{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "(DEMetropolis_comparisons)=\n", "# DEMetropolis and DEMetropolis(Z) Algorithm Comparisons\n", ":::{post} January 18, 2023\n", ":tags: DEMetropolis, gradient-free inference\n", ":category: intermediate, how-to\n", ":author: Michael Osthege, Greg Brunkhorst\n", ":::" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Running on PyMC v0+untagged.9358.g8ea092d\n" ] } ], "source": [ "import time\n", "\n", "import arviz as az\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import pymc as pm\n", "import scipy.stats as st\n", "\n", "print(f\"Running on PyMC v{pm.__version__}\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "az.style.use(\"arviz-darkgrid\")\n", "rng = np.random.default_rng(1234)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Background\n", "For continuous variables, the default PyMC sampler (`NUTS`) requires that gradients are computed, which PyMC does through autodifferentiation. However, in some cases, a PyMC model may not be supplied with gradients (for example, by evaluating a numerical model outside of PyMC) and an alternative sampler is necessary. Differential evolution (DE) Metropolis samplers are an efficient choice for gradient-free inference. This notebook compares the `DEMetropolis` and the `DEMetropolisZ` samplers in PyMC to help determine which is a better option for a given problem. \n", "\n", "The samplers are based on {cite:t}`terBraak2006markov` and {cite:t}`terBraak2008differential` and are described in the notebook [DEMetropolis(Z) Sampler Tuning](DEMetropolisZ_sampler_tuning). The idea behind differential evolution is to use randomly selected draws from other chains (DEMetropolis), or from past draws of the current chain (DEMetropolis(Z)), to make more educated proposals, thus improving sampling efficiency over the standard Metropolis implementation. Note that the PyMC implementation of `DEMetropolisZ` is slightly different than in {cite:t}`terBraak2008differential`, namely, each `DEMetropolisZ` chain only looks into its own history, whereas the {cite:t}`terBraak2008differential` algorithm has some mixing across chains.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this notebook, 10 and 50-dimensional multivariate normal target densities will be sampled with both `DEMetropolis` and `DEMetropolisZ` samplers. Samplers will be evaluated based on effective sample size, sampling time and MCMC chain correlation $(\\hat{R})$. Samplers will also be compared to `NUTS` for benchmarking. Finally, MCMC traces will be compared to the analytically calculated target probability densities to assess potential bias in high dimensions. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Key Take-Aways (TL;DR)\n", "Based on the results in this notebook, use `DEMetropolisZ` for lower dimensional problems ($\\approx10D$), and `DEMetropolis` for higher dimensional problems ($\\approx50D$)\n", "* The `DEMetropolisZ` sampler was more efficient (ESS per second sampling) than `DEMetropolis`.\n", "* The `DEMetropolisZ` sampler had better chain convergence $(\\hat{R})$ than `DEMetropolis`.\n", "* Bias was evident in the `DEMetropolisZ` sampler at 50 dimensions, resulting in reduced variance compared to the target distribution. `DEMetropolis` more accurately sampled the high dimensional target distribution, using $2D$ chains (twice the number of model parameters). \n", "* As expected, `NUTS` was more efficient and accurate than either Metropolis-based algorithms. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Helper Functions\n", "This section defines helper functions that will be used throughout the notebook. " ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### D-dimensional MvNormal Target Distribution and PyMC Model\n", "`gen_mvnormal_params` generates the parameters for the target distribution, which is a multivariate normal distribution with $\\sigma^2$ = `[1, 2, 3, 4, 5]` in the first five dimensions and some correlation thrown in." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def gen_mvnormal_params(D):\n", " # means=zero\n", " mu = np.zeros(D)\n", " # sigma**2 = 1 to start\n", " cov = np.eye(D)\n", " # manually adjust the first 5 dimensions\n", " # sigma**2 in the first 5 dimensions = 1, 2, 3, 4, 5\n", " # with a little covariance added\n", " cov[:5, :5] = np.array(\n", " [\n", " [1, 0.5, 0, 0, 0],\n", " [0.5, 2, 2, 0, 0],\n", " [0, 2, 3, 0, 0],\n", " [0, 0, 0, 4, 4],\n", " [0, 0, 0, 4, 5],\n", " ]\n", " )\n", " return mu, cov" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`make_model` accepts the multivariate normal parameters `mu` and `cov` and outputs a PyMC model. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def make_model(mu, cov):\n", " with pm.Model() as model:\n", " x = pm.MvNormal(\"x\", mu=mu, cov=cov, shape=(len(mu),))\n", " return model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Sampling\n", "`sample_model` performs MCMC, returns the trace and the sampling duration. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def sample_model(\n", " model, D, run=0, step_class=pm.DEMetropolis, cores=1, chains=1, step_kwargs={}, sample_kwargs={}\n", "):\n", " # sampler name\n", " sampler = step_class.name\n", " # sample model\n", "\n", " # if nuts then do not provide step method\n", " if sampler == \"nuts\":\n", " with model:\n", " step = step_class(**step_kwargs)\n", " t_start = time.time()\n", " idata = pm.sample(\n", " # step=step,\n", " chains=chains,\n", " cores=cores,\n", " initvals={\"x\": [0] * D},\n", " discard_tuned_samples=False,\n", " progressbar=False,\n", " random_seed=2020 + run,\n", " **sample_kwargs\n", " )\n", " t = time.time() - t_start\n", "\n", " # signature for DEMetropolis samplers\n", " else:\n", " with model:\n", " step = step_class(**step_kwargs)\n", " t_start = time.time()\n", " idata = pm.sample(\n", " step=step,\n", " chains=chains,\n", " cores=cores,\n", " initvals={\"x\": [0] * D},\n", " discard_tuned_samples=False,\n", " progressbar=False,\n", " random_seed=2020 + run,\n", " **sample_kwargs\n", " )\n", " t = time.time() - t_start\n", "\n", " return idata, t" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`calc_mean_ess` calculates the mean ess for the dimensions of the distribution." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def calc_mean_ess(idata):\n", " return az.ess(idata).x.values.mean()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`calc_mean_rhat` calculates the mean $\\hat{R}$ for the dimensions of the distribution." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def calc_mean_rhat(idata):\n", " return az.rhat(idata).x.values.mean()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`sample_model_calc_metrics` wraps the previously defined functions: samples the model, calculates the metrics and packages the results in a Pandas `DataFrame`" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def sample_model_calc_metrics(\n", " sampler,\n", " D,\n", " tune,\n", " draws,\n", " cores=1,\n", " chains=1,\n", " run=0,\n", " step_kwargs=dict(proposal_dist=pm.NormalProposal, tune=\"scaling\"),\n", " sample_kwargs={},\n", "):\n", " mu, cov = gen_mvnormal_params(D)\n", " model = make_model(mu, cov)\n", " idata, t = sample_model(\n", " model,\n", " D,\n", " step_class=sampler,\n", " cores=cores,\n", " chains=chains,\n", " run=run,\n", " step_kwargs=step_kwargs,\n", " sample_kwargs=dict(sample_kwargs, **dict(tune=tune, draws=draws)),\n", " )\n", " ess = calc_mean_ess(idata)\n", " rhat = calc_mean_rhat(idata)\n", " results = dict(\n", " Sampler=sampler.__name__,\n", " D=D,\n", " Chains=chains,\n", " Cores=cores,\n", " tune=tune,\n", " draws=draws,\n", " ESS=ess,\n", " Time_sec=t,\n", " ESSperSec=ess / t,\n", " rhat=rhat,\n", " Trace=[idata],\n", " )\n", " return pd.DataFrame(results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`concat_results` concatenates the results and does a some data wrangling and calculating. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def concat_results(results):\n", " results_df = pd.concat(results)\n", "\n", " results_df[\"Run\"] = results_df.Sampler + \"\\nChains=\" + results_df.Chains.astype(str)\n", "\n", " results_df[\"ESS_pct\"] = results_df.ESS * 100 / (results_df.Chains * results_df.draws)\n", " return results_df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`plot_comparison_bars` plots the ESS and $\\hat{R}$ results for comparison. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def plot_comparison_bars(results_df):\n", " fig, axes = plt.subplots(1, 3, figsize=(10, 5))\n", " ax = axes[0]\n", " results_df.plot.bar(y=\"ESSperSec\", x=\"Run\", ax=ax, legend=False)\n", " ax.set_title(\"ESS per Second\")\n", " ax.set_xlabel(\"\")\n", " labels = ax.get_xticklabels()\n", "\n", " ax = axes[1]\n", " results_df.plot.bar(y=\"ESS_pct\", x=\"Run\", ax=ax, legend=False)\n", " ax.set_title(\"ESS Percentage\")\n", " ax.set_xlabel(\"\")\n", " labels = ax.get_xticklabels()\n", "\n", " ax = axes[2]\n", " results_df.plot.bar(y=\"rhat\", x=\"Run\", ax=ax, legend=False)\n", " ax.set_title(r\"$\\hat{R}$\")\n", " ax.set_xlabel(\"\")\n", " ax.set_ylim(1)\n", " labels = ax.get_xticklabels()\n", "\n", " plt.suptitle(f\"Comparison of Runs for {D} Dimensional Target Distribution\", fontsize=16)\n", " plt.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`plot_forest_compare_analytical` plots the MCMC results for the first 5 dimensions and compares to the analytically calculated probability density. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def plot_forest_compare_analytical(results_df):\n", " # extract the first 5 dimensions\n", " summaries = []\n", " truncated_traces = []\n", " dimensions = 5\n", " for row in results_df.index:\n", " truncated_trace = results_df.Trace.loc[row].posterior.x[:, :, :dimensions]\n", " truncated_traces.append(truncated_trace)\n", " summary = az.summary(truncated_trace)\n", " summary[\"Run\"] = results_df.at[row, \"Run\"]\n", " summaries.append(summary)\n", " summaries = pd.concat(summaries)\n", "\n", " # plot forest\n", " axes = az.plot_forest(\n", " truncated_traces, combined=True, figsize=(8, 3), model_names=results_df.Run\n", " )\n", " ax = axes[0]\n", "\n", " # plot analytical solution\n", " yticklabels = ax.get_yticklabels()\n", " yticklocs = [tick.__dict__[\"_y\"] for tick in yticklabels]\n", " min, max = axes[0].get_ylim()\n", " width = (max - min) / 6\n", " mins = [ytickloc - (width / 2) for ytickloc in yticklocs]\n", " maxes = [ytickloc + (width / 2) for ytickloc in yticklocs]\n", " sigmas = [np.sqrt(sigma2) for sigma2 in range(1, 6)]\n", " for i, (sigma, min, max) in enumerate(zip(sigmas, mins[::-1], maxes[::-1])):\n", " # scipy.stats.norm to calculate analytical marginal distribution\n", " dist = st.norm(0, sigma)\n", " ax.vlines(dist.ppf(0.03), min, max, color=\"black\", linestyle=\":\")\n", " ax.vlines(dist.ppf(0.97), min, max, color=\"black\", linestyle=\":\")\n", " ax.vlines(dist.ppf(0.25), min, max, color=\"black\", linestyle=\":\")\n", " ax.vlines(dist.ppf(0.75), min, max, color=\"black\", linestyle=\":\")\n", " if i == 0:\n", " ax.text(dist.ppf(0.97) + 0.2, min, \"Analytical Solutions\\n(Dotted)\", fontsize=8)\n", "\n", " # legend\n", " labels = ax.get_legend().__dict__[\"texts\"]\n", " labels = [label.__dict__[\"_text\"] for label in labels]\n", " handles = ax.get_legend().__dict__[\"legendHandles\"]\n", " ax.legend(\n", " handles[::-1],\n", " labels[::-1],\n", " loc=\"center left\",\n", " bbox_to_anchor=(1, 0.5),\n", " fontsize=\"medium\",\n", " fancybox=True,\n", " title=\"94% and 50% HDI\",\n", " )\n", " ax.set_title(\n", " f\"Comparison of MCMC Samples and Analytical Solutions\\nFirst 5 Dimensions of {D} Dimensional Target Distribution\"\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`plot_forest_compare_analytical_dim5` plots the MCMC results for the fift 5 dimension and compares to the analytically calculated probability density for repeated runs for the bias check. " ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "def plot_forest_compare_analytical_dim5(results_df):\n", " # extract the 5th dimension\n", " summaries = []\n", " truncated_traces = []\n", " dimension_idx = 4\n", " for row in results_df.index:\n", " truncated_trace = results_df.Trace.loc[row].posterior.x[:, :, dimension_idx]\n", " truncated_traces.append(truncated_trace)\n", " summary = az.summary(truncated_trace)\n", " summary[\"Sampler\"] = results_df.at[row, \"Sampler\"]\n", " summaries.append(summary)\n", " summaries = pd.concat(summaries)\n", " cols = [\"Sampler\", \"mean\", \"sd\", \"hdi_3%\", \"hdi_97%\", \"ess_bulk\", \"ess_tail\", \"r_hat\"]\n", " summary_means = summaries[cols].groupby(\"Sampler\").mean()\n", "\n", " # scipy.stats.norm to calculate analytical marginal distribution\n", " dist = st.norm(0, np.sqrt(5))\n", " summary_means.at[\"Analytical\", \"mean\"] = 0\n", " summary_means.at[\"Analytical\", \"sd\"] = np.sqrt(5)\n", " summary_means.at[\"Analytical\", \"hdi_3%\"] = dist.ppf(0.03)\n", " summary_means.at[\"Analytical\", \"hdi_97%\"] = dist.ppf(0.97)\n", "\n", " # plot forest\n", " colors = plt.rcParams[\"axes.prop_cycle\"].by_key()[\"color\"]\n", " axes = az.plot_forest(\n", " truncated_traces,\n", " combined=True,\n", " figsize=(8, 3),\n", " colors=[colors[0]] * reps + [colors[1]] * reps + [colors[2]] * reps,\n", " model_names=results_df.Sampler,\n", " )\n", " ax = axes[0]\n", "\n", " # legend\n", " labels = ax.get_legend().__dict__[\"texts\"]\n", " labels = [label.__dict__[\"_text\"] for label in labels]\n", " handles = ax.get_legend().__dict__[\"legendHandles\"]\n", " labels = [labels[reps - 1]] + [labels[reps * 2 - 1]] + [labels[reps * 3 - 1]]\n", " handles = [handles[reps - 1]] + [handles[reps * 2 - 1]] + [handles[reps * 3 - 1]]\n", " ax.legend(\n", " handles[::-1],\n", " labels[::-1],\n", " loc=\"center left\",\n", " bbox_to_anchor=(1, 0.5),\n", " fontsize=\"medium\",\n", " fancybox=True,\n", " title=\"94% and 50% HDI\",\n", " )\n", " ax.set_title(\n", " f\"Comparison of MCMC Samples and Analytical Solutions\\n5th Dimension of {D} Dimensional Target Distribution\"\n", " )\n", "\n", " # plot analytical solution as vlines\n", " ax.axvline(dist.ppf(0.03), color=\"black\", linestyle=\":\")\n", " ax.axvline(dist.ppf(0.97), color=\"black\", linestyle=\":\")\n", " ax.text(dist.ppf(0.97) + 0.1, 0, \"Analytical Solution\\n(Dotted)\", fontsize=8)\n", " return summaries, summary_means" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Experiment #1. 10-Dimensional Target Distribution" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "All traces are sampled with `cores=1`. Surprisingly, sampling was slower using multiple cores rather than one core for both samplers for the same number of total samples.\n", "\n", "`DEMetropolisZ` and `NUTS` are sampled with four chains, and `DEMetropolis` are sampled with more based on {cite:t}`terBraak2008differential`. `DEMetropolis` requires that, at a minimum, $N$ chains are larger than $D$ dimensions. However, {cite:t}terBraak2008differential recommends that $2D\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC Runs for 10-Dimensional Experiment
 samplertunedrawschainscores
0DEMetropolisZ500005000041
1DEMetropolis2000020000101
2DEMetropolis1000010000201
3DEMetropolis66666666301
4nuts2000200041
\n" ], "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# dimensions\n", "D = 10\n", "# total samples are constant for Metropolis algorithms\n", "total_samples = 200000\n", "samplers = [pm.DEMetropolisZ] + [pm.DEMetropolis] * 3 + [pm.NUTS]\n", "coreses = [1] * 5\n", "chainses = [4, 1 * D, 2 * D, 3 * D, 4]\n", "# calculate the number of tunes and draws for each run\n", "tunes = drawses = [int(total_samples / chains) for chains in chainses]\n", "# manually adjust NUTs, which needs fewer samples\n", "tunes[-1] = drawses[-1] = 2000\n", "# put it in a dataframe for display and QA/QC\n", "pd.DataFrame(\n", " dict(\n", " sampler=[s.name for s in samplers],\n", " tune=tunes,\n", " draws=drawses,\n", " chains=chainses,\n", " cores=coreses,\n", " )\n", ").style.set_caption(\"MCMC Runs for 10-Dimensional Experiment\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "tags": [ "hide-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 50_000 tune and 50_000 draw iterations (200_000 + 200_000 draws total) took 123 seconds.\n", "Population sampling (10 chains)\n", "DEMetropolis: [x]\n", "C:\\Users\\greg\\Documents\\CodingProjects_ongoing\\pymc\\pymc\\pymc\\sampling\\population.py:84: UserWarning: DEMetropolis should be used with more chains than dimensions! (The model has 10 dimensions.)\n", " warn_population_size(\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 10 chains for 20_000 tune and 20_000 draw iterations (200_000 + 200_000 draws total) took 142 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 10_000 tune and 10_000 draw iterations (200_000 + 200_000 draws total) took 147 seconds.\n", "Population sampling (30 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 30 chains for 6_666 tune and 6_666 draw iterations (199_980 + 199_980 draws total) took 153 seconds.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 2_000 tune and 2_000 draw iterations (8_000 + 8_000 draws total) took 59 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n" ] } ], "source": [ "results = []\n", "run = 0\n", "for sampler, tune, draws, cores, chains in zip(samplers, tunes, drawses, coreses, chainses):\n", " if sampler.name == \"nuts\":\n", " results.append(\n", " sample_model_calc_metrics(\n", " sampler, D, tune, draws, cores=cores, chains=chains, run=run, step_kwargs={}\n", " )\n", " )\n", " else:\n", " results.append(\n", " sample_model_calc_metrics(sampler, D, tune, draws, cores=cores, chains=chains, run=run)\n", " )\n", " run += 1" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Results of MCMC Sampling of 10-Dimensional Target Distribution
 SamplerDChainsCorestunedrawsESSTime_secESSperSecrhatESS_pct
0DEMetropolisZ104150000500006296.480000127.65000049.3300001.0000003.150000
1DEMetropolis1010120000200003492.280000147.46000023.6800001.0000001.750000
2DEMetropolis1020110000100005537.930000156.31000035.4300001.0000002.770000
3DEMetropolis10301666666665657.900000166.25000034.0300001.0100002.830000
4NUTS1041200020007731.26000072.360000106.8500001.00000096.640000
\n" ], "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results_df = concat_results(results)\n", "results_df = results_df.reset_index(drop=True)\n", "cols = results_df.columns\n", "results_df[cols[~cols.isin([\"Trace\", \"Run\"])]].round(2).style.set_caption(\n", " \"Results of MCMC Sampling of 10-Dimensional Target Distribution\"\n", ")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_comparison_bars(results_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`NUTs` is the most efficient. `DEMetropolisZ` is more efficient and has lower $\\hat{R}$ than `DEMetropolis`. " ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "image/png": 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Oz89P+uOPPzSO/fvvv1LJkiUlpVIprVmzRpYlOjpamjJliqRUKqVy5cpJr1690sjXrVs3uZ6nTZsmy6VSqaS5c+dKSqVSql69uhQXF5ekTnSxadMmSalUSmXLlpXOnj0rH3/9+rXUqVMnSalUSu3bt0+Sb8yYMZJSqZR27dqV6mupUb8vV65ckR4+fCgplUqpT58+GmkmTpwoKZVK6eTJk9KLFy8kpVIpKZVKjTRr166VlEql1LJlyzTLIEn/vWP16tWTJEmSvLy8JKVSKf35559ymqioKMnDw0OqVq2aFBcXJy1btkx+1olp2rSppFQqpQ0bNnyWLMmhfg5ly5aVVq1aJfn7+6cqX2BgoHTw4MEk7+Tr16+lIUOGSEqlUlqyZEmSfFmtPWt79pIkSfPmzZOUSqXUqlUr6d9//5WPR0ZGyu2oTZs2GnmaNWsmy5e4nahUKunixYvSsWPHtNalNtKjfletWiXLERMTI40cOVJnm1P3wa1bt5aeP38uHz9//rxUtmxZydXVVVIqldLFixdTfQ9qRo8eLSmVSmnKlCnyMbUs06ZN05pn165d8n00adJEevz4sXzu+vXrkoeHh6RUKqVTp05p5Pvw4YO0e/duKTQ0VOP4+/fv5b507NixSa6nrc+Jj4+XateuLSmVSunOnTtJ8rx9+1YqWbKk5OrqqnE99fvYrVs3nXWi/iYsXrxY43hQUJBUrlw5SalUSj///LNGufHx8dKJEyeSvEef801S1++nfU1ynDt3Tm4vPXv2lE6ePClFRESkmE+lUklt2rSR6+TNmzfyuVOnTkllypRJtl1/Wo8p1a+ub6kk6W7vKZUdEREhvws//fST9PHjR/nc7t27pRIlSsjflMSon7Orq6vUtWtX6eXLl/K5Y8eOyfn8/Pzk48HBwZKLi4tUrlw5ydfXV6O8qKgoycfHR7p7967OexAIMoJss7KiNr9IyfxLF+oVgC5dushmMZAwWzN37lysra0JCgqSzQU+pWbNmvTu3VteicidO7cc0ePkyZO0b99eNi+AhJmUfv36AXDmzBmtZcbFxTFkyBAqV64sH7O3t5fDax45ckRj5h8SQsx+6hRqaGhI+/btadKkCc+ePdNp7mFgYMCvv/7Kd999Jx9LaUZHveTfq1evJKsATk5OdOzYUePYunXriIuLo27duvTr10+uLyMjI3755ReKFy/Ox48f2bp1q9brOTk5MWHCBFkuPT09fvrpJ2xtbXn9+nWy4X0TI0kSa9euBWDo0KFUq1ZNPmdra8uiRYtQKBTcvHkzWdOUL6FYsWKULFmSCxcu8Pr1awBiYmI4dOgQefLk0ZDpU770ff8U9cpJ4tWpY8eOERYWRrNmzXRGLMsIWRIzefJkrKysCA8PZ/78+TRo0IDKlSvz/fffs2bNGp3mmQ4ODjRu3DjJO2lra4u3tzcKhSJZn4Ss0p61ERISwoYNG7CwsGDFihUaJnImJiZMmjQJd3d3bt++ja+vr3zO398fS0tLunTpovE89fT0qFSpUpr2UPrS+q1evTr9+/eX5VAoFIwfPx4jIyNu3rzJ+/fv5bQBAQEcPXoUAC8vL41ISFWqVGHo0KGfbQqWeGWzWbNm8nH1sz1w4ECyZcfFxTFnzhwcHR3lY2XKlKF9+/YAnD59WiN9rly5aN26NVZWVhrHc+fOzaRJk8ifPz9//fWXVtObT9HX16dVq1aA9tWVP//8k7i4ODw9PZNc73NZs2YNHz9+pEqVKsyZM0ejXH19fWrXrp3kPfqSb1JaqFq1qvy9uXDhAv3796d8+fK0aNGCX375hRMnThAfH58k34ULF7h9+zZGRkYsWLCAvHnzyudq1qzJoEGDAFi7dm2Grq58CT4+Pjx//py8efPi5eWlYWbbunVruV60WTpAwrd/3rx5GtE+PT09qVu3LqDZpz19+hSVSkXlypUpV66cRjnGxsY0bdo02TD4AkFGkG2UlfDwcACddvUp5VV3ltpsQU1NTWVTm3Pnzmkto127dkmOJR5EaDtfsmRJANke9VMUCoXWfC4uLpQrVw5Jkjh79myS848ePWLx4sUMHjyY7t2707lzZzp37syVK1eAhGVybVStWjXNoYnVA4fDhw+nqiNX15+2etbT05OP66rntm3bJjFNUygUsr1vagZ7kFBHL168wNjYWKsZlZ2dnWxOqEuW9KBly5bEx8fLJjgnTpzgw4cPNG3aFEND3cH4vuR914baNvr8+fOyOVJqTMASy5IR+xa5uLjg4+NDr1695EFEaGgop0+fZt68edSvX5+FCxeiUqmS5FWpVBw9epSpU6fSr18/unTpQufOnenduzd6enr4+/snMXtTk5Xa86ecOnWKmJgYqlevrjGxoEY9aIQEvwQ1+fPn58OHD+n2Pn9J/aoH84lR74UBmu347NmzSJJEhQoVKF68eJJ87dq1Q6FQfNY9/P3330RERODg4KBhhlOtWjVsbGwIDQ3VqXxCwjvh7u6e5Lj6mK534cKFC8yaNYv+/fvTtWtXuY/++PEjkZGRBAQEpEr+Nm3aoKenh4+PTxKlSq3ApOdeKseOHQOgb9++ador6XO/SWll2rRpLFmyhIoVK2JgYEBcXBz3799n27ZtDBgwgJYtWyaZ0FK3uUaNGmFra5ukzE6dOmFkZERQUJAcCTKrob6H9u3ba51gVPspXb9+XasvVY0aNbT2Jer3+FNzaEgwO3v+/PmXCy8QpAPZJnSxeoZP18cxOdQzBUZGRjpDVRYrVgwgifOgmkKFCiU5ljjamLbz6hj26sHep3z33Xc6HZGdnJy4evVqEnlWrVrFokWLtA7e1CSetUxM0aJFdebRRdeuXdm7dy/Lly9n3759VK9enfLly1OpUqUkis+HDx9kB1K1zfmnfE49A7IfiS7H3k9Rl58/f36dg+yUZEkPmjZtire3N/v27aN3797yykbi1T1tfMn7rosWLVowd+5cfHx8aN68OWfOnKF48eIpOrebm5vz4cOHVNd9WrG1tWXcuHGMGzeOR48e8c8//3DhwgWOHz/Ohw8fWLlyJQqFQsNH4MOHD/Tv31/en0UXHz580KrwZZX2rI0HDx4ACYOFzp07a02jVjgTO/z37NmTadOm0adPH1xdXalatSrlypWjQoUKqQp4kJiMqF9IaMdPnjzReJfUdaKrf7KwsMDOzk6nYpAcaoW8adOmGoNvQ0NDGjduzObNm9m3b5/OVSdd3wv1u/LpuxATE8Pw4cPllSJdpDbgQsGCBalYsSKXLl3i9OnT8kz4vXv3uHfvHra2tlpDo38OYWFh8vtUpkyZVOf7km/S59CgQQMaNGhAWFgYt27d4saNG5w4cYJbt27x8OFDevfujY+Pj/yM1O+Xur//FAsLC/Lnz09AQAD+/v46v12ZSUr3UKRIERQKBbGxsTx9+jTJykdK73Hi9mhnZ0ejRo04dOgQDRo0oFKlSlSsWJFy5cpRpkyZZCfZBIKMItusrKgHxp/zwVJ/UGxsbHTOFqlndXUNRLRFQEpclrYPdkozU5+GXtR2LrE8V65cYcGCBejp6TFy5EgOHDjA9evXuXfvHvfv32fAgAEAOk0MPmdmvESJEvz+++9Ur16dV69esW3bNkaPHk2tWrXo27evRnSvxB2erntLqZ51rSSoV1tSu0yvLj+5Ok5JlvTA1taWKlWqcPfuXa5cucLp06cpWrSo1tnaxHzJ+66L5s2bo6+vz/79+zl48CBxcXEpKk0ZJYsunJycaNWqFV5eXhw5ckQ2qVq3bh0xMTFyutmzZ3P9+nUcHR1ZsmQJp0+f5p9//uH+/fvcv39fllmXiU9WaM+6+PjxIwAvXrzg2rVrWv+pZ+YTO/t37doVLy8vXFxcuHPnDmvWrGHAgAFUrVqVSZMmyeWmhi+t37S0Y3W/kVyo+cSmO6nl9evXsolnYhMwNWpTsBMnTuisG119pq7AJKtXr+bo0aPY2tri5eXF8ePHNepNvbqTGjMwNWpHe7UzPfy3qtK8efNkTTjTQuJ3M1euXKnK86XfpC/BwsKCqlWr8uOPP7Jjxw5+/fVX9PX1CQ4OZtu2bXK61LxfaWmfmYH6HnT1MXp6ejoVaEj5Pf70u+rt7c3gwYOxsbHh7NmzLFiwgK5du1KjRg3WrVuXrGIqEGQE2UZFLlu2LJs3b+b69evExcWlSbtXz1KHhIQgSZLWQYc6Qouu6EwZQXJhLNXnEsujthHv27cv/fv3T5Ino8IJlilThnXr1hEeHs61a9e4dOkSPj4+nD17Vp7Fyp07t0aHGBwcTL58+ZKU9bXqWV1+chGYvpYsLVu25OzZs/z888/ExsamaHYFCe87JOwu/+7du3SxSbezs6Ny5cqcP3+ekJAQ9PX1U6WslC1blocPH3LlyhV69uz5xXKkFmtrayZNmkTTpk2JiIjAz8+PkiVLEhcXJ2+ctnz58iQz8nFxcamOuJSepLU960LdjgYMGMDw4cPTJEOrVq1o1aoVb9684cqVK5w7d46DBw+yfft23rx5w8qVK1Ms42vXr/p+k6u/tERSU/Pnn3/KPgzJvefR0dEcOnRIq+na51wTEpQ9bSsen9NHN2zYkOnTp3PixAlCQ0PJlSuX7FuZniZgid/Njx8/pkphyaxvkjYaNWrEX3/9xaFDhzSivKXl/UpN+1SPH3RNnKXnarga9T3oageSJKWpj0kJY2NjhgwZwpAhQ3j06BG+vr6cOHGCU6dOyfvY9O3b94uvIxCklmyzslKrVi3MzMwIDg7m8OHDacpbqFAh9PX1iYmJ0enz4OfnByQsp34tXrx4oXMmR71ikVieoKAg4L+B7Kekl12wLszNzalRowajRo3ir7/+olChQrx69Up2Ms2dO7c8u6NrP5WvVc/q8pOr468lS/369TEzM+P58+fo6elpOG7ronTp0jg4OBAXF8f27dvTTRb1oO358+dUqFBBqx3zpzRp0gRIcDz/2jbMic0X1LP4ISEhREREYGVlpdV06OHDh1odbTOatLZnXahNPb5kjwpbW1uaNGnCzJkz2bFjB/r6+pw4cUIO9JAcX7t+1XXyaShmNeHh4Z816FWbXObOnZu8efNq/acekKc1LLoukuujQ0NDte7TkxImJiY0adKE2NhYDhw4wOnTp3n79i1ubm5afXzS4muSGAsLC7k/SK1DfGZ/kz5F3V8kXvFTv1/q/v5TwsLC5EAeqWmf6lVDXcpPav2R0kJK9+Dv709sbCwGBgY6TTA/F3UgnZUrVzJ58mSAdP0mCQSpIdsoK7lz55ads2fNmpWiScrVq1e5du0akDDIVnem6o0lExMVFcWOHTuAhCg2X4vY2Fh27tyZ5PiDBw/w9fVFT09PI2KU2rFO2+zK2bNnv+qHwdTUVI7nn3gApK4/bfUsSRK///67RrqMwsnJCXt7e6Kjo+Vnm5hXr17JSm9Gy2JqakqfPn2oUqUKHTt2lJ2Mk8PAwIAffvgBSJjdvnPnTrLpHz16xIkTJ1Ist0GDBlSvXp0qVarITpkpUaVKFcqWLUtsbCxjxozRuc+Imq1btxIWFpZiuXFxcSnasqvbsL6+vjwQUZtwhYWFad3rQx0F7muT1vasi1q1aqFQKDh9+nS6+FMVK1ZMHpSnRln52vWrbn9XrlzROhjbsWNHmqOBqc2Q9PT02L17N+fOndP6T903+Pr6ygPvL0Fdd9r66N9+++2zlTx14IY9e/Yk2VtFlwzJ7YOji3r16gEJsqaGr/lNSs3qmtrHKrHSoV7hOnTokNbNVLdt20ZMTAwODg6p8utU90PPnj0jNDQ0yXltfYCaz3026jayY8cOrf2v+nvr4eGRIYFQ1Kh9mVLTjwgE6Um2UVYABg8eTNmyZXn79i2dOnVi7969SRrukydPmDp1Kj169NCY+fj++++BhIFU4pCbYWFh/Pzzz4SEhODg4EDTpk2/zs2Q4OS5ZMkSjYg+L1++ZMyYMUDCwDLxLIk6jODq1as1Vohu3brF+PHjU7WxVFqZPHkyBw8eTLK0feXKFdkeXB0lCaBPnz4YGhpy7Ngx1q9fL9u2xsTEMHPmTB48eECuXLl0Og6nF3p6evIy9ZIlSzTCE799+5YRI0YQGxtLmTJlNELNZhRDhgxhw4YNTJ06NdV5OnbsSMOGDYmMjKRHjx5s2rQpiRLw4sULFi5cSNu2bVM1o2dubs66devYsGGDPDBJDXPnzsXKyorLly/TpUsXLl26pGG3rFKp8PX1pW/fvkyZMiVVNs0RERF4enri7e3N/fv3NcwqJEnixIkTjB07FkjYkFK9apc7d26KFy9OXFwcs2bNkn1Z4uPjWb16NQcPHvzs6FFfQlrbsy7s7Ozo2bMnsbGx9O3bN8mmepIkcevWLSZPniz3A2FhYQwfPjzJc4mPj2fjxo28f/8eMzMzjRC8uvja9Vu4cGHq1q2LJEmMGTNGYxXl0qVLLF26NM3XU6+UeHh46HQuBnB0dMTd3R1JkmRn/C9B3UfPmTNHXmWT/n838PXr1392H12qVCmUSiW3b9/m2LFjKBQKnd8qdYhxPz+/ZE2ftNG3b19y5crFuXPnGD9+vMZkgkql4tSpUxqTIl/zm7Ry5Uq6dOmCj49Pkn7w9evX/PLLL/KkgDrkMyRsiuvu7k5MTAwjRozQUHrOnj3L0qVLgYQxQmpWpaysrChVqhQxMTHMmTNHVqTV7SO5iH/qdzFxH5EamjVrhr29PW/fvmXs2LEaK7j79u2TfXTU45wv4cKFC3h5eSWZOAgPD5cnKlxdXb/4OgJBWsg2PiuQsFfHunXrGDduHIcPH2bMmDFMnjyZQoUKYWxszOvXr+Vl9u+++05jYFCnTh369+/P6tWrGTVqFPPnzydPnjw8fvyYiIgILC0tWbRokVbH24yibNmymJub0717d4oUKYKZmRkPHjwgLi6OggULMmnSJI30HTt2ZOvWrTx9+pTGjRvj6OhIbGwsT548oVixYjRp0iTVM2Kp5caNG/zxxx8YGhpSuHBhzM3NCQ4OlmchW7RooTHYL1GiBBMmTGDatGl4eXmxbt06OdLKhw8fMDIyYt68eVpDSKY3Xbt25fr163Jo3MKFC2NhYcGDBw+IjY3F3t6eefPmZbgcX8KCBQuYOXMmW7duZcaMGXh5eVGoUKEkz8HKykoO75wRFCxYkG3btjFkyBBu375Njx49sLKywt7eHkmSeP78uTywKV26dKrakZ6eHmFhYaxbt45169ZhaWmJg4MDKpWKFy9eyOUplUqmTZumkXfEiBH8+OOPbNu2jcOHD1OgQAGCgoIIDQ3lxx9/ZN++fekyU54W0tqek2P48OG8fv2a/fv306NHD2xtbcmfP79syqoerKhXx1QqFQcPHuTgwYOYmZlRqFAhDA0N5TrR09Nj/PjxqbZn/9r1O3nyZO7du8ft27epV68exYsXJyIiAn9/f2rXrk14eLgcBjclVCqV7NORGv+wFi1a8M8//7Bv3z4GDhz4RfcxZMgQzp8/z/Hjx6lZsyaFCxfmzZs3vH79mpYtW/LixYs0D1TVtGnThjlz5hAXF0fDhg11+rHZ2NhQuXJlLl68SL169ShWrBjGxsbkzZuXhQsXJnsNe3t7OQTxrl272L9/P05OTqhUKgIDA4mIiGDw4MHUqVMH+LrfJD09Pa5evcrVq1fR19enUKFC5M6dm5CQEF6+fElcXBwGBgaMHTsWNzc3jXzz58+nR48eXL58mdq1a1O8eHHCwsLkCZ6WLVvSqVOnVMsyatQo+vTpw969ezl+/DiFChUiMDCQsLAwxo0bx/Tp07Xma9y4MQ8fPmTAgAE4OzvLUfoWLFiQ7DfR1NSURYsW0bdvXw4ePMjJkycpWrQowcHBsgnbwIEDqVWrVqrvQRfh4eGsX7+e9evXY2Njg729PXFxcQQEBBAZGUmuXLkYN27cF19HIEgL2WplBRJmhhcvXszmzZtp164d3333HYGBgdy7dw9JkqhduzYzZ87k8OHDspmSmpEjR7Jy5UqqVatGREQE9+/fx9ramk6dOrFv3z5KlSr1Ve9FT0+PpUuXMmTIECRJws/PD2trazp37sz27duTdF4WFhZs2bKFVq1aYWFhwZMnT4iNjaV3795s27YtQxzFx40bR48ePXB2diY0NJS7d+8CCcvSK1askJ3tEtOlSxc2b95MvXr1UKlU3Lt3DxMTE1q0aMGePXvkPSIyGj09PebNm4eXlxfly5cnODiYhw8f4uDgQN++fdm9e3eys65ZAUNDQyZPnszevXvp1q0bRYoU4fXr19y9e5eoqCiqVKnChAkT+Pvvv6lSpUqGylKkSBH27t3LvHnzaNCgAaampjx69IgnT55gaWlJ8+bNWbNmDdu2bcPIyCjF8nLlysXhw4cZP368vHISEBDAo0ePUCgUVKtWjSlTprBr164kbcHT05M1a9ZQtmxZoqKiePLkCYULF2bu3Ln89NNPGVUFyZLW9pwchoaGzJ07l9WrV8srYHfv3uXNmzcUKVKEbt26sWnTJnmlxNzcHG9vb1q2bMl3331HUFAQfn5+WFpa0qJFC/bu3ZsmB/KvXb92dnbs3LmTTp06YWVlJc/qDh06lKVLl6bJD0O9CatCoaBRo0YpplfvefTkyRMNx+zPwc3Njc2bN1OtWjVUKhVPnjwhT548TJw4Ud4c9HNp2bKlHPkrJcf6+fPn06ZNGywsLLhz5w6XL1/m5s2bqbpO1apV8fHxoVu3btjb2/P48WNevnxJwYIF6du3r4YC+DW/SSNGjGD16tV069YNV1dXIiIiuHv3LiEhIRQpUoROnTqxe/dureathQsXZs+ePfTp0wd7e3sePnxIcHAwFSpUwNvbGy8vrzS9Y5UqVWLt2rWUK1eO2NhY/P39cXV1ZePGjcl+3/r378/gwYMpVKgQfn5+XL58mcuXL6doWgsJk0D79u2jY8eOWFtbc//+fSIiIqhevTqrV69m2LBhqZY/OcqVK8fEiROpU6cOZmZmPHr0iKCgIAoVKkS/fv3466+/xMqK4KujJ2XVLVtzMJcuXaJHjx5UrFhRq2+HQCDIPoj2LPgaPHr0iCZNmmBra8upU6fSLWSxQCAQZHWy3cqKQCAQCATfGmrH7RYtWghFRSAQfFMIZUUgEAgEgizMs2fP2LZtGwYGBmnyrRAIBIKcQLZysBcIBAKB4Fth5syZ/PPPP9y7d4/IyEg6duyY7vtoCAQCQVZHKCsCgUAgEGRB7t27x/Xr18mbNy/t2rVj1KhRmS2SQCAQfHWEg71AIBAIBAKBQCDIkgifFYFAIBAIBAKBQJAlEcqKQCAQCAQCgUAgyJIIZUUgEAgEAoFAIBBkSbK9stK9e3ecnZ25dOlSZouSbdm9ezfOzs6MHTs2s0XJdC5duoSzszPdu3fPbFGyBJcuXaJ79+54eHjg7OyMs7MzgYGBmS3WV2fJkiU4OzuzZMmSzBYl08nu/YWnp+c3+x5nJwIDA3F2dsbT0zOzRQF0fxuympyQNWUSCL6ELBkNzNPTk6CgoGTTjBs3jl69en0dgf6fo0ePcvfuXerVq0eJEiXSnH/JkiUsXbo02TQHDx7Eycnpi8o0MjIid+7c5MuXDzc3N2rVqkWdOnXERmKCNPHw4UP69u1LbGwsBQoUwNnZGQBjY+MU8/r5+XHx4kVu3brFrVu38Pf3R5IkvL29admyZYr5T506xW+//ca///5LTEwMjo6OtGnThq5du6Kvn7Y5lrFjx7Jnzx6NYyYmJuTKlQt7e3vc3NyoX78+lStXRk9PL01lC3I22t6d1HDs2DEKFCiQARJ9HT58+MD//vc/cuXK9Vnf2UuXLtGjRw+NY4aGhlhYWGBtbU3JkiWpWLEizZo1w8LCIp2k1k5gYCB79uzBwcGBNm3aZOi1vhYbNmzg48eP9OzZk9y5c2e2OAJBhpMllRU1RYoUwcbGRus5Ozs7APLnz4+joyOmpqYZLs/Ro0flTu9zlBU1+fPnJ3/+/FrPfe59WFhYoFQqAZAkiQ8fPvDo0SP+/fdftm/fjoODA3PmzKFixYpJ8ubKlQtHR0dsbW0/69o5CVNTUxwdHXU+n2+JnTt3EhsbS/fu3Zk4cWKa8i5YsIBjx4591nVXr17N/PnzAShYsCBmZmbcu3ePGTNmcP78eZYtW5ZmhQUgT548FC5cGID4+Hg+fPjAv//+y82bN9m8eTMuLi54e3vLSllirK2tcXR0xNra+rPuKSfxLfUXRYoUwcPDI8nx27dvExMTo/MblRqFPivz4cMHli5dioODwxdPCqrrT5IkwsPDefXqFQcOHODAgQN4eXkxatQounbtmiSfQqHA0dFR/tZ/LkFBQSxdupSKFSt+kbKSlb4NGzduJCgoiNatW2tVVtKr7gSCrEKWVlZ++OGHFDsXb2/vryRN+tG2bVuGDBmSrmWWLFmSTZs2aRyLiYnhypUrLFu2jKtXr9KzZ09WrlxJrVq1NNLVr1+f+vXrp6s82ZVSpUpx6NChzBYjS/D48WMAatSokea8dnZ2NGzYEDc3N0qVKsXChQu5ceNGivmuX7/OggUL0NfXZ+7cuTRr1gxI2G+ib9++HD9+nN9++42+ffumWaaaNWsyZ84cjWNRUVGcPn2aJUuWcO/ePTp27MiWLVsoWbKkRrpu3brRrVu3NF8zJ/It9RcDBgxgwIABSY6rV/9T84361tm6davGb0mSuH//Pv/73//YvXs306ZN4+XLl4wcOVIjnZ2dXZbqi7PTtyGr1Z1A8KVke58VgW6MjIyoVq0amzZtomXLlqhUKkaNGsWHDx8yWzRBNiAqKgpIMJlKK5MnT2bx4sX079+fypUrY2RklKp8K1asQJIk2rdvLysqAC4uLrKPxOrVq4mNjU2zTNowMTGhQYMG7NixgypVqhAZGcmwYcOIj49Pl/IFAoEmenp6uLi4MHv2bKZPnw4ktGnhdyoQCHSR7ZUVXQ72Y8eOxdnZmd27d/Ps2TPGjh1LjRo1KFmypIaT7PHjx+nbty+VKlXC1dWVypUr07x5c6ZPn86jR4+A/5zV1LbL48aNk52Ns4PTrYGBAdOmTcPW1pYPHz7wxx9/aJzX5TCb2KEwPj6e1atX07hxY0qVKoWnpydLliwhLi4OSBjYLlq0iPr16+Pu7k69evVYs2YNye05euvWLYYPH06NGjVwc3OjatWqDB06lH///VdrenV9Q4JPQ9euXSlbtizlypWjX79+OvMFBQXxyy+/ULduXdzc3Chbtix169Zl0KBBHDhwQOc9a+P58+dMnjwZT09P3NzcqFSpEv369ePUqVNa0yd2zP748SMzZ86kdu3asp/EsmXL5DpMjCRJ7N27l65du1K+fHnc3NyoVq0abdq0wdvbm5cvX+qsV23ExsayadMm2rVrh4eHB2XKlKFFixasWLGCyMhIjbTqtnP58mUAevToIdd9RjpVh4WFcf78eQDatWuX5HyjRo2wsLDg3bt36T6wMTExYe7cuRgZGREQEJBkVlKXg33ithMVFcX8+fOpW7cupUqVomHDhhqrnaGhocyYMYM6derg7u5O06ZN2b17d7JynTlzhgEDBlC1alXc3NyoWbMm48aN4+nTp0nSfupUu2/fPtq0aUPp0qWpWLEiQ4cO5dmzZ1qv8+DBA0aOHEmtWrVwc3OjfPnyNGjQgJEjR3L69Gmd96yNhw8fMnr0aGrWrCm36yFDhuhcWUvcV7969Ypx48ZRvXp1uY42b96sNd+HDx/YsWMHAwcOpH79+pQqVYpy5crRvn17Nm7cqLVdZTRRUVH4+PgwfPhwGjZsSNmyZSlbtiwtW7Zk+fLlREREaM2X2On/4sWL9OvXj0qVKiX5tj19+pQRI0ZQuXJlSpcuTcuWLeWVi+QCB0iSxIEDB+jduzeVKlXCzc2NunXrMmPGDN68eaORduzYsdStWxdI6DsTf+u0mUh+CR06dJCvtXr1ao1zyTmJp7ZP7969u+w7c/nyZY37SFxuasYLqQm+IkkSmzZtonnz5pQuXZoqVaowevRonj9/niRtapzgP61zddtT+/TWrVtX457U70pKZYeGhuLt7U3Dhg0pVaoUFSpUoHv37uzfv1/rNztxm4+JiWHJkiXyt75WrVrMnj1b57stEKQHWdoMLD148uQJs2fPJioqiuLFi2NhYSE70f7+++/yzI6trS0uLi6EhYUREBDAgwcPKFiwIE5OThgbG+Ph4UFAQADBwcFJ7JTTasN66dIlHj58yLt377CyssLd3Z1WrVplqA24iYkJrVq1Ys2aNZw8eZL+/funKf/w4cM5fPgwTk5O2Nvb4+/vz9KlS3n+/DlTpkyhR48e3L59m2LFimFra8uzZ8+YN28ekZGRDB06NEl5GzZsYM6cOUiShJWVFcWLF+f58+ccPnyY48ePs2DBAho0aKBVlq1btzJ16lTy5s2Lo6MjT5484cyZM1y9epWdO3dqBCgIDAykXbt2hIaGyjbHBgYGvHjxgqNHjxIYGEjTpk1TVQc3b96kX79+fPjwATMzM5RKJcHBwZw5c4YzZ87w448/8tNPP2nN+/HjRzp27EhAQADFixdHX1+fp0+fsnjxYl68eMGMGTM00nt7e7N+/XoA7O3tKVKkCKGhoTx48IA7d+7g4eHBd999lyq5o6Ki+OGHH7h48SIATk5OGBoa8vDhQ+7fv8/hw4f57bffZH8MtZ3+gwcPCAsLQ6lUyk6wRYoUSdU1P4d///2X2NhYjI2Nk5hhQYIdtru7OxcuXODmzZtUr149Xa9va2tLvXr1OHjwICdPnkz1ewEJymCvXr24desWxYoVQ5Ik/P39mTFjBu/fv6dz58506dKFoKAgihcvTlxcHH5+fowbNw5Jkmjbtm2SMmfOnMnGjRuBBH+b4sWL8/TpU3bv3s2RI0dYs2aNVn8KgPnz57N69WocHBwoUqQIjx8/5vDhw1y7do39+/dr9F+3bt2ie/fuREVFkStXLpycnFCpVLx48QIfHx8iIyOpWbNmqurh2LFjDBs2jJiYGHLnzo2zszPPnz/nyJEjHD16lKlTp9KhQweteZ8/f07btm358OEDxYoVQ09PDz8/P6ZNm8aHDx8YOHCgRvoTJ04wceJEFAoF+fLlQ6lU8u7dO27fvs2tW7c4d+4cK1as+Cz/ps/l9u3bjBw5EkNDQ/LmzUvRokUJCwvDz8+Pe/fucfToUbZs2aJztfLAgQMsWrSIXLlyUahQIY109+7do3v37nz48AETExOcnJx49+4dU6ZMkSfWtBEbG8uoUaNkBTxfvnx89913BAQEsGnTJg4dOsSmTZtwdHQEEtq4m5sbt2/fxsjICDc3t3SsoaR06tSJY8eOcenSJaKiolJcyU1Ln65+Jx48eKDh1wlo/d4mN15IDVOnTmXr1q3Y29vj5OSEn58f+/fv5+zZs2zevJmiRYumuixt5MmTBw8PD9lnys3NTWPVOleuXCmWERAQQM+ePXnx4gUKhQKlUsmHDx+4fPkyly9f5ty5c8yZM0frfcfGxtKnTx98fX0pVqwYDg4OBAQEsGHDBh4+fCh/swSCdEfKgtSpU0dSKpXSrl27UkzbrVs3SalUShcvXtQ4PmbMGEmpVEolSpSQBgwYIIWGhsrnoqKipNjYWKlChQpSyZIlpb///lsjb2xsrHT8+HHp8uXLWstMjVzaWLx4saRUKrX+K1Wq1GeVqy6zW7duKaY9fvy4pFQqJXd3d43ju3btkpRKpTRmzBiN4xcvXpSUSqXk6uoq1axZU/r333/lc5cuXZJcXV0lZ2dnacCAAVKzZs2kp0+fyuf3798vKZVKyc3NTXr37p1GuadOnZKcnZ2lSpUqSYcPH9Y4t337dqlkyZJS2bJlpVevXmmcU9dV6dKlNerq48ePUs+ePSWlUikNGzZMI8+0adPkewsLC9M45+fnJ/3xxx9a7/nT+oyIiJBq164tKZVK6aeffpI+fvwon9u9e7dUokQJSalUSidPntTIp34+rq6uUteuXaWXL1/K544dOybn8/Pzk48HBwdLLi4uUrly5SRfX1+N8qKioiQfHx/p7t27UmqZM2eOpFQqperVq0u3b9+Wj/v7+0uNGjWS7+lTdLWtz0Fd1t69e3Wm2b59u6RUKqUGDRroTDNx4kRJqVRKo0ePTvW11e320/dbG5s2bZKUSqXUsGFDjePq57h48WKN4+q24+rqmqQN+Pj4yG27T58+Uvfu3aW3b9/K51esWCEplUqpWrVqUlxcnEa5W7dulZRKpeTp6alR/3FxcdLy5cslpVIp1axZU4qKipLPPXv2TFIqlVLJkiUlDw8PjXfx9evXUvPmzSWlUinNnTtX41o//PCDpFQqpQULFkjR0dEa527duiXt379f6z1/Wp8vX76UPDw8JKVSKc2YMUMuKz4+Xr5XV1fXJO+u+vm4urpKQ4YMkd6/fy+f27x5s9xnJT4uSZJ09+5d6cSJE0lkfvr0qdS1a1dJqVRKu3fvlj5F/X159uxZknOpRdc3KjAwUDp48GCSvub169fSkCFDJKVSKS1ZskRneSVKlJCWLFkixcbGSpIkSSqVSoqOjpbi4+OlZs2aSUqlUurXr59Gn3ro0CHJzc1NcnV11Xpf8+bNk5RKpdSqVSuNPjwyMlKaMmWKpFQqpTZt2mjkUb9LderU+az6UfejSqUyxbQfP36UnJ2dJaVSKV2/fj1FGdKrT09MSuOF5MpJ3O5cXV0lHx8f+VxISIjUq1cvSalUSu3atZNUKlWK95cYXXWY0jusq2yVSiW1adNGvo83b97I506dOiWVKVNGUiqV0ubNmzXyJe7nmjRpIj1+/Fg+d/36dbndnzp1Sue9CARfQpY2A/vU3Er9Ly17YNjY2DB//nysrKzkY8bGxoSGhvL+/XuUSiX16tXTyGNoaEidOnWoUKFCet0KkDCTM2DAAHbu3MmlS5e4efMmW7dupWbNmkRFRTF+/HiOHz+ertdMjHoFKDo6mrCwsFTni42NZdKkSRoR0CpWrEjDhg2RJIkTJ07g5eVFwYIF5fPNmzenTJkyxMTEyOZEahYtWoQkScycOTPJ6kn79u3p0aMH4eHh7NixQ6s87dq103BqtbCwYNy4cUCC2Uxi/P39AejVqxfm5uYa55ycnOjYsWOq6sDHx4fnz5+TN29evLy8NMJttm7dWi7nU1MGNQYGBsybN08jOounp6dsApFY7qdPn6JSqahcuTLlypXTKMfY2JimTZvi4uKSKrnDwsJkM5HJkyfj6uoqnytcuDBeXl4AHDp0SKtp0dfk/fv3AFhaWupMo458k1F+V+rVqpCQkDTli4uLS9IGmjZtStmyZYmKisLX15e5c+eSJ08e+fz333+PnZ0db9684f79+/LxmJgYli5dioGBAUuWLKFSpUryOQMDAwYOHEjDhg15+fIlf/31l1ZZBg8erBFIw9bWlmHDhgEkMetSt5Hvv/8+iW+Ru7s7zZs3T1UdbNmyhbCwMEqUKMGECRPksvT19RkwYAC1atUiNjZW5+yrlZUVc+bM0Yhu1KVLF1xdXYmOjk5i+ufi4kLt2rWTyFywYEFmzZoFwJ9//pkq2dMLBwcHGjdunKSvsbW1xdvbG4VCkaxMNWvWZPDgwRgaJhg96OnpYWRkxLlz53jw4AFWVlYsWLBAo400bNiQ/v37a/XjCgkJYcOGDVhYWLBixQqNPtzExIRJkybh7u7O7du38fX1/dLb/ywsLCzkFYHg4OAU06dXn64NXeOF1BAXF0enTp00VmStra2ZN28exsbG3Lp1K9P9ci5cuCCvmC1YsIC8efPK52rWrMmgQYMAWLt2rVZzsLi4OObMmSOvwgGUKVOG9u3bA0n7FoEgvcjSyoraHOXTf4mXclOiQYMGmJmZJTluY2ODkZER/v7+3Lt3Lz3F1kmnTp0YPnw47u7uWFlZYWJigoeHB6tXr6Z+/fpIksTs2bOT9fP4EhKHRQ4PD091PisrqyQKHSAPmEuWLKnVbEf9YUxsJx8UFMSdO3fIkyePPFD/FLWd7ZUrV7Se1+bP4OzsjLGxMR8/fiQ0NFQ+rlbQDh8+/EX1evbsWSBBmdL28VLbRV+/fl2r7W6NGjW0mm25u7sDmnWklvnmzZtabZ3TwtWrV4mMjMTe3l5rfZcqVYqyZcsiSRLnzp37omt9KdHR0UCCuZcu1ANTtfN/eqPuK9LSPkB3G1C3kZo1ayYJI2pgYCDboyd+/jdu3ODNmzc6y4TPayPa3jX4733TpvikBfX7oy0MLfzXRnS9Z02bNtXaV6vNkLT528TExPDnn38yceJE+vbtS5cuXejcuTNjxowB+Gp9e2JUKpVs8tavXz9Zpt69e6Onp4e/v38SPzE1rVq10npc7cvVoEEDraY+uiKSnTp1ipiYGKpXr661/9HX16d27doASSaVvibqb1Nq2l169ena0DVeSC3a3v08efLQsGFD4L/vSGahvn6jRo20msF16tQJIyMjgoKC5GiQiSlRooTcjyRGfUxstCrIKLK0z0p6hIXUtcGigYEB3bt3Z926dbRu3RoPDw8qVapE+fLlKVeu3FeNk6+np8fIkSP5+++/efr0Kffv30/1zHlaSDyI/nRGKjkSzxYnRm33ntL5xNd98OABkDAw7dy5s9Z86kHrq1evtJ4vVKiQzuu9ePGCiIgI2f+ia9eu7N27l+XLl7Nv3z6qV69O+fLlqVSpUppi0Ktn84oVK6b1fJEiRVAoFMTGxvL06dMkzy8tdWRnZ0ejRo04dOgQDRo0oFKlSlSsWJFy5cpRpkwZedY1NTx58gSAokWL6rS9LlasGNevX5fvMbNQt7nkIn3FxMQAnxehLDWon0NaN6rLiDYSFBSks418/PgR0N5GrK2ttQ5o1as6nyrTPXv25Pz580ycOJH169dTvXp1ypUrR6VKldK0r0xKbaR48eIAvH37lrCwsCR1rKtd65L7+fPn9OnTR37HtaFerftafPjwgf79+3P9+vUU02nbU0vX90pdt7oc3B0cHLCwsEiyYq5+l27evKnzXVKvZujqb78GaWl36dWnayMtGzJ/ikKhkPdx0lVuZvexKbVRCwsL8ufPT0BAAP7+/knqI6V+LK2TPAJBasnSykp6kNwmi6NGjcLOzo4tW7bg6+srL4NbWFjQpUsXhgwZkuqQq1+Ko6MjVlZWvHv3joCAgAxRVtSz9CYmJmkajOmqQ/XgN6XziWe/1IOssLAwrl27lux11UrLp+ia+VI70ia+XokSJfj9999ZsmQJFy9eZNu2bWzbtg09PT2qVavG+PHjU/WBUn9ME5vxJEZPTw8bGxtevXqltcNOi8yQ4GBfrFgxduzYwdmzZ+UZMRsbG/r160fv3r1T5TisllvX5qqJ7ymzPzRq05bkBphq86+M2rVZ3UaSqy9tZEQbCQkJSdEcTVsbSeld+5TatWuzevVqVqxYwc2bN3n8+DEbN27E0NCQevXqMX78+FQNAlNqI4mPh4eHJ+mDdNWRrjYyduxYnjx5QunSpRkyZAglSpTA0tIShUJBXFwcrq6uXz0i2OzZs7l+/TqOjo6MGDGC0qVLY21tLX9HatasyatXr3Qq5LrqQL0Sk9wkk7m5eRJlRf0uvXjxghcvXiQru67+NqP5+PGjLLeudycx6dWna+NLNpe2srLS2caySh+b2u9BQEDAZ33HBIKMIscrK8mhr69Pz5496dmzJ4GBgfj6+nL69GmOHDnC6tWrCQ8P55dffvlq8qhnzDNqj4erV68CaF3G/VqoOzsPD48km4VlFGXKlGHdunWEh4dz7do1Ll26hI+PD2fPnqV37974+PikOPhVy63LplqSJHlgmZZVK10YGxszZMgQhgwZwqNHj/D19eXEiROcOnVK3gg1NRsjquVObtCrvqf0kPtLUM9Kvnjxgri4OK0rSGpTIF0zmF+Kuo2UKlUqQ8pPDepn1rx5c+bNm/dVrlmrVi1q1arFu3fv8PX15eLFi/j4+Mi+TNu3b0/WPA8S5P748SPBwcFaV0kSt50vfddevXrFpUuXMDU1ZfXq1Ro+BkCKA/OMIC4uTo64tXz58iSRn+Li4nj79u1nla0eRCcXHja5weWAAQMYPnz4Z107o7l27RqSJKFQKFI9SZcefXp68+7dO1QqldaBu7Zvg7aJisRkRCjg7PQ9EAgSI9Th/6dAgQK0atWKBQsWsGLFCgB27dqFSqWS06QlhGFaCQkJkTuJL13K1kZkZCT79u0DSLKD/ddEvfz8+PFjjbr9Gpibm1OjRg1GjRrFX3/9RaFChXj16lWqnALVIXv9/Py0nvf39yc2NhYDAwOd5iyfi9ppdOXKlUyePBmA7du3pyqv2hHy0aNHOj+K6nvKyLDEqaFkyZIoFAqio6O17pkTGxvLP//8A0Dp0qXT/fqvX7+WA1xkhTby8OHDr35ttX/axIkT8fHxIVeuXPz777/cvn07xbwptRH1/eTNmzfNZnafol4BK1q0aBJFBdAIWPC1CAkJISIiAisrK60hah8+fPjZE1HqutV1X8+fP9caNOVz36WM/NZ9inrSqkqVKmk2v05Nn/617kVtAqwNdWjpxH2sWgHVpThkRMCTlNpoWFiYrOhn9vdAIEiMUFa0UKZMGSDBiTexSYq6I80I594NGzYgSRK5cuVK95WP+Ph4Jk+ezNu3b7G0tKRTp07pWn5aKFKkiBz7fu/evZkmh6mpqRyo4fXr1ymmV+/psWPHDq3mEurN/zw8PL7IQTMl1O9mamQGKFeuHKamprx48YJjx44lOf/PP/9w/fp12YQiM7GwsKBKlSoA7Ny5M8n5Q4cOERYWhpWVFRUrVkzXa0dFRfHzzz8TExNDkSJFZIfYzKB8+fJYW1tz7969TI0elDdvXgoUKACkrY3o2sRR3UbSY38ctc9ScHCwViV87dq1X3yNtKKWKSwsTOs34ktkUrfNI0eOaFVKdG0uWqtWLRQKBadPn06Tv4T6XjIqkIWa7du3c+LECSDBR/VL0NWnf617gYSIeJ8SEhIir7gl7mPVvmVRUVFalUld0TDhv3tKq+lejRo1gIS+9NPNQAG2bdtGTEwMDg4OX7wnjECQnnyzyoqfnx+//PILt27d0vjYxcTEyCsrDg4OGg6maucyX1/fNEchefjwIVOmTEnSKUVHR7Ny5UrWrFkDaA8f+rnExsZy7tw5evTowb59+zAwMGD+/Pmp2jgqIxk1ahR6enpMmzaNHTt2JLErf/bsGStWrODIkSNffK3Jkydz8ODBJNF3rly5woULFwB0RlxKTLNmzbC3t+ft27eMHTtWw+Ri3759bNu2DUh4fl/KhQsX8PLySjL7FR4eLg94EocgTg4LCwvZsXbatGkaKxZPnz6VdyFv3Lhxuq8IfQ4DBgxAT0+PHTt24OPjIx+/d+8ec+bMAaBfv37p1kaioqL4+++/ad++PRcuXMDMzIxff/0VAwODdCn/czA2NpY3Uv3pp5/4+++/k/Q3Dx48YO7cubLZ2pcwfPhwTp48KQcvUHPo0CEePHiAnp5eqtpI586dsbCw4O7du8yaNUsuT6VSyZvRKhQKevfu/cUyFytWDEtLS16+fMmKFSvk+omOjmbGjBlaV+Yymty5c8sbfia+//j4eFavXs3BgwdTNKXTRdWqVXF2diY0NJRRo0ZphO4+evQoq1ev1lq2nZ0dPXv2JDY2lr59+yZRfiVJ4tatW0yePFkj2pqNjQ3m5uYEBwcnu+Hk5yBJEvfu3WPcuHFMmjQJgIEDB1K+fPlU5U9rn65WuP38/NIckjwtGBoasmXLFo2oeu/evWP06NFER0fj5uZG5cqV5XN6enqy4j5nzhyNb8qePXvYtWuXzmupxyJpjeBWuXJl3N3diYmJYcSIERqmmWfPnmXp0qVAwnfsa66uCQQp8c36rMTGxsqOeblz56ZgwYJIksSzZ8/4+PEjCoVCNrlRU79+fRYuXMiBAwe4ceMG+fPnR19fn9atW6cYtSwuLo6tW7eydetWbGxs5PCLjx8/ljvddu3apXlneTX//vuvPCiVJImPHz/y7NkzeealQIECeHl5pfqDkJHUqlWLSZMmMXPmTCZOnMjs2bMpUqQIenp6vHz5UrbrnjJlyhdf68aNG/zxxx8YGhpSuHBh+QMcFBQEQIsWLTQ+ILowNTVl0aJF9O3bV97hvGjRogQHB8vL5gMHDkwX86Hw8HDWr1/P+vXrsbGxwd7enri4OAICAoiMjCRXrlzyvjKp4aeffuLOnTtcunSJ1q1bU6xYMXkH+/j4eFxcXNLdN+vAgQNMmzZN/q2eDZ4yZYq8BwaQZPBUrlw5fvrpJxYtWsTIkSNZtGgRZmZmPHz4EJVKRe3atenTp89nyXT69Gm5jahUKt6/f09gYKDs7FyiRAm8vb3TFBo9o+jSpQsvXrxg9erVDB48GCsrKwoWLIhKpSIoKIh3794BaOzB8rmcOXOGgwcPYmRkRJEiRTA2Nubly5fyzOuPP/6oMwpQYuzs7PD29uann37if//7H3v37qVQoUI8f/6c4OBg9PX1mTRpUroED1EoFPz0009MmzaNX3/9lS1btmBnZ4e/vz/h4eFMnz6diRMnfvF10sqIESP48ccf2bZtG4cPH6ZAgQIEBQURGhrKjz/+yL59++S+Jy3o6+vj7e1N9+7dOXHiBDVr1sTJyYnQ0FCCgoLo3r07x48fJygoKImiPXz4cF6/fs3+/fvp0aMHtra25M+fn5iYGJ49eyYPktWhpSFhIN2oUSN27dpF69atKV68uLxirF4hSy2Jo5CFh4fz8uVL2WLB3NycUaNG0aVLl1SXl9Y+3cbGhsqVK3Px4kXq1atHsWLFMDY2Jm/evCxcuDBN95IcdnZ21KxZk2HDhjF37lysra3x8/MjKioKKysrvL29kygAQ4YM4dSpU5w9e5bq1avj6OjI69evefPmDVOmTNH5DWzcuDEnT55kypQpbNmyRTaFHD9+vMZeOp+ip6fH/Pnz6dGjB5cvX6Z27doUL16csLAwAgICAGjZsmWmWl8IBNr4ZpWVwoULM2PGDM6ePcu9e/fk8Jf29vY0bdqUvn37JplpLlSoECtXrmTVqlX8+++/PH/+HEmSUmWS4uDgwE8//cT169d5/PgxT548ITY2ljx58lCzZk3at28vL9F+DomjaxkZGZErVy6cnJxwdXWldu3a1KlTJ1Nniz+la9euVKhQgY0bN3Lx4kX8/PwwMjLiu+++o3LlytSvXz9dBv7jxo3j2LFjXL16lRcvXvD06VPy5ctH9erV6dq1K3Xq1El1WaVLl2bfvn2sWrWKs2fPcv/+fczMzKhevTo9evRINz+HcuXKMXHiRM6dO8fDhw959OgRhoaGFCpUiBo1atCrVy+tMfJ1YWJiwrp169i6dSv79u2T/YWcnJxo0qQJvXr1+qIoONqIjo6WB9SJiYiISNFxdODAgbi4uLBhwwbu3LnD27dvUSqVtGnThm7dun32exwcHCzPJBobG5MrVy5KliyJm5sb9evXl03QsgojR46kTp06bN68matXr3Lv3j3Mzc2xs7Ojbt26NGzYMF1knjNnDqdPn+b69eu8fv2aiIgIvvvuO+rXr0/Pnj3TtDlu3bp12b17N6tXr+bixYvcu3ePXLlyUb9+ffr27UvZsmW/WF41Xbt2JVeuXKxfvx4/Pz959rpv377UrFkzU5QVT09P1qxZw7Jly7h79y5PnjyhePHijB8/nhYtWsh+g5+Di4sLu3btYtGiRXLfULhwYX755Re6du0qr0R+6hhtaGjI3LlzadasGdu3b+fmzZvcvXuX3LlzU6RIEcqWLUvDhg01NvoDmDBhAubm5hw7doz79+8nG1I8OdTfJUNDQywsLLCxsaFatWpUqlSJZs2apdl/6XP69Pnz5zN//nzOnTvHnTt3iIuLw8HB4bPuJzkmT55M0aJF2bFjBw8fPsTMzIz69eszfPhwrddzcnJi8+bNLFiwgGvXrvHkyROcnZ2ZPn06derU0amstGrVig8fPrBz504CAgLkENWp2Sy3cOHC7NmzhzVr1nD8+HEePnyIkZERFSpUoH379rRo0UKsqgiyHHpSRu1AKBAIBAKBIMMJDQ2lcuXK5M6dW+dGoQKBQJBd+WZ9VgQCgUAgyAmoHezTc+VKIBAIsgpCWREIBAKBIItz//59tm3bpuGILUkS+/bt49dffwUQvgYCgSBHIszABAKBQCDI4ly6dIkePXpgYGCAvb09VlZWPHv2TPYN69ixo0ZQC4FAIMgp5FhlJTQ0NLNFSDWWlpYa+7kIvh3Es/82Ec/92+RLnntISAhbtmzh8uXLvHr1irCwMMzNzVEqlbRs2ZL69euns7SC9CI7tPfE2zQIBFmNbzYaWFZCX19Y432riGf/bSKe+7fJlzx3GxsbBg8enI7SCL4Wor0LBF+GaEECgUAgEAgEAoEgSyKUFYFAIBAIBAKBQJAlEcqKQCAQCAQCgUAgyJIIZUUgEAgEAoFAIBBkSYSyIhAIBAKBQCAQCLIkQlkRCAQCgUAgEAgEWRKhrAgEAoFAIBAIBIIsiVBWBAKBQCAQCAQCQZZEKCsCgUAgEAgEAkEaCQwMxNnZmbt372a2KDkaoawIBAKBQCAQCNKVsLAwZs6cSZ06dShVqhSdOnXi1q1bOtP/8ssvODs7s2HDBo3js2fPpmLFitSuXZsDBw5onDt48CADBgzICPHTjbFjx+Ls7Kzxr0OHDhppYmJimD59OpUqVaJMmTIMGDCAly9fapwfPXo0Hh4eNGzYkAsXLmjkX7NmDdOnT09RliVLltCyZcskxz9VutS/1f/Kli1L06ZNmTp1Kv7+/hp5d+/eTfny5VNbHZ+FYYaWLhAI0kx8fDw3b94EoHTp0hgYGGSyRFmb7FRfT/wlgoKgRIk48thktjS6yU51mhUQ9SUQJGXixIk8fPgQb29v8uXLx/79++nduzcHDx7Ezs5OI+3Ro0e5efMm+fLl0zh+/PhxfHx8WLduHQEBAYwbN46qVatibW3Nhw8fWLRoURLlJitSo0YNZs+eLf9WKBQa52fOnMmJEydYuHAhVlZWzJkzhx9++IHdu3djYGDAtm3buHPnDtu2beP06dOMHDmSc+fOoaenx7Nnz9i5cye7du1Kd7k3bNhAsWLFiIqK4v79+2zcuJGWLVuycuVKqlSpku7X04VQVgSCLEZUVBT16tUD4NmzZ5ibm2eyRFmbxPX1z+2nmJllvfp6/0Fi3ny4cVM+QpnSMGokWObWy0zRtBIRESnewTQg2qxAoElUVBRHjhxh+fLlVKhQAYAhQ4Zw9OhRtmzZwvDhw+W0r169Ytq0aaxbt44ffvhBo5xHjx5RsWJF3N3dcXd3Z9asWTx79gxra2vmzp1Lly5dsLe3T1Gep0+fMnv2bG7evElkZCRFixZl5MiRVK1aVU7j6elJhw4dCAgI4NChQ1haWjJw4EA6duwop7l16xa//PILjx49onjx4gwcODBV9WFkZIStra3Wcx8/fmTXrl14e3vL8sydO5fatWtz/vx5atSowaNHj/D09KR48eIULFgQb29vQkNDsbGxYcqUKYwaNQoLC4tUyZIWrKysZLkLFiyIp6cnPXv2ZMKECfz9999fbWJGKCsCQRZDT0+PggULAhAdDfr6UiZLlLWJjoYCBQry6hW075Q160tfH8zNYdoUPUq7w81/YO58iR69QKXKevKqVAl1CuIdTA3R0chtVk8v6ymfAsHXJi4ujvj4eIyNjTWOm5iYcO3aNfm3SqVi9OjR9O3bl+LFiycpx8XFhe3bt/P+/XuePXtGVFQUhQsXxtfXlzt37jBlypRUyRMREUGtWrUYNmwYxsbG7NmzhwEDBnDo0CENZee3335j6NChDBgwgMOHDzNlyhTKly+Pk5MTERER/PDDD1SuXJm5c+cSGBjIzJkzU3X9y5cvU6VKFXLnzk2FChUYPnw4efLkAeD27dvExsZSrVo1Ob2dnR3Fixfn+vXr1KhRAxcXF/bt20dUVBRnz57F1tYWa2tr9u3bh7GxMfXr10+VHF+Kvr4+PXv2ZNCgQdy5c4dSpUp9lesKZUUgyGKYmZnJJiXVa6sAMVBMHlNy21wndxY2q1KpYPRIPTxrJwxkPWuDJMHkqVnz2errm5Hb5joALdqAeAdTwlRuswKBACwsLChbtizLly+naNGi5M2bFx8fH27evEnhwoXldGvWrMHQ0JAePXpoLadGjRq0aNGCdu3aYWJigpeXF6ampkydOpXZs2ezdetWNm3ahLW1NdOnT9eq8ECC0uPi4iL/Hj58OEePHuX48eN069ZNPl6zZk26du0KwPfff8+GDRu4fPkyTk5O/Pnnn6hUKmbNmoWpqSnFixfn5cuXKSpMNWvWpFGjRtjb2xMYGMivv/5Kz5492b17N0ZGRrx9+xaFQoGlpaVGvrx58/L27VsA2rZty/3792nSpAnW1tYsWrSI9+/fs2TJEjZu3MjChQs5ePAghQoVYtasWUnM7BLz4MEDypYtq3FMklLfxzs6OgIJfi1CWREIBIIcRGl3zd9lvk4fLxAIBJmCt7c348ePp2bNmhgYGFCyZEmaNWvGv//+CySsKGzcuJHdu3cnuyI5ZMgQhgwZIv9esmQJVapUwdDQkBUrVvDnn39y4sQJxowZw+7du7WWERERwdKlSzl58iSvX78mPj6eqKgonj9/rpHO2dlZ/ltPT4+8efMSHBwMJJikOTs7Y2pqKqf5dNCvjSZNmsh/K5VK3Nzc8PT05OTJkzRo0EBnvsQKhEKhYPLkyRrnx44dS/fu3bl79y7Hjh1j3759rF27lhkzZrBkyRKd5To6OrJixQqNY69evaJ79+4p3ktivuYqslBWBIIszN9/CZOS1FK/cdae/b/5T8KKipobuoPiZAnEuycQCL6EQoUK8fvvvxMREUFYWBj58uVj2LBhFChQAABfX1+Cg4OpU6eOnCc+Ph4vLy82btzI8ePHk5T56NEj/vzzT/bs2cOuXbsoX748NjY2NG7cmPHjxxMWFqbVd8Pb25uzZ88yZswYChUqhImJCUOHDiU2NlYjnaGh5rBYT09PVhrSsvqQHPny5cPe3l6OqpU3b15iY2N5//69xupKcHCwTmXowoUL+Pn5MXPmTLy9valZsyZmZmY0btyYzZs3J3t9hUKhsboFpMn35NGjRwDyc/waCGVFIMhiREVF0a9fPwDWrl2LiYlJJkuUtVHXl72dxOLFazE2znr1NWmyxIJFEpKUsKJy4xYs/FWiTGmYPjXrKQXR0VF8//33gHgHU0NUVBTduok2KxBow8zMDDMzM96/f8/Zs2cZPXo0AC1bttRwcAfo27cvLVu2pE2bNknKkSSJX375hTFjxmBubo5KpSIuLg5A/l+lUmmV4erVq7Ru3Vr27QgPDycoKChN91GsWDH2799PVFSU3MZv3LiRpjIAQkNDefHihRz5zM3NDYVCwblz5+RVmNevX/Pw4UO5rhITHR3NtGnTmD9/PgYGBsTHx8uKlNpXKKNQqVRs2rSJAgUKULJkyQy7zqcIZUUgyGLEx8dz8OBB+W9B8iSur1wWKszNs97gf8ZUmDpD0vBRqeAaypRh77G0KpqJkmknPFwl3sE0INqsQJCUM2fOIEkSjo6OPH36FG9vbxwdHWVFxNraGmtra408CoWCvHnzUrRo0n5x+/bt5MmTh7p16wLg4eHBkiVLuHHjBqdPn6ZYsWLkzp1bqyyFChXi77//xtPTEz09PRYtWqRTsdFFs2bNWLhwIRMmTGDgwIEEBQWxfv36ZPOEh4ezdOlSGjRogK2tLUFBQSxcuBBra2s5gmCuXLlo27YtXl5eWFtbY2lpiZeXF0qlMokyB7Bs2TJq164tKwseHh7MnTuXNm3a8Pvvv+Ph4ZGm+0qOd+/e8ebNG6Kionjw4AH/+9//uHXrFqtWrfqqIdqFsiIQZDGMjIxYuHCh/LcgeVJVXxEhX1GipFgZwcJp8ORBOK8P7aBI9HGccj2CPRDnUJ6oelPB1CrzBDTTjE4g3sG0IepLIEjKx48fWbBgAS9fvsTKyooGDRowfPjwJHuMpIa3b9+yatUqtm7dKh8rVaoUvXv35ocffsDGxgYvLy+d+ceNG8f48ePp1KkT1tbWfP/994SHh6dJBnNzc1auXMnkyZNp1aoVxYoVY9SoURr+NJ9iYGDAgwcP2Lt3Lx8/fsTW1pZKlSqxcOFCDXO18ePHY2hoyLBhw4iKiqJKlSrMmTMniULw4MEDDh06xN69e+VjjRo14vLly3Tt2hVHR0fmz5+fpvtKjl69egFgamqKvb09lSpVYvr06UnMyDIaPSm9jPCyGKGhoZktQqqxtrbOVvIK0o+v9uxjIzL+GlkYiyXlMlsEACQ9fTDKRVT9KagcyqEfdBWTvydDTBh6Utpm+dKTsCFXM+3a2QKFWboUI/r6b5Ps8Nw/XeEQCLISYmVFIPgGyCqD9W8dPUlFZP0pxCsbARCvbES0JGFyYESmyiXej+QJG3E3s0UQCASCb5YMVVY8PT01HJgOHjyIk5PTZ5fXuXNnjc2ENm7cSKVKlb5IRoEgq6FSqbh//z6QEEZRX18/kyXK2qgkibtvE/wESuQ1QD+Lb8qnctBUDOILlM8kSXST3eo0sxFtViAQCDKODF9ZyZUrFz179gS0LzPeunVLdpCKjY2lWLFi9OzZk+bNmydJ27ZtW6pWrcrly5e5fPlyRosuEGQKkZGR8k62z549w9zc/IvLzMlmPuHhEZQtqgTg2eMHmJsnNdnJSisH+kFX5ZUVAINA30yUJoFP34/U1KngPzKizQoEAoEggQxXVnLnzq3T+ejSpUv07dsXhUJB06ZNyZUrF0eOHGHUqFEEBQUxYMAAjfTt2rUDEjYEEsqKICeTJ0+e9C0wnWzusyQK6b/6UphqvdewAee+slDaMfnzJ4yPTSdGkogvUB6DQF+Mjs8grkAFopotyjzBPq2zVNSpQJN0b7MCgUAgADLRZyUuLo6JEyeip6fH5s2b5RBsgwYNolOnTixZsoRGjRpRpEiRzBJRIMgUzM3NefjwYWaLkW1IVX19Eu0qMwgIvc9rj1ZUuLoTi0Q+KnGFqxLVZB6YZh0HV/EOpg1RXwKBQJBxpElZkSSJvn37cu7cORYvXkzDhg3lcyqVil69enHp0iWWLVsmx4/WxcWLF3n69Clt2rTR2FjGwsKCH3/8keHDh7N7925GjMhcx1OBQJD1eRf5NrNF0MmH6FAWnRvNrVcX5WNNnCrQy7EjRnmcibNxBOIhC92DlWnezBZBIBAIBAIgjcqKnp4eXl5etGjRgkmTJlGqVCny588PJOzae+nSJTp27JiiogLIZlzVq1dPck5t+ytMvQQCiIxNWyz4b5F2W90yWwSd6OvpY67IzaQ6q3G3q8w/ry6y6NzPHLr6M6pMDFecHH92f5TZImRLTBXCV0UgEAjSmzSbgdna2jJr1iwGDBjAqFGj2LRpE3fu3GHx4sU4OTkxfvz4VJXj7+8PoHVjGUtLS6ytrQkICEireAJBticqKoqhQ4cCsHjxYppv+fwIet8CqliJgO0JkasKdzBAX5G1IlepJBXDqnlTy7EFALUcWyBJEjNO/pDJkumm6fqiWbpOsxrqd7CuUxsWL16MiYlJmssIDw+nWbNm1KtXjwkTJnyxTGvWrCEyMlLuS3Th4+NDqVKlKFSoEACnT5/m5s2byW50l1J5586dY/bs2UnO+fn5sXDhQt6/f49KpcLY2JiJEyemGCW0VatWzJ8/P8V0p06dIm/evLi6ugJw9+5dtm7dyrRp0z7rXgQCQdbgs+Ir1qlTh27duuHr68uCBQsYNWoUAPPnz091Jx0WFgYkRAvThoWFBR8/fvwc8QSCbE18fDw7d+5k586dxMfHZ7Y4WR5JBaHXVYReV5FFFypwt6us8bvUd1UySZLUkR3qNCuhrq8vabN///03zs7OnDx5koiIr7eJ64EDB3j69Kn8u2bNmp+tqKTE5MmT6dixI7///jtbtmxhzpw56boZ4alTp/j333/l3yVKlBCKikCQA/hsB/uff/6Zy5cvs2bNGgDGjRtHiRIl0k0wgeBbxcjIiJkzZ8p/C5Oc5ImNjaX6peIA6GfRbW7/eXVRXlkBuPXyQiZKkzL7et5nQ/z/AOjVsycKhSKTJcraxMbGsiH+fygMjDAyMvqsMv7880/69OnDnj17OHbsmBy+38fHh7///pvcuXPz+PFjFAoFM2fOxMHBgeDgYCZNmkR4eDgxMTGUL1+eESNGoPfJvjhdu3Zl7NixuLu7A7Bnzx58fX2pWLEi9+7dY8GCBaxatYqBAwcSEhKisTLi4+PDtm3bkCQJQ0NDZs2aRb58+Rg5ciTv378nOjqa4sWLM378+BQnK1++fEm+fPnk33Z2dvLfwcHBeHt7ExgYiCRJdOjQgVatWiUpY+DAgXTt2lU2IR83bhzVqlXDxsaGs2fPcuXKFfbv30+7du0oUKAAS5YsYcOGDQD89ddf/P777/K1x44dS758+ZKt46dPnzJ9+nQiIyORJIkaNWokiVQqEOQEPD096dGjB7169QIS9oxKjQ/61+CzP+3GxsbUrFmTBw8eYGpqStu2bdOU38LCAkDn6klYWJjOVReBICejUCgYOHDgf78RA8XkMFXA6RVZd4fxacf7sfjCOCRJotR3Vbj18gJLLozH1bgc48sswbho7swWMQm5Ta0YOvinzBYj22Cq4Ivq6/Hjx7x+/ZrKlSsTHx/Ppk2bNPYau3PnDps2bSJ//vwsW7aMTZs2MXbsWCwsLJg3bx5mZmbEx8fz888/c+LECTw9PTXKb9++PTt37pSVlZ07dzJ69GjKlCnDoUOHNAb/Pj4+cr6rV6+yYcMGVq5cSd68eYmKigLAwMCAadOmYWlpiSRJeHt7s2vXLrp27Zrsffbp04eBAwfi6uqKq6srnp6eODs7A7BgwQIKFy6Ml5cXISEh9OrVi+LFi8smXSlRtWpVqlevTokSJWjfvr0sv5pHjx7Jiku+fPn47bffmDNnDgsWLEi2jnfu3Em1atXkAdz79+9TJY8g8xk7dix79uwBwNDQEEtLS5ydnWnatClt2rSRN2/9dANzNSNHjqR///4EBgZSt25dDAwMOHHihIaS/fr1a2rXrk18fDzHjh2jQIECqZKte/fuuLi4pIvJZ0Zx9uxZLC0tU0y3ZMkSli5dqvP8kCFDGDx48BfJ8tnKyvXr19mwYQNWVla8e/eOqVOnMm/evFTnV4ckDggIwM1N0zn2/fv3hIaGUrZs2c8VTyAQfEOoo1fFBUdlsiRJmVB2OV5Xf9LwUXF+oqTTjma8jjiLeSU77GdXxtDaOBOl1CQuQrMeDfOk3QdDkHr2799P48aNMTAwoGrVqnh5efHkyRMcHR0BKF26tBzMxt3dne3btwMJETqXLVvGzZs3kSSJ0NBQihcvnkRZadSoEWvXriUkJAR/f3/09PQoU6ZMinKdP3+exo0bkzdvQvtSr5yoVCq2bt3K+fPniY+PJywsLFXlde3alUaNGnH16lWuX7/OgAEDGD9+PPXr1+fKlSv89FOCwmdjY0Pt2rXx9fVNtbKSElevXqVatWryyk7btm3ZsGEDkiQBuuu4TJkyLF26lMjISDw8PKhQoUK6yCP4OtSoUYPZs2ejUql4+/YtZ86cYebMmRw+fJgVK1ZgaJgwDB46dCgdOnTQyPvp5q758uVj7969/PDDf3353r17sbOz4/nz5+kuuyRJxMfHyzJ+bWxtbVOVrk+fPnTq1CnJ8QULFnD06FGaNWv2xbJ8Vg2EhYUxatQoDA0N2bx5MwsWLODPP/+kRo0atGzZMlVlVKhQgVWrVnH27FmaNm2qce7cuYQN3CpWrPg54gkE2RqVSkVgYCCqyFgKOBSQZ38E2lGpVAQGBQLwvt4Z9PWyXn11pzn1bSvyNk8w+aK/o/zoVpgNsSPi8iuCxl3kYb39oJIyW0wZlaTilRQKgJ2eNe73k58x/9ZRv4P6pgoKFEhbm42Li+Pw4cMYGhpy5MgRICHIho+Pj+w7kti0TF9fX/aL2bJlC+/fv2fdunUYGxuzaNEiYmJiklzDxMSEJk2asH//fh48eCBvsPy5HD58mOvXr7NixQrMzc3Ztm0bN27cSFXePHny0KBBAxo0aED+/Pk5fPgw9evX15r2U3M2SFjVUan+c6TSdr/akCRJo7xPy9ZVx56enpQqVYrLly+zY8cO/vjjDxYuXJiqawoyHyMjI3nQbWdnh6urK6VLl6ZXr17s2bNHXoUzNzdPcXDeqlUrdu/eraGs7N69m1atWrF8+XKNtH5+fnh5eeHr64upqSnVqlVj3Lhx2NjYMHbsWC5fvszly5fZuHEjAMeOHSMoKIgePXqwdu1aFi5cyIMHD1i7di0eHh54e3tz4MABwsLCcHNzY9y4cZQqVQpI2GC9R48erFq1igULFvDkyRNcXFyYMWOGvHIJCe128eLFBAQEkC9fPrp160afPn103m9iM7CYmBjmzJnDkSNHeP/+Pba2tnTs2JEffvgBc3PzJIrd/v372bdvH6tWrUqX/RI/S1mZPHkygYGBTJkyhWLFijFz5kz++ecfpk6dioeHBwULFkyxjCpVqlCwYEF8fHzo0aOH7O8SFhbG8uXLMTQ0pHXr1p8jnkCQrYmMjJRnKQ+Ze2Gql3Vm3LMikVI0jcLHAP9fX2TN+vrujR3fvbGj0PKaWDYrAoBlsyJIEjwbdDpzhfuEaGLpFDEdSKjTOy5bM1mirE3id/DZs2dJPtzJcfr0aezt7Vm3bp187NGjRwwePFjDHFQbHz9+JE+ePBgbGxMcHMzx48d12pe3a9eOfv36ERsbyy+//CIfNzc3lwPefEr16tWZOXMmrVq1Ik+ePLIZ2MePH7G0tMTc3Jzw8HAOHDiAg4NDivd68uRJqlevjqGhIXFxcfj5+clmMxUqVGDfvn18//33hIaGcurUKWbNmpWkjAIFCnDnzh1q1qzJ8+fPuXnzJnXq1EnxXipUqMDvv/9OcHAwefLkYc+ePZQvX16rQpSYp0+f4uDgQJMmTShZsiT9+/dP8T4FWZsqVarg4uLCkSNHZGUlNXh6evLHH3/g6+tL+fLl8fX15f3799SpU0dDWXn9+jXdunWjQ4cOjB07lujoaObNm8ewYcPYuHEjEyZMwN/fn+LFi8vR+mxsbGRTtLlz5zJmzBgKFixIrly58Pb25vDhw8yZMwcHBwfWrl1Lv379OHLkCFZWVvJ1vb29mTBhAnnz5mXhwoUMHDiQw4cPo1AouH37NsOGDWPw4ME0adKE69evM3XqVKysrGjTpk2K975p0yaOHz/OokWLyJ8/Py9evODly5da096+fZtJkyYxcuRIatSoker6TY40Kyt79+7Fx8cHT09POnfuDIC1tTVeXl706dOHUaNGsXnz5hSXrQwNDZkxYwb9+vWjS5cuNGvWDAsLC44cOUJgYCDDhg2Tl8AFgm8NMzMzVBFxmS1GtsGEz3NqzgzMKtpp/DavZKcjZeaSneo0K2CCEfpmaZ//279/v8YGywBOTk7Y2tpy5syZZPN26NCBCRMm0L17d2xtbZM1UcqXLx/FixenUKFCGo7wrVq1YvHixWzevDmJclS2bFl69erF0KFD0dPTQ6FQMGvWLJo0acLp06fp1KkTtra2lClThjdv3qR4rydPnmT58uUoFApUKhUlS5bk+++/B2DEiBF4e3vTtWtXJEmiV69eWk3AunfvzsSJE7l48SKFCxfWSNO4cWOmT5/O8ePHZQd7NUWLFmXgwIHy4FDtYJ8Sx48flwd8kiTx888/p5hHkPUpWrQo9+/fl3/PmzePX3/9VSPNypUrqVSpkvxboVDQokULdu3aRfny5dm1axctWrRIEoBk69atuLq6amxqPmvWLGrVqiWbdyoUCkxMTLSu5gwdOlTebzAiIoI//viD2bNnU6tWLQCmT5/OuXPn2LlzJ/369ZPzDR48WM43Z84catWqxd9//02TJk347bffqFKlCoMGDQLA0dERPz8/1q1blypl5cWLFxQuXJhy5cqhp6enc3IiODiYwYMHU79+ffr27ZtiuaklTT3rs2fPmDZtGra2tnK0IjVVq1ald+/erF+/niVLljB8+PAUy6tcuTJbtmxh8eLF/PXXX8TGxlKsWDF++uknWrRokWJ+gSAnYm5unmAGFhGb2aJkGwLpBZAtVgAiLr+SV1YAwi+9yjxhdGCqZ8xhC2/5t+u9zpkoTfYgkF7om6U9GMaiRYu0HlebhwAaNt/Vq1eXneHz58/P+vXrteZXKwFqIiIiePDgASNHjtQ4nrg8bddr1qyZVptzXQ61utIDTJkyRetxSDAP8/Ly0npu79698t8ODg789ttvWtOVLFmSrVs1+wB1JDCAJk2a0KRJkxRlTlwnvXr1kp3rBTmHT80C+/btm2TQntiRXk27du3o2LEjI0aM4NChQ2zbti1JuPI7d+5w6dIlrX7XT58+TXEiXh0IQ50+NjYWDw8P+ZhCoaBUqVI8eqQZKTSx35iVlRWOjo48fvwYSAjiUbduXY30Hh4ebNy4kfj4eAwMDJKVqXXr1vTp04dGjRpRo0YNateunaTfiI2NZejQoeTJkyeJjvClpElZKViwINeuXdN5fsyYMYwZMyZNApQqVYq1a9emKY9A8C3wOQOfb50S1zuknCgTeTrgFEGTLiFJCSsq4Zde8fyXS5hXtqPQilqZLZ5OxLuYvdm9eze//fYbbdu2xd7ePrPFEQgynUePHmmsvFlbW2vdpPxTlEolRYsWZcSIETg5OaFUKrl7VzMapUqlok6dOvIehIlJjdO6qalpkmOfmit+qmylhDqQxOfi6urKsWPHOH36NOfPn2fYsGFUrVqVxYsXy2lmzJiBv78/u3btwtg4fc2xMzzEQFBQkOzgc/DgwRR3oE2Ozp07J6ssCQSCb5usHrWq0KpaPPn+sIaPikWN/BRcUgNDm6wtuyD70qZNm1SZeggE3wIXLlzgwYMHn71i1rZtW6ZOnapzpdDV1ZXDhw/j4OCg0yVCbQqZEoUKFUKhUHD16lV5oiE2Npbbt2/Ts2dPjbQ3btyQ07x//x5/f3+KFi0KJJiWfjp+vnbtGkWKFElxVUWNhYWFvDrZsGFD+vXrx7t377CysmLbtm3s2rWLjRs38t1336WqvLSQocpKjx49NPZR+dKdatu2bUvVqlXl36lx6BMIshvR0dGyXbS3t3e6z1DkND6tLylSu4NtZhP9IZTLS37mdcRFjJ3yYRyTB3PXAhSaOIk4/XDi3oVntogy0dHR/DIrwSRHvIMpI9qsQJA1iYmJ4c2bNxqhi1etWkWdOnU0Nh0NDw9P4ndlamoq7wmYmA4dOtCoUSNy59a+R1aXLl3Yvn07I0aMoF+/flhbWxMQEMCBAweYMWMGBgYGODg4cPPmTQIDAzEzM9NwlE+MmZkZnTt3xtvbG0tLS+zt7Vm7di1RUVFJovotX74ca2tr8uTJw8KFC7G2tpYDbvTp04d27dqxbNkymjRpwo0bN9i8eTOTJ09OVT1u2LABW1tbXFxc0NfX59ChQ9ja2pI7d26uXr3K9OnTGTRoEAULFkxSjyYmJl+8b2KGKivpbef5peEWBYKsSlxUhPx3VEQEmzZtAmDa5EkYSPG6sglIWl8+XUtlskTa0dPXR2GWm+rjV5HPtRKv71zi8uIxHBhYGykVM2xfk+h4iU2+0YB4BxNjaGKm9XhcXJz8Ds6aNeuzlJUxY8bQrVs33N3dWbNmDbt378bW1paoqCjMzc1p1KgR7dq1S3EW9MGDBzx9+lQjKtiaNWvo1atXEkfg1JB4x/hff/2VEiVK0KBBgzSXIxBkBmfOnJEj0OXOnRsXFxcmTpxI69atNUKML168WMOkCaBjx45MmzYtSZmGhobY2NjovKadnR1bt25l3rx59O3bl5iYGOzt7alRo4Z8zT59+jB27FiaNm1KVFQUx44d01neqFGj5OAO4eHhuLm5sXbt2iQbNo4cOZKZM2fi7++Pi4sLK1askENyu7q6smjRIhYvXsyKFSuwtbVl6NChqV5xNTMzY82aNQQEBKCvr4+7uzurV69GX1+fnTt3Ehsby6JFi7T64LVu3Zo5c+ak6jq60JO+1JAtixIaGprZIqQaa2vrbCWvIP1QP/vNjf+zI49TSRx7kTA4rJvfAEP91Nulfotkp/qqPn4VhWv8tzN5wOn9nJ09IBMl0k52qtOvSde/tG/8FhMTw5IlS4CE3ZoT79mRGF19/Z07d1i+fDnLli0DEpSLyMhIOXLV8+fPmTJlCs7Ozkkc5D/Fx8eHc+fOMXv2bPlY5cqVOX78OGZm2pWt5EisrISEhDBgwAD++OMPsf9TGsgO3/gvtXwRZB7qfVauXLmic7Unu5M522IKBAKdGOrr0dBBNM3Ukp3qK59rJc3fbpUzSZLkyU51mhUwMjJKUYlIjr179yYJX5wYe3t7Jk6cSOfOnfnhhx+wsLDgr7/+4vfffwf+C8NraGjImjVrCA8Pp3v37ri5ucllfP/99+jr6/Prr79ibGzMr7/+ip+fH9HR0ZQqVYqRI0diaGjIkydPmD59OnFxcRQpUkRj00UbGxvs7e25cuWKRkhXgUAgyEjE10ggyAJ03OOX2SLkGLa1LpbZIujk9Z1LGisrr29fzERpkke8k1+Pa9eu0aVLl2TTqPdHCQgIwMTEhCVLlrBhwwby5cvHb7/9xpw5c1iwYAHff/99kpWVPXv2sGbNGnllZfbs2ZQtW5bx48cjSRKzZs1ix44ddO7cmSlTptChQweaNm3K7du3k2yC6O7ujq+vr1BWvnEkSSIy8ute09Q0aVQswbeBUFYEgixAYlt4SZIIDg4GEvYeEJ1z8nxaX223/pPJEmnnzMzvubJsPEgS+dwq8/r2Ra4sn0A+9yrUGL86s8XTQJIk3oUl+FGJdzBlvrTNvn79mjx58qQ6/dWrV6lWrRr58uUDEoLPbNiwIdXhSU+fPs3t27fZsmULkBAgQKFQEB4ezuPHj2ncuDEAbm5uSSJ45smTh+vXr6daVkHOQ5IkuvX6wI0bX3fj4rJlDNm0Ibfojz6hUqVKGhtc5kSEsiIQZDEiIiJQKpVAwkas5ubmmSxR1iZJfVmlftD3NakxcQ3nvAZp+Kh8V7Ym1cYsw8Qya8kcHh6OsmBBQLyDqeFL26yJiQnR0dHJpgkICCAqKooiRYpw+/ZtjQFbWgdvkiTh7e2dJKJmeHh4imVFR0eLaGcChLog+JoIZUUgEAi+AiaWeag76w/eBzxA+vAGvdy2WBZWZrZYgixAsWLFCAgI0Llh3PPnz5k5cyZt2rTB3NycChUq8PvvvxMcHEyePHnYs2cP5cuXR09PD3Nzc8LCNMN3m5mZERYWJpuB1ahRg40bNzJ69GgMDQ358OED79+/p2DBghQtWpTDhw/TuHFj7ty5k2SXbH9/f4oXL54xFSHIFujp6bFpQ+4cYwbm7OzMsmXLNCLopZWxY8fy4cMHli9fno6SCdSIaGBZgOwQKUSQMYhn/20invu3ia7nvn37dl69esWQIUMAtIYubtiwIe3bt5dDFx88eJDNmzcD/znY58uXj7CwMIYPH05kZCTu7u6MGTOGtWvXcuTIEdmx3tjYmGXLlnHjxg309PQwNDRk0KBBVKxYUcPB3tnZGX9/f3r27En16tWRJIkOHTqwdOlS7Ozsvl7FZXOyQ3vPydHA3rx5w8qVKzl58iSvXr0iT548lChRgp49e1KlSpV0UVY+fvyIJEmZHo0rJiaG9u3bc+/ePfbu3UuJEiUyVZ70IscqK2/fvk3V7qBZgezQkQkyBvHsv03Ec/820fXcIyIiGDBgAKtWrcLU1DQTJEsdly5d4siRI0yaNCmzRclWZIf2rvZ/ymkEBgbSuXNncufOzZAhQ3B2diYuLo6zZ8+ybds2Dh06lC7KSlZhxowZBAQEcPr06RylrORYM7CgoCCNkItZmXfv3vH+/fvMFkOQCYhn/20invu3SXLPvWPHjly9epWC/+8rlBXx9/enefPmBAQEZLYo2Yrs0N5zqrIydepU9PT02LFjh8Y+Q8WLF6dt27by79DQUAYNGsTZs2exs7NjzJgx1K1bF4D4+HgmTZrExYsXefv2Lfnz56dLly707NlTzv+pGVj37t1xdnbGyMiInTt3olAo6NSpk7x6CrBkyRJ27drF27dvsbKyolGjRkycOPGz7/XUqVOcO3eOJUuWcPr06c8uJyuSY5WVmJgYDAwMUtztNytgbGyscxMxQc5GPPtvE/Hcv02Se+4eHh5fWZq0U7NmzcwWIVuS1dt7fHx8ZouQIbx7944zZ84wfPhwrRuiJjbZWrp0KaNHj+bnn39m06ZNjBo1ihMnTmBlZYVKpeK7775j0aJFWFtbc/36dX755RdsbW1p0qSJzuvv2bOH3r17s337dm7cuMHYsWPx8PCgWrVqHDp0iA0bNrBgwQKKFy/O27dvuXfvnpz3l19+4c8//0z2/g4cOIC9fcKG0m/fvmXSpEksW7YMExOTtFZVlifHKisABgYGKBSKzBYjRRQKRbaQU5D+iGf/bSKe+7eJeO7fJuK5Zw5Pnz5FkiSKFi2aYtrWrVvTrFkzAEaMGMHvv//OrVu3qFmzJgqFgqFDh8ppCxYsyPXr1zl06FCyyoqzszODBw8GoEiRIvz+++9cuHCBatWq8eLFC/LmzUvVqlVRKBTY29tTqlQpOe9PP/1E3759k5VZvRomSRJjx46lU6dOuLu7ExgYmOL9ZjdytLIiEAgEAoFAIPj2ULtkpyaCmLOzs/y3mZkZ5ubmhISEyMe2bt3Kjh07eP78OdHR0cTGxuLi4pLqMgFsbW3l/ZgaNWrE//73P+rVq0eNGjWoVasWderUwdAwYVieJ0+eVO+9tGnTJsLCwvjhhx9SlT47IpQVQY4iPj6ef//9F4CSJUtmCzPAb5lv8Xk9CzTg33v65LIwoGCBnGl+oeZbfL7ZFfGsBDmNwoULo6enx6NHj1J0nv905UtPT08O0nTw4EFmz57NmDFjKFu2LObm5qxbt46bN28mW6Za8UhcplqByp8/P4cOHeLcuXNcuHCBqVOnsm7dOjZt2oRCoUiTGdjFixe5efMm7u7uGufbtm1L8+bN8fLySrac7IBQVgQ5iujoaDp16gTAlStXtNqpCrIOiZ/XseO+mJrm3Of1MUyPNWst+feu2nY9LyVLxPB9v/fkssiRQRmJjIwR7TGbIPpOQU7DysqK6tWrs3nzZrp3757knf7w4UOqQg1fvXqVsmXL0rVrV/nY06dPv1g+ExMT6tatS926denSpQuNGzfmwYMHuLq6pskMbOLEiQwbNkw+/vr1a/r27cvChQspXbr0F8uZFRDKiiBHoaenh729PZIE0dF66OtntkTJExkFUVGZLUXmER2tR/789rx9a8CgofnQ18+5AyR9fTA3h2lT9CjtDjf/gbnzjRg52pZsEmU9zahUEeTPn+AAmh3aY0aTVdu7icl/fSdkzMZ7AkFmMHnyZDp37kz79u0ZOnQozs7OxMfHc+7cObZu3cpff/2VYhmFChVi7969nDlzhgIFCrBv3z7++ecfChQo8Nly7d69m/j4eEqXLo2pqSn79u3DxMREboNpMQNT51GjVsoKFSrEd99999kyZiWEsiLIUZiamvL333/TvrMd/X/MbGlSy7e9uZq17S2stW/cnaNQqWD0SD08aycMBD1rgyTB5Kk5c1UFQF/fDGvbWwDZqD1mNFmvve/Y+kruOwWCnETBggXZvXs3K1euxMvLi9evX2NjY4OrqytTpkxJVRmdO3fm3r17DB8+HD09PZo2bUqXLl2+KDxw7ty5Wb16NXPmzEGlUqFUKlm5cmWO3pzzS8ixm0JeuXIFIyOjbBGBw8rKinfv3mW2GDmK9p2z3oBAINi3S488ef6btQ4OlmjZNkd2wYJsxI6trzJbhBxNVv/Gx8bG5hhzIUHORKysCHIkm37LHh9fSysr3mfhj9jXonvvb0O5vPlPwoqKmhu3Mk2Ur0Z2aYtfA9HeBQKBIO0IZUWQo4iOjmbUqFEAzJs3D2Nj40yWKHlMTSA65+3flGrUzyuPFUybNj/LP68vYcEiKxYsVCBJ+pQplaCoLFykomSJWEYMe5fZ4mUI0dHRjB49Esge7TGjycrtPbv1nQKB4NtBKCuCHEV8fDzHjx+X/xZkbRI/LwvzOMzMsu4uz5+D0Xt/FB+DiM3lwMhhjvy61IrJU/+7x1Lusfw0+B25c+dMU7CIiDjRHrMJou8UCARZFaGsCHIUCoVCdprLDv5K3zppfV4GUe8yVqB0Qj/6A3a+CzF9/V8c/nz5SjNt0HAC3ublfZgVlhbvKOgQk3AyC0aIijex+uIyRHvMPohnJRAIsirCwT4LkNWd7wRpQy8uMtVpLS2teP/+XcYJk8MotqNpZouQKiQ9fTDKRVT9KagcyqEfdBWTvydDTBh6UvaIU+zX/kBmi5DjsLS04l14dGaLIfjKZPVvvHCwF2R1xMqKQJDOpHVA/Q1E7f3m0JNURNafQryyEQDxykZESxImB0ZksmSpJ7sohtmNd52PZ7YIAoFAkK3I0C26du/ejbOzs/xv+PDhn13W+fPnNcrq3r17OkoqyCmoVCr8/Pzw8/NDlVN32stBqCSJO2/iuPMmDlUOW+RVOZTT+B1foHwmSZJ55OTnm9MQfadAIMiqfJWVlbp161KiRAmKFy8uH3v69Cn79u3jzp073Llzh9evX+Pg4CA7+H1KwYIFGTx4MABLly79GmILsiFRUVG0bNkSSDAFVO/k+jVJi/nMt24GFhERSfkqNQDwvXAGMzPTZNNnp9l+/aCr8soKgEGgbyZKk3bSwwwsrc83p2NpaQVZ1AwsK/SdAoFAoI2voqzUq1ePNm3aaBzz9fVl6dKlGBgY4OTkxNu3b5Mto2DBggwZMgQQyoogeTJ7B1jJMA0DMoUpkmHWHLx8DSRDSX5ekqFJinX3uPXuryHWF5P/3FSMj00jRpKIL1Aeg0BfjI5PJzJfaa6V7km4XijmkjX5LYpktqg6SdN7rLOMtD3fHI/CFMi67T2z+06BQCDQRqb5rFSoUIFt27bh4uKCiYkJ7u7umSWKIAdhZmbG2bNnM1sMQSqJM4ji4LH9CX8TxYfoFMJi6SV/OqvwocJPFL3yK7kT+aiE5nVlkuk7fK/0lo+52JSjd8kJWBhZZoaYyRMd8sVF5DazEe0xmyD6ToHg28bT05MePXrQq1cvAJydnVm2bBn16tXLXMHIRGWlYMGCFCxYMLMuL8hhRKUhAldWIirOKNvKnh4MOl43s0XIUIrk0qegyoBn+vE8jT+PeWRuJtVZjbtdZf55dZFF535m3Ll2qLJJhLC0sqb++cwWIUuRldq7ybe+yiXI8YwdO5Y9e/YAYGhoiKWlJc7OzjRt2pQ2bdqgr5/gtu3p6UlQUFCS/CNHjqR///4EBgZSt25dDAwMOHHiBHZ2dnKa169fU7t2beLj4zl27BgFChRIlWzdu3fHxcWFCRMmpMOdZgxnz57F0jJrTKSJaGCCHMH3f1fNbBEEgiT4G6jwN/h/RUSCYdW8qeXYAoBaji2QJIkZJ3/IRAkzFtEusy6bGl/PbBEEggynRo0azJ49G5VKxdu3bzlz5gwzZ87k8OHDrFixAkPDhGHw0KFD6dChg0Zec3Nzjd/58uVj7969/PDDf3323r17sbOz4/nz5+kuuyRJxMfHyzJ+bWxts06s0gyNBiYQfG1UsRJPNsfxZHMcqlgRfSir8609L3e7yhq/S31XJZMk+Tp8a883OxMdHc3PP//Mzz//THR01vWrEQjSgpGREba2ttjZ2eHq6sqAAQNYvnw5p0+fllddIEExsbW11fj3aZCJVq1asXu3pt/k7t27adWqVZLr+vn58f3331O2bFmqVq3K6NGjCQlJMK0dO3Ysly9fZuPGjXKE28DAQC5duoSzszNnzpyhTZs2uLu74+vrS0xMDDNmzKBKlSq4u7vTuXNnbt26JV9Lne/kyZO0aNECd3d32rdvz/379zVkOnz4ME2bNsXNzQ1PT0/Wr1+fbN05Oztz9OhRAGJiYpg2bRrVq1fH3d0dT09PVq1alfIDSCfEyoogR6A2N4mMiKT6uIToQ38uP4VpFo8+ZGVlybt37zNbjEyjj08VQq8nrDwUameQydJkPP+8uiivrADcenkhE6XJeJbWPp6t2mNGk5Xbe3x8PAcOJESAU+9kLxDkRKpUqYKLiwtHjhyhffv2qc7n6enJH3/8ga+vL+XLl8fX15f3799Tp04dli9fLqd7/fo13bp1o0OHDowdO5bo6GjmzZvHsGHD2LhxIxMmTMDf35/ixYszdOhQAGxsbGRTtLlz5zJmzBgKFixIrly58Pb25vDhw8yZMwcHBwfWrl1Lv379OHLkCFZWVvJ1vb29mTBhAnnz5mXhwoUMHDiQw4cPo1AouH37NsOGDWPw4ME0adKE69evM3XqVKysrJIEwNLGpk2bOH78OIsWLSJ//vy8ePGCly9fprruvhShrAhyBGr7awNTQ8aMGQOAhWkuFIaKzBQrRUwMzTAxjMlsMTKNpfWOsDMkYaaqXb02GCpybpe05MbPLD4/DkmSKPVdFW69vMCSC+NxsSnPkDJemS1ehmCqnytbtceMJiu3d4VCIT8rheLbfk6CnE/RokU1Vh7mzZvHr7/+qpFm5cqVVKpUSf6tUCho0aIFu3btonz58uzatYsWLVokaS9bt27F1dWVESP+C7Aya9YsatWqxZMnT3B0dEShUGBiYqLV1Gro0KFUq1YNgIiICP744w9mz55NrVq1AJg+fTrnzp1j586d9OvXT843ePBgOd+cOXOoVasWf//9N02aNOG3336jSpUqDBo0CABHR0f8/PxYt25dqpSVFy9eULhwYcqVK4eenh4ODg4p5klPcu7IQPBNolAo6NGjR2aLIUglNhb56N9nQGaL8VUYWnYuy2+O1/BRcTWvwKCyXuQyyrkhY0V7zB6IvlPwLSFJEnp6/4WX7Nu3b5JBe2JHejXt2rWjY8eOjBgxgkOHDrFt2zbi4+M10ty5c4dLly5RtmzZJPmfPn2Ko6NjsrIljo779OlTYmNj8fDwkI8pFApKlSrFo0ePNPKVKVNG/tvKygpHR0ceP34MwOPHj6lbVzOgjYeHBxs3biQ+Ph4Dg+QtG1q3bk2fPn1o1KgRNWrUoHbt2lSvXj3ZPOmJUFYEAkGWQRWaNWed0wNzzBlpOw+/7cd4+eoxeUPy8t0bO1RlHxE3tgT6ljl3Nlvf2iizRRAIBAKZR48eaUTusra2pnDhwinmUyqVFC1alBEjRuDk5IRSqeTu3bsaaVQqFXXq1GHUqFFJ8qfGad3UNKm5bGLFCpIqWykhSV/mM+jq6sqxY8c4ffo058+fZ9iwYVStWpXFixd/UbmpRSgrghyFSqXixYsXAOTPnx+96Kzt1KsyikOKjE85YQ5FpVLx4uX/P6/v8hPa6FQmS5TB6Othl8sSj9kDMatoR8TlVwSNu8i7zhdAlbXf1c9BJal4JYVi/UdV8n+XXw4V+q2Sldu7SqXi5bvXQELf+a0/K0HO5cKFCzx48EDeTySttG3blqlTp+r07XJ1deXw4cM4ODjojOSlUChQqVIOWV+oUCEUCgVXr17F3t4egNjYWG7fvk3Pnj010t64cUNO8/79e/z9/SlatCgATk5OXLt2TSP9tWvXKFKkSIqrKmosLCxo0qQJTZo0oWHDhvTr1493795p+M1kFEJZEeQooqKiaNCgAQBXrlwhos65TJYoeYIzW4BMJlKKplF4gp38IXMvTPWMM1miDEYl4TC7MpbNigBg2awIkgTPBp3OXLkyiGhi6RQxHVp8I883BbJye0/cFq9cuZIkEpJAkB2JiYnhzZs3GqGLV61aRZ06dTSieIWHh/PmzRuNvKamplhYWCQps0OHDjRq1IjcuXNrvWaXLl3Yvn07I0aMoF+/flhbWxMQEMCBAweYMWMGBgYGODg4cPPmTQIDAzEzM9M54DczM6Nz5854e3tjaWmJvb09a9euJSoqinbt2mmkXb58OdbW1uTJk4eFCxdibW0tb+jYp08f2rVrx7Jly2jSpAk3btxg8+bNTJ48OVX1uGHDBmxtbXFxcUFfX59Dhw5ha2ursw7Sm0xTVkJCQvD29pZ/x8XFERoaytixY+Vjc+bMyQzRBNkcbUuogqyLCd+WiZBZRU07aPNKSe2icxLf2vPNzoi+U5DTOHPmDNWrV8fQ0JDcuXPj4uLCxIkTad26tcbq4eLFi5OYNHXs2JFp06YlKdPQ0BAbGxud17Szs2Pr1q3MmzePvn37EhMTg729PTVq1JCv2adPH8aOHUvTpk2Jiori2LFjOssbNWoUkiTx888/Ex4ejpubG2vXrk2yYePIkSOZOXMm/v7+uLi4sGLFCoyMEvpfV1dXFi1axOLFi1mxYgW2trYMHTo0Vc71kKA0rVmzhoCAAPT19XF3d2f16tVfbQVWT/pSQ7Zk2L17N+PGjWP27NlJKkS9I2hyfBojWo2zszMVK1Zk06ZNOvNeuXIFIyOjbBHVxMrKinfv3mW2GDmSrGpyocbS0pL377NmKNPMILj28cwWIcMptLymvLIC8O5P/xy7sqImz0nPzBYhS5DV27ueac4PH54ZZPVvfGxsLKVLl85sMQSfyaVLl+jRowdXrlz5aisdX5tMW1kpUKCATmVEIEgvsvrHV9/MEL2YrC3j18TmUK3MFiFD+TjuFkETLyFJCSsq4Zde8XzSJRQe1uSaVSqzxcswsno7/FqI9i4QCARp56soK+PGjWPcuHE0adKEhQsXflYZ58+fp3fv3uksmUAgyErk9KhRBj9ZEuv9XmMlRVEpD7mmuaFvlbPvXSAQ5BwkSYLYiK97UYVZmiJgCXIOGaqslChRgsGDB8u/ixcv/tllFSxYUKOsr70hjSB7EBMTw4wZMwCYOHGibK8pyJqEvX3FnPkJExhjRw7Psc8rNuw99zfO5N2Da6AHxk75sLGtSIEuXTAukY84wuFDeGaLme7ExMTgvXgZINpjVkf0nYLUIkkS8WtbID298lWvq1eoIgb99gmF5RMqVaqU4y2VMtRnJTMRPivfJhEREVSoUAHQjGgTHx2ZmWLpJKvbsGc0R/pXY5RvNADzyhtjbJAzP0J6+voozHJTcagX+Vwr8frOJS4vHkNsxAekVISvzK5Ex0vy87147gxm37gDd1Zu7xGRkVSuVgPQ/awMjL/t5/e5ZPVvfFp9VhKUlZZITy9noFRJEcrKt4sIXSzIURgaGjJ06FD5bzWnBn69nVYFqcdAD5oV+L/27js8qjJ9+Ph3kkw6qYQAIXSYYOgiNYiU3Y0BeUUpgtJZxQUiNQlSoyhFJUgzIOxPAUUpAVbRgKCs9CZdiqL0EiIkSOpk5rx/ZBkZQkmdM+X+XBcXM5Nzztwzz3PKPecpLqbH9koxGmkePZNqbZ8DyP9fUdgxfajKkZWte8t398hOuDjZcSHbuDyj8tiy6vDvg5YOS1ghjUaD85ANdtMMTKfTsWDBAtMwv8URFxfH7du3WbhwYSlGJu6SZEXYFVdXV1577TW1wxCF5OKk4R8hjnEYqhDewvx5/ZYqRWI5jlS+tk7KShSFRqMBVy+1wyiUGzdukJiYyLZt27h+/TqBgYHUq1eP/v3706pVq1J5jwkTJpR4lviS+Oijj/jvf//LyZMn0Wq1HDhwoMAyV65c4a233mLPnj24ubnx3HPPERMTYxNNPuXIJBxCu492qB3CA1lzsxBLcKQ7Xikn9prurACkHN+jYjSWY637nhocfX8XwtIuXbpE79698fHxYdy4ceh0OvLy8tixYwfx8fEkJyeXyvuUK1euVLZTXHq9nsjISBo3bsyaNWsK/N1gMPDaa6/h7+/P559/TlpaGrGxsSiKwqRJk1SIuGgkWRF2RVEUbt26BYC/v7/plrG1trV2cffEOTtX7TBU0ybhO279ry23v5+f3bZFPr4whv3z3wRFoUL9lqQc38P+BRPw0z1J/ddnqh1emVEUhfSM/P5i9+6Pjsqa9/eHHTuFsGXx8fFoNBpWr15t6sMK+QM+vfjii6bnt27dYtiwYezYsYPg4GBiY2NNcwEaDAYmTZrEnj17SE1NpVKlSvTp04f+/fub1r+/GVjfvn3R6XS4urqyZs0atFotL730EiNGjDCtM2/ePNauXUtqaip+fn5ERkYyceLEYn3Ou83fk5KSHvj3HTt28Ouvv7Jt2zaCg4NNMcfFxTFq1Ci8vb2L9b6WIsmKsCtZWVm0bZvfSfTeDvbCOhm07nSMyr/bYM/lVX/YLH5ePNGsj0pAeEueeHUaruX8VYysbGVmZtK2dcEBL4T1kWOnsDdpaWls376dUaNGPbA+3zuB4vz58xk3bhwxMTEsX76csWPH8sMPP+Dn54fRaKRixYrMmTMHf39/Dh06xOTJkwkKCiIqKuqh779u3ToGDhzIqlWrOHz4MHFxcTRt2pQ2bdqQnJzMJ598wuzZs6lTpw6pqamcOnXKtO7kyZP56quvHvn5Nm7cSOXKlQv1XRw+fJg6deqYEhWAiIgIcnNzOX78OC1bWnezZElWhBCijLmW86fxmAVkXP6NzJSLBNd+AmO5ILXDEkIIu3XhwgUURaFmzZqPXbZbt2506dIFgNGjR7NixQqOHj3K008/jVarNd25gPypNA4dOkRycvIjkxWdTmeacqN69eqsWLGC3bt306ZNG65evUr58uVp3bo1Wq2WypUr07DhXxMDv/HGGwwePPiRMVeoUOGxn+uu1NRUypcvb/aar68vWq2W1NTUQm9HLZKsCLvi6enJiRMn1A5DFJKjlZdXSE28QmriY+VDmZYWRytfWyZlJezN3Q7vhWnSqNPpTI89PT3x8vLi5s2bptdWrlzJ6tWruXLlCjk5Oej1esLCwgq9TYCgoCD++OMPACIjI/n000/p1KkTbdu2pV27drRv3940imlgYCCBgYGF+6CF9LDvwRaafNp1smIwGNQOoVD0ej16vV7tMIQKpOwdk5S7Y5Jyd0zWXu62cq1UVNWqVUOj0XD27NnHDkt8/5x8Go0G4//mwPrmm2+YPn06sbGxNGnSBC8vL5YuXcqRI0ceuc17p0+4u827CVSlSpVITk5m586d7N69m/j4eJYuXcry5cvRarWl3gysfPnyBeJNT09Hr9eXelJUFuw2WXF1dSU3N9cmdsKcnBxyc62z06UoW1L2jknK3TFJuTsmKXd1+Pn5ERERwWeffUbfvn0L9Fu5ffu2Wb+Vhzl48CBNmjTh5ZdfNr124cKFEsfn7u5Ox44d6dixI3369OHZZ5/lzJkzhIeHl3ozsMaNG5OYmEhKSoppvZ07d+Lq6kr9+vVL9DkswW6TlZCQEFNWbO38/f1No7AIxyJl75ik3B2TlLtjknJXz5QpU+jduzc9evQgOjoanU6HwWBg586drFy5km+//fax26hatSrr169n+/btVKlShQ0bNnDs2DGqVKlS7LiSkpIwGAw0atQIDw8PNmzYgLu7u+lOSVGbgV25coX09HSuXLmCwWDg5MmTpti9vLyIiIigdu3axMTEEBMTQ3p6OjNnzqRnz55WPxIY2HGy4uzsjLOzs9phFIpWqy1wC1I4Bil7xyTl7pik3B2TlLt6QkNDSUpKIjExkZkzZ5KSkkJAQADh4eFMnTq1UNvo3bs3p06dYtSoUWg0Gjp37kyfPn348ccfix2Xj48PixcvZsaMGRiNRurWrUtiYiL+/sUbHXLu3LmsW7fO9Pz5558HYNmyZbRo0QJnZ2cWLVpEfHw8vXv3xt3dnS5duhAbG1vsz2BJGkXNKTfLkC39imGLv7oYDAZT+8dGjRrZTGJobWyx7B9E6kPR2Eu5lwV7rktS7kVnD/XBFsq9uBfJQliC3d5ZEWUrOzvb1GHt4sWLeHl5qRyRUJPUh6L59WweJ08qhIRAjerWPxKLJUldEveS+iCEkGRFFItGoyE0NNT0WDi2u/XBaIT025Crt8sbtiWWflvh/Q/g8JF002uNGymMHQO+PrIfAWRlIccWYSLnGiGENAOzArZwizgryy6rier8/PxJS7Pusi+Kvz0r9eRRnJzAywvGjdHQqAEcOQbvfaCQkQE2Mh6IRXz3rX1elNrb/l5SHh72Wc73s4VzvDQDE9ZM7qyIQpGL0LJy8/GLCLthNOYnKh2eyb9I6/AMKApMiZf96172e7yR/f1eO7Y5RrIihCgZJ7UDEEIIR9Kogfnzxg3ViUMIIYSwBXJnRRTK/c0ysrOz+de/hgCwcOES3N3d1QjL5tlLs5C79WHXbgip+jFOTlIfHubIsfw7KncdPqpaKFbJaMymWsg/Afs7ttjL/m5J2dnZDBmSf65ZssS+6oMQonAkWRGFcn/bYqPRyKZN+ZMpuboaHabtcWnz9NSQk2P739299WH1F0Y8PW3/M5WE5ubvON2+jNEnBCWghun1SVMUZs9RUJT8OyqHj0LChwqNG8Hb8Y79nd2VmWmkQX37PLbYy/5uSQaDgW+++cb0WAjheCRZEcXi6upKQkKC6bFwbPfWhwpBbmi1xbggy7SD9vxZabhvmYLL5QOml/JCmpHdKR48/JgWpyF+lidT4v+aIO6pJnqmxGTi52oD/TQ8A8r8Lby93OTYIkzkXCOEkNHArIAtjBRil/SZakeAn58faWlpaodhFbznPal2CCWmaJzAtRzZf5uKMeRJnC4fxP27KZB7B43y13BfZ/+sxcWMqoR6XaBWubMqRlw0d0YcVDsEm1aq+7vWs3S2I8qcLZzjZTQwYc0kWbECtnAgs0fes+upHYKwQ1ldEjDUjTQ9dzn9Le4bR6sYkbBHd0afVDsEUUi2cI6XZEV06NCBfv36MWDAAAB0Oh0LFiwwTcqqJmkGJorFaDRy+vRpIL9COznJwHKOzKgonEzNb09er7wzTg48eZsxxPwOkaFKM5UisU1Sl8S95FwjiisuLo5169YB4OLigq+vLzqdjs6dO/PCCy+Y6lKHDh24fPlygfXHjBnDq6++yqVLl+jYsSPOzs788MMPBAcHm5ZJSUnhmWeewWAwsHXrVqpUqVKo2Pr27UtYWBgTJkwohU9aNnbs2IGvr6/aYQBlnKwkJSUxfvx40/OoqChT29Oi2rVrFwMHDjQ9b968OcuXLy9xjKJ4srKyaNOmDQAXL17Ey8tL5YiKzhqatNhLM7CMjEya1KwLwMXfzuDlVfQmKvbQDAzA6fJBszsrzpcOPGJp22KJfaY06pK1spf93ZLs4Vwj1NO2bVumT5+O0WgkNTWV7du3884777Bp0yY++ugjXFzyL4Ojo6Pp2bOn2br317UKFSqwfv16XnvtNdNr69evJzg4mCtXrpR67IqiYDAYTDFaWlBQkCrv+yAW+QY6duxIvXr1qFOnDpBfAD/++CPff/89P/30E1euXCEvL49q1aoRFRXFwIEDcXNzM9tGaGgow4cPB2D+/PmWCFs8RmBgoNohlIwVtPnWuHqBNlftMEpOq/xVH7Qexfpu7wzdWcpBWZ77V2/gtvVtchUFQ5VmOF86gOv308ir8hTZXeaYlvPz8yUtLV29QIvLEvtMKdQla2U3+7uF2fy5RqjG1dXVdNEdHBxMeHg4jRo1YsCAAaxbt44ePXoA+YnJ4y7On3/+eZKSksySlaSkJJ5//nkWLlxotuyvv/7KzJkzOXDgAB4eHrRp04bx48cTEBBAXFwc+/btY9++fSxbtgyArVu3cvnyZfr168eSJUtISEjgzJkzLFmyhKZNmzJr1iw2btzInTt3qF+/PuPHj6dhw/xJuvbu3Uu/fv1YtGgRs2fP5vfffycsLIxp06ah0+lMMW3atIm5c+dy/vx5KlSowCuvvMKgQYMe+nnvbQaWm5vLjBkz2Lx5M+np6QQFBdGrVy+z76IsWSRZ6dSpEy+88ILpeW5uLq+++iqurq40b96ciIgIcnNz2bFjBwkJCWzZsoUVK1aYjaceGhrKiBEjAElWrIGXlxe//PKL2mEIK1Eq9cECI02Vteyuc3H/ZqxZH5W8aq3JjnofPPw5f+s0l/88Rz33Rvh7VlQxUuslxxZxL6kPorS1atWKsLAwNm/ebEpWCqNDhw588cUXHDhwgGbNmnHgwAHS09Np3769WbKSkpLCK6+8Qs+ePYmLiyMnJ4f333+fkSNHsmzZMiZMmMC5c+eoU6cO0dHRAAQEBJiaor333nvExsYSGhpKuXLlmDVrFps2bWLGjBmEhISwZMkShgwZwubNm/Hz8zO976xZs5gwYQLly5cnISGB119/nU2bNqHVajl+/DgjR45k+PDhREVFcejQIeLj4/Hz8zO7Pn+Y5cuX8/333zNnzhwqVarE1atXuXbtWqG/u5JS5d6Sk5MTo0aNok+fPvj4+Jhe1+v1jBgxgh9++IEVK1aYJoISQtiGtKxUtUNQX9RMXG7+jkv6ZfJ8Q8gLqMHtnFTmfD+Qo9f3mBZrGNySkW3ew8dNOrbez8+jvNohCCHsWM2aNU19oQDef/99PvzwQ7NlEhMTadGihem5Vqula9eurF27lmbNmrF27Vq6du2KVqs1W2/lypWEh4czevRfP1q9++67tGvXjt9//50aNWqg1Wpxd3d/4N2c6OhoU9PHzMxMvvjiC6ZPn067du0AePvtt9m5cydr1qwxu04ePny4ab0ZM2bQrl07vvvuO6Kiovi///s/WrVqxbBhwwCoUaMGv/76K0uXLi1UsnL16lWqVavGk08+iUajISQk5LHrlCZVkhWtVsvQoUMf+Pprr73GDz/8wP79+yVZsQFZ+gy1Q7Bp7npXu/oOu6+sr3YIVslJ44SX1odJ7RfTILglx67vYc7OGIasa4fxniGNRb6v+trOcM5FYW/7u6V4aKWfiihdiqKguWfwjsGDBxe4aL+3I/1d3bt3p1evXowePZrk5GS+/PLLApOVnjhxgr1799KkSZMC61+4cIEaNWoUeP1eDRo0MFter9fTtGlT02tarZaGDRty9qz5cbJx48amx35+ftSoUYPffvsNgN9++42OHTuaLd+0aVOWLVuGwWDA2dn5kTF169aNQYMGERkZSdu2bXnmmWeIiIh45DqlyepGA7vbkehxX5xQV3Z2NtHR0Ww9m0S1ns44FWcSQGE3jHqF86vyD9hSHwoyKkZGtplFuxpdAWhXoyuKojBtm2Xa+9oSo16hfmQ1QOqSyK8PtQ/+PwDmzp1r1jxciOI6e/as2chd/v7+VKtW7bHr1a1bl5o1azJ69Ghq1apF3bp1OXnSfBhxo9FI+/btGTt2bIH1C9Np3cPDo8BrmvtGRbw/2Xqcks5SEh4eztatW/nxxx/ZtWsXI0eOpHXr1sydO7dE2y0sqxsDcO3atQCmW1nCOhkMBtasWcOtQ0bkh2GhGOHWIaPUh0doENzS7HnDiq1UisS6SV0S91KMsGbNGtasWVPgF2whimP37t2cOXOGv//978Va/8UXX2Tfvn28+OKLD/x7eHg4v/zyCyEhIVSrVs3sn6dn/oAhWq0Wo/HxB7iqVaui1Wo5ePCvkRj1ej3Hjx+nVq1aZssePnzY9Dg9PZ1z585Rs2ZNAGrVqsVPP/1ktvxPP/1E9erVC31zwNvbm6ioKKZNm0ZCQgKbNm2y2OiGVnVn5ccff+TLL7+kVq1aRer0JCzP1dWVd955B70hlwH9+xdosykKxxYmCysMvV7PJ4ZPWXJgGk5WdVSxHseu7zHdWQE4em23itFYLycXmPrWFAC7O7bYy/5uSXq9ns9YCeSfd4QoitzcXG7cuGE2dPGiRYto3749zz//vGm5jIwMbty4Ybauh4cH3t7eBbbZs2dPIiMjzfpc36tPnz6sWrWK0aNHM2TIEPz9/Tl//jwbN25k2rRpODs7ExISwpEjR7h06RKenp5mHeXv5enpSe/evZk1axa+vr5UrlyZJUuWkJ2dTffu3c2WXbhwIf7+/gQGBpKQkIC/v79pQsdBgwbRvXt3FixYQFRUFIcPH+azzz5jypQphfoeP/nkE4KCgggLC8PJyYnk5GSCgoIe+h2UNqu5rDh27BijRo2iXLlyfPjhh3JQsnJarZbXX39d7TBsnofWi2w7GMrUQwvRw9+gX9bLaodild76fghzd49HURQaVmzF0Wu7mbfnTRpWbMXk9h+rHZ7VsdcO9vayv1uShxY514hi2759OxEREbi4uODj40NYWBgTJ06kW7duZhOMzp07t0CTpl69evHWW28V2KaLiwsBAQ8fvTI4OJiVK1fy/vvvM3jwYHJzc6lcuTJt27Y1veegQYOIi4ujc+fOZGdns3Xr1odub+zYsSiKQkxMDBkZGdSvX58lS5YUmLBxzJgxvPPOO5w7d46wsDA++ugj07V0eHg4c+bMYe7cuXz00UcEBQURHR1dqM71kJ80ffzxx5w/fx4nJycaNGjA4sWLLTZJq0YpaUO2R7g7KeT06dMf+YX8/PPPDBgwAKPRyL///W/T2NEPo9PpHjsppC39eiW/tjkuKXvHkJ79B+9u+xcHr/zX9FoTv9ZMjPoYX3eZQ8JRyP7umGyh3P39ZVRCW3V3npX9+/db7E6Hpal+Z+XEiRMMGjQIg8FQqERFWAej0cilS5cAqFKlisWya2Gd7taHvFs5VKkcIvXhPl54EV97MQe+XMvFS6cpf7M8FW8E88fKA7hNb4mLv9vjN+IgjEYjl65cxsXfTY4tQs41Qgh1k5UTJ04wcOBA8vLyWLp0KY0aNVIzHFEEWVlZpmHyLl68iJeX+dCSxky9ClHZHoOr3i6+q4zMDFN9SPaaiYdGLr4LcNIQUM6TBtNfx7N5MJn7rnN5/B5+6fQfMJbZDW6bk6XkEJkRC8D5M7/h5Wk/w9bay/5uSfceW+6tD06e9tOXyRYpikJ2XqZF39PdxbNII2AJ+6FasnI3UdHr9SxZsuSB41EL63Z3VIsHORG20oKRCLVlKTm4I/3MHsmoEDK9Jb5dqgPg26U6igIXh/2oblxW6G5dOtlktSS+Du7eY8u99aHBhX5qhuXQFEVh8BftOXLFsoOENKrcmqUvfS8Jy31atGhhNsGlPVIlWUlLS2PgwIGkp6fTtm1bdu3axa5du8yWKVeuHAMGDFAjPFEIXl5eplvzQnho3NjkPUvtMKyeZ3PzSca8WhScdMzRSV0S95L6YK0kYRCWo0qycufOHdLT04H8kRq2b99eYJmQkBBJVmxY+KneaodgE/z8/ElLs+6Ol0Uhd9QeLXPfddOdFYCMvdfVC8bK2eMxxN72d+GYNBoNS1/63m6agel0OhYsWGAa5rc44uLiuH37NgsXLizFyMRdqiQrVapUsftbVo5O2hMXjrOXFqdc+/mu6h3qqXYIVuvC0P9yedJeFCX/jkrG3utcmbwXr5bBVP2ondrhWR17PIbY2/4uHJdGo8FDaxv9yW7cuEFiYiLbtm3j+vXrBAYGUq9ePfr370+rVqUzOe+ECRNKPEt8cV26dImFCxeyZ88eUlNTqVChAl27dmXo0KFm04BcuXKFt956iz179uDm5sZzzz1HTEyMTUwVYpFkZfz48YwfP56oqCgSEhKKtY1du3YxcODAUo5MFFdOTg4xMTEAzJo1Czc3aVfuyKQ+PF7VRe24OGK7WR8V96d8qZrYDpcAdxUjsy5Sl8S9pD6Ikrh06RK9e/fGx8eHcePGodPpyMvLY8eOHcTHx5OcnFwq71OuXLlS2U5x/PbbbyiKwltvvUW1atU4c+YMkyZNIisri9jY/MFKDAYDr732Gv7+/nz++eekpaURGxuLoihMmjRJtdgLq0znWTl58iRbtmwxPa9Tpw6RkZHF2tbFixdZv3696XlISMgj526x9jHN72ULY7DfLyMjg9DQUODBo4GJwrHFsn+Qe+vDr8ePPHLwBUeWc/sWB6e9TcaJS+S4/kGOewoV6rek+YhZuPnIPAcAmZmZ1K6fPzKkvR1b7GV/tyR7ONfYQrnb6zwr//znPzl9+jTJyckFzku3b9/Gx8cHnU7HtGnT2LZtGzt27CA4OJjY2Fg6duwI5F/oT5o0yXTnolKlSvTp04f+/fubtnV/M7C+ffui0+lwdXVlzZo1aLVaXnrpJUaMGGFaZ968eaxdu5bU1FT8/PyIjIxk4sSJpfK5lyxZwsqVK02TTf73v/9l6NChbNu2jeDg/L6SGzduJC4ujt27d+Pt7V0q71tWyvTOSr169ahXr16pbCs0NNSskIW6NAY942NjTI/zsi3bdtVe6LNc7eK7u7c+fDWwOS5O0vnyQTROTmg9fWg+YyYVwluQcmIv++bGsvH1Z1CMRrXDswp5RoUuVVxo8PJouzu22Mv+biku7p5otVomTJgAgFYrTehE4aWlpbF9+3ZGjRr1wB/Q7p1Acf78+YwbN46YmBiWL1/O2LFj+eGHH/Dz88NoNFKxYkXmzJmDv78/hw4dYvLkyQQFBREVFfXQ91+3bh0DBw5k1apVHD58mLi4OJo2bUqbNm1ITk7mk08+Yfbs2dSpU4fU1FROnTplWnfy5Ml89dVXj/x8GzdupHLlyg/8259//mk2w/3hw4epU6eOKVEBiIiIIDc3l+PHj9OyZctHvpfaVJ8UUtimdb2e4O4usm7bXFVjEdbBdMiUROWhFKOR5tEzqdb2OYD8/xWFHdOHqhyZ9XBx0vCPEBfYNleOLQ7u5W+v4OrqypgxY9QORdigCxcuoCgKNWvWfOyy3bp1o0uXLgCMHj2aFStWcPToUZ5++mm0Wi3R0dGmZUNDQzl06BDJycmPTFZ0Oh3Dhw8HoHr16qxYsYLdu3fTpk0brl69Svny5WndujVarZbKlSubTYr+xhtvMHjw4EfGXKFChYd+7hUrVhAXF2d6LTU1lfLly5st5+vri1arJTU19ZHvYw0kWRFCCAuqEN7C/Hl96/5FSwghbNHdXg6FGUFMp9OZHnt6euLl5cXNmzdNr61cuZLVq1dz5coVcnJy0Ov1hIWFFXqbAEFBQfzxxx8AREZG8umnn9KpUyfatm1Lu3btaN++PS4u+ZflgYGBBAYGFu6D3uP69esMGTKEyMhIevToYfa3h30PtjBvjSQrolh6Jv3CH//bkQMDAmyislsjPz8/0tLS1A6jxBRFMdWHLYObS314hJQTe013VgBSju9RMRrroygKd/Lg+U/32d2xxV72d0tSFMV0gRcYGGhX9UGUrWrVqqHRaDh79uxjhyW+v4mhRqPB+L+mud988w3Tp08nNjaWJk2a4OXlxdKlSzly5Mgjt3k38bh3m3cTqEqVKpGcnMzOnTvZvXs38fHxLF26lOXLl6PVaovVDOz69ev069ePxo0b8/bbb5stW758+QLxpqeno9fri5UUWZokK6JYco3wRIN7O8FKh+ri0Hp44ZKdq3YYJZaRkWGqD9LB/uG2v/NP9i94ExSFCvVbknJ8D/sXTqBCg1a0fXOx2uFZhbsd7N9s0Mjuji32sr9bUmZmJnXr1gVst4O9UIefnx8RERF89tln9O3b96Ed7B/n4MGDNGnShJdfftn02oULF0ocn7u7Ox07dqRjx4706dOHZ599ljNnzhAeHl7kZmB3E5Xw8HCmT5+Ok5OT2bKNGzcmMTGRlJQU03o7d+7E1dWV+vXrl/izlDVJVoQQpcrNNwB3uaB4oLYTP2bnzGFmfVQqNnmaNrELcPe1/l+3LMGglWGchRClY8qUKfTu3ZsePXoQHR2NTqfDYDCwc+dOVq5cybfffvvYbVStWpX169ezfft2qlSpwoYNGzh27BhVqlQpdlxJSUkYDAYaNWqEh4cHGzZswN3d3XSnpCjNwK5fv07fvn2pVKkSsbGxZs3XgoKCgPzO9LVr1yYmJoaYmBjS09OZOXMmPXv2tPqRwECSFVFM97fnFI5N6kPhuPsG0vHdL1DSrnH51BHKVaqBb7W6aodlVaQuiXtJfRAlERoaSlJSEomJicycOZOUlBQCAgIIDw9n6tSphdpG7969OXXqFKNGjUKj0dC5c2f69OnDjz/++PiVH8LHx4fFixczY8YMjEYjdevWJTExsVhDSO/cuZPz589z/vx5nn76abO/3Z2A3dnZmUWLFhEfH0/v3r1xd3enS5cupnlYrF2ZzrOiJmsf0/xetjAGuygbUvaOScrdMUm5OyZbKHd7nWdF2Ae7vbNiMBhMnaOsnV6vR6/Xqx2GUIGUvWOScndMUu6OScpdiJKx22Tl8uXL5ObaRkfGtLQ00tPT1Q5DqEDK3jFJuTsmKXfHZAvl/rA5O4SwBnabrOTm5uLs7Iyzs7PaoTyWm5sbrq6uaochVCBl75ik3B2TlLtjsvZyNxgMaocgxCPZbbIC+R2K7h872xpptVqbiFOUPil7xyTl7pik3B2TlLsQJWPXyYq9MxgM/PzzzwA88cQTNnEXSdgOqV+l7+IlZ65dc6FuHQ2+vmpHYx+knoqyJPVLCPVJsmLDcnJyeOmllwDYv3+/TMQnStW99Wvr9wfw8JD6VVx/3tHw8RJffj75V1OQJ+r5888h6ZTztssBGS0mKytXjoOizMh5Vgj1SbJiwzQaDZUq5U8glJOj4b4JS4UNyMqG7Gy1o3iwnJz8+pWa6syw6Ao4OclJuricnMDLC96aqqFRAzhyDN77wJUx44KwkUELrZbRmGkzx0Fr3t9FQe7u+efZuxP1aTQalSMSwjHZ7Twr+/fvx9XV1Sbaifr5+ZGWllasdXv0Di7dYIQQZeKtqRo6PPPXxc7WHxSmxNvl4VcIu7B65fVS2U5JzvGWoNfradSokdphCPFQVvwblBBC2I9GDcyfN26oThxCCCGELZFmYDZu+f+Vzi8/Qh2+fn6kW/EvbgB9B8rdu9Jw5Bh0eOav54ePqhaK3bGV46At7O9CCMfUoUMH+vXrx4ABAwDQ6XQsWLCATp06qRsYkqzYtJycHMaNGwvA+++/j5ubm8oRiaLycIccd7WjeLCcnBzGjh1LoB+89dYHUr9KYPYcP2YnaFEUJxo3zE9UEuYYeaKentEj09QOz6blHwfHANZ/HLTm/V082N3jIFh//RLm4uLiWLduHQAuLi74+vqi0+no3LkzL7zwAk7/6+DWoUMHLl++XGD9MWPG8Oqrr3Lp0iU6duyIs7MzP/zwA8HBf/2Al5KSwjPPPIPBYGDr1q1UqVKlULH17duXsLAwJkyYUAqftGzs2LEDXysZtlKSFRtmMBj4/vvvTY+FKE331i9vrzw8Pa13UjNLck0/h/bPy+jLhZDrW71Q64wZmcaH8/2YEv/Xd9iwgZ43hqfh4yP9VkoiMzNPjoOizMh51ra1bduW6dOnYzQaSU1NZfv27bzzzjts2rSJjz76CBeX/Mvg6Ohoevbsabaul5eX2fMKFSqwfv16XnvtNdNr69evJzg4mCtXrpR67IqiYDAYTDFaWlBQkCrv+yCSrNgwrVbL1KlTTY+FKE2FqV/O2WmWC0hlTjm3CT6QgEfKEdNrWRUacb3ZKIxuPo9c198Vpo6+xcXLrlxN0VKnlhv+Pjfz/2ijo0MZ3P3UDgGQ46AoW1K/bJurq6vpojs4OJjw8HAaNWrEgAEDWLduHT169ADyE5PHXZw///zzJCUlmSUrSUlJPP/88yxcuNBs2V9//ZWZM2dy4MABPDw8aNOmDePHjycgIIC4uDj27dvHvn37WLZsGQBbt27l8uXL9OvXjyVLlpCQkMCZM2dYsmQJTZs2ZdasWWzcuJE7d+5Qv359xo8fT8OG+R0f9+7dS79+/Vi0aBGzZ8/m999/JywsjGnTpqHT6Uwxbdq0iblz53L+/HkqVKjAK6+8wqBBgx76ee9tBpabm8uMGTPYvHkz6enpBAUF0atXL7PvoixJsmLDtFqtaUezFZq8LLVDsC56N6v9Tlw10LNbl/89y4O8vALL1Fz3gmWDUpGicQLXcmR1ScAY8iROlw/i/t0Uqn07CI1SuPGHa959cK6sorScX3tsVDsEoHD11GpY8f5eHIqLh9ohlDlbPM+KR2vVqhVhYWFs3ry5SGXboUMHvvjiCw4cOECzZs04cOAA6enptG/f3ixZSUlJ4ZVXXqFnz57ExcWRk5PD+++/z8iRI1m2bBkTJkzg3Llz1KlTh+joaAACAgJMTdHee+89YmNjCQ0NpVy5csyaNYtNmzYxY8YMQkJCWLJkCUOGDGHz5s34+fmZ3nfWrFlMmDCB8uXLk5CQwOuvv86mTZvQarUcP36ckSNHMnz4cKKiojh06BDx8fH4+fnxwguPP48vX76c77//njlz5lCpUiWuXr3KtWvXCv3dlZQkK8Kiaq/urHYIVsd6brSKR9EoRrL+NhVD3UgADHUjyVEU3DeOVjkydci+XDz2tL//0vt7tUMQolhq1qzJ6dOnTc/ff/99PvzwQ7NlEhMTadGihem5Vqula9eurF27lmbNmrF27Vq6du1a4I7bypUrCQ8PZ/Tov84N7777Lu3ateP333+nRo0aaLVa3N3dH3g3Jzo6mjZt2gCQmZnJF198wfTp02nXrh0Ab7/9Njt37mTNmjUMGTLEtN7w4cNN682YMYN27drx3XffERUVxf/93//RqlUrhg0bBkCNGjX49ddfWbp0aaGSlatXr1KtWjWefPJJNBoNISEhj12nNJVpspKUlMT48eNNz6OiokhISCjWtnbt2sXAgQNNz5s3b87y5ctLHKMtMxqN/Pbbb0D+judkzbOhCZtjVBROpua30a5X3hknmRANY8iTZs8NVZqpFIm4S+qpKEtynrVPiqKYTfI5ePDgAhft93akv6t79+706tWL0aNHk5yczJdfflmgL9OJEyfYu3cvTZo0KbD+hQsXqFGjxiNja9Dgr3HuL1y4gF6vp2nTpqbXtFotDRs25OzZs2brNW7c2PTYz8+PGjVqmOrub7/9RseOHc2Wb9q0KcuWLcNgMODs7PzImLp168agQYOIjIykbdu2PPPMM0RERDxyndJkkTsrHTt2pF69etSpU8f02ubNm/n66685deoUqampKIpC5cqVad26NUOGDClQSUJDQxk+fDgA8+fPt0TYVi87O5v/9//+H5A/Caanp/XPMG4tTUesha+vH+npaWqH8UCZmVk0a9UWgAO7t+PpWbDJh6P9uu50+aDpzgqA86UDKkajLmvZlwtTT62FNe/v4sFs8TwrHu/s2bNmI3f5+/tTrVq1x65Xt25datasyejRo6lVqxZ169bl5MmTZssYjUbat29vGkXuXoXptO7hUfAYprnvR5j7k63HKen87+Hh4WzdupUff/yRXbt2MXLkSFq3bs3cuXNLtN3Cskiy0qlTpwIZ63fffcepU6do0KCBqfBOnjzJ8uXLWb9+PZ9//rlZchMaGsqIESMASVbu5e/vr3YIReIIbZyLROuB4pKjdhQPpLgopvqluLg/sOx+65Zk6bBUU2lnPG5b3yJXUTBUaYbzpQO4fv82WRUacbXNlCJty8fXl9vp6WUUqWVYy75cmHpqNax4fxcPZ2vnWfFou3fv5syZM6b5RIrqxRdfJD4+3jTwwv3Cw8PZtGkTISEhDx3JS6vVYjQ+vq9j1apV0Wq1HDx4kMqVKwOg1+s5fvw4/fv3N1v28OHDpmXS09M5d+4cNWvm95SsVasWP/30k9nyP/30E9WrV3/sXZW7vL29iYqKIioqin/84x8MGTKEtLQ0s34zZUW1PivTpk174Hjlq1evZuLEicybN89iGZut8vT0ZMeOHWqHIexUYeqXtYwIZQlXIqZSadc7eN7TRyWzYjOutp6A0a3wY9Ff/vMsd/74BW8lgJBytcoiVIcix0FRlqR+2bbc3Fxu3LhhNnTxokWLaN++Pc8//7xpuYyMDG7cuGG2roeHB97e3gW22bNnTyIjI/HxefAokH369GHVqlWMHj2aIUOG4O/vz/nz59m4cSPTpk3D2dmZkJAQjhw5wqVLl/D09HzoBb+npye9e/dm1qxZ+Pr6UrlyZZYsWUJ2djbdu3c3W3bhwoX4+/sTGBhIQkIC/v7+pgkdBw0aRPfu3VmwYAFRUVEcPnyYzz77jClTCvdD2yeffEJQUBBhYWE4OTmRnJxMUFDQQ7+D0qZasvKwiZWeffZZJk6cyIULFywckRDiQW7n3FQ7BKuR1joO99sXcbtzjRzvimT7hAIGKMR3dCc3nf/7+R1O3Txoei0s4EkGPjEBb1frmHjLVvm4BagdghDCCm3fvp2IiAhcXFzw8fEhLCyMiRMn0q1bN7P+R3Pnzi3wA3mvXr146623CmzTxcWFgICHH3OCg4NZuXIl77//PoMHDyY3N5fKlSvTtm1b03sOGjSIuLg4OnfuTHZ2Nlu3bn3o9saOHYuiKMTExJCRkUH9+vVZsmRJgQkbx4wZwzvvvMO5c+cICwvjo48+wtU1f26v8PBw5syZw9y5c/noo48ICgoiOjq6UJ3rIT9p+vjjjzl//jxOTk40aNCAxYsXW6wPl0YpaUO2R7jbwX769OmF/kK+/vprxowZQ9euXXnvvfceuIxOp3tsB/v9+/fj6upqE+Oi+/n5kZaWVqrbzLaj4THtmZ+fL2lp1t0c6J/ftVY7BLvgpHHCS+vDyDazaBDckmPX9zBnZwwZ+tsYCzn0sXiwj/+2S+0QCsUW9nfxF/dSalJYFuf40qTX62nUqJHaYYhiujvPyv79+y12p8PSVB+6eMuWLZw8eZKsrCx+/fVXduzYQZUqVUxjT4uHy8nJYdKkSUD+UHb33q2SC0xRUka9wvlV+aOcVOvpjJNWRlkqCaNiZGSbWbSr0RWAdjW6oigK07ZZZlIte2XUK3Qa0ByQeipK1/JnDz3yPCuEsAyrSFbWrVtnel6/fn0SEhIIDQ1VMSrbYDAY2Lgxf0Seh3X0EqK4FCPcOpT/i3/V7oXrgCcerUFwS7PnDSu2UikS+yH1VJQlOc8+mKIoGDMtOwGrk6dLkUbAEvZD9WRlxowZzJgxgz///JOff/6ZhIQEXnjhBebNm0erVnIifxStVktsbKzp8b1spVmEo7PmZiF6fR6r01bx5ekPcVL9SGEfjl3fY7qzAnD02m4Vo7EPTi4wZlz+oAc9/tETrdZ6K6s17+/iwR51nnVUiqJw5G+rub33qkXf16dlJRpt7iEJy31atGhhNsGlPbKao3q5cuVo0aIFS5YsITIyktjYWLZu3SoHh0fQarX069fvgX8rrba2omy5u3ji7pKrdhgP5O4CgwYMpntON7VDsQvzDscwd9d4FEWhYcVWHL22m3m73yQsoBkjGs9UOzybZisd7K15fxcP9qjzrEOTfEFYkNUkK3d5e3vTqFEjtmzZwoULF6hVS4b2FEJNtnIhaK3yfruD4VIm/6o4lcVO75j1UalfviX/avQu5VxlHgchhG3QaDQ02tzDbpqB6XQ6FixYYBrmtzji4uK4ffs2CxcuLMXIxF1Wl6wApKSkABR6ohpHZTQauXo1/zZspUqVLDaEnHAMeX9kc/X6NQAqBVeU+lVExnQ9GTNOoj90y/Ta0CaDSRs1jEzfP/E2+BPiWRMywJghv7YXh5O/qxwHRZmS+vVgGo0GZy/baPly48YNEhMT2bZtG9evXycwMJB69erRv3//UutuMGHChBLPEl8SQ4cO5dSpU/zxxx/4+vrSqlUrxo4dS3BwsGmZK1eu8NZbb7Fnzx7c3Nx47rnniImJMQ1vbM1USVZyc3P5+eefady4cYG/rV27lqNHj1KtWjWqV69u8dhshZJlICsrk7///e8A7Nu+B08PT5WjEkVldM1DyTKoHcYDXX12C5EZ+W21k71m4qGRUXCKxEmDczktVRc+jWfzYDL3Xefy+D14DUjDy6gAd7jJRbWjtGmB2zrY1HHQmvd3R6fxePCPo9nZ2ab6tX//fjw9rbd+iYIuXbpE79698fHxYdy4ceh0OvLy8tixYwfx8fEkJyeXyvuUK1euVLZTXC1btmTo0KEEBQVx/fp1Zs2axRtvvMEXX3wB5A8U8dprr+Hv78/nn39OWloasbGxKIpiGu3OmqmSrGRnZ9OrVy/q1q1LWFgYwcHB/Pnnnxw7dowTJ07g6enJu+++q0ZoNuOPZ74nS8nBnfyM+Gbkf8mSi0mb84faATzG3folisGoEDK9Jb5dqgPg26U6igIXh/2oblx2xNaOg9a+vzuy8nv/9tC/eXhIH1BbFR8fj0ajYfXq1WaJZp06dXjxxRdNz2/dusWwYcPYsWMHwcHBxMbG0rFjRyD/Qn/SpEns2bOH1NRUKlWqRJ8+fejfv79p/fubgfXt2xedToerqytr1qxBq9Xy0ksvMWLECNM68+bNY+3ataSmpuLn50dkZCQTJ04s1uccMGCA6XFISAj//Oc/GTZsGHq9Hq1Wy44dO/j111/Ztm2b6W5LXFwccXFxjBo1Cm9v72K9r6Wokqx4eHgwYsQI9u7dy+7du0lLS8PFxYWQkBD69+/PgAEDqFy5shqh2RQPjRubvGepHYawU1K/Ss6zebDZc68WwQ9ZUhSX1FNRljw9PTlw4IDaYYhiSEtLY/v27YwaNeqBd8TunUBx/vz5jBs3jpiYGJYvX87YsWP54Ycf8PPzw2g0UrFiRebMmYO/vz+HDh1i8uTJBAUFERUV9dD3X7duHQMHDmTVqlUcPnyYuLg4mjZtSps2bUhOTuaTTz5h9uzZ1KlTh9TUVE6dOmVad/LkyXz11VeP/HwbN2584LVyWloaX331FU2aNDENUnX48GHq1Klj1iwsIiKC3Nxcjh8/TsuWLQtsx5qokqxotVqGDx/O8OHD1Xh7uxC4rYPaIYhS4OvrS3q6dQ5l+scz36sdgs3L3HfddGcFIGPvdfWCsUO2dhy05v1dCHtz4cIFFEWhZs2aj122W7dudOnSBYDRo0ezYsUKjh49ytNPP41WqzWbqDw0NJRDhw6RnJz8yGRFp9OZrnOrV6/OihUr2L17N23atOHq1auUL1+e1q1bo9VqqVy5Mg0bNjSt+8YbbzB48OBHxlyhQgWz5++99x6fffYZWVlZNG7cmMTERNPfUlNTKV++vNnyvr6+aLVaUlNTH/PtqM8iycr48eMZP348UVFRJCQkFGsbu3btYuDAgaUcme16WPtaYVucPF3Q5FpnWQYkt1M7BJv25/ijXJ64F0XJv6OSsfc6Vybtxam+B26vu6J4+uNZqZraYdo0WzsOWvP+LoS9udvhvTAjiOl0OtNjT09PvLy8uHnzpum1lStXsnr1aq5cuUJOTg56vZ6wsLBCbxMgKCiIP/7IbwwaGRnJp59+SqdOnWjbti3t2rWjffv2uLjkX5YHBgYSGBhYuA/6P4MHD6Z79+5cuXKF+fPnExsby6JFi0yf/2Hfgy3MW1OmyUq9evXM7p7UqVOn2NsKDQ0121ZISEiJYrMHubm5TJs2DYCJEyfaxIgOwjbk3r5FriGXGR/k/7gQN2aU1K8icptQlezpv5v1UckOTuGsPhHDwkwA/Oo2RddvAlpvX7XCtG23M8jNNa+n3uWlqZ0oPXKetV3VqlVDo9Fw9uzZxw5LfP+cfhqNBqPRCMA333zD9OnTiY2NpUmTJnh5ebF06VKOHDnyyG3eTTzu3ebdBKpSpUokJyezc+dOdu/eTXx8PEuXLmX58uVotdpiNQMLCAggICCAGjVqUKtWLdq1a8fhw4dp0qQJ5cuXLxBveno6er2+yEmRGso8WalXr16pbCs0NNSsY5KAvLw81q5dC+R3lHrcQdSQk2WJsEQR5GW7WmW57BjZiRyDwroDOQC0ubIZN2fr//XFGrnVqoBbbiC57rcwBmTTKjqBCuEtSDmxl31zY9k3uQfK/06Koujur6d/X7xT5Ygezlr3d/FwOVlZpvPsuNEjcVYKdrZ3dpMO+NbIz8+PiIgIPvvsM/r27Vug38rt27fN+q08zMGDB2nSpAkvv/yy6bULFy6UOD53d3c6duxIx44d6dOnD88++yxnzpwhPDy8WM3A7nU3KcrNzR8W/26zsJSUFNN6O3fuxNXVlfr165f4s5Q1q5xnRRSOi4uLqR3l/Rn8g/z39YiyDknYEWcNdKniYnosiifHPYUc9/y5oyKiF1Gt7XMA+f8rCjumD1UzPJt3fz2V45woTXlGxVS/do/shItTwYNhh38ftHRYopCmTJlC79696dGjB9HR0eh0OgwGAzt37mTlypV8++23j91G1apVWb9+Pdu3b6dKlSps2LCBY8eOUaVKlWLHlZSUhMFgoFGjRnh4eLBhwwbc3d1Nd0qK0gzs6NGjHD16lCeffBIfHx8uXrzI3LlzqVq1Kk2aNAHyO9PXrl2bmJgYYmJiSE9PZ+bMmfTs2dPqRwIDSVZsmqurK6+99trjFxSiGFycNPwjRA4RpalCeAvz5/WtewQWWyD1VJQlqV+2LTQ0lKSkJBITE5k5cyYpKSkEBAQQHh7O1KlTC7WN3r17c+rUKUaNGoVGo6Fz58706dOHH38s/jD0Pj4+LF68mBkzZmA0Gqlbty6JiYn4+/sXeVtubm5s3ryZefPmkZmZSVBQEG3btiUhIcHU4sbZ2ZlFixYRHx9P7969cXd3p0uXLsTGxhb7M1iSRlFzys0ytH//flxdXQu0Q7RGfn5+pKWllfn7SPMD62OtowPJr9NlI+LNv+6sAJz/8T9yZ6WUtftoh9ohPJS17u+iZB7XDMxS5/ji0uv1NGrUSO0whHgo+bnAhimKwq1btwDw9/d/7IgO0q7W+ri4e+Kcnat2GAVEzNmSX7/+d4L19/OziRFDrNnxhTHsn/8mKAoV6rck5fge9i+YgJ/uSeq/PlPt8GzW/fXUmo9z1rq/i4cr6nlWCFH6JFmxYVlZWbRt2xbIv5P0oEmPhCgOVx9/MjMz6RiVfxdA6lfJ1R82i58XTzS7kxIQ3pInXp2Ga7mi3/oX+e6vp0KUJjnPCqE+SVaEEMICXMv503jMAjIu/4Ym4yaKVwBeIY+frEwIIYRwZNJnxQpYe3tWUXak7B2TlLtjknJ3TNZe7tJnRVg7J7UDEEIIIYQQQogHsetmYAaDQe0QCkWv16PX69UOQ6hAyt4xSbk7Jil3x2Tt5W4r10rCcdltsuLq6kpubq5N7IQ5OTmmWUaFY5Gyd0xS7o5Jyt0xSbkLUTJ2m6yEhIRgNBrVDqNQ/P39TUMjCsciZe+YpNwdk5S7Y5JyF6Jk7DZZcXZ2xtnZWe0wCkWr1drEQACi9EnZOyYpd8ck5e6YpNyFKBm7TVbUYDAYOHLkCACNGjWymWRJOBapp+r6/ZzCoSO5+Pkq1KguE8xZitR7YQukngpRkCQrpSg7O5tOnToBcPHiRby8vFSOSIiC7q2nx45fwNNT6qklpN9WeP8DOHwE4E8AGjdSGDsGfH0kaSlrrlo5PgvrJ9cRpScuLo5169YxZswYXn31VdPrW7ZsYdiwYZw+fZqkpCTeffddDhw4UGD9Zs2a8eabbwIwfvz4R77XsmXLaNasGUuWLGHdunVcuXIFd3d3qlevTq9evXjxxRdL98M5GElWSkFWVv5UNTk5UKVKqOmxk1PhprBxc1NM2xCORY2yv7ee9nip8PVUlIyTE3h5wVtTNTRqAEeOwXsfKPQbAEajlEFZ+09S8Y7PpUmO9Y7pbrl7eDz+RwmNRkNoaKjpsSgZNzc3Pv74Y3r16oWvr2+xthEVFUXbtm1Nz0eMGEGdOnWIjo42vebr68u8efNYtWoVkyZNon79+mRkZHDs2DFu375d4s/h6CRZKQV/e/buyccDn4BDAHR9AaCwJ6WbZRCVsA1qlP1f9VRYjtEI48Zo6PBM/gVIh2dAUWBKvFy8WkLXF4p7fC5Ncqx3TPnlvmPb45MPT09PUzMwUXKtW7fm/PnzLFq0iJiYmGJtw93dHXd3d9NzrVaLu7s7QUFBZsv98MMP9OnTh2effdb0WlhYWPECF2ZkUkghhLCQRg3MnzduqE4cQgjhCJycnBg9ejQrVqzg2rVrZfpe5cuXZ8+ePdy8KT9KlDa5s1IKvvu2ZLdq/fz8SUuTYQ0dkdpl/9ddQWEJR47l31G56/BR1UJxOCU9TpcGtfd3oQ4pd3X97W9/o169esydO5d33323zN5n/PjxREdH06ZNG2rXrk2TJk3o2LEj7dq1K7P3dBSSrJSCu+1Qs7OzGTJkCABLliwxu234KJ6eGnJy1D+RCstTo+zvradrvvwYN7fC1VNRMpOmKMyeo6Ao+XdUDh+FhA8VGjeCt+Nl/y9rGk1OsY7PpUmO9Y6pKOVe3OsI8Whjx46lf//+DBo0qMzeo3bt2nz99dccP36cn376if379/P666/TrVs33nnnnTJ7X0cgyUopMhgMfPPNN6bHQlije+vpokVGvLzk4qkoNH/8ilPaBYx+VVECaxd6vWnxED9NMeuj8lQzmDJRg5+flEFZy8iQ47OwfnIdUTaeeuopIiIimD17Ni+88ILpdW9vbzIzMzEYDGbDRBsMBjIzMylXrlyR3sfJyYmGDRvSsGFDBgwYwIYNG4iJiWHo0KGmgRNE0UmyUopcXV1JSEgwPRbCGhWqnmZKm9sCstJw3zIFl8t/DXGZF9KM7E7x4OH32NX9XCHhLfj9ghNp6eXw8/2TGlWN+X/MLKOY1eYZoHYEJnJ8FrZA6mnZGTNmDM8//zzVq1c3vVazZk0MBgM///wzDRr81anwxIkTGAwGatSoUaL3rF07/wetrKysEm3H0UmyUoq0Wi39+/dXOwxzenu9CrIPSq6rxctIC/Tv0+N/z/Sg1xdYxjuxjUVjsgWKxglcy5HVJQFjyJM4XT6I+3dT8Fr2HBrFWOjtNHj8InbjzoiDaodgUph6X9bU2N+thtZT7QhsglVeR9gJnU7Hc889x4oVK0yv1a5dm6effpo333yT8ePHExoaysWLF5k+fTpPP/20KdkojOjoaJo2bUqTJk0oX748ly5dYvbs2VSvXp2aNWuWxUdyGJKs2DnveU+qHYJ4hDzAW+0gRKFoFCNZf5uKoW4kAIa6keQoCu4bR6scmfWS4485R97f74w+qXYIQvDGG2/w7bffmr2WkJDAvHnzmDp1KteuXaNixYo888wzjBgxokjbjoiI4Ouvv2bRokX8+eefBAUF0bJlS4YPH46Li1xul4RGUZQyGw4oKSnJbNbPqKgo0+3Notq1axcDBw40PW/evDnLly9/6PK3bll+5A2j0cjp06eB/AzeyalwI0P7+/uXWbzes+uVyXaF7TIqCidT89tC1yvvjJNMPFZoGa/9iOL119j6mowbeC16WsWIRGFJvVeXIycrRTnHF/c6oqT8/f0t8j5CFIdFUr2OHTtSr1496tSp89Blbt++TefOnUlJSSEiIoKlS5ea/T00NJThw4cDMH/+/DKNt7iysrJo0ya/+czFixfx8vJSOSLraoYhCvLz8yMtLc2i75mRkUmTmnUBuPjbGby8CjbPkF/EH8zp8kHTnRUA50sHHrG0sKbjT2HqfVlTY38XtsUaryOEUJtFkpVOnTqZjb7wINOmTePOnTsP/XtoaKjplpy1JisAgYGBaodgTtoJWzWNqxdocy37plrlr3qq9XhgHbkzdKdlY7IB7l+9gdvWt8lVFAxVmuF86QCu308jr8pTZHeZU6Rt+fn5kpaWXjaBWhNrOv4Uot6XNVX2d2FzrO464gEURSEv27L9r1zcPdHIHVGHZBWN6L7//ns2bNjAxIkTmTZtmtrhFJuXlxe//PKL2mEI8UiFqqdWNIqTtcjuOhf3b8aa9VHJq9aa7Kj3wePxTSjO3zrN5T/PEVKuOv5etSDX+bHriNIjx2dhC2yhniqKwtpXO3Dt2B6Lvm+lhq14YdFWSVgckOrJSlpaGpMnT6ZLly60b9/eppMVIWxJWlaq2iHYnqiZuNz8HZf0y+T5hpAXUAMwwCO+y9s5t5izcxxHr/91Ym8a0pbhLd7Fx03aiVuCn0d5tUMQwq5IwiAsSfVk5e2338ZgMDBx4kQyMjLUDqdUZekL93nc9a6FXlbYFzXLvvvK+qq8r6Nx0jjhpfVhUvvFNAhuybHre5izM4Yh69phLMKQx6L4vup7Vu0QADnWO6pHlbuH1vb6pGg0Gl5YtFWagQmLUTVZ+e677/j6669JSEjA39/f5pOV7OxsoqOjAZg7dy7PfV5L5YiEKMioVzi/Kn9UpGo9nXHSysG/LBkVIyPbzKJdja4AtKvRFUVRmLbtNZUjcxzPLa8l9V5YpS2Drpk9v/86wt3dXY2wHkuj0aD1sL1E60F0Oh0LFiygU6dOxd5GXFwct2/fZuHChaUYmbhLtWTl5s2bTJkyhU6dOhEVFaVWGKXKYDCwZs0agGIP0SxEWVOMcOtQ/i/6VbtLvwlLaBDc0ux5w4qtVIrEcUm9F7ZAriNK340bN0hMTGTbtm1cv36dwMBA6tWrR//+/WnVqnSOxRMmTKAMZwIptNzcXHr06MGpU6dYv3499erZx/QVqiUr8fHx5OXlMXXqVLVCKHWurq688847pseFbXpQlvOsCOumRtnr9Xo+MXzKkgPTcFK9IahjOHZ9j+nOCsDRa7tVjMbxfNX3rKneAwzo3x+tVmvxOORY75iKUu73X0eIkrl06RK9e/fGx8eHcePGodPpyMvLY8eOHcTHx5OcnFwq71OuXLlS2U5JzZo1iwoVKnDq1Cm1QylVqlyqbNmyheTkZGbMmEFQUNDjV7ARWq2W119//a/nFO5k6KH1IluGs3RIapS9hxaih79Bv6yXLfq+juqt74cwd9d4FEWhYcVWHL22m/l73qRhxVZMbv+x2uE5BA+tl6neqx2HHOsdT1HK/f7rCFEy8fHxaDQaVq9ejafnX8OV16lThxdffNH0/NatWwwbNowdO3YQHBxMbGwsHTt2BPLvdk2aNIk9e/aQmppKpUqV6NOnD/379zetf38zsL59+6LT6XB1dWXNmjVotVpeeukl0xQcAPPmzWPt2rWkpqbi5+dHZGQkEydOLPZn/e9//8vOnTuZN28eP/74Y7G3Y41USVZOnsyfyTYuLo64uLgCf9+xYwc6nY6wsDA2bNhg6fCEsFt5f2SbHnvjrWIkjiHvVg79P3uFxbXmMi3nrz4qzco/zbjGc/DOlDIoay6B1tnmXwhRttLS0ti+fTujRo0yS1Tu8vHxMT2eP38+48aNIyYmhuXLlzN27Fh++OEH/Pz8MBqNVKxYkTlz5uDv78+hQ4eYPHkyQUFBj+zGsG7dOgYOHMiqVas4fPgwcXFxNG3alDZt2pCcnMwnn3zC7NmzqVOnDqmpqWZ3QyZPnsxXX331yM+3ceNGKleuDEBqaiqTJk1iwYIFVtvPqSRUSVaeeOIJunfvXuD1zMxMvvnmGypWrEhERASVKlVSIbqiM2bq8/83Grl0+RIAVUKq4OTkVKj1Da560zaEY7F02Z9ssgqjYuS6kt8kIVjjj5OmcPVUFIOTBm05Le/2WcaNerc5d/gwmrk3qXA+kCvGLVxROz4HEH6qN1D843NpkmO9Y7q33J08H93iwmg0cunS/+ppFXXqqb24cOECiqJQs2bNxy7brVs3unTpAsDo0aNZsWIFR48e5emnn0ar1ZoGPYD8ScoPHTpEcnLyI5MVnU7H8OHDAahevTorVqxg9+7dtGnThqtXr1K+fHlat26NVqulcuXKNGzY0LTuG2+8weDBgx8Zc4UKFYD8eW/i4uJ46aWXaNCggan+2BNVkpWOHTuabq/d69KlS3zzzTfUrl3b1GbTFpwIWwlAlpJDZEYsAMleM/HQuKkZlhAPlIOelzLfBv5XT5F6WmaMCiHTW+LbpTq+QO1aDUlzPcfFYfZ1i96ayfFZWJMGF/o98u9ZWVk0btwYgIsXL+LlZR8jbqnhbof3wgx3rNPpTI89PT3x8vLi5s2bptdWrlzJ6tWruXLlCjk5Oej1esLCwgq9TYCgoCD++OMPACIjI/n000/p1KkTbdu2pV27drRv3x4Xl/zL8sDAQAIDAwv1OZcvX86dO3d47TX7HWFSuteWMnekQ5ywflJPLcezebDZc68WwQ9ZUpQ1qffCFjyoyZIoumrVqqHRaDh79uxjhyW+f8ANjUaD0Zg/euA333zD9OnTiY2NpUmTJnh5ebF06VKOHDnyyG3eTTzu3ebdBKpSpUokJyezc+dOdu/eTXx8PEuXLmX58uVotdoiNQPbs2cPR44coUGDBmZ/f/HFF3nuueeYOXPmI7djCyRZKQV3mxkAXGJAkdf38/MnLU1GiHFEli77E2Er8dC4scl7lsXe09Fl7ruOb5fqpucZe6+rF4wDKunxuTTJsd4xFaXcvby87LIZjxr8/PyIiIjgs88+o2/fvgWSwNu3b5v1W3mYgwcP0qRJE15++a9BaS5cuFDi+Nzd3U0tjfr06cOzzz7LmTNnCA8PL1IzsIkTJzJy5EjT6ykpKQwePJiEhAQaNWpU4jitgVUlK1WqVOH06dNqh1Fkj2uD+jjOXlqcci0/jKZQn6XLvt6hnhZ7LwEXhv6Xy5P2oij5d1Qy9l7nyuS9+ESEEDKvjdrhOYSSHp9LkxzrHZOUu3qmTJlC79696dGjB9HR0eh0OgwGAzt37mTlypV8++23j91G1apVWb9+Pdu3b6dKlSps2LCBY8eOUaVKlWLHlZSUhMFgoFGjRnh4eLBhwwbc3d1NHeaL0gzs7jp33U3KqlatSsWKFYsdozWxSLIyfvx4xo8fT1RUVLEnOdq1axcDBw4s5ciEcCwyMpJlVV3Ujosjtpv1UXF/yhfvf2nJuHMB32p1VYxOCCHsW2hoKElJSSQmJjJz5kxSUlIICAggPDy80PP89e7dm1OnTjFq1Cg0Gg2dO3emT58+JRoe2MfHh8WLFzNjxgyMRiN169YlMTERf3//Ym/TnmmUMpxy8+TJk2zZssX0vE6dOkRGRhZrWxcvXmT9+vWm5yEhIbzwwgsPXV6NibdycnKIiYkB8ifmcXMrXAdOmSjMcalR9jk5OYwZmT/fxDtTJxe6noriyzn7J5mnUzi5bQFXL35ner1C/ZY0HzELNx85QZW1nJwcJkx9CzCv9+5+hfv1sjTIsd4xFaXci3sdUVJykSysWZkmK2pS44SQkZFBaGgoAL//egavQnaS8/PzIy0trQwjE9ZKjbLPyMykRu38X/Tfb+aGm/PjR0oRJadxckLr6UPz6JlUCG9Byom97Jsbiz7zNsr/OnKKspNjUBh7IAcwr/e91v1qsRjkWO+YilLu9x6ff//1DL4B5cswsr9IsiKsmSQrpSg3N5d58+Zx5NOZdKzkjIuTXAQK65NnVNh61QAg9dTCIt5cRLW2z5men//xP+yYPlTFiByH1HthC+6vp/03XbXI+0qyIqyZJCtl4LNnKz9+ISGEw3nhs8N4BFQwPc+6mULSy43VC0gIYdVe/tYyU8dKsiKsmVWNBmYvitqsQJoGOC61yv7LbrUt/p4CUk7sNbuzknJ8j4rRCJBmYKLsSbkLUTKSrJQiRVFMs5MGBgYWatZUAK2HFy7ZuWUZmrBSapS9oig8M38bAAEBAYWup6Jktr/zT/YveBMUhQr1W5JyfA/7F06gQoNWtH1zsdrh2T1FUUwzUt9b713cLTcBnxzrHVNRyv3+6wghhDQDK1X3drC/ePEiXl5ehVpPRohxXGqUfXHrqSiZ7PQ/2DlzGNcO/TXcZcUmT9MmdgHuvnJRUtasod7Lsd4xFaXc1aqn0gxMWDO5syKEEBbg7htIx3e/IP38GZTbN9D4BMk8K0IIIcRjSLJSiry8vEzNDISwVlJP1eVbrS7+/i3kF3YLk3ovbIHUUyEKclI7ACGEEEIIIYR4EElWhBBCCCGEEFbJbjvYCyGEEEIIIWyb3FkRQgghhBBCWCVJVoQQQgghhBBWSZIVIYQQQgghhFWSZEUIIYQQQghhlSRZEUIIIYQQQlglSVaEEEIIIYQQVkmSFSt3+PBh6tWrh06nY/HixWqHI8pAZmYmGzZs4I033uAf//gHDRs2pFmzZrzyyit8/fXXaocnSsnRo0f55z/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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_forest_compare_analytical(results_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Based on the visual check, the traces have reasonably converged on the target distribution, with the exception of `DEMetropolis` at 10 chains, supporting the suggestion that the number of chains should be at least 2 times the number of dimensions for a 10 dimensional problem. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Experiment #2. 50-Dimensional Target Distribution\n", "Let's repeat in 50-dimensions but with even more chains for the `DEMetropolis` algorithm. " ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC Runs for 50-Dimensional Experiment
 samplertunedrawschainscores
0DEMetropolisZ500005000041
1DEMetropolis200020001001
2DEMetropolis4004005001
3DEMetropolis20020010001
4nuts2000200041
\n" ], "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# dimensions\n", "D = 50\n", "# total samples are constant for Metropolis algorithms\n", "total_samples = 200000\n", "samplers = [pm.DEMetropolisZ] + [pm.DEMetropolis] * 3 + [pm.NUTS]\n", "coreses = [1] * 5\n", "chainses = [4, 2 * D, 10 * D, 20 * D, 4]\n", "# calculate the number of tunes and draws for each run\n", "tunes = drawses = [int(total_samples / chains) for chains in chainses]\n", "# manually adjust NUTs, which needs fewer samples\n", "tunes[-1] = drawses[-1] = 2000\n", "# put it in a dataframe for display and QA/QC\n", "pd.DataFrame(\n", " dict(\n", " sampler=[s.name for s in samplers],\n", " tune=tunes,\n", " draws=drawses,\n", " chains=chainses,\n", " cores=coreses,\n", " )\n", ").style.set_caption(\"MCMC Runs for 50-Dimensional Experiment\")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "tags": [ "hide-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 50_000 tune and 50_000 draw iterations (200_000 + 200_000 draws total) took 148 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 2_000 tune and 2_000 draw iterations (200_000 + 200_000 draws total) took 185 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Only 400 samples in chain.\n", "Population sampling (500 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 500 chains for 400 tune and 400 draw iterations (200_000 + 200_000 draws total) took 214 seconds.\n", "c:\\Users\\greg\\.conda\\envs\\pymc-dev\\Lib\\site-packages\\arviz\\data\\base.py:221: UserWarning: More chains (500) than draws (400). Passed array should have shape (chains, draws, *shape)\n", " warnings.warn(\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Only 200 samples in chain.\n", "Population sampling (1000 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 1000 chains for 200 tune and 200 draw iterations (200_000 + 200_000 draws total) took 245 seconds.\n", "c:\\Users\\greg\\.conda\\envs\\pymc-dev\\Lib\\site-packages\\arviz\\data\\base.py:221: UserWarning: More chains (1000) than draws (200). Passed array should have shape (chains, draws, *shape)\n", " warnings.warn(\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 2_000 tune and 2_000 draw iterations (8_000 + 8_000 draws total) took 94 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n" ] } ], "source": [ "results = []\n", "run = 0\n", "for sampler, tune, draws, cores, chains in zip(samplers, tunes, drawses, coreses, chainses):\n", " if sampler.name == \"nuts\":\n", " results.append(\n", " sample_model_calc_metrics(\n", " sampler,\n", " D,\n", " tune,\n", " draws,\n", " cores=cores,\n", " chains=chains,\n", " run=run,\n", " step_kwargs={},\n", " sample_kwargs=dict(nuts=dict(target_accept=0.95)),\n", " )\n", " )\n", " else:\n", " results.append(\n", " sample_model_calc_metrics(sampler, D, tune, draws, cores=cores, chains=chains, run=run)\n", " )\n", " run += 1" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Results of MCMC Sampling of 50-Dimensional Target Distribution
 SamplerDChainsCorestunedrawsESSTime_secESSperSecrhatESS_pct
0DEMetropolisZ504150000500001309.830000163.8700007.9900001.0000000.650000
1DEMetropolis50100120002000792.730000236.8300003.3500001.0900000.400000
2DEMetropolis5050014004001083.880000415.2600002.6100001.4100000.540000
3DEMetropolis50100012002001616.890000633.7600002.5500001.7100000.810000
4NUTS50412000200010570.020000105.300000100.3800001.000000132.130000
\n" ], "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results_df = concat_results(results)\n", "results_df = results_df.reset_index(drop=True)\n", "cols = results_df.columns\n", "results_df[cols[~cols.isin([\"Trace\", \"Run\"])]].round(2).style.set_caption(\n", " \"Results of MCMC Sampling of 50-Dimensional Target Distribution\"\n", ")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "image/png": 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TR3j8+LHKcX369BHkcrnQsmVLYd26dcLTp08FQRCE7Oxs4d133xXkcrkwdepUoU2bNsLevXvF4+7cuSP069dPkMvlwqZNm1TOeebMGTEvLi4uwt9//y3uS0lJEdzd3QW5XC74+fkVK8fu3buF5ORklW0FBQXC9u3bhRYtWgj9+vUT86i0cuVKQS6XC05OTsLo0aOFu3fvivuePHkiCIIg3Lp1S7wHz1u8eLEgl8uFefPmCbm5uSr7rl27JmzdulVl2+XLl4UWLVoIcrlc+PHHH8W85OXlCV988YUgl8uF9u3bC6mpqSrHeXp6ivd58eLFYr6KioqEpUuXCnK5XOjevbtQWFhY7J5oEhERIcjlcqFdu3bCqVOnxO1paWnCmDFjBLlcLnh4eBQ7bt68eYJcLhd27txZ4mspKT8v6o69efOmeG/OnTun9rhbt26pPa/y/pw5c0bt9tLct99++02Qy+WCu7u7ymdBEAThwYMHQnh4uKBQKEpc5pfdL4VCIfTu3VuQy+XChx9+KOTk5Ij7du3aJTg5OQlyuVw4fvy4ynEl+cy+ivLeqPuvV69ewsWLF4sds337dkEulwsDBgzQeN6FCxcKcrlcmDt3bonyIQj/d4/mzZv3yrTKz+3AgQNVtivvycqVK1W279y5U/wMDB06VKV+2LdvnyCXy4XWrVsLkyZNEsaPHy/cv39f3L969WpBLpcL3bp1K/bd2rJliyCXy4W+ffuqfO4KCwuFVatWCXK5XOjZs6fK30NZjyjrtuf/rmlpacLbb78tyOVyYenSpSrXmjZtmiCXy4Xvv/9eyMvLU9l38eJFlbr1+TK/eD/v3bsnuLi4CHK5XFiyZIl4rqdPn4plbdmypRAXF6dynPLv07JlS8HPz0/Izs4W923atEmQy+VCq1atVLYLgiDExcUJf/zxR7E8JycnC+PGjRPkcrmwa9cu4UWv+r6XhKa65vbt28KBAweK1ddpaWmCn5+fIJfLhaCgII3nc3JyEoKCgoSCggJBEJ7VJXl5ecLTp0+FoUOHCnK5XPD29haysrLEY3/77TfB2dlZaNmypdpyfffdd4JcLheGDx8uXL58Wdz++PFj8Xdh5MiRKsdo+k0qKeXvrFwuf2XanJwcwdHRUZDL5cI///zzyjyU9ndRmRdPT0+NeVB+Bp2cnITp06cLmZmZ4j7ld0zTeZ7/3rVs2VLYt2+fuC8jI0Pw8vIS5HK5MGrUKKGoqOiV5Xuepnv4qs+wpnMXFRUJI0eOFMuRnp4u7jtx4oTQtm1btc9Nz9dzgwcPFm7cuCHu++eff8Tv/YkTJzSWhcjQsJs9VSrK7uplXWpH2SI/duxYuLu7i9vNzc2xdOlSyGQypKSkiK24L+rZsycmTpwotrDUrFkTfn5+AJ71GvDw8MDbb78tpq9fvz68vb0BPOumqk5hYSH8/PzQuXNncVuDBg3wzTffAAAOHz5crEvq8OHDxZZkJWNjY3h4eGDw4MG4deuWxq6kRkZGWLFiBerVqydue9WMx8phBF5eXqhRo4bKviZNmmD06NEq23766ScUFhaiX79+8Pb2Fu+XqakpPv/8czRr1gw5OTnFJiR6/pyffvqpmC+JRIIPP/wQ1tbWSEtLw5UrV16aXyVBEBAWFgYAmDlzJrp16ybus7a2xvLly2FiYoILFy7g77//LtE5y0rZddvHxweFhYVwcXGBq6truV6jNPctKSkJAPDOO++ofBYAwMrKCu+//3659RzYt28f7ty5gzp16uCbb75RmVV+xIgR4ufnxe6tSmX5zCo5Ojpi4cKFOHDgAM6fP4+oqCgEBwejcePGuHv3Lry9vYstI5idnQ0AL52cUDlz88OHD0uUj9JSljUjI6NUxxUWFuKbb75RqR+GDBmCdu3a4cmTJ4iOjsbSpUtVevtMmTIFdevWRXp6uspnJD8/H8HBwTAyMkJQUJBKbx8jIyPMmDEDAwcOxL1798SVRV7Mi6+vL3r16iVus7a2xkcffQQAxbrNK+uZKVOmqLTyAUCrVq1U6taX2bx5M3Jzc+Hk5IRPP/1UPFe1atUwffp09OrVCwUFBRpb72rVqoXAwECV2bnHjh2Lli1bIi8vr9jQiubNm6N3797F8mxnZ4evv/4aAPDrr7+WKO/lxdbWFm+99Vax+tra2hrffvstTExMXpqnnj17wtfXF8bGzzp4SiQSmJqa4vTp00hISECtWrXw/fffq3xHBg4ciKlTp6odnpORkYHw8HCYm5tj9erVcHJyEve98cYb+Oyzz9CqVStcunQJ0dHRr1v8MjE3NxdblB88ePDK9KX9XSwNKysrLFu2TGW1jZLWeYWFhRgzZoxKjx6ZTIbvvvsOZmZmuHjxYoXPC/D333+LPS6+//571KlTR9zXs2dP+Pj4AADCwsLUdrcvLCxEYGCg2IsDANq2bQsPDw8AxesWIkPGYJ4qlUePHgEoW/fkR48eiQGuurFm1atXF7tdapqYTN342ecfStTtV3bT1TQO2sTERO1xzZs3R/v27SEIAk6dOlVs//Xr17Fy5Ur4+vpi/PjxeO+99/Dee+/h3LlzAJ51hVSna9eupV4mRrkEzqFDh9T+sL5Ief/U3WeJRCJu13Sf33nnnWJdUk1MTMQxe5rG277o+vXruHv3LszMzNR2qa1bt644XEMbk9E9P368ffv2mDhxIm7cuIHBgwdjzZo15X690tw3ZbB44sQJsdu/tig/vx4eHmofSJVjSf/55x+14x3L8plVWrhwIcaPH48mTZqgevXqsLS0RP/+/bF161a8+eabyMrKQkhIiMoxysn8XjbEQBm4PXnypEz5ehWpVArg/+q8kmrRooXaoQHNmzcH8OxB+cV7aWRkpPYzcv78eaSnp2s8JwBxLKyy3nmRurpNOYzpxe+xsp5R92KgNJTfZXXLjAH/93nT9J0fMmSIeP+fp+zmra7+yc/Px6+//oqFCxdi8uTJGDt2LN577z3MmzcPgOb6WJuKiorEIQXe3t5iniZOnAiJRILExESN331Ny2Yq55IYMGCA2q7UmmbUP3HiBPLz89G9e/diLw+BZy9alMOuoqKiSlA67VA+W5Tke1fa38XSGDBggNrPYEmp++zXrl1b/L1T90yhS8rrDxo0SO0wgzFjxsDU1BQpKSniSinPc3JyUjscUrlN0/MWkSHimHmqVJRvv8sSfCQnJ6OoqAimpqbFWrWVmjZtCgAqE9o9r2HDhsW2PT/mU91+5XrQmh4O6tWrp3b9a+DZ2/2YmJhi+Vm7di2WL1+OoqIitccB/9e6+KKyjJUbN24cfvnlF6xatQp79uxB9+7d4erqik6dOhULDB4+fCi2JjZp0kTt+cpynwGIrYklneBGef769etrfDB6VV5eh3L8uCAIuH//Pm7dugVjY2O0atVKK0vSlea+ubm5wdbWFqdOnUKPHj3Qo0cPcVLHZs2alWu+lPdWea9f5ODgABMTExQUFCA5OVkMPJVed3ynOpaWlpg6dSo+//xzHD16FIIgiGMzlS8cXjYBYH5+PgDtzd6v/Ftpqhs00VS3KeupV+1//jOSkJAA4NkkX++9957a43JycgBA7SSfMplMbcCn6Xv8/vvv46+//sLChQuxbt06dO/eHe3bt0enTp3EerQkXvV5U36+79+/j9zc3GL3uLT1z507dzBp0iTcvHlTY5401cfa8vDhQ0ydOhX//PPPK9Opezmuqe5W3ltNE9DZ2trC3Nwcubm5KtuVn6ULFy5o/CwpW8PVfZZ0pTTfu9L8LpaWpvtfEiYmJrC3t3/pebXxe1car/qOmpubo379+khKSkJiYmKx+/Gqeqy0L0GJ9BmDeapUlD+QZXnrqqzcraysNE4ko+zqpemHQN2D+/PnUvdQ9KpJa16c3E7dvufzc+7cOXz//fcwMjLC7Nmz0bdvXzRo0ADVq1eHRCLBDz/8gDVr1micQbksb/udnJzw888/IygoCGfOnMG2bduwbds2SCQSdOvWDQsWLBB/bJ9/0NVUtlfdZ009L5StziVtBVGe/2X3+FV5eR0vrv0cExMDHx8ffPPNN6hdu3apJvIridLcN6lUis2bN2PFihU4dOgQDhw4IM5637RpU8yZMwd9+vQpl3wpPxOa/g4SiQRWVlZITU1V+3d4nRaql2nbti0AICsrC1lZWWLAqHzR8rIATNm9/vmu2OVJOet0aZfW1PQZUNZDr9r//GdEGahnZGS8sru/sjfD8zT93TRNBNe7d2+EhoZi9erVuHDhAm7cuIGNGzfC2NgYbm5uWLBgQYmCpFd93p7f/ujRo2KBW2nrn/nz5+PmzZto06YN/Pz84OTkBEtLS5iYmKCwsBAtW7bU+Yz2AQEB+Oeff9CoUSN8/PHHaNOmDWQymdijpGfPnkhNTdX4wkrTPVC+SH+xW/nzatSoUSyYV36W7t69q3HVGCV1nyVdyMnJEfP9st8MpdL8LpbW6wxxqlWrlsbvmLpnioqg/I6+rH6rXbs2kpKSSvWboMtJJol0hcE8VSrt2rXDpk2b8M8//6CwsFAcz1cSyoePjIwMlVa4592/f18lrS687CFZue/5/CjHOU6ePBlTp04tdsy9e/fKOYfPtG3bFj/99BMePXqE2NhYnD17Fvv27cOpU6cwceJE7Nu3DzVr1lT5kX3w4AFsbGyKnUtX91l5/peNf9Tl37x9+/ZYsmQJfHx88PXXX6Nfv35qW4A0vawo7yV36tWrJ66x/N9//+Hs2bM4dOgQLl26BB8fH2zZsgVt2rR57esoPxOa/g6CIKj9rGvb8/XH8+u5K1u17t69q7GeUXa11tQC9rpiYmIAAK1bt9bK+UtC+Xd7++238d133+nkmr169UKvXr2QlZWF6OhonDlzBvv27cNvv/2G5ORkbN++/ZUrLEilUuTk5ODBgwdqW9mf/xy+7uctNTUVZ8+eRfXq1REaGqoyxhnAKwNXbSgsLBRnjF+1alWxni2FhYVivVdayiDzZXXRy4Kv6dOnY9asWWW6trbFxsZCEASYmJgU6x2kSUl/F3UpKysLRUVFagNbdfWsuhd5z9PGUm/Kz8PLnn+U31Nd/iYQ6SO+oqJKpVevXpBKpXjw4AEOHTpUqmMbNmyIatWqIT8/X+OY62vXrgGAuA64Lty9e1fjW3LlMj/P50c5WVe7du3UHqPtsZk1atRAjx49MGfOHBw8eBANGzZEamqqOOFMzZo1xbftmpYp0tV9Vp7/ZfdY139zNzc3tG3bFllZWVi/fr3KPuUDTmZmptpjSzpXQGkZGxujTZs2mDp1Knbu3IkhQ4bg6dOn2LlzZ7mcX3lvlff6RYmJiSgoKICRkZHGLs7aoMyPmZmZShDWokULmJiYIC8vD5cvXy52XEFBAf79918AKJeXHS9KS0vDsWPHAEBl8jhdU3aBvXr1qs6vXatWLbi5uWHhwoXYt28fLCwscPnyZVy6dOmVx77q86YsT506dUo9jOFFyh4UjRs3LhbIAyjxZJ3lKSMjAwqFArVq1VI7ROXq1asqL69KQ3lvNZXrzp07xVrlgbJ/lkqzHNvrUk7I2qVLlxJPNqf0qt9FQHdlUQ5XUkfdM4XyBY2mwFrTuV7Hq76jubm54oswXT6PEekjBvNUqdSsWVOcPO3rr79+ZXf7mJgYxMbGAnj2Y6sMgCMiIoqlffLkCSIjIwGg3NeNfpmCggLs2LGj2PaEhARER0eLXfaUlA8Z6lo5T506pdOJlqpXry6ul5uWliZuV94/dfdZEAT8/PPPKum0pUmTJmjQoAHy8vLEv+3zUlNTxZdCuvybT5kyBcCz+/P8SwblKg3KQPF5hw4d0tm4W2WA+vzf9HUo721kZKTaLrTKz4mLi4vWutS/qKioCBs2bAAAdOzYUaX13dzcHF26dAEAtd/N3377Dbm5uahVqxY6duxYrvl68uQJPvnkE+Tn58PBwUGcsKoiuLq6QiaTIT4+vkJnv65Tp4743SjJZ1L5edu0aZPa/crPW3l855VDrx48eKC2ZVO5moYuKfOUm5urdoLG18mT8rfo8OHDaoP2Xbt2qT2uV69eMDExwcmTJ0s1XltZFm1NNKm0fft2/PHHHwCeDY96HZp+F3VVFuDZig4vysjIEHtsPP9MoZzb4smTJ2pftqj77VRSlqm0QyN69OgB4Fldmp6eXmz/tm3bkJ+fD1tbW63MmUJkSBjMU6Xj6+uLdu3a4f79+xgzZgx++eWXYj8kN2/exJdffokJEyaovG1WBlFbtmxRWZYnNzcXn3zyCTIyMmBra6uypIu2GRsbIygoSGUG33v37omzIA8YMECltbJ9+/YAni3j9XxL7cWLF7FgwYJStyiUxKJFi3DgwIFiEw+eO3dOXNLt+dmuJ02aBGNjYxw9ehTr1q0TJ+rLz8/H//73PyQkJMDCwkLjREjlRSKRYPLkyQCAoKAgleXn7t+/j48//hgFBQVo27atytKA2tavXz80adIE2dnZKsvz9ezZE8Czh+3nH3gvXryIJUuWvLJ7cWmEh4cjPDy8WHfbO3fuiAGsphnMS2vo0KFo0KAB7t+/j/nz56u8wNizZw+2bdsG4P++n+Xll19+QWhoaLEyKv/2MTEx4nJlL5o+fTokEgkiIyNVlqqMj49HYGAgAMDb27vYcmRl9eTJE/z+++/w8PDA33//DalUihUrVsDIyKhczl8WZmZmmDlzJgDgww8/xO+//14sYE1ISMDSpUvFYQGvY9asWTh+/Lg4uaDSb7/9hoSEBEgkkhJ9Jt977z2Ym5sjLi4OX3/9tXi+oqIi/Pjjjzh+/DhMTEwwceLE185z06ZNYWlpiXv37mH16tXi/cnLy8OSJUvU9uzQtpo1a6JZs2YoLCxUKf/Tp08RGhqKAwcOlLku6dq1KxwdHZGZmYk5c+aoLM145MgRhIaGqj133bp18f7776OgoACTJ08u9nJIEARcvHgRixYtUvlds7KyQo0aNfDgwQONPb3KShAExMfHw9/fH5999hkAYMaMGSVeMrS0v4vKF1LXrl0r9ZKTpWFsbIzNmzerrAqRlZWFuXPnIi8vD87Oziq/dxKJRHyxFRgYqFI/7969+6U9tJQT0ZV2BYLOnTujVatWyM/Px8cff6zSOHHq1CkEBwcDePaboMveGUT6iGPmqdIxNTXFTz/9BH9/fxw6dAjz5s3DokWL0LBhQ5iZmSEtLU2cDbdevXoqgXCfPn0wdepUhIaGYs6cOVi2bBlq166NGzduQKFQwNLSEsuXL9faDNXqtGvXDjVq1MD48ePh4OAAqVSKhIQEFBYWws7OTnzIUBo9ejS2bNmC5ORkvPXWW2jUqBEKCgpw8+ZNNG3aFIMHDy7Wfft1nT9/Hlu3boWxsTHs7e3Fhytll393d3eVhwPl+s6LFy/GN998g59++kmcmfbhw4cwNTXFd999p3ZJmvI2btw4/PPPP9i3bx+8vLxgb28Pc3NzJCQkoKCgAA0aNNDZeGAliUSCSZMm4dNPP0V4eDjGjx8PMzMzvPPOO9i8eTOuXr2KIUOGoHHjxsjPz0diYiKGDBmC9PT0clu2KSUlBRs3bkRAQABsbW1Ru3Zt5ObmIikpCU+fPoVcLi+XYAd41lK1fPlyTJ48GQcOHMDx48fRuHFjPHjwQOxKOWPGjHLvUp6VlYVly5Zh2bJlYhmfPHmC69ev4+nTpzAxMcGiRYvUPry3b98eH374IZYvX47Zs2dj+fLlkEqluHr1KoqKitC7d29MmjSpTPk6efKk+CKrqKgI2dnZuH37tjgZmZOTE7799luxda8ijR07Fnfv3kVoaCh8fX1Rq1Yt2NnZoaioCCkpKcjKygIAlTXoy+rPP//EgQMHYGpqCgcHB5iZmeHevXtiy90HH3ygcRbr59WtWxfffvstPvzwQ2zYsAG//PILGjZsiDt37uDBgweoVq0aPvvssxKPi34ZExMTfPjhh1i8eDFWrFiBzZs3o27dukhMTMSjR4/w1VdfYeHCha99ndL6+OOP8cEHH2Dbtm04dOgQ3nzzTaSkpCAzMxMffPAB9uzZI9bfpVGtWjV8++23GD9+PP744w/07NkTTZo0QWZmJlJSUjB+/HgcO3YMKSkpxV5EzZo1C2lpadi7dy8mTJgAa2tr1K9fXxz6pgwilUsHAs/qykGDBmHnzp0YMWIEmjVrJvbeUdfz62Wef3n86NEj3Lt3T+ztVKNGDcyZMwdjx44t8flK+7toZWWFzp0748yZM3Bzc0PTpk1hZmaGOnXq4IcffihVWV6mbt266NmzJz766CMsXboUMpkM165dw5MnT1CrVi18++23xQJkPz8/nDhxAqdOnUL37t3RqFEjpKWlIT09HV988QW++OILtdd66623cPz4cXzxxRfYvHmzONRkwYIFKsv2vkgikWDZsmWYMGECoqKi0Lt3bzRr1kz8DQKAYcOGYcyYMeVyT4gMGYN5qpRq1KiBlStXIjo6Grt370Z0dLT4MCyTydC7d2/0798fQ4cOLRaYz549Gy4uLoiIiMClS5dw//592NjYwN3dHdOnTxfXjtUViUSC4OBgrF27Fnv37sW1a9cgk8ng5uaGmTNnFpvt1dzcHJs3b8ayZctw4sQJ3Lx5E3Xr1sXEiRPh6+tb7oE88Gy99KNHjyImJgZ3795FcnIybGxs0L17d4wbN07trOdjx46Fo6Mj1q1bh9jYWMTHx4t/m2nTpmlckqa8SSQSfPfdd+jRowciIyMRHx+Pu3fvwtbWFv369cOUKVNKtexVeXF3d8eKFSuQlpaGHTt2YNy4cTAzM8OGDRvw/fff448//kBiYiLefPNNzJs3D15eXnj//ffL7fpjxoyBpaUlzpw5g+TkZMTFxcHS0hKtWrXC22+/jVGjRpXrS602bdpgz549WLt2LU6dOoUrV65AKpWie/fumDBhglbGhnfv3h2TJk3ChQsXkJKSgvj4eHFcfqdOnTB+/PiXfg5nzJiB5s2bIzw8HP/99x/u378PuVyOkSNHwtPTs8yt5g8ePBBboszMzGBhYYEWLVrA2dkZ/fv3F7v464vZs2ejT58+2LRpE2JiYhAfH48aNWqgbt266NevHwYOHFgueQ4MDMTJkyfxzz//IC0tDQqFAvXq1UP//v3x/vvvo0OHDiU+V79+/bBr1y6EhobizJkziI+Ph4WFBfr374/JkydrnHOkLMaNGwcLCwusW7cO165dE1s/J0+ejJ49e1ZIMN+3b1/8+OOPCAkJQVxcHG7evIlmzZphwYIFcHd3x549e8p87ubNm2Pnzp1Yvnw5Tp8+jatXr8Le3h6ff/45xo0bJ/ZkeXHiMmNjYyxduhRDhw7F9u3bceHCBcTFxaFmzZpwcHBAu3btMHDgQDRq1EjluE8//RQ1atTA0aNHceXKlZcuGfkyyiF3xsbGMDc3h5WVFbp164ZOnTph6NChpZ4/oSy/i8qXi6dPn8Z///2HwsJC2Nralqk8L7No0SI0btwYkZGRuHr1KqRSKfr3749Zs2apvV6TJk2wadMmfP/994iNjcXNmzfh6OiIr776Cn369NEYzA8fPhwPHz7Ejh07kJSUJC5B+HyPDU3s7e2xe/du/Pjjjzh27BiuXr0KU1NTdOjQAR4eHnB3d2erPBEAiVDSNZyISKfOnj2LCRMmoGPHjqVuYSAiItI3mZmZ6Ny5M2rWrIlz585VdHaIiAwex8wTERERkdYpJ8Arz54PRERVGYN5IiIiIioXV65cwbZt21QmShMEAXv27MGKFSsAgGOdiYjKCcfMExEREVG5yMrKwueff44vv/wSDRo0QK1atXDr1i1xMsTRo0ejb9++FZtJIqJKgsE8EREREZWLpk2bwtvbG6dPn8bdu3dx9+5dmJubo0uXLnj33XcxePDgis4iEVGlwQnwiIiIiIiIiAwMx8wTERERERERGRgG80REREREREQGhsE8ERERERERkYFhME9ERERERERkYBjMExERERERERkYBvNERERERERacObMGQQFBeG///6r6KxQJcSl6YiIiIiIiMpZbm4uBg0ahPT0dMjlcvzyyy8wMjKq6GxRJcKWeSIiIiIionK2atUqZGVlYf78+UhISMDmzZsrOktUyTCYJyIiIiIiKkc3btzAxo0b4ePjg4kTJ2LUqFFYuXIlMjIyKjprVImwmz0REREREVE5mjx5MjIzM7F9+3YYGxsjNzcXQ4cORbdu3fC///2vorNHlQSDeSIiIiIiIiIDw272RERERERERAaGwTwRERERERGRgWEwT0RERERERGRgGMwTUbkbP348HB0dcfbs2YrOChEREZHO7N+/H46OjsX+a9++PcaNG4dff/21orNIlYhxRWeASq9v375ISUl5ZbqAgACMHDlSZdudO3ewYcMGnD59Grdv30ZRURGsrKxQr149tGvXDl27dkWPHj2KnSszMxMbN27E8ePHkZiYiIKCAshkMtjY2KBt27bo2LEj+vfvj2rVKvf7oQMHDmDXrl24fPkyHj58iBo1aqB27dpo2rQpOnXqhP79+8PGxqais0lEGlSG+jMoKAjBwcEq26pVqwZLS0s4OTlh5MiRePvtt0t0rspu165dSElJwYgRI/Dmm29WdHaIqAqIi4sDAFhbW8POzg4AkJeXh8TERERHRyM6Oho3b97EzJkzKzKbVEkwmDdgDg4OsLKy0ri/du3aKv/++++/4ePjg0ePHsHIyAj16tVD7dq1kZ2djfPnz+Off/7Brl27irWmXrlyBZMmTcL9+/cBAPXq1YO1tTUePXqE+Ph4XLp0CT///DNiY2NRo0aN8i+oHigoKMBHH32EI0eOAAAsLCzQuHFjGBkZ4datW7h+/ToOHToEQRDg6elZwbklolepDPWnubk55HI5AKCwsBBJSUn466+/8Ndff+HEiRNYunQpJBJJqc5Z2ezevRtRUVHo2LEjg3ki0on4+HgAwPvvv48pU6aI23NzczF37lwcO3YMoaGh8PT0fOnvEFFJMJg3YNOmTSvWcqRJbm4uZs2ahUePHqF37974/PPPYWtrK+5/+PAhjh49ioMHD6ocV1RUhFmzZuH+/fto06YN/ve//6FZs2bifoVCgZMnT2Lbtm2V+qFx3bp1OHLkCN544w0sWbIEgwcPhpGREQBAEARcunQJe/bsgbm5eQXnlIhKojLUny1atEBERITK9TZu3IiAgAD8+uuv6NOnD4YMGVLq8xIRUdkpg3nly1Ylc3NzLFiwAMeOHUNBQQH+/fdf9OrVqyKySJUIg/kq4sSJE8jMzIS5uTmWL1+O6tWrq+yvWbMmRowYgREjRqhsv3jxIq5fvw4AWLlyJerVq6eyXyqVYtCgQRg0aJB2C1DBdu/eDQCYPn16se6rEokErVq1QqtWrSoia0SkZYZSf1arVg1eXl44e/Ysjh07hn379jGYJyLSoQcPHiA9PR0A4OjoWGz/m2++iWrVqqGoqAgFBQW6zh5VQgzmq4hbt24BeNa19MUH0ZIcJ5PJij2Ivo758+dj9+7dCAgIQLt27bBixQqcPXsWjx49QuPGjeHp6YlRo0ZpPP769esICwvD2bNnkZaWhho1aqBNmzaYOHEiunTpUiy9cpzs0aNHcfv2bYSFheHff/9FVlYWNm7ciE6dOr00v7dv3wYAODk5lam89+7dQ1hYGP7880/cvXsXpqamcHJywrhx4176IH/69Gls2bIF58+fR1ZWFmrVqoVGjRph0KBB8PDwgKmpqUr648ePIyIiApcuXcKjR49gY2ODnj17Ytq0aahfv36x8z9/X+7fv4/g4GBcuHABBQUFaNGiBfz8/NTeTwDIyMjAypUrcfToUWRlZaFBgwZwd3fH1KlTy3SPiPSVvtWfr9KhQwccO3YMSUlJKtsfP36MiIgI/Pbbb0hMTMTTp0/h4OCAt99+GxMmTChWnyjH5vv6+mLcuHEIDg7G8ePHkZqairfffhuBgYFi2tLWVa9Th5ekrjp79iwmTJgg/vv5/w+ozolw/vx5HD58GGfOnMHdu3eRk5OD2rVro2PHjpg6dapKb4rnCYKArVu3YsuWLUhMTIS5uTm6dOmCjz76COfOnYO/vz9GjBihcp+UyvqbQET6TTlevmbNmmrrfeV8KwDQpEkTneaNKqfKPVsZiZTdv5OSkvDw4cNSH5eVlSU+mJanpKQkeHh44OjRo6hfvz7q1KmDuLg4fPrpp1iyZInaYw4cOIBhw4Zh165dyMrKQtOmTWFiYoITJ05g4sSJKt1OX7R//35MnDgRFy9ehJ2dXYkfsJVjWS9evFjqMkZFRWHo0KGIiIjAvXv3YG9vD3Nzc0RFReHDDz/EN998o/a4xYsXY9KkSfj9999RUFAAR0dHmJqaIjo6GosXL0ZaWppK+mXLlmHatGk4deoU3njjDcjlcmRkZGDLli0YNmwY/v33X415PH78ODw9PfHvv//Czs4OxsbGiImJgbe3t9oZ6dPT0/Huu+9iy5YtyMjIEH+QVq5cCT8/PwiCUOr7RKSv9LX+1ETd9y81NRWjRo3CsmXLcOXKFdSpUwe2tra4du0ali5dCi8vLzx58kTt+TIyMvDOO+9g69atMDc3R5MmTVQm6yttXfU6dXhJ6yoLCwu4uLiIfwO5XA4XFxfxv+fnRJg7dy5++uknpKSkoE6dOmjSpAkePXqEvXv3YtSoURpX5fj000/xxRdf4MqVK7C2tka9evXw+++/45133kFycrLGMpT1N4GI9J+mLvZKoaGhAICOHTuiUaNGOssXVWICGZw+ffoIcrlc2LlzZ4mPuXHjhtC8eXNBLpcLI0aMEH777Tfh4cOHrzwuOztbaNu2rSCXy4X+/fsLu3btEh48ePA62RcEQRDmzZsnyOVyoUWLFsL48eNVznnw4EGhZcuWglwuF/744w+V4+Li4gRnZ2ehVatWwrZt24SnT5+K+44ePSq4uLgITk5OQlxcnMpxynvm5OQkBAUFCQUFBYIgCEJRUZGQl5f3yvzOnj1bkMvlQsuWLYXvvvtOuHLlilBUVPTK4+7duyd07NhRcHR0FNasWaNyrZiYGKFHjx6CXC4Xjh07pnJceHi4IJfLhTZt2gi//PKLSjkzMzOFdevWqdyzY8eOifdzz5494vacnBzBx8dHkMvlQp8+fYTHjx+rvS8tW7YU1q5dKxQWFgqCIAj5+flimT08PIqVS3nOESNGCHfu3BG3//XXX0K7du3Ev9+ZM2deeY+IdKky1J8rV64U5HK54OnpqXb/9OnTBblcLkybNk0QBEF4+vSpMHr0aEEulwuzZs0S0tPTxbR3794Vxo4dK8jlciEwMFDtdZycnITRo0cLd+/eFfc9efJEEITS11WvW4eXtq7y9PR8ZV20e/duITk5WWVbQUGBsH37dqFFixZCv379VPIpCM9+p+RyueDs7Cz8/vvvKmWeNGmSWAfOmzdP5biy/iYQkWH4+OOPBblcLixatEjc9vjxY+Hff/8V/Pz8BLlcLri5uQm3bt2quExSpcJg3gApH2pe9V92drbKcatXr1bZ7+joKAwcOFCYP3++sH//fo1B7e7duwUnJyeVY/v27SvMmjVLiIyMFHJyckpdBmUw7+zsLKSlpRXbHxAQIMjlcmHcuHEq2319fQW5XC5s2LBB7XkjIiIEuVwu+Pv7q2xX3jPlw21p3bt3T+jbt6/KPWjfvr0wYcIEISgoSLh+/bra45Tl+Prrr9XuVwbhEyZMELc9fvxY6NixoyCXy4Xdu3eXKH9jxowR5HK5sGTJkmL7FAqF0KlTJ0EulwuRkZEq+152Xx48eCA4OzsLcrlcyMrKErcnJiYKjo6OglwuFxISEoodt379evEeMZgnfVMZ6k9NwXxRUZHK9++XX34RBOFZkCyXy4V33nlHfJH5vNTUVKFt27ZC27ZtVV74Ka/j7Ows3Lt3r9hxZamrtFGHa6qrBKFkwfzLzJkzR5DL5UJMTIzK9nfffVeQy+XCqlWrih2TlZUluLq6qg3my/KbQESGY8iQIRp/V9q3by/88MMP5fJSl0iJ3ewNmIODg0q3wRf/U862rjR9+nRs2LABvXr1gomJCQRBwM2bN7Fr1y7MmjULAwcOVNudcPjw4dixYwcGDx4sjhe9ffs29u/fj08//RT9+vUrNotzSQ0YMADW1tbFto8dOxYAEBsbC4VCAQDIz8/HiRMnYGRkpHEW6r59+wIAzp07p3b/8OHDy5TPunXr4pdffoGvr684i3VOTg7OnDmDoKAgDB48GAsXLkR+fr7KcYcPHwYAeHh4qD1vjx49YGJign/++QeFhYUAnpU5KysLNjY2cHd3f2XeHj16hPPnzwMAxo8fX2x/9erV8e677wJ4Nq5VHXX5s7KyEsv6fBfhU6dOQRAEdOjQQe1Y0lGjRsHExOSV+SaqSJWh/rx8+TLee+89vPfee/Dw8EDnzp0REBAAABg4cKA4Wefvv/8OABgxYgSMjYtPlWNjY4NWrVpBoVDg0qVLxfZ37doVdevWLba9tHVVedThpamrSuP69etYuXIlfH19MX78ePG+KvOh7DoLPFvd4MKFCwCgthyWlpZwc3NTe52y/CYQkWHIy8vDzZs3AQDOzs5wcXFB27ZtxefcnJwc5Obmcjk6KlecAM+AlWZpJaXOnTujc+fOePLkCS5duoQLFy7gxIkTiIqKwp07dzB16lTs2rWr2KQcLVq0wA8//ICCggLExcXh4sWL+PPPP3H69GlkZWXh448/hkwmQ+fOnUuVn8aNG6vdbmdnB1NTU+Tn5yM5ORnNmzdHYmIi8vLyYGJiorJu5/OE/z9WNDU1Ve3+15lsxMLCAn5+fvDz88OtW7fw77//4syZMzh27BjS09MRGRmJp0+fig/Tjx49QkpKCgDgs88+e+m58/LykJWVhTp16oizX7du3VplXKomycnJKCoqgqmpKezs7NSmadq0KQAgMTFR7f6GDRuq3V67dm3cvHlTfKHy/Dk0/e3Mzc1Rt25dcdJAIn1UGerP3NxcxMbGAng2k33NmjXRsWNHDB8+HCNHjhSXu7ty5QoAYOvWrdi3b5/acym/1y+Obwc0f9dLW1eVRx1emrqqpNauXYvly5eLk1Kpk52dLf7/5ORkCIKAWrVqqX3JAaifxbqsvwlEZBiuXr2KwsJCmJiYYMuWLeLEn4IgYPPmzVi8eDEiIiIwYsQItGzZsoJzS5UFg/kq6o033oCrqytcXV0xefJkREdHY8qUKVAoFFi/fr3GyedMTEzQunVrtG7dGp6enrh69SomTZqEtLQ0rF27ttQPo89PQvQ8iUQCKysr3Lt3D48ePQLw7I0mABQUFIgPsJrk5eWp3V6amahfxs7ODnZ2dhg8eDD8/f2xcOFC7Nu3D7t378bMmTNRv3595ObmiulflV8A4uRTyuNq1qxZorwo74+VlZXGtaqVD4TKtC/SdF+UD+jCcxNqKR+WX/ZmuU6dOgzmqdLSl/qzY8eOL50sTklZpyQkJLwyrbpJ8KRS6UvPW9K6Spt1uLq6qiTOnTuH77//HkZGRpg9ezb69u2LBg0aoHr16pBIJPjhhx+wZs0alVZyZR2onBhVHXX7yvqbQESGQTmTfePGjVVW8JBIJBg3bhwOHDiA6Oho7N69m8E8lRsG8wQAcHV1xXvvvYeffvqpVDO2N2vWDNOnT8fixYvLNNN7RkaG2u2CIIj7lA9Fyv+tW7cuTp48WepraUv16tXx5Zdf4sCBAygqKsKlS5dQv359lQfgS5culbjrubKcJZ01W5k+IyMDgiCoDejv37+vkvZ1KMul6W8HPFtnlaiqqKj6s6SU39n169eja9eu5XbestZV+lSH//rrrwCAyZMnq11W8969e8W2Ke/ny3oBqHtxWtbfBCIyDMpeUJqWMXZ3d0d0dDSOHj2KhQsX6jJrVIlxzDyJlF20CwoKdHIc8H/dNF90+/Zt5Ofno1q1amK3Snt7e5iYmCA9PR1ZWVmlvpY2mZubiy3VyvtgYWEBGxsbAMC1a9dKfC7lOPR///33pd0+lRo2bIhq1aohPz9f43hR5fUdHBxKnA9NlOdQjgt70aNHj9Q+ABNVZhVRf5aUstt/SVrmS6O0dZU+1uHKbu/t2rVTu//5sfJKyjo3MzNT7bAE4P8e6p9X1t8EIjIMypb55s2bq93fu3dvAMCdO3fU1i1EZcFgvopQttq+zD///APg2QOXUnZ29isn4VF3XEkdPnxYbDV+3ubNmwEALi4uYmtG9erV0b17dxQVFZWoa2l5elVLc1JSkpjm+fswYMAAAMCGDRtKfC0XFxfIZDKkpqZqHN/6vBo1aogPouruy5MnTxAZGQkA6N69e4nzoYnyHOfOnVP7QBoZGanVwIRI1/S1/iwpZT20bds2jd3Xy6K0dVVF1OFvvPEGAM1d1s3MzACor+NPnTql9oHb3Nwcbdq0AQDs3r272P6cnBwcPXpU7fXK8ptARIZB+RJPUzBft25dsdX+jz/+0Fm+qHJjMF9F7N27F8OGDcP27duRmZmpsu/hw4dYsWIF9u7dCwB45513xH3nzp3DoEGDEB4eXmxCoidPnmDjxo348ccfix1XUkVFRZgzZ45Kl+3ff/9dfNCbPHmySvoPP/wQpqamWL16NUJDQ4s9oKWlpWHDhg3YsmVLqfPyMsOGDcOiRYtw4cKFYi1Q586dg6+vLwRBQPPmzdGiRQtx35QpU1CrVi3s3r0bAQEBxbqjZmVlYceOHVi1apW4zczMDB988AEAYNGiRdi3b59KIJGdnY3w8HCVe6acTGrLli1it1Hg2RjNTz75BBkZGbC1tcWQIUNe+17Y29ujX79+EAQB8+bNU2mFP3v2LIKDg9l9lCoVfa0/S6p///5o27Ytbty4genTpyMpKUllf35+Po4fPw5/f/9SnbcsdZWu63BlzwdNs+O3b98eABAaGqrSs+nixYtYsGCBGOy/yMvLCwCwatUqHDt2TNyenZ2NWbNmaeyCX5bfBCLSf7du3RLnBdEUzANAr169ADCYp/LDMfMGbO3atWKLqzpvvfUWJkyYAODZ5BtXrlzBZ599hs8++wxvvvkmrKys8PDhQ6SkpIgtqZMmTUL//v1VznPr1i0EBAQgICAA9erVg7W1NRQKBe7cuYPHjx8DAIYMGQJPT89Sl2Hy5MnYvHkzevfujaZNmyIrK0vs9jh27FhxmSIlJycnfP/995g7dy6WLVuG4OBgNG7cWOy6effuXQDQOFNyWeXl5WHr1q3YunUratSogTfffBPGxsa4e/eu+KBar149fP/99ypj1uvVq4dVq1bBx8cH4eHh2LRpExo1aoTq1asjIyMDt2/fhiAIGDx4sMr1xo8fjxs3bmDLli2YPXs2lixZgjfffBMZGRm4d+8enj59Cjc3N7Frf58+fTB16lSEhoZizpw5WLZsGWrXro0bN25AoVDA0tISy5cvF1upXteiRYsQHx+PS5cuwc3NDc2aNYNCoUBiYiJ69+6NR48eaXx4JtIHlaH+LKlq1aohKCgI06ZNw19//YUBAwbA3t4etWrVwqNHj5CUlISCgoIyzZxe2rpK13X44MGDsWnTJvz444/4/fffYW1tDYlEgilTpqBnz54YPXo0tmzZguTkZLz11lto1KgRCgoKcPPmTTRt2hSDBw/G+vXri5130KBBeOedd7Bz507MmDEDdnZ2sLS0xLVr12BmZobJkydjzZo1xWb5L+tvAhHpN2WrfL169SCTyTSm6927N9asWYOLFy/i/v37XLGCXhuDeQOWmJiocakx4Nkal0pjx46Fo6MjTp48idjYWKSmpiIuLg7GxsawtbVF27Zt4eHhAVdXV5Vz9O3bF9u2bcPJkydx7tw53LlzRxx3WadOHbRq1QojRowQxwGVloODAyIjI7F8+XJERUUhNzcXzZs3x7hx4zSuw9u/f3/s378f4eHhOHXqFG7evIlq1aqhbt266N+/P9zc3Iq9BHhdv/76K06cOCFe7+7du1AoFDA3N4erqyv69OmDMWPGwNzcvNix7du3x4EDB7BhwwYcP35cXEqubt266NGjB/r06SN2vVSSSCT44osv0KdPH2zZsgUXLlxAfHw8rKys0KFDBwwcOFAce6k0e/ZsuLi4ICIiApcuXcL9+/fF9Z+nT5+O+vXrl9v9qFu3Lnbs2IEVK1bg6NGjuHbtGho0aICZM2di6tSpmDRpUrldi0gbKkP9WRo2NjbYtm0bduzYgQMHDiAhIQF37txBnTp10Lp1a3Tt2hVvvfVWqc9blrpKl3W4q6srli1bhg0bNuDatWvi33zEiBEAnnWZ37x5M5YtW4YTJ07g5s2bqFu3LiZOnAhfX1+1gbzSkiVL4OzsjC1btiAxMRGPHj1Cnz59MGvWLJw6dQqA+klHy/KbQET6zc3NTe1cGS9q165didIRlZREKO06LkTlYP78+WI3w9Ku9UxERKTPvvrqK/z888/w9/cXu+QTERGVN46ZJyIiIionjx49wqFDhwA8mySQiIhIWxjMExEREZVSeHi4uBSVUmpqKmbOnIn09HS0bNkSrVu3rqDcERFRVcAx80RERESldPToUQQEBMDCwgJ2dnbIz8/HjRs3UFRUBJlMhsDAwIrOIhERVXIM5omIiIhKacKECahZsyYuX76MGzduQBAENGzYED169MCUKVNQt27dis4iERFVcpwAj4iIiIiIiMjAcMw8ERERERERkYGpdN3sMzMzdXo9S0tLZGdn6/SaFaEqlJNlrBx0XUaZTKaza2mTrutOgJ/HyoJlrBxYd74anzHLH8tYObCM2lGSepIt86+pWrWqcQurQjlZxsqhKpSxsqgKfyuWsXJgGakiVIW/CctYObCMFUc/c0VEREREREREGjGYJyIiIiIiIjIwDOaJiIiIiIiIDAyDeSIiIiIiIiIDw2CeiIiIiIiIyMAwmCciIiIiIiIyMAzmiYiIiIiIiAyMcWkP2LNnD2JiYnDp0iUkJCSgoKAAAQEBGDlypNr0ubm5CAoKwuHDh5Geng5ra2sMGDAAfn5+MDc3V3vMr7/+ig0bNuDatWswMTFB27ZtMXPmTLRq1aq02SUiIiIiIiKqdErdMr9ixQps27YNd+7cgY2NzUvTKhQKeHp6Ijw8HI0aNYKXlxeaNGmC8PBweHp6QqFQFDtmzZo1mDNnDh48eIAxY8bgrbfeQmxsLN577z2cPXu2tNklIiIiIiIiqnRK3TK/ZMkS2Nvbw9bWFqGhoVi2bJnGtGFhYYiLi4O3tzfmzp0rbl+5ciVCQkIQFhaGmTNnitsTExMRFBQEBwcH7NixAxYWFgCA8ePHw8PDAwsXLsTBgwdhbFzqbBMRERERERFVGqVume/atStsbW1fmU4QBERGRkIqlcLHx0dl37Rp02BpaYkdO3ZAEARx+65du1BYWIgZM2aIgTwANGvWDMOGDUNycjLOnDlT2iwTERERERERVSpamwAvMTERaWlpcHFxgVQqVdlnZmYGV1dXpKamIikpSdweFRUFAOjWrVux8/Xo0QMAcO7cOW1lmYiIiIiIiMggaK2/ujJId3BwULvf3t5eTKdMk5iYCKlUCmtra43pExMTyz2vRKRfuvcueo2jH5TpqFPHubgHERm+stefrDuJiAyN1oL5nJwcANA4Y71yuzId8Gzmeysrq5emz83Nfel1LS0tUa2abn9YZDKZTq9XUapCOVlGfVG2h8rXYRj3hYiIiIjomUo3k1x2drZOryeTyZCZmanTa1aEqlBOlrFqK+t94UsAIiIiIqoIWmvCVk5gp6klXbn9+YnuzM3NVVrq1aXX1NJPREREREREVFVoLZh/1Rh35Zh6ZTrg2fh6hUKB9PR0jek1jcEnIiIiIiIiqiq0Fsw7ODjAxsYGsbGxUCgUKvvy8vIQHR0NGxsblWC+Q4cOAIDTp08XO9+ff/6pkoaIiIiIiIioqtJaMC+RSODh4QGFQoGQkBCVfWvXrkV2djY8PDwgkUjE7SNHjoSxsTFWr16t0t3+6tWr2LNnDxo2bIjOnTtrK8tEREREREREBqHUE+BFRkYiJiYGAJCQkCBuU64R7+bmBjc3NwCAt7c3jh07hrCwMMTFxaFly5aIj4/HyZMn4eTkBG9vb5VzN2rUCL6+vli+fDnc3d0xcOBAKBQK7N+/H4WFhfjqq69gbFzp5uwjIiIiIiIiKpVSR8YxMTHYvXu3yrbY2FjExsYCAGxtbcVgXiqVIiIiAsHBwTh06BCioqJQp04deHl5wdfXF1KptNj5Z8yYAVtbW2zYsAFbtmyBiYkJ2rVrh5kzZ6J169ZlKSMRERERERFRpVLqYD4wMBCBgYElTm9hYQF/f3/4+/uX+Bh3d3e4u7uXNmtEREREREREVYLWxswTERERERERkXYwmCciIiIiIiIyMAzmiYiIiIiIiAwMg3kiIiIiIiIiA8NgnoiIiIiIiMjAMJgnIiIiIiIiMjClXpqOiIiIiIiIKpfuvYvKeOSDMh116jjblV8X7yARERERERGRgWHLPBGRjuzZswcxMTG4dOkSEhISUFBQgICAAIwcOVIlXUFBAY4dO4Y//vgDFy5cwN27dyGRSNC0aVMMHz4cY8aMgZGRkdpr/Prrr9iwYQOuXbsGExMTtG3bFjNnzkSrVq10UUQiIiIi0hEG80REOrJixQqkpKRAJpPBxsYGKSkpatMlJydj5syZqFGjBjp37oy+ffsiJycHf/zxBxYvXow///wTq1evhkQiUTluzZo1+OGHH9CgQQOMGTMGCoUC+/fvx3vvvYeffvoJnTp10kUxiYiIiEgHGMwTEenIkiVLYG9vD1tbW4SGhmLZsmVq05mbm2PRokUYMWIEqlevLm5XKBQYP348/vjjD/z222946623xH2JiYkICgqCg4MDduzYAQsLCwDA+PHj4eHhgYULF+LgwYMwNma1T0RERFQZcMw8EZGOdO3aFba2tq9MV7duXYwdO1YlkAcAqVSKiRMnAgDOnTunsm/Xrl0oLCzEjBkzxEAeAJo1a4Zhw4YhOTkZZ86cKYdSEBEREZE+YDBPRGRAlC3rL46Zj4qKAgB069at2DE9evQAUPwFABEREREZLgbzREQGZOfOnQCA7t27q2xPTEyEVCqFtbV1sWPs7e3FNERERERUOXDwJBGRgdi2bRtOnjyJzp07o1evXir7cnNzYWVlpfY4c3NzMY0mlpaWqFZN9+93ZTKZzq+payxj5WA4ZSzbes9lZTj3hYio8mEwT0RkAI4fP46vvvoKtra2WLp0abmfPzs7u9zP+SoymQyZmZk6v64usYyVQ1UoY1mV9b7wJQAR0etjN3siIj33559/ws/PD7Vr18aGDRtgY2NTLI25uTlycnLUHq9skVe20BMRERGR4WMwT0Skx06ePAkfHx/IZDJs3LgRdnZ2atM5ODhAoVAgPT292L6kpCQxDRERERFVDgzmiYj0lDKQr1mzJjZu3ChOZKdOhw4dAACnT58utu/PP/9USUNEREREho/BPBGRHlIG8paWlti4ceMrW9VHjhwJY2NjrF69WqW7/dWrV7Fnzx40bNgQnTt31nKuiYiIiEhXOAEeEZGOREZGIiYmBgCQkJAgblOuEe/m5gY3Nzdcv34dPj4+yM/PR8eOHbF///5i57K1tcXIkSPFfzdq1Ai+vr5Yvnw53N3dMXDgQCgUCuzfvx+FhYX46quvxDXqiYiIiMjw8cmOiEhHYmJisHv3bpVtsbGxiI2NBfAsQHdzc8P9+/eRn58PAGoDeQDo2LGjSjAPADNmzICtrS02bNiALVu2wMTEBO3atcPMmTPRunVrLZSIiIiIiCoKg3kiIh0JDAxEYGDgK9N16tQJV65cKdM13N3d4e7uXqZjiYiIiMhwcMw8ERERERERkYFhME9ERERERERkYBjMExERERERERkYBvNEREREREREBobBPBEREREREZGBYTBPREREREREZGAYzBMREREREREZGAbzRERERERERAaGwTwRERERERGRgWEwT0RERERERGRgGMwTERERERERGRgG80REREREREQGhsE8ERERERERkYFhME9ERERERERkYBjMExERERERERkYY11cRBAE/P7774iIiMDNmzeRk5ODevXqoVOnTpgyZQrs7OxU0ufm5iIoKAiHDx9Geno6rK2tMWDAAPj5+cHc3FwXWSYiIiIiIiLSWzoJ5r/55husX78e1tbW6NevH8zNzREfH4/t27dj37592Lp1K+RyOQBAoVDA09MTcXFx6NatG4YMGYL4+HiEh4fj7Nmz2Lx5M6RSqS6yTUREREQVbM+ePYiJicGlS5eQkJCAgoICBAQEYOTIkaU+V25uLtatW4fDhw/j1q1bMDExgZ2dHfr16wdfX18t5J6ISHu0Hsynp6djw4YNsLW1xd69e1Va1sPDwxEQEID169cjICAAABAWFoa4uDh4e3tj7ty5YtqVK1ciJCQEYWFhmDlzprazTURERER6YMWKFUhJSYFMJoONjQ1SUlLKdJ47d+7g/fffx61bt9C1a1f06tUL+fn5SE5OxqFDhxjME5HB0Xown5KSgqKiIri4uBTrIt+7d28EBAQgIyMDwLPu+JGRkZBKpfDx8VFJO23aNPz888/YsWMH/Pz8IJFItJ11IiIiIqpgS5Ysgb29PWxtbREaGoply5aV+hxPnz7FzJkzkZaWhvDwcHTu3Fllf2FhYXlll4hIZ7Q+AZ69vT1MTEwQGxuL3NxclX0nTpwAALFCTUxMRFpaGlxcXIp1pTczM4OrqytSU1ORlJSk7WwTERERkR7o2rUrbG1tX+schw4dwr///otJkyYVC+QBwNhYJyNPiYjKldZrLplMhlmzZuHbb7/F4MGD0bdvX9SoUQMJCQn4+++/MXr0aHh6egKAGKQ7ODioPZe9vb2YTlMaIiIiIqLnHThwAAAwaNAg3L17F8ePH0dOTg7s7OzQs2dP1KhRo4JzSERUejp5DTl58mTY2Njg888/x5YtW8Tt7dq1g7u7O0xMTAAAOTk5AKBxxnrldmU6dSwtLVGtmm5X3JPJZDq9XkWpCuVkGfXFA51f0TDuCxERlcWlS5cAADExMQgICEB+fr64z8rKCsuXL0enTp0qKntERGWik2B+1apVWLVqFXx9fTF8+HDUrFkTcXFxCAwMxIQJE7B8+XIMGDCgXK6VnZ1dLucpKZlMhszMTJ1esyJUhXKyjFVbWe8LXwIQEem/Bw+evSResmQJJk2aBE9PT5iammL//v345ptv4OPjgwMHDsDGxkbjOdhgpB0soz7RbWOK4dyXZ/Qxv1oP5v/++2+sWLECXl5emD59uri9ffv2WLt2Lfr164eAgAAMGDAAFhYWAFBsbL2ScrsyHRERERHRqwiCAODZ5Mtz5swRt48fPx6pqan48ccfsWPHDnzwwQcaz8EGo/LHMlZthnRfKuLvWJKXB1p/vaic5E5d1yUrKys4Ojrizp07yMjIEMfEJyYmqj2Xcky9Mh0RERER0asoh2r27du32L4+ffoA+L+u+EREhkLrwXxBQQEAiMvPvUi53dTUFA4ODrCxsUFsbCwUCoVKury8PERHR8PGxobBPBERERGVWKNGjQAANWvWLLZPuS0vL0+neSIiel1aD+ZdXFwAAOHh4cUmrtu9ezeSkpLQsmVLmJubQyKRwMPDAwqFAiEhISpp165di+zsbHh4eHCNeSIySHv27MHnn3+OkSNHwtnZGY6Ojti1a5fG9Lm5uQgICECfPn3g7OyMPn36ICAgQONQJAD49ddfMWrUKLRt2xYdOnTAlClT8O+//2qjOEREBkO5HN21a9eK7VNue93l74iIdE3rY+YHDRqErVu3IioqCgMGDEDfvn1Rs2ZNXLlyBadPn4apqSkWLFggpvf29saxY8cQFhaGuLg4tGzZEvHx8Th58iScnJzg7e2t7SwTEWnFihUrkJKSAplMBhsbG6SkpGhMq1Ao4Onpibi4OHTr1g1DhgxBfHw8wsPDcfbsWWzevBlSqVTlmDVr1uCHH35AgwYNMGbMGCgUCuzfvx/vvfcefvrpJ87UTESVXkZGBjIzMyGTyWBlZSVuHzlyJMLCwvDzzz/jnXfeQd26dQE8e2m6du1aAMBbb71VIXkmIiorrQfzRkZG+Omnn7BhwwYcPHgQ+/fvR0FBAWrXro2hQ4di2rRpkMvlYnqpVIqIiAgEBwfj0KFDiIqKQp06deDl5QVfX99iD69ERIZiyZIlsLe3h62tLUJDQ7Fs2TKNaZUvNL29vTF37lxx+8qVKxESEoKwsDDMnDlT3J6YmIigoCA4ODhgx44d4kSh48ePh4eHBxYuXIiDBw/C2Fgni5gQEZWbyMhIxMTEAAASEhLEbVFRUQAANzc3uLm5AQA2bdqE4OBg+Pr6ws/PTzyHnZ0dPvnkEyxZsgTu7u7o378/TE1Ncfz4caSkpGD06NHo0qWLjktGRPR6dPJUZ2pqiilTpmDKlCklSm9hYQF/f3/4+/trOWdERLrTtWvXEqUTBAGRkZGQSqXw8fFR2Tdt2jT8/PPP2LFjB/z8/MRhR7t27UJhYSFmzJihsuJHs2bNMGzYMGzduhVnzpxB9+7dy69AREQ6EBMTg927d6tsi42NRWxsLIBn3eOVwfzLjB8/Hra2tvjpp5+wf/9+PH36FE2bNsX06dPx7rvvaiXvRETaxCYaIiI9k5iYiLS0NHTv3r1YbyQzMzO4urri6NGjSEpKgoODAwCILVTdunUrdr4ePXpg69atOHfuHIN5IjI4gYGBCAwMLFFaPz8/lRb5F/Xt21ftjPZERIZI6xPgERFR6SiX4VQG6i9SruihTAc8ewEglUphbW2tMb2mZT+JiIiIyPCwZZ6ISM8oV/5Qrov8IuX251cIyc3NVZnsSV36l82Cb2lpiWrVdP9+VyaT6fyausYyVg6GU8YHOr2a4dwXIqLKh8E8EREhOztb59eUyWTIzMzU+XV1iWWsHKpCGcuqrPeFLwGIiF4fu9kTEekZ5QR2mlrSldufn+jO3NxcpaVeXXpNLf1EREREZHgYzBMR6ZlXjXFXjpVXpgOeja9XKBRIT0/XmF7TGHwiIiIiMjwM5omI9IyDgwNsbGwQGxsLhUKhsi8vLw/R0dGwsbFRCeY7dOgAADh9+nSx8/35558qaYiIiIjI8DGYJyLSMxKJBB4eHlAoFAgJCVHZt3btWmRnZ8PDw0NcYx4ARo4cCWNjY6xevVqlu/3Vq1exZ88eNGzYEJ07d9ZZGYiIiIhIuzgBHhGRjkRGRiImJgYAkJCQIG5TrhHv5uYGNzc3AIC3tzeOHTuGsLAwxMXFoWXLloiPj8fJkyfh5OQEb29vlXM3atQIvr6+WL58Odzd3TFw4EAoFArs378fhYWF+Oqrr2BszCqfiIiIqLLgkx0RkY7ExMRg9+7dKttiY2MRGxsLALC1tRWDealUioiICAQHB+PQoUOIiopCnTp14OXlBV9fX0il0mLnnzFjBmxtbbFhwwZs2bIFJiYmaNeuHWbOnInWrVtrv4BEREREpDMM5omIdCQwMBCBgYElTm9hYQF/f3/4+/uX+Bh3d3e4u7uXJXtEREREZEA4Zp6IiIiIiIjIwDCYJyIiIiIiIjIwDOaJiIiIiIiIDAyDeSIiIiIiIiIDw2CeiIiIiIiIyMAwmCciIiIiIiIyMAzmiYiIiIiIiAwMg3kiIiIiIiIiA8NgnoiIiIiIiMjAMJgnIiIiIiIiMjAM5omIiIiIiIgMDIN5IiIiIiIiIgPDYJ6IiIiIiIjIwDCYJyIiIiIiIjIwDOaJiIiIiIiIDAyDeSIiIiIiIiIDw2CeiIiIiIiIyMAwmCciIiIiIiIyMAzmiYiIiIiIiAwMg3kiIiIiIiIiA8NgnoiIiIiIiMjAMJgnIiIiIiIiMjAM5omIiIiIiIgMDIN5IiIiIiIiIgPDYJ6IiIiIiIjIwBhXdAaIiEg9QRDw+++/IyIiAjdv3kROTg7q1auHTp06YcqUKbCzs1NJn5ubi6CgIBw+fBjp6emwtrbGgAED4OfnB3Nz8woqBRERERFpA1vmiYj01DfffAM/Pz/cvHkT/fr1g6enJ958801s374dw4YNQ0JCgphWoVDA09MT4eHhaNSoEby8vNCkSROEh4fD09MTCoWiAktCREREROVNpy3zv//+OzZv3ozLly/j8ePHqFOnDtq2bYu5c+eifv36Yjq2LhFRVZeeno4NGzbA1tYWe/fuVan7wsPDERAQgPXr1yMgIAAAEBYWhri4OHh7e2Pu3Lli2pUrVyIkJARhYWGYOXOmzstBRERERNqhk5Z5QRDw+eefw9fXF7dv38bgwYMxYcIEuLq64p9//kFKSoqYlq1LRERASkoKioqK4OLiUuwlZu/evQEAGRkZAJ7VsZGRkZBKpfDx8VFJO23aNFhaWmLHjh0QBEEneSciIiIi7dNJy3xERAS2bduGcePG4dNPP4WRkZHK/sLCQvH/s3WJiAiwt7eHiYkJYmNjkZubqxLQnzhxAgDQuXNnAEBiYiLS0tLQvXt3SKVSlfOYmZnB1dUVR48eRVJSEhwcHHRWBiIiIiLSHq23zD958gQhISGws7PDggULigXyAGBs/OydAluXiIiekclkmDVrFlJSUjB48GB88cUXWLp0KaZMmYKlS5di9OjR8PT0BAAkJSUBgMZA3d7eXiUdERERERk+rbfMnz59GllZWRgxYgSKiopw+PBhJCYmwsLCAl27dhUfMgG2LhERPW/y5MmwsbHB559/ji1btojb27VrB3d3d5iYmAAAcnJyAEDjnCLK7cp06lhaWqJaNd3PiSqTyXR+TV1jGSsHwynjA51ezXDuCxFR5aP1YP7SpUsAACMjI7i7u+PmzZvivmrVqsHLywvz5s0DULrWJQbzRFTZrVq1CqtWrYKvry+GDx+OmjVrIi4uDoGBgZgwYQKWL1+OAQMGlMu1srOzy+U8pSGTyZCZmanz6+oSy1g5VIUyllVZ7wtfAhARvT6tB/MPHjx7Q7x+/Xq0aNECkZGRaNKkCeLi4vDZZ59h3bp1sLOzw9ixYw22damq/CBVhXKyjPpCty1LgP7dl7///hsrVqyAl5cXpk+fLm5v37491q5di379+iEgIAADBgyAhYUFgGcrgaij3K5MR0RERESGT+vBvHJ8u4mJCUJCQlC3bl0AgKurK1auXAl3d3esX78eY8eOLZfr6bp1qaq8ra8K5WQZqzZ9a11STnLXqVOnYvusrKzg6OiIf/75BxkZGWKvpcTERLXnUvZ6en5YExEREREZNq03YStb052dncVAXqlZs2aws7NDcnIyHj58yNYlIqL/r6CgAMD/LT/3IuV2U1NTODg4wMbGBrGxscWW78zLy0N0dDRsbGwYzBMRERFVIloP5hs3bgxAcwCu3P7kyRO2LhER/X8uLi4AgPDw8GJDi3bv3o2kpCS0bNkS5ubmkEgk8PDwgEKhQEhIiEratWvXIjs7Gx4eHpBIJDrLPxERERFpl9a72Su7iN64caPYvoKCAiQnJ0MqlcLKygrW1tYqrUvPz2jP1iUiqkoGDRqErVu3IioqCgMGDEDfvn1Rs2ZNXLlyBadPn4apqSkWLFggpvf29saxY8cQFhaGuLg4tGzZEvHx8Th58iScnJzg7e1dgaUhIiIiovKm9Zb5hg0bonv37khKSkJkZKTKvtDQUDx8+BBubm4wNjZm6xIR0f9nZGSEn376CXPmzEH9+vWxf/9+bNy4EdeuXcPQoUOxc+dOuLq6iumlUikiIiLg5eWFGzduYP369bh69Sq8vLwQERFRbLlPIiIiIjJsEkE5Q50WJScnY8yYMXjw4AF69+6Nxo0b4/Llyzhz5gxsbW2xbds2WFtbAwAUCgXGjh2LuLg4dOvWrVjr0ubNm1/6UKrryb2qyoRiVaGcLKP+6N67SOfXPHW8bO829W0W/LKqiM+FoXweXwfLWDkYUhl1XX9WpbqTz5jlj2XUL4ZSf1SEivg7lqSe1MkdbNiwIXbu3ImRI0fiv//+Q0REBJKSkjBu3DhERkaKgTzA1iUiIiIiIiKiV9H6mHml+vXrIyAgoERpLSws4O/vD39/fy3nioiIiIiIiMjwGE7fBiIiIiIiIiICwGCeiIiIiIiIyOAwmCciIiIiIiIyMAzmiYiIiIiIiAwMg3kiIiIi0lt79uzB559/jpEjR8LZ2RmOjo7YtWvXa52zoKAAw4YNg6OjIwYNGlROOSUi0i2dzWZPRERERFRaK1asQEpKCmQyGWxsbJCSkvLa51y1ahWSk5PLIXdERBWHLfNEREREpLeWLFmCY8eO4cyZMxgzZsxrn++///5DaGgoPv7443LIHRFRxWHLPBERERHpra5du5bbufLz8zF//ny0adMGnp6eWLJkSbmdmyq37r2LynjkgzIddeo421zp1RjMExEREVGVEBwcjKSkJOzZswcSiaSis0NE9Fr4yoeIiIiIKr2LFy8iLCwMfn5+aNSoUUVnh4jotbFlnoiIiIgqtfz8fPj7+8PJyQmTJk0q0zksLS1RrZpu28FkMplOr1cRDKeMZesuX1YVc1+qQhnLTh/zy2CeiIiIiCq15cuXIykpCTt37oSRkVGZzpGdnV3OuXo5mUyGzMxMnV5T16pCGcuqKtwXQypjRXxWS/LygN3siYiIiKjS+u+//xAeHo7p06fD0dGxorNDRFRu2DJPRERERJXWlStX8PTpUwQFBSEoKKjY/ps3b8LR0REWFhaIjo6ugBwSEZUNg3kiIiIiqrQcHBwwatQotft27NgBCwsLDBw4ENWrV9dxzoiIXg+DeSIiIiKqFDIyMpCZmQmZTAYrKysAgIuLC1xcXNSm37FjB+rUqYP//e9/uswmEVG5YDBPRERERHorMjISMTExAICEhARxW1RUFADAzc0Nbm5uAIBNmzYhODgYvr6+8PPzq5gMExHpCIN5IiIiItJbMTEx2L17t8q22NhYxMbGAgBsbW3FYJ6IqCphME9EREREeiswMBCBgYElSuvn51eqFvkrV66UNVtERBWOS9MRERERERERGRgG80REREREREQGhsE8ERERERERkYFhME9ERERERERkYBjMExERERERERkYzmZPRKTnfv/9d2zevBmXL1/G48ePUadOHbRt2xZz585F/fr1xXS5ubkICgrC4cOHkZ6eDmtrawwYMAB+fn4wNzevwBIQERERUXljME9EpKcEQcCiRYuwbds2NGzYEIMHD0aNGjWQlpaGc+fOISUlRQzmFQoFPD09ERcXh27dumHIkCGIj49HeHg4zp49i82bN0MqlVZwiYiIiIiovDCYJyLSUxEREdi2bRvGjRuHTz/9FEZGRir7CwsLxf8fFhaGuLg4eHt7Y+7cueL2lStXIiQkBGFhYZg5c6bO8k5ERERE2sUx80REeujJkycICQmBnZ0dFixYUCyQBwBj42fvYwVBQGRkJKRSKXx8fFTSTJs2DZaWltixYwcEQdBJ3omIiIhI+xjMExHpodOnTyMrKwtubm4oKirC4cOHERoaii1btiApKUklbWJiItLS0uDi4lKsK72ZmRlcXV2Rmppa7DgiIiIiMlzsZk9EpIcuXboEADAyMoK7uztu3rwp7qtWrRq8vLwwb948ABCDdAcHB7Xnsre3F9NpSkNEREREhoXBPBGRHnrw4AEAYP369WjRogUiIyPRpEkTxMXF4bPPPsO6detgZ2eHsWPHIicnBwA0zliv3K5Mp46lpSWqVdN9Zy2ZTKbza+oay1g5GE4ZH+j0aoZzX4iIKh8G80REekg5vt3ExAQhISGoW7cuAMDV1RUrV66Eu7s71q9fj7Fjx5bL9bKzs8vlPKUhk8mQmZmp8+vqEstYOVSFMpZVWe8LXwIQEb0+jpknItJDytZ0Z2dnMZBXatasGezs7JCcnIyHDx/CwsICwLN15tVRblemIyIiIiLDx2CeiEgPNW7cGIDmAFy5/cmTJ+KY+MTERLVplWPqlemIiIiIyPCxmz0RkR7q1KkTAODGjRvF9hUUFCA5ORlSqRRWVlawtraGjY0NYmNjoVAoVGa0z8vLQ3R0NGxsbBjMExEREVUibJknItJDDRs2RPfu3ZGUlITIyEiVfaGhoXj48CHc3NxgbGwMiUQCDw8PKBQKhISEqKRdu3YtsrOz4eHhAYlEossiEBEREZEWsWWeiEhPLVq0CGPGjMHChQtx5MgRNG7cGJcvX8aZM2dga2uLTz75REzr7e2NY8eOISwsDHFxcWjZsiXi4+Nx8uRJODk5wdvbuwJLQkRERETljS3zRER6qmHDhti5cydGjhyJ//77DxEREUhKSsK4ceMQGRkJa2trMa1UKkVERAS8vLxw48YNrF+/HlevXoWXlxciIiJUut4TERERkeFjyzwRkR6rX78+AgICSpTWwsIC/v7+8Pf313KuiIiIiKii6bxl/scff4SjoyMcHR1x/vx5tWlyc3MREBCAPn36wNnZGX369EFAQIDGZZeIiIiIiIiIqhKdBvPXr1/HypUrX9rdU6FQwNPTE+Hh4WjUqBG8vLzQpEkThIeHw9PTEwqFQoc5JiIiIiIiItI/Ogvmnz59innz5qF58+Zwc3PTmE45eZO3tzfWrVuHOXPmICwsDD4+PoiLi0NYWJiuskxERERERESkl3QWzP/444+Ij4/H119/DSMjI7VpBEFAZGQkpFIpfHx8VPZNmzYNlpaW2LFjBwRB0EWWiYiIiIiIiPSSToL5hIQEBAcHY8aMGWjWrJnGdImJiUhLS4OLi0uxrvhmZmZwdXVFamoqkpKStJ1lIiIiIiIiIr2l9dnsCwsLMX/+fDRp0gRTp059aVplkO7g4KB2v729vZhOUxpLS0tUq6bbef1kMplOr1dRqkI5WUZ98UDnVzSM+0JERERE9IzWg/k1a9bgypUr2L59O0xMTF6aNicnBwBgbm6udr9yuzKdOtnZ2WXMadnIZDJkZmbq9JoVoSqUk2Ws2sp6X/gSgIiIiIgqglabsOPj47FmzRpMmjQJLVu21OaliIiIiIiIiKoMrQbz8+bNg52dHfz8/EqU3sLCAgA0riev3K5MR0RERERERFQVabWbfXx8PACgVatWavePHj0aABASEgI3NzdxTHxiYqLa9Mox9cp0RERERERERFWRVoP5UaNGqd0eHR2NxMRE9O3bF1ZWVrC1tQXwbOI7GxsbxMbGQqFQqMxon5eXh+joaNjY2DCYJyIiIiIioipNq8H8//73P7Xb58+fj8TEREybNg1t27YVt0skEnh4eCAkJAQhISGYO3euuG/t2rXIzs6Gj48PJBKJNrNNREREREREpNe0Ppt9aXl7e+PYsWMICwtDXFwcWrZsifj4eJw8eRJOTk7w9vau6CwSERERERERVSjdLsheAlKpFBEREfDy8sKNGzewfv16XL16FV5eXoiIiFDpek9ERERERERUFVVIy3xgYCACAwM17rewsIC/vz/8/f11mCsiIiIiIiIiw6B3LfNERERERERE9HIM5omIiIiIiIgMDIN5IiIiIiIiIgPDYJ6IiIiIiIjIwDCYJyIiIiIiIjIwDOaJiIiIiIiIDAyDeSIiIiIiIiIDw2CeiIiIiIiIyMAwmCciIiIiIiIyMAzmiYiIiIiIiAwMg3kiIgPx448/wtHREY6Ojjh//rzaNLm5uQgICECfPn3g7OyMPn36ICAgALm5ubrNLBERERFpFYN5IiIDcP36daxcuRJSqVRjGoVCAU9PT4SHh6NRo0bw8vJCkyZNEB4eDk9PTygUCh3mmIiIiIi0icE8EZGee/r0KebNm4fmzZvDzc1NY7qwsDDExcXB29sb69atw5w5cxAWFgYfHx/ExcUhLCxMh7kmIiIiIm1iME9EpOd+/PFHxMfH4+uvv4aRkZHaNIIgIDIyElKpFD4+Pir7pk2bBktLS+zYsQOCIOgiy0RERESkZQzmiYj0WEJCAoKDgzFjxgw0a9ZMY7rExESkpaXBxcWlWFd8MzMzuLq6IjU1FUlJSdrOMhERERHpAIN5IiI9VVhYiPnz56NJkyaYOnXqS9Mqg3QHBwe1++3t7VXSEREREZFhM67oDBARkXpr1qzBlStXsH37dpiYmLw0bU5ODgDA3Nxc7X7ldmW6F1laWqJaNd2/35XJZDq/pq6xjJWD4ZTxgU6vZjj3hYio8mEwT0Skh+Lj47FmzRpMmjQJLVu21Pr1srOztX6NF8lkMmRmZur8urrEMlYOVaGMZVXW+8KXAEREr4/d7ImI9NC8efNgZ2cHPz+/EqW3sLAAAI3rySu3K9MRERERkWFjyzwRkR6Kj48HALRq1Urt/tGjRwMAQkJC4ObmJo6JT0xMVJteOVZemY6IiIiIDBuDeSIiPTRq1Ci126Ojo5GYmIi+ffvCysoKtra2AJ5NfGdjY4PY2FgoFAqVGe3z8vIQHR0NGxsbBvNEZHD27NmDmJgYXLp0CQkJCSgoKEBAQABGjhxZ4nNER0fjyJEjiIqKQkpKChQKBWxtbdGvXz9MmzYNNWvW1GIJiIi0g8E8EZEe+t///qd2+/z585GYmIhp06ahbdu24naJRAIPDw+EhIQgJCQEc+fOFfetXbsW2dnZ8PHxgUQi0XbWiYjK1YoVK5CSkgKZTAYbGxukpKSU+hwffvghMjMz0b59ewwbNgwSiQRRUVEICwvD4cOHsXXrVtSuXVsLuSci0h4G80RElYS3tzeOHTuGsLAwxMXFoWXLloiPj8fJkyfh5OQEb2/vis4iEVGpLVmyBPb29rC1tUVoaCiWLVtW6nO8//77GD58OGxsbMRtgiDgyy+/xJYtWxAcHIxFixaVZ7aJiLSOE+AREVUSUqkUERER8PLywo0bN7B+/XpcvXoVXl5eiIiIUOl6T0RkKLp27SoOKSqrqVOnqgTywLMeTR988AEA4Ny5c691fiKiisCWeSIiAxIYGIjAwECN+y0sLODv7w9/f38d5oqIyDAZGz97FDYyMqrgnBARlR5b5omIiIioStq5cycAoFu3bhWcEyKi0mPLPBERERFVOXFxcQgJCUHt2rVLNKeIpaUlqlXTbTuYTCbT6fUqguGU8YFOr1Yx96UqlLHs9DG/DOaJiIiIqEq5desWpk2bhqdPn+L777+HlZXVK4/Jzs7WQc7+j0wmQ2Zmpk6vqWtVoYxlVRXuiyGVsSI+qyV5ecBgnoiIiIiqjJSUFLz//vvIyMhAUFAQOnfuXNFZIiIqE46ZJyIiIqIq4fbt2xg/fjzS0tKwfPly9OnTp6KzRERUZgzmiYiIiKjSu337NiZMmIC0tDT88MMPcHNzq+gsERG9FnazJyIiIqJKISMjA5mZmZDJZCrj4JWBfGpqKn744Qf079+/AnNJRFQ+GMwTERERkd6KjIxETEwMACAhIUHcFhUVBQBwc3MTW9k3bdqE4OBg+Pr6ws/PTzzHhAkTkJKSgrZt2+LKlSu4cuVKses8n56IyBAwmCciIiIivRUTE4Pdu3erbIuNjUVsbCwAwNbW9pVd5lNSUgAA58+fx/nz59WmYTBPRIaGwTwRERER6a3AwEAEBgaWKK2fn5/aoFxdSzwRkaHjBHhEREREREREBobBPBEREREREZGBYTBPREREREREZGC0PmY+NTUVBw8exMmTJ3Hjxg3cv38flpaWcHFxgbe3N9q0aVPsmNzcXAQFBeHw4cNIT0+HtbU1BgwYAD8/P5ibm2s7y0RERERERER6TevBfEREBH788Uc0bNgQXbt2Re3atZGUlIQjR47gyJEjWLZsGQYPHiymVygU8PT0RFxcHLp164YhQ4YgPj4e4eHhOHv2LDZv3gypVKrtbBMRERERERHpLa0H861bt8amTZvg6uqqsj06OhpeXl748ssv4ebmBlNTUwBAWFgY4uLi4O3tjblz54rpV65ciZCQEISFhWHmzJnazjYRERERERGR3tL6mPkBAwYUC+QBwNXVFZ06dUJWVpa4XIggCIiMjIRUKoWPj49K+mnTpsHS0hI7duyAIAjazjYRERERERGR3qrQCfCMjY1V/jcxMRFpaWlwcXEp1pXezMwMrq6uSE1NRVJSks7zSkRERERERKQvKiyYv3PnDv766y9YW1tDLpcDgBikOzg4qD3G3t5eJR0RERERERFRVaT1MfPqFBQU4JNPPkF+fj7mzJkDIyMjAEBOTg4AaJyxXrldmU4dS0tLVKum23cUMplMp9erKFWhnCyjvnig8ysaxn0hIiIiInpG58F8UVERFixYgHPnzuHdd9/F8OHDy/X82dnZ5Xq+V5HJZMjMzNTpNStCVSgny1i1lfW+8CUAEREREVUEnTZhC4KAhQsXYu/evXB3d8eXX36pst/CwgLAs3Xm1VFuV6YjIiIiIiIiqop0FswrW+R37tyJoUOHIjAwsFh3eOWY+MTERLXnUI6VV6YjIiIiIiIiqop0EswXFRXh008/xa5duzB48GB8++234jj55zk4OMDGxgaxsbFQKBQq+/Ly8hAdHQ0bGxsG80RERERERFSlaT2Yfz6QHzRoEJYuXao2kAcAiUQCDw8PKBQKhISEqOxbu3YtsrOz4eHhAYlEou1sExEREREREektrU+AFxISgl27dkEqlcLBwQGrV68ulsbNzQ1OTk4AAG9vbxw7dgxhYWGIi4tDy5YtER8fj5MnT8LJyQne3t7azjIRERERERGRXtN6MJ+SkgIAUCgUWLNmjdo0tra2YjAvlUoRERGB4OBgHDp0CFFRUahTpw68vLzg6+sLqVSq7SwTEVW41NRUHDx4ECdPnsSNGzdw//59WFpawsXFBd7e3mjTpk2xY3JzcxEUFITDhw8jPT0d1tbWGDBgAPz8/DQu+UlEREREhknrwXxgYCACAwNLdYyFhQX8/f3h7++vpVwREem3iIgI/Pjjj2jYsCG6du2K2rVrIykpCUeOHMGRI0ewbNkyDB48WEyvUCjg6emJuLg4dOvWDUOGDEF8fDzCw8Nx9uxZbN68mS9DiYiIiCoRna8zT0REr9a6dWts2rQJrq6uKtujo6Ph5eWFL7/8Em5ubjA1NQUAcWiSt7c35s6dK6ZfuXIlQkJCEBYWhpkzZ+q0DERERESkPTpdZ56IiEpmwIABxQJ5AHB1dUWnTp2QlZWFK1euAAAEQUBkZCSkUil8fHxU0k+bNg2WlpbYsWMHBEHQSd6JiIiISPsYzBMRGRhjY2OV/01MTERaWhpcXFyKdaU3MzODq6srUlNTkZSUpPO8EhEREZF2MJgnIjIgd+7cwV9//QVra2vI5XIAEIN0BwcHtcfY29urpCMiIiIiw8cx80REBqKgoACffPIJ8vPzMWfOHBgZGQEAcnJyAEDjjPXK7cp06lhaWqJaNd2/35XJZDq/pq6xjJWD4ZTxgU6vZjj3hYio8mEwT0RkAIqKirBgwQKcO3cO7777LoYPH16u58/Ozi7X85WETCZDZmamzq+rSyxj5VAVylhWZb0vfAlARPT62M2eiEjPCYKAhQsXYu/evXB3d8eXX36pst/CwgLAs3Xm1VFuV6YjIiIiIsPHYJ6ISI8pW+R37tyJoUOHIjAwsFh3eOWY+MTERLXnUI6VV6YjIiIiIsPHYJ6ISE8VFRXh008/xa5duzB48GB8++234jj55zk4OMDGxgaxsbFQKBQq+/Ly8hAdHQ0bGxsG80RERESVCIN5IiI99HwgP2jQICxdulRtIA8AEokEHh4eUCgUCAkJUdm3du1aZGdnw8PDAxKJRBdZJyIiIiId4AR4RER6KCQkBLt27YJUKoWDgwNWr15dLI2bmxucnJwAAN7e3jh27BjCwsIQFxeHli1bIj4+HidPnoSTkxO8vb11XQQiIiIi0iIG80REeiglJQUAoFAosGbNGrVpbG1txWBeKpUiIiICwcHBOHToEKKiolCnTh14eXnB19cXUqlUZ3knIqKqpXvvojIeWbalFE8dZ+diIoDBPBGRXgoMDERgYGCpjrGwsIC/vz/8/f21lCsiIiIi0hd8rUVERERERERkYBjMExERERERERkYBvNEREREREREBobBPBEREREREZGBYTBPREREREREZGAYzBMREREREREZGAbzRERERERERAaGwTwRERERERGRgWEwT0RERERERGRgGMwTERERERERGRjjis6Avujeu6iMRz4o8zVPHee7FCIiIiIiIio9RpNEREREREREBobBPBEREREREZGBYTBPREREREREZGAYzBMREREREREZGAbzRERERERERAaGwTwRERERERGRgWEwT0RERERERGRgGMwTERERERERGRgG80REREREREQGhsE8ERERERERkYFhME9ERERERERkYIwrOgOkO917F73G0Q/KdNSp43xfREREREREVN4YaREREREREREZGLbMU6VSFXofVIUyEhERERHRy+ltMH/x4kUEBQXh/PnzKCgoQNOmTfH+++/j7bffruisERHpLdadRFTZ7NmzBzExMbh06RISEhJQUFCAgIAAjBw5slTnKSoqwubNm7Ft2zYkJSVBKpWiU6dOmDVrFhwcHLSTeSIiLdLLYP7s2bOYPHkyTExMMGTIEFhYWODw4cOYM2cOUlJSMH369IrOIhGR3mHdSUSV0YoVK5CSkgKZTAYbGxukpKSU6TyLFi3C9u3b0bRpU3h6euLBgwc4cOAATp8+ja1bt6Jp06blnHMiIu3Su2C+sLAQCxcuhEQiwaZNm9CiRQsAgI+PD8aMGYOgoCAMGjSIb1CJiJ7DupOIKqslS5bA3t4etra2CA0NxbJly0p9jjNnzmD79u1wdXXF+vXrYWpqCgAYPnw4Jk6ciC+++AI///xzeWediEir9G4g7JkzZ5CcnIyhQ4eKD6MAYG5ujg8++ACFhYXYtWtXBeaQiEj/sO4kosqqa9eusLW1fa1zREZGAgA++ugjMZAHgC5duqB79+44d+4cbt68+VrXICLSNb1rmY+KigIAdO/evdi+bt26qaQhIqJnWHcSvVrZJxDl5KGG7uzZs5BKpXBxcSm2r3v37vjzzz9x7tw5NGrUqAJyR0RUNnoXzCcmJgIA7O3ti+2ztLSETCZDUlKSjnNFRKTfKrLurAoBEsv4MoZTRqqaFAoF0tPTIZfLYWRkVGy/cviRsh4tb/xuEZG26F0wn5ubCwCwsLBQu9/c3Bz37t3TeLxMJivTdf+7UKbDDArLWDmwjKRORdWdQNX4e7GMlQPLWDXl5OQAeFYPqqPcrqxHNeEzpmYsY+VQFcr4Ol7nWUlb+OqOiIiIiIiIyMDoXTCvfDuqfIv6otzcXI0tT0REVRXrTiIi9ZR1n6aWd+V2TS33RET6Su+CeeW4JXVjO7Ozs5GZmal2TCgRUVXGupOISD2pVApra2vcvn0bT58+LbZfOVaeS3cSkaHRu2C+Q4cOAIBTp04V23f69GkAQMeOHXWaJyIifce6k4hIs44dO0KhUCA2NrbYPmW9qaxHiYgMhd4F8126dIGdnR327duHuLg4cXtubi5WrVoFY2NjjBgxogJzSESkf1h3EhEBGRkZuH79OjIyMlS2v/vuuwCA5cuXIz8/X9z+999/49SpU+jQoQOXpSMigyMRBEGo6Ey86MyZM/D29oaJiQmGDh0Kc3NzHD58GLdv38ZHH32EGTNmVHQWiYj0DutOIqqMIiMjERMTAwBISEjAf//9BxcXF3HokJubG9zc3AAAQUFBCA4Ohq+vL/z8/FTOs3DhQkRGRqJp06bo1asXHjx4gAMHDsDMzAxbt25F06ZNdVswIqLXpHdL0wFA586dsXnzZqxcuRIHDx5EQUEBmjZtig8//BDu7u4VnT0iIr3EupOIKqOYmBjs3r1bZVtsbKzYZd7W1lYM5l9m8eLFcHR0xLZt2xAREQGpVIo+ffpg1qxZbJUnIoOkly3zRERERERERKSZ3o2Z11d37tzBuXPnKjobZZaamopz587h8ePH4raioiKEhoZizJgxmDhxIk6ePFmBOXx9VaGMVL5yc3NVxk5S+WPdqf+qQhmp/LH+LB+GXkcCVaMOqQplpPKlqzqyyrbMOzk5oWnTpli1ahXs7OxemT44OBghISEqE0sZEn9/fxw9ehSnT5+GiYkJACAkJARBQUFiGmNjY2zZsgWtWrWqqGy+lqpQxvKWk5OD3377DVFRUUhKShLXKLewsIC9vT06duyIQYMGVdr1yZ2cnODh4YHFixdXdFYMBuvOylevVIUyagPrT9af6lS1OhKoGnVIVShjeWMdqZs6ssq2zAuCgKtXr2LUqFH4888/Kzo7Wnf+/Hl06dJFrICKiorw888/o3Hjxjh+/DgiIyPxxhtvYN26dRWc07KrCmUszzfD+/btg5ubGz7//HP8+uuvuHjxIpKTk5GcnIyLFy/i119/xeeffw43Nzfs27dPW0WqUIIgoIq+zywz1p2Vr16pCmUs71Y11p+sPzWpanUkUDXqkKpQRj5jli9d1ZF6OQGerrRs2RIJCQmYPn06PvroI0yZMqWis6Q16enp6NOnj/jv//77D5mZmfDz80O9evVQr149uLm5ISoqqgJz+XqqQhmXL18uvhlWWr16tcqb4XPnzr3yzfCpU6cwZ84c1KlTBx9//DF69OgBe3t7VK9eHQDw+PFjJCUl4eTJk9i4cSPmzp0LKysrdO3aVXuFK2dt2rR5ZRqJRILdu3dj79694r/Pnz+v5ZwZPtadlateqQplLK+6E2D9qcT6U7OqVEcCVaMOqQpl5DNmyelTHVllW+YBoE+fPoiIiIBMJsP333+PWbNm4cmTJxWdLa14+vSpytuhmJgYSCQSdO7cWdxWt25d3L9/vyKyVy6qQhnL683w2rVrUadOHfzyyy+YMmUKmjdvLlayAFC9enU0b94cU6dOxa5du1C7dm2sWbNGq2Urb3l5eZBIJKhdu7bG/wRBgKmpqfhvKyuris62QWDdWbnqlapQxvJsVWP9yfrzVapSHQlUjTqkKpSRz5glp091ZJVumQeAtm3bYufOnfDz88PBgwdx8+ZNhISEwNbWtqKzVq4aNGiAixcviv8+cuQIrK2t0bhxY3Fbeno6atasWeJzKhQKXLhwAYmJiSrjYBwcHNC6dWvUqFGj/ApQAlWhjOX1Zvi///7DO++8gzp16rzymjY2Nnjrrbewa9eu186/LvXs2ROnTp3CwIEDMWvWLJiamhZL07x5cwwZMgRfffVVBeTQsLHuLHu9AuhX3VIVylierWqsP59h/flyVaWOBKrG81dVKCOfMUtOn+rIKh/MA8/epP3888/44osvsGvXLowaNQrff/89unTpUtFZKzcDBgzAmjVrMHPmTJiZmSEmJgbjxo1TSXP16lW8+eabrzzXgwcP8N133+HAgQPiLI3Kt5USiQQAYGpqisGDB2POnDmoXbt2OZdGvapQxvJ6MyyRSEo1jscQx0WGhoZix44d+Oabb/DHH39gyZIlcHV1rehsVSqsO58pab0C6GfdUhXKWJ6taqw/qaSqQh0JVI3nr6pQRj5jlpw+1ZEM5v8/U1NTfP3113BycsI333yDKVOmYPbs2Zg4cWJFZ61cTJ48GadPn8bhw4cBAHK5HL6+vuL+69ev499//8W0adNeep779+/j3XffxZ07d9CkSRN069YN9vb2MDc3B/BsGYakpCScPn0au3fvxtmzZ7F9+/YSvZ17XVWhjOX1ZrhFixY4cOAApkyZgrp167407b1797B//360aNHi9TJfAUaNGoXu3bvj008/xYQJE/Dee+9h9uzZkEqlFZ21SoN1Z8nqFUB/65aqUMbybFVj/cn6szQqex0JVI3nr6pQRj5jlo7e1JFCFeXo6CgEBQWp3Xf27Fmhc+fOQvPmzYU5c+YIT548EYKCgoTmzZvrOJfl78qVK8KVK1eEwsJCle23bt0Sfv/9d+HevXsvPf7TTz8VnJychJ07d77yWjt27BCcnJyEhQsXvlaeS6syl3H58uVC8+bNBT8/P2HOnDlC8+bNha+++kolzahRo4TRo0e/9DwnT54UHB0dhS5dugirVq0SLly4IGRlZQlPnz4Vnj59KmRlZQkXLlwQQkJChC5dugjNmzcX/vzzT20WTeu2bt0quLi4CH369BFOnTolCMKzekDXn09Dx7qzbPWKIOh33SIIlbuM5VV3CgLrT9afL1dV60hBqNzPX0qVuYx8xiy7iqwjGcxrkJKSIgwfPlxo3ry5MGLECGH+/PmVprJ9Hd26dRM+/PDDEqefOXOm0K1bN+1lSAv0uYw5OTmCh4eH4OjoKDg6Ogpvv/22kJmZKe6/du2a4OjoKHz//fevPNeePXuEDh06CI6OjkLz5s3V/ufo6Ci4uroKe/bs0WKpdOf27dvC+++/LzRv3lzw9/fnw2gZsO4sO32uW8qLvpaxPOtOQWD9yfpTM9aRZaev9Ud50ucy8hnz9VRUHclu9ho0aNAAW7duxYIFC7B//37ExcVVdJb0wsOHD9GwYcMSp2/YsCH++OMPLeao/OlzGc3NzbF9+3YkJCQAAJo0aQIjIyNxv5mZGYKDg1+5tBIAuLu7o3fv3jh48CCioqKQlJSkMgGLvb09OnbsiLfeeqvUE1/pK1tbW4SHh2PTpk1YtmxZRWenUmLdqZk+1y3lRV/LWJ51J8D6k/Vn2bGO1Exf64/ypM9l5DPm66moOpLB/EuYmZlh2bJlcHJywg8//ICioqKKzlKJTZgwARKJBN988w3q1auHCRMmlOg4iUSCDRs2aNxfv379Uq2hGRUVhfr165c4fWlUhTJqIpfL1W5/8803SzxJFQDUrFkTo0ePxujRo8srawZh3LhxcHNzQ1JSEqytrSs6O5UO60719KVuqQpl1KS86k6A9Sfrz7Iz5DoSqBrPX1WhjJrwGfP16LqOrLLB/NGjR0v8Jsjb2xsdOnTAjRs3tJyr8hMVFQWJRILHjx+L/y4J5Syamrz99tsIDg7GnDlzMHv2bI0VzN27d/Hdd9/h4sWL8PPzK13mS6gqlJG0p27duq+cmIWKY92p3qvqFUB/6paqUEbSLtafmlX2OhKoGs9fVaGMpD26rCMlgmCA6wFQhcnPz8eMGTNw+vRpSCQSNGrUCPb29rCwsAAA5OTkICkpCTdv3oQgCOjevTtWr14NExOTCs55yelTGbXZgqakb+ucElVW+lS3aIu+lFEXdSfA+pOoPOlL/aFN+lRGPmNWDgzmAaSmpiI5ORnOzs6oXr06AKCoqAhhYWE4duwYqlevjokTJ6Jnz54VnNP/196Zx0VV/f//dRFRCxE3MIREcxlzwY8Kftwyl7IsFdH8aqS4palIaC7pp34fS9Pkq6AGLnxxwa2yWNSg/OS+i6biviQmKIkiLriy3d8ffBgZmBnuzNw798yc9/Px8PHozj1z7nmZPDnn3HvPYQNRFBEfH4+ffvoJp0+fLvd4mIODA1q3bo3BgwfD398fDg4OKrXUfFjJqNFoIAgCkpOT0bBhQ2g0GknfEwShwvfwWN3nVEkSEhKQkJCAdevW6T0mTIPcaTqsuEVJWMiopDsB8qe+Y6I85EjTYcEfSsNKRupjyotajqTBPICZM2di586dOHjwoHbmKyoqCt999522jKOjI77//nvJi+PwQl5eHtLT03Vm21599VU4OTmp3DL5sMeMpuxzevXqVXh4eFhtn1MliYyMRFRUlPaXUNljwjTInZZhj24piz1mJH+SP6VCjrQMe/RHWewxIznSuo7k9p350pw6dQodO3bUiraoqAgbNmxAo0aNsHr1aty5cwcjR47E6tWrERERoXJrpXHs2DGzv+vr6yu5rJOTExo3bmz2tSyBh4xKsXjxYty6dQvz5s1DQECA0bJxcXH48ssvsWTJEsyZM8dKLSRsAXKnLqZ4BVDPLTxkVBLyJyEVe3QkwEf/i4eMSkGOtC40mAdw584ddO/eXXt87tw53Lt3D5MmTUK9evVQr1499OrVy6TVJ9Vm2LBhkhYr0oepM0jPnz/Xzig6OzujatWqZl3XVHjIqBR79uzB22+/XaFkAWDgwIHYt2+fzW3/QigPuVMXc2bf1XALDxmVhPxJSMUeHQnw0f/iIaNSkCOtCw3mARQWFqL02wZ//PEHBEHAP//5T+1n7u7uyM7OVqN5ZjFx4kSzJSSFlJQUbN68GceOHcPt27d1zrm5ucHPzw+DBw82+S6OKfCQUamZYZb3OSVsB3KneajtFh4yKnlXjfxJSMUeHQnw0f/iISP1Me0DGswD8PDwwOnTp7XHO3bsQN26ddGoUSPtZ3fu3JG81QgLKLWNhSiK+Pe//42ffvoJoijCxcUFLVq00HkPJj09Hdu2bcMvv/yCDz74AF9//bUibeEho1Izw7awzynBPuRO02DFLTxkVPKuGvmTkIo9OhLgo//FQ0bqY9oHNJgH8Pbbb2PFihUICQlBlSpV8McffyAwMFCnzJUrV+Dp6alSC9lh06ZN2Lx5Mzp27IjJkyejdevWesulpqZi8eLF+Omnn9CsWbNyf58sw1JGpWaGbXGf0wcPHgAAatSooWo7iBeQO02DJbcoBSsZlbyrZmv+JHeqBznSNFjxh5KwlJH6mC+wZU/SavYongUbNWqUdva0adOmWLduHVxdXQEAV69exXvvvYdx48Zh8uTJKrZUHk6cOIELFy7g0aNHcHZ2hkajQbt27SR9t1+/fhAEAfHx8ahUqZLRsgUFBRg4cCCKioqwbds2OZouGR4yWgJL+5wCQE5ODi5duoRGjRrB3d1d59zp06fx//7f/8OlS5cAAK+99hpmz56N9u3bm3wdWo1ZXsid0r0C2IZbeMhoKSz501ruBMif5sCbIwE++l88ZLQElhwJ2H8fk+7Mo3ixic2bN+Py5csAiv9Hlv4Bq1KlCiIjI21+25DU1FTMmDED169fB1D8qE/JjFyDBg0wf/58/OMf/zBax/Xr1zF8+PAKBQQUb7fStWtXrF+/3vLGS4SHjHLg5OSEmJgYnX1O09LSdMo4ODjAx8fHKnu5btq0CVFRUdi6dauOaO/cuYMxY8bg4cOHcHJygqOjI/788098/PHH2LJli0nvZBHyQ+6U7hWAbbfwkFEuWPInuZNteHEkwEf/i4eMcsCSIwH79yQN5kvRtGlTvZ97enra/CNQV69exYgRI/D06VN06dIFfn5+qFu3LrKzs5GSkoL9+/dj9OjR2Lx5s9EtMl566aVyC3UY4/bt23jppZfkiFAhPGQsjaV30ARBwMCBAzFw4EDV9zk9fvw4GjZsiCZNmuh8vm7dOjx8+BC9e/dGWFgYnJycEBsbi2+//RaxsbH48ssvrdI+wjjkzoq9ArDrFh4ylsZSdwLs+JPcaRvYsyMBPvpfPGQsDfUxbciTImFVcnNzxefPn1v9uqGhoWKLFi3EAwcO6D1/8OBBsUWLFmJoaKjRekJCQsSWLVuK+/btq/Cae/fuFVu2bCl++umn5jTZZHjIKIqieOrUKbF3796iRqMRNRqN2KxZM+1/9+7dWzxx4oTV2iIX3bt3FydPnlzu8/fee098/fXXxezsbJ3PBwwYIPbp08fk63z33XeiRqMxeEywi627UxTZdQsPGUWR3CmK5rtTFMmftoCte5Jlf/CQURTJk6Joe31MLu/MDx8+HIIgYMGCBahXrx6GDx8u6XuCICA2Ntaia/v6+iq6MqUhjh49it69e6Nz5856z3fq1Am9e/fG4cOHjdYzZcoUHDx4EGPHjsU///lPdOrUCd7e3jqrcP711184ePAgjh49iurVq1vtPTAeMsp5B60sau5zmpOTg/r16+t89uTJE1y9ehWtWrVC7dq1dc61adMGCQkJVmsfUQy5szxSvQKw6xYeMirpTkA9f5I72UJNRwK270lW/QHwkZH6mMXYmie5HMynpKRAEAQ8ffpUeywFOVZ8FEVRZ89Ra5Gbm1vho1yenp7aHzRDNGjQAD/88ANmz56Nw4cP4/Dhw+X+Xkry+fr6Yvbs2WjQoIFljZcIDxkjIyORn5+PVatWlfuF8vHHH+PQoUMYO3YsoqKiEBERUWF9LOxzWsKTJ090ji9cuABRFNGyZctyZatXr47CwkKTr9GrVy8doZc9JoxD7tSPFK8A7LqFh4xyuxNgx5/WcCdA/pSCmo4EbN+TrPoD4CMj9TGLsbU+JpeD+YsXLxo9NhcfH58KywiCgISEBGzdulV7fOrUKVmubww3N7cKr5Oamgo3N7cK62rcuDE2bNiAv/76CykpKfjrr7/w6NEjAMWzbd7e3vDz84O3t7cMLZcODxnlmhkWGdrnFCj+BXjy5Emdz0o6Rfp+rnJyclCnTh2Tr6PRaKDRaAweE8Yhd+pHqlcANt3CQ0Y5nz5gyZ/WcidA/pSCUo4E+PEki/4A+MhIfcxibK2PyeVgXimeP3+OqlWrolatWgbLZGZmwsnJSbstibXo2bMn1q9fj8WLF2P8+PGoUqWK9tzz58+xcuVKHD16FMOGDZNcp7e3t9VFYwweMso1M8zSPqcA8Oabb2LVqlVYsWIFPvroI1y/fh0bN25E5cqV0a1bN73tsodFg4hieHMnwJZbeMgo59MHLPmT3MkPvHmSJX8AfGSkPuaLdtmSJ2mfeRkZO3YsDhw4gKCgIEyePFnvKo0ajQYffPAB5syZY9W23b9/H4MHD0ZGRgZcXV3RunVr1K5dG3fv3sWZM2eQk5MDLy8v/PTTT1b/JSAXPGTs2bMnPD09jb5bN2LECGRkZGDnzp0Gy7C2z+n9+/fh7++PrKws7WeiKGLkyJGYMWOGTtm0tDT06dMHISEhmDBhgqT6Hz9+jAcPHsDNzQ2Oji/mMJOTk7Fz505Uq1YNgYGBaN68uTyBCJMgd6oLDxnlcifAlj+VdidA/mQF8qS68JCR+pi22cfk8s78sWPHzP6usfc6oqOj8fPPP2PBggXYvXs35s6di/bt25t9LTlxdXXF5s2bERYWhuTkZOzdu1d7rkqVKggICMDUqVNlF9C1a9eQnZ1tlfdhrJExNzcXZ86cwdOnT1G/fn2rP2Io18wwa/ucurq64scff8SSJUuQmpqKGjVq4J133tGbY+/evdBoNOjRo4fk+hcuXIjExEQcPHhQK9pNmzZhzpw52nfTkpKSEBcXh0aNGskTyg4hd1rPnYD1/GmtjGr6U867aiz5U2l3AuRPU1DKkQB5Uh/Ux5QX6mPaZh+TyzvzGo3G7MVGLly4UGGZW7du4V//+hcOHz6MoUOH4rPPPtPuEanWrGlp8vPzkZaWpt07slGjRqhcubIi15o5cyYSExMl/b3JiSUZk5OT0bRp03IrdUZERGDNmjXIz8/Xfta4cWP87//+r9WEK9fMcMeOHfHGG29gwYIFkq47ffp07N+/X9L7pCzSt29feHl5YdmyZdrP3nzzTQDFEs7OzsaMGTPw/vvv45tvvlGplexD7rSeOwF1/GlpRlb9KeddNfIn+dMQSjsSIE+WhvqY8kJ9TPNQ25Fc3pmfOHGibCuH6qNevXpYtWoVfvzxR4SFhWH37t2YM2eOwQUlrE3lypXRrFkztZuhKJZknDJlCoKDgxEcHKz9bMGCBVizZg1cXV3RrVs31KxZE6mpqTh58iRGjBiBLVu2wN3dXa7mG0SumWE/Pz8kJyfj/fffR9euXY2W3bdvH3799Vf07NlTjgh66dmzJ4KCgiRv42Mqt2/fRqdOnbTHly5dwq1btzBt2jTtnY3t27dbdFeFB8id5M6KYNWfct5VY8mfSrsTIH+agtKOBMiTLEB9TFej9bDkSMD++5hcDuYnTZpklev8z//8D7p06YJ//etfGDNmDAYMGGCV61bEiRMncOHCBe2MYvPmzdG2bVtJ383MzDTpWo8fPzaniRZjScayZGVlYf369WjcuDHWrl2rs8LlmjVrtBL+/PPP5Wq+UVxdXTFv3jx89dVXZs8Ms7bP6c2bN/Hw4UPF6n/27JnO380ff/wBQRB0Oj9eXl7YtWuXYm2wB8idlnnFFvwppzsBtvwphzsBtvyptDsB8qcpWMuRgH160hYcCVAfsyJYciRg/31MLgfz1qR+/fpYu3YtNm7ciEWLFqnalmPHjuGLL75Aeno6gOLFH0pmkBs0aCDp/asePXooPutsCXJkLMvhw4dRWFiIqVOnltuqYuTIkdi2bRv27dtnNdGWYMnMMMv7nCpBvXr1cOnSJe3x3r174eLiovP3d//+fe2jioT62Js7Abb9qYQ7ATb9aemdQ/In+ZMV7M2TLDsSoD6mVMiR1nUkDebLUHa2TaPRoF27dhbXGxgYiF69euH69euoW7euDC01jZMnT2LUqFEoKChAt27d0K5dO9SpUwfZ2dk4fvw49u3bh1GjRmHdunVo06aNwXoEQUCNGjXQsmVLSde9fPky7ty5I1MK48iVsSy3b98GYHiP1zZt2iA+Pl6OCCZh6cwwq/ucKkHXrl2xadMmLFiwAFWqVMH+/fvRv39/nV8uaWlpeOWVV1RspW1D7qzYK6z6Uyl3Amz6U467auRP8qepKOVIwH48yaojAepjUh/TMGo7kgbz/yU1NRUzZszA9evXAZSfbZs/fz7+8Y9/WHQNd3d3q7zzoo/w8HAIgoD169eXmzX8+OOPkZKSgtGjRyM8PBzr1q0zWI+3tzfy8vIQExMj6boli5NYA7kylqV69eoAoLOqZ2kMfa4Ucs8Ms7bPqRKMGzcOu3fvxpo1awAAderU0XkcMjMzEydOnDB5H22C3GmKV1j1p1LuBNjypxJ31cif5M+KsIYjAfvwJKuOBKiPCVAf0xBqO5IG8wCuXr2KESNG4OnTp+jSpQv8/PxQt25dZGdnIyUlBfv378fo0aOxefPmcqtP2gpnz55Fnz59DP4A+vn5oU+fPvjPf/5jtJ7XX38dycnJePjwIVxcXJRoqtnIlREAdu7ciZs3bwJ4MWuakZGh95GjW7duoWbNmha0XDpK3kFTm4SEBKSkpEguLwiC0b1QS1O3bl0kJSVpV0r19fXVvrsFFL93N2PGDHTp0sW0RnMOudM0r7DqTzkzAmz6k9z5AlPcCZA/LYEHRwLUxwSoj8k69tzHpME8gMjISOTn52PVqlXlVgP9+OOPcejQIYwdOxZRUVGIiIgwqe6EhAQkJCRoZ+nKHlsLJyenCmds3d3d4eTkZLRMixYtkJSUhHPnzqFjx44VXtfV1dVqj97JlREo3iKm7FYnv//+eznRFhQU4NixY3j99ddNb7AZKHkHzRjW2Mv15s2b2l9uUjD1vbqqVauie/fues81adIETZo0Mak+gtxZglSvsOpPOTMCbPpTLXcCyvtTaXcC5E9zUdKRgP15klVHAtTHpD6mcdR0JA3mARw9ehS9e/c2uK1Hp06d0Lt3b7P2P7x586bOVgRlj61Fx44dceTIEaNljhw5orO1gj4+/PBD9O7dW/Is4YwZMzBjxgzJ7bQEuTLu3LlT7+fVqlUr99n58+fRsGFDvP3229IbagFy30GTSnR0tOJ7uSq9vRIhP+TOYqR4BWDXn3JmZNWfarkTUN6f5E52UdKRgP15klVHAtTHBKiPySo0mAeQm5sLT09Po2U8PT2Rm5trpRbJz+eff46hQ4di5syZCA0N1ZldzMrKQkREBLKzs7F06VKj9VStWhX169dXurlmIVdGU/K1bt0a69evN7vNpiL3HTSWqF69uqL/tv78809s2LABZ86cQW5uLgoLC8uVEQQBO3bsUKwN9ga5U7pXAHb9KWdGVv1J7rQM8qd58OBIgPqY1MdkH3vuY9JgHoCbmxtOnTpltExqairc3Nys0yAFmD59OmrUqIHExERs27YNHh4eqFWrFnJycpCZmYnCwkI0a9YM06dP1/meqe/WqQkPGeWaGbaVvVzlIiUlBWPGjEFeXh4cHR1Ru3ZtVKpUqVy5kq1SCGmQO+3DKzxklPPpA/In+VMqPDgS4MMhPGSkPqZ5qO1IGswD6NmzJ9avX4/Fixdj/PjxOitHPn/+HCtXrsTRo0dteqXW0os+FBQUID09XbtSZQkXL14s9z2W9/ssCw8Z5ZoZZn0vV7lZtGgRCgsLMXfuXAwYMECvZAnTIXcWY+te4SGjnE8fkD/Jn1LhwZEAHw7hISP1Mc1DbUfSYB7AhAkTsGfPHqxcuRI//vgjWrdujdq1a+Pu3bs4c+YMcnJy4OXlhQkTJqjdVLPRJxi5YGUBFh4yyjUzzPJerkpw8eJF9OnTB4MGDVK7KXYFudNyWHALDxnlvKtG/iSkwoMjAT76XzxkpD6meajtSBrMo3g1zM2bNyMsLAzJycnYu3ev9lyVKlUQEBCAqVOnwtXVVb1GMgwrC7AoCSsZ5ZoZZm0v1507dyq6Dc3LL7+M2rVrK1Y/r5A7LYcVtygJCxnlvKvGkj+VdidA/rQEcqTlsOAPpWElI/UxzUNtR9Jg/r+4urpi3rx5+Oqrr5CWloZHjx7B2dkZjRo1QuXKldVunuw8efJEm/Gll15SuzmKYI8Z5ZoZZm0vV0EQkJuba3ARIAcHBzg7O+vs22kK3bp1w/Hjxy1pImEAcqf9YY8Z5byrxpI/lXYnQP60FN4cCdinQ8pijxmpj2mbfUwazJehcuXK5fZ5tBdK9jpNSEjQmWnz8vJCQEAARo0aZZMrVJaGh4xywNperlLfr3rllVcwYMAAjBs3zqT/j9OmTcPQoUMxd+5cfPbZZ3q3gCEsg9xp217hIaNcsORPpd0JkD/lwp4dCfDhEB4yygFLjgTsv49Jg/kynDhxAhcuXNDOtjVv3hxt27ZVu1kW8+zZM4wcORKnTp1CpUqV4O3tjTp16uDu3btIT0/HkiVLsGfPHqxduxZVq1ZVu7lmwUPGspg7M8zaXq6+vr5Gz4uiiHv37uH69etYtmwZDh8+jNjYWMl3NUJDQ/HSSy9h48aNiI+Ph7e3t94ZWFtadZY1yJ226xUeMpbFkrtqLPlTaXcC5E+5sFdHAnw4hIeMZaE+pm30MWkw/1+OHTuGL774QjvTJoqidhanQYMGmDt3Ltq3b69mEy0iJiYGJ0+exPvvv4+pU6eiXr162nNZWVlYtGgRtm7dipiYGAQHB6vYUvPhISMgz8wwa3u5St1H9f79+1iwYAESExOxadMmBAUFSfpe6ffAnjx5gvPnz+stx9Pqq3JB7rR9r/CQEZDvrhpL/lTanQD501Ls3ZEAHw7hISNAfUxb7GPSYB7AyZMnMWrUKBQUFKBbt25o164d6tSpg+zsbBw/fhz79u3DqFGjsG7dOrRp00bt5ppFUlISWrZsiYULF5Y75+7ujrCwMKSlpSEpKclmJcRDRh5nhktT8u5hamoqkpOTJYtW6dW6eYXcaR9e4SEjudM8dwLkT0vgwZEAHw7hISN50jb7mDSYBxAeHg5BELB+/fpys6Mff/wxUlJSMHr0aISHh5u8TUSvXr10ZqfKHluLmzdvYsSIEUbLdOzY0aYfkeMhIy8zw8YQBAGdOnXCli1b1G4K95A7i7F1r/CQkdxJ7lQDJR0JkCetCQ8ZyZO26UkHtRvAAmfPnkWfPn0MPubk5+eHPn364MyZMybXrdFoMGDAAIPH1qJatWrIyckxWiYnJ8emF7bhIWPpmeHSkgVezAy3bNkSSUlJJtedkJCA4cOHGzxmCWdnZzx9+lTtZnAPubMYW/cKDxmVdCdgO/4kd1oXJR0JkCetCQ8ZqY9ZjK15ku7MA3BycoK7u7vRMu7u7ja9QqWPjw+SkpIQFBSEJk2alDv/559/Ijk5GX5+fiq0Th54yKjkzDAr+5xKITMz0+jCKiX7lfbq1QvOzs4m7V/q7+9vWeM4gtxpH17hIaPSd9VsxZ8VuRMgf8oJD44E+HAIDxmpj1mMrfUxaTCP4n+YR44cMVrmyJEj6NSpk+Q6Hz9+jAcPHsDNzQ2Oji/+mpOTk7Fz505Uq1YNgYGBaN68udntNoVPPvkEhw4dwqBBgzBo0CD4+vpq39tKSUlBfHw8CgoKMHbsWKu0Rwl4yMjDzHBFZGVlYefOnUZ/Hj///HMIggAfHx84Oztrj41RsigRdUalQ+60D6/wkJHcKc2dAPlTTpRwJECeVAMeMpInbbOPSYN5FP9PGTp0KGbOnInQ0FCdWdSsrCxEREQgOzsbS5culVznwoULkZiYiIMHD2pFu2nTJsyZMweiKAIofpwlLi4OjRo1kjeQHtq2bYtFixbhiy++wMaNG7Fp0ybtOVEUUb16dXz77bdo166d4m1RCh4y2uvMcGZmptHzRUVFuH//Pk6dOoVVq1bh6dOnGDZsmMHy8+bNgyAIqFu3LgBg/vz5sraXKIbcaR9e4SEjuVOaOwHyp5wo4UiAPKkGPGQkT9pmH5MG8wCmT5+OGjVqIDExEdu2bYOHhwdq1aqFnJwcZGZmorCwEM2aNcP06dN1vmdsv8Djx4+jY8eOOvsyRkdHw93dHQsXLkR2djZmzJiBVatW4ZtvvlE0Xwm9e/dGly5dsGPHjnJ7nfbs2VPvnohSYGUBFsD+M9rrzHCPHj0kbdkhiiIcHBwwffp0o79MAgICdI7VeIeQB8idlnkFYMct9p6R3CnNnQD5U06UcCTAlydZ8EcJ9p6RPGmbfUxBLJnC4xiNRmPW9wRBwIULF/Se69ChA/z9/TFz5kwAwKVLl9C/f39MmzYNo0ePBgBMnjwZ586dw3/+8x/zGm4CkZGR8PLyQv/+/RW/llrwkBEAtm/fji+++AK5ubk6ciqZGZ4zZw7eeecdk+uNjIxEVFSU9t902WMlqehOkYODA6pXr46mTZuiX79+8Pb2VrxNRMWQO+0DHjICyrkTUM+f5E62UcKRAHlSDXjICFAf0xY9SXfmocz+gM+ePUPlypW1x3/88QcEQUDnzp21n3l5eWHXrl2yX1sfK1asMGlfWVuEh4yAsnfQ1GL9+vVqN4EwA3KnfcBDRoDcSVgfpfafJk9aHx4yAuRJW4QG8wpRr149XLp0SXu8d+9euLi4oFmzZtrP7t+/r/OIlJJ4eHjgwYMHstbJ2gIsPGQsPTNc8oeQxt9//43ly5fj0KFDuH37NvLz88uVEQQB58+fV6F1RAk8uBNgyy08ZCR3Wgb5ky148CRL/gD4yEieNB81HUmDeT08efJEOxNlrgi7du2KTZs2YcGCBahSpQr279+P/v376zyykpaWhldeeUWuZhvlvffeQ0JCAnJzc1G9enVZ6mRtARYeMtrrzPDs2bNN/o4gCPj3v/8tqWxGRgY++OADPHz4EI0bN0ZeXh48PDxQpUoVZGRkoKCgABqNRrZ/N7xC7pQOS27hISO58wWmuBMgf8qJHI4E+PAkS/4A+MhInnyBLfUxaTD/X/Lz87Fq1SokJCQgPT1d+7mXlxcCAgIwatQok/YBHTduHHbv3o01a9YAAOrUqYNJkyZpz2dmZuLEiRMVvschF+PHj8f58+cRFBSEkJAQtGrVCrVr17aoTtYWYOEho1J30NTmhx9+kFy2dGdFqmgjIyPx6NEjrF27Fn5+ftBoNAgICEBwcDCysrIwe/ZspKWlYfXq1Sa3nXfInebBklt4yEjuNM+dAPnTUuR2JMCHJ1nyB8BHRvKkbfYxaTCP4nePRo4ciVOnTqFSpUrw9vZGnTp1cPfuXaSnp2PJkiXYs2cP1q5di6pVq0qqs27dukhKSsLhw4cBAL6+vjrvmTx+/BgzZsxAly5dFMlUFh8fHwDFC1iMHz/eYDlTHgG5ffu2zj6Mly5dwq1btzBt2jS0b98eQPFCGseOHbOg5dLhIaNSd9DUZt26dZLKZWZmYtmyZUhPT5e0MmkJhw4dwhtvvKF3dVJ3d3csWbIEffv2xeLFi/H1119Lrpd3yJ0vMPXxOZbcwkNGcqd57gTIn5aghCMBPjzJkj8APjKSJ22zj0mDeQAxMTE4efIk3n//fUydOhX16tXTnsvKysKiRYuwdetWxMTEIDg4WHK9VatWRffu3fWea9Kkid49HJWiRApywtoCLDxkVOoOmtpUtFXSgwcPsGLFCmzatAnPnz9HmzZtMHXqVMn137t3T+cRNUdHRzx9+lR77OTkhE6dOmHHjh2mN55jyJ3mw5JbeMhI7jTPnQD50xKUciRg/55kyR8AHxnJk7bZx6TBPIrfR2nZsiUWLlxY7py7uzvCwsKQlpaGpKQkk2XLCkqs5MjaAiw8ZFTqDhrAzj6npXn+/DliY2MRExODhw8folGjRpgyZQp69eplUj01a9bUEaurqytu3rypU6ZSpUrIzc2Vpd28QO40H5bcwkNGJd0JsOdPudwJkD8tgQdHAnz0v3jISH1M2+xj0mAewM2bNzFixAijZTp27IjY2FiT6v3zzz+xYcMGnDlzBrm5uSgsLCxXRhAEm53NZm0BFiVgLaNSd9CA4v1wS++JW/bYmoiiiJ9//hmRkZHIysqCm5sbpk2bhoEDB8LBwcHk+ry9vXXeVWzdujUOHDiAjIwMeHl5IScnB9u3b4eXl5ecMewecqf5sOYWJWApo5LuBNjxp9zuBMiflqCUIwH79yRL/lAK1jJSH9M2+5g0mAdQrVo15OTkGC2Tk5ODatWqSa4zJSUFY8aMQV5eHhwdHVG7dm1UqlSpXLmS1SqVpnnz5ggODsbEiRMNlomOjkZERAQuXLggqU7WFmDhIaO975UJADt27EB4eDiuXbsGZ2dnTJkyBUFBQahSpYrZdXbt2hWRkZF4+PAhXFxcEBQUhN27d6Nfv35o1KgR0tPT8ejRI53/t0TFkDuLMdUrAFtu4SEjudN8yJ/mo4QjAT48yZI/AD4ykifNQ21H0mAexY+VJCUlISgoSO87Rn/++SeSk5MrfOeiNIsWLUJhYSHmzp2LAQMG6JWsNRFFUXaps7YACw8ZlYCVfU6PHz+OhQsXIjU1FZUrV8aIESPwySefoEaNGhbX/eGHH6JDhw7aGdcOHTogPDwckZGRuHLlCjw8PBAaGorBgwdbfC2eIHeaD0tu4SGjUrDgTyXdCZA/LUEJRwJ8eJI1f/CQUQlYcCRg331MGswD+OSTT3Do0CEMGjQIgwYNgq+vL+rUqYPs7GykpKQgPj4eBQUFGDt2rOQ6L168iD59+mDQoEEKtlxe7t27Z9JqqgBbC7BIwdYzKjEzzMI+p5988gn27t0LBwcH+Pv749NPP9VZKMhSnJ2dte+ClfDuu+/i3Xffle0aPELuLMYcrwBsuaUibD2jUk8fqO1Ppd0JkD8tQQlHAvx4khV/SMXWM1If0zzUdiQN5gG0bdsWixYtwhdffIGNGzdi06ZN2nOiKKJ69er49ttv0a5dO8l1vvzyy6qvAJmYmKhzfPHixXKfAUBhYSFu3bqF+Ph45sRYETxkLI0SM8Ms7HO6Z88eCIKAV155BdnZ2fjyyy8r/I4gCIiOjlakPYQ0yJ226xUeMpZGqacP1PYnuZNtlHAkQJ60FjxkLA31MV9gS56kwfx/6d27N7p06YIdO3bgwoULePToEZydndG8eXP07NlT57EXKXTr1g3Hjx9XqLXS+Pzzz7WLaAiCgJ07d2Lnzp3lypX84FatWtXk1VTVXoCFh4ymYurMMCv7nIqiiBs3buDGjRuSypu6VzIAFBQU4Nq1a3j48CGKior0lvH19TW5Xp4hd5rnFUBdt/CQ0VTMuavGgj+t4U6A/GkucjsS4MeTavuDh4ymQn1Mw6jlSBrMA4iMjISXlxf69++v/WMp06ZNw9ChQzF37lx89tlnJi9uIgfz588HUPwPeNasWejVqxd69uxZrpyDgwNcXV3Rpk0bk94dYWEBFh4yKj0zzMI+p/p+OcqJKIpYsmQJNmzYgMePHxsta8ojtrxD7jTPK4D6buEhozXuqqntT6XdCZA/LUEJRwJ8eFJtfwB8ZKQ+puWo7UgazANYsWIFgoKCZK0zNDQUL730EjZu3Ij4+Hh4e3vrnX0VBMGsLUmkMGDAAO1/Hzt2zKCEzIWFBVh4yKj0zDAL+5wqvddoVFQUVqxYARcXF/j7+8Pd3V1nIRbCPMid5qO2W3jIaI27amr70xr7NJM/zUcJRwJ8eFJtfwB8ZKQ+puWo7UiyMQAPDw88ePBA1jpTUlK0//3kyROcP39ebzlzH3czlZLZRTlhbQEWe82o9Mwwa/ucKkF8fDw8PDwQFxeHmjVrqt0cu4HcaT4suKUEe81ojacPyJ+EMZRwJMCHJ9X2R1nsNSP1MS1HbUfSYB7Ae++9h4SEBOTm5qJ69eqy1Hnx4kVZ6pGb33//Hb/88gvS0tLw7Nkz/P777wCAq1evYteuXejXrx/c3d0l1cXCAiz6sLeMSs8Ms7bPqRJkZ2djyJAh1BGVGXKneV4B2HBLWewtozWePiB/EsZQwpEAH55U2x+GsLeM1Me0HLUdSYN5AOPHj8f58+cRFBSEkJAQtGrVSvUfLrkpKirClClTsH37dgDFj8k8e/ZMe75GjRpYvHgxioqKMG7cOEl1srAAS2l4yKjEzDAP+5x6enri0aNHajfD7iB3mucVgC238JBRqacPyJ+EMXhwJMBH/4uHjNTHNA+1HSmISq6qYCM0b94cQPEjJsYeSRIEweCjTKyzevVqhIWFYciQIZg6dSrWrFmDZcuW6SzEMHz4cOTn5+P777+XVGdOTg6GDh2Krl27qrYAS2l4yFiC3HfQ7J2NGzciKioK27Zts8uOlFqQO4sx1SsAW27hIWMJ5E7TIX+aDw+OBPjof/GQsQTypGmo7Ui6Mw9ot0awhJKVH3v16gVnZ2e9K0Eawt/f3+LrV0RCQgJatmyJ2bNnA9D/HlWDBg2wZ88eyXWysABLaXjIqNQdNHsjMzNT57h79+5ISUnBkCFDMHHiRDRv3tzgI48eHh7WaKJdQO4sxlSvAGy5hYeM5E7pkD/lQw5HAnx6kiV/AHxkJE9KgzVH0mAewPr16y2uo2Q1SB8fHzg7O+usDmmIkplaa4j2+vXrCAwMNFrG1dUV9+/fl1wnawuw8JBx7dq1+O2338rNDJdQp04dtGvXDnv27DFJtLa2z2lF9OjRQ+//E1EUMXPmTIPfs/W7I9aG3FmMqV4B2HILDxmVcidA/iyB/FkeORwJ8OlJlvwB8JGR+pjSYM2RNJiXiXnz5kEQBNStWxeAcu/nmUvVqlUrfJ8jMzMTLi4ukutkbQEWHjIqMTPMwj6ncuPv72+1X36EZfDoToAtt/CQUamnD8ifhDXg0ZMs+QPgIyP1MaXBmiNpMI/id5qCg4MxceJEg2Wio6MRERGh825MaQICAnSOS68OyQLNmzfHgQMHkJeXBycnp3Ln79+/j/3798v2SJga8JBRiZlhFvY5lZtvv/1W7SZwAbnTPrzCQ0alnj4gfxLGkMORAHmSBXjISH1MabDmSAe1G8ACoija1IyQOQwbNgx///03QkJCkJWVpXMuPT0dwcHByM3NtemtIXjIqNTMcMk+p/Yg2dIsX74c4eHhyM/PN1gmLy8PERERiI6OtmLL7ANyp314hYeMSj59QP4kfxqCB0cCfDiEh4zUxzQNVhxJd+Ylcu/ePVStWlXtZphNr169MHbsWERHR+PNN9/UrpjZsWNH3L9/H6IoYsKECejYsaPBOlhfgIWHjErMDLOwz6kSHDp0CEuXLsW0adNQuXJlg+WcnJzg6uqKsLAwtGrVyui/D8J0yJ3FsOwWHjIqdVeN/En+tBRbdyTAR/+Lh4zUx5QOS47kdjBf9gfo4sWLen+oCgsLcevWLcTHx6NJkyYmXePvv//G8uXLcejQIdy+fVvvzI01F4yZMmUKOnTogA0bNuD06dPIy8tDUVERunbtimHDhqFr165Gv8/6AiyA/WccNmwYgoODERISgq+++krnXHp6OmbNmmXyzDBr+5zKRWJiIlxcXPDRRx9VWDYwMBArV65EfHw8dUYrgNxpulcA9t1i7xmVcCdA/gTIn2WxhiMB+/Mky/4owd4zUh9TOiw5ktt95jUajaTFC0r+eqpWrYqlS5fijTfekFR/RkYGPvjgAzx8+BCNGzfG5cuX4eHhgSpVqiAjIwMFBQXQaDSoXr26bKudKk18fDwEQcBbb70FZ2dnJCQkSP4ua+93GcIWMoaHhyM6OhqCIKBatWp4+vSp9h2mkpnhkJAQyfWxus+ppbz11lto2bIlIiIiJJWfMmUKTp8+bTOrqaoFudM8bMEtlsJ6RrndCZA/SyB/vkBpRwL26UnW/SEHtpCR+pjSYMmR3A7mS36ARFHErFmz0KtXL/Ts2bNcOQcHB7i6uqJNmzaoUaOG5PpnzJiBpKQkrF69Gn5+ftBoNAgODkZwcDCysrIwe/ZspKWl4fvvv0etWrVky0XwwcGDB7Uzww8ePMDLL78MHx8fyXfQSjN8+HDk5ubi4sWLqFatmur7nMqFj48PgoKCMGXKFEnlw8PDERsbi9TUVIVbZtuQOwlbRk53AuTPEsifL1DakQB5klAW6mNWDEuO5PYx+9IzXMeOHTMoW3M5dOgQ3njjDfj5+ZU75+7ujiVLlqBv375YvHgxvv76a9muS/BB586d0blzZ1nqYm2fU7lwcHAwuihJWfLz8+HgQGuCVgS5k7Bl5HQnQP4sgfz5AqUdCZAnCWWhPmbFsORIbgfzpVFiv8579+6hUaNG2mNHR0c8ffpUe+zk5IROnTop+kiaj4+Pyd8RBAGnTp2SvzEKwUNGpWFtn1O5cHNzw5UrVySXv3LlCtzc3BRskf1B7nyBrXmFh4zWgPxZDPlTP0rtB0+etA48ZFQacmQxSjqSBvOl+P333/HLL78gLS0Nz549w++//w4AuHr1Knbt2oV+/frB3d1dUl01a9bUEaurqytu3rypU6ZSpUrIzc2VL0AZnj9/DkdHR0V/waq9AAsPGQnzaNeuHbZu3YobN27A09PTaNkbN27gyJEjVltEx94gd5qHmm7hISNhPuRPeZHTkQA/nlTbHzxkJMyDJUfSYB5AUVERpkyZgu3btwMoXozk2bNn2vM1atTA4sWLUVRUhHHjxkmq09vbG+np6drj1q1b48CBA8jIyICXlxdycnKwfft2eHl5yRumFI6OjigoKICLiwsCAgLQr18/uLq6ylZ/2QVY8vLyDC7AohQ8ZKSZYfMIDAxEfHw8QkJCEBMTY/C9wXv37uHTTz9FYWEhhg4dauVW2jbkTvNR2y08ZCR3mg/5Ux6UcCTAhyfV9gfAR0bypHmw5EhuF8ArzerVqxEWFoYhQ4Zg6tSpWLNmDZYtW4YLFy5oywwfPhz5+fn4/vvvJdUZHR2NyMhIHDhwAC4uLjh69ChGjBiBqlWrolGjRkhPT8ejR4/w1VdfYfDgwYrkun//PhITE5GQkIBLly7ByckJPXr0wMCBA9GlSxeL309hYQEWHjJqNBqzZoZ37dql93PW9zmVk/nz5yM2NhY1a9bEkCFD0KFDB9SrVw8AkJWVhcOHD2Pz5s3IycnByJEjMWPGDJVbbFuQO81HbbfwkFFudwLkT/KnaSjhSIAPT6rtD4CPjNTHNB9WHEmDeQB9+/ZFlSpV8PPPPwMAIiMjERUVpSPbL7/8Env27MH+/fsl1fno0SNcvXoVr732mnbVxl9//RWRkZHIyMiAh4cHhg0bhsDAQPkD6eHMmTOIi4tDcnIycnNz4ebmBn9/fwwcOBCvvvqqWXV27doVrVq1wrJlywBAR0IAkJeXh759+6JDhw5WWYDFXjO2bNlSOzsrx8xwybY5ycnJaNiwoaRtdEr2OS39M2ELiKKIiIgIrFq1CkVFRXrPV6pUCWPGjEFoaKjNLcCiNuRO87wCsOGWEuw1o9zuBMifZc+TP42jhCMBPjyptj/KYq8ZqY9pPqw4kh6zB3D9+vUKhVeyx6JUnJ2dyz268u677+Ldd981p4kW06pVK7Rq1QqzZs3Cb7/9hri4OERHRyM6Ohrt27fH119/jYYNG5pUJwsLsJTGXjMeOHBAOzM8b948LFy40KKZ4Xnz5kEQBNStWxeAcgv0sIAgCJgyZQoGDRqEuLg4nDx5EtnZ2QCAOnXqoG3btggICLBowMIz5E7zvAKw4ZYS7DWj3O4EyJ/kT9NQwpEAH55U2x9lsdeM1Mc0H1YcSYN5FL/D9OjRI6NlMjMz4eLiYqUWKYeTkxP69euHfv364eTJkwgNDcXx48eRlpZmsoRYWIBFH/aW0dXVFSNGjMCIESN0Zoa3b99u1sxwQECAznHpbXTslVdffRWTJ09Wuxl2B7nTPK8AbLilLPaWUW53AuRPwjR4ciRgf/0vfdhbRupjWo7ajqTBPIDmzZvjwIEDyMvLg5OTU7nz9+/fx/79+9G+fXuT6y4oKMC1a9fw8OFDvY9gAICvr6/J9ZpLYWEhdu3ahbi4OBw4cAAFBQVo0aIFvL29Ta6LhQVY9GHPGZW6g0YQ5kDuNM8rAHtuAew7I7mTUAMlHQnYtydZ8kdp7DkjedI2ocE8gGHDhiE4OBghISH46quvdM6lp6dj1qxZyM3NxbBhwyTXKYoilixZgg0bNuDx48dGy1rjHZHLly8jPj4eW7duRU5ODmrWrIkPP/wQgwYNQtOmTc2qs2vXroiMjMTDhw/h4uKCoKAg7N69G/369dNZgGXSpEkyp9EPDxlLkPsOGkGYA7nTPK8AbLmFh4wlkDsJa6KEIwE+PMmaP3jIWAJ50ragBfD+S3h4OKKjoyEIAqpVq4anT59q32MSRRETJkxASEiI5PoiIyMRGRkJFxcX9OzZE+7u7nB01D93UrLQhdw8evQI27ZtQ1xcHM6dOwcHBwd06dIFAwcORI8ePQy2x5T61V6AhYeM+jA0MxwWFobXXnvN5Ppon1PCXMid5l9DTbfwkFEfcrsTIH8SxpHbkQAfnmTBHzxk1Af1MW0LGsyX4uDBg9iwYQNOnz6NBw8e4OWXX4aPjw+GDRuGrl27mlRXjx49AABxcXGoWbOmEs2tEB8fH+Tl5cHb2xsDBgzAgAEDtAtS2As8ZCyNvpnhvn37WjQzXHaf08uXLxvc53T9+vUyJyLsAXKn7cFDxtIo4U6A/ElIQ05HAuRJa8FDxtJQH9M2ocG8QrRu3RpDhgzBrFmzVGtDyd6RpizuIwgCkpKSFGyVvPCQUemZYRb2OSWIEsid1oGHjNZ4+oD8SagBedI68JCR+pi2D70zrxCenp4VrmBqDQoKCpCWlqb4NdRcgMXeM3bu3Fk7Mzx58mTZZ4YPHTqEN954A35+fuXOubu7Y8mSJejbty8WL15slb1cCb7hyZ0l11HLLfaeUWl3AuRPQh148iT1MYuhPiZhCBrMK0RgYCCioqJw9+5d1K5dW5U2XLx4UdH6WViAhYeMz58/h6OjIwRBQGJiIhITEyv8jikzwyzsc0oQJfDgTkB9t/CQUWl3AuRPQh148KTa/gD4yEh9TNuH28G8j4+Pyd8RBAGnTp3Sey4zM1PnuHv37khJScGQIUMwceJENG/eHNWrV9f7XQ8PD5PbwgJRUVFYsWIFXFxc4O/vb3QBFluFlYxKzgyzsM8pYTuQO+WBFbcoCQsZlb6rRv4kyiK3IwE+PcmCP5SGlYzUx7Rt7OunwgRKZqLc3Nxkqa9Hjx4QBKHc56IoYubMmQa/Z8urN8bHx8PDw0PVBViUhoWMSs8Ms7bPKcE25E55YMEtSqN2Rms8fUD+JMoityMBPj2ptj+sAQsZqY9p+3A7mHd0dERBQQFcXFwQEBCAfv36wdXV1ez6/P399YpWTYKDg9GnTx/06dNH+1lqaipSU1MxfPjwcuVjY2Oxbt067Ny5U1L92dnZGDJkiKqS5SGj0rC6zynBJuROy70CqO8WHjJaA/InURa5HQnw6UkW/MFDRqUhRyoPt4P5AwcOIDExEQkJCZg3bx4WLlyIHj16YODAgejSpYvJ0vz2228Vaqn57NixAxqNRuez/fv3IyoqSq+EcnNzyz3KZQwWFmDhIaPSfPjhh+jQoQMcHBwAAB06dEB4eDgiIyNx5coVeHh4IDQ0FIMHD1a5pQQLkDst9wqgvlt4yGgNyJ9EWeR2JMCnJ1nwBw8ZlYYcqTwOajdALVxdXTFixAhs2bIFP/30EwICAnDo0CGMHTsWb775JiIiInQeC5HK8uXLER4ejvz8fINl8vLyEBERgejoaEsiqE5gYCD27NmDu3fvqt0UxWAhY3BwMJKTk3U+S01Nxbp16/SWj42NRc+ePSXX7+zsDB8fHzg7O2s/e/fdd5GUlITTp0/jt99+Q2BgoHmNJ+wOcqc8sOAWpVE7o9LuBMifRHmUciTAlyfV9oc1YCEj9TFtH24H86Vp1aoVZs+ejQMHDmDBggXw9vZGdHQ0evfujWHDhuHatWuS6jl06BCWLl0KV1dXVK5c2WA5JycnuLq6IiIiAocPH5YrhuJkZmbq/OnevTt8fX0xZMgQJCYm4tKlS+XKlPyxFVjMuGPHjnILk+zfvx/z58/XW96cO2gEYQ7kTumw6Ba5YS0juZNQG7kcCdi/J1nzhxKwmJE8aftw+5i9PpycnNCvXz/069cPJ0+eRGhoKI4fP460tDQ0bNiwwu8nJibCxcUFH330UYVlAwMDsXLlSsTHx6Njx45yNF9xeFiAhYeMhlB7L1fCdiF3VgwPbuEhoyHIn4QxLHUkYP+e5MEfPGQ0BDlSOWgwX4rCwkLs2rULcXFxOHDgAAoKCtCiRQt4e3tL+v7JkyfRqVMnODk5VVi2ZF/FkydPWthq68HiAixyw0PGsrCwzylh25A7K4YHt/CQsSzkT0IKljoSsH9P8uAPHjKWhRypPDSYB3D58mXEx8dj69atyMnJQc2aNfHhhx9i0KBBaNq0qeR6bt++bdLWCp6eniatDKw2LC7AIjc8ZCwLK/ucErYHuVM6PLiFh4xlIX8SxpDLkYD9e5IHf/CQsSzkSOXh9m/z0aNH2LZtG+Li4nDu3Dk4ODigS5cuGDhwIHr06GHWPzQHBweji5KUJT8/X7u6o1Ls2bMH2dnZ2uOzZ88CAGbPnl2u7JkzZyTVuXz5cjx9+hSTJk0y+N5WXl4eoqKi8PLLL2Ps2LGmN9wEeMioJCzsc0rYDuTO2eXKSvUKwJZbeMioNORPoixKOBLgx5Os+YOHjEpCjlQebgfznTt3Rl5eHry9vTF58mQMGDAAdevWtahONzc3XLlyRXL5K1euwM3NzaJrVsTZs2e14inNDz/8oLd8RY//lCzAMm3aNEkLsISFhaFVq1aKvrPFQ0Yl4WGfU0I+yJ3meQVgzy08ZFQa8idRFiUcCfDhSRb9wUNGJSFHKg+3g/nnz5/D0dERgiAgMTERiYmJFX5HEAQkJSUZPN+uXTts3boVN27cgKenp9G6bty4gSNHjsDf39/ElkvH0LYSlsDaAiw8ZASUu4MG8LHPKSEf5E7zYcktPGQElHUnQP4kyqOEIwE+PMmaP3jICFAf09bhdjAPFK+sWHY7BksIDAxEfHw8QkJCEBMTg1q1auktd+/ePXz66acoLCzE0KFDZbt+Wfz8/GSvk7UFWHjICChzB62EwMBAREVF4e7du6hdu7bZbST4gdxpHiy5hYeMgLLuBMifhH7kdiTAhydZ8wcPGQHqY9o63A7mL168KHudLVq0QFBQEGJjY/Hee+9hyJAh6NChA+rVqwcAyMrKwuHDh7F582bk5ORg5MiRaNGihezt0EdWVhZ27NiBM2fO4N69ewCAWrVqoWXLlnjrrbckP4rF8gIs9ppR7pnhsvuDdu/eHSkpKRgyZAgmTpyI5s2bo3r16nq/6+HhIWtbCNuD3GmeVwD23FKCvWZU4q4a+ZOoCCUcCfDhSZb8URZ7zUh9TNuH28G8Unz++eeoUqUKVq1ahRUrVmDFihU650VRRKVKlTBu3DiEhoZapU1Lly5FTEwM8vPzIYqizrnExESEhYVh3LhxmDBhQoV1sbgAC2DfGeWeGeZ5n1OCXezdnQB7bgHsO6MSd9XIn4Sa2LsnWfJHaew5I/UxbR8azMuMIAiYMmUKBg0ahLi4OJw8eVL7HkqdOnXQtm1bBAQE4NVXX7VKeyIiIrBy5Uo4OTmhf//+8PX1hZubG0RRxJ07d3D06FH89ttv+O6771BYWIhJkyYZrY/FBVh4yFiCHDPDPO5zSrCPvbsTYM8tPGQsQa67auRPQk3s3ZMs+oOHjCVQH9NGETll4sSJYlJSks5np06dEmNjY/WWX7t2rdijRw9rNE020tPTxddff13s2bOneO3aNYPl0tLSxO7du4stWrQQ09PTjdY5c+ZMsUWLFmJGRkaF18/IyBBbtGgh/utf/zK16ZLhIWMJS5YsEVu1aiVqNBqxWbNmOn80Go3YunVrMSoqSvF2EHxD7nyBKV4RRbbcwkPGEsidhDXhwZGiyEf/i4eMJZAnbRfln01hlB07dpRbnGT//v2YP3++3vK5ubnl3gNhnYSEBBQVFWHBggXw9vY2WK5hw4YICwtDQUEBtmzZYrTOwMBAFBQUICQkBDk5OQbLWWsBFh4yAsUzw8uWLQMA9O/fH9988w3+7//+D9HR0fjmm2/Qt29fiKKI7777Dt99952kOpcvX47w8HCjj3vl5eUhIiIC0dHRsuQgbB9y5wtM8QrAllt4yAgo406A/EkYhgdHAnz0v3jICFAf09ahx+ztmBMnTqBJkyZo165dhWXbt2+PJk2a4Pjx40bLsbYACw8ZMzIyEBMTA09PT8TExOj9hTJw4ECMHz8eo0ePxsqVK+Hv7290gRXe9jklCFNQwisAW27hIaMS7gTInwQB8NH/4iEj9TFtHxrM2zFXr15Ft27dJJf38fHBvn37KizH0gIsPGQ0dWb4o48+wpYtWxAcHGywLIv7nBIEKyjlFYAdt/CQUQl3AuRPggD46H/xkJH6mLYPDebtmNzcXJP2dKxduzZyc3MrLMfSAiw8ZFRiZpjFfU4JghWU8grAjlt4yKjU0wfkT4Lgo//FQ0bqY9o+NJi3Y549e2b08ZayVK5cGc+ePZNc/tVXX8XkyZPNaZps8JBRiZlh1vY5JQiWUNorgPpu4SGjUnfVyJ8EwUf/i4eM1Me0fbhdAI8gbAUlZoZZ2+eUIAhCbpS6q0b+JAjCXqA+pu3D9Z35PXv2aB9rAYCzZ88CAGbPnl2u7JkzZ6zVLFnZtm0bUlNTJZVNT09XuDXKYO8ZlZgZZnmfU4J9yJ262KJXAPvPqNRdNfInURE8OBKwf4cA9p+R+pi2D9eD+bNnz2oFW5offvhBb3lBEJRukuxcv34d169fl1yeMvJBu3btsHXrVty4cQOenp5Gy964cQNHjhyBv7+/dRpHMA+5szyUkR/In0RF8OBIgA+H8JBRbsiR1kUQRVFUuxFqkJKSYtb3/Pz8ZG6Jcty8edOs79WvX1/mligHDxk1Gg0aNGggeSGU9PR0pKen48KFCwbLnDt3DgMHDsTrr7+OmJgY1KpVS2+5e/fuYcyYMTh//jx+/vlnRbdHIWwDcqdhbMkrPGRUwp0A+ZMwDg+OBPhwCA8ZqY9p+3A7mCcIW0Gj0Zj8HUEQKuyQzp8/H7GxsahZs6akfU5nzJhhVvsJgiDUQCl3AuRPgiDsA+pj2j40mEfxP6odO3bgzJkzuHfvHgCgVq1aaNmyJd566y16j4NQFaVmhkVRREREBFatWoWioiK95ytVqoQxY8YgNDSUHh0jykHuJFhGybtq5E9CCuRIgnWoj2n7cD+YX7p0KWJiYpCfn4+yfxWCIMDJyQnjxo3DhAkTVGohQShLenq66vucErYHuZMgyJ+EYciRBEGOtAZcD+YjIiKwcuVKODk5oU+fPvD19YWbmxtEUcSdO3dw9OhR/Pbbb8jPz8eECRMwadIktZtMEAShOuROgiAIw5AjCYKwFtwO5jMyMvDOO+/glVdeQUxMDLy9vfWWu3btGkaPHo3bt2/j119/hZeXl3UbShAEwRDkToIgCMOQIwmCsCYOajdALRISElBUVIQFCxYYFC0ANGzYEGFhYSgoKMCWLVus10CCIAgGIXcSBEEYhhxJEIQ14XYwf+LECTRp0gTt2rWrsGz79u3RpEkTHD9+3AotIwiCYBdyJ0EQhGHIkQRBWBNuB/NXr15F69atJZf38fFBWlqagi0iCIJgH3InQRCEYciRBEFYE24H87m5uahdu7bk8rVr10Zubq6CLSIIgmAfcidBEIRhyJEEQVgTbgfzz549Q+XKlSWXr1y5Mp49e6ZgiwiCINiH3EkQBGEYciRBENaE28E8QRAEQRAEQRAEQdgqjmo3QE22bduG1NRUSWXT09MVbg1BEIRtQO4kCIIwDDmSIAhrwfVg/vr167h+/brk8oIgKNgagiAI24DcSRAEYRhyJEEQ1kIQRVFUuxFqcPPmTbO+V79+fZlbQhAEYTuQOwmCIAxDjiQIwppwO5gnCIIgCIIgCIIgCFuFFsAjCIIgCIIgCIIgCBuDBvMEQRAEQRAEQRAEYWPQYJ4gCIIgCIIgCIIgbAwazBMEQRAEQRAEQRCEjUGDeYIgCIIgCIIgCIKwMWgwTxAEQRAEQRAEQRA2Bg3mCYIgCIIgCIIgCMLG+P8ftE2X0gMRWwAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_comparison_bars(results_df)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The efficiency advantage for `NUTS` over `DEMetropolisZ` over `DEMetropolis` is more pronounced in higher dimensions. $\\hat{R}$ is also large for `DEMetropolis` for this sample size and number of chains. For `DEMetropolis`, a smaller number of chains ($2N$) with a larger number of samples performed better than more chains with fewer samples. Counter-intuitively, the `NUTS` sampler yeilds $ESS$ values greater than the number of samples, which can occur as discussed [here](https://discourse.pymc.io/t/effective-sample-size-larger-than-number-of-samples-for-nuts/6275)." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_forest_compare_analytical(results_df)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We might be seeing low coverage in the tails of some `DEMetropolis` runs (i.e., the MCMC HDIs are consistently smaller than the analytical solution). Let's explore this more systematically in the next experiment. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Experiment #3. Accuracy and Bias\n", "We want to make sure that the `DEMetropolis` samplers are providing coverage for high dimensional problems (i.e., the tails are appropriately sampled). We will test for bias by running the algorithm multiple times and comparing to both `NUTS` and the analytically-calculated probability density. We will perform MCMC in many dimensions but analyze the results for the dimension with the most variance (dimension 5) for simplicity. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 10 Dimensions\n", "First check in 10 dimensions. We will perform 10 replicates for each run. `DEMetropolis` will be run at $2D$ chains. The number of tunes and draws have been tailored to get effective sampler sizes of greater than 2000. " ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "tags": [ "hide-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 92 seconds.\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 81 seconds.\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 81 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 82 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 81 seconds.\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 86 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 81 seconds.\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 85 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 96 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (20 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 20 chains for 5_000 tune and 5_000 draw iterations (100_000 + 100_000 draws total) took 86 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 70 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 77 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 76 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 76 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 79 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 72 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 69 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 77 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 72 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 25_000 tune and 25_000 draw iterations (100_000 + 100_000 draws total) took 78 seconds.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 42 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 43 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 40 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 43 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 47 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 37 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 44 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 42 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 43 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 42 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n" ] } ], "source": [ "D = 10\n", "reps = 10\n", "samplers = [pm.DEMetropolis] * reps + [pm.DEMetropolisZ] * reps + [pm.NUTS] * reps\n", "coreses = [1] * reps * 3\n", "chainses = [2 * D] * reps + [4] * reps * 2\n", "tunes = drawses = [5000] * reps + [25000] * reps + [1000] * reps\n", "\n", "results = []\n", "run = 0\n", "for sampler, tune, draws, cores, chains in zip(samplers, tunes, drawses, coreses, chainses):\n", " if sampler.name == \"nuts\":\n", " results.append(\n", " sample_model_calc_metrics(\n", " sampler,\n", " D,\n", " tune,\n", " draws,\n", " cores=cores,\n", " chains=chains,\n", " run=run,\n", " step_kwargs={},\n", " sample_kwargs=dict(target_accept=0.95),\n", " )\n", " )\n", " else:\n", " results.append(\n", " sample_model_calc_metrics(sampler, D, tune, draws, cores=cores, chains=chains, run=run)\n", " )\n", " run += 1" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC and Analytical Results for 5th Dimension of 10 Dimensional Target Distribution
 meansdhdi_3%hdi_97%ess_bulkess_tailr_hat
Sampler       
DEMetropolis-0.0217002.214500-4.1254004.1742002772.4000005331.7000001.010000
DEMetropolisZ-0.0002002.226000-4.1886004.1598003089.1000005587.2000001.000000
NUTS0.0014002.257800-4.2527004.1964002618.1000002798.0000001.000000
Analytical0.0000002.236068-4.2055824.205582nannannan
\n" ], "text/plain": [ "" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "results_df = concat_results(results)\n", "results_df = results_df.reset_index(drop=True)\n", "summaries, summary_means = plot_forest_compare_analytical_dim5(results_df)\n", "summary_means.style.set_caption(\n", " \"MCMC and Analytical Results for 5th Dimension of 10 Dimensional Target Distribution\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visually, `DEMetropolis` algorithms look as reasonable accurate and as accurate as `NUTS`. Since we have 10 replicates that we want to compare to the analytical solution, we can dust off our traditional statistics and perform an old-school one-sided t-test to see if the sampler-calculated confidence limits are significantly different than the analytically calculated confidence limit. " ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC Replicates Compared to Analytical Solution for Selected Confidence Limits
 SamplerConfidenceLimitPvalue
0DEMetropolishdi_3%0.018270
0DEMetropolishdi_97%0.307391
0DEMetropolisZhdi_3%0.555155
0DEMetropolisZhdi_97%0.177881
0NUTShdi_3%0.336053
0NUTShdi_97%0.847152
\n" ], "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "samplers = [\"DEMetropolis\", \"DEMetropolisZ\", \"NUTS\"]\n", "cls_str = [\"hdi_3%\", \"hdi_97%\"]\n", "cls_val = [0.03, 0.97]\n", "dist = st.norm(0, np.sqrt(5))\n", "results = []\n", "for sampler in samplers:\n", " for cl_str, cl_val in zip(cls_str, cls_val):\n", " mask = summaries.Sampler == sampler\n", " # collect the credible limits for each MCMC run\n", " mcmc_cls = summaries.loc[mask, cl_str]\n", "\n", " # calculate the confidence limit for the target dist\n", " analytical_cl = dist.ppf(cl_val)\n", "\n", " # one sided t-test!\n", " p_value = st.ttest_1samp(mcmc_cls, analytical_cl).pvalue\n", " results.append(\n", " pd.DataFrame(dict(Sampler=[sampler], ConfidenceLimit=[cl_str], Pvalue=[p_value]))\n", " )\n", "pd.concat(results).style.set_caption(\n", " \"MCMC Replicates Compared to Analytical Solution for Selected Confidence Limits\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A higher p-value indicates that the MCMC algorithm captures the analytical value with high confidence. A lower p-value means that the MCMC algorithm was unexpectedly high or low compared to the analytically calculated confidence limit. The `NUTS` sampler is capturing the analytically calculated value with high confidence. The `DEMetropolis` algorithms have lower confidence but are giving reasonable results. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 50 Dimensions\n", "Higher dimensions get increasingly difficult for Metropolis algorithms. Here we will sample with very large sample sizes (this will take a while) to get at least 2000 effective samples. " ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "tags": [ "hide-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 459 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 471 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 473 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 467 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 480 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 466 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 580 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 864 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 878 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Population sampling (100 chains)\n", "DEMetropolis: [x]\n", "Chains are not parallelized. You can enable this by passing `pm.sample(cores=n)`, where n > 1.\n", "Sampling 100 chains for 5_000 tune and 5_000 draw iterations (500_000 + 500_000 draws total) took 855 seconds.\n", "The rhat statistic is larger than 1.01 for some parameters. This indicates problems during sampling. See https://arxiv.org/abs/1903.08008 for details\n", "The effective sample size per chain is smaller than 100 for some parameters. A higher number is needed for reliable rhat and ess computation. See https://arxiv.org/abs/1903.08008 for details\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 592 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 451 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 429 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 420 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 422 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 425 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 364 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 208 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 206 seconds.\n", "Sequential sampling (4 chains in 1 job)\n", "DEMetropolisZ: [x]\n", "Sampling 4 chains for 100_000 tune and 100_000 draw iterations (400_000 + 400_000 draws total) took 212 seconds.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 32 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 31 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 31 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 32 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 31 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 29 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 30 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Auto-assigning NUTS sampler...\n", "Initializing NUTS using jitter+adapt_diag...\n", "Sequential sampling (4 chains in 1 job)\n", "NUTS: [x]\n", "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 30 seconds.\n", "Chain \n", "array(0)\n", "Coordinates:\n", " chain int32 0 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(1)\n", "Coordinates:\n", " chain int32 1 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(2)\n", "Coordinates:\n", " chain int32 2 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n", "Chain \n", "array(3)\n", "Coordinates:\n", " chain int32 3 reached the maximum tree depth. Increase `max_treedepth`, increase `target_accept` or reparameterize.\n" ] } ], "source": [ "D = 50\n", "reps = 10\n", "samplers = [pm.DEMetropolis] * reps + [pm.DEMetropolisZ] * reps + [pm.NUTS] * reps\n", "coreses = [1] * reps * 3\n", "chainses = [2 * D] * reps + [4] * reps * 2\n", "tunes = drawses = [5000] * reps + [100000] * reps + [1000] * reps\n", "\n", "results = []\n", "run = 0\n", "for sampler, tune, draws, cores, chains in zip(samplers, tunes, drawses, coreses, chainses):\n", " if sampler.name == \"nuts\":\n", " results.append(\n", " sample_model_calc_metrics(\n", " sampler,\n", " D,\n", " tune,\n", " draws,\n", " cores=cores,\n", " chains=chains,\n", " run=run,\n", " step_kwargs={},\n", " sample_kwargs=dict(target_accept=0.95),\n", " )\n", " )\n", " else:\n", " results.append(\n", " sample_model_calc_metrics(sampler, D, tune, draws, cores=cores, chains=chains, run=run)\n", " )\n", " run += 1\n", "\n", "results_df = concat_results(results)\n", "results_df = results_df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC and Analytical Results for 5th Dimension of 50 Dimensional Target Distribution
 meansdhdi_3%hdi_97%ess_bulkess_tailr_hat
Sampler       
DEMetropolis-0.0077002.236900-4.2244004.1785002583.2000005619.6000001.034000
DEMetropolisZ-0.0097002.172500-4.0885004.0796002616.8000005408.7000001.000000
NUTS0.0300002.244200-4.2350004.1449002552.6000002811.2000001.000000
Analytical0.0000002.236068-4.2055824.205582nannannan
\n" ], "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "summaries, summary_means = plot_forest_compare_analytical_dim5(results_df)\n", "summary_means.style.set_caption(\n", " \"MCMC and Analytical Results for 5th Dimension of 50 Dimensional Target Distribution\"\n", ")" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
MCMC Replicates Compared to Analytical Solution for Selected Confidence Limits
 SamplerConfidenceLimitPvalue
0DEMetropolishdi_3%0.152028
0DEMetropolishdi_97%0.318463
0DEMetropolisZhdi_3%0.001217
0DEMetropolisZhdi_97%0.005154
0NUTShdi_3%0.490542
0NUTShdi_97%0.212516
\n" ], "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "samplers = [\"DEMetropolis\", \"DEMetropolisZ\", \"NUTS\"]\n", "cls_str = [\"hdi_3%\", \"hdi_97%\"]\n", "cls_val = [0.03, 0.97]\n", "results = []\n", "for sampler in samplers:\n", " for cl_str, cl_val in zip(cls_str, cls_val):\n", " mask = summaries.Sampler == sampler\n", "\n", " # collect the credible limits for each MCMC run\n", " mcmc_cls = summaries.loc[mask, cl_str]\n", "\n", " # calculate the confidence limit for the target dist\n", " analytical_cl = dist.ppf(cl_val)\n", "\n", " # one sided t-test!\n", " p_value = st.ttest_1samp(mcmc_cls, analytical_cl).pvalue\n", "\n", " results.append(\n", " pd.DataFrame(dict(Sampler=[sampler], ConfidenceLimit=[cl_str], Pvalue=[p_value]))\n", " )\n", "pd.concat(results).style.set_caption(\n", " \"MCMC Replicates Compared to Analytical Solution for Selected Confidence Limits\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see that at 50 dimensions, the `DEMetropolisZ` sampler has poor coverage compared to `DEMetropolis`. Therefore, even though `DEMetropolisZ` is more efficient and has lower $\\hat{R}$ values than `DEMetropolis`, `DEMetropolis` is suggested for higher dimensional problems. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "Based on the results in this notebook, if you cannot use `NUTS`, use `DEMetropolisZ` for lower dimensional problems (e.g., $10D$) because it is more efficient and converges better. Use `DEMetropolis` for higher dimensional problems (e.g., $50D$) to better capture the tails of the target distribution. " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Last updated: Fri Feb 10 2023\n", "\n", "Python implementation: CPython\n", "Python version : 3.11.0\n", "IPython version : 8.7.0\n", "\n", "pymc : 5.0.1+5.ga7f361bd\n", "numpy : 1.24.0\n", "pandas : 1.5.2\n", "sys : 3.11.0 | packaged by conda-forge | (main, Oct 25 2022, 06:12:32) [MSC v.1929 64 bit (AMD64)]\n", "matplotlib: 3.6.2\n", "scipy : 1.9.3\n", "arviz : 0.14.0\n", "\n", "Watermark: 2.3.1\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -n -u -v -iv -w" ] } ], "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": "3.11.0" }, "vscode": { "interpreter": { 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\n", 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\n", 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