{
"cells": [
{
"cell_type": "markdown",
"id": "2596fc0efde23134",
"metadata": {
"collapsed": false,
"jupyter": {
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}
},
"source": [
"# NOvA Data Release for [arXiv:2311.07835](https://arxiv.org/abs/2311.07835)\n",
"\n",
"## Introduction\n",
"\n",
"This data release corresponds to a 2022 reanalysis of the NOvA 2020 $\\nu_e$ appearance and $\\nu_{\\mu}$ disappearance data (data first analyzed in [Phys. Rev. **D**106, 032004](https://doi.org/10.1103/PhysRevD.106.032004)).\n",
"The reanalysis uses a Bayesian statistical approach instead of the preceding frequentist one.\n",
"Full details on the reanalysis may be found in the publication: [arXiv:2311.07835](https://arxiv.org/abs/2311.07835).\n",
"\n",
"This Jupyter notebook illustrates how to make plots similar to those in the paper using these MCMC samples.\n",
"(While this MCMC chain does not explicitly contain values for the systematic uncertainty parameters used in the model,\n",
" which means that those parameters cannot be plotted directly here, they are correctly implicitly marginalized\n",
" in any distribution made from the samples.)\n",
"\n",
"This notebook illustrates a few different techniques:\n",
" * [Creating simple 1D or 2D marginal distributions in parameters of interest](#Simple-marginals)\n",
" * [Computing credible intervals or regions](#Credible-intervals/regions)\n",
" * [Transforming to other variables](#Transformations)\n",
" * [Selecting sub-regions of phase space with selections](#Subsample-selections)\n",
" * [Changing priors via reweighting](#Changes-in-prior)\n",
"\n",
"### Sampling conditions\n",
"\n",
"The MCMC chain in the data release was created by running the [Stan](mc-stan.org) MCMC sampler using the model and data described in the paper.\n",
"The sampled parameters were:\n",
" * $\\Delta m_{32}^2$\n",
" * $\\theta_{13}$\n",
" * $\\theta_{23}$\n",
" * $\\delta_{CP}$\n",
" * 67 systematic uncertainty parameters (sampled values not included in the data release)\n",
"\n",
"For the oscillation parameters, priors uniform in the variable specified were chosen.\n",
"This means, in particular, that no constraint on $\\theta_{13}$ from reactor experiments was applied during sampling.\n",
"(However, there are examples below showing how to apply such a constraint _post hoc_, or transform to other choices of prior, as desired.)\n",
"These priors are also documented in the file itself (see `priors` cell below). \n",
"For the systematic uncertainties, all priors were assumed to be Gaussian; please see the cited references in the paper for more details on how these systematics were constructed.\n",
"\n",
"Additionally, though the values of $\\Delta m_{21}^2$ and $\\theta_{12}$ were fixed during sampling to the 2019 PDG values (as described in the paper), their values are included in each entry in the chain in order to facilitate computation of quantities that may require them, such as the Jarlskog invariant (see example below).\n",
"\n",
"### Software prerequisites for running this notebook\n",
"\n",
" * [matplotlib's pyplot](https://matplotlib.org/stable/api/pyplot_summary.html)\n",
" * [Uproot](https://uproot.readthedocs.io/en/latest/)\n"
]
},
{
"cell_type": "code",
"id": "initial_id",
"metadata": {
"ExecuteTime": {
"end_time": "2024-05-27T13:37:32.514754Z",
"start_time": "2024-05-27T13:37:32.511215Z"
}
},
"source": [
"import os.path\n",
"\n",
"import scipy.stats\n",
"import uproot\n",
"\n",
"DATA_RELEASE_FILENAME = os.path.expanduser(\"~/data/arxiv-2311.07835.data-release.mcmcsamples.root\")\n",
"data_release_file = uproot.open(DATA_RELEASE_FILENAME) "
],
"outputs": [],
"execution_count": 13
},
{
"cell_type": "code",
"id": "dcf02bc4f7786cfd",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:37:44.496339Z",
"start_time": "2024-05-27T13:37:32.515554Z"
}
},
"source": [
"samples = data_release_file[\"mcmc_samples\"]\n",
"print(\"Available parameters:\", \", \".join(samples.keys()))\n",
"\n",
"# note: there are a LOT of samples in this chain.\n",
"# we recommend using a small fraction (e.g., 1e5) for testing\n",
"N_SAMPLES = int(1e5)\n",
"kwargs = {\n",
"# \"entry_stop\": N_SAMPLES # uncomment this line to restrict to the smaller fraction\n",
"}\n",
"vals = samples.arrays(library=\"np\", **kwargs)"
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Available parameters: Deltam2_32, Deltam2_21, Theta12, Theta13, Theta23, DeltaCP\n"
]
}
],
"execution_count": 14
},
{
"cell_type": "code",
"id": "c2093153be1e0a20",
"metadata": {
"ExecuteTime": {
"end_time": "2024-05-27T13:37:44.501087Z",
"start_time": "2024-05-27T13:37:44.497683Z"
}
},
"source": [
"import pprint\n",
"\n",
"priors = data_release_file[\"parameter_priors\"]\n",
"print(\"Priors:\")\n",
"pprint.pprint({p.member(\"fName\"): p.member(\"fTitle\") for p in priors}) # Uproot appears not to have a nice interface for TNamed "
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Priors:\n",
"{'DeltaCP': 'Prior uniform in DeltaCP (rads).',\n",
" 'Deltam2_21': 'Parameter fixed (7.53e-5 eV^2) in NOvA given lack of '\n",
" 'sensitivity.',\n",
" 'Deltam2_32': 'Prior uniform in Deltam2_32 (eV^2), across both mass '\n",
" 'orderings. Equal prior on both mass orderings.',\n",
" 'Theta12': 'Parameter fixed (0.5873 rads) in NOvA given lack of sensitivity.',\n",
" 'Theta13': 'Prior uniform in Theta13 (rads).',\n",
" 'Theta23': 'Prior uniform in Theta23 (rads).'}\n"
]
}
],
"execution_count": 15
},
{
"cell_type": "code",
"id": "3dfd7fed783d440a",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:37:44.521674Z",
"start_time": "2024-05-27T13:37:44.501919Z"
}
},
"source": [
"# We'll use these for formatting in plots below.\n",
"PARAMETER_LABELS = {\n",
" \"Deltam2_21\": r\"$\\Delta m_{21}^2$ ($GeV/c^2$)\",\n",
" \"Deltam2_32\": r\"$\\Delta m_{32}^2$ ($GeV/c^2$)\",\n",
" \"Theta12\": r\"$\\theta_{12}$ (rad)\",\n",
" \"Theta13\": r\"$\\theta_{13}$ (rad)\",\n",
" \"Theta23\": r\"$\\theta_{23}$ (rad)\",\n",
" \"DeltaCP\": r\"$\\delta_{CP}$\",\n",
"}"
],
"outputs": [],
"execution_count": 16
},
{
"cell_type": "markdown",
"id": "b5bef3fda2d536cb",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"source": [
"## Simple marginals\n",
"\n",
"A fairly straightforward thing you can do: simply plot the marginal distributions in one or two dimensions.\n",
"Here we make a so-called \"triangle plot\" that shows all the pairwise 2D marginals and all the 1D marginals of all the parameters.\n"
]
},
{
"cell_type": "code",
"id": "dc368f85e17d12ad",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:38:19.941577Z",
"start_time": "2024-05-27T13:37:44.523166Z"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"# If you want to restrict the list considered you can choose from the list outputted above\n",
"# instead of taking all of them...\n",
"#marginal_params = samples.keys()\n",
"marginal_params = [\"Deltam2_32\", \"Theta13\", \"Theta23\", \"DeltaCP\"]\n",
"\n",
"fig = plt.figure(figsize=(8, 8))\n",
"\n",
"nrows = ncols = len(marginal_params)\n",
"shared_xaxes = []\n",
"shared_yaxes = [] \n",
"for row, param_y in reversed(list(enumerate(marginal_params))):\n",
" for col, param_x in enumerate(marginal_params):\n",
" #ax = axes[row][col]\n",
" if col > row:\n",
" continue\n",
"\n",
" # we do this complicated dance instead of just using plt.subplots()\n",
" # so that we don't wind with 1D marginals sharing y-axes with the 2D ones\n",
" kwargs = {}\n",
" if row + 1 < nrows:\n",
" kwargs[\"sharex\"] = shared_xaxes[col]\n",
" if 0 < col < ncols - 1:\n",
" if col < row: # only \"middle\" panels share axes (with the leftmost neighbor in the row)\n",
" kwargs[\"sharey\"] = shared_yaxes[-1]\n",
" \n",
" ax = plt.subplot(nrows, ncols, row * ncols + col + 1, **kwargs)\n",
" ax.set_xlabel(PARAMETER_LABELS[param_x])\n",
" if col < row: # the last one is the special 1D marginal...\n",
" ax.set_ylabel(PARAMETER_LABELS[param_y])\n",
" elif col == row == 0: # but we only want to label it for the topmost row...\n",
" ax.set_ylabel(\"Posterior density\")\n",
" else: # otherwise it gets in the way\n",
" ax.set_yticks([])\n",
"\n",
" if any(\"share\" in kw for kw in kwargs):\n",
" ax.label_outer()\n",
" \n",
" if \"sharex\" not in kwargs:\n",
" shared_xaxes.append(ax)\n",
" if \"sharey\" not in kwargs:\n",
" shared_yaxes.append(ax)\n",
" \n",
" # this is the 1D marginal\n",
" if col == row:\n",
" ax.hist(vals[param_x], density=True, bins=100)\n",
" # this is a 2D marginal\n",
" else:\n",
" binc, xedges, yedges, image = ax.hist2d(vals[param_x], vals[param_y], density=True, bins=[50, 50], vmin=0, cmap=\"Reds\")\n",
" \n",
"plt.subplots_adjust(wspace=0, hspace=0)\n",
"plt.show()"
],
"outputs": [
{
"data": {
"text/plain": [
""
],
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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 17
},
{
"cell_type": "markdown",
"id": "c8e71585010c19d1",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"source": [
"## Credible intervals/regions\n",
"\n",
"Bayesian credible regions are defined as an interval (1D) or region (2+D) containing a specified fraction of the posterior probability, in analogy with frequentist confidence regions.\n",
"Credible regions require a specification of the procedure used to select regions of the posterior to sum to the desired total posterior amount.\n",
"In our credible regions, our convention is to sort the marginal bins by content in one dimension, then to find the interquantile range(s) that correspond to the desired fraction(s) of the posterior in this sorted space.\n",
"All bins in the marginal posterior distribution with content larger than or equal to the resulting quantile boundaries are deemed to be within the corresponding credible interval/region.\n",
"The credible regions/intervals obtained by this procedure are so-called \"highest posterior density\" regions/intervals. \n",
"\n",
"We illustrate this in one dimension with one of the marginals from above. The next section uses it in two-dimensional marginals as well."
]
},
{
"cell_type": "code",
"id": "95dfa21b4f4df3d",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:38:19.947286Z",
"start_time": "2024-05-27T13:38:19.943221Z"
}
},
"source": [
"import collections\n",
"import numpy as np\n",
"\n",
"def quantile_thresholds(arr, quantile_levels):\n",
" \"\"\" Obtain the threshold values denoting where \n",
" intervals or contours enclosing a specified fraction\n",
" of a histogram would fall.\"\"\"\n",
" \n",
" assert all(0 <= f <= 1 for f in quantile_levels)\n",
" \n",
" arr = arr.flatten()\n",
" total = np.sum(arr)\n",
" breakpoint_sums = quantile_levels * total\n",
" sorting_indices = np.argsort(arr)[::-1]\n",
" cdf = np.cumsum(arr[sorting_indices])\n",
" \n",
" # searchsorted() returns the index where a value could be inserted into the list without changing the sorting\n",
" return (arr[sorting_indices[np.searchsorted(cdf, qlevel)]] for qlevel in breakpoint_sums)\n",
"\n",
"# use an OrderedDict to ensure that they always come out in this order\n",
"QUANTILE_LEVELS = collections.OrderedDict([\n",
" (0.683, r\"$1\\sigma$\"),\n",
" (0.955, r\"$2\\sigma$\"),\n",
" (0.997, r\"$3\\sigma$\"), \n",
"])"
],
"outputs": [],
"execution_count": 18
},
{
"cell_type": "code",
"id": "64a6acb008000572",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:38:21.022095Z",
"start_time": "2024-05-27T13:38:19.948305Z"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"binc, edges, curves = plt.hist(np.rad2deg(vals[\"Theta23\"]), bins=250, density=True, histtype=\"step\")\n",
"quantile_levels = list(reversed(QUANTILE_LEVELS.keys()))\n",
"quantile_labels = list(reversed(QUANTILE_LEVELS.values()))\n",
"threshs = list(quantile_thresholds(binc, np.array(quantile_levels)))\n",
"print(\"Sigma thresholds:\", list(threshs))\n",
"\n",
"min_alpha = 0.2\n",
"alpha_diff = (1 - min_alpha) / len(threshs)\n",
"for tidx, thresh in enumerate(threshs):\n",
" plt.fill_between(edges[:-1], binc, where=binc > thresh, step=\"post\", color=curves[-1].get_edgecolor(), alpha=min_alpha + alpha_diff*tidx, label=quantile_labels[tidx])\n",
"\n",
"plt.xlabel(r\"$\\theta_{23}$ (deg)\")\n",
"plt.ylabel(\"Probability density\")\n",
"plt.legend()\n",
"plt.show()\n",
" "
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sigma thresholds: [0.004276894842219119, 0.03873316091688087, 0.0852277296207986]\n"
]
},
{
"data": {
"text/plain": [
""
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 19
},
{
"cell_type": "markdown",
"id": "747e10a677c0a7c4",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"source": [
"## Transformations\n",
"\n",
"A sensible thing to want to do is to transform the quantities that were sampled into some other quantity that can be computed from them.\n",
"In principle, this is as simple as performing whatever operation you want to on the samples as you accumulate them in histograms.\n",
"\n",
"**However**: because the result of histogramming MCMC samples is actually a probability ***density***, what's being plotted is $P(\\vec{x}) d\\vec{x}$.\n",
"Therefore, to change variables, you must incorporate a Jacobian factor to account for the change of the differential.\n",
"This is the reason why we supply the chain with samples in $\\theta_{13}$ rather than $\\sin^{2} (2 \\theta_{13})$, for example: the Jacobian factor of $\\partial(\\theta_{13})$ is simply 1, whereas to convert in the other direction you would need a Jacobian factor $\\partial(\\sin^{2} (2 \\theta_{13})) = 2 \\left| \\cos (2 \\theta_{13}) \\sin(2 \\theta_{13}) \\right|$...\n",
"\n",
"Moreover, even though the variables themselves have been transformed, the _priors_ on those variables remain whatever they were during sampling unless a further transformation is applied to them as well.\n",
"See [Changes in prior](#Changes-in-prior) below for guidance on how to reweight to alternate priors.\n",
"\n",
"Here we demonstrate some of the transformations that can be made by showing our marginals in the traditional $\\left( \\sin^{2} \\theta_{23}, \\left| \\Delta m_{32}^2 \\right| \\right)$ and $\\left( \\delta_{CP}, \\sin^{2} \\theta_{23} \\right)$ planes."
]
},
{
"cell_type": "code",
"id": "c34446dddda0c327",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:38:50.000684Z",
"start_time": "2024-05-27T13:38:21.023712Z"
}
},
"source": [
"import numpy as np\n",
"\n",
"TRANSFORMED_PARAMETER_LABELS = {\n",
" \"ss2th13\": r\"$\\sin^2 \\left(2 \\theta_{13}\\right)$\",\n",
" \"ssth23\": r\"$\\sin^2 \\left(\\theta_{23}\\right)$\",\n",
" \"abs_dm32\": r\"$\\left| \\Delta m_{32}^2 \\right|$ ($10^{-3}$ GeV/$c^2$)\",\n",
" \"dcp_pi\": r\"$\\delta_{CP}$\",\n",
"}\n",
"\n",
"CUSTOM_XTICKS = {\n",
" \"dcp_pi\": ( np.linspace(0, 2, 5), [\"0\", r\"$\\frac{\\pi}{2}$\", r\"$\\pi$\", r\"$\\frac{3\\pi}{2}$\", r\"$2 \\pi$\"])\n",
"}\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"vals[\"ss2th13\"] = np.sin(2 * vals[\"Theta13\"])**2\n",
"vals[\"ssth23\"] = np.sin(vals[\"Theta23\"])**2\n",
"vals[\"abs_dm32\"] = np.abs(vals[\"Deltam2_32\"] * 1e3)\n",
"vals[\"dcp_pi\"] = vals[\"DeltaCP\"] / np.pi\n",
"\n",
"contour_levels = np.array(list(QUANTILE_LEVELS.keys()))\n",
"contour_labels = list(QUANTILE_LEVELS.values())\n",
"for xvar, yvar in ((\"ssth23\", \"abs_dm32\"), (\"dcp_pi\", \"ssth23\")):\n",
" binc, edgesx, edgesy, image = plt.hist2d(vals[xvar], vals[yvar], vmin=0, density=True, cmap=\"Reds\", bins=(100, 100))\n",
" for ax in (\"x\", \"y\"):\n",
" getattr(plt, f\"{ax}label\")(TRANSFORMED_PARAMETER_LABELS[locals()[f\"{ax}var\"]])\n",
" \n",
" if xvar in CUSTOM_XTICKS:\n",
" plt.xticks(*CUSTOM_XTICKS[xvar])\n",
" plt.colorbar()\n",
" \n",
" # plot some contours too\n",
" contour_breakpoints = np.array(list(quantile_thresholds(binc, contour_levels)))[::-1]\n",
" C = plt.contour(edgesx[:-1] + (edgesx[1:] - edgesx[:-1]) / 2, \n",
" edgesy[:-1] + (edgesy[1:] - edgesy[:-1]) / 2,\n",
" binc.T, levels=contour_breakpoints)\n",
" labels = dict((k, v) for k, v in zip(contour_breakpoints, reversed(contour_labels)))\n",
" plt.clabel(C, fmt=labels, inline=True)\n",
" \n",
" plt.show()"
],
"outputs": [
{
"data": {
"text/plain": [
""
],
"image/png": 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e1mw2c3xPGlt/3s/2FftJ2ZfetE5v0PPnhQ8x/vqhwnCX7jUnjRH7ceoE1vXr1zNnzhwSExOpr6/n2WefZdq0aRw+fBhPT88W96mtrWXq1KkEBwfzzTffEBERQVpaGn5+fhd38p2QlZ9tJj+rmKBIf66ZfVlHT+e88QnwYubvpjBofB9euutd+g7rYe0ybkbjDXnL8r3U1dRz2czhF2uqEonDqK2pY/XnW1n28XoLY8DoYmDijYnMmjuV2IFR7XJsnU5Hn2Ex9BkWw73/dz1nTheyfcV+fv1qOwe3pvDKve/z54UPMv76Ye1y/C6Lotj/IOWkRqFTe0ZE8vLyCA4OZv369UyYMKHFbd59913+/ve/c/ToUYzGFtQ7z4Ou6BlRVZWHRr5A6pEsHn79Fmb+bkrztW0ez6HYvHjOrq8oqUSn1wkJt9bjFZ0pZeP3Saz430Zqqup49I07GDShr2PmK5G0F6pKVUUNPy/cyNdvriQ/qxjQDOz+I2OZfPMIJs4agY9/yw9rNgYXltv+o2WqN/H6Qx+z9usd6PQ6nn7/fibfPLJhOOf8EXQEF8sz8mtwBF52ekbKzWYmn8mUnhF7KCkpAcDf/9waEz/++COjR49mzpw5/PDDDwQFBXH77bfz9NNPoz9HYmNNTQ01NTVNy6WlpS1udymzf/MxUo9k4ebhwrTbx3T0dC4YT1+P89quW7APU+8Yw7jrh7Lif5t4+Z73mP3SLK68a1w7z1AiuTDys4tZ/tE6ln6wjpICTaU4IMyPmx6dxuW3jGrVG3ix0Bv0PP3BbIwuBlZ9voXXHviI2uo6rrxbXleS1uk0xojZbObxxx9n7NixxMfHn3O7kydP8uuvv3LHHXfw008/kZKSwu9+9zvq6up4/vnnW9xn3rx5vPjii+01daenMLeEfz/yKQCTbx6Jl587rXpDRE9IRzvXrB64bDyBNczX3cMFdw8Xbv/D1dTX1rP5x91MunEEru4u7TJNiaTNqCqpRzL54h8/sf67JEz1JgBCewRy6xNXMfWO0bi4NnqAHX0dtnU87brT63X8/u17MLoaWP7xBv455xPSk7N58OUbLUMMl7CnpL24lHvTdBpjZM6cORw8eJBNmza1up3ZbCY4OJj3338fvV7PsGHDyMzM5O9///s5jZFnnnmGJ598smm5tLSUqKj2ibU6G6qq8vffLuB0Si4BYX7c+vurOnpKF4WUfemk7EtvemJTdDpOHDgtE1slTkPakSw+nfcjG5Yk0RhNjx8dx4zfTmbcdUOdurO1TqfjsX/fibefJ4v/9TNfv7mK4VMGMHRS/46eWqdGcUDOiLPe4zqFMTJ37lyWLVvGhg0biIyMbHXbsLAwjEajRUimX79+5OTkUFtbi4uL9VOvq6srrq6uDp93Z2DZx+vZ9cshjK4GXv/xCcJ6BHHxS3cvHqqqoigKlWXVzP/DF3z71mqGTRnAd2/9wu1/uBpTs1JIAJPJ3LLKq0TSTqQnZ/PZa0tZ983OJiNk/PVDue2p6fQaHN3Bszt/FEVh9oszqa6q5ft31rDgpe8ZMrGf0/4YdgZ0ivaydwxnxKnvsqqqMnfuXJYsWcKvv/5KTEyMzX3Gjh1LSkoKZvPZH5Vjx44RFhbWoiHSlTmdksv7z34NwAMvziK6b3jLG6pq6y9svFRz214292/bfNSGMWuqapo8wwnjevPBjhfx8HbHYNDzyrePcs//XYe7h+U5otfrUFXV4nySSBxGs/NWNZv5/PWlPJj4HGu/3oGqqoy9dgjvbnmO5z57uMEQae06u8gv6z9GeGnc9vurcPNw4eiuU2z7eX97f6KSTopTGyNz5szhs88+Y9GiRXh7e5OTk0NOTg5VVWeVN++++26eeeaZpuWHH36YwsJCHnvsMY4dO8by5ct59dVXmTNnTkf8CU7NG4/8j+rKWk2L4OHJHT2ddkNRFPKzi/nfKz9SXqzJXtfX1RMaHciQSf3Yu+EoiVPjURSFY3vS+Pcj/+O1Bz7kLze9yf5Nx1AUBZ1O1xSvl0gcTWlhBS/e8Q4L//oDZrPK6OmDeGfzX3hh0e/arTz3YuEf4sv1v9HuL5+88gOdqIDT6VB0ikNeF8prr72Goig8/vjjTe9VV1czZ84cAgIC8PLyYtasWeTm5rZ5bKc2Rt555x1KSkqYOHEiYWFhTa8vv/yyaZv09HSys7OblqOioli5ciU7d+4kISGBRx99lMcee4w//elPHfEnOC1FeaXs33QMgKfevhedneVizk5mSi47Vh9kyTtrqK+rx2DUIpQVJZUERfhjNpv59q3VvHjH25w4kEFUr1C69wnjmRlv8LeHPqK6ssapY/SSzsuBzcf47diX2Lx0Dwajnif+ezcvfTmXuITuHT01h3Hz41fi5uHCif0ZHNlxsqOn02lpbJRn7+tC2LlzJ++99x4JCQkW7z/xxBMsXbqUr7/+mvXr15OVlcXMmTPbPL5T54ycjwW9bt06q/dGjx7Ntm3b2mFGlw6HtqYA0KN/BCHdAzp4Nu3PoPF9eOyNO/jbbxewaekeLrthOPs2JlOYU8Lgif3YvHQP7//fN/x23s1cefe4Jp2SkO6BvPX7RWz9aR+3/v4qbnmiayT4StqfM6cL+fy1paz43ybMZpWI2GD+vPChTpUXcr74+Hsy4YbhrPp8Cz9/srFZB3BJZ6C8vJw77riDDz74gJdffrnp/ZKSEj766CMWLVrE5Mma92vBggX069ePbdu2MWrUqPM+xqX9OCw5J4e2aZ1vB4yKpc2xZ1vbm82WL6sxbOSMmE2Wrzbvb/lSG17xo+P4375XmHb7aFKPZOHl58FNj01j5sOX8/V/VjHpxkRuePhyXFwNTccy1ZsI6xlE3+Ex7Fp9qIO+LUmnpYXrp/hMKe8+vZh7Bz3LTws3YjarTL19NG9v/Au9BnfnvPNCbF5ntq4bO3NE2phDctU94wFY9+1OyooqzmN/iYgjPSOlpaUWr+ZaWyJz5szh6quvZsqUKRbvJyUlUVdXZ/F+37596d69O1u3bm3T3+bUnhFJ+6CqKttXaIlkCeN6d/Bs2p/G7H1TvQm9Qc+suVMtQjUp+zM4uusUD7w0y2K/tKNZJCedIjjCnz99+ACevu4ATRU5EklbqCip5Lt31vDNf1c3dZxOGNeb+5+/gQGj4hq2unR/lAeMiqVnfCQnD55m/h8X8/T798vrqI04srRXlK94/vnneeGFF6y2X7x4Mbt372bnzp1W63JycnBxcbFqtxISEkJOTk6b5iWNkS7Ivo3JZBzPwc3TlZHTBnb0dC4aeoO+KfTXaIgA+Ph7Ed0vnCM7T5Iwrjc6vY6q8mo+fmEJxfll3PLkVfgGejdV1MgbqKQtVJRWseSdNXz71uqmBOq4Qd2Z/eJMhk3u32XOJ0VRmPuP23jq6n+yZvE2eg+ObtaMU3KxycjIsJCDb0neIiMjg8cee4zVq1fj5tZKiw0HII2RLsj37/4KwNTbRjfIp1+6T2MiSgsZXMGR/ky5dRSfvPwDaUeyKMgtoSCrCFcPF+577gaGT9EUfy/1JF+JYzGbzSz/eD0LXvxeC0sA3fuEcdcz1zLhhmFd8nwaOLY3v3n1Jt55+kve+/PX9BgQwdCJ/Tp6Wp0GexJQm48B4OPjY7M3TVJSEmfOnGHo0LMdmE0mExs2bOCtt95i5cqV1NbWUlxcbOEdyc3NJTQ0tE3zksZIV6BZPPZMRgFbl+8F4LqHJp7vAOccr8VlcXuzLWNHXC9cbYq51dWo4vbiBsJyC9vf8vg0xl4ziJWfbSGqdygRccEMm9wfTx93UNXWQzNd5MlWch40XAunDmfyrzmfcHTXKQCieody55+u4bKZw5uJ6J0jD+M8xj/n/m0Zy9b+4nltNZ6N8/4c18UND19Oyt50Vn+xlZfvfo+3N/4fodGBrY8lAS6+Auvll1/OgQMHLN6777776Nu3L08//TRRUVEYjUbWrFnDrFlamDs5OZn09HRGjx7dpnlJY6SL8cvibZjNKoPG96FHv4iOno5ToImaqUTGhTD7hRssbqKNRkhLF/C+jcn0HR6Dq0fXVO+VWGM2m/nmzdUs/Ov31NXW4+Htxr1/mcF1D05sKA3vOl7Ic6EoCo/9507SkrM4tjuNL99YwWP/vrOjpyVpAW9vb6tecJ6engQEBDS9P3v2bJ588kn8/f3x8fHhkUceYfTo0W2qpAFZTdPlaFRAnHhjYgfPxHlQFAW9XteUE9K8pPxcTxGZJ87wzA3/5sGRL7Bz9cGLMk+Jc1NZVs2Lt7/DB3/5hrraekZdNYiPkv7KDQ9fLjVqBFzdXbj3/2YAsHnpHqs2DJKW6UidkXPxxhtvcM011zBr1iwmTJhAaGgo3333XZvHkZ6RLkRRXmmT23jUlQnn3rBNruKWls021rfx6VC8emyFYWxtL8bqG6ajUxRoDMc0n2MLF29BdhG+AV5kn8rj2Rv+zfgZw/jd67cQGN7N9vwlnZdznLtZJ8/w/K3zST2ShdHVwNy/38ZV945v+OrVc+/f1lCK2spYtvZtK7bCn1bhUhvjCdsPvqwv3t08KDpTyu61h0mcInRjl9eNFTpF0e5Tdo5hD6K2l5ubG/Pnz2f+/Pl2jSs9I12IHSsPoKoqvQZ3b/lHU3LeJIzrzUe7XmLWnCno9Do2fp/EgyNfYMWnm6XcdReiMLeEz15fxpzLXiH1SBb+ob78a8UfmX7fhC5TJXOhGF0MXH6L5spf9uH6Dp5N58AZPSOOQhojXYiTB08DkDCuTwfP5NLAw9uN3752M29v/D/6DOtBeXEl//zdQv50/Rtkp+Z19PQk7YSqqhzefoJ5sz/gjn5P88nLP1BeXEnf4THM3/B/9B1uu6GnROOa2ZehKApblu/l8I4THT0dSQcijZEuRGlhOQDdglsv55K0jdiBUfznlz/xwEuzcHEzsnvtER4a+QLfv7tGdvu9xDi45ThzJ77CY1Ne49evdlBfZ6L/iFj+9OFs/rXyjwSG+XX0FDsV0X3DmXbHGADe/dNX0qtoAwWlKaH+gl+2qqA6CJkz0oUoLdC0Dnz8PWk1ji1iq3RXzBERf4CF9dY3nLbdgBRFJ75huawTkgXF2Ld4PHG88ygFFjfXG3Tc8sQVjL12MG888in7Nx1j/h8Ws23Ffp565z7LHyln9ZNKrGk4V4vzyvjgL9+w6vMtABhdDUy+aSTXPTSR3kOa95Kxswy+LdtbrbLzh9zqvBbn0sb9z5P7np/B+iW7OLLzJGu/2cHkm0Ze0DhdAUXXwu2qrWM4qb0nPSNdiJKCMqDRGHFuzGaV+npzp3tSiowL4e/Lf8+cf9yGi5uRpDWHeWjk86z5clun+1skGoe2pfDQqBeaDJHp945n0ZG/8dQ79wqGiORCCAj149bfaw0oF/71B3mddFEc4hmpq6sjJyeHyspKgoKC8Pf3d8SwEgdiqjeRejgLgMheIR08G42CwkqOJOdzJPkMR5Lzycktp6a2npoaE7W1pqbtdDoFvV4hwN+DIQmhDBsSwZBBYfh4O6e+h06nY8ZvJjPksn68/uCHHN+bzmsPfMSK/23izj9dS8L4PjK5sRNwfG8aX/17BRuWJGE2menRL5wn3rqb/iNkx1lHM/Phy/nkrz+QfSqPojOl+If4dvSUnBMHiJ45q2f2go2RsrIyPvvsMxYvXsyOHTuora1tEoiKjIxk2rRpPPTQQyQmSj0LZ+DkwdPUVNXi5edBVO+2yfQ6koqKWtasP8lPK49x4lTRee1jNmuiZDm55fy8OoWfV6egKDCgXzDTp/VmwrgeuLo6X8Qxum8Yb/76DF++sYLPXlvG3g3J7N2QTPzoXtzxp2u6VF+SzsSuNYf48l8/s3f90ab3Jt6YyJP/vRt3r/btz9FVcfdyIyI2mNMpuZw6lCmNkXPgSDl4Z+OC7uD/+te/eOWVV4iNjeXaa6/l2WefJTw8HHd3dwoLCzl48CAbN25k2rRpjBw5kv/+97/06tXL0XOXtIHDO04C0Hd4zHn0xLARtxbl3W3liJhNnM4s5aslh1i7MZWaGs3rodMp9OjuS99eAfTvE0h0lC/u7gZcXQy4uurR63WYTOamV1pGKUn7cti9L4fU9BIOHj7DwcNneOfDHUyZ2JOJE3rQJy4And7y+IqYQyJGJ61kS2zpmtj4/JptbjDqueOP1zD1ttEsfmMFKz7ZxMGtx3nm+jeYcMMwnnr7Xty93VsfT9J+NDu3y4srefvpxaxepLU+1xv0TLwxkRsfmUpcQvfGHc65f4vLNrcXr51zz89qA1tjWWHjvLZSe7dxnVgNbyPHxOo6stwgZkBEgzFymmGT+9s4mORS44KMkZ07d7JhwwYGDBjQ4voRI0Zw//338+6777JgwQI2btwojZEO5uguzRjpP6LnRT/2iVNF/OH/VlNeUQtA90gfrp4Wx+UTY7RQy3mKNwUHeZI4NAwUHXn5lfyy7hQ/rU4h90wFS5YdZcmyo/h3c2NkYhSjR0QxJCHUaTwmwVEBPPqvO7j9D1fz9X9W8uP7a9mwJInkpFSenH8PQyfJm29HYTabWfX5Vj567luK88vQ6RSu+81kbnp0GsGRMuR8sYiJj2TjD7tJ2Zfe0VNxWjTPiL29aRw0GQdzQXfqL7744ry2c3V15be//e2FHELiYHJS8wGI6h12UY+bfrqEP73wC+UVtfSO8+c39w0nvl+A3RdUUKAHt904gFtm9idpXy6rfj3BzqQsCouq+XnVcX5edRxfH1duu2kg107vh4uLcxglgWF+PPzaLYy7dgivP/QxuekFPH3tv7jq3vE88NIsfPy9OnqKXQZVVdmxYj+fvb6sSZm4e58wnnjzLuLHyIeni01jLs7BrSkdPBPnRYZpJJ2evEwtP6PFJ702y0q37h5WzVoYJju3nKf/soqSkhriYrrx2vOT8PJ0AbNJ2L+Nru5m7mMdkJgQSGJCILV1JvYfymN7Ujabd5wmv6CKdz/axbc/HOauWxKYOilG65gqhG2swjhWyzb908J0bcvTDxzbiw+2P89HLyzhh/fW8vPCjaz7ZgfX3H8ZM+dObV2vwlnvJs5IC+e2qd7E+iW7+PJfK5qEAN29XLnrmeu44eFJGIwGms45e8verUKYbW2dcO71NkvkxfU22igoVm0ShP3F9WIYx9bxbKzvP6IneoOe3PQC0pOz6d43HEnXoc2lvVVVVWRmZlq9f+jQIYdMSOJ4TCbzWWMk6uK4nfMLKvnTc7+QX1BJdJQP8xoNkXbExahn+OBQ5jw4jP+9cy2PP5xIoL87efmV/Gv+Nh58dBkr15ygrs5ke7CLgLuXG3P/cRv//PkP9IyPpKq8hq/fXMXd8c/w78c+JevkmY6e4iXHoW0pPDjiBebd/yEnD57G3cuVmx6dxoI9L3PTo9MaDJFLh7LyGk5nllLrJOd8a7h7uTH8ci1c+cvibR08G+eksTeNvS9nRFHbUNT9zTff8PjjjxMYGIjZbOaDDz5g5EhNoGbo0KHs3r273SZ6MSktLcXX15eS7HR8fDq/Wml+ZiG39fkjOr2OnwreQa8XTkYrlVDx6U64kYnbm+otFisra3j86RWcSismLMSLf71yOQH+Hucezw7PiLZ87kZ4NTX1LF15ksXfHqK0rAaAwAAPZl7Xj+nTeuPhYWy7Z8TW8dvauA9FCxmsOsjif/7U5KZWFIXR0wcxc84UEsb1PhvactKbiVPScC5VV9aw8K8/8N38X1BVFR9/L2743eVc9+AkQXenjY3sOtgzUlxSTcqJAgqLqigsqqKouIrCwiqycsrIzilvytPS6xUiw33oEe1HbIw/gxNC6RUboHkKG7DyjIjnsbjelqfE1nXSwnWw5sttvPbAR/Qa3J23Nz1HZ6G0tBTfsO6UlJS0y29G42/Swf6xeOvt6wBdZjIRf/hEu831QmnTY8DLL79MUlISISEhJCUlcc899/Dss89y++23S6EaJyY/qxiAgFDfhptP+31Xqqry7/nbOJVWTDc/N15/aQoB/h1XLeLqauDG6/sxfVocy1ce57ulR8kvqOT9BUl89d0hHrh3GFMn90JnMxTTviiKwsgrBjLyioHs33SMxW/8zM5VB9myfC9blu8lNiGKmx+/gstmJsp29G1AVVX2bzrGG4/8j8wTmqdp2h1j+O28m/Hu5vzifyKlZTXs2p3JgUO5HDiUS1pGic19XF301NSaSMsoIS2jhPWb0gDw9nJhyKAwEodGMGFsNB6eHa/b03+kljdy6lAmtTV1uLgaO3hGzkWjpLu9YzgjbTJG6urqCAnRBLOGDRvGhg0buOGGG0hJSXHaP7BLIhiGBdnFAAScb98Mq6czYb1ZlHc/u/zdj0dYuzEVvV7h/54aS2iQO5gtPSeYRM+IKCffRpeyTc+GCQ8XuOnaOK6/MoY1G0/z5ZLDZGWX84//bOanFcnMeSiRXrEBAChWT6PieMLxrSp/RTl6G/MX9k8Y14uEcb1IO5rN9+/+yupFWzmxP4N593/IZ/OWcdtTVzHpphEthxQu9evwPB96ctLyWfPVdtYs3kbGsRxAO/+f+O9djLxiYONgtsdvq+fDar0tT4eYb2W9Pr+gki3bM9i8LYN9B3MxC2NGRfgQEuRBt25udPN1o1s3d0KDPQkP9SI0xAs3Vz15BZWkppWSml7M0eMF7NmfS1l5LRs2p7FhcxrvfbyT6dN6cd30PgQHaUaalcdQzIUS/zad6MG0qu3FFqHRgfj4e1FaWM6pQ5n0GdrD5j6SS4M2GSPBwcHs37+fhIQEAPz9/Vm9ejX33HMP+/fvb5cJSuwnv63GyAVy4lQh7y9IAuChe4cwsH9wux7vQnAx6rlqSixTLuvBkuXH+OyrgxxOzmfuUz8zcVwP7rhlINHdnaOcM7pvGI/9+w7ue+4GfvxgLd/NX03G8Rz+9psFvPvM11w2azhX3T2OXoOlJLmqqhzbk8aWZXvYsmwvqUeymta5uBmZettoHnhpFl5+nUPTpaqqjo1b01m9JoV9B3Mt1sVE+zEkIYSB/YOJ7xeEr0+jR+PchlpwoCfBgV6MGKYlhZpMZpJTCtm1N5tfN6SSlV3OV0sO893So9x1awK3zByAvgOahSiKQu+h0ez65RDHdqdKY0RAVtM08Omnn2IwWO7i4uLCF198wdy5cx06MYnjSE/OBiA8Jqhdj/PpF/sxm1XGjIhkxvTe7XosezEa9dw8ox+Tx0fzwf/2sXZjKms3prJ+cxqTJsRw562DiAx3jniqj78ndz59DTN/N4UfP1jLt2+tpjivjKUfrGPpB+uITYjiyrvHceVdY3Hz7FoKoYW5JXzz5irWfbuzKUkbtB+1QeN7c/mtoxl//VA8fRqNEOcOJycfz2fpT8ls2JJGdbXmUVQU6NcniLGjohg7IoLwMG9tYztC43q9jv59g+jfN4g7bx7I9qRMvv3hKPsPnWHBZ3spKKxk7m9GdYjHu0e/CHb9cojME7m2N+5iSGOkgcjISKv3tmzZgo+PD2PHjnXYpCSO5eSBDAB6Doxqt2OcOFXIlu0ZKArcf2dCpwnbBQZ48Mzvx3HzDf353+L9bN1xmjXrTrJ2wymmXR7HfXcOwT/AObQ/PLzduPXJq7jp0WnsWX+UlZ9uZvPSPZzYn8H8p77gmzdXMecftzF6+uCOnmq7U3SmlC/fWMHSD9dRW10HgJunK4lT4xl37RCGT4nvFA0hAerrzWzamsaSHw9z+Ghe0/vhYd5Mm9yTKRN7NoVObKusth2dTmF0YiSjEqNYvuo4/313Bz/+dAxvLzfuvXOIw49ni5BoLVyam1Zw0Y8t6TjsrmObM2cOc+fOJT4+3uL9EydOEBwcjLe3t72HkLSVZoaA2Wxu0lKIHdhgTLa1QuA84uaLvjwAwISx0XQP97LM+xBzREx1lst1tZajC9U5VghxdcUgJLmJsW6jUFIsyMWj0xPb3YsX/ziGYycK+fTrw2zflcWK1cfZuj2dTz+ciVszJVelBf0Fk8lsUZlgOUEbSSY2dUmE6Rt0DL+8P8Mv709pQTm/fr2Dr99cRW56Ac/d/Bajpw/i7j9fR+zAKNtGobMZjS2cm3mZhZw8mElJfhl5mYWcTsll4/e7qanSzpt+iT255YkrSZwaj4tb81uaA3JCbG1v1Sqh9Xyo5jkhdXUmVq4+xqJvDpFfUAmAwaDjsrFRXD0tjgF9A8+ea/W11sdrq2fERlWYotNzzbQ4VLPKf9/byedf7cfT08iNM7RyW8XWeWqzEsnGfBvGC4lqMEbS81vfvgui6BQUO5Ptrb5HJ8FuYyQ5OZmJEydavf/LL7+wdOlSli1bZu8hJHZQmFNCZVk1Op3Sbg3ycs6Us2mbJuF8+43xNrZ2bnrH+vPXZy/j0NE83vloN0MHhVoYIi2RnV3Kz6uO4efnxoxrB1hVPLYnPgFezPjt5Vxx1zgW/W05X7+5iq0/7WPrT/vw7ubJgJGx9B8ZS/zoOPom9sToJEq0tjDVm9i+4gDLF2xg5+qDLVbr9R0ew93PXsfwKQOaGV3OHYYBqK01sWL1cb787iB5+ZoR4ufrxjVX9uKaaT3x79Ysr6UDqhSvvbIX5eW1LPh8H+8vSKK8opZ7bh90HumnjiG0wTOSeTIPs9l8Hr20ug4yTNMKPj4+FBVZd18dP348f/7zn+0dXmInjaVxYga+I/l5dQqqCkMGhRIT7Wft+eiEDOgbxJuvT6PeZNstvu9gDrlnyjl4KIcvvtzHbx4axZTJF1dO3N3TldkvzmTKbaP45JUf2b5iP2VFFWxbsZ9tK7Tkcg9vN4ZM7MeIaQMZMS2ewPBuF3WOtjDVmzi8LYVtP+9nzVfbm6rAAHr0jyAgzBf/EF/CewbTf0RPhkzs12nCgQC1tfUs+zmZL789SGFRFQD+3dy5ddYApk+Lw8WoB9U5xMlundWfunqVz77cz6KvDuDj7cqsGRfnQSOqdyjuXq5UllZxYn+GTNDuIthtjFx55ZX84x//YPHixRbv63Q6amtrz7GX5GLh6eeBomiiWmVFlXQLbikps41y8M2e1kwmMyvXaE34rp4aq7mlrUTRBOOkpspyuHphfW2N5bKNUl9VDMuIokAGyzCNIoZtxOWG7XWAi8JZF3nT8Sz/visn92TyuGjMqsrGLWks+mIPoYEexA9o8ESJJY5WYlE2ugLbktluthjdN4znPv0NdbX1nNifweHtJzm0PYX9m45RnFfG5qV72Lx0D6BpOky6aQSX3TD8HOdF+1FTVUtOWgE5aflkp+ZxaFsKSWsOUVZU2bSNX6A30+4cw1X3jCMyLuQcIzm6i24bu+yKZe4thGlq60ysWJ3CF98cpKBQO/eDAj245YZ+XDkpGhcXPWDSwplWHbFbCfvYyh8Rw4NmG6Jlzf5WBbj7lgF4uOl4/5O9fPTJbhLiQ4jrGdBsGxtif1alvq1Pt/G7MRj1JIztzfaVB9iz9gi9BjV0TO5Ehmd74QgFVWdVYLXbGPnrX//KiBEjmDVrFi+88AIDBw6kurqa119/vakEWNJx6PU6vPzcKSuqpLSw3OE/Ott3nqawqAo/X1dGJ0Y4dOzOgKqqKICLix6zWWXiuB78tPI46zelnjVGOgCji4G+w2PoO7wnM+dMwWw2k7Ivgx2rDrBz1UGO7DzJ4e0nOLz9BO/8cTHxY3oRGh2IX5A3foHe+AR44eHthpunKx5ebnj4uGvv+3u2KrpWV1vP8b1pZJ/Kw1RvxlRvwmxSKS+pJDs1j+xTeWQczyXvdGGL+/v4e5E4dQBjrhnCqKsScHGSrssXQklpNavXpDQJ7UFDg8dZA7hicgxGo95ag8fJmHVdXw4cyWPrjkxe/ftG5r9xNe5u7S9ENmRiX80YWX+Emx+/ot2P11mQYZpWiIqKYtu2bTz88MMMGjQIV1dX6uvr8fX1ZenSpY6Yo8ROjA2hmpoqx4dP1m1KBWDKxIabaxej+YOzTqeg0+mprKxttl51iotfp9PRe0g0vYdEc+fT15CfXcyG73ax9psdHN11iv2bjrF/0zGb4yiKgo+/J92CfQiM6EZgeDeCI7thMqkc2nqcIztPNSWW2sLD243QHoGERQfSo38EiVPj6ZvYU0gEdv4cEJFDR86w9OdkNm5Oo65e814EBnhw243xXDG5hxaO6SQoisLv54zktyk/czqrlM8W7+fBe4e1+3Ebuyan7Etv92NJnAOHPHZER0fz008/kZ6ezt69ezEajYwcORJ/f+cQj+rKmOpNFJ8pBSAgzNehY5vNKrv3auJSXckrohkYmoXRXEb+8NE8Vv5ynKycMp58dBxgKb3cmLfjDPl4gWF+zJwzhZlzppB18kxTGKc4r5TignJKC8qpKq+mqqKGqvJqyourKCuqQFVVSgrKKSkotxAWa453N09iB0ZidDWi1+vQ6XW4e7kS2iOI0OhAonqFEBkXgk+AV6fK+bBFfkEF89/bxqatZ39Ae8X6c82Vvbj8sp5aOKat6sJOgI+3K4/+NpHnXt3Atz8c5vKJPenZo33zjXwbyukry6rb9TidDSkH3wLPPfcc119/PcOGnbWSu3fvTvfu3R0yMYkdNHtcL8guxmxW0Rv0rYRobJToWQ2vrT+ekk9JaQ0e7gb69fI/G8MWb7hi6a6wLOaQUGt5A1KFnA2rWLkYGxdySMQcEdUoCIO5WPbkUNwEfQph/8ZS4vyCKo6fKmLvwXySjxeQfrqEXrH+PPvUeHrH+qGa6igpraaq2oxOpxASrN1gTXVCGbBVQzEbOSZWaRDN3rBVbtnCjSi8ZxDhPW0L4plMZkoLyynOK6Mwp4S804XkZRWTd7qI+rp6+o3oycAxvejeJ6xZBUQb85GsVtvZqE7EZuM6WzkiJmG1CZPJzLIVx1nw2V4qq+rQ6RSmTurBtVf0onfPxgeAeqivtz6+jWvF6njNy96tpOgtaXPJu9UAZ8+VUcPCGDcqik3bMvjP/K28MW8aepe2WtXnLw/v4a1VFNVW11FfV3/JdVO+UBQcEKZxyEwczwV/w6dPn+aqq67CxcWFa6+9luuuu47LL78cF5f2bRMvaRuNsfnAcD+Hl8gl7dWUXQcPDMFgcILH/Xam0SNy6Gg+C784SFlFLaVltcT3C+KKyT3pHedPbEw30Buoqannh+XJfL/sKP7d3CkuqWbQwFAeeXgU7h6aMdSqNokTotfr6BbkQ7cgH2L6N3rCnPXW1v6oqsrWHaf5dPF+Uk5q11nfXgE8/nAiPXv4aRt1Qk/IufjdA8PZvS+bI8fy+Wl1Ctde3b/djuXhffYBobKsBh9/aYyA9Iy0yMcff4zZbGbz5s0sXbqUxx9/nOzsbKZOncr111/PNddcI8M0TkB9nXYzdGmHpLPk45ooUcKA9pWZdxYaL+L9h/PYfziP6Cgf5r8+hW7+msej0WNUW2vi9Tc2k5pezPQrejF6ZHdM9SpvvrOVW+/+igdnj+Caq/p2KkNEchazWWXztnQ+/3I/J05pRoiHh5H77xzM1VNjLtnvNTDAg3tuG8Q7Hyfx2ZcHmDalN67tlGBsMBpw83SluqKGsqKKTqOmK7lw7LpqdDod48eP529/+xvJycls376dkSNH8t577xEeHs6ECRP4xz/+QWZmpqPmK2kjjT05KkqrbGzZdk6mavoyse0cP3Y2bpvZj4/fvBKDQcfsx1bww09a4qeiKNTWmvjqu0Ns23map58Yy523JBDXM4A+vQO5dnpfqqrreHP+Zu66/0uq2iGhWNJ+mExm1m44xW8e/ZGXXlvHiVOFuLsZuGXmABa+cz3XTe9zyRoijVx9ZS9CgjwpLKpi2c/J7XosvyBNvbs4r7Rdj9OpUM5W1Fzoy1mdmRds1h48eNBKAr5fv37069ePP/7xj+Tl5fHjjz/y448/AvDUU0/ZN1PJ+dPMDefp5wFARUlrxkjb4/IVlbXk5JYDENPdR5CpFrQXRHl3UWekuqLV9WIOCfXCeKLbUQhHqWJsXMwRcfGw3F7MUXE9u95sVsHVnQh/A2//dRxrt2Tyn4/3serXE7z0x9G4uRr48aej3HXzAPrE+FBXVYXRVTteYWE5sTHduPrKPvh4u+JmBHNdLTq9cBlahdNsxNot/n4b2g+2NEtEbK13dK8Um4qjbcwJsWpdYCMnpIVzVzNCUln0zUFOZ2o/jB4eRmZM783Mq+PwaQwp1Ndah2XEc1/MhxLXi5o7Yg6Jhc5I69+lKuaMCOeZIv7tLmKTRWv5eBeDwu03DeCNt3fwxTcHuGpqHO7uxobDi5+9fb96foHe5KTmU5xXZtc4lxIyTNMCCQkJJCYm8sADD3Drrbda9aAJCgpi9uzZzJ492+5JSi6cRs9ITVUtdbX1DpMDT00rBjTXrY+3a+sbX0LoGnpDmMwqep3CpDERTJoQw9rNGZhMKvmFVZSW1WpKtNBU7rxt52n27MuhZ49uXH3F2Y7GznpjkGhht01b0/nwf3vIytZ+EL29XLjhmj7MuLo3Xp4ul1ROyPkydWIMXy45TFZ2OSvXpDDjmn7tchy/IC3hvvBMSbuML3EuLtinuH79egYMGMDvf/97wsLCuOeee9i4caMj5yZxAGbT2acnvQOTTNMytBtEj+5+DhuzM6FvKOk1NcjFTxobRXCgB4H+7vTvE8CqX09RVV1PZnYZe/bnMP+DXfj5unHrzAEW+0mck+MpBfz+mRW89PoGsrLL8PVx5f67BvO/d6/jzpvjNUOki2Iw6Lj2Sk0HZMv2jHY7TmOPmpxTsmFeI4rOMS9n5IIfk8ePH8/48eP573//y1dffcXChQu57LLLiIuLY/bs2dxzzz2EhnacAqVEo1GAyuhqcGg1TVp6MQDdoxyrXdLZEHMEPD2M/O7+ofztv9uZ+8dVqKq2zZiRkdwyc0BTE7RLPbegs5JfUMGCT/ew+let35KLi54br+/HLTMHaOGILugJaYnRiRG8t2AP+w/mUlZeg7eX472jEbHBAJxOyXX42J0VGaZpBU9PT+677z7uu+8+UlJSWLBgAfPnz+cvf/kLV155ZVPOiKRjaDRG3DzseJJrQYshvcEz0j3Sx3q9lXaC0GtGzAERc0aqKoVlYX2djcRP8WIzCKe5m7vFouoq5KjUWc5PcbOcvyr8Pc11SVRVJS7Kg/f/Non9h/MxGnUEh/gQ0NiJtb7WqneOqhq0ZFZFwd3NgKIKehDispWuSrO/11abd3HZpo5He9+42pivZCtHpa05IQ3nakVFLV8tOcR3PxyhplZ7b9KEaGbfPpDgoIbv11Sn9Y+xOJ6YEyKcK+K5XicuCzkhQj6UKvZ1as0YEvV19ELOiKtw3gu7K1Z6N6K+zdnxw0M8iY7yJS2jhF27M5k0IcZ6Pq3p4YDNlJKIhn5EmSekMdIVcGhdVlxcHM8++yzR0dE888wzLF++3JHDSy4AU0Npr6M1RtJPa8ZIdBcN05wLRTmbT5LQP1B7U/xRaIFPvtjHmvWnuPmGAVw7ve9F6f8hgZqaepatOMYXXx+ktEwzJAb0DeKhe4fQr0+g9IS0wqgRkaRllLBuY2rLxoidBEVoVXoFOTJnpAmdYvnwcaFjOCEOM0Y2bNjAxx9/zLfffotOp+Pmm2+WyatOgG9DeVxpYQWmelOrTc7OF5PJ3NR9NDRY1v+L6Nt4sdfU1LMjKYuSkho+WLibr5cc5uaZ8VxzVW9plLQTNTX1/LTyGIu/OUBhkXYuR0X6cP+dgxgzItJpXdnOxNRJsXz57SG278qkoLCSwCDHhmzLi7XvxbubvMc0cQl3yrPLGMnKymLhwoUsXLiQlJQUxowZw5tvvsnNN9+Mp6c8gZwB30BvdDoFs1mlOL+MgFA/u8csKqrCbFbR6RT8fFzBLLiSRVe2LddztRAmqSy3XK4QlsXSX7HUV5S9Fo0DsYTR3bK0Fw8vi0XVUyw19hKWhTCUu+V6RXCPi8d31et5/59T+XVjOp9/c5js3AreX7CLL77ez/Rpccy4pi8B/mfnqIh/X/MwjlVYRnS9YwM7S31tYUu+3WZl74WFYRqprqrl51UpfLnkcJMREhzowR03DWDa5Bj0qJbluGLpbV3rITtqhBCjrbCNVRindTn4VqX/hfNCFc4zq1JeAVUs/RVL4oX9u0d4079vIIeP5rNm7UluuWlwq+O3lZJ8rYLJL9DbxpZdB5kz0gJXXXUVv/zyC4GBgdx9993cf//99OnTx5FzkzgAvV6HX5APhbklFOWWOsQYyWtohx7g764lYsrCELsxGHRMm9SDyeO7s2bTab749hBZ2eV8+d1hvv3xKBPHRXPrrPgunzB8oWTnlvHzqhR+XnWcklLNQAgO8uC2Wf2ZNqlZx2nRkJa0yrRJsRw+ms/qdjBGGvVFGsXPJJc2F2yMGI1GvvnmG6655hr0+vZpiT1v3jy+++47jh49iru7O2PGjOH1119v1ehZuHAh9913n8V7rq6uVFd33e6PLg2iROfb2t0WxSXaZ+nv525jS0lbMRh0XHF5LFMmxrBtVybf/niUg4fz+GXdKX7dkMrUST25+/bBBAd52R5MwvETBfzvi33s2JXZ5FQICfbklpkDuGJyT2T/NfsYNzqKf7+znbSMEioqavFsh5Ln+nppIDYhc0asuRhVMuvXr2fOnDkkJiZSX1/Ps88+y7Rp0zh8+HCrYSAfHx+Sk89KFTurW+piUV6seTK8/BwTOisv14waLy9n1lpodGd3zu9er9cxdmQUY0dGkZxSyKKvD7J1x2lWrjnBrxtOcd30vtw8M76pVFhiSXpGMQs/38PGzWlN7w0dHMY10+IYlRh5trGjKn/o7MHH25Vufm4UFVdzOquUPr0CHTZ2ZG+tmibjWI7Dxuz0yJyR1tm4cSPvvfceJ06c4JtvviEiIoJPP/2UmJgYxo0bd8HjrlixwmJ54cKFBAcHk5SUxIQJE865n6IoUuOkAbPZ3CQF76hmU+UVDcaIp5EWg/xinFtcFnMsxGWxtLdc6E1R1SyHQ2eCsFyIyQO/SnCp115Gkza1aiNUuUC1CxR5QEYAFAaBuVkuhZuQQ+Ih5KhU+VguewuS3h5CKbCQEyPKyytiHoIgT4/B8jPt09OXF58ey5Fj+Xz02X72H8rj2x8O88Pyo0waH83Ma/sR21NrSmmVT2KVM2Kj1LdVqXnOQ67dBjZzRmwtCzkhzZZVVeXo0TyWrjjGrxtSMZtVFAUmT4jmjpsGEBnu03Au1kPjKSnmG4nfna3WBGJrAzFnpFpYrhFzRoRzX8wZaS1sJHqkxRwP4TxThc/OqpRXLIE3COOJVWF67buJCPOmqLiazKwS+vQKOPd8RWzI2XfvHQZAbloB1ZU1uHmKcvWSSwm7jZFvv/2Wu+66izvuuIM9e/ZQU6NdXCUlJbz66qv89NNPdk+ykZISrcTLVjfg8vJyoqOjMZvNDB06lFdffZUBAwacc/uampqmeQOUll46jZkqS6ubusk2SsPbS0WDMeLh0YGVHt4V0Oc0xOaguJ5Dd0QBPOq0FxUQUQTxmah1esjxh4wgSA8GOsdNrl/vQP7+4iSS9p/hs68ONsTqT7F67Sl69vBj2uRYLp8Uh59v5/h7HEXG6RLWbkzl1/WnmmTbAUaPiOTe2+KbpPkl7UNEmDcHj+SRmeXY+6ZfkDd+gd4U55dxYn8GA0b3cuj4nRGloR2FvWM4I3YbIy+//DLvvvsud999N4sXL256f+zYsbz88sv2Dt+E2Wzm8ccfZ+zYsVYN+prTp08fPv74YxISEigpKeEf//gHY8aM4dChQ0RGRra4z7x583jxxRcdNldnwt3LFaOLgbraegqyiwmLCbJ7zMbnmbaWsDoGFXqfhsRklIYnM7XcFU4GQ5Yf1BigSge1etCp4F4HnibwqIWQEogqQPGog6g8iMpDHXkUskIgLRJygkF1bmVURVEYPiSc4UPCOXIsn++WHmXzttOcTC3m3Y+T+PB/exg9IoorLo9j2JBwDEbn/nsuBFVVOXGykE3b0tm0NY209LM6FK6uesaP7s51V/Wmb+9AGYa5CESEawmmjjZGAGprNe+Ou1fXMrDPiQzTnJvk5OQWQya+vr4UFxfbO3wTc+bM4eDBg2zatKnV7UaPHs3o0aOblseMGUO/fv147733+Otf/9riPs888wxPPvlk03JpaSlRUVGOmXgHozfoieoTyskDp0k9kuUQY6Qx3l5Xf5HLaAz1MGw/SvdMANQsfzjcHdJ9LJVCm7u2K12huMGdfTwUUFFDayAiH3rkoPhVQFQ2RGWjVrnBsRjI6Q/1zq/v0a93IH/+/ThKy+tYtzGVlWtOcPxEIRu3pLFxSxo+3q6MGxPNZeNiGDQwtNNL0JeWVrNqzXGWrzzW1D0XQK9XGDIojMmXxTA2MaKpi6zk4hAZroUxm38njqDoTCmVpVXodApRvWXY/VLHbmMkNDSUlJQUevToYfH+pk2b6Nmzp73DAzB37lyWLVvGhg0bzundOBdGo5EhQ4aQkpJyzm1cXV1xdb10O8/26BeuGSOHMxk9fVALeQBtG8/YIJxWX28GFJtaD2Ic3iqHRNQZEXVFysvBtwImHUTxq0Q1g7q1O+wN1Y5fVWy5vSgXL6rPlhgh2RvwQg2qQhlYBr3zUTyqYdAR1H7HIDkCjkRCpZt1DouYR+BpuV4V4/4eNrQlRF0SUQdFXBb0IHzc9Vw3LYbrpsVwMr2Ulb9qlTclpTX8tPIYP608ho+3K0MHhTJ0SDjDBocRFKjlD1lLgNt6arL3qar1nBBVWDabTBw8coaVv5xg3aZU6uq0c8vVRc/wIWGMHRXJyGHheDcmU5tNYGr2+ZuFc9FGawKr707MCRFbF1gtC+eGrXOnRphPvY1rpfn3JeZ4iOeJeB0K360q5JgodcI90M3Gdd2wHBmunb+ns0pQzeazBQN25hdln8oDIDCim8O6jXd2FMUBYZpL1TPy4IMP8thjj/Hxxx+jKApZWVls3bqVp556ir/85S92ja2qKo888ghLlixh3bp1xMS0XXLYZDJx4MABpk+fbtdcOjPhPbWGUzlpjul+qWvqWGtnMuP5YqyHK/eieNSiVriiroiFHEdoDyiQ54G6xR+2RaH2zkcZkoXSrRoGpqMOyIAToXCiH5R3jlLanj268fD93XjonsHsP3yG9Zsz2LQ1g9KyGtZtSmPdJq26JDrKl5GJkYweEUW/PkFO5zU5mVrE2vUnWbsxlTN5Z3/wY2O6cc2VvZg8PlrzgNjqVSNpd8JDtWujoqKOsrIafHwcE1JplIEPimg9R7BLIcM05+ZPf/oTZrOZyy+/nMrKSiZMmICrqytPPfUUjzzyiF1jz5kzh0WLFvHDDz/g7e1NTo5W4uXr64u7u5aMeffddxMREcG8efMAeOmllxg1ahRxcXEUFxfz97//nbS0NB544AH7/tBOTEWp9jTm5edhY8vzo7ahkZirS/voy1gxKFUzRErdYdlQKKq3vU9bMevgaDDq0SDoUwn9M1DCiqFXNmpcNpwOh6O9oKRziI7p9TqGDAxlSEI4jzyUyKGjeezZl0PSvhyOpRSQllFCWkYJX313CF8fV0YMi2TYkHCGDg6n20UsFzabVXLPlJNyspCTqUWcOFXIiZOFFgaIh7uR8WO6M31aHH17+Tvtk11XxcVFj5ubgerqesorah1mjDQayGaTNDi7AnYbI4qi8Oc//5k//OEPpKSkUF5eTv/+/fHysv9J8p133gFg4sSJFu8vWLCAe++9F4D09HSLJnBFRUU8+OCD5OTk0K1bN4YNG8aWLVvo37+/3fPprBQ2PGGcW3217b1UQEsWBNXa/WvVxVdYttGp1KLc0bsc+p/Wxt0QpRkiQrWTWmXp6jZVCq5vEWG+eg/BPV3uDkmRqGH+KKPyUHqVQVQWamQWHAmCw32hqtkN10cs/xSOL4ZxvC0NGkX4PFQ3oQTbVSgNtgrjNJu/lRS+Dj2Q0LcbCX27cc+tAygtqyFpXy7bdmWyc3c2JaU1rF57gtVrTwAQE+1HwoBg/P3d8fV2w8fHlYBu7vSI9rvgfAyzWSW/oJLMrFIys0pJyyjhxKkiTqYWUVllbVwaDTpGDAtn0rgoRg4Nw9W14VYlhjFEz4hQRi2eazbl2G2FZcRWBWIYRlwvLoshRDFMU2tDmLB5aEYMP4r3XKswjbC9eB65WYaExJCV4nruhxlPDyPV1fVUVtroqN0GXBs6jddUO0as8ZJAhwNEzxwyE4fjsECci4uLw3/wrX7UWmDdunUWy2+88QZvvPGGQ+fR2Wk0RvxDHfNUX91kjFyEOO6goyh6FTXNF9K6tf/xmpPtgbokGjVKQUnMRIkrhP55qL0L4HA0HO4BdZ0vlu3j7cqkcd2ZNK479SY4dDSPHbuz2LMvl5RTRZxKK+ZUWrHVfjqdQlSEDzE9/IgI88Fg0KHXK+j1OsxmlYqKWsor6qioqKWispbKqnqqquqoqKyjqKiKmtqWK1uMBh3R3X2J7dGNnj386NnDj7ie/nh6GLtO11z3GggtgKB8CC4Bgxn0Zq0iTFGhzB0KvKDIFwp8tJcT4eFupIAqKqocaIw0NImsqZTGSCOyN00LVFVVsWbNGq655hpAq0hprtWh1+v561//ipsoKCW56BgbLurUw5kwK9Hu8c7HSHQIHlUokWdQVVA3RV+cY7ZEoQfqyl6oe8tQxqajhJVDwinU3qfhQE/IHuD0JcHnwmDQMSg+hEHxmtplcWkte/bnkHKykNLSGkrKaigtrSE3r4KCwqqm8M6FoNcrhIV4ERHuQ1SEDz17dCM2xo+oCJ9miqgX6dzqaHQmCCyEoGwIz9equlojoFx7oYWq1WojnA7WtHJyAsB0kUKm58CzQXOoUYPIEZgbPKrO+uPZIUg5eGs++eQTli9f3mSMvPXWWwwYMKApl+Po0aOEh4fzxBNPOGamkgvm6vsmsPvXw/z4wVpueeJK3L3sqxzy8db2Lytv5yeWHloJL5k+UOwEsue53qjf9YcB1TDkBIpvBSQmo1achiPxkBlJZ5Wfb8TP141J43swaXwPq3UFhVWcOFXEqfRics9UYDKZMZtVTA0/Gl6eRrw8XfDwMOLp4YKnhxF3dyMeHkb8fN0IDfZsQZumixgfAPp6CMuAqCwIzkcxNFePBQp9INMXsv00xWCzAiad5hnxq4SAMgiqgMASFLc6iMuEuAYRv119IbfjGpW6u2s/JVUthNwulPysIgACwvwcNqbEeblgY+Tzzz/nj3/8o8V7ixYtairn/eyzz5g/f740RpyAsdcOITw2mKwTZ/jly21cO/syG3u0LgnemKCmdT+1/vEVn2Ssfm5EiWsxh6S2Vture0OuyCFfi9i6udwyrl9fbPlUaRZcxeZqsdTXcn46V8s8CJ2QF2H0F2LxlZ6wKwZ1YBHK2FwUrwoYvh016hBs6QlnhPJzMadEzGPwEtvIC/LydZY5JFY5JbVnSzSt8knE8k+duCyW9orLZ/8Z4KsnYHAQIwa3Raum2bev1oH4W2VD7t1mawHxs7Qq3RWWxZyQWiHno605IOVllstW+1dARCHE5UL3fBRjMwOk3AhpPqhpPppWTo2hWSly4/8b/t50FyAADCGgM6OGl6P0KoUeBShetTD6EOqBStgXR9OXZitHRLzuxGUrzm04NnpGKtsSUrHh8cjPKgYgMNzv/Me81LmEq2ku2LeckpLCwIEDm5bd3NwsEklHjBjB4cOH7ZudxCHo9TquukvrEZT0yyG7x/P10TwjpaU2EkXtoVu5pilSr4Pjfu13nAtFVWC/P+qHfVB3dEet1aGElKPcsB9G7gO3rtslWoIm0BeXCjN3oFxxACX2DIrRjFrshnlHJObFCaj/G4r6Sw847q8ZIueLWQenfWBzT/h8OGqSZvwqA0/B6EOaJ+Ui0+gZcWTOSH52MSA9I81RdI55OSMX7BkpLi62yBHJy8uzWG82my3WSzqW8FhNa6S0qNLGlrbxbQjTlJS14/cbqrloyfHXpN2dlTod7ImC5BDUEWkofc6gxGSiRubAwV6aoquk6+BeBX1OQc/TKC6aG0it1UNKKKSEoJ424thQngK7olHL3GDCCZTYLFSdGbacu2VGe+BibBBCrHNcGW5RbkMVoDRGugQXbIxERkZy8OBB+vRpOU65f//+NqulStoPVVSitAPfhkZsJSXt+PQfXKz9/4xf+x3DkVS6wLpeqIdCYUI6SmAxDDmKGpUDh8ZCRefQJ5FcIO6V0OsodE9F0WvXmlrqCYfC4XgI1DfeatvpmkkOAZ0H6rgDKDE5qFWucNz+ZPXzpTE068jk9qIzWgl/t2DnqhzqUC7hMM0FGyPTp0/nueee4+qrr7aqmKmqquLFF1/k6quvtnuCEsfQeI9wxHnYGKYpK6+lvt6Mwd4nPSutiDoIKtb+ne1lpcVgKhNyRkosl6tLLW/4dTae1nR6y/m7CSXLpnLL4xt8Lb1LBv9mx88BJT0GdUAByoTTKIHFqON+ht0xWh8dVbGWDLchEa66C+sFefnm+g+qkG8itn23yikRTwixDX2b5eIFbOWEiPlDQk6IahKSTESdEVvy7WJOiJhDUi70U6kUqlqqhOVSoZLIJR8GnIZeOWcbN572Rk0K0/JAqqqB4mbHt5yvucpGjoXweevczn6fqnDfVY54Q01vmJqM0j8N9UwI5DbL7/EQ9X0sP0tV+OwVW2XVzb7bxjQsUVLIHopypTEiIrv2tsCzzz7LV199RZ8+fZg7dy69e/cGtMZ5b731FvX19Tz77LMOm6jEPhpPQJMDmtt5e7mg0ymYzSrFJdUE+jg4jOJeqymumoF8b6CzhfsUOBSoJSZOSUfpUQqJJ1B75MG23lAnvSSdGsUM4XnQOw0ltKDpbTXLD3VrCGR14I/nyUDUQyUoA3Jg+AH4aeJFKTtvakfjQGukOF8zRvyCHNH6QeLsXPBZGhISwpYtW+jXrx9/+tOfuOGGG7jhhht45pln6N+/P5s2bSIkJMSRc5XYQXCk1t8hOzXPxpa20et1hIVoFSbppy9Mc6JVGqtLKlw7XD/BLspdUL+PRd3cF7VWjxJUCtfsgiF7wKWzGVgSMEPMabhmA8qE3SihBVrTxrQA1OWDYcXgjjVEGtnWA7XSiOJVBdFZF+WQjX2q9AbHGD5ms5nyYs3L5SNWs3VlGsM09r7awDvvvENCQgI+Pj74+PgwevRofv7556b11dXVzJkzh4CAALy8vJg1axa5ublt/tPsko+MiYlhxYoVFBYWNnXFjYuLw99fNjZyNro3tOAuzCmhoqQST9829KkRT15FISrSh8zsMrJyyhnaX/i+Rde+rWZmoivfo8HVXuEKJhNqrViqa+m6rxXCKBWVlutF7YN6wTukE9yWmsz9WdwrLI/vVWEZCjEJ5YzGCsv56Df7wt44uCwXJb4YYlJRw07Dru5wOBRqRElywVDxEp4Ma1sJ4whhGMVouay6CMcyCPLuNaKcvLW8vMX4tloBiIhhFzEUILYGEDs+C+tthmHEMItYemtVmiuGZUoBVSvPHX4CxV9br1YZ4HAQ6jZPKDWiee9yMQvnhlloTWCuFecvhKWEz08xWH7++mYaQXqxZ4ux2Xe5OxhlXCb0PQ7Hg7TwoK1S3rZep82++7qGa8roIGOkoqSq6bNwVE+tS4IOED2LjIzktddeo1evXqiqyieffML111/Pnj17GDBgAE888QTLly/n66+/xtfXl7lz5zJz5kw2b97cpuM4RMva39+fESNGOGIoSTvh6euBf6gvhTklZBzPpe9w+6o8wkK0H8jsnHIbW14Ang038HL7xNmcigoj6k+RqPu6oVyZixJQCeNOovbPht0JkCcNeKfEuxLGHEMJ16q71Go9alI47A/RBMnKymwM0EHsD0JNzEXxrUTtngtpoe16uEZjxOAgY6S8WDMaXd1dcBF0gCSOoVTo8eXq6oqrq/U999prr7VYfuWVV3jnnXfYtm0bkZGRfPTRRyxatIjJkycDWu+4fv36sW3bNkaNGnXe83HSimNJexDRUyvvzUnLt3ussIa24Vk57XAzdmt4Gq66BG9CmZ7w7WDUjT1Rqwwo/lUoU7bD8INgdJxGg8ReVIg9CdfvRAkvQjUpqAeiUD8dBHvCNEPEmanTw9Hu2r97n273wzV28nZxUCfv4nztvuLj72ljy65FY28ae18AUVFR+Pr6Nr0aO9+3hslkYvHixVRUVDB69GiSkpKoq6tjypQpTdv07duX7t27s3Xr1jb9bZ2vy5fkgvEJ0AyIsiIbfTDOg/CwRs9IOxgjugZ3sNnJb/gXiqrA4TBICUIdlYrSLxelVwZq5BnY3RdK/OjssvKdGo9KGLYHJVgz2tUsP9jcV+vmXGP/tXPRSAmHQSchpMiqAsvRlDf0pPHydLGx5fmRl6l5ooIipMfQAgeGaTIyMvDxOZvj1JJXpJEDBw4wevRoqqur8fLyYsmSJfTv35+9e/fi4uKCn5+fxfYhISHk5OS0aVrSGOlCeHfTnjJKRWOkhZwQ4Q1hUUd4mFYRkpldjoqQOyDurxeelmwdr1FB0owWpxZi42LcvVYo3RVzRMqFHJIaQXNFzHJwEfY36iw9FhVCDomPsL1HueWN36XGcntDVbP16d4oA/1QJqWhdKuGsftQM9O1qpvShli5mMfgLVTjuDeLqXtYJvuprqI8vPBjIZTyKrZKe4UcEqsMEfG7FHNCxLwDsbxUzBGxlecglkWLZdO2SnXLm4UZXWugVwoMyNbUUut0qOtDYY8/UAFUYC6xDEuaxPwhIX/JJJwLZls5IsLnpxc7Yze7FhS95XejdxfyZYq9ULN9UcJKUCOyID+cNmErh6QZ5eXa9+bl1ez8sUNH4ExGIQDBUdIYscQBOiMN9/PGhNTzoU+fPuzdu5eSkhK++eYb7rnnHtavX2/nPCyRxkgXwqfBGCkrsP/pLiTYE51OoaamnsKiagL8HdjIrskz0kW8A5k+qIsGoA7LQRmehRJRhDpjBxzsDvu7d/TsLn08q6BfKsRlNjWvU7N9YF0cnO7kobP0AAgr0RJw7Y/OnpPySkd7RhqMkUhpjDgDLi4uxMXFATBs2DB27tzJf/7zH2655RZqa2spLi628I7k5uYSGtq2PKU2+8GLioooLNROlLy8PL777jsOHbK/34mk/QmJDgAg/Vi23WMZjXqCArUn8tw8+yXmuzxmHewMR10Uj5rZDUWvogxKg5k7IOo0Xaq77cXCWAvDjsL1m1D6ZqAYzKhnvFB/7gc/xkOpE3SKtpczDU++vlWtb2cnpWWaMeJtZ0fwRgpzpBR8SzgyZ8QeGtu9DBs2DKPRyJo1a5rWJScnk56ezujRo9s0Zps8Ix9++CGvvvoqAH/4wx/4/PPPGTRoEM8//zyPPfYYDzzwQJsOLrm49BnaA4DkpFRUVbX7pAwK9CT3TAVn8ivp3yfAATNsoPF3t4s4RiwocYNVg1C758OIFBTvahiRhNrzFOxNgBIpmGY3ihliTkHfIygu2o+omu0Ph2LghCuX1IlX1eCp8GjohN0Of1ttnYnKSs2D5OfnZmPr86M4T8tF8wuWgmcWdEBp7zPPPMNVV11F9+7dKSsrY9GiRaxbt46VK1fi6+vL7NmzefLJJ/H398fHx4dHHnmE0aNHt6mSBtpojLz55pscOnSIqqoqunfvzqlTpwgKCqKkpITLLrtMGiNOTkx8JEYXA6WFFeSkFhAW0ygVfWFP3UGBWtjnTEGlZRxT1KYQJMmtc0hEXZLG91uelyrkkJjqLberqrKMy5cLkuPVQs5IvSifIBzPVbh4q0st968R8gC8qy2XfWssc0pcBF0SFyEHRudXDfkK7ItFTcxHGZWHEliIOnkdHAiD5AHNep0AHs1yRqqFREVBMhw34Wlf0BlRxZwRK52RNlZLiHkHYg6JKAdvK0dE1BERc0REHRGLnBEVQk7B0HQUP20/Nd8NdUMEpPkAZiizFAWsF1sPFFuOL+aE1FRYzremRjjXhHNXTKHRC+eam5vl5+PebL3OzfL2rfcWQkomE5Rp35diMKMq1VDfhjCKzVYA2nJJifY36/UKXl6u585psPnwc3Z9kzES5AQicl2cM2fOcPfdd5OdnY2vry8JCQmsXLmSqVOnAvDGG2+g0+mYNWsWNTU1XHHFFbz99tttPk6bjBGDwYC7uzvu7u7ExcURFKT9mPn6+jrE9SNpX1xcjfQcGElyUipHdp5sZoxcGMFBmjGSk+vgCgO14VzSdfHQhEkH24IhNRJ1TCpKbAEMykaNK4Kd/SEruKNn2ElQIeIMJBxD8dMSUNUqo9btNsnr7Pl2KWLSo9boUVxN4FYN5Y7J6WhOYZFmsPn6uDnkd0BVVQpyigHwC5SekeY4IszS1v0/+uijVte7ubkxf/585s+fb8+02pYzotfrqW548mqeSVte3g7CV5J2IX6UloS0f/Mxu8eK66kllx09XmBjyzZS3fC07tbJkwcdRYUrrO6Durwfaqkrimc1ysTdMCEJfOS11ypBhTB1qybf7leOWqNH3RUNXw6Ho2GXtiHSSKNeTzu1IEg5pZXhRnf3c8h4ZzIKKSuqRG/QExErDW4LGsM09r6ckDYZI7/88ktTLbKv79nYdWVlJe+//75jZyZpFxLG9wFg/0b7jZEB/bQbxcm0EiqrHGg4VDaPc0uayOgGXw1GPdwD1aygRObB9E0wJAncZBKxBV5lMGILypTtKIElqPV61EOxsDgR9nSHui5USNho3Lu2z/V0LEUraOjTO9Ah4x1NOgVAz/gIXN0d78mROCdtuiKbGyAAOTk5hIaGEhwcTHCwtGCdlmZuuYRxfVAUhYzjOeRnFxPYUra6DR0QpaE/SVCQF6HBXuScKefI8SKGDW4o5RJzQsQ8AzEvwSCchtUNeQ6eddZjYd0Cu07oNWMSAvE1QifRCiFuX2Wj06hB+Diq9Zbb11aJOSSWy3XCsp8wX1XIGTEKbeUNYq+a1QGw0xPGZqLEFUN0GmpEBhyKhJQ+UNcsD8Rd6OvhIlQ7uAsKl+J3IS6LeQQi4lOXmBNiM2dEMGrFvj22ckaUQkhIg97ZKDpVS1k5HIS6I0IzcissRfrMxZaepfpSS6OurtAyBFlbaTm/snLL5erq1vsgiflN4rlsNFp+vmbhXDYYzp4beg/L71Ktt/wslcZ9qxu+Q9EzYpUTcn45IuL65BTNM9qnV5DlNhf4AJ68SzNG+gyLcYCmxiXGBTS6a3EMJ8Quictp06Y5ah6Si4SXnwdxg6IA2LP2sN3jDeivGaFHjjlQxKCxJ413lVb5ILGm2A11eSzmL/ug5viiGMwog9Lh2rXQLwX09bbHuJTwrITh+2HWNpS+WZohkh6A+sVA1HUxZ71tXZGaBmOkHdoNmExmUtO1MtzesY6pqDtxIEMbr6H6T3IWRac45OWM2GWM2OzQKXFKhk+JB2DH6oN2j9W7l+aaPX6iyO6xmijxQK02oBjNEOSkjcichRwv+Gkw6up41EJPFJd6lEHH4Np10PcEGC7lvBsVAgth5B6Yvg4lNgNFr6Jm+aH+NATWJEDRJaAVYi+NeTHnqE6zh4KiKsxmFb1eISDAMd11s06eASCqV/s295M4F3YFTmUFTedkxLSBfPGPn0hacwhTvQm92GlTTOqz+prPvtE7TjNGjp0oPOvm1QmnlRiWEUt9xfWubnDGH7qfgYgKlP2tN8yzdRqKYRsxLFMiuNJrhe1Fi73KII6nE5YF13yp5fZiWMlPkLP3EsI2JiEfx+hn6W7XVVdDHrAnGnVIDcqI0yi+NTA4GbXfCTgaAYcjodrFutRXLIV1aV0u3gpbH774wCKGZeptyb8L6ysrtdyHXrlaKMbv7PzVNF/UzQFaM0LqgXzUcsu/TwzDmEoswzx1wnK5EIYRWwFU2Gg1UG/jgU0vXFwewrlp0Fuur3dvxVMohhsbj928VN6iBF8Iv1q1cRCuY514JSjk5WufV2CAB3q99fpWl1s4d2pr6pqk4MNl8qo1l3CYpgtlcUka6ZcYg3c3D8qKKjmy8xTxo2MveKzYnv7odAoFhVXkF1QS6KCnI85004yRkCLAgYJqlzKqAscCUVP8UXsXoAzJQvGvhkFpqAMy4EQInIiFkk5aLulSC/1PQP9msu11OjgegHowGPK8NGNFYkljW4V2+A06k6fl1DSqMdtLbloBZrOKm6cr3YKlxogVOhwgeuaQmTgcJ52WpD3RG/QMvqwfAAe3HLdrLHc3I716dgNgy3YHtirP89P+H1CClEJvI2YdHA1C/SIBdU08ap63llPSJxtl+iaYvB0icjtPPo6hDgYch2vXoSQ0yLbne6Fu7o26YAjq2p6aISJpmcYS+XrHP3umZWj5IhGhjjFw9244CkDPAZHS894CziIH3x7YdXbqW6h0kHQOYvqHs/H7JDIb4rP2MGlCD5JTCvll/Smum97bAbND6zhqBsWtDtXLBOXSidd2FEgPgvRA1JAS6HcaovNRQgohpBC12gVOR0JGdyjyw6lk0BUzBOdBZDpE5KIYtfCOWuAFSTFw2h9QoK59e65cEnRr+IzKHO9pONZQSdO7l2O8lxt/2A3A2GuHOGQ8SefBrjv8nj17HDUPyUUmvKcWj806L2Ok9VjvpAkxvL9wD0ePFXA6q5zIICHHw2ArR0QoNzUaASOUeYFvOUTUw8mziYg6oaTRRSiHFN19ol/FLLxTLcTaK4W4v+g/KBe299ELOSJGSyPdJEygvsLyDZNQalwvlH96C3LyYgmnsdn++hrLnAu1sSy4CC13JCAC4nOhXx6KRy3EnYS4k6jF7pAeqKm65vmdzRsyCt+dVd6AgK2kduGzpb7Z36YzQ0AeRBdATB6K+9n8DLXQHXVnJBzyQDsftSdyMSxjKhXk28XlEsvtRfl2sVRXzBGprLH87MVzpU74++uEc0X0sLsI5bSKkFJjFPKLmpf6WpXyGsU2DHrNqPNrKI+uDrC89sSSe+E6VcT1LZT+nmgQPIuLDbB9btigurKGfRuTAWmMnJMO6E1zsZCPm12UiNgQAE6n5No9Vjc/d4YkhJK0N5ttu05z41Uxdo8JQLGPZoyEVsHJTprn4GyUu6Ju6w7bo1C7l6D0K4ToAq1Xi18GJGRoUumngyDbHwqCodoxnVitUMzgXwqBpRBWCOEFTR4QaJBsP+6PeiwQznihGSHV5xxO0gK+1VqZc50Oqh2Uz9VAaWkNRcXa9xEdZX8Dx5MHTmM2mfEP8ZXKq+dCJrC2TH5+Ph9//DFbt24lJycHgNDQUMaMGcO9997b1LtG4nxE9dbK5gpzSijJL8PXzh4QgwaGkLQ3u8Ft6yBjJM8forNQostRt8ibk0NRFUjzg9xQMNajRhVCVAFEFWoeiV5Z2gtQSzy176LYC8p9oNQLqtrY3VYxa9L1fiXQrRT8S8C/tCkRtWlalS6QHgBpAZDZDbX6Ui5Nvgh0axBtK2r0KDmOYye0EE14mDce7q1XvJ0PuRnaeBFxIXaPJel8XLAxsnPnTq644go8PDyYMmUKvXtruQK5ubm8+eabvPbaa6xcuZLhw4c7bLISx+Hp4054bDBZJ85w4kAGQyf1t2u8xj41KScKHTE9jewGYzaiElxNUCNzlNqFOgOcDNZeLnrU0CKIKIDQQuhWjuJbAb6WSqRqvU5Teq3Xa4mRZh0Y6hteJtCbtSoOteFlrEfRWyfMqrUGyPeBM36QGQg5bjhV7kpnp1tDWKrIs/XtLoDk443Kq47JFynILgYgMNzPIeNdkkjPiDWPPPIIN910E++++65Vdq6qqvz2t7/lkUceYevWrXZPUtI+xA6M0oyR/actjREbcvAtyUjHxWp6I6ezyqioMuHpcfZJSTEIOSIulloXqss52tyb3VFLfVB8SlH71EKKdtPTC09hooS2uGyoa/3iq6d1HRIxp0SMjNcKOiNCyge1Rss3xJyVeiEHU0y7EHVJugnrzc28B8Zulq54vSAtr/MSP3vxu3GBQh0cDgKCwBPU8FKUkHLoVg3+VeBTrXk0DG1rvKbW6iHfA/I8UfM9IdcL8vScNT5MUFdsuVO1ZVjGLPw9pkrLOZhKLbevK7bMEbGlG1JVZZmfUybkZVQK+T3VQs6IqFEjnnk68VrSWe7vpor3Us65rLjY0AExGiGg4eQq9W5hvQ39H1FnRJj7WWMksOGeYOu+0fp1WJCt5QEFhPq1ul3XxgHGiJMa+xdsjOzbt4+FCxe2WCakKApPPPEEQ4bIJCRnpvfgaDZ+n8SW5Xu58dGpdpV8+fm6ERzkyZm8Co4cK2D4YAepJ+aGgk8pSmwRaorUG7no1BjglD/qKc3zpRgMoDOjetaC0aS9XEzaj2qd/uzLpNNEtvRo/6/XQZmbVdIlyDBM+6FCYIOCsYM9I6qqNrWA6NPLMQ3yTh/XQv1BEd0cMp6kc3HB6c+hoaHs2LHjnOt37NhBSIiM/TkzU24bhdHFwMGtKU1Z7PYwbHAYANt2Zdk9VhOZWh8dYorApYv1W3FWzJphQaEn5Ppo3YTTAiDLD/K8odhDW1/qrv27yBPK3HHWJ7JLFt9KFK9qVJOihcEcyOmsMkpKqjEadfSKs/8hobamjr0N96CEcQ6SB7gU0ekc83JCLtgz8tRTT/HQQw+RlJTE5Zdf3mR45ObmsmbNGj744AP+8Y9/OGyiEgfS4AEJjPDnqnvH8+P7a/l03jIGT+jXsIHa4vbnWm7s4jtmVDQ/r05ha1I2cx7SnfW0WHWCFdzDYmdZj2YCVnWeqEUeKN0qoX85HAtHL4Qa3Lwsqz1che6k7tWWF5+rMH83YbnEcjZWKtuiK14s/hUr58RLXyf8KOsQvAVCwYhZrA0W8G4WxlHrLA02vbel50FfLYRtjJbfjc7T8rNUDJZ5Oqr4Xdq6sdULBqTw2YnzFTsYm2ss528qF8Iy5ZYfVk2Z5fpKQa69orJ1OfcyQa5eDMOIYRrxXBBDdCLuwsdlFlsvCBiFVg3Ny9h1LmI3bCHMEt1wJp8JAL2HdcdmW92zrbpvnz32waNaiKZv7yBcXRuO28awTHPj9ODWE1RX1OAf4ktsQpSN/bowMmfEmjlz5hAYGMgbb7zB22+/janhItbr9QwbNoyFCxdy8803O2yikvbh1t9fxc8LN7J/0zH2bzpm11PJkEFhuLkayMuvJOVkEb1i/R0wQwWOh8KIk9ArB46FO2BMiaQLEJ6n/T/bMWGU5hw4oo09cIBjvN87Vh4AYPiUAU6rECppX+zy19xyyy1s27aNyspKMjMzyczMpLKykm3btklDpJMQFOHPlNtGA7Dmy212jeXqaiBxWAQA6zen2z23Jk6EaGqsIaXgI3uPSCQ2MZghqKGyLcuxEgtms0rSXi2/IyHe/tywyrJqVn2+GYDR0wfZPd4lTaNnxN6XE+KQ4JHRaCQsLIywsDCMoqtQ4vSMnzEUgG0r9mMWFTLbyKQJmsbIrxvTMIvxjQulyhUyG7wsvXIcM6ZEcikTUYGiV1Er3KDMscmrR48XUFRcjYeHkYR4+z0jP76/lrKiSqJ6hTL66sH2T/BS5hI2RtpNgTUjI4Pnn3+ejz/+uL0OIXEQg8b3wd3LlcKcEo7vTafP0GjLDcS4diulviNHdMfTw0h+QRUHjhQwKD7EumTQ1d1yWSzttcoh8YC0aIgqhF5nULxjLeak97Ecz9PTslbWvdwyT8JdyHPwEPQvXE2Wf1+tWSzNtVxfKZb+CjkeLoqwXqgoMYgfJ62jCOWparO8BZMwF/c6QVRMyMkQpfV1Qo6GWD6qE8tJRYTjq2J+jfhZCscTq21Mgly7Wch5qRFyQMorLP++SmF9ZbXl+BUmcdny86qyUbpbZWq9bNsoyh6I+ULCl20QtjeIZevN8kQUV+G6cjt7HSmxDSGavKCzuSJuwnVnlTMiLOvE0l5tLlt3aAnqI4ZHYmyec2TzxLXeoKqihm/+uwqA2/54NXqD1BJqFUckoDppAmu7zaqwsJBPPvmkvYaXOBAXVyNDJ2rJq3vXH7VvLBcD48d0B+CXtSftnlsTWcGoNUYUj2qIKXfcuBLJpUj3Uu3/eY5Xwd66U+vOPWZkd7vH+vXL7ZQUlBPeM4jJN42wezxJ5+WCPSM//vhjq+tPnnTgD5Gk3Ykd1J3Ny/aSccz+MMgVl8ey4pcT/LoxlQfuGYKvm+19bGLWQ2oE9ElFGVaAKnvVSCQtE1iJElSJalYgx7FtFHLOlJN+uhSdTiFxaITd45UUaDooCWN7S6/I+SCraayZMWMGiqJYu2GbIbOiOw9RvbRENEc0zuvfJ5C4nv6knCxk3aY0rp9i/xMUAMd6oPZKRYkpRw2shnxHWDkSyaWF0r8hRJMVBrWObXK4a082oF3jXl72j+3WUEpeXVlrY0sJII2RlggLC+Ptt9/m+uuvb3H93r17GTZs2AVPTHJxiWxoTtWogmhBG+XhFb2eyyfGkHKykLUb07j+CsvGeYoYq3azTLBTPb0s13s1ekG8ITcSwk6jjCpBXaeVLBq7We7v3fC01YhvheXxKktbzwMoF/IAxDbwVsIjtJ5jIuYhuCiWT4Ci3LxRsdxezCOorBNaxzcrMFJt5B+7CscyCDkkenfLz0rUGTHphe/aRqDXaj7CZ2GubV1npF5olFddI+iACDkgopx7lY0cETEnpMZGjkiZIM0v/nkuwnflIiSFiOutckSEZVdBS6S5xo6ot6N4eIDeBH0bq2h6g3uza0PIGVGEXC1x2VoOXseuPdr9YfjQ8BZ+1GwtW+PWkLNUXdG21gKSS48LzhkZNmwYSUlJ51xvy2sicS4iYoNRFIWSgnLOnLa/2d3EcT1QFDh8NI/M7DLbO5wvJ/to/++TD96ynbxEYkF0AYprPWq5K+Q7qCVDA9U19ezdrxkjQweFOWTMY7tTARxXeXepcwlX01ywMfKHP/yBMWPGnHN9XFwca9euvdDhAZg3bx6JiYl4e3sTHBzMjBkzSE4+f9nyxYsXoygKM2bMsGseXQF3LzcGjIoFYMOScxuZ50tAgEdTTHnZKgfmDxUFoJ72QdGrKCNOO25cieRSoLcWRuFYKI6uT9i8LYPKqjpCgj3p7QAJ+PysIlZ8qumLXH3fBLvH6xJIOXhrxo8f3+p6T09PLrvssgsdHoD169czZ84cEhMTqa+v59lnn2XatGkcPnwYT8/Wa+dTU1N56qmnbM5TQpOlfNmsERzcmsL673Zx4yPTmm3QVnl4zbV83dV92ZGUyaq1qdxz+yDcXBtON9EdLJb6ugmlvZ5CsuqBARC5FXrno5zsha7ccr2xm2W1jVeZpavfW+zUKrjmg4ytJ9IVC656lzZ6AMXyT7FLsJvOctm6nFQI4zTrSqwolmEKMYxiEvTKXcUQklBaK4ZpxDwwRfisVPEJ10Zpr1jKWyuEYWprhbCMsL7GRtjGVlddMURWJ6wXQ25iKa4YdhGfOcXWA2IYxkP4YfD2sizX9fCwvEXrm+VpKN5CODNQRYko1j7yjGjwFdaL15V43YnhU2Fuq37VHiqmTY5DbzBYn1xtlINf9tF6TPUmBo7tzZhrBre6reTS54JMpPT0tqlrZmZmXshhWLFiBffeey8DBgxg0KBBLFy4kPT09FbDQwAmk4k77riDF198kZ49e17QsbsiE24Yhk6ncHTXKbJT8+web/jQCEKDvSgrr2XdpjQHzLCBIl/U1DDtXjckGStjSSLpisQ2eApzAqDCo/Vt20jumQr27te8LtMuj7N7vNqaOpZ/vAGAGb+dbPd4XQYZprEkMTGR3/zmN+zcufOc25SUlPDBBx8QHx/Pt99+e8ETFMcE8PdvvefJSy+9RHBwMLNnzz6vcWtqaigtLbV4dUX8Q3xJGK/lZKz8bIvd4+n1Oq6Zro33/fJjjs0h2tsb1aRDCS2EWAfmpEgknRGDGeIytH+nOL7R3C8bUlFVGJwQSmiIl+0dbJCyN53i/DL8Ar0ZK70i54+CA4yRjv4jWuaCjJHGMMnUqVMJDQ3l6quv5sEHH+SRRx7hzjvvZOjQoQQHB/Pxxx/zt7/9jUcffdTuiZrNZh5//HHGjh1LfHz8ObfbtGkTH330ER988MF5jz1v3jx8fX2bXlFRXbdr5DX3a6G1nxdupE6obLgQrprWG1cXPSdTi9l/6Izd4zVR6Q5HNaVYZVIO6KR3RNKFiS9AcatDLXeH047VFlFVlTXrNc/m1EmxDhmzUUKgx4AIqS8iAS4wZyQgIIB//etfvPLKKyxfvpxNmzaRlpZGVVUVgYGB3HHHHVxxxRWtGg1tZc6cORw8eJBNmzadc5uysjLuuusuPvjgAwIDz79T5TPPPMOTTz7ZtFxaWtplDZKx1w3BP8SXwtwSNi/dw8RZidZuvTbIw/v4uDN1ck+WrTjOd8uOMSgh3EoeXhFKe3G3zAFRvX0t11c0eEIyhqDGZaH418CoSjikdfQ1BlnmjPgIbeZrBYl0U4Eg6S3YNa5CooCbzjIvoVQsV7VhF+mERxNRDt4W4vDNS4/1dYIUvVHIgRDmbvXVCoMbDJZv6IXJKkLOh9VchQHFnBWxisJWjkhdrVCKK+SI1As5IvXi8W1453RWOR6tbm5diqsTly2f97z0lj+8Pm6Wt2APD8trw8XXMq/D4Hf2WlE8GkIxOjMk5mv/PtkPPBuuF6GtgmKVIyKW8gry8g25X8nH8jmdVYari55xY3qcPWnEBBqb7v+z6zOOa8ZIo76R5DyROiMt4+7uzo033siNN97oqPm0yNy5c1m2bBkbNmwgMjLynNudOHGC1NRUrr322qb3Ghu/GQwGkpOTiY21tuxdXV1xdXWsOFBnxWA0MP2+8Xz22jKWfrhOM0bs5IZr+7JsxXG27TxNZlYpEYEutnc6H+qNkDwQEnbB8Aw4EQjVDhpbIuks9M5D8a5BrXGF9B4OH74xcXXs6GgrY+lCST2k5RFG9rK/0V5XQtHpUOyshrF3//bCOWfVgKqqzJ07lyVLlvDrr78SExPT6vZ9+/blwIED7N27t+l13XXXMWnSJPbu3dtlvR1t5ap7tAqkA5uPk59dbPd4URG+jBgWjqrCd0vt631jRUYMar4nils9jJMtCCRdDLdaGNWQHJ7SR2ub4EDy8itZuUa7rqZf0cshY2Ycy2HHqgMAJIzr7ZAxuw6OSF51Ts+IUxsjc+bM4bPPPmPRokV4e3uTk5NDTk4OVVVnu7LefffdPPPMMwC4ubkRHx9v8fLz88Pb25v4+HhcXORT8/kQHOlPv8SeqKrKtp/3OWTMG2f0B2DVmhOUlDpQbVHVwbo4VJOCElsAPQocN7ZE4tSoMP4Uils9ar4HnHSMsdCcxd8eoq7ezKD4YAYNdIzQ2ed/W4bZrDLqqkHEJTioVYSk02NXmKa9eeeddwCYOHGixfsLFizg3nvvBbQyY52Tup06M4lTB3Bk50n2bUzmmvsFQaK2ysPr9AxOCKdXrD/HTxSy9JdT3HnTgLMbuAghMg9RDl7IGfERuvZWREJyOfQ/ARNOoUvpBTVnT22XKsu+F91qBMlxIYdEFYqp9KL2huVq3IXYeY2NpBFRIlwvDCi2nbd1dqutlDbXCZooYs6HtQyI5Rv1ovy5WcgZsfGQZTW+ufXxxXwecf96IT/HJOqWiMcXlvVWn62QEyNsL+aAeAjfvphjIuqOiDkiXoKcvpeX5QOSTzfLa8Hob5lPpXRrdi0kVKLEFmgN8XYNBk8/y8l7Cfo8Qm6WVQ6JMNfySlNTiObOWwe1oP0vfvm2c0jSk7NZ+/UOAO7+83VOm7/gtMickY7hfEpB161b1+r6hQsXOmYyXQytxHcpu345RGlhBT7+rYvM2UJRFG6cMYB5/9zIDz8d54are+PpoPgzAId6oUbmoPhUwJTTqMujcVZ3pERiN+51MKxBjfpgLBT5goPTL1avPUFNrYmePbqREO+YwRe89D1ms8qYqwfTa3C0Q8bsUlzCxoh0KUhaJH5UHD36hVNeXMnCl39wyJiXjetBVIQPJaU1fPvj+cv6nxdmPWwfhGpWUPoUw5B8x44vkTgRyrgsFNc61CJvOOyYctvmqKrKitUpAEyf1sshHdjzs4rYvHQPAPc+N8Pu8SSXFk7tGZF0HHqDnrn/vJ2npv+D5R+tZ/o944kb1BjftSEPL5b8mXUNY+q4765hvPTaWr5Zmsw1V/XBv5s7GCxd01alvkLYxqrUt6qhba3ZH5Jrod8ulMuyoDIU8nwx1FnKv7sK+imBggdOJ8RN9MWWOS6iK95D17rkuBj6EDu9iqEDcXyj8Hm21unVIIRh9GIMSEAMm5iFSl2dMJ64vdVXL3734vGEz0J0fuqF/cUwjji+wWD5PGUWthdDXuLx3IQQrygHL37WIuL4YljH28XyFuvjYxmW8fO1XDYGWoZWDAGWy4qPD4SUoMQ3NLM8PBK8uzUczMdycuJ1JC4bhfCo7myY5tjxAk6lFePioufyibEois5ivTaZtpX2bliShKqq9B8ZS0z/iFa3lZwDR/SWcdK0hjYbIxs2bLDrgBMmyIZInYVB4/sw8cZE1n2zk//+fhH/Xv203U9I48ZE06dXAMnHC/jsqwM8+psRDpptA+l9Ud3SUWLOoE48CMuGO3Z8iaQj0ZlhzHEA1PSeUHz+ekptYUVDBc340dFWeS0XyrpvNcXuSTfaLxfQZbmEwzRtNkbEZNK2oCgKJlPrIkkS5+I3r9zElmV7Obz9BGlHs+jRz74nGkVRePDuITz1l1/4aVUKM6/pS2SwIzVeFNjcF7VbOYpfpWaQ/C+8yTsjkXRqRp5A8a9ArTbA0UHtcoj8gkpWr0sF4KppjqnQKckv48jOBgNnxjCHjCm5tGjzHdpsNl/wSxoinY/A8G70H6E1Gzy09YRDxkyID2HksHDMZpWvvz/skDEtqDfAmgTUWj1KSAnK5FzHH0MiudgMLULpn6X9e2MfqGsfocZF3xymttbEgH7BDktc3b9Z8+b06BdOQKifQ8bsklzCjfJkzojEGuFkHTC6F3s3JHNw23Guvn/CecjDCzauEGtW9AZuvWkQ25Oy+GXdKe6+ZQAB/s3KDMWSQ3cbpb41lnLv1DWU8u41wIhNKMMKoTQAjms3Vpd6y5wRRYjzByjFFsti3oVbuWUOSmW15Xg1NtrQ20LMU7DVtt7YLAZsNFp+9mIOhphjIeZgiJ+FuN5WTohYASeeKuJ8xDuQavnRWh1P/PvEHBbx+UontFdShIwdo1BxJf514uit5esAeLhZnuveYumukDPiGmqZ52EMslxWAgK0f0QUwxVabyf1YD8ojYNgP8vJCblViocwloso/y58+DoDWdll/PyL9tAx+57hKM23sarkPX/59wNbNGNkoBQ5s49LOEzTLr7rqqoqMjMzrd4/dOhQexxO0s7Ej9Zahu/bkIzJRi+S8x6zfzDx/YOpqzfz9Q8OVmVt5EwE6rEGPZPxJyCwvPXtJRJnxKcKpiWj6EBNi4Rkx4ubNfLJF/swmVSGDw1nYLxj+saoqsqetUcAGCSNEck5cLgx8s0339CrVy+uvvpqEhIS2L59e9O6u+66y9GHk1wEBoyMxcvPg7zMIlZ9vsVh495+UwIAP65I4XRWmcPGteDYANS0bigGM1x5CHwr2+c4Ekl7YDTBlUdRXE2ouV6wezDtpZ+TcrKQtRtSAbjvDsflo6z7diepR7JwdXdh8IS+Dhu3S9JYTWPvywlx+KxefvllkpKS2Lt3LwsWLGD27NksWrQIOD8RM4nz4e7lxu1PTQfgq3+vxGQSi1MvjOFDw0kcFkF9vZl3Pt7TTueHAr/2QS3wQPGog2sPQKAD5eglkvZCUWFKMop/FWqFEVb2dXjvmeZ88MluACaN70Gv2ACHjFlVUcMH//cNALc9dRW+QumypI3InJHzp66ujpAQLTY/bNgwNmzYwA033EBKSopDhHMkHcPV91/GF//8idMpuWxZtpfx1w89u9Lqez0/3RFFgd89OJIH933Pzj3ZbNudy+jESKtW5oq7cAOrs5R3V+vrWl1PTTVsmYA6fguKXyncnQnLBkChprtgSwc2wL3CYtmjxDJHpbzC8vhVVZaJCmLbe1spJOLHJeqeiHkfhmbrDUJOhYvR8sdLlIM3iJoqgly5OJ7V5ARUG4aqKqzWW30YgvS+Yjl/a50Ty/nU1lruL+b7uNL6eGZT65oz4mfv6mo5nqen5S3Vw9syydTgZ6n1YQwUc0T8G/6lokxMRYkuRq3XweZEcPEDP/+zGwt6O4ooBy/mXlnljJyd+6692ezZl4PBoOO+u4ai6PTWuV+25OBbuL9/+a+fycssIjQ6gBsfvcJpfwg7DTJn5PwJDg5m//79Tcv+/v6sXr2aI0eOWLwv6Vx4eLtx3UOTAfjmzVUOGzcywpdZ12qu27c/3EW10DfGYdS6woaxqEW+KO51cO1BCG6n0JBEYi9Ds1Hi8zSRtq2DodCv3Q5VX2/m/YV7Abj+6r6EhTrGe1FVXs23838B4KFXbsbVXTYqlZwbhxsjn376KcHBwRbvubi48MUXX7B+/XpHH05yEbn+oUnoDXoO7zjJqcPWCcoXyu03xRMc5EHumQq++Oagw8a1os4FNo5BzfVCcauHaw5CjOzyK3EyeuejG3Na+/fu/pDpmETSc7Fk2TFS00vw8Xbl9psGOmzcTUv3UF1RQ3hsMOOuG+Kwcbs0MmfkLLYqZSIjI3F1daWwUJMrzsvL47vvvuPQoUOMHTvWzulKOpJuwT6Mnq4ltv38ySaHjevubuTh2ZpS6jffH2m/ZFbQDJJl8ajp3VCMZpRpR2F0AdZFnBJJB9C9GOXyUwCoe0LheI92PdyZvAr+9+UBAB68bxg+Pm429jh/1ny5DYApt4yUIXpHoeCAnJGO/iNapk05I9988w2PP/44gYGBmM1mPvjgA0aOHAlolTK7d+/mww8/5NVXXwXgD3/4A59//jmDBg3i+eef57HHHuOBBx5w/F8haV+a3Uiuunc8m37czS9fbOOBF2fh4mZsQZyh7bojY0f3IHHYCXYmZfLWgr3Me27i2RuYGOv2EPp11As5JLVCgmpLeQy7glBrD6LEnUI3OR81Qg+b4sCss9DtAFBcLbNK9B5VFstuZZbLtZWWOSQ1NZZ5DCYhL8HURh0So5VWSLN/CzkOYs6IlW6IkBOiiH+70UY/kjaiCqXhYs6Iwc3ylmQSwnbiZ+fqarlcV9d6Tki9qfXPWvzzDEIOjaurkJMj5IwYvC3zNPS+lstizsjZHBGgdz7K5cdR9CpqWggcGgjBgty7j9/Zf4t6O6LOiJgzYrDWFXl34T5qakzE9w9m2pQ+ljlBYn6QzV40Z5cLcoqbynkvv2UUEokt2uQZaa1SppE333yTQ4cOsWvXLv7whz+wZMkS5s+fz6ZNm3jrrbccOnnJxWfY5QMIivSnrKiCr//ruNwRRVGY8+AIjAYdu/flsnRFisPGbhFVB/sSUPcORDWD0icXrtkPXtW295VIHImiooxNRzftpGaIpIbC5oG09yPsjl2ZbNqajk6n8MhDiTYF7drC0g/XYzZrTfHCewbb3kFyflzC1TRtMkZaqpR57733eOmll5q20ev1uLu74+/vT1xcHEFBQQD4+vpKV90lgF6vY/YLNwDw+WvLOJ3iOKn1iHAfZt+jVem8t3APJ04VOWzsc3KiJ6yMR63Ro4SUwczd0Ke0/Y8rkQC416FcfxRlSA4A6qEemiHSzr2UKqvq+M+7mgbUzGv7EtOjm8PGLi+u5Pt31wBw4yNTHTauhEvaGGlTmKaxUiYhQROraqyUueeee5oqZQwGA9XV1bi5uVkkrJaXS/XLS4XJN49k9RdbSVpzmI+e/47nP/+t5QZtLfVVz7q6Z84YyJ792Wzfmckr/9rK/H9Ox90glvpauqNVkyDvLvRAsnLMi/WlJXpYH4E6fAeKfxHKzEzUZBV29AKTHoObZZhI72WZ06Ivs1xvKLcME7lVW4ZtzDVCKbKor9LW2t9mn7cihBUUgxgS07W6jNX61m9cVvuLCH+bWPorfhVqreV3qRNCZAZx/zrL7d2FMJNZWC8eTwxriYghOp2L5S1T72VZuqsXwjQ6T8tzQ+nW7Ec/tBSmHUbxqEGt08O2BCjvD80iNxZhGQDvs/uLpbzidWFV2tusZH7h4n3k5VcSGuzF3XcMcVgpL8D37/1KRUkVPfqFM/a6oU774ydxLtpkfp9Ppcwvv/yCq6t2gfr6no1pVlZW8v7779s7X4kToCgKv3n1ZnQ6hU0/7ubwjpMOHfupR8cQGODB6cxS3v1ol8PGbpVKT9h4Geqx3qgqKH2y4Nqd4C/LfyUORmeGoRlw3UHNECnxhFWj4XT7Vs00cvRYPj/8dAyAx+aMwt3NltLO+VNZVs13DeW8t//xGnROWrnRaVEcUEljZWQ6B22aVWRkJKGhLV8wjZUy5wrHBAcHk5iYeAFTlDgjMf0jmHbHGAA+efkHh47t6+PG00+MRVHg59Up7Nqb49Dxz4mqg8PxsGowaqULil8lXL0LhueCIqttJA7ArxJmHEAZkaH1mjkVDqvGQOnFUSY1mcy8+d5OVBUun9iT4UMiHDr+8gUbKCuqIDIuhAkzhzt0bAmXdJjGbhOptLSU//znPzzzzDO8//77bN++ncpK2f+jK3DH09dgMOrZvfYI+zcdc+jYgwaGct30PgD8+91dVFbV2djDgWT7ww8jUVODUPQquvFZKLNSwLvW9r4SSYuoMKwQbtyPElyBWqNH/aWXFpqpv3jN05etPE7KySK8PI385n7HGgtms7kpV+SWJ660UvOVdE7mzZtHYmIi3t7eBAcHM2PGDJKTky22qa6uZs6cOQQEBODl5cWsWbPIzW1bPqHdV8HMmTPZt28fiYmJLF26tGmSsbGxDBo0iC+//NLeQ0icjQbLOrRHEFfePY5lH61n4cs/8s+fn9K8Ym0u9RVWN+QZzL4nke07M8k5U87Hiw4y96EGz5rYpl4o9VXNgqS41XSEd/RC+aqxQSnyUDhqySnon4QSVQ73HYFj3VF2BEP1Wde24m0pF2+otqzIMVdYLqt1Qk5LfevLVojzb5ZDYuWVFHNAWtn3fPZvMzbyYWzKx4ufjTiemEPSxr5JtnJerMq6BRVRxU1QFfUWys49PMCjBsYno0RqCdlqbhDsGgLV7hAglOeKOSK+/haLSrOcEdwty4Rx9bBc1lve3ssq6/nfYk1T5N47h9AtQPDGtLmU15IDW45zJqMQT193Jt88stVtJRdIB8jBr1+/njlz5pCYmEh9fT3PPvss06ZN4/Dhw3h6aufgE088wfLly/n666/x9fVl7ty5zJw5k82bN5/3cew2RrZu3cq6deuaQjA1NTUcOHCAvXv3sm/fPnuHlzg5t//xalZ+upkDm4+x4fskLrvBcU9b7u5Gnnh0LE//30p+/Pk4o0ZEMnxwmMPGt40Cp3tCmivqyIMoIUXQLxU1NgP2h2uvuov3VCvpZBhNMDAdEjJQ3Oq1HjMHB8CJGC628pTZrPLmO9spK6slursvV1/Ry+HH+HnhRgAmzBiu6Q9JHI/igJyPhv1LSy2rBl1dXZvyPZuzYsUKi+WFCxcSHBxMUlISEyZMoKSkhI8++ohFixYxebLWMmTBggX069ePbdu2MWrU+enM2O1HS0hIwNBMTMfV1ZXhw4fzwAMP8N///tfe4SVOTlCEPzc9Ng2Af835hOzUPIeOP3RQONdcqd04X/vXFjIyO6DsttwT1oxAXTsMtdAHxcWEMjwD7twFY06Cn+wCLGmGWx3KyEyUe/ehjDilGSL5XvD9UK2U/CIbIqqqMv+j3azflIbBoOOR3450eAjl1OFMfv1qBwBX3z/BoWNLmqFTHPMCoqKi8PX1bXrNmzfvvKZQUlICaNW0AElJSdTV1TFlypSmbfr27Uv37t3ZunXr+f9p573lOfjb3/7Gc889R02NvCF3Ve5+9jriR8dRWVbNf3+/yNqVbie/vW8oveP8KS2r4ennfyU3r8L2Tg5HgewgWDEadXUf1CJ3zSgZmI3u/iMoM05CTKlMdO3KeNehjEtHuXc/yogsFDcTarE76vo+8OMQKPG0PUY78OmXh1i6IgVFgT8+PpaEASEOP8bCl75HVVXGXz+UPkN7OHx8iePJyMigpKSk6fXMM8/Y3MdsNvP4448zduxY4uPjAcjJycHFxQU/Pz+LbUNCQsjJOf/iA7t9zD169KC0tJT+/ftzyy23MGrUKIYMGUJUVJS9Q0s6CXqDniffuoffjH6RnasOsvGHPUyYMezsBlYxSqskEWG1ZQ6Hq7sbrzw/lSefWUHG6RKefmkD/3xlKgH+DToKVjkklm3ZRfNAEdycqlh+aHRpfbnCE9b3Rw0+Az1TUEJzUXqWovQsRa1wg6PBcCQMqrT9dN6Cqmt9fduWzTbyIJr//eLfYis+3LS9CnoVXHXaB1an03J9RMNSr8fiE22a2zmOI+4vzkf826xyTIT1da13dbZlCFvliNj6vIxCuMHdUrtDcXMDn0oYlAGxuSh67fhqoQ8cioWiWECBRlV3byFHRFwWJN4VUfK9mZaIla6IoMeD3siPPyXz2dda37BHHh7NpMvimg1ur66Itnx4+wm2LN+HTqdw73M3OG21xiWBA8M0Pj4++Pj42NjYkjlz5nDw4EE2bXJcb7JG7PaMzJo1i9TUVMaOHcuWLVu455576NGjB0FBQUybNs0Rc5R0AqJ6h3LLk1cC8NbvF1GS71h9Dj9fN/7216mEhniRlVPOsy+tpay8I6tbFDgTAtvGoi4dj3o0GrXGiOJZjTIsHW7bAZcfgegCTVfCmdGp0K8U5bZUlN8eRnnoKARVtbKD0sKrK6FCt0oYlgnX7Ua5aSdK7xxNyj3XH3XtcFg5pkE3pOM+m/2Hcnn7Q02n557bB3HtVX0dfgyTyczbTy8GYNpdY+ne52LmdHVBOrC0d+7cuSxbtoy1a9cSGRnZ9H5oaCi1tbUUFxdbbJ+bm3tOKZCWsNszcvDgQbZu3cqgQYOa3ktNTWXPnj1NqqySrsFtv5/Oxu+TSDuazZtPfs7/ffIbh7YACAzw5G9/ncbjT//EqbRi/vLKOv724uW4dPRvYZkn7O4He3ujRuVC3ClNWr5nvvaaoIcUf9QsLyh0hzwD1Ottj3uxaPBMqYd84UAAyqQsMLfwoSoq+FeDq0nzopgBYz2YFEi/ODoZHYpvDSQUoPQuQOl21tulqkCGP+zrDuXO8WNcVFzNq//YhNmsMvmyHtx+U3y7HGf5x+tJTkrFw8ede/8yo12OIelYVFXlkUceYcmSJaxbt46YmBiL9cOGDcNoNLJmzRpmzZoFQHJyMunp6YwePfq8j2O3MZKYmEhFhWUMv0ePHvTo0YMbbrjB3uElnYEGg8PF3YU/fjCbRyfNY8OSJNZdt5NJN45oQ6igEdHVfvY0DYvoxrwXpvL7Z1dy+Gg+8z9M4omHxQoewZUuji64ORWhtFc1CGEZN0FWu1xIonVvdv6Xh8K23qi+RRCZDhEZKO7VEJ+HEn82uVctd4N8P8jtBqd9oNT97EzF0IStUEZbcnTO9V3kBGj/968GYyaKrw+YmoUB9CbonwlxuWAwg2eN5lEByPeC7yMB1SrEhiDNbzNMI6CK+9sI+yjieOJ6sYzbqtRZOBf9zRCZDzE5KMElzealgzOBkBMBOWFQ0yD7HiCEToROungJRpunpZvcKvTi5We53q1Z+a54njbIvZtMZub9ZzuFRVV0j/Ll8Tlj0RmMtkNSVmGb1q/b0sIKFrz0PQD3P38DAaF+rW4vcQCNKqr2jtEG5syZw6JFi/jhhx/w9vZuygPx9fXF3d0dX19fZs+ezZNPPom/vz8+Pj488sgjjB49+rwracABxshjjz3GCy+8wFdffWWVwCLpevQe0oM7/jid/726lP8++TkDx/YmMMzX9o5tIKZHN579wwT+76U1/Lw6hdgevlx3leNLFe2ipJv2OpSA6n0aInPArxR8KlDcalG8qsErB3rkwEhQK100g6TSFSqN2v+rjFreSZVe+3etAeray6Oicjbkolrn8fTKhWGp8Es/SPeH4DKYlAxZfrAzumGj83VRqQ2H6WiXloDODN414FMNEcXQvRCl21kBR9UMnAmCtAjICtPEysScEifgsy8PsPdALm6uBp770yTc3dtnjp//bRnlxZX06B/BNbMva5djSAQ6QGfknXfeAWDixIkW7y9YsIB7770XgDfeeAOdTsesWbOoqanhiiuu4O23327Tcew2Rm688UYAevXqxQ033MDIkSMZMmQI8fHxuLi42Nhbcily21PT2frzfo7vSePvv13AvCWPOrxHxfAh4dx7x2A+/nQP8z9MwsPdwJSJMbZ3vOgocCZAezWg6ivBrwxCirRXYDGKRy142M6BUc1oRkmtXvt/TeO/9doPvN6seSx0qhZqaXypChwIh4JzhVMavTIN/29ujHjUQEIG7OwJ6Q1/R4EnZPtqc6524awx0wLjUiCoTAvvuNRrL4UGY8sIlS6aiFy14ez/aw1Qr4NaGv6v14y0KkMLInoNcz2ncaOCiwnc68C74f9eteBV0+z/NSge1iq/qhnI84P0IEgNBfzOcQznYOfuLBZ9cxCAx+eOJrq7X7scZ8/6oyx5W1NbfejlG6Xa6iXM+VRHurm5MX/+fObPn3/Bx7HbGDl16hT79u1rEjl79dVXSU1NxWAw0KdPH5k30gUxGA386YPZ/G78y+z+9TDfzV/TLq3Eb5kVT0FhJT8sT+Yfb+3AxcXAhDGdoIqrxgVyA7QXgLkaNaBMC32414J7tfYj714HbnXgVqtpV+hVzZPuVq+9aFs5vZrm34ox0oBZsc5J9a4G9xo4EUyT0aGgGTx15/EjFFqK4t9CiwiPOu0VcO72EVYhNhXNIDHpNFExo/lsBUtdg9HSOCfj/7d33/FNVvsDxz/pSJrultIFpewyCzJlr7KvgOgVvIgICg4c/FBRr0IBERDnvepFRYbjAiqX4UAR0FL2RvYutEAX3TNtk+f3R6HSdKQjadLyfb9eeWmecZ5zSJp8c873nMdQOKTkqK/wBASlwA4yNYVDT1e9IdEf8u7oWdCWfa61Xb+RzqL3d6MoMHJIcwb1b2aR66QmZrD4ieUoisLwSX3oOtgy+SiiFGacTWNrqh2MBAcHExwczKhRo4q2ZWRkFAUo4u7UKCSApxY/xL9e+IYVczfQsV8rmoc2KtxZMomj+PMSY9dGT28tc60CnnmyJ7m6ArZsu8TC9/egy+/B4H6Nyq2byqiXRjHKc1AZPVeMp/aqjVYpNM4LyDH6cs036vHI05XcrwRAJoUP4zwJvR5QUOz1hQmj9rngmF/4/4754JhX+P8GVeHN/gy3puWqlMKhB7tbwy4GP/A2EYw43UrMdHOBPA9AgcAUMDiApj44AagKr+mfBeebg5dXOQUCRzujaPIg37Hwiz3fsTCmcdKBJvfWf/NAnQdqXeF/HQsKe3kc9IUPx3zQ5BX2MDuXPr1X5WgoDEDKoOQ7QK6msCcnxwmytKBzgWwtZDtDjhb0ThR7w7k7FS/EeIVKjVF0YpxfZPTeKJbzAaA1ej2MlngvcbzjHfW5Y7n3rKw85iyKJDMrjzYh9Xl6WveS+TvGvZMmc0hKTuVVFIV3n15FclwajUICeOad8TKVtyapMMMwjVlqYnZmX8s6IyODNWvWsHz5cg4fPsyzzz5r7kuIWmLk5L4c/O0ke34+xuLHv2Dp7jk4qs37lrOzUzHjmXsxGBS2/n6Zd/61h4z0HMbeF2LW61ifCvQOhQ+DUQ7And2o1f2gMtyx7sjt6+Y5gkMBOOWAzhns9BAcUxgkXKvA7JGUMoIVnRMoRusclJfwqjKgOOoKgxeVUjgjSW9f+F+VUlgftb6wrlCY01Fwa3++Y+Gxxv8+DkbvR3sb/aQuR0ZmHuGLI4m5loZPPWfmvNYftaNlcot+WBbB/i0ncNQ48PqX03ByLrl8uBBVYbZvhsjISJYvX866detwdnamb9++HDp0yFzFi1pIpVIx8+NHOX3gElfPxvK/j7Yy/sXhZr+Ovb0dLz7XE3c3Df/bdIZPVx4lMyuPiePamXVqcZ3mmAfuGaC+lTfhk1zYO5GthcR6hUNLnf+E6Ebgng5B1+HP9pBfg3lhit2tno0yvgB1QPbd9XrHJ2Tx+oIIoq+l4+zsyNx/DsDbyzJjSRkpWax6cyNQmCfStF0tGBKta6wwm6amVKtWcXFxLF68mBYtWjBixAgKCgr4/vvviY2NZd68eeaqo6jFPHzcmPbW3wH45u2fSIpLtch17OxUTJvcmccmdCy81nen+OSLI+greRfXu5Z3KvTfDd0PQ54aWl2AbkcKe0B0TrCva+GQT9vT4JUKR0PheiAlp2GLmnIpKoUXXttK9LV0fLy1fLBoGC2b1zN9YhV9+8GvZKZm06RtA0ZNG2Cx64hyWHHRM0urcs/Ifffdx/bt2xkwYABz585lzJgxRbcTBuQX6d3M6LUPG38vGz/dzvkjV9n1w1FGT+tf7vElYmQTIbPq1jCFCpgw/h5cXdR8/PkBfvjlAtdiM3l9Zk/cXO/8BW+09kSJrnujYRDjHBGjPAHFyWi1Uq3Rc+OcEePnBUazOEosB19aDsmdFSgnIFAqGIzl1YPfW5fcrrIDb0CpD6dCipfnqYDKxHCAcV2Nb1NvMF7+3fh4o/Ir2p7bjPOPjNcZMR6mKbEcvFHPj8Y4h8SoF8LovaLSGOV8GOWAlNhvXJ7xWiK33pvHTsQzd3Ek2dn5NA72ZGF4GPV9jYa8zLTcO8DN2FQ2fvo7AJPn3G/22XGigupwAmuVa/Xzzz8zduxY5s2bx4QJE4oFIkLcSaVS0e/+rgB8+/4vJMQkWfR6o0aGMPuVvmg09hw5FssLr/7GtRtWuNtvraSU8rhzn+HWo5ypvMKiDh29wetv/kF2dj7t2/rxwaLh1Pex7OfvZ//8Dl1OHm26NePe4aEWvZa4O1U5GNmzZw9arZaBAwcSEhLC/PnzuXTpkjnrJuqQ4ZN6E9TCn8TrKbwy6kNSEi0bHPTpGcyHi4dR38eZazcyeP6V3zjyZ8XvIHn3UpXyuHOf3a2HBCLWsPfANcIXRZKfb6BHtyAWzxuMq6tl83YiNx4mYt1B7OzteGbJOOn1tiaVqrB3sToPG339VEo17/eelZXFt99+y4oVK9i7dy9du3ZlwoQJtG3blsGDB6M37qatBdLT0/Hw8CAtNrrSdzUUZUu4lsz/DV5MQkwyzTs04t2fX8TFw5kSeQclljuv5PLod3T1p6TkMHfBNk6fS8TOTsULT9/L8EGNjY43cdfc/OJTcRWj5+iMpvIan59X/K69it7EsIxxe/XG9Su5ONdfx1by783Un79xXUoMm5j5fFPDMMbDOsbDLsaMP3hLLAdv4o7NxtO+jYfsHI2elxjSMxqWMT7e+HmJ2T2FwzKKovD9xjMs//oYigI9uwfxxqsDcbxz1oypqbymlnsvZZgmJTGdqV3DSUvK5B8vj2Ry+P2IktLT0/EIaERaWppFvjNufyclL5uLu7OT6RPKKys7F++pcy1W16qq9uCRi4sLU6ZMYdeuXZw+fZq+ffuycOFCwsLCzFE/UYf4NvTm7R9m4unjxsU/o5k97hMKTNwSvrq8vLQseWsIg/o3xWBQ+OCTvXzx1TFJbBW1hk5XwHsf7+eLrwoDkb8Na8kbs/oVD0Qs5D8vryUtKZOm7RryyGv3Wfx64u5l1kyWkJAQlixZwrVr11i/fj0jR440Z/GiDmjYwp9FG2fg7K7lxO7zbPrsD4tfU+1oz6wZvZj4cOGdpb/beIa5b+8kK7ucHgYhbEBsXCb/98+t/Pb7ZezsVDwztSvPPdUdBwfLJyEe2n6KiP8dxM5OxUtLHzP7GkGiCurwbBqLvKPt7e0ZM2YMP/zwgyWKF7Vc8w6NeGph4XTfrxb+YLHpvndSqVRMHN+BV2f2Rq22Z/+hGzw3awtnzt+0+LWFqIrdB67zzIu/cPFyCh7uGhbOGcCYv7WukZwNXU4eH838LwCjnxpIi47BJs4QNeL2bJrqPmxQpUPdyMjIal2wb9++1Tpf1A1DJ/Zi86qdnD0UxRdz1vPK54//tbPEZ62Jqb7GOSTG4/x3/P+ggS1p2MCDeYv+4NqNDP7vn9sYN7YNjzzU/q9ub+M/VuPyjPMKjKdfGuWEKPnFp2uqjHNGSiz/XlD+fuO8ijuel0gBM5WDYXy88RddZfebup7xv21lc1yMpwabPL78pf5L1Md4Wre90Uek8WtvX/z4Eu8N46m6xtc3Lt/OgYICAyu+Oca6TWcAaNOqPq+/3A/f+i7Fzy/RFhM5IBXIEbltzXu/cuNyIvUCPJn0+miEsLRKByPGtxGuDJVKVSsTWoX52dnZ8ey7D/PcgEVsW7OPfvd34d7hHWrk2iEtfPjs36P4+LP9/L4jijXrTnHoaCyvv9ibwAAT924RwoLS0nN5c8lOjp9KAOCB0W14YlLnGhmWue30gUt898GvADyzZDwu7jZ8d8C7ze0ZMdUtwwZV+h1uMBiq/JBARNwppHMT7pvaH4AFkz7n9IGamxru5qrhtRf7MvuVfri5qrlwKZknZ/zMmv+dJC9f3qei5u09eJ1pL/zM8VMJOGsdmDOrD0893rVGA5GoU9d448F/k59XQM+RHekzulONXVtUgOSMCGEZTy9+iK6D26HLyeONBz/ixuWEGr1+316NWfrBCELb+qLL07Pymz958v9+5dDR2Bqth7h7ZWXn894nBwhfvIuU1FyCgzz4YNEQevco/+7T5rb/1+PMGLKEjJRs2nRrxqvLn5A1RUSNqfY6I5a0aNEi1q9fz9mzZ9FqtfTs2ZO3336bkJCy78i6fv16Fi5cyMWLF8nPz6dFixa8+OKLTJw4scLXlXVGalZOZi4vj3yXc4ev0LhNA/69/VW0rnfOpbfcOiS3nyuKwvaIy3y+8hApqYXrgvTo3pApj9xDcANXE+cbX9/Ecu7G64oY55gY19c4h8S4vDuPL/FvUc0/75rOOan27dGN832M8yTKzwcqkWNinENifLzxuiImyjN+vv9ILB9/dpD4xCxUqsJhmcmPdEKtvnWccU7JnfUvsY6IibaWkSOiKArfvv8rK+ZtQFEU2vVozvxvn8XN2+h9L8pUY+uMfLnIPOuMTHqt7q0zYkk7duxg+vTp7Nu3j61bt5Kfn8+QIUPIysoq8xxvb29ef/119u7dy/Hjx5k8eTKTJ09my5YtNVhzURlaFw1zVz+Dt58HV05fZ+6Epehy8kyfaEYqlYqwAc1YufR+7r+vFXZ2Kvbuv8aTL/zEJ18cJj1DZ7oQISooNi6TOQsjmb0ggvjELPx8XXhnwWCenNL1r0Ckhnzz9k8sn7seRVEYOaUvS356ETcvub2HTaru6qvmyDmxEJvuGTGWmJiIr68vO3bsqNSsnE6dOjFy5EjefPPNCh0vPSM17NZb8PSBS7wy6gNys3R0CWvLvDXTUTs5UhM9I8UPNxAdk8byr4+wd/81ANxc1fzj720ZOaQ5To7GN3uTnpEi0jNS7vPcfIV1m86ydv1p8vL02NurGHtfayaMa4+z1rHkbB8L94xsXbOXJdNWAPDUood44NnB5RwvylJjPSPfvI27c/USitOzc/B+5BXpGamOtLQ0oLD3oyIURWH79u2cO3eu3OBFp9ORnp5e7CFqXptuzXhr3fM4Oas5tO0U8yYstfgKrWVpFOTBvH8O4O35YTRu5EFGZh6frTzKxCd/YO2GM7JgmqgUvd7AL9suM3n6T3y19gR5eXruCfXjsw//xtTHOuGsdTRdiJldPB7Nh89/DcBDM4YWD0SEqGG1pmfEYDAwatQoUlNT2bVrV7nHpqWl0aBBA3Q6Hfb29vznP/9hypQpZR4/d+5c5s2bV7Ic6Rmxij8jz/L6A/9Gl5PHmKcGMv2d8eWfUN2eEhM9J/qCArZsv8ia708QF58JgKuLmjF/C2HM31rh7mL069Xk9U3sN9UTZHxvmvJ6Rkz9eRv/+jXudakk448T4wRIU/srXb5xz4GpnhZT928xlfNRomel/OcKdhw4fIPPVx0h5nrhjxw/X1eemNSJvr2CsSuxzoiJ8u+8fhVzRAAyU7N5pu8CYqMS6TakPW9+/yx2pu7zI8pUYz0j/11inp6RCbNsrmek1gQjTz/9NL/88gu7du2iYcOG5R5rMBi4fPkymZmZbN++nTfffJONGzeWuUaKTqdDp/srJyA9PZ2goCAJRqxFUdj1wxHmTVgKwOPzxjJ+5rByjy/+3LzByO3y9HoDv0dGsfq741y79cWidXLgvmEteGBUCF6e2gpeX4KRsvZXunwbDkZOnUlk5eoTRWuGuLtpmDAulJHDWqK+tcBeiWGZGghGFEVh4eRlRPzvIP7B9fgkcjbu3i4yLFMNNRaMrH7XPMHIP16yuWCkVtxs4Nlnn+Wnn34iMjLSZCAChQtqNW/eHICOHTty5swZFi1aVGYwotFo0Gg0pe4T1tF7VCemvfV3Pn/9e5aHr8fN05mRU6y7eq+9vR2DBzRjQO9G7N4Xw+rvT3L5SgrfbTzDxs3n6dsjiJ7dG9K5gx9ap1rxpyUs4FJUCqtWn2D/4RsAODraMWZkCP94sB0ubtZfQOy3/+4h4n8HsXew558rpxUGIkJYmU1/YiqKwnPPPceGDRuIiIigSZMmVSrHYDAU6/kQNu7WL7S/vzCU9JQs1r67mX/N+C+uns70G9u1lOONN5hIYixnOfVCxre5L36+g9qOfn2b07dPM/YfvMZ/vz3G2fM32bbjCtt2XEGttqdzxwB69WhEz25BuDobLRFu6volnhtXr7z8AlPJvqY6QivZUVrJng5VNRNWSx5d9SXPS1XppNDC55lZeUTsusrWPy5z5tzNW0WpGDa4BRPGdShcyr2c8/+6fmV6O0y1taRrF+L4+KU1AEx6YzStuzUzeY6wIXV4BVabDkamT5/O6tWr2bRpE25ubsTFxQHg4eGBVlv4C+PRRx+lQYMGLFq0CChcm6RLly40a9YMnU7H5s2b+frrr1m6dKnV2iGqbkr4/WQkZ/LzikgWTvkCRYH+D5QSkFiBSqXi3m5BdOscwOmziezcc5Xd+2KIT8hk74Fr7D1wDQcHO+7t0oDhg5vTqYM/9va1KmdclEOvN3D0RBzbIqLYuTea/PzCINLOTkW/3sE8+nAHGjb0snIt/5KbrePtaSvIzdLRsW8ID/1fOUOfwjaZ40Z3deVGeTXpdgBhPLyycuVKHnvsMQCio6Oxu+PXTFZWFs888wzXrl1Dq9XSqlUrvvnmG8aNG1dT1RZmpFKpeO79CeTl5LN1zV7eeWolAU3qE9KpsbWrVkSlUtG2tS9tW/vy5JQuRF1NYdfeaHbuucrV6DR27Yth174YvDyd6HVvEH17BNG+TX0JTGohg0Hh7IUk/oi8wo490aSm/dXj2iTYk8EDmzGwXxO8vaw/HHOnvNx8wsd/wtlDUTi7a3n508ny/hM2pdYksNYkWWfExigKer2B8HEfs3/LCXwCPfl4x+vU8/e8fUCJ48t/biqh1NTxitFu46TPv/ZHXUnhl98usH1HFBmZfy3k5umhoUvHADqG+tGxnS++Ps7lXM+4+PL+ZK07TGNyqMDc64rUwDCNXm/g5Jmb7NoXw+7917mZnFO028NdQ9+ejRg8oCkhLeqhMpqRYvIuweYcpjGu+y35eQXM+8dS9m85gZOLhsUbZ9D23uaSsGpGNZbA+t2H5klgfWiGzSWwSjBSCglGbFNWeg7PD1hI9LlYWnVpwnu/vHxrUTRjlf1CNp5NY2J2SyWDFVDIz9dz7HgskbuvsnvfVTIyiq8wG+jvRnCwB/6+rvjVd8HP15UWzbwLcw0qUH6ZKvvnXemPA+Pja/gLztQXqqlgpJT96ek6Tp1N5NzFJM5dSOL8xaRigaRW60CPbkEM7NeUzvc0KH4ju8oGGyaDqXKCkQoEWgX5BSyY9Dm7fzyKRqvmrfUv0KFP2bfTEFVTY8HIun+bJxh58HkJRmoDCUZs1/VL8TzX/y0yUrLpM7oTryx7HI3WKEHUBoORO+XnFXDiVDxHj8dy7Hgc5y8mYShjpVTf+i60be1D+9a+hLSoR+NGHjiWuIurBCMV31/yyz8pOYeTZxI4fjKBE6cTuBKdVqIYNzc1PbsF0btnMJ06BP61ZHsFE1yL1GAwcjM2lXefXsnh7adxVDsw//vn6DKoLcL8JBipPpvOGRHCWINmfrzx1VO8PvZf7Nx0hLirN5n99VMENK5v7apVmIODHfd0COCeDgEAZGXpOHPuJrHxGcTFZxIfn8mNuAwuX0klITGLhMQs/oi8CoCjgx1Ngj1p3tQLv/oueHk54e3lhI+3M4EBrjhp5E+6NIqikJGZR2xcFjfiM4m6ksrFqBQuRaUU3RjxTo0autO6pQ8tW/oQ0tyHpk28cHCwQ2WjyX/Gdm46zAfPfU1GShZqJ0fe+PJJCUTqBJX5hzZthHxyiVqnU//WvLX+BRY+9jkXjkUzve8CXln2BN2Htrd21arExUVNl06Bf2241TuRk5PP2fM3OXE6nlNnb3LxUjIZmXmcv5TM+UvJJcpRqcDf14XgIA+CGrrj4a7B1dkRV1c1bi5qPD01eHtqcXNVY2ej0/uqS683cDMph5jr6VyJSeNKdDpXotO4HptR5hL+KlVh8mn7tr6EtvWjfRtfPD1u3Rm1jDwMW5WVnsN/Zq3lt//uAaBZaBCvLX+C4FaBJs4UtUIdnk0jwzSlkGGa2iHhWjJvPrKUs4eiAJj42n1MfO2+Uta6qOawTaWPN95t4mZzpoaFii6rEBefybnziVy+kkJSUjbJqTkkp+SQeDOrRB5KWeztVXh6OOHh7oSHuwZ3dw3ubhqcnR1xdnLA2dkRJ40D9vZ2ODiocLg16yI7p4Cc3AKyc/IpKDCgdXJAq3VA6+SA2tEeBVAMCgqFM4ycNPY4aRxwcnLA0dEORbn9T6fg6GiPTz3nYvdk0esNxMVnEnM9nazsfNRqexwd7FCr7TEYFLKz88nKyScrO5/s7Hyyc/LJySkgN7eA5NQc4hOySLyZhV5f9kdaPW8tAf5uBDX0oHlTb5o3rUeTxp5ob+ceVTbHxNSqpyWKq/iS7aWXV3YC69WzNwgf/wnXLyWgUqkYN3MYj74+Gke1/Oa0tBobpln/H9xdqjlMk5WD99hnZJhGCHPxbejNe1tm8ekr3/LjFxF8vehHkmJTef7DR+rktEWVSkWAvxv+vi706924xP6U1ByuRqcSHZPG9dh0MjLyyMwqfGRk6EhJzSU9Q4der5CUnEPSHbNCrMXZ2REfby2KArHxmRQUmAjcKsDBwY4Af1eaBHvRuJEnjYO9CGrgjr+fKxqjYazKLkdvq+Kjk5h13/skx6VRv6E3r33xOO17S6KqqD0kGBG1mlrjyPMfTKB5h0b864Wv2bxqJ9kZucz6fMpd94vQy1OLl6cTHUP9yzwmP6+A1LTcosAkLV1HerqO9Awd2TmFPQ45Ofnk5Bag1xvQ6wunVStK4SwSrdYRZ60jDg525N7qJcnNLSAvT49KVfjlrlIVrseRqyvstcjVFZCfb0ClUt0a9VCRqyso7N3Izif6juETjdqeBoFueHg4kZ+vJz/PQF5+YdnOzo64OKtxcXHEWavG+VZ9tE4OeHg44e/rgp+fG95e2juGoepGsFGe9KRMXrv/Q5Lj0mjcOpB3N7+Eh4+btaslLMHOrvpDhzY69Hh3fVqLukmlYsTkvrh6OrNoSuENwLIzcpn99ZM4OWso2fVd8vxiTA3DqCo5bKMyvhuq8X6jDwcT5ZVYu6LYjfLKH3VVOzng6+SEr19ZR9TcqG1OTj43k7JJvJmFokBQA3d8fFwqmc9SyWCjsuuQmBp2qe46J9WcDaTLyWP2uI+JOR9H/QZeLNzwggQidZnKDAmsNtobaJshkhBV0Pf+Lsz//jk0WjUHfjvBzKFL2Lv5TwwlcjKELdBqHQlq6EGnjoF0vicQX1/XOptYawkpCenMGf8Jp/dfwtXTmYUbXqB+A29rV0uIKpFgRNQpXcPasXjjDFw8tFw4Fs2ccR/zRNdwNq/aSV5u6bMphKhtdm46zNRu4Rz5/TRqJ0fmr51O49YNrF0tYWkq1V8zaqr8sM2AX4IRUee069mCLw7O56EZQ3F21xJzPo4PnvuKqffOJer0dWtXT4gqS0/OYvETXzD/kU9JS8qkabuG/Pv312jfq6W1qyZqwu1hmuo+bJDkjIi6R6XCJ9CLqQv+zj9m/Y3NKyNZ99Fv3LiUwPMDFzHrs8n0Gd35jhNM3C+l0jklxhWqbI6JianJJoov/9jqrrBqSiXrXunyTB1e2eMreb3q3vvG5Pml10dRFP74/gBLX/2W1MQM7OxUjJs5nIn/HHXXJWqLukl6RkSd5uKu5e/PD+HzveF07NeK3Cwd8x/5lJXzN6DXSy6JsH3ZGbksnLyMRY9/QWpiBsGtAvhg6ytMmTtWApG7TbWHaMywaJqF2GathDAzDx83Fm+cwQPPDgZg9TubeW3Mh1y/lGDlmglRtitnrvNs/7eI+N9B7B3smfTGaJbunkObbs2sXTVhDXYq8zxskAQj4q5h72DPU4se4rXlT6B2cuRoxBmmdg/ny7d+QJdTsdVLhagJiqLw61e7eLbfQmLOx+ET6Ml7v7zEI6/8TXpDRJ0k72pR9xmNyw98qDstOzXmk5fXcGjbKb5Z/BPb1u7j6UXj6DGyg+nl5Cubl1DixrbGeQPVvLNuedUpcaypupv7Lrzm/hVW2XU5TBVX2fpVd50QE+VReH+Zj19azbY1+wDoPKgNryx7HK/67jabfChqSB2+N41t1koIC2vY3I+F619g9tdP4RPoSdyVm4Q//AnPD1zE0R1nrF09cRdSFIVdPxxh2r1z2bZmH3Z2KibPGcPC9S8UBiJCyGwaIeoelUpF3zGd6RrWltXvbmbDf7Zz9lAUs/72Pvf0b82EV0YS2qulrf7tijrkzMHLfPbP7zm17yIA/o19mPXpZJmyK4qrwz0jEoyIu49RdKF10/L4vAe4/5kw1rzzMz8t38HRiDMcjThDUEt/Rk7uy+CHe+Bez7WM8qpdofJ3V2qopZpDSuZmaiqxxetn6anBlR+GudONywmsnL+RiP8dBECjVfPg80MY93/D0Lo6Va4uQtRiKkWp9MIDdd7t2zWnxUbb1C2WRc2Iu5LI2vd+Yft3+8nN0gHgqHZg6MRePDFvLC4ezkZnmFoHpJp/YpU638b+nCUYKXVrelImXy/+kR+/2IG+QI9KpWLIhJ48NmcMPoFelauDsLr09HQ8AhqRlpZmke+M299JKb99g7uL8edPJcvKysZryCMWq2tVSTBSCglG7nK3/iSy0nP4Y90Bfl4RycU/owGo38CLmZ9MosugtneeUKHyqlufCh5cvWuZmwQjxZ7l5xXw4xcRfLP4RzJSsgHoEtaWx+eNpXloI+v3ZIkqqbFgZOtq8wQjg/9hc8GIDNMIUQYXdy1/m9KPv03px7HIs7z/7FfERiXy2pgPGT6pD0++9WApvSRClKQv0LNt7T6+WfwjcVeTAGjariFPLnqITv1bW7l2QlifBCNCGCtl+feOfVvx2d5wVsxdz8ZPf+eXL3cSufEQIyb1YcxTA/ENqlfx8izae1HNX9bm7ii19C99c5df3am+RnQ5eezd/CdfLfyBmPNxAHj7efDoP0cxbFJv7B3sq1hRcVeSBFYhhNZFw/R3Hqb36E7864VviDkfx/f//o31/9nO8Em9uf/pQQS19C9lnRJxN8nT5XN4+2ki/neAPT//WZR35OblwviZwxk1rT9Ozhor11LUSiozrKBqo59PEowIUUkdeofwxcF5HPztJOs+3sqxHWf5afkOflq+g/oNvenUvzWdBrSmfa8W1G/gbe3qihqQmpjBwa0n2L/lBIe2nyIrLadon0+gJ8Mn9eGB6WEyrCdEGSQYEaIK7Ozs6D4slO7DQjm+6zyr3/2Z4zvPk3gtmS3f7GbLN7uBwi+i1l2b0rprU9r1bEHLe4Kxd7DNblJROXq9gV0/HGX9J9s4c+Ayd84F8Pb3oN/YLvR/oCutuzaV3jJhHjJMI8RdzMQXSWjvloT2bkluto6Tey9y5PfTHN1xlssnr3HzRio7Nx1h56YjAGhdNbTr2YIOvUPoN7YL/sE+Fbi+ORpRQaXky5S7v7LMXZ7Zma6PwWBg25p9rH3vF2IuxBVtb96hEd2GtKP70FBCujTB3t7OBtsnajVzrKBqo+9JCUaEMBMnZw1dBrUtmvabk6XjwtGrnDl4mdP7L3FizwUyUrI4+NtJDv52khVz19N7dCcefG4Irbs2tXLtRWmS4lL55ctdJMQkk5utIzdLR2xUIlfO3ADAzcuZMU8NYsRjfWR9ECGqQYIRISxE66Ip6jWBwl/UUaeu8+fOc+z75ThHI84QueEwkRsO065Hc0ZO6UfPkR1xdpOVN60tISaJbz/cwi9f7iRfV1Biv7ObE/94eST3PdFfXi9Rc1QqMwzTSM+IEHVTBf+47eztaRbaiGahjRg7fTCXT8aw7qOt/PHdfk7uvcjJvRfRaNX0GNmBgX/vTsd+rdC6aKjZcRpTwyjVnKZczeXTzUlRFJJiU7l04hpJN1JIT84iLSmThGtJ7PnpGAX5egDadG9GtyHtcHLWoHXR4OSqoUOfEOr5e9rsB7uoo6wwTBMZGck777zD4cOHiY2NZcOGDYwZM6Zov6IohIeHs2zZMlJTU+nVqxdLly6lRYsWlbqOBCNCWEnTdkHM+mwKU8LvZ/PKSLZ/t58blxKIWHeQiHUHsXewp3mHIFp3a0bz0CD0+XrSU7LISMlCl5PHPf1a021oexzV8mdcUTmZufzy1S72/3qcS8djSEvKLPPYjv1aMWHWSDr0CZEEVGEbrJDAmpWVRYcOHZgyZQpjx44tsX/JkiX8+9//5ssvv6RJkybMnj2boUOHcvr0aZycKt5rKMvBl0KWgxc16tafoKIonD9yhd+/P8DOjYdJvJ5i8lR3b1f6P9iVQeO60zy0EWonx+pWxsR+Sy/gZpkv/YyULDZ+9jsb/rOdjJSsou129nY0aumPf7AP7vVccfd2xd3bhQ59QmjTvVkFqitBiqjB5eAjN+Lu6lK9sjKz8Oo7pkp1ValUxXpGFEUhMDCQF198kZdeegmAtLQ0/Pz8WLVqFePHj69w2fKTSggboVKpCOnchJDOTXhq0UMkxCRzat9Fzh6O4srpG2i0aty8nHH3cqGgQM/OjUdIjk/jh8//4IfP/wAKpxIHNPHFP7geAY198Gvkg19wPer5eZCfV0BOlo7c7DxQFJp3CMbdu3ofbLYmKy2b2Ks3SbqRSnJ8GskJ6cRfTWLH+oNkZ+QC0KCZL6OfHEjbe5vTuHWgGQI4IWqInRkWPbt1fnp6erHNGo0GjaZyi/FFRUURFxdHWFhY0TYPDw+6d+/O3r17JRgRolYp5de1SqXCL9gHv2AfBo67t/jOWz0pTy8ex5GIM2xbs5d9v54gOz2HmzdSuXkjlRO7K3bpJm0b0L5XS1p0aER+XgFZaTlkZeQUBizcHqJWodY4Ui/QE9+G3vgGeePt54HGyRFHjSOOGocKDWPo9QbSkzJJjk8jN0uHg9oBtcYBB0cHFEUhOyOX7MxccjJyKcgvwM7eDnt7e+wd7EhJzODK6etcOXOdq2dukJudh4u7tuiRm60j7urNopvPldXWf7w8kj5jOhdOuy3j314Im2XGYZqgoKBim8PDw5k7d26lioqLK5za7ufnV2y7n59f0b6KkmBEiFrK3sGermHt6BrWDkVRSLuZSeyVxFuPmyREJxEXnUT81ZukJKSj1jji5KrByVlDni6fG5cSiDp1nahT16tdF1dPZxo296NRSACNQgJw93Yh4Voy8dFJxEcnkRCTRMK1FAx6gxlaXigztfTAw9PHDZ8GXnj7eeDt546Xnwdtuzej65B22NnZ5oJPQtS0mJiYYsM0le0VMTcJRoSoA1QqFZ713fCs71bhNUtSEtM5uecCx3dfIPpcLFoXTWFPg4e26N4piqKAArk5edy8nkLCtSQSYpJJTcwoVlZmajZnD0Vx9lCUyXp6+LiidXWiIF9PQV4B+XkFqFSgdXXC2dUJrasTDmoHDHoDBr0BvV6Pi7szjdsE0rhVII3bNMDV05ms9JzCR1o2aic1/o198G9UD62rTLUVdZQZZ9O4u7tXO7/F398fgPj4eAICAoq2x8fH07Fjx0qVJcGIEHcpr/ru9BndmT6jO1f6XEVRyM8rIF9XQF5uPqmJ6USfjyPmfBzR52LJTMvGt6E3fkH18GtUD9+gevgH18PL113uVCtEVdnYcvBNmjTB39+f7du3FwUf6enp7N+/n6effrpSZUkwIkRtYwN5DiqVCrWTGrXGERd3LV6+7jRp29B03So7ec8G2irE3SwzM5OLFy8WPY+KiuLYsWN4e3vTqFEjZsyYwYIFC2jRokXR1N7AwMBia5FUhAQjQgghRG1ghUXPDh06xIABA4qez5w5E4BJkyaxatUqZs2aRVZWFtOmTSM1NZXevXvz66+/VmqNEZB1Rkol64wIUUGVvfGd9IyIOqjG1hnZv8U864x0H2qxulaVpJYLIYQQwqpkmEYIUXWV7bmQng4hqs7OrvBR3TJskAQjQgghRC2gUqmqfZ8kW73PkgQjQgghRG2gUplhaq9tBiO22V8jhBBCiLuGTQcjixYtomvXrri5ueHr68uYMWM4d+5cuecsW7aMPn364OXlhZeXF2FhYRw4cKCGaiyEEEJYyO2pvdV92CCbDkZ27NjB9OnT2bdvH1u3biU/P58hQ4aQlZVV5jkRERE8/PDD/PHHH+zdu5egoCCGDBnC9evVv/+GEEIIYT12f63CWtWHjX7t16p1RhITE/H19WXHjh307du3Qufo9Xq8vLz4+OOPefTRRyt0jqwzIoQQoqJqap2R1CMRuLu5Vq+sjEw8O/W3uXVGalUCa1paGgDe3t4VPic7O5v8/Pxyz9HpdOh0uqLn6enpVa+kEEIIYQlWWIG1pthmf00pDAYDM2bMoFevXrRr167C573yyisEBgYSFhZW5jGLFi3Cw8Oj6BEUFGSOKgshhBDmc3udkeo+bJBt1qoU06dP5+TJk6xdu7bC5yxevJi1a9eyYcOGctfJf+2110hLSyt6xMTEmKPKQgghhKiAWjFM8+yzz/LTTz8RGRlJw4YNK3TOu+++y+LFi9m2bRuhoaHlHqvRaNBoNOaoqhBCCGEZdXiYxqaDEUVReO6559iwYQMRERE0adKkQuctWbKEt956iy1bttClSxcL11IIIYSoAUUzYqpZhg2y6WBk+vTprF69mk2bNuHm5kZcXBwAHh4eaLVaAB599FEaNGjAokWLAHj77beZM2cOq1evpnHjxkXnuLq64upavSxkIYQQQpifbYZItyxdupS0tDT69+9PQEBA0ePbb78tOiY6OprY2Nhi5+Tl5fHggw8WO+fdd9+1RhOEEEII86jDi57ZdM9IRZZAiYiIKPb8ypUrlqmMEEIIYVWqW4/qlmF7bDoYEUIIIcQtdTiB1aaHaYQQQghR90nPiBBCCFEb1OGeEQlGhBBCiFqh7uaMyDCNEEIIIaxKekaEEEKI2kCGaYQQQghhVXV3lEaGaYQQQghhXdIzIoQQQtQKdbdrRIIRIYQQojaowzkjMkwjhBBCCKuSnhEhhBCiNlBhhp4Rs9TE7CQYEUIIIWoFyRkRQgghhDVJzogQQgghhGVIz4gQQghRK8gwjRBCCCGsSYZphBBCCCEsQ3pGhBBCiNqgDveMSDAihBBC1Ap1N2dEhmmEEEIIYVXSMyKEEELUAiqVClU1h1mqe76lSDAihBBC1AZ1OGdEhmmEEEIIYVXSMyKEEELUCnU3gVWCESGEEKJWMMMwjQQjQgghhKgyyRkRQgghhLAM6RkRQgghagXJGRFCCCGENckwjRBCCCGEZUjPiBBCCFEb1N1RGglGhBBCiNqh7kYjMkwjhBBCCKuSnhEhhBCiNqjDCawSjAghhBC1QR0ORmSYRgghhBBWJT0jQgghRK1QdxNYJRgRQgghagMVZhimMUtNzE6CESGEEKI2kJwRIYQQQtytPvnkExo3boyTkxPdu3fnwIEDZi1fghEhhBCiVlCZ6VE53377LTNnziQ8PJwjR47QoUMHhg4dSkJCQvWbdIsEI0IIIURtcHuYprqPSnr//feZOnUqkydPpk2bNnz66ac4OzuzYsUKszVNckZKoSgKAOkZGVauiRBCCFt3+7vi9neHpa9jjjLS09OLbddoNGg0mhLH5+XlcfjwYV577bWibXZ2doSFhbF3795q1+c2CUZKkXHrxQpq2dbKNRFCCFFbZGRk4OHhYfZy1Wo1/v7+ZvtOcnV1JSgoqNi28PBw5s6dW+LYmzdvotfr8fPzK7bdz8+Ps2fPmqU+IMFIqQIDA4mJicHNzQ2VjWYeW0p6ejpBQUHExMTg7u5u7erUKGm7tP1uazvc3e03V9sVRSEjI4PAwEAz1u4vTk5OREVFkZeXZ5byFEUp8d1WWq9ITZJgpBR2dnY0bNjQ2tWwKnd397vug+k2abu0/W50N7ffHG23RI/InZycnHBycrLoNUrj4+ODvb098fHxxbbHx8fj7+9vtutIAqsQQgghSqVWq+ncuTPbt28v2mYwGNi+fTs9evQw23WkZ0QIIYQQZZo5cyaTJk2iS5cudOvWjQ8//JCsrCwmT55stmtIMCKK0Wg0hIeHW3380Bqk7dL2u9Hd3P67ue2VMW7cOBITE5kzZw5xcXF07NiRX3/9tURSa3WoFEvPRRJCCCGEKIfkjAghhBDCqiQYEUIIIYRVSTAihBBCCKuSYEQIIYQQViXBSB1X1ds+r127FpVKxZgxY4ptVxSFOXPmEBAQgFarJSwsjAsXLlig5uZh7vY/9thjqFSqYo9hw4ZZoObVV5m2r1q1qkS7jBdYqk2vvbnbXldfd4DU1FSmT59OQEAAGo2Gli1bsnnz5mqVaS3mbvvcuXNLvO6tWrWydDPuToqos9auXauo1WplxYoVyqlTp5SpU6cqnp6eSnx8fLnnRUVFKQ0aNFD69OmjjB49uti+xYsXKx4eHsrGjRuVP//8Uxk1apTSpEkTJScnx4ItqRpLtH/SpEnKsGHDlNjY2KJHcnKyBVtRNZVt+8qVKxV3d/di7YqLiyt2TG157S3R9rr6uut0OqVLly7KiBEjlF27dilRUVFKRESEcuzYsSqXaS2WaHt4eLjStm3bYq97YmJiTTXpriLBSB3WrVs3Zfr06UXP9Xq9EhgYqCxatKjMcwoKCpSePXsqX3zxhTJp0qRiX8YGg0Hx9/dX3nnnnaJtqampikajUdasWWORNlSHuduvKEqp22xRZdu+cuVKxcPDo8zyatNrb+62K0rdfd2XLl2qNG3aVMnLyzNbmdZiibaHh4crHTp0MHdVRSlkmKaOun3b57CwsKJtFbnt8/z58/H19eXxxx8vsS8qKoq4uLhiZXp4eNC9e3ez3kraHCzR/tsiIiLw9fUlJCSEp59+mqSkJLPWvbqq2vbMzEyCg4MJCgpi9OjRnDp1qmhfbXntLdH22+ri6/7DDz/Qo0cPpk+fjp+fH+3atWPhwoXo9foql2kNlmj7bRcuXCAwMJCmTZsyYcIEoqOjLdqWu5UEI3VUebd9jouLK/WcXbt2sXz5cpYtW1bq/tvnVaZMa7FE+wGGDRvGV199xfbt23n77bfZsWMHw4cPL/EBZk1VaXtISAgrVqxg06ZNfPPNNxgMBnr27Mm1a9eA2vPaW6LtUHdf98uXL7Nu3Tr0ej2bN29m9uzZvPfeeyxYsKDKZVqDJdoO0L17d1atWsWvv/7K0qVLiYqKok+fPmRkZFi0PXcjWQ5eAJCRkcHEiRNZtmwZPj4+1q5Ojato+8ePH1/0/+3btyc0NJRmzZoRERHBoEGDaqKqFtGjR49iN73q2bMnrVu35rPPPuPNN9+0Ys0sryJtr6uvu8FgwNfXl88//xx7e3s6d+7M9evXeeeddwgPD7d29SyqIm0fPnx40fGhoaF0796d4OBgvvvuu3J7T0XlSTBSR1X2ts+XLl3iypUr3HfffUXbDAYDAA4ODpw7d67ovPj4eAICAoqV2bFjRwu0ouos0f5mzZqVOK9p06b4+Phw8eJFm/lSMsctvx0dHbnnnnu4ePEiQK157S3R9tLUldc9ICAAR0dH7O3ti7a1bt2auLg48vLyauz28dVlibar1eoS53h6etKyZcty3xuiamSYpo6q7G2fW7VqxYkTJzh27FjRY9SoUQwYMIBjx44RFBREkyZN8Pf3L1Zmeno6+/fvN+utpM3BEu0vzbVr10hKSir2BW1t5rjlt16v58SJE0Xtqi2vvSXaXpq68rr36tWLixcvFgXeAOfPnycgIAC1Wl1jt4+vLku0vTSZmZlcunTJpl73OsPaGbTCctauXatoNBpl1apVyunTp5Vp06Ypnp6eRdMWJ06cqLz66qtlnl/aDILFixcrnp6eyqZNm5Tjx48ro0ePtsnpnYpi/vZnZGQoL730krJ3714lKipK2bZtm9KpUyelRYsWSm5urqWbUymVbfu8efOULVu2KJcuXVIOHz6sjB8/XnFyclJOnTpVdExtee3N3fa6/LpHR0crbm5uyrPPPqucO3dO+emnnxRfX19lwYIFFS7TVlii7S+++KISERGhREVFKbt371bCwsIUHx8fJSEhocbbV9dJMFLHffTRR0qjRo0UtVqtdOvWTdm3b1/Rvn79+imTJk0q89zSghGDwaDMnj1b8fPzUzQajTJo0CDl3LlzFqp99Zmz/dnZ2cqQIUOU+vXrK46OjkpwcLAydepUm/tQvq0ybZ8xY0bRsX5+fsqIESOUI0eOFCuvNr325mx7XX7dFUVR9uzZo3Tv3l3RaDRK06ZNlbfeekspKCiocJm2xNxtHzdunBIQEKCo1WqlQYMGyrhx45SLFy/WVHPuKipFURRr984IIYQQ4u4lOSNCCCGEsCoJRoQQQghhVRKMCCGEEMKqJBgRQgghhFVJMCKEEEIIq5JgRAghhBBWJcGIEEIIIaxKghEhhBBCWJUEI0IIIYSwKglGhBBCCGFVEowIIYiJiaF///60adOG0NBQvv/+e2tXSQhxF5F70wghiI2NJT4+no4dOxIXF0fnzp05f/48Li4u1q6aEOIuID0jQtRB/fv3Z8aMGRU+PiAggI4dOwLg7++Pj48PycnJJY5LSkrC19eXK1euFNuuKArvv/8+TZo0wdnZmTFjxpCWllbl+o8fP5733nuvyucLIWoX6RkRog5KTk7G0dERNze3Sp97+PBhJk2axMmTJ0vsmzlzJhkZGSxbtqzY9pdeeolNmzaxfPlyXFxcGDNmDA8++CAffPBBlep/8uRJ+vbtS1RUFB4eHlUqQwhRe0gwIoQokpycTJ8+fVi2bBk9e/Ysti87O5uAgAC2bNnCvffeW7R9//799OjRg0OHDtGpUycA5s+fz3//+1/OnTtX5bp07dqVxx57jOnTp1e5DCFE7SDDNELUUuvWraN9+/ZotVrq1atHWFgYWVlZQMlhmv79+/P8888za9YsvL298ff3Z+7cucXK0+l0jBkzhldffbVEIAKwefNmNBpNsUAE4N1332XQoEFFgQiAn58fN2/erFb77rvvPtauXVutMoQQtYMEI0LUQrGxsTz88MNMmTKFM2fOEBERwdixYymvo/PLL7/ExcWF/fv3s2TJEubPn8/WrVuBwpyPxx57jIEDBzJx4sRSz9+5cyedO3cutk2n0/Hzzz9z//33F9uem5tb7eGVbt26ceDAAXQ6XbXKEULYPgdrV0AIUXmxsbEUFBQwduxYgoODAWjfvn2554SGhhIeHg5AixYt+Pjjj9m+fTuDBw9m9+7dfPvtt4SGhrJx40YAvv7662JlXr16lcDAwGJlHjlyhJycHF588UVmzZpVtD0/P58BAwZUq42BgYHk5eURFxdX1EYhRN0kwYgQtVCHDh0YNGgQ7du3Z+jQoQwZMoQHH3wQLy+vMs8JDQ0t9jwgIICEhAQAevfujcFgKPeaOTk5ODk5Fdt2e/rvsWPHim0fOXIkvXr1IiYmhokTJ5KQkICDgwOzZ8/m73//O6mpqYSFhVFQUEBBQQEvvPACU6dOLVaGVqsFCnNVhBB1mwQjQtRC9vb2bN26lT179vDbb7/x0Ucf8frrr7N//36aNGlS6jmOjo7FnqtUKpMByJ18fHxISUkpti09PR0fHx+aN29etO3q1atcuHCBBx54AAcHBz788MNi65eMGDECNzc3IiMjcXZ2Jisri3bt2jF27Fjq1atXVM7tqcX169evcB2FELWT5IwIUUupVCp69erFvHnzOHr0KGq1mg0bNljsevfccw+nT58uts3Hx4e0tLRiuSpvvfUWI0aMoE2bNmWuX2Jvb4+zszNQmHeiKEqJfJeTJ0/SsGFDfHx8LNYmIYRtkGBEiFpo//79LFy4kEOHDhEdHc369etJTEykdevWFrvm0KFDOXXqVLHekYEDB5Kbm8vixYuJiopiwYIF/PjjjyxdurTE+YcPH0av1xMUFARAamoqHTp0oGHDhrz88sslgo6dO3cyZMgQi7VHCGE7JBgRohZyd3cnMjKSESNG0LJlS9544w3ee+89hg8fbrFrtm/fnk6dOvHdd98VbfPz82PVqlUsXbqUtm3bsm/fPnbt2lUUcNyWnJzMo48+yueff160zdPTkz///JOoqChWr15NfHx80b7c3Fw2btxYIo9ECFE3yaJnQogK+/nnn3n55Zc5efIkdnYV+y2j0+kYPHgwU6dOLXPa8DPPPMPAgQN58MEHAVi6dCkbNmzgt99+M1vdhRC2S3pGhBAVNnLkSKZNm8b169crdHxZ65fEx8eTkZEBQFpaGpGRkYSEhBTtd3R05KOPPjJv5YUQNkt6RoQQFrNr1y769u1bbFrx119/TU5ODtOmTStKXJ0+fTpPPvmkFWsqhLAmCUaEEEIIYVUyTCOEEEIIq5JgRAghhBBWJcGIEEIIIaxKghEhhBBCWJUEI0IIIYSwKglGhBBCCGFVEowIIYQQwqokGBFCCCGEVUkwIoQQQgirkmBECCGEEFYlwYgQQgghrOr/AW9uWMipVKQoAAAAAElFTkSuQmCC"
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
""
],
"image/png": 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kP4m1lv7dwzz90Ha2P93Dnp2DrFjXwboTVrDuxBXUN+V4+O5nePjuzTz8y808+9hOyqWAMDAE5RCAwd4RBntH+O0vnpr2GHVNWZavaWf52g46VraQzaVJ5yKrWX1TjuXrOqJ2sKYNz19a13MhWXNcNJCbZNmqVk46ZwObH9pOuVgmV5/htq/9iv/69O2cdPZ6XvKGs/jRV+7mucd38ZI3nMUZLz4RqFjfphn0WGsp5suMDU8wPjxBuRSy5rjlYuB9cDDGEJTCBTnWfFEqlOnZ3s/u5/owoeHcl88uUmSuLHTG1Je+9KU8/PDDNb9dccUVnHDCCbz3ve9NHICAG4QcMEN7hnnjue+bMq/vDyY0jA5NMDo0sc9tGppzNLTU0dhSRyqTmjLPKwX1zbnoS3FZI83tDZQKZQZ7RxnoHWGobxTP09Q1ZMk2ZKa+gCIdRPTl09zewLJVrXSuaqWtq2nKfz/cH2kjlFb4FZNuKuOzbFULy9d00LWmbaq8MDRT1oFJl0s6m8JPeZWvaEMYGAoTRXY928fOLXvY8Uwvw31jHL9pLae/4Dg6j2rbe8L78TVYLkWug/qm3AF9LUYX4kCtL1IPM8ev1/me4jyJuYaP13xVRfsqoGN5Ix3LT+a8i0+edt8zX3wCZ77o+FjZ1lomRgtsf7qH7U/3sO2pbnY928dQX6S3GeodZXRogomRAlse2cmWR3bOWF3P16w6upNTzj2a551/DM877xg6V7dNb3FcaO1WFaVCmV1betm5ZQ+5+gxrjltO+8qW2nrO4Xh9u4bo3trH9qd72LG5h4vfdC5NLTl2PLWL733hZ5xwxhr+7JOXoZTiqKOX8W8f+m9OPHMd60/owpRL07prvvDB7/KtT90e++BIpX2OPXU1J52zgXUnrmDPziF2PN3D9s099HcPR+62hiy5hgzpbIpi5eOgMF6kVAym+pdU2idbl6F9RTPty5vpWNGCn/J47ondPPfYTp57YjeF8RLL17az7sSVrDtxBS0djezZOUjP9gF6dwxQmCjR3N5Aa2cjLR2NaK3o3TFY+RvAhIYV6yMt06oNy2hqq698+JQp5Utk6zOsPX45a05Yyaqjl+H5Hv27htjxTA87n9nDnp2DDPaO0N89zGDvKGEQkqlLk81FHz9BEDI+PMHYcJ6x4TzDfWNTrt+1Jyzn3ItPArP/74i5stCDkMbGRk455ZSa3+rr62lvb4/9vi/cIOQAaW5riEz8KR09ICesYOX6DtqWN9PW2URrVxP1jdkpP63na8qlgInRAhOjBcZH8vgpj/qmXOUvS31zXfRVmmSJXMTUFJ6naWiuo6G5Ln4YpfB8D8/3SGdTNLU1cMKZ6+Z87FQ66rAchz5KKeqbcpywaR0nbFonVkb/FPMlurcN0L21n+6tfQz0jEQvjUKZcjFguH+M3c/2seu5PkqFMtue7Gbbk9384Eu/BCDXkKGtK3oOWzobyWRTlZdE9LIoFwNSaQ8/5eOnPbBQyJcoTpQo5ktYG1mCsnVRNFP03xmy9Wly9Rn8tB/53SsfCIWJUiRy7h9neGAMExpS6SgCyU/7DHQP0701rkvK1mc46uhOOla20NLRQFN7Ay0dDXiehzGRzseEhtXHdnHBq0+b8bre+tW7+fr1t5LKpDj6lFUcdUwnAL/5yeOMDU3wpmteNjXg6VrTTmNL3dTH0L7GpUEQTg1AtFbUV5750cFxHvv1szGd0MEiagf9/OqWh5M3noanH9zG0w9uS9xOawVKzdldnGvITFkGHcm4nv0AUUrxhV/9NS3LotH3fuPapcMxI5lcmrXHL2ft8ctn3M6YyC30zMM7eOiXT/Pw3c/w1IPbyI8V2TkWRQctJeqbcqzcsIz8WIFdz/ZRGC+y+aHtbH5o+4z7vfCSMxIHIW98z8u47F0XMzIwxhc/+r985tqb+Zsv/hH93cM0NOfoWtNOqVgmnUmRHytQKpbpWBG52/YlffmDv3wFr/8/L6WuMbJqqIola/dzfTx6zxYevWcLOzb30Lm6jdXHdHHUsV10HtVKuVCe0lMVC5FLKFufoa4hSzrrUy6FU9bN/FiB/u5h+nYN0989RKlQZs3xK6Lw8hNX0tRWz7anunn20Z089/huRofG6Tyqja7VbXQe1UZdY7YStTbCYO8oJjR0HtVG51GtdK1uA6XY/dwedj6zh53P9DI+WiCTS0WC+FyKsaEJtj7ZzdYndzMxUgAsfsqLosHWL6NrTVs0oO1qoq2ziVTGp1AZrBYmSlMfkg3N0cdk+4pmmtsbFk3zuxQmsPvZz342q+3dIGQOtHVN+sydttfhWGi01ixb1cqyVa2c+/LngVIU8yV6d0Qm9ME9owz2DFMslGlsqaO+ueLmTPuRADuIIoUAsnUZMrkUmVwagMJEkcJEicJ45d+q/y6XArBgrMGENhJ4t0eWjKbWevyUN/WSLRcDmtrqWXP8clo6GqasEeVSQPe2AXZs7mGgJ3KnjlRco2FoIkG5jvRRx5+xNvFaeJ4mxNDW1cxb/r+X85G3/xs/+davMYGZcrVMCqG3P93Dnl1DnPnSk6au43RMZ/FUSrFy/TJWrl/GRW885wDu2uxpXdbIqRcce8D7rz9pZeI2Fiph/JbWria8uaQdnSpx4Zkp+GG/9l8EAbAbhBwoYRD97Q/z7tefrbkwyR+zkKnEE441W82FWG8TtB/yAbWzvpaCgz5F+CyjBGbbAc02YmOGusQ6v9lGtyTVfT/OLZPWrN7QzuoN7ULPMg1zbGuzphLpBpDyNas3dLB6Q8e+t68+njEzCkezdWk8LISGx+7ZTN/OQY4+eRX9PSPc/K8/4cnfPMvxZ6zlNz9+hK/9w61c9Ptn09HVhK1EMlRKm6HySZFCs8w9NO8kHW/m50wpTduyKvG6CedepamyFj4a8FDCDUIcDofjEGXPriG+ev2tnPb8yFLQva2fe370KCedvZ5zX34KvTsGOe35x/Khy79A+/JmjLGc/8rn8Qd/+XJg+pw0jkOXpeCOmS1uEOJwOByHKLn6DOViwNduuI1Svkzn6lYueNVGXv2Hz0drzfI17fzFv7yF+3/2JMYYVm1YxnGnrXFC78MUzdzSti/GZHKuJTocDschSmNLHX/5qT+oLE3vcuhc1crL33LuwlXK4ZgFbhBygFhTxob7SDCWNDfLXOdFmK1GZNa+7bn5Vw8qMb/47FKIxjQgieXNcQ4NuXssk+jB1ufMUmcxowRk5u8kK9cnaUKkIDKxnc58Lomuhdm2+ySdw0LnfBFMhvxOZrqdLF6puNjUGAPYBOHiXIzxs31u5vacxbVdc00CM9993t7y9vmeOAhEeaXmsP/8VWW/cYMQh8PhOITZn4iIaFDiovgOd1Tlf3PZf6FxgxCHw+FwOA4DnDD1SKJchPLknAazNdOKZWmin/XEWXM0Lc7WrDzjsQ7y19ZcTdqzDb1Lct+EorwkE3xSeVrMtZBQXyvWK7l/UluS28fWV5n1E8uW7paksuc3hNfO1t0Scy8l3KvY/nN9TheY2YQkz7crKenYs7yWsXs913DrOfWB0+xfvVwuzrzvEY4bhDgcDofDcRjgLCEOh8PhcDgWBc00BsbZ7L8IxrrFCAt2OBwOh8PhcJaQA6Zciv4gWWcgdQOzZT5TCB8I85lVUZ5Lkm4gyVcr/PaxUL2klMmJIbsCWX95b5PuVSzsU3wHJIXzeanaZXn+cntZH7m/vLeeuB/V9ydBv6JSaXn0GbdPvPcz1SU64sz7zzZkN6mtzHda91mH+M5z+u8kvVJNXWQ4dUI7Tjx2wv6zvtbzrE2bZb8Tq3/1c1ecmFtdZoGLjnE4HA6Hw7FoHGqJ+J07xuFwOBwOx6LgLCEOxyIzWAzoKwYMlUKGiyWGyiEDxZD+UshAMWCgFJLxNC0pTVs2TWs6ckuUjaUYGkrGkg8N40H0VwgNDSmPjrRHe1rTkfFpz3i0pz3acpa2jE/WU3hu8jKH47BizhlTF6FLcIOQA8QO78GG+/D1xfz8s9QJzDF3RGL5s/W/zrT/fMfjzzYFfRKyvFhej9prEUuxnHRv5HqzN5V2X8mwM19mZzFkPLCULQTGEljL7qJh83jAM+MBA8Hi5I/QgK8goxWrspoNdR4b6lOsz00OUqL1aa04ocGnPldXs7/MSRJL2y41HZ4/8/okzUhirona4ytf6F8kSW1ttjoHmUo8DGrXC82JEuefmHpcalZmq2dK6keqy5vtuUtmqxlJuJeJ5SeRVJ68FnPt16rqZ8fH96OC84ML0Z1nPv3pT/OJT3yC7u5uTj31VP7lX/6Fs88+e5/bDw0N8f/+3//j29/+NgMDA6xdu5YbbriBV77ylQdcpuPIxljLaGDpK4V0F0K6CwHdhYCRwFIyllJoKBrIG8NYYBkLon/3lEKKs+gnW31FS0rR7CuafU2rr2hPK9p8aPMVRQODgWUwgKGyAQVppUgrS1or6jTUeYp6DVmtGA0tfWVLfwB9ZctA2dBftvSXzVS9DFCyUAotT4yHPDEewp7StPXzFZzWnOG89iznteU4piFFQzpBWOpwOBwJLNlByDe+8Q2uueYabrzxRs455xxuuOEGXvayl/Hkk0/S2dkZ275UKnHRRRfR2dnJzTffzKpVq9i6dSstLS0HXKbj8GS0bNiRLzNSNowElpHAMFAK6SkE9BZK9BZDBkqGkbJhNDAHrLPXQFdGsyrr0exrfA0e4CtFR1pzdJ3HsVlYn/Oo8/bxDRL7QkuIUpBfZML6YJUib6BkIstM2VgKBrbmQ57Jh2zJG7bnQ0rWYiwEFkYCQ3fR8JuhIr8ZKvIvzwwD0JXxWFefYm1dimUZn/aMT3vaoz3jsbouRUdOJ08qd4RTCg19hTK7J4oMFMrU+x6bljWS9sQEdNaCtdGXrrumjn2gUeg52DPmsu+Bouzspx9cEM455xzOOussPvWpTwHRLJCrV6/mz/7sz/irv/qr2PY33ngjn/jEJ3jiiSdIpaY3w862zOkYGRmhubmZgR9+kab6uuk32oeJfp/rY/vv3X4sMGwZLbK1EOIpRVtKRZ19StOSUmil9mlmtdYSAoGBwFpKBorWUgyhbG2kMUgpvJjZW9RPhnVWvxiTQjwDYZKerdl1BteTtZEWYqhsGKx85fcXAwbKlkJoqfcU9SlNg6cYCSwPjQY8NFrm2fzsBxYNGpanFctTsDwNLZ4ioyGtor+cp2jUUK8tjV5kwViegnR5esvCPkkK0Y3NwivwxXdFUkh0zIUiXXXR8rai5e685q5Ry/3jlgFxW6ejTsPanMe6nGZjg8/prVlOqPdJTWZTSgjpVdJ9I+sq3S1JJvKktPNJA74kN2jS4KDqWbA2mtH2K1uH+N9dowyUQhpSHmVjObstx9XHtNGS9qa2i45fe9FHA8h4ivTk9YzVt3Z72dXHUvxXbyvb4SzdM0mz3MYGUrN1v2jRNmSGrgS3a2JGr0Ccv2xrsnwZKl/VVkbGJ2h7+eUMDw/T1NQ083EPkMn30n+3Ladezk49C8aN4TUD3Qe1rpIlaQkplUrcd999XHvttVO/aa258MILufvuu6fd53vf+x7nnXceV111Ff/93//NsmXLePOb38x73/tePM87oDIBisUixeLe3P8jIyP73NZaS1jl9x8PLcNlw1AxZCiYfFkaBkrRfwPU+yp6WXqKkoGhwDBc2W7rREh3ad8DFl9BR1rTlfboSGsKxkblV/bfH3eAByxLa9rTmrKFfBi92Es2+n111uOonM/yjMdIYOgpGvYUAwYDS04rGn1Fo69p9BXL0prObIplGU2Tr+kuhuwcL7OjEDJQNjR4iuZUtK7RV+Q8RdbTZHXUkRogrFzDQmjpKYZ0FwO6i4bBkqFoKy4QE9VzsBzV80Bo8xUtvqLJg6bKf3elFctS0JVStKcUTZ6iybM0e+zt6BP1PUtyTD9n1mQUa+o9LuuIlocCy9bA47mCZVvRMBBAfwD9ZUNvybK7ZJkw8Ph4yOPjIT/sK8NzebIaTmxIcXKDz0ktWU5uTLO+3j9iRbI9hYDXrGriFSsaaE55/Kx3nGse7ObYhjSXrWlGKYWxlv/YOsx/7xxhVz6gXOlfAgv/fHoXL+2sX+zTcCwRnDB1nujr6yMMQ7q6ump+7+rq4oknnph2ny1btvCTn/yEt7zlLfzgBz9g8+bN/J//838ol8t84AMfOKAyAa677jo+9KEPxX4vG8ul9/QwERjGQ8tEuH8v/QOhI6VYn4u+WvrLhoGyZSiIOqHuYmQq319SFSGir2AkiCwl3SUz7WBnJAh5ZiIEZvk1v8CkFLSkNO2VwUN7SpPTMB7CuLGMhZaUUpzS6LOxDjY2eLSnKl8LsS+aWVqtjlBafEVL1uPUhqofq6xgJWPZXtZsLYRsngh5cDTkgdFIS/PASJkHRsqwKw9Eg+l6T1NXGZC3pjQnNqbZ2JLllOYMq3P+YeeCmDyfa47vmPqtbCwv6qznec0ZnhorYaxFK8V1j/fxm8E8b17dyNo6n3/ePER3IeDydS2c15ZLPFakazIMl0LGQktGR9e5Ia2o86L0VNEHQPQBNVw2DBRKDJRDRssWX0PW88hoRdZTpJQipan8G32ENPiq5h5Za5mo9IvWVtxJRCnEjAVU9K+vFcvSHv4hLi+y1tJfMvQUA/qLIX3FgJSGVy93A8QkluQg5EAwxtDZ2cnnPvc5PM9j06ZN7Ny5k0984hN84AMfOOByr732Wq655pqp5ZGREVavXo2vYMt4mZkCGzwFzX7kNmnyNa2pyb+oo1XAeGgZCyKrSVpHL9OWijhxVVZzTL1PEzLrZWS27SsbeouGPQH0lQwZrWhLaVp9S1tKk9NRhENKgacUaU3kvqkQTD44JRgsG/yKWyGnIa2jAc6OQsj2IvQUQ5p9TVfGY1kK2tKaQmgZCyPNwHBFvNlbsvQWQ0YCQ2fGY1VFE7EsrZkILcMVDcZIELlMCgbyxlI2Fq3AQ6FVJK7szGiWZzRdaU1HWpOpWEzSCrKVl1WLZ6OOVO3DUiFNk9LM6jgopLXi6DqPo+s8XtIW/WY8n+fyIY+OBjw6VubRsZDHx8rkQ8twYBiu8h78eqgE28cAaPI16+p91tWnWVcXaVBW16VY06RpSh3iby+iF5gBUlqxpxjQVwp5ftZHK8Uv9oxzV/8EV6xr4fWrohfaH64zfGrzEMuzPnW+JrR2WkvSj3rG+X+P9DER2oM+f68GGlOanKeYqAi093f47ilYnvVZlfXpyvo0pnRlYBOVZy1Y7NT3QUqDrz1SOhpAlS0ERIO4SfeVtgZF1A5b0h4taZ/WlEfOiyyutmJhMjCVXNVC5N4thQwVSgyVo3Oo9xR16RT1viYwUf81XAwYKofszAc8O17m2fESY+JlsKHeX/BBiIuOmSc6OjrwPI+enp6a33t6eli+fPm0+6xYsYJUKoVX9TV24okn0t3dTalUOqAyATKZDJlMJva7GtzDZzdkyGqoV4b6ij7Ar7z0/YpWIOobLBBW/kj2V076E8vA0DSVUooUsKLyh9JQXcWg8ifLm1qOHhYf6AK6JnUAtrJfpT5HA2SBun00TQ1k9hVGqYmdd6XuteeiqWn6SZqIqe0m/xLcI1KTIklKwy4tI3K9HNQkbS/DNmPlifWzTe2d5A9O2l5qSqp94UkhtVLjIcrSSrMB2KDgdxuBjgyh1fSWYcLAuNVMGOgpWR6ZMDychycmDCOB4aHhEg8Nxy1yzb5iRUbT6CkafEWDp6j3FTmtqPM0dZ4iq6NBuK+j51JXklMrFbU8rzLoTVdcgym1d50iGrzXeYr6yktxRz7knqES9w4U+M1IgKfglAafjc1pTmlM4QHP5kOemyjzXD4koxXXn9A4473QgC2X+PSWPE3KcFFdETvcxx07J+jwDC+vL2GHCwC0lUKyNmR0ZBibmQBro6ntRVsqj4aMh3vbT1ZDvVaUrWU8RH7a7L1tKorWavWh2VOUbUVLZqBgIrFy2UbC5qKJBgEGGC4bhsXjMN2Eal7lN0UUnRVY2JkP2JnfD6HREkYRWa3bfWj3YU3GQH8vTOQXsA4ubfu8kE6n2bRpE7fffjuXXHIJEFk6br/9dq6++upp97ngggv46le/ijEGXelYn3rqKVasWEE6HXWOsy0ziXMbKx14kljQ4XBMi6cUKybHLlUDote0e+D7lIzl2YJla8Gwtax4Lm94rhCyvRCFHA8HluFgkedWAroHyvx4YPoBdGd6/zr2L+8u8uuRkGvXZVmb1Rhr6S1FVs16T1EKonDswXIkrO6qlLuv0n+nxeMHz8tR70Xap3TVaMBaS9FY8pVLp1Q0YPBUJCiejfurYCyjVjMcWPIG6j1oxNLoQ0ZVytqHaNjYKJR8Z6DZWYz0RKOhZczAWKU8rWq/8CejugIbWXh8paY+/iY/fQyRxaNoItf1UMWFXTAWr1KeLFcRic1bfDVlkfYUFXd7ZK2OrNtRKH2Tp+jKaNZnNevTljUZRWZ/tWOOKZbkIATgmmuu4fLLL+fMM8/k7LPP5oYbbmB8fJwrrrgCgLe97W2sWrWK6667DoB3vvOdfOpTn+Jd73oXf/Znf8bTTz/Nxz72Mf78z/98v8t0OBxLi7RWHF+nOL5OxyIUxg1sL0QuwLHKi2s8iP47H0YvsIkwevEENhI9R/9OWuCj/y/bSMNSmAxdNpMvsuhlXbZRuZOvlZSCU5tSnN2oObspqtPDYwEPTVgeHS2jFazN+azPatbVeXSlk6MVfrinyH92l/jTVRkuaIm65byJ3tWTx52M4n54PHITnNkYWaL2NWCYFLxPh1KRhSg7DxN3ZHUkMF9WbQjbz5ewVorOtKIz53F6Y5VlLXFiy1kmeJxt0sSk40mSLK4LhFbJgT9J+y80S3YQctlll7Fnzx7e//73093dzWmnncYtt9wyJSzdtm3blMUDYPXq1dx666285z3vYePGjaxatYp3vetdvPe9793vMh0Ox6FDvac4od7nhEm3u3QtzVbMOkOYqLWWEorxwFLvV754S3uj5s5q9uPuqP3MbHzfcJnPb5/grcvTvLZzbxn1nuKkBo/P7ijwq+Ey5zZqvtJd4n/7yrx7dYa0VrUhvI4jnkNRE7Jk84QsVabyhHzqr2jKVYQYibqCWaaHTko1nrS/1B3IvCnSfSR9/XPp1OSLYLYp52f7xRJLZS22TxKiyi8Yea1l+UmajfLMx7MloWtI0pDEonXk+SXkYYmlTpe6DpHqXLaV6vLkvc2JyIyYnkTmchDHlloruV7WNZ2tXU56ruT+sRwqc5xCQBLOMq26UmwrweXbfdIKrm4P2VmG/lDhAW9tCUgpy3V7Utw9oUkr6PItl7cEvLrJYMtB7e2W5yfbUlIOn5mQz4F8juW9ie2fkK8mKc9HUgp+yXxPFyGvVVJupartR/JF2q7+uwXJE/LDjhVzzhPyir7dLk+Iw+FwHAkULYyFsD5j+bcBTYsXJcZbl470Dp0+fKCzzNZSJJDt9CxtlfefM4A4JIeiJcQNQhwOh2ORODYDvz6u8tW8D6tXiwctOWewdiTjomOOJPb0QLbiv00y9UkT/Xx7wKT5LcmEHzOTJ+wfC6utWpYm3qRjJblPZpH6GojXXZafcO1t0r2RZmG5fSzcWtRful8EpiDLq62/KUv3j4GshYICq1Aiy1NSemy5XmdqzdxKpG1X2Sqdg7zXQ0O1y+laTYTKChN9YjjwLJdj5QmTfSzV98yuqFnnkJHunNistFIsKY8X3dvJKNrqrSdDh2uKsra2eSW5CmOu0emPP4W8vrMpW56rdOslukMSXMRJ6+W1SNLnyOc0yTU12z6+msLSTva42LhBiMOxlPAsNIaoZWXoKuN1FlFdZVSDgZxBVb6IbRlsnw97Uth+HxSoumgbsgbKCpvXUKj8pQ0qV1mfttg9PnZrGnbVw6DP4hhiHVA72NgXzvXi2B9c2naH43BCWaLv03l+Mj0DHSVYVkK35aGzhGoOoSlA1e+fGFKlQK0IYMUBhgYeW4Tzx4FB7JiGPWnsgA9DaehPYXujfx0Ox6GDrvzNZf+Fxg1CHI5JJgcdtjLosHOVeU1ioasIGyZQ6ydgTR7l79u8awNgwMd2pzG7PWx3CoY97ISCcRVZNppDVFeA7jLQFkRJLSY0dqJi+UjZiuWk4r4pKchrbF5BWaFWlFHrSqhVpcjK0lBArRf1KCvoy0BvBrujDnY2RIMUZzVxOJYkTph6BGFHRrDFypei9Acm+WqTbF5y/6RwMxkamJrlbZW+4KT6VW+f5JuV6yVJYYSSpGuZpAkB0BbM5EBDaEQKldwPjQFqTR71vDHs7R3QF/mYTb7Wv2umsnVaaA1RHSVUZ4BqC1FtIbQGqPYQlRXHGVeYHR5mp8bu9DC9GjusMf02GmhUBkKmFFCTYHuyvtuBR+SJhdOEX+ua9ZEGxBIlz86Bn0GvNqgug+406C6L6grRR1XqvKIAKwqoU4ejww9rzDNpzJY0bKuD3hSTXZfUpygxr4vKipBcoSGJ3Uu5Xupd5PqkUHPZdpLaWlLIa9Xs2tOWl6B/srNty3JZ6jKSQvmTzkeWPxuS9C/y2Emh5lJfJJallksl5YhJ6kMTtGk26VrNEFpvi26+qplwgxDH4Y9vYN0Y6uQhWDuG/elyeLiV2Lh/zRj69D5Yl4dMpZMZSEWDln2gT51Anz2OOqqEqpvBulFUmM1pwt9qwkdT2O7KnDlJA8qDTVlhtniwxSOkaiChLKrDoNdb9JoAfUwZvT5ANRu8Mwp4ZxSAEeyIh306i9mSgR110O/0JQ7HoqHU3JLXLYIoxA1CHIc/bUXUSUMw5kOoUJ0FrGchVExpPjoKqPP7sD0+9qsrUCeMo04cw/6mGXozkavGTvOANofo46IvYhuA3eNDr4/t97H9HqZPw4CH7fcgVIRjxXgZSxGrsHs8zJCHeSCyYOhGH7WmhD66hD6mhFpXRjWFqE3j6E3jwAB21MNuzWC3ZmF3HezO7LU6ORyOg4pzxzj2jbZQF0AuhDoT/auAso789WUdvRQtkUndEkVKpCykLaRM9HWeMZAJUZkQO+FDfxr2+DCYcp39vsh72Idb4dlGVKhg7TikDeT3mnDVxkGoC7A/7oKyxg6kIqHomjz2nlb2NRe6eSJLkNfYXalIu1ESJveFtmwcTAKF3ZIh3JIhvA10nY9aV0QdU4j+XV1ENYaoUybglAlgINKV7Mpgt9TB9mbozk0/mHM4HEckbhBygNiBIWw6unyR335qDbY+QHUEqBUl1Kpy9O/yADXPV7u6K7chMOJhRzWMVf4tKigpbGWgYwc9bK+PGs5UrAAVhI5A5opALle5EHRdZp/rpis7lsdC6leS8oYk+K1taZpokTFgtwdMYB7UeKcVCUtD0JfCGgN1Ial1w4Q/bcQMVCwVoxZvwGJbS5S6B6YGeLFBRa+FJwDKQBkj/L/BRK2GJO6Krv2hVK4t3xPprIvFWt9zUvoCLfZXqiCWa7dPpbRY3qtz0GKdzqZhJ/BLBWTRDQ3odRXXzYYyekOAarCwtoBaWwAGsOMK+3QGsyMFW+uwO9JTgxKdEzoA2TaErsBKTUaSvmi2OWrm2BZjOodA3ruEnC5JA1ipMZHPmjieLF9la6Ofqp8deWyp94kht08nPNcSmZ9GXgu5vWgbMc2GvFdSMzLbFPbyWst+Rq6vuh5muj7pIOEsIUcS2sKaAqq9jG4potrLqI4A2gNUZvoHzoZEEQzjCsYrD0U6snSotI20gorI9K+IBgolhS0pKAGFKLrBTigoKlSTQXWFqM4wOmZriGoNiV6I+8aGRLkhgskmV8k9Me7BiAcjPnbEiyI0+lIwnD4MrCyR28U+lwbfotoDbE+lEy5qaAmjvBswJVxVrSFmwIvi1g4jg8ZBI1CYzSnM5ui6Kl+hOsNoUHJiCX1CCVVvUacV0KcVgFHsuMY+mcXc1wC79opcHQeKhYYoz4xqK0J7EDX9QEGgoaxg0I/a+rgHYaUf0haagmjf9gDVVkJ1lKEphDEPhlPYIR+G/SgHTaCiMm0lP0022hffQk8aeuognzBwccw7ao6akMWYDNENQg4U3+K9Y9e0q6wBBj1sTwq7M4XZ5mN2+jBYGWXIL5zYqF1O5lS7vfzi0RkPmkyUa6LRoJpM1JlkKu6clIVs9OJVy4Io6qEjPjpXTD9ityEw5GOHK53QsIcd8rFP56CUmXafpYeKBneBhmEPdVQJ+0Q2GlzUR64Z1RZgt2T2fnY1hdgtqcpg7SDkCznsUdhen7DXJ7wrh856qDVl1NFF9Ooy6tgiqt6gzphAnzGB7R/E3teEfbDpCH2BWWgOoDGAuhCVi/4lVFDU2IKGokY1BFFYdlsJ1RJELtrJ5zxjog+a/TmaBUa96CMoO/+jbNvvQ08m+ogKJ/+IPmgM0XJZR33LSAqGUtGA51B5zrSF+jD6qwtQ9WHUl+RCVDaEvMb8uHWxa7nkcYOQA6T47DDhMx7kKwK+PR62x8P2eoS7TK27A0NkyoiQprykiYylWVVPF4K7u3qD6mMr1JTpMQrP1B0a1RlGlhdbCW9TRJaVlspfm0Etm7SyEFl42uODFLMljXkgh/ltNupApFlVunJiJuOJ6GHOGRjXKGly399w5YwBDXZkBk2GttiSRW32UCvyBAUfJhQEBm+rhz57jNKvAuygJnVpAatCij9W2IGxqjJqjx+Wau9NGNYevyTWB4F0v4j9xXojzbwJ7pyk9XH3TO2ydP+k0nvvX1qE3KbTtRY36crxhblf12fgYeDhFJBCperRGwK8s4p4Z1esiRf3Yy/sj56lnWns9hRmpx+5EfO1lpJYivmkwbx0O4rzkYP72MeCKE+63qLyLWQq7TlnoM5ECegaDKohjHKyKCJLQuWlrFpNlBW3M4ietTliDdg+jd0dhX5jFKQsKgVkLGpZiO4yUTRX0972Z0NgTGH2eJjdCtujsQMamix6mUW3G1Tr5ICHyKKoo3BzO6qxowqMiqKplpuov2gPZjWkiOqgK25ljR3T2BEN4z6M6igL8GQ+Hw2UFKbXRw2narVGykBrGPUtgz4YMagNDXu/NlRs+gLpjrJBNNhQa8vo9SXU2mI0oBZR4tWYXo/gvzIEcuqFg4hW8WY/2/0XGjcImQPFjzYC0/hLw/37ElkcFHZIY4eqRJlyoFCDhTbQnWE0OGk1UWe0MkBtKKM3lNAbSvC6YeyAh+3zsQM+dtCLwjWHUlEmzolooEM6Shuu2gLUSXnU0QXUyjIqBXZEY7enMY/msM9lIqvNyiJ6ZRkaTDTgG/GxQx4ECtVZjqw7zSG0hoS3NRL+sH7GUwEwj6VJvWYClbORayuvCG7JkX7HGNm/mog6uZKi9K0Mtmcp38tDHLPXfVP+dj3+OSW85+fRawLUihBW5OHM/NTmNq+i9tWdwu5ORV/Z3anIrbDQNAXoU0fQG/NR+/OIXspz7FFtOcrFMvUiHlfRyzZno5T9WYsdU9g+D9urMX0ejE+6bCM3rR3SkYh4Rk2JhfroWbZ5hR1TqKIn8tPsJdZHJLytVCPotQFqeRgl5ksBHiiPSHDvVZaztiqnjonWNxtU8+wsM7ZciUwralRrEFmGq6pshyoRamUVDQgbw6hPKSrs5gz2yXrsEzmY8KIggPYyqiWIkvodVYr+2uN5WKoHTXZMRf89rmFCRf3UAqO0Qs1hJOEmsHMsQRQMa8zwNALF5hBvUwl9Rh69pry3MyEehmoDEjto1WRQJxfQJxdm2GrfIa6qM0lcFrlVbG/kvkpdNo5qMphnfcrfqKf4j02oE/LYXk34uB9NEkeRQ8Y8fChTVIR35QjvykGjQa8uo9eHqKPK6JVBpHfKWdTqMqyutUDYMY0d9GHIj/QOAz52dzrSJpQntVcGtbIIq4uolI0EsbvropdObWnQEqC6ytBZRC0vRTqHcS+KsprQqHUF1PH5mpecxAZE+q98pP+yox6MqihFvlGVyDeiskc8bI+P2U70otyX/kqKNYO5uFAUjGrMaNVJ7M8kNvvLhMY8nobHK0eTZUuRrFYVXYqJrEWNFtVoUI0mmkupKVomayLDsiV6nnMm+lhJgVopLMzFyO2jchbVEqJapknmVmdRGwuwsRC50Qs60rjsA9vjY55LY57xsVtS2D3RwC1mRXPsN24Q4jhwhj3MzxswP2+ITJXLAlSXib5E2sLI2tEeoprDmgGINUQpxJ/OYB7NYLamYUSjVgToE0rojXnoLENvxRS/M40d8lA5E3UkLSGkLHZPCno97LAX+Z9HPGqyiwrUsoD0Hw+jukIYjUzU4SMpwl9HNnDb7RFulfZwNwBZcEY15rEM9umqAYJvUZ0W1RmgV5ZQy8uoFZUotAaDaijBahGJZIiscYGCrvK0gwbbl4raTZ2p+PbD6Gt8PzBb0ph76zDb0tExykTNr6gi8aZ8L8kXlfhinTay60jCKBjyIguCUrWzCgtLTI2bUVlUh0V1Bai0wQ762L7ImgRAvUF1mihwwI8srgwr7JgX5bk5oYj3vCJqVSlqB0RWN4b8aKLHHWnMVh+7PRVNiUDcRb5UcBPYHUGUhicoVdww0hddFn5+6YePZSxOCMWLS0ZqO6t0aiZ3SrIOQMuvFOlrl9PFp6bppYeAnZN+9clplFLobCryRzeZyGRc1JXgneiYe7+QDDytCZ7IwHczTAlBa66Nh0pJ3+3kxQmAYOaOvN/At7KY7R62PzrHMF+iWq8Tlipf2RWztNR4GPEiKYuQWhlim8/P/GIpiZDbQJQfiptfTtIPiWXZMrT8mhY7pEVbSZf2luD7tXXNZGrbgSfaUYN0S47XDhKq9SYQb2dahHnq4RQ8DZCu/BFpHDpDVLuJMry2GdTyEH1UgGoxsGzv9Tf9GrMliu7QGwL08jCKAOkQlpUgGpCaHR52p4/Nq2ig02ShwWIHNeFdGcz2yT2i80r8Gpb6HdFPSP3TbHPMWCmfimUyF3omYUmpbuuyz/D8mfsQk+CC1mmRwl++7WSfI10K0nIitjd7gimrCwS1bWcY6K4OXrWV8OrK9X/Yh/9KRZGFuej+Mi7Or1TbT2jRB4ZiOofq8wsWcMDiBiEOx3SUVWRmhlm08oPwNIxpwgerOi9tK+G4VcdzibQOLYoKu93Hbgc8XWMH0+2gVgWolMVsTWH2CGFqE+h1ZaizkSBzuOIuGam4TBKEqfJjwHFoYwc9GJxaWsyqHDAuRNfhOCSoWFmMOgzynzj2yaiHfcKrep2IQcNE5PaZxC5pQbnDcXjiBiGOIxA38HA4HIcfzh1zBJHPB/he9OUkdQOSUPiKZS6GpFwQUocgfe+FQq3PUZbvC3+uzOdga92ZsfI9T/iuq/27Ml2ziLc3BTHltvTlytTSMtw5dm2ERkP4YqX4z4gYfWlujGkyxPmUS8JPL+6NTKOeqBkRfnj5zBeFLmBC6gTE9nJ/2RRTsV5FuCTEWjH1DZmqE06XpYZApJiX91ZcC5lnROZQyeWEHqZYe+886XeXbUUcPxB5PGLbS62W9N3LaydzR4jGIHO8SOT1SMrxEiREv8h+R+o45PFiqdBl/WfQtKR8KQydsWqxLOmqIO5lTKcmtpf5axIid6SuzcocLpIZpqKAuB4nSfMin/PqazkuU8ofRA5Fd8zMikaHw+FwOByOg4SzhDgcDofDcRjg3DEOh8PhcDgWBa1ULAx/tvsvNG4QcoAUCuGUJkTG5yf5WqWvVvpyfeGvlPOLxKbkFu0mLWLy5dQFRaFzkPvL49fVCV9zlX9X5g+IHSwUHj85xbfMNyD9/nJ+DznvjliWvlvpK5brk/z6gdg+EL7fsvDbSz9+bL08XkIeEC1UG1IjIrFC8yE1HrK8WCJLEaJsqhq3lu1S6GHqxTwaBZH4Vl67bLa2LSTlVJFaJqXkc1G7vdSo2GBmnYDUWMjy5HMb29/ItlK7XBQaGKlzkOXLtijbaqwfEI+a1CnI51pSrYeS28by5SQ8R/K5k32cXJaak31NETVJrN8RyO19T/aZIreT1GolvIulVkxS3RaKC6gJORRxgxCHw+FwOA4DnDvG4XA4HA7HoqCYY3SMm8Du0KEcGCatnaUE94YkHt4mTOgklVe7vS9MmYWCTOte69KQplSZflseT5qRq02bVpjvVSBdTbXnouNzzdcuS/fMRO2EdTolmmwszFKEyon6JIVTx6uXFFY5swk/6ZGW1ZHumLIM6xT3Xu4vz05arWUIsPQBZ2XkYtUZFERdZPhvQYbcxsIuRQitDIMUbSnmlhTPmTTJy7DPcjCzq04iU4VL95F0zSW5DGQIsySfl8/VzG5Y6cKQ00Mk9Tvy+skw2uqmEWjZByWEyCY8h7KPiYW+yymbElDCcyfbsayPvJfyXsW2T7h30u0ad0/t/e9Sggv1SMcNQhwOh8PhOAxQOq4NmtX+i5A02A1CHA6Hw+E4HJhjsrLFEIW4QYjD4XA4HIcBTph6BGGMxVQ88Mm+4YR0zgk5kGMpk4VvviRCwDJZoQGRvnwxhbo8vieUDFJXIX3v1UjfqkSmxtYizXtsvdCAyOnO5cX3xLUqC51CUvi09AXL85FfGTE/fWnmkNxYiv6ENOrxNO3C954w26dser6sf0KvI+tfTTyTttQsSA3FzCGoKjWzXz4WNirDqZP0OTILu7w4YrlUnlmbVSrOvF5qSCTxFP8za1hkW43pf2LTQYjjiesjt68uXz7jnnhTxPqEhJBZqUeRzyG10i/81Ox8CjZhc3ntYuHXMrRf6p2Ezk6WJ7evXlyMF/uhhBuEOBwOh8NxGBBZQuYyd8w8VmY/cYMQh8PhcDgOAw5Fd4ybwM7hcDgcDsei4CwhB0i1JiRxWmvpK05K/yx9twnbS39sTJMiUyrLXB7pmfdPCw2JzEsyE1qm2o4lJxB1ydbm/pYaESWd0wl5O6RvWWo2ZCbrdErmapg5xl/6zmW6at8Iv3vCvZG3Oi3KL4kNMuLTpZTQGOXZJN1JU6M8EH7vhH2T0pLLUMKkqe2tnnm9NEMnpWGX+0sNSlJ9pMYipiuQ9y4p1XeChkS2tZKobylB1yCXY9NJVP13LFQzmLlu8trLayfzasi2IetCgh5HPmeeTtC5JWjVYtouUV/Zj+iYnmff+YkWMk+ImzvG4XA4HA7HouDcMQ6Hw+FwOBz7ibOEHCC+r/ErJkBpaoxZxOWMkTJFsNg/JV0Wgli6auFTiIfXzby9DH2Uh5ful+rRsidm7I35EwRKzKIrU2XLobiVIbNyVl3pzhHlm0LtzKkpakPtZDpnea5y5taiV7u9TGmvRXnSECvdK0Y4NdLM7H5Jx1wYzIi8vPL2yLYo8avqEzOJJ5j7k9vRzG7ApPDo+GzU8nizc8/Eowpmdq/I8hLdTwlhoXJ/2bblvUu6/tIlIl0U8my9qv3ltnL6ANlHJV0LeS+SpkfQWrpxRV1FnyXdJ/L4SWnYtZ352sVcceJ84zMU7z2et4DmBTXHZGVzSnR2gLhBiMPhcDgchwHOHeNwOBwOh8Oxn7hBiMPhcDgchwGTlpC5/M2Gz3zmM2zcuJGmpiaampo477zz+OEPfzirMpw75gCpDoVK8l3LKb2lf1HqDmK+dxkGKpalP1L6T9NCRyH9pVIzEvdv1lKdGl2G3CoxZbeSZcWFBTNuL32/Erl9LKRXnLsW26f82u09ofEoiWU/JZ9SoVGJ+bZn1v/YWskKBRHOF9OQCN91IHULCRoQefl9oQyQ+1f7s3MJWiUZ3iyJhTNL7VLsXGdODS5T0M80nTok+7tlWnnZ9qTGI6bhSNLnyOnupS4iFsIsthdtR55NSrTNvEgr74v7F0udXl2W0O/INAGyblLzIa+VmFkiVr7UgMh7Le+dvJWyPNl2shk5lQUzIsPBpeYkJbRwso/3q77vF/Ilq7SK6+xms7+d3b5HHXUUf/d3f8exxx6LtZYvfelLvOY1r+GBBx7g5JNP3q8y3CDE4XA4HI7DgPnShIyMjNT8nslkyGQyse1/93d/t2b5ox/9KJ/5zGf41a9+td+DEOeOcTgcDofDMcXq1atpbm6e+rvuuusS9wnDkK9//euMj49z3nnn7fexnCXE4XA4HI7DgPnKmLp9+3aampqmfp/OCjLJww8/zHnnnUehUKChoYHvfOc7nHTSSft9TDcIOUD8lCZV8Rkr4dePaT58MR19gvM4KV+CRPpP5fbpjPC/ikYqfdvS/+pnRW6PKl+5zMsh84BIlDxWgmYklidE5gEp1eb9UFrkLRG+WyvzeIj9JVmxf1CQ2wtNSVB7PunaLPSJeh8lpjSXvm0pBAiEDzdvZM6Z2u1lzgJpClXiANV5RGSK+azQ22TEtYppPkQ7lX58eW3qMjM/N/LS+CKJivTjS6QGw7MzPxeFotAHyfw6MhW5OH6QkKdE6iJi+YMStGMS2XZj+iSZI6eqfHnukiT9i9QHJWk8ZFuQadylXkiee7y+YvuYjq52a6knklq3xLTuov5yeoiFYr7cMZNC0/3h+OOP58EHH2R4eJibb76Zyy+/nDvuuGO/ByJL3h3z6U9/mnXr1pHNZjnnnHO4995797ntF7/4xalkLZN/2Wy2Zps//MM/jG3z8pe//GCfhsPhcDgchx3pdJpjjjmGTZs2cd1113HqqafyT//0T/u9/5K2hHzjG9/gmmuu4cYbb+Scc87hhhtu4GUvexlPPvkknZ2d0+7T1NTEk08+ObU8nSL+5S9/Of/+7/8+tTyTqclxkPAtBNMM2dMG70UT6PUlzI4U5okU5tkUlCvbKgsNBkoKikt+DO1wOBwLxlLImGqMoVgsJm9YYUkPQq6//nquvPJKrrjiCgBuvPFGvv/973PTTTfxV3/1V9Puo5Ri+fLlM5abyWQSt0nC99SUOTYpfKwkzLhpES6WNLulNEPHzdgzNxxZfiYrwmj9hGUZNlu/18dghdVRyzTu0iS/weK9ZgC1poTdlia8tw7zYA5KCn3WBN7LR1GN0fXSJ5XgYrAB0JeCOgMNIUpHv4U3t8K9udq65hTq5DwqazEP1GFGRMiutMMKZEivLdfun4qlJp85zFTOrplXteUlpe6W+8tlK0J0m+S9oxZpRZfrZVupDr2UJngZ9phKz9wuk0z08bTvMuyz9vjxtOu1y9I9JMNGJdLELt01srzQm9m9UhLla7G9fHYksi3FZppN2F7OAC2vp7xfMxHro0RjyGRmfq6SnpMkF7JEPjfZ7MyuO3nvpfskaQbjQInQeeEWLhSEW7aqjxVdyEFFMUd3zCy3v/baa3nFK17BmjVrGB0d5atf/So/+9nPuPXWW/e7jCU7CCmVStx3331ce+21U79prbnwwgu5++6797nf2NgYa9euxRjDGWecwcc+9rFYqNDPfvYzOjs7aW1t5SUveQkf+chHaG9vn7a8YrFYM6qToUuO/SRl8V49gvf8iak8JmpNCX9NCXvJULRcaY2238f8uhHVVUJtKKCaQ1heK7xRPvhvHCRcW8T8NgsFjT5nAn1aHpWLOhR98TDBDxswd+XAzH2E73A4HI699Pb28ra3vY3du3fT3NzMxo0bufXWW7nooov2u4wlOwjp6+sjDEO6urpqfu/q6uKJJ56Ydp/jjz+em266iY0bNzI8PMwnP/lJzj//fB599FGOOuooIHLFvPa1r2X9+vU888wzvO997+MVr3gFd999N54XH81fd911fOhDH5r/EzyCUGtL+L8/jF4ZiTrNg3WYO5pRxxRQm0bRy6Pf7bjC/LQVe28jhAoL2DCE9gDVHmDHPeyggnGN96phvBeO4Z03gXfeRM3xbL8HRqGWBaTeMIJ5wTjhd5swjzu3m8PhOHxZaHfMv/3bvx3wsSZZsoOQA+G8886riU8+//zzOfHEE/nsZz/Lhz/8YQDe+MY3Tq1/3vOex8aNGzn66KP52c9+xktf+tJYmddeey3XXHPN1PLIyAirV68+iGdxmKAs+uQi3kvH0RsiK4Yd1ZhvdWCfjlwotjtN+NMcanUZdVQZ80AObeVAQUF/CtufihYr0TLh/zRjnsqiT5lAn1SAnME8lMP+pgG7JQMK9Dlj6IuG0ctD9J8OYp5IE/x3I3ZXaqGugsPhcCwcc4yOmbU/Zh5YsoOQjo4OPM+jp6en5veenp791nOkUilOP/10Nm/evM9tNmzYQEdHB5s3b552ELKvTHHpjCZd0UokpV+WGg6J9FdK37kMzZPEps1O2F6nam+7zta+lGO6CRkeV+UPrU2DbqErRJ+Sx9s0geqsWDgCsL9twNzWCsNSX5KDgRwMgOcRu5gy5LdGn9Jdj93WhPlhZR+rsKVg6kEy9zRhH2lEv2gYdd4I+oQSqeP6MffVYe5owJYUnq6c+5iGosYWa90+Rqburr0yaFFf6WaXqb9lGGdJpNbWQqwrw0BTKRH2KXQMUjeRlE47iWrfufTjS21TLBW3ONd4qu6ZQ3ilZsIXx5Ph27LdyhT+OsElF9eg1F4rOR38bNO0y3sp94+XL547oVuQ11dSl5r5eLLfmKltJH0h+wlh/kn6HdnHJdVVvrlk25FvU9mW5NQWni+PLzQkRmpIagtsaKjtQ4tV0z2kEvQmRzpLdhCSTqfZtGkTt99+O5dccgkQqW5vv/12rr766v0qIwxDHn74YV75ylfuc5sdO3bQ39/PihUr5qPaRyTquALe88dRa0qohr0Pp80r7L1NmF81wehkUzsI8fMzzXdQ8DC3tME9jeiLhtCnjuOdNYF3lnDhlMH8vJHg1khf4nA4HIcaSyE6ZrYs2UEIwDXXXMPll1/OmWeeydlnn80NN9zA+Pj4VLTM2972NlatWjWVUvZv//ZvOffccznmmGMYGhriE5/4BFu3buUd73gHEIlWP/ShD/G6172O5cuX88wzz/B//+//5ZhjjuFlL3vZop3nIUt7gH/JKPqUwtRPNgD7dBbzSA7z2xyaJaLDGExhvrmM8I46vFcOo9aU94aKaItKgffSUfRZ4wQ/qMf8yolZHQ7HoYXScSvPbPdfaJb0IOSyyy5jz549vP/976e7u5vTTjuNW265ZUqsum3btposg4ODg1x55ZV0d3fT2trKpk2buOuuu6Yyt3mex0MPPcSXvvQlhoaGWLlyJRdffDEf/vCHXa6Q2ZA1eC8Zw3vxOMoHG4L5ZT3mwTrs7nRt/o8ldlnttjTBjcv2/qAUYFEnF/BfOYzqDEi9cRTzwjzB1xvhqZlDDx0Oh2OpcChaQpRNyiHuqGFkZITm5maePfMEGveRc0L66ZOm/Ja3QDaEWGpvmbJY5C+QKYdn1FVMs17L9NCT69sDvPPH0eeMo7JRnc3mLOb77bAnyh0i82zEGrWcnlz69bNi1CJFDvGLN+OyLF/m/ajRDWiLPncM/dJhVL3BGjB31RF+v2kqMZoRmhEr/L3huEjSI+oTTNRmj4hPeV67XBQ5ZmTq79j+su0l+Lqlr1z61qt1DFJfInMtyFst18u6xLRHsl3K6QqSOkiZG0Km9JeajISU/fJaJt0riUy5L3NbyKY7W72OROYRkRoUWb68nNX7J+Vsiet3Zs7DIa+FrJtE6o1iyLYip3uQfarcXuqHZFuQ9ZP9iOiXwpLIR1RVn5EgZN29jzM8PLzfqdBny+R7adt5J8VyBc2qnCBkzd2PHdS6Spa0JcSxNFDHFfBeNoJeu/cFbLp9wlubUU83siiS6oOBUZi7GjEP1uG9cgh95jje8yfQzysQfLcZ+9tcchkOh8OxWGgV+9Cb9f4LjBuEOPZNg8G/dBTvrEjzYUOwT2cI72zAPpkFFCpzmAxAqpnwCG9uxzxQj/eaflRnSOryQcI7i5hv1kF4GJ6zw+E49JmvGewWEDcIccTRFn1WAf+SUVS9jdwSd9YT/qQRxrxFaaiLgX0mS/kTnXgXj+JdNBZle11RovRvTTDstCIOh8MxV9wg5ADxcylSFd+b9A/KfAZGzuEQ04jM7L+UL/2k9VrqMuR8IkLzoTMpUBa1oYQ+I49+XmEq1NbsSmG+0w47MtGUy6laDYnUk8TwxfqUyEky2wFNIHy3svxQ+GblclqIIMS9k7klbNnD3pEl7K5Hv34P+uiAzF8NEdzcgn0yiy3Jeyfurbj38t5JjYkvfM/Sly7TrAVlcXyZSyNBfyR9/ZJq37/040utk2zXSX54uV5nas9O6nli+Wqk71uerNQJiPK8htoZto3QC/npmfVFntABxPQ28tr7tT/IuWo8mdtilhKRbELekKS5Z3JV90PqR2Q7kecqdWmyD5SaCbm9RIlcRlIfJDUosfmtRO4jqQWL6YPknFFCI2LFhPNeLl2zrFKiX6q6Pl6wcCEnh6Iw1Q1CjnBUR4h3QR59Zh7VtvdBteOa8GeNmJ83oLVrJvbJOsLPrES/qRu9IiD19gFsUWGeSWOfShM+lIVBd50cDsci4jQhjkMCz6I3FfHPK6CP2/slbvMK81AO89s67DOZvXkyXO6uiIEUwb8sw3vlSDRRXoPBO6kIJxXxXjlK8I0Wwl+5lPAOh8Oxv7hByAGiM6kpt0fMbBzbVvwgTV4JYaXSTB0PsZXuln2ZOi361AL+q8dQHZWU6gbs5iz2vgbsYzkINDrtQ3aG8qon+pOT/onw4Ji7JJ5XfB91nTx4LL9z7bK0WSe4Z2Lbl8XsvAmuL1VS8KMc5jYLnSVYP44+ZQK1pkTqrUPoNfWE/9M0NYAziPKtCIeWLgNhBpbxODLM0/dmNrEnhWUmpddOVbUteWwt251wj8SmA0gI15blSZO7JGZSF640ryEj1svc3dKdJNquOL4M+fXkvZNtWyCfazm9QhhId87M4dhJyCkDlNp/F0u2vvbeSXeKvFYx15g817pa94W8trKPSXLNaekGjrm05XM8c5qCWCi/dB0mfYhJC0J1uLPsEw8mTpjqWLJkDKkrBtHHR3kq7KjG3N2Ivb8Bhl0zmDVWQU8Gu8MnvLMpSgn/4hG83xlHrS4T/EerE686HI4FRWkVz68zy/0XGvf2ORKoD0ldOYheW450DL9owv6iCUrOzzIvWIX5USt2Rwb9hj70hhKpv+wl/HYz5m6fwyaPisPhcMwz7i10mKPWlkj/RV80ABlXlD/Vjr29xQ1ADgL2sTrK1y/DbE+h6iz+HwyRescINMxspnfMBgv+LMNGHI4jhUl3zFz+FhhnCTlAdM5HV8LIZOrreD7mmX29SWFRMqQ25n+NpXWP5kPRzx/He80IygPb6xN+ZRm6T/hmAZVNEFNKHUb1PDvyXNOifKk5mKUGxErNhpzjJ0HzYeV6uSyR/lsZ4hs7H3EvxhXmczns7wyjXzyEd3oJfewg4Y+bMI9m0f3C1y7TuMvqyGVxKzwZYhxLL127vfRtS53HTKnVvbTQUMgwxQRdQEy7lBByW71WrSijzy6gT52AphB6UpjnUtjnMtjdfrSxb6HJgAH7aDaWUj9JQ0KSrqFJhPTmRQp/+ZzLVOBSByHPVw6uEmJ0Y6H/Muw1YX85vUNYrKqvaOd+vXjuEsrWdVKPIzQldbIhi3Ynw79Toq0lhF9LYmkNYhtUl2fxNwV4Lx0BDeY39QR3Zmo+3OS9jV37qvK0v3AvdqXm6I5xgxDHvNAR4L96BL0xynRqHqrD/Fe7s34sFEZhf9pC+EQO/bo96BUB/iVD2N8F89sc5mf12B3xwaCjGgutIXp9CX1mHn2CmJNnRRlvRRnOm5h+70GP4JYGzAM5KDt32GFJxkSDzj0HqL1qC1ANBjvowTBgFWptKZoZfMPeAab3u0OoYzKUP9fKknetOmGqY/GwqPVlvBeNoU8pojTYAML/bYJ7WljyD8/hyO4MwT91oZ8/hj45j15fwjsjj3dGnvDBLOFXWhe7hkuLlIkS5Z1cQG8ooZr3ft3aEOxjOcz9ddidadSqEmptEbW+iGoPIQACheqIvrhVa0jqTcPY3xshvLcO82AW+5zT5xw2NIekru5DtYfYXo/wgWx0j3f5kLFR22kOo9s96MFwKppuoc6gT8ujN02g11elJwiAYS9qS4AtKczPG2HEQ//eIPrEIvrEIubx7PT1cRwwbhByyGPRJxXxLh6rnWDusQzhLY3YHWn04Ti/y6FCqDB3NGLuaEStLKGfP4o+I493WgGVHSD8dMMR/qVuUWsCvHPz6E0FVG6vmd+GYHeksM9kCO+qQ43sNfHbIR/z8D5eCHUh+uwJvPPHUW0h/ovH4cXj2EFN+FAWuzUFKQupEDIW2+9hfpPBDVAOEeoM/p/0Tw0YVGeI/7JxeNk4tgRqGiOjNcCohnqD8qt+G9HQVPmtPYymqLg3h/lxC4xUNmwL8F40ivd7o5gnq/In7Qsv+iBUWYt5VOZnOMho5pisbN5qst+4QcgBotL+VGrhWH4BQcw3nDS9fUKK4WjZok4o4r18FL2mXNlPYe6rw97TAnvSKEDVTRNTLxup1HzI+kmdxwy6DiXLim0gypZ5RqTmYrblxVbLay10AfL40tct08SXSjOuVzKfQfXx+1OY/8piHyjg/eEe9AlFMn9mo3DecW+ywrXVkTlapOZD+sKTfOUy3bbUSch03dXHT5g+PeYXF5l2p7ZXFrWqjDq5hHfaBKpr7zW0Ax7m/nrs5gx056AcHXNyyoDa8mROmMq5ln34ZYbgl82oE/LoUydQJ+ZRrQb/d6Z335gXFyn/e3P01Tz5W3HmNPAzaVgAbJIGRZD06ojlGZG5NES/kdTPyPVebm95sT5DEntOk57jmddroXuL7T+5nDH4fzKAXh5ghz2Cm5ahlpfRGydQx+WnBiA2r2DUAwu0hqi0hea9U1HYBxqwv62DUR+0hVYDLUE08BhIRc9xpcr2jhbsWePo5QH+W4axmzPYgoa8Ag9UnYE6g6o3qDUl1PoSKm2xvT7Bs014pYUL1T9i07aXy2W6u7uZmJhg2bJltLW1zUexhwgW0gZyJtJc5A/SUFJb1PIAdVQZvTpEHV1Er6okHCspzC8bIvPhuJc8n4tjUbFbsoQ3LcO7Yg/6uBKp9+4h+K9m7G9larLDD33WBN6rRlBNVa6WksI8nMP+ph67JRPlYCEuyJ41VmEfryN8vC4SrW6YQD8vj2oNoaii5zVUqFMm0GtLpP5kkPI/tkHRaaeWJBmD/8f96DVl7Lgm+LdO6E1he9KEv62P+uGGMBp8lKvvocVmA1RriC0p6E2hqweQRsFQKvqbjoIm/FEj/qXDeGfk4Yx8YlXtmMbuTkFCMkHHHAYho6Oj/Od//idf//rXuffeeymVSlhrUUpx1FFHcfHFF/PHf/zHnHXWWfNZ36WDZ0l/uAdyBlXVnu2wxvaksN1+9O8eH7tDwZgi9q1Tb9Bry6i1ZdSqMpQVttvH7NTYbh/VatBHl9DHBKi1pZiZMRp81GF+3rz3S9pxSGCfyxJ8tgvvDX3RXDSXDxL+qEz43ezUS/hwQ58+gXfZUKRXKijs5gzm0Rzm4RwU9cH9CgsU9vEc4eN7B3pTFsbbm/Hf2RMJiN86TPBvLYftPTg0sagTC/i/O4JaHmAnFMFN0QCkhpKGgekGkArGPewc+khzVz1ByqJWlCOXYdZEf0bBhMZO6OjfXh/7dAb2pFkU996RMnfM9ddfz0c/+lGOPvpofvd3f5f3ve99rFy5klwux8DAAI888gi/+MUvuPjiiznnnHP4l3/5F4499tj5rvui4vkZyOwdgNgQlAeq2aCai3BcrZrfTqjISuIRjY4nzXizwBYUdlcGdqWwu9LYp3Iw7kWm06qP6H2nba+Q5F6RLwOxvsZFIt0X0r0xW3dKgvsklvY9YebU2LIM+ZX1E+6VWCpuea28mU3ylMTxqk30/SnMp9Nw0RD6d0bwLh4j0xUQfL116ktOmthNUbh/EtK+x9JZy/rL1OkzmPCT0rTH3IpV7gN9YgHvzdEAxPyqEfODNjBVrpbMNGGUM6TCnna9DPmtXRsPX568tv0e4Zfa8f60F+95RbhknPD7zfEZhmXIcbb2WibO+puQKjxpfcxFkVB+jITpIqrXJ96LJDeorIr4ISk8e/J4alUJ79Uj6GOj/tSOacJ/X4bqzk65S6arb9Isu0nXyopBqM5k4FcZLJGHJ7Z/5VpOfmrK6RoWjCMlOubXv/41P//5zzn55JOnXX/22Wfz9re/nRtvvJF///d/5xe/+MVhNwgBCP9lJRQVZtRG4sKMRXWWI7fJ8jJqWYDqLEc+yToLdXGfsO3xsTvT2J3paGDSVYaucrTfuMY+m8Fuy2Gfy0BfKvpCm+UcEo4lTKgwt7Rie1PoS/ujuX1a+wg+0yFMyocIaYM6thgNuIcUdlSjjy3h/8EgygPzYD3mf9uidryEjA12e4bw5lb8Nw3ivWgMdVSZ4JZ67DOL9EV7JNMRoE8qok8qoCsfc7YM5q5GzE+boaBrrM+OQ5sDGoR87Wtf26/tMpkMf/qnf3oghzg02FP5ip4UnBUVdnsGu71WEa1SFjqCSKwUqigjVahgxIOCTjSBJX7hOA557P0NhP0+3lv3oNeU8S4dJvxWy2JXa3b4Fv8d/egNpWlXmydymP/qWLKuDnN/PUHW4r16CH1MkfTVRcyWFOHP6jFPZCEhz51jDvgW/cIxvHMnpsKsJwnvy2Fua4Uhp3VLQulprFCz3H+hcXd1IQg0dKdx9gvHjGzNEvxnK/6V/XhnT4CF4GuNS/alLfFeO4TeUMIWVTR5X2OIylmsgfBn9fDTjuTwxkXG3NWAeTyL9+JR9Fnj6A1l9IahaM6lJ9KYhzKYhzPRx4NjHrDoU4v4l4ztzdERgH02g3kig3k0C32puLvGMT1HijtmJgYHB7HW0tbWxp49e/jFL37B8ccfv0/XzSGLp6dCFpO6o8Q07UmWDrm/nCJd7i91GVIHkKQBSQrZrV6W28Y0B9K3PHNa9Nh6eS5yfYLmI1Y/WZ48fkKIcCyktygyeYrtVSzkVxxP6Hfss/WEN1u81w/gnTMBviX8WsvUy3um9NAAVrqqTcIjnjgFelWBSX70exqxxxYJb27HPpONtEq+AQ2qpCOvRnX1E0J+YxbCpPTXsn7SbZm0flKDMZTCfKcN+9MW9AWjqI3jqNYQ79Qi3qnFSJfw9TbCh4VWSrwodUakRRdp3uW9jKWZRyD1Own7J7ptY7qMqrTkgdSriG1lBJ7UYMykS/MtamXkqtZnjaOPrszsPewR/qgZ+3DdVHZnBdO+pWIaD3HtpTYqFk4t6y+fg1lOtSHX66o+OqYtctQwr4OQL3zhC3zsYx8D4C//8i/5yle+wqmnnsoHPvAB3vWud/GOd7xjPg/ncByW2PsbCMsa7419eJvyqI6A8JstUcjfYqKtsGRYql+VdmeG4JMrI1fjJMEhbDEY9TG3tMItLbCijDppHH3aBKojwHt7H+bTrVE+E8d+oU7MR3qbNSVUtba9DOaOJswdTYemDmoJofQc5445VKJj9sU///M/8+ijj5LP51mzZg3PPvssy5YtY3h4mN/5nd9xgxCHYz+xD9cRlpbhvSmaAVm9Zw/hbY2Et+YW3qWhKl95k9Es501gHsrAxDTdR3g4fvUp2J3G7PAxP2nCu6wffWoe/7WjlD+RPmTcZYuGsngXjeJdPDr1kx3T2O4UdneK8OcNqFE3l9K8cKS7Y3zfJ5fLkcvlOOaYY1i2bBkAzc3Ni5KJzeE4lLFP5ij/fSf+64bRpxTwXzGKPiVP8JUm7K4Fsooouzd52OoS/qUjqLVlgqFW7BNHoKQsUITfaUUdGyUL1OflMXfVLXatli4Zg//GQfTzosk0w1/WE95ZH0X6VTucnORjfjhS8oTsC8/zKBQKZLNZ7rjjjqnfx8bG5vMwS46kDKUxXcAco10m08VPkZSLQ+o0EjQfSuoeZlpO0o/IY8u8G1kx/8d8D1bl8aSmRNYvIW17zBecpLeRWKEhScgVoQpZzFcy2FMn0L83gF4dkPrLAezOVGQRqURamfvrML+pj/v5ZW4M6bvXM/vWAcga/MuGUJUXiX00B911qLRXO0iR7TrWruS1T9AuSWQKfdlWYjldxPHKYn95rcXhpJ9/6toWfMyPm/F+bxD/VWOUH6mHvI7nIZE6AanhkNPbiwyxRrYNqXuQTTsj8paI8uX2MhKi2hSvMlLbtY806pNlT9eltQX4b++PUqwHEH6nDXtfAwqwiMrI6QKys8wvJPUyOWFZSZouoigiukQfq2Tbkvcm1u/tLT+2r6OGeXXA/fjHPyZdSYTV3Nw89fvExASf+9zn5vNQDscRhML+tp7wH1diHs6iPNBryuh1JfSGEvrYIt4bBiF1EDq7+hD/jwZAQ3hjF+aXjaiOAH125cPiCA35Mr9qwPb4qAaDf2VflBbeUYXFf/NgZY4XTfjZLux9DYtdqcOeyblj5vK30MzrIKS5uZliscjOnTtrfu/s7KSuzpksHY45MeYRfLmd8j91Ur6pneA/987RZB/NzU3U1xZCfXwQo44uQZ0h+G4TdlsGc1sz5uks6vgCNAYcsYm8jCL4Sit2XEd5XV43xBE7IpsGdXIBva6ELSnKn1oWy53kOEhMumPm8rfAzKs75uabb+bd7343HR0dGGP4/Oc/zznnnAPAW9/6Vu6///75PNyiotPePmeajJlxY9mXZw7vipmtZahdUqp0SUK65ljq8tm4WGbjupnm2InuFy32NwkZo5LSvMv1MqQ3wV1jC4XZHS8hXDopDDM2o3KoYWfUoatXDUXbjGiCbzTHTMQQdxXK0EMyBu91w+gz8oTfbMHcV8nKW3GzqPYwygY8nIp6i5LG7kijjylA1sJodeEJ91K6X2RbkMjw6YQU+4nuGYGMBJCpuhUz3wt6c4Rf6cB7Ry/eWRPY51KYu+uryhNhnkkzHktXmQzHluVJj0Zx5uuRlIiq9vjCPeKJ52Cme6ct/itHojr9ohE1nI6Vl9THxWZzln2tdEnLe500fYNczgm3cFK/oRPWS/eOY5/MqyXkIx/5CPfddx8PPvgg//7v/84f/dEf8dWvfhVIaLQOh2NWqNVF9AuiEUDwzRaYOIBHuSHEu2QEVW+wz6bRLxyLLCKwV+fRFkYp2LWdmhHUPp6D9gCVdb5uuyWLuaUFAO/SYdQq9/LRZ+ZRXQF2XGPuaFzs6hxhqL0RMgfytwiWzXm1hJTLZbq6ugDYtGkTP//5z7n00kvZvHmzi45xOOaTrvLUl63eUCTcnoo+Ng0QsN/T0dtuH3N/DrstReqDPXhnThDe3ghB9LyaR7P4f9QfuWryUXehVpdgTGPzLqcDgPl5I2ptEX1yHv2iccKvHNnhpmplZJGxO1Mus+wCM1ddxyGvCens7OShhx6aWm5ra+O2227j8ccfr/nd4XDMDXt/PWHlK9N7yTjpD/WQ/tseMh/pIfN3PZGYtCHBdTXmYe6pi6YeL2rCHzaiXzCGWrnXRWV3paDPx3v18JTwVR1bwG6tTKjoABTmZ00A6FMKkD4yLERqdQn/DcOoNbXWH3NXHdYQTT7nLEOOBObVEvIf//Ef+MLnnU6n+drXvsbVV189n4dafHxvr49b+A+V7INE6F3SFN4x33fSdPLSN54w3XzMfymR5aVnCHdLmh5clpWURj1puvakhAKxuMUEzUaS/kWG6Mo07iXRySb5nhOufWxKcqFDmHJrhhD+bzN2WxrvNYPQYGp8/t4pRfSaPoKvtmCfqvJ3y+tZ9ituFoX5ZRPe+RPoF44RfqcFJjzIewS3NuH/wQB6ZQ+kbJRK/qvtla+mvVlT96WRmmK2fnvZNmZ5LSVJ0yXYQq0+SGpGjEgFrqvrtyuL7fNQHSH6eUXMA3WxfkBOtxDTmAhkiG08BFpqTsRqmcJfpHWXIb0z1kX0WXqDxf+TAVTWos+dwNxTR/j9psgtuCeFeSCHtymP99Jhgi+2x9Omy3sh9C+x50Dq2BKmW0hsK3OVByRpv7JVQtyFnBXuSMkTMjo6ygc/+EF+8IMf0NfXR3NzM8cddxwXXHABr3vd61i+fHlsnwsuuGDOlXU4HLXYh+sIHq6KPPOArjL+G/tRy8uk/nSA8mfaI2vHPlFTKdmD/2rB/5M+zEM57CNRdlb7cB3Bp72pOT4mv/qj6dSdm3USuysVDUI25jEPHMbRgJ7Fv2IPKmuxg140r855E+gTipT/YRlMKOz2NGzKR5ah9iCa0NBx0DkU3TEHNAh529vexn333ceVV15JV1cX+Xye9773vWzZsoX3v//9vPrVr+Yzn/kMK1eunO/6OhyOmbAKutMEn+rCe1N/pFM4c4JwxkEIUeIzZbFbsthHo1lkw34fdVIBVW8Iv9eM2V5tUXFC8ynqQvTr+tAnVJK59R3mmWQrCfIAzGM57EM5vN8fQLWH+G8ZhIxFb6hMSjeqoeQGqo59c0BPy49+9CPuvPNOTj/99Knf/vqv/5of/OAHeJ7HRz/6Uc466yzuvPNO1q9fP2+VdTgc+0mgMb9sjAYhJxQJqzKbJu76nVZSf70b/896oaAJvtpWCdud3KIykd2R/nHrG9TRBfQl/aimEFuG8H+aMXfVJ+97KGMV4c1t+FfuwbtgjHDQI/hKC/7V/egTo4zAtqQwv6gn/GljJE49zMdlS4YjxR3T1dXFxMTEtOvWrl3L5z73OT7ykY/wrne9i+9973tzquCSxZi9fsGYb3rmlMSxtOuzzG8QIxbDLpaF/1RJjUfS/nPxn8b8+gn+UfkQxLZPEFtKpD5G5gVJ0rQkLKukPCKSJF+1vFcyXbZMNS7KM1U6AvtMCltQqEaDWh1gd1TyNSj2huDW7K9gRQnv1UMQKMytzZhfVrteqraDuKYidm1mOUqR9yYp5X/ScyLWJ2mxYnlDZF4Pa1HLy+gzJ1DrSqijSqhKFW2PT/CfbTUzHcf2T2i6sbTv8vBSeyYlIp7MCyKfpdr7Y0pSc1KVtl3qT6Q+5vEU4S/q8V4wjvfqYdSuFPaZDKwrYu6rx9zeDKN+1FL8acz8sm77SpE/dUCx3hf3Supnsgl9rNSqJenmkvKGSI1K9fmE4lgHk0NwArsDUsxcffXVvP3tb+e3v/3tPrf5gz/4A37yk58ccMUcDsccMQq7I3opqrWReVyfnsf/i17UcdMMlpRFV7YLrluB+UUlx4NzvUzhv6MP70Vj6HXRAMSOasI76yj/Y0fNAORIIPxuE8E3mrHjCr2yjD62iN2Twvb6Tiq0SCit5vy30ByQJeSaa65h165dnHHGGVx00UVccsklGGNqRrtf//rX6ejomLeKOhyOWVIXTg0+7PbI+qU3TUTzeWwoET6VRR1bQL9kBPPzRuzjuWgSvHsqc3xMfjkb90aZxO5KoVqKmO0pgv9ohT6PqTfukZYSwyrMPfWYR7J4rxhDnzkRDUZ+bxj76mHs1gz2gTrMbxr22xXoOPI4YE/dJz/5Sd7whjfwyU9+kr/4i78gn89z6qmn0tHRwfDwMIVCgS9+8YvzWNUlhvb2mS49ZvaV7hdhOoy7IOYYuiiRLoOEsNMYM6Vel2ZUWVaSmVUi07TH3CEJJnhpo5Zp3pNcX0kp8YXLwEozbML2sfKlyyAhbFNi5Eys1bN3njuGSoHZnsI860E2QB0T+ezD++vQZ0/gvW4Q5YE6qkT5HztQQ7noZapsbGrUmIleuhvk+ti9F+vltZrJpA1xE3oSsXshwp2FmTzmDpHPsdaY25vRJ/VW5VKpak/S7SrdVaI86Q6RSPeKDLGNIa6XKQgXRSphlFS9v3xO5b2udrWNewTfaIT/qUdvyuOdXkAfXUatL8L6Ipwwgfnaspq5jWRK/KS2FXPtJfWxSc9lUh8rmat7ZqE4BN0xc5ILnXPOOXzrW9+iVCpx//3389RTTzEyMkJHRwcveclL6OzsnK96OhyO6dAWfe449pkMtqdqAKgs+tworXt4Zx2g0KfkUT6Ybh99ch7/VdH8HnZMR7PBXj5I+K+Z6GXhvlynxW7PYJ7Iok8o4F04Svj11sWu0tJhQmN+UY/5RT20Gbwz8ngvG8U7qYi6spfwC51QOtLMRQuMZo7C1HmryX4zL5rldDrNueeey7nnnjsfxTkcjv1EnzeGf8kwNq8I/q0Ddkb5KdQZ46jWEDumMA/kot9aoq8zlbJTA5DwtgbCO+tJ/cUe9IoA+4ohzPfapj/YEY9FnTmOWhNZkybTkzumYcgj/EkD5pk0qSsH0GtK2JeMTM2z43BMckDjnm3bts1q+507dx7IYRwOx0woi/eCseg/cxb/HX2wpgApg75oCIDw9oZoFlwgfCCHDYlmxgXCX9UT/rAJRj2Cr7YA4J0/hjouv+CnsuSpC/He2o//+4OoOovdkSKsXDPHvrFb01NtSz9/BDrKM+/gmBOTycrm8rfQHJAl5KyzzuKSSy7hHe94B2eddda02wwPD/PNb36Tf/qnf+KP//iP+fM///M5VXTJYfeG6MbCw2LhYNIXLfyZciwoh4ZJ088nTBcfI6mhJYWzVes+kjQVMV9qgl/bJKSgT9R8iPKS6pMUspvkW07SKcjjJx1PhokWhH6nant1Uh7VHmLHFXZXCn1sCe+KXuyWDKo5xA56hHfk9vrPezXmnnq888exezzC7zVNHc9uzu0NuXx9P+XPdMCeVE39Yn57gSnWnpuO6WtmDi+OIa/9LEPRKQvNR0lqoWYOIZ58TtWxBfzLBlDNBhtA+IMGwp/Wo2rjlhM1JbG06UKjITUiJi/q68ntZ9ZHyfMzoi1pGcZaTSxcWOpzEvq0qhT+5rEs5rEM+qQi3u8NEP5vExZAEU2COOAnpnWPHV+gk3R18jmd7dQVswzdn1E3dzA5UvKEPPbYY3z0ox/loosuIpvNsmnTJlauXEk2m2VwcJDHHnuMRx99lDPOOIOPf/zjvPKVr5zvejscRzbaol80DEB4Vx3hbY2k3jGAPq6EOikKvw1vbZqaDXeS8PtN2FEdpRUX/vnw+82oY4vo5QHp9/ZihzV2WxqzNYO5pz6W/uZIQJ8/hn/pEACm2yP4cks0Oyy4ZG2zIPjvFlLH9aCPK6Kv2VOzLvxJA+ZHzgV4pHJA7pj29nauv/56du/ezac+9SmOPfZY+vr6ePrppwF4y1vewn333cfdd9/tBiAOx0FAXzyEWl3CFhXhL+uhrCh/oQ3zRJSe3WxNY+6fZv6Sosbc1gTTpRYPFMGX2jCb05Hbptmgn1fAf/Uw/lW90HQEaSById5lA1MDkPBX9ZQ/2bF3AOKYHf0+4f80Y4d0NLit/AvgvWQMfcHIIlfwMGEyOmYufwvMnISpuVyO17/+9bz+9a+fr/o4HI4E1EkT6N+JOu3ga817JwcrK4KbOlAry1GkzIFEuOxJEdy4DNIGdVQZtaaM94JR9PIAdWU34Re7oP9wfhFb1PMm0K/uRzWYyOv68wbC7zfHQnwds8P8sgHzy4aa3/SLR/FfNYJ+1RB2yMc+ehhP/LcQHGkhukcythRi95UWUMb3y7wgCb71mG5Cxvcn+cqlDzIp/0JSbguZ5r26PLkuyfcqNSRyf6n5KJdql5N8sVIjIkmK70/yBctrk6SJSZjy2xaKtetlLonqttMe4J01hr5gPNr0jgbMA1lg7zFtIcBuUUDlPKRvvZRgzZhsm3mwT6fg6RTh/WlS7xxALwvwrtxN8IUO7K7J+2Yjt0So0OmEVNky10RZtpWEDjBJT5SUdl0WVxD38oRxvBeMo4+N7onp9gm+3ozdmmY6X5QpyTwj8rmbWSNiQqnxmFmzktiPGJknpPb8YmnpyzPXb0ZEWTot6irbmdR8VOpubq8nbAnwLpjAe2MfwX+0Yx/PxfVDsbwgCccTbS8xx01iv5Bw7WfK/bSQmpBDkCUftP3pT3+adevWkc1mOeecc7j33nv3ue0Xv/jFmNI3m83WbGOt5f3vfz8rVqwgl8tx4YUXTrmRHI6lij5znNQ1PXgvHUNlLWZzmvD7TQtz8EGf8j+3Y3amUI2G1Ht68f+8h9S1u0ldt5PUx3aiTjm0I2rUpnFSbx+IUo8HENzaGLlftqaTd3bMAUX4nWbMY1lUClJv78f/sx7UGWPgH4EipDkzV1fMITB3TD6fnzbk9tFHH52XClXzjW98g2uuuYYPfOAD3H///Zx66qm87GUvo7e3d5/7NDU1sXv37qm/rVu31qz/+Mc/zj//8z9z4403cs8991BfX8/LXvYyCkkTjzkci4G2eG8YwL9sEJW2mGfSlL/cRvD5joVNpz7mEdy4DLMtcsXo1WVUW4jyI+OV//Lh2ARphwyexbu4IvL9dR3lj3dFupnQJWxbEIwi+M82wvvqsAHoNWX83x/Av3YX+lWDqLXFQ7dtLTRaz/1voas8m41vvvlmjj32WF71qlexceNG7rnnnql1b33rW+e9ctdffz1XXnklV1xxBSeddBI33ngjdXV13HTTTfvcRynF8uXLp/66urqm1llrueGGG/jrv/5rXvOa17Bx40a+/OUvs2vXLr773e/Oe/0djrmizx/DO3sCayD4YRPBjR3Yh3KL84IsaILPLyP4VivlL7dR/tQySp/owk4oVFeAOmn6mbWXDBmD/v0+vCu7UaePgRe92PQ5Y1FityFN+F8tMOC81AtOWRN+vY3yR1YQ/KAJO+ih6g3eC0bx39mD9/92oN/Qh3reOGSdNmefHO7C1I985CPcd999dHV1cd9993H55Zfzvve9jze/+c2xabznSqlU4r777uPaa6+d+k1rzYUXXsjdd9+9z/3GxsZYu3YtxhjOOOMMPvaxj3HyyScD8Oyzz9Ld3c2FF144tX1zczPnnHMOd999N2984xtj5RWLRYrFvX77kZFpVNzi3ONTcs+sW5BXLjZ9O0IXMVekLkGMfuX09DPqGhI0D4l5OmIaCuHbTSp/tnM4yO1LCZqTpLli5PZFqfEQ91poQKQvu6bt5Az+Syup17/djLmrPqYLkG3LBtLXLeYzEfoiqWNQnthfdkpjEN6VrayK1pk76/EuHkO/aIjgqRRMeNMeO5EkrVTScyWouVatAf4f9qK6ouvtbSiiX6Exj+bQZ0Yam+BHDdi8mX5/4nk2kjQsch4g+VzLvCryfEyhtm2qhK9U2QfH5q6RO0hNTHX9El5GOpaDRORAETlITHFmLdLUPDkTYL6fIfxRDn1yEX16AX1iEVVvUGeMwxnjWEMUOv5gZcLFoo7pkWLnnvDcyO1jOWSknkZqQCRVOV9swhxBRzqzGoSUy+Upy8KmTZv4+c9/zqWXXsrmzZvnPdNaX18fYRjWWDIAurq6eOKJJ6bd5/jjj+emm25i48aNDA8P88lPfpLzzz+fRx99lKOOOoru7u6pMmSZk+sk1113HR/60Ifm4YwcjlngG7y37YkiNLp9zK+WbtRA+PMG9AvHUSvL+O/djbmzEbs5AwMZGNMshp+5hoYQ/x29qPYAO6Qxv65DnzmBajV450YDENvvYX6VW9x6OvZiFeaRLOaRbJQT5+gAfXIBdWKUx0atK6HXlbAXjRLe0gQPNLv5juDwj47p7OzkoYceYuPGjQC0tbVx2223cfnll/PQQw8dlArOhvPOO4/zzjtvavn888/nxBNP5LOf/Swf/vCHD6jMa6+9lmuuuWZqeWRkhNWrV8+5rg7HPtEW7y196PXFaE6Y/2xdWP3HbJnQBJ9vw3/dCGplGe+iEbgoWmXzCrrTmNtasM9mZy7nYJAx+G+vDED6PMqf6oARj/DWRtSpRbwLxsCD8FutTgOyVDEKuyVDuCUD/wO0BuhTSnjPH0MtC/BfN4Q9M0/4+eXTD0S0hZSF4pKPw5g7h/sg5D/+4z/whak+nU7zta99jauvvnpeK9bR0YHnefT09NT83tPTw/Lly/erjFQqxemnn87mzZsBpvbr6elhxYoVNWWedtpp05aRyWTIZDKx320pmDJvxsygCTcy5q4R++tMbR4GK8y2Spoe5QGkSyAWBiv2iLmThBl5JlebdG9IV07S9O1y/5TIQTHbcGN57kn7y+WkNOwyRFdunxDCO6P7hcjMqy8aQZ9YwJYU5c+1Yrd7TIaIxsI8ZVp3Gboo760wDcdcBjOYpeOum6p29KSH+XhbZD4/K4/uDKEtROUsrC+i39GDubMhmsCsksXVyOkOEtwxsfXSfVFTnkUdm8d71QhqZYAd1ZT+tQUGAKLt7K9TmF/vnQU3HnI7c3SGvHbSvSL7gVCEJCf1E0FZHr/2eDJVubzXni9CgGXaeJFKYDYpu8OEe5d07eLbi5BfGVpefbxusAM5wjuzUWjvK0YxT6YwE1XXv6p81VXGe+E4anURPIu5vQX722ztwF70qbGpOESIcexez9A2ZTtx1DKrQchRRx21z3UXXHDBnCtTTTqdZtOmTdx+++1ccsklABhjuP322/d7wBOGIQ8//PBU1tb169ezfPlybr/99qlBx8jICPfccw/vfOc757X+DseBYu5owKwpEf6yAbvlEEoMZhXm/hzm/opbw7eoZQHeCyfwzs/jvXAMfUyR4MZOKBykr1Lfok+bQJ8/hl4dvShsXhF8rg36XJ71wwqjCH9RT/hAFlXad3uyFuyeFPbpLPpNfahlZWA6q5xl0V2Hc2WuES6LEB0zLzLw22+/ndtvv53e3l6M+PKbKZIliWuuuYbLL7+cM888k7PPPpsbbriB8fFxrrjiCgDe9ra3sWrVKq677joA/vZv/5Zzzz2XY445hqGhIT7xiU+wdetW3vGOdwDRl8e73/1uPvKRj3Dssceyfv16/uZv/oaVK1dODXQcjvln8qtIRbkPAs2MHV5JE/xbe2X9IfwVFSjs7hTBN5oxj2Tw31Rx17y5H3NbFAHBmJ4/X35LQOrKPlRnZHGwZTC/rCf8SQOMeRzS19Kxb8a8md0IvSnsQDaKhrJgd6b34d6sFubaaNFyaGlNDnd3zHR86EMf4m//9m8588wzWbFixbwKVC+77DL27NnD+9//frq7uznttNO45ZZbpoSl27ZtQ1eN3AYHB7nyyivp7u6mtbWVTZs2cdddd3HSSSdNbfN//+//ZXx8nD/+4z9maGiI5z//+dxyyy2xpGZzoiGMplJvDWDQxw760b8709B3CH3ZOuaBqsHG0WN4F/cQ/usKyCd9lR9CHd9+YB7NEvxbBv+qXvQJBfQJUV4eGxC9RDwLvo16pADsM1nMUznsk1kY9gELGQMNYTSWGBLPUWeJ1BV7UC0hdlgT3tmAuSdXGXw4jmgmc4ysLEWDkKFpXnsZg1pVjNYNVKY8cKlJFgRl5xhbu2LFCj7+8Y8flDwhS5GRkRGam5vpveyFNE36Eat8qer4PN7r+1GN0/tEzU4f89s6zMO5yiRi07xslIV6AxMajIr76WVKYhlOJrdPiw5b6i6kTkOa5MT2NaGCSfvK9TOlgJ8OOahNCgFO0mhIEjQgVu6fF5lBpaalWBVWqeyUZkOdOoZ+fR92e5rwC8sqIjkbC6mN6RLk9O4yPbU4/1jqbzn9u/BlS/3RjLoMcS9iadrFvjKVN1qhTijgXzSGaguhycSy9E+HHdOQNaiqw5mtKcy99ZiH61AdZfw/6kfVG8xun/JnWmHYi4dlyjTlsfBwGe48s+bDiPKM2F9qNkKhkwiFRiMQbSEtr59A1j8Q5aWEJiRI0Gl41f2YvNcJ+hO5XupRYn2SLD8788dZTAcn9CyxdqtqrRrK99EvGsU7Z5zyvy5Dje89njoxj/6dUVTWQHMIGYPdnoY+H/NEDvtwXTwkN0uUZWs6sWvKoNYXIW2xD+cYKQd0ffNOhoeHaWo6OFmOJ99L/e9+LU2ZA//QHSmWab/h2we1rpI5W0JKpRLnn3/+fNTl0KY5wHvlEPrUKGGT2eUT3lmPagqjzJIdIWptCb0qQK8agVeOYIsKxjR2tGKWzlhUSwitAcoHO+gR3taEfbBhaUdHOKanYsbVrxhAnV/JL2NBHV3EPpbjcLN27A/2iSzlJyp5RlIKmkNUvYFQYYsWG4BqNOjji+gTS6i1JVRDVe6OgoKURa8to9cOwRuGptaZ51KUP9saDd4djkkqj5leX4omdixWDbZOG8d78Si2O0XwrXYY1XiXDEY5SToCtFGED9ch3adqQxH/8v7Iuj2useMa8hq1ooxaX0SlwO7xKD+8wGHfR6I75h3veAdf/epX+Zu/+Zv5qM+hRWuAPiWPOiWPWltEabAGwjvqCX/QOBUFMDXqrzPojXn0aQXUhiIqYyETotqntwao1hD/9wexLxolvK0F+0ju0PJPOtAvHUQdP0H4+eWoOoM6aQzvwmGCIQ92HeHzkhhVcVdGi5MRFXYQwm1pzE805AyqLYg6+VENZRW5O8/Ko8+cQK+ILD/m4RzlLzfCDAJFxxFKxWijVpUI76mf6pcBvBeNYramMf/TNhWibZ7O4h1VJPxRc9TnRnvXFKnaQ1QK1LrpE0naAQ/zbCYKD3bMyJwHIYVCgc997nP8+Mc/ZuPGjaSE6f7666+f6yGWJsvKpK7tq/nJPJMh/N9WzHP7GChMaMyv6jG/boz8380hqjGEBhP9W1LYAT8S7E1o9LnjeC8ZRXUG+G/pw/b5mPvrsQ/Ww6DTlix5lIUVJcydzbAtG2ncRkFfNIw+uog50gch+0NeR1+bsNddMuZhftqA+XkTNAdRL9bvQ9IMwY4jE6uiZ7HJYHelosGvBrW+AMvLmK9XBiDKglWRWwYqM0VPqlNrMXfVU342DR1BZMmrM6h6gx3yME9koddjUSydR2J0zEMPPTQV7vrII4/UrJvvLKpLCdutsH0edsgjfCBN+FAGBiv5HGRuhn3l5ahY6JXnU3srLBAS3pYl/EUa7yV5vBeNozqCaKKti4cxW9KEP2nEPpGNTwAkUxIn3YdZpj63VbqOWNlJEqOkPB2xKbRn1kAkpmWXGhKRR8TK8uWyLF/mIZk8f23BqFpNRjbEW1vAPJid+t0+qVGnadQp45gfZ+OajonaLysjcwzIPCEi94SNzVAuc1OI9eJ4Mb1R1e3QKZGKu7aoWFryMCHvhs6JQVhS25muHY9NHS0+nfsc9TJhQrptqQGRGo9yLM/HzMi8Hfm8uH7i8sjLEYr6FAq19ffkdBBi/2CGfiKdFtdKVCYMapezWZmvRuTdEIfyRTv26mpzM5mx2glGZd6OmG4u7YOy6OPKqObKfQjA9BhsvoTyNLqlAEWFeQ6gAEQDEX3MOGaXh9kdxh+oSQKwzyl4LjX9CVWdry0v4OD4SHTH/PSnP52PehyCKMp/3wmhiosF55OCJry1kfCn9eiNBbwz86hjS+gNJfSGfsJ767A/aD8ysgEuVY4dQ60fx/6qDSZ1qyoalNjeFNRVOrLKhGnh/Vn814xCzsAEHInaEIfjoKNArQxIvW58ajl1xSjmkTThHfVRrpqMRa0rYZ9LQ9agzyigjy5TvrHl0HR9K+Y4CJnd5tdddx3f/va3eeKJJ8jlcpx//vn8/d//Pccff/x+l+Gmi5wLC5nmuaQxv6nD/KYO1WbxfmcU/fzxaIbV44qYb7djn3ZzXyw4zxtGvaInSsxV0vDTBih4UQdWUthdKbznj2F+2TDVXvSqKIMn+cl8IQ6HY94xivCndYQ/rUP5FrUqQJ9UQnUYVLPBPJrBPJ4m9bYRwgczqM4Q1RkQfLcxGpQ4Ernjjju46qqrOOusswiCgPe9731cfPHFPPbYY9TX1+9XGQc0CLnmmmv48Ic/TH19fc28KtNxuGpCgtECwaR5WpiZpalw9imMhdlazEhpexTmm/Wo36RIvXUUvSzEe3sv5skM5tEs5okcDFbtI+snUxLLkK6k1OtVYauxMEfp/hDuDSXdHXLULkN4E9Kgx5alKyzJvRILsU1I+15NSxk2jGBua4W8Rl/ah+o3mHvqoRxds/CWetIn5vHe3E/w/UZMqYh/6gTm0RThRKlSn73XIMzPPKtvWaRply6BeNSpCKUU11uul/hVbdOXMxyLmVFlSG7MVSfdNcLELsM0jbgWsedEzqIbS1E/s4VShsRKd4qsfrFY23aCYOZrJ90j8lmJ3bsE740MsZW3brYhubIteP7eZRlyOzEhQruF68gXxy6N1h5bumfSYjbnkri2ulwbCp8SbSsprfpUH1fJEaI8H55WhE9Hbp5oaoqQ8AsZvDPL+MeH2O0ewc312H4vPlt2knVB3puq5XAh07YvsDvmlltuqVn+4he/SGdnJ/fddx8vfOEL96uMAxqEPPDAA5QrL4cHHnhgn9sdzpqQpYDdkqZ0XRupSyfwXjAehTUeXwSGMTtThP/Vgt0en/fGMU8UNPaxemx3GnrTmKYQ/cpB7KiHfTgXCeDGNcG3m/HfOET63UVQED6aovy9yVlx3TPicBw0alwqNva42UFNcFsGe9fhYflQWtfmcTqA/SHKO1LNvuZQkwwPDwPR5Lb7ywENQqp1IEeuJmSJUFKE32kmvLMefXIhmu56XQm9qoy6ag/mJ43Yn7W6PCMHg4KHfbR+ys1i72jBtpTwLhkkHNfYZzKRWPWRLKW/X4ZeVSbMlzGPVjo85VwxDsfCUZ0F1e79VzEVGeOIkDPFf+ADH+CDH/zgjPsYY3j3u9/NBRdcwCmnnLLfx5qzJiSfz2Otpa4u+rLbunUr3/nOdzjppJO4+OKL51q8Y3/Z42N+1oD5WQM0WbzXDOGdnse7aBR7YpHwmx2wx4X1zjuTuqBKdEz4rTa8K3vxLh0k+Go7bFfocyegPwrdM2OV7ac6PTcQcTgWD3XozQ8zI3N0x1RMRdu3b6/JmLo/VpCrrrqKRx55hDvvvHNWR5zzIOQ1r3kNr33ta/nTP/1ThoaGOPvss0mn0/T19XH99dcftrPT2sBgJyfEkr7eQkKqcInwv8p02OF4acb1Mb//SIrwP1qxD2fxXj+EOqqE92e7CL/dgvl1fSykV/rWVUr4W6WuojoXTEI4r9R42JLQPIj9lXR0J2k8JFJDkhT2mbS9WC91CjXTdGuLKZQx/9JC6v/14b1qAJ0HfVyZwt83YceKidO/h0JnIcM8YzoDsVyKpSavPR0Zpil1A9KF6nt716dEmKYsC3FuntBwVGsOIK7xkFPdS6TGI2nGiXJp5rTqUhOSpPGQmpBYiK7UqAjk8eJp3We+tzIEuizTvAudhZEaF3m/BKqqacf0JrLssjz2zOcu71WxKPo8qU/xZr428tppLdqeP/O5yukKZB8rien0UjPr/qqfcyNTvh9M5kkT0tTUNKu07VdffTX/+7//y89//nOOOuqoWR1yznGd999/Py94wQsAuPnmm1m+fDlbt27ly1/+Mv/8z/881+Idc8A8mKP88U7MExlUCvzLhtAvGcV9fR8kjJpysQRfakZtKKM6QgofasZur0zC5nA4HIcJ1lquvvpqvvOd7/CTn/yE9evXz7qMOVtCJiYmaGxsBOBHP/oRr33ta9Fac+6557J169a5Fu+YKyMewRfa8V41gvfiMfxXjmDaTJSm2OlEDgxtK5m6prl+VqGWB6SuHMI+l6Lw8UpobsVd43A4HAeNBY6Oueqqq/jqV7/Kf//3f9PY2Eh3dzcAzc3N5HL7lzJizpaQY445hu9+97ts376dW2+9dUoH0tvbu2Cz8DmSUITfbyb4bjPWgD53DP0HeyA1u4yODmBFEe89O2HZDC63phDzWIbyDW1uAOJwOBaOybTtc/mbBZ/5zGcYHh7mRS96EStWrJj6+8Y3vrHfZczZEvL+97+fN7/5zbznPe/hpS99Keeddx4QWUVOP/30uRa/ZCkP5ylVYtOTMpf7ib5asX9CDLycElwHteuNSDc9mb/B3JbG9DaRumIEfWIedfUugq+1wu66mu2l71g6EWK6jZlI0nCIuYbsLPOAJF78pLTvQvMhUyzbKn2POnkC7/f3oNLA+hHCZxtivmBTDOAhRfDbHFDGlEo1AxB5bwOR96Mo7l2QoPEoSY2JnB4+nPleJV2+6twTUvMg/fiyrFRabB/I7UU7TdBIJNVVaqPktZDlSf2MvNaS2LUWm8vyA7lBAlI5kDgDgngyw5I4vtRTJRy/+vKmxMUuiHOX974g83yI9VKOIvtEqQGRGpRSuXZZ6l9imhUx6JeaFCtS2sv9PZH3RO4fTtQsxnLkVOcNkc/84USSLmt/mLMl5PWvfz3btm3jN7/5TU3ikpe+9KX84z/+41yLd8wz5rcZgn/twA5rVGeIf1Uf6pSJ5B2PdOpC9GXRAMQ8nia8u27f21Yr7Z0FxOFwLBST7pi5/C0w85K2ffny5Sxfvrzmt7PPPns+inYcBOzWNOW/78R/0xD6eQW8N/dh/qcVc3fjYldtyaJOmUClwOz0KX+29TAK6XM4HIcNR+IEdkcqxtqpED0ZqieR7hMZBinN0HJCPM+TM1CKhpKrdWnE0lvLVN0qgBKUPteI/waF/8I83msG0c8fwQ542AEf2+dh7svBkB8LZ6MqRFgpoY2QKd+TTNIyZFemfU+ywcuQ4AR3SyzkV4bW7WPmV70xmgQrvDeDrTLbm7wI4RVma+neKYr018Vi7fGlyT9pJlQZplkqSffNzDMqy/WxEN6q8oNQmqhrFmMzrUp3hzS5y2PJ9UlNJ5ZWXbiy5MyuMhxZugzktZQuBvmUS/dPKcE0Ld0jctmX9ZEugITtx2U4dsL7RAthtak6Q+mOkV49eWzDzHWTy564F77QIsh2nMvO7JIuBzO7a5K8uHJZ3nuZEl/22YF4rqvbWl72UQcTNwhxHFJYRfDNBhjz8V4+imoPUe0hEA0M7EVjhDc3w8PNi1vPxaa9jFofzSkT3ufS4DscDsd84QYhRzwK8+NGzN11qGVBNAhpC6N5aDaU8F43TPhsA4x5yUUdjnSW8f+wD6XBPJOBwSP0OjgcjqXPAUS4xPZfYNwgxBEx7mHHPexz0aK5rQH/XX3otWX0i4Yx/7v/ExIdLqjjK9EwWYsd8Ai/2QYkRPs4HA7HYuHcMUcOxWLIZFSW1IRIf6H0Ncf8iwnO25IIvctmxW0TugQZ8hvTiIiQMStDISv1Cb5XT/rPhlDnjGLvaIChynGrdBOxdMbpBE1CLltbuaQQWulPlSN1ub+cvlyeu9RsyBDbUgBY9ItH0S8fiSwgT6cofaEJxoIaPQjEU/QboQGRYZ8yDbvUKeTzMjV57enI/YsJoZNSR1CQvnjZ9MTlS5u9168ojp3L1FqFpH5F9mfyuYhpQuRU9OJ4Me2UeO7kcxZP0y70QAmaC+nJLwiRipSCyZDZskyxL8qTx5PI6yezyhs7s8ZFalbSCWnbqzeXchzZRXlCT+KJY5eY+diyJilR14wVbWFM6ItEeWnRFsuiLWXEevncybbhiwdDPpcSGXJcvf2E7JMcNSy87cVxyGCeTBE+lUL54F06CN4RkHY8Z/DePID/ymgAEvwiS+lfmmHMPSoOh2OJcwiG6Lqe1TEDiuC7DdgA9IkFvHf2Qsvh6o6wqJPHSf1lN97peWwIwbdbCL7euHemXIfD4VjKLHDG1Hmp8oIf0XFIYbelCG9ahp3Q6DUl/Hf3oE44zJKbtZTRb+7Fe1MvqtFge3yCzyzD3N2w2DVzOByOwxqnCTlACoUQv+KekOmhY2na5ZTfcspu6Q8VKYCl61jmQ5AaE+kfDSeKNcsyDbz0JSOmqQ4e0gTXtZL+o2H0ugDv8j2EP2sg/GEzWjQhmeNEp8X6kfHa9VmRg0RqQGTd5HTvMsW8zAMizn2yfmplCX3GBPq4AnpF9JsNIby1juDWuor+tBjTy4Rjhdryg5lzU4yPC42IzG8g8iEkpRaXOgKZS6JspCaHGUnyVlfXV+aOkCnnZdxQWuhx5PTq0qZmZE6UBK1UTBMi9Tpy+4RrlxfXTubRmBDr43KamTUhsj7xe1m7PiPadlGeb8LNlfdrRLS9nNTYVP13Ws18bElafEHLthAkJPerE22lJPoBWZ+UKM/UPpaEYl6sQrG2tck+VpKUaV3m2ynJfqmKechsvv8o5ihMnbea7DduEOLYPwY9Sv/Yiv+aMfyX5PFeNIZaU8J8uwP6U8n7LyV8i391L6pSbWvAPpMm/G4z4XOLWjOHw+E4cFx0jOOwJlQE326EnTm83x9Ebyih/nw35kct2LsaD51U5papAUjwjWbMwzmYmPwSm2F2XIfD4VjKHIKDEKcJccwa81Ad5X/owjydQaUt3qsH8f6kBzpLyTsvBUKFLUQPm3kmUzUAcTgcDsdC4iwhB0g5MEy6oKWmoijmHZB+fpnvID6Pwcxzy2ihO/C0yAUhYtrl/ulc7fFic9+UhH83l65Ztl4APVD+VAveBQW83xtBrS3i/fluzB1NmNubpyJKzGxj5GVdxPggPteLWI7lQJlu3h4LeQ3ZEHIBtmpOFKkBMfnagZU1UtMx872WyHwD8tpLDYjMTSF1AEnTtUtf/my/c6rn/AhEu5S5HwoJdTHCzy7nE0lJDUQwu7aTNHdLXrQFmddDakLkrZSaEikbkNdaLkuJy6A4vzpx/sNCZiDPL5bjRSCvr2wrBTHDc7XuIs/M7UzqVfLi5mYT8oJkhIZE9hNSzyKNrCUlroWoX07kGcmIeY2kri6QuZISpqySOjyp9arOY2KSJkGaT9QcI1xkkqkFwA1CHHNAYX5Vj3kig//aEfQpBbyXjKCOLRB+rR0GlqBWJGPwLh1EtVY6oUPEg+RwOByJOHeM44hkyCe4qY3yF1ujUN7VJfx3daOOLiTvu4Co1SX8d3ejz5iIImFuacY+uwQHSg6Hw3GE4CwhB0ixEJKquEFk2vUkd0tSmvcwkGbjWmJhqGI5JUyPKZm6XLoopPlOujxmMHNXr7O/zVLamiL1liH0MSW8P9hD+Nnl0FPlzpEhtSKkV9ZNXjwlU09P624R9VMW/TtjeK8YQXlg+zXlLzdjn03HjydTbcv0zgmuNpm6vCTSqst7Ly21RfFDSaYeTwgDLco0+cyMNLPLUMjqtfGQ0n2b8yHu3pDugVhdElxZEukekUbv+LUR91KmXZeh8DLcWZQ/LNPEx+pXuyxDfCdkWxAuBOl+kfdKuoHleom8/jLte/X6RFePcOVI90tS+HBLQop5I9uhdElb2S/Uli/dmDZBrpYR3yJJ4eHSnTOT+yZICG+eV5wlxHHEM+RRvrENszmNylm8y3sXPd2799oh/FdHA5DwgQylj7djn00n7+hwOByHEkrP/W+BcYMQx/wTKsJ7KurXegN6EQchnkWfFWV4Df6nieDfmyNRquP/b+/NwyM5q3v/z1tVvUpqraNds3pmvMx4BrwM3kJsjBcSuH6AACEYY5bkEptcfhPCDycE44Qb8wRCzOILiX8BfMPlmgQHwkPuNYsxxgSz2DAeL7N79hlptEvdrd6q3t8f1dKo35ZUo5FGLWnO53l6NNVV9dZbS1edOud7zisIglBxJBwjzD8hjXNrEgDvyQTkK/fQVx15lAM6ZeE9WU15cEsQBGGZYKmykPes119gxAg5SyxbTWg5zPCnOQR5WRn1gLRVM55qDkNdVgbeTMM06j87RjjE1DGEjALaVtRIyTV1DZNKIFtG+WMVCWFdP4JqcNGDNu4TVSU1kC2jZLznlm5bGfoVc7pMw2Fg6lfUSj8YrA+HmEohUZaSa2hUvGxp8bKg4enLYttm2XdDiBAULzaHSDeHBTd1C2bc39QVmLoOs/0yE23y8lPpbSZhplWa17G5p+bZCJof1F55CfuZNSNBZdyTxrkzNRempsOcb2pOguabZdVNzHNXrhEpXT5j9M/U7JjLT5ZBmJoQM9241khRzRRm3lbc0FgkjX01U37tsnRoI+XW/B2WpVNjYKTQmloz457tuKbmZOaHs3lfKEzSC5n6lHPKXEMqEo4RljyWxr5+FAD3/9ZW1AsCp40Q74hoQARBEBYb4gkR5peQRkX91xDv+VjAwuceq6voCREjRBCE5c4SzI4RI0SYXyZ7HpWmotXAIh5qhR9g0MekHoggCMsca44VU+ey7lkiRshZ4rl6IqZs1gkxg62Fgll3w1jcWN4x2jPS+cuGRLfNHHqz1LkZuw8ZOg67bIXS+cbyJdZyWYL85HlTaDyMtsw6IcqZeYhtkzINyKT+qA5fz6EHbPSoAjy0GSwOqENihUp/IvlcacEBs1yzYw5JbqgszHOXy85ciyJnnnyDsiHFA3QTQXlKM5WBN28Wpv7E1FQEaT7yxjdlFfsD7FdzefN3FaQZMa8dU/dgHgvzTJi6iVxZXZCZNSrm/pn9La8jwowE9a9MQ2Kcodwk7YJZg8TUbKTNoSgC64qUTpt1RVLG76jG+B2Z+h1tXvfGwTHbn21+nqnVUmb9IGN5x9ze5PpJATVT5pUl6AkRTYgwf0Q9nLcPAKBzCryFv6BLqCoaAI6G+AKKwwRBEIQzQowQYV5Q7XlCH+rH2jyGLoD7rTooVNYI0XtjeL02KuHh/P5QZeuVCIIgnGuWYLEyCcecJZNTdM0Sv6b3LWiUXJPZrm8ub2aElZWRN64zy6hZXBZCMUMWk/bXioRQF45hv2MAFdZ+Wu7XGtFHIygFVrj0EjPDIUHbLqNsX4wU2cnhnazC/XoT6q4e7E1Z1J8MUPjnOhg43SczBbdsRGEzVGakJpaXYZ9d+MR0e5sn0zZc5spwBJeX1zZSbgNCJOZ8M8Qyee5sPbVmyq7psi8b5bVs32YuS+4xs4s8qLtmeCaof2bKq8moEXY1RwUuGwk2wCY201zNUYrN0Jv5yzGvLbP/5rUzebpsxGCjr2b4waQsHdqYNlN0zfBLEOa5ixkxaHOEZE9Pf11PtbyZwmv+7svv+dP/bsML6YRVzDEcM289OWPEEyLMjbYc9h/0o8Iab0+Uwmdb0Ecjle7VaY6Hcb/WhE4rrFU5Qh/qRa0KGEhCEARBWBDECBHOGtVewPnDXlRE4x2I4H6lCdKzE5YuBPqlGIUHWvEOhlFRjf36kUp3SRAEYf4Zz46Zy2ehu7zgWxSWBaqtQPgDg6gqD+9IGPfhpsoLUWdiyMH9X03oAlhrc6i12Ur3SBAEYX4Zz46Zy2eBEU3IWRIKWYSKVqOpCzA1GGXrOrOz/ZxQ6fJhY9pMETbnh6YorV6yvqnLMNY3dRrWWo3z3iFUtcY7GqLwUBNkFKCx45EZ1y0rfxyUl2nqUUrnlmtMYkbJ+cwkzUfKwvtVFfZVKeybkhQeipWlBFvR0mOhc0bs10zJNbZv2wEl+824vLG/EeO9IK+NFN8APVC5ZmTm4zebUuvmsiZmprq5uNl3k7Ay933mOL0y9iajZ9ZklA1vYLz1mSXwzUvRnM4Zsf5641pKBuiDyjUcpdPmT8NMOzV11mZ75tbD5vrG/MnXinnswgF6mbJjZbRt9t0k6Do1MfUy5rVnakTMdGTzWJj3zCBdXpnObobfpdk3oZRF7wl58MEHWb16NdFolG3btvHLX/7yjNZ75JFHUEpx2223lXz/rne9C6VUyeeWW245Bz1fnlivyODcdQpV7eEdC1F4aAVkFv1lNIH7RA3aBWtDFuddfajOfPBKgiAISwHJjplfvvGNb7B9+3a+9KUvsW3bNh544AFuvvlm9uzZQ3Nz87TrHTp0iA996ENcd911U86/5ZZb+MpXvjIxHYksIiHlokVj35jGeUNxdNyXohQeaYCxpWOAADDo4D6ewL5xBOuSDOFLMrgvhXEfq0YfltLugiAsYZSa20i4UqyslM985jO8733v48477+Tiiy/mS1/6EvF4nC9/+cvTruO6Ln/wB3/Afffdx9q1a6dcJhKJ0NraOvGpr68/V7uwPLA0zltGJwwQ96lqCl9tXHoGSBHvBwnyf9eC+2wc7YF9cY7QBwewtmQq3TVBEITzikXrCcnlcjz77LPcc889E99ZlsWNN97I008/Pe16f/VXf0VzczPvec97eOqpp6Zc5sc//jHNzc3U19dzww038IlPfILGxsYpl81ms2Szp0WMIyN+ZkUoZBMu6h3M+KCZM27GF834oxlPNEt7m2XczbLrpiakrPS5qemIBmhAxmt7WBq1IUvod5OojjzaA++7dfBsI3ZxbLqyuh7mdHmRk9JpQ69Sps7OG+ES29C3BKi5yzQp43VERsPw71W4T2SwbhnE2jSG884hKNTivRCdWF4b+h1Tg+IYGpGY8ZOy86WajqAKzt5Y6fJxY/9Caubh581ps5x1WSzf2L6pu5isAzFPXZBGJGK4ds26HmZc3yRqnOu8obEoPVJgGefaLJMeLdOAlI2fYLQ/s6bD1DmUlzIvba9giDjMOiFmbQ4Tc/lIUE0Ys9ZFgK5j8rUSt6efB+XnLljzUTptloE31zfnm/ofU7MyWw2Iqcsz635EDC1X0NAZZbWaJl0LIfNCPZfMNaQi4ZjT9PX14bouLS0tJd+3tLSwe/fuKdf56U9/yj/90z+xY8eOadu95ZZbeOMb38iaNWs4cOAAf/7nf86tt97K008/jW2Xp5fef//93HfffXPal6WGaipgXZ3GvmwMlfB/fTqtcL/ZgH4hjlX5wXHnj/4Q3tdXwFv7sLakcd47jPujPO5/VIMrijJBEJYQS3DsmEVrhMyW0dFRbr/9dh566CGampqmXe5tb3vbxP83b97MpZdeyrp16/jxj3/Ma17zmrLl77nnHrZv3z4xPTIyQldX1/x2flGgsTbksa8fw9qUmzCIdVLh7ajCezwBqcVXA2Re0ArvX5ogM4C1LYlzYxprUxbvlzEKv4rA4DLdb0EQlhfiCZk/mpqasG2bnp6eku97enpobW0tW/7AgQMcOnSI17/+9RPfjZfQdhyHPXv2sG7durL11q5dS1NTE/v375/SCIlEIlMKV6MRa8JdHDLCGaZb1Rzltqx0d9n80m3ZhuvQDLeosANK+3ltHlhhI9xihDxKSqlXu9iX57CuSKLaToc+9J443jM1sD8O2L7bvmq8vUnth0q3ZYZLysIr5rSZxmiuH42WTgfVqHcN32dZyflS3YeKTFr/hx24+wexbuvDanWx3pDEeUMS71AY7+lq9G+qMDHL0qt0af0RnTSmjd0xMUfhzWRLRxlOZ2dO2Y0Yh8c1QgBmiMKkLEN6kls7yJ1vBi9ixr6YqeYBFevLXOROfmYXeNoIfZn3U9usm24Z6dTGfPN2XGv0Z9Q1z4XRvNGCOVKsiXk808a1HTSKbmGWQyOZZfKjk85X2Nj5BscMCwaE0spSfM3Q0MzhEjOcYobSzOXN14SYEU4x77FmOMYsY2CGwIOuXc8IxU0+dQXzniSUsGiNkHA4zGWXXcbjjz8+kWbreR6PP/44d999d9nyF154Ic8//3zJdx/96EcZHR3ls5/97LTei2PHjtHf309bW9u878M5Z7I+QKszH6/a1lhbx7BeMYbamEUVf386p/CerYJf1kH/pEyR88gRoHdV4R6MojalUJemUKszWKtzWKsHcFdncb8Vg/TSFOQKgrDMseaYHTOXdc+SRWuEAGzfvp077riDyy+/nCuvvJIHHniAVCrFnXfeCcA73/lOOjo6uP/++4lGo2zatKlk/bq6OoCJ75PJJPfddx9vetObaG1t5cCBA3z4wx/mggsu4Oabb17QfZsVtp5anzD+5hbVWOsKOFsK2FsLZD9ZC8mpH5SqtUDoj/tRDaetc+9oGP2bKrzfxGHMLnu7P+/I2OhnEv4nmsG6Ool9wyj2VSmsLWkKj1Xh/iRW8VGCBUEQShBNyPzy1re+ld7eXj72sY/R3d3N1q1beeyxxybEqkeOHMGaRa1727bZuXMnDz/8MENDQ7S3t3PTTTfx13/914urVkhcE7rSI3y9h71Gk3kwhPtsuTvCuSFP6OY8VsdpF4j7q1B52sAkdJ8NlkYPW3g/j+P+JoYaWk5K03lmxMF7rA69P4r9u0Oo9jyhNyZxXpvCeymCu9PBfTEk3hFBEISzQGkzn1SYkZGREWprazlyzSUkitoMFZqlLWfEhstSZtfnCb0ui3fcInRjjsJ3qyj8MDbh+VC2wtqcxbklhfvLKN7zUexXp7EuyeL+oAq9M+GHaiaWN9LXVmvoD0HBmrr/QbqO2PRGi3KMtsx1zfllDQRY4qYGJGBam/FYc3kzBThj1AqZ/PNQGi4cQL1mAJU43a72QO+K4f5bA2536Qi9bqp02suWbs81NB+pVOl0wbhWCsZw8fl86XTOqCUeJMExU45N3cFkXYbZlqltMuPs5qk04+om5p3IjOObwyOYcficoQnJm3XVDUx9jDmdMQ6WqaEwU2LN4e7N+TkzhdboT8GYbxkH0GzPxGy/yjhhs2nf1BqZZ87UhJTp2AJSZE1NiDkdMTUjAcM/hA0RS9jQeJhlEcr0Rsa1a1575vAL5mOzvGz76fkjBZdVP9/F8PAwiUSCc8H4c2ng4ftJxAOEZzO1k87QcMc957SvJovaE3K+oocUhe+HcV8MYbV4WOvz8JMoZBXgC1Dtq8fQgzbuk3GUpXB/Ekc1u1jr8rg7AzbQs4i8PksJrdC/qUE/Vw0rM6gNadQFaVRrHnXJGGrlSfSjVXi/ihA8+oUgCMI8swQ1IeJDXoToHtt38QPuzhBWVwFVNW5ZK9/Y6Crg/uckizdpQVqBU1zOzAQQ5g9PwaEY+vuNFB5oI/9AK7o7hKrxCL9rlNAHhlEtheB2BEEQznPECFmsFDNf3BcdSHioxknu/7QFCQ/db59eNq9QrQVf8yEsLN1hCp9vxf1eLToH9oV5Ih8bJHT3EPbleV9YLAiCcK5Rao4D2IkwdckQbk4QLmopzOHdTcpKh4csqPYgrGHYhpkGcvWAXBJnvYXu83UhqtWFnMJZHYZCHBUNQ3UeVT2IlavFqqvCz9ctXlCm6NbUZRi1PgJ1HTOJeM11y8fAnn7dM5lvtmdqOsxYtSmCyJVqNMrWN/Qu2pivwqV1P+zJ7T1bhberFuvmPtiYxr4oj31RHj1i4f28Cvfparxeo7aEoQlx4jNrSLIZoxaGcThMTUje0JC4ZmlxM1ZvxMrdSToJU/NhYtbLMePuJqbEwYzLm/qXIPmaqY8x9zVnzDc1JWb7I0nj3BvbMzUYpubC1NdoQ1Niltg3987cntmeuT1Td2FqVMztm7qPyc2ZGg2zL2ZZdfMOaGpCzOu0ytBslF075nVpzDfr6YQMTUjU0HCYtZbMsIMVMe+BAS9zZm0ns3bTpM2F8wvoFZXsmPML+7VJyCm8UQVJhc4r/xwqwNL+0Y1oVAxURKMaXVRbwf9U+z/b3N82Q/c0p8HS4Cn0sQhqVRb9q2rIKxizoTuC9duDeAMhyDmoV/fBYAgOjBfUknBMRRgM4T3SBnV51GUjqFeMoBIe9k2jWDeM4v4qivtEHH1CfnqCIAhyJzxblMZ+XfKsq9xqD9+gmGl8knF5x94o1pVJiHp+bYqMjfejeqzX92G95wSENPRG0N9vgaxN+TuVsOAMhdCPN1L4P1VYm8awrktircrhXJXBuSqDtz+E+6so3s9tSe8VhKWEpVH1HqrBQ9VpVK2HqteohPa92wqUpdHDNoV/rV7YvknZ9vOHUHMNPOui4y6Mf2ztP/89AOUbDDnLNzbyFow46FMR6A1DXxgKln8CWsOljZtppYUYNA5h3z4C1Tk4mEA/2Yn+Tj20pGGoBsZrfSSmCKeYpdVNwsb2zeXL2jOWn0x5XubMbZkXfWHmUXPLjo0XUBI5aHkzHGOEb5QZvjFSeMvCNca0k07D0QR8vQWvIw2X9aMuSmJdkMe6II/ze6D3xvCej6P3RdEDpel1ZqgvZIRvvLHS/sUNN7WXKe2PF+AaLnNDT9p+0OjMZtpk2QjLZaG5mZc3S33rgjEisZGSGzXnG8fOy5kjGpca6+l06bGpqiq9ds3wjhnqKi/dPfPyQWme5vbMdGoTc3YoVNpePm+Eb4wQxuT+lqXc2jOHS8yhKsz0XzPF1VzfDKeYYUFz+2Vl1I0Ci2Z4xa6a4Z4FqMnLOxrV7KJWFFD1BUi4qFrXT8uvLU6fgfRO94ZQTyQI5RYwHLMEs2PECDlbPMv3PEDwIBhnW4qlKYt6yxFIFGAoAmkHvbce9tb680ci/mfCaJikAxEWH8fj6IMhdE0BtXnU/7TmUBePYV08BoB3zEG/HEGfdNCnHPRJG1LjMT5BEOadag/r0hTWRRlUZw7q3UCHgHaBYQdGHfSoDSkHkrb/0jn+IjpWAQ+neEKEeSVlox9rg6EGyEw6VSVv65rTxoc8qJYEow76Z/Xon9Xj1SSxtqSxNo6hOvNYnQXoLH1z0imFdzCM90IE79cOjEj4RhBmRcLFfmUGtWKSN0yB6iigVuXLnr16TKF7QzDgoIdtSDq+J3vYhiEHlQmXlkEwPQhBow0KE4gRspgZc+Dlaog7jBcpK0eMjyXNqTDeD8J4P6iDahe1OoVamUe1FHx3cIOLqtLYm7LYm7KE3gbeQQd3VwhvfwjvJQ1ji/38a6jRWC0a1eKi6j2/OIClUEpDCFTCQ9X68XViGjIKsgqdUei0hR600H0KPWDh9VvoUwFZZcJ5jn/N2ZvyOK/KYV1cmPEl3zsWQu+K4u2Pok85qDGHyffVstCiOaT0YkGyY84jamsh4scZlalbMDHTTs3wjKnJMCnPZSydNi+ceHzm9iJGWV9z/bAx39RRTNaEWDPrBMo0HbahETHbNttz8zPPN49NkAakTG9jxGvzhgbEXN/QrCizzPvYWOl0dfWM821Tk9LtQrf/Xw3oQhqacrAuhdqQQnVksNYUsNYUgDHCHtATQg86kLbQac//eyqEPhJGD8x8LZSlvZpvcNYUN2JbQ0MBa4VGNRSgrgBRjYp4EPFTz1XE8wXTYQ/iHio6/2+GesRC9xffVkds/011xIYhG30yhDdmaDCM2Lw2NBdhc75xLEyNiTb0NV5+Zs1HkEbExNRVlKcsz7h6IJahu1AlL/ZGCqvxpm8OJxAOlf4uzeXNbdnVM2ufyjQeRkpvieYj6mFvcFGrs9Ca93Uc9SlU2Dh/R6NwKI721Gn7YtTxMwozcRTFAcNjQI1xjzXv0ebBN++hk6ZV1rinnEssK7jMQdD6C4wYIYKwmClY0B2F7ij6Pxvxwn65eFZlUCszqMYCtOVRbVO7BXTSQp9y/JL/HkXLxk8nJw/kiv/PFT0P2eL/He3fxCPaNzDqXT8boL4ANd6sQ8faA0Yc6A+hh53TWWEa//9JG1IhSNmQsSCs0XbBN2binq+Lqs2jal1oyKOqPN97ksjCmuyU29O9vjGiux10t4N3RKF7bb/irbA0sTSq1cVanUe151HrcqjO8nAKFK+5/hDezirU7joYnGRImEZDgHZfOHeIESIIS4mkg/51An6d8O2JaBbVlYNqF2IeRFxUtYvqyENLHlXtoarn/01MZ5XvgRhw0EO2L8LL2r6xk7OKfxU6b/lGxaCDsma+05e5vAtuSbJ5iWci6kJdFhqLGQw1LqrG9f+u8OvwqBYXWsyMGn8kaT1go/ssdL/l/3/IwjvloYcsP6tNWBxENNa6As7FY1jr86iuAmqKy0j3OehDEfTRSNEzFoah08auip4vVsYcwzEVCO2LESIIS5lRB/3S6Z9xiVs75EFD1hfjhYqaIqV9PYaj/e+KnwmvR9hDhTW6UPSI5BQ6p/wQx3AIBm30oA1JqywV3EwxLSMg6jgrMjb6WASORU4bKhNGivaHNWjKYLXlUa2F4iePioBqc6Ft+tRub1Chu228ExZet4U+aeGdsNG9kn02rzgatcJD1WjfeEwUa240aKzGYi2OJg9lPKX0mEKfCPmfoyG8fRGsjBFCNg3a8wXJjjl/UCuaUbFi+fKg+KA53zYOu6nxCNKAmLqIoFocJmbZdfPCC6rlMRlT82HWEDHqbri2w+Exl4Npl8G8x2BBM5z3SLmaiKWIWRC3FZaC0YJmqGAxnPfwgHVxh41xxeZqh9aIRW/O40ROcSLrvzG/qi5MkzI0HtqIu5uaEPNYm5oQs26JqSGpCtCUZEo1IKrKCB2UaVKM7Rl1SpRZ6jugzgn5PJyaNG3GfM3li9MTV7DjlD92E8VPUEl+89owj3WAVso0apR5rEzMfUlrOID/AXQ+h67NQ30OanOo6izU5v1QT00BEgWUo7HqNdQXsC8yupdV0Ouge0K+5uREDN3nwJANBVWuGTGHcwi4T+gAjUjgfWUGPc+UGMurSboLbdRUKa8JY3TNrCFjnst6C9WWR3X4YRSrIwUr8mdWb2PIgaPV6KNVcCwOQ2FATUjyrRhQa9x3TAPZrH1kHsuoYcTM9lqeQReoMuXhQuE0YoQI80JBa15MevwilebnQ3n2plxqQ4rmkEVz2CJqw/60y56Uy1jAvXY6fsjpH7NF+XgVAJuqbF5dH+LyhE2No4gpTcxWJGxFLGAsE2G5o2A47H+YwoBD+8UH6/LQmIe6MWjKo1b40yqioTOP6vTXm/zY0RkFSQs9aqGTFqQs9Kjy/5/F16G4xfoS49oclP83q9ApC0ZAp5WfGTRe8NDoHzbgTjVvrhSrfYZ1MZRmzLa1rwWq1mBr33iwQYW0n8HVVByWosYDfXo/VQh/mIraqX/0OqNgxIa045ckSPoCY19k7MCgA8MhVFVsyvUFA8mOEZYrY672vRYuDBU0/XnNkazmSDbHoYzHy2MeKeM+M1jQHJrC4ohavlejKWxRF/I/VbYi62kyrmbM1RQ0JEKKWseiNmThadiXyrNrNM/etEuheD9uiVi0RWySrmZPqsALKZcXUlO72uscRVvY/3RFFBvjFhfGLNZGFaEKVAoUFhvKfximHTgRw8tMevBZGl2TQTXnUS1FIXBz3n/whrWf/RN1UU0BFXzPEO0BBfxqy8Xw2bgWQntAxk9fJlsUGHvKf/CPb16d/ihH+6GwsEaF9GlxctEYUhENMV3ildA5IO0LlVWV9o2Pue5Tv40+EcI7Hkb1RNAnwr4BgkIZ2TWVeBguCyQ7RljKuFpzMAvPZwrsSmtO5DQnc/7fkTO4tyZsuLIuzLbaEFsSDqmC5lS2wKmcJulq1sZsLqqNsDpmnx7BM8jFbM53C2Q9zWDeoyls4UwKbfVmXX7Sm+bJwQL7xlzGXM2Ypxlz/XvzUEEzVNDsSpc2GVKwIWZxaZXF1pjH1riiI3wGGgfh/MFT0BtC94bQL/pf+WXk/ewhqj2IFXxPQLXnD1AZd/2/YfzBKO3i3+J9Xln4hkJEo6rGU5knzSsaDibKAuIaFZ+LYaBn9KWocaNlkjRYu/gDdRbU6aymAr4wedBG9zvo4eLOWb7HBE+he2wYiEH29APOChqlVjhvECPkbGlsgXg0eDkoF0mZAdWg8VFMnYWpczA1IebyxYdpQWtOZD0OZ+FoxqU/5zGY9x/MfTmP3SmXlDn+9+RmFb7nImxTF7LoijmsqoqwKu6wuirMuuoQdlBfTcxjYe77FLHWKNA2RVPNNfDmepc3G99rrRkteHRnCpxMZzkxVuBQOs/u0Ry7R3OMFjQvpj1eTHv87+I6jvI/lrKwgfaoze80R3lTg38MJjB1Cmb/yzQmARqSnFF3JKC9sgdJkEbExJw/07UYpF0KiqObRt00epRp2zOng/Y18NwY6xv9s43ldVB7WkMS/zNVf2bQI01Iam3PFw07HqhCcTwq5WfsuMWPU6zH4rj+X1sXH/rK/zvOuOajoPyxq1z7dOaPhb88+POyFqS073kJexAHYq7//zEbshH/7/gVN6nvCsq1Q5PPvQ20zk5ToUzdWlAtJlPTYWJqQsxaSSZl9Y9MHV6Abm7ytZQ2ftPnEgnHCJUm5Wp+k8qzc9Slp2hk9Bc8BvK+AVIIeHmKWXBxTZhLEiFWxx3aIjZt8RCtUYdqW/negUk/OGX+WBchSikSIZtEyGZDVWl/vUKe4xmXF0Zy7BjOsWMow65kgYKmeKz8A7YnVWDPwSQPHoLfXRHiDU0hNsRtEgu+N8KyxrV8t13W9v8/FVkbUgQbbbM16saNrJzt16cZmTyomzwqlgTG/fms1l9g5MpaYmjtayZGXejJa07m4WQhz7GsZmfKY1fam1KwOU7Egq6ozcqYzYqwRb2jqC96NjZUOayN2zjmW8MSMDTOFqUUnTGHzpjDLS1xKOTJepqBnH8cXe3rU349nOORE2PsShZ49FSeR0/5b9EtIcUFMcW6mMXaqMXasGZtVFG/WMs6C4KwfBFPyHlEfSOMK7aDwilmuKQYotBa05fXvJyBg2n/7bvKVsRtP021L+dxMF3g4JjHoXSBgbxHsjCVN6N0e50xh1fWx1gZD9EQtmkIKRrCNh2xEC1RG8t8q3ECCjiYlrUZcilZdpYXsdG2WQJfm8fSfHtzzZTcAFePER5SZln2fI4o0G60t64Z3nyB5td9SR45MsyzQxm6My49eU1PXvOfI6XtNoYtLq4Jc1FVnIuqHV6RCLEiYkPOSNcLKAsfGFIoS0E2U3QDytCbmNfG5DTOIPGuaaya103QIF/mts19N/teFt4JKMlvLm/ON4+90Z4KSu8OSiEu2x/jXM1WH1WWohsQegs6vpPnm/PMsuXmtspeXALexmcoc+63Z2yvLBwSUJbAHB4iHPBiVRY6DChbcAZh49PbHpt+niBGyNmS8zQ/GcxzJONyJKs5OuZflB1Rm46woiNqMeZq9qddDmQ0+1MFxjxN2FKEFYQsRW/OYyQoPjINtoIVYZvWqE1b1KEt5nBRTZhX1kVoM9PZgnQZwhmhlOKy+iiX1fvx5NG8x/7RDHuTOV5O5Xk5ledgKs+Jot7mqf4MT/WfXn9TjcMNdQ43NIS4IGaJ8FUQhPlFipWdPxSA9+9KTjEnaGhPo4gP0Bm1WVvlELMUKVeTKvjFu+pDFmviNmuqw6yJ2zSHbWpCFtUhh/i4PgMqcuEIUBOy2FoXYWvdJBGd55J2PfYl87w0mmfXcJYXk3l2Jwu8MOp/Pnc0Q62jWBW1WBVRrCqGcjbEbVY6+nTmkCAIE3jj2cX4/xQHYj6n5DzNgYxmVybHrpRLTvup/vU21DqQ8eBEVnMyrzmZ1eS1JqQUIQXtEYu/uWCB65tYam4HpQKlCsQIOUvilmJbrUONreiKO6yM+vl2J7Iux8YKnMh4hC3FurjN+uoQF8QdEiGLnKfJuR45ralzLFbHbKJlIzQGZCxUIJdbOHPitsWW2ghbaiPQ6hsovVmXHw9k+dGpMX4+XGC4oNmZdNlp2LERBetiijVRRWdY0RXSdIYVqyPQ5EjRcGF50etZ7CmE2O+GSGvF5lCe68JTVxgteT7O0w8h62mO5eBo3vdo9+Q1vXlNXx76irWQ8meZCb32bFc8zxAj5CxRtY185ZriMOlm/DEo/BEk9DSNjqDY+UzpYVBWJr4sDBDU/5naL0vLDEjjnOVbfuDSs9SAlMfxZ/ZcaVNzYkyXaUrM6WLsuBl4SzO8ZX2BjOtxOJXjcCrPoZE0h9IFDiRz7E/mGfM0L6X9j0ldyOKCuMO6uIMHDOQ8+gseQ3mPupDFqpjje1didvHjEFcB16IZ2zaZfL6CzmXxunWL4um0pxjzNGlX42r/Mna1Pz/jaTJApnhtr4nZrA3rkqq2Y8rhWDG0FbUVcUtTZauJ4naBGgwT81ybehkT83cYlG5t/k6DNCzm+kFvoea5CvKAmv3PGqmipq5ipnXN35F5DzOvjbCRYjsFfQXNJ05Ad97XwlXb8FhG8/Ow4s+aHbTWKKXQWnPEC/FyxuNEVjPqavYO+8bB5zfE/OXMfbFtClqzL+XyUrLArj6PXck8vTmPvKcpaJeC1owWNEGmQsKxuCgR4aJEhBrHYijvMphzGcr7L5rtMYf2WIi2mEPUtsh7vkckZilUQzUqnA7Ywjwi4RhBEIKI2hYbE1E2JqLQdNoL5mrN0XSefck8R9J5jo0VOJrOc3SswLEx/6b3zLDHM8NTGU4uO6b4vi3ie9sUFAu3aXIeNIctVsX8cFBX1CZm+c/I8VtQyoVR17/hp1yNoxQR5Ve7DVnF6raeb0SMupqTWf8BcSLrcSp3dhokPzRp0RRSnMh69OSmfzx0RCw2xIshrKhNyDpd28VRCnvS/2sdxZqYJTe7RYYDJCz4kw5YV+UbDY/2a/7mhMdbmjSrIr4B8oNhzT+eylLQmrQLJ3KaxpDiNfX+GZ1KW5XzNK96up/sGVyKVbZiZdyhK+bQHrVZEbZpijo0hW06iplzVpB4f7FUXF7g7Jif/OQnfOpTn+LZZ5/l5MmTfOtb3+K2226bVRvyuxSERYKtFKviIVbFJ73VFd+mM67mYDrPvpEMB9MuIeVn4DREHGpDFn05j8PpAkdSeQ6PFTiScRnM+8bBySnuxC+Pufx8+Nzuj4V/g4/YCodiLS3l72fUUkRtRdTy67EcSBcYzGuOZjyOTnphTziKprAfxkwXDaKsB8ezHsezHk8Mnpk3JKJgQ9zi4rjFuphFg6OoVx4NjqI5BLW2VMhdaOocxV93np52lOJNjfDXxyFZdPrsz8CfHXL5064wb2t2yHjwoQNZNPCnK6f3toQtRXPYYiCvuaTa8TPVakJ0RW3ClsIpJgckHEV9qHxE6OVclmA+SaVSbNmyhXe/+9288Y1vPKs2xAgRhCVA1FZcVBPmotjUIZAJJrn4B/MeB1M5joy5WMp/4MdsRUgpTmZdDo/5hsuxrEdBazx9elDAKltRY/s36bitKGg/fp71fE9K1IKIrYhZ/vzWsEV7zKEjatEa8QcPDFuzywDqT2fZN+YykNd0RixWVkdKq9MWQwJDeY99KZe9ozn2pF26i0X4xmu65CeFfVygJ+eRcuH5lMfz5gBHRaot6IpAZ1iRsP02srjkPN94qrYV1XhU29DoKNrD0GFBexiqRKJ11nhaYymFq31B9r8NaOodaC3a4Z876fKaOsU7i1+ELXh1nc2/9BYCtRr/e2sdtY7CUqo85LxcmadwzMjISMnXkUiEiFnFFrj11lu59dZbz357iBFy1qjaRlR11dQzZ2tFBy1v6i7KcuxnOT+o3HYZRntzUYjN9m0zSPMRVDvBjPiacfvQzLFrVVZ7ISDub8bty+qYmMO9G7UogjQmZXVBpq9d0QA0NHpcxgzM9viWzDOvq1nqBoy2m+qgaaa+FI9lPXBlI1xpzp9Gy+RpzZF0nl0DSV4cyXJsrMBgzmUg5zGQcxnMeyQ92DUGu8Ym93G6YzP+vd++oyCk/Ldrp/h23RyxaQkpWiK+fsXP6vD3N2Yr6hxFbRjqQv6beJ2jSFj+A9nE05oxD9JakXY1IQVVjqJK+WGyaQnS8FgWWvvailTRy5QsaAbyHv0Fv07RUMGbyEoZx9W+xqeg/b7lNUUdBOS1Ju9Brvg362nu3ZBgU2LqMuwWfr0k27I4ki7wD7tP8Udr62hoS4BSvLDrGH+8thbVUDdhqGSHh6iNpknXNFE/7jUsq0lj02BMl84PuEeWLT+75IDJlaSVM1UW5blBKTUnj974ul1dXSXf33vvvXz84x+fS9emRYwQQRCWNZZSrK4Kszpcxa2tk14cig+ejOtxfKzAkeQYR9MF0m6xno+lCFm+3Tpa8EgV/DGI+nIuxzMux8cKjBR0scR/8THtagbzcHhs9qPp2lB8c2eizYL200CnI2Kd1vGME7cV1UVPVpWtyGk/lJV2IV00FsYNibxnljqcf05lZ96CUopUwePeXQNcWR/hjR1VKKU4lSngak2V4++h1oCC54eztMdCNEQkZHKuOHr0KInE6UEppvKCzBdihAiCcF4TtS3WVYdZe4bjUU7guowWPJIFTWHioa4ZKnj0ZD1OZXL0ZL2JDCBV9ISkXX/QyKG8y3BeM1jwvRAuMDBD8UIL34uS9zTjmt2phJdjnqb/LNJDo5YfhmsIWTSGLZrCFnUhi/ERCMb7b6vT499ZShG2fE+QLw72izGGbYuQgoiluKQmOBTyyb1DZD3NB9bVEi8O+KmUn5mydzTH7+B7mZ4ZHGNfMse719YTs62JDBqhyDyFYxKJRIkRci4RI+RsiVZDrNr/f5lrLuBHMevS5gFfBLUXOH+W4Zj53PZsKXMxB4QEgtY3Xe6B4ZwguX1A+McsVme2F9T/gJTisv7P+niY8yetH3SsZxsWnGlbZ7K9svVL90WXhbZmHtBNBQ0BMEW6dwJOD2JozjfP/Qz7l3M9hnJ5BrMuHn6YJVQM78RsiyrHImKddrXnPE264JIqeBNXlJ/OCmnXYyTvksy7JPMeEVsRty2qwg4x2yJkKWylcLSLoyDuWMQdC9tMr5+mr0H7AgSHO2DCgPjn/b3sG9P89yvX0pEoFveybJqBazvyfONQP9GqGtqqwvzbwSRXtdXzOxetRTn26TtT0H1mluGU8iEIZnkPnXztLGS9EEnRFQRBEGZL2LZojoZojk7yGsxgIIYtRTjsUDc5czRIH2U+WN2g6s7nFqUUP+sZ5ZM7j7MuEeWbB/s5MJLhcDLL6pooH7tsFX+yqYO6sMO3D/cRty1u6mzg7etbiDm2eEGmQs2xYqoMYCcIgiAsd8YNCA9NV1WY9YkoQ7kCWxuruLWrng11VTTHQoQti/df3M77L+mccn2hsiSTSfbv3z8xffDgQXbs2EFDQwMrV648ozbECBEEQRAWlHED4tqWBI/dfPEUmTulXhtP6wnHjm3NLQNkWbPA4ZhnnnmG66+/fmJ6+/btANxxxx189atfPaM2xAg5WyJRiIwPTmT+IIJigPOs6QikdP3AH3Dg9ibNn2vf5pqyW+aynq1iPqg9c/YsNSN2kOZilhoVM6U4UNMRdC2a8+eg/wnalukmLtPLBDDLdOyy3gbqeUxmd20EalZmSKcGZh4OHsr7X1YWPkCTYxJ4bczQlqmpCNDbzNRewfMmjA6F8ot+UnqfssvKBAS1bx6LsgWm7U9Qf6dpcPrlc7McXmAuLHDF1N/+7d+e4p44O8QIEQRBECqGY1kyKOd5jBghgiAIgrAcUGqO4RgRpgqCIAiCcDYscDhmPhAj5CxRThgVNLLixMIBZdMXWBMSGFsP7M/kdWfeVLDkYLYrBMXlZ54dyGx1BkHrz7FOh55znY/ZakJmYp5vUE5Ae0HX5Ww1GmXrm8c24Fqbc3/meC5m/VsL+p0HdGdG5lqbaA4aizMi4J4XsP05C18nrX/Gz4nzFDFChEWL53mceLmP3c8eZmQwxZWvvYTOdSsq3S1BEITFiRQrE4TTeJ6HV9C4BZfsWI6Th/o5caiXEwf76D0+SCaVI5POMZbKks/mccIOobBDKGwzlsqy9zdHSA6PTbT3xXu+yfqtXVz/psvZcu16hvuT9J0Yovf4IIW8y7pNnVxwaRdtqxuxROgmCML5hjXHYmVzWfcsESPkbLFC0w8PPefzONcQxfSux1w2T9+JIfpODJHL5vFcjed6uAWXkYEUw/1JhvqSjA6m0BosS2HZFpatsB0b27awHQvLtkBrXFejPU0+l6f/5DB9J4fpOznEUO8onjvblMhywtEQF2zpIhIN8dxP97Fvx1H27Tg64zrxRJS1l3TQtb6VrvXNdK1vpW5FDWPJLOnRMdLJLKGwzcoNrXRe0EI4OsPYFrNOPzNd+AFplwHtq0AX/SznzzYUN3n+XMN4s10+aP3ZpBdPtfwshwAwUxFNl31g6Gy2/SubPdvjF3Q+AsJVs2kr4FzMZ3jjjPoTGH4pW2G2PTrz9q3gsXPOZ8QIWcYkh9M8/7MDPPef+3jxFwfoPtzPUO9oxfrT0FpL+5om2tasoKWrgapEjGg8QrQqTCjs4BZcctkC+WwB27G44NIu1m7qxAn5D/LB3hF++u+/4YlHn+HInm4aWmtZ0VHPivY6AA48f4wDLxwjPZLhhacP8MLTBwL7ZFmKtjUrqG2sIj2aITk8RmpkjKpEjE2vWscrXr2RV/72hTR31jM6mGaoL8lIf5JwNETnBc1UjY91IQiCUGmWYDhG6blWGjnPGBkZoba2luHD+0gkaqZeaA5GdSHvcnh3N/ufP0o2nScUcXBCNk7IYmQg5YcfTgzRf3KYcDREQ0uChpYEdStqSI9mfC/HyWFOHR3g0K4TeFMUhIrEQjS11xOJhia8GrZjUV0Xp66phrqmamoaqrEs5XtJXO+0x8R1cfMurquxLIUqekps26KhJUFTRz1NbXU0tNQSijhYlu9BccI24ci5fyMo5Aoc2XOSgy+d4Oi+Ho7t7+Ho3h5Gh9PEq6PEqiPEa6JkUlmO7OkuCffMhGWpKY9lY1stKze0svqidtZv6WLD1i4617dgF0cCDdR9zlmsKJ6QSQ0GNRDQH/GEnHVb4gmZdtbIyCi1q9YzPDx8zkamHX8uDf7suySqq86+nWSK+qt/95z21UQ8IfPIWCrL3h1H2PXMIfb8+hCOY3PJq9ZyybZ1rL2kHa3h0K4T7Pn1YfbuOEJqJINSauL6PXGwj5dfPE4+O38V9jovaGbLtRu49Jr1rNzYSnNnPTX1Veeu7HGFyyk7IZu1mzpZu6kzcFmtNQM9Ixzec5LU0BhVdTGqEjGqaqL0dw/z3FN7+fWPd7PrmUMToaXq2hiJxmoyqSwDPSP0nxym/+Qwv3lyz0S70aoway/uYM3F7ay5pJ21l3TQ1FZHKOIQjoYIR0JEYiEpPS2cEzLpHKnRDNmxPIW8S01dnPoV5S9Mnuedtmu0BlV8qRA91dJFPCHLnwlPyNEDvPsVf43WuqiZsGbUQcSqI7gFj1wmeOTKqtoY6y/toqa+inyuQD7nUsgXqK6NsaKjgab2Opra68iO5Rk8NcJAzzCDp0apqonS2F5HY6s/f/2WLpra64N36nx6GJ7F5T6WzJBOZqltrJ4IDQEkh9Ic3d/NkT3dHHj+KPt2HGH/zmNkUtnANpVSxGoixKujxGuiNLTU0rF2BW1rmmhfvYL6lgQ1dXGq6+IkGqpwQvaEV0p7mkismPY32zTTIGbrXDinzDE9e7aHYq4puIEdOvecPNzP//r0Yzzzo90U8gWckMP6LZ28+Y9vYMu16wMGfpvpZM92X8512YHZbW62K2jg5KE+RgdTvic35H9sx8Z2LGzHxrItTh0b8MPAzx/j4AvH0WgaWmppaE7QuqqRN931Gt8T0rVuYTwhT/+fuXtCrnrdgnpCFr0R8uCDD/KpT32K7u5utmzZwuc//3muvPLKwPUeeeQRfv/3f5//8l/+C9/+9rcnvtdac++99/LQQw8xNDTENddcwxe/+EXWr19/Rv0ZP9lDR/bz5lUfKZu/oqOOi65Yy4WXryGXyfPiLw7w0i9eJjXiu/2rEjE2vnIVG165isbWWrT2hZ2ep2lqq2P91pW0rWky3kbO8ZNAjJC5NFgy5boex/b38PLzx3j5xeMceukEL794nJGBFLmx3JQhnbOha0ML17/pCq5/0yvpXNc8aY4YIWe7+nIwQgZ6Rtj33FHaVjfRtrqRwd5RHvx/v8nJw/185rt/QnVtfGK5Z360i55jA7gFD8tSnDjYz4atXbzxv14/hbGy/IwQrTXp0QypkQypEV8LdvDF4zz3n/t47qf75qyf61jXzFef/fjCGiE//79zN0JedauEY8b5xje+wfbt2/nSl77Etm3beOCBB7j55pvZs2cPzc3N06536NAhPvShD3HdddeVzfvbv/1bPve5z/Hwww+zZs0a/vIv/5Kbb76Zl156iWg0Oqv+feWZe329RMHDLXjUraihqb2u7AfmuS5H9nTjhGza167AChqoSliy2LbFqo1trNrYxvVvvqJsvpsvkB3Lk0lnSSezpEczpEfG6D0+yImDfZw42MuJg70M9yV9kexwekrD5ejeHv7n/d/lf97/XdZv7SLRUMXoYJqRgRSp4TFq6uM0tfui3ca2Wl8EXBX2hcDxMKGwPaHlsUM2ifoqapuqqW2oJhoPkxweo+/EIL0nhhjuT5JoqKa5o44VnfVUJWK4BY/UyBjJ4TGSw2lSRUFvcniMTDpHKOwQiYUIR0NEY2E/zFUbo7o2RiQW8ve9ePPPZfOEwn6IKhxxyOUKHNnTzaFd3RzefZLRoTSdFzSzamMrqza20rqqcULLZNkW4UiImvo4odCivp0tCA0tCbbddMnEdHNHPTe8+TK++Bffor97hOraOEf29vDwJ/+DvpPDJBqq2LfjKAM9I9StqKbzgunvq4udQt5loGeE3uODnDo2QO/xIZLDabTnj8CrPU1yJE33kQFOHR3g1LHBGT3ToYhD/YoEhYKvgyvkXdxiJqGbd/E8TW1jNesu7WTdpk7WbuogFAkx0D3MwKkR4tWRads+Z0g4Zn7Ztm0bV1xxBV/4whcAP4bZ1dXFBz7wAT7ykXIvBIDruvzWb/0W7373u3nqqacYGhqa8IRorWlvb+dP//RP+dCHPgTA8PAwLS0tfPWrX+Vtb3tbWXvZbJZs9rR7fWRkhK6uLoaPHphBmDpHAV95g7NcfrbNiydkDg2e0+17nkdyeAzP9SaMhkLe5Rffe4EnHn2GX/9497ykQk/GdizcwvRthsIO+YUcGfQMiVVHqG2oJp6IFt3nfs2ZcDREor6K6roYNXVV1DfX0La6ifZiltZEiM04N5mxPCcO9gLQvmYF0dhshdWVu7WOJbMM9Y3S3z3Mt/7xSSKxMB9+8B2MpbL8jz9/lBd//jL//Rv/lbbVTTz3n/v4woe/ydWvu5Q7/+J3p2nx3HpCtNaMDqUZ7kti2ZYf+rAtPE8zlsoylswwlsoyMpDi1LFBTh0bpPf4AP3dI4wMJBnuT014m2eLE7J9IzkRpWVlI1uuXc+Wazew8bLVhMLTG7ae552RfmZBPSG/+N7cPSHbbhZPCEAul+PZZ5/lnnvumfjOsixuvPFGnn766WnX+6u/+iuam5t5z3vew1NPPVUy7+DBg3R3d3PjjTdOfFdbW8u2bdt4+umnpzRC7r//fu67777yDVnWxPDTgcz3M35RGQ1zU80v+I16vo/dbI2aWW7eUhaJhnJj96Y/uJqb/uBqBntHeOaHLwFQUx+npj5OVSJGcihN7/HBYrbUEOmRDJl0jkw6y1gq67/NFT14hXyhmH48Sj5bmDBAahuraWqvo7aphqG+UfqODzIykCoxQGLVEaoSMarr/O1W1/pp1/mc7/HJZfyCdKmRMVJFr4lb8AhHQ1QlYsRrokRiIfLZAtlMnlwmj2Upuja0surCNlZf2EaioZqj+3s4vPskR/acpPfYIK53OmMrny2gtWYsmWUsGazHKTm+tkVja4Lq2rj/qYuTSWc5duAUvccGS5Zt7mygc30zDc0JQpEQoYhDKGSjLOX3xfPwPE044hCv8QXO8aJOa9WGVpraayceWoO9o+zfeZSj+3r8t3Gl/GwzpWhb3cTFV66hofnsHwJP/cdOPn3X1whFHFZuaOXuv30L2A77nj/IL3+4iw9/8Z20rW0BYNVFHXRtaGHg1AhYFq7rYTvl97ZDu05wZG+3b9yFLJywn/2WHs2STvrXVzadI58vUMi5RT1bgdxYnlw2XxTK+teOKo5xkk3n6DnST/fRftIjmbPe33Fsx2JFez0rOutp7mygpqFqIotPoYjXRGjuaqSlq5GWrgYaWmsJR89AJD7Fi6VlW9PPn8xCCn3nOiJxBUTJi9YI6evrw3VdWlpaSr5vaWlh9+7dU67z05/+lH/6p39ix44dU87v7u6eaMNsc3yeyT333MP27dsnpsc9IYKwGKhfkeC1v/+qSd+cvdGntSaTypIcHqO2sXrKIm6ZdI7hvtEJ42Oqh9VM29baNxxmXm92uK5HatgPRY0MpEiPZnALri/ozhXIpHOMDqVJDvnz+7uHOXnQr9yby+TpPT5E7/GhKduuqYujtSY5PMapYwOcOjZw1v2MxsO0r10xkWofRNvqJi6+Yg1aa3qLlYH7u4e59Jr1fPLRu2dc94Y3X8G1v7uV0cEU3/wfP+KTf/RVPvWdD9JzdADtaV7x6o0U8i5OyKaQc8mkcrStagKmf54+9e+/4X9+8j9mu9uzIp6IgmbCSAaIVUWI1USJV0eorouzosM3MJo7G2hsq6W2qYbaxipqG6upqo2fTo+fkcX0Ijd/+NmWZ79vlcjYW7RGyGwZHR3l9ttv56GHHqKpqWne2o1EIkQiFYjtCcICo5QiVh0lVj29NioaDxNd2TinbcynAQK+DifRUE2ioXpW63muy0D3CP09wySH0r6+ZShNKOzQeUEznRc0k2ioRmvNcH+SY/tPcWxfD6NDKXLZ02/7WuuJysJKKfLZPKnRzETxu1NHBzh+4BSZdI6XXzg+cRw6L2hm9cXtVNVE8Yq6hUK+wOFdfp2bk4f6OHmor6zfM4UIxvEzOSziNVHuuOd32LfjCN/5/56koaWWcMTBsiy08h/yw/1J9j9/lLf+PzcBTBtiWNHZwKar1lHIuxSKBp7reRMZXtF4hEg8PDH0Qijs4IxrgyIhwlEHJ+Sg1GkHohOyae5qoHWV752IxqcZ7G1ReX+F+WTRGiFNTU3Ytk1PT0/J9z09PbS2tpYtf+DAAQ4dOsTrX//6ie88z/+ROY7Dnj17Jtbr6emhra2tpM2tW7eeg70QBGGxYlnWRLr7TCilikX8atj0qnVntS234HLyUB/H9vVQXRtj3eZOYjXTV9tNDY/x0q9eZu9vDhOOhGhqr/NFxu11RGMzj8qazxUIhZ2Jt9rjB3oZ6BmZqBHUe3yQYwdO0bl2BaeODvDI33+fVRe2seWamTMEb3nHVdzyjqv8iTnr3IRzglJzFKaKJ2SCcDjMZZddxuOPP85tt90G+EbF448/zt13l7siL7zwQp5//vmS7z760Y8yOjrKZz/7Wbq6ugiFQrS2tvL4449PGB0jIyP84he/4P3vf//sOliMaZ7hwgHzg3QFS+gHXhY7DVzhXPVkYSjr/jxrXua7Sum5PN6BKa2zj7ufU2Z7KObw4LXDNp3r2+hc3zb9QpPaq6qv5oqbLuWKmy6dfvvlHWR0MMXDf/NdrrjxYiKxCP3dQ/zoX39FvCbGDW95FZl0lpUb27j/vV9h89UX0H24n/Rohrs//ftnrnGDc69zm28jZ77bn83yC/lgn9VzaZr1F5hFa4QAbN++nTvuuIPLL7+cK6+8kgceeIBUKsWdd94JwDvf+U46Ojq4//77iUajbNq0qWT9uro6gJLvP/jBD/KJT3yC9evXT6Totre3Txg6giAIS5VQJEQ6meEf/uJRRofSNLQkeMWrL+RPv3A7iYYqEg1V/MVX3st3Hvoxp44NsnZTB695yzY61jUHFDIThHPDojZC3vrWt9Lb28vHPvYxuru72bp1K4899tiEsPTIkSOzLjH84Q9/mFQqxR/+4R8yNDTEtddey2OPPTbrGiGCIAiLjWg8zIe/eEdxamqDYvVF7fzJZ95e8p0YIMuFOdYJQeqELHomyrafOHz2edRzGUTsbNoXzp75dgtX/Oc2z/UeFpRzHbas9LmZP7TWJQPumS9rrutNjBcznhpcWeYaxqx0/6dnZGSE2vZVC1InZOg3T5KomZ1Au6Sd0SR1r3i11AkRBEEQzp6gVM0zS2MVlhxLsE6IXImCIAiCIFQE8YQIgiAIwnJAsmPOI+Z6ss225jJfOHfM+2if5/hcBmpY5jFV8Zyn0M6y70HrB/bXWH6hU4aFScxzSm4lWdAU3aU3gJ2EYwRBEARBqAjiCREEQRCE5YCEYwRBEARBqAyKuYWyxAgRBGEunMvy0/O57nywkPs6H+sLglCGGCGCIAiCsByQcIwgCIIgCBVhCRohkh0jCIIgCEJFEE+IIAiCICwLRJgqCIIgCEIlWILhGDFCBEEQBGE5sPQcIaIJEQRBEAShMognRBAEQRCWBUvPFSJGiCAIgiAsB5agJkTCMYIgCIIgVATxhAiCIAjCckAxR0/IvPXkjBEjRBAEQRCWBUtPEyLhGEEQBEEQKoJ4QgRBEARhObAEhalihAiCIAjCskDCMYIgCIIgCGeEeEIEQRAEYTkg4RhBEARBECqCGCGCIAiCIFQG0YQIgiAIgiCcEeIJEQRBEIRlgFIKNYeQylzWPVvECBEEQRCE5cAS1IRIOEYQBEEQhIognhBBEARBWBYsPWGqGCGCIAiCsCyYYzhGsmMEQRAEQThfEE+IIAiCICwHlqAwVYwQQRAEQVgWLD1NiIRjBEEQBEGoCOIJEQRBEITlgIRjBEEQBEGoCEsvGiNGiCAIgiAsD5aeFSKaEEEQBEEQKoJ4QgRBEARhOSCaEEEQBEEQKsISNEIkHCMIgiAIQkUQT4ggCIIgLAuWnjBVjBBBEARBWA4o5hiOmbeenDESjhEEQRAEoSKIESIIgiAIy4FxYepcPmfBgw8+yOrVq4lGo2zbto1f/vKXZ7yuGCGCIAiCsCxQ8/CZHd/4xjfYvn079957L7/+9a/ZsmULN998M6dOnTqj9cUIEQRBEAThrPjMZz7D+973Pu68804uvvhivvSlLxGPx/nyl798RuuLMHWWaK0BGBkdrXBPBEEQhMXO+LNi/NlxTreVTM5JmDqSTPp/R0ZKvo9EIkQikbLlc7kczz77LPfcc8/Ed5ZlceONN/L000+f0TbFCJkl/f39AHRtuKTCPREEQRCWCv39/dTW1p6TtsPhMK2trfPyXKqurqarq6vku3vvvZePf/zjZcv29fXhui4tLS0l37e0tLB79+4z2p4YIbOkoaEBgCNHjpyzC0o4M0ZGRujq6uLo0aMkEolKd+e8Rs7F4kLOx+JheHiYlStXTjw7zgXRaJSDBw+Sy+Xm3JbWGmV4U6bygswXYoTMEsvyZTS1tbXy414kJBIJOReLBDkXiws5H4uH8WfHuSIajRKNRs/pNkyampqwbZuenp6S73t6emhtbT2jNkSYKgiCIAjCrAmHw1x22WU8/vjjE995nsfjjz/OVVdddUZtiCdEEARBEISzYvv27dxxxx1cfvnlXHnllTzwwAOkUinuvPPOM1pfjJBZEolEuPfee89pjEw4M+RcLB7kXCwu5HwsHpb7uXjrW99Kb28vH/vYx+ju7mbr1q089thjZWLV6VB6IfKGBEEQBEEQDEQTIgiCIAhCRRAjRBAEQRCEiiBGiCAIgiAIFUGMEEEQBEEQKoIYIbNkLkMWC4IgCMuP+++/nyuuuIKamhqam5u57bbb2LNnT6W7tSQQI2QWzHXIYmF+2L17N42Njaxbt46tW7dSXV3NtddeW+luCUJFGBoa4vLLL2fr1q1s2rSJhx56qNJdOu948sknueuuu/j5z3/OD37wA/L5PDfddBOpVKrSXVv8aOGMufLKK/Vdd901Me26rm5vb9f3339/BXt1fnLrrbfqnTt3aq213rBhg04mkxXu0fnJhRdeqIEpP5///Ocr3b3zgkKhoFOplNZa62QyqVevXq37+voq3Kvzm1OnTmlAP/nkk1pr+Z3MhHhCzpDxIYtvvPHGie9mO2SxMH/s2bOHjRs3kk6ncV2XqqqqSnfpvOTRRx8F4PHHH+fkyZMcOnQIy7L413/9V973vvdVuHfnB7ZtE4/HAchms2it0VqLx7CCDA8PA6cHPJXfyfSIEXKGzDRkcXd3d4V6dX4yOjpKJBIhHA7z4osvctFFF1W6S+ctPT09OI7DNddcQ2trK319fXiex3XXXbdsK0QuRoaGhtiyZQudnZ382Z/9GU1NTVx44YVs27aNb3/72+zYsYOOjg6+973vVbqryx7P8/jgBz/INddcw6ZNmwD5ncyEGCHCkuOll17i4osvBmDXrl1s2LChwj06f3n++efZsGHDxI30ueeeo7m5+YxLNgvzQ11dHc899xwHDx7k61//+sSopuIxXHjuuusuXnjhBR555JGJ7+R3Mj1ihJwh8zFksTA/vPjii1xyySUAVFVV8f3vf5/+/v4K9+r8ZOfOnWzevHli+rnnniuZFhaWlpYWtmzZwlNPPSUewwpw9913893vfpcnnniCzs7Oie/ldzI9YoScIfMxZLEwP7z73e/mvvvuA+BNb3oTzz//PI2NjRXu1fnJzp07ufTSSyemn3vuuZJp4dzT09PD6Ogo4GsRfvKTn7Bx40bxGC4gWmvuvvtuvvWtb/GjH/2INWvWlMyX38n0iBEyC7Zv385DDz3Eww8/zK5du3j/+98/qyGLBWE54XkeL774YsnN9MCBA6xevbpynToPOXz4MNdddx1btmzhuuuu4wMf+ACbN28Wj+ECctddd/G1r32Nr3/969TU1NDd3U13dzdjY2PyOwlARtGdJV/4whf41Kc+NTFk8ec+9zm2bdtW6W6dVyilZpwvl/TCsG/fPjZs2MDhw4dZuXIlAK973et4+umn+e53v8s111xT4R4KwsIw3T3pK1/5Ctdcc438TmZAjBBhyXH06FFuv/12Tp06heM4/OVf/iW/93u/V+luCYIgCLNEjBBhyXHy5El6enrYunUr3d3dXHbZZezdu1eU/8J5SZBncDrk1i8sBkQTIiw52tra2Lp1KwCtra00NTUxMDBQ2U4JQoUYL06mtebIkSO8+tWv5qKLLmLz5s38y7/8S8n8yR9BWAw4le6AIMyFZ599Ftd16erqqnRXBKHiOI7DAw88UOIlfN3rXideQmHRIkaIsGQZGBjgne98pwzYJQhF2traaGtrA0q9hGKECIsVCccIS5JsNsttt93GRz7yEa6++upKd0cQFh3iJRSWAuIJEZYcWmve9a53ccMNN3D77bdXujuCsOgQL6GwVJDsGGHJ8dOf/pTf+q3fKin+88///M9SBlkQ8L2Er33ta3nf+94nRrqw6BEjRBAEYZmgtebtb387Gzdu5OMf/3iluyMIgYgRIgiCsEwQL6Gw1BAjRBAEQRCEiiDZMYIgCIIgVAQxQgRBEARBqAhihAiCIAiCUBHECBEEQRAEoSKIESIIgiAIQkUQI0QQBEEQhIogRoggCIIgCBVBjBBBEARBECqCGCGCIAiCIFQEMUIEQRAEQagIYoQIgnBGdHd38/a3v53W1lbC4TDt7e18+tOfrnS3BEFYwjiV7oAgCEuDP/qjPyKfz/PDH/6Q+vp6enp6GBoaqnS3BEFYwogRIgjCGZHNZjl8+DBPP/00N954I6985Ssr3SVBEJY4YoQIghBIoVDglltu4frrr6e2tpYvfOEL7N27l69//etUV1dXunuCICxRRBMiCEIg/+2//Te6urrYsmULq1ev5tOf/jQ7d+7ki1/84sQyX/3qV7nsssvYunUrl156KQ8//DAAn/nMZ+jo6GDLli2sX7+e73//+5XaDUEQFhlihAiCMCM7duzga1/7Gm94wxtKvq+treXkyZMA/MM//ANf/vKX+d73vseOHTt44okn0FoD8MILL/B3f/d3PPfcc3zqU5/i4x//+ELvgiAIixQxQgRBmJFHH32UDRs2EAqFJr5LpVLs3buXSy65hMHBQT760Y/yyCOP0NTUBEBjYyPvete7AN8IufDCCwHo6OjAdd0F3wdBEBYnYoQIgjAjg4ODpFKpku/+8R//EYA3vvGNfOtb3+L666+nvb29bF2tNbt372bjxo24rssXv/hFXve61y1IvwVBWPyIESIIwoxs27aNXbt28fd///fs27ePz3/+89xzzz08+OCD1NfX88ILL7B169Yp1z148CDZbJarrrqKq666itbWVj7ykY8s7A4IgrBokewYQRBm5B3veAdHjhzhc5/7HPfeey+bN2/m3/7t3yY8GlVVVXieN+W6L7zwAq9//ev55je/uZBdFgRhiaD0uHpMEAThLPjZz37Ge9/7Xp566ikaGxsZGRnhO9/5Du94xzv4m7/5G/L5PPfee2+luykIwiJEwjGCIMyJq6++mu3bt3P99dezefNmrr32WvL5POB7QjZv3lzhHgqCsFgRT4ggCIIgCBVBPCGCIAiCIFQEMUIEQRAEQagIYoQIgiAIglARxAgRBEEQBKEiiBEiCIIgCEJFECNEEARBEISKIEaIIAiCIAgVQYwQQRAEQRAqghghgiAIgiBUBDFCBEEQBEGoCGKECIIgCIJQEf5/JioF2lE7UW4AAAAASUVORK5CYII="
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 20
},
{
"cell_type": "markdown",
"id": "685982fc4c6a178f",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"source": [
"## Subsample selections\n",
"\n",
"Another quite reasonable thing to do is to examine the marginals restricted to a subpopulation of samples that fulfill some criteria.\n",
"This is as simple as making cuts on the samples themselves.\n",
"For example, one might want to look at the mass orderings separately, which shows the relative probability between them.\n",
"\n",
"It's worth bearing in mind here that if any variable, or its prior, has had a transformation applied to it, then the relevant Jacobian(s)\n",
"must also be applied when using the samples after a cut. This is particularly important if, as in this example, \n",
"one desires to compute the fraction of samples that lie on either side of a cut.\n",
"(So, for example, if one wishes to reweight the prior on some variable, the appropriate Jacobian must be applied\n",
" to each sample as a weight when summing them.) \n"
]
},
{
"cell_type": "code",
"id": "8daa091c6f5adbdf",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:38:53.110967Z",
"start_time": "2024-05-27T13:38:50.025905Z"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"\n",
"fig, axs = plt.subplots(nrows=1, ncols=2, sharey=True, figsize=(12, 6))\n",
"\n",
"norm_factor = 1./len(vals[\"Deltam2_32\"])\n",
"vals[\"dm32_NO\"] = vals[\"Deltam2_32\"][vals[\"Deltam2_32\"] > 0]\n",
"vals[\"dm32_IO\"] = vals[\"Deltam2_32\"][vals[\"Deltam2_32\"] < 0]\n",
"ignored = axs[0].hist(vals[\"dm32_NO\"], weights=norm_factor * np.ones_like(vals[\"dm32_NO\"]), bins=250, range=(0.0021, 0.0027))\n",
"axs[0].set_ylabel(\"Probability density\")\n",
"axs[0].set_title(\"Normal ordering\")\n",
"\n",
"ignored = axs[1].hist(vals[\"dm32_IO\"], weights=norm_factor * np.ones_like(vals[\"dm32_IO\"]), bins=250, range=(-0.0027, -0.0021))\n",
"axs[1].set_title(\"Inverted ordering\")\n",
"\n",
"for iord, ord in enumerate((\"NO\", \"IO\")):\n",
" frac = norm_factor * len(vals[f\"dm32_{ord}\"])\n",
" axs[iord].annotate(f\"Fraction of posterior in {ord:s}: {frac:.2f}\",\n",
" xy=(0.95, 0.95), xycoords=\"axes fraction\", ha=\"right\")\n",
"\n",
"fig.supxlabel(r\"$\\Delta m_{32}^2$ (GeV/$c^2$)\")\n",
"\n",
"fig.subplots_adjust(wspace=0, hspace=0)"
],
"outputs": [
{
"data": {
"text/plain": [
""
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 21
},
{
"cell_type": "markdown",
"id": "7754f2dabe3006bd",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"source": [
"## Changes in prior\n",
"\n",
"Like with variable transformations, one can reshape the posterior by altering the prior in some variable(s).\n",
"This can be done with MCMC so long as the desired new prior overlaps meaningfully with the posterior sampled using the previous prior (otherwise there will be an insufficient number of MCMC samples to accurately produce the new posterior).\n",
"One of the most common uses of this technique with our MCMC chains is to impose a constraint on $\\theta_{13}$ that comes from reactor antielectron neutrino appearance experiments.\n",
"This satisfies the criteria just mentioned because we sample uniformly in $\\theta_{13}$, and the posterior in $\\theta_{13}$ from that sampling is quite broad. \n",
"\n",
"To show everything working altogether, below we recreate our marginals for the Jarlskog invariant in normal and inverted mass orderings, respectively, with the 2019 PDG reactor constraint imposed as a change in prior for $\\theta_{13}$.\n",
"The new prior is a Gaussian prior in $\\sin^2 (2 \\theta_{13})$ with mean 0.085 and standard deviation 0.003.\n",
"We also use a prior uniform in $\\sin^2(\\theta_{23})$, instead of uniform in $\\theta_{23}$, as in our published plots, though this is an essentially negligible change to the posterior.\n"
]
},
{
"cell_type": "code",
"id": "8f2a1363ca152417",
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"ExecuteTime": {
"end_time": "2024-05-27T13:39:50.305480Z",
"start_time": "2024-05-27T13:38:53.111968Z"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import scipy.stats\n",
"\n",
"def J(th12, th13, th23, dcp):\n",
" return np.sin(th12) * np.cos(th12) * np.sin(th13) * np.cos(th13)**2 * np.sin(th23) * np.cos(th23) * np.sin(dcp)\n",
"\n",
"# we'll reuse these a few times, no sense regenerating every time\n",
"reac_constraint = scipy.stats.norm(loc=0.085, scale=0.003)\n",
"quantile_levels = np.array(list(reversed(QUANTILE_LEVELS.keys())))\n",
"quantile_labels = list(reversed(QUANTILE_LEVELS.values()))\n",
"\n",
"for ordering in (\"NO\", \"IO\"):\n",
" fig, axs = plt.subplots(nrows=2, ncols=1, sharex=True)\n",
"\n",
" sel = vals[\"Deltam2_32\"] > 0 if ordering == \"NO\" else vals[\"Deltam2_32\"] < 0\n",
" \n",
" jacobian = 2 * np.sin(vals[\"Theta23\"][sel]) * np.cos(vals[\"Theta23\"][sel]) # this step not strictly necessary if we were content with prior uniform in th23, but published result does it this way\n",
" \n",
" # the reactor constraint is a Gaussian prior on sin^2 (2 theta_13), so we need to apply the transformation in two stages:\n",
" jacobian *= 4 * np.sin(vals[\"Theta13\"][sel]) * np.cos(vals[\"Theta13\"][sel]) # first, to sin^2 (theta_13)\n",
" jacobian *= reac_constraint.pdf(vals[\"ss2th13\"][sel]) # and then, the Gaussian constraint on that\n",
" jacobian = np.abs(jacobian) # it's actually the absolute value of the Jacobian determinant...\n",
" \n",
" jacobian_sindcp = jacobian * np.abs(np.cos(vals[\"DeltaCP\"][sel]))\n",
" \n",
" for ijac, jac in enumerate((jacobian_sindcp, jacobian)): \n",
" binc, edges, curves = axs[ijac].hist(J(th12=vals[\"Theta12\"][sel], th13=vals[\"Theta13\"][sel], th23=vals[\"Theta23\"][sel], dcp=vals[\"DeltaCP\"][sel]), \n",
" weights=jac, bins=250, density=True, histtype=\"step\")\n",
" threshs = list(quantile_thresholds(binc, quantile_levels))\n",
" for tidx, thresh in enumerate(threshs):\n",
" axs[ijac].fill_between(edges[:-1], binc, where=binc > thresh, step=\"post\", color=curves[-1].get_edgecolor(), alpha=0.05 + 0.4*tidx, label=quantile_labels[tidx])\n",
" \n",
" axs[1].invert_yaxis()\n",
" for ax in axs:\n",
" ax.axvline(0, linestyle=\":\", color=\"black\")\n",
" \n",
" axs[0].annotate(r\"Prior uniform in $\\sin \\delta$\", xy=(0.99, 0.9), xycoords=\"axes fraction\", ha=\"right\")\n",
" axs[1].annotate(r\"Prior uniform in $\\delta$\", xy=(0.99, 0.05), xycoords=\"axes fraction\", ha=\"right\")\n",
" \n",
" axs[0].legend(loc=\"upper left\")\n",
" \n",
" #fig.add_subplot(111, frameon=False)\n",
" fig.supxlabel(r\"$J = \\sin(\\theta_{12})~\\cos(\\theta_{12})~\\sin(\\theta_{13})~\\cos^2(\\theta_{13})~\\sin(\\theta_{23})~\\cos(\\theta_{23})~\\sin(\\delta_{CP})$\")\n",
" fig.supylabel(\"Posterior density\")\n",
" fig.suptitle( (\"Normal\" if ordering == \"NO\" else \"Inverted\") + \" ordering\" )\n",
"\n",
" fig.subplots_adjust(hspace=0)\n",
" fig.show()"
],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/tmp/ipykernel_844351/2796244920.py:49: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
" fig.show()\n"
]
},
{
"data": {
"text/plain": [
""
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
""
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data"
}
],
"execution_count": 22
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}