIGLgEil7H0HkwiE7P0KrRoUZ+ewqaaw1c/7p4sxkNkHdKgJiuD9Kk0gLgEiuaNj3atBo0Nymg0Wi443R2hpeXF1xdXe96XgzE84D0MsaAM/8H/LiRK4INATBlFTD7vwFXflOAkj4mGQLcE88tADclVnURN3qjqhCoOg5omoDLR7gF4KbFCprMjeIImQ6MnMrFIYQQQgghhAwojp3QEAh4T/tkT76+vmhoaDBaFxgYiOPHjxuta2hogFar7fJ0aU8CAwO7PHV68+ZNs2NoNBo0NDQYPcV+8+ZNTJ8+nXccW/D19YWzs7NNjunGjRtd1tfW1naJU19fj9GjR1vW4N4kEPCe9smeTPVvW3Gk/t25BgjfGjd82wdwT5YPGzbMqH3mHiffa0p9fT38/PysaHXf4W5m9/51Xq3VoUndhiZVG5rVbe2jMDSGNriLuISBp6sLxC5OXW6O99Z5EBMTY9T3zOkT3TE1GsRDLIQAwDCp6WQ9NxoEXabCatMzBA0LREtjHYa4idrX6aFoqIOLiwuk3j4AYNheA9OFg3ViKQDg5LlyNDtzBcAFEOF6bQOkfoFoFrhD1aqHs0ppVB+kc2LE2UmAgICAAXkekF5UfwX4/mXgylHutf+9wOIPBm7R74FK6AqEPsAtAKDXtRcZL7yd5Gi+AVw9xi0/vQdAAATc215kvD3JMZinFSOEEEIIIWSAGIRVD20vKioKZWVlRutiY2NRWlqKmpoaw7qsrCyIxWJER/OvCxIbG4tDhw4ZrcvKyjLrRm10dDSEQqFRnJqaGpSWlvZ5QkMkEiE6OrrLMR06dMistsTGxkIul+PEiROGdcePH4dcLu8Sp7S0FFFRUdY1fBAz1b9txZH6d3h4uGExNZ2ZpcLCwhAYGGjUPo1Gg5ycHLP7PJ9rikqlwuXLlwd9n9frGZpUWlxvVOKCTIELN5pwvVGJJpUWjDGInJ0w1F2E0KHuiBzmhVF+HvDzFMNV6GxyBEBvnQcSicSo73l6etp8H3wI2qeaErk4w03kAk9XIYa4ieDrIcZDDz6AgtyjCPZxQ5ivOyL8PVF2Mh8xMTGICvXFuGFeuCfAE6P9PBAy1B0jvN0wTOoKP08xfNxFkEqEiAgfBV//ABzPO4qOn65Go0HR8Z8wYfIUtGjaIFdqUd+iQW2TGjVyFa41tKKirgWXa5vx640mnKtRYNg996G0tBS5p3/FpZtNKL/Vgs+/+g5isRgjI+7FrWY1Gls1qG1swuXLlzH+vvu40SdWFGUn/ZROC+S/C+yM5ZIZLq7Aw2nACzmUzBgInJyBYROBaauBpf8LrL8AvPgL8MiHwKSnAJ/RABiX9Dj5P8D+54B3xgHv3QccWA0U/S9Q+ys3eocQQgghhBDSrzj0CI3+IiEhARs3bjR6Qjw+Ph6RkZFITk7GW2+9hfr6emzYsAErV6406+nvdevW4aGHHsK2bdvwyCOP4JtvvsHhw4eRn5/PO4ZUKsVzzz2H9evXY+jQofDx8cGGDRswYcIEzJkzx6xjLSsrg0ajQX19PZqamgxPFk+aNIl3jJdffhnJycmIiYlBbGwsdu3ahaqqKqxevZp3jHHjxmHevHlYuXIlPvnkEwDAqlWrkJiYaCgIDnD1H6qrq80+TnKbqf4NAJcuXUJzczNkMhmUSqWhL0RGRkIkEvGK7Wj925SO42pubkZtbS2Ki4shEokQGRnJ6/MCgQApKSnIyMhAREQEIiIikJGRATc3NyQlJfFuB99ryrFjxyAWixEbG2vWcQ4E6jZdey2MNrSo2wz1JwB+ozB60pvngSnNzc24dOmS4XV5eTmKi4vh4+OD4OBg3nGqqqpQX1+Pqqoq6HQ6Q/vCw8ONplnryerVq7Fjxw68/PLLWLlyJQoLC/Hpp59i7969d60Notfr0dzcjBZNC1Y9/xx27HgHk8aEYcKECXjrz3+Gu7s7fv/ccri5u5mcBqtjREjH32Mfmo1REWPwhzWr8NKmzVA0NuBPf9yIJb97Gq0QobWRmxbrZGE+hCIxvMPG4+x1uSFh07UY+u3RIHeud3YSwMlO0zISK10rAr5by93MBoCwOCDxXWCoA47WJLYhEHD/vkNHA1FPceuabtwevVFZwPWHxkpuOb2X28bN9/bojeBYIPA+wJn+e0QIIYQQQohDY31MLpczAEwul3d5T6lUsrKyMqZUKvu6WVabNm0a+/jjj43WVVZWsoULFzKJRMJ8fHzYmjVrmEqlMtoGANu9e3ePsb/88ks2ZswYJhQK2dixY9n+/fuN3t+9eze72z+lUqlka9asYT4+PkwikbDExERWVVVltE1cXBxbvnx5j3FCQkIYgC5Lh/LycgaAHT16tMc4H374IQsJCWEikYhNnjyZ5eTkGL2flpbGQkJCeoxRV1fHnnzySebp6ck8PT3Zk08+yRoaGoy2ycjIYAkJCT3GIXdnqn/HxcWZ7Avl5eWGbfpb/zbF1DF27ptHjx7tctx30uv1LC0tjQUGBjKxWMweeughVlJSYrTN8uXLWVxcXI9t4XNNWbVqFXvhhRfMPcx+Sa/XsyalhlU3tLLzNQp2+mqD0VJ2Xc6u1rewxlYNa9Pprd5fb54Hd+roV3cunfswn+vk8uXLTcbpfI0OCQlhaWlpPcbJzs5mUVFRTCQSsdDQUPbRRx+ZbG/Hcev1etbc3MxqampYdXU1q66uZjdu3GCbNm2y+DzQ6/VM26ZjFy5dYfPmL2ASiYR5+/iw51atZhU3GtjV+hZWcauZXbrZxJYlP8OWJj/Dzlxr7NIvzFlKrzWyczVy9usNBbtS28wq61pY5Y0GduyX0+zzgkvs61PXWPaFm+z01QZWVdfCFEoN0+ut72vEQioFYwf/wFialLE0L8beDGXs1OeM0b8JYYwxpZyxi4cYO7yZsb/OZ2yzH9dPOi9vDGPsfxczdvRNxq7kMKZusXerCSGEEEIIGTR6yht0JmCsb8daKxQKSKVSyOXyLiMVVCoVysvLERYW1qtFiHvDwYMHsWHDBpSWlsLJid9MXhUVFYiIiEBZWRkiIiIs3nd6ejqys7ORnZ1tcQwACA0NRXp6OlasWGFxjOzsbCxZsgRXrlwxeorZXB1t2LNnj8Ux1Go1IiIisHfvXjzwwAMWxyHUv3uyZ88ebNmyBWVlZRAK+RVtNmXmzJmYOXMm0tPTLY5RW1uLsWPH4ueff0ZYWJjFcRyZrn0qqSZVGxQqLXT6TqMwIICb2Bmeri7wchWaPQrjbux5Hphii+ukUqmEj48PDh48iFmzZlkcp/N5oNPpoFAo0NbWBgBmFfy29XkQGhraXhuEmawP0vXvt7fpDmvT4Ob1a0g/ehPVTbou7wudBZBKRPB2E8LbTYQhHX+6CzGkff0Qt/b33bn3h0hEELnQLKBWOX8QOLgBUFRzryf+DojfArgPtW+7iONqUwPXi4GqAq4Wx9VjgEpuvI2TCzBsEhASCwRP50ZzuPnYo7WEEEIIIYQMeD3lDTqjMdU2smDBAly8eBHV1dUYOXIkr89kZmZi1apVVt/k+vHHH/H+++9bFeP8+fPw9PTE008/bVWczMxMpKamWpXMAICcnBzk5uZaFaOyshKbNm2iZIYNUP/uXmZmJjIyMqxKZjQ1cfP9f//991a1pby8HDt37hxwyQxtmx4KlRYKo4LeHBcnp/YEhgs8XF3gzDPRYAl7ngem2OI6mZOTg9mzZ1uVzAC449y8eTMUCgXUajUAbpovT09PuLu780os9dZ54CwAnJ0EMKdsGGPdJz1UKqBF7IyH7vFDRYMWDa0aNLZyf6rb9NDqGG41q3GrWW1Wuz3ELreTH53+NCQ/Oq3vSJB4il1smrTrlxQ1wA9/AM59y732DgUS3wNGW9enySDgIgaCp3LLgy8Bej1Qe46bnqqqkEtyNF0Hqn/mloLt3Of8xhlPUzWE3+8DQgghhBBCiG3QCA1CCCEOhTEGVZseCqUWCpUWSo3xU/BiF2d4SbhRGG4i00W8Sd/R6XRoampCa2urYZ27uzs8PDzg7NxNcY1+rKfvKkqNzpDgaGzVoKG1I+HR+e/Gf8qVWovrErs4CYySHkPcRBgiuT3yw9ut84iQ238fEKNB9HqgaDdwOB1QKwCBM/DAWuChPwAiN3u3jgwEjHH1NqqO3U5y3Pq163bSkVyCIziWS3L4jgF6MblOCCGEEELIQEUjNAghhPQbjDG0qNugaJ9KStOmN3rfTeRiSGLYeiopYhlDwe+WFsOoGVdXV3h5ecHFZXB+vZCInCERSRA0RML7Mx3TqBklP1pMJz8a2hMlja1aKLU6tOkZbjVrcKtZY1Y73UXOXJKjfRqsLskP965JEC9XBxoNcvMc8N064Opx7vXwaGDRB0DgePu2iwwsAgE34sc7FJj4W25dy632QuPtSY6a04D8KlByFSj5kttG4s0lN4KncdNUDZsIuIjsdRSEEEIIIYQMOIPzjgMhhBC767iRq1C1oemOehhOAgE8xFwSw9NVCKEzPe3qKBhjaG1tRVNTE/R6LvEkFAohlUohEtFNO3M5Owm4kRVuIoTBnffnVFpdp0THHcmPltvJj4ZWDRqVWsOoET0DWjQ6tGiUqG5UmtdOiRDSLiM/uiY/vN1vT5EldrHhKB2tCsh7G8h/D9BrAZEH8HAacP9zgNPAGw1EHJC7LzBuEbcAgLoZuHayfYqqAuDaz4CyAbhwkFsAwEUCjIhpn6JqGjBiCiD2sN8xEEIIIYQQ0s9ZldDYunUrUlNTsW7dOrz33ns2ahIhhJCBilc9DIkQHmKX9roHxFEwxqBWqy0u+E1sy1XojECpMwKl/Kfo1OsZmlRtXZIgRsmPVm2XkSGtGh10eoa6Fg3qWjQAWnjvUyJ0NjHyoyPhYaJ4upsQXq5CON15/pfncaMy6i9zr8csABa8BUhH8G4LITYn9uDqtXTUbNFpuVEbHVNUVRVyCY6KPG4BuOnRht3Hjd4IiQVGTgM8/Ox3DIQQQgghhPQzFic0Tp48iV27duG+++6zZXsIIYQMIFQPY2DQarWQy+XQaLipjcwt+E0cg5OTAFI3bpRFqBmjQdRtnUaDtBjXB5ErTYwIadWiUcmNulJqdVDKdbguV/FvpwCQStoTHK4CeLdcxhD5eXgLpsFbPA1D7psP71HRGHJLBO9WhSEZ4iqkURrEzpyF3GiMETFcTRe9nqu7UVXAFRmvKuSmqLp+iluOfch9bmgEl9zoSHIMCeGmvCKEEEIIIYR0YVFCo7m5GU8++ST+53/+B2+88Yat20QIIaQfo3oYA4dOp4NCoYBSeXtqInd3d3h6esKJit4OGmIXZwR4OSPAy8zRIOq2LsXRucTI7aRIRxKkI1HSotFBz9D+GW17tID2BUArgGMAjp3qsk9XoVOPIz+820eJSCW335dKTIwGIcRWnJwA/7HcEvMst67xKleDoyPJUXsOqLvILb98xm3jOex2kfHgWMA/kgqNE0IIIYQQ0s6ihMZ//ud/YuHChZgzZ85dExpqtRpqtdrwWqFQWLJLQgghDozqYQwsHQW/m5ubDesGe8FvYh4nJwGkEiGkEiFChvL/nLpNB3nNFTRkvomGq6VoZB5o9IhAw5hlaBQF3jFF1u0i6W16BpVWjxq5CjVmjAYRdBoN4u0mxP1hPlgeG2pWYXdCzDJkJLfc9wT3urW+PcHRPoLj+imgqQY4+xW3AICrlJuaKngal+QIigJcxPY7BkIIIYQQQuzI7LsS+/btwy+//IKTJ0/y2n7r1q14/fXXzW4YIYQQx0b1MAYeKvhN7ErXBvHxnfDP3gp/bSsgFANx/wVMXwe4dN//GGsfDdKiRaOyU8KjxTj5cWfxdO66BUPdkHIAv1Q14q/55XjuwVF4cXY43MWUwCO9zM0HGLuAWwBA0wpU/3x7iqqrJwCVHLj4I7cAgIsrMDyaG70RHAuMnAK4etnvGAghhBBCCOlDAtb5DtRdXL16FTExMcjKysLEiRMBADNnzsSkSZO6LQpuaoTGyJEjIZfL4eVl/MVbpVKhvLwcYWFhcHXlP62BI6irq8O4ceNw4sQJhIaG2rs5BEBJSQnmz5+PCxcuwN2d/1zhpCvq3/3D999/jz/+8Y8oKirqlemAGOOegOaSGIOvHsZAPg8GesHvHTt2ICsrC99++63VsfrzdxWHVv0LV/RbdoZ7HToDSHwP8A3vtV1q2vSQK28nPGrkSuw9UYVjV+oBAIFerti0cBwS7xvW788B0o/p2rjzomMER2Uh0HrLeBuBExAw/vYUVcGxgGeAfdpLCCGEEEKIhRQKBaRSqcm8QWdm3fEqKirCzZs3ER0dDRcXF7i4uCAnJwcffPABXFxcoNPpunxGLBbDy8vLaBmItm7dikWLFhnd5KqqqsKiRYvg7u4OX19frF271lBQla+zZ8/iscceQ2hoKAQCQbeJo7tRq9V48cUX4evrC3d3dyxevBjXrl0zO05JSQni4uIgkUgwfPhwbN68GWbkxAx27txpuBkUHR2NvLw8s2Ns2bIF06dPh5ubG4YMGdLl/QkTJmDKlCl49913zY5NjPVW/waA/fv3IzIyEmKxGJGRkThw4IDZMXbt2oWZM2fCy8sLAoEAjY2NZscAHKt/m7Ju3TpER0dDLBZj0qRJXd5PTEyEQCDA559/bpP9AYCeMTSrtLjeqMQFWRMu3mzCDYXKkMxwE7kgUOqKewI8MSbQE8OkEriLXQbkzb+Bep3XaDSoq6tDfX092traIBAI4OXlBX9/f0gkEshkMiQlJWHMmDFwcnJCSkqKRe0zpa/O3ZUrV+LkyZPIz8+3UcuJzaibgcxU4C8PczdtXYcAj3wILP+uV5MZACBycYKfpxgRAZ6YEuaDRyYNx96V0/CXp2Mw0kcCmUKFF/eeQtL/HMevN5p6tS2EdMvZBRg+GYj9T2DZ34H/ugSs+RlY9AEw8XeAdyjA9Nz5c/xj4MvlwP+7B/ggCvj6P4FTfwfqLgMWfJ8hhBBCCCHEEZmV0Hj44YdRUlKC4uJiwxITE4Mnn3wSxcXFcHZ27q12OjSlUolPP/0Uzz//vGGdTqfDwoUL0dLSgvz8fOzbtw/79+/H+vXrzYrd2tqKUaNG4c0330RgYKDFbUxJScGBAwewb98+5Ofno7m5GYmJiSaTUN1RKBSYO3cugoKCcPLkSWzfvh1vv/023nnnHbPa8sUXXyAlJQWbNm3CqVOnMGPGDMyfPx9VVVVmxdFoNHjiiSfw+9//vtttnnnmGXz00UdmHScx1pv9u7CwEMuWLUNycjJOnz6N5ORkLF26FMePHzcrTmtrK+bNm4fU1FSzPteZo/VvUxhjePbZZ7Fs2bJut3nmmWewfft2q/aj0zM0tmpQVd+KczUKXLnVglvNamh0ejgJBPByFWKEtwTjhnkh3N8D/p6ucBUO7Ov/QLzOt7W1oaGhAbdu3TIkYdzd3REQEAAPDw9DUkqtVsPPzw+bNm0yjM60lb46d8ViMZKSkqw+N4iN/fojsHMacOxD7obshCe4G7VRT3HFLexAIBBgTmQADr0Uh5Q5ERC7OKHwSh0WvJ+HN74vQ5NKe/cghPQmgQDwjQCilwNLPgbWnQZePgc8/lfg/pXcSA0IgPorQPHfgW/+E9g+Gfh/Y4D/exo49jFQcxrQ03djQgghhBDSTzErxcXFsXXr1vHeXi6XMwBMLpd3eU+pVLKysjKmVCoZY4zp9XqmUbXZZdHr9byPaf/+/czX19do3cGDB5mTkxOrrq42rNu7dy8Ti8Umj52PkJAQ9u6775r9ucbGRiYUCtm+ffsM66qrq5mTkxPLzMzkHWfnzp1MKpUylUplWLd161YWFBRk1s9rypQpbPXq1Ubrxo4dy1599VXeMTrbvXs3k0qlJt9Tq9VMLBazI0eOWBS7N+n1etaiabHL4ij9e+nSpWzevHlG6xISEthvf/tb3jE6O3r0KAPAGhoazP6so/ZvU9LS0tjEiRNNvldRUcEAsMuXL5sVU6PVsVtNKnaltpmdudbITl9tMCxnq+Wsqq6FNbZqWJuO/8+CD71ez5rb2uyyOMp50FlfXOd1Oh2Ty+WsurrasNTV1TGtVnvX/Zj7O5+vvjh3s7OzmUgkYq2trVa19c7vKsQCChlj/7ecsTQvbnl3PGMXD9m7VSZV1bWw5//3JAt55XsW8sr3LOaNQ+yrX66adf0gpM+1NjB24UfGDqUx9pd4xjb73j7fOpYtwxn7bAljOX9mrDyfMQ1d0wghhBBCiH31lDfozKErHbZp9Ni1Lscu+171fhyEYn5PHOfm5iImJsZoXWFhIcaPH4+goCDDuoSEBKjVahQVFWHWrFk2bW9PioqKoNVqER8fb1gXFBSE8ePHo6CgAAkJCbziFBYWIi4uDmKx2LAuISEBGzduREVFBcLCwu4aQ6PRoKioCK+++qrR+vj4eBQUFPA8Iv5EIhEmTpyIvLw8zJ492+bxraFsU2Lq51Ptsu/jScfhJnTjtW1v9u/CwkK89NJLRusSEhIsnnLHGv2xf5sSEhICf39/5OXlYdSoUd1uxxykHkarXo/RuSW9EvtuLj80Ae48RxYOhOs8G6AFv/meuzExMdBqtThx4gTi4uLs1dzBTa8HTn0GHHqNK3IscOam0Zn5KiByzFpXI33c8D9Px+DohZt4/duzqKhrxUtfnMbnx6vw+uLxiAwamFOpkn5OMgS4J55bAECrAq7/AlQW3C40rlYAl49wCwA4i4CgKK7+Rsh0YORULg4hhBBCCCEOxuqERnZ2tg2a0b9VVFQY3dACAJlMhoAA42J83t7eEIlEkMlkfdk8yGQyiEQieHt7G60PCAgwqy0ymaxLIdyOY5TJZLxu+N66dQs6na7Lz8bctphj+PDhqKio6JXYg0Fv9m9TcXqzL9ytLf2xf5vSXZ/XM4ZWdRsUqjYolFpodHqj991ELoYkxkCfQspc/fk6X1NTA5VKNWALfvM9d93d3TFkyBBUVFRQQsMeai8A36UAVe3J3WGTgMUfAMNsO41Zb5k1xh/TXxqKv+SVY8e/L+FkRQMSt+fh6dhQvDT3HkglQns3kZDuCV25JEXIdO61XgfcKAWqjt1OcjTfAK4e55af3gMgAALuBYKn3U5yeAX1tBdCCCGEEEL6hEOP0HAROWHV+/a56eAi4l9eRKlUwtXVtct6UzeJGGMOc/PIkrbcuT1rLzBoizi99XORSCRobW3tldjWkLhIcDzJvFoRttw3X73dv/uyL1jSFlPrLYljToz58+cbComHhITg7NmzZu2/c5/X6fVoUnFJjCaVFjr97aKgTgIBPMRcEsPTVQihs1lllWzCzckJlx+a0Of77dg3X/31Oq/T6aDRaFBfXw+Aa6+npyfc3d1NttHDw8Pw96eeegoff/yxTdqRkZGBjIwMw+uysjIEBwfbJDbA/9x11N8HA1qbGsh7B8h/B9BpAKE7MPu/gSmruGLH/YjYxRn/OSscj0YNx5Z/leFgiQx7Cirw3enreGX+WDw+eQScnBzj3CekR07OXDJx2ERg6gtcwfD6K1xio6oQqCwE6i9zSY8bpcDJv3CfGxLCJTaCpwHB07laHg7y+44QQgghhAweDv0/SYFAwHvaJ3vy9fVFQ0OD0brAwMAuhY0bGhqg1Wq7PNHb2wIDA6HRaNDQ0GD09O7Nmzcxffp0s+Lc+dTxzZs3AYD3Mfn6+sLZ2dlknN76udTX12P06NG9EtsaAoGA97RP9tSb/bu7PtXX50hPbQH6vn//5S9/gVKpBMBNCWSuuvp6uHl5o/xWC5rVbYabuwDg4uQET1cXeEmE8BC7wNnON98EAgHvaZ/sqb9d59va2tDU1ISamhpDIW93d3d4enrCqYdETnFxseHvXl62m0pn9erVWLp0qeH1naNdrGHOuVtfXw8/Pz+b7ZvcRcVPwPcpwK1fudcRCcDCt4Ehtktm2cPwIRLsfDIa+RdvIe3bUlyubcEf/nkGe09UYfPi8ZgwQmrvJhJiHoEAGDqaW6Ke4tY13bid4KgqBGQlQGMlt5zey23j5sslNzqSHIET+12ikhBCCCGE9D99/zjuABQVFYWysjKjdbGxsSgtLUVNTY1hXVZWFsRiMaKjo/u0fdHR0RAKhTh06JBhXU1NDUpLS81KaMTGxiI3NxcajcawLisrC0FBQV2m++iOSCRCdHS0UVsA4NChQ2a1xRylpaWIiorqldiDQW/279jY2C59ISsrq9f6wt3a4ij9e/jw4QgPD0d4eDhCQkLuuj1jDEqNDjcUKpRW1uLy5csIGj0OTSotGGMQuzjDz1OM0X4eGDfMEyN93CCVCO2ezOhP+st1/scff4RCocDNmzdRUVGBCxcuYPr06fD394dUKu0xmQHA0O/Cw8Ph7+9vs/b5+PgYxXZxsd0NL77n7uXLl6FSqej3QV9QNgDfrgX2LOCSGe7+wOO7gaQv+n0yo7MHI3zxw7qHkLpgLNxFzjhV1YjFH+Yj9UAJGlo0dw9AiCPzDADufRSYvw14IRd4pRJ4aj8wYwMQ8iDg4gq03gLOfw/8mAr8z2zgzWDgs0eA7G1AeS6goRFxhBBCCCHE9ugRGhvoKD7aeQREfHw8IiMjkZycjLfeegv19fXYsGEDVq5cadZTrxqNxnATTaPRoLq6GsXFxfDw8EB4eDivGFKpFM899xzWr1+PoUOHwsfHBxs2bMCECRMwZ84c3m1JSkrC66+/jhUrViA1NRUXL15ERkYGXnvtNbOmV3n55ZeRnJyMmJgYxMbGYteuXaiqqsLq1at5xwCAqqoq1NfXo6qqCjqdzvBkcXh4uGHalIqKClRXV5t1nMRYb/bvdevW4aGHHsK2bdvwyCOP4JtvvsHhw4eRn59vVhtlMhlkMhkuXboEACgpKYGnpyeCg4Ph4+PDK4aj9W9TLl26hObmZshkMiiVShQcP4lmjQ6BweGGJyJPnjgOkUiMadNiESB1pXoYNuLo13kvLy88/fTTWL9+PQQCAby9vfHGG29g/PjxWLJkCZytHAXTcX1tbm5GbW0tiouLIRKJEBkZaVXcvjx38/LyMGrUKIccsTdgMAac/Qr44VWghRslg+gVwJx0QOLd0yf7LZGLE1Y9NBqLJw7H1h/O4Zvi6/j8eBUOltTgvxLG4Lf3B1PymAwMrl5A+BxuAbjp5K4Xc3VxKguBq8cAlRy4ks0tAODkwtXLCYnlpqgKnga48bu2E0IIIYQQ0i3Wx+RyOQPA5HJ5l/eUSiUrKytjSqWyr5tltWnTprGPP/7YaF1lZSVbuHAhk0gkzMfHh61Zs4apVCqjbQCw3bt3dxu3vLycAeiyxMXFGbbZvXs3u9s/pVKpZGvWrGE+Pj5MIpGwxMREVlVVZbRNXFwcW758eY9xzpw5w2bMmMHEYjELDAxk6enpTK/Xd2nv0aNHe4zz4YcfspCQECYSidjkyZNZTk6O0ftpaWksJCSkxxjLly83+bPpvO+MjAyWkJDQYxxyd73Vvxlj7Msvv2RjxoxhQqGQjR07lu3fv9/ofT79Oy0tzWRf6Lzv/ta/TXkoLs7kcR4sOM1KrjWy8tpmtvyZ59jKVavMjk3uzhGv83q9nimVSnbjxg12+fJl9swzzzBvb2+rrvOmmGpf5z589OhRBoCVl5ebFbevzl3GGIuPj2dbt241q32m9OfvKr2qoZKxvz/OWJoXt2yPYaziJ3u3qs8VXr7F4t/JYSGvfM9CXvmeJX6Qx36prLd3swjpfTodY7JSxo7vYuzLZxh7e+zt60HnZccUxr5dx9jpLxhrqLprWEIIIYQQMnj0lDfoTMBYp8nV+4BCoYBUKoVcLu/yBKtKpUJ5eTnCwsJMFl91ZAcPHsSGDRtQWlp61yk9OlRUVCAiIgJlZWWIiIiweN/p6enIzs5Gdna2xTEAIDQ0FOnp6VixYoXFMbKzs7FkyRJcuXLFqF6HuTrasGfPHotjqNVqREREYO/evXjggQcsjkOof3ewR//WtumhUGmhULXdtR5Gfd0tjB07Fj///DPCwsIsbh8xzdHOA41GA4VCYZhq6W4FvwHbnAem7NmzB1u2bEFZWZlFdV96Yos2l5aW4uGHH8avv/4KqdS6+gb9+btKr9C1ASc+Af79BqBtBZxFwIz1wIMvAS5ie7fOLrQ6Pf5WWIl3D/2KJnUbAGBpzAi8Mm8shnoMzp8JGYQY4+ptVB0DKgu4Ohwd9XQ68xrRPoIjlqvF4TsG4Pk7lhBCCCGEDCw95Q06oymnbGTBggW4ePEiqqurMXLkSF6fyczMxKpVq6y6yQUAP/74I95//32rYpw/fx6enp54+umnrYqTmZmJ1NRUq272AkBOTg5yc3OtilFZWYlNmzZRMsMGqH9z+qJ/M8ag0rYnMZRaKLU6o/fFLs7wkrjAy1UIN5Gz0Y3r8vJy7Ny5k5IZvcRRzoOOgt8dheMBwMPDAx4eHj0mWmx1HpiSmZmJjIwMmyczbNXm69ev47PPPrM6mUHuUHOaq5VRU8y9Dp4OLHof8LvHrs2yN6GzE559MAyLJgbhzR/OY/8v1/B/P19DZqkM6+PH4MmpwXBxphu2ZIATCADvUG6Z+FtuXcut9iLj7UmOmtOA4hpQ8iW3ANz0dCOn3Z6mathEwEVkr6MghBBCCCEOiEZoEEKInekZQ6u6DQpVGxRKLTQ6vdH7biIXQxKD6mEMXnq9Hs3NzWhubjask0gk8PT0tGmRbdIz+q4CQNMCZG8FCncCTAe4SoG5fwKikunJahOKKuvxx6/PoqxGAQAYN8wLmx+5F/eHaTFHEwABAABJREFUUi0BMsipm4FrJ9uTHIXA1ZNAm9J4GxcJMCKmfQRHLDBiCiD2sE97CSGEEEJIr+I7QoMSGoQQYgc6vR5NKi6J0aTSQqe/fSl2EgjgIeaSGJ6uQgjpSd5BjTGG1tZWNDU1Qa/nkl0ikQheXl4Qieip1b426L+rXDwM/OsloLGKe33vb4B5bwKeAfZtl4PT6Rk+P16Jt368AIWKm4bqN1HD8er8sfD3GoT9iBBTdFpu1EbHFFVVhYCywXgbgTMw7L7bRcaDYwEPP/u0lxBCCCGE2BQlNAghxMFo2vRo4lkPw9nJdA0EMngwxqBSqaBQKKDTcVOPOTs7w8vLC66urt3WySC9a9B+V2m+CWRuBEr/yb2WjgQW/j/gngT7tqufqWtW460fL+CLn6+CMcBD7IKUORFYPj2UkteE3Emv5+puVBUAle0JDvnVrtsNjbg9RVXwNG6aK/odSQgZaPR6LsnbfKN9ucn92VILePgDgfcBgRMANxoBSgjpvyihQQghdmZNPQwyuN1Z8NvJyQmenp5wc3OjfmJng+67CmPAqb8DWf8NqBoBgRMw9ffArFSa9sUKxVcb8do3pThzTQ4AuCfAA68vHo/Y0UPt3DJCHFzjVa4GR0eSo/Zc1208h90uMh4cC/hH0nR4hBDHpWkxTlAY/mz/e5OM+7PlJqBvu3s8rxHcSLbACe3LfcCQYEr0EkL6BUpoEEKIHVA9DGINSwt+k74zqL6r3LoEfJ8CVORxrwPvAxZ/AARF2bVZA4Vez/B/P1/FtszzaGjVAgAWTQxC6oKxGCaV2Ll1hPQTrfXA1eO3p6m6fqrrDT+xFAieejvJERQFuIjt015CyOCgawNab91ORtw5qqLzOk3z3eN1JvEBPAK4URkeAYC7Lzd6TVYCNFSY/ozrEGDYROPFZzQlewkhDocSGoQQ0keoHgaxFhX87j8GxXeVNg3w0/tA7luATg0I3bgRGVN/DzhTf7S1xlYN3s66gH8crwJjgJvIGWsfjsCzD4RB5EK/Mwgxi6YVqC7ikhuVBcDVE4C2xXgbZ3F7ofFp3DRVI6cArt3/h5kQQgBwo1ZV8jsSFN0kKlpuATDjVpuLhKtH1jlRYfR3f8AjEHD3A1x6qKGnkgOyUi65ISsBZKeBm+cBvbbrtiIPIGB8pyTHfYDfWMBZaPaPhhBCbIUSGoQQ0ov41sPwFLvAiephkG5Qwe/+Z8B/V6k6Bny3Dqg9z70On8PVyvAOtWuzBoPSajle+6YUv1Q1AgBG+bnj9cX3YkYEFTwmxGK6NkB2xniaqtZbxtsInLibesGxt2txeAbYp72EkL6nVXHTOXU31VPnRIVOzT+uwIlLQBiSE3cmKDqtE3v23pRQbWrg5jmg5jR3Paw5zSU92pRdt3UWAQH3cqNyh00Ehk0CAiIBIY0cJYT0DUpoEEKIDVE9DGJLVPC7/xqw31WUjcCR14Gf/8q9dvMF5m8Dxj9Gcy73Ib2e4atT1Xjzh3O41czV0Jl3byD+uCgSw4fQzQRCrMYYUHepfYqq9iSHqSlafEbdLjIeMp17TddCQvoPvR5oret5qqeORSU3L7ZYejsh0WVURadEhdtQwMlBpxjWtXHXwprTxokOtaLrtgJnwG8Ml+DoSHQETqCRbYSQXkEJjT5WV1eHcePG4cSJEwgNDbV3cwiAkpISzJ8/HxcuXIC7u7u9m9OvDdb+PRDqYezYsQNZWVn49ttv7d2Ufs9W5wEV/O5d33//Pf74xz+iqKioV+qO9OfvKiYxBpz7Fjj4B6BZxq2LSgbmbgbcfOzbtkFMrtTivcO/4rPCSuj0DK5CJ6yZFY7nZ4xy2N83hPRbiuvtU1QVckmOG6XoMlWMR8DtKaqCp3E38xz1RiUhA5m6uZupnjr9vekG0FILMN3d43VwFvUwgqJz0sJ/4I5W0OuBxgqg5sztREfN6a6j2jr4jLo9XVVHosPdt0+bTAgZePgmNGhiXhvZunUrFi1aZHSTq6qqCosWLYK7uzt8fX2xdu1aww0svs6ePYvHHnsMoaGhEAgEeO+99yxq365duzBz5kx4eXlBIBCgsbHRojglJSWIi4uDRCLB8OHDsXnzZliSE9u5c6fhZlB0dDTy8vLMjtHQ0IDk5GRIpVJIpVIkJycbHdeECRMwZcoUvPvuu2bHJsZM9e9169YhOjoaYrEYkyZNsjj2/v37ERkZCbFYjMjISBw4cMDsGGq1Gi+++CJ8fX3h7u6OxYsX49q1axa1R6fXo7FVg6r6VuQW/4qlv/0dpkffh8jhQ/BW+kZ4uQoxwluCccO8EO7vAX9PV4tuLvXVObly5UqcPHkS+fn5FsUnt1l7nW9ra0NDQwNu3bpl2MbDwwO1tbV4+umnERYWZtV13pQtW7Zg+vTpcHNzw5AhQyyOk5OTg+joaLi6umLUqFH4+OOPzY7BGEN6ejqCgoIgkUgwc+ZMnD171uw4d/uZJyYmQiAQ4PPPPzc79qAjvwbs/R3wf09zyYyh4cDy74FHdlAyw86kEiHSFt2L7198EFNCfaDS6vF21q9IeC8X/z5/w97NI2Rg8QriRqMtfBv4fT7wSgWQ9CXw4EvAyGncjc7mG0DZN0DmK8CuOODNEOBvv+FqDVX8BGhNTN1CCOFHp+USi9dPARcygaL/BXLeAv61AfgiGfg0AXh/ErAlCNg6HNg+Gdg9H/hyBfDDH4C8/wec+jtwMYu7Ad8su53McPMF/O8FRs0C7vstMH0tEL8F+M1fgOXfAf95gjvn//sm8FIpsPLfwO/2Aove5+qH3f8cMC4RGHk/4B0ycJMZAFcg3GcUcO+jwJw0IPkr4L8uAS+fA363D5iZCoxZCHiN4LavvwKcPQAcTgf+/hvgrdHAO/dy3y2z3wQu/ADIq7mHZwghxMaosqMNKJVKfPrppzh48KBhnU6nw8KFC+Hn54f8/HzU1dVh+fLlYIxh+/btvGO3trZi1KhReOKJJ/DSSy9Z3MbW1lbMmzcP8+bNw8aNGy2KoVAoMHfuXMyaNQsnT57Er7/+ihUrVsDd3R3r16/nHeeLL75ASkoKdu7ciQceeACffPIJ5s+fj7KyMgQHB/OOk5SUhGvXriEzMxMAsGrVKiQnJ+O7774zbPPMM89g9erV2LhxI5yd6SkqS5jq3wB3c/LZZ5/F8ePHcebMGYtiFxYWYtmyZfjTn/6EJUuW4MCBA1i6dCny8/MxdepU3nFSUlLw3XffYd++fRg6dCjWr1+PxMREFBUV8fp376iHIVdq0aLRGRICSpUaQ339sG79H7D7kw/h4y5CqK9tRvv01TkpFouRlJSE7du348EHH7RJ2wcja67zdyv4rVKpbHKdN0Wj0eCJJ55AbGwsPv30U4tilJeXY8GCBVi5ciX+/ve/46effsJ//Md/wM/PD4899hjvOH/+85/xzjvvYM+ePbjnnnvwxhtvYO7cubhw4QI8PT15xeD7M3/mmWewfft2PPXUU2Yf76Cg1wEn/gf4958ATTPgJORu3M1YDwgHwKiTAWTcMC988cI0fHv6Orb86xwq61rx7J6fMWecP15LvBfBQ93s3URCBh7JEOCeeG4BuPn1r//SPk1VIVdoXK0ALh/hFoBLegRFtdfhmA6MnMrFIWSwa9MAN8uAWxfbR1GYqEvRWmdeTKF7z1M9GQpo+1KBa2sJBFzS1ysIGDP/9vqWOq7geM3p2yM66i8DimvccqHTvQM339tFxztGdHiH0TR+hBCrOPSUU4wxtKnNKLpkQy5iMe+pP7766iu88MILqK2tNaz74YcfkJiYiKtXryIoKAgAsG/fPqxYsQI3b97scdhMd0JDQ5GSkoKUlBSzP9shOzsbs2bNQkNDg9lP63700UfYuHEjbty4AbFYDAB48803sX37dly7do33z2vq1KmYPHkyPvroI8O6cePG4dFHH8XWrVt5xTh37hwiIyNx7Ngxw43vY8eOITY2FufPn8eYMWMAcDfzvLy8cPDgQcyePducw+11jDEwpX2e5hJIJFb1787S09Px9ddfo7i42Ox2LFu2DAqFAj/88INh3bx58+Dt7Y29e/fyiiGXy+Hn54e//e1vWLZsGQDg+vXrGDlyJA4ePIiEhIQun7GkHsbMmTMxadIkmz49D/TNOZmTk4P4+Hg0NjZCInGsp4oYY11+/n1FIuRf68SS67ynpydaWlrQ1NRkSJLdreC3La7zpuzZswcpKSkWjQR65ZVX8O233+LcuXOGdatXr8bp06dRWFjIKwZjDEFBQUhJScErr7wCgBtZFRAQgG3btuGFF17gFYfv79bKykqEhobi8uXLGDVqlDmHe1f9fsopWQnw7Vru5hzA3XRb9D7gP86+7SJ31aTSYvu/L+Gv+eVo0zOIXJywOm40/mPmaJqGipC+pNcBN862T1PVnuRovnPklADwj2wvMt6e5PAKsktzCelzjHHnRfHnwNmvAU3T3T8jcL49pZNHoIkERac/xR69fgjEAioFN2VfTadER+1501N/ib06FR5v/3NoBOBMz1wTMtjxnXLKoa8WbWo1Plj+uF32vfZ//wkhzxsVubm5iImJMVpXWFiI8ePHG264AEBCQgLUajWKioowa9Ysm7a3LxQWFiIuLs5w4xTgjmnjxo2oqKhAWFjYXWNoNBoUFRXh1VdfNVofHx+PgoICs9oilUqNnuKfNm0apFIpCgoKDAkNkUiEiRMnIi8vz/ESGkolLkyOtsu+x/xSBIEbv6c6TfVvWyksLOzyRHpCQoJZSYOioiJotVrEx8cb1gUFBWH8+PEoKCgwJDQGQj2MO/E9J2NiYqDVanHixAnExcXZq7kmKbU6RL72o132XbY5AW4ifr8Gzb3OFxQUICoqylDw28XFBV5eXhCbkSx3FIWFhUbnF8Ad56effgqtVguh8O5PvpWXl0MmkxnFEYvFiIuLQ0FBAe+EBt/frSEhIfD390deXp7NExr9lqYVyNkGFGzn/mMp9gLmpAPRz3BTDBCH5+kqROqCcXgiegTSvj2Lgst1+ODIRXz1yzX8MTES8ZEB/e76Qki/5OTcfgPuPmDqC9zN2/ort4uMVxZyTyrfPMstJ//CfW5ISHtyI5arxeEbQU8ok4GloQI4vQ84vZf7ewfXIUDAvYDnMMAz0PSoCokPfR/p71y9uORtyPTb67RK4EZZp9Ecp7nXagVQmc8tHVwkXD/pGMUx7D4uMewi7rovQsig59AJjf6ioqLC6OYKAMhkMgQEBBit8/b2hkgkgkwm68vm2YxMJutSCLfjGGUyGa+Exq1bt6DT6br8bAICAsz6uchkMvj7+3dZ7+/v3yXO8OHDUVFRwTs2MWaqf9uKqfPEkr4gEong7e3dJU5NTQ0aWzVQqNrQpNJCp789IM1JIICHmEtieLoKIXTuf1+g+Z6T7u7uGDJkCCoqKhwuodFf8L3Ou7u7QyQS4cqVK7jvvvsGRMHv7s7TtrY23Lp1C8OGDeMVo+Nzd8aprKy0qi3d/W6la38nl44A378ENLb/rMctBub/GfC6+78dcTwRAZ74x/NTcbBEhjf+VYZrDUq88LcixN3jh/TF9yLMRlMjEkJ4EgiAoaO5JepJbl3TDe4J9Y5FVsJdgxsrgTP7uG3cfNsLjbcnOQIn0tPJpP9RN3H1ZYr3Gt+cFnkAkY8Ck37HJfAoWTE4CSXAiGhu6aDTArUXuOSGrH26KlkJNw1q9c/c0sHJhRtFHDixUwHy8YCIvusQMtg59DcmF7EYa//3n3bbN19KpdLktBOmbl4xxvrtTS2g6zF1TKNi7jGZimNtjO7iSCQStLa2mhW7LwgkEoz5pchu++aru/5ts7bYoC901lEPo1XdhkZlG6rqb//buzg5wdPVBV4SITzFLnByur0fD4/bQ5efeuopi4oem5KRkYGMjAzDa3NrxdwN33PSUc8DidAZZZu7TgvWV/vm627X+ba2NigUCqhUKkMf9vDwgIeHB5z64D9wq1evxt///nfD6871OmyBrv39VMst4MdU4MwX3Guv4cCCt4GxC+zbLmI1gUCAhfcNw6yxftjx70v4n7wryPm1Fgnv5uL5GWFYMzuc9wg0Qkgv8AzgCuve+yj3WqUArp3gRm9UHeNu2LXeAs5/zy0AVxdg5P1cgiM4FhhxPyCiOjnEAen1QEUuN6XUue8Abcf3LQEQ9hAwKQkYt4huOhPTnIVcUiJwPID2JLBez410qyk2TnQoG7hkh6wEKO74v46AG+E2bKLxtFUS7252SAgZiBz6fzoCgYD3tE/25Ovri4aGBqN1gYGBOH78uNG6hoYGaLXaLk+X9heBgYFdnoC9efMmgK5P3XbH19cXzs7OJuOY83MJDAzEjRt3zlUL1NbWdolTX1+P0aNH847dVwQCAe9pn+zJVP+2le76lDl9ISAgABqNBhcqa+Dk6mGox1BbexPjJ99vsh6GKZ1rgFhS46Y7q1evxtKlSw2vbTnaxZxzsr6+Hn5+fjbbt60IBIJ+cdOtp+u8XC5HS0sLAKCxsRFarRYRERE27Ud3s3nzZmzYsKFXYnfXz1xcXDB06FDeMQBuhEXnER2WXPv5/m511D7fZ859x9XKUNYDEHDTosz+b0DMrwA76R/cRC74w7yxeDx6BNK/K0Pur7XYmX0ZB05V478XRmLBhMB+/SANIQOGqxcQPodbAKBNDVwvvj1F1dVjgEoOXMnmFoB7MnnYpNt1OIJjATcf+7SfEAC4dQk4/Tlw+guu8HOHoeHAxN8B9y0Dhoy0X/tI/+XkBPiGc8uE9mnnGQPkV28XHe9IdDTVALd+5ZaSL2/HGBLcaRRH+5+e/fPeGyHk7hz/LlI/EBUVZfRkLADExsZiy5YtqKmpMdy8ycrKglgsRnS0feomWCs2NhapqanQaDSGgrZZWVkICgrqMu1Nd0QiEaKjo3Ho0CEsWbLEsP7QoUN45JFHzGqLXC7HiRMnMGXKFAAw3FicPn260balpaV4/HH71GIZCEz1b3O16fRo0eigadMDYHATuUAickZsbCwOHTpkVEcjKyury7/hnTrXw/AacQ9chEJ8ezATCYu4PtXccAuXLpzD22/9GWMC+d28Cw8Pt/j4euLj4wMfn975zyffc/Ly5ctQqVSIiorqlXYMBneeB4wxTJo0CVu2bMGVK1cQEBAAkUiEU6dOQSwWG65LfcXf39/kNHy2EBsbi++++85oXVZWFmJiYnjVzwCAsLAwBAYG4tChQ4Z+qNFokJOTg23btpnVFj6/W1UqFS5fvjw4+7xWBWRtuj1ne8B4YNEHxkP9yYAzys8D//vM/ThUdgObv+emofrPz3/BA+FD8friexHuT4ksQhyKixgInsotD77EPZ1ce+52kfHKQqDp+u3pVwq2c5/zG3u7yHjwNO4GHiG9SdkAlH7F1cW4dvL2elcpcO9vgElPAiNiqB4MsT2BgLvGDQkGxiXeXt904/YIjo6lsRJorOKWc53+3yIdCUQ9xdWMo+QGIQMKJTRsoKMIb0NDg2Ee//j4eERGRiI5ORlvvfUW6uvrsWHDBqxcudKsp3Y1Gg3KysoMf6+urkZxcTE8PDzMugErk8kgk8lw6dIlAEBJSQk8PT0RHBzM+2ZrUlISXn/9daxYsQKpqam4ePEiMjIy8Nprr5n19N/LL7+M5ORkxMTEIDY2Frt27UJVVRVWr17NO8a4ceMwb948rFy5Ep988gkAYNWqVUhMTDQUBAe4ee+rq6sxZ84c3rGJMVP9GwAuXbqE5uZmyGQyKJVKwwiHyMhIuLgI0appQ7OaW5QaHdgdcQUCAR5/eiV+98g8bH4jA4/9Zgm+/+5bHD58GPn5+biTTq9Hk6qtSz0MsbsnfvPbZLz7xh8RPnIYhgf64Y+v/AETJkzAgnnWT2XUcVzNzc2ora1FcXExRCIRIiMjrYrbl+dkR2FkRxyp1F90nAf19fWQSCRQKBS4//77cc8992DdunX485//jObmZrz66qt2u86bUlVVhfr6elRVVUGn0xn6c3h4uNE0az1ZvXo1duzY8f/Zu+84qeqr8eOf6TtlK9sLZWFBASmCtAWp9t57ixE1McYkpmgSJUXNLz7Pk2I3Gk2MgtHYgyiKIL2pdGSBXbb3Pr3c3x93dnaH3YUFdne2nPfrNa/ZuffOd74DM3dm7rnnHH784x9z1113sXHjRl5++WWWLl3a5XloNBoeeOABHn/8cXJycsjJyeHxxx/HYrFw4403dnmcrn62btq0CZPJxMyZM7s89oBQ9S28/R2o2K3ennU/LPg16I2RnZfoFRqNhnPHpXL26CSeXX2I59ccYv3BGs7/81q+M3sE9y/MwWaSr/5C9ElardoMN2UcTLtLPTO5vjAY3AgGOaoPQNV+9bL9FfV+MZmtGRzDZkHiGOlVIE6d3weHVqnZGPuXg9+tLtfoYNRCNRtjzIVg6PvVNMQAFJ0C0edAzjmty1pKU5XtaM3oqD6gZnisfgK+/B8Yd4WasZw5NXJzF0J0H6WXNTQ0KIDS0NDQbp3T6VT27t2rOJ3O3p7WKZsxY4by/PPPhy07cuSIctFFFylms1lJSEhQ7rvvPsXlcoVtAyivvPJKp+Pm5+crQLvL3LlzQ9u88soryvH+Kx999NEOx2n72HPnzlVuu+22Y46zc+dOZc6cOYrJZFJSU1OVJUuWKIFAoN18v/jii2OO88wzzyjDhg1TjEajcuaZZypr1qxpN99hw4Ydc4yamhrlpptuUqKjo5Xo6GjlpptuUurq6sK2efzxx5XzzjvvmOOI4+vo9T137twOX1Nrtu1WdhXXKzuK6hRA+e3/PqPsKKpT9pc1Kkeqm5WC6mZlT0mDsqOoTtlRVKf8z/OvKsNH5ih6g0HJzhmtvPTPN5QGh0dxe/2K2+tTnnruRQVQdgbHbLnsKWlQimrsSr3Do9jtDuW+++5TEhISFLPZrFx88cVKYWFhu/ke7/XdkY6eY9vX5hdffKEASn5+/gmN21vvSUVRlHPPPVd54oknTmh+or3p06crTz75pFJSUqKUlJQoZWVlyr59+/rMfr4jt912W4djt91HDxs2THn00UePOc7q1auVyZMnK0ajURk+fLjy3HPPha3vyvsgEAgojz76qJKamqqYTCbl7LPPVnbt2tVuvm2fd0e68tm6ePFi5e677z7mOCerT35XCQQU5avXFOX3qYryaIyi/L9sRclbGelZiQg7Um1X7nx1izLs5x8pw37+kXLW71cq731d3O4zQgjRTzRXKcreDxVlxcOK8sI8RVkSr+7z217+MExRXr9OUdb9WVEKtyiK1x3pWfc5gUBA2V1Sr7yx+Yiyq7g+0tPpGzxORSnfrSg731KUD3+kKE/mhL+unpmpKOv/qiiN5ZGeqRBd525WX9N/WxT+en5xvqJ8s0xRvK7jjyGE6HXHihu0pVEU5egTp3tUY2MjsbGxNDQ0tDuD1eVykZ+fz4gRI3q0CXFPWL58OQ8++CC7d+/ucgPYgoICcnJy2Lt3Lzk5OSf92EuWLGH16tWsXr36pMcAGD58OEuWLOH2228/6TFWr17NFVdcweHDh8PO5j9RLXN49dVXT3oMt9tNTk4OS5cuJTc396THER2/vj0+P01uH80uH3a3D18gfFdSWVrEBblnsnHbN0wcdzoGfev7QlEU3L4Ado8Ph9tPs9uH1x/o8LGf+78/sG3jOl5+66Mu98PoSHe8vjvy6quv8thjj7F3794ul9/pqu6Y8+7du1m4cCEHDhwgNja2+yY3iLQ0/P7vf//L7373O1atWkVMTEyXGn73tf380ZxOJwkJCSxfvpz58+ef9Djd9T6YN28e8+bNY8mSJSc9RlVVFaeddhrbtm1jxIgRJz1OZ/rcdxVXI/z3x601hEfMhStfhOjUyM5L9Bmr9lfwmw/3cqRGbdo6bUQCv71sHKel9l6fHyFED3A3qyWACjepvTiKt7VpzhykN6tnIw+dqWZyZE4DU9cyNAcErwvsldBcCc0VlFTV8MOvUtlW5g1tMi49hhumDeWySelER3Xvd/k+RVHAXt3ae6A6r/Xv+kI4Op/eMgTOuEZt8J06QUpKif6t5CvY8iLs/g/4PeoyazJMvQOmfke+NwvRhxwrbtCW5J13kwsvvJC8vDxKSkrIyupaI6wVK1awePHiUzrIBfDJJ5/wl7/85ZTG2L9/P9HR0dx6662nNM6KFSt4+OGHTymYAbBmzRq+/PLLUxrjyJEj/PKXv5RgRje48MIL2f/tAfYezCcuKY1mty/YD6OVVqPBZtKrlyg96z9cx+LFi5k6cVy78TQaDVEGHVEGHUOs6jKPz4/d7cfu9gX7bahlqjZ9uYonnvxfRqdEE2XQndT8u+v13ZEVK1bw+OOPd3swo7vmXFpayj//+U8JZpyEQCBAU1NTqOH3woULKS4uxuv1drmkVF/az3dkzZo1LFiw4JSCGdA974OmpiYOHTrERx99dEpzyc/P59lnn+2RYEafU/KVWmKqLl8tA7Hgl5D7AGhPbl8pBqYFp6Uwa2Qif/vyMM+sPsiW/Fou+us6bpkxjB+dM5pY8wA+gCfEQGaywcj56gXA71XLrBzZEAxybARnLRSsVS+gflakTWhtMj50JtiSIvccTkYgAI4aaK4IXiqPulYvSlMFBU4zO5VsdgSy2RkYyS5lBG68RGm8nJGkZ0eNlj2ljfzqvd089t99XDwhjeunDeXMoXEndOJUn+L3Ql1BB4GLPHDVd36/qFgYkqMGwLLnw8gFUrJSDBwZZ8IVz8M5v4Ptr8K2l9Xm4mv+H6z9Xxh7OUy/R/rBCNGPSIaGEKJDgYCCvaUPhsuH0+sPW69Bg8WowxalBjHMRh3abvzwb9k19dsfE6LfUhQFu91OU1NT6HVoNBqJiYkJNV8Xg1ef+K6iKLDpWVj5KAS8asPDq15Wm8sKcQzFdQ5+/9E+VuwpByDRZuQXF5zOlZMz0Grl81aIASUQUA9kF25Qm4wXboKGwvbbDclp7cMxdCbED4/MAT13c1hAIjxA0TZoUQlK+O8SRYFyEkKBi51KNjsD2TRibfcwE7WHeFr/V7K0VdTGjued5O+zrDyNg1Wt2S1jUqK5floWV0zOIM7SR7/7Oeug+mB44KImD2oPQ8DXyZ2CTZYTRwcvOa1/WxPlQK4YPPxe2PcBbH4Rija1Lk+frAY2xl0BelPk5ifEINbVDA0JaAghAPUgrtPrp9mlBjHsHj9H7x6iDLpQFobVpEcnBz/EAKIoCi6Xi8bGRvx+9YeyXq8nJiYGk8kkwTUB9IHvKvYaeO9eyPtEvX3axXDZ02A+tcxIMbh8eaCKJR/u4XCVmoF25tA4fnvZeMZnSDafEANaQ3EwuBHM4qjc236b6LTWJuNDZ0DyuJNvNO73gr0qPCjR1FHQohK89i4PW6fY2GGYzE7dWHb6h7PDnUKVt/1nslGnYWx6LBMzY5mQGcfErFiyo5rRbv0bbH05lLGgRMWzPed+lrpn8dHeOtzBTHSjXsuF41O5ftpQpo9I6P3vggG/2tS4bXmoliCGvbLz+xks4cGKlr8TssFg7r35C9EflH6jlqPa9Tb43eoyaxJMCZajikmL6PSEGGwkoCGEOCZFUfD4AmoGRvDiP6oPhkGnDZWQspn0GHQn+WNGiD7O4/HQ0NCA16vWVNZqtURHR2OxWCSQIcJE9LtK/lp45y41RV5ngvMfh6l3yhmV4qR4fAH+vj6fv36eh8PjR6uBG6cP5cFzx/TdM5KFEN3LUQtFm4NlqjZC6dftz+43xaoZgC1BjoSRamnDDks9VUJzeesyR82JzcdghegUsKWALRlsKTRHpbLbk8ZOezw76o3srApQVO9pd1edVsPolOhQ8GJCZixjUqM7//3iscPXr8OmZ9QSTQA6Iw1jb+L96BtYus/DvrLG0ObZiVauOyuLq6Zkkmjr5jO33c1QczA8cFFzUL34XJ3fLzq9g8BFjrr8ZINQQgxW9mq1HNXWl6GpVF2m1cPYy2Da3ZA1Tb5zC9ELJKAhhGjH6w9gD5aQanb78BzViFun1WA1tgYwTHqtHMwVA1pLw2+Xq/XHos1m61LDbzE4ReS7it8HX/4R1vwRUNSDFle/Aqnje+fxxYBW1uDksf/u46OdZQDEWwz8+JzRXHFmJjaTtNsTYlDxOKBkuxrcOLJBbTruaT61MTW6YHAiORioaHtJDrt268zsK2tiZ3E9O4oa2Flcz8GqZjo6YpGdaGVCm8yLsWmxmI0n0UMq4If9H8GGp6F4S2ixMvIcduZ8j2Uliby/oxSHR83eNeg0nDs2leunZZE7MrHr5foURT0h4ei+FtV50Fjc+f10Rhgyqn3gYsgoMEWf+PMVQhyb36vuEza/oO4LW6RNgul3w7grwSDHK8XJ8foD5FfbOVDRxIGKZr4/fyQmvfQ/bEsCGkII/C19MIIBDNfRfTA0ah+MaFNrHwwJYIjB4OiG3wBms5mYmBh0OvlCITrX699VGkrgP99Vy4MATL4ZLvgjGNvXBRfiVGw4VM2j7+8hr1I9eBll0DIyyUZWvIWhQyxkJVgYGrxkxJkx6iXoK8SA5/dBxa42Zao2t5Y6ioo7KigR/Ds6NXyZOaHDbAGfP8DBqmZ2FjWwo7iencUN7C9vxOtvf3giPTZKzbrIimViZhzjM2KJNRu6//kWboaNT8G+j4DgPFLPoPms+/nQexbLtpWwo7ghtHlWgpnrpmZxzdQsUmKC3wm8LrWPRdu+Fi1/Hys4ZEls39cicRTEDVMzYoQQva9sh9pnY9dbreWoLIkw5XY4606ISY/o9ETf5fMHKKhxkBcMXByobCKvoonDVXZ8bSqjfPzDOZye1vlB+8FIAhpCDEKKouDw+EMlpBwd9MEwG1obeVuM0gdDDC6dNfyOjY3FYOiBH8ZiwOnV7yr7l8P731MbfxptcPGfYcI1PfuYYlDz+gO8vukI/9x4hMPVndez12ggPdZMVoJZDXgkhAc9hliNcoKEEANVwK9e9F0vTacoCgU1jrDMiz2ljTiPOtkKIMFqbM28CF4nRfdyc96aQ7DpOfjmdfAGm4XHZMD0u9mbcTXLvqnj3a+LaXKr89dpFBZEF3GDbjVznSvR0f55AWq2SsKI9oGLIaPAktA7z00IceLsNfDVq2o5qsYSdZlWD6dfojYRz5ou5agGKX9AoajWEcy4CAYvgoGLoyuitLCZ9IxKtjEmJZrFc7MZmWTr5Vn3bRLQEGKQ8PgCNLm8NLl82N0+/Ee9pY06bSiAYTPp0UsfDDEIScNv0V165buKzw0rH4HNz6u30ybB1X+HISN75vGEOIqiKByqauZIjYPCWvVSVOukKPh3Rwch27IYdQxNsJAZDHZMGxHPgtNSJKtDiEFAURTKG12hwMXOYvW60eVrt63NpGd8RgwTM+NCfS8y481953uZoxa2vayeod2SmWK0gc6A02Hnv4HpLPMtYJsyJnSXNGq4xrSJ61JKyUhLaxO4yIH4EScUCBJC9DF+n1qOasuLcGR96/LUCWpgY/xVUo5qgAoEFErqnaGgRV5FE99WNHGwshm3r+PAhdmgIyfFRk5yNGNSbeSkRDM6JZr02Ki+8znXB0lAQ4gBLBBQqLF7qHd42h1U0Gk1oeCFLUqPUSd9MMTgJg2/RXfq8e8q1Qfh7TugfKd6e+Z9sPBROQAi+gxFUahu9gSDHI5QkKPldlmjq8N694k2I9+ZPYJbZw6X3hxCDCB1dk+oZNTO4np2FDdQ1eRut51Rr2VsWkwo62JiVizZibau96CIJJ8bdv4bNj4NVfuDCzUQlwWJo8kzT2RZ/Wm8U2SjzqXuADUamDs6ievPGsrC05M7b04uhOifynepfTZ2vQW+YD9GyxC1HNXUOyE2I6LTEydHURTKGlxhGRd5FU3kVTaHeikdzajXMirJxpjUaHJSbIxOjmZMajQZceb+8RnXx0hAo5fV1NRw+umns2XLFoYPHx7p6YhOfPTRR/z6179m+/bt/bLhr6Io1Du8lDe68AbT1zSAxagn2hzsg2Ho/j4Y8voe+K6++mpmzZrFj3/840hPpdsc3fBbo9FgtVpPuuG3vA/6r6effppPP/2UDz744JTH6tHvKjuWwUc/Bq9drTl+xfMw+rzufQwhepjb56ekzklRnZPCWgeHKptZvquMyuABzlizge/kjuD2WcOJtUipPyH6k2a3j90lrYGLncX1FNU6222n02rISbapmRfBvhejU6L7f5aWokDJV+pJBgkjwWgJW+32+flkTwVLNxey8XBNaHlStImrp2Ry/VlZDBsiPbCEGFActfDVP9RyVA1F6jKNLliO6m4YOlPKUfVBiqJQ2eRun3FR0UyTu31GIYBBp2FkUjDTItnG6FQ142JogkVKuXejrgY0+vk3ir7jiSee4JJLLgk7yPXDH/6QKVOmYDKZmDRp0kmNu2fPHq666iqGDx+ORqPhz3/+80mN43a7+cEPfkBiYiJWq5VLL72U4uLiEx5n165dzJ07F7PZTEZGBr/97W/b9Wg4Ge+88w7nnXceiYmJaDQavvnmm5Map7CwkEsuuQSr1UpiYiL3338/Ho8ntP7iiy9Go9HwxhtvnPKce5OiKDS6vORVNlNU58DrD2DQacmIM3N6Wgwjk20kR0dhMep75Izznnp9d+TLL7/kkksuIT09HY1Gw3vvvddtY/f1OdfV1XHLLbcQGxtLbGwst9xyC/X19ac8v67sRx555BEee+wxGhsbT/nxIs3v99PQ0EBlZWUomGGxWEhOTiYmJuakg5kdvQ+Ot8/piu7az3fkscceY9asWVgsFuLi4rpt3P722XTXXXexdetW1q1bd1Lz7HHuZnj3Hnj3bjWYMXwO3LteghmiXzLpdWQn2Zg7OolbZgxjyaXj2PCLBfzftRPJTrLS4PTyp88OMPv/reLJT/ZTaz+xfaYQone4fX6+KarnnxsL+Mm/d3DO/63hjCWfcP2Lm3h8+X7+u7MsFMwYkWjlsknp/Prisbx9z0x2LzmPFQ+czf+7egI3TR/G+IzY/h/MAPWgZOYUSD2jXTAD1P3fpRPTWbp4Bl88OI975o4k0WakqsnNc6sPMffJ1dz4t018uKMUt+/YpfuEEP2EJQFm/wju/waufU39Hq/4Ye978MoF8MIc+Oo18LYP/oreUd3sZsOhal5dn8/D7+7imuc3MOm3K5n++Ofc8vIWfvfRXpZtLeLrwnqa3D70Wg2jkm1cdEYaDyzK4dmbzuSzH5/N3t+ez4oHzuapGybzg4U5nDculRGJVglmRIjke3cDp9PJyy+/zPLly8OWK4rCd77zHTZv3szOnTtPamyHw0F2djbXXHMNP/rRj056jg888AAffvghy5YtY8iQIfzkJz/h4osvZvv27eh0ui6N0djYyDnnnMP8+fPZunUrBw4c4Pbbb8dqtfKTn/zkpOcGYLfbyc3N5ZprruGuu+46qTH8fj8XXXQRSUlJrFu3jpqaGm677TYUReGpp54KbXfHHXfw1FNPcfPNN5/SnHuLw+OjvMFFczBKrNNqSIo2kWg19Ur6Wk++vjtit9uZOHEid9xxB1dddVW3jQt9f8433ngjxcXFrFixAoDFixdzyy238OGHH57S/LqyH5kwYQLDhw/n9ddf59577z2lx4uUnmz43dH7oKv7nOPprv18RzweD9dccw0zZ87k5Zdf7rZx+9tnk8lk4sYbb+Spp55i9uzZJz3fHlG2A97+DtQcBI0W5j0Ec34C2q49fyH6A71Oy5VnZnLZpAyW7yrj6VUH+baiiWe+OMTf1xVw84yh3HV2NsnR/StDW4iBwucPcLCqmZ1FDaHyUfvLG/H625+4lhYb1aZpdxxnZMYSa5Zsq6ONSLTyiwtO48fnjObzfRUs3VrE2rwqNhyqYcOhGuItBq46M5Prpw1lVLI0hBWi39PpYeyl6qV8N2x5AXa+pZam+uA+tT/elNvgrO9CbGakZzsg1dk9asZFpZpx0ZJ90dnJM1oNDB9iJSdFbdDd0uNiRKJ1YAThB7g+XXJKURQUb8fNVXqaxtD1vgPvvPMOd999N1VVVR2uX7JkCe+9995JZx20GD58OA888AAPPPDACd2voaGBpKQkXnvtNa677joASktLycrKYvny5Zx3XtfOAH3uued46KGHqKiowGQyAfCHP/yBp556iuLi4m7JDCgoKGDEiBF8/fXXJ3wG/ccff8zFF19MUVER6enpACxbtozbb7+dysrK0OvtyJEjDB8+nEOHDpGdnX3Kcz5ZiqLg83T++nb7/FQ2umlwqjtfjUbDEKuRRJvplBt764197/XdEY1Gw7vvvsvll1/ereP2xTnv27ePsWPHsmnTJqZPnw7Apk2bmDlzJvv372fMmDHHGaFrjrUf+c1vfsPnn3/Ol19+2S2P1SWKAl7HKQ4RbPjd1EQg2PBbp9cTEx197JJABkuX0387eh90dZ9zIk52P388r776Kg888EC3ZPwcrb98Nq1Zs4Zzzz2X+vp6zGbzCc21rW4rOaUoakPBT38Ffg/EZMCVf4PhuSc/phD9RCCgsHJfBU+tymN3iZoZaNJruWHaUBafnU163Mm/R4UQx6YoCgU1jrCG3btLGtv15QOItxiCgQs1gDEhK1YCj6egqNbBW9uK+Pe2YsobXaHlZw2P54ZpQ7nwjDSiDHJCgxADhqMWvn4NtvwtvBzVaRepTcSHzZJyVCeh0eVVS0SVN3Ogoom8SjVw0VH/JlD/ibPiLYxOiWZ0io3RKWqvi5FJNtnn9kFdLTnVpzM0FG+A0kc2ROSx0387C42xay/sL7/8kqlTp/bwjE7e9u3b8Xq9nHvuuaFl6enpjB8/ng0bNnT5oNHGjRuZO3du6IARwHnnncdDDz0UCkRE0saNGxk/fnzowCKo83O73Wzfvp358+cDMGzYMJKTk1m7dm1EAxo+T4AXf7gmIo+9+C9zMZgGxut7oNi4cSOxsbGhYAbAjBkziI2NZcOGDd0W0DiWadOm8cQTT+B2u8Pe5z3K64DH04+/3TFoAHPwckIeLgVj1+oYd/Q+6Oo+R3Sstz+bpk6ditfrZcuWLcydO7d7n8yJctTC+/fBt/9Vb4+5EC57Rk1ZF2IQ0Go1nDculXPHprD62yr+uiqPrwvreXVDAa9vPsLVU7L43ryRZCW0L+kihOg6RVEob3Sxo6ghLIDR6GpfH9xm0jM+I0bte5EZx4TMWDLjzT1Sznawykqw8ONzx3D/whzWHKhi6ZZCVu2vZGtBHVsL6ljywR6umJzB9dOGcnraiZ8YI4ToYywJkPtDmPF9OPCx2kS8YC3s+0C9pIxX+2yccQ0Y5GSOozW7fWpD7go1cPFt8O+2AeGjZcSZQ0GLlsuoZBvmLh7fFf1Hnw5o9BcFBQVhB7T6mvLycoxGI/Hx8WHLU1JSKC8vP6Fxjm6Em5KSEloX6YBGeXl5aD4t4uPjMRqN7Z5nRkYGBQUFvTi7/quvv74HivLycpKTk9stT05OPqH36anIyMjA7XZTXl7OsGHDeuUx+4uO3gcnss8R7fX2Z5PVaiUuLo6CgoLIBjSObID/fBcaS0BnhHN/D9MWy9lZYlDSaDTMPy2ZeWOS2HCohr9+nsfm/FqWbink39uKuGJyBt+bN5LsJCnHIkRX1Nk9oZJRLY27Ozpj1ajXMjYtJpR5MTErluxEW6+UsxVqGb6Fp6ew8PQUyhtcvLWtiGVbiyipd/KPjUf4x8YjTMyK48ZpWVw8IR2rSQ7bCNGv6fRqk/DTL4GKPWqW9o43oWI3fPADtRzVmcFyVHFZkZ5tr3N6/BysbA6WiGotFVVS33nfkbTYqNbm3CnRjE5VAxc22V8OGn36f1pj0JL+21kRe+yucjqdp1Z2IkIURTnhM26O3r6lYllXx3n99de5++67Q7c//vhj5syZc0JzOJH5QcfP02w243CcWpmbU6U3aln8l7koikKdw0NVkxuvXy1BFWXQkRoThS2qZ+rR6o2Rf32vXbuWCy64IHT7hRde4KabbuqWsS+44ALWrl0LqBk5e/bs6ZZxe3LO0PXXb2cKCwsZO3Zs6PbDDz/Mww8/3OXHbynD06vvDYNFzZToIr/fT7PdjsNuDy0zWyxE22xd7rkQ9thd1Nn74FT/z7rLPffcw7/+9a/Q7ebm5m4Z91RfUyejJz+bIrrvD/hh7f/C6idACUDCSLjmFUibGJn5CNGHaDQackclkjsqkS35tTy1Ko+1edW8vb2Yd74q5uIJ6Xx//ijGpEZHeqpC9BnNbh+7S1oDFzuL60NNutvSaTXkJNvUzIusWCZmxjE6JVrqg/cRqbFR/GBhDt+fP4p1B6tZtrWQT/dUsKOonh1F9fz2w71cOimDG6ZlcUZGrGTMCNHfpYyDS/4CCx+Fr/8FW/8G9YWw/s+w4a9qOappd8Pw2QPuhCeX18+hquZQxkVL4KKozkFnzRCSok2MTrGRkxzNmFS1ZNSo5Gjp3ST6eEBDo+ly2adISkxMpK6uLtLT6FRqaioej4e6urqwM2ErKyuZNavrAaPU1NR2Z81WVlYCtDtLuTOXXnppWEmdjIyMLj9+V+a3efPmsGV1dXV4vd5286utrSUpKanbHvtkOQIByhtcuH1+0GkwmwykxkQRazb0mS+rPfX6njp1algPi66+hrripZdewulUf9CdajPotnpyzqmpqVRUVLRbXlVV1eXHSU9PD5tfQsKJla+pra0F6N33hkbTpbJPrQ2/7erBaoMFk8lETExMt/4fd6aj98GJ7HN62m9/+1sefPDBbh/3VF9TxxKJz6aI7fsby+Cdu9QUc4AJ18NF/wMmOTgrxNGmjUjgtTun83VhHc98cZDP9lXywY5SPthRyvnjUrlvwSjGZ8RGeppC9Cq3z8++siY1eBEsH3WwqrnDA0AjEq1tmnbHMi49Vkpt9ANarYazRydx9ugkqprc/OerYt7cWkR+tZ2lWwpZuqWQsWkx3DAti8smZxDTQye+CSF6iSUBcu+Hmd+HAyvUclT5a2Dfh+oleRxMXwxnXAvG/lWC0+MLkF9tD5aIUgMXeRXNFNTYCXQSuEiwGtv0t2jNvIi3Gnt38qLf6NMBjf5i8uTJYWfG9jVTpkzBYDCwcuVKrr32WgDKysrYvXs3f/zjH7s8zsyZM3n44YfxeDwYjepO5dNPPyU9Pb1duY/OREdHEx3dMwdwZs6cyWOPPUZZWRlpaWmh+ZlMJqZMmRLazuVycejQISZPntwj8+gKu9tHeYMLu0etX6vXakiOjiLBZkTbRwIZLXrq9W02mxk1alS3jwvdGyhrqyfnPHPmTBoaGtiyZQvTpk0DYPPmzTQ0NHT54K5erz+l+e3evZvMzEwSExNPeozuFmr43diIP9jwW6/XExMT06uZcR29D7q6z+kNycnJHZYsO1Wn+po6lt7+bDp06BAul6v39/0HPoX37gFHDRiscNH/wqQbencOQvRDk4fG89JtZ7GntIGnVx3k493lrNijXhaelsx9C0YxeWj88QcSop/x+QMcrGpmZ1FDqHzU/vJGvP72R4HSYqPaBC/iOCMjlliLHOju75KiTdwzdyR3n53NpsO1LNtayMe7ytlb1siv39/DY8v3cfGEdG6YlsWZQ+P7zIlwQoiToA02CT/tIqjcFyxHtQwq98CHP4SVj8KZt6rlqOL7Vllorz/AkRo7B47KuCiotuPrJHIRazaE9bjICf6daOulHp5iwJCARjdoaT569FmmBw8epLm5mfLycpxOZ+gs17Fjx4YOuhyPx+Nh7969ob9LSkr45ptvsNlsXT7IFBsby5133slPfvIThgwZQkJCAg8++CBnnHEGixYt6vLzvPHGG/nNb37D7bffzsMPP0xeXh6PP/44jzzyyCl/iaqtraWwsJDSUrX0zLfffguoZ96mpqZ2aYxzzz2XsWPHcsstt/Dkk09SW1vLgw8+yF133UVMTGtTtU2bNmEymZg5c+YpzflkuLx+KhpdNDi9AGg1GhJtRpKiTei0fTPtuydf3x1pbm7m4MGDodv5+fl88803JCQkMHTo0JMet6/P+fTTT+f888/nrrvu4oUXXgBg8eLFXHzxxafcELyr+5G1a9eGNWiONLfbTWNjI15v8P2i1RIdHY3FYun1H24dvQ+6us85nu7Yz3emsLAwtH/1+/2h1/yoUaOw2U6+Jn1//Gxau3Yt2dnZjBw58sSe7MnyeeDz38DGp9XbqWfA1a9CYs8EiIQYqMalx/LczVM4UNHEM18c5MMdpXy+v5LP91cyJyeRHyzIYdqI7sseE6I3KYrCkRpHWN+L3SWNOL3+dtvGWwyhrIsJwfJRydH9r+yx6DqNRsPMkUOYOXIISy7x8M7XJSzbUkheZTNvby/m7e3F5CTbuH7aUK6cnCFnMgvR3yWfDhf/CRY+Al+/rgY36o+opag2Pg1jLlSbiA+f06vlqPwBhcJahxqwKG/iQGUzeRVNHK6y4wmWTT+azaQPy7gYk6KWi0qKNkkQVnQPpZc1NDQogNLQ0NBundPpVPbu3as4nc7entYpmzFjhvL888+HLZs7d64CtLvk5+eHtgGUV155pdNx8/PzOxxj7ty5oW1eeeUV5Xj/lU6nU7nvvvuUhIQExWw2KxdffLFSWFjYbr633XbbMcfZuXOnMmfOHMVkMimpqanKkiVLlEAg0G6+X3zxxTHHOVrLczj68uijj4a2ue2228Ked0eOHDmiXHTRRYrZbFYSEhKU++67T3G5XGHbLF68WLn77rtPaH6nyuPzK0W1dmVnUb2yo6hO2VlUpxTV2hWP19+r8zhZPfX67sgXX3zR4bhtX5uPPvqoMmzYsBN+Hn19zjU1NcpNN92kREdHK9HR0cpNN92k1NXVhW0zbNiwsPdFV3RlP+J0OpWYmBhl48aNJzR2T/B6vUpNTY1SUlKilJSUKKWlpUpjY6Pi90f2/dLR+6Ar+5ze2s935Lbbbutw7Lb76J56TfWlzyZFUZRzzz1XeeKJJ07oeXY25+N+V6k+qCgvzFWUR2PUy/KfKYrX1fn2QoguO1TZpDz472+UkQ/9Vxn284+UYT//SLnm+Q3K2gNV7d73QvQ1ZfVOZcXuMuWPK/YpN7+0SZmw5JPQ67jtZeyvP1aufX6D8th/9yof7ihRCmvs8voWiqIoSiAQULYV1Cg/+fc3yphfLQ+9ZnJ+uVy5f+lXyoaD1fJaEWKg8PsUZf9yRfnHpa2/Kx6NUZRnZijK1pcVxd3cvQ/nDyhHqu3Kyj3lyjNf5Ck/XPqVcsGfv1RG/3J5h59Vw37+kXL6rz9WLn1qrfLgv79RXlxzSPlif4VSUueQ/ZA4aceKG7SlUZTOWq/0jMbGRmJjY2loaGh3BqvL5SI/P58RI0b0uybby5cv58EHH2T37t1ou3imfUFBATk5Oezdu5ecnJyTfuwlS5awevVqVq9efdJjAAwfPpwlS5Zw++23n/QYq1ev5oorruDw4cNhZ/N3h3nz5jFv3jyWLFly0mNUVVVx2mmnsW3bNkaMGNF9k+uE1x+gptlDdbObQPCtFhNlIDU2iihD/6llG8nXd0daXqOvvvpqt47b1+fsdDpJSEhg+fLlzJ8/v3smFvTMM8/w/vvv8+mnn3bruCfC7/fT3NyMvU3Db4vFQnR09Ik3/O4BA2E/f7SefE31pc+m3bt3s3DhQg4cOEBs7KnV3j/ud5Vdb8OHD4CnCczxcNkzagq5EKJbFdU6eG7NId7aVhQqxTN5aBw/WDCK+WOS5ew/EXF1dk9Y5sXO4gYqm9zttjPqtJyeHhPKvJiYGUt2kg2dVl7D4tgaXV7e/6aUpZsL2VvWGFo+ItHKdWdlcfWUTCnjIsRAUbm/tRyVN/h7OSq2TTmq4V0eSlEUShtcarZFsExUXqXa56KjDEGAKIOWUck2RicHMy5S1UbdGXFmtPJ5JbrRseIGbUnJqW5y4YUXkpeXR0lJCVlZWV26z4oVK1i8ePEpHzj95JNP+Mtf/nJKY+zfv5/o6GhuvfXWUxpnxYoVPPzww90ezGhqauLQoUN89NFHpzROfn4+zz77bI8GM3z+AI0uL/UOL3a3j5aIocWoJy02Cqup/73tIvn67siaNWv48ssvu33cvj7nNWvWsGDBgm4/8Axq8/Snnnqq28ftikAggMPhoKmpiZYYe282/O6q/r6f70hPvqb60mdTaWkp//znP085mHFMHjt8/DP4OthrZehMuOoliM3succUYhDLSrDw+BVn8IMFo3hhzWGWbink68J6vvPqNsZnxHDf/BzOHZsiP7JFr7C7fewqUQMXO4IBjKJaZ7vttBoYnRLNxGDJqImZcYxOicao75ulZ0XfFhNl4JYZw7h5+lB2lTSwdEsRH3xTQn61nT98vJ//+eRbzh2XwvVnDWX2qETZHwrRnyWfBhf/n1qO6ptgOaq6AtjwFGxoKUe1GEbMDZWjUhSFikZ3qL9FXkUz31Y0cbCymWa3r8OHMeq0ZCdZGZMa7HERbM6dlWCRQLvoUyRDQ4huEAgooSBGk9tH27eVxagnyWYkxmyQswWFaENRFJxOJ01NTRFt+C3Eiejwu0r5bnj7Dqg+AGhg7s/g7J+Brv8FsIXoryqbXLy0Np9/bTqCw6N+poxJieb7C0Zx0Rlp8iNcdBu3z8++siY1eFGkBi8OVjXT0a/qEYnWNk27YxmXHovZGPmsUzFw2d0+PtpZyhtbithRVB9anhlv5rqpWVwzNYvUWPmeLUS/F/BD3krY8gLKwVVUE8OBQBYHrFM4EH82ef5UDlQ6aHR1HLjQazVkJ1nJSYlmdHIw4yIlmmEJFvQ6CbKLyOlqhoYENIQ4SQFFodnlo97ppdHpDZWUAogy6IgzG4izGDDq5UeLEEfrqOF3TEwMZrNZAn+iTwv7rmIywbaXYcXD4HdDdBpc+SKMODvS0xRi0Kq1e/j7unz+saGApuDZh9mJVr43fxSXT0qXH+nihPgDCnmVTewsagiVj9pf3hgqc9ZWWmxUm+BFHGdkxBJr6TuZpmLw2VfWyLIthbz7dUnooKZWAwtOS+aGaUOZOzpJ9olC9DO1dk8w26KJb1vKRZXVU+fquDm3TgPDEq2MCTbnbmnUPXyIVbIDRZ8kAQ0heoDPH8Dh8dPk8tLg9OILtL59jDotcRYDsRYj5n7UH0OI3uT1emlqasLlcgGg0Wiw2WxYrdYu96UQIpJC31XSEoj65EHY94G6IudcuPw5sCZGdoJCCAAanF7+saGAl9fl0+BUg+dZCWa+N28UV52ZKT/iRTuKonCkxhHW92J3SWOH9cTjLYZQ1sWEYPmo5Gj5/Sr6JpfXz/JdZSzdUsjWgrrQ8tSYKK6dmsm1Z2WRGW+J4AyFEEdrcHg5UNlaKqqlbFR1s6fD7TUaGBYfRY6xltFNWxjt2cVoTTHZmnJMYxbB9Lshe16oHJUQfZUENIQ4RYqi4PapAQyH24fd48ftC/9Bo9cGgxhmAxajTs4sF6ITfb3htxBd5XK5yM/bz4j1PyOqfDNoDXDOb2D6vSBBOSH6nGa3j9c2HuGltYepsasHAdJio7hn7kiuOyuLKDkJZdAqb3AFgxctAYyGUPCrLatRx/iMWCZmxTEhU+17kRkvGaWifzpY2cSyLUX856ti6hzq612jgTk5Sdw4LYuFp6dgkKwNIXpNk8tLXmUzecFsi5bARUWju9P7ZMab22VcjEyytZY0DATg4Gew+Xk49HnrHRPHwLS7YOINYLL18DMT4uRIQEOIExQIKDi9fuweHw63H4fHF5aB0cKk12E16Yg1G7CZ9PJjRohjCAQC2O12mpub+3TDbyG6RFFw1RaTf2AfI9b/mCiDHq7+O2ScGemZCSGOw+HxsXRLES+sOURlk3qQICnaxOI52dw0YygWo/S8Gcjq7B52ljSws6i1aXfL66Ato07L6ekxocyLiZmxZCfZpAeLGHDcPj+f7qlg2dZC1h+sCS1PtJm4ekom15+VxfBEawRnKMTA4vD4QpkWeZXNocyLknpnp/dJj40KC1qMTolmVLINq+kEvrNU56kNxL95AzzN6jJTLEy+GaZ9FxKyT/GZCdG9JKAhxHF4/YFQ5oXD48fp9XP020Gr0WA26LCYdFiNeixGndQZFaILpOG3GHD8Xqg7gsvRSH5JFSMqPyXqvEchqvMvWUKIvsfl9fPWtiKeW32I0ga1/GGC1cids0dw68xhREdJsL2/s7t97CppCMu8KKx1tNtOq4HRKdFhfS/GpEZLOTIx6BypsbNsaxFvbSumurk10DczewjXT8vi/PGpmKQvpBBd4vL6OVjZTF5lE9+WBzMvKpsoqu08cJEcbWJMajQ5yWrwIiclmpwUGzHd+Z3E1agGNba8CLWHggs1MPo8mLYYRi6QclSiT5CARj9zpMbe4fIT+d853qYn+l/d6dadrOj66Er49m3uqNFo0Gk16DSg1ap/azXh16F1Gk3oWqPhmJkSiqLg8gZweFoCGD48vvZNk/Q6LVajDotRj9WoI8qoQys7dSFOiDT8FgOOqxHqj0DAh8unIb/Oy4jR44kymyM9MyHESfL4Arz7dTHPfHEodLA7JkrPHbkj+E7uCGnm3E+4fX72lTWxs7ieHUVqEONgVXOHv6GGD7Go/S4y1fJR49JjJDNHiDa8/gCf76tk2dZC1hyoCr2P4i0GrjwzkxumZTEqOTqykxSij3D7/ORX2/m2PLzHRWGtgw4KfQCQaDOGghajU9WMi9HJ0b37nSMQgEOr1HJUB1e2mdxoNbAx8XowyftcRI4ENPqZncX1kZ5Cv6ZBg07bPtCh1Wrw+QM4PX78HbzUoww6NYBhUgMYBp1WDrgKcZK8Xi+NjY243eqZXdLwW/R7SgCayqC5Ur2tj8JlTie/uHRQflcRYiDy+QN8uLOUp1cd5FCVeoKRzaTnlpnD+O7sEQyxmSI8Q9HCH1DIq2xiZ1FDqHH3/vJGvP723/FTY6JCgYsJmbFMyIiTIJUQJ6C4zsG/txXz1rYiyoLZbABTh8Vz/bShXHRGWmu9fiEGMK8/QEG1nQMVzXxb0RTsddFEQY0DfyeRiziLIVgiSi0V1RLE6HPfKaoPwta/wdevg6dJXWaKgUk3qb02hoyM7PzEoCQBjV5WU1PD6aefzpYtWxg+fPiJ37+584Y/IZqwq/Yrjn23TheczOH7zsfseLSuPoaCgj+g9rPwK0ro2h9QCCgEr4O3g+s6k7dvD9+79VreX7MFi8WKVqPBYtRhNamloyxGHTo5yCrEKZOG32JA8rmhrgC8wTIllkSIycDl8fTb7ypCiM75Awof7y7j6VUH2V+u/qg3G3TcNH0oi8/OJjlG3u+9SVEUjtQ4QoGLncX17C5pxOn1t9s2zmII9btouZb/LyG6hz+gsOZAJUu3FLFqf2XoAG50lJ4rJmdw/VlDGZsu5TdF/+fzBzhS62jXnDu/2t5h4BzU98Hoo3pc5KTYSLKZ+teJsu4m+GYpbHkBag62Ls85F6bfDdkLQI6diV4iAY1e9uCDD1JXV8fLL78cWvbDH/6QdevWsXv3bk4//XS++eabkxr7P//5D7/+9a85dOgQI0eO5LHHHuOKK644oTHcbjcPPvggS5cuxel0snDhQp599lkyMzNPaJxdu3Zx3333sWXLFhISErj77rv59a9/fcI762effZYnn3ySsrIyxo0bx5///GfmzJlzQmPU1dVx//3388EHHwBw0cWX8OT//ZmY2Fj8wWDHrTdcx8RJk/j1r35FlEHXvz5UhOjjpOG3GLCcdVBfBIofNDqIGwrmOKB/f1cRQhxfIKDw2b4Knlp1kF0lDQAY9VounpDGsAQridFGEm2m4EX9+4Sac4oOlTe4gsGL1r4XDU5vu+2sRh3jM8IzL7ISpKSlEL2hotHFW9uKWLa1iOK61n4AEzNjuX7aUC6ZmI5N9oeijwsEFIrqHGFBiwMVzRyqau6wLDmonz1tm3PnpEQzJiWalJh+Frg4nkAADq+CzS9A3qety4eMgml3w6QbpByV6HES0OhFTqeT9PR0li9fzsyZM0PL77//fsaMGcPmzZvZuXPnSQU0Nm7cyJw5c/jd737HFVdcwbvvvssjjzzCunXrmD59epfHuffee/nwww959dVXGTJkCD/5yU+ora1l+/btXT6DurGxkdGjRzN//nx++ctfcuDAAW6//XYeffRRfvKTn3R5Lm+++Sa33HILzz77LLm5ubzwwgu89NJL7N27l6FDh3Z5nAsuuIDi4mJefPFFABYvXszw4cP58MMPQ9t8+OGH3HPPPRQWFsqZ4kJ0k84afsfGxmIy9bE0WiFORMAPjSXgqFFvG6wQPwz0ra/r/vpdRQhxYhRFYfWBKp76PI+vCuuPua3ZoAsFOoZYTSSFBT3UwMcQm4kkm4kYs35gHfw4CXV2DztLGthZVM+OYPZFZVP7bHWjTsvp6TFhmRfZSTZ02sH97ydEpAUCCusPVbNsSxGf7i0Pnb1uNeq4dFI61581lAmZsYN+XyciS1EUSuqdoYDFgQq110VeZRMub8eBiyiDlpxkNctiTJuMi4y4QRg4rzkEW1+Cr/8F7kZ1mTEaJt+k9tqQclSihwyIgIaiKKGmsr3NYDB0eYf1zjvvcPfdd1NVVdXh+iVLlvDee++dVEDjuuuuo7GxkY8//ji07Pzzzyc+Pp6lS5d2aYyGhgaSkpJ47bXXuO666wAoLS0lKyuL5cuXc95553VpnOeee46HHnqIioqK0EHLP/zhDzz11FMUFxd3+d9r+vTpnHnmmTz33HOhZaeffjqXX345TzzxRJfG2LdvH2PHjmXTpk2hwM6mTZuYOXMm+/fvZ8yYMQB4PB5iYmJYvnw5CxYs6NLYQojOScNvMWB5nWqJKV+wTrQtBaJTQROeXi0BDSEGF0VR2HS4lvUHq6ludlPd7Aleq5fODop0xqjTMiSY2dFy3RL0SIpWAyItwZF4i7HfH7y3u33sLlEzLlrKR7U0YW9Lq4HRKdFq1kVmHBMz4xiTGo1RLyUuhOjLqpvdvPNVMcu2FHG4urX87OlpMdwwLYvLJmUQa5bMbdFzFEWhvNGlBi3KgxkXlc0crGjC7mlfphDUzMtRSTZGp9iCmRdqxkVmvBltP//c7XbuJtixDLa8CNUHWpePOkctRzVyoZSjEt2qqwGNPp0P6PV6efzxxyPy2A8//DBGo7FL23755ZdMnTq1R+axceNGfvSjH4UtO++88/jzn//c5TG2b9+O1+vl3HPPDS1LT09n/PjxbNiwocsBjY0bNzJ37tywM7DPO+88HnroIQoKChgxYsRxx/B4PGzfvp1f/OIXYcvPPfdcNmzY0MVnpM4lNjY2LEtlxowZxMbGsmHDhlBAw2g0MnHiRNauXSsBDSFOgTT8FgOWoqgZGQ0lQAC0eogbBlFSD1oIoX7ezRw5hJkjh7RbpygKdo+fmmBwo6opPNhREwp+eKhuctPk9uHxByhrcIU12e2MVgMJ1tbSVqHraFMoIJJka/3boIvs57Hb52dfWRM7i+vZUdTArpJ6DlY201HP1OFDLEzIjAs17h6XHoPF2Kd/mgohOpBoM7H47JHcNSebzfm1LNtSyPLd5ewra+SR9/fw+PJ9nJ2TxMSsODLjzWTEmUmPM5McbUIf4X2W6F8URaGqyd2abVHZxLflTeRVNtPk8nV4H4NOQ3aiLZRx0VI2amiCRV5/XWWKVhuEn/VdOPyFWo7qwCdwcKV6SRipZmxMulF+P4leJd8au0FBQQHp6ek9MnZ5eTkpKSlhy1JSUigvLz+hMYxGI/Hx8ac8ztENz1vmVl5e3qWARnV1NX6/v1ueU3JycrvlycnJ7cbJyMigoKCgy2MLIVr5/X6amppwOFrPppSG32LACPjUXhmuevW2KVoNZujkTEIhxPFpNBpsJj02k55hQ6zH3d7l9VNjV4MbrYGP8KBHy/I6h5eAQug2NB13/DiLgSHW1qBHUptyV20DIknRJqIMp/YZ7g8o5FU2sbOoNfNif3ljh41TU2OiQoGLlr4XsRbZzwoxkGg0GmZkD2FG9hCWODy881UJy7YWcqCimU/3VvDp3oqw7XVaDakxUcEARxTpwUBHS8AjI94s/TgGsZpmNXARClpUNHOgsol6R8cVXHRaDSMSrWrGRXIw4yLVxrAh1ogH+wcMjQZGLlAvtYdhS7AcVe0hWPFzWPU7NagxbTEk5kR6tmIQ6NOfEAaDgYcffjhij91VTqezR8tOHF3GRVGUbintcjLjdDSXjpafzDinOkZn45jN5rCDsUKI45OG32LA89jVElN+D6CBmDSwJqtf1oUQogdEGXRkBA/YHY/XH6DO7qHqqGBHS0Ckqk0wpNbuwR9QqHd4qXd4OVRlP+74NpO+Tcmr9o3OW7JAEm1GbCY9R2ococDFzuJ6dpc04vS2L+URZzGE+l20XCfHSHk+IQaTOIuR78wewR25w9lZ3MDm/Br2lTVRUu+ktN5JeYMLX0Dtb1BS7+x0nJgofViQIz0Y/MiMb8nyiOr3ZfkGu3qHp01/iya+Dfa5qLF7Otxeq4FhQ6zkJNsYk9qacTEi0YpJLyfb9ZqEbDj/cZj/MOxcBptfhOpv1bJUW15Uy1BNvwdGLZJyVKLH9OmAhkaj6XLZp0hKTEykrq6uR8ZOTU1tl3FQWVnZLsPheGN4PB7q6urCsjQqKyuZNWvWKc8F6PJ8EhMT0el03fKcKioq2i2vqqpqN05tbS0jR0rDIiG6oqXhd2NjI4GAWhdcGn6LAUVRwF4JjWWAAjojxA8H4/HPrhZCiN5i0GlJjonqUjAgEFCod3rVbI42wY6ao7NAmtS/Pf4AzW4fzW4fR2qOf9KPTqvB30HdKItRx/iM2DbBiziyEqSnlhBCpdFomJgVx8SsuLDl/oBaOqgloFHa5lJS76K03kmD00ujy0djeRP7yzvOUOsoyyMjPjzTQ7I8+oZGl1fNsqhoCjXnPlDRRGWTu9P7DE2wtOlxYWN0SjQjk2ynnGEoupHJppaimnonHF6tBjO+/RgOfa5eErLblKOKjfRsxQAje/duMHnyZP71r3/1yNgzZ85k5cqVYX00Pv300xMKREyZMgWDwcDKlSu59tprASgrK2P37t388Y9/PKG5PPzww3g8nlCg6dNPPyU9Pb1dKarOGI1GpkyZwsqVK7niiitCy1euXMlll112QnNpaGhgy5YtTJs2DYDNmzfT0NDQ7t9m9+7dXH311V0eW4jBShp+iwHP74X6I2pzO4CoOIjLUvtmCCFEP6XVakiwGkmwGhmdEn3MbRVFocntCwU31F4fbqrCgh6tARG7x48/oGDUaTk9LTqs78XIJJucHS2EOGE6rYbU2ChSY6OYMiy+w22a3b5ggKNtwMN1SlkeLcEO9XaUZHn0ALvbR15l24yLZvIqmo7ZNyojztyux8WoZJv0VepPNBoYOV+91ObD1pfgq9fU0lQrfgGftylHlTQ60rMVA4RGaakl0kuO1a3c5XKRn5/PiBEjerSEU3fbtWsXZ555JpWVlWEZEAcPHqS5uZnnn3+eL774gjfffBOAsWPHdjnzZMOGDZx99tk89thjXHbZZbz//vv86le/Yt26dWENsY/n3nvv5aOPPuLVV18lISGBBx98kJqaGrZv397lOvgNDQ2MGTOGBQsW8PDDD5OXl8ftt9/OI488wk9+8pMuz+XNN9/klltu4fnnn2fmzJm8+OKL/O1vf2PPnj0MGzasy+NccMEFlJaW8sILLwCwePFihg0bxocffhjapqCggOzsbPLz809obCEGE2n4LQYFd5NaYirgAzQQmwmWISdcYqq/flcRQoiT4fT4qXV4SLKZMOrlO4EQom/wBxQqm1xhWR0dZXkcj16rISUmioxQw/L2/Twky6M9l9fPwWDg4ts2GRfFdZ0Hl1JjosgJZlq0ZFzkpETLv+9A5bHDzjfVJuJV+1uXj1wA0+6GnHOlHJXo0LHiBm1JQKObzJw5k9tvv5277747tGzevHmsWbOm3bb5+fmhjAaNRsMrr7zC7bff3unYb7/9Nr/61a84fPgwI0eO5LHHHuPKK68MrX/11Ve54447ONZ/pcvl4qc//SlvvPEGTqeThQsX8uyzz5KVlRU23+HDh/Pqq692Os6uXbv4/ve/z5YtW4iPj+eee+7hkUceCZ29XVBQwIgRI/jiiy+YN29ep+M8++yz/PGPf6SsrIzx48fzpz/9ibPPPju0fsmSJbz66qvHbOZdW1vL/fffzwcffADApZdeytNPP01cXFxomyeeeII1a9awYsWKTscRYrCSht9iUFAUaCqD5mCZQn2UWmLKcPwa9h3pz99VhBBCCCEGiyaXl7IGV4dZHiV1TsobXR2W0ztarNkQltUxmLI8XF4/h6vs5FWqpaK+LVcbdRfWOujs8FOizRQKWLQEL3JSook1Sx/GQUlRIP9LNbDx7XIg+MKJHwHT7oJJN4E5LpIzFH2MBDR62fLly3nwwQfZvXt3l89oLigoICcnh71795KTk3PSj71kyRJWr17N6tWrT3oMgOHDh7NkyZJjBleOZ/Xq1VxxxRUcPnw4LFvlRLXM4VjBleNxu93k5OSwdOlScnNzT3ocIQYaafgtBg2fG+qOgDfYINcyBGIyQHvyAbv+/F1FCCGEEEKojpXlUVynXje6fMcdRx8sodWa1dEa+MgMXlv7eBaCxxegoMbOt+VqqagDFc0cqGyioNpOZzGfeIshLGjR8ne8te/3wRURUlcQLEf1T3A1qMsMVph4vVqOKvm0iE5P9A1dDWj07b1qP3LhhReSl5dHSUlJWNbDsaxYsYLFixefUjAD4JNPPuEvf/nLKY2xf/9+oqOjufXWW09pnBUrVvDwww+fUjADYM2aNXz55ZenNMaRI0f45S9/KcEMIYIURcHhcNDU1BRq+G0wGIiJiZGG32LgcdZDfSEoftDo1F4Z5lP7bBJCCCGEEAODTqshLdZMWqyZKZ1Up+4oy6OkrjXTo7xR7eVRXOc8ZrmljrI8MtpcJ0WbeiXLw+cPUFDjaA1aBJt051fb8XUSuYiJ0qvBitRoRie3lopKtBmlz6I4MfHD4dzfw7yHYOe/1SbilXth28vqJXseTL8nWI5KKkaIY5MMDSGEGOACgQBut5umpiZ8PvUsI2n4LQasQAAaS8BRrd42WNQvz/ruCdrJdxUhhBBCCAEdZ3mU1DnDGpqfaJZHZpuyVulxUaHAx4lkefgDCoW1jlBz7pbgxeEqOx5/oMP72Ex6tcdFcrTapDtVzbhIjjbJ70XRMxQFCta2lqNSgq/NuGFqxsbkm6Uc1SAkJaeEEGKQUhQFj8eDx+PB7Xbj8XhC6zQaDdHR0VgsFmn4LQYer0tNZfYFz5CzJUN0Gmi677Uu31WEEEIIIURXHZ3l0RLwaJvl0dVeHhlH9e9IjzOTFhtFdbObvIpm8oKNug9X2/H4Og5cmA26sObcOcFSUemxURK4EJFTX6iWo9r+D3DVq8sMlmA5qrulHNUgIgENIYQYJBRFwefz4Xa7QwGMo3ftOp0Os9mMzWaTQIYYeBQFnLXQUKye2aPVq2f2RHX+BehkyXcVIYQQQgjRXdpmeRQHy1mFyludQJbH0Ux6LaNCJaJsjAkGLjLizGgHaBNzMQB4HLDrLTVro3JP6/IRc2H63TD6fClHNcD16x4avRxjEUKIfsfn84UyMNxud6gnRguNRoPJZApd9Po+ubsX4tQF/NBQBM469bbRppaY0vVMg/uj32tCCCGEEEKcrBPq5VHnDOvnUVrvorTBSbzFSE6KjZzkaHKCQYyMeHOv9OUQolsZLTDlNjjzVjiyXg1s7P8I8teol7ihcNZdcOYt0h9xkOtTGRp+v5+8vDwsFgtJSUmS7iaEEEGBQACPx4PX68Xj8eD3+9ttYzAYMBqNGAwGDAaD7EPFwOdxqv0yAsGyatYksCRCD7z2W0q5VVVV4ff7ycnJkWwnIYQQQgghhOhJ9UVq0/Dtr7aexGawwIRr1XJUKWMjOj3RvfplySmA5uZmiouLJUtDCDGoKYqC3+/H5/Ph9Xo7DGDodDoMBgN6vR6dTicBDDG4uJvAWQ8oaokpy5Bua/x9LBaLhbS0NIxGY48/lhBCCCGEEEIIwOsMlqN6ESp2tS4fPgem3wNjLpByVANAvw1ogJqp4fV6e3NaQggRUYFAgOrqaoqLiykqKqK0tLRdECMuLo7MzEyysrLIyMiQ+v1icHLUwee/gSPr1Nsj5sHCX0NUbI8/tE6nQ6/XS/BQCCGEEEIIISJBUaBwI2x+HvZ9BErwuEnsUJj2XZh8C1gSIjtHcdL6dUBDCCEGg7q6Og4fPszhw4fJz8/H4XCErbfZbGRnZzNixAiys7OJje35A7ZC9Gn5a+Gdu6CpDHQmOP9xmHpnj5SYEqIzit+Pp7AQd14e3qJitBYzUePHYz7jjEhPTQghhBBCiMGjoRi2tpSjqlWX6c1qOarpd0PKuIhOT5w4CWgIIUQfY7fbyc/PJz8/n8OHD1NXVxe23mg0Mnz4cLKzs8nOzpZeQkK08Pvgyz/Cmj8CCiSOhqtfgdTxkZ6ZGMAURcFXWoorLw/PwYO48/LUvw8dRnG7220fNX488TfdRMyFF6A19Xz5MyGE6A3+5ma8paX4ysvxlpWDBvSJSUSNH4chOTnS0xNCCCHUclS7/6NmbZQfVY5q2mIYcyHo9JGbn+gyCWgIIUSEeTweCgsLQ1kY5eXlYeu1Wi2ZmZmhAEZGRgY6ndR8FCJMQ4malXFkvXp78s1wwR/BaI3svMSAoSgK/upq3MGghTsvD/eBPNwHDxKw2zu8jyYqCtOoURiHDsVvb8axYSNKsFyqLj6euKuvJv766zBkZPTmUxFCiBOieDx4KyrwlpXhKyvDW1aOt6wMb1kpvuDfgebmTu+vT0/DPGEi5gkTME+aSNTYsWilJKoQQohIURQo3ARbXoC9H7QpR5UFZ90JU24Hc3xEpyiOTQIaQgjRy/x+P2VlZaEARlFRUbs+GMnJyaEAxrBhwzDJWbxCdG7/cnj/e+CsA2M0XPwnmHBNpGcl+jF/Q0Nr4OJAXiiA4a+v7/gOBgOm4cMx5eRgGp2jXufkYMjIQNMmAO2rraX+rbepW7YMX1mZulCrxbZgPgk33YRlxgzJuBNC9ColEMBfU4O3vBxvaXiQwltejresFH91jXrw5zi0sbEY0tIwpKSARoO3pAT3wYPt76vXEzVmDOaJE4iaMAHzxIkYhw+X/Z8QQoje11AC2/4O218BR426LDodbnkXkk+L7NxEpySgIYQQPUxRFGpqasL6YLiPKkMSExPDyJEjQ70wbDZbhGYrRD/ic8PKR9SUYYC0SXD132HIyIhOS/QfAYcD96FDYUEL98GD+CoqOr6DRoNx6NCwoIUpJwfjsGFoDIYuP67i89G8ejW1r7+OY+Om0HLjyJHE33gDsZddjs4m2UVCiFMXVgqqtAxveXiWha+8PJQ5diwaoxFDWhr6tDQ1aJGWqv6dmoYhPQ1Daipaa/v9lr+5Gdfu3Th37MS5cyfOHTvwV1e3204bG4v5jDMwT5yoBjrOOAN9vJwdK4QQopd4XbDnHfjySag9DOYEuOUdSJ8c6ZmJDkhAQwghekBTU1NYAKOxsTFsfVRUVKiJd3Z2NgkJCXJWmhAnovogvH0HlO9Ub8+8DxY+CnpjZOcl+qSAx4MnP781cBHMvvAWFXV6H316GqacHKLaBi6ys7u9TIr74EHq3lhKw3vvEXA4ANBarcRefjnxN92IKTu7Wx9PCDFwdFoKqrwMX2nZcUtBhWg06JOTMaSmok9Pw5CWjiE1FUN6GvpgwEIXH98t31Vb+g45d+wIBTlce/ageDzttjUOG0bURDWDwzxhIlFjRqMxyue8EEKIHuSohX9dCaVfq9n/N74Jw3MjPStxFAloCCFEN3C73RQUFISCGFVVVWHrdTodQ4cODQUw0tLS0Gq1EZqtEP3cjmXw0Y/Ba1fPnLnieRh9XqRnJfoAxefDU1iE+2BLxoUauPAUFMBRpf1a6BITMeWMas24GDUK06hR6KKje3Xu/uZmGt57n7rXX8eTnx9abp01k4Q778SWKz+khBhMeqQUVNsgRTDLwpCWhj45+YSyzLqb4vHg+vYAzp07cO7YgWvHTjxHjrTbTmMyETV2bKgXh3nCBPTp6X3mpCBFUXDv30/TypXYN29Bn5SEbXYu1tmzMaSmRnp6QgghusrVCEtvgCPrQB8F174Go8+N9KxEGxLQEEKIk+Dz+SgpKQkFMIqLizl6N5mWlhYKYAwdOhRDBH8oCjEguJth+YOwY6l6e/gcuPJFiEmP7LxEr2s5w9eV16ZUVN5BPIcOdXiWL4A2JiYYtBiFaVRO6G99QkIvz/7YFEXBsXEjta+/QfMXX0AgAEDKQ78g4bbbIjw7IUR3iXQpqL7OV1eHa9eu1lJVO3cSaGhot50uMTGYwTFBLVU1/oxeLdmnKArufftoXPEJjZ+swHuksMPtTDmjsObOxjp7NpapU6QpuhBC9HVeJ7x1OxxYAVo9XPk3GH9lpGclgiSgIYQQXaAoChUVFeTn53P48GEKCgrwHvUjMyEhIRTAGD58OBaLJUKzFWIAKtsBb38Hag6CRgvzHoI5PwGt7vj3Ff2Woij4q6tDQYuWAIYn72CoPNPRNGZzKMsilHUxOkc9A7mPnMXbVZ7iEqqff46Gt/8DwJC7vkvSj3/c756HEINNj5WCasms6IFSUH2doih4CgrUDI6dO3Hu2Inr22/B5wvfUKPBNGoU5kkT1YbjEyZiGjUSja77vi+Eghgfr6Dxk0/wFrYGMTQmE7az52CbOxdvWTn2detw7toVCk63bGM56yyss3OxzZ6NceTIQfF/KIQQ/Y7fC+/eA7vfBjRwyV9gipxg1BdIQEMIITpRX18f1gfDbreHrbdYLKEAxogRI4iXxoVCdD9FgS0vwqe/Ar8HYjLgqpdg2KxIz0x0M399fai3RdtyUf76+o7vYDBgGjEiLGhhysnBkJGBZgCV9FMUhZq/vUTV//0fALFXXknab3+DRq+P8MyEGJy6vRRUamp4kKIPlYLq6wIuF669e9Usjh07cO7cga+0rN12WouFqDPOCC9VlZR0Qo+lKAquvXtpWvFJx0GMuXOJOf88bHPntsuI8dfXY9+4keZ167CvW4+voiJsvT4tTS1NlTsb68wZ6GJjT2huQgghelDAD//9CWx/Rb197u9h1g8iOychAQ0hhGjhcDjC+mDU1taGrTcYDAwbNiwUxEhOTpY+GEL0JEctvH8ffPtf9faYC+GyZ8DSt0oEiRMTsNtxHzoUFrRw5+Xhq6zs+A5aLcahQ9sFLoxDhw6qA331//kPZb9+BAIBbPPmkfGn/0NrNkd6WkIMOFIKqn/zVlaGMjicO3bg3L0bpYOMPkN6utpwfMJEzBMnEjX29A7LQCmKQu2r/6DujTfwFhWFlmuiorCdfXanQYzOKIqC5+BBmtetx75uHY6tW8NLJWq1mCdMwDp7NrbZuUSdcUa3ZpcIIYQ4CYoCnz0K6/+i3j77pzD/lyDZdREjAQ0hxKDl9XopKioKBTBKS0vD1ms0GjIyMkIBjMzMTPRyRqwQvePIBvjPd6GxBHRG9UyYaYvlS2M/EvB48OTn4z7Qts9FHt7i4k7vY0hPDwtamEaNwpidLbXGg5pWraLkRz9Gcbsxn3kmWc89K2fyCnECjlsKqrycQFPT8QfqpBSUPi0VQ1r6oCoF1dcpfj/ug4dw7vgG586duHbsxH3wYPsMGr2eqDFj1H4cEydgnjgRbXQ0VX/+C/VvvQUEgxgtmRhnn90tAamA04lj2zbs69bRvG49nkOHwtZrY2OxzpqJbfZsrLm50lxcCCEiae3/wee/Uf+edjec/weQk1wjQgIaQohBIxAIUFZWFiohVVhYiO+ourtJSUmhAMawYcOIkoNoQvSugB/W/i+sfgKUACSMhGtegbSJkZ6Z6ITi8+EpLAoLWrjz8vAcOQJ+f4f30SUlEhXMuDCOGkVU8Fpns/Xy7Psfx/btFN37PQKNjZhycsh66W8YUlIiPS0hIu7oUlC+8rJgSSgpBSXC+Zubce3ejfObHaGG4/7q6s7voNGQ/POfEX/ttWh7uEeet6wsVJrKvnEjgcbGsPVhzcXPmorWZOrR+QghhDjKlr/B8gfVvyfeAJc+DTo58bW3SUBDCDFgKYpCbW1tWB8Ml8sVtk10dHRYHwzZ3wgRQY1l8M5dULBWvT3xBrjwSTBFR3ZeAlAPFnpLy3DnHQgrFeU5fDi8XEYb2pgYNduibYPunBz00nPolLi+PUDRXXfhq6zEkJ5O1ssvYRoxItLTEqJHSSko0VMURcFbUopr545QqSrX3r0oHg+m0aNJuv8HRC9a1Pvz8vlw7tqlBjeO11x8zhyM2dmSFSSEEL1hx5vw3r2g+OG0i+Hqv4NeAsy9SQIaQogBpbm5mfz8/FAQo6GhIWy9yWRi+PDhoSBGYmKifPEXoi848Cm8dw84asBghYv+FybdEOlZDUqKouCrqmrNtgg26vbkHSTQQR1yAI3FgmnkyLCghSknB31ykuxje4inuISiO+/Ec+QIuoQEsl58EfP4cZGelhAnpddKQaWloktIkP2SOC7F4yHgcqHrQ8cipLm4EEL0IfuXw1u3g98N2fPgutfBJNnmvUUCGkKIfs3v94eCF4cPH6biqC/2Wq2WoUOHMmLECLKzs0lPT0cnjfWE6Dt8HrUO6can1dupZ8DVr0LiqIhOa7AIeDy4du3CfeCAGrwI9rvwHxUMbqExGDBmZ4cHLkbnYEhPRyP1Y3udr6aGorsW49q7F63FQuazz2CdMSPS0xIiTE+VgmobpDAEsy2kFJQYLKS5uBBC9AGHV8PSG8Frh8xpcNO/wSyZ6L1BAhpCiH7J6/WydetWNm3aRONRtWVTU1NDGRhDhw7FaDRGaJZCiGOqPQxvfwdKv1ZvT78HzvmtpOv2IEVR8Bw6hH39epo3bMCxZSuK09l+Q60W47BhR2VcjMI4dKgcLOxj/M3NFN/3AxybNqExGEj/n/8h5rxzIz0tMcgoPh+ObdvwFBw5pVJQrUEKKQUlxIk4oebis2dL7yUhhOguxdvgX1eBqx5SxsMt74ItOdKzGvAkoCGE6FcCgQA7d+5k1apVoUCG1WplzJgxoT4YVvmxK0Tft+tt+PAB8DSpZ7Fc9gycdlGkZzUg+WpqsG/YiH3DBuzr1+OrrAxbr0tMxDx+fChoYcrJwZidLY1G+5GA203pT39G06efglZL6qOPEn/dtZGelhgEvJWV1L/9NvX/fgtfeXnnG0opKCF6lTQXF0KIXlSxB167AporIGEk3PoexA2N9KwGNAloCCH6BUVRyMvL47PPPqMyeDAuJiaGuXPnMnHiRPR6fYRnKIToEo8dPv4ZfP0v9fbQWXDV3yA2M7LzGkACbjfOr74KZWG49+4LW68xmbBMnYo1Nxdr7ixMo0fLQcQBQPH7Kf/Nb6n/978BSHrghwy5+275vxXdTlEUHJu3ULdsGU2ffQY+HwC6uDjMkyZJKSgh+piuNhe3zVEDHNJcXAghTkLNIfjn5dBQCDGZalAjMSfSsxqwJKAhhOjziouLWblyJUeOHAEgKiqK2bNnM336dAzy41iI/qN8N7x9B1QfADQw92dw9s9AJwHJU6EoCu4DeaEMDMe2bSguV9g2ptNOw5o7C1tuLuYpU+RMzAFKURSq/vpXap57HoD4W28h5Re/kP4molv4GxtpeO996pYtw3P4cGi5efJk4m+4nujzzpN9ixD9gDQXF0KIHtJQAq9drv7etSSq5afSJkR6VgNSjwQ0nnvuOZ577jkKCgoAGDduHI888ggXXHBBt09MCDFw1dTU8Pnnn7N3714AdDod06dPZ/bs2VgslgjPTgjRZYoC216GFQ+D3w3RaXDlizDi7EjPrN/yVVVh37gR+/r12DdsxFdVFbZen5QUysCwzpyJPjExQjMVkVD7z9eoePxxAGIuuYT0xx+Ts+PFSXPu2UPd0qU0/nd5qOeOxmIh9tJLiL/hBqLGjInwDIUQJ0uaiwshRDezV8O/roSyHWCKVRuFD50R6VkNOD0S0Pjwww/R6XSMGjUKgH/84x88+eSTfP3114wbN65bJyaEGHiamppYs2YN27dvp2XXM2nSJObNm0dcXFxkJyeEODHOOvjgftj3gXo751y4/DmwygH2ExFwuXBs2x7KwnB/+23Yek1UFJazzgplYRhHjZJyEYNcw4cfUvrQw+DzYT17Dpl//jNaORlAdFHA5aLx4xXULV2Ka+fO0HJTTg5xN1xP7KWXorPZIjhDIURP6Gpz8ehFi4hetEiysoQQoiOuBnjjeijcAAYLXPcvGLUw0rMaUHqt5FRCQgJPPvkkd955Z4fr3W43brc7bGJZWVkS0BBiEHG73WzYsIENGzbg9XoByMnJYdGiRaSkpER4dkKIE1a0Bd6+U60jqjXAOb+B6feClL85LiUQwH3ggJqBsX6DWkaq7RmTQNTYsaEsDPOZZ6I1GiM0W9FXNX/5JcX3/xDF5cI8aRJZzz+HTk4MEMfgKSigbtmb1L/7LoGGBnWhwUDMuecSf8P1mKdMkWCpEIPIsZqL6+LiSLj9NuJvvlkCnEIIcTSPA/59Kxxcqf4WvvplGHtZpGc1YPR4QMPv9/PWW29x22238fXXXzN27NgOt1uyZAm/+c1v2i2XgIYQA5/P52P79u2sWbMGh8MBQEZGBosWLWLEiBERnp0Q4oQFArD+T7DqMVD8ED8Crv47ZJwZ6Zn1ad6KSuwbN2BfvwH7hg34a2rC1utTU7HOmtVaRiohIUIzFf2J4+uvKbrnXgINDRhHjWToSy9hSE2N9LREH6L4fDR98QX1S5dh37AhtNyQnk7cddcRd9WVUrZOCBFqLt68eg0NH3yAr6wMULM2Em67lYSbb0Ynx26EEKKVzwPvLoY974JGC5c+BZNvjvSsBoQeC2js2rWLmTNn4nK5sNlsvPHGG1x44YWdbi8ZGkIMPoFAgL179/L5559TV1cHqNlcCxcuZOzYsXIGoBD9UVOF+qXt8Gr19vir4eI/QZR8lh+ttazDeuwbNuDOywtbr7FYsAbLSFlzczFmZ8t+UZwUd14ehd+9C19FBfr0NIa+9DKmbDlhYLDzVlRS//Zb1P/7rdamwBoN1rPnEH/DDdjmzJFa+UKIDil+P43Ll1P93PN4Dh8GQBsdTcItt5Bw263SSFwIIVoE/PDRA/DVP9Xb5/8BZtwb0SkNBD0W0PB4PBQWFlJfX89//vMfXnrpJdasWdNphsbJTkwI0T8dPnyYlStXUhY8s8dqtTJv3jzOPPNMdPLjWYj+6eBn8O49YK9Sa4Ve+CRMugnkIDyglpFy7dsX7IOxAef27SjB8noAaDREjR8fysKwTJqERspIiW7iLSmh8M7v4ikoQBcfT9aLL2I+Y3ykpyV6maIoODZvpu6NpTR9/jn4/QDo4uOJu/pq4q67FmNmZoRnKYToLxS/n6ZPPqH6uedw5x0EQGu1En/LzSTcdhv6+PgIz1AIIfoARYFPfwUbn1Zvz3sY5v5Mfiefgl7robFo0SJGjhzJCy+80K0TE0L0L2VlZXz22WccCjaYMxqN5ObmMmPGDEzSVE6I/snvhVW/g/V/UW8nj4NrXoGkMZGdVx/gLS8PlZCyb9iAP5iN1kKfnoYtNxfrrFlYZsyQH/6iR/lqaylafDeu3bvRWixkPv0U1lmzIj0t0Qv8DQ00vPcedcvexJOfH1punjKF+OuvJ/q8c6UPjxDipCmBAE2frqT62WdxHzgAgNZiIf6mm0i443YpkymEEIoCX/4PfPF79faM78N5j0lQ4yT1WkBj4cKFZGVl8eqrr3brxIQQ/UNdXR1ffPEFO3fuBECr1TJ16lTOPvtsbNJEToj+q65Abfxdsk29fdZ34dzfg8Ec0WlFSsBux751aygLwxMM3rbQWixYpk9Xm3nPmoVxxHApIyV6lb/ZTvEP7sOxcRMag4H0J/9IzPnnR3paooc4d++hbukbNP53OYrLBaj7oZjLLiX++huIGjM6wjMUQgwkSiBA0+efU/3sc7j37QPUEprxN1zPkDvukH48Qgix+QX4+Gfq35Nvhkv+ClqpUnKieiSg8fDDD3PBBReQlZVFU1MTy5Yt4w9/+AMrVqzgnHPO6daJCSH6Nrvdztq1a9m6dSv+YFmD8ePHs2DBAhLkTB0h+rc978IH94O7EaJi4dKnYeylkZ5Vr1L8flx792Ffr/bBcHz9NbQtI6XVEnXG+FAWhnniRDQGQ+QmLAQQ8Hgo/enPaPrkE9BoSH30EeKvvz7S0xLdJOB00rj8Y+qWLcO1a1douWn0aOJvvIGYiy9BZ7NGcIZCiIFOURSav/iC6meexbVnDwCaqCjir7uOId+9E31SUoRnKIQQEfTNUnj/e6AEYOxlcOVLoJdM2RPRIwGNO++8k88//5yysjJiY2OZMGECP//5z7sczDiRiQkh+iaPx8OmTZtYv349brcbgBEjRrBo0SIyMjIiPDshxCnxOmHFQ7D9FfV25jS4+mWIGxrZefUSb2kp9g0baF6/HseGjfgbGsLWGzIy1AyM3FysM6ZLY0zRJyl+P+W/+x31y94EIPH+H5B4772SMdSPufPzqV/2JvXvvUcguF/SGAxEn38+8Tdcj3nyZPn/FUL0KkVRaF6zRg1sBAOsGpOJuGuvZch3v4shJTnCMxRCiAjZ9yG8/R3we2DUIrj2NTBaIj2rfqPXSk6dKAloCNE/+f1+vvnmG7744guam5sBSElJ4ZxzzmHkyJHyQ1qI/q5yH7x1B1TtAzQw58cw7yHQDdysA3+zHceWLaEsjLb15wG0NhuWGdOxzpqFLTcXw9Chsq8T/YKiKFQ/9TTVzz4LQPxNN5Hyy4fRaLURnpnoKsXno2nVKuqWLsWxcVNouSEzk7jrriXuqqukdr0QIuIURcG+bh3VTz+Dc8cOADRGI3FXX82QxXdhSE2N8AyFECICDq2CZTeB1wFDZ8KNb6qVD8RxSUBDCNEtFEVh//79fP7551RXVwMQFxfHggULGD9+PFo5OCJE/6Yo8NU/4ONfgM8J1mS48kUYOT/SM+t2it+Pa/fuUBaG85sd4PO1bqDTYT7jjFAWhnnCGWj0+shNWIhTVPvav6h47DEAYi66iPQnHkcjDaL7NG9FBfX/fov6t97CV1mpLtRosM2dS/yNN2CdPVsCU0KIPkdRFBwbN1L1zLM4t28H1Eyy2KuuJHHxYgzp6RGeoRBC9LLCzfDGNeBqgNQJcPM7YJOyfMcjAQ0hxCkrLCxk5cqVFBUVAWA2mzn77LM566yz0MtBPiH6P1cDfPhDtWcGwMiFcMXzYBs4ZQI8xSVqBsb69dg3bw6Va2lhGDoUa+4srLNmYZ0+HZ18NxEDTMNH/6X0F78Anw/r7Nlk/vUvaC2S9t6XKIqCY9Mm6t5YStOqVRDsTaYbMoS4q64i7tprMWZKWU8hRN+nKAqOzVuofuYZHFu3qgsNBuIuv5whdy/GmJkZ2QkKIURvKt8Fr10B9ioYkgO3vgexsh88FgloCCFOWmVlJZ9//jnffvstAHq9npkzZ5Kbm0tUVFSEZyeE6BbF2+HtO6D+CGj1sPARmPkD6Odn/vqbmnBs3hzKwvAeKQxbr42OxjpjRjALYxbGrKwIzVSI3tO8dh3F99+P4nQSNXECWc8/jz4+PtLTGvT8DQ3Uv/su9cvexFNQEFpunjqF+BtuIOaccySjRgjRb9m3bKH62edwbAqWzdPrib3sUhLvvhvj0MHRn00IIag+CP+8DBqLITYLbn0fhoyM9Kz6LAloCCFOWGNjI1988QXffPMNiqKg0WiYPHky8+bNk/erEANFIAAbn4LPfwsBn9rw++pXIHNqpGd2UhSfD+euXdjXb8C+YYNavzl4djOglpGaNAnrrJnYcnOJGj9eykiJQcn5zTcU3X0P/oYGjCNHMvSlv2FIS4v0tAYl565d1C1dRuPy5SguFwBaq5XYyy4j7vrriBo9OsIzFEKI7uPYvp3qZ57FvmGDukCnI/aSSxhy92JMI0ZEdnJCCNEb6ovgtcuh5qBa4vmWdyF1fKRn1SdJQEMI0WVOp5P169ezadMmfMF68qeddhoLFy4kKUlq/AkxYDRXwbt3w6HP1dtjL4dL/gLmuEjO6oR5CgtDjbztmzYTaGoKW28cNkzNwJidi2XaNHQ2W4RmKkTf4j54kMLv3oWvvBx9WhpDX34JU3Z2pKc1KAScThqXL6du6TJcu3eHlptOO434668n9pKL0VqtEZyhEEL0LMfXX1P93HPYv1yrLtBqibnoIhLvvUc+i4QQA19zJbx2JVTsUhuE3/QfyDor0rPqcySgIYQ4Lq/Xy9atW1m7di1OpxOArKwszjnnHIZKGrAQA8vh1fDOYmiuAH0UXPD/4MzbQKOJ9MyOy9/YiH3TplAWhjfY16eFNjYW68yZWGfNxDorV2rNC3EM3tJSCu/8Lp78fHRxcWS9+ALmCRMiPa0By304n7plS2l4730CjY2A2ig3+oLzib/hBsyTJqHpB/thIYToLs6dO6l+9jmaV69WF2g0xFxwgRrYyMmJ6NyEEKJHOevhjWuhaDMYrHDjmzBiTqRn1adIQEMI0alAIMCuXbtYtWoVDcEGuYmJiSxatIgxY8bID2shBhK/D1Y/Dmv/D1Ag6XS4+u+QMjbSM+uU4vXi3LlTDWCsX49z1y61VFYLvR7LpElYZ+dinTWLqHHj0Oh0kZuwEP2Mr66OosV349q1C43FQuZTf8WWmxvpafUaRVEINDTgKSlBcTiIGj8erdncfeN7vTR9voq6Zctaa8cDhsxM4q+/jtgrr0SfkNBtjyeE6LqAx4P72wME7HbMZ4yXzKgIcu7eQ/Vzz9H8eTBzWKMh+rzzSLz3XqLGSOk9IcQA5bHDmzdDxV74zgpIkNJ7bUlAQwjRjqIoHDx4kM8++4yKigoAoqOjmT9/PhMnTkQnBwSFGFjqi+A/d6pngABMuR3OewKMlohO62iKouA9coTm9euxr9+AY/NmAnZ72DbG7Gy1jNSsmVjOmobOJgcghDgV/mY7Jff/APuGjWAwkPHH/0fMBRdEelrdxt/UhLekRL0UF+MpKcFbXBJaFmhuDm2rMRiwnn02cVddiW3OHDQGw0k9pre8nPp/v0X9W2/hq6pSF2q12ObNI/6G67Hm5qLRarvj6QnRbyiKop6U4PejBAIQCKjXLbf9fhR/AAKt18fdRgmg+IPbdXQd2iZ8XH9DI7X/+Ae+4O8gfVISyT99kJhLLpETuiLItW8f1c8+R9PKlaFl0eecQ+L37iXq9NMjODMhhOghPjc0lkowowMS0BBChCkpKWHlypUUFBQAYDKZmD17NtOnT8doNEZ2ckKI7rfvQ3j/++BqAFOM2itj/JWRnlWIv76+tYzU+vV4S0vD1uvi4tQSUrlqFoY0Lxai+wU8Hkp//nOaPl4BGg0pv/4VCTfeGOlpdUnAbm8XpPCWBAMXJaUEghmox6JLTESj1eKrrAxbFnvZpcRdeSWmkSOPO4YSCGDfuJH6ZctoWvUF+P2hceKuvor4a6/FkJ5+8k9U9Lh2B86PPvgePFB+7G1aDpx3dJBdCTuo3vF1ACWgHohvuQ7bJjRG+DZh1x09Ttu5KoEO7xu2raJ08jxbtu0g0HD09VFjhGVY9hG62FgwGPBXVwNgnjyZlF/9EvO4cRGe2eDm+vYA1c8/R9OKTyB4mMq2cCGJ996Lebz83wghxGAgAQ0x6HkDCt/andT7/Awx6Ek06kkw6NENsrNvampqWLVqFXv27AFAp9Mxbdo05syZg8XSt87SFkJ0A68LPv0lbH1JvZ0xRS0xFT88otNSPB6cO3aoWRgbNuLatSv0YxUAgwHLmWdinTULa24uUWNPlzOZhegFit9P+e9/T/3SZQAk3ncfid//XsTPVg44nXhLS1uzK44KXvjr6o47hi4+HkNGBobMTAwZ6RgyMjBmZqrL0tPRms0oioL7QB4N771Hw/vv46+tDd3fPGkSsVddScwFF6Cz2cLG9tfXU//ue9QvW4bnyJHQcstZZxF/w/VEL1qEphtOGGl3kLiTA+cdb3OMs947O7h+1EH8Dg+gd3qAPrhN8MD5MQ/iBzo+uH5iB84D7Q/IHy8T4KjrvniwfVDS6dTP/KOvO1oWdq0BrQ50WjSdXWva3EevxzJ1KvE33gAaDbWv/oPq559HcThAoyHummtI+tED6OPjI/0v0q8F7HacO3fi2P4Vzq+/xldZQcDlRhsVhcZiRmu2oDWb0ZrN4bct6jJ/UxP2detxfvNNaEzzlCkk3H4blsmT1fuZzfI9UQghBiAJaIhBpSV4sbPJyY4mBzuanOyzO3EHwl/eGiDeoCPRYCDRqA8FOhINeoYEr9suj9Xr0PbTAEhzczNr1qxh+/btBII/1iZMmMCCBQuIi4uL7OSEED2j6gC8fQdU7FZv5/4QFvwadCdXPuVUKIqCJz8/lIFh37JFPWDQhnHUSGy5uVhzc7FMnYpWgqxCRISiKFQ//QzVzzwDQNw115D8kx+jO873hXZnc5/EwXZfdU37DIviEvw1NcedtzY2FmNGhhqgODpwkZFxwrXxFa+X5i+/pP4/79C8Zk0o20JjNmOdPh30evz19XiLitSsjpafUTod+oQEdIlD1CDG0We/Bzo76z384HuHB9xF5B3voLpG0/FynVY92K7VHuOAvHqNVtP5AfnQtTpey7hHX4eNodMdf5uwbdtcH+tx2gYajrVN8N8kbNy2czr63y2CvBUVVD75PzR+9JH63x0TQ9L99xN//XVo9PqIzq2/8FVXq8GLr7bj2P4Vrn37emX/pYmK6jgw0kGgRGMO3rZYQoGT1mVtblvU+0hvNiGEiAwJaIgB6+jgxc4mJ3s7CF4AxOi1JBsN1Hp91HpP/EuVXgMJhtZAR6LRwBCDjlSTkQk2MxOizcQa+tYXXbfbzcaNG9mwYQMejweAUaNGsWjRIlJTUyM8OyFEj1AU+OZ1WP5T8DrAkghXvgCjFvXqNHx1dTg2bgxlYfjKysLW6xIS1AyMWbOw5s7CkJLSq/MTQhxb7euvU/H7x0BR0JhMakDgWGe39zCtzRYMUmRgyEhvza4IXnTR0T322L6qKho++ID6/7yD5/DhHnucUxY8uHzMA+Za7TEOlLdu0+kB+ZZtj/U4xzpgfvQYnR2QD22j6fSAfNjjdHjAPHit0YYfgO8oiNClbTQRz1YSvcOxbRvlv38M9/79AJhGjyblV7/EOm1ahGfWt6gnrBSEgheOr7bjPVLYbjt9WhqWM8/EPOVMTCNGoDGZUFwuAk4nAYeTgNOB4nS2uR1c5nC0ue1EcTrwNzbhr6tDCf627Q0aozEYGGkNkoQCJRZr6zJLJ4GRTgIlWrP5pPs0CSHEYCABDTEgeAMKBxwudjQ6uhS8mGCzMCHawoRoMxOjLQw3G0M/QnwBhTqfj2qPeqnx+qj2tvk7bLmXRl/XUtCzzSYmxViYFG1mUrSF8dEWLLreP9PI7/ezfft21qxZgz3YTDc9PZ1zzjmHESOk0ZAQA5a7CT76Eex6S709Yi5c+SJE93wAM+Dx4Pzqa+wb1CwM1969YWWkNEYj5ilnqlkYs2ZhOu20iJ+JKYQ4tuYvv6Tyf/8P97ffnvpgXTjYrouLxZCRGZZh0RK40MbERPxgsuvgQYq+exe+8nJ1gU6H+YwzsMyYgXH4cDRHH/jvylnuoWtt52ewt9mm87P6tRH/9xFiIFH8fur//W+q/vwX/ME+PDEXXkDyT386aHt5KR4Prn37QsEL51dfh5XmA0CjwZSTg3nKmVjOnIJlypk90jvIU1hI1fPP0/j+B6GgetSECcRecTmmESNCgZKAIxgsaRsoaRc4aQ2aBJxONZDidIaXQ+0pBkNYgOOEMkzalObStGScWC3ok5LkO7YQYkCQgIbod0LBi2DgYkej45jBizNsFia2CV4MMxu7tTyUOxCg9uhAh0cNghxxevimyUGRq/1ZIlpgjDUqGOSwMCnGwhk2c4+VrlIUhT179rBq1Spqg18u4+PjWbhwIePGjZMfukIMZKVfw9vfgdrDoNHBgl9C7o/Ug2Q9QFEUPIcOYV+/nuYNG3Bs2YridIZtYxo9OtQHwzJ1ClqzuUfmIoToOS1n4Co+b/uD7dpOyusMwIPtTau+oPSnPyVgt6NPTibhttuIvfIKqa8vxADnq6uj6q9/pf7Nf0MggMZsJvHuxSTccQdakynS0+sxSiCAr7oa97cH1ODF9q9w7tyJ4nKFbacxGjFPmIB5yhQsZ07GPGmS2mi9l3iKi6l54UXq33sPvF4ALFOnknjf97FMn37Snz2KoqC43WqQw+5AcTq6kFHSNjBy1G2HI2xZT/bs0SUlEr1oETHnnYdl6lQplyaE6LckoCH6JG9Aocjl4bDTTYHTTb7DHfq7yOXB18GrsSV40RK46Ingxcmq8fiCPTscfNPk4JtGBxUeX7vthkUZuTl9CNelJpBs6r4U0/z8fFauXElpaSkAVquVuXPnMmXKFHRS91OIgUtRYNNzsPIRCHghNguuehmGTu/2h/LV1GDfsDGUheGrrAxbr0tMxDprJrbcXCwzZ2JITu72OQghRG9SFIWa55+n6q9PgaJgmTqVjL/+BX1CQqSnJoToRa59+yj//WM4t28HwJCVRcpDv8A2dy6Kzwc+H0qbS/htP4rPqy7z+1G8PvW236+u9/rA7wv9rfjbjOEN3qfl/r7gfXxeCP0dvL83OEbL9qH7tt++3f3bztfvB1/737EAuthYNXgx5UzMZ55J1LhxaI3G3vyv6JC3pITql16i4e3/oAQDG+YpU0j83r1YZ83qU0F1RVFQPJ7W7JFOAyVHZZO0BEXCAimtGSUt27QtA6mLjyd60UKizz0P64zpUuJKCNGvSEBDRIwnEKDQ5SHf4Sbf6Sbf6aHA6eaww02x24P/GK+4aJ02rGTUhGDZqL4QvOiqcreXbxrVAMeOJgdbG+w0+9WzMfQaOC8xllvTE5kTbzvp51VeXs5nn33GwYMHATAYDOTm5jJz5kxMA/isISEEYK+B978HB1aot0+7GC57Gszdc8ZwwO3G+dVXoSwM9959Yes1JhOWqVPVLIzZuZhGj+5TPxiFEOJUBOx2Sh96mKZPPwUg/sYbSXnoF3JASIhBSlEUGj/6L5VPPtnupI4BSavFkJmJZfJktYTUlCkYR4zo0+WMvGVl1Lz0MvVvvRXqs2GeOJHE+76PdfbsAf89VfF4sG/eTOMnn9D82ef46+tD67QxMUQvWED0+edhmzULTR8IRAkhxLFIQEP0KJdfDVq0BCrynW4KnB7ynW6KXR6OlUxp1moZYTYywmJiuNlEttnEcLOREWYTqSZDvwpedIXd7+fDynpeK61he6MjtHxoMGvj+hPI2qivr2fVqlXs3LkTAK1Wy5QpU5g7dy42m61H5i+E6EPy18I7d0FTGehMcP7jMPVOOIX9pqIouA/khTIwHNu2tSstYDrtNKy5s7Dl5mI+80y0UVGn+kyEEKLP8RQVUfz9+3AfOAAGA6mP/Jr4a66J9LSEEH1AwG6n+vkXqH311VA2QBidDo1er5bnMxjUv0O39Wj0BrXnjl6v3tbpQ9ug16nrO7ytA32b+xv06u2W+xv0wcc2tL9tCD5+y/31wcfXtz5262Oq17rY2H5brshbUUnNyy9R/+a/UdxuQO2xkfi9e7HNnTvgAxsAis+HY+tWGj/9lKaVn+Gvrg6t00ZHh4Ib1tzcPpFlI4QQR5OAhjhlLn+AApebAocnmGnReilxeTnWC8eiCwYtzKbWi0W9TjHqB8WXiY7sbXbyr9Ia3q6oDTUdb8nauDltCHMTojsM6DgcDtauXcuWLVvwB9NJx40bx4IFCxgyZEivPgchRAT4ffDlH2HNHwEFEkfD1a9A6viTGs5XVYV940bs69dj37ARX1VV2Hp9UhLW3FysubOwzpyJPjGxG56EEEL0XfaNGyl54Ef4GxrQJSWS+Ze/YjlzcqSnJYToYwJOJwGXq30wYJD+vu2LfFVV1Lz8d+qWLQudpBM1diyJ3/8etgULBs3/leL34/zqKxo/+ZSmTz4J+76vtdmwLZhPzPnnq8ENqfIghOgjJKAhusThD3DE2b40VIHTTan72EELq04bzK4wkW1pzbLINptIGsRBi65w+APBrI1qtrXJ2siKMnJz2hCuT0sgxWTA6/WyadMm1q1bhzt4lsnw4cM555xzyMjIiNT0hRC9qaFEzco4sl69PflmuOCPYLR2eYiAy4Vj2/ZQFob722/D1muiorCcdZYawJg1C1NOjuzDhRCDgqIo1P3zn1T88Unw+4k64wwyn34KQ0pKpKcmhBDiFPhqaqj5+9+pe2MpitMJqFnHid+7l+hFi/p0Ga3upgQCOL/+msYVn6jBjTbl07RWK7YFC4g5/zyss2dLcEMIEVES0BAhdr+fI8FyUC3Bivzg7TJ3B+mybUTrtKHMipbgRUu5qESDBC26w75g1sZbbbI2dMB0vUL6vm8YUnoEDZCSksKiRYsYNWqU/LsLMVh8+zG8dy8468AYDRf/CSYcv/yJEgjgPnBAzcBYvx7Htu2hmsItosaOVQMYubmYJ0+WHy9CiEEn4HZT/ugSGt57D4DYyy8n9TdLZH8ohBADiK+2ltpXXqXu9dfVBtqAafRoNbBx7rmDKrABweDGN9/Q9MknNH7yKb7y8tA6rdWKbf58os87F9ucOVJmVgjR6ySgMcg0+/xhgYp8pzvUlLvC4zvmfWP1umBZKGMo22JEMHgxxKCTg+e9RM3aqONvh4rZ7W19W8a6nVweZ+aHE08n3Sw/sIUYFHxuWPkobH5OvZ02Ca7+OwwZ2eldvBWVagZG8OKvqQlbr09JCS8jlZDQg09ACCH6Nm9FBcX3/QDXrl2g05Hy858Rf8st8r1XCCEGKF9dHbX//Cd1r/2LQHMzAMZRI0m8915izj9f7TcyyCiBAM4dO2ha8QmNn36Kr6wstE5rsWCbN09tKH722RLcEEL0CgloDEBNPn8oWFHg8HDY2ZJt4abyOEGLeL0ulGnRtjTUcIuJeL0ELfqCwsJCPvvsMwoLC6m1RHMgaxR5qUOxo/7f6DRw3pBYbk5Xe23o5P9MiIGp+iC8fQeU71Rvz7wPFj4K+vDGfQGnE8e2bdjXrce+YQPuvLyw9RqzGeu0aaEsDGN2tuzrhRACcHz1NcU/vB9/VTW62Fgy/vwnrDNnRnpaQggheoG/oYHaf75G7T//SaCpCQBjdjaJ995DzAUX9Num6KdKCQRw7dxJ44pPaPz0E3ylrcENjcVC9Ly5RJ97Hra5Z6M1myM4UyHEQCYBjX6qsSVo4WjThDvYlLvae+ygRYJB12ET7uFmI/GGwfmh3B9UVVXx+eefs3//fgD0ej0zZswgNzcXjCY+qqrntdIatjTYQ/fJjDJwU9oQrktNID3K2NnQQoj+Zscy+OjH4LWDZQhc/hyMPg8I/sjYty/YB2MDzu3bUbxtygZqNESNG6dmYcyahXnyJLRG2T8IIURbdW+9RflvfwdeL6bRo8l85mmMWVmRnpYQQohe5m9spPZf/6L2H/8k0NAAgHHYMIbccw+xl1w8aAMboPaXcu3apfbcWLECb2lpaJ3GbMY2dy4xLZkbFksEZyqEGGgkoNGPNPn83LDjEIedbmq9/mNum2jQq0EKi5Fsc2tpqBFmI7EStOhXGhsbWb16NV9//TWKoqDRaJg0aRLz58/v8L2x3+7k9dIa/l1eR4Ov9XVyujWKuQnRzEuIZnqsDbNucNUAFWJAcDfD8gdhx1L19vA5cOWLeB1a7OvVRt72jRvx19WF3U2floY1dxa23FwsM2agj4+PwOSFEKLvU7xeKp54gro31P1s9Lnnkv7E42it1gjPTAghRCT5m5up+9fr1L7yCv5gYMOQlUXiPXcTe+mlaAyGCM8wshRFwbV7N40rVtC04hO8JSWhdZqoKDW4cd652ObOlc9UIcQpk4BGP6IoCtlf7sIZUBtCJxn17RpwtwQuYvSDr67jQONyuVi/fj0bN27E51OzbsaMGcPChQtJTk4+7v2d/gAfVdXzemkNmxvstH0Dm7QazoqxMic+mjnxNiZEW9BrpcSMEH1a2U61xFTNQQI+HfbUm7A3pGLfsBHPoUNhm2otFizTp4eyMIwjhksZKSGEOA5fTQ0lP3wAx7ZtoNGQ9MP7GXL33bL/FEIIEeJvtlO39A1q//5K6CQiQ0YGQ+5eTNzll6ORzGc1uLFnL02frKBxxSd4i4pC6zRRUdjmzCH6/POInjdPghtCiJMiAY1+5ouaRpKMeoabTdgkaDEg+Xw+tm7dypdffonT6QQgKyuLRYsWMWzYsJMas8bjY21dE2vqmlhT20Sp2xu2PlqnZWacjTnx0cyOt3GaNUp+vAvRVygKyqYXcL35G+wlWuzVMTiqdNAmAwutlqgzxmOdpWZhmCdOHPRniQkhxIlw7d1L0X334SstQ2u1kv7kk0QvmB/paQkhhOijAg4HdcvepObll/HX1ACgT08jcfFiYq+8Ukq6BimKgmvvXrWh+Cef4C0sDK3TmEzYzp6j9tyYPx+dTYIbQoiukYCGEH1EIBBg9+7drFq1ivr6egASExNZuHAhp512WrcFGBRF4aDDzdq6JtbXN7O+rpl6X3gJs0SDntnxrQGOYWZTtzy2EKLrvKWlNH/xKfZ3XsCRV4vfE14mzpCRoWZg5OZinTEdXWxshGYqhDgef0ChotFFUa2D4jpn8OLA7QswNMHCtBEJTM9OwCQnq0REw3//S9kvf4XicmEcNozMZ5/BNHJkpKclhBCiHwg4ndT/+99Uv/QS/qpqAPSpqQy567vEXX01WpP8lm6hKAru/ftDPTc8R46E1mmMRqxz5qg9N+bPR2ezRXCmQoi+TgIaQkSYoigcOnSIlStXUlFRAYDNZmP+/PlMmjQJna5nD274FYXdzU7W1TWzrq6JTfX2UFmzFllRRubE25gdH83sOBvJJjnzW4ju5m+249iyRe2DsWEDnvz8sPVasxHLrNlYc3Ox5eZiGDpUMqmE6CMCAYXKJjdFdQ6K6xwU16pBC/W2k9J6J77Asb9KW4w6Zo9KZOHpycwfk0xyTFQvzX7wUvx+qv70J2peehkA65w5ZPzv/6CT3x5CCCFOUMDlov6tt6n529/wVVYCoE9OZsh3v0vctdegjZLP9bYURcH97behnhuegoLQOo3BgHX2bDW4sWABuujoyE1UCNEnSUBDiAgqLS1l5cqV5AcPXJpMJnJzc5kxYwbGCKWoegIBtjc6WFfXxLq6ZrY32vEd9e4fY41SAxxx0cyKt0nPFiFOguL349q9G/uGDTSvX4/zmx0Q7JcDgEbBnODFOsKC9dZfY55/hZSREqKPKKl3sq2glm0FdWwtqOVwlR2PP3DM+xh0GtLjzGTGm8mKt5AZb8ao15JX0czqA1VUNbnDtj8jI5YFpyWz4LRkzsiIRSu9rrqVv6GBkgd/in3tWgCG3PVdkh54AE0Pn0gihBBiYAu43dT/5z/UvPg3fOXlAOgSExly553EX38dWrM5wjPsexRFwX0gL9Rzw3P4cGidxmDAmpur9txYsEBOOhBCABLQECIiamtrWbVqFbt37wZAp9Nx1llnMWfOHKx9rCmW3ednU4M9FODY3ewMazCuBSZGW0IZHGfFWjHrtJ0NJ8Sg5ikuxr5+g5qFsXkzgYaGsPWGzHSsSc1YrQVYk93ozroeLnwSTHJWkhCR4g8oHKhoYltBLVsL6thWUEtpg6vddjqthrTYqFCwIjPeQlaCep0ZbyYlJgpdJ0GJQEBhT2kjq/ZXsmp/BTuKw/cNiTYT88cksfD0ZGbnJGEz6XvkuQ4W7kOHKP7e9/EcOYImKoq0x35P7EUXRXpaQgghBpCAx0PDO+9S/eIL+ErLANANGcKQ79xB/PXXSzPsTiiKgjsvL9Rzw3PoUOtKgwHrrJnEnHc+0QsXSMldIQYxCWgI0Yuam5v58ssv2bZtG4FgWacJEyYwf/584uPjIzy7rqn1+thQ18zaYIDjkDP8jFKTVsPUGGsowDEp2oJezioVg5S/qQnH5s2hLAzvkcKw9droaKwzZmDNnYU1LYBx86/AUQMGK1z0vzDphgjNXIjBy+X1801RvZqBcaSO7UfqaHL5wrbRaTWMS49h6rAEzhoez/iMWNJio9B3U0C/ssnF6m+r+GJ/JV8eqMLuae11ZdBpmD5iCPNPS2bhackMT5QDIieiadUXlP70pwTsdvTpaWQ9/TRRY8dGelpCCCEGKMXjof7996l54UW8xcUA6OLjSbjjDuJvvFEaYR+HOy+Pxk8+pemTFbjzDrauMBiwzpzRGtyIi4vYHIUQvU8CGkL0ArfbzaZNm1i/fj0ejweAkSNHsmjRItLS0iI8u1NT6vKwrr41wFHm9oatt+m0zIyzhZqMn2aNQit1/8UApfh8OHftUrMwNmzAuWMH+FsPRKLTYZ40Ceusmdhyc4kaPx4NAfj8N7DxaXWb1DPg6lchcVREnoMQg01Ns5vtR+rYdkQtH7W7pAGvP/xrr9Wo48xh8UwZFs9ZwxOYlBWHtZeyJDy+AFsLavl8n5q9UVDjCFufnWgNlaaaOjwBo16yJDuiBALUvPACVX99ChQFy9SpZPz1L+gTEiI9NSGEEIOA4vXS8OFHVD//PN5C9SQnXWwsCXfcTvxNN0mfiC5wHzoU6rnhzstrXaHXY50xQ+25sXAh+n5ysqgQ4uRJQEOIHuT3+/nqq69YvXo1drsdgLS0NM455xyys7MjPLvupygKh51u1gYzODbUNVPn84dtM8SgZ3Z8a4BjWJRRGhuLfs1TWBhq5G3ftJlAU1PYeuOwYVhzc7HmzsIyfTo6m611Ze1hePs7UPq1env6PXDOb0Fv6sVnIMTgoSgKR2ocbG3pf3FE7X9xtORoE2cNT2DqcDWAcVpqdLdlX5yqw1XNwdJUlWzJrw1rNh5t0jNndCILTkth3pgkEm2yLwEI2O2UPvQwTZ9+CkD8jTeS8tAvpC+REEKIXqf4fDT+979UP/d8qBG2NiaGhNtuJeGWW6RHRBe5Dx+m6ZNPaFzxCe5vv21doddjnT5d7bmxaJEEN4QYoCSgIUQPUBSFvXv38vnnn1NbWwtAfHw8CxcuZOzYsWi1feOgSE8LKAp7mp2hAMemejvOQHjT1MwoA7PjokMlqlJMcnBBRJ6iKPjr6/HX1OCrrsZXVY2vphp/6O+W5VX4a2rC7quNjW0tIzUrF2NmRscPsutt+PAB8DSBOR4uexZOu7Dnn5wQg4jXH2BfWWOo98XWgjqqm93ttstJtjF1uFo+6qzhCWTGm/tFsL3R5WVdXjWf76tk9beV1Ng9oXUaDUzMjGPhacnMPy2Zcekx/eI5dTdPURHF378P94EDYDCQ9ugjxF19daSnJYQQYpBT/H4al39M9XPPhZpga202Em69hYRbb5USSifAnZ/fGtzYv791hU6Hdfo0os87n+hzFklWphADiAQ0hOhmBQUFrFy5kpKSEgAsFgtz585lypQp6PWDu4mnJxDg60YHa+uaWVfXxPZGB96jdi05FhNTY62MMJvQaTRoAQ2g1RAqVaVF/VsDWHRa0k0GJsVYsOp0vf2URD+iKAqB5mZ81cHARHU1vupgYKKmGn9VcFlNDb6aGvB6jz8ogF6PZdIkrLNzsc6aRdS4cWiO9Vr02OHjn8HX/1JvD50FV/0NYjNP/UkKMcg1u318XVgXCmB8XViP0xueKWjUaZmQGcuU4fGcNSyBKcPiibcaIzTj7hMIKOworueL/ZV8vr+SPaWNYetTY6KYf1oSC05LIXfUECzGgf+dxL5xIyUP/Ah/QwO6pEQy//pXLJMnR3paQgghRIji99P0ySdUP/dcqEeE1mol/uabSbj9NskwOEGeggIagw3F3fv2ta7Q6bBMO0vtuXHOIvRDhkRukkKIUyYBDSG6SUVFBZ999hl5wVqOBoOBWbNmMXPmTKKioiI8u77J7vezpd4eCnDsanZysjsao0bDjDgr8xNimD8kmjGWqEF5JupgFHA41CBEZ1kU1VX4g4ELxd3+zOxj0cbGok9MVC9DhqBPSkQ3JHg7SV1mGDqs6838KvbAW3dA9beABub+DM7+GegG/oFFIXpCRaMrVD5q25Fa9pY2EjjqgyQmSs/UNuWjzsiIJcow8APg5Q0uvvhWLU21Lq86LLBj1GuZmT0k1HsjK8ESwZl2P0VRqPvnP6n445Pg9xM1YQKZT/0VQ0pKpKcmhBBCdEgJBGj6dCXVzz6rZhUCWouF+JtuJOGOOyS74CR4jhxRG4qvWIFr797WFVotlrPOIub884g+5xz0iYmRm6QQ4qRIQEOIU1Rf///Zu+/4tupz8eMf7W1LsiQ709lxyCYbsheUDmhvKdACbdkJ0JZbRlvur+PeS1ugt7RQEnYHUFYHdDAyyYDsTRJnx7GT2JKsYe11zu+Po8g2SYAMRx7f9+uVV6JzZPtxEkvnfJ/v8zwh3n//fbZu3QqASqVizJgxTJs2DZsY7HVGgpksa0NRdkQT1CXThUUpifzuekBGaWUlA7IMkVyOg/EURz82jLyHQVdIbkxx2CjRdv7Fq85ESqc/VkXhy1dWnEhSNFdVSPH4p3/CFtQWC1qXC82JRIXLhdZV9rHHLjRlZaj152nXtizDxhfg3R9CLgW2bvCVZ6Dv1PPz+QWhC5AkmQO+aHP7qJoAtYHESc/r6TAxro+zMMB7oMeKWt21E9zJTI51hwIs293A0movdcHWf28DPVZmDvEwc7CHMZWOdjMv5GxIqRT1P/4J4bfeAqD0qquo+NlPURvEPBFBEASh/ZMlicjSpfgXLCxUGKhMJhzXXUfZTd8Wi+9nKX3kCE3vvUfk3fdI7tzZfEKtxjxhPO677sI8ZkzxAhQE4YyIhIYgnKV4PM7q1atZt24duZyy6/Giiy5i5syZuMRFxgUlyzL74ymWB5pYHojwYShKqsUWXY0KxpUo1Rszy2wMtZoK7auE4ssGgzT9859EV68mU3eUrN+P1NT06R/YgspgQOt2oy0rQ+M+UVHhyldUlOUrKpTzapOpjb6T00gE4R/fgd3/UB4PnAtXLQSLeJ0QhE+SyubYURcuJDA21gQJJ1onr9UqqKooYVwfR6EKo1vpBf4Z72BkWWa/VxksvrTay6aaILkW75mlJh3TBrmZWeVh2iB3h2rHlWlooO6uu0nu2AEaDeUP3I/jhhtExaYgCILQ4ciyTHT5+/iffLKwAK8yGnFccw3Om29C5/EUOcKOK11XV5i5kdyxo3DcdvnleO79PvqeohWwILR3IqEhCGcok8mwbt06Vq9eTTKZBKCyspI5c+bQU7zxtQvxnMTaUJRlgSaWN0Y4kGjdZsit1zLdaWOms4SpDhtlXaCPeHskZ7MEX3kV3xNPnDqBodMpbZ5OVEy4TvzZjdbV8rgLtcXSPhesatfDX26G8BFQ62DOz2DifGVaryAIrYTjGTYdCRQSGNvqwqSzUqvnGHVqRvdyFBIYo3vbsRl1RYq4cwjHM6zY52PZ7gbe3+sjFG9OGqlVcHFvh1K9UeVhcLmtfb7WAvHNW6j7znfI+f1oSkvp8ZvHsEyaVOywBEEQBOGcyLJMbOVKfE8uILl9OwAqvR77175G2a23iHaK5yhdV0fj088Q+utfQZJQ6XQ4v3kjZbffjkZ03BCEdkskNAThM5IkiW3btrF8+XKa8ouvHo+H2bNnM3DgwHZ7gy9ATSLF8kCE5YEmVgWjxHPNC2QqYHSJmRn5BMeoEjMa8W/Z5mJr1tDw858XBt8ZBg2i9MtfxjhkSCFZoS4t7bg/V1IOVv8alv8C5Bw4+sJXX4AeFxc7MkFoF2RZpi6YYGNNcwJjb0P0pOe5rPpC66ixfZwM7V6CrgO3Q2rvcpLMliNBllUrszeq6yOtzvewm5hR5WZWVTmT+pe1m1kkwddfp/5//hcyGQyDBtHzyd+h79Wr2GEJgiAIwnkjyzKx1R/gf/JJEifaXet02K/+KmW33oquW7fiBtjBJffswfvww8Q+XAOAxunE/Z27sX/1q6i0YgOkILQ3IqEhCJ9ClmX27t3LkiVL8Pl8AJSUlDBz5kxGjBiBWi0WVjqSlCSxIRxjWaOS4NgdS7Y6b9dqmOa0McNpY4azhHKD2Pl7PqXr6vA+/AiRxYsB0NjtuL/3XexXX41K0z4Wxs5Z0zH4221weJXyePjV8Plfg1G8lwldV06S2X28qdA6auPhIPVNyZOe189lYWy++mJcHyd9yswdN7HZCRwNJVhW7WV5tZcP9vtJtaiYMerUXNrfxYz8YPHu9gvf6kvOZGj4xS8I/vkVAGyXXUb3nz+E2mK54LEIgiAIwoUgyzLxNWvwPbmAxKZNykGdDvtXvoLrtlvR9ehR3AA7MFmWib7/Pt5HHiV96BAAhoED8DzwA6yTLy1ydIIgtCQSGoLwCWpra1m8eDFHjhwBwGg0MmXKFMaPH49OJxa6O4PjqbRSvdEYYUWwiaaPtTcZZjUVkhvjSi3ouvhg2bMlxeP4n32WwPMvIKfToNHguPZa3HffhcZuL3Z458+ed+HNeZAIgM4Cn/8VjLxOtJgSupx4OsvW2hAbDwfZcDjAliMhoqlsq+do1SqG9SgttI8aU+nAZRWDm9urRDrHmoN+lu5WEhzHwq0TUlUVNmblW1ON6uVA08bvl9nGRo5+93vEN24ElQr3d79D2e23iwSYIAiC0CXIskx83Xr8CxYQX79eOajVYv/yVZTddpuoVDwHciZD8NXX8P/ud+TCYQAsU6dQ/sADGPr3L3J0giCASGgIwin5/X6WLl3K7t27AdBoNEycOJHJkydjutADhYULJivJbG6KsTwQYVmgiW2RRKvzVo2aKQ4bM8tsTHeW0MvYcQalFossyzS9/TbeR39Ftr4eAPPEiZT/6IcYBw0qcnTnUSoKS/8b1j+tPK4YAV/9PbgGFDcuQbhAfJEUm1q0j9p5rIms1PrS0WbQMrrSwbhKJYExqpcdk76TVGZ1MbIsU10fKbSm2nwkSMs7BYdZx/TBSnJj6iA3pabzuwkksXMndXffTfbYcdQWC90ffRTbzBnn9WsIgiAIQkcR37AB34IFxNesVQ5oNJReeSWu229DX1lZ3OA6sFw4jH/BQgIvvwzZrLIp75prcN19F1qHo9jhCUKXJhIagtBCJBLh/fffZ/PmzciyjEqlYtSoUUyfPp3S0tJihydcYL50hhWBSGH+RiCTa3V+oNnATGcJM8psTCy1YhR93VtJ7t5N/UMPkdiolELrunfH88AD2ObO6Tw7aCUJtr8GS34KUSVhw8T5MPunoBU7zYXOSZZlDvljheqLjTVBDvljJz2vosTIuL5OpQKj0sngClub79oXiiMQS7Nir5elu72s3OujKdlcjaNRqxhb6ShUb/R3W8/pPSD8r39z/L/+CzmZRF9ZSc8FT4rdkoIgCIIAxDdvxv/kAmIffKAc0Ggo/cIXKLvjdgx9+xY3uA4sffgwDY/+iujSpQCobTZc8+bhuP4bqPVik6MgFINIaAgCkEwm+fDDD1mzZg2ZTAaAQYMGMWvWLMrLy4scndAeSLLM9kiC5YEmlgcibAzHaNmcyqRWcYndxowyZbh4X5O+8yzan6FsMIjvN78l9MYbIEmojEbKbruVsptuQm00Fju88yMVhZ1/g/XPQv125ZijD1zxKxg4p6ihCcL5ls5K7DwWLiQwNtUEaYylWz1HpYLB5TZl/kWlk7F9HPSwm7rs62BXlslJbKoJsrzay9JqL/u9rYe993aamZmfuzGhnxOD9rNV6ci5HL7HHqPxuecBpfVDj1/9Co24TxAEQRCEVhJbt+JbsIDYyvxMP7Waks9/Htcdt4tNAOcgtnYdDQ8/TCrfyUPXuzeee7+PbU4n2rAnCB2ESGgIXVo2m2Xjxo2sXLmSeDwOQM+ePZk9ezZ9+vQpbnBCuxbKZFkVjLIs0MTyxgj16Uyr85VGPTPKSpjptHGpw4qlswy8/gRyNkvwlVfxPfEEUlMTACVXfA7Pvfei6969yNGdJ8e2wqY/wI6/QDqiHNNbYeq9SmWGqMoQOoGmZIbNNUE21SgJjK21IZKZ1vOF9Fo1o3raGdvHwbg+Ti7u7aDULGZLCSc70hhnWXUDy/b4WHugkXSu+f+SWa9h8gAXM6s8zKjyUF5y6qR3Lhzm6L33EVulLMyU3Xor7u99F1UXeG8VBEEQhLOV2LED/4KFRJcvVw6oVJR87nJc8+ZhGDiwuMF1UHIuR/jNN/H+5jfkfH4AzOPG4fnBA5iGDi1ydILQdYiEhtAlSZLERx99xLJlywiFQgCUlZUxa9YshgwZIrLrwhmRZZnqWJJlgQjLG5tYF46RafGSqVepmGC3MMNZwswyG4PNxk73fyy2Zg0NP/85qX37ATBUVVH+ox9iGT++yJGdB8km+OgvSiLj+Lbm485+cPE3YfT1YHEVLTxBOFfHw4nC7IsNh4NU1zfx8as+u1nH2Mp8+6g+Dob1KP3MO+sF4YRYKssH+/2F2RveSKrV+WE9SphZVc7MKg8jepSiVqtI7d9P3Z13ka6pQWU00v3nD1FyxRVF+g4EQRAEoeNJ7NyJf+FCokuWFo7ZLrsM1/x5GAcPLmJkHZcUi+F/7jkCL/weOZUClYrSK6/Efc896Mo9xQ5PEDo9kdAQupwDBw6wePFi6vMDiq1WK9OnT2f06NFoxE4/4TyIZnN8EIqyrLGJZYEItcnWrVm6G3TMcNqY4SxhisNKqU5bpEjPXbruKN6HHyayeDEAmtJS3Pd8D/vVV3fsnbOyDEc3KUmMj/4Gmfx8AI0ehnwRxnwLKieDWsxNEToWSZLZ640UEhgbDwc5Gkqc9LzeTnOh+mJcHwf9XFbUYv6FcB7JsszOY00sy7em2lYbanXeZTUwuSTLsHdeZlTtDuyeMno++TuMQ4YUJ2BBEARB6OCSu3fjX/gUkUWLCsdsc2bjmjcP40UXFTGyjitz7Bjex35D0z//CYDKZKLslpuVdssmU5GjE4TOSyQ0hC7j2LFjLFmyhIMHDwKg1+uZPHkyEydORC8GOQltRJZlDiZSLA9EWNrYxJpQlKTU/HKqUcHYEkthuPgwqwl1B6jekOJxGp97jsbnnkdOp0GjwXHttbjvvguN3V7s8M5eIgQ73lASGQ0fNR8vG6gkMUZeB5ayIgUnCGcumcmxrTbExholgbGpJthqYDOAWgVDu5cWEhhjKx14TtP6RxDaii+S4v09SuXGqn0+oqlc4ZxWzjG+j5NZw3sws8pDX5eliJEKgiAIQseW3LsX/8KFRN59jxNludaZM3HNm4dp+LAiR9cxJbZto+GXD5PYsgUAbXk5nv+8h5IvfhGV2AQnCOedSGgInV4wGGTZsmXs2LEDALVazbhx45g6dSoWi7ghFi6sRE5ibSjK8kCE5YEm9sVbt9tw6bRMd9qYWVbCNIeNMn37qt6QZZmmt9/G++ivyOarnMwTJlD+ox9hHDyoyNGdJVmG2nWw6Y+w8++Qze9W1xhg6FVKIqP3JGXqsSC0c4FYmk01J9pHBdhxNEwm1/oSzqzXcHFvR2GA96jedqyG9vVaI3RdUixGzQ8fZM3mA2yoGMLGgROolVsn2Pq5LMyo8jCrysPYPk70WrFQIAiCIAhnKrV/P/6nnqbp7bdBUmZcWaZNxX3nnZhGjChydB2PLMtE3n0X76O/InPsGADGYcMo/+EPMI8ZU+ToBKFzEQkNodOKxWKsXLmSDRs2IOXfnIcPH87MmTNxOBxFjk4QFEfy1RvLA02sCkaJtRiWqgJG2czMKLMx01nC6BIzmiIuqid376b+oYdIbNwEgK57dzwPPIBt7pyOORMkHoDtrynVGL7q5uOei5TZGCO+BmZn0cIThE8jyzJHAnE2HA6yqUaZf7HfGz3peW6bQZl9UelkXB8nQ7rZ0GrEArDQ/qRra6m78y5Se/ei0umo+MmPsX/1qxz0RVlW7WX5Hi/rDgbItqh0tBq0TB3kYmZVOdMHu3FZDUX8DgRBEASh40kdPETj008R/ue/mhMbkyfjunM+5tGjixxdxyOlUgT++Ccan34aKaa0LrZddhmee7+PvlevIkcnCJ2DSGgInU46nWbNmjV88MEHpNPK7IJ+/foxZ84cunXrVuToBOH00pLEhnCM5YEIyxqb2BVLtjpv12qY6rQxMz9/o9yguyBxZYNBfL/9LaHX3wBJQmU0UnbrLZTdfDNqYwdrSyPLUPOBUo2x6y3I5StktCYY9h8w5pvQc5yoxhDapWxOYvfxCBsOB9iYT2D4PjZUGWCAx9oqgdHLaeqYSUehy5BzOcJv/YOGhx5CisXQuF30fPzxUy6iNCUzrN6nDBZ/f48Xf7R5TpVKBSN72plZ5WFmlYeh3UvE/31BEARB+IzShw/jf/oZwv/4B+SU1o+WSybhmj8f89ixRY6u48n6/fgef4LQX/6i3EfrdDhuvAHXHXegsdmKHZ4gdGgioSF0Grlcji1btvD+++8TjSo7VCsqKpgzZw79+/cvcnSCcObqUxmWB5pYHoiwIhAhnM21Oj/UamSGs4QZThvjSi3oz3NvTjmbJfjKq/ieeAKpqQmAkis+h+fee9F1735ev1abi3ph26uw+U/QuK/5ePlwJYkx4mtgLC1efIJwCrFUli1HQoUExpYjIeLp1q8DOo2KET3tjK10MLaPkzGVDpwWMRdK6BikZJLwm28R+P3vSdfUAGC6+GJ6PPZrdOXln/7xksz2o2GW7W5g2R4vHx1tanW+vMTAzCoPMwZ7mDzQhbmdtXEUBEEQhPYoXVuL/+mnCb/5FmSV2WvmCRNwzZ+PZcL4IkfX8ST37MX78C+JfbgGAI3Tifs7d2P/6ldRacW1iSCcDZHQEDo8WZbZvXs3S5cupbGxEQC73c6sWbMYOnQoajGASegEspLM1kicpY1KgmNbJE7LF2WrRs0Uh40ZThszykroZTy3Bc3Y2rU0PPRzUvuUxX9DVRXlP/ohlvEd6AI2m4a978LWP8O+RSDnF4J1Fhj+VSWR0f1iUY0htBvepiQbDgfZWBNg4+Egu443kZNaX37ZjNpC8mJcHycjepZi1GmKFLEgnJ1sIEDwz68QfPllcsEgAOqSEspuuYWym7591jf3DU1Jlld7WVrt5YP9/lYJQL1WzcR+ZczKV2/0cprPy/ciCIIgCJ1Vuu4ojc88Q+jvf4dMBgDz2LFKK6qJE0UV5BmQZZnoihV4H36E9KFDABgGDsBz/wNYp0wucnSC0PGIhIbQodXU1LB48WLq6uoAMJvNTJ06lbFjx6IVmW6hE/Ons6wMKq2plgciNGayrc4PNBsK1RuT7FaMn7FffrruKN6HHyayeDEAmtJS3Pd8D/vVV6PSdJBF0+PbYevLsP11SASaj/cYC6OvV5IZBlHiKxSXLMsc8EXZcDioVGAcDnIkED/peT3sJsb1cTCmj5NxfRwM8thQq8XNo9AxpQ8fpvGPfyT8t78jp5R2aboePXB+85vY/+MrqC2W8/a1kpkc6w4F8gmOBmoDiVbnB3qshdZUYyodYq6MIAiCIJxG5tgx/M8+S/gvf0XOJzZMF1+sVGxceolIbJwBOZMh+Nrr+J94glw4DIBl6hTK778fw4ABRY5OEDoOkdAQOiSv18uSJUvYu3cvADqdjkmTJnHJJZdg7Gg9/QXhHEmyzI5oguX55MbGphi5Fq/YJrWKSXYrM8uUBEc/k+Gki04pkaDx2WdpfP4FZZFJrcZx3XW4774Ljd1+Yb+hsxHzKwmMrX+Ghh3Nx60VMPJaGPV1cA8uXnxCl5fK5vjoaFipwMgP8Q7GM62eo1JBVUWJMv+ij5OxlQ66201FilgQzp/4li0EXvg9kSVLlFlGgHHoUMpuvgnb3Llt3m7hRAJx6W4vy6q9bKwJtqp+KjFqmTbYw8wqN9MHeXCItm2CIAiCcJJMfT2Nzz5H6I03kPPzSk0jR+K6cz6WKVNEYuMM5MJh/AsWEvjzn5XqF40GxzVfw3X33WgdjmKHJwjtnkhoCB1KOBxm+fLlbNu2DVmWUalUjBkzhmnTpmETQ5UEAYBwJsuqYJRl+fkbx1OtF017G/XMLCthptPGJaUWpMWLaHj0V2SPHweU/qjlP/oRxsGDihH+Z5fLKK2ktv5ZaS0l5atUNHqo+jyM+gb0mwEaUa0lXHjheIbNR5qrL7bWhUhnpVbPMerUjOplZ1wfJ2P7OBnd206JUVekiAXh/JJzOaLLl9P4/AsktmwpHLdOm4bzppswjx9XtIWPcDzDyn0+llV7Wb7HS6hFclGtgot7O5hR5WHWEA+Dy21igUYQBEEQWsg0eAm88DzBV18rVFwahw/HNX8e1unTxfvmGUgfPkzDr35FdMlSANQ2G6477sBxw/Wo9WKDhSCcjkhoCB1CIpFg9erVrFu3jmx+KNWQIUOYNWsWLperyNEJQvslyzLVsSTLAxGWB5pYG4qRafFyrs3lGL5vN+N3beNS7zEm3PRNSubOad8XoQ07YcvLsP01iPubj3cfrSQxhv0HmJ3Fi0/ocmRZ5mgowcYW7aP2eiN8/MqpzKJnbB8HYyudjO3jYGj3UvRa0eZG6FyUQd9vEvj9HwqDvlU6HSVf+iJl3/52u2unkJNkttYGC9Ub1fWRVue7lxqZOURpTXVJf5eYWSMIgiAIeVmfj8YXfk/wlVeQk0kADBcNwT1/PtZZs9r3PWU7E1u7joaHHya1ezcAut698dz7fWxz2vm9uSAUiUhoCO1aJpNh/fr1rFq1imT+DbJ3797MmTOHXr16FTk6Qeh4YtkcK+vqeWf1OlYZrBx3eVqd72bQcW2Fk/m9Pdi07WjRJh6AHW8oszGOb2s+bvHAyGtg5Neh/KLixSd0KTlJprq+iU01wXwLqQDHw8mTntfXZWFspSNfgeGgr8sibkiETut0g74d112H4xtfR+fxfMpnaB+OhhIsr1aSGx/s95NqUVll1Km5pL+rMHtDtIQTBEEQBMg2NhL4/e8J/PkV5LgyE85QVYVr3jxsc2ajUosNPJ+FnMsRfvMtvL95jJxP2bhnHjsWzw9+gGnY0CJHJwjti0hoCO2SJEls376dZcuW0dTUBIDb7Wb27NkMGjRILAgJwlmQs1mCr76G7/HHkZqakIHQV6/mo+tuZEVWzYehCIl8T3GnTsN/9qngxu5l6It1AZrLwv4lShJjzzsg5VuCqHUw+HNKNcaAWaARLXqEtpVI59haG2Lj4QAbaoJsqQkSSWVbPUerVjG0RynjKpX5F2MqHbhthiJFLAgXzoUc9H2hJdI51hz0s6zay7LdXo59LHFZVWFjZr411aheDjRqcX0qCIIgdF3ZYJDA7/9A8KWXkE4kNgYOxDV/njIzS9OONsy1Y1IsRuPzzzfPt1SpKL3yStz3fA9deXmxwxOEdkEkNIR2RZZl9u3bx5IlS/B6vQCUlJQwY8YMRo4ciVpk9gXhrMTWrqXhoZ+T2rcPAMPgwZQ/+CMs48cXnpPMSSxubOLhQ8fZH1cWpfqZDPx0QHfmlJVcuESid7eSxNj2GsS8zccrRsDo62HYV8FSdmFiEbokfzTFxnzlxcaaIB8dDZOVWl8GWQ1aRve2F6ovRvWyY9aLeS1C1yGlUvh+/WsCf3qxKIO+LzRZltnTEGHpbi/Lq71sPhKk5cuCw6xj+mClcmPqIDelJpFsFwRBELqmXChE4x//SPDFl5CiUQD0/fvjmjePks9dLhIbn1Hm+HG8v36Mpn/+EwCVyUTZzTdTdtO3UZvNRY5OEIpLJDSEdqOuro7FixdTk++3bDQamTJlCuPHj0enEzeFgnA20nVH8T7yCJFFiwDQlJbi/t53sV999WkXm7KSzJ+PN/LIoXr8GWUX+lSHlZ8N6MEQaxu118imYetLsPlFOLa5+bjZBSOugVHXQcXwtvnaQpcmyzKHG+P52RfK/IuD/thJzysvMTCuj7OQwKiqKBG7sYUuK+vzceS22wt9ni3TplJ2081FHfR9oQVjaVbs9bG02suKPV6aks1VWxq1irGVjkL1Rn+3tcv8vQiCIAjCCblwmMCLLxH405+Q8p039H374pp3ByVXXNHpNj+0lcT27TT84pcktmwBQFtejvue71H6pS+Jdl5ClyUSGkLR+f1+li1bxq5duwDQaDRMmDCByZMnYxZZZ0E4K1IiQeOzzzaXqarVOK67Dvfdd6Gx2z/T54hkc/y2poFnan2kZRk1cEP3Mu7v242y87kTvWYN/OMuaNyvPFZrYeBlMPobMGAOaPXn72sJXV4mJ7HzWJPSPupwgE01QfzR9EnPG1xuUwZ454d493SYxIKkIADpI0c4cvMtZGpr0TiddPv5Q9imTy92WEWVzUlsqgkqramqvezzRlud7+U0MauqnBlVHib0dYrB4oIgCEKXkotECL70Eo1/+CNSOAyAvrKSsjvuoPSLXxCJjc9AlmUi776L91f/R+boUQCMw4ZR/oMHMI8dW+ToBOHCEwkNoWgikQgrVqxg06ZNnPjvNWrUKKZPn479My64CoLQmizLRN55h4ZHf0X2+HEAzBMmUP6jH2EcPOisPmdNIsV/HzjGv33KxWeJVs33+1Tw7R6uc5+vse01eOtOZT6GxQ2Xfk+pyLC6z+3zCkJeJJlhy5H8/IvDQbbUBklmpFbP0WvUjOxVytg+Tsb1cXBxbwd2s0ikCcLHJaurOXLLreT8fnQ9e9L7hefR9+5d7LDandpAnGXVXpZWe1l7oJF0rvk1x6zXcOkAF7OqPMyo8lBeYixipIIgCIJw4eSiUYIv/5nA739PLhQCQNerF67bb6P0yitRic4cn0pKpQj86U80PvU0UkypKrfNnYvnvnvR9+pV5OgE4cIRCQ3hgkulUnz44Yd8+OGHZDLKkN+BAwcye/ZsysWAI0E4a8nqahr+9yHiGzcCoO3ejfL7H8B22dzzsrP8g2CEH+8/ys6oMhS1v8nAT852voYsw4pH4P2fK48vuhK+9Dswitd74dzUh5OF9lEbDgeprm/iY+MvsJt1jM0P7x7Xx8GwHqUYtGLHtCB8kvjGjdTOm48UiWAYPJhezz6DzuMpdljtXiyV5YP9fpbvUao3GppSrc4P61HCzKpyZlZ5GNGjFLVoZScIgiB0clIsRvCVV2h84ffkAgEAdD16UHbbbdi/fBUqvdhY9Gmyfj++J35H6I03QJJQ6XQ4brwB1x13oLHZih2eILQ5kdAQLphsNsumTZtYsWIF8XgcgB49ejBnzhz69OlT3OAEoQPLBoP4fvtbQq/nL2aMRspuvYWym29GbTy/Oz9zssyrxwP84uDxwnyNaQ4bPxvYnSrLZ5yvkU3DP78L2/6sPL70uzDrpyD6fwpnSJJk9nmjzfMvaoLUBRMnPa+309wqgdHfbRWLhoJwBiLLlnP0nnuQUylMY8bQa+ECNOL6/IzJsszOY02F1lTb6kK0vMNyWfVMH+xhVpWHyQNd2Ixip6ogCILQeUnxOMFXX6PxhRfI+f0AaLt1w3XbrZT+x3+gFomNT5Xcsxfvww8T+/BDADQOB+7v3P2JMzMFoTMQCQ2hzUmSxM6dO1m2bBnBYBAAp9PJ7NmzGTJkiOhJLghnSc5mCb76Gr4nnij0IrV97nLK77sPXffubfq1TzVf48YeLu7rU/HJ8zUSIXjteji8ClQa+PyvYOxNbRqr0HkkMzl2HA3nExhBNh4OtBrEC6BWwUXdSxhb2TzAW7R0EYSzF/r7mxz/r/+CXA7r9On0eOzXqE2fMYEtfCJfJMX7e7ws3+Nl5V4/0VTz65lOo2J8XyczBnuYNaScvi5LESMVBEEQhLYjJRKE3niDxmefI+vzAcrg67Jbb8V+9VdRGwxFjrB9k2WZ2MqVNDz8COmDBwHQD+hP+QMPYJ0ypcjRCULbEAkNoU0dPHiQxYsXczzfy99isTB9+nQuvvhiNBrR3kMQzlZs7VoaHvo5qX37ADAMHkz5gz/CMn78BY3jcCLF/7SYr1Gq1fD9PuV861TzNYI18PLV4N8Deitc/QcYOOeCxit0LMFYmk01QTbUKAmMHXXhVr3oAUw6DRdX2hlbqSQvRvd2YDWI3UiCcD40vvB7vI88AkDplVfS7X//R/S3biPprMTGwwGWVntZXu3loD/W6nxfl4WZVR5mVnkY18eJXiuqGgVBEITORUomCf3lrzQ++yzZhgYAtG43Zbfegv1rXzvv3Qc6GzmTIfja6/ifeIJcfsOjZcoUyu+/D8PAgUWOThDOL5HQENrE8ePHWbJkCQcOHABAr9dz6aWXMnHiRAwiuy4IZy1ddxTvI48QWbQIAE1pKe7vfbfoJaWrgxF+8rH5Gj8d0J3ZJ+Zr1G2CV66BmA9s3eEbr0PF8KLFK7Q/sixTG0iwsUaZfbHxcIB93uhJz3NZDYzr09w+aki3EnQasbAnCOeTLMv4fv0Yjc8+C4DzW9/Cc/99qERrwAvmkD+Wb03VwPpDATK55lsxq0HLlIEuZlZ5mD7Yg9smrq0FQRCEzkNKpwn/9a/4n3mWbH5zrMblouymm3Bcew1qs7nIEbZvuXAY/8KnCLz8MmQyoNFg/9rVuO++G63TWezwBOG8EAkN4bwKBoMsW7aMHTt2AKBWqxk7dixTp07FarUWOTpB6LikRILGZ5+j8fnnkVMpUKtxXHst7u/cjcZuL3Z4wKnna0x32Pipeh9V//gWZBNQPhy+/hqU9ihusELRZXMS1fWRQvuoDYcDeCOpk57X323Jt45SEhi9nWbRqlAQ2pCczVL/s58ReuMvALj/8z8pu/UW8XNXRJFkhtX7/CyrVtpT+aPpwjmVCkb0tDNzsIdZQzwM7V4i/q0EQRCETkFKpwn//U0an36azLFjAGicTspu+jaO665DbRHtGD9J+vBhvP/3f0QWLwFAbbXimncHjhtuEPNJhA5PJDSE8yIWi7Fq1So2bNhALpcDYNiwYcycOROnyAALwlmTZZnIO+/Q8OivCrtTzOPHU/7gjzAOHlzk6E4tks3xm5oGns3P19DIOW489hb3qg9S9h8LwWArdohCEcRSWbbWhthwOMCmmiCba4LE0rlWz9FpVAzvUcq4Pk7GVDoYU+mgzCp2HgvChSKlUhy7917lxletpuJnP8Vx9dXFDktoQZJkdhwNF1pT7TgabnW+vMTAjMFKa6pLB7iwiBZ8giAIQgcnp9OE//EP/E89TaauDgCN3Y7z29/G8Y1voLGKxMYnia1bT8PDvyS1azcAul698Nx7L7a5c8QmCKHDEgkN4Zyk02nWrl3LBx98QCql7Kzt27cvc+bMoXsbDyUWhM4uWV1Nw/8+RHzjRgC03btRfv8D2C6b2/4vPKQch9/7X/474uBt91QASrVq7u3TjW/1cKFTt/P4hXPmjSTZdDiotI+qCbDzWBM5qfWlhM2oZUylQ6nAqHQwspcdo07MVxKEYshFo9TdeRfxdetQ6XR0/79fUTJ3brHDEj5FQ1OS5dVellV7Wb3fT7xFolivUTOxfxkzB7uZWVVO7zLRokMQBEHouORMhvA//4X/6afI1BwBlBbMzm99E8f116OxiY1zpyPncoTf+ge+xx4rDF43jR1D+QM/wDR8WJGjE4QzJxIawlnJ5XJs3bqV5cuXE40qPc4rKiqYPXs2/fv3b/+LrYLQjmWDQXyPP07otddBklAZDJTdeitlN9+E2mQqdnifLhWFv94Me98FYPWsx/mxYQK7Ysp8jQFmAz8d0INZTpt4regkZFnmgC/GxsOBQgKjpjF+0vN62E2Mzc+/GFvpYFC5DY1IbglC0WUbG6m99TaSu3ahtljo+eSTWCZOKHZYwhlKZXOsOxhgWbWXpdUN1AYSrc4P8FiZVeVhRpWHMZUOMX9IEARB6JDkbJamt9/Gv/Ap0ocOAaAuKcF54404b7wBjVhDPC0pFqPx+edpfOH3yEnl/rz0yitx3/M9dBUVRY5OED47kdAQzogsy1RXV7N06VL8fj8AdrudmTNnMmzYMNRiWKQgnDU5myX46mv4nngCKay0kLBdfjnl992LrkcHmTnRdFwZ/n18G2iN8OWnYehV5GSZV/LzNRrz8zVmOG38dEAPBluMRQ5aOFPprMRHx8LNCYzDAYLxTKvnqFQwuNyWn3+hJDF62DtAQk4Quph03VFqb76ZdE0NGqeTXs8+g2no0GKHJZwjJdEcVZIbu71srAm2qpIrMWqZOsjNrCEepg3y4LSIXtqCIAhCxyLncjS98y7+hQtJHzgAKHMinDfegPPGG9vNrMn2KHP8ON7HHqPpH/8EQGU0UnbzzcomSjF0XegAREJD+MyOHDnC4sWLqa2tBcBkMjFt2jTGjh2LViv68wrCuYitXUfDQw+R2rcPAMPgwZT/6EdYJowvcmRnoGEnvPw1aKoDswuuexV6jWv1lKZsjt8cbuDZOh8ZWUajgm92d3Fv3wqcOvE60l6FExk2HwkWEhjbakOkslKr5xi0akb1shcSGKN7Oyg16YoUsSAIn0Vy715qb7mVrNeLrnt3ej3/HIa+fYsdltAGwokMK/f6WJ4fLN4yCa1WwejeDmZWKbM3qipEBaUgCILQcci5HJFFi/AvWFi4n1abzTiuvx7nt7+F1uEocoTtV2L7dhp++TCJzZsB0Ho8uO+5h9Irv4RKbFgW2jGR0BA+ldfrZenSpezZswcArVbLpEmTuPTSSzEaxc5qQTgX6bqjeB95hMiiRYDSA9T9ve9iv/pqVB0pUbh/Kbz+TUhHoGwgfOMNcJ5+UexQPMV/HzjGO36lEqVEq2Z2WSlDLEbKdFrK9FqcOq3yZ52GEq1GLK5cQEdDCTYeDrDxcJANhwPsaYjw8asAp0XP2EpHofpiWPdS9Fpx0SsIHUV88xZq581DCocxDBxAr+eeQ1deXuywhAsgJ8lsrQ0Wqjeq6yOtzncvNTKjysOsIR4m9XNh0ovZRoIgCEL7J0sSkcVL8C9YQCq/fqUym3F+/Tqc3/422rKyIkfYPsmyTOS99/A++isyR48CYBw6lPIfPIB53LhP+WhBKA6R0BBOKxwO8/7777N161ZkWUalUnHxxRczbdo08W8iCOdISiRofPY5Gp9/HjmVArUax7XX4v7O3R2vNHbTH+Ff94Ccg8pL4ZqXwOz8TB+6Ohjhx/uOFuZrnI5WRYsEhxanvsWfdRrKWjxWjmnRitkMn0lOktnbEGnVPupY+OR/jz5lZsb2cTIun8Do57KIJJMgdFDRlSup+853kZNJTKNG0euphR3vvUc4b46FEiyr9rK82ssHB/wkM80VeAatmksHuJiRr94QrQMFQRCE9k6WJKLLluFbsIDUrt0AqEwmHNdeS9lN30brdhc5wvZJSqUI/OlPND71NFIsBoBtzhw8992LvnfvIkcnCK2JhIZwkkQiwQcffMDatWvJZpVe91VVVcyaNQu3eOEXhHMiyzKRd9+l4ZFHyR4/DoB5/HjKH/wRxsGDixzdGZIkWPY/sPrXyuPhX4Mrfwdawxl9mpwssz4cY2UgQl0qTSCdozGTpTGTJZDJEstJn/5JTsGu1TQnQfSa0yZElGoQDRZN19iBmszk2FobKiQwNtcEiaSyrZ6jUasY1r2kkMAYU+nEbTuzf1dBENqn8D//xbEf/hCyWSxTp9DzN78RvZKFgmQmx5oDjSytbmB5tY+jodaDxasqbIXWVKN7O9CIzQOCIAhCOyXLMtHl7+NfsIDkRx8BoDIYcFx7Dc6bbkZX7ilyhO1TtrER3+NPEHrjDZAkVDodjhtuwHXH7WLgutBuiIRGB3Ps2BtotTb0BjcGfTkGgxu1+vwsMmUyGTZs2MCqVatIJJSbl169ejFnzhx6i2ysIJyzZHU1DQ/9nPiGDQBou3ej/P4HsF02t+PtdM8k4c15sPNvyuOp98OMHymToM+zRE4ikE9uNGayNKazBDKtkx6N6WzhcTCT42zesExqVYsESHOlR/PjfFIkf65Uq0HdAf7dGqMpNtYE2VSjtI/66GiYTK7135BFr+HiSgdjK5UExqjedsz6DtTyTBCEzyTw4ks0PPQQACVf+ALdf/FzVDox60Y4NVmW2dMQYVm1l2W7vWw+EqTFXHEcZh3TBrmZOaScaQPdlJrF/yVBEASh/ZFlmdiqVfiefJLktu0AqPR67FdfTdmtt6CrqChyhO1Tcs9evA8/TOzDDwHQOBy47r4Lx9e+1rHaYwudkkhodCCyLLH8/YuQ5Uyr41qtHYPBg8FQjkHvRm8oVx7rPRgMHvT6cgwG12kTH5IksWPHDpYtW0Y4rPSzd7vdzJ49m0GDBnW8hVZBaGeywSC+xx8n9Nrryg4Hg4GyW2+l7OabUJs6YOuGWCO8+nWoXQtqLXzxcRj9jWJHVZCTZYKZ3McSINkWCZBcIQFy4nhKOvO3OI0KHFotA8wGJjtsTHZYubjEjL6Iw9NkWaamMc6GE/MvagIc9MVOel55iUGpvqhU2kdVVdjQasT8C0HorGRZxv/EE/gXLATAcf31lP/oh2LYo3BGgrE0K/b6WFbt5f09XpqSzdV9GrWKMZUOZuWrNwZ4rOIeQhAEQWhXZFkm9sGH+J98ksSWLQCodDpKv/ofuG69FV337kWOsP2RZZnYypU0PPwI6YMHAdD370/5A/djnTq1yNF1fnJORs5JqMU8s5OIhEYHkssl2LXrPlJpL6mUl3S6AUlKf+aP1+kcGPQe9Plkh17vpqlJzc6ddXi9adJpEwaDh+nTZzNy5Eg0XaT9iiC0FTmbJfjaa/gefwIpnyy0XX455ffdi65HjyJHd5YaD8DLX4XAQTCUwjUvQr9pxY7qnMiyTCwnFRIen1QBciIB0pQ9dRsss0bNhFILkx02pjisDLOa2rSKI5OT2HWsiQ2HA/kKjCD+aOqk5w0qtzbPv6h00tNhEgtNgtBFyLkc9f/zP4RefQ0A13fuxjVvnngNEM5JNiex+UiIpdUNLNvtZZ832up8L6eJmYM9zBxSzoS+Tow6cV8hCIIgtA+yLBNfuxbfk0+S2LhJOajTYf/ylym77Tb0PTvovXobkjMZgq+/jv+J35ELhQCwTJ5M+QP3Yxg4sLjBdVKyLBP6+37Sx6K4vjkUjU1f7JDaFZHQ6MBkWSabDZNKeUmlvaRT3vyfG0infKTSDfnEh/ecEh8Gg0ep+sj/2WAoR693oVaLHyZBOJ3Y2nU0/PznpPbuBcAwaBDlDz6IZcL4Ikd2Do6shVeug0QASnvDN94AT1WxoyqKtCQRzOTwpTNsicRZFYyyOhghkMm1ep5Dq+ESh1Wp4LBbGWA2nNMiYjSVZcuRYGF495YjIRIf+5p6jZoRPUtbzL9wYDeL12tB6IqkdJpj9z9A5N13QaWi4sf/D8d11xU7LKETqg3EldZU1V7WHGwk3SLxb9JpmDzQVZi9UV5iLGKkgiAIgtAstm49/gULiK9bpxzQaim96kpct9+Ovlev4gbXDuXCYfwLnyLw8suQyYBajf1rV+P+znfQOp3FDq9TaVp2hKZFNaCCsm8OxVQl/n5bEgmNLqA58dGA33+AbdtX4vPtQ69PYDQkcTrVGE1p0mkfsnwmiQ9nvqWV+zTtrkTiQ+h6MkeP0vDIo0Teew8ATWkpru9+p+P3mfzor/D3eZBLQfeL4bpXwVZe7KjaFUmWqY4lWR2MsCoYZU0oSvRjA80r9DomO6xMdliZ4rDRw/jJr48NTcnm9lGHA+w+3sTHu2OVmnSMzbeOGtfHwbAepWInrCAISLEYdXffTezDNaDT0eORhyn53OeKHZbQBcTTWT7Y38iy6gaWVXtpaGpdOTi0e4nSmmpIOSN6lKIWg8UFQRCEIotv3Ih/wQLluglAo6H0S1/Cdftt6Pv0KWps7VG6pgbvr35FZPESANRWK655d+C44QbUerEGeK5imxoIvqFsjrVf2R/rJNEO7eNEQqOLiEajrFixgk2bNiFJygLbyJEjmTFjBna7HTiR+AgpVR6nqvTIV4KkUmeX+Ghd9VHeYrC5khRRq8UgQaHjkhIJGp99jsbnn0dOpUCtxnHtNbjuvhutw1Hs8M6eLMPqX8PS/1YeV30BvvIs6M3FjasDyEoy2yJxVgUjrA5G2dAUO2lWR1+TnikOG5MdNiaVWgiGlATGpvz8i9pA4qTP28tpYmylk7F9HIzr42SA2yoWgwRBaCUbDFJ72+0kd+xAZTbT84nHsV56abHDErogWZbZeayJ5dVellZ72VYXouVdpcuqZ/pgpXJjykAXNqO4HxAEQRCKJ755i5LYWL1aOaBWU/rFL1B2+x0Y+vUtbnDtUGzdehoe/iWpXbsB0PXsiefee7FdNle0Nz1LyX1B/L/fCZKMdVpP7J8T/+9ORSQ0OrlUKsWaNWv48MMPSaeVJMSAAQOYPXs2FRUVZ/U5T5348BZme5xoc5VKeU8aYP5JlMRHi0qPE5UfBg/6woBzkfgQ2hdZlom8+y4NjzxK9vhxAMzjx1P+4I8wDh5c5OjOUS4D/7oHtryoPJ44H+b+L6jF7v+zkchJbAzHWB2KsioYYWtTnI9P4lA1pVEHUqgbU6iDaTSSzJBuJYzroyQwxlY6qSgVrToEQTi9zLFjHLnlVtIHD6Kx2+n1zNOYRowodliCAIA/muL9PT6WVTewaq+fSKp5sLhWrWJ8X2ehNVU/t7WIkQqCIAhdWWLbNnwLFhBbsVI5oFZTcsUVuO64HcOAAcUNrp2RJYnwm2/he+wxsj4fAKYxYyj/wQ8wDR9W5Og6lvSxKL6ntyOncphGunFeMxiV2Lx4SiKh0Unlcjk2bdrEihUriMViAHTv3p05c+bQt++Fye7JskwmEySd9pFKNbRKdChVHz7SqQZSad8ZJz50OjsajQmN2oxGY0KtMSmPNWY06hOPzWjURuX3/GN1q8cm1PnnazQmVCp1G/5tCJ1Rcs8eGv73IeIbNgCg7d6N8vsf6By7EZJheP2bcHA5qNRw+cMw4bZiR9WhheLpwuDuTTUBth5vIlmiQyozIDkNyLbWyVoNMNJmYpqzhMkOK2NKLBg14nVKEITTSx04wJGbbyFbX4+2ooLezz+HoX//YoclCKeUzkpsPBwozN446I+1Ot/XZWHGYA+zhngY18eJXiveAwVBEIQLK7HjI/wLFhBdvlw5oFJhu/wyXPPmYRw0qLjBtTNSLEbj8y/Q+MILyMkkAKVXfgn3PfegO8sN1V1JNpjEu2AbUiSNoV8prpuGoRLXPqclEhqdjCzL7Ny5k2XLlhEIBABwOp3MmjWLiy66qF0ussqyRCYTyg82VxIdLQeaK1UfDaTT/jNKfJwptdpwiqSHkhRRt0iCKAkQc3MSRd0yQXJyIkUtEiadTjYYxPf444Reex0kCZXBQNktt1B2y82oTaZih3fuAofglWvBVw06M3z1BRgs+q6fCVmWqQsm2FgTKAzw3tsQPel5Lqu+0D5qQM9S/EYVa8JRVgej1CRbt/YzqlWML7UwxWHjUoeVkTYzmnb4mi4IQnEktm+n9rbbyYVC6Pv1o/fzz6Hr1q3YYQnCZ3bIH2NZtZfl1V7WHWokk2u+/bQatEwZ6GJGlYcZgz24bYYiRioIgiB0Ncldu/AvXFiYGQFgmzsX1/x5GKuqihhZ+5M5fhzvY4/R9I9/AqAyGim76SZlvcQsWlefihTP4H1qG1lvAm25Gc8dI1GbOvAM1gtAJDQ6kUOHDrF48WKOHTsGgMViYdq0aYwZMwaNpuO3iFESH0FSKS/ZbBM5KUEul0DKxcnlkuSkOLlcglwujpRLksvFC89RjiVaPc7lEkjSyf3p20ohUfLxBEk+KaLWtEikqM1oNC2el0+iFJImLR4rSROjSJhcAHI2S/C11/A9/gRSOAyA7fLLKb/vXnQ9ehQ5uvOk5kN47XqIN4KtG1z3CnQfXeyo2r2cJLP7eBMbDwfYUKMkMD4+BBWgn9vCuBbzLyrLzKdNNB9JpFgdUpIbq4MRvOlsq/MlWjWX2K1MdtiY7LAy2Gxsl0lrQRDaXvSDD6i7+zvI8TjG4cPp9czTHXt+k9DlRZIZPtjvZ+luL8v3+PBHW7+njuxlZ2a+emNo9xLx/icIgiBcEMnqavwLnyLy3nuFY9bZs3DNm4dp6NAiRtb+JHbsoOEXvySxeTMAWo8H9z33UHrll1CpxfrVCXJGwvfCDtKHmtCU6HHPH4XWLjZufBqR0OgE6uvrWbJkCfv37wdAr9dzySWXMGnSJAwG8UPwSWRZRpLyyY98UkTKtUh6SB9LkLRIiki5ODmpxfFcvMXnShQhYdIiQfLxShN1ixZbLR4rlSYnEi0tjzUnVU58rq5+oxhbu46Gn/+c1N69ABgGDaL8wQexTBhf5MjOk2QYVj4Ka58CKQPdRinJjJLuxY6s3fJFUvx1cx0f7Pez5UiIaKp1wkGrVjG8Zynj+jgZU+lgbKWDMuvZvSbLsszeeIpVwQgfBKN8EIrQlG09gcOt1zLZbi1UcFSaxOu/IHQFTe+8w9H7H4BMBsslk+jx+BNorJZihyUI540kyew4Gi60ptpxNNzqvMdmYGaVhxlVHiYPcGExiB2NgiAIQttK7t1L41NP0fTOu5BfLrXOmIFr/nwxN6IFWZaJvPce3kd/ReboUQCMF11E+Q9/gHncuCJHV3yyJBN4tZrEdj8qgwbPvJHoKsR1/GchEhodWCgUYtmyZWzfvh0AtVrNmDFjmDZtGlarGKLXHsiylE9yJE6T9IifttKkkFiR4i0+vnUiRZKSF+x7UbdIeJxIiqg/9rhVguTjiZST5pm0TL4Y2m3CJHP0KA2PPFrYgaEpLcX13e/g+NrXUGk7wQ2zlFOGfi/9H4j7lWNDvwJXPgl6UQ76cbIss6kmyItra3h7x/FW7TBsBi0XVzoY18fB2D5ORva0Y9K3TXVcTpbZHkmwOhhhdTDK+nCUhNT6bbq3Uc9kh5LgmOyw4tbrTvPZBEHoqIKvvEL9f/8PyDK2yy+n+yMPo9brix2WILQpb1OS5Xu8LN3tZfV+P/F0rnBOr1EzoZ+TWVUeZlaV07tMXMsIgiAIbSd14AD+hU/R9PbbICkbzizTpuKePx/TyJFFjq79kFIpgi++iH/hU0j5Ob+2OXPw3Hcv+t69ixxd8YT+fZDoqqOgUeH69jCMA+zFDqnDEAmNDigej7Nq1SrWr19PLqdcwA8dOpSZM2dSVlZW5OiEC6k5YdIyQZJsbrHVIinSuvKk+WM+XmnS3JorjiSd3DKnbahazRs5ecC7qVUViVJpYkSjNqPT2TGb+2K1DkalOn+Lx1IiQeNzz9P43HPIqRSo1TiuvQbX3Xd3njYeh1fDOz+Ahh3K47KBcNnPYdDc4sbVDsVSWd7cepQX19RQXR8pHB/Vy86XR/dgXB8ngytsaNTFScylJIlN4bhSwRGKsrkpRvZj79qDLUam5BMck+xWSrQdvxWhIHRVsizjX7AA/xO/A8B+7TVU/L//h6oTtBgVhDORyuZYd7B5sPiRQLzV+QEeKzOrPMys8jCm0oFOI1pcCIIgCOdf6uAhGp9+mvA//9mc2Lj0Ulx33on5YtHC+YRsYyO+J54g9Pobyt+TTofz+utxzbsDTRdb+42sPkr4XwcBcF4zGPNoT5Ej6lhEQqMDyWQyrF27ltWrV5NKKQvNffr0Yc6cOfToLP37hXZFlqVCmy0pFz99pckpZ5WcqtKkReJESpzXhIlOV4bbNQu3ey5O5yWo1Wff2ify3ns0PPII2WPHATCPG0f5fz2IcfDg8xZvUQUPw6L/B7v/oTw2lsK0H8D4W0EjdvG3tN8b4aW1R/jrpjoi+ZZSBq2aK0d154aJfRjes7TIEZ5aNJtjbThWqOD4KNq6/Z0aGGkzFyo4xpVaMIlFHkHoEGRJouHnvyD40ksAuObPx3X3Xe220lEQLhRZljngi7GsuoFl1V42HA6Sa1G9WGLUMnWQm1lDPEwb5MFpEdVMgiAIwvmVrqnB//QzhN96C/IbkM2TJuK+807MY8cWObr2I7VvHw0PP0Js9WoANHY7rrvvwnHNNZ2jE8aniO/wE/jzbpCh5PI+lEzvVeyQOhyR0OhAQqEQTzzxBLlcjvLycubMmUP//v3FDazQYclyrtW8kZYD2089v+TkeSbptI9odC+5XLTweTUaK2Vl0/C451JWNh2t9rO1YEvu2UPD/z5EfMMGALTdu1F+//3YLrusc/ycpSKw6tew5knIpUClhjHfhhkPgkVUd52QyUks2dXAi2tr+PBAY+F4nzIz10+s5KtjemI3d6xFkMZ0lg9DUVblExwHE62TiXqVirGlFqY4lCHjo2xmdEWqNhEE4fTkdJpjP3qQpn/9C4DyBx/EecP1RY5KENqncCLDqn0+lu328v5eH4FYunBOpYKLezsK1RtVFbbOca0nCIIgtAvp2loan3mG0N/fhKyyMc48fjyu+fMxTxgv3nPyoitX0vDwI6QPHABA378/5Q/cj3Xq1CJH1nZSh8P4ntsBWRnLxG7YrxTrumdDJDQ6mCXP/gNbiY0xV1yC1iYGvgoCgCRlCIXW4/Utwu9bTCrdUDinUulxOi/B474Ml2sWev3JC/fZYBD/E08QfPU1kCRUBgNlt9xC2S03ozaZLuS30jYkCba9Akt/BtH8303faXD5L6B8aHFja0e8TUleWV/Ln9fX0NCkLPirVTBrSDk3TKxk8gAX6k6yyH80mWZ1MMrqkJLgOJ7KtDpv0aiZZLcqQ8adNoZYjKjFRZYgFJUUj1P33e8RW7UKtFq6/+IXlH7xC8UOSxA6hJwks7U2xPJqL0urvew+3tTqfLdSYyG5cUl/V5vNwBIEQRC6lnTdURqffZbQ3/4GGeWeyzR2DO758zFPmiQWsgE5myX4+uv4H3+CXCgEgGXyZDz334dx0KDiBneeZbxxvAu3ISeyGC8qo+z6Iag6yRrDhSYSGh1IrinN8V+uAwnQqDBdVIZlXAWGAXbxAyAIebIs0dS0HZ/vPby+RSQSh1ucVWO3j8XtnovbNQejrkJ54/zt4+TCYQBsl19O+X33oussbdyOrIN3H4BjW5THjr5w2UMw+Aple2IXJ8syaw8GeGltDe/trCebb01RZtFz7fheXDe+Nz0dnXugqCzLHEikWB1UKjg+DEYJZnOtnuPUabjUbivM4Ohj0ouLb0G4gHKhELV3zCOxdSsqo5Gej/+2U+9cE4S2diyUYPkeL8urlcHiyYxUOGfQqrmkfxkzh5Qzs8pDD3sn2NwiCIIgFFXm+HElsfHGX5BPJDZGj8Y1fz6WyZeKeysg19SE/6mnCbz4opL8Uauxf+1q3HffjbYTzAvORdJ4n9xKLpRC38uG69bhqMUGirMmEhodiJTOkdjqI7qhnkxt81BajcOAZVwFlrHlaEpE1YYgnCDLMrHYPny+Rfj8i4hEdrY6r/caMazLYNyqwmIbTMWPHsQycUKRoj3PwnWw+Cfw0V+Ux3obTL0XJs4DrXidiCQz/H2LMuR7n7e5XdnYSgc3TKrk8mEVGLro0GxJltkZTbAqGGV1MMLacIx4Tmr1nB4GHZMdtsIMjgqDmL0iCG0l09BA7S23kNq3H3VpKb2eWoh5tBguKQjnSzKTY82BxsJg8aOh1nOnqipszKjyMKvKw+jeDjRiI5kgCIJwljINDTQ++xyh119HTiutEI0jR+CePx/L1KkisQGkjxzB++iviCxeDIDaasV1x+04brwRtb5jtX4+QUpl8T2zg8zRKNoyI+55I9FYO+b30l60SULjF7/4BX/729+orq7GZDJxySWX8PDDDzP4DAbqioTGJ0sfjxFbf5z4Fi9yMr+TVg3GwU4s4yswDnKi0ogXQkFoKZE4SsOBNzi2688knI3KZOQ8k7ESt2cuHvdcSkpGoVJ10AHJ6Th88FvlVzYBqGD09TDrx2D1FDu6oquub+KltTX8ffNRYun8kDa9hqtG9+D6CZVc1F2833xcWpLY0hQvVHBsaoqT+dglwUCzgUsdSgXHJXYrDl3nH+QmCBdC6tAham++hcyxY2g9Hno//xyGgQOLHZYgdFqyLLO3IcrS6gaWV3vZVBOkxVxx7GYd0we5mTmknGkD3ZSaRUJfEARBOHMZr5fA888TfPU15JTS7tg4bBiu+fOxzpguEhtAfMMGGn7xS5K7dgGg69kTz733Yrtsbof6+5FzEv4/7iK1N4jaosMzfyTaMlH9ea7aJKFx+eWXc+211zJu3Diy2SwPPvggO3bsYNeuXVgslvMaWFcnpXMkdviJbagnfbi5F6ymRI95bDmWcRVoHcYiRigI7YOUSND43PM0PvcccipFrkSF5uYxJMdoCEXXIUnNgyL1eg9u92zcrrk4HBNQqztA5lyWYcdfYMlPoOmocqz3JcqcjO6jihpasaWzEu/urOelNTWsPxwoHO/vtnDDxEq+MqYnJUaxIPFZxXMS68PRQgXH9kiClhcIKmC41VSo4Jhgt2DRdM1qF0E4F4mPdlJ7223kAgH0lZX0ev559D07STtEQegggrE0K/f5WLrby4q9PsKJ5plTGrWKMZXKYPFZVR4GeKwdaoFFEARBKL6sz0fj7/9A8JVXkBNKhaDhoiG458/HOnMmKnUH3Wh5nsiSRPitf+B77DGyXi8ApjFjKP/BA5iGDy9ydJ9OlmWCf91HfGMDKp0a920j0PeyFTusTuGCtJzy+Xx4PB5WrFjB1M/Y71ckNM5cxhsntr6e+OYGpHhWOagCw0AHlnEVmC5yotJ07RdDoeuRZZnIe+/R8MgjZI8dB8A8bhzl//UgxnzVWDYbpTGwEp9vEX7/cnK55hZEWq0NV9lM3O65lJVNRaNph/MUjm6Cd34AdeuVx6W9Ye5/w0VXdek5GcdCCV5Zf4RX1tfijyq7XjRqFXMvKueGSZVM6lcmFh7Og1Amy4ehaKGCY1881eq8TqViTImZS/PtqS4uMaPv4hfmgvBpYmvXUXfnnUixGMaLLqLXs890it7BgtCRZXMSm4+E8q2pGtjbEG11vqfDxKwqDzOqPEzsV4ZRJ5L5giAIwmeTbWwk8Ic/EHj5z8jxOACGwYNxzZuHbe6cLp/YkOJxGp9/gcbnn0dOJgEovfJLuO+5B11FRZGjO73w4hoiS4+ACspuvAjTEHE9f75ckITG/v37GThwIDt27GDYsGGnfE4qlSKVal4EaWpqolevXiKhcRbkrERiZyOxDfWk9ocKx9VWHZYx+aoNlyhvEjq/5J49NDz0c+LrlYV+bbdulD9wP7bLLjvtQrYkpQgG1+L1LcLvX0I67S+cU6sNOJ1TcLvn4HbNQqdzXJDv47SajsPSn8G2V5THOgtMuQcm3QW6rvkzLssyH+xv5MW1h1m8q6HQJsJjM3Dd+N5cN743FaWiaq0t1acyfBCMsCqf4DiayrQ6b1KrmWi3FCo4hllNaERiSRAKmhYt4tj370XOZDBPmEDPJ3+HxmotdliCIHxMbSDO8j1elu72suZgI+ls87wpk07DpQNczBriYcZgj7j2EARBED6TbDBI4A9/JPjSS0ixGACGgQOUxMZll6Hq4pXvmfp6fI/9hvBbbwGgMhopu+kmym65GbW5fW0+jW2oJ/jXfQDYvzwA64RuRY6oc2nzhIYsy1x55ZUEg0FWrVp12uf99Kc/5Wc/+9lJx0VC49xkGxPENtQT29iAFG1eVDL0K8UyvgLTUBcqXdfO9AqdTzYYxP/EEwRffQ0kCZXBQNkttyhvcqbPvtAvyznC4S34fIvw+haRTNYWzqlUGuyl43C75+J2z8Fo7N4W38qpZZKw5new6teQUS5yGHEtzP4JlFzAONqRcCLDXzfV8dLaGg76Y4XjE/s5uWFiH+YOLUcnKtQuOFmWqUmmWRWMsDqoVHE0ZrKtnmPXarjUYeVSu1LBMcBsEJUzQpcVfOMN6n/yU5AkbHPm0P1Xj6I2GIodliAInyKezvLB/sZC9UZDU+tqxaHdS5hZ5WFmlYeRPe2oxWBxQRAE4RPkQiECf/oTgT+9iBRVKgL1/fvjuuMOSq74XJdPbCR2fETDL39JYtMmALRuN+577qH0qivbRTVLYk+Axj/uBAlsM3pRelmfYofU6bR5QuPOO+/k3//+N6tXr6Znz56nfZ6o0Ghbck4iuTtAbEM9yb1BTjQ8V5u1mEd7sIyvQFf+2eabCEJ7JWezBF9/Hf9vHycXDgNgu+wyyu+/D12Pc+s7Lssy0Wg1Pt8ifP5FRKPVrc6X2EbkkxtzsVj6n9PX+oQgYNdbsPj/QeiIcqznOLj8l9BzbNt8zXZu57EwL66p4c2tR0lmlJ2RVoOWr1zcg+snVjKoXPSnbE8kWWZPLMmqfAXHmlCUaE5q9ZwKvY7JDmv+l42exg4ww0YQzpEsyzQ++xy+X/8aAPvVX6Xipz/t8jergtARybLMruNNLNvtZdkeL1trQ7S8k3ZZ9Uwb5GHWEA9TBrqwiTlegiAIwmnkmpoI/OlFAn/6E1KTMjdX36cPrnl3UPL5z6PSaoscYfHIskxk0WK8jz5Kpq4OAONFF+H5wQNYxo8vWlzpugi+Z7YjpyXMF3twXD1IbNhrA22a0Lj77rt58803WblyJX379m2TwIQzlw0liW1oIL6xnly4xSDkyhKlamO4C7Ve3EALHUts3XoaHnqI1N69ABgGDaL8Rz/CMnFCm3y9ROIIXt8ifL5FhMObocVYZLO5P273XDzuudhsw8/Pm9fx7fDuD6DmA+WxrTvM+RkMv7rLzclIZnK889FxXlxTw+YjocLxweU2bphUyVWje2A1dN0Lu44kK8lsi8QLFRwbmmKkpNaXG31NeqY4bPkqDhsuvfi3FToXWZLwPvIogT/8AYCyW2/F/Z/3iBsfQegk/NEUK/b4WFbtZeVeH5FUc6WiVq1ifF9noXqjn1u0lxMEQRBOlotECL78MoHf/6GweVNX2RvX7XdQ+sUvoNJ13eS4lE4TfPFF/AufKlSz2ObMxnPvvegrKy9oLNlAEu+CrUjRDIYBdlzfGopKW/yKkc6oTRIasixz99138/e//53333+fgQMHtllgwtmTJZnk3iCx9fUkqxshv0lWZdRgHqVUbei7i4tqoX1L7tmDf+FTRN59FwB1aSnu79yN45prLthuhVTKh9+/BJ9vEYHgGmS5RXs3Q0V+5sZc7PbxqNVnGFPUC8v+Bza/CMigNcKl31V+6btWVVVtIM6f1x/htQ21BGJKMlarVvG54d24YWIl4/o4xAJgB5fISWxqihXmb2xtiiN97DlDrUYm25X5G5PsVqxakYAXOi45k+H4f/2/Qh9gzwMPUPbtbxU3KEEQ2kwmJ7HhcIDl1V6WVns56Iu1Ot+nzMzMqnJmVnkY39eJXiyCCIIgCC3kojGCf/4zgRdeIBcKAaDr2ZOy22/DfuWVqPRdt7o9Gwjge+IJQq+9DpIEOh3O66/HNe8ONBdgXTkXy+B7ahtZXwJdhQX3HSNQG8VmvLbSJgmN+fPn8+c//5m33nqLwYMHF46XlpZi+oz960VC48LKNaWJbaontqGBXCBZOK7racUyrgLzKDfqTrLjOZfN4D10kGQ0glqjxWK3Y3E4MVptYjG0A5BlmdTevUSWLiW6dBnJnTuVE2o19mu+hvs730HrKN6w7mw2gt+/HJ9/MY2N75PLxQvntFo7btdM3O65OJ1T0Gg+YUBkNg3rnoIVj0A6ohwb9h8w+2dg79XG30X7IUkyK/f5eHFNDcv2eAstG7qVGvn6+N5cM74XHpsYtNlZNWVzrA1FCxUcu2PJVuc1KhhtMxcqOMaWWDCKWSlCB5Gpr+fo9+9Vev9qNHR76H+xX3VVscMSBOECOuyP5edueFl3qJFMrvmW22rQMnmAi5n5weJum5inIwiCICikWIzgq6/S+PwL5AIBAHTdu1N2223Yv/LlLp3YSO3bR8PDjxBbvRoAjd2O6+672nTTq5zJ4XvuI9I1TWhKDXjmj0RTKt6321KbJDROtyj8+9//nm9961vnNTDh/JIlmdSBELEN9SR2NkL+olqlV2MemZ+10dPaoRb+s+k0x/fvoW7XR9Tt3sGxvXvIplMnPU+j1WJxOLE4nFjt+d8dTix2h/J7/pfJVtKhvv/OQM5kiG/aTGSZksTIHD3afFKrxTZrFq55d2CsqipekKeQy6UIBj/A61uE37+ETCZYOKdWmygrm4rbPRdX2Ux0uvzrnCzDnndg0YMQOKgc6zZKmZNROenCfxNFEoyleWNTLS+tPcKRQHNSaPIAF9dPrGT2EA9asXDd5fjSGT7IDxdfFYxQk0y3Om9UqxhXamGKQ6ngGGE1oxWDV4V2Juv30/j8CwRffRU5kUBtsdD9V49imzGj2KEJglBE0VSW1ft8+QSHD3+09f3KyJ6lheqNod1LxGBxQRAEASkeJ/ja6zQ+/zw5vx8AbbdulN16C/avfhV1F05sRFetouHhh0nvPwAoQ9XL778Py9Sp53VNT5ZkGl/eTXJnIyqjFs+8EWJG8QXQ5kPBz5ZIaBRfLpomvtlLbEM9WV+icFxXYcEyPl+1YW5/ffoyySRH9+7m6O6PqN31EfX795DLZls9x2QrocTtIZtOEwuHSEaaPvPnV2u0WByOQtJDSYA4sDhbJ0JMthJUarHgerZy0Rix1auILF1GdOVKpHyfSACVwYDlkkuwzZqJdcYMtGVlRYz0s5GkLOHwRiW54VtMMnWscE6l0uJwTMJtGI5701IM+/NzMqzlMOvHMPLr0EX+L22rDfHi2hr+ue0YqazSbMhm1HL1mF58Y2Jv+ove0kILRxIpVoeifJBPcHjTrV/rbRo1lzisSgWH3UqVxSgS0kLRZH0+Gp97nuBrryEnlWoj06hRdH/4lxe8v68gCO2bJMl8dCzM0t1elu/xsr0u3Oq8x2ZgxmAPM4d4mDzAhaWTVNILgiAIZ0dKJgm9/jqNzz5H1ucDQFteTtktt2D/2tWoDV2zWkDOZgm+/jr+J35HLqhsMLVceimeB+7HOGjQuX9+WSb8z4NEPzwGGhXum4dh6Gc/588rfDqR0BA+lSzLpA81EdtQT3yHH/KLjGjVmIe7lFkbfYpXtZCKxzm6Z2e+AuMjGg7uR8rlWj3H4nDSc8gweg4ZRq+LhuHs0atVvNlMhngoSDTYSCyY/z0UJBoMEMv/igYDJM4o8aHB5nJT0W8g3QdV0W1gFZ6+/dBo218SqD3JHD+O77eP0/TvfyNnmmdRaBwOrDNmYJs5A8sll6A2m4sY5bmRZZlI5CN8vkX4/IuJxfa1PElpJIfbOh732J9itg8tXqAXSDKT45/bjvHi2ppWN+wXdSvhxkmVfGlUd8xiELTwKWRZZm88xep8e6oPQ1HC2dbvBS6dlsn5BMdkh5VKU9e8sBcurIzXS+D55wm++hpyStlxbRw5Avddd2GZPFkk2QRB+FTepiTv7/GxtLqBVfv8xNPN7296jZoJ/ZTB4rOqyuld1nGvkQVBEIRzI6VShP7yFxqfeZZsQwMAWrebsltuxv61r6H+jGMAOptcUxP+p54m8OKLkMkoLcuvvhr3d+4+pw2ykZV1hN8+BIDzuirMI93nK2ThU4iEhnBGpHiG+BalaiNT32I2gNukzNoYU47G0nYL9rIsEwsFqd+/l7rdO6jbvRPvoYPIcuuxsTaXm15DhtEjn8CwV3Q/LwsGuWyGWCioJD1CAWKBALFQoJD4iAYDxEJB4k1hOMWPjEanw9O3P90HKgmObgMHU+ISL3igVGQ0Pvcsgd//obDgo6+sxDprFrZZMzGNGoVK08mG/+YysOE54mt/gdeaxufS01TS+ufHYhmE2z0Xj3suVutFnWrh67A/xsvranh9Yx3hhJK80mvUfH5EN66fWMnFve2d6vsVLqycLLMjkijM31gfjpKQWr8u9zLqmeKwMtlhY7LdiscgEs7C+ZNp8NL43HOEXn+98L5mGjUK1513Ypl8qXh9EwThrKSyOdYfCrB0tzJ7o2VrToD+bguzhpQzY7CHsX0c6ESLzs8kFw4TXb2a2MqVxNauQ1NSgnniRCwTJ2AeN+6CDJQVBEE4X6R0mvBf/4r/mWfJHj8OgMblouymm3Bce02H3iB6LtJHjuD91f8RWbQIALXViuuO23HccMMZV7HEt3kJvLIHgNIr+mKb2vO8xyucnkhoCGdFlmXStRFi6+tJbPchp/MJBY0K09AyLOMrMPSzozrD3q6yLJOMRWnyNhD2NRD2Kr+avPWEfV6afN5Tzr+wl3ej50XDClUYpZ7y8/FtnrVcNks8HCJwrI7j+/ZwfF81x/btOWVrK6uzjG4DB9N90BAGTbyUEpenCBEXj5zNEvrr3/A98USh56N57Fg899+Hcfjwzrvgs28xvPcj8O9VHpcPg8t/QbL7IPy+Jfh8iwiG1iHLzS10jMaeuN1zcLvmYrePQaXqeAmenCSzvNrLi2trWLHXVzjew27iGxN7c83YXpRZxa554fxLSRKbwnFWh5QEx+amGNmPXdkMthiZbFcqOCbZLZTqRGWQcOYyDQ00PptPZKSVOS+m0aNx3XUnlksu6bzva4IgXHCyLHPAF2N5tZel1Q1sPBwk2yJ5bzNqmTrIzawqD9MHe3Baum4v9Y+TZZnUnj1EV6wkunIliS1bQJJO/WS1GuNFF2GeMB7LxImYL74YtUX0RxcEof2T02lCb75J49PPFGaRahwOnDd9G+fXv95lX8viGzbQ8MuHSe7cCYCuZ088934f22WXfaZr9dTBEL7nP4KcjPWS7pR+sZ+4xr/AREJDOGdSMkt8m0+p2qiLFo5rnEYs4yqwjClHU9J88ZxOJk5OWLT4czoRP9WXaaZS4ezWozmBcdEwbE5XW317540sy4QajnN8r5LcOL63Gt+RQ8gtLpxVKjX9xoxn1NwrqBw+qtPP4IiuWo33kUdI7VNaLukqe1N+331YZ83qvG8Gvr1KImP/YuWxuQxm/j+4+EZQt05QZDJh/P5l+PyLaGxciSQlC+d0Oidu12zc7rk4nZegVrfvJEBjNMVrG2t5ee0RjoaUmTwqFUwb5OaGiZVMH+xBI4ZbChdQNJtjXThWqOD4KJpodV4NjLCZmZJvUTW21IJZ7HIVPkGmvp7GZ54l9MYbhZaJpjFjcN85H/OkSZ33fU0QhHYjnMiwKj9Y/P09PgKxdOGcSgWje9kL1RtDutm63OtSLhojvnZNIYlxoh3LCYaBA7BMnYp18mRy4SZi69YSX7uO9KFDrT+RVotpxAilemPCREyjRnbZ/vSCIHQMciZD+B//wP/U02RqawHQ2O04v/UtHNd/A421682qlCWJ8D/+ge/Xj5H1egEwXXwx5T/8Aabhw0/7cZmGGN6F25GTWUxDy3B+Y8gZb+YWzp1IaAjnVfpolMi6YyS2eiGt/JeRkQkbAtSmqznk20EiEv6UzwLmUjul7nJKPOWUespb/bnE5e40cygyyST1B/dxfN8eDm/dRO2uHYVz9opujJxzBUOnz8ZktRUxyvMvuXcv3kceJbZ6NQCa0lJcd87Hce21qPSddOdYIggrHoH1z4CUBbUWJtwBU+8Dk/1TPzyXSxAIrFKGivuXkc02/xxpNBbKyqbhds/FVTYdrbZ9/H+RZZnNR0K8uOYwb++oJ51Tknd2s46vje3FNyb0prKsa+4IEdqfxnSWD0PRwgyOA4nW1YB6lYqxpZbCDI5RNjM6ceEqoMx+anz2WUJv/KU5kTF2DO677sI8YUKXWzAUOjdJkokGkjT5E4R9icLvYV+CaCCFyabD0c2Co8KMo8KCs5sFe7kZnaHjVZV2dDlJZltdiGX51lS7jreuFO9WamRGlYdZVR4u6e/CpO98/0bKLMjDRFeuILpiBfGNm5Te6XkqoxHLxIlYp03FOnUquh49Tvl5Mg0NxNetI7Z2HbG1a8geO97qvMpgwHTxaCwTlBZVxmHDUGlFlacgCO2PnMkQ/te/8T+1kEzNEQDUpaU4v3kjzuuv75Lt9aR4nMbnX6Dx+eeRk8omUsfXv075fz140ibjXDiFd8E2cuEU+soS3LcMQ6XrfO+fHYFIaAhnTMrliDT6lYoKXz1NPm+r1lDRYACNSkcvy2D620biMjb3kYtlmzgU2c7R3H70ZVYlQeEpp9TtodRToTx2e9AZjEX8Dounsa6WbYvfZueKpYVKFa1Oz+BLpzJq7uep6D+wyBGem6zPh+/xJwj99a9KSbdOh/Mb38A17w40paXFDq9t5LKw+Q+w7CFIBJRjgy6HuQ+Ba8BZfUpJyhAKrVeSG77FpNLNu8tUKj1O5yTcrrm43bPR6y989VI8neWtrcd4cU1Nq5vnkT1LuWFSH74wohtG8aYvtHPHkmlWh6KFCo7jqUyr8xaNmomlVqWCw2ljiMWIWixcdxmyLJPYtInASy8TWbwYcsqAXvO4cbjuvBPzhPEikSF0WJl0jiZfc8KiyZcgnE9cRBqTSLkzvy20OY04uilJDkeFGUc3C84KC0Zr59ik1BEcDydYXu1jWXUDq/f7SWaaq8QNWjWX9C9jZpWHGVUeejo6bm91KZkkvn59oQrjxE7kE3S9e2OdNg3r1KmYx48748oKWZbJ1NURW6tUb8TWrSu0zT1BbbFgHju2MIPDMHhwp6+8FwShY5GzWZrefhv/wqcKVWhqmw3njTfivPGGzrs+8wkyDQ34fv0Y4bfeAsBx/fWUP/ijwjW9lMzie2o7mfoYWrcJ9x0j23SGsPDJREJDOIksScRCwXzCouGk9lCRRl+rNkmnojUYKHUrFRXu0krc6e6Y/SZUJ6qeVWAc5MAyvgJjlROVaOPRSjqZoPqDFWx979/4appLnCv6D2TknCsYfOlUdPqOU9YsJRIE/vhHGp95FimuJGpsc+fiuff76Hv3LnJ0bejg+/DuD8G7S3nsroLLfg4DZp23LyHLEk1N2/H5FuHzLyIeb1kSr6K0dAwe92W43XMxmdp2SNUBX5SX1tbwl011RJLK7A+DVs2XRnbn+omVjOxlb9OvLwhtRZZlDiZSrAoqFRwfBKMEs7lWz3HqNFxqtxUqOPqa9GJBu5NKbNtGwy8fVvqt55knTsQ1bx6WCeOLGJkgfDayLJOMZgqVFR9PWsTD6U/8eLVGRYnLRInLRKlb+VXiMmIrMxIPpwnWxwnUxwgejxGsj5OMZk77uUw2XXOSo0Wyw+owiNfQNpTM5FhzsFGZvbHbW2gHesLgchszhyjVG6N7O9p9W9B03VGiK1cQW7GS2Lp1hR22ACqdDvO4cVinTcUydSr6Pn3O6/8tWZZJHzhAbO064uvWElu/ASncuiOBprQU84QJmCdOwDJxIvq+fcX/b0EQ2gU5l6Pp3XfxL1xIev8BQBmU7bjhepw33ojW4ShyhBde+J//5Nh99wPguvNO3HffhZyV8P9hJ6n9IdRWHe4/G+sAAQAASURBVJ75o9A6u+ZG7PZCJDS6IFmWSUSa8okKL2FvffMMC5+XJl8DuczpbzwANFotJW4PJe7W7aCUXxWYbCUnXaTJGYnETj+x9fWkDjZf5KltOixjKrCMK0dbZmqT77mjkmWZ4/uq2brobfauWUUuqywSGy1Whk6fzci5V+Co6F7kKE9PliSa/vlPvI/9hmx9PQDGESMof+B+zGPGFDm6NtR4ABb9P9jzb+Wx0Q4zHoSxN4Gm7crPZVkmFt+vJDd8i4hEPmp13mq9CLd7Lh73XCyWQeflRiqbk1iy28uLaw/zwf7GwvHKMjPXT6jkq2N64hADKIVORpJldkYTrA4qFRxrwzHiudaJ/h4GHZfmkxuTHVa6GcTPQUeXrjuK7ze/oelf/wKUFiOlX/oijuuvxzh4cJGjE4TWpJxENJhqTlrkExYnWkRlkrlP/Hi9SZtPVLRIWuQTF1aHEfUZLHAnommCx+ME62OF3wP1MaKB1Gk/RmvQ4Cg3F6o6nBUWHN3MlLhNaMRGqPNKlmX2eaMs3e1lWXUDm2qCtJgrjt2sY/ogNzOqPEwb5MZuLv77mZxOE9+8hejKlURXrigswp2grajAOnWqksSYOPGCDr2VczlSe/Yo7anWrSWxYWNhQ1chPre7UL1hnjARfc9Tt7oSBEG4UGRJIrJoEf4nFxRmnKrNZhzXX4/z29/qcomNwEsv0/C//wuA54c/RGWcQHyLF5Vejfu2Eeh7to82312ZSGh0Uql4vNWg7bCvPj98W2kPlUkmPvHjVSo1NpdLSVa4m5MVJfl5FlaH85zKZjP+BLEN9cQ3NSC12LVlGGDHMq4C09AyVFpxs9JSvCnMR8sXs23x2zT5vIXjlSNGM2ru5+l38TjUmvbTxie2fj3ehx8huXMnALru3XH/539ScsXnOm/JdbIJVj4K656CXBpUGhh3C0z/AZidFz6c5DF8vkV4fYsIhTYAzQuuJlNv3O65uN1zKS0ZjUp1Zv8m3kiSV9fX8ud1R6hvUnbBqVQwq8rD9RMrmTrQfUaLHYLQkaUlia1NcaWCIxRhUzhO+mOXTQPMBiY7bEy2W7nUYcWhE721O4p0bS3+p58m/OZbkN9YUHrVVbjv+R668vIiRyd0ZZlUrtUMi5ZVFtHGJJL0ybdvVodBqbRwmyh1NSctSt0mjBeghUI6mSXUECdYHy9UcwTrY4S9idPGrtaoKHWbxJyONhSKp1mxt3mweDjRfK+mUasY09vBzCEeZlZ5GOixXrBKg4zXS2zVKqLvryD24YdIsVjzSY0G0+hRWKdOwzptGoZBA9tNBYScyZD46KPCDI7E5s3I6dZVULqePZXqjQkTMU8Yj87jKVK0giB0dbIkEVmyBP+ChaSqqwFQmc04rruWsptuQltWVuQILxzfggX4H38C/ZArMQz+PKih7JtDMQ2+8Gs7wslEQqODyqRTNPm8SpXFKVpDJaORT/0cFoczn7Bonl+hzLAox1bmQnMBBpnJWYnE7gCxDfWk9gUh/79MbdFivrgcy7gKdJ6O28O1LUhSjsNbN7N10b85tHUT5H80bWVuRsy+nOEz52KxFy97njp0CO///R/RJUsBpYds2R2347zxxjPuUdthSDnY+jIs/W+I+ZRj/WfCZb8AT1VxY8tLpwP4/cvw+RcRCKxCkppvpPR6N27XbNzuuTgcE1GrT73zTpZl1h8K8OLaGt79qJ5sfrGhzKLnmnG9uG58b3o5xc+rIMRzEuvD0UIFx/ZIgpYXUSpguNVUqOCYYLdgaUcJaUGRPnIE/1NPK3108zMyLJdMwv2f38c0bGiRoxO6AqWqOtNq+PaJ2RZhf4JE0ye3htJo1ZS4jIWERYmrdaWFtp3Os8rlJJp8CYLH862rTlR2NMTJpk5fWSLmdJx/2ZzEltoQS3d7WV7tZU9D63vMng4TM6uU5MbEfmXndUaanMuR2L6d6IoVRFeuJLVrd6vzGqcT65QpWKdPw3LJJaft957NSSQyOZIZiWQml/914pjyK5HJkcpIJLM5Eukc6azEqN52Jg9wnffEiJRKkdiyldg6ZQZHYseOQrL8BH3//ljyLarM48Z1uZ3RgiAUnyzLRJctw//kApK7lBbaKqMRx7XXUnbzTWjd7iJH2PZkWeb4z/6AlFRmn5ouylJ244wiRyWcIBIaHUg6EecvP/8xTd4GYqHgpz7faCtR5li4PfmWUM1Dt0vcnnY3gyEbSBLbWE98YwO5Fjdo+j4lWMZXYB7uQtVOb7yKJdRQz/Yl77Bj+WKSEWX4slqjZeCESxg19wp6VA29YLuTssEg/gULCb7yinJRrtFg/9rVuO+6q3Nn8Ws+hHcegPrtymNnf2VOxqDLlJKFdiibjdEYWInPtwi/fxm5XLRwTqu1UVY2A7d7LmXOqWi1FqKpLH/fcpSX1tS0upG9uLedGyf14XPDKzBoxc+mIJxOKJNlTSian8ERZW882eq8TqXi4hIzkx1WJjtsjCkxo++slWwdQLqmRklk/OMfzYmMSy9Vhn1fPLrI0QmdTS4nEQ0kW1RYJFsN5M58wgI+gMGsba6scLX+3Wo3oOpE1ZKyJBMNpQrVHGJOx4VXF4wrczeqvXx4oJF0tkX1r07DpQNchQRHRempe4vLskw6J50ywZDyNyKtX4tuwxqMW9ejabFJT1apCPYawNFBozk8YCR1nkoSWbnV5ziRnGj5ubOfUqn0ScZUOvj+nEFcMsB11p/j0+SiMRKbNykzONauJbl7d2HDGgAqFYaqquYEx9ixaKzWNotHEAShJVmWib7/vpLY+Ehpaa0yGLBf8zXKbr4FXXnnrShL7Gqk8cVdIEOq+p9kDr5Hr2eewTJxQrFDExAJjQ5FlmUev/GrZNNKv1m9ydQ8v8J9oiVUhZLAcJdjMHfMndJyTia5R6naSFYHClUbKqMW82g3lvHd0He7cH1QO4JsOs3etavZuujfHN+3p3Dc1auSkXM/z0VTpqM3tc3/BymdJvjSy/ifegqpSUmqWKdNw3P/fRj692+Tr9kuBGtg8Y9h15vKY0MpTLsfxt8G2uL3Fv6sJClNMLgGr28Rfv8S0ml/4ZxKZcCXHsF7Bwaz/vhFRDNWTDoNV43uzjcmVDKsx6l3wgmC8MkaUhlWByOsDikVHHXJ1gtxJrWaiXYLl9qtTHHaGGY1oRGLbm0uffgw/oVPEf7Xv5oTGZMn47pzPubRIpEhnL10MntSa6gTjyOBFPInLbiqwGo3tGoHVai0cF2Y1lAdgZjTceHF01k+3N/I0mqleuNEC9ITupUasZv1pLJK9UOiRTXEiZUFlSzRL3yMcQ3VjGvYTVXgCOoWNY0RnYnNnsFsKK9iY/lgwoZz61lu1Kkx6jQYtRpMeg0GrRqTXnls1DX/OSfLvPtRPal8wmZiPyf/OWcw4/u2fZuRXChEbMMG4vkZHB+fD4JGg2nYsMIMDtPo0aiNYjCtIAhtS5ZlYqtW4XvySZLblM2cKr0e+9VXU3brLegqKooc4fmVro3ge2Y7ckbCfLGb2IrfEV26FLXZTO8//hHT8GHFDrHLEwmNDubQ1k2YbCWUesoxWm2dfldRLpwitrGB2IZ6cqHmGxJ9LxuW8RWYRrhRi365rTQc3M+2xW+ze/WKQvJLZzRx0dSZjJrzOVy9+5yXryPLMpH3FuH9v/8jU1sLgKGqivIH7scyadJ5+RrtUioKqx+DD5+AXApUarj4mzDzv8DSdru3LgRZztEY3MzGPW+SCC+jRN88q0WS1aTVwxlY+Xl6d/8cRmP7HUYvCB2JLMscSaZZlW9PtToYpTHTuvWEXavhEru1UMEx0Cx2FZ9PqUOHaHzqKcL//BdIyuKVZeoU3PPnYxo1qrjBCR1KNJiibk+gVWuoJn+CROT01QMAGp1aSVKcaA/VMmlRZkKjE4vrZ0vM6bgwZFlm1/GmQvXG1toQp1s9MGcSjPbuKyQxnKnWbayOlfVkX98RHB4wisbKgegNeky6fMJBp1ESEoVf6kJyopCsaJGwaPkxBq36jN47G5qSLFi+n1fW15LOKe8NUwa6+M85gxjd+8K1gMr6fMTWrSe2dg3xdesL910nqHQ6TKNHKzM4Jk7ENHw4Kp1IdAqC0DZkWSb24Yf4n1xAYvNmQHkdKv2Pr+C67TZ03Tv+OkHWn8C7cBtSLINhkAPXNy9Czmaove124uvWobHbqXz5pc69gbcDEAkNoUOQJZnU/hCxDfUkdjZC/gZEpddgHuXGMr4CXY8LN5SuI0jGouxasZSti94mePxo4XjPIcMYOfcKBo6fhEZ7dhe7iW3baHj4kcIbmNbtxv2971J61VWoOmsfeEmC7a/B0p9B5LhyrM8UuPyXUNHxs/PHwwleWV/LK+uP4IukAJneJcf56kUHGFa2FTmzr9XzbbbhePJDxS2WAcUJWhA6IVmWqY4lC8mND0NRojmp1XMq9DomO6yFGRw9jR2nKqw9SR08iH/hUzT9+9/NiYxpU3HfeSemESOKHJ3QkSSjGTa9e5gd7x8ll5VO+RyjRVdIVpTmZ1gov5uxlOo7VWuojkDM6WhboXiaw41xwokMBo0K0/FaDBvXoFr3IdL2bZBrTtyrzGYskyZhnTYV69Sp7W6X79FQgt8t288bG2sL7atmVnn4zzmDilKtnK47qgwYz8/gyHq9rc6rzGbMY8ZgmTgB84SJGIdUdd77M0EQikaWZeLr1uH/3ZPEN25UDup02K+6irLbb0ffs0dxAzxLqZomAq/tIRdIouthxX3biMIm6lw0xpFvf5vkjh1oy8vp8+eX0fXomN9nZyASGkKHk4ukiW9uILahgaw/UTiu62ZRZm2M9qA2tv1A845ClmWOfLSNbYveZv/Gtcj5RRtzqZ0Rsy5j+KzLKXF9toFO6bqj+H79a5refhsAlclE2U03UXbTt1FbOnEbsNr18O4P4Ogm5bGjD8z9X6j6Qrudk/FZyLLMmgON/GlNDYt3N5DL36S5rAa+Pr4X103oTbdSEwCJxBF8vsV4fYsIhzdBi3YAZnM/3PnkRoltOCqV2EkqCOdLVpLZHokXKjg2NMVIfWxXcR+TnikOm5LksNtw6cV74CdJHTjQnMjIX95ap0/Hded8TMOHFzk6oSPJpHJsW1rLlkU1pJPKIri7tw13b1vrKgu3CYNJ/Fx2BGJOx/khJRLE1q4lunIlsRUryRw71uq8vm9frFOnYp02FdPYsaj17T8xXxuI8/jSffxty9HCNfPci8q5Z84ghnQrznqFLMukDx0mvm6tMoNj3TpyoVCr56hLSjCPH4dlgtKiSj9gQJf8PykIQtuJrV+P/8kFxNetUw5otZRe+SVct9+Ovnfv4gb3GUnxDOF3DxNbXw+AxmHAM38UGlvr96dsMEjN9TeQPnAAfWUllS+/hNbVsTt1dFQioSF0WLIskzoYVqo2PvJDNl+1oVNjGqFUbeh7d/62XGci0uhn+9L32LH03cJgeZVKTf+x4xk59/NUDhuJ6hSDaHORCI1PP03gTy8ip9OgUlH65S/j/u530JWXX+hv48IJH4UlP4EdbyiP9VaYei9MmAe6jturNpzI8LfNdby0toYDvljh+Pi+Tm6YWMllQyvQa0+flEil/fh9S/D5FxEIfIgsN9/gGwwVuF1zcLvnYLePR60WOxYF4XxK5iQ2NsXyA8YjbI3EyX3sCu0ii5HJ+QTHJLsVm1bszARI7d+Pf8FCmt55pzmRMWMGrvnzRR9c4YzkchK7Vx9jw78PE29KA1DW08qkq/rTe6hTXHt2UmJOxydLHzlCdMVKoitXEl+3TrlnyFPp9ZgnTFCSGFOnoK+sLGKk5+aQP8Zvl+zlrW3HCm21Pj+iG/fMHsgAz7nN+DhXsiSR2ruX2FqleiO+YQNSLNbqORqXC8v48YUWVbpevcRrliAI50V840b8CxYS+/BD5YBGQ+kXv4jrjtvR9+lT1NhOR5ZlElt9hP59ECm/ccE8ppzSK/qiOc2cskx9PTVf/waZY8cwDBlC5R//gEasW19wIqEhdApSPENss5fYhnqyDfHCca3HXKjaON2LUVeUy2bZv2Et2xb9m9pdOwrHHd26M3LOFQydNhuj1YqcyRB8/XX8v3uSXFBJgJgnTqT8gfsxDhlSrPDbXjquzMhY/RhkE4AKRn8DZv4YbB03gbPrWBMvrq3hzS1HSWTyA2/1Gr5ycU+un1jJ4IozvwnLZiP4G9/H51tEY+MKcrnmmyatthSXayYe91ycziloNKbz9r0IgqBoyuZYG4qyOl/BsTvWeiirRgWjbOZCBcfYEgvGTraI9mlS+/bhX7iQpnfebU5kzJqFa/48TEOHFjm6jkmWZXZEE9SnMvQy6qmyGLvEgpgsyezf5GXtPw7S5FOqhEtcRiZ8qR8Dx5aLtlFdVFed0yGl0yQ2blSSGCtWkD58uNV5bfduWKdNwzp1KpaJE1GbOtd14L6GCL9Zso9/71Ba0apVcOWoHnxn1kD6utpH5bqczZLcuTNfvbGW+KbNyKnWCTht926F6g3zxImde7OaIAgXRHzLFiWxsWqVckCtpuQLn8d1xx0Y+vUrbnAtZPwJQm/uJ7U/BIDWbcLx5QEY+tk/9WPThw9z+BvXk2tsxDRmDL2fe7bTvc+1dyKhIXQqsiyTPhIhtr6exHYfcibfx1irwjTUhWV8BYZ+pV3ipvuzaqw7wtZFb7Nr5VLSCeXmXKvX07/fILpt2oF5/0EA9P364bnvXqzTp3fevz9Zho/+Cot/Ak11yrFeE+Fzv4Tuo4sb21lKZXO8+1E9L66pYWNNsHB8oMfKjZMquWp0D2zG85Psy+VSBIMf4PUtwu9fSiYTKJxTq02UlU3B7ZqLyzUTne7C9xwWhK7Al87wQVBJcKwORTicSLc6b1SrGFdqYbLdxhSHlRE2M9pOugib3LsX/4KFRN57r5DIsM2ZjWv+/M6dlG8jkiyzqSnOv3wh/u0LUZdsrs6bWGrhF4N6MsTaOW/kZFmmdneANX8/gL82CigthsZ9vi8XTe6O5hOqGoWuqzPO6cjU1xeqMGJr1iDHmzeSodVivvhiJYkxbSr6/v077z1DC7uPN/HY4r0s2tUAgEat4iujlcRGL6e5yNG1JqXTJLZuJb52HbH160hs2w6Z1q3U9H36FKo3zOPHo3U6ixStIAgdXWL7dvxPLiC6YoVyQKWi5IorcM27A8OA4s3hlLMSkfdraXq/Vun0olVRMqM3tmk9UZ3BNV1y925qbvwmUiSCZeoUev3ud6g6QAvFzkIkNIROS0pmiW/1EltfT+ZYi13jZUbM4yqwjCk/qR9eZyDFM6SPRkkfjZKpjZA+GiUXTaPSqlHp1KgNWtRmLWqzTvndpPxZ0sscr9nLvo2r8DXWkZaSpHMJrMkEwyZOZvTd30NvsRb722s7RzfDuz+E2rXK49JeMOdnMPQrHXJOxtFQgpfX1vDahloaY8qCplat4rJhFdwwsZIJfdu2JYYkZQmHN+HzLcLnW0Qy1dw7WaXS4rBPwO2+DLd7NgaD2AkmCG2lNplmdX7A+KpgBG862+q8TaNmkt3KcJuJgWYjgyxG+pkMHbqKI7lnL/4FC5RERp5tzhxcd87HWFVVxMg6npwsszYU5d++MG/7wtSnmxe+TGo1/c0G9seTJCUZjQpu6eHm3r4VnarNWcOhJta8uZ+je0IA6IwaRs/pzchZvdCLmW3CWehIczrkbJbE1q2FJEZqz55W5zVuV76N1DQsl0xCYytuy6Vi2lEX5teL97B8jw9Qrru/Nq4Xd80YQHd7+0z2SvE48c1bCjM4kjt3Qn7e4gmGwYMLA8bN48Z26X9jQRDOTuKjnfgXLCC6bJlyQKXCdvlluO6Yh3HwoAsaS/JAiNCb+8nmK20NA+04rhyA1nV2r9PxTZs4cvMtyMkkJVdcQfdHH0Gl6TzXwe2ZSGgIXUK6LkJsQz3xrT7kEzui1CpMFzmxjO+GYYC9Q7YJkFJZMkdjpOuUxEWmLkK2MfnpH3gGcnKWdC5JhhS6EjPWbi4MDmtzQsSsRVP484kkiQ6VroMshkXqYel/w9Y/AzLozDD5HrjkbtC1z5uP05EkmVX7/by4poZl1Q2c6HJQXmLg6+MruW58LzwlF372hyzLRKI7C8mNWGxfq/MlJaPxuOfgds/FbO57weMThK5ClmX2xVOsyic4PgxFCWdP3iWsBnqb9Aw0GxlgNjDQYmSQ2chAs4FSXftdwE1WV+N/cgGRxYsLx2yXXYZr/jyMgwcXMbKOJSPJfBCKFJIYjZnmJJhVo2auq5TPu0uZ4SzBrFFTm0zzk31HedsfBqBcr+WnA3pwlcfeoXdnB+tjrHvrIAe2KIuTaq2K4dN6MuZzlZisnW9DjNA+tIc5HdnGRqKrVhFbuZLo6g+QmpqaT6pUmEaOxDptKpapUzEOGXLK+Xtd2aaaIL9ZspdV+/wA6DVqrhvfiztnDCjKdfiZyDU1Ed+4sTCDI7V3b+snqNUYhw3DMmECxmHD0PXsgdpkRm02oTYpv9DpOvRrvyAIbSe5axf+hQuJLF5SOHahNh3lomnCbx8ivtkLgNqqw/6FfphGus/5NSu6ciW18++EbBb7dddS8eMfi9fBC0AkNIQuRUrlSGz3EdtQT/pIpHBcYzdgGuZC6zSiKdWjKTWgKTWgtujaTaJDzuRIH4uRyScv0nURJat8ip9MjdOIvqcVfU8buh5WtA4jck5CzkjIySxSPP8rkSEXThDfuov0oTrQmFDpLWhsTtCYQDr5c39WKp26VdJD3TLpYdKe+pxJh0pzgf6+M0lY+ySs+jWklfYRjLgGZv0ESntcmBjOk1A8zV82KUO+Dzc2l/5fOqCMGyZWMmtIObp2tNs6Hj+Ez7cIr28xTU1bWp2zWAbids/F7Z6LzTpUXAgIQhvKyTI7IgnWhqLsiSfZF0uyL546ZZLjBI9ey0CzkYEWJcExyGxkgMVAhb54CxjJ3buViowTN0cqlZLImHfhd311VClJYkUgwr98IRb5mwi1+D9g12q4zFXKF9ylTHXaMJxm8XJpYxMP7qsrtDm7xG7lF4N6MtjSvhfwPi4aTLHhXwfZvaYeWZJBBVUTKhj3xb6UlHWsjQ5C59GWczpkSSK5c2dhFkbyo48KbfoANKWlWKZMUZIYkyejdTja/PvtDNYdbOTXi/ey7pDSgtWgVXPDxErumN4fl9VQ5Og+m2xjI/H165UZHGvXkq6p+fQP0mgKyQ2VqTnRoTabUBlP/We1SXms69ED08gRogpEEDq55J49+Bc+1aotbFvNt5MlmfimBsLvHEKKZ0EFlvEVlF7eF7Xp/G3UCv/73xy79z6QZcruuB3P97533j63cGoioSF0WZn6GLH19cQ2e5GT2VM/SaNCU9Kc4NCU6tGUGNDamx+rrfrznvSQsxKZ+hjpOiVxkTkaJdMQO2WCQVNqQNfTWkhg6Hso1ROf+jVyOcJvvonvN78l61N2H5pGj6b8Bw9gGjkSWZaR05KS9IimOLp9N0c2bCJUV49eZcSgMWEx2ylz98JmcUJaRopnlDeJc3i1UBk16DxmDP3tWCf3OP/D3GUZdv8TFv0XhPIX5T3GwOUPQ69x5/drtbEddWFeXHuYt7YeI5VV/nPYDFr+Y4wy5HuAp/23CEulGvD5luDzLSIYWossN/8sGo09cLuUyg27fSwqlSjdFIS2JssyvnSWvXEluaEkOZLsj6c4njp9KxSbRs0As5GBFkOhddVAs5HeRn2bzehI7tqF78kFRJcuVQ6oVJR87nJc8+ZhGDiwTb5mZxLPSSxrbOLfvhCLG5uI5povMlw6LVe4S/m8284ldiu6z/hvmMxJLKz18tuaBpKSjFYFt/Z08/0+FVjbeRuqZCzD5vdq2L68jlx+BlufES4mXtmPsh7t//1U6JrOdk6H3Zqje3o/du8ODAe2oIqEWp03XDREaSU1bRqmESNE+4yzJMsyHx5o5P8W7WHzkRAAZr2Gb17Sh9um9MNh6VjVXpnjx4mtW0d8/QZS+/aRbWhASiSQksmTZnGcNY0G89ix2ObMwTZ7FrqKivPzeQVBaHdS+/bhX/gUTe+805zYmD4d153zMQ0ffs6fP9MQI/j3/aQPK5WGugoL9q8MwNC7bdaYg6++Sv1PfwaA54EHKPv2t9rk6wgKkdAQujw5kyPxUSPpugi5UIpsU5pcOIUUSX+2hXk1aGyGVpUdhWSHRad8DlkGSVZeoyUZZBlZaj6ODFI6R+a40j4qczwGuZO/uNqqU5IWPa3o8smLs5kDEvvwQxoeeZRUdTUAup498dx7L7bL5n7qDttQ/XG2LXmHj5YvJhlVqlzUGi2DJl7KqLmfp9vAKkhLheRGy99zJx4nsiedk5Mn33SpTFpKZ/fGMrH7+ancqN+hzMk4vEp5bOsGs38Gw6+GDlIun8zk+Nf247y4toZttaHC8aoKGzdO6sOVo7pjMbTfljCfJJMJ429cjs+3iMbGlUhSonBOp3Pics3C456Lw3EpGk3H2NkmCJ1JJJtjXzzJvlhK+T3/58OJ1GkL+vQqFf3MBqV1VSHRYaC/2YjpLCvHTtWHt+Rzn8M1f15RBwx2BJFsjiWNTfzLF2JZY4REi17pFXodn88nMSbYLWjOoeLmSCLFj/cf5V2/cgPZzaDjpwO68yV3+2tDlUnn2L6sli2LjpCKK0n1bgNKmXRVf7oNsBc3OEE4SyfN6TgeJb6zGs3uDZQe305J+BDqFq/cWY2RgKOKph4jYOh4bP17XLA5HV2BLMus2Ovj14v3sr1Oac9nNWi56dI+3DylH6Wm4g98P1dyJqMkNxIJ5PzvUiKBFE8gJ5v/LCXiyMlk/s/5x4kkUjxOav9+MrW1rT6v8f+zd97xcZ1l2r6md81opFHvxbbce43tuMhJHBLSHAgkAQJslrLLB1vYRljYQtmFhYWEhd1lKaGlk+Ikkrtjucbdkm1ZvWuk0Yymt3O+P4480sR24iJZxedK9BvpvMcz76ic8t7Pc9/z5mLZuJGUykq0RUXj8+ZkZGTGlHBDA33/9VMG33gjkeNjWrMax+c/j2H+/Gt+PjEaZ3BHG9497RAXUWiUpFQWYl6Vg2KMnSv6fvoznP/xHwBk/8u/YHvwgTF9vVsZWdCQkbkCYlwg7o0S94RHfESSP/eGb8iW6f1QGNRJXReaPAsqq/aGbibCTU30fue7+HbtAkBpsZD+uc+R+ujHUWqvTRiJRsKc3/8OJ6q20nVhOCDQUVDEvE2bqbjtdrQG41U/nxgXEYJRBH+USLsP3zsdkrADqDON2O4pQV92nS3uPifs/Gc4+isQBVDrpYyMVf8PdJOj6rK1P8BvDrbw3JE2BgJSBZRGpWDznGweX1HIwoLUKXWjGY8Hcbneodf5Nn19O4jFPIkxlcpEWtpaHOmVpKevQ62W29JlZMaTsCDQGAhzITAkdAxZVzUEQgSvYIWiAPL12iH7Ksm6qtwkZXakXiGnI3jqNH1PP504h6FQkHL33aR/7k/RlZaOzZubArijMd7ukzoxdg94CY/4meTrtdztsPIhh42FKUaUo3weqe7z8A/1HbSEJBuq1alm/rU8j/IJYEMVjwucreni8OtN+D3S/NJyTSy/r5TC2WlT6pwqc2si+P34DxxIBHrHuruTxsXsQkIlC3Glz6JTkYfXfeWOjtHO6bhVEUWRbXW9fL/6PHVdkuCbolfz2dUlfOq2YsyTtChpNIm0teGt3oZ32zaCx44l2Z/pysulzo3KjehmzJCP0zIyU4xwUxP9//VTPK+/DnHpnGRauZL0L34B48KFV/UcofMDDLxygbhLypbVV9ix3VuKOvXmXHuKokjvv/07rp//HJRKcn/4A1IqK2/Ka99qyIKGjMwNIMZFBF+E2EixY3Doc3cYIRAFpQKFAlAoQKkY/lqpAAXShZhSgUKlQJ1pRJsrdWCo7PpRu0iLDw7S98xPcP3mN1I7sFpN6iOPkP75z42KD25P4wWOV23l7L7dxCJSaKHWYGDmmvXMq9xMen7hNT+nKIj4D3UzWNUs2VgB+llp2O4uQW2/ypNRLAKHfgq7vwvhoUDDWfdD5TfBVnDNc7rZxAWR3ed7+fX+Fnaddyau53NtBj62rICPLMmfNB68N4IgRHG7D+F0VuPsqyYcHr4hVyg02FNX4HBsIt1RiU6bPo4zlZGRGYkgirSFIknWVRe7O9zvk9ORrlEnWVcV9HRh//UvMb61FQWAUjksZJSU3LT3M5noi8R4q8/D671u3nF7iY24ii816KROjAwbc82GMV8QCsUFftzay49aewgLIhqFgifzHXy5KBPTONjYiKJIw1EnB19txN0j5U5Z0vQsu7eE8iWZKCdIdpqMzLUiiiKR5mYpzHv3HgKHDyOOsAFS6PWYli3DtHYN5jVr0OblJf37sczpkElGEETeOtPNf1Sfp75XyvJLNWp4cm0pj68oxKiVhQ2AaG8vvh078FZvw3/wIMSGrWk1eXlD4kYlhvnz5HB6GZkpRKSlhb6f/QzPK39MCBvG5ctxfOHzGJdc3iY8PhjB/XoDwZN9AKhStNjuLUU/6+YXqYiiSNfXvobnhRdRaDTk/+ynmFasuKlzuBWQBQ0ZmSmMKIp4XnqZ3u99j7hLCqQzrV1D5le/OiaLQCGfjzO7t3Oi+g0GujoT2/Nmzmb+prspW7IclfraWqqFQJTBba34DnRK3TBqBZbVeVhuz0d5pRslUYTzb8Hbfw+uBmlb9jy489tQuPI6393Nw+WP8NyRNn5zsIU217Dt0pppDh5bXsj6GRmobtEFF1EUGPSewumswumsIhBoHDGqwGpdRMZQqLjBkD9u85SRkbkyoijSF41dYl1VHwjR+T45HcZgkOJwgBm5WUzPTKfcqKPcpKdIrxuznI7JRHc4yhtON284PRxw+5IaSGeY9IlOjBmm0SuYuBZagmH+vr6Dbf1SgUGuTsM3ynK522G9afNpq3Ox/+UGnK2SZabBomHRXUXMXp2LSiMvhslMPoRwmMChw/h278a3Zw/R1takcU1eHua1azHfvhbjkiUo9ddeoXq9OR2OAgvlSzKZeVsOulEMXp1KxAWR10928sNt9TT2SZ3p6WYtf7q2lEeXF6LXyKLQReIeD75duxisrsb/zj7EUCgxpnKkY9mwAUtlJaalS1FoJr+Fl4yMDETa2+n/6c9wv/xyQtA0LllC+he+gHHZUhQKhVQIe7ALz1vNiOE4KMC8MoeUTYUox7HrTYzH6fjyV/BWVaEwGin8v59jmDdv3OYzFZEFDRmZKUqsv5+urz2V8BjXlpSQ+bd/g3n16jF/bVEQaD19kuNVb9Bw5CCiOOSDaEtlzoY7mLvhTixp11ZJH+3x436tkfAFNwDKFC22u4oxzHckL4T01kk5GY07pa9NDtjwdZj/MVBO3JsCURQ51ubm2f0tvH6qi8hQyLfVoGHLojw+vryQ4nTTOM9y4uH3X8DprKLXWYXXeyppzGyuwDEkbphN0+W2dBmZSYAvFuf08VMcq9pOvcdHa1YOLVm5dGZkEb9C9aVGoaDYoEuyrrqY02Gc4lYobaEIb/RKIsbhQX/S2FyzgbsdNu7OsFJmHH+Lp4tU9Xn4+/oO2oZsqG5PtfAv03IpHcM59rYMsv/lBtrPDgCg0amYX1nA/I35aPXyQqvM5CLa0YFvqAvDf+BA0sIuGg2mJYsxrVmDec1atMVFY3b9c0lOR7c/8XnINyxOaw1q5q3PY+76fPQmeaH5csTiAq8c7+Q/t9fT6pI6xzJTdHxhXRkfWZKPTj1x72HGAyEQwPfOO3irt+HbtQvB602MKVNSsKy7XRI3Vq1CaTCM30RlZGRGhWhHB33//d+4X3xJchwBDIsWkfro5wg1GIm2S51umjwzqfeXo82dGLbiQiRC+5/+Kf6a/aisVgqf/TW68vLxntaUQRY0ZGSmIN5du+j6+38g3t+PQqPB8aU/x/6JT4xLtcpgn5NTO97m1Pa38bulhQSFUknpomXM33Q3BXPmXfWNliiKhGr7cb/RlPBE1BZYsGwoQJ8notj9bTj8vyDGQaWF5Z+D1X8J+ol7DAlG4rx6ooNf7W/hTOdgYvucXCuPrSjknrk5GLTyTczVEAp1SrZUzircnsOI4nDVoEFfgMNRSbqjEmvKApRKeQFLRmaiETh6jL6nn8a/b5+0QaXCeu+9pP/pk5CfT1MwMmxdNWRjdeF9cjoA8vQaybpqhNBRbtJjv0JOx2SgMRDmDaeb151uTniDSWOLUox8yGFjs8NKoWHiWhIG4gI/aunh6dZeIqKIVqHgcwUZfKkwc1RFKHdPgIOvNnLh3V5AsseZvSaXRXcVYUy5tuwwGZnxQoxGCRw9hm/Pbvx79hCuv5A0rs7MxLxmDea1azAuX4HKPP4FMH5PmKYTfZzc2c7AUCaeRq9i7ro85m8oQG+WhY3LEY0LvPhuOz/acYEOt3R8z7Hq+eL6crYszkMzxUX660GMRPAfPIS3uhrv9u3E+/sTYwqDAfNtt2HZVIl57VpU8rqSjMykJtrVRf9//w/ul15FW3YnmpINKJQqUIP1rhLMK3JQTLCubcHvp+WJJwidOIk6I4PC3/7mEstHmetDFjRkZKYQQiBAz3e/i/v3fwCk4LScf/839NOnj/PMIB6LcuHwAY5XvUF77enE9tTsXOZVbmbW2g3ozVenpItRAe877Xh3tiFGpE4GpcKNQXkAvfIg+oocFHf+I9gnrrd6o9PHswdaeeHdNgZDUvukVq3knrk5PLaikHl5N8+CYyoSjQ7g7NuO01mNy7UXQQgnxtRqG+lpt5Oevo60tLVyqLiMzDgTOHqUvh8/jb+mRtqgUmG978OkP/kk2oL3zzsSRJH2oZyOCyOsq+oDIVzRK1uhpGnUlBt1TBsKIi8fEjxydZoJd+wVRZFzgRBv9Hp4w+mm1j9cja0AlttM3O2wsTndSo5+ci3SNwXC/F19OztdUnVtrk7DP5fncmf6jZ0D/e4wh99oonZfF6IgggKmL81i6T3FpKTL1boyE59oby/+ve/g27MH/759CD7f8KBSiWHBgoSIoZs+cbtQRUGk4ZiTI1ub6O+QhA21TsWctbnM31gwKYRFQRQ46zqLiEiFvQKlYuxFhXAsznOH2/jxzgv0DErXsPl2A3++vpz7F+SiloWNyyLG4wSPHZNCxauriXYOWyCj0WBavhzLxo1YNqxHnS7n7snITEaCZ/oZeOU8gldaQ4l2HCF86g/ophWS/vnPYV67dsKdE+NuNy2PPU64vh5NQQFFv3kWtcMx3tOa9MiChozMFCF46hSdf/XXRJqbAbB/8pM4vvz/UOomXoVmX1sLJ6q3UrtnB5GgVH2k1uqYsWot8zdtJrOk7KqeJ35yG95X9+P3LUFkuBpNoVGiK0/FMNOOfoYdlXli3CzF4gLbz/by7IEW9tb3Jbbn2w08uqyQhxfnk2qaGHOdSsRiflyuvTidVfT17yIW8yTGFAo1NtsS0tM3kJ62DqOxaPwmKiNzixE4cgTn008T2H9A2qBWDwsZ+TeegdMXiQ3lcyTndHS8X06HSkmZcci6yqhPhJMXGXRobmLFlyiKnPYFecPp4XWnmwuBYVFWpYDbbBbudli5y2HFoZ3clc6iKPJWn4d/qO9I/GzW2y38S3kexcZru4YJB6IcfbuVkzvaiEWlgoeiOWks+3Ap6XkTw35ARuZyiPE4oVOnJCupXbsJ1dYmjatSUzGvWY157VpMK1eistnGZ6LXiSiINJ3s4/AbTfS1SeKMWqNk1tpcFlQWYLJOrPuV3kAvNZ011HTWcKDzAANhqcs8w5jBxoKNbCzcyMKMhajG2M42FI3z24OtPLOrgT6fdB4oTjfxpQ3l3DMv55bN1LsapM7+WrzbJHEjcqFheFChwLBoISmVlVg2bkSTmzt+E5WRkbkqYu4w7lcbCNVKXViqVB2Wten4dz7HwB/+kLBf1M+aRfoXPo953boJJWxEe3pp+fjHiba3o5s+ncJf/RKV1Tre05rUyIKGjMwkR4zF6PvZz+h7+hmIx1FnZpLz7W9hWrFivKf2gUSCAere2cXxqq30tTYntmeXTWfeps1MX7EatfYyC/x9F+Dtv4P6twEQ9Q7Cs/+JYHQRobNu4p7hhR8UoC1IkcSNmWloHMYxfleX4vSG+cPhVn57sJVOj3SiVShg3fQMHltRyNpyB0r5huSmIAgxPJ6j9PXvoK9vB4FAQ9K40VhKevp60tM3fKA1lSAKnOo7xem+01xwX6DJ00QgGiAuxokLceJinJgQIy7GERERxaGPi/8NfQ7SDfIM+wxm2GdQYa9gun06Js34W0bIyIwFgcOHcT79DIEDw0KG7f77SXvyT25KC7Y/FudCMDwkdIQTgkdTMEzsCle7agUUG3SUGnVkajU4tBry9VpWpZrJG6WuCFEUOTYY4HWn1InRMpQxAaBVKFhjl0SMO9Ktk9oy60r443H+s6WXZ1p7iQ7ZUH2hIIM/L8zE8AHVyLFInJO72jn6VgvhgFSxl1ViZcX9peSU227C7GVkrp3YwAD+d/ZJXRh79xJ3u5PG9bNnS4Hea9egnz0bxRVyhCYToijScqqfw2800dsidWapNEpm3ZbDgk2FmFPHR9gIx8Mc7TlKTWcN+zr3UT9QnzRu0pgQRZFALJDYZtfbWV+wnsqCSpZkL0GjHDtxORCJ8ev9LfzX7gYGApLwW55h5v9tnMZds7Pk+4irINzYKHVubNtG6FRy7p5+5kwsmyqxVFaiKy0dpxnKyMhcDjEu4qvpYLC6RXLnUCqwrMnFsr4A5ZA1d6yvj/6f/x8Dv/sd4lDBrK6igvTPfw7Lhg0T5vwZaW2l+eMfJ+7sw7BgAQX/+z8ojTd/fWqqIAsaMjKTmEhrK51//VWCx48DkLL5LrKeemryVW2JIh3najlRtZXzB/YhxKXFCL0lhdm3b2Re5WZsmVkQdMPu78Khn4IQA6Ualj4Ja/8aDLbEc0W7/IRq+wnWuYh2+JJeS51uQD8zDcNMO9qClDHzWBRFkSMtA/xqfwtvne4iGpcOoalGDR9ZUsDHlxWQb5dPXuNNINBMX98O+vp34HYfRhRjiTHJmmot6enrE9ZUoihy1nWWN5vf5K2mt+jyd43JvBQoKEwpTBI5ZqTNwK63j8nrycjcDPwHD9H39NMEDh2SNmg0kpDxJ3+CNm/8qyOjgkhTMJzo6rgQCHM+ID0G4sIV/12pQcdqu4W1qWZWpVpIuYbw1rgoctjj53Wnm61OD50jukcMSgXr7Cl8KMPGxrSUa3reyUxDIMTfne9g94C02Jmv1/Iv5blsSr+0ik2IC5zd382h15vwu6ViBnuOieX3lVI0J21CVebJyIiiSLiuLhHoHTxxAoThY4vSYsF02yrMa9ZiXn3blLbEEUWRtloXh99oortRypBTqhXMXJXDwjsKsdj1Y/76TZ6mhIBxpPsIofhIOz8FM9NmsjJnJatyVzHXMRdBFNjfuZ/qlmp2te1iMDKcfZeiTeH2/NupLKxkRc4KdKqxEWZ84Ri/2NfEz/Y0JixrK7JT+PLGcipnZsrHvKsk2tmJd9t2vNu2EThyJOnvUFtcjKVSEjf0s2fJ31MZmXEk0uZl4KV6okNZTNrCFFLvL0OTdfnCv5jLhev/fsHAb36DEJAEaN306aR/7nNYNlVOCGEjdO48LY89hjA4iOm228h/5mkUlyvilflAZEFDRmYSIooinhdfpPtfv4UYCKA0m8n6+lOkfOhDk/6iy+8e4PTOak5sexNvn1PaqFBQXJTBPOVhijUtKBVA+Sa4418hvfx9ny/mDhOqk8SNcIMb4sOHMqVJjX5GGoYKO7ppqQmF/4bmH47x8rEOnj3Qwtlub2L7ggIbjy0vZPOcbPSaW2NRarIRjQ7icu0ZEjiSralARUCdwxFfhD0DHvpi0sWQSWNiSdYSym3llNhKsGqtqJQq1Ao1KqUKlUL6UCgU0sfF/xTDj6Io0u5tp85Vx1nXWer66+gN9l52jhnGDEncGCFy5JhyJv3fvczURRRFAheFjMOHpY0aDbYHHyD9s5+dFDYPgijSGY5S75e6OJyRGM5IjFp/kOODAUZKHUpgQYqRNakW1totLEwxon3PzVNMEKlx+3jd6ebNPg/OyLCQalIpqUxL4W6HjfVpFkyqW/N8IYoibzg9PHWhIyHy3JVu5d+n55OmVSOKIo3HnRz8YyMD3dINq9muY9k9JUxbJlcry0wc4j4f/poaqQtj9x5iTmfSuG7aNMxr12BeswbD/PkoNJPbQu5aEUWR9nMDHH69ia4L0nWXUqVgxopsFt1ZOKqZN56wh4NdBxNWUu8tSnEYHKzIWcGqnFUsz1n+vkUkUSHK4a7DVLdWs6N1B66QKzFmVBtZk7eGjYUbWZ27GqNm9AuYBkNR/ndvEz9/pwlvWDqHzM2z8uXKadw+zSFfF14DMZcL344dDFZXE6jZjxgdLixQZ2dLmRuVGzEuWoTiFj0ny8jcbIRQDM9bzfgPdoEICoMa611FmBZnXVVBamxgANcvf8nAr59F8A+JIWWlpH/uc6Tceee4/y0Hjh2j9YlPIwaDWO66k9x///dxn9NkRBY0ZGQmGTGXi66nnsK3bTsAxiVLyPn2tybFotC1IAhxmo4d4fgrz9J8vimxPUUXZ+6aNczZ8jmMVtu1PWcoRuj8gNS9cXYAMTS8iIRagb4sFX2FHUNFGqprDCms7/Hy7IEWXjzagW/oxkKvUfLhebk8tqKQ2bmyP+JkQhBiNPVs42TLs8R9x0hVhpLGfZgxWVcwp/BRHPbl72tNdT30B/slcWNI5DjrOkvLYMtl903RpiQ6OS4KHUXWItSjPCcZmWtBFEUCBw7gfPppgkfeBUCh0WB96EFJyMjJGecZjg6eaIwat4/dAz72urw0BMNJ40aVkpU2MyttZmxqFYcH/bzd50kKLLeqVWxKT+FDDhtrUy3o5bDXBP5YnB+09PBfbU6iokimVs1TFjvC1k56m6XqaL1Jw+LNRcxak4NaLhiQGWdEUSTS2Ihv9x58u3cTePddiA1fbyoMBkwrViQCvTXZ2eM424lFx/kBDr/RTMc5Ka9CoVQwfXkWi+4sxJZx7aJAXIhzuv80NR1SF8apvlMI4rAErVFqWJi5kFU5q1iZs5JpqdOuSwiIC3GO9h5lW8s2trVuozcwXJSiV+lZlbuKjYUbWZu3FovWcs3P/364AxF+tqeRX9Q0E4hI55WFBTa+UjmdVWVyl9q1Evf58O3ejbd6G749exADwxZjKrsd8/p1pFRWYlyxAqVcUS0jM+qIokjwZB/u1xsQvJK4aFyQgfXu4uvKRY273bh+9Wtcv/41glcqNtWWlJD+uT8lZfPmcRURfO/so+1zn4NoFNvDD5P1jX+Uj9nXiCxoyMhMIny7d9P59/9AvK8PNBoyvvTn2D/1qamp5rqaoOof4OzrDET0nPQWcXowh1BIOrGp1GqmLb+NeZvuJmfajGs++ItxgXDzYMKaKu5KXrDW5FswVNgxzExDnWm87PNH4wLVtT38en8L+xv7E9uL0008uryQhxbmYTXeWpV2kx1XyEVVcxVvNr3J0d6jie0ZagWbM3OZYxRRh5uSrKl0umwKCz5LTs7DqFSjV0n4XvxRP+dc55JEjgvuC8SE2CX76lV6ylPLE10cFfYKylPLx8wCQUbmIqIoEti/H+ePnyZ4VPobUmg02LY8RNpnPzvlF+/aQxH2DHjZ4/KyZ8CbJFyMxK5RcVe6lbsdNm5LNV/SxSGTzBlfkM8eb6RxqHJ2xdkgG89FWLw+nwWVBWgNsoArM34IwSD+gwfxD1lJRTs6ksa1RUWY167BtGYNxiVL5IXQD6DzgpsjW5tpq5W6HhQKmLY0i0V3FZJ6BZuRi3T7u9nXsY99nfs40HUAb8SbNF5sLU4IGIuzFmNQj+5128V8tW0t26huqabDN/y7oFFqWJGzgo0FG1lfsB6rbvSKnfp8YX66u4Ff7W8hHJNEm6XFdv6ichrLStJG7XVuJYRQCH/NfrzV1fh27CDuGe7cVppMmG+/HUvlRsyrV6M0ybl3MjI3Sqw/yMAfGwifl0RtdboB232l6MtSb/i544ODuH79a1y//BXCoFQQoy0qIu1Pn8T6oQ+hUI/PdeTgW2/T8ZWvgCCQ9tnPkvEXXxmXeUxWZEFDRmYSIASD9P7bvzHw298BoCsvI+e730VfUTHOMxsDwl7Y8+9w4BmIR0ChgsVPwLq/I6o2cX7/OxyveoPuC+cT/8RRWMz8TXcz47a1aPXXfmMiiiKx3gDB2n5CtS4ibck3Pyq7HkOFFCquK0qh1x/hd4da+d2hVnoGpWpcpQI2VmTy2IpCVpWmy3YXkwhfxMf21u282fQmB7oOEBeHFyAXZS7irqK7qCyqTFgPxGJe+vtHWlO5AdBo7ORkbyEj404sljk3pcIiEo/Q4G7grOsstf21nHWd5dzAOYKx4CX7qhQqiq3Fw5ZVaVL4eIpWPsfK3DiiKOLfV0Pf008TPHYMAIVWi23LFtI++xk0WVnjPMObjyCK1PqC7BnwcXTQTyAuUGjQcbfDynKrGbV8nrgq3L0BDr3aSO2xXqrnG3m3TPLWn2XQ89O5RZQZx9ZrX0bmckTa2qQujD27CRw8hBge7s5SaLUYly5NdGFoCwvHcaaTl+4mD0e2NtNyaqhoSAHlizNZdFchaTlmAIKxIO/2vMu+jn3UdNbQ6GlMeg6LxsLynOVSFkbOKrLNN09Uv5i7Vt1STXVLNc2DzYkxlULF0qylbCyUxI10w+jkpfQOhnhmVwO/PdhKZCj76baydL5cOY1FhTe+KHirIsZiBI4cwVtVjXfbNmK9w104Cq0W0223Sbkb626fdFmWMjLjjRgT8O5tZ3B7G8QEUCmw3J5Pyu35KDSjW/AT9/kYePZZXP/3i4RIqSkoIP3JJ7Hee8+42D4OPP883V97CoCMv/wL0j7zmZs+h8mKLGjIyExwgqdO0/nXf02kSbJdSn38MTK+8hWU+il2Ay8IcPw3sP2b4B+6SCxZB3d+CzIuFW66G+o5Ub2Vs+/sJhaNAKA1GJm1dgPzKjeTlpd/3VOJD0YInpXEjdCFAYgNH/6CKtgbj/IOUQ4Qw2jW8tElBXxsWQE5trGrzpcZXUKxEHva9/Bm05vsad9DRIgkxmamzWRz8WbuKLqDLNP7L8LG42G6ul+kpeWnhELtie06XTYZjjtwZNyJzboQheLmdVHFhTit3tZhy6p+qZtjIDxw2f1zzblJIscM+wwcBtl/WebqEEUR/zv76Pvxj6WAW4aEjIcfloSMzMxxnqHMZMXvCXNkazO1ezsRBOk8XL4kE+/tDr7W1YMrGsegVPLP5bl8LNsuH7NkxhQxEiHw7rtDIsYeIo3JC+fqnOwhAWMtpmXLUBpHPzfhVqW3ZZAjW5tpOtEnbVCAqjRAbeFu9oV2JF3DKRVKZqfPTnRhzE6fPSEsOEVRpMHdQHVrNdtatnF+YLgwS6lQsjBjIRsLN7KxYCOZphs/b3Z5gvx4xwWeO9JGdCg/8PbpDr5SOY25ebYbfv5bGVEQCJ08yWB1Nd7qbURbW4cHVSqMS5dI4saGjWgyM8ZvojIyk4Bws4eBly4Q6x0K8C6xYru/DI1jbM+hcZ+fgd/9FtfP/4/4gHSPrMnLI+3JP8H24Q/f9JDu/v/9X3r/7d8ByPqnb5K6ZctNff3JiixoyMhMUMRYjP7/+R+cP34aYjHUGRlkf+tfMa9aNd5TG31a9sNbX4UuaTEMe4kU+D3tTqnP/H0I+rzU7t7O8ao3cHcPh/vlz5rL/E2bKV28HNUNtBAODobYW92I51Qfc0IiqQxXCQhK0JfYMM5KQ1+Rhtom2/lMZKJClP2d+3mr6S12tO3AH/UnxoqtxdxVfBd3Fd1FkbXomp9bEKI4+7bR27uV/v5dxOPDnrtabTrp6RvJcGwiNXUFSuXNt5oQRZGeQM8lIkenv/Oy+9v19iSRo8JeQZ4lD6VCtsWRkRBFEf/evTiffprQiZMAKHQ6bB95mLRPf0a+iZe5bsLBGMeqWjixvY1YRKowLpiVxvL7SnDkS/7z3eEof1bXwt4BHwB3O6TA8FTN+C9cykwdoj09+PYMZWHU7EcY4aePSoVx4ULMt6/FvGYN2rIyWVQbI9whN/u79nPw1Akihy3kOocLnZpST9JUdpjZFWWszFnJ8uzlo2rlNFa0DLZQ3SKJG2f6zySNzXPMo7Kwko2FG8k131hGYpsrwI921PPi0Q7iQ8Jw5cxM/t+6MkpTTURCMaLhONFwfPjzUByVRknx3HTU2iloazyKiKJI+Hw93mqpcyN89mzSuGHePCybKrFs3Ch3asnIjCDuj+J5s4nAkR4AlCY11rtLMC7IuKnnUsHvZ+D3f6D/5z8n3i91A6pzskn/kz/B+sADN9Uisvd736f/v/8blEpyv/99Uu6846a99mRFFjRkZCYgkbY2Ov/6qwnbDssdd5D9jX+cei2s7jaofgrOvCR9rUuBtX8NS58E9bWdPERBoOX0CU5UvUHDkUOIQ6F/plQ7czfcwZwNd2CxX30799nuQX69v4WXj3UkQvbMGhVPlmey2WDA1Ooj5ky29dHkmDDMlMQNTY5JvrGdAIiiyJn+M7za8CpvNb2V1KWQbcrmzuI72Vy8memp00ft5xWPh3C59tLrfJu+vu3EYoOJMbXaQlraOhyOTaTZ16BWj6/nrifskUSO/rpENkfzYHNSaOZFTBoT01OnJ7o4KuwVlNhK0CjlnJhbCVEU8e/Zg/PpZwidHBIy9HpSP/IR7J9+Ak2GLGTIXB9Bb4Qz73RyfFsrYb+UDZRZnMKK+0vJnXapVYogivykzcm3G7uIiiLZOg0/rihgVerohu7K3DqIsRjBkyfx7dqNb8+eSxYnVenpUhfGmjWYVq1EZZF/18aCqBDllPMU+zr3UdNRw5n+M4gML0VkhgpY59yCrT0fkK7diuaksXhzMZnFk2/doMPXIQWKt2zjuPN40tjMtJlsLKhkXdZ6snW5REOXig+X/TocS3weDcfx+6MMeMLEInG0Iqj44GteY4qW+RsLmLUmB61eFouvhkhrK97qbXirqwkeP540pps2Terc2FSJbtr1BdDLyEx2RFEkcLQXz9ZGhKFrPdOSLKx3FaEcx+xRIRhk4A9/oP9//5e4U+oGVGdlkfbZz2B76CGUurEvXBVFke6v/yPu554DjYb8//rJ1CxmHkVkQUNGZgIhiiKel16m51/+BSEQQGkykfm1f8D64Q9PrYueiB/e+QHU/CfEQoACFj4O678GZscNP/1gn5NT29/i5Pa3CXjcACiUSsqWLGf+prvJnzX3st/PSEzgzdNdPHughcPNwwvfZRlmHlteyP0Lc0nRD59oo84AoVoXwbp+Ii2DjLjXQmXVoZ9px1CRhq7EikItV7bfTLr93bze+DqvNrxKk6cpsd2ut7OpcBObSzYzzzFvzDsOBCHCwMBBnH1VOJ3VRCLOxJhSqcNuX43DUYkjfQMazcTwNg7GgpwfOM/Z/rMJkaN+oD7J0uEiGqWGMltZksgxLXUaRo1stTHVEEUR365d9D39DKHTp4EhIeOjHyXt00+gdtz4sVvm1kCIC3icQfraffR3+Ojv8NPf4cPbH0rsk5plZPl9pRTPS//A658T3gCfP9NCQzCMAvizggz+qjgbjZxRInMVxFwu/Hv3SlZS+/YhjAj+RaHAMHcuprVrMK9Zi35mBQqlfD03FrR726nprKGms4aDXQfxRX1J42W2MslGKnclizIXoVPpcHX5efetZuoP9XBxpaJglp3Fm4vJLh3/Lo2QP4rfEx4WGkJxouEYkRFCQzQ0JD4Mfe4PBBnwevAHgggRUMe1aIWxsxmOIqLQKLGYtRiNGrR6FRqdCleXH9+AlAujM6mZtz6fuevy0I3jguNkI9rTi2/HdrzV1fgPHoL4cEafpqAAy8aNWCo3Ypg3Tz6uyNwSRJ0B3C9fINwonWfVmUZS7y9DVzT+x+uLCKEQ7ueep/9//ieRlaPOyCDtM5/B9vCWMbd9F+NxOv7yL/G++RYKg4GCn/8vxgULxvQ1JzOyoCEjM0GIDQzQ/dRTeKu3AWBYvIicb38Hbd6NtRpPKAQBTj0P2/4RvENWN4W3STkZ2XNH/eXisSj1h/Zzomor7XWnE9tTc/KYX3kXM9duQG8y0+EO8ruDrfz+cCt9PmnRVqVUcMesTB5dXsiKkrQPXFCJ+yKEzg4QrOsnfH4AMTpc4a7QqdBPT8VQkYZ+euq4Vh9MZQLRANtat/HqhVc51H0oUc2nU+lYX7Cee0vvZXn28nHzUhZFAc/gMZzOKpy9VQRDw567CoUKm3UJjow7cKRXotffvNDKqyEqRGnyNCW6Oc66znLOdQ5v1HvJvgoUFKYUUmGvSBI6bHrbzZ+4zA0jiiK+nbvoe/ppQmckWwyFwUDqI4+Q9sSnUKePTpCpzNQk6I3Q1+HD1eGnr8NHf7sPV5efePTSLjCAjEILc9fnU744A6Xq6hd4/PE4T9V38JsuFwDzLUZ+MrOQYqNsBSmTjCgIhM7U4tsjdWGETp6CEbe5SqsV8223YV67BtPq1ahTJ0axwVQjEA1wuPuw1IXRWUPLYEvSuFVnZUX2ClbmrGRlzsr3zZVw9wR4961mzh3sQRyyVcqbkcqSu4vIKb/5P79YNM6RN5o5VtWayP8ZDUQEoqoIUWUIUStgMuhJtdiwmi1o9Wo0OhWaIUFCq1MPfz70qBnaR6tX0eQO8OO9DbxdKy3YqZQK7l+Qy5c2lJNvNxKPCZw72M3Rt1rwDHWkaw1q5q3PY96GfFnYuEbibjfeXbvwVm/D/847iOFwYkztcGCp3Ihl40aMS5aMSyixjMxYIkYFBne14d3VBvEhEXVDAZbbcids0acQDuN+4QX6//t/iHV3A6BypJP26U+T+pGPoDSMXXaqGInQ9oUv4t+7F6XVSuGvfoV++rQxe73JjCxoyMiMM2Ishue11+n9/vek9jaNBsef/Rlpn34ChWoK+Za2H4E3vwodR6SvbQWw6Z+h4t4PzMkYDfpamzle/Sa1e3YQDUkX5kqNFlfWbN4WSujVStXFGRYdH1tWwEeXFJBlvT4FXozGCTV4CNX2E6zrR/BGhweVoCuyop+ZhmFmGmr7FAt3v8nEhTiHug/xWsNrbGvdRjA2bAO2OHMx95beS2VhJWateRxneSmiKOLzn5PEDWcVPl9d0niKZS4OxyYcjjswmUrGaZbvjyiKtPvak0SOs66zOIPOy+6fZcpKiBsXH7NMWVOr+2wKIYoivh07pI6M2lpgSMj42COkPfEE6rS0cZ6hzEQiHhVwdftxdfjoG+q46G/3ERi8tLMLQK1VkpZrTnyk55mw55jRm25sIef1Xjd/ea4NdyyOSaXkX8vzeDgrVT7O3OLEBwfx19RIXRh79xLv60sa11VUYB7qwjDMnYPiBrLXZC6PIAqcc51LdGEc7T1KTIglxlUKFfMc81iZs5JVuauosFegUl7bfZDHGeToW82c3d+dEBJyym0subuI3Ok35zjQ3ehhx6/qGOgeCrg1qS8jLlxGbEja9h5xQq8miI+9PXvZ3rqNfZ37iArD9xa55lw2FmyksqiSOelzrqn7+HSHh/+oPs/2s0OVyEoFWxbn82fry8ixGRDiAheO9nJkawsDXVL2nFavYu76fOZtyL/hY/atiBAI4Nv7Dt7qany7diH4hruRlFYrlnXrsFRuxLRq1ZhXg8vIjDWhCwO4X2kg1ifdo+unp2L7cNmkWQMRIhE8L71E389+RqxTymtVpaWR9sQTpD7yUZTGsXElEAIBWj/9GYLHjqFypFP029+izc8fk9eazMiChozMOCHG4wxu3Urfj58m0iJVJWlLS8n57ncwzJo1zrMbRQY7pY6Mk3+QvtaYYM1fwPIvgObmn8ic/YM8/9wr9BzcQUpw+IbWl5LLtHV3ct/9d2EwjN68REEk2uEjWNtPsLafWE8gaVydacQwJG5ocs0oZIuMq6LB3cCrDa/yeuPr9AZ6E9sLUwq5p+QePlT6oRsOUryZBIOt9A6JGx7PUUb6lxmNZWQ4KnE4NmGxzJnwC3N9wb6EwHHRsqrN23bZfa066yUiR2FK4TUvYsiMHqIo4tu+HefTzxCuk4Q2hdGI/eMfw/6pT6G228d5hjIThaAvwpm9nVw40oOrK5CojE5CAdZ0A2l5F8ULE2m5ZqzphjE733WEInyxroX9bmnx7b4MG9+ZlodVDgy/ZRBFkXB9Pb7du/Hv3kPg2LEkuxelyYRp5cpEF4Ym88rV/zLXT3+wPyFg7O/cT3+oP2k815wrCRg5q1iavRSLdnQySQb7gxx7u5Xamk6EmHRcyi61svjuIvIr7GNyHRWNxDn4aiMntreBCIYULWsfmUbpgtHPlfJFfOxp38O21m3sbd9LKD5s15dhzJDEjcJKFmQsuOrrqWOtA3y/+jx766V7I61KyUeX5vOFdWVkpugRBZGGY04Ov9GEq1M6tmr0Kuauy2P+xgJZ2LhOhEiEwMGDeKuq8W7fTtzlSowpjEbMq1djqazEvHaNnNkjM6mI+yJ4Xm8kcFwqdFNatNjuKcEw54OtRCciYiSC+5VX6P/pz4h2dACgSk3F/sSnSH3kY6jMo5+LGfd4aHn8E4TPnUOTl0fhb36DJlPOKhyJLGjIyNxkREFg8M036Xv6GSKNjYB0MEz7zKdJ/fjHp04lRjQINT+Cd/4DokOL+PM+BhuegpSbb6dzusPDr/e38McTHYSiAogipUIvlYoGtO2nEYdudPWWFOasq2Re5V1YM7JGfR6x/iDBOheh2n7CzR4Y4bqhtGgxVNjRz0xDX2pFoZEXdUfiCrl4s+lNXm14ldr+2sR2i9bCXUV3cU/pPcxzzJuUF0kjCYedOPuqcTqrGBg4gCgOV+HpdTmkOyrJcGzCal2Mcpzss64Vb8TLOde5JJGj0d1ITIxdsq9BbaA8tVyyrLJXMCNtBuW2crQq7TjM/NZBFAS827bR98xPEkG4SqOR1I9/HPsTn5JtV2QSiKJIXU0XNS9eIBwY/hvWGdUjui5MpOWZsWebxiVMNi6K/Lill+82dxEXIU+v4emKQpbZJla3nszoIfj9+A8elLow9uwh1tWVNK4tLZUCvdeuwbhwIQqtfE4ZbaLxKMedx9nXIdlI1bmSu08NagNLs5YmbKQKUwrH9JrNNxDiaFUrtXs7icekC+7M4hQWby6icPYH28leLR3nBtjx7FkGh6yZpi/P4rYt5TdlkT8QDbCvcx/VLdXsad+DP+pPjNn1djYUbGBj4UaWZC1Bo/zg+RxudvG9qnMcaJQW1nVqJY8uL+Rzt5eSbtYhCiKNx50cfqOZ/g6ps0CjVzH39iFhwywLG9eLGI8TPHoU77ZtDFZXJ6rBAdBoMK1YLoWKr18vd8nKTFhEQcR/uBvPm82IoRgowLQ8G+sdRSjH4XpwtBGjUTyvvkbfT39KtFWyj1ZZrdg/9SlSH/04KvPoXmfGnE6aP/4osa4u8p55BvPq20b1+Sc7sqAhI3OTEAUBb1U1fU//mHD9BWDo4PfpT2P/+MdQmkZf1R0XRBHOvAzVXwfPUEZA/jIpJyN30U2dSigaZ+upLn59oIVjre7E9hlZFh5bUch983Mx6dT43QOc2lHFyW1v4e0fsstRKCiev4j5m+6maP5ClGNQMS4EooTOSbkboXMDiOHh6kGFRolu2lDuxoxUVOZb88Y7Eo+wq20XrzW8xjsd7yQWwNUKNbfl3ca9pfeyNm/tlF3sjkYH6e/fRa/zbfr7dyMIw5ZaGo2d9PQNZDg2kZq6CpVqcnnFh+NhLrgvJIWPnx84n2QbdhG1Qk2JrSSpm2OGfcaEsxKbjIjxON7qbfT95CeEz50DhoSMxx7D/slPyEKGTBLu3gC7fnOWjnNuANJyzczfmE/ejFRMNt2EE5SPevx8rraFllAEJfDloky+XJiFWu6GnBJEmpvx7dmDb/ceAocOIUaHCwAUOh3G5cuGRIy1aPPyxnGmUxNRFGn1tiYEjEPdhy45h8+wz0h0YczPmD8u12t+T5hjVa2c2dNBbCi/x1FgYfHmIornXX+1cCQUY/9LDZzeI1XrmlN1rP3YdIrmjE+2VDgeZn/nfqpbqtnZthNvZDjnzKqzsi5/HZWFlSzPXv6BP4eaC318r/o877YMAGDQqPjEyiKeXFNCqkmLKIg0nejj0BtN9LcPCRs6FXNuz2N+ZT6GW/S+ZbQQRZHQmVq81dV4t20j0tAwPKhUYly4EMumSiwbN6LJyRm/icpMOkRRREQcfkRE+v8924eWf9+7b2L7e7aJiMS7g8Te6EZsH+oay9Kh3OyAHF3Sfpd9vZHbL/N6gihc1X7vfQ8XMzUvN9+Lz3Pxua/p+xOP43/3XbzbqoletLE0GjCtvg3TqlUoDPpLn+sqv4/vnYemZwBdr5vb7/sz7Hq5U34ksqAhIzPGJOw7fvTj4cWilBTSPvVJUh97bNRV3HGl8zi89TfQul/6OiUXKr8Jsx+8KTkZF2lzBfjNwVaeO9KGyy/5d2tUCu6anc1jKwpZXHh5H10hHqfx6GGOV71By8ljie0pjkzmVd7F7HWVGFOsYzJnMSYQbvQQrO0nVNdP3DPCd1wB2sIUSdyYaUfjGBuvxomCKIqccJ7gtYbXeLP5zaQbsllps7in9B7uKr7rljuhx+MhXK53pNyNvu3EYu7EmEplIi1tLQ7HJtLTbketnpxt6XEhTstgS0LguPjoCXsuu3++JT/ZsiqtgnSDHFJ9NUQ7O3G/+BLuF19MhN0pTSZSH3sU+ydkIUMmGSEucHx7G4deayIeFVBrlCy9p4R5G/KuKbx7PPDG4vxdfTvPd0sLc0tSTPx4ZgGFhsklAstIIZ2Bw0ekQO/du4m2tCaNa/LyMK9dK3VhLF06dbqeJxC+iI+D3Qep6ahhX+c+OnwdSeN2vT3RgbEiZ8WEOicHBiMcr27l1J4OYkNFRGl5ZpZsLqJkvuOabPBaz/Sz8zdn8bmkcOdZq3NY+UAZWsPEqECOClEOdx2mqqWKnW07cYWGrYzMGjNr89dSWVDJqtxV6NWX/zsRRZE99X18v+ocJ9ql6zCTVsUTtxXzmdUlpOjVhKIhWk65OPZmG652qSNfrVUyfXUGFesz0Js1V7VgdzWLjkkLj1e7oHkN+wqicFVzeL/3cMXFz/db0HzP+OXeg7a1l5QDdaTsr8XYkNx95i/NZmDZNAaWTSeYZ7/ye7jG+cLoLyKP9/f8/d7rFff9gMX1Ky1MX8v3ZeTrXXZxfRS/L2OBTtDwsb7NPNC/ETUqgooQv8p4jVdTdyMohA9+Apmr4oV7XmC6ffp4T2NCIQsaMjJjhCiK+HbuwvnjHxGulVqulWYz9k98AvsnHkc1lX6vvT2w45tw7DeACGoD3Pb/YOWfg/bmLL4Lgsjueie/3t/CznO9XDxi5Vj1fGxZAQ8vySfDcvU3tgNdHZyofpMzu7YR8kuVRyq1mmkrVjN/02ayy2eMWSWqKIpEO/2E6qTcjWinP2lc7TCgr0jDMNOOtiBlSuRuCKJA62ArbzW/xWsNr9HqHV6kyDBmcE/JPdxTeg+lttJxnOXEQRBiuN2HcPZV4XRWEw53J8YUCi12+woc6ZtwODai1U6cxYTrQRRFuv3dl4gc3f7uy+6fbkhPiBwVaZLQkWfOm3CV4+OBGI3i272bgeefx79nLxcPlCqbjdSPPYL98cdR2WzjO0mZCYezzcvOX5/F2SqJy7nTU1n36HSsk0xcf7lngL8+14Y3LmBRKfnO9HweyJSFu4lOtLMz0YXhP3AAMTiiA0Cjwbh4EeY1koihLS6Wj/WjjCAK1PXXsa9zH/s69nHSeTLJLlKtVLMgY0GiC2O6ffo1hVKPB0FfhBPb2ji5q51oSBI27DkmFm8uonRhBsr3ua4O+aPse6Ges/ula5CUdD3rHp1B3oyJW2QTE2Ic6z1GVXMV21u34ww6E2MGtYHVuaupLKxkTd4ajJpLj+uiKFJd28V3d+ylxV+L0tCK1tiOSuciLg4VYIlQODCbxe134vBLwbVRZZgzme9wPHcHIY3vkueVuT7SPSJLzossOycwox2UI1bp2tPg4HQFh6YpacriphYUytyaLPHO5vM9D5MVle43aywn+FnWC/RrPKAAxcX/FMOPQPI2acfENiXKq9pv5HNfsu/QI3DZfZUK5Qful/R6V9p3xLZ4v4tYeztiIIBCBIVShTY3F21uHkqt9tL3cA3fFxEl/2/hn5FjljuyRiILGjIyo0zM5cLzx1dxv/gCkQtSe6jSaCT18cdI++Qnp9ZiUSwMB56BPd+Di1X0c7bAxn8E69i39ouiSIPTx7a6Xn57sJVW13Dg9urydB5bXsj6GRmob6B6NBoJc65mL8fffoOexvrEdkdRCfM3baZi1e1oxrgCMOYOJ8SNcKMH4sOHY6VJg36GHcNMO7ryVJTayZO70eHr4K2mt9jftZ9TzlMEYsM/P4PaQGVhJfeU3sOSzCVySPT7IIoCg95TUueGs4pAoHHEqBKbdREOxyYcjk0YDFPHcmMgNMBZ19mEyFHXX0fLYMtlq48sGgvT7dMTXRwz7DMosZagniQZJDdKpL0d9/Mv4HnpJWLO4YUM47Jl2LZswVK5EaVOrlaXSSYWiXP4jWaOVbciCiI6o5pVD5UxY0X2pF00bg2G+UJtK4cHpUKBhzJT+da0PCxq+RwzURCjUQLHjuEfEjHC9fVJ4+qMDCnMe80aTCtWTK1O5wlCb6BXCvPuqGF/137cYXfSeIGlQBIwclexNGvpZRfBJwMhf5QTO9o4uaOdSFASaVKzjCy6q4jyxRmXdJ81Hney+7fnCAxGQAFz1+Wx/MOlaHST5/ghiAInnSepbqmmuqWaLv9wtb9OpWNlzkoqCyuZnT6b+oF6Tvef5kzfGc70n0nK57giIhS4Z7G47U4y/AUARJURajP3cTxnO0GtdL94xUXKq1zgSyxGXuUC6fUufF52gfNy+13DwufIfS++j8u+/6v4vhi8EQpP9lJ0rJvsOieqEfeIPruBtoW5tC/Moa/cAUrlBy7yXvX35XLv4QPe69X8bN9vHpfd74N+PtfwM3vfn8Uo/Y5d1+/NB+x7uZ/Flebwvt/zq/xeXnwUPBEG32gmdLofAJVVh+3DpRhm3tr5Lgmb+WeeIXz+PDAik/BTn0RtvzbxezAW5wfNPVT3e9i2ZDo65cQuGLjZyIKGjMwoIMbj+N95B/cLL+LduRNi0kWxwmjE/vGPYX/iiall3yGKcPZ1qPoHGGiWtuUshLu+A/lLR/Wl4oJIlydIS39g6MNPc78/8XUwOpw7kaJXs2VxPh9fVkCJY/RvcLsvnOd49VbO7dtDLCpVJGkNRmbdvoF5lZtJy80f9dd8L0IoRuj8AKHafoJnB6SwrYuolejLbOhn2jFUpKGyTDz/2v5gP1UtVWxt3Mpx5/GkMbVSzaKMRdxbdi8bCzZO2hvk8cbvv0Cv822cziq83tNJYxbzLByOShyOTZhM0ybtouSVCEQDnB84P9zN0V/HBfcFokL0kn21Si3lqeXDllVpM5iWOg2D2jAOMx99xEgE746duJ97Dn9NTWK7ym7H9sD92B56CG1R0fhNUGZC03F+gJ3PnsXTK1XDly7MYPVHyjFZJ7/wFRNEftDSw/ebuxGAQr2Wn8wsZKF1imSZTUJiTie+ve/g27MH/759CN5hq0mUSgzz50tZGLevRTd9+pQ7d4034XiYoz1HqemUbKTqB5JFJJPGxLKsZazKXcWKnBXkW8b+evdmEg5EObmznRPb2wgHpOtqq8PAoruKmLYsk0ggxp4/nOfCkV4AbJlG1j9eQXbp2NjQ3ixEUaS2vzYhbozsjr4cBrWBOelzmJM+h7A/n63vCrQ4lSAqSDNr+cxtpTyytACjVgMitNUOcHRrK73N0t+zSqNk9upcFtxRMCXOJRONuNeLb/cevNXV+PbsSepmU9ntWDZswFK5EdOKFSg0cni7zPUhCiK+/Z0MVrVI+Z9KMK/KJWVjIcpJJO6ONaIg4N2+nb5nfkK4TnJrURgMpD7yCGlPfAp1+vs7KMQEkWe7+vluUxeuofWu/5pZyH1yZ3ESsqAhI3MDRFpbcb/0Ep6XXyHW05PYrp87F9sDD5By92ZUlsnpZX9Fuk9LORnNe6WvzVlSR8bcj8AoKMYuf4SXj3VQc6GP5n4/ba4gkfiVvRd1aiULC1K5b0EO987LxXATOhSCPi9ndm3jRPVW3N3DlU0Fs+cyb9PdlC5ahko99pXfYlwg3DwoiRt1LuKuUNK4Nt8iiRsz01BnGMdtAcAX8bGjbQdbm7ZyoPMAcVE6KStQsCRrCRsKNrAkawlF1iI0SvkCezQJhTpxOqvodVbhdh8Ghv+WDIYiMoY6N1JS5qGY4BYR10s0HqXR05gkcpwbOHfZSkOlQklRSlGSyFFhr8CqmzyLFpHmZtwvvID7pZeJu4Y9s00rV2J7+GEs69eh0E48sVNmYhAORKl5qYHadzoBMFm1rHlkOiXzHeM8s9HnkNvH5+taaA9FUSngr4qy+LPCTFTyYvmYI8bjhE6fxrd7D77duwmdOZM0rkpNxbT6NikPY9WqqdXdPAEQRZEmTxP7OqUw7yPdRwjFh68hFSiYmTYz0YUx1zH3lrg+iwRjnNrdzvHqNkJ+qRBCZ1QTj4vEwnEUSgULKgtY8qEi1JqptXAniiLnB86zrXUb21q20TzYTLmtnNnps5mdPptZabMotZUmdbbG4gJ/PN7JD7fXJ7rkMyw6vrCujI8uzUenVknB8bUuDr/eRE/TICAJG7NW57BwUyEmmyxsjAVCKIS/pgZvVTXenTsRPMNZdJrCArL+4WuYV982jjOUmYxE2r0MvHyBaIdkIafNt2C7vwxtjtwpeSUkG/qd9D39TOJaR6HXk/qRj2D/9BNoMjIu+Tc7+gf5xwudnA9I5+Vyo46nSnPYmJYiF3S8B1nQkJG5RoRQCG9VFe4XXiRw6FBiu8pmw/rhe7E+8CD66dPGcYZjhL8Pdv4LvPsLEAVQ6WDlF+G2r4Duxk5igiBS09DP7w+3UnWm5xIBQ6NSkG83UpRmojBNeiwYesxLNaAZp0BSURBoOXWc41VbaXz3EOJQsJk51c6cDXcyd8MdmO03p+1SFEViPQGCdf0Ea11E27xJ4yq7HsPMNPQVdnRFVhSqsT0ZRuIR9nbsZWvjVna37yYcDyfGZqXN4q7iu7iz6E4yTZljOg+ZYSKRfvr6duB0VtHvegdRHA6e12kzSXdUkuHYhM22FOUUX7gQRIF2b3tSLkddf11SaOZIckw5zLDPSAgcM+wzyDRmTpiLSiESwVtVjfv55wkcPJjYrnKkY3vgQWwPPYg2f2pV1MqMPo3HnOz+/TkCHunYMGt1DiseKEM3QUJuxwJPNMZXz7fzSq8bgOVWEz+eWUieXhb9Rpu4241v3z58u3fj3/sO8YGBpHH97NlSF8baNehnz0ahmloLxuONJ+zhYNfBRBfGe3OoHAZHQsBYnr2cVP2tWwUaCcU4vaeD49WtBL2SsJGWa2b94zPIKLw11iVEUbzqa5xoXODFd9v50Y4LdLilroAcq54vri9ny+I8NColoijSVufi8OvNdDdKi+sqtZKZQ8KGOVUWNsYKMRolcPgw3m3bGHzr7USxi2XTJjL/5qtocmRPfpn3RwjHGKxqwVfTCSIo9CqsdxZhWpo9JbI8bwaiKOLbvVsSNk6dAkCh02F7+GHSPvNpNJmZnPUH+caFTna6pHWcVLWKvyzO4vGcdDTy9/myyIKGjMxVIIoiodNncL/0IoOvvzHcCq9QYFq1CttDD2Jevx5UaqIRgVg4TjQcRxRFdEYNepP6Eh/WSUMsAof/G3Z9B8JD1R0zPwyV34TUoht66m5PiOePtPGHI220Dwy3xc7JtfLh+TnMyEqhMM1Ijs2AaoIfxAf7ejm57W1O7XibgMcNgEKppHzJCuZtupv8WXNu6uJnfDBCsK6fUJ2L0IUBiA0fwhUGNYYZdvQVdvTTUlHqR2exKi7EOdxzmDeb3qS6uRpvdFhUKUopYnPxZu4qvosia9GovJ7M9ROL+ejv343TWUVf/y7i8eGwRrXaSnr6OjIcd2C3r0almhoWTB+EKIo4g85EF8dFoaPD13HZ/VN1qZeIHIUphTc1DDXc0ID7uefx/PGPxN1uaaNCgWnNalK3bMG8dq1sKyDzgfg9Yfb+/jwNx6R8FWuGgXWPziB32q2xoCmKIs/3DPC359vxxwWsahX/Nj2fezNs4z21SY0oioTPnpW6MPbsIXj8OAjDBStKsxnTbbdJIsbq21A7pl4X0HgSF+Kc6jvF/s797Ovcx6m+Uwji8Pdfq9SyMHMhq3JWsTJ3JeW28gkj0k8UYtE4A90BFAoF9mzj5L2Xu0lEYgJ/ONLG0zsu0D0oVRbn2w38+fpy7l+Qi3pI2Gg/O8DhN5rouiDdVyrVCmatymHhnYWYU8c2l/BWJ+7z0fejH+N69lmIx1EYDKR/7nOkffITcveuzCWIokjoTD/uVxuID0rFLoZ5DmwfKpmQ1taTAVEU8b/zDn0/fprgiRMAuO1p/PaLf8mL2UUIgEah4Im8dL5cmIlNM3WLikYDWdCQuWWJReP43RGi4TixSJxoKE40Eh/+Ohwn7PbjrztP4HwjkcEAcZWOuEqLYLBAWgaiyUosriAaiRMLC8Rj72ONZFSjN2nQmzUYzJrE5/qhzw0WLVklVowpE+TkIIpQXwVv/x30X5C2Zc2BO78NRdffohqNC+w828sfDrex81wvwtCRxaJXc/+CXB5enM/s3Mlj7/Je4rEo9QdrOF61lY6zwxYK9pw85m26m1lr16Mz3lyfbiESJ3x+gGCdi9DZfgT/iNwNlQJdqQ1DhR39zDTU1+hpK4oiZ/rP8EbjG7zd/DbO4HDgcIYhgzuL72RzyWZm2mfKN8oTFEEI43LVSKHifduIRoe7FJRKPWlpa3CkbyI9fT0azeT927xeBiODnHOdSxI5mjxNCeu0kRjUBqanDoePV9grKLOVoVGNnqgghEJ4336bgeeeJ/juu4nt6qwsbA8+iO3BB+RqO5mrQhRF6mq6qHnxAuFATLJT2VTAkrunnp3K1dAcDPO5My0c80rWKY9k2/nnslxMcmD4VRP3+fHvr0kEesd6e5PGdeXliUBv44IFsuA6ynT7u9nXsY99nfs40HUAbyS5W7fEWsLKnJWszFnJ4qzFUyYzSmZiEYrG+e3BVp7Z1UCfT+rQLk438aUN5dwzLweVUoEoinScG+DwG8101rsBSdgoX5xJyTwH2WVWDPKC6ZgROnee7n/6JsEj0nWktriYrKe+hmnFinGemcxEITYQwv3HBkJnpftClV1P6n1l6G+RYpexRhRFXPtqeOadI/xi7hL8Bik7dL2zk39cMptpxQXjPMPJgSxoyNxS+D1hzh3o5tzBblxdfhij32qFUoFGq0ShVCTC5a6WtDwz+RV28itSySmzob4JmRCX4DwHb/0tNGyXvjY5YP3XYMGjoLy++TT3+XnuSBvPv9uO0ztsP7S02M5Hl+Rz1+zsm5J/cTNxtjZzomortXt3Eg1JHShqnY6Zt61j3qbNZBSV3PQ5iYJIpHWQYK2LUG0/sb5g0rgm15wQNzTZpiuKEI2eRt5sepOtjVuTQgRTtClUFlZyd8ndLMxYiOo6f19kxgdRjOP2HMU5FCoeCg13JygUalJty3E4NuFwVKLTXer5easQioW44L4gWVb1n+Ws6yznB84neZBfRK1UU2Yrk7o5hrI5ptunY9Jcm7AZOnce9/PP43n1VYRByYcalQrz2rXYHt6CefVq2aJF5qpx9wbY9ZtzdJyTbH8cBRbWPz6D9Lwplvt1jUQFke81d/PDlh5EoMSg4yezCplnMY731CYkoigSaWoa6sLYTeDIuxCNJsYVBgOm5culLIw1q2WxdZQJxoK82/Mu+zqkLIxGT2PSuEVrYXn2cqkLI2cl2ebscZqpzK1IMBLnV/ub+a/dDQwEpONCeYaZ/7dxGnfNzkI51H3fcW6AQ683JYSNi6Q4DGQVp5BZbCWrJIW0XDMqtdwlM1qIosjgq6/S891/I97fD4DlrjvJ/Ju/QZMpWwLfqohxAd87nQxua0GMCqBSYFmTR8r6fBS3YLHLWCCKIq85PfxzQyetIanzZXpfD3/6q58yv74ONBps991H2pN/gjYvb5xnO7GRBQ2ZKY8QF2g946J2XyfNp/oRheFfZbVGiUavQqNToVIIKH1uxL4elEEvqngYVTyM1mbGNL0U86wZaK1G1Fppf41OhUarQq1779dKVGplYiFYiAuEAzGCvighX5SQX3oM+iKE/DFCvgghXxSvK0x/hy9p7iq1kuwy65DAYSc9zzy2PoUBF+z6Nhz+HxDjoNTA8s/Bmr8E/bVXZoeicd4+083vD7Wxv7E/sT3NpOWhRXk8vCSfUsfUD5EKBwLU7d3J8ao36G8fXvzPmVbB/E2bKV9+G+pxqlKMOgNSqHiti0jrYJLIp7Lp0FdIoeK6Yis94V7eanqLrU1bqXPVJfbTq/Ssy1/H5pLNrMpZNarV6DLjhyiK+Hy19A6JG35/fdK4NWXBkLixCaOxaHwmOYGICTGaPc2JXI6L3RzvrZAFKXC1IKUgSeSYYZ9BmiE5c0cIBBh88y3czz2XaEsG0OTkYNvyENYHHpBvOmWuCSEucHx7G4deayIeFVBrlCy9p4R5G/JkO5UR1Az4+GJdC53hKBqFgq8WZ/H5ggyUcqchQihE4NAhfLt249uzh2h7e9K4prBgSMBYi3HJYpQ62Rt/tBBFkXp3PTUdUg7G0Z6jRIThPCylQsns9NkJAWN2+uykEGcZmfHAF47xi31N/GxPI4MhqdBvRpaFL1dOY9PM4Tyy7kYP9Ud6aKt1MdAduOR5VBolGQUWMkeIHLJF1Y0THxzE+Z8/YuC3vwVBQGk0kv7FL2J/7FG5i+4WI9wyiPvleqJDf3/a4hRS7y9HkyEXdYwWRwf9fL2+k8ODfgCytBr+tiSbLVmpBA8fpu+ZnxA4cEDaWa3G+uF7SX/ySbQFcsfG5ZAFDZkpi8cZoG5fF2f3d+H3DF/sZxanMPO2HIrmpKPTCvi2b8fz4ov49x+QbJYAZUoK1nvuwfbgA+hnzrxpcw4MRmg/56KtboD2Ohe+gXDSuMGiIW+G1L2RX2EfvYu4eAze/T8p9Ds4FNI4/W7Y9E+QVnrNT3e2e5DfH2rj5WMdeIJSRY5CAWunOfjoknzWz8hEewtW2IiiSEfdGY5XvUH9oRqEuGRZY7CkMGf9JuZuvAtrxvgtTsZ9EUJnXQRrXYTrB6SqjCFCqggHTSc5YD7JYfMZwuooK3JWsLlkM+vz12PUyBc6U51AoAmns4peZxWDg8eTxkymaWQ47sDh2ITZXCHbiw0hiiKd/k7O9p9NCiDvDfRedv8MQwYz0mZQFk8n70QXWVvfJa0rgAJArcaybh22hx/GtHKF3I0hc80427zs/PVZnK2SyJY3I5XbPz4dq0M+fl+OgWiMvzrXxutOyed9lc3MZ/McrEo1Y7nFbKgi7e34dksCRuDAQcTw8PWpQqPBuHQp5rVrMK9Zg7aoaPwmOgVxh9zs79rPvo597O/cT28w+fyRZcpKCBjLspdh1d161pAyk4PBUJT/3dvEz99pwhuWhI05uVa+UjmN26c7kq4dw4EoPc2D9DQN0t04SE+T57KuByabLtHFkVmSQkaBZXzcDaYAobo6ur/xTSnvCNCVl5H11FMYlywZ34nJjDlCIIrn7Wb8h7pBBKVRjXVzMcZFmfI93SjREYrwr41dvNgjrbUZlAo+X5DB5wsyML3nns5/5Ahdz/wvg0dPEVUbieksaJbexqwvPoCptHA8pj9hkQUNmSlFLBKn4ZiTuppOOs65E9v1Zg3Tl2cxc2UO9hwTobo63C++hOe11xA8nsR+xhXLsT34EJbKjeNeUSaKIu6eAK21LtrrXHScdxMNJ3u2p2YZE90bOdNsaK8n3LlhB7z1d+Acqrh3VMCd34LSddf0NL5wjNdPdPK7w22caHMntufaDGxZnMeWxfnk2mSv3ov43QOc2v42J7a/ha+/T9qoUFCyYDHzN91N0byFKJTjI/p4wh72NO/mwrFTWJpVLPXOxh4fvkEWFCLqIjOWWZkYZqahtsvVUbcaoXA3fc5tOJ1VDLgPII7Ik9Dr83A4NpHhuAOrdQEKhXxj+V76g/1SLseIbo7mwebL7msOKyjX5DKrdAUzcxdQYa+gyFokV93KXDWxSJzDbzRzrLoVURDRGdWseqiMGSuyb+hGNSpEaXQ30jLYgl6tx6K1YNFYpEetBYPaMOlvhEVR5HddLv6+voPgUKC1Aigz6pifYmSBxcj8FCOzzAZ043TOHgvESITA0aOJQO9IQ0PSuDo7WwrzXrsG07JlKE03NxtsKhMVopx0nqSms4aajhrO9J9BHNE+q1fpWZS1iFU5q1iVs4pia/Gk/zuTubVwByL8bE8jv6hpJhCRrh8XFNj4i8rprCpLu+zvsyiKeHqDdDd56GkcpLvJQ3+HP8l5AUCpVJCWZ5ZEjhIrmcUpWB2T/1x0sxAFAc/LL9P7798jPiAtvFo/fC8Zf/VXqNPTx3l2MqONKIoETzhxv96I4JOKUI2LMrFuLkZlkrtzbgRRFImG47i8EX7S6eQXLjfhoXP5RkHLR30azH6BsD9KOBAlHIgR8kuP4WDsstb49z1oJrdy6U1+JxMbWdCQmRI4W73U7evk/OGe4eoNBRRU2KlYlUPxvHQI+PC8/jqeF14kVFub+Lfq7Gxs99+P9YH7J7RHXTwm0NPkoa1ugLY6F73Ng4z8q1QqFWSVWsmvSCWvwk5GYUrCm/Sy9DfA238P59+UvjbYYd3fwaJPgerqFspEUeRYm5s/HGrjtZOdiYtStVLBplmZfGRJAbeVpaMaS5usSY4Qj9Nw9BAnqrbScvJYYrs1I5O5G+9i9rpKjCnXX20XF+L4oj58UR/eiDfxcfHrwcggvogvsa0/2M9J50li4nAVVEXqDD6Scj/LvXNRXQgT60luA9dkGdHPTMNQkYYmd4xt0WQmHNGom76+HTidVfS79iIIwzkSGk0aDsdGHI5N2FNXoFTK1iMjEUWR0OnTuJ97ju6qN2i2BGnKVNCUraKtzEKLIUCMS8PHdSod01KnJVlWlaeWo1fL4qJMMh3nB9j57Fk8vVJeUunCDFZ/pByT9fr/FtsG23ih/gVeufAKrpDrivupFeqEuDHyI0WbcsVtJdaSCVlh3hQI878dTqr6BhN+xyPRKBTMNOuZbzGywmbmngwbqkm2gBbt6cW/Vwrz9tfUIPj9w4MqFcYFCzDfvhbTmjXoysvlBcJRpN3bTk1nDfs69nGo+xC+aLIFbXlqOatyVrEiZwWLMhehU8nnUpnJT78vzE/3NPKr/c2EhrrClxbb+UrlNJaXpH3Av4ZoOI6z9WIHxyDdjR4Cg5cen/UmDZklKcOdHEUpaA1yUcj7EXe76f2PH+B+7jkQRZQWC44vfYnURz4qdwhPEWJ9QQb+eIHwUHaN2mEg9f4ydCW2cZ3XRCMWjSeLDYHYkAgxcluUkD+WECbCgShBf4zjhRp2zjHiM0gFLwW9UTYdD5A9cOm93eVQa5XojBq0yhiqoIfKv9qAPUcuIBmJLGjITFrCgSjnD/VQV9OVsE8AsNj1VKzKZsaKbMw2LYFDh3C/8CLe6urhFnmNBsuGDdgefHDSWneE/FE6zkniRludi8G+5DBanVFN3nRJ3Mgpt2F1GKQgtZAHdn8XDv4UhCgo1bDks3D7V8GQelWvPeCP8PKxDv5wuI1zPcPf+xKHiY8uyeeBhXmkm+WbrWvF1dnByW1bOb1rG+GhhQSVRkPhkiUUrFmOJjcdX9THYHRYhHivQOGNePFGh7ZFfJfcFF8tZbYyNhZu5M6iOym1JduOxfqDBOukUPFwsweGnalQpmilUPGKNPSlNhSaqVOxKvPBxOMB+vv34nRW0de/g1hsMDGmUplJT1+Hw7GJNPta1Opb94Is7vXiee013M89T/js2cR2bVERtocfxnrfh1Hb7UTjUS64LySsqi52cwRjwUueU6VQUWwtTogcM9NmMt0+nRStfA11KxIORKl5uYHavZ0AmKxa1jwynZL5jut6vqgQZWfrTp4//zwHug4ktps1ZkpsJcSEWNI5KS5e3c3ae1EpVCzNWspD0x5iXcE6NMqJVyHojEQ5PhjgmDfA8cEAx70BXNHk9zvXbOBb0/JYZJ24xzkxHid44mTCSipcV5c0rkpLG+7CWLkSlXw/NmoEogEOdx9mX6cU5t0y2JI0btPZWJG9gpW5K1mZs5IMY8Y4zVRGZuzpHQzxzK4GfnuwlUhcuqlYVZbGVyqns6jw6u5NYSj7bSBMd6OHnibJpqq31YsQe88ylgLs2SYyi1PIGrKqsmeZ5IKsyxA8dYruf/wGoTNnANDNrCD7qacwzJ8/vhOTuW7EmIB3dzuDO1shJoJaQcq6Aixr81BMUUvweFwgMiRGhC4jRoSHxIhQYIQo4Ze+jo+w4L5amjLUVM830pMqCaf2gMC9TTEWB1ToTWp0RjV6owadUY3OpEFvVKMzatCZhrYNjavkdZQPRBY0ZCYVQlygs95N3f4uGo46EwcYpVpByXwHM1fmkDcjlVhPN55XXsH90stE29oS/143bRq2hx4k5Z57UKde/QXSZMDjDCS6NzrODVziM6pQgMUcxRo7j03RQoqqh5S8LFLWf4KU8hkfaFclCCL7G/v5/eE23j7dnbjg1GuUbJ6TzSNLC1hcmCpX7I1AEAUC0UCSyHBFEWLENn9gkJTGEPkNStI82sTz9aeEOVvoozHHT1x1bYdkvUqPWWu+xBLkcttmpc2iyFp0de8xECV4boBQbT+hcwOIkeFFHYVWib48Ff3MNPQz7HLr6i2GIEQZcB/E6Xwbp7OaSMSZGFMqtdjtq3GkbyI9fT1arX0cZ3pzEEWR4PHjuJ97nsE330QMSSK0QqvFcscdpD68BcPixR94DBVEgdbB1iSRo66/joHwwGX3zzXnJkLHK9KkR4fBIR+rpzCNx53s/t05AkP5YbNW57DigTJ011GR2uZt46X6l3i5/mX6Q/2AFGq/MnclW8q3sCZ/zSWigyiKBGNBBiODSee3937ti/qStg2EBuj0dyaeJ8OQwZbpW3ho2kOkGyau1YUoirSGIhz3BjjqCfC77n4GY9I10sey7fxdSQ7p2olRDRwbGMC/d6/UhfHOO8RH2K6iUKCfO0cSMdasRT9r5rhZX041BFHgnOtcQsA41nuMmDB8na5SqJjnmMfKnJWsyl1Fhb0ClXLyFVvJyNwIXZ4gP95xgeeOtBGNS/c5t0938JXKaczNs13Xc8ajAn3tPsmqakjkeG8RIIBWryKjKIWsIZuqzOIUDGbtZZ7x1kOMx3E/9xy9//EDhEGpUMm2ZQuOr3x5yq2nTHXCjW4GXr5AzCkVRunKbaR+uAx1+sS3BRcFkXAwliRChALRK349smMiGrq+IpuLKBRIgsNFsSEhPGjQmaRHvUlNjw5+EvGyOyR9f1NUSr5clMkTeY4pZUs6kZAFDZkJjxAX6DjvpuFoL43HnQS90cSYPcfEzFU5TF+WhU4r4t2xE/eLL+Lftw+GvI6VZjMpd9+N7aEH0c+efUss4ghxgd4Wb6J7o6/VQ/TSDtwk9GYNKekGrOl6UtINQx96InolbzY4+cO77bS6hq2GZuWk8NGlBdw7LwerYWouVEfjUbxRb6IbYjAyeNXWTRe/Fi9ngHgNpLm1VLRYKO4yoRKk3924VoF/moX4vCxMmQ7MWnPCrsOsMV9q8aGxoFGN/c9IjAmEGz0Ea/sJ1fUT94z4pVOAtjAFw8w09DPT0EyCCyeZ0UMUBQYHj9PrfBuns4pgsHXEqJJU21Icjk04HJXo9TnjNs+xIO5243n1NdzPP0e4/kJiu7aslNSHH8Z6772obLYbeg1RFOkJ9AyLHP1SJ8fIxeGR2PX2hMgxI02yrMq35KNUyBfbkxm/J8ze35+n4ZgkHtoyjax7dDo55de24BAVouxu283z55+nprMmsT3dkM79ZffzQPkD5FnGxqKzdbCVVy68wov1LybsrNRKNZUFlTw28zHmOOaMyeuOJs5IlH9q6OS5bklktKlV/G1JNo/mpN10GypREAjV1uHbsxv/7j0ET55kpF+p0mrFvGqV1IWxejVq+9QXl28W/cF+KQdj6OO99my55lwpzDt3JcuylmHWmsdppjIyE4s2V4Af77jAC0fbiQ9lZFTOzOTLG6cxM+fG14UCgxF6mjx0DwkcPc1eYuFLFzytDsOQVZUkcqTlmVGpbt3rpFh/P73//j08L78MgMpmw/EXX8H24IOy+D3BifujeLY2EXi3BwClWYPtQyUY5t3cAqeLuRKXEyEutXS6ulyJa0GrV43ogtAMdUtoLitSjOyg0OpU79vBNRCN8f3mbv6vo4+YCCoFfCInnb8oyiJtghS0TFVkQUNmQhKPC3ScG6Dh3V4aj/cR8g+LGDqTmtKFGcxcmUNGkYVwfT2eF1/C8+qrifAqAOOSJdgeehDLpk0oDbfo4ulAM1R9DbH2VQJCKh5VGe6SJ/CYFjPoijDYF2SwL5T0/b0ccUQGlSJ+NaRmGJk9LY1ppamkDIkfOqN6wglFFytE32vDdNGK6ZKOiRE2TRe3heKXVvBcDxqlJuERflFwuChCXE6AuLgtRZuCWWvGpDER9vk4s2sbJ6rfxN3TlXjugtnzmL/pbkoXL0M5gazTRFEk2umXxI3afqJd/qRxtcMg5W7MTEObb5HbvG8hRFHE7z9Pr7MKp/NtfL5kmxOLZQ4ZjjtwODZhMpVe4VkmNqIoEjxyhIHnn8f71tuIEUncU+j1pNx1F7YtWzAsmD/mx01P2JOwqboodDQNNiGIl7ZPmzQmpqdOT3RyVNgrKLGVTEjLH5lkRFGkrqaLmhcvEA7EUCgVLNhUwJK7i1Brrv680OHr4MXzL/LyhZfpC/Yltq/MWcmWaVtYm7/2pv0+ROIRqlqq+P3Z33PCeSKxfUPBBv58wZ9TYiu5KfO4EQ66ffzt+XZq/dK1xDyLgW9Py2dBinFMXzfu9eLfV4Nvzx58e/cQd/YljetmzJC6MG5fi2HuXBRq+WZ7NIjGoxzrPZYQMOpcyec2g9rA0qyliS6MAkvBhLt2lpGZSDT3+fnP7fW8cryDi9nfm+dk8eWN0yjPtIza6whxAVdXYFjkaPQw0B24ZD+VRklGoYXMYmsij8OceutZLAfefZfub3yT8PnzABjmzSPr60+hnzlznGcm815EUSTwbg+erU0IQ+4dpmVZWO8oQmm8/uu5682VCPtjCMKNLStfzJUYKUZcFCmGRYiLnw+LFVqDCuUoC5IRQeCXHf18r7kbd0wSRTempfBUaQ7TTHKu4c1AFjRkJgzxmED72QGpE+OEk7B/uBVbb9ZQMt9B2cIMcqbbIBhg8I2tuF98kdDJk4n91A4H1vvvx/bgA2gLC8fhXUwQwl7Y+33Y/zTEw6BQSmHf6/4eTJeGrIWDMQb7gjQ0udl/sofGZg/akIBNUJAiKFDz/jdcWoOalHQ91nQDlvd0eVjS9FJ2xzUSE2L4o/6EHUVCaBghPCTG3mvdNNRVcb0e3u/FpDElhIaLIsPVWDdd/BjN8EZREGg5eYzj1VtpfPcw4tDCpNmextwNdzJnwx2YUydehWXMHSJU5yJY20+40QPxERWiJg36CjuGijR05TaU2okjzMiMPcFgK05nNb3OKjyedxlZfmM0luJwbCLDsQmLZc6EX/yJDQzgefkV3M8/T6SpKbFdN306to88jPVDHxp3H/pgLEj9QH2SyHF+4DwR4TJBx0oNZbayhFVVhb2CaanTMGrGdkFW5urxOAPsfPYcHeekgg5HgYX1j88gPe/qFntiQozd7UPdGB01ia5Cu97O/WX38+C0B8m35I/Z/K+Guv46nq17ltcbX0cQBZQKJR8u/TCfn/95skxZ4zq3DyImiPyis4/vNHbhjQsogEdz0vjbkmzsmtEREkRRJHLhgiRg7NpN4NgxiA1fQyuNRkyrVmJaswbzmjVoMjNH5XVvdURRpNXbyr4OyUbqUPehS/KNKuwVCQFjvmP+TemWlZGZalzo9fGDbed541QXoijZv9w7L4cvbSinxDE2nU0hf5Teloth41Inx3vtnAHMqbohiypJ5HAUWFDfAvcxYiyG69ln6fvPHyEEAqBUkvrIIzi+9Ofjfp0rIxHtDTDwcj2RJskmTJNlxHZ/ObpC6edzs3MlRqJUKyRRIsm2afLkSoiiSFX/IN+40EljUMronWHS842yXNbaR09slflgZEFDZlyJRwXa6lw0HO2l6WRf0oWCwaKhZEEGpQsd5JbbUKqUhM6exfWrX0v+48Ghmwa1Gsu627E++CDm2267tSvNBAFO/A62fwN8UkshxWvhzm9B5qzL/pNQNE5VbQ9/ONzKvgv9ie1pJi0PLspjy8I8snUaBvuCeJwhqaujP8jg0OeBwQ/wslKA2aaTBA7Hey2tDBgsGhQKBaIoctZ1lh1tO9jZupNzA+cufS4R9DETlrAdS9iOOWxHHzOBCD7dAG5DD25DLwHNIBc1GLVCfUXB4b3bLmfdZNaYJ6yP8aCzl5Pb3+Lk9rcJDko+2EqVirIlK5i/aTN5MyfmArAQihE6N0Cwrp/Q2QHE0IgbBLUSfbkNQ0Ua+go7KovsX3srEY700eesxumswjWwH1Ec0Z2ny8bhqMTh2ITNugSlcmIc60VBIHDoEO7nnsNbvQ0xKs1ZYTRivXszti1b0M+ZmH+LF4kJMZo8TdS56qjrl3I5zrnO4Y16L9lXgYLClELJsiptRkLoSNXLPso3EyEucHx7G4dfayIWFVBrlCy9t4R56/OuqgKt09fJi/Uv8nL9yziDw/k2y7OXs2XaFtblr5twi68N7gZ+dOxHbG/dDoBWqeWRGY/wmTmfwaa3je/kPoCesGRD9UKPJDylqlX8fWkOH8u2o7yOY4MQCOA/cBDfHinQO9bZlTSuLSlJBHobFi1CqZXPpaOBL+LjYPdBajpq2Ne5jw5fR9K4XW9nZY4U5L0iZ8WEzn6RkZlsnO0e5AfV9bx1phsApQIeWJjHn68vpyBtbAstRFHE3ROQBI4hq6r+dh/vXSFTKhWk55vJHLKpyipJISXdMKGvAW+EaE8vvd/5DoNbtwKgSk8n86//ipR77pmy73kicdlcCW8Yxck+dI1uFCIICuix6enUKAkG4jc9V+Jylk5qrXLS/n6c9gb4+oVO9rl9AKRr1Hy1JItHstJQy44TNx1Z0JC56cSicdpqXVw42kvziT4iIw6mxhQtpQsclC7MILvchlKpQBQEfHv24PrFLwkcOJDYV1tSgu3BB7F++F7U6fINA60H4K2/gc5j0tepxXDHv8D0zdIZ5z2c6/by+8OtvHysA3dgaAFOAavLHTyyJJ8NFZlor6KzIhqJ4+2TxA1PXzBhYzU49Hks8v4KvlIDUXOAXlUHTnUHg/p+QhofiAoskVRsEQfWiANzOBVDyIIq/sELLCqdgpQMPamZJtKzLdgyjaRmmbBlGKZk1UwsGqX+UA0nqt6g42xtYrs9N5/5mzYzc816dEbTOM7wyohxgXDTIKG6foK1/cQHwsODCtDmW9BXpGGYaUedYZy0Fz8y104s5qWvbydOZxX9rt3E48Pt/xpNKunpG3A4NmFPvQ3VKHZBXfX8+vpwv/wy7udfINo6nAminzUL28MPk3L3ZlTmyeuJLooi7b72ROj4ReuqkYvfI8k0ZiaJHDPtM8kyZcl/s2OAs83Lzl+fxdkqCU55M1K5/ePTsTref0EnJsTY276X588/zzsd7yR1Y9xXdh8Plj9IQUrBmM//RjnhPMEP3v0BR3qOAGDWmPnU7E/xaMWjE757aP+QDdXZIRuqBRYj356exzzLB8870tKCb/cefHv2EDh0KGFlB6DQ6TAuW4p5zVrMa9egzR/frpqpgiAK1PbXJrowTjhPJHX/qpVqFmYsTIgY0+3T5SwiGZkx5nSHh/+oPs/2s70AqJUKtizO44vry8m13Tyb6UgohrPVO9TFIdlVBS9T6Kc3axIWVZklKWQWpqA1TIyinNHCv38/3d/8p0R3snHJErKe+hq68vJxntnEZzRzJRxqBXMNKswq6dq7OypwMhAn+D4ruWOVKzHV6AlH+XZTF7/vciECOqWCJ/Mc/FlhJhb11FtfmizIgobMTSEWidN6ZkjEONlHdETwlsmqpWRhBmULM8gqtaIcOjAKwSCeP/4R1y9/NWzdoVKRcscmUh997Kb4j08K3G2w7etw+kXpa60F1v4VLPtTUCcv8gUjcV472cnvDrVyrNWd2J5j1bNlcT5bFueRlzp6iwGiKBL0RhPixmBfEFevj47OXgb7Q6j8OhRc+42f0aolJU2Pxa7HYNEiAoN9QdzdAQb7gpdUyyRQgCVVjy3LKIkcmUZsWdKjyaabEr9PzpYmTlRvpXbPTqJhacFEo9NTsfp25lVuJqNo4vqOi6JIrCdAsFYSN6LtvqRxVZoew5C4oS20olBN/p+XzNURj4dwDezD2fs2zr7txGLuxJhKZSQt7XYc6ZWkp69DrR67Vl9REPDvq8H9/PN4d+xI2LooTSZS7vmQlI0x6/LdcFOFvmDfcC7HkNDR6m297L5WnTXRwXHxsTClcMJ2vU10ouE4h19v4vj2NkRBRGdUs+qhMmasyH7f81e3v5sX61/kpfqX6A30JrYvy17GQ9MeYkP+hgnXjfFBiKLIvs59/PDoDznrOgtAmj6NJ+c9yUPlD03o9xMVRH7e4eTfmrrxDdlQPZ6Txt+UZJM6woZKiEQIHD6Mf88efLv3EGluTnoeTU4O5tvXYl67FuPSpbduXtwo0xvolXIwOmrY37Ufd9idNF6YUijZSOWsYknWkgkvosnITFWOtQ7w/erz7K2XcoK0KiUfXZrPF9aVkZly8/3rRVHE6wrR0zRIT+Mg3U0enG1ehNh7bkwVYM82SSJHidTJYc8yTfrFYTESof//fkHfT36CGAqBWo398cdxfOHzKE0Ts7BuNHnfXImRFk5jkCth0iqZbVRx0YQzolLgzDYTzTSiN2lvaq7EVCMQF/hpWy8/au0lEJcKde/LsPF3JdkUGG69DJ2JhixoyIwZ0UicllP9NBzrpflUP7ERIoY5VUfpggxKF2WQVZySdAKP9vYy8Nvf4v7d74l7hmx0zGZsDz+M/dGPo8nJuenvZUISCcC+H0ofsSCggAWPwoanwJyRtGt9j5ffHGzlxaPteIfsfdRKBRsrMvnI0nzWlDtQjeFFlCvkYnfbbna07WB/537CcakKXymoyBELWWlZy0zNfByxHAL9UUKBKIhgtkuihSVtxGOq/n29E+NRAY8ziLsnwECPH3dPQPq8O3BZ79OLqHUqbBmGIZHDJD0OfWh0k2/xLRwIULt3ByeqttLfPrzYmDN9JvM3baZ82SrUmom74AMQHwwTrHMRqu0n1OCGETcESqMa/XQ7+pl29NNSUeqmVqWTzJURhBhuz2GcziqczirC4e7EmEKhwZ66AofjDtIdG9FpR6d7L9rTi+fll6RujI5hixH9vLmkPvwwKXfeeUvcrF0JX8THuYFz1PXXSbkcrrM0uhuJiZcecw1qA+Wp5UkiR1lq2ahmDU1FWs/0s+u35/D2S0J16cIMVn+kHJP18t+3uBDnnY53eP788+zt2JsIgk/VpUrdGNMepDBl8meNCaLAW01v8aNjP6Ld1w5AnjmPLy74IncV3zWhq+W7w1G+2dDJS0M2VHaNim9YVGw4ewr/7j34DxxADIwIplWrMS5enLCS0paUTIlCjPEmHA/zbs+77O/cz77OfdQP1CeNmzQmlmUtY1XuKlbmrCTPkjdOM5WRkbkch5tdfK/qHAcaXQDo1EoeXV7In64txWEZ32uLeFTA2e6lZyiHo7tpMHEeH4lWr0pkcWQWp5BVbEVvntj3aVci2tFB97e+hW+bZA+pzswk82//Bssdd0z4c5YQFxJixGXDrccyV0KleE92xAfnSmgNKoQz/XirWxBDccnqe2UOKZsK5XvjG0QQRV7uGeBfGrvoDEtuJgtTjHyzLJfF1lv3nm+iIQsaMqNKJBSj5XQ/DUd7aTndn2Q3ZLHrKV0o2UllFqVcUoUQqqvD9Ytf4tm6FYY8yDV5edgffwzrAw+iMssHDgBEEU69IHVlDA4trBWshLu+DdnzknY92e7m394+l6hcASiwG3lkaQEPLcob04u8Nm8bO1t3sqNtB8d6jyUWUwByzbmsL1jP+vz1zM+Yj/omeOGLokjIF2VgSOBwdwcSnw86g+9bGWFO1SV1dFwUOiyp+glfTSOKIu11pzletZULh2oQ4pKwaEixMmf9JuZtvIsUR8YHPMv4I4TjhOsHCNb2EzrrQhgpTqkU6EptGGZKweKqKyzwyUw9RFHE6z1F75C4EQg0jBhVYLUuIsOxCYdjEwbDtVmwiPE4vr17cT//Ar5du2Dob0dpsWC9915sD29BP3366L2ZKUYkHqHeXc/Z/rMJkeP8wPlLQnNByjoqthUniRwz7DMwayevZdf1IgoiPncYd28AT08Ad0+Qvg4vHefcgHQ+WvvIdIrmXl6s6/Z383L9y7xY/yI9gZ7E9qVZS6VujIINaFVTL08hGo/yYv2L/NeJ/6I/JOWBTU+dzpcWfonbcm+bsIsoYizGob011Lz+FuXHj1Da0ZY0rnY4MK2VwrxNK1dOahu7iYIoijR5mtjXuY99nft4t/tdQvHhBUYFCmalzWJlrtSFMccxB41yci4sysjcStQ09PH9qvMcaZFEYoNGxeMrC3lyTSl208Q57/k9YamLYyiLo6d58LIWzdYMA1mJLA4r9lwTqklUTe/bvZvuf/4Xom3Sec20ciWZX/sHdMXFY/q6l82VeE9HxMivR3ZM3IxciZHbbyRXItLpw/3yBSJtkv2oJs9M6n1laPPkUOob5ZDbx1MXOjnulYpKcnUa/qE0h/sybBP2evJWRRY0ZG6YSChG86k+Gt510nKmP0mdTknXJzoxMgotlxwAREHAt3u3lI9x8GBiu2HhQuyf/ASWDRtQqCZfdfyY0fEuvPk30H5I+tpaAJu+CTPvS8rJaHD6+H7Ved44JYVEqpQKNszI4NHlhdxWlp6w9RpNRoZ672jdwfmB80njFfYK1hWsY33+eqalTptQJ4N4XGAw0dWRLHiEfNEr/ju1Ron1otAx9JE6JHho9ROvKsI34OLUjrc5ue0tfK6hAHiFgpKFS5i/6W6K5i5AoZz4F8qiIBJpGZRCxWtdxPqSF0g1uWYMFXb0M9PQZJsm1O+azNji91/A6ayi11mF13sqacxsnonDsYkMxyZMpisfg6JdXbhfeBH3Sy8R6xoO2jUsWoRty0Ok3HGHbO1yncSFOC3eFs72D1lWDQkd77V0uUi+JT/ZsiqtYsqE7IZ8Udy9gUQXofR5EE9vgNhlqvwUCpi7Lp+l9xZfcn6JC3H2de7j+fPPs6d9T6KAwKaz8eHSD/PQtIcoshbdjLc17gSiAX5T9xt+fvrn+KKSbeHizMV8aeGXmJ8xf3wnN0Ssrw/f3nfw7dmN/519CF5vYiyuUFBXXM7B2fPJWL+OP1m/CptWXky/UTxhDwe7DlLTKYV5d/u7k8YzDBmsyFnBqtxVLM9eTqo+dZxmKiMjcyOIosie+j6+X3WOE+2S04NJq+KJ24r5zOoSrIaJdzwV4gKuLj/dQ10cPU2DDHQHLtlPrVHiKLRIIkeJ1MVhsk3sIi4hFKL/v/+H/v/+b8RIBIVGg/0znyb9T/7kfa+l3y9XIvnzD86VuB4mcq6EEI4zuK0F374OEEChU2HdVIhpRc6EL7Sc6LQEw/xzQxevOd0AmFRKvlSYyWfzHBgmkZh4KyELGjLXRTgYo/lkHw1He2k94yIeGyFiOAyULcygdKEDR8GlIgaAEAgM52Nc9ARWqUi54w7sn/wEhrlzb9I7mSQMdsH2b8CJ30lfa0yw+suw4ougGb4Y6PaE+OH28zx3pJ24IKJQwP0Lcvnyxmnk20ff4zcmxDjaczQhYnT5hxf/VAoVizIXsb5gPevy15FjnpxWYSF/NGFZ5e7xDz0G8DiDCPErHxZNVu1QN0eyfZUlTT8mgtK1IMTjNLx7kONVW2k9dTyx3ZqZxbzKzcxZvwm9afJUgUZ7A0Oh4i4irYNJF7Eqmw7DzDT0FXZ0xVYUVxF0LzM1CIU6E+KG230YGD5PGQyFCXEjJWU+xCVxfeC55/DvfQcEaV+V1Yr1vvuwbXkIXVnZ+LyRKY4oivQEeqjtr00SOd674HiRdEP6JbkceZa8CSlcRsNxPE5JqBgWLaTHsP/KFohKpYIUh0E6b2RIj9mlNuw5yZ2qvYFeXqp/iZfqX0o6/y7OXMxD0x5iY+HGW9bKyx1y8z+n/offnf0dEUEKaV2Xv44vLfwSpbbSmzoXURAInT6dCPQOnUoWW1U2G6Y1qzGvWYt38RL+qT/AH3vdAKRp1DxVmsOWrFSUE/B3fKISE2Kc7judEDBO951O6hTWKrUsylyUsJEqs5VNyGOIjIzM9SGKItvrevl+9XlquwYBsOjVfHZ1CZ9aVYRFP/GEjZGE/FF6mwfpbhoWOS5nnWxO1ZFZbCWrRLKrchSYUWsmTjHoxVwJ3/lGBn/wXWLvHgBATMskeO+T+AsXjVmuhFqrvESMuChS6C8RJCZHrkSwth/3HxuIeyT7bsOcdGwfKpHdCW6QwVicH7b08N9tTiKiiBL4WHYaf12cRYZuYh8rbnVkQUPmqgkHojSd7KPh3V5a61xJAVe2TGPCTio9z3zlyteeoXyM34/Ix7BYsD28BfvH5XyMS4gGYf+PYe9/QNQvbZv3CGz4OqRkJ3bzBKI8s/sCv9jXTHhIXNpYkcFf3TGD6Vmj23YYiAbY37mfHW072N2+G0/YkxjTq/Ssyl3F+oL1rMldg01vG9XXnkgIcYHB/lCSddXFDo/gYOSK/06lVmK9mNWRCCU3YcsyojPc/K4OV2c7J6rf5MyubYQD0u+YyZZK5Z/8GaWLlt70+dwocV+E0FkXwVoX4foBxBGVzgq9Cv10u9S9Md2Ochy+3zLjQyTioq9vB07n27gG3kEQhv9G1VET+mOgPRBGd16BQlBgXLoU28MPY6nciFIn3ySMB+6QOyFuXHxs9jQjXqbszqwxM90+nQp7BRVpktBRbC2+KTYx8biAty80QqyQxAtPbwDfQPh9/+1FO0NbhnQ+sA6JFylp+iveTMeFODWdNbxw/gV2t+8mLkr2CFadlXtL7+WhaQ9RYi0Z9fc5Wen2d/OTEz/hlQuvIIgCSoWSe0ru4Qvzv0C2OfuDn+A6iXs8+Pftw7d7N7697xB3uZLG9bNmYR6yktLPmXNJN/Jel5e/q2+nPiD9Di21mvjWtDxmmeXusCvR7e9mX4dkI3Wg6wDeiDdpvMRaIoV5565iUeYiDGr5eykjM9URBJGq2m7+o7qecz3SMcFm1PDkmlI+sbIQo3Zy3AuIgoi7N5Do4uhuGsTV4eO9K3RKlYL0PDOZJVYpdLzYSkq6/oYE21HLlRBFHH0nKL/wAvqwZAvmTJtDfdlDhK7QffuBuRIjBQvTCKsno+Z9MzcnGzF3GPerDYRqJYcFVaoO24fLMMywj/PMJjcxQeQ3Xf18t6mb/qgkGK5ONfONslxmytdbkwJZ0JB5X0L+KE0nnFx410n7WVdSRXpqlpHSRRmULczAnvP+ti6h2lpcv/wlnq1vDudj5Odjf/xxrPffL+djvBdRhNo/QtXXwDMU6Jy3BO78DuQtSuwWjMT5v5om/mtXA4NDYd9LilL56p0zWFw0eie4K4V6g2RpcXv+7azPX8/ynOXyDSKS+DfSuiphZdUbSBIC34shRXtZ+6r3W9waLaKhEGdr9nD4tZcY6JSCVWet3ci6T34WnXFy/n2K0TihejehOhfBun6EkfZhSgW6Eiv6Cil3Q23Xj99EZW4q0cAAHXv/i56OV/Fn9iKOOGQpY1rSbGvIKn6ANPsaVCr5eDaRCEQDnB84z1nXsGVV/UA9UeFSa0CtUkt5avlwN0faDKalTruuc5QoivjdkaQOC8+QePFBGUx6kwZbpgFbhhHre8QLjfbqqyidAScvX3iZF8+/SKe/M7F9YcZCtkzfQmVh5S3bjXE1NLob+dGxH7GtdRsAGqWGj874KJ+d89lRsxcSRZHB199g4Pe/J3jsWKLTC0BpNmNatUrKwlh9G5qMD86uiggCP21z8v3mHoKCgBJ4Ii+dvy7OJkU9cSpwx4tgLMiR7iPUdNZQ01lDo6cxaTxFm8Ly7OUJESPLlDVOM5WRkRlvBEHk9VNd/GDbeRqdUgFXmknL524v5dHlhegnUFfD1RIJxXC2eOke6uDobhq8bFGdwaJJhI1nFqeg0aoI+aNEEjkTsaHMiZuTK2HQxnGceAXLkddRCHFEjRbu/ji6Bz+O3mq8oVyJqYYYF/HVdDJY3YIYiYNSgWV1LpYNBSiv4RpS5lJ29g/yjw2dnPNLGVplRh1PleZQmZZyS//OTTZkQUPmEoK+CE3HJTup9rMDSTfq9hwTpQuHRYz3QxQEfLt24/rFLwgcOpTYbli8CPsnPoFl/Xo5H+NydJ2At/4WWvZJX1tyoPIbMGdLIicjGhd47kgbP9xWT69XEhdmZFn46zuns256xqgchCdaqPdUQBBEvP2hpG6OizZWAc+VuzqUKgXWIfuR1Is2VkNih940uhXIsUiEfc89y5HXXwZRJMWRwV1f+Ap5FbNH9XVuNqIgEmn3Eqp1EaztJ9ab7E2ryTKhn2nHMDMNTY5Z9iCdgkRaWnC/8ALul14m3i9VOIlqEcV9M4iuTcGtryMaHa6iVir1pNlX43DcQXr6ejQa63hNXeZ9iApRGt2Nw90c/XWcGziH/2JX4wiUCiVFKUVJIkeFvQKrTvrZhvzRJLFipE3U5QI7L3IxT0kSKwzDXRcZRvTm6z9GC6LA/s79vHD+BXa17SImSoULKdqURDfGzbZPmuycdJ7kB0d/wOHuwwCYNCY+OeuTPD7zcYya67fmjLlcdH/963irtyW26crLMK1Zg3ntWowLFqDQXN/vQkcowtcvdPC6U+qIdWjVfL00hwczU2+pm25RFKl311PTIdlIHe05mrATA+nve076HFblrGJl7kpmp81GpZTvM2RkZIaJxQVePdHJD7fX09Iv3QtkWHR8YV0ZH12aj24Si8WiKN1nSuKGJHI4W73va5F8LYx2rkS4oYHub/5TIkdVW1hI5te+hvm2VaMy38lOpM3LwMv1RDul61ltYQqp95ehyZqchYYThXP+EP94oYOdLqljK1Wt4i+Ks/hETjoa+f5/0iELGjIABAYjNB530nC0l47zbsQRIkZarpmyRZKdVOpVHECFQAD3K68w8MtfEWlpkTaqVKTceaeUjzFnzli9jcmNrxd2/BMc/TUggloPq74kfWil77sgiGw93cX3qs7T1Ced3PJSDfzFpmncOy8X1Q0chCdzqPdUIBKM4e4NJDI6Lj66ewPJ7brvQW/WvMe+aqirw2FAdQNdHe1nz/DWM/+Bp6cbFAqWfvghVm75GCr11PCRjPUFCdZJ4kak2ZOUu6FM0SZCxfUlNhRTqGX5VkOIRPBWV+N+/gUCBw4ktqsc6dgeeBDbQw+izc8HQBTjuD1HcTqrcDqrCIXaE/srFGpSbctwODbhcFSi02Xe9Pcic/UIokC7tz3Zsqr/LP2hflRxDdZQOtZQBraQA2swA0ckF2vIgTp85Q4HhVJBSro+ySLqYr6FyaobVRG0L9jHKxde4YXzL9Dh60hsX5CxgC3TpG4MvVruKrteRFGkprOGHx79IXWuOgDsejtPzn2SLdO2oFFd23nOu307XU99XRJKNRrSn3wS2/33ocnNHdV573IN8vfnO2gISoUsy4dsqCqmsC3CQGiAA10H2Nexj/2d++kN9iaNZ5myJAEjZyXLspclxEkZGRmZ9yMaF3jpaDv/uf0CHe4gANlWPV9cX8aWRflop0jmXiwap6/NlxA5epulPBGdUYPWIGVJaI1qdAZ1kiChM2oSosRY5kqIosjgG1vp+c63iTv7ALDceSeZf/NVNFm3ZledEIrhebsZ/4EuEEGhV2PdXIRpcZZccHcD9EVi/FtTF8929RMXQaNQ8EReOl8uzMSmkYtzJyuyoHEL4/eEaTru5MLRXjrPu5M8GNPzzZQtyqB0QQa2zKurWIv29DDw7G8YeO45hBH5GKkfeZjUj38cTfbYeRVParpOwrFn4fhv4aLf7+wHYeM3wJaf2G1vvZPvvnWOUx3S9zbNpOXP1pfxyLKC664muRVCvSc7oiDiHRjR1dE9nNfxfv7sI0NlU4fEjouf682aqxKkIsEAO3/535zeWQ1ARnEpm//sL0nLzf+Afzm5iPujhM4PEKrtJ3RuQGrpHUKhVaGfZkNfkYZ+hh3VKHfEyIwN4cZG3M89j+eVV4i73dJGhQLT6tuwbdmC5fbb37daWhRFfL46ep1v43RW4fcnC7wpKQvIcFTicGzCaCwew3cicz0IcQGvK3RJGLerx0dg4FJ7qpH4tG48+l6CpkEM6Soysq0UF+Yxu3gaxalFKBVjs8ghiAIHug7wwvkX2Nm6M9GNYdFYuKf0Hh6a9hDlqeVj8tq3KoIoUNVcxY+O/YhWr2TvmWvO5YsLvsjm4s0f+LOOe730/Ou38Lz8MgC6adPI+e530M+YMWZzDg/ZUP1HczdBQUSlgM/kOvjL4iwsk7iy+CJRIcpJ50n2deyjprOG2v7apNwcvUrP4qzFiS6M4pRiucBGRkbmuonEBP5wpI2nd1yge1CynslLNfDnG8p5YEEu6gkaDj3ViPt89P3oR7ie/Q3E4yiMRhxf+AL2xx+77u7GyYYoigRP9eF+rRHBK3UfGhdkYL27GJVZO86zm7yEBYH/ae/jB83deONSkejmdCv/UJpDiVG2ap3syILGLYbfHabhmNSJ0XnBnVSVnFFooXRhBqULHVgdV992HzxzBtcvf8ng1jchJt2AawoKsD/+OLb770NpktviLiHgglPPw7FfQ/ep4e3Z8+Gu70DB8sSmE21uvvv2WfZdkCxSzDo1n11dwqdXF2PWXbuaPDLUe1fbLgYjg4mxWynUeyoQCcXw9AYZ6PEnZ3V8gD2KzqhOWFZJIocp4emuukxFUv3BGqp+9iNCPi9qrY61jz7BvE2bp+QighgTCDe4Cda5CNX2Ex/pRasAbVEKhoo0DDPTUKdP3arYyYgQCuGtqmLguecIHnk3sV2dmYntwQexPfjAdVdMBwJNOJ1V9DqrGRw8ljRmMk3D4dhEhmMTZvPMKfl3MRERRZHAYCQh8I4M4/Y4g+9rsaAzqhOdFvp0JT6Diy51CxeEWmq9p2nyNCXCtkdiUBuYnjpdsqwaCh8vs5WhVV3/jWZfsO//s3fe8XHUd/p/z/a+q7LqzWruxgVswBQXbIOpCZgkJBdyuVzuUknvhRSOXAqpdyl3vwRSyAWc0ExxwQZMNcWALRc1W13aVdneZ+b3x6xWkiW5IVnF8/ZLr11P2f3uajU7830+n+fhkcZH+HvD32kLtmWWX+C+gC21W9hYsVHNpppkklKShxoe4tdv/ZreqFIhWptVyx3L7+Dy4svH/JsOv/wKnV/7KqnOLhAEcj7yL+R+6lNoDOdm0qEtluDbDR080asUueQbdHy7uph35blm3DGoPdjOi50v8kLHC+zr3kcoGRqxviarJtOFsTx/uZoVo6KiMuHEkiL3v9LKfz/TRG9IKRibk2vljvU1XH9B0TtyQVA5fWJHjtD9ne8qOVQo1o353/wm1pUrp3hkk0uqP4bvkUZiR5WwdF2uGdeNVZhqJibj63xElmUe8/r5flMnrTHlen6xzcyd1UWszrJP8ehUJgpV0DgPCA3EaHrDS9N+D11NI61V8iocVKdFDMcZTM4p+RjP0P+He4m8+mpmueXCC8n+0O3Y1q5V8zFORBKhaY8iYhx9AsT0RKnWAHM3w7IPQNV60CgTyk3eED/efpQnD3YDYNBq+MDF5XxibRU5tjO7mAsnw+xt38uOlh3sbd9LTIxl1qmh3rMPWZIJ+eInZHUoAeXB/ti4+wkCOHLNI7o5BkUPKRVk+29+TsvbygnmnGUXsunf78Dqmr0nWrIsk+wIZcSNZNdIT35dnlkRN5bmYShUhdupIlZfj+/BrfgfeQQpkBZoNRpsV16J69Yt2C6/HEE3ca3E8XgPXu8uvN7tDPheQU5X0gOYTCVpW6qNuJzLEQT1e/CdEo8kR+RZDM+3SMbHD6rU6jWKJdQJYdyufDMm68m71GKpGI2+xoxV1ZH+I9QP1I/47hxEp9FR5awaIXLMy56HVT/+MUGSJfZ17+PBow+yu203KWmoG+O6quu4pfYWarNqz+BdUpkIIskI9x+5n98f+D3BpNIxuzxvOZ9d8VmW5i0FFOHU+9Of0n/fHwHQl5ZS9IO7saxYMSVjfrovwNcb2jkeVc4pL3XZ+I/aYuZZp++5XCQZYV/3PsVGquslWgItI9ZnGbO4uOhiVhet5pKiS8iznDpAXUVFRWUiiCZE/vTycX7zbDP9YeW4Wp1n4zNX1bB5USEaVdiYdGRJwv/Qw3h+/GPEAWWC33HD9eR/8Yvo3O4pHt3EIosSwb0dBJ9uRU5KoBWwrynFsaZUtTx+B+wPRPh2Ywf7/Mq1e75Bx1crC7m1IBvNDCv6UDk5qqAxSwn2x2h6w0PTGx66mwMj1hVUOqhankflMjeOnDO74JEiEXwPPUT/H/9IskVpz0enU/Ixbr8d8+KZHRw8KfQ1wZt/gTf/CsHOoeUFSxQRY/EWsGRnFnf5o/x8VwMPvt6OKMkIArx7WQmf3VBDSdaZBVYe7D3IfXX3sadtD3FxyJ5IDfU+f0kmRPyekdZVg/dPNjloMOtw5pkQY2/SVf8EspTCZHOw4V8/Se3Fl57DVzB1pAZixA73Ez3cR7zJD8OyhkzzsnGsL8NQqlZ8nAukaJTAk0/he+ABom++mVmuKyrEdcstuN797nPivZtM+unt3Y23dwd9fc8hSUMT3np9Dm73VbjdG8nOugSNRq0qHo9UUsTvjeLviWbsoQZvo8HxLaIEAey55qEw7rwhEdbmmthci5SUoiXQMkLkONx/eESX43DKHeUZcWN+9nyqXFUkxSS7WnextX5rxuIIYEnuEm6pvYWr51ytFhVMA3wxH78/+Hv+cvgvmdDpNaVr+ITxavR3/TeJ5mYAXO95D/lf+uKUdyLHRIlft3n4eUsPMUlGJ8C/lrj5fEUBtmlgQyXJEkf7j/JCp2Ijtd+zPyPiAegEHUvcS1hdvJrVRauZnzN/0qzdVFRUVE6HUDzFfS8e53fPNeOPKuch8wrsfHZDLRsX5M+4TriZiOjz4fnZz/D97QGQZTQ2G+477iDrfe+d0EKlqSJ+3M/AQ42kepRwemOlE9e7qtGfgVOKykg6Ygnubu5ia48ihJk1Ah8vy+PjZXlY1WLrWYkqaMwiAr3RTCdGz7FhF9gCFFY5qVqmdGLYss48SDLZ3c3AX/7CwAMPDuVjOBxD+RjnaWjTmMgyeA7Dsefg0CPQ+uLQOnMWLL4Vlr0fCi8YsZsvkuDXzzRx74vHiacUu6ANC/L5wsa5zC04/UlSSZbY276XP9T9gdd7hmxXyuxlbKzYyIbyDczPnq+eiKmMQJZlIv7EiG6OgZ4wvp4Igb7YiM4uSewlGX4SWfQCYHIspWThDWQXudJ5HVay8i1YnIZZ+zmTYiliRweIHuwlerA38/4Ya1w41pVhnKMGk04GscOH8T34IP5HH0MKpW1JdDrsa9fiunUL1ksvnbLuQFGM0tf/HF7vDnp7d5NKDX0Pa7U2cnPW4M7bRE72leh0519HjyTJhPpjw8SKIfEi2D/yGHMiFqdhWBB3WrzIt+DIHdsm71whyzJd4S4O9x/mcN9QALkn4jnlvja9jWsrr2VL7RbmZs89B6NVOVO6w9385q3f8OjRf3DjCyI3vyChlcFn13D/jS7q59nQaXSjfwQdeo1+1HKtoEWnOWGdMHr/zPoT1mk1WvTC6Mcd/PEmNPyqS+R5vyIW5Ok1fLkii+vcjhHPeS7Egt5oLy91vsSLnS/yYueL9Mf6R6wvsZWwuljpwFhVsAqbwTbpY1JRUVE5UwKxJP9v7zF+//wxgnHl2Lq42MnnNtSyZq571l7nTCeiBw7Q/Z3vEjt4EADj/PkUfvtbmJcundqBnSVSJIn/yeOEX1VcODRWHc7NlViW56mfp7MknBL5VauH37R5iKYLDrcUZPHVOYUUmdT8kdmMKmjMcPzeiCJivOHB0xIcWiFAUbVLycRY5sbqOrvK0OjBdD7Gk8PyMcrT+Rg3qfkYGfqPKQLGsWeV27B3aJ2gUayklr1fsZbSjfxdRBIp/vDCcX7zbBPBmPIer6zI5svXzGVFeTanS1yMs61pG/cduo9j/mOAUvW2uXIz75//flXEUDlrUkkRf9riZSAtdvR3Behp3E4irFjOCRoXeus1aHSFmf30Jm1mEnIwsyOrwIIzz4LeMHuqJJK9UYJ72ojs92S6NgxzHIqwUT3z/MynG2IoTOCJx/E9uJXYgaHMIX1pKa4tW3C966Zp14IuSUkGfK/g9e7A691JIjE0wa3RGMjOugy3eyO5uesxGE7/OD/dkWWZaDA5osNiMN/C740gpcY/lTSYtJnuCtcwiyhnnhmDaWZV4vXH+jnSp4gbR/qVbo6WQAt6jZ552fO4ufZmrq64GotercKb7sSbmzn2+c8gH24A4IX5Av9vo4aQZfoe1+OmpYSyPoCkzwdAHzuIrf+P6FJdAGgEzRkJKeMuO2G5XqNHlEX2e/ZzpP/IiDGZdWZWFazi0uJLWV20mjJH2Tl/X1RUVFTOFl8kwf/sbeYPLxwnklA62peVufj8hrmsrs5Rz/UnGVkU8T34IJ57fpqxl3VtuQX35z6HLmtm2B/Lskxkvwf/48eQwkrXj+XCfJzXzEFrPT+CzycaUZb5W3c/P2juwpNQ5tEudlq5s7qYpQ71HPt8QBU0ZiC+nghN+z00vu6ht20oOE8QoKjWRfXyPOYsdWN1np2IIYsioT176L/3PiKvvZZZbrnoIrL/+UPYrrxSzccIdsOxvXDsGUXA8LWOXK8zK8HeVWsVSylH0aiHSIoSf3u1jZ8/3YA3qNhBzSuw8+Wr551RxYcv5uNvR//G/Ufuz1TA2fQ2ttRu4bb5t1FgVbtnVCYHWZZp2PcGT//vz4kE+kHQkFu2Do3hIoJ9cU72rWHLNo7o5sjYxGQZZ+xFQao/RvDZNsKv9UA6kNhQZse+rgzT3KwZ+7qmAlmWiR2sw/fAAwQefxwporRjo9djv2o9WVu2YLn4YgTN9LclkWWJQOAtPN7teL07iEaH+8VrcLkuIi+du2Eyjf6umI4koilFsBjstEiHcft6IiRiJ8m10Glw5g1ZRDmHdV2Y7SfPtZjpSLKk2ujMIGRJYuDPf8bzk3uQ43E0Tifub3yN8JplRFNRUlJq5I+cOumypJQ8o+2H/yTl5JjLx9xHHnw+8Ns2EXJcC4IB5BTmwJNYA48gyPFTvwETwPzs+VxadCmri1ez1L0UvVadsFFRUZnZ9IXi/Pa5Zv740nFiScVRYeWcbD63oZaLK3OmeHSzn1RfH54f/wT/Qw8BoHU6cX/+c7huuWVaXxMkvRF8DzcqlsWALs9C1ruq1Y7+d8DzA0HubOzkYCgKQLnJwDerirjW7ZzV1xMqI1EFjRlEaCDGtl+9TV/HMBFDI1Bcq3RiVC51Y3GcfUuVFA7je+hhJR+jdVg+xuZrlHyMhQvf6UuYuUQH4PgLQx0Y3pGVZ2h0UHwhVF4Jc66AkotGdWIMIkkyjx/o4ic7jnK8T5mkK8028/kNc7nhgqLTDhtrC7bxp0N/4uHGh4mmlAN5gbWAD8z/ADfX3Ky276ucM2KhELv+9784+tJeAIpq57Pp3z8LgjPd1REekdcRj6TGfSydQTMykLzAQla+dUZVaaf8cULPtRN6pRvS9nH6YhuOtaWYFuRMqK//bEMMBgls28bAAw8SP3w4s9xQXo7r1ltx3nQjupyZe8EoyzLhcD0e7w683h2EQodGrLfbF2fEDau1eopGqSAmJfy9Y4dxRwKJ8XcUwJFjOiGMWxExbNkmNVBTZdqT7Oyk86tfI/LKKwBYL7uMwru+jz4/f4pHduYci0T5RkMHT/cr1w4FBi1fKHOw1qVDlMVxRZRBcWSUEHMKIUWURWqzarmk8BJyzDP3WK2ioqJyMjzBGP+9p4n797WSSJ/rr67O4XMb5rKifGZ0DMxkIm+8Qfd3vkv86FEATBcsoeBb35p281VyUiLwTBvBZ9qUYjedBsf6MuyXFyNMoWXqTKYpEuN7TZ081at06jh0Gj5bXsCHS3IxTmNRS2VyUAWNGYQkydz7lReIh5KUzMuiankec5bmYra9M1+4ZHc3A3/+s5KPkW7h0zidZN16K1kfeP+MvIB7xyTC0PrykIDR9RbI0rANBChYnBYwroSyS8B4cgFBlmX2NvTyw+1HONihvM+5NgOfWlfD+1aWYTjNL7W3vW9zb929PN36NFJ6TPOy5/GhhR9iY8VG9Bq1Ak7l3CPLMkeef4Zd/+/XJKIR9CYz6/7531h45foRVRKyLBMLJU/I6lDuB7xRJGn8rxqry5ixrhouetizTdNSJBCDCYJ7Owi/3ImcUP5WdfkWHOtKMS92T8sxTwWyLBN98018D24l8OSTyFFFoBUMBuwbN+K6dQuWiy6aldU20WgbXu9OPN7t+P2vMzxIwmKpxO3eRJ57I3b74gl5/bIsIyYlknGRZFwkEUvfRlMEhokXvp4Iwb7YSbuszA4DrjzzCHsoV54Fh9uETn+ed3GqzEhkWcb/8CP03HUXUiiEYDaT/+Uv4XrPe2b88WdHr5+vN3TQFkuHnGfZuau2mCrLmefqqaioqKgodPmj/NeeRv72ahvJdHf2mrluPrehliUlrqkd3CxHTqUY+Mtf8P7il0jhMGg0ZL33vbg/cwfaaTB/GGv04Xu4kVSvcl1jrM0i68YqdDnmKR7ZzGQgmeKnx3v4fYeXlAxaAT5YlMvnKwrINcyMokeViUcVNGYY3c1+XHkWTLZ3PmkdPXBQycd46qmR+Ri3367kY1jOI9+5VAI6Xh8SMNr2gZQcuU1OzVAHRsXlYDl93/P9rQP88KmjvNTcB4DNqOOjV1TyL5fNwWo89QFYkiWebXuWe+vu5Q3PG5nlq4tX86GFH2JVwaoZf7GtMjvwe3p48r/uoeNIHQA1qy5lw79+ErP91MdxUZQIeIdldQwTPGKh5Lj76fSajHXNiYKHwTz1JzhiOEnohQ5CL3QixxU7Hl2uGfvaUixL3Qja87OaRPT78T/6GL4HHiDe0JBZbqiuImvLFhw33DBjfHEngniil17vLry9O+jvfxFZHvrM6/X5OK1rsRnXoheWkIoLJOMpRYyIiyTTwkQyLpKMpYbuDxMtBn/kk4iGJ6I3Dsu1GBQv8pUcHOM0+NtSUZkoUn19dH3724R2PQ2Aedkyin5wN4by8ike2cQRESV+2dLDf7V6SMgyekHg42V5fLo8D+v5biWroqKi8g5o64/wq92NbH2jHTF9nnXV/Hw+t6GWBUXqXNZkkuzx4PnhDwk8/jgA2pwc8r74BZw33jgl8yNiKIH/8WNKtiKgsetxXV+FeXGuOl9zFiQlmXs7evnJ8W58KeU6en22g29VFzHXqhZlnO+ogsZ5hiyKBHfvpv+++4i+9npmuWXlSrI/9CFsa66c1v6DE4YkQveBIQGj5SVIhkdu4ygZEjDmXDFmDsapaPSE+PH2ozxV1w2AQavhny4p5xNrq8m2nrqzJpaK8VjzY/yx7o8cDxwHQKfRce2ca/ngwg9Sm1V7xmNSUZlsJEnk1Uf/wYsP/BlJFLFlZbPp45+lYsmys37MWDiZsazy9YTTtxH83iiSOP7Xk8VpGJHRoYgeVuw55976RoqmCL3YSeiFDqS07ZY224T9yhKsK/LPi9ZjWZaJvv46vgcfJPDUduS44uUuGI04rrkG161bMC9bNiNP+EVRGhIWMiJCarSocDLBIb0uJQYxZr2JtegNbAUH0eiHPO9TcRuhziWE2pcT7lmALJ1dgYPOoEFv0qE3atEbtRmbKOXvRMm3sDgMM/J3oaJyJgR37aLrW99G7O8HvR73pz9Fzoc/PGvz4o5F4nytoZ09/UEAio16vldTzDW5qu+0ioqKyjvheG+YX+xu4OH9HQzWj2xeXMBnrqqlNt8+tYOb5YRffpnu736PRHMzAJYLLyT/W9/EVHtu5ktkSSb8Wjf+J48jR1MggPXiQpybKtDMENvk6YQsy+zoC/Ddxk6aosp10Fyrie9UF7EmW50fVlFQBY3zBCkcxvePh5R8jLY2ZaFOh/PazWTffjumBQumdoCTjSxDb0NawHhWCfSO+UZuY8kZEi/mXAnZlUrS+lnQ6Yvy810NPPh6G5IMGgHevbyEz26opdh16jbDgdgAfzv6N/565K+ZoG+73s6WuVu4bd5t5FvPQxswlRlHT3Mjj//yxwx0tgOwfPONXP6+29EZ3plN3nAkUSLQFxthXTXY4RE9ic9/Jpx4uH1VgXJrtEyubZsUTxF+uYvg3g6kdOeJ1mnAfmUp1ovyEWahXU9qYAD/w4/ge/DBzIUGgHHuXFxbtuC8/jq0znMXjCdJ8jDhITVChEjEUyd0PAwXH0aKEcPXiSnp1E98FgjaBPaiI9hL3sSSvx+tYShHS5ZMEFuBNnkpRi7BYHSgN+rQm7QZocJg0irL0v/Xm7ToDFo1y0LlvEcMBum56z/wP/wwoByPiv7zB5jmzZvagZ0DZFnmqV4/32jooCOufA+tzbZzV00JlZaxM+BUVFRUVE6PRk+Inz/dwLa3O5FlZUrhhguKuGN9DZXuc5dzmRIluvwx2geitA9E6PTFcFn0VOfZqM6zkWc3ziohW04k6Lv3Pnp//WvFwlarJfuDHyT3E59Aa7NO2vMmu8MMPNRIokWxFdcXWsl6dw2GUlXEOhsOBiPc2djJ8z7lmidXr+PLlQW8ryAHnXr9ojIMVdCY5SS7uuj/85/xPfAgUlCpxNI4nWS9971k3XYb+vy8KR7hJOJrG+rAOPYcBLtGrjfYoWL1kICRtwDeYXfKQDjBr59t4t4Xj2cCwjYuyOcLm+aeVlVGa6CVPx76I480PkJMjAFQaC3knxb8E++ueTdW/eR9EauoTAbJeIxn//wH3tqhtAHnlJSx+VNfIK+ictKfOx4ZmdWRsbLyRJBS43+lme36YRkd1oyNlSPXhGYC7aGkhEh4XzfB59qR0uKLxq7HfnkJ1lWFaIwzW9iQZZnIK/vwPfAAwZ07kZPKpJlgNuO4djNZt96KafGpsyFkSSaZGN35kBglOpwoTIyxLv3/VHJyxAcAjU5QhIQThIVBMUFv1GHI3B+5fEiAGFyuQ2/QZD53kpTC738Nj3c7Xu8O4vHuzPMKgp7srEtwuzeS696A0ZA7aa9RRWWmE375FTq/9lVSnV2g0ZDzL/9C7qc+iWYCBfeZQESU+EVLD/+dtqEyCAKfKMvjU+X5WM5TO0QVFRWVieJId4Cf7WzIuDVoBHjXshLuWF9DWc47t/dOihLd/hhtA5G0aKEIF+0DUToGonT5o5zMadRu1FGZZ6PKbVVEDrcidJRlW9DN4O+AZGcnPXffTXDnLgB0eXnkf/Ur2K++ekIFHCkhEny6leDeDpBkBIMGx4YKbJcWIWjVifczpSee5D+PdfHXrn5kwKgR+GiJm0+X52PXzezrYpXJQRU0ZinRAwfo/8O9BLZvB1HxmjNUVJB9+wdx3njj7MzHCHnheFq8aH4WBo6NXK81QtmqtICxBoqWgnZiKrEjiRR/eOE4v3mmiWBcsZJZOSebL189jxXlp/aAf8v7FvceVIK+5XQo7Pzs+fzzon9mQ/kGdBq1TVFlZtO8/1W2//rnRPw+tDodl733g6y49qYpsbiTJJlgX2xEN8egjVXEP35Xh0Yr4HSbT8jqsJKV/85yjeSURPi1HoLPtCH6lJZajUWH7fJibJcUzag2ZVmWiXV76X/4cfq2PUWspx9Ra0TUGtGUV2FYeSm6+YsQ0Z22DVMqnTsyGQgaYaSAMCgiDBMaDJl1ulEihGGw82HYcu05sg6TZZlg8ABe7w483h1EIk3DXxlO5wry3BtxuzdiNpeekzGpqEx3pFgMzz33MPDHPwGgLyuj6Ad3Y1m+fIpHNrU0RWJ8vb6DZwaU4qdSk4Hv1xSzMccxq6p3VVRUVKaCgx1+frqznqePKLkKOo3AlgtL+OS6mpO6NyRFiS5fLCNStJ8gXHQHYicVLAAMOg0lLjPFWWaKnGb6IwmaPCFa+iOZvI9R+2g1zMm1Up2viBw1+YrQMSfXinEGTSyHnnuO7u/fRbK1FQDrpZeS/41vYKyc844fO3qkH98jjYgDyrWbaUEOrhuq0LnULsczJSpK/KbNwy9bPUREpejsxjwXX68spMysvp8q46MKGrMIWRQJPv00/ff9kejrw/IxVq0i+0O3Y7tyluVjxALQ8sKQgOGpG7le0ELx8qEOjNKVoD+13dOZkBQl/u/VNn7xdAPeoPJlNr/QwZeunsuaWvdJLwJFSeSZ9me4r+4+9nv2Z5ZfXnw5H1r4IS4quEi9iFSZVUT8Prb/9hc0v74PgNKFS7j645/Fkeue4pENkYim8HkimYyOwVufJ4J4kqp+k1U/OpS8wILDbUZ7mhVOsigR2e8huKeNVJ/SoSWYdNhWF2FfXYRmgq2wZFlGTEpjiAgnWC6daLU03rpIgmRSBibnuCUIjBYcxupoGLVutOgwKEZodMKsOc6Gw014vTvwencQCL49Yp3NNh+3exN57o1YrbWz5jWrqJwJ0QMH6PzyVzK2d673vof8L34RjVXtfgXlO+Fxr59vNXbQmbahuirHwfdriqlQJxRUVFRU3jH7Wwf46a4Gnqv3AqDTwHVLilg/P59IIjVCrOgYiJ6+YJFlpthlpiTLQkmWOf1joTTLTK7NOKbNaDwl0toXodETUn68ym2TN0RsnGsejQDlOdaMZVVN+rbKbcNqnJ4FWFI8Tt///C99v/sdciIBej05//Jhcv/t39CYz3xuSAzE8T3WTPRALwBapxHXjVWYF+RM9NBnPZIs81DPAP/R3JWxv1xmt/DdmmIucqrnZiqnRhU0ZgFiKIz/H/9Q8jHaFa969HqcmzeT/aHbMc2fP7UDnChkGbregiOPQ9Nu6NwP8gmVu/mLhgSM8kvBNDmfHUmS2Xagi5/sOEpLXwSAsmwLn99Yy/VLik7qTR5LxXi06VH+eOiPtARaANBr9FxXeR0fXPBBqrOqJ2XMKirTAVmWOfD0dvb88X9IxeMYrVbWf/hjzFt95bSeZJUlmeDAsK6O7qG8jtBAfNz9BI2AI9dEVoF1mI2V8mO268d8zbIoEz3gJbC7jZRHOb4IRi2WlQUYLywgpRNGiQqDHQ6JMQSH4d0PiRPWyae6SnoH6LQyBqthhMhgOKH7QT+s++FUwoRWr5nWn5HpRCzWide7E693Bz7/q8jDvivN5jLc7o3kuTfhcCxFEGZRoYOKyhjIySS9v/ktvb/5DYgiOrebwru+j+2KK6Z6aNOSsCjys+M9/KbNS1KWMWoEPlmWxyfL8jHPYAsSFRUVlXNNPCWmOyyGWUH5ohzuCtDsDZMQT22BatRpKM4aLVYM3s+1ji1YnC2SJNPhi9LoCdHgCaZvFbEjGEuNu1+xyzxK6KjOs+GyTA8rx0RrK93f/z7h5/YCoC8qIv8bX8e+bt1p7S9LMuGXu/BvP44cF0EDttXFOK4qn/E2wVPBPl+Ibzd2sj+oXOsWG/V8o6qIG/NcaNTrPZXTRBU0ZjDJzk76//wXfA8O5WNonU5c73svWe+bJfkYkgitL8ORbXB4G/hbR67PrhwSMCouB9vkVnrLssyz9V5++NRRDnUpoU+5NiOfXl/Ney8qw3ASq5H+WD9/O6IEfQ/EBwCwG+y8Z+57uG3ebbgt06dKXUVlsunv7ODJX/2Y7qYGQOnWmHfpFRTPW0B2UcmM6iZLxFL4PVEGesIjszp6IqQS41+oGC26jMih1WtGCw7RJFlxkXJJwpG+UEnJMsfjEo1xifgEfivrDJoRQsLojIdhAoNeQGprJvHqyyTffgNtMopWjKM36ci6ag05t9yAbcE8BDW0bVqQSPTT27sbb+8O+vv3IklDtmoGQx5u91W43ZvIcq1Co5nYLiAVlakm3tRE55e+TKxO6eJ1bN5Mwbe+idblmtqBzQAawjG+1tDO3gEllLM8bUO1Idc5xSNTUVFRmR7EUyKdwyyhOk6wheoJxjjVLJogkNlGqxG4sDyLm5YVM6/ATkmWhVybYVoU9MiyjCcYVwSOniCN3hANPUpHR29ofMveXJsxI3DUpC2sqvNtuG3nPpBclmWCu3bR8x93k+pS8lVta9aQ/42vYygpGXe/REeIgYcaSLYr34f6UjtZ76rGUHTuAt5nCy3ROHc1d/GoxweAVavh02X5fLTUrRZNqJwxqqAxA4m+/Tb9995LYPuOoXyMOXOG8jHOonVuWpGKKxZSRx6DI09ApHdonc4M1eth7jWKiOE6d77gb7QO8MOnjvBycz+ghGh99IpKPnzZnJO2WLYEWvhj3R95pOkR4qJSyV1sK+afFvwT76p+Fxb9LMwzUVE5DcRUin0PP8grDz+AmA6MBjDZ7BTNnU/x3AUUz11AflUNOv3Mm2iVZZmwLz5kXzUsoDzYHzujx8rXCcw1achKi6aiDF0agS6TDsmsO4kN0+hg6hO7JHQG7WlVdiW7uvD9/R/4/v73zEUAgHn5cly3bsGxadPM//6Z5aRSYfr6n8Pr3U5v7x5EMZRZp9M5yM1Zh9u9kZycy9Fq1e8mlZmLLEkM/OlPeH5yD3IigcbppOBb38R57bVTPbQZhSzLPOr18e2GTroTyvf0plwH360uply1oVJRUZnlxJIinb5oprPixAyLnsD4XdqDmPSacborlNtsi57nG/v4yc563mrzAWA1aPnwZXP4yGWVOCfYcnYyGAgnMgLHYGdHkydEp3/86x2HSUdNvj2T0VGV7uwocpontONkLKRIhN5f/4a+e++FZBLBaCTn3z5Kzkc+gsYw1FEixVMEdrQQerETZKVj3nl1BdZVhWrh1hkSSIn8vKWH/2nzkpBlBOC2wmy+PKeQPOP0/4yrTE9UQWMGkezooOOLXyL6xhuZZZaLL1byMa64YkZVNI8iHoSGnUonRv0OSASH1pmcUHsNzL8eqtaB4dxOsjR6gvxo+1G21/UAik/lBy8u5+Nrq8m2jt1CmZJS7OvexwNHH2B36+5M0PfCnIV8aNGHuKrsKjXoW0Ulja+nm7pnd9Fx5BBdDUdJJUZeHGj1egqqahSBY95CimrnY7LN7IqYZELEn87q8HsiyDInWDHpRuVD6IxapNYAoWfaSRxXOsTQCFiW5+FYW4ouZ+LFBDmVIvTcc/j+9gChvXtBUjpONE4nrptuxLVlC8Zq1SZvJiJJcQYGXsbj3YHXu5Nksi+zTqMxkZN9OW73RnJz16HXu6ZuoCoqZ0iyo4POr36NyD4lr8l6xeUUfu/7s6NzeYoIpUTuOd7D79o9pGQwaQQ+XZ7Px0vzMKkVlSoqKjOUWFKkwzfYWREdFb7tCZ5asDDrtaPEiuEWUTnW0+uwkGWZ3Uc83LOznrpO5TzfbtLxkcsq+fBlFdhNM2/SNxRP0TTMsqoxbWHV2h8ZNxvErNdm7KqGW1iVZVvQTfD3Tby5me7vfo/Iyy8DoC8vo+Ab38R62WpidX34HmtC9CvdJ+Ylubiuq0LrmB4WWjOFlCTzl64+fnism76kYll2mcvGd2qKWWhTC+FU3hmqoDGDkBIJGtevR/T5cV57rZKPMW/eVA/r7An3Qf2TcPgxaNoD4rATBlsBzLtWETEqLgPtuf8C7/RF+enOev7+RjuSrIRg3bKihDuuqqXYNfrgm5JSvN7zOk8df4qnW57O2EoBXFlyJbcvvJ0L8y+cFi2jKirTFTGVwnO8iY4jh5Sfo4eIBvyjtsstLad43oKMyGHPdZ83f1uyLBNv9hPc00a80acs1IDlgjzsa0vR571z0TfR3oHv71vx//0fpDyezHLLRRfhuvVW7Bs3oDGq1bmzBVkW8fv34/XuwOPdQSzWllknCFpcrlXkuTfhdm/AaMyfwpGqqIyPLMv4H3qYnrvuQgqHEcxm8r/8ZVzvufW8+X6YbI6GY3y1vp0XfUp3V4XZwF01JazPUa/VVFRUph+DgkX7wOjuivaBKN7TECwsBu1IseKE8O3s0xQsThdZltle181PdzZwtEcp8nRZ9Hz0ikpuv6Ri2oZvnwmxpMix3vAooeNYb5ikOPa0o0GrYU6udaTQkW9jTq4Vo+7sMyxkWSbwxBN4fvCfpLxeBHM2tqs+DdoiALTZJrJuqsZUm3XWz3G+sqcvwJ1NnRwNK5061RYj36oqYkOOQz0vU5kQVEFjhhHetw9DRQX6vBlaZeZvV0K9Dz8GLS+APMxfPrsS5l0H82+A4hUwRR0nA+EE//1MI/e91EIipYxv08J8vrBxLjX59hHbipLIG5432H58OztbdtIf68+syzJmsbFiI7fNu41KV+U5fQ0qKrMFWZYZ6Oqk42gdHUcO0Xn0EANdnaO2s+XkpsUNReTILStHo5n9AW3xlgDB3a3EjqYFVAHMi3NxrCtDX2A9o8eSk0mCe/bge+BBwi+8kDH01WZl4XzXu3DdcgvGyjkT/RJUphmyLBMKHcbr3YHXu4NQ+OiI9Q7H0nSo+EYsFvXzoDI9SPX10fWtbxN6+mkAzMuWUfSDuzGUl0/xyGYfsizzsMfHnY0d9CSUastrcp18t6aYUpNauaqionLuiCXFccWK9oEovaHTEyxKsyzprorRtlBZFv2UTL5KkszjB7r42a56mrxhAHKsBj62pooPXFyOST/7rnOSokRrfySTzTGY1dHoCRFLjp1LqBGgPMdKlXsoo6Mm30aV23ZG4k/KH8Tz04cQQ0UIOiOylEKf4yfvU9egsahFXGfC0XCM7zR2sLtfEeSydFo+P6eA24ty0atWXSoTiCpoqEw+3nolD+PwY9C5f+S6gsUw73qlEyNvvpKKNUVEEil+//wxfvtsM8G4coG2ak42X75mHsvLhhR5SZZ40/MmTx1/ip0tO+mNDmV8OI1Oriq7ik0Vm7io4CLVVkpFZRII+wborD+c6eDwHGtCSucJDWIwW4blcMynoLoWvdE0RSOefBLtQQK724gdGrINMi3IwbGuFEOJ/SR7QqKlBd/Wrfgeehixd+h4Zr30ElxbtmBbv36En6zK+UUkcjwjbvgDI7/DrdaatLixCZttgVptpTIlBHbupPvbdyL294Nej/vTnyLnwx9G0M6+yZ7pRDAl8uPj3fxvuxdRBrNG4DPlBfx7mRvjTLbBVVFRmTZEEyIdvghtY4gVHQORk4ZRD2I1aE+aYeGaIsHidBElmUfe7ODnTzfQ0hcBwG038ok1VbxvVdk76k6YKUiSTIcvmu7mUDI6GtNWVsFYatz9il3mTDZH9bBbl2XkdU28NYDvH40kuxXhSI51Ennht0jBLgzVVRR861tYV66c1Nc4G+hNpPjRsS7+3NWHKINeEPhwcS6frcjHpVfnxVQmnkkTNJ577jl+9KMf8frrr9PV1cVDDz3ETTfdNOEDU5mGyLIiXBzZpogYvfXDVgpQdnG6E+M6yKqYqlFmSKQk/u/VVn7xdGOmimNBoYMvXT2XK2sVGxtJlnjb+zbbj29nx/EdeKJDFix2g531Zeu5uuJqVhauRK+Zef6WKiozmWQsRldj/VAXR/0RkrHoiG00Wi35c6opmjfUxWFxOKdoxJNHsjtMYHcr0QO9pKN7MM3Nwr6uDGP50HeplEgQ2rWLgQcfJPLSy5nl2txcXO9+N65bbsZQVnauh68yzYnHe/B6d+H17mDA9zKyPHQRaTIV43ZvxJ27EZdrBYIw+y+wVaYWMRik5/t34X/kEQCMc+dS9MP/xDR37hSP7PzicCjKV+vbedmvTARVmo38R20xa7LV6zcVFZXTQ5Zl9rf5eKmpj0NdgTMSLGxG3RhixdB9p3l6CxanS1KU+Mcb7fzi6UY6fMp1TqHTxCfXVbNlRSkG3fknJMuyjDcYz1hXDQodjZ7QST87uTYj1XlWFmZb2eBNUdwSRgAEsw7X5jmYl7kJPPoonh//WCmWABzXX0/+l76Izu0+R69u5hCXJP63vZefHe8mKCqdNNfkOvlmVRGVaneLyiQyaYLGk08+yQsvvMDy5cu5+eabVUFjtiOmoPWltIixDQLtQ+s0eqi8UhEx5l0LtulhlyVJMo+93clPdtTT2q9UO5RlW/j8xlquX1KEIMCB3gOKiNGyg+5wd2Zfm97GurJ1bKrYxCWFl6CfgowPFRWVsZFEEW/r8UwHR+eROkID/aO2yyoqGbKpmrcAV37hrLjgAUh6IwT3tBF50wPpDm1jlRPTfD3h5x8j8MjDiAODNlUC1ssuw3XrFuxr1iDo1eOZyqlJJv309u3B691OX99zSFIss06vz8adexVu90aysy9Fo1EvZlQmlvBLL9H5ta+T6uoCjYacj3yE3E9+Qu0mmyJkWeYfPQPc2dSJN21Dda3byXeriylWbahUVFTGwR9J8o/97dz/SisNntCY2wwJFqPFitIsCw6zbtacv58OiZTE315r4792N9IdUM69SrLMfHp9De9eVjzhwdkzlYFwImNX1dATUu73BOn0K+/ZVej4FCZyUN6vJ0jwR2OKvHwbNXl2qvNsVNoEsh75P4wP/BmNLKGx2XDfcQdZ73svgk7tOJBlmW1eP99r6qQ1pghIi21m7qwuYnXWyR0CVFQmgnNiOSUIgipozEaSMWh+RrGTOvokRIasTtBboGaDYidVuxFM06MSOhBLcqgzwFttPv72WhvNaT/KXJuRO66q4dYVJTT6j7D9+Ha2H99OZ3jIq9+is7C2bC1XV1zNpUWXYtCqF2gqKjMBWZYJeHsyAkfHkUP0tbeO2s7idKW7NxZSPG8B7vI5aGf4yWqqL0rg6RYi+z0gC+lljSSObkMQ+nDd/G5cN9+Mvrh4ikeqMpMRxSj9/XvxeHfQ2/s0qVQgs06rtZGbswa3eyM5OVei09mmcKQqMx0pGsVzz08Z+NOfANCXlVH0gx9gWb5sikemAhBIifzoWBf/r70XCTBrNHyuIp9/K3VjUG2oVFRUUM7L32gd4P5X2tj2difxdGalWa9l7Tw3S0tdlOdYKXadn4LF6RJLivx1Xyv/tacp4zJRkWPhjqtquOGCYrRqVsGY+LtC9P2jAUObIqD1GgR+a0qxPRhGGmfG06wVKIn0Uuo5TmmwhyqngRUfuY25l604bwWk/YEIdzZ28Eq6OzPfoOOrlYVsKchGq/69qpwjpo2gEY/HiceHQpsCgQClpaWqoDHdiAWgYYfSidGwExLDKinMWTB3s9KJUbUW9OYpG6Ysy3QHYhzqDFDXGVBuu/y09Y+0obGbdHz08jlctjDBsx272H58O+2hoe4Ss87MmpI1bJqzidVFqzHpZq8Hv4rK+UQ0FKTz6OGMwNHTVI+YGunBqjMaKaqZS1Fa4CiqmYvBbJmiEZ858YYGBh58EP8jjyIntBhqNqEvvwwh3VGmL7biWF+OaX62eqGoMmFIUhKfb58ibnh3Ek/0ZNZpNAayslaT595Ebu56DIbsKRypykwjeuAAnV/6MoljxwBwve+95H/hC2is1ikemcqJ1KVtqPalJzqqLUburinh8my1YlNF5XzFH03y8P4O/rqvlSPdwczyeQV23r+qjBuXFeMwqV3CZ0o0IfKnl4/zm2eb6Q8rVfLVeTY+c1UNmxcVolGFDQDklETw2XYCe9ogJYFOwLG2DPuVJQg6DbGkyLHecCaboyltYXWsN0xSHHsqVIfEnFwrtYWuEVkdc3KtszK0HaAzluA/mrvY2qN0+ps1Ah8ry+MTpXlYz4M8F5XpxbQRNO68806+853vjFquChrTgJAXjj6hiBjNz4A4zI/QXqRkYcy7DspXg3ZyqpllWSaaihJOhgknw6SkFBpBgyAIyLJAx0CURk+YRk+Yhp4wDZ4wvkgSENJVyQJy+n6R00xtgYPa0hBGewN72nfSEmjJPJdJa+KKkiu4es7VXFZ8GWbd1AkzKioq54ZUIkF3c4OSwXFU6eSIh8MjthEEDe6KOSO6OGxZ02tCVopGCTz5FL4HHyS6fyjAWVdUiOvmm7FffSOxwwnCr3QhJ5WKOH2BFfu6UsyLchHUix6VCUSWJQKBt/B6d+Dx7iAaPT5srQaX6yLc7g3kuTdhMhVN1TBVpjlyMknvr39D729/C6KILi+Pwru+j+3yy6d6aConQZZlHuwZ4LuNnfQmlYKBG/JcfKe6iEKj2uWsonI+IMsyb7b5uP+VVh57u5NY+tzTpNdw3ZIibltVxrJSl1pYMwGE4inue/E4v3uuGX80CShi0Wc31LJxQf55/R7Hm30MPNRIyqsUtxqrXbhuqkafe+p5npQo0dIfyWRz1Lf1ceTQcY6nDMR1Y3+XaQTFyrw6bV01KHRU5dmwGWdm9384JfKrVg+/afMQTbey3JKfxdcqCylSrSVVpohpI2ioHRrTDF8rHHlcCfVufQlkaWhdTjXMv16xkypaBuO0kCelJJFkhFAyRDgZJpKMZASJET+pketG7ZNeL3PWH8FTYtQaubz4cjbN2cQVxVdg0c+cKmwVFZWJR5Yk+tpbMx0cHUcPEfB6Rm3nzC9gztILuWDDNeSWlk/BSBViR47ge+AB/I9tQwqmq960Wuzr1uLasgXr6tUI2qGqGTGUIPR8J6GXOpHjIgC6PDP2tWVYlrgRtOfvRY/K5CDLMuFwA17vdrzenQRDdSPW2+2LcLs3kufehNVaPUWjVDldUqkgweAhEgkvGo0Bu2MJJmPBhD9PvLGRzi99mdihQwA4rr2Wgm9+A63LNeHPpTI5+JMpfnismz90KDZUFq2Gz1cU8K8luaoNlYrKLCUYS/Lwm53c/0orh7uGbChr823ctrKMdy0vwWlWuzEmg0Asye+fP8b/23uMYFwRkxcXO/nchlrWzHWfV8KGGE7if+IYkdeVbmGNTY/rukrMF7zz9yH0+uu8ffdPafSEaXXk01k2j87KRTSHRAKx1Lj7FTlNVOfbqXYrIkdNvo1qt40s6/QUBSRZ5m/d/fyguYuedEbWKqeV71QXs9ShzpmpTC3TRtA424GpTBCyjOw5QvTwQ4SPPkHYe5iwRiCi0RAWNISzKwgXLCLsriFstCpiQ2psgWJQnEhIiVM/7xkPUwDJiCxrARlBkAEZBBmNABpBRvluktP/JKThYswwsk3ZrMhfwVVlV3Fl6ZVY9aplgYqKyvgEer3p7g3FqsrbcgyGfTWWLFjE0o3XUn3RxWh1k3+RJoXD+J94At8DDxI7cCCzXF9SgmvLFpzvugl9Xt7JHyOSJPRiJ8HnO5HTJ9+6HBP2NaVYluUh6NTJJpXJIRptx+vdgde7A5//NRhWtGCxVOJ2b8Tt3ojDvuS8uviejohilGDoEMHAAQKBAwSCB4hEmuGEQhOLZQ5ZWZeSlXUJWa5V78hSTJYk+v/4R7z3/BQ5kUDrdFLw7W/h2Lz5Hb4alaniYDDCV+rbeS0QAaDGYuTu2hIuU4NDVVRmDW+3K90Yj77VSSShFMwYdRquXVLIbSvLWFGepX6nnyN8kQT/s7eZP7xwPPO7WFbm4nMbarmsOndW/x5kWSbyeg/+J44hRZTrG+uqApybKtBYJu4aTU6lGLj/frw//wVSOAyCgOu974WPfIxjUYGGdFdHgydIoyecyToZi1ybgSr3kMBRk690d+TZjVP2u3phIMidjZ0cCCmdLeUmA9+sKuJat3NWf35UZg6qoDHDGeyCOFFQyHQ4pMZel9kn2kc45iMiRokgI03CgcmoNWLVW7HoLNgMNiw6C1a9NfNj0VkQRSOBiIb+oECPT6ajX6Y/JCBLRmTRqIgYkhFkPbk2IwuKnCwodLCwyMGCIgcVOdaTBl/JclrekCVkWUZCwqAxqAdiFRWVsyYeCdN+uI66Z3bR+NrLyJIinlpdWSxev4kl66/GnpM74c8bPViH74EHCGzbhhRRJobQ67GvX0/WrVuwXHwxwhlWvUqxFKGXugg9344UVk78tS4j9jUlWFcUIOhVYUNl8kgkevH2Po3Xu53+/peQ5aGCCKOxALd7A+7cjbhcK9FoZmar/kxBkhKEQkcIBA8SCLxNMHiAcLgBWRZHbWsyFmEyl5JKBQmFjgAjC0hstgVkZ11CVtYluFwXnXYgfKK9g66vfpXIq68CYL3icgq/9330+ScXaFWmP4OVnt9r6qQ/qXym3pXn4tvVxRQY1WptFZWZSCie4pE3lWyMgx1D3RhVbivvX1XOu5cX47JMz+rz84G+UJzfPdfMfS8dz1h+razI5nMba7m4MmeKRzfxJD0RBh5qIHFM+SzqCyy43lWDsXzy5hSTHg+eH/6IwLZtAGizs8n70hdx3njjiPkmXySRyegYntXR4YuO99DYTboRtlU1aRurYpd50vJRmiNxvtfUyZO9fmUMWg2frSjgX0pyMaqdlSrTiEkTNEKhEI2NjQAsW7aMe+65h7Vr15KdnU1ZWdmEDex8Iikled+292WEilAiNCldEBoErHoLFr1tSHTQW7DqrCOEiMzywf/rrFgN1sx2Fr0Fi96CXjN0gZIUJRp6QhzqClDX6aeuM8DhrgDBcdryKnIsLChysHCYgOGeQpVaRUVFZSyCfb28/fR2Djz9FGGfEpImaDRUrVjF0o3XUrZoyRmLDMMRQyEC27Yx8MADxA8dziw3lJfjunULzptuQpfzzi9KpIRI+JUugs+1IwUV/12Nw4D9ihKsKwvQGNSwN5XJJZUK0tv3DF7vDvr6nkUUh7JsdDoX7tx1uN2byM6+DK3WNIUjnflIUopwpFHpvAi+TSBwgFDo6AhBaRCDwY3DsQS7fTEO+yIcjsUYDEOCbTIZwOd7hf6BlxgYeIlwuH7E/oKgxWFfonRvZF+K07EcrdY4YhtZFPE9uBXPj36EFA4jWCzkf/nLuG7dop73zTJ8yRQ/ONbNfR29yIBVq+GLFQX8S4kbvZrlpKIyIzjY4ecvr7Ty6JsdhNMdAAadhs2LCrhtVTkXVajdGNMJTzDGr59p4i+vtJJIKcLG6uocPrehlhXl0ysT8GyQkyKBPW0En20HUUbQa3BcVY7tsiIE7bmZhA+//DLd3/0eieZmAMwXrqDgm9/CNLf25PvFUzR5QzT0hGhM3zZ5Q7T0hZHGmYU167VUuq0ZoaM6z05Nvo3ybAu6s3y9vmSKe4738PsOLykZtAL8U1EuX6goINegFhSpTD8mTdB45plnWLt27ajlt99+O/fee++EDex8QpZllv95OSlp9OT/8C6I4WKDTW/DqjViCfdhHWjF6m3AkghjlSRskoRFa8Jaugpr5Xqs1Rux2PIx68wTcvIRjCU53BXkUFq4ONQVoKEnREIcbQGl1wrU5tuVjotCBwuLncwrsGM3qdVaKioqMwcxlaLx1Zd5a8fjtB0asoHKKizmgg2bWXjleky206tSlmWZ2FtvMfDggwSeeBI5qlTvCHo99o0bcd16K5aVF03KxaKcFAm/1kPwmXZEv9IerbHqsV1ejO2SQjQzNNBOZWYhinEGBl7A491Bb+/TJJP9mXVarYXs7CvIc28iN3ctOp1qW3MyZFkiEjlGIHgg03kRDB5CkmKjttXpXDgci3HYF+NwLMbuWILRcGaBovFELwNpcWOg/yWisdYR6zUaA07nCrKzLsUerUZ+voXAo48Rb2gAwLx8OUU/uBvDaRRBqcxc3gpG+Gp9O2+kbajmWU3cXVvCJa7T+55UUVE5t4TjKR57q5P797Xydrs/s7wy18ptq8q4eXnJtM0CUFHo8kf5rz2N/O3VNpKiMsV3Za2bz22o5YJS19QO7iyJNQww8HAjYp9yTmOal43rhip02ee+8EVOJOi77z56//vXyrWbVkv2P/0TuZ/8JFrbmVmcx5Iix/vCitDhGfpp7g1lfncnotcKVORYM9ZVg3kdlW4rJv3YhWlJSea+zl5+cqybgZQiTq7LtvPt6mLmWtXiIZXpyzmxnDobVEFjbF7peiUjXgwXLoZ3QQAQ80P9DjjyGDTsguRQhSOWHJh7jRLqXbkG9O/sICXLMp5gnEOdSteF0n0RoKUvMub2dpOOBYWOEZ0X1Xk2DKpXu4qKyiyir72VN3c8waHnniaRFiN0BiPzVl/J0o2bya8cO/hY9PvxP/oYvgcfJF4/VOVsqKrCteUWnDfeiC4r65y8BjklEX4jLWz0KxcJGosO2+pibJcWoTGrwobKuUGSUvj9r+FJ527E412ZdYKgJyvrYiV3I3cDRqN7Ckc69ciyTCzWls67UDovgsE6RDE0alut1obDvgi7YzEOxxIc9sWYTCUTLpRGo+0MDLzMwMCL9A+8hNjpwfyGBtMbGgytw87/rCby7vgM2e//AIJW7Qg7H5Bkmb929XNX85AN1S35WXyrqog81YZKRWVacKgzwP37Wnh4fyehdNC0Xitw9SIlG+Piymy1G2OG0dYf4Ve7G9n6Rjtiug3gqvn5fHZDDQuLnFM8utNDDCbwbWsm+pYXULrKXddXYV6UM+Wfx2RnJz13/4Dgzp0A6PLyyP/Kl7Ffc807HltKlGjtj2Ssq4b/RJOjLUIBNAKUZluoybNRlbauqnJbadXL/LClh6aoUsA212rizqoi1uaoc7Aq0x9V0JhNhDxw5HE4sg2anwUpObTOUQLzr4N510HZJaA9u0koUZI53hdWOi7SAsbhrgC9obGtrwqdpkzXxaCAUZI1MR0gKioqKjOBRCzK4b3P8NaOx/G2Hs8sL6yeywUbNzP3ksvR6vVE33hDycZ4ajtyXDmpFIxGHFdfjevWLZiXL5+yY6csykTe9BB8po2UN90pYtRiu7QI22XFaK3qpJPKuUOWZYLBg3i92/F4dxKJNA5bK+B0Lsft3kieeyNm8+yu8JdlmXi8m0Dw7bR11EECgQOkUr5R22o0Juz2henOC8U+ymKpQBDOTUFJor2d4FNPEXhqO7GDB4degwCJGonocuXHnFdFbe23yMm+7JyMS2V60J9M8YPmLv7U2YeM4tn9pTmF/HNxLjrVhkplioimorzc+TJZpizmZs/FrDNP9ZDOGZFEim1vd3H/K6282ebLLK/IsfC+lWXcsqKEHJtx/AdQmREc7w3zi90NPLy/I2NvdM2iAj67oZba/OnZ/SpLMuF93fifOoYcE0EA2yVFODaWozFNr2Kr0N69dH/v+yRblU5V66WXkP+Nb2KsnDPhzyVJMp3+aCabY8jCKkjgBIt3ya4jNdeJlKMUN+tFmUuSWq7PcjI3305Nnk3ttlKZ9qiCxkxnoEURMA4/Bq0vA8N+Tbm1MP96RcQoWgZnOBEWS4oc7Q5m8i4OdQY40h0kkhit+moEqHLb0qKFgwWFThYUOchWD4IqKioqgDLx2Hn0MG9u38bx55/DFo5gjyZwJpLYEyLmcARd+kpC43RirKnBWF2NxmpB0OkRtFoEvQ60OgSdDkGnBZ0OYfD/eh1otcq2Oi2CbuS2gk4HI9ZpEfTpx9XplMca/NFqQa8fJaDIkkz0QC+B3a2kepQuPMGgwXpxIfbLS9Da1WO+yrknHG7G692B17udQPDtEetstvlK54Z7Izbr3BlfUJFI9KY7Lw5ksi8Sid5R2wmCAbttntJ5YV+Cw7EYi6XqnIeqJ9raCDz1FMGnthOrqxtaodFgWbkSx9WbsK1fS9Tkpbd3D21t92bEmPz866mp/vp533FzvrE/EOEr9W28FVTE8wVpG6pVqg2Vyjlma/1Wfv7Gz/HFfQBoBS1VrioW5S5iYc5CFuYspCarBoN2dp37HOkOcP8rrTy0vyOTc6nTCGxaWMBtq8q4pDJn0sKIVaaORk+Inz/dwLa3O5FlZero+iVF3HFVDVXu6XP8TXSF8T3UQKI1CIC+2EbWu6oxlExP8QVAisfp+9//pe+3v0NOJECvJ+ef/5ncj/07GvPki6SyLOMNxWnsCbHfE+CBYJCjekn5JUsy2uMhdM1BhBNsrHKshnQ+x2AouZLTkadm2qpME1RBY6Yhy+A5nBYxHoXuAyPXFy1LixjXg/vk4UPD8UUS6Y6LQEbAaPKGM+2HwzHpNcwrSAsX6a6Lufl2zGpYrIqKisoIpHiceEMj0Tf3E9m3j9iRo6S6u5WT2ZmARjNS7NAOiSHIGqS4DKIAGi1otGgdJrRZFjQmw9C2+mGiywkiDLpBAWYMgWb4//W6UQLNiHVa7UhBZnDbsdYNijU63TsKaleZnsRiXXh7d+L17sDn24csDxVhmE1luPMUccPpWHbOOhPOlmTSP0y4ULIvhlttDSIIWqzWWhz2xWkBYzE221w0mqmZZDupiLFqJY5NV2PfcBW6nJxR+6ZSQZqaf0p7+58ACa3WRlXVFygpvg1BUM8zzxdEWeb+rj7+o6kr4+d9a0EW36wqwm1QOwJVJpeEmOB/DvwPv3nrNwAUWAtIikn6Yn2jttVpdNRm1bIoZxELcxWRo9JVOdoOepoTS4rpbowW3mj1ZZaXZQ91Y7jtajfG+cDR7iA/3VnPU3XdgFK4+q5lJXx6fTXlOWeWATGRSAmRwK4WQs93gKR0ijs2lmO7pAhhhghsidZWuu+6i/CzzwGgLyoi/+tfw7Zu3aQLBFFR4rdtHn7R6iGSzrS9Ic/FpwtziQUSNHpCIyysOnzRcR/LbtRRnc7oqMkfFDzsFLvMM17sTA3EiDf5iB8LIBg0GCudGOc40dpml3A9W1AFjZmEvx3uux76m4eWCRooX50WMa4FZ8lJH0KWZTp80WGWUQEOdwXGPWBlWw0nWEY5mJNrQzvDD1QqKioqE40YCBA7dIjIG28Q2fcq8YYGxP5+RYgeB8FsJpqXS6/ZQCDgQ5BlNDKYLBYKKqpwl5Sh0+mRU0lIicipFHIqBWIKOZlCFpVlpJcr/0/C8HXjbZvenmRSuZWkc/huTRMEYZRgM1KAGSa6nNjJcqptx+qmGSbCjNtNk1k3XJw5YdsTBZoTH2dQyNFqz+sKqmRyAG/v03i9O+nv34skxTPrDAY37tyrcLs3kZW1asom/wdJpUIEg3UjOi+i0dYxthSwWKpGhHbbbAvQaqc2tDHR2krgqe0En3qK2KFDQytOQ8QYi0DwIEePfDPTcWO3L2bevO/jsC+ajOGrTFP6Einubu7iz13KRLJDp+HLcwq5vUi1oVKZeJr9zfy9/u882vRopivjYxd8jI8u+ShaQUtPpIe6vjrqeus41HeIg30H8cf9ox7HqDUyL3ue0sWRFjkqHBVoNdNPlG3oCfKXV1r5xxvtGUsanUZgw4J8bltVxuqq3Bk/Qalydhzs8POzXfXsOuwBlM/FLStK+NT6Gopd59Z6LXqoD9+jTYg+5TzOvDgX13WVaJ0zT2STZZnQ00/T/R//QapTKVKxXXkl+d/4OobS0kl5voc8Pu5q6qQjrljSL7Nb+G5NMRc5xxeowvEUTd7QKKGjpS/MGDXPgFL4XOUe3tGhdHWU51jQa6dnEZEYShBv8hNv8hFr8mWC5U9El29RxI1KF8Y5DlXgmCaogsZMQpLgnnkQ9UHVWkXEqL0GrGNfHCZFiSZvaKjzIt194Y8mx9y+LNvCgsKRnRf5DrWdTEVF5fxEliRl8l8UlQn/9K0iEij3xYEB/I9tI/TMHpKtbSd9PI3NhqGiAtPSC7CuXo1l6dIR4d6+7i7e2vUkB/fsJBZS2qg1Wh21F69m6cZrKZo7f1KPx5nXmxoSP+RkUnmtg0LK4LpkWigZJo4k2nxE9veQ7AqCLAIihhIbxhoHGpOgPE5ymOgyrkAzbN1YAs0JYxwp0KTG3RZx7JC8Wc8wW7FMd0pGnEkLJXo9upwc9EWF6AoL0RcVoS8sQl9UiD4/H8Ew80/aU6kwff3P4fXuoLd394iAbJ3OTm7OOtzuTeTkXI5Wa5nUsYhijFDo0LDQ7oNEIk2MsA1NYzaX4bAvyXRe2O0L0emmh/WDLMsEt++g73e/GyliaLVYV63EPihiZGef5eOLdHT8labmH5NKBREEHVWVn6es7CPTvrtGZWJ5wx/mK/XtvB1SCrAW2czcXVty0skYFZXTIS7G2dmyk631W3m95/XM8nxLPh+74GPcXHvzuPvKskxHqEMROfrqONR7iLq+OkLJ0KhtLToL83PmZ6yqFuYupMxeNiXX2bGkyJMHlWyMV48PZJaXZJl538oytqwoIc8xtSK5yvThzTYf9+ys57l6JXhbrxV470VlfGJtNQXOyf2cpPxxfI82EatTRG2ty4jrpmrM887uvGI6IUUi9P7mt/T94Q+QTCIYjeR89F/J+chH0BgnRqh51R/m240dvBFQbIKLjXq+XlXETXkuNGd57ImnRI71hhWhI53R0dgT4lhvmIQ4dnGcXitQkWPNCB2DoeSVbism/bkVeqVYinizImDEm3wkuyMjN9CAocSOscqFHBeJN/tJdodHPY4qcEwPVEFjptH5JuRUgXGkR2A4nuJId2BE58XRniCJ1OiDil4rUJNnZ0G682JhkYP5RQ4cppnVGquiojJ5yKKIFI0pE80nTOKPmthPicp2kjRimSymYKxlwx9nxDIpPUk+bFlKBEkctUy5L6UfJzV62XAhIqWMbWi7oWWymFImz4fvk57YP1lnxanQOp0YqquxXHQhllWrMC9YgNbpPK19k4k49S89z5s7Hqe7sT6z3F1WwQUbr2X+5WswmKZvKGX8mJ/A7lbiDT5lgQDmJW4c60rR50/d5NMIgepEgeZEYSQlQiqZEW+Uz8mQmCOnksMEmsHHEodEldR4As0J206gmDNpgo0goHO70RcWois6QexIix8ah2NGFT9IUoKBgZfxeLfT27trRAaFRmMkO/ty8twbyc1dj17vesfPFQodHWEdFQ7Xj7DCGsRoLMThWDIstHvhO37+ySI1MEDnF75I+IUXlAVaLdZVq7BfvQn7VWcvYoxFPO7laP2deL1PAZCdfTkLFvwYoyF3wp5DZfojyjJ/6uzj7uYu/GkbqvcWZPP1qkLVhkrljGnyNbG1fiuPNj1KIBEAlIyMK0qu4JbaW1hdtPqsOiokWaI10JoROep66zjcf5hoarQbgt1gZ0HOgozIsSh3EYXWwkn7Pm30hPjrvlb+/kY7vohS4KjVCKyfl8dtq8q4osatdmOojMtrx/u5Z2c9LzYp4oJBp+EDq8r52JqqCbcjk0WZ0EudBHa0ICdE0AjYLi/Gsb4MzSyzOY83N9P9ve8ReellAPTlZRR84xvYLr/8rB+zNRrn+81dPOrxAWDRavh0WR7/VpqHeZI6JVKiRGt/JNPR0TR46w2NmcELSoRHWbaFardtmIWVnSq3FfsEzU3KSYl4SyAjYCTag3DCFKm+0IqxyoWx2oWxwjEqWF4MJ0kc8ytCSPMYIggnCByVTrRW9bzkXKAKGjMQbzBOXac/k3dxqDPA8b7wmHNvNqMuYxc1aBlVnWfDqJtdXwQqKipnjxSNEn7pJYK7dxN+4UXEvr6Zk/EwDRAMBgyVldiuvBLr6ksxLViA1jYxFdQ9zY28ueNxjjz/LKmk8jsxmM0suGI9SzduJqekbEKeZzJItAUJ7G4ldrg/s8y8MAf7ujIMxdOjwnw2Icvy2ALNYEfNoEAzRreNnEiQ8nhIdnWR7Owk2dVJqrOLZFfXaR0LNBaLInYUFqUFj0JF8Ejf1+XlIein54m9LIv4/fvxenfg8e4gFhvqtBIELS7XqnSo+AZMxoKTPpYkpYhEmjKdF8HAAYKhI8jy6PfQYMgd2XnhWDxjJuijdXW0f+pTpDq7lIrCf/kXsv7pAyM6ziYaWZbp7Pwb9Q3fQ5Ji6PU5LFzwE3Jyzv6CX2Vm0ptIcVdzJ3/tUr5bnDotX60s5J+KctDOIGFV5dwTS8XY0bKDrfVb2e/Zn1leaC3k5pqbuan6JvKt+RP+vKIkcsx/bITIcaT/CAlp9HdDljGLBbmKyDGYy5FnyTvr546nRJ462M1fXmll37Gh87Fil5n3XFTKey4qJV/txlA5A15q6uOenUcz3T1mvZYPXlrOv11RRbb1nVepJ9qDDDzUSLJD6XQylNnJencN+oLZ25EnyzLBJ5+k5+4fkPIqnTD2DRvI/9pX0RcWnvbjBFMiP2/p4X/avcQlGQF4X2E2X55TSL5xas7DJUmm0x/NWFYNt7AazzkGoNBpygSSD2Z0VOfZTvkZk0WZREdQETAafcRbApAaOVGqyzEp4kVVWnw4w+6K0xE49AWWjLhhmKMKHJOFKmjMIAbCCTb+7Dm8wfiY6/MdRhYWOUfYRpVmWdRKCxUVlVEkPR5CzzxDaPcewi+9hBwf+7iSQatVApQHg6EHg5bHWjbo3T9qmUbJDxi2TNApYdLKMm06j2CcZYOPpz2dZbqh5xu2TNBq0lkF2qGcAm36+XQjxytLEpHXXiO0axfBZ55FjgydrBgqKnBs3oxj8zUYq6sn+bcFsVCIumd38dbOJxjo6swsL12wmAs2Xkv1RRej1elO8ghTR6IzRHBPG9GDvRlHHdO8bOzrSjGWqd/v0xlZlhH7+tJCRxfJrk6SnZ2kMv/vUnJiToVGgy4vb4TYcaK1ldZuP/XjTDKyLBMKHcHr3YG3dweh0JER6x2OpbjdG8lzb8RoLCAW6yKYDusOBA8QDB5CkkZX4ep0rnTmxaJ058VijMaCGdXVMoj/kUfo+ta3keNxDOXllPzqlxhras7Z84fCDdQdvINQ+CgAZWX/SlXl56Y8A0Xl3POqP8xX69s5mLahWmIz84PaEparNlQqJ9Aw0MDW+q081vwYwYRi6akVtKwpXcMttbdwSeEl5zzfIiklafI1UderiBwHew/SMNBASk6N2tZtdo/I41iYu5Bs08m74Jq9SjfG1tfbGUh3Y2gEWDcvn/evKuOKWveUZmKKkog36qUz1ElHqIOOUAdd4S5SUgqn0Um5vZwKZwUVjgryLHkz8vtyNiPLMnsbevnJznreavMBYDVo+efVc/jXyytxWs588laKpQjsaCH0UifIIJh0OK+pwHpRwYwJ/X6niKEQvb/8Ff1//jOIIoLFgvvjHyP7gx88qf1rSpK5v6uP/zzWTV9SOYZc5rLxnZpiFtqmZ1e/LMt4Q/GRQkfawmq8+U6AHKshbVmVFjvcNio0WpxdERLNisggx0d2hGjsBkyDAka1E51rYkVcMZQgfixAvNlHvNlPqkcVOM4VqqAxg5BlmWXf24k/mqQy18qCIueIwO5c28wLRVJRUTk3yLJMvL6e0J49BHfvIfb22yPW64uKsK1bh23tGoxz5iCYzWhMJqWq+jwKFpZFkci+fQSeeILAjp1I/qGwR11RIc7Nm3Fs3oxx/uTmWYw7Pkmi5eBbvLXjcZpe24csKz2z1qxsFq/bxJL1m7DnTM8q72RPmOCeNiJveTPChrHGhWNtGcbK07PjUpl+SNEoya5upatjsMMjLXYM/pAcvwJrEI3NNtTRMbzbI21tpXO7ldyPc0gk0oK3dwde7w78/v2MlXFxIlqtDbt9YVrAWILDsRiTqXTGH0PlZJKeH/6IgT/9CVACLIt+9EO0U3COLooxGhrvpqPjzwA47EtYuPBnWCzl53wsKlNLSpK5r7OX/zzWRSBts/v+wmy+VllEjmF6ivwq54ZoKsr249vZWr+Vt7xvZZYX24oz3Rhui3sKRziauBinYaBhSOToO0iTrwlJHm0hXWgtHCFyLMhZgFlrZ3tdN/e/0spLzX1D2zpNmW6MQue5mdyUZAlvxJsRKzpDnXSGOzP3B8WL08Gis1DuUASOOY45GaGj3FGORT+5mVcqJ0eWZXYf8XDPznrqOhXrNrtJx0cuq+TDl1Wclm2QLMtED/bie6wZKaB0LVmWunFeW4nWfn4WK8SO1tP93e8SfV3J9TFUVVHwrW9hXbVy1LbP9Ae4s7GTI2ElzLrKbOTb1UVsyJlZdrDD8UeSNHqDisAxrKOjwze6aGgQK1COlgo0VOh01BY5mFubQ+XiPAx5lnP6XqgCx7lDFTRmGA09QYqzzFjUk3QVFZVTICcSRF57jeDuPYR27ybZ2TlivWnJEuzr1mJbuw5jbc2MPel5p8iSRPTNNwk8/gSB7dsRe4f89LXuXBxXX4Nj8zWYly6dVu9RoNfLgd3beXvXU0T8PgAEjYbqCy/mgo2bKVt0wbQa7yDJ3ijBZ9qIvOEBSTm1MMxx4FhXhrHaNS3HrHL2yJJEqrdXETu6ukh2dA4TOzpJdXQiDhMOx0WrRZ+fP7a11WCWh3XyKrPjcQ/e3l14vTsYGHgJWU6h0Ziw2xdgT2deOOyLsVjmzLrA6lRvLx2f+SyR114DIPfjHyf3k59QOvSmEK93B4cOf4VUyo9Wa2Pe3O9SUHDjlI5JZWrwJpJ8r6mTB7oVC5QsnZavVRVyW6FqQ3W+cbT/KFvrt/J48+MEk0o3hk7QsbZsLbfU3MLFRRejmUHH6GgqytH+o5kujrq+Oo77jyOPJbAnc0lGihFjxUixEi4ru4B/WjmXNXPd6CbBNz+QCNDkaxoSLEKdI8SLUwkWWkFLgbWAYlsxRbYiiqxFGLQG+mP9tARaOB44TnuwHXGMzKlB8i35GYFjjnMOFY4KKpwVFFgKznnXzfmMLMtsr+vhpzvrOdqj/N25LHo+ekUlt19SgdU49txVqj+G75FGYkeVY7cux4TrpmpMNZNnYTlTkGUZ/8OP4PnRjzLd0I7rriPvS19En5fH0XCM7zR2sLs//X7rtHxhTgG3F+Win2UdLWIgQbzJR//Rfhoa+2gOxTiOlPnpQDoxFiODSa+hMtdGTSajQ+nsKM+xop+kPJFR4w8liGcsqsYTOKzpDA5V4DgTVEFDRUVFZRYh+nyE9u5V8jD2Po8UCmXWCUYj1ksvxbZuLbYrr0Sfd/aevDMdWZaJ1R1SOjGefJJUV1dmndblwr5pE47Nm7FcuEKxoZrGiKkkja++zJs7Hqf90MHM8qyiEpZuuIYFV67HZJ1+mRWp/hjBZ9sIv9YDYlrYKLNjX1eGaW6WKmycR0jhMMnu7mHdHeluj0Hxo6cHUqeu5NQ4nYq4MWhnNdjdUViIvqgYnTt3QibhRTGGLKfQai2zTrw4kejbb9P+qU+T6ulBY7VS9MP/xL5+/VQPK0Ms1kld3efw+V8FoLDg3dTW3olOp9oOnY+84gvx1fp2DqUrVZfaLdxdW8Iyh1rFPZuJJCOZboy3e4c6kEtsJdxcq3Rj5JqnZ/fq2RBKhDjYe4iHDr3Mi21v0p9qRmPoG7WdgMAc55wRnRxzs+di1p19l0Z7sJ2njj/FzpadHO47PLawkmaUYGErUu5blVu3xY1Oc/IizaSYpC3UxnH/cY4Hjo+4HYgPjLufQWOgzFE2QuQYvHUY1LmlyUKSZB4/0MXPdtXT5A0DikXQv19ZxQcuLsecDvSWRYng3g6CT7ciJyXQCtjXlOJYU4qgn93nVWeK6Pfj/fnPGfjr/4EsE8gr4P++8HUesOciAjoBPlzs5rMV+WTpZ0fRsxRJEj/mJ9aoBHmnPCd0ZmgFDKV2jFUuTNUu5EILLb4YDZ7giFDyZm+YhDi21KHTCFTkWoesq9I/VW4bJv3kXvtnBI6mtMDhUQWOs0UVNFRUVFRmOImWFqULY88eIq+/DuJQJZM2Nxf72jXY1q7FesklaMzT00fzXBFvaMD/xBMEnniCZEtrZrnGZsN+1VU4rt2M9eKLp22A8anobWvhrZ1PcOi53SSiysmfzmBk/mVXcsHGa8mfUzXFIxxNyh8n9Fw7oVe6IW0Zoi+y4lhXhmlBznnjm6syPrIokurtTQscwzI8Ooe6PaRA4NQPpNejz88/wdpKETv0RYXoCwrQWNSJz0F8f/873Xd+BzmZxDBnDiX/9SuMlZVTPaxRSFKK4y3/zbFjvwQkLJY5LFr4c+z2hVM9NJUpICXJ3NvZy382dxEUJQTgn4py+EplIdmzZLJHReFw32GlG+PY44STyuSpTqNjXek6bqm9hVWFq2ZUN8bp0NYf4a/7WnngtXZ6Q4rPvCDApTVmLp4XxWDt5Ej/Ier66ugKd43aXytoqXJVKSJHzkIW5S6iJqsGg3Z8a5+uUBc7Wnbw1LGnONh3cMS6QmshJfYSRaSwF5+xYPFO8Mf9HPMfGyV0tAZbSUrjW11mm7JHdXRUOCoothej18zM8//phijJPPJmBz9/uoGWPmWy1m038ok1Vdyc7yL8WHOmSt1Y6cR1UzX6PPX862T43j7Arx7bwR+WXkzYohRtbNDJ3LliPlWWic2EONdICZHE8QCxJkXASHaERrq8CqAvsmUEDEOFA43h1KJDSpRoG4jS0BOk0RuiMZ3R0egJEUmM3fklCFCaZRkldFTn2U7LQu1sEIMndHCcKHAIisDhele1mj95AqqgoaKiojLDkEWR6FtvZfIwEk1NI9Yba2qwrVuHfd1aTIsXT7ktyFST7O7G/9hjBB59jHhDQ2a5YDJhX7cWx+bNWC+/HI1x9uQQJaIRDj//DG/ueILe1uOZ5YU1c1m68VpqL74M3UnC5aYCMZgguLeD8MudyAlF2NDlW3CsK8W82K0KGyonRQyFhgLLRwkenaR6PCPE3vHQulzoi4qGrK1O6PbQ5uTM+mOqnEjQfffd+P76fwDY1q+n6D9/gNY2/Tq9hjMwsI+6Q58lHu9GEAxUV3+J0pIPqd1e5yk9ccWGamuPUsWdrdfy9coi3leYjUb9TMxYwskwTx57kq31W6nrq8ssL7OXcUvtLdxQdQM55pwpHOHEkxQlnj7cw19eaeX5xl4GZ2XcdiO3XljCey8qozR79GRwX7SPuj4lj+NQ7yEO9h2kN9o7ajudRkdtVu0IkcOsM/N069PsbNnJgd4DmW01goaVBSu5uuJqrii5YtrlkIASON4Z6uRY4NiQ0BE4Tou/BU/UM+5+OkFHib1kVFZHhbOCLKPaOXw2JEWJf7zRzi+ebiTgi/IxTNyAcv0hWHS4rq3EslwNfT8ZsizzuNfP95o6aYkpGSPVna18/G/3saz+EM6b303e5z+PLju3vkVYAAEAAElEQVR7ikd6+siiRKItSLzRR6zJR6I1mOnWH0TnNmOsdmGqUnImNGcRND8ekiTTFYgpQocnRJNXCSRv8ITwR8cXQwscJmrylS6OIQsrO9nWM7umliSJZDJJIpHI/Az/fywQJdodIOoJEO0NkYjESSJy9UdvwlU2/Y65U4kqaKioqKjMAKRwmNCLLxLavYfQM88gDgxrs9bpsFx0Ifa167CtW4uhpGTqBjpNEENhgjt34n/0ESIvv8Lg1Z+g12O94gocm6/BvmbNpHruTwdkWabj6CHe2vEE9S+/gCQqtj0mu4PFazew5KprcOUXTPEoRyKGk4Re6CD0QidyXJmA1uWasa8txbLUjXCO/E5VZhdyKkXK4zlB7FAEj1T6/1I4fMrHEQwGdIUFY4odusEsjxksjiY9Hjru+AzR/ftBEMj91CfJ/fd/nzEiTjLp4/Dhr+Dt3QlATs5aFsz/TwyG2TXBqXL6vOQL8ZX6do6mbaiWOxQbqgvsajXwTKKur46t9Vt5ovkJIimlelWn0bGhbAO31N7ChQUXzrpujPaBCP+3r40HXmvDE4xnll9ek8v7V5Wxfn7+GXvA94R7MiJHXV8ddb11+OK+k+4jILAsbxnXzLmGq8qvmtH2XeFkeFRHx/HAcVoCLURT4wcOOwyOIYFjWFdHmaMMo3bmfuefC2RZJvh6D72PNmFIFyxtI8HDToEPX1XDu5cXT0rGy2zgzUCEOxs7eNmvnJ/mG3R8pbKQdxug75578P/9H4BiuZr32c/iunXLtDxfkyWZZFeYeLoDI37MnyleG0TrNGKsdikiRqUTrfPc/13JskxvKEGjJ0SjJ0hjT4CmHj8t3gD+cBQdEnokdIKo3BckdIg4DAJuq5ZskwanUcCqB7NGRpDFUWJFIpEgdRo2umPxb//2bxQWFk7wq57ZqIKGioqKyjQl2dOT7sLYTeTlV5ATicw6jcOB7YorsK9bi/Wyy9Cqx0nkVIrwSy/hf+RRgrt2IcdimXWWCy/EceMNODZtOm/fq7BvgIN7dvLWzicJ9nmVhYLAnKUrWLrxWiqWLkczjQIUpWiK0IudhF7oQIooJ37abBP2K0uwrshH0E2/E3aVmYssy0jBYFrw6Bzq9ujsyixLeTwZcfRkaHNyRmV56ArTHR/FRWizpmelZ2T/fjo+fQcprxeN3U7Rj36Ifc2aqR7WGSPLMh0df6Gh8S4kKYHBkMfCBT8hO/vSqR6ayhSRlGR+3+Hlh8e6CadtqG4vzuUrcwpwqTZU05ZQIsQTx55ga/1WDvcfziyvcFRwS+0tXF91PdmmmVOVfDqkRIndRzzcv6+VZ+u9ma+cXJuBLReW8r6LyijLmTgxTpZlOsOd1PXWjejmCKfCXJR/ERvKN7C+fP2MFjFOB0mW8EQ8Y1pYdYW7xs0K0QgaCq2FQ10dw8SOPIvaeZD0RvA90kS80QeA1m3m5Robd709ZJlWkWPhjqtquOGCYrRqNzYAnbEE/9HclekwNGsE/r00j0+W5WHVDV2rRd7YT/d3v0v8yBEATIsXU/Dtb2NeNLWWm7Isk+qNKuJFo494sz9zLTeIxqrDWOVSbKSqXGhzTGf995JKpcbsdHin/xdPo7P7nWIwGDI/er3+pP9fvny5Ojd+AqqgoaKiojJNkGWZ+OHDBPfsIbR7D7G6uhHr9aWl2Netw7Z2LZYVy2dszsNEIssy8SNH8D/yKP7HtyF6h1rpDXPm4LzxBhzXXY+hpHgKRzm9kESR5v2v8daOxzn+1huZ5Q53PhdsuIZFazdgcTincIQjkeIi4Ze7CO5tRwopbcBapwH7FSVYVxYgTHJwm4rKIHIySbLHQ6qrc8jOapjgkezsRI6OX+E5iGA0psWOQow1NTiuuw7TokVTNvEhyzK+vz1A9113QTKJobqK0l/9CkNFxZSMZ6IIhY5y4OCniUQaAYHy8n+ncs4daFSP9POW7niS7zR28JDHByg2VN+sKuI9BaoN1dmSSEl0+KK09kdoS/+09kdoH4giyTLZVgMLihwsLnayuNhJWbblpMc6WZaHujGOPZGpmtdr9GwoT3dj5F846yaKO31R/u/VNh54tY3uwFBBzurqHG5bWc6GBfkYzlEhhyRLJKWk2nmQJpaK0RJoGbOzI5QMjbufRWeh3FE+ysKq3FGORX9uOsRkWUYKhRD7+xEHBkj5fOjz8jBWVyNMovWsnJIIPtNGYE+bYiWk0+BYX4r98hIEnYZoQuTPL7fw62eb6A+nbZTybHzmqho2LypEc54KG2FR5L9aPfy61UNUUqZfb8nP4quVhRSbxv59yakUA/f/Fe/Pf650GgsCWe97L+477kDrPHfXcyl/XBEv0kHeYiAxcgODBl2FHaHcilBiQnbqSKYmRnyQpLGDvycKQRBGCAvDxQatTk9MEgglwR+X6Y+KeMMi3ohIXNKQQkMKLSlZQzJ9X6PVUZrroCrPQU2+neo8xcKqPMd6xl135zuqoKGioqIyhUiJBJFX9hHas5vgnmdIdQ0L8BMEzBdckMnDMFRVzboLuLMl2dNDYNs2/A8/MiIXQ5uVhWPzZpw33TilE4QzhYHuTt7a+SR1e3YSCysXZVqdjtpLLmfpxs0U1sybNu+hlBAJ7+sm+Fw7UvokWWPTK8LGqkI0RlXYUJlaZFlG8vuHCRxdmQyPZGcnqc4uUl7vmPtaVq4k7wufx7xkyTkds5RI0PO97+F7cCsA9k2bKPqPu2aNHZ8oRqlv+B6dnX8DwOFYxqKFP8NsVq0Zz2eeHwjy1fp2GiJKhfCFDgs/qC1hkWpDNYpBC47WYWLF8NuuQOx0GtcyOM16FhU7WJQWOAZFjlAyxOPNj7O1fitHB45mtp/jnMMtNUo2hsvkmvgXOIWIkswzRz3c/0ore456SM9fkm01sGVFCe9dWcac3NlxLJ6NyLJMX6xvzK6OjlAHojx+dXe+JT8jcAwPJy+wFKA9Sbe0nEoh+nyk+vsR+wcQfQND9wcGEAf6SQ3e7+8n5fNBcnQmgGAwYJw3D9PCBZgXLcK0aBHGqioE3TvvWIs1+fA91EiqVxEjjbVZZN1YhS7HPGrbcDzFvS8e53fPNWeyC+YV2PnMVbVsWpg/ba5BJhtJlnmgu5+7m7voSSidDKucVu6sLmaZ4/S+l5IeD54f/ojAtm0AaLOzyfviF3HedOMZvY+SJI3oeBhPTIiHY0R7AsR6Q0QHIiTjSs5DCpGkIJISRFI6mZRWIimLJFNJJntKWavVjupqOJ3Oh1P9X6vVnvFnMZ4SOd4bSdtXhWjwKHkdzb1hEqmxBRidRqAi15rO5hgKI69y2zCpBXxjogoaKioqKueY1MAAoWefJbR7D+Hnn0eKRDLrBLMZ6+pLlTyMNVeiy1F9vweRwmECO3cSePRRwi+9PJSLYTBgW7cO5w03YLv8MrVz5SxIJuIcfXEvb+14nO6mIYHIXVHJ0o2bmb96DXqTaQpHOISckgi/1kPwmTZEnzIZpbHosF1ejO2SIjQm1T5EZfoiJRKkenpIdigiR/jFFwlu346cnnCwX301eZ+545x0RyS7u2m/4w5ib70NgoD7c58l5yMfmZUTCD2eJzhy5GukUkF0Ojvz5v0H+Xmbp3pYKlNIQpL43/Zefny8m4gooQH+uTiXL80pwHme2VBFEina+qMZoULpsBgULaJEkye33TDrtZRmmynLtlCabaE0S7nVawW6/TEOdPg52OHncFeQhDh8IkdGY2rDmvsqgu0tZEEpVtBrDGyq2MiW2i0sy1s2645JXf4of3u1jb+92kaXf6gb45LKHN63qoxNC/Mx6tTJq5lMUkzSFmob1dFx3H+cgfhQDqIxIeOIgD0KjohMdlRHqeSiOGXDHTfgjGmwhFLog1FkXwDJ7z+r8WgsFrRZWWicDpLtHUiBwKhtBJMJ07x5mBYvxrxYETkMFRWnnckghhL4Hz9GZL8SvK6x63FdX4V5ce4p/4YDsSS/f/4Y/2/vMYJxZUJ/UbGDz22oZe3c2W3d9cJAkDsbOzkQUgSgMpOBb1YVcZ3bedLXLUnSmEJD8O0DeP72f8R6+0jpdAgV5ZjWrEGy20+r8yE5hgA20eh0ujGFg3cqPmi10/+4KUoybf0RGoYJHU0eJZA8khj7u1YQoDTLwi/et4ylpa5zO+BpjipoqKioqJwD4s3HlC6M3XuUsNVhrZE6tzvThWFZtQrNNJk4ng7Iokj4pZfxP/oIwZ27Rti5mC9cgfOGG3BcffV5m4sxGXQ31vPmzic4+sJzpJLK5ILBbGHhmvVcsGEzOcWlUzxCBVmUiOz3ENzTRqpPmRAQTDpsq4uwry5CY1GFLZWZQbKzE+8vf4X/4YcVoVarxXXrFtwf/zg6t3tSnjPy2mu03/EZxL4+NE4nxT/+MbbLL5uU55ouRKPt1NV9Bn9gPwBFhbdSW/tNtFq1Kv98pjOW4DtNnTyStqHK1ev4VnURW/KnZ9bN2SBKMt2BGK19EdoGIiOEi7b+aMbLfjwEAYqcZkqyFNGiLNtCWY6Fkizlfq7NcFrvVSIlUd8T5LXWDna0PsHR8C4S2o6hccbzSA6sIulfhtPoHNHJsaTYRWm2ecb+TkRJ5rl6L395pZXdR3oy3Rgui54tK0p438oyKt22qR2kyjtCliREv3+oO2JgIN05kbZ76leWJ/p7SfT1IvsDaOJnPnksC5CymxFcTgzZuZjd+eizc9FmudBlZ6PNykKblY0uOyt9P2vEtaUsyyTb2ojV1RE9eJDYwTpidXVIodH2WRqbDdPChRmBw7RoMfriohF/h7IkE3mtB9+Tx5CjKRDAenEhzk0VZ1xk5I8k+Z+9zfzhhWOE05O7S0tdfH5jLZdVn1oYmY6IojimcNAUifHfA3FeSCgHAzMyN0kR1iWDyKdhs3S2wdJngl6nRy9o0UlatEkBPVr0shYdWvRoMZiNmLKsmHKsWPIdGMzG0xIfNNMwuHyqkWWZLn8sI3Q0pjs6GjwhfBHlOPHsF9dQnqN27Q1HFTRUVFRUJgE5lSK6fz/BPc8Q2r2bxPHjI9Yb58/HvnYNtrXrMC1ccNrVL+cLsXQuRmDbthEWLYbycpw33Yjj+usxlKiWIZNJNBSk7pldvLXzCXzdQ1ZoZYuWcMHGa6lasQrtBLSmv1NkUSZ6wEtgdxspj9LtJBi02C4pxHZ5MVrb5HkEq6hMJLGj9XjvuYfQs88CSsdezj9/iOwPfxitbWImumRZZuAv99Pzgx9AKoVx7lxKfvVLDKXTQ6icbCQpybFjv+B4y68BGYulikWLfoHdNm+qh6YyxeztD/K1hiEbqlVOK3fXlrDANtomZTrijyRpGxguVAzddviiJMWTX8o7TDrKchSBYrDDYrDjothlfsf5DbIs85b3LR6sf5Adx3cQE5VCBKPWyKq8dcwxrKO/v4i6zsAYnRwKJ9pVzQSRoycQ44FX2/i/V9vo8A0V5ayck837V5WxaWGBaiUyTZESiaHsiWG2TqmBYRZPg8LFwACizzeiYO10EQwGtGkhIuWwELZq8Zkleg1xOvVhjmv66dAGCVggYIGQCeRhGRM6QUeJvWRUVkeFs4Is4+kJs7IkkTjeQqzuINEDBxSR49Ah5Fhs1LbarCxMixdhXrQIfcVi4i12kh3prJtCK1nvrsFQaj/j92E4/eEEv322ifteOk4sqbynKyuy+eyGWi6pmnj3AlmWRwgPp5PfcLoZDycGS8d1el4vn8vBokokjQZBlpnfeYyLWo5gTibGGeH4CIIwrnCgkySkI0eQW1vRpVIYjEZcV16JfcmS0Z0ROj1CfxKpI4rcEkZqDUNy5PeGNtuEqcqFsdqJsdKF1q5eY002sizTF07Q0BNi5ZxstOdpvsx4qIKGioqKygQhhsKEn3+e0J7dhJ55FnF4W7Bej3XlSmzr1mJfuxZ9UdHUDXSakuzxKLkYjzxCvL4+s1zrcim5GDfegGnJkml94TobkSWJlgNv8uaOJ2h+fR+yrFxY2LKyWbx+E4vXb8KenTvFo1QqxKJ1vQR3t5HsCgMg6DVYVxViv6IYrUMNt1SZGYT37cPzk58oVlAokwe5H/sYWe99zzsK8ZRiMbq/fSf+Rx4BwLF5M4Xf/x4ay/nXodDf/yJ1hz5PIuFBozFQXf01Soo/oH6/nOckJInftnm553gPUUlCK8CHi3P54pxCHFNsATRe+HbbQITWvgiB2MmrdfVagWKXeYRQMdhtUZplwTlJXY3+uJ9tzdvYWr+VRl9jZnlNVg231NzCtZXX4jSODK4d7OQ42OHnQPrnyAwSOSRJ5rkGL/e/0srTRzyI6XYMp1nPzctLuG1VKdV572zCV+XMGB6OnervRxzwpfMm0vf7+xWhIn1fHBhQApbPAo3DgS7dGaHNzkabnZX+vyJa6LKzMgKGLisLwWI55ec1lAjREmjhWOAYx/3HMyHlLYEWoqnouPs5DI5RWR0r8leQZco65euQUyniTU3EDhxQOjkOHCRWX69kcmgNGOZei6F6I4JGiyzGIXUIU60R85JFmBcuROtynelbNwpPMMavn2niL6+0pnMHZFbPyeITa8qZn2c96zDpsZZN9nSnrNVytKSKl0tqiOmU421txM8NQQ9lGvmsbZZ0Ot2pPz9799L9/e+TbGkFwHLJxeR/4xtobQXEG33EmvzEm33IsZHii8amx1jlwlTtwljlQpetukioTC9UQWOG8etWD/lGPRc5rZQY9eqFl4rKFJPs7CS4Zw+h3XuI7NuX8UEH0Dqd2NZciW3tOqyXrZ6wCtvZhBQOE9y1C/8jjxJ++eVMZZOg12NbuxbnjTdgu/zydzSJpzJxBHo9vL1rOwd2byfi9wEgaDRUX3QxSzdeS+nCqRecZFkmdrifwO5Wku3p9nmdgPXCAuxXlqDLUk/GVaY/siwT3LkT7z0/zXT46UtKcH/mMzg2X3PGXX3Jzk7aP/kpYocOgUZD3he/SPaHbp/yv9epJJHo5/DhL9PbtxuA3NyrWDD/B+j1p57oUZnddMQSfLuxg21epTDFbdDx7aoibp5EG6oTw7dH5llE6fRHTxm+nWszUpY9UrQozVLsoQocpnNW2SnLMm943mBr/VZ2HN9BQlKqjk1aE1fPuZpbam9hSe6ZnS8MFzneTmdynI7IsaTYxeJi5zkROTyBGA++3s5f97XSPjA0yXxheRa3rSpj8+JCtRtjgpBTqXS3xJCtU+Z+f386LPvU4dinRKdTrJyystMixAn3T7R4crnOaZafJEt4Ip4xg8m7wl3IjD5oGLVGrq28lvfPfz+1WbVn9nyJBME9Bwm94EdOKF3aya43ib/9f8jR/sx2MiBUVKBbuBDt3LloqqsQSkpIajRnJT7E4wnCsTiIKSb7tEWr1Z51nsNYy3Q6HXtDcb5/vIfGdAfgXKuJO6uKWJtz7uY5pXic3t/+kcD219G6qtG656ExjRSTBZMWY6ULU5UTY7ULXd6pxTYVlalEFTRmEHFJonbvAeLpKo9Co56VTisXOa2sdFpZYDWjU1uQVFQmFVmSiNUdIrRnD8E9e4gfPjxivaG8HNv69djXrsG8bBnCNLDkmW7Iokj45ZcJPPoogZ27kIeFoptXDOZibELrdJ7kUVSmEjGVpOGVF3lzxxN0HKnLLM8uKuGCjdey8Mp1GC1T6/EpyzLxBh+B3a0kjqfDDzUCluV5ONaWosuZGTYiKuc3ciqF7+//wPurXyJ6ewEwLphP3uc/j2316tN6jPDLr9Dx2c8iDgygdbko/uk9WC+5ZDKHPWOQZZm29ntpbPwhspzAaCxg4YKfkpW1cqqHpjINeKY/wNfqO2iOKpNQF6dtqOafpQ1VJJGifSBKa9/ZhW+b9JpMV8VgfsVQnoUZi2Fqzzl9MR+PNj3K1oatHPMfyyyfmzWXLbVb2Fy5Gbth4joTBkWOwS6OqRA5JEnm+cZe7n+llV2He0ilr9MdJh3vXl7CbavKqM1XuzFOB1mSSLa1kWhpObnFk8/3zsKxB0WI7CxFnMjcH9k5oc3ORmO3z9gJ3VgqlunkGBQ6jvQfGdEptSp/Fe+teS8X5l6ImBJP2sUQD0YJ1nuJeUMkBQlRLyPnGkhpUyRCIeLRqLKPLCOeg3DmlKwhiQa9Xk+23YLdYnrH4oNer5/QYOm6UJQ7GzvYO6AUWOXodXxpTgHvL8w5J/N2YjBBvNlHvNFPrMmH2D/SQkxOJZDCrVhWVODYuAJDsR1BOzM/7yrnJ6qgMYPwJVP89HgPr/jDHAxFSJ3wG7FqNaxwWNICh40VDgu2KW6PVlGZDUjxOJGXXya4ew+hPXtIeTxDKzUazMuXYV+7FtvadRgr50zdQKc5saP1+B95RMnFGPYe6svLcN5wA84bbjhvfNxnE72tx3lz55Mcem43yZhSkagzGpl/2RqWbryWvIrKKR4hxJt9BHa3EW/0KQsEsCzNw762FH3e+We3ozLzkCIR+v/4J/r+938zwZ3WSy/B/bnPY160cMx9ZFmm/7778PzoxyCKGBfMp/SXv0RfXHwuhz4jCAbrOFh3B5HIMUDDnIpPUlHxCTQatSjhfCcuSfym1cvPWrqJSjJaAT5S4uYLFQXYT7jOGi98W7k9u/Dt0mH2UKcbvn0ukWWZ13peY2v9Vna27CQpKVXwZp2ZzXM2c0vtLSzMWXjOxn02IsfitMBxJiKHJxjjwdfa+b9XW2nrH+rGWFGexftWlnHt4kLMBvU6/FTIskz0zTcJPLaNwJNPIg4MnP7OgoDW5UKbnX3aFk8a4/lpPzowMMChQ4eor6+n19dLMBpETIro5cnvJtHLMtpkEl08jjYlokul0IkpdMkUOknCaLNiys7BnOfGUlyMubAQg9F4UvGhM5Dgl3uaeHh/B2kNkWsWFfDZDbXTQkD0xJP857Eu7u/qRwYMgsC/lrq5ozx/Uu0LpViKeLOfeJOPWKOPVE9k5AYaAUOpHWOVE8nfTN9vfkCyow0A65VXUPCNb6jX4iozClXQmKFERIn9gTCv+sO84g/zeiBMIDXyRE0DLLSZMx0cFzmtFJtU2xYVldMh1ddH6JlnCe7ZTfiFF5GjQxcrGosF62WXYVu3FtuVV6LLUu0pxiPp8RDY9jj+Rx8lfuRIZrnW6cS++RpcN96I6YILpt0FusqZE49EOLx3D2/ueJy+9tbM8sLaeSzdeC21q1ajm2LrsHhLgODuVmJH0xfMApgX52JfW4ahcGo7SlRUTofUwAB9v/kN/ff/NWOf4di8Gfdn7sBQVpbZTopG6frmtwhs2waA88YbKPjOd9CYVMu18UilwtTXf4eu7r8D4HJexMKF92AynV7mVbLHg/+hh4jV1ZE23FBmqAe/3wQhvUhQ1mWWCZl1yiJh3H0RhGHfl6P3HVp/4r7Dn/vEfYVhiwb/P3rfwe3GHt+w5z7J+EY8/ljvy+m8tlHjO2Fsp/P4I17DCWMb5/H7kiJ/7erjFX+MuKhFi4G5Fgc6WU97VKY9KtEZlUcVnJ2IQy9QYtFQYtVSbNVSatVSatNSbNVRZNVh0A5/DcN+ZycZ36jXNmz/Ua9txHs8zr7DnkMQTlyu/H8gEWBb53b+0fY4LeH2zOub56jh5oobuLr4Kmx66wnv68jxDQ1lrM+joIxgnPGdjV3VOxU5JEnmhaZe/rqvlR11Q90YdpOOdy8r5n2ryphXoM5bnA7xY8cIPLYN/7ZtJFuHzhkFgwHDnDnocnNH2jq50l0Ume6KbLQOB8I56ASYqQyKGHV1dXR2dp50WxmZlJBC1IiYjWaybdlYTVZ0kgY8cbRR0MkajHYL9gVuzDm20+qE0OuHLNJTXi/RAweJHTxI9OABYgcOjilgCSYTpvnzleDxxYsxLVqEobx8TKvNRk+IXzzdwGNvdyLLyuHh+iVF3HFVDVXuc2/1HBUlftfm5RetPYTTx5cb8lx8vbKQcvPEi2lyUiTeEsh0YCTbg5zoMqYvtGKscmGsdmGc40BjHCrUkKJRen/zW/p+/3tIJhEMBnI++lFy/vUj5634pzKzUAWNWYIkyxwNx9jnD2d+2mKJUdsVn2BTNd9mRqtOJKqoIMsyiaYmpQtj926ib73FcLNiXUEB9nVKF4Zl1Uo0aqbDuEiRCMGnn1ZyMV58cWQuxpo1Si7GFVeouRizFFmW6Thcx5s7n6DhlReQRMVCw2x3sGjdRi646mqceQVTOsZEe5DA7jZih/oyy0wLcnCsK8VQMvWVXSoqpyLR3o73F78g8Ng25btKpyPrPe8h9+MfQ4pGaf/kpxQRWasl/ytfIesD71eF49Oku/tRjhz9JqIYQqdzMn/+3eS5N425rZxKEXpuL74HHyT07LOZ7zuVmUtS0OKxZNFtyabbmkO3NXvoviWbkOHkXX06KUVeZICCcD8Fkb70bT+F4T7yI/3Yk+MH+E53ZKCuTGDXMoF9tQIpnXJMMcVlLjskc9WbEpXdUzCwcUSTjCBy4jaCQFLQ0mLLo8FZTIOjiAZHEcdteSTH6MoaFDnaB6K09A1VPC8rc3HbyjKuW1KkdmOcBqneXgJPPIn/sceIHTiQWS6YzVgvuRhdQQGCVocUDKZXjCOanrHgOlwcHOvzwNC+4wiipy0mjzO+EcLkGILwaYvJo8Y38rn9iQT1fj8Nfj+eYcV4AlBss1GblU1hTTW2mhqM6S4IUSPyVOtT/OXIXzJWcWbJxNdi/86K1loEGQSjFufVFVhXFSJMkFWSLMskOzqJHTxI7OABReyoq8t0oQ5HY7djWrgQ8+JFmBYtxrxoIbqiosz7erQ7yM921fPkQeUApBHgXctK+PT6aspzJr9gSZZlHvb4+H5TJx1xpdhkqd3Cd6uLWOmaOGFFFmUS7UHijT7iTT7irQFOVNF1uWaM6QwMY6ULrfXUXTjx5mP0fP97hF98CQB9WRkF3/g6tiuumLCxq6hMBqqgMYvpiifY51e6OPb5w9SFoogn/BZtWg0XOoYEjuUOC1bVpkrlPEFOJom8/kYmD2N4hRCAaeFCbOvWYl+7FuP8+epk0EmQRZHIK6/gf+RRgjt3Ig3PxVi2DOeNN+C4+mq0LtfUDVLlnBP2DXBg9w7e2vUkoT7F/x9BoHLZhVywcTMVFyxHo5m675xkd5jA7laiB3ozFU3G2iwc68swlqvnHirTn9jhw3ju+SnhvXsBENIVdXI8jjY7m+Kf/RTrSjUP4kyJRFqoq/sMgeDbABQXv5+a6q+h1SodLon2Dnx/34r/Hw+R6unJ7GdesQL7hqvQGI1kLp1kWTm+yPKwQgnlvjy4juHrh7aTT7XvSR5fHvz/mT5+epsxxza4f2bfYfuP2ndw2Yn7M/LxR7yOYfufzb6Dr4txxibLyMj0CwY6tVa6NFa6tFblfvrHqzUjCaMrgYeTlYqSmwjgiPnJTgTIjfmplCMskCPkpcJoT3w/x3zvxnjf0+Mb830f8drOcN8R24zzvmUef/S+fpPEMwtldi2B7qyh96GqS2b9mzKrD0mYR9fRzTiSgpYWRwENrhIaXCU0uko45iwkNUzksBt1vGt5Me9bWcb8QvU84VRkipwefUwpckoXuaDVYqytRWu3k2htJdU9FUrY7CBks9JWWkpbaSkD2dmZ5YIk4fZ6KW1ro6StHVN8yPJO53ZjveJybJdfgXX1pWjtdiRZ4sXOF9n37DOsPbQEd0r5Y38jtx7tRjcbFl6NQTu5xWiyJJE43jIkcBw4QOzwYeT4aLs+bXa20sWxaDGmRQsxL17Mkbien+2qZ9dhxdpYpxG4ZUUJn1xXTUnW5FjMvuYP863GDt4IKNe+RUY9X68s5F35WWje4dyBLMkkeyJDAsYxP3J8ZNaSxmHANNiBUeVC5zq7zgpZlgk++SQ9P/jPjDW0fcMG8r/6FfRFp9epqqJyrlEFjfOIcErkjUAkI3K8FggTOqHVVisoNlXDuzgKjWoVtcrsQQwGCe/dq3RiPPccUiCQWScYDFguuVjJw1izBn3B1FaRzwRi9fUEHn0U/2PbRkzq6MsGczGuH2GDonJ+IokizW+8yps7Hqfl7f2Z5c68fJZcdQ2L1m7A4nBO2fiS3gjBPW1E3vRA+mvRWOnEvr4MY6VTFTNVpj2hl16i6ytfHToOa7XkfvIT5H7kIwj6yffIno1IUoLm5p/S0vo7AKzGGiq97yH22AvKxFz60kjrcuG86SZcW27BWFU1lUNWSRNNiLQNRDLh2yPzLCYufLslGudbjR1s71XOJQuNeu6sLuIGt2vGf29IssQrXa+wtX4ru9t2k5JSAFj1Vq6rvI6ba25mfs78UfvJ4wgpGTHlhGXDt1PujrPv8KmIMfcdFHPGFrlO+/HT20jBIL3/8z8MPP0MLY4CGvMqybnsEt790ZuxZalzEydDTqUIv/QS/kcfI/j008jDipx0eXkIOh3Jrq5hIqXSxW1esQLTwgVoXcrfz5jCJif+zscQ8Ti14DvyM8MJn5dTCI+nEIxP+txnJBiPv29A0HDMaOSY0UDfsO94QZYpSCSYE41SHo1hHhSQBj/nySTRgwdHWCmj1WJethTrJeuQWUiiTVEng5YoP3X/iZcsbwKQbcrmvXPfy5a5W8g1547+xU8ScipFvLGR6AHFpip28CCx+npIpUZtqyssxLxoEQOlVTwYcvD3kJ2wwYxeK/Dei8r4xNpqCpwTY73ZGo1zV3MXj3h8AFi0Gj5Vlse/leZh0Z5cFB8PWZYR+2LEmtICRpMfKZwcsY3GosNY6RwSMHJPL/fndBFDYXp/9Sv6//QnEEUEs5ncj3+MnNtvV90VVKYdqqBxHiPKModD0RFdHIMtcsMpNRkyAscqp5W5VtM7VptVVM4lifZ2Qrv3ENyzm8irr404AdJmZ2O78kolD+PSS9FYVR/9U5HyevE//jj+Rx4lfvhwZrnG6cRxzdU4b7gR87KlM/5iXmVyGOjq4K2dT3LwmZ3Ew2EAtHo9cy++jAs2Xkthzdwp++yk+qIEn20n/HoPgy2NhnIHjnWlGGuz1M+0yrRECofp/Po3CD71FACC1Yqc/tvSl5eR95nPYN+0aUz/aZVT07N/K+33fg/jC3G0oaFjgPXSS3Bt2YJt/XrVhvIcM93Ct3f0+vlGQwetabvfK7Js3FVTQo115mXW9EZ7ebjxYf5e/3faQ0PZGEtyl3BL7S1sqtiERT85lc7Tkcjrr+P54Y8UK1pAm5uL+5OfxHXLzQi60fZU5yuyLBM7eBD/o48ReOIJxL4hS0/BbEZOpTK5T4MYqqqwrr4U2+rVWC66CI3l/PlcnQ29vb2ZTIyeYUVkgiAwZ84cFixYwPz587Ge4lpWSiSIvPoq4ef2Etq7l8SxFvRV6zHOux5BZ0SWRDS6VuxXFpG6aAEPdTzJ/UfuxxNRqvb1Gj2b52zmAws+wLzseZP6msd9DfE48SNHRmRyJJqaR4hkg/Rl5fO2tYh6VynHcstYueES/nXjAvLsZ3d8DqZEftHSw+/avcQlGQF4X2E2X55TSL7xzAtIxECcWJM/04Uh+kZ+fwkGDcY5TiUHo8qFvtA6YbZfJyN2tJ7u736X6OuvA8rfa8E3v4n14lWT/twqKqeLKmiojKAjlsiIG/v8YQ6FopzoBuzQaVjhULo3Vjqt/5+99w6P47qv/j+zvVd0gCBAEGBBYScldlIiJVISZVmU40R2LCdxYiexndjJmzhO4sQpdt7EjmPHTvz+4rjGSSzKtkhJVGFvEjsJgA0kQfS+i+19Z35/zGKBJcAOkAC153n2mdmZwezdxe7Mvfd8zzkssBjvmoXOIouJgCSKRBoaZBXG3r1Em5oy9msqKtJ5GPp5ddlAuduAGA7j37Ub7/btBA8fHvYJV6sxrVmN9dlnMa1Zk53UyeK2EY9GuHTkIGfefp3e5ivp7XllFczbuJk5K9agfkABxglPRCY2jvekvWnVJSYs60rRzXVkiY0sJg1ira1yXsbly6BWU/BnX8D6/PN4X3mF/m9/h+SAbPWmq6kh748+j/GRRx5wi6cGxEgE/9tv4/nZy4ROnEhvT1olQo+I6J9Zxew1X0etfnDKsocd3nD8OqJCfnQMhukYDBG/3kf3Oph1KqY7DUyzDxMWQ8simw7tOFvshpMi327r41ttvURFCbUg8DvTcvnDsnyMk7yfKUoi73W9x7bL29jbtpeEJBf+mNQmnp7xNFurtjLLMesBt/LBQZIk/G+9Td/Xv562p9XMmEHe5z+Haf3693WfINbWhnfHDnw7XiPW0jK8Q6EYlSmktFoxLH8U04oVGFesQF1YeH8bOwUxMDDAuXPnOH/+/JgkRnV1NbNnz74liXEjRFt9uH92nqRLJpuS7itETv8Y0d8tH6BWY1i8CN2alRybo+Z/Bt6ifqA+/fdLCpbw4pwXWVuyFuUDtJAFWVkQOX+OSOO5tGVVvL199HEIdFjyYfZcatY/inPRfLSzqm45hk2IEv/d4+IfmnsYiMvXyBU2E389s4ga8+2TcWIoTrRZDvGOXvGQ6L8uV0kpoCk1p22kNCVmBNWDmWuTJAnvq6/S94//lCYpLU89Rd6f/B/UeXkPpE1ZZDESWUIji5vCn7apCnDMG+SkL0ToOpsqlQA1JkOa4FhqNZJ3F+x0FlncC8RwmOC776byMPalJ3EAUCoxLFqUzsPQTJ/+4Bo6hSCJIqFjx+RcjLfeyszFmD8f67NbMD/5JCq7/SZnySKLW6PnShNn3n6DS0cOkIjLFa5ag5HqNY8xb+NmHEUlD6RdSV8M/4EOgke7keLyvU9dYMS8fhr6mpz7UiGVRRY3QmD/fjr/+P8g+nwoc3Mo+Zd/wbBwYXq/GAzi+sEPcH/vP9PXb+PKleR9/nPo5oy2islCrkj0vPwy3h07EL1eeaNCgWnVKqwvbMVdcZXmlq8jSQl02iKqq/8Zm23xg230FEUsIdLpCWeQFu2DKeLCFcIXGW0nMhJqpUCxTZ9BVKTVFnYDVsODGYu0hKN8samT3W7ZhqpYq+avZxbzVO7ksy/sD/XLaozLr9AZ6Exvn5c7j61VW9k4feP7So1xK0ixGIP/+zMGvvMdkoODAOgXLyL/j/8Y/bx5D7h19w8Jtxvfzp34tu9IK1fGhEqFfv48mcBYuRLd3LnZIrLbQH9/f1qJ0ZfKMgBQKBRpEmPWrFl3TWKAPKnufbOF4LFUiLZBhXXzDHQ1VsLHTxA4cIDA/v2j8iXV06bR9vhcXqvwsCd0hqQkW1oVm4p5cc6LPDfzOUya8QvBvlckBgeJnDufIjga8J5pQOnqH32gWo1u1qwRmRw1aGdWpL+v+91+vnSlk4vBCAAVei1fmlnEBqflltd1MZYk1uIjklJgxLsCw3ZjAAKoi01oK2zoKmxoyiwoNJPrd5L0+ej/xr8w+N//DZKEwmgk9zOfxv7ii1ml2n2AKCYZaGslr2zGg27KpEOW0MjijpAQJc4Hw2kFx3FvkO4xbKqm6zSyRZVNtqqqMmRtqrIYfyT6+/Hv20dgz16CR45kBIYpTCZMq1dhWrcO06pV2TDqO0D08mW8Q7kYI0L61CUlw7kYZWUProFZPLQI+32c27eLs+/sxNPbnd5eWjOP+RufomLxMhQPYDCcDMQIHOoi8G5XOoxPlavHvL4UQ10ugjJ7f8vi/kESRVzf/S793/wWSBL6+fMp/pd/QZ0/drVcwuVi4N/+ncH//d+05YflmWfI/exn0ZQU38+mT0qIwSC+nTsZfPllImeHK09VRYXYnn8e2/PPZ2Rq+Xz1NJ77LOFwG4KgpLzsM5SVfQpBmFwTEA8akiQxEIilVBXDeRZDKotubxjxFqPLHJOWaQ59BlExLZVlUWDRoZykpLIkSbzt8vHFyx10ROTf3Fq7mb+rKqbC8GBtqJJikiNdR9jWtI39HfvTE5JmjZlnZjzD81XPU2WveqBtnOxI+v24/uN7uH/wg/TYw/zkk+T94R9MuaIpMRZD9PsR/X6S/gBiwE/S70f0BxCDgfR6wjNIrPka8fb2NJkzFtTTS9MEhmHpUpSmyTO5PZnR39+fVmJcT2LMmDGDuXPnMnv2bAz3aMslSRKhU31432hGDMqksWFxPtZN5SiNo0ngWEsLgf37Cew/QOj4caQRtmGuHC17NhXwZokLP/JEv1Ft5LmZz/Frs3+NaZZp99TWiUKst5djbx7m1NtHsLdfodLTjjUWGnWcoNfTvXwl33nsaQ7a5f6VTaXk82UFfKzYieYGNp5SQiTW7id61UPkiodYuz9tYzsEVZ4+TWBoZ1hRPCAC/k4RbjxHz5e/TKRe7itpZ82i4Et/mVFMk8X4IOT10HL2FNfOnKTl7CkiAT+f/O6PMdqyhaQjkSU0srgnSJJERzTOMU8gTXBcCEa4/stiUylZZBkmOOabDeizNlVZ3CEkSSLadJnA3j349+xN30yHoC4qwrR+Peb16zAsXpwNrroDJAYG8KVyMSLnz6e3KywWLJs2YX12C/oFCyZddWEWDyckUaS1/jRn3nmD5pPHkSRZHWFyOKl77ElqH3sCk91x39slhuIEjnThP9SFlKoeVjp1WNZOw7Ag74FJwrN4/yDp99P1f/6EwN69ANg+9CHy//yLt2X3F2tro/9fvonv9dcBOYTV/mu/ivOTn3zfKe1kv/dzeF5+Gd9rrw0rEFUqzOvXY3vhBYzLH71hNXEi4efSpS/R0/sqADbbMqqrv45OWzDm8e8HXO71s+1UB1f7Avccvi3nWQyHb09VhJIi32rt5dttfcQkCY0g8KnSPD47Pf++2/X2Bnv5xZVf8PPLP6c7OFwwsDBvIVurtrJh+gZ0qqmX+fEgEe/pof+b38L7i1/I3v1qNfYPf5ic3/3UhF9TJUlCikbHJiICqW1+P8mAHzEQHF5Pb5eXUix2T+0QDAZMK5ZjXLES44rlaKZNzknsyYi+vr40idHfP6waGCIxhpQY90piAIiRBOHzLoLHeoi1yOoxVb4B+wdmoi2/PetEMRgkePQogf2yemOo6C2ihoPVAjtXaOmwyH1jAYG109by0bkfZXH+4kk5fpQkibfO9fLPb1/Cc62VKk87Nf4uVon9KAb7+MH6TWxf9TiiUokymeC5fW/zsYPvkF9Rjq66RlZz1NaizMsn0RMiesVD5KqH2DVvWtU9BKVNKxMYM21oK6woLdoH9K7vHZIo4nl5G31f/3payWr94AfJ+6PPo3Lc/7HZwwJRTNJ79QrXzpzg2ukT9DRfyciE0RqMbPn8FymtqXuArZx8yBIaWYw7fIkkJ0YEjZ/yhQhf56GpFgRqzfq0RdUSq5FczdRgprO4v5BiMUInTuDfu4/Anj3EOzsz9uvq6tJ5GNqqyknZYZqsECMR/Lt34331VYKHj0AyNfGgVmNavRrrli2Y1q5BoZ26na4spj58/X3U736T+t1vEfbJHWeFUsnMJY8yf+NmSubW3vffvRhJEHivm8DBjnSFm9Kmxby2BOOiAgR1ltjIYvwRvXyZjt//NLHWVgSNhoK//AtsW7fe8XnC587R/7WvETzyLgAKoxHnJ34Lx6//+kMfypr0+fC+9hqel7cRvXAhvV0zfTq2F7Zi/cAHUOXk3Pb5urt/zqWmL5FMhlCr7cyZ8w/k5jw2EU2flEiKErsv9PLDd1s4fMU1ar8gQKFFN8oW6m7Dt6cqroWi/NnlDva6/YBsQ/W3lcU8mTOxNlRJMcnhrsO83PQyBzoOIKaKAywaC1sqtrC1aisVtooJe/33CyKXLtH3T18jePAgIKvEnZ/4BI6P/TqKMbLAJElCCofTRMRYpMRY5IMYCKTXk4HAqJDte4HCYEBhNiOYjCiUKpLBIMmBgUz1u9WKYdFCjCtWop05E3VxMeqiQoQbVKpnkQlJkujr60vbSQ2MsEdWKBRUVFSklRh6vf6eX2+IxAg3DBBpGkyrBAS1AvNjpZhXFt91IU66yPDAfoL7DxA6fRoxmaS+XOCNJQJnKobPW2Wu4KN1L7GpfBNa5eQbU4qixOsN3XxjVxNXBoIkS00kZ5qRUp/NWlcPv/v2q+S9d2RMAlDQWVBYp6O0l6G0laGwl6FyONBWWNMkhtKhe+judYnBQfq+9jW8214B5OtD3h/+AbYXXshay90mQj4vrSkVxrWzp4j4fRn7c8tmUD5/EeULFlNUOfuBuBRMdmQJjSwmHHFRojEQ5ngqh+OYN0hfbLQvbrlew1KrKU1wVBq0D92FP4tbQ4zFSPT0ED5bT2DvHgIHDiIGAun9glaLcflyTOvXYVqzJhtIdYeQczGO492eysUIBtP7dPPqsG7ZgmXz5vddtW4Wkx+JeJzLx45w9u3X6bw4rCJyFE9j/sbNzF29Hq3h7v2E7wZiLEnwaDf+Ax2IfnliQWHRYF5dgnFpwaTzwM1i6sK3cyddX/xzpFAIVWEhJd/8Jvramns6Z+DwYfq+9jWi5+WJfWVuDrm/9/vYnv8ggvrhKTKRJInwqVN4fvYyvrfeQorI1hiCRoN540ZsL7yAYemSu+5zhkLXaGz8LP7AOQCKi1+kpOSjmIyV4/YeJhu8oTj/e6KNH73bSsegHGiqEGDj3AJWVuakCYuJCN+eqpAkiTcHvPz55U46U3a96x1m/q6yhHLD+E7y9QR7+MXlX/DzKz+nJzhsHboof1FajTEZJxanOoJHjtD7T/+UvqaqCgrQzZmTQUokAwF5XJO8uXrptiEIKEwmFGYTSqMJhdksr5tSS7MZRcZ6amk2ozSZ5L81mYh39+B77TW8O3YQu3o1fXqF1Ypl05NYt2SV2neDIRJjSIkxksRQKpVpEmPWrFnjR2JccBOu788gMUC2OdLX5mJcnI/KPr5qrKTPR/DIEQL79hM4eJBWXOxcrGB/rUBMLX9nbKKOrQVP8uKqT5Njmlzjd0mSeK3Pw59dbKc/VYgr+GLktIX53MJSPjQrH+nKIMH36gmfqSfRfZWkpwXR1wmSOOp8qsJC9LW1qUyOGnQ1NSjN5vv9tu4LQqdP0/Plv0kXiehqaij40pfuuY/6MEISRXqbr9B8+gQtZ07SfbUpQ4Wh0Rsoq1tA2YJFlM9bhMnhfICtnRrIEhpZ3HdIkkRbJJa2qDrqDXIpFbA0EnaVkiUpcmOp1cg8swHdFLWpkuJxEgMDJHp7iff1kejtI9HXS7y3l0RfP4neXpJuNwqLBZXTiTLHicqZg8rpQOlMrec45fWcHBQm06ToUKblzsGg/AiFbr0eDCGGMteT6fXQmNVGypwczOvWYlq3DuOjj6IYhw7f+w3Rq1fxvrod72s7SHQNWw2oi4uxPrsFyzPPoC0vf4AtzCKL20d/6zXOvvMG5w/sJR6V7x9qrY45q9Yyb8Pm+x6aJsVFgid68O/rIOmVqxkVRjWmVcWYHi1EoZ3atilZPBhI8TihU6fx7tieroAzPPIIxV//2rjJ+iVRxPfGTvq/8Q3iHR0AaMrKyP3DP8S8ccOk6GvcLRKDg3h/+SqebdsyJui0lTOxvfAC1i1bxi1fSxSjXLn6T7S3/2d6m9FYSV7uJvLyNmEyPRyZBJd6/PzgSAu/PN2ZtpOyGdR8eEkpH3mklBL7w63wGQ8Ek0m+2drHd9r6iKdsqH6vNI/PTM+/JzvehJjgUOchtjVt42DnwbQaw6a1saViC89XPc8MazZQdKIhiSK+116j7xvfyOhvjwmFYphYGLGUCQnTdUSEGaU5tX8EKaEwGO5aIZH0ePC9+RbeHTsInzyZ3i5oNJjWr8e65RlMK1dmLXzvEJIk0dvbmyYxXK5h9doQiTFkJ6UbQ8FzpxAjCSIX3ITq+4lcHoTEaBLDUJeDOv/+FP1Iokjk3HkCB/bTfWQvr6sv8NYiAZdF7k+okrDWW8SvlX2QBWs/9MCL6M74QvzVlU7e88pFfnkaFRuTapL7uqgIiSxCyTSuI+ZVAtrpFjSleqCPRG8z0XONhBvPEWtuzpikHoKmrAxdbS36mmp0tbXo5sx5aOY0pESCwZ/+N/3f/KZM2AoCtg//Cnl/8AcorbdnafawIuz30VJ/mpbTJ7h29lTabWAIuaVllC9YTPn8xRRWzUaZDVm/I2QJjSwmBTzxBCd8IZng8AQ44w8RuS4pUCMIzDMbWGI1stxuYrnNdN/9Z28FSRSJXrlC+PQZwqdPE718mXhfL8kB15g3truFoNGkiA5nJgGS40TpcKLKGdqeg9JqTXd0pXgcMRpFDIWQQqEUkXAj8mGIeAjd+JhQaPwqjEa+P50OTXk5ptWrMa9fh662NitnvgskXC58r7+B99VXiZw7l96uMJuxPPmknIuxcGH2s81iyiIaCnH+4B7Ovv0Gro629PaiWXOZv3EzlctWoLqPleZSQiR0qg/fvnaS7lQVuF6FeUURphXFKPTZTmoWN0fS5yNw4CCBvXsJHDyI6BuWnzt+8zfI+8M/RJiAwY4UizH4vz9j4DvfSQe+6urqyPujz2NcunTcX2+iIIkioaNH8bz8Mv53dqUDTAW9HsvmTdi2bkU/f/6EETUu9yHa23+A230ISRou0DAYZpKfJ5MbRmPVlCKKkqLEO+d7+eGRFt5tHp6Ym1No4aXl03l2fjE6dVaFcae4GorwZ02d7B+Ubaim6TT8XWUxG3PubPKnK9DFzy//nF9c+QV9oeEw4SUFS9hauZXHpj+WVWM8AIjRqKyEDkfGJCKUJhOCwXD/LTOjUQJ79+HdsYPAgQPDhWSCgGHZMqzPPIN544aHtpp8oiBJEj09PWk7Kbfbnd6nVCqZOXNmWokxLiRGdIjEGCDS5M4kMXL16OtyMdTmoMq//9+x65FwufAe3M9b9a/wiraRpoJhRcPcNokP9JeybvZmrKvXoZs7576NS7siMb5yrZuXe+Q+jxaB34yp+WhTBHVnMOPYBBIXSXJZJ1C5pIjHHitHrRt7fJEMBIicO0+ksYFwYyORhsZ0wUgGlEq0M2eiq6mW1Rw1teiqKqc0gZjo76f3//4jvh07AFA6HOT90R9h/cCz75v5BkkU6b12Vc7COHOSnstN6SxIAI1ez/TaBZTNX0T5/EWYnbdvc5rFaGQJjSwmJWKiSKM/nLaoOuYNMhDPtKnSKQSW20w85rTwuNPCdP3976wnAwHCZ8+mCYzw2bMZ9kgZUKlQ5eaizstDlZ+PKi8PVX4e6tS60u5ADPhJDLhIul0kBlwkXAMkXal1t4vkgCvDIui2oFSi0GoRo9EJIR+GIBgMKIwGlAYjQmqpMBpRGA3y8vrnRqPs1zrW+iRRoExFiJEIgT178L66ncChQ8P/c5UK06pVWJ99FtO6tdlcjCweKkiSRMeFRs68/QZXjh1BTH3v9RYrtes3Mu/xTVhy75+8XUpKhM704d/XTqJftmMRtEpMy4swrSxGaXx47HyyuHfEWlvx791LYO8+QidPQmK4v6O02zGtWYP12S0YH310wtuSDARw/+f3cf3gB0ipoGzjmtXkfe5z6GbNmvDXv1vE+/rw/uKXeLZtI97ent6uq67G9sILWJ5+CqXJdP/aE/cxMLCLvr6duNyHkKRh322DoYK8vCfJy9uMyThr0vZ3PKEY/3O8nR+/20qnR76OKRUCT1Tn89LycpaU2Sdt26cKJEni9X4vf3mlk66UDdUGp4W/rSy+6bgmLsY50HGAbU3bONx5GAl5mG7X2nl25rN8sPKDlFuzqtssZKTtZndsx//W2xljVe3s2VifeQbLU5tRFxQ8wFZOPQyRGENKjOtJjMrKSubOnUtVVdX9ITFqczDU5U4KEuNGkBIJjr/3C/7r/E/Yr24mmZrjzhuU2HRS5PFOB3mPrMG0ejXGFcsnhFgLJpN8p01WyYVTBbSb+5L87oUwBZHhz1RdYEBbYUMos7Dd5eObh6/R75dV2GVOA599vJIt84pRKm79WScGB4k0NhJpbCTc0EikoYHEiCD4IQhqNdrZs9HX1qCrqUVfW4Nmxowpl0kRPHqMnr/5MrErsjpWv3AhBV/6y0ndj7wXRAIBWupPce30CVrOniLk9WTsz5k2PaXCWETRrDkoVdlx4HghS2hkMSUgSRItYdmm6qg3wD63P93xH0KlQct6p4XHHRaW2YxoxpkFliSJeGsrodNnCJ8ZVmBcr7wQDAb0dXXo589DX1ODqrAQdX4+SodjXJhpMRK5IekxvM1FcmCApNc79kkE4cZkws2IhozjDMMkhUH/vmHdJyMkUSR04oSci/HmWxkDFV3dUC7GpnGzKMkii8mMwKCbhj1vUb/rTQLuVDWxIDBj4RLmb9hM2bz7p0qSRIlwwwC+PW0keuXJYUGjwPhIIeZVJSjNU7cKK4u7h5RMEj5zhsDevfj37suwQwLQzKzAvG4dpnXr0M+b90AGson+fgb+7d8Y/NnLMsEiCFiffZbcz3wadVHRfW/PWJCSSQIHD+J5eRuBffvSBL7CZMLyzNPYX3gB3dy5D7aRQCLhp39gt0xuuA5cR26Up2ypNmMyzZ4Uk1AXun388EgLvzzTSSQuVxXaDWp+dWkpH3lkOkW2h8MiYzIhmEjyz629/Ht7HwkJtAqBT5fm83uleRk2VJ2BTl5peoVfXvkl/eHhybBlBcvYWrWV9aXr0Siz95UsZEQuXcK3Ywfe114n0TOcpaIqLMT69NNYnnkaXdXDYYd3vyBJEt3d3WklxmBK0QigUqmYOXMm1dXVVFVVoR2H4rGbkhg5evR1k5/EuBF6gj389NR/8krzL/Ehk+b6qMS6eoknT4gUBFQYFizAtFYmODQzZ97TexQliZd7BvlKczc9MXkeab5P5A/Oh6nxiigsGvSzHWgrbGgrrChNmdfScCzJT95r5d/2X8UdlO/jFblG/uDxKp6qLURxG8TGSMR7e1MERwORBpnsGGvuRjAY0M2dg75mOJNDXVo66f/fUjyO+0c/ov/b35ELZJRKHB95kZxPf/q+FphMBCRRpK+lWQ7zPn2C7suXMlQYap2e6bXzKF+wmLJ5i7Dk5D7A1j7cyBIaWUxJSJLExWCEXS4fu10+jvuCIzOvMCoVrLGbecxpYb3TTKH2zjv3YjhMpLExg8BIjui0DEFdUoJ+wQL0C+ZjmD8fbVXVhNhB3A2keJyEexApEkbQ6VHotAg6HYJGM+lvglncGtHmZryvbse3Ywfxrq70dnVREZYtz2Dd8izaGdkKvSzenxCTSa6ePMrZd3bSWn86vd2aX8C8xzdRs24DevP96V9IokTkggvfnnbinSnCUaXAtLQA05oSVNasYuphRzIQIHjosGwltX8/SY9neKdKhWHx4nRWlKa09EE1cxRiLS30feNf8L/5JiBbXtpffBHnb3/igflexzs78bzyczw//3nGJJ1+wQJZjfHkEygMkzPLIZHwMzCwh96+N3C7DyCKw+SGXl+WsqXajMk057720xJJkV0Xevn+4RaOXhuuMp5baOGlFWVsmVeUtZW6D2gKRvji5Q4ODsr3iek6DX9dkY8qfJptTds40nUkrcZw6Bx8YOYHeL7yeUotk+eakcWDRby7G9/rr+PdvoNoU1N6+5DdrOWZpzEsXpwtRLsDSJJEV1cX58+f5/z586NIjJFKjPEhMZJELrpkEuPSICSGJ0qHSAx9bS7qgqlHYoyFcCLMa82v8ZNzP6bZdw0AQYJFl0WeOi4xt01CAFRFhZhWr8a0eg3GR5bd0X3+yGCAv7rSSX1AJk6KIiKfuRjlsd4EKrsWy7pSDAvzEFS3/l0Eowl++G4L393fjDcsEyOzC8z8weNVPFGdf9f/E0mSiHd0EGloSKs4wufPp9WyI6GwWtFXp7I4UpZVqvy7f+2JRLy7m96v/gP+t94CQJWbS96f/AmWpzZPyvbeCJFAgNaG01w7fZKWsycJejLnBZ0lpeksjOLZWRXG/UKW0MjioYA3nmD/YIBdLi97XP5R9lQ1Jj2POS085jCz0GJENQaDHu/uJnz6tExgnD5N5OLFDNsHkAfyuurqDAJDlZtlXLO4f0i43XIuxvbtRBoa0tsVJhOWTU9i3bIF/aJF2YFKFlmMgLurk/pdb9C4bxfRlG2fUq1m1qOrmL/xKQpm3h9Pe0mSiDQN4t/dRqxN9k1HKWBclI957TRUjnu3JMhi8iDe2Yl/7z4Ce/YQPH582KsceTBqWrUK8/p1GFeuRDnJ+7rh+nr6/ulrhI4dA+TJMecnPoHjox+5L6GWUjyOf+9ePC9vI3joUFodq7TZsD77LLatz6OtrJzwdownZHJjL319b+By77+O3JhOXt5m8vM2YTLNnbDr02BwyFaqhS6vnPujVAg8WVPAS8vLWDw9ayt1vyFJEtv7Pfzl+dMEBnehCxxAIQ5X7T5a+Chbq7aybto61MrshEkWcvaS/+238W7fQej48fT1UVCrMa1di+WZpzGtWZO1m70DDJEYQ3ZSnhFFCEMkRnV1NZWVleNKYoTrBwiPRWLU5qCvzUFdaHxor8mSJPFu17v8+MKPOdR5KL29PGhg06Ewy8/G0aSclAWNBsPSpTLBsWY1munTxzzntVCUv7naxRsD8jXUlJD4+NUYH26LYbDrsKybhmFBHsJd5LL6I3H+81AL/3GwGX9UnjOqLrLwuQ1VrJ+dNy7/JymZJHbt2jDBca6R6IWLSLHYqGOVuTnoq2tkFUdtLbra2gceuD4SgYOH6PnbvyHeKmceGh55hIK/+HO0FRUPuGVjQ5Ik+luvce30Ca6dOUFX00UkcYQKQ6ujtHY+5fMXUb5gEZac+2dtnMUwsoRGFg8dREmi3h9mt8vHLpePM/4QI7+8NpWSdQ5ZvbHGbkZ3cD/93/4O0QsXRp1LlZuLfuFC9PPnY1gwH+3cuSimcFBTFlMTcoDfXry/fFXOxRgi2lQqTCtXYn12C6Z161CMgz9rFlk8zIhHI1w8coAzb71O37Vhm5+88grmb3yK2StWo9ZO/O9IkiSiV73497QRbU5NVCnAsCAf89oS1LmTs7o8i5tDEkUiDQ349+wlsHdvRnUsgGb6dEzr12NatxbDwoWTRs15u5AkieChQ/T909eIXroEyISCaf16NKXTUNpsqYcdpd2Wfn63k2iJ/n4Chw4TPHiQ4OHDGVYMhkcewfbCVswbNjwU/bJEIsDAwB76+nficu1HFKPpfXp9acqWahNmc824TJKc7xq2lYqmJs4cRg2/trSUFx8ppdCatZV6EIgn4+xp38MrTa/wbve76e2iwkrcvJoXZ23lT6rmo7uLybcsHi6IsRiB/fvx7XiNwL59GROchiVLsDzzNJYnnkBpvbOQ+fczJEmis7MzrcQYSWKo1eoMJYZmHO47MonhJlzfP5rEcOrQ1+U+9CTGjdDsbeanF37K9qvbCSdkVYVdYeIpdynr3+7DdLUn43jN9OkY16zGtGYNhiVL8AkK/rm1l//sGCAuSSgkiQ+2x/ntqzHyLDrM66ZhmJ+HoLz3z9UbivP/HWzm+4evEYzJjMv8aTY+t6GKVZU54/6/k2IxIpcvyzZV5+RMjujly2NmpaqLi9HV1KQzOXTVcyckl+R2IUajuL73PVzf/X9I0Sio1ThfeomcT31yUihro6EgrfWnZSupMycJDroz9juKp6UIjMUUz65Gpc4WFTxoZAmNLB569Mfi7HP72e3ysdftx5sYvtgLksTslissazzDI+fPUmvUYRypvigqet91ILKYHJBEkfDJk3i3b8f35luIfn96n66mBuuzz2J5anM2FyOLLO4CkiTRc7WJs2+/wcUjB0imKue1RiPVax5n3obNOIqK70tboi1efHvaiTalpMsC6OtysaybhrrAeF/akMXdQwyFCB45Iod67z9AcmBgeKdCgWHhQkypPIyHxQJQEkV8r71G/zf+JcPu8EYQDAaUNisqm10mOez2YfJj5LrVSqK/n/Dp0wQOHRpVaKLMycH23HPYtj5/w2rMhwGJRBCXay+9fTtxufYhipH0Pr2uNBUovgmzufaO+qiJpMjb53v5weEWjrUMD9Jrii187NEynsnaSj0wtPna2HZ5G69eeRV3RP7fCAgsL1rOo9O38MvADN5NKWjK9Rr+rrKE9c7s+Pj9hvTYYMdr+N58E9HnS+/TVs7E8swWrE8/NWlyjqYCJEmio6MjTWJ4RxDnarWaqqoq5s6dS2Vl5fiQGLFhEiNyaRApfh2JUZuLvu79SWKMBW/UyyuXX+GnF35Kb6gXAJVCxRM5q/hAdzGFBy4SOnEiXeyXUCjZ8dgmfvjU83hTBUrL+xN89lKUWQYtlvWl6OflItxh3sXtwB2M8d39V/nhuy3p/KklZXY+t2EWj1Y4x/31RkIMh4lcuChncjTKmRyxa9fGPFZTXp7K4qhFV1ODbu6c+14UGevooPdv/07OP0O2E8v/whcwP/74ff3eS5LEQFsLzadP0HLmJJ2XzmeoMFRaLaU18yifLwd6W/Py71vbsrg9ZAmNLN5XiCdFDh85yhvHTnM4t4ir08oy9udqVKx3WHjMaWGtw4xFlR3YZXF/Eb12TSYxtu8g3tmZ3q4qKsT6zBasz25BO2PGA2xhFlk8XAj7fTTu28XZd97A2ztc8VVaO5/5GzdTsWgZivsQyhxr9+Pb00bkwvBEo77aiXl9KZriqR2e97Ah3tNDYN8+/Hv3Enr3vYzKWIXJhHHVSszr1mFctWpSyf3HG1IiQejECYJH3iXhdpH0eOTHoCe9PlbF4J1AV1ODcdVKTKtWoa+rm3KqlnuFTG7so69vJwOuvRnkhk43jby8J8nP23xTcsMdjPHfx9r4yXutdKcmxVUpW6mPryhjYWnWVupBIJaMsadtD9uatnG052h6e64+lw/M/AAfrPwgJeYSQJ50+WWfh7+60klvTJ64eyrXyl/PLKZEN/UVSlncHNErV/Bu34H3tR0kurrT21V5eViefhrrlmfQzpqV/R3fJkRRpLOzM20n5RtBDA2RGNXV1cycOXN8SYyGASIX3RkkhtKpw1CbUmIUZUmMGyEuxtndtpufnP8JZ/vPprcvyl/Ei+VbWdSq5u1zV/h6SSVtKeufGYEkf3ApyiMdvahzPVg2VGNYsABhgqvq+/wR/n1fMz852kospbpZXuHkcxuqWFx2/woRk34/kXPniTQOZ3KMWYSiVKKtrJRVHCnLKl1V1YR/TgD+PXvo/du/S7fLuHoVBX/+5xOaJRcNhWhrOCOTGGdPEnC7Mvbbi0qYsWARZfMXUzK7GtVDoAJ+mJElNKYYQqFr6HQlKBRZedOdInj0GP3f+ibhEycBEHQ6Yi99nDNPfYB9kST7B/0EkyM6GAIstRp5LEVwzDbqsp2MLCYEicHB4VyM+vr0doXRiPnJJ7BueRbDkmyAXxZZTCQkUaSl/jRn3n6d5lPDHtQmh5O6x5+kdv0TmOwTPxCJdQXw720n3DjAkF+ibrYD8/ppaEuz/aEHAUmSiJw7T2DvXvx79xA9n6kcUJeUYFq3DvP6dRgWLULIDn4A+TclBgIkBwfTBEdiaH0E6TFyv9JmQzdnDsaVKzAuX47KObFVjVMJyWSIgSFyY2AvohhO79PpSlLKjc1YzHUIgkBjp5cfHmnh1bNd6UkVp1HDry0r5cVl0ymwjl9FpiiJ+KI+fDEfeYY8dKqsBeaN0OJt4ZXLr/DqlVcZjMrKPAGBlcUreb7qeVaXrEZ9g3GeP5Hkn1p6+I+OfpIS6BUCf1hWwO9My0Wb7SM+VIj39snh3jt2ZKjVFEYj5ieewLrlGQxLliDch4KLhwGiKGYoMUaSGBqNJkOJoR6HidybkhgOHYahYO8siXHHqO+v5ycXfsI7Le+QkBIk1NOIOz9OQCPnaNliIp+8EuPZ5h4SZ14h0XmSoQ61wmzGuGIFpjVrMK1aiSonZ8La2eON8O29V/if423Ek/Lrr67K5fMbqpg3zTZhr3szJNxuWcXRIKs4wo2NmcriFASNBu2c2alMjlr0tTVoyssn5HojhsMMfPe7uL73nxCPI2g0OD/xCZy//Ylxyf2RJImB9laujVBhiCOKbVQaLaU1dbIKY8EirHkF9/yaWdw/ZAmNKQRJkjh8eAWJZBC7/RGcjtU4HCsxGB5e2f14IHTqFP3f/Bah994D5Au0/Vc/jPO3fisj0DsqihzzBNnl9rHH5eNyKJpxnmKtmsecFh53WlhhN2HMdiCzuAfIuRj78L76KoGDB4dzMZRKjCtXYHv2WUzr12dzMbLI4gHA29dL/e43adjzNmGfbD+gUCqZuXQ58zdupmTO+PjY3wzx3iD+ve2EzvaniQ3tTBuW9aVoZ2Q9sScaYiRC8L33COzZS2DfPhJ9fcM7BQH9vHlpEkMzc2Z2QiKL+wqZ3NhPX98bGeRGQlTQOLiWvR2P09g7rOyqLbby0vIynqorvC1bqUgigifqwR1x44l4cEdTy4gbT9TDYGSQweggg5FBPFEPnqgHUZIn7FSCiipHFbU5tdTl1lGXU8d0y/T39W8kmoyyu3U32y5v43jP8fT2PEMeH6z8IM/NfI4i0+3bBF0IhPlCUwfveYMAVOi1/F1VMWsd2THzeEGSJKIXLhDv6kJbWXlfbO6SgQD+t9/Bu2M7ofeOpgsrUKkwrV6NdcszmNauzY4NbhNDJMaQEsM/wr5Xo9Ewa9Ys5s6dy8yZM8ePxLiUIjEujEFi1Oagr8uSGOOFxsFOPt9whrOJQhAUIMUxe3fxvMvDb8z/NSoX1pH0eggePkLgwH6CBw+RHBzMOIeupiYdLK6rqZmQCfuOwRD/uucKL5/sICnKv+nH5+TxhxuqqC56sP15SZJI9PamCY5IYyPhc+cQR1ivDUFhMKCbOzdNcOhqa1GXlIzbdznafI3ev/0bgkfk/Cj1tGkU/PkXMa1Zc8fnioVDtDacSWdhBFyZpI29sFjOwpi/iJK5tVkVxhRGltCYQohEezh27Bni8cxwGr2+FIdjFU7HKuz2R1CpHlzQz2RCuL6e/m9+i+ChQ/IGtRr7C1tx/s7voM6/tf9dazjKLpeP3S4fRzwBIuLwT0AjCCy3mXg8x8JjDgvlhntnj7N4+CFJkux9++p22ft2ZC5GdTXWZ7dg2bx5QqtFssgii9tHIh7n8tHDnHn7DbounU9vd5aUMm/jZuauWo92gkPs4gNh/PvaCZ3qg9R9SFNukYmNmbbsoHgckejvx79vH4G9+wgeOYIUGbb3EQwGTCtWyHkYa1ZnlQNZTBokk2GutO/jJ+9e4rWLeQxG5QkSpZBkadFFXligYlHVIpKaaTIZMYKIuJ6wGCIqhkJY7xQ6pY5IMjJqu0VjSRMctTm11ObUYtPZ7uFdTw00e5t5pekVtl/djifqAUAhKFhVvIqtVVtZWbwSleLubNQkSeKV3kH++moX/SkbqqdTNlTFWRuqu4IYCslE9t59BPbvzyCyzRs3UvTVr4x7cK0UixE4dBjvju0E9uyVg3JT0C9ciHXLM5ifeOKhti8cT4iiSHt7O+fOnePChQtjkhjV1dVUVFSMI4kxSLihf0wSQ1+bg6E2B3WxKdtfGyeEkyLfvdrDNzv6CKU+0mpXN4rQj+mRGgBZ9bZm2ho+OuejLClYgiAISMkkkcZGAvsPENi/n8i5cxnnVdrtmFavwrh6NaYVK1DabOPa7lZXkG/uvsIvTncMdefZVFPAH26ooip/8szfSZJEvK1NtqkayuQ4fwEpFBp1rNJqlXM4amvQ18qZHLczz3az1/a/+Sa9X/lq+vpr3vA4+V/4wk2zgSRJwtXRJhMYp0/QefE8YjKR3q9Sa5hWXUv5gsWUz1+MraDwrtuYxeRCltCYYpAkEb//HG73QVzuQ3i9J5Gk4R+rIKiwWhbgcMoEh9lcgyC8vyTIkfPn6f/mt9IhQ6hU2J57jpxPffKuQ9JCSZEjngC7XD52ubx0ROIZ+2fotTzmNPOY08KjNlNW9p1FBmItLXi3b8e7fQfxjo70dlVhIdann5ZzMWbOfIAtzCKLLG6FvpZmzr7zBhcO7iMelSfs1Fodc1evY97Gp8gtLZvQ10+4I/j3txM80Qsp6bpmmhnzY6XoZmU98O8GkiQRvXQpZSW1L8PyD0BVUIBp7VpMq9eiX7gYQa0BSUKhVYJKvs9L0SRiII4YTYIoIYkSUkIkkUgQj8WIxeLEYjGSiSR2gwW1QoWUlNLHKnRKNGUWVLZsxW0Wt4doMioTD5FBTrb1s+O0nxNXJJKifA3QqMPk5J5Ea91PROEjKILEnV8fVAoVdq0dm86GQ+vAprNh19qx61KP69ZtWhsqhYruYDf1A/XU99fT0N/ABfcFosnoqPNPt0xPkxvzcudRZa9CrZz6lrqRRIR3Wt9hW9M2TvWdSm/PN+TzfOXzPFf5HAXG8bO08CWS/OO1br7XMYAI6BUKPleWz+9My0WTHY/cEvHOTvz79xPYt4/Qe0czMpEEgwHN9OlEL1+GRAL1tGmY1q3FuHQphsWL73rCU5IkwqfP4N2xHf/ON+W8oRQ0M2Zg3fIMlqefRlNScm9v7n0CURRpa2tL20kFAoH0Pq1Wm1ZiTAiJcdGNFBtBYti16OtysyTGBECSJH7e2s/fXe2mSyH3g+d6k/yxW8Ha5dPRVtl4r+c9fnL+JxzsPJj+uyp7FR+Z8xE2z9iMVjlchJro7ydw8BCBAwcIHjqEOOJ7g0KBfv58Wb2xds24ZtRc7Q/wL7sus6O+C0kCQYBn6or47OOVVOROzsw8KZkkevUqkcZz6UyO6MWLSPH4qGNVubnDKo4a+XGnhGwyEGTg29/G/aMfQTKJoNeT86lP4XzpY2lb11gkTFvDWa6dOcG1MyfxD/RnnMNWUJiykVpMydwa1JpsAfLDiCyhMcWRSAQYHHwPt/sQLvcBwuHWjP1qtR2HfQUOxyoczpXotA+vJ1zkUhMD//qv+N95R96gUGB99llyfvdTaKZNG7fXkSSJy6Eou10+drl8HPUGSIz4degVClY7TDzmsLDeacmG9b1PkRgcxLdzJ95XXyVydkQuhsGA+cknsW7ZgmHpkmwuRhZZTDFEQ0HOH9jDmbffwN3Znt5ePHsu8zY+ReXS5agmMEgv6Y3iP9BB4GgPpHzx1UVGLOtL0c11IigmZvAsSalJ+NRk/NCEPMnUUhyxTN7k+c32jXHs0PYxjx3r9W/xN2I8RqLjPLHW08TbTiMFM8MARfs0YoWziRZUEbHmkVCIxEmSIElcGLEUksPbr99PEkkY3W0WJCgUHSxJVJArZfZtNaVmjMsKMdTlINyGJVAWDwdEScQf86etnIYUE0MqiuutndwRN6F4lISvhtjgcsRwWfpcCl07GsdhVOYGBMXoMHadIGFSShgVEhaVlhxjCQXWOeRbZuHQOUYRFSb1+EzGxZNxmgabqB+QCY76gXpafa2jjtMoNMxxzkkTHLW5tRQZi6bMhOCVwSu8cllWY/hisj+/QlCwumQ1L1S9wIqiFSgVE/fbPpeyoTqWsqGqNGj5+8oSVjkmT+XvZICUTBI+W09g3z4C+/YRbWrK2K8uLpaJ7LVrMSxdgkKrJXTqFB2/9/uZdjWCgHb2bJncWJYiOG4xZxFtbsa7Ywe+114n3j7cf1Dm5mDd/BSWZ55BVz13ynznHySGSIwhJcb1JMbs2bPTJIZKdXcqqJGQ4jKJEWoYIHLBlUli2EaQGCVZEmMicLRzkL88385Zlfy554dFPutW8OHF09DPcoz6zK95r/FfF/6L7Ve3pxWHDp2DD836EL8y61fI0We6IUjxOKHTpwkeOEBg/wGZxBwBVV4epjWrMa5ejfHR5ShNxnt+T5d6/HxjVxM7G3sAUAjwgQXFfPaxSqY77/38Ew0pFiPSdDlFcMiWVdErV0AURx2rLimRVRw1NehqatFVV9/WZxhpaqLny18mfOIkEhCbOYPQpg10uvvpvHiOZGK4sFupVjOtui5tJWUvLB7Pt/tgEQuCpx2cM0F579ezhwlZQuMhQzjchst9CLf7IG73EZLJQMZ+o7Eylb2xCpttCUrl1K8IjDY3M/Cv/4pv55sM0dyWp58m53c/hba8fMJf359IcmDQz+6UPVVvLJGxf7ZRx+NOOVh8scWIeoImm7J48BBjMTkXY/t2AgcOwFDVglKJccVyrFuexfzYehR6/YNtaBZZZHHPkCSJjvMNnHn7Da4cfzcdMGew2qhdv5G6x5/EkpM3Ya+f9MfwH+ok+G5XemCtyjdgWTcNfV3uKGJDioskvFGSnghJT5SkJ0oitUx6o0gJ8abkBPe1F5gJCWmYOBDGJhCGto+1jWgAa08Ljq4WnD0dqEYMgBJKJb35+XQVF9FVVERknK/PShSoBXnwEZGGK38rjdN41FmLMaQm3hWA1PhP0KswLszDuKwQdd7E2pllMf4YqZ4Yy9rpeqLCG/WSlEaTD2NBTJiIDy4l7lmGlJBtpQQhSV5eJ3Nn9FORr8Chc2DT2uTlCEWFRWXA732Xvr6d9A/szhgfaDX55OY9QV7eZmzWRfdF2e2NemkYaKC+vz5NdAyRACPh0DnSORy1ubXUOGswaSZPBWskEeHt1rfZ1rSN032n09sLjYXpbIx8493bb9wpJEni5d5Bvnyli4G4fJ17Ns/GX80solD7/i2wSvr9BA8dkkmM/QcyFBEoFOgXLsC8di2mNWtumImU9PkIHj5M8NgxQkePEWtuzjxAENDNmYNh2TIMS5fIBIfZTGJgAN8bb+DdvoNIY+PwyxoMmDdswLLlGYzLliGMw6T7ww5RFGltbU2TGMFgML1viMSorq5mxowZ94nEyMFQm5slMSYQLX1+vny6lTc08vVMn5D4zUGB35s3DVvVaCLjenijXn5++ef89OJP6QnKxIFKoWJz+WZenPMic51zx/y7eFcXgQMHCezfT/C995DCI2wY1WoMixdhWr0G05rVclj2Pfz/z3V5+ed3LrPrQi8ASoXAC4tK+P31MymxT61+oBgOE7lwgUhDA+HGc0QaGoi1tIw+UBDQzJiBvqYaXY2s5tDOnj0qHygeidDaeJamX26j5cI5wqrM/ok1vyAd5j1tbi1q7RSd24xHwNsBnhbwtMFgq7z0pJbBlPrkM6fBMeOBNnWyIUtoPMQQxTg+31lc7oO43Qfx+eoZOSOhUGix2ZbicKzE6ViF0Vg1pW7GsdZWBr7zHbw7XkszweYnnyT393/vgdn3SJJEYyCcIjf8nPQFGclRW1QK1tjlYPH1TjO5mqkvrX+/Q5aNn5ZzMXbuRPQND8i1c+dge/ZZLE89lc3FyCKLhxgBt4uGPW9Tv2sngUE550oQFMxYtIT5GzYzvW7BhKmxksE4/kMdBA53QWqwrTCqURcaEbRKkl6ZtBADo2Xh4wKFAAoBQSEgKiSSCpG4QiQhJEko5WVcEDOUDUOEg/xIkJCSxKUEcSlJQkrI62LqISVIiLc34ZuGJGHx+Sjq6qK4sxPngCvDcCes09FVVERncTF9+XkkVSrUKjVqtRqNWo1arUGj0aBRq9FoNag1qeeph1qpQi2oUKvV6Ew6NHrd8D61OmNdOSJg0u12s3//fs6ePSt/dAoFS5cuZcXCR5DO+Qge7SHpGbbm0ZRbMS0rQF+Tg6DKqvkeJERJ5PLgZS4NXqIv1JcmJ64nKkKJ0R7TtwOT2jQmEWHX2fH7HBy9pOfYlQSJ1E8hx6ThxWXTeXFZKXmWOxvAJ5NR3O6D9PXvpL9/Vwa5odHkkZf3BHm5m7HZFiEI90ctJEkSbf42meDor6dhoIFL7kskpMwiIQGBCluFbFWVW0tdTh0zbTMnVPkwFpoGm3il6RV2NO/AH5M9+pWCkrXT1rK1aiuPFj5639s0Et54gn+41sMPOmUbKqNSwefLCvhESe77prAqeu0agX0pK6mTJ2EEka2wWDCtWoVp7VqMK1fcVT5For9fJjeOHSd09OjoSTtBQFNaSqy9fbhiWanEtHIlli3PYF4/xQucEjFIRkGpAdXEWbkkk0laW1s5f/78KBJDp9OllRjjR2KIRJrchOpTwd6x4f6H0qaVMzHqsiTGRGOwP8g/H2/hB5oYMaWAIEl8wCfwp3NKKK1y3vFnnxAT7G7bzU/O/4Qz/WfS2xflL+Kjcz7K2mlrb3jNFqNRQsdPyMHi+w8Qa73OEaWkJB0sbli2bNSk/O3ibLuHr7/TxP4mefJarRT4lSXT+P11lRRYp+hEPTIZHDl3jnBjI5EGOZMj0dU9+kCVCk3lTOJVlfRbDHQHvHS1XctQYSgEAYcvSK4vRH5CouyTn8LxkY9MfkI4GU8RFq1jExb+MT6P66G1wkdegWlLJr69UwhZQuN9hHh8ELf7SJrgiEZ7MvZrNfk4HCtxOFfhsK9Ao3E8oJbeHLGODgb+7d/w/vJVSFXEmh5/jNzf/310s2c/4NZlwh1PsN/tZ5fLx163D3c8c1JmnlnPY04LjzsszLcYUGQ7RlMGsdZWvK9ux7tjR4ZsXFVQgPWZp7Fu2YK2svIBtjCLLLK430gmEjSfPMaZt1+nrfFserstv5B5GzZRvfZx9OY779OIsWRaVSErK0aoLLyywiLD+/AGEDQKlDYdSpsWlU2L0qYlYRTwK8LEpATxZJxYMkE8ESeeWsaSceLxuLwvHiMWl5/H4jF5GYulH8nkHRIPd4GxiAONRoNaocDW1YW1qQnT+QuoXJlWUswoR7FsGZoVK9DNnYtWp0ufQ61Wo7iP9n/d3d288847NKcqfLVaLatXr2bpkqUkrvkJvtdN5KI7XYOiMKowLC7AtLQAlXMKT4BNUZzpO8PfH/17Lrgv3NbxKkGFTWcbJii0thvmTth1cvaERplZPR9LiOxs7OYHR1o43eZJb58/zcbHV5SxqaYQzTiQXKIYxe0+TG/fGwwM7CKRGBmgm0te7pPk5W3CZlt838iNIUQSES66L2aoOLqCXaOO06v0VDurM5QceYbxV8eFE2HeanmLbU3bONs/fH0vNhXzfOXzfGDmB8g15I77694LGvwhvtDUwQmfTLRVGXR8paqYFfaHz4ZKisUInTolB3rv2zdq0lFTUYFp7RrMa9eiX7Bg3CfA4r19hI4dI3TsGMFjR4m3tqX36efNw7LlGSybNqFyTM7xdQaifvB1ZT78Q+ud4OuG0MDw8QYnWIrAXCQvhx7mQrAUg6UQtBY5LOA2MERiDCkxQiPCiHU6HXPmzGHu3LmUl5ePL4nRMEDk/HUkhlVWYuhrc9BMM2dJjAlGdCDE999t4ZvqCG6tfI9bEoK/qihk0ezxUbs19Dfwkws/4e2Wt9OkebGpmBeqXmBJwRJmOWZlZG1cj1hLC4GUNVXo2LGMHAlBq8XwyLIUwbHmrnJwTrS4+fo7TRy5KvdjNSoFLy4r5VNrK8gzT11iYyQSLpccON7QSKD+LB1Xm+ghSb/ZQFibWfBrQKDYkUdZzTxmrH8cRSJJ79/8bTr3TjtrFgVf+ksMCxc+iLciQ0zK18YMsmIEYeHrBGm0FVcG1EawTwdbKdhSy5HP9bb78lamGrKExvsUkiQRDF3B7ZLJjUHPMUQxMuIIAbO5BqdjFQ7HKqzWBSgUD1ZNEO/uZuDfv4vnlVfSVTbGNavJ/fRn0NdUP9C23Q6SksQZX4hdKWuq+kA4Y79TrWKdw8zjTgtrHGbs6knONL8PkfR4UrkY2wmfOZPerjAYMG/ciPXZLRiWLkVQZv3Ps8ji/Q5XZzv17+zk3P7dRENyRaFKrWHW8tXM37iZgplVAEiihBiIDds/ZdhBycSFGErc7KVkCKC0aFBYtJAQiQ+EIS53nkWjQHy+ich0JW6vB5fLhdvtxuVyZVQ7jhcEQcgkG64nH27x/EbHqNXqjMmEpMdD4OBBAnv3Ejh4CNE/PBkraDQYHlmGed06TGvXoi4sHPf3ea+4cuUK77zzDr29ss2A1Wpl/fr11NbWIvriBI/3EDreQ9I3bFWlrbRhXFqIfq4DQZlVbUwkBsIDfOPkN3j16qvA8MR5kanohuHYNq0Ni8Zy15Neff4I/320nZ8cbaXfL6t11EqBp+uK+NjyMuZPs43X2xsFmdw4Ql/fG/QP7CKRGFacajQ55OY+QV7eJuy2pfed3BjCQHggncPR0N9Ao6uRYHz0NazAWEBtjqzgqMutY45zDnrV3ZGBl9yXeLnpZV5vfp1AXFazqAQV60rXsbVyK48UPYLiPth03S1ESeJ/e9z8zdWudGHVB/PtfKmiiHzt1FaKJ1wu2RZm3z6Chw9nhvqq1RiXLEnlYaxBU1p6X9sW7+sjevEimunT0Uyffl9f+4aQJAi55ck1f3eKnOiSCYqhdX83REfbv90zNKYUwXEDwsNSzGBUybETJzh79mwGiaHX69N2UuXl5RnKx7uFTGLIwd7hC26k6HUkRm0O+rosiXG/EB8I89ahFr6qCHHFLP9/p8fgz0vyeHpu4YT8D3qDvfzvpf/l5aaX8UQ96e0qQcVM+0yqndVU51RT7aym0laJWjn6eimGQgTfO0pg/34CBw6Q6M6stNfMmIFpjWxNZVi4MB1ofTt496qLr79zieMtcnaPTq3gY4+W8durZ+A0Td2Aa0mSGOzuouXMCZpPn6DjQiPJEaSQQhDIEVTk9LvJ6R/EGI1nqKwVRiO66rmgVhM+dTptB2Z97jny/ujzqJzO8W+0KEKg5zrComX4ua8TxFuM1VS6FDkxFmFRBgbHbZO+WQwjS2hkAcjyc4/3uJy94TpIIHgpY79SacRufzRFcKzEYCi7b22L9/Xh+u7/w/Ozn6UZcOPy5eR+5tPo58+/b+0Y1a5knP5wP32hvoxHb6g3ve6P+VEIClQKFSqFCqWgRKlQohSUiEobHtVMBlUzcSvKSAjDNyYFsNhqTGdvzDXqsp2pBwQxFiOwfz/eV18lsH9ELoZCgXHFCqxbtsi5GIap5XGZRRZZ3B9EvUEu7ztM65ETxFxBDCoLRqUFmzkfs96JMqaUg7JvAUGrzFBWKG26EetaJIMCj8+Ly+WSH/0u+lu7cQ8OEiRy03MbDAYMBsNdkQ9jkRFKpXLC7lnRa9fkCty9ewmdOpVWagIonU554LhuLably1EY7z1UUZRE2v3tNA02ccl9iabBJq56rmLWmKnJqeGx0sdYUrAEleLuihBEUaS+vp49e/bgS1kWFhQUsGHDBioqKpCSEpGLbgJHu4leHhxWbZjVGJcUYFxSgMr+cFTsTRYkxAT/c/F/+PaZb6cnsJ+b+RyfXfhZnPoJGCgDZ9o9/PBIC6/VdxFPXQ9yzVo+smw6v7ps2n2vyhTFGG734VTmxjsZ5IZa7UzZUm3CZluK4i6/++OBpJik2duczuNoGGjgiucK4nWVkEpBSZW9SiY5cmUVR5ml7IZERCge4s2WN9nWtI2GgYb09hJTCc9XyWqM60NlJzsG4wm+2tzNj7pcSIBJqeCPywv4jeKpY0MlSRLRS5fkLIy9+wjX18uT9Cmk7wFr12BcvmJcgnunDMQkBHqvU1YMERcjlBXJ6K3PBbK9iWUEATFKfVEEGgPEw2OoOLqGyRFfJ0S8N32pGCoOsIwjLEJEnszWK5PMccLcEjvlZaUobSUyAWIuBNXd5cFIcZHI5UHC9WORGBr0tbkyiVFiHpVDlsXEIN4f4sz+Vv5BDHIoV76XWJLwh3lOfrOmGM19UM+GE2Feb36d3W27Oe86jzviHnWMRqFhlmMWc51z00THDOuMjL6fJElEL19OB4tf30dVGAwYVyzHuHo1ptVrUOffWkkoSRKHrgzwtbebONPuAcCoUfLSijI+sWoGNsPUyEaKRyO0n2/g2umTtJw5iac3k/ix5ObJYd4LFjOtug6NTo8kisTb2gg3NMrB443niJw/n5lncj00GmwffI6cT34SdUHB7TdQkuScCk8bDLZkqisGW8HbDsnYzc+hUINt2jBZYSsFe9kwgWHKyxIWE4AsoZHFmIhGe3G7D6UCxg8Rj2de2PW6UhzOVTgdK7HbH0WlGn/pcsLlwvX//QeD//3fSFG582VYsoTcz34Gw+LF4/56Q5AkCV/Ml0FMDK33h/rTz8e62d31a6Ikrq0kpp9PTDePpCZTnuhQiqxzmHg6P49VdjMmVVYBMJGQczHO4N3+Kr6dbyJ6hzvi2jlzsG7ZguWpzajzJi7wN4ssspj8kESJpD+WUlVEMoO2U+tS+NbqCgkJhVmN2mm4IWmh0KlIJpN4PJkKi6F1r9fLzbpqWtRYRD1WyYBNZSJvdglFyyrIKchFd5d+v/cDUiJB+PRp/CkSI3btWsZ+bWUlpnXrMK9fh66u7p6ySvwxfzonoWmwiSZ3E5c9lwknbjJ4Qg4u3jB9A0+WPcnC/IV3Va0dj8c5evQoBw8eJJrq81RUVLBhwwYKUoOyhDtC8FgPwRM9w5koAuhmOTAuLUA325GdhLlHHO85zt8f/XuueK4AMNc5ly8u+yJ1uXXj/lqxhMgbDbKt1NBEBcCCUhsvLR8/W6l7hSjGcA8eoa/vTfr73yaRGO4TqdUO8lLKDZtt2QMlN4YQioc45zqXkcfRH+4fdZxZY5azOIZIjpxaeoI9bGvaxuvXXk8rP1QKFeunrWdr1VaWFS6b1GqM28HZlA3VqZQN1Wyjjq9UlfCobfKErY+EGIkQfO89mcTYt59ET6Zlsm7u3LQKQ1dTM2F5VQ8UiehokuB6S6hAL0i3aftoyEkRE8WpZeHwujn1XDuOY/tYUCZTriM8JF83l/qi7PSU45Vk8mkGrTzCaSpoRckNLFqMudepO0YSLsUZ7ZcSQ0qMAcLnXaNJjJoc9HW5shIje/+8b4j3Bmnd28Y3o35eKVGTVAioJPh1m4U/ri19YE4VkiTRE+zhnOuc/BiQl77YaNWSXqVntmM21c5qmejIqc4gypM+H8EjRwjsP0Dg4EGSAwMZf6+dMyedvaGvq7upDZ4kSey91MfX32misVNui1mr4jdXlfMbK8ux6Caf2m6wp4trp09y7cwJOs41kIgPEwIKpYqSOdVpEsNRPO22CqGkRILo1eYUwSFnckQuXRouOB0Bpd2OfuFC9LU16Gpq0FeUoBTdo8mKIXuoW/T1EZRgLU4RFtNH20OZC+ABZme9X5ElNLK4JSRJxO8/lyI4DuL1nkQaEdInCCqslgVyuLhzNWZz9T1J0RODg7j/8z9x/+S/0gysfsECmchYtmzcqz6veq7yi8u/oGGgQSYtwv1Eb7N6Ra1Qk2fII8+QR64+lzxDHvmG/PQ2m9ZGUkrKD1FeJsRE+nlCSqSfB+NBLrov0jDQQKOnn6B2LjH9PGLauaAYqd5IUq4OssZu4MPFM6i12rPqjXFCrK0N7/YdeLdvJ9427H2rysvD8szTWLc8i25W1QNsYRZZZHE/IUYSo0iKpCcy/NwX5Ubj7ZEQdKoMNYWol+jquMSl+sP09bcQSQaQkJhet4DaDZvIrZjFYIq4GEleeDweRPHGL6jRaHA6nTidThwOR8ZSr9UROt2Hf287CVck3S7TiiLMK4pQGCbPYCjp9xM8dAj/nr0EDxwgOYJUlm1EFmNatx7TurV35U+cFJPDqosR5MVY/vwgV+bNtM9kln0WVfYqZtpn4ov6eLf7Xd5pfQdvdLh9efo8NpZt5MnyJ6nLqbvj+3MwGOTAgQMcP348/b+eP38+69atw2q1AvIETfi8i+DRbqJXh19badViXFqAcUk+SsvUtSN4EOgJ9vD1E19nZ8tOAGxaG59d+Fmem/ncuIc79/ki/NfRNv7raBsDAbm/qVEqeLqukI8tL2PeBNpK3StEMc7g4Lv09e2kr/9tEglPep9a7SA3dyP5eZsnDbkB8kRQb6iXs/1naehvoGGggfOu80SSN1eu5Rvy+fCsD/Nc5XMTpsx5UBAlif/udvN3zcM2VFvz7fxlRRF5k8CGKt7Tkw70Dr73HlJk+H8l6HQYly/HtHYNpjVrUOePj6/+A0M6ryKloMhQVqSIi5Dr1ucBecLNXDhCWVE8ts3TBIZ43y4GBwfZuXMnTU1NgGy5uGnNUmbnaq57/92Z6o9bVUkDkqQiolhBWFhHOFKLJA6/X6VBRF+lQz+vAE1lCUK2SPC+It4TZGBPKz/0+fiPGVoCarmPtMFo4K9qSqkwTL4CG0mS6PB3pEmOxoFGzrvOE0qERh1rVBuHVRwpJUeJqQQkicj5CwQO7Cewfz+R+oYMdZnCasW0ciWmNasxrlx5w6wdSZJ461wv39jVxMUe2WbVqlfz26tn8NLyMozaB3ffjceidJxv5NqZE1w7fQJPT6YKw+zMTRMYpTV1aPTj424hxmJEL10ifPIYvtd+SbTpCmJMAkb3v9XGBHpnHJ0jhs4RR2ePo1QP/R8E+Ro5Vn6FrVS+nionR78mi2FkCY0s7hiJRIBBz1HcroO43AcJh1sy9qvVduz25Tgdq3E4VqDT3Z5vddLnw/X97zP4wx8hpnwzdbW15H7mMxhXrhjXSfuudhf76o9wsuUsXf5uFJIChaRAkJSppQKD0ohJZcKgNMoPhQG9Uo9OoUer0KEVtKhQI4kgihJiUkISxfS6mJRQKAWMVi1Gm/ww2YbWNRhtWlTqsTtR8WScy57LNA40cqb/PO96ArSIuUR18xHVmR13bdJNhdrFSquWZ4vKqXXOGhUumcWNkfR48L35ppyLcfp0ertgMGDZsEHOxVi2LJuLkUUWDxmkpETSf31mRSZpIUVuo9pRIaC0alLKCl2atEgrLayyuiLjtSUJv9/PwEA/TWfPcPVcA4ODHkSNFlGthZtUmKpUqgyiYuS60Wi85b1SSkqEG/rx7Wkn0SffawWNEsOiPIyLC9AUP5gq3Vh7O4G9e/Hv3Uvo+Il0VhaA0mqVJ6/WrcO4ciVK0+230Rfz0eRukkmL1OOK58oNVRf5hnxmOWTiYojAKLWU3tBSKi7GOdp9lDevvcmetj3448M5HkXGIp4oe4Inyp9grmPuHfVj3G43u3fv5ty5c4AchPqxj32MwuuyQOL9IYLHegid7B3OWlGAbo4T07JCtDNt2arTmyCejPOj8z/iu/XfJZwIoxAUvFD1Ap9e8GmsWuu4vY4kSZxO2Uq90dCdtpXKM2v5yCPT+dWlpeSaH/wk451AJjfeS2VuvEM8PpjeJ5MbG8jL3YTd/sgDz+G7HnExzlvX3uJnTT+jvr+e5A0q29UKNXOcc+Sw8ZSSo9hU/NAUErlTNlQ/TtlQmZUK/mRGIS8V5aC6j9cNSRSJNDTgT6kwohcuZOxXFRViXrsW09q1GJYuRTGJVYWA7Lde/z+w/x8h7GJ4Yk2SJzHFpOy3LsZvHRQ7BEEp51BoTbL6QGdNPWyy97reCQYbKDWy9YlSDQrV8FKhlifjRu5L7x+xb2ibxnTX1k43QyKR4PDhwxw8eJBEIoFCoWD58uWsXr0aza3yBcbMAJEJD8nbS6TfRNhbSTi+CIlhuzEFLgzKQ+iVh9AIFxGE1LSWUiNXVY9J/AwtC+TPI4t7QqwrgG9PK2/0+fjmLC0dBrmfO1er4ctzprHSPv5uHxMJURJp8bWkFRznBs5x0X1xTKLcorFk5HHU5NTgjKgJHT4sqzcOHcpwg0AQ0NXVyuqN1WvQVc8dpTwTRYk3Grv553eauNovqwmdRg2fXFPBRx6Zjl5zf+YtPL09XDt9nGtnTtJ+roFEbLgoWKFUUjx7WIXhLCm9t3tnNDA6bHukPdQIazsxIRAZVBN2q4m41ITdGuKBMfrxAmimFaKvnotuwRL08+ajnT0bhXZq9cfez8gSGlncM8LhdlxuOVzc7T5CMhnI2G80VuJwrMLpWIXNthSlMrMTmgwEcP/oR7i//4N0oKd2zhxyP/1pTOvWjtugwT8Y4eC+M1w+1odqcHLIqrVGVZrkMNl1FFXamF7tRGca3XEKxoOcGzjP/t4r7BsMcClmJaAuB2HEsWIUbfQi0xW9PGpRsTyvgtqcWsqsN/YJfj9CisUIHDiA99XtBPbtS2ezoFBgfPRRrM9uwfz449lcjCyymKKQJAkpkswI1h5FWvii6TyCm0FhUKG0jiQpdBmEhcKsGXPCWJIkgsFghsJi5DI+hjw6DVFEEY+iiMdwOp1U1tYxY24NTqcTs9mMYhwsNSRRInxuAP+eduLdw6G66mITxsX5GObnodBPXCWSlEwSPlsvB3rv20v08pWM/ZoZMzCtW4t53Tr08+ffVIoPsuqizd+WzroYso7qDnaPebxWqWWmbWaavBh63MskdiwZ43DnYd5seZN97fsyqvdKzaUyuVH2BFX2qtvu23R0dPD666/T3d2NXq/npZdeIn+MimQpLhJuHCBwtJtYy7A1gtKhk1Ubi/JRmrPFDiNxuPMwXz32VVp8LQDMz53Pny37M+Y454zba0QTSV6v7+aHR1o42zE82F403c5Ly8t4sqYA9UMQ7i6KcQY9R2Vyo/+dDKtatdpObs4GOVDc/ugDJTcCsQBvXHuDbU3buOAenjQvs5Tx1IynKLeU0+xrTis5RgbFDsGhc2RYVdXk1GDWTK3JuOtx2hfiT5vaOeuXid65Rh1frSph6QTaUCUDAYKHDstWUgcOkHSPsPIVBPTz56espNairaqcOiRS5yl444+h88SDbsm9QaWDZb8DKz8Hetu4nPLq1au88cYbuFyy4qS8vJzNmzeTm5t7V+eTEiKRKx45E+O8K6MIRWFSYChLoM8fQKO5hhDozrToCvZzW51ABNn7/oYWV6mH5n2U13IHiHUG8O1u43THIP88S8sph9yXy1Uq+UJlEb9S4EA5VX7bt0BCTNDsbc4gOS4NXiIuju7vO3SOYZLDNoeKXgHtkbMEDhwYRegqc3IwrVolqzeWL0c5Ym40KUpsP9vJv+y6TItL7nPmmrX87toKfnVpKbobFM/e9XuMxei40Mi10ye4duYkg92dGftNDiflCxZTPn8RpTXz0d7JXEo8DJ72FFnROsIOKrW8HaWaISetroiF1Xj3niJ8zU08qEJZXof1+Q+R9HiJNDYSbmwcFeIOgEqFrqoKXU0Nutoa9LW1aGfOvOU4JIsHgyyhkcW4QhTj+HxnUwTHIXy+s4zsLCgUGmzWpTicq7DrFxH9xXEGv/efaTsJbWUlOZ/+fcyPPz4uHqixcIKGY60cP9REol2DkKqQSQoJ/JZ+HE4LxdYi9GodCoWAoBRQKITMdaWAoLh+XTG8rkw9FCOep9aTCZGQN0bAEyV43SMRH7siRxCgoMJKWW0OZXU52AsMN+zEtwX6ebnjMrtdPi5ETYSFzIGHMt6JJnwGfaSRfGEAp86KQ+fArrNj1Vqxaq3YtDYsGkv6uVUjbzNrzONus/AgIUkSkbNn8W7fju/1NzIsTLSzZmF99lksTz11WwFdWWSRxYOFlBRJeuXsioR3bNJipE/yDaEUUFq1GXZQGaSFVYtCe/PrYCgUGpVnMbQcykIYC4IgYLfbR9lD2axWei80UP/OTrqahgc1OdOmM2/DZuasWndnA4RbQJIkolc8BI/3ED7nGg4oVykw1OZgWJyPdoZ1XCaTxGCQwOHDcqj3/v2ZE1hKJYZFi+Q8jHVr0ZSV3fA83qg3rba4PHiZS+5LXPFcuaGFTKGxcJi0cMjL6ebpE3qPiyQiHOw8yJvX3uRAx4GMts2wzuDJsid5ovwJZlhn3PpckQg/+tGP6Orqwmg08vGPf5ycnBsHEsd7gwSP9hA81Ts8waMU0Fc7MS4rHLf/51RFZ6CT/3vs/7KnfQ8ATp2Tzy/+PE/PeHrcPpdeX4T/eq+Vnx5rYyAgW6RolAqemVfES8vLqC0ZP/XHZIMoJvB4jqZsqd7KIDdUKhu5uRvIz9uE3b78vpAbkiTRONDItsvb2HltZ1qdpVao2TB9A1urtrI4f/Go//2QzcjZgWGrqgvuCyTEzFwkAYFya3k6h6Mut46Ztpk3VHVNViQlif/qcvH3zd14EvJ140MFdv6ioohczfj8n2KtrQT27cO/bx+hEyczfM8VJhPGVSsxr12LcfVqVHb7uLzmfUOgH3b/NZz+ceZ2nQ1MufJEm8EpP/Q2ebvOChqzrI4QE5CMy6qNZDyl4EgMrw/tExOQTNzguPjwvlHHxWVlyO0cNxJ6B6z5P7D4N+9aseHz+XjrrbfSikOTycQTTzxBTU3NHV9zb0pimDUYanPkYO9Sy83ViYkYBHpSCo+R4ekjA867R38eN4LWOiKP5AYh6gbH+yYUONbux7enjbbmQb5TqeX1IhWSIKAVBH63NI/fK817X2SCjnTdOO86zznXOS4PXh5TFZhnyKPaWc0cXRkz2mKUHL2Gav+JtHMJIPeVFyzAtHYNxtWr0VbKZG8iKfLzU518c89lOgble1yhVcfvrZvJhxZPu6c8Lm9fTzoLo+1cPYlopgqjaNYcyucvpnzBYnKmTb/xbzoRk8O1R+VXpJaB3ls3RmcbYQc1PdMeyjpNVrCNgBSP4/7Rj+n/9reRQiFQKrG/+GvkfuYzKE0mEgMDhBsaiDQ0Ej4nZ3JkjE1SELRadHPmoKutTWdyaMrKHs7MpimGLKGRxYQiHvfgdh9O5W8cIBrNDHJTeEB7QYHRVUDJ45/G8eTWe74wJJMibedcvLv/PK6LMRTJ4Ztlr+Ua2tlRHlu7hGXlowcv9wuSJBENJdLkRsATxdsXorXRjaszU+FiydFRVpdDWW0ORZU2lDe4IUmSxIVAmFe6O3hnYJDLUTUSw8cKYhh1pBFN+CyayFmUSc8t22nWmLFqRhAfWkv6+dA2q9aaQYhYNJYJHcSFE2GuDF7h0uAlLrkv0RnoJBAPYNFYyNHn4NQ7ceqc5OhzyNHnYHfH0L7zHqHX3yTe2po+jyo3F8szz2B9dgu6WbMmrL1ZZJHFnUGSJMRQItP+yZtpDSX6Y7enrjCqUNp0NyQtFCb1bdnxRKPRMQkLl8tFOHzzEDmbzTYqz8LpdGKz2VDewsqur6WZs2+/wflDe9MDCLVOz9xV65i/cTM5pWW3/hDuAMlgnNDpPoLHe0j0Dg+glE4dxsUFGBfl3XE2Q7y7G//evQT27iP03nvDijhAYTbLVWfr1mFavQqlNXOSNykmafW3pjMuhjIveoI9178MADqlLq26qLRXMssuL8fTOuhu0B/x8/VzO9nX9hYB/ykYkUOm05Uxr+gxfm/usyxwlt/wHOFwmB/+8If09PRgNpv5+Mc/juMGHstDEGNJwvX9BI72EG8ftsJS5eoxLi3AsDAfpfH9Y6URSUT4fuP3+V7j94gmoygFJS/OeZFPzvvkuFXYX+rx8697r7CzoZuEKF+kCiw6PvJIKR9eWkqO6f1lYyCTG8fo699JX99bxOPDFZYqlVW2pcrbhMO+HIVifBVE/pif15tfZ1vTNi4NXkpvL7eWs7VyK1sqtmDT2e7onNFkVM6762+QQ8cH6ukMdI46Tq/SM9c5V7aqyq2lLqeOfOPUyHpwxRL8fXMX/9UtT+pYVAr+tLyQjxXn3HEltRSPEzp1OhXovY/YtWsZ+zXl5WkVhmHhAgT1FLweJeNw/D9g71dgRJ4SKj1s+ios/NjUmsSWJNkG6/I78M5fwkDqt2Mvhw1/DXO23Pb7SSaTHD9+nD179hCLxRAEgaVLl7Ju3Tp0d2AbliYxGgYIn3MhRYbvoWkSozYHzfRbkBh3ClGUq8Jvlunh64JY4NbnAlBqhwPYb2RxZcqf0j790TYf/t1tDF4Z5EdlGn5criGilP8nz+fb+bMZhRTr3t9q0UgiwqXBS2klx3nXea56riKNMbApMhYxWyikolti2skOpp3qwjiiVkpVWJgOFjc+8ggJjY6XT7bzr3uu0O2VC2mKbXo+89hMPriw5LYUoYl4nM4L57h25jjXTp/E3dWRsd9kd1A2fzHlCxYxvXY+WkNKnZRMgK9jdNj2EGHh6+KWgzeNeXR2xcg8C93d9efjPT30fvUf8L/5JgDK3Bzy/+RPsTy1OWM+UJIkEl1dhBvPycHjDY1EGhsRA6N/4wqTCV11dZrg0NXUoi4uGvf5RUmSaB4Icqp1kK2LSt7XBUljIUtoZHHfkIxE6P3Fv9F96keES/3EKiWkjPuZgNlcjdOxCodjFVbrgtse3EiSRG+LjzOHmrl6sh8iwx2BQV0vntJWFq6o4OkFT2DRTO7vk88VprXBRUvDAB2XBhETwz89tU5J6VwHZXU5TK92or+JfYQnnmD/oJ93BrzsdvkYTGQqQvIVfqYpenAmr6KONeOLevDFfHijXgLx2+yY3QBmtVkmP0YoPkY+zyBDUiSJRWtBPaJSbyjE8ZL7Upq8aBpsotXXOuYNfySMYYlHLkqsbhSZM+IeHFULNNXZaV1RTmReJTnGPJkA0Q8TIE6dE51qknvzZpHFFIaUEEl6r8+siJIYobKQbqBgy4BKyFBSpDMrhh5WLYo78JCNxWK43e4x1RbBYPCmf2s2m8fMtbDb7ajHYYImGgpybv8ezr79esbAonh2NfM3bqZy2XKUqvGbCJIkiXhHgODxHkJn+4fVLgLoZjkwLslHN9uBMMbASBJFIufOyXkYe/YSvXgxY7+6tBTzurWY1q3HsGhhegJrpOpi6Hp/xXOFaHJslUuRsShDcVFlr6LUXDqplIWSJPHz3kH+trmb7qhM5AhiCE3oFNrQe2gijQgMV+mZDDN5qnwTvzn7GQpNo/PHgsEgP/jBD+jv78dqtfLxj38cm812W22JdQYIHusmdLofKZZ6TZWAoTYX47ICeSLoIR0kSZLE3va9/N/j/zc9+by0YClfWPoFZtpnjtvr7DjbyR+/fJZIqt+2JCfBx2YleKJUkicRFErZBz+9VFz3fAK2TyJIUpJBzzH6+nbS3/8WsdhAep9KZUnbUjkcK+6a3JAkifqBerY1bePNa2+mlVEahYYnyp5ga9VWFuQtGNfvuivsomFAJjgaBhpoHGgcsx+dZ8ijLqcureSY65yLQT15rU1PeoN8oamD+oBM2tea9HylqoTF1ptb6yQGBwkePCiTGAcPpe2EAVCpMCxZLOdhrFlzUyXelEDzftj5J9CfaRFD4Tx4/nuQU/lg2jVeSCZkxcnev4dgn7ytdDk88XdQvPCmf9rW1sbrr79Ob69cdV1cXMzTTz89KgfqRpASIpGrHsL1Y5EYavQ1ORhqc9GUjTOJcTeI+G5OePi6IDRw6/MACAqZ1LgR4TEU7K6ZXNeOaKsP365Wwpc9vFGk4tuVWvp18j1oicXIX1cWsdAy+Wy5JEkiHG7F5ztLKNyGIChQCCoEQY2gUCEIqtTz1EOhHn5+o/XUQ6FQj7kuPzK/s6F4iAvuCxkkx5Ad5vUowc7MfiXTz7mY0R6nvBd0cRDUagxLl2Jasxr18pW80ivw7X1X6ffL/ejpTgOffaySZ+cXo7zuN+Pr7+PamRM0nz5Be2M98eiwqlhQKCiqmkP5/IWUV04n15REGJVl0Sp//2+QR5WGSj+asBj5XG+fUAI4cOgwvX/zN8RSRa6GZcso+Mu/QFtRccO/kUSRWGurbFOVUnNELlxAioxWhSvtdtmmKkVw6GtrUN2hpV4sIXKuy8uJlkGOt7g52TqIKygrffd8fg0zcieHdf5kQZbQyGLCIcVieH7+cwb+/bskeuSqSnVREY7f+wTSqkLcviO43YcIBDInPZRKI3b7ozgcK3E6VmEwlI06t7c/xIX3uqg/0kp8cPjiF1L7actroHiBiS2PbGRuztwJfY8ThVgkQcfFQVoaBmhpcBH2xYZ3ClBQbqWszklZbQ6OohuHwYqSxFl/mN0uH7tdPs74QxmUgF2lZJ3TwmMOM2sdFiwqCV/UhzfmlZdRL96YF0/EgzfmxRv1pvd7op7085FhqHcDk9qEVWtFKSjxpAiWseDQOZhln8UsxyzKLGWYNWb8QTfie6ew7z1LwZl2lKkJBRFoKBM4UCNwbJZAVHPrm6RJbSJHn4ND50irPkYSHiOVIOpsUFwWWaQhSRJiMD46syJNYEQQ/bcn31eY1CNICt0owkJhVN/xpFQikWBwcHBMtYXPN/b1ZghGo3HMIG6Hw3HrIMtxgiRJtJ9r4Ozbr3P5+LtIokz8GKw2atc/Qd3jT2DJGV/bPLnKf4DgiZ6MbAaFSY1hUT7GxfkoTQLBd98jsHcP/n37SPaPGLgrFOgXLEiRGOtQlJXS7m9Pqy2GCIze0NhSc71KT6WtUlZcpPIuKu2Vk7444aw/xJ83dXLcJ5NhpToNLxXnUG3SI0oSScAf9bC3fTfvdewiFGhAGHFnnmar5ldmPsXm8ifJNQwPhvx+Pz/4wQ9wuVzY7XY+/vGP31E/WYwmCJ3pJ/hed0Z2iirfgGlZIYaFeaNC7KcyWrwtfPX4VznceRiQQ9//aMkf8cT0J8ZtUlsMuvjGz97im5fkysFVinr+RPU/1ChaxuX894TbJkDGIlzG+tsbHXsnZIsCSVAQifUSDF8jGLpKQgwjCYAAglKH0ViFyVKNwTQThUJ7y3b4xBivDZxhW997XA4Ne2JXGAp5oXgtTxetwKqx3heSSJRErnmvpQmO+v56LnsuI14X/qwUlFTaK9N5HPNy5026zLukJPGjLhdfbe7Gm7Kh+tVCB1+cUUSORr5OSJJE9PJlAvv2E9i3j/CZM3JlewpKux3TmjWY1q7FuGI5SvPUzhsB5Am8t74IF7bLzwXFcLj38s/A+r+YkEDtB4ZoAA7/Cxz5FqQs25j3q/L7tBZnHBoMBtm1axenT58GQKfTsWHDBhYsWHDD/C8pISJGEojhBPHuIJFLg5OfxLhTJKIp0uNGFlfd8uM6S7sbQme7eaaHuXDCJ4cBote8+Ha3Eb3i4ZRdyddna7lokQtLpuk0/EVFEc/kTh6by3jcg893Fq/vLD7fGXy+euLxwfveDmEU+TG0rk6vSyiIJOOEkjGC8TD+eIhQIkoSAVGCJLJLrCiBLqrA5BexBMDqk7D6QWO0op5WTpshn70+HZ6YgqSkxGk08PicAqYpIwy0tNLbfA1fv0u+hIkCkiig1eoozDNTYpMo0nrRBbtR+LoRknEEERQSCJKEICE/ht6YUjOsqsggLFIPY84DV6yJsRju732PgX//LlI0CioVzo+/RM6nPnXb+alSIkH06lUiDcMqjkhTU4aN4hBUBQXoaqrR19SmyY6RinR/JM7pNg8nWtwca3Fzpt1D5LrCPq1KwfxpNv78qbkPtWXp3SBLaGQxYZDicbyvvsrAd/6NeFcXIP+gcz75SWwffA7hugmgaLQvZU0l52+M9NwF0OtKcThXYjI8iuvKDBrfdeFpG67cjCuiXHM0QKWXx5Y/wsbyDQ9Vpb0kSvS1+WmpH6ClYYCB9szqL7NTJ+du1DoprrKjVN94QNQfi7PX7We3y8c+tz89SAH5hrTQYuBxp4XHnBZqTHoUt3njSYgJ/DH/MMmRUnxcT4iMJEmGjhsLSkFJubWcKnsVsxyz0iSGU2kh4XaTGHARa20hfPIkvjd2kvR40n+rrarC+uwWLE8/TdxhxhVx4Qq7GAgPyMvIQHp9aPtAeICYGBuzLTeCVWslR5eTofQYaXk1tM2utU+qyuEssrgbSHHxhpkVQ+skbq2uENSKDCXFKNLCqkW4yTXsZkgmk3g8njHtobxeLzfrzuh0ulGExdD6ndgj3A/43QM07H6bht1vEhiU75eCoGDGoqXM37iZ6bXzx93bNd4fIniil9DJXhL9/SR660l015McuCDbbqSgMBoxrlyJctUyOmryuCR2pwmMq56rN1RdFJuK01ZRQ9f9ElPJlLp29sfifKW5m//udiMBBqWCz5bm8zvTctHdROp/qL+Dfz63g/M9e1BGL40gNwTm5S3kmfJNPD79cZx6J16vl+9///t4PB5ycnJ46aWXMJnurGJrSIUTeK+bcH1/WhUlqBXo5+ViWlaIusQ0aSYh7hSheIj/V///+OH5H5IQE6gUKl6qfolP1H5ifKrixSQ07yV44r/5XEMpbyUXA/Db6p38SWUXSqVKrlQUk6mleN3z67cnbnGsOPpvpdtQsj3EkICzWg0vm028bTQQSV3vtKLIE8EQL/gDzIvGGPdv8I2IDoXqhqRISFBwXgX1SpEGhUi9IkGfMPr/Z0ZBtaCnVjAwT2miVmnCodTdPSE1LtsVeJLwk24PuwaDJAUFFgl+w+NhzsXLhN47Q7y3P+N9aCtnYFr5COaVy9HVzEVQacZotyq1PoWuMfGwPLF/6J8hEUFm4AT5t2guhOf+HWasfdCtnDh4O2D3l6H+fwGQlEakZZ9FnP8JxKSG0w1n2HviEJGYXLlcU1jFiuKF6JIqpGgSMZJEiiQQo6llJIkYSQxnd10HhUmNvjYHQ20OmjLr1CMx7hSiKIeV3zDTI/WIh259LpCr4W9pcZUn/w7vAJIkEW324t/dRrTZS7tB4JtVOvbmyySnSangD6bn81slN+/3TDREMUYgcHEEeXGWUOjaqOMEQYPZXI3JKCuqJCmBKCWQpASSGB97XYojSUlEcWg9gSQmEIfWpUR63+2Fz09tCCjSSpWRpMyodUGVVr6k1S8jlSwZyhj16GNvpYwZ9Tx1nuvXBRWJ3gFc3/wOwQOHEURQ5RaQ/0f/B8vjT96QfL0ZxGiU6KVLsoojZVkVvXJVtvEbAZfOwsWqJVycXkODoYDLUTXX9wZsBjWLp9tZXOZgSZmDmmIL2vdB5szdIEtoZDHukJJJfK+9Rv+3v0O8rQ2Qfepyfvt3sH3oBRTaW/sHS5KIP3Aet+sgLvdBvJ6TSAxXLEiigrBrBoHeuVwLGGkyepm/tJLnqp9lumX6hL23yYTAYISWIWuqi4MkRzC5Kq2S0jkOyuqcTK/JwWC5cZVQQpQ46QuyK6XeOB/MlM/laVQ85rTwmMPCaocZywRcTJNiEn/MLxMcEQ/i1RZ0F9uwhQRwe0i4XCQHBki4XCRcLsQbVFIrc3OwPp3KxZg9+47bIUkSgXggg/S4nvBwReR1d9hNQrrNKhpAISiwaW1jKz2GFCApYsSqtU6qCr0s3h+QxGF1RWJEfsVw8HYUMXCb6gqzZozMimHSQmEYLbe+E4iiiNfrHUVYuFwuPB4PonjjiT6NRjMmYeF0OjGMY9j2/UIykeDqyaOcfft12hrr09ttBYXM27CZ6rWPozfde0WsJElEL1yQ8zD27CWSCvdMt8NgwzW9hCuLHJyqSXIxfo2+UN+Y59Kr9FTaK2XSwj6suhivHIMHgZgo8p8dA3ytpQd/Uv7+bc2388WKQgq1t1+p2x+L8+/Nl/jZ1Z3EfUdQx66k9ykFJUsLlvJk+ZMssizilf96BZ/PR35+Ph/72Mfu+vsrhhOETvUSONpDom94okRdbJKzNubnodDe3b1fkiSk2IiJrNQE1tB65rYkCrMaTYkZ3UwbCsOdKyAlSeKtlrf4xxP/mP7+rShewZ8u+VPKrGV39R4yMNgCZ34Kp/+LDm+E34p9novSdDQk+PuFfrY+vVkOfr0fGPK6H0WS3IAAueH2W5EtE7F97PZJUoJYtJ9oqJ1opBspGYFUBagCJRq1k4jaxlsqJa/g54ow3A+rFJVsTah5Kq7EOuo1Jx9J1KNU0qDV0KDVUq/VcF6rITzGJEpxPEFdNEpdNEZtNMqcaIwHUfsfDysIdOkIdGkJ9miRkiNy+pQSxvwopqIIpsIIauOdfI7CPSt+JkRJpFBC2Sqo3Cg388IOWZXhlce26GwQ8cjrs5+GLd+6f7/9CUZ8IEzkohsxGJcf4UT6Gi1GE4jBCFIogiTJY3qX4Oew+iJ9Cnl8ZhdNrIjPokCy3dHrCholKqcObbkVXbUTbfn7gMS4U0gSRLw3sbhKbQ+PDjYeE4ISzAU3sbgqlNfVOrkfeNWDb1cbsRYffhX8x0wtPyvVEBdAAXykyMkflxeQq7m/DgaSJBGJdOLznUkTGH5/I+IYhYp6/XSslvlYLPOwWOdjNs2WlYAT1rYh4mOYDBFTBMj16yOJEElKpsiVeGr/GOtSgkDUS1+wm75QNwOhHgbD/cTEGCrAGFNgjioxRpVoRQFBISEoQFBIKJUielUcnTqBWplAUICoEJCUKiSlEkmhlJ8LICEhISJKSRg1/f4wQoFCocFimUfFjM9hsy2+q7MkAgEuHG3gvfpWTnYFOJMw0DNGrl9B0EVtfIAFNiVLq/KZs2gO+jlzUNwnB4CpjCyhkcW4QRJFfDt3MvCv306HvikdDpyf+AT2X/0wijuobk0mRXqueLnWMEDzmT6CHi+G3EsYC85hLDiHxpw5SaJSWXE4VuB0rMbhWIlOd3v+nA8L4rFk2pqqtX6AoDfTmiqnxISz2ISjyIizSF6a7NoxJxS7IjH2uP3scnk5MBgglBxBlAiw1GriMaeFx50Wqgxjn+NuEG1uxvfGTnw7dxK7evXWf6BSoXI4UBUWoJs7F/P6xzA++giC6v5YZYiSiC/qk4mOFPGRVnxERhAgYRfuiPuWuR8joRJUOPSOMZUe14eem9RTt4I2i/sLMZYkeV249vWkBYlbf08FtQKlXSYnVCPyKzLUFap7J+QkScLv949pD+V2u0kmb+zTqlKpxiQsnE4nRuON7fmmOlwd7Zzd9Qbn9u0mFpYnplVqDbNWrGb+xqcoqLgzP28xGiV09Gg61HvINhJAEsBV7uDsTBXvTPPSnJsYs9K22FhMlaMqbRc1yz6LEnPJQ0Xa7nb5+NKVTq6EZOVJnVnP31WWsOQWXvM3Q0wU2d7n4d+az9Pcvx9t6Cjq2HBloUpQsShnEaqrKpxuJ2VFZXz0ox+9JyWRJEnEWn0E3+sm1DCQrpoVtEoMC/IwLi1AUzSsBBFjSSKXBold85IMxeXJrhFkhRhJyPkrdzOCUIBmuhX9HAe62Q5Uufpb/m4vD17mK8e+wvGe44Cs+PmTJX/C2mlr7+03H4/Axdfg1I/g2n4ATohV/E7887gkMzl6Bd99aRmLpj8ck5mTBZIk4vWeorfvDfp6d3IhMMC7ARVnQkoSKd2FVqHmyfIneWHWr1CXU3fv1/YHSBIlxDhXQj3UBztoCHVRH+qmOTZ6UlKNgtkaO7UaB7UaO/NUNkoUOgRJumdCaeR2KZkg0hMlcDVK4FqMSH/mPVcwSKhLRLTFSSxFSUxqCcXDqCQqnAcKNXSekJ/rnZCMQCwoV8A/+RVY9NLUUprcAGIsiX9PO/6DHTdUTYxEjAQnVc2cV7YjCaCWFCzRVTDPUY1Sr0GhU6LQqRC0qaVOiUKnRNCqhvfplCi08jFZ8mIcEQ+PsLgaI9PD3w3+nltnHqQgae0kkk4SURsR8vhp8Ur+deYSBpXyhOs6q44vVU1ntkk/ke8qjUTCj89Xn7KPOoPXe4Z43DXqOJXKisVSh9WyAIt1HlbLPNRq+31p44Qg6h8RuN16XQB3K/5AhOaAg0shB50BG6I4XIwiItFvj9KZG6EjN4zbEkMrSswYFLF7TWgUs1iz7iM8t+rxmyqjJUmUiRjxVgTNEPEiq1uGn49N0AwfO+I8Y6hkMhQ01ytjxKF915NDiRSxNNyOofdwOwSN07mOihmfx2yec/N/TyJJY6ePEy1ujrcMcqLVjSeUWQyoEKDKrKRO8lLdf5mqxnexdTSPPplaja6qajiTo7YWbUXFfZvrmirIEhpZ3DMkUcS/axcD3/pXopcvA6C0WnH81m/i+LVfQ2G8vQF9NBSn7Zyba/UDtDYOEAsP32CTQoIuy2Va7OcQygJsnFXLI1YL8eAZ3O4jJJOZ9ktGYyUOxyqcjpXYbEtRKu/PzXUyQJIkBtoD8ufYMEBfq3/M49RaJfYCA/YCI/bC1LLAgDVXjyIlD42KIkc9QTl7w+1LT9YMoUSn5jGHbE210m7GcIey0lh7e5rEGBkcK6jVGJYsQVVUiMqZg8rpRJXjROlILZ1OlFbruNupTBQSYgJP1DNMelxHeIzc7ol67ujcGoUmTW449I6xLa9Syo/JHD6Zxb1BEiXEQDwjWDtNWqQsosTgbSiKBFCaNSOUFboMpYXKpkXQ35u6IqPdkkQwGBzTHsrtdhMfw4t0CEqlErvdPqbawmw235Vc+GFBPBLhwuF9nHnrdfpbhyfBCyoqmbfxKWYtX4VaM3Y1WsLlIrBvP749uwkeOQLhYdVeVC1QXwYnKgVOzRTwGoe/B3qVnpn6CsqDhUzryaE8VERZtAijYEBf7cS4pABthe2hmrBoDkX5yyud7HLJVak5ahV/VlHIhwsct23VeCtIksTbLh+fPNdKNNpNRfIUzthxrnoup49RSAoKQgXM18/nz37lz7Aa7t1fNxmMEzrZS/BYD4mBcHq7ptSMYVE+YihO4GAnYug2lYpKAYVOCVolSbVIRBUnpAjjVwQZlLwMiG7cCQ85CRs14ZnkBzMnHFROHfraHIxLC1E5Mkkbf8zPv539N3564ackpSRapZbfrP1NPl798XuzHu0+C6d+DA0/kytiU/iZ/bf5Yu8a4qLA3EIL/9/HFlNse//0M+8nPBEP269uZ9vlbVzzDl/LitQiy40JFhkTmNRGcnLWk5e3CadjDUrl5LIHvBf4Y34aBxrTeRwNAw24I6NJDrvWTk1ODXW5ddTl1FGTW3NXOUPJQJDgu0fkQO/9B0gOjMhDEgT0dXWY1sp5GL4ZFfxtczc/65H95+0qJX9WUciLhc7M699EkERi4i7PcQcEVHhQtlZKpO6BCg3kzYGes/Lzwnnwwf+A3Ko7/pwnGyRJInLOhWdHM0mvPNbTlFvRFBpRGFQo9CoEnSpNQAhaJRfbm3jn0F4CQXkMXq1o5glxFxaCsmJlw5fBWfEg31YWt4KYhEDfDQkPydcJ3i6EpPwbkIBdjkf48ozf5bJRdsSoCl7jr65+h/WDx0BtGDvEfCjTw1IMxtzbyiLKaKaYIBi8jNd3Gp/vLD7fWYLBK1xfLSEIKkymOWn1hdU6H72+bGoVMcWC4GkfQVa0pMiKFIERzsz7SEoCXSEL14J2rgUcDEQz5930OhXlFUWUVVejrq7iijpKQ89ZGlqPcSnSRkg5ug+njQmUJ3NZVLqIullrqM2to8RcMrU+xzvASIIm2nKV3q/9I6FTxxH1EH5aT2BhAJn0EMjPf4YZ5X+AwSB//73hOKfaBtMExtl2D9HrrJd1agXzSmwsKXOwpNzBwlIbZl2mgine15e2qQo3NBJpaMiwUh/CtP/4D0wrV0zQJzE1kSU0srhrSJJEYO8++r/1LaIXLgCgMJtxfPwlHL/+6yhvw8/Z0xdKZ0J0XfZkFPGEVQHa7OdpsTeiK0vwWMU6NpRtYIZ1RsY5RDGBz3cmnb/h89UzkmlVKDTYrEtwOFfhdKzGaKx6aC/IYyHojdJ7zYerM4C7K4irK4inN4Qk3sCvVClgzTPgKDBgLzSmSQ9bgYGORILdbtma6ognQHTEObQKgeW2YfVGmX7sybJ4dze+nW/i27mTSEPD8A6VCuPyR7Fs3oz5sccejtDAu0A8GZfzPq7P/BhheTX0PBAP3PqEI6BX6TMsr0aqPnJ0Oel9+cb8h6p6+mGAGE0OKynGIiy80duqphM0SpR27XV2UDpUQyoLqwZhAvxuQ6HQmPZQbrebaHTsPAUAQRCw2+1jqi2sVuv7mrS4HUiSRPfli5x5+w2a3j1IMiEPXHRGE9XrNjBvwyZsufn0nztF51uvkjj4LsbLXQgjvkouM5ycKXBypkDjdIG4WqDEVJJWXAypLorNxenrhhhOEDrTR/BEL/HO4euU0qbFuDgfw+J8VLapNekoShLBpIgvkaQvluB/e9z8V5eLuCShEuC3SnL5XFnBhNgyApzwBvlIfTOeRJJZRh3/t0zgZNdu3mx5M2OiV4WKdaXr2DRjE6uKV91zlphsMeEleLSbcOPAKLWFwqxBX+NEadEiKAUkQcIfD+CJDuKNyJlZgZCfcDhEPBJDEZMwJPUYRT3GpE5einoMST0qlIQUYZp0bVzUX0NCoioynbpQFWopVZEmgK7KjvHRIjSVVl5veZ2vn/g6rohcmflY6WP88ZI/pthUzF0hPAj1L8PpH0PPsIUblhIS817kK4Pr+d4J+bU21RTwtQ/Nw6DJVsuNJyRJ4kTvCbY1beOd1neIizKxrVfp2VS+iecrP8g0dZz+/jfp69tJNDqsHFMqjeQ415GXtxmn8+EiN0D+bDoCHTT0y+RG/UA9F1wX0p/RSJRby6nNqaUup4663Doq7ZWoFKO/q7H29nSgd+jYMaT46Dwk09q1mFavQuV0jvr79zwBvtDUwYWUZe18s4GvVpUw3zKFimgkSf7teztkux5vB0lvJ4fDHXw/0oE5OMCX+vtxhjzy8Q9R8Hd8IIxn+1WiTfJEqdKmxfZMBbq5jjHHywMDA7z++utcS7kxOBwONm/ezMxCG+z9ezj5fZk0Uqhh6W/Dmj+Ww6mzmDKQJInIBTe+PW3EO/wIBGi2BvnG/AIO6+TxuUMM8398e/lI9xuofO3D9mu3gkIFpoJhO6sx8j0iGgFf8ALeVO6Fz9eAKIZHnUqnK5GJC8t8LNZ5mE3Vk/+aH4/I1xlPyyh1BZ42OUPlFvAr82hJTOeaz0xrf5LYyABpQaBwZhXlCxZTPn8x+eUVNywAFSWRlsFrnKl/i5MX9nMucJV2e4SYevTv3iToqM6poSZ/HjU5NVQ7qykwFjyUc2qSJOF/6y16v/JVEr29JHIlwr+Vg39aN+6IjSuemXTFNnLZU86l3vD1ERk4jBoWT7eztNzB4jIHcwstaO7QuUCSJOKdXSmCI5XJce4cM3e9g9JmG783+xAgS2hkcceQJIngoUP0f/Nb6QlphdGI42O/juOll1De5P8lihI9zV6ZxKgfYLAnM9TKre+h1d5Iq70Ra6mWjeUb2Dh94x35HsfjHtyDR1L5GwcyBjoAGk0eTsdKHI5VOBwr0GhGd84fdiQTIt6+MIM9QQZ7gri7Qwz2BPH0hEjEbyC7E8Ds0KUVHYZ8A5dtAscVcfZ6A3RGMwdTFXptOlh8UTxE9O138L3xBuHTp4cPUigwPrIM86ZNmB9/HJU92+G9E0QSkbTa42aWVwPhASLJyK1PmEKBsYBN5Zt4qvwpZjlmTeA7yAJkdUXSH8u0f7qOtJDCt6musFyfWZGptBB0ygnrfEaj0TEJC5fLRTg8eiAyElardUx7KJvNhlKZDUEbD4R8Xs7seoNT7/yMhKsLayRKrjdOsVtEd91c2NUCODlTwbnZerRzZlPlmJUmMCrtlRjVt2+lFOsMEDzRQ+h0P1Ik9T0WQFtpx7g4H/1c57hYlN0MkiQRSor4kkl8CRF/Iok3kcSfSOJLPfwpsiL9fGg9mcSfkPeN1RFe7zDz5cpiZhomfhB9MRjmw2ea6YnFKdGp+d95FczQa2kabOLl+pd5/errBFTDBJJBZWBd6TqeLHuS5UXL0SjvbvJNEiVCp/vwvd2art69X+hW93PSeAGfMsCc8AwWhIbzsdxaP69a9vCW7TB2Rw5/uvRPWVF8F5VroggtB2Q1xoUdMBRar9TA7KdgwUfwFq7k0/9bz4EmebLhDx6v5DPrK1E8RIqjB43ByKCsxmjaRouvJb19jmMOW6u2srl8MyZNZrGUJIn4fGfp69tJX99OItGu9D6l0oDTuY68vE3kONc+tGrtWDLGJfcl6gfq00qOdn/7qON0Sh1znXOps1ezuN/EtIY+pMPHiV3NtLpQl5ZiXrcW09q1GBYtQrgND++EKPH9zgH+4Vo3gaSIAHy0yMkXZhRiVz84wi8pJgkmggSD/UQGr5IYbEX0tiN4O1D5e9EG+tCH3JjCXjTJsRWhSWCoF9KnVHHs0d/gsbVfRq+a2t8nMZbEv68d//6UvZRSwLymBPPaaSg0o/tdsViMgwcPcvjwYURRRKVSsWrVKlasWIFqpAVK3wV4+y/gyjvyc70d1n4BFv8GKO9vrkIWdwZJlIhccOHb3Ua8KwiA26DgPx6xsU0dRwQ0gsBvleTyB2X5mQUcsVBmkPlYFleB3lEWdAkF+M0qfGY1XosKn1lFdIzMLiUaLKoSrIbZWGyLseStRmspn8iP4+6QjKcIi9F2UHja5M/hVtBawDYd7NPBVkrSPI1uv4Zr7R6uNV2jv60143C92ULZ/EWUz1/E9LoFGCx3r9Jtv9rGf//0B3S3HyZp6KY9X6QlDxKq0X0du85OtbOaamd1muTINeTe9WtPNsT9AU586z85fKie8/ZSGvPL6dOMthYtdehYWp6TDvGuyJ0Ya2NJFKeMO8n9RJbQyOKOEHzvPfr/5ZvpSWlBr8fxkY/g+I2P33AyOhZO0HbeLec7NLiIBIc7jKKQpMt8lVaHTGIUF+WxsWwjG6ZvGJdwb0mSCIWu4nIfxO0+yODgUURx5MSugNlcnbKnWoXVugCFYupX29wtJFHC744w2CMTHIPdQQZ7Qrh7gkRvYlejM6uJlhm5WqKhwQznhATGgI81p4+x7sS7zLt8AcXQJUQQMCxahHnzJiwbN6LKyblP7+79C0mSCCVCY4abZ4SeR+R9CXH4fz3bMZsPzPwAT5U/hU1ne3BvYgpDjCRGkRRJT2T4uS8GN1BMjYSgU2YEa48iLcxyhfREIhaLpTMsricvgsHgTf/WbDaPaQ9lt9tRq7OD3PGGKzTAlYaD9J1+j9i58+ivdlHQEUI/Oh+RiBqaSpR0zclHv2EtldXLqbJXUWwqHje1lhRPEm50ETzeQ7R52L5HYVBhWJiPcUk+6vzRRIkkSYRFKU0wDJERI4mGoX3eRBJ/cui4EfuSydsRMN0WVAJYVEqWWo38VkkuK+33V03YFo7y4bPNNIejONUqfjpvBvPMciV0c3Mz//ryv9Kia6HP3odXGv6czWoz60vXs6l8E0sLl6JW3Po3J0kS4UYXvndaSPTJpKTCrMa8dhpNYjPdR5qY6S3BJMqvLyISUkQIKsPEVAlEDQg6BSq9Fq1Bj8FkwmKxYjSZZesSvWxhotApZTsTrZKkJ0q02Uv4opvoVU+G8iyiiHFSf46gKsKj/jrMovx9SQoiuhonthXT0Ey33P5A0tMuB3yf+Yk80TCEvGpY+FGo/RAYnTT3B/itH52guT+ITq3g6x+az+ba91dW20RBkiSO9xxnW9M2drXtSisNDCoDm2dsZmvVVv5/9t4zTI7rvvL+VVXn3D05Z+RIAAwiEZjAJImURFmSZUqy17LkKMtp137tXa9317tOsixLXllrSVayJEs0JUrMCQBBEiByBibnPJ1zd9V9P1RPT/dMDzAAARAgcZ6nn6quqq6unum+de89/3PO6rLVSz6XTm48zeTUsySTI/l9smylvLyQ3LiO1AOXAH/SX2RV1Tt4jLZzETZ1Czb0ChwFQyFNloisrMey7Q5aHngUV8fKS56MmUhl+B89o/x4Qq/29xkV/rS1lo/WXJwNnxCCRDZBLBMjkokQS+eWmRjRdJRoJppfxlNhpOgEltg01pgfZyKEOxmlLB2nPJOiJqvi1ZaW4zEjy4wbDIwbFAKKzPZEmoqs/p3c76nk911GQopCpbWS39z4m7y/7f0lVS/XMoQQJE/7Cf6sBzWok7fmZV4872/DWF6apDl37hzPPPMMwZwFSkdHBw888AA+33lyg7pfhOf+FKZ0FwfKOmDn/4Rl970j8kbeSRCaIHFqhsjLg2TG9L582iLzo/f4+Jo5Qyz3+3lvhZs/a6ulaREXhgu+TzZFbPoA4enXCEWOE072ENWmKZIFAwiBI6biDmdwRbK4IlnscZUF3xqTo9jOylWz0O7KVn7RFlfnhabqKq5SZEVgQCdyLpQbZLTnyQo8uWXhc6uHaMBP/9FD9B05yMCJo6TiBWMsSaKmbZlOYmzcRHVrx2Wf6B4JJvjKC2c49cJrbBg/RX32FEnXDD3VEr01EoMVoJYYc1ZaK1lVvoo1ZWtYXa6THV7L9VGwmsqqnBgOcaA/wIF+P4cGAoQS8/IvNJVWbYqOtnGa3Ifp8PZSboemps/SUP+Jd2zhxLWMG4TGDSwJ8YMHmfrSPxJ/800AJLMZ78c+Rtmnf7Wk/Dg8naD/hK7CGOkMohUMSFNKPG8lNeQ5S1tlMzubd7KzaSeNrsYr+jlUNUUodDBPcESjZ4v2K4odr/fWfP7Gdee7eAWRiKSL1ByB8TiBsRjRwFy1piETp2L6KOXThynzn9PDAXM41dLBK5tuZfemW6msq+XunHpjs8uO4UaF4zWDZDbJqyOv8lTvU+wZ3pOfXDDKRu5suJNH2h/hPbXvOW9Y2LsJQhWokVJB23OkhUguIXBPnlNXLEZayJarM2jOZrMEAoGSaotwOHze19rt9pL2UD6fD9MSqjxv4OKR0TL0BnvpO/U6gaMHUc924uyZpH4sja1EMX3KAFP1DpIddUitLcQwMHZ6ADWsKyZlxcCyW29n/c4HqVu+6i3fA5OqlicZwjmSIRBIMN0bwD8cIZJViRolIgaJuNNI3GMkZlWIaHOKiSVk1S8JigQuRcFpUHAZFJwGGVdu3aXMbpvb585tn9umYJWlt71fMJXO8PFjvRyPJnAoMt9e28p7vHrleldXF9///vdRNRXfah+JxgTPDzzPVGLOxsBj9nBP0z3c33w/m6s2L2jPhRCkOgOEnh/IW4ZJVgOuHfUE12r89dG/ZdfQLgDcJjcfqH0/HRXLqfHWUO9soNJWeVnuEVpKJdUdIHHGT+zcNM8ou/lWxU8JG2KYNCOPTb2XreGbqMrO9UPTPkHZ7S04N9WUbjOzKTj7FBz5LvS8TN5Dy+yCtY/CxsegdmN+wu3Vril+83uHCSez1LotfO0Tm1lT99YzSt7tmEnM8NOen/J45+MMRubIpNVlq3l02aM80PLARSnB5kMIQThyXCc3Jp9ZSG6U7dDJjfI735HkhhCCdE8P0V27iOzaReLwEV2JlEPcpnCoVXCwDY61SsQt+vddlmTaPe2sLV/L+or1rC1fS6un9aKI7YyW4ZXJCf6iu4f+WABJS9Bu0fhwpQWvktZJinRkwTKaiRZtU4UKQuDRNGqyKtXZLDVZlSo1S3VWpSarLytVlaW0NnFZZspoIWC2EbI4idk8xG0+Mo5KMs4qJFcdFqsXp9GJ3WjHaXKyzN2KLRkBkx3N4uKZvmf4xyP/yEhU/z61udv4/KbPs61+29t+X1gKsjO6vVTyXM5eym3G875WLKvLSl5/MBjkmWee4dy5cwC4XC4eeOABVqxYsbTPq2bhyLfh5f8F8VweS+sO2Pm/oHrN5fpYN3CJEJogcWKa8MuDZCdyrhlmhT13lPMFW4bhtD4GXO+08hftddziubCdeCFSqSnC4aOEwscIh48SDp9YkHsKYDZX43JtwO1aj8u1HpdShxIPzFN4zK7nVCCpUIl3LAHZWGBpVdriCkf1nH2cpkF0fB5h0T/3PDyiZ/icDwZLjpwoRVg0g823gNTTVJXRrrP0Hz1E75GDTPUXK+csThfN6zbSunEzTetveksqjIvB4Eycf3ipiyeODOOLBdkycYaH4n00jJ5iwJ3KExw9tTIjZaCVaBZq7bV5cmN1+WpWla26pIyny41QIsPhAZ28ONDv59hwiPS8/AurUWFjo4fNTV5Wj52j6utfxDw5hkAg//JGAndME0/p/yuTqZKWlt+mtubDyEsoGrqBy4MbhMYNnBeJo0eZ+tI/6sGg6GHNno98hLJPfxpjVWX+OKEJJgbC9B/T8zBmRoordYOWSQa8pxjwnmTc2cvKipW6EqPxXhpcDVf1MxUilZrMZ2/4/XvJZIqD9iyWBt2eqmwrPu97MBjenbkO50NyOsjUk88Rfe5ZxMmDSOrcTT7saGCichOnOrZwrK2a7hojw2WGopu4XcAtRgt3+1w81FRGtWNh1YemCRKRNPFQmng4TTyc0pehNOmUiqxIeCptlNc7KKtzYHPdmDi9HAgmgzzd9zQ/6f4JZ/xn8tsrbZU83PYwD7c/fFmUVNcqhBCIpJojKZKlSYtwaoGnfCnINgOKu9AOqpiwkJ2mqxqWrKoqwWCwpD1UKBTifLd8i8VSkrAoKyvDYrnGvWuvc8wkZjjnP8vg2QOEjh1GOteLdyBAy5iGvQR5kTFI+BvcZJY14li7jtpN22hYcyvyPEVMNp2mc99ejr7wNGOdc0S/p6mV9nsfpGbzrSQMJsIZNWfbNKuKKLBvUgvtmrS8pVP6MnUfJZgjIQrIB3chCaEUEBSGQoJCf41Nka+LSaelIJJV+cSJXt4IxjDLEl9b3cx95foA98yZM/z7v/87Qgg2b97M/Q/cz5GpIzzX/xwvDLxQFCpcZinj3qZ7eaDlATZUbiDTHyH0XD/pfp28lEwKjq11GG7z8a/d3+YbJ75BWktjkAx8fOXH+ez6zy6wAbqc0ITGK4Ov8NXjX+WsX/9uNqv1/Prwo6yLz4XxJqUURmFAyU1tppUsqVVGmnesxVrnhvGTOolx/IeQKOjrNW/VSYyV7wPT3MS2EIJ/fb2f//nUGVRNcFOjh68+tolK54027lKhCY39Y/v5ceePeXno5bwa1G6081DLQ3xo2YdYVbbqsr+vEIJI5AQTeXJjOL9Pli2Ule2gqvIBysruxGC4dBLl7YaWThN/84Ae6L1rF5nh4aL95mXLcGzfjuPOHVjXrycp0pyZOcPxqeMcnz7OiakTjMfHF5zXrJiptddSaavEY/ZgN9lRNVVXSeSUEoVExMVYnFo1jeocWVGtzpEUNdksVapKdVbFuoR7iCbJJG1lpJ2VqM5qhKse2dOA0duKxdeG0dsMFvdlUQak1TQ/OPsD/vn4PxNO6+3kpqpN/P6m32dtxdq3fP4rAZFRCe8aJrJ7CLI5e6mt9TjvKm0vlc1meeONN9i9ezfZbBZZlrntttvYvn37pRWnJEPw6hdg3z+BmgZJho2/BHf+KTirLsMnvIGLgVAFieNTOpExpasvJbNC1x2V/I1H5VBU31ZrNvInrTV8sMp7QYWVqiaJRE4SDh/LZ18UEsmzUBQbTufaHHmhZ19YzNUX/yFS0UUsrsZ00iEypgeeL2WQBmCvBJNdf61aQspcCNkInoY5ssLTCN7mOQLDUbmktiYWDNB39BB9Rw8xcPwwqXlK9+q2Dpo3bKZ142aq2tqR38Ziwp6pKF96qYsnj40iBBi1LL/qCvFIqh/Dm6+THhggaYT+KuipkehrtdPbYGDYWDrvs8nVxKqyVXnLqpVlK99SEcNSMBJM5MK7/RzsD3BuIrIg/6LcYWJTk5ctzXr+xepaF8aCbEk1HGbqH75E4PvfB01DsltR/vMOJusOkkzp33ertYnWlt+lquq9SDcySa84bhAaN1ASiZOnmPrHLxHbvUffYDDg+dCHKP/sZzDW6DL7TEpl6Ixfz8M4OUMiPNf4CzTGnX30+07Q7z1FyDrJmrI1eTupemf92/GxzgshNCLR0/hn9jLj30ModBgh5mRmkqTgcm2gzLcVn28rLtdaJOndWaWuxeNEd+8m/PTTRHfvQaTn/vfmjg5cDz2I/d77SFgrF+R0jPgTdJYrdNcY6ak2kjAXNPRC0BDWWBeTWB+XKZ9IkwynSUbSC24454PVZcqTG7NLb7UN5Qr7tL+TcdZ/lp90/4Sf9/6cUEFVzE2VN/GBjg+ws2knNuP1VeUoVA01pGdXZEOlSQuRWoK6QpFQ3PMzKwpIC7cZuYQf7JWGpmmEw+EFhMXMzAzBYBDtPBYMJpOpJGFRVlaGzXZ9/Z+vR2TUDL2hXjr95xjqPEzs5HGMnQPUDCdoHS+2C5lF1iARbixDrGjFve4mGjbvwL1iNZJhYZV6QtXoiSfpjqfojCfpjacIZHQyIpBIEkgmiSGRNVy+CqNZsmGOfFBwG+dICIcK5tEY5t4wVn8KRxYcWYHHZaZyfSUVN1VhdF6azcE7FQlV47On+3luOowiwRdXNPLhat0C5MSJEzz++OMA3Hrrrdx3331IkkRWy3Jg/ECe3JidkGtPNPBp/6OsC3foJzdIOG6txbG9nt3+V/nrA3/NaEzPJ7il5hb++OY/ps3TdsU+W1bL8mz/s3z9xNfpDnYD4DA6+M0Nv8lHVnwEOSpInvOTOOMn1R1ApOfaM4FAKjCnmLD0YpKfZKW6C4OU1e0oNvyi/ihb+BnSWY3/9uRJvv+mnkPwoZvq+csPrsF8hQLf3+mYTkzzk+6f8Hjn4wxH5ybZ15av5dFlj3J/8/1Xrf+gkxsn85kbieScOkSWzZTNKjfK7sRguHJE3eVCdmqKyO7dhHe9Qvy1N6Agr0oYDcTXtTGzqYXRdTX4PcqcIiJn4zSflBBLnfxbAhyKhWZM1AsFW0rFmcpQk81Ql03TqqWoTEexZM6fr5WHvRLc9eCuA3eDXmXtrp972Csvr63MEhBOh/n6ia/z3dPfJa3p46CdTTv53E2fu+KOAxeDxJkZgj/rRfXrHQdzuwfPw20YK0r/5np7e3n66aeZntYVFU1NTTz00ENUVlaWPP6iEOiHF/8cTj2hPzc54I7Pw22/CcYbVi1XEkII1JkkyZ4g0VdHyE7niAyrgdAd1XyxAp6c0cd3Vlnmt5sq+WxDJTZl4e9KCI14vL9AfXGEaPQcQsxXLkjY7e1z6gv3Ruy2duSrZdOmZiAyvnimR3hE3z+fwJAUva3xNBVlWeQJDGc1XAK5oGkqY12d9B05SN/Rg0z29RTttzicNK+/iZYNm2hefxM2t+ctfPgrg86JCF98sZOnT+jktyzBIxvr+O1lZtzHDxLds4f4m2/m54biZuhrMDG0pZ7eFhtd5iAjyYXEuYREq7s1r+BYXbaaFb4VWAyXVkSiaYLOyQgH+vwc6A9wsN/PaGjh4Kml3M7mPIHhpaV8afkXiVOnGP+LvyB57DgAppXt8Ie3MqL+lExmBgCHYyVtbX9AmW/7O6aY6lrEDULjBoqQPHuWqX/8MtGXXtI3KAruRx6m/Nd/A1N9HdFAkv4TM/Qdm2bkXAC1QJalGtL0u0/R7z3JoOc0KWOcdeXr2Nm8k3ua7qHOUfc2fapLQzYbIxjcz4x/D37/XuLxvqL9BoMHn+89eYLDYnln+ylrqRTRPXuIPPMMkVd2IQoGTaaWFlwPPIDrwQcwt7ef9zyFOR3T41EOzkR5I5vimF0w5i7uHNiSGu1jGdrHMrRNZPBZjNjcJmyu3MNtxmRRyKY1AmMxpkeihKYSJYsxZEXCW20vJjrqb6g5LhZpNc2uoV080f0Er4++jpazFbMarNzffD+PtD/CxsqNb/uNWwiBSGQXhGsXkhZqJL00dYXdoFtALUJayA7jVVVXFEKfnImUtIfy+/2o6uKEjMFgWNQeyuFwvO3/w3cLphPTdPo76fSfY7jnKKlTp7H3jNE8qtE6LnCWIC9Ug0SsqRLDymX4NtxM9abbsbS3I81TXgQzWbriKbpiSTrjSbpiKbriSYaS6YuatjKmU5jTSczpJE5FodLroabMh9to1AkKZc6iyTlfHaHIOAwKyhK/T0II0gNhYgcmSByfQmRy/QxZwrLSh31LNZYO7xXPi7lekNUEnz83yI/GdQuR/9Fex6cb9FDGw4cP8+STTwKwbds27rrrrqLXZtQMB0+9QfqVCdrG9ArJLCrPeV5nV9MRljWtojvQzfFpfcBWba/mj7b8Efc03nPF2oe0mubJnif5+omv5ye/HUYHH1vxMX5p1S/hsyz0bBcZjVRfiMSZGZJn/aiB0sHlMTlOX10/tffcxJplm0ra6MxEU/z69w7zZp8fSYI/eWAlv7q15UZ7eJHQhMa+0X38uOvHvDL4CtncRJfD6OC9re/l0WWPsty3/G29RiEEkeipHLnxNInEPHLDt43KygcpL7/ripEbWS2r50IUZEIsZsmkL8PYeydpODFB+6kgjSPFE3F+BxxulzjULnGySSJluvjvrUE25G2XHEYHsiSTFVkS2QThVJhQOgRC4NM0XVmRValVNZbLdlplM7VZDU8qihKbRrqQlzzodm/u+gKSog5c9QXrdWC4dsnssegYXz76ZX7W8zMEAoNk4BeW/wKfWf+Zku3V1ULWnyT4sx6SZ3RFmuIy4X5vK9a15SXbs0gkwvPPP8+JEycA3UJ0586drFu37vK3f4P74Nk/htHD+nN3A9zz57DmQzfyNS4T1HCa9FCE9PDsI4pIzBEOss2A2FrLN2oV/mV8hpQmkICP1vj4zy01VJvn+pPptL9IeREOHyObXWhBazKV58iLDbp1lGvtte9uoWkQn9EJj1R0ri1SLg/pEg8F51QYxw6TjBUrFqpa22nZsImWjZupbl/2tqowLganRkP8/QtdvHhmAgBFlnj0pnp+++52as0Q27+f6O7dRPfsITtaHISeXNHE6Lbl9C9z0WkNcsp/hon4xIL3UCSFdk/7nF1V2WqWeZdhVBYWWyUzKseHQ3n7qEMDASLJYoJNkSXW1LrY3OxjS7OXTU0+Kt5CoZTQNIKPP87U3/4dakgnA50feojUxysZmvpe3l7N495CW9sf4PFsvuT3uoHFcYPQuAEAUt3dTP3jl4k895y+QZZxv++9lP36rxOSfPQd1/MwpoeKG+GkLUKX6zD93pOMuXrQZJV1FevY2aRnYtQ43jmT/InEMH7/q8z4XyUQeJ1sNlK032Zrp6xMDxf3eG5+R4QCiXSa6Ouv6yTGiy+hFUghjfX1Oonx0IOYly9/y51dIQT9M3GeGfazOxLjQDZFvGDKTQG2uO357I2VdkvJ90wns/jHYswMR5kZjjI9oi/Ti+QYWF0myuvsRSSHt9p+Q82xBEzEJvhZ7894ouuJIg/sJlcTj7Q/wvvb3k+l7TJUdJWAyGqooXn2T6Fi0qKwYndRKFIBSWFZGLTtNpeU419NCCGIxWIl7aH8fj+ZTGbR18qyvEBlMbt0Op3IV7mi8d2MWdXFucA5OmfOMdp7HPVsF5WDYVrHoHVc4CpRrKopMqmWakyrV1Gx4Rbc62/C3N6OlLN9EEIwlsroxEU8SWcsSVeOvJjOLO7z6zEodNgsdNjNtNssVJgMeeWEyyDniQmHLDN6+jjHXnia7gP7EDllj93jZe3d97Hu7vtxlpVfkb+ZlswSPz5F/MAE6aG5e67iMmHbVIV9cxWGsuv/XvtWoQnBf+se4f8N6xW1v9dcxR82VyNJEvv37+eZZ54B4O6772br1q2APtkVfnGA+JFJndiVINyh8UT1K/w08DSJbPGXcWPlRv5oyx+xpvzy+J5rQmM6Mc1odFR/xEYZDA/y8tDLeRWg1+zlsVWP8ZEVH7mw33J4FI5+D3H4e2T9KgltCwn1ZtJiJRLF7ZxAMGgdZ3htlNV3bGF1xRokSeLseJhf/dZBhgMJnGYDX/rYRu5ccWXuYe9UTMWndDVG1+P5nAGA9RXreXTZo9esmlMIQTR6mok8uTGQ3yfLJny+bVTlyQ1nPrS6kIjILxdbn7VmykTy2+b/zkrBnBas7Rfc1CO4qVvgm+fg0V0Dh9pljrTLTNbbsZscOE1OHEYHdpO9KBOiaGl0Fu135F5nkk1I6SiERiA0DOFhfRkagdAQWmgIwiPI6uJ9j1lkJZmsswqzrw3JVY/qquNVzc23Ylb6jOWMmSt5tKmZP2qpxm28vsK15+Oc/xx/f/jveW3kNUC3UvuVNb/CY6sew2q4evcpkdGI7B4ivGsYshrIEo6tdbjuaiypFlZVlYMHD/Lyyy+TSulk8JYtW7jrrruwWq/gdWsanHxcV2yEc8qt+i1w159By7YbxMZFQEtmddJiKEp6OEJmKIIaLmGbZJAw1Tgwri7jiWYzfzs8gT+jj4/v8Dj48/ZaVtkVIpEzRdkXhWTvLGTZjNO5poC82IDFUvuuJ/81TWW8u4u+owfpO3KIid6uov0Wu4OmdRtp2biZ5vU3YfdcH4HZi+HYUJAvvNDJ7k49p82oSHxkSwO/dWcH1W6LXqTU3U10zx6iu3YTP3wYCortZJsN23tuI7X1JgZXlXFWHeHUzClOTp8sskedhVE2ssy7jHbnOszZVYRDFfSMw8mRMGm1eNxvNylsbPSyudnLzc0+1jd4sJsv/30mGwgw9YW/J/ijH+mfyeXC+/lPE9o0yfDod9ByCr7y8rtpa/19HI63t5jjnYYbhMZ1hq6urvxk1OVAqq+P6a/8E+GnngIhQJKw3/8gqQc+yfCUkYHj08RChTdEQcQ7xWnnfvq9pwhYx0DSByo7m3ays3kn1fZL8EG8zqBpWcKRY/hndIIjHD4OzDWismzC495CWdl2qqofxmy6MpM9VwIimyW2fz/hZ54h8sKLaKE5eyFDdXVeiWFZs+aKdlrSmsaboRgvzYR5aSZCZ7y4TLnWbNTJDZ+LrV4H9vNYQQihq0JmhqPMjESZHo4yMxIjOBkvreaQJbw1Nsrm2VbZ3dduhdjbCSEEhycP85Pun/Bc/3P5Abosydxeezsf6PgAO+p3lKyoWOx8WiyzMLOigLDQopmlqSscRp2kcJcmLWT726OuyKga46EkQ4E4I4EEkiRhlTXkbAItGSEbC5MM+wkGdNJidpBZCpIk4fV6S9pDud3uG6TFVYYQgpnkDOf85+gMdHLOf5bx/tMYzw3QNJaldVwnL9zxha/VFBm1tQ7bmnWUbdiCZfUazMs6kE0mspqgP6mrLWatorpiKbrjSaLq4uRdrdmYJy46bJb8ernRcNFteMQ/zYmXnuP4S88RC+gDDUmSadt8Mxt2vpfGNeuQrtD3LTMeI3ZgnPiRSbT4HFFjbnNj31KNdXU5kvHd+10XQvD3AxP8dZ8u5f+VunL+Z0cdsiSxd+9eXnzxRQAe3HEfHcEKYgfGQdUbUcuqMtw7mzBU2Xi672n+9sDfMp3UyREZGa2gf9PmbuP+lvu5v/l+mt3Ni16PqqlMxicZjY0WkRaz62OxMTJa6QnRKlsVn1z9ST7U8aHzT35n09D5LBz5DnS/CLPV4CYnrPkg3PQJVM86Ul1BoqenSJyZQckWf+fTUoazrgFebVD4yblyEhlBU5mNf/nEZjqqrvHK0msEqqby+ujr/Ljzx+we3q2HOQNOo5P3tb2PDy37EMu8yy5wlquHjJpZlHSYDaf2xwaYCZ/DHxsgmomR1CApJJKaRAojCU3LK1QvB8yKGYfRgcPkwGF0UBMxsOpsnJZTfqrPTaFk5t5Ls5jIbF6NfPsWrFvvwFnTgMPowGa0LS28O5vWq5ELSArCI3PPw8N65sEFIYGjCuGuJ2n3MW4w0kuaE+kAhxLjDCkCvywjJIlbam7h9zf9PivLVgIwmkzz5z2jPDkZBKDCZOC/ttXyaJX3up8Q3Te2jy8c/EI+e67SWslvbPgNHm5/GMMVttpJnPMTfLIHdSZnL9XqxvNIO8bK0u3o8PAwP//5zxkf1+8btbW1PPTQQ9TVXUVXhXQc9n0FXv17yOQK5zxNsPxB6LgHmu4A443solmIjEZ6LEp6KEJmWF/O2kcVQQJDpQ1TgxNTvRNTgxNRYeGVUIz/1TtKV1wfV7RZZD5XPs46bR+RyDEikdMIsZAMsdlacbnW5wkMh2PFjeDjHOLhEP3HDtN35CD9x4+QjBSrVyqb22jZuJmWDZuo6ViOrFwfKoyLwaEBP194oZPXunW7JZNB5uO3NPLrO9qKssfUSITYa6/rBMeePag5a7tZmFeswLFtG/ZtWwkvq+F08Cwnp05xaKSXE8MJouEq1HgzWnph9o7VnGFZrYHbW6vZuaKVNbUeDCUs064UEkePMvYXf0HqtN72W1avxvunv8GY9UXGxn6MECogUV31MK2tn8NqvXasCa9n3CA0riOoqsrf/M3fkEwm8Xq9dHR00N7eTnNz80UHdKWHhpj+yj8RevJJ0DRSJhexrb+Av+k2RofSZAs6zhg1ZsoGOW5/jQHvaZK5cJ+NlRvZ2aTbSb0bSIzzIZMJ4g+8nic4Uqk5aZ0kGSgvv5va2l+gzLf1mszdEKpK/OAhws88TeT5F1D9c4y4UlGO6777cT34ANYNG67YZNWFMJBI8bI/wkszYV4LREhoc02SSZK4zePg7jInd5e5aLWalzQgyqRU/KMxpocjzIzE8mRHOlG6qtnqNBYpOcrqHPiq7Sjv4km0+Yhn4jzX/xw/6f4JhycP57d7zB7e2/peHml/hGXOjkUzK2bXyS5hosAgF6kpiu2gLBjcJiTj2/N70zTBRCTJwEycQX+c4UCC4UCcoZkYg/4YU9EM2hLuqkZUzFIWM1lsRnBbDHhsJspdVio9Dmp8LmrLPfgcZrw2I26rCbfViOmGwuiqIK2mddXFLHkROMfkwFl8AwHaxoROXowJPCXIC6HI0NqIc91GHGvX6eTF8mUkFQM98eQCq6i+RIrMIl0xRYIWq05YtNvMdNhzxIXNjOMK+P6r2Sw9B/dx9PmnGTp1PL/dW1PL+nsfZPX2e7A4roxFi8hqJE7PEDswTqo7mCc2JYsB28YK7FuqMdVe+973VwrfGJ7iT7r0yvgPVXn54opGjLLE7udeIbZnhFVqPYZccLa5w4N7ZzOmBifn/Of4y/1/mW+3G5wN/Jeb/wubqjaxa2gXz/Y9y97RvfkgZ4AVvhVsrdtKla2KmeQMI9ERxmJjjEZHmYhN5G2GFoMiKVTZqqh11FLrqKXGXsPGyo3cWnMryvlsFybP6iTGsR9AvGAw3PgeuOkxWPWwHu45D0LV7czCh0eJnZjCkJIQCL5Lmq+RQgAdhhQfuznK9tvfQ1vZ+S003+2YiE3wRPcT/EfXfzAWm+v3bqzcyKPLHuXepnsva2W6JjRimVhpK6ZcJkQkM7e9UBFReGxKXbxA4GIhAQ6DFYfZjdPkKiIlitZLbStYNyCTOHaM6Ct6oHeqq7iq11hfj+POO3Fs347t5i3Ii437NA1iU/NUFfNUFtEJllQRYnHPy6uYZwXlrAVD6evIqBlOzZziJ90/4cmeJ/Pk5Xtb38tvb/xtah21AOzxR/iTrmG6c5Ort7jt/J9l9ax0XN/KO01oPNP3DP945B/zSqU2dxu/u+l32V5/+f3Us/4kwZ/3kjytTybKLhOeh1qxrittLxWPx3nppZc4dOgQABaLhbvvvptNmza9fUUwkXHY/ddw/N8hXeCCYLDqio2Oe/WHt/ntub63AUITZCfjBdZRUTJjMUoNIBSfBVO9I09eGGsdyGaFvniKl/1hdvkjvBaIEM+91iUleFT6D7arP8VAsYuB0ejNqy708O71GI3uq/KZrwdomspET7euwjh6iPGeLgrDPs02e5EKw+F9+6znrjb29c7whec7ebNfn0uyGGU+cVszn9nWSpmjuDBUaBrJM2eI7t5NbPceEsePgxCoSAy4qjlVv4pzbTdxwlrJZHphO2azhRHmHoSlG8XWj2ScyQu7bAYbK8tWsrpsNWvK17C6bDUNzoYrTpgLVSXw/R8w9Q//gBaJgCTh+fCHcfzGB+if/jqTk08DIElG6uo+SnPzb11Xhc/XIm4QGtcRIpEIjz/+OIODg0Vhroqi0NzcTHt7Ox0dHZSVlS36Y82MjDD91X8m8MQTRM1VTJevJdByO0GKG1rJkWW0vJPDlt2MurtR5SwSkk5iNO/knsZ7qLIvZEZvQK+SjMd7mPG/ysTEU4TDR/L7zOYaams+TG3th7FYat/Gq9RvIomjx3QlxrPPkp2ayu9TvF6cO3fieuABbFs2I11jlQQJVeONYJQXZ8K8OBNmMFlcSdJsNXG3z8U9ZS5u8ziwXAQ7L4QgGkjpKo7hWTVH9LxqDk+1rWQ2x/VSZZbJZBgcHKS7u5v+/n5SqRSapqFpGrIsI0kSsiwveCy2HRUkVZBOJQlFgySTcYxZBauwYFPNWIQZGQkJCRmJDCoxKUVQiqEhMCCjIGNQDBgMBowmIwaTEZPFhNFqxmQzY7SbMVpNGI1G/ZjcsnC91LbZ9cs5YEtlVfb3+tnbPU33ZJT+6RjDgThp9fy3TRkNh5TCIenf37RQSEsm0hhIam/t+uwmBY/NhMdm1B9WE26bEY8199xmyq3njrEacduMN0JvF4EQgunEtG4XFejMExjBkT4aRzO0jc+RF95YidfLMkp7C84167GuXYNl9WrirW10Z0URcdEdTzF8nnwLqyzRbrPkCIuc4sJuocVqwvQ2TULMDA9y7IVnOLX7JdIJnbkxmMysuH0bG3Y+RFXrlZsUzgaSxA9NEDs4gRqcm6Q01jmwb67CtqES2Xp925hcCv5jIsDvnBkgK+Ahl4O/9htI7h1FpPRJiwkpiOXOWlbv3EQoFeIrR7/CD8/9EE1oWBQLv7bu1/jE6k9gVooHn+F0mJcHX+bZ/mfZN7ovX4m/GAyygRp7DbX22jxpUeuozT+vtFUuvWI5GYZT/wFHvgvDB+a2O6pg/cdg42NQfnHftchwmD/47mGeC+o/2g9i5HewYEAiLaU54xlELLOy9tabaappvahzv1Ohaiqvjb7Gjzp/xJ7hPXmVgsvk4v1t7+dDHR+i3Vv8fxBCkFJT57ViWrBv9nnBtlimROP6FmA1WEvaLs0nHWYtmhxGB4o6QzJ8kHhwLyLZj0nSnXEkyYjPdwdVlQ9QXn4vRuOFx65qOExs714iu3YR2/MqajA4t1NRsG3ciOPOHTh27MDU2qr3KZOhRaygcs/DowsDbktBMecCtuuLSYr88zowXx6F0nBkmH888o883adP5JhkEx9f+XH+09r/hNvsJq1p/PPQFF/onyChaSgS/Ke6Cv6wpRrndd4nSatpfnD2B3ztxNfyVnqbqjbxe5t+j3UV697y+UVWI7JnmMgrQ3relCzhuKMW192NyCWsVTRN49ixY7zwwgvE4/r9ev369dx77704rlARwkUjHYPul6D7Beh6QQ9vLkRZB3TszKk3br+m81UuBkIIVH+SdE51kR6OkBmJzuWIFUB2GHXiot6BMafAUOy6WiKaVdkbiPKKP8jLMwGG5vG3LhFkK7t4mMexE0eSTDidK4uyL6zWxutmDHu1EA+HGDh2mL6jh+g/dpjEPBVGRXOrnoWxYRO1y1a+I1UYS4UQgr3d0/zd850cHQoC+rj0U7c38+mtrXhsxUR4MqNydCjIm2dG2X9igKMBlZhU3H4pmkpH2s+mchO33tTGbXeso9xlRRMaA+EBTs2c4tT0KU7PnOaM/0xJO0enycmqslWsKVuTz+Wosddcke96dnqayb/5G0I/1XPsFK+Xyj/4faR7Oujt+wJ+/6sAyLKVxoZfprHx00vqN9zAQtwgNK4zqNE0GUmlb7Cf7u5uuru7CYWKZcEejyev3mhpacFkMpGZmGDyq1+j78UTTHtWMl22ltS8oDK5MkWf9wRvml9mxjYCEkhI3FR1U16JcaX88N/JiEbPMTr674yNP0E2O/u/kijzbaW29qOUl9911SSbQgiSp08Tfuppws8+UxTSJLtcOO+5B9eDD2K/5eYF4bLXKoQQ9CRSOWuqMG8EY0VVzFZZ4g6vM5+90WC5tBDwTFpXcxTmcsyMREnFz6/mKLSs8tVcG2oOIQRTU1P09PTQ3d3NwMAA2ez5K2nfaZBl+YKkx4UIkt6Qxs+7kxwaTZAqMa8noeGQ0jilVJ64cEgpKqwyjWV2Giq9lJcVh3LPqu1UTRBOZAgmMgTiaULxDMFEmmA8k3ukCSZy64kMoXiaQDxDOJnhrdytbSYlR27ohIfXrqs+POchQ9xWI5a3SQlzJZBSU/QGe/PkRae/k85AJ5rfT2tOdaGrLxZ6mYNOXpjaWrGtWYtl9Woiy5bT19BIV1YqyLhIMXOefAufUSmyh5pVXtRbTMjX6CAznUxwdu9ujj73c6YG+/Pbq9uXsWHnQyy77Q6Mpisz8SA0Qao7SOzgOIlTM3krJQwytrXl2DZXYW51v6sG6C+OBXjxuS5+qSeNJ6P/PYw1ds75pni5+w0kWaLxjka+OfVNAik9UHxn007+YPMfLCn/LJAM8NLgS5yaOcV0Yppya3kxcWGvpdxafn6lxYUgBAy+oZMYp56ATE7qJCmw7H5djdF+7yWFd06Ek/zatw9ybDiEQZb409tbuG8kSbYvgiSKvycaGoPOCTKtRjpuXk9d67snJHw2tLov1MfPen7Gi4MvFvla1znqaPe0U24t10mLRXIkCpU9bxWFodVOkxOHyTGXCVEqK6KAkJhdtxvtb8n+R8+26mRy8hkmJp8hHu/O79PJjduprHyAivJ785XNQgjSff1Ed+kqjPihQ8Ve4i4XjltvwrGxDUeHD0WdKSYtwiOQWhjEuwCSDI7qEiRFgcrCXn7VMwpOTZ/i7w79HQfGdULSZXLxa+t+jY+t+BgmxcRwMs2fd4/w8yl9rFRpMvDn7XV8oNJz3f/ewukwXz/xdb57+rukc37qO5t28rmbPkej69JsR5KdAYJP9uTthkwtbryPtGGsWqhOAxgfH+epp55iaGgIgIqKCh566CGam5sv6f2vCoSAiVNz5MbgPigk0o02aNmukxvt94K36e271ouEGknnci9yyovhSJGd5iwks4Kpbpa4cGBqcKK455wINCE4Honz4uQIr8wEOBo3ohbkRikiwzLOsY6jrOMoyy0aHvf6nPJiA07nSmT5nUEKXU4ITWOit1sP9D5ykLGeziIVhslqo2ndBt1Kav0mHL7LYwf/ToIQglfOTfKFFzo5OaLfu5xmA794SyOral2cHg3zZr+fkyMhMvOKAB1mhfUeA2tiIyw78yatR1/FUpDbpJSV4di6Fcf2bdhvvx2lYL5Y1VR6Q71FJMdZ/9l821sIr9nLqvIcyVG2mtXlqy/rfGf8wAHG/+IvSHXpfQTrhg1U/7f/Srw6SE/P3xIOHwXAYHDT3PRZ6us/gaLcsNi7GNwgNK4zjPzZa4iMhmSUkawGJItCyJRgSJtiMDXBaHwKtcDTVZZkfKoZy7SCRitZzY1AvwEqRglRF+Oc8yBvmF4gbtIbGgmJTVWb8kqMClvF2/JZ32lQ1RRTU88xOvpDAsF9+e1GYxm1NR+itvYXsNlarsh7p4eHCf/sZ4R+9nPSvb357bLdjuPuu3A98ACO22/Ph8xez4hmVV4NRHhpJsJL/jBjqWKP7uV2C3f7XNxd5uRmtwPjW8hPmFVzzCc5ghPxkpPKkizhrbYVKTnK6xzY3FdezRGPx+nt7aW7u5uenh4ikeJQe6fTSVtbGy21TTgkK8SyaNEMaiRNJpIiG02jRpNkk1kEeqiqhihaCgSapC+xyGBVwKogWRQwy2BWSBky9CT6ORs6iz/pRxYyqqRitBrZ0LKB7U3b8Zl8ZLNZMpkM2Wz2otcX26+q568mXgqEgBHNxYlsDRNi7t5kJU29EqJMiuGSUpRbBE0VrgWERVlZGRbLleuoqJogkpwjOvJkSCEBUrAeSujPQ4mlWWAtBqtRyZMbs4qQRcmQ3H6P7e0lQoQQTCWmiuyiugJd9IX6sEeztI4L2nJh3a3jgrJIiZPIMqbWVsxr1hDrWMZwazunaxo5p5FXXMTPk29RNz/fImcVVW66flUFQghGO89y7Pmn6Ny3FzVHllocTtbceS/r73kAT/WFJ8wvFWosQ/zIJLED42Qn5ry+lDIL9s3V2DdVorjeuYN3oWrEDkwQfnkQLRcKOmCT+PlaJ59/YCXlJgPf+vdvMXB2AA2NN6rewF5j549v+WNuqbnl0t5TaEhL8e5fKiLjcOz7OpExMzdRTFmHTmKs+yg4L10lfGwoyK995yAT4RQem5H/+/FN3NamT0ZoiSyxQxOE9w4hgqUzPoKmKNFmjcabVlCzuvltszY8H2ZDq89nyZS3ZsqpHxbYOKUjJNXkhd9siZCQilUQ5wmtLmXZNLvPJF97CthoVCc3JqeeIRabs4uSVCNl46twnHEj3hwgM1xcbW6qsOBsknFUhbHaJ1nSz8jqLU1S5K2gamCJmWVXG0IIXh15lb8/9Pd0B/Xfdp2jjt/Z+Dvc33I/siSzyx/mTzpH6E3opeW3eez872X1rLBf3zZUAOOxcb585Ms82fMkAoFBMvALy3+Bz6z/DD7L0mxpssEkoZ/3kjiZs5dyGnV7qfUVJX8XqVSKXbt2sW/fPoQQGI1GduzYwa233opyvVWRJ4LQuytHcLwI0fHi/eXL56ypGm+7ZtQbWjJLekQnLWYJjEJVaR6KhLHGPpd7Ue/AUGFbkPU3Gg/y3Og5XvGH2R93EBLFv40qMcY6jrJROcetLiNV7lU59cU6TKYbE++LIREJ03/8CP1HDtJ37DCJcHHRcEVjM80bN9O6YTM1y1agGK7fvvrVghCCQX+cb77WzxNHRgglFslOc5nZ3Oxjc5OXLc0+VlQ7i/IvMhOTxPa+SnTXbmKvv44WK1Bs5hSN9u3bcGzbjnlZx4K2MKNm6A526yRHjujoCnSVtEatsFbkFRyzJMdS2+eSf4NMBv93vsv0l7+MFo+DLOP9+Mcp/+3fIpDaR0/vF/L9BrOpipaW36am5tEbGTVLxA1C4zqCyGoM/+leJBbvxGfIMioHGJZnGJJniMrFAxGHsFCn+qjAhUmGhJIkqsSJKQlsDge15Q20VrfjdLqRrQb9YTMg5dYlo3zNDSKuR8TjfYyO/ZixsR+TTs/5P3s8t1BX+xEqKu5HUd5aJ0wIQXzfPqb/+WvE980RKJLZjOPOO3E9+ACObduQr+Dk6tsNIQSnY8m8euNAKEbh1KJTkdnu09Ubd/lcVJkvz40jk1YJjMXytlWz2RyLqTksDmORkqO83oG3xobhLUySqKrK8PBwnsAYHR0t2m+QFepcVTSaq6jTynBFTfrk1wVskgAkk1Iyt8IwG7rtMiEtIcPhzMwZnuh+gqd6nyKcnqs63Fy1mUfaH+HepnvPHwh7kdA07ZJJkVQ6w/6xDM8OqIzEcqSwJFjvTrO1WmNdgzdPXJSVlWGzXb7rvhrQNEEkmZ1TgeSIjrwiJKETI4EcGRIqOOatECFmg4y3QOmRJzvsc6THrB2Wt4AMsVzkvSilpugJ9uTJi9lHMBXEGRdzyosceVFeqghWkjC2tpJcvoLJtg66Gls5XF3PaQ36Eimyi/wdDAX5FnmrKLuFdqsZ+3Vup3EhxENBTrzyAsdffIbw1GR+e/OGTWzY+SAtGzcjv5UK/vNACEFmOKoHiR+bytstIYFluQ/7liosK3xIVzEw8EpCaIL40UnCLw6i+vW+n+IxE76jmg9rISZVlSaLgdu1n/NC1/e4eepmGmINSLLEx37xYyxrv7jQ5lish+GR7+H3v0Y83oMkKSiKFUW2IssWFNmMIplRJBOKZERBf8jIKMKAImT9oYGiyciaQMlmsY/0Yu7dP1eFa7TDmg/Axk9Aw81vuar8p0dH+KMfHyeV1VhW5eBfPrGFxrKF7bUQglRviNi+MRKnppntPAhEUT88LWeJ1GaoWt9C+bpGDO63PoGWVtOLWzGdz7KpYD2WiV3W0GrQlREes4cKawUus+u8mRClti05tPp6gxCQDOatn2I9rxPcu5vkiXEy/SAyc59ZkgW2yhSO2hSO2iQmx7xCC4P1wlZQJfJhrjeomsqTPU/y5SNfZjKh3xtWla3i9zf9PjfX3ExK0/jq4BRfHBgnoQkMEvxqfQV/0Fx9RXKhrjbO+c/xxcNfZO/IXgDsRju/suZX+KWVv7Rov1dkNSJ7R4i8NJizlwLHe+pw3dOIbFk4sSqE4PTp0zz77LP5IqaVK1dy//3343a/A/IQhIDxE3PkxtD+eeoNO7Ru18mN9nvB03B1LiurkRmLFagvImSnEgttiyUwVNjyqgtTvRNjjX3B+EkIlZlIJ69OdLE7EGNf3E2/KLattog4q6VTbDGPs81tZKWvA5drIzZb8+UtNniHQWgak/299B05SO/Rg4x3dSIK7psmq5WmtRtpzllJOctuZB1cCKomODMW5kC/n4P9AQ70+5mMLJ5bZTcpfPI9TfzWnR3YStjklYJIp4kfPpILFt9NurunaL+huhrHtm26euPWW5Htpe+ZKTVFp7+TUzOnODl9klMzp+gN9ZbsO9XYa1hTvoZVZatYXbaaVWWrcJsvrh3NjI8z8Vd/ReSZZwE9p7bqj/4I50MPMDHxU3p7v0gypc/XWK3NtLV+nsrKB2/8hi+AG4TGdQRNU/nSY48iazIm2YJJtuB0luP2VmExepCydrS4CVk1Y5ItGGSZlJxg2jDNmMHPpBxClQrUG0KiSvPQoJVRr5XhFfbzkiUAKNIc0TFLcsx7LlsNyJaC7bbccSblBhkyD5qWYWbmFUZGf8jMzB5mR8wGg5vq6oepq/0oDsfyizqnEILorl1Mf/WrJI/lwlolCdutt+B+3/tx7rwX5VrxSb3KCGSy7PZHeHEmzMv+MP5M8UByncPK3WV69sYGlw3lMn5fhRDEgql8Jscs2XE+NYenajabw055vZOyOgd2T+nKRKEJpocm6D7bRU9/L4OTw6TV4ioIr+agXvNRp/mo1jz5YNjiNwbFdZ6gbY8ZyXL5fstaPENsOMCp/uM8F3mZn4WfIyXrVcV2o537m+/nkfZHWF+x/m1pP5IZlR8dGuZre3oY8uuyfptJ4RdvbuQ/bW2hxn39Vwy+FWiaIJLKFltiFVhgFZIhxfZZGdS3wISYDLJuiWUrzgZxW40YzWGS0ggRbZCZdD9jiV5G40NoQsURFznFRY68GBNULEJeqI1NBDs6GGhu53h9E69W1tErLd7Ztiky7TYzywqsotptFlqs5rekBHsnQNNU+o4c4tjzT9F37HBetu+qqGTd3fez9q6d2NyeK/f+aZXE8WliB8dJ98/9w2WHEdumKuybqzBWXF8k5CyEECRPzRB6foDspK5IkR1GXHc2YL+lBskg0xmN8fChUwQ0E3LWj3vyr/hgw2aWDS2jr6sPo9HIY489RmPj+a1PhFCZnn6Z4eHv4A+8dsU+kyucoSZdQ3Xbr2JY89HL4uWvaYK/e+EcX3lFH/jevaKSL350A07LhQsZ1HCa2IFxYm+OoYb0+5NAkJYymEWxsjXmy2BbUUaq1UCkPEUkW1r9cD5yopQtwqVCkZQFtkvzyQanyYlFsTASHeHwxGHO+M/oSkvAbXbz/tb38+HlH6bFfWVUxNc8Mgk9myI0NC+/Ql8XoRFSk0mioxYioxaSM0YoGE8pFhVHbRJ7bQpjY4a0QyJlNoCnAXPFJhx1d2PwLdcDuK3eq24F9XYinonz3TPf5Rsnv5HPSNlat5XPb/o8Hd4OhpJp/lvXCE9P65XS1SYjf95ey8PvABsqgH1j+/jCwS9wxn8G0CuDf3PDb/Jw+8NFlmjJrpy91FTOXqrZhefhdkw1pSfqZmZmePrpp+np0ds7r9fLgw8+SEdHxxX+RG8jEkHofUW3pup+EaITxfsrVs5ZUzXetmig/cVAaILsVJz0UDQX2h3RQ7tLFIcpHvMccVHvwFTvKJlzkkpNEAwe5ZS/k93BFG8myzgtVpCSiscbbdIgN1v9bPdYub2yDZ9rzQ2rmiUgGY3Sf/ww/UcP0Xf0EPFQsGh/eUOTbiO1YRO1y1eiGG5UyZ8PibTKkaFAnrw4Mhgkmiou4DQqEmvq3Nzc7GNzs48NDR5e657miy920j+j91srnGZ+Y0cbH7u58aLV++nhYaJ79hDbvYfY/v2I5FxBt2Q0YtuyRSc3tm3D3HL+fkw8E+dc4Bynpk9xcuYkp6ZP0R/uL3lso7Mxr+BYVbaKVWWrsBsvXHAQfe01Jv7if5AeGADAdvPNVP/XP8PY2sDIyPfp6/8KmYxu7el0rKat7Q/w+bYipaOXLdvqnYQbhMZ1hHQizov/8k8EJ8YIjI2SjJbyv5iDLGTSNsGQO0rEniVqEdjMFTSZl2NPuUgligdMTpOdJkcNDZYq6uVyDCkJkciiJTJoiSy81UIvWUK2KshWY2kSpJAksRiKFSLmdz4ZkkyOMjr2OGOj/55nZwFcrvXU1n6Eqsr3YjAs3kgKVSXy/PNM//PXSJ09C+hqDM+jj1L2K7+Msa7uin+G6wmaEByNxHkpFyx+LFIcHuUzKtzp03M3dvic+IxXRlaaTav4Z9UcIwVqjlhxZ8AAWGVw24yUe/VJXKOcZTo9xUhyguHsFGGp+DNYhJE6zUedWkad5sOOTkbklRSlSAunGUm5cr81oQkyI1GS5/wkOwOkhyLFVUsSRFwpThu6Oal00msepscyhNdXziPtj/D+tvdfFRu8UCLDd/cN8M3X+piO6m2lx6LwwQ4b99eoGFIREuEQiUgYxWDE7vXh8JVh93hxeMtw+HyYrLZ3fLt1qRBCEE1lixQgpciQUAnFSHaWCJEyyOYJZPMYimVcX5rHkQx659iemCMvZu2jKkOluzLTZdUM1rXSVdPE0bpmTtQ1EHfYEUYZjDIoUn6SqcxoyKssCoO5a83Gazbf4lpCcHyMYy8+w8lXXsj3Y2TFwLJbb2fDzoeoXb7yiv5uMpNxYgcniB+eQIvOkb6mZhf2LdVY15Yjm679CmAhBKmuIKHn+8kM62EuksWAc0c9jvfU5j/DoYlD/OX+v+RMeIpQ5X9GNdbhUgQ/3LCctTYT3//+9+np6cFkMvHJT36SuhJ9hXTaz+jYjxgZ+R7J5EjuAqDcn6J2PIUzot+vVEVCVUCVJTRFRjWaUI1G/WEwoBoUNIOCqsi5YyVUGVRZoMmCrKQSl+dsBBTFRlXle6mr+xhO59pL/l5EU1k+/8OjvHBan+D67PY2/vC+5SgXSTQKVZA86ye6b5RUVzC/PaGkCEtRKrJe5ALv8qAS4YDjJG86TnLYfoa4cnH2TbOh1aVsl0plRhQeN7vParCe9+82Eh3h8c7H+Un3T5hKTOW331J9C48ue5S7Gu/CpFz/dqSLQlN1i7PwyDzCouB5fHrhy7ISsQkT0VEL0VEL2URxm2Gpd+O4qR3He7Zg2XAzkreBmBxncvp5JqeeIRo9mz9WkhS8ntv0zI2KnZhMl25tcb1iJjHDPx//Z3507kdkRRZZknmk/RF+Y/1vUGWv4qWZMP9f1zD9ubHr7R4Hf7msnuX2638CVxMaz/Y9y5eOfImRqN6+trnb+N1Nv8sdzlsJPd1H4rj+HZQdRtwPtmDbWFnyd53JZNi7dy979+5FVVUUReGOO+7gjjvuwHidZCNeFmgaTJyArud19cbwm1BYdW1yQOuOOfWG+8JjZCEEajCVt4xKD+VCu9ML7WxluyFHXDhzJIYDxbGwHVXVOOHwScLho4wGT/N6OM2hTBMn2MCUVGyr6JVi3GILscPrYGfNMmod1Rf9Z3k3QgiRV2H0HT3EWOfZIhWG0WKlae16WjZspnnDJlzlN6zWz4eZaIqDAwEO9Pk5MBDg1EhoblyWg9Ns4KYmL1uavXkCoxRJkVU1/uPICF96qYvhgD6HUe2y8Jt3tfORzQ2YluD2MB9aMkn8wAGiu3YT3b2bzPBw0X5jUyOObdtxbNuG7eYtyOYLq2oj6Qhn/WeLSI7h6PCC4yQkWtwteZJjddlqlvuWYzUsLH7U0mn83/gG0//3q4hUCgwGyj71Scp//dfRzILBoW8yOPgvqGoUa1xl+ZgVbyCJ/Lsn3xEqzcuJG4TGdYRUIsvpV0fpPzHNWE8ILZtAaCGEFkTOTGKM9yOpMyQNGTIX8MQ0GE3YquvAV05CMRNMptAK/sWyLNPQ0JAPF6+srISMhpbIosWzaIlsjuzIPZJz60Xbc4+l2NicFxJFahDFYULxmjF4LSheCwavGcVr0cmP63xCSQgVv/81RkZ/yPT0i4ict5+i2KmqfIjauo/icq7Lf06RyRD6+VPMfO1rpPv6AJBtNry/+DF8n/oUhvIb8silYCqd4eVc7sYuf5hwtkDNBGxy2bm7TLenWuM4/wTBxUKoAjWSQg3qj2wgSXIyQXIijhpKISeyKJqeVTEjRRiWZxhR/ExIIYQ099uShEQVHurMlbRUNFBXX4vRay0iLUrJ0q801GiaZFeQ5Dk/qa4A2jyyRvFZUNwmspPxBftmMWMI0mseps8yiqnWwdo1m7lt1VZMxoubaBGaRioeJ54jI2ZJidnnY4Eoz8/YeT1VQQr9b+XMhNkYOsaq6FmMJbw2F4PBbMbh9WH3+HB4fTh8PuzeMn3d69NJEK9OfNzA4hBCMBGfoDPQyVn/Wc7MnOOcv5Ph6CAix7TbE4KWidnAbmgbl6kMlv5fDdvL6fbU05V79HjqiBvPr7RRZAmH1YDPZqJs1voqH45eEKI+zz7LYb7+70lXCpl0is439nLs+acZ6z6X317R2Mz6nQ+xcusOTJYrp4ASqkbyrJ/YgQmS5/x5YlUyK9jWV2DfUo2x3nFN/v9S/SFCzw2Q7tOrliWTjOOOOpxb65Gters1GZ/kC4e+wFO9TwF6AO+vrP88P4qv5WgkgV2R+dbaFm62m/ne977HwMAAFouFT33qU1RX6xMl4fAJhoe/w8Tkz9ByqgFjFmrH4tSNJrEayuDmX9MnhewVYLDonuUGC8iGS6o0T6WmmJj4GSOj3ycen8v8cjhW0VD/CaqrH7koX+Ehf5xf/dZBzk1EMBlk/upDa/nAxvqLvq75yE4niL45RvzgRD7IVZMEg/Zx4mqC1mQ9lgL1horKlDvMVEWUUE0SvEasJhs2kw2bya4/zDYcZj1XwmF2ohgUkKXL/h3MaBl2D+3mx50/5vXR1/NqDJ/FxyPtj/Chjg9dclDxNQUhIBHIhWoPlyYtwqPFNjWLwWgnI9cQnXAS7c8S6wkiClS+ksWC/fbbcezYjmPbdoxV5w8Vjcf7mJh8msnJZ4hGz8ydR1Lwem4tIDfeXX73A+EB/uHwP/DCwAsAWBQLj616jF9Z8ysYFBv/NDTJlwYmSOZsqD7TUMnvNVW9I+wb02qaH5z9AV878TViySgP++/ksen3YdaMIIHjtlpc9zbl2/j56Ozs5JlnniEQCADQ1tbGgw8+SFnZu+s7VBJxf0698aJuURWbKt5fuWqO3Gi8FRQjaiyjKy4KCAwtttD/XzLJGOsceuZFToGheM0L2m0hNGLxHsKhY4TDRwmEjnMqnuaYWMdxNtDFcjRp7ntsQGWDLcWdPhf3VTez2mG/tHuBEJBNQioKqTBk4rqFndV78ee6TpCMRRk4fpS+owfpP3qIWDBQtL+svjGvwqhbseqGCmMRCCEYmInzZr+fgzkLqd7p2ILjql0WtrT42NKs518sq3JeVMFIOqvxo0NDfPnlbsZCeuFHncfK79zdzgdvqsd4idawQgjSff1E9+wmtmcPsQMHITP3G5YsFuy33opj+zYc27ZdVPFvKBXKZ3HM5nKMx8YXHKdICm2etnwex5ryNXR4O/KFIunhESb+8i+JvvwyoNtlVf3xH+PceS+ZqeMkn/0NHL0n86Uywft+F89t//2S/h7vVNwgNK4jpBNZvv4Hr6LlyAG3NY2n/zXKRw7iCg8wUib4960y+1dImISJ99g3ssWylmatktR0kODEGKGJcUJTEwitWG4hJAnV5iTrcKM63Gim4ooXq9lMS1MjK1avoWPZMqzWpU8yCCEQOTJEzBIiyWLCYyEJkpkjQxYzJi8ByaQUEB3zl9cf4ZFKTzM+9h+Mjv078XhffrvDvpya8g9h2ycT/Mb3yIzoFT2yy4Xvl34J72O/hMH7zu2oXGlkNMHBcCyfvXEmVlxVWWUycHeZrt7Y5nXiPM9ASgiBSKpkgynUYHKOtAjOERhqOLXQWzWHGElGFH+OxAiQorgzbdasWFJejEkvIu1GFnMDHbPdQHmdHj4+m83hq7FjuMLVx0IVpIfCJDsDJM8FyIxEi/ZLZgVLuwfzci+WZT4MHr06QgiBFkmTHo2RGYuSGY2RGYuRnSnhPQsk5RRhVwJLlR1buZ2sNUvamCYZj5KIhEiEFxIWiUh4QfsHEDC4OezZwFnH3ICiLD3DpuAR2mM9GBUJq9OlP1zugqUTNZsl5p8hGvATDfiJBf2kYgs7fIvBaLEWkRyzRIf+KMPu1VUfxndw3s0sktmknnURyAV15zIvCjNWrElB64SgdQxWTBppn5DwTpeufJ6srOZUYwvnGpo5V99CV3UjcYMVKSMgo2HIaHiRcQsJmwaGrEBLq6RTKuFccHr6PKHeF4JBlgoIDlNxHshiZIjNiPNdRoRM9HZz9PmnOfvabrJp3WvXZLWyatvdbNj5IGX1V3ZyVQ2liB2eIHZwAnVm7rtkrLZh21yNbWMliv3tH/CmR6KEn+8neS43ODdIOG6pwXlnQ776M6Nm+O6Z7/LVY18lno0jIfHoskf57Y2/jdfiJZpV+dSJPvYGo5gkiX9e3cRdLivf/va3GRkZweGw8P731xIKP0k4fCT/3s64RP1QmKqpFIqtCm7/HGz6ZTBdGUJWCEEweIDR0R8yOfV0nlCxWptoaf5tqqvfjySd/162v3eGX//eYfyxNBVOM197bBMbGy9v30hkVOLHp4ntHyM9eH7l9CVDQic2ZAlkXS0mKcyRHbIEyty6flzxayRZYlSe5GllF89IuwhIc2Gnm6V1vM9wL7cbtuiD7BKvRS4+d/G1SCWuhQu/dnZbwTmQcvsLPs/Ca8mdO5MoJilKERaZ+IX/vrIBnLXz8irqEI46EmMJooc7ib62n9TZc0UvM9bW4tixA8edO7DdfPOSKj1LIR7vY3LyWSYnnyESPVV4YXi9t1BZ+SCVFTsxmd49BUpHJ4/yhUNf4Mik3gZ5zV4+u/6zfHj5hxlNafzX7hGem9b7BTVmI/+9vY73Vbgv230zFkoxeGoGg0mhqtmFs0zvf4mMdsXzJP1nRxh//BSuiD7WPmXt4cjGQX5xx6dKEo3BYJBnn32Wszl1vtPp5P7772fVqlXvqn7EkqFpMH5Mt6bqegFGDqJpJjKijbS2jLS0irS0GjVdYv5JzoV2F+ReGCoXhnYDpNPThMLHCIeO6MvwcaZVAyfYwHE2cJJ1RKRiD/4ms8adPi93lXm53S5hz8YhnSMiUtHcekR/pKM5kiJSenvh60qRthUrofEWaLhVX3pbrlu7OyEEUwN9eRXGaOeZorGe0WyhMafCaNmwCVfF+QnndyuyqsbpsTAH+gMc7PdzoD/AdHRh/sXyKiebmr15AqPOc3kKPZMZlR+8OchXdvUwlcvdaCqz8bm7O3h4Q91Fq2rnQ43GiO97g+juPUT37CE7UWxLZ+5ox75NDxa33bQR6SJVbdOJaU7PnM6THCenTzKTnFlwnEE2sMy7rIjkqDwyxMxf/h8yIyMYbCrVd9lxOAeRcoWUkZomuhuNrNu5F0V5d9tdz8cNQuM6w+s/Pkf87H6cz30b15Q+iT3qhR9tlXlzlZGb62/lvqb7uLPhTjwWT8lzqNkskekpguOjBCbGCE2MERjPkR0T42QzaTSjmazDRdbuRrU7oTC0UwiskqDcYaehpprGlla81TV4qmsxX4EgXJFRi8mOeBY1kkYNJMkGUvmlFrmw57BkknOKDt1uZz7xIduN12Tnr3BgPzX8NJY9WRwvKigh/Vplr5OyX/403l/82Ls2H+NKYiSZ1skNf5g9/iiJgk6SWQh2mqzcY7CwWRioSGiooWLSIh9Gez7IEorHjHAZmDCGGMpOMhAZYyZaXFViNptpaWmhra2N9vZ2PB4P8VC6OJtjJEpgPI4okVEgSeCpshWRHGV1DhwlqokuBmo4RfJcQCcxuoKI5Dz/zBo7luU+LMu8mJqcJYN4hRCk4rECEiJMIhIi7g8SG58hNu0nPDNDPBJETadIqQmy4tK8xk1WK1anixlnPa8r7RzPeBE5z+tVHolfXO1kR0cZdrcbq9ON2X5xlVGZVJJYIEA0oBMds+uxHOmhb/OTTixhsiV/zbY5pYdnlvgoyyk/fDg8PuxeL0bztU98CCEYj43nw7lnCYyB8EBRGJs1JWgZF7RPyKydttI8puGeLE0WjZZV0tnUwrnGVjqbWulsaCZq19tDey7fosNmYVlBMHeT5fz5FkIIEhm1RDh6QTZIbj0Qz+SzRALxDOnspRMhiiwVhKSXIEPmkSSzWSJOswH5Os7rSEajnNr9EsdeeIrA2Jz1YsOqtazf+RDtW25FMVw5lZnQBKm+EPED48RPzsDs/1CRsK4uw76lGnObp+TkxZVEZjJO+IUBEidy1jcy2DdX47yrMU8IA7w++jr/e///zvv9rqtYx5/c8iesLltddL6kqvEbpwd4ejqEDPzdigYesIZ44YU/w+E8gsmkDyQlZKr8UD/gxxXJIjmq4Y7Pw6ZPwgVUTZcTmUyQ0bEfMTDwtbyvsM3WTmvL71BZ+UDJwMTvvznIn/3kJFlNsKbOxf/7xOYrnnmUHonqxMZQRL//5h5C6H1ZkdYQWe2tq5YvAhmy7HMe5xnPXo445myOvFkXO4O3sTP4Hmoz16LFhorCDIo0jSJNoUhTGKSpgufTKFKpAKQSZ5I8aFIVqlKBJleiKlVohkpUQzXCWIVmKAPFgCRLaKkYmYHjpLsPkeo+jIgXvIckY2xajmXlzZhX34yxtlnvy8g5AkeZI2iQcySNVEjqcEGSKJmeIBDaRyC0l1i8GyFpIKkICVzuNZRX7MBXsR2zuWwe0cPc+a7BccylQAjBy0Mv88VDX8y3aU2uJj530+e4p/EeXpgJ86ddIwwm9X7gNq9uQ9Vuu7Q+UCyUoufwFD2HJxntDhYV0lgsCh4JPELgNcqUuYyY7UZkq7HYNtk2L1vSVrx/fuBzIdRQiuDTfSSO5dQDNoWXO47yd6l/RpM0DJKBDy//MJ9Z9xnKrGWoqsobb7zB7t27yWQySJLErbfeyo4dOzBfIrn2boDIamTGZ0O7o6SHgmSnkiAW/m4M0hAm2xSmOjvG1Sswrd+CZFn4t1XVFJHQMcKBNwmFjxKOniaZmSCDgXOs5DgbOMEGBqXmotc5tBRbkz3siJ5kR+AwTbH+OTJisUq3twKTQ1dQlrDRw16pExuNt+kqlep1oLz9hRyLIRWPMXDiKH1HdBVGNOAv2u+ra6BlwyZaNm6mbsVqDO8my7UlIpbKcnQoyJt9fg4O6PkX8XkWaiZFZl29m03NXm5u9rGpyYvHdmVtKBNple/tH+D/7uphJqa3760Vdn73nmW8d23NZRnnCCFIdXbq1lR79pA4ckQnO3OQHQ5ddbltG/atd2CsvHgSbNZhYFbJcXrmNCdnThJKhRYca1bM3GJr4LGebrZEBpmdJkkb2jD84j8it96OqiZukBklcIPQuI4wcuYgQ5/8ZdxhfaJwwgNP3GEge+/t3Nt2P3c23Inb7D7/SS4AoWlEA36CE2MEx8cITozhHxtlfHqaQCJN2mJDMxf/kKRsGiUaxhAN4ZAEvqoqPFU1eKpr8FTV4K6qwVtdg9V1+SpnSl57RiMbTKIGdMueueVFEB5GucjCam759hMeaiRC4Hv/xsy3/hUtENS3eQTRe1Xit2tY3M3U1f4C1TUfwvwuquK6khBCIBLZIjVFKpBkcipGzJ/AGM7gTWosRQgp2wxFwdqzmRWy24Q/G6ZvfJCenh4GBgZQ1eLORF1dXZ7AqKurQ7mApRxANqMSGIsvyOZIRhfKpQHMNgNlOTVHy9py6ld6z/tdF1mN1ECY1KwKY7x4klmyGjC2OaDeiFYpk1Lj84iKOfVEokA9oalLIH9KQFFMWBQ7NtmBWbZhVmyYFWtu3YrV4cReXY6zvgJ7cwVHBPy/o8O81jNXOXHPyko+u72Nzc1Xz786nUwsIDnmljkCxO8nk1q697rZbs8pO3w4PF7svkKbqzIcXi92jw+D6er4oieyCV11kVNbzJIXkXRxNbMlJWiZgDXTVtZMJTbMLwAAbMBJREFUW6kdSeEeLz1hNVZWQWdjC+eaWulsbKGroYWww0m50UCHvZC40MmLGvPVb7uTGZVALvejMA+kFBlSSJgkM5dOhMgSc0RHARkyS46UIkM8NiMui/GaIkKEpjF48jhHn3+KnoP7837Hdq+PtXfdx7q778NZdmXvc1o8Q/zYFLED42RGC3IdPGbsm6uwba7C4Lmy5GE2kCT84iDxwxP63IYE1vUVuO5pwlg+1xcbjY7yNwf+hhcHXwR066DPb/o87297P3KJyX6ArCb4g7ODHB/fw708wxYOIqG3v6mUjcBYM/eNHaY8E9Wr17f+Hmx8DIxvH2GazcYYHv4OA4NfI5vVB4QOxwpaW36X8vJ7kCSJrKrxP586w7++3g/AQ+tq+NtH12O9hnJRtGRWJ//P+kme8y+wWjQ2OLEs82Lp8KCUWZEE8wiS3FIV+vdCE/n9s8uh+BBPTPycn089QyAbBHR/51scm3jY8yB32G/FgAKq0K3lhSh+D02ARoltYgFZM3ctpY4rcX2qhiRCyOokSnYCRUyiaJMoYgoZfangR5Iu3BZqwooqKlBFBVlRnl9XmX1eDpz/XqdFJ8iOHyc7fgJ1prPYa99gxVC1GkP1OpTK1cjXQyBnoTomT64wj1xZhAxZjHCRSihrFlEDFe2/DESPisqe0Vf5cfePCaZDqJJKm6+dT675FK2+FXxn3M83x6ZJCIEkS3yyvpxfa6rEbjTMfbbZ95uHWDBFz5FJug9NMtYTKppDrmx2osWzzEwmSk4tO2TwGSS8ioTXIOOUuWCOlmSSdRLENkdyYFb0bIaBsE52SmBZ4cNxRx0Gr4WeVB9fPPkl9o7uBcButPPx6o/DaZiZ1vuwjY2NPPTQQ1RVVZ3v7d91EJogO53IkRcRMsNR0mPRku4PikPCVCEwWsYwZQ9jCr2MHC5WZSEbEDYfCaedkB3C5iQhS4aoVSBkCQGMUZsnMM6wmpQ0d8+UhMa6SCd3Bt5kR+AAm8KnMJ7P8k6SweTUg4DNDp2QyK/nlmbn3Pbz7Tc5QM71B6JTMLQfhvbB4H4YPQLavPGh0Q71m+cIjvot+vneJgghmB7sp+/oIfqOHGS080zRmNFgNtO4Zk6F4a688VuYj6lIKq+8ODjg59RoGHVe8aPLYmBzjri4ucXH2jr3RYd0Xy7EUlm+9UY/X9vTSzCufz+XVzn5/L0d3Le6+rKO69RQiNhrr+nqjVdfRfUXE2SWVauw56yprOvWIS1hLqYUhBCMREfyNlWnp08zOnGMj0yP8ZFIFEtuyv1Ni5mvOdyEA2Y6onZu2vZhNm/9MA3OhkX79e9W3CA0riNkM2n23HUTxpTK8fcup/4XPsGOlrvfMomxVAghSETCDHV3ce7cOYZGR5mJxIqzwoVATsQwxEIYoiHkZJzZpsZkteKuqsFTVY2nulYnPXLEh9NXhiRf2R+nyGhkQ7OKjoXEhxZeKuExL7vDM6fykB2Xf9IsGwjg//a3CXz3e2gRfQLQ2NBA2a/+KvLdbYxOP87ExM9RVX3CRZIMlJffTV3tR/D57rigJcO7GSKrqymK7J/yz3V7KJFewoBalvDbZAZMMGqRGLfIjFsl/FaF2io7G+u93FntocmqV/XEYjF6e3vp6emhp6eHSKR4YtflcuUJjJaWFmyXSfkkhCAezqk5hufUHMHxONq8Do2v1s76uxtYfnM1ilHWXzvmJ3h8mPC5USIDkyRTUVJqgrQWJ6nGyZgypJUUaS1BIh65KPVBIYwWXT1hc5WyeHJhK3zuchGXUzzd/wxPdD/B9NQErcl6WpP1rM52sCrbhiNiQQJUBHvI8l1SnMu1XApwf7mTX11Xz6oV5Rir7ddkIHA6EddJD7+f2KzqI6g/LyRCZu16lgKLw1mU5WEvsrma3eZdsresEIKx2FiRVVRnoJPByGCR6gLAnBa0TypsCnhpnzRQPRTHPR5EKtHVGPeV09nYmicwuhqbcZeX58K4zXnSosNuwWu8+hkxlxvJjEooZ3c1S4iUCkefH6KeyFwaGQj6PJPbasypQGZVH8VkSHFuiL50WY1vWQJ+IURmpjn+0rOceOm5vA+yJMu0b76V9TsfpHHN+itOVqVHosQOjhM/MolI5v7OEpg7vNg3V2FdVXbeytuLhRpJE355kNib4/lqfsuqMtw7mzBWz4UBJrNJvnnqm3z9xNdJqSkUSeFjKz7Gb2z4DZymxSdes9kY4xM/ZXj428RiXfntYdrY2D3Ek6P34KcMnxzhl+9chvO2T+nZGNcIstlILjDx66iqbmnodK6lovZ3+bNnrOzt1qtPf//eZfzWXe1L+n7EVY3xVIbRVJrxVIaxVIbRVCa/bSyVIaUJ3uNx8P5KDw9WuDFfhn6r0ATp4QjJM36SZ/1kxoqLAxSPGcsKH5aVPiytHiTj4u+ZVtO8PPgyP+78MfvH9+e3V1greKT9ET7Y8UHqnW89P+SCSEVLWEENF2dZZJdA0stGhCtnBeWsA1c9wlkLjjqEI7c0OnXSRBSSJpyXhNHSGZKnjhM/+BqJQ6+THRsqeltDTSPWdbdgXnsL5tbVukr9QkSPyJE6mk4ylSR/Sl2fEDlSaZYQWuS1qqpP3mkqCAlJXP/3uquOHNGTFDCa1hhJafjnFRD4zDJ1DiP1LiNWQA2kUIUgbJSJN7kJqjAxGCbiX9jXUhSJMpcJn92Az6zgVSTM2ZzlcjL71gruZVBNMMIkR+hjCr3dM8kGtrfcwtrmlSizahBbsTrkct6b3nYIodvI5a2WInlFg0hGUIMJMlOQnjGQDthIR1wIdSGhKUlRTFKn/pA7McldKFKgxBtCxiARchoIu4yEnQZCTgPZgnY4jo1TrOWktp4TbGBCKZ5Ir8yG2ZHq4051lG3SNGUmUwniYT5hkSMhjNarYwOVSeikxuA+/TG0D5LzqsglBarXzhEcjbeB88qSBql4nMETehZG39FDRP3F9j3e2vq8CqN+xeqrVqh1PUAIQd90jIP9gXwGRv/MwnF5ncfK5px11OZmL8sqnddUgRNAJJnhG3v7+Ze9vURyDhCra1383r3LuGtF5WUfAwhNI3nyZN6aKnniRNF+xePBvnWrrt644/ZLt3mP++G1f0C8+TWknD3msLee71Y18R/qNIlsYsFLvrLxf7Ft3fsv7f3eobhBaFxnOHHkBRo7NuJ2XBsV+NlslsHBQbq6uujq7GR6pvhGoyAwJWII/ySGWAhpkeprxWjEXVldQHbMLV0VVVfUYmIWIqvlA5nnqzvUQBI1kr5gZ1QyynrlfQl1x8USHpnJSfzf/FcCP/whIq43cqa2Nso/82u4HnwQqeBvks3GmJx8ipHRHxIOH81vt5hrqan9MDXVH8RqvQqD2GsIQgjdnixHThSRFjk7KC164f8pgGw35hUVheoKg0e3LpPtRiRZIqaqvBaI8mIue2MkpVcTyJpGVdjPuugMzYEpJH+x1NdgMNDc3JwnMcrLy6/4BJ2azeZVETF/gKmhKWZGpvGPTDE9PI2aiYFIYJCSSFKSTCa2YFJ6KZAkGYvTWUBCuOZIiRJEhcXpxGi6tIkzIQSn/ad5ousJnu57Oq8AMKkWlqd+kd6JZYzn5lDMwPsw8VFMVBdqbCQwlFkx1tox1jgw1tox1TiQndemHV0hhBA68eH3F9lbFStAdDJEzZRW6pSC1enSyQ1fGXaPnudhcDvw2xOMyX6GshP0xQfoCnYTySz0kDdlBGsDLtb5PTSNQuVQBN/YDHKJbsWk16dbRjW20NvcRmr5CmqqK4usolptFmyXGBD3TkYyk8v9KCBDQoUKkHlkSCj3PJZ+a0SIyzJnjVVIhrgLFCDzyRCXxYDhIv+HajZD94F9HHv+aYZOzw0uvLX1bLj3AVZtvxuL/cpWD4qMSuLkDLED46R65wb7ss2AbXMVzq31KM5LH1Br8QyR3cNEXx9F5CbazO0eXDubMDfO9YWFEOwa2sVfHfgrRqK6/eiW6i388c1/TIe3Y9Hzx+N9DA1/h7Gxx/NEgCJbmRLr+SvxEYalRj4x+lP+8/jTfDv7XkIJlcrKSj75yU9it9sXPe/bhUwmyMDgvzA8/C1Gwg6+dOTXmIhXYjHCFz9yE/evqUEIQTirMpojKcZzRMVYjqSYfQSzF/c78BkVfqHax2O1ZbRdosVNKWSDSZJnc+qN7uCc7Rl6H9Pc7sGy0od1hQ/Fpd8r+0P9PN71OD/t/imBVI70Q+KOujv40LIPsa1+G8aLCFI/L9SMHqRdiqSYXU8Gl3YuR1U+r0LPr5hdb9CzLOyVcxXFbxHZQIDYnj1Edu0i9upetGhBtpfRiH3LZj0PY/t2TE1Nl+U9rxQSiWEmp55hcuIZwqGTSEIBISMJBbfzJip891Dm24HJWL44kbKY2qaIXJlT3iyqtplP9OQImqUqieYIIQoIoVklT/F7z75GVVXi6RiZbAZFyMjImDDqiqNFuqkJTTCa1hjNCPzzLN+8ikSdUaLWJGOdN5EnmWQcd9Th3FaPbJkbd8XDaSb6w0z0hZjoCzPRHyaTXNiG2D1mqltcVDa7qKy1U1ZuQckKsjMJom+Mkh7I9ZkMMqY6B5LNUJQrKRJZPYcSwVllhIOGHtKSTo6sUOvYnG3Dwvl/25JRLrDDmk96GOZss2zFVlmSWbm69opxP3Q+B+MnIDQ4lwmRz4OI6gRGbiyiCYeeeSE69KXWgcZChbVEEqPUg0nu0skLqRNFGi/mCYw2MDnQLHaiTgshh0zYmiFkSpBQiicVNWT6tVbOptdxXN7AadMK1ILiQRMatzgt7Kgs506fk5V2yzU/flgATYOpszD4xhzJERpceJy3RSc2mm7Tl2Xtb4mAEUIwMzSQV2GMnDtdrMIwmWlcs47mDZto2bAZT1X1Jb/XOw0ZVePUaDinwPBzaCDAdLS4WFeSdIXDHIGh519cLwjFM/zL3l6+sbcvP3bZ0ODh9+5dxtaOKzd3kp2eJrp3L9Hdu4ntfS1fYAyALGNdt04PFt++HfPKlRe+jkQQ3vgy7Pu/OXs5oPYmuPP/g/a7QZJQNZW+UB8nRw9zcM+/czp4jv4Kwc9XfYna99x1RT7n9YobhMYNXFYEg0G6u7vp7u6mt7eXdLq4IS33ePDZLNjUNNnADOHJMUKTE+e1mZEkGVdFRd66qqyhiYqmFiqbWzFZrl4jnCc8FrG1UsNLmBw3yCXsrOaID9lhJDs6yszXv07wx48jcn8/88qVlH/2szjvveeCSpZo9Bwjoz9kfPwneUsGAJutFZ/3dny+9+D13obBcB3I5heBUPWKxlR3kFRvkMxkfG4QNjt4WqpHtYRevWSQ9aC//EPRlyYFuSCsUn9NTkYv5bblllJuKRAEMxEORkc5FxkjHZlEUYstJfx2F5K3hg53LXe76qhTjCXOt/h7FG4DyGSSJBJRkskoyUSEZCJKIrdMxiN6UHY8tz0WIZ26NPWEQTZhsTmweT3YfJ4cMeHC6swt56koLHbHFVdflUJKTfFc30t89dWjnOltQGT0QY6kxFnfHuT377yJW2wryI7FyYxF80HkWqT0RL/sMGKssWOsdWCqsWOssWMot+nWCdcZhBCkYrGCfA8/Uf8MsWBg3jY/qpohalUJONMEXGn8zgwBV5qwLTv3eyiAJQ2rxp20T9lpnJKpG4tTM1GavJjy+OhsbKGvuY3EsuUYV6+ivrYmbxXVaDFhuMaqhN6JSGV1RUgofnFkSDSVvfDJzwOnxbBIHsjiZIjbasSgyEwPDXDshWc4vecl0gl9ssFgMrPyju2sv/dBqlrbL8ef5rzIziSIHZwgdmhiTuFpkHHcUo1ze31+snkp0FJZontHiewZzmcumRqduHY2Y2n3FB07EB7g/7z5f9g7otuPVNoq+cPNf8h9zfeVHEQJoTI9/QrDI9/F7381v91qaaQ+3UjtoVcxRGb4Vs37+S8dn0dIMg9XuPjv1W6++6/fJBqNUlNTwyc+8Qms1mtr4KsJwUwmy09P9PA3P+kilZGxWFK0bhxH9dYRMjQykVGKcq/OB5siU2s2UmM2Um02Ums2UZN7XmM2ogp4fjrED8b9jKXm7hW3exw8VlvGA5dJtZH/fGmVVE9QJzfO+PV+Zg5pKcP+xrN6NkZ6juCrtFXywY4P8oH2D1DrqL24NxQCYlOlSYrZ9cg4S6oEMbuLArbzhMXsc1ftFVX95P2xX9lFdPduEkeP6p8vB8Xnw7F9O44dO7Df/p7rNn8ukRjRyY3JZ4oKmkDC7d5EVeUDVFTej8X8zpv46wn28MVDX2TX8C4AbAYbn1rzKT687Jf45nCEfzs7RttQmhXDGWr8xferqkYnrat9tKz0YneaS6tthMBY40CxX5gMFJogMB5nvC+UIzrC+EeizO/6yLLE6gozTRkNJaeMtt9cjfv+ZmRb6fcZHhjiqaefYmxiXL92bwV3rXoPY6FBjg8dxZhWcKo2apUaWs1NWDLGPCHyllQhErrCY5E8kJJkSG7b+ZRkRYjNwNmfw+mfQt9u0Er3KzRhzoV2d+RJDFWUat80jLYgJlcYkzeBsSyLsUxBss7aMc0pIoTJTlKECSW7CEdOEAofIxo9haYtdGxIWNZxznQvR8UqDiQ8BOdNW7Qnhtkxs48dgTe5LXgMu5aEmvXQfi903At1m0G5zlVVoeE5cmPwDZg4xYIvmK2sWMFRvQ4M5y/ySCfiDJw8Rv+RQ/QdPURkZqpov7emNm8jVb9q7Q0VRg7RVJYjgwEO9Ac40OfnyFBggWWtySCzod6TJzBuavLitl7/WSL+WJp/3tPDt18fyKvTtzR7+fy9y3hP25Ut+hbZLImjR/PqjdS5Yls6Q0UF9m1bcWzbvrBvkQzD/q/C61+G2RyNqrVw55/A8gfOSwamuroI7HqJ6k9/9kp8rOsaNwiNG7hiyGazDA0N0d3dTVdXF5OTk0X7bTYbbW1ttLW2UuXzkA6FCE6MEhjX8ztCE2MEJ8YXt1CRJHw1dVS1tlPV2k5lSxuVzW1XJJh8KcjbFwVK21qp4dR5O5ZadIJU97NkB/ZBzk/T1LoKz4c/if3O7Rh9Vl3hscQJPlVNMTX1HKOjPyQQfJPisiUZl3MNXu+teL234nZvxmC49qovZyGE7oGa6g6S7AqS7A7AEqygribSZBmV/QzLfkbkGSJysZ2CWRgxmMoZ8lbyWn0VI87i7+mysMrtU1lun1ZZFUyjZhOktAQpNU5aS5BU46TVBEktrm/LrafVBCk1gcalVVmbZaueN5FbmhQrFllfmhUbJouDqLAwnTAS0CxgNLPyjlo23tuI03dthk8nMyo/eHOQr+7uZTys/x/sFhVb+Rsk7M8jybmAMXcrj7Q/wvva3ke5Ve8AqZE0mbFYEcmRnUqU/u0aZIzVNr0ie5bkkhcjoBYnpOYfs5Awm7dNLnXMYuc63zUUv19CS9Kd7NUf8V464910x3qIaaXJL0fSTOuEk6YJMw3TMk0TcRonp1BKTB5Ouz301DUyWl6O3+tF9XmosFtpMcrUO+w4PblsD18Zdq8Xm9ujZ8WUuvYbuCaQUbViO6z5xEciXaAEmSNJIm+VCDEb8uHoLrOMFA2QGh9AhKexqEksWoqaqjLW3byFtVs2Ue6247YaMV4hVY9QBclzfiK7hkgPzlbbSti3VOPc0YDBvfikrchoRPeNEdk1mM9RMFbbcd3XhGWFr+j7Hs/E+drxr/Ht098mo2UwyAY+tfpTfHrtp7EZF/Z7MpkAo6P/zvDI90gmR3JbJcq9W6kPOfHtfxIpkbPY8LbAtj/kJ9X38VvnhskKuNPn5K+qHfzgW98iHo9TX1/PY489dtXCZjOaYCKdKVBRpPMWUGM5G6iJZAatP4rhXAgJ0Dwm0ht8YF5oG+g1KIsSFTUWfZtTkZfUxmQ1wcv+MN8eneGlmXD+9uAzKny0uoz3VXqwKhIyUi4iQJq7NaD77Mu55dxtY/bY4mOk3DESAnU8TteJY/x06Emel/cQNuj2VLKQ2JJcy8OeB9mx+h7sy8qQzSUmz5LhHDGRs4NaoLIYBXUJtoWKqTRJMauscNWB5eqP3bRkkvj+/UR27SK6azfZsbGi/eaVK3Hs2I5zxw4sa9e+LcUWVxLJ5CiTk88wMfkM4fCRon1u9yYqKx+gsuJ+LJaat+kKrwwOjB/gCwe/wMmZkzhSXtaG38Pm2F1kxuZ+AwKYqDSyenMVD21txOm98v3XdDLL1GAkr+BI9gZZpgncuUKYQFbjeEIjblKobHJS1eKiusVNVYsLq9NEIpHgpZde4uDBgwCYzWbuvvtuNm/ejJz77obTYb5x4ht898x3SeV+uzubdvK5mz5Hg6MBkVLR4pk8waHFZ9Ufmbnn8Vk1yNw28RayvAAwyAsUH/l1JYUcPo08uR956hAyIWSiyFIEqaoF0XQnWUM76aiPTNBGesZIJiCV7Icbyq0Y6x2Y6p2YGpwYaxa3jc1kwoQjxwmHjhIOHyMUPkom419wnMHgweq6iT7TVo6oy3kj7uBcvLjYyanIbPM52eFzst3rpNFsgJFD0PUCdL+g2zcVwuKBtrt0cqP9HnBcfMDwNYdEEIYPzKk4hg8uvH8YrAtyOITZiX9kiN4jB+k/epDhM6fRCor+DEYTDavX0rJxs67CqH5ntVeXislwUicv+vUA79OjYea5ReOxGdnU6GVLi48tzV7W1LkxG649G+XLhalIiq/u7uE7+wZI59Sst7WW8fs7l121PMzM+Hie3Ii98UbeVQUAgwHbpk047rgFd+UoytnvIiVybU7FSrjzj2HF+y6bEvXdihuExvWGF/4rKGZ9oGB2FSzdOc/F3Daj7ep4Ll4EwuFwntzo7e0llSq+6dXW1tLR0ZEPPpZl3bc/FvDnA8oD46NMD/Yz2d+7wEdxFt4cyVHZ0kZVSxuVLW1X3IZiKSgiPIJJMjMJUqdOkjj+Junuw6jTfcz21pSKFZiWPYhSvrx4cG2QdJujfI5HcZ6H7DCVJDwymTDB4D78/tfxB/YSj/cV7ZckAy7nWrze23IExyYU5e2drFajab0ysStIqiuIGlp8kG2otGLwWZEdBmS7CdluQLEbdcm0LOkVUiInec8tRf55qW1z++Zvm32uaRoToSn6/SP0zwwzFp5EFPS2ZUmmzllJo7uWOkcFDhRSyRiJZJREMspgKkxvOsJ4KkIyFcOajGFNxrElYljSSw+ALvo7KEbMRjsWkx2z0YbFaMdktGMx2DCbbFgMdswGG2ajHbPBikmxIovZQYLI/50MFTYsrW7MbR4MVTaEgL6jUxx6doCp3ISdLEssu7mKjTub8NW+NTJM0zJkMgFMpoq3NGEdS2X53v4Bvranj+mo/n2pdln4zPZWPnZzIyaDxKGJQzzR9QQvDLxAUtX/zoqksLV+K4+0P1LSmkNLq2Qn4qRHozrZMRolMx5bUr7KtQiBYMI4Q595hF7LCH3mEfosw4wZpxHSwlu9LBS8mWoaZ7zUTBupnUzTOjJDy9hoSfIi6HAxUl2P31dJzGYnJQuM8WmkhL/oN3I+SEhYFDsWxYHV4MCq6A+LIffc4MRqcGA22PSB/XkJoXnPZwNO55NLFGyTFzvXUgio0gqrksdcgACbe91S3q/E+5c6P8V/i9lzyQ4jituM4jJd0RyZjKoVWGOVzgOZ3VdIhsz65l4qHGZDUTi6Ox+absRjNc0pQfL2Wfp20xL9x4UQpLqDhF8c1MNdAZRZYqO+KEBcqBqxgxNEXhrMV90byq247m3Eurai6D4uhOC5/uf4m4N/w2RcLwy5ve52/suW/0Kzu3nBdYQjJxke/g4TEz9D0/R20GDwUFf5MHVjKaz7vzPnjV3WDtv+ENY8mq8efXkmzH862UdCE2xx2fm7ajv/8Z1vk0wmaW5u5uMf/zhG4+Wv8JtKZ/j2yAz7QlE6Y0km09nztxaawHA6iGFEHzy6m11suLWWOpuZCiWBEnoJOfQsXjGFFz915dtobf08TseKy3rdw8k0/zY2w7+N+hlPL93K76KgpTEnDmCJvoIpNVcNqCo+UvbtpG3bMEkuatJT1CUnqUtNUpeepDY9SU16ktrkJNWpSVzZ6HneJPdWSMyYy5m0VjFpqWLKWsWUtZppSxVTtiqmrdVEzF4kSc6TLlBI0ugEzlwTM7d9lrSZ3S7BeYmd2e3zzyOjn0QGbDPT1B7YT82BfVQcPYyhYGyhmkzMbNzE9C23MXPzrWQqqwoIo8L3Lb6WXM3AAvLpoj8rszUIUr4Wofj8xZ/1rZxfnndMOjXO9NTzTE89SyRyFAkNCYGEwOPaSGXlg1RW3o/FcpEqnmsQ4ZkE3YcmObyvi9ToXHstENgbJCxr6/mKLUm3ovdX7va5+F/L6mi2XpicjWZVjkcSJDWNLW47ziVODqaTCQ4//SRHnv0ZSlZmnWcH9SbdDjBDmm6th/7EOImojBAmkMxIkhkkM0gmpIoMIcsoWaHfH9auWcvO+3bidJZW14/HxvnK0a/w0+6fIhAYJAMfXv5hPrPuM5RZy5Z0zYUQueyPPBkSzxaQIsUEiZi3/S2pQs4D2WXKERc5AqPOsaiqRdOyxGLnCIWPEQ4dIRQ+Rjzes+A4STLidKzE6VqP37KFI2obr0WMvBGMkiiYLZaA9U4bd+ZIjJtcdoznKzCMTkL3S9D1PPS8vNCGr2YDdOzMqTc26Tk91zuyKRg7VmBT9QbkiibSmsxgzENfrIy+eCWRVHG/ylNVkyMwNlG/eu0lWw+/UyCEoGcqlg/wPtDvZ9BfOv9iS7NOYNzc7KOtwnHN5V9cDUyEk3zllW6+/+YgmZxDx7ZlFfzevcvY0OC5atehpdMkDh4kuns30d17yAz14W2LUbYqisGi33+yeMms/BXM7/095GtgfvKdgBuExvUEIeC/e1lST0FSdILD4tJl3/MJkPy+WTJkdl8BKWJyXjHGUFXVvHqju7ub8fHxov1WqzWfJ9De3o6jhBQ8Fgww0dfNRG83k309TPT2LJApzsJTVUNlaztVLW1UtbRT2dqG1XH1LZeygQCxvXuJ7nmV2N69qIHiADL77dtwffAxjFXtBUqPXIZH6PwKDwAUaY7oKAwrnyeXTmXHCSYPEU4eJJQ+SEorrmKTMOKQV+OSN+JkIw6xEhnj4mGIhX64sz64Yr5HLov75s7bpsUzi1r/zMJQYcV+cw22jRUojqsjPw2FQnR3ddF57hz9g4MLSDmrQcGpSFgyKeRokFQuo+Ji8gpmIZBIWKwkLHYUhwOP20Otz0d9ma8of2LO8smF0XxlSSghBMNnAxx6doCRc3Pf3Zb15dx0fxPVLe4lnkcjEj3NzPQrzMzsJhw5hRBpFMWBw7Ech2MlDsdynI6V2O3LLqgeiiQzfPuNAf7l1V4CuSqqOo+VX9/Rxoc315esTommozzb/yw/6f4Jx6aO5bf7LD7e2/pePtD+Adq9i9vWCE2Q9SfJjEbRZsMez0OEIeYIo3yA6bzXLNx28URb/picH3ZCJOgTQ3SLfnqlQXoYpJdB4tLCoDEAM24s1FMZcFM9KdM2FqdjaIKW0WEM2kIVUMzuIlTdglbejMPbTJWjCbPZo7tRiZzVcZ4EVEllEySyYRKZKIlshEQ2SkKNklRj+fWUGrsI4kPGotjzpIclR3zkSRCDvs0sW2+oOy4CktWAwW3KERxmlPx6buk2I1mUq/o3zaoa4WRWJ0HOQ4bMhOOMT87gjySICwOpt0jO240KlRYTlQYDZYqCR5ZxCJnmBhcP3duCe16lrxCCVE+I8EsDpPsKiI1NVTi21ZMZihB6cQB1Jkeous247mnEdlPVAgu7rkAX//vN/82B8QMA1Dnq+M9b/jM7GnYU/e01LcXk5LMMD3+HUEFlttOxmvqqD1LVM4iy/1/mJO7ly2DbH8GaD5acSHkzGOWxE32Esiqr7Ba+UGnj6X/7Lul0mvb2dj760Y9iuEzZZn3xFP93aJIfjvtJzSs3NEoS1YVKCrORWrMRuwrf+XknZ4dDyBL8fw+t4ldub17wfYzHB+jr/xLj408yq1KtrHyQ1pbPYbdfXluyrCZ4yR/mO6MzHA3H0XJFAhr6xKqWb/rF7C0ArWB7KSjpYSyxXVhie5G12bBwiWoq2ZRx855kmvrUFHWpCSrSAeQltJsBg5NRcyUj5kpGLZUMm6uKno+ZKsjK1641iqRpLB/s5bYTR7j1xGGWDfUX7Z/wlrFvzUb2rd3IkeWrSb3LJ8YWgyRUZASSBIok5wgquZhIoZgwKSRmpIJjilVIheTNPEKmlGJp/vnnbyt4beF2UyiDpyeGuzuGdWKuLy6AQBUcqxjjTOU0MUuGKls56yo2MJSxcTwSRwMU4CaXjS1uOyZZLnEtEFU1vjc6QyCXr1NhMvDnbbV8sMq76L1PU1VOvPw8r//oeyRCIdpdG1nj2YpJsSCEoDdyjOOB3aS10oVLqtlCqqoJ1a6PUeVUAvP4CMZkBsVoxWy3Y3M5cZa5cHhdmO0OzDa7/rDbmVYD/MfQkxwIHCVt1DBaLXxi/S/z2KrHSir5LjeEJhBpVSdApsfQzr2G1ncYbXIUDTuacKLhQJjr0awNaEoZWkpGS2SKioQkqwFTnQNTgxNTToGhLKJ2FEKQSo0RCh8lHDpKKHyMSOQkWom/scXSgNu1Hpd7A5JtA0cy9ewJJnnFP5d7OIsqk4EdPhd3+pxs9TopM11iu6hmc+qN53X1xtix4v1WL7TdrZMbbXeDo+LS3ucaghAC//Agfa89S9/h/YwMTaIW3OgUSaPBFqTFEaClxop3xc1zNlXly665otwrjXRW4+RoKE9gHBoI4I8tzL9YUe1iS7OXzc26AqPGfW3ZgL7dGAkm+PLLXfzo4DDZXH/y7hWVfP7eZaypW9ocxWVBNgWHv4145a+QEvrcZDpqYPqkg9CAFYSEZDJhu+UWHNu24di+DVNj49W7vncYbhAa1xPUDLzyl5AK67LxBcuQHp51CcG9pSEVExylSI9S6pAi4sS1JM/ISCSSJzd6enpIJos7ITU1NXlyo6GhIS+1nY94OMRkbzcTfT1M5JbhqYmSx7orq3Ryo6Utr+iwuS5vYyc0jeTJk0T3vEr01T0kj58o8vCVHQ7st92GY/s27Fu3YqyqWvxcqoYaSi/M7pgNMg+lFh8VXwBp6xQJ7xnivjPEfWfJWoqJFkk1Yg22Y/OvxOZfiSXcgiQW/7+qQiWjpeY9kqQXbJt7FO4DqLa20u7ZQJmphtm6NckoY11Xgf3makyNzrc8mSaEIJNKkgiHSITDxCP6MhEOkYiEiYRCTAdDBBIpIgKyyrxKIDWLIRZGiYUxxMLImYW+q7MwGE06CVEYiu1cmDlhcrrokoy8mtR4MRDlZLR44rnCZOAun4u7y1xs9zpwG9+eiYeJvjCHnxug9+gciVi33MOm+5qpX7lwsJfNRpjx72VmZhczM7tJp0uTjwshYbU24nCswOFYiTNHeFgsdYQTKt94rY9vvtZHOFe93VRm4zd3tPOBm+qWbDHTG+zlJ90/4cmeJ5lJzim/1pav5ZH2R7i/5X5cpmv7PqQJjZHoCJ2BTjr9nXQGOjkXOMdQZKjk8bJkwGhuICvVUT5tp21M0DYaYfngMC2jgxhL5Bql3W7UFStxrFlD1YZ12NaswVBdfVl+h4WkjpZViYUCxAKBXLh5bhn06zkfuWU8EipqT88HWVGwu7zYXV5sTg92lwe704vdqS9tTg92pxuzxYGEVJKQKk0kkSdyFz9mKWqwhWTWfAIs/zrmnUtb6rkWP0aoAi2aRg2llqw8koxyjtww5UiPwnWd+JDtS7dJvNzQNJW+Iwc5/NzTnDtxkpRsIamYkb3VVKzdgqN5OYmUTDSYIhFKkYpkyMazSEkVJaVhzgjsQsKhSRhYZPIKga3FyX2PtFO3bGG7l+wJEnlpsChAfBayw4jzzgYcN9cs8BuPpCP809F/4vtnv48qVMyKmV9d+6t8avWnsBjmCJRkcoyRkX9jZPSHZDJ62yVJRiorH6Ch/GFcp15F2v81vZ8IusR9+x/CqkcuWBF6OprgI8d6mEpnabaa+EKZmZd+8G+oqkpdXR3r1q0jEomgaRput5uOjg58vqVL/I+G43x5cIKnpkL5afjNLhsfqfGxxmGj3mKkzGhAnvc3PT0a5tPfPshIMIHTYuDLv3gT25edfwIoFuuht+8fmJx8KrdFprrq/bS0/DY2W/OSr/mKIRlCBIcQ4RES/n5emNzP46GzHNXmgidrslk+GInygUiMqkVy5zSDBdVZS8ZaQ0orJ57wEo+4SFJJQionRQVZqwNjkwtjiwtjowssSr6Z0eaRLYXbBfPW88vi7aLgPLNL5p1/wbF54qf4/LPXIsVjlB8+SOWb+6g6sB9LcK6PKiSJmeUrGd5yC8Obb8Xf3JI/V/G1zBFLRedf8FlKfO6C1y7+WfXXLvys+msLz194DUXvu+C9Cq9l3vUXrL9b4ImqrBxKs2ooTW1g7jegSTBYYeB0vYlz9Sai1stbjFdtMiJJ5HNz3uNx8H+W1bPMXqC6E4KeQ2/y6ve+iX90mDJzHTdXP4hLzrWJ5QayNxlJ25IkYzFS8RjpeCy/Ho9GGE1k8GPQZy41DdP0KKaZCaS3+F9WJUHWCHaHC5+nCkuO/DDbHLmlDbPNgcWe227NLe06UWKyWJduzxYahtNPwumfwND+4n11m2H1I7Dy/eBtWvDSWVWIZJSLAtjnI5uNEo6cIBw6RjisExjp9OSC4xTFkScv3K4N2J1rOZO08Yo/wi5/hMORWFHcolmWuMVtz5MYK65UmHdkArpf1MmN7pfnCg0AkKB2o05udOzU168T9UYmmWTw1HH6jhyk7+ihBfMv7qpqWlatoKXKSIMyhHF0P0ycXDhvZfXlyI0cwVGz4YI5HNcbwskMhwcCHOwPcHDAz9Gh4IL8C7NBZkNDcf6Fy3L9519cDQzOxPmHl7p44shw3pbr/tXVfP7eZSyvvoIFzWoGjnwX9vwthIf1be4G2PaHaMs/QOzAIaJ79hDdvZvsaHExsamlJU9uWDdvRr6RFbNk3CA03mkQAtKxYrKjFAGSihRsCy08RruMsnmjfREipDQhohodDIdVukeDdA9NMDZRPPFpt9tZuXIlq1evpqmpaVFyYxaJSDhPcEz29zLR20VoYrzksc7/v707j5LjLA/9/62l92X2Gc0+0mhfbFmSLVu2bMs2xpgAzoVgLgkOS3LjsPgHDtyQcH9sh+BAwnLC4kCAwAXD9Q8CjrkIY+FYtpGMbcmSLFu7NNJo9qVnel+r6vdH9fR0zyLNyJrRyDyfc/p0d3V39dvb21XvU8/7VNdQt9iuyVGXD3R4y8pn9XLtLIxd9lx6U2RhuFaswH/jVnxbt+K96iqUizR1g2VYGJHSrI6xczM5xVQdmmIPNKn23CSKZh8GZWIQVzsZVQ8SUQ4TtU6SySUwMxpGRsXIaJgZJ2qqCjJlWBkvZkYlk02RySTJZJIYxsy+P7riwO8ox6dXEHCU49cr8DsqqHAtwqmOH4kTSvdyKnqAYUc/lYtb8lOJ2Z+Rv7KqsMFpmgapaJRkNEIiH5SYFKwoui0ViZArCkJYgOnyYPiC5PxlGB5/aZaSZaEm4+jxCF4zS8DtwhsI4s0HKSYGJ4qvO9wXdpRwbzrDk8NRnghFeCoUJVZ0iIumwNVBH7dV2QGOOdv4PodQb5x9vznDsef7MfNbDTUtAa66vYVFK0YJhZ5iaHgn4fBeLGv8e6hpXioqtlBdtY2KimtxuxtIJDqIxY4Qix0hGjtMLHZ0yp2UaMbHbztfzxOdW0jm7D/8xVUaH9i2jLuuWox+gXPlZ80su7p38ciJR3jq7FPk8u11aS5ua72Nu5bexTWLrkFVLu1cl/FsnOMjx+3gxcgxjoaOcnz0OPFsfMr7a3olWUcTWaWRppCPJb1ZlnWNsPzsaZZ0d+LMTe4fzLIynKvXUHbFWtxr1uBZuxa9vn5BZTkYuRyJ8KhdwDx/ihcXNc+fkpHJg8nT0RwOfOWV+Cvsky9/sq9X4a+sxFdeicvnW1DvxcViWRZW2sAIpzHCmfx5GiOSGV8WSWMmZjj9k6agBZxTBz7GzgNOlItY38KyLDIpg/homng4TWI0zVDXEGcPnWS4awjTdIHiQ1H9KMrMA8KaR0P1aJhujaQK0f4EVdnx74C3xs3Vt7WwfPMinPnBmLFpqEZ/eZLcQFFwWgHPlTWU3daKXj1+hJ1pmTx68lG+svcrhFL2PLu3tdzGR6/+KI3+xsI6R0ef42zXDxka2oGVr7nlctbR2PhOGipux7XnJ/D8tyGTn2KodjXc9D9h1VumzLw1DINoNEokEik59Y2GebFvAEcygS+TQj3PrsBYoGPNmjVTZtZalsXOUJSvdw6wa3R8+qPXVQX5QEstm8vO/bt67OU+PvLwfpJZg8XVPr7z55tor5l5yn4sdpRTp77C4NAOABRFo37RW2lr+yAeT+OM1zMr2ZRdq6JQr2Ji/YpuyEQ55nDwHwE/v/T7iOZ/D5plcVMiyduiMbakMmiB+qJ6FfmaFcW1LLxVk45sNZM5UsdG7MLiR0Olv10FnK1BPKsqca+sRK/1Lph+LdPZSWznTmI7dxJ/YQ8UZbqqfj++G27Af/NN+G+8EX0WgbTXGqskuFIa6LAmBJYmBkxS6UEGh3cyOLSTcPQgVn5iKlDw+ldRUXkjFRVbcbrq5ix4U5LJNGH9lgW5kTSZQ6NkXwlj9pX2oUqLD1YGsVaUYfm0KZ83konyfN8ejo0cxwJURWNl1SqCvlU8H80Sz29TN7sdXFPmx5f/7Y29lmvK/Ly1rgITi389O8hXTveRNC10Bf66uZYPt9UR6TjB0z/6d7oOv4xL9XJV3W20ulfZzfTolL2+Dd81i6YM7luWxeHDh3nssceIROzA88qVK7njjjsIBgNkEklS8SihnhH6Tg0w1DnMcE+I6HAEy0hhWWmw0oVzVcuiqhksM00uk+CiDN8oSiHo4fJ6C8EQt89HoLqW2mo/zcpJ3Cd+Bd17Sh/bfC2sfgusehOUN8/6qS3LIB4/Uci+iEQOEIsfZ+IRfIqi4fetJFh2JcHglZQF1+P1LqEvkysEMJ4JRQvZNmOWeV3cXBng5sog15X78c5Rra1pGTm7DsWJHXYGR9/B0ts9lXbNjbHsDd/spw+bK5ZlMdLbTce+vXTs30PXoYMYRfsTmq7TtHqdXdD7qo1U1DdO/n9JRSbX4chNyCDX3XYwbCzA0Xy1PXZ0GekLp+zaF/kMjCN9k+tfVHgdbGqrZFOrnYGxrrFsxlOeiqmdHIzxL08c59EDPfbBEQr80RUN/D+3LmNp7UWc7snIwUsPw1NfgNEz9rJAA2y9HzbcA3ppdpllWWROnrRrbzz1FIkXX4Si347i9doHPOcDHI5Fiy5eW1+DJKAhJrMsyKXyAY6ofeTAlAGRKQIh6ej45Yl/SBcoipeTylJOqO2cMBtIWeMRy4BLZXVrLWvXrKRp2RUonooZpSmmYjEGTo9ncQx0nGCkt2fK+/orq/IBjvHi4/6K8Z2n82Zh+Hz4tmzBd+NW/Fu3zmunZORyhLrPMjrQRyoaJRWLkoxFScdipPJHB6UTcdKJhH2kUCJOLj19rYrZcrg9+P2VlHtqCLqq8evleNUAbsuHM+dCz00/mGQ5IFGVpNs4zumug4z0dk95NLbT48ETCJJOJEjFYzM+YnuMqelYwQqssioybi/GhMFqj8tJQ20NrU1NtC9dSkV1DW5/AFWb/yNmMqbJ8+E4vx2O8MRwhOOJ0s+q0eXg1qogt1UFub7Cj28e2xgNpdi34xhnTjyJp+YA/vqDOHylxfa83iVUV22jquomyss3oarnnwoikxkiFjtKLHaEzsFT/J/9Xh4/tZqMYfcDTf5u/mjJb9hYdwBVscazOXwr8Qfsc4+nGWWWQYjh5DD/99T/5ZETj3Bi9ERheYOvgbcsfQtvWfqWwgDjXDEtk+5odyHbYix40RXrmvoBio7haCTraMFSG2kMeWjvSbG8q5flZzpo7+7EmZscbFSCQbxr1+Besxb3WjuA4WhsWDADW6+WkcsSHx3P+CgEPEKhfObHCLGREKloZMbr1B1OfJVjQY8q/OUVduCjsqoQCPFXVOL0LJwBwovJyhqF4IYRzpALpzEj9vlYAMSMZmZ2+LBCUf2OKaa3yp+rTo1MKpcPVGRIhNPERtMkRjPEI2nio2kS4QzxcJrcLOrbWGYSTc8SrPZT01pHoMqLr8yFr8yJr9yFN+jEV+ZCm5BFkc4ZfOeXRzn4VDcrUirOfBaHw62x6rp6Vi0rw9rTX8jOUBwqnrXV5MIpMqfy3zUVvOtrCWxr5pjaweef+zwvDb4EQFuwjb+75u/Y0rgFgFwuTl//f9LV9UPi8WOFdpSXb6ap6V3UeK5C/f034fnvwFhws24dmes/SrT+eiKxWEmwojiAEYudv7YC2B+nw+0ml8+ira6upr29ncHBQTo6OgqDZ4qi0N7ezrp161i5ciWaw8kvB0f5RudAIetQV+CP6yp4f3Mtq/znnjbBNC2+/uQJvrzDft03LK3mG+/cQNk086efTyRykFMdX2V4eGe+vQ4aGt5OW9v7cbtexTZaLgP7H7KPvh0LWMSnz0ZMKgq/8Xn5WcDPAff4/2Gj6uG/la/mroabqK1ZZQctAvUzyng+F8u0yHRGSB0JkTwcItdfOie3VunGs9IObriWlKHM42CKlcuRePFFYjufIrZzJ5lTp0pud7S2ELh5G/5tN+PdsAFFjl68qNLpAQYGH2Ng4NeMjr5AcecdCKyjrvYN1Nbeiccz+0Hp2QoPJjixd4CTLw4W6raBvXvXuKKC9g21LFlfgzc48+/A0dBRvrL3K+zq2QVAwBHgXWveS7/nVr7TEyZngVtV+FBLHR9oqcU9zcB2ZzLN/3uim98MRSiLhHj9nt/SeuwlFBSWlW/kiuqb0Qx729u7qY6yO9qmnRY3FAqxfft2TpywtzHLy8u58847Wb58+Xlfj5E1GezKFxzPFx2PDJbud1uWha4blDdojHo62ZvYyZB6BpMU7Z5WbqzeQoUSsPcD85ki6XiMdCJRuGxMccDLVBQs6j0R2nyjtC1tpu7aN6OueTMEZ1ejJZ0eKGRdhMP7iEZfxjAmH6zjctVTFlyfD2CsJxhYi6Z5SBkmvw/HCkGMo/HSGR+CusrWigDbKoPcVBmg2b3A+pFI73j2xsmdk7M3GjfmC4u/Lp+9Mb8D3tl0irOvHKRj/x469u0hPFCahRGsqSvUwmhZc8XsD+bLZaDvpdI6HImJNVMVqFtbmsVRNrf7Y7NhmhYnB2M8fzrE3tMjPH86RNfI5DGxlkovm9oquKatkk1tFbTX+F+T+wsLwbH+KF/97TG2H7QPaFYVuGt9I/fduoy26ldRB9Q04OWfw1P/CMP5sQJfrR3I2PgecMzs+29Eo8R3P0vs6aeIPf00xuBQye32wdD57I3161Eu0pSvrxUS0LjMfPaXh3DqKgG3TtCtE3A77Mse+3zsut+pX/qiQLnMNAGR6PkzSMbOM6U72QYqHTTxCis4xFLSjHcU5YRZo3awrixGXWU5SvnYUWvN40evBRth4rRBeelEPJ/BMVaT4wShaQbRy3wBFutuqsIxXKfOQDRacrtr+fLCNFIXMwvjXLKZDN2HT9J15Ch9J08w0nOa6HAXlnlhhVRVzYnudKM7vehODw6XB91ln6sOC0uNYyojGNYgLlXDp5ThVcrwmOV4zCq8Rj3OVAAle+5BddWro1d50Krc6FUe9Eo3jkU+HIt8JfOJZ5IJBs50MNBxsnAa6urEmqIosdvnL2RHjGdJ2FkULn+AaM5gcDRCd/8AA0OlfxoOh4O2trZCDZeqqqoFu4FxJpnmieEITwxH2TUaJVV0uIdTUdhS7ufWfPbGEu/czCOdSJxhePhJhoZ3Mjr6HKY5nvFiGjqJgZVkR69i8YrXs+6GqwtHLs9GbzjJt546xU+e7ySdsz/v1fUu3r0pwfrawyTiR4jFjpLOTD29nKb58PuWF6atsgMdy9H186edWpbFK8Ov8MiJR9h+ajvR7PhvfXP9Zu5aehe3NN/yqucmjmViHB89XjJd1PGR4yRyk4vAARhaBTlHM4azBVNtonHYwdLeGCvOnGbl2Q7au87gmKJ2ixoM4l6zGs+aNePBi6amBfsdn0+5TKYQ3IiP2gGPsYyPsSBIfCRkB05nSHe5CtkdvqKsj/EMkCr8FRU4PXM/t/V8swwTI5rNBz3SJQGQ4qwPDIucZZEyITV2blqkrPz52HKLkukhzsfp0QtBCV+ZC1+5E2/QZQcpypwkwr0cf24Hx3bvLGTqOT1e1tx0K1fefidVjTMbuOsZTfLAo6/QvW+Iq9I6bais8mgsygdALFXBf209wW3NaAF78CTdGSH6RCepoyNEtBg/qHmUX1fswsLCq3u598p7+bNVf4ZDc5BIdNDV9SN6en+GYdjfPVX1sGjRXdTUvB0j4iDy3ENEju8iajiJ4CfiaiDibiKStiZN4TkdTdMIBAIEg8HC+dgJr5f/1TXKcxkLt0Pn0wGFjkd/jmVZbNq0iTvuuINUKsXLL7/MwYMH6e7uBiCrahxvXMwrrSsYzm97eTWVd9VX8ZfNNTTNYDCpN5zkb/6/A+w+aQ9qvHtLG//rjasuOBOvWDj8IidPfYWRkd0AqKqTxsY/o631r3A4qgjnDLrTWbpTGbrTWZKGybXlPtYHvKVTYRlZ2P9jePqf7OyLiRzeokyKRo56/Pw03cuvwoeJGfbnoys621q28bZlb+PahmvnJRMwF0qROmoHN9InR0t+YIpTxbWsohDgGPvuXtTnH6sr9+ROYr/7HWakKKis63g3bsR/8834b74J1+LFF/35xdTS6QEGBx+nf2B7Prgxvp0dCKyltvZO6mrfgMdz8eb8Hu1PcOLFAU6+OMDQ2fH/WEVVaFxefkFBjKns7tnNV/Z+hSOhIwDUeev4k9X38nh6HbvC9qBjm8fJPyxr4taqqccfktEIDz/0vxl4ageaaVDpamB9013UmPY2paPBR/lbluJqnfrx2WyWXbt28cwzz2AYBpqmcf3113PDDTfgfBWBumQ0Uwhu9HeE6T8dJTNFhn7cGabff5oB/xlaltbwvlv+lCXVbVOuM5fJkE7EScVjpOP5abLOvEj6xZ+SGu5mNOOhJxkklCndhnH7A7SsW0/blVfRduUGApXVk9ZtGEmi0VcIR/YRCR8gHNlPOt076X6a5iUQWFcIYJQF1+Ny2VM0W5bF8USaJ0MRdoaiPDsaK9kXUoCrgl5urrSDGFcFvOiXenxkpowsnH0+n72xw56eqZi3Gpbeak9N1X4LeOcmU83OwrCnkTp76GBJXUhN12lctZbF6zey+KpNVDZc5P0Jy7IHijufhTPP2ucjHZPvV95iBzYKdThWzFuwJ50zeLk7bBfv7gix58wI4WTp/peqwKr6IFfngxdXt1VSF5zbupdisld6wnxlx3F+e9geL9BUhbdtaOJDty6lqWIW+2GmCYf/E3b+Iwza/yV4KuGGD8PVfwnOC9+ns0yT9JEjhcLiyQMHSsYimx78JoFt2y54/a9FEtC4jJimRfsnts/oAHRFAb9TnzLYEXRPuO5xTAqQBNwOfM75Lfg5JdMoDYCkRiE2AJFuciNdnOwZ4eVhlSOpKrKMBw2qCLGWo6zlKDUUT/mk2Ee55Xcq7fOW8YBHWZNdnCv/ujPJhB3kOHGckeefw9p/AH93H2WJVMmM2llVYaQySGLFYnLXrMOxcjGuukpMj04sGyOWjRHNRIllYoXrsUyMaHZ8WSqXotZbS3OgmZZAC82BZpqDzTQHmqn31WNmIBZKEx1JERmM0neqg9DZDsKDnSQjXeTSg8BU8yo7UbRKFNUDihtF8aAoLlBchXMUJ4rizp+PXR8PRCiARwWfquRP4NPsy14V9PN8T5KmRdy0iBvY5/lTwgRTU1E1BVVX0PKXXT4HZdUeGldU0LK6krLayQV9k7kke7te4PDpfQyGerCcGrrPg+5z49Bd6KqOQ3WgKRokINWfItmXJD4Qx8yVBkECVQFqm2tZ1LKIuqY6XLoLh+bAoThwaI7CuorPL/W0QxMlDZPdozGeGI7w2+EInanSeh5LPC5urQpwa1WQa8v80x59dj6mmWZk9IV8LYydJBKlG5ZudyNVVTdTHriRnldaOPDbARJhuy0un84VNzdxxbZm3P7zB/nOhhI8+NRJfrani0x+WoANLeV86NZl3Ly8ZtJ3IpMJEctPVTU2dVUsfhzLmrq2idvdTMC/cjzQ4V+Bx9MybTZHKpfiic4neOTEIzzX+1yhcLWqqCwpW8LqqtWsrlrNmqo1rKhcgUeffNSxaZl0RbvGsy5C9nl3rHvK57RwkHM0knO2YDiaMbUmGkI6y7v6WXf2NGvPdtDYeRo9MzmzSg0EcK9ejXvtmkIAw9HcfOn79ctcNpMuqe9RGvQYJjYyQnwkRDox9RRgU3G4PSXTXPkrq/CVV4wHQyor8ZdXXvDUdZdKNmOQCNsZFYUMivxUUPFwmvionWmRSU1dE2AqOuBW7aNp3cqEc4dqBy8qXbgq3EXZHtPX9UjGohx66gn2P/4rRvvGB1Oa11zB+tvvpH3TtWgzOBrq+T3dnP3lCTanx6YssTibsTiaMtAr3ay9sZHV1zcU+j7DNHj4+Yf4xpEHiSj2AN628NV8oPovaNu2hv7cM/R0/4h44oXCcxhGNZHIBvp6lxAeTZOd4dGzDoejJEBRfAoEApSVleHxeM45hWfcMHjfwdPsHIniVBT+p9diaPsjAFRVVdHe3k5ZWRnBYJCIafHDgTC/wU1St1+vO5Nmw0And1f6uG7dWppn0Bf9+mAvH//5QcLJLB6Hxmfesoa3b7o4R4gnDZOedIaeVJb+0O9x9H8Tf9rOjsng4gnlTh6x3kJMmRz4bnE7+dP6Kt5RF6Tu6C/saQZGTts3+hfB5v9h1ysp2q5M5JI8dvoxfnbsZxwcGp9WpMnfxFuXv5W7lt5FtWfyoN98MdMG6ROjdvbGkZCdYVXE0eQvBDccDf4Lqo1jWRaZEyeI7txJbOdTJPftswcG8rSKCvsoxJtvwnf99Wiy/3fJpTNDDA78hoGB7YyMPk9pcGMNtTV3Ulv7BrzeyTURzme0387EOPHiAMNdpUGMphXjQQzPRQ6mmZbJr079iq/t+xq9cbvPX1Gxgmvb/5IfjTbRl7EHI++oDvK5ZU2FwGs2k2bfr3/J84/8lHQijlP1sK7tLSy17Nce1eH4tTXcfscy3PrUB3OdOHGCX/3qV4zkpyNesmQJd955J9XVF/+3b5kWI/2JkiDHcHfcrrtV/H5gYlUkWb6ymZaltdQtDlK5yDf5Nz5wGH77aTj2mH3d4YNr/hI2/xWRjM7pAy9y+sCLdB48MGn7p6qpmdaNrVS1O9ADw8RiLxOLHylMmThOwedblg9e5Gtf+JaW7JOOZnM8MxJjZz6IMbGY9yKnIz+NVIAbKwNUXqJagxddpMfO3jj+uJ29kSk6mFJR89kbt9tTVNWvv+AB/WwmTdcrB+nYv5eOfXsY7S8NMgWqa1hy1Sba1m+iZe0VON3zXJg62pfP3shncPS9NLkOh7u8NIOj4apJ0/5cqHAyy4ud+eDF6RH2d42SmTCu4HaoXNVcUSjgvaG1Ar/rNfI9fA04cHaUr/z2GDuP2hm0Dk3h7qub+eC2ZSwqO8d+lmXB0e12TeOxAKO7DLbcB5v/yp5C/yIrTGX/1FMkXniB9l9vR/W+9g6CezXmNKDxzW9+k3/6p3+it7eXNWvW8NWvfpWtW7de1Ib9IckaJt948gSRZI5IKks0lSWayuVP45czxuQj1i+EqlAS4BgLekwMiATcDoKe0vuMXfY45icokslkOH74ZV4+sI9jp7swijbW6pwJ1modrE3vpcKcmLZoM4CQphJVVWJOHzF/DQmlDLpUXKfSBI+FccZKN5h6ax0cXKyxt83klSaTzKvY3lYsBW8miD9TgT9dQSBtn/szFfhTAfwJCz0Twcr1Yxr9WMYwU1YAV9w43IvwljUSrG2lunkJNS0NeAJuVE3BNCxM08TIWpiGaV83LAzDxMyYqPEMSiKHlsiip3LoSQM9k8ORMacpiWqzgJQCKUUhYUHcNIgZWaI5g3jOIGdqWKYGXNjGVaDKTeOqMnKNYU54D/B86Pe8NPQSuWmyTxyGg5pUDXXJOuqSdfhypemEKS1Fv6effk8/A54B0trsp9nSFA1d1acMdpzvfLrbSi5rDnRFLz1X9SmXTVq/otOdNnkunGZXOMneSIYMKigaoOHRdG6s9HNrZZBbqoLnPUo2lepleHgnQ8M7GRnZjWGMZw0oik5Z2Uaqq7dRVXUzPu/Skt+8kTU58vte9j3eSTifDq87Vdbc0Mj61zXjr5i84XB6KM43njzBL/Z1k8v/ljcvruS+W5expX12GTOmmSWRPE0sejgf4Mhnc6SnrqOjaV58vhX4/SsI+Fflgx0rJmVz9MR6+M+T/8mjJx6dcgooVVFpC7bR4GvA6/CSNbMMJgY5MXqSlDH1dHyGVlnIusg5mjH1JhqGLTb3nOWq7jMsOX2SqtOn0KY44lr1+XCvWWOf8gEMR0vLzAs5iosum0rZBcxDIft8rK5HaNi+PGoHQzLJmU/P6PR47SBH5Vh2h13Tw74+lglSgcM5NxlZY3JZoyg4YU/zlMgHKOLh8Smh0jOttQHoLs3OqChz5bMqxqd88np13KqCy7RQk7mimh7jmR4zruuhKuPTWRUVMVeDDnr6j/PKnv/i1Et7sPI7yL6KSq649fWsu/X1Ux5lmhtJEXmik8Te/sIsLTvVHA9lU9RmVDaaTrSsfYPmUGnfWAXLR/jRme/SH+rHa3ipVxexKrkUPZnCW3+QqoZDuD32AJ9lQSjUSG/PCkZGGmDCv7GHJEHdIFjbTHDRYgJTBCzc7otTXyltmnzwUCe/HBxFBT4S0ODJx4jH7cGrqMvDgaalHKlvJZefHqksleDq/jO0d59CKTqyMxAIsGbNGjZs2EBtbW3J88TTOT77y0M8vMfOdriiqYyv3r2eJTOsl5EzLfozWXqKsiu6Uxl60hm6U1m60xlC2QkDaZbFOg7wNv4PSzkOQBIPO9U3c8T7Nqo95QD8biRGIpflLQP/xUfP/ID2pN1Gy1eDcsNHYNN7wTE+wHN4+DA/O/YzftXxq0KdI13RuaXlFt62/G1srt+84A6QsEyLbE+sENzIdpVmpakB5/jUVMvKUZ3TZ+Ka6TSJ518o1MPIdpcG710rVhSyMDxXXIFyCabzFDOTzgwxOPi4HdwYeY6S4IZ/DbW1b8gHN9qmXcdIXzw/ndQAw93jg96KqtC0soKlG2pZvL4azzTTNF1MaSPNjw//mH976d8K2bfXLLqWYN27+OlokJxlD47/auMyKrMpHv70xxnu6kRB4YrWW1jh3oSSj/s91+bhf7WpjLhU2j0uHljexI2V49uN4XCY3/zmNxw6dAgAv9/PHXfcwZo1a+b1IJNsxmDwTJS+jjAnj/XQfXIYR3Ly4JjDrVHXFrRPdTnqzn4b7+Hv2QPHigYb3w03/S0E6iY91jQMzh59gTNHtzMSegHL0Y23JonmmrzfqmuVlFdsHJ8+KrAOXS/t5w3LYn8kkZ9GKsKLkUTJHrBLVbi2zF8IYlyKeoLzzsjaRdePPw7HfwsDr5Te7quxAxtLb5tR9sZIXw8d+/Zyev8ezr5ysKS+pKrpNK1ana+FsYnKxgV2YFQ6atfeGAtwdL0A2QnZ7ZoLGjfksziug+ZrIP+ffj49o8l8/YsRXjgd4mh/dNLBxVU+J5vaKtjUamdgrG0swzHf9VjErO09E+LLO46x64Q9PujUVf50cwt/fXM7tYGi8QnLsrOknvwH6N1vL3MF4dr3w3Xvn7eaLpZlLazf3gIxZwGNhx9+mHe9611885vf5Prrr+db3/oW3/nOdzh06BAtLedPUZWAxoVLZY1CkCNSFOyIJLMTlo9dLg2MRFK5koDAq6GrCv6SIEhppsjErJCx+4xnjThw6er0P96Seh92FkcmOkhPxxH6Oo4SGerGZaVwk8ZFmnKXQoXLwK8kUXQHL7o9PKbn2KEkGcFkSS+sP2Vx1UmTpT2lw+8JJxxcrLBvicL+JQqh4NRtclk6jpyKnrZwZBUcORVP2k0wXYkvU0HArKbMUY9frcVllaOkvRhxBcsEy8piGYOYuX4sY6AoeDH58zA0nbjHScRvkazV0VqC1LQtoqm8KMMj0IzfOb5haKZy5IZT5IaT5EIpckNJjJB93YicZ75zXUGvHJ8WSq/2FK5rFa5pi7qaZoZI5CVGRn5PKPQcoyMvYRg5yAc5LFPHoS8iENhAwLsen28dVraCgbNhjrzUReRMFszx99rEoD9whq6yIyTqB2ldUktzWTPmqEmqP0VmIIM5apa8FkuxMMoM0uVpkuVJUu4UWStLzsyRNbNkzfHLxefFt7+WWKig6FhooOhoqo5Hc+LXHfh1F05Vo1FP06pHaFZHqVBLj7RK42ZYbSCsNRPTm1A133hARdHywZnSwI2m6ITOxDn70ijxoQyqqaMrGq2ratiweQlLGpt4vi/JQ7t7eebISKFY2tVtAd53Qz1XtwRxKBP+yEv+lqxplpfeNjZImc2NkkyeIpE4STJ5kkTyJMlEB5hZFAsUy0K1sC+bFi69Fo+rEY+zEY+zAbejHqdWjmIahLDYlephT+gQx8On6E0Nk7JMrCkzpsBSHOQcTXbwwtFCztmCojWwMRznmu4OVnaeouH0KQKnTqNMEbxQPG4cy5fgWNGOY8USnCuWoDUuKgpeTPdeTHhfpvtbn+b9s2a1vpl9HlM9ZizzpXT1F76+qa9aRc9zjo7vQl7vhNus4l3vSU9lkU1nSEQTJCIxktEEiWiCZDROIhq3l0fjJKMJctmZBwecbieegBev34s34M1f9tjnY5f9XjRdK2mUkbNIxVWSCZVkXCUVV0jmr6fi9rJkXCWTnvmOmqZbeHwGHq+B22fi8Rp4fAZuj33u8Zl4vDkcjuL3yWL8mzDN5zvhc7NyBmbKwExmsVI5zFQufz1nL0vmIGMUPc6Cyc8AQIYUI5lehpM9ZM0MYKGgUlHdwKK2pVS1NaKYLozj9RhnasC03w+jdohUaxd9Vortpz2cGFHxKVlqMShXchhksbTJ/yc+/zANDUepqTmNptn9RjbrJNTXTqJ/GT5XJWU+jaARItj3LAFrlCBRgvXLcFz/QWi7obR+2Ll+I6/ydsOy+PzJHn4+YB9h/Cc1ZYTDEZ4z3BzV/Fj5dlQkwqwdOMniUA8O00A1TdSciWIo+f/08fY6Najyu2isqWDUUck3jnrpTSgowP+4uoK/ubEOZ34KSsuyj9AdyGTpT+foy2QYSGcZyGTpS9vLh7PZkunJlAmvb+y6W1Wpc+r5k4Nap4M6p0alcYBc5KekM3YGoq76aK1+K02Vb8Q8tZvM8/+GP9IJQFj38+O6N/Bs0+3ctqiOZV43aSPF80PP8fTA05yJnyk8b62rlhtqb2BL9XUEHcHif6YJb7lZ+q5bE7uv4kdO/XkVfj3W5NePZU1YUvwfWXodwEznyA0lyQ4nyYXSYBT9t6kKWrkLvcreLlTdGkoogvvAIdz7DuE6eAw1PT44Zjl0UquXkrpqNan1qzCqKxj/HeZrsFil78fE1k5qYVGWh8X467WmunfR6xtbqkx8Pya+vxPfrYnvtzVhfef8P2DS51X67KWfxcTXYrd1fJlSdN+pnnvy7nvp/9553tnJ35X8NpRlZklnh8ikB8jmRoue357m0+WsxuGsQdc8ZCNOUj0BUt1BcpGiQSLFwlkTw90QwVUfRXUaKJM+7Yl9/vT/6yWffdH7MdX3p3idCTPF71Iv80LqCEb+t7fasZgWaxW65cZtWVQ+d4LMYISGshaua7gTPVUGgCOYonx9L87KJI8YVXwq08IAdjDmLdoQn9Q6ONMZZueJOBnDQlFgc4uHm5f6cOvqlO/3tC9wjm4/PjjA7hP9hMNVqMl2lORisCYfFBHQ+qmrilO3cQOL1rVT3exHd2gYRppY7FChcHc4coBUavLUe5apkxr2Eu3RiQ94SAx4yMZ0AlW1tF5hT03Vum49br+fnlSGnaEoT4aiPDMSZXSKYt7bKoPcXBng2nko5l34HVnF247Fv698n1X4XVnj77VVvF1b3LdZRestfUzJ79aySq5PaosFRHuxOp6BjmfsQf1sYvx5FBVr0RXQegO0XY+Vn44p3NfLqf17OL1/76Q6ooGqGhav30jbVRtpXXvl5TUtqpHN1+H4/Xgtjkm1rBSoXT2ewdFyLZQ3Y5oWxwdiJQW8u0cnH3TUWuVlU2sl1yy2MzCWVPtkoPky9vtTw3z58WM8f9qu/el2qNxzXRt/tXUxVQPP2oGMrny2tMNnZ2Ns+dCcTfMmZmfOAhqbN29mw4YNPPjgg4Vlq1at4q677uKBBx6YdP90Ok26qBhxJBKhublZAhqXgGVZJAtBETsbZDwYUhQgmSIQMp4pkuUixURwamo+KKKz2DHKF40vUONI56egCsMFDDabwF2N9XQ4x6e9+dCjBltfKW30UDX0tkKo1SBdk8NHFr9p4jdNAqaJ37Ts65aZX25hH1um8ETkPgaMFcSyZWTMc28I5FL7MNIvYZkhptq9cOrgDeSwylJEyzL0BDOc8WTp1Ezi5/n/rDThnUN3cuPoTQSMc6fCJdUkQ45BBh1DDDoGGXIOMuAYZMgxxKg+iqlM/aFON6w3zS7a+K5YfmNsqrWOaBopRUE3nDREltI8upK20ZUEUqVHA6X9J0j5O8lQmspZrYRp13pp13pp0/pxKkWDgbMeYLWzeHKWRVaBHApZxSKnQBaFHJAFckr+skL+fvbyksegjN9WWG5fL6xPGV/f+H2VyecT7jf+2Py5opCb5QaWQ7H4VH0Sf9FBkqYFZzIqh1Iah5Ia3dnSwahXK1r5F2RHrkA/lCis1ahxkVsSxCqfcJSelQPLsN91y0CxcoCBYhn2bdjL7ul7gj8Z3I2GicMy0C0Dh2mgYaKbBg7LQLOMwm26ZaBPlfV0DicdOp+sruK400FymkyIKgOacyqtOYUWA1qyCvW5HLqVRbGyKAMG7HFASIXcFOvQLajMoVRmUapyKFU5CBpM9bFOXDR5EO/c95+0vgk/k/M9/nzPP2n9F/n5zrv+870f5/nPmv3rP/fzT1r/DF6/AmCBglK4//iyqR837fPl23M8tZX9iT8mYVSQsspm+GjQyODVRvCpIbzqCF4thE8N4dPs6778daeSQFEuND9v4elOBHmsZx3bGj6MU/WQJsujjt2k1SQpZYb1siwF1XChmU6WLH+a2pbxKYhcUajvydI8GMU5RY2ohebjSz/M9xv/uHD9xpE9fLDzx2wd3TvtdzGDzlGWcJBVnKAVM7/llLUUfp5eRxIX9QzzFec3uFY9Mg+vYjILGKx2cqrVS9xnb18sPh1nSef0GVVpBf6xsoLtfh+J/H+CblncFk/wtmiMq1Pp18zvYCrRLjdDh/ykQqX/27rHwN+Qwt+QwleXQdUv0g6CWNAsS+FnoS8wkF1WWKaSo8l5gKXu3Sx2P49bnXlNqrnWpWt8raKc7X47q9tpWvxpJMqaw1W8PNKAS83x31rfiMl6FOIE9R/h136Fooz30xHNxxfb3sv3Gv+Y6miYt778JFa+lmATPfwRT7CIoSmff6EwLZVQroW+7HL6s8vpzy5jJNfMxK0LVTdpf/0/o/tPY1mT98W93nbKgnbR7rKy9fh8y1EUneGuzsL0VN2HXynJBlAUlZ/e9T466lpL1uVOp1jcd5r23tMs6TlFWSI6y+DC2E2lB7NMCi4UVmdNsa/42qVqGo0r19i1MNZvpKq59bUzQG9ZEDqVD27ka3GETk6624f5KP/FNURSpQcPaarC6qL6F5vaKkqP3hevCZZlsevEMF/acZR9naOsUDr5evmPWZa0pyJF98DV74MbPgK+Szc9qJhspgGNWU36lslk2Lt3Lx//+MdLlt9+++3s3r17ysc88MADfOYzn5nN04g5oigKXqeO16lTd4GxJMuySGSMoqDHeFZIcabIxOmyIkXBklg6h2VBxjAJxTOE4hniJKhxH56q1XbqlzuYPy8rumyfpxUXPaE4p3tD9ISiVJqnGSLCrck0d4RDrPCoDOtBfIvS+OrT+OtTrPIWDSaEZ/UOMJpdRChbX1jiUqL4tSEC2iABbQi/mj/XBjk+Ci8k7SkXfFqGOk+UWneMuvzJr2fGBzAzMLYtbAEjqkqnQ+esrnPW4eCsQ6dT1znr0BnRNEIqhBSrEMwIa1F6nIP0OAbpdQ7R4xyk1zFIr3OQsBa7mOPU05j5sFulYbApOcI1xu+42vFbFpfniOZqOJtZz9n0es5mriRhOcmg4ybFEjpp5wztnKHciuajBBenxXr+dLltwliMBUuUQgCl+PJ4YGQ8CBIv92K6VIgY5CIGmbBBlalwraKwiaJgiqKMB2QUZVIgpRDkKbo86XkVhSOWSqo6gK4mMKod5Bb7sMpcoEzx16Po+ewSV+H1TaXOeIKr4h2v+v0zUMkqOoaikVU1copOTrHPRzWdl9z2jqrbNFmazbI8k2V5JpM/z1J2ngHJlKnTMWD/9hXNxF2RxV2ZxZM/dwZyTJqN5CJ8p8XlzirtQl9Fv23hJJRrK1xXyeLLBySKAxO+QvDCvuxSYlMG1l77LEazKmdih6l0LuLAyNNE2qqw8sEMJxmCRAkQt7MoiBWdogSIgenicOp1vJJ4PUb31ShNL1E7lKapJ0VZJDfHf8MT1j7pQ5z57SawInEa1TJ449DT/PXZh1kbtwcKsqo9qG1NOObayj9+7L86YXk4SjuHrGV0K/VscxzBMDN8yvm/KVMSxJTS+bnHHq9gb68qKKiKfV1VFBRFQR27HWWK38bMXp8C1Mah5rBCf6XFqQboavTQ2pVG09ygu+15yxU7NJg2TVKmxX6Ph4Sq0pwzeVM8y+uTOcpNAD+jLn+h/YXXU/T8StHrm/h6C7dPaO7E+098fdZ5Pt9J/6HK9M8/7eNN7GmqVJNUyF6jVqOgt6g4mhWUaiem4iUCRKd6ztm2+Tzv2eT7n/v5pnvNyoTr099/4jqVKS8Wr7948Xlfz/nad77f8KTF5/7zOO/6znG7ZZkYZhLDSGKaKaxECiVnUB04Q13FMerKTuJw2APY3WyY+vVMeKrzfb6vpg+bePtfAtvMFD9QBnhZTfDrsirWr24leDBHsNXBIf9e1qU9VDftQXNowJtLHh8EPkc3d48+zLeTy7GyGh7N4HWLRllfnkNVbprT9l/Y7eMXDcukI3yaI6HDpI1dbG6wuHXDFtItNzLQGaX/1Hg9jmQ0C1oSy8ricFQSDF5ZqH0RDFyBwzH1IEJ1cyvVza1s+qM/JptJ033oZU6/9CKnD+xjuKsTT3gEpaaZRQNdLO46QdvZ49QPdKMW1UmYnLv8B0AZ+52M/6/ZQQdl/Ob8f2JhgQJYVv6gLwNMOwsKVcNdUUfruvUsvmoTLWvX43qtzsuvKFDVbp+u+jN7WWygtA5H7wHCpp9IOofHobGhtZxNrZVc3VbJVS3l+KT+xWueoijcsKya65dWsfPoID97LMzS0YOgOe2pRG+4f8op9sTlY1YZGj09PTQ2NrJr1y62bNlSWP75z3+eH/zgBxw9enTSYyRDQ0xkmhbxTK4k8yOWSLA0+gLNixaVBi2c/lkVvxodHeXM0BlWLV6FU9Gh/yBm3wkUTUUpFA8r3iE5x8ZgyW2KnTESH+Jsp4rpq8cfsAgEwemc+jGGadJ14hQ5U6OusQ5/0Fe6vgtpQ140l+RsaohYOIOW0cn5slhOs3RjqCjAML4apWSdxbteSslyderlRRtYxe0rWc94A0qWm2aWXC5Mha+FNu+i/NzSU2+cm6ZF55k4mjdLY00F6qSU4/O/R+e87QLe86kfdzHX9yrbd47HGMAr0SSZ7BAbK5tKivDNfH0zaPeE245E02QxCOYsGoqKcVmWRc5SyFoWWSuf7WJZZE17ecay7KwZ07KDKZaVXwbu0En8kTOgOkDVQHNgqjqKqmNpOorqxNIcKPnbLNVhz92tOlFUHVQddAeKotqDZPlvu6LkfyeWQSbVy4uD+2ivvJImxYF39AyqkcGtKgQ09Zzf3bHXN5IIkdv1CmUrluFsqkOZVEhyJjumM/xOXNDtE26e1M/OzY53cb90rrtPOXAzizYoE/q6891/fm6fePeL//wWFulEgsToCEM9YTR3A+XVPnxBHZd3Qu2rP8D351y3x8KjhLv70LI6WqWLeHiUUDxJU3u7Xa/C5Z7y/YumsgTcjpL1G4bJQGeYyiYDl7Nm2ufPDiTI9sbwXll7/vbPc5QpZZj0ZbK0eWZXt8WyrEJ/nrYsMqbFcChEOBqlvL6BjAUZ0ySWTjMai2HpDuqCAZrcTupdDlzzXB/INHMMDf2WmspbUPTp5/ff3bMbh+pgU92m184RrjOU7Q8R+92TBG66CX0OihyLy0s2O8JgTxeV1Stx+2aYvbZAWJbFM93PoCs6Wxq3YJkmRxJpDkQTvKO+asbreO6557jiiivwXmaDxdFMlF+e/CX/feV/n7IfsyyL6HCK0dF91DQ24XZfnLoKsdAwp0ZG8SpQpmtFMTilaP1F+7DnGdAv3q8tPF6h6DET9odLnqdo33bisnMEF8abWdwWJjymqM0T2lLa/ov8H5JL2wP4lmnX1hC2TJwDR0+iVLSwqj4o9S+EXa9i/0OwZBuUNV7q5ohzmJMpp8YCGrt37+a6664rLP+Hf/gHfvjDH3LkyPnTx6WGhhBCCCGEEEIIIYQQQgghxsw0bjCrMGV1dTWaptHX11eyfGBggLo6SdURQgghhBBCCCGEEEIIIcTcmFVAw+l0snHjRnbs2FGyfMeOHSVTUAkhhBBCCCGEEEIIIYQQQlxMs66Ec//99/Oud72LTZs2cd111/Htb3+bzs5O7r333rlonxBCCCGEEEIIIYQQQgghxOwDGnfffTfDw8N89rOfpbe3l7Vr17J9+3ZaW1vnon1CCCGEEEIIIYQQQgghhBCzKwp+MUhRcCGEEEIIIYQQQgghhBBCjJmTouBCCCGEEEIIIYQQQgghhBCXggQ0hBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHgSUBDCCGEEEIIIYQQQgghhBALngQ0hBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHgSUBDCCGEEEIIIYQQQgghhBALngQ0hBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHgSUBDCCGEEEIIIYQQQgghhBALngQ0hBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHgSUBDCCGEEEIIIYQQQgghhBALngQ0hBBCCCGEEEIIIYQQQgix4Onz/YSWZQEQiUTm+6mFEEIIIYQQQgghhBBCCLHAjMULxuIH05n3gEY0GgWgubl5vp9aCCGEEEIIIYQQQgghhBALVDQapaysbNrbFet8IY+LzDRNenp6CAQCKIoyn0+9oEUiEZqbmzl79izBYPBSN0cI8Rok/YwQYq5JPyOEmGvSzwgh5pL0MUKIuSb9zPQsyyIajdLQ0ICqTl8pY94zNFRVpampab6f9rIRDAblyyyEmFPSzwgh5pr0M0KIuSb9jBBiLkkfI4SYa9LPTO1cmRljpCi4EEIIIYQQQgghhBBCCCEWPAloCCGEEEIIIYQQQgghhBBiwZOAxgLhcrn41Kc+hcvlutRNEUK8Rkk/I4SYa9LPCCHmmvQzQoi5JH2MEGKuST/z6s17UXAhhBBCCCGEEEIIIYQQQojZkgwNIYQQQgghhBBCCCGEEEIseBLQEEIIIYQQQgghhBBCCCHEgicBDSGEEEIIIYQQQgghhBBCLHgS0BBCCCGEEEIIIYQQQgghxIInAQ0hhBBCCCGEEEIIIYQQQix4EtCYR9/85jdZvHgxbrebjRs38swzz5zz/k899RQbN27E7XazZMkS/vVf/3WeWiqEuFzNpp/5+c9/zute9zpqamoIBoNcd911/OY3v5nH1gohLkez3Z4Zs2vXLnRdZ/369XPbQCHEZW22fUw6neYTn/gEra2tuFwu2tvb+d73vjdPrRVCXI5m28889NBDXHnllXi9Xurr63nPe97D8PDwPLVWCHG5efrpp3nTm95EQ0MDiqLwyCOPnPcxMgY8OxLQmCcPP/wwH/7wh/nEJz7Bvn372Lp1K294wxvo7Oyc8v4dHR3ceeedbN26lX379vH3f//33HffffzHf/zHPLdcCHG5mG0/8/TTT/O6172O7du3s3fvXrZt28ab3vQm9u3bN88tF0JcLmbbz4wJh8Pcc8893HrrrfPUUiHE5ehC+pi3v/3tPPHEE3z3u9/l6NGj/OQnP2HlypXz2GohxOVktv3M7373O+655x7e97738corr/DTn/6UF154gb/4i7+Y55YLIS4X8XicK6+8kq9//eszur+MAc+eYlmWdakb8Ydg8+bNbNiwgQcffLCwbNWqVdx111088MADk+7/t3/7tzz66KMcPny4sOzee+/lwIEDPPvss/PSZiHE5WW2/cxU1qxZw913380nP/nJuWqmEOIydqH9zDve8Q6WLVuGpmk88sgj7N+/fx5aK4S43My2j3nsscd4xzvewalTp6isrJzPpgohLlOz7Wf++Z//mQcffJCTJ08Wln3ta1/ji1/8ImfPnp2XNgshLl+KovCLX/yCu+66a9r7yBjw7EmGxjzIZDLs3buX22+/vWT57bffzu7du6d8zLPPPjvp/q9//evZs2cP2Wx2ztoqhLg8XUg/M5FpmkSjURkQEEJM6UL7mX//93/n5MmTfOpTn5rrJgohLmMX0sc8+uijbNq0iS9+8Ys0NjayfPlyPvrRj5JMJuejyUKIy8yF9DNbtmyhq6uL7du3Y1kW/f39/OxnP+ONb3zjfDRZCPEHQMaAZ0+/1A34QzA0NIRhGNTV1ZUsr6uro6+vb8rH9PX1TXn/XC7H0NAQ9fX1c9ZeIcTl50L6mYm+9KUvEY/Hefvb3z4XTRRCXOYupJ85fvw4H//4x3nmmWfQddnsFEJM70L6mFOnTvG73/0Ot9vNL37xC4aGhnj/+99PKBSSOhpCiEkupJ/ZsmULDz30EHfffTepVIpcLseb3/xmvva1r81Hk4UQfwBkDHj2JENjHimKUnLdsqxJy853/6mWCyHEmNn2M2N+8pOf8OlPf5qHH36Y2trauWqeEOI1YKb9jGEYvPOd7+Qzn/kMy5cvn6/mCSEuc7PZljFNE0VReOihh7jmmmu48847+fKXv8z3v/99ydIQQkxrNv3MoUOHuO+++/jkJz/J3r17eeyxx+jo6ODee++dj6YKIf5AyBjw7MihcvOguroaTdMmRfwHBgYmReDGLFq0aMr767pOVVXVnLVVCHF5upB+ZszDDz/M+973Pn76059y2223zWUzhRCXsdn2M9FolD179rBv3z4++MEPAvbgo2VZ6LrO448/zi233DIvbRdCLHwXsi1TX19PY2MjZWVlhWWrVq3Csiy6urpYtmzZnLZZCHF5uZB+5oEHHuD666/nYx/7GABXXHEFPp+PrVu38rnPfU6OnBZCvGoyBjx7kqExD5xOJxs3bmTHjh0ly3fs2MGWLVumfMx111036f6PP/44mzZtwuFwzFlbhRCXpwvpZ8DOzHj3u9/Nj3/8Y5kHVghxTrPtZ4LBIAcPHmT//v2F07333suKFSvYv38/mzdvnq+mCyEuAxeyLXP99dfT09NDLBYrLDt27BiqqtLU1DSn7RVCXH4upJ9JJBKoaunQmaZpwPgR1EII8WrIGPDsSUBjntx///185zvf4Xvf+x6HDx/mIx/5CJ2dnYU0xb/7u7/jnnvuKdz/3nvv5cyZM9x///0cPnyY733ve3z3u9/lox/96KV6CUKIBW62/cxPfvIT7rnnHr70pS9x7bXX0tfXR19fH+Fw+FK9BCHEAjebfkZVVdauXVtyqq2txe12s3btWnw+36V8KUKIBWi22zLvfOc7qaqq4j3veQ+HDh3i6aef5mMf+xjvfe978Xg8l+plCCEWsNn2M29605v4+c9/zoMPPsipU6fYtWsX9913H9dccw0NDQ2X6mUIIRawWCxWOKALoKOjg/3799PZ2QnIGPDFIFNOzZO7776b4eFhPvvZz9Lb28vatWvZvn07ra2tAPT29ha+2ACLFy9m+/btfOQjH+Eb3/gGDQ0N/Mu//AtvfetbL9VLEEIscLPtZ771rW+Ry+X4wAc+wAc+8IHC8j//8z/n+9///nw3XwhxGZhtPyOEELMx2z7G7/ezY8cOPvShD7Fp0yaqqqp4+9vfzuc+97lL9RKEEAvcbPuZd7/73USjUb7+9a/zN3/zN5SXl3PLLbfwhS984VK9BCHEArdnzx62bdtWuH7//fcD42MtMgb86imW5MgJIYQQQgghhBBCCCGEEGKBkymnhBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHgSUBDCCGEEEIIIYQQQgghhBALngQ0hBBCCCGEEEIIIYQQQgix4ElAQwghhBBCCCGEEEIIIYQQC54ENIQQQgghhBBCCCGEEEIIseBJQEMIIYQQQgghhBBCCCGEEAueBDSEEEIIIYQQQgghhBBCCLHg/f9vr/PZaUeW/AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,10))\n",
    "for offset,(t,coef) in decomp.items():\n",
    "    plt.plot(t,coef)\n",
    "plt.legend(decomp.keys(),ncol=3)\n",
    "savefig(fig,\"Coefs_Vor6.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Case of a field of tensors\n",
    "\n",
    "On the CPU, the decomposition time increases linearly with the number of tensors.\n",
    "On the GPU, the decomposition runs on a single thread, and there are $2560$ of them on a nvidia $1080$ class card. \n",
    "Therefore time is rather insensitive to the number of tensors until that number is reached.\n",
    "\n",
    "**Notes on the GPU implementation.**\n",
    "The GPU based Voronoi decomposition is approximately $100$ times faster than the CPU based one (except on the first call on a given machine, where JIT compilation takes a little while). However, it is also less stable, since it uses single precision scalars. In order to address this issue, the GPU implementation is first run using single precision, and then using double precision for the matrices whose decomposition proved to be excessively inaccurate.\n",
    "\n",
    "<!--- This needs to be sorted out. One possibility would be to make a second call using double precision for the few tensors which were not correctly decomposed. Another approach is to try debug the code.--->\n",
    "\n",
    "<!---\n",
    "**Note on CPU/GPU computation time**\n",
    "Computation time is dominated ($90\\%$) by the solution of a linear problem, with 15 variables and 36 constraints. \n",
    "Currently this is done using the following algorithm:\n",
    "\n",
    "* Academic paper : Seidel, R. (1991), \"Small-dimensional linear programming and convex hulls made easy\", Discrete & Computational Geometry 6 (1): 423–434, doi:10.1007/BF02574699\n",
    "* Source code : https://github.com/cgrushko/seidel-lp-solver\n",
    "\n",
    "This algorithm appears not to be well adapted to the task at hand, since it is mostly intended for linear programs in dimension $<10$, and its complexity grows exponentially with the dimension. Also, the GPU seems not to like it (lots of branching).\n",
    "--->\n",
    "\n",
    "<!---In the current implementation, the GPU code appears to be quite slow, in addition to being less stable due to the use of single-precision floating point variables. A multi-threaded CPU implementation--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:56.428456Z",
     "iopub.status.busy": "2024-04-30T08:46:56.428344Z",
     "iopub.status.idle": "2024-04-30T08:46:56.430977Z",
     "shell.execute_reply": "2024-04-30T08:46:56.430745Z"
    }
   },
   "outputs": [],
   "source": [
    "def decomp_time(n):\n",
    "    np.random.seed(42)\n",
    "    D = MakeRandomTensor(6,(n,))\n",
    "    start = time.time()\n",
    "    coefs,offsets = VoronoiDecomposition(D)\n",
    "    print(f\"Decomposition of {n} matrices completed in {time.time()-start} seconds\")\n",
    "    print(\"Tensor shape: \",D.shape,\", max reconstruction error : \",np.max(np.abs(D-Reconstruct(coefs,offsets))))\n",
    "#    assert allclose(D,Reconstruct(coefs,offsets))\n",
    "    return D,coefs,offsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:56.432316Z",
     "iopub.status.busy": "2024-04-30T08:46:56.432213Z",
     "iopub.status.idle": "2024-04-30T08:46:56.446797Z",
     "shell.execute_reply": "2024-04-30T08:46:56.446476Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decomposition of 10 matrices completed in 0.012002944946289062 seconds\n",
      "Tensor shape:  (6, 6, 10) , max reconstruction error :  1.7532642004880472e-12\n"
     ]
    }
   ],
   "source": [
    "decomp_time(10);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:56.448411Z",
     "iopub.status.busy": "2024-04-30T08:46:56.448302Z",
     "iopub.status.idle": "2024-04-30T08:46:56.519467Z",
     "shell.execute_reply": "2024-04-30T08:46:56.519127Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decomposition of 100 matrices completed in 0.06799983978271484 seconds\n",
      "Tensor shape:  (6, 6, 100) , max reconstruction error :  3.227640377190255e-12\n"
     ]
    }
   ],
   "source": [
    "decomp_time(100);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:56.521071Z",
     "iopub.status.busy": "2024-04-30T08:46:56.520952Z",
     "iopub.status.idle": "2024-04-30T08:46:57.148380Z",
     "shell.execute_reply": "2024-04-30T08:46:57.148044Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decomposition of 1000 matrices completed in 0.6193840503692627 seconds\n",
      "Tensor shape:  (6, 6, 1000) , max reconstruction error :  4.46931380793103e-12\n"
     ]
    }
   ],
   "source": [
    "decomp_time(1000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the GPU, decomposition time should be mostly insensitive to $n\\leq 2500$, and scale linearly with $n$ beyond that limit. \n",
    "\n",
    "<!---\n",
    "TODO : investigate this GPU failure, which is probably due to roundoff errors.\n",
    "Decomposition of 10000 matrices completed in 73.4375216960907 seconds\n",
    "Tensor shape:  (6, 6, 10000) , max reconstruction error :  7.562082901426454\n",
    "\n",
    "CPU does not fail here.\n",
    "Decomposition of 10000 matrices completed in 340.8524580001831 seconds\n",
    "Tensor shape:  (6, 6, 10000) , max reconstruction error :  5.329070518200751e-13\n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.150078Z",
     "iopub.status.busy": "2024-04-30T08:46:57.149949Z",
     "iopub.status.idle": "2024-04-30T08:46:57.151800Z",
     "shell.execute_reply": "2024-04-30T08:46:57.151568Z"
    }
   },
   "outputs": [],
   "source": [
    "if large_instances: decomp_time(10000);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.153150Z",
     "iopub.status.busy": "2024-04-30T08:46:57.153053Z",
     "iopub.status.idle": "2024-04-30T08:46:57.154655Z",
     "shell.execute_reply": "2024-04-30T08:46:57.154432Z"
    }
   },
   "outputs": [],
   "source": [
    "if large_instances: decomp_time(50000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Under the hood, Voronoi's first reduction \n",
    "\n",
    "**Voronoi's first reduction.** Voronoi associates to each positive quadratic form, defined by a positive definite matrix $D$, the following optimization problem\n",
    "$$\n",
    "    V(D) = \\min_M \\mathrm{Tr}(D M)\n",
    "$$\n",
    "where $M$ is a symmetric matrix, subject to the following linear constraints: for all $e \\in Z^d \\setminus \\{0\\}$\n",
    "$$\n",
    "    <e,M e> \\geq 2.\n",
    "$$\n",
    "The set $\\mathcal M$ of matrices $M$ obeying these constraints is known as Ryskov's polyhedron. (The constant $2$ in the above equation is customary, but may of course be replaced with an arbitary positive constant, such as $1$.)\n",
    "\n",
    "**Dual linear program.** Voronoi's first reduction is a well posed linear program, hence it admits a dual linear program, namely\n",
    "$$\n",
    "    \\max_\\lambda \\sum_{e \\in Z^d\\setminus\\{0\\}} \\lambda(e)\n",
    "$$\n",
    "where $\\lambda : Z^d\\setminus\\{0\\} \\to R$ is constrained to be non-negative, and to obey \n",
    "$$\n",
    "    \\sum_{e \\in Z^d\\setminus\\{0\\}} \\lambda(e) e e^T = D.\n",
    "$$\n",
    "\n",
    "**Computation of the decomposition.**\n",
    "We numerically solve Voronoi's first reduction, using a *highly precomputed* simplex-like method. \n",
    "By precomputation, we mean that all the vertices of Ryskov's polyhedron are known in advance, as well as their connectivity. Indeed, a famous result of Voronoi states that Ryskov's polyhedron admits only finitely many classes of vertices, up to arithmetic equivalence (linear changes of variables with integer coordinates).\n",
    "\n",
    "From the solution to the primal linear program, Voronoi's first reduction, we can then deduce a solution to the dual linear program, namely the matrix decomposition that is of interest to us. \n",
    "\n",
    "The primal linear program admits a unique solution, for generic $D$. However, the dual linear program usually has several solutions, because some of the vertices of Ryskov's polyhedron are degenerate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 Voronoi's perfect forms\n",
    "\n",
    "Ryskov's polyhedron in dimension $d=6$ admits $7$ classes of vertices, up to arithmetic equivalence, see above. They are described in detail in the following reference:\n",
    "* Barnes, E. S. (1957). The complete enumeration of extreme senary forms. Philosophical Transactions of the Royal Society of London. Series a, Mathematical and Physical Sciences, 249(969), 461–5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.156103Z",
     "iopub.status.busy": "2024-04-30T08:46:57.156026Z",
     "iopub.status.idle": "2024-04-30T08:46:57.159390Z",
     "shell.execute_reply": "2024-04-30T08:46:57.159140Z"
    }
   },
   "outputs": [],
   "source": [
    "perfect_forms6 = expand_symmetric_matrix(np.array([\n",
    " [2. ,1. ,2. ,1. ,1. ,2. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,1. ,2. ],\n",
    " [2. ,0. ,2. ,1. ,1. ,2. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,1. ,2. ],\n",
    " [2. ,0. ,2. ,0. ,1. ,2. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,1. ,2. ],\n",
    " [2. ,0.5,2. ,1. ,1. ,2. ,1. ,1. ,0.5,2. ,1. ,1. ,1. ,1. ,2. ,1. ,1. ,1. ,1. ,0.5,2. ],\n",
    " [2. ,0.5,2. ,1. ,1. ,2. ,1. ,1. ,0.5,2. ,1. ,1. ,0.5,0.5,2. ,1. ,1. ,0.5,0.5,0.5,2. ],\n",
    " [2. ,0.5,2. ,1. ,1. ,2. ,1. ,1. ,0.5,2. ,1. ,1. ,0.5,0.5,2. ,1. ,1. ,1. ,1. ,1. ,2. ],\n",
    " [2. ,0. ,2. ,0.5,1. ,2. ,1. ,1. ,1. ,2. ,1. ,0.5,1. ,1. ,2. ,0.5,1. ,1. ,0.5,0. ,2. ]]).T\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perfect forms are beautiful mathematical objects, and each of these matrices has a particular story to tell.\n",
    "In particular, the form of index two:\n",
    "* Defines the densest periodic ellipsoid packing in dimension 6.\n",
    "* Defines the root lattice of the lie group E6.\n",
    "* Is a highly degenerate vertex of Ryskov's polyhedron, with 36 pairs of vectors $\\pm e \\in Z^6 \\setminus \\{0\\}$ saturating the constraint $<e,M e> = 2$. It also has $38124$ neighbor vertices on the skeleton of Ryskov's polyhedron, whose complete list is included in the C++ source code of the agd library."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.160757Z",
     "iopub.status.busy": "2024-04-30T08:46:57.160679Z",
     "iopub.status.idle": "2024-04-30T08:46:57.163026Z",
     "shell.execute_reply": "2024-04-30T08:46:57.162788Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7.      , 4.      , 3.      , 5.484375, 3.796875, 5.0625  ,\n",
       "       5.359375])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linalg.det(np.moveaxis(perfect_forms6,-1,0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.164413Z",
     "iopub.status.busy": "2024-04-30T08:46:57.164333Z",
     "iopub.status.idle": "2024-04-30T08:46:57.166554Z",
     "shell.execute_reply": "2024-04-30T08:46:57.166322Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2., 0., 0., 1., 1., 1.],\n",
       "       [0., 2., 1., 1., 1., 1.],\n",
       "       [0., 1., 2., 1., 1., 1.],\n",
       "       [1., 1., 1., 2., 1., 1.],\n",
       "       [1., 1., 1., 1., 2., 1.],\n",
       "       [1., 1., 1., 1., 1., 2.]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perfect_forms6[:,:,2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the other hand, the perfect form of index $0$ admits counterparts in all dimensions. It is optimal (up to arithmetic equivalence) for a matrix $D$ if, and only if, $D$ admits an obtuse superbase. See the notebook on [Selling's reduction](TensorSelling.ipynb).\n",
    "\n",
    "It is a non degenerate vertex of Ryskov's polyhedron, and thus has $21 = \\mathrm{dim}(S_6)$ such vector pairs $\\pm e\\in Z^d$ saturating the constaint $<e,Me>\\geq 2$, and $21$ neighbor vertices on the skeleton of Ryskov's polyhedron. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.167908Z",
     "iopub.status.busy": "2024-04-30T08:46:57.167824Z",
     "iopub.status.idle": "2024-04-30T08:46:57.170196Z",
     "shell.execute_reply": "2024-04-30T08:46:57.169926Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2., 1., 1., 1., 1., 1.],\n",
       "       [1., 2., 1., 1., 1., 1.],\n",
       "       [1., 1., 2., 1., 1., 1.],\n",
       "       [1., 1., 1., 2., 1., 1.],\n",
       "       [1., 1., 1., 1., 2., 1.],\n",
       "       [1., 1., 1., 1., 1., 2.]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perfect_forms6[:,:,0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Computing Voronoi's first reduction\n",
    "\n",
    "In order to obtain the full Voronoi decomposition, we use the split argument.\n",
    "\n",
    "<!---\n",
    "**Note on the retry64_tol argument.** In this mode, with the \n",
    "--->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.171680Z",
     "iopub.status.busy": "2024-04-30T08:46:57.171608Z",
     "iopub.status.idle": "2024-04-30T08:46:57.182115Z",
     "shell.execute_reply": "2024-04-30T08:46:57.181753Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "D = MakeRandomTensor(6)\n",
    "a,vertex,objective,weights,offsets = VoronoiDecomposition(D,steps='Split')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, the second perfect form is optimal, up to arithmetic equivalence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.183731Z",
     "iopub.status.busy": "2024-04-30T08:46:57.183612Z",
     "iopub.status.idle": "2024-04-30T08:46:57.186053Z",
     "shell.execute_reply": "2024-04-30T08:46:57.185803Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(2)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vertex # Index of the optimal perfect form"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The linear change of variables, defining the arithmetic equivalence, is returned as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.187376Z",
     "iopub.status.busy": "2024-04-30T08:46:57.187282Z",
     "iopub.status.idle": "2024-04-30T08:46:57.189415Z",
     "shell.execute_reply": "2024-04-30T08:46:57.189178Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  1.,  0., -1., -1.,  0.],\n",
       "       [ 1.,  0.,  0., -1.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., -1.,  0.,  0.],\n",
       "       [ 0., -1., -1.,  1.,  1., -1.],\n",
       "       [ 0.,  0.,  0.,  1.,  1.,  0.],\n",
       "       [-1.,  0.,  0.,  1.,  0.,  1.]])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And the optimal matrix for Voronoi's decomposition is thus obtained as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.190732Z",
     "iopub.status.busy": "2024-04-30T08:46:57.190629Z",
     "iopub.status.idle": "2024-04-30T08:46:57.192326Z",
     "shell.execute_reply": "2024-04-30T08:46:57.192095Z"
    }
   },
   "outputs": [],
   "source": [
    "def dot_tADA(A,D):\n",
    "    return lp.dot_AA(lp.dot_AA(lp.transpose(A),D),A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.193604Z",
     "iopub.status.busy": "2024-04-30T08:46:57.193523Z",
     "iopub.status.idle": "2024-04-30T08:46:57.195172Z",
     "shell.execute_reply": "2024-04-30T08:46:57.194949Z"
    }
   },
   "outputs": [],
   "source": [
    "M = dot_tADA(a,perfect_forms6[:,:,vertex])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.196495Z",
     "iopub.status.busy": "2024-04-30T08:46:57.196413Z",
     "iopub.status.idle": "2024-04-30T08:46:57.198540Z",
     "shell.execute_reply": "2024-04-30T08:46:57.198305Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2., -1.,  0., -1.,  1., -1.],\n",
       "       [-1.,  2.,  1.,  0., -2.,  1.],\n",
       "       [ 0.,  1.,  2., -1., -2.,  1.],\n",
       "       [-1.,  0., -1.,  2.,  1.,  0.],\n",
       "       [ 1., -2., -2.,  1.,  4., -1.],\n",
       "       [-1.,  1.,  1.,  0., -1.,  2.]])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The value of Voronoi's first reduction is also, by Kantorovitch duality, (twice) the sum of the coefficients of the decomposition of $D$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.199917Z",
     "iopub.status.busy": "2024-04-30T08:46:57.199838Z",
     "iopub.status.idle": "2024-04-30T08:46:57.201926Z",
     "shell.execute_reply": "2024-04-30T08:46:57.201691Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48.6937132003662"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lp.trace(lp.dot_AA(D,M)) # Value of primal linear program"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.203291Z",
     "iopub.status.busy": "2024-04-30T08:46:57.203205Z",
     "iopub.status.idle": "2024-04-30T08:46:57.205203Z",
     "shell.execute_reply": "2024-04-30T08:46:57.204970Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(48.6937132)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "objective # Common value of the primal and dual linear programs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.206525Z",
     "iopub.status.busy": "2024-04-30T08:46:57.206449Z",
     "iopub.status.idle": "2024-04-30T08:46:57.208697Z",
     "shell.execute_reply": "2024-04-30T08:46:57.208455Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48.69371320036792"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2*np.sum(weights) # Value of dual linear program (matrix decomposition)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The offsets involved in the decomposition of $D$ saturate the constraint $<e, M e> \\geq 2$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.210063Z",
     "iopub.status.busy": "2024-04-30T08:46:57.209986Z",
     "iopub.status.idle": "2024-04-30T08:46:57.212348Z",
     "shell.execute_reply": "2024-04-30T08:46:57.212109Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
       "       2., 2., 2., 2.])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lp.dot_VAV(offsets,np.expand_dims(M,axis=-1),offsets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Most common optimal form\n",
    "\n",
    "Not all perfect forms are equal. The form of index two takes is optimal most of the time ($90\\%$ of cases), up to arithmetic equivalence, whereas the form of index zero is rarely optimal. These two forms are discussed above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:57.213701Z",
     "iopub.status.busy": "2024-04-30T08:46:57.213605Z",
     "iopub.status.idle": "2024-04-30T08:46:58.432420Z",
     "shell.execute_reply": "2024-04-30T08:46:58.432018Z"
    }
   },
   "outputs": [],
   "source": [
    "np.random.seed(42)\n",
    "D = MakeRandomTensor(6,(20000 if large_instances else 1000,))\n",
    "a,vertex,objective,weights,offsets = VoronoiDecomposition(D,steps='Split')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:58.434293Z",
     "iopub.status.busy": "2024-04-30T08:46:58.434163Z",
     "iopub.status.idle": "2024-04-30T08:46:58.436663Z",
     "shell.execute_reply": "2024-04-30T08:46:58.436391Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found optimal forms [1 2 3 4 5 6] with counts [ 83 890  10   5  11   1],\n",
      " hence frequency [0.083 0.89  0.01  0.005 0.011 0.001]\n"
     ]
    }
   ],
   "source": [
    "index,counts = np.unique(vertex,return_counts=True)\n",
    "print(f\"Found optimal forms {index} with counts {counts},\\n hence frequency {counts/vertex.size}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Voronoi's first reduction in lower dimensions \n",
    "\n",
    "The theory descibed in the previous section for six dimensions applies as well in all other dimensions. We briefly reproduce similar results in dimension $2$, $3$, $4$ and $5$. There is a single perfect form in dimension $2$ and $3$. In other words, all vertices of Ryskov's polyhedron are arithmetically equivalent in these dimensions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:58.438163Z",
     "iopub.status.busy": "2024-04-30T08:46:58.438055Z",
     "iopub.status.idle": "2024-04-30T08:46:58.440996Z",
     "shell.execute_reply": "2024-04-30T08:46:58.440767Z"
    }
   },
   "outputs": [],
   "source": [
    "perfect_forms2 = expand_symmetric_matrix(np.array([\n",
    "    [2.,1.,2.]\n",
    "]).T)\n",
    "perfect_forms3 = expand_symmetric_matrix(np.array([\n",
    "    [2.,1.,2.,1.,1.,2.]\n",
    "]).T)\n",
    "perfect_forms4 = expand_symmetric_matrix(np.array([\n",
    "    [2, 1, 2, 1, 1, 2, 0, 1, 1, 2],\n",
    "    [2, 1, 2, 1, 1, 2, 1, 1, 1, 2.]\n",
    "]).T)\n",
    "perfect_forms5 = expand_symmetric_matrix(np.array([\n",
    "    [2,1,2,1,1,2,1,1,1,2,0,1,1,1,2],\n",
    "    [2,1,2,1,1,2,1,1,1,2,1,1,1,1,2],\n",
    "    [2,0.5,2,0.5,0.5,2,-1,-1,-1,2,-1,-1,-1,0.5,2]\n",
    "]).T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:58.442412Z",
     "iopub.status.busy": "2024-04-30T08:46:58.442311Z",
     "iopub.status.idle": "2024-04-30T08:46:58.443889Z",
     "shell.execute_reply": "2024-04-30T08:46:58.443664Z"
    }
   },
   "outputs": [],
   "source": [
    "perfect_forms = (None,None,perfect_forms2,perfect_forms3,perfect_forms4,perfect_forms5,perfect_forms6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-30T08:46:58.445207Z",
     "iopub.status.busy": "2024-04-30T08:46:58.445131Z",
     "iopub.status.idle": "2024-04-30T08:46:59.738078Z",
     "shell.execute_reply": "2024-04-30T08:46:59.737753Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "---- Dimension 2 ----\n",
      "Decomposed matrix : \n",
      " [[0.81647351 0.91777115]\n",
      " [0.91777115 2.48898508]]\n",
      "Optimal vertex of Ryskov's polyhedron has class 0, and value : \n",
      " [[ 6. -3.]\n",
      " [-3.  2.]] \n",
      "Common value of the primal and dual linear programs : 4.370184339584078\n",
      "4.370184339584078 4.370184339584078 4.370184339584078\n",
      "Minimal weight 0.10129763611014386 (must be non-negative)\n",
      "Offset norms w.r.t optimal vertex [2. 2. 2.] (must be two)\n",
      "\n",
      "---- Dimension 3 ----\n",
      "Decomposed matrix : \n",
      " [[ 1.06841485 -0.08963958 -0.06552819]\n",
      " [-0.08963958  0.70200555 -0.73715916]\n",
      " [-0.06552819 -0.73715916  3.05670529]]\n",
      "Optimal vertex of Ryskov's polyhedron has class 0, and value : \n",
      " [[2. 2. 1.]\n",
      " [2. 6. 3.]\n",
      " [1. 3. 2.]] \n",
      "Common value of the primal and dual linear programs : 7.549703933010018\n",
      "7.549703933010018 7.549703933010018 7.549703933010018\n",
      "Minimal weight 0.035153608391365165 (must be non-negative)\n",
      "Offset norms w.r.t optimal vertex [2. 2. 2. 2. 2. 2.] (must be two)\n",
      "\n",
      "---- Dimension 4 ----\n",
      "Decomposed matrix : \n",
      " [[ 4.68590969  2.87198961  0.99534872  2.45469031]\n",
      " [ 2.87198961  5.99243377  1.72366886  1.07077618]\n",
      " [ 0.99534872  1.72366886  5.34506365 -0.95048934]\n",
      " [ 2.45469031  1.07077618 -0.95048934  4.69431083]]\n",
      "Optimal vertex of Ryskov's polyhedron has class 0, and value : \n",
      " [[ 2. -1.  0. -1.]\n",
      " [-1.  2. -1.  0.]\n",
      " [ 0. -1.  2.  1.]\n",
      " [-1.  0.  1.  2.]] \n",
      "Common value of the primal and dual linear programs : 25.433759643747482\n",
      "25.433759643747482 25.433759643747486 25.43375964374748\n",
      "Minimal weight 0.2427733777756641 (must be non-negative)\n",
      "Offset norms w.r.t optimal vertex [2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.] (must be two)\n",
      "\n",
      "Reduced 1000 random positive definite matrices.\n",
      "Found optimal forms [0 1] with counts [764 236],\n",
      "hence frequency [0.764 0.236]\n",
      "\n",
      "---- Dimension 5 ----\n",
      "Decomposed matrix : \n",
      " [[ 5.79675256 -1.64227078 -1.8973522   1.35873272  3.02118772]\n",
      " [-1.64227078  4.80083533 -0.8203728  -3.39651079 -0.21430139]\n",
      " [-1.8973522  -0.8203728   4.54561602  1.33988971 -2.62273808]\n",
      " [ 1.35873272 -3.39651079  1.33988971  6.38186716 -0.79150986]\n",
      " [ 3.02118772 -0.21430139 -2.62273808 -0.79150986  3.8393835 ]]\n",
      "Optimal vertex of Ryskov's polyhedron has class 0, and value : \n",
      " [[ 2.  0.  0. -1. -1.]\n",
      " [ 0.  2.  1.  1.  1.]\n",
      " [ 0.  1.  2.  0.  1.]\n",
      " [-1.  1.  0.  2.  1.]\n",
      " [-1.  1.  1.  1.  2.]] \n",
      "Common value of the primal and dual linear programs : 26.278202412012355\n",
      "26.278202412012355 26.278202412012362 26.27820241201236\n",
      "Minimal weight 0.026685915733476933 (must be non-negative)\n",
      "Offset norms w.r.t optimal vertex [2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.] (must be two)\n",
      "\n",
      "Reduced 1000 random positive definite matrices.\n",
      "Found optimal forms [0 1 2] with counts [975  10  15],\n",
      "hence frequency [0.975 0.01  0.015]\n",
      "\n",
      "---- Dimension 6 ----\n",
      "Decomposed matrix : \n",
      " [[ 7.28380813 -1.91552559  0.77040122 -0.76997375 -5.78315428  3.2924392 ]\n",
      " [-1.91552559  8.12584371  3.09389792  1.60303287  3.3532303  -4.82701984]\n",
      " [ 0.77040122  3.09389792 15.11899155  6.46441512 -2.98807881  2.78370843]\n",
      " [-0.76997375  1.60303287  6.46441512  9.74790599  0.78084802  1.32851281]\n",
      " [-5.78315428  3.3532303  -2.98807881  0.78084802 11.25845622 -5.0365393 ]\n",
      " [ 3.2924392  -4.82701984  2.78370843  1.32851281 -5.0365393  13.97420385]]\n",
      "Optimal vertex of Ryskov's polyhedron has class 2, and value : \n",
      " [[ 2. -1.  1.  0.  1. -1.]\n",
      " [-1.  2. -1.  0. -1.  1.]\n",
      " [ 1. -1.  2. -1.  1. -1.]\n",
      " [ 0.  0. -1.  2. -1.  0.]\n",
      " [ 1. -1.  1. -1.  2.  0.]\n",
      " [-1.  1. -1.  0.  0.  2.]] \n",
      "Common value of the primal and dual linear programs : 69.65668867903864\n",
      "69.65668867903864 69.65668867904145 69.65668867903881\n",
      "Minimal weight 0.010874275890620537 (must be non-negative)\n",
      "Offset norms w.r.t optimal vertex [2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.] (must be two)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Reduced 1000 random positive definite matrices.\n",
      "Found optimal forms [1 2 3 4 5 6] with counts [ 81 894   3  10  11   1],\n",
      "hence frequency [0.081 0.894 0.003 0.01  0.011 0.001]\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(42)\n",
    "for d in range(2,7):\n",
    "    if d<=3 and VoronoiDecomposition.default_mode == 'gpu_transfer': continue # low dim not implemented on GPU\n",
    "    print(f'\\n---- Dimension {d} ----')\n",
    "    D = MakeRandomTensor(d)\n",
    "    a,vertex,objective,weights,offsets = VoronoiDecomposition(D,steps='Split')\n",
    "    print(f\"Decomposed matrix : \\n {D}\")\n",
    "    \n",
    "    M = dot_tADA(a,perfect_forms[d][:,:,vertex])\n",
    "    print(f\"Optimal vertex of Ryskov's polyhedron has class {vertex}, and value : \\n {M} \")\n",
    "    \n",
    "    print(f\"Common value of the primal and dual linear programs : {objective}\")\n",
    "    print(objective,2*weights.sum(),lp.trace(lp.dot_AA(D,M)))\n",
    "    assert allclose(objective,2*weights.sum())\n",
    "    assert allclose(objective,lp.trace(lp.dot_AA(D,M)))\n",
    "\n",
    "    print(f\"Minimal weight {np.min(weights)} (must be non-negative)\")\n",
    "    assert np.allclose(D,Reconstruct(weights,offsets))\n",
    "    assert np.all(weights>=0)\n",
    "\n",
    "    offset_norms = lp.dot_VAV(offsets,np.expand_dims(M,axis=-1),offsets)\n",
    "    print(f\"Offset norms w.r.t optimal vertex {offset_norms} (must be two)\")\n",
    "\n",
    "    if d<=3: continue\n",
    "    nTest=1000\n",
    "    D = MakeRandomTensor(d, (nTest,))\n",
    "    a,vertex,objective,weights,offsets = VoronoiDecomposition(D,steps='Split')\n",
    "\n",
    "    index,counts = np.unique(vertex,return_counts=True)\n",
    "    print(f\"\\nReduced {nTest} random positive definite matrices.\")\n",
    "    print(f\"Found optimal forms {index} with counts {counts},\\nhence frequency {counts/vertex.size}\")"
   ]
  },
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   "outputs": [],
   "source": []
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