{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# How to fit tritium measurements" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data processing\n", "\n", "Let's first start with the measurement data. Here we have 7 samples (`LIBRASample`).\n", "\n", "Each `LIBRASample` has 4 measurements `LSCSample` (because the bubbler has 4 vials) and a time as a string.\n", "\n", "Each `LSCSample` is defined by an activity and a name/label.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from libra_toolbox.tritium import ureg\n", "from libra_toolbox.tritium.lsc_measurements import LSCSample, LIBRASample, GasStream\n", "\n", "\n", "sample_1 = LIBRASample(\n", " [\n", " LSCSample(0.396 * ureg.Bq, \"1-1-1\"),\n", " LSCSample(0.375 * ureg.Bq, \"1-1-2\"),\n", " LSCSample(4.575 * ureg.Bq, \"1-1-3\"),\n", " LSCSample(0.448 * ureg.Bq, \"1-1-4\"),\n", " ],\n", " time=\"7/29/2024 09:44 PM\",\n", ")\n", "\n", "sample_2 = LIBRASample(\n", " [\n", " LSCSample(0.386 * ureg.Bq, \"1-2-1\"),\n", " LSCSample(0.417 * ureg.Bq, \"1-2-2\"),\n", " LSCSample(5.659 * ureg.Bq, \"1-2-3\"),\n", " LSCSample(0.509 * ureg.Bq, \"1-2-4\"),\n", " ],\n", " time=\"7/30/2024 09:28 AM\",\n", ")\n", "\n", "sample_3 = LIBRASample(\n", " [\n", " LSCSample(0.393 * ureg.Bq, \"1-3-1\"),\n", " LSCSample(0.410 * ureg.Bq, \"1-3-2\"),\n", " LSCSample(6.811 * ureg.Bq, \"1-3-3\"),\n", " LSCSample(0.492 * ureg.Bq, \"1-3-4\"),\n", " ],\n", " time=\"7/30/2024 9:59 PM\",\n", ")\n", "\n", "sample_4 = LIBRASample(\n", " [\n", " LSCSample(0.406 * ureg.Bq, \"1-4-1\"),\n", " LSCSample(0.403 * ureg.Bq, \"1-4-2\"),\n", " LSCSample(4.864 * ureg.Bq, \"1-4-3\"),\n", " LSCSample(0.467 * ureg.Bq, \"1-4-4\"),\n", " ],\n", " time=\"7/31/2024 9:56 AM\",\n", ")\n", "\n", "sample_5 = LIBRASample(\n", " [\n", " LSCSample(0.322 * ureg.Bq, \"1-5-1\"),\n", " LSCSample(0.369 * ureg.Bq, \"1-5-2\"),\n", " LSCSample(1.900 * ureg.Bq, \"1-5-3\"),\n", " LSCSample(0.470 * ureg.Bq, \"1-5-4\"),\n", " ],\n", " time=\"8/1/2024 11:47 AM\",\n", ")\n", "\n", "sample_6 = LIBRASample(\n", " [\n", " LSCSample(0.343 * ureg.Bq, \"1-6-1\"),\n", " LSCSample(0.363 * ureg.Bq, \"1-6-2\"),\n", " LSCSample(0.492 * ureg.Bq, \"1-6-3\"),\n", " LSCSample(0.361 * ureg.Bq, \"1-6-4\"),\n", " ],\n", " time=\"8/2/2024 11:24 AM\",\n", ")\n", "\n", "sample_7 = LIBRASample(\n", " [\n", " LSCSample(0.287 * ureg.Bq, \"1-7-1\"),\n", " LSCSample(0.367 * ureg.Bq, \"1-7-2\"),\n", " LSCSample(0.353 * ureg.Bq, \"1-7-3\"),\n", " LSCSample(0.328 * ureg.Bq, \"1-7-4\"),\n", " ],\n", " time=\"8/4/2024 3:14 PM\",\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "All the `LIBRASample` objects are then passed to a `GasStream` class that takes a `start_time` argument as a string." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "libra_run = GasStream(\n", " [sample_1, sample_2, sample_3, sample_4, sample_5, sample_6, sample_7],\n", " start_time=\"7/29/2024 9:28 AM\",\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ".. note::\n", " We have only one gas stream here because it is a 100 mL BABY experiment. For 1L BABY experiments and LIBRA experiments, several `GasStream` objects will be created." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The background activity (measured with a blank sample) is substracted using the `substract_background` method of `LIBRASample`.\n", "\n", ".. note::\n", " We can also use different background LSC samples for different LIBRA samples if need be\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "background_sample = LSCSample(0.334 * ureg.Bq, \"background\")\n", "\n", "for sample in libra_run.samples:\n", " sample.substract_background(background_sample)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the dataset:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from libra_toolbox.tritium.plotting import plot_bars\n", "import matplotlib.pyplot as plt\n", "\n", "plot_bars(libra_run)\n", "plt.legend(reverse=True)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use `get_cumulative_activity` to compute the cumulative release from these measurements:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "release_measurements = libra_run.get_cumulative_activity(form=\"total\")\n", "\n", "plt.scatter(libra_run.relative_times_as_pint, release_measurements)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have processed our data, we can move on to parametric optimisation." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Parametric optimisation\n", "\n", "In order to perform the parametric optimisation, we need to parametrise the model.\n", "Here the free parameters are $k_\\mathrm{top}$ and $k_\\mathrm{wall}$.\n", "\n", ".. note::\n", " For details on how to make a tritium release model, see [Tritium release](tritium_model.ipynb)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "from libra_toolbox.tritium.model import Model\n", "import numpy as np\n", "\n", "P383_neutron_rate = 4.95e8 / 2 * ureg.neutron * ureg.s**-1\n", "A325_neutron_rate = 2.13e8 / 2 * ureg.neutron * ureg.s**-1\n", "\n", "baby_diameter = 1.77 * ureg.inches - 2 * 0.06 * ureg.inches # from CAD drawings\n", "baby_radius = 0.5 * baby_diameter\n", "baby_volume = 100 * ureg.mL\n", "baby_cross_section = np.pi * baby_radius**2\n", "baby_height = baby_volume / baby_cross_section\n", "\n", "exposure_time = 12 * ureg.hour\n", "\n", "irradiations = [\n", " [0 * ureg.hour, 0 + exposure_time],\n", " [24 * ureg.hour, 24 * ureg.hour + exposure_time],\n", "]\n", "\n", "def make_model(k_top, k_wall):\n", "\n", " baby_model = Model(\n", " radius=baby_radius,\n", " height=baby_height,\n", " TBR=5.4e-4 * ureg.particle * ureg.neutron**-1,\n", " k_top=k_top,\n", " k_wall=k_wall,\n", " irradiations=irradiations,\n", " neutron_rate=P383_neutron_rate + A325_neutron_rate,\n", " )\n", "\n", " return baby_model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now create an error function that will compute the squared error between the measurements and the values computed by the model:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "from libra_toolbox.tritium.model import quantity_to_activity\n", "from scipy.interpolate import interp1d\n", "\n", "SCALING_FACTOR_K_TOP = 1e-6\n", "SCALING_FACTOR_K_WALL = 1e-8\n", "\n", "all_prms = []\n", "errors = []\n", "\n", "\n", "def error(prms, verbose=False):\n", " global all_prms\n", " global errors\n", " if verbose:\n", " print(f\"params = {prms}\")\n", "\n", " # make the model and run it\n", " model = make_model(\n", " k_top=prms[0] * SCALING_FACTOR_K_TOP * ureg.m * ureg.s**-1,\n", " k_wall=prms[1] * SCALING_FACTOR_K_WALL * ureg.m * ureg.s**-1,\n", " )\n", "\n", " model.run(7 * ureg.day)\n", "\n", " # compute the error\n", " computed_release = quantity_to_activity(model.integrated_release_top())\n", " computed_release_interp = interp1d(\n", " model.times.to(ureg.day).magnitude, computed_release.to(ureg.Bq).magnitude\n", " )\n", "\n", " err = 0\n", " measurements = libra_run.get_cumulative_activity(form=\"total\")\n", "\n", " for time, measurement in zip(libra_run.relative_times_as_pint, measurements):\n", " # here we need to use .magnitude because the interpolation function does not accept pint quantities\n", " time = time.to(ureg.day).magnitude\n", " err += (measurement.to(ureg.Bq).magnitude - computed_release_interp(time)) ** 2\n", "\n", " err *= ureg.Bq**2\n", "\n", " # store the results for later\n", " all_prms.append(prms)\n", " errors.append(err.magnitude)\n", "\n", " return err.magnitude" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Using the Neldear-Mead algorithm\n", "\n", "We will minimise the `error` function with `scipy.optimize.minimize` with an initial guess.\n", "\n", "First we use the Nelder-Mead algorithm." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/remidm/miniconda3/envs/libra-toolbox/lib/python3.12/site-packages/scipy/integrate/_ivp/base.py:23: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n", " return np.asarray(fun(t, y), dtype=dtype)\n" ] } ], "source": [ "from scipy.optimize import minimize\n", "\n", "initial_guess = [1.6, 5]\n", "res = minimize(error, initial_guess, method=\"Nelder-Mead\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that the optimiser has found a minimum, let's plot the results:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Optimised parameters: [1.63987719 4.76387654]\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from libra_toolbox.tritium.plotting import (\n", " plot_integrated_top_release,\n", " plot_integrated_wall_release,\n", ")\n", "\n", "optimised_prms = res.x\n", "print(f\"Optimised parameters: {optimised_prms}\")\n", "\n", "model = make_model(\n", " k_top=optimised_prms[0] * SCALING_FACTOR_K_TOP * ureg.m * ureg.s**-1,\n", " k_wall=optimised_prms[1] * SCALING_FACTOR_K_WALL * ureg.m * ureg.s**-1,\n", ")\n", "\n", "model.run(7 * ureg.day)\n", "\n", "plot_integrated_top_release(model, label=\"Top release\")\n", "plot_integrated_wall_release(model, label=\"Wall release\")\n", "plt.scatter(libra_run.relative_times_as_pint, release_measurements, color=\"black\", label=\"Measurements\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also show the parameter space:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "all_prms_array = np.array(all_prms)\n", "\n", "plt.scatter(\n", " all_prms_array[:, 0], all_prms_array[:, 1], c=np.log10(errors), cmap=\"viridis\"\n", ")\n", "plt.plot(all_prms_array[:, 0], all_prms_array[:, 1], color=\"tab:grey\", lw=0.5)\n", "\n", "plt.scatter(*optimised_prms, c=\"tab:red\")\n", "plt.annotate(\n", " \"Reference\",\n", " xy=optimised_prms,\n", " xytext=(optimised_prms[0] - 0.02, optimised_prms[1] + 0.1),\n", " arrowprops=dict(facecolor=\"black\", arrowstyle=\"-|>\"),\n", ")\n", "plt.annotate(\n", " \"Initial guess\",\n", " xy=initial_guess,\n", " xytext=(initial_guess[0] - 0.004, initial_guess[1] + 0.05),\n", " arrowprops=dict(facecolor=\"black\", arrowstyle=\"-|>\"),\n", ")\n", "\n", "plt.xlabel(rf\"$k_{{top}}$ (scaled)\")\n", "plt.ylabel(rf\"$k_{{wall}}$ (scaled)\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally we show how the error decreased with the number of iterations:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(errors)\n", "plt.xlabel(\"Iteration\")\n", "plt.ylabel(\"Error (Bq²)\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### `scipy.minimize` default algorithm\n", "\n", "What would happen if we chose another algorithm? Let's use the default algorithm with the same initial guess." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/remidm/miniconda3/envs/libra-toolbox/lib/python3.12/site-packages/scipy/integrate/_ivp/base.py:23: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n", " return np.asarray(fun(t, y), dtype=dtype)\n" ] } ], "source": [ "from scipy.optimize import minimize\n", "\n", "initial_guess = [1.6, 5]\n", "res = minimize(error, initial_guess)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "all_prms_array = np.array(all_prms)\n", "\n", "plt.scatter(\n", " all_prms_array[:, 0], all_prms_array[:, 1], c=np.log10(errors), cmap=\"viridis\"\n", ")\n", "plt.plot(all_prms_array[:, 0], all_prms_array[:, 1], color=\"tab:grey\", lw=0.5)\n", "\n", "plt.scatter(*optimised_prms, c=\"tab:red\")\n", "\n", "plt.annotate(\n", " \"Initial guess\",\n", " xy=initial_guess,\n", " xytext=(initial_guess[0] - 0.004, initial_guess[1] + 0.05),\n", " arrowprops=dict(facecolor=\"black\", arrowstyle=\"-|>\"),\n", ")\n", "\n", "plt.xlabel(rf\"$k_{{top}}$ (scaled)\")\n", "plt.ylabel(rf\"$k_{{wall}}$ (scaled)\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The algorithm converged towards the same minimum." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(errors)\n", "plt.xlabel(\"Iteration\")\n", "plt.ylabel(\"Error (Bq²)\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "However, it required a lot more iterations (or rather function calls), which is why it took longer to converge.\n", "\n", "This is because this algorithm is not derivative free. Nelder-Mead is therefore preferred." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Comparing sample activity to predictions\n", "\n", "It is also possible to compare the measured sample activity to the sample activity predicted by the model (see [LSC sample activity](tritium_model.ipynb#LSC-sample-activity))" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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5PJmIBBk5ciRcXFywevVqrFixAhMnToRGo7np9Tt37sT06dMxZMgQdOrUCTqdDjk5OXUeb8CAATh48CDS09OtH3FxcRgzZgzS09Ph6upqj5fV6AntUQHM3dZ1ncsjx5fLigoRCeLj44NRo0YhMTERRUVFGD9+/C2vj4qKwsqVKxEXF4eioiI899xz8PSs+z9evr6+6Ny5c43HvL29ERAQUOtxZyZ8C32i6lhRISKREhISkJ+fj0GDBiE0NPSW1y5duhT5+fno1q0bHnvsMUyfPh3BwcEKReo8NFL1tViNTFFREfR6PQoLC+Hn5yc6HKqjyrduXkoNfQu4UgqkTQNua277c2tfarS/zkSNXllZGc6cOYPIyEg2h9Itfx9sef9mRYVUQ5KuN9NyHxUiIgKYqJCKFBkAo8l8n/uoEBERwESFVMSy2Zunm/mDiIiIiQqpBvdQISKiP2OiQqqRz11piYjoT5iokGrkWpYms6JCRERVmKiQauRxDxUiIvoTJiqkGvnsUSEioj9hokKqwZOTiYjoz4Sf9UPKei/1oizP+0yPkAY/B3tUiEjN5syZgw0bNiA9Pb3O36PRaLB+/XoMHz5ctrgcHRMVUg3LOT/c7I3I8dzq6Ax7s/UojWHDhqGiogKbNm2q9bUdO3bg7rvvxoEDBzB79mxMmzbNXmECAJKSkpCUlISzZ88CADp16oRXX30VgwcPtus4jRmnfkg1uH0+EYmQkJCALVu2ICsrq9bXkpOTERcXh5iYGPj4+CAgIMCuY7ds2RLz5s3D/v37sW/fPvTv3x8PPfQQDh8+bNdxGjMmKqQa3EeFiER44IEHEBQUhOXLl9d4vKSkBGvXrkVCQgIA89RP165drV9PTU3FwIEDERgYCL1ej759+yItLc2msYcNG4YhQ4YgKioK7dq1w7/+9S/4+Phgz549DX1ZDoOJCqlGLqd+iEgArVaLcePGYfny5ZCk69NGa9euhdFoxOjRo2/4fcXFxYiPj8cvv/yCPXv2ICoqCkOGDEFxcXG94jAajVizZg1KS0vRu3fvej2HI2KPipP54NARWZ63oc201U9OZjMtESlt4sSJmD9/PlJSUtCvXz8A5mmfRx55BHq9/obf079//xqff/LJJ/D390dKSgoeeOCBOo998OBB9O7dG2VlZfDx8cH69evRsWPHer8WR8OKCqlCcbWTkzn1Q0RKi46Oxh133IFly5YBAE6ePIkdO3ZYp31u5PLly5g0aRKioqKg1+vh5+eHkpISZGRk2DR2+/btkZ6ejl9//RVPPfUU4uPjceSIPH9UNkasqDiZ0yGDZHrmygZ9t6WawpOTiUiUhIQETJs2DYsXL0ZycjLatGmDvn373vT6+Ph45ObmYtGiRWjVqhV0Oh169+6N8vJym8Z1d3dH27ZtAQDdu3dHamoqFi1ahI8//rhBr8dRsKJCqpDHPVSISLCRI0fCxcUFq1evxooVKzBx4kRoNDdfVr1z505Mnz4dQ4YMQadOnaDT6ZCTk9PgOEwmEwwGQ4Ofx1GwokKqYKmosJGWiETx8fHBqFGjkJiYiKKiIowfP/6W10dFRWHlypWIi4tDUVERnnvuOXh62vaPWGJiIgYPHozw8HAUFxdj9erV2LZtGzZv3tyAV+JYmKiQKlgqKtxDhcgx2boJmygJCQlYunQphgwZgtDQ0Fteu3TpUkyePBndunVDWFgY3nrrLcyePdum8bKzszFu3DhcvHgRer0eMTEx2Lx5MwYOHNiQl+FQmKiQKvCcHyJSg969e9dYolzdnDlzMGfOHOvnsbGxSE1NrXHN//zP/9T4/GbPZbF06dL6BepE2KNCqsDt84mI6EaYqJAq5HIPFSIiugEmKqQK7FEhIqIbYaJCqpDPVT9ERHQDbKZ1MpVpRlmeV3t/w76fzbRERHQjrKiQKnDDNyIiuhEmKqQK1kSFFRUiIqqGiQoJx5OTiYjoZpiokHAl5UAlT04mIqIbYKJCwuVWTft4aHlyMhGRSBEREVi4cGGdr58zZw66du0qWzwAExXVysvLw4kTJ1BYWCg6FNlxDxUiEm38+PHQaDS1Pk6ePCk6NKfHREWlvvrqK7Rr1w7jxo0THYrsuIcKEanB/fffj4sXL9b4iIyMrHVdeXm5gOicFxMVlcrJyQEABAQECI5EftxDhYjUQKfToXnz5jU+XF1d0a9fP0ydOhUzZ85EYGAgBg0aBABISUlBz549odPpEBISghdffBGVlZXW5+vXrx+mTZuGmTNnokmTJmjWrBmWLFmC0tJSTJgwAb6+vmjbti02btx4y7giIiLw5ptvYty4cfDx8UGrVq3w7bff4sqVK3jooYfg4+ODmJgY7Nu3r8b3rVu3Dp06dYJOp0NERAQWLFhQ4+vZ2dkYNmwYPD09ERkZiVWrVtUau6CgAI8//jiCgoLg5+eH/v3748CBA/X9EdcLExWVys3NBeAciUoup36IHJYkSSgtLVX8469OLbbVZ599Bnd3d+zcuRMfffQRzp8/jyFDhqBHjx44cOAAkpKSsHTpUrz55pu1vi8wMBB79+7FtGnT8NRTT2HEiBG44447kJaWhvvuuw+PPfYYrl69esvx33vvPfTp0we//fYbhg4disceewzjxo3D2LFjkZaWhjZt2mDcuHHW171//36MHDkSjz76KA4ePIg5c+bglVdewfLly63POX78eGRmZuLnn3/GV199hQ8//BDZ2dk1xh0xYgSys7OxceNG7N+/H926dcOAAQOQl5dnnx9sHXBnWpWyJCqBgYGCI5EfT04mclxXr16Fj4+P4uOWlJTA29vbpu/5/vvva8Q6ePBgrF27FgAQFRWFt99+2/q1l19+GWFhYfi///s/aDQaREdH48KFC3jhhRfw6quvwsXFXAfo0qUL/vGPfwAAEhMTMW/ePAQGBmLSpEkAgFdffRVJSUn4/fffcfvtt980tiFDhuCJJ56o8T09evTAiBEjAAAvvPACevfujcuXL6N58+Z49913MWDAALzyyisAgHbt2uHIkSOYP38+xo8fj+PHj2Pjxo3Yu3cvevToAQBYunQpOnToYB3zl19+wd69e5GdnQ2dTgcAeOedd7BhwwZ89dVXmDx5sk0/3/pioqJSTjn1w0SFiAS65557kJSUZP28eqLTvXv3GtcePXoUvXv3hkajsT7Wp08flJSUICsrC+Hh4QCAmJgY69ddXV0REBCA2267zfpYs2bNAKBWJePPqj+P5Xtu9jzNmzfH0aNH8dBDD9V4jj59+mDhwoUwGo04evQotFptjdcVHR0Nf39/6+cHDhxASUlJrfeha9eu4dSpU7eM156YqKiUM1VU2KNC5Li8vLxQUlIiZFxbeXt7o23btjf9Wn24udXcc0Gj0dR4zJLomEymOj+P5Xvq8zy2KCkpQUhICLZt21bra9UTGrkxUVEpp6qo8JwfIoel0Wjq/SavZh06dMC6desgSZI1Sdi5cyd8fX3RsmVLwdGZ49u5c2eNx3bu3Il27drB1dUV0dHRqKysxP79+61TP8eOHUNBQYH1+m7duuHSpUvQarWIiIhQMPqahDbTzpkzp9aa9ejoaJEhqYYzNdPmcXkyETUyTz/9NDIzMzFt2jT88ccf+Oabb/Daa69h1qxZ1v4UkZ599lls3boVb7zxBo4fP47PPvsM//d//4fZs2cDANq3b4/7778fTzzxBH799Vfs378fjz/+ODw9r/9DfO+996J3794YPnw4fvjhB5w9exa7du3Cyy+/XGuFkZyE/zQ7depUY836L7/8Ijok4SorK61ZrVNM/VRVVAId748uInJQLVq0wH//+1/s3bsXXbp0wZNPPomEhARr46xo3bp1w5dffok1a9agc+fOePXVV/H6669j/Pjx1muSk5MRGhqKvn374m9/+xsmT56M4OBg69c1Gg3++9//4u6778aECRPQrl07PProozh37py1J0YJGsnea7hsMGfOHGzYsAHp6el1ut5gMMBgMFg/LyoqQlhYGAoLC+Hn5ydTlMq7cuWK9ZeloqICWq39Zugq39L89UX1oH2p7r9Gf44h9C3gSinw23SgcwN/922Jg4jsq6ysDGfOnEFkZCQ8PDxEh0OC3er3oaioCHq9vk7v3w2qqFRPGurrxIkTCA0NRevWrTFmzBhkZGTc9Nq5c+dCr9dbP8LCwho8vhpZpn30er1dkxQ1Mpmq7aPCqR8iIvoTmxKVjRs3Ij4+Hq1bt4abmxu8vLzg5+eHvn374l//+hcuXLhg0+C9evXC8uXLsWnTJiQlJeHMmTO46667UFxcfMPrExMTUVhYaP3IzMy0abzGwplW/BQaAFNVEYQbvhER0Z/V6c/19evX44UXXkBxcTGGDBmCF154AaGhofD09EReXh4OHTqEH3/8EW+88QbGjx+PN954A0FBQX/5vIMHD7bej4mJQa9evdCqVSt8+eWXSEhIqHW9TqezbjrjyJxpxY+lmuKrA9wdu3hERET1UKe3hrfffhvvvfceBg8efMNu5pEjRwIAzp8/jw8++ACff/45nnnmGZuD8ff3R7t27Zz+tEpnWvGTU2q+VWM1Zffu3XjyySfx4IMP4o033hAdDhGRU6pTorJ79+46PVmLFi0wb968egdTUlKCU6dO4bHHHqv3czgCZ5r6UfMeKtu3b8fvv/+ONm3aiA6FqFERuEaDVMRevwdClyfPnj0bKSkp1rXZDz/8MFxdXTF69GiRYQnnVFM/VXuoqHFpsmWzpDvvvFNwJESNg2Wn1L86YI+cg+X34M+789rK5q6AWbNm1fnad99995Zfz8rKwujRo5Gbm4ugoCDceeed2LNnT536WxyZM079qG37fJPJxESFyEaurq7w9/e3nlvj5eVV4ywccg6SJOHq1avIzs6Gv78/XF1dG/R8Nicqv/32G3777TdUVFSgffv2AIDjx4/D1dUV3bp1s15Xl1/ONWvW2Dq8U3DGqR+19aj88ccfyMvLg6enJ2JjY0WHQ9RoNG/eHMBfH7JHjs/f39/6+9AQNicqw4YNg6+vLz777DM0adIEAJCfn48JEybgrrvuwrPPPtvgoJydU039qHQPFcsOyb169Wpw2ZLImWg0GoSEhCA4OBgVFRWiwyFB3NzcGlxJsbA5UVmwYAF++OEHa5ICAE2aNMGbb76J++67j4mKHTjT1I/lnJ8AlfWocNqHqGFcXV3t9kZFzs3mRKWoqAhXrlyp9fiVK1duulEb2caZpn5ELU9+L/XiLb/+n60pAIDsoI5/eW11z/QIaVBcRERUk82rfh5++GFMmDABX3/9NbKyspCVlYV169YhISEBf/vb3+SI0alIkuRUFZVcFfaoFF65hNzz56BxcUHEbd1Fh0NE5NRsrqh89NFHmD17Nv7+979b5x+1Wi0SEhIwf/58uwfobAoLC2E0GgE4R6KixmbaMwdSAQAhbaLh4eMrOBoiIudmc6Li5eWFDz/8EPPnz8epU6cAAG3atIG3t8qaDBopSyOtt7e3w58+KklAjgoTlbO/7wMARHbpITgSIiKq9+kq3t7eiImJsWcsBOdqpC0tB8rNxSPFE5UPDh256dcupJobaY/5N7/ldTfCHhUiIvuyqUfl559/xoIFC6wrIj7++GOEh4cjKCgIkyZNwrVr12QJ0pk4UyOtpT/FQwt4qWQFsFRZgfJzJwAAHq07CI6GiIjqXFFZsmQJnnrqKURGRuLll1/Ga6+9hn/961947LHH4OLigs8//xwBAQENOuuHnGsPlerTPmrZvLI86wykygq4ePtC26yF6HCIiJxenSsqixYtwnvvvYcTJ05gw4YNePXVV7F48WIkJSVh8eLF+PTTT/HVV1/JGatTcKapH+uBhCrqTzGcPgoA0EW259bfREQqUOeKyunTp/Hggw8CAO6//35oNBr07NnT+vVevXohMzPT/hE6GbUkKi9tBvw9gMdigRA/ecYQuTT5dMigGz4ef9GEFQCei9mPf97kmlurbFBcRERUU50TlbKyMnh6Xt/nXKfTQafT1fi8spL/SDeUZepH5MGMhkrg/V3m24c6AnK1h1oSlUAVVVR+PWY+lrxne1ZTiIjUoM6JikajQXFxMTw8PCBJEjQaDUpKSlBUVAQA1ltqGEuiIrKZNjXLnKQ08wHayRhGrsqmfgpKJBzLMt/v2U5sLEREZFbnREWSJLRr167G59VPlbUkL9QwakhUdpwx394VIW+Tq9p2pU09br5t3RwI8ufvMhGRGtQ5Ufn555/ljIOqWM5REpmobD9rvr0zQt5x1LYrrWXap1c0kxQiIrWoc6LSt29fOeOgKqIrKhVGYHeG+f5dkfKOpbZdafdaEpX2ggMhIiKrOi1PLi0ttelJbb2ezEwmk3XVj6hm2rQL5h1jm3gCnYPlHUtNUz+SJOHXY+b7bKQlIlKPOlVU2rZtixkzZiA+Ph4hITdeAyJJEn788Ue8++67uPvuu5GYmGjXQJ2BGg4k/OWs+fbOVoCLzWdr20bk1E9lmrHG51mFQHYB4OoC3FZkQmVa/Z5Xe3/DYyMiouvqlKhs27YNL730EubMmYMuXbogLi4OoaGh8PDwQH5+Po4cOYLdu3dDq9UiMTERTzzxhNxxOyTLtI+vr2+Npd9K2nnWfCv3tA+grqmf3y6YbzsGAx4q2c6fiIjqmKi0b98e69atQ0ZGBtauXYsdO3Zg165duHbtGgIDAxEbG4slS5Zg8ODBcHV1lTtmhyW6P0WSrven3B4u71iGSvMUE6CuRCU2VGwcRERUk02nJ4eHh+PZZ5/Fs88+K1c8Du+91Is3/drh3eb1sZWe+ltedzMNPbn3ZK65yuHuCnST+Q3b0p/i6gLoPeQdqy6YqBARqZPMXQhki9KCPACAt39TIePvqToBoXsLQGdTCms767SPpzoOJLQkKl3l2oaXiIjqRea3I/qzDw4duenXCv4wH4iXJbnc8rqbaWhFZfc5821vmad9AHXtoXK5BDhfZE6YujBRISJSFVZUVMRUXAgAcPH1FzK+pT9FiURFTdvnp1dVU9oFAL5iepiJiOgmmKioiLHEnKi4+sp0XPEtFJYBh7PN9+VupAXUdSAh+1OIiNSLiYqKmErMBzu6+OgVHzs1y7zqp3VToLmv/OPlVu0JqIqKSlXfMhMVIiL1sblHJSIiAhMnTsT48eMRHq7An94O5nTIoJt+7Q6DEbsBLAlbhIdD3q/Hs1fWOy5Lf0qvsHo/hU1yr5lv1dCjwooKEZF62VxRmTlzJr7++mu0bt0aAwcOxJo1a2AwGOSIzenkmAsqCFS+oKJofwpQberHW5nxbib/GnDavNiKjbRERCpUr0QlPT0de/fuRYcOHTBt2jSEhIRg6tSpSEur577jBADIMbeoIFDhFhWTCfi1ammyYomKZerHU5nxbuZA1bRPRBN1TEMREVFN9e5R6datG95//31cuHABr732Gj799FP06NEDXbt2xbJlyyBJkj3jdHiVRgn5Jeb7Sicqf+QARQbA2x3o3EyZMdUy9cP9U4iI1K3e+6hUVFRg/fr1SE5OxpYtW3D77bcjISEBWVlZeOmll/Djjz9i9erV9ozVoeVWTftoNEBTBZpZq9uXZb6NDQW0Cp2AkKeS5cm/XzLfctqHiEidbE5U0tLSkJycjC+++AIuLi4YN24c3nvvPURHR1uvefjhh9GjRw+7BuroLP0pTX0BV1dlt2rdf958G9dCuTFzqqZ+RPeoHKpKVG5rLjYOIiK6MZsTlR49emDgwIFISkrC8OHD4eZW+6jZyMhIPProo3YJ0NFUphlv+PjlM+bbQPebX/NXtPfXL6Z9VYlKd4USlUojUFBmvi9y6qfSCBy9Yr6v1JQXERHZxuZE5fTp02jVqtUtr/H29kZycnK9g3JGlgpDgMIVhvLK6w2lcS2VGTO/7Pr9JgIPJDyRaz7F2dsdiGwiLg4iIro5m5tp77nnHuTm5tZ6vKCgAK1bt7ZLUM4oR9BOrYezzW/W/h5AG4XOQrQsTW7iqVxPzI0crJr26dQMcOHWh0REqmTzP89nz56F0Vh7asJgMOD8+fN2CcoZWZbrKj0VYmmk7d5CuVOMcwS91j87dNl8y2kfIiL1qvPUz7fffmu9v3nzZuj113clMxqN2Lp1KyIiIuwanDPJEbQBmtL9KYB6VvywkZaISP3qnKgMHz4cAKDRaBAfH1/ja25uboiIiMCCBQvsGpwzsSQqQQonKtYVPwr1pwDXX2uA4M3eDlZVVG5jRYWISLXqnKiYTCYA5hU9qampCAwMlC0oZyRiOuRaxfXpDyWXJqth+/yiMuBsvvl+Z1ZUiIhUy+ZVP2fOnJEjDqdn3VdEwUQl/SJgNAHB3kBLBc8XulL1WpWuHlVnSdBCfcX3yhAR0c3VKVF5//33MXnyZHh4eOD99299qu/06dPrFci8efOQmJiIGTNmYOHChfV6jsbMUmVQcnly9WkfpRppAXVs9mZtpGU1hYhI1eqUqLz33nsYM2YMPDw88N577930Oo1GU69EJTU1FR9//DFiYmJs/l5HIWJ5clpVotItVLkxATHVoz9jIy0RUeNQp0Sl+nSPvad+SkpKMGbMGCxZsgRvvvmmXZ+7sbhWAZSWm+8rWWWwbPTWVelERQU9Kge5NJmIqFGweR+VX375xa4BTJkyBUOHDsW99977l9caDAYUFRXV+HAElmkfN1fAT6fMmOWV17ePV/pAPtFTP5IkWSsqTFSIiNTN5kSlf//+iIyMxEsvvYTDhw83aPA1a9YgLS0Nc+fOrdP1c+fOhV6vt36EhYU1aHy1qD4VolSvyJFsoMII6D2AVv7KjGkhahdei0uXLqGgDHDRANFBYmIgIqK6sTlRuXDhAp599lmkpKTgtttuQ9euXTF//nxkZWXZ9DyZmZmYMWMGVq1aBQ+Puh34kpiYiMLCQutHZmamreGrknVfEQXfuH+vqih0CVG2kdZgMKDYYL4vatXP0aNHAQCtmwIetc/UJCIiFbE5UQkMDMTUqVOxc+dOnDp1CiNGjMBnn32GiIgI9O/fv87Ps3//fmRnZ6Nbt27QarXQarVISUnB+++/D61We8Nt+nU6Hfz8/Gp8OAIRUyGW/hSlp32uXDHPN2ldzNUcESyJCqspRETqZ/M+KtVFRkbixRdfRJcuXfDKK68gJSWlzt87YMAAHDx4sMZjEyZMQHR0NF544QW4ugo8rU5hIqZCRCUqOTk5AJSd5vqzI0eOAAA6BIsZn4iI6q7eicrOnTuxatUqfPXVVygrK8NDDz1U514TAPD19UXnzp1rPObt7Y2AgIBajzs6pQ8klKRqiYrCy3MtFRWRK35YUSEiajxsTlQSExOxZs0aXLhwAQMHDsSiRYvw0EMPwcuL23vWl9LLdTMKgIIy8yqjjgpXFawVFSYqRERUBzYnKtu3b8dzzz2HkSNH2v28n23bttn1+RoLpc++sVRTOgQB7g2a/LOdpaIiqpE2Pz8fly6ZO4k59UNEpH42v03t3LlTjjicmtI7tYrqTwGuV1REna9jqaa01AO+Cu1ZQ0RE9VenROXbb7/F4MGD4ebmhm+//faW1z744IN2CcyZKD31U31pstJEV1Q47UNE1LjUKVEZPnw4Ll26hODgYAwfPvym12k0mhsuK6Zby1G4mda6db4TVlS44oeIqHGpU6JiMplueJ8aTpKAK1WJSrACVYbCMuBMvvm+iAP5WFEhIiJb2Lzh24oVK2AwGGo9Xl5ejhUrVtglKGdSUAZUVuV+Skz9HK46jK+FH9BUQFVD9KofS6Ki9GonIiKqH5sTlQkTJqCwsLDW48XFxZgwYYJdgnIm2SXmW70HoFNgBc6RbPNtJ0GH8YncR6W0tBRnz54FwIoKEVFjYXOiIkkSNDfYUjQrKwt6vd4uQTkTy7SPUlMhloqKiIqCyWRCbm4uADEHEh47dsw8dmCg0H1ciIio7ur8N3xsbCw0Gg00Gg0GDBgArfb6txqNRpw5cwb333+/LEE6MqUTFZEVlYKCAmuztYhExTrt07EjgO3KB0BERDarc6JiWe2Tnp6OQYMGwcfHx/o1d3d3RERE4JFHHrF7gI5OVEVFRKJimfbx0ym/0RwA/PHHHwCA6OhoMFEhImoc6vx28dprrwEAIiIi8Oijj0Kn425Z9nClqkdFiUQlJycHl6vG6yCgR8PSSCtqxc+JEycAAO3atQNq94MTEZEK2dyj0rFjR6Snp9d6/Ndff8W+ffvsEZNTuVK12ZsSb96HDx8GAEQ2AXwE5JmWikqAoETl+PHjAKoSFSIiahRsTlSmTJmCzMzMWo+fP38eU6ZMsUtQzsRaUfG59XX2cOjQIQDiVvxYKyoC+lMkSbImKlFRUcoHQERE9WJzonLkyBF069at1uOxsbHWXT+p7pTsUbFUVETtISKyonLp0iWUlpbCxcUFrVu3Vj4AIiKqF5sTFZ1Oh8uXL9d6/OLFizVWAlHdZCu4K61qKioCEhVLNSUiIgLu7u7KB0BERPVic6Jy3333ITExscambwUFBXjppZcwcOBAuwbnDKwnJ8v85i1JkvBExbrZm4CpnxqNtERE1GjYXAJ55513cPfdd6NVq1aIjY0FYF6y3KxZM6xcudLuAToyk+n6yclyV1QuXbqE/Px8uGiA9oHyjnUzIrfPZyMtEVHjZHOi0qJFC/z+++9YtWoVDhw4AE9PT0yYMAGjR4+Gm5ubHDE6rPwywKjQOT+WakpUAOAh6D+TyIoKG2mJiBqnejWVeHt7Y/LkyfaOxelYzvlp4gm4uco7luhpH0DsOT+c+iEiapzq3f165MgRZGRkoLy8vMbjDz74YIODchY5Cq74sWwf30HgqcGipn6MRiNOnjwJgIkKEVFjY3Oicvr0aTz88MM4ePAgNBoNJEkCAOtBhZazXOivZSuYqFi2j28v6NTga9euobTU/IKVXvVjSajd3d0RFham7OBERNQgNq/6mTFjBiIjI5GdnQ0vLy8cPnwY27dvR1xcHLZt2yZDiI5LyT1UrImK4EZaNzc3+Cm8K65l2qdt27ZwdZV5jo2IiOzK5orK7t278dNPPyEwMBAuLi5wcXHBnXfeiblz52L69On47bff5IjTISl1zk9eXp61P6SdoETF2p8SGAiN5qKiY3PFDxFR42VzRcVoNMLX1xeA+U3nwoULAIBWrVrh2LFj9o3OwSk19WP579KyZUshZ/wA1fpTApXPlLjih4io8bK5otK5c2ccOHAAkZGR6NWrF95++224u7vjk08+4dbkNrI208p8zo9l2ic6OhpAlryD3YSlohIUpHyTDFf8EBE1XjYnKv/4xz+sTZGvv/46HnjgAdx1110ICAjAv//9b7sH6MiUrqiYE5Uf5R3sJtRQUWGiQkTU+NicqAwaNMh6v23btvjjjz+Ql5eHJk2aWFf+UN3kKHTOT42KSuFfXCwTURWViooKnDt3DgDQpk0bRccmIqKGs7lH5UaaNm3KJKUeLBu+yb2viHXFT/v28g50C9WbaZWUkZEBo9EIDw8PhISEKDo2ERE1nF0SFbKd0QTkXjPfD5axR6WiogKnTp0CYJn6EcOSqAQHK7vj3OnTpwEArVu3hosLf92JiBob/sstSO5VoGqvPAR4yjfO6dOnUVlZCW9vb7Ro0UK+gf5CdnY2ALGJChERNT5MVASxbPYW4AVoZdyDrPq0j8jpOSYqRERUH0xUBFFqV9qaS5PFEZWoWKa92EhLRNQ41StRWblyJfr06YPQ0FDrioqFCxfim2++sWtwjkypRKXm0mQxDAYDCgvNy41YUSEiIlvYnKgkJSVh1qxZGDJkCAoKCqyHEPr7+2PhwoX2js9hZSu0fb4aKiqWRlqtVgt/f3/FxpUkyVpRYaJCRNQ42ZyofPDBB1iyZAlefvnlGge8xcXF4eDBg3YNzpHlKFBRkSRJFUuTLdM+QUFBiq68ycvLQ1FREQAgMjJSsXGJiMh+bH7XOHPmDGJjY2s9rtPprDvW0l9TYlfa3Nxc5OfnAxB7zo3oRtrQ0FB4esq4tIqIiGRjc6ISGRmJ9PT0Wo9v2rQJHTp0sEdMTkGJc35OnjwJAAgLCxP6Ri06UeG0DxFR42XzFvqzZs3ClClTUFZWBkmSsHfvXnzxxReYO3cuPv30UzlidEhKVFQsiUrbtm3lG6QOmKgQEVF92ZyoPP744/D09MQ//vEPXL16FX//+98RGhqKRYsW4dFHH5UjRoekxDk/aklURO1Ky6XJRESNn82JCgCMGTMGY8aMwdWrV1FSUqL4G5AjUOKcH7UkKqyoEBFRfdUrUbHw8vKCl5eXvWJxGhVGIK/qnJ9mMvaonDhxAgATFSYqRESNV50SldjY2Dpvv56WltaggJyBpZri6gI0lbHH1VJREbniBxCTqJSXlyMzMxMAExUiosasTonK8OHDZRk8KSkJSUlJOHv2LACgU6dOePXVVzF48GBZxlOLy1WJSrA3INe2Inl5ecjLywMg/o1aRKJy7tw5mEwmeHl5oVmzZoqNS0RE9lWnROW1116TZfCWLVti3rx5iIqKgiRJ+Oyzz/DQQw/ht99+Q6dOnWQZUw0sFZVgGad9LI2koaGh8PaWefvbW5AkSUiiUn3aR+RhjERE1DD17lHZt28fjh49CgDo2LEjunfvbvNzDBs2rMbn//rXv5CUlIQ9e/Y4dKJyqSpRkbM/RS2NtCUlJSgrKwNg3plWKZZEhTvSEhE1bjYnKllZWRg9ejR27txpPbeloKAAd9xxB9asWYOWLVvWKxCj0Yi1a9eitLQUvXv3vuE1BoMBBoPB+rlle/TGRomKiloSFUs1xdvbW9HKjmU6kYkKEVHjZnOHxOOPP46KigocPXrU2gdx9OhRmEwmPP744zYHcPDgQfj4+ECn0+HJJ5/E+vXr0bFjxxteO3fuXOj1eutHWFiYzeOpgaVHpTlX/MjGcqp3q1atFB2XiIjsy+ZEJSUlBUlJSTUOuWvfvj0++OADbN++3eYA2rdvj/T0dPz666946qmnEB8fjyNHjtzw2sTERBQWFlo/LKs6GhslKyrOuOIHYKJCROQobJ76CQsLQ0VFRa3HjUYjQkNDbQ7A3d3d+ld/9+7dkZqaikWLFuHjjz+uda1Op4NOp7N5DLW57EQ9KkxUiIioIWyuqMyfPx/Tpk3Dvn37rI/t27cPM2bMwDvvvNPggEwmU40+FEeULXOiUlhYaN22XvT28SISlbKyMly8eBEAEBERodi4RERkfzZXVMaPH4+rV6+iV69e0GrN315ZWQmtVouJEydi4sSJ1mst+3jcTGJiIgYPHozw8HAUFxdj9erV2LZtGzZv3mxrWI3KZZmnfixLk5s1awZfX195BqkjEYmKZUrQy8sLAQEBio1LRET2Z3OisnDhQrsNnp2djXHjxuHixYvQ6/WIiYnB5s2bMXDgQLuNoTYVRiDnqvm+XBUVtUz7AOI2ewPM0z7cQ4WIqHGzOVGJj4+32+BLly6123M1FleqTk120QABMh2TxESF/SlERI6i3hu+ZWdnIzs7GyaTqcbjMTExDQ7KkVXfPt9Vpu3z1XQYHxMVIiJqCJsTlf379yM+Ph5Hjx6FJEk1vqbRaGA0Gu0WnCNSYmnymTNnAKhjszMRiYplszc20hIRNX42JyoTJ05Eu3btsHTpUjRr1ow9ADZSYmmyWhIVo9GInJwcAKyoEBFR/dicqJw+fRrr1q1TRf9DYyR3RaWyshIZGRkAxCcqeXl51qnBwMBAxcZlokJE5Dhs7pIYMGAADhw4IEcsTkHuikpWVhaMRiN0Oh1CQkLkGaSOLNM+AQEB1qXscqusrERWVhYAJipERI7A5nePTz/9FPHx8Th06BA6d+4MNze3Gl9/8MEH7RacI5L75GTLtE+rVq3g4iJTt24diehPOX/+PIxGI9zc3IQnakRE1HA2Jyq7d+/Gzp07sXHjxlpfYzPtX5N76kct/SmA2BU/4eHhwhM1IiJqOJv/JZ82bRrGjh2LixcvwmQy1fhgkvLXrCcny7RhLBMV9qcQETkSmxOV3NxcPPPMM2jWrJkc8Tg8VlTkxUSFiMix2Jyo/O1vf8PPP/8sRywOr7KyUvbt8y2Jihr2ELEkKkFBQYqNadlDhYkKEZFjsLlHpV27dkhMTMQvv/yC2267rVYz7fTp0+0WnKPJycmBJJm3zw+Uaft8NVVULl26BABo3ry5YmOyokJE5FjqterHx8cHKSkpSElJqfE1jUbDROUWLl++DMCcpMixff61a9dw8eJFAExU1FBRIiKihrM5UbH8xU62s7xxy9WfYnmT9vHxQUBAgDyD2MCSmCnVzyRJQGZmJgAgLCxMkTGJiEheXL+pIOsbtwKNtKKPNpAkSfGKSt41oKysDADQsmVLRcYkIiJ52VxRkSQJX331FX7++ecbnp789ddf2y04R2NNVGRammxpJFXDtE9hYSEMBgMA5SoqmQXm2+DgYOh0OkXGJCIiedmcqMycORMff/wx7rnnHh5KaCMlKyqiWV6rn58fPD09FRnzfJH5ltUUIiLHYXOisnLlSnz99dcYMmSIHPE4NGdKVEQ00mYWmm+ZqBAROQ6be1T0ej1at24tRywOT+5mWmdPVM5XJSpspCUichw2Jypz5szBP//5T1y7dk2OeByaZelwiBNsn6/0ih+AFRUiIkdk89TPyJEj8cUXXyA4OBgRERG1NnxLS0uzW3COxpKoyHHOT7EByMvLA6COzc6EVFSqelRYUSEichw2Jyrx8fHYv38/xo4dy2ZaGxgMBmsiIUdFxVJN8Pf3h5+fn/0HsJHIqR9WVIiIHIfNicp//vMfbN68GXfeeacc8Tgsyxu3uyvQVIZFMJalueHh4fZ/8noQstkbExUiIodjc49KWFiYKv5ib2yqT/vIUYTKKDDfqiVREbLZW6X5fosWLRQZk4iI5GdzorJgwQI8//zz1s3FqG7k7E8BrlcTnDVRsVSUgoKC4OHhociYREQkP5unfsaOHYurV6+iTZs28PLyqtVMa+nDoJqsK35kWpqspoqKyWRCdnY2AOWmfthIS0TkmGxOVBYuXChDGI7PmSoqeXl5qKw0z8MEBwcrMib7U4iIHFO9Vv2Q7eTeQ0VNzbSWaZ+AgAC4u7srMiY3eyMickw2JyrVlZWVoby8vMZjbLS9MTkrKkYTkFU19aGGREXEZm9ZPOeHiMgh2dxMW1paiqlTpyI4OBje3t5o0qRJjQ+6MTkrKpdLgAoj4OrqipCQEPsPYCMRe6hkceqHiMgh2ZyoPP/88/jpp5+QlJQEnU6HTz/9FP/85z8RGhqKFStWyBGjQ5CzomJppG3RogW02gYVyeyC5/wQEZG92Pyu9t1332HFihXo168fJkyYgLvuugtt27ZFq1atsGrVKowZM0aOOBs1o9FoXQUj5660apj2AbjZGxER2Y/NFZW8vDzr6cl+fn7W5ch33nkntm/fbt/oHER2djZMJhNcXFxkOTlZTY20ADd7IyIi+7E5UWndurX1lN7o6Gh8+eWXAMyVFn9/f7sG5ygs0z7NmjWDq80/8b+WobKKirDN3rzBzd6IiByMzW+bEyZMwIEDBwAAL774IhYvXgwPDw8888wzeO655+weoCOwNtLK1OiqtoqK0lM/ls3eWnDBGRGRw7G5R+WZZ56x3r/33ntx9OhRpKWloW3btoiJibFrcI5C7kRFTbvSAspXVCyJSku9IsMREZGCGrxEJCIiAhEREXYIxXHJXlFR0dRPZWUlrly5AkC5ROViVaISyooKEZHDqfPUz+7du/H999/XeGzFihWIjIxEcHAwJk+eDIPBYPcAHYGciUppOZB71XxfDYlKTk4OJEmCi4sLAgMDFRnzQrH5NlSmXX+JiEicOicqr7/+Og4fPmz9/ODBg0hISMC9996LF198Ed999x3mzp0rS5CNnZyJiqWa4qcD9Hrxcx+WaZ+goCC4uroqMqaloiLXOUpERCROnROV9PR0DBgwwPr5mjVr0KtXLyxZsgSzZs3C+++/b10BRDXJmqgUmG/D/O3+1PViSVSU3D7fWlHh1A8RkcOpc6KSn59f480nJSUFgwcPtn7eo0cPZGZm2jc6ByFnomJtpBVfTAFw/bWGhoYqN2ZVRUWuAx+JiEicOicqzZo1s+6fUl5ejrS0NNx+++3WrxcXF8PNzc3+ETZykiRZqwxyJCrWM25UkqhcuHABgHyNw39WYQSyS833WVEhInI8dU5UhgwZghdffBE7duxAYmIivLy8cNddd1m//vvvv6NNmzY2DT537lz06NEDvr6+CA4OxvDhw3Hs2DGbnkPt8vLyrCdMy7EKRm17iFgSFaUqKpdLzLdaFyDQS5EhiYhIQXVOVN544w1otVr07dsXS5YswZIlS+Du7m79+rJly3DffffZNHhKSgqmTJmCPXv2YMuWLaioqMB9992H0tJSm55HzSxTIQEBATV+XvZiTVRUUlFReurnQrVpHxcZdv0lIiKx6ryPSmBgILZv347CwkL4+PjUWtGxdu1a+PjYdpDNpk2bany+fPlyBAcHY//+/bj77rtrXW8wGGosgS4qKrJpPBHkngpx9orKxapG2hCVvH4iIrIvm/8G1ev1N1x22rRp0wZXDAoLC63PdSNz586FXq+3foSFhTVoPCWcP38egHyH5V1Q2WZnSveoWF8/G2mJiBySaorlJpMJM2fORJ8+fdC5c+cbXpOYmIjCwkLrR2NYZWRJVFq2bGn3575aDuRfM99XQzOtyWRSfOrHWlFhokJE5JAavIW+vUyZMgWHDh3CL7/8ctNrdDoddDqdglE1XFZWFgB5KiqWaR9vd/OGb6Ll5uaisrISgHLb56utokRERPalikRl6tSp+P7777F9+3ZZKg8iyTn1c6Faf4pGY/ent5ll2icoKEixpeqX2KOiqJMnT2LDhg1wd3fH9OnTRYdDRE5AaKIiSRKmTZuG9evXY9u2bYiMjBQZjizknPrJUlk1QelGWuD6rrSc+pHPmTNn8MUXX+CLL77AoUOHAJh/n6dNmwaNGjJkInJoQhOVKVOmYPXq1fjmm2/g6+tr3RhNr9fD09NTZGh2I+fUzwWVrfjhrrSOIz8/H1988QVWrVqFXbt2WR/XarXo168fhg8fjoqKClmW3BMRVSc0UUlKSgIA9OvXr8bjycnJGD9+vPIB2ZnBYMCVK1cAyNujopZERekVP4ZKIKfq5Gi1VJUau/379+PDDz/EF198gWvXzJ3aGo0G/fv3x5gxYzB8+HA0adJEcJRE5EyET/04MkuFQafTISAgwO7Pr7ZGUqWnfiz9Ke6uQFPHKMAJYTQasW7dOixYsAB79+61Ph4TE4Px48dj1KhRilbJiIiqU0UzraOqPu0jx1y+Ws/5UWxX2mqnJrNVwnbl5eVYuXIl/vd//xcnTpwAALi7u2PEiBF4+umn0bt3b/agEJFwTFRk5GybvSm+hwr7U+rFaDRi1apVeOWVV5CRkQHAvMni9OnT8fTTTyMoKEhwhERE1zFRkZGciUqlEbhUdSCfs/aoXKxWUaG/JkkSNm/ejBdeeAG///47APN/q9mzZ2Py5Mk2H4FBRKQEJioyknNp8uUSwGgCXF2AZip4fzGZTNZVW9yVVn3OnDmDadOm4T//+Q8A88q6l156CdOmTXOYFXZE5JiYqMhIiV1pQ3zNyYpoOTk5qKyshEajQbNmzRQZU21TX2pUXl6Od999F6+//jquXbsGNzc3TJs2DS+99JIsDd5ERPbGREVGSuxKq5Y3aRG70rKicmuHDh3C2LFjceDAAQDmbQCSkpIQHR0tODIiorpTwd/ijkuJXWnV1p/Czd7EM5lMePfdd9G9e3ccOHAAAQEBWLFiBX766ScmKUTU6LCiIhOTyaTYOT9qICJRsTQTN2eiYpWdnY0xY8bgxx9/BAAMHToUn376aZ0OiXwv9aIsMT3TQ5nmaiJyTKyoyCQnJwcVFRXQaDSyrIJR2660Si9NrjACuVW70qqhmVgN9u7di+7du+PHH3+El5cXPv74Y3z33XeKnWRNRCQHVlRkYqmmBAcHy9Kzcb5qsze19agotTQ5u6qaonXhrrQAsGTJEkydOhXl5eVo37491q9fjw4dOtj0HM/khskUXaVMz0tEzoAVFZlYVvzI0Z8CXJ/6cdZdaS3TPs18ABcn/i02mUzWfVDKy8vx8MMPY+/evTYnKUREauXE/8TLS87+FEmquTxZDURVVIKdeNqnrKwMo0ePxoIFCwAAb7zxBtatWwc/P5WU2YiI7IBTPzKRM1EpNgBXK8z31TL1Y6kghYXJNX1Qk+VAwuZOmqgUFxdj2LBhSElJgZubG5YtW4axY8eKDouIyO6YqMgkMzMTgDxTP5b9Q3x1gLe73Z/eZuWVwOXLlwHIN9X1Z9ml5ltnrKgUFhZi8ODB2L17N/z8/PD1119jwIABosMiIpIFExWZWA57a9Wqld2f+5LKNjq7WGw+R8bd3R2BgYGKjGmtqKjkZ6CUgoICDBo0CHv37kWTJk3www8/IC4uTnRYRESyYaIiE0uiEh4ebvfntlRU1LIs17r5XIsWcFGos/WyE/aolJSUWJOUgIAAbNmyBbGxsXZ7/so0o92eqzrt/bI8LRE5CSYqMjCZTNapHzkSFcuKF7VUVCxLpZWa9gGuJyrO0qNiMBjwt7/9zZqk/PTTT4iJiREdFhGR7LjqRwbZ2dkoLy+Hi4uLLMt11TbtYVmBpGiiorKqkpyMRiPi4+OxZcsWeHt747///S+TFCJyGkxUZGCZ9gkNDZVlsze1HcaXJbCi0kwlPwM5zZ49G//+97/h5uaG9evXo2fPnqJDIiJSDBMVGcjZnwKor6KidKJSVgEUlJnvO3pF5dNPP8XChQsBACtXrsTAgQPFBkREpDAmKjJQKlFRTUWlaupHqT1ULEuT3V0Bfw9FhhRix44dePrppwEAr7/+OkaNGiU4IiIi5TFRkYHcicpFlVVUlG6mrV5R0mgUGVJx586dwyOPPIKKigqMGDEC//jHP0SHREQkBBMVGciZqJRVAPnXzPfVUFGpNF5PnJRKVKxLk70VGU5x5eXlGDlyJK5cuYLY2FgsX74cGkfNyIiI/gITFRnIudmb5U3a3RVoooJTgy+VACYJ0Gq1CA4OVmRM69JkFSRqcnj55Zexd+9e+Pv7Y/369fDy8hIdEhGRMExUZHDu3DkA8m72ppZpD0sjbWhoKFxdXRUZ07I02RE3e9u4cSPeeecdAEBycrIsyS4RUWPCRMXOrl69ipycHAAybfamtv4UEXuoOOhmbxcuXMC4ceMAAFOnTsXw4cPFBkREpAJMVOzMsiOtr68v9Hq93Z/fuoeKSt6kRe6h4kgVFUmSMHnyZOTk5KBr166YP3++6JCIiFSBiYqdVW+klaMBkhUVx+xR+fzzz/Gf//wH7u7u+Pzzz+Hh4cDrromIbMBExc6UWpqshhU/gNhzfhxls7eLFy9i+vTpAIA5c+agU6dOgiMiIlIPJip25nS70gqoqFxyoHN+JEnCE088gYKCAnTv3h3PPfec6JCIiFSFiYqdOWtFRaldaUvLgZJy8321JGsN8fXXX+O7776Dm5sbkpOTodXyQHMiouqYqNiZnEuTAXX1Z5hMyveoWF6/pxvg467IkLIpLS3FzJkzAQAvvPACbrvtNrEBERGpEBMVOzt9+jQAIDIy0u7PbTRdf6NWQ0XlYjFQaQJcXYDmzZsrMmb1pclq2EemId58801kZWUhIiICiYmJosMhIlIlJip2VFFRYV2e3Lp1a7s//5VS8y6wGg0QpILt488VmG9b+kGxKQtH2eztjz/+wIIFCwAAixYt4u6zREQ3wUTFjjIzM2EymeDh4SFLhcHSnxLsDWiV2QT2ljIKzLfh/sqNaTk5ubGf8zNr1ixUVFRg6NChGDZsmOhwiIhUi4mKHVmmfSIiIpxiDxURiUpOVaIS1IgrKlu3bsXGjRuh1Wrx3nvv8cBBIqJbYKJiR2fOnAEgz7QPoL4VP5apn1b+yo1pqaioYeqrPkwmE55//nkAwFNPPYWoqCjBERERqRsTFTuyJCpyNNICQLbKNjoTWlFppInKmjVrkJaWBl9fX7zyyiuiwyEiUj0mKnYk54ofQH07sloSlVZNlBvTkqw1xkTFYDDg5ZdfBgC8+OKLCAoKEhwREZH6MVGxI7krKlcsjaQqSFQk6frUj5IVFTX9DGy1bNkynD17FiEhIdb9U4iI6NaYqNiRpaIiV4+Kmk4Nzrtm3iUWAMLtf0j0TVkSlcBGtprXYDBg7ty5AICXXnqJy5GJiOpIaKKyfft2DBs2DKGhodBoNNiwYYPIcBqkpKQEOTk5AJyjR+Vcvvm2mQ/g4abMmCYTkHPVfL+xTf0kJycjMzMToaGhePzxx0WHQ0TUaAhNVEpLS9GlSxcsXrxYZBh2YZn2adKkCfR6eUoMaurPENFIm19m3p0XUMfPoK7Ky8ut1ZQXX3wRHh4egiMiImo8hJ6ANnjwYAwePLjO1xsMBhgMBuvnRUVFcoRVL3JP+1Qagdxr5vuqqKgUmG+VXJpsmfbRewDujejsvuXLlyMjIwMhISGYNGmS6HCIiBqVRtWjMnfuXOj1euuHUif21oUSjbSSBLhogAAVtDeIXJrcmHalNRqNePvttwEAzz//PKspREQ2alSJSmJiIgoLC60flnN11ED2PVSqNZG6quC/mpDt86umvgIbUaLyzTff4NSpU2jSpAmrKURE9dCICuiATqeDTqcTHcYNnTp1CoB8Uz/ZKlrxA4id+mlMFZV33nkHAPD000/D27sRBU5EpBIq+NvcMRw/fhwA0K5dO1me31JRUUN/ClCtoqLgZm/WpcmN5P1+165d2L17N9zd3TF16lTR4RARNUpMVOygsrLSOvUj19kt1hU/KkhUSsuB3KplwiIqKo1lxY+lmvLYY4/Jcpo2EZEzEDr1U1JSgpMnT1o/P3PmDNLT09G0aVOEh4cLjMw2Z8+eRWVlJTw8PNCiRQtZxlDT9vlnqvZQ8fcwr8BRypVGdHLy6dOnrfsCPfvss2KDISJqxIQmKvv27cM999xj/XzWrFkAgPj4eCxfvlxQVLazTPtERUXBxUWeIpW1R0UF1YQzeebb1k2VHbcxVVQ++ugjSJKEQYMGoUOHDqLDISJqtIQmKv369YMkSSJDsIsTJ04AkG/aB1BXM+0pUYmKipK1WykrK8OyZcsAmJtoiYio/tijYgeKJCoqaqYVXVFRezPt2rVrkZubi/DwcAwdOlR0OEREjRoTFTuQe8UPoK7t809XJSqRCiYq1c/5UXtF5cMPPwQAPPHEE3B1dRUcDRFR48ZExQ7krqhIkjorKm0UTFTyrgGmqllCNVdUfvvtN+zZswdubm5ISEgQHQ4RUaPHRKWBDAYDzp07B0C+ikpBGVBhNN8X3aNiMl1f9aNkRcWSqDXxBNxUXKT4+OOPAQCPPPIImjVrJjgaIqLGj4lKA506dQqSJMHX1xfBwcGyjGFZmqz3AHSC9xI+XwSUGwGtC9DST7lxcxrBip9rFcCaNWsAgNvlExHZCROVBqo+7aPRaGQZ44oK91CJaAJoFaxsNIZG2m+OAIWFhYiIiEC/fv1Eh0NE5BCYqDTQsWPHAMjbSHtZRY20p3LNt5EKbp0PqGsfmZtZkWa+jY+Pl20/HSIiZ8N/TRvoyJEjAICOHTvKNoYad6VVemlyjsorKpkFwI/mcykxbtw4obEQETkSJioNpESiYj01WAWJymlBe6hkq/zk5FXp5tVZffv2le0EbSIiZ8REpQFMJpM1UenUqZNs41xW0bSHqERFzRUVSbo+7TN+/HihsRARORomKg2QmZmJ0tJSuLm5oU2bNrKNc0VF2+eL2OwNqFZRUcHP4M9Ss4ATuYCXG/A///M/osMhInIoTFQawFJNadeuHdzc3GQb57JK3qTzrgK5VbvDKrnZG1CtouKl7Lh18eVB8+2DHQAfHxVmUkREjRgTlQY4fPgwAHn7UwD1HEh4PMd828IP8NEpO7YlQVLb1I/JBHxVlaiMuE1sLEREjoiJSgMo0Z8CVGumFfwmbUlU2gUqO64kXU9UAlRWUdmVYd4ET+8BDJJvhToRkdNiotIASqz4MVQCxQbzfdH7qIhKVIoMQKXJfF9ticqXv5tvH+wgftdgIiJHxESlniRJUnRpstbF/Fe7SJZEJUrhRMXSn+LlBnjK1wpks0ojsO6Q+f6oGLGxEBE5KiYq9XT27FkUFxfDzc1NtlOTgZpNpDLt0F9nlkSlvdKJikr7U7afNa9GCvAC+su36IuIyKkxUamn9PR0AOb+FHd3d9nGUcubtNEEnKzaPr9dkLJj51X9DJp6KjvuX1lb1UQ7vKO6T3QmImrMmKjU02+//QYAiI2NlXUctWx0llFg7pdxdwVa+Ss7tlqStepMJuD7o+b7j3QWGwsRkSNjolJPlopK165dZR3H0qOilkbatgGAq8K/NWpc8bM3C7hUAvjpgL6RoqMhInJcTFTqSemKiug3aVErfgAgVyU/g+q+raqmDG4PuHO1DxGRbJio1ENOTg6ysrIAAF26dJF3rKpqgloqKkISFcvUj5oSFfOCLzzYQWwcRESOjolKPVimfdq0aQM/Pz9Zx1JLj8ofV8y3SjfSAtcTlaYqSVT+uAIcyzE30N7PTd6IiGTFRKUeLNM+cvenANUaSQW/SR++bL7tFKz82GrbPv+7qmmfe1oDfoL3tiEicnRMVOrh119/BQD06NFD9rFyVNBMm11iburVaIAOAhKVHJU1037DaR8iIsUwUamHPXv2AABuv/122ceyrPoJEJioWKoprZsA3vJtGXNTeSpKVC6XmFf8AMAwJipERLJjomKjzMxMnD9/Hq6uroiLi5N1LJPp+rRHkMA36UOWaZ9myo8tSeqqqPxwwhxTbCgQKm97EhERgYmKzSzVlJiYGHh7y1vmyC8DTJL5vsj+jMMCE5WScqDCaL4vuk8HAH44br5lEy0RkTKYqNhIyWkfS3+K3kPsFu2Hs823IhIVy8/AQwt4CZh2qs5oMldUAOA++Y53IiKiapio2GjXrl0AlO1PEdlIK0liKypqWvGTmgXkXTMnjreHiY6GiMg5MFGxQVFREVJTUwEAd999t+zjqWEPlcxCoNgAaF2AdgHKj5+rogMJLdWUe9sCWh5CSESkCCYqNti+fTuMRiNat26NiIgI2cdTwx4qv18037YPFLNVvJoOJNxU1Z8yiNM+RESK4SklNti6dSsAYMCAAYqMp4aKStoF821sCzHjq+VAwiulwL7z5vuD2EjrcN5LvSjbcz/TI0S25yZyBqyo2EDpRMXSoyKyopJW9ebcLVTM+Go5kPDHk+Z+nduac1kyEZGSWFGpo6ysLBw8eBAajQb33HOPImOq4UDC3ywVFVGJigqmvwBgS1V/Cqd9HNMzuXJ2R1fK+NxEjo+JSh198803AIDevXsjOFiZfeRFT/1cKgYuFJu3zu8qqHqthgMJJQnYdtp8f0BbcXGQciRJwjUDcNUAlJUDZRWAoaLqfjnQviUQqNeIDpPIKTBRqaP169cDAB5++GHFxswRPPVjmfaJDgR8dGJiUMPy5FN55tVPbq7AHeHi4qBbKy8vR0FBAQoKClBYWGi9X/2jsLAQJSUluHr1KkpLS1FaWmq+f86I0nLgagWst7fy79HA3zrXLS7t/Q1/bUTOjIlKHWRnZ2Pbtm0AFE5UBL9JW6Z9ugqa9gHUsX3+z6fMt7eHid90ztkYDAZkZWUhMzMTly5dQnZ2Ni5fvozs7OxaHyUlJbLE4OZq3nBQ5wp4uFXd57+cRIrh/251sHLlShiNRvTo0QNt2rRRbNwrgqd+UqsO3+smaMUPoI4DCS3TPve0FheDo6qsrMTZs2dx/PhxHD9+HOfOnUNGRgYyMzORkZGBy5cv2/ycfn5+8Pf3v+GHXq+Hj48PvL294eXlZb312DAMXm7mRNS72q2nG+DKJQdEQjFR+QsmkwlLliwBAEyaNEmxca+WA9eqys8immlNJmB3hvl+b0HTHWo4kFCSgJ8tiYpyOarDKS8vx5EjR3DgwAEcPHjQmpicOnUKlZW3bjb19PREWFgYWrRogeDg4Jt+BAQEwM/PD66utu/GV/l7fV8ZEclNFYnK4sWLMX/+fFy6dAldunTBBx98gJ49e4oOC4C5N+XYsWPw9fXFqFGjFBvXUk3RaQEfAdMNx3LM28V7aIFYQY20VysAQ9V7mKg+ncPZ5v8Wnm5Az5ZiYmhsyiuB3y4CezKA9IvAwS+74siRI6iouHHjh6enJ6KiohAVFYXWrVsjPDwcYWFh1tuAgABoNGxcJXJWwhOVf//735g1axY++ugj9OrVCwsXLsSgQYNw7NgxxVbX3My1a9fw8ssvAwBmzpwJPz/lNtCoviutiH+jd50z3/YME7MjLXC9mdjdFfAW1Bti6U+5s5W4n4PaFRuA7WeAnefMVbh9WUBZjSLJAQCAv78/unTpgi5duiA6Ohrt2rVDu3bt0KJFC7i4cH6FiG5M+D+97777LiZNmoQJEyYAAD766CP85z//wbJly/Diiy8Kiys3NxfTp0/HsWPH0Lx5c8yaNUvR8UUvTd5VNe0jcpVLruBkDajWn8JpHyujCdh/Hth6Ethy0pycVJpqXhPgZW4+jmsJdJv+Dbp06YLw8PBGXxkxVAJFBqDCWPVhqnlbbgQqqz9uBExff42KigpUVFSgvLwcFRUVMBqNMBqNMJlMdr81mUyQJKnGB4Baj9nrcVuvvZHG8DVbv0eSJOTk5KBPnz5YuHDhTb+3MdDpdIr+of5nQhOV8vJy7N+/H4mJidbHXFxccO+992L37t21rjcYDDAYDNbPi4qKZIkrKSkJTz/9NADA1dUVy5cvh7+/vyxj3Yzok5N3V1VU7mglZnxA/B4qlUYg5Yz5fj820gIwv1G3fhvILq35eJumwN2R5t+X3uFAu8DryaX2wQeVD1Qmy/cDU7+18Zs+f0SWWKhxOHfuHFavXi06jAYZPXq00NcgNFHJycmB0WhEs2bNajzerFkz/PHHH7Wunzt3Lv75z3/KHle7dubDXDp06IB3330XgwYNsttza1+6eVZe3bWkJLh8PRVBPUZB+5L9fkHqMn5JSQmufhgN4DzuXJgHbZMmdhu/rjEAwNV16+C6chSCOt4N7Us/KR5D5pkz8FjcG9CVocf7OdBqhRcgZVWXn4kWQNvNfWA4fBgDBgzAfffdh4EDB6J168adydX1d9Jj6VLg28fh4uICNzc364e7u3uNz//qcTc3N7i4uMDV1dXutxqNptYHgDo/LvdjN9MYvqbRaLDheF6dvsdYWYHk5xNuOgbVnUa6VT1LZhcuXECLFi2wa9cu9O7d2/r4888/j5SUFPz66681rv9zRaWwsBDh4eHIzMy0a1nKYDDg6tWraGLnN2hbGY1GGAwGeHkpX1KQJAmXLl1CSIjYA9VMJhPKysqE/AwA88/B8ntKZhcvXkRQUJDDJ243YjQaAaBeK4vIMSzef6lO10mSZPNU55TuzesTUqNUVFSEsLAwFBQUQK/X3/Jaof/SBAYGwtXVtdZeCZcvX0bz5rX/g+l0Ouh017dItUz9hIXJeU4HERGR/F4SHYAAxcXF6k5U3N3d0b17d2zduhXDhw8HYP4LeuvWrZg6depffn9oaCgyMzPh6+tr9yY9S7Zn72pNY+Hsrx/gz4Cv37lfP8CfgbO/fkC+n4EkSSguLkZo6F9vfS68djtr1izEx8cjLi4OPXv2xMKFC1FaWmpdBXQrLi4uaNlS3s0t/Pz8nPYXFODrB/gz4Ot37tcP8Gfg7K8fkOdn8FeVFAvhicqoUaNw5coVvPrqq7h06RK6du2KTZs21WqwJSIiIucjPFEBgKlTp9ZpqoeIiIicC7eDvAmdTofXXnutRvOuM3H21w/wZ8DX79yvH+DPwNlfP6COn4HQ5clEREREt8KKChEREakWExUiIiJSLSYqREREpFpMVIiIiEi1mKjcwOLFixEREQEPDw/06tULe/fuFR2SYrZv345hw4YhNDTUfADXhg2iQ1LU3Llz0aNHD/j6+iI4OBjDhw/HsWPHRIelqKSkJMTExFg3eOrduzc2btwoOixh5s2bB41Gg5kzZ4oORRFz5sypdbBgdHS06LAUd/78eYwdOxYBAQHw9PTEbbfdhn379okOSxERERE3PMRyypQpQuJhovIn//73vzFr1iy89tprSEtLQ5cuXTBo0CBkZ2eLDk0RpaWl6NKlCxYvXiw6FCFSUlIwZcoU7NmzB1u2bEFFRQXuu+8+lJaWig5NMS1btsS8efOwf/9+7Nu3D/3798dDDz2Ew4cPiw5Ncampqfj4448RExMjOhRFderUCRcvXrR+/PLLL6JDUlR+fj769OkDNzc3bNy4EUeOHMGCBQuEH1SrlNTU1Br//bds2QIAGDFihJiAJKqhZ8+e0pQpU6yfG41GKTQ0VJo7d67AqMQAIK1fv150GEJlZ2dLAKSUlBTRoQjVpEkT6dNPPxUdhqKKi4ulqKgoacuWLVLfvn2lGTNmiA5JEa+99prUpUsX0WEI9cILL0h33nmn6DBUY8aMGVKbNm0kk8kkZHxWVKopLy/H/v37ce+991ofc3Fxwb333ovdu3cLjIxEKSwsBAA0bdpUcCRiGI1GrFmzBqWlpejdu7focBQ1ZcoUDB06tMa/B87ixIkTCA0NRevWrTFmzBhkZGSIDklR3377LeLi4jBixAgEBwcjNjYWS5YsER2WEOXl5fj8888xceJEux/+W1dMVKrJycmB0Wisdc5Qs2bNcOnSJUFRkSgmkwkzZ85Enz590LlzZ9HhKOrgwYPw8fGBTqfDk08+ifXr16Njx46iw1LMmjVrkJaWhrlz54oORXG9evXC8uXLsWnTJiQlJeHMmTO46667UFxcLDo0xZw+fRpJSUmIiorC5s2b8dRTT2H69On47LPPRIemuA0bNqCgoADjx48XFoMqzvohUqMpU6bg0KFDTjc/DwDt27dHeno6CgsL8dVXXyE+Ph4pKSlOkaxkZmZixowZ2LJlCzw8PESHo7jBgwdb78fExKBXr15o1aoVvvzySyQkJAiMTDkmkwlxcXF46623AACxsbE4dOgQPvroI8THxwuOTllLly7F4MGDERoaKiwGVlSqCQwMhKurKy5fvlzj8cuXL6N58+aCoiIRpk6diu+//x4///wzWrZsKTocxbm7u6Nt27bo3r075s6diy5dumDRokWiw1LE/v37kZ2djW7dukGr1UKr1SIlJQXvv/8+tFotjEaj6BAV5e/vj3bt2uHkyZOiQ1FMSEhIraS8Q4cOTjcFdu7cOfz44494/PHHhcbBRKUad3d3dO/eHVu3brU+ZjKZsHXrVqebn3dWkiRh6tSpWL9+PX766SdERkaKDkkVTCYTDAaD6DAUMWDAABw8eBDp6enWj7i4OIwZMwbp6elwdXUVHaKiSkpKcOrUKYSEhIgORTF9+vSptS3B8ePH0apVK0ERiZGcnIzg4GAMHTpUaByc+vmTWbNmIT4+HnFxcejZsycWLlyI0tJSTJgwQXRoiigpKanxl9OZM2eQnp6Opk2bIjw8XGBkypgyZQpWr16Nb775Br6+vtbeJL1eD09PT8HRKSMxMRGDBw9GeHg4iouLsXr1amzbtg2bN28WHZoifH19a/UkeXt7IyAgwCl6lWbPno1hw4ahVatWuHDhAl577TW4urpi9OjRokNTzDPPPIM77rgDb731FkaOHIm9e/fik08+wSeffCI6NMWYTCYkJycjPj4eWq3gVEHIWiOV++CDD6Tw8HDJ3d1d6tmzp7Rnzx7RISnm559/lgDU+oiPjxcdmiJu9NoBSMnJyaJDU8zEiROlVq1aSe7u7lJQUJA0YMAA6YcffhAdllDOtDx51KhRUkhIiOTu7i61aNFCGjVqlHTy5EnRYSnuu+++kzp37izpdDopOjpa+uSTT0SHpKjNmzdLAKRjx46JDkXSSJIkiUmRiIiIiG6NPSpERESkWkxUiIiISLWYqBAREZFqMVEhIiIi1WKiQkRERKrFRIWIiIhUi4kKERERqRYTFSIiIlItJipEJFy/fv0wc+ZM0WEQkQoxUSEiIiLVYqJCREREqsVEhYgUVVpainHjxsHHxwchISFYsGBBja+vXLkScXFx8PX1RfPmzfH3v/8d2dnZAABJktC2bVu88847Nb4nPT0dGo2mxsnfROQYmKgQkaKee+45pKSk4JtvvsEPP/yAbdu2IS0tzfr1iooKvPHGGzhw4AA2bNiAs2fPYvz48QAAjUaDiRMnIjk5ucZzJicn4+6770bbtm2VfClEpACenkxEiikpKUFAQAA+//xzjBgxAgCQl5eHli1bYvLkyVi4cGGt79m3bx969OiB4uJi+Pj44MKFCwgPD8euXbvQs2dPVFRUIDQ0FO+88w7i4+MVfkVEJDdWVIhIMadOnUJ5eTl69eplfaxp06Zo37699fP9+/dj2LBhCA8Ph6+vL/r27QsAyMjIAACEhoZi6NChWLZsGQDgu+++g8FgsCY+RORYmKgQkWqUlpZi0KBB8PPzw6pVq5Camor169cDAMrLy63XPf7441izZg2uXbuG5ORkjBo1Cl5eXqLCJiIZMVEhIsW0adMGbm5u+PXXX62P5efn4/jx4wCAP/74A7m5uZg3bx7uuusuREdHWxtpqxsyZAi8vb2RlJSETZs2YeLEiYq9BiJSllZ0AETkPHx8fJCQkIDnnnsOAQEBCA4OxssvvwwXF/PfTOHh4XB3d8cHH3yAJ598EocOHcIbb7xR63lcXV0xfvx4JCYmIioqCr1791b6pRCRQlhRISJFzZ8/H3fddReGDRuGe++9F3feeSe6d+8OAAgKCsLy5cuxdu1adOzYEfPmzau1FNkiISEB5eXlmDBhgpLhE5HCuOqHiBqlHTt2YMCAAcjMzESzZs1Eh0NEMmGiQkSNisFgwJUrVxAfH4/mzZtj1apVokMiIhlx6oeIGpUvvvgCrVq1QkFBAd5++23R4RCRzFhRISIiItViRYWIiIhUi4kKERERqRYTFSIiIlItJipERESkWkxUiIiISLWYqBAREZFqMVEhIiIi1WKiQkRERKr1/7DUYhfA6G8wAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from libra_toolbox.tritium.plotting import plot_sample_activity_top\n", "\n", "plot_sample_activity_top(\n", " model, replacement_times=libra_run.relative_times_as_pint, color=\"black\", label=\"From model\"\n", ")\n", "plot_bars(libra_run, index=libra_run.relative_times_as_pint)\n", "\n", "plt.legend(reverse=True)\n", "plt.ylabel(\"Sammple activity (Bq)\")\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "libra-toolbox", "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": "3.12.5" } }, "nbformat": 4, "nbformat_minor": 2 }